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job_idjob_titlesalary_usdsalary_currencysalary_localexperience_levelemployment_typecompany_locationcompany_sizeemployee_residenceremote_ratiorequired_skillseducation_requiredyears_experienceindustryposting_dateapplication_deadlinejob_description_lengthbenefits_scorecompany_name
0AI00001Data Scientist219728USD219728EXPTSwedenMSweden0Python, Computer Vision, R, DockerAssociate13Transportation2024-09-232024-10-3111326.6TechCorp Inc
1AI00002Head of AI230237JPY25326070EXPTJapanLJapan50Kubernetes, MLOps, Tableau, PythonBachelor10Transportation2024-07-262024-09-1222998.5Cloud AI Solutions
2AI00003Data Engineer128890EUR109557EXCTGermanySGermany100Spark, Scala, Hadoop, PyTorch, GCPBachelor12Automotive2025-01-192025-03-2813295.5Quantum Computing Inc
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...............................................................
14995AI14996AI Product Manager39171USD39171MICTChinaMChina50Azure, R, NLP, Docker, Computer VisionPhD4Consulting2025-01-072025-02-0711075.2Smart Analytics
14996AI14997AI Product Manager77555EUR65922ENCTNetherlandsMNetherlands50Python, TensorFlow, Mathematics, AWS, Computer...PhD0Energy2024-12-222025-02-1218709.7Autonomous Tech
14997AI14998Data Engineer28380USD28380ENFLIndiaMIndia50Azure, Kubernetes, Spark, Statistics, MLOpsAssociate1Government2024-05-042024-05-2115589.0Digital Transformation LLC
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PhD \n", + "\n", + " years_experience industry posting_date application_deadline \\\n", + "0 13 Transportation 2024-09-23 2024-10-31 \n", + "1 10 Transportation 2024-07-26 2024-09-12 \n", + "2 12 Automotive 2025-01-19 2025-03-28 \n", + "3 2 Automotive 2024-07-20 2024-09-06 \n", + "4 0 Finance 2025-03-16 2025-05-09 \n", + "... ... ... ... ... \n", + "14995 4 Consulting 2025-01-07 2025-02-07 \n", + "14996 0 Energy 2024-12-22 2025-02-12 \n", + "14997 1 Government 2024-05-04 2024-05-21 \n", + "14998 0 Real Estate 2024-05-08 2024-06-22 \n", + "14999 6 Transportation 2024-11-23 2024-12-15 \n", + "\n", + " job_description_length benefits_score company_name \n", + "0 1132 6.6 TechCorp Inc \n", + "1 2299 8.5 Cloud AI Solutions \n", + "2 1329 5.5 Quantum Computing Inc \n", + "3 1132 6.8 Cognitive Computing \n", + "4 2011 9.3 Advanced Robotics \n", + "... ... ... ... \n", + "14995 1107 5.2 Smart Analytics \n", + "14996 1870 9.7 Autonomous Tech \n", + "14997 1558 9.0 Digital Transformation LLC \n", + "14998 546 8.4 Machine Intelligence Group \n", + "14999 1034 9.7 Quantum Computing Inc \n", + "\n", + "[15000 rows x 20 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc273523-575a-4125-9ff9-dce8f6f75972", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From ccff3b396e74f35b2c1f61f95931c86e6cdfb0bd Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Mon, 8 Dec 2025 15:23:44 +0100 Subject: [PATCH 03/26] First commit --- notebooks/Project1.ipynb | 155 +- notebooks/ai_job_dataset1.csv | 15001 ++++++++++++++++++++++++++++++++ 2 files changed, 15151 insertions(+), 5 deletions(-) create mode 100644 notebooks/ai_job_dataset1.csv diff --git a/notebooks/Project1.ipynb b/notebooks/Project1.ipynb index 24e7c65d..c79987ea 100644 --- a/notebooks/Project1.ipynb +++ b/notebooks/Project1.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 5, + "execution_count": 1, "id": "05ae7d72-68d0-412d-b459-ceded1805bd8", "metadata": {}, "outputs": [], @@ -15,7 +15,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 2, "id": "b60dc083-ca2a-4103-869d-4b5bcb04da03", "metadata": {}, "outputs": [ @@ -403,7 +403,7 @@ "[15000 rows x 20 columns]" ] }, - "execution_count": 6, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -414,11 +414,156 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 3, "id": "bc273523-575a-4125-9ff9-dce8f6f75972", "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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salary_usdsalary_localremote_ratioyears_experiencejob_description_lengthbenefits_score
count15000.0000001.500000e+0415000.00000015000.00000015000.00000015000.000000
mean121991.9382678.292366e+0550.1966676.3656671500.8526007.499540
std63968.3618463.425325e+0640.8440845.598551574.7246471.444202
min16621.0000001.662100e+040.0000000.000000500.0000005.000000
25%74978.5000007.383075e+040.0000002.000000998.7500006.300000
50%107261.5000001.090355e+0550.0000005.0000001512.0000007.500000
75%155752.2500001.673278e+05100.00000010.0000001994.0000008.800000
max410273.0000003.368541e+07100.00000019.0000002499.00000010.000000
\n", + "
" + ], + "text/plain": [ + " salary_usd salary_local remote_ratio years_experience \\\n", + "count 15000.000000 1.500000e+04 15000.000000 15000.000000 \n", + "mean 121991.938267 8.292366e+05 50.196667 6.365667 \n", + "std 63968.361846 3.425325e+06 40.844084 5.598551 \n", + "min 16621.000000 1.662100e+04 0.000000 0.000000 \n", + "25% 74978.500000 7.383075e+04 0.000000 2.000000 \n", + "50% 107261.500000 1.090355e+05 50.000000 5.000000 \n", + "75% 155752.250000 1.673278e+05 100.000000 10.000000 \n", + "max 410273.000000 3.368541e+07 100.000000 19.000000 \n", + "\n", + " job_description_length benefits_score \n", + "count 15000.000000 15000.000000 \n", + "mean 1500.852600 7.499540 \n", + "std 574.724647 1.444202 \n", + "min 500.000000 5.000000 \n", + "25% 998.750000 6.300000 \n", + "50% 1512.000000 7.500000 \n", + "75% 1994.000000 8.800000 \n", + "max 2499.000000 10.000000 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4498be2-3f6d-463b-bede-2cb9cc7bbe9d", + "metadata": {}, "outputs": [], - "source": [] + "source": [ + "df[" + ] } ], "metadata": { diff --git a/notebooks/ai_job_dataset1.csv b/notebooks/ai_job_dataset1.csv new file mode 100644 index 00000000..5c9e5669 --- /dev/null +++ b/notebooks/ai_job_dataset1.csv @@ -0,0 +1,15001 @@ +job_id,job_title,salary_usd,salary_currency,salary_local,experience_level,employment_type,company_location,company_size,employee_residence,remote_ratio,required_skills,education_required,years_experience,industry,posting_date,application_deadline,job_description_length,benefits_score,company_name +AI00001,Data Scientist,219728,USD,219728,EX,PT,Sweden,M,Sweden,0,"Python, Computer Vision, R, Docker",Associate,13,Transportation,2024-09-23,2024-10-31,1132,6.6,TechCorp Inc +AI00002,Head of AI,230237,JPY,25326070,EX,PT,Japan,L,Japan,50,"Kubernetes, MLOps, Tableau, Python",Bachelor,10,Transportation,2024-07-26,2024-09-12,2299,8.5,Cloud AI Solutions +AI00003,Data Engineer,128890,EUR,109557,EX,CT,Germany,S,Germany,100,"Spark, Scala, Hadoop, PyTorch, GCP",Bachelor,12,Automotive,2025-01-19,2025-03-28,1329,5.5,Quantum Computing Inc +AI00004,Computer Vision Engineer,96349,USD,96349,MI,FL,Finland,L,Finland,50,"MLOps, Linux, Tableau, Python",PhD,2,Automotive,2024-07-20,2024-09-06,1132,6.8,Cognitive Computing +AI00005,Robotics Engineer,63065,EUR,53605,EN,FT,France,S,France,100,"R, Scala, SQL, GCP, Python",Associate,0,Finance,2025-03-16,2025-05-09,2011,9.3,Advanced Robotics +AI00006,Data Scientist,111794,SGD,145332,SE,CT,Singapore,S,Norway,50,"NLP, MLOps, TensorFlow",Master,7,Technology,2024-11-10,2025-01-20,1021,5.1,Cloud AI Solutions +AI00007,AI Consultant,113897,CAD,142371,SE,PT,Canada,L,Poland,50,"PyTorch, Linux, NLP",Associate,9,Gaming,2024-02-29,2024-04-21,2268,7.4,AI Innovations +AI00008,Head of AI,168639,AUD,227663,SE,FT,Australia,L,Vietnam,100,"Spark, SQL, Tableau, Computer Vision, Linux",Associate,9,Consulting,2024-02-26,2024-03-17,1497,5.5,TechCorp Inc +AI00009,Data Scientist,92624,JPY,10188640,MI,FT,Japan,L,Japan,50,"Kubernetes, SQL, Docker, Deep Learning",Bachelor,4,Government,2024-08-18,2024-10-03,1724,9.5,DataVision Ltd +AI00010,Machine Learning Engineer,215627,GBP,161720,EX,FT,United Kingdom,M,United Kingdom,50,"Git, Scala, GCP",PhD,10,Government,2025-01-18,2025-03-20,902,7.8,DeepTech Ventures +AI00011,Data Engineer,129706,USD,129706,MI,CT,Denmark,L,Denmark,0,"SQL, PyTorch, Statistics, TensorFlow, NLP",Bachelor,3,Consulting,2024-03-10,2024-05-17,2247,5.2,Cloud AI Solutions +AI00012,Deep Learning Engineer,76559,USD,76559,EN,FL,United States,S,United States,100,"Data Visualization, Mathematics, PyTorch, GCP",Bachelor,1,Government,2025-02-09,2025-04-14,694,8.3,Machine Intelligence Group +AI00013,Principal Data Scientist,185834,USD,185834,EX,CT,United States,L,United States,100,"Linux, Data Visualization, Python, TensorFlow",Associate,14,Telecommunications,2024-03-27,2024-06-03,1710,8.9,Autonomous Tech +AI00014,Principal Data Scientist,89801,USD,89801,MI,PT,Sweden,M,Belgium,100,"Linux, MLOps, Deep Learning",Master,3,Healthcare,2024-10-30,2025-01-06,1361,8.7,Cloud AI Solutions +AI00015,Principal Data Scientist,252601,USD,252601,EX,PT,Norway,L,Norway,100,"Kubernetes, SQL, AWS, Git, Computer Vision",Master,19,Gaming,2024-07-24,2024-08-14,572,5.1,TechCorp Inc +AI00016,AI Product Manager,20520,USD,20520,EN,FT,India,S,India,0,"Hadoop, Git, Computer Vision, Kubernetes, Data Visualization",Master,0,Gaming,2024-08-22,2024-10-05,2455,7.5,Predictive Systems +AI00017,Robotics Engineer,192789,CHF,173510,SE,PT,Switzerland,S,Switzerland,100,"Tableau, Git, Python, Java",Master,5,Healthcare,2024-03-27,2024-06-08,524,5.9,Quantum Computing Inc +AI00018,Machine Learning Researcher,107184,SGD,139339,SE,FL,Singapore,S,Singapore,50,"Azure, GCP, Computer Vision",Master,7,Automotive,2024-05-07,2024-05-28,2111,9.2,DeepTech Ventures +AI00019,Robotics Engineer,141909,EUR,120623,SE,FT,Netherlands,M,Netherlands,0,"Git, Kubernetes, MLOps, Spark",Associate,6,Healthcare,2024-12-22,2025-01-20,1601,7.8,Cloud AI Solutions +AI00020,Data Engineer,118238,USD,118238,SE,FL,Ireland,M,Ireland,100,"AWS, Python, Azure, SQL, Computer Vision",Associate,7,Education,2024-11-07,2025-01-02,2431,8.2,TechCorp Inc +AI00021,Data Scientist,155210,AUD,209534,SE,PT,Australia,L,Argentina,0,"Spark, NLP, AWS",Master,7,Energy,2025-01-24,2025-03-18,595,9.7,Neural Networks Co +AI00022,Data Engineer,96699,AUD,130544,SE,FT,Australia,S,Australia,0,"GCP, Linux, Mathematics",PhD,5,Technology,2025-03-29,2025-04-13,582,9.7,TechCorp Inc +AI00023,AI Software Engineer,161477,EUR,137255,SE,FT,France,L,France,50,"Mathematics, Spark, Linux",Bachelor,8,Real Estate,2025-02-04,2025-03-03,1861,9.5,DataVision Ltd +AI00024,AI Software Engineer,316709,USD,316709,EX,CT,Denmark,L,Denmark,50,"Data Visualization, Azure, Statistics",PhD,18,Transportation,2025-04-29,2025-06-21,1284,7.6,Autonomous Tech +AI00025,ML Ops Engineer,62089,CAD,77611,MI,CT,Canada,S,Singapore,50,"Python, GCP, Linux, SQL, Deep Learning",PhD,3,Media,2024-03-18,2024-04-25,2264,9.7,Predictive Systems +AI00026,Principal Data Scientist,77985,USD,77985,EN,CT,Denmark,S,Denmark,0,"SQL, TensorFlow, Computer Vision, Kubernetes",Associate,0,Automotive,2025-03-07,2025-04-03,655,9.4,Neural Networks Co +AI00027,Robotics Engineer,55315,EUR,47018,EN,PT,Austria,S,Austria,0,"Spark, Deep Learning, SQL, NLP, Python",PhD,0,Media,2025-01-09,2025-03-22,1107,9.5,Future Systems +AI00028,AI Architect,246647,SGD,320641,EX,PT,Singapore,M,Singapore,50,"Scala, Mathematics, SQL",Master,16,Telecommunications,2024-08-08,2024-08-26,2347,6.6,DeepTech Ventures +AI00029,Deep Learning Engineer,29050,USD,29050,EN,FT,China,S,Germany,0,"PyTorch, Kubernetes, Deep Learning, Hadoop",Associate,1,Consulting,2025-02-06,2025-03-19,555,5.2,AI Innovations +AI00030,Head of AI,120599,GBP,90449,MI,CT,United Kingdom,L,United Kingdom,50,"Linux, AWS, Python",Master,4,Energy,2024-09-21,2024-11-07,699,6.4,Quantum Computing Inc +AI00031,AI Specialist,277727,SGD,361045,EX,PT,Singapore,L,Singapore,50,"Python, Git, TensorFlow",Associate,13,Healthcare,2024-10-04,2024-11-05,529,9,Future Systems +AI00032,Data Engineer,158734,CAD,198418,EX,PT,Canada,S,South Korea,50,"Data Visualization, NLP, Computer Vision",Master,16,Retail,2024-05-20,2024-07-29,1607,6.2,Future Systems +AI00033,Data Engineer,139438,JPY,15338180,SE,FL,Japan,L,Japan,0,"Python, Spark, Git, Data Visualization, Docker",PhD,9,Retail,2025-03-16,2025-05-12,1826,9.9,Cognitive Computing +AI00034,Head of AI,131432,SGD,170862,SE,PT,Singapore,M,Sweden,50,"Kubernetes, Data Visualization, Deep Learning, Azure, Computer Vision",Master,5,Manufacturing,2024-05-03,2024-07-15,1134,5.3,Cognitive Computing +AI00035,Data Analyst,140290,USD,140290,MI,PT,Denmark,L,Denmark,50,"PyTorch, SQL, R, Azure",Associate,4,Real Estate,2024-07-18,2024-09-26,2437,5.7,DeepTech Ventures +AI00036,Research Scientist,90858,EUR,77229,MI,CT,France,L,France,50,"Scala, PyTorch, Deep Learning, Kubernetes, Java",Bachelor,2,Real Estate,2024-08-13,2024-09-13,1793,7.1,DataVision Ltd +AI00037,Autonomous Systems Engineer,126597,GBP,94948,SE,FL,United Kingdom,L,Singapore,50,"PyTorch, Java, TensorFlow, Computer Vision, SQL",Master,6,Government,2024-03-30,2024-04-13,2236,7.8,Machine Intelligence Group +AI00038,AI Architect,53274,USD,53274,EN,FL,Finland,M,Finland,100,"Spark, Python, Statistics, Hadoop, TensorFlow",Associate,0,Automotive,2025-03-22,2025-04-12,1444,6,Autonomous Tech +AI00039,Machine Learning Researcher,155357,USD,155357,EX,FL,Sweden,S,France,100,"TensorFlow, SQL, Computer Vision, Kubernetes",Bachelor,17,Real Estate,2024-12-11,2025-01-01,830,5.2,Cloud AI Solutions +AI00040,Principal Data Scientist,116292,EUR,98848,MI,FL,Netherlands,M,Hungary,50,"Java, Docker, Python",Bachelor,4,Gaming,2024-07-28,2024-09-06,2404,7.9,Quantum Computing Inc +AI00041,Computer Vision Engineer,140363,EUR,119309,SE,CT,Austria,L,Austria,100,"MLOps, Hadoop, TensorFlow, Kubernetes",Master,6,Manufacturing,2025-01-31,2025-04-06,1852,9.8,TechCorp Inc +AI00042,Research Scientist,162306,USD,162306,SE,CT,Israel,L,Luxembourg,0,"Statistics, SQL, Tableau, Hadoop, R",Master,9,Energy,2024-11-12,2024-12-08,1066,5.6,Neural Networks Co +AI00043,Data Analyst,134224,USD,134224,EX,FT,China,L,China,0,"Python, SQL, Git",Master,16,Technology,2024-10-13,2024-11-15,1743,6.6,Quantum Computing Inc +AI00044,Research Scientist,77500,GBP,58125,MI,CT,United Kingdom,S,Norway,0,"Mathematics, Hadoop, TensorFlow",PhD,3,Technology,2024-08-20,2024-10-29,811,10,Machine Intelligence Group +AI00045,Computer Vision Engineer,154083,USD,154083,SE,PT,Ireland,L,Ireland,50,"Hadoop, Python, Deep Learning",Associate,7,Manufacturing,2024-01-09,2024-02-16,1969,7.7,Neural Networks Co +AI00046,Machine Learning Engineer,79445,USD,79445,MI,FL,Ireland,M,Ireland,50,"Python, Statistics, TensorFlow, Computer Vision",Bachelor,4,Real Estate,2024-09-28,2024-10-16,511,7.2,Cloud AI Solutions +AI00047,Head of AI,157466,CHF,141719,SE,FL,Switzerland,M,Switzerland,100,"Git, Data Visualization, Spark, Computer Vision, Azure",Associate,8,Automotive,2024-01-21,2024-03-03,547,5.2,Future Systems +AI00048,Head of AI,38972,USD,38972,MI,FT,India,L,India,0,"Kubernetes, Mathematics, TensorFlow, MLOps",PhD,4,Real Estate,2024-01-28,2024-03-09,2163,7.1,AI Innovations +AI00049,Deep Learning Engineer,66090,CAD,82613,MI,PT,Canada,S,Canada,0,"AWS, SQL, R, Scala",PhD,3,Technology,2025-04-10,2025-04-29,1901,5.3,DeepTech Ventures +AI00050,Data Analyst,47943,USD,47943,MI,PT,China,L,China,50,"TensorFlow, Mathematics, NLP, Docker",PhD,2,Finance,2024-11-23,2025-01-13,2483,6.2,Smart Analytics +AI00051,ML Ops Engineer,217318,USD,217318,EX,PT,Ireland,M,Malaysia,100,"SQL, PyTorch, Hadoop",Bachelor,17,Finance,2024-11-14,2024-12-22,1647,7.8,Cognitive Computing +AI00052,AI Architect,84705,USD,84705,MI,CT,Norway,S,Norway,50,"Scala, Spark, PyTorch",PhD,3,Government,2024-12-19,2025-01-11,879,6.6,Autonomous Tech +AI00053,NLP Engineer,36076,USD,36076,SE,FT,India,M,India,50,"Python, TensorFlow, Data Visualization",Master,7,Media,2024-08-14,2024-09-23,580,7.5,Cognitive Computing +AI00054,AI Consultant,160216,USD,160216,EX,FT,Israel,L,Israel,100,"Deep Learning, Linux, Python, SQL",Master,15,Education,2024-05-09,2024-05-29,941,6,Predictive Systems +AI00055,Deep Learning Engineer,60826,GBP,45620,EN,FT,United Kingdom,S,United Kingdom,0,"SQL, Kubernetes, Azure",Bachelor,0,Energy,2024-11-02,2024-11-30,1731,6.3,Autonomous Tech +AI00056,Deep Learning Engineer,237320,GBP,177990,EX,PT,United Kingdom,M,United Kingdom,0,"Kubernetes, MLOps, Scala",Bachelor,16,Real Estate,2024-11-12,2024-12-28,991,7.7,DataVision Ltd +AI00057,Robotics Engineer,60243,EUR,51207,EN,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Linux, Mathematics",Master,1,Healthcare,2024-12-05,2024-12-20,1661,8.8,Future Systems +AI00058,Head of AI,74091,JPY,8150010,EN,PT,Japan,M,Japan,50,"Deep Learning, NLP, R, Linux, SQL",Bachelor,1,Consulting,2025-01-18,2025-03-23,1295,7.2,Quantum Computing Inc +AI00059,AI Specialist,68535,EUR,58255,EN,FT,France,L,France,100,"SQL, Scala, PyTorch",Associate,1,Media,2024-05-01,2024-06-17,1943,5.5,Machine Intelligence Group +AI00060,Robotics Engineer,99401,USD,99401,MI,FL,Norway,S,Norway,50,"Hadoop, Kubernetes, Data Visualization, Python, Linux",Bachelor,3,Healthcare,2024-03-20,2024-04-20,1371,9.4,Quantum Computing Inc +AI00061,Machine Learning Researcher,67632,USD,67632,EN,FT,Ireland,L,Ireland,0,"Linux, GCP, Deep Learning",Master,0,Government,2024-07-13,2024-08-10,2133,8.9,Advanced Robotics +AI00062,ML Ops Engineer,133163,EUR,113189,SE,CT,Netherlands,M,Netherlands,0,"SQL, Statistics, MLOps, PyTorch, Kubernetes",Associate,6,Media,2025-01-03,2025-01-21,2141,7.9,Neural Networks Co +AI00063,Robotics Engineer,125752,USD,125752,MI,FT,Norway,S,Norway,0,"NLP, Statistics, Scala",Master,4,Automotive,2024-05-17,2024-06-24,2390,6,Machine Intelligence Group +AI00064,AI Product Manager,70927,JPY,7801970,EN,CT,Japan,M,Japan,0,"Git, Computer Vision, Docker, SQL, Hadoop",Associate,1,Technology,2024-03-07,2024-04-05,1847,9.3,Quantum Computing Inc +AI00065,Data Engineer,80810,GBP,60608,EN,PT,United Kingdom,L,United Kingdom,0,"Azure, MLOps, Python, Linux, TensorFlow",Master,1,Energy,2024-10-30,2025-01-01,1476,5.4,Algorithmic Solutions +AI00066,Machine Learning Engineer,59614,SGD,77498,EN,CT,Singapore,S,Singapore,100,"Java, Kubernetes, GCP, Linux, Data Visualization",Associate,1,Healthcare,2024-11-07,2024-12-19,1581,7.3,Quantum Computing Inc +AI00067,Robotics Engineer,151907,EUR,129121,EX,FT,Germany,S,Ghana,50,"Python, R, MLOps",Associate,16,Media,2024-09-21,2024-10-16,1433,6.1,Quantum Computing Inc +AI00068,Data Scientist,76317,USD,76317,EX,CT,India,M,India,0,"TensorFlow, Deep Learning, Spark",Bachelor,14,Energy,2024-06-19,2024-07-15,1228,9.1,DataVision Ltd +AI00069,AI Research Scientist,160534,USD,160534,SE,FL,Denmark,M,Denmark,100,"GCP, SQL, MLOps",Master,9,Gaming,2024-06-10,2024-07-07,1651,8.3,Advanced Robotics +AI00070,AI Consultant,40687,USD,40687,MI,FT,India,L,India,50,"SQL, R, GCP, PyTorch, AWS",Master,3,Transportation,2024-07-16,2024-08-25,804,7.3,Algorithmic Solutions +AI00071,Computer Vision Engineer,129265,AUD,174508,SE,FL,Australia,S,Australia,0,"Java, Scala, TensorFlow",Master,5,Consulting,2025-04-06,2025-05-07,2410,6.9,DataVision Ltd +AI00072,NLP Engineer,94396,USD,94396,EX,PT,China,M,China,100,"Scala, Python, Tableau, Mathematics",Master,18,Government,2024-07-30,2024-08-18,1033,9.5,Advanced Robotics +AI00073,NLP Engineer,158237,USD,158237,EX,CT,South Korea,L,South Korea,0,"Python, NLP, GCP",Master,11,Finance,2025-01-24,2025-03-29,1676,6,Quantum Computing Inc +AI00074,Robotics Engineer,239068,USD,239068,EX,PT,Denmark,L,Denmark,50,"TensorFlow, Java, NLP, Hadoop, GCP",PhD,18,Media,2024-08-26,2024-10-30,1321,6.8,Autonomous Tech +AI00075,Robotics Engineer,81401,USD,81401,MI,FL,Finland,M,Belgium,0,"Java, Spark, Data Visualization, AWS, Git",Associate,2,Retail,2025-02-07,2025-04-11,1930,6.3,Future Systems +AI00076,AI Specialist,144229,CHF,129806,MI,FT,Switzerland,M,Japan,0,"Python, TensorFlow, MLOps, PyTorch",PhD,2,Media,2024-01-02,2024-03-02,1213,9.5,DeepTech Ventures +AI00077,AI Consultant,78936,EUR,67096,MI,FL,Germany,S,Germany,0,"Mathematics, Tableau, R, NLP, SQL",Bachelor,4,Consulting,2024-11-30,2025-01-03,697,6.9,Cloud AI Solutions +AI00078,AI Consultant,101054,USD,101054,SE,PT,South Korea,L,United Kingdom,0,"PyTorch, Python, TensorFlow",Bachelor,6,Healthcare,2025-02-04,2025-03-20,2396,8.8,DeepTech Ventures +AI00079,AI Specialist,91807,EUR,78036,SE,FT,Austria,S,Austria,50,"Linux, Azure, Scala, Python",Master,9,Education,2024-07-21,2024-09-13,1519,8.3,TechCorp Inc +AI00080,Machine Learning Engineer,49858,EUR,42379,EN,CT,Austria,S,Singapore,100,"PyTorch, Spark, Linux",Bachelor,1,Healthcare,2024-01-25,2024-04-02,1215,9.2,AI Innovations +AI00081,Robotics Engineer,80596,EUR,68507,EN,FT,Austria,L,Switzerland,0,"Kubernetes, Scala, PyTorch, Mathematics",Master,1,Education,2024-06-27,2024-08-26,1512,6.8,Digital Transformation LLC +AI00082,Head of AI,76026,USD,76026,MI,FT,Sweden,M,Sweden,50,"Tableau, SQL, R, Scala",PhD,4,Healthcare,2025-02-12,2025-03-24,1079,8,Predictive Systems +AI00083,Deep Learning Engineer,84841,USD,84841,MI,CT,Sweden,L,Sweden,0,"Azure, Linux, TensorFlow, GCP",Associate,4,Transportation,2024-11-18,2025-01-05,2456,5.7,Cognitive Computing +AI00084,Data Scientist,158900,CHF,143010,SE,FL,Switzerland,M,Switzerland,50,"Python, Statistics, Mathematics, Docker, TensorFlow",Associate,8,Finance,2024-06-14,2024-07-05,2367,6,Quantum Computing Inc +AI00085,Autonomous Systems Engineer,153858,EUR,130779,EX,CT,Germany,S,Germany,50,"MLOps, Azure, Java",Master,13,Gaming,2025-04-29,2025-06-21,2133,5.1,Cloud AI Solutions +AI00086,Data Scientist,115314,USD,115314,MI,CT,Denmark,M,Finland,0,"Java, Git, R, Azure",Bachelor,3,Real Estate,2024-06-01,2024-06-27,1783,7.9,Smart Analytics +AI00087,Machine Learning Engineer,181068,USD,181068,EX,FT,Israel,S,Israel,100,"R, Java, Hadoop, Mathematics",PhD,13,Transportation,2024-01-26,2024-03-25,1322,8.5,Machine Intelligence Group +AI00088,AI Software Engineer,119021,USD,119021,EN,FT,Denmark,L,Portugal,0,"Computer Vision, Docker, Linux, GCP",PhD,1,Transportation,2025-03-07,2025-05-10,1461,7.3,DataVision Ltd +AI00089,Data Analyst,219746,USD,219746,EX,FL,Israel,M,Czech Republic,100,"R, Python, Scala, TensorFlow",PhD,15,Finance,2024-07-02,2024-09-12,1485,7,Smart Analytics +AI00090,AI Consultant,115774,USD,115774,EX,FL,China,L,China,50,"Hadoop, Scala, NLP, PyTorch, SQL",Associate,10,Real Estate,2024-02-04,2024-03-09,1618,5.3,DataVision Ltd +AI00091,AI Consultant,130984,CHF,117886,EN,PT,Switzerland,L,Philippines,50,"MLOps, Deep Learning, Kubernetes, Azure, GCP",Bachelor,1,Retail,2024-01-08,2024-03-20,1774,5.3,DataVision Ltd +AI00092,ML Ops Engineer,191223,CHF,172101,EX,FT,Switzerland,S,Germany,0,"NLP, Azure, SQL",PhD,18,Healthcare,2024-04-07,2024-06-07,1926,6.8,Neural Networks Co +AI00093,AI Consultant,155502,USD,155502,SE,FT,Norway,M,Italy,50,"Python, NLP, AWS, Spark",PhD,9,Consulting,2025-01-29,2025-02-22,2449,7.6,Future Systems +AI00094,AI Specialist,86140,EUR,73219,MI,PT,Germany,L,South Korea,50,"Scala, Kubernetes, Deep Learning, AWS",Master,4,Real Estate,2025-03-11,2025-04-12,1816,7.3,Predictive Systems +AI00095,AI Architect,96028,GBP,72021,MI,FL,United Kingdom,L,Australia,0,"Data Visualization, MLOps, GCP, PyTorch",Bachelor,4,Healthcare,2025-03-09,2025-03-28,1878,6.6,Future Systems +AI00096,Principal Data Scientist,134920,USD,134920,SE,PT,United States,S,United States,0,"SQL, Mathematics, Data Visualization, Kubernetes",Associate,7,Consulting,2025-04-03,2025-05-12,1930,6.7,Predictive Systems +AI00097,Research Scientist,107694,USD,107694,SE,FL,Ireland,M,Estonia,50,"Spark, Linux, MLOps, R",Associate,5,Retail,2024-03-20,2024-04-22,2292,5.1,Future Systems +AI00098,Deep Learning Engineer,114301,USD,114301,MI,FT,Finland,L,Finland,0,"Tableau, MLOps, Python",Bachelor,4,Real Estate,2025-02-08,2025-03-05,1506,7.5,Digital Transformation LLC +AI00099,Machine Learning Researcher,92728,GBP,69546,MI,FT,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes, Azure",Bachelor,4,Transportation,2024-12-25,2025-02-05,1948,9.3,Cognitive Computing +AI00100,NLP Engineer,76826,SGD,99874,EN,PT,Singapore,M,Singapore,50,"Git, R, Statistics, PyTorch, Deep Learning",Bachelor,1,Government,2025-04-08,2025-05-10,804,7.4,Predictive Systems +AI00101,AI Consultant,48870,USD,48870,SE,PT,India,L,India,0,"Hadoop, Java, Azure, Spark, Statistics",Associate,7,Healthcare,2025-03-26,2025-05-16,1108,5.6,Cognitive Computing +AI00102,Data Scientist,89527,AUD,120861,MI,FT,Australia,L,United States,50,"Linux, Azure, SQL, R, Java",Master,4,Finance,2024-12-09,2024-12-30,1299,5.8,Predictive Systems +AI00103,Autonomous Systems Engineer,81103,AUD,109489,EN,CT,Australia,L,Australia,0,"Mathematics, SQL, Kubernetes",Master,0,Media,2024-05-26,2024-08-07,2055,7,Digital Transformation LLC +AI00104,Machine Learning Engineer,283428,USD,283428,EX,CT,Denmark,L,Denmark,0,"Python, TensorFlow, MLOps, Data Visualization",Associate,13,Healthcare,2025-03-10,2025-05-11,1275,5.1,Smart Analytics +AI00105,AI Product Manager,104906,USD,104906,MI,FL,United States,S,Portugal,50,"PyTorch, Java, Spark, Statistics",Bachelor,3,Technology,2025-01-26,2025-03-28,2101,8,Cognitive Computing +AI00106,AI Software Engineer,231496,USD,231496,EX,PT,Finland,L,Finland,50,"Tableau, R, Kubernetes",Master,18,Automotive,2025-02-13,2025-04-10,895,5.5,DataVision Ltd +AI00107,Robotics Engineer,147402,JPY,16214220,SE,FT,Japan,L,Japan,100,"Azure, GCP, Scala, R, Python",Bachelor,8,Automotive,2024-12-11,2025-02-01,593,7,Algorithmic Solutions +AI00108,Data Scientist,69331,EUR,58931,EN,FT,Austria,L,Austria,100,"AWS, Git, NLP, Java, Computer Vision",Master,1,Healthcare,2025-04-11,2025-05-21,639,8.8,AI Innovations +AI00109,AI Consultant,215842,EUR,183466,EX,CT,France,S,France,0,"Deep Learning, TensorFlow, Spark, Python",Bachelor,12,Healthcare,2024-12-19,2025-01-28,2098,6.7,Machine Intelligence Group +AI00110,Data Scientist,79833,USD,79833,SE,PT,South Korea,S,South Korea,0,"Java, SQL, PyTorch, TensorFlow, AWS",PhD,6,Healthcare,2024-01-04,2024-01-18,1284,5.7,Predictive Systems +AI00111,Data Scientist,304859,USD,304859,EX,FT,Norway,L,Norway,100,"Linux, SQL, Mathematics",Bachelor,15,Media,2025-03-22,2025-05-05,2460,6,Advanced Robotics +AI00112,Research Scientist,112217,EUR,95384,SE,CT,Germany,S,Israel,0,"Spark, Scala, Azure",Associate,8,Technology,2025-03-07,2025-04-23,1679,10,Digital Transformation LLC +AI00113,Head of AI,45738,USD,45738,EN,FL,South Korea,M,South Korea,100,"TensorFlow, Hadoop, Spark",Associate,0,Manufacturing,2024-03-17,2024-04-05,1481,9.5,DeepTech Ventures +AI00114,Machine Learning Researcher,195309,EUR,166013,EX,PT,Germany,S,Germany,50,"SQL, Tableau, PyTorch, NLP",Bachelor,18,Consulting,2024-12-14,2025-02-23,1277,5.3,DeepTech Ventures +AI00115,Data Scientist,141439,USD,141439,SE,FL,United States,L,United States,50,"Kubernetes, GCP, Git, SQL",PhD,9,Retail,2024-06-24,2024-07-13,1021,6.3,Digital Transformation LLC +AI00116,AI Consultant,125836,USD,125836,MI,FT,Norway,L,Norway,100,"Statistics, Kubernetes, Spark, GCP",Master,2,Transportation,2024-12-27,2025-02-22,1650,10,Predictive Systems +AI00117,Machine Learning Researcher,58213,USD,58213,EN,FT,Israel,S,Thailand,50,"Azure, Linux, Kubernetes",PhD,0,Telecommunications,2025-04-13,2025-06-08,1087,5.5,Cloud AI Solutions +AI00118,ML Ops Engineer,82191,EUR,69862,MI,CT,Germany,M,Germany,0,"Spark, GCP, Hadoop",Bachelor,2,Media,2024-08-05,2024-10-16,1906,9.5,Quantum Computing Inc +AI00119,Machine Learning Researcher,207975,AUD,280766,EX,CT,Australia,S,Colombia,0,"SQL, Azure, Computer Vision",Master,13,Telecommunications,2025-02-21,2025-04-07,1475,9.9,Future Systems +AI00120,Computer Vision Engineer,115664,USD,115664,SE,PT,Ireland,M,Ireland,0,"TensorFlow, R, Data Visualization",Bachelor,7,Automotive,2024-03-27,2024-05-15,1449,7.8,Smart Analytics +AI00121,AI Software Engineer,109337,USD,109337,SE,PT,Ireland,M,Ireland,50,"Data Visualization, PyTorch, Python, Mathematics, Git",Associate,9,Government,2025-04-26,2025-05-13,901,8.1,Predictive Systems +AI00122,Data Analyst,115386,USD,115386,SE,PT,Finland,M,Finland,100,"MLOps, Statistics, Hadoop, SQL",Associate,7,Energy,2024-09-02,2024-11-03,2387,6.7,Smart Analytics +AI00123,Autonomous Systems Engineer,64431,GBP,48323,EN,FT,United Kingdom,L,United Kingdom,50,"Git, Deep Learning, Python, Statistics, TensorFlow",Bachelor,1,Automotive,2025-01-25,2025-02-25,825,9,DeepTech Ventures +AI00124,Data Engineer,108088,USD,108088,SE,FL,United States,S,United States,100,"Tableau, Python, Docker, Azure",Bachelor,9,Consulting,2024-10-07,2024-12-15,1769,8,Smart Analytics +AI00125,ML Ops Engineer,228314,GBP,171236,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Hadoop, SQL, Statistics, TensorFlow",Master,16,Telecommunications,2024-10-18,2024-12-04,1005,6.5,Cognitive Computing +AI00126,Data Scientist,153260,AUD,206901,SE,CT,Australia,L,Australia,0,"MLOps, Java, NLP",Master,9,Education,2025-04-02,2025-05-04,1768,9.7,DataVision Ltd +AI00127,Data Scientist,63667,USD,63667,MI,CT,Israel,S,Norway,100,"R, Data Visualization, SQL, NLP",PhD,4,Energy,2025-03-20,2025-05-12,1336,7.9,Algorithmic Solutions +AI00128,Research Scientist,31185,USD,31185,MI,FL,China,S,Colombia,100,"AWS, GCP, NLP, SQL, Statistics",Associate,3,Healthcare,2025-03-11,2025-04-07,1510,9.2,Neural Networks Co +AI00129,Machine Learning Engineer,132167,EUR,112342,SE,PT,Germany,M,Germany,50,"MLOps, Docker, Linux, Computer Vision",Bachelor,9,Education,2024-08-04,2024-10-12,1110,6.2,Quantum Computing Inc +AI00130,AI Research Scientist,223349,JPY,24568390,EX,FL,Japan,L,Japan,100,"PyTorch, Mathematics, TensorFlow",Bachelor,11,Gaming,2024-07-31,2024-09-27,1489,5.9,Smart Analytics +AI00131,AI Architect,26957,USD,26957,EN,CT,India,M,India,100,"Azure, Computer Vision, Statistics",Bachelor,1,Transportation,2025-03-23,2025-04-17,2335,9.5,DataVision Ltd +AI00132,AI Software Engineer,93564,USD,93564,MI,CT,Sweden,S,Sweden,0,"PyTorch, Docker, Data Visualization, Scala, Computer Vision",Associate,2,Transportation,2025-03-25,2025-04-13,515,9.7,Advanced Robotics +AI00133,Computer Vision Engineer,113846,EUR,96769,SE,PT,France,S,France,100,"SQL, Git, R, Hadoop, Docker",Associate,6,Energy,2024-09-02,2024-10-30,2447,7.8,DataVision Ltd +AI00134,AI Specialist,147580,EUR,125443,EX,FL,France,M,France,0,"Linux, Deep Learning, Hadoop, Kubernetes, Docker",PhD,17,Telecommunications,2024-11-13,2025-01-10,2416,5.9,Cloud AI Solutions +AI00135,Data Engineer,50514,CAD,63143,EN,PT,Canada,M,Philippines,100,"SQL, PyTorch, Tableau, NLP",PhD,1,Automotive,2024-08-04,2024-08-28,2384,9,Cognitive Computing +AI00136,AI Product Manager,94158,EUR,80034,MI,FL,Germany,M,Vietnam,100,"PyTorch, R, Scala",Master,2,Education,2024-09-01,2024-10-10,867,5.5,Future Systems +AI00137,Principal Data Scientist,161009,EUR,136858,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, AWS, GCP",Associate,19,Transportation,2024-02-17,2024-03-17,1247,7.1,Cognitive Computing +AI00138,Data Analyst,91911,USD,91911,EX,FT,India,L,India,100,"PyTorch, SQL, Azure, Docker",Associate,15,Technology,2024-06-15,2024-08-15,2149,5.9,Cloud AI Solutions +AI00139,AI Specialist,248071,EUR,210860,EX,FL,Germany,M,Czech Republic,50,"Kubernetes, R, GCP",Bachelor,15,Consulting,2025-04-13,2025-04-29,616,7.6,Future Systems +AI00140,Autonomous Systems Engineer,150204,EUR,127673,SE,PT,Germany,M,Germany,50,"Docker, Linux, Kubernetes, Data Visualization",Bachelor,9,Transportation,2025-03-18,2025-04-12,1478,6.3,Neural Networks Co +AI00141,AI Product Manager,181517,EUR,154289,SE,CT,Netherlands,L,Netherlands,50,"SQL, Kubernetes, NLP, MLOps",PhD,9,Government,2024-08-13,2024-09-05,981,8.9,TechCorp Inc +AI00142,Data Analyst,64573,EUR,54887,EN,PT,France,L,France,100,"Kubernetes, GCP, Mathematics, Python",Master,1,Government,2024-07-19,2024-09-30,1495,9.2,AI Innovations +AI00143,ML Ops Engineer,89332,USD,89332,MI,CT,United States,S,United States,100,"Python, TensorFlow, Deep Learning, Docker, PyTorch",Bachelor,4,Finance,2024-08-20,2024-10-23,2011,6,Predictive Systems +AI00144,Machine Learning Engineer,118239,USD,118239,SE,FL,Sweden,S,Indonesia,50,"AWS, Hadoop, PyTorch, Statistics, Azure",PhD,9,Energy,2024-08-03,2024-09-22,576,8.1,Future Systems +AI00145,AI Specialist,103715,JPY,11408650,MI,FT,Japan,S,Japan,50,"Python, Azure, Statistics",Bachelor,4,Automotive,2024-12-11,2025-01-20,2224,9.3,Neural Networks Co +AI00146,AI Consultant,151680,AUD,204768,EX,FL,Australia,S,Australia,100,"Computer Vision, AWS, Kubernetes",Associate,14,Manufacturing,2024-06-20,2024-07-31,2439,6.9,Cognitive Computing +AI00147,Data Analyst,142589,EUR,121201,SE,FT,Netherlands,L,Netherlands,0,"Docker, Tableau, Kubernetes, Data Visualization, GCP",Master,8,Government,2024-10-25,2024-11-11,2431,6,Predictive Systems +AI00148,Research Scientist,63062,USD,63062,EN,PT,Sweden,L,Sweden,50,"PyTorch, R, Mathematics, Kubernetes",Associate,1,Real Estate,2024-09-05,2024-10-18,1558,6.7,Smart Analytics +AI00149,Data Engineer,80691,JPY,8876010,EN,CT,Japan,L,Japan,100,"Deep Learning, Computer Vision, PyTorch, Statistics, Spark",Master,1,Retail,2024-12-21,2025-01-04,624,8.1,DataVision Ltd +AI00150,Data Analyst,171580,JPY,18873800,SE,PT,Japan,L,Kenya,100,"SQL, Spark, MLOps",PhD,7,Manufacturing,2024-10-14,2024-12-09,1931,6.7,Predictive Systems +AI00151,Autonomous Systems Engineer,58331,USD,58331,SE,PT,China,M,Chile,0,"Hadoop, Java, NLP, Mathematics, Python",Master,5,Transportation,2024-11-23,2025-01-24,2002,6.1,Cognitive Computing +AI00152,Head of AI,85620,CAD,107025,MI,FT,Canada,L,Canada,100,"TensorFlow, GCP, MLOps, NLP",Associate,4,Healthcare,2025-01-22,2025-02-23,848,5.8,Quantum Computing Inc +AI00153,AI Consultant,220871,EUR,187740,EX,FT,Austria,M,Austria,0,"Linux, Tableau, Spark, Scala",Associate,14,Automotive,2024-06-28,2024-07-31,821,5.2,DeepTech Ventures +AI00154,ML Ops Engineer,93007,EUR,79056,MI,CT,France,M,France,50,"Docker, SQL, MLOps, GCP, Hadoop",Bachelor,4,Energy,2024-06-05,2024-07-23,1595,6.4,Cognitive Computing +AI00155,AI Specialist,191783,SGD,249318,EX,FT,Singapore,S,Singapore,100,"Java, GCP, PyTorch",PhD,14,Healthcare,2024-10-04,2024-10-27,2352,5.6,Advanced Robotics +AI00156,Head of AI,83683,USD,83683,MI,FL,Israel,S,Czech Republic,50,"Mathematics, Computer Vision, MLOps, Git, Deep Learning",Bachelor,3,Education,2024-05-15,2024-06-07,818,5.3,Smart Analytics +AI00157,Research Scientist,107869,USD,107869,SE,FL,Ireland,S,Ireland,50,"SQL, Linux, GCP",Associate,8,Finance,2024-02-17,2024-04-01,2148,7.3,Predictive Systems +AI00158,Autonomous Systems Engineer,73528,USD,73528,MI,PT,Sweden,S,Poland,0,"NLP, R, Git, MLOps",Associate,2,Finance,2024-03-01,2024-05-05,557,8,Algorithmic Solutions +AI00159,NLP Engineer,47642,USD,47642,MI,FL,China,L,Sweden,100,"Python, TensorFlow, NLP",PhD,3,Telecommunications,2024-11-22,2025-01-13,2171,8,DeepTech Ventures +AI00160,AI Software Engineer,179937,EUR,152946,SE,PT,Netherlands,L,Netherlands,50,"Python, TensorFlow, NLP, Kubernetes",Associate,6,Real Estate,2024-06-01,2024-07-29,774,8.1,Machine Intelligence Group +AI00161,Data Engineer,157066,CHF,141359,MI,PT,Switzerland,L,Sweden,0,"GCP, Docker, NLP, Data Visualization",PhD,2,Transportation,2024-05-01,2024-05-26,887,9,Neural Networks Co +AI00162,Data Scientist,57299,USD,57299,EN,CT,Israel,M,Israel,0,"PyTorch, Spark, TensorFlow",Bachelor,1,Retail,2024-01-17,2024-02-19,794,7.8,DataVision Ltd +AI00163,Data Engineer,176844,CAD,221055,EX,FL,Canada,L,France,50,"Linux, Scala, Tableau",PhD,10,Telecommunications,2024-06-08,2024-07-19,577,5.4,Digital Transformation LLC +AI00164,AI Research Scientist,64892,CAD,81115,EN,CT,Canada,M,Canada,50,"Kubernetes, Scala, Azure, Computer Vision",Associate,1,Transportation,2024-11-05,2025-01-03,1645,5.7,Algorithmic Solutions +AI00165,AI Specialist,63024,EUR,53570,EN,CT,Austria,L,Austria,0,"Git, Statistics, Data Visualization",Bachelor,1,Gaming,2024-04-04,2024-05-05,1745,9.2,Algorithmic Solutions +AI00166,Principal Data Scientist,136695,CHF,123026,MI,FL,Switzerland,S,Switzerland,50,"Linux, GCP, Tableau, Java",Bachelor,2,Gaming,2024-12-10,2024-12-27,1424,5.9,Algorithmic Solutions +AI00167,Data Scientist,69744,USD,69744,EN,PT,South Korea,L,South Korea,50,"Python, Docker, Tableau",Associate,1,Telecommunications,2024-12-30,2025-01-22,1077,8.4,Autonomous Tech +AI00168,AI Specialist,135137,EUR,114866,EX,FL,Austria,M,Austria,0,"Kubernetes, GCP, Data Visualization",PhD,18,Finance,2024-04-06,2024-05-17,1590,5.4,TechCorp Inc +AI00169,Computer Vision Engineer,143037,USD,143037,EX,FL,Sweden,S,Sweden,0,"Data Visualization, Linux, Azure, Java",PhD,13,Manufacturing,2024-05-24,2024-07-07,775,9.5,Autonomous Tech +AI00170,Machine Learning Engineer,113068,GBP,84801,SE,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, Java, Data Visualization, Kubernetes",Master,9,Gaming,2024-06-10,2024-07-05,1805,6.6,Machine Intelligence Group +AI00171,AI Software Engineer,113917,GBP,85438,SE,PT,United Kingdom,S,Russia,0,"SQL, Kubernetes, GCP",Master,9,Government,2024-10-07,2024-10-26,1720,7.3,Future Systems +AI00172,Head of AI,80311,USD,80311,EX,PT,India,M,India,50,"Git, GCP, Computer Vision, Kubernetes, Docker",Bachelor,13,Finance,2025-01-17,2025-03-11,1052,5,Smart Analytics +AI00173,Autonomous Systems Engineer,160261,EUR,136222,SE,CT,Germany,L,Germany,50,"AWS, Linux, Scala, GCP, Python",Associate,6,Education,2024-02-26,2024-04-16,748,9.9,Smart Analytics +AI00174,Research Scientist,152241,CHF,137017,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, SQL, Git, PyTorch, Computer Vision",Bachelor,8,Gaming,2024-04-05,2024-06-05,1807,5.9,AI Innovations +AI00175,Research Scientist,74172,USD,74172,MI,CT,Israel,M,Israel,100,"Statistics, Kubernetes, GCP, Spark",PhD,2,Government,2024-01-24,2024-03-22,1780,7.5,Algorithmic Solutions +AI00176,Computer Vision Engineer,105632,USD,105632,MI,FL,Finland,L,Norway,100,"AWS, R, MLOps",Bachelor,3,Government,2025-01-03,2025-01-30,2376,9.4,Machine Intelligence Group +AI00177,Principal Data Scientist,89515,SGD,116370,MI,CT,Singapore,L,South Africa,100,"PyTorch, NLP, Computer Vision",Associate,4,Gaming,2025-01-17,2025-03-29,2328,7.4,DataVision Ltd +AI00178,AI Software Engineer,102319,USD,102319,MI,FL,Denmark,M,Colombia,50,"Deep Learning, Mathematics, Data Visualization, NLP",Associate,4,Energy,2024-07-14,2024-08-01,1939,6.2,Cognitive Computing +AI00179,AI Software Engineer,110536,USD,110536,MI,CT,Denmark,M,France,50,"SQL, Spark, Mathematics, Linux, TensorFlow",Associate,2,Real Estate,2024-05-01,2024-06-22,1559,5.4,DeepTech Ventures +AI00180,NLP Engineer,176372,USD,176372,SE,FL,Denmark,S,Denmark,0,"SQL, AWS, Computer Vision",Bachelor,5,Technology,2024-05-02,2024-07-05,729,8,AI Innovations +AI00181,AI Software Engineer,58111,EUR,49394,EN,FT,Austria,S,Austria,100,"Docker, Linux, Java",Bachelor,0,Finance,2024-01-20,2024-02-17,889,5.6,Digital Transformation LLC +AI00182,AI Product Manager,39802,USD,39802,SE,PT,India,M,Spain,100,"Git, Hadoop, Linux",Associate,8,Consulting,2024-02-05,2024-03-06,2046,8.3,Digital Transformation LLC +AI00183,Head of AI,147385,EUR,125277,SE,FL,France,L,Denmark,50,"Java, Statistics, AWS, Scala",Master,9,Consulting,2024-03-08,2024-03-25,1576,8.6,Cloud AI Solutions +AI00184,Research Scientist,118122,USD,118122,EN,FT,Denmark,L,Denmark,0,"Git, Scala, MLOps, Docker, Hadoop",Associate,0,Automotive,2024-07-20,2024-09-06,2018,9.3,Cloud AI Solutions +AI00185,AI Architect,75225,AUD,101554,EN,FT,Australia,L,Russia,100,"Deep Learning, MLOps, Linux",Master,0,Real Estate,2024-10-10,2024-11-26,2399,7.5,Machine Intelligence Group +AI00186,AI Research Scientist,48325,CAD,60406,EN,FL,Canada,M,Canada,100,"Spark, TensorFlow, Hadoop",Associate,0,Manufacturing,2025-03-26,2025-06-07,1523,6.2,Algorithmic Solutions +AI00187,Data Scientist,64973,USD,64973,EN,CT,Sweden,L,Sweden,0,"Git, Spark, NLP, MLOps",Master,0,Energy,2024-03-08,2024-04-24,1016,6.4,AI Innovations +AI00188,Computer Vision Engineer,78182,AUD,105546,MI,PT,Australia,M,Australia,50,"Hadoop, Docker, Computer Vision, Linux",Associate,4,Retail,2024-03-22,2024-05-22,1582,7.9,Cloud AI Solutions +AI00189,Data Analyst,357875,USD,357875,EX,PT,Norway,L,Norway,50,"Git, AWS, Linux, Tableau, Java",Associate,10,Retail,2024-01-19,2024-02-27,1044,8,Advanced Robotics +AI00190,AI Software Engineer,61953,USD,61953,SE,FT,India,L,India,50,"AWS, NLP, Tableau, SQL, PyTorch",Associate,8,Finance,2024-08-20,2024-10-14,1469,6.3,Advanced Robotics +AI00191,AI Product Manager,236982,USD,236982,EX,FL,Denmark,L,Poland,0,"AWS, Kubernetes, Tableau",Master,10,Gaming,2025-03-20,2025-04-03,597,5.1,Smart Analytics +AI00192,Principal Data Scientist,90203,EUR,76673,MI,PT,Austria,S,Austria,50,"Python, R, MLOps, GCP",PhD,3,Finance,2025-03-08,2025-05-12,1774,7.5,Autonomous Tech +AI00193,NLP Engineer,109984,JPY,12098240,SE,CT,Japan,S,Switzerland,0,"Data Visualization, Linux, SQL",Associate,7,Energy,2024-08-07,2024-08-31,1535,8,DeepTech Ventures +AI00194,AI Specialist,146371,CAD,182964,EX,PT,Canada,S,Ireland,100,"MLOps, Python, Scala, Docker",PhD,14,Healthcare,2024-11-15,2024-12-17,2313,5.4,Machine Intelligence Group +AI00195,Deep Learning Engineer,268088,EUR,227875,EX,PT,Netherlands,M,Netherlands,0,"NLP, AWS, Tableau, Scala, Computer Vision",Associate,10,Finance,2024-11-04,2024-12-21,1385,9.5,Predictive Systems +AI00196,Data Engineer,97647,GBP,73235,MI,CT,United Kingdom,S,Norway,50,"Java, Data Visualization, Scala, R",PhD,4,Government,2024-02-27,2024-04-08,1305,6.2,DeepTech Ventures +AI00197,Principal Data Scientist,221711,EUR,188454,EX,FT,Germany,S,Turkey,0,"TensorFlow, Kubernetes, NLP, PyTorch",Bachelor,17,Gaming,2025-01-14,2025-03-16,1652,8.9,Machine Intelligence Group +AI00198,Data Scientist,78716,EUR,66909,EN,PT,Germany,L,Germany,100,"Azure, Statistics, Kubernetes, Java",Bachelor,0,Automotive,2024-07-12,2024-08-13,2401,8.2,DataVision Ltd +AI00199,Principal Data Scientist,169717,CHF,152745,SE,CT,Switzerland,S,Switzerland,50,"Spark, Scala, PyTorch, Statistics",Master,5,Education,2024-03-07,2024-04-03,1003,9.5,DeepTech Ventures +AI00200,Data Analyst,92798,EUR,78878,MI,CT,Austria,L,Austria,50,"Linux, Kubernetes, SQL, Git",PhD,4,Consulting,2024-09-07,2024-11-12,1685,6.4,Neural Networks Co +AI00201,AI Product Manager,37177,USD,37177,MI,FL,China,S,China,0,"R, AWS, Hadoop, Spark",Associate,2,Automotive,2024-06-13,2024-08-25,869,6.1,Digital Transformation LLC +AI00202,Data Analyst,85505,USD,85505,MI,CT,Israel,S,Israel,50,"Java, Linux, R",Bachelor,4,Gaming,2025-01-21,2025-03-28,1983,5.1,Future Systems +AI00203,Robotics Engineer,113625,EUR,96581,MI,FT,France,L,France,100,"R, Python, Data Visualization, Scala",Associate,3,Automotive,2024-12-13,2025-01-02,2036,5.8,Advanced Robotics +AI00204,ML Ops Engineer,121846,AUD,164492,SE,PT,Australia,L,Australia,50,"NLP, AWS, Docker, Python",Master,6,Retail,2025-02-06,2025-04-20,2213,7.4,DeepTech Ventures +AI00205,Robotics Engineer,115136,JPY,12664960,MI,FT,Japan,M,Japan,50,"Scala, Python, Mathematics",Bachelor,3,Finance,2024-08-09,2024-09-03,1542,6.3,Neural Networks Co +AI00206,Data Scientist,265646,EUR,225799,EX,FT,France,L,Canada,0,"PyTorch, Computer Vision, SQL, AWS",Bachelor,16,Healthcare,2024-12-28,2025-01-11,1473,9.4,Predictive Systems +AI00207,AI Consultant,92726,CHF,83453,EN,FT,Switzerland,L,Switzerland,0,"Kubernetes, R, GCP, MLOps, Mathematics",Bachelor,0,Telecommunications,2024-09-22,2024-11-17,2013,9.8,AI Innovations +AI00208,Research Scientist,50607,USD,50607,EN,FL,Israel,S,Israel,100,"Azure, Tableau, Kubernetes, Deep Learning, Computer Vision",Bachelor,0,Telecommunications,2024-06-10,2024-08-05,1801,8.6,Autonomous Tech +AI00209,Machine Learning Researcher,219875,USD,219875,EX,PT,Sweden,L,Sweden,50,"NLP, Kubernetes, Tableau, Linux, R",Master,15,Automotive,2024-09-12,2024-11-15,1609,8.4,TechCorp Inc +AI00210,Robotics Engineer,93342,USD,93342,EX,CT,China,M,China,100,"Spark, Python, Azure",Master,11,Transportation,2025-02-15,2025-04-02,1345,7.2,AI Innovations +AI00211,Data Scientist,99132,EUR,84262,MI,FL,Netherlands,L,Netherlands,50,"Python, Linux, R",PhD,3,Government,2024-05-17,2024-06-15,2121,9.7,Advanced Robotics +AI00212,Data Analyst,148775,SGD,193408,SE,CT,Singapore,L,France,0,"Java, PyTorch, Scala",Associate,5,Real Estate,2024-01-07,2024-01-26,1222,6.3,Smart Analytics +AI00213,Data Scientist,63090,USD,63090,EN,CT,Denmark,S,Denmark,100,"AWS, MLOps, Python, Tableau, Azure",Master,0,Retail,2024-01-25,2024-03-18,1913,5.4,Neural Networks Co +AI00214,Robotics Engineer,39782,USD,39782,EN,CT,China,L,China,0,"Data Visualization, NLP, Python, R, Computer Vision",Bachelor,1,Transportation,2024-10-30,2025-01-04,2183,8.9,Quantum Computing Inc +AI00215,AI Architect,240915,CAD,301144,EX,PT,Canada,L,Canada,0,"TensorFlow, Java, MLOps",Master,14,Energy,2024-02-23,2024-04-17,1222,7.3,Advanced Robotics +AI00216,Robotics Engineer,69061,SGD,89779,MI,FL,Singapore,S,France,100,"Data Visualization, Linux, Tableau, Mathematics, Kubernetes",Master,4,Real Estate,2024-12-17,2025-02-01,1319,6.9,Future Systems +AI00217,Machine Learning Engineer,146403,EUR,124443,SE,PT,Netherlands,L,Netherlands,100,"Python, Scala, Java, Computer Vision, Azure",PhD,5,Gaming,2024-01-04,2024-02-07,1031,8.4,Algorithmic Solutions +AI00218,AI Consultant,56884,USD,56884,EN,CT,Finland,M,Finland,100,"Python, Mathematics, Tableau, Kubernetes",Bachelor,1,Government,2024-08-08,2024-08-24,532,9.1,Autonomous Tech +AI00219,AI Consultant,172277,CHF,155049,SE,PT,Switzerland,L,Switzerland,0,"Hadoop, Spark, Kubernetes, PyTorch, Azure",Bachelor,9,Technology,2024-08-09,2024-08-26,1725,9.7,Quantum Computing Inc +AI00220,Data Engineer,254054,EUR,215946,EX,CT,Austria,L,Austria,100,"R, Tableau, Data Visualization, Spark",Bachelor,17,Education,2024-09-26,2024-11-08,1518,9.8,Digital Transformation LLC +AI00221,Machine Learning Researcher,97442,EUR,82826,SE,FT,Germany,S,Germany,50,"Computer Vision, Linux, TensorFlow",PhD,5,Retail,2024-07-07,2024-08-01,1164,5.5,DataVision Ltd +AI00222,NLP Engineer,84037,USD,84037,EX,PT,China,S,China,50,"Computer Vision, NLP, GCP",Bachelor,19,Retail,2024-01-24,2024-02-12,2292,6,Autonomous Tech +AI00223,Principal Data Scientist,104614,EUR,88922,MI,CT,Netherlands,S,Netherlands,50,"SQL, Python, Linux, Computer Vision, Hadoop",Bachelor,4,Telecommunications,2024-10-10,2024-12-09,1895,7.9,Digital Transformation LLC +AI00224,Data Scientist,103566,USD,103566,SE,CT,Finland,S,Finland,100,"Git, Linux, Java, Statistics",Bachelor,7,Manufacturing,2024-01-09,2024-03-04,1777,8,Predictive Systems +AI00225,Autonomous Systems Engineer,69417,USD,69417,EN,CT,Ireland,L,Canada,50,"Data Visualization, Java, Docker, Kubernetes",Master,0,Energy,2024-04-22,2024-05-12,1887,9.4,Cloud AI Solutions +AI00226,AI Product Manager,27748,USD,27748,EN,FT,China,S,Israel,100,"NLP, Java, TensorFlow",Master,0,Automotive,2024-12-09,2025-02-03,1984,5.8,Autonomous Tech +AI00227,NLP Engineer,245370,USD,245370,EX,FL,Sweden,M,Sweden,100,"Tableau, Java, TensorFlow",Master,14,Real Estate,2024-03-17,2024-04-03,2030,8.4,Cognitive Computing +AI00228,AI Software Engineer,86794,JPY,9547340,MI,FL,Japan,S,Japan,50,"Scala, SQL, Hadoop, Statistics, GCP",Bachelor,4,Finance,2025-02-25,2025-04-25,1875,8.2,Cloud AI Solutions +AI00229,Computer Vision Engineer,58554,USD,58554,EN,FT,Ireland,S,Ireland,0,"Linux, Java, R, SQL, Mathematics",Master,1,Healthcare,2024-11-20,2024-12-22,2448,9.3,Cognitive Computing +AI00230,AI Specialist,152077,GBP,114058,SE,FT,United Kingdom,L,Canada,50,"Kubernetes, Git, Statistics",PhD,6,Automotive,2024-01-30,2024-03-20,2336,9.6,Cognitive Computing +AI00231,Data Scientist,152349,JPY,16758390,EX,FT,Japan,S,Japan,50,"MLOps, Scala, Java",Associate,10,Healthcare,2024-08-04,2024-09-30,1703,5.5,Quantum Computing Inc +AI00232,Deep Learning Engineer,155935,USD,155935,EX,FL,Israel,S,Ghana,50,"Python, Hadoop, Git",Associate,17,Retail,2025-03-25,2025-04-27,661,8.8,Predictive Systems +AI00233,Deep Learning Engineer,299354,CHF,269419,EX,FL,Switzerland,S,Switzerland,100,"MLOps, Scala, Docker",Bachelor,14,Retail,2024-06-16,2024-07-31,572,6.8,Advanced Robotics +AI00234,Autonomous Systems Engineer,112130,JPY,12334300,SE,FT,Japan,M,Japan,100,"SQL, Azure, Deep Learning",Associate,5,Energy,2024-03-14,2024-05-14,2021,9.4,Cognitive Computing +AI00235,AI Product Manager,299005,GBP,224254,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, MLOps, Statistics, Computer Vision",Master,16,Transportation,2024-06-17,2024-08-17,687,9.5,Cloud AI Solutions +AI00236,AI Product Manager,57697,JPY,6346670,EN,FL,Japan,M,Japan,100,"Python, TensorFlow, Deep Learning, MLOps",PhD,1,Energy,2024-03-23,2024-05-01,1370,9.7,DataVision Ltd +AI00237,Deep Learning Engineer,140199,SGD,182259,EX,FT,Singapore,S,Singapore,0,"Docker, Data Visualization, Python",Associate,18,Manufacturing,2025-03-26,2025-04-22,568,6.7,Predictive Systems +AI00238,Computer Vision Engineer,107028,USD,107028,EX,CT,China,M,Ghana,50,"Git, Linux, Statistics, Mathematics",PhD,11,Education,2024-10-29,2025-01-01,1172,5.8,Future Systems +AI00239,Data Analyst,48978,USD,48978,EN,FL,South Korea,M,Switzerland,50,"Computer Vision, Kubernetes, Git",Associate,1,Gaming,2024-02-21,2024-04-21,647,7.3,Future Systems +AI00240,Principal Data Scientist,101366,EUR,86161,MI,FL,France,M,France,100,"Python, Data Visualization, Linux, Azure",Master,3,Manufacturing,2025-01-04,2025-01-20,1292,6.7,DataVision Ltd +AI00241,AI Research Scientist,79125,EUR,67256,MI,CT,Netherlands,S,Netherlands,100,"Computer Vision, GCP, NLP, Statistics",PhD,4,Media,2024-03-05,2024-05-14,510,7.8,Smart Analytics +AI00242,Machine Learning Engineer,51110,USD,51110,SE,FL,China,S,China,50,"TensorFlow, Mathematics, Deep Learning, Computer Vision, R",Master,6,Automotive,2024-03-22,2024-05-06,1861,9.8,Cloud AI Solutions +AI00243,Data Scientist,96374,EUR,81918,MI,PT,Germany,S,Germany,0,"Deep Learning, SQL, Git, PyTorch",Associate,3,Retail,2024-05-08,2024-06-08,744,8.8,TechCorp Inc +AI00244,Autonomous Systems Engineer,92286,SGD,119972,EN,PT,Singapore,L,Singapore,100,"AWS, Java, Python, Mathematics",PhD,0,Energy,2025-02-04,2025-04-05,830,8.3,Advanced Robotics +AI00245,Data Scientist,102456,USD,102456,SE,FL,Sweden,S,Sweden,100,"PyTorch, Git, R, Azure",PhD,7,Education,2024-08-31,2024-11-12,552,6.9,Algorithmic Solutions +AI00246,ML Ops Engineer,138420,USD,138420,EX,CT,Sweden,M,Sweden,50,"PyTorch, Docker, Data Visualization, GCP, TensorFlow",PhD,17,Transportation,2024-02-13,2024-03-21,1582,5.3,DataVision Ltd +AI00247,AI Software Engineer,203654,CAD,254568,EX,PT,Canada,L,Canada,100,"SQL, Kubernetes, Computer Vision, GCP",PhD,12,Retail,2024-01-19,2024-03-23,1049,8.1,Advanced Robotics +AI00248,Robotics Engineer,121706,EUR,103450,SE,FT,Austria,L,Austria,50,"Hadoop, Data Visualization, Python, TensorFlow, Mathematics",PhD,8,Real Estate,2024-12-31,2025-02-23,2066,9.1,Neural Networks Co +AI00249,AI Software Engineer,112939,SGD,146821,SE,CT,Singapore,S,Netherlands,0,"R, Azure, Computer Vision, Deep Learning",PhD,9,Consulting,2024-10-30,2024-11-21,2008,10,Smart Analytics +AI00250,AI Software Engineer,223145,EUR,189673,EX,CT,Germany,L,Brazil,50,"Kubernetes, Scala, MLOps, Statistics",Bachelor,19,Energy,2024-01-02,2024-01-26,2356,7.1,AI Innovations +AI00251,Data Engineer,198959,AUD,268595,EX,FT,Australia,M,Australia,0,"Spark, Python, Deep Learning, TensorFlow, Mathematics",Master,11,Telecommunications,2025-03-11,2025-04-04,1821,7.1,Neural Networks Co +AI00252,Machine Learning Engineer,249841,USD,249841,EX,CT,United States,M,United States,100,"Scala, Linux, Java, Data Visualization",Associate,14,Healthcare,2024-01-08,2024-01-29,2130,7,Machine Intelligence Group +AI00253,AI Architect,81300,CHF,73170,EN,CT,Switzerland,S,Switzerland,0,"SQL, Python, Scala",Master,0,Energy,2024-04-26,2024-06-02,1225,9,AI Innovations +AI00254,Machine Learning Engineer,89201,USD,89201,EX,CT,China,L,Colombia,0,"Kubernetes, Mathematics, Data Visualization, SQL",Master,16,Gaming,2025-02-15,2025-03-15,1146,5.7,TechCorp Inc +AI00255,Robotics Engineer,123827,CHF,111444,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, GCP, AWS, SQL, NLP",Master,4,Telecommunications,2025-01-14,2025-03-11,543,8.3,Quantum Computing Inc +AI00256,AI Product Manager,321014,USD,321014,EX,FL,Denmark,M,Denmark,100,"Hadoop, Scala, MLOps",Master,16,Finance,2024-04-02,2024-06-13,1990,5.3,Neural Networks Co +AI00257,ML Ops Engineer,195690,USD,195690,EX,PT,Ireland,L,Ireland,100,"Azure, Kubernetes, PyTorch",Associate,11,Education,2024-01-15,2024-03-12,1481,6.2,Neural Networks Co +AI00258,AI Software Engineer,88109,SGD,114542,MI,FL,Singapore,M,South Korea,100,"SQL, Hadoop, Tableau, Spark",Bachelor,2,Government,2025-03-24,2025-06-01,2164,9.9,AI Innovations +AI00259,Deep Learning Engineer,93310,EUR,79314,SE,PT,Germany,S,Germany,0,"TensorFlow, Statistics, Mathematics",Associate,8,Retail,2024-08-24,2024-10-22,1732,5.5,Smart Analytics +AI00260,Deep Learning Engineer,180162,EUR,153138,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, Java, Spark, NLP",Associate,12,Technology,2024-03-06,2024-04-29,2049,9.7,Autonomous Tech +AI00261,Deep Learning Engineer,324764,CHF,292288,EX,PT,Switzerland,M,Switzerland,0,"TensorFlow, Kubernetes, Docker, Tableau, Scala",Associate,14,Manufacturing,2024-08-05,2024-10-03,1915,8.2,Quantum Computing Inc +AI00262,AI Consultant,57105,SGD,74237,EN,FT,Singapore,M,India,0,"Scala, Data Visualization, Python, GCP",Associate,1,Telecommunications,2024-05-26,2024-08-01,2453,6.9,DataVision Ltd +AI00263,Research Scientist,131121,USD,131121,EX,PT,Finland,M,South Africa,100,"Data Visualization, R, Kubernetes",Bachelor,11,Education,2024-10-02,2024-12-04,1707,7.3,Digital Transformation LLC +AI00264,NLP Engineer,87993,USD,87993,SE,FL,Israel,S,Netherlands,50,"MLOps, Deep Learning, Azure, Kubernetes",Associate,6,Real Estate,2024-11-10,2025-01-04,1598,9.4,Cognitive Computing +AI00265,Data Analyst,77654,EUR,66006,EN,CT,Austria,L,Austria,50,"PyTorch, Hadoop, Tableau, Docker",Associate,1,Retail,2024-10-11,2024-12-03,1681,7.7,Neural Networks Co +AI00266,Machine Learning Engineer,47769,AUD,64488,EN,PT,Australia,S,Australia,50,"Java, Python, Data Visualization, Docker",Master,1,Transportation,2024-02-24,2024-04-01,2173,5.2,Neural Networks Co +AI00267,NLP Engineer,112750,GBP,84563,SE,PT,United Kingdom,S,United Kingdom,100,"Git, Statistics, Spark",Master,8,Real Estate,2024-04-14,2024-05-15,529,5.5,Predictive Systems +AI00268,AI Architect,63413,USD,63413,EN,PT,Denmark,S,Denmark,0,"Tableau, Hadoop, Statistics, MLOps",Associate,0,Gaming,2024-06-11,2024-08-09,2014,7.5,DataVision Ltd +AI00269,Robotics Engineer,96518,EUR,82040,SE,FT,Austria,S,Norway,0,"GCP, Deep Learning, Java, Statistics, Spark",Bachelor,5,Automotive,2024-02-20,2024-04-23,702,8.4,TechCorp Inc +AI00270,AI Research Scientist,136768,USD,136768,MI,PT,Norway,M,Norway,50,"Python, Java, SQL",Bachelor,4,Healthcare,2025-03-08,2025-04-01,2160,9.5,Smart Analytics +AI00271,Research Scientist,143660,CAD,179575,SE,FL,Canada,L,Canada,100,"Statistics, Java, Data Visualization, Azure",Master,8,Education,2024-01-22,2024-03-07,1728,6.7,Algorithmic Solutions +AI00272,Data Engineer,122612,SGD,159396,SE,FT,Singapore,S,Singapore,50,"GCP, Azure, Tableau, Computer Vision, Scala",Associate,9,Media,2024-10-26,2024-11-12,1794,5.8,TechCorp Inc +AI00273,Principal Data Scientist,224629,AUD,303249,EX,FL,Australia,S,Australia,100,"R, SQL, Kubernetes, Statistics, Linux",Master,15,Healthcare,2024-07-14,2024-07-31,2418,9.6,Cognitive Computing +AI00274,Computer Vision Engineer,110517,EUR,93939,SE,FT,France,L,France,50,"Python, TensorFlow, Hadoop, R",PhD,7,Manufacturing,2024-10-17,2024-11-27,2208,8.2,Advanced Robotics +AI00275,Robotics Engineer,78533,SGD,102093,EN,CT,Singapore,M,Singapore,100,"Deep Learning, Spark, Git",Bachelor,0,Government,2024-10-22,2024-12-24,1972,5.7,Future Systems +AI00276,Head of AI,282152,CHF,253937,EX,CT,Switzerland,S,United Kingdom,50,"Spark, Kubernetes, SQL",PhD,15,Energy,2024-03-23,2024-06-03,678,7,DeepTech Ventures +AI00277,Data Scientist,240352,CHF,216317,EX,CT,Switzerland,M,Switzerland,50,"TensorFlow, Spark, Computer Vision",PhD,18,Automotive,2024-06-24,2024-08-02,886,6.8,Cognitive Computing +AI00278,Computer Vision Engineer,87353,CHF,78618,EN,FL,Switzerland,M,Switzerland,50,"Java, Git, AWS",Associate,0,Technology,2025-03-17,2025-04-01,2072,7.5,DataVision Ltd +AI00279,Research Scientist,201368,EUR,171163,EX,FL,Austria,M,Austria,100,"Git, PyTorch, NLP",Associate,10,Transportation,2024-02-16,2024-03-15,2032,6.4,Cognitive Computing +AI00280,AI Consultant,102371,USD,102371,MI,FT,Sweden,M,Sweden,50,"Scala, Java, Linux, AWS",Associate,3,Telecommunications,2024-12-29,2025-02-22,2442,6.5,Cloud AI Solutions +AI00281,Machine Learning Engineer,160729,USD,160729,MI,FT,Denmark,L,Denmark,50,"Python, TensorFlow, Kubernetes, Mathematics, MLOps",PhD,3,Government,2024-03-22,2024-04-12,660,7.8,Cognitive Computing +AI00282,Data Analyst,127341,USD,127341,SE,CT,Ireland,L,Finland,0,"Python, Linux, TensorFlow, Java",Associate,8,Manufacturing,2025-01-07,2025-01-28,1241,6.4,Cognitive Computing +AI00283,AI Product Manager,132125,EUR,112306,SE,FT,Netherlands,L,Netherlands,50,"Deep Learning, Computer Vision, Tableau",Associate,6,Manufacturing,2024-06-13,2024-08-11,1042,7,Advanced Robotics +AI00284,Data Scientist,106892,CAD,133615,MI,PT,Canada,L,Canada,100,"MLOps, Python, Computer Vision, AWS",PhD,2,Gaming,2025-01-18,2025-03-19,2323,5.5,Digital Transformation LLC +AI00285,Machine Learning Researcher,101740,EUR,86479,MI,CT,Germany,L,Germany,100,"Scala, Python, Tableau",Master,3,Finance,2024-08-22,2024-09-18,1429,8.8,DeepTech Ventures +AI00286,Machine Learning Researcher,48965,USD,48965,MI,PT,China,M,China,0,"Python, TensorFlow, Spark, GCP",Bachelor,2,Automotive,2024-11-01,2024-12-26,1541,5.9,Future Systems +AI00287,Autonomous Systems Engineer,53173,USD,53173,EN,FL,Sweden,S,Sweden,50,"TensorFlow, Kubernetes, Python, Data Visualization, GCP",Master,0,Telecommunications,2024-02-09,2024-04-20,1299,8.3,Machine Intelligence Group +AI00288,Computer Vision Engineer,201645,EUR,171398,EX,PT,Netherlands,S,Netherlands,100,"Scala, Kubernetes, Data Visualization",Associate,17,Real Estate,2024-12-11,2025-01-11,1871,9.2,DataVision Ltd +AI00289,Robotics Engineer,47718,USD,47718,MI,FT,China,L,China,100,"R, Kubernetes, AWS, SQL, TensorFlow",Master,3,Retail,2025-01-03,2025-02-09,649,6.2,Neural Networks Co +AI00290,AI Architect,358613,USD,358613,EX,FL,Norway,L,Norway,0,"AWS, Java, Statistics",PhD,16,Telecommunications,2024-08-06,2024-09-17,1555,9.6,Autonomous Tech +AI00291,AI Product Manager,96280,USD,96280,EN,FL,United States,L,United States,50,"Spark, MLOps, SQL, PyTorch, Computer Vision",Bachelor,0,Technology,2024-10-13,2024-12-15,2353,6.2,Digital Transformation LLC +AI00292,ML Ops Engineer,87032,USD,87032,SE,PT,South Korea,S,Netherlands,50,"PyTorch, Linux, Deep Learning",Master,7,Manufacturing,2024-11-13,2025-01-02,1397,5.5,Algorithmic Solutions +AI00293,AI Architect,112059,JPY,12326490,SE,FT,Japan,S,Japan,50,"Docker, Python, Kubernetes, GCP, TensorFlow",Bachelor,9,Education,2024-06-21,2024-08-23,1799,7.3,Machine Intelligence Group +AI00294,AI Specialist,115102,EUR,97837,SE,FT,Austria,L,Austria,100,"Python, Linux, Kubernetes, Hadoop",PhD,7,Automotive,2024-05-10,2024-07-19,2334,9.2,DeepTech Ventures +AI00295,AI Specialist,271779,USD,271779,EX,CT,Ireland,L,Ireland,50,"Computer Vision, Azure, Data Visualization, NLP",Master,11,Automotive,2025-02-06,2025-03-23,1247,9,Cloud AI Solutions +AI00296,AI Research Scientist,66364,CAD,82955,MI,PT,Canada,S,Colombia,50,"Python, SQL, NLP",Bachelor,3,Gaming,2024-08-18,2024-09-01,1891,6.6,AI Innovations +AI00297,Deep Learning Engineer,131466,USD,131466,MI,PT,Norway,L,Norway,50,"R, AWS, Hadoop, NLP, Spark",PhD,2,Automotive,2024-01-02,2024-01-25,1013,7.9,TechCorp Inc +AI00298,Head of AI,42235,USD,42235,EN,FT,South Korea,S,Ghana,100,"Python, Data Visualization, Kubernetes",PhD,1,Government,2024-04-19,2024-06-27,2078,6.4,DeepTech Ventures +AI00299,Deep Learning Engineer,55844,EUR,47467,EN,FL,Netherlands,M,Estonia,50,"Java, NLP, Python, Deep Learning, Computer Vision",PhD,1,Transportation,2024-05-04,2024-07-10,976,7.9,Quantum Computing Inc +AI00300,Machine Learning Researcher,75499,USD,75499,EN,FT,Sweden,L,Sweden,0,"GCP, Linux, Deep Learning, Java, Kubernetes",PhD,1,Education,2024-10-02,2024-10-27,2054,9.6,Future Systems +AI00301,AI Architect,84962,SGD,110451,EN,CT,Singapore,L,Israel,50,"GCP, Data Visualization, Azure",Associate,1,Finance,2024-05-15,2024-06-29,1804,6.2,TechCorp Inc +AI00302,Data Analyst,144336,CHF,129902,MI,CT,Switzerland,M,Switzerland,0,"Data Visualization, Java, Mathematics, AWS",Bachelor,3,Gaming,2025-02-06,2025-03-30,1336,7.8,Machine Intelligence Group +AI00303,AI Consultant,52300,USD,52300,SE,PT,China,S,China,100,"Docker, TensorFlow, GCP",Bachelor,8,Consulting,2024-03-10,2024-04-19,800,9.1,DataVision Ltd +AI00304,Data Engineer,157426,EUR,133812,EX,PT,Austria,S,Turkey,100,"Scala, Tableau, Java",PhD,13,Manufacturing,2025-04-07,2025-05-16,1741,6.2,Cloud AI Solutions +AI00305,Deep Learning Engineer,174692,USD,174692,EX,CT,South Korea,M,Portugal,100,"Linux, Python, TensorFlow",PhD,12,Automotive,2025-04-20,2025-06-27,731,7.9,Autonomous Tech +AI00306,NLP Engineer,142293,USD,142293,MI,PT,Norway,L,Sweden,50,"Git, Java, Deep Learning, Linux, Mathematics",Master,2,Energy,2025-04-05,2025-06-01,1398,7.1,Quantum Computing Inc +AI00307,AI Architect,109818,USD,109818,SE,FL,South Korea,S,South Korea,0,"GCP, Git, Statistics",PhD,9,Consulting,2024-01-04,2024-02-02,2344,5,Advanced Robotics +AI00308,AI Research Scientist,69642,USD,69642,EN,FT,Norway,M,Norway,0,"Java, SQL, Scala, PyTorch, NLP",Master,0,Automotive,2024-01-19,2024-03-31,583,7.9,AI Innovations +AI00309,Principal Data Scientist,70652,EUR,60054,MI,FL,Netherlands,S,Netherlands,50,"Computer Vision, Scala, Mathematics",Master,2,Media,2024-10-30,2024-12-30,1086,9.1,Advanced Robotics +AI00310,Data Analyst,242235,GBP,181676,EX,FL,United Kingdom,L,United Kingdom,100,"R, PyTorch, Docker",Master,12,Education,2024-12-18,2025-03-01,2038,6,Machine Intelligence Group +AI00311,AI Architect,211982,SGD,275577,EX,FT,Singapore,S,Singapore,50,"Hadoop, AWS, Docker",PhD,19,Manufacturing,2024-01-12,2024-02-18,1352,6.8,Machine Intelligence Group +AI00312,Principal Data Scientist,88077,EUR,74865,EN,FL,Germany,L,Germany,100,"Python, GCP, TensorFlow, Mathematics, PyTorch",Bachelor,1,Transportation,2024-02-20,2024-04-18,986,8.2,Machine Intelligence Group +AI00313,Robotics Engineer,107261,EUR,91172,MI,CT,Germany,L,Germany,50,"Hadoop, Tableau, Java, Git",Associate,3,Manufacturing,2024-10-19,2024-11-04,1617,9.7,AI Innovations +AI00314,Computer Vision Engineer,284132,USD,284132,EX,FT,United States,M,United States,0,"Deep Learning, Docker, Hadoop, Data Visualization",Master,10,Government,2025-04-24,2025-07-06,1832,5.1,Autonomous Tech +AI00315,AI Software Engineer,105482,USD,105482,SE,CT,South Korea,M,South Korea,100,"SQL, Git, AWS",PhD,5,Consulting,2025-02-13,2025-04-25,1845,5.9,Cognitive Computing +AI00316,AI Architect,161728,GBP,121296,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, PyTorch",PhD,15,Finance,2025-03-03,2025-04-19,1932,8.6,DataVision Ltd +AI00317,Data Engineer,131352,USD,131352,SE,PT,Norway,S,Sweden,0,"Scala, MLOps, GCP, Java",Bachelor,9,Retail,2024-11-02,2024-12-13,1802,5.8,Machine Intelligence Group +AI00318,Data Analyst,161727,EUR,137468,SE,FT,Austria,L,Finland,100,"Docker, GCP, SQL",PhD,6,Technology,2025-01-26,2025-04-04,1940,5.9,Cognitive Computing +AI00319,Data Analyst,151527,USD,151527,SE,FL,United States,L,Romania,0,"Java, SQL, Kubernetes, Git",PhD,7,Retail,2024-07-18,2024-09-02,845,7.1,Machine Intelligence Group +AI00320,Machine Learning Researcher,112476,USD,112476,SE,FT,Israel,L,Israel,50,"Hadoop, Git, Statistics",Master,6,Consulting,2024-04-20,2024-05-10,2413,8.7,TechCorp Inc +AI00321,ML Ops Engineer,72913,CAD,91141,MI,FT,Canada,M,Canada,0,"R, SQL, Mathematics",PhD,3,Telecommunications,2025-04-01,2025-05-31,941,7,Cognitive Computing +AI00322,Data Analyst,68734,CAD,85918,EN,FT,Canada,L,Malaysia,100,"Computer Vision, Python, TensorFlow, Docker",PhD,1,Finance,2024-08-28,2024-10-24,805,8.5,Algorithmic Solutions +AI00323,NLP Engineer,179564,EUR,152629,EX,FL,Netherlands,S,Netherlands,50,"Python, AWS, Git",Bachelor,11,Government,2024-01-24,2024-03-17,654,9.1,Quantum Computing Inc +AI00324,Data Scientist,71265,GBP,53449,EN,PT,United Kingdom,S,United Kingdom,0,"PyTorch, TensorFlow, Azure, Computer Vision, Java",Bachelor,1,Automotive,2024-03-27,2024-05-12,2172,9.5,DeepTech Ventures +AI00325,Deep Learning Engineer,143064,USD,143064,SE,FL,South Korea,L,Denmark,100,"Scala, Python, TensorFlow",Master,8,Telecommunications,2024-02-26,2024-04-13,1887,7.2,DataVision Ltd +AI00326,Deep Learning Engineer,196042,EUR,166636,EX,CT,Austria,L,Italy,0,"Kubernetes, PyTorch, Tableau, Docker, Computer Vision",PhD,14,Consulting,2025-02-14,2025-03-20,911,7.3,Advanced Robotics +AI00327,Data Engineer,101946,USD,101946,SE,FL,Ireland,S,Ireland,0,"SQL, PyTorch, Data Visualization, Computer Vision",Bachelor,7,Finance,2025-02-14,2025-04-20,1521,7.1,Digital Transformation LLC +AI00328,Autonomous Systems Engineer,89020,GBP,66765,MI,FL,United Kingdom,S,Brazil,50,"Kubernetes, R, Git, AWS",PhD,4,Media,2024-09-06,2024-10-27,1497,9.2,Algorithmic Solutions +AI00329,Autonomous Systems Engineer,134011,JPY,14741210,SE,PT,Japan,S,Israel,100,"Deep Learning, Statistics, Spark",PhD,9,Energy,2024-08-10,2024-09-15,2405,8.8,TechCorp Inc +AI00330,Data Analyst,97657,SGD,126954,MI,CT,Singapore,M,Singapore,100,"Scala, Git, MLOps",Master,2,Gaming,2024-08-28,2024-09-15,2240,8.9,Predictive Systems +AI00331,Deep Learning Engineer,153990,USD,153990,EX,PT,South Korea,M,Luxembourg,50,"Scala, Git, Deep Learning, SQL, Kubernetes",Bachelor,14,Consulting,2024-06-29,2024-08-12,1020,5.7,Algorithmic Solutions +AI00332,Robotics Engineer,124696,EUR,105992,SE,FT,Netherlands,S,Argentina,100,"PyTorch, Python, Computer Vision",PhD,6,Automotive,2024-05-17,2024-07-09,1117,5.5,TechCorp Inc +AI00333,Robotics Engineer,94884,USD,94884,MI,PT,Ireland,S,Ireland,0,"Linux, Hadoop, GCP",Bachelor,2,Retail,2024-11-06,2024-12-19,961,9.2,Cognitive Computing +AI00334,AI Architect,101192,CHF,91073,EN,FT,Switzerland,M,Switzerland,50,"R, Scala, Kubernetes, Git",PhD,0,Transportation,2024-12-28,2025-01-28,1793,5.8,DeepTech Ventures +AI00335,AI Product Manager,106624,USD,106624,SE,FT,Ireland,M,Ireland,100,"Git, Statistics, Azure",Associate,6,Telecommunications,2025-02-02,2025-02-25,2175,5.2,Cognitive Computing +AI00336,Data Scientist,187401,GBP,140551,EX,FT,United Kingdom,M,Germany,100,"TensorFlow, Docker, Spark, Python",Bachelor,12,Energy,2024-10-24,2024-11-11,1400,9.5,TechCorp Inc +AI00337,Data Analyst,165694,USD,165694,EX,FL,United States,M,United States,100,"Python, Kubernetes, MLOps",Associate,15,Retail,2024-01-04,2024-03-15,2434,8.8,DataVision Ltd +AI00338,Machine Learning Engineer,122206,USD,122206,SE,FL,United States,M,United States,50,"Spark, AWS, Linux, SQL, PyTorch",Bachelor,6,Healthcare,2024-01-31,2024-03-06,2282,9.2,Algorithmic Solutions +AI00339,Data Engineer,91226,SGD,118594,MI,PT,Singapore,L,India,0,"Python, TensorFlow, PyTorch, SQL",Bachelor,2,Transportation,2024-12-06,2025-01-16,519,7.7,Autonomous Tech +AI00340,AI Product Manager,110449,CHF,99404,MI,FL,Switzerland,S,Switzerland,100,"Mathematics, Linux, NLP",Bachelor,3,Energy,2025-02-01,2025-02-19,1970,5.9,Algorithmic Solutions +AI00341,AI Architect,275705,EUR,234349,EX,FT,Netherlands,L,Netherlands,100,"MLOps, SQL, Kubernetes, Spark, Java",Bachelor,16,Finance,2024-04-25,2024-05-29,2299,5.4,Future Systems +AI00342,ML Ops Engineer,161670,USD,161670,EX,PT,Finland,M,Brazil,0,"MLOps, Python, TensorFlow, GCP",Associate,11,Technology,2024-08-13,2024-09-18,1061,5.9,Machine Intelligence Group +AI00343,Computer Vision Engineer,95328,GBP,71496,MI,PT,United Kingdom,S,United Kingdom,50,"MLOps, Spark, Git, Deep Learning",PhD,3,Technology,2025-03-25,2025-04-26,734,8.5,Smart Analytics +AI00344,AI Consultant,68548,EUR,58266,EN,PT,Germany,M,Germany,0,"Hadoop, Spark, Statistics, Tableau",Associate,1,Transportation,2025-02-24,2025-03-26,1762,7.8,Digital Transformation LLC +AI00345,AI Consultant,378502,USD,378502,EX,FT,Denmark,L,Denmark,0,"SQL, Mathematics, Scala, Hadoop",Bachelor,12,Consulting,2024-09-29,2024-12-01,2234,8.4,Future Systems +AI00346,NLP Engineer,76682,USD,76682,SE,CT,South Korea,S,South Korea,0,"PyTorch, Kubernetes, Azure, GCP",Master,7,Gaming,2024-09-25,2024-11-12,643,10,Machine Intelligence Group +AI00347,Deep Learning Engineer,108478,USD,108478,MI,CT,Sweden,L,Sweden,0,"Hadoop, Java, Docker, Deep Learning",Master,2,Transportation,2024-04-24,2024-05-10,1436,9.4,Cognitive Computing +AI00348,Research Scientist,114526,JPY,12597860,MI,FL,Japan,M,Belgium,0,"Python, TensorFlow, SQL, NLP",Associate,3,Real Estate,2024-02-16,2024-03-05,1095,5.8,Future Systems +AI00349,AI Specialist,75609,USD,75609,EN,PT,Norway,S,Norway,0,"AWS, Python, Git, Statistics",PhD,0,Government,2024-09-19,2024-11-30,2109,9.9,Algorithmic Solutions +AI00350,Data Analyst,214389,USD,214389,SE,FL,Denmark,L,Denmark,100,"Java, Kubernetes, Python, SQL",Associate,6,Retail,2025-04-29,2025-06-13,2348,8.8,Smart Analytics +AI00351,NLP Engineer,104396,USD,104396,SE,CT,Finland,S,Finland,100,"SQL, Azure, Data Visualization, NLP",Master,7,Telecommunications,2024-08-13,2024-10-15,1398,5.3,Quantum Computing Inc +AI00352,Principal Data Scientist,53469,EUR,45449,EN,PT,France,M,United Kingdom,50,"Docker, Statistics, Data Visualization",PhD,0,Government,2024-01-10,2024-02-20,1249,6,Smart Analytics +AI00353,Head of AI,327929,USD,327929,EX,FL,Denmark,L,Denmark,0,"TensorFlow, Python, Data Visualization, NLP, Tableau",PhD,14,Transportation,2024-02-19,2024-04-14,1000,6.5,Smart Analytics +AI00354,Data Scientist,87984,JPY,9678240,MI,PT,Japan,S,Japan,100,"Computer Vision, Git, Tableau, Data Visualization",Bachelor,2,Consulting,2024-01-08,2024-02-19,560,7.4,Algorithmic Solutions +AI00355,AI Architect,127823,JPY,14060530,SE,CT,Japan,S,Japan,0,"Linux, MLOps, Tableau",Associate,8,Automotive,2025-04-17,2025-05-24,1762,7.3,Future Systems +AI00356,Machine Learning Researcher,93295,AUD,125948,MI,FL,Australia,M,Australia,0,"Spark, Mathematics, Linux",Associate,4,Education,2024-02-10,2024-04-04,582,5.1,Algorithmic Solutions +AI00357,NLP Engineer,25560,USD,25560,MI,PT,India,M,India,50,"Kubernetes, Linux, Tableau, Mathematics",Master,2,Transportation,2024-02-29,2024-04-02,1775,7.5,Cognitive Computing +AI00358,Deep Learning Engineer,110777,GBP,83083,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, Python, GCP",PhD,3,Transportation,2024-07-10,2024-08-31,1446,8.5,Quantum Computing Inc +AI00359,AI Specialist,253223,EUR,215240,EX,FL,Germany,M,Germany,0,"Scala, Kubernetes, SQL, Hadoop, Docker",Bachelor,17,Retail,2024-07-24,2024-08-27,1970,5,Algorithmic Solutions +AI00360,ML Ops Engineer,234867,EUR,199637,EX,PT,Netherlands,M,Israel,0,"Spark, Statistics, MLOps, R",PhD,10,Automotive,2024-11-18,2024-12-27,826,5.1,Digital Transformation LLC +AI00361,AI Consultant,49385,USD,49385,EN,FT,Finland,S,Finland,50,"NLP, Statistics, Hadoop",Master,0,Media,2025-03-28,2025-04-13,1111,6.6,Advanced Robotics +AI00362,Data Scientist,59557,USD,59557,SE,CT,China,L,Denmark,100,"PyTorch, GCP, NLP, Spark",Bachelor,8,Telecommunications,2024-03-26,2024-06-06,977,6.3,TechCorp Inc +AI00363,AI Product Manager,95864,EUR,81484,SE,PT,France,S,France,0,"SQL, Hadoop, Tableau, Data Visualization",Master,6,Energy,2024-01-22,2024-03-27,1764,7.6,Predictive Systems +AI00364,AI Product Manager,217693,USD,217693,EX,PT,Israel,L,Israel,0,"GCP, MLOps, Scala, Kubernetes, Docker",Associate,18,Transportation,2024-04-15,2024-05-19,1099,9.7,Digital Transformation LLC +AI00365,ML Ops Engineer,108994,EUR,92645,MI,FL,France,L,France,100,"Kubernetes, Mathematics, Scala",Associate,2,Energy,2024-07-24,2024-08-31,1864,9.9,AI Innovations +AI00366,AI Software Engineer,75633,USD,75633,MI,FT,South Korea,S,Ghana,100,"Scala, Linux, NLP, R, Computer Vision",Associate,4,Gaming,2024-06-07,2024-06-27,1965,8.1,Advanced Robotics +AI00367,AI Research Scientist,62810,EUR,53389,EN,FL,Germany,S,Germany,100,"Deep Learning, Python, Tableau, Computer Vision, Statistics",Associate,0,Automotive,2025-02-13,2025-04-05,1004,9.7,Predictive Systems +AI00368,Data Engineer,151628,EUR,128884,EX,FT,France,S,France,100,"Python, TensorFlow, Java",Bachelor,15,Real Estate,2024-08-02,2024-09-30,539,8.3,AI Innovations +AI00369,AI Research Scientist,125355,SGD,162962,SE,FL,Singapore,M,Singapore,100,"Docker, NLP, AWS",Master,9,Transportation,2025-02-27,2025-05-07,2194,9.7,Quantum Computing Inc +AI00370,Principal Data Scientist,136102,USD,136102,SE,PT,Denmark,M,Denmark,100,"Linux, PyTorch, Tableau, Mathematics",PhD,7,Telecommunications,2024-03-08,2024-04-08,1973,5.1,Machine Intelligence Group +AI00371,Deep Learning Engineer,56934,EUR,48394,EN,PT,France,L,France,0,"Git, SQL, NLP, PyTorch",PhD,0,Automotive,2024-02-07,2024-03-26,1672,6.9,Advanced Robotics +AI00372,ML Ops Engineer,67190,EUR,57112,MI,FL,France,S,Italy,50,"Scala, Tableau, Python, Docker, Hadoop",Master,4,Gaming,2024-02-18,2024-04-06,1470,8.3,AI Innovations +AI00373,AI Software Engineer,125164,EUR,106389,SE,FL,Austria,L,Austria,50,"Azure, Deep Learning, MLOps, Linux",PhD,9,Transportation,2024-06-26,2024-08-24,2025,5.1,TechCorp Inc +AI00374,NLP Engineer,85407,SGD,111029,EN,PT,Singapore,L,Singapore,50,"Statistics, GCP, AWS, SQL",Master,1,Media,2024-07-08,2024-09-17,646,8.2,Autonomous Tech +AI00375,ML Ops Engineer,112057,JPY,12326270,SE,FL,Japan,S,Japan,0,"Python, TensorFlow, PyTorch, SQL, Deep Learning",Master,7,Manufacturing,2025-03-13,2025-04-03,789,8.5,Neural Networks Co +AI00376,ML Ops Engineer,95078,USD,95078,MI,CT,Denmark,M,Denmark,0,"SQL, MLOps, Scala",Bachelor,3,Automotive,2025-02-26,2025-04-21,1839,5.7,Quantum Computing Inc +AI00377,AI Product Manager,198651,USD,198651,EX,CT,Norway,M,Norway,100,"SQL, Spark, TensorFlow, Deep Learning, Kubernetes",Bachelor,18,Retail,2024-05-08,2024-05-27,2463,5.7,DeepTech Ventures +AI00378,AI Software Engineer,220998,JPY,24309780,EX,CT,Japan,S,India,50,"SQL, Linux, Tableau, Azure, Scala",Bachelor,12,Education,2024-05-04,2024-06-16,731,7.3,Cloud AI Solutions +AI00379,NLP Engineer,74126,USD,74126,EX,FT,India,S,India,100,"Scala, PyTorch, Docker, Deep Learning, SQL",PhD,12,Government,2024-09-22,2024-10-29,1926,7.5,Predictive Systems +AI00380,Machine Learning Engineer,75172,EUR,63896,MI,CT,Austria,S,Austria,100,"SQL, Kubernetes, Docker, NLP",Associate,4,Media,2024-09-09,2024-11-15,2261,8.5,Cognitive Computing +AI00381,Deep Learning Engineer,60975,EUR,51829,EN,FT,Austria,L,Austria,100,"SQL, Hadoop, Tableau, Kubernetes",Master,1,Transportation,2024-11-21,2025-01-29,620,9.6,Cloud AI Solutions +AI00382,Principal Data Scientist,89175,EUR,75799,MI,FT,Germany,L,Singapore,0,"Computer Vision, AWS, GCP, Deep Learning, Spark",PhD,2,Manufacturing,2024-01-11,2024-02-21,2215,8.9,Digital Transformation LLC +AI00383,Computer Vision Engineer,149285,EUR,126892,SE,FL,Netherlands,L,Netherlands,50,"Python, Mathematics, Kubernetes",PhD,5,Education,2025-01-06,2025-03-02,1359,5.4,Predictive Systems +AI00384,AI Product Manager,192204,EUR,163373,EX,FT,Germany,M,Germany,0,"Mathematics, Linux, SQL",Bachelor,13,Media,2025-02-01,2025-03-10,1161,6.7,Future Systems +AI00385,NLP Engineer,94197,CHF,84777,MI,PT,Switzerland,S,Norway,100,"Spark, TensorFlow, Deep Learning, GCP",Associate,4,Finance,2024-09-28,2024-10-28,1172,5.3,Future Systems +AI00386,Autonomous Systems Engineer,90408,EUR,76847,EN,FL,Germany,L,Czech Republic,100,"Linux, SQL, Git",PhD,1,Technology,2024-01-25,2024-03-10,892,7.1,Autonomous Tech +AI00387,ML Ops Engineer,72940,USD,72940,MI,FT,Ireland,S,Czech Republic,0,"GCP, Hadoop, Java",PhD,3,Technology,2024-03-24,2024-05-07,1913,8.1,DeepTech Ventures +AI00388,Machine Learning Engineer,140696,JPY,15476560,SE,PT,Japan,S,Japan,0,"AWS, Java, GCP",Master,9,Real Estate,2024-04-03,2024-04-25,1774,5.6,Neural Networks Co +AI00389,Robotics Engineer,210902,CHF,189812,EX,FT,Switzerland,S,Switzerland,0,"Java, NLP, TensorFlow, PyTorch, Git",Bachelor,12,Real Estate,2024-09-25,2024-11-28,982,9.8,Cognitive Computing +AI00390,Computer Vision Engineer,78559,SGD,102127,EN,FL,Singapore,M,Singapore,100,"Python, PyTorch, Computer Vision",Bachelor,0,Automotive,2024-12-03,2025-01-13,586,5,AI Innovations +AI00391,AI Consultant,32923,USD,32923,MI,FT,India,M,India,50,"Kubernetes, MLOps, PyTorch, Linux, AWS",Master,4,Gaming,2024-01-20,2024-03-26,1442,9.2,AI Innovations +AI00392,Research Scientist,112363,JPY,12359930,SE,FL,Japan,S,Ukraine,0,"Python, TensorFlow, Azure, NLP, Data Visualization",Bachelor,9,Finance,2024-04-26,2024-05-12,843,9.4,Autonomous Tech +AI00393,AI Consultant,188028,USD,188028,EX,CT,United States,L,United States,50,"Scala, SQL, NLP",Associate,11,Retail,2025-04-25,2025-06-22,852,8.9,Quantum Computing Inc +AI00394,AI Product Manager,165794,USD,165794,EX,FT,Norway,S,United States,100,"Python, Azure, R, Kubernetes",Bachelor,16,Gaming,2025-01-26,2025-03-16,903,8.6,Advanced Robotics +AI00395,ML Ops Engineer,109778,EUR,93311,MI,FL,Netherlands,L,Netherlands,50,"Scala, GCP, Mathematics",PhD,3,Media,2024-02-11,2024-02-28,2366,8.9,Smart Analytics +AI00396,Head of AI,162918,USD,162918,EX,FL,Ireland,L,Ireland,0,"Hadoop, AWS, Scala",Bachelor,17,Consulting,2024-10-16,2024-12-12,721,5.5,TechCorp Inc +AI00397,Autonomous Systems Engineer,219603,USD,219603,EX,PT,United States,M,United States,0,"Python, Mathematics, Data Visualization",PhD,12,Transportation,2024-05-06,2024-06-16,894,8.5,DeepTech Ventures +AI00398,Head of AI,304991,CHF,274492,EX,FT,Switzerland,L,Switzerland,100,"Azure, PyTorch, Kubernetes, NLP, Java",Associate,17,Manufacturing,2024-03-08,2024-04-15,2314,6.5,Algorithmic Solutions +AI00399,AI Research Scientist,99431,AUD,134232,SE,FL,Australia,S,Estonia,50,"Kubernetes, TensorFlow, SQL",Associate,5,Retail,2024-04-09,2024-05-19,1227,6.7,DeepTech Ventures +AI00400,Data Scientist,92131,USD,92131,MI,CT,Sweden,L,Sweden,0,"SQL, Git, Statistics",Bachelor,3,Retail,2024-04-29,2024-07-01,1590,6.2,Digital Transformation LLC +AI00401,Research Scientist,111236,JPY,12235960,MI,FL,Japan,M,Japan,100,"Python, Spark, Linux, TensorFlow, Java",Master,3,Media,2025-03-05,2025-04-08,1407,6.1,Cloud AI Solutions +AI00402,AI Research Scientist,263705,USD,263705,EX,CT,Norway,M,Norway,0,"SQL, Scala, Linux",Bachelor,10,Technology,2024-12-16,2025-01-24,870,6.3,Cognitive Computing +AI00403,Head of AI,37401,USD,37401,MI,CT,China,S,Colombia,0,"Linux, Deep Learning, Statistics",Bachelor,2,Real Estate,2025-03-27,2025-06-04,728,8.3,Smart Analytics +AI00404,ML Ops Engineer,122481,GBP,91861,MI,FT,United Kingdom,L,Mexico,50,"MLOps, Tableau, Hadoop, AWS",Bachelor,3,Healthcare,2025-02-03,2025-03-11,1575,8,DeepTech Ventures +AI00405,Deep Learning Engineer,29050,USD,29050,EN,FL,India,L,India,50,"Spark, Azure, TensorFlow, Mathematics",Master,0,Real Estate,2024-05-24,2024-06-10,1106,6.7,Neural Networks Co +AI00406,Principal Data Scientist,142280,GBP,106710,SE,FT,United Kingdom,L,United Kingdom,100,"NLP, SQL, GCP, Kubernetes",Bachelor,9,Transportation,2024-08-30,2024-10-04,1311,9.9,TechCorp Inc +AI00407,AI Consultant,75989,USD,75989,EN,PT,United States,L,United States,0,"SQL, Java, TensorFlow, MLOps",PhD,0,Healthcare,2024-09-25,2024-11-19,2338,6.3,TechCorp Inc +AI00408,Computer Vision Engineer,103477,SGD,134520,SE,PT,Singapore,S,Singapore,100,"Scala, Data Visualization, TensorFlow, Azure, Statistics",Associate,6,Gaming,2024-02-11,2024-03-28,2343,8.9,Advanced Robotics +AI00409,ML Ops Engineer,111121,USD,111121,MI,FT,United States,S,United States,100,"Docker, Scala, Git, R",Associate,3,Healthcare,2024-03-05,2024-03-22,1349,7.6,Algorithmic Solutions +AI00410,Data Engineer,357359,CHF,321623,EX,CT,Switzerland,M,Switzerland,100,"PyTorch, MLOps, R, Scala, Tableau",PhD,19,Consulting,2024-06-28,2024-08-06,1855,7.3,Machine Intelligence Group +AI00411,ML Ops Engineer,107663,CAD,134579,MI,FT,Canada,L,Canada,100,"Docker, SQL, AWS, Computer Vision, Deep Learning",Bachelor,2,Education,2024-08-06,2024-09-10,683,5.3,Algorithmic Solutions +AI00412,Data Scientist,83352,GBP,62514,MI,PT,United Kingdom,S,United Kingdom,0,"PyTorch, SQL, GCP, AWS, TensorFlow",Bachelor,2,Education,2024-10-12,2024-11-07,1599,6.6,Future Systems +AI00413,Deep Learning Engineer,55431,GBP,41573,EN,CT,United Kingdom,S,United Kingdom,100,"Data Visualization, Git, Computer Vision, Kubernetes",Master,0,Retail,2024-03-08,2024-04-26,721,9.9,Cognitive Computing +AI00414,Data Scientist,149644,EUR,127197,SE,CT,Germany,M,Germany,100,"Git, Kubernetes, Linux",Associate,9,Education,2024-03-19,2024-04-18,825,7.7,Algorithmic Solutions +AI00415,AI Software Engineer,94453,USD,94453,MI,FT,Ireland,S,Ireland,50,"Computer Vision, Spark, SQL, GCP",PhD,2,Gaming,2025-04-05,2025-06-01,1352,5.2,Machine Intelligence Group +AI00416,Robotics Engineer,40773,USD,40773,MI,FT,China,M,China,0,"Python, Kubernetes, Docker, GCP",Bachelor,2,Finance,2024-05-26,2024-06-14,2359,6,Neural Networks Co +AI00417,AI Consultant,94832,CAD,118540,MI,CT,Canada,L,Australia,50,"GCP, TensorFlow, Linux",PhD,2,Education,2025-03-21,2025-05-18,1023,8.7,Advanced Robotics +AI00418,AI Specialist,66884,EUR,56851,EN,CT,Austria,L,Austria,100,"TensorFlow, AWS, Python, Mathematics, Deep Learning",Master,1,Transportation,2024-10-28,2024-12-18,1927,7.9,Quantum Computing Inc +AI00419,ML Ops Engineer,222209,USD,222209,SE,FL,Norway,L,Norway,50,"TensorFlow, SQL, Deep Learning",PhD,7,Finance,2024-03-15,2024-05-07,1846,6.3,Autonomous Tech +AI00420,Robotics Engineer,181591,JPY,19975010,EX,FL,Japan,S,Romania,50,"Python, TensorFlow, Java, Linux",Associate,15,Real Estate,2024-06-06,2024-07-19,2025,7.4,Cognitive Computing +AI00421,AI Research Scientist,70146,USD,70146,EN,PT,Sweden,M,Sweden,0,"Python, Azure, Deep Learning, TensorFlow, Data Visualization",Bachelor,1,Healthcare,2025-03-29,2025-05-17,1790,7,Quantum Computing Inc +AI00422,AI Software Engineer,77528,USD,77528,MI,CT,Ireland,M,Ireland,100,"Python, Spark, TensorFlow, Statistics, Java",Bachelor,2,Gaming,2024-01-12,2024-03-05,950,6.7,Future Systems +AI00423,AI Software Engineer,133696,CAD,167120,EX,FL,Canada,M,Canada,50,"AWS, Deep Learning, R, Computer Vision",Master,15,Government,2024-09-21,2024-11-28,2050,6.5,Neural Networks Co +AI00424,Deep Learning Engineer,266317,USD,266317,EX,FL,Norway,M,Norway,0,"R, GCP, MLOps, Azure, Python",Associate,19,Technology,2024-05-16,2024-07-07,970,5.3,Predictive Systems +AI00425,Head of AI,171903,USD,171903,EX,CT,Israel,L,India,100,"Kubernetes, Spark, Docker, Scala, Hadoop",Master,19,Healthcare,2024-07-27,2024-09-03,2156,9.3,Advanced Robotics +AI00426,Research Scientist,134807,CAD,168509,EX,FL,Canada,M,Denmark,0,"GCP, Kubernetes, SQL, Azure, Computer Vision",Bachelor,17,Manufacturing,2024-08-22,2024-09-05,1624,8.8,Digital Transformation LLC +AI00427,AI Product Manager,123091,EUR,104627,SE,FL,France,S,France,0,"Scala, TensorFlow, Spark, SQL",Bachelor,6,Consulting,2025-02-13,2025-03-31,2071,6,Digital Transformation LLC +AI00428,Data Engineer,55885,USD,55885,SE,FT,China,S,China,50,"Python, R, MLOps, Kubernetes",Bachelor,9,Education,2024-08-30,2024-09-19,875,8,Neural Networks Co +AI00429,Robotics Engineer,190416,USD,190416,EX,PT,Israel,S,Israel,100,"Linux, Hadoop, Kubernetes, Computer Vision, Deep Learning",Master,11,Finance,2024-10-11,2024-11-20,1500,9.8,Quantum Computing Inc +AI00430,Deep Learning Engineer,155137,USD,155137,SE,FL,Norway,S,Argentina,100,"Git, PyTorch, TensorFlow, SQL, Python",Master,6,Real Estate,2025-02-20,2025-03-22,2010,6.3,Predictive Systems +AI00431,Deep Learning Engineer,233502,SGD,303553,EX,FL,Singapore,L,Singapore,0,"Azure, Hadoop, R",Bachelor,14,Gaming,2025-02-13,2025-02-27,1261,9.1,Neural Networks Co +AI00432,Autonomous Systems Engineer,106241,USD,106241,SE,FT,South Korea,L,South Korea,100,"SQL, NLP, Python, Java",Associate,7,Consulting,2024-04-19,2024-06-12,1827,8.3,Advanced Robotics +AI00433,Principal Data Scientist,170331,JPY,18736410,EX,PT,Japan,L,China,100,"Kubernetes, Python, Computer Vision, Deep Learning",Master,17,Transportation,2025-01-11,2025-02-01,602,5.6,Autonomous Tech +AI00434,Machine Learning Researcher,190752,USD,190752,SE,PT,Denmark,M,Denmark,100,"TensorFlow, Spark, Deep Learning",Master,9,Gaming,2025-01-05,2025-02-01,1336,7.6,DeepTech Ventures +AI00435,Machine Learning Engineer,57858,JPY,6364380,EN,FL,Japan,S,Japan,0,"SQL, Hadoop, AWS, Mathematics",Bachelor,0,Consulting,2024-10-15,2024-11-10,1143,8.3,DataVision Ltd +AI00436,AI Consultant,60290,EUR,51247,EN,FT,Germany,M,Germany,50,"Computer Vision, MLOps, R",Associate,0,Real Estate,2024-09-01,2024-09-22,1266,9.6,Autonomous Tech +AI00437,Machine Learning Researcher,78662,USD,78662,MI,CT,South Korea,L,Norway,0,"Spark, Computer Vision, Mathematics",PhD,2,Technology,2024-02-09,2024-04-12,1998,9.9,Cloud AI Solutions +AI00438,Deep Learning Engineer,68057,USD,68057,EN,CT,Denmark,S,Denmark,0,"R, MLOps, AWS, Python",Master,1,Real Estate,2024-03-15,2024-05-12,2060,6.3,Cognitive Computing +AI00439,Data Engineer,152822,USD,152822,SE,CT,United States,M,India,50,"Git, Mathematics, Docker",Master,5,Healthcare,2025-03-29,2025-04-14,1541,5.8,Advanced Robotics +AI00440,Head of AI,168351,USD,168351,SE,FL,Sweden,L,Sweden,100,"Docker, Spark, Data Visualization, GCP",Bachelor,7,Energy,2025-03-03,2025-03-17,1746,9.3,TechCorp Inc +AI00441,Machine Learning Researcher,280392,USD,280392,EX,FT,United States,M,United States,0,"Docker, Hadoop, Azure, Python, Scala",Associate,15,Government,2024-10-17,2024-12-06,1427,5.8,Neural Networks Co +AI00442,AI Specialist,165716,USD,165716,EX,FL,Finland,L,Norway,50,"Data Visualization, R, Java",PhD,18,Media,2025-04-18,2025-05-22,2251,6.2,Quantum Computing Inc +AI00443,Computer Vision Engineer,187794,USD,187794,EX,FT,Finland,M,Finland,0,"Git, AWS, SQL, Kubernetes",PhD,11,Energy,2024-09-17,2024-10-02,1284,9,Quantum Computing Inc +AI00444,NLP Engineer,245697,EUR,208842,EX,FT,Germany,L,Germany,0,"GCP, Python, Mathematics",PhD,10,Healthcare,2024-08-22,2024-09-07,2112,9,Cognitive Computing +AI00445,Data Analyst,79411,CAD,99264,MI,CT,Canada,S,Canada,0,"SQL, Linux, Git, PyTorch, NLP",Master,3,Retail,2025-01-16,2025-02-27,2121,7.8,DeepTech Ventures +AI00446,AI Software Engineer,117847,USD,117847,SE,FT,South Korea,L,South Korea,100,"Scala, Python, Hadoop, Docker",Associate,7,Finance,2024-12-03,2024-12-17,1511,5.3,Cloud AI Solutions +AI00447,Principal Data Scientist,112962,GBP,84722,SE,FT,United Kingdom,M,Canada,100,"SQL, Python, Kubernetes, TensorFlow, Docker",Associate,9,Media,2024-06-04,2024-06-29,905,6.9,Machine Intelligence Group +AI00448,AI Product Manager,166397,AUD,224636,SE,FT,Australia,L,Australia,100,"Git, NLP, GCP, TensorFlow, Python",Master,7,Real Estate,2024-11-10,2024-12-01,2239,5,DeepTech Ventures +AI00449,Machine Learning Engineer,135988,USD,135988,SE,PT,Denmark,M,Israel,100,"Azure, Scala, GCP, MLOps",Bachelor,5,Media,2024-01-09,2024-03-08,1645,9.9,Neural Networks Co +AI00450,AI Specialist,30929,USD,30929,MI,FT,India,M,India,100,"Git, Azure, Kubernetes, R, SQL",PhD,2,Consulting,2024-04-14,2024-05-07,1963,9.6,DataVision Ltd +AI00451,Machine Learning Engineer,112165,EUR,95340,SE,FL,Germany,M,Germany,50,"Azure, AWS, Spark",Master,5,Technology,2024-02-11,2024-03-05,2021,8.9,Smart Analytics +AI00452,Data Scientist,100758,EUR,85644,MI,FL,Germany,M,Germany,100,"Python, Scala, NLP, Spark",Associate,4,Telecommunications,2024-04-21,2024-05-24,1162,9.1,Predictive Systems +AI00453,Principal Data Scientist,83754,USD,83754,EN,PT,Norway,L,United Kingdom,100,"Mathematics, Computer Vision, Git",Master,0,Finance,2025-01-15,2025-02-06,2164,7.8,Cloud AI Solutions +AI00454,Head of AI,109895,CHF,98906,MI,PT,Switzerland,S,Switzerland,100,"Tableau, Scala, Python",Associate,4,Consulting,2024-03-08,2024-04-25,2487,8.9,AI Innovations +AI00455,Machine Learning Engineer,160760,EUR,136646,EX,FT,Netherlands,M,Netherlands,50,"NLP, Linux, TensorFlow, Data Visualization",Bachelor,11,Energy,2024-02-23,2024-04-19,1258,7.1,Algorithmic Solutions +AI00456,Machine Learning Engineer,167415,AUD,226010,SE,PT,Australia,L,Australia,100,"Linux, Python, TensorFlow",Bachelor,5,Energy,2024-11-15,2024-12-04,2488,6.7,DataVision Ltd +AI00457,Data Scientist,58948,AUD,79580,EN,CT,Australia,L,Australia,100,"Azure, NLP, PyTorch",Master,1,Healthcare,2024-07-13,2024-09-09,515,7.4,Cloud AI Solutions +AI00458,ML Ops Engineer,73406,USD,73406,MI,CT,South Korea,L,South Korea,0,"Mathematics, Java, R",Bachelor,3,Retail,2024-12-28,2025-01-15,677,6,DeepTech Ventures +AI00459,AI Software Engineer,153534,EUR,130504,EX,FT,Austria,L,Austria,100,"MLOps, Linux, Docker, PyTorch",Associate,19,Gaming,2024-06-04,2024-07-16,1625,7.5,Predictive Systems +AI00460,Data Scientist,81787,JPY,8996570,MI,PT,Japan,M,Japan,50,"Java, Spark, AWS, Linux, MLOps",PhD,4,Manufacturing,2025-03-08,2025-05-11,577,5.9,Predictive Systems +AI00461,Computer Vision Engineer,121967,USD,121967,MI,PT,Ireland,L,Ireland,0,"AWS, TensorFlow, Statistics, Mathematics",Master,4,Finance,2024-06-30,2024-08-19,914,6.5,Algorithmic Solutions +AI00462,Data Analyst,181438,JPY,19958180,EX,CT,Japan,S,Japan,50,"Java, Spark, TensorFlow",Associate,14,Real Estate,2025-01-25,2025-03-04,2075,5.5,Quantum Computing Inc +AI00463,Autonomous Systems Engineer,60296,USD,60296,EN,PT,Ireland,L,Ireland,50,"Spark, Azure, PyTorch, Python, TensorFlow",Master,1,Retail,2025-01-21,2025-02-26,635,7.3,Algorithmic Solutions +AI00464,AI Specialist,64191,USD,64191,EN,PT,Sweden,M,Vietnam,50,"Kubernetes, Linux, Data Visualization, PyTorch",Master,1,Healthcare,2024-11-26,2024-12-11,2243,5.6,Future Systems +AI00465,AI Research Scientist,96896,CHF,87206,EN,FL,Switzerland,S,Italy,50,"Python, Scala, Azure, Hadoop",PhD,0,Gaming,2024-09-25,2024-12-05,1137,7.4,Algorithmic Solutions +AI00466,Principal Data Scientist,78105,USD,78105,MI,PT,South Korea,M,South Korea,50,"Scala, SQL, Data Visualization",Bachelor,2,Healthcare,2025-02-14,2025-03-24,2258,5.2,Predictive Systems +AI00467,Robotics Engineer,71686,EUR,60933,EN,PT,Germany,S,Germany,50,"Kubernetes, PyTorch, Linux",Master,0,Retail,2024-09-21,2024-10-20,1282,8,Cognitive Computing +AI00468,AI Research Scientist,148827,EUR,126503,SE,PT,Germany,M,Australia,0,"Python, Spark, NLP, R",Associate,9,Finance,2024-11-27,2025-01-31,1119,5,Neural Networks Co +AI00469,Data Analyst,92179,CAD,115224,SE,FL,Canada,S,Canada,100,"Python, Tableau, TensorFlow, GCP",Associate,8,Transportation,2025-03-01,2025-05-01,2487,8.2,Cognitive Computing +AI00470,Computer Vision Engineer,75460,EUR,64141,MI,FL,Austria,M,Austria,50,"Computer Vision, NLP, Kubernetes",Bachelor,3,Retail,2024-09-27,2024-11-17,1175,6.1,Advanced Robotics +AI00471,AI Architect,146580,EUR,124593,EX,PT,Netherlands,M,Netherlands,50,"Git, Docker, Mathematics, SQL",Associate,17,Education,2024-10-23,2024-12-20,1494,9.8,DataVision Ltd +AI00472,Data Analyst,68722,USD,68722,EN,FL,United States,S,Finland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Technology,2025-01-11,2025-03-06,1575,6.3,Neural Networks Co +AI00473,ML Ops Engineer,60841,USD,60841,EN,CT,United States,S,United States,50,"NLP, Scala, AWS, SQL, Hadoop",PhD,1,Automotive,2025-03-22,2025-05-27,2340,5.4,Machine Intelligence Group +AI00474,Deep Learning Engineer,49130,USD,49130,EN,FL,Sweden,S,Luxembourg,50,"TensorFlow, Python, Data Visualization, Deep Learning, AWS",Master,0,Education,2025-04-12,2025-05-16,2022,9.1,Advanced Robotics +AI00475,AI Product Manager,162683,USD,162683,SE,FT,Finland,L,Finland,50,"Python, TensorFlow, NLP, Kubernetes, Statistics",Master,9,Consulting,2024-12-30,2025-03-07,1100,9.1,Algorithmic Solutions +AI00476,Data Analyst,151676,EUR,128925,SE,PT,Germany,M,Germany,50,"Java, Hadoop, Data Visualization, MLOps, TensorFlow",Master,8,Government,2024-12-07,2025-01-15,1822,8.9,Advanced Robotics +AI00477,Head of AI,140928,USD,140928,MI,CT,Norway,M,Philippines,50,"Linux, TensorFlow, Hadoop, Docker",Master,4,Education,2024-04-10,2024-06-22,1543,8.9,DeepTech Ventures +AI00478,AI Specialist,140382,AUD,189516,SE,FL,Australia,M,Colombia,100,"Mathematics, GCP, Python, TensorFlow, NLP",Associate,8,Finance,2024-09-26,2024-11-22,2458,6.8,Cloud AI Solutions +AI00479,Machine Learning Engineer,179691,USD,179691,EX,CT,Ireland,S,Egypt,0,"TensorFlow, PyTorch, Scala, AWS",Bachelor,18,Energy,2024-09-29,2024-10-26,2128,6.7,Predictive Systems +AI00480,Principal Data Scientist,132280,EUR,112438,SE,FL,France,L,France,100,"Docker, Linux, Tableau, Git",PhD,8,Retail,2024-10-24,2024-12-14,599,8.1,Future Systems +AI00481,Computer Vision Engineer,90861,USD,90861,MI,FL,Norway,S,Norway,0,"Linux, SQL, R, Git, AWS",Associate,4,Telecommunications,2024-05-23,2024-07-14,783,7.9,Predictive Systems +AI00482,Data Engineer,102239,USD,102239,EX,PT,China,L,China,50,"Hadoop, Linux, R",Master,11,Technology,2025-04-16,2025-05-04,1574,9.5,Predictive Systems +AI00483,Machine Learning Engineer,71795,EUR,61026,EN,CT,Germany,M,Germany,0,"Python, Computer Vision, Hadoop, GCP, SQL",Master,1,Energy,2024-06-17,2024-08-13,2350,5.4,AI Innovations +AI00484,NLP Engineer,55230,EUR,46946,EN,FL,France,L,France,0,"Tableau, Data Visualization, Git, Linux, Hadoop",PhD,1,Media,2024-03-17,2024-04-02,840,9,Cognitive Computing +AI00485,AI Consultant,56030,EUR,47626,EN,PT,Germany,M,United States,50,"Docker, Deep Learning, Kubernetes, Spark",Bachelor,1,Government,2024-07-22,2024-08-20,1612,7.1,Autonomous Tech +AI00486,Head of AI,99246,USD,99246,EX,PT,India,L,India,100,"Spark, SQL, PyTorch, Java",Associate,17,Real Estate,2024-09-15,2024-11-02,1339,7.8,Predictive Systems +AI00487,AI Product Manager,130136,CAD,162670,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, TensorFlow, Computer Vision, Hadoop",PhD,11,Consulting,2025-01-05,2025-01-31,2026,6.3,DeepTech Ventures +AI00488,AI Research Scientist,51311,JPY,5644210,EN,FL,Japan,S,Japan,100,"Tableau, Linux, TensorFlow, Data Visualization",PhD,1,Telecommunications,2025-01-15,2025-03-09,856,6.7,Digital Transformation LLC +AI00489,Machine Learning Engineer,59010,USD,59010,EN,FL,South Korea,S,South Korea,100,"Hadoop, Computer Vision, Mathematics, GCP, Git",Associate,1,Real Estate,2024-12-27,2025-02-09,1203,9.1,Quantum Computing Inc +AI00490,AI Research Scientist,139257,USD,139257,SE,CT,United States,L,United States,50,"Azure, TensorFlow, Kubernetes, Computer Vision, Hadoop",Master,5,Manufacturing,2024-02-27,2024-03-25,1275,7.4,DataVision Ltd +AI00491,Data Analyst,50920,USD,50920,EN,FL,Finland,S,Finland,0,"Git, Scala, SQL",Master,0,Manufacturing,2024-11-05,2024-12-13,2039,8.6,Smart Analytics +AI00492,AI Specialist,116377,CHF,104739,EN,CT,Switzerland,L,Indonesia,100,"Azure, Scala, Deep Learning, Computer Vision, Statistics",Associate,0,Finance,2025-01-16,2025-02-01,1586,7,DeepTech Ventures +AI00493,Principal Data Scientist,101911,CHF,91720,EN,FT,Switzerland,M,France,0,"Linux, GCP, NLP",Associate,0,Education,2024-11-06,2024-12-23,1975,7.1,Cognitive Computing +AI00494,Data Analyst,92714,EUR,78807,EN,PT,Netherlands,L,Portugal,50,"Java, Mathematics, Tableau, Spark, PyTorch",Master,1,Technology,2024-03-17,2024-03-31,1305,9.3,Neural Networks Co +AI00495,Head of AI,83757,GBP,62818,EN,CT,United Kingdom,L,United Kingdom,0,"Statistics, Mathematics, Data Visualization",Bachelor,0,Media,2024-08-09,2024-09-20,1023,5,Advanced Robotics +AI00496,AI Specialist,88018,CAD,110023,MI,PT,Canada,L,Canada,50,"MLOps, NLP, SQL, Data Visualization",Master,2,Energy,2025-04-03,2025-04-29,1955,5.2,DataVision Ltd +AI00497,Data Scientist,51864,USD,51864,EN,FT,Finland,S,Finland,100,"Computer Vision, Scala, Data Visualization",Master,1,Transportation,2024-03-05,2024-05-02,2470,6.3,Cloud AI Solutions +AI00498,Head of AI,96976,SGD,126069,MI,CT,Singapore,L,Indonesia,50,"Spark, Hadoop, Scala, Linux",Associate,4,Manufacturing,2024-06-03,2024-07-08,1038,9.4,Predictive Systems +AI00499,Computer Vision Engineer,120263,USD,120263,EX,FT,South Korea,M,Chile,100,"Python, GCP, Spark",Bachelor,13,Retail,2024-10-23,2024-12-08,2046,6.7,Predictive Systems +AI00500,Data Scientist,178114,CHF,160303,SE,PT,Switzerland,S,Colombia,0,"AWS, Java, GCP",PhD,9,Consulting,2024-11-17,2024-12-31,1369,5.7,Cognitive Computing +AI00501,AI Research Scientist,94379,AUD,127412,MI,CT,Australia,L,Australia,50,"TensorFlow, GCP, PyTorch",Master,3,Finance,2025-01-05,2025-01-28,784,7.9,DeepTech Ventures +AI00502,AI Software Engineer,268149,USD,268149,EX,FT,Norway,M,Norway,0,"Git, Python, Azure, Statistics, AWS",PhD,17,Media,2024-02-03,2024-03-15,1961,5.6,Machine Intelligence Group +AI00503,NLP Engineer,90472,CAD,113090,MI,CT,Canada,L,Canada,0,"Mathematics, AWS, Git, Kubernetes, SQL",Master,3,Finance,2024-10-07,2024-11-18,1473,8.7,Quantum Computing Inc +AI00504,AI Product Manager,86547,USD,86547,SE,FT,Israel,S,Israel,0,"Git, Computer Vision, NLP, R",PhD,7,Healthcare,2024-11-08,2025-01-02,1978,8.8,Machine Intelligence Group +AI00505,AI Consultant,150700,EUR,128095,SE,CT,France,L,India,0,"Computer Vision, Azure, Data Visualization, Scala",PhD,6,Retail,2024-06-08,2024-07-06,2425,8.1,Predictive Systems +AI00506,AI Specialist,216740,USD,216740,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Azure, Python, Linux, Docker",Bachelor,14,Healthcare,2025-04-14,2025-05-01,1701,5.3,TechCorp Inc +AI00507,AI Software Engineer,59227,EUR,50343,EN,FL,Netherlands,M,Netherlands,0,"Docker, Tableau, Kubernetes",PhD,1,Healthcare,2025-01-22,2025-02-19,624,9.7,TechCorp Inc +AI00508,AI Software Engineer,163281,CAD,204101,SE,PT,Canada,L,Canada,0,"Git, TensorFlow, Tableau",PhD,5,Transportation,2025-01-20,2025-02-18,2007,7.3,Advanced Robotics +AI00509,Data Engineer,66305,USD,66305,EN,FT,United States,S,Estonia,100,"GCP, Java, AWS, Data Visualization",PhD,1,Transportation,2024-11-09,2024-12-30,1348,6.9,Smart Analytics +AI00510,AI Consultant,126408,CAD,158010,SE,PT,Canada,L,Canada,100,"Spark, Python, GCP, SQL",Bachelor,6,Automotive,2024-08-11,2024-09-18,1300,6.6,Machine Intelligence Group +AI00511,NLP Engineer,144024,EUR,122420,SE,FL,Netherlands,L,Netherlands,100,"AWS, R, Deep Learning, Kubernetes",Associate,7,Automotive,2024-07-03,2024-08-09,1552,9.6,Smart Analytics +AI00512,AI Software Engineer,108805,USD,108805,SE,FT,South Korea,M,South Korea,0,"AWS, Azure, Linux, Mathematics",Master,6,Transportation,2024-12-25,2025-02-08,2105,8.1,Cognitive Computing +AI00513,Data Analyst,79093,EUR,67229,MI,PT,France,M,Ireland,50,"Linux, Java, Tableau",PhD,3,Energy,2024-08-11,2024-09-03,837,8.9,Cloud AI Solutions +AI00514,Machine Learning Engineer,295893,USD,295893,EX,PT,Denmark,S,Denmark,50,"Spark, Python, Java, NLP, TensorFlow",Bachelor,15,Retail,2024-04-13,2024-06-18,1210,7.9,Algorithmic Solutions +AI00515,AI Specialist,83000,JPY,9130000,MI,FT,Japan,M,Japan,50,"TensorFlow, Hadoop, Data Visualization",PhD,2,Education,2024-12-12,2025-01-23,1006,5.2,Quantum Computing Inc +AI00516,AI Software Engineer,80124,USD,80124,EN,CT,United States,M,United States,0,"R, AWS, Hadoop, Kubernetes",Master,0,Education,2024-11-07,2024-12-14,665,9.8,Autonomous Tech +AI00517,Data Engineer,69336,EUR,58936,EN,FL,Germany,L,Vietnam,0,"Mathematics, Spark, Python",Bachelor,1,Gaming,2024-12-28,2025-01-30,1975,9.8,Autonomous Tech +AI00518,Data Engineer,42380,USD,42380,SE,FL,India,L,United States,0,"Azure, Docker, Java, MLOps",Master,5,Telecommunications,2024-08-02,2024-09-18,1526,6.9,TechCorp Inc +AI00519,Data Scientist,149450,EUR,127033,EX,PT,Germany,M,Philippines,0,"Mathematics, Spark, Docker, Hadoop",Bachelor,18,Telecommunications,2024-09-10,2024-11-01,1201,7.7,Smart Analytics +AI00520,AI Software Engineer,285891,CHF,257302,EX,FT,Switzerland,S,Singapore,50,"Java, Python, MLOps, Linux, Azure",Master,16,Consulting,2024-08-22,2024-09-29,1105,5.8,Neural Networks Co +AI00521,Computer Vision Engineer,75240,USD,75240,EN,CT,South Korea,L,South Korea,100,"Mathematics, Hadoop, Docker",PhD,1,Telecommunications,2024-01-20,2024-02-03,1921,9.3,Algorithmic Solutions +AI00522,Data Scientist,124786,JPY,13726460,SE,FL,Japan,M,Japan,0,"NLP, AWS, Data Visualization, MLOps",Bachelor,7,Education,2024-03-20,2024-05-24,1442,8.3,Algorithmic Solutions +AI00523,Machine Learning Researcher,109043,CHF,98139,MI,FL,Switzerland,S,Switzerland,0,"GCP, Azure, Linux",Associate,3,Government,2025-03-08,2025-05-15,1570,5.6,Machine Intelligence Group +AI00524,Machine Learning Engineer,89035,USD,89035,SE,CT,Finland,S,Ireland,50,"SQL, Docker, NLP, Python",Associate,5,Telecommunications,2024-08-29,2024-09-20,864,6.6,Quantum Computing Inc +AI00525,Machine Learning Engineer,190529,USD,190529,EX,FL,Finland,M,Finland,50,"Linux, Spark, Tableau, Mathematics, Azure",Bachelor,19,Technology,2024-10-11,2024-11-03,1090,10,Neural Networks Co +AI00526,Machine Learning Engineer,169009,USD,169009,SE,PT,United States,M,Finland,100,"Docker, Kubernetes, Azure",Master,9,Healthcare,2024-11-21,2025-01-25,1366,9.7,TechCorp Inc +AI00527,Autonomous Systems Engineer,48714,USD,48714,EN,FT,Israel,S,Israel,100,"Git, R, Python, Mathematics",Master,1,Energy,2025-03-15,2025-04-01,530,8.6,Advanced Robotics +AI00528,ML Ops Engineer,97541,EUR,82910,SE,FT,Netherlands,S,Netherlands,0,"MLOps, Python, Kubernetes, TensorFlow",PhD,5,Manufacturing,2024-12-16,2025-01-21,1792,9.2,Predictive Systems +AI00529,Robotics Engineer,144493,EUR,122819,SE,CT,Germany,M,Germany,0,"Spark, Java, Deep Learning, R",PhD,5,Education,2025-04-18,2025-05-26,2224,7.1,TechCorp Inc +AI00530,Computer Vision Engineer,185421,USD,185421,EX,CT,Denmark,S,Nigeria,0,"PyTorch, SQL, Docker, TensorFlow",Associate,11,Media,2024-06-18,2024-08-03,1524,9.7,DeepTech Ventures +AI00531,Principal Data Scientist,287164,USD,287164,EX,FL,Sweden,L,Sweden,0,"Azure, TensorFlow, Statistics, PyTorch, R",Bachelor,18,Consulting,2024-08-31,2024-10-03,1681,8.4,AI Innovations +AI00532,AI Consultant,120968,JPY,13306480,SE,PT,Japan,S,Japan,0,"Azure, Hadoop, Scala, Computer Vision, Python",PhD,8,Healthcare,2024-10-25,2024-11-30,952,7.3,Advanced Robotics +AI00533,AI Research Scientist,135171,USD,135171,EX,CT,Sweden,S,Sweden,50,"Azure, Deep Learning, GCP, TensorFlow",Associate,14,Healthcare,2024-05-14,2024-05-31,1460,6.7,Cognitive Computing +AI00534,AI Architect,129545,CHF,116591,EN,PT,Switzerland,L,Finland,100,"Scala, Python, Computer Vision, Deep Learning",Master,1,Government,2024-03-14,2024-04-20,561,9.3,TechCorp Inc +AI00535,Data Analyst,97794,SGD,127132,MI,CT,Singapore,L,Singapore,50,"PyTorch, R, Data Visualization",PhD,2,Gaming,2024-04-04,2024-06-12,984,6.1,Autonomous Tech +AI00536,Deep Learning Engineer,145395,CAD,181744,EX,FL,Canada,M,Brazil,100,"Computer Vision, Data Visualization, Python, Spark, TensorFlow",PhD,18,Automotive,2024-07-27,2024-09-08,1959,7.5,TechCorp Inc +AI00537,Computer Vision Engineer,204217,USD,204217,EX,CT,Sweden,M,Kenya,50,"GCP, Deep Learning, R",Associate,11,Education,2024-09-28,2024-11-16,1581,7.2,Future Systems +AI00538,Autonomous Systems Engineer,98702,USD,98702,EN,FT,Denmark,L,Denmark,0,"Statistics, Kubernetes, R, SQL",Bachelor,0,Telecommunications,2025-02-17,2025-03-11,1517,9.4,Machine Intelligence Group +AI00539,Deep Learning Engineer,99895,GBP,74921,MI,CT,United Kingdom,S,New Zealand,0,"R, PyTorch, GCP, NLP, Git",Bachelor,3,Finance,2025-01-27,2025-03-20,2257,10,Machine Intelligence Group +AI00540,NLP Engineer,135571,EUR,115235,SE,FL,Netherlands,S,Netherlands,100,"Git, Spark, R, SQL, Tableau",PhD,8,Telecommunications,2024-07-13,2024-09-01,2391,8.7,Advanced Robotics +AI00541,AI Specialist,119266,USD,119266,SE,PT,Ireland,L,Ireland,50,"SQL, Python, Data Visualization",PhD,6,Government,2024-04-04,2024-05-21,1518,9.2,Digital Transformation LLC +AI00542,Research Scientist,110844,EUR,94217,SE,CT,Austria,L,Austria,50,"Scala, Statistics, MLOps, Deep Learning",Associate,8,Transportation,2025-02-07,2025-03-09,1353,9.6,DeepTech Ventures +AI00543,NLP Engineer,145736,EUR,123876,SE,FT,Netherlands,L,Ghana,50,"Linux, Python, NLP, TensorFlow",Master,9,Transportation,2025-01-16,2025-03-05,2348,6.1,Cloud AI Solutions +AI00544,AI Software Engineer,232735,EUR,197825,EX,PT,France,M,France,0,"Spark, PyTorch, TensorFlow, Deep Learning, Azure",Bachelor,11,Manufacturing,2025-04-15,2025-06-25,1449,9.7,Future Systems +AI00545,Machine Learning Researcher,56990,USD,56990,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Hadoop",PhD,1,Telecommunications,2024-02-17,2024-03-25,2274,6.2,Algorithmic Solutions +AI00546,AI Software Engineer,169605,USD,169605,EX,FT,Israel,M,Israel,0,"Data Visualization, AWS, TensorFlow, R, Linux",PhD,15,Real Estate,2024-05-17,2024-06-16,1672,6,Digital Transformation LLC +AI00547,Machine Learning Engineer,145138,USD,145138,SE,PT,Finland,L,United Kingdom,0,"PyTorch, Git, Python, AWS",PhD,8,Real Estate,2024-12-25,2025-02-16,793,5.2,AI Innovations +AI00548,Data Scientist,139121,EUR,118253,SE,FL,Germany,L,Germany,50,"Git, Kubernetes, Python, Linux",Bachelor,5,Finance,2024-10-20,2024-11-17,587,9.2,Cloud AI Solutions +AI00549,AI Product Manager,178631,USD,178631,EX,PT,Israel,S,Malaysia,100,"TensorFlow, Spark, Computer Vision, NLP",Bachelor,13,Automotive,2024-09-28,2024-11-18,1081,6.8,Machine Intelligence Group +AI00550,NLP Engineer,90723,SGD,117940,MI,PT,Singapore,S,New Zealand,0,"Linux, Scala, Git",Bachelor,4,Retail,2024-12-28,2025-01-20,2414,7.3,DataVision Ltd +AI00551,ML Ops Engineer,49069,USD,49069,MI,CT,China,M,China,100,"Python, Docker, TensorFlow",PhD,4,Automotive,2024-11-26,2025-02-06,1659,7.2,Autonomous Tech +AI00552,Deep Learning Engineer,68202,JPY,7502220,EN,FL,Japan,L,Japan,50,"TensorFlow, Java, AWS, R",Master,0,Automotive,2025-04-08,2025-05-08,1446,5.6,Cloud AI Solutions +AI00553,Data Analyst,116676,EUR,99175,MI,FL,Germany,L,Germany,0,"R, TensorFlow, Kubernetes, Scala, Statistics",Associate,3,Media,2024-03-25,2024-04-26,1460,5.8,Smart Analytics +AI00554,AI Specialist,153139,USD,153139,SE,FT,Finland,L,Finland,100,"Python, Spark, Scala, Deep Learning, Mathematics",PhD,7,Real Estate,2025-04-28,2025-05-21,609,6.8,Autonomous Tech +AI00555,Computer Vision Engineer,131402,EUR,111692,EX,FL,Netherlands,S,Netherlands,50,"MLOps, Tableau, SQL",Master,13,Media,2024-12-31,2025-03-14,1147,5.1,DeepTech Ventures +AI00556,Machine Learning Engineer,54607,EUR,46416,EN,CT,Austria,M,Austria,50,"Git, Java, Hadoop",Associate,1,Real Estate,2024-08-11,2024-10-18,1342,6.4,Advanced Robotics +AI00557,Autonomous Systems Engineer,71774,JPY,7895140,MI,CT,Japan,S,Egypt,100,"Java, Data Visualization, Deep Learning, MLOps, Spark",PhD,4,Government,2024-02-04,2024-03-17,2022,9.7,DataVision Ltd +AI00558,Data Engineer,110765,EUR,94150,SE,FL,Germany,S,China,0,"PyTorch, GCP, TensorFlow",PhD,6,Technology,2024-03-02,2024-03-21,721,5.4,AI Innovations +AI00559,Data Analyst,265991,USD,265991,EX,PT,United States,L,Vietnam,100,"AWS, Git, Docker, Azure, Computer Vision",Master,13,Finance,2024-07-24,2024-09-24,1528,7.7,DataVision Ltd +AI00560,AI Research Scientist,83839,USD,83839,MI,FL,Israel,L,Israel,50,"Scala, Spark, GCP, Azure, NLP",Bachelor,4,Real Estate,2024-03-09,2024-03-29,1589,7.2,DataVision Ltd +AI00561,Machine Learning Engineer,236251,SGD,307126,EX,PT,Singapore,L,Singapore,100,"Tableau, Mathematics, AWS, NLP, Deep Learning",Bachelor,13,Healthcare,2024-09-04,2024-10-08,678,8,Future Systems +AI00562,AI Research Scientist,241129,AUD,325524,EX,FT,Australia,M,Australia,100,"Python, Computer Vision, Git, Scala",Bachelor,16,Manufacturing,2025-02-27,2025-03-15,962,7.5,Cloud AI Solutions +AI00563,Machine Learning Researcher,159083,USD,159083,SE,PT,Israel,L,Israel,100,"Linux, Computer Vision, Data Visualization",Bachelor,7,Education,2024-11-27,2024-12-25,1205,6.5,Quantum Computing Inc +AI00564,Computer Vision Engineer,103506,USD,103506,SE,FL,South Korea,L,South Korea,0,"Tableau, Azure, AWS",Master,8,Healthcare,2024-09-05,2024-11-10,1490,9.1,Future Systems +AI00565,Principal Data Scientist,232495,USD,232495,EX,PT,Denmark,M,Denmark,0,"Deep Learning, AWS, Azure",Master,10,Real Estate,2025-02-01,2025-04-11,2289,8.2,Future Systems +AI00566,AI Research Scientist,112744,CHF,101470,EN,CT,Switzerland,L,Switzerland,50,"AWS, Kubernetes, Hadoop, Spark",Associate,1,Gaming,2025-01-20,2025-03-28,779,5.1,Cloud AI Solutions +AI00567,Autonomous Systems Engineer,129622,USD,129622,SE,PT,South Korea,L,South Korea,0,"GCP, R, Computer Vision, PyTorch, Git",PhD,5,Energy,2024-05-21,2024-07-30,1268,5.7,TechCorp Inc +AI00568,Machine Learning Engineer,100903,EUR,85768,SE,CT,Austria,S,Austria,0,"Docker, Python, AWS, Spark, TensorFlow",Bachelor,5,Education,2024-06-21,2024-08-28,683,8.2,Future Systems +AI00569,Principal Data Scientist,238019,EUR,202316,EX,FL,Austria,M,Estonia,0,"Python, Kubernetes, TensorFlow, Azure",Bachelor,11,Telecommunications,2025-02-18,2025-03-12,1577,9.7,Future Systems +AI00570,Machine Learning Engineer,41302,USD,41302,EN,PT,China,L,China,100,"GCP, Azure, NLP",Bachelor,0,Manufacturing,2024-02-09,2024-02-29,991,8,DataVision Ltd +AI00571,Deep Learning Engineer,128647,USD,128647,EX,CT,Ireland,S,Ireland,100,"SQL, Computer Vision, Python, AWS, Java",Associate,17,Real Estate,2025-01-16,2025-02-23,1579,7.8,Advanced Robotics +AI00572,AI Software Engineer,52696,EUR,44792,EN,FL,France,S,France,50,"Docker, Kubernetes, Python, GCP",PhD,0,Government,2024-06-06,2024-06-20,1102,5.6,Machine Intelligence Group +AI00573,Principal Data Scientist,229071,GBP,171803,EX,FT,United Kingdom,L,United Kingdom,0,"Java, Python, Data Visualization, MLOps",Associate,19,Education,2024-07-16,2024-08-19,629,8.8,Quantum Computing Inc +AI00574,Autonomous Systems Engineer,215282,USD,215282,EX,FL,Denmark,M,Denmark,50,"MLOps, NLP, Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-06-17,2024-08-13,528,7.8,Algorithmic Solutions +AI00575,Principal Data Scientist,199110,EUR,169244,EX,FT,France,S,Ukraine,0,"TensorFlow, Hadoop, Kubernetes, SQL",Master,10,Finance,2024-05-01,2024-06-16,908,5.5,Future Systems +AI00576,NLP Engineer,75004,USD,75004,EN,FT,United States,L,United States,50,"Computer Vision, Linux, Spark, Hadoop",Bachelor,1,Technology,2024-08-30,2024-09-27,786,8.5,Smart Analytics +AI00577,Research Scientist,149575,USD,149575,SE,PT,Israel,L,Israel,50,"Linux, PyTorch, Git, R",Master,6,Transportation,2024-03-11,2024-04-21,821,9.5,Cloud AI Solutions +AI00578,Deep Learning Engineer,138904,USD,138904,EX,CT,Israel,S,Israel,50,"Scala, Python, Deep Learning",Master,15,Telecommunications,2025-04-06,2025-05-31,1452,5.4,Autonomous Tech +AI00579,Computer Vision Engineer,133658,SGD,173755,SE,FL,Singapore,L,Singapore,50,"Kubernetes, R, Mathematics",Master,7,Telecommunications,2025-01-30,2025-04-09,1637,8.8,Cognitive Computing +AI00580,Research Scientist,148968,EUR,126623,EX,FT,Austria,S,Mexico,0,"Spark, Scala, Hadoop, Computer Vision",PhD,10,Education,2024-12-01,2025-01-28,2122,5.7,Neural Networks Co +AI00581,AI Product Manager,87661,JPY,9642710,MI,PT,Japan,S,Japan,100,"Data Visualization, Hadoop, PyTorch, NLP",Master,3,Finance,2024-04-30,2024-05-25,885,5.9,Cognitive Computing +AI00582,Data Analyst,235575,CAD,294469,EX,PT,Canada,L,Japan,0,"Scala, Tableau, Linux, PyTorch, Spark",Master,12,Technology,2024-02-13,2024-03-13,2033,6.8,Machine Intelligence Group +AI00583,Computer Vision Engineer,195175,USD,195175,EX,PT,Israel,S,Israel,100,"AWS, Spark, PyTorch, Kubernetes, Tableau",Master,14,Real Estate,2025-02-19,2025-03-28,1435,7.1,AI Innovations +AI00584,Data Engineer,143318,CAD,179148,SE,PT,Canada,M,Canada,100,"GCP, PyTorch, Tableau, Git",Master,8,Energy,2024-07-18,2024-08-01,2002,9.3,AI Innovations +AI00585,Machine Learning Engineer,102959,CHF,92663,EN,FL,Switzerland,L,Switzerland,100,"Scala, Hadoop, Docker",Master,1,Finance,2024-07-15,2024-08-26,1849,7.7,Advanced Robotics +AI00586,ML Ops Engineer,90379,AUD,122012,MI,FL,Australia,S,Italy,100,"Data Visualization, Docker, Python, TensorFlow",Master,4,Finance,2025-04-20,2025-07-02,1029,7.5,Predictive Systems +AI00587,Principal Data Scientist,71203,CAD,89004,EN,FT,Canada,M,Canada,100,"TensorFlow, Git, SQL, Kubernetes, Java",Associate,0,Energy,2025-03-24,2025-04-27,1537,6.2,Advanced Robotics +AI00588,AI Consultant,177188,EUR,150610,EX,FL,Netherlands,S,Netherlands,100,"Scala, AWS, Git",Bachelor,13,Manufacturing,2025-01-06,2025-01-23,1619,8.6,Machine Intelligence Group +AI00589,Machine Learning Engineer,95416,USD,95416,MI,CT,Sweden,M,Brazil,100,"Java, Docker, Computer Vision, Linux, Mathematics",Master,2,Technology,2024-05-24,2024-06-09,938,5.6,Cognitive Computing +AI00590,Head of AI,89044,USD,89044,EN,CT,Norway,L,Czech Republic,50,"SQL, PyTorch, Tableau",PhD,1,Government,2024-04-11,2024-06-19,1762,7.2,Quantum Computing Inc +AI00591,NLP Engineer,78263,EUR,66524,EN,PT,Netherlands,M,Ireland,100,"Python, TensorFlow, GCP",PhD,0,Energy,2024-07-10,2024-09-21,1563,6.9,Predictive Systems +AI00592,ML Ops Engineer,231654,JPY,25481940,EX,PT,Japan,M,Japan,0,"Python, Mathematics, GCP, Computer Vision, AWS",PhD,11,Finance,2024-09-08,2024-09-28,1880,10,Digital Transformation LLC +AI00593,NLP Engineer,149046,USD,149046,SE,PT,Sweden,L,Sweden,0,"Python, Kubernetes, TensorFlow, Computer Vision, PyTorch",Associate,9,Technology,2024-08-19,2024-09-30,2359,5.5,Predictive Systems +AI00594,Machine Learning Researcher,84232,CAD,105290,MI,CT,Canada,S,Canada,100,"GCP, Scala, Azure, Statistics",Master,4,Gaming,2024-12-23,2025-01-29,537,7,Machine Intelligence Group +AI00595,ML Ops Engineer,94348,CAD,117935,SE,FT,Canada,S,Canada,50,"GCP, SQL, Spark, Linux",Master,7,Energy,2024-03-02,2024-04-12,527,7.4,DataVision Ltd +AI00596,Data Engineer,128839,USD,128839,SE,FL,Finland,M,Finland,50,"Mathematics, Statistics, Deep Learning, Java, Kubernetes",PhD,6,Retail,2024-11-05,2025-01-13,2263,8.5,Algorithmic Solutions +AI00597,AI Architect,166829,EUR,141805,SE,FL,Netherlands,L,Netherlands,100,"AWS, Kubernetes, Deep Learning",Associate,5,Consulting,2024-11-02,2024-11-30,2187,9.3,Cloud AI Solutions +AI00598,AI Software Engineer,67959,GBP,50969,EN,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, NLP, TensorFlow, Spark",PhD,1,Real Estate,2024-01-02,2024-01-20,599,7.4,Machine Intelligence Group +AI00599,AI Architect,80303,AUD,108409,MI,FT,Australia,M,Australia,50,"Python, GCP, Git, Java, Mathematics",Bachelor,4,Healthcare,2024-08-09,2024-10-07,812,9.3,Smart Analytics +AI00600,Data Engineer,104350,EUR,88698,MI,FL,Netherlands,S,Netherlands,50,"MLOps, Mathematics, Git",Bachelor,2,Transportation,2024-02-04,2024-04-04,2112,7.4,Algorithmic Solutions +AI00601,AI Consultant,146664,EUR,124664,SE,PT,Netherlands,L,Netherlands,50,"Python, SQL, Computer Vision, Java",PhD,8,Automotive,2024-04-04,2024-05-29,589,8.1,Machine Intelligence Group +AI00602,AI Software Engineer,119423,EUR,101510,SE,PT,Germany,M,Germany,50,"GCP, TensorFlow, Computer Vision, AWS",Master,9,Gaming,2024-11-19,2024-12-31,1840,9,Algorithmic Solutions +AI00603,AI Consultant,31988,USD,31988,EN,PT,China,M,China,50,"Docker, Mathematics, Scala",PhD,0,Automotive,2024-01-14,2024-02-20,2450,6.1,Future Systems +AI00604,AI Architect,94563,GBP,70922,EN,FT,United Kingdom,L,United Kingdom,50,"Git, TensorFlow, Deep Learning, Azure, Computer Vision",Bachelor,1,Finance,2024-01-05,2024-03-01,1461,9.7,DeepTech Ventures +AI00605,Autonomous Systems Engineer,85269,USD,85269,EN,FL,Ireland,L,Ireland,50,"MLOps, Deep Learning, PyTorch",Bachelor,0,Technology,2024-02-11,2024-03-30,953,7.9,DeepTech Ventures +AI00606,AI Architect,87092,USD,87092,EN,PT,Israel,L,Israel,50,"Kubernetes, Statistics, Scala",PhD,0,Healthcare,2024-02-25,2024-04-14,1931,9.9,Predictive Systems +AI00607,Machine Learning Researcher,75721,USD,75721,EN,FT,Finland,L,China,100,"Docker, Git, Python, Mathematics",PhD,1,Manufacturing,2024-07-05,2024-09-12,2487,5.1,DeepTech Ventures +AI00608,Research Scientist,158003,USD,158003,SE,FT,Sweden,L,Sweden,0,"Python, SQL, Tableau, Data Visualization",Master,7,Government,2025-04-20,2025-06-22,634,5.9,Future Systems +AI00609,Autonomous Systems Engineer,189198,JPY,20811780,EX,FL,Japan,M,Japan,0,"Computer Vision, Spark, Data Visualization, Java",Associate,18,Finance,2024-03-27,2024-06-01,2153,6.9,AI Innovations +AI00610,Research Scientist,57287,EUR,48694,EN,FL,France,M,France,100,"AWS, PyTorch, Computer Vision, GCP, Scala",Associate,1,Technology,2024-10-15,2024-12-08,1413,7.1,Machine Intelligence Group +AI00611,AI Specialist,116891,GBP,87668,MI,FT,United Kingdom,L,Japan,0,"TensorFlow, PyTorch, GCP, NLP",Bachelor,2,Education,2024-12-31,2025-03-11,865,8.1,Autonomous Tech +AI00612,Autonomous Systems Engineer,86678,USD,86678,MI,FT,Sweden,S,Hungary,50,"AWS, Mathematics, GCP, Git",Associate,4,Telecommunications,2025-04-08,2025-05-19,1812,6.6,Autonomous Tech +AI00613,Research Scientist,237261,EUR,201672,EX,PT,Germany,L,Germany,50,"Mathematics, Scala, PyTorch",Bachelor,16,Government,2024-06-04,2024-07-26,686,7.1,Neural Networks Co +AI00614,Data Engineer,340350,CHF,306315,EX,FT,Switzerland,L,France,0,"Python, Spark, Deep Learning, Azure, TensorFlow",PhD,17,Gaming,2024-07-14,2024-08-13,2373,7.2,Algorithmic Solutions +AI00615,Data Scientist,143376,USD,143376,SE,FL,Norway,S,Norway,50,"PyTorch, Mathematics, Deep Learning, Linux, AWS",Associate,8,Transportation,2025-04-06,2025-05-25,1159,7.7,Advanced Robotics +AI00616,Robotics Engineer,212213,CHF,190992,SE,FL,Switzerland,M,Switzerland,0,"Azure, SQL, Kubernetes, NLP",Associate,9,Consulting,2024-03-19,2024-04-30,1213,6.8,Autonomous Tech +AI00617,Principal Data Scientist,147392,SGD,191610,SE,CT,Singapore,L,Finland,100,"NLP, MLOps, SQL, Linux",Associate,5,Automotive,2025-03-03,2025-03-23,1701,5.8,AI Innovations +AI00618,Machine Learning Engineer,93630,USD,93630,SE,PT,Finland,S,Finland,50,"Kubernetes, SQL, PyTorch",Master,6,Energy,2025-02-27,2025-03-24,1022,6.5,Neural Networks Co +AI00619,AI Software Engineer,99867,CHF,89880,EN,FT,Switzerland,M,Switzerland,0,"Python, Git, TensorFlow",Master,0,Healthcare,2024-06-27,2024-08-09,1864,6.4,Advanced Robotics +AI00620,NLP Engineer,167900,CHF,151110,MI,FL,Switzerland,L,India,100,"Python, AWS, TensorFlow, Data Visualization, Computer Vision",Bachelor,3,Automotive,2025-03-25,2025-05-22,2095,5,DeepTech Ventures +AI00621,Computer Vision Engineer,113585,USD,113585,MI,FL,Norway,S,Egypt,50,"Computer Vision, Python, Statistics, TensorFlow",Associate,4,Government,2024-12-12,2025-01-27,1077,8.5,Digital Transformation LLC +AI00622,AI Software Engineer,88040,GBP,66030,MI,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, AWS, PyTorch, Deep Learning, Data Visualization",PhD,2,Finance,2024-08-03,2024-10-04,1715,8.2,Quantum Computing Inc +AI00623,Autonomous Systems Engineer,234891,USD,234891,EX,CT,South Korea,L,South Korea,0,"Spark, Scala, Statistics, Computer Vision",Master,19,Retail,2024-08-26,2024-09-22,2055,7,Future Systems +AI00624,Machine Learning Researcher,55689,EUR,47336,EN,PT,Austria,L,Austria,50,"Python, Mathematics, Deep Learning, Linux, GCP",Master,1,Government,2024-11-28,2025-01-27,1296,7.5,Predictive Systems +AI00625,Deep Learning Engineer,192002,EUR,163202,EX,FT,France,S,Japan,50,"MLOps, Java, Linux, Hadoop, PyTorch",PhD,15,Education,2024-08-21,2024-09-19,1600,8.8,DataVision Ltd +AI00626,Research Scientist,88478,USD,88478,EX,CT,India,L,India,100,"R, AWS, Mathematics",Bachelor,12,Education,2024-02-05,2024-03-18,703,6.5,Neural Networks Co +AI00627,ML Ops Engineer,233768,EUR,198703,EX,FT,Austria,M,Austria,50,"Python, Azure, Scala, AWS",Master,13,Manufacturing,2024-10-06,2024-11-12,2390,5.4,Autonomous Tech +AI00628,Autonomous Systems Engineer,394510,CHF,355059,EX,PT,Switzerland,L,Switzerland,0,"MLOps, Java, Statistics, Deep Learning, SQL",Master,18,Finance,2024-02-15,2024-04-28,1628,9.6,Smart Analytics +AI00629,AI Research Scientist,96275,CHF,86648,EN,FT,Switzerland,S,Switzerland,0,"Python, NLP, GCP, Docker, Java",PhD,0,Gaming,2024-01-09,2024-02-16,2313,7.4,Neural Networks Co +AI00630,Data Scientist,67084,USD,67084,SE,PT,China,M,Japan,100,"SQL, MLOps, Java",Associate,5,Government,2024-06-21,2024-07-18,852,8.7,AI Innovations +AI00631,Head of AI,87326,USD,87326,MI,PT,South Korea,M,South Africa,100,"PyTorch, NLP, MLOps",PhD,3,Retail,2024-06-17,2024-07-21,1777,7,Future Systems +AI00632,Research Scientist,88829,USD,88829,MI,PT,Finland,M,Belgium,50,"SQL, Linux, Deep Learning, Scala",Master,3,Consulting,2024-04-23,2024-07-05,1733,7.3,Cognitive Computing +AI00633,Autonomous Systems Engineer,110532,USD,110532,MI,FL,Denmark,M,Denmark,50,"Computer Vision, Mathematics, NLP",PhD,3,Manufacturing,2024-09-27,2024-11-05,2039,8.5,Future Systems +AI00634,AI Product Manager,60357,USD,60357,EN,CT,South Korea,L,Belgium,0,"Azure, TensorFlow, NLP, Python, PyTorch",Associate,0,Media,2024-03-06,2024-04-05,562,9.6,DataVision Ltd +AI00635,AI Research Scientist,315064,CHF,283558,EX,FL,Switzerland,S,Switzerland,0,"NLP, Git, Scala, Hadoop, Docker",Bachelor,18,Real Estate,2024-04-15,2024-05-18,1191,9.6,Cognitive Computing +AI00636,AI Software Engineer,70097,USD,70097,EN,PT,Denmark,S,Denmark,100,"Git, Python, TensorFlow",PhD,0,Finance,2025-04-13,2025-06-10,2054,5.4,Quantum Computing Inc +AI00637,Principal Data Scientist,117235,USD,117235,SE,FL,Ireland,M,Ireland,50,"Scala, Git, Azure",PhD,6,Government,2025-01-24,2025-03-30,1962,7.4,Autonomous Tech +AI00638,Principal Data Scientist,65851,USD,65851,EN,FT,Sweden,S,Turkey,100,"Hadoop, Python, Statistics, Scala",Associate,0,Energy,2025-01-03,2025-03-06,692,8.3,Quantum Computing Inc +AI00639,Computer Vision Engineer,84191,JPY,9261010,MI,FL,Japan,M,Japan,100,"R, Docker, Git, GCP, Statistics",Master,2,Consulting,2024-07-20,2024-09-06,1495,8.2,TechCorp Inc +AI00640,NLP Engineer,134590,USD,134590,MI,FT,Norway,M,Norway,0,"Python, SQL, Docker, TensorFlow, Tableau",PhD,2,Manufacturing,2024-04-12,2024-06-07,1564,8.4,AI Innovations +AI00641,AI Product Manager,139686,AUD,188576,SE,FL,Australia,M,Australia,100,"NLP, SQL, GCP, Tableau",Master,6,Education,2024-03-25,2024-04-28,2364,8.3,Smart Analytics +AI00642,AI Software Engineer,115226,USD,115226,SE,PT,South Korea,L,South Korea,0,"Python, Kubernetes, TensorFlow",Bachelor,5,Telecommunications,2025-04-19,2025-05-03,1761,5.9,Quantum Computing Inc +AI00643,Deep Learning Engineer,262115,EUR,222798,EX,PT,Netherlands,L,Netherlands,0,"Java, GCP, Computer Vision",Associate,12,Consulting,2024-05-08,2024-07-07,736,9.2,Algorithmic Solutions +AI00644,Data Scientist,111532,EUR,94802,SE,FL,Austria,S,Austria,50,"NLP, Java, Computer Vision, R, Deep Learning",Master,6,Gaming,2024-07-03,2024-07-17,517,5.4,Algorithmic Solutions +AI00645,Research Scientist,267795,SGD,348134,EX,CT,Singapore,M,Egypt,50,"Java, Azure, Kubernetes, PyTorch, Docker",Associate,11,Transportation,2024-10-07,2024-11-10,1026,5.4,DeepTech Ventures +AI00646,AI Software Engineer,63052,EUR,53594,EN,FT,France,M,United Kingdom,100,"Scala, Python, MLOps",Master,0,Retail,2024-02-05,2024-03-22,1183,6.6,Cognitive Computing +AI00647,AI Architect,54424,USD,54424,EN,FL,United States,S,Austria,0,"R, Kubernetes, Mathematics, Hadoop, SQL",PhD,1,Energy,2024-01-02,2024-01-21,1220,9.2,DeepTech Ventures +AI00648,AI Software Engineer,67908,USD,67908,SE,FT,China,M,Colombia,100,"Git, Spark, AWS, Scala",Bachelor,6,Gaming,2024-01-21,2024-02-28,2163,9.4,Smart Analytics +AI00649,ML Ops Engineer,115395,GBP,86546,SE,FL,United Kingdom,S,United Kingdom,100,"R, Kubernetes, Data Visualization",Bachelor,6,Government,2024-10-28,2024-12-30,1312,7.8,Predictive Systems +AI00650,Data Scientist,122516,AUD,165397,SE,FT,Australia,S,South Africa,100,"Deep Learning, Python, Git, Kubernetes, GCP",Master,9,Transportation,2024-07-23,2024-10-03,2397,8.7,AI Innovations +AI00651,Machine Learning Researcher,118846,EUR,101019,SE,FL,France,S,France,50,"SQL, AWS, NLP, PyTorch, Computer Vision",PhD,5,Manufacturing,2024-10-06,2024-11-11,1725,9.3,Machine Intelligence Group +AI00652,Machine Learning Engineer,98835,USD,98835,MI,FT,Sweden,M,Sweden,0,"AWS, Deep Learning, TensorFlow",Bachelor,2,Consulting,2024-02-06,2024-03-15,705,9.3,Neural Networks Co +AI00653,Data Engineer,295640,USD,295640,EX,FT,United States,M,United States,0,"AWS, GCP, Git, SQL",Master,11,Media,2024-01-08,2024-02-14,1782,8.3,Machine Intelligence Group +AI00654,Machine Learning Engineer,136359,SGD,177267,SE,CT,Singapore,M,Singapore,50,"R, Deep Learning, MLOps",Bachelor,9,Telecommunications,2024-08-30,2024-09-28,769,9.6,TechCorp Inc +AI00655,Principal Data Scientist,187425,USD,187425,EX,CT,Sweden,L,Sweden,0,"SQL, TensorFlow, Docker, Python, GCP",PhD,13,Consulting,2025-02-05,2025-02-25,1415,9.3,Cognitive Computing +AI00656,Machine Learning Engineer,91932,USD,91932,MI,FL,Sweden,M,Sweden,50,"MLOps, Kubernetes, Tableau, Scala",PhD,2,Manufacturing,2024-09-06,2024-10-18,1272,6.8,TechCorp Inc +AI00657,AI Software Engineer,71409,USD,71409,EN,FT,United States,L,United States,0,"Git, Linux, Data Visualization, Deep Learning",PhD,0,Telecommunications,2024-01-23,2024-03-17,1482,9.7,Neural Networks Co +AI00658,Machine Learning Engineer,48739,USD,48739,EN,FL,Ireland,S,Latvia,50,"Python, TensorFlow, Linux, PyTorch",PhD,0,Retail,2024-03-28,2024-05-11,1628,5.1,Predictive Systems +AI00659,AI Architect,61632,EUR,52387,EN,CT,Germany,S,Colombia,50,"Spark, Kubernetes, Data Visualization, Hadoop",Bachelor,1,Real Estate,2025-02-05,2025-02-19,910,6.1,Cloud AI Solutions +AI00660,Machine Learning Researcher,98216,JPY,10803760,MI,CT,Japan,S,New Zealand,0,"Spark, Deep Learning, NLP, PyTorch, Data Visualization",PhD,4,Energy,2024-04-16,2024-06-22,1612,6.4,DataVision Ltd +AI00661,AI Product Manager,104633,EUR,88938,SE,FL,Germany,S,Germany,100,"PyTorch, Spark, Tableau, Data Visualization",Master,6,Education,2024-08-06,2024-10-17,1922,7.3,Digital Transformation LLC +AI00662,AI Software Engineer,41990,USD,41990,MI,CT,China,L,India,100,"Scala, Azure, Deep Learning, Spark, Git",Associate,2,Government,2024-07-30,2024-09-24,1928,9.8,Autonomous Tech +AI00663,Data Analyst,238728,SGD,310346,EX,CT,Singapore,S,Singapore,0,"Python, MLOps, TensorFlow, NLP, Tableau",Master,12,Gaming,2024-08-25,2024-10-04,2000,7.7,Algorithmic Solutions +AI00664,AI Consultant,329444,CHF,296500,EX,FL,Switzerland,M,Switzerland,100,"Hadoop, Scala, Linux, Python",Bachelor,14,Real Estate,2024-12-27,2025-02-10,1268,8,Smart Analytics +AI00665,Research Scientist,70081,USD,70081,EN,FT,Israel,L,Israel,100,"Hadoop, R, Tableau, Python",Bachelor,1,Government,2024-04-20,2024-06-20,1280,7.4,AI Innovations +AI00666,Head of AI,288084,USD,288084,EX,FT,Denmark,L,Denmark,0,"Docker, Hadoop, Linux",Associate,15,Education,2024-10-06,2024-12-15,1022,7.1,Autonomous Tech +AI00667,AI Consultant,65282,USD,65282,MI,FL,Israel,S,Israel,100,"Scala, Tableau, NLP",Associate,2,Consulting,2024-03-22,2024-05-19,2126,5.5,TechCorp Inc +AI00668,Machine Learning Engineer,126052,SGD,163868,SE,PT,Singapore,S,Singapore,50,"Java, Scala, MLOps, R, Linux",PhD,6,Consulting,2024-07-23,2024-09-18,1915,7.4,DataVision Ltd +AI00669,Data Scientist,247685,USD,247685,EX,PT,Ireland,M,South Africa,100,"Data Visualization, SQL, Linux, Scala",PhD,12,Automotive,2025-03-28,2025-05-31,1375,7.5,Cognitive Computing +AI00670,AI Software Engineer,80022,GBP,60017,MI,FL,United Kingdom,M,United Kingdom,0,"Linux, PyTorch, Python, Statistics, Deep Learning",Master,3,Energy,2024-03-11,2024-04-21,603,5.5,Smart Analytics +AI00671,Data Analyst,96062,SGD,124881,EN,CT,Singapore,L,Singapore,0,"SQL, Scala, Data Visualization",Associate,1,Finance,2024-09-11,2024-11-08,2460,8.6,Algorithmic Solutions +AI00672,Principal Data Scientist,174460,USD,174460,SE,FL,Denmark,L,Denmark,100,"R, Mathematics, Python, Data Visualization, Docker",Master,9,Media,2025-02-27,2025-04-16,960,8.7,Smart Analytics +AI00673,AI Software Engineer,183335,EUR,155835,EX,PT,Austria,M,Austria,100,"NLP, PyTorch, Hadoop, Tableau, SQL",PhD,12,Education,2024-04-24,2024-05-30,897,8.4,Neural Networks Co +AI00674,Data Engineer,223437,USD,223437,EX,FL,Sweden,M,Sweden,100,"Linux, R, SQL, AWS",Bachelor,18,Gaming,2025-02-14,2025-03-24,2274,6.2,Neural Networks Co +AI00675,AI Specialist,177360,USD,177360,SE,PT,Denmark,L,Turkey,50,"Azure, TensorFlow, SQL",Bachelor,6,Consulting,2024-07-23,2024-09-18,1564,7.1,AI Innovations +AI00676,AI Consultant,206532,JPY,22718520,EX,FT,Japan,M,Canada,100,"SQL, Deep Learning, MLOps, Linux",Bachelor,10,Technology,2024-02-22,2024-03-09,1130,6.4,Cloud AI Solutions +AI00677,Robotics Engineer,112216,EUR,95384,MI,CT,Austria,L,Austria,100,"Deep Learning, TensorFlow, Kubernetes",PhD,4,Energy,2024-12-10,2024-12-25,715,6.3,Algorithmic Solutions +AI00678,AI Software Engineer,55817,CAD,69771,EN,PT,Canada,S,Canada,100,"Python, Azure, Deep Learning, SQL",Associate,0,Technology,2025-01-24,2025-03-23,1550,6.1,Autonomous Tech +AI00679,AI Specialist,324267,USD,324267,EX,CT,Norway,L,Norway,50,"Scala, Java, Mathematics",PhD,11,Finance,2024-04-05,2024-06-05,1346,6.5,Predictive Systems +AI00680,NLP Engineer,76065,JPY,8367150,MI,FT,Japan,S,Japan,50,"R, SQL, Kubernetes, Java",PhD,4,Education,2025-02-21,2025-04-10,1473,5.6,Predictive Systems +AI00681,Machine Learning Researcher,146849,CHF,132164,SE,PT,Switzerland,M,Spain,0,"Azure, SQL, MLOps",PhD,8,Education,2024-07-17,2024-08-17,1337,7.4,Predictive Systems +AI00682,Head of AI,81041,SGD,105353,EN,FL,Singapore,M,India,50,"Kubernetes, SQL, PyTorch",PhD,0,Healthcare,2025-02-12,2025-04-21,722,5.5,Advanced Robotics +AI00683,Computer Vision Engineer,106945,USD,106945,EN,PT,United States,L,Malaysia,100,"Tableau, Java, AWS, Data Visualization, Scala",PhD,0,Government,2024-02-11,2024-04-01,615,9.4,Quantum Computing Inc +AI00684,Robotics Engineer,329543,USD,329543,EX,PT,Denmark,L,Singapore,100,"Data Visualization, Scala, Statistics, NLP, Hadoop",Associate,18,Technology,2024-08-01,2024-09-21,553,8.4,Neural Networks Co +AI00685,Machine Learning Engineer,92316,USD,92316,SE,CT,Israel,S,United States,100,"Kubernetes, Deep Learning, Scala, PyTorch, R",Associate,6,Transportation,2024-12-27,2025-03-08,834,7.2,Cognitive Computing +AI00686,AI Research Scientist,209495,JPY,23044450,EX,FL,Japan,S,Japan,100,"TensorFlow, AWS, Kubernetes",PhD,19,Government,2025-03-15,2025-05-18,1511,6.9,AI Innovations +AI00687,Data Analyst,201545,USD,201545,EX,CT,Ireland,L,Australia,0,"Scala, Mathematics, Spark, Kubernetes",PhD,17,Telecommunications,2024-09-16,2024-11-23,1552,6.7,Cloud AI Solutions +AI00688,Principal Data Scientist,122321,CAD,152901,SE,PT,Canada,S,Canada,0,"Hadoop, Python, Deep Learning",Master,6,Consulting,2024-09-28,2024-12-05,2048,6.1,Cloud AI Solutions +AI00689,Machine Learning Researcher,120647,CHF,108582,EN,CT,Switzerland,L,Switzerland,50,"Tableau, MLOps, Data Visualization",Bachelor,0,Manufacturing,2024-07-26,2024-10-04,1544,9.1,Algorithmic Solutions +AI00690,Data Analyst,56584,USD,56584,EN,FL,South Korea,S,Sweden,100,"Tableau, Mathematics, Kubernetes, Git",Bachelor,0,Consulting,2024-02-10,2024-04-17,1670,5.3,AI Innovations +AI00691,AI Architect,143314,CHF,128983,SE,CT,Switzerland,S,Australia,50,"Hadoop, Java, GCP",Bachelor,8,Finance,2024-09-02,2024-10-31,2319,8,Autonomous Tech +AI00692,NLP Engineer,130879,JPY,14396690,SE,PT,Japan,M,Japan,0,"Python, Azure, MLOps",Master,6,Real Estate,2024-04-12,2024-06-19,2280,5.4,Cloud AI Solutions +AI00693,Machine Learning Engineer,79223,AUD,106951,MI,FL,Australia,S,Egypt,100,"Java, Kubernetes, R, Azure",Associate,4,Government,2024-11-15,2024-12-29,1232,5.5,Quantum Computing Inc +AI00694,Deep Learning Engineer,145545,USD,145545,SE,FL,Norway,M,Norway,100,"Docker, Tableau, Hadoop, Computer Vision",Bachelor,5,Retail,2025-01-21,2025-03-14,1802,8.8,TechCorp Inc +AI00695,Computer Vision Engineer,100393,JPY,11043230,MI,PT,Japan,L,Japan,50,"Java, Spark, AWS",Master,3,Education,2024-09-07,2024-10-21,947,9.2,Neural Networks Co +AI00696,AI Software Engineer,197280,USD,197280,EX,FT,Ireland,S,Ireland,100,"TensorFlow, Kubernetes, Linux, NLP",Master,16,Telecommunications,2024-08-05,2024-09-08,777,6,Autonomous Tech +AI00697,Computer Vision Engineer,88090,USD,88090,MI,FT,South Korea,M,South Korea,100,"Python, Computer Vision, Scala, Spark, TensorFlow",Associate,3,Retail,2025-01-02,2025-02-08,1674,10,AI Innovations +AI00698,Computer Vision Engineer,69911,USD,69911,MI,FT,South Korea,S,South Korea,100,"Kubernetes, TensorFlow, GCP",Master,3,Automotive,2024-09-12,2024-11-16,582,7.3,DataVision Ltd +AI00699,ML Ops Engineer,218971,CHF,197074,EX,FL,Switzerland,M,Switzerland,0,"Mathematics, Python, Tableau, AWS",Associate,18,Telecommunications,2025-03-22,2025-04-06,1989,6.5,Digital Transformation LLC +AI00700,AI Product Manager,79860,EUR,67881,EN,FT,Austria,L,Austria,50,"Mathematics, NLP, Tableau, Java",Bachelor,0,Government,2025-04-26,2025-05-23,2214,7.6,TechCorp Inc +AI00701,AI Architect,118343,CAD,147929,SE,CT,Canada,M,Indonesia,100,"GCP, PyTorch, AWS, Tableau, Kubernetes",Master,9,Automotive,2024-11-03,2024-11-29,2230,5.7,Advanced Robotics +AI00702,Research Scientist,142832,USD,142832,SE,FL,Finland,L,Finland,100,"Spark, Deep Learning, Python, AWS",Bachelor,6,Consulting,2024-12-14,2025-02-24,2222,6,Neural Networks Co +AI00703,Computer Vision Engineer,103304,EUR,87808,SE,CT,France,S,South Korea,0,"Deep Learning, SQL, Mathematics, Kubernetes, Tableau",Master,9,Media,2024-08-06,2024-09-15,1382,9.6,Neural Networks Co +AI00704,NLP Engineer,51555,USD,51555,SE,FT,India,M,India,50,"Java, R, NLP",PhD,6,Technology,2024-12-15,2025-01-17,1452,8,AI Innovations +AI00705,Robotics Engineer,33564,USD,33564,MI,FT,India,L,Israel,0,"Scala, Tableau, Kubernetes, Deep Learning",Associate,4,Media,2024-03-30,2024-05-06,562,5.8,DataVision Ltd +AI00706,AI Specialist,46733,USD,46733,MI,FT,China,S,Ireland,50,"Scala, PyTorch, Data Visualization, SQL, Java",Associate,3,Media,2024-12-20,2025-02-09,777,9.4,Digital Transformation LLC +AI00707,AI Architect,163489,EUR,138966,SE,FL,Germany,L,Germany,50,"Spark, Python, TensorFlow, NLP",Bachelor,8,Technology,2024-11-16,2025-01-24,1573,9.4,Machine Intelligence Group +AI00708,AI Consultant,127499,SGD,165749,SE,CT,Singapore,M,Singapore,100,"Docker, R, GCP, Scala, Hadoop",Master,9,Government,2024-11-29,2025-01-22,830,9.8,AI Innovations +AI00709,Head of AI,169543,EUR,144112,SE,FT,Germany,L,Germany,50,"Statistics, Git, Linux, Hadoop, Kubernetes",PhD,8,Energy,2024-09-24,2024-10-28,1703,5.1,DeepTech Ventures +AI00710,AI Specialist,252321,EUR,214473,EX,FT,France,L,France,100,"Statistics, AWS, Azure",Bachelor,14,Education,2024-04-05,2024-05-07,966,9.9,Smart Analytics +AI00711,Robotics Engineer,83888,GBP,62916,MI,FT,United Kingdom,M,United Kingdom,100,"MLOps, Deep Learning, Docker, Spark",Master,2,Technology,2025-03-04,2025-04-02,1553,6.1,Quantum Computing Inc +AI00712,NLP Engineer,117983,AUD,159277,SE,FT,Australia,M,Finland,50,"Computer Vision, Data Visualization, Java",Associate,5,Media,2024-03-08,2024-04-07,2450,7.8,DeepTech Ventures +AI00713,Research Scientist,153305,SGD,199297,EX,FL,Singapore,M,Singapore,100,"R, Docker, Scala, Mathematics, PyTorch",PhD,19,Education,2025-03-03,2025-03-22,824,7.7,Smart Analytics +AI00714,Deep Learning Engineer,112643,JPY,12390730,SE,FT,Japan,S,Japan,50,"PyTorch, Python, TensorFlow, Mathematics, AWS",Associate,9,Gaming,2024-12-31,2025-03-13,1976,6.1,Predictive Systems +AI00715,AI Product Manager,64605,USD,64605,EN,FT,Norway,S,Norway,50,"Deep Learning, MLOps, Python",Associate,1,Gaming,2025-02-26,2025-03-14,875,8.6,Cloud AI Solutions +AI00716,Autonomous Systems Engineer,62679,EUR,53277,MI,CT,France,S,Ireland,50,"R, SQL, Kubernetes, Azure, TensorFlow",PhD,3,Consulting,2024-08-13,2024-09-08,819,7,Cognitive Computing +AI00717,AI Consultant,161602,EUR,137362,EX,PT,France,L,France,100,"Hadoop, Kubernetes, Git, Docker",Associate,11,Automotive,2024-02-20,2024-03-20,2361,9,Advanced Robotics +AI00718,Computer Vision Engineer,124703,GBP,93527,SE,PT,United Kingdom,M,Latvia,0,"AWS, PyTorch, Tableau",Bachelor,6,Healthcare,2024-09-30,2024-11-13,1138,8.4,Cognitive Computing +AI00719,Head of AI,200853,USD,200853,EX,FT,Israel,M,Israel,50,"R, Statistics, SQL, Deep Learning",Master,13,Technology,2024-11-11,2025-01-17,1274,7.5,Algorithmic Solutions +AI00720,ML Ops Engineer,34021,USD,34021,MI,PT,India,S,India,50,"Git, Python, GCP, SQL, Java",PhD,2,Energy,2024-02-15,2024-03-25,2324,5.3,Cognitive Computing +AI00721,Robotics Engineer,90355,EUR,76802,MI,CT,Germany,M,Germany,50,"Deep Learning, Data Visualization, NLP, R",Bachelor,2,Energy,2024-11-17,2024-12-20,2458,9.4,Future Systems +AI00722,Machine Learning Engineer,63360,USD,63360,EN,FL,Ireland,M,Ireland,100,"Computer Vision, MLOps, SQL, Docker, PyTorch",Master,1,Telecommunications,2024-10-22,2024-11-19,1383,5.1,DataVision Ltd +AI00723,Data Analyst,185352,USD,185352,EX,PT,Ireland,S,New Zealand,0,"Scala, MLOps, Data Visualization",Bachelor,10,Government,2024-09-27,2024-11-06,1306,6.1,Advanced Robotics +AI00724,AI Software Engineer,85462,SGD,111101,EN,FT,Singapore,L,Switzerland,50,"NLP, Kubernetes, Git",Master,1,Transportation,2024-05-11,2024-06-27,591,9.9,Predictive Systems +AI00725,AI Product Manager,119183,EUR,101306,SE,PT,Austria,L,Austria,100,"Git, MLOps, Spark, Linux, Hadoop",Associate,9,Telecommunications,2025-01-16,2025-02-23,2480,9.5,Digital Transformation LLC +AI00726,Machine Learning Engineer,116244,EUR,98807,SE,CT,Austria,M,Austria,50,"R, Kubernetes, Spark",Bachelor,6,Technology,2024-02-02,2024-03-04,1029,6.1,Algorithmic Solutions +AI00727,Machine Learning Researcher,287291,USD,287291,EX,FT,Norway,S,Norway,50,"Scala, R, Tableau",Master,19,Manufacturing,2024-08-27,2024-10-31,1944,9.3,Quantum Computing Inc +AI00728,Data Engineer,160191,EUR,136162,EX,FL,Germany,S,Germany,50,"Linux, Git, Statistics, Deep Learning, Java",PhD,17,Automotive,2024-11-28,2025-01-24,688,9.9,TechCorp Inc +AI00729,AI Architect,207916,USD,207916,EX,FL,South Korea,M,South Korea,100,"Kubernetes, Mathematics, Hadoop, Deep Learning",Master,15,Retail,2024-10-17,2024-11-25,1085,8.7,Algorithmic Solutions +AI00730,Deep Learning Engineer,215737,USD,215737,EX,CT,Israel,S,Israel,50,"Linux, Scala, Git, SQL",PhD,15,Manufacturing,2024-06-29,2024-08-27,1269,5.2,Neural Networks Co +AI00731,Principal Data Scientist,89008,USD,89008,EN,CT,Denmark,L,New Zealand,0,"PyTorch, AWS, MLOps",Master,0,Telecommunications,2024-01-04,2024-02-12,1540,8.3,Future Systems +AI00732,Principal Data Scientist,122155,GBP,91616,SE,PT,United Kingdom,S,United Kingdom,100,"PyTorch, Hadoop, Computer Vision",Bachelor,9,Media,2024-02-16,2024-03-27,1762,5.3,TechCorp Inc +AI00733,Data Scientist,40715,USD,40715,EN,FL,China,L,South Korea,0,"Python, NLP, Hadoop, Docker, Tableau",PhD,1,Technology,2024-07-06,2024-08-10,1018,7.9,Cloud AI Solutions +AI00734,Robotics Engineer,188499,CHF,169649,SE,PT,Switzerland,S,India,0,"Git, Data Visualization, Hadoop",Bachelor,9,Finance,2024-10-31,2024-11-18,870,6.6,Digital Transformation LLC +AI00735,AI Specialist,181167,GBP,135875,EX,PT,United Kingdom,M,Thailand,100,"Azure, MLOps, Mathematics, Docker",Bachelor,16,Transportation,2024-11-30,2025-01-25,1237,9.7,DataVision Ltd +AI00736,AI Software Engineer,137580,USD,137580,SE,CT,Denmark,M,Denmark,50,"Deep Learning, Kubernetes, AWS, Mathematics, GCP",PhD,7,Healthcare,2024-07-02,2024-09-06,1646,7.9,Neural Networks Co +AI00737,Autonomous Systems Engineer,81092,CAD,101365,EN,CT,Canada,L,India,0,"NLP, SQL, Statistics, Data Visualization, Scala",PhD,0,Finance,2025-04-27,2025-05-23,623,8.2,Digital Transformation LLC +AI00738,Principal Data Scientist,167011,EUR,141959,EX,PT,Germany,M,Russia,0,"Azure, MLOps, Python, Data Visualization, Mathematics",Master,16,Healthcare,2024-05-15,2024-06-12,2468,7.6,DeepTech Ventures +AI00739,Data Analyst,115690,SGD,150397,MI,CT,Singapore,M,Singapore,50,"Python, MLOps, Git",Master,2,Consulting,2024-11-25,2024-12-20,1357,6.2,Future Systems +AI00740,Head of AI,85081,JPY,9358910,MI,CT,Japan,M,Japan,100,"Docker, Git, Hadoop",Associate,3,Energy,2024-11-15,2024-11-29,1877,9.6,Smart Analytics +AI00741,AI Product Manager,204925,USD,204925,EX,CT,Norway,S,New Zealand,100,"TensorFlow, Azure, Scala, Kubernetes, Spark",PhD,13,Manufacturing,2025-03-10,2025-04-18,2392,5.3,Autonomous Tech +AI00742,NLP Engineer,71330,USD,71330,EN,FT,Ireland,M,Ireland,100,"Statistics, Kubernetes, Deep Learning, Scala, AWS",Master,1,Finance,2025-01-12,2025-02-03,1304,5.3,Smart Analytics +AI00743,ML Ops Engineer,147961,CHF,133165,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, Git, SQL",PhD,2,Gaming,2024-11-18,2025-01-27,2488,7,Digital Transformation LLC +AI00744,AI Architect,81537,EUR,69306,MI,PT,Germany,M,France,100,"GCP, Linux, Kubernetes",Associate,2,Media,2025-02-21,2025-03-08,1123,8.1,Quantum Computing Inc +AI00745,Autonomous Systems Engineer,169303,EUR,143908,EX,FL,Germany,M,Germany,0,"Linux, Kubernetes, AWS, Data Visualization",PhD,14,Transportation,2024-05-08,2024-07-09,1444,7,Machine Intelligence Group +AI00746,Autonomous Systems Engineer,79345,USD,79345,EN,FL,United States,L,United States,100,"Spark, Kubernetes, SQL, AWS",Associate,1,Gaming,2024-01-01,2024-03-03,2459,7.1,Cognitive Computing +AI00747,NLP Engineer,141710,EUR,120454,EX,FT,Austria,S,Argentina,100,"Azure, Python, Git, Docker",Master,12,Real Estate,2025-04-28,2025-06-20,975,7.4,AI Innovations +AI00748,Research Scientist,176540,USD,176540,EX,FT,Sweden,S,United States,0,"TensorFlow, Kubernetes, Git, Java, Docker",Master,16,Healthcare,2024-09-17,2024-11-19,738,5.5,Algorithmic Solutions +AI00749,Deep Learning Engineer,75872,SGD,98634,EN,FT,Singapore,S,Netherlands,0,"Hadoop, MLOps, Python, Computer Vision, Docker",Associate,0,Retail,2025-01-06,2025-01-30,1818,8.4,Digital Transformation LLC +AI00750,Machine Learning Researcher,39100,USD,39100,MI,CT,China,M,Netherlands,100,"SQL, Docker, Python, Mathematics",PhD,3,Energy,2025-04-08,2025-04-22,1101,5.7,DeepTech Ventures +AI00751,Data Analyst,60610,USD,60610,MI,PT,South Korea,S,South Korea,50,"PyTorch, Computer Vision, Mathematics, R",Associate,3,Finance,2025-03-23,2025-05-24,748,5.4,Digital Transformation LLC +AI00752,NLP Engineer,64997,USD,64997,EN,CT,Finland,L,Finland,50,"Computer Vision, TensorFlow, Java",PhD,0,Automotive,2024-12-01,2025-01-01,1749,7.9,Autonomous Tech +AI00753,Principal Data Scientist,79831,USD,79831,MI,FT,Finland,S,Finland,0,"Scala, Java, Kubernetes, Data Visualization, Git",Bachelor,4,Retail,2024-05-09,2024-06-22,1863,9.6,Autonomous Tech +AI00754,Data Analyst,75434,JPY,8297740,EN,FT,Japan,L,Austria,100,"Computer Vision, SQL, Linux, AWS, Mathematics",PhD,1,Technology,2025-04-23,2025-05-12,2180,7.3,DataVision Ltd +AI00755,NLP Engineer,135956,USD,135956,SE,PT,Israel,M,Israel,100,"Kubernetes, Scala, Computer Vision",Master,8,Transportation,2024-02-11,2024-04-20,1899,5.7,TechCorp Inc +AI00756,Machine Learning Engineer,91194,CAD,113993,MI,PT,Canada,S,Canada,0,"Azure, Spark, Linux, Scala, SQL",PhD,3,Media,2024-08-13,2024-09-20,689,9.9,Neural Networks Co +AI00757,Research Scientist,182045,USD,182045,EX,CT,Israel,S,India,100,"Computer Vision, Hadoop, Kubernetes, Spark, Statistics",PhD,10,Technology,2024-11-25,2025-01-26,1620,10,Digital Transformation LLC +AI00758,Data Engineer,143858,USD,143858,EX,FT,Israel,M,Israel,50,"Deep Learning, Kubernetes, Hadoop, Linux",Associate,10,Automotive,2025-01-03,2025-02-05,1182,7.8,Digital Transformation LLC +AI00759,Data Analyst,135781,USD,135781,SE,FT,Finland,M,Finland,100,"Linux, R, Hadoop, Computer Vision, Python",Master,7,Retail,2024-11-26,2025-02-03,1587,6.2,Cloud AI Solutions +AI00760,AI Product Manager,151948,USD,151948,MI,FL,Denmark,L,Germany,100,"Statistics, Computer Vision, NLP, Python, TensorFlow",Bachelor,3,Manufacturing,2024-11-11,2024-12-10,1738,6.3,Predictive Systems +AI00761,AI Research Scientist,97414,CAD,121768,SE,FL,Canada,S,Canada,0,"Tableau, R, SQL, GCP, Docker",Master,6,Healthcare,2024-08-04,2024-08-30,748,9.3,Autonomous Tech +AI00762,Autonomous Systems Engineer,44257,USD,44257,MI,PT,China,M,China,50,"Kubernetes, Hadoop, GCP, Scala, Azure",PhD,4,Manufacturing,2024-11-28,2024-12-23,1984,6.4,Autonomous Tech +AI00763,Machine Learning Researcher,183099,USD,183099,SE,FT,Denmark,M,Denmark,100,"GCP, Docker, MLOps, Tableau, PyTorch",Master,9,Manufacturing,2025-01-21,2025-02-11,542,8.9,Cloud AI Solutions +AI00764,AI Product Manager,66978,EUR,56931,EN,FT,France,M,France,50,"Azure, Linux, Statistics, NLP",Associate,0,Gaming,2025-04-06,2025-05-07,721,9.4,Cloud AI Solutions +AI00765,Computer Vision Engineer,58844,USD,58844,EN,PT,United States,S,Kenya,100,"SQL, Python, Mathematics",PhD,1,Technology,2024-03-15,2024-04-20,874,7.2,Digital Transformation LLC +AI00766,Data Scientist,86679,EUR,73677,EN,PT,France,L,France,50,"Scala, Docker, Spark, MLOps, NLP",PhD,1,Gaming,2024-04-09,2024-04-24,865,5.7,Cognitive Computing +AI00767,Research Scientist,102607,EUR,87216,MI,FL,Austria,L,Austria,50,"Scala, Python, Tableau, Statistics",Associate,4,Telecommunications,2025-04-16,2025-05-16,2191,8.4,Autonomous Tech +AI00768,AI Research Scientist,117860,USD,117860,MI,FL,Norway,S,Norway,0,"Linux, Python, Scala",Master,3,Consulting,2024-02-21,2024-03-23,1949,9.6,Cloud AI Solutions +AI00769,Data Engineer,53776,AUD,72598,EN,PT,Australia,M,Mexico,50,"PyTorch, Spark, TensorFlow",PhD,1,Energy,2025-03-31,2025-05-21,1959,10,Advanced Robotics +AI00770,Autonomous Systems Engineer,22245,USD,22245,EN,FL,India,S,India,100,"R, AWS, Mathematics, Deep Learning, MLOps",Bachelor,1,Automotive,2025-03-07,2025-04-27,2075,7.7,TechCorp Inc +AI00771,Deep Learning Engineer,86753,USD,86753,EN,CT,Denmark,S,Hungary,50,"Kubernetes, MLOps, SQL, Python",Bachelor,0,Consulting,2025-01-27,2025-03-19,527,8.3,Quantum Computing Inc +AI00772,Data Scientist,59445,CAD,74306,EN,PT,Canada,S,Canada,50,"Kubernetes, GCP, Java, Deep Learning, Statistics",Associate,0,Finance,2024-02-26,2024-03-21,1565,6.9,Autonomous Tech +AI00773,Machine Learning Researcher,181623,USD,181623,SE,FL,Norway,L,Norway,100,"Azure, Scala, Python, Git",Bachelor,7,Telecommunications,2024-02-14,2024-03-10,2148,9.1,Neural Networks Co +AI00774,Machine Learning Engineer,23848,USD,23848,EN,FL,China,S,Poland,0,"TensorFlow, Spark, NLP, Mathematics",Associate,1,Real Estate,2024-02-29,2024-04-17,1126,8.6,Machine Intelligence Group +AI00775,Head of AI,67555,USD,67555,SE,PT,China,L,China,100,"Mathematics, Scala, Java",PhD,5,Education,2024-11-30,2025-01-08,1445,8.8,Future Systems +AI00776,Autonomous Systems Engineer,156672,USD,156672,EX,FL,Sweden,L,Sweden,0,"Statistics, SQL, Python, AWS, Computer Vision",Associate,19,Real Estate,2025-03-23,2025-05-11,2253,7,AI Innovations +AI00777,Data Analyst,99310,USD,99310,EX,FT,China,S,Vietnam,50,"Scala, Java, Deep Learning",Associate,14,Transportation,2024-04-28,2024-05-28,1790,5.8,TechCorp Inc +AI00778,Data Scientist,106468,USD,106468,SE,FL,South Korea,S,Singapore,0,"Kubernetes, PyTorch, SQL, Computer Vision, Tableau",PhD,5,Energy,2025-02-07,2025-03-21,735,8.3,DataVision Ltd +AI00779,NLP Engineer,133549,JPY,14690390,SE,PT,Japan,L,Portugal,50,"Statistics, Docker, TensorFlow",Master,8,Government,2024-02-03,2024-03-05,762,7.5,Autonomous Tech +AI00780,AI Consultant,101850,USD,101850,EN,FL,Norway,L,Norway,50,"Mathematics, NLP, MLOps, Linux",PhD,1,Healthcare,2025-04-04,2025-04-24,1992,7.7,TechCorp Inc +AI00781,Data Analyst,135555,USD,135555,EX,FL,China,L,China,50,"Deep Learning, Scala, Python",Associate,18,Real Estate,2025-01-14,2025-02-16,1694,6.9,Advanced Robotics +AI00782,Data Scientist,194650,USD,194650,EX,CT,Norway,M,Norway,0,"GCP, Scala, PyTorch, SQL",Master,13,Automotive,2025-01-01,2025-01-16,1290,9.4,Cognitive Computing +AI00783,NLP Engineer,48184,USD,48184,SE,FT,India,S,India,50,"Kubernetes, Docker, Python, TensorFlow",PhD,8,Real Estate,2024-06-02,2024-07-06,526,7.4,Digital Transformation LLC +AI00784,NLP Engineer,102143,EUR,86822,MI,PT,Netherlands,S,Austria,100,"Docker, Git, Scala, Mathematics",Master,2,Technology,2024-10-02,2024-10-16,883,8.9,Cognitive Computing +AI00785,Data Engineer,130584,USD,130584,SE,FT,Finland,L,Hungary,0,"Kubernetes, Azure, Spark",PhD,6,Gaming,2024-05-29,2024-06-27,1303,8,Predictive Systems +AI00786,ML Ops Engineer,197290,USD,197290,SE,FL,Denmark,M,Nigeria,50,"Python, TensorFlow, Statistics, PyTorch, Deep Learning",Bachelor,5,Education,2024-08-30,2024-09-15,1376,8.8,TechCorp Inc +AI00787,AI Architect,57552,EUR,48919,EN,FL,Germany,M,Germany,50,"Hadoop, TensorFlow, Tableau",PhD,0,Retail,2024-04-21,2024-05-15,2185,5.4,Algorithmic Solutions +AI00788,AI Specialist,138325,USD,138325,SE,CT,Sweden,M,Sweden,0,"Azure, Spark, Data Visualization, R, Python",Master,7,Transportation,2024-10-25,2024-11-17,1112,5.6,Machine Intelligence Group +AI00789,AI Product Manager,62787,USD,62787,EN,FL,Norway,S,Singapore,0,"Hadoop, Scala, R, Python",Associate,1,Automotive,2024-09-11,2024-10-10,1204,5.1,Cloud AI Solutions +AI00790,AI Research Scientist,96898,EUR,82363,SE,FL,Austria,M,Austria,50,"Docker, Tableau, SQL, Deep Learning, MLOps",Bachelor,8,Healthcare,2024-09-15,2024-10-22,1719,6.3,Future Systems +AI00791,AI Software Engineer,101690,USD,101690,MI,CT,Norway,S,Norway,100,"Scala, Deep Learning, Git, TensorFlow",Bachelor,4,Telecommunications,2025-03-21,2025-05-01,2046,9.9,Predictive Systems +AI00792,Data Scientist,104342,USD,104342,MI,CT,United States,L,United States,50,"Azure, SQL, Python, AWS",Bachelor,2,Technology,2024-08-23,2024-09-21,2196,7.8,Future Systems +AI00793,Principal Data Scientist,182831,EUR,155406,EX,PT,Austria,S,Chile,100,"Kubernetes, Linux, Scala, Deep Learning, Azure",Master,18,Transportation,2024-12-22,2025-01-27,1334,5.8,Quantum Computing Inc +AI00794,AI Specialist,65362,EUR,55558,EN,PT,France,L,Japan,0,"TensorFlow, AWS, NLP, Data Visualization",Bachelor,1,Government,2024-09-12,2024-10-12,1819,5.2,Predictive Systems +AI00795,AI Software Engineer,116249,EUR,98812,SE,FL,France,M,France,50,"Scala, Java, MLOps, Azure",PhD,8,Finance,2024-05-02,2024-06-10,1595,8.6,Digital Transformation LLC +AI00796,Machine Learning Researcher,181065,USD,181065,EX,FL,Norway,S,Norway,0,"Java, R, Statistics, Linux, Mathematics",Master,19,Healthcare,2024-10-18,2024-11-03,2202,8,Machine Intelligence Group +AI00797,Data Engineer,110326,EUR,93777,SE,PT,France,S,France,0,"PyTorch, Hadoop, AWS, Python",Associate,8,Technology,2024-11-08,2024-12-14,739,9.3,Quantum Computing Inc +AI00798,AI Research Scientist,113275,EUR,96284,SE,FT,Netherlands,M,Netherlands,0,"Docker, Java, Tableau, Hadoop",Master,6,Consulting,2024-03-08,2024-04-17,1264,8,Quantum Computing Inc +AI00799,Autonomous Systems Engineer,86720,CAD,108400,SE,CT,Canada,S,Canada,0,"Spark, Kubernetes, SQL, Data Visualization",Bachelor,7,Consulting,2024-03-21,2024-05-18,821,6.7,Smart Analytics +AI00800,Deep Learning Engineer,88527,USD,88527,SE,CT,South Korea,M,South Korea,100,"Python, Docker, Linux, Spark, Scala",Master,8,Technology,2024-02-14,2024-04-27,1973,6.3,TechCorp Inc +AI00801,AI Software Engineer,75281,USD,75281,EN,FL,Finland,M,Finland,100,"Git, Python, Tableau, Spark",Associate,0,Technology,2024-07-12,2024-08-01,1666,8.4,Advanced Robotics +AI00802,Principal Data Scientist,63784,AUD,86108,EN,FL,Australia,L,Australia,100,"SQL, Deep Learning, Data Visualization, TensorFlow",Master,0,Healthcare,2025-02-14,2025-03-01,668,10,Quantum Computing Inc +AI00803,AI Product Manager,140500,SGD,182650,SE,CT,Singapore,L,Malaysia,0,"Kubernetes, Data Visualization, MLOps, Python, GCP",PhD,7,Energy,2024-12-15,2025-02-10,1733,8.6,Predictive Systems +AI00804,Deep Learning Engineer,30726,USD,30726,EN,FT,India,L,India,100,"Spark, Kubernetes, MLOps, Git",PhD,1,Telecommunications,2024-10-02,2024-10-18,782,7.9,Predictive Systems +AI00805,AI Specialist,242789,SGD,315626,EX,PT,Singapore,M,Singapore,50,"Data Visualization, Hadoop, MLOps, SQL",Associate,15,Manufacturing,2024-06-10,2024-07-03,592,8.7,DeepTech Ventures +AI00806,ML Ops Engineer,126827,USD,126827,EX,FT,South Korea,S,South Korea,0,"Python, Git, R, NLP, PyTorch",Master,17,Real Estate,2024-05-24,2024-06-19,2410,9.6,Digital Transformation LLC +AI00807,Robotics Engineer,77753,JPY,8552830,MI,CT,Japan,M,Japan,100,"Linux, Python, Java, Azure, Git",PhD,2,Automotive,2025-04-09,2025-06-19,845,9.4,Neural Networks Co +AI00808,Autonomous Systems Engineer,204502,USD,204502,EX,PT,United States,S,United States,100,"NLP, Linux, PyTorch",Master,13,Consulting,2024-11-23,2024-12-14,1899,9.7,Machine Intelligence Group +AI00809,Machine Learning Engineer,76869,EUR,65339,MI,PT,France,S,France,50,"SQL, Git, TensorFlow, Statistics",Bachelor,4,Healthcare,2025-03-11,2025-04-24,1199,7.6,AI Innovations +AI00810,Computer Vision Engineer,128192,USD,128192,SE,FT,Ireland,S,India,0,"R, SQL, PyTorch, Docker, Deep Learning",Bachelor,5,Energy,2024-11-01,2024-12-12,2010,5.4,Cognitive Computing +AI00811,Machine Learning Engineer,234782,CHF,211304,EX,PT,Switzerland,M,Switzerland,0,"Mathematics, SQL, MLOps, TensorFlow, Kubernetes",Associate,19,Education,2024-02-05,2024-03-25,1540,7.4,Quantum Computing Inc +AI00812,Robotics Engineer,243016,USD,243016,EX,CT,Norway,S,Norway,0,"SQL, Deep Learning, Data Visualization",PhD,14,Consulting,2024-04-20,2024-06-27,2207,5.9,Machine Intelligence Group +AI00813,ML Ops Engineer,232932,GBP,174699,EX,CT,United Kingdom,L,United Kingdom,50,"Statistics, Spark, Python, AWS, Azure",Bachelor,19,Education,2024-05-27,2024-07-02,2321,7.9,DeepTech Ventures +AI00814,AI Software Engineer,157713,EUR,134056,EX,FT,France,L,France,100,"Statistics, Azure, NLP, Data Visualization, Deep Learning",Associate,11,Real Estate,2024-03-29,2024-04-18,1275,7.3,Quantum Computing Inc +AI00815,Computer Vision Engineer,78731,GBP,59048,MI,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, PyTorch, SQL, Mathematics, Scala",Bachelor,4,Retail,2025-01-12,2025-01-26,893,9.7,DataVision Ltd +AI00816,Machine Learning Engineer,118802,CAD,148503,SE,PT,Canada,L,Canada,50,"GCP, Docker, Azure, Tableau, PyTorch",PhD,5,Telecommunications,2025-01-18,2025-02-08,2228,9.6,Digital Transformation LLC +AI00817,AI Software Engineer,86119,CHF,77507,EN,PT,Switzerland,M,Switzerland,50,"MLOps, Scala, Azure",Master,1,Retail,2025-03-14,2025-04-18,1655,7.2,Future Systems +AI00818,Head of AI,148519,GBP,111389,EX,CT,United Kingdom,M,United Kingdom,50,"MLOps, Java, Scala, R",PhD,19,Retail,2025-02-11,2025-02-26,1578,5.8,Neural Networks Co +AI00819,AI Research Scientist,48058,USD,48058,EN,PT,South Korea,S,South Korea,100,"Spark, Hadoop, TensorFlow, Data Visualization, Computer Vision",Associate,1,Manufacturing,2024-08-26,2024-11-06,1378,5.2,Future Systems +AI00820,AI Architect,68183,EUR,57956,EN,FT,France,M,France,0,"Mathematics, SQL, Spark, Kubernetes, PyTorch",PhD,0,Retail,2024-12-08,2025-02-11,1399,5.9,Algorithmic Solutions +AI00821,Principal Data Scientist,237151,GBP,177863,EX,FT,United Kingdom,S,United Kingdom,100,"Git, Computer Vision, Tableau, Azure",PhD,15,Energy,2025-04-02,2025-05-20,2094,9.5,Algorithmic Solutions +AI00822,Data Engineer,95252,USD,95252,MI,PT,Ireland,S,Ireland,50,"Scala, MLOps, SQL",Bachelor,4,Real Estate,2024-11-05,2024-12-17,1479,9.9,AI Innovations +AI00823,NLP Engineer,142166,JPY,15638260,SE,CT,Japan,L,Japan,50,"Python, TensorFlow, Computer Vision, AWS, Statistics",Master,5,Transportation,2024-11-02,2024-12-20,1946,6.1,DeepTech Ventures +AI00824,Machine Learning Engineer,107965,USD,107965,SE,CT,Sweden,S,Romania,100,"SQL, Kubernetes, MLOps, NLP, GCP",Bachelor,9,Healthcare,2024-08-16,2024-08-31,1211,7.3,Advanced Robotics +AI00825,ML Ops Engineer,239943,EUR,203952,EX,FT,Netherlands,L,Netherlands,50,"Azure, MLOps, R, Python, TensorFlow",Bachelor,12,Real Estate,2024-05-16,2024-07-11,602,9.1,Machine Intelligence Group +AI00826,Robotics Engineer,287023,USD,287023,EX,PT,Ireland,L,Ireland,100,"Computer Vision, Linux, GCP, Scala",Master,10,Education,2025-03-31,2025-04-29,543,7.4,Cloud AI Solutions +AI00827,AI Architect,108794,USD,108794,MI,FL,Norway,L,Ukraine,0,"Hadoop, Kubernetes, Docker, Statistics, SQL",Associate,4,Government,2024-09-27,2024-11-26,1050,5.9,Advanced Robotics +AI00828,AI Specialist,91776,USD,91776,EN,FT,United States,M,Germany,0,"Docker, Computer Vision, AWS, Python, TensorFlow",PhD,1,Technology,2024-03-19,2024-04-25,2314,6.1,Predictive Systems +AI00829,Robotics Engineer,61890,USD,61890,EN,PT,South Korea,L,Italy,0,"Java, R, SQL",Bachelor,1,Consulting,2024-12-20,2025-01-15,709,5.4,Advanced Robotics +AI00830,Data Analyst,345294,USD,345294,EX,FT,Norway,L,Norway,100,"Kubernetes, TensorFlow, GCP",PhD,11,Telecommunications,2025-02-03,2025-04-06,1012,6.6,DataVision Ltd +AI00831,AI Product Manager,78569,USD,78569,MI,CT,Israel,L,Israel,0,"Spark, PyTorch, MLOps, NLP, Kubernetes",Master,4,Healthcare,2024-11-20,2024-12-05,2033,7.4,DataVision Ltd +AI00832,Autonomous Systems Engineer,66673,EUR,56672,EN,PT,France,M,France,100,"Git, Scala, Python",Master,0,Telecommunications,2024-11-27,2024-12-14,1825,8.6,Future Systems +AI00833,Machine Learning Researcher,183500,CHF,165150,SE,CT,Switzerland,M,Switzerland,50,"TensorFlow, Python, Computer Vision, Statistics, Scala",PhD,8,Transportation,2025-01-24,2025-03-08,686,9.1,Digital Transformation LLC +AI00834,ML Ops Engineer,165234,SGD,214804,EX,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Python, NLP",Associate,10,Manufacturing,2024-05-07,2024-05-22,913,6,Future Systems +AI00835,Principal Data Scientist,119549,SGD,155414,MI,FT,Singapore,L,Singapore,100,"Kubernetes, NLP, MLOps",Master,2,Consulting,2024-11-05,2024-12-12,1344,5.7,Digital Transformation LLC +AI00836,NLP Engineer,325936,USD,325936,EX,PT,Norway,L,Norway,100,"Scala, Spark, Deep Learning",Bachelor,19,Government,2024-09-01,2024-11-04,1066,8.3,Cognitive Computing +AI00837,ML Ops Engineer,157221,SGD,204387,SE,FT,Singapore,L,Singapore,0,"PyTorch, Java, GCP, Python, Hadoop",Associate,7,Gaming,2025-02-24,2025-03-23,908,8.5,Future Systems +AI00838,Machine Learning Engineer,98221,USD,98221,SE,PT,South Korea,L,South Korea,0,"Python, Deep Learning, AWS, Statistics",Bachelor,6,Finance,2024-05-04,2024-06-10,1650,6.7,Algorithmic Solutions +AI00839,Autonomous Systems Engineer,155502,GBP,116627,EX,CT,United Kingdom,M,India,50,"Kubernetes, Java, Docker, Hadoop",Master,11,Healthcare,2025-03-18,2025-05-10,503,9.5,DeepTech Ventures +AI00840,Principal Data Scientist,276679,USD,276679,EX,FT,Denmark,L,Denmark,0,"PyTorch, GCP, MLOps, AWS, Mathematics",Master,11,Telecommunications,2024-07-11,2024-09-21,1457,8.7,Predictive Systems +AI00841,AI Product Manager,187955,EUR,159762,EX,CT,Germany,S,Turkey,0,"Docker, Git, Linux",Master,19,Manufacturing,2025-02-01,2025-04-04,2439,7.9,Smart Analytics +AI00842,Data Engineer,135585,USD,135585,MI,FT,Denmark,L,Denmark,100,"AWS, Python, GCP",Associate,4,Real Estate,2024-06-02,2024-08-11,2302,5.1,Cloud AI Solutions +AI00843,Machine Learning Researcher,138945,USD,138945,SE,PT,United States,L,Kenya,50,"Java, Azure, Data Visualization, NLP",Master,5,Transportation,2024-07-08,2024-08-01,1468,7.3,TechCorp Inc +AI00844,Autonomous Systems Engineer,89723,EUR,76265,MI,FL,Netherlands,S,Netherlands,50,"Python, PyTorch, Spark, TensorFlow",Associate,3,Education,2024-06-17,2024-08-12,914,5.3,Advanced Robotics +AI00845,Computer Vision Engineer,74250,USD,74250,EN,FL,United States,L,Colombia,100,"NLP, R, TensorFlow",Associate,0,Consulting,2024-09-22,2024-10-07,2179,5.3,Predictive Systems +AI00846,Machine Learning Researcher,209546,USD,209546,EX,FT,Norway,M,Norway,100,"NLP, SQL, PyTorch, Git, Spark",Associate,11,Telecommunications,2025-01-24,2025-02-23,2485,7.7,Smart Analytics +AI00847,AI Product Manager,137463,JPY,15120930,EX,FL,Japan,S,Japan,0,"AWS, Git, Python, NLP, Scala",Associate,13,Healthcare,2024-05-28,2024-06-11,1088,7.9,Autonomous Tech +AI00848,Head of AI,83657,USD,83657,EN,FT,Ireland,L,Ireland,0,"Python, MLOps, Data Visualization, Spark",Master,0,Government,2024-06-25,2024-08-14,1808,6.4,Predictive Systems +AI00849,Data Engineer,120560,USD,120560,MI,FT,United States,M,Vietnam,0,"Hadoop, MLOps, Spark, Kubernetes",Bachelor,3,Retail,2024-08-18,2024-09-15,1128,7.5,AI Innovations +AI00850,AI Architect,87119,USD,87119,SE,PT,Israel,S,Denmark,100,"Scala, Statistics, Java",Associate,7,Media,2025-04-05,2025-05-17,1585,8.6,AI Innovations +AI00851,Principal Data Scientist,71418,USD,71418,MI,FL,South Korea,L,South Korea,100,"AWS, Linux, R",Master,4,Government,2024-10-17,2024-12-22,1154,8.8,Predictive Systems +AI00852,AI Consultant,46727,USD,46727,EX,FT,India,S,India,50,"SQL, Docker, Python",Bachelor,19,Automotive,2024-08-31,2024-10-20,1896,6.9,Advanced Robotics +AI00853,Data Scientist,164321,USD,164321,EX,PT,Sweden,S,Netherlands,50,"Kubernetes, GCP, PyTorch",Master,16,Energy,2024-08-01,2024-09-10,2008,6.4,Predictive Systems +AI00854,AI Product Manager,80460,JPY,8850600,EN,FL,Japan,M,Indonesia,0,"Python, Scala, TensorFlow",Bachelor,1,Energy,2025-01-17,2025-03-02,2267,9.9,Quantum Computing Inc +AI00855,Robotics Engineer,99510,EUR,84584,SE,CT,France,S,France,50,"Deep Learning, SQL, PyTorch",Associate,8,Technology,2025-04-26,2025-06-26,2131,9.8,Neural Networks Co +AI00856,Head of AI,145409,CHF,130868,MI,PT,Switzerland,M,Switzerland,100,"Git, NLP, Tableau, Python",Associate,2,Energy,2024-06-03,2024-08-04,1347,8.8,Cognitive Computing +AI00857,Data Analyst,289465,USD,289465,EX,PT,United States,M,United States,50,"Docker, MLOps, Python, Statistics, SQL",Bachelor,13,Retail,2025-04-08,2025-05-20,1420,9.2,Digital Transformation LLC +AI00858,ML Ops Engineer,85216,JPY,9373760,EN,FT,Japan,M,Japan,0,"AWS, Data Visualization, Python",Bachelor,1,Telecommunications,2024-09-17,2024-10-23,797,8.8,Cognitive Computing +AI00859,AI Software Engineer,88921,CAD,111151,MI,CT,Canada,S,Canada,100,"SQL, Kubernetes, Azure, Hadoop",PhD,3,Technology,2024-09-01,2024-09-21,1630,8.8,Advanced Robotics +AI00860,NLP Engineer,65144,USD,65144,EN,FL,Sweden,L,Argentina,100,"Hadoop, MLOps, Docker, Deep Learning, Statistics",Associate,0,Retail,2024-09-16,2024-11-25,1121,5.5,Quantum Computing Inc +AI00861,Data Analyst,103403,USD,103403,MI,CT,Israel,M,Israel,50,"Tableau, SQL, Linux, NLP, Kubernetes",Bachelor,3,Technology,2024-01-14,2024-02-11,2139,6.6,Smart Analytics +AI00862,Deep Learning Engineer,121368,USD,121368,SE,FL,Israel,M,Israel,50,"Spark, Python, Data Visualization",PhD,8,Energy,2024-04-01,2024-05-29,1567,5.2,Predictive Systems +AI00863,Head of AI,168109,AUD,226947,SE,CT,Australia,L,Australia,50,"Data Visualization, GCP, SQL",Bachelor,7,Gaming,2025-01-25,2025-03-22,2457,9.6,Cognitive Computing +AI00864,Robotics Engineer,40616,USD,40616,MI,CT,China,S,Canada,0,"TensorFlow, Git, Python, Hadoop",Associate,2,Finance,2024-07-31,2024-08-27,2010,5.9,Neural Networks Co +AI00865,NLP Engineer,176886,CHF,159197,EX,CT,Switzerland,S,Switzerland,0,"PyTorch, Scala, Deep Learning, Computer Vision",Master,16,Real Estate,2024-02-18,2024-04-22,1045,9.8,DataVision Ltd +AI00866,Autonomous Systems Engineer,107548,EUR,91416,MI,CT,Germany,M,Germany,0,"Linux, Python, TensorFlow",Master,2,Consulting,2024-08-16,2024-10-17,1812,9.7,AI Innovations +AI00867,AI Software Engineer,313203,CHF,281883,EX,FL,Switzerland,S,Switzerland,50,"Kubernetes, Python, Mathematics, Java",Master,15,Finance,2025-04-02,2025-06-14,1078,6,Algorithmic Solutions +AI00868,AI Consultant,147571,EUR,125435,EX,FT,France,M,United States,0,"R, GCP, Git",Associate,12,Consulting,2024-12-14,2025-02-12,679,5,Advanced Robotics +AI00869,Deep Learning Engineer,239432,EUR,203517,EX,PT,France,M,France,100,"R, NLP, Java, Hadoop",Associate,19,Automotive,2024-06-03,2024-08-02,1371,8,Machine Intelligence Group +AI00870,Machine Learning Researcher,119559,USD,119559,MI,CT,United States,L,United States,0,"PyTorch, Linux, NLP, MLOps, Java",Bachelor,2,Real Estate,2025-03-31,2025-05-15,546,5.9,Quantum Computing Inc +AI00871,AI Consultant,72051,SGD,93666,EN,FT,Singapore,S,Singapore,100,"AWS, Kubernetes, Tableau, Azure, Java",Master,0,Education,2024-09-11,2024-10-07,2394,6,Future Systems +AI00872,Machine Learning Engineer,80766,AUD,109034,EN,FT,Australia,L,India,100,"Java, R, NLP, Azure",PhD,1,Media,2025-02-03,2025-02-18,845,7.2,Future Systems +AI00873,Computer Vision Engineer,75201,CHF,67681,EN,PT,Switzerland,M,Switzerland,100,"Data Visualization, SQL, Scala, Deep Learning, Hadoop",Associate,0,Telecommunications,2024-08-11,2024-10-21,505,6.5,Cloud AI Solutions +AI00874,Machine Learning Engineer,367330,CHF,330597,EX,PT,Switzerland,L,Belgium,100,"Kubernetes, SQL, Mathematics, Deep Learning, Computer Vision",Master,12,Finance,2025-01-25,2025-02-26,1732,6.1,Cloud AI Solutions +AI00875,AI Specialist,99824,CHF,89842,EN,FL,Switzerland,S,Switzerland,100,"Tableau, Linux, AWS, Python, Mathematics",Master,1,Manufacturing,2025-01-30,2025-03-15,1530,9.4,DataVision Ltd +AI00876,Computer Vision Engineer,183643,GBP,137732,EX,FL,United Kingdom,L,United Kingdom,50,"Git, Python, NLP",Bachelor,16,Transportation,2024-09-30,2024-10-22,1295,9.9,DataVision Ltd +AI00877,Research Scientist,86875,CAD,108594,MI,FL,Canada,L,Canada,0,"Kubernetes, NLP, SQL",Bachelor,2,Education,2025-01-27,2025-03-10,2499,8.1,DataVision Ltd +AI00878,AI Architect,92050,USD,92050,EN,PT,Denmark,S,Denmark,100,"Spark, Docker, Computer Vision, NLP, Data Visualization",PhD,0,Healthcare,2025-02-04,2025-03-26,1907,5,DataVision Ltd +AI00879,Machine Learning Engineer,188547,EUR,160265,EX,CT,Germany,S,Indonesia,100,"Hadoop, SQL, Computer Vision, PyTorch, Docker",Bachelor,10,Transportation,2024-07-01,2024-08-17,1395,7.2,Cloud AI Solutions +AI00880,Data Scientist,93400,USD,93400,MI,FT,Ireland,S,Ireland,0,"Scala, Azure, Data Visualization, PyTorch, Git",Bachelor,4,Government,2024-11-09,2025-01-08,1829,5.7,Machine Intelligence Group +AI00881,Data Scientist,121492,EUR,103268,SE,PT,Germany,M,Germany,50,"AWS, Tableau, Kubernetes, Python",Associate,5,Technology,2025-04-11,2025-06-15,799,6.4,Future Systems +AI00882,AI Software Engineer,214716,CAD,268395,EX,CT,Canada,M,Canada,100,"SQL, Java, Git, Scala, Spark",Bachelor,13,Transportation,2024-01-29,2024-04-02,1629,7.4,Smart Analytics +AI00883,Machine Learning Engineer,96552,USD,96552,MI,PT,Denmark,S,Chile,0,"Spark, Git, Data Visualization, Kubernetes, SQL",Bachelor,3,Transportation,2025-03-01,2025-04-25,1746,6.7,DataVision Ltd +AI00884,Research Scientist,82126,EUR,69807,MI,CT,France,M,France,50,"Tableau, Hadoop, Python, AWS",PhD,4,Energy,2024-06-20,2024-08-31,1435,6.3,AI Innovations +AI00885,ML Ops Engineer,101793,EUR,86524,MI,FT,France,L,France,50,"TensorFlow, Azure, Python, Deep Learning",PhD,3,Education,2024-07-14,2024-07-31,926,5.5,Future Systems +AI00886,AI Research Scientist,119593,CAD,149491,MI,PT,Canada,L,Canada,100,"Data Visualization, Python, Tableau",Master,3,Government,2024-02-17,2024-04-23,908,6.3,Autonomous Tech +AI00887,AI Software Engineer,83380,USD,83380,EX,FL,China,M,China,0,"R, Scala, AWS, Data Visualization",PhD,18,Education,2024-08-19,2024-09-06,848,9.6,Advanced Robotics +AI00888,NLP Engineer,104077,EUR,88465,MI,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, Docker, Azure",Associate,3,Transportation,2025-03-29,2025-05-19,821,6.8,Smart Analytics +AI00889,Research Scientist,107155,EUR,91082,SE,PT,France,M,France,100,"Scala, SQL, GCP, Git, Linux",Associate,5,Real Estate,2024-09-29,2024-11-03,2162,6.2,Autonomous Tech +AI00890,AI Architect,95613,USD,95613,EN,FL,Denmark,M,Denmark,50,"Hadoop, Docker, Scala",Associate,0,Consulting,2024-11-08,2024-12-06,1404,8.3,TechCorp Inc +AI00891,AI Research Scientist,79915,USD,79915,MI,CT,Israel,S,Israel,0,"PyTorch, Hadoop, TensorFlow",Master,2,Consulting,2024-01-08,2024-01-29,2279,9.7,Advanced Robotics +AI00892,ML Ops Engineer,152836,USD,152836,SE,FT,Israel,L,Israel,100,"Statistics, PyTorch, NLP, Git",Associate,9,Education,2024-01-25,2024-02-24,2225,5.8,Predictive Systems +AI00893,AI Research Scientist,201144,SGD,261487,EX,FT,Singapore,M,Singapore,50,"Linux, AWS, R, Deep Learning, Docker",Associate,10,Government,2024-11-09,2025-01-10,1814,7.9,TechCorp Inc +AI00894,Machine Learning Researcher,74068,USD,74068,MI,FT,Israel,S,Israel,100,"SQL, PyTorch, Linux",PhD,4,Healthcare,2024-11-11,2024-12-06,1384,5.9,Digital Transformation LLC +AI00895,Principal Data Scientist,94861,EUR,80632,MI,FT,Netherlands,S,Netherlands,50,"Git, Scala, Tableau, Spark",Master,2,Government,2024-06-01,2024-07-10,1711,5.7,Autonomous Tech +AI00896,Head of AI,89534,USD,89534,MI,FL,South Korea,M,Romania,100,"Azure, AWS, GCP, Git, Kubernetes",PhD,4,Consulting,2024-02-21,2024-04-30,1229,7.5,AI Innovations +AI00897,Research Scientist,121009,USD,121009,MI,PT,Denmark,L,Switzerland,50,"R, Scala, Computer Vision, Azure",Associate,2,Government,2024-10-17,2024-12-20,2092,7.5,Autonomous Tech +AI00898,AI Software Engineer,98503,USD,98503,MI,FT,Denmark,M,United Kingdom,100,"Kubernetes, Linux, Hadoop",Bachelor,3,Energy,2025-01-24,2025-03-07,2120,7.1,Algorithmic Solutions +AI00899,Autonomous Systems Engineer,92133,USD,92133,MI,FL,Finland,L,Finland,100,"R, Scala, GCP",Bachelor,2,Automotive,2024-08-24,2024-10-18,2014,6.8,Predictive Systems +AI00900,Research Scientist,108765,USD,108765,MI,PT,United States,M,United States,0,"Spark, TensorFlow, Java, Azure",Bachelor,4,Automotive,2024-06-24,2024-07-28,1043,8.9,Autonomous Tech +AI00901,Machine Learning Engineer,93440,CHF,84096,EN,CT,Switzerland,M,Switzerland,0,"Statistics, Git, Kubernetes, Python, Azure",Bachelor,0,Retail,2024-10-17,2024-11-20,659,6.1,Cloud AI Solutions +AI00902,AI Architect,88745,SGD,115369,MI,FT,Singapore,S,Singapore,100,"SQL, Deep Learning, GCP, MLOps, Spark",Associate,4,Finance,2025-03-02,2025-03-22,1741,9.5,Algorithmic Solutions +AI00903,Research Scientist,105976,USD,105976,SE,PT,Ireland,M,Ireland,100,"SQL, Hadoop, Kubernetes",Associate,7,Transportation,2024-03-16,2024-05-20,1015,7.6,Digital Transformation LLC +AI00904,NLP Engineer,59221,USD,59221,MI,PT,South Korea,S,South Korea,0,"Statistics, Spark, Tableau, Java",Associate,3,Media,2024-09-09,2024-10-19,1905,5.3,Quantum Computing Inc +AI00905,NLP Engineer,61996,USD,61996,EN,FT,Sweden,L,United States,100,"Scala, Kubernetes, Computer Vision, SQL",PhD,0,Gaming,2024-02-25,2024-03-23,2259,7.8,Quantum Computing Inc +AI00906,ML Ops Engineer,90426,EUR,76862,MI,FT,France,S,France,50,"Git, Data Visualization, Spark",Master,3,Real Estate,2025-04-02,2025-04-28,1535,6.2,Autonomous Tech +AI00907,AI Consultant,60924,EUR,51785,EN,PT,France,S,France,0,"Scala, Hadoop, Java",Associate,0,Healthcare,2024-08-09,2024-09-03,2378,7.5,Advanced Robotics +AI00908,Data Engineer,243192,CAD,303990,EX,CT,Canada,L,Canada,0,"Scala, Azure, Kubernetes, Java, Statistics",Bachelor,16,Automotive,2024-03-07,2024-05-19,1815,9,Machine Intelligence Group +AI00909,Deep Learning Engineer,166087,EUR,141174,EX,FT,France,L,France,0,"Mathematics, Git, Data Visualization, Scala",Associate,10,Finance,2024-01-20,2024-02-14,2264,9.3,Smart Analytics +AI00910,Research Scientist,85173,USD,85173,EN,CT,Finland,L,Finland,0,"Statistics, Java, NLP, Git",Bachelor,0,Real Estate,2024-07-18,2024-09-06,2477,5.6,Machine Intelligence Group +AI00911,AI Specialist,309247,CHF,278322,EX,CT,Switzerland,L,Switzerland,100,"Computer Vision, GCP, Statistics, Azure, TensorFlow",Associate,10,Telecommunications,2024-02-18,2024-03-26,749,5.1,Digital Transformation LLC +AI00912,Computer Vision Engineer,121556,EUR,103323,MI,FL,Germany,L,Germany,0,"Data Visualization, Scala, PyTorch",PhD,3,Gaming,2025-04-17,2025-05-04,1461,5.2,Neural Networks Co +AI00913,AI Consultant,89998,JPY,9899780,EN,CT,Japan,L,Japan,50,"Scala, TensorFlow, Linux",PhD,1,Technology,2024-06-11,2024-07-20,617,8,Cognitive Computing +AI00914,AI Architect,63415,EUR,53903,MI,FT,France,S,France,100,"Kubernetes, Scala, Hadoop, Java, NLP",Master,3,Energy,2025-02-19,2025-04-13,1601,5.4,Future Systems +AI00915,Data Scientist,132964,USD,132964,MI,PT,Denmark,M,Denmark,0,"Scala, Python, MLOps",Master,2,Energy,2024-04-01,2024-06-11,1070,6.9,Machine Intelligence Group +AI00916,ML Ops Engineer,65099,SGD,84629,EN,PT,Singapore,S,Singapore,50,"Linux, PyTorch, SQL",Associate,0,Transportation,2024-02-03,2024-02-21,2192,5.1,DataVision Ltd +AI00917,AI Product Manager,170410,USD,170410,EX,FT,South Korea,L,South Korea,100,"MLOps, PyTorch, Tableau, SQL",Associate,16,Healthcare,2024-01-25,2024-02-18,1497,9.6,DataVision Ltd +AI00918,Data Engineer,25440,USD,25440,EN,CT,India,M,India,0,"Kubernetes, Scala, AWS",Master,1,Gaming,2024-10-28,2024-11-12,987,6.4,Advanced Robotics +AI00919,Research Scientist,173489,JPY,19083790,SE,FT,Japan,L,France,50,"Git, SQL, Kubernetes, Mathematics, PyTorch",Bachelor,8,Energy,2025-01-12,2025-01-29,647,5,Cloud AI Solutions +AI00920,Computer Vision Engineer,216939,USD,216939,EX,FT,United States,L,United States,100,"GCP, Git, MLOps, Mathematics, Scala",Master,13,Real Estate,2024-02-18,2024-04-25,1487,5.8,Algorithmic Solutions +AI00921,Autonomous Systems Engineer,117695,USD,117695,SE,FL,United States,S,Austria,50,"Hadoop, Azure, Java, Linux, Deep Learning",Bachelor,9,Gaming,2024-04-30,2024-06-10,894,9.4,Neural Networks Co +AI00922,AI Specialist,78936,AUD,106564,MI,CT,Australia,M,Australia,100,"Python, Git, TensorFlow, Deep Learning",Associate,4,Telecommunications,2024-09-07,2024-11-13,1081,9,Cloud AI Solutions +AI00923,NLP Engineer,113661,USD,113661,EN,FT,Norway,L,Norway,50,"Python, PyTorch, Git, Linux",Associate,0,Manufacturing,2025-02-16,2025-04-25,1471,5.9,Quantum Computing Inc +AI00924,Computer Vision Engineer,226030,JPY,24863300,EX,FT,Japan,S,Japan,50,"Git, SQL, Spark",Bachelor,17,Energy,2025-01-04,2025-02-16,744,9.8,AI Innovations +AI00925,Machine Learning Researcher,162220,USD,162220,EX,CT,Finland,S,Russia,50,"Spark, Data Visualization, PyTorch",Master,17,Transportation,2024-01-27,2024-03-12,862,5.5,Future Systems +AI00926,Deep Learning Engineer,165689,USD,165689,EX,FT,Ireland,S,Ireland,0,"R, TensorFlow, GCP, Linux, Statistics",PhD,19,Automotive,2024-11-13,2024-11-29,567,9.5,Cognitive Computing +AI00927,Principal Data Scientist,319536,CHF,287582,EX,FT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Java, Tableau",PhD,16,Technology,2024-01-22,2024-02-17,1950,6,DeepTech Ventures +AI00928,Data Scientist,97294,USD,97294,SE,CT,Israel,M,Israel,50,"Azure, Java, Spark, Linux, R",PhD,7,Manufacturing,2024-07-17,2024-08-21,985,7.9,Quantum Computing Inc +AI00929,Machine Learning Researcher,94506,USD,94506,EN,FT,Denmark,L,Denmark,50,"Docker, Scala, Azure, Mathematics, MLOps",Associate,1,Consulting,2024-09-29,2024-11-06,2181,9.4,Quantum Computing Inc +AI00930,Data Engineer,122519,USD,122519,SE,PT,Israel,M,Israel,50,"Data Visualization, MLOps, Hadoop, Docker",Bachelor,8,Manufacturing,2024-07-19,2024-08-09,644,7.3,Machine Intelligence Group +AI00931,Autonomous Systems Engineer,61916,USD,61916,MI,FT,South Korea,S,South Korea,100,"Java, Statistics, GCP, Kubernetes, NLP",Associate,2,Energy,2024-10-16,2024-11-03,1639,5.1,Autonomous Tech +AI00932,Principal Data Scientist,78823,USD,78823,MI,FL,Israel,M,India,50,"Python, GCP, TensorFlow, Mathematics",Associate,4,Technology,2024-09-07,2024-09-26,756,5.2,Machine Intelligence Group +AI00933,Data Engineer,111124,USD,111124,EN,CT,Denmark,L,China,0,"Spark, GCP, Data Visualization",Master,0,Technology,2024-04-23,2024-07-01,1021,8.5,Neural Networks Co +AI00934,Robotics Engineer,91289,EUR,77596,EN,FL,Netherlands,L,Netherlands,0,"PyTorch, Spark, Azure, Kubernetes, Java",Master,0,Education,2024-02-06,2024-03-10,972,8.5,DataVision Ltd +AI00935,AI Specialist,195659,USD,195659,SE,PT,Norway,L,Norway,50,"Python, Hadoop, TensorFlow, Computer Vision",PhD,6,Media,2024-02-08,2024-03-18,1789,7,Future Systems +AI00936,Data Engineer,199412,EUR,169500,EX,PT,Germany,S,Norway,50,"Java, Scala, Docker",Bachelor,17,Government,2024-02-05,2024-03-08,1254,8.1,Smart Analytics +AI00937,Data Engineer,202421,USD,202421,EX,FL,Norway,L,Norway,100,"Kubernetes, Git, PyTorch",Master,19,Manufacturing,2024-11-22,2025-01-28,2135,6.4,Machine Intelligence Group +AI00938,Data Scientist,133682,GBP,100262,MI,FL,United Kingdom,L,United Kingdom,100,"Hadoop, Spark, MLOps, GCP, R",Associate,3,Manufacturing,2025-03-20,2025-05-05,2382,8,Autonomous Tech +AI00939,Data Analyst,205143,GBP,153857,EX,PT,United Kingdom,L,South Africa,0,"TensorFlow, Azure, NLP",Associate,11,Finance,2024-08-28,2024-10-29,2193,9.1,Future Systems +AI00940,Head of AI,27765,USD,27765,EN,CT,China,S,China,0,"MLOps, Deep Learning, Python, Tableau",Bachelor,1,Consulting,2025-01-15,2025-02-12,968,9.3,Cloud AI Solutions +AI00941,NLP Engineer,170181,USD,170181,EX,PT,Ireland,M,Ireland,100,"Deep Learning, Python, Azure, TensorFlow",Bachelor,11,Gaming,2024-12-26,2025-01-24,2089,8,DataVision Ltd +AI00942,ML Ops Engineer,103167,USD,103167,MI,CT,United States,M,United States,100,"AWS, Kubernetes, MLOps",Associate,2,Healthcare,2024-04-05,2024-04-21,1873,8,Predictive Systems +AI00943,ML Ops Engineer,194546,USD,194546,EX,PT,Sweden,L,Sweden,0,"TensorFlow, Docker, Python, Hadoop",Master,16,Retail,2025-01-07,2025-03-05,1532,7.2,Digital Transformation LLC +AI00944,Research Scientist,130072,USD,130072,EX,CT,Israel,S,Israel,100,"R, Data Visualization, Java",Master,13,Government,2024-10-14,2024-11-20,2006,5.4,Cloud AI Solutions +AI00945,AI Specialist,39197,USD,39197,EN,PT,China,L,Australia,0,"Kubernetes, Java, SQL, NLP",Associate,1,Energy,2024-05-17,2024-07-08,1770,6.7,Quantum Computing Inc +AI00946,Autonomous Systems Engineer,204421,EUR,173758,EX,FL,Austria,L,Austria,50,"PyTorch, Data Visualization, Azure",Master,14,Energy,2024-07-30,2024-09-05,2389,8.5,Neural Networks Co +AI00947,Head of AI,112925,CHF,101633,EN,FT,Switzerland,L,Switzerland,100,"SQL, GCP, Spark, Azure, Linux",Bachelor,0,Government,2024-11-07,2024-11-26,1221,5.7,DataVision Ltd +AI00948,Data Scientist,265788,SGD,345524,EX,FT,Singapore,M,Turkey,0,"MLOps, Data Visualization, Scala, Python, AWS",Associate,18,Technology,2025-01-26,2025-04-07,2270,5.4,Smart Analytics +AI00949,Machine Learning Researcher,98150,USD,98150,EN,FL,Denmark,L,Denmark,0,"Data Visualization, Java, Hadoop",PhD,1,Energy,2025-03-11,2025-04-27,1648,7.6,Autonomous Tech +AI00950,Data Engineer,126741,USD,126741,SE,FL,United States,S,Romania,50,"PyTorch, Data Visualization, Azure, Computer Vision",Master,9,Finance,2024-05-29,2024-07-20,1974,5.9,Predictive Systems +AI00951,ML Ops Engineer,75006,USD,75006,EN,FL,Israel,M,Austria,100,"MLOps, TensorFlow, Scala",Associate,1,Finance,2024-02-15,2024-03-01,1642,7.3,DeepTech Ventures +AI00952,AI Research Scientist,84346,EUR,71694,MI,FT,Austria,S,France,0,"Statistics, Spark, GCP",Associate,4,Manufacturing,2024-09-20,2024-10-27,2188,7.5,DataVision Ltd +AI00953,Autonomous Systems Engineer,48241,USD,48241,SE,PT,India,M,India,50,"SQL, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-03-16,2025-05-06,2398,9.9,Neural Networks Co +AI00954,Research Scientist,162681,EUR,138279,EX,CT,Germany,L,Germany,50,"Python, Scala, Data Visualization",Associate,18,Telecommunications,2025-02-21,2025-03-09,2201,9.8,Advanced Robotics +AI00955,Deep Learning Engineer,125204,JPY,13772440,SE,CT,Japan,S,Vietnam,100,"Data Visualization, Kubernetes, Scala, NLP",Master,7,Retail,2024-04-30,2024-05-20,2284,5.9,Cloud AI Solutions +AI00956,Machine Learning Engineer,140001,EUR,119001,SE,FT,Netherlands,M,Luxembourg,50,"Python, TensorFlow, GCP, Computer Vision, Java",Bachelor,8,Manufacturing,2024-12-14,2025-02-06,1825,6.5,Autonomous Tech +AI00957,AI Software Engineer,162125,AUD,218869,SE,FT,Australia,L,Austria,100,"Computer Vision, Docker, TensorFlow",Bachelor,8,Consulting,2024-12-10,2025-02-07,565,5.4,Predictive Systems +AI00958,Deep Learning Engineer,128132,SGD,166572,SE,FL,Singapore,S,Japan,100,"Python, NLP, TensorFlow",PhD,7,Technology,2024-08-10,2024-09-24,1112,6.2,Cognitive Computing +AI00959,NLP Engineer,225554,USD,225554,SE,FT,Denmark,L,Latvia,50,"PyTorch, R, Docker",Bachelor,8,Technology,2024-09-12,2024-11-17,1301,9.3,Cloud AI Solutions +AI00960,ML Ops Engineer,130639,EUR,111043,SE,FT,Germany,M,Germany,0,"Python, Hadoop, PyTorch, Git, TensorFlow",PhD,7,Healthcare,2024-09-12,2024-11-12,1996,6.9,TechCorp Inc +AI00961,Data Analyst,66422,USD,66422,EN,FT,United States,S,United States,0,"Python, Hadoop, Kubernetes",Associate,0,Retail,2024-05-13,2024-07-18,1765,5.4,Autonomous Tech +AI00962,AI Architect,54625,CAD,68281,EN,CT,Canada,S,Ireland,0,"Scala, SQL, GCP, Computer Vision, Mathematics",Bachelor,0,Technology,2024-05-01,2024-07-08,1946,5.7,Cloud AI Solutions +AI00963,ML Ops Engineer,135145,USD,135145,MI,PT,Norway,M,Norway,50,"SQL, Docker, PyTorch, GCP, Kubernetes",Bachelor,3,Automotive,2025-04-27,2025-05-15,998,7.5,Smart Analytics +AI00964,ML Ops Engineer,61177,CAD,76471,EN,FL,Canada,S,Canada,100,"Spark, R, AWS, GCP, MLOps",Bachelor,0,Consulting,2025-04-04,2025-05-30,1465,6.8,Cognitive Computing +AI00965,AI Product Manager,74961,USD,74961,EX,FT,China,L,China,100,"Kubernetes, Git, Java, Azure, Tableau",PhD,16,Consulting,2024-07-17,2024-09-05,954,6.8,Smart Analytics +AI00966,NLP Engineer,47280,USD,47280,MI,PT,China,M,China,100,"Computer Vision, TensorFlow, Statistics, Python",PhD,2,Finance,2025-03-30,2025-06-05,985,9.4,Algorithmic Solutions +AI00967,Research Scientist,141577,USD,141577,EX,PT,Finland,S,Finland,50,"AWS, SQL, Python",Associate,13,Transportation,2024-09-16,2024-10-16,1955,6.1,TechCorp Inc +AI00968,NLP Engineer,130504,CHF,117454,EN,FT,Switzerland,L,Philippines,100,"Spark, MLOps, Tableau, Git",Bachelor,0,Media,2025-02-11,2025-02-26,691,8.4,Neural Networks Co +AI00969,Research Scientist,107421,USD,107421,MI,CT,Norway,S,Norway,50,"Git, Docker, Tableau, PyTorch",Bachelor,2,Consulting,2024-08-02,2024-09-23,1782,8.9,DataVision Ltd +AI00970,Data Analyst,93042,USD,93042,MI,PT,United States,S,United States,50,"Statistics, Linux, Git, Hadoop, Mathematics",Master,2,Finance,2024-10-14,2024-11-02,803,5.2,DataVision Ltd +AI00971,AI Consultant,168047,USD,168047,EX,FL,Ireland,L,Ireland,0,"Data Visualization, Linux, Docker, Python, GCP",Master,11,Government,2024-06-25,2024-08-04,1693,9.7,Predictive Systems +AI00972,AI Specialist,27281,USD,27281,EN,PT,China,S,Latvia,100,"Java, SQL, Tableau, GCP",PhD,1,Telecommunications,2025-01-04,2025-03-01,1739,7.1,Advanced Robotics +AI00973,Research Scientist,99145,USD,99145,MI,FL,United States,M,United States,100,"Kubernetes, Mathematics, Data Visualization, MLOps, Hadoop",Master,4,Media,2025-01-20,2025-03-09,954,9.2,Advanced Robotics +AI00974,Deep Learning Engineer,121002,USD,121002,SE,PT,Finland,S,Finland,100,"AWS, NLP, Kubernetes",Master,8,Consulting,2024-03-07,2024-05-12,1557,8.6,Cognitive Computing +AI00975,Data Scientist,259814,USD,259814,EX,PT,Norway,M,Vietnam,50,"PyTorch, R, TensorFlow, AWS, Statistics",Associate,12,Automotive,2024-04-15,2024-05-07,1416,5,DeepTech Ventures +AI00976,Computer Vision Engineer,209072,EUR,177711,EX,CT,France,L,France,100,"TensorFlow, PyTorch, SQL, AWS",Bachelor,15,Transportation,2024-03-23,2024-05-16,1826,7,Predictive Systems +AI00977,AI Software Engineer,50802,USD,50802,SE,CT,China,M,Russia,50,"MLOps, Computer Vision, Data Visualization, Java",PhD,5,Energy,2024-10-13,2024-11-20,501,6.5,Cognitive Computing +AI00978,NLP Engineer,112292,JPY,12352120,MI,PT,Japan,M,Japan,100,"Docker, Hadoop, Kubernetes, AWS",Bachelor,2,Gaming,2024-09-04,2024-10-30,875,8.7,TechCorp Inc +AI00979,Machine Learning Engineer,255076,USD,255076,EX,PT,Ireland,L,Finland,0,"Azure, Docker, Scala",PhD,15,Finance,2024-12-15,2025-02-21,1651,6.2,Digital Transformation LLC +AI00980,Head of AI,75393,EUR,64084,MI,FL,Netherlands,S,Finland,50,"Scala, Hadoop, Linux, GCP",Master,2,Consulting,2024-12-15,2025-01-30,1146,5.1,Quantum Computing Inc +AI00981,Head of AI,96519,USD,96519,EN,FL,United States,L,United States,100,"TensorFlow, Tableau, Git, Scala",Master,1,Finance,2024-07-24,2024-09-08,984,9.6,Autonomous Tech +AI00982,Deep Learning Engineer,135767,USD,135767,SE,FL,Sweden,L,Ukraine,50,"Scala, Azure, Git, Python, R",Associate,7,Gaming,2024-09-05,2024-10-13,736,8.7,DataVision Ltd +AI00983,AI Research Scientist,169082,USD,169082,EX,FT,Finland,L,Finland,50,"GCP, Hadoop, Python, Tableau, Mathematics",Master,17,Finance,2024-02-10,2024-03-22,914,6.9,Quantum Computing Inc +AI00984,AI Software Engineer,91630,EUR,77886,MI,FL,Germany,L,United States,50,"SQL, Linux, Data Visualization, NLP",Bachelor,3,Finance,2024-12-31,2025-03-04,2243,5.6,Machine Intelligence Group +AI00985,Research Scientist,172863,USD,172863,EX,CT,United States,M,United States,100,"SQL, Scala, Kubernetes",Bachelor,13,Transportation,2024-10-24,2024-11-08,2023,8.9,DataVision Ltd +AI00986,Head of AI,103897,USD,103897,MI,FL,Finland,L,Finland,100,"Scala, Java, Git, Azure, R",Associate,3,Retail,2025-04-06,2025-05-02,1242,8.9,Future Systems +AI00987,Computer Vision Engineer,93834,CAD,117293,MI,PT,Canada,L,Canada,100,"TensorFlow, PyTorch, AWS",Associate,2,Gaming,2024-09-01,2024-10-21,1303,5.8,Smart Analytics +AI00988,Autonomous Systems Engineer,53634,GBP,40226,EN,CT,United Kingdom,S,United Kingdom,0,"SQL, Hadoop, Kubernetes",PhD,0,Telecommunications,2025-04-16,2025-06-15,1608,7.3,Machine Intelligence Group +AI00989,AI Research Scientist,127594,USD,127594,SE,FT,Finland,L,Finland,0,"Python, TensorFlow, Hadoop, PyTorch",Bachelor,8,Automotive,2024-12-19,2025-02-24,926,6.4,Future Systems +AI00990,AI Product Manager,292915,CHF,263624,EX,FT,Switzerland,L,Thailand,100,"Data Visualization, Python, R, Azure",Bachelor,16,Media,2025-01-14,2025-02-25,2345,8.2,Future Systems +AI00991,Data Scientist,174020,USD,174020,EX,FT,Israel,S,Israel,100,"TensorFlow, PyTorch, MLOps, Computer Vision",Bachelor,18,Media,2025-01-25,2025-04-08,2090,6.6,Cloud AI Solutions +AI00992,ML Ops Engineer,88526,EUR,75247,MI,CT,Germany,S,Egypt,100,"Python, Git, MLOps, NLP, Spark",Master,4,Real Estate,2025-03-05,2025-05-17,1279,7.6,Cognitive Computing +AI00993,AI Software Engineer,74475,AUD,100541,EN,PT,Australia,M,Australia,0,"TensorFlow, Data Visualization, R",Associate,1,Transportation,2024-09-09,2024-10-10,734,9.8,Neural Networks Co +AI00994,Deep Learning Engineer,96427,USD,96427,EX,CT,China,S,China,100,"Computer Vision, Hadoop, Statistics, Deep Learning",PhD,18,Automotive,2024-10-10,2024-11-10,1393,7.3,Cognitive Computing +AI00995,ML Ops Engineer,225810,SGD,293553,EX,FT,Singapore,S,India,100,"Data Visualization, Spark, Kubernetes",PhD,19,Gaming,2025-02-19,2025-04-15,1937,8.2,Cloud AI Solutions +AI00996,AI Research Scientist,168512,EUR,143235,EX,CT,Netherlands,S,Hungary,0,"Java, Linux, MLOps, Tableau",Bachelor,10,Consulting,2024-10-15,2024-11-29,929,6.5,Cognitive Computing +AI00997,Head of AI,168159,GBP,126119,EX,CT,United Kingdom,M,United Kingdom,50,"Azure, PyTorch, GCP, Deep Learning, Kubernetes",PhD,14,Finance,2024-05-26,2024-06-27,1479,5.4,Cognitive Computing +AI00998,Research Scientist,59148,CAD,73935,EN,CT,Canada,L,Canada,0,"AWS, R, PyTorch",PhD,1,Government,2024-11-07,2024-12-12,1951,7.1,Predictive Systems +AI00999,Data Analyst,65802,GBP,49352,EN,PT,United Kingdom,L,Ghana,100,"Azure, Hadoop, Git",PhD,0,Telecommunications,2024-03-20,2024-05-18,1364,6.8,DataVision Ltd +AI01000,AI Architect,110206,EUR,93675,MI,CT,France,L,France,100,"Git, R, Python, Azure, Tableau",PhD,4,Finance,2024-11-29,2025-01-07,903,6.5,Autonomous Tech +AI01001,Data Analyst,149976,EUR,127480,SE,FL,France,L,France,100,"GCP, Git, Data Visualization, PyTorch",Bachelor,9,Energy,2024-05-31,2024-08-07,1685,7.2,TechCorp Inc +AI01002,Principal Data Scientist,179731,AUD,242637,EX,CT,Australia,M,Australia,50,"Python, GCP, Kubernetes, Deep Learning",Bachelor,18,Education,2024-03-29,2024-05-12,2328,7.2,Algorithmic Solutions +AI01003,Research Scientist,148216,USD,148216,EX,FL,Israel,S,Israel,100,"Kubernetes, Python, Scala, Computer Vision",PhD,10,Telecommunications,2024-12-13,2025-02-14,1572,6.3,Machine Intelligence Group +AI01004,AI Research Scientist,69697,CAD,87121,MI,FL,Canada,S,Canada,0,"GCP, AWS, Hadoop, Statistics, Docker",PhD,4,Automotive,2025-01-05,2025-03-09,1809,6.1,Future Systems +AI01005,Autonomous Systems Engineer,193479,CHF,174131,SE,CT,Switzerland,S,Switzerland,50,"Computer Vision, Linux, Tableau, NLP",Associate,6,Manufacturing,2025-02-01,2025-04-12,1620,9,Predictive Systems +AI01006,Data Engineer,27327,USD,27327,EN,CT,India,M,India,100,"Hadoop, Python, SQL, Azure, Kubernetes",PhD,1,Gaming,2024-03-10,2024-04-08,858,8.8,AI Innovations +AI01007,Deep Learning Engineer,175817,USD,175817,SE,PT,Denmark,L,Denmark,50,"SQL, Python, GCP, Computer Vision",PhD,9,Automotive,2024-12-14,2025-02-05,2179,10,Future Systems +AI01008,AI Software Engineer,79605,EUR,67664,MI,FT,France,S,France,50,"Mathematics, SQL, Computer Vision",PhD,2,Technology,2024-05-03,2024-07-10,1656,9.9,Smart Analytics +AI01009,AI Specialist,136610,USD,136610,SE,FL,Denmark,M,Denmark,100,"NLP, Azure, Data Visualization, Kubernetes",Bachelor,6,Education,2024-10-29,2025-01-06,1763,9.8,TechCorp Inc +AI01010,Data Scientist,54165,EUR,46040,EN,CT,France,S,France,100,"PyTorch, Git, Mathematics, SQL",PhD,1,Healthcare,2024-12-17,2025-01-12,1474,7,DataVision Ltd +AI01011,AI Consultant,82548,USD,82548,EN,FL,Denmark,S,Malaysia,50,"R, Tableau, Kubernetes",Associate,1,Real Estate,2025-02-20,2025-03-18,1171,6.9,AI Innovations +AI01012,Research Scientist,149033,USD,149033,EX,FL,South Korea,M,South Korea,100,"SQL, R, Docker, Data Visualization",Bachelor,17,Technology,2024-06-15,2024-08-13,1619,9.1,Machine Intelligence Group +AI01013,Machine Learning Engineer,26672,USD,26672,MI,PT,India,M,India,50,"AWS, PyTorch, MLOps, Deep Learning",PhD,2,Real Estate,2024-11-21,2025-01-10,1601,9.1,Algorithmic Solutions +AI01014,AI Consultant,103610,USD,103610,MI,FT,Sweden,L,Sweden,50,"Mathematics, Python, TensorFlow, Scala",Associate,3,Government,2024-07-02,2024-08-27,859,6.4,Predictive Systems +AI01015,Principal Data Scientist,59901,GBP,44926,EN,CT,United Kingdom,M,Colombia,100,"R, Hadoop, Python, Computer Vision",Bachelor,1,Finance,2024-03-20,2024-05-27,2189,8.2,Cognitive Computing +AI01016,Machine Learning Engineer,84403,USD,84403,MI,FT,Finland,M,India,0,"Tableau, Spark, Python",PhD,4,Finance,2024-09-10,2024-11-05,2085,5.6,Neural Networks Co +AI01017,AI Product Manager,235236,EUR,199951,EX,FL,France,M,South Africa,50,"GCP, Python, Data Visualization, MLOps, TensorFlow",Associate,10,Healthcare,2024-09-01,2024-10-11,2164,7.5,Machine Intelligence Group +AI01018,AI Research Scientist,140841,USD,140841,SE,FL,United States,S,United States,100,"Python, TensorFlow, Kubernetes",PhD,9,Finance,2024-10-17,2024-11-29,1005,5.2,Future Systems +AI01019,Deep Learning Engineer,64188,EUR,54560,EN,PT,Austria,M,Austria,0,"Kubernetes, Scala, Mathematics, SQL",Bachelor,1,Media,2025-01-16,2025-02-01,2217,5.6,Digital Transformation LLC +AI01020,Principal Data Scientist,140677,CHF,126609,SE,FL,Switzerland,S,Switzerland,100,"Python, TensorFlow, GCP, PyTorch",PhD,6,Retail,2024-05-22,2024-06-14,1249,5.2,Machine Intelligence Group +AI01021,Research Scientist,275555,USD,275555,EX,FT,Ireland,L,Egypt,0,"R, Linux, Scala",Associate,15,Retail,2024-12-16,2025-01-14,801,6.9,TechCorp Inc +AI01022,AI Specialist,174133,CHF,156720,SE,FT,Switzerland,M,Switzerland,0,"R, Deep Learning, TensorFlow",Associate,8,Real Estate,2025-01-23,2025-02-18,1540,9.6,Smart Analytics +AI01023,Machine Learning Engineer,49918,USD,49918,EN,CT,South Korea,M,South Korea,0,"Git, Python, SQL",PhD,0,Manufacturing,2025-04-17,2025-05-07,1226,8.1,AI Innovations +AI01024,Computer Vision Engineer,211602,USD,211602,EX,FL,Norway,L,Turkey,50,"AWS, Hadoop, NLP, Computer Vision, Statistics",Master,16,Real Estate,2025-03-27,2025-04-30,1244,7.3,Neural Networks Co +AI01025,AI Software Engineer,192792,USD,192792,EX,FT,Israel,L,Ireland,50,"Scala, NLP, SQL, Linux, Docker",PhD,15,Technology,2024-06-12,2024-08-11,2314,6.2,Digital Transformation LLC +AI01026,AI Specialist,70846,EUR,60219,MI,CT,Austria,S,Turkey,100,"TensorFlow, Java, R",Associate,4,Gaming,2024-02-11,2024-04-07,1268,9.4,Digital Transformation LLC +AI01027,AI Architect,93783,USD,93783,EN,PT,United States,M,United States,100,"MLOps, Java, Azure, Mathematics, PyTorch",Bachelor,1,Finance,2024-05-19,2024-06-10,1828,10,Neural Networks Co +AI01028,AI Architect,41072,USD,41072,MI,FT,China,S,China,0,"R, Docker, MLOps",Associate,3,Telecommunications,2024-04-11,2024-05-24,2158,6.6,Advanced Robotics +AI01029,AI Architect,102805,CAD,128506,MI,PT,Canada,M,Switzerland,100,"Azure, TensorFlow, Data Visualization, NLP",Master,3,Education,2024-12-16,2025-02-02,1000,9.9,Autonomous Tech +AI01030,AI Product Manager,113537,USD,113537,MI,FT,Ireland,L,Ireland,0,"GCP, Scala, Hadoop",PhD,4,Media,2024-01-20,2024-03-21,1063,8.1,DeepTech Ventures +AI01031,Research Scientist,73590,USD,73590,EN,FL,Denmark,M,Denmark,100,"Python, Git, Tableau, R",Master,1,Retail,2024-11-01,2024-12-27,1490,9.2,Digital Transformation LLC +AI01032,Computer Vision Engineer,96582,USD,96582,EN,CT,Denmark,L,Denmark,100,"Java, Computer Vision, GCP",PhD,0,Real Estate,2024-08-27,2024-09-29,649,9.1,DataVision Ltd +AI01033,AI Research Scientist,62705,USD,62705,EN,PT,Israel,M,India,0,"Java, GCP, Linux, Spark, Python",Bachelor,0,Gaming,2024-10-19,2024-12-08,723,5.1,Smart Analytics +AI01034,AI Product Manager,77955,GBP,58466,EN,FT,United Kingdom,M,United Kingdom,50,"Data Visualization, Computer Vision, Scala",Master,0,Education,2024-06-07,2024-07-04,2444,7,Autonomous Tech +AI01035,Data Analyst,129874,AUD,175330,EX,FT,Australia,S,Australia,0,"Linux, Statistics, Computer Vision",PhD,15,Education,2024-11-16,2024-12-05,2443,7.5,Quantum Computing Inc +AI01036,AI Architect,106907,GBP,80180,MI,CT,United Kingdom,L,United Kingdom,100,"NLP, Java, SQL, Spark, Mathematics",Associate,4,Gaming,2024-12-08,2025-02-16,1589,7.3,Algorithmic Solutions +AI01037,AI Consultant,110152,USD,110152,MI,CT,United States,L,United States,0,"Tableau, Azure, R, NLP",Bachelor,4,Gaming,2024-02-24,2024-03-27,976,8.9,Cognitive Computing +AI01038,AI Research Scientist,49922,USD,49922,MI,FT,China,L,China,50,"Azure, Spark, Scala, SQL, Deep Learning",Bachelor,4,Government,2024-07-26,2024-09-14,1580,8.8,DataVision Ltd +AI01039,AI Software Engineer,84890,USD,84890,EN,CT,Ireland,L,Ireland,100,"GCP, Hadoop, Azure, Scala",PhD,0,Gaming,2024-05-28,2024-07-01,2159,9.2,Cloud AI Solutions +AI01040,Data Scientist,73564,EUR,62529,MI,PT,France,M,Singapore,50,"Scala, Tableau, Docker, SQL, Mathematics",Associate,4,Consulting,2024-04-05,2024-05-26,1702,7.5,Cognitive Computing +AI01041,Autonomous Systems Engineer,196201,USD,196201,SE,PT,United States,L,Philippines,0,"Git, Python, Java",Master,5,Consulting,2025-02-15,2025-04-07,1756,8.8,Cloud AI Solutions +AI01042,NLP Engineer,164425,USD,164425,SE,CT,Finland,L,Italy,0,"GCP, Docker, R, Git",Master,9,Education,2024-07-17,2024-09-02,1881,5.6,Autonomous Tech +AI01043,ML Ops Engineer,158518,JPY,17436980,SE,FT,Japan,L,United Kingdom,0,"GCP, NLP, Deep Learning, Docker, R",Bachelor,6,Healthcare,2025-02-06,2025-02-25,2218,7.2,Quantum Computing Inc +AI01044,Autonomous Systems Engineer,137246,USD,137246,MI,PT,Norway,M,Norway,100,"TensorFlow, Kubernetes, AWS, Linux, Docker",Bachelor,4,Consulting,2024-04-12,2024-05-14,609,8.4,Machine Intelligence Group +AI01045,NLP Engineer,222330,EUR,188981,EX,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Scala",Associate,15,Automotive,2025-04-08,2025-05-12,1335,9.6,Autonomous Tech +AI01046,ML Ops Engineer,73721,USD,73721,MI,FL,Israel,S,Sweden,100,"Java, Tableau, MLOps",Master,2,Real Estate,2025-03-06,2025-04-14,1797,5.2,Predictive Systems +AI01047,AI Software Engineer,125284,CHF,112756,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, SQL, Hadoop, Spark, Deep Learning",Associate,3,Healthcare,2024-02-01,2024-02-15,553,9.4,DeepTech Ventures +AI01048,AI Software Engineer,266424,USD,266424,EX,PT,Ireland,L,Ireland,50,"Azure, Scala, R, Tableau",PhD,17,Education,2024-04-19,2024-06-26,515,5.2,DataVision Ltd +AI01049,AI Consultant,158788,EUR,134970,EX,FL,France,S,France,50,"Linux, Mathematics, SQL",Associate,14,Automotive,2025-03-07,2025-04-12,559,7,Advanced Robotics +AI01050,Autonomous Systems Engineer,99628,SGD,129516,MI,FL,Singapore,S,Singapore,100,"PyTorch, AWS, Azure, Kubernetes, MLOps",Associate,3,Government,2024-07-22,2024-08-27,799,5.1,Smart Analytics +AI01051,AI Architect,52727,GBP,39545,EN,FT,United Kingdom,S,Austria,100,"Java, SQL, Linux",Bachelor,1,Energy,2025-03-17,2025-05-24,1166,9,Neural Networks Co +AI01052,AI Specialist,38473,USD,38473,MI,PT,India,L,India,100,"Tableau, Spark, Scala, NLP",Master,4,Manufacturing,2024-10-05,2024-11-03,2320,7.9,Smart Analytics +AI01053,Machine Learning Researcher,64133,USD,64133,EN,PT,United States,M,Sweden,0,"Azure, AWS, TensorFlow, Hadoop",Master,1,Real Estate,2024-09-24,2024-12-03,955,7.8,DataVision Ltd +AI01054,Data Analyst,47110,CAD,58888,EN,CT,Canada,S,Canada,50,"Java, Linux, Kubernetes, Azure",Bachelor,1,Media,2024-11-26,2025-01-06,844,8.4,Quantum Computing Inc +AI01055,Machine Learning Engineer,71783,EUR,61016,EN,CT,France,L,France,50,"Mathematics, SQL, Computer Vision",Associate,1,Media,2024-07-31,2024-10-07,524,8.8,Cognitive Computing +AI01056,AI Software Engineer,83829,USD,83829,EN,FL,Norway,S,India,50,"PyTorch, TensorFlow, Statistics, Hadoop, Python",Bachelor,0,Finance,2024-06-18,2024-08-29,1929,8.3,TechCorp Inc +AI01057,Robotics Engineer,91511,USD,91511,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, Mathematics, Spark",PhD,4,Technology,2024-11-17,2024-12-09,1221,5.7,Quantum Computing Inc +AI01058,ML Ops Engineer,198095,EUR,168381,EX,PT,France,S,France,50,"Git, R, Python, Scala",PhD,14,Education,2024-07-01,2024-08-27,1815,9.5,Machine Intelligence Group +AI01059,AI Product Manager,119407,USD,119407,SE,PT,Norway,S,Norway,0,"Git, Java, Tableau, Linux, Deep Learning",PhD,7,Manufacturing,2025-02-15,2025-03-24,2040,6.2,Algorithmic Solutions +AI01060,Data Engineer,87493,USD,87493,MI,FL,Denmark,S,Denmark,100,"MLOps, Hadoop, Linux, Scala",PhD,4,Energy,2024-12-04,2025-01-21,2032,6.5,Advanced Robotics +AI01061,Data Engineer,121335,USD,121335,SE,PT,Norway,S,Norway,50,"Python, Spark, Mathematics, SQL",Associate,7,Automotive,2024-12-06,2025-01-11,1573,7.9,DeepTech Ventures +AI01062,AI Architect,289174,SGD,375926,EX,FL,Singapore,L,Singapore,0,"Hadoop, SQL, Data Visualization, Deep Learning",Master,13,Retail,2025-02-04,2025-03-26,2451,8.5,Cognitive Computing +AI01063,Deep Learning Engineer,154280,USD,154280,SE,CT,Finland,L,Finland,0,"Data Visualization, Python, AWS",Bachelor,5,Education,2024-01-28,2024-03-21,547,9.6,Autonomous Tech +AI01064,Head of AI,62297,CAD,77871,EN,PT,Canada,S,Canada,100,"Mathematics, Hadoop, MLOps, Linux",Associate,0,Healthcare,2024-09-26,2024-11-02,2467,7.4,AI Innovations +AI01065,AI Software Engineer,114311,CAD,142889,MI,FL,Canada,L,Canada,50,"Mathematics, Computer Vision, Python",PhD,2,Telecommunications,2024-04-10,2024-04-27,1979,8.8,TechCorp Inc +AI01066,AI Research Scientist,163458,CAD,204323,SE,CT,Canada,L,Canada,50,"Azure, Python, Deep Learning, Spark",Master,7,Real Estate,2024-07-30,2024-10-05,1096,7.4,Cloud AI Solutions +AI01067,AI Software Engineer,107211,EUR,91129,MI,CT,France,L,Singapore,0,"Statistics, R, Computer Vision",Master,4,Government,2024-10-18,2024-11-13,678,8.4,Machine Intelligence Group +AI01068,Deep Learning Engineer,136382,USD,136382,MI,FL,Denmark,M,Spain,50,"AWS, Mathematics, NLP",PhD,2,Transportation,2024-10-03,2024-12-06,1219,6.1,AI Innovations +AI01069,Head of AI,249477,CHF,224529,EX,CT,Switzerland,S,Switzerland,50,"NLP, Hadoop, Python, Data Visualization, R",Associate,11,Government,2024-01-31,2024-03-01,1495,7.3,Predictive Systems +AI01070,Data Analyst,177617,EUR,150974,EX,PT,France,M,France,0,"AWS, TensorFlow, Data Visualization, Deep Learning",Master,11,Gaming,2024-12-13,2025-01-06,1493,8,Predictive Systems +AI01071,Computer Vision Engineer,66870,EUR,56840,EN,FL,Austria,M,Austria,0,"Azure, Deep Learning, Python, Git, Docker",Associate,1,Technology,2024-06-09,2024-07-08,2209,9.8,TechCorp Inc +AI01072,AI Software Engineer,79882,EUR,67900,MI,PT,Netherlands,M,Netherlands,0,"Spark, Hadoop, Git, Python, R",Associate,3,Education,2024-10-14,2024-11-16,1560,6.2,AI Innovations +AI01073,AI Research Scientist,114997,EUR,97747,MI,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Python",Bachelor,4,Telecommunications,2024-03-10,2024-03-25,1176,8.2,Predictive Systems +AI01074,Principal Data Scientist,67556,CHF,60800,EN,FT,Switzerland,S,Switzerland,100,"MLOps, Python, Hadoop, Kubernetes, Deep Learning",Master,1,Finance,2024-10-19,2024-12-07,885,6.6,Algorithmic Solutions +AI01075,Deep Learning Engineer,50726,USD,50726,SE,FT,India,M,Australia,0,"Java, AWS, R, Computer Vision, Git",Master,9,Telecommunications,2024-05-02,2024-05-18,556,8.3,Neural Networks Co +AI01076,Data Scientist,45956,EUR,39063,EN,FT,France,S,Italy,0,"Data Visualization, MLOps, AWS",PhD,1,Consulting,2024-11-12,2024-12-14,2065,6.6,Smart Analytics +AI01077,Data Engineer,29934,USD,29934,MI,FT,India,S,India,50,"SQL, Kubernetes, MLOps, Scala, Linux",Bachelor,2,Technology,2024-07-10,2024-08-01,2366,7,DataVision Ltd +AI01078,Deep Learning Engineer,89070,USD,89070,EX,PT,India,M,United Kingdom,0,"Python, Scala, Linux, GCP, Deep Learning",Associate,14,Technology,2025-02-23,2025-04-20,1673,8.1,Autonomous Tech +AI01079,AI Consultant,123195,EUR,104716,SE,FT,Germany,L,Chile,100,"GCP, SQL, Tableau, Spark, Mathematics",Bachelor,6,Finance,2024-12-16,2025-01-21,1581,8.6,Digital Transformation LLC +AI01080,Research Scientist,83392,USD,83392,MI,PT,South Korea,L,Singapore,100,"R, PyTorch, Tableau, Deep Learning, GCP",Associate,3,Automotive,2024-03-27,2024-06-05,1328,7.3,Digital Transformation LLC +AI01081,Principal Data Scientist,241040,USD,241040,EX,FT,Norway,S,Norway,100,"Azure, Linux, Data Visualization",PhD,18,Retail,2024-04-15,2024-06-08,2485,6.9,Cloud AI Solutions +AI01082,AI Consultant,226924,GBP,170193,EX,FL,United Kingdom,S,United Kingdom,100,"AWS, Docker, Kubernetes, Deep Learning, Tableau",Bachelor,17,Government,2024-08-30,2024-10-29,860,8.1,Neural Networks Co +AI01083,Data Analyst,28173,USD,28173,EN,FL,India,M,Singapore,100,"R, SQL, AWS",PhD,1,Gaming,2024-03-17,2024-04-23,2356,8.7,Predictive Systems +AI01084,Autonomous Systems Engineer,96863,EUR,82334,MI,PT,France,M,France,0,"Python, TensorFlow, Tableau",PhD,3,Government,2024-08-18,2024-10-19,1317,7.6,Future Systems +AI01085,ML Ops Engineer,126853,USD,126853,EX,FT,China,L,China,100,"AWS, Spark, NLP, Azure",PhD,13,Real Estate,2025-04-18,2025-05-12,2007,7.3,Algorithmic Solutions +AI01086,Principal Data Scientist,143421,USD,143421,SE,CT,United States,M,United States,100,"Azure, MLOps, Hadoop",Bachelor,6,Telecommunications,2024-11-07,2024-12-28,1193,9.5,DeepTech Ventures +AI01087,AI Consultant,20785,USD,20785,EN,PT,India,S,India,0,"Kubernetes, Spark, Azure, PyTorch",Master,1,Manufacturing,2024-12-24,2025-01-22,642,6.2,Cognitive Computing +AI01088,AI Research Scientist,67394,EUR,57285,EN,FT,Austria,M,Austria,100,"Tableau, Java, Python, Azure, R",PhD,0,Education,2024-11-07,2024-12-23,989,9.1,Algorithmic Solutions +AI01089,Data Engineer,93436,AUD,126139,MI,CT,Australia,L,Hungary,50,"Tableau, PyTorch, Scala, Azure",Master,3,Gaming,2024-01-21,2024-03-09,1503,6.1,Digital Transformation LLC +AI01090,ML Ops Engineer,95063,EUR,80804,MI,PT,France,M,France,100,"Kubernetes, Spark, Scala",Associate,2,Government,2024-09-08,2024-10-22,2378,9.6,Machine Intelligence Group +AI01091,Computer Vision Engineer,167478,USD,167478,EX,PT,United States,M,United States,100,"Statistics, Git, Docker",Bachelor,18,Healthcare,2024-03-16,2024-04-13,626,7.2,Machine Intelligence Group +AI01092,Autonomous Systems Engineer,139198,CHF,125278,SE,CT,Switzerland,S,Switzerland,100,"Java, Linux, Python, Hadoop, Azure",Master,5,Automotive,2024-02-27,2024-04-05,2301,9.1,Digital Transformation LLC +AI01093,Computer Vision Engineer,215699,USD,215699,EX,PT,Ireland,L,Ireland,0,"Computer Vision, Java, MLOps, AWS",Master,19,Automotive,2024-06-03,2024-06-30,2486,8.5,Advanced Robotics +AI01094,Research Scientist,138827,AUD,187416,EX,CT,Australia,S,Australia,100,"Docker, Data Visualization, Tableau, TensorFlow, AWS",Master,15,Manufacturing,2025-04-28,2025-05-28,1069,9.4,Machine Intelligence Group +AI01095,AI Consultant,79327,JPY,8725970,EN,PT,Japan,M,Japan,100,"AWS, TensorFlow, SQL, Computer Vision",Master,0,Real Estate,2025-02-26,2025-04-20,1008,7.3,Machine Intelligence Group +AI01096,AI Research Scientist,70002,USD,70002,EN,FT,Finland,L,Finland,50,"Mathematics, SQL, Data Visualization, MLOps",Master,1,Gaming,2024-12-31,2025-02-10,2355,9,Cognitive Computing +AI01097,AI Research Scientist,85342,EUR,72541,EN,FL,Netherlands,L,Netherlands,50,"Java, SQL, Spark",Associate,1,Energy,2024-11-25,2025-01-20,1783,6.7,TechCorp Inc +AI01098,AI Architect,116683,SGD,151688,SE,FT,Singapore,M,Singapore,100,"AWS, PyTorch, Python, Spark",Master,5,Automotive,2024-03-27,2024-05-12,2269,5.3,Cloud AI Solutions +AI01099,Head of AI,127338,EUR,108237,EX,CT,France,S,Estonia,50,"Scala, Spark, TensorFlow",Associate,19,Gaming,2024-03-09,2024-04-29,2085,5.1,Cloud AI Solutions +AI01100,Research Scientist,80026,USD,80026,SE,FT,South Korea,S,South Korea,100,"R, Java, Linux, GCP",Master,9,Healthcare,2024-04-24,2024-06-06,1833,6.7,Neural Networks Co +AI01101,Deep Learning Engineer,119475,CHF,107528,EN,PT,Switzerland,L,Switzerland,0,"Spark, Azure, Python",PhD,1,Gaming,2024-05-03,2024-07-14,2219,5.9,Predictive Systems +AI01102,ML Ops Engineer,254552,AUD,343645,EX,CT,Australia,L,Egypt,0,"Deep Learning, Python, Java, GCP, TensorFlow",Associate,12,Transportation,2024-04-23,2024-05-13,1757,5.6,Cognitive Computing +AI01103,Head of AI,118245,USD,118245,SE,PT,Ireland,M,Canada,0,"Mathematics, AWS, Data Visualization, Computer Vision",Master,6,Consulting,2024-08-16,2024-10-08,1898,9.3,Neural Networks Co +AI01104,AI Software Engineer,117254,EUR,99666,SE,FL,Austria,M,Austria,0,"SQL, Data Visualization, R, Spark, GCP",PhD,7,Government,2024-12-26,2025-02-18,2230,9.3,Autonomous Tech +AI01105,Data Scientist,256695,USD,256695,EX,FL,Ireland,L,Ireland,50,"MLOps, Scala, AWS",Bachelor,14,Automotive,2024-06-11,2024-07-26,617,9.1,Autonomous Tech +AI01106,Computer Vision Engineer,188203,USD,188203,EX,FL,Finland,M,Finland,0,"Hadoop, R, Python, Git",Bachelor,15,Real Estate,2024-08-12,2024-09-07,1201,9.4,Advanced Robotics +AI01107,Computer Vision Engineer,191049,USD,191049,EX,FL,United States,S,United States,0,"AWS, Linux, Azure",Bachelor,17,Education,2024-06-02,2024-07-06,887,7.7,AI Innovations +AI01108,AI Product Manager,75973,EUR,64577,EN,FT,Germany,M,Thailand,50,"SQL, NLP, Tableau",Master,1,Automotive,2024-08-16,2024-09-27,646,7.7,DataVision Ltd +AI01109,Machine Learning Researcher,205143,SGD,266686,EX,FT,Singapore,M,Singapore,100,"Scala, Docker, MLOps",PhD,14,Transportation,2024-08-04,2024-08-28,2458,9,Machine Intelligence Group +AI01110,AI Specialist,92600,USD,92600,SE,FT,Ireland,S,Ireland,0,"SQL, Java, Computer Vision",PhD,8,Healthcare,2024-03-03,2024-04-03,1281,6.1,Predictive Systems +AI01111,Research Scientist,307696,USD,307696,EX,CT,Denmark,L,Czech Republic,100,"Data Visualization, TensorFlow, Python, MLOps, Deep Learning",Bachelor,12,Government,2024-09-25,2024-10-17,526,7.3,Advanced Robotics +AI01112,Machine Learning Engineer,289667,USD,289667,EX,FL,United States,L,United States,0,"Mathematics, Scala, PyTorch",Master,15,Automotive,2024-10-26,2024-12-20,2369,6.6,Cognitive Computing +AI01113,AI Product Manager,104108,USD,104108,SE,FT,Sweden,S,Sweden,50,"Spark, Java, R, TensorFlow, SQL",PhD,9,Automotive,2025-01-02,2025-02-26,1083,6.1,Predictive Systems +AI01114,NLP Engineer,85459,USD,85459,EN,FT,Denmark,M,Denmark,50,"Statistics, Spark, PyTorch",Bachelor,1,Retail,2024-07-18,2024-08-13,2416,6.6,DataVision Ltd +AI01115,Computer Vision Engineer,48088,EUR,40875,EN,FT,France,M,France,0,"NLP, Scala, Java",Bachelor,0,Finance,2024-04-08,2024-05-19,1362,9.7,Smart Analytics +AI01116,AI Architect,103764,USD,103764,SE,PT,Sweden,S,Sweden,50,"SQL, Docker, AWS",Associate,9,Manufacturing,2024-11-15,2025-01-01,1227,9.4,Future Systems +AI01117,Deep Learning Engineer,135128,SGD,175666,SE,PT,Singapore,M,Singapore,100,"NLP, R, Azure, SQL, Java",Master,9,Government,2024-05-15,2024-07-11,693,6.1,Machine Intelligence Group +AI01118,NLP Engineer,78044,JPY,8584840,MI,PT,Japan,S,Japan,0,"TensorFlow, Azure, Python, Tableau",Bachelor,4,Gaming,2024-11-08,2024-12-12,1943,7.9,Autonomous Tech +AI01119,Research Scientist,77226,SGD,100394,MI,FT,Singapore,M,Singapore,0,"Scala, Spark, Computer Vision, Python, Tableau",PhD,3,Telecommunications,2024-07-16,2024-08-29,1506,6.6,Predictive Systems +AI01120,Machine Learning Engineer,149651,CAD,187064,EX,CT,Canada,M,Canada,100,"TensorFlow, Python, Kubernetes, MLOps, AWS",Associate,11,Gaming,2024-09-18,2024-11-15,943,7.9,DeepTech Ventures +AI01121,Machine Learning Engineer,183833,EUR,156258,EX,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, R",Associate,10,Healthcare,2025-03-24,2025-05-29,2012,9.6,Future Systems +AI01122,Computer Vision Engineer,104425,EUR,88761,MI,PT,Germany,L,China,0,"MLOps, Java, Python, Kubernetes, Computer Vision",Bachelor,4,Transportation,2024-07-30,2024-08-24,532,5.7,Quantum Computing Inc +AI01123,AI Consultant,163323,USD,163323,EX,CT,Sweden,S,Sweden,0,"NLP, Data Visualization, AWS, Python, TensorFlow",Bachelor,10,Gaming,2024-10-14,2024-11-11,1137,6.6,Autonomous Tech +AI01124,Data Engineer,136850,EUR,116323,EX,FT,Germany,S,Norway,0,"Tableau, Python, TensorFlow, Computer Vision, GCP",PhD,11,Healthcare,2024-08-14,2024-09-02,831,7.2,Cloud AI Solutions +AI01125,AI Consultant,133658,GBP,100244,SE,FL,United Kingdom,S,United Kingdom,100,"Kubernetes, SQL, GCP",PhD,8,Manufacturing,2024-05-17,2024-06-24,1514,6,Smart Analytics +AI01126,AI Specialist,168161,JPY,18497710,SE,FT,Japan,L,Japan,0,"Python, GCP, TensorFlow, Computer Vision, Hadoop",PhD,6,Government,2025-02-06,2025-03-12,2290,5.8,Cloud AI Solutions +AI01127,AI Research Scientist,87945,JPY,9673950,MI,FT,Japan,M,Japan,0,"Computer Vision, PyTorch, Data Visualization",Associate,2,Consulting,2025-04-30,2025-06-13,1525,6.3,Autonomous Tech +AI01128,Data Analyst,150603,USD,150603,SE,FL,Norway,M,Norway,50,"GCP, R, Computer Vision, Linux, SQL",Master,9,Healthcare,2024-05-14,2024-07-09,2451,9.6,Cloud AI Solutions +AI01129,Research Scientist,41667,USD,41667,MI,CT,China,M,China,100,"Data Visualization, Kubernetes, MLOps, TensorFlow",Master,3,Finance,2024-06-03,2024-08-12,1963,9,Cognitive Computing +AI01130,Machine Learning Researcher,270857,USD,270857,EX,FT,Denmark,L,Denmark,0,"Spark, PyTorch, Hadoop",Associate,14,Healthcare,2025-01-09,2025-02-17,1836,7.5,Machine Intelligence Group +AI01131,AI Product Manager,70021,JPY,7702310,EN,FL,Japan,M,South Korea,100,"SQL, Git, Python",Master,1,Automotive,2024-09-30,2024-11-08,2044,9,Machine Intelligence Group +AI01132,Deep Learning Engineer,180120,USD,180120,EX,FL,Finland,S,Finland,50,"PyTorch, R, Java, SQL",Bachelor,19,Gaming,2025-03-21,2025-04-27,2134,9.4,TechCorp Inc +AI01133,Data Analyst,109592,CAD,136990,SE,FT,Canada,S,Kenya,50,"GCP, Spark, AWS, Python, Mathematics",Master,8,Gaming,2024-04-30,2024-06-13,1754,8.9,TechCorp Inc +AI01134,NLP Engineer,248395,EUR,211136,EX,FL,Germany,M,Germany,100,"Kubernetes, Data Visualization, Java, Scala, MLOps",Master,11,Energy,2024-06-19,2024-08-31,2176,7.6,Digital Transformation LLC +AI01135,ML Ops Engineer,166428,EUR,141464,EX,FL,France,S,Luxembourg,50,"Linux, AWS, Deep Learning, Computer Vision",Bachelor,12,Real Estate,2024-10-28,2024-12-07,2272,9.4,DataVision Ltd +AI01136,AI Product Manager,64110,SGD,83343,EN,FL,Singapore,S,Ukraine,50,"Kubernetes, Statistics, Scala, Deep Learning",Master,1,Manufacturing,2024-02-23,2024-03-17,1013,7.7,Autonomous Tech +AI01137,NLP Engineer,89254,USD,89254,MI,CT,Israel,M,Israel,50,"Azure, PyTorch, Data Visualization, Computer Vision, Mathematics",Bachelor,2,Real Estate,2025-02-03,2025-03-03,736,5.6,Neural Networks Co +AI01138,ML Ops Engineer,89632,CAD,112040,SE,FT,Canada,S,Brazil,50,"PyTorch, Git, Python",Master,7,Technology,2024-09-11,2024-10-26,1963,8.9,Digital Transformation LLC +AI01139,Research Scientist,94147,JPY,10356170,MI,FL,Japan,S,Austria,100,"NLP, Python, GCP, Mathematics",Associate,4,Telecommunications,2024-07-04,2024-08-12,2179,9.7,DeepTech Ventures +AI01140,Data Scientist,95536,USD,95536,EX,PT,China,M,Poland,50,"PyTorch, TensorFlow, GCP, NLP",Bachelor,12,Consulting,2024-07-13,2024-08-13,2028,5.3,DataVision Ltd +AI01141,AI Specialist,128104,USD,128104,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, Git, Data Visualization",Master,6,Manufacturing,2024-03-16,2024-04-12,1759,6.7,DeepTech Ventures +AI01142,Data Analyst,224736,USD,224736,EX,FL,Denmark,S,South Africa,100,"Python, TensorFlow, SQL, Kubernetes, AWS",Associate,15,Manufacturing,2024-01-18,2024-02-12,617,6.5,Machine Intelligence Group +AI01143,Principal Data Scientist,132221,JPY,14544310,MI,FT,Japan,L,Japan,0,"Python, Git, GCP, NLP, Hadoop",PhD,4,Consulting,2024-09-26,2024-10-22,1834,9.4,Cloud AI Solutions +AI01144,AI Consultant,107463,EUR,91344,SE,FT,Austria,M,Ireland,0,"Data Visualization, PyTorch, Git, Computer Vision",PhD,7,Media,2025-03-17,2025-04-19,1360,6.3,DataVision Ltd +AI01145,Machine Learning Researcher,200093,CAD,250116,EX,FL,Canada,M,India,50,"Statistics, R, Tableau, Hadoop",Bachelor,18,Real Estate,2024-09-22,2024-11-06,1322,8.4,Advanced Robotics +AI01146,Machine Learning Engineer,168952,AUD,228085,SE,PT,Australia,L,Australia,100,"SQL, R, Hadoop, Docker",Master,7,Finance,2024-02-11,2024-02-25,1398,5.9,Digital Transformation LLC +AI01147,Deep Learning Engineer,223789,JPY,24616790,EX,FT,Japan,S,Japan,100,"Hadoop, SQL, Linux",Bachelor,10,Technology,2024-05-22,2024-06-16,1821,5.2,Machine Intelligence Group +AI01148,Data Engineer,121814,USD,121814,SE,CT,South Korea,L,South Korea,0,"Spark, Linux, Hadoop",PhD,7,Telecommunications,2024-04-11,2024-05-26,808,9.6,Predictive Systems +AI01149,NLP Engineer,188710,USD,188710,EX,PT,Finland,S,Finland,0,"SQL, Hadoop, Tableau",Associate,19,Transportation,2024-05-31,2024-07-28,2221,5.7,Smart Analytics +AI01150,AI Consultant,73645,AUD,99421,MI,PT,Australia,S,Australia,50,"Python, Spark, Data Visualization, NLP",Bachelor,3,Government,2024-03-23,2024-04-22,1750,9.6,Advanced Robotics +AI01151,ML Ops Engineer,167924,GBP,125943,EX,FL,United Kingdom,S,Ghana,0,"Hadoop, SQL, GCP, Scala, Computer Vision",Master,13,Education,2025-03-24,2025-05-11,2123,10,Future Systems +AI01152,NLP Engineer,104995,USD,104995,MI,FT,Sweden,L,Sweden,50,"Tableau, GCP, Mathematics",Bachelor,3,Media,2024-02-10,2024-02-29,2335,5.9,Algorithmic Solutions +AI01153,NLP Engineer,319365,CHF,287429,EX,FT,Switzerland,M,Switzerland,100,"Python, Linux, TensorFlow, AWS",Associate,15,Telecommunications,2024-08-01,2024-08-31,2420,7.4,Advanced Robotics +AI01154,Data Engineer,120902,USD,120902,SE,FL,South Korea,L,South Korea,0,"Linux, Python, MLOps, Spark, Mathematics",PhD,6,Healthcare,2024-12-15,2025-02-07,592,7.2,DataVision Ltd +AI01155,AI Research Scientist,93958,EUR,79864,MI,CT,Germany,M,Latvia,50,"SQL, Data Visualization, Scala",Master,3,Real Estate,2024-11-25,2025-02-04,2028,7.9,Advanced Robotics +AI01156,Machine Learning Researcher,204959,USD,204959,EX,CT,Denmark,L,Denmark,50,"TensorFlow, Python, GCP, R",Bachelor,10,Manufacturing,2025-03-27,2025-04-30,2354,6.1,Digital Transformation LLC +AI01157,Computer Vision Engineer,45750,USD,45750,MI,FL,China,M,Denmark,0,"Statistics, PyTorch, TensorFlow, Computer Vision, Deep Learning",PhD,2,Energy,2025-03-09,2025-03-24,972,7.4,TechCorp Inc +AI01158,Data Engineer,191169,EUR,162494,EX,CT,Germany,M,Egypt,100,"Scala, Java, Computer Vision, AWS",Associate,13,Gaming,2025-03-19,2025-04-03,2281,5.6,Algorithmic Solutions +AI01159,Robotics Engineer,187320,JPY,20605200,EX,PT,Japan,L,Spain,100,"Java, TensorFlow, Data Visualization",PhD,16,Education,2024-09-23,2024-11-10,701,8.8,Cloud AI Solutions +AI01160,AI Architect,45995,USD,45995,SE,FL,China,S,China,0,"Python, TensorFlow, Linux, Statistics",Bachelor,8,Telecommunications,2024-12-03,2024-12-22,1433,8.3,AI Innovations +AI01161,Principal Data Scientist,189388,EUR,160980,EX,FL,France,S,France,50,"TensorFlow, Python, PyTorch, AWS, R",Associate,10,Healthcare,2024-11-23,2025-01-20,2162,9.9,Digital Transformation LLC +AI01162,AI Research Scientist,77764,CHF,69988,EN,PT,Switzerland,M,Ghana,100,"Kubernetes, SQL, Data Visualization",Master,0,Finance,2024-11-28,2024-12-21,1143,8,Cognitive Computing +AI01163,Data Engineer,70260,EUR,59721,EN,FL,Germany,L,Germany,0,"Linux, Data Visualization, MLOps, Git",Master,1,Education,2024-12-05,2025-01-03,604,8,Cloud AI Solutions +AI01164,Autonomous Systems Engineer,59125,EUR,50256,EN,PT,Germany,S,Germany,50,"Scala, Python, Tableau, Computer Vision",PhD,1,Gaming,2024-10-22,2024-12-14,706,7.7,Smart Analytics +AI01165,Head of AI,85915,CHF,77324,EN,FL,Switzerland,S,Switzerland,0,"Python, Tableau, Java, AWS, Statistics",Associate,1,Telecommunications,2025-04-15,2025-05-29,1359,8.5,Cognitive Computing +AI01166,AI Software Engineer,161147,USD,161147,SE,FL,Israel,L,Israel,50,"Spark, Linux, Kubernetes, Hadoop, Python",Associate,9,Energy,2024-09-05,2024-11-03,1023,6.3,Cognitive Computing +AI01167,AI Consultant,145874,USD,145874,EX,PT,Israel,M,Israel,50,"GCP, Statistics, MLOps, Python, AWS",PhD,16,Education,2024-08-23,2024-11-01,1826,9.6,Smart Analytics +AI01168,Research Scientist,41928,USD,41928,MI,PT,India,L,India,50,"AWS, MLOps, NLP",Associate,3,Telecommunications,2024-07-06,2024-09-04,1539,7.1,Quantum Computing Inc +AI01169,NLP Engineer,244108,USD,244108,EX,CT,Denmark,S,Denmark,0,"Hadoop, Python, SQL",Associate,14,Transportation,2024-05-21,2024-06-29,974,8.9,AI Innovations +AI01170,NLP Engineer,74765,CHF,67289,EN,FT,Switzerland,M,Vietnam,50,"Tableau, Deep Learning, Kubernetes, AWS",Master,0,Retail,2025-04-20,2025-06-25,861,6.6,Quantum Computing Inc +AI01171,AI Software Engineer,111797,USD,111797,SE,CT,Finland,S,Finland,50,"Python, MLOps, Linux",Bachelor,8,Finance,2024-07-14,2024-09-06,778,7.1,Cognitive Computing +AI01172,AI Product Manager,129173,AUD,174384,SE,FL,Australia,M,Australia,100,"Scala, Spark, MLOps, Mathematics, Linux",PhD,8,Automotive,2024-08-12,2024-10-10,1154,9.1,Neural Networks Co +AI01173,Robotics Engineer,109849,USD,109849,SE,FL,Ireland,S,Ireland,0,"SQL, TensorFlow, MLOps",Master,5,Transportation,2024-11-08,2024-11-27,1872,9.3,Smart Analytics +AI01174,NLP Engineer,86314,CHF,77683,EN,FL,Switzerland,L,Switzerland,0,"Scala, Python, TensorFlow, Computer Vision",Bachelor,0,Retail,2025-01-30,2025-03-15,2197,9.2,Cognitive Computing +AI01175,AI Product Manager,134718,CHF,121246,MI,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Linux, R",Bachelor,4,Finance,2024-10-09,2024-11-11,2272,6.1,TechCorp Inc +AI01176,Machine Learning Researcher,146659,USD,146659,SE,CT,Sweden,M,Sweden,100,"TensorFlow, PyTorch, Kubernetes",Associate,6,Government,2025-01-24,2025-02-15,2107,8.3,DeepTech Ventures +AI01177,NLP Engineer,207301,GBP,155476,EX,FL,United Kingdom,M,United Kingdom,100,"Java, SQL, Spark, TensorFlow",Master,15,Real Estate,2024-01-06,2024-02-17,1385,6.5,DeepTech Ventures +AI01178,Data Scientist,86551,EUR,73568,MI,CT,Netherlands,S,Netherlands,100,"Scala, Statistics, SQL",PhD,2,Finance,2024-01-18,2024-02-14,752,8.8,Neural Networks Co +AI01179,AI Consultant,101086,SGD,131412,MI,FL,Singapore,L,Latvia,0,"Tableau, AWS, Hadoop, Kubernetes, SQL",Bachelor,2,Automotive,2024-11-02,2024-12-18,1462,10,Autonomous Tech +AI01180,Computer Vision Engineer,243742,USD,243742,EX,FL,Ireland,M,Ireland,100,"Linux, GCP, AWS",Master,16,Automotive,2024-10-18,2024-11-12,972,8.4,Future Systems +AI01181,AI Software Engineer,45910,EUR,39024,EN,FL,Austria,S,Austria,100,"Linux, Data Visualization, Git, Scala",Master,0,Automotive,2024-09-17,2024-10-25,1021,9.7,Machine Intelligence Group +AI01182,Principal Data Scientist,165181,EUR,140404,EX,CT,France,L,France,100,"TensorFlow, NLP, Hadoop, Kubernetes, Python",Bachelor,14,Finance,2024-01-07,2024-02-25,1029,6.7,Quantum Computing Inc +AI01183,Machine Learning Researcher,47299,AUD,63854,EN,PT,Australia,S,Australia,100,"SQL, Linux, Git, Tableau",Master,1,Telecommunications,2024-06-17,2024-07-23,2432,6.8,DeepTech Ventures +AI01184,AI Specialist,69234,CAD,86543,EN,FT,Canada,M,Ireland,100,"Computer Vision, Java, Data Visualization",PhD,0,Retail,2024-01-15,2024-02-13,1184,5,AI Innovations +AI01185,AI Product Manager,95021,SGD,123527,MI,FL,Singapore,L,Belgium,50,"MLOps, Tableau, Python, Docker",Bachelor,3,Telecommunications,2024-10-12,2024-10-26,2138,5.7,Future Systems +AI01186,Machine Learning Engineer,27279,USD,27279,EN,CT,India,L,India,0,"Statistics, Mathematics, Tableau",Associate,0,Real Estate,2024-02-27,2024-03-25,1258,6.5,TechCorp Inc +AI01187,Machine Learning Researcher,74665,SGD,97065,EN,FL,Singapore,S,Singapore,100,"R, Azure, PyTorch",PhD,0,Retail,2024-01-14,2024-03-05,1743,7.5,Advanced Robotics +AI01188,AI Consultant,105569,USD,105569,SE,CT,South Korea,M,France,0,"Python, Java, Data Visualization, Deep Learning",Associate,7,Manufacturing,2024-06-07,2024-07-06,765,6.9,Future Systems +AI01189,Principal Data Scientist,75073,USD,75073,EN,FL,Sweden,M,Sweden,0,"Python, R, Tableau, Data Visualization, AWS",Associate,1,Retail,2024-11-20,2025-01-28,1316,5.8,Future Systems +AI01190,AI Software Engineer,185794,USD,185794,EX,FT,Denmark,M,Singapore,100,"R, MLOps, Computer Vision, Git",PhD,18,Energy,2025-01-27,2025-02-13,691,7.1,DeepTech Ventures +AI01191,AI Specialist,222006,USD,222006,EX,FL,United States,S,New Zealand,100,"Hadoop, Spark, Mathematics",Bachelor,19,Energy,2025-02-19,2025-03-27,987,9.1,TechCorp Inc +AI01192,Robotics Engineer,95988,USD,95988,MI,PT,Ireland,M,Switzerland,0,"PyTorch, Linux, Scala, Mathematics, GCP",Master,2,Real Estate,2025-02-21,2025-03-18,1899,9.6,Autonomous Tech +AI01193,Autonomous Systems Engineer,75420,GBP,56565,EN,CT,United Kingdom,M,Israel,50,"Linux, Spark, TensorFlow, Python",Associate,1,Media,2024-07-03,2024-09-02,1590,5.9,Quantum Computing Inc +AI01194,AI Consultant,56066,CAD,70083,EN,FL,Canada,S,Japan,0,"Spark, Kubernetes, TensorFlow",PhD,0,Technology,2024-09-28,2024-10-28,1278,9.1,Neural Networks Co +AI01195,ML Ops Engineer,34199,USD,34199,MI,CT,India,S,India,100,"Java, Kubernetes, Azure, GCP",Associate,3,Energy,2025-02-11,2025-04-09,1150,6.6,DeepTech Ventures +AI01196,Robotics Engineer,123046,USD,123046,SE,PT,Israel,M,Israel,50,"Python, Docker, Data Visualization, MLOps, Deep Learning",Master,9,Media,2024-09-13,2024-10-08,1501,6.8,Predictive Systems +AI01197,Research Scientist,155715,EUR,132358,SE,CT,Austria,L,Brazil,100,"Java, Kubernetes, Docker",Associate,8,Manufacturing,2024-09-01,2024-10-31,1240,6.6,Cloud AI Solutions +AI01198,AI Architect,135052,CHF,121547,MI,CT,Switzerland,M,New Zealand,100,"GCP, Python, Git, Java, Computer Vision",PhD,4,Finance,2024-07-08,2024-09-15,1191,6.2,Smart Analytics +AI01199,AI Research Scientist,139723,GBP,104792,SE,PT,United Kingdom,L,Canada,100,"Kubernetes, Spark, MLOps",Associate,5,Finance,2024-06-27,2024-07-23,1731,9.7,Cloud AI Solutions +AI01200,AI Software Engineer,126789,USD,126789,SE,CT,Israel,S,Israel,50,"Hadoop, Git, Statistics",Bachelor,6,Healthcare,2024-07-31,2024-08-14,2157,5.9,DeepTech Ventures +AI01201,Data Analyst,51041,SGD,66353,EN,FT,Singapore,S,Singapore,100,"Statistics, AWS, Scala, PyTorch",PhD,1,Healthcare,2024-01-30,2024-02-19,1755,6.8,Cloud AI Solutions +AI01202,Machine Learning Engineer,66473,AUD,89739,EN,FT,Australia,M,Australia,100,"Docker, Kubernetes, Statistics, Spark",Master,0,Energy,2025-02-04,2025-02-20,2260,7.9,Future Systems +AI01203,AI Consultant,82798,JPY,9107780,EN,FT,Japan,L,Japan,50,"Azure, SQL, AWS",Master,0,Real Estate,2025-01-10,2025-03-06,1844,8.2,Quantum Computing Inc +AI01204,Machine Learning Researcher,208808,USD,208808,EX,CT,Ireland,M,Estonia,100,"Java, Python, PyTorch, SQL",Associate,16,Healthcare,2024-01-16,2024-02-29,2313,5.3,Autonomous Tech +AI01205,Principal Data Scientist,85454,USD,85454,EN,FT,Denmark,M,Denmark,100,"SQL, Scala, Kubernetes",PhD,0,Government,2024-12-20,2025-02-05,1407,7.8,Cloud AI Solutions +AI01206,Principal Data Scientist,312926,CHF,281633,EX,FT,Switzerland,S,Switzerland,100,"Kubernetes, Git, Mathematics, Hadoop, PyTorch",Bachelor,17,Media,2024-08-07,2024-10-14,1468,6.5,Predictive Systems +AI01207,Computer Vision Engineer,112468,USD,112468,EN,FT,Denmark,L,Italy,100,"R, Java, Linux",Master,0,Manufacturing,2024-11-13,2024-11-30,1081,9.1,Neural Networks Co +AI01208,Data Analyst,184835,USD,184835,EX,PT,Sweden,L,Sweden,100,"GCP, Python, TensorFlow, SQL",Bachelor,12,Consulting,2024-09-22,2024-10-31,570,6.7,Algorithmic Solutions +AI01209,Robotics Engineer,114775,EUR,97559,SE,PT,France,L,France,100,"Python, Git, TensorFlow, Data Visualization, Linux",Bachelor,7,Education,2024-06-20,2024-08-10,1743,9.4,Neural Networks Co +AI01210,Deep Learning Engineer,87755,CAD,109694,MI,PT,Canada,L,Portugal,100,"Deep Learning, Scala, Data Visualization, TensorFlow",Bachelor,3,Energy,2024-11-03,2024-12-15,1436,6.4,Predictive Systems +AI01211,AI Consultant,226988,SGD,295084,EX,CT,Singapore,S,Singapore,0,"Statistics, NLP, Linux",Master,12,Manufacturing,2024-05-03,2024-06-13,2480,5.1,Advanced Robotics +AI01212,Data Scientist,109751,CAD,137189,SE,PT,Canada,S,Denmark,100,"Azure, Kubernetes, Spark, Computer Vision",PhD,9,Energy,2024-09-01,2024-10-13,2171,7.1,Future Systems +AI01213,NLP Engineer,110714,USD,110714,EX,FL,China,M,China,100,"NLP, Scala, Kubernetes, Python",Master,15,Finance,2024-06-01,2024-08-13,835,7.9,TechCorp Inc +AI01214,AI Architect,243320,USD,243320,EX,CT,Israel,L,Israel,0,"NLP, Scala, Python, Computer Vision",PhD,16,Telecommunications,2024-09-17,2024-11-17,2026,5.8,DataVision Ltd +AI01215,Machine Learning Researcher,137660,USD,137660,SE,FT,Sweden,M,India,100,"Tableau, Kubernetes, SQL, Java",Associate,6,Technology,2024-07-19,2024-09-02,964,8.2,Future Systems +AI01216,Deep Learning Engineer,101137,USD,101137,MI,CT,Denmark,M,Belgium,50,"R, Azure, Deep Learning, SQL, Java",Master,2,Telecommunications,2025-01-02,2025-02-06,2016,10,DataVision Ltd +AI01217,Data Analyst,76750,EUR,65238,EN,FT,Netherlands,M,Netherlands,0,"Java, Git, Data Visualization",Bachelor,0,Gaming,2024-07-20,2024-09-01,723,6.9,Cognitive Computing +AI01218,Machine Learning Researcher,225610,USD,225610,EX,PT,Denmark,M,Denmark,50,"PyTorch, Deep Learning, TensorFlow",Associate,14,Telecommunications,2024-06-21,2024-08-10,810,7.1,Predictive Systems +AI01219,AI Consultant,250681,USD,250681,EX,FL,Denmark,S,Denmark,0,"TensorFlow, R, Spark, Python",PhD,15,Retail,2024-07-17,2024-09-22,818,6.3,Smart Analytics +AI01220,Deep Learning Engineer,68073,USD,68073,EN,PT,United States,M,United States,50,"MLOps, AWS, SQL, NLP, Statistics",Master,0,Technology,2024-03-11,2024-04-05,1104,5.4,TechCorp Inc +AI01221,Data Scientist,83363,EUR,70859,MI,FL,Germany,S,Germany,100,"Git, Linux, MLOps, Mathematics",Bachelor,2,Energy,2024-08-01,2024-09-15,2321,6.2,Cognitive Computing +AI01222,AI Architect,82241,USD,82241,EN,FL,United States,L,United States,0,"Spark, R, Deep Learning, Java, Git",Master,0,Education,2024-03-04,2024-05-09,515,9.9,Neural Networks Co +AI01223,AI Research Scientist,70446,USD,70446,EN,PT,South Korea,L,South Korea,0,"Python, Git, TensorFlow, GCP, PyTorch",Master,1,Energy,2024-11-08,2024-11-27,688,8.3,Digital Transformation LLC +AI01224,Machine Learning Researcher,91327,USD,91327,EN,PT,United States,M,United States,0,"Hadoop, Scala, Statistics, Git",Bachelor,0,Technology,2024-06-20,2024-07-15,703,5.6,Advanced Robotics +AI01225,Data Scientist,39389,USD,39389,MI,CT,India,L,India,0,"Data Visualization, SQL, Hadoop",Associate,4,Media,2024-10-03,2024-11-12,1197,9.6,Neural Networks Co +AI01226,Robotics Engineer,81525,EUR,69296,EN,CT,Netherlands,L,Netherlands,0,"AWS, Data Visualization, PyTorch",PhD,0,Finance,2025-04-03,2025-06-04,2353,5.8,DeepTech Ventures +AI01227,Data Analyst,64441,EUR,54775,EN,PT,Germany,S,Germany,50,"PyTorch, TensorFlow, Tableau, GCP",Associate,1,Retail,2024-10-15,2024-11-18,604,5.3,Cloud AI Solutions +AI01228,Data Scientist,154936,CAD,193670,SE,FL,Canada,L,Spain,0,"Data Visualization, Python, Scala, TensorFlow, Statistics",Master,7,Energy,2024-01-23,2024-03-19,1911,5.5,Autonomous Tech +AI01229,Machine Learning Engineer,252651,USD,252651,EX,CT,Finland,L,Finland,0,"Python, Java, MLOps, Computer Vision, Deep Learning",Associate,11,Media,2024-07-25,2024-09-09,1989,9.7,AI Innovations +AI01230,AI Research Scientist,85211,GBP,63908,MI,PT,United Kingdom,M,United Kingdom,0,"AWS, MLOps, Deep Learning, SQL",Bachelor,2,Energy,2024-08-28,2024-09-20,1984,6.7,Advanced Robotics +AI01231,Head of AI,75989,USD,75989,MI,CT,South Korea,S,South Korea,0,"PyTorch, TensorFlow, Docker, Hadoop",Associate,2,Telecommunications,2024-11-22,2025-01-08,1985,5.6,Algorithmic Solutions +AI01232,NLP Engineer,81874,USD,81874,MI,CT,Ireland,M,Ireland,50,"Azure, GCP, Statistics, PyTorch",Bachelor,2,Real Estate,2024-10-16,2024-12-09,1992,8.5,Autonomous Tech +AI01233,Robotics Engineer,159436,USD,159436,SE,CT,Israel,L,Australia,50,"TensorFlow, Data Visualization, Java, Azure",Associate,7,Telecommunications,2024-02-02,2024-03-12,1302,10,DeepTech Ventures +AI01234,AI Research Scientist,116597,USD,116597,SE,FT,Finland,M,Switzerland,50,"Deep Learning, Statistics, AWS",Associate,5,Media,2024-12-12,2025-01-11,762,8.9,Future Systems +AI01235,ML Ops Engineer,123943,JPY,13633730,SE,CT,Japan,M,Japan,50,"Python, TensorFlow, GCP, SQL, Git",PhD,9,Consulting,2024-08-04,2024-08-31,2347,8.3,DataVision Ltd +AI01236,Principal Data Scientist,142168,EUR,120843,SE,PT,France,M,France,50,"Mathematics, TensorFlow, Docker, NLP",Associate,9,Gaming,2024-05-21,2024-06-07,1546,7.3,TechCorp Inc +AI01237,Machine Learning Engineer,145212,USD,145212,MI,FT,United States,L,United Kingdom,50,"Linux, R, Deep Learning",Master,3,Finance,2024-01-14,2024-03-20,1063,7.7,Neural Networks Co +AI01238,Data Engineer,150880,JPY,16596800,SE,FT,Japan,L,Japan,100,"Mathematics, R, Data Visualization",Associate,6,Gaming,2024-12-11,2025-01-15,2362,6,Neural Networks Co +AI01239,ML Ops Engineer,78416,USD,78416,MI,FL,Israel,M,Israel,0,"Kubernetes, Python, Data Visualization, TensorFlow, AWS",PhD,4,Technology,2024-12-29,2025-03-11,521,8.6,Machine Intelligence Group +AI01240,Robotics Engineer,167446,EUR,142329,EX,CT,Netherlands,L,Netherlands,0,"Git, Azure, PyTorch, Deep Learning",Associate,13,Education,2025-04-28,2025-05-26,2462,5.7,DataVision Ltd +AI01241,AI Architect,136891,USD,136891,EX,FT,South Korea,S,South Korea,50,"Data Visualization, Java, Linux, AWS",Associate,13,Manufacturing,2024-11-09,2025-01-06,2072,6.3,Cloud AI Solutions +AI01242,AI Product Manager,56186,CAD,70233,EN,CT,Canada,L,Sweden,0,"Tableau, Deep Learning, Spark, TensorFlow, Hadoop",Bachelor,0,Retail,2024-02-09,2024-03-02,1179,7.5,Future Systems +AI01243,Data Scientist,89015,CAD,111269,MI,FL,Canada,L,India,100,"Kubernetes, Python, Azure",PhD,3,Transportation,2025-02-25,2025-03-24,1473,8.2,Cloud AI Solutions +AI01244,Principal Data Scientist,101256,GBP,75942,MI,CT,United Kingdom,L,Brazil,0,"PyTorch, Linux, Spark",PhD,4,Manufacturing,2024-10-28,2024-11-12,635,6.8,Digital Transformation LLC +AI01245,Machine Learning Engineer,223846,EUR,190269,EX,FL,Austria,M,Austria,50,"Hadoop, TensorFlow, Python",PhD,10,Finance,2024-11-02,2024-12-03,1775,8.2,Algorithmic Solutions +AI01246,Data Analyst,89705,CAD,112131,MI,PT,Canada,L,Canada,0,"Scala, Python, Kubernetes",Associate,4,Gaming,2024-11-23,2025-01-08,1486,8.3,DataVision Ltd +AI01247,Head of AI,173178,USD,173178,EX,FL,South Korea,L,South Korea,0,"Python, AWS, Statistics, Computer Vision, SQL",Associate,17,Real Estate,2025-03-10,2025-04-07,2301,6.6,TechCorp Inc +AI01248,Deep Learning Engineer,119123,USD,119123,SE,PT,Norway,S,Portugal,100,"Data Visualization, Python, TensorFlow",Associate,9,Automotive,2024-11-16,2025-01-05,2295,9.7,Autonomous Tech +AI01249,Robotics Engineer,205428,USD,205428,EX,FL,United States,L,United States,0,"R, Spark, Mathematics, TensorFlow, Deep Learning",Associate,10,Finance,2024-06-30,2024-08-22,1349,8.2,TechCorp Inc +AI01250,Deep Learning Engineer,107614,USD,107614,SE,FT,Israel,M,Switzerland,0,"Statistics, NLP, GCP, Python, PyTorch",Bachelor,5,Gaming,2024-04-02,2024-06-11,2346,7.6,Advanced Robotics +AI01251,AI Architect,96395,USD,96395,SE,FT,Israel,M,Israel,50,"Git, PyTorch, Statistics",PhD,5,Energy,2024-10-21,2024-11-27,824,5.4,Quantum Computing Inc +AI01252,Deep Learning Engineer,113420,USD,113420,EN,CT,Norway,L,Norway,50,"Spark, Hadoop, PyTorch, TensorFlow, NLP",Master,1,Technology,2024-07-10,2024-09-11,1658,7.3,DataVision Ltd +AI01253,Machine Learning Engineer,186496,USD,186496,EX,FL,Israel,L,Israel,100,"Azure, AWS, Computer Vision, Java",Bachelor,19,Finance,2024-04-02,2024-05-14,1245,9.2,Smart Analytics +AI01254,Research Scientist,212359,USD,212359,EX,FL,Finland,M,Finland,0,"PyTorch, NLP, Hadoop",Associate,13,Technology,2024-08-01,2024-08-31,508,8.3,TechCorp Inc +AI01255,Head of AI,48963,USD,48963,SE,CT,India,L,India,100,"Python, Computer Vision, TensorFlow",Associate,9,Telecommunications,2025-04-15,2025-05-27,1577,5.6,Quantum Computing Inc +AI01256,Principal Data Scientist,84644,EUR,71947,MI,FL,France,L,France,100,"NLP, Kubernetes, Python",Bachelor,4,Healthcare,2025-02-25,2025-04-03,1615,5.7,Quantum Computing Inc +AI01257,Robotics Engineer,129200,USD,129200,MI,CT,Denmark,L,Denmark,100,"Java, SQL, Kubernetes, Computer Vision",Associate,4,Manufacturing,2025-03-06,2025-05-16,1076,9.3,Neural Networks Co +AI01258,AI Research Scientist,131449,JPY,14459390,SE,FT,Japan,M,Japan,50,"SQL, Hadoop, NLP, Deep Learning, GCP",Associate,9,Retail,2025-02-25,2025-05-08,2118,7.4,Digital Transformation LLC +AI01259,Computer Vision Engineer,37726,USD,37726,EN,CT,China,L,United States,0,"Git, Python, PyTorch, GCP, AWS",PhD,1,Media,2024-03-18,2024-04-03,2339,9.5,Machine Intelligence Group +AI01260,Robotics Engineer,147408,USD,147408,SE,CT,United States,L,United States,0,"Scala, Python, AWS",Master,6,Media,2024-09-26,2024-11-18,652,6.5,DeepTech Ventures +AI01261,Autonomous Systems Engineer,68165,USD,68165,EN,PT,United States,S,Netherlands,0,"Azure, Linux, Computer Vision, R, Java",Bachelor,1,Finance,2024-07-30,2024-10-07,1978,8.5,Quantum Computing Inc +AI01262,Head of AI,153774,USD,153774,EX,FL,Finland,M,Finland,100,"Azure, Hadoop, AWS, Docker",Master,15,Automotive,2024-06-30,2024-08-18,1117,6.7,Quantum Computing Inc +AI01263,AI Consultant,139995,EUR,118996,EX,PT,Austria,S,Colombia,50,"Mathematics, Computer Vision, Linux, Scala, PyTorch",Associate,13,Government,2024-02-13,2024-04-18,546,9,Machine Intelligence Group +AI01264,Computer Vision Engineer,126306,CAD,157883,SE,CT,Canada,S,Vietnam,0,"Azure, R, TensorFlow, AWS, Deep Learning",Associate,6,Transportation,2024-04-20,2024-06-17,2177,8.8,Algorithmic Solutions +AI01265,Principal Data Scientist,142937,USD,142937,SE,FL,United States,S,United States,50,"Git, Python, R, MLOps, Statistics",Bachelor,5,Healthcare,2024-03-12,2024-05-15,1101,5.8,Cloud AI Solutions +AI01266,Data Analyst,157493,USD,157493,SE,FL,Norway,L,Norway,0,"PyTorch, Hadoop, TensorFlow",PhD,8,Media,2024-04-01,2024-04-30,1738,5.9,Algorithmic Solutions +AI01267,Research Scientist,81840,USD,81840,EN,FT,Denmark,S,Denmark,50,"Python, Docker, Deep Learning, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-07,558,8.5,Neural Networks Co +AI01268,AI Product Manager,120340,USD,120340,MI,CT,Norway,S,Norway,0,"Spark, TensorFlow, Python",Associate,2,Transportation,2024-12-18,2025-02-20,2435,9.3,Algorithmic Solutions +AI01269,Deep Learning Engineer,133498,GBP,100124,MI,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,3,Gaming,2024-04-02,2024-05-04,2347,9.6,Autonomous Tech +AI01270,Autonomous Systems Engineer,168321,EUR,143073,EX,PT,Netherlands,M,Netherlands,100,"Mathematics, R, NLP, Deep Learning",Master,18,Automotive,2025-02-13,2025-04-27,1845,7.9,Future Systems +AI01271,Machine Learning Engineer,128450,CAD,160563,SE,PT,Canada,M,Canada,50,"SQL, Hadoop, Git, AWS",Bachelor,7,Healthcare,2024-03-29,2024-05-23,552,6.2,DeepTech Ventures +AI01272,Robotics Engineer,71869,SGD,93430,EN,FT,Singapore,M,Luxembourg,100,"Tableau, Azure, Scala, Computer Vision",Associate,0,Energy,2024-10-23,2024-12-19,1601,7.9,Advanced Robotics +AI01273,AI Architect,86340,USD,86340,MI,FL,Sweden,M,Sweden,0,"AWS, Scala, Hadoop",Master,2,Consulting,2024-12-17,2025-02-05,1229,5,Smart Analytics +AI01274,AI Product Manager,73047,CAD,91309,EN,PT,Canada,M,Australia,100,"NLP, Computer Vision, Python, Hadoop, TensorFlow",Associate,1,Finance,2024-01-17,2024-02-04,1706,8.6,Predictive Systems +AI01275,Principal Data Scientist,125916,AUD,169987,MI,PT,Australia,L,Australia,50,"Tableau, Python, SQL",Master,3,Real Estate,2024-10-25,2024-12-04,1314,9.1,Autonomous Tech +AI01276,AI Software Engineer,107722,USD,107722,SE,PT,Finland,M,Finland,0,"GCP, R, Docker, SQL",PhD,6,Media,2024-08-04,2024-09-20,2439,5.2,DeepTech Ventures +AI01277,AI Architect,100220,USD,100220,MI,PT,Ireland,M,Ukraine,100,"Java, Azure, Spark, Mathematics",Associate,3,Real Estate,2025-04-12,2025-06-17,1841,9.7,DataVision Ltd +AI01278,Machine Learning Researcher,141420,USD,141420,EX,FL,Finland,S,Finland,50,"Linux, PyTorch, Hadoop",Associate,15,Telecommunications,2024-07-26,2024-10-07,877,9.3,Cognitive Computing +AI01279,ML Ops Engineer,43276,USD,43276,SE,FT,China,S,China,0,"AWS, Docker, Computer Vision, PyTorch, SQL",Bachelor,7,Finance,2025-01-26,2025-02-22,2494,6.5,Machine Intelligence Group +AI01280,ML Ops Engineer,101313,EUR,86116,SE,FT,Germany,S,Germany,50,"Statistics, Spark, Data Visualization",Associate,6,Government,2025-03-28,2025-05-08,937,9.9,DataVision Ltd +AI01281,Data Analyst,238881,EUR,203049,EX,FT,Austria,L,Austria,0,"PyTorch, NLP, Scala, Linux",PhD,13,Technology,2024-05-03,2024-07-09,897,7.5,Future Systems +AI01282,Data Scientist,144471,SGD,187812,SE,FL,Singapore,M,Singapore,100,"Java, Deep Learning, Azure",Associate,8,Real Estate,2024-04-01,2024-05-09,984,6,Neural Networks Co +AI01283,Head of AI,71781,EUR,61014,MI,CT,Austria,M,Estonia,100,"Docker, R, Linux, SQL",Bachelor,4,Education,2024-05-05,2024-06-15,2151,5.9,Quantum Computing Inc +AI01284,AI Architect,34334,USD,34334,MI,FT,India,M,Norway,50,"Hadoop, GCP, PyTorch, MLOps, TensorFlow",PhD,3,Government,2024-07-20,2024-08-07,1662,5.8,Neural Networks Co +AI01285,AI Research Scientist,59699,USD,59699,EN,PT,Sweden,L,Sweden,0,"Tableau, MLOps, Scala, Java, NLP",Master,1,Telecommunications,2024-03-09,2024-04-17,526,9.8,Autonomous Tech +AI01286,AI Specialist,74398,SGD,96717,EN,PT,Singapore,L,Denmark,50,"GCP, Kubernetes, Data Visualization, Deep Learning",PhD,1,Gaming,2024-07-05,2024-08-04,560,6.5,Smart Analytics +AI01287,Data Scientist,114132,USD,114132,MI,CT,Israel,L,Israel,100,"R, Spark, NLP, Hadoop",PhD,4,Real Estate,2024-04-02,2024-06-01,1575,7.8,Quantum Computing Inc +AI01288,AI Specialist,82988,USD,82988,EN,FL,Israel,L,United Kingdom,50,"NLP, TensorFlow, PyTorch, Deep Learning, AWS",PhD,1,Gaming,2024-11-05,2024-11-20,1031,5.3,Algorithmic Solutions +AI01289,Data Engineer,129184,USD,129184,MI,FT,Denmark,M,Denmark,100,"Scala, Java, Computer Vision, R, Tableau",Associate,4,Transportation,2024-06-19,2024-08-22,2210,8.1,Autonomous Tech +AI01290,Head of AI,122761,USD,122761,SE,PT,Sweden,S,Sweden,100,"Java, Scala, Mathematics",Master,7,Automotive,2024-07-17,2024-09-06,1608,9.1,TechCorp Inc +AI01291,Machine Learning Engineer,176080,USD,176080,EX,PT,South Korea,S,South Korea,50,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,10,Manufacturing,2024-08-08,2024-09-14,2453,7.3,Cognitive Computing +AI01292,AI Software Engineer,132322,USD,132322,MI,CT,Denmark,L,Denmark,0,"PyTorch, MLOps, Scala, Computer Vision",PhD,3,Healthcare,2024-09-08,2024-11-11,2323,6.5,Machine Intelligence Group +AI01293,Head of AI,220734,EUR,187624,EX,CT,Netherlands,S,Netherlands,50,"TensorFlow, Azure, Scala, Statistics",Associate,19,Media,2024-04-24,2024-05-20,1183,8.8,Advanced Robotics +AI01294,Deep Learning Engineer,210396,USD,210396,EX,PT,Ireland,S,Ireland,0,"Git, MLOps, Kubernetes, Java, Azure",PhD,10,Energy,2025-03-19,2025-04-05,1745,5.2,Future Systems +AI01295,Research Scientist,178095,USD,178095,SE,CT,Norway,L,New Zealand,100,"Python, Tableau, Azure, Statistics",Bachelor,9,Healthcare,2024-09-16,2024-10-12,1142,5.7,Machine Intelligence Group +AI01296,AI Consultant,130897,EUR,111262,EX,FL,France,S,France,50,"GCP, Linux, Data Visualization",Associate,11,Real Estate,2024-03-05,2024-03-30,1235,5.1,Advanced Robotics +AI01297,Computer Vision Engineer,278652,EUR,236854,EX,FL,Netherlands,L,Netherlands,100,"R, Kubernetes, NLP",PhD,14,Real Estate,2025-04-19,2025-05-29,1960,5.7,Cognitive Computing +AI01298,ML Ops Engineer,241681,USD,241681,EX,FL,Finland,L,Finland,0,"Kubernetes, Azure, AWS",Associate,10,Gaming,2024-10-25,2024-12-05,2150,6.3,TechCorp Inc +AI01299,Data Scientist,108165,USD,108165,MI,FL,Norway,S,Poland,50,"Data Visualization, Linux, MLOps, R, NLP",PhD,2,Media,2025-03-09,2025-05-16,962,7.7,Smart Analytics +AI01300,AI Research Scientist,37809,USD,37809,SE,CT,India,M,Estonia,0,"Hadoop, Data Visualization, NLP, Python, Docker",Bachelor,7,Government,2024-05-24,2024-06-13,1144,9.4,DeepTech Ventures +AI01301,Machine Learning Engineer,59161,USD,59161,SE,CT,China,L,China,100,"SQL, Tableau, Scala, Data Visualization",Bachelor,6,Consulting,2024-10-03,2024-11-01,848,9.8,Neural Networks Co +AI01302,Deep Learning Engineer,65717,AUD,88718,EN,FL,Australia,M,Australia,50,"Scala, Git, TensorFlow, Linux",PhD,1,Gaming,2024-08-25,2024-10-20,2168,8.9,Neural Networks Co +AI01303,Machine Learning Engineer,131415,USD,131415,EX,FL,South Korea,M,Czech Republic,0,"TensorFlow, Scala, Computer Vision",Master,14,Finance,2025-04-27,2025-06-20,686,9.2,DataVision Ltd +AI01304,NLP Engineer,165177,CHF,148659,SE,FL,Switzerland,S,Switzerland,0,"Azure, Kubernetes, NLP, AWS",PhD,6,Energy,2024-07-07,2024-09-09,2397,8.6,Algorithmic Solutions +AI01305,Machine Learning Researcher,134710,USD,134710,SE,PT,Finland,L,Finland,50,"Python, Hadoop, NLP",Associate,9,Automotive,2025-01-27,2025-03-22,898,5.9,Smart Analytics +AI01306,AI Specialist,132331,EUR,112481,SE,CT,France,L,France,100,"NLP, Scala, Kubernetes",Master,6,Automotive,2025-02-14,2025-03-17,1623,6,Quantum Computing Inc +AI01307,Machine Learning Researcher,25085,USD,25085,EN,CT,China,S,China,100,"TensorFlow, Scala, PyTorch, GCP, Git",Associate,1,Manufacturing,2024-07-31,2024-09-25,2291,5.2,DataVision Ltd +AI01308,AI Architect,81436,USD,81436,EN,FL,United States,M,United States,50,"Java, Docker, Tableau, Linux, Deep Learning",Associate,0,Technology,2024-11-25,2025-01-31,1081,8.4,Autonomous Tech +AI01309,Robotics Engineer,121581,JPY,13373910,SE,FT,Japan,M,Japan,100,"GCP, Kubernetes, AWS, Docker",Associate,8,Technology,2024-12-10,2025-01-31,1652,9.7,Quantum Computing Inc +AI01310,NLP Engineer,85043,USD,85043,MI,CT,South Korea,M,South Korea,100,"Kubernetes, PyTorch, Computer Vision, GCP, Git",Master,3,Telecommunications,2024-08-20,2024-10-26,1219,8,DeepTech Ventures +AI01311,Principal Data Scientist,77847,EUR,66170,EN,PT,Netherlands,L,Netherlands,50,"Mathematics, Linux, Scala, GCP, Kubernetes",Bachelor,0,Consulting,2024-07-31,2024-09-24,2283,7.1,Cloud AI Solutions +AI01312,Research Scientist,112294,EUR,95450,SE,FT,France,M,France,50,"Python, Java, Hadoop, Deep Learning",PhD,6,Government,2024-09-17,2024-11-16,2496,7.4,Smart Analytics +AI01313,Autonomous Systems Engineer,118482,USD,118482,SE,FT,Finland,M,Portugal,50,"Kubernetes, Docker, NLP, Python, Deep Learning",Master,7,Finance,2024-02-01,2024-02-20,1250,7.6,Neural Networks Co +AI01314,NLP Engineer,76423,USD,76423,EN,PT,United States,M,United States,0,"SQL, Data Visualization, Scala, GCP",Associate,1,Consulting,2024-05-27,2024-07-17,2180,8.7,Autonomous Tech +AI01315,Computer Vision Engineer,66969,EUR,56924,MI,CT,Austria,S,Israel,0,"Python, TensorFlow, Spark, Deep Learning",Associate,2,Government,2024-06-29,2024-08-20,2048,8.5,Predictive Systems +AI01316,AI Architect,88996,USD,88996,MI,FL,Ireland,L,Ireland,100,"SQL, Mathematics, Python",Bachelor,4,Finance,2024-01-12,2024-02-03,2325,8.4,Smart Analytics +AI01317,AI Architect,67741,GBP,50806,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Spark, Computer Vision, PyTorch, Linux",Master,0,Manufacturing,2024-07-24,2024-08-18,808,8.6,Smart Analytics +AI01318,AI Architect,104123,CHF,93711,EN,FL,Switzerland,M,Switzerland,0,"TensorFlow, Computer Vision, NLP",Master,0,Automotive,2024-09-16,2024-10-12,1848,5.4,TechCorp Inc +AI01319,AI Specialist,52117,SGD,67752,EN,FL,Singapore,S,Singapore,50,"Kubernetes, GCP, Linux",PhD,1,Government,2025-03-20,2025-05-17,1881,8.5,Cognitive Computing +AI01320,AI Specialist,107002,USD,107002,EN,CT,Denmark,L,South Korea,100,"GCP, R, Tableau, Statistics, Data Visualization",Bachelor,1,Retail,2024-03-12,2024-04-20,2188,9.9,Algorithmic Solutions +AI01321,Head of AI,171421,JPY,18856310,EX,FT,Japan,S,Japan,0,"Scala, Computer Vision, Tableau, Statistics",Bachelor,12,Education,2025-02-26,2025-04-27,867,7.3,Quantum Computing Inc +AI01322,Principal Data Scientist,102160,USD,102160,SE,FL,Finland,M,Norway,50,"Kubernetes, Scala, Tableau, MLOps",Associate,5,Transportation,2024-12-16,2025-02-04,1617,9.4,Advanced Robotics +AI01323,Robotics Engineer,78797,GBP,59098,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, TensorFlow, R",Associate,0,Automotive,2024-10-11,2024-12-01,708,9.2,DeepTech Ventures +AI01324,Machine Learning Researcher,143483,CAD,179354,SE,CT,Canada,M,Malaysia,0,"Linux, Deep Learning, PyTorch, Mathematics",PhD,8,Education,2025-03-18,2025-04-08,2064,6.2,Machine Intelligence Group +AI01325,Autonomous Systems Engineer,224567,USD,224567,SE,FL,Denmark,L,India,0,"Spark, Linux, Tableau, Data Visualization",Bachelor,7,Automotive,2025-02-03,2025-03-24,1751,7,Smart Analytics +AI01326,Autonomous Systems Engineer,141545,AUD,191086,SE,FL,Australia,L,Australia,0,"Computer Vision, Mathematics, Spark",Bachelor,8,Automotive,2024-10-16,2024-11-09,2451,7.8,Digital Transformation LLC +AI01327,Data Engineer,56427,USD,56427,EN,FT,Israel,M,Hungary,0,"Kubernetes, Tableau, SQL",Bachelor,1,Transportation,2025-01-26,2025-04-07,838,6.1,Future Systems +AI01328,Robotics Engineer,90510,USD,90510,MI,CT,Norway,S,China,100,"SQL, Spark, Mathematics",Bachelor,4,Retail,2024-03-05,2024-04-01,2031,7.2,Future Systems +AI01329,Research Scientist,158669,USD,158669,EX,PT,Israel,S,Israel,100,"SQL, Computer Vision, Docker, AWS, PyTorch",Associate,19,Manufacturing,2024-08-12,2024-08-28,1226,7.8,Digital Transformation LLC +AI01330,AI Software Engineer,74539,JPY,8199290,EN,FT,Japan,S,South Korea,50,"GCP, Java, SQL, R, AWS",PhD,1,Media,2024-12-11,2024-12-30,746,5.1,Neural Networks Co +AI01331,Computer Vision Engineer,124395,EUR,105736,SE,FL,Netherlands,S,Russia,0,"Spark, Git, SQL, Python, TensorFlow",Master,9,Energy,2025-04-15,2025-06-10,2301,9.2,DataVision Ltd +AI01332,AI Research Scientist,174114,USD,174114,EX,PT,United States,M,United States,0,"Data Visualization, MLOps, Tableau, Python, Kubernetes",Master,10,Real Estate,2024-05-15,2024-06-13,2132,7,Digital Transformation LLC +AI01333,Autonomous Systems Engineer,321202,CHF,289082,EX,CT,Switzerland,M,Switzerland,0,"Scala, Linux, Computer Vision",Master,19,Telecommunications,2024-01-14,2024-03-27,1102,9.8,Advanced Robotics +AI01334,NLP Engineer,73469,USD,73469,MI,FL,Sweden,S,Sweden,0,"Python, Hadoop, TensorFlow",Associate,3,Media,2024-02-02,2024-04-08,1664,8.2,DataVision Ltd +AI01335,ML Ops Engineer,142197,USD,142197,SE,PT,Sweden,L,Finland,50,"R, PyTorch, NLP, GCP",PhD,8,Media,2025-03-31,2025-05-14,1349,7.3,Digital Transformation LLC +AI01336,Machine Learning Researcher,157699,EUR,134044,EX,PT,France,S,France,50,"Python, GCP, Scala",Bachelor,19,Consulting,2024-11-05,2024-12-03,1625,7.9,Cognitive Computing +AI01337,Research Scientist,101213,USD,101213,SE,CT,Finland,S,Finland,100,"SQL, Scala, Statistics, Git",Associate,9,Real Estate,2025-04-06,2025-04-28,801,5.1,Predictive Systems +AI01338,AI Architect,84729,USD,84729,MI,CT,Sweden,S,New Zealand,100,"Scala, Spark, Hadoop, Python",Master,3,Automotive,2024-04-07,2024-05-31,1053,9.3,TechCorp Inc +AI01339,Robotics Engineer,87739,CHF,78965,EN,CT,Switzerland,M,Switzerland,0,"R, SQL, Java, Statistics, Linux",Master,0,Finance,2024-10-09,2024-10-28,2211,10,AI Innovations +AI01340,Autonomous Systems Engineer,30121,USD,30121,EN,FL,China,M,Spain,50,"R, Docker, PyTorch",PhD,0,Manufacturing,2024-04-08,2024-06-19,1586,8.1,Digital Transformation LLC +AI01341,Machine Learning Engineer,100916,JPY,11100760,MI,CT,Japan,S,Japan,50,"Scala, Python, MLOps",Bachelor,2,Real Estate,2024-03-17,2024-05-15,2096,5.6,DeepTech Ventures +AI01342,Computer Vision Engineer,55277,USD,55277,EN,FL,Israel,S,Israel,50,"Git, GCP, Kubernetes, Computer Vision, R",Bachelor,0,Finance,2024-08-28,2024-09-24,1348,6.9,DeepTech Ventures +AI01343,ML Ops Engineer,113420,USD,113420,MI,PT,Ireland,L,Romania,0,"Python, TensorFlow, Tableau, MLOps",Master,4,Manufacturing,2025-02-04,2025-03-31,858,7.3,Digital Transformation LLC +AI01344,Machine Learning Engineer,50194,USD,50194,EN,FL,Finland,M,Finland,0,"SQL, Java, Python, Scala, Deep Learning",Bachelor,1,Automotive,2025-02-08,2025-04-11,664,8.1,DataVision Ltd +AI01345,Head of AI,98859,USD,98859,EX,CT,India,L,India,50,"Azure, Python, Kubernetes, Statistics, Deep Learning",Associate,14,Consulting,2024-04-25,2024-06-20,1997,9.2,Predictive Systems +AI01346,Deep Learning Engineer,195373,CHF,175836,SE,FL,Switzerland,M,Switzerland,100,"PyTorch, Git, Tableau",Associate,7,Finance,2025-02-21,2025-03-21,555,7.2,Cloud AI Solutions +AI01347,AI Software Engineer,150038,AUD,202551,SE,CT,Australia,M,Australia,100,"SQL, TensorFlow, Mathematics, Python",Master,8,Automotive,2024-04-26,2024-05-21,2430,5.8,Autonomous Tech +AI01348,AI Software Engineer,46960,USD,46960,EN,PT,South Korea,S,Chile,100,"NLP, Azure, Data Visualization",PhD,1,Government,2024-05-21,2024-07-18,2271,9.1,Autonomous Tech +AI01349,Research Scientist,256508,EUR,218032,EX,FL,Germany,L,Germany,0,"R, Data Visualization, Docker, Scala, Deep Learning",Associate,14,Government,2024-07-04,2024-08-28,1511,7,DeepTech Ventures +AI01350,Principal Data Scientist,123766,GBP,92825,MI,CT,United Kingdom,L,United Kingdom,50,"Python, TensorFlow, R, Computer Vision, PyTorch",Bachelor,4,Retail,2024-06-14,2024-07-20,868,5.9,Neural Networks Co +AI01351,Data Analyst,138655,EUR,117857,SE,PT,Germany,L,Germany,50,"Deep Learning, NLP, Kubernetes, Hadoop",Master,9,Technology,2024-03-10,2024-04-09,1039,6.2,Digital Transformation LLC +AI01352,AI Software Engineer,112307,EUR,95461,MI,FT,Netherlands,M,Vietnam,0,"Python, Azure, Linux, TensorFlow, Java",Associate,3,Government,2024-05-04,2024-06-30,1320,9.4,Future Systems +AI01353,AI Product Manager,75008,USD,75008,EX,FT,India,L,New Zealand,50,"PyTorch, TensorFlow, Spark, Tableau, Scala",Bachelor,15,Retail,2024-09-23,2024-10-29,1493,8,Algorithmic Solutions +AI01354,Robotics Engineer,72038,USD,72038,MI,CT,South Korea,S,South Korea,50,"Python, Docker, AWS, GCP",PhD,3,Energy,2024-05-01,2024-06-26,2322,5.3,DeepTech Ventures +AI01355,AI Software Engineer,141038,USD,141038,SE,CT,Finland,M,Finland,100,"Statistics, MLOps, Python, Linux, Deep Learning",Bachelor,6,Transportation,2025-04-06,2025-04-25,1720,7.3,Algorithmic Solutions +AI01356,AI Research Scientist,113496,USD,113496,SE,CT,Israel,S,Israel,50,"R, Spark, TensorFlow",PhD,9,Real Estate,2024-10-29,2024-11-13,542,8.3,Neural Networks Co +AI01357,Computer Vision Engineer,100144,EUR,85122,SE,FL,France,S,France,0,"Tableau, PyTorch, TensorFlow",PhD,8,Healthcare,2024-09-18,2024-10-22,1494,5.8,Cloud AI Solutions +AI01358,AI Research Scientist,210470,SGD,273611,EX,PT,Singapore,M,Singapore,0,"PyTorch, Azure, Hadoop, Java",Bachelor,12,Real Estate,2024-07-05,2024-07-25,1609,8.3,Autonomous Tech +AI01359,Head of AI,66974,CAD,83718,MI,FT,Canada,S,Canada,100,"Python, Docker, TensorFlow, PyTorch",Master,3,Media,2024-07-03,2024-08-14,2141,7.4,Future Systems +AI01360,Autonomous Systems Engineer,137007,EUR,116456,SE,FT,Netherlands,L,Malaysia,100,"Scala, Computer Vision, SQL, PyTorch, Azure",Associate,8,Government,2025-03-10,2025-05-02,1033,6.7,Cognitive Computing +AI01361,Machine Learning Engineer,80135,USD,80135,MI,CT,Ireland,S,Ireland,50,"Data Visualization, GCP, AWS, SQL, NLP",PhD,4,Government,2024-07-23,2024-10-01,2267,8.8,Smart Analytics +AI01362,Research Scientist,158546,EUR,134764,SE,FT,Netherlands,M,Netherlands,50,"SQL, Hadoop, R, Computer Vision, Docker",Associate,9,Manufacturing,2024-02-03,2024-04-09,2352,9.9,Algorithmic Solutions +AI01363,Deep Learning Engineer,194317,USD,194317,EX,FT,Denmark,M,Denmark,100,"Git, GCP, Tableau, Kubernetes",Bachelor,19,Energy,2024-03-31,2024-06-02,1493,7.2,Digital Transformation LLC +AI01364,Head of AI,83493,EUR,70969,MI,CT,Netherlands,M,Netherlands,50,"Java, Spark, GCP",Master,2,Automotive,2024-05-26,2024-06-10,2305,6.9,Predictive Systems +AI01365,Data Analyst,104222,USD,104222,EN,FT,United States,L,Malaysia,100,"Spark, SQL, Azure, Git, Hadoop",PhD,1,Government,2024-12-06,2025-01-01,1541,5.3,AI Innovations +AI01366,Autonomous Systems Engineer,49854,USD,49854,MI,CT,China,L,China,100,"Python, Hadoop, Computer Vision, Spark, Kubernetes",Master,4,Automotive,2025-01-06,2025-01-28,2345,6.9,Cloud AI Solutions +AI01367,Autonomous Systems Engineer,158519,CAD,198149,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, Mathematics, Hadoop, AWS",Bachelor,14,Government,2025-03-07,2025-04-26,2403,9.8,TechCorp Inc +AI01368,Autonomous Systems Engineer,180734,USD,180734,SE,PT,United States,L,United States,50,"Java, Python, Linux",Master,6,Technology,2024-02-12,2024-04-09,2239,6.3,Machine Intelligence Group +AI01369,ML Ops Engineer,261993,USD,261993,EX,PT,Ireland,L,Russia,0,"SQL, GCP, Mathematics, NLP",Master,11,Telecommunications,2025-04-11,2025-05-10,2341,5.4,Cognitive Computing +AI01370,Robotics Engineer,98054,USD,98054,SE,FT,Finland,M,Finland,0,"PyTorch, SQL, Git, MLOps, AWS",Associate,9,Gaming,2024-01-08,2024-03-04,950,9.8,DataVision Ltd +AI01371,AI Product Manager,82903,USD,82903,MI,PT,South Korea,M,South Korea,50,"Mathematics, Docker, NLP",Bachelor,4,Gaming,2024-12-24,2025-03-05,2095,8.2,Algorithmic Solutions +AI01372,AI Software Engineer,121557,USD,121557,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Scala, Statistics, GCP",PhD,4,Education,2024-08-27,2024-10-09,1642,8.2,Cognitive Computing +AI01373,Data Analyst,172640,USD,172640,SE,FT,Norway,S,Norway,50,"Linux, Kubernetes, SQL",PhD,6,Manufacturing,2024-11-08,2024-12-31,1912,6.7,DataVision Ltd +AI01374,AI Product Manager,122704,EUR,104298,SE,FT,France,M,France,50,"Azure, Tableau, SQL, GCP, Git",PhD,9,Retail,2024-05-24,2024-07-10,1627,9.2,Future Systems +AI01375,Deep Learning Engineer,60832,JPY,6691520,EN,CT,Japan,S,Japan,0,"Tableau, Java, Python, Azure",Bachelor,1,Transportation,2024-06-07,2024-08-17,2416,5.8,AI Innovations +AI01376,AI Research Scientist,134265,USD,134265,EX,FL,South Korea,L,South Korea,0,"Kubernetes, GCP, Mathematics, AWS",Associate,19,Media,2024-09-27,2024-11-06,635,7.2,Cloud AI Solutions +AI01377,Machine Learning Engineer,65618,USD,65618,EN,FT,Denmark,S,Thailand,100,"R, Linux, Hadoop, Git, Computer Vision",Bachelor,1,Gaming,2025-03-15,2025-04-08,508,5.4,Neural Networks Co +AI01378,NLP Engineer,104745,GBP,78559,SE,FL,United Kingdom,S,Denmark,100,"Docker, Linux, Data Visualization, R",Bachelor,7,Government,2025-02-01,2025-03-13,1749,9.3,DataVision Ltd +AI01379,AI Software Engineer,53253,GBP,39940,EN,FL,United Kingdom,S,United Kingdom,50,"PyTorch, Spark, TensorFlow, Azure, Hadoop",Master,0,Technology,2025-04-11,2025-06-03,652,9,Cloud AI Solutions +AI01380,Computer Vision Engineer,166691,JPY,18336010,EX,PT,Japan,S,Japan,100,"Mathematics, Deep Learning, Scala, R, PyTorch",Master,14,Automotive,2024-05-17,2024-06-10,1849,7,DeepTech Ventures +AI01381,Computer Vision Engineer,146267,CAD,182834,EX,PT,Canada,M,Canada,0,"Scala, R, Docker",PhD,10,Gaming,2025-01-10,2025-02-13,2428,7,DeepTech Ventures +AI01382,AI Consultant,97969,USD,97969,SE,FT,Finland,M,Finland,0,"Spark, PyTorch, MLOps, Tableau",PhD,9,Energy,2024-06-09,2024-07-07,530,9.7,Advanced Robotics +AI01383,Principal Data Scientist,206614,CAD,258268,EX,PT,Canada,M,Ireland,100,"Hadoop, R, Kubernetes",Bachelor,14,Government,2024-02-11,2024-03-20,874,6.2,Machine Intelligence Group +AI01384,Data Analyst,78327,EUR,66578,MI,FT,Austria,M,Austria,0,"Data Visualization, NLP, Mathematics",PhD,3,Consulting,2024-06-29,2024-08-23,2076,5.7,AI Innovations +AI01385,Robotics Engineer,70510,EUR,59934,EN,PT,Austria,L,Turkey,0,"R, Python, TensorFlow, Tableau, Statistics",Bachelor,0,Gaming,2024-08-28,2024-09-29,912,7.1,DataVision Ltd +AI01386,Data Analyst,41791,USD,41791,SE,FT,India,M,India,100,"Linux, SQL, Mathematics, Hadoop",Bachelor,7,Media,2024-12-02,2025-01-11,2227,9.7,Algorithmic Solutions +AI01387,AI Consultant,115800,EUR,98430,MI,FL,Austria,L,Luxembourg,50,"Python, TensorFlow, Spark, PyTorch",Bachelor,3,Media,2025-02-02,2025-03-29,1284,7.9,Digital Transformation LLC +AI01388,Machine Learning Engineer,113860,USD,113860,SE,PT,Finland,L,Sweden,100,"SQL, PyTorch, Python, Docker",Associate,6,Healthcare,2024-05-02,2024-07-11,1096,8.5,AI Innovations +AI01389,Data Analyst,181595,USD,181595,SE,FT,United States,L,United States,100,"Docker, PyTorch, Data Visualization, Hadoop, Spark",Master,7,Automotive,2024-12-31,2025-03-10,1181,8.7,Digital Transformation LLC +AI01390,AI Product Manager,157567,EUR,133932,EX,FT,Austria,L,Israel,50,"Azure, Hadoop, Java, Deep Learning",Associate,18,Finance,2024-01-14,2024-02-22,2191,5.6,Quantum Computing Inc +AI01391,Autonomous Systems Engineer,124885,EUR,106152,MI,FL,Netherlands,L,Netherlands,0,"Linux, AWS, Spark, SQL, PyTorch",PhD,4,Automotive,2024-12-11,2025-01-11,1416,9.2,Smart Analytics +AI01392,NLP Engineer,123910,USD,123910,EX,FL,Ireland,S,Ireland,50,"PyTorch, Tableau, Computer Vision, Git",Bachelor,16,Transportation,2024-09-22,2024-11-24,1656,8,Neural Networks Co +AI01393,AI Specialist,137838,USD,137838,SE,FL,Sweden,L,Belgium,0,"Mathematics, MLOps, Tableau, Kubernetes, Python",PhD,8,Gaming,2024-07-12,2024-08-07,732,7.8,Cloud AI Solutions +AI01394,Data Engineer,313735,USD,313735,EX,FT,Denmark,M,Denmark,0,"NLP, Linux, Kubernetes",Associate,12,Healthcare,2024-12-16,2025-01-06,1940,6.7,Neural Networks Co +AI01395,Computer Vision Engineer,96380,USD,96380,EN,PT,Denmark,M,Ireland,50,"Kubernetes, Python, Statistics",Bachelor,0,Media,2024-10-12,2024-11-30,1399,9,Digital Transformation LLC +AI01396,Data Engineer,63171,EUR,53695,EN,CT,Netherlands,M,Netherlands,100,"Scala, Hadoop, AWS",Bachelor,0,Automotive,2024-12-24,2025-03-03,561,8.8,AI Innovations +AI01397,AI Specialist,123969,USD,123969,SE,FT,Sweden,S,Sweden,0,"SQL, PyTorch, GCP",Bachelor,9,Energy,2025-04-01,2025-04-22,1527,9.8,Quantum Computing Inc +AI01398,Data Analyst,54611,EUR,46419,EN,CT,France,M,France,0,"Python, Linux, TensorFlow, Computer Vision, PyTorch",PhD,0,Technology,2024-12-11,2024-12-26,865,9,Machine Intelligence Group +AI01399,Machine Learning Engineer,119705,USD,119705,MI,PT,Denmark,L,Switzerland,0,"MLOps, Python, R, AWS, Docker",Bachelor,3,Education,2024-03-23,2024-06-02,1556,7.2,Quantum Computing Inc +AI01400,Autonomous Systems Engineer,173697,CHF,156327,SE,FL,Switzerland,S,China,50,"Python, AWS, Scala",Associate,9,Media,2025-01-09,2025-03-23,927,8.2,Algorithmic Solutions +AI01401,Data Scientist,144553,AUD,195147,SE,CT,Australia,L,South Korea,0,"Data Visualization, R, Linux, MLOps",PhD,6,Telecommunications,2024-07-22,2024-09-21,1806,5.8,AI Innovations +AI01402,Research Scientist,76409,GBP,57307,MI,FL,United Kingdom,S,Brazil,50,"AWS, Hadoop, PyTorch",Master,2,Government,2024-10-29,2024-11-12,2125,8.3,DataVision Ltd +AI01403,NLP Engineer,105022,AUD,141780,SE,FT,Australia,M,Japan,0,"Mathematics, Python, Data Visualization, Deep Learning, GCP",PhD,8,Government,2024-01-11,2024-03-12,1947,8.4,Cognitive Computing +AI01404,Data Engineer,147919,AUD,199691,SE,PT,Australia,L,Australia,0,"TensorFlow, Linux, Azure, Mathematics",Bachelor,8,Manufacturing,2024-05-20,2024-07-28,1479,7.6,Neural Networks Co +AI01405,Data Engineer,105054,CHF,94549,EN,CT,Switzerland,L,Switzerland,100,"Azure, Java, Data Visualization",Master,0,Technology,2024-03-06,2024-04-21,740,5.3,Advanced Robotics +AI01406,AI Architect,168883,USD,168883,EX,PT,South Korea,S,South Korea,50,"PyTorch, Spark, R, TensorFlow",Bachelor,17,Government,2024-04-02,2024-04-28,1976,5.5,TechCorp Inc +AI01407,AI Architect,54905,USD,54905,EN,PT,Finland,S,Malaysia,50,"SQL, Python, Azure, Hadoop, Mathematics",PhD,0,Government,2025-02-24,2025-03-31,1770,6.6,Machine Intelligence Group +AI01408,Data Scientist,73214,USD,73214,EX,CT,China,M,China,50,"SQL, Statistics, PyTorch, AWS",Bachelor,19,Government,2024-01-14,2024-03-03,1326,8.6,Future Systems +AI01409,Computer Vision Engineer,75589,USD,75589,MI,PT,South Korea,S,South Korea,50,"Python, Statistics, Computer Vision, Linux",Bachelor,4,Automotive,2024-02-11,2024-04-16,2026,7.2,Digital Transformation LLC +AI01410,Robotics Engineer,104795,CHF,94316,EN,CT,Switzerland,M,Japan,50,"Deep Learning, TensorFlow, Python, Linux, Java",Master,1,Telecommunications,2025-04-06,2025-05-28,1865,6.6,Future Systems +AI01411,AI Architect,19456,USD,19456,EN,CT,India,S,India,0,"Java, GCP, AWS, Deep Learning, Spark",Associate,1,Automotive,2024-02-24,2024-03-11,1072,9.7,Autonomous Tech +AI01412,Data Engineer,212599,EUR,180709,EX,FT,Austria,S,Austria,50,"Python, Docker, SQL, Linux",Master,13,Automotive,2024-07-11,2024-07-27,1697,10,DeepTech Ventures +AI01413,AI Research Scientist,63226,JPY,6954860,EN,CT,Japan,M,Japan,0,"Hadoop, Python, TensorFlow, Deep Learning",Bachelor,1,Government,2024-10-04,2024-12-07,963,6.7,Cloud AI Solutions +AI01414,AI Architect,188891,USD,188891,SE,PT,United States,L,Portugal,0,"Python, SQL, Linux",Master,5,Automotive,2024-01-16,2024-03-01,2133,5.8,DeepTech Ventures +AI01415,Head of AI,45335,USD,45335,EN,FT,South Korea,S,South Korea,100,"NLP, SQL, Java, MLOps, Kubernetes",Bachelor,0,Manufacturing,2024-06-01,2024-06-17,1381,6.3,Predictive Systems +AI01416,NLP Engineer,114078,GBP,85559,MI,CT,United Kingdom,M,United Kingdom,50,"Java, TensorFlow, GCP",PhD,4,Technology,2024-05-01,2024-05-26,1203,6.5,Digital Transformation LLC +AI01417,AI Software Engineer,221905,USD,221905,EX,FL,Norway,L,Norway,0,"Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-11-19,2024-12-05,1585,5.9,Algorithmic Solutions +AI01418,Principal Data Scientist,34898,USD,34898,MI,FL,China,M,China,100,"Kubernetes, Linux, Git, SQL, R",PhD,4,Retail,2025-01-17,2025-02-14,1878,7.1,AI Innovations +AI01419,Autonomous Systems Engineer,288283,USD,288283,EX,FL,Ireland,L,Vietnam,50,"Tableau, Statistics, Spark, Kubernetes, Git",Master,17,Consulting,2024-01-31,2024-03-21,882,7.1,Cloud AI Solutions +AI01420,Robotics Engineer,75188,USD,75188,MI,FT,Ireland,M,Ukraine,50,"Python, Git, Azure",Associate,3,Government,2025-04-11,2025-05-26,1123,9,TechCorp Inc +AI01421,Principal Data Scientist,87149,USD,87149,EN,FL,Denmark,S,Italy,50,"Azure, Kubernetes, Docker, SQL, Data Visualization",Associate,1,Real Estate,2024-11-02,2024-11-18,1009,7.4,TechCorp Inc +AI01422,Robotics Engineer,91150,USD,91150,MI,CT,Norway,S,Norway,50,"Java, Python, Computer Vision",PhD,4,Retail,2024-06-05,2024-08-04,2308,7,Quantum Computing Inc +AI01423,Research Scientist,126040,AUD,170154,SE,FL,Australia,S,Australia,50,"Docker, SQL, Mathematics, Spark",Master,9,Manufacturing,2024-05-07,2024-06-21,2052,9.9,DeepTech Ventures +AI01424,AI Research Scientist,187737,USD,187737,EX,FT,Sweden,L,Sweden,0,"Java, R, Mathematics, Computer Vision",PhD,15,Government,2024-03-30,2024-04-25,1706,7,Machine Intelligence Group +AI01425,AI Product Manager,125535,USD,125535,MI,PT,United States,M,United States,0,"Hadoop, PyTorch, Scala, GCP",Bachelor,3,Retail,2024-06-17,2024-07-16,2147,7.7,TechCorp Inc +AI01426,AI Product Manager,373536,USD,373536,EX,FL,Norway,L,Norway,100,"NLP, Kubernetes, Spark",Master,10,Technology,2025-03-20,2025-05-22,730,9.4,DeepTech Ventures +AI01427,Deep Learning Engineer,100732,CHF,90659,EN,FT,Switzerland,M,Switzerland,100,"Tableau, Python, Hadoop, Kubernetes",PhD,1,Media,2024-06-16,2024-07-30,1200,10,Predictive Systems +AI01428,Data Engineer,212371,GBP,159278,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Kubernetes, Tableau, Hadoop, Scala",Bachelor,15,Consulting,2025-03-06,2025-03-20,615,9.5,Autonomous Tech +AI01429,AI Software Engineer,65466,EUR,55646,EN,PT,Germany,L,Germany,0,"Mathematics, PyTorch, Statistics",Master,1,Finance,2024-03-25,2024-05-04,1943,8.2,Quantum Computing Inc +AI01430,Computer Vision Engineer,109204,SGD,141965,MI,PT,Singapore,M,Nigeria,50,"Mathematics, Data Visualization, MLOps, Tableau",Associate,3,Retail,2024-09-15,2024-11-16,1841,5.3,AI Innovations +AI01431,Data Engineer,72736,JPY,8000960,MI,CT,Japan,S,Germany,50,"R, Python, Data Visualization, PyTorch",Associate,2,Telecommunications,2025-02-13,2025-03-21,1794,8.9,AI Innovations +AI01432,Autonomous Systems Engineer,20520,USD,20520,EN,FL,India,M,Israel,100,"R, Spark, Hadoop, Kubernetes, GCP",Associate,0,Gaming,2024-07-21,2024-08-07,2201,8.9,Cloud AI Solutions +AI01433,AI Architect,158930,USD,158930,EX,PT,Ireland,M,Ireland,100,"Spark, PyTorch, Mathematics",PhD,19,Transportation,2025-01-29,2025-03-23,965,7.9,DeepTech Ventures +AI01434,Principal Data Scientist,76074,CHF,68467,EN,FT,Switzerland,M,Switzerland,100,"Scala, Spark, MLOps",Master,0,Gaming,2024-06-14,2024-07-22,2169,6,Cognitive Computing +AI01435,Machine Learning Researcher,59343,EUR,50442,EN,FT,France,S,France,0,"NLP, Mathematics, Kubernetes, Computer Vision, Tableau",Bachelor,1,Government,2024-03-29,2024-05-11,690,8.2,Advanced Robotics +AI01436,Data Scientist,104447,USD,104447,MI,CT,United States,S,United States,100,"Deep Learning, Data Visualization, AWS, TensorFlow, Scala",Bachelor,2,Technology,2024-12-10,2025-02-15,1675,8.4,Neural Networks Co +AI01437,AI Software Engineer,43120,USD,43120,MI,PT,China,M,China,50,"AWS, Docker, NLP",Bachelor,4,Automotive,2024-03-04,2024-04-21,1871,8.9,DataVision Ltd +AI01438,Machine Learning Engineer,219852,EUR,186874,EX,FL,Austria,L,Austria,100,"Hadoop, Kubernetes, TensorFlow, GCP",Associate,14,Healthcare,2024-01-11,2024-03-11,1760,6.6,DataVision Ltd +AI01439,Data Engineer,40164,USD,40164,SE,CT,India,S,India,0,"Scala, Kubernetes, Git, Docker",Bachelor,7,Telecommunications,2024-11-21,2025-01-23,2230,5.9,Digital Transformation LLC +AI01440,Data Analyst,164110,SGD,213343,EX,FT,Singapore,S,Singapore,50,"SQL, Git, GCP",Associate,15,Gaming,2025-01-04,2025-02-01,1042,7.8,Future Systems +AI01441,Machine Learning Researcher,33846,USD,33846,MI,PT,China,S,China,100,"PyTorch, Hadoop, Statistics, AWS, Computer Vision",Bachelor,2,Transportation,2024-03-06,2024-03-22,804,6.8,Digital Transformation LLC +AI01442,Data Engineer,126266,USD,126266,MI,PT,Sweden,L,Sweden,100,"PyTorch, Spark, TensorFlow",Master,4,Energy,2024-06-28,2024-07-28,1765,6.6,Machine Intelligence Group +AI01443,Head of AI,98327,USD,98327,MI,PT,United States,L,United States,50,"R, Data Visualization, Mathematics",Associate,4,Education,2024-09-12,2024-10-04,1849,5.1,Neural Networks Co +AI01444,Data Scientist,77366,GBP,58025,MI,PT,United Kingdom,S,Japan,50,"Python, TensorFlow, NLP, Azure, AWS",PhD,3,Automotive,2024-06-19,2024-08-04,2357,5.6,Cognitive Computing +AI01445,ML Ops Engineer,76129,USD,76129,EN,FL,Denmark,S,Indonesia,50,"Hadoop, PyTorch, MLOps",Master,0,Education,2024-12-01,2024-12-15,788,7.8,Cloud AI Solutions +AI01446,AI Product Manager,134331,CHF,120898,MI,PT,Switzerland,L,Switzerland,100,"Java, Mathematics, TensorFlow",Associate,2,Energy,2024-01-11,2024-02-19,842,10,DeepTech Ventures +AI01447,Data Engineer,56083,EUR,47671,EN,FL,Austria,M,Austria,0,"Python, Statistics, SQL, R, Linux",Master,1,Transportation,2024-07-24,2024-08-16,1613,6.4,AI Innovations +AI01448,Robotics Engineer,147444,USD,147444,EX,CT,Finland,S,Finland,0,"Scala, Spark, Java",PhD,15,Technology,2025-04-18,2025-06-06,2271,5.6,Cloud AI Solutions +AI01449,AI Product Manager,92983,USD,92983,EN,CT,Norway,S,Ghana,50,"TensorFlow, Scala, GCP, Git",PhD,0,Education,2025-01-04,2025-01-26,1036,7.8,Neural Networks Co +AI01450,ML Ops Engineer,83859,EUR,71280,EN,FL,Austria,L,Austria,50,"Tableau, Hadoop, PyTorch",Bachelor,1,Real Estate,2025-01-18,2025-03-31,2435,8.2,Predictive Systems +AI01451,NLP Engineer,84786,EUR,72068,MI,FL,Germany,M,Ukraine,0,"Java, Linux, Statistics, Git",Master,2,Transportation,2025-02-04,2025-03-18,1912,9.2,Digital Transformation LLC +AI01452,Computer Vision Engineer,154829,EUR,131605,EX,CT,Germany,S,Kenya,100,"Tableau, AWS, Hadoop, Kubernetes, Git",Bachelor,11,Energy,2024-08-21,2024-10-30,2309,5.4,DataVision Ltd +AI01453,Machine Learning Engineer,216967,GBP,162725,EX,FT,United Kingdom,S,Chile,0,"R, Scala, NLP, Git, Docker",Bachelor,12,Education,2024-07-18,2024-09-29,1500,8.6,Future Systems +AI01454,Computer Vision Engineer,90170,USD,90170,MI,PT,Ireland,L,Ireland,100,"Git, TensorFlow, Deep Learning",Bachelor,3,Transportation,2024-04-12,2024-05-08,2067,5.6,TechCorp Inc +AI01455,AI Software Engineer,59279,SGD,77063,EN,PT,Singapore,M,Singapore,0,"Python, TensorFlow, PyTorch, Linux",Associate,1,Education,2025-02-22,2025-04-02,2481,9.2,Cloud AI Solutions +AI01456,AI Specialist,85165,USD,85165,EX,FL,China,L,China,100,"MLOps, Spark, Azure, TensorFlow",Bachelor,19,Automotive,2025-03-11,2025-04-29,1813,6.6,Digital Transformation LLC +AI01457,Machine Learning Researcher,58417,EUR,49654,EN,PT,Netherlands,S,United States,100,"Spark, Docker, GCP, Statistics, Python",PhD,1,Technology,2024-07-22,2024-09-17,1842,8.4,Smart Analytics +AI01458,Research Scientist,160456,EUR,136388,EX,CT,Netherlands,M,Netherlands,100,"Python, TensorFlow, MLOps, Spark, R",Master,11,Manufacturing,2024-04-08,2024-05-27,1814,5.4,Autonomous Tech +AI01459,Robotics Engineer,29590,USD,29590,EN,FT,China,S,South Korea,0,"Linux, Data Visualization, Java, Hadoop, NLP",Bachelor,1,Retail,2024-06-10,2024-08-07,1355,5.4,TechCorp Inc +AI01460,Deep Learning Engineer,242489,GBP,181867,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, Hadoop, Python, Mathematics, Docker",Bachelor,19,Telecommunications,2024-08-14,2024-09-04,985,5.8,Algorithmic Solutions +AI01461,ML Ops Engineer,136042,GBP,102032,SE,FT,United Kingdom,S,Austria,0,"Scala, Kubernetes, Linux, AWS",Bachelor,8,Gaming,2024-07-19,2024-09-08,2139,8.7,Future Systems +AI01462,AI Software Engineer,104200,CAD,130250,SE,FT,Canada,M,Canada,100,"Linux, Kubernetes, Scala",Master,9,Gaming,2025-03-26,2025-05-11,2429,6.3,Advanced Robotics +AI01463,Principal Data Scientist,137878,EUR,117196,SE,CT,Germany,L,Latvia,50,"R, SQL, Tableau, MLOps, Kubernetes",Master,7,Manufacturing,2025-03-10,2025-03-31,640,7.2,Cognitive Computing +AI01464,ML Ops Engineer,187710,USD,187710,SE,PT,Denmark,M,Denmark,50,"Git, NLP, SQL",Bachelor,8,Consulting,2025-02-15,2025-03-25,1597,7.4,Algorithmic Solutions +AI01465,AI Software Engineer,50439,USD,50439,SE,CT,India,M,India,100,"Spark, Python, TensorFlow, Statistics, Java",Master,7,Telecommunications,2024-01-08,2024-03-03,2331,7.7,Algorithmic Solutions +AI01466,AI Architect,29300,USD,29300,EN,FT,India,L,India,50,"Tableau, R, MLOps",PhD,1,Media,2024-11-03,2025-01-01,2378,8.5,Algorithmic Solutions +AI01467,Machine Learning Engineer,93689,USD,93689,EX,FT,China,S,China,0,"Python, TensorFlow, Mathematics, Kubernetes, Docker",Associate,18,Real Estate,2024-04-02,2024-05-26,2251,8.3,Smart Analytics +AI01468,Data Analyst,182500,USD,182500,EX,FL,United States,M,United States,0,"Mathematics, MLOps, Azure",Associate,16,Automotive,2024-11-22,2024-12-29,1397,9.6,Neural Networks Co +AI01469,Robotics Engineer,149041,AUD,201205,SE,FL,Australia,L,Australia,0,"PyTorch, TensorFlow, Scala, Git",PhD,8,Education,2025-03-10,2025-04-23,851,7.2,Digital Transformation LLC +AI01470,Computer Vision Engineer,43748,EUR,37186,EN,PT,France,S,Mexico,50,"Deep Learning, Java, SQL, Git, Docker",PhD,0,Education,2024-12-18,2025-01-30,692,9.5,AI Innovations +AI01471,Principal Data Scientist,54185,EUR,46057,EN,FT,Germany,S,India,0,"Computer Vision, PyTorch, Scala, GCP",Master,0,Telecommunications,2025-03-18,2025-05-29,755,6.8,TechCorp Inc +AI01472,NLP Engineer,69436,USD,69436,EX,PT,India,M,India,100,"Data Visualization, Kubernetes, Python",Associate,19,Automotive,2024-11-10,2024-12-04,748,8.4,Neural Networks Co +AI01473,Data Analyst,103188,USD,103188,EN,PT,United States,L,United States,0,"Git, Spark, Python, Java, GCP",PhD,1,Transportation,2024-03-24,2024-04-24,1596,5.6,Smart Analytics +AI01474,AI Research Scientist,116739,CHF,105065,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Java, Hadoop",Bachelor,0,Education,2025-01-21,2025-02-11,2191,6.3,Future Systems +AI01475,Deep Learning Engineer,73367,EUR,62362,EN,FL,Austria,M,Austria,0,"AWS, SQL, Tableau, PyTorch",Bachelor,1,Gaming,2024-11-30,2024-12-30,521,6.3,Predictive Systems +AI01476,Data Engineer,72979,JPY,8027690,EN,CT,Japan,S,Japan,50,"PyTorch, R, Docker, GCP, Azure",Associate,1,Retail,2025-02-21,2025-03-27,2262,6.5,Neural Networks Co +AI01477,Data Engineer,193939,USD,193939,EX,PT,Israel,M,Israel,100,"TensorFlow, Python, Hadoop, Tableau, Data Visualization",Bachelor,12,Technology,2025-01-28,2025-03-24,1382,8.6,DeepTech Ventures +AI01478,Research Scientist,151333,USD,151333,EX,FL,Ireland,M,Ireland,50,"Kubernetes, R, Statistics, GCP, Scala",Master,19,Gaming,2025-03-04,2025-05-04,503,5.8,Cognitive Computing +AI01479,Data Scientist,63229,USD,63229,SE,CT,China,S,China,100,"Scala, Java, Statistics, AWS, Kubernetes",Associate,6,Education,2024-12-17,2025-01-21,2342,9.8,Cognitive Computing +AI01480,Principal Data Scientist,188397,CHF,169557,SE,FT,Switzerland,S,Netherlands,50,"Git, PyTorch, AWS, Docker, GCP",Master,7,Healthcare,2024-09-02,2024-10-31,1198,9.6,AI Innovations +AI01481,Robotics Engineer,102987,USD,102987,MI,FT,Denmark,M,Denmark,0,"Python, GCP, MLOps, Azure, Hadoop",PhD,4,Retail,2024-07-28,2024-10-05,1017,6.5,DataVision Ltd +AI01482,AI Specialist,226210,USD,226210,SE,FT,Denmark,L,Denmark,50,"PyTorch, Scala, TensorFlow, AWS, Deep Learning",PhD,9,Manufacturing,2024-02-15,2024-03-29,2494,5.6,Future Systems +AI01483,AI Architect,18309,USD,18309,EN,FL,India,S,India,100,"PyTorch, Deep Learning, TensorFlow",Associate,0,Media,2024-10-14,2024-12-12,1247,7.6,DeepTech Ventures +AI01484,AI Software Engineer,210459,USD,210459,EX,CT,Israel,S,Israel,0,"Python, Computer Vision, NLP, Azure, Java",Master,17,Government,2025-02-19,2025-04-26,898,6.9,Advanced Robotics +AI01485,Robotics Engineer,70962,USD,70962,SE,CT,China,M,China,0,"Computer Vision, SQL, Linux",Associate,6,Consulting,2025-02-10,2025-03-22,1509,5.3,Machine Intelligence Group +AI01486,AI Research Scientist,71103,EUR,60438,MI,PT,Netherlands,S,New Zealand,0,"R, AWS, Kubernetes, Linux, Mathematics",Bachelor,3,Healthcare,2024-06-04,2024-08-16,1863,8.7,Predictive Systems +AI01487,Computer Vision Engineer,94344,USD,94344,EN,FT,Denmark,M,Argentina,50,"AWS, Tableau, SQL, PyTorch",Master,0,Education,2024-08-31,2024-09-27,1961,8.1,Predictive Systems +AI01488,Autonomous Systems Engineer,31310,USD,31310,EN,FT,China,M,China,100,"Tableau, Kubernetes, Scala",Bachelor,0,Healthcare,2025-03-16,2025-04-20,712,6.8,DataVision Ltd +AI01489,AI Product Manager,186865,USD,186865,EX,PT,Ireland,L,Ireland,100,"Data Visualization, Python, TensorFlow, AWS",PhD,17,Technology,2024-06-07,2024-08-14,1906,8,Cognitive Computing +AI01490,AI Product Manager,22689,USD,22689,EN,CT,India,S,India,50,"Deep Learning, SQL, MLOps, Data Visualization, Git",Bachelor,0,Finance,2024-08-20,2024-09-29,835,5.1,DataVision Ltd +AI01491,AI Product Manager,71875,USD,71875,EX,FT,China,M,China,50,"Hadoop, SQL, Data Visualization, TensorFlow",PhD,17,Healthcare,2024-01-30,2024-03-22,2427,8.7,DataVision Ltd +AI01492,AI Specialist,91093,USD,91093,EN,FT,Denmark,M,Denmark,50,"Tableau, SQL, Python",Master,1,Finance,2024-07-07,2024-07-22,1322,7.4,Cloud AI Solutions +AI01493,NLP Engineer,59983,USD,59983,MI,CT,South Korea,S,Colombia,50,"SQL, PyTorch, Tableau, Kubernetes",Master,3,Finance,2025-02-22,2025-04-04,1654,9.6,Smart Analytics +AI01494,AI Specialist,315917,CHF,284325,EX,FL,Switzerland,M,Switzerland,50,"Statistics, SQL, Tableau, Computer Vision, Docker",PhD,13,Media,2024-01-21,2024-03-01,870,7.4,Predictive Systems +AI01495,Robotics Engineer,49015,USD,49015,EN,FT,Ireland,S,Ireland,100,"Scala, Data Visualization, SQL, MLOps",Bachelor,1,Healthcare,2024-11-30,2025-01-28,920,5.1,Predictive Systems +AI01496,NLP Engineer,45174,USD,45174,EN,CT,South Korea,M,South Korea,50,"Python, Scala, SQL",Associate,0,Consulting,2024-07-27,2024-08-17,857,5.7,Quantum Computing Inc +AI01497,Head of AI,124375,USD,124375,MI,FL,Norway,L,Norway,0,"SQL, Computer Vision, Git, GCP, PyTorch",Master,3,Transportation,2024-10-22,2025-01-01,2017,6.1,TechCorp Inc +AI01498,Principal Data Scientist,24919,USD,24919,EN,CT,India,M,Indonesia,0,"TensorFlow, Tableau, GCP",Associate,0,Gaming,2024-07-25,2024-08-18,2434,7.3,Predictive Systems +AI01499,AI Architect,103196,EUR,87717,SE,FL,Austria,M,Austria,50,"SQL, Java, Kubernetes, Deep Learning",Master,9,Automotive,2025-04-08,2025-06-02,2102,8,DataVision Ltd +AI01500,Computer Vision Engineer,101200,USD,101200,EN,FL,Norway,M,Norway,100,"SQL, Computer Vision, PyTorch, Git, Tableau",Bachelor,1,Government,2024-11-04,2024-11-21,2344,6.9,Advanced Robotics +AI01501,Data Scientist,146547,USD,146547,SE,FT,Finland,L,Canada,100,"TensorFlow, NLP, Mathematics, Tableau, Kubernetes",Bachelor,9,Automotive,2024-10-30,2024-12-27,669,6.9,Machine Intelligence Group +AI01502,Autonomous Systems Engineer,72296,USD,72296,SE,CT,China,L,China,50,"Scala, AWS, NLP, Git, Python",Associate,8,Automotive,2025-03-21,2025-05-14,1029,9.8,Algorithmic Solutions +AI01503,ML Ops Engineer,63430,USD,63430,EN,FL,United States,S,Thailand,50,"GCP, Deep Learning, PyTorch, AWS",PhD,0,Automotive,2024-11-14,2025-01-08,2301,6.9,Machine Intelligence Group +AI01504,Computer Vision Engineer,266480,USD,266480,EX,FT,Israel,L,Israel,100,"SQL, Python, Tableau, Statistics",Bachelor,16,Consulting,2024-12-02,2025-01-20,1350,6.4,Predictive Systems +AI01505,Computer Vision Engineer,115622,EUR,98279,SE,CT,Austria,S,Austria,0,"Spark, Hadoop, Data Visualization, MLOps, Azure",Master,6,Transportation,2024-07-26,2024-08-18,589,7.9,DataVision Ltd +AI01506,NLP Engineer,59313,USD,59313,SE,FT,India,L,Philippines,0,"Data Visualization, GCP, Linux, Computer Vision",Master,7,Manufacturing,2024-12-26,2025-02-16,901,7.3,AI Innovations +AI01507,Research Scientist,106901,EUR,90866,MI,FL,Germany,L,Germany,50,"TensorFlow, Python, Statistics",PhD,3,Manufacturing,2025-04-14,2025-06-23,746,5.8,Smart Analytics +AI01508,NLP Engineer,179377,EUR,152470,EX,CT,Netherlands,S,Nigeria,0,"Data Visualization, GCP, Scala, R, AWS",Associate,11,Technology,2024-09-21,2024-10-23,1996,6.3,Algorithmic Solutions +AI01509,Data Engineer,98356,USD,98356,MI,CT,Sweden,M,Sweden,0,"NLP, PyTorch, Scala, Deep Learning",Associate,2,Technology,2024-12-12,2025-01-17,1771,6,Autonomous Tech +AI01510,Data Analyst,143818,SGD,186963,SE,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, TensorFlow, Statistics",Bachelor,8,Manufacturing,2024-05-16,2024-07-14,807,8,DeepTech Ventures +AI01511,AI Research Scientist,148765,CAD,185956,SE,PT,Canada,L,Canada,50,"Computer Vision, PyTorch, SQL",Associate,6,Gaming,2025-04-28,2025-07-10,1542,6.4,Quantum Computing Inc +AI01512,Research Scientist,88116,USD,88116,EN,FT,Norway,S,Singapore,0,"R, NLP, GCP",PhD,1,Telecommunications,2025-03-14,2025-03-29,2478,6.7,Predictive Systems +AI01513,Robotics Engineer,49914,USD,49914,EN,FL,South Korea,S,South Korea,50,"Hadoop, Python, Computer Vision",PhD,0,Telecommunications,2024-01-30,2024-04-11,1057,6.9,Quantum Computing Inc +AI01514,Autonomous Systems Engineer,39015,USD,39015,EN,PT,China,L,China,0,"R, Linux, SQL, PyTorch",PhD,0,Automotive,2024-10-27,2024-12-10,1371,6.3,Digital Transformation LLC +AI01515,AI Architect,88810,GBP,66608,MI,FL,United Kingdom,L,Russia,0,"Tableau, Scala, Spark",PhD,4,Finance,2024-07-25,2024-09-25,963,9.9,Predictive Systems +AI01516,Machine Learning Engineer,224663,USD,224663,EX,FL,United States,L,United States,50,"TensorFlow, Deep Learning, Computer Vision",Associate,19,Automotive,2024-11-28,2025-01-18,1986,9.9,DeepTech Ventures +AI01517,Data Scientist,63881,AUD,86239,EN,CT,Australia,L,Australia,0,"PyTorch, GCP, Computer Vision, AWS",Associate,0,Transportation,2024-10-24,2024-11-10,1505,9.4,Digital Transformation LLC +AI01518,Machine Learning Researcher,95307,USD,95307,SE,CT,South Korea,M,South Korea,0,"Hadoop, AWS, Scala, TensorFlow",Master,6,Energy,2024-09-22,2024-10-21,1156,8.5,DeepTech Ventures +AI01519,AI Software Engineer,102086,USD,102086,EN,PT,Norway,L,Norway,100,"Mathematics, Git, Java",PhD,0,Education,2024-01-16,2024-02-10,1340,8.2,Autonomous Tech +AI01520,Deep Learning Engineer,97103,AUD,131089,MI,PT,Australia,M,Australia,100,"Statistics, Tableau, Data Visualization",PhD,2,Technology,2024-12-31,2025-01-23,1745,8.3,Future Systems +AI01521,Data Scientist,174876,CHF,157388,SE,PT,Switzerland,M,Switzerland,100,"SQL, Spark, GCP, PyTorch, Azure",Bachelor,7,Retail,2024-05-23,2024-07-07,2247,7.3,Autonomous Tech +AI01522,Machine Learning Researcher,77585,EUR,65947,MI,FT,France,M,France,50,"GCP, Scala, Deep Learning",Associate,2,Gaming,2024-08-13,2024-10-15,2332,5.5,Machine Intelligence Group +AI01523,Robotics Engineer,83753,USD,83753,EN,PT,Denmark,M,Denmark,0,"Tableau, Spark, Python, MLOps",Master,0,Retail,2024-05-26,2024-07-02,1715,5.8,Algorithmic Solutions +AI01524,Deep Learning Engineer,191492,JPY,21064120,EX,FT,Japan,S,Japan,0,"Python, MLOps, Mathematics",Bachelor,11,Healthcare,2024-05-21,2024-07-26,1072,7.3,TechCorp Inc +AI01525,AI Consultant,71219,USD,71219,EN,FL,Israel,M,Israel,0,"PyTorch, SQL, TensorFlow, Scala, Python",PhD,0,Healthcare,2024-04-03,2024-05-25,1209,9.4,TechCorp Inc +AI01526,Computer Vision Engineer,143605,AUD,193867,SE,PT,Australia,L,Australia,50,"Git, TensorFlow, Computer Vision, MLOps, Deep Learning",Bachelor,9,Media,2024-03-27,2024-04-16,1914,6.8,Digital Transformation LLC +AI01527,Data Analyst,261388,USD,261388,EX,FL,Norway,L,Norway,100,"Tableau, Mathematics, Scala, Java, Computer Vision",Bachelor,11,Finance,2024-10-20,2024-12-27,688,10,DeepTech Ventures +AI01528,Data Engineer,115250,GBP,86438,MI,FT,United Kingdom,L,United Kingdom,0,"Java, Tableau, PyTorch, Statistics, Azure",Bachelor,3,Retail,2024-07-01,2024-08-03,1696,8.9,Algorithmic Solutions +AI01529,AI Research Scientist,214259,USD,214259,EX,FT,Ireland,M,Ireland,0,"Tableau, Linux, PyTorch, Docker, Deep Learning",Associate,16,Education,2024-10-07,2024-10-31,609,6.8,Algorithmic Solutions +AI01530,Machine Learning Researcher,50907,USD,50907,SE,FT,China,S,Poland,0,"Statistics, Scala, Deep Learning, NLP",Bachelor,6,Telecommunications,2024-04-23,2024-05-18,1329,6.2,DataVision Ltd +AI01531,NLP Engineer,157211,USD,157211,EX,CT,Israel,S,Israel,0,"Java, GCP, Computer Vision, Git, Hadoop",Master,11,Education,2024-11-10,2024-12-02,1072,8.1,Machine Intelligence Group +AI01532,ML Ops Engineer,110447,EUR,93880,MI,FT,Germany,M,Germany,50,"Java, Python, Git, SQL, Computer Vision",Bachelor,4,Gaming,2024-08-18,2024-10-19,666,6.9,Cognitive Computing +AI01533,ML Ops Engineer,108700,SGD,141310,MI,CT,Singapore,L,Singapore,0,"Git, NLP, Kubernetes, Statistics",Bachelor,4,Education,2024-09-23,2024-10-28,1849,8.3,Digital Transformation LLC +AI01534,Head of AI,67170,EUR,57095,EN,CT,France,L,Australia,100,"AWS, R, SQL, Mathematics",Master,1,Finance,2025-01-07,2025-03-07,832,6.6,Machine Intelligence Group +AI01535,Computer Vision Engineer,45079,USD,45079,SE,FL,China,S,China,0,"Data Visualization, Spark, Linux",Master,6,Energy,2024-09-15,2024-11-17,1064,6,Advanced Robotics +AI01536,AI Architect,97906,AUD,132173,MI,PT,Australia,S,Australia,100,"Linux, SQL, R, Computer Vision, Spark",Bachelor,3,Government,2024-04-28,2024-06-05,2486,5.6,TechCorp Inc +AI01537,Principal Data Scientist,88189,USD,88189,SE,PT,South Korea,S,South Korea,100,"Scala, Hadoop, Tableau, Git",Associate,8,Retail,2025-03-02,2025-04-20,1536,7.3,Machine Intelligence Group +AI01538,Robotics Engineer,103595,CAD,129494,MI,FT,Canada,M,Canada,0,"TensorFlow, Computer Vision, Python, MLOps",Associate,2,Consulting,2024-04-04,2024-05-20,657,6.9,Smart Analytics +AI01539,Data Analyst,113624,USD,113624,SE,CT,Finland,S,Sweden,50,"SQL, GCP, Linux, Tableau, Hadoop",Bachelor,8,Technology,2024-05-24,2024-06-23,2433,7.2,Smart Analytics +AI01540,Autonomous Systems Engineer,134364,SGD,174673,SE,CT,Singapore,M,Singapore,100,"Mathematics, NLP, Docker, Tableau, Git",Master,8,Healthcare,2024-12-22,2025-01-18,1559,7.7,Smart Analytics +AI01541,AI Product Manager,143237,AUD,193370,EX,FT,Australia,S,Australia,100,"Docker, Python, Kubernetes",PhD,12,Real Estate,2025-02-13,2025-03-31,723,6.6,Predictive Systems +AI01542,ML Ops Engineer,61187,CAD,76484,EN,FT,Canada,L,Canada,100,"TensorFlow, Computer Vision, SQL, Scala, Hadoop",Associate,0,Telecommunications,2024-08-21,2024-09-21,1196,7.9,Machine Intelligence Group +AI01543,Autonomous Systems Engineer,64608,USD,64608,EN,FT,South Korea,M,Colombia,50,"GCP, Python, Hadoop, TensorFlow",PhD,0,Government,2025-03-21,2025-05-16,2441,8.1,Smart Analytics +AI01544,Principal Data Scientist,311834,CHF,280651,EX,FT,Switzerland,L,Switzerland,0,"Kubernetes, Hadoop, Python, Data Visualization, Mathematics",Bachelor,14,Transportation,2024-02-29,2024-04-11,1088,7.6,DataVision Ltd +AI01545,Deep Learning Engineer,127894,USD,127894,MI,CT,Denmark,M,Denmark,50,"TensorFlow, Azure, GCP, Java",Master,4,Finance,2024-07-17,2024-09-04,538,8.3,Machine Intelligence Group +AI01546,Data Scientist,75336,GBP,56502,EN,FL,United Kingdom,S,United Kingdom,0,"NLP, Java, MLOps, Kubernetes",Bachelor,0,Telecommunications,2024-09-12,2024-10-21,2367,9.7,AI Innovations +AI01547,Research Scientist,66416,USD,66416,EN,FL,Ireland,S,Ireland,50,"R, SQL, Linux, Mathematics",Associate,1,Telecommunications,2024-04-05,2024-06-09,1592,8.4,AI Innovations +AI01548,AI Architect,49315,USD,49315,EN,FT,Israel,S,Israel,50,"GCP, Git, Data Visualization, Tableau, MLOps",Bachelor,0,Government,2024-11-05,2024-12-08,1778,6.7,Neural Networks Co +AI01549,AI Architect,130837,EUR,111211,SE,FT,Germany,S,Germany,100,"Python, TensorFlow, Deep Learning, Scala, Computer Vision",Master,9,Automotive,2024-02-03,2024-03-18,1032,7.6,DataVision Ltd +AI01550,Head of AI,93179,CAD,116474,SE,PT,Canada,S,Canada,0,"Kubernetes, NLP, MLOps, Spark, Hadoop",Associate,5,Gaming,2024-08-28,2024-10-20,2076,5.8,Future Systems +AI01551,Machine Learning Researcher,88696,EUR,75392,EN,PT,Netherlands,L,Netherlands,50,"Java, Mathematics, GCP",Bachelor,1,Consulting,2025-03-23,2025-04-11,896,5.3,Smart Analytics +AI01552,AI Specialist,125978,GBP,94484,SE,PT,United Kingdom,S,United Kingdom,100,"Azure, TensorFlow, Scala",Bachelor,8,Energy,2025-03-01,2025-05-12,1769,9.5,Predictive Systems +AI01553,Robotics Engineer,73015,EUR,62063,EN,CT,Netherlands,M,Netherlands,50,"Git, GCP, Tableau, MLOps",Bachelor,1,Gaming,2024-02-19,2024-04-26,647,5.7,Machine Intelligence Group +AI01554,Data Analyst,89921,EUR,76433,MI,CT,Austria,S,Austria,100,"R, NLP, Python",Bachelor,2,Finance,2024-12-07,2025-01-20,1779,5.3,Digital Transformation LLC +AI01555,AI Specialist,145615,USD,145615,SE,FL,Denmark,S,Denmark,50,"Deep Learning, MLOps, PyTorch, Git, Statistics",Master,8,Automotive,2024-08-16,2024-10-28,2383,5.3,Quantum Computing Inc +AI01556,Machine Learning Researcher,72798,EUR,61878,EN,PT,France,L,France,0,"Deep Learning, SQL, Tableau, Python",PhD,1,Finance,2024-02-26,2024-04-20,976,8.1,Algorithmic Solutions +AI01557,AI Architect,202771,EUR,172355,EX,FL,France,S,Estonia,0,"Linux, Spark, Computer Vision",Master,19,Gaming,2024-04-30,2024-06-04,1300,8.1,Machine Intelligence Group +AI01558,Computer Vision Engineer,101963,SGD,132552,MI,FL,Singapore,S,Singapore,50,"Data Visualization, Scala, Tableau, Java, Mathematics",PhD,2,Telecommunications,2025-01-27,2025-03-04,2401,8.7,Cloud AI Solutions +AI01559,Principal Data Scientist,131393,EUR,111684,SE,FL,Netherlands,L,Egypt,0,"Python, Data Visualization, TensorFlow",Associate,6,Gaming,2024-06-30,2024-09-04,1399,7.3,Predictive Systems +AI01560,Data Engineer,216001,USD,216001,SE,PT,Denmark,L,Philippines,100,"Java, GCP, Deep Learning, Docker, Spark",Associate,7,Education,2024-11-17,2024-12-05,2098,7.9,Machine Intelligence Group +AI01561,AI Research Scientist,165488,USD,165488,EX,FT,South Korea,S,Egypt,100,"Tableau, Computer Vision, Docker, Python",Associate,17,Finance,2024-01-01,2024-03-12,732,5,Smart Analytics +AI01562,AI Consultant,279330,SGD,363129,EX,FT,Singapore,L,Nigeria,100,"PyTorch, Mathematics, Docker, Statistics, R",Associate,11,Media,2024-08-26,2024-09-25,1724,5.4,Algorithmic Solutions +AI01563,Head of AI,120176,EUR,102150,SE,CT,Austria,M,Austria,0,"Computer Vision, AWS, Data Visualization, Linux, R",PhD,9,Retail,2024-04-16,2024-06-07,922,8.9,Advanced Robotics +AI01564,AI Architect,242800,EUR,206380,EX,FL,Netherlands,M,Netherlands,50,"Docker, Git, Data Visualization, MLOps",PhD,14,Finance,2024-07-09,2024-08-10,1726,8.7,Algorithmic Solutions +AI01565,Autonomous Systems Engineer,135978,AUD,183570,SE,FT,Australia,S,Romania,0,"Azure, GCP, Linux, Python",Associate,7,Gaming,2025-04-19,2025-05-08,1352,9.8,Machine Intelligence Group +AI01566,Computer Vision Engineer,233643,CHF,210279,SE,PT,Switzerland,L,Switzerland,100,"Linux, GCP, TensorFlow, Docker, Python",Master,6,Education,2024-03-30,2024-06-10,1082,9.4,Neural Networks Co +AI01567,AI Architect,63249,USD,63249,MI,FT,South Korea,M,South Korea,100,"Spark, Data Visualization, Kubernetes, Python, Docker",Associate,2,Education,2024-08-12,2024-09-15,839,6,TechCorp Inc +AI01568,Data Engineer,89516,USD,89516,EX,PT,India,L,India,0,"Java, R, MLOps, Spark",Master,11,Real Estate,2024-03-12,2024-05-08,1876,9.7,Algorithmic Solutions +AI01569,Principal Data Scientist,176954,EUR,150411,EX,FT,France,M,Australia,50,"SQL, Python, MLOps",Master,15,Transportation,2024-08-18,2024-09-20,1122,6,Cloud AI Solutions +AI01570,Head of AI,55961,USD,55961,MI,PT,China,L,China,50,"Spark, Kubernetes, MLOps, Azure, Data Visualization",Associate,3,Education,2024-10-01,2024-12-03,1474,8.7,Smart Analytics +AI01571,Head of AI,132864,GBP,99648,SE,FT,United Kingdom,M,United Kingdom,100,"Scala, Python, Tableau",Bachelor,6,Finance,2025-03-18,2025-04-08,616,5.8,DataVision Ltd +AI01572,Research Scientist,104418,AUD,140964,MI,CT,Australia,M,Austria,50,"R, Git, MLOps, Spark",Associate,4,Manufacturing,2025-02-20,2025-04-03,2135,5.3,Algorithmic Solutions +AI01573,Deep Learning Engineer,80490,AUD,108662,EN,FL,Australia,M,South Africa,0,"TensorFlow, Java, Git",Bachelor,0,Healthcare,2024-06-15,2024-07-11,1830,9.8,Cognitive Computing +AI01574,Head of AI,85744,USD,85744,MI,FT,Israel,L,Israel,50,"R, GCP, Mathematics",Bachelor,3,Automotive,2024-12-04,2025-01-09,1123,7.8,DeepTech Ventures +AI01575,Principal Data Scientist,101111,EUR,85944,SE,FL,Austria,S,Netherlands,100,"Docker, Mathematics, Tableau, Linux",Master,9,Education,2025-02-09,2025-02-24,1304,8.8,Future Systems +AI01576,Machine Learning Engineer,195573,CAD,244466,EX,FT,Canada,L,Canada,100,"Mathematics, GCP, Kubernetes",Master,18,Telecommunications,2024-03-07,2024-04-23,1002,6.4,DataVision Ltd +AI01577,Robotics Engineer,136148,AUD,183800,SE,FL,Australia,M,Indonesia,0,"Azure, Java, SQL, Python, Computer Vision",PhD,9,Retail,2024-06-14,2024-07-02,1581,8.4,Quantum Computing Inc +AI01578,AI Architect,108512,SGD,141066,MI,FT,Singapore,L,Denmark,50,"Computer Vision, Linux, Data Visualization, Java, Azure",Master,4,Government,2024-03-23,2024-04-10,2122,9.3,Machine Intelligence Group +AI01579,Data Engineer,216695,EUR,184191,EX,FL,Germany,S,Germany,0,"Java, Tableau, Python, Deep Learning",Master,16,Education,2024-08-11,2024-09-07,646,7,Digital Transformation LLC +AI01580,NLP Engineer,169781,CHF,152803,SE,CT,Switzerland,S,Switzerland,50,"Python, Hadoop, Linux",PhD,5,Telecommunications,2024-08-20,2024-10-18,2253,8.6,Cloud AI Solutions +AI01581,Robotics Engineer,306082,CHF,275474,EX,PT,Switzerland,L,Switzerland,0,"Spark, AWS, Statistics",PhD,19,Telecommunications,2025-03-12,2025-05-16,1909,8.5,AI Innovations +AI01582,AI Research Scientist,82438,CHF,74194,EN,CT,Switzerland,S,Switzerland,0,"PyTorch, Java, MLOps",Associate,0,Finance,2024-10-20,2024-12-26,1139,5.2,DataVision Ltd +AI01583,NLP Engineer,57552,USD,57552,EN,FT,Ireland,M,India,0,"R, SQL, Deep Learning, PyTorch, Git",Associate,0,Finance,2024-03-10,2024-05-05,2293,7.6,Predictive Systems +AI01584,Head of AI,54111,CAD,67639,EN,CT,Canada,M,Canada,50,"Statistics, Spark, TensorFlow, Scala, GCP",PhD,1,Technology,2025-03-11,2025-04-13,1725,9.3,TechCorp Inc +AI01585,AI Product Manager,139157,EUR,118283,SE,PT,Germany,M,Germany,0,"Java, Azure, Python, MLOps",Bachelor,7,Media,2025-03-06,2025-05-13,1081,9.7,Cognitive Computing +AI01586,Deep Learning Engineer,84808,EUR,72087,MI,FT,Austria,M,Austria,100,"Git, Linux, Hadoop, GCP, Python",PhD,4,Telecommunications,2024-04-25,2024-05-18,764,5.7,TechCorp Inc +AI01587,AI Software Engineer,141179,EUR,120002,SE,CT,Austria,M,Austria,100,"Java, Python, TensorFlow",Associate,7,Transportation,2024-04-07,2024-06-03,1342,6.3,Advanced Robotics +AI01588,Computer Vision Engineer,318090,USD,318090,EX,PT,United States,L,United States,0,"PyTorch, MLOps, Hadoop",Bachelor,14,Technology,2024-04-04,2024-04-23,1247,6,DeepTech Ventures +AI01589,Data Analyst,130980,EUR,111333,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, R, Linux",PhD,3,Healthcare,2024-07-04,2024-09-04,1109,10,DataVision Ltd +AI01590,Robotics Engineer,134292,USD,134292,EX,FT,Israel,S,Israel,0,"NLP, Git, Tableau, GCP",Bachelor,13,Government,2024-11-14,2025-01-17,696,8.4,Cognitive Computing +AI01591,AI Architect,137679,AUD,185867,EX,PT,Australia,M,Australia,50,"R, Linux, Python, Deep Learning",Associate,11,Gaming,2024-09-19,2024-10-31,1964,8.3,Autonomous Tech +AI01592,AI Product Manager,179453,EUR,152535,EX,FT,France,M,France,0,"SQL, Tableau, Azure, Kubernetes, Python",Bachelor,12,Technology,2024-02-27,2024-04-12,996,8.9,Digital Transformation LLC +AI01593,ML Ops Engineer,118618,USD,118618,SE,FL,Ireland,M,Ireland,50,"Python, Java, Git, Hadoop, Statistics",Associate,8,Healthcare,2025-03-29,2025-05-21,1265,7.8,Advanced Robotics +AI01594,Data Analyst,154250,USD,154250,SE,PT,Finland,L,Finland,0,"AWS, Mathematics, PyTorch, TensorFlow",Associate,7,Education,2024-11-15,2024-12-14,2495,9,DataVision Ltd +AI01595,Machine Learning Researcher,63563,USD,63563,MI,FT,South Korea,M,Romania,50,"Java, Data Visualization, SQL, MLOps, Python",PhD,4,Manufacturing,2025-03-13,2025-04-22,1537,5.7,Predictive Systems +AI01596,Head of AI,199854,GBP,149891,EX,FT,United Kingdom,S,United Kingdom,100,"NLP, Hadoop, Kubernetes, Docker",Master,18,Consulting,2024-10-21,2024-12-22,660,5.3,Smart Analytics +AI01597,ML Ops Engineer,123361,EUR,104857,SE,FL,Germany,L,Germany,0,"NLP, Spark, Hadoop, Python",Master,6,Media,2024-09-27,2024-10-14,1538,8.9,TechCorp Inc +AI01598,AI Consultant,103643,USD,103643,SE,CT,Finland,S,Portugal,0,"Linux, Azure, Python",Master,6,Manufacturing,2024-12-11,2025-02-19,858,8.8,Cognitive Computing +AI01599,Data Scientist,61632,USD,61632,MI,CT,South Korea,M,United Kingdom,0,"R, Git, Scala",Bachelor,4,Real Estate,2024-01-06,2024-02-16,607,6.5,DataVision Ltd +AI01600,Data Engineer,64782,USD,64782,EN,CT,South Korea,M,South Korea,50,"GCP, Azure, Data Visualization, Git",Master,0,Automotive,2025-02-04,2025-03-03,942,8.1,AI Innovations +AI01601,Machine Learning Engineer,160583,USD,160583,SE,FL,Norway,L,France,100,"Data Visualization, Spark, Kubernetes",Master,7,Healthcare,2024-01-24,2024-03-28,1801,8,Advanced Robotics +AI01602,NLP Engineer,259300,SGD,337090,EX,CT,Singapore,M,Singapore,100,"Spark, GCP, Azure, Python, Tableau",Master,16,Healthcare,2025-03-10,2025-05-12,1482,5.3,DeepTech Ventures +AI01603,AI Architect,99029,EUR,84175,MI,PT,Netherlands,M,Netherlands,100,"Hadoop, Azure, Python, TensorFlow, Git",Master,2,Healthcare,2024-08-18,2024-10-04,1003,9.3,Future Systems +AI01604,Principal Data Scientist,84037,USD,84037,EN,CT,Ireland,L,Ireland,100,"TensorFlow, PyTorch, SQL, Spark, Docker",Associate,1,Energy,2024-11-20,2024-12-31,1267,6.6,Smart Analytics +AI01605,Computer Vision Engineer,70093,USD,70093,MI,FT,South Korea,L,Egypt,0,"R, Azure, PyTorch",PhD,2,Consulting,2024-11-23,2025-01-06,945,9.4,Future Systems +AI01606,Head of AI,133209,EUR,113228,SE,FT,Germany,M,Malaysia,0,"Hadoop, Python, Linux, TensorFlow, Java",PhD,9,Healthcare,2025-02-14,2025-03-15,1859,6.7,Autonomous Tech +AI01607,Head of AI,116248,USD,116248,SE,FL,Sweden,M,Sweden,100,"Python, TensorFlow, PyTorch",Associate,9,Transportation,2024-08-10,2024-10-21,1971,5.7,AI Innovations +AI01608,Machine Learning Researcher,62383,CAD,77979,EN,PT,Canada,M,Canada,100,"Data Visualization, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Media,2024-06-18,2024-08-10,1148,9.2,Quantum Computing Inc +AI01609,AI Consultant,192600,CHF,173340,EX,CT,Switzerland,S,Switzerland,100,"Linux, MLOps, GCP, TensorFlow",Associate,12,Transportation,2024-06-09,2024-08-05,1620,8,Neural Networks Co +AI01610,Research Scientist,91590,CAD,114488,MI,PT,Canada,M,Canada,0,"Statistics, SQL, AWS, Mathematics, Azure",Associate,2,Telecommunications,2024-11-18,2025-01-06,770,7.2,Algorithmic Solutions +AI01611,AI Consultant,102798,USD,102798,SE,FL,South Korea,L,South Korea,50,"Spark, SQL, Statistics",Bachelor,7,Real Estate,2025-03-15,2025-04-07,1954,8.6,AI Innovations +AI01612,AI Architect,103697,EUR,88142,MI,FT,Germany,M,Germany,0,"SQL, Python, Hadoop, Computer Vision, GCP",Associate,2,Media,2024-05-18,2024-07-01,1173,9.2,Quantum Computing Inc +AI01613,Machine Learning Engineer,28499,USD,28499,MI,CT,India,S,Brazil,0,"Tableau, SQL, Scala, AWS, GCP",Master,2,Manufacturing,2024-01-26,2024-03-20,2350,8.9,DeepTech Ventures +AI01614,Research Scientist,69768,USD,69768,MI,PT,South Korea,L,Mexico,0,"Kubernetes, Docker, AWS, SQL, Python",Bachelor,3,Automotive,2024-10-03,2024-11-24,2257,7,Predictive Systems +AI01615,Research Scientist,71036,AUD,95899,MI,FT,Australia,S,Australia,100,"Azure, Scala, MLOps, Computer Vision, Data Visualization",PhD,4,Real Estate,2024-05-08,2024-06-04,1216,7.4,Advanced Robotics +AI01616,Data Scientist,121894,GBP,91421,SE,CT,United Kingdom,S,United Kingdom,50,"Linux, Python, Kubernetes, TensorFlow, Git",Master,7,Transportation,2024-04-12,2024-05-29,1233,5.3,Cognitive Computing +AI01617,AI Software Engineer,60930,EUR,51791,EN,FL,Austria,S,Austria,50,"Tableau, PyTorch, Scala, GCP",Master,0,Consulting,2024-05-14,2024-06-16,1096,9.8,TechCorp Inc +AI01618,Principal Data Scientist,124442,USD,124442,SE,CT,Finland,M,Finland,0,"Computer Vision, Docker, SQL, Mathematics, Hadoop",PhD,7,Consulting,2025-04-02,2025-06-08,970,8.2,Advanced Robotics +AI01619,Computer Vision Engineer,88420,USD,88420,MI,CT,Sweden,L,Sweden,50,"Git, Hadoop, Java",Bachelor,2,Manufacturing,2024-08-11,2024-09-04,2056,5.9,Future Systems +AI01620,AI Consultant,84817,USD,84817,EN,CT,Ireland,L,Ireland,100,"Python, GCP, SQL",Bachelor,0,Telecommunications,2024-12-12,2025-02-01,1659,5.3,Smart Analytics +AI01621,AI Consultant,155811,SGD,202554,SE,CT,Singapore,M,Singapore,0,"Tableau, Git, SQL, Statistics",Master,6,Education,2024-10-09,2024-12-10,1916,5.3,TechCorp Inc +AI01622,AI Product Manager,95395,USD,95395,MI,PT,Israel,M,Japan,0,"TensorFlow, Deep Learning, Python, Computer Vision, PyTorch",Master,3,Media,2024-11-14,2025-01-12,908,8.2,DataVision Ltd +AI01623,NLP Engineer,82987,EUR,70539,MI,FT,Germany,S,Germany,0,"Python, NLP, AWS, Computer Vision, R",Bachelor,2,Real Estate,2024-10-30,2024-11-24,2035,5.8,Cloud AI Solutions +AI01624,Data Scientist,161403,USD,161403,EX,FL,Finland,M,Finland,50,"SQL, Statistics, PyTorch, Deep Learning",PhD,15,Finance,2024-05-16,2024-07-15,1635,9.8,DataVision Ltd +AI01625,Robotics Engineer,151191,USD,151191,SE,FT,Denmark,S,Denmark,0,"NLP, Tableau, Scala, GCP",PhD,8,Energy,2025-04-01,2025-04-24,890,6.7,Digital Transformation LLC +AI01626,Machine Learning Researcher,92075,EUR,78264,SE,CT,France,S,France,100,"GCP, Java, R",Bachelor,6,Government,2024-11-02,2024-12-05,2261,7.7,Cloud AI Solutions +AI01627,Autonomous Systems Engineer,43996,USD,43996,MI,FL,China,S,China,100,"Python, Azure, TensorFlow, Hadoop",Master,2,Manufacturing,2024-02-22,2024-03-16,2422,7.2,DataVision Ltd +AI01628,AI Research Scientist,25803,USD,25803,EN,PT,India,M,India,50,"Kubernetes, MLOps, Azure, Linux, Computer Vision",Master,0,Technology,2024-12-30,2025-03-04,1599,7.1,DataVision Ltd +AI01629,Machine Learning Engineer,99682,USD,99682,EN,FL,United States,L,Ukraine,0,"SQL, Scala, Git",Associate,0,Technology,2025-03-12,2025-04-19,2193,5.3,AI Innovations +AI01630,Autonomous Systems Engineer,108655,USD,108655,EX,PT,China,L,China,0,"PyTorch, Mathematics, Spark, Java, Hadoop",Associate,17,Gaming,2024-05-11,2024-06-25,1410,7.9,Algorithmic Solutions +AI01631,Machine Learning Researcher,79605,AUD,107467,MI,PT,Australia,M,Australia,50,"GCP, Tableau, Data Visualization, MLOps, Python",Master,3,Real Estate,2024-05-29,2024-07-25,789,7,DeepTech Ventures +AI01632,AI Specialist,68143,EUR,57922,EN,PT,Netherlands,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2024-01-25,2024-02-23,1355,5.5,Future Systems +AI01633,ML Ops Engineer,177618,SGD,230903,EX,PT,Singapore,S,Singapore,0,"Hadoop, SQL, NLP",Bachelor,18,Energy,2024-02-08,2024-03-19,957,8.1,Neural Networks Co +AI01634,Robotics Engineer,220052,CAD,275065,EX,CT,Canada,L,Ghana,50,"Hadoop, Scala, Tableau",Master,17,Media,2025-01-02,2025-01-26,1422,9.1,DeepTech Ventures +AI01635,AI Software Engineer,83629,GBP,62722,MI,PT,United Kingdom,M,Denmark,100,"Python, Tableau, Deep Learning, Data Visualization, Hadoop",PhD,2,Gaming,2024-04-12,2024-05-24,2018,6.2,Autonomous Tech +AI01636,AI Software Engineer,162381,EUR,138024,SE,FT,Netherlands,L,Netherlands,0,"Scala, Python, GCP",Bachelor,6,Gaming,2024-09-19,2024-11-27,1315,5.4,DataVision Ltd +AI01637,Machine Learning Researcher,124109,USD,124109,SE,FT,Sweden,M,Sweden,0,"Python, Hadoop, Git, GCP",Bachelor,8,Transportation,2024-01-31,2024-03-22,1835,5.9,Predictive Systems +AI01638,AI Product Manager,59192,AUD,79909,EN,CT,Australia,M,Indonesia,0,"Linux, TensorFlow, PyTorch, Java, AWS",Associate,1,Media,2024-03-28,2024-04-15,1675,6.3,Smart Analytics +AI01639,AI Research Scientist,49329,USD,49329,SE,PT,India,M,India,0,"Hadoop, Tableau, Kubernetes, PyTorch, Computer Vision",Associate,7,Energy,2025-01-25,2025-03-17,1500,5.9,DataVision Ltd +AI01640,Autonomous Systems Engineer,76915,USD,76915,EX,FT,India,M,India,100,"Statistics, Python, TensorFlow, GCP",Associate,13,Government,2024-10-14,2024-12-13,1541,5.4,Quantum Computing Inc +AI01641,AI Product Manager,101027,USD,101027,EX,FT,China,M,China,100,"Java, Deep Learning, Python",Master,11,Media,2024-01-28,2024-03-06,882,8.8,Predictive Systems +AI01642,Machine Learning Engineer,238301,USD,238301,EX,FT,Norway,S,Norway,100,"Linux, SQL, PyTorch, AWS, Hadoop",PhD,13,Transportation,2024-10-08,2024-11-25,2043,5.7,Quantum Computing Inc +AI01643,Data Scientist,143521,USD,143521,SE,PT,Ireland,L,Luxembourg,50,"SQL, Docker, Azure, MLOps",Associate,5,Retail,2024-04-26,2024-05-23,2414,8.2,Neural Networks Co +AI01644,AI Research Scientist,139551,JPY,15350610,SE,FL,Japan,L,Luxembourg,100,"MLOps, TensorFlow, SQL, Linux",Bachelor,7,Education,2025-01-18,2025-03-10,1243,7,AI Innovations +AI01645,Autonomous Systems Engineer,85768,EUR,72903,EN,FL,Austria,L,Austria,50,"Hadoop, Statistics, NLP, Python",Master,1,Manufacturing,2025-04-09,2025-06-11,1439,9,Cloud AI Solutions +AI01646,Data Engineer,252548,USD,252548,EX,FL,United States,L,United States,50,"Kubernetes, Python, AWS, GCP",PhD,13,Consulting,2024-09-12,2024-10-12,2479,6.3,DeepTech Ventures +AI01647,AI Architect,116048,EUR,98641,MI,CT,Austria,L,Austria,0,"SQL, Azure, Computer Vision, Statistics",Bachelor,4,Government,2024-06-11,2024-07-18,526,9.6,Machine Intelligence Group +AI01648,Head of AI,29834,USD,29834,EN,PT,China,L,China,0,"SQL, Docker, NLP",Bachelor,0,Gaming,2024-05-01,2024-05-22,1564,9,DataVision Ltd +AI01649,Machine Learning Engineer,120609,CAD,150761,SE,FT,Canada,S,Canada,0,"Spark, PyTorch, Statistics",Bachelor,5,Energy,2024-06-11,2024-08-09,844,6.4,Algorithmic Solutions +AI01650,Robotics Engineer,79431,EUR,67516,MI,PT,Austria,L,Austria,0,"R, Hadoop, Azure, Java, Docker",Master,2,Real Estate,2024-04-04,2024-05-09,1677,5.6,Algorithmic Solutions +AI01651,Research Scientist,194187,CAD,242734,EX,CT,Canada,S,Canada,100,"Python, Computer Vision, Spark",Master,14,Telecommunications,2024-12-14,2024-12-29,2369,8.9,Machine Intelligence Group +AI01652,Principal Data Scientist,177785,USD,177785,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Python, Scala, Linux",Master,7,Energy,2024-05-16,2024-06-17,1684,9.6,AI Innovations +AI01653,Computer Vision Engineer,231560,USD,231560,EX,CT,Israel,L,Israel,100,"Spark, Git, SQL, TensorFlow, Azure",Associate,14,Media,2024-01-04,2024-02-03,881,7.6,Smart Analytics +AI01654,AI Software Engineer,114280,CHF,102852,MI,FT,Switzerland,M,Switzerland,0,"Statistics, Kubernetes, Tableau, Docker, Scala",PhD,4,Healthcare,2024-08-31,2024-10-05,695,6.9,Predictive Systems +AI01655,Deep Learning Engineer,75014,EUR,63762,EN,PT,Netherlands,S,Indonesia,100,"Python, Tableau, Azure",Bachelor,1,Finance,2024-11-23,2025-01-21,1349,7.1,TechCorp Inc +AI01656,Data Engineer,32244,USD,32244,EN,CT,India,L,India,100,"SQL, Docker, GCP, Computer Vision",Associate,0,Automotive,2024-05-23,2024-07-29,915,6.3,Cognitive Computing +AI01657,Data Engineer,130809,USD,130809,SE,CT,Sweden,L,Sweden,100,"Python, Git, Kubernetes, GCP",PhD,9,Real Estate,2025-04-30,2025-06-29,696,8.1,Advanced Robotics +AI01658,Data Scientist,194628,CAD,243285,EX,CT,Canada,M,Canada,0,"Git, SQL, Data Visualization, PyTorch, Azure",Associate,19,Real Estate,2024-03-03,2024-04-07,1807,8.9,Digital Transformation LLC +AI01659,Deep Learning Engineer,31750,USD,31750,EN,FL,China,M,Italy,100,"PyTorch, SQL, AWS",Bachelor,1,Energy,2024-11-23,2024-12-27,1036,5.4,Predictive Systems +AI01660,Autonomous Systems Engineer,72863,USD,72863,MI,CT,Israel,S,Netherlands,0,"Git, MLOps, Java, Mathematics",Bachelor,2,Healthcare,2024-04-12,2024-06-02,2466,5.9,Smart Analytics +AI01661,AI Architect,158698,EUR,134893,EX,CT,France,M,France,100,"SQL, Kubernetes, R",Bachelor,11,Manufacturing,2025-04-19,2025-06-10,1473,5.6,Neural Networks Co +AI01662,AI Consultant,70435,USD,70435,EN,CT,United States,L,Germany,0,"Computer Vision, Azure, MLOps, NLP, Git",PhD,0,Real Estate,2024-02-10,2024-04-19,1111,8.5,Smart Analytics +AI01663,Robotics Engineer,70871,USD,70871,MI,FT,Israel,M,Israel,100,"Computer Vision, Kubernetes, Git, PyTorch",Bachelor,2,Consulting,2024-10-18,2024-11-07,2450,7.5,Cloud AI Solutions +AI01664,AI Research Scientist,69256,USD,69256,EN,FT,Finland,L,Hungary,50,"Docker, Tableau, Kubernetes",Master,0,Retail,2025-01-01,2025-03-07,1772,8.3,Cloud AI Solutions +AI01665,Computer Vision Engineer,172569,EUR,146684,EX,CT,Germany,M,Germany,100,"Kubernetes, Spark, PyTorch, GCP",Bachelor,14,Consulting,2025-01-08,2025-02-02,2081,6,Predictive Systems +AI01666,Data Engineer,105421,USD,105421,MI,PT,Ireland,M,Netherlands,50,"R, SQL, Statistics, Java, Data Visualization",Master,4,Manufacturing,2024-10-18,2024-12-20,1129,5,Advanced Robotics +AI01667,Research Scientist,280936,USD,280936,EX,PT,Ireland,L,Ireland,0,"Spark, Python, TensorFlow, SQL, Linux",Bachelor,13,Finance,2024-01-27,2024-03-16,2149,7.9,AI Innovations +AI01668,AI Research Scientist,244804,USD,244804,EX,FT,Denmark,S,Denmark,100,"Azure, Computer Vision, TensorFlow, Python, GCP",PhD,12,Real Estate,2025-01-24,2025-03-17,2021,9.3,Advanced Robotics +AI01669,AI Architect,116583,USD,116583,MI,PT,United States,S,Colombia,100,"SQL, Computer Vision, Kubernetes, AWS, R",Bachelor,2,Transportation,2024-01-17,2024-01-31,2075,9.1,Digital Transformation LLC +AI01670,Computer Vision Engineer,44363,USD,44363,SE,CT,India,M,India,50,"Hadoop, Tableau, R, MLOps, AWS",PhD,9,Government,2024-10-25,2024-12-03,1663,6.6,Algorithmic Solutions +AI01671,Robotics Engineer,103234,GBP,77426,MI,FT,United Kingdom,S,Nigeria,50,"GCP, MLOps, Scala",Associate,4,Media,2024-06-25,2024-08-29,1363,8.2,Machine Intelligence Group +AI01672,AI Research Scientist,241862,USD,241862,EX,FL,Norway,M,France,0,"Scala, PyTorch, Docker, Mathematics, SQL",Master,17,Retail,2025-02-21,2025-04-22,1897,5.9,Machine Intelligence Group +AI01673,Data Scientist,61352,USD,61352,EX,PT,India,L,Argentina,100,"Python, SQL, MLOps",Master,19,Consulting,2025-01-31,2025-04-11,901,9.7,DataVision Ltd +AI01674,Principal Data Scientist,247449,USD,247449,EX,FT,Ireland,M,Ireland,50,"SQL, Mathematics, AWS, Linux, R",Bachelor,16,Manufacturing,2025-04-11,2025-05-19,1591,6.1,Smart Analytics +AI01675,NLP Engineer,91517,USD,91517,MI,CT,Denmark,S,Denmark,100,"Linux, PyTorch, Tableau",Bachelor,4,Energy,2025-01-05,2025-01-24,1982,6.5,Predictive Systems +AI01676,Deep Learning Engineer,231797,EUR,197027,EX,PT,Netherlands,L,Israel,100,"SQL, Java, Deep Learning, MLOps",Bachelor,13,Retail,2024-11-02,2024-11-18,1062,7.4,Cloud AI Solutions +AI01677,AI Software Engineer,29053,USD,29053,EN,FT,China,L,China,100,"Scala, GCP, NLP, PyTorch",Associate,1,Finance,2024-05-17,2024-06-15,503,5.3,Smart Analytics +AI01678,Data Scientist,38480,USD,38480,MI,FT,India,L,India,50,"Scala, Spark, PyTorch, AWS",Bachelor,2,Consulting,2025-03-25,2025-05-06,2254,5.6,Autonomous Tech +AI01679,Data Scientist,49357,USD,49357,EN,FT,Finland,S,Finland,0,"Java, Mathematics, Tableau, NLP, Deep Learning",Bachelor,1,Transportation,2024-07-02,2024-07-31,2422,5.9,DeepTech Ventures +AI01680,Data Analyst,100391,CAD,125489,SE,FT,Canada,M,Nigeria,50,"Hadoop, Linux, SQL",Bachelor,9,Government,2024-10-05,2024-12-02,1941,5.7,Algorithmic Solutions +AI01681,ML Ops Engineer,72840,CHF,65556,EN,FL,Switzerland,S,Switzerland,50,"Python, Git, Java, Docker",Associate,0,Gaming,2024-02-28,2024-03-19,2048,5,Autonomous Tech +AI01682,Data Scientist,265397,EUR,225587,EX,FL,Germany,L,Germany,100,"Scala, AWS, NLP, Statistics",Master,16,Retail,2024-07-24,2024-08-21,1192,5.9,Predictive Systems +AI01683,NLP Engineer,92492,AUD,124864,EN,FL,Australia,L,Australia,100,"Tableau, SQL, Git, Python",PhD,0,Consulting,2024-05-26,2024-07-24,1700,9.4,TechCorp Inc +AI01684,AI Specialist,110408,USD,110408,SE,CT,Sweden,S,Sweden,0,"Python, Linux, R, Computer Vision",Associate,7,Technology,2024-09-25,2024-12-01,2267,10,Quantum Computing Inc +AI01685,NLP Engineer,139699,EUR,118744,EX,FT,Germany,M,Ireland,50,"Azure, Deep Learning, Scala, Mathematics",Associate,19,Finance,2024-07-25,2024-08-31,582,9.1,Advanced Robotics +AI01686,ML Ops Engineer,80747,EUR,68635,MI,CT,Netherlands,S,Netherlands,50,"NLP, Data Visualization, Python, TensorFlow, Linux",Master,3,Telecommunications,2024-02-22,2024-03-09,1345,7.1,Cognitive Computing +AI01687,Data Scientist,86520,EUR,73542,MI,FL,Austria,S,Nigeria,100,"Python, Git, TensorFlow",Bachelor,4,Finance,2024-07-08,2024-09-05,1578,6.4,Machine Intelligence Group +AI01688,AI Specialist,55997,USD,55997,EX,CT,India,M,Israel,50,"NLP, Azure, Python",PhD,12,Manufacturing,2025-03-25,2025-05-28,1550,5.4,AI Innovations +AI01689,AI Software Engineer,107119,SGD,139255,MI,PT,Singapore,M,Singapore,100,"Kubernetes, MLOps, Java, TensorFlow",Bachelor,3,Transportation,2024-04-22,2024-06-21,2417,5.3,Advanced Robotics +AI01690,Research Scientist,117336,EUR,99736,SE,FT,Austria,S,Malaysia,0,"NLP, Scala, Python",Bachelor,9,Consulting,2024-08-23,2024-09-10,1052,6.3,DeepTech Ventures +AI01691,Head of AI,164003,EUR,139403,EX,PT,Austria,S,Vietnam,0,"NLP, Java, PyTorch, GCP",PhD,16,Education,2024-03-09,2024-03-25,645,6,TechCorp Inc +AI01692,Computer Vision Engineer,109093,USD,109093,MI,FL,Ireland,L,Ireland,50,"Statistics, Azure, Scala, GCP, NLP",Master,4,Manufacturing,2025-04-26,2025-06-12,2262,8.6,AI Innovations +AI01693,Machine Learning Researcher,60847,USD,60847,EN,FL,Ireland,M,Ireland,50,"Azure, Mathematics, Python",Associate,0,Manufacturing,2024-12-19,2025-02-26,1775,7.8,DeepTech Ventures +AI01694,AI Product Manager,64394,USD,64394,MI,FT,South Korea,S,South Africa,0,"Azure, Deep Learning, GCP, Spark, R",Bachelor,4,Gaming,2024-01-24,2024-02-20,1682,9.2,Digital Transformation LLC +AI01695,Principal Data Scientist,56336,USD,56336,EN,FT,Sweden,M,Sweden,100,"Python, MLOps, Git",Bachelor,1,Transportation,2024-12-15,2025-01-23,1402,9.9,Predictive Systems +AI01696,AI Consultant,151360,JPY,16649600,EX,PT,Japan,M,Japan,50,"Scala, Kubernetes, Computer Vision, NLP, Git",PhD,11,Transportation,2024-05-26,2024-07-29,2089,5.4,Digital Transformation LLC +AI01697,Head of AI,108867,EUR,92537,SE,FL,Netherlands,M,Netherlands,50,"Mathematics, Java, Spark",PhD,7,Automotive,2024-07-15,2024-09-15,1367,6.6,Cognitive Computing +AI01698,AI Consultant,163581,EUR,139044,SE,CT,Germany,L,Germany,50,"GCP, Computer Vision, Hadoop",PhD,8,Automotive,2024-10-15,2024-12-01,1213,8.5,Machine Intelligence Group +AI01699,AI Product Manager,111866,JPY,12305260,MI,FT,Japan,M,Japan,0,"Java, Kubernetes, SQL, Mathematics",Bachelor,2,Media,2024-11-04,2024-12-30,1683,9.3,Cloud AI Solutions +AI01700,NLP Engineer,56511,USD,56511,EN,CT,South Korea,L,Israel,50,"Kubernetes, Java, Deep Learning, Mathematics, Computer Vision",PhD,0,Media,2024-10-29,2024-11-30,2130,7.1,Future Systems +AI01701,NLP Engineer,40401,USD,40401,MI,CT,China,L,China,100,"TensorFlow, SQL, Mathematics, Linux",PhD,4,Healthcare,2024-05-11,2024-06-10,2122,9.1,TechCorp Inc +AI01702,Research Scientist,130250,CHF,117225,MI,FL,Switzerland,L,Hungary,0,"Data Visualization, GCP, Scala, Docker",PhD,2,Media,2024-03-30,2024-05-22,2139,5,Algorithmic Solutions +AI01703,Computer Vision Engineer,41173,USD,41173,MI,CT,China,S,Austria,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2025-04-29,2025-06-23,1174,6.2,Smart Analytics +AI01704,Data Engineer,69187,USD,69187,EN,FL,United States,S,United States,50,"Kubernetes, Spark, Java",Associate,0,Media,2024-01-31,2024-04-04,1954,9.2,Quantum Computing Inc +AI01705,NLP Engineer,80973,USD,80973,EX,FT,India,S,Australia,100,"Linux, Python, Tableau, Kubernetes, SQL",Associate,11,Energy,2024-04-07,2024-05-31,1601,7.7,Quantum Computing Inc +AI01706,AI Software Engineer,117099,USD,117099,SE,PT,Ireland,M,Ireland,50,"Spark, Java, Computer Vision, Tableau",Bachelor,7,Real Estate,2024-10-03,2024-10-20,672,6.3,DeepTech Ventures +AI01707,AI Architect,62738,USD,62738,EN,FL,Finland,S,Canada,0,"Git, SQL, GCP",Associate,1,Consulting,2024-02-06,2024-03-01,1244,9.7,Neural Networks Co +AI01708,AI Product Manager,120017,EUR,102014,MI,FT,Germany,L,Germany,100,"Java, Kubernetes, Deep Learning",Bachelor,4,Education,2025-02-03,2025-03-17,588,8.6,Digital Transformation LLC +AI01709,AI Architect,146456,USD,146456,MI,FL,United States,L,United States,0,"SQL, Spark, Linux",PhD,2,Real Estate,2024-08-20,2024-10-17,1112,5.3,Autonomous Tech +AI01710,Data Engineer,116585,AUD,157390,SE,FL,Australia,M,Australia,0,"Mathematics, Computer Vision, Linux, Kubernetes",Master,8,Energy,2024-02-26,2024-04-21,1405,8.2,DeepTech Ventures +AI01711,AI Architect,48908,EUR,41572,EN,FT,France,M,France,100,"Spark, TensorFlow, Python, NLP, Statistics",Master,1,Healthcare,2024-12-28,2025-03-06,739,7.1,Machine Intelligence Group +AI01712,Head of AI,140368,USD,140368,MI,FT,Norway,M,Norway,0,"Java, Linux, Statistics, GCP",Master,2,Manufacturing,2024-06-25,2024-08-09,1177,8.6,Future Systems +AI01713,Deep Learning Engineer,117338,JPY,12907180,MI,FL,Japan,L,Brazil,100,"PyTorch, SQL, Hadoop, Deep Learning, Kubernetes",Associate,3,Manufacturing,2024-12-07,2025-01-22,1586,6.8,Quantum Computing Inc +AI01714,Head of AI,25199,USD,25199,EN,PT,China,M,Germany,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Media,2024-04-18,2024-06-22,849,9.8,Machine Intelligence Group +AI01715,AI Architect,101321,EUR,86123,MI,FT,France,M,France,50,"Python, Statistics, Tableau",PhD,3,Gaming,2025-03-24,2025-04-20,2449,7.7,Predictive Systems +AI01716,Machine Learning Engineer,86336,USD,86336,MI,FT,Ireland,S,Ghana,0,"Deep Learning, SQL, Data Visualization, PyTorch",Master,4,Retail,2025-03-09,2025-05-21,1028,8.6,TechCorp Inc +AI01717,Machine Learning Researcher,104654,JPY,11511940,MI,FL,Japan,L,Japan,100,"Azure, Deep Learning, R",Master,2,Energy,2024-02-24,2024-04-20,739,8.1,Cognitive Computing +AI01718,AI Specialist,93107,USD,93107,MI,FT,Ireland,L,Mexico,0,"PyTorch, GCP, Tableau",Associate,3,Gaming,2024-03-18,2024-04-05,2334,9.5,Smart Analytics +AI01719,AI Consultant,113304,USD,113304,MI,CT,Norway,S,Norway,0,"SQL, Azure, PyTorch",Bachelor,3,Healthcare,2024-04-24,2024-05-19,517,6.1,Algorithmic Solutions +AI01720,Deep Learning Engineer,159382,USD,159382,EX,CT,Ireland,M,Ireland,100,"Java, Python, Computer Vision, R",Master,12,Transportation,2024-07-03,2024-07-18,617,8.7,Future Systems +AI01721,AI Specialist,112099,USD,112099,SE,FL,South Korea,M,South Korea,50,"Azure, Python, Computer Vision",Bachelor,9,Media,2024-07-03,2024-07-17,1317,8,Advanced Robotics +AI01722,Head of AI,106493,USD,106493,MI,PT,Norway,M,Norway,0,"Linux, Scala, PyTorch, MLOps, Tableau",Master,4,Real Estate,2025-03-27,2025-05-18,1839,7.1,AI Innovations +AI01723,AI Architect,76693,SGD,99701,EN,FT,Singapore,M,Singapore,100,"Mathematics, Statistics, PyTorch",PhD,1,Real Estate,2025-04-14,2025-05-02,740,8.4,Neural Networks Co +AI01724,NLP Engineer,145475,USD,145475,SE,CT,Finland,L,Latvia,100,"Spark, Java, Deep Learning, AWS",Associate,9,Energy,2025-02-11,2025-03-14,1076,8.5,DataVision Ltd +AI01725,Data Analyst,79166,GBP,59375,EN,FT,United Kingdom,L,United Kingdom,50,"Scala, Kubernetes, MLOps, Azure, AWS",PhD,0,Finance,2024-09-24,2024-10-08,1643,9.6,DeepTech Ventures +AI01726,AI Architect,187864,USD,187864,EX,FL,Sweden,M,Sweden,0,"Git, PyTorch, SQL, Scala",Associate,16,Gaming,2024-12-06,2025-01-07,921,6.1,Future Systems +AI01727,AI Consultant,50080,USD,50080,EN,CT,Israel,S,Israel,100,"Deep Learning, Python, Mathematics",Bachelor,1,Technology,2025-01-27,2025-04-06,2110,6.6,Autonomous Tech +AI01728,Autonomous Systems Engineer,103470,JPY,11381700,MI,CT,Japan,L,Japan,100,"Computer Vision, R, Kubernetes, Tableau",Master,2,Technology,2024-11-14,2024-12-09,1694,6.9,Predictive Systems +AI01729,Machine Learning Engineer,84323,USD,84323,MI,FT,Sweden,M,Sweden,50,"Kubernetes, Git, Statistics",Bachelor,3,Real Estate,2024-11-25,2025-01-08,1134,8,DeepTech Ventures +AI01730,Robotics Engineer,71020,CAD,88775,MI,PT,Canada,S,Czech Republic,100,"Java, Tableau, PyTorch, NLP, SQL",Bachelor,3,Manufacturing,2024-02-21,2024-04-23,1253,9.7,Future Systems +AI01731,NLP Engineer,74489,USD,74489,EX,FL,China,M,Austria,50,"Linux, Docker, SQL",PhD,11,Healthcare,2024-06-03,2024-07-24,1437,9.7,TechCorp Inc +AI01732,AI Product Manager,55564,AUD,75011,EN,FT,Australia,M,Australia,50,"SQL, PyTorch, Git, Azure, AWS",Bachelor,0,Transportation,2025-03-22,2025-06-02,2036,6.3,Predictive Systems +AI01733,AI Consultant,84737,USD,84737,EN,CT,United States,S,United States,0,"Spark, Data Visualization, Computer Vision",Bachelor,1,Telecommunications,2025-01-06,2025-02-02,1139,6.8,DeepTech Ventures +AI01734,AI Software Engineer,125029,EUR,106275,SE,FL,France,M,France,50,"SQL, Azure, Java, Spark, AWS",Master,5,Healthcare,2025-01-19,2025-03-23,1740,5.6,DataVision Ltd +AI01735,Robotics Engineer,93053,EUR,79095,MI,FL,France,S,France,0,"Spark, R, Data Visualization",PhD,3,Education,2025-01-06,2025-02-15,629,5.1,DeepTech Ventures +AI01736,AI Architect,116161,USD,116161,MI,FT,United States,S,United States,50,"SQL, PyTorch, GCP, Linux",PhD,2,Technology,2025-01-07,2025-02-22,1201,7.2,Predictive Systems +AI01737,AI Software Engineer,96819,USD,96819,MI,FT,United States,S,United States,0,"Spark, Python, Tableau, Kubernetes",PhD,3,Finance,2024-11-18,2025-01-12,1105,7.7,TechCorp Inc +AI01738,Computer Vision Engineer,21074,USD,21074,EN,CT,India,M,India,50,"Git, Azure, Data Visualization",Associate,0,Retail,2024-06-29,2024-07-30,1551,7.4,Algorithmic Solutions +AI01739,Data Scientist,131324,USD,131324,MI,PT,Denmark,M,Denmark,100,"Tableau, Deep Learning, GCP, Java",PhD,2,Transportation,2024-12-14,2025-02-16,2003,6,Digital Transformation LLC +AI01740,Principal Data Scientist,58660,USD,58660,EN,CT,Finland,M,Finland,50,"Hadoop, Spark, Tableau",PhD,1,Finance,2024-10-09,2024-11-22,1205,9.9,Digital Transformation LLC +AI01741,Machine Learning Engineer,132875,EUR,112944,MI,PT,Netherlands,L,Malaysia,50,"GCP, Python, Mathematics, Linux, SQL",PhD,4,Consulting,2024-08-28,2024-10-31,1392,6.1,Quantum Computing Inc +AI01742,Computer Vision Engineer,74316,USD,74316,MI,FT,South Korea,S,South Korea,50,"TensorFlow, GCP, Azure",Bachelor,3,Energy,2024-11-17,2025-01-04,1075,9.4,Advanced Robotics +AI01743,Data Engineer,65320,EUR,55522,EN,FT,France,S,France,100,"Java, Python, Git",Bachelor,1,Media,2024-04-01,2024-05-18,915,8.7,Digital Transformation LLC +AI01744,Autonomous Systems Engineer,128941,USD,128941,SE,CT,Finland,L,Finland,50,"TensorFlow, Spark, PyTorch",Master,7,Manufacturing,2025-01-26,2025-03-07,2349,7.6,Cognitive Computing +AI01745,Principal Data Scientist,42409,USD,42409,MI,CT,China,M,South Korea,100,"PyTorch, TensorFlow, NLP",Bachelor,2,Media,2024-04-16,2024-05-09,2188,9.6,Algorithmic Solutions +AI01746,NLP Engineer,76564,GBP,57423,EN,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, Azure, Scala",PhD,0,Government,2024-03-03,2024-04-13,1639,9.4,Neural Networks Co +AI01747,NLP Engineer,289808,EUR,246337,EX,FT,Netherlands,L,Luxembourg,100,"Statistics, TensorFlow, PyTorch, Data Visualization, Hadoop",PhD,17,Automotive,2025-03-17,2025-04-28,2224,6.3,Neural Networks Co +AI01748,Data Analyst,62042,CAD,77553,EN,FL,Canada,M,Kenya,50,"Python, Azure, Tableau",Bachelor,1,Government,2024-02-15,2024-03-21,1611,6.1,TechCorp Inc +AI01749,AI Product Manager,98976,EUR,84130,MI,FT,Netherlands,M,Netherlands,100,"Statistics, Python, Mathematics, Linux, Hadoop",PhD,4,Manufacturing,2024-11-08,2024-12-24,2377,6.9,Autonomous Tech +AI01750,AI Architect,122469,USD,122469,EX,FL,South Korea,M,South Korea,50,"Linux, Scala, Java, Deep Learning, Spark",Bachelor,19,Education,2024-09-05,2024-10-17,1048,7.1,Future Systems +AI01751,NLP Engineer,187847,USD,187847,EX,FT,Ireland,M,Ireland,50,"PyTorch, TensorFlow, SQL, R",PhD,16,Transportation,2024-01-27,2024-02-16,2318,10,DeepTech Ventures +AI01752,AI Consultant,157782,JPY,17356020,EX,FT,Japan,S,Japan,0,"Spark, NLP, GCP",Master,13,Transportation,2024-11-25,2025-01-06,670,9.1,Cognitive Computing +AI01753,Research Scientist,128659,USD,128659,MI,FL,Denmark,S,Mexico,50,"Python, Linux, Scala, TensorFlow",Bachelor,2,Gaming,2024-03-04,2024-05-03,1580,5.7,Algorithmic Solutions +AI01754,AI Architect,61499,USD,61499,EN,FL,Finland,M,Ukraine,100,"Scala, Data Visualization, SQL, Tableau, MLOps",PhD,0,Government,2024-08-12,2024-10-13,1241,6.6,Neural Networks Co +AI01755,Deep Learning Engineer,66190,USD,66190,EN,FL,Ireland,L,Ireland,50,"Computer Vision, Git, Tableau, Linux, Python",PhD,1,Telecommunications,2024-10-18,2024-11-22,642,9.5,Digital Transformation LLC +AI01756,Machine Learning Engineer,29153,USD,29153,EN,FL,China,M,China,0,"Hadoop, Linux, Deep Learning, Mathematics, Git",PhD,0,Media,2024-01-16,2024-02-14,1718,9.1,Predictive Systems +AI01757,Deep Learning Engineer,64431,JPY,7087410,EN,FT,Japan,S,Japan,0,"Java, Tableau, MLOps",Master,1,Gaming,2024-03-06,2024-04-13,1972,9.2,Machine Intelligence Group +AI01758,Data Analyst,330366,USD,330366,EX,FL,Denmark,L,Denmark,0,"NLP, SQL, Tableau, Docker",Bachelor,17,Gaming,2024-03-14,2024-04-20,736,7.9,DataVision Ltd +AI01759,Machine Learning Engineer,128575,USD,128575,MI,PT,United States,M,United States,0,"Linux, Kubernetes, Spark",Bachelor,3,Automotive,2025-04-26,2025-05-21,518,9.4,Cloud AI Solutions +AI01760,AI Software Engineer,150066,GBP,112550,SE,PT,United Kingdom,M,United Kingdom,100,"Java, NLP, AWS, R, SQL",Associate,9,Media,2024-04-28,2024-07-10,1608,9.3,Predictive Systems +AI01761,Data Engineer,147214,SGD,191378,SE,CT,Singapore,L,Singapore,0,"Azure, Tableau, Scala, NLP, SQL",Associate,6,Gaming,2024-06-12,2024-07-31,1222,7.4,Cognitive Computing +AI01762,Computer Vision Engineer,35538,USD,35538,EN,FT,China,M,New Zealand,100,"AWS, Git, PyTorch, Java",Bachelor,0,Consulting,2024-11-03,2024-11-17,1062,9.5,DeepTech Ventures +AI01763,ML Ops Engineer,131200,EUR,111520,SE,FL,Germany,S,Germany,100,"GCP, Scala, NLP, Computer Vision, AWS",PhD,7,Government,2024-10-23,2024-12-30,1286,6.9,DeepTech Ventures +AI01764,Computer Vision Engineer,65465,USD,65465,EN,FT,South Korea,M,Switzerland,100,"Java, Linux, Scala",Associate,1,Consulting,2024-08-08,2024-09-29,728,8.9,TechCorp Inc +AI01765,AI Software Engineer,239103,GBP,179327,EX,CT,United Kingdom,M,United Kingdom,50,"R, Python, TensorFlow, Computer Vision",Associate,12,Automotive,2024-07-04,2024-07-25,1486,9.7,AI Innovations +AI01766,Robotics Engineer,107447,EUR,91330,SE,FL,Germany,S,France,50,"Data Visualization, Spark, R",Master,8,Technology,2024-07-13,2024-07-31,633,8.4,AI Innovations +AI01767,Machine Learning Researcher,56221,USD,56221,MI,FT,South Korea,S,South Korea,100,"PyTorch, SQL, MLOps, Data Visualization, Statistics",Master,4,Real Estate,2024-10-18,2024-12-08,575,8.1,Predictive Systems +AI01768,Deep Learning Engineer,123027,AUD,166086,MI,CT,Australia,L,Australia,0,"Linux, Kubernetes, Tableau, Java",Associate,4,Technology,2024-07-27,2024-09-03,1040,5.2,Predictive Systems +AI01769,AI Research Scientist,117390,JPY,12912900,SE,FT,Japan,S,Japan,50,"Java, SQL, Scala, Kubernetes",PhD,5,Education,2024-10-23,2024-12-21,2199,7.3,Algorithmic Solutions +AI01770,Autonomous Systems Engineer,89124,EUR,75755,MI,PT,France,L,France,100,"Kubernetes, TensorFlow, AWS, Linux, Azure",Master,4,Finance,2025-04-15,2025-05-02,1308,9.1,DataVision Ltd +AI01771,AI Product Manager,251508,EUR,213782,EX,PT,France,L,France,0,"GCP, R, Tableau, Spark",Associate,15,Finance,2024-09-05,2024-11-07,2493,9,Future Systems +AI01772,AI Software Engineer,100520,USD,100520,EX,CT,China,L,China,100,"Azure, Python, SQL",Associate,15,Media,2024-07-27,2024-09-29,1705,6.9,DeepTech Ventures +AI01773,Data Scientist,348466,CHF,313619,EX,PT,Switzerland,M,Switzerland,100,"GCP, SQL, Tableau, Data Visualization",Bachelor,13,Energy,2024-02-28,2024-04-19,1875,7.4,TechCorp Inc +AI01774,Autonomous Systems Engineer,132749,USD,132749,SE,FL,Norway,S,Latvia,0,"Linux, Computer Vision, SQL",Bachelor,5,Government,2024-03-22,2024-05-26,2272,7.5,Digital Transformation LLC +AI01775,AI Specialist,63454,USD,63454,EN,FT,Sweden,M,Colombia,50,"Azure, NLP, Deep Learning",PhD,1,Government,2024-12-30,2025-01-26,1742,5.1,Advanced Robotics +AI01776,ML Ops Engineer,102787,EUR,87369,SE,CT,Germany,M,Egypt,100,"Data Visualization, SQL, Python, Computer Vision",Bachelor,5,Transportation,2024-08-21,2024-10-01,1436,7.7,AI Innovations +AI01777,NLP Engineer,19313,USD,19313,EN,FT,India,M,Australia,50,"Python, MLOps, Linux, Deep Learning, Computer Vision",Associate,1,Finance,2024-10-07,2024-10-30,1240,9.1,DeepTech Ventures +AI01778,Machine Learning Researcher,129410,USD,129410,SE,FL,Ireland,M,Ireland,100,"Hadoop, Spark, Python, Kubernetes",Master,5,Automotive,2025-04-23,2025-07-04,1559,6.1,DataVision Ltd +AI01779,NLP Engineer,172013,JPY,18921430,EX,FT,Japan,L,Japan,0,"TensorFlow, Tableau, Azure",Master,11,Manufacturing,2025-01-13,2025-02-08,597,8.1,Machine Intelligence Group +AI01780,Autonomous Systems Engineer,158074,USD,158074,EX,CT,South Korea,S,Estonia,50,"SQL, PyTorch, Deep Learning, Tableau",PhD,14,Government,2024-03-08,2024-04-08,2054,9.4,Smart Analytics +AI01781,Data Engineer,70476,SGD,91619,MI,FL,Singapore,S,Poland,50,"AWS, Deep Learning, Python, SQL",Associate,4,Telecommunications,2024-12-20,2025-01-07,2322,6.3,TechCorp Inc +AI01782,Principal Data Scientist,90948,USD,90948,MI,CT,Israel,L,Canada,100,"Linux, GCP, Tableau, Deep Learning",Master,3,Manufacturing,2024-10-25,2024-12-10,1802,5.7,Quantum Computing Inc +AI01783,Machine Learning Researcher,238184,EUR,202456,EX,CT,Netherlands,M,Romania,50,"Python, Java, GCP, TensorFlow",Bachelor,10,Technology,2024-07-08,2024-07-25,715,6,Machine Intelligence Group +AI01784,Computer Vision Engineer,142525,USD,142525,EX,CT,Finland,M,Finland,0,"PyTorch, Kubernetes, NLP, Java",Bachelor,14,Gaming,2024-03-08,2024-04-04,647,6.7,DeepTech Ventures +AI01785,Deep Learning Engineer,210001,EUR,178501,EX,FL,Netherlands,S,Romania,50,"Python, Spark, NLP, Mathematics, Deep Learning",Bachelor,12,Consulting,2024-01-20,2024-03-21,1318,6.8,Cloud AI Solutions +AI01786,Data Analyst,124024,USD,124024,MI,FL,Denmark,L,Indonesia,0,"Spark, Python, Hadoop",Master,4,Manufacturing,2024-07-27,2024-08-24,973,6,Advanced Robotics +AI01787,AI Product Manager,269130,USD,269130,EX,PT,Denmark,M,Denmark,0,"Spark, Tableau, GCP",Associate,17,Manufacturing,2025-04-28,2025-07-10,1322,6.4,Autonomous Tech +AI01788,AI Specialist,44705,USD,44705,SE,CT,India,M,China,100,"Hadoop, Statistics, Scala, Mathematics, Kubernetes",Bachelor,8,Energy,2024-06-02,2024-07-04,1945,9.4,Digital Transformation LLC +AI01789,Data Analyst,79352,EUR,67449,EN,PT,Netherlands,M,Netherlands,100,"MLOps, Java, Python",Bachelor,0,Finance,2025-03-19,2025-05-10,2050,9.5,Cloud AI Solutions +AI01790,AI Consultant,143377,JPY,15771470,SE,FL,Japan,M,Japan,50,"TensorFlow, Computer Vision, MLOps, Data Visualization, Python",PhD,7,Real Estate,2024-01-27,2024-02-19,786,5.3,Machine Intelligence Group +AI01791,Machine Learning Engineer,40231,USD,40231,MI,FL,China,M,Malaysia,100,"Tableau, TensorFlow, Scala, Python, Mathematics",Bachelor,4,Retail,2024-01-27,2024-02-12,967,7.5,Advanced Robotics +AI01792,Robotics Engineer,79846,GBP,59885,MI,PT,United Kingdom,M,Ukraine,50,"PyTorch, Kubernetes, Computer Vision, GCP, Linux",PhD,2,Energy,2024-05-28,2024-07-03,668,5.9,Advanced Robotics +AI01793,Research Scientist,138782,USD,138782,EX,FL,Ireland,S,Malaysia,0,"Azure, Spark, R, Statistics, SQL",PhD,12,Manufacturing,2025-01-29,2025-03-13,1957,9.3,DeepTech Ventures +AI01794,ML Ops Engineer,199769,EUR,169804,EX,CT,Austria,S,Portugal,0,"AWS, Python, PyTorch",Associate,18,Transportation,2024-06-13,2024-08-19,580,7.9,Machine Intelligence Group +AI01795,AI Research Scientist,305289,USD,305289,EX,FL,Denmark,L,France,100,"Docker, MLOps, Data Visualization",Associate,17,Technology,2025-04-11,2025-06-08,1208,9.1,Algorithmic Solutions +AI01796,AI Product Manager,230691,EUR,196087,EX,FT,Austria,M,Estonia,0,"Git, Python, Linux, Kubernetes, AWS",Master,17,Consulting,2025-02-22,2025-03-10,1625,8.6,Future Systems +AI01797,AI Product Manager,238615,JPY,26247650,EX,CT,Japan,L,Austria,0,"Kubernetes, Git, Java, GCP, SQL",Bachelor,19,Manufacturing,2024-07-04,2024-08-11,1578,8.1,Neural Networks Co +AI01798,Machine Learning Engineer,98044,USD,98044,SE,FT,Sweden,S,Sweden,100,"Scala, R, TensorFlow",Associate,7,Telecommunications,2024-02-06,2024-03-31,1120,5.1,Cloud AI Solutions +AI01799,AI Research Scientist,69231,AUD,93462,MI,PT,Australia,S,Australia,100,"Scala, Java, R, Deep Learning, SQL",Associate,3,Gaming,2024-08-19,2024-10-02,2261,9.7,Machine Intelligence Group +AI01800,NLP Engineer,233794,AUD,315622,EX,FT,Australia,L,Australia,50,"Azure, Spark, SQL, Mathematics",Master,19,Transportation,2024-01-14,2024-02-18,902,6.8,Neural Networks Co +AI01801,Computer Vision Engineer,145411,EUR,123599,SE,FT,Netherlands,S,Netherlands,50,"TensorFlow, SQL, Deep Learning, R",PhD,8,Manufacturing,2025-03-20,2025-05-19,1854,6.4,Advanced Robotics +AI01802,ML Ops Engineer,119952,USD,119952,SE,FT,United States,S,Russia,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,9,Finance,2024-10-14,2024-11-06,1828,8.2,Neural Networks Co +AI01803,AI Architect,152045,USD,152045,EX,PT,United States,S,United States,50,"Mathematics, Docker, Tableau",Associate,17,Retail,2024-10-22,2024-12-23,2178,7.6,Predictive Systems +AI01804,AI Software Engineer,60657,USD,60657,SE,FT,China,L,China,0,"Java, Data Visualization, Git, Statistics",Master,8,Government,2025-02-06,2025-03-10,2006,5.1,DeepTech Ventures +AI01805,AI Specialist,157794,USD,157794,EX,PT,South Korea,L,Argentina,50,"Java, Spark, MLOps, Statistics, Python",Associate,13,Media,2025-03-04,2025-04-16,2398,8.4,DataVision Ltd +AI01806,Data Engineer,37836,USD,37836,MI,FT,India,L,Sweden,50,"GCP, Mathematics, Hadoop",Bachelor,2,Finance,2025-04-23,2025-07-05,1374,7.8,Neural Networks Co +AI01807,AI Research Scientist,68797,USD,68797,MI,FL,Israel,S,United Kingdom,100,"TensorFlow, Docker, Git, R",Bachelor,2,Manufacturing,2024-04-02,2024-05-05,2438,5.1,Autonomous Tech +AI01808,Data Scientist,144648,EUR,122951,SE,FL,France,L,France,50,"GCP, Kubernetes, Docker, Spark, Azure",Associate,6,Government,2024-04-22,2024-05-29,1741,5.8,Cloud AI Solutions +AI01809,AI Architect,88724,USD,88724,EN,FT,Ireland,L,Ireland,0,"Scala, Python, Data Visualization",Bachelor,1,Telecommunications,2024-01-26,2024-03-12,2198,9.9,Digital Transformation LLC +AI01810,Data Engineer,186244,CHF,167620,SE,PT,Switzerland,S,Switzerland,50,"Python, Scala, Computer Vision, MLOps, Linux",Master,5,Media,2025-02-14,2025-04-13,2167,5,Neural Networks Co +AI01811,Deep Learning Engineer,88469,USD,88469,SE,FL,South Korea,S,Czech Republic,0,"Spark, R, Scala, Java",Master,6,Education,2025-02-26,2025-04-02,1641,5.2,Machine Intelligence Group +AI01812,Principal Data Scientist,310111,USD,310111,EX,CT,Norway,L,Norway,0,"Statistics, Computer Vision, NLP, Linux",Bachelor,19,Retail,2024-08-08,2024-10-02,1834,6.2,AI Innovations +AI01813,AI Consultant,98560,SGD,128128,SE,CT,Singapore,S,Switzerland,100,"Statistics, MLOps, Mathematics, GCP",PhD,5,Education,2024-11-25,2024-12-09,1838,9.6,AI Innovations +AI01814,AI Specialist,159392,USD,159392,SE,FT,Norway,M,Poland,0,"Java, R, PyTorch",Bachelor,6,Media,2024-10-13,2024-11-27,1842,8,Autonomous Tech +AI01815,Data Engineer,109927,USD,109927,MI,FT,Norway,S,Norway,0,"PyTorch, Kubernetes, TensorFlow, Git",Associate,2,Manufacturing,2025-03-20,2025-05-04,1979,5,Autonomous Tech +AI01816,AI Consultant,135881,EUR,115499,SE,PT,Germany,S,Germany,100,"PyTorch, SQL, NLP",Bachelor,9,Transportation,2025-03-17,2025-04-30,1232,8.4,TechCorp Inc +AI01817,Data Engineer,170048,USD,170048,EX,CT,United States,S,Israel,100,"Statistics, Linux, Tableau, R",PhD,16,Automotive,2024-02-20,2024-03-28,1561,9.8,Machine Intelligence Group +AI01818,Computer Vision Engineer,86374,USD,86374,EX,CT,India,M,India,50,"TensorFlow, Statistics, Scala, Python",PhD,12,Healthcare,2025-01-01,2025-02-09,1201,9.7,Advanced Robotics +AI01819,Computer Vision Engineer,79277,CAD,99096,MI,FT,Canada,S,Canada,100,"PyTorch, R, GCP, Java, Linux",Master,2,Real Estate,2024-05-10,2024-06-02,1121,9.6,AI Innovations +AI01820,Data Scientist,73902,USD,73902,MI,FT,Finland,S,Turkey,100,"Deep Learning, Scala, TensorFlow, MLOps",Master,2,Gaming,2024-02-03,2024-04-03,1351,9,Cognitive Computing +AI01821,Principal Data Scientist,61896,USD,61896,EN,FL,Ireland,M,Ghana,0,"Kubernetes, Azure, SQL, R, Docker",Associate,1,Automotive,2024-01-13,2024-02-12,1699,5.2,DeepTech Ventures +AI01822,AI Product Manager,57201,CAD,71501,EN,PT,Canada,L,Canada,100,"Linux, Tableau, MLOps, Azure",Bachelor,1,Healthcare,2024-12-08,2025-01-30,1408,6.3,AI Innovations +AI01823,Principal Data Scientist,72205,USD,72205,EN,CT,Sweden,M,Brazil,100,"Tableau, Docker, Spark, Kubernetes",Bachelor,0,Transportation,2024-03-31,2024-05-22,943,9.2,Quantum Computing Inc +AI01824,AI Specialist,45721,USD,45721,EN,FL,Israel,S,Singapore,0,"Azure, AWS, Docker",Master,1,Retail,2024-01-16,2024-02-09,2151,7.9,Quantum Computing Inc +AI01825,AI Research Scientist,76605,USD,76605,EN,CT,Denmark,M,Denmark,100,"Spark, Java, Deep Learning, Kubernetes, AWS",Master,1,Healthcare,2024-12-31,2025-03-06,1455,9.9,TechCorp Inc +AI01826,Data Engineer,90927,EUR,77288,MI,FL,Netherlands,L,Netherlands,0,"R, Git, Deep Learning",PhD,2,Automotive,2024-03-05,2024-04-25,777,6.5,Digital Transformation LLC +AI01827,ML Ops Engineer,129674,CAD,162093,SE,CT,Canada,L,Canada,50,"MLOps, Python, NLP, Linux, Hadoop",Master,5,Energy,2025-02-14,2025-04-20,1628,9.7,Smart Analytics +AI01828,Autonomous Systems Engineer,79647,USD,79647,EN,CT,Israel,L,Brazil,100,"Azure, Tableau, Spark",PhD,0,Automotive,2024-06-28,2024-09-03,1836,5.4,DeepTech Ventures +AI01829,Autonomous Systems Engineer,143268,USD,143268,SE,CT,United States,L,United States,100,"Scala, Docker, SQL, Git, MLOps",Bachelor,6,Finance,2024-04-22,2024-06-02,2000,7.5,Neural Networks Co +AI01830,Principal Data Scientist,55944,USD,55944,EN,CT,United States,S,United States,0,"Python, Scala, GCP",Master,1,Consulting,2024-04-21,2024-06-22,2218,8.8,Cloud AI Solutions +AI01831,Head of AI,147714,USD,147714,SE,PT,Denmark,M,Denmark,50,"R, Hadoop, Scala",PhD,7,Gaming,2024-03-05,2024-03-23,1834,5.2,Neural Networks Co +AI01832,AI Product Manager,62923,GBP,47192,EN,FL,United Kingdom,L,United Kingdom,100,"SQL, Statistics, MLOps",Master,0,Automotive,2024-05-17,2024-06-02,2457,5.2,Predictive Systems +AI01833,Deep Learning Engineer,195780,USD,195780,EX,FT,Denmark,S,Japan,100,"Java, PyTorch, Spark",PhD,13,Automotive,2024-04-24,2024-06-03,943,6.5,Machine Intelligence Group +AI01834,Data Analyst,127106,USD,127106,SE,CT,United States,S,Estonia,50,"Python, R, NLP, MLOps, Java",Bachelor,8,Automotive,2025-04-12,2025-06-06,935,5.4,Advanced Robotics +AI01835,Deep Learning Engineer,57038,USD,57038,EN,FT,South Korea,L,South Korea,100,"Data Visualization, R, Hadoop, PyTorch",Master,1,Media,2024-01-06,2024-02-01,2304,5.1,Predictive Systems +AI01836,AI Software Engineer,130998,USD,130998,SE,CT,South Korea,L,South Korea,100,"Data Visualization, PyTorch, Tableau, Git",Bachelor,8,Real Estate,2024-08-01,2024-09-15,1062,5.7,DeepTech Ventures +AI01837,Autonomous Systems Engineer,66589,EUR,56601,EN,FT,Austria,S,Austria,50,"Azure, NLP, GCP, PyTorch",Associate,1,Transportation,2024-11-03,2025-01-07,2290,5.9,AI Innovations +AI01838,Computer Vision Engineer,194996,EUR,165747,EX,CT,Netherlands,L,Malaysia,100,"Data Visualization, Docker, Git, PyTorch, Java",Associate,12,Gaming,2024-10-23,2024-12-10,1664,9.5,Cognitive Computing +AI01839,Data Engineer,152454,EUR,129586,SE,FT,Austria,L,Finland,0,"Statistics, Docker, Hadoop, R",Master,7,Real Estate,2024-08-03,2024-09-01,1068,8.1,DeepTech Ventures +AI01840,Data Analyst,72614,EUR,61722,EN,CT,Germany,S,Germany,50,"Tableau, GCP, MLOps, PyTorch, Git",Associate,0,Real Estate,2024-05-24,2024-07-09,1330,6.5,Predictive Systems +AI01841,Machine Learning Researcher,69406,EUR,58995,EN,CT,Netherlands,L,Netherlands,50,"Hadoop, PyTorch, Data Visualization, TensorFlow, Scala",Associate,1,Education,2024-08-26,2024-09-24,1163,6,Future Systems +AI01842,Machine Learning Engineer,109931,CHF,98938,MI,FL,Switzerland,S,Mexico,50,"TensorFlow, Git, Computer Vision",Master,4,Technology,2025-03-12,2025-05-04,1832,7.5,Future Systems +AI01843,AI Software Engineer,37793,USD,37793,EN,CT,China,M,China,50,"Python, TensorFlow, MLOps, Statistics, Scala",Bachelor,1,Retail,2024-02-05,2024-02-27,2034,8.8,DataVision Ltd +AI01844,Autonomous Systems Engineer,273120,USD,273120,EX,FL,Ireland,L,Ireland,100,"Mathematics, Linux, TensorFlow",Bachelor,15,Retail,2025-04-16,2025-06-27,910,8,Neural Networks Co +AI01845,ML Ops Engineer,105016,CHF,94514,MI,CT,Switzerland,M,Switzerland,100,"Scala, Mathematics, SQL",Master,3,Retail,2025-02-17,2025-04-13,1877,6.2,Cognitive Computing +AI01846,Machine Learning Engineer,231563,CAD,289454,EX,CT,Canada,M,Canada,0,"PyTorch, Hadoop, Kubernetes",Bachelor,10,Education,2024-05-05,2024-06-11,1289,7.7,Neural Networks Co +AI01847,NLP Engineer,120136,USD,120136,SE,CT,Finland,M,Finland,50,"Hadoop, Docker, SQL, TensorFlow, Tableau",Associate,5,Real Estate,2024-07-20,2024-09-19,1156,9.1,Quantum Computing Inc +AI01848,Robotics Engineer,25404,USD,25404,EN,FT,India,L,India,100,"Python, Azure, TensorFlow, GCP",Associate,0,Retail,2024-03-27,2024-04-13,650,8.1,Digital Transformation LLC +AI01849,Data Analyst,58557,JPY,6441270,EN,PT,Japan,M,Japan,100,"R, Docker, Computer Vision, Deep Learning, Hadoop",Associate,1,Government,2025-01-26,2025-02-21,1676,6.7,Predictive Systems +AI01850,AI Software Engineer,78957,EUR,67113,EN,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Java",Master,1,Telecommunications,2024-02-26,2024-04-12,540,8.2,Neural Networks Co +AI01851,NLP Engineer,22675,USD,22675,EN,FL,India,L,India,50,"GCP, R, Data Visualization",PhD,0,Transportation,2024-01-15,2024-03-27,2064,8.5,DataVision Ltd +AI01852,NLP Engineer,147152,USD,147152,SE,FT,Norway,S,Norway,0,"Scala, SQL, PyTorch, Computer Vision, Deep Learning",PhD,9,Finance,2024-10-11,2024-12-08,660,6.2,Cognitive Computing +AI01853,AI Architect,103466,EUR,87946,SE,FL,Austria,M,Austria,100,"Hadoop, Spark, PyTorch",Bachelor,9,Technology,2024-11-28,2024-12-31,1886,6.3,Machine Intelligence Group +AI01854,Machine Learning Researcher,78287,USD,78287,EN,FL,Ireland,M,Ireland,0,"Spark, AWS, Hadoop, Java",PhD,1,Real Estate,2025-02-21,2025-05-04,2397,9.4,Autonomous Tech +AI01855,AI Consultant,142221,EUR,120888,SE,CT,Germany,M,Germany,50,"Git, Kubernetes, Python, TensorFlow, Hadoop",Associate,9,Gaming,2024-07-21,2024-09-26,1266,9.3,Future Systems +AI01856,Machine Learning Engineer,82950,USD,82950,EN,FT,Norway,L,Germany,50,"Kubernetes, Data Visualization, SQL, Mathematics, GCP",Master,0,Gaming,2024-07-21,2024-08-24,800,6.1,Cognitive Computing +AI01857,AI Product Manager,124220,USD,124220,MI,CT,Ireland,L,Ireland,0,"Linux, Computer Vision, Tableau, Kubernetes",Associate,3,Government,2024-08-16,2024-10-11,2005,9.7,Cloud AI Solutions +AI01858,NLP Engineer,78087,CAD,97609,EN,FT,Canada,L,Belgium,50,"MLOps, R, Computer Vision",Bachelor,1,Technology,2024-02-09,2024-03-26,760,9.2,AI Innovations +AI01859,Machine Learning Researcher,50319,GBP,37739,EN,FT,United Kingdom,S,United Kingdom,50,"Deep Learning, MLOps, Java, Git",Bachelor,0,Government,2024-03-29,2024-05-17,2216,10,Smart Analytics +AI01860,Data Analyst,82880,EUR,70448,MI,PT,Netherlands,S,Turkey,0,"TensorFlow, Python, Spark, MLOps",Bachelor,3,Education,2024-05-31,2024-07-19,1846,7.1,Algorithmic Solutions +AI01861,AI Specialist,119491,USD,119491,MI,FT,Ireland,L,Ireland,50,"R, AWS, Spark, Linux, Computer Vision",Master,3,Automotive,2024-04-30,2024-06-27,1982,7.5,Future Systems +AI01862,AI Specialist,202791,USD,202791,SE,FT,United States,L,United States,0,"Kubernetes, Tableau, GCP",Bachelor,8,Technology,2025-02-27,2025-05-03,1627,5.7,DeepTech Ventures +AI01863,Autonomous Systems Engineer,203607,EUR,173066,EX,FL,France,M,Czech Republic,0,"Linux, Data Visualization, NLP",Bachelor,13,Automotive,2024-06-13,2024-08-25,615,8.8,AI Innovations +AI01864,ML Ops Engineer,76776,SGD,99809,EN,FT,Singapore,L,Singapore,0,"Computer Vision, R, Tableau, Linux",PhD,1,Gaming,2024-09-02,2024-10-02,2193,6.9,Neural Networks Co +AI01865,Data Analyst,66728,USD,66728,EN,FL,Sweden,S,Indonesia,100,"Scala, Kubernetes, Computer Vision, TensorFlow",PhD,1,Education,2024-08-17,2024-09-16,679,6.9,Autonomous Tech +AI01866,AI Software Engineer,135400,USD,135400,SE,FL,United States,S,Luxembourg,0,"Hadoop, Python, TensorFlow",Bachelor,5,Consulting,2024-11-09,2024-12-12,856,5.6,Cloud AI Solutions +AI01867,Research Scientist,123743,CAD,154679,SE,FT,Canada,S,Austria,50,"R, Java, Statistics, GCP, Git",Associate,7,Consulting,2024-07-21,2024-09-13,1360,5.3,Cloud AI Solutions +AI01868,Deep Learning Engineer,109631,USD,109631,MI,FL,Norway,S,Germany,50,"AWS, Computer Vision, Data Visualization, NLP",Master,3,Manufacturing,2025-04-05,2025-06-09,2205,6.4,Future Systems +AI01869,Principal Data Scientist,153283,USD,153283,SE,FL,Norway,L,Israel,100,"Python, NLP, Kubernetes, Mathematics",Associate,6,Automotive,2024-04-19,2024-06-02,2060,8.2,Algorithmic Solutions +AI01870,AI Consultant,96402,USD,96402,MI,CT,Norway,M,Norway,0,"Statistics, Scala, Tableau, Computer Vision",PhD,4,Healthcare,2024-07-15,2024-09-25,2089,9.6,Neural Networks Co +AI01871,Research Scientist,158028,USD,158028,SE,FT,Denmark,L,Denmark,100,"Hadoop, Python, TensorFlow",PhD,9,Retail,2024-02-25,2024-04-03,1515,7.3,Predictive Systems +AI01872,NLP Engineer,45538,USD,45538,SE,FL,India,S,India,50,"Git, TensorFlow, Java",Bachelor,8,Gaming,2024-02-06,2024-02-26,1204,9.4,TechCorp Inc +AI01873,AI Architect,115560,USD,115560,MI,FT,Finland,L,Finland,100,"Data Visualization, Linux, AWS, MLOps, Kubernetes",Master,3,Government,2024-03-24,2024-05-02,1753,9,TechCorp Inc +AI01874,AI Consultant,136534,EUR,116054,SE,PT,Germany,M,Germany,100,"Python, TensorFlow, Scala, Java",Master,6,Education,2024-12-19,2025-02-05,1155,7.6,TechCorp Inc +AI01875,AI Research Scientist,211480,USD,211480,EX,CT,Ireland,S,Philippines,50,"Git, TensorFlow, Data Visualization, Computer Vision, Kubernetes",Master,16,Education,2024-05-16,2024-07-17,847,6.5,Cognitive Computing +AI01876,Deep Learning Engineer,112194,USD,112194,SE,FL,Ireland,S,Ireland,50,"Git, Docker, Kubernetes, GCP, Tableau",Bachelor,7,Government,2024-01-27,2024-03-13,1418,8.8,Cloud AI Solutions +AI01877,Autonomous Systems Engineer,150077,USD,150077,EX,FT,Sweden,M,Italy,100,"R, GCP, Linux, Data Visualization, Azure",Bachelor,14,Manufacturing,2024-01-18,2024-03-02,1325,8.6,AI Innovations +AI01878,AI Consultant,125806,USD,125806,SE,CT,Sweden,S,Sweden,50,"Mathematics, Kubernetes, Computer Vision, R",Master,6,Technology,2024-01-01,2024-01-30,1313,5.8,Future Systems +AI01879,Head of AI,66045,USD,66045,EN,CT,Israel,S,Israel,0,"Java, Docker, Computer Vision, Linux, PyTorch",Bachelor,0,Energy,2024-02-17,2024-03-11,1759,9.8,Digital Transformation LLC +AI01880,AI Research Scientist,174743,USD,174743,SE,FT,Norway,S,Poland,0,"SQL, Python, AWS, Java",Bachelor,8,Automotive,2024-09-16,2024-10-31,2102,7.6,AI Innovations +AI01881,AI Product Manager,96725,EUR,82216,EN,CT,Netherlands,L,Romania,0,"Scala, Hadoop, Data Visualization, Azure",Bachelor,1,Consulting,2024-03-22,2024-04-24,2067,6.5,Smart Analytics +AI01882,Data Analyst,61494,USD,61494,EX,PT,India,S,India,50,"Scala, SQL, PyTorch, Statistics",Master,15,Gaming,2024-05-31,2024-06-28,700,9.2,Algorithmic Solutions +AI01883,Autonomous Systems Engineer,51504,CAD,64380,EN,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, Kubernetes",Bachelor,0,Finance,2024-02-16,2024-04-20,725,10,Future Systems +AI01884,Research Scientist,84676,USD,84676,EN,FL,Norway,L,Norway,50,"Hadoop, Git, Data Visualization, PyTorch",Bachelor,1,Automotive,2024-02-13,2024-03-08,2299,5.6,Neural Networks Co +AI01885,Data Engineer,116829,USD,116829,MI,FT,United States,S,United States,100,"GCP, MLOps, AWS",Bachelor,2,Manufacturing,2024-02-02,2024-02-23,2179,5.6,Algorithmic Solutions +AI01886,Machine Learning Researcher,253322,USD,253322,EX,FT,Norway,M,Norway,0,"PyTorch, SQL, MLOps, TensorFlow, Computer Vision",Associate,17,Consulting,2025-01-02,2025-01-29,928,6.3,AI Innovations +AI01887,Machine Learning Researcher,307829,CHF,277046,EX,CT,Switzerland,L,Switzerland,50,"Python, R, Computer Vision, Hadoop, NLP",Master,18,Healthcare,2024-07-09,2024-07-25,2073,9.3,Digital Transformation LLC +AI01888,Head of AI,74701,USD,74701,EN,PT,United States,L,United States,50,"SQL, Git, Java, Mathematics",Master,0,Telecommunications,2024-12-25,2025-02-10,2396,6.5,Cloud AI Solutions +AI01889,Machine Learning Researcher,77814,CAD,97268,MI,PT,Canada,S,Canada,100,"Python, MLOps, Git, Java",PhD,3,Technology,2024-03-23,2024-04-28,2111,5.3,Predictive Systems +AI01890,Head of AI,153857,USD,153857,SE,FL,Ireland,L,Ireland,50,"NLP, Linux, Scala",Master,5,Finance,2024-11-14,2024-12-18,2443,8.8,Autonomous Tech +AI01891,Head of AI,53752,EUR,45689,EN,FL,Netherlands,S,Netherlands,50,"R, Mathematics, SQL",PhD,0,Government,2024-02-26,2024-05-06,1201,5.2,Advanced Robotics +AI01892,Head of AI,67828,USD,67828,EN,PT,Denmark,S,Denmark,0,"PyTorch, Scala, TensorFlow",PhD,0,Government,2025-04-23,2025-07-01,2053,9,Cognitive Computing +AI01893,Machine Learning Engineer,98247,USD,98247,MI,PT,Ireland,S,Vietnam,50,"SQL, TensorFlow, Python, Computer Vision",Bachelor,2,Telecommunications,2025-03-30,2025-04-19,993,7,Digital Transformation LLC +AI01894,AI Product Manager,171970,USD,171970,SE,FL,United States,M,United States,100,"NLP, Linux, MLOps, TensorFlow, Python",PhD,5,Finance,2024-05-17,2024-07-16,698,9.9,Autonomous Tech +AI01895,Machine Learning Engineer,143515,JPY,15786650,SE,FL,Japan,S,Japan,50,"PyTorch, Linux, Tableau, Kubernetes, Spark",Bachelor,9,Consulting,2024-04-24,2024-07-02,2340,7.8,DeepTech Ventures +AI01896,Head of AI,39901,USD,39901,SE,CT,India,S,India,50,"Spark, AWS, Python, Deep Learning",Bachelor,6,Retail,2024-07-11,2024-09-12,685,6.5,Smart Analytics +AI01897,Autonomous Systems Engineer,117566,JPY,12932260,SE,FT,Japan,S,Ukraine,50,"Kubernetes, Python, NLP, Deep Learning, Mathematics",Master,8,Transportation,2025-03-31,2025-05-30,2123,5.2,Smart Analytics +AI01898,Head of AI,113872,CHF,102485,EN,FL,Switzerland,M,Switzerland,50,"SQL, AWS, Statistics, PyTorch",PhD,1,Retail,2024-12-17,2025-01-14,2123,8.5,AI Innovations +AI01899,Machine Learning Engineer,68525,USD,68525,EN,CT,Finland,L,Finland,100,"Mathematics, Kubernetes, R",Master,1,Telecommunications,2024-09-01,2024-09-30,1605,7.2,Advanced Robotics +AI01900,Data Analyst,143796,GBP,107847,SE,FT,United Kingdom,L,Belgium,50,"R, Scala, PyTorch, Git, Python",Master,7,Manufacturing,2024-08-19,2024-10-08,1811,5.6,Predictive Systems +AI01901,NLP Engineer,267822,GBP,200867,EX,CT,United Kingdom,M,Canada,100,"Tableau, Docker, AWS, NLP",Associate,16,Automotive,2024-08-19,2024-09-30,997,9.7,Digital Transformation LLC +AI01902,AI Research Scientist,92727,USD,92727,SE,FL,South Korea,M,Denmark,100,"MLOps, Data Visualization, Java",PhD,8,Retail,2024-01-05,2024-02-07,2179,8.6,Cloud AI Solutions +AI01903,AI Research Scientist,87977,EUR,74780,MI,FT,France,L,France,0,"Hadoop, Linux, Java",Master,3,Real Estate,2024-04-14,2024-05-07,1923,10,Future Systems +AI01904,Autonomous Systems Engineer,71922,EUR,61134,MI,PT,Germany,S,Germany,0,"AWS, Spark, Data Visualization, Git, Scala",PhD,3,Manufacturing,2025-03-07,2025-03-20,1861,9.3,Cognitive Computing +AI01905,Principal Data Scientist,31507,USD,31507,EN,FT,China,L,China,100,"Tableau, Linux, Python, Statistics, R",PhD,0,Gaming,2025-01-26,2025-04-02,1263,8.9,TechCorp Inc +AI01906,Principal Data Scientist,30492,USD,30492,EN,FL,China,M,China,100,"SQL, PyTorch, Tableau, Statistics",PhD,0,Healthcare,2024-10-04,2024-11-19,748,5.1,Advanced Robotics +AI01907,AI Research Scientist,116151,EUR,98728,MI,PT,Netherlands,M,Netherlands,50,"Azure, Linux, Computer Vision, Tableau",Master,3,Automotive,2025-04-16,2025-05-12,1794,9.6,Quantum Computing Inc +AI01908,Machine Learning Researcher,71966,CAD,89958,MI,FL,Canada,M,Canada,50,"Tableau, Python, TensorFlow, Computer Vision, Azure",Associate,2,Finance,2024-03-04,2024-05-05,779,6.1,Autonomous Tech +AI01909,Computer Vision Engineer,163401,GBP,122551,SE,FT,United Kingdom,L,United Kingdom,50,"Python, SQL, Linux",Master,6,Automotive,2024-09-18,2024-11-11,744,6.7,Quantum Computing Inc +AI01910,Robotics Engineer,61330,EUR,52131,EN,CT,France,M,Denmark,0,"Hadoop, Scala, Linux",PhD,1,Consulting,2024-08-09,2024-10-03,1120,9.6,TechCorp Inc +AI01911,Data Engineer,214921,USD,214921,EX,PT,Ireland,S,Ireland,0,"R, MLOps, SQL, Computer Vision, Docker",PhD,16,Media,2025-02-21,2025-04-17,793,8,Algorithmic Solutions +AI01912,AI Product Manager,76932,EUR,65392,EN,FL,Germany,M,Germany,100,"Tableau, TensorFlow, Docker, Spark, SQL",PhD,1,Government,2024-04-29,2024-06-29,614,6.6,Future Systems +AI01913,Research Scientist,169028,CAD,211285,EX,FT,Canada,S,Canada,0,"Java, Deep Learning, Computer Vision, Hadoop",Master,11,Gaming,2024-07-17,2024-09-24,1655,6.5,Smart Analytics +AI01914,Autonomous Systems Engineer,118035,AUD,159347,SE,PT,Australia,L,Australia,0,"Mathematics, Linux, Kubernetes, Python",Associate,9,Automotive,2024-04-18,2024-06-29,1343,8.9,DeepTech Ventures +AI01915,AI Product Manager,113938,USD,113938,MI,PT,Denmark,M,Denmark,100,"Data Visualization, GCP, TensorFlow",Associate,3,Finance,2024-12-02,2025-01-19,863,5.5,Smart Analytics +AI01916,Autonomous Systems Engineer,109615,CAD,137019,SE,FL,Canada,S,Canada,100,"Hadoop, Kubernetes, Scala, Statistics, GCP",PhD,7,Media,2025-03-26,2025-04-22,2420,9.6,Smart Analytics +AI01917,Data Analyst,27659,USD,27659,MI,PT,India,M,India,100,"NLP, Data Visualization, MLOps, Hadoop",Master,2,Healthcare,2024-10-03,2024-10-26,2282,6.1,Neural Networks Co +AI01918,AI Product Manager,67740,USD,67740,EN,PT,United States,S,Austria,100,"Python, Scala, Linux",PhD,0,Real Estate,2025-03-14,2025-05-16,1682,9.8,DeepTech Ventures +AI01919,Machine Learning Researcher,174654,USD,174654,SE,CT,Sweden,L,South Korea,50,"Scala, R, Hadoop, AWS, Python",Master,6,Energy,2024-02-21,2024-03-26,502,5.4,DeepTech Ventures +AI01920,Data Analyst,232730,CAD,290913,EX,FT,Canada,M,India,50,"Hadoop, Kubernetes, Data Visualization, Mathematics, Tableau",PhD,15,Technology,2024-03-11,2024-05-19,1522,5.4,Cognitive Computing +AI01921,Data Analyst,63711,EUR,54154,MI,PT,Austria,S,Austria,50,"Computer Vision, Data Visualization, Python, NLP, AWS",PhD,3,Energy,2025-02-02,2025-02-22,1411,7.5,DataVision Ltd +AI01922,Principal Data Scientist,116990,USD,116990,SE,CT,South Korea,M,South Korea,100,"Computer Vision, R, Scala, GCP, SQL",Associate,8,Media,2024-01-08,2024-03-05,731,6.6,Autonomous Tech +AI01923,AI Architect,105481,USD,105481,MI,CT,Israel,L,Israel,0,"PyTorch, SQL, Computer Vision, NLP, TensorFlow",Master,3,Manufacturing,2024-03-15,2024-04-23,2371,5.2,DeepTech Ventures +AI01924,Data Analyst,161259,EUR,137070,EX,CT,Netherlands,M,Netherlands,0,"Spark, SQL, MLOps",Associate,11,Education,2024-10-15,2024-12-05,1598,9.3,Advanced Robotics +AI01925,Research Scientist,121460,USD,121460,SE,FT,Ireland,L,Ireland,50,"Java, AWS, Mathematics",Bachelor,8,Healthcare,2024-08-28,2024-10-21,848,6.3,Digital Transformation LLC +AI01926,Data Engineer,70644,USD,70644,EN,FL,Sweden,M,Sweden,100,"Python, TensorFlow, Deep Learning",Master,1,Consulting,2025-03-14,2025-04-20,2323,7.4,Future Systems +AI01927,NLP Engineer,109579,GBP,82184,SE,CT,United Kingdom,M,United Kingdom,100,"Python, Docker, Mathematics, Linux, Hadoop",Bachelor,7,Real Estate,2024-10-12,2024-12-04,2482,8.3,Cognitive Computing +AI01928,Head of AI,90547,CAD,113184,MI,CT,Canada,S,United Kingdom,100,"Kubernetes, Docker, Tableau, Azure",PhD,4,Consulting,2024-10-26,2024-12-15,2228,6,Predictive Systems +AI01929,Machine Learning Researcher,218360,USD,218360,EX,PT,South Korea,L,South Korea,0,"GCP, PyTorch, Linux, Azure",Bachelor,18,Healthcare,2024-03-27,2024-04-11,960,6.4,Predictive Systems +AI01930,Robotics Engineer,140380,EUR,119323,SE,PT,Austria,M,Austria,100,"Kubernetes, Scala, R, Computer Vision",PhD,6,Media,2025-04-02,2025-05-10,2084,9.7,Neural Networks Co +AI01931,Computer Vision Engineer,119973,USD,119973,SE,FT,South Korea,L,South Korea,50,"Azure, Python, TensorFlow",Bachelor,7,Transportation,2024-02-18,2024-04-20,2141,6.7,TechCorp Inc +AI01932,NLP Engineer,102535,USD,102535,MI,CT,United States,S,United States,100,"Scala, Python, Linux, Tableau, Computer Vision",Bachelor,4,Energy,2024-01-04,2024-03-09,2029,7.7,DeepTech Ventures +AI01933,Machine Learning Researcher,106806,AUD,144188,MI,FT,Australia,L,Australia,50,"SQL, Java, Docker",Bachelor,2,Manufacturing,2025-03-02,2025-04-09,1517,8.7,Predictive Systems +AI01934,Deep Learning Engineer,54346,CAD,67933,EN,CT,Canada,S,Canada,100,"MLOps, TensorFlow, SQL, Scala",Associate,1,Media,2025-02-27,2025-03-22,1549,8.5,Future Systems +AI01935,AI Consultant,70194,USD,70194,SE,CT,China,L,China,0,"Linux, PyTorch, TensorFlow, AWS",PhD,6,Automotive,2024-07-08,2024-08-24,1557,6.3,Cloud AI Solutions +AI01936,Computer Vision Engineer,94729,EUR,80520,MI,FL,Netherlands,S,Argentina,100,"Data Visualization, Spark, Mathematics",PhD,3,Transportation,2025-03-21,2025-04-18,770,6.5,Neural Networks Co +AI01937,NLP Engineer,46286,USD,46286,EN,FT,Finland,S,Finland,100,"Python, Git, Kubernetes",Master,0,Transportation,2024-09-18,2024-11-20,2261,9.6,Algorithmic Solutions +AI01938,Machine Learning Engineer,166362,USD,166362,SE,CT,Norway,L,Denmark,50,"Data Visualization, PyTorch, Hadoop, Linux",Associate,9,Technology,2025-03-14,2025-04-03,884,6.9,Smart Analytics +AI01939,AI Software Engineer,185959,GBP,139469,EX,CT,United Kingdom,S,United Kingdom,100,"AWS, SQL, Data Visualization, Computer Vision",Master,12,Manufacturing,2024-04-21,2024-06-15,2359,6.1,Advanced Robotics +AI01940,AI Software Engineer,124415,USD,124415,SE,PT,South Korea,M,South Korea,50,"SQL, Spark, R",Associate,9,Media,2024-04-15,2024-05-30,2248,6.3,Advanced Robotics +AI01941,AI Architect,69802,USD,69802,EN,CT,Ireland,S,Netherlands,50,"Linux, Kubernetes, Python, TensorFlow, Data Visualization",Master,0,Transportation,2025-04-10,2025-05-24,1731,7.8,Machine Intelligence Group +AI01942,NLP Engineer,220589,USD,220589,EX,FL,United States,S,United States,50,"Scala, Spark, Linux, TensorFlow",Master,18,Telecommunications,2024-02-11,2024-03-30,1595,5.7,Autonomous Tech +AI01943,AI Specialist,80123,AUD,108166,MI,PT,Australia,S,Australia,0,"TensorFlow, Kubernetes, NLP, Linux",PhD,4,Manufacturing,2025-01-17,2025-02-27,1255,9.2,AI Innovations +AI01944,Data Scientist,116909,USD,116909,MI,FL,United States,S,Brazil,100,"MLOps, Linux, SQL, NLP",Bachelor,2,Telecommunications,2024-07-28,2024-10-08,2205,9.1,DataVision Ltd +AI01945,Machine Learning Engineer,43728,EUR,37169,EN,PT,Austria,S,Austria,0,"Java, Python, Azure, NLP",Bachelor,1,Government,2024-10-28,2025-01-06,2246,5.4,DataVision Ltd +AI01946,Autonomous Systems Engineer,64573,EUR,54887,EN,FT,Austria,L,Austria,50,"AWS, Java, NLP",PhD,0,Finance,2025-04-26,2025-06-30,2310,9,Future Systems +AI01947,NLP Engineer,117914,CHF,106123,MI,FL,Switzerland,S,Switzerland,100,"Hadoop, NLP, R",Bachelor,2,Transportation,2024-07-29,2024-10-10,1827,6.1,Autonomous Tech +AI01948,Autonomous Systems Engineer,152384,USD,152384,EX,CT,South Korea,L,Ukraine,100,"Kubernetes, R, Tableau",Bachelor,16,Real Estate,2025-01-19,2025-02-16,1687,6.3,Digital Transformation LLC +AI01949,AI Software Engineer,68312,EUR,58065,MI,FL,Austria,M,Austria,100,"Python, Deep Learning, Computer Vision, Spark, TensorFlow",PhD,3,Telecommunications,2025-03-31,2025-04-19,509,5.2,DataVision Ltd +AI01950,AI Specialist,85129,CAD,106411,MI,PT,Canada,M,Canada,100,"SQL, Kubernetes, Git, Statistics, Docker",Master,4,Real Estate,2024-01-01,2024-01-17,1017,8.8,Advanced Robotics +AI01951,AI Software Engineer,146496,CHF,131846,SE,CT,Switzerland,S,Switzerland,0,"R, Hadoop, Mathematics, Tableau",Bachelor,7,Consulting,2025-03-06,2025-04-12,1644,6.6,Autonomous Tech +AI01952,Research Scientist,120458,USD,120458,MI,FT,Norway,M,Norway,0,"SQL, PyTorch, AWS, Linux, Computer Vision",Master,4,Retail,2025-02-28,2025-03-31,650,5.8,AI Innovations +AI01953,AI Architect,306393,USD,306393,EX,PT,Denmark,M,United Kingdom,100,"Python, Scala, Computer Vision, Mathematics, TensorFlow",Master,12,Retail,2024-04-29,2024-05-27,2084,6.5,Quantum Computing Inc +AI01954,Data Analyst,119182,USD,119182,SE,FT,Ireland,M,Ireland,0,"Mathematics, Azure, Kubernetes, Git",Associate,6,Gaming,2024-08-02,2024-10-10,1648,5.6,Neural Networks Co +AI01955,AI Product Manager,190595,CHF,171536,EX,PT,Switzerland,S,Switzerland,100,"R, PyTorch, GCP, Tableau, Java",PhD,18,Automotive,2024-10-12,2024-11-06,668,5.2,Future Systems +AI01956,AI Product Manager,133627,AUD,180396,SE,PT,Australia,M,Indonesia,100,"Data Visualization, PyTorch, Spark, GCP",PhD,9,Transportation,2024-08-04,2024-10-13,1422,7.2,AI Innovations +AI01957,AI Specialist,102896,USD,102896,MI,FL,Norway,S,Israel,100,"TensorFlow, Azure, MLOps",Bachelor,2,Energy,2024-04-21,2024-05-05,1871,6.3,Machine Intelligence Group +AI01958,AI Consultant,53828,EUR,45754,EN,CT,France,S,France,100,"Hadoop, TensorFlow, Spark, Computer Vision, SQL",PhD,0,Technology,2024-03-17,2024-04-07,1829,6.3,DataVision Ltd +AI01959,Robotics Engineer,229532,EUR,195102,EX,FT,Netherlands,L,Austria,100,"PyTorch, Tableau, Linux, Python",Master,19,Finance,2025-01-02,2025-03-15,548,7.8,Cognitive Computing +AI01960,Machine Learning Researcher,50929,USD,50929,SE,FL,India,L,India,100,"Spark, Kubernetes, Azure, Deep Learning",Associate,7,Healthcare,2024-12-31,2025-01-30,1837,7.8,Machine Intelligence Group +AI01961,Autonomous Systems Engineer,119585,EUR,101647,SE,PT,Germany,S,Germany,50,"R, Kubernetes, Git",Master,5,Media,2025-02-27,2025-04-28,1402,6,Future Systems +AI01962,Deep Learning Engineer,94488,USD,94488,EN,FT,Denmark,M,New Zealand,0,"Linux, TensorFlow, SQL",Associate,0,Manufacturing,2025-03-24,2025-04-20,2344,7.6,Autonomous Tech +AI01963,Data Analyst,62316,EUR,52969,MI,PT,Austria,S,Austria,50,"Statistics, Python, Deep Learning, Git, TensorFlow",PhD,2,Manufacturing,2024-03-24,2024-04-07,602,6.4,Quantum Computing Inc +AI01964,ML Ops Engineer,108014,USD,108014,EN,PT,Denmark,L,Denmark,50,"MLOps, Spark, SQL, NLP",Bachelor,1,Real Estate,2024-05-07,2024-06-02,1694,8.3,Machine Intelligence Group +AI01965,Deep Learning Engineer,137340,EUR,116739,SE,CT,Netherlands,M,Netherlands,50,"Git, MLOps, Java",Associate,5,Automotive,2024-07-31,2024-09-16,776,9.1,DeepTech Ventures +AI01966,AI Consultant,51851,AUD,69999,EN,FL,Australia,M,Australia,50,"MLOps, Scala, Kubernetes, Python, TensorFlow",PhD,0,Education,2024-05-17,2024-07-20,2465,6.1,TechCorp Inc +AI01967,Machine Learning Engineer,158813,USD,158813,SE,PT,Norway,S,Norway,100,"Tableau, Git, Azure, Scala, GCP",Associate,7,Telecommunications,2024-05-17,2024-06-27,2495,6.8,TechCorp Inc +AI01968,NLP Engineer,272366,USD,272366,EX,CT,Norway,M,Norway,100,"Mathematics, TensorFlow, Tableau, Linux, R",Bachelor,11,Consulting,2025-02-25,2025-03-15,1869,5.8,Cloud AI Solutions +AI01969,AI Research Scientist,66656,USD,66656,EN,PT,Finland,S,France,0,"Kubernetes, PyTorch, Java, AWS, Deep Learning",Bachelor,0,Media,2025-02-16,2025-04-20,559,9.2,Neural Networks Co +AI01970,Computer Vision Engineer,97650,EUR,83003,MI,CT,Austria,M,Austria,100,"MLOps, Data Visualization, TensorFlow, Tableau, SQL",PhD,4,Healthcare,2024-08-31,2024-09-14,1105,5.2,Future Systems +AI01971,Data Scientist,198520,USD,198520,EX,FT,Sweden,L,Sweden,50,"Hadoop, PyTorch, Deep Learning, TensorFlow",Bachelor,15,Retail,2025-02-24,2025-03-24,1825,9.4,Machine Intelligence Group +AI01972,Computer Vision Engineer,113590,CHF,102231,MI,FL,Switzerland,M,France,0,"Git, Computer Vision, PyTorch",Bachelor,4,Gaming,2025-01-17,2025-03-20,2437,5.8,AI Innovations +AI01973,Data Scientist,153445,EUR,130428,EX,CT,France,S,France,0,"Python, Data Visualization, TensorFlow, Deep Learning",Master,10,Manufacturing,2025-03-25,2025-04-12,2026,7,Digital Transformation LLC +AI01974,Robotics Engineer,97324,SGD,126521,EN,FL,Singapore,L,Singapore,50,"Java, Tableau, Kubernetes",Bachelor,0,Manufacturing,2024-07-27,2024-09-23,1832,8.8,Algorithmic Solutions +AI01975,Research Scientist,44666,USD,44666,EN,PT,South Korea,S,South Korea,50,"Kubernetes, Python, AWS",Associate,0,Education,2024-11-06,2024-11-30,2233,6.3,Machine Intelligence Group +AI01976,Deep Learning Engineer,296548,USD,296548,EX,PT,United States,M,United States,100,"Tableau, Azure, Java",Bachelor,18,Technology,2024-06-15,2024-08-13,768,9.8,AI Innovations +AI01977,AI Architect,89790,EUR,76322,EN,CT,Netherlands,L,Netherlands,100,"SQL, Git, MLOps",PhD,0,Government,2024-06-11,2024-08-04,1109,9.6,Cognitive Computing +AI01978,ML Ops Engineer,146337,SGD,190238,SE,PT,Singapore,M,Portugal,0,"R, Data Visualization, Java, GCP, Python",Bachelor,9,Consulting,2024-07-09,2024-07-23,1346,5.6,Neural Networks Co +AI01979,Machine Learning Engineer,99555,CHF,89600,MI,PT,Switzerland,S,South Africa,100,"NLP, Docker, PyTorch",Master,4,Energy,2024-02-13,2024-03-05,1281,8.8,Future Systems +AI01980,NLP Engineer,153992,JPY,16939120,EX,FT,Japan,M,Japan,100,"Linux, GCP, MLOps, Data Visualization, Git",PhD,10,Media,2024-07-05,2024-07-27,1340,8.2,Algorithmic Solutions +AI01981,Deep Learning Engineer,103750,EUR,88188,MI,FT,Netherlands,S,Netherlands,100,"Python, Statistics, Mathematics, TensorFlow, Java",Bachelor,4,Government,2025-02-25,2025-04-05,1399,9.5,DataVision Ltd +AI01982,Principal Data Scientist,88704,USD,88704,MI,PT,Ireland,L,Ghana,0,"Linux, Hadoop, R, Mathematics, Kubernetes",Master,2,Real Estate,2024-01-31,2024-03-25,1929,5.3,Cloud AI Solutions +AI01983,Data Analyst,118310,JPY,13014100,MI,PT,Japan,L,Japan,100,"TensorFlow, Data Visualization, Statistics",Master,3,Telecommunications,2024-06-10,2024-08-06,1801,7.4,Smart Analytics +AI01984,Deep Learning Engineer,171397,EUR,145687,EX,FT,Germany,S,Germany,100,"Azure, Linux, Deep Learning",Master,17,Healthcare,2025-03-22,2025-05-23,1983,5.5,Future Systems +AI01985,AI Research Scientist,80403,CAD,100504,MI,CT,Canada,M,Canada,50,"Scala, Java, Deep Learning",Associate,3,Automotive,2025-02-09,2025-03-12,681,9.5,Algorithmic Solutions +AI01986,Robotics Engineer,118077,USD,118077,SE,FL,United States,S,Norway,50,"Statistics, Azure, TensorFlow",Master,6,Manufacturing,2024-05-24,2024-08-01,1654,5.7,TechCorp Inc +AI01987,Head of AI,103534,USD,103534,SE,FL,Sweden,M,Sweden,100,"SQL, Tableau, PyTorch",Associate,9,Technology,2024-12-04,2025-01-26,2035,7.6,Predictive Systems +AI01988,Computer Vision Engineer,101905,EUR,86619,MI,FT,Austria,M,Switzerland,100,"TensorFlow, Python, GCP",Associate,2,Consulting,2024-04-11,2024-05-22,1083,6.1,AI Innovations +AI01989,AI Research Scientist,182075,USD,182075,EX,CT,South Korea,L,Estonia,0,"Kubernetes, Mathematics, Tableau",PhD,18,Finance,2024-03-12,2024-04-19,979,7.8,DeepTech Ventures +AI01990,AI Research Scientist,230990,SGD,300287,EX,FL,Singapore,M,Singapore,0,"SQL, PyTorch, Computer Vision",Master,16,Government,2024-03-13,2024-04-04,574,8.7,Digital Transformation LLC +AI01991,Computer Vision Engineer,215816,EUR,183444,EX,PT,Germany,S,Germany,100,"Mathematics, PyTorch, NLP",PhD,19,Retail,2024-01-15,2024-02-23,2001,8.2,Cognitive Computing +AI01992,Research Scientist,83946,EUR,71354,EN,FL,Germany,L,Germany,50,"R, Spark, Statistics",PhD,1,Energy,2025-04-30,2025-05-30,726,5.2,DeepTech Ventures +AI01993,ML Ops Engineer,96785,USD,96785,MI,PT,Ireland,S,United Kingdom,0,"TensorFlow, R, SQL, Data Visualization, AWS",Bachelor,2,Telecommunications,2024-03-29,2024-05-27,712,5.5,TechCorp Inc +AI01994,Data Scientist,82495,EUR,70121,MI,PT,Netherlands,M,Malaysia,100,"Linux, Git, MLOps",PhD,3,Gaming,2025-03-10,2025-04-05,856,5.8,Neural Networks Co +AI01995,Machine Learning Engineer,131731,GBP,98798,MI,CT,United Kingdom,L,United Kingdom,0,"TensorFlow, AWS, Linux",PhD,3,Technology,2024-11-08,2024-12-31,814,8.2,Digital Transformation LLC +AI01996,Head of AI,56604,USD,56604,EN,CT,Israel,M,Israel,100,"Kubernetes, PyTorch, Statistics, NLP, TensorFlow",PhD,1,Retail,2024-11-17,2025-01-12,1845,7.4,Cognitive Computing +AI01997,Data Analyst,63776,USD,63776,EN,FL,Ireland,S,Ireland,100,"Spark, Mathematics, Java, Statistics, Python",Bachelor,1,Retail,2024-12-04,2025-01-15,2083,7.1,Digital Transformation LLC +AI01998,AI Architect,68800,CAD,86000,MI,CT,Canada,M,Canada,100,"PyTorch, R, Tableau, Deep Learning",Associate,4,Government,2024-08-15,2024-08-29,868,6.4,Smart Analytics +AI01999,AI Architect,45902,USD,45902,MI,CT,China,S,China,100,"SQL, Scala, Tableau, R",Associate,3,Transportation,2024-04-10,2024-06-17,2292,9,Autonomous Tech +AI02000,Data Scientist,87974,SGD,114366,MI,CT,Singapore,S,Singapore,100,"Mathematics, R, TensorFlow, Hadoop",PhD,4,Retail,2024-11-20,2025-01-31,1465,6.4,Quantum Computing Inc +AI02001,AI Architect,141156,USD,141156,SE,CT,Sweden,M,Sweden,100,"Azure, R, Deep Learning, Scala, Java",PhD,8,Manufacturing,2024-09-19,2024-10-03,928,6.4,Machine Intelligence Group +AI02002,Autonomous Systems Engineer,72809,CHF,65528,EN,CT,Switzerland,M,Switzerland,100,"Linux, Hadoop, Deep Learning, PyTorch, Computer Vision",PhD,1,Telecommunications,2024-05-09,2024-06-18,924,9,Advanced Robotics +AI02003,Autonomous Systems Engineer,74905,CHF,67415,EN,PT,Switzerland,M,South Korea,100,"Statistics, SQL, PyTorch, Deep Learning, Azure",Bachelor,1,Healthcare,2024-12-17,2025-02-06,1485,7.6,Neural Networks Co +AI02004,Deep Learning Engineer,83543,CAD,104429,MI,FL,Canada,L,Portugal,50,"Data Visualization, SQL, MLOps, PyTorch",PhD,4,Transportation,2024-09-28,2024-11-16,1281,5.5,AI Innovations +AI02005,ML Ops Engineer,74348,EUR,63196,EN,FL,France,L,France,0,"Kubernetes, Deep Learning, SQL, Python, NLP",PhD,0,Gaming,2024-02-12,2024-03-05,1746,8.1,DeepTech Ventures +AI02006,AI Product Manager,221177,USD,221177,EX,PT,Israel,M,Russia,50,"Python, Git, Data Visualization, Mathematics, GCP",Associate,10,Manufacturing,2024-08-12,2024-09-04,1529,9,DeepTech Ventures +AI02007,Machine Learning Engineer,188560,USD,188560,EX,FT,Israel,S,Israel,100,"Python, Kubernetes, NLP, Linux",PhD,14,Finance,2024-07-20,2024-08-06,1635,6.9,Cloud AI Solutions +AI02008,Principal Data Scientist,63698,JPY,7006780,EN,FL,Japan,M,Japan,0,"Computer Vision, Java, R",PhD,0,Media,2024-12-28,2025-03-02,1197,5.2,Neural Networks Co +AI02009,AI Architect,80238,USD,80238,EN,CT,Norway,L,Norway,50,"MLOps, Docker, GCP, Scala, PyTorch",Bachelor,0,Manufacturing,2024-12-29,2025-02-27,2410,5.4,Quantum Computing Inc +AI02010,Autonomous Systems Engineer,161051,EUR,136893,EX,PT,Austria,L,Austria,50,"Linux, Python, Scala",Bachelor,15,Education,2024-12-18,2025-01-22,1314,5.2,Smart Analytics +AI02011,NLP Engineer,130144,EUR,110622,SE,FT,Germany,S,Argentina,0,"GCP, PyTorch, TensorFlow, Python, Data Visualization",Bachelor,8,Finance,2024-02-04,2024-02-27,2268,5.5,Autonomous Tech +AI02012,AI Research Scientist,50319,USD,50319,EN,PT,Israel,S,Israel,0,"PyTorch, Java, Python, Mathematics, SQL",Bachelor,1,Media,2024-05-12,2024-05-30,782,7.7,DeepTech Ventures +AI02013,Machine Learning Researcher,256545,USD,256545,EX,CT,Sweden,L,Sweden,100,"PyTorch, SQL, Computer Vision, Spark, Azure",Bachelor,18,Healthcare,2025-02-02,2025-02-20,2493,6.9,Autonomous Tech +AI02014,AI Research Scientist,138961,USD,138961,SE,FT,South Korea,L,South Korea,0,"TensorFlow, Docker, SQL",Associate,6,Government,2024-04-11,2024-06-13,1018,8.6,TechCorp Inc +AI02015,Machine Learning Engineer,60037,EUR,51031,EN,CT,Germany,L,United Kingdom,0,"Mathematics, Scala, Data Visualization",Bachelor,0,Education,2024-07-25,2024-08-31,2188,6.3,AI Innovations +AI02016,AI Software Engineer,102110,USD,102110,MI,PT,Norway,M,Norway,0,"Git, Python, Java",Master,3,Retail,2024-11-17,2025-01-17,1311,8.1,AI Innovations +AI02017,Research Scientist,159317,EUR,135419,SE,FL,Germany,L,Germany,50,"Java, TensorFlow, PyTorch, Azure, GCP",PhD,9,Automotive,2025-02-25,2025-03-16,2179,5.8,Machine Intelligence Group +AI02018,Data Analyst,113026,EUR,96072,SE,PT,Netherlands,S,Netherlands,0,"R, GCP, Kubernetes, Spark, Linux",Bachelor,6,Technology,2024-12-19,2025-03-01,1999,9.2,Machine Intelligence Group +AI02019,Data Engineer,175703,USD,175703,SE,FL,Denmark,S,Denmark,50,"Deep Learning, Azure, Hadoop, SQL, Git",Bachelor,8,Telecommunications,2024-03-07,2024-04-19,1080,7,Autonomous Tech +AI02020,Deep Learning Engineer,79945,USD,79945,MI,CT,United States,S,Luxembourg,0,"Git, Statistics, Azure",Master,2,Retail,2024-02-21,2024-04-19,1292,7.3,Machine Intelligence Group +AI02021,Data Analyst,78895,AUD,106508,EN,FL,Australia,L,Australia,0,"MLOps, Kubernetes, TensorFlow, Python",PhD,1,Gaming,2024-03-03,2024-04-22,655,8.2,Neural Networks Co +AI02022,Head of AI,65331,USD,65331,EN,FT,Ireland,S,Ireland,50,"Azure, Kubernetes, AWS, MLOps, TensorFlow",PhD,0,Consulting,2024-06-29,2024-07-23,629,5.2,Advanced Robotics +AI02023,AI Software Engineer,88502,USD,88502,EN,PT,Denmark,L,Denmark,100,"Linux, Git, Deep Learning, SQL, Azure",PhD,0,Gaming,2024-03-06,2024-04-23,2419,8.8,Neural Networks Co +AI02024,AI Research Scientist,218753,SGD,284379,EX,FL,Singapore,M,Norway,0,"Git, Python, Mathematics",Bachelor,17,Media,2024-08-06,2024-09-06,1029,8.6,Cloud AI Solutions +AI02025,Machine Learning Researcher,286960,SGD,373048,EX,FL,Singapore,L,Singapore,50,"Scala, Mathematics, Data Visualization, Git, Python",PhD,13,Energy,2024-07-02,2024-07-19,1324,7.9,Future Systems +AI02026,Autonomous Systems Engineer,54703,USD,54703,EN,FL,Sweden,M,Sweden,0,"Hadoop, Git, Tableau, Scala",PhD,0,Gaming,2024-04-19,2024-06-07,2069,6.4,Advanced Robotics +AI02027,Machine Learning Engineer,119409,USD,119409,SE,PT,Finland,L,Belgium,0,"AWS, MLOps, Kubernetes, Azure, Spark",Bachelor,5,Technology,2024-07-27,2024-09-03,2467,6.3,Autonomous Tech +AI02028,AI Software Engineer,169745,CAD,212181,EX,CT,Canada,M,Canada,50,"Java, SQL, PyTorch",Master,16,Real Estate,2024-03-20,2024-05-06,2094,5.4,Digital Transformation LLC +AI02029,AI Product Manager,117185,EUR,99607,MI,FT,Austria,L,Brazil,50,"Java, Kubernetes, Scala, Computer Vision, Git",Associate,2,Gaming,2025-01-13,2025-02-04,1341,7.6,Quantum Computing Inc +AI02030,AI Specialist,67488,EUR,57365,EN,PT,Germany,L,Italy,0,"SQL, Azure, PyTorch, Docker, TensorFlow",Master,0,Education,2024-10-02,2024-11-21,1857,7.4,Algorithmic Solutions +AI02031,Data Analyst,237063,AUD,320035,EX,FT,Australia,L,Australia,0,"Azure, Java, NLP, Hadoop",Bachelor,12,Technology,2024-07-17,2024-09-09,2126,9.3,Future Systems +AI02032,Data Engineer,121918,EUR,103630,MI,FL,Germany,L,Germany,50,"Kubernetes, Statistics, Tableau",Associate,2,Gaming,2024-07-09,2024-08-08,1044,5.7,Autonomous Tech +AI02033,Deep Learning Engineer,147358,USD,147358,EX,CT,Ireland,S,Argentina,0,"AWS, Python, Kubernetes, TensorFlow, Docker",Master,19,Transportation,2025-02-22,2025-04-06,932,6.2,DeepTech Ventures +AI02034,Data Analyst,159954,SGD,207940,SE,CT,Singapore,M,Singapore,50,"R, Kubernetes, MLOps, AWS, PyTorch",Master,8,Energy,2024-10-10,2024-11-04,886,7.5,Future Systems +AI02035,Data Analyst,112591,USD,112591,SE,FL,South Korea,M,Thailand,0,"Azure, Scala, Data Visualization, Mathematics",Bachelor,5,Government,2024-04-21,2024-05-07,758,5.4,TechCorp Inc +AI02036,AI Consultant,51670,EUR,43920,EN,CT,France,M,France,50,"R, MLOps, TensorFlow, Hadoop",Bachelor,1,Energy,2024-03-25,2024-04-26,1983,9.2,Predictive Systems +AI02037,Data Analyst,54739,USD,54739,EN,CT,Finland,S,Finland,50,"Statistics, MLOps, Tableau, SQL, Linux",PhD,1,Consulting,2024-09-20,2024-11-06,2488,6.7,Future Systems +AI02038,Principal Data Scientist,93238,EUR,79252,SE,CT,France,S,France,0,"NLP, Docker, Python, AWS",Bachelor,5,Education,2024-07-13,2024-08-24,1683,6,DeepTech Ventures +AI02039,AI Research Scientist,84825,USD,84825,MI,FL,Ireland,L,Malaysia,100,"Kubernetes, Mathematics, Tableau, MLOps",Associate,2,Technology,2024-05-16,2024-07-20,1709,6.7,TechCorp Inc +AI02040,AI Software Engineer,78450,USD,78450,MI,FT,Sweden,S,Sweden,100,"Computer Vision, Python, Git, TensorFlow",Bachelor,4,Energy,2024-12-18,2025-01-01,505,5.5,AI Innovations +AI02041,Head of AI,66222,USD,66222,EN,FL,South Korea,L,South Korea,50,"SQL, Deep Learning, NLP, Python",PhD,1,Technology,2024-09-04,2024-10-10,692,9.7,Algorithmic Solutions +AI02042,ML Ops Engineer,87393,USD,87393,MI,FL,United States,S,China,100,"Docker, Kubernetes, Data Visualization, Mathematics, Hadoop",Associate,2,Automotive,2025-01-14,2025-02-13,703,9.5,Smart Analytics +AI02043,Data Scientist,293844,GBP,220383,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Git, Tableau",Master,13,Healthcare,2024-02-11,2024-03-20,905,5.1,Neural Networks Co +AI02044,NLP Engineer,89635,USD,89635,EX,CT,China,S,China,50,"NLP, Scala, SQL, Deep Learning, Azure",Master,17,Manufacturing,2024-02-02,2024-04-05,1941,6.3,Quantum Computing Inc +AI02045,Data Analyst,40827,USD,40827,SE,CT,India,M,Argentina,100,"Deep Learning, PyTorch, Scala, Computer Vision",Associate,8,Consulting,2024-01-21,2024-03-11,867,6.1,DataVision Ltd +AI02046,AI Architect,53958,USD,53958,MI,PT,China,L,New Zealand,50,"SQL, Docker, Tableau",Bachelor,2,Real Estate,2024-05-12,2024-07-15,2051,7.5,DeepTech Ventures +AI02047,Autonomous Systems Engineer,209986,EUR,178488,EX,PT,France,S,France,50,"Scala, Kubernetes, Data Visualization, SQL, R",Associate,15,Real Estate,2024-04-12,2024-05-11,1552,5.3,Smart Analytics +AI02048,Data Engineer,48509,USD,48509,EN,FL,Finland,S,Finland,0,"Git, Mathematics, Hadoop, AWS, Azure",Bachelor,1,Education,2025-03-30,2025-05-03,2109,9.7,TechCorp Inc +AI02049,Autonomous Systems Engineer,256412,USD,256412,EX,CT,Denmark,L,Germany,0,"Java, TensorFlow, Spark, AWS",PhD,18,Real Estate,2025-04-10,2025-05-21,2390,5.7,TechCorp Inc +AI02050,Research Scientist,54244,USD,54244,EN,FL,South Korea,M,South Korea,100,"Python, Java, Tableau, TensorFlow",Master,0,Manufacturing,2024-05-29,2024-06-30,896,5.3,Cloud AI Solutions +AI02051,AI Architect,58064,USD,58064,EN,FT,Sweden,S,Denmark,100,"Kubernetes, MLOps, Statistics",Bachelor,0,Real Estate,2025-03-11,2025-04-30,1851,6.3,Predictive Systems +AI02052,Data Analyst,89637,USD,89637,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, MLOps, Hadoop",Bachelor,8,Gaming,2025-01-01,2025-02-15,795,7.4,Quantum Computing Inc +AI02053,Autonomous Systems Engineer,74071,USD,74071,EN,FL,Denmark,S,Vietnam,100,"R, Computer Vision, PyTorch, GCP",Bachelor,1,Technology,2024-04-11,2024-04-30,1809,7.5,Algorithmic Solutions +AI02054,AI Consultant,89562,EUR,76128,MI,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, Python, SQL, TensorFlow",PhD,4,Retail,2024-10-02,2024-10-16,750,9.4,Neural Networks Co +AI02055,Research Scientist,199418,CHF,179476,SE,FT,Switzerland,L,Switzerland,0,"Python, R, GCP, Spark",PhD,9,Government,2024-03-01,2024-05-01,1597,9.1,Advanced Robotics +AI02056,Robotics Engineer,128887,EUR,109554,EX,PT,France,M,France,50,"Azure, AWS, Tableau",Bachelor,13,Consulting,2024-03-19,2024-04-26,963,8.3,AI Innovations +AI02057,Data Analyst,72518,EUR,61640,EN,PT,Germany,S,Germany,50,"Python, SQL, Tableau",Bachelor,1,Finance,2024-05-30,2024-07-16,506,6.3,DataVision Ltd +AI02058,Autonomous Systems Engineer,63237,EUR,53751,MI,CT,France,S,France,0,"NLP, Kubernetes, Scala, Git, Tableau",PhD,4,Automotive,2024-01-17,2024-02-19,737,6.6,DeepTech Ventures +AI02059,Deep Learning Engineer,135732,GBP,101799,SE,PT,United Kingdom,S,Switzerland,100,"Python, SQL, Java, Computer Vision",Bachelor,5,Government,2024-05-01,2024-07-03,1777,5.8,Cognitive Computing +AI02060,AI Software Engineer,99662,USD,99662,EX,CT,China,M,China,100,"Kubernetes, Azure, Python, Hadoop",Bachelor,12,Transportation,2024-02-04,2024-03-14,1974,5,TechCorp Inc +AI02061,AI Consultant,282892,USD,282892,EX,FL,Ireland,L,Israel,100,"Scala, Java, Kubernetes",Master,14,Real Estate,2024-01-23,2024-02-14,2335,9.5,TechCorp Inc +AI02062,Computer Vision Engineer,126107,USD,126107,MI,CT,Denmark,L,Denmark,100,"Azure, Scala, Kubernetes",PhD,4,Retail,2024-08-23,2024-10-30,1170,9.4,Quantum Computing Inc +AI02063,Research Scientist,157203,USD,157203,SE,FL,United States,M,United States,0,"Git, Python, Computer Vision, Mathematics, AWS",PhD,5,Technology,2024-10-21,2024-12-01,1718,6.6,TechCorp Inc +AI02064,AI Specialist,91180,USD,91180,EN,CT,Norway,M,Norway,0,"Java, GCP, AWS, Hadoop",Master,0,Consulting,2024-12-09,2025-01-23,1561,5.4,Digital Transformation LLC +AI02065,Data Scientist,102489,USD,102489,EX,CT,China,M,China,50,"Tableau, Git, Kubernetes, MLOps, Computer Vision",PhD,19,Retail,2024-08-04,2024-09-15,1000,5.7,Smart Analytics +AI02066,AI Architect,220299,USD,220299,EX,FT,Finland,L,Finland,100,"NLP, Scala, Data Visualization",Associate,18,Retail,2025-04-18,2025-06-27,994,9.8,Smart Analytics +AI02067,AI Specialist,83499,USD,83499,MI,FL,Israel,M,Israel,50,"Data Visualization, Linux, Python, TensorFlow, PyTorch",Master,4,Manufacturing,2025-01-03,2025-02-28,1120,8.5,Cloud AI Solutions +AI02068,AI Research Scientist,72075,EUR,61264,EN,FT,Germany,M,Germany,50,"MLOps, Azure, AWS, Deep Learning, R",Associate,1,Government,2024-08-02,2024-10-03,1635,6.1,Advanced Robotics +AI02069,Deep Learning Engineer,87037,EUR,73981,MI,CT,Netherlands,M,Netherlands,0,"Deep Learning, Docker, NLP, Hadoop",Master,2,Automotive,2024-10-06,2024-11-02,967,5.4,Smart Analytics +AI02070,AI Research Scientist,123099,USD,123099,MI,FT,Denmark,S,Denmark,0,"PyTorch, AWS, MLOps, Python",PhD,2,Consulting,2025-02-22,2025-05-04,1204,7.5,Autonomous Tech +AI02071,Machine Learning Engineer,104913,EUR,89176,SE,CT,Germany,S,China,0,"Kubernetes, Scala, NLP, Mathematics, TensorFlow",Associate,5,Technology,2024-08-13,2024-10-24,2478,7.5,Machine Intelligence Group +AI02072,Deep Learning Engineer,221690,EUR,188437,EX,CT,Austria,L,Mexico,50,"PyTorch, Python, Git, Spark, Azure",Bachelor,19,Telecommunications,2024-08-05,2024-08-29,1602,7.3,Digital Transformation LLC +AI02073,Data Scientist,113653,EUR,96605,SE,FL,Germany,S,Germany,0,"Data Visualization, Kubernetes, Mathematics",Master,8,Real Estate,2024-01-06,2024-03-09,2077,8.6,DataVision Ltd +AI02074,Computer Vision Engineer,250419,USD,250419,EX,PT,United States,L,United States,100,"Data Visualization, Python, Azure, Scala, GCP",Bachelor,18,Retail,2024-05-17,2024-06-08,2362,7.2,Algorithmic Solutions +AI02075,AI Consultant,108412,EUR,92150,SE,CT,France,S,France,100,"Java, Python, Data Visualization, Linux",Associate,8,Gaming,2024-09-14,2024-10-16,1441,8.1,Algorithmic Solutions +AI02076,AI Specialist,186753,EUR,158740,EX,FL,Netherlands,S,Netherlands,100,"Mathematics, SQL, PyTorch",Associate,16,Technology,2025-04-05,2025-06-01,2436,8.9,Advanced Robotics +AI02077,AI Product Manager,134362,GBP,100772,MI,FT,United Kingdom,L,Finland,100,"Tableau, Hadoop, R, Docker",Associate,3,Consulting,2024-04-04,2024-05-15,2222,7.5,Smart Analytics +AI02078,Data Scientist,157702,USD,157702,EX,CT,Sweden,S,Vietnam,0,"Python, TensorFlow, Data Visualization, PyTorch, Hadoop",PhD,19,Real Estate,2024-04-25,2024-07-07,2122,8,Algorithmic Solutions +AI02079,Data Scientist,69203,USD,69203,EN,FL,Israel,M,Israel,0,"Spark, Scala, Python, Kubernetes, Docker",Master,0,Manufacturing,2024-02-16,2024-04-03,1738,9.9,Advanced Robotics +AI02080,AI Product Manager,97206,GBP,72905,MI,FL,United Kingdom,M,New Zealand,0,"TensorFlow, Scala, Deep Learning, Statistics, AWS",PhD,2,Consulting,2024-03-04,2024-03-18,1813,9.6,Quantum Computing Inc +AI02081,Data Scientist,82737,USD,82737,SE,CT,China,L,Japan,50,"Python, R, TensorFlow",Bachelor,9,Government,2024-06-06,2024-08-17,2069,9.9,DeepTech Ventures +AI02082,Machine Learning Engineer,99693,USD,99693,SE,PT,Sweden,S,Sweden,0,"Docker, Scala, Git, AWS",PhD,7,Telecommunications,2024-08-29,2024-10-20,1189,8.3,Autonomous Tech +AI02083,Autonomous Systems Engineer,82795,USD,82795,EN,PT,Finland,L,Finland,0,"SQL, Git, PyTorch, Spark, GCP",Associate,1,Transportation,2024-08-22,2024-09-13,1102,9.8,AI Innovations +AI02084,AI Research Scientist,174298,USD,174298,EX,FL,Finland,M,United States,50,"TensorFlow, Kubernetes, Statistics, SQL, AWS",Bachelor,13,Technology,2024-09-06,2024-09-28,721,7,Advanced Robotics +AI02085,Machine Learning Researcher,270830,CHF,243747,EX,PT,Switzerland,M,Switzerland,100,"PyTorch, Kubernetes, Tableau, SQL, Spark",Bachelor,11,Consulting,2024-11-10,2024-12-22,1174,7.1,Predictive Systems +AI02086,Machine Learning Researcher,68593,USD,68593,MI,PT,Israel,M,Israel,50,"Docker, Tableau, GCP",Master,3,Transportation,2024-10-05,2024-12-07,1095,9.1,Cloud AI Solutions +AI02087,Machine Learning Engineer,67495,EUR,57371,EN,PT,Netherlands,S,Netherlands,50,"Python, Kubernetes, Computer Vision",Bachelor,1,Transportation,2025-01-18,2025-03-19,2058,6.2,Smart Analytics +AI02088,AI Product Manager,114616,GBP,85962,MI,FL,United Kingdom,M,United Kingdom,50,"Statistics, Kubernetes, GCP, NLP, TensorFlow",Master,3,Energy,2024-03-25,2024-04-15,869,5.6,Neural Networks Co +AI02089,Data Engineer,213578,USD,213578,EX,CT,Sweden,M,Japan,50,"PyTorch, Kubernetes, Hadoop, R",Associate,15,Energy,2025-04-14,2025-05-03,1459,8.6,Algorithmic Solutions +AI02090,AI Product Manager,212620,USD,212620,EX,CT,Denmark,L,Denmark,0,"GCP, PyTorch, Data Visualization, Computer Vision",Bachelor,16,Education,2024-09-10,2024-11-10,905,9.1,Cloud AI Solutions +AI02091,Computer Vision Engineer,56144,USD,56144,SE,CT,China,M,China,100,"SQL, Docker, PyTorch, Kubernetes",Master,6,Real Estate,2024-02-08,2024-03-04,2052,7.4,AI Innovations +AI02092,Research Scientist,81572,EUR,69336,MI,FL,Austria,L,Luxembourg,0,"Computer Vision, Linux, PyTorch, Scala",Master,2,Healthcare,2024-09-25,2024-10-31,2115,8,AI Innovations +AI02093,Head of AI,69805,EUR,59334,EN,FL,Germany,S,South Korea,100,"SQL, Linux, Java, TensorFlow",PhD,1,Government,2024-07-09,2024-07-27,1396,6.2,Autonomous Tech +AI02094,ML Ops Engineer,134815,EUR,114593,SE,CT,Netherlands,S,Vietnam,100,"Docker, Tableau, Git, Kubernetes",PhD,7,Transportation,2024-07-14,2024-08-13,1842,9.6,TechCorp Inc +AI02095,NLP Engineer,201072,EUR,170911,EX,PT,Germany,S,Norway,100,"Linux, PyTorch, Git, Mathematics, Statistics",Bachelor,12,Education,2025-02-09,2025-03-21,965,6.2,Autonomous Tech +AI02096,AI Research Scientist,295447,JPY,32499170,EX,FL,Japan,L,Japan,50,"Spark, Linux, Statistics, PyTorch",Master,13,Finance,2024-01-31,2024-03-26,2060,5.6,Neural Networks Co +AI02097,Deep Learning Engineer,76720,USD,76720,EX,FL,China,M,China,50,"SQL, Kubernetes, TensorFlow, Scala",Associate,14,Gaming,2025-02-25,2025-04-02,970,7.9,Neural Networks Co +AI02098,Machine Learning Engineer,125533,USD,125533,SE,FL,Denmark,S,Denmark,0,"Deep Learning, Java, Scala",PhD,8,Automotive,2024-10-11,2024-12-01,1268,9.5,Digital Transformation LLC +AI02099,Robotics Engineer,253018,CAD,316273,EX,FT,Canada,L,Nigeria,50,"R, PyTorch, SQL, Scala",Associate,17,Government,2024-12-31,2025-03-06,1852,7.6,Cognitive Computing +AI02100,AI Product Manager,133162,GBP,99872,SE,FT,United Kingdom,S,United Kingdom,50,"Python, NLP, SQL, Linux, Kubernetes",Bachelor,7,Gaming,2025-04-14,2025-05-17,779,7.6,Digital Transformation LLC +AI02101,AI Architect,91600,USD,91600,MI,FL,South Korea,L,South Korea,100,"Python, GCP, Scala, Docker, Computer Vision",PhD,4,Finance,2024-04-26,2024-05-30,621,7.1,DataVision Ltd +AI02102,AI Product Manager,157559,EUR,133925,EX,CT,Austria,L,Austria,0,"Azure, MLOps, Scala, Computer Vision",Bachelor,19,Telecommunications,2025-03-13,2025-05-23,873,7.5,DeepTech Ventures +AI02103,Data Scientist,171584,USD,171584,EX,CT,Finland,M,Finland,100,"PyTorch, Python, Statistics",PhD,13,Education,2024-08-28,2024-09-24,1690,6.8,Autonomous Tech +AI02104,ML Ops Engineer,156785,CAD,195981,EX,FT,Canada,M,Canada,50,"SQL, PyTorch, Linux, Tableau",Bachelor,16,Media,2024-03-31,2024-04-20,2139,6.3,DataVision Ltd +AI02105,Machine Learning Engineer,293023,USD,293023,EX,CT,Denmark,M,Australia,100,"Docker, Computer Vision, Python, NLP, Deep Learning",Master,12,Manufacturing,2024-08-10,2024-10-10,1377,8.6,Smart Analytics +AI02106,Principal Data Scientist,86508,JPY,9515880,EN,FT,Japan,L,Japan,0,"Computer Vision, TensorFlow, GCP",Master,0,Technology,2025-03-28,2025-06-09,1511,8.8,Cloud AI Solutions +AI02107,AI Software Engineer,81412,USD,81412,EX,FT,China,S,Philippines,0,"Tableau, Linux, MLOps, Spark, Mathematics",Master,18,Media,2024-06-10,2024-07-22,1689,8.6,Advanced Robotics +AI02108,NLP Engineer,186673,EUR,158672,EX,FT,Austria,S,Austria,50,"Docker, Linux, SQL",Associate,10,Healthcare,2024-07-12,2024-08-22,1860,10,Advanced Robotics +AI02109,Principal Data Scientist,112912,USD,112912,MI,PT,United States,L,United States,100,"SQL, Spark, Git",Bachelor,4,Education,2024-09-19,2024-10-15,631,8.3,Cloud AI Solutions +AI02110,Principal Data Scientist,51942,USD,51942,EN,PT,Sweden,M,Japan,0,"R, Linux, Git, GCP, Deep Learning",PhD,0,Energy,2024-01-24,2024-02-27,828,6,Quantum Computing Inc +AI02111,Research Scientist,127418,USD,127418,MI,FT,Norway,M,Norway,0,"Hadoop, Java, Data Visualization",Associate,3,Automotive,2025-03-05,2025-04-16,1167,6.1,Machine Intelligence Group +AI02112,Research Scientist,96844,USD,96844,EN,CT,Denmark,L,Denmark,50,"MLOps, Kubernetes, Python, TensorFlow, PyTorch",Bachelor,0,Finance,2025-01-23,2025-03-03,2403,7.9,Autonomous Tech +AI02113,Principal Data Scientist,205497,USD,205497,EX,PT,Norway,M,Belgium,100,"Spark, TensorFlow, Data Visualization",Master,13,Automotive,2024-03-12,2024-04-14,990,5.2,Future Systems +AI02114,Machine Learning Researcher,36123,USD,36123,MI,FT,China,S,China,50,"R, SQL, Git, PyTorch",Associate,3,Manufacturing,2025-01-10,2025-02-18,812,9.3,Quantum Computing Inc +AI02115,Data Engineer,26530,USD,26530,EN,PT,China,S,China,0,"Scala, MLOps, SQL",Master,0,Automotive,2025-03-26,2025-04-25,2428,7.5,DataVision Ltd +AI02116,Deep Learning Engineer,118399,CAD,147999,SE,FL,Canada,L,Canada,50,"PyTorch, Scala, R",Master,9,Technology,2024-09-27,2024-11-05,2031,6.9,Cloud AI Solutions +AI02117,Data Analyst,100255,GBP,75191,MI,FT,United Kingdom,M,India,100,"Git, SQL, TensorFlow",Bachelor,2,Consulting,2025-04-25,2025-05-14,1999,8.9,Smart Analytics +AI02118,Research Scientist,129800,SGD,168740,SE,FT,Singapore,L,Singapore,100,"SQL, Computer Vision, Tableau, Python",Associate,6,Consulting,2025-03-18,2025-05-11,1202,8.2,DataVision Ltd +AI02119,Data Engineer,165833,AUD,223875,SE,PT,Australia,L,Australia,100,"NLP, Hadoop, Tableau, TensorFlow, SQL",Associate,8,Consulting,2024-12-31,2025-03-13,604,8.2,DataVision Ltd +AI02120,Computer Vision Engineer,84617,EUR,71924,MI,FL,France,L,France,50,"Azure, Java, Statistics",Master,3,Healthcare,2024-06-24,2024-07-15,1313,8.4,DeepTech Ventures +AI02121,AI Product Manager,228358,USD,228358,EX,FL,Sweden,M,Sweden,50,"TensorFlow, SQL, Python, GCP",Master,19,Transportation,2024-10-01,2024-11-15,849,5.3,Predictive Systems +AI02122,Deep Learning Engineer,89402,CHF,80462,EN,FT,Switzerland,S,Ireland,100,"Java, Git, Kubernetes, Scala, Mathematics",Associate,0,Real Estate,2024-03-28,2024-05-18,1854,8.7,Digital Transformation LLC +AI02123,AI Software Engineer,251892,USD,251892,EX,FT,Finland,L,Finland,100,"Spark, Python, Computer Vision, Data Visualization",Master,14,Technology,2024-07-22,2024-08-20,1045,7.9,Algorithmic Solutions +AI02124,NLP Engineer,91223,USD,91223,MI,PT,Ireland,L,Ireland,100,"Python, R, Statistics, GCP",Associate,4,Energy,2024-06-14,2024-08-24,1730,5.3,Algorithmic Solutions +AI02125,Robotics Engineer,178163,EUR,151439,EX,FL,France,L,France,100,"Linux, Hadoop, NLP, Kubernetes",Bachelor,18,Media,2024-07-07,2024-08-30,610,7.8,Cognitive Computing +AI02126,Machine Learning Researcher,110328,USD,110328,MI,FL,Denmark,M,Denmark,50,"AWS, Data Visualization, Tableau, TensorFlow",Bachelor,2,Energy,2024-11-04,2025-01-02,2362,5.9,DeepTech Ventures +AI02127,Research Scientist,80058,USD,80058,EN,CT,Norway,L,Norway,0,"SQL, PyTorch, Statistics, NLP",Master,0,Consulting,2025-04-13,2025-05-08,2081,8.4,AI Innovations +AI02128,Machine Learning Researcher,81768,USD,81768,SE,CT,China,L,China,100,"Git, R, Computer Vision",Master,7,Consulting,2025-03-10,2025-04-23,1020,5.1,Digital Transformation LLC +AI02129,Computer Vision Engineer,273957,EUR,232863,EX,FT,Netherlands,L,Netherlands,100,"Kubernetes, Azure, Spark, GCP",PhD,13,Government,2024-07-10,2024-08-28,589,7,Advanced Robotics +AI02130,Principal Data Scientist,71171,JPY,7828810,MI,CT,Japan,S,Japan,100,"Python, Statistics, Scala, Git",Master,2,Gaming,2025-03-24,2025-04-30,2269,8.9,AI Innovations +AI02131,Research Scientist,262050,EUR,222743,EX,CT,Netherlands,M,China,50,"Python, R, Tableau, Mathematics, GCP",Bachelor,19,Real Estate,2024-05-09,2024-06-14,2049,6.9,Digital Transformation LLC +AI02132,Principal Data Scientist,74346,JPY,8178060,EN,FL,Japan,S,Japan,50,"Git, MLOps, Python, Scala, Computer Vision",Associate,0,Technology,2024-07-31,2024-08-26,1392,5.6,Cognitive Computing +AI02133,AI Architect,26055,USD,26055,EN,FT,India,M,United States,100,"Python, AWS, Data Visualization, NLP",Master,1,Manufacturing,2025-02-04,2025-04-14,2432,5.8,Smart Analytics +AI02134,Autonomous Systems Engineer,113953,USD,113953,MI,FT,Israel,L,Israel,50,"GCP, PyTorch, Tableau",Bachelor,2,Healthcare,2024-07-07,2024-09-05,1361,9.1,Cloud AI Solutions +AI02135,Data Engineer,176525,GBP,132394,SE,CT,United Kingdom,L,United Kingdom,0,"R, Scala, Data Visualization, Linux, PyTorch",Associate,7,Manufacturing,2024-03-15,2024-04-28,2353,9.3,Advanced Robotics +AI02136,Robotics Engineer,137979,CHF,124181,SE,CT,Switzerland,S,Netherlands,0,"Linux, Python, TensorFlow",Bachelor,6,Gaming,2024-10-26,2024-12-29,1773,9.3,Cloud AI Solutions +AI02137,Data Engineer,232117,GBP,174088,EX,PT,United Kingdom,M,United Kingdom,100,"Computer Vision, SQL, Java",Master,15,Government,2024-11-21,2024-12-16,945,6.7,Cognitive Computing +AI02138,Data Analyst,130819,USD,130819,EX,FT,Finland,M,Finland,100,"Java, R, Mathematics",PhD,15,Telecommunications,2024-09-08,2024-10-04,1792,8.5,Neural Networks Co +AI02139,Machine Learning Engineer,245291,GBP,183968,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Python, Docker, Linux, NLP",Master,17,Telecommunications,2024-11-21,2025-01-19,1549,9.1,Future Systems +AI02140,NLP Engineer,121783,EUR,103516,SE,CT,France,M,Colombia,0,"Mathematics, PyTorch, SQL, Linux",PhD,5,Energy,2024-03-19,2024-04-09,2367,9.4,Cloud AI Solutions +AI02141,Machine Learning Engineer,145307,SGD,188899,SE,PT,Singapore,S,Chile,0,"Scala, Hadoop, MLOps, NLP, Java",Bachelor,5,Gaming,2024-05-17,2024-07-17,1974,8.5,Future Systems +AI02142,Robotics Engineer,77107,USD,77107,EN,FL,Norway,M,Norway,50,"Tableau, Kubernetes, Data Visualization",Bachelor,0,Consulting,2024-08-12,2024-08-30,527,5.8,Digital Transformation LLC +AI02143,AI Architect,67501,CAD,84376,EN,CT,Canada,S,Canada,0,"NLP, Tableau, Scala, PyTorch, SQL",PhD,1,Technology,2024-12-23,2025-02-20,720,6.4,Algorithmic Solutions +AI02144,Robotics Engineer,67669,USD,67669,EX,CT,China,M,China,100,"Deep Learning, Docker, Tableau",Bachelor,14,Gaming,2024-04-28,2024-06-09,1412,9.3,Cognitive Computing +AI02145,Head of AI,100999,EUR,85849,MI,FL,France,L,France,0,"MLOps, PyTorch, Kubernetes, Azure",Associate,2,Energy,2024-02-09,2024-04-02,2384,6.4,Algorithmic Solutions +AI02146,AI Consultant,57275,USD,57275,SE,CT,China,L,China,0,"Python, R, Azure",Associate,7,Real Estate,2025-01-23,2025-04-01,1686,9.4,Quantum Computing Inc +AI02147,Data Analyst,116317,USD,116317,EX,FT,Finland,S,Finland,0,"Data Visualization, Hadoop, Spark, Azure",Master,19,Energy,2024-01-24,2024-03-13,2115,5.8,Algorithmic Solutions +AI02148,Autonomous Systems Engineer,72220,USD,72220,EN,FT,United States,S,Argentina,50,"Statistics, Kubernetes, Mathematics",Bachelor,1,Education,2024-04-01,2024-05-18,1403,9.8,Autonomous Tech +AI02149,Computer Vision Engineer,48520,USD,48520,MI,CT,China,L,China,0,"Data Visualization, Python, TensorFlow, GCP, PyTorch",Associate,4,Transportation,2024-08-17,2024-09-03,1182,8.9,Predictive Systems +AI02150,AI Architect,91794,SGD,119332,MI,FT,Singapore,S,Russia,100,"Docker, Python, TensorFlow",Associate,4,Government,2024-10-23,2024-11-18,1817,9.2,Machine Intelligence Group +AI02151,Head of AI,148235,EUR,126000,SE,FL,Netherlands,L,Ireland,100,"Data Visualization, TensorFlow, Docker, Git",Associate,7,Manufacturing,2024-08-20,2024-09-07,2094,6.2,Neural Networks Co +AI02152,AI Software Engineer,63004,EUR,53553,EN,FL,Germany,S,Germany,100,"Azure, PyTorch, Docker, Kubernetes",PhD,1,Healthcare,2025-03-17,2025-04-28,1850,8.4,Future Systems +AI02153,Principal Data Scientist,256279,USD,256279,EX,PT,Finland,L,Finland,0,"Kubernetes, Python, Java, Linux",Master,13,Healthcare,2024-11-17,2025-01-25,573,6.5,Cognitive Computing +AI02154,Machine Learning Engineer,100220,USD,100220,MI,PT,United States,M,United States,100,"Kubernetes, Git, Scala, Statistics, GCP",Bachelor,2,Automotive,2025-03-09,2025-04-19,1993,9.5,Advanced Robotics +AI02155,Deep Learning Engineer,97614,CAD,122018,SE,CT,Canada,S,Canada,50,"Azure, Scala, SQL, Git",Master,7,Healthcare,2024-06-05,2024-06-25,1140,9.9,Cognitive Computing +AI02156,Data Engineer,128100,USD,128100,SE,FL,Sweden,S,Switzerland,100,"Python, AWS, Git, MLOps",PhD,7,Consulting,2024-09-05,2024-09-24,1215,10,Cloud AI Solutions +AI02157,AI Specialist,78590,USD,78590,EN,FL,Denmark,M,Denmark,50,"Python, Data Visualization, TensorFlow",Bachelor,0,Transportation,2025-03-11,2025-04-11,1220,8.7,DataVision Ltd +AI02158,Research Scientist,56489,USD,56489,EN,CT,United States,S,India,0,"Hadoop, Scala, Tableau, GCP",Master,0,Consulting,2024-08-10,2024-09-05,501,8.1,Predictive Systems +AI02159,Head of AI,145462,GBP,109097,SE,PT,United Kingdom,S,United Kingdom,100,"Git, NLP, Azure",PhD,9,Energy,2025-03-15,2025-05-09,2279,5.1,Quantum Computing Inc +AI02160,Robotics Engineer,114141,USD,114141,SE,FT,South Korea,M,South Korea,100,"Git, Java, Deep Learning, Scala, Mathematics",Master,9,Transportation,2024-03-30,2024-04-17,1412,8.6,Digital Transformation LLC +AI02161,Data Scientist,122099,USD,122099,SE,PT,Israel,S,Israel,100,"Azure, GCP, Python, TensorFlow",Bachelor,9,Media,2024-04-29,2024-06-30,1064,5.2,Digital Transformation LLC +AI02162,Data Engineer,109552,SGD,142418,SE,PT,Singapore,M,Singapore,0,"Linux, SQL, Kubernetes, Azure, Python",Master,7,Telecommunications,2024-08-28,2024-10-17,897,5.1,DeepTech Ventures +AI02163,AI Product Manager,57229,EUR,48645,EN,FT,Germany,S,Germany,0,"Kubernetes, Spark, Computer Vision, PyTorch",Associate,1,Manufacturing,2024-08-22,2024-10-10,831,6.6,Quantum Computing Inc +AI02164,NLP Engineer,174350,EUR,148198,EX,FL,France,M,France,100,"Kubernetes, SQL, Docker, Spark, R",Master,12,Technology,2024-08-14,2024-08-29,2021,6.8,Cognitive Computing +AI02165,AI Consultant,131413,USD,131413,SE,FL,Finland,L,Finland,0,"Java, GCP, Kubernetes",Master,6,Media,2024-05-26,2024-07-15,2012,5.7,Algorithmic Solutions +AI02166,NLP Engineer,109502,CAD,136878,SE,FT,Canada,S,Canada,100,"Data Visualization, SQL, R, PyTorch",Associate,7,Education,2025-04-21,2025-06-27,1888,7.3,DataVision Ltd +AI02167,Autonomous Systems Engineer,29846,USD,29846,MI,FL,India,S,India,50,"Spark, Deep Learning, Computer Vision",Master,4,Finance,2024-08-31,2024-10-06,2061,7.4,Future Systems +AI02168,Computer Vision Engineer,155786,USD,155786,SE,FT,Denmark,M,Portugal,0,"R, Computer Vision, Linux, Deep Learning",Master,8,Transportation,2025-04-12,2025-05-06,2317,5.1,Algorithmic Solutions +AI02169,Data Scientist,84770,USD,84770,EX,FT,India,M,India,100,"AWS, Tableau, Git, Deep Learning",Bachelor,17,Finance,2024-11-25,2024-12-28,1787,7.4,Algorithmic Solutions +AI02170,Computer Vision Engineer,89112,USD,89112,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Java, Python",PhD,2,Technology,2024-07-22,2024-08-06,669,6.1,DeepTech Ventures +AI02171,AI Specialist,104744,USD,104744,EN,FT,Denmark,L,United States,0,"Docker, Python, Scala",Master,1,Technology,2025-01-27,2025-04-03,2167,8,Predictive Systems +AI02172,Data Analyst,199544,USD,199544,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Docker, Hadoop, GCP, Linux",Bachelor,11,Education,2025-03-11,2025-04-01,2130,9.5,Quantum Computing Inc +AI02173,Machine Learning Engineer,93564,EUR,79529,MI,CT,France,S,Hungary,100,"SQL, Azure, Tableau, Java, Statistics",Bachelor,3,Energy,2024-01-05,2024-02-03,1181,6,AI Innovations +AI02174,AI Specialist,109257,AUD,147497,MI,PT,Australia,M,Australia,100,"Linux, Git, Statistics, R",PhD,2,Energy,2024-09-15,2024-11-10,1854,8.5,Advanced Robotics +AI02175,AI Product Manager,233827,EUR,198753,EX,FT,Austria,L,Sweden,100,"Kubernetes, R, SQL, AWS",Associate,19,Retail,2024-04-17,2024-05-09,2089,8.7,Algorithmic Solutions +AI02176,AI Specialist,199622,USD,199622,SE,CT,United States,L,United States,0,"TensorFlow, Deep Learning, MLOps, Git, Kubernetes",PhD,8,Consulting,2024-11-04,2024-11-25,1993,10,Cognitive Computing +AI02177,Data Analyst,158846,USD,158846,EX,PT,Sweden,S,Ukraine,50,"Python, Git, Scala, NLP",Bachelor,10,Technology,2025-03-29,2025-04-20,1386,9.9,Neural Networks Co +AI02178,AI Software Engineer,43785,USD,43785,EN,PT,Israel,S,Israel,100,"Statistics, SQL, Spark, Tableau",Bachelor,0,Telecommunications,2024-05-23,2024-07-07,2022,8.6,Neural Networks Co +AI02179,AI Architect,101184,USD,101184,EX,PT,China,S,Estonia,100,"Data Visualization, Docker, Python, Kubernetes",Master,10,Healthcare,2025-03-16,2025-04-20,513,8.3,Machine Intelligence Group +AI02180,Principal Data Scientist,89965,USD,89965,EX,FT,India,L,India,0,"Python, SQL, Computer Vision, Docker, Java",Associate,16,Manufacturing,2025-02-21,2025-03-20,2467,7.2,AI Innovations +AI02181,Principal Data Scientist,73352,SGD,95358,EN,PT,Singapore,L,Brazil,50,"Docker, Data Visualization, Python, Mathematics, R",Bachelor,0,Finance,2025-02-14,2025-04-08,954,7,Digital Transformation LLC +AI02182,Head of AI,199823,USD,199823,EX,CT,Finland,L,India,0,"Azure, Computer Vision, TensorFlow",Bachelor,11,Transportation,2024-07-22,2024-08-20,2424,5.4,Neural Networks Co +AI02183,ML Ops Engineer,77392,GBP,58044,EN,FL,United Kingdom,M,Latvia,50,"Python, Azure, TensorFlow, Statistics, AWS",PhD,1,Technology,2024-02-26,2024-04-01,841,6.5,Algorithmic Solutions +AI02184,Machine Learning Researcher,75898,CAD,94873,EN,FT,Canada,M,Portugal,0,"Git, PyTorch, SQL, Python",PhD,0,Education,2024-02-03,2024-03-26,1178,8.2,AI Innovations +AI02185,Data Analyst,76715,USD,76715,EN,PT,Israel,L,Israel,50,"Tableau, Hadoop, Deep Learning",PhD,0,Energy,2025-03-24,2025-05-12,756,6.7,DataVision Ltd +AI02186,Machine Learning Engineer,99717,JPY,10968870,MI,PT,Japan,M,Japan,50,"GCP, Azure, Linux, Scala",Master,3,Media,2024-02-18,2024-04-11,1134,7.3,Neural Networks Co +AI02187,AI Research Scientist,181613,USD,181613,EX,FL,Israel,L,Israel,50,"Scala, Linux, Java",Bachelor,11,Consulting,2024-08-02,2024-09-21,514,7.4,Cloud AI Solutions +AI02188,Autonomous Systems Engineer,109710,EUR,93254,MI,PT,Netherlands,L,Australia,100,"SQL, Linux, PyTorch, NLP",Bachelor,2,Energy,2024-04-06,2024-04-27,2356,6.3,Digital Transformation LLC +AI02189,AI Product Manager,195849,JPY,21543390,EX,PT,Japan,L,Japan,0,"Scala, Statistics, NLP",PhD,11,Finance,2024-03-18,2024-05-17,1271,6.8,Future Systems +AI02190,Data Scientist,125807,USD,125807,SE,FT,Sweden,L,Indonesia,0,"Python, Data Visualization, Docker, NLP",PhD,8,Media,2024-05-05,2024-05-31,1151,5.8,Digital Transformation LLC +AI02191,Research Scientist,104357,CHF,93921,MI,PT,Switzerland,M,Switzerland,100,"Java, AWS, Mathematics, Hadoop",Master,3,Government,2025-01-23,2025-02-10,1996,9.6,Smart Analytics +AI02192,Data Scientist,176952,EUR,150409,EX,CT,Netherlands,S,Netherlands,50,"Java, MLOps, R, Linux, NLP",Master,12,Transportation,2025-02-24,2025-03-12,2382,9.7,Smart Analytics +AI02193,Head of AI,57405,EUR,48794,EN,FL,France,M,France,100,"PyTorch, Computer Vision, Git, Azure, Scala",Master,1,Technology,2024-08-31,2024-09-26,605,7,Quantum Computing Inc +AI02194,Data Analyst,130621,EUR,111028,EX,FL,France,S,France,0,"Linux, Hadoop, Python, Computer Vision, Git",PhD,16,Real Estate,2024-05-13,2024-07-22,1072,8.9,Smart Analytics +AI02195,Research Scientist,78485,CAD,98106,EN,PT,Canada,L,Canada,0,"Scala, SQL, Statistics, Hadoop",PhD,0,Retail,2024-07-27,2024-09-20,1057,8,AI Innovations +AI02196,AI Consultant,200595,CHF,180536,SE,CT,Switzerland,M,South Africa,50,"Hadoop, Python, Deep Learning, Azure",Master,5,Media,2024-05-20,2024-07-12,2146,9.2,DeepTech Ventures +AI02197,AI Architect,50119,EUR,42601,EN,FL,France,M,France,0,"Docker, Azure, Computer Vision",PhD,1,Energy,2025-01-03,2025-03-01,2042,5.7,Smart Analytics +AI02198,Computer Vision Engineer,78348,EUR,66596,EN,FL,Germany,L,Czech Republic,0,"Tableau, Java, Kubernetes",Master,1,Finance,2024-08-22,2024-09-09,867,7.6,TechCorp Inc +AI02199,AI Software Engineer,158752,USD,158752,MI,FL,Norway,L,China,0,"Python, GCP, TensorFlow, Computer Vision, PyTorch",PhD,2,Energy,2024-02-19,2024-04-02,751,8.1,Smart Analytics +AI02200,Data Scientist,35696,USD,35696,MI,CT,India,L,India,100,"Scala, TensorFlow, Python, Computer Vision, Kubernetes",PhD,3,Transportation,2024-12-22,2025-02-17,2146,9.8,DataVision Ltd +AI02201,AI Architect,81558,AUD,110103,MI,PT,Australia,S,Portugal,50,"Python, Kubernetes, Deep Learning, AWS, MLOps",Master,4,Media,2024-06-03,2024-07-17,1216,9.3,Cognitive Computing +AI02202,AI Architect,240445,JPY,26448950,EX,PT,Japan,L,Japan,0,"Data Visualization, NLP, Python",PhD,12,Finance,2024-10-11,2024-12-10,2060,5.2,Predictive Systems +AI02203,Research Scientist,60197,USD,60197,SE,FT,China,M,Indonesia,100,"PyTorch, NLP, Hadoop, Statistics, Kubernetes",Master,5,Energy,2024-04-26,2024-07-06,2308,5.2,Machine Intelligence Group +AI02204,Deep Learning Engineer,67887,USD,67887,EN,FT,Norway,M,Norway,0,"PyTorch, Java, Spark, Hadoop, GCP",Bachelor,1,Transportation,2024-11-20,2025-01-22,1444,7.6,Autonomous Tech +AI02205,AI Research Scientist,251281,CAD,314101,EX,FL,Canada,L,Canada,50,"Data Visualization, Python, Azure, Scala, Spark",PhD,11,Transportation,2024-09-16,2024-11-14,1947,8.9,AI Innovations +AI02206,Data Engineer,266985,CHF,240287,EX,CT,Switzerland,L,New Zealand,50,"Tableau, PyTorch, Statistics",PhD,19,Automotive,2025-04-11,2025-04-25,889,7.1,Machine Intelligence Group +AI02207,AI Consultant,129783,EUR,110316,MI,FL,Netherlands,L,Netherlands,0,"Spark, Git, Statistics, PyTorch",Associate,4,Education,2024-01-11,2024-03-22,1435,6.1,Neural Networks Co +AI02208,Data Analyst,79996,GBP,59997,EN,FL,United Kingdom,L,United Kingdom,100,"Azure, GCP, Data Visualization",PhD,1,Healthcare,2024-08-22,2024-10-25,2334,8.6,Autonomous Tech +AI02209,Data Engineer,86496,CAD,108120,MI,FT,Canada,S,Canada,100,"Scala, Java, Mathematics, AWS, TensorFlow",PhD,2,Government,2025-01-17,2025-02-19,777,8.7,Advanced Robotics +AI02210,ML Ops Engineer,114996,USD,114996,MI,FT,Israel,L,Israel,50,"Scala, NLP, Hadoop",Master,4,Technology,2024-10-05,2024-11-13,820,5.7,Predictive Systems +AI02211,AI Architect,124110,USD,124110,SE,FL,Israel,L,Israel,0,"GCP, R, Tableau, Data Visualization, Scala",Bachelor,8,Media,2025-01-09,2025-03-08,975,5.6,Autonomous Tech +AI02212,AI Software Engineer,99108,USD,99108,SE,FT,South Korea,S,South Korea,100,"TensorFlow, Azure, Java, PyTorch, Computer Vision",Bachelor,5,Finance,2024-11-07,2024-12-28,895,6.2,Future Systems +AI02213,AI Product Manager,141155,CHF,127040,MI,PT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Tableau",PhD,3,Real Estate,2024-01-09,2024-02-05,1858,6.8,Future Systems +AI02214,AI Product Manager,71602,USD,71602,EN,FT,Ireland,M,Ireland,100,"Git, Computer Vision, Python, TensorFlow, NLP",Associate,1,Manufacturing,2024-06-14,2024-07-14,1203,7.7,Algorithmic Solutions +AI02215,Machine Learning Researcher,99305,USD,99305,EN,FT,Norway,L,Norway,100,"Kubernetes, SQL, NLP, Statistics",Master,1,Finance,2024-03-17,2024-05-29,1286,7.3,Digital Transformation LLC +AI02216,Machine Learning Engineer,268561,EUR,228277,EX,FT,France,L,India,0,"Git, Python, TensorFlow, Linux",PhD,17,Gaming,2025-02-19,2025-03-12,2172,6.4,AI Innovations +AI02217,AI Software Engineer,101510,CHF,91359,EN,CT,Switzerland,L,Austria,100,"SQL, Hadoop, PyTorch, Deep Learning",PhD,0,Gaming,2024-02-10,2024-03-04,1555,7,Machine Intelligence Group +AI02218,Principal Data Scientist,270963,USD,270963,EX,CT,Denmark,L,Austria,0,"MLOps, Statistics, GCP, PyTorch, Scala",PhD,13,Transportation,2024-10-20,2024-12-23,2253,6.3,Autonomous Tech +AI02219,AI Specialist,79001,USD,79001,MI,CT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker",PhD,4,Retail,2024-10-15,2024-12-18,1577,8.2,Machine Intelligence Group +AI02220,Principal Data Scientist,51039,GBP,38279,EN,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, R, Computer Vision",Master,0,Energy,2024-07-10,2024-08-23,527,5.9,Digital Transformation LLC +AI02221,ML Ops Engineer,86750,EUR,73738,EN,PT,Netherlands,L,Austria,50,"Java, Linux, Azure, GCP",Master,1,Energy,2025-04-21,2025-06-24,2026,8.5,DeepTech Ventures +AI02222,Research Scientist,52962,CAD,66203,EN,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Data Visualization, Python, Spark",Associate,1,Telecommunications,2024-07-20,2024-09-30,1427,6.8,Smart Analytics +AI02223,AI Software Engineer,253468,USD,253468,EX,CT,Sweden,M,Sweden,100,"Scala, R, Data Visualization, NLP, Python",Bachelor,19,Gaming,2024-08-12,2024-10-03,2402,7.5,TechCorp Inc +AI02224,AI Specialist,122016,EUR,103714,SE,PT,Germany,L,Australia,50,"Kubernetes, Hadoop, Tableau, PyTorch",Bachelor,7,Education,2024-11-10,2024-11-24,2156,9.1,Smart Analytics +AI02225,Research Scientist,51691,AUD,69783,EN,FT,Australia,S,Malaysia,50,"PyTorch, Linux, Git, TensorFlow, Deep Learning",PhD,1,Manufacturing,2024-03-11,2024-04-11,2158,9.4,DeepTech Ventures +AI02226,Principal Data Scientist,119127,USD,119127,EX,FT,Israel,S,Israel,0,"SQL, Tableau, MLOps",PhD,13,Finance,2025-02-01,2025-04-03,2048,6.3,Autonomous Tech +AI02227,Computer Vision Engineer,190161,USD,190161,EX,FL,Israel,S,Israel,100,"Azure, AWS, Statistics, GCP, Tableau",Associate,15,Technology,2024-05-12,2024-06-23,741,7.6,Smart Analytics +AI02228,Computer Vision Engineer,241186,USD,241186,EX,FT,Denmark,S,Denmark,0,"SQL, TensorFlow, Mathematics",PhD,14,Telecommunications,2024-09-23,2024-11-03,2069,6.3,Advanced Robotics +AI02229,Research Scientist,103949,CAD,129936,SE,CT,Canada,M,Czech Republic,50,"Kubernetes, Java, Data Visualization, MLOps",Associate,8,Education,2024-09-05,2024-10-20,1017,7.6,Smart Analytics +AI02230,Deep Learning Engineer,199232,USD,199232,EX,FT,Sweden,M,Sweden,100,"PyTorch, Data Visualization, Deep Learning",Bachelor,14,Government,2024-06-01,2024-06-18,1509,7.4,Advanced Robotics +AI02231,AI Research Scientist,157050,USD,157050,EX,PT,Sweden,S,Finland,0,"Tableau, Hadoop, R, Linux",PhD,17,Retail,2024-08-19,2024-09-18,852,7.4,Predictive Systems +AI02232,Computer Vision Engineer,84353,USD,84353,MI,PT,Israel,S,Luxembourg,0,"Azure, AWS, Computer Vision",Bachelor,2,Media,2024-08-26,2024-10-07,1724,7.8,Machine Intelligence Group +AI02233,Robotics Engineer,192697,USD,192697,EX,CT,Denmark,S,Denmark,50,"Java, PyTorch, Mathematics, Data Visualization, SQL",Master,12,Healthcare,2025-02-14,2025-03-09,2434,8.7,DeepTech Ventures +AI02234,NLP Engineer,154367,CAD,192959,SE,FT,Canada,L,Mexico,100,"Git, SQL, GCP, Tableau",PhD,5,Transportation,2024-12-12,2025-01-18,1287,5.1,Neural Networks Co +AI02235,Principal Data Scientist,305641,CHF,275077,EX,PT,Switzerland,S,Switzerland,0,"R, NLP, MLOps, Scala, Docker",Master,19,Transportation,2024-12-26,2025-03-08,674,7.7,Neural Networks Co +AI02236,Computer Vision Engineer,337542,CHF,303788,EX,FL,Switzerland,L,Netherlands,50,"Python, NLP, Tableau",PhD,15,Real Estate,2024-10-26,2025-01-07,1813,6.9,Machine Intelligence Group +AI02237,AI Software Engineer,82530,USD,82530,MI,CT,Finland,M,Germany,100,"Java, GCP, Kubernetes, MLOps",Bachelor,2,Technology,2024-08-13,2024-08-27,1062,5.3,Future Systems +AI02238,AI Specialist,183461,USD,183461,EX,CT,South Korea,L,South Korea,100,"Hadoop, Deep Learning, Data Visualization, Java",PhD,10,Telecommunications,2024-07-15,2024-09-08,2037,7.7,Digital Transformation LLC +AI02239,ML Ops Engineer,112033,USD,112033,SE,CT,Israel,M,Israel,50,"GCP, SQL, Data Visualization, Linux, Scala",Bachelor,9,Transportation,2024-01-29,2024-02-19,775,9.4,Cognitive Computing +AI02240,Deep Learning Engineer,121109,EUR,102943,MI,FL,Germany,L,India,100,"PyTorch, Tableau, MLOps, Linux",PhD,3,Healthcare,2024-07-13,2024-09-06,1184,6.8,Digital Transformation LLC +AI02241,NLP Engineer,208944,EUR,177602,EX,FT,Austria,S,Austria,100,"Data Visualization, R, AWS, Azure",Bachelor,16,Technology,2024-09-27,2024-10-27,924,5.5,AI Innovations +AI02242,AI Product Manager,60646,CAD,75808,EN,PT,Canada,L,Canada,50,"TensorFlow, MLOps, Python, AWS",Master,1,Gaming,2024-01-17,2024-03-29,1189,6.8,Neural Networks Co +AI02243,AI Architect,83782,EUR,71215,MI,FT,Germany,M,Germany,100,"Kubernetes, Statistics, MLOps",Associate,2,Transportation,2024-07-14,2024-07-31,1645,7,Algorithmic Solutions +AI02244,Research Scientist,130792,USD,130792,EX,FL,Finland,S,United Kingdom,0,"Spark, Kubernetes, Data Visualization, Python, Linux",Associate,14,Gaming,2025-04-11,2025-04-26,697,8.4,AI Innovations +AI02245,Head of AI,98316,USD,98316,SE,FL,South Korea,M,South Korea,50,"Linux, Hadoop, SQL",Associate,9,Education,2025-02-16,2025-03-14,1669,7.8,Digital Transformation LLC +AI02246,AI Software Engineer,157782,EUR,134115,SE,PT,Netherlands,M,Netherlands,100,"Git, Python, SQL, Deep Learning, Spark",Bachelor,9,Retail,2025-01-01,2025-02-27,709,5.6,Smart Analytics +AI02247,Computer Vision Engineer,54428,USD,54428,EN,PT,South Korea,M,Netherlands,50,"TensorFlow, Mathematics, Tableau, Kubernetes, Linux",Master,0,Manufacturing,2024-10-26,2024-11-19,1158,5.2,DeepTech Ventures +AI02248,Autonomous Systems Engineer,90867,EUR,77237,MI,FT,Germany,L,Germany,50,"Azure, Git, Hadoop",PhD,2,Education,2025-04-16,2025-06-04,634,9.7,Advanced Robotics +AI02249,Machine Learning Researcher,67221,EUR,57138,EN,FT,Austria,S,Austria,50,"Scala, Hadoop, Computer Vision, GCP",Master,1,Technology,2024-05-05,2024-05-29,2072,7.1,Digital Transformation LLC +AI02250,Principal Data Scientist,154303,EUR,131158,EX,FL,France,M,France,100,"Linux, Git, Tableau",Master,17,Manufacturing,2024-05-23,2024-06-22,2153,7.8,Cloud AI Solutions +AI02251,Data Engineer,100244,CHF,90220,EN,FT,Switzerland,S,Russia,0,"Kubernetes, Java, Docker",Associate,1,Healthcare,2025-03-16,2025-05-11,1905,9.8,Machine Intelligence Group +AI02252,Principal Data Scientist,135424,USD,135424,SE,PT,Denmark,S,New Zealand,100,"Tableau, Azure, Git",PhD,5,Automotive,2024-07-08,2024-08-16,562,7,Quantum Computing Inc +AI02253,AI Research Scientist,61375,EUR,52169,EN,PT,France,S,France,100,"Computer Vision, Python, TensorFlow",Bachelor,0,Automotive,2024-12-20,2025-02-24,1802,9.5,Algorithmic Solutions +AI02254,AI Consultant,113261,USD,113261,MI,PT,Sweden,L,Sweden,0,"Tableau, Python, GCP, TensorFlow",PhD,4,Real Estate,2024-12-04,2025-01-12,1918,8.7,Autonomous Tech +AI02255,AI Product Manager,114736,EUR,97526,SE,PT,Austria,S,Mexico,0,"Python, Computer Vision, GCP, MLOps, Data Visualization",Master,9,Government,2024-04-21,2024-05-08,2032,5.1,Machine Intelligence Group +AI02256,NLP Engineer,48296,USD,48296,MI,PT,China,M,Chile,50,"SQL, Java, Python",Associate,2,Government,2024-08-27,2024-11-01,1041,6.4,Cognitive Computing +AI02257,AI Software Engineer,205168,USD,205168,EX,CT,Sweden,L,Sweden,100,"Spark, TensorFlow, NLP, Computer Vision",Associate,10,Real Estate,2024-10-27,2024-11-15,2325,7.7,Cognitive Computing +AI02258,Data Engineer,44379,USD,44379,SE,FL,China,S,China,0,"Python, Docker, Tableau, Kubernetes",Bachelor,7,Energy,2024-03-28,2024-05-16,2495,6.4,Neural Networks Co +AI02259,Head of AI,89555,AUD,120899,EN,FL,Australia,L,Austria,100,"Azure, Git, Computer Vision, SQL, Scala",Master,1,Telecommunications,2025-01-28,2025-02-28,608,8.8,Cloud AI Solutions +AI02260,Head of AI,186544,CAD,233180,EX,FL,Canada,L,South Africa,0,"AWS, Spark, PyTorch, Linux",Master,15,Automotive,2024-08-14,2024-09-08,990,9.5,Autonomous Tech +AI02261,Deep Learning Engineer,130260,USD,130260,MI,FL,Norway,M,Norway,50,"AWS, Deep Learning, Java, Linux",Associate,3,Finance,2024-04-28,2024-06-13,543,5.1,TechCorp Inc +AI02262,AI Specialist,61880,USD,61880,EX,FT,India,S,India,100,"Spark, Git, Scala",Bachelor,14,Media,2025-01-05,2025-03-18,2089,6.2,Smart Analytics +AI02263,Robotics Engineer,185105,EUR,157339,EX,FT,France,M,France,50,"TensorFlow, Data Visualization, Spark",PhD,11,Real Estate,2024-11-11,2024-12-16,944,6,Neural Networks Co +AI02264,AI Consultant,60068,EUR,51058,EN,CT,Netherlands,M,Netherlands,0,"Docker, Git, R, Linux, Scala",Bachelor,1,Technology,2024-03-07,2024-03-23,1856,5.8,Quantum Computing Inc +AI02265,AI Product Manager,152832,JPY,16811520,SE,FL,Japan,L,Japan,100,"Linux, PyTorch, TensorFlow",Master,9,Consulting,2025-02-01,2025-03-15,2241,7.9,TechCorp Inc +AI02266,AI Consultant,163684,AUD,220973,SE,CT,Australia,L,Belgium,0,"TensorFlow, Python, Spark, Java",Associate,5,Automotive,2024-05-01,2024-07-04,2186,9.7,Future Systems +AI02267,Machine Learning Engineer,51675,AUD,69761,EN,PT,Australia,M,Australia,50,"Git, Scala, Computer Vision, Java, Deep Learning",Bachelor,0,Healthcare,2025-01-08,2025-02-02,1966,5.3,Cloud AI Solutions +AI02268,Principal Data Scientist,270523,USD,270523,EX,PT,Norway,S,Thailand,100,"SQL, MLOps, PyTorch, TensorFlow, Tableau",Associate,12,Gaming,2024-06-16,2024-07-30,1569,9.7,TechCorp Inc +AI02269,Principal Data Scientist,138679,EUR,117877,SE,PT,France,M,Finland,100,"Statistics, Tableau, Linux",Master,8,Retail,2024-11-10,2024-12-30,681,6.2,Autonomous Tech +AI02270,Data Scientist,153448,GBP,115086,EX,PT,United Kingdom,S,United Kingdom,100,"PyTorch, TensorFlow, Hadoop, Kubernetes, R",Bachelor,16,Manufacturing,2024-11-26,2024-12-10,2074,9.7,Quantum Computing Inc +AI02271,Autonomous Systems Engineer,99198,CHF,89278,EN,FL,Switzerland,M,Malaysia,100,"PyTorch, NLP, Git, Azure, Mathematics",PhD,0,Education,2024-01-27,2024-03-20,916,6.3,DeepTech Ventures +AI02272,AI Architect,108736,EUR,92426,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, TensorFlow, Java, SQL, Azure",Associate,6,Automotive,2024-11-28,2024-12-21,1268,7.8,AI Innovations +AI02273,AI Product Manager,108349,EUR,92097,SE,PT,Netherlands,S,Netherlands,0,"Linux, MLOps, NLP",Bachelor,8,Education,2025-02-14,2025-04-25,944,5.1,Cloud AI Solutions +AI02274,AI Consultant,97976,USD,97976,SE,FL,Finland,M,Finland,100,"TensorFlow, Kubernetes, Deep Learning, Scala, Azure",Associate,9,Telecommunications,2024-01-05,2024-02-12,1332,5.6,TechCorp Inc +AI02275,Data Engineer,106852,USD,106852,MI,FT,Sweden,L,United States,50,"Kubernetes, SQL, GCP, Computer Vision",PhD,2,Automotive,2024-07-21,2024-09-01,2193,9.1,Algorithmic Solutions +AI02276,AI Research Scientist,157337,CHF,141603,SE,CT,Switzerland,S,Italy,100,"Scala, PyTorch, MLOps, SQL",Bachelor,5,Retail,2024-06-24,2024-07-30,1623,6.4,Digital Transformation LLC +AI02277,Data Engineer,119797,CHF,107817,EN,FT,Switzerland,L,Switzerland,50,"Python, Linux, Deep Learning",Associate,0,Telecommunications,2024-06-27,2024-07-27,624,6.4,Neural Networks Co +AI02278,Machine Learning Researcher,69161,USD,69161,EX,FL,India,M,India,100,"Deep Learning, TensorFlow, Kubernetes, Statistics",Master,15,Healthcare,2024-07-31,2024-09-18,997,5.6,Machine Intelligence Group +AI02279,Data Engineer,138491,AUD,186963,EX,FL,Australia,M,Australia,50,"Deep Learning, TensorFlow, Linux",Bachelor,18,Government,2024-12-19,2025-01-26,839,5.6,Autonomous Tech +AI02280,AI Product Manager,103654,GBP,77741,MI,FL,United Kingdom,M,United Kingdom,0,"GCP, Python, Docker",Associate,2,Real Estate,2025-04-05,2025-04-26,591,9.9,TechCorp Inc +AI02281,Deep Learning Engineer,61991,USD,61991,EN,CT,Ireland,S,Ireland,50,"Mathematics, Python, AWS, TensorFlow, Scala",Bachelor,0,Retail,2024-11-06,2025-01-11,2413,7.5,Autonomous Tech +AI02282,AI Research Scientist,81076,EUR,68915,EN,CT,Austria,L,Austria,100,"Python, Linux, MLOps, TensorFlow, Azure",Master,0,Consulting,2025-03-28,2025-06-09,927,7.4,Digital Transformation LLC +AI02283,Data Engineer,84481,USD,84481,MI,CT,Israel,S,Israel,100,"Mathematics, Data Visualization, TensorFlow",Master,4,Government,2024-06-24,2024-08-08,1198,8.5,Autonomous Tech +AI02284,Machine Learning Engineer,31910,USD,31910,MI,FL,China,S,Singapore,0,"TensorFlow, SQL, Mathematics, NLP",Bachelor,2,Technology,2024-04-05,2024-06-06,1846,7.7,Cognitive Computing +AI02285,Principal Data Scientist,103659,AUD,139940,MI,PT,Australia,L,Australia,50,"Docker, SQL, NLP, GCP, MLOps",Bachelor,2,Media,2024-03-02,2024-04-08,2362,9.8,Predictive Systems +AI02286,Machine Learning Researcher,241811,AUD,326445,EX,CT,Australia,L,Romania,0,"PyTorch, GCP, Python, Spark, MLOps",PhD,19,Government,2024-06-11,2024-08-06,2082,8.8,Smart Analytics +AI02287,Principal Data Scientist,85528,EUR,72699,MI,PT,Netherlands,M,Netherlands,50,"NLP, Mathematics, Java, R",Associate,3,Technology,2024-12-18,2025-01-21,927,8.4,Algorithmic Solutions +AI02288,Research Scientist,233646,SGD,303740,EX,CT,Singapore,M,Singapore,0,"Statistics, SQL, Computer Vision, Linux, Deep Learning",Bachelor,12,Real Estate,2024-06-23,2024-08-03,2210,5.6,Digital Transformation LLC +AI02289,AI Specialist,180558,USD,180558,EX,PT,Denmark,M,Denmark,100,"GCP, Computer Vision, Java",PhD,10,Finance,2025-04-24,2025-05-31,1812,6.5,DeepTech Ventures +AI02290,Data Scientist,94791,EUR,80572,MI,CT,Germany,L,Germany,100,"TensorFlow, Statistics, Kubernetes, PyTorch, R",Master,3,Government,2024-04-08,2024-05-05,1246,6.5,Machine Intelligence Group +AI02291,Robotics Engineer,189914,USD,189914,EX,FT,United States,M,United States,0,"TensorFlow, Hadoop, Linux, Scala",Bachelor,17,Energy,2025-04-27,2025-06-30,2134,7.6,TechCorp Inc +AI02292,Machine Learning Researcher,96777,GBP,72583,MI,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, PyTorch, Java",Associate,3,Education,2024-07-05,2024-07-19,2490,5.5,Quantum Computing Inc +AI02293,AI Architect,29644,USD,29644,MI,PT,India,L,Norway,100,"Hadoop, Python, SQL, Deep Learning, Azure",Associate,4,Gaming,2024-03-20,2024-04-26,825,8.1,Future Systems +AI02294,Autonomous Systems Engineer,191246,USD,191246,EX,CT,United States,L,Kenya,50,"TensorFlow, Python, AWS, R, PyTorch",Bachelor,16,Technology,2025-02-23,2025-05-06,2386,5.7,AI Innovations +AI02295,Data Analyst,74691,USD,74691,MI,CT,South Korea,L,South Korea,50,"MLOps, Tableau, AWS, Linux",Associate,4,Telecommunications,2024-01-09,2024-03-01,1718,7.9,Autonomous Tech +AI02296,NLP Engineer,94955,JPY,10445050,EN,PT,Japan,L,Japan,0,"Spark, R, MLOps, Kubernetes, Azure",Bachelor,1,Automotive,2024-12-19,2025-01-14,2392,9.9,Smart Analytics +AI02297,Robotics Engineer,174201,USD,174201,SE,PT,Norway,M,Norway,50,"Java, Docker, Tableau, Statistics, MLOps",Bachelor,9,Real Estate,2025-02-05,2025-03-14,1951,7.3,DataVision Ltd +AI02298,Machine Learning Researcher,110906,CHF,99815,MI,FL,Switzerland,M,Switzerland,100,"Linux, Spark, Hadoop",PhD,3,Energy,2024-10-05,2024-12-01,2406,9.8,Cloud AI Solutions +AI02299,Research Scientist,129560,SGD,168428,SE,CT,Singapore,S,Singapore,100,"Scala, Java, MLOps",Master,9,Government,2024-08-05,2024-10-02,2483,9.5,Quantum Computing Inc +AI02300,Deep Learning Engineer,56552,AUD,76345,EN,PT,Australia,M,Australia,0,"MLOps, Python, GCP, SQL, Linux",Master,1,Retail,2024-09-01,2024-10-01,1431,8,Machine Intelligence Group +AI02301,AI Product Manager,82665,USD,82665,SE,FT,China,L,Finland,100,"Kubernetes, R, Java, SQL, NLP",Master,6,Gaming,2024-01-26,2024-02-13,1960,7,DataVision Ltd +AI02302,AI Specialist,57257,USD,57257,EN,CT,Ireland,S,Ireland,50,"Deep Learning, MLOps, Hadoop, GCP",Bachelor,0,Healthcare,2024-04-12,2024-04-27,1328,9.7,Machine Intelligence Group +AI02303,Deep Learning Engineer,156738,USD,156738,SE,FT,United States,S,United States,50,"Spark, Scala, Mathematics",PhD,8,Transportation,2024-07-31,2024-08-22,1295,6.4,Cognitive Computing +AI02304,Data Analyst,105347,EUR,89545,SE,CT,Netherlands,S,Netherlands,0,"Linux, R, MLOps",Bachelor,6,Consulting,2024-01-27,2024-03-05,2296,9.4,Advanced Robotics +AI02305,AI Product Manager,223454,JPY,24579940,EX,FT,Japan,S,Japan,100,"Computer Vision, R, PyTorch, GCP",Associate,19,Retail,2025-02-25,2025-03-17,510,5.4,DeepTech Ventures +AI02306,Machine Learning Engineer,72740,USD,72740,MI,PT,Finland,M,Netherlands,0,"GCP, Linux, MLOps, Tableau",Bachelor,3,Media,2025-01-08,2025-02-14,2001,5.1,Autonomous Tech +AI02307,Research Scientist,107622,USD,107622,MI,PT,Ireland,L,Ireland,50,"Git, SQL, PyTorch",Associate,4,Telecommunications,2024-03-06,2024-04-05,602,5.9,TechCorp Inc +AI02308,Principal Data Scientist,150523,EUR,127945,EX,CT,France,S,France,100,"Java, NLP, AWS",Master,18,Education,2024-11-20,2024-12-30,1927,6.8,Neural Networks Co +AI02309,Data Scientist,134704,EUR,114498,SE,FT,Austria,L,Malaysia,0,"Statistics, SQL, GCP, NLP",PhD,5,Manufacturing,2024-08-02,2024-08-27,2230,9.1,AI Innovations +AI02310,Research Scientist,51843,USD,51843,EN,CT,Finland,S,Sweden,0,"Kubernetes, Hadoop, Java, Computer Vision, Tableau",Master,1,Technology,2024-08-25,2024-10-16,797,7.3,TechCorp Inc +AI02311,AI Research Scientist,81429,EUR,69215,MI,FL,Germany,M,Germany,50,"Linux, Git, GCP, AWS, Spark",Master,3,Healthcare,2025-02-14,2025-03-02,2079,5.8,AI Innovations +AI02312,Deep Learning Engineer,208862,CAD,261078,EX,FL,Canada,L,Canada,50,"MLOps, Tableau, Git, Python, Scala",Associate,13,Gaming,2024-06-20,2024-07-25,1901,5.6,Neural Networks Co +AI02313,Machine Learning Engineer,90374,USD,90374,SE,FT,Israel,S,Israel,50,"R, Tableau, Azure, SQL",Master,7,Media,2024-07-10,2024-09-17,1887,9.5,Algorithmic Solutions +AI02314,AI Consultant,61463,EUR,52244,MI,PT,France,S,France,100,"Scala, Azure, MLOps, Python",Associate,3,Finance,2024-11-24,2025-01-11,2182,6,Machine Intelligence Group +AI02315,Deep Learning Engineer,109194,USD,109194,SE,CT,Finland,M,Finland,50,"R, Computer Vision, GCP",Associate,7,Technology,2024-04-01,2024-06-05,1756,7.6,Quantum Computing Inc +AI02316,AI Software Engineer,170066,USD,170066,EX,CT,South Korea,S,Thailand,0,"Data Visualization, Python, PyTorch",Associate,18,Education,2024-05-31,2024-07-18,835,6.1,Quantum Computing Inc +AI02317,Machine Learning Engineer,130203,USD,130203,SE,FL,Sweden,M,Sweden,100,"SQL, Statistics, R, MLOps, Hadoop",Bachelor,5,Education,2024-04-27,2024-06-22,1041,8.1,Algorithmic Solutions +AI02318,Robotics Engineer,92631,USD,92631,MI,CT,United States,M,United States,50,"AWS, Java, Python, GCP, Tableau",Associate,2,Transportation,2024-12-12,2025-01-11,2185,7,Cloud AI Solutions +AI02319,Data Analyst,124406,EUR,105745,SE,CT,France,S,France,50,"Computer Vision, PyTorch, Linux, AWS, SQL",PhD,6,Transportation,2024-01-15,2024-02-21,1041,9.3,Quantum Computing Inc +AI02320,Machine Learning Researcher,81253,USD,81253,MI,FL,Israel,M,Israel,0,"Azure, Git, NLP, Deep Learning, TensorFlow",Bachelor,4,Retail,2024-11-18,2025-01-13,2045,7.4,DeepTech Ventures +AI02321,Data Analyst,94671,EUR,80470,MI,CT,Germany,M,Germany,0,"PyTorch, Kubernetes, Mathematics",Associate,4,Automotive,2024-07-01,2024-08-11,1911,8.4,Smart Analytics +AI02322,Data Scientist,104689,USD,104689,MI,FL,Ireland,M,Ireland,50,"Tableau, Python, TensorFlow, Hadoop",Bachelor,2,Gaming,2024-01-02,2024-03-05,1563,5.7,DeepTech Ventures +AI02323,Research Scientist,124477,EUR,105805,SE,PT,Netherlands,L,Netherlands,100,"Java, R, SQL, Git",Associate,7,Government,2024-02-22,2024-03-17,655,8.5,Future Systems +AI02324,Machine Learning Engineer,225013,EUR,191261,EX,PT,Netherlands,S,Argentina,0,"SQL, Python, Java",PhD,17,Transportation,2024-08-18,2024-09-09,1668,7,Future Systems +AI02325,AI Specialist,57156,USD,57156,EN,PT,Finland,M,Finland,100,"GCP, MLOps, PyTorch",PhD,0,Technology,2024-10-24,2024-12-09,1115,8.4,Machine Intelligence Group +AI02326,Robotics Engineer,75630,USD,75630,MI,PT,Israel,S,Israel,100,"NLP, Mathematics, MLOps, Docker",Associate,2,Finance,2024-11-30,2025-02-07,1371,5.3,Cognitive Computing +AI02327,Data Scientist,193038,USD,193038,EX,CT,Israel,M,Israel,50,"GCP, Linux, MLOps, Mathematics, AWS",PhD,12,Automotive,2024-08-30,2024-10-30,2331,8.4,Predictive Systems +AI02328,ML Ops Engineer,354091,USD,354091,EX,FT,Norway,L,Thailand,0,"Java, Scala, GCP, Mathematics, MLOps",Master,15,Gaming,2024-05-26,2024-06-24,2237,9.6,Autonomous Tech +AI02329,Computer Vision Engineer,116471,CAD,145589,MI,FL,Canada,L,Canada,50,"Statistics, Linux, Azure, Kubernetes, Computer Vision",Master,4,Real Estate,2025-03-04,2025-05-13,1445,6,Neural Networks Co +AI02330,Computer Vision Engineer,52386,EUR,44528,EN,PT,France,M,Thailand,100,"Python, Kubernetes, Data Visualization, TensorFlow",Master,1,Manufacturing,2025-04-27,2025-06-09,1561,8.3,Cloud AI Solutions +AI02331,AI Specialist,23595,USD,23595,EN,CT,China,S,China,100,"NLP, Python, TensorFlow",Associate,1,Retail,2024-08-13,2024-10-13,1556,7.7,Predictive Systems +AI02332,AI Research Scientist,123617,AUD,166883,EX,FL,Australia,S,Australia,0,"MLOps, Mathematics, Python, TensorFlow, Git",Associate,17,Transportation,2024-07-07,2024-09-07,838,5.6,Quantum Computing Inc +AI02333,Robotics Engineer,294173,USD,294173,EX,FT,United States,L,Switzerland,0,"SQL, GCP, Tableau, TensorFlow, Python",Master,16,Media,2025-01-25,2025-02-22,1739,5.6,DeepTech Ventures +AI02334,Data Engineer,158889,USD,158889,SE,FT,United States,L,Netherlands,100,"AWS, Hadoop, Deep Learning, Mathematics, SQL",Master,9,Technology,2024-01-20,2024-03-27,1615,6.4,Future Systems +AI02335,Research Scientist,92187,USD,92187,SE,PT,Israel,S,Spain,0,"Data Visualization, Computer Vision, GCP, Scala, NLP",PhD,8,Telecommunications,2024-08-25,2024-09-22,1474,5.5,Quantum Computing Inc +AI02336,ML Ops Engineer,266476,EUR,226505,EX,PT,France,L,France,0,"Azure, Hadoop, Data Visualization, Spark",Bachelor,18,Gaming,2024-02-22,2024-04-22,886,8.2,Autonomous Tech +AI02337,Data Scientist,64951,EUR,55208,EN,FL,Netherlands,S,Austria,0,"PyTorch, Kubernetes, Java, Azure, MLOps",Master,1,Media,2024-03-15,2024-04-23,1222,9.2,DeepTech Ventures +AI02338,AI Research Scientist,173215,EUR,147233,EX,CT,Netherlands,M,Netherlands,50,"Computer Vision, AWS, Python, TensorFlow, Data Visualization",PhD,19,Telecommunications,2024-02-15,2024-03-15,733,5.1,TechCorp Inc +AI02339,Machine Learning Researcher,114900,USD,114900,MI,PT,Denmark,M,Indonesia,0,"Python, Kubernetes, Git",Bachelor,3,Retail,2024-12-17,2025-02-27,1669,9.5,Future Systems +AI02340,AI Consultant,65123,USD,65123,MI,FT,Finland,S,Finland,0,"SQL, R, AWS, Python",PhD,3,Manufacturing,2025-02-10,2025-03-22,1882,9.2,Smart Analytics +AI02341,AI Consultant,176135,EUR,149715,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Deep Learning, SQL, NLP",Bachelor,17,Automotive,2024-02-18,2024-03-21,512,9.6,Neural Networks Co +AI02342,AI Specialist,128894,USD,128894,EX,FL,South Korea,M,South Korea,100,"Scala, AWS, MLOps, Data Visualization, Statistics",Bachelor,15,Telecommunications,2024-01-24,2024-03-25,2001,8.2,TechCorp Inc +AI02343,AI Specialist,140129,CAD,175161,EX,CT,Canada,M,Canada,0,"Java, Python, GCP",Bachelor,15,Finance,2024-03-19,2024-05-25,1796,6.1,AI Innovations +AI02344,Head of AI,211366,EUR,179661,EX,CT,Austria,S,Austria,100,"R, SQL, Kubernetes, Git, Tableau",Associate,17,Consulting,2025-03-30,2025-04-14,1025,6.6,Future Systems +AI02345,Data Scientist,89067,GBP,66800,MI,FT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Tableau, Git",Master,2,Government,2024-03-23,2024-06-03,1133,8,Predictive Systems +AI02346,Deep Learning Engineer,120608,AUD,162821,SE,FL,Australia,S,Spain,100,"Python, TensorFlow, Data Visualization",Master,9,Healthcare,2024-10-23,2024-11-26,2358,5.9,Advanced Robotics +AI02347,AI Research Scientist,173641,CAD,217051,EX,FL,Canada,S,Canada,0,"Python, Linux, Scala, TensorFlow, R",Bachelor,11,Healthcare,2025-01-20,2025-02-28,2102,5.6,DeepTech Ventures +AI02348,AI Research Scientist,93978,JPY,10337580,MI,PT,Japan,L,Austria,50,"Python, Git, Kubernetes, TensorFlow, Scala",PhD,2,Manufacturing,2025-02-06,2025-03-13,1541,5,Cognitive Computing +AI02349,Data Analyst,291451,CHF,262306,EX,PT,Switzerland,S,Switzerland,100,"Python, TensorFlow, PyTorch, SQL, Hadoop",Associate,18,Education,2024-10-05,2024-12-14,2356,5.5,Cognitive Computing +AI02350,Data Engineer,115058,USD,115058,MI,FL,Denmark,L,Denmark,100,"Scala, NLP, Python, Deep Learning",Master,4,Consulting,2024-03-26,2024-05-10,2092,7.1,Predictive Systems +AI02351,Head of AI,121394,USD,121394,MI,PT,Norway,M,Norway,100,"Linux, Kubernetes, MLOps, PyTorch",PhD,4,Gaming,2024-10-18,2024-12-23,1538,6.8,DeepTech Ventures +AI02352,AI Specialist,51431,USD,51431,MI,CT,China,L,China,50,"Deep Learning, Git, Mathematics, Data Visualization, R",Bachelor,4,Manufacturing,2024-05-31,2024-06-17,2302,7.1,Smart Analytics +AI02353,Robotics Engineer,90064,USD,90064,MI,FT,United States,M,United States,0,"Python, TensorFlow, Computer Vision, Kubernetes",Associate,3,Real Estate,2025-01-29,2025-03-28,1740,8.5,Future Systems +AI02354,Data Scientist,120867,JPY,13295370,SE,PT,Japan,S,Australia,50,"Java, R, Tableau",Associate,6,Retail,2024-03-31,2024-04-29,2008,5.7,Cloud AI Solutions +AI02355,Data Engineer,51975,EUR,44179,EN,FT,Netherlands,S,South Africa,100,"Git, Docker, MLOps",PhD,0,Retail,2024-03-21,2024-04-29,1266,5.5,Cognitive Computing +AI02356,AI Product Manager,125213,EUR,106431,SE,FL,Netherlands,S,Netherlands,50,"R, AWS, Azure",Associate,7,Manufacturing,2024-07-26,2024-09-20,1233,9.9,Machine Intelligence Group +AI02357,AI Specialist,73632,EUR,62587,EN,FL,Netherlands,L,Netherlands,100,"Git, Kubernetes, Spark",Master,0,Automotive,2024-09-23,2024-10-10,2163,7.7,DeepTech Ventures +AI02358,AI Consultant,147336,USD,147336,SE,CT,Israel,L,Israel,50,"Hadoop, Scala, PyTorch, TensorFlow, Python",Master,9,Healthcare,2024-03-12,2024-05-03,2452,8.1,Cloud AI Solutions +AI02359,Data Engineer,113940,JPY,12533400,SE,FL,Japan,S,France,0,"Java, AWS, Linux, GCP, Docker",Associate,7,Transportation,2024-01-28,2024-03-21,1981,6.4,TechCorp Inc +AI02360,Robotics Engineer,115793,EUR,98424,SE,PT,Netherlands,M,Austria,0,"GCP, Statistics, Hadoop",Associate,5,Retail,2025-04-16,2025-06-07,2490,6.9,Digital Transformation LLC +AI02361,Research Scientist,385250,CHF,346725,EX,CT,Switzerland,L,China,0,"Kubernetes, SQL, Docker, Java, Python",Associate,19,Retail,2024-12-31,2025-02-20,2183,6.5,Smart Analytics +AI02362,ML Ops Engineer,97449,EUR,82832,EN,FT,Netherlands,L,Belgium,50,"Linux, Tableau, Python, Deep Learning, TensorFlow",Associate,0,Manufacturing,2024-02-11,2024-03-10,665,5.2,Machine Intelligence Group +AI02363,Autonomous Systems Engineer,158205,EUR,134474,EX,CT,France,L,Mexico,100,"Scala, Linux, Docker, Statistics",Associate,12,Healthcare,2024-08-12,2024-08-27,656,8.8,Predictive Systems +AI02364,Machine Learning Researcher,227940,SGD,296322,EX,FL,Singapore,L,Finland,0,"GCP, Java, SQL",Associate,11,Consulting,2024-09-27,2024-11-13,1038,9.3,Smart Analytics +AI02365,AI Specialist,82774,USD,82774,MI,PT,Israel,L,Sweden,50,"TensorFlow, Java, Deep Learning, Spark",Associate,3,Technology,2024-02-27,2024-04-01,1190,7.9,TechCorp Inc +AI02366,Data Engineer,151102,CHF,135992,SE,CT,Switzerland,S,China,0,"SQL, TensorFlow, AWS, NLP",Associate,6,Real Estate,2024-12-19,2025-01-24,1992,8.7,Advanced Robotics +AI02367,Computer Vision Engineer,135010,USD,135010,MI,CT,Norway,M,Ireland,50,"Statistics, AWS, PyTorch, Data Visualization, Spark",PhD,4,Retail,2025-01-01,2025-02-03,589,6.2,Algorithmic Solutions +AI02368,Head of AI,99493,JPY,10944230,MI,FL,Japan,S,Japan,100,"Deep Learning, Tableau, SQL",PhD,2,Energy,2024-06-25,2024-07-22,2338,8.6,TechCorp Inc +AI02369,AI Product Manager,104842,GBP,78632,MI,CT,United Kingdom,L,Australia,50,"Azure, Scala, AWS, TensorFlow, Statistics",Master,2,Healthcare,2025-03-15,2025-05-26,1211,8.6,Cloud AI Solutions +AI02370,Head of AI,77587,USD,77587,EN,FT,Sweden,L,Estonia,100,"TensorFlow, Linux, R",Master,0,Manufacturing,2024-05-06,2024-06-05,2238,8,Smart Analytics +AI02371,ML Ops Engineer,94792,SGD,123230,MI,FL,Singapore,L,Singapore,50,"AWS, MLOps, Python, TensorFlow",Master,4,Transportation,2024-03-06,2024-05-11,695,6.8,Autonomous Tech +AI02372,AI Consultant,170382,EUR,144825,SE,PT,Netherlands,L,Netherlands,0,"Statistics, Scala, Java",PhD,6,Manufacturing,2024-12-09,2025-01-30,1927,7.3,Autonomous Tech +AI02373,AI Consultant,69714,USD,69714,EN,PT,Finland,M,Switzerland,100,"Scala, Linux, Python",Associate,0,Manufacturing,2024-04-15,2024-06-03,1972,5.9,Quantum Computing Inc +AI02374,AI Specialist,61848,USD,61848,EN,FT,Ireland,L,Ireland,100,"Hadoop, Data Visualization, Python, PyTorch, Deep Learning",PhD,0,Real Estate,2025-01-10,2025-03-05,651,8,Quantum Computing Inc +AI02375,Computer Vision Engineer,65280,EUR,55488,EN,CT,Netherlands,M,Netherlands,100,"Azure, PyTorch, Spark, SQL",PhD,0,Retail,2024-11-04,2024-12-08,1890,6.5,Neural Networks Co +AI02376,Deep Learning Engineer,67421,USD,67421,EN,PT,United States,S,Sweden,50,"Docker, Tableau, Kubernetes, SQL, GCP",PhD,0,Real Estate,2025-02-15,2025-04-10,2051,8.7,Advanced Robotics +AI02377,Data Engineer,276843,USD,276843,EX,FL,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, GCP",PhD,11,Retail,2024-08-10,2024-09-09,740,6.2,Cognitive Computing +AI02378,Computer Vision Engineer,86366,USD,86366,MI,CT,Norway,S,Norway,0,"Statistics, AWS, Kubernetes, Computer Vision, GCP",PhD,4,Education,2024-01-16,2024-03-28,1664,7.7,DataVision Ltd +AI02379,AI Specialist,113593,SGD,147671,SE,PT,Singapore,M,Singapore,100,"SQL, Data Visualization, Tableau, TensorFlow",PhD,9,Real Estate,2024-04-06,2024-06-16,1375,6,Neural Networks Co +AI02380,Autonomous Systems Engineer,248477,USD,248477,EX,CT,United States,L,Austria,100,"Git, TensorFlow, Linux, NLP, Docker",Associate,17,Telecommunications,2024-08-08,2024-08-28,2245,7.4,Machine Intelligence Group +AI02381,Head of AI,140516,USD,140516,SE,FL,Israel,M,Israel,0,"Python, Kubernetes, Tableau, AWS, Computer Vision",Bachelor,5,Real Estate,2024-02-06,2024-04-01,2138,5.8,Algorithmic Solutions +AI02382,ML Ops Engineer,101660,USD,101660,MI,CT,Israel,M,Israel,50,"Tableau, GCP, Hadoop",Master,4,Telecommunications,2025-01-08,2025-02-01,1455,5.1,AI Innovations +AI02383,NLP Engineer,59401,AUD,80191,EN,PT,Australia,S,Australia,0,"Statistics, Python, MLOps, Data Visualization",Associate,1,Real Estate,2025-02-22,2025-03-11,2022,6.2,DataVision Ltd +AI02384,Machine Learning Researcher,282872,CHF,254585,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, SQL, Mathematics",Master,16,Consulting,2024-10-20,2024-11-14,1004,7.7,TechCorp Inc +AI02385,AI Consultant,79004,USD,79004,EN,FL,Denmark,S,Denmark,50,"R, PyTorch, Mathematics",Bachelor,1,Government,2024-10-07,2024-11-22,1888,9,Digital Transformation LLC +AI02386,Autonomous Systems Engineer,90214,USD,90214,EX,CT,China,L,China,100,"Java, PyTorch, SQL, NLP",PhD,14,Healthcare,2024-11-23,2024-12-08,1536,6.3,Machine Intelligence Group +AI02387,NLP Engineer,177517,USD,177517,EX,PT,Denmark,S,Denmark,0,"PyTorch, Tableau, Java, GCP, R",PhD,10,Consulting,2024-05-02,2024-06-22,1170,9.2,TechCorp Inc +AI02388,Research Scientist,138067,USD,138067,SE,PT,Denmark,S,Denmark,100,"Linux, GCP, R, Mathematics",PhD,6,Automotive,2024-05-19,2024-07-17,1830,5.3,Predictive Systems +AI02389,AI Product Manager,175216,EUR,148934,SE,FL,Germany,L,Austria,100,"Linux, Statistics, Data Visualization",Bachelor,6,Retail,2024-10-24,2024-12-14,909,7.9,Quantum Computing Inc +AI02390,Machine Learning Engineer,67149,EUR,57077,EN,PT,France,M,France,0,"Data Visualization, Kubernetes, Spark",Master,0,Telecommunications,2024-12-10,2025-02-06,840,8.6,Advanced Robotics +AI02391,AI Consultant,65086,USD,65086,EN,CT,Sweden,L,Sweden,0,"Data Visualization, PyTorch, Kubernetes, Azure",Associate,1,Government,2024-11-10,2025-01-22,1761,8.1,Predictive Systems +AI02392,Principal Data Scientist,97236,USD,97236,MI,PT,Denmark,S,Ireland,0,"Spark, SQL, Computer Vision",PhD,3,Manufacturing,2024-10-15,2024-12-04,2272,6.9,Advanced Robotics +AI02393,Data Analyst,33499,USD,33499,MI,PT,India,L,India,50,"Data Visualization, R, Linux, GCP",Bachelor,2,Energy,2025-04-03,2025-05-15,1644,8.9,Quantum Computing Inc +AI02394,Data Analyst,83973,EUR,71377,MI,FL,France,S,France,0,"GCP, SQL, Git",PhD,2,Energy,2024-04-15,2024-06-18,2438,7.1,Neural Networks Co +AI02395,AI Software Engineer,77052,USD,77052,MI,CT,Ireland,S,Ireland,50,"GCP, Hadoop, TensorFlow, Deep Learning, AWS",Associate,2,Education,2024-10-08,2024-11-07,1146,9.3,Autonomous Tech +AI02396,NLP Engineer,121702,SGD,158213,SE,FT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Kubernetes, Data Visualization, Java",Bachelor,5,Transportation,2024-07-15,2024-08-09,1798,6.5,Advanced Robotics +AI02397,Data Scientist,226834,USD,226834,EX,CT,Norway,L,Norway,0,"PyTorch, SQL, NLP, R",Master,14,Finance,2024-11-19,2025-01-27,1368,8.2,DataVision Ltd +AI02398,AI Specialist,269663,GBP,202247,EX,FL,United Kingdom,L,Singapore,100,"Mathematics, Git, SQL, TensorFlow",Master,13,Government,2024-08-10,2024-09-15,1189,8.7,AI Innovations +AI02399,ML Ops Engineer,121309,USD,121309,SE,FT,Sweden,L,Sweden,100,"SQL, Deep Learning, Tableau",PhD,7,Real Estate,2024-09-11,2024-10-01,1599,7.5,AI Innovations +AI02400,Machine Learning Researcher,81603,USD,81603,MI,FT,South Korea,S,South Korea,100,"Python, Mathematics, Data Visualization, Scala, Azure",Bachelor,2,Consulting,2025-04-19,2025-06-11,927,9.5,Predictive Systems +AI02401,AI Architect,101849,USD,101849,MI,PT,Denmark,S,France,0,"Python, Azure, TensorFlow",PhD,2,Telecommunications,2024-07-16,2024-09-24,546,8.6,Algorithmic Solutions +AI02402,Deep Learning Engineer,184180,JPY,20259800,SE,PT,Japan,L,Ukraine,0,"Tableau, TensorFlow, GCP, Data Visualization",PhD,9,Automotive,2024-11-15,2024-12-28,2001,7.7,Algorithmic Solutions +AI02403,AI Architect,117248,USD,117248,EN,CT,Denmark,L,Denmark,100,"Docker, Kubernetes, Statistics, Tableau, Python",PhD,0,Education,2024-07-20,2024-08-07,624,7.9,Future Systems +AI02404,Machine Learning Researcher,95725,JPY,10529750,MI,CT,Japan,S,Japan,0,"AWS, Linux, Kubernetes, Data Visualization",Bachelor,4,Media,2025-03-27,2025-05-05,720,6.6,Smart Analytics +AI02405,Computer Vision Engineer,101075,EUR,85914,MI,CT,Germany,M,Germany,0,"TensorFlow, Statistics, Spark, Linux",Bachelor,2,Healthcare,2024-05-19,2024-06-18,2308,5.7,Autonomous Tech +AI02406,AI Architect,138619,CAD,173274,SE,PT,Canada,M,Canada,50,"Kubernetes, PyTorch, Linux, AWS",Bachelor,9,Telecommunications,2025-01-01,2025-01-15,690,7.3,Machine Intelligence Group +AI02407,Data Engineer,138645,AUD,187171,SE,CT,Australia,L,Australia,100,"Deep Learning, Mathematics, PyTorch",Bachelor,5,Finance,2024-10-28,2024-12-18,1590,9.7,TechCorp Inc +AI02408,AI Product Manager,55621,EUR,47278,EN,CT,Netherlands,M,Netherlands,50,"R, Python, Computer Vision, Deep Learning",Bachelor,1,Healthcare,2025-02-04,2025-04-04,684,7.8,Quantum Computing Inc +AI02409,Head of AI,135303,EUR,115008,SE,FL,Germany,L,Germany,100,"AWS, Git, SQL, Docker, Statistics",Bachelor,7,Retail,2024-09-14,2024-09-29,2317,7.9,Neural Networks Co +AI02410,Data Scientist,172436,USD,172436,SE,FT,United States,L,United States,50,"Tableau, Hadoop, Python",Associate,6,Real Estate,2025-03-07,2025-03-31,1364,5.4,Neural Networks Co +AI02411,Data Scientist,152590,AUD,205997,EX,PT,Australia,M,Australia,50,"GCP, Python, NLP, Computer Vision, Data Visualization",Bachelor,17,Finance,2024-08-12,2024-09-02,1932,9.5,DataVision Ltd +AI02412,AI Specialist,110412,USD,110412,SE,PT,Finland,L,Austria,50,"Docker, Spark, Hadoop, Git, SQL",Master,5,Healthcare,2024-03-01,2024-03-17,2307,8.4,Autonomous Tech +AI02413,Data Analyst,98339,GBP,73754,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, Python, Java, Linux",Bachelor,8,Retail,2024-05-09,2024-05-30,1819,7.5,Quantum Computing Inc +AI02414,Machine Learning Engineer,68002,USD,68002,EN,FT,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, Python",Bachelor,0,Consulting,2024-10-04,2024-11-29,1489,5.7,Cloud AI Solutions +AI02415,Data Engineer,187944,JPY,20673840,EX,CT,Japan,S,Germany,50,"Python, SQL, TensorFlow",Associate,10,Retail,2024-08-02,2024-08-29,1862,9.4,Cognitive Computing +AI02416,Autonomous Systems Engineer,50316,USD,50316,EN,CT,Sweden,S,France,100,"Linux, Docker, Data Visualization, PyTorch, Deep Learning",Bachelor,1,Education,2024-02-10,2024-04-07,1983,9.2,Neural Networks Co +AI02417,Data Analyst,104865,USD,104865,MI,FT,Denmark,M,Denmark,100,"NLP, Python, Java, Statistics",Master,2,Gaming,2024-09-02,2024-10-28,608,7.7,Cloud AI Solutions +AI02418,Deep Learning Engineer,79547,EUR,67615,MI,FL,France,S,France,50,"Statistics, Java, Data Visualization, Computer Vision, Linux",Bachelor,4,Government,2024-06-07,2024-08-17,2315,7.9,Future Systems +AI02419,Data Analyst,48817,USD,48817,EN,PT,Israel,S,Singapore,50,"Linux, R, Git, Kubernetes, Statistics",Bachelor,0,Energy,2024-01-02,2024-02-19,2161,8.2,Algorithmic Solutions +AI02420,Deep Learning Engineer,60358,EUR,51304,EN,FT,France,M,France,50,"Git, Scala, Tableau",PhD,1,Government,2025-01-24,2025-03-09,2400,8.9,DeepTech Ventures +AI02421,Data Scientist,36483,USD,36483,EN,CT,China,M,China,100,"AWS, Java, Tableau, Python",Bachelor,1,Real Estate,2024-12-19,2025-02-03,2044,7,Predictive Systems +AI02422,AI Specialist,34602,USD,34602,MI,CT,India,S,India,50,"Scala, TensorFlow, MLOps, Spark, Deep Learning",Bachelor,4,Consulting,2025-02-05,2025-02-21,2409,9.4,Advanced Robotics +AI02423,Data Scientist,183641,CHF,165277,SE,FL,Switzerland,S,Ukraine,50,"Mathematics, PyTorch, Spark, Scala, AWS",Master,8,Government,2025-01-11,2025-02-04,2248,9.1,AI Innovations +AI02424,Principal Data Scientist,137861,USD,137861,MI,CT,Denmark,M,Denmark,0,"Scala, Mathematics, Computer Vision, Deep Learning",Associate,4,Technology,2024-05-27,2024-07-17,988,8,Cloud AI Solutions +AI02425,Data Engineer,55797,EUR,47427,EN,PT,France,S,France,100,"GCP, Scala, Spark, Python",PhD,0,Manufacturing,2024-06-26,2024-08-06,2194,9.5,DeepTech Ventures +AI02426,Principal Data Scientist,60447,CAD,75559,EN,CT,Canada,L,Canada,50,"Scala, Tableau, Azure, Spark, SQL",Master,1,Retail,2024-03-05,2024-04-25,2068,7,DataVision Ltd +AI02427,Head of AI,188935,EUR,160595,EX,FT,Austria,L,Austria,0,"Java, AWS, R",PhD,14,Retail,2025-01-29,2025-03-12,1647,5,AI Innovations +AI02428,Data Engineer,74196,USD,74196,EX,FL,India,L,India,50,"TensorFlow, Python, Git, Hadoop",Associate,19,Education,2024-03-06,2024-04-22,910,8.1,Machine Intelligence Group +AI02429,AI Architect,171635,CHF,154472,SE,FL,Switzerland,S,Switzerland,100,"R, Tableau, Spark, SQL, Computer Vision",Bachelor,9,Gaming,2024-07-23,2024-09-07,2310,6.8,Neural Networks Co +AI02430,AI Architect,71217,EUR,60534,EN,CT,Netherlands,M,Netherlands,0,"Python, NLP, TensorFlow, AWS",Master,0,Government,2024-06-15,2024-07-02,2397,5.9,Quantum Computing Inc +AI02431,Data Scientist,55275,GBP,41456,EN,CT,United Kingdom,S,United Kingdom,0,"PyTorch, NLP, Java, Python, Docker",Bachelor,1,Technology,2025-04-02,2025-06-08,933,6.2,Autonomous Tech +AI02432,Machine Learning Engineer,63318,USD,63318,EN,CT,Ireland,S,Vietnam,50,"SQL, GCP, PyTorch, Kubernetes",Associate,1,Finance,2025-01-26,2025-02-25,937,9.7,Algorithmic Solutions +AI02433,AI Specialist,102417,USD,102417,MI,CT,South Korea,L,South Korea,50,"Linux, SQL, PyTorch",Master,2,Transportation,2024-08-15,2024-09-01,2253,8.2,AI Innovations +AI02434,Deep Learning Engineer,145507,USD,145507,SE,FT,Ireland,L,Ireland,0,"Deep Learning, Python, NLP, GCP, Git",Master,8,Real Estate,2024-07-08,2024-08-04,1577,8,Neural Networks Co +AI02435,Machine Learning Engineer,70110,EUR,59594,EN,FL,Germany,S,Finland,0,"Kubernetes, Python, Data Visualization",Master,1,Education,2025-01-01,2025-02-12,680,5.1,Autonomous Tech +AI02436,AI Research Scientist,171213,USD,171213,EX,CT,South Korea,M,South Korea,0,"Git, Docker, Deep Learning, Kubernetes, Statistics",PhD,10,Retail,2025-01-06,2025-02-28,731,5.8,Autonomous Tech +AI02437,Robotics Engineer,84500,USD,84500,MI,PT,Sweden,M,Turkey,0,"Spark, Python, TensorFlow, SQL",Associate,4,Consulting,2025-01-15,2025-03-22,1603,9.2,Cognitive Computing +AI02438,Machine Learning Researcher,156224,USD,156224,EX,FL,Israel,S,Israel,0,"Data Visualization, NLP, Java, R, Mathematics",Bachelor,15,Telecommunications,2024-07-07,2024-09-17,2135,9.7,Predictive Systems +AI02439,Research Scientist,92098,USD,92098,MI,FL,Sweden,S,Sweden,0,"TensorFlow, Mathematics, MLOps, Computer Vision",Associate,3,Retail,2025-04-23,2025-05-20,825,5.1,Future Systems +AI02440,Principal Data Scientist,167891,USD,167891,EX,FT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, Deep Learning",Master,15,Government,2024-03-16,2024-05-28,2352,7,Cognitive Computing +AI02441,Data Engineer,101538,SGD,131999,MI,CT,Singapore,S,France,0,"Kubernetes, Data Visualization, Python, Statistics, AWS",PhD,4,Telecommunications,2024-08-01,2024-10-07,2037,5.9,Machine Intelligence Group +AI02442,Computer Vision Engineer,156055,CAD,195069,SE,PT,Canada,L,Canada,100,"Python, SQL, TensorFlow, GCP",PhD,9,Consulting,2024-10-23,2024-12-21,865,9.5,DeepTech Ventures +AI02443,Principal Data Scientist,97531,EUR,82901,MI,PT,Germany,S,Malaysia,50,"Git, Scala, Python",PhD,4,Healthcare,2025-02-13,2025-03-29,1379,6.9,AI Innovations +AI02444,Deep Learning Engineer,66041,USD,66041,EN,CT,Sweden,S,Sweden,0,"GCP, Kubernetes, Docker",Associate,0,Telecommunications,2024-08-16,2024-10-25,746,7.9,AI Innovations +AI02445,Principal Data Scientist,78618,EUR,66825,EN,FL,Germany,M,Turkey,50,"Python, Azure, Scala, Hadoop",Master,1,Education,2025-04-25,2025-05-29,633,8.3,Advanced Robotics +AI02446,Data Scientist,63321,JPY,6965310,EN,CT,Japan,S,Japan,0,"Python, TensorFlow, PyTorch",Associate,1,Government,2024-05-03,2024-07-04,2329,8.4,Autonomous Tech +AI02447,Machine Learning Researcher,171661,AUD,231742,EX,CT,Australia,S,Australia,50,"PyTorch, Hadoop, Computer Vision",Bachelor,14,Government,2024-04-17,2024-06-06,2090,5.7,DeepTech Ventures +AI02448,Data Engineer,65836,CAD,82295,EN,CT,Canada,S,Luxembourg,100,"Scala, Statistics, PyTorch",Master,0,Energy,2025-03-21,2025-04-14,2090,5.3,Quantum Computing Inc +AI02449,Machine Learning Engineer,27320,USD,27320,EN,CT,India,L,India,0,"Python, Kubernetes, Tableau, PyTorch",Bachelor,0,Energy,2025-04-07,2025-06-15,1130,7.5,Cognitive Computing +AI02450,AI Specialist,135041,EUR,114785,SE,CT,Germany,S,Germany,100,"SQL, Kubernetes, Statistics, Hadoop",Associate,5,Energy,2024-07-20,2024-08-29,1002,5.8,Autonomous Tech +AI02451,AI Specialist,113501,USD,113501,SE,PT,United States,S,United States,0,"Spark, Docker, Python, Kubernetes",Master,5,Automotive,2024-01-29,2024-02-29,2412,9.8,Smart Analytics +AI02452,NLP Engineer,84009,USD,84009,EN,FT,Denmark,S,Denmark,50,"Kubernetes, R, Azure, AWS",Master,1,Retail,2024-12-07,2025-02-15,1122,6.1,TechCorp Inc +AI02453,Data Scientist,202038,CAD,252548,EX,FT,Canada,S,Canada,0,"Tableau, TensorFlow, Scala",Associate,17,Government,2024-10-08,2024-10-26,2244,7.4,Cloud AI Solutions +AI02454,AI Research Scientist,157447,USD,157447,SE,PT,Norway,M,Nigeria,0,"R, Python, Git, NLP, Java",Master,5,Healthcare,2024-02-18,2024-04-03,2450,8.4,Future Systems +AI02455,Research Scientist,69117,USD,69117,EX,FL,China,S,South Korea,50,"Scala, Docker, Kubernetes",PhD,16,Government,2025-04-12,2025-05-04,517,8.7,Neural Networks Co +AI02456,AI Consultant,85916,SGD,111691,MI,FT,Singapore,S,Ireland,50,"Scala, Python, Data Visualization, NLP",Associate,2,Gaming,2024-12-19,2025-02-21,2108,5.7,Predictive Systems +AI02457,NLP Engineer,208144,EUR,176922,EX,FL,France,S,France,100,"Hadoop, MLOps, Spark, Git",Master,16,Technology,2024-06-01,2024-07-03,922,9.3,Machine Intelligence Group +AI02458,Computer Vision Engineer,201845,CAD,252306,EX,FT,Canada,L,Canada,100,"Data Visualization, Kubernetes, Scala, AWS, TensorFlow",Associate,11,Energy,2024-11-29,2025-02-05,1453,6.8,Neural Networks Co +AI02459,AI Software Engineer,70992,AUD,95839,EN,FL,Australia,S,Austria,0,"R, Data Visualization, AWS, Scala",PhD,0,Media,2024-05-01,2024-05-20,1609,6.8,DeepTech Ventures +AI02460,Computer Vision Engineer,78762,EUR,66948,MI,FL,Netherlands,S,Malaysia,50,"AWS, Azure, Docker, Hadoop, TensorFlow",Associate,4,Gaming,2024-06-08,2024-06-26,1864,7.5,Advanced Robotics +AI02461,Autonomous Systems Engineer,124250,USD,124250,SE,CT,South Korea,M,United Kingdom,0,"Linux, PyTorch, Kubernetes",PhD,9,Finance,2025-04-16,2025-05-27,1031,7.5,Future Systems +AI02462,AI Architect,79482,USD,79482,EN,PT,Norway,M,South Korea,0,"Computer Vision, Spark, Linux, Deep Learning",Associate,0,Healthcare,2024-09-30,2024-10-14,1803,5.6,Neural Networks Co +AI02463,Machine Learning Engineer,139133,EUR,118263,SE,CT,France,M,France,0,"Hadoop, SQL, Computer Vision, PyTorch",Master,6,Energy,2024-09-11,2024-10-28,1604,7.3,Digital Transformation LLC +AI02464,Computer Vision Engineer,220326,USD,220326,EX,FT,Norway,L,Norway,100,"PyTorch, Linux, TensorFlow, Azure, Hadoop",Master,10,Retail,2025-03-12,2025-05-11,1484,5.1,Autonomous Tech +AI02465,Machine Learning Researcher,56936,USD,56936,SE,FT,China,L,China,0,"Spark, Python, Tableau",Associate,7,Automotive,2024-09-14,2024-11-24,2347,6.1,Machine Intelligence Group +AI02466,Data Scientist,186597,SGD,242576,EX,FL,Singapore,M,Singapore,100,"Git, PyTorch, TensorFlow, Hadoop",PhD,12,Manufacturing,2024-09-12,2024-10-28,796,8.1,Quantum Computing Inc +AI02467,Autonomous Systems Engineer,98276,EUR,83535,MI,CT,Netherlands,M,South Korea,100,"Computer Vision, Hadoop, SQL",Associate,4,Finance,2024-09-29,2024-12-04,1681,7.8,Quantum Computing Inc +AI02468,Machine Learning Researcher,265980,EUR,226083,EX,FT,Netherlands,M,Netherlands,0,"Azure, Kubernetes, Tableau, Computer Vision, Statistics",Master,18,Consulting,2025-01-20,2025-02-15,1629,7.3,Neural Networks Co +AI02469,Principal Data Scientist,28831,USD,28831,EN,CT,China,S,Kenya,0,"Computer Vision, SQL, PyTorch, Docker, TensorFlow",Master,1,Energy,2024-09-23,2024-11-10,1887,7,DeepTech Ventures +AI02470,Machine Learning Engineer,41710,USD,41710,SE,FT,India,S,Mexico,100,"Docker, Java, Hadoop",Master,5,Finance,2024-06-11,2024-07-17,1648,9.4,Advanced Robotics +AI02471,AI Software Engineer,183499,JPY,20184890,SE,FT,Japan,L,Japan,0,"NLP, Git, Python, Java",Associate,8,Technology,2024-05-07,2024-06-21,1918,6.6,Cognitive Computing +AI02472,NLP Engineer,106203,CAD,132754,SE,PT,Canada,S,Canada,50,"Scala, Hadoop, Tableau, SQL, Deep Learning",Associate,6,Telecommunications,2024-06-02,2024-06-25,869,8.1,DataVision Ltd +AI02473,AI Architect,165971,USD,165971,EX,FL,Denmark,S,Denmark,0,"Docker, Hadoop, GCP",Associate,16,Consulting,2024-02-24,2024-05-06,584,7.4,Neural Networks Co +AI02474,Deep Learning Engineer,124861,USD,124861,MI,PT,Denmark,L,Denmark,0,"Kubernetes, Deep Learning, Scala, Java",Associate,4,Retail,2025-01-28,2025-04-11,2295,6,Smart Analytics +AI02475,AI Research Scientist,90314,USD,90314,MI,CT,Ireland,S,Ireland,0,"MLOps, NLP, PyTorch, Kubernetes",Associate,2,Education,2024-01-01,2024-01-18,1471,5.2,Cognitive Computing +AI02476,Data Engineer,82549,USD,82549,EN,PT,Denmark,S,Denmark,100,"Tableau, Java, SQL, Computer Vision, Kubernetes",Associate,0,Manufacturing,2024-03-05,2024-04-14,2066,6.2,DataVision Ltd +AI02477,ML Ops Engineer,24960,USD,24960,EN,FT,India,M,Norway,100,"Kubernetes, Hadoop, Java, Mathematics, Deep Learning",Associate,0,Retail,2025-04-16,2025-05-19,1088,7.1,DeepTech Ventures +AI02478,Deep Learning Engineer,106178,AUD,143340,MI,PT,Australia,M,Australia,0,"PyTorch, GCP, Kubernetes, Statistics, Computer Vision",Associate,3,Government,2024-03-30,2024-06-10,1148,5.2,Cognitive Computing +AI02479,Principal Data Scientist,136353,CHF,122718,MI,FT,Switzerland,M,Switzerland,100,"NLP, Azure, Tableau",Bachelor,4,Technology,2024-04-25,2024-06-29,1915,6.1,Algorithmic Solutions +AI02480,Machine Learning Researcher,140620,USD,140620,MI,FT,Denmark,L,Denmark,50,"NLP, Spark, Scala",Master,4,Technology,2025-03-20,2025-04-15,825,5.1,Predictive Systems +AI02481,Machine Learning Researcher,261035,USD,261035,EX,FT,Finland,L,Finland,50,"Python, AWS, Statistics, TensorFlow, NLP",Master,10,Technology,2024-03-14,2024-04-08,1299,8,Algorithmic Solutions +AI02482,Robotics Engineer,119849,SGD,155804,MI,CT,Singapore,L,Singapore,0,"SQL, PyTorch, Computer Vision",Master,3,Government,2024-04-09,2024-05-27,1022,6.5,Smart Analytics +AI02483,AI Consultant,58782,EUR,49965,EN,CT,Germany,S,Germany,50,"Hadoop, Linux, SQL, Computer Vision",Associate,1,Telecommunications,2025-03-24,2025-04-26,1785,7.7,Machine Intelligence Group +AI02484,Autonomous Systems Engineer,77795,GBP,58346,EN,FL,United Kingdom,L,United Kingdom,100,"Tableau, Python, Mathematics, Scala",Master,0,Gaming,2024-12-02,2025-01-30,1815,6.5,AI Innovations +AI02485,Data Analyst,162430,EUR,138066,EX,FT,Austria,M,Austria,0,"SQL, Scala, AWS, MLOps, NLP",Bachelor,15,Retail,2025-02-04,2025-03-07,621,7.6,DeepTech Ventures +AI02486,Robotics Engineer,156099,JPY,17170890,SE,FT,Japan,M,Poland,0,"Deep Learning, PyTorch, R",Associate,7,Gaming,2025-01-07,2025-01-30,2171,6.5,Predictive Systems +AI02487,NLP Engineer,105660,USD,105660,SE,FL,South Korea,M,South Korea,0,"Spark, PyTorch, Tableau, Statistics, AWS",Bachelor,6,Government,2024-11-30,2024-12-28,1284,6.4,TechCorp Inc +AI02488,ML Ops Engineer,100617,USD,100617,MI,PT,Finland,M,Ireland,0,"Docker, Scala, Data Visualization, NLP",Associate,2,Manufacturing,2025-04-04,2025-05-20,871,6.8,Cognitive Computing +AI02489,Deep Learning Engineer,85747,JPY,9432170,EN,PT,Japan,L,Japan,0,"GCP, Linux, SQL",Associate,0,Government,2024-07-26,2024-08-21,1790,8.8,DataVision Ltd +AI02490,AI Product Manager,103946,SGD,135130,MI,CT,Singapore,M,Singapore,0,"SQL, AWS, Tableau, Java, R",Master,3,Finance,2025-01-14,2025-03-22,2223,9.5,Advanced Robotics +AI02491,Deep Learning Engineer,163429,USD,163429,SE,PT,United States,L,Colombia,100,"Statistics, GCP, TensorFlow, Tableau",PhD,6,Real Estate,2025-04-18,2025-06-25,829,9.2,TechCorp Inc +AI02492,NLP Engineer,134989,CHF,121490,SE,CT,Switzerland,S,Ghana,100,"Azure, Deep Learning, Docker",Bachelor,8,Transportation,2024-05-27,2024-07-16,1154,6.9,Digital Transformation LLC +AI02493,AI Architect,232913,USD,232913,EX,PT,Israel,L,Israel,0,"AWS, MLOps, Data Visualization",PhD,14,Consulting,2025-03-19,2025-04-16,955,5.3,Cloud AI Solutions +AI02494,Machine Learning Researcher,72913,CHF,65622,EN,PT,Switzerland,S,Switzerland,0,"Scala, Python, TensorFlow, Spark, Linux",Master,1,Automotive,2024-06-13,2024-08-24,913,5.9,Neural Networks Co +AI02495,NLP Engineer,62004,CAD,77505,EN,CT,Canada,S,Poland,50,"TensorFlow, Statistics, Hadoop",Master,0,Government,2025-03-09,2025-05-19,2303,7.7,TechCorp Inc +AI02496,Head of AI,54572,USD,54572,EN,FL,Israel,S,Finland,100,"NLP, Scala, PyTorch",Bachelor,0,Retail,2025-04-27,2025-07-03,2392,8,Advanced Robotics +AI02497,Data Scientist,304083,CHF,273675,EX,FL,Switzerland,S,Switzerland,100,"Kubernetes, AWS, Python, Git",Master,15,Transportation,2024-06-20,2024-08-18,1922,7,Autonomous Tech +AI02498,Head of AI,263203,AUD,355324,EX,FL,Australia,L,Australia,0,"Java, Kubernetes, Tableau",PhD,18,Automotive,2024-08-26,2024-09-25,1516,8.6,DeepTech Ventures +AI02499,Machine Learning Researcher,78835,EUR,67010,EN,CT,Germany,L,Brazil,0,"Computer Vision, AWS, Data Visualization, Hadoop, PyTorch",Associate,1,Retail,2024-09-28,2024-11-29,2474,9.1,DeepTech Ventures +AI02500,AI Specialist,91165,USD,91165,EX,PT,China,M,China,0,"AWS, Spark, Git",PhD,10,Education,2024-08-02,2024-08-28,700,9,Quantum Computing Inc +AI02501,Robotics Engineer,141371,USD,141371,SE,PT,Finland,M,Turkey,100,"Java, Git, Mathematics, GCP, Hadoop",Bachelor,7,Consulting,2024-10-25,2024-12-27,1708,5.6,Quantum Computing Inc +AI02502,AI Architect,176050,EUR,149643,EX,FL,Austria,S,Austria,0,"Python, MLOps, TensorFlow",Associate,14,Gaming,2024-04-03,2024-05-04,1629,6.5,Advanced Robotics +AI02503,Research Scientist,164808,USD,164808,SE,PT,Norway,S,Norway,50,"Docker, SQL, Kubernetes, Java",Master,6,Real Estate,2024-08-17,2024-09-11,705,6.4,Cognitive Computing +AI02504,Principal Data Scientist,73825,USD,73825,MI,FL,South Korea,S,South Korea,50,"Spark, SQL, Computer Vision",Associate,3,Manufacturing,2025-01-24,2025-02-18,1905,6.6,TechCorp Inc +AI02505,Data Scientist,56305,USD,56305,EN,FT,Finland,M,Finland,100,"Java, Statistics, Git, Hadoop",Bachelor,0,Consulting,2024-06-29,2024-07-22,904,7.7,Advanced Robotics +AI02506,Computer Vision Engineer,95982,SGD,124777,MI,FT,Singapore,S,Singapore,0,"Scala, Spark, Tableau, SQL",Master,4,Telecommunications,2024-04-20,2024-06-29,2187,7.5,Machine Intelligence Group +AI02507,Robotics Engineer,139813,EUR,118841,EX,FL,France,S,France,100,"Python, Linux, Kubernetes",Bachelor,12,Automotive,2024-08-06,2024-08-27,2393,6.7,Quantum Computing Inc +AI02508,AI Architect,103705,CAD,129631,MI,PT,Canada,L,Canada,0,"Docker, Java, PyTorch",Bachelor,2,Finance,2024-01-12,2024-03-12,1589,6.5,TechCorp Inc +AI02509,AI Product Manager,90682,EUR,77080,MI,FT,Austria,M,Austria,100,"Computer Vision, Tableau, GCP",Master,2,Transportation,2025-03-08,2025-04-06,2327,7.9,Algorithmic Solutions +AI02510,Autonomous Systems Engineer,71388,EUR,60680,EN,PT,Netherlands,S,Belgium,50,"Linux, Git, Kubernetes",Associate,1,Manufacturing,2024-09-19,2024-11-16,1567,7,TechCorp Inc +AI02511,Deep Learning Engineer,96336,USD,96336,MI,PT,Israel,M,Vietnam,100,"Java, Linux, Tableau, Scala",Master,2,Transportation,2024-10-28,2024-12-19,2444,9.1,Advanced Robotics +AI02512,Deep Learning Engineer,128679,USD,128679,EX,CT,Finland,M,Finland,0,"R, Python, Linux",Master,10,Transportation,2024-06-29,2024-08-04,1288,8.4,Neural Networks Co +AI02513,Robotics Engineer,109988,EUR,93490,MI,FL,France,L,France,50,"SQL, MLOps, Java, Azure",Master,3,Retail,2025-02-11,2025-04-11,2329,7.8,Autonomous Tech +AI02514,Robotics Engineer,146873,EUR,124842,SE,FT,Netherlands,L,Vietnam,50,"Kubernetes, SQL, AWS, GCP",PhD,9,Real Estate,2025-03-16,2025-04-24,1914,7.5,TechCorp Inc +AI02515,Machine Learning Engineer,165141,USD,165141,EX,PT,South Korea,M,South Korea,0,"Java, Python, Tableau, Linux, Deep Learning",Master,15,Consulting,2024-03-10,2024-04-14,1945,5.9,Autonomous Tech +AI02516,Machine Learning Engineer,77901,AUD,105166,EN,FT,Australia,M,Australia,100,"Python, AWS, Statistics",Associate,0,Energy,2024-10-18,2024-12-03,2251,7.8,Smart Analytics +AI02517,Research Scientist,94620,SGD,123006,EN,PT,Singapore,L,New Zealand,100,"Hadoop, Java, Spark",Associate,1,Automotive,2024-09-22,2024-12-04,1019,8.6,Cloud AI Solutions +AI02518,Principal Data Scientist,162374,GBP,121781,SE,CT,United Kingdom,L,United Kingdom,50,"Git, Azure, Computer Vision, Mathematics, PyTorch",Associate,9,Retail,2024-03-08,2024-04-16,1503,9.9,Smart Analytics +AI02519,Data Engineer,85536,USD,85536,EN,FL,Finland,L,Finland,100,"MLOps, GCP, SQL",PhD,1,Automotive,2025-01-19,2025-03-17,1202,5.8,Future Systems +AI02520,Research Scientist,132794,GBP,99596,SE,PT,United Kingdom,M,United States,100,"NLP, Git, Python, Mathematics",PhD,7,Telecommunications,2024-10-07,2024-12-05,1060,10,Quantum Computing Inc +AI02521,Head of AI,51202,CAD,64003,EN,CT,Canada,S,Canada,50,"Mathematics, Deep Learning, Kubernetes",PhD,0,Transportation,2024-06-09,2024-07-26,2084,9,Machine Intelligence Group +AI02522,Machine Learning Researcher,105407,USD,105407,MI,CT,Ireland,M,Ireland,0,"Git, Hadoop, Scala, Spark",Bachelor,3,Technology,2024-07-15,2024-08-01,515,6.2,Algorithmic Solutions +AI02523,NLP Engineer,94037,USD,94037,MI,CT,Finland,M,Finland,50,"GCP, Kubernetes, R",Associate,3,Automotive,2024-07-15,2024-08-04,2256,7.6,Advanced Robotics +AI02524,Data Engineer,206898,EUR,175863,EX,FT,Austria,S,Austria,100,"Mathematics, Linux, MLOps",Associate,13,Healthcare,2024-01-10,2024-03-14,527,9.1,Digital Transformation LLC +AI02525,Deep Learning Engineer,243562,CHF,219206,EX,PT,Switzerland,M,Switzerland,0,"Git, Java, Data Visualization",Master,19,Telecommunications,2024-02-01,2024-02-15,1421,5,Machine Intelligence Group +AI02526,Data Analyst,51859,USD,51859,EN,PT,Ireland,S,Luxembourg,100,"Git, PyTorch, Statistics, Docker, Python",Master,1,Technology,2025-03-09,2025-03-28,1458,8.8,Quantum Computing Inc +AI02527,ML Ops Engineer,86795,USD,86795,MI,PT,Sweden,S,Sweden,100,"Tableau, GCP, Linux, Computer Vision, Java",Bachelor,4,Retail,2024-08-02,2024-09-20,659,9.1,Digital Transformation LLC +AI02528,AI Research Scientist,81483,EUR,69261,MI,CT,Germany,M,Ireland,50,"Linux, AWS, Python",Bachelor,4,Gaming,2025-03-26,2025-04-13,1391,9.8,AI Innovations +AI02529,ML Ops Engineer,269686,CHF,242717,EX,PT,Switzerland,M,Portugal,50,"Python, NLP, SQL, Linux, Git",PhD,10,Healthcare,2024-09-29,2024-10-17,1421,9.8,AI Innovations +AI02530,AI Architect,55579,USD,55579,EN,PT,South Korea,S,South Korea,50,"MLOps, Python, Deep Learning",Master,0,Education,2024-10-13,2024-11-05,1101,8.8,Predictive Systems +AI02531,AI Software Engineer,60607,USD,60607,EN,FT,Ireland,L,Ireland,0,"Data Visualization, SQL, GCP, Python, Mathematics",PhD,0,Energy,2024-12-16,2025-02-18,2279,5.8,Machine Intelligence Group +AI02532,NLP Engineer,131631,EUR,111886,SE,PT,Germany,M,Germany,50,"AWS, Data Visualization, Azure",Associate,7,Manufacturing,2024-08-12,2024-09-12,697,8.4,DeepTech Ventures +AI02533,Machine Learning Engineer,54944,EUR,46702,EN,FT,Germany,S,Germany,100,"Statistics, SQL, Python",Bachelor,0,Energy,2025-01-21,2025-03-29,975,7,Cognitive Computing +AI02534,AI Software Engineer,191195,CHF,172076,SE,PT,Switzerland,M,Switzerland,100,"PyTorch, Python, Docker, Kubernetes, Hadoop",Master,5,Healthcare,2024-12-02,2024-12-24,2199,5.2,AI Innovations +AI02535,Data Engineer,120333,CAD,150416,EX,FT,Canada,S,Brazil,100,"Java, NLP, MLOps, TensorFlow",Master,13,Government,2024-01-20,2024-02-03,2326,7.2,Smart Analytics +AI02536,Deep Learning Engineer,65699,USD,65699,EX,FT,China,S,China,0,"Statistics, SQL, Docker",Associate,17,Telecommunications,2025-03-21,2025-04-12,2252,6.9,AI Innovations +AI02537,AI Architect,64976,USD,64976,EN,PT,Israel,M,Luxembourg,0,"Tableau, Azure, Linux, Data Visualization",Master,1,Transportation,2024-02-06,2024-03-12,979,8,Cognitive Computing +AI02538,Research Scientist,209582,USD,209582,EX,CT,Denmark,M,Denmark,0,"SQL, Linux, Computer Vision, AWS",Bachelor,10,Government,2025-02-15,2025-04-19,1382,6.4,Smart Analytics +AI02539,Data Scientist,145591,USD,145591,SE,PT,United States,S,Austria,0,"Tableau, Git, PyTorch",Bachelor,7,Healthcare,2024-08-24,2024-10-18,1653,9.9,TechCorp Inc +AI02540,AI Product Manager,291098,USD,291098,EX,FL,Denmark,M,Denmark,100,"AWS, Kubernetes, R, Python, Statistics",Associate,16,Technology,2024-07-26,2024-09-14,2086,8.7,Algorithmic Solutions +AI02541,Autonomous Systems Engineer,196197,USD,196197,EX,FT,Sweden,L,Sweden,50,"Python, SQL, Kubernetes",Associate,11,Telecommunications,2024-05-04,2024-05-18,2425,8.7,Quantum Computing Inc +AI02542,Principal Data Scientist,186336,USD,186336,EX,PT,South Korea,L,France,0,"R, Docker, Java",Bachelor,10,Healthcare,2024-06-20,2024-07-20,1557,5.9,DataVision Ltd +AI02543,Data Scientist,62080,USD,62080,SE,PT,India,L,India,100,"Spark, Statistics, Data Visualization, Azure, Computer Vision",Bachelor,8,Manufacturing,2024-03-05,2024-04-18,774,6.8,Smart Analytics +AI02544,AI Software Engineer,85101,USD,85101,EN,FT,Denmark,S,Ireland,0,"NLP, Deep Learning, Git, Azure, R",Associate,1,Healthcare,2025-04-27,2025-05-12,1077,7.4,Quantum Computing Inc +AI02545,Robotics Engineer,149817,AUD,202253,SE,FT,Australia,M,Australia,0,"PyTorch, Computer Vision, MLOps, Statistics, Mathematics",Bachelor,7,Media,2024-02-07,2024-03-02,964,7.3,Algorithmic Solutions +AI02546,AI Architect,73727,EUR,62668,EN,FL,Austria,L,Austria,50,"GCP, Java, NLP, Computer Vision, Statistics",Associate,0,Retail,2025-03-09,2025-04-04,2292,6.1,Algorithmic Solutions +AI02547,Machine Learning Researcher,95260,USD,95260,EX,FT,China,L,China,100,"Docker, Git, R, SQL",Master,14,Education,2024-09-22,2024-10-16,1846,9.7,AI Innovations +AI02548,AI Specialist,59469,USD,59469,EN,CT,United States,S,United States,0,"R, Mathematics, Data Visualization, Deep Learning",Master,1,Transportation,2024-09-05,2024-10-06,1302,5.1,Digital Transformation LLC +AI02549,Data Engineer,95741,USD,95741,MI,CT,Ireland,S,Ireland,50,"TensorFlow, Spark, R, AWS, Linux",Master,4,Technology,2024-11-08,2024-11-29,836,6.9,Predictive Systems +AI02550,Data Analyst,99330,CHF,89397,EN,FT,Switzerland,S,Vietnam,0,"Kubernetes, Scala, Deep Learning, GCP",Master,1,Telecommunications,2024-01-22,2024-02-21,636,6.5,AI Innovations +AI02551,Data Engineer,169622,USD,169622,EX,PT,United States,M,United States,100,"GCP, Mathematics, Java, PyTorch",Associate,10,Media,2025-04-10,2025-05-02,1878,5.7,Autonomous Tech +AI02552,NLP Engineer,34014,USD,34014,MI,CT,India,L,India,0,"AWS, R, Kubernetes",Master,2,Government,2024-10-16,2024-11-25,2084,5.6,Advanced Robotics +AI02553,Deep Learning Engineer,48009,EUR,40808,EN,CT,France,S,France,100,"Linux, Java, R, Tableau",Associate,1,Automotive,2024-06-20,2024-07-05,1365,8.1,Quantum Computing Inc +AI02554,Machine Learning Researcher,186879,USD,186879,EX,FL,Ireland,M,United States,0,"Tableau, R, Linux",PhD,13,Consulting,2024-10-22,2024-12-05,923,7.4,Machine Intelligence Group +AI02555,Machine Learning Engineer,43587,USD,43587,SE,CT,India,L,Kenya,100,"Mathematics, Tableau, Azure, Linux",Bachelor,6,Government,2024-07-03,2024-07-22,1803,7.8,Algorithmic Solutions +AI02556,AI Product Manager,296908,USD,296908,EX,FT,Denmark,M,Denmark,0,"Scala, PyTorch, AWS, SQL",Associate,17,Education,2024-01-14,2024-02-12,963,8.2,DeepTech Ventures +AI02557,Principal Data Scientist,185850,CHF,167265,SE,FL,Switzerland,L,Switzerland,0,"Linux, Kubernetes, PyTorch, Deep Learning, Docker",Associate,9,Manufacturing,2025-01-19,2025-02-27,1056,9.1,Advanced Robotics +AI02558,AI Specialist,171053,CAD,213816,EX,CT,Canada,M,Canada,50,"GCP, Kubernetes, Data Visualization, Scala",Associate,18,Finance,2024-04-10,2024-05-30,1822,6.7,Quantum Computing Inc +AI02559,ML Ops Engineer,149653,EUR,127205,EX,PT,France,L,France,0,"Computer Vision, Mathematics, Scala, Data Visualization, Python",PhD,13,Transportation,2024-11-02,2024-11-16,1909,5.8,TechCorp Inc +AI02560,AI Specialist,86772,USD,86772,MI,PT,United States,M,United States,0,"TensorFlow, Kubernetes, PyTorch, Azure",PhD,3,Government,2024-06-25,2024-07-14,934,6.9,AI Innovations +AI02561,Machine Learning Researcher,80745,EUR,68633,MI,FL,Austria,L,Austria,100,"Data Visualization, Python, Spark",Master,4,Healthcare,2024-08-07,2024-09-05,2274,7.6,Autonomous Tech +AI02562,Principal Data Scientist,88333,CAD,110416,MI,FT,Canada,L,Canada,100,"MLOps, GCP, Java, Hadoop",Master,3,Transportation,2024-10-31,2025-01-03,1219,7.5,Quantum Computing Inc +AI02563,Data Engineer,294564,CHF,265108,EX,FT,Switzerland,M,United States,0,"Git, Python, TensorFlow",Master,16,Healthcare,2024-02-28,2024-05-10,1523,9,DeepTech Ventures +AI02564,Autonomous Systems Engineer,151837,USD,151837,SE,FL,United States,S,Estonia,100,"SQL, Mathematics, Tableau, Git",Master,6,Automotive,2025-03-24,2025-04-23,1538,6.9,Algorithmic Solutions +AI02565,Deep Learning Engineer,258351,USD,258351,EX,FL,United States,M,United States,50,"Python, TensorFlow, Scala, Deep Learning",Associate,14,Transportation,2024-12-24,2025-02-14,2412,8.3,AI Innovations +AI02566,AI Specialist,93903,CAD,117379,SE,CT,Canada,S,Canada,50,"Java, MLOps, Statistics, Tableau, Linux",PhD,5,Education,2025-02-20,2025-04-17,968,5.6,Cloud AI Solutions +AI02567,AI Product Manager,129113,USD,129113,SE,CT,Israel,S,Israel,0,"Hadoop, Computer Vision, Kubernetes, R, Docker",Bachelor,9,Automotive,2024-09-30,2024-10-16,2205,8.5,Future Systems +AI02568,AI Software Engineer,86397,EUR,73437,EN,PT,Germany,L,Germany,0,"Computer Vision, Git, Kubernetes, PyTorch",Bachelor,1,Automotive,2024-07-19,2024-09-25,1310,6.3,Algorithmic Solutions +AI02569,Autonomous Systems Engineer,124460,USD,124460,SE,CT,Sweden,M,Brazil,100,"SQL, Scala, Python, AWS, Hadoop",Master,9,Healthcare,2024-06-08,2024-07-07,2132,9.4,AI Innovations +AI02570,Data Engineer,149448,EUR,127031,EX,FT,France,M,France,50,"MLOps, Mathematics, Data Visualization",Master,18,Retail,2024-03-30,2024-04-17,1536,9.8,DeepTech Ventures +AI02571,Data Engineer,58804,EUR,49983,EN,PT,Germany,M,Germany,0,"Statistics, Java, Spark",Associate,1,Healthcare,2024-04-24,2024-06-19,609,7,Cloud AI Solutions +AI02572,AI Consultant,79567,CHF,71610,EN,FL,Switzerland,S,United States,100,"TensorFlow, Deep Learning, Computer Vision",PhD,0,Retail,2024-07-18,2024-08-09,1174,7.3,DataVision Ltd +AI02573,AI Specialist,92586,EUR,78698,MI,PT,Austria,M,Austria,50,"Python, Deep Learning, Kubernetes, Computer Vision",Master,4,Energy,2024-10-19,2024-11-02,739,7.1,Neural Networks Co +AI02574,Data Engineer,88553,JPY,9740830,EN,PT,Japan,L,Italy,0,"PyTorch, Computer Vision, Deep Learning",Associate,0,Finance,2025-01-25,2025-03-24,903,7,DeepTech Ventures +AI02575,Deep Learning Engineer,180911,EUR,153774,EX,FT,Netherlands,M,Netherlands,50,"Kubernetes, Statistics, R, Python, Mathematics",Master,13,Retail,2024-09-29,2024-11-13,1874,6.6,TechCorp Inc +AI02576,Computer Vision Engineer,180125,USD,180125,SE,FL,United States,L,United States,100,"TensorFlow, SQL, Git, AWS",Associate,8,Automotive,2024-12-07,2024-12-21,2412,8.4,Machine Intelligence Group +AI02577,Computer Vision Engineer,52185,EUR,44357,EN,FT,France,S,France,50,"R, Spark, TensorFlow, Data Visualization, SQL",Master,1,Retail,2024-06-27,2024-08-22,2119,9.3,Smart Analytics +AI02578,Machine Learning Researcher,246154,EUR,209231,EX,CT,Austria,L,Austria,0,"Deep Learning, Computer Vision, TensorFlow, Scala",Associate,14,Finance,2025-01-05,2025-03-07,1880,9.6,Cognitive Computing +AI02579,AI Specialist,57512,EUR,48885,EN,FL,Netherlands,M,Australia,100,"Statistics, PyTorch, SQL, Scala, Data Visualization",Associate,0,Consulting,2024-03-23,2024-04-19,575,6.8,AI Innovations +AI02580,Head of AI,170182,CHF,153164,MI,FT,Switzerland,L,Switzerland,0,"TensorFlow, Java, GCP",Master,2,Retail,2024-02-07,2024-03-03,1519,6.4,Cloud AI Solutions +AI02581,Data Scientist,40011,USD,40011,MI,CT,China,M,China,100,"Linux, Tableau, Spark, Java",Associate,3,Finance,2024-07-25,2024-08-30,1950,9.5,DeepTech Ventures +AI02582,Machine Learning Engineer,112165,GBP,84124,SE,CT,United Kingdom,M,Japan,100,"GCP, Kubernetes, Java, SQL, Deep Learning",Associate,7,Finance,2024-07-22,2024-09-02,1763,5.6,Smart Analytics +AI02583,Head of AI,118931,USD,118931,SE,CT,Ireland,L,Ireland,100,"Python, GCP, Scala",PhD,8,Government,2024-09-21,2024-10-28,1210,9,Cognitive Computing +AI02584,AI Specialist,163364,USD,163364,SE,FL,Finland,L,Mexico,0,"PyTorch, Spark, TensorFlow",Bachelor,8,Government,2025-01-06,2025-02-18,1293,6.9,Cloud AI Solutions +AI02585,Data Scientist,131301,USD,131301,EX,FL,South Korea,S,South Korea,0,"Linux, Spark, Deep Learning, Kubernetes",PhD,18,Education,2024-04-10,2024-05-02,2382,7.5,Quantum Computing Inc +AI02586,AI Software Engineer,68441,USD,68441,MI,PT,Ireland,S,Ireland,50,"Kubernetes, Statistics, GCP, Tableau",Master,4,Real Estate,2024-10-02,2024-10-20,1488,8.3,DataVision Ltd +AI02587,Robotics Engineer,135907,USD,135907,MI,CT,United States,L,United States,0,"NLP, GCP, Tableau",PhD,2,Energy,2024-09-26,2024-11-28,597,6.5,Machine Intelligence Group +AI02588,AI Architect,99860,EUR,84881,SE,FT,France,M,France,100,"PyTorch, AWS, NLP, Java, Azure",Master,6,Telecommunications,2024-06-19,2024-08-27,654,8.9,Quantum Computing Inc +AI02589,NLP Engineer,91537,USD,91537,MI,FL,South Korea,L,Argentina,100,"PyTorch, Tableau, NLP, TensorFlow",PhD,3,Telecommunications,2025-03-21,2025-05-29,845,6.9,Future Systems +AI02590,AI Specialist,167565,USD,167565,SE,PT,United States,M,France,50,"Hadoop, Azure, Deep Learning",Master,5,Energy,2024-07-10,2024-08-21,916,6.8,Digital Transformation LLC +AI02591,Machine Learning Researcher,102636,SGD,133427,MI,PT,Singapore,L,Singapore,100,"SQL, MLOps, PyTorch, Data Visualization, TensorFlow",Associate,2,Energy,2024-10-20,2024-12-13,663,7.1,Future Systems +AI02592,AI Consultant,116030,EUR,98626,SE,CT,Germany,M,Germany,100,"TensorFlow, Linux, PyTorch, GCP, Azure",PhD,6,Media,2024-04-05,2024-05-13,1375,5.9,Machine Intelligence Group +AI02593,AI Architect,84644,CAD,105805,EN,PT,Canada,L,Canada,100,"Kubernetes, Python, Hadoop",Master,1,Government,2024-12-25,2025-02-16,2101,8.9,Predictive Systems +AI02594,Research Scientist,65082,AUD,87861,EN,CT,Australia,M,Nigeria,50,"Python, Deep Learning, Kubernetes, Linux",PhD,1,Energy,2024-07-17,2024-08-06,1907,8.2,DataVision Ltd +AI02595,AI Software Engineer,62534,AUD,84421,EN,PT,Australia,M,Australia,50,"Python, Git, TensorFlow",Master,0,Telecommunications,2024-11-26,2025-01-12,2305,6.5,DeepTech Ventures +AI02596,AI Specialist,241137,CHF,217023,SE,FT,Switzerland,L,Switzerland,50,"Spark, Kubernetes, Tableau, Python, Statistics",Master,5,Education,2024-12-05,2025-02-04,1926,7.6,Machine Intelligence Group +AI02597,AI Software Engineer,85906,USD,85906,EN,PT,Finland,L,Finland,50,"Statistics, Linux, Scala, Kubernetes",Associate,1,Media,2024-10-21,2024-11-27,1026,7.7,Cognitive Computing +AI02598,Data Scientist,99399,USD,99399,SE,FT,South Korea,S,Singapore,50,"R, Python, Mathematics",Master,9,Real Estate,2024-03-21,2024-04-10,1095,5,Machine Intelligence Group +AI02599,Machine Learning Engineer,69551,USD,69551,EN,FL,Denmark,S,Denmark,0,"Docker, Python, Hadoop, SQL",Associate,0,Transportation,2024-10-24,2024-11-21,1355,6.4,Quantum Computing Inc +AI02600,Autonomous Systems Engineer,98388,USD,98388,MI,FT,South Korea,L,South Korea,0,"Python, Computer Vision, TensorFlow",Bachelor,4,Energy,2024-07-23,2024-09-17,1870,5.8,Machine Intelligence Group +AI02601,NLP Engineer,59613,CAD,74516,EN,CT,Canada,M,Canada,100,"Computer Vision, R, Docker",PhD,1,Retail,2024-02-07,2024-03-06,1939,6.2,Advanced Robotics +AI02602,AI Software Engineer,84934,USD,84934,EN,FL,United States,S,United States,100,"Computer Vision, Deep Learning, Tableau, Linux",Master,0,Telecommunications,2024-08-16,2024-10-18,1161,6.7,Quantum Computing Inc +AI02603,Data Analyst,86399,USD,86399,EX,FT,India,L,India,50,"Docker, R, Linux",Associate,18,Technology,2024-07-23,2024-09-10,1885,7.5,AI Innovations +AI02604,Data Scientist,167659,AUD,226340,SE,FT,Australia,L,Australia,50,"Kubernetes, TensorFlow, Spark, SQL",PhD,8,Education,2024-12-30,2025-01-22,1211,6.1,Digital Transformation LLC +AI02605,Data Engineer,101084,AUD,136463,MI,CT,Australia,L,Australia,100,"Java, TensorFlow, AWS, Computer Vision",Bachelor,2,Manufacturing,2024-08-01,2024-09-11,724,8.4,Neural Networks Co +AI02606,AI Architect,32520,USD,32520,EN,CT,China,M,Romania,50,"GCP, Linux, Statistics",PhD,1,Technology,2025-02-02,2025-03-08,1144,6.9,Smart Analytics +AI02607,Data Scientist,109024,EUR,92670,SE,FT,Germany,S,Germany,100,"Azure, SQL, TensorFlow, Tableau, Deep Learning",Bachelor,6,Real Estate,2024-09-11,2024-11-10,931,7.8,Predictive Systems +AI02608,AI Consultant,130052,USD,130052,SE,CT,Norway,S,Portugal,100,"Python, PyTorch, Data Visualization, Kubernetes",Associate,8,Healthcare,2025-02-22,2025-03-09,1571,5.6,DeepTech Ventures +AI02609,Deep Learning Engineer,118889,EUR,101056,MI,PT,Austria,L,Austria,50,"Tableau, Deep Learning, Kubernetes",PhD,2,Energy,2024-04-11,2024-05-13,2266,9.5,Smart Analytics +AI02610,Robotics Engineer,120628,USD,120628,EX,FT,Finland,S,Egypt,100,"Hadoop, Linux, Azure, MLOps, Kubernetes",Associate,15,Automotive,2024-04-26,2024-06-12,1815,9.4,DataVision Ltd +AI02611,AI Specialist,74800,CAD,93500,EN,FT,Canada,L,Canada,0,"Azure, Hadoop, Kubernetes, TensorFlow, Statistics",PhD,0,Automotive,2024-07-20,2024-09-04,688,5.2,Quantum Computing Inc +AI02612,AI Software Engineer,64207,GBP,48155,EN,PT,United Kingdom,M,Portugal,0,"Docker, GCP, SQL, AWS",Associate,1,Technology,2024-10-24,2025-01-03,2149,8.1,AI Innovations +AI02613,Computer Vision Engineer,133828,CHF,120445,MI,FT,Switzerland,S,Indonesia,100,"Scala, Spark, Data Visualization, R, Git",Associate,2,Automotive,2025-01-26,2025-02-17,1345,8.3,Advanced Robotics +AI02614,AI Product Manager,79575,AUD,107426,EN,FL,Australia,L,Australia,0,"Linux, AWS, Scala, PyTorch, Docker",Bachelor,1,Energy,2024-01-10,2024-03-18,1969,7.7,Advanced Robotics +AI02615,Autonomous Systems Engineer,131921,AUD,178093,SE,CT,Australia,M,Australia,100,"PyTorch, AWS, Tableau",Bachelor,7,Healthcare,2024-04-25,2024-05-22,546,7.1,Predictive Systems +AI02616,Machine Learning Engineer,237422,USD,237422,EX,FL,Denmark,L,Vietnam,100,"Scala, TensorFlow, SQL, NLP",PhD,18,Retail,2024-08-31,2024-10-04,2210,7.3,Cloud AI Solutions +AI02617,Computer Vision Engineer,78318,EUR,66570,MI,FL,Germany,S,Germany,100,"Data Visualization, Python, Java",Bachelor,2,Manufacturing,2025-04-03,2025-06-10,1370,8.5,Cognitive Computing +AI02618,Autonomous Systems Engineer,108458,EUR,92189,MI,FL,Netherlands,L,Netherlands,100,"Docker, Java, Computer Vision",Bachelor,2,Manufacturing,2024-09-26,2024-11-10,524,7,Smart Analytics +AI02619,Data Analyst,263428,GBP,197571,EX,CT,United Kingdom,M,United Kingdom,100,"MLOps, GCP, Python, TensorFlow, Scala",PhD,18,Gaming,2024-04-28,2024-06-10,1293,5.8,Digital Transformation LLC +AI02620,AI Consultant,46582,USD,46582,MI,PT,China,S,China,100,"MLOps, Deep Learning, Python, NLP, Scala",Bachelor,3,Automotive,2024-03-12,2024-05-14,1625,6.3,DeepTech Ventures +AI02621,Robotics Engineer,169033,SGD,219743,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Data Visualization",PhD,17,Healthcare,2025-03-06,2025-03-24,1506,8.4,TechCorp Inc +AI02622,Machine Learning Researcher,59167,USD,59167,MI,FL,South Korea,S,South Korea,0,"Statistics, Git, Linux, GCP, Computer Vision",Bachelor,2,Telecommunications,2024-12-18,2025-02-14,965,7.3,AI Innovations +AI02623,Deep Learning Engineer,76863,SGD,99922,EN,PT,Singapore,S,Singapore,0,"AWS, Hadoop, NLP, Python, Scala",Master,0,Telecommunications,2024-11-17,2024-12-20,1525,6.4,Quantum Computing Inc +AI02624,Research Scientist,54769,USD,54769,EN,FL,South Korea,S,South Korea,0,"Python, Scala, Java",Bachelor,1,Consulting,2024-12-10,2025-02-10,1118,7.9,TechCorp Inc +AI02625,AI Product Manager,227468,USD,227468,EX,FT,United States,M,Colombia,50,"Linux, TensorFlow, Deep Learning",Master,14,Retail,2024-01-03,2024-03-10,1849,7.9,Algorithmic Solutions +AI02626,Deep Learning Engineer,27385,USD,27385,EN,FT,China,S,Malaysia,50,"TensorFlow, Python, R, Statistics, Spark",PhD,0,Consulting,2024-11-22,2025-01-28,1243,5.3,Quantum Computing Inc +AI02627,NLP Engineer,192062,USD,192062,EX,PT,Norway,M,Norway,100,"TensorFlow, SQL, Mathematics",PhD,10,Real Estate,2024-08-07,2024-09-27,1863,5.4,Cloud AI Solutions +AI02628,Data Analyst,84809,USD,84809,MI,FL,Israel,M,Israel,100,"TensorFlow, AWS, Python, Computer Vision, Scala",Associate,4,Automotive,2024-11-27,2024-12-31,519,8.3,Algorithmic Solutions +AI02629,Computer Vision Engineer,129372,USD,129372,SE,CT,Israel,M,Ukraine,50,"Deep Learning, MLOps, Azure, Java",Master,6,Transportation,2024-03-19,2024-04-04,2253,6.9,Neural Networks Co +AI02630,Principal Data Scientist,61768,CAD,77210,EN,FT,Canada,L,Canada,100,"Java, Git, Kubernetes, PyTorch, Data Visualization",Associate,1,Automotive,2024-02-26,2024-03-14,1170,7.5,Cloud AI Solutions +AI02631,AI Product Manager,33922,USD,33922,EN,CT,China,M,China,100,"Spark, Python, Git, Linux",Associate,0,Technology,2024-07-17,2024-08-15,590,7.1,Algorithmic Solutions +AI02632,Research Scientist,127911,USD,127911,SE,PT,Sweden,M,Sweden,100,"AWS, Python, TensorFlow, Statistics, Deep Learning",Bachelor,6,Real Estate,2024-08-14,2024-09-15,847,9.3,Future Systems +AI02633,AI Consultant,132207,EUR,112376,EX,CT,Austria,S,Austria,100,"Hadoop, Python, Statistics",Master,16,Automotive,2024-01-29,2024-03-16,1880,7.1,Cloud AI Solutions +AI02634,AI Specialist,60862,CAD,76078,EN,CT,Canada,S,United Kingdom,0,"SQL, Computer Vision, Tableau, PyTorch, Scala",PhD,1,Healthcare,2024-07-26,2024-09-06,1914,5.5,Autonomous Tech +AI02635,Machine Learning Researcher,30483,USD,30483,MI,FT,India,S,India,100,"Kubernetes, NLP, Linux",PhD,2,Finance,2024-12-21,2025-01-15,2424,9,TechCorp Inc +AI02636,AI Product Manager,99046,USD,99046,MI,FL,Denmark,S,Denmark,0,"MLOps, R, Kubernetes",Associate,4,Healthcare,2024-12-15,2025-01-30,990,8.9,Quantum Computing Inc +AI02637,AI Product Manager,126174,USD,126174,MI,CT,Denmark,S,New Zealand,0,"Data Visualization, Kubernetes, Scala, Python",Associate,3,Healthcare,2024-06-25,2024-08-27,877,6.1,Cognitive Computing +AI02638,Deep Learning Engineer,226713,USD,226713,EX,FT,Denmark,S,South Africa,50,"Python, TensorFlow, Docker, Mathematics",Bachelor,11,Education,2025-03-16,2025-05-04,760,8.7,Advanced Robotics +AI02639,Robotics Engineer,66662,SGD,86661,EN,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, Kubernetes, Spark, SQL",Bachelor,0,Consulting,2024-03-03,2024-03-28,2192,6.7,Autonomous Tech +AI02640,Machine Learning Engineer,156202,USD,156202,EX,CT,Ireland,S,China,0,"TensorFlow, Data Visualization, Python",Bachelor,14,Media,2024-05-14,2024-06-15,1849,6.6,Predictive Systems +AI02641,ML Ops Engineer,106445,USD,106445,SE,CT,South Korea,S,South Korea,50,"Docker, Deep Learning, Python, GCP, Mathematics",Master,9,Technology,2025-02-01,2025-03-31,2203,7.7,Advanced Robotics +AI02642,Research Scientist,57527,USD,57527,SE,CT,China,L,China,50,"R, SQL, Scala, Tableau, AWS",Associate,7,Telecommunications,2024-11-24,2024-12-18,1466,9.9,DataVision Ltd +AI02643,Data Analyst,71613,USD,71613,EN,CT,Ireland,L,Norway,0,"Azure, Python, GCP, TensorFlow, MLOps",Associate,1,Media,2024-05-12,2024-06-06,1682,8.8,Quantum Computing Inc +AI02644,Data Engineer,214057,USD,214057,SE,FT,Norway,L,Norway,0,"Scala, Deep Learning, Computer Vision, Data Visualization, Docker",PhD,9,Education,2024-12-11,2025-02-03,1422,7.3,DeepTech Ventures +AI02645,AI Research Scientist,113033,USD,113033,SE,PT,Finland,L,Finland,50,"MLOps, Spark, Azure",Bachelor,6,Media,2024-10-07,2024-10-21,1899,6.8,Advanced Robotics +AI02646,Computer Vision Engineer,83831,AUD,113172,MI,FT,Australia,L,Philippines,50,"Scala, Hadoop, Linux, SQL",Associate,4,Retail,2025-02-21,2025-03-25,904,5.3,Cloud AI Solutions +AI02647,Deep Learning Engineer,130289,USD,130289,SE,CT,United States,S,United States,0,"Kubernetes, Scala, Deep Learning",Associate,6,Government,2025-03-10,2025-04-15,2201,9.8,Algorithmic Solutions +AI02648,Data Engineer,128723,CAD,160904,SE,CT,Canada,S,Canada,100,"Scala, Tableau, Python",Master,7,Transportation,2024-09-11,2024-11-13,1131,5.8,DeepTech Ventures +AI02649,AI Consultant,197237,AUD,266270,EX,FL,Australia,S,Australia,0,"Hadoop, Python, Tableau, SQL",Associate,10,Telecommunications,2024-10-10,2024-12-10,2281,6.6,Future Systems +AI02650,Machine Learning Engineer,49680,USD,49680,MI,FL,China,L,China,100,"AWS, Spark, Tableau, NLP, Kubernetes",PhD,2,Finance,2024-02-26,2024-03-20,785,9.9,Future Systems +AI02651,Computer Vision Engineer,79494,USD,79494,MI,CT,United States,S,Indonesia,0,"Scala, Spark, Hadoop",Bachelor,3,Finance,2025-01-07,2025-02-24,1427,6.2,Algorithmic Solutions +AI02652,Data Engineer,120305,SGD,156397,MI,PT,Singapore,L,Singapore,0,"Computer Vision, SQL, Docker, Python, Hadoop",Bachelor,3,Education,2024-09-24,2024-10-18,1572,8.5,Algorithmic Solutions +AI02653,Research Scientist,109402,USD,109402,EX,FL,South Korea,S,South Korea,50,"Python, Scala, TensorFlow, Java, AWS",Bachelor,11,Telecommunications,2024-08-30,2024-10-25,2305,9,Machine Intelligence Group +AI02654,Computer Vision Engineer,131199,SGD,170559,MI,CT,Singapore,L,Russia,50,"R, Linux, Statistics, Spark",Bachelor,3,Consulting,2024-01-25,2024-03-19,593,7.2,TechCorp Inc +AI02655,Data Engineer,89303,USD,89303,MI,PT,Israel,L,Israel,0,"PyTorch, Mathematics, SQL, Scala, NLP",Associate,4,Energy,2024-03-25,2024-04-20,1319,8.3,TechCorp Inc +AI02656,AI Consultant,152868,AUD,206372,EX,FL,Australia,S,United States,0,"Hadoop, Java, Git, Statistics, Spark",PhD,13,Telecommunications,2025-02-13,2025-03-16,1303,6.8,Cloud AI Solutions +AI02657,Machine Learning Engineer,77521,USD,77521,MI,CT,South Korea,L,South Korea,50,"Spark, Hadoop, Tableau, MLOps, Linux",Associate,2,Finance,2025-01-25,2025-04-07,2414,8.6,DataVision Ltd +AI02658,ML Ops Engineer,140909,GBP,105682,SE,FT,United Kingdom,S,United Kingdom,100,"AWS, R, SQL",Master,9,Government,2024-01-14,2024-03-24,1248,9,Future Systems +AI02659,Data Engineer,156224,USD,156224,EX,CT,Finland,L,Finland,0,"Azure, Data Visualization, Statistics",PhD,18,Telecommunications,2024-09-21,2024-10-17,1780,9.1,DataVision Ltd +AI02660,AI Software Engineer,98611,SGD,128194,MI,FT,Singapore,M,Chile,100,"MLOps, Git, Kubernetes",Associate,3,Healthcare,2024-09-14,2024-10-16,1867,9.6,Algorithmic Solutions +AI02661,AI Research Scientist,129667,USD,129667,SE,CT,Ireland,M,South Korea,50,"Hadoop, Data Visualization, SQL, MLOps",Bachelor,7,Real Estate,2024-01-26,2024-02-17,2455,5.6,Cognitive Computing +AI02662,AI Research Scientist,143589,EUR,122051,SE,PT,Austria,M,Germany,50,"Scala, GCP, Computer Vision, Statistics, Tableau",PhD,5,Manufacturing,2024-03-04,2024-05-01,1222,6.3,Quantum Computing Inc +AI02663,Deep Learning Engineer,102918,USD,102918,EN,FT,United States,L,Luxembourg,100,"Python, TensorFlow, Deep Learning, R",Master,0,Finance,2025-04-08,2025-05-19,2329,7.7,DataVision Ltd +AI02664,NLP Engineer,233285,EUR,198292,EX,FT,Austria,L,Ukraine,100,"MLOps, R, Computer Vision",Master,10,Finance,2025-01-12,2025-02-20,1375,6.2,Neural Networks Co +AI02665,AI Research Scientist,161043,USD,161043,SE,FL,United States,M,United States,100,"PyTorch, Spark, Mathematics",Master,5,Energy,2024-07-18,2024-09-21,1559,9.8,Advanced Robotics +AI02666,AI Architect,184501,GBP,138376,EX,FL,United Kingdom,L,Russia,100,"Statistics, TensorFlow, Deep Learning",Associate,18,Consulting,2024-12-10,2025-01-13,1574,6.9,Digital Transformation LLC +AI02667,NLP Engineer,77968,USD,77968,EX,PT,India,S,India,50,"Deep Learning, Spark, MLOps, Hadoop, SQL",Bachelor,10,Retail,2024-03-06,2024-05-16,585,6.2,Digital Transformation LLC +AI02668,AI Architect,251626,USD,251626,EX,PT,United States,S,Argentina,50,"Mathematics, Data Visualization, MLOps, Docker",Bachelor,17,Media,2024-12-30,2025-02-08,2096,7.4,Neural Networks Co +AI02669,AI Product Manager,93801,USD,93801,MI,FL,Finland,L,Malaysia,100,"Python, Git, SQL, Docker",PhD,3,Retail,2024-01-24,2024-02-21,1501,8.3,AI Innovations +AI02670,Autonomous Systems Engineer,85270,USD,85270,EN,FL,United States,M,Indonesia,100,"Spark, Scala, AWS, Deep Learning",PhD,0,Government,2024-01-09,2024-01-24,1067,8.8,DataVision Ltd +AI02671,AI Product Manager,116844,USD,116844,EX,PT,South Korea,S,Malaysia,50,"Docker, Spark, Python, Java",Master,12,Transportation,2025-03-17,2025-04-17,2064,9.8,TechCorp Inc +AI02672,AI Consultant,115484,USD,115484,SE,FL,Finland,S,Finland,0,"Kubernetes, Spark, Git, Computer Vision, Java",Master,6,Gaming,2024-09-16,2024-10-28,1669,5.3,Digital Transformation LLC +AI02673,NLP Engineer,215938,USD,215938,EX,CT,Norway,M,Australia,100,"Linux, Kubernetes, Mathematics, SQL",Bachelor,15,Consulting,2024-01-06,2024-01-25,920,8.1,Smart Analytics +AI02674,Head of AI,112832,USD,112832,SE,FT,Ireland,S,Ireland,0,"R, SQL, Tableau, PyTorch, Java",Master,9,Consulting,2024-03-11,2024-05-17,1000,6.1,AI Innovations +AI02675,Principal Data Scientist,375327,CHF,337794,EX,CT,Switzerland,L,South Africa,0,"SQL, Python, Deep Learning, Kubernetes",Bachelor,12,Automotive,2025-02-23,2025-03-23,700,7.9,DeepTech Ventures +AI02676,AI Product Manager,167432,CHF,150689,SE,FL,Switzerland,M,United Kingdom,50,"Statistics, NLP, MLOps, Linux",Master,9,Healthcare,2024-11-02,2024-12-20,1081,7.9,Machine Intelligence Group +AI02677,Autonomous Systems Engineer,117408,CHF,105667,MI,PT,Switzerland,L,Switzerland,50,"Scala, MLOps, Hadoop, SQL",Master,2,Healthcare,2024-01-14,2024-03-16,2132,7.4,Neural Networks Co +AI02678,Research Scientist,76644,USD,76644,MI,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Data Visualization",Bachelor,3,Technology,2024-02-28,2024-04-09,2292,6,TechCorp Inc +AI02679,Autonomous Systems Engineer,80930,USD,80930,EN,FL,Finland,L,Finland,100,"Git, MLOps, Tableau",Associate,1,Consulting,2024-01-14,2024-03-14,1105,9.2,Predictive Systems +AI02680,ML Ops Engineer,96017,EUR,81614,MI,FL,Austria,M,Austria,0,"Python, Git, NLP, Mathematics, TensorFlow",Master,3,Energy,2024-09-23,2024-10-30,1268,9.5,Predictive Systems +AI02681,Deep Learning Engineer,85062,USD,85062,EN,PT,Denmark,L,Denmark,0,"Kubernetes, Statistics, Python, Java",PhD,0,Education,2024-05-05,2024-07-11,1703,6.8,Advanced Robotics +AI02682,Data Analyst,123126,EUR,104657,SE,FT,France,L,Luxembourg,50,"Linux, SQL, R",Bachelor,9,Manufacturing,2024-02-21,2024-03-25,2431,6.2,DataVision Ltd +AI02683,Robotics Engineer,131093,USD,131093,EX,FL,Finland,M,Finland,50,"PyTorch, Mathematics, Git, R",PhD,13,Real Estate,2024-06-10,2024-08-22,1037,9.8,Advanced Robotics +AI02684,Data Scientist,110151,JPY,12116610,MI,FL,Japan,M,Malaysia,0,"Git, AWS, Python, Kubernetes, Docker",Bachelor,2,Real Estate,2024-01-11,2024-02-05,1352,8.1,Algorithmic Solutions +AI02685,NLP Engineer,120418,CHF,108376,MI,FL,Switzerland,M,Switzerland,0,"GCP, Docker, Mathematics",Master,4,Technology,2025-04-25,2025-06-18,1356,8.8,Quantum Computing Inc +AI02686,Data Analyst,135377,USD,135377,EX,FL,South Korea,L,South Korea,100,"Spark, SQL, Linux, Azure, AWS",Master,10,Transportation,2024-09-16,2024-11-10,784,6.7,Autonomous Tech +AI02687,ML Ops Engineer,87833,USD,87833,MI,FT,Ireland,L,Ireland,50,"Git, Azure, MLOps, Python",PhD,3,Technology,2024-01-10,2024-02-21,2222,8,Advanced Robotics +AI02688,AI Architect,227660,EUR,193511,EX,FL,Germany,S,Germany,50,"Computer Vision, Python, Deep Learning",Bachelor,15,Government,2024-10-16,2024-11-03,1915,9.8,DataVision Ltd +AI02689,Deep Learning Engineer,133632,USD,133632,EX,FT,China,L,China,0,"NLP, Python, Mathematics, GCP",Associate,15,Telecommunications,2024-12-31,2025-01-18,850,8.8,AI Innovations +AI02690,AI Software Engineer,78480,USD,78480,EN,FT,Norway,M,Norway,50,"Spark, Git, Deep Learning, Docker",Associate,1,Healthcare,2024-07-22,2024-08-28,1560,7.4,DeepTech Ventures +AI02691,Head of AI,206088,EUR,175175,EX,FT,France,M,China,0,"Statistics, Tableau, SQL, Data Visualization, PyTorch",Associate,14,Healthcare,2024-03-27,2024-05-28,821,9.3,Future Systems +AI02692,Head of AI,153198,CAD,191498,SE,PT,Canada,L,Canada,100,"Linux, Mathematics, Deep Learning, PyTorch, Azure",Master,9,Transportation,2025-02-01,2025-02-21,1912,8.2,Machine Intelligence Group +AI02693,Head of AI,92186,EUR,78358,MI,FT,France,M,France,100,"Deep Learning, Python, Spark",PhD,2,Retail,2024-09-07,2024-09-28,612,7.8,Advanced Robotics +AI02694,Data Engineer,123240,USD,123240,SE,PT,Finland,M,Finland,0,"NLP, GCP, R",PhD,7,Media,2024-11-05,2024-11-25,2331,9.4,Quantum Computing Inc +AI02695,Data Analyst,77013,SGD,100117,MI,PT,Singapore,M,Singapore,50,"Hadoop, AWS, Linux",Bachelor,4,Retail,2024-06-29,2024-08-01,2245,5.3,Autonomous Tech +AI02696,AI Software Engineer,79315,AUD,107075,MI,PT,Australia,S,Australia,50,"Java, Scala, Hadoop",Master,3,Technology,2024-09-24,2024-10-26,928,7,Smart Analytics +AI02697,Autonomous Systems Engineer,82499,USD,82499,MI,PT,Israel,S,Israel,50,"Linux, Git, TensorFlow, PyTorch, R",Master,3,Energy,2024-12-23,2025-02-08,1156,8.6,DeepTech Ventures +AI02698,AI Research Scientist,89597,USD,89597,MI,CT,Ireland,M,Ireland,100,"PyTorch, Git, Tableau",Master,3,Gaming,2025-04-28,2025-06-27,638,9.4,Future Systems +AI02699,AI Consultant,79127,USD,79127,MI,CT,South Korea,L,South Africa,50,"Spark, Kubernetes, PyTorch, Mathematics, TensorFlow",Bachelor,4,Retail,2025-04-18,2025-06-01,660,9.8,Predictive Systems +AI02700,NLP Engineer,181523,EUR,154295,EX,FT,Germany,S,Germany,100,"Java, SQL, Mathematics",PhD,16,Automotive,2025-03-19,2025-04-25,1872,8.7,Smart Analytics +AI02701,Machine Learning Researcher,136263,USD,136263,EX,FT,Sweden,S,Italy,0,"MLOps, Docker, TensorFlow, Statistics",PhD,14,Technology,2024-06-22,2024-08-27,1042,8.8,DataVision Ltd +AI02702,Computer Vision Engineer,83502,JPY,9185220,MI,FL,Japan,M,Japan,0,"Data Visualization, Java, TensorFlow",Master,4,Education,2024-11-02,2024-11-24,1113,8,TechCorp Inc +AI02703,Autonomous Systems Engineer,80445,USD,80445,EN,FL,Israel,L,Vietnam,100,"Spark, Kubernetes, Linux, Deep Learning",Master,0,Automotive,2024-11-29,2025-01-13,1701,5.6,Algorithmic Solutions +AI02704,NLP Engineer,129262,EUR,109873,SE,CT,Germany,M,Germany,100,"Scala, Mathematics, Deep Learning",Bachelor,5,Education,2025-03-31,2025-06-03,1314,5.9,AI Innovations +AI02705,AI Research Scientist,318729,USD,318729,EX,CT,Denmark,L,Denmark,100,"SQL, PyTorch, MLOps, Scala",PhD,15,Transportation,2024-04-20,2024-06-26,1885,5.1,TechCorp Inc +AI02706,Head of AI,42907,USD,42907,SE,CT,India,S,India,50,"AWS, Spark, NLP",PhD,9,Energy,2025-01-08,2025-02-21,1752,6.7,Quantum Computing Inc +AI02707,AI Architect,35590,USD,35590,MI,CT,China,S,China,50,"Deep Learning, AWS, SQL, Kubernetes",PhD,2,Energy,2025-03-11,2025-04-17,2175,7.9,Machine Intelligence Group +AI02708,ML Ops Engineer,201427,USD,201427,EX,PT,Sweden,M,Sweden,0,"Python, SQL, MLOps, Azure",Bachelor,15,Media,2024-01-04,2024-02-17,1405,6.4,Smart Analytics +AI02709,Head of AI,206878,USD,206878,EX,PT,Israel,S,Portugal,100,"Java, R, Computer Vision, Git, GCP",PhD,11,Government,2024-05-17,2024-07-01,2015,7.1,Neural Networks Co +AI02710,Data Engineer,59555,AUD,80399,EN,FL,Australia,L,Sweden,0,"SQL, Deep Learning, Linux, Python, PyTorch",Master,0,Healthcare,2025-04-18,2025-06-12,631,8.4,Neural Networks Co +AI02711,Computer Vision Engineer,40698,USD,40698,MI,FL,China,L,Egypt,100,"R, PyTorch, Tableau, Scala",Associate,2,Healthcare,2025-04-19,2025-06-18,1730,6.9,Future Systems +AI02712,AI Consultant,60205,USD,60205,EN,FT,Ireland,S,Denmark,50,"AWS, Java, Data Visualization",Associate,1,Retail,2024-06-29,2024-07-18,2272,7,Cloud AI Solutions +AI02713,AI Research Scientist,153723,SGD,199840,EX,CT,Singapore,M,Singapore,0,"Deep Learning, Linux, Computer Vision",Associate,16,Transportation,2025-01-28,2025-04-02,743,5.1,DeepTech Ventures +AI02714,AI Architect,185811,USD,185811,EX,PT,Israel,S,Israel,50,"Hadoop, Kubernetes, Tableau, Spark",Associate,12,Government,2025-04-13,2025-05-26,513,6.5,Autonomous Tech +AI02715,AI Product Manager,49147,EUR,41775,EN,FL,Germany,S,Germany,0,"Data Visualization, Docker, Spark, TensorFlow, Statistics",PhD,1,Gaming,2024-02-05,2024-04-08,996,8.1,TechCorp Inc +AI02716,Computer Vision Engineer,102077,USD,102077,MI,PT,Norway,M,Norway,0,"Kubernetes, Java, Statistics, Mathematics",Bachelor,3,Education,2024-05-05,2024-05-26,2332,5.2,Cloud AI Solutions +AI02717,Robotics Engineer,62401,USD,62401,SE,CT,China,M,Kenya,100,"TensorFlow, Java, Azure, Tableau, R",PhD,6,Retail,2024-08-24,2024-09-25,889,5.4,Cloud AI Solutions +AI02718,AI Architect,107823,EUR,91650,SE,CT,Austria,M,Australia,50,"Statistics, PyTorch, Tableau, Scala",Associate,5,Media,2024-11-10,2024-12-26,1821,8.7,DeepTech Ventures +AI02719,AI Consultant,91347,EUR,77645,MI,CT,Austria,S,Austria,100,"AWS, Linux, Docker",PhD,3,Energy,2024-08-10,2024-10-11,539,6.3,DeepTech Ventures +AI02720,AI Specialist,51459,USD,51459,SE,PT,India,L,India,100,"R, Docker, Statistics, SQL",PhD,5,Transportation,2024-04-23,2024-05-30,1996,9,Smart Analytics +AI02721,AI Product Manager,81873,USD,81873,EN,FT,Denmark,M,Denmark,100,"Linux, Computer Vision, Data Visualization, Git",Associate,0,Healthcare,2024-08-19,2024-09-08,1229,9.3,Cloud AI Solutions +AI02722,ML Ops Engineer,83272,USD,83272,MI,CT,United States,S,United States,50,"Kubernetes, SQL, TensorFlow, NLP",Master,2,Real Estate,2024-05-23,2024-07-07,1214,5.3,Smart Analytics +AI02723,Machine Learning Researcher,116075,SGD,150898,SE,CT,Singapore,S,Singapore,50,"Python, Spark, Java, TensorFlow",Bachelor,7,Education,2024-08-23,2024-10-31,781,5.1,AI Innovations +AI02724,Head of AI,89742,USD,89742,SE,PT,Finland,S,Finland,0,"PyTorch, Statistics, Data Visualization, SQL",Bachelor,9,Telecommunications,2024-08-25,2024-09-19,1044,7.7,Smart Analytics +AI02725,Machine Learning Researcher,72250,USD,72250,EN,FL,Ireland,L,Nigeria,0,"MLOps, Git, PyTorch",Associate,1,Education,2024-10-28,2024-12-05,1070,8.1,Cloud AI Solutions +AI02726,AI Product Manager,89161,CHF,80245,EN,CT,Switzerland,M,Switzerland,100,"Kubernetes, Statistics, Tableau, Data Visualization",Master,1,Consulting,2025-03-04,2025-03-25,905,5.5,Digital Transformation LLC +AI02727,AI Software Engineer,248371,SGD,322882,EX,CT,Singapore,M,Singapore,100,"Spark, Python, Data Visualization, Kubernetes, Deep Learning",Master,19,Retail,2025-01-19,2025-03-05,628,9.1,Machine Intelligence Group +AI02728,Head of AI,237882,GBP,178412,EX,FL,United Kingdom,M,United Kingdom,0,"R, Linux, SQL, Mathematics, MLOps",PhD,12,Consulting,2024-11-11,2024-12-17,1603,7.7,Autonomous Tech +AI02729,AI Product Manager,234093,CHF,210684,SE,FT,Switzerland,L,Switzerland,0,"Data Visualization, TensorFlow, Statistics",Bachelor,8,Consulting,2025-03-21,2025-05-19,2420,5.4,Cloud AI Solutions +AI02730,Head of AI,69998,EUR,59498,EN,FT,France,M,France,50,"Azure, Kubernetes, Scala",Associate,1,Government,2024-07-17,2024-08-09,557,8.1,Algorithmic Solutions +AI02731,Principal Data Scientist,92320,EUR,78472,MI,FL,Netherlands,M,Norway,50,"R, SQL, Azure",Master,3,Government,2024-05-01,2024-06-25,2297,9.4,DeepTech Ventures +AI02732,Principal Data Scientist,61179,CAD,76474,EN,FT,Canada,S,Canada,100,"Hadoop, Kubernetes, MLOps, Docker",PhD,0,Media,2024-04-09,2024-05-11,1420,7.8,Autonomous Tech +AI02733,Deep Learning Engineer,61702,EUR,52447,MI,CT,France,S,France,50,"Java, Hadoop, Tableau, Kubernetes, AWS",Bachelor,3,Technology,2025-02-05,2025-02-20,1250,9,Autonomous Tech +AI02734,Autonomous Systems Engineer,85122,USD,85122,EN,FL,Norway,L,Norway,100,"PyTorch, TensorFlow, Azure, Git",Master,1,Energy,2024-03-29,2024-04-27,734,8,Quantum Computing Inc +AI02735,Data Analyst,78254,USD,78254,EN,PT,Denmark,M,Denmark,0,"TensorFlow, AWS, Hadoop",Bachelor,1,Technology,2025-01-25,2025-02-15,1718,8.4,Quantum Computing Inc +AI02736,AI Research Scientist,70895,USD,70895,EN,PT,Sweden,S,Sweden,50,"Scala, PyTorch, MLOps, SQL, Computer Vision",Associate,1,Government,2025-01-11,2025-03-18,1398,5.8,Future Systems +AI02737,Data Engineer,199927,USD,199927,SE,CT,Norway,L,Latvia,50,"SQL, Spark, PyTorch",Associate,6,Healthcare,2024-03-17,2024-04-02,1138,6.9,Cloud AI Solutions +AI02738,Deep Learning Engineer,170229,CAD,212786,EX,CT,Canada,M,United States,50,"Deep Learning, R, Hadoop, Kubernetes, SQL",Master,16,Retail,2024-03-29,2024-04-30,1109,8.8,Smart Analytics +AI02739,Data Engineer,154419,USD,154419,MI,FT,Norway,L,Norway,50,"Tableau, Computer Vision, Python, TensorFlow, Java",Master,4,Technology,2024-08-12,2024-10-08,1099,9.3,DataVision Ltd +AI02740,AI Product Manager,162643,EUR,138247,SE,CT,Netherlands,L,South Africa,100,"Python, TensorFlow, Tableau, PyTorch",PhD,9,Media,2024-03-24,2024-05-21,2247,7.3,Neural Networks Co +AI02741,Computer Vision Engineer,268185,JPY,29500350,EX,CT,Japan,L,Argentina,50,"Data Visualization, Spark, NLP",Bachelor,11,Automotive,2024-12-27,2025-01-16,942,8.7,TechCorp Inc +AI02742,Data Scientist,180863,GBP,135647,SE,PT,United Kingdom,L,United Kingdom,50,"Python, GCP, TensorFlow, NLP, PyTorch",Bachelor,5,Automotive,2024-01-21,2024-02-20,1397,7.6,Cognitive Computing +AI02743,Machine Learning Researcher,34377,USD,34377,EN,CT,China,L,China,0,"PyTorch, TensorFlow, Computer Vision, Mathematics",Bachelor,1,Real Estate,2024-03-01,2024-05-03,1626,5.8,Machine Intelligence Group +AI02744,Deep Learning Engineer,66309,USD,66309,EX,PT,China,M,China,100,"Spark, Tableau, Linux",Associate,12,Real Estate,2025-01-23,2025-04-05,2186,7.5,TechCorp Inc +AI02745,Computer Vision Engineer,151661,SGD,197159,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, NLP, Mathematics",Master,17,Automotive,2025-01-21,2025-03-24,2125,6,Algorithmic Solutions +AI02746,Principal Data Scientist,169405,JPY,18634550,EX,FL,Japan,M,Sweden,100,"R, Hadoop, Linux",Bachelor,10,Consulting,2024-02-12,2024-03-16,2077,9,DeepTech Ventures +AI02747,NLP Engineer,72571,JPY,7982810,EN,CT,Japan,S,Japan,50,"AWS, Hadoop, SQL, PyTorch",Associate,0,Consulting,2024-11-22,2025-01-29,1015,5,Machine Intelligence Group +AI02748,Data Scientist,240989,GBP,180742,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, TensorFlow, NLP, MLOps",PhD,15,Energy,2024-08-22,2024-10-13,2290,8.6,Future Systems +AI02749,Data Analyst,44658,USD,44658,EN,FL,Finland,S,Finland,0,"AWS, PyTorch, Tableau",Bachelor,1,Energy,2024-08-26,2024-10-14,1578,9.3,Smart Analytics +AI02750,Autonomous Systems Engineer,51559,EUR,43825,EN,CT,France,S,France,50,"Scala, Deep Learning, Computer Vision, PyTorch, SQL",PhD,1,Technology,2024-06-24,2024-07-27,2101,9.5,Cognitive Computing +AI02751,NLP Engineer,165686,CHF,149117,MI,CT,Switzerland,L,Switzerland,100,"Docker, Statistics, Python",Bachelor,2,Real Estate,2024-05-23,2024-06-23,1760,7.2,DeepTech Ventures +AI02752,Head of AI,105339,CHF,94805,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Git, Deep Learning, Data Visualization",Master,0,Healthcare,2024-08-02,2024-08-24,876,8,Algorithmic Solutions +AI02753,AI Software Engineer,209800,EUR,178330,EX,CT,Netherlands,M,Netherlands,0,"Kubernetes, Python, SQL",PhD,18,Consulting,2024-11-19,2024-12-05,2126,8.9,Predictive Systems +AI02754,AI Architect,118780,USD,118780,MI,FT,United States,M,United States,0,"SQL, Data Visualization, TensorFlow, MLOps",Associate,3,Consulting,2025-02-06,2025-03-13,933,6.8,Smart Analytics +AI02755,AI Consultant,125984,CAD,157480,SE,FL,Canada,S,Canada,100,"NLP, Java, Computer Vision",Bachelor,6,Finance,2024-10-30,2024-12-23,1473,9.1,Future Systems +AI02756,Research Scientist,121739,SGD,158261,SE,FT,Singapore,M,Singapore,0,"PyTorch, Java, Spark",PhD,6,Technology,2024-08-19,2024-10-25,1712,8.9,Cloud AI Solutions +AI02757,Deep Learning Engineer,141394,EUR,120185,SE,FT,Netherlands,M,Chile,50,"Hadoop, TensorFlow, Python",Bachelor,5,Telecommunications,2024-05-08,2024-06-01,1923,8.8,Cloud AI Solutions +AI02758,Machine Learning Researcher,74325,USD,74325,EN,FL,Norway,S,Norway,0,"Linux, MLOps, SQL, R",Master,0,Technology,2024-06-21,2024-08-02,2350,9.2,DataVision Ltd +AI02759,Head of AI,181015,SGD,235320,SE,PT,Singapore,L,Singapore,100,"Java, SQL, GCP",Master,7,Technology,2025-03-01,2025-03-26,968,6.6,Cognitive Computing +AI02760,NLP Engineer,54802,SGD,71243,EN,FT,Singapore,M,Singapore,0,"Scala, Python, Docker, Computer Vision",Bachelor,0,Healthcare,2025-03-24,2025-05-20,733,6.3,Smart Analytics +AI02761,Data Analyst,113391,JPY,12473010,MI,PT,Japan,M,Japan,100,"Scala, Data Visualization, Git, Spark",Master,3,Automotive,2024-04-11,2024-05-16,865,8.5,Future Systems +AI02762,NLP Engineer,171064,USD,171064,EX,CT,Ireland,L,Ireland,50,"AWS, PyTorch, Computer Vision, Hadoop, SQL",Bachelor,15,Consulting,2024-11-10,2024-12-27,1791,7.2,Cloud AI Solutions +AI02763,Head of AI,122125,USD,122125,MI,FT,Denmark,M,Denmark,100,"Scala, Tableau, Python, Linux",Bachelor,3,Media,2024-10-08,2024-12-18,1199,7.4,Cognitive Computing +AI02764,Machine Learning Engineer,133237,AUD,179870,SE,CT,Australia,S,Australia,50,"Python, Hadoop, Linux, Scala, Computer Vision",Associate,5,Retail,2024-04-22,2024-06-26,1707,8.4,Machine Intelligence Group +AI02765,Deep Learning Engineer,89475,JPY,9842250,EN,PT,Japan,L,Japan,100,"Python, TensorFlow, Git, Mathematics, Spark",PhD,1,Transportation,2025-01-01,2025-02-27,1924,5.1,DeepTech Ventures +AI02766,AI Product Manager,92805,USD,92805,MI,FL,United States,S,New Zealand,50,"Linux, Spark, Scala, MLOps",Associate,2,Government,2024-04-10,2024-06-21,1389,8,Digital Transformation LLC +AI02767,AI Product Manager,277302,AUD,374358,EX,PT,Australia,L,Australia,100,"Git, Statistics, TensorFlow, SQL, Kubernetes",Master,14,Finance,2024-03-27,2024-05-08,1139,5.7,Quantum Computing Inc +AI02768,AI Consultant,157131,USD,157131,SE,FT,Norway,L,Norway,50,"Spark, Tableau, Computer Vision, NLP",PhD,8,Automotive,2024-07-01,2024-08-31,1981,7.3,Cognitive Computing +AI02769,Machine Learning Engineer,124242,EUR,105606,SE,CT,France,S,Singapore,50,"Spark, Mathematics, MLOps",Master,6,Media,2024-04-29,2024-07-09,2466,9.1,Predictive Systems +AI02770,Robotics Engineer,165005,AUD,222757,EX,FL,Australia,L,Austria,0,"Mathematics, Computer Vision, Data Visualization, Statistics",PhD,18,Education,2024-08-08,2024-09-14,1077,7.9,Quantum Computing Inc +AI02771,Data Analyst,55240,EUR,46954,EN,CT,Austria,S,Austria,0,"Kubernetes, Deep Learning, Git",Bachelor,1,Finance,2024-06-24,2024-08-24,1766,9.7,Neural Networks Co +AI02772,Robotics Engineer,39042,USD,39042,SE,PT,India,M,Colombia,0,"Deep Learning, Linux, Java",Bachelor,6,Manufacturing,2025-02-28,2025-04-17,655,8.5,Autonomous Tech +AI02773,Machine Learning Researcher,64577,USD,64577,EX,FL,India,M,India,50,"NLP, SQL, Scala",Bachelor,15,Government,2024-03-01,2024-04-21,1560,6.6,Cognitive Computing +AI02774,Head of AI,50657,USD,50657,EN,CT,Israel,S,Israel,0,"Python, Java, Tableau, TensorFlow, Mathematics",PhD,0,Real Estate,2024-11-23,2024-12-14,1622,9.1,TechCorp Inc +AI02775,Machine Learning Engineer,108147,GBP,81110,SE,FL,United Kingdom,M,Switzerland,100,"MLOps, Kubernetes, R",Associate,6,Finance,2025-02-07,2025-02-25,690,5.1,Future Systems +AI02776,Robotics Engineer,186468,USD,186468,EX,FL,Norway,M,Norway,100,"TensorFlow, AWS, Data Visualization, Python",Master,17,Automotive,2024-09-06,2024-10-09,2476,5.1,Digital Transformation LLC +AI02777,Data Engineer,148941,EUR,126600,SE,PT,Germany,M,Germany,0,"Python, NLP, Docker, GCP",Bachelor,6,Media,2025-04-24,2025-05-18,2164,9.1,Digital Transformation LLC +AI02778,AI Software Engineer,61003,USD,61003,EN,FT,Norway,S,Norway,100,"Statistics, Computer Vision, Data Visualization",PhD,0,Manufacturing,2025-04-09,2025-05-26,847,7.2,Cloud AI Solutions +AI02779,ML Ops Engineer,130513,USD,130513,SE,PT,Ireland,L,Ireland,0,"Linux, Kubernetes, Scala, Java",Bachelor,9,Technology,2024-05-30,2024-06-22,1034,5.3,Future Systems +AI02780,AI Architect,218583,EUR,185796,EX,FT,France,L,France,100,"Hadoop, R, SQL, PyTorch, Git",PhD,18,Gaming,2024-05-06,2024-06-10,1862,9.4,Machine Intelligence Group +AI02781,AI Consultant,57623,USD,57623,EN,FT,Sweden,S,Sweden,50,"Tableau, AWS, Hadoop, Docker, Statistics",Bachelor,0,Media,2024-05-30,2024-06-20,973,9.8,Future Systems +AI02782,AI Product Manager,63893,USD,63893,EN,FL,South Korea,M,Australia,0,"Linux, Deep Learning, Java, SQL, AWS",PhD,1,Finance,2025-01-12,2025-01-27,984,9.8,Smart Analytics +AI02783,AI Consultant,198531,USD,198531,EX,FL,Norway,M,Norway,100,"AWS, Kubernetes, NLP, Statistics",Associate,12,Transportation,2025-04-14,2025-05-14,1650,9.5,Cognitive Computing +AI02784,Machine Learning Researcher,66355,SGD,86262,EN,FT,Singapore,S,Singapore,100,"Kubernetes, Tableau, Hadoop",PhD,1,Finance,2024-03-10,2024-03-28,762,8.1,Cognitive Computing +AI02785,Head of AI,71500,USD,71500,EN,FT,Finland,L,Finland,0,"R, Hadoop, Linux, SQL, Computer Vision",Master,1,Automotive,2025-01-26,2025-04-01,1426,6.3,AI Innovations +AI02786,AI Specialist,99853,USD,99853,MI,FT,Israel,L,Israel,0,"Computer Vision, Kubernetes, SQL, Docker",Master,2,Consulting,2025-01-07,2025-03-21,679,10,AI Innovations +AI02787,Autonomous Systems Engineer,160109,CHF,144098,SE,PT,Switzerland,M,Thailand,100,"MLOps, AWS, Spark, R",Master,5,Consulting,2024-02-18,2024-03-28,914,9,Digital Transformation LLC +AI02788,AI Specialist,126146,USD,126146,SE,CT,Sweden,M,United Kingdom,50,"PyTorch, TensorFlow, R, SQL, Spark",Master,9,Media,2025-03-06,2025-05-10,2264,8.7,Quantum Computing Inc +AI02789,AI Consultant,32128,USD,32128,EN,PT,China,L,China,50,"Python, Spark, MLOps, TensorFlow, Scala",Master,0,Media,2024-04-23,2024-07-02,1091,7.4,Future Systems +AI02790,AI Software Engineer,23707,USD,23707,EN,FL,India,M,Spain,0,"PyTorch, Hadoop, Deep Learning, Linux",Bachelor,1,Healthcare,2024-03-02,2024-04-27,1306,9.8,Predictive Systems +AI02791,Data Scientist,210918,CAD,263648,EX,FT,Canada,L,Japan,50,"Python, R, Docker, Linux",Master,10,Energy,2024-01-03,2024-01-31,881,7.5,Future Systems +AI02792,AI Architect,132476,EUR,112605,SE,CT,France,L,France,50,"PyTorch, Spark, Statistics, Python",PhD,6,Education,2024-10-16,2024-11-05,2332,7.4,Digital Transformation LLC +AI02793,Research Scientist,97049,EUR,82492,SE,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Git",PhD,5,Telecommunications,2025-01-10,2025-03-02,1819,8.1,Smart Analytics +AI02794,AI Software Engineer,52529,CAD,65661,EN,FT,Canada,M,Ireland,100,"MLOps, Spark, Tableau, Scala, Statistics",Master,0,Manufacturing,2024-03-06,2024-04-27,2052,5.1,Cognitive Computing +AI02795,Principal Data Scientist,204220,EUR,173587,EX,PT,Austria,S,Egypt,50,"Computer Vision, Deep Learning, Linux",Bachelor,12,Automotive,2024-03-24,2024-04-13,607,8.7,TechCorp Inc +AI02796,AI Software Engineer,132720,SGD,172536,SE,FL,Singapore,L,Singapore,50,"R, Hadoop, Tableau",Bachelor,8,Media,2024-08-04,2024-10-16,1384,6.8,Advanced Robotics +AI02797,Autonomous Systems Engineer,81244,USD,81244,MI,CT,Finland,L,Finland,50,"Docker, Hadoop, Statistics, Linux",Master,4,Manufacturing,2024-05-17,2024-06-27,1528,9.8,Machine Intelligence Group +AI02798,Machine Learning Researcher,161739,USD,161739,MI,FL,Norway,L,Norway,100,"NLP, Kubernetes, PyTorch, Docker, SQL",Master,3,Automotive,2024-04-06,2024-06-08,1521,6.4,DataVision Ltd +AI02799,ML Ops Engineer,71582,CAD,89478,MI,CT,Canada,S,Canada,0,"Kubernetes, Scala, AWS, TensorFlow",PhD,4,Manufacturing,2025-01-18,2025-02-05,865,9.2,DataVision Ltd +AI02800,Robotics Engineer,55770,USD,55770,SE,PT,China,S,China,0,"Docker, R, AWS, Python, Kubernetes",Bachelor,6,Manufacturing,2025-02-17,2025-03-12,1015,9.6,Smart Analytics +AI02801,AI Product Manager,176027,USD,176027,SE,CT,Norway,M,Norway,0,"R, SQL, Tableau",Bachelor,7,Government,2024-08-01,2024-10-05,1205,5.3,Machine Intelligence Group +AI02802,AI Product Manager,47687,USD,47687,SE,CT,India,L,Japan,0,"Data Visualization, TensorFlow, Statistics",Associate,9,Telecommunications,2024-07-20,2024-09-18,681,6.2,Advanced Robotics +AI02803,Autonomous Systems Engineer,60812,USD,60812,MI,PT,South Korea,M,South Korea,0,"R, Git, Deep Learning, GCP",Master,4,Finance,2024-07-02,2024-08-07,628,7.4,Predictive Systems +AI02804,Research Scientist,126567,JPY,13922370,MI,PT,Japan,L,Netherlands,50,"PyTorch, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-12-15,2024-12-29,2386,7.1,Cognitive Computing +AI02805,Research Scientist,97033,SGD,126143,MI,CT,Singapore,S,France,0,"Azure, GCP, Spark, Statistics, Computer Vision",Master,2,Real Estate,2025-02-08,2025-04-19,2196,9.6,Future Systems +AI02806,AI Specialist,70605,USD,70605,EN,FL,Norway,S,Norway,0,"Kubernetes, GCP, Spark, Tableau, Python",Bachelor,0,Consulting,2024-08-04,2024-09-14,1382,8.9,Autonomous Tech +AI02807,Deep Learning Engineer,121078,USD,121078,SE,FT,Israel,L,Israel,50,"Computer Vision, Azure, Data Visualization, Java",Bachelor,5,Retail,2024-06-11,2024-07-22,1033,5.9,DeepTech Ventures +AI02808,ML Ops Engineer,255771,USD,255771,EX,FT,Denmark,S,Denmark,0,"Azure, Kubernetes, Tableau, Python, Hadoop",Master,10,Transportation,2024-11-13,2025-01-14,1097,5.4,Machine Intelligence Group +AI02809,Data Engineer,111629,EUR,94885,SE,PT,France,L,France,50,"Tableau, Statistics, Spark",Master,9,Healthcare,2024-02-07,2024-03-13,1123,6.3,DeepTech Ventures +AI02810,Autonomous Systems Engineer,127275,USD,127275,MI,PT,Denmark,S,Denmark,100,"Java, AWS, SQL, NLP, Deep Learning",Associate,3,Automotive,2024-08-07,2024-09-19,2009,7,Smart Analytics +AI02811,Robotics Engineer,226295,USD,226295,EX,FL,Ireland,S,New Zealand,100,"Docker, Python, AWS",Associate,19,Consulting,2025-01-26,2025-02-12,615,7.6,Autonomous Tech +AI02812,AI Consultant,60249,USD,60249,EN,FL,Sweden,M,Sweden,50,"Scala, Mathematics, Tableau, Statistics, MLOps",Associate,0,Real Estate,2024-01-15,2024-03-05,2151,5.3,Quantum Computing Inc +AI02813,Principal Data Scientist,154394,USD,154394,SE,FL,United States,S,United States,0,"Kubernetes, Hadoop, Python, Azure",Master,5,Manufacturing,2024-04-19,2024-06-20,611,9.2,Digital Transformation LLC +AI02814,Deep Learning Engineer,77141,EUR,65570,MI,CT,Netherlands,S,Russia,0,"Kubernetes, Data Visualization, Mathematics",Associate,2,Automotive,2025-03-24,2025-04-09,1999,7.6,DataVision Ltd +AI02815,AI Product Manager,89813,EUR,76341,MI,PT,Austria,M,Austria,100,"GCP, Java, PyTorch",Associate,2,Technology,2024-06-20,2024-08-20,2490,8.9,Algorithmic Solutions +AI02816,Research Scientist,80989,USD,80989,MI,FT,Finland,S,Finland,0,"R, Statistics, Hadoop, Docker",PhD,4,Retail,2025-02-14,2025-04-25,540,8.4,DataVision Ltd +AI02817,Data Engineer,271778,CHF,244600,EX,PT,Switzerland,L,Switzerland,50,"AWS, Scala, Docker",Bachelor,12,Consulting,2024-03-23,2024-05-31,1285,5.1,Algorithmic Solutions +AI02818,AI Research Scientist,46378,USD,46378,SE,FL,India,S,India,100,"SQL, NLP, PyTorch",Associate,9,Finance,2025-01-26,2025-02-11,1773,9.2,Digital Transformation LLC +AI02819,Principal Data Scientist,101913,EUR,86626,MI,FL,Germany,L,Germany,50,"Spark, Java, MLOps, PyTorch",PhD,3,Telecommunications,2025-01-12,2025-03-23,2063,7.4,Quantum Computing Inc +AI02820,Data Analyst,29407,USD,29407,MI,PT,India,M,India,50,"SQL, TensorFlow, Tableau",PhD,4,Retail,2024-04-30,2024-06-23,2053,5.5,Predictive Systems +AI02821,AI Specialist,122457,USD,122457,EX,FL,South Korea,M,South Korea,0,"Scala, Deep Learning, R, Hadoop, Statistics",Master,12,Automotive,2024-03-13,2024-05-23,595,6.7,Machine Intelligence Group +AI02822,AI Research Scientist,121296,EUR,103102,SE,CT,France,M,Philippines,100,"Data Visualization, SQL, PyTorch",PhD,6,Technology,2024-02-12,2024-03-24,602,6.3,Neural Networks Co +AI02823,AI Specialist,154186,USD,154186,SE,CT,Norway,S,Norway,0,"Git, PyTorch, Tableau, MLOps",PhD,6,Gaming,2024-11-07,2024-12-15,1374,9.5,AI Innovations +AI02824,Robotics Engineer,215813,CAD,269766,EX,CT,Canada,S,Canada,0,"Python, Hadoop, SQL",Master,17,Government,2025-01-06,2025-02-04,664,6.1,TechCorp Inc +AI02825,Robotics Engineer,121313,SGD,157707,MI,FT,Singapore,L,Switzerland,50,"Git, NLP, PyTorch, Python",Associate,4,Gaming,2024-10-05,2024-11-20,1250,8,Predictive Systems +AI02826,Machine Learning Researcher,103697,JPY,11406670,MI,CT,Japan,S,Japan,0,"SQL, Scala, Hadoop, Azure",Bachelor,2,Energy,2024-01-30,2024-03-07,657,5.6,Algorithmic Solutions +AI02827,Research Scientist,148481,CHF,133633,MI,FT,Switzerland,M,Switzerland,0,"Python, MLOps, SQL, Java, Kubernetes",Bachelor,3,Manufacturing,2024-07-11,2024-09-16,1271,8.3,Future Systems +AI02828,AI Software Engineer,247799,USD,247799,EX,CT,Norway,S,Norway,50,"PyTorch, SQL, Linux, Hadoop",Associate,18,Media,2024-04-27,2024-06-30,717,7.8,Cognitive Computing +AI02829,Autonomous Systems Engineer,250860,USD,250860,EX,FL,United States,M,United States,50,"SQL, Tableau, Kubernetes, GCP",Associate,10,Transportation,2024-06-25,2024-07-11,891,7.8,Quantum Computing Inc +AI02830,Research Scientist,163167,AUD,220275,EX,CT,Australia,S,Australia,100,"Kubernetes, Java, GCP, SQL, AWS",Bachelor,19,Energy,2024-01-27,2024-04-03,1603,5.9,Autonomous Tech +AI02831,Principal Data Scientist,323671,USD,323671,EX,CT,United States,L,United States,50,"Computer Vision, Hadoop, Deep Learning",PhD,15,Telecommunications,2025-04-28,2025-06-15,1701,8.3,TechCorp Inc +AI02832,Robotics Engineer,70337,USD,70337,EN,FT,Norway,S,Norway,100,"Hadoop, NLP, SQL, Scala",Associate,1,Healthcare,2024-08-27,2024-10-10,888,9.2,Machine Intelligence Group +AI02833,Data Analyst,63357,EUR,53853,EN,FL,Germany,M,Egypt,100,"Mathematics, Data Visualization, Scala, SQL, Tableau",Bachelor,1,Government,2025-02-15,2025-03-29,2153,5.6,Digital Transformation LLC +AI02834,Head of AI,107154,USD,107154,SE,FL,Israel,S,Israel,0,"PyTorch, GCP, NLP, Java",Master,8,Healthcare,2024-06-22,2024-08-26,1412,6.5,TechCorp Inc +AI02835,AI Research Scientist,184525,USD,184525,SE,PT,Norway,M,Norway,0,"SQL, Python, AWS, TensorFlow",Master,5,Retail,2024-01-26,2024-02-09,2036,5.8,Algorithmic Solutions +AI02836,Robotics Engineer,94391,EUR,80232,MI,FL,Austria,L,Austria,100,"Spark, PyTorch, Python, MLOps",Master,3,Media,2025-01-05,2025-01-27,1704,5.7,Smart Analytics +AI02837,NLP Engineer,134275,USD,134275,SE,FL,South Korea,L,South Korea,0,"Spark, Azure, Computer Vision, Data Visualization, SQL",PhD,9,Automotive,2024-08-26,2024-11-05,1728,5.9,Autonomous Tech +AI02838,AI Consultant,211162,USD,211162,EX,FT,United States,M,United States,50,"Spark, Python, Tableau",PhD,19,Technology,2024-04-12,2024-05-17,2411,9.2,DataVision Ltd +AI02839,Computer Vision Engineer,70647,USD,70647,EN,PT,Ireland,L,Ireland,0,"Python, Statistics, Mathematics, Docker, TensorFlow",Bachelor,0,Education,2024-07-17,2024-09-10,1471,9.5,DataVision Ltd +AI02840,Principal Data Scientist,243402,USD,243402,EX,FT,Finland,L,Finland,0,"AWS, NLP, Docker, Linux",Bachelor,11,Consulting,2024-04-28,2024-05-12,2037,8.1,Digital Transformation LLC +AI02841,AI Product Manager,57000,USD,57000,EN,FL,South Korea,S,India,100,"Linux, SQL, Scala",Associate,0,Finance,2024-11-08,2025-01-03,1424,7.6,Smart Analytics +AI02842,Data Analyst,90610,USD,90610,MI,CT,Israel,S,Israel,50,"Kubernetes, Scala, Mathematics",PhD,4,Telecommunications,2025-02-14,2025-03-18,2329,9.1,Future Systems +AI02843,Research Scientist,240830,EUR,204706,EX,FL,Austria,L,Austria,50,"PyTorch, SQL, Java, Linux, Statistics",PhD,16,Manufacturing,2024-03-29,2024-04-13,563,9.3,Smart Analytics +AI02844,Robotics Engineer,205777,EUR,174910,EX,FL,Austria,L,Colombia,0,"GCP, Spark, TensorFlow, Git",Bachelor,11,Healthcare,2025-04-18,2025-05-27,1273,6.4,DataVision Ltd +AI02845,Machine Learning Researcher,52483,USD,52483,EN,FT,Finland,M,Finland,100,"Hadoop, Data Visualization, SQL",Bachelor,0,Manufacturing,2024-08-30,2024-09-21,1921,9.4,Neural Networks Co +AI02846,Principal Data Scientist,35085,USD,35085,MI,PT,India,M,India,50,"Python, TensorFlow, Mathematics, Hadoop",Associate,4,Media,2025-04-17,2025-05-05,525,9.2,Algorithmic Solutions +AI02847,Principal Data Scientist,170138,USD,170138,SE,PT,Ireland,L,Belgium,0,"Linux, Python, TensorFlow, AWS, Tableau",Master,7,Technology,2025-04-08,2025-05-22,1991,7.6,Advanced Robotics +AI02848,AI Software Engineer,86746,USD,86746,MI,FT,Ireland,M,Turkey,100,"Docker, SQL, Computer Vision",Associate,2,Consulting,2024-12-19,2025-02-26,2126,7.6,Predictive Systems +AI02849,Data Analyst,27601,USD,27601,MI,FT,India,S,India,50,"Python, TensorFlow, Mathematics, MLOps, SQL",Bachelor,4,Technology,2024-05-17,2024-07-06,2050,9.4,Future Systems +AI02850,Principal Data Scientist,114696,USD,114696,SE,FT,Sweden,S,Sweden,0,"Computer Vision, Java, Git, TensorFlow",Associate,7,Government,2025-02-28,2025-05-10,736,6,Neural Networks Co +AI02851,Data Analyst,123445,USD,123445,SE,FT,Finland,M,Canada,50,"Kubernetes, Python, AWS, SQL",Master,5,Telecommunications,2025-04-26,2025-06-15,1506,5.1,Quantum Computing Inc +AI02852,Head of AI,70615,USD,70615,EN,CT,South Korea,L,South Korea,50,"PyTorch, GCP, Linux, Spark",Associate,0,Automotive,2025-04-16,2025-06-19,1374,5.4,Neural Networks Co +AI02853,Data Scientist,190307,CAD,237884,EX,CT,Canada,L,Canada,100,"Statistics, Kubernetes, Azure",Master,17,Consulting,2024-03-30,2024-04-16,746,5.6,Cognitive Computing +AI02854,AI Software Engineer,319590,USD,319590,EX,FL,United States,L,United States,100,"PyTorch, MLOps, GCP",Master,19,Government,2024-01-01,2024-03-14,720,6.4,Cloud AI Solutions +AI02855,AI Research Scientist,207479,USD,207479,SE,PT,Norway,L,China,0,"NLP, Python, Computer Vision, Mathematics",Master,7,Technology,2024-06-03,2024-06-17,2025,6.2,Cloud AI Solutions +AI02856,AI Product Manager,131422,USD,131422,MI,FL,United States,L,Vietnam,50,"Java, Computer Vision, AWS",Associate,4,Gaming,2024-05-24,2024-07-17,1676,5.2,Digital Transformation LLC +AI02857,ML Ops Engineer,95848,EUR,81471,MI,PT,Germany,M,Thailand,0,"Linux, Spark, Deep Learning",Associate,4,Consulting,2024-09-08,2024-10-22,919,5.3,Predictive Systems +AI02858,Robotics Engineer,94145,JPY,10355950,MI,FL,Japan,L,Japan,50,"Python, R, Mathematics, Scala, NLP",PhD,4,Real Estate,2024-01-20,2024-03-09,721,7.5,AI Innovations +AI02859,AI Consultant,130395,CAD,162994,SE,CT,Canada,L,Canada,100,"GCP, Python, MLOps, Kubernetes",PhD,9,Real Estate,2024-12-01,2025-02-05,1098,6.4,Neural Networks Co +AI02860,Robotics Engineer,77116,EUR,65549,EN,CT,Germany,M,Germany,100,"Kubernetes, Computer Vision, Hadoop",Associate,0,Education,2024-03-23,2024-05-01,2136,5.7,Algorithmic Solutions +AI02861,Robotics Engineer,21922,USD,21922,EN,PT,India,L,Romania,50,"Spark, Java, GCP",Bachelor,0,Finance,2024-11-06,2025-01-12,624,5.3,TechCorp Inc +AI02862,AI Research Scientist,248823,USD,248823,EX,CT,United States,S,United States,100,"Python, Git, Mathematics, TensorFlow, Statistics",Bachelor,13,Education,2024-10-05,2024-12-01,990,6.8,Advanced Robotics +AI02863,Head of AI,36405,USD,36405,MI,PT,India,M,India,100,"Linux, Deep Learning, Python, NLP",Master,3,Automotive,2024-10-21,2024-11-13,2089,5.7,DataVision Ltd +AI02864,Principal Data Scientist,253609,EUR,215568,EX,CT,France,L,France,50,"Spark, Tableau, Linux, Python, R",PhD,15,Transportation,2024-10-23,2024-11-12,2390,6,Advanced Robotics +AI02865,NLP Engineer,203699,CHF,183329,SE,CT,Switzerland,M,China,0,"Python, Kubernetes, Computer Vision, TensorFlow, Statistics",PhD,5,Media,2025-02-04,2025-02-21,1665,7.3,Autonomous Tech +AI02866,Machine Learning Engineer,141871,CHF,127684,MI,FL,Switzerland,M,Estonia,100,"Scala, SQL, TensorFlow, Java",Bachelor,2,Finance,2024-01-19,2024-03-02,1034,7.5,Machine Intelligence Group +AI02867,AI Consultant,190310,AUD,256919,EX,PT,Australia,S,Australia,50,"Linux, PyTorch, R, Computer Vision, Python",PhD,10,Technology,2024-11-23,2024-12-18,793,9.6,Smart Analytics +AI02868,Data Scientist,68143,USD,68143,MI,CT,South Korea,S,China,50,"Mathematics, TensorFlow, Git, Python",PhD,2,Gaming,2024-12-29,2025-02-07,560,9.2,Autonomous Tech +AI02869,Robotics Engineer,74136,USD,74136,EN,FL,Ireland,L,Ireland,50,"Statistics, SQL, Azure",PhD,1,Automotive,2024-03-27,2024-06-01,886,9.6,DeepTech Ventures +AI02870,NLP Engineer,73619,EUR,62576,EN,CT,France,L,Estonia,0,"Kubernetes, R, MLOps",PhD,0,Telecommunications,2025-01-26,2025-04-04,1664,6.1,Digital Transformation LLC +AI02871,Research Scientist,77655,USD,77655,EN,PT,Denmark,M,Denmark,50,"Python, Spark, NLP, Java, SQL",Master,0,Media,2025-03-02,2025-05-04,859,9.1,Cloud AI Solutions +AI02872,NLP Engineer,123447,EUR,104930,SE,FL,Austria,S,Austria,50,"Python, TensorFlow, MLOps, Computer Vision",Associate,5,Retail,2024-11-21,2025-01-28,2155,9,Neural Networks Co +AI02873,AI Software Engineer,89174,USD,89174,MI,FL,United States,S,United States,50,"Linux, Statistics, SQL",PhD,4,Gaming,2024-04-10,2024-04-27,1358,7.6,Neural Networks Co +AI02874,Data Analyst,59752,USD,59752,SE,FT,India,L,India,100,"Deep Learning, SQL, Data Visualization, PyTorch, Hadoop",Associate,8,Retail,2024-07-17,2024-09-08,1777,6.7,Neural Networks Co +AI02875,AI Research Scientist,82657,USD,82657,EN,FT,United States,M,United States,100,"MLOps, Python, Linux, Deep Learning",Master,0,Consulting,2025-01-17,2025-03-14,1168,7.6,Digital Transformation LLC +AI02876,Data Analyst,60940,GBP,45705,EN,FL,United Kingdom,M,United Kingdom,50,"GCP, Statistics, Tableau, Data Visualization, NLP",Associate,1,Finance,2025-02-28,2025-04-30,1822,9.4,TechCorp Inc +AI02877,AI Specialist,147265,EUR,125175,EX,FT,Germany,M,Indonesia,50,"Kubernetes, Hadoop, PyTorch, Azure, Git",PhD,15,Real Estate,2024-04-11,2024-05-31,1634,7.4,Future Systems +AI02878,AI Research Scientist,87462,USD,87462,MI,PT,United States,M,Turkey,50,"Git, R, Mathematics, Linux",Associate,4,Telecommunications,2024-09-29,2024-11-18,808,5.4,DeepTech Ventures +AI02879,Principal Data Scientist,203296,CAD,254120,EX,FL,Canada,S,Canada,0,"Java, MLOps, R, Scala",Master,14,Telecommunications,2024-03-01,2024-04-12,1334,9.5,Machine Intelligence Group +AI02880,Machine Learning Researcher,102443,USD,102443,EN,FT,United States,L,Turkey,0,"NLP, TensorFlow, Data Visualization",PhD,0,Technology,2024-07-06,2024-08-13,2438,5.9,TechCorp Inc +AI02881,Autonomous Systems Engineer,165965,SGD,215755,EX,FL,Singapore,S,Singapore,50,"PyTorch, TensorFlow, Python, Statistics, Azure",Master,14,Healthcare,2024-03-31,2024-04-24,567,8.1,Algorithmic Solutions +AI02882,Computer Vision Engineer,142165,USD,142165,SE,FT,Israel,M,Thailand,0,"Python, Tableau, TensorFlow, Mathematics, PyTorch",Bachelor,6,Finance,2024-10-08,2024-12-12,544,8.6,DeepTech Ventures +AI02883,ML Ops Engineer,96944,SGD,126027,MI,FL,Singapore,S,Singapore,100,"Data Visualization, Linux, Scala, Azure",Associate,4,Consulting,2024-11-16,2025-01-19,2107,6,Quantum Computing Inc +AI02884,Data Analyst,101791,USD,101791,MI,FT,Norway,S,Norway,50,"R, Python, TensorFlow, Spark, Computer Vision",Bachelor,2,Technology,2024-04-23,2024-06-20,1704,7.1,Predictive Systems +AI02885,Data Engineer,24801,USD,24801,EN,FL,India,L,Estonia,100,"Scala, Spark, Python, Statistics",Bachelor,1,Manufacturing,2024-07-18,2024-08-18,2393,5.5,AI Innovations +AI02886,AI Specialist,76230,USD,76230,MI,CT,South Korea,M,South Korea,0,"GCP, PyTorch, Computer Vision",Master,3,Real Estate,2024-01-22,2024-03-16,1380,8.2,Future Systems +AI02887,AI Research Scientist,63817,CAD,79771,MI,FL,Canada,S,France,100,"PyTorch, Computer Vision, Mathematics",Bachelor,3,Consulting,2024-06-03,2024-08-12,1787,6.4,Algorithmic Solutions +AI02888,AI Specialist,65577,EUR,55740,MI,FL,Austria,S,Austria,0,"Scala, Mathematics, Linux, MLOps",Associate,3,Energy,2024-10-11,2024-11-04,1471,7.3,TechCorp Inc +AI02889,Autonomous Systems Engineer,114972,JPY,12646920,MI,FT,Japan,M,Japan,100,"Docker, Mathematics, Hadoop",PhD,3,Education,2024-01-25,2024-03-24,1490,7.5,Neural Networks Co +AI02890,AI Product Manager,87185,EUR,74107,SE,PT,Austria,S,Austria,100,"Spark, GCP, Git, Python",PhD,9,Consulting,2024-11-04,2024-12-27,2477,8.8,Autonomous Tech +AI02891,Deep Learning Engineer,212207,CHF,190986,SE,CT,Switzerland,M,Switzerland,100,"Tableau, Scala, Java, Spark, Linux",PhD,8,Gaming,2024-07-14,2024-08-24,519,6.9,Future Systems +AI02892,Machine Learning Engineer,90028,USD,90028,EN,PT,Denmark,L,Denmark,50,"R, SQL, PyTorch, Statistics, Kubernetes",Associate,1,Education,2024-12-24,2025-01-19,2044,7.2,DeepTech Ventures +AI02893,AI Product Manager,156876,JPY,17256360,SE,PT,Japan,L,Ireland,100,"Java, AWS, Computer Vision, Deep Learning",PhD,5,Gaming,2024-08-10,2024-08-28,1727,8.8,Neural Networks Co +AI02894,AI Consultant,116522,USD,116522,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Mathematics, Deep Learning",PhD,6,Manufacturing,2024-03-20,2024-05-09,2027,8.7,Neural Networks Co +AI02895,ML Ops Engineer,156992,CAD,196240,SE,FT,Canada,L,Denmark,0,"Data Visualization, Java, R",Associate,6,Technology,2025-01-28,2025-03-05,2468,9.3,Smart Analytics +AI02896,AI Architect,86246,USD,86246,EN,PT,Sweden,L,Denmark,0,"Java, Linux, Computer Vision, Python",PhD,0,Energy,2024-08-30,2024-09-15,1034,5,DeepTech Ventures +AI02897,Research Scientist,71217,EUR,60534,EN,CT,Austria,M,Israel,0,"GCP, Docker, Statistics, Kubernetes",PhD,1,Media,2024-12-13,2025-01-08,2027,7.4,Neural Networks Co +AI02898,AI Consultant,206746,EUR,175734,EX,CT,Netherlands,L,Netherlands,100,"AWS, Spark, Python",Associate,14,Government,2024-05-22,2024-06-24,1248,8.7,Algorithmic Solutions +AI02899,AI Consultant,169673,EUR,144222,EX,FL,Netherlands,S,Hungary,100,"Git, Scala, AWS",PhD,17,Technology,2024-02-11,2024-04-01,749,8.9,Algorithmic Solutions +AI02900,AI Product Manager,144440,GBP,108330,EX,FL,United Kingdom,S,United Kingdom,0,"NLP, Hadoop, Python",Associate,16,Gaming,2024-10-20,2024-11-19,1944,5.2,Cognitive Computing +AI02901,Machine Learning Engineer,153212,EUR,130230,EX,FT,France,L,France,100,"Deep Learning, Tableau, Python, TensorFlow, Data Visualization",PhD,16,Real Estate,2024-11-14,2025-01-01,1882,5.3,Future Systems +AI02902,Head of AI,204044,EUR,173437,EX,FL,France,S,France,0,"Python, Spark, Deep Learning",PhD,10,Education,2024-11-25,2025-01-31,788,9.1,Smart Analytics +AI02903,Autonomous Systems Engineer,151754,EUR,128991,SE,FT,Germany,L,Germany,100,"Scala, R, Tableau, SQL, GCP",Bachelor,7,Media,2025-04-30,2025-07-05,966,7.8,Quantum Computing Inc +AI02904,Computer Vision Engineer,31800,USD,31800,MI,FT,India,M,India,0,"Scala, Java, Statistics, Tableau",Associate,3,Gaming,2024-01-12,2024-02-28,977,8.8,Neural Networks Co +AI02905,Machine Learning Researcher,58310,JPY,6414100,EN,FL,Japan,M,Japan,0,"R, Docker, NLP, AWS, Hadoop",Bachelor,0,Retail,2024-09-22,2024-11-09,2121,9.9,TechCorp Inc +AI02906,Research Scientist,56624,USD,56624,EN,FL,South Korea,L,United Kingdom,100,"Hadoop, MLOps, Statistics, PyTorch",Bachelor,1,Government,2024-12-03,2024-12-27,2253,8.6,Cloud AI Solutions +AI02907,Machine Learning Researcher,150671,JPY,16573810,SE,FT,Japan,L,Denmark,50,"Mathematics, Scala, Git, Data Visualization, SQL",Bachelor,6,Gaming,2024-05-03,2024-07-07,2248,6.4,Quantum Computing Inc +AI02908,Deep Learning Engineer,202936,GBP,152202,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, SQL, Tableau, Computer Vision",Associate,15,Transportation,2025-03-01,2025-03-30,1479,8,AI Innovations +AI02909,Machine Learning Engineer,162469,AUD,219333,SE,FL,Australia,L,Australia,50,"Azure, Hadoop, Kubernetes, Python, TensorFlow",Master,9,Finance,2025-04-01,2025-05-26,2079,5.2,Future Systems +AI02910,Robotics Engineer,212416,USD,212416,EX,CT,Norway,L,Norway,50,"Linux, Azure, SQL, Statistics",PhD,15,Gaming,2024-05-19,2024-06-05,1563,6.3,Future Systems +AI02911,Robotics Engineer,109255,CHF,98330,MI,PT,Switzerland,S,Switzerland,50,"Deep Learning, Git, Statistics, PyTorch, Computer Vision",Master,3,Gaming,2024-11-15,2025-01-03,2497,5.6,Neural Networks Co +AI02912,Head of AI,88844,CAD,111055,MI,FT,Canada,S,Canada,0,"Azure, Spark, Tableau, GCP, AWS",PhD,3,Media,2024-01-26,2024-02-26,2105,6.8,DataVision Ltd +AI02913,Data Engineer,113440,USD,113440,SE,PT,South Korea,M,Luxembourg,50,"AWS, Tableau, Kubernetes, Docker",Bachelor,9,Automotive,2024-08-20,2024-09-14,2313,9.9,Autonomous Tech +AI02914,Data Engineer,98544,USD,98544,MI,PT,Sweden,L,Sweden,0,"Statistics, Azure, Git, AWS",Associate,2,Manufacturing,2024-09-21,2024-11-19,1775,6.1,AI Innovations +AI02915,Principal Data Scientist,216605,USD,216605,EX,FL,Israel,M,Israel,0,"Deep Learning, Python, Data Visualization, Hadoop, TensorFlow",Bachelor,17,Government,2024-01-05,2024-03-14,920,5.1,Digital Transformation LLC +AI02916,Data Analyst,43555,USD,43555,MI,FL,China,M,South Korea,50,"TensorFlow, GCP, Azure, Scala",Bachelor,4,Energy,2024-05-08,2024-07-02,1426,6.8,TechCorp Inc +AI02917,AI Product Manager,216702,USD,216702,EX,FL,Ireland,S,Ireland,50,"Git, Kubernetes, NLP, Hadoop",PhD,11,Education,2025-04-06,2025-06-17,1477,7.8,Smart Analytics +AI02918,NLP Engineer,172329,USD,172329,SE,CT,Norway,L,Norway,100,"Hadoop, Kubernetes, Scala, Java, PyTorch",PhD,7,Technology,2024-06-05,2024-07-23,2023,6.9,Autonomous Tech +AI02919,Data Scientist,162643,USD,162643,EX,CT,Ireland,M,Ireland,100,"R, GCP, SQL, Docker",Bachelor,17,Finance,2024-06-22,2024-07-13,809,5.2,Autonomous Tech +AI02920,Computer Vision Engineer,239531,CHF,215578,EX,FT,Switzerland,M,South Africa,0,"SQL, TensorFlow, Git",Associate,10,Media,2024-06-11,2024-08-16,2292,5.8,Autonomous Tech +AI02921,Deep Learning Engineer,169678,USD,169678,SE,PT,Norway,M,Norway,100,"TensorFlow, Python, Azure, Scala, NLP",Bachelor,8,Manufacturing,2024-06-15,2024-07-24,1276,6.1,Neural Networks Co +AI02922,Autonomous Systems Engineer,119875,USD,119875,MI,CT,Denmark,M,Denmark,50,"Computer Vision, SQL, PyTorch, R",Associate,4,Healthcare,2024-11-20,2025-01-05,2145,9.7,Cloud AI Solutions +AI02923,Machine Learning Researcher,136892,JPY,15058120,SE,FT,Japan,L,Japan,100,"TensorFlow, MLOps, R, AWS",Associate,8,Finance,2025-04-03,2025-05-03,953,5.8,Machine Intelligence Group +AI02924,Principal Data Scientist,213789,GBP,160342,EX,PT,United Kingdom,M,United Kingdom,100,"Data Visualization, Python, Tableau, Spark, Hadoop",Bachelor,15,Manufacturing,2024-10-26,2024-12-13,1726,6.5,Smart Analytics +AI02925,AI Product Manager,145769,GBP,109327,SE,PT,United Kingdom,S,United Kingdom,0,"Scala, Kubernetes, Statistics",Associate,7,Government,2025-01-07,2025-02-03,588,6.1,Algorithmic Solutions +AI02926,Principal Data Scientist,178902,USD,178902,EX,PT,Finland,S,Finland,0,"PyTorch, Python, Data Visualization",Associate,18,Media,2024-02-19,2024-04-24,1082,8.3,Cloud AI Solutions +AI02927,Machine Learning Researcher,57877,USD,57877,SE,PT,China,S,China,50,"MLOps, Linux, Docker, Deep Learning, Computer Vision",PhD,8,Gaming,2024-06-27,2024-07-28,2380,8.4,Algorithmic Solutions +AI02928,Autonomous Systems Engineer,74494,CAD,93118,MI,FT,Canada,S,Canada,100,"MLOps, AWS, Python",Bachelor,2,Retail,2024-11-05,2024-12-15,554,5.4,Algorithmic Solutions +AI02929,Data Analyst,23410,USD,23410,EN,CT,China,S,China,0,"Java, Kubernetes, NLP",PhD,0,Finance,2024-07-23,2024-09-07,1946,6.1,Advanced Robotics +AI02930,AI Specialist,144968,JPY,15946480,SE,PT,Japan,S,Japan,50,"Java, Computer Vision, Python, Data Visualization",Master,6,Consulting,2024-10-12,2024-12-24,1986,7.8,Neural Networks Co +AI02931,ML Ops Engineer,283252,CHF,254927,EX,FT,Switzerland,S,Switzerland,100,"TensorFlow, Azure, Deep Learning, Python, Linux",Master,18,Energy,2024-02-29,2024-04-18,2390,5.5,DeepTech Ventures +AI02932,Computer Vision Engineer,70074,GBP,52556,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, Statistics",Associate,0,Automotive,2025-03-03,2025-05-07,2141,9.7,DeepTech Ventures +AI02933,Autonomous Systems Engineer,111820,SGD,145366,SE,FL,Singapore,M,Mexico,100,"Kubernetes, Scala, PyTorch",Associate,5,Manufacturing,2024-11-01,2025-01-08,533,8.3,DeepTech Ventures +AI02934,ML Ops Engineer,190557,USD,190557,EX,CT,Israel,S,Israel,100,"Scala, Statistics, PyTorch, Docker",Master,12,Retail,2024-12-26,2025-01-13,798,6.9,Machine Intelligence Group +AI02935,Data Scientist,111831,USD,111831,SE,FL,Ireland,S,Ireland,50,"GCP, Tableau, Python",Associate,7,Manufacturing,2024-05-04,2024-06-24,533,8.3,Digital Transformation LLC +AI02936,Machine Learning Engineer,19152,USD,19152,EN,FT,India,M,India,100,"Java, Scala, Tableau, Data Visualization",Master,1,Gaming,2024-03-10,2024-05-01,1579,9.7,Smart Analytics +AI02937,Machine Learning Researcher,193150,USD,193150,EX,FL,Ireland,S,Ireland,100,"Python, TensorFlow, Tableau",PhD,12,Finance,2024-01-07,2024-02-22,911,7.8,Autonomous Tech +AI02938,Machine Learning Researcher,56802,USD,56802,EN,CT,South Korea,M,France,0,"Python, Scala, Statistics, Spark, Docker",Bachelor,1,Gaming,2024-11-17,2025-01-20,1044,8,TechCorp Inc +AI02939,Data Engineer,128940,EUR,109599,SE,CT,Germany,L,Germany,50,"SQL, PyTorch, Mathematics, Azure",Associate,5,Retail,2024-01-22,2024-03-12,2032,6.5,DataVision Ltd +AI02940,NLP Engineer,142396,USD,142396,SE,FL,Ireland,L,Philippines,100,"Tableau, Python, R, Docker",Master,6,Automotive,2024-05-14,2024-07-01,1925,8.3,Cloud AI Solutions +AI02941,Robotics Engineer,47879,USD,47879,SE,PT,China,S,China,100,"TensorFlow, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-09-18,1035,9.3,TechCorp Inc +AI02942,Data Analyst,129487,SGD,168333,SE,FL,Singapore,M,Singapore,0,"Linux, PyTorch, Data Visualization, Kubernetes",Associate,7,Telecommunications,2024-07-20,2024-09-01,803,6,Advanced Robotics +AI02943,Head of AI,272031,EUR,231226,EX,FL,France,L,France,0,"PyTorch, TensorFlow, Data Visualization",PhD,12,Healthcare,2024-05-15,2024-07-08,666,9.6,DataVision Ltd +AI02944,Data Analyst,125924,GBP,94443,SE,PT,United Kingdom,L,Australia,0,"Linux, Statistics, Git",Bachelor,6,Technology,2025-02-07,2025-03-09,780,6.9,Advanced Robotics +AI02945,Principal Data Scientist,24104,USD,24104,EN,FT,India,S,India,50,"Python, TensorFlow, Tableau, PyTorch",Associate,0,Media,2025-04-01,2025-05-31,860,5.2,Smart Analytics +AI02946,Principal Data Scientist,69920,EUR,59432,EN,FT,Germany,M,Germany,0,"SQL, Scala, Git, GCP",Bachelor,1,Telecommunications,2024-09-13,2024-10-25,2048,5.8,Neural Networks Co +AI02947,Data Scientist,99241,EUR,84355,SE,FT,Austria,S,Austria,50,"Kubernetes, Git, Mathematics",Bachelor,5,Manufacturing,2024-06-13,2024-08-06,803,9.8,Predictive Systems +AI02948,Principal Data Scientist,80687,CHF,72618,EN,CT,Switzerland,S,Switzerland,50,"AWS, NLP, Python, Mathematics, Scala",PhD,1,Automotive,2024-06-26,2024-07-26,1786,7.7,Algorithmic Solutions +AI02949,Deep Learning Engineer,45985,USD,45985,MI,FT,China,L,China,50,"Deep Learning, Python, Docker",PhD,2,Transportation,2024-04-28,2024-07-05,1598,8.6,TechCorp Inc +AI02950,NLP Engineer,71121,USD,71121,MI,PT,South Korea,M,Mexico,50,"Tableau, Deep Learning, TensorFlow, Python, Java",Associate,4,Technology,2024-08-20,2024-09-06,905,8.6,Algorithmic Solutions +AI02951,Principal Data Scientist,214331,USD,214331,EX,FL,Finland,L,Finland,50,"GCP, Python, TensorFlow, Docker, Statistics",Bachelor,10,Transportation,2024-03-02,2024-03-23,1877,8.9,Algorithmic Solutions +AI02952,NLP Engineer,179501,EUR,152576,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, Git, AWS, R, Java",Bachelor,9,Consulting,2024-04-13,2024-05-12,1341,8.5,DeepTech Ventures +AI02953,AI Specialist,213182,USD,213182,EX,FL,Denmark,L,United Kingdom,0,"Hadoop, R, GCP, Deep Learning",Bachelor,15,Real Estate,2024-10-26,2024-12-30,2424,9.3,Smart Analytics +AI02954,Data Analyst,257116,USD,257116,EX,CT,United States,M,Ghana,50,"NLP, R, SQL",PhD,16,Healthcare,2024-09-18,2024-10-19,2162,6.3,Autonomous Tech +AI02955,Principal Data Scientist,210838,EUR,179212,EX,FT,France,S,France,50,"SQL, Azure, Git",Associate,13,Government,2024-07-18,2024-09-26,723,8.1,DeepTech Ventures +AI02956,ML Ops Engineer,161032,USD,161032,SE,PT,Norway,S,Norway,0,"SQL, R, Java, AWS",Associate,5,Telecommunications,2024-01-14,2024-02-08,1827,7.6,Autonomous Tech +AI02957,Data Engineer,97860,EUR,83181,MI,FL,Austria,L,Chile,50,"PyTorch, Computer Vision, R",Bachelor,4,Healthcare,2024-09-19,2024-10-07,2445,6.1,Algorithmic Solutions +AI02958,Machine Learning Researcher,76742,GBP,57557,EN,FT,United Kingdom,S,United Kingdom,0,"GCP, Python, TensorFlow, NLP, Computer Vision",PhD,1,Energy,2024-10-26,2024-12-03,2112,5.1,Autonomous Tech +AI02959,AI Architect,124869,USD,124869,EX,CT,Sweden,S,Czech Republic,0,"Mathematics, Hadoop, GCP, Azure",Bachelor,19,Telecommunications,2024-04-11,2024-05-18,718,7.8,Smart Analytics +AI02960,Data Analyst,158246,USD,158246,SE,FT,Norway,L,South Korea,50,"Tableau, Spark, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-08-28,2024-09-28,939,9.5,TechCorp Inc +AI02961,Data Engineer,277909,USD,277909,EX,CT,Sweden,L,Sweden,0,"Python, Hadoop, Scala, TensorFlow",Master,16,Technology,2025-04-06,2025-06-06,1601,6.7,Neural Networks Co +AI02962,Principal Data Scientist,58343,EUR,49592,EN,FT,Germany,S,Germany,50,"SQL, Spark, Data Visualization",Bachelor,0,Education,2024-10-23,2024-12-01,535,6.5,Neural Networks Co +AI02963,AI Product Manager,98072,USD,98072,MI,PT,Sweden,L,Sweden,0,"TensorFlow, R, Statistics",Associate,4,Energy,2024-03-26,2024-05-19,710,7.8,Predictive Systems +AI02964,ML Ops Engineer,58209,USD,58209,SE,CT,India,L,India,50,"Kubernetes, Python, Spark",Bachelor,6,Government,2024-03-10,2024-05-15,621,7.8,Advanced Robotics +AI02965,Principal Data Scientist,101880,EUR,86598,SE,PT,Germany,S,Czech Republic,50,"Spark, Azure, Docker",PhD,7,Retail,2025-02-04,2025-04-03,1759,8.1,Cloud AI Solutions +AI02966,AI Architect,119812,USD,119812,MI,FL,United States,M,Italy,0,"Deep Learning, Git, Data Visualization, Statistics",Bachelor,4,Manufacturing,2024-02-02,2024-02-17,1503,7.7,TechCorp Inc +AI02967,Research Scientist,184524,USD,184524,EX,FL,Finland,S,Finland,100,"SQL, PyTorch, Deep Learning",Bachelor,12,Manufacturing,2024-10-15,2024-10-30,619,9.1,Smart Analytics +AI02968,AI Architect,212494,EUR,180620,EX,CT,Austria,M,Austria,50,"Spark, Mathematics, Java",Bachelor,19,Automotive,2024-01-03,2024-02-15,1929,6,Digital Transformation LLC +AI02969,NLP Engineer,83942,EUR,71351,MI,CT,Netherlands,S,Israel,0,"Linux, SQL, AWS",Bachelor,3,Finance,2025-04-05,2025-05-10,678,9.8,Machine Intelligence Group +AI02970,ML Ops Engineer,92507,GBP,69380,MI,PT,United Kingdom,L,Canada,100,"Git, Data Visualization, AWS, SQL",Master,3,Government,2025-04-01,2025-06-06,2111,7.5,Future Systems +AI02971,Machine Learning Researcher,71494,EUR,60770,MI,PT,France,M,South Africa,50,"R, Kubernetes, AWS, Python, Computer Vision",PhD,4,Education,2025-04-19,2025-05-31,738,8.3,Smart Analytics +AI02972,AI Product Manager,89952,AUD,121435,MI,FT,Australia,S,Australia,50,"Linux, Spark, Deep Learning",Master,2,Government,2024-07-18,2024-08-06,2280,8.2,Digital Transformation LLC +AI02973,AI Product Manager,74909,USD,74909,EX,CT,India,L,Argentina,100,"Statistics, Kubernetes, Git, GCP, Python",Master,17,Media,2024-02-28,2024-03-14,618,9.2,Algorithmic Solutions +AI02974,Data Scientist,121133,AUD,163530,SE,PT,Australia,M,Australia,100,"Python, Kubernetes, MLOps, Azure",Master,6,Manufacturing,2025-01-01,2025-03-13,1194,8.2,Autonomous Tech +AI02975,Head of AI,106190,SGD,138047,MI,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, Tableau",Bachelor,3,Finance,2024-03-05,2024-05-17,1987,7.2,AI Innovations +AI02976,AI Software Engineer,261845,EUR,222568,EX,FL,Netherlands,M,Netherlands,50,"Python, GCP, Hadoop",PhD,19,Automotive,2024-06-14,2024-08-05,1868,5.7,Quantum Computing Inc +AI02977,Robotics Engineer,104354,EUR,88701,MI,CT,Austria,L,Switzerland,100,"Java, Linux, TensorFlow, Hadoop",Associate,4,Transportation,2025-04-06,2025-04-23,611,9,TechCorp Inc +AI02978,AI Architect,86549,USD,86549,EN,FT,Sweden,L,Sweden,100,"Azure, PyTorch, Data Visualization, Kubernetes",Associate,1,Education,2025-01-27,2025-03-07,1075,6.2,DataVision Ltd +AI02979,ML Ops Engineer,170055,USD,170055,SE,FT,Sweden,L,Netherlands,100,"AWS, Linux, Scala, MLOps, Mathematics",Associate,6,Energy,2024-02-12,2024-03-31,2029,5.2,Machine Intelligence Group +AI02980,Computer Vision Engineer,92633,USD,92633,SE,FT,Israel,S,Israel,0,"Spark, Docker, Data Visualization, PyTorch",PhD,9,Real Estate,2024-05-08,2024-06-16,1790,7,DataVision Ltd +AI02981,Deep Learning Engineer,108025,EUR,91821,SE,FL,France,S,Vietnam,100,"Docker, Java, Linux, Statistics, Computer Vision",Bachelor,5,Manufacturing,2024-08-27,2024-10-11,856,8,Algorithmic Solutions +AI02982,NLP Engineer,231357,EUR,196653,EX,FT,France,L,France,100,"TensorFlow, Data Visualization, SQL, Scala",Master,10,Real Estate,2025-02-05,2025-03-18,771,7.4,Autonomous Tech +AI02983,AI Consultant,75714,AUD,102214,MI,PT,Australia,M,Australia,0,"Git, SQL, Computer Vision, Hadoop, Java",Associate,3,Real Estate,2025-04-25,2025-05-18,895,7.1,Neural Networks Co +AI02984,Machine Learning Researcher,48731,EUR,41421,EN,CT,Austria,S,Austria,100,"R, Hadoop, Docker, Computer Vision, Python",PhD,0,Real Estate,2024-10-05,2024-12-15,1480,9.2,Future Systems +AI02985,AI Architect,63620,EUR,54077,EN,FL,Austria,L,Austria,100,"Linux, Spark, NLP, Kubernetes",Master,1,Energy,2024-05-01,2024-06-14,1567,7.5,DataVision Ltd +AI02986,Deep Learning Engineer,146711,USD,146711,SE,FL,United States,S,United States,50,"R, NLP, Kubernetes",Bachelor,8,Retail,2024-04-09,2024-06-02,1302,6.2,Cloud AI Solutions +AI02987,Autonomous Systems Engineer,217093,USD,217093,EX,PT,Finland,M,Finland,0,"Scala, PyTorch, GCP",Associate,15,Government,2024-01-01,2024-03-13,1010,9.5,Predictive Systems +AI02988,Computer Vision Engineer,158838,EUR,135012,SE,FL,Netherlands,L,South Africa,100,"Hadoop, Python, R",Master,7,Media,2024-11-21,2025-01-20,814,6.7,Cloud AI Solutions +AI02989,Machine Learning Engineer,26471,USD,26471,MI,CT,India,S,India,50,"Tableau, Git, Python, Computer Vision",Master,3,Healthcare,2025-04-15,2025-05-24,2355,8.1,Machine Intelligence Group +AI02990,Principal Data Scientist,52315,EUR,44468,EN,FT,Germany,M,Germany,100,"AWS, Python, Tableau",Master,0,Technology,2024-01-02,2024-02-21,1188,9.6,Quantum Computing Inc +AI02991,Research Scientist,155395,USD,155395,SE,PT,Finland,L,Finland,100,"Git, NLP, Scala",Bachelor,7,Consulting,2024-07-05,2024-08-06,1078,6.3,Smart Analytics +AI02992,Deep Learning Engineer,103774,USD,103774,SE,CT,Sweden,M,Sweden,100,"Python, Java, TensorFlow",PhD,5,Manufacturing,2024-02-14,2024-03-18,738,8.7,Machine Intelligence Group +AI02993,AI Specialist,116286,USD,116286,SE,CT,Finland,M,Czech Republic,0,"AWS, Java, Statistics, Mathematics",Associate,7,Media,2025-04-27,2025-06-01,1491,6.7,Cognitive Computing +AI02994,ML Ops Engineer,75877,USD,75877,EN,CT,United States,S,United States,50,"NLP, Python, SQL, Git",Master,0,Healthcare,2025-01-11,2025-02-22,751,9.7,Future Systems +AI02995,Data Analyst,73643,AUD,99418,MI,FT,Australia,S,Indonesia,0,"Azure, Spark, MLOps",Bachelor,2,Consulting,2024-07-04,2024-07-27,1225,9.9,Advanced Robotics +AI02996,AI Specialist,252203,CHF,226983,EX,FL,Switzerland,L,Switzerland,50,"Hadoop, PyTorch, Java, Computer Vision, Mathematics",Bachelor,13,Automotive,2025-04-18,2025-06-12,1635,7.6,Predictive Systems +AI02997,AI Specialist,82912,USD,82912,MI,FT,Israel,M,Indonesia,0,"R, Tableau, Linux",Bachelor,4,Energy,2024-08-03,2024-08-25,2064,7.6,Advanced Robotics +AI02998,AI Specialist,152624,USD,152624,SE,FL,Ireland,L,Ireland,100,"R, Python, Git, GCP, Linux",Master,9,Retail,2024-11-28,2025-01-15,1068,5.4,Future Systems +AI02999,AI Architect,87630,USD,87630,MI,FT,South Korea,L,South Korea,100,"AWS, Linux, Deep Learning, R",Associate,2,Manufacturing,2024-05-01,2024-06-16,945,8.8,Cognitive Computing +AI03000,AI Research Scientist,234953,SGD,305439,EX,FL,Singapore,S,Singapore,50,"Linux, R, TensorFlow, Git, Tableau",PhD,12,Consulting,2024-04-14,2024-05-18,930,9,AI Innovations +AI03001,AI Research Scientist,121264,SGD,157643,SE,FL,Singapore,S,Singapore,0,"Spark, Kubernetes, GCP, TensorFlow",Master,7,Government,2024-01-14,2024-03-21,1534,9.8,Digital Transformation LLC +AI03002,Machine Learning Researcher,158964,USD,158964,MI,PT,Denmark,L,Denmark,0,"Scala, SQL, Java, Docker, PyTorch",Master,4,Education,2024-06-25,2024-07-10,638,7.6,Cloud AI Solutions +AI03003,Computer Vision Engineer,73586,JPY,8094460,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, Docker, Data Visualization",Bachelor,1,Retail,2024-11-26,2025-01-15,1557,7,DeepTech Ventures +AI03004,Machine Learning Engineer,230512,GBP,172884,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Kubernetes, Python",Master,13,Telecommunications,2024-05-26,2024-06-24,827,7,Advanced Robotics +AI03005,Autonomous Systems Engineer,125009,CAD,156261,SE,CT,Canada,S,Czech Republic,50,"Kubernetes, Computer Vision, SQL",PhD,7,Telecommunications,2025-01-28,2025-03-31,1710,5.3,Advanced Robotics +AI03006,AI Architect,262701,USD,262701,EX,PT,Sweden,L,Belgium,50,"Python, AWS, TensorFlow",Bachelor,19,Gaming,2024-12-02,2025-01-07,1868,9.6,Autonomous Tech +AI03007,ML Ops Engineer,266606,USD,266606,EX,CT,Denmark,S,Denmark,50,"Hadoop, Python, Tableau, Deep Learning",PhD,18,Automotive,2025-02-02,2025-03-30,1674,8.3,Smart Analytics +AI03008,NLP Engineer,140178,SGD,182231,SE,FT,Singapore,S,Singapore,100,"Tableau, Deep Learning, Hadoop, MLOps",Bachelor,5,Retail,2025-04-15,2025-06-20,2368,5.3,Future Systems +AI03009,NLP Engineer,187857,CAD,234821,EX,FL,Canada,L,Canada,0,"Deep Learning, Spark, Data Visualization, SQL, Kubernetes",Bachelor,18,Consulting,2024-07-21,2024-09-28,1818,5.9,Cognitive Computing +AI03010,Data Analyst,42710,USD,42710,MI,FT,China,M,Spain,100,"Java, R, Hadoop, Linux",PhD,2,Finance,2024-11-30,2025-01-16,691,9.8,Digital Transformation LLC +AI03011,Data Scientist,84841,EUR,72115,MI,PT,Netherlands,M,Netherlands,50,"Java, R, Tableau, SQL, Scala",Bachelor,4,Transportation,2024-03-02,2024-04-23,2405,7.6,Advanced Robotics +AI03012,AI Consultant,74980,EUR,63733,MI,CT,Austria,S,Austria,0,"SQL, PyTorch, R, Hadoop, Python",Bachelor,3,Telecommunications,2024-06-25,2024-08-19,1005,8.3,TechCorp Inc +AI03013,AI Consultant,84006,EUR,71405,MI,CT,France,M,Brazil,0,"Deep Learning, SQL, Mathematics",Master,3,Real Estate,2024-06-20,2024-08-04,1656,6.9,Digital Transformation LLC +AI03014,AI Consultant,174420,EUR,148257,EX,CT,France,S,Romania,100,"Kubernetes, Scala, Java, Spark",PhD,19,Education,2024-01-16,2024-03-23,1377,9.3,Future Systems +AI03015,Computer Vision Engineer,243382,USD,243382,EX,PT,Sweden,M,Sweden,50,"Linux, Kubernetes, Git, Docker, Python",Associate,19,Gaming,2024-04-22,2024-06-10,1260,8.7,Advanced Robotics +AI03016,AI Consultant,72001,EUR,61201,MI,PT,Austria,S,Austria,0,"Java, Hadoop, Scala, GCP",PhD,4,Government,2024-04-01,2024-05-16,698,9.4,Cloud AI Solutions +AI03017,AI Architect,349094,USD,349094,EX,PT,Denmark,L,Denmark,100,"PyTorch, Scala, NLP, Computer Vision",Bachelor,13,Healthcare,2024-03-04,2024-05-09,2490,8.9,Cloud AI Solutions +AI03018,Machine Learning Engineer,135760,USD,135760,SE,FT,Norway,S,Norway,50,"Azure, Linux, Docker, SQL",Bachelor,5,Consulting,2024-08-28,2024-09-30,1383,7.4,Quantum Computing Inc +AI03019,AI Research Scientist,127359,EUR,108255,SE,CT,France,L,France,50,"Computer Vision, Java, SQL",Master,9,Telecommunications,2024-06-19,2024-08-08,1050,5.7,Smart Analytics +AI03020,Data Engineer,97760,SGD,127088,SE,PT,Singapore,S,Ireland,0,"TensorFlow, GCP, Tableau, Computer Vision",PhD,6,Technology,2024-03-09,2024-04-17,2013,6.9,Machine Intelligence Group +AI03021,AI Software Engineer,217718,JPY,23948980,EX,FT,Japan,M,Japan,100,"MLOps, R, Computer Vision, Scala",Associate,13,Telecommunications,2024-08-08,2024-10-13,1785,9.8,Smart Analytics +AI03022,Deep Learning Engineer,129149,CAD,161436,SE,CT,Canada,S,Canada,100,"R, Kubernetes, Mathematics",Associate,5,Gaming,2025-04-18,2025-06-30,650,6.7,AI Innovations +AI03023,Data Analyst,66925,USD,66925,EN,PT,Ireland,S,Ireland,50,"SQL, Java, PyTorch, Git, Spark",Master,1,Technology,2024-05-26,2024-06-10,783,5.4,Digital Transformation LLC +AI03024,Data Engineer,87198,EUR,74118,MI,PT,Germany,S,Germany,50,"Git, R, Kubernetes, Spark",Bachelor,2,Gaming,2024-12-18,2025-01-25,1440,9.8,Autonomous Tech +AI03025,AI Software Engineer,94601,USD,94601,EN,PT,United States,L,United States,0,"AWS, Java, Deep Learning, Python, TensorFlow",PhD,0,Telecommunications,2025-01-20,2025-03-30,874,9.3,Neural Networks Co +AI03026,Principal Data Scientist,51043,USD,51043,EN,PT,South Korea,M,South Korea,100,"Data Visualization, AWS, TensorFlow, SQL, NLP",Associate,0,Gaming,2024-07-21,2024-08-30,1749,5.9,Smart Analytics +AI03027,Autonomous Systems Engineer,88860,EUR,75531,MI,CT,France,L,France,50,"Hadoop, Computer Vision, Mathematics, MLOps",Bachelor,3,Retail,2024-09-27,2024-12-08,1581,10,Machine Intelligence Group +AI03028,AI Specialist,91219,USD,91219,MI,FT,Sweden,S,Sweden,50,"GCP, Java, SQL, Deep Learning",PhD,4,Transportation,2025-04-16,2025-06-01,1553,5.8,Autonomous Tech +AI03029,AI Product Manager,23010,USD,23010,MI,FL,India,S,India,100,"Python, Computer Vision, Java",Master,4,Gaming,2024-08-24,2024-11-02,1484,7.7,Predictive Systems +AI03030,Autonomous Systems Engineer,84775,USD,84775,MI,PT,Finland,L,Finland,100,"PyTorch, SQL, Computer Vision",PhD,4,Consulting,2024-11-23,2024-12-08,1320,5.7,Neural Networks Co +AI03031,Machine Learning Researcher,182231,USD,182231,EX,FT,Norway,M,Norway,100,"Tableau, Computer Vision, NLP, Python, MLOps",PhD,11,Government,2024-02-16,2024-03-29,2292,8.2,Autonomous Tech +AI03032,Data Engineer,76682,USD,76682,EX,FT,India,M,India,0,"PyTorch, AWS, Data Visualization, Deep Learning",PhD,12,Finance,2025-04-25,2025-06-15,552,8.7,Neural Networks Co +AI03033,NLP Engineer,103728,EUR,88169,SE,CT,Austria,S,Austria,100,"R, Spark, TensorFlow",Master,8,Gaming,2024-05-01,2024-06-01,700,9.8,Digital Transformation LLC +AI03034,Machine Learning Engineer,108739,CHF,97865,EN,FT,Switzerland,L,Switzerland,0,"Scala, Linux, Computer Vision, Java",Associate,0,Telecommunications,2024-04-23,2024-06-11,829,6.3,Neural Networks Co +AI03035,AI Architect,127790,USD,127790,SE,PT,Israel,L,Israel,50,"GCP, R, Tableau",Master,8,Finance,2024-06-07,2024-07-18,880,6.2,Cloud AI Solutions +AI03036,Deep Learning Engineer,113774,USD,113774,MI,CT,United States,L,Belgium,50,"Data Visualization, R, Java, Tableau",Associate,3,Automotive,2024-04-28,2024-05-27,529,9.4,Algorithmic Solutions +AI03037,Research Scientist,119989,USD,119989,EN,FL,Denmark,L,Denmark,100,"Data Visualization, Linux, Tableau",Associate,1,Telecommunications,2024-07-15,2024-08-25,1170,6.1,Advanced Robotics +AI03038,Machine Learning Engineer,75024,USD,75024,MI,PT,Israel,S,Netherlands,100,"Tableau, Azure, AWS, SQL",Associate,4,Government,2025-04-13,2025-05-22,1521,9.3,Advanced Robotics +AI03039,Research Scientist,67687,USD,67687,EN,CT,Ireland,M,Indonesia,0,"R, Deep Learning, SQL, Data Visualization, Kubernetes",PhD,1,Media,2024-08-12,2024-10-08,508,5.4,AI Innovations +AI03040,Data Scientist,82087,USD,82087,MI,FL,United States,S,United States,100,"MLOps, Hadoop, Java, Spark, Tableau",PhD,4,Media,2024-10-11,2024-11-07,1535,6.8,AI Innovations +AI03041,Computer Vision Engineer,240800,USD,240800,EX,FL,Sweden,M,Sweden,50,"Kubernetes, Deep Learning, SQL, PyTorch",Bachelor,15,Consulting,2024-08-27,2024-09-11,2073,8,TechCorp Inc +AI03042,Principal Data Scientist,76214,EUR,64782,MI,PT,Germany,S,Germany,0,"Python, R, SQL, Kubernetes, Mathematics",PhD,3,Media,2025-02-26,2025-04-14,1646,6.7,Autonomous Tech +AI03043,AI Consultant,259438,CHF,233494,EX,PT,Switzerland,L,Switzerland,0,"Git, Scala, Hadoop, SQL",Bachelor,13,Energy,2024-01-19,2024-02-03,2304,5.3,Predictive Systems +AI03044,Data Engineer,245492,USD,245492,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Deep Learning, Mathematics, AWS",Master,17,Manufacturing,2024-07-24,2024-09-30,2187,8.1,Autonomous Tech +AI03045,ML Ops Engineer,102823,CAD,128529,MI,FL,Canada,M,Canada,100,"Linux, R, TensorFlow, Deep Learning, Data Visualization",Master,3,Manufacturing,2025-04-04,2025-04-24,1976,9.7,Digital Transformation LLC +AI03046,Deep Learning Engineer,283410,USD,283410,EX,FT,Ireland,L,Ireland,50,"Docker, Statistics, Deep Learning, R, SQL",Bachelor,18,Telecommunications,2024-01-27,2024-03-15,1313,7.1,Machine Intelligence Group +AI03047,Machine Learning Engineer,208241,USD,208241,EX,FT,Ireland,M,Kenya,50,"Kubernetes, Azure, Data Visualization",Bachelor,18,Automotive,2024-08-18,2024-10-22,2371,8.9,TechCorp Inc +AI03048,ML Ops Engineer,105274,GBP,78956,MI,PT,United Kingdom,S,Brazil,100,"Java, Git, R, Linux, SQL",PhD,3,Government,2025-01-08,2025-02-16,936,7.4,Neural Networks Co +AI03049,Principal Data Scientist,94841,USD,94841,MI,FL,Israel,L,Israel,0,"SQL, Java, Linux, NLP, Tableau",Bachelor,3,Media,2024-09-17,2024-11-12,651,6.1,Future Systems +AI03050,Autonomous Systems Engineer,114463,EUR,97294,MI,FT,Austria,L,Austria,50,"Python, Hadoop, SQL, Docker",Master,2,Consulting,2024-07-28,2024-09-23,2088,6.8,AI Innovations +AI03051,Data Engineer,158187,USD,158187,SE,PT,Denmark,S,Denmark,100,"SQL, R, Data Visualization, Docker",Bachelor,5,Telecommunications,2024-03-20,2024-05-21,835,6,Future Systems +AI03052,Principal Data Scientist,45177,USD,45177,EN,PT,South Korea,S,South Korea,50,"R, Linux, Python, Tableau, Mathematics",PhD,1,Education,2024-01-23,2024-02-06,1425,5.5,Smart Analytics +AI03053,Head of AI,147403,EUR,125293,SE,PT,Germany,L,Germany,50,"Kubernetes, Hadoop, NLP, Statistics, Python",Associate,8,Automotive,2024-04-26,2024-05-31,1232,8.4,Predictive Systems +AI03054,Deep Learning Engineer,103578,USD,103578,SE,FL,Ireland,S,Ireland,50,"TensorFlow, Linux, PyTorch, Tableau",PhD,5,Transportation,2024-10-16,2024-12-06,2330,8.9,Quantum Computing Inc +AI03055,Deep Learning Engineer,90139,AUD,121688,MI,FL,Australia,L,Australia,100,"R, Mathematics, Data Visualization, Linux, Kubernetes",Master,4,Telecommunications,2025-01-10,2025-02-08,1856,7.4,DataVision Ltd +AI03056,AI Product Manager,140051,EUR,119043,SE,FT,France,L,France,100,"Scala, Git, Statistics, Computer Vision, Python",Master,5,Automotive,2024-01-13,2024-03-02,1252,7.4,Quantum Computing Inc +AI03057,Head of AI,55899,USD,55899,EN,FT,Israel,M,Israel,50,"Tableau, Azure, Hadoop",Bachelor,0,Education,2024-06-01,2024-07-03,1765,8.2,Future Systems +AI03058,Machine Learning Engineer,228939,EUR,194598,EX,CT,Germany,M,Mexico,50,"NLP, AWS, Git, GCP, Mathematics",PhD,14,Transportation,2024-09-10,2024-10-20,2130,8.5,Neural Networks Co +AI03059,Computer Vision Engineer,169575,CHF,152618,SE,PT,Switzerland,S,Switzerland,50,"Tableau, Git, Computer Vision, Python, Statistics",Associate,8,Energy,2025-04-09,2025-06-16,1773,5.1,Autonomous Tech +AI03060,AI Specialist,92434,GBP,69326,EN,CT,United Kingdom,L,Vietnam,0,"Data Visualization, Spark, Computer Vision, SQL, PyTorch",Bachelor,0,Gaming,2024-10-27,2024-12-11,1856,7.4,TechCorp Inc +AI03061,NLP Engineer,45214,CAD,56518,EN,CT,Canada,S,Canada,100,"GCP, Computer Vision, Python, R, TensorFlow",PhD,1,Finance,2024-01-25,2024-03-23,2385,7.6,DeepTech Ventures +AI03062,Principal Data Scientist,125545,AUD,169486,MI,FT,Australia,L,Thailand,50,"Python, Git, TensorFlow, NLP",Associate,4,Technology,2024-09-14,2024-10-20,868,8.1,Future Systems +AI03063,AI Research Scientist,63222,USD,63222,EX,FT,India,M,India,100,"MLOps, TensorFlow, Tableau, Linux",PhD,15,Government,2024-03-21,2024-05-29,1313,5.4,Neural Networks Co +AI03064,Deep Learning Engineer,90458,USD,90458,MI,PT,Finland,L,Finland,0,"SQL, Python, NLP, Statistics",Master,2,Transportation,2024-10-26,2024-12-04,834,9.1,DataVision Ltd +AI03065,Data Analyst,53532,USD,53532,EN,PT,Sweden,S,Brazil,0,"Kubernetes, Statistics, Tableau, Mathematics, Java",Bachelor,1,Energy,2025-03-04,2025-04-17,1479,8.4,Algorithmic Solutions +AI03066,Computer Vision Engineer,111068,USD,111068,MI,FL,Norway,M,United States,100,"Data Visualization, Python, TensorFlow, Docker",Master,4,Telecommunications,2025-03-23,2025-04-24,618,8.8,Future Systems +AI03067,AI Research Scientist,51281,CAD,64101,EN,FT,Canada,M,Ireland,50,"SQL, Kubernetes, Scala, Mathematics",Master,0,Government,2025-01-25,2025-02-20,1572,6.7,Neural Networks Co +AI03068,Robotics Engineer,70333,USD,70333,EX,CT,India,S,India,100,"Tableau, Data Visualization, SQL, PyTorch",Bachelor,12,Finance,2024-05-13,2024-06-24,1694,7.8,Neural Networks Co +AI03069,Data Scientist,113289,USD,113289,MI,PT,Norway,M,Italy,50,"Python, Java, Hadoop, AWS, Kubernetes",Bachelor,4,Gaming,2024-09-17,2024-11-26,1355,7.9,Algorithmic Solutions +AI03070,Deep Learning Engineer,76340,USD,76340,EN,FT,Israel,L,Israel,100,"AWS, SQL, Python",Master,0,Retail,2024-07-29,2024-09-19,1293,8,Predictive Systems +AI03071,Deep Learning Engineer,83602,USD,83602,MI,CT,Finland,M,Finland,100,"Data Visualization, R, NLP, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-15,884,5.7,Quantum Computing Inc +AI03072,Machine Learning Researcher,140958,AUD,190293,EX,CT,Australia,M,Thailand,0,"Docker, Hadoop, Mathematics, Kubernetes",Master,15,Consulting,2024-05-31,2024-07-29,1825,7.2,DeepTech Ventures +AI03073,Machine Learning Engineer,224243,USD,224243,EX,FL,United States,L,United States,50,"Java, R, SQL, Data Visualization, Linux",PhD,17,Media,2024-06-25,2024-08-19,1126,7.2,Predictive Systems +AI03074,AI Product Manager,182443,USD,182443,EX,PT,Sweden,L,Sweden,50,"Computer Vision, Python, Tableau, Data Visualization",Bachelor,15,Technology,2024-10-26,2024-12-02,2303,6.3,Autonomous Tech +AI03075,Principal Data Scientist,116360,AUD,157086,SE,CT,Australia,S,Australia,0,"Mathematics, Kubernetes, Data Visualization, GCP, PyTorch",Master,9,Technology,2024-02-03,2024-03-03,1533,6.7,DeepTech Ventures +AI03076,Machine Learning Engineer,59186,SGD,76942,EN,CT,Singapore,S,Singapore,0,"Java, R, Computer Vision, Tableau, Statistics",Master,1,Government,2025-04-16,2025-06-27,1282,6.6,Digital Transformation LLC +AI03077,AI Product Manager,230221,CAD,287776,EX,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Python",Master,11,Manufacturing,2024-02-06,2024-04-07,883,7.7,Cognitive Computing +AI03078,AI Specialist,249223,EUR,211840,EX,FL,Germany,L,Chile,50,"Scala, TensorFlow, SQL, Kubernetes",Master,14,Retail,2025-04-13,2025-05-23,1427,6.4,Cognitive Computing +AI03079,Principal Data Scientist,170776,USD,170776,SE,CT,United States,M,United States,0,"Java, Data Visualization, R, Scala",Master,5,Gaming,2025-01-16,2025-02-03,1122,8.8,DeepTech Ventures +AI03080,Computer Vision Engineer,76117,EUR,64699,EN,FL,Germany,M,Estonia,0,"R, Git, Hadoop",Master,1,Consulting,2024-01-03,2024-02-07,1271,9.4,Algorithmic Solutions +AI03081,AI Research Scientist,65226,AUD,88055,EN,FT,Australia,L,Australia,0,"Kubernetes, PyTorch, Azure, SQL",PhD,0,Finance,2024-10-26,2024-11-28,684,5.5,Machine Intelligence Group +AI03082,Computer Vision Engineer,63087,EUR,53624,EN,PT,Austria,M,Austria,0,"Git, Azure, Statistics, GCP",Associate,1,Telecommunications,2024-12-19,2025-01-26,2458,8.8,Cloud AI Solutions +AI03083,Machine Learning Engineer,44772,USD,44772,MI,FL,China,M,China,50,"R, Java, Data Visualization",Master,4,Transportation,2024-01-01,2024-01-24,1106,9.3,Algorithmic Solutions +AI03084,Data Scientist,204283,AUD,275782,EX,FT,Australia,S,Brazil,100,"Python, Scala, Kubernetes, Docker",Associate,12,Retail,2024-04-21,2024-06-19,1045,8.5,Advanced Robotics +AI03085,Machine Learning Engineer,114299,USD,114299,SE,PT,Ireland,M,Portugal,100,"GCP, Java, MLOps",Bachelor,8,Transportation,2024-10-26,2024-11-22,1175,6.8,Future Systems +AI03086,AI Consultant,298889,USD,298889,EX,FT,Norway,L,Norway,50,"GCP, Statistics, Git, Hadoop",Associate,16,Consulting,2024-02-29,2024-04-06,1175,6.8,Cloud AI Solutions +AI03087,AI Specialist,71400,JPY,7854000,EN,FT,Japan,S,Japan,50,"Azure, Docker, MLOps",Bachelor,0,Manufacturing,2024-02-13,2024-03-13,2014,8.1,TechCorp Inc +AI03088,Research Scientist,69118,USD,69118,EN,FL,United States,S,United States,100,"Spark, TensorFlow, Git, Docker, Java",Associate,0,Telecommunications,2024-12-12,2025-02-16,739,6,DeepTech Ventures +AI03089,Robotics Engineer,47701,USD,47701,MI,PT,China,M,China,0,"Git, Linux, Mathematics, Kubernetes, Spark",Master,3,Education,2024-08-02,2024-08-17,2068,9.5,Advanced Robotics +AI03090,Data Scientist,162815,USD,162815,SE,FL,Norway,L,Norway,50,"Mathematics, Docker, Statistics",Bachelor,9,Gaming,2024-12-13,2025-01-30,1879,7.3,Predictive Systems +AI03091,Deep Learning Engineer,136275,CHF,122648,MI,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Spark",Associate,3,Automotive,2024-07-11,2024-09-07,506,7.9,Future Systems +AI03092,AI Specialist,77774,CAD,97218,MI,PT,Canada,S,Canada,0,"AWS, Deep Learning, Docker",PhD,2,Retail,2025-04-16,2025-06-09,675,6.2,Neural Networks Co +AI03093,Computer Vision Engineer,151655,JPY,16682050,EX,FT,Japan,S,Japan,0,"Scala, SQL, MLOps, Azure, Kubernetes",Bachelor,17,Energy,2025-02-04,2025-02-27,1886,9.8,DataVision Ltd +AI03094,AI Specialist,147631,USD,147631,SE,FT,Finland,L,Finland,50,"Scala, Deep Learning, Java, Azure, PyTorch",PhD,5,Automotive,2024-03-18,2024-04-10,834,7.5,Digital Transformation LLC +AI03095,Robotics Engineer,44181,USD,44181,EX,CT,India,S,India,100,"GCP, Kubernetes, PyTorch",PhD,15,Transportation,2024-03-28,2024-05-15,2429,8.4,Predictive Systems +AI03096,AI Specialist,92006,EUR,78205,MI,FL,Germany,M,Germany,100,"Spark, Linux, NLP, SQL, Python",PhD,2,Real Estate,2024-10-06,2024-11-10,1434,6,DeepTech Ventures +AI03097,Data Analyst,104944,EUR,89202,MI,CT,Germany,L,Germany,0,"Python, Deep Learning, Data Visualization, R",Master,3,Education,2024-03-10,2024-04-04,1885,6.2,Predictive Systems +AI03098,ML Ops Engineer,261580,USD,261580,EX,CT,United States,M,United States,50,"Linux, Docker, Data Visualization, GCP, SQL",Bachelor,10,Transportation,2024-11-29,2024-12-31,1601,5.1,Neural Networks Co +AI03099,AI Software Engineer,32682,USD,32682,MI,FT,India,L,India,0,"GCP, Kubernetes, Azure",Master,4,Real Estate,2024-06-08,2024-07-17,1624,8.3,Algorithmic Solutions +AI03100,Research Scientist,46243,USD,46243,EN,FT,Sweden,S,Sweden,0,"Hadoop, TensorFlow, Git",Bachelor,1,Real Estate,2025-02-09,2025-04-13,1897,8.6,Quantum Computing Inc +AI03101,AI Software Engineer,51801,CAD,64751,EN,CT,Canada,S,Canada,0,"R, SQL, Linux, Kubernetes, Hadoop",PhD,1,Government,2024-03-16,2024-04-13,1014,8.8,Smart Analytics +AI03102,AI Software Engineer,110654,SGD,143850,MI,PT,Singapore,M,Singapore,0,"Hadoop, Mathematics, Kubernetes, PyTorch",Associate,4,Technology,2024-07-31,2024-09-04,1544,7.4,Cognitive Computing +AI03103,Data Scientist,123362,USD,123362,SE,CT,Israel,S,Israel,0,"Linux, AWS, MLOps, Scala, Python",PhD,8,Energy,2024-03-23,2024-05-08,1021,6.9,Future Systems +AI03104,Principal Data Scientist,66961,USD,66961,MI,FT,South Korea,M,South Korea,100,"Hadoop, Computer Vision, Java, Linux, R",PhD,3,Retail,2024-11-23,2025-01-04,960,7.7,Machine Intelligence Group +AI03105,Autonomous Systems Engineer,96935,USD,96935,MI,FL,Denmark,S,South Korea,50,"AWS, Data Visualization, MLOps",PhD,2,Education,2024-04-02,2024-05-17,597,9.4,DeepTech Ventures +AI03106,NLP Engineer,165702,JPY,18227220,EX,PT,Japan,L,Japan,50,"SQL, R, Linux, PyTorch",Master,12,Retail,2024-08-13,2024-09-01,1511,5.4,Autonomous Tech +AI03107,Computer Vision Engineer,102570,CHF,92313,MI,PT,Switzerland,M,Switzerland,0,"R, SQL, Data Visualization, Computer Vision, Java",Master,4,Healthcare,2024-11-15,2024-12-27,2061,7,Cognitive Computing +AI03108,Principal Data Scientist,31054,USD,31054,MI,CT,India,S,India,50,"Azure, Scala, Java, Mathematics",PhD,4,Government,2025-04-06,2025-05-05,716,5.4,Cognitive Computing +AI03109,AI Software Engineer,26978,USD,26978,EN,CT,China,M,China,0,"Kubernetes, Linux, Mathematics, Hadoop, Scala",Bachelor,1,Healthcare,2024-12-22,2025-01-30,2254,5.5,Neural Networks Co +AI03110,Machine Learning Engineer,45155,USD,45155,SE,FT,China,S,China,50,"Computer Vision, Tableau, Azure, Kubernetes, Spark",Master,5,Gaming,2024-04-03,2024-05-07,582,9.2,Smart Analytics +AI03111,Deep Learning Engineer,84059,USD,84059,MI,FL,United States,S,United States,50,"Linux, Docker, TensorFlow",Bachelor,4,Manufacturing,2024-06-23,2024-07-09,1520,9.1,Future Systems +AI03112,AI Product Manager,66866,USD,66866,EX,FT,India,L,India,0,"Spark, TensorFlow, SQL",Master,13,Transportation,2024-08-09,2024-09-29,2158,9.9,Cloud AI Solutions +AI03113,AI Software Engineer,56427,USD,56427,EN,CT,Ireland,M,Belgium,0,"Docker, Mathematics, PyTorch, Scala",Associate,0,Media,2024-12-19,2025-02-05,568,8.4,Autonomous Tech +AI03114,Principal Data Scientist,91432,USD,91432,MI,FL,Israel,L,Chile,50,"Git, Hadoop, Computer Vision",PhD,3,Healthcare,2024-01-09,2024-03-19,958,7.4,AI Innovations +AI03115,ML Ops Engineer,117486,EUR,99863,SE,FL,France,L,France,50,"Python, R, Computer Vision, Data Visualization, Statistics",PhD,9,Automotive,2025-02-18,2025-04-13,1430,6.9,Digital Transformation LLC +AI03116,ML Ops Engineer,85568,USD,85568,MI,CT,Finland,M,Sweden,0,"Kubernetes, Spark, Tableau, Statistics",PhD,2,Finance,2025-04-11,2025-06-17,538,9.7,Cognitive Computing +AI03117,ML Ops Engineer,308132,EUR,261912,EX,FL,Netherlands,L,India,0,"Hadoop, MLOps, Spark, Linux, R",Associate,19,Retail,2025-04-04,2025-05-24,991,7.7,Future Systems +AI03118,Head of AI,262758,SGD,341585,EX,FL,Singapore,M,Singapore,100,"Python, Computer Vision, Scala",Master,19,Transportation,2024-08-31,2024-09-22,1556,7.2,Autonomous Tech +AI03119,Principal Data Scientist,61958,USD,61958,EX,FL,India,M,Canada,50,"Java, Python, Tableau, Kubernetes, Docker",Master,12,Gaming,2024-10-23,2024-12-27,1245,8.3,Digital Transformation LLC +AI03120,Data Engineer,116493,USD,116493,SE,FL,Ireland,M,Brazil,0,"Linux, AWS, SQL, Kubernetes",PhD,8,Transportation,2024-05-30,2024-07-13,2110,5.1,TechCorp Inc +AI03121,Machine Learning Engineer,174253,SGD,226529,EX,FT,Singapore,S,Singapore,100,"Hadoop, Azure, NLP",Bachelor,14,Education,2025-04-02,2025-04-16,783,5.7,Algorithmic Solutions +AI03122,Research Scientist,133772,USD,133772,SE,PT,United States,S,United States,50,"Kubernetes, PyTorch, GCP",Bachelor,7,Media,2024-04-19,2024-05-04,1741,7.8,Smart Analytics +AI03123,Machine Learning Engineer,183867,USD,183867,EX,FT,Israel,L,Israel,0,"Scala, Computer Vision, Tableau, AWS",PhD,15,Manufacturing,2024-10-05,2024-12-08,1829,6.4,Advanced Robotics +AI03124,Data Analyst,100550,JPY,11060500,MI,FL,Japan,L,Japan,100,"Tableau, Hadoop, Azure, PyTorch, TensorFlow",Associate,3,Transportation,2025-02-28,2025-04-15,842,6.9,Digital Transformation LLC +AI03125,Data Engineer,209570,EUR,178135,EX,FT,Austria,M,Austria,100,"SQL, Python, Java",Associate,10,Telecommunications,2025-01-04,2025-03-08,1946,6.3,Cognitive Computing +AI03126,Machine Learning Researcher,27770,USD,27770,EN,CT,India,L,India,50,"Deep Learning, PyTorch, MLOps, TensorFlow",PhD,0,Manufacturing,2025-01-31,2025-03-25,695,6.1,Machine Intelligence Group +AI03127,Head of AI,239820,SGD,311766,EX,PT,Singapore,M,Singapore,100,"Java, Python, NLP",Bachelor,13,Retail,2024-04-12,2024-06-01,1250,8.2,Future Systems +AI03128,Machine Learning Researcher,90202,USD,90202,EN,FL,Ireland,L,Ireland,50,"Kubernetes, MLOps, PyTorch",PhD,0,Consulting,2025-01-15,2025-03-16,1443,8.8,DataVision Ltd +AI03129,Computer Vision Engineer,47313,EUR,40216,EN,FL,Austria,S,Austria,0,"Python, NLP, TensorFlow",Master,0,Consulting,2025-03-22,2025-05-10,1996,7.4,Predictive Systems +AI03130,Data Analyst,57899,USD,57899,EN,CT,Israel,M,Israel,100,"R, Computer Vision, GCP",Bachelor,1,Healthcare,2024-02-18,2024-04-01,1649,7.8,Machine Intelligence Group +AI03131,ML Ops Engineer,181110,GBP,135833,SE,PT,United Kingdom,L,Mexico,0,"SQL, R, Scala",Bachelor,5,Consulting,2025-04-09,2025-04-29,692,7.4,Autonomous Tech +AI03132,Principal Data Scientist,81776,USD,81776,MI,PT,South Korea,L,South Korea,0,"SQL, Java, Docker, Tableau, Computer Vision",PhD,2,Finance,2024-09-28,2024-12-08,1310,8.1,Advanced Robotics +AI03133,ML Ops Engineer,144619,GBP,108464,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, AWS, Kubernetes",PhD,12,Retail,2025-03-02,2025-05-02,1415,5.4,Digital Transformation LLC +AI03134,AI Specialist,79986,EUR,67988,MI,FL,Germany,S,Germany,50,"Hadoop, Python, MLOps, NLP",Associate,2,Automotive,2024-01-10,2024-03-17,772,6.7,Predictive Systems +AI03135,AI Architect,70655,USD,70655,EN,FT,United States,M,United States,50,"Mathematics, Linux, SQL, AWS, Tableau",Master,1,Healthcare,2024-07-30,2024-09-01,2024,5.8,Future Systems +AI03136,AI Specialist,250855,USD,250855,EX,PT,United States,S,United States,0,"Spark, Git, Data Visualization, MLOps",Master,15,Energy,2024-04-05,2024-05-01,1802,6.1,Advanced Robotics +AI03137,Machine Learning Engineer,91522,GBP,68642,MI,CT,United Kingdom,M,United Kingdom,100,"Tableau, Azure, PyTorch, SQL, Deep Learning",Bachelor,2,Technology,2024-03-27,2024-05-07,1299,7.3,Digital Transformation LLC +AI03138,Principal Data Scientist,124095,CAD,155119,SE,FL,Canada,S,Ghana,50,"SQL, Scala, GCP",Master,9,Media,2024-05-31,2024-06-28,932,8.3,Cloud AI Solutions +AI03139,Computer Vision Engineer,84282,CAD,105353,MI,FT,Canada,M,Indonesia,50,"Scala, Linux, Kubernetes, Python",PhD,2,Energy,2024-07-22,2024-09-15,1571,6.4,Digital Transformation LLC +AI03140,Data Scientist,163240,USD,163240,SE,FL,United States,M,Russia,50,"Scala, SQL, Azure",Master,5,Government,2024-09-23,2024-11-10,896,8.1,Quantum Computing Inc +AI03141,Machine Learning Researcher,168185,USD,168185,SE,CT,Ireland,L,Ireland,50,"Computer Vision, Git, Python, TensorFlow",Bachelor,7,Consulting,2024-11-08,2024-12-06,2288,7.5,DataVision Ltd +AI03142,Robotics Engineer,116627,USD,116627,MI,CT,United States,S,United States,0,"TensorFlow, NLP, Azure, Linux, Mathematics",Master,3,Education,2024-03-07,2024-05-03,1812,9.9,Machine Intelligence Group +AI03143,AI Product Manager,101270,USD,101270,MI,FT,United States,S,United States,50,"Python, Azure, Tableau",Associate,2,Healthcare,2024-01-03,2024-02-12,602,7,Digital Transformation LLC +AI03144,ML Ops Engineer,65343,USD,65343,EN,CT,Sweden,M,Sweden,100,"GCP, SQL, Tableau",Bachelor,1,Media,2025-03-06,2025-05-15,818,9.8,Predictive Systems +AI03145,Computer Vision Engineer,137416,USD,137416,SE,FT,South Korea,L,Colombia,50,"SQL, Python, MLOps",PhD,9,Telecommunications,2024-07-28,2024-09-22,1997,8.8,Machine Intelligence Group +AI03146,Robotics Engineer,295909,EUR,251523,EX,FL,Netherlands,L,Netherlands,100,"Spark, TensorFlow, Tableau, AWS, Python",Bachelor,10,Healthcare,2024-08-09,2024-08-23,1672,9.7,AI Innovations +AI03147,Autonomous Systems Engineer,143218,USD,143218,SE,FL,Ireland,M,Finland,0,"SQL, Scala, Spark, Azure",PhD,8,Technology,2024-02-15,2024-03-01,1730,9.3,Neural Networks Co +AI03148,Head of AI,190216,EUR,161684,EX,FL,Netherlands,L,Netherlands,0,"Python, MLOps, Kubernetes",Associate,18,Manufacturing,2024-04-10,2024-04-27,2389,5.4,Smart Analytics +AI03149,Data Analyst,151114,JPY,16622540,EX,FT,Japan,S,Japan,50,"Spark, Statistics, Docker, Linux, Hadoop",Master,18,Gaming,2025-04-06,2025-05-03,1213,5.7,Algorithmic Solutions +AI03150,Robotics Engineer,77870,USD,77870,EN,CT,Norway,L,Norway,50,"TensorFlow, PyTorch, AWS, Deep Learning",PhD,0,Automotive,2025-01-12,2025-03-11,2177,5.8,Smart Analytics +AI03151,Robotics Engineer,49183,JPY,5410130,EN,FL,Japan,S,Japan,50,"Tableau, Statistics, Python, NLP, Computer Vision",Master,0,Consulting,2025-02-13,2025-02-27,2439,8.5,DeepTech Ventures +AI03152,Autonomous Systems Engineer,62143,USD,62143,EN,PT,Israel,M,Ukraine,100,"Python, GCP, Deep Learning",Associate,1,Education,2025-01-24,2025-02-24,2048,5.3,Quantum Computing Inc +AI03153,AI Software Engineer,121259,AUD,163700,SE,CT,Australia,M,Belgium,0,"Statistics, Git, Deep Learning, Data Visualization, GCP",PhD,5,Real Estate,2025-02-01,2025-03-03,2113,8.3,Advanced Robotics +AI03154,AI Software Engineer,128628,JPY,14149080,SE,PT,Japan,M,Japan,50,"Statistics, Python, Kubernetes, Git, TensorFlow",Bachelor,9,Telecommunications,2024-12-01,2024-12-21,2034,7.3,Cloud AI Solutions +AI03155,Research Scientist,115473,CAD,144341,SE,CT,Canada,M,Ukraine,50,"Python, Kubernetes, Azure, Spark, TensorFlow",Associate,8,Government,2025-01-21,2025-02-25,1666,9.7,Quantum Computing Inc +AI03156,Data Engineer,238600,USD,238600,EX,FT,Israel,M,Israel,0,"PyTorch, NLP, Python, GCP",Master,11,Media,2024-01-26,2024-03-31,1708,9.6,Advanced Robotics +AI03157,AI Product Manager,113103,CHF,101793,EN,PT,Switzerland,L,Switzerland,0,"SQL, Linux, NLP, Azure, PyTorch",Bachelor,1,Real Estate,2025-01-21,2025-03-19,1928,6.4,Advanced Robotics +AI03158,Deep Learning Engineer,47429,USD,47429,SE,PT,India,S,India,50,"R, Git, SQL, Docker",Associate,7,Government,2024-04-28,2024-06-19,1964,6.3,Algorithmic Solutions +AI03159,AI Research Scientist,274181,USD,274181,EX,PT,Israel,L,Philippines,0,"Scala, AWS, SQL, MLOps",Associate,17,Technology,2025-02-18,2025-03-10,780,9.2,Neural Networks Co +AI03160,Principal Data Scientist,139553,CAD,174441,SE,FT,Canada,M,Canada,50,"Kubernetes, Java, Spark",Bachelor,6,Consulting,2024-12-13,2025-02-03,2398,8.9,Digital Transformation LLC +AI03161,AI Product Manager,83557,USD,83557,MI,CT,Finland,S,Singapore,100,"NLP, Kubernetes, Hadoop, R",PhD,3,Consulting,2024-08-25,2024-10-14,2148,5.2,Autonomous Tech +AI03162,AI Consultant,211357,AUD,285332,EX,CT,Australia,S,Turkey,0,"Scala, Git, Spark, Python",Master,15,Transportation,2024-12-16,2025-02-09,2101,8.2,Digital Transformation LLC +AI03163,ML Ops Engineer,181722,CHF,163550,SE,PT,Switzerland,M,Switzerland,100,"Azure, R, GCP",PhD,8,Real Estate,2024-02-11,2024-04-04,1248,7.2,Machine Intelligence Group +AI03164,Computer Vision Engineer,137403,CAD,171754,SE,CT,Canada,M,Indonesia,0,"TensorFlow, Mathematics, Computer Vision, Python, GCP",Bachelor,8,Finance,2024-03-17,2024-04-07,2482,5.8,Quantum Computing Inc +AI03165,Principal Data Scientist,65926,SGD,85704,EN,CT,Singapore,S,Singapore,0,"Python, MLOps, GCP, Mathematics",Master,1,Transportation,2024-10-08,2024-12-03,666,7.8,DeepTech Ventures +AI03166,Head of AI,63867,USD,63867,EN,CT,Sweden,L,Italy,100,"MLOps, Tableau, GCP, PyTorch, TensorFlow",PhD,0,Real Estate,2025-04-01,2025-05-22,1004,9.7,Advanced Robotics +AI03167,Deep Learning Engineer,73754,EUR,62691,EN,CT,Germany,L,Germany,0,"Linux, R, Data Visualization",Associate,0,Real Estate,2024-07-26,2024-08-17,1181,7.4,Predictive Systems +AI03168,Data Analyst,100588,GBP,75441,MI,CT,United Kingdom,S,United Kingdom,0,"Git, AWS, SQL",Master,4,Government,2024-02-23,2024-03-08,722,9.7,AI Innovations +AI03169,Robotics Engineer,215335,USD,215335,EX,PT,Ireland,S,Ireland,100,"NLP, SQL, Tableau",Bachelor,19,Technology,2025-03-17,2025-04-07,1676,7.2,Quantum Computing Inc +AI03170,AI Architect,96892,GBP,72669,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Linux, PyTorch",PhD,1,Real Estate,2024-07-02,2024-09-03,680,7.3,Neural Networks Co +AI03171,Head of AI,203281,USD,203281,SE,CT,Norway,L,Norway,0,"SQL, Docker, Azure",PhD,9,Technology,2024-07-24,2024-09-30,875,8.7,Cloud AI Solutions +AI03172,Deep Learning Engineer,128930,CHF,116037,MI,PT,Switzerland,M,Switzerland,0,"SQL, PyTorch, GCP, Tableau, Deep Learning",Associate,3,Consulting,2024-12-20,2025-02-21,1288,5,Machine Intelligence Group +AI03173,AI Architect,59295,CAD,74119,EN,FL,Canada,S,Canada,50,"MLOps, Linux, SQL, Statistics",Bachelor,0,Consulting,2024-03-22,2024-04-20,1581,5.1,Algorithmic Solutions +AI03174,AI Architect,149462,CAD,186828,EX,CT,Canada,S,Canada,100,"Spark, Computer Vision, R, SQL",PhD,13,Real Estate,2024-05-28,2024-06-30,1196,7.9,Digital Transformation LLC +AI03175,Data Analyst,134389,USD,134389,EX,FL,South Korea,S,South Korea,50,"Python, Java, MLOps, GCP, Deep Learning",PhD,12,Manufacturing,2025-04-30,2025-05-26,2156,8,Quantum Computing Inc +AI03176,Deep Learning Engineer,77125,USD,77125,EN,FT,Sweden,L,Sweden,50,"Azure, SQL, Linux, Data Visualization, Git",Master,1,Telecommunications,2024-10-22,2024-12-11,2144,8.6,Machine Intelligence Group +AI03177,Autonomous Systems Engineer,177796,GBP,133347,EX,PT,United Kingdom,L,United Kingdom,0,"SQL, Tableau, GCP, AWS",Bachelor,12,Real Estate,2024-09-18,2024-10-03,1210,8.5,Algorithmic Solutions +AI03178,Robotics Engineer,146724,USD,146724,SE,CT,Denmark,M,Denmark,100,"Data Visualization, Python, MLOps, Kubernetes",Bachelor,5,Media,2024-09-01,2024-10-05,628,9.4,DeepTech Ventures +AI03179,Data Engineer,170330,USD,170330,SE,CT,Norway,M,Norway,100,"Git, Statistics, Spark, Python, MLOps",Master,6,Manufacturing,2024-05-06,2024-05-29,2072,7.8,Quantum Computing Inc +AI03180,Computer Vision Engineer,79412,USD,79412,MI,CT,South Korea,S,Finland,100,"NLP, Docker, SQL, Python",Master,3,Energy,2024-09-13,2024-10-22,1679,9.2,Future Systems +AI03181,AI Specialist,124306,EUR,105660,SE,FL,Netherlands,L,Netherlands,100,"Python, Azure, GCP, Mathematics, R",Associate,7,Finance,2024-11-02,2024-12-23,1981,6.4,TechCorp Inc +AI03182,Head of AI,119037,EUR,101181,SE,FT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, Tableau, Python, TensorFlow",Bachelor,7,Technology,2024-12-24,2025-01-16,1560,9.9,Algorithmic Solutions +AI03183,NLP Engineer,222977,EUR,189530,EX,FL,Germany,L,Germany,0,"NLP, Computer Vision, Data Visualization, Docker, SQL",PhD,13,Finance,2025-02-21,2025-03-24,869,9,Machine Intelligence Group +AI03184,Data Engineer,136646,CAD,170808,SE,PT,Canada,M,Canada,100,"Python, Docker, Hadoop, Deep Learning",PhD,9,Telecommunications,2024-05-03,2024-06-06,1317,8.4,Algorithmic Solutions +AI03185,AI Specialist,192004,JPY,21120440,EX,FT,Japan,L,France,0,"Kubernetes, AWS, PyTorch",Master,11,Real Estate,2024-05-25,2024-08-03,2244,6.5,Future Systems +AI03186,Research Scientist,270814,GBP,203111,EX,PT,United Kingdom,L,Sweden,0,"Spark, Deep Learning, Azure, Java, Tableau",Bachelor,17,Gaming,2024-05-18,2024-07-25,1890,6.6,Neural Networks Co +AI03187,AI Consultant,125599,USD,125599,SE,FL,Sweden,M,Sweden,0,"Computer Vision, Java, Data Visualization",Associate,8,Technology,2024-03-07,2024-04-17,723,7.7,TechCorp Inc +AI03188,Machine Learning Engineer,102825,USD,102825,MI,PT,Finland,L,United Kingdom,100,"Docker, Tableau, Hadoop, Computer Vision",Associate,3,Technology,2024-02-16,2024-04-02,1608,7.2,Cloud AI Solutions +AI03189,AI Research Scientist,233678,JPY,25704580,EX,FT,Japan,L,Malaysia,100,"MLOps, Azure, Tableau, NLP, PyTorch",Associate,15,Consulting,2024-08-04,2024-09-30,1310,6.8,Predictive Systems +AI03190,AI Consultant,92649,EUR,78752,MI,PT,Netherlands,M,Czech Republic,100,"Spark, Tableau, MLOps",Associate,4,Energy,2024-09-04,2024-09-23,644,9.9,Advanced Robotics +AI03191,AI Research Scientist,102702,EUR,87297,MI,CT,Germany,M,Germany,0,"GCP, Docker, Scala, Python",PhD,4,Automotive,2025-03-05,2025-04-18,765,7,Machine Intelligence Group +AI03192,Autonomous Systems Engineer,220138,SGD,286179,EX,PT,Singapore,S,Singapore,0,"Java, Linux, Scala, Kubernetes",Associate,10,Finance,2024-12-10,2025-01-28,1094,5.1,Machine Intelligence Group +AI03193,NLP Engineer,102269,SGD,132950,MI,PT,Singapore,L,Singapore,50,"SQL, Python, Deep Learning, Linux",Bachelor,3,Energy,2024-08-19,2024-10-31,1527,10,Cognitive Computing +AI03194,AI Software Engineer,164789,USD,164789,EX,FL,Denmark,S,Denmark,100,"Linux, Scala, Docker",Master,15,Retail,2024-02-22,2024-04-09,2219,9.6,DeepTech Ventures +AI03195,AI Software Engineer,37291,USD,37291,MI,FT,India,L,India,50,"PyTorch, TensorFlow, Docker, Hadoop, Linux",Associate,2,Consulting,2024-12-19,2025-01-27,2137,8.6,AI Innovations +AI03196,NLP Engineer,112266,USD,112266,MI,FT,United States,M,United States,50,"Azure, Kubernetes, AWS",Associate,3,Transportation,2025-03-18,2025-05-22,2235,5.7,Cloud AI Solutions +AI03197,NLP Engineer,67601,USD,67601,EN,FL,South Korea,L,Canada,0,"NLP, GCP, Scala",Associate,0,Finance,2024-01-26,2024-03-27,2022,5.7,Cognitive Computing +AI03198,AI Software Engineer,265839,CAD,332299,EX,CT,Canada,L,Canada,0,"Tableau, SQL, Hadoop, Computer Vision, PyTorch",Master,16,Technology,2024-07-12,2024-08-17,1079,9.9,Cloud AI Solutions +AI03199,Autonomous Systems Engineer,127393,CAD,159241,SE,FT,Canada,S,Canada,50,"SQL, Tableau, Docker, PyTorch",PhD,6,Finance,2025-03-02,2025-04-06,961,9.6,Digital Transformation LLC +AI03200,Machine Learning Engineer,79956,USD,79956,MI,FL,Israel,M,Israel,50,"SQL, Scala, Hadoop, Computer Vision, Python",Associate,3,Automotive,2024-05-05,2024-07-16,1366,7,AI Innovations +AI03201,AI Product Manager,64844,USD,64844,EN,PT,Finland,M,Finland,100,"MLOps, Linux, TensorFlow",Associate,0,Manufacturing,2025-03-11,2025-04-05,642,6.3,AI Innovations +AI03202,Data Analyst,255126,GBP,191345,EX,PT,United Kingdom,L,Netherlands,50,"Docker, MLOps, Data Visualization",Master,17,Technology,2024-02-26,2024-03-11,1055,5.4,Cognitive Computing +AI03203,Data Analyst,55235,USD,55235,EN,FL,Sweden,M,Sweden,100,"Scala, Kubernetes, NLP, Azure",Associate,0,Gaming,2025-01-19,2025-03-16,2002,6.9,Cognitive Computing +AI03204,AI Product Manager,179903,EUR,152918,SE,FT,Netherlands,L,Netherlands,0,"Linux, Scala, Java, Docker",Master,7,Media,2024-01-24,2024-03-30,759,6.3,Machine Intelligence Group +AI03205,Deep Learning Engineer,99326,USD,99326,MI,FT,Finland,L,Finland,100,"Tableau, R, Linux, Git, Java",PhD,2,Transportation,2024-11-09,2024-12-01,713,7.9,Algorithmic Solutions +AI03206,NLP Engineer,36397,USD,36397,MI,PT,China,S,China,100,"NLP, Tableau, Docker, MLOps, Data Visualization",Master,4,Gaming,2025-03-20,2025-05-18,863,9.6,Advanced Robotics +AI03207,Head of AI,55499,USD,55499,SE,FT,China,L,China,50,"Spark, R, Hadoop, Kubernetes",PhD,6,Consulting,2024-03-15,2024-04-29,2352,9.4,Future Systems +AI03208,Data Analyst,32595,USD,32595,MI,FT,India,M,Kenya,100,"Python, MLOps, Data Visualization, AWS",Master,3,Government,2024-09-08,2024-10-05,1738,6.4,Advanced Robotics +AI03209,AI Software Engineer,257447,USD,257447,EX,PT,United States,S,United States,0,"Python, PyTorch, TensorFlow, R",Master,19,Consulting,2024-04-07,2024-06-05,2080,6.7,Predictive Systems +AI03210,Research Scientist,92838,EUR,78912,MI,CT,Austria,M,Austria,0,"PyTorch, Azure, MLOps, GCP",Bachelor,2,Real Estate,2024-04-24,2024-05-10,957,7.2,Cloud AI Solutions +AI03211,ML Ops Engineer,90741,EUR,77130,MI,FT,Austria,S,Austria,0,"Tableau, NLP, GCP, Java",PhD,4,Retail,2024-05-05,2024-06-27,2471,7.1,Cloud AI Solutions +AI03212,Computer Vision Engineer,76319,USD,76319,SE,FL,South Korea,S,South Korea,0,"TensorFlow, Python, Docker, Java",Master,6,Media,2024-03-20,2024-05-24,839,6.4,Autonomous Tech +AI03213,AI Specialist,210418,EUR,178855,EX,FT,Austria,L,Austria,100,"Java, Azure, MLOps",Master,11,Government,2024-11-12,2024-12-14,1743,8.4,DataVision Ltd +AI03214,AI Software Engineer,196045,EUR,166638,EX,FL,Germany,M,Romania,0,"Docker, Python, Kubernetes",PhD,10,Education,2024-11-02,2024-11-23,512,5.2,Neural Networks Co +AI03215,Deep Learning Engineer,135969,CHF,122372,SE,FT,Switzerland,S,Belgium,100,"R, Kubernetes, Docker",PhD,8,Technology,2024-09-18,2024-10-09,1530,5.3,Future Systems +AI03216,Head of AI,48643,EUR,41347,EN,FT,Netherlands,S,Netherlands,100,"NLP, Scala, R, Tableau, Python",Bachelor,1,Retail,2024-03-11,2024-04-04,2102,7.5,DeepTech Ventures +AI03217,AI Architect,78066,USD,78066,EN,PT,Finland,L,Egypt,0,"Python, Data Visualization, Kubernetes",Bachelor,0,Real Estate,2025-03-24,2025-05-26,2098,7.9,TechCorp Inc +AI03218,Machine Learning Researcher,41677,USD,41677,EN,CT,South Korea,S,South Korea,100,"MLOps, R, Kubernetes, Deep Learning",Associate,0,Energy,2024-07-09,2024-09-15,1351,6.1,Autonomous Tech +AI03219,Deep Learning Engineer,93162,JPY,10247820,EN,FT,Japan,L,Japan,100,"Python, Deep Learning, Java",Master,0,Manufacturing,2024-09-06,2024-11-10,1406,9.7,Cognitive Computing +AI03220,Research Scientist,64788,EUR,55070,EN,PT,Germany,S,Hungary,50,"PyTorch, Statistics, Spark, SQL, GCP",Associate,0,Media,2024-11-18,2025-01-28,1017,6,Neural Networks Co +AI03221,AI Architect,154205,USD,154205,EX,CT,Ireland,S,Ireland,50,"Azure, AWS, GCP, Spark",Bachelor,19,Media,2024-10-15,2024-10-31,1369,7.8,Algorithmic Solutions +AI03222,Principal Data Scientist,143701,USD,143701,SE,CT,Israel,M,Israel,100,"Tableau, SQL, Scala, Azure",Associate,8,Media,2025-04-04,2025-06-14,557,6.2,DataVision Ltd +AI03223,Data Scientist,164876,CHF,148388,SE,PT,Switzerland,S,Switzerland,0,"Kubernetes, AWS, Scala, GCP",Bachelor,9,Government,2025-01-01,2025-01-16,1603,6.2,Neural Networks Co +AI03224,Autonomous Systems Engineer,35464,USD,35464,EN,FT,China,M,China,0,"Mathematics, Docker, Azure",PhD,1,Education,2024-02-03,2024-02-28,736,9.4,DeepTech Ventures +AI03225,AI Specialist,59626,USD,59626,EN,FL,Ireland,M,Ireland,0,"Linux, Java, Scala",Bachelor,1,Gaming,2025-03-15,2025-04-18,624,5.5,TechCorp Inc +AI03226,AI Specialist,307432,USD,307432,EX,FL,Norway,M,Norway,100,"Linux, Python, NLP",PhD,11,Manufacturing,2025-01-31,2025-03-30,2437,9.6,Digital Transformation LLC +AI03227,AI Architect,176090,USD,176090,SE,FL,Norway,S,Luxembourg,100,"Hadoop, AWS, Spark",Associate,6,Technology,2025-02-27,2025-04-07,2082,9.2,AI Innovations +AI03228,AI Architect,66682,USD,66682,EN,FL,United States,S,United States,0,"Scala, Java, NLP, R",Associate,0,Finance,2024-08-19,2024-09-24,1664,9.8,Digital Transformation LLC +AI03229,Data Analyst,39616,USD,39616,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Scala, Tableau, R, Python",PhD,0,Real Estate,2024-06-13,2024-07-30,550,8,DeepTech Ventures +AI03230,AI Product Manager,122403,CHF,110163,EN,PT,Switzerland,L,Singapore,100,"TensorFlow, Kubernetes, NLP",Associate,0,Finance,2024-01-23,2024-03-02,2351,8.2,Cognitive Computing +AI03231,Deep Learning Engineer,130431,USD,130431,SE,FT,Finland,M,Finland,100,"Linux, R, NLP",PhD,8,Government,2024-08-26,2024-11-07,1081,6.4,Smart Analytics +AI03232,AI Software Engineer,91342,EUR,77641,MI,PT,Germany,S,Germany,100,"Hadoop, SQL, Docker",Bachelor,4,Healthcare,2024-02-05,2024-04-15,524,6.7,TechCorp Inc +AI03233,AI Product Manager,34743,USD,34743,EN,FL,China,M,China,100,"R, Hadoop, PyTorch",Master,0,Real Estate,2024-03-08,2024-05-01,1698,7.9,Future Systems +AI03234,Computer Vision Engineer,75941,EUR,64550,MI,FT,France,S,France,100,"Statistics, R, Python, GCP",Master,3,Telecommunications,2024-06-30,2024-08-12,1131,6.5,Machine Intelligence Group +AI03235,AI Product Manager,53406,USD,53406,EN,CT,South Korea,M,South Korea,100,"NLP, Kubernetes, Python",Associate,0,Manufacturing,2025-03-01,2025-05-12,2231,9.6,Neural Networks Co +AI03236,Autonomous Systems Engineer,280999,CHF,252899,EX,FT,Switzerland,M,Switzerland,100,"Linux, Kubernetes, GCP, Python",Associate,18,Gaming,2024-06-11,2024-08-17,1120,9.3,Predictive Systems +AI03237,Computer Vision Engineer,211482,SGD,274927,EX,PT,Singapore,L,Singapore,50,"Scala, Statistics, Python",Bachelor,17,Education,2024-09-26,2024-11-06,1183,8,DeepTech Ventures +AI03238,AI Architect,188072,CHF,169265,EX,CT,Switzerland,S,Switzerland,100,"SQL, Kubernetes, Azure",Associate,11,Automotive,2025-02-15,2025-03-15,1142,5.9,Predictive Systems +AI03239,NLP Engineer,89391,EUR,75982,MI,FL,Germany,M,Germany,0,"SQL, Hadoop, Java",Bachelor,2,Consulting,2025-04-15,2025-04-29,2251,6.3,DeepTech Ventures +AI03240,Machine Learning Researcher,172617,CHF,155355,SE,FL,Switzerland,L,Switzerland,0,"Data Visualization, NLP, Azure",Associate,7,Real Estate,2024-11-08,2024-12-19,1254,6.3,Digital Transformation LLC +AI03241,Head of AI,247125,SGD,321263,EX,FT,Singapore,L,Singapore,100,"TensorFlow, Git, Java, Azure, NLP",PhD,18,Energy,2025-03-23,2025-04-11,616,6.1,Advanced Robotics +AI03242,AI Architect,58586,EUR,49798,EN,CT,Austria,L,Austria,0,"Python, AWS, Kubernetes, Scala, Statistics",PhD,0,Government,2025-02-10,2025-03-02,1313,8.6,Quantum Computing Inc +AI03243,AI Consultant,66857,USD,66857,EN,FT,United States,M,France,100,"GCP, Scala, Mathematics",Associate,0,Manufacturing,2024-04-16,2024-05-05,1143,8.9,DeepTech Ventures +AI03244,Machine Learning Engineer,61082,USD,61082,EN,FT,Ireland,S,Ireland,0,"MLOps, Data Visualization, PyTorch, Kubernetes, Python",PhD,1,Government,2024-10-19,2024-12-13,1334,6.9,DataVision Ltd +AI03245,Principal Data Scientist,109973,SGD,142965,MI,FL,Singapore,M,Singapore,100,"Kubernetes, MLOps, Spark, R, SQL",Associate,4,Real Estate,2024-03-04,2024-03-29,1826,9.1,Machine Intelligence Group +AI03246,Machine Learning Engineer,96154,GBP,72116,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, Data Visualization, Scala, Tableau",PhD,3,Telecommunications,2024-10-28,2024-12-15,1199,8.5,Smart Analytics +AI03247,Data Engineer,80737,EUR,68626,MI,CT,France,L,France,50,"Java, Python, Docker",PhD,3,Manufacturing,2024-08-25,2024-09-15,1683,7.5,Quantum Computing Inc +AI03248,Data Analyst,60211,USD,60211,EN,PT,Israel,S,Israel,50,"NLP, Deep Learning, PyTorch, Mathematics, Scala",PhD,0,Technology,2025-01-16,2025-03-09,1572,5.4,DataVision Ltd +AI03249,AI Research Scientist,77885,EUR,66202,MI,PT,Austria,M,Austria,50,"Docker, Azure, Kubernetes",Associate,2,Gaming,2024-09-16,2024-10-07,1002,8.5,Algorithmic Solutions +AI03250,Machine Learning Engineer,91640,CAD,114550,MI,PT,Canada,S,China,50,"PyTorch, TensorFlow, Java, MLOps, AWS",Bachelor,4,Education,2025-03-02,2025-04-13,2355,6.5,Digital Transformation LLC +AI03251,Principal Data Scientist,136201,CAD,170251,EX,FT,Canada,S,Canada,100,"Kubernetes, Java, MLOps",Associate,11,Healthcare,2024-09-24,2024-11-22,1786,9.9,Smart Analytics +AI03252,Machine Learning Researcher,100307,SGD,130399,SE,PT,Singapore,S,Singapore,100,"R, SQL, Statistics, PyTorch",Associate,8,Government,2024-04-16,2024-05-10,844,7.7,Cloud AI Solutions +AI03253,AI Specialist,71821,CAD,89776,EN,FT,Canada,L,Canada,0,"Azure, R, NLP, Hadoop, Git",Bachelor,0,Manufacturing,2024-08-27,2024-09-24,1281,7.9,Future Systems +AI03254,AI Software Engineer,92325,USD,92325,MI,CT,Finland,L,Finland,100,"TensorFlow, Python, Java, Linux",Bachelor,2,Telecommunications,2024-07-26,2024-08-28,1168,8.5,Digital Transformation LLC +AI03255,Machine Learning Researcher,128402,EUR,109142,SE,PT,Germany,S,Germany,0,"Spark, SQL, Azure, GCP, Deep Learning",PhD,5,Government,2025-01-18,2025-03-10,2118,6.3,Quantum Computing Inc +AI03256,Data Analyst,49741,USD,49741,EX,CT,India,M,India,0,"Docker, MLOps, Spark",Associate,12,Real Estate,2024-02-11,2024-04-19,1653,8.1,TechCorp Inc +AI03257,AI Software Engineer,189605,CHF,170645,SE,FT,Switzerland,S,Switzerland,0,"TensorFlow, Python, Tableau, Deep Learning",PhD,5,Real Estate,2025-02-06,2025-03-22,1625,6,Cognitive Computing +AI03258,Machine Learning Engineer,91412,SGD,118836,EN,FL,Singapore,L,United States,100,"Deep Learning, SQL, Hadoop",Associate,1,Education,2025-01-25,2025-03-19,966,7.7,Machine Intelligence Group +AI03259,Robotics Engineer,214536,USD,214536,SE,CT,Denmark,L,Poland,50,"SQL, Java, Statistics, Computer Vision, Deep Learning",PhD,8,Healthcare,2024-08-26,2024-10-23,1367,9.8,AI Innovations +AI03260,Machine Learning Researcher,93353,USD,93353,MI,PT,Norway,S,Norway,0,"Computer Vision, SQL, NLP, PyTorch, AWS",Associate,3,Education,2024-06-30,2024-07-30,2332,5.1,Autonomous Tech +AI03261,AI Architect,119157,USD,119157,SE,CT,Finland,L,Finland,100,"Kubernetes, PyTorch, GCP, Azure",Bachelor,7,Government,2024-01-07,2024-01-24,783,5.4,Advanced Robotics +AI03262,AI Specialist,262609,CHF,236348,EX,CT,Switzerland,L,Switzerland,50,"Hadoop, TensorFlow, PyTorch, Azure",Bachelor,16,Education,2024-05-11,2024-07-22,2100,5.6,Cloud AI Solutions +AI03263,AI Product Manager,69585,AUD,93940,EN,PT,Australia,S,Australia,100,"Computer Vision, Mathematics, Azure, R",PhD,0,Real Estate,2024-12-23,2025-01-20,1195,9.8,Machine Intelligence Group +AI03264,AI Product Manager,74761,AUD,100927,EN,PT,Australia,M,Australia,50,"MLOps, GCP, Docker, Python",Bachelor,0,Government,2024-12-07,2025-01-15,1022,6.9,AI Innovations +AI03265,ML Ops Engineer,162450,CHF,146205,SE,PT,Switzerland,M,Switzerland,0,"Spark, Git, Mathematics, Kubernetes, Python",Associate,7,Automotive,2024-07-06,2024-08-05,2224,6.5,Machine Intelligence Group +AI03266,Data Scientist,88851,USD,88851,EN,FL,Norway,S,Norway,100,"Data Visualization, Linux, Hadoop, Tableau",Bachelor,1,Retail,2025-03-30,2025-04-27,776,9.7,Quantum Computing Inc +AI03267,Autonomous Systems Engineer,91547,EUR,77815,EN,CT,Netherlands,L,Denmark,100,"PyTorch, Scala, Spark, SQL",Master,0,Finance,2025-02-22,2025-03-14,1399,6.3,DeepTech Ventures +AI03268,Principal Data Scientist,58081,EUR,49369,EN,FT,Germany,M,Germany,50,"TensorFlow, Kubernetes, Python, R",PhD,0,Technology,2024-12-27,2025-01-16,1995,8.1,Cloud AI Solutions +AI03269,Computer Vision Engineer,103246,EUR,87759,SE,PT,Austria,S,Austria,50,"Docker, Scala, GCP, AWS",Associate,5,Finance,2024-06-29,2024-08-28,1275,5,Quantum Computing Inc +AI03270,AI Research Scientist,32356,USD,32356,EN,CT,China,S,Estonia,100,"MLOps, R, Hadoop, SQL",PhD,0,Government,2025-01-11,2025-02-08,804,5.2,DeepTech Ventures +AI03271,AI Product Manager,48264,USD,48264,SE,FL,China,S,Hungary,0,"MLOps, PyTorch, Tableau, Data Visualization",Associate,7,Education,2024-08-02,2024-09-27,602,7.5,Neural Networks Co +AI03272,Research Scientist,66275,JPY,7290250,EN,PT,Japan,S,Japan,50,"Python, Tableau, SQL, MLOps",Master,1,Manufacturing,2024-10-01,2024-10-28,1057,7.8,Cloud AI Solutions +AI03273,Machine Learning Researcher,177406,JPY,19514660,EX,FT,Japan,L,Mexico,50,"Hadoop, Spark, Kubernetes",Master,14,Consulting,2024-09-12,2024-10-22,1985,8.4,Algorithmic Solutions +AI03274,Deep Learning Engineer,68779,USD,68779,EN,PT,United States,M,Poland,50,"Python, Git, NLP, Mathematics",PhD,0,Automotive,2024-05-24,2024-06-13,1842,9.1,Predictive Systems +AI03275,Robotics Engineer,93037,EUR,79081,MI,CT,France,M,France,0,"Git, Azure, Computer Vision, Python",PhD,2,Finance,2025-02-20,2025-03-23,1043,5.9,Cognitive Computing +AI03276,AI Product Manager,90694,CAD,113368,SE,CT,Canada,S,Canada,50,"R, Hadoop, Computer Vision, TensorFlow",Associate,8,Manufacturing,2024-12-30,2025-03-09,951,6.9,Quantum Computing Inc +AI03277,Autonomous Systems Engineer,197861,USD,197861,EX,FL,Israel,L,Malaysia,50,"Hadoop, MLOps, TensorFlow",Associate,17,Manufacturing,2025-03-25,2025-05-28,2052,7.2,DataVision Ltd +AI03278,AI Research Scientist,68932,USD,68932,MI,PT,South Korea,M,Chile,0,"Azure, Python, Linux",Master,2,Finance,2024-09-10,2024-10-02,2382,9.7,Quantum Computing Inc +AI03279,AI Software Engineer,83285,EUR,70792,MI,CT,France,M,France,100,"Data Visualization, SQL, R, NLP",Master,2,Media,2024-11-07,2024-12-02,886,9.7,Neural Networks Co +AI03280,NLP Engineer,161470,USD,161470,SE,CT,Israel,L,Israel,0,"Data Visualization, Kubernetes, Computer Vision",PhD,6,Retail,2025-01-18,2025-02-27,1896,9.2,Autonomous Tech +AI03281,NLP Engineer,101298,USD,101298,EN,FT,Norway,M,Norway,50,"NLP, GCP, Scala",Master,1,Technology,2024-12-27,2025-02-18,1133,9.3,Machine Intelligence Group +AI03282,AI Software Engineer,98441,USD,98441,MI,PT,United States,M,United States,0,"Mathematics, Java, Scala, Docker",PhD,2,Finance,2024-03-04,2024-05-15,1689,8.7,Digital Transformation LLC +AI03283,Principal Data Scientist,142540,USD,142540,SE,FT,South Korea,L,Czech Republic,0,"R, PyTorch, Linux, Mathematics",Master,6,Telecommunications,2024-07-19,2024-09-29,1555,8.7,Autonomous Tech +AI03284,Machine Learning Researcher,141976,USD,141976,SE,FT,Israel,M,Indonesia,50,"Git, Kubernetes, PyTorch",PhD,9,Telecommunications,2024-09-14,2024-10-29,2038,9.2,DeepTech Ventures +AI03285,Robotics Engineer,56123,USD,56123,EN,PT,Finland,M,Finland,50,"GCP, Python, AWS",Master,1,Manufacturing,2024-02-15,2024-04-28,503,5.1,Algorithmic Solutions +AI03286,NLP Engineer,93288,EUR,79295,MI,PT,Germany,L,Germany,0,"Statistics, Scala, Mathematics, Kubernetes",Bachelor,4,Gaming,2024-07-22,2024-08-28,2014,7.3,Machine Intelligence Group +AI03287,AI Consultant,111008,USD,111008,MI,FT,United States,S,United States,100,"Azure, R, Mathematics, NLP",Master,4,Consulting,2024-10-27,2024-12-20,2364,8.4,Smart Analytics +AI03288,NLP Engineer,188040,SGD,244452,EX,FT,Singapore,S,Singapore,0,"Scala, Git, SQL, Java, Mathematics",Associate,11,Transportation,2024-06-25,2024-08-12,2155,7.7,DataVision Ltd +AI03289,Computer Vision Engineer,37867,USD,37867,MI,PT,China,S,China,0,"Git, Statistics, Scala",PhD,4,Real Estate,2024-01-08,2024-02-04,2351,8.9,Predictive Systems +AI03290,AI Research Scientist,130573,USD,130573,EX,PT,Israel,S,India,100,"SQL, AWS, Python",Master,18,Finance,2024-02-02,2024-03-05,1006,5.4,Advanced Robotics +AI03291,AI Product Manager,84549,EUR,71867,EN,FL,Austria,L,Austria,50,"Linux, Mathematics, MLOps, Java, PyTorch",PhD,0,Transportation,2024-03-08,2024-04-22,1947,9.8,DataVision Ltd +AI03292,AI Specialist,115767,USD,115767,EN,PT,Denmark,L,Denmark,50,"PyTorch, Python, Linux, Mathematics",PhD,1,Gaming,2025-01-23,2025-03-25,2233,5.3,Autonomous Tech +AI03293,AI Consultant,229034,CHF,206131,SE,FL,Switzerland,L,Malaysia,50,"R, Statistics, Data Visualization, Deep Learning",PhD,5,Gaming,2024-02-08,2024-04-08,1422,9.4,DeepTech Ventures +AI03294,AI Research Scientist,128520,SGD,167076,SE,PT,Singapore,S,Singapore,0,"Scala, TensorFlow, Kubernetes, Docker, Mathematics",Master,6,Media,2024-12-27,2025-01-23,1971,6.5,AI Innovations +AI03295,Data Analyst,73935,EUR,62845,EN,FT,Netherlands,S,Netherlands,100,"Spark, PyTorch, Java, GCP",Associate,0,Government,2024-03-18,2024-04-10,806,8.6,Machine Intelligence Group +AI03296,AI Product Manager,113864,USD,113864,SE,FT,Ireland,S,Kenya,50,"R, Hadoop, SQL, Data Visualization",Master,6,Finance,2025-04-21,2025-06-25,859,5.3,Predictive Systems +AI03297,Computer Vision Engineer,98526,SGD,128084,SE,PT,Singapore,S,Singapore,50,"Azure, PyTorch, NLP",Associate,7,Manufacturing,2024-06-20,2024-08-21,974,8,Autonomous Tech +AI03298,Deep Learning Engineer,66726,USD,66726,EN,PT,Finland,M,Finland,100,"Docker, Computer Vision, Python, Spark",Bachelor,0,Real Estate,2024-06-17,2024-07-10,1308,7.8,Cloud AI Solutions +AI03299,Data Analyst,88638,AUD,119661,EN,CT,Australia,L,Sweden,100,"Mathematics, Deep Learning, Python, Java, TensorFlow",Master,1,Healthcare,2025-03-29,2025-06-03,835,7.6,DataVision Ltd +AI03300,Autonomous Systems Engineer,93012,USD,93012,MI,PT,United States,S,United States,50,"Kubernetes, Deep Learning, Git",PhD,3,Finance,2024-12-07,2024-12-21,1664,9.8,Cloud AI Solutions +AI03301,Computer Vision Engineer,78878,USD,78878,EN,FL,Denmark,L,Canada,50,"Scala, GCP, MLOps, Linux, Spark",Associate,0,Consulting,2025-01-17,2025-03-27,1459,9.1,Advanced Robotics +AI03302,NLP Engineer,82710,JPY,9098100,EN,FT,Japan,M,Japan,0,"Linux, Computer Vision, Tableau, NLP",Master,0,Gaming,2024-06-03,2024-07-20,1488,6.3,DeepTech Ventures +AI03303,Machine Learning Engineer,29961,USD,29961,EN,FT,China,S,Canada,100,"Data Visualization, Python, Kubernetes",Bachelor,1,Real Estate,2025-01-20,2025-02-15,1613,6.1,Future Systems +AI03304,NLP Engineer,273589,USD,273589,EX,FL,Denmark,M,Denmark,100,"R, Spark, GCP, Azure",PhD,11,Real Estate,2025-02-21,2025-04-11,763,7.4,Cognitive Computing +AI03305,AI Consultant,73518,JPY,8086980,EN,FL,Japan,M,Japan,0,"Data Visualization, NLP, AWS, Spark, Computer Vision",PhD,1,Real Estate,2024-11-14,2024-11-30,1298,7.4,AI Innovations +AI03306,Autonomous Systems Engineer,62379,JPY,6861690,EN,FT,Japan,L,Japan,50,"Deep Learning, Python, TensorFlow",Bachelor,1,Retail,2024-02-21,2024-03-26,1088,6,Autonomous Tech +AI03307,Data Analyst,73138,USD,73138,EX,CT,India,L,India,100,"PyTorch, GCP, MLOps, R, Deep Learning",Master,19,Real Estate,2024-01-14,2024-02-28,1574,9.4,Cloud AI Solutions +AI03308,Data Engineer,308012,EUR,261810,EX,FT,Netherlands,L,Israel,0,"Statistics, Spark, SQL, PyTorch, GCP",PhD,19,Automotive,2024-10-26,2024-11-29,852,8.5,Predictive Systems +AI03309,Robotics Engineer,72475,USD,72475,EN,FT,Israel,M,Israel,0,"Linux, TensorFlow, Python, Scala",Master,1,Retail,2024-11-04,2025-01-04,2425,8.7,Autonomous Tech +AI03310,Research Scientist,71202,USD,71202,EN,CT,Norway,S,Norway,0,"Hadoop, MLOps, Git, Linux, NLP",Master,0,Automotive,2025-02-02,2025-02-23,2495,7.8,Predictive Systems +AI03311,AI Research Scientist,178194,EUR,151465,EX,FT,Netherlands,M,Netherlands,100,"Deep Learning, Git, R",Associate,15,Retail,2024-07-18,2024-08-21,2376,7.5,DeepTech Ventures +AI03312,AI Consultant,26837,USD,26837,EN,CT,India,M,India,0,"PyTorch, SQL, Scala",Bachelor,0,Healthcare,2024-01-27,2024-03-06,1504,7.4,Advanced Robotics +AI03313,Principal Data Scientist,97019,USD,97019,MI,FL,Finland,M,Estonia,50,"NLP, Spark, Scala, Git",Bachelor,4,Retail,2025-02-11,2025-04-25,1089,6.5,DataVision Ltd +AI03314,Robotics Engineer,118655,EUR,100857,SE,FT,France,L,Czech Republic,0,"Computer Vision, Tableau, Scala",Bachelor,7,Consulting,2025-02-23,2025-03-27,822,7.4,Machine Intelligence Group +AI03315,AI Specialist,84059,JPY,9246490,MI,FT,Japan,S,Japan,100,"SQL, Docker, Mathematics, GCP",PhD,2,Healthcare,2025-04-04,2025-06-06,2331,5.4,Quantum Computing Inc +AI03316,AI Consultant,205243,CAD,256554,EX,FL,Canada,M,Poland,50,"Java, Tableau, Statistics, Mathematics",Master,11,Education,2025-03-12,2025-05-18,1170,8.7,Digital Transformation LLC +AI03317,AI Research Scientist,65453,USD,65453,MI,PT,Israel,S,Romania,50,"Python, PyTorch, GCP, Java, Deep Learning",PhD,4,Transportation,2024-02-06,2024-03-25,818,8.8,Neural Networks Co +AI03318,Computer Vision Engineer,103929,USD,103929,SE,CT,South Korea,M,South Korea,0,"Data Visualization, Python, Linux, Mathematics",Bachelor,9,Transportation,2024-01-12,2024-01-27,996,6.4,Smart Analytics +AI03319,Head of AI,83770,JPY,9214700,MI,PT,Japan,M,Russia,0,"Kubernetes, NLP, PyTorch",Master,3,Telecommunications,2025-01-31,2025-03-12,1521,6.7,AI Innovations +AI03320,AI Software Engineer,71511,EUR,60784,EN,FL,Germany,M,Germany,50,"Mathematics, R, Java, Git, Linux",Bachelor,1,Government,2024-01-24,2024-04-05,2237,5.2,Smart Analytics +AI03321,Robotics Engineer,86602,USD,86602,MI,FT,Sweden,S,Egypt,100,"PyTorch, TensorFlow, Data Visualization",Master,4,Government,2024-06-10,2024-08-21,1231,6.9,TechCorp Inc +AI03322,AI Consultant,57477,SGD,74720,EN,CT,Singapore,S,Singapore,50,"Python, Hadoop, MLOps, Deep Learning",Master,1,Finance,2024-05-20,2024-06-21,665,6.8,Neural Networks Co +AI03323,Machine Learning Engineer,104741,JPY,11521510,MI,FT,Japan,M,Japan,50,"Docker, Python, Computer Vision, Scala",PhD,4,Technology,2024-08-10,2024-09-12,595,6.6,DataVision Ltd +AI03324,Computer Vision Engineer,257714,USD,257714,EX,FT,Denmark,S,Denmark,100,"Python, Docker, Spark, Azure, Linux",Master,12,Finance,2024-07-22,2024-08-20,1875,5.9,Advanced Robotics +AI03325,Data Engineer,67170,JPY,7388700,EN,FL,Japan,S,Japan,100,"Kubernetes, Scala, NLP, Deep Learning",Bachelor,0,Retail,2024-10-22,2024-12-21,2375,6.8,Advanced Robotics +AI03326,Machine Learning Engineer,145681,EUR,123829,SE,PT,Austria,L,Austria,0,"TensorFlow, Computer Vision, Data Visualization",Associate,5,Consulting,2024-01-20,2024-03-29,808,7.1,DeepTech Ventures +AI03327,AI Specialist,118285,EUR,100542,MI,PT,Austria,L,Ireland,50,"Statistics, Scala, Data Visualization, Spark, Java",Bachelor,2,Government,2025-04-14,2025-05-07,1534,5.3,Cognitive Computing +AI03328,Principal Data Scientist,151221,USD,151221,SE,FL,United States,M,United States,0,"PyTorch, Scala, Hadoop, GCP",Master,6,Technology,2024-07-18,2024-08-17,638,8.6,Machine Intelligence Group +AI03329,Robotics Engineer,97110,CHF,87399,EN,FT,Switzerland,L,Switzerland,50,"Python, GCP, Mathematics",PhD,0,Healthcare,2024-04-25,2024-07-04,825,8.7,Cloud AI Solutions +AI03330,Research Scientist,142010,USD,142010,SE,CT,Israel,L,Israel,0,"Spark, Mathematics, Data Visualization, PyTorch, MLOps",Associate,9,Technology,2024-06-01,2024-07-18,590,5.7,Cloud AI Solutions +AI03331,AI Product Manager,221988,EUR,188690,EX,FT,Netherlands,S,Philippines,100,"Kubernetes, Data Visualization, Git, SQL",Associate,13,Technology,2025-02-15,2025-03-07,2002,9.2,DataVision Ltd +AI03332,AI Consultant,171046,USD,171046,EX,CT,United States,S,United States,100,"PyTorch, AWS, MLOps, Docker",PhD,13,Government,2024-10-09,2024-11-06,1843,6.9,Cloud AI Solutions +AI03333,Research Scientist,71257,USD,71257,EN,FT,South Korea,L,Kenya,50,"Data Visualization, AWS, Tableau, SQL",PhD,0,Technology,2025-02-17,2025-03-07,2459,8.3,TechCorp Inc +AI03334,ML Ops Engineer,109428,USD,109428,SE,PT,Ireland,S,Ireland,0,"Scala, SQL, NLP, Mathematics",Bachelor,5,Healthcare,2024-12-13,2024-12-29,2367,6.1,Smart Analytics +AI03335,Autonomous Systems Engineer,221626,AUD,299195,EX,CT,Australia,M,Romania,100,"Kubernetes, GCP, Data Visualization",Bachelor,13,Healthcare,2024-10-18,2024-11-24,1179,7.6,Machine Intelligence Group +AI03336,Deep Learning Engineer,189458,GBP,142094,EX,CT,United Kingdom,S,Portugal,0,"PyTorch, Spark, SQL, Hadoop, Mathematics",Master,10,Energy,2024-04-14,2024-05-09,1518,5.1,Smart Analytics +AI03337,Principal Data Scientist,200620,CHF,180558,EX,PT,Switzerland,M,Australia,50,"Computer Vision, AWS, Python, TensorFlow",PhD,17,Energy,2024-04-30,2024-07-01,1920,5.4,Machine Intelligence Group +AI03338,AI Specialist,205234,CAD,256543,EX,FT,Canada,S,Canada,50,"Hadoop, Azure, NLP",Bachelor,18,Energy,2024-12-23,2025-02-24,809,7.8,Neural Networks Co +AI03339,Research Scientist,247132,USD,247132,EX,PT,Israel,L,Israel,50,"Python, Kubernetes, SQL",PhD,10,Government,2024-04-21,2024-06-01,673,9.4,TechCorp Inc +AI03340,Deep Learning Engineer,97358,USD,97358,EN,CT,Norway,M,Canada,50,"PyTorch, AWS, Azure, Git, TensorFlow",Master,0,Telecommunications,2024-05-14,2024-07-06,1847,7.1,Quantum Computing Inc +AI03341,Head of AI,57152,SGD,74298,EN,FL,Singapore,M,Singapore,0,"Statistics, Git, Data Visualization",Master,0,Automotive,2024-01-15,2024-03-25,1629,9,Smart Analytics +AI03342,Data Engineer,103950,EUR,88358,SE,PT,France,M,France,100,"Spark, Hadoop, NLP",Master,8,Consulting,2024-06-12,2024-07-25,1220,7.7,Future Systems +AI03343,Principal Data Scientist,112737,AUD,152195,SE,FL,Australia,S,Australia,0,"NLP, Scala, Mathematics, Java, SQL",Bachelor,5,Transportation,2024-08-17,2024-10-12,820,9.9,Neural Networks Co +AI03344,AI Product Manager,81647,JPY,8981170,EN,PT,Japan,L,Denmark,50,"GCP, Tableau, SQL, Computer Vision, Azure",Master,1,Media,2025-03-15,2025-05-10,2037,9,Predictive Systems +AI03345,Autonomous Systems Engineer,80194,USD,80194,MI,PT,Finland,M,Finland,100,"Python, GCP, Statistics",Associate,3,Automotive,2024-06-29,2024-08-07,1331,6.4,Algorithmic Solutions +AI03346,Machine Learning Researcher,50217,USD,50217,SE,FT,India,L,India,0,"Scala, TensorFlow, Tableau",Master,7,Energy,2025-01-29,2025-03-25,677,8.8,Neural Networks Co +AI03347,AI Consultant,242187,SGD,314843,EX,FL,Singapore,S,Netherlands,100,"Statistics, Tableau, PyTorch, NLP",Bachelor,10,Healthcare,2025-03-11,2025-04-12,2106,5.2,Autonomous Tech +AI03348,Head of AI,140261,USD,140261,SE,FL,Norway,M,Norway,100,"Linux, TensorFlow, SQL, Deep Learning, Java",Bachelor,6,Manufacturing,2024-09-02,2024-10-27,640,8.4,Advanced Robotics +AI03349,Data Engineer,92105,USD,92105,MI,FT,Finland,S,Austria,50,"AWS, Hadoop, Spark, NLP, Git",PhD,4,Transportation,2024-12-18,2025-02-17,1207,9,Digital Transformation LLC +AI03350,Research Scientist,123667,USD,123667,SE,PT,Ireland,M,China,50,"PyTorch, Statistics, Azure",PhD,6,Energy,2024-05-21,2024-06-13,1651,9.9,Machine Intelligence Group +AI03351,Machine Learning Engineer,93495,USD,93495,MI,PT,United States,S,United States,0,"TensorFlow, Kubernetes, Hadoop, Azure, Scala",Bachelor,3,Telecommunications,2024-11-14,2025-01-18,1663,6.5,Digital Transformation LLC +AI03352,Research Scientist,164403,AUD,221944,EX,FT,Australia,L,Australia,0,"Python, Git, TensorFlow, Hadoop, Mathematics",Bachelor,14,Government,2025-01-26,2025-03-26,1244,6.3,AI Innovations +AI03353,Deep Learning Engineer,161726,GBP,121295,SE,PT,United Kingdom,M,Indonesia,50,"AWS, Python, Tableau, R",Bachelor,8,Manufacturing,2025-03-03,2025-03-26,1141,8.1,Advanced Robotics +AI03354,Data Engineer,65395,AUD,88283,EN,CT,Australia,S,Australia,100,"PyTorch, Statistics, SQL, AWS",Bachelor,0,Transportation,2025-02-12,2025-04-20,2277,5.7,DeepTech Ventures +AI03355,Research Scientist,163112,USD,163112,SE,PT,Finland,L,Finland,50,"Python, Linux, Java, R",PhD,8,Telecommunications,2024-06-08,2024-08-02,1351,5.6,Autonomous Tech +AI03356,NLP Engineer,120372,USD,120372,SE,PT,Sweden,S,Sweden,0,"Spark, MLOps, Deep Learning",Associate,7,Real Estate,2024-12-27,2025-03-07,1014,5.1,Smart Analytics +AI03357,AI Consultant,80130,USD,80130,EN,FT,Denmark,L,Denmark,100,"SQL, PyTorch, R",Associate,1,Gaming,2024-12-27,2025-02-28,2374,7.3,Advanced Robotics +AI03358,Deep Learning Engineer,69483,USD,69483,SE,CT,China,L,China,50,"Python, R, GCP, Docker",Master,6,Technology,2024-07-26,2024-08-19,733,6.5,Digital Transformation LLC +AI03359,AI Specialist,275292,USD,275292,EX,FL,Denmark,M,Denmark,50,"Git, PyTorch, MLOps, Spark, Kubernetes",Master,16,Government,2024-03-12,2024-03-28,572,9.9,Machine Intelligence Group +AI03360,Data Analyst,90173,EUR,76647,MI,CT,Germany,L,Germany,50,"Linux, Scala, Mathematics, AWS, SQL",Bachelor,4,Technology,2024-11-25,2025-01-29,1158,7.8,Quantum Computing Inc +AI03361,AI Consultant,115690,JPY,12725900,MI,CT,Japan,L,Latvia,100,"Spark, Scala, Tableau, SQL",Master,3,Automotive,2024-11-25,2025-02-05,2463,9.8,Neural Networks Co +AI03362,Machine Learning Engineer,52110,USD,52110,EN,CT,Sweden,M,Luxembourg,100,"Mathematics, Scala, Python, Kubernetes",Associate,0,Energy,2024-06-01,2024-08-07,838,5.6,Cloud AI Solutions +AI03363,Deep Learning Engineer,163804,USD,163804,SE,CT,Norway,M,Estonia,100,"R, Java, Azure, Mathematics, NLP",PhD,7,Energy,2024-04-24,2024-06-25,2440,8.9,AI Innovations +AI03364,Machine Learning Researcher,173688,EUR,147635,SE,PT,Netherlands,L,Netherlands,100,"R, Linux, Git",Associate,6,Media,2024-09-05,2024-10-08,2247,8.2,Autonomous Tech +AI03365,Machine Learning Researcher,244135,AUD,329582,EX,PT,Australia,M,Australia,100,"Linux, SQL, Git, Data Visualization",Master,17,Automotive,2024-12-24,2025-01-16,2027,7.7,Machine Intelligence Group +AI03366,Research Scientist,177041,USD,177041,EX,CT,Finland,S,Estonia,100,"Azure, R, Tableau, Hadoop",Associate,12,Transportation,2024-05-06,2024-05-30,959,7.9,Neural Networks Co +AI03367,Head of AI,113070,CHF,101763,MI,FL,Switzerland,M,Poland,0,"R, Kubernetes, Tableau",PhD,4,Technology,2024-09-10,2024-11-15,1787,8.8,DeepTech Ventures +AI03368,Machine Learning Engineer,34381,USD,34381,SE,CT,India,S,India,0,"Hadoop, Python, Statistics, Linux, AWS",PhD,6,Retail,2025-02-28,2025-03-20,2339,5.2,Machine Intelligence Group +AI03369,AI Architect,102804,USD,102804,EX,FL,China,M,China,100,"Computer Vision, Azure, MLOps, NLP",PhD,11,Government,2024-09-17,2024-11-15,1482,5.7,TechCorp Inc +AI03370,AI Architect,124994,EUR,106245,SE,CT,Netherlands,L,Ukraine,50,"Python, Spark, Tableau",Associate,9,Manufacturing,2024-03-11,2024-05-17,867,7.6,Neural Networks Co +AI03371,Autonomous Systems Engineer,48674,USD,48674,SE,FT,India,M,Ukraine,100,"Scala, NLP, TensorFlow, Java, Git",Associate,9,Technology,2025-02-14,2025-03-07,2390,8.8,DataVision Ltd +AI03372,Autonomous Systems Engineer,83060,GBP,62295,EN,FT,United Kingdom,M,United Kingdom,50,"Scala, Hadoop, Azure, Java",Associate,0,Manufacturing,2025-04-08,2025-04-26,920,5.2,Algorithmic Solutions +AI03373,Computer Vision Engineer,116877,SGD,151940,MI,PT,Singapore,L,Singapore,0,"Mathematics, Spark, PyTorch, Java, SQL",Master,2,Healthcare,2024-12-22,2025-02-21,1090,9.4,AI Innovations +AI03374,AI Consultant,49966,USD,49966,SE,CT,India,M,India,100,"AWS, Git, NLP, Spark",Associate,5,Consulting,2024-10-23,2024-12-03,2239,5.7,DataVision Ltd +AI03375,Machine Learning Engineer,109823,USD,109823,SE,CT,Ireland,S,France,0,"Azure, Linux, Data Visualization, Tableau",Associate,7,Real Estate,2024-09-09,2024-09-27,590,6.4,Digital Transformation LLC +AI03376,Computer Vision Engineer,89964,EUR,76469,MI,CT,Netherlands,M,Romania,100,"Java, GCP, Mathematics",Master,2,Energy,2024-03-26,2024-04-28,1914,7.8,Cloud AI Solutions +AI03377,NLP Engineer,99897,CHF,89907,EN,CT,Switzerland,S,Switzerland,0,"Tableau, SQL, Linux",Associate,1,Energy,2025-02-17,2025-04-16,501,5.5,TechCorp Inc +AI03378,AI Product Manager,112037,CHF,100833,EN,FT,Switzerland,M,Switzerland,0,"AWS, SQL, R, Computer Vision",Associate,1,Telecommunications,2024-02-13,2024-04-04,1799,5.3,DataVision Ltd +AI03379,Robotics Engineer,97555,USD,97555,MI,FL,Sweden,S,Ireland,0,"Deep Learning, AWS, Mathematics, Python",Bachelor,3,Education,2024-07-18,2024-08-05,1520,9.7,Autonomous Tech +AI03380,Deep Learning Engineer,51067,USD,51067,MI,FT,China,L,China,0,"AWS, Kubernetes, R",Bachelor,2,Real Estate,2024-09-29,2024-11-29,705,8.4,Quantum Computing Inc +AI03381,AI Software Engineer,74645,AUD,100771,EN,PT,Australia,M,Australia,50,"Kubernetes, Python, Data Visualization, Statistics, Deep Learning",Master,1,Government,2024-03-18,2024-05-12,652,8.5,Predictive Systems +AI03382,ML Ops Engineer,73008,JPY,8030880,MI,CT,Japan,S,Japan,50,"Java, Kubernetes, Azure",Master,3,Finance,2024-10-18,2024-12-14,1485,8.2,AI Innovations +AI03383,Autonomous Systems Engineer,31006,USD,31006,EN,FT,China,S,China,100,"Python, Data Visualization, Linux, MLOps",PhD,0,Government,2024-06-08,2024-07-24,1097,9.2,Machine Intelligence Group +AI03384,Data Scientist,101583,USD,101583,SE,PT,South Korea,S,Canada,0,"Python, Scala, Hadoop, AWS",Master,9,Government,2024-07-29,2024-09-02,1325,6.1,Smart Analytics +AI03385,Computer Vision Engineer,90261,USD,90261,MI,CT,Sweden,M,Romania,0,"Tableau, Kubernetes, Scala, AWS, Git",Associate,4,Retail,2024-07-08,2024-07-23,1414,6.5,Future Systems +AI03386,AI Product Manager,111512,GBP,83634,MI,FL,United Kingdom,M,Latvia,0,"Statistics, NLP, Linux, Kubernetes, Hadoop",Bachelor,2,Media,2024-05-26,2024-06-15,1256,6.6,Smart Analytics +AI03387,AI Software Engineer,135059,JPY,14856490,SE,PT,Japan,M,South Africa,0,"PyTorch, Computer Vision, Scala, Azure, Linux",PhD,8,Telecommunications,2024-06-01,2024-08-02,1857,8.1,DataVision Ltd +AI03388,AI Architect,188799,USD,188799,EX,CT,Denmark,S,Denmark,50,"Tableau, Docker, NLP, Kubernetes",Associate,13,Real Estate,2024-03-28,2024-04-14,953,9.3,Autonomous Tech +AI03389,Data Scientist,133225,USD,133225,SE,FL,Ireland,S,Ireland,50,"PyTorch, Spark, Docker",PhD,5,Telecommunications,2024-08-27,2024-09-18,573,7,Smart Analytics +AI03390,Autonomous Systems Engineer,60400,USD,60400,SE,FL,China,S,China,0,"Computer Vision, Git, Python",Bachelor,5,Healthcare,2024-12-11,2025-01-06,1043,5.6,DeepTech Ventures +AI03391,Data Scientist,114422,USD,114422,SE,FT,Ireland,M,Ireland,100,"Azure, Linux, Mathematics, Data Visualization",Bachelor,7,Real Estate,2024-06-22,2024-08-11,2321,5.9,Cognitive Computing +AI03392,Research Scientist,85322,USD,85322,EN,CT,Denmark,S,Denmark,100,"Kubernetes, Scala, Mathematics, Azure",Bachelor,1,Healthcare,2024-10-28,2024-12-19,2265,5.8,AI Innovations +AI03393,Head of AI,64462,EUR,54793,MI,FL,Austria,S,Colombia,0,"Scala, PyTorch, TensorFlow, NLP",Master,4,Gaming,2024-04-17,2024-05-24,640,7.8,DataVision Ltd +AI03394,Deep Learning Engineer,214640,CAD,268300,EX,CT,Canada,M,Canada,100,"PyTorch, Kubernetes, GCP, Statistics, AWS",Bachelor,13,Media,2025-01-01,2025-02-04,708,8.6,Algorithmic Solutions +AI03395,NLP Engineer,160700,USD,160700,EX,FT,Israel,M,Israel,100,"Spark, GCP, Scala",Bachelor,18,Consulting,2025-04-15,2025-05-22,1966,6.4,Digital Transformation LLC +AI03396,Machine Learning Researcher,114986,CAD,143733,SE,CT,Canada,S,Israel,0,"AWS, Kubernetes, Azure",PhD,9,Automotive,2024-05-31,2024-08-05,1103,9.5,Predictive Systems +AI03397,Robotics Engineer,160285,GBP,120214,SE,PT,United Kingdom,M,Ireland,50,"Kubernetes, Computer Vision, Python, Git, Mathematics",Master,9,Technology,2025-01-12,2025-03-09,1719,5.4,Digital Transformation LLC +AI03398,ML Ops Engineer,184764,AUD,249431,EX,FT,Australia,L,Argentina,100,"Kubernetes, Python, Scala, Git, TensorFlow",Master,17,Media,2024-07-16,2024-08-18,2153,5.3,Advanced Robotics +AI03399,Deep Learning Engineer,168868,CHF,151981,MI,FL,Switzerland,L,Switzerland,50,"Kubernetes, Deep Learning, Data Visualization",Bachelor,3,Technology,2025-04-12,2025-06-17,2054,7.7,Neural Networks Co +AI03400,AI Architect,59852,GBP,44889,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Tableau, Linux, Scala, Deep Learning",PhD,1,Manufacturing,2025-01-21,2025-04-02,1905,8.8,Quantum Computing Inc +AI03401,Computer Vision Engineer,127118,EUR,108050,SE,CT,Austria,S,France,100,"Spark, Statistics, AWS, GCP, Scala",PhD,6,Technology,2024-10-16,2024-11-04,610,6.6,Quantum Computing Inc +AI03402,Machine Learning Engineer,62015,USD,62015,EN,FL,Sweden,L,Sweden,50,"GCP, SQL, Deep Learning, Python",PhD,1,Consulting,2024-04-17,2024-05-12,1071,9.3,Future Systems +AI03403,AI Software Engineer,70434,EUR,59869,EN,FL,Austria,L,Austria,50,"Python, Spark, Git, Deep Learning, Tableau",Master,1,Telecommunications,2024-04-18,2024-05-13,2274,6.7,AI Innovations +AI03404,AI Software Engineer,102013,USD,102013,EX,PT,South Korea,S,South Korea,0,"Linux, AWS, R",Associate,17,Transportation,2025-04-06,2025-06-04,2244,7.6,AI Innovations +AI03405,AI Architect,178561,USD,178561,EX,CT,Finland,L,Philippines,50,"Data Visualization, Linux, Git, PyTorch",PhD,19,Education,2024-01-23,2024-03-13,651,8,DeepTech Ventures +AI03406,Head of AI,63698,USD,63698,EN,FL,South Korea,L,Kenya,100,"Linux, Python, TensorFlow, MLOps",Bachelor,0,Automotive,2024-02-15,2024-04-14,1653,6.8,Smart Analytics +AI03407,NLP Engineer,70117,USD,70117,EN,CT,Sweden,M,Ukraine,50,"SQL, Data Visualization, Scala, Computer Vision, Azure",Master,0,Real Estate,2024-10-05,2024-12-03,2200,6,Quantum Computing Inc +AI03408,AI Specialist,125886,USD,125886,SE,CT,Israel,L,Ukraine,0,"PyTorch, MLOps, TensorFlow, SQL, Computer Vision",Associate,5,Automotive,2024-10-15,2024-10-31,923,5.9,AI Innovations +AI03409,Head of AI,143263,EUR,121774,SE,CT,Germany,L,Germany,100,"Data Visualization, NLP, Java, PyTorch",PhD,9,Gaming,2024-06-28,2024-08-03,1811,8.7,Quantum Computing Inc +AI03410,Autonomous Systems Engineer,61495,USD,61495,MI,CT,South Korea,S,South Korea,100,"AWS, Hadoop, Mathematics",PhD,4,Finance,2024-12-27,2025-02-24,2423,8.6,Machine Intelligence Group +AI03411,Robotics Engineer,275523,USD,275523,EX,CT,Norway,S,Netherlands,0,"NLP, Scala, Hadoop, Data Visualization",PhD,17,Technology,2024-08-19,2024-09-16,891,8.9,AI Innovations +AI03412,Data Engineer,65593,EUR,55754,EN,CT,France,M,France,100,"Deep Learning, Data Visualization, PyTorch, Kubernetes, Tableau",Master,1,Telecommunications,2024-02-29,2024-04-26,1617,6.2,DataVision Ltd +AI03413,Robotics Engineer,63298,USD,63298,EN,FT,United States,S,United States,50,"Hadoop, Python, TensorFlow, PyTorch, Statistics",PhD,0,Manufacturing,2025-04-30,2025-06-25,1610,9.9,Predictive Systems +AI03414,AI Software Engineer,70299,EUR,59754,MI,PT,France,M,France,100,"SQL, PyTorch, TensorFlow",Bachelor,2,Energy,2025-01-19,2025-02-16,2016,8.4,Cloud AI Solutions +AI03415,Machine Learning Engineer,202655,SGD,263452,EX,FL,Singapore,M,Singapore,0,"Linux, Hadoop, Git",Bachelor,12,Energy,2024-02-17,2024-03-27,2364,8,Quantum Computing Inc +AI03416,AI Specialist,256495,USD,256495,EX,PT,Norway,L,Norway,0,"Python, TensorFlow, Hadoop, Java",Bachelor,13,Transportation,2024-03-08,2024-04-05,1154,8.7,Neural Networks Co +AI03417,AI Product Manager,84934,AUD,114661,EN,PT,Australia,L,Australia,100,"Spark, Linux, R",Master,0,Energy,2024-10-06,2024-11-06,1062,8.9,Smart Analytics +AI03418,Research Scientist,83381,EUR,70874,MI,FL,Germany,S,Germany,100,"Git, Python, TensorFlow, NLP",Bachelor,3,Real Estate,2024-04-20,2024-06-07,1342,9.7,Algorithmic Solutions +AI03419,Data Analyst,26293,USD,26293,EN,FT,India,M,India,50,"PyTorch, SQL, AWS",Bachelor,1,Technology,2025-03-19,2025-05-12,2348,6.2,DataVision Ltd +AI03420,Head of AI,114838,USD,114838,SE,CT,Sweden,S,Sweden,50,"NLP, Python, Computer Vision, R, Deep Learning",Associate,9,Automotive,2025-01-11,2025-02-14,1472,7.1,Smart Analytics +AI03421,AI Specialist,130423,AUD,176071,SE,PT,Australia,S,Australia,0,"Python, Git, TensorFlow",PhD,9,Automotive,2024-11-09,2024-12-22,1640,8.3,Smart Analytics +AI03422,Head of AI,73362,USD,73362,MI,CT,Israel,S,Romania,0,"Python, Data Visualization, TensorFlow",Associate,4,Energy,2024-04-11,2024-06-13,1395,9.4,Algorithmic Solutions +AI03423,Research Scientist,55846,USD,55846,MI,FL,China,L,Sweden,100,"Tableau, Python, Statistics",Master,2,Media,2024-08-15,2024-09-01,1702,7.3,TechCorp Inc +AI03424,AI Product Manager,216173,USD,216173,EX,FT,South Korea,L,Hungary,50,"Python, Git, TensorFlow, Linux",Associate,17,Automotive,2024-04-19,2024-06-07,2275,8.4,Autonomous Tech +AI03425,Data Engineer,184151,GBP,138113,EX,FT,United Kingdom,M,United Kingdom,0,"Python, Docker, Tableau, GCP",Associate,12,Energy,2024-05-11,2024-06-28,957,8.4,Smart Analytics +AI03426,AI Product Manager,109524,CAD,136905,MI,FL,Canada,L,Canada,0,"PyTorch, Hadoop, MLOps, Kubernetes, Linux",PhD,4,Telecommunications,2024-03-27,2024-05-01,1174,8,AI Innovations +AI03427,Research Scientist,83789,USD,83789,EN,FT,United States,M,Colombia,0,"Python, MLOps, SQL, NLP",PhD,0,Healthcare,2025-01-15,2025-02-13,2307,6.7,Digital Transformation LLC +AI03428,Computer Vision Engineer,163508,USD,163508,EX,PT,South Korea,S,South Korea,0,"Scala, R, Deep Learning, Azure",PhD,17,Energy,2025-02-22,2025-04-15,1992,7.7,Smart Analytics +AI03429,Principal Data Scientist,159674,CHF,143707,MI,CT,Switzerland,L,Switzerland,100,"Scala, SQL, Python, Tableau",Master,2,Retail,2024-05-08,2024-06-06,888,8.1,Autonomous Tech +AI03430,Machine Learning Engineer,72337,USD,72337,EN,FL,Norway,S,Finland,50,"Git, Spark, Docker, TensorFlow, Linux",Master,0,Technology,2024-08-23,2024-10-25,598,9.8,Smart Analytics +AI03431,AI Research Scientist,168105,EUR,142889,EX,CT,Germany,L,Germany,100,"Kubernetes, Scala, Python",PhD,10,Telecommunications,2024-01-12,2024-01-27,1693,8.2,Algorithmic Solutions +AI03432,Data Scientist,157793,USD,157793,SE,PT,United States,L,India,0,"Docker, SQL, Computer Vision, Java",Bachelor,7,Telecommunications,2024-01-20,2024-03-09,2041,8.3,Quantum Computing Inc +AI03433,Machine Learning Engineer,186928,USD,186928,SE,FL,Norway,L,Chile,100,"Computer Vision, Python, Kubernetes, AWS",Master,9,Retail,2024-11-01,2024-11-24,1184,5.4,AI Innovations +AI03434,AI Specialist,97344,USD,97344,MI,PT,Ireland,S,Philippines,0,"Docker, Python, Computer Vision",Bachelor,2,Finance,2024-12-02,2025-01-18,1143,6.9,Cognitive Computing +AI03435,AI Product Manager,47190,EUR,40112,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, GCP, AWS, Deep Learning",Associate,0,Finance,2024-12-16,2025-01-04,539,9.7,Neural Networks Co +AI03436,Data Scientist,64670,CAD,80838,EN,PT,Canada,M,Canada,50,"Git, Azure, SQL, Mathematics",PhD,1,Consulting,2024-10-04,2024-11-24,1319,6.8,Machine Intelligence Group +AI03437,AI Architect,126076,USD,126076,SE,CT,Finland,S,Finland,50,"Data Visualization, Python, Linux, Statistics, TensorFlow",PhD,8,Media,2024-05-14,2024-07-22,2017,9.8,Predictive Systems +AI03438,Principal Data Scientist,98433,AUD,132885,MI,CT,Australia,M,Australia,50,"Linux, PyTorch, AWS, Deep Learning, MLOps",Master,2,Media,2024-02-10,2024-04-15,2422,9,Machine Intelligence Group +AI03439,Robotics Engineer,31915,USD,31915,EN,CT,China,L,China,100,"Statistics, Spark, Kubernetes, R, SQL",Bachelor,0,Gaming,2024-08-31,2024-10-07,1804,9.6,Neural Networks Co +AI03440,Data Scientist,175657,USD,175657,SE,PT,Norway,S,Norway,100,"Data Visualization, Spark, MLOps",Bachelor,5,Government,2024-10-07,2024-11-29,1903,9.8,Digital Transformation LLC +AI03441,Deep Learning Engineer,200463,USD,200463,EX,FL,Israel,M,Israel,0,"Scala, Hadoop, Deep Learning, AWS",PhD,19,Media,2024-10-17,2024-12-16,885,5,Quantum Computing Inc +AI03442,Robotics Engineer,109629,USD,109629,SE,CT,South Korea,S,Poland,100,"MLOps, Kubernetes, GCP",Associate,6,Finance,2024-04-12,2024-05-19,811,6.7,DataVision Ltd +AI03443,NLP Engineer,80126,USD,80126,EN,FT,Finland,L,Australia,100,"AWS, Tableau, Linux, Data Visualization",Master,0,Automotive,2024-01-31,2024-02-14,1963,6.2,Future Systems +AI03444,Machine Learning Engineer,91862,GBP,68897,EN,FT,United Kingdom,L,Malaysia,100,"TensorFlow, NLP, Git",PhD,0,Healthcare,2024-07-10,2024-09-02,2134,6.2,DeepTech Ventures +AI03445,Data Scientist,102655,JPY,11292050,MI,CT,Japan,L,Canada,50,"Kubernetes, R, PyTorch, GCP, Java",Master,4,Retail,2025-01-12,2025-02-01,864,6.5,Cloud AI Solutions +AI03446,Data Scientist,147186,AUD,198701,SE,CT,Australia,M,Chile,50,"TensorFlow, Mathematics, Kubernetes, SQL, Statistics",PhD,5,Telecommunications,2025-04-26,2025-06-18,983,7.4,DataVision Ltd +AI03447,Research Scientist,184149,USD,184149,EX,FT,Ireland,S,Ireland,0,"GCP, SQL, Data Visualization, Mathematics",Bachelor,14,Automotive,2024-03-31,2024-04-26,645,6.8,Digital Transformation LLC +AI03448,Computer Vision Engineer,273048,USD,273048,EX,FL,Norway,M,Germany,50,"Python, Mathematics, Data Visualization, Computer Vision",Master,16,Energy,2024-12-15,2024-12-30,892,6.2,Cloud AI Solutions +AI03449,NLP Engineer,105192,GBP,78894,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, TensorFlow, Hadoop, Linux",Master,2,Media,2024-05-21,2024-06-27,845,5.2,DataVision Ltd +AI03450,Deep Learning Engineer,37406,USD,37406,MI,PT,India,M,India,0,"Git, Java, Linux, Python",Master,4,Education,2024-01-27,2024-03-01,1756,6.8,DataVision Ltd +AI03451,AI Specialist,27619,USD,27619,EN,FT,India,M,India,0,"Tableau, Python, R, Kubernetes",Bachelor,0,Government,2024-08-10,2024-10-11,570,8.8,Smart Analytics +AI03452,Machine Learning Researcher,94921,USD,94921,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Spark, Docker",PhD,8,Media,2024-04-04,2024-06-12,2257,5.4,Quantum Computing Inc +AI03453,Data Scientist,199186,USD,199186,EX,FT,Israel,M,Israel,0,"Docker, Kubernetes, Hadoop, Java",Master,13,Automotive,2024-05-26,2024-07-02,2222,9.8,Neural Networks Co +AI03454,ML Ops Engineer,118265,SGD,153745,SE,PT,Singapore,M,Belgium,50,"Kubernetes, R, PyTorch, Git",PhD,8,Energy,2024-08-31,2024-11-01,1950,7.6,Advanced Robotics +AI03455,Computer Vision Engineer,75240,SGD,97812,EN,CT,Singapore,L,Kenya,100,"Azure, Kubernetes, NLP, Computer Vision",Bachelor,1,Technology,2024-05-15,2024-06-30,826,9.8,AI Innovations +AI03456,Research Scientist,65569,USD,65569,EN,FL,Israel,M,Switzerland,50,"GCP, Java, MLOps",PhD,1,Gaming,2024-04-16,2024-06-20,2302,6.3,Predictive Systems +AI03457,Data Scientist,205247,USD,205247,EX,FL,Denmark,S,Denmark,0,"Docker, Kubernetes, Git, SQL",PhD,17,Real Estate,2024-01-16,2024-03-22,1888,7.3,Digital Transformation LLC +AI03458,Data Scientist,37999,USD,37999,MI,CT,India,L,India,100,"Statistics, GCP, MLOps",PhD,4,Government,2024-12-20,2025-01-20,1159,6.2,Quantum Computing Inc +AI03459,Data Engineer,136750,JPY,15042500,SE,CT,Japan,M,Japan,100,"Tableau, Linux, TensorFlow, MLOps",Associate,7,Consulting,2024-03-17,2024-04-10,939,6.6,Neural Networks Co +AI03460,AI Product Manager,55482,USD,55482,EN,FL,Finland,M,Finland,100,"Python, Data Visualization, TensorFlow, Deep Learning",Associate,1,Consulting,2025-02-28,2025-04-05,2469,7.1,DeepTech Ventures +AI03461,Principal Data Scientist,126580,AUD,170883,MI,CT,Australia,L,Australia,0,"Data Visualization, GCP, Computer Vision, Kubernetes",Bachelor,2,Consulting,2025-04-24,2025-06-07,1369,5.4,AI Innovations +AI03462,Deep Learning Engineer,45523,USD,45523,MI,PT,China,L,Switzerland,0,"Spark, GCP, Hadoop, SQL",PhD,2,Retail,2024-08-11,2024-10-17,733,7.2,Future Systems +AI03463,Computer Vision Engineer,69117,USD,69117,MI,PT,Finland,S,New Zealand,0,"Deep Learning, AWS, Docker",Master,4,Finance,2025-03-02,2025-03-30,1948,9.6,Algorithmic Solutions +AI03464,Robotics Engineer,147154,USD,147154,MI,PT,United States,L,United States,0,"MLOps, Scala, SQL, PyTorch, NLP",Master,3,Education,2025-03-07,2025-04-23,1786,8.8,Advanced Robotics +AI03465,Computer Vision Engineer,129411,EUR,109999,SE,CT,Germany,M,Germany,0,"Azure, SQL, NLP, Deep Learning",Associate,6,Retail,2024-04-02,2024-04-25,2001,7.2,Cloud AI Solutions +AI03466,NLP Engineer,103365,AUD,139543,SE,CT,Australia,S,Australia,0,"Hadoop, Statistics, GCP, MLOps, Spark",PhD,7,Education,2024-07-17,2024-09-21,1363,7.2,TechCorp Inc +AI03467,Machine Learning Researcher,155656,USD,155656,SE,FL,United States,L,United States,50,"Deep Learning, R, PyTorch, Docker, Linux",Master,8,Transportation,2025-02-23,2025-03-28,2452,7.1,Cloud AI Solutions +AI03468,Deep Learning Engineer,60372,EUR,51316,EN,PT,Netherlands,M,Netherlands,100,"SQL, GCP, Java",Bachelor,1,Gaming,2024-01-14,2024-02-19,1363,7.7,TechCorp Inc +AI03469,Machine Learning Engineer,90624,EUR,77030,SE,FT,Austria,S,Spain,50,"GCP, Hadoop, PyTorch",Associate,8,Retail,2025-02-24,2025-04-08,655,8.9,Autonomous Tech +AI03470,Principal Data Scientist,28839,USD,28839,EN,CT,China,S,Estonia,50,"Scala, Python, SQL",Master,1,Real Estate,2024-08-20,2024-10-18,1826,10,Cognitive Computing +AI03471,Data Analyst,95397,EUR,81087,MI,FT,Germany,S,Germany,50,"Deep Learning, R, Spark",Bachelor,3,Healthcare,2024-02-06,2024-02-21,705,5.3,DataVision Ltd +AI03472,ML Ops Engineer,265922,JPY,29251420,EX,CT,Japan,L,United States,0,"GCP, Tableau, AWS, SQL",Associate,16,Energy,2024-03-16,2024-05-01,1345,5.6,Predictive Systems +AI03473,NLP Engineer,123952,CHF,111557,MI,CT,Switzerland,M,Switzerland,50,"PyTorch, Java, Git, Computer Vision",Bachelor,2,Automotive,2024-05-14,2024-06-20,713,8.8,Cloud AI Solutions +AI03474,Data Scientist,243390,EUR,206882,EX,FT,Germany,M,Indonesia,100,"Linux, PyTorch, Tableau, Java, Git",Bachelor,12,Automotive,2024-12-01,2024-12-31,1715,9,Cognitive Computing +AI03475,Autonomous Systems Engineer,86886,JPY,9557460,MI,FT,Japan,M,Poland,100,"Kubernetes, Tableau, Azure, NLP, Python",Associate,2,Energy,2024-12-23,2025-02-26,1947,8.7,Machine Intelligence Group +AI03476,Machine Learning Researcher,86470,CHF,77823,EN,FT,Switzerland,S,Switzerland,0,"Python, Java, GCP, NLP",PhD,1,Education,2024-11-30,2024-12-14,1713,6.3,Cloud AI Solutions +AI03477,Principal Data Scientist,128696,EUR,109392,SE,PT,France,L,Malaysia,0,"Git, Linux, Data Visualization, PyTorch",Associate,6,Energy,2024-10-05,2024-11-14,1015,6.2,Autonomous Tech +AI03478,Data Analyst,108456,USD,108456,MI,CT,United States,L,United States,0,"TensorFlow, Deep Learning, Kubernetes, Python",Bachelor,2,Retail,2024-05-19,2024-07-04,1400,5.5,Machine Intelligence Group +AI03479,Data Engineer,114242,USD,114242,SE,FT,Ireland,M,Ireland,0,"Statistics, R, Scala",Master,9,Retail,2024-08-03,2024-09-22,2189,6.4,Smart Analytics +AI03480,Data Engineer,94224,USD,94224,MI,CT,Finland,L,Finland,0,"Spark, Scala, Computer Vision, Mathematics",PhD,2,Technology,2024-10-10,2024-12-14,540,9.2,TechCorp Inc +AI03481,Data Engineer,277483,SGD,360728,EX,FL,Singapore,L,Singapore,50,"MLOps, Spark, Data Visualization, Hadoop",Bachelor,19,Finance,2024-07-30,2024-09-09,770,9.7,Cognitive Computing +AI03482,Computer Vision Engineer,40704,USD,40704,MI,FT,China,M,China,50,"NLP, PyTorch, Tableau, Git, Docker",PhD,2,Media,2024-03-06,2024-05-10,795,6.8,TechCorp Inc +AI03483,Machine Learning Engineer,93238,EUR,79252,EN,CT,Netherlands,L,Portugal,100,"AWS, Statistics, Hadoop",PhD,1,Finance,2024-03-20,2024-05-24,2049,7.8,DeepTech Ventures +AI03484,Machine Learning Researcher,196588,CHF,176929,SE,FT,Switzerland,M,Estonia,0,"Data Visualization, Docker, R",Associate,9,Energy,2024-07-03,2024-09-04,1947,7.5,Autonomous Tech +AI03485,AI Software Engineer,90440,GBP,67830,MI,PT,United Kingdom,M,United Kingdom,50,"PyTorch, AWS, Computer Vision, NLP, GCP",Master,2,Energy,2025-03-19,2025-04-30,2326,6.6,Neural Networks Co +AI03486,AI Consultant,150604,USD,150604,MI,FT,Denmark,L,India,100,"Hadoop, Mathematics, GCP, Kubernetes, MLOps",Associate,2,Gaming,2024-09-03,2024-09-26,762,6.4,Advanced Robotics +AI03487,ML Ops Engineer,58876,USD,58876,SE,PT,India,L,India,0,"MLOps, GCP, SQL",Master,8,Government,2024-11-02,2025-01-02,730,6.3,AI Innovations +AI03488,AI Product Manager,28266,USD,28266,MI,CT,India,S,India,100,"NLP, Data Visualization, Tableau, Mathematics, MLOps",Master,2,Telecommunications,2025-01-26,2025-03-18,901,9.2,TechCorp Inc +AI03489,Research Scientist,83652,CAD,104565,MI,FL,Canada,M,Nigeria,100,"Azure, Tableau, Linux, AWS, Docker",Master,3,Energy,2025-02-01,2025-03-14,2027,6,AI Innovations +AI03490,AI Specialist,69368,USD,69368,EN,FT,Norway,S,Israel,50,"Spark, Python, Git, Azure",Associate,1,Manufacturing,2024-05-16,2024-06-08,1302,7.8,Autonomous Tech +AI03491,Head of AI,130656,USD,130656,SE,PT,Israel,L,Israel,50,"SQL, Mathematics, TensorFlow",PhD,9,Government,2025-02-21,2025-04-01,1038,5.4,Autonomous Tech +AI03492,AI Architect,168459,EUR,143190,SE,PT,Germany,L,Germany,0,"Spark, Hadoop, Scala, MLOps, R",Associate,6,Telecommunications,2024-04-07,2024-04-22,2246,7.9,Advanced Robotics +AI03493,Data Scientist,72394,AUD,97732,MI,CT,Australia,S,Ghana,100,"Deep Learning, GCP, SQL, Python",Master,4,Technology,2024-08-06,2024-08-28,882,6.4,Predictive Systems +AI03494,Principal Data Scientist,37641,USD,37641,MI,FL,India,M,India,0,"Python, Hadoop, SQL, Git, AWS",Master,2,Technology,2025-01-16,2025-03-08,897,5.7,Smart Analytics +AI03495,Deep Learning Engineer,109311,USD,109311,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Hadoop, Python, Linux",Bachelor,2,Government,2024-09-13,2024-11-21,2222,6.1,Algorithmic Solutions +AI03496,Machine Learning Engineer,237727,USD,237727,EX,FL,Denmark,M,Austria,50,"Python, NLP, Data Visualization",Bachelor,16,Telecommunications,2024-03-15,2024-05-25,728,7.3,Advanced Robotics +AI03497,AI Consultant,138467,USD,138467,EX,FT,Sweden,M,Sweden,0,"Python, Hadoop, SQL, Computer Vision",Associate,19,Technology,2024-07-21,2024-08-08,612,10,Digital Transformation LLC +AI03498,Head of AI,125705,EUR,106849,SE,FL,France,M,France,100,"PyTorch, Python, Scala",Bachelor,9,Energy,2024-11-06,2024-12-03,2098,8.1,AI Innovations +AI03499,ML Ops Engineer,107784,USD,107784,MI,PT,Norway,L,Norway,0,"SQL, Statistics, Data Visualization, Python, Mathematics",Bachelor,4,Technology,2024-07-07,2024-09-17,1589,5.9,TechCorp Inc +AI03500,Computer Vision Engineer,49527,USD,49527,SE,CT,India,M,India,0,"Python, Scala, AWS",Master,6,Media,2024-11-03,2025-01-11,1906,9.6,Advanced Robotics +AI03501,AI Software Engineer,73779,JPY,8115690,EN,PT,Japan,S,Poland,0,"Python, Azure, Statistics",Bachelor,1,Transportation,2024-07-05,2024-08-26,1183,10,Digital Transformation LLC +AI03502,AI Consultant,98422,USD,98422,MI,FL,United States,L,United States,50,"SQL, GCP, Statistics, Hadoop, Linux",PhD,3,Real Estate,2024-06-18,2024-07-16,2175,5.9,Algorithmic Solutions +AI03503,Principal Data Scientist,110310,SGD,143403,MI,PT,Singapore,L,Singapore,100,"PyTorch, Deep Learning, Spark",Associate,4,Retail,2025-02-28,2025-03-27,1821,6.7,Future Systems +AI03504,ML Ops Engineer,167443,EUR,142327,EX,FL,Austria,M,Austria,50,"R, Scala, NLP",Master,19,Transportation,2024-12-25,2025-01-21,2422,6.3,Cloud AI Solutions +AI03505,Machine Learning Engineer,135296,SGD,175885,SE,FT,Singapore,S,Singapore,0,"Spark, Kubernetes, Computer Vision",Associate,7,Media,2024-02-18,2024-03-07,2274,9.6,TechCorp Inc +AI03506,Data Scientist,101322,SGD,131719,MI,CT,Singapore,L,Singapore,100,"TensorFlow, Data Visualization, Git",Master,4,Technology,2024-10-30,2024-11-16,1477,9,AI Innovations +AI03507,AI Consultant,81204,AUD,109625,MI,FL,Australia,S,Australia,100,"Python, Hadoop, Linux, NLP, Statistics",PhD,2,Education,2024-01-07,2024-01-30,2214,5.5,DataVision Ltd +AI03508,Machine Learning Engineer,216778,USD,216778,EX,CT,United States,M,United States,100,"AWS, Azure, MLOps",Bachelor,12,Consulting,2024-06-22,2024-07-24,2366,6.3,DeepTech Ventures +AI03509,Computer Vision Engineer,176928,AUD,238853,EX,FL,Australia,M,Australia,100,"GCP, Git, Hadoop",PhD,14,Real Estate,2024-11-29,2025-01-15,1015,5.7,Neural Networks Co +AI03510,Research Scientist,76676,USD,76676,SE,PT,South Korea,S,Russia,0,"Java, SQL, MLOps, Mathematics, Hadoop",PhD,7,Retail,2024-05-27,2024-07-09,2390,9.1,Smart Analytics +AI03511,Data Analyst,167099,USD,167099,SE,PT,United States,L,United States,0,"R, Git, MLOps",PhD,7,Energy,2024-07-03,2024-07-30,720,8.7,Cognitive Computing +AI03512,ML Ops Engineer,89898,USD,89898,SE,CT,South Korea,M,South Korea,50,"SQL, Azure, Scala, MLOps, Python",Master,5,Transportation,2025-03-11,2025-03-30,1286,6,Quantum Computing Inc +AI03513,Robotics Engineer,123146,USD,123146,SE,PT,South Korea,M,South Korea,50,"Spark, Python, Linux, Statistics, Tableau",Master,9,Technology,2024-03-25,2024-05-03,1632,8,Predictive Systems +AI03514,ML Ops Engineer,244148,USD,244148,EX,FT,Denmark,L,Australia,50,"AWS, Python, TensorFlow, PyTorch, Scala",PhD,16,Transportation,2024-12-29,2025-01-14,1215,8.8,AI Innovations +AI03515,Machine Learning Researcher,212784,CHF,191506,EX,FT,Switzerland,S,Switzerland,50,"NLP, Linux, Python, R, TensorFlow",Bachelor,14,Manufacturing,2025-02-25,2025-04-06,689,9.1,Predictive Systems +AI03516,Principal Data Scientist,206443,AUD,278698,EX,PT,Australia,M,Australia,0,"Python, Kubernetes, GCP",Master,15,Gaming,2024-04-27,2024-06-19,2094,7.6,Future Systems +AI03517,ML Ops Engineer,55944,JPY,6153840,EN,FT,Japan,M,Japan,50,"MLOps, Java, R",Bachelor,0,Technology,2024-04-28,2024-05-26,1744,9.3,Machine Intelligence Group +AI03518,Autonomous Systems Engineer,71392,USD,71392,EN,FL,Sweden,S,Sweden,50,"Linux, Statistics, SQL, Git, Mathematics",Bachelor,1,Gaming,2024-05-05,2024-06-28,1567,8.5,Cloud AI Solutions +AI03519,Principal Data Scientist,126751,CAD,158439,SE,PT,Canada,M,Latvia,0,"Git, Java, R, GCP, SQL",Master,8,Technology,2025-01-24,2025-02-23,1506,7.2,Predictive Systems +AI03520,AI Specialist,99185,USD,99185,SE,CT,Finland,M,Finland,50,"GCP, Python, Linux, SQL",Bachelor,5,Retail,2024-01-20,2024-03-13,599,9.6,Cognitive Computing +AI03521,Machine Learning Engineer,218350,AUD,294773,EX,CT,Australia,S,Australia,0,"PyTorch, Tableau, TensorFlow",Master,16,Media,2024-10-28,2024-12-03,909,8.7,Algorithmic Solutions +AI03522,Principal Data Scientist,123624,SGD,160711,MI,PT,Singapore,L,Singapore,100,"PyTorch, Scala, Computer Vision, Spark",Associate,3,Automotive,2024-08-25,2024-09-25,1195,9.5,Cloud AI Solutions +AI03523,AI Research Scientist,150816,USD,150816,EX,PT,Ireland,S,Nigeria,50,"Python, AWS, Computer Vision, Docker, Data Visualization",PhD,18,Technology,2024-10-24,2024-12-09,1118,6.4,TechCorp Inc +AI03524,Computer Vision Engineer,248052,CAD,310065,EX,PT,Canada,L,Canada,0,"Docker, Scala, Data Visualization, Azure, Spark",Master,15,Real Estate,2024-08-08,2024-09-20,1640,6,Predictive Systems +AI03525,Research Scientist,174068,SGD,226288,SE,CT,Singapore,L,Singapore,100,"Mathematics, PyTorch, TensorFlow",Associate,9,Transportation,2024-12-06,2024-12-21,1050,8.7,Smart Analytics +AI03526,Data Analyst,202119,USD,202119,EX,CT,South Korea,L,South Korea,50,"NLP, Python, Spark, TensorFlow",Bachelor,13,Transportation,2024-07-08,2024-08-24,1755,6.6,Cloud AI Solutions +AI03527,AI Research Scientist,52293,USD,52293,EX,CT,India,M,India,50,"AWS, Docker, Statistics",Associate,10,Real Estate,2024-05-25,2024-07-01,2424,5.9,Quantum Computing Inc +AI03528,Machine Learning Researcher,127194,EUR,108115,EX,FL,France,S,France,100,"PyTorch, Docker, TensorFlow, Deep Learning",Associate,10,Real Estate,2024-01-05,2024-03-05,853,7.6,Neural Networks Co +AI03529,Machine Learning Researcher,133885,USD,133885,MI,FT,United States,L,United States,100,"Hadoop, Spark, Tableau",PhD,3,Automotive,2025-01-28,2025-02-23,1070,8.6,Digital Transformation LLC +AI03530,AI Software Engineer,134073,EUR,113962,SE,CT,France,M,France,0,"Hadoop, MLOps, Linux, Spark",Associate,9,Automotive,2024-07-17,2024-08-29,2452,8.7,Predictive Systems +AI03531,Data Analyst,128939,CAD,161174,SE,PT,Canada,L,Canada,100,"Data Visualization, Deep Learning, SQL, MLOps, Java",PhD,5,Telecommunications,2024-11-27,2025-01-24,824,5.1,DeepTech Ventures +AI03532,Data Scientist,65196,USD,65196,MI,PT,Ireland,S,Ireland,0,"GCP, Git, NLP, PyTorch, Statistics",PhD,4,Finance,2025-03-23,2025-04-15,1393,7.4,Cloud AI Solutions +AI03533,Deep Learning Engineer,122554,USD,122554,MI,FL,Ireland,L,Ireland,100,"Kubernetes, R, Python, AWS",Associate,2,Real Estate,2024-12-16,2025-02-05,1118,6.5,DeepTech Ventures +AI03534,NLP Engineer,72995,EUR,62046,EN,CT,Netherlands,S,Kenya,100,"Mathematics, R, Python, Docker, PyTorch",Master,1,Consulting,2024-07-24,2024-08-28,1205,8.6,DeepTech Ventures +AI03535,AI Architect,36919,USD,36919,SE,FT,India,M,India,100,"Hadoop, Scala, Python, Docker",PhD,9,Real Estate,2025-01-26,2025-03-26,842,8.7,Smart Analytics +AI03536,Computer Vision Engineer,111161,JPY,12227710,SE,CT,Japan,S,Japan,50,"Git, Linux, GCP, AWS, SQL",Bachelor,5,Technology,2024-03-01,2024-05-03,999,7.6,AI Innovations +AI03537,Principal Data Scientist,226559,USD,226559,EX,PT,South Korea,L,Argentina,50,"R, Python, Azure, SQL",PhD,11,Consulting,2024-01-27,2024-04-06,679,8,Future Systems +AI03538,AI Product Manager,194134,USD,194134,EX,FT,United States,M,United States,0,"Scala, Docker, Data Visualization, Kubernetes, PyTorch",Bachelor,11,Gaming,2024-08-19,2024-10-01,653,7.3,DataVision Ltd +AI03539,Machine Learning Engineer,48340,CAD,60425,EN,CT,Canada,S,Canada,100,"PyTorch, R, Data Visualization",Bachelor,0,Finance,2024-11-06,2024-12-21,2251,8.2,Future Systems +AI03540,ML Ops Engineer,93478,USD,93478,MI,FL,Sweden,S,Sweden,100,"AWS, SQL, Mathematics",PhD,4,Gaming,2024-01-25,2024-03-18,990,8.9,Cognitive Computing +AI03541,AI Specialist,135053,GBP,101290,SE,FT,United Kingdom,L,United Kingdom,0,"Azure, Deep Learning, TensorFlow",Bachelor,9,Education,2024-04-18,2024-06-23,974,5.4,DataVision Ltd +AI03542,AI Specialist,118702,AUD,160248,SE,CT,Australia,M,New Zealand,50,"AWS, MLOps, Hadoop, NLP, R",Master,5,Government,2025-01-21,2025-03-23,2213,8.3,Neural Networks Co +AI03543,Computer Vision Engineer,66189,USD,66189,EN,CT,Ireland,S,Ireland,0,"Scala, Kubernetes, Python",Associate,1,Education,2024-02-09,2024-03-03,1274,7.5,Quantum Computing Inc +AI03544,NLP Engineer,135922,USD,135922,SE,FL,Finland,M,Finland,100,"Hadoop, Statistics, Azure",Bachelor,8,Finance,2024-03-07,2024-04-24,2462,9.3,Autonomous Tech +AI03545,AI Research Scientist,220929,USD,220929,SE,FT,Denmark,L,Denmark,50,"Linux, Azure, Spark",Master,8,Energy,2024-01-17,2024-03-26,2021,5.8,Machine Intelligence Group +AI03546,NLP Engineer,82829,JPY,9111190,MI,FT,Japan,M,Japan,100,"Spark, Kubernetes, NLP, Hadoop",Associate,2,Technology,2025-04-05,2025-04-29,1930,7.3,Smart Analytics +AI03547,NLP Engineer,91897,AUD,124061,MI,PT,Australia,S,Australia,50,"MLOps, PyTorch, TensorFlow",PhD,3,Manufacturing,2024-09-30,2024-10-16,533,5.1,DataVision Ltd +AI03548,Research Scientist,120965,USD,120965,MI,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Kubernetes",Master,4,Media,2024-01-02,2024-02-08,2239,9.6,Advanced Robotics +AI03549,Machine Learning Engineer,310818,CHF,279736,EX,PT,Switzerland,S,Switzerland,100,"SQL, Python, MLOps, Java, Mathematics",Bachelor,18,Technology,2025-01-27,2025-03-30,1771,6.4,Smart Analytics +AI03550,Deep Learning Engineer,73677,EUR,62625,EN,FL,Austria,L,Austria,50,"SQL, Git, Linux, AWS",Bachelor,0,Technology,2024-07-30,2024-08-30,1254,6.4,Quantum Computing Inc +AI03551,Principal Data Scientist,71156,USD,71156,EN,CT,United States,L,India,0,"Azure, Mathematics, Kubernetes, Deep Learning, Data Visualization",Associate,0,Government,2024-02-17,2024-03-16,2491,7.6,Digital Transformation LLC +AI03552,AI Software Engineer,190140,EUR,161619,EX,PT,Germany,M,Germany,100,"MLOps, Data Visualization, Python, TensorFlow, Deep Learning",Master,17,Real Estate,2024-07-04,2024-07-26,1541,7.4,Future Systems +AI03553,ML Ops Engineer,133027,EUR,113073,SE,FT,Austria,L,Austria,50,"Spark, Linux, Java, PyTorch",Master,5,Telecommunications,2024-08-09,2024-08-27,901,6,Smart Analytics +AI03554,Research Scientist,232210,USD,232210,EX,PT,South Korea,L,Spain,50,"Scala, PyTorch, AWS, Spark, SQL",Master,15,Consulting,2024-08-07,2024-09-05,2085,5,Cognitive Computing +AI03555,Data Analyst,113916,GBP,85437,SE,FT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Hadoop, R, AWS",Associate,8,Energy,2024-05-12,2024-07-02,2364,6,AI Innovations +AI03556,Head of AI,228576,SGD,297149,EX,PT,Singapore,M,Singapore,0,"GCP, Java, SQL, Git",Associate,13,Education,2024-07-25,2024-09-03,1965,7.8,Smart Analytics +AI03557,Machine Learning Researcher,25011,USD,25011,EN,CT,China,M,Portugal,0,"SQL, Linux, Hadoop, Mathematics",PhD,1,Manufacturing,2024-09-01,2024-11-03,1692,9.1,Algorithmic Solutions +AI03558,AI Product Manager,139200,USD,139200,SE,PT,Sweden,M,Sweden,0,"Git, Azure, Tableau, MLOps",Master,5,Energy,2024-05-31,2024-07-16,1241,9.1,Machine Intelligence Group +AI03559,Computer Vision Engineer,292522,CHF,263270,EX,FL,Switzerland,S,Switzerland,0,"R, Java, Tableau, MLOps",Associate,15,Consulting,2024-01-01,2024-01-27,824,7,Machine Intelligence Group +AI03560,AI Specialist,159257,USD,159257,SE,FL,Denmark,L,Denmark,100,"R, TensorFlow, Data Visualization, Tableau, NLP",PhD,5,Healthcare,2024-10-03,2024-12-14,1309,9.8,Quantum Computing Inc +AI03561,AI Research Scientist,108189,USD,108189,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, Azure, GCP, Scala",Master,5,Media,2025-02-26,2025-03-30,1421,5.9,Neural Networks Co +AI03562,Robotics Engineer,112943,USD,112943,SE,CT,Sweden,M,Sweden,100,"SQL, Statistics, Tableau",Master,7,Media,2024-01-16,2024-02-02,1584,7.4,AI Innovations +AI03563,Data Engineer,101976,SGD,132569,MI,CT,Singapore,M,Singapore,50,"Python, Computer Vision, Git",Master,2,Technology,2024-08-24,2024-11-02,2384,6.8,Machine Intelligence Group +AI03564,Principal Data Scientist,90165,GBP,67624,EN,CT,United Kingdom,L,United Kingdom,100,"GCP, Hadoop, Statistics, Computer Vision",Bachelor,1,Technology,2024-05-21,2024-06-15,700,6.6,Cloud AI Solutions +AI03565,ML Ops Engineer,179183,JPY,19710130,EX,CT,Japan,S,Japan,100,"Scala, R, Kubernetes, Python, Docker",Master,18,Real Estate,2024-05-30,2024-06-27,1393,7.2,Digital Transformation LLC +AI03566,NLP Engineer,113638,EUR,96592,SE,PT,Netherlands,M,South Africa,50,"SQL, Python, TensorFlow, Statistics, PyTorch",Bachelor,5,Transportation,2025-04-18,2025-05-12,2288,5.5,Predictive Systems +AI03567,Data Analyst,50907,SGD,66179,EN,PT,Singapore,S,Singapore,0,"Hadoop, SQL, Statistics",Bachelor,0,Manufacturing,2025-03-29,2025-04-26,902,7.7,Smart Analytics +AI03568,AI Consultant,167654,EUR,142506,EX,PT,France,M,France,50,"Kubernetes, Mathematics, Linux, SQL",Bachelor,13,Consulting,2025-04-07,2025-05-27,2217,7.5,DeepTech Ventures +AI03569,Machine Learning Researcher,119056,CHF,107150,MI,FL,Switzerland,S,Switzerland,50,"Docker, Python, Tableau",Master,2,Gaming,2024-09-02,2024-11-02,2403,8.9,Autonomous Tech +AI03570,Autonomous Systems Engineer,95121,USD,95121,MI,PT,United States,M,Poland,0,"Python, TensorFlow, Azure, NLP",PhD,2,Retail,2025-01-26,2025-02-24,1927,7.1,Smart Analytics +AI03571,AI Architect,111821,JPY,12300310,MI,FL,Japan,L,Turkey,50,"Linux, AWS, MLOps, SQL",Master,4,Healthcare,2024-03-04,2024-04-30,1694,5.8,Cognitive Computing +AI03572,Principal Data Scientist,183873,GBP,137905,EX,FT,United Kingdom,M,United Kingdom,0,"PyTorch, Git, Computer Vision, Java, MLOps",Associate,18,Education,2024-07-04,2024-08-04,684,6.5,AI Innovations +AI03573,AI Architect,247623,CHF,222861,EX,FL,Switzerland,L,Switzerland,100,"Java, Statistics, R, SQL, MLOps",PhD,15,Retail,2024-12-12,2025-01-15,2363,9,Future Systems +AI03574,AI Product Manager,70419,USD,70419,SE,FL,China,M,China,0,"Hadoop, Scala, Tableau, PyTorch, Mathematics",PhD,5,Manufacturing,2024-02-15,2024-03-04,1299,5.4,Advanced Robotics +AI03575,AI Architect,80822,CAD,101028,MI,CT,Canada,M,Canada,50,"Kubernetes, Git, Python, Docker",Bachelor,2,Real Estate,2024-11-12,2024-12-22,2216,8.2,DataVision Ltd +AI03576,AI Research Scientist,116798,USD,116798,MI,FL,United States,L,United States,100,"Python, AWS, Tableau, Computer Vision",Associate,2,Media,2024-09-08,2024-11-09,1703,9,Advanced Robotics +AI03577,AI Consultant,32773,USD,32773,EN,PT,India,L,India,50,"Python, MLOps, R, Java",Master,1,Transportation,2024-11-20,2024-12-12,1687,5.4,Machine Intelligence Group +AI03578,AI Research Scientist,153325,AUD,206989,EX,PT,Australia,S,Australia,100,"Kubernetes, Deep Learning, Scala, Linux",Bachelor,18,Energy,2025-04-30,2025-07-11,951,9.7,DeepTech Ventures +AI03579,AI Consultant,139637,EUR,118691,SE,FL,Germany,L,Germany,0,"AWS, Hadoop, MLOps",Associate,9,Retail,2025-03-20,2025-04-09,2137,6.9,Neural Networks Co +AI03580,AI Product Manager,228479,CHF,205631,SE,FT,Switzerland,L,Switzerland,0,"Git, Linux, Spark, Python, GCP",Bachelor,6,Real Estate,2025-04-24,2025-05-30,630,7.4,DeepTech Ventures +AI03581,Data Analyst,213432,USD,213432,EX,FL,Denmark,S,Norway,0,"Kubernetes, NLP, Azure",PhD,14,Automotive,2024-11-14,2024-12-30,1371,9.8,TechCorp Inc +AI03582,Data Scientist,120417,USD,120417,SE,FL,Norway,S,Norway,50,"Python, TensorFlow, GCP, Statistics",Master,7,Real Estate,2024-09-01,2024-10-28,1954,8,Autonomous Tech +AI03583,Computer Vision Engineer,128062,USD,128062,MI,FL,Denmark,S,Denmark,50,"R, Spark, Statistics, Deep Learning",Master,3,Transportation,2024-07-19,2024-09-28,2040,8.6,Quantum Computing Inc +AI03584,AI Product Manager,152788,EUR,129870,SE,FT,France,L,France,100,"Statistics, Deep Learning, Java, Docker",Associate,8,Gaming,2024-08-17,2024-10-28,1390,7.1,Smart Analytics +AI03585,Data Engineer,151742,EUR,128981,EX,PT,France,L,France,0,"TensorFlow, Python, NLP",Bachelor,19,Gaming,2024-06-28,2024-07-21,816,8.9,DeepTech Ventures +AI03586,Robotics Engineer,127281,USD,127281,SE,FL,South Korea,L,South Korea,100,"Deep Learning, Kubernetes, Linux, Mathematics, Hadoop",PhD,8,Gaming,2024-12-15,2025-02-23,2078,7.3,Future Systems +AI03587,Autonomous Systems Engineer,95779,CAD,119724,MI,PT,Canada,M,Canada,50,"Python, Computer Vision, SQL",Associate,2,Real Estate,2025-01-07,2025-01-28,1351,6.2,Future Systems +AI03588,AI Software Engineer,127704,AUD,172400,SE,CT,Australia,L,Australia,0,"SQL, Python, Git, Statistics, MLOps",Associate,5,Automotive,2024-01-22,2024-02-17,2062,9.4,TechCorp Inc +AI03589,Computer Vision Engineer,119308,CAD,149135,SE,FL,Canada,S,Canada,50,"Computer Vision, Hadoop, Python, GCP",Bachelor,8,Education,2025-01-01,2025-01-15,564,8,Machine Intelligence Group +AI03590,ML Ops Engineer,62680,AUD,84618,EN,FT,Australia,M,Australia,50,"GCP, Java, SQL, R",Associate,1,Technology,2024-11-07,2024-12-18,2105,6.6,Advanced Robotics +AI03591,Data Scientist,272438,AUD,367791,EX,PT,Australia,L,Norway,50,"AWS, Scala, NLP, PyTorch",PhD,17,Consulting,2024-03-10,2024-04-13,1144,8.1,Cognitive Computing +AI03592,AI Software Engineer,174329,EUR,148180,SE,CT,Netherlands,L,Netherlands,100,"R, NLP, Java",Master,7,Energy,2024-04-30,2024-05-27,1675,7,Smart Analytics +AI03593,Computer Vision Engineer,46653,USD,46653,EN,CT,Israel,S,Israel,0,"Python, GCP, Statistics",Associate,0,Technology,2024-04-20,2024-06-27,2203,5.6,DeepTech Ventures +AI03594,Head of AI,173890,USD,173890,EX,FT,Israel,M,Israel,100,"MLOps, Python, TensorFlow, Data Visualization, GCP",Associate,17,Finance,2024-04-08,2024-05-19,1771,6.1,Cloud AI Solutions +AI03595,Deep Learning Engineer,338945,CHF,305051,EX,FT,Switzerland,M,Switzerland,50,"MLOps, Git, Statistics",Master,14,Government,2024-04-06,2024-06-02,817,9.6,Advanced Robotics +AI03596,AI Architect,140480,USD,140480,SE,PT,South Korea,L,South Korea,50,"Deep Learning, AWS, Tableau, Azure",Master,7,Retail,2024-06-19,2024-08-10,863,5.1,Cognitive Computing +AI03597,Data Engineer,92646,USD,92646,MI,FT,Israel,S,Israel,100,"Spark, R, Statistics",PhD,2,Education,2024-06-07,2024-08-18,832,6.9,Autonomous Tech +AI03598,Data Engineer,54404,USD,54404,EX,PT,India,M,India,0,"PyTorch, MLOps, TensorFlow",PhD,10,Media,2024-05-05,2024-07-17,875,8.9,Machine Intelligence Group +AI03599,AI Specialist,113043,GBP,84782,SE,CT,United Kingdom,M,United Kingdom,0,"Deep Learning, Computer Vision, Tableau, Spark",PhD,8,Consulting,2025-01-30,2025-04-05,1712,8.2,Digital Transformation LLC +AI03600,Data Analyst,159400,EUR,135490,EX,CT,France,S,Turkey,50,"Deep Learning, Mathematics, TensorFlow",Bachelor,14,Real Estate,2025-01-23,2025-02-21,1732,8.4,Machine Intelligence Group +AI03601,Deep Learning Engineer,31170,USD,31170,EN,FL,China,S,South Africa,0,"Kubernetes, TensorFlow, MLOps",PhD,0,Transportation,2024-11-01,2024-12-09,1498,8.8,Advanced Robotics +AI03602,Principal Data Scientist,108438,USD,108438,MI,FL,Sweden,M,Indonesia,0,"Docker, NLP, Python",Bachelor,2,Real Estate,2024-08-02,2024-08-19,1635,8.9,Smart Analytics +AI03603,AI Architect,111346,USD,111346,SE,FT,United States,S,Indonesia,50,"Scala, Python, TensorFlow, Kubernetes, Statistics",Bachelor,7,Retail,2024-11-11,2024-12-01,970,9,Predictive Systems +AI03604,Deep Learning Engineer,223449,USD,223449,EX,FT,Denmark,S,Denmark,0,"Linux, Computer Vision, Git",Associate,16,Real Estate,2024-03-13,2024-04-26,1483,5.9,AI Innovations +AI03605,Computer Vision Engineer,48324,USD,48324,EN,FT,Sweden,S,Poland,50,"Docker, Azure, Tableau, Kubernetes",Bachelor,0,Telecommunications,2024-10-10,2024-11-19,1822,9.4,AI Innovations +AI03606,Autonomous Systems Engineer,66696,AUD,90040,EN,FT,Australia,M,Australia,100,"Docker, Scala, Computer Vision, Git",Bachelor,1,Retail,2024-07-01,2024-07-29,1526,6.5,Smart Analytics +AI03607,AI Research Scientist,210386,USD,210386,EX,CT,Sweden,S,Sweden,50,"Java, Git, GCP",Bachelor,16,Consulting,2024-11-30,2025-02-01,883,8.6,DataVision Ltd +AI03608,Machine Learning Researcher,48698,USD,48698,MI,CT,China,M,China,0,"Python, Java, AWS, NLP",PhD,3,Finance,2024-11-22,2024-12-16,1110,8,Smart Analytics +AI03609,Machine Learning Researcher,60193,EUR,51164,EN,CT,Austria,M,Austria,50,"Python, TensorFlow, Azure, SQL, PyTorch",Bachelor,0,Government,2024-02-12,2024-03-01,526,5.1,Cognitive Computing +AI03610,AI Specialist,60740,USD,60740,EN,PT,United States,M,United States,100,"AWS, R, Deep Learning, Python, Scala",Bachelor,0,Consulting,2024-03-20,2024-05-12,1052,7.3,Future Systems +AI03611,AI Specialist,118920,USD,118920,MI,CT,Norway,S,Canada,0,"Deep Learning, SQL, Statistics, Mathematics, Java",Master,3,Education,2024-08-19,2024-09-15,1491,5.2,Future Systems +AI03612,Principal Data Scientist,87000,AUD,117450,EN,CT,Australia,L,Australia,100,"R, SQL, Tableau",Associate,1,Finance,2024-07-31,2024-09-05,1336,6.9,DataVision Ltd +AI03613,Deep Learning Engineer,204824,USD,204824,EX,CT,Israel,M,Israel,0,"Hadoop, Computer Vision, Python, MLOps, Kubernetes",Bachelor,12,Media,2024-09-20,2024-10-10,1610,8.8,Advanced Robotics +AI03614,Principal Data Scientist,87194,USD,87194,MI,PT,Norway,S,Norway,0,"Computer Vision, Python, Tableau",Associate,2,Technology,2024-07-18,2024-08-07,1333,9.5,Neural Networks Co +AI03615,Autonomous Systems Engineer,232255,USD,232255,EX,CT,Norway,L,Portugal,100,"Deep Learning, Azure, PyTorch",Associate,16,Automotive,2024-05-28,2024-06-28,2132,9,Digital Transformation LLC +AI03616,Data Engineer,101827,USD,101827,MI,FL,Sweden,L,Sweden,50,"Azure, Docker, Git, NLP",Master,4,Telecommunications,2024-10-05,2024-11-08,1136,7.7,Future Systems +AI03617,Head of AI,240245,GBP,180184,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, R, Data Visualization, Computer Vision",PhD,16,Retail,2024-05-06,2024-06-15,1309,8.9,DeepTech Ventures +AI03618,Data Scientist,167576,USD,167576,SE,CT,Sweden,L,Sweden,50,"Tableau, Hadoop, R, Python",Bachelor,9,Energy,2025-03-06,2025-04-25,1628,8.3,Neural Networks Co +AI03619,AI Research Scientist,215103,CAD,268879,EX,CT,Canada,M,Canada,0,"Python, Git, TensorFlow, Docker, Linux",Master,13,Finance,2024-05-31,2024-07-24,1236,8.7,Smart Analytics +AI03620,Machine Learning Engineer,48369,EUR,41114,EN,PT,Austria,S,Austria,0,"GCP, Kubernetes, SQL, Hadoop, Docker",PhD,1,Telecommunications,2024-06-05,2024-07-18,2049,6.2,Quantum Computing Inc +AI03621,Research Scientist,133879,SGD,174043,SE,FT,Singapore,S,Singapore,100,"Docker, Scala, GCP, Deep Learning",Bachelor,9,Automotive,2024-09-25,2024-11-22,1927,5.1,Machine Intelligence Group +AI03622,Machine Learning Researcher,28565,USD,28565,EN,FT,China,L,China,100,"Statistics, Linux, SQL, Scala",Master,0,Healthcare,2025-02-23,2025-03-27,1764,5.4,Cognitive Computing +AI03623,ML Ops Engineer,159550,USD,159550,MI,PT,Denmark,L,Belgium,50,"Tableau, Linux, Kubernetes",PhD,3,Consulting,2024-01-17,2024-03-19,844,9.1,DataVision Ltd +AI03624,ML Ops Engineer,78403,EUR,66643,MI,FL,Netherlands,M,Netherlands,0,"MLOps, GCP, Data Visualization, Git",PhD,2,Automotive,2025-04-11,2025-05-16,1044,6.9,Neural Networks Co +AI03625,Head of AI,87867,USD,87867,EN,CT,Sweden,L,Sweden,50,"Linux, Git, Statistics",Associate,0,Consulting,2025-04-26,2025-07-06,2334,9.2,Algorithmic Solutions +AI03626,Machine Learning Engineer,116358,USD,116358,SE,CT,Israel,L,Norway,50,"NLP, Kubernetes, Docker, Deep Learning, GCP",Bachelor,8,Telecommunications,2025-01-28,2025-03-21,2472,5.1,Future Systems +AI03627,ML Ops Engineer,198454,SGD,257990,EX,PT,Singapore,L,Singapore,50,"Hadoop, Statistics, Mathematics, Kubernetes, R",Bachelor,18,Gaming,2024-02-05,2024-03-06,1969,5.8,AI Innovations +AI03628,Data Analyst,118657,EUR,100858,SE,PT,Germany,M,Germany,100,"MLOps, SQL, Kubernetes, Mathematics",Associate,6,Gaming,2024-12-03,2025-01-19,1755,8.6,DataVision Ltd +AI03629,Research Scientist,86457,USD,86457,EN,CT,Israel,L,Israel,100,"Mathematics, Java, Git, Linux, Computer Vision",Bachelor,1,Media,2024-04-05,2024-05-18,750,8.2,Digital Transformation LLC +AI03630,AI Research Scientist,52898,EUR,44963,EN,PT,France,M,Poland,50,"Scala, Tableau, Computer Vision, Java, Git",PhD,1,Energy,2024-12-15,2025-01-14,1017,7,Machine Intelligence Group +AI03631,Deep Learning Engineer,25159,USD,25159,EN,PT,India,M,India,50,"Data Visualization, Spark, AWS",Master,0,Manufacturing,2024-04-02,2024-06-11,615,5.5,Predictive Systems +AI03632,AI Research Scientist,67708,USD,67708,MI,CT,Ireland,S,Ireland,50,"Python, Java, SQL, Linux",Bachelor,4,Transportation,2024-04-19,2024-05-17,1446,8.5,Smart Analytics +AI03633,Machine Learning Engineer,214023,USD,214023,EX,FL,Denmark,L,South Korea,0,"R, SQL, Tableau, AWS, Java",Bachelor,13,Energy,2025-03-28,2025-04-20,1796,5.7,AI Innovations +AI03634,AI Product Manager,110880,SGD,144144,SE,CT,Singapore,M,Singapore,0,"MLOps, R, Linux, Python",Master,7,Retail,2024-02-15,2024-03-15,843,8.1,Cognitive Computing +AI03635,Data Engineer,49214,USD,49214,EN,CT,South Korea,M,Sweden,50,"AWS, Linux, Kubernetes",PhD,1,Healthcare,2025-01-05,2025-01-21,1103,6.9,Quantum Computing Inc +AI03636,Robotics Engineer,65197,USD,65197,MI,PT,South Korea,S,South Korea,50,"PyTorch, Hadoop, TensorFlow, Java",Associate,4,Technology,2024-12-04,2025-01-15,903,6.8,Quantum Computing Inc +AI03637,AI Consultant,94494,AUD,127567,MI,PT,Australia,S,Spain,50,"Kubernetes, SQL, Tableau",PhD,2,Real Estate,2024-10-10,2024-12-16,1260,6.6,AI Innovations +AI03638,ML Ops Engineer,93560,CHF,84204,EN,FL,Switzerland,M,China,50,"Linux, AWS, Tableau, Spark, Git",Associate,1,Telecommunications,2024-08-20,2024-10-10,1422,7.3,Predictive Systems +AI03639,Deep Learning Engineer,65918,USD,65918,EN,CT,Ireland,S,Ireland,50,"Docker, Python, Mathematics, Kubernetes, Git",Master,1,Retail,2024-11-09,2025-01-18,1621,6,DataVision Ltd +AI03640,AI Product Manager,136380,EUR,115923,SE,FL,Austria,L,Austria,100,"Mathematics, Tableau, Scala",PhD,6,Consulting,2025-01-28,2025-04-04,1271,7.8,DataVision Ltd +AI03641,Computer Vision Engineer,58677,USD,58677,EN,FL,Finland,M,Finland,100,"R, PyTorch, Azure, SQL, Statistics",Master,1,Gaming,2024-06-04,2024-08-02,1115,9.4,Digital Transformation LLC +AI03642,AI Specialist,78838,USD,78838,MI,FT,Israel,M,Israel,0,"Deep Learning, GCP, Git, Python",Bachelor,2,Energy,2024-07-26,2024-09-13,792,8.9,Autonomous Tech +AI03643,AI Architect,269456,USD,269456,EX,CT,Norway,M,Norway,50,"Python, Scala, Azure, Deep Learning, Computer Vision",Bachelor,15,Telecommunications,2024-02-10,2024-04-03,1052,9.8,Cloud AI Solutions +AI03644,AI Research Scientist,134951,USD,134951,SE,FL,Sweden,L,Sweden,100,"Tableau, Deep Learning, GCP, Python, TensorFlow",Bachelor,9,Automotive,2024-01-28,2024-02-13,1296,8.8,Smart Analytics +AI03645,AI Specialist,71037,USD,71037,EN,PT,Ireland,S,Ireland,0,"Hadoop, R, Java",PhD,0,Healthcare,2025-01-27,2025-03-26,2034,8.9,Cognitive Computing +AI03646,Deep Learning Engineer,81347,CHF,73212,EN,FT,Switzerland,M,Finland,0,"Deep Learning, Kubernetes, Linux",PhD,1,Healthcare,2024-12-11,2025-01-15,2320,9,AI Innovations +AI03647,Deep Learning Engineer,42928,USD,42928,MI,PT,China,S,China,0,"Docker, Linux, TensorFlow",Bachelor,3,Government,2024-03-02,2024-05-08,1427,9.3,DeepTech Ventures +AI03648,AI Architect,133466,CAD,166833,SE,PT,Canada,L,Canada,0,"PyTorch, TensorFlow, Azure",Associate,7,Technology,2024-07-25,2024-09-16,1603,5.4,Cloud AI Solutions +AI03649,Robotics Engineer,199990,USD,199990,EX,FT,Norway,M,Norway,100,"Docker, Kubernetes, AWS, Java",Associate,10,Education,2024-11-13,2024-12-07,1983,5.9,Cloud AI Solutions +AI03650,Machine Learning Researcher,146195,USD,146195,EX,FT,Finland,S,Finland,50,"Spark, Statistics, Hadoop",Master,17,Healthcare,2024-10-04,2024-12-07,502,6.8,Digital Transformation LLC +AI03651,NLP Engineer,98140,EUR,83419,EN,FL,Netherlands,L,Netherlands,100,"Kubernetes, R, Tableau, Data Visualization, AWS",Master,1,Finance,2024-01-01,2024-02-06,1249,6,AI Innovations +AI03652,Data Analyst,37739,USD,37739,EN,PT,China,L,China,100,"Linux, Kubernetes, Data Visualization, MLOps",Associate,0,Retail,2024-02-24,2024-03-12,1183,9.1,Neural Networks Co +AI03653,Deep Learning Engineer,76141,USD,76141,MI,CT,Ireland,S,Ireland,50,"Docker, SQL, PyTorch",Associate,4,Manufacturing,2024-02-13,2024-03-10,1482,9.2,Algorithmic Solutions +AI03654,Robotics Engineer,168289,USD,168289,EX,PT,United States,S,United States,50,"Scala, NLP, Git, Kubernetes",Bachelor,15,Transportation,2024-03-11,2024-05-19,924,6,Smart Analytics +AI03655,ML Ops Engineer,35309,USD,35309,MI,CT,India,M,Belgium,0,"Linux, PyTorch, NLP",PhD,4,Government,2025-02-01,2025-03-24,1527,5.1,AI Innovations +AI03656,Head of AI,252143,EUR,214322,EX,CT,Netherlands,M,Netherlands,100,"Docker, Data Visualization, Hadoop, Statistics",Bachelor,13,Automotive,2025-03-08,2025-03-23,1165,5.5,Digital Transformation LLC +AI03657,Robotics Engineer,61954,USD,61954,EN,PT,Sweden,M,Sweden,100,"SQL, MLOps, PyTorch, Hadoop",Master,1,Education,2024-09-16,2024-11-28,1789,9.3,Quantum Computing Inc +AI03658,Deep Learning Engineer,128736,USD,128736,SE,FT,Sweden,S,Turkey,0,"Git, Hadoop, Mathematics, SQL, R",PhD,5,Finance,2024-09-20,2024-11-28,797,6.1,Machine Intelligence Group +AI03659,AI Product Manager,90524,EUR,76945,MI,CT,Germany,L,Philippines,50,"NLP, Java, Deep Learning, Git",Bachelor,3,Consulting,2024-08-02,2024-09-10,2227,5.1,Smart Analytics +AI03660,Machine Learning Researcher,164213,GBP,123160,EX,FT,United Kingdom,M,United Kingdom,0,"Git, Hadoop, MLOps",Associate,19,Retail,2024-07-30,2024-09-22,2447,7.1,Quantum Computing Inc +AI03661,Data Analyst,106152,SGD,137998,MI,FT,Singapore,L,Singapore,0,"R, Git, Linux",Associate,4,Transportation,2025-04-03,2025-06-14,1267,7.2,DeepTech Ventures +AI03662,Robotics Engineer,101811,EUR,86539,SE,CT,France,M,Brazil,50,"Kubernetes, Python, Tableau",Associate,9,Transportation,2024-03-31,2024-05-23,1113,8.1,Neural Networks Co +AI03663,Machine Learning Engineer,130689,JPY,14375790,SE,FT,Japan,M,Argentina,0,"R, Spark, Data Visualization, Statistics, Azure",Master,8,Manufacturing,2024-04-02,2024-05-23,594,9.8,Neural Networks Co +AI03664,NLP Engineer,134597,USD,134597,EX,FL,Finland,S,Finland,0,"GCP, Java, PyTorch",Associate,14,Gaming,2024-03-07,2024-04-01,1997,6.2,TechCorp Inc +AI03665,Data Scientist,127982,USD,127982,SE,PT,South Korea,L,South Korea,50,"Spark, Kubernetes, Git, Tableau, Python",Bachelor,9,Automotive,2024-04-01,2024-06-04,804,9.3,Cognitive Computing +AI03666,AI Software Engineer,76846,USD,76846,EN,PT,United States,L,Sweden,100,"NLP, Deep Learning, Spark, MLOps",Master,0,Manufacturing,2024-04-13,2024-05-17,590,5.2,Cognitive Computing +AI03667,AI Software Engineer,121507,USD,121507,SE,FL,United States,M,United States,100,"Tableau, Kubernetes, AWS, GCP",Associate,7,Telecommunications,2025-02-05,2025-04-09,1356,7.4,Machine Intelligence Group +AI03668,Principal Data Scientist,190021,USD,190021,EX,FL,Norway,S,Norway,100,"Deep Learning, Java, Spark, Git",Associate,15,Transportation,2024-03-23,2024-05-01,789,8.4,Digital Transformation LLC +AI03669,Robotics Engineer,146680,CAD,183350,SE,FT,Canada,L,Spain,50,"Scala, PyTorch, Computer Vision, Hadoop",Master,5,Energy,2024-04-06,2024-05-19,2431,9.9,Autonomous Tech +AI03670,Autonomous Systems Engineer,82088,GBP,61566,EN,CT,United Kingdom,M,United Kingdom,0,"AWS, Linux, MLOps",PhD,1,Manufacturing,2024-01-11,2024-02-08,1485,9.8,Algorithmic Solutions +AI03671,Computer Vision Engineer,142953,USD,142953,SE,CT,Ireland,L,Ireland,50,"Kubernetes, Java, MLOps, GCP, Mathematics",Bachelor,6,Technology,2024-01-16,2024-03-15,1720,8.7,Quantum Computing Inc +AI03672,AI Specialist,178787,USD,178787,EX,PT,Israel,S,Israel,0,"Docker, Data Visualization, NLP",PhD,15,Technology,2025-04-27,2025-06-07,1111,6.5,AI Innovations +AI03673,Data Engineer,216277,EUR,183835,EX,PT,Austria,M,Austria,100,"Git, Java, MLOps",Master,13,Telecommunications,2024-02-23,2024-03-30,1084,8.5,Cognitive Computing +AI03674,Data Scientist,94882,USD,94882,MI,FT,Finland,L,Finland,50,"Data Visualization, Java, Git, Python, SQL",PhD,3,Education,2025-01-15,2025-03-10,985,8.3,Smart Analytics +AI03675,Data Scientist,73031,GBP,54773,EN,PT,United Kingdom,L,United Kingdom,50,"Computer Vision, Tableau, Python, TensorFlow",Associate,1,Education,2024-11-10,2025-01-22,1425,8.3,Smart Analytics +AI03676,Data Engineer,126700,USD,126700,EX,PT,Sweden,S,Sweden,0,"Linux, Hadoop, Python, TensorFlow",Bachelor,17,Manufacturing,2024-05-18,2024-06-18,2292,7,Machine Intelligence Group +AI03677,Head of AI,95630,GBP,71723,MI,FT,United Kingdom,S,United Kingdom,100,"Scala, Mathematics, Java, Spark, AWS",Master,3,Finance,2024-10-28,2025-01-04,2231,7.4,Algorithmic Solutions +AI03678,Deep Learning Engineer,75175,USD,75175,EN,CT,United States,S,United States,100,"NLP, Linux, SQL",Bachelor,1,Transportation,2025-02-10,2025-03-24,807,5.4,DataVision Ltd +AI03679,Machine Learning Engineer,83872,USD,83872,MI,PT,Israel,L,Egypt,0,"Scala, R, Tableau, Mathematics, Linux",PhD,2,Healthcare,2024-07-17,2024-08-22,619,9.7,AI Innovations +AI03680,Data Scientist,156742,USD,156742,SE,FT,Israel,L,Israel,0,"Deep Learning, R, Java",Bachelor,8,Finance,2024-07-07,2024-08-06,857,9.1,Smart Analytics +AI03681,Principal Data Scientist,111290,USD,111290,SE,FT,Finland,M,Finland,50,"R, Kubernetes, Docker, GCP",PhD,6,Telecommunications,2025-01-30,2025-03-02,2301,6.7,Cloud AI Solutions +AI03682,Computer Vision Engineer,83694,GBP,62771,MI,CT,United Kingdom,M,United Kingdom,0,"Scala, SQL, Hadoop",Bachelor,3,Media,2025-03-28,2025-06-04,1440,7.2,AI Innovations +AI03683,Principal Data Scientist,63711,EUR,54154,EN,FT,France,M,France,50,"Scala, SQL, R",PhD,0,Telecommunications,2024-12-14,2025-01-20,1184,6,Algorithmic Solutions +AI03684,Machine Learning Engineer,108037,EUR,91831,MI,FL,Netherlands,M,Netherlands,100,"GCP, SQL, MLOps, Data Visualization",Associate,2,Real Estate,2024-03-29,2024-05-28,929,7.7,Cognitive Computing +AI03685,Machine Learning Engineer,151599,SGD,197079,SE,FL,Singapore,M,Philippines,0,"Hadoop, Scala, SQL, Kubernetes, AWS",Master,5,Healthcare,2025-04-05,2025-05-09,1044,7.1,Quantum Computing Inc +AI03686,AI Architect,113115,EUR,96148,MI,CT,Netherlands,L,Netherlands,50,"Docker, Spark, Hadoop, NLP",Bachelor,3,Energy,2024-04-18,2024-06-23,1096,6.1,Advanced Robotics +AI03687,Head of AI,213162,USD,213162,EX,FL,Israel,M,Israel,0,"Spark, Python, Tableau, Azure",PhD,18,Real Estate,2024-03-20,2024-05-22,744,9.6,Machine Intelligence Group +AI03688,Deep Learning Engineer,172013,AUD,232218,EX,CT,Australia,L,Italy,50,"R, TensorFlow, Linux, Spark, Mathematics",PhD,16,Manufacturing,2024-05-12,2024-06-04,1245,8.3,Cognitive Computing +AI03689,NLP Engineer,81655,USD,81655,EX,PT,China,L,China,0,"Python, Linux, Git, TensorFlow",Bachelor,12,Consulting,2024-12-10,2025-02-02,580,8.6,Advanced Robotics +AI03690,NLP Engineer,70576,EUR,59990,MI,FL,France,S,France,100,"Computer Vision, R, Azure",PhD,2,Energy,2024-07-11,2024-08-19,1274,9.2,Cognitive Computing +AI03691,Machine Learning Engineer,27457,USD,27457,MI,FL,India,M,India,0,"Kubernetes, Java, Azure",Bachelor,4,Education,2025-04-15,2025-06-27,1890,6,Quantum Computing Inc +AI03692,AI Product Manager,115606,SGD,150288,SE,CT,Singapore,M,France,100,"R, SQL, Scala, Mathematics",Associate,9,Retail,2024-11-21,2025-01-17,2279,8.3,Predictive Systems +AI03693,ML Ops Engineer,85378,EUR,72571,EN,PT,Austria,L,Austria,100,"Computer Vision, Git, Kubernetes",Associate,1,Government,2024-07-09,2024-09-08,500,6.6,DeepTech Ventures +AI03694,AI Specialist,305455,CHF,274910,EX,PT,Switzerland,M,Argentina,0,"Git, Azure, Statistics, R",Master,16,Healthcare,2024-03-29,2024-04-12,1280,5.2,DataVision Ltd +AI03695,Robotics Engineer,115424,USD,115424,MI,FT,Finland,L,Finland,0,"Python, Git, Deep Learning, Spark",Bachelor,4,Finance,2024-02-23,2024-03-23,2154,6.3,Autonomous Tech +AI03696,AI Consultant,73524,USD,73524,EN,FL,United States,S,Vietnam,0,"Python, PyTorch, NLP",Bachelor,0,Government,2024-03-05,2024-04-12,757,6.1,AI Innovations +AI03697,AI Research Scientist,164239,EUR,139603,EX,FT,Germany,M,Germany,50,"Python, Computer Vision, Azure, Java",Bachelor,17,Telecommunications,2024-01-09,2024-02-07,542,9.4,Smart Analytics +AI03698,Head of AI,187030,USD,187030,EX,FT,South Korea,S,South Korea,50,"Docker, Python, R, Kubernetes",PhD,17,Retail,2025-01-28,2025-03-06,2173,8.7,Cloud AI Solutions +AI03699,Principal Data Scientist,201791,AUD,272418,EX,CT,Australia,S,Australia,50,"PyTorch, AWS, Python, NLP",Bachelor,12,Automotive,2024-04-06,2024-04-30,1444,9.7,AI Innovations +AI03700,AI Product Manager,189693,USD,189693,EX,FT,Norway,M,Norway,0,"Computer Vision, PyTorch, Spark",Associate,13,Technology,2024-06-30,2024-09-03,2479,7.2,Autonomous Tech +AI03701,Data Engineer,65796,EUR,55927,EN,PT,Austria,L,Austria,0,"Spark, AWS, Linux, TensorFlow, Azure",Associate,1,Real Estate,2025-03-29,2025-06-09,765,9.1,Autonomous Tech +AI03702,Principal Data Scientist,50207,EUR,42676,EN,FT,France,S,France,50,"Docker, Scala, GCP, Mathematics",PhD,0,Gaming,2024-04-03,2024-05-17,2206,8.8,Future Systems +AI03703,Data Scientist,90924,EUR,77285,MI,CT,Germany,M,Germany,0,"Java, R, NLP, GCP, Linux",Bachelor,3,Technology,2024-05-01,2024-05-26,1171,5.2,Future Systems +AI03704,Autonomous Systems Engineer,66161,CAD,82701,MI,FT,Canada,S,Canada,100,"R, Hadoop, TensorFlow, Git, SQL",Associate,4,Education,2024-07-08,2024-08-31,1791,5,Smart Analytics +AI03705,Data Engineer,166384,AUD,224618,EX,CT,Australia,L,Netherlands,100,"NLP, R, Java, Azure",Bachelor,18,Technology,2024-03-24,2024-05-20,2322,9.5,Cognitive Computing +AI03706,Autonomous Systems Engineer,124008,USD,124008,SE,FL,United States,M,United States,50,"Computer Vision, Azure, PyTorch",Master,6,Technology,2024-11-25,2025-02-02,625,8.6,Smart Analytics +AI03707,AI Software Engineer,83812,USD,83812,MI,CT,Ireland,M,Ireland,0,"Kubernetes, SQL, Tableau",PhD,2,Gaming,2024-06-28,2024-09-09,1991,6,Machine Intelligence Group +AI03708,Computer Vision Engineer,142427,SGD,185155,SE,PT,Singapore,S,Singapore,100,"Git, Python, Tableau, Computer Vision",Bachelor,5,Automotive,2024-12-12,2024-12-27,1392,5.8,AI Innovations +AI03709,AI Consultant,186900,USD,186900,SE,PT,Denmark,M,Denmark,100,"PyTorch, Scala, MLOps, Linux",Bachelor,5,Retail,2024-08-17,2024-09-24,1593,7.9,DataVision Ltd +AI03710,AI Specialist,129050,CAD,161313,SE,CT,Canada,M,Canada,0,"SQL, Deep Learning, Kubernetes, Scala",PhD,9,Healthcare,2025-04-18,2025-05-04,835,9.8,Future Systems +AI03711,Machine Learning Engineer,274462,CHF,247016,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Hadoop, Tableau, MLOps",Bachelor,14,Energy,2025-03-17,2025-04-23,2406,6.4,Quantum Computing Inc +AI03712,AI Product Manager,62465,JPY,6871150,EN,CT,Japan,M,Japan,50,"Mathematics, PyTorch, Tableau, Computer Vision, Git",PhD,0,Telecommunications,2024-12-07,2025-01-03,955,7.6,Smart Analytics +AI03713,Principal Data Scientist,73182,USD,73182,MI,PT,Israel,M,Sweden,100,"Linux, TensorFlow, Scala, SQL, Spark",Associate,2,Retail,2025-03-25,2025-04-30,1570,7.7,Neural Networks Co +AI03714,Deep Learning Engineer,184437,GBP,138328,EX,FL,United Kingdom,S,United Kingdom,50,"Linux, Hadoop, Tableau",PhD,17,Consulting,2024-07-07,2024-08-16,1473,5.4,Predictive Systems +AI03715,Robotics Engineer,94373,GBP,70780,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, TensorFlow, Azure",Bachelor,2,Healthcare,2024-06-26,2024-08-01,1713,8.6,DataVision Ltd +AI03716,Autonomous Systems Engineer,222341,EUR,188990,EX,PT,Austria,M,Denmark,100,"Azure, Scala, Data Visualization",Bachelor,16,Media,2025-01-15,2025-03-23,1873,7.3,Machine Intelligence Group +AI03717,Deep Learning Engineer,54047,CAD,67559,EN,PT,Canada,M,Canada,0,"NLP, Deep Learning, Scala, AWS",Bachelor,0,Government,2024-10-26,2025-01-01,804,5.6,Cloud AI Solutions +AI03718,NLP Engineer,127771,USD,127771,SE,CT,Denmark,S,Denmark,50,"SQL, Azure, Linux",Associate,9,Education,2024-07-06,2024-07-21,677,9.1,DataVision Ltd +AI03719,AI Specialist,93985,EUR,79887,MI,CT,France,M,France,50,"Statistics, Kubernetes, MLOps, R",PhD,3,Gaming,2024-02-18,2024-04-07,548,7.2,DataVision Ltd +AI03720,ML Ops Engineer,66798,EUR,56778,MI,PT,Germany,S,Kenya,0,"NLP, SQL, PyTorch, Java, Computer Vision",Associate,4,Technology,2024-06-03,2024-07-24,1988,5.5,AI Innovations +AI03721,Machine Learning Engineer,155058,USD,155058,SE,FL,Sweden,L,Sweden,100,"Statistics, Kubernetes, GCP, AWS",PhD,7,Gaming,2025-03-15,2025-04-15,1894,5.5,Cloud AI Solutions +AI03722,ML Ops Engineer,280160,JPY,30817600,EX,PT,Japan,L,Japan,0,"Mathematics, Tableau, Linux, Data Visualization",PhD,15,Manufacturing,2024-10-02,2024-11-21,2398,5.6,TechCorp Inc +AI03723,Autonomous Systems Engineer,77244,EUR,65657,MI,FL,France,S,France,50,"Spark, Tableau, TensorFlow, Data Visualization",Associate,4,Manufacturing,2024-01-19,2024-03-23,769,8.2,Cloud AI Solutions +AI03724,Autonomous Systems Engineer,216834,USD,216834,EX,FL,Israel,M,Estonia,100,"Kubernetes, Mathematics, Python",PhD,11,Manufacturing,2025-04-20,2025-07-02,1824,6.6,DeepTech Ventures +AI03725,AI Product Manager,110485,USD,110485,MI,FT,United States,L,Norway,50,"Python, TensorFlow, Spark, PyTorch, NLP",Master,2,Transportation,2024-06-16,2024-07-24,2063,8.6,Neural Networks Co +AI03726,Computer Vision Engineer,43499,USD,43499,SE,FT,China,S,China,50,"SQL, Java, Kubernetes, TensorFlow, Tableau",Bachelor,7,Media,2025-03-24,2025-05-27,537,5.1,DeepTech Ventures +AI03727,Computer Vision Engineer,266981,GBP,200236,EX,PT,United Kingdom,L,United Kingdom,0,"Data Visualization, Java, Spark",Bachelor,13,Telecommunications,2024-10-06,2024-11-05,1978,9.5,Algorithmic Solutions +AI03728,Machine Learning Researcher,126042,USD,126042,SE,FT,Finland,M,Finland,50,"Git, Docker, MLOps, Mathematics, Kubernetes",Associate,8,Automotive,2024-08-28,2024-10-08,1314,7.2,Neural Networks Co +AI03729,AI Specialist,173706,CAD,217133,EX,FL,Canada,S,Canada,50,"Kubernetes, Python, Azure, R, Mathematics",Master,10,Media,2025-01-20,2025-02-22,2026,8.8,Cloud AI Solutions +AI03730,AI Architect,75161,AUD,101467,EN,FT,Australia,M,Portugal,0,"GCP, Python, NLP",Associate,0,Real Estate,2025-02-10,2025-04-22,2388,5.6,Cloud AI Solutions +AI03731,Autonomous Systems Engineer,115030,USD,115030,SE,FT,Israel,M,Israel,50,"Git, TensorFlow, Tableau, Docker",Associate,7,Media,2024-09-07,2024-10-15,623,7.8,Machine Intelligence Group +AI03732,AI Product Manager,151796,AUD,204925,SE,FT,Australia,M,Australia,0,"Python, Kubernetes, Tableau, Computer Vision",PhD,8,Real Estate,2025-03-24,2025-05-26,2435,6.3,Algorithmic Solutions +AI03733,AI Research Scientist,59337,USD,59337,SE,FL,China,M,China,100,"GCP, MLOps, Tableau, R, Hadoop",Master,8,Government,2024-12-23,2025-01-22,617,9.7,Advanced Robotics +AI03734,Robotics Engineer,84211,CHF,75790,EN,PT,Switzerland,L,Finland,100,"TensorFlow, Python, Git",Bachelor,0,Real Estate,2025-03-13,2025-05-18,2309,9.8,AI Innovations +AI03735,Data Analyst,121798,CAD,152248,SE,PT,Canada,S,Sweden,50,"Linux, Tableau, AWS",Associate,5,Media,2025-04-13,2025-06-06,2077,9.9,TechCorp Inc +AI03736,Principal Data Scientist,198790,USD,198790,EX,PT,Israel,M,Ireland,50,"Python, Data Visualization, TensorFlow, Deep Learning, AWS",Associate,11,Government,2024-08-12,2024-10-16,2155,7.2,Autonomous Tech +AI03737,Data Engineer,80590,USD,80590,EN,CT,Norway,L,Thailand,0,"SQL, Spark, MLOps, Statistics, Python",Bachelor,1,Gaming,2024-10-07,2024-11-03,865,8.8,Algorithmic Solutions +AI03738,Principal Data Scientist,158320,EUR,134572,EX,CT,Germany,M,Colombia,50,"SQL, Python, MLOps, Deep Learning",Associate,19,Automotive,2024-01-26,2024-03-16,2065,5.4,Machine Intelligence Group +AI03739,AI Software Engineer,28067,USD,28067,MI,CT,India,S,South Africa,0,"Python, Deep Learning, Scala, Azure, Git",Master,3,Real Estate,2024-12-31,2025-01-19,928,8.1,Quantum Computing Inc +AI03740,Machine Learning Researcher,221734,EUR,188474,EX,FL,France,M,France,100,"MLOps, Hadoop, Python",Bachelor,12,Media,2024-11-12,2024-12-30,1964,8.2,Digital Transformation LLC +AI03741,Research Scientist,66023,USD,66023,EN,CT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, R, Git, Data Visualization",Master,1,Energy,2024-06-22,2024-08-07,820,6,Smart Analytics +AI03742,Machine Learning Engineer,79053,EUR,67195,MI,PT,Austria,M,Austria,100,"Statistics, PyTorch, Azure, Linux, TensorFlow",Master,4,Finance,2024-01-26,2024-03-11,1071,7.5,Quantum Computing Inc +AI03743,AI Specialist,90414,USD,90414,SE,CT,South Korea,M,South Korea,100,"Statistics, TensorFlow, Hadoop",Master,9,Healthcare,2024-07-03,2024-07-28,2008,7.4,TechCorp Inc +AI03744,Head of AI,44966,EUR,38221,EN,CT,France,S,France,0,"PyTorch, TensorFlow, Kubernetes, Scala, Java",Bachelor,1,Healthcare,2024-06-16,2024-08-03,1948,7.6,Quantum Computing Inc +AI03745,Principal Data Scientist,135292,USD,135292,SE,FL,United States,M,Egypt,100,"Deep Learning, Kubernetes, AWS, Scala, NLP",Bachelor,6,Transportation,2024-06-25,2024-07-31,846,9.2,Cloud AI Solutions +AI03746,Principal Data Scientist,224798,EUR,191078,EX,PT,France,M,France,0,"Mathematics, Git, Docker",PhD,19,Media,2024-12-04,2024-12-26,802,6.9,Cloud AI Solutions +AI03747,Deep Learning Engineer,169956,AUD,229441,EX,FT,Australia,S,Australia,100,"Spark, Java, Docker, Computer Vision",Bachelor,10,Gaming,2025-01-26,2025-03-06,750,6.9,Predictive Systems +AI03748,Data Scientist,218143,SGD,283586,EX,FT,Singapore,L,Singapore,0,"Spark, Tableau, Python",Master,19,Energy,2024-05-10,2024-07-17,2434,5.6,AI Innovations +AI03749,AI Research Scientist,123186,EUR,104708,SE,PT,Germany,S,United States,0,"Git, Docker, SQL, Kubernetes",Bachelor,5,Consulting,2024-10-14,2024-11-07,1709,8,Digital Transformation LLC +AI03750,Robotics Engineer,69645,CAD,87056,MI,FT,Canada,S,Canada,100,"Git, Scala, Spark",PhD,2,Automotive,2024-09-09,2024-11-06,1857,8.9,Cloud AI Solutions +AI03751,Head of AI,157091,EUR,133527,EX,PT,Austria,L,Austria,0,"Statistics, Tableau, SQL, Hadoop",PhD,16,Telecommunications,2024-12-21,2025-01-24,888,9.3,TechCorp Inc +AI03752,AI Specialist,90830,EUR,77206,MI,CT,Germany,L,China,50,"Azure, PyTorch, NLP",Associate,4,Retail,2025-03-29,2025-05-26,1841,9.2,Advanced Robotics +AI03753,Deep Learning Engineer,249590,EUR,212152,EX,PT,Netherlands,M,Netherlands,0,"Hadoop, Docker, Data Visualization",PhD,17,Transportation,2025-03-10,2025-03-24,2428,6.1,DeepTech Ventures +AI03754,Computer Vision Engineer,123791,USD,123791,SE,PT,Israel,M,Israel,0,"Linux, AWS, MLOps, Azure, Kubernetes",Bachelor,7,Finance,2024-06-17,2024-08-20,1043,7,Machine Intelligence Group +AI03755,Head of AI,117223,USD,117223,SE,PT,Finland,S,Finland,100,"Docker, MLOps, Computer Vision, Statistics",Bachelor,5,Education,2024-10-17,2024-11-06,2009,9.4,Future Systems +AI03756,NLP Engineer,27366,USD,27366,MI,CT,India,S,India,100,"Data Visualization, Scala, R",PhD,3,Energy,2024-06-04,2024-08-09,2448,6.5,Smart Analytics +AI03757,Machine Learning Researcher,182032,EUR,154727,EX,CT,Austria,L,Austria,0,"MLOps, SQL, AWS, NLP, Spark",Master,13,Consulting,2024-07-27,2024-10-02,1455,8.9,Advanced Robotics +AI03758,Data Analyst,31017,USD,31017,MI,FT,India,L,India,0,"Java, SQL, Deep Learning, PyTorch, Azure",Master,2,Gaming,2024-09-14,2024-10-26,669,5.8,Machine Intelligence Group +AI03759,Head of AI,148948,USD,148948,EX,CT,Finland,S,Finland,100,"Spark, R, MLOps",PhD,16,Technology,2024-06-21,2024-08-14,2352,7.5,Predictive Systems +AI03760,Data Engineer,126217,CHF,113595,MI,CT,Switzerland,L,Switzerland,50,"TensorFlow, Kubernetes, NLP, Deep Learning, Statistics",Bachelor,3,Energy,2024-10-30,2024-12-14,1310,8.9,Neural Networks Co +AI03761,AI Research Scientist,85615,EUR,72773,MI,PT,France,M,France,100,"Deep Learning, NLP, MLOps, Statistics, Kubernetes",Master,3,Gaming,2024-10-17,2024-11-24,2387,9.4,Predictive Systems +AI03762,Deep Learning Engineer,224102,USD,224102,EX,CT,Sweden,M,Sweden,100,"Tableau, Computer Vision, R",Bachelor,17,Government,2024-04-24,2024-05-16,1525,10,Smart Analytics +AI03763,Autonomous Systems Engineer,67594,EUR,57455,EN,PT,Germany,M,Germany,0,"Git, Deep Learning, Python, Tableau",Associate,1,Retail,2024-11-03,2024-11-25,2297,9.8,Cloud AI Solutions +AI03764,Autonomous Systems Engineer,172931,EUR,146991,EX,CT,Germany,S,Germany,100,"Java, Scala, Statistics, Data Visualization",Bachelor,19,Real Estate,2024-08-15,2024-09-13,992,5.9,Future Systems +AI03765,AI Research Scientist,109233,SGD,142003,SE,FT,Singapore,S,Singapore,50,"Python, TensorFlow, R, SQL",PhD,9,Healthcare,2024-07-02,2024-09-12,1286,5.7,Quantum Computing Inc +AI03766,AI Architect,240499,SGD,312649,EX,FT,Singapore,L,Singapore,100,"Hadoop, PyTorch, SQL, R, MLOps",Associate,18,Media,2025-04-28,2025-05-27,2292,7.4,Advanced Robotics +AI03767,Autonomous Systems Engineer,92133,USD,92133,EN,PT,Denmark,M,Denmark,100,"Java, Git, Statistics, R",PhD,1,Education,2025-03-09,2025-05-08,1048,7.5,DeepTech Ventures +AI03768,Machine Learning Researcher,76049,USD,76049,EX,PT,India,M,India,50,"NLP, Python, Linux, Data Visualization",Bachelor,12,Telecommunications,2024-01-07,2024-02-06,1742,5.8,TechCorp Inc +AI03769,Machine Learning Researcher,272882,AUD,368391,EX,CT,Australia,L,Australia,50,"R, SQL, Spark",PhD,19,Transportation,2025-01-29,2025-03-22,656,6.3,Quantum Computing Inc +AI03770,AI Specialist,60278,USD,60278,MI,CT,South Korea,S,South Korea,100,"Spark, NLP, Linux, Kubernetes",Associate,2,Manufacturing,2024-08-11,2024-10-18,1855,9.2,Machine Intelligence Group +AI03771,AI Product Manager,232998,USD,232998,EX,FT,Norway,L,South Africa,50,"Git, SQL, Deep Learning, Scala",Associate,17,Government,2024-08-14,2024-10-18,1447,6.5,Quantum Computing Inc +AI03772,AI Software Engineer,125478,SGD,163121,SE,CT,Singapore,S,Singapore,100,"R, Linux, SQL, Statistics, Deep Learning",Master,9,Consulting,2025-03-23,2025-04-09,703,6.9,Smart Analytics +AI03773,AI Consultant,80666,EUR,68566,MI,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, SQL, R, GCP",Associate,3,Healthcare,2024-03-24,2024-05-11,1026,7.3,TechCorp Inc +AI03774,AI Software Engineer,130187,CHF,117168,MI,CT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Linux, SQL",Associate,4,Consulting,2024-11-19,2025-01-06,1055,5.3,Future Systems +AI03775,Data Analyst,112669,USD,112669,MI,FT,Finland,L,Japan,50,"SQL, Git, TensorFlow, NLP, AWS",Associate,4,Gaming,2025-01-02,2025-02-06,1107,8.8,Machine Intelligence Group +AI03776,AI Research Scientist,117310,CAD,146638,MI,FT,Canada,L,Canada,100,"Python, Azure, NLP",PhD,2,Technology,2024-11-27,2024-12-28,1372,7,Predictive Systems +AI03777,Autonomous Systems Engineer,104436,USD,104436,EN,FL,United States,L,United States,100,"Scala, PyTorch, SQL, AWS",Master,1,Consulting,2024-11-09,2024-12-07,2286,9.8,Cognitive Computing +AI03778,Robotics Engineer,151858,USD,151858,SE,FT,Denmark,L,Denmark,50,"GCP, Data Visualization, MLOps, SQL, Linux",Master,7,Education,2024-09-25,2024-10-12,2069,8,Cloud AI Solutions +AI03779,AI Software Engineer,300122,USD,300122,EX,FL,United States,L,United States,100,"Linux, Data Visualization, Kubernetes",Bachelor,11,Manufacturing,2025-04-12,2025-05-24,1771,8.4,Machine Intelligence Group +AI03780,Research Scientist,123704,USD,123704,MI,PT,United States,M,India,100,"Python, GCP, TensorFlow, Linux, PyTorch",PhD,4,Energy,2024-05-11,2024-05-27,1820,5.6,Quantum Computing Inc +AI03781,NLP Engineer,123407,CAD,154259,SE,PT,Canada,M,Canada,100,"Mathematics, Python, MLOps, SQL, Linux",Bachelor,7,Energy,2024-11-04,2024-11-23,2275,5.9,TechCorp Inc +AI03782,AI Research Scientist,113350,SGD,147355,SE,PT,Singapore,S,Singapore,100,"Scala, Mathematics, Data Visualization, Deep Learning, Java",Bachelor,8,Real Estate,2025-03-23,2025-05-19,1968,7.3,AI Innovations +AI03783,Principal Data Scientist,240944,JPY,26503840,EX,CT,Japan,M,Japan,50,"MLOps, Statistics, Linux",PhD,17,Education,2025-03-05,2025-03-23,1690,6.5,Smart Analytics +AI03784,Autonomous Systems Engineer,56468,USD,56468,MI,FT,China,L,China,100,"R, NLP, TensorFlow, Data Visualization",Master,2,Media,2024-09-06,2024-10-30,1620,9.1,Quantum Computing Inc +AI03785,AI Specialist,23467,USD,23467,EN,FL,India,S,India,0,"Azure, Linux, Computer Vision, AWS, Docker",Bachelor,1,Education,2025-03-22,2025-04-08,1780,8.7,Predictive Systems +AI03786,AI Product Manager,41589,USD,41589,SE,FT,India,S,India,100,"Java, GCP, Azure, PyTorch, Mathematics",PhD,5,Manufacturing,2024-05-18,2024-06-25,1576,7.1,TechCorp Inc +AI03787,Autonomous Systems Engineer,56436,USD,56436,SE,FL,India,L,South Korea,50,"Git, PyTorch, Azure, Data Visualization",PhD,6,Telecommunications,2024-03-05,2024-04-02,2128,8.9,Autonomous Tech +AI03788,Deep Learning Engineer,102052,USD,102052,EN,FT,Denmark,M,Denmark,50,"Scala, Computer Vision, GCP, Git",Master,0,Finance,2025-03-07,2025-03-26,2234,9.6,Cognitive Computing +AI03789,Data Engineer,140417,GBP,105313,SE,PT,United Kingdom,M,New Zealand,0,"SQL, MLOps, PyTorch",Bachelor,5,Energy,2024-10-03,2024-12-15,939,6.5,Predictive Systems +AI03790,Head of AI,62079,USD,62079,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Python, AWS",Master,0,Media,2024-01-29,2024-04-05,845,8.3,Advanced Robotics +AI03791,Robotics Engineer,181941,GBP,136456,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Hadoop, SQL",Bachelor,9,Transportation,2024-09-15,2024-11-16,1538,7.2,Cloud AI Solutions +AI03792,Deep Learning Engineer,48759,USD,48759,EN,CT,South Korea,S,South Korea,50,"Kubernetes, Deep Learning, Python",PhD,0,Gaming,2024-06-28,2024-07-21,891,6.7,Smart Analytics +AI03793,Data Engineer,94775,EUR,80559,SE,PT,France,S,France,50,"Statistics, AWS, Spark, Deep Learning",PhD,8,Retail,2024-07-01,2024-08-29,1544,6.4,AI Innovations +AI03794,AI Specialist,111479,JPY,12262690,SE,FL,Japan,S,Poland,100,"Git, Java, GCP, Deep Learning",Master,6,Technology,2024-06-18,2024-08-13,568,9.1,Algorithmic Solutions +AI03795,Data Analyst,196602,USD,196602,EX,CT,Finland,M,Philippines,50,"Statistics, PyTorch, Git, Mathematics",Master,15,Manufacturing,2024-05-29,2024-06-12,1304,5.3,Advanced Robotics +AI03796,Principal Data Scientist,264173,EUR,224547,EX,PT,France,L,France,100,"Mathematics, Python, TensorFlow, MLOps, NLP",PhD,15,Technology,2024-12-15,2025-02-17,2407,9.6,DeepTech Ventures +AI03797,Head of AI,69502,SGD,90353,EN,CT,Singapore,M,Singapore,0,"Hadoop, SQL, PyTorch, Scala, R",PhD,1,Education,2024-12-31,2025-01-23,1948,8.8,Smart Analytics +AI03798,ML Ops Engineer,130004,EUR,110503,SE,PT,Germany,S,Italy,50,"MLOps, SQL, Python",PhD,6,Retail,2024-01-06,2024-02-03,1868,9.7,AI Innovations +AI03799,AI Product Manager,225220,USD,225220,EX,CT,Finland,M,Finland,0,"GCP, Python, TensorFlow, Hadoop, Deep Learning",PhD,11,Real Estate,2024-11-18,2025-01-02,699,8.5,AI Innovations +AI03800,Robotics Engineer,96826,SGD,125874,MI,CT,Singapore,M,Singapore,0,"GCP, PyTorch, Azure, R",PhD,3,Finance,2024-04-13,2024-05-26,1526,5.2,Digital Transformation LLC +AI03801,Machine Learning Engineer,56293,EUR,47849,EN,FL,Germany,S,Estonia,50,"SQL, Data Visualization, R, Computer Vision, NLP",PhD,1,Technology,2024-05-16,2024-07-11,1637,5.2,DeepTech Ventures +AI03802,Principal Data Scientist,197669,USD,197669,EX,FT,Denmark,M,Denmark,50,"Kubernetes, PyTorch, SQL, Docker",Bachelor,17,Real Estate,2025-04-11,2025-05-24,909,7.5,TechCorp Inc +AI03803,Machine Learning Engineer,129726,SGD,168644,SE,FL,Singapore,M,Singapore,50,"Python, Scala, GCP, R",Master,8,Government,2024-08-30,2024-10-26,967,5.1,Autonomous Tech +AI03804,AI Product Manager,146815,USD,146815,EX,PT,Sweden,S,Indonesia,0,"Computer Vision, PyTorch, Scala",Master,12,Consulting,2025-03-02,2025-04-17,850,5.4,Machine Intelligence Group +AI03805,Data Scientist,108448,USD,108448,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, AWS, NLP, Computer Vision",Master,5,Real Estate,2024-04-18,2024-05-12,2123,9.9,DataVision Ltd +AI03806,NLP Engineer,56987,GBP,42740,EN,CT,United Kingdom,S,Romania,0,"Linux, Tableau, TensorFlow, Deep Learning, Git",Master,0,Manufacturing,2024-02-05,2024-02-29,579,5.1,DeepTech Ventures +AI03807,Research Scientist,109575,USD,109575,SE,CT,Finland,S,Finland,0,"Hadoop, SQL, Python, Tableau, Deep Learning",Bachelor,6,Automotive,2024-10-19,2024-12-13,2369,9.7,Machine Intelligence Group +AI03808,AI Research Scientist,61632,USD,61632,EN,CT,Israel,L,Israel,50,"GCP, R, Tableau, Data Visualization, PyTorch",Bachelor,1,Real Estate,2024-10-26,2024-12-29,1601,6.6,Cognitive Computing +AI03809,Research Scientist,86859,USD,86859,MI,CT,Sweden,M,Sweden,0,"NLP, R, AWS, Linux, Deep Learning",Master,4,Technology,2024-06-27,2024-08-25,1979,7.7,Predictive Systems +AI03810,Data Analyst,93901,EUR,79816,MI,PT,Austria,M,Austria,100,"Python, Scala, Git",Bachelor,2,Gaming,2024-04-22,2024-05-17,2379,5,DeepTech Ventures +AI03811,Machine Learning Researcher,78383,USD,78383,SE,CT,South Korea,S,Austria,0,"Azure, Python, MLOps, R",Bachelor,9,Government,2024-10-30,2024-12-25,2250,6.8,Algorithmic Solutions +AI03812,Data Scientist,105143,USD,105143,EX,CT,China,L,China,0,"Deep Learning, Tableau, TensorFlow, R",Bachelor,13,Manufacturing,2024-06-08,2024-07-22,1396,9.6,Cognitive Computing +AI03813,AI Product Manager,113830,EUR,96756,SE,PT,France,M,Ukraine,0,"SQL, Hadoop, TensorFlow, Data Visualization, Linux",Associate,5,Healthcare,2024-10-06,2024-11-15,2416,7.3,Cloud AI Solutions +AI03814,Research Scientist,104205,EUR,88574,MI,FT,Netherlands,M,Romania,0,"Python, Docker, Tableau",Bachelor,4,Education,2025-02-10,2025-04-12,1015,6.6,Autonomous Tech +AI03815,Data Scientist,76948,USD,76948,MI,FL,Finland,S,Finland,0,"Deep Learning, Python, GCP, TensorFlow, Linux",Associate,3,Healthcare,2024-07-30,2024-09-14,2006,9.8,DataVision Ltd +AI03816,Data Scientist,158361,CAD,197951,SE,FT,Canada,L,Austria,100,"Spark, Python, Tableau, TensorFlow, GCP",Master,6,Energy,2024-06-26,2024-08-25,950,7.2,Digital Transformation LLC +AI03817,ML Ops Engineer,246286,USD,246286,EX,PT,Sweden,M,Sweden,100,"Scala, Spark, PyTorch, GCP",Associate,15,Gaming,2024-05-17,2024-07-22,1743,9.9,Advanced Robotics +AI03818,AI Architect,29444,USD,29444,MI,PT,India,M,India,50,"Git, Python, MLOps, NLP",Associate,3,Technology,2025-01-21,2025-02-24,1338,5.3,Machine Intelligence Group +AI03819,Data Scientist,65572,USD,65572,EX,PT,India,L,India,100,"NLP, Kubernetes, Data Visualization",PhD,10,Manufacturing,2025-03-06,2025-05-12,1167,8.5,Autonomous Tech +AI03820,AI Research Scientist,89996,EUR,76497,MI,FL,Austria,M,Austria,0,"MLOps, GCP, Python, TensorFlow, Computer Vision",PhD,3,Energy,2024-06-03,2024-07-11,1872,8.5,Neural Networks Co +AI03821,Head of AI,251600,EUR,213860,EX,FL,Germany,M,Germany,50,"PyTorch, Kubernetes, NLP",Associate,16,Energy,2024-07-03,2024-07-22,634,8.1,Advanced Robotics +AI03822,Principal Data Scientist,97239,GBP,72929,EN,FL,United Kingdom,L,United Kingdom,0,"Hadoop, Scala, Spark, TensorFlow, Tableau",Bachelor,0,Transportation,2024-09-19,2024-11-14,1174,7.8,Cloud AI Solutions +AI03823,Research Scientist,117805,JPY,12958550,SE,FL,Japan,S,Japan,100,"Linux, Azure, Python, Computer Vision",Associate,8,Energy,2024-07-31,2024-09-28,1354,7.7,Autonomous Tech +AI03824,Deep Learning Engineer,124143,USD,124143,MI,CT,United States,M,Finland,100,"Scala, Python, Computer Vision",PhD,2,Automotive,2024-03-20,2024-04-26,1879,9.1,Quantum Computing Inc +AI03825,Robotics Engineer,119551,USD,119551,SE,PT,Sweden,S,Sweden,50,"AWS, Azure, Python, TensorFlow, MLOps",PhD,9,Media,2024-03-28,2024-04-22,1443,8.8,DataVision Ltd +AI03826,NLP Engineer,122489,USD,122489,MI,PT,Ireland,L,Mexico,50,"Linux, Git, Tableau",Master,2,Retail,2024-01-20,2024-02-24,2181,8.3,AI Innovations +AI03827,AI Product Manager,297922,USD,297922,EX,CT,Denmark,L,Denmark,0,"Linux, Java, Tableau, Spark",Master,19,Finance,2024-02-01,2024-02-17,868,9.1,Cloud AI Solutions +AI03828,Autonomous Systems Engineer,284790,CHF,256311,EX,FT,Switzerland,M,Switzerland,100,"Tableau, Computer Vision, Git, MLOps, GCP",Associate,12,Real Estate,2024-03-17,2024-05-02,1087,6,DeepTech Ventures +AI03829,Machine Learning Engineer,140500,SGD,182650,SE,FT,Singapore,S,Singapore,100,"Scala, GCP, Data Visualization, Deep Learning, Mathematics",PhD,8,Energy,2024-11-11,2024-12-25,2434,7.7,AI Innovations +AI03830,NLP Engineer,116663,CHF,104997,MI,PT,Switzerland,S,Finland,50,"Kubernetes, Java, Spark",Master,4,Technology,2025-04-06,2025-06-05,899,6.3,Algorithmic Solutions +AI03831,AI Product Manager,136106,USD,136106,SE,FT,Norway,S,Norway,0,"TensorFlow, Statistics, Linux",Bachelor,6,Energy,2024-01-17,2024-02-09,1312,8.2,AI Innovations +AI03832,AI Specialist,120352,AUD,162475,SE,FL,Australia,S,United Kingdom,0,"Python, TensorFlow, Data Visualization",Associate,8,Technology,2025-02-22,2025-04-20,1026,5.1,Algorithmic Solutions +AI03833,Principal Data Scientist,115824,USD,115824,EX,PT,Finland,S,Finland,100,"Azure, Mathematics, GCP",Associate,10,Energy,2024-10-24,2024-12-23,1678,9.8,Advanced Robotics +AI03834,Data Engineer,192495,USD,192495,EX,PT,Israel,S,Israel,100,"SQL, Data Visualization, Spark, PyTorch",Associate,16,Government,2025-02-21,2025-03-13,1136,9.2,Autonomous Tech +AI03835,AI Consultant,70175,USD,70175,EN,CT,Finland,L,Finland,50,"Python, TensorFlow, MLOps, Tableau",Associate,0,Gaming,2024-03-27,2024-05-07,1939,5.9,Digital Transformation LLC +AI03836,Deep Learning Engineer,36741,USD,36741,MI,FL,India,M,India,100,"Azure, AWS, Spark, Hadoop, GCP",PhD,3,Consulting,2024-01-13,2024-02-01,825,8.6,Quantum Computing Inc +AI03837,Research Scientist,60568,USD,60568,EN,CT,Finland,L,Finland,100,"TensorFlow, SQL, Spark, Mathematics",Master,1,Government,2024-03-06,2024-04-17,1308,5.3,DeepTech Ventures +AI03838,Autonomous Systems Engineer,56833,USD,56833,EN,CT,Israel,M,Israel,50,"Statistics, Mathematics, Deep Learning, Python, TensorFlow",Associate,1,Gaming,2025-02-06,2025-03-19,1659,9.3,Machine Intelligence Group +AI03839,AI Research Scientist,138563,SGD,180132,SE,FT,Singapore,S,Singapore,100,"Tableau, SQL, Computer Vision",Associate,5,Consulting,2024-02-17,2024-03-16,1786,6.1,Machine Intelligence Group +AI03840,Autonomous Systems Engineer,69031,EUR,58676,MI,FL,Germany,S,Germany,50,"NLP, TensorFlow, Scala, Mathematics, R",PhD,3,Telecommunications,2024-09-25,2024-11-09,1921,7.4,Future Systems +AI03841,Principal Data Scientist,49258,USD,49258,EN,CT,Sweden,S,Sweden,100,"R, Docker, Python, Scala, Kubernetes",Bachelor,1,Consulting,2025-01-30,2025-04-04,1364,8.6,Advanced Robotics +AI03842,Machine Learning Engineer,177507,USD,177507,EX,FT,Sweden,M,Sweden,50,"Deep Learning, SQL, PyTorch, Git",Master,16,Gaming,2025-03-13,2025-04-11,1788,7,Cloud AI Solutions +AI03843,Robotics Engineer,278819,USD,278819,EX,CT,Denmark,M,Netherlands,100,"Computer Vision, Hadoop, R",Bachelor,12,Finance,2024-01-23,2024-03-02,1360,6.4,Algorithmic Solutions +AI03844,Data Analyst,101827,JPY,11200970,MI,PT,Japan,M,Japan,50,"Azure, PyTorch, MLOps, Python",Bachelor,4,Gaming,2024-06-07,2024-07-20,1347,5.8,Advanced Robotics +AI03845,Data Engineer,84062,SGD,109281,EN,CT,Singapore,L,Singapore,0,"Kubernetes, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Real Estate,2024-04-26,2024-05-27,2252,8.9,Cognitive Computing +AI03846,Deep Learning Engineer,102646,CHF,92381,MI,PT,Switzerland,S,Spain,50,"Hadoop, Linux, SQL, Python, Java",Bachelor,4,Healthcare,2024-12-26,2025-01-15,2383,6.6,AI Innovations +AI03847,AI Architect,95477,USD,95477,MI,CT,Norway,M,Norway,0,"GCP, TensorFlow, MLOps",Master,4,Gaming,2024-05-23,2024-08-01,1534,8.4,DeepTech Ventures +AI03848,Autonomous Systems Engineer,46111,USD,46111,SE,FL,China,S,China,0,"Spark, Kubernetes, Linux, Mathematics",Master,6,Transportation,2025-01-07,2025-01-25,518,5.9,Machine Intelligence Group +AI03849,Machine Learning Researcher,97023,EUR,82470,MI,FL,Netherlands,M,South Korea,50,"Python, TensorFlow, Linux, PyTorch, Mathematics",PhD,3,Retail,2024-07-31,2024-09-17,2239,8.7,DataVision Ltd +AI03850,Robotics Engineer,220428,USD,220428,EX,CT,Finland,M,Russia,100,"PyTorch, NLP, Statistics, TensorFlow",PhD,18,Energy,2025-01-14,2025-02-15,2110,8.2,Future Systems +AI03851,Data Analyst,111944,USD,111944,MI,FT,United States,L,Japan,50,"GCP, Java, Python, Tableau",PhD,4,Energy,2024-01-19,2024-03-13,1258,6.3,Algorithmic Solutions +AI03852,AI Product Manager,186617,GBP,139963,EX,FL,United Kingdom,L,United Kingdom,100,"AWS, Mathematics, Python",Bachelor,18,Government,2024-01-14,2024-03-23,1910,6.5,Smart Analytics +AI03853,Data Analyst,161013,EUR,136861,EX,FL,Netherlands,M,Netherlands,100,"SQL, Spark, NLP",Bachelor,18,Real Estate,2024-07-04,2024-08-13,1215,7.1,Digital Transformation LLC +AI03854,Principal Data Scientist,30458,USD,30458,MI,FL,India,S,India,100,"Kubernetes, NLP, SQL",Master,2,Consulting,2024-07-30,2024-09-27,1135,8.8,Algorithmic Solutions +AI03855,Research Scientist,64590,USD,64590,EN,FL,Israel,S,Israel,100,"Kubernetes, MLOps, Computer Vision, Azure",PhD,0,Technology,2024-01-17,2024-03-23,2116,9.5,Quantum Computing Inc +AI03856,ML Ops Engineer,113088,USD,113088,SE,PT,South Korea,S,Russia,0,"PyTorch, Kubernetes, Scala, Java, AWS",PhD,6,Automotive,2024-06-19,2024-07-07,2410,8.2,Autonomous Tech +AI03857,Research Scientist,110516,EUR,93939,MI,CT,Netherlands,L,Netherlands,0,"Python, SQL, Java, GCP, Docker",Associate,3,Media,2025-04-16,2025-05-10,1068,7.3,Future Systems +AI03858,Data Analyst,33400,USD,33400,EN,PT,China,S,China,0,"Statistics, Docker, PyTorch, AWS, Python",Associate,1,Consulting,2024-08-30,2024-10-12,2143,9.2,DataVision Ltd +AI03859,Research Scientist,57862,CAD,72328,EN,FT,Canada,M,Canada,0,"GCP, Mathematics, Kubernetes, Statistics",Master,1,Gaming,2024-07-12,2024-09-14,1817,6.1,Digital Transformation LLC +AI03860,Machine Learning Engineer,111403,EUR,94693,SE,FL,Germany,M,South Africa,50,"NLP, GCP, AWS, SQL, Python",Associate,5,Retail,2024-09-26,2024-11-15,2297,8.5,Future Systems +AI03861,AI Consultant,51736,EUR,43976,EN,FT,Netherlands,S,Netherlands,50,"Data Visualization, Kubernetes, Docker, Statistics",Bachelor,0,Government,2024-07-08,2024-08-01,982,5.1,Digital Transformation LLC +AI03862,Data Engineer,23717,USD,23717,EN,FL,India,M,India,50,"Tableau, Azure, R",Bachelor,0,Gaming,2024-05-27,2024-06-26,2332,7.6,Advanced Robotics +AI03863,Principal Data Scientist,109386,USD,109386,MI,FL,Ireland,M,Ireland,0,"Computer Vision, PyTorch, Kubernetes",Master,2,Government,2025-03-28,2025-05-26,1823,6.5,Advanced Robotics +AI03864,Deep Learning Engineer,74878,CAD,93598,MI,PT,Canada,M,Canada,50,"Python, Java, GCP",Bachelor,4,Government,2024-03-24,2024-04-15,2256,7.7,Predictive Systems +AI03865,Autonomous Systems Engineer,65141,USD,65141,EX,FT,India,M,India,0,"Java, R, SQL",Associate,16,Gaming,2024-12-07,2025-01-28,1317,9.2,Cloud AI Solutions +AI03866,AI Architect,128867,CHF,115980,MI,PT,Switzerland,M,Switzerland,50,"Spark, TensorFlow, SQL, Python",Bachelor,4,Energy,2024-10-06,2024-12-06,2112,5.2,DeepTech Ventures +AI03867,Data Analyst,90726,CHF,81653,EN,CT,Switzerland,S,Hungary,100,"Computer Vision, Java, Docker",Associate,1,Telecommunications,2024-09-24,2024-11-07,601,7.2,DeepTech Ventures +AI03868,Deep Learning Engineer,194760,USD,194760,EX,FT,Israel,M,Israel,100,"Python, Tableau, Git, TensorFlow",Master,17,Technology,2024-04-17,2024-05-18,2424,5.2,TechCorp Inc +AI03869,Autonomous Systems Engineer,107056,USD,107056,SE,CT,Ireland,S,Switzerland,0,"TensorFlow, Hadoop, PyTorch, Azure, GCP",Bachelor,5,Healthcare,2024-11-13,2024-12-05,1395,7.6,Future Systems +AI03870,Principal Data Scientist,108594,CAD,135743,SE,FT,Canada,M,South Africa,50,"Hadoop, TensorFlow, Kubernetes",Bachelor,9,Automotive,2025-03-02,2025-03-21,1796,9.7,DataVision Ltd +AI03871,Data Engineer,79163,EUR,67289,MI,CT,Germany,S,Germany,50,"Mathematics, Linux, R, Docker",Master,2,Technology,2024-12-24,2025-02-26,948,8.6,Advanced Robotics +AI03872,Principal Data Scientist,32589,USD,32589,EN,FT,China,M,China,100,"Java, Spark, Tableau, Hadoop, R",PhD,0,Finance,2024-09-08,2024-09-28,2482,6.1,Machine Intelligence Group +AI03873,Machine Learning Researcher,151184,USD,151184,SE,PT,United States,L,United States,50,"Python, Statistics, Computer Vision, TensorFlow, Spark",Associate,9,Telecommunications,2024-06-19,2024-08-19,1282,8.1,Autonomous Tech +AI03874,AI Research Scientist,80519,USD,80519,SE,PT,South Korea,S,South Korea,100,"GCP, Python, Docker, Computer Vision",Bachelor,7,Finance,2024-10-27,2024-12-28,1784,8.5,Future Systems +AI03875,Autonomous Systems Engineer,67798,USD,67798,EN,FT,Finland,S,Finland,50,"NLP, Mathematics, Linux",Bachelor,1,Consulting,2024-02-04,2024-04-17,1593,9,Predictive Systems +AI03876,Data Engineer,142055,JPY,15626050,SE,PT,Japan,L,Japan,0,"Python, Deep Learning, MLOps, Scala, Linux",Master,5,Retail,2024-08-09,2024-09-24,2229,6,Smart Analytics +AI03877,Data Scientist,120576,GBP,90432,SE,PT,United Kingdom,M,United Kingdom,50,"AWS, TensorFlow, Scala, Tableau",Associate,5,Finance,2025-01-15,2025-02-08,2007,6.4,Cloud AI Solutions +AI03878,Principal Data Scientist,125509,USD,125509,MI,FT,Norway,M,Norway,0,"MLOps, Statistics, Kubernetes",PhD,3,Transportation,2024-12-23,2025-01-27,2272,8.5,Advanced Robotics +AI03879,Data Analyst,55931,USD,55931,EX,PT,India,M,Vietnam,50,"Linux, Docker, AWS, Python",Associate,13,Finance,2024-03-07,2024-04-22,2317,8,DataVision Ltd +AI03880,Machine Learning Researcher,231123,JPY,25423530,EX,FT,Japan,L,Japan,50,"NLP, R, SQL, Tableau",Bachelor,13,Consulting,2024-07-09,2024-08-06,1704,6.8,DeepTech Ventures +AI03881,AI Product Manager,228322,USD,228322,EX,FT,South Korea,L,South Korea,0,"Kubernetes, Statistics, MLOps, SQL",Bachelor,17,Education,2025-02-25,2025-04-21,1258,9,Machine Intelligence Group +AI03882,Research Scientist,143444,USD,143444,EX,PT,Finland,S,Russia,0,"TensorFlow, Scala, Linux, PyTorch",Bachelor,14,Finance,2024-04-21,2024-05-30,1040,8.8,Future Systems +AI03883,AI Product Manager,72811,AUD,98295,EN,FT,Australia,M,Australia,0,"PyTorch, SQL, Java, Statistics, Azure",Associate,0,Manufacturing,2024-04-23,2024-06-17,1188,9.5,Quantum Computing Inc +AI03884,Research Scientist,53482,USD,53482,SE,FL,China,S,China,0,"Python, Git, Hadoop, Scala",Bachelor,5,Automotive,2024-01-20,2024-03-15,1359,6.2,Quantum Computing Inc +AI03885,Computer Vision Engineer,69221,AUD,93448,EN,PT,Australia,S,Australia,0,"Python, MLOps, Docker",Bachelor,1,Media,2024-01-14,2024-02-20,2077,5.7,TechCorp Inc +AI03886,ML Ops Engineer,171506,USD,171506,SE,CT,Norway,L,Mexico,50,"Data Visualization, Kubernetes, GCP, Scala",Master,5,Transportation,2024-02-24,2024-03-14,2170,7.8,Smart Analytics +AI03887,Data Analyst,149279,EUR,126887,EX,FT,France,S,France,100,"Kubernetes, Hadoop, Computer Vision, Python, Statistics",PhD,18,Technology,2024-10-01,2024-11-09,1669,9.7,DataVision Ltd +AI03888,AI Architect,123862,EUR,105283,SE,FT,France,M,France,50,"TensorFlow, SQL, Deep Learning, MLOps, Spark",PhD,5,Transportation,2024-07-07,2024-09-04,1315,8.1,DataVision Ltd +AI03889,Data Scientist,261986,USD,261986,EX,PT,Israel,L,Israel,50,"Hadoop, Kubernetes, Java, R",PhD,12,Energy,2025-02-11,2025-03-07,2344,8.3,Machine Intelligence Group +AI03890,Principal Data Scientist,158894,AUD,214507,EX,PT,Australia,S,Austria,0,"Kubernetes, SQL, Linux, Java, PyTorch",PhD,15,Media,2024-04-21,2024-06-17,1938,5.8,Digital Transformation LLC +AI03891,Deep Learning Engineer,137974,EUR,117278,SE,CT,Austria,L,Hungary,50,"Docker, Scala, Hadoop, Git",PhD,6,Telecommunications,2024-08-29,2024-11-07,2039,6.1,Digital Transformation LLC +AI03892,Head of AI,90760,JPY,9983600,MI,CT,Japan,L,Japan,100,"Hadoop, Tableau, Docker",PhD,4,Education,2024-12-17,2025-02-13,1338,9.3,DeepTech Ventures +AI03893,Data Engineer,137606,SGD,178888,SE,CT,Singapore,L,Latvia,0,"GCP, Python, Mathematics, MLOps",Associate,6,Telecommunications,2024-08-24,2024-10-18,858,8.8,Future Systems +AI03894,Deep Learning Engineer,133207,EUR,113226,EX,FL,France,S,France,50,"SQL, Python, TensorFlow",Master,19,Government,2024-10-02,2024-11-27,629,8.3,Machine Intelligence Group +AI03895,AI Product Manager,100495,USD,100495,EX,FT,India,L,India,50,"PyTorch, MLOps, Java, NLP, Scala",PhD,10,Media,2025-03-12,2025-05-17,2399,6.6,Digital Transformation LLC +AI03896,AI Product Manager,91306,EUR,77610,MI,CT,Germany,S,Germany,0,"Tableau, Python, Hadoop, Mathematics",Master,2,Energy,2025-01-24,2025-02-15,2200,5.4,TechCorp Inc +AI03897,AI Specialist,331986,USD,331986,EX,PT,United States,L,Indonesia,0,"PyTorch, Mathematics, MLOps, SQL",Bachelor,11,Consulting,2024-11-18,2025-01-19,2486,5,Machine Intelligence Group +AI03898,AI Software Engineer,75194,EUR,63915,MI,CT,Germany,M,India,0,"Python, TensorFlow, Spark, Azure",PhD,4,Real Estate,2024-08-27,2024-10-07,610,8,Advanced Robotics +AI03899,AI Product Manager,89154,USD,89154,EN,PT,Denmark,M,Singapore,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Technology,2024-03-28,2024-05-28,1881,5.9,DataVision Ltd +AI03900,AI Consultant,64299,USD,64299,EN,PT,South Korea,M,South Korea,50,"Git, Data Visualization, TensorFlow",Bachelor,0,Transportation,2024-08-15,2024-09-18,683,7.8,TechCorp Inc +AI03901,AI Specialist,137294,EUR,116700,SE,FT,Germany,L,Germany,100,"GCP, TensorFlow, MLOps, Mathematics, SQL",Bachelor,8,Government,2024-06-10,2024-07-30,1946,6.4,TechCorp Inc +AI03902,Data Scientist,101275,USD,101275,MI,FL,Ireland,M,Ireland,0,"Git, Kubernetes, Computer Vision, Deep Learning",Associate,2,Technology,2025-01-30,2025-03-29,795,8.7,Cloud AI Solutions +AI03903,Autonomous Systems Engineer,139984,USD,139984,MI,PT,United States,L,United States,100,"Spark, SQL, Mathematics, Docker, Deep Learning",PhD,2,Retail,2024-02-09,2024-04-11,930,8.9,Future Systems +AI03904,Deep Learning Engineer,151316,EUR,128619,EX,FL,France,S,United States,100,"Hadoop, SQL, Deep Learning",Master,12,Consulting,2025-01-04,2025-02-25,2299,6.4,Advanced Robotics +AI03905,NLP Engineer,84471,USD,84471,EN,PT,Denmark,M,Ireland,100,"Python, Git, GCP, Spark",Master,1,Finance,2024-05-14,2024-06-24,796,5.6,AI Innovations +AI03906,Data Engineer,104379,GBP,78284,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Statistics, R, PyTorch",Bachelor,5,Transportation,2024-02-03,2024-03-11,2366,6.3,Machine Intelligence Group +AI03907,Principal Data Scientist,252832,USD,252832,EX,PT,Denmark,S,Denmark,50,"Scala, TensorFlow, Tableau",PhD,10,Energy,2024-10-14,2024-12-24,1983,8.7,Cognitive Computing +AI03908,Machine Learning Researcher,214285,EUR,182142,EX,FT,Germany,L,Chile,100,"Git, Azure, Data Visualization, R, Computer Vision",Master,17,Manufacturing,2024-05-17,2024-07-20,1999,9.6,DataVision Ltd +AI03909,Data Engineer,100489,USD,100489,EN,CT,Norway,L,Norway,100,"Kubernetes, MLOps, SQL, TensorFlow, R",Associate,0,Automotive,2024-10-22,2024-11-30,1403,7.7,AI Innovations +AI03910,Research Scientist,116902,AUD,157818,SE,FT,Australia,M,Australia,50,"GCP, Mathematics, Data Visualization",PhD,8,Real Estate,2024-07-04,2024-08-06,739,6,DataVision Ltd +AI03911,Data Scientist,98004,USD,98004,EN,PT,Norway,M,Israel,0,"Git, AWS, GCP, Deep Learning, Docker",Master,1,Telecommunications,2024-07-22,2024-09-24,2303,6.7,Machine Intelligence Group +AI03912,ML Ops Engineer,216802,USD,216802,EX,FL,United States,S,United States,50,"Python, TensorFlow, Tableau, PyTorch, Azure",PhD,15,Education,2025-03-11,2025-04-21,869,6,Smart Analytics +AI03913,Principal Data Scientist,97639,USD,97639,MI,FT,Sweden,M,United States,50,"Python, TensorFlow, Spark",Master,4,Energy,2024-12-15,2025-02-15,1662,8.8,Quantum Computing Inc +AI03914,AI Specialist,112321,USD,112321,MI,CT,Israel,L,Israel,0,"Mathematics, GCP, Computer Vision, TensorFlow, Spark",PhD,4,Gaming,2024-02-11,2024-03-21,2160,6,Predictive Systems +AI03915,Data Engineer,192260,AUD,259551,EX,FT,Australia,S,Finland,0,"Tableau, MLOps, GCP, Scala",Bachelor,18,Automotive,2024-10-04,2024-12-14,1151,9.4,Quantum Computing Inc +AI03916,Head of AI,109993,AUD,148491,MI,PT,Australia,L,Australia,50,"SQL, Linux, AWS",Associate,4,Telecommunications,2024-02-06,2024-04-12,1361,8.9,Autonomous Tech +AI03917,AI Product Manager,65943,USD,65943,MI,FL,Sweden,S,Sweden,50,"Python, Kubernetes, Java, Hadoop",Master,2,Finance,2024-08-26,2024-10-09,861,9.3,DeepTech Ventures +AI03918,AI Software Engineer,90867,SGD,118127,MI,PT,Singapore,M,Singapore,100,"SQL, Scala, GCP, Kubernetes, Tableau",Associate,3,Education,2024-11-22,2024-12-23,1269,9.5,DataVision Ltd +AI03919,ML Ops Engineer,84856,USD,84856,EX,FT,India,M,India,100,"AWS, Azure, Spark, Data Visualization, Deep Learning",Bachelor,13,Automotive,2025-03-16,2025-05-05,1793,9.5,Future Systems +AI03920,Data Analyst,171549,EUR,145817,EX,FT,France,M,South Africa,0,"Spark, Linux, Tableau, TensorFlow, Data Visualization",Bachelor,11,Manufacturing,2024-08-12,2024-09-15,1377,5.2,AI Innovations +AI03921,AI Research Scientist,191772,EUR,163006,EX,FL,Germany,M,Thailand,0,"Docker, Statistics, Scala, Kubernetes",Bachelor,19,Telecommunications,2024-07-22,2024-08-14,1912,8.4,Advanced Robotics +AI03922,Robotics Engineer,111326,USD,111326,SE,FT,Ireland,S,Ireland,100,"Computer Vision, SQL, Git, Deep Learning, GCP",Bachelor,6,Retail,2024-08-17,2024-09-16,565,7.3,Cognitive Computing +AI03923,Robotics Engineer,180543,JPY,19859730,EX,CT,Japan,M,Japan,50,"SQL, Deep Learning, Python, NLP",Associate,16,Transportation,2024-06-26,2024-07-13,1493,7.1,Predictive Systems +AI03924,AI Research Scientist,35560,USD,35560,EN,FT,China,M,China,50,"Kubernetes, Azure, Python, Deep Learning",Bachelor,1,Energy,2024-06-21,2024-08-09,983,5.7,Future Systems +AI03925,AI Software Engineer,80024,USD,80024,SE,PT,China,L,China,0,"Hadoop, Linux, Data Visualization",PhD,8,Manufacturing,2024-06-06,2024-06-23,1425,10,Machine Intelligence Group +AI03926,AI Architect,62790,USD,62790,EN,PT,Finland,M,Norway,100,"Python, TensorFlow, AWS, Docker",Master,1,Healthcare,2024-09-01,2024-11-12,1164,8.4,Advanced Robotics +AI03927,NLP Engineer,172119,USD,172119,SE,FT,Norway,M,Norway,0,"MLOps, Mathematics, Tableau, Docker, Azure",Associate,5,Finance,2024-03-05,2024-03-20,727,5.8,Quantum Computing Inc +AI03928,AI Software Engineer,144594,USD,144594,EX,FT,Finland,S,Finland,100,"PyTorch, Python, Azure",Associate,14,Finance,2025-04-30,2025-06-24,1107,6.8,Algorithmic Solutions +AI03929,Autonomous Systems Engineer,59241,EUR,50355,EN,FL,France,S,France,50,"Git, PyTorch, Hadoop, Azure, Deep Learning",Bachelor,0,Transportation,2024-01-30,2024-03-19,2005,9.1,Neural Networks Co +AI03930,Research Scientist,114166,EUR,97041,SE,CT,Netherlands,M,Netherlands,0,"SQL, GCP, NLP, Statistics",Bachelor,9,Media,2024-03-05,2024-04-15,2009,6.8,Cloud AI Solutions +AI03931,AI Product Manager,32706,USD,32706,EN,CT,China,S,Hungary,0,"Hadoop, R, SQL",PhD,1,Manufacturing,2024-03-07,2024-04-26,1525,8.4,Smart Analytics +AI03932,AI Research Scientist,120324,USD,120324,SE,FL,Sweden,M,Sweden,0,"PyTorch, TensorFlow, Tableau, SQL",PhD,8,Real Estate,2024-08-24,2024-10-08,1364,8.8,Algorithmic Solutions +AI03933,NLP Engineer,59232,CAD,74040,EN,PT,Canada,L,Austria,50,"Java, Computer Vision, Mathematics, Hadoop",Master,0,Manufacturing,2025-01-16,2025-03-22,1616,8.4,Neural Networks Co +AI03934,AI Architect,221142,CHF,199028,EX,PT,Switzerland,M,Switzerland,50,"PyTorch, Statistics, TensorFlow",Associate,18,Real Estate,2025-02-25,2025-03-29,1739,5.6,Neural Networks Co +AI03935,Research Scientist,48487,USD,48487,EN,CT,Israel,S,Israel,50,"Mathematics, AWS, Data Visualization, Azure, Git",Associate,1,Manufacturing,2025-03-07,2025-04-18,1412,7.8,DeepTech Ventures +AI03936,Machine Learning Researcher,145495,SGD,189144,SE,FT,Singapore,M,Singapore,0,"NLP, Hadoop, Linux",Bachelor,8,Healthcare,2024-10-25,2024-12-07,1094,5,Algorithmic Solutions +AI03937,Autonomous Systems Engineer,64092,SGD,83320,EN,FL,Singapore,L,Kenya,50,"Kubernetes, SQL, Spark, Python, Statistics",Associate,0,Consulting,2024-10-11,2024-12-15,779,7.3,Predictive Systems +AI03938,Data Analyst,135974,USD,135974,SE,CT,Denmark,S,Kenya,0,"Hadoop, Tableau, Python, Mathematics",Master,9,Education,2024-11-09,2024-12-31,2321,7.6,Quantum Computing Inc +AI03939,AI Product Manager,215605,USD,215605,EX,FL,Israel,M,Israel,0,"Java, R, SQL",Master,12,Technology,2024-12-16,2025-01-26,1940,5.6,Predictive Systems +AI03940,Principal Data Scientist,109621,USD,109621,MI,PT,United States,L,Singapore,0,"SQL, AWS, Git, MLOps, GCP",Bachelor,2,Energy,2024-12-20,2025-01-05,849,9.8,Future Systems +AI03941,AI Specialist,155788,USD,155788,SE,FT,United States,S,United States,0,"SQL, Data Visualization, Scala, Azure, Linux",Associate,6,Gaming,2024-06-07,2024-07-29,2489,7.7,Autonomous Tech +AI03942,Research Scientist,114493,USD,114493,SE,FT,Israel,L,Luxembourg,0,"Spark, NLP, Python, Deep Learning",Associate,9,Manufacturing,2024-06-22,2024-07-06,1482,6.2,Digital Transformation LLC +AI03943,AI Architect,127669,EUR,108519,SE,FT,Germany,S,Finland,100,"Mathematics, Kubernetes, Statistics, GCP, Tableau",Master,7,Government,2025-04-23,2025-07-03,1199,8.5,TechCorp Inc +AI03944,Machine Learning Engineer,184048,SGD,239262,EX,CT,Singapore,M,Singapore,0,"TensorFlow, R, Azure, GCP, Hadoop",Master,11,Technology,2024-01-24,2024-02-10,924,6.6,Algorithmic Solutions +AI03945,Machine Learning Engineer,62821,USD,62821,MI,FL,Finland,S,Finland,100,"Python, Linux, Scala, Kubernetes, TensorFlow",PhD,2,Transportation,2025-04-04,2025-05-30,1805,7.6,Autonomous Tech +AI03946,Data Analyst,116061,USD,116061,MI,FL,Norway,M,Norway,50,"Scala, Statistics, Python, Git",PhD,2,Gaming,2024-05-07,2024-07-11,1188,9.5,Predictive Systems +AI03947,Deep Learning Engineer,68069,JPY,7487590,EN,CT,Japan,M,Japan,100,"Docker, R, Deep Learning, Statistics, Mathematics",PhD,1,Consulting,2024-10-10,2024-10-31,2039,8.5,Future Systems +AI03948,ML Ops Engineer,55034,USD,55034,EN,FL,South Korea,S,Czech Republic,100,"R, GCP, Statistics, SQL, Tableau",Bachelor,1,Media,2024-09-27,2024-11-07,1092,8.6,Advanced Robotics +AI03949,AI Product Manager,197089,EUR,167526,EX,FT,Germany,M,Germany,100,"Hadoop, TensorFlow, Tableau, Data Visualization, Kubernetes",Bachelor,13,Government,2024-04-28,2024-06-26,1527,9,Quantum Computing Inc +AI03950,Data Analyst,63965,EUR,54370,EN,FL,Austria,S,Austria,100,"SQL, Spark, PyTorch, AWS, Java",Master,1,Consulting,2024-11-17,2024-12-02,1541,9.2,Cognitive Computing +AI03951,Research Scientist,88359,CHF,79523,EN,FT,Switzerland,S,Switzerland,100,"TensorFlow, Python, NLP",Associate,0,Real Estate,2024-11-04,2024-11-19,1376,6.4,Machine Intelligence Group +AI03952,ML Ops Engineer,58746,USD,58746,EN,CT,Ireland,S,Ireland,50,"SQL, Python, NLP, Scala, Git",Associate,1,Retail,2024-10-16,2024-11-21,748,9,Future Systems +AI03953,ML Ops Engineer,84148,USD,84148,EX,FT,China,M,China,50,"Tableau, PyTorch, Azure, Linux, NLP",Bachelor,17,Retail,2024-08-26,2024-11-05,1420,5.2,Neural Networks Co +AI03954,Machine Learning Engineer,106957,CHF,96261,EN,FL,Switzerland,M,Switzerland,50,"R, PyTorch, Computer Vision",Master,1,Healthcare,2024-11-27,2024-12-12,1030,6.4,Future Systems +AI03955,Autonomous Systems Engineer,83304,CAD,104130,MI,PT,Canada,S,Denmark,50,"GCP, Scala, Data Visualization, TensorFlow",PhD,3,Education,2024-03-30,2024-05-01,943,6.3,TechCorp Inc +AI03956,Principal Data Scientist,169228,USD,169228,EX,FL,United States,M,United States,100,"Python, Azure, Mathematics",Bachelor,10,Education,2024-04-02,2024-05-11,1923,9.7,TechCorp Inc +AI03957,Deep Learning Engineer,87246,CAD,109058,MI,CT,Canada,S,Nigeria,50,"Deep Learning, Python, Mathematics, MLOps",Master,3,Gaming,2024-05-01,2024-06-26,916,9.4,DataVision Ltd +AI03958,Research Scientist,71057,GBP,53293,EN,PT,United Kingdom,M,United Kingdom,100,"Python, PyTorch, Kubernetes, Azure, SQL",PhD,0,Retail,2024-03-04,2024-05-13,1746,7.6,AI Innovations +AI03959,Data Engineer,197354,CAD,246693,EX,CT,Canada,M,Mexico,50,"SQL, R, Tableau, Statistics, Scala",Associate,11,Energy,2024-01-30,2024-03-18,2412,8.8,DeepTech Ventures +AI03960,Research Scientist,128498,USD,128498,EX,FL,Israel,S,China,0,"Mathematics, SQL, Linux",Bachelor,15,Technology,2024-04-29,2024-06-08,1531,9,Advanced Robotics +AI03961,AI Architect,186865,USD,186865,SE,CT,Denmark,L,Denmark,0,"TensorFlow, Azure, NLP, Git, SQL",Master,8,Telecommunications,2024-11-07,2024-12-21,1088,5.3,Quantum Computing Inc +AI03962,AI Research Scientist,107253,USD,107253,MI,FT,United States,M,Russia,100,"Linux, Computer Vision, Python, Data Visualization, Git",PhD,2,Automotive,2024-01-25,2024-03-27,2074,9.8,TechCorp Inc +AI03963,NLP Engineer,63687,USD,63687,MI,FL,Israel,S,Israel,50,"Computer Vision, Kubernetes, SQL, Deep Learning",PhD,4,Education,2024-07-18,2024-09-05,1291,9.5,Neural Networks Co +AI03964,Principal Data Scientist,79216,USD,79216,MI,FT,Israel,S,Israel,100,"PyTorch, Linux, Data Visualization",Associate,2,Education,2024-06-12,2024-07-20,1511,6,Autonomous Tech +AI03965,Data Scientist,231383,USD,231383,EX,FT,Israel,L,Israel,0,"GCP, TensorFlow, Scala, Python, Data Visualization",Master,11,Technology,2024-02-21,2024-04-07,2362,8.9,Smart Analytics +AI03966,Data Engineer,43977,USD,43977,SE,PT,India,S,Sweden,100,"Scala, Data Visualization, Tableau, Java",Bachelor,9,Automotive,2025-04-22,2025-05-15,1455,8.7,DeepTech Ventures +AI03967,Principal Data Scientist,58328,USD,58328,SE,FT,China,M,China,50,"Data Visualization, Scala, Linux, Java",Bachelor,8,Telecommunications,2024-10-09,2024-12-13,860,6.6,DataVision Ltd +AI03968,Machine Learning Engineer,26547,USD,26547,EN,PT,India,L,Turkey,0,"Python, Azure, SQL, Computer Vision",Master,1,Finance,2025-04-01,2025-05-25,976,7.8,TechCorp Inc +AI03969,Autonomous Systems Engineer,55423,USD,55423,EN,CT,South Korea,S,Australia,0,"Docker, SQL, Java, PyTorch, Linux",Master,0,Real Estate,2024-12-12,2025-01-12,1325,7,Advanced Robotics +AI03970,Machine Learning Engineer,24833,USD,24833,MI,FT,India,S,Mexico,0,"R, SQL, Data Visualization",Master,3,Media,2024-12-20,2025-03-03,2055,9.3,Advanced Robotics +AI03971,Principal Data Scientist,110197,USD,110197,MI,FL,United States,M,United States,100,"R, PyTorch, Scala",PhD,3,Real Estate,2025-01-02,2025-03-01,1672,8.7,Machine Intelligence Group +AI03972,AI Architect,72964,USD,72964,EN,FL,Israel,M,Ukraine,100,"AWS, Spark, MLOps, Scala",Associate,0,Government,2024-03-07,2024-04-04,2318,9.2,AI Innovations +AI03973,Robotics Engineer,59921,USD,59921,EN,CT,Sweden,M,Spain,50,"Data Visualization, Python, TensorFlow, Docker, Statistics",Bachelor,1,Finance,2024-11-02,2025-01-11,1707,8.4,Smart Analytics +AI03974,AI Software Engineer,56383,EUR,47926,EN,CT,Austria,S,Argentina,100,"Azure, AWS, NLP, Spark",PhD,0,Telecommunications,2024-12-05,2025-02-15,1841,8.8,Digital Transformation LLC +AI03975,AI Specialist,71225,USD,71225,EX,FL,India,S,India,0,"Git, MLOps, Deep Learning, Python",Master,19,Government,2024-10-14,2024-11-01,987,6.9,Cloud AI Solutions +AI03976,AI Consultant,64188,USD,64188,EN,CT,Sweden,M,Sweden,50,"Statistics, Hadoop, R, TensorFlow",Bachelor,1,Consulting,2024-06-04,2024-06-26,1597,7.2,AI Innovations +AI03977,Machine Learning Researcher,111850,USD,111850,MI,FT,Norway,S,Norway,0,"MLOps, Python, TensorFlow",PhD,2,Real Estate,2024-02-25,2024-03-21,2475,6.4,Algorithmic Solutions +AI03978,Machine Learning Engineer,193873,EUR,164792,EX,FT,Netherlands,M,Netherlands,0,"Scala, Kubernetes, Deep Learning, Java",Master,12,Real Estate,2024-11-10,2025-01-11,2444,8.6,Machine Intelligence Group +AI03979,Head of AI,69980,USD,69980,EX,CT,China,M,China,50,"Mathematics, PyTorch, Statistics, Kubernetes, Hadoop",PhD,17,Technology,2024-01-03,2024-02-05,1838,8.5,Future Systems +AI03980,AI Specialist,17744,USD,17744,EN,FT,India,S,Kenya,0,"AWS, Git, NLP",Master,1,Media,2025-03-11,2025-04-09,1086,7.8,DeepTech Ventures +AI03981,Research Scientist,55353,EUR,47050,EN,PT,France,L,France,100,"PyTorch, TensorFlow, Java, SQL, Mathematics",Associate,0,Consulting,2024-10-17,2024-12-10,1210,8.2,Neural Networks Co +AI03982,AI Specialist,29786,USD,29786,EN,PT,China,M,Latvia,50,"Spark, Statistics, Data Visualization",Bachelor,0,Telecommunications,2024-11-17,2025-01-19,2453,7.3,Advanced Robotics +AI03983,Machine Learning Researcher,75425,EUR,64111,MI,FT,France,M,France,100,"Python, Kubernetes, Deep Learning, Hadoop, R",Master,4,Telecommunications,2025-01-06,2025-02-04,1488,9.1,DeepTech Ventures +AI03984,Data Engineer,154886,EUR,131653,EX,FT,Austria,S,Australia,0,"Git, SQL, Python",Master,13,Gaming,2024-03-04,2024-04-17,2028,9.6,Advanced Robotics +AI03985,Data Engineer,99073,CAD,123841,SE,FT,Canada,M,Canada,0,"Git, Kubernetes, SQL, PyTorch, Hadoop",PhD,9,Automotive,2025-03-07,2025-04-25,1381,6.4,Quantum Computing Inc +AI03986,Head of AI,73454,EUR,62436,EN,FT,France,M,France,0,"Azure, Java, Docker",Bachelor,0,Telecommunications,2024-02-04,2024-02-29,2135,8.8,DataVision Ltd +AI03987,AI Consultant,59838,USD,59838,SE,CT,China,S,China,100,"Kubernetes, PyTorch, Linux, Computer Vision, MLOps",Associate,9,Government,2024-10-19,2024-12-31,2206,7.2,TechCorp Inc +AI03988,AI Consultant,87537,USD,87537,MI,FT,Israel,M,South Korea,0,"Java, Scala, Deep Learning, Azure",Master,2,Energy,2025-02-28,2025-04-22,2433,8.3,Predictive Systems +AI03989,AI Architect,26899,USD,26899,EN,CT,India,M,Estonia,0,"Scala, NLP, Docker",Master,0,Healthcare,2024-05-09,2024-07-19,1252,5.6,DataVision Ltd +AI03990,AI Architect,89970,USD,89970,SE,PT,South Korea,S,Germany,0,"R, MLOps, AWS",Bachelor,7,Telecommunications,2024-11-08,2025-01-03,809,5.6,Cognitive Computing +AI03991,Deep Learning Engineer,135427,USD,135427,SE,FL,Finland,L,Finland,50,"Java, GCP, Scala",PhD,6,Government,2025-03-24,2025-05-14,1411,6.9,Machine Intelligence Group +AI03992,NLP Engineer,55414,EUR,47102,EN,PT,Austria,M,Latvia,0,"Hadoop, Python, Spark, TensorFlow",PhD,0,Transportation,2025-01-27,2025-02-21,977,8.9,DataVision Ltd +AI03993,AI Architect,214757,CHF,193281,SE,CT,Switzerland,M,Switzerland,100,"Tableau, TensorFlow, Kubernetes, Azure",PhD,8,Energy,2024-08-26,2024-09-11,2055,8.7,Cloud AI Solutions +AI03994,AI Specialist,165695,USD,165695,SE,FL,United States,M,United States,50,"MLOps, Kubernetes, Deep Learning, Git",Associate,5,Finance,2025-02-24,2025-04-26,1087,7.7,Algorithmic Solutions +AI03995,AI Research Scientist,88990,USD,88990,EN,CT,Denmark,M,Denmark,50,"Python, TensorFlow, AWS",Master,0,Government,2025-02-19,2025-03-07,697,5.4,Advanced Robotics +AI03996,Head of AI,74202,GBP,55652,EN,FT,United Kingdom,M,United Kingdom,0,"Python, Kubernetes, GCP, Spark",Associate,1,Consulting,2025-01-24,2025-03-26,1970,6.7,Cognitive Computing +AI03997,Computer Vision Engineer,127421,USD,127421,EX,FT,Finland,S,Netherlands,100,"SQL, Docker, Tableau, PyTorch",Master,11,Healthcare,2024-04-12,2024-04-29,920,9.1,DeepTech Ventures +AI03998,Computer Vision Engineer,278984,CHF,251086,EX,PT,Switzerland,L,Austria,0,"Python, TensorFlow, MLOps, GCP, Data Visualization",Master,14,Finance,2024-02-11,2024-03-09,595,6.2,Smart Analytics +AI03999,Autonomous Systems Engineer,158896,USD,158896,SE,FT,Norway,S,Norway,0,"Data Visualization, Tableau, Hadoop, MLOps",Master,9,Technology,2024-03-19,2024-05-23,541,5.4,TechCorp Inc +AI04000,Robotics Engineer,135260,USD,135260,MI,FT,United States,L,United States,0,"Scala, Python, Hadoop, TensorFlow",PhD,2,Consulting,2024-01-29,2024-02-19,1479,5.3,TechCorp Inc +AI04001,AI Architect,75021,EUR,63768,MI,FT,Austria,S,Colombia,50,"Java, R, Data Visualization, NLP",Bachelor,2,Government,2024-02-01,2024-03-04,1164,9.1,Machine Intelligence Group +AI04002,Head of AI,154992,EUR,131743,EX,FL,Austria,S,Austria,50,"Linux, Git, Spark",Associate,19,Automotive,2025-03-28,2025-04-22,1595,6.9,DataVision Ltd +AI04003,Robotics Engineer,190121,JPY,20913310,EX,FL,Japan,L,Japan,100,"Git, Linux, Deep Learning",PhD,11,Government,2024-04-16,2024-06-21,1539,7.5,Predictive Systems +AI04004,Machine Learning Engineer,385410,CHF,346869,EX,FL,Switzerland,L,Switzerland,0,"Data Visualization, Java, GCP",Bachelor,16,Real Estate,2024-12-18,2025-01-04,849,5.5,Cognitive Computing +AI04005,Computer Vision Engineer,100524,USD,100524,SE,FT,Israel,S,Chile,50,"TensorFlow, Hadoop, Kubernetes",Master,5,Real Estate,2025-03-09,2025-05-15,1296,7.4,DeepTech Ventures +AI04006,Machine Learning Researcher,277819,USD,277819,EX,PT,Denmark,M,Denmark,100,"Data Visualization, Python, SQL, Hadoop",Master,14,Gaming,2025-03-22,2025-05-02,1616,9.1,Autonomous Tech +AI04007,NLP Engineer,65703,AUD,88699,EN,FL,Australia,S,Australia,50,"Hadoop, TensorFlow, Python, NLP",Associate,1,Finance,2024-01-21,2024-03-02,532,8.9,Machine Intelligence Group +AI04008,Data Scientist,132522,EUR,112644,SE,FT,France,L,France,50,"Scala, PyTorch, Java, Deep Learning, Mathematics",PhD,6,Transportation,2024-04-13,2024-06-10,1844,7.3,TechCorp Inc +AI04009,Autonomous Systems Engineer,165364,EUR,140559,EX,FL,France,S,France,0,"Computer Vision, Tableau, Hadoop, R, Deep Learning",Master,11,Transportation,2025-04-07,2025-06-14,1602,5.7,Digital Transformation LLC +AI04010,Principal Data Scientist,106407,AUD,143649,SE,CT,Australia,S,Australia,0,"PyTorch, Hadoop, SQL, Azure",PhD,9,Technology,2024-08-07,2024-09-11,1007,5.1,Predictive Systems +AI04011,Autonomous Systems Engineer,72285,JPY,7951350,EN,CT,Japan,M,Turkey,50,"Python, Spark, Hadoop, Computer Vision, TensorFlow",Bachelor,0,Education,2024-02-16,2024-03-17,2400,6.7,Algorithmic Solutions +AI04012,Principal Data Scientist,105498,USD,105498,SE,FT,Finland,S,Finland,0,"Linux, R, Statistics, SQL, Java",Associate,8,Telecommunications,2024-03-20,2024-05-17,1901,9.7,DeepTech Ventures +AI04013,Autonomous Systems Engineer,93513,EUR,79486,MI,CT,Netherlands,S,Netherlands,50,"R, Python, Tableau, Git",Bachelor,3,Energy,2024-10-14,2024-11-17,915,7.7,Cognitive Computing +AI04014,Data Scientist,56370,USD,56370,EN,PT,Finland,M,Finland,0,"MLOps, Python, Docker",PhD,0,Real Estate,2024-02-08,2024-03-27,722,7.5,Future Systems +AI04015,Computer Vision Engineer,111901,EUR,95116,MI,FT,France,L,Indonesia,50,"Scala, Linux, Java, Git, Statistics",Associate,2,Healthcare,2025-03-14,2025-04-07,750,9.7,Cognitive Computing +AI04016,AI Product Manager,250059,USD,250059,EX,CT,Denmark,S,Denmark,0,"Python, TensorFlow, Hadoop, Mathematics, Computer Vision",Associate,18,Telecommunications,2024-09-18,2024-10-22,2174,6.3,Neural Networks Co +AI04017,Research Scientist,273161,USD,273161,EX,CT,Denmark,M,Switzerland,50,"PyTorch, Tableau, Deep Learning, Statistics",Bachelor,19,Consulting,2024-11-21,2024-12-06,612,5.3,Quantum Computing Inc +AI04018,Data Engineer,132189,EUR,112361,SE,FL,Germany,S,Estonia,100,"Linux, Data Visualization, Scala",Master,8,Education,2025-01-23,2025-03-28,1573,6.8,Autonomous Tech +AI04019,AI Architect,66589,EUR,56601,EN,PT,Germany,M,Germany,50,"Linux, Java, NLP",Associate,0,Real Estate,2024-04-14,2024-05-18,1587,9.5,Smart Analytics +AI04020,Data Analyst,60676,EUR,51575,EN,FL,France,M,Singapore,0,"Computer Vision, GCP, Python, Spark, TensorFlow",Bachelor,0,Education,2024-05-27,2024-06-23,1379,8.3,Quantum Computing Inc +AI04021,Principal Data Scientist,109570,CAD,136963,SE,CT,Canada,M,Romania,0,"GCP, Azure, Data Visualization, AWS",PhD,9,Government,2024-12-17,2025-01-15,2415,5.9,DeepTech Ventures +AI04022,Machine Learning Engineer,58052,USD,58052,EN,FT,Israel,S,France,50,"Git, Statistics, MLOps, Azure",Associate,1,Consulting,2024-08-18,2024-10-19,1438,7.2,DeepTech Ventures +AI04023,AI Research Scientist,98945,EUR,84103,MI,FL,Austria,M,Austria,0,"MLOps, PyTorch, Git, AWS",Associate,3,Manufacturing,2024-12-06,2025-01-26,1831,9.1,Algorithmic Solutions +AI04024,AI Product Manager,199637,USD,199637,EX,CT,Israel,L,Israel,100,"Java, Linux, Hadoop",Bachelor,12,Consulting,2024-02-08,2024-02-24,2356,9.9,TechCorp Inc +AI04025,AI Software Engineer,78109,USD,78109,MI,PT,Finland,S,Finland,50,"NLP, Git, Hadoop, Docker",Master,4,Consulting,2024-04-07,2024-05-19,1816,8.6,Predictive Systems +AI04026,AI Software Engineer,73974,USD,73974,MI,FL,Israel,M,Malaysia,0,"Python, GCP, Tableau",Associate,4,Automotive,2024-03-20,2024-04-14,1538,6,Cloud AI Solutions +AI04027,AI Software Engineer,134116,EUR,113999,SE,PT,France,M,France,100,"NLP, SQL, MLOps",Bachelor,7,Manufacturing,2024-05-25,2024-06-16,832,5.2,Digital Transformation LLC +AI04028,Deep Learning Engineer,135851,USD,135851,SE,CT,Finland,L,Ghana,100,"Docker, AWS, Tableau, GCP, TensorFlow",Associate,7,Consulting,2024-09-21,2024-10-14,543,8.9,Digital Transformation LLC +AI04029,Deep Learning Engineer,142460,USD,142460,SE,PT,Ireland,M,Thailand,100,"Tableau, Statistics, Linux, Mathematics, Deep Learning",Master,5,Education,2024-04-02,2024-04-20,697,6.5,AI Innovations +AI04030,Head of AI,69316,USD,69316,EN,PT,Denmark,S,Japan,50,"SQL, Spark, GCP",Associate,0,Government,2024-04-05,2024-04-24,862,8.1,DataVision Ltd +AI04031,Deep Learning Engineer,82158,EUR,69834,EN,FT,France,L,France,50,"AWS, MLOps, SQL, PyTorch, Git",Associate,1,Retail,2024-05-17,2024-06-22,1467,5.6,Machine Intelligence Group +AI04032,AI Product Manager,167922,USD,167922,SE,PT,Ireland,L,Ireland,100,"SQL, AWS, MLOps",Master,5,Healthcare,2024-12-03,2024-12-24,824,9.4,Quantum Computing Inc +AI04033,NLP Engineer,142118,EUR,120800,SE,FL,Austria,L,Austria,100,"Python, Git, SQL, AWS",Associate,8,Manufacturing,2024-07-06,2024-08-18,1172,5.8,Cognitive Computing +AI04034,Deep Learning Engineer,215397,USD,215397,EX,FT,Israel,S,Israel,50,"Data Visualization, Statistics, Hadoop, Deep Learning, Docker",Associate,15,Retail,2024-10-07,2024-12-07,2434,7.6,Quantum Computing Inc +AI04035,Research Scientist,294594,CHF,265135,EX,FT,Switzerland,L,China,0,"Data Visualization, AWS, SQL, PyTorch, Java",Associate,10,Manufacturing,2024-06-23,2024-07-07,1111,5.5,TechCorp Inc +AI04036,AI Specialist,63057,USD,63057,EN,CT,United States,M,United States,50,"NLP, Scala, Data Visualization",Associate,1,Energy,2024-07-30,2024-08-27,2384,10,Cloud AI Solutions +AI04037,ML Ops Engineer,217874,EUR,185193,EX,FL,Austria,M,Portugal,100,"Java, Hadoop, Computer Vision, R, Python",Master,19,Education,2024-08-26,2024-10-09,2330,9.6,Smart Analytics +AI04038,Autonomous Systems Engineer,32792,USD,32792,SE,PT,India,S,India,50,"GCP, Python, SQL, R",Associate,8,Gaming,2024-10-05,2024-12-16,2354,7.7,Advanced Robotics +AI04039,ML Ops Engineer,116266,JPY,12789260,SE,CT,Japan,M,Japan,100,"Kubernetes, Linux, Data Visualization, NLP, Docker",PhD,7,Education,2025-02-08,2025-03-07,1459,6,Future Systems +AI04040,AI Research Scientist,70410,EUR,59849,EN,FL,Austria,L,Austria,50,"PyTorch, Kubernetes, Docker, TensorFlow",PhD,1,Technology,2024-11-11,2024-12-14,1600,5.3,DeepTech Ventures +AI04041,Data Analyst,56897,CAD,71121,EN,FL,Canada,L,Canada,100,"Java, MLOps, R",PhD,1,Consulting,2024-09-04,2024-09-27,2164,8.6,Cognitive Computing +AI04042,Autonomous Systems Engineer,135997,CHF,122397,MI,PT,Switzerland,S,Ghana,100,"Linux, Python, Kubernetes, MLOps, Data Visualization",Associate,3,Technology,2024-05-14,2024-07-09,1556,7.9,Cloud AI Solutions +AI04043,Machine Learning Engineer,50494,USD,50494,EN,FT,Israel,S,Israel,100,"Git, Tableau, PyTorch, Kubernetes, Spark",Associate,1,Media,2024-09-07,2024-10-01,2213,6,DataVision Ltd +AI04044,AI Research Scientist,144481,GBP,108361,EX,PT,United Kingdom,S,United Kingdom,0,"Git, Linux, Data Visualization, Azure",Bachelor,13,Retail,2024-10-06,2024-12-06,1779,5.1,DeepTech Ventures +AI04045,Principal Data Scientist,102340,USD,102340,MI,FT,Ireland,M,Ireland,50,"GCP, Computer Vision, Linux, Tableau",PhD,3,Retail,2024-06-04,2024-06-24,807,5.4,TechCorp Inc +AI04046,AI Research Scientist,289309,USD,289309,EX,FL,Denmark,S,Denmark,50,"Python, Azure, Tableau, Mathematics",Associate,19,Finance,2025-03-07,2025-04-25,557,7.2,Machine Intelligence Group +AI04047,AI Specialist,86564,GBP,64923,EN,PT,United Kingdom,L,United Kingdom,0,"Linux, Azure, TensorFlow",Associate,0,Education,2024-05-22,2024-06-30,2341,6.6,Cognitive Computing +AI04048,Computer Vision Engineer,105245,GBP,78934,MI,CT,United Kingdom,L,United Kingdom,0,"Spark, R, Computer Vision, Deep Learning, Python",Master,3,Government,2025-03-07,2025-04-04,2141,7.9,AI Innovations +AI04049,Principal Data Scientist,135249,USD,135249,EX,FT,Sweden,S,Sweden,100,"Mathematics, Git, Spark, SQL, PyTorch",Master,14,Energy,2024-09-23,2024-10-20,1386,8.8,Predictive Systems +AI04050,AI Research Scientist,351014,CHF,315913,EX,FT,Switzerland,L,Egypt,50,"Statistics, MLOps, Python, TensorFlow",Master,10,Consulting,2024-10-25,2024-12-13,922,5.8,Quantum Computing Inc +AI04051,Data Scientist,170313,GBP,127735,SE,PT,United Kingdom,L,United Kingdom,0,"Azure, Scala, Statistics, SQL, Deep Learning",Master,5,Gaming,2024-07-27,2024-08-29,1363,5.6,Algorithmic Solutions +AI04052,Autonomous Systems Engineer,96839,USD,96839,MI,FL,Israel,L,Israel,0,"Scala, Data Visualization, Computer Vision",Associate,3,Automotive,2025-02-16,2025-03-31,2388,9.8,DeepTech Ventures +AI04053,Machine Learning Engineer,112039,USD,112039,EX,CT,South Korea,M,South Korea,0,"TensorFlow, GCP, Scala",Bachelor,16,Finance,2024-10-01,2024-12-06,1359,5.5,Future Systems +AI04054,Autonomous Systems Engineer,161578,GBP,121184,SE,FL,United Kingdom,L,United Kingdom,50,"Python, Linux, Kubernetes, Git, GCP",PhD,9,Energy,2024-03-23,2024-04-19,538,8.7,Quantum Computing Inc +AI04055,Deep Learning Engineer,162342,USD,162342,SE,CT,United States,L,United States,0,"Deep Learning, SQL, Scala",Associate,7,Manufacturing,2025-03-11,2025-05-06,1837,6.3,Autonomous Tech +AI04056,AI Software Engineer,81152,CAD,101440,MI,FL,Canada,M,Indonesia,50,"Mathematics, Hadoop, SQL, Python, Data Visualization",Master,3,Media,2024-01-16,2024-03-15,1532,5.1,DeepTech Ventures +AI04057,Robotics Engineer,146791,EUR,124772,SE,PT,Germany,L,Germany,50,"MLOps, Git, Kubernetes",Bachelor,6,Media,2024-11-07,2024-12-21,661,6.9,Predictive Systems +AI04058,AI Architect,231457,SGD,300894,EX,FL,Singapore,M,Singapore,0,"Computer Vision, TensorFlow, Linux, Tableau",Associate,13,Manufacturing,2024-01-28,2024-03-28,671,6.5,Cognitive Computing +AI04059,Data Scientist,114857,EUR,97628,SE,PT,Austria,S,Argentina,0,"Python, TensorFlow, Tableau, NLP",Associate,7,Manufacturing,2024-06-26,2024-07-27,1809,9.5,Future Systems +AI04060,Computer Vision Engineer,73750,USD,73750,EX,CT,China,L,China,50,"Spark, PyTorch, SQL, Computer Vision",Associate,15,Gaming,2024-07-29,2024-09-12,1258,9.7,TechCorp Inc +AI04061,Data Engineer,87162,SGD,113311,EN,FL,Singapore,L,Singapore,50,"Computer Vision, Spark, Python, Scala",Bachelor,0,Real Estate,2024-10-20,2024-11-29,979,9.8,Autonomous Tech +AI04062,Machine Learning Engineer,85264,USD,85264,EX,CT,China,M,China,50,"Linux, Java, Docker, SQL, Git",Master,17,Education,2025-01-09,2025-02-11,1762,8.9,Digital Transformation LLC +AI04063,Principal Data Scientist,72355,CAD,90444,EN,FL,Canada,M,Canada,0,"Git, MLOps, Kubernetes, Hadoop",Associate,0,Energy,2024-11-15,2025-01-27,1357,5.3,TechCorp Inc +AI04064,ML Ops Engineer,83615,AUD,112880,MI,CT,Australia,S,Australia,50,"Git, Hadoop, Mathematics",Associate,4,Retail,2024-01-09,2024-02-05,2152,9.3,DataVision Ltd +AI04065,Machine Learning Researcher,201139,USD,201139,SE,FT,United States,L,Denmark,0,"Python, Azure, TensorFlow, Hadoop",PhD,8,Energy,2025-03-07,2025-04-17,2236,8.2,Digital Transformation LLC +AI04066,Research Scientist,227744,USD,227744,EX,FT,Denmark,M,Denmark,50,"Docker, Mathematics, R, SQL, Computer Vision",Bachelor,11,Media,2025-02-23,2025-04-26,656,9.3,Predictive Systems +AI04067,Research Scientist,50231,CAD,62789,EN,PT,Canada,M,Canada,100,"Scala, Spark, SQL, Mathematics",Associate,1,Media,2024-07-17,2024-07-31,572,7.1,Machine Intelligence Group +AI04068,Data Analyst,149410,EUR,126999,EX,FT,Austria,M,Austria,50,"Kubernetes, PyTorch, MLOps",PhD,15,Automotive,2024-04-20,2024-06-19,941,9.2,AI Innovations +AI04069,Data Engineer,322650,CHF,290385,EX,FL,Switzerland,S,Switzerland,50,"NLP, Linux, Python",PhD,18,Consulting,2024-07-24,2024-08-24,1900,6.3,Autonomous Tech +AI04070,Head of AI,138075,CAD,172594,SE,FL,Canada,L,Canada,50,"GCP, Kubernetes, Data Visualization, SQL",Bachelor,8,Technology,2025-03-05,2025-04-21,2390,6.1,Cloud AI Solutions +AI04071,Data Engineer,70492,USD,70492,MI,FL,South Korea,L,South Korea,0,"NLP, R, Kubernetes, Linux, TensorFlow",Bachelor,4,Media,2024-09-10,2024-11-05,1832,8.5,DataVision Ltd +AI04072,AI Architect,50946,USD,50946,EN,FT,South Korea,S,South Korea,0,"Deep Learning, Java, Computer Vision, AWS, Kubernetes",Associate,0,Transportation,2024-05-11,2024-07-06,1102,7.1,Autonomous Tech +AI04073,AI Architect,74567,JPY,8202370,EN,FT,Japan,M,Sweden,0,"TensorFlow, Linux, Python, SQL, AWS",Associate,1,Manufacturing,2024-02-19,2024-03-15,514,5.3,Cognitive Computing +AI04074,Machine Learning Engineer,63683,AUD,85972,EN,CT,Australia,L,Australia,100,"Python, NLP, GCP, Mathematics, Git",Associate,0,Government,2024-12-08,2025-01-07,1692,5.7,TechCorp Inc +AI04075,AI Product Manager,93281,USD,93281,EN,FT,United States,L,Ukraine,100,"Hadoop, Python, Azure, Spark, Statistics",Bachelor,1,Technology,2024-08-20,2024-10-15,1066,6.7,Cloud AI Solutions +AI04076,Deep Learning Engineer,86606,CAD,108258,MI,PT,Canada,S,Ireland,0,"Docker, Scala, Linux",Bachelor,3,Media,2024-05-08,2024-06-29,573,6.2,Smart Analytics +AI04077,AI Software Engineer,114314,EUR,97167,SE,CT,France,M,France,100,"Azure, Git, Hadoop, Data Visualization, Mathematics",PhD,7,Media,2024-09-26,2024-11-11,743,5.1,AI Innovations +AI04078,Machine Learning Researcher,44105,USD,44105,SE,PT,India,L,India,0,"Java, Hadoop, MLOps",PhD,6,Retail,2024-07-10,2024-09-01,724,5.7,Future Systems +AI04079,AI Specialist,87807,EUR,74636,MI,FT,Austria,L,Austria,50,"PyTorch, Git, Java, Scala, TensorFlow",Bachelor,3,Automotive,2024-03-30,2024-04-19,2006,7.2,AI Innovations +AI04080,Principal Data Scientist,105998,AUD,143097,MI,FT,Australia,L,Australia,100,"Spark, Tableau, GCP, Linux, Hadoop",Bachelor,4,Energy,2024-09-05,2024-11-16,1627,7.3,Cloud AI Solutions +AI04081,Deep Learning Engineer,205845,CHF,185261,SE,CT,Switzerland,M,Portugal,0,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Associate,9,Telecommunications,2024-03-05,2024-04-06,2211,8.5,Machine Intelligence Group +AI04082,AI Architect,108031,SGD,140440,SE,CT,Singapore,S,Singapore,50,"Mathematics, Azure, PyTorch",Associate,6,Manufacturing,2024-09-20,2024-10-30,1358,9.2,DeepTech Ventures +AI04083,AI Consultant,43599,USD,43599,MI,PT,China,S,China,50,"MLOps, R, TensorFlow, SQL, GCP",Associate,4,Media,2024-02-23,2024-05-01,2059,6.4,Quantum Computing Inc +AI04084,Data Scientist,100782,GBP,75587,MI,FL,United Kingdom,S,United Kingdom,100,"Mathematics, R, SQL, Spark",Bachelor,3,Manufacturing,2025-02-21,2025-04-09,2245,9.9,Algorithmic Solutions +AI04085,Autonomous Systems Engineer,124064,SGD,161283,SE,PT,Singapore,S,Israel,50,"Java, Scala, NLP, Azure",PhD,8,Gaming,2024-12-25,2025-02-16,1257,7.4,DataVision Ltd +AI04086,Head of AI,32020,USD,32020,EN,FL,China,L,China,100,"SQL, Hadoop, PyTorch, Linux",Associate,1,Media,2024-01-09,2024-01-30,878,8.5,Algorithmic Solutions +AI04087,Machine Learning Engineer,88815,USD,88815,MI,FL,Finland,M,Finland,50,"Linux, Java, Git, Mathematics, NLP",Bachelor,3,Finance,2024-08-21,2024-10-25,2150,6.1,Digital Transformation LLC +AI04088,Data Analyst,102567,CHF,92310,MI,FT,Switzerland,M,Switzerland,50,"Hadoop, Python, PyTorch",Master,4,Consulting,2025-01-14,2025-03-03,1066,7.6,Predictive Systems +AI04089,Computer Vision Engineer,72234,USD,72234,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, SQL, Python, Kubernetes",Associate,1,Telecommunications,2024-03-08,2024-05-01,1659,9.1,Algorithmic Solutions +AI04090,NLP Engineer,284726,CHF,256253,EX,FL,Switzerland,M,Italy,0,"Python, PyTorch, TensorFlow",Master,15,Gaming,2025-02-28,2025-05-07,697,6.5,Algorithmic Solutions +AI04091,Principal Data Scientist,103801,EUR,88231,MI,CT,Netherlands,M,Russia,50,"NLP, AWS, Linux, Statistics, Computer Vision",Master,3,Telecommunications,2025-02-22,2025-03-08,1806,5.2,Neural Networks Co +AI04092,AI Specialist,211598,EUR,179858,EX,FT,Germany,L,Israel,50,"TensorFlow, Scala, Hadoop, Deep Learning, PyTorch",Master,10,Manufacturing,2024-11-18,2025-01-20,1067,6.5,Cloud AI Solutions +AI04093,Principal Data Scientist,65479,GBP,49109,EN,CT,United Kingdom,M,Portugal,50,"GCP, Kubernetes, SQL",Associate,1,Manufacturing,2024-08-06,2024-10-05,2120,8.9,DataVision Ltd +AI04094,ML Ops Engineer,55701,CAD,69626,EN,CT,Canada,S,Canada,50,"Azure, PyTorch, Git",Associate,1,Energy,2024-10-09,2024-12-21,1684,9,TechCorp Inc +AI04095,Machine Learning Researcher,265222,CHF,238700,EX,CT,Switzerland,S,Switzerland,0,"Git, Azure, Spark, Mathematics, AWS",Master,14,Gaming,2025-03-09,2025-03-27,1418,9.8,TechCorp Inc +AI04096,NLP Engineer,33734,USD,33734,MI,FT,China,S,China,50,"R, SQL, NLP, Azure",Associate,4,Gaming,2024-04-27,2024-06-29,964,7.2,Smart Analytics +AI04097,AI Software Engineer,69684,USD,69684,MI,FT,South Korea,S,Spain,50,"Git, R, Tableau, SQL",Bachelor,3,Energy,2025-02-01,2025-03-03,850,7.1,Future Systems +AI04098,AI Specialist,96701,AUD,130546,MI,FT,Australia,L,Australia,50,"PyTorch, Hadoop, Git",Master,4,Technology,2024-07-20,2024-09-30,1167,9.2,Predictive Systems +AI04099,Deep Learning Engineer,180946,USD,180946,EX,FL,Ireland,M,Ireland,50,"Scala, AWS, Git, Hadoop",Bachelor,19,Finance,2024-12-14,2025-01-31,1194,8.5,Advanced Robotics +AI04100,Data Analyst,166915,USD,166915,EX,FL,Finland,M,Finland,100,"Java, PyTorch, Kubernetes, Mathematics, Data Visualization",Associate,12,Technology,2025-02-04,2025-04-08,880,5.2,AI Innovations +AI04101,Autonomous Systems Engineer,121685,USD,121685,SE,FL,Sweden,M,Sweden,0,"Data Visualization, Deep Learning, Python, Statistics",Bachelor,9,Consulting,2024-03-13,2024-05-15,1830,5.2,TechCorp Inc +AI04102,Research Scientist,167790,USD,167790,SE,FL,Norway,L,Norway,100,"Linux, NLP, Python",Bachelor,6,Government,2025-02-27,2025-03-16,1947,9.7,DeepTech Ventures +AI04103,Robotics Engineer,80516,EUR,68439,EN,CT,Netherlands,M,Netherlands,0,"Scala, Git, SQL, Python",PhD,1,Media,2024-09-13,2024-10-21,1007,6,Cognitive Computing +AI04104,Data Scientist,100310,GBP,75233,MI,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Docker, GCP",Associate,2,Education,2024-01-18,2024-03-05,1460,7.7,Cognitive Computing +AI04105,Research Scientist,120643,USD,120643,SE,FT,Sweden,M,Sweden,0,"Docker, R, Deep Learning, Java, Computer Vision",Associate,6,Technology,2025-04-21,2025-06-23,817,7.2,Cognitive Computing +AI04106,AI Architect,68168,EUR,57943,MI,PT,Austria,S,Austria,100,"PyTorch, Linux, SQL, GCP, R",Bachelor,3,Telecommunications,2025-01-09,2025-02-22,2194,5.9,TechCorp Inc +AI04107,Data Engineer,103407,USD,103407,EX,FL,India,L,India,0,"Python, NLP, Statistics",Master,17,Government,2024-10-30,2024-12-23,2100,6.4,Cognitive Computing +AI04108,Principal Data Scientist,79353,JPY,8728830,EN,FT,Japan,M,Japan,0,"GCP, PyTorch, NLP",PhD,0,Telecommunications,2024-05-04,2024-06-19,1235,7,AI Innovations +AI04109,Principal Data Scientist,215826,GBP,161870,EX,FT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Azure, R, Statistics",Associate,14,Telecommunications,2024-04-03,2024-05-25,886,8.7,DeepTech Ventures +AI04110,Data Analyst,124330,EUR,105681,MI,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Deep Learning",Master,3,Retail,2024-12-12,2025-02-19,1635,5.3,Advanced Robotics +AI04111,Machine Learning Engineer,53595,EUR,45556,EN,FT,France,M,Luxembourg,100,"NLP, Git, Docker, Hadoop, Spark",Master,0,Consulting,2024-09-19,2024-11-06,1568,5.2,Advanced Robotics +AI04112,AI Research Scientist,141469,EUR,120249,EX,FL,Germany,S,Germany,0,"R, Python, Computer Vision",Master,14,Transportation,2024-06-08,2024-08-02,1693,6.5,Predictive Systems +AI04113,Computer Vision Engineer,115046,USD,115046,MI,FT,Sweden,L,Sweden,100,"Kubernetes, AWS, GCP, Scala",Master,4,Media,2025-03-14,2025-05-23,739,8,Predictive Systems +AI04114,Machine Learning Engineer,147907,CHF,133116,MI,PT,Switzerland,M,Egypt,0,"SQL, AWS, Scala, Tableau",Associate,4,Automotive,2025-03-11,2025-04-01,1372,8.8,Machine Intelligence Group +AI04115,AI Product Manager,50641,USD,50641,EX,FL,India,S,Hungary,50,"Data Visualization, GCP, R, Hadoop",PhD,19,Healthcare,2024-06-19,2024-08-25,1905,9.3,DataVision Ltd +AI04116,AI Product Manager,214441,EUR,182275,EX,FL,Netherlands,M,Philippines,0,"Linux, Scala, Python, NLP, Mathematics",PhD,10,Manufacturing,2024-02-19,2024-03-29,2265,6.3,Future Systems +AI04117,Computer Vision Engineer,114417,GBP,85813,MI,FL,United Kingdom,M,United Kingdom,50,"Python, R, Mathematics",PhD,2,Technology,2024-03-28,2024-05-14,2050,9.9,Digital Transformation LLC +AI04118,AI Consultant,112932,JPY,12422520,MI,FT,Japan,L,Japan,100,"Scala, Computer Vision, NLP, PyTorch, Spark",Bachelor,4,Healthcare,2025-03-03,2025-04-08,2449,9.3,Autonomous Tech +AI04119,ML Ops Engineer,72211,USD,72211,EN,CT,Israel,L,Israel,0,"Git, Scala, SQL, Mathematics",Bachelor,0,Retail,2024-04-16,2024-05-05,2062,9.8,Cognitive Computing +AI04120,Deep Learning Engineer,182222,AUD,246000,EX,CT,Australia,L,Spain,100,"Azure, Deep Learning, Java",Master,18,Energy,2024-10-01,2024-11-06,1155,7.2,AI Innovations +AI04121,Machine Learning Engineer,83596,EUR,71057,EN,FT,Germany,L,Germany,50,"Data Visualization, NLP, Kubernetes, Python",PhD,0,Government,2025-01-04,2025-03-18,1822,5.2,Future Systems +AI04122,NLP Engineer,109011,CHF,98110,EN,FT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Data Visualization, R",Associate,1,Consulting,2024-01-25,2024-03-12,2002,8.6,DataVision Ltd +AI04123,Deep Learning Engineer,74573,AUD,100674,EN,PT,Australia,L,Australia,0,"Git, Python, Mathematics, Tableau, Docker",PhD,0,Retail,2024-10-21,2024-12-26,926,8.1,Cognitive Computing +AI04124,Principal Data Scientist,117158,EUR,99584,MI,PT,Netherlands,L,Philippines,50,"Python, TensorFlow, Git, Computer Vision, Azure",Master,2,Consulting,2024-11-19,2024-12-17,1918,6.4,Future Systems +AI04125,Head of AI,84442,JPY,9288620,MI,FL,Japan,M,Sweden,50,"SQL, TensorFlow, Mathematics",PhD,2,Telecommunications,2024-12-30,2025-02-23,1372,6.8,Cloud AI Solutions +AI04126,Machine Learning Researcher,64765,USD,64765,EX,FL,India,L,Brazil,100,"PyTorch, Scala, Hadoop, Computer Vision",PhD,11,Media,2024-05-14,2024-06-24,1270,5.8,Algorithmic Solutions +AI04127,Data Scientist,161364,USD,161364,SE,FT,Norway,S,Norway,100,"AWS, MLOps, SQL, Azure",Bachelor,9,Real Estate,2024-02-27,2024-04-29,1176,6.5,Algorithmic Solutions +AI04128,Data Scientist,259567,AUD,350415,EX,PT,Australia,L,Australia,0,"GCP, Docker, Python, Azure, Data Visualization",Master,11,Government,2025-03-23,2025-05-11,789,10,Smart Analytics +AI04129,Machine Learning Engineer,58926,USD,58926,MI,FT,South Korea,S,Finland,0,"Statistics, PyTorch, Java, Scala, Azure",Bachelor,3,Education,2024-05-19,2024-07-04,1330,9.8,Smart Analytics +AI04130,Machine Learning Researcher,205317,USD,205317,SE,FL,United States,L,Argentina,100,"Scala, AWS, Tableau",Associate,7,Government,2024-10-25,2024-12-18,2425,7.3,Neural Networks Co +AI04131,Robotics Engineer,142793,CHF,128514,MI,PT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Mathematics, Statistics, GCP",Bachelor,4,Telecommunications,2024-06-19,2024-08-18,1439,7,Algorithmic Solutions +AI04132,AI Architect,48948,USD,48948,SE,FL,India,L,India,50,"Git, GCP, Python, AWS, NLP",Bachelor,5,Technology,2024-08-30,2024-09-19,2439,8.5,Neural Networks Co +AI04133,Machine Learning Engineer,101284,USD,101284,MI,FL,Ireland,M,Ireland,0,"Kubernetes, Docker, R, Azure",Bachelor,2,Finance,2024-05-07,2024-06-14,2361,7.2,Future Systems +AI04134,Autonomous Systems Engineer,94804,USD,94804,MI,CT,South Korea,L,Vietnam,100,"SQL, PyTorch, GCP",Associate,2,Finance,2025-04-20,2025-06-25,1817,8.7,Cognitive Computing +AI04135,AI Consultant,55274,SGD,71856,EN,FT,Singapore,S,Singapore,0,"Python, TensorFlow, Spark, Deep Learning",Associate,1,Real Estate,2024-12-13,2025-02-04,1539,8.1,DataVision Ltd +AI04136,Machine Learning Engineer,46056,EUR,39148,EN,CT,France,S,France,100,"Kubernetes, Scala, GCP",Associate,1,Government,2024-07-03,2024-09-12,2123,7.8,Smart Analytics +AI04137,AI Research Scientist,71471,SGD,92912,EN,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, NLP, Deep Learning, Scala",Master,0,Education,2024-07-31,2024-09-20,989,6.3,Quantum Computing Inc +AI04138,Data Analyst,173574,AUD,234325,EX,CT,Australia,S,Australia,0,"Linux, Hadoop, R",Master,12,Finance,2025-03-07,2025-04-30,832,5.8,AI Innovations +AI04139,AI Software Engineer,228777,CAD,285971,EX,PT,Canada,L,Canada,0,"Scala, Deep Learning, Data Visualization, Kubernetes, Statistics",PhD,18,Energy,2024-10-02,2024-10-24,2368,8.5,Algorithmic Solutions +AI04140,Data Engineer,218206,AUD,294578,EX,FL,Australia,M,Australia,0,"Linux, TensorFlow, Statistics, Python, Computer Vision",PhD,17,Technology,2025-04-27,2025-06-05,2119,5.6,Digital Transformation LLC +AI04141,Autonomous Systems Engineer,218548,EUR,185766,EX,CT,Netherlands,L,Netherlands,100,"Git, Hadoop, Linux",Master,11,Energy,2024-11-08,2025-01-09,1487,9.7,Digital Transformation LLC +AI04142,Data Scientist,137310,EUR,116714,SE,FT,France,M,France,100,"Scala, NLP, Java, Kubernetes, Linux",PhD,5,Government,2024-10-27,2024-12-13,1017,5.8,Advanced Robotics +AI04143,Research Scientist,112353,EUR,95500,MI,CT,Netherlands,L,Netherlands,0,"PyTorch, GCP, Mathematics, Deep Learning",Associate,2,Media,2024-11-18,2025-01-29,1367,9.6,Algorithmic Solutions +AI04144,Data Analyst,217691,EUR,185037,EX,FT,Germany,M,Germany,50,"R, SQL, NLP",PhD,10,Real Estate,2025-01-17,2025-03-04,1455,9.8,Machine Intelligence Group +AI04145,Data Engineer,82416,EUR,70054,MI,FL,France,L,France,100,"Git, Tableau, Hadoop, Java, Linux",PhD,2,Telecommunications,2024-07-25,2024-08-08,1499,9.1,Machine Intelligence Group +AI04146,Data Engineer,271408,USD,271408,EX,CT,Finland,L,Finland,50,"Kubernetes, R, SQL",Associate,19,Real Estate,2025-02-22,2025-05-04,2037,5.3,Neural Networks Co +AI04147,Robotics Engineer,50767,USD,50767,EN,FT,Israel,M,Israel,100,"Kubernetes, Git, Python",Master,0,Government,2024-08-13,2024-10-04,735,9.7,DeepTech Ventures +AI04148,Computer Vision Engineer,110614,EUR,94022,SE,FT,France,L,France,100,"SQL, Python, Kubernetes",Master,6,Real Estate,2024-12-11,2025-01-01,1473,5.7,Autonomous Tech +AI04149,Computer Vision Engineer,92141,EUR,78320,MI,CT,Netherlands,M,Spain,100,"Scala, Python, Statistics, Deep Learning",PhD,3,Technology,2024-04-18,2024-05-15,1681,6.9,DeepTech Ventures +AI04150,Machine Learning Engineer,48318,USD,48318,EN,FL,South Korea,M,South Korea,50,"Spark, Kubernetes, Statistics",PhD,1,Retail,2025-04-08,2025-04-22,871,5.6,Cloud AI Solutions +AI04151,Research Scientist,263753,EUR,224190,EX,FL,Austria,L,Austria,100,"Linux, Python, Git, Spark",Bachelor,11,Automotive,2024-04-23,2024-06-02,850,8.3,Algorithmic Solutions +AI04152,Machine Learning Researcher,273323,CHF,245991,EX,PT,Switzerland,M,Switzerland,50,"SQL, Statistics, Tableau",PhD,12,Automotive,2025-04-10,2025-05-26,991,8.7,Machine Intelligence Group +AI04153,Research Scientist,62268,USD,62268,MI,FT,Finland,S,Vietnam,0,"Docker, SQL, Spark, Linux",Associate,2,Transportation,2025-02-21,2025-04-13,1843,6.9,Cognitive Computing +AI04154,NLP Engineer,116686,USD,116686,MI,FT,Ireland,L,Ireland,50,"Azure, SQL, Data Visualization, Python, Kubernetes",Master,2,Finance,2025-04-16,2025-06-21,2006,9.9,Smart Analytics +AI04155,AI Research Scientist,129353,EUR,109950,SE,FL,Germany,M,Germany,0,"Python, Deep Learning, Java",PhD,9,Finance,2024-12-29,2025-03-08,2476,8.5,Smart Analytics +AI04156,Principal Data Scientist,267772,EUR,227606,EX,FT,Netherlands,L,Netherlands,0,"Python, R, MLOps, GCP, Kubernetes",Master,15,Real Estate,2024-12-28,2025-02-11,1950,7.8,Quantum Computing Inc +AI04157,AI Architect,59923,EUR,50935,EN,CT,Netherlands,M,Netherlands,100,"R, Java, Mathematics, MLOps, NLP",Associate,1,Consulting,2025-02-04,2025-04-06,1615,7.1,AI Innovations +AI04158,Data Analyst,75531,USD,75531,EX,CT,India,L,India,0,"Java, R, Spark, MLOps",PhD,11,Manufacturing,2024-11-09,2025-01-18,1354,9.1,Quantum Computing Inc +AI04159,AI Specialist,71196,USD,71196,EN,FL,Israel,L,Chile,0,"Data Visualization, Deep Learning, Docker",Master,1,Transportation,2024-01-27,2024-03-21,2117,9.2,Neural Networks Co +AI04160,AI Specialist,88243,USD,88243,MI,FL,Sweden,S,Germany,50,"SQL, Java, PyTorch",Master,2,Automotive,2024-10-03,2024-10-24,1074,9,Future Systems +AI04161,Robotics Engineer,105621,JPY,11618310,SE,PT,Japan,S,Japan,100,"Python, R, GCP, MLOps, TensorFlow",Associate,7,Gaming,2024-06-03,2024-07-28,889,5.6,AI Innovations +AI04162,AI Product Manager,98658,CAD,123323,SE,CT,Canada,S,Canada,0,"SQL, Scala, Python",Associate,5,Consulting,2024-02-09,2024-03-23,1266,6.2,Algorithmic Solutions +AI04163,Machine Learning Researcher,61301,USD,61301,EX,FL,India,L,India,100,"Python, TensorFlow, GCP",Associate,10,Education,2024-03-19,2024-05-10,1512,7.6,Cognitive Computing +AI04164,Head of AI,170872,USD,170872,EX,FT,Norway,S,Norway,0,"AWS, Hadoop, Data Visualization",PhD,16,Consulting,2024-06-10,2024-07-06,1985,10,Smart Analytics +AI04165,AI Software Engineer,56083,USD,56083,EN,FT,South Korea,L,Nigeria,0,"Kubernetes, Hadoop, Statistics",Bachelor,1,Education,2024-12-06,2025-02-02,1313,8.6,DeepTech Ventures +AI04166,AI Architect,71351,EUR,60648,EN,FL,Netherlands,S,Netherlands,0,"Python, TensorFlow, Computer Vision, PyTorch, SQL",PhD,1,Finance,2024-11-15,2025-01-20,1598,6.3,Cloud AI Solutions +AI04167,Deep Learning Engineer,131806,AUD,177938,SE,CT,Australia,L,Australia,0,"TensorFlow, Linux, Java",Bachelor,6,Retail,2024-08-13,2024-10-04,2368,6.9,Neural Networks Co +AI04168,Head of AI,85952,USD,85952,EN,CT,Norway,M,Norway,50,"NLP, Data Visualization, TensorFlow, Linux",PhD,1,Automotive,2024-01-07,2024-02-24,1437,7.8,Cloud AI Solutions +AI04169,Head of AI,177858,SGD,231215,SE,FT,Singapore,L,Singapore,0,"TensorFlow, Mathematics, Docker, Tableau, Deep Learning",Associate,8,Education,2024-10-02,2024-10-23,1797,9.6,DeepTech Ventures +AI04170,Head of AI,210574,USD,210574,SE,FL,Denmark,L,Chile,0,"Hadoop, Scala, Python, Computer Vision, Deep Learning",Associate,9,Government,2024-08-24,2024-10-31,874,6.1,TechCorp Inc +AI04171,Computer Vision Engineer,96894,USD,96894,MI,FT,South Korea,L,Vietnam,100,"Scala, Spark, Data Visualization",Master,4,Gaming,2024-11-18,2025-01-25,1945,5.2,AI Innovations +AI04172,AI Research Scientist,137829,AUD,186069,EX,FL,Australia,M,Australia,100,"GCP, Hadoop, PyTorch, Spark, R",Bachelor,16,Energy,2024-11-03,2024-12-28,1831,7.4,Neural Networks Co +AI04173,Data Analyst,99906,USD,99906,MI,CT,Israel,M,Israel,50,"Kubernetes, SQL, Python, Deep Learning",Bachelor,4,Education,2024-05-30,2024-07-27,517,8,DeepTech Ventures +AI04174,AI Consultant,78189,CAD,97736,EN,FT,Canada,L,Canada,50,"Docker, GCP, Java, Mathematics",Bachelor,1,Retail,2024-06-21,2024-07-29,2449,5.3,DeepTech Ventures +AI04175,Head of AI,221259,JPY,24338490,EX,CT,Japan,L,Austria,100,"Python, SQL, Scala, Tableau",PhD,12,Energy,2025-01-22,2025-02-15,1106,8.1,AI Innovations +AI04176,Data Engineer,69907,GBP,52430,EN,CT,United Kingdom,S,United Kingdom,100,"GCP, Git, SQL, NLP",Bachelor,1,Retail,2024-09-15,2024-11-01,531,7,Predictive Systems +AI04177,Computer Vision Engineer,114573,EUR,97387,MI,CT,Germany,L,Germany,0,"Scala, TensorFlow, SQL",Master,4,Manufacturing,2024-02-22,2024-03-24,1045,8.9,Algorithmic Solutions +AI04178,Autonomous Systems Engineer,91770,CAD,114713,SE,PT,Canada,S,Canada,100,"Python, Deep Learning, TensorFlow, Hadoop, GCP",Master,7,Finance,2025-02-08,2025-03-04,1669,9.5,Autonomous Tech +AI04179,AI Research Scientist,97661,EUR,83012,SE,FT,Germany,S,Germany,0,"Scala, Data Visualization, Git, AWS, Hadoop",PhD,5,Healthcare,2024-12-24,2025-02-02,1681,7.9,Cognitive Computing +AI04180,Machine Learning Researcher,93001,USD,93001,SE,FT,Israel,S,Israel,0,"R, Kubernetes, AWS",Master,8,Healthcare,2024-05-23,2024-08-01,2033,7.1,Cloud AI Solutions +AI04181,Machine Learning Researcher,138207,CAD,172759,EX,FL,Canada,S,Canada,50,"AWS, Java, Data Visualization",Bachelor,19,Healthcare,2024-01-30,2024-02-22,1932,5.6,Future Systems +AI04182,ML Ops Engineer,87070,EUR,74010,MI,FT,Austria,L,Ghana,0,"Data Visualization, Kubernetes, SQL, Deep Learning, GCP",Bachelor,4,Real Estate,2024-02-17,2024-03-08,1838,5.7,Future Systems +AI04183,Research Scientist,102685,USD,102685,SE,FT,South Korea,S,Indonesia,0,"NLP, Kubernetes, PyTorch, Azure, Tableau",Bachelor,9,Consulting,2024-10-03,2024-11-26,1996,9,DataVision Ltd +AI04184,AI Consultant,36735,USD,36735,MI,CT,India,M,India,0,"Python, AWS, Data Visualization, TensorFlow, Spark",Associate,2,Media,2025-02-12,2025-03-19,1482,7.2,Cognitive Computing +AI04185,Machine Learning Researcher,141810,EUR,120539,EX,PT,Germany,M,Germany,100,"Kubernetes, Azure, Statistics, R, Tableau",Associate,18,Telecommunications,2024-04-09,2024-06-16,1488,5.2,Algorithmic Solutions +AI04186,Head of AI,44764,USD,44764,EN,FT,South Korea,M,South Korea,50,"Spark, Kubernetes, NLP, Python, Linux",Associate,1,Energy,2025-02-08,2025-02-27,910,9.1,Future Systems +AI04187,Machine Learning Engineer,251178,EUR,213501,EX,FL,Austria,L,Austria,0,"GCP, Scala, SQL, Deep Learning",Associate,15,Government,2024-08-10,2024-09-30,674,5,Digital Transformation LLC +AI04188,Autonomous Systems Engineer,293534,USD,293534,EX,CT,Norway,M,Norway,50,"Java, PyTorch, AWS, R, Hadoop",Associate,19,Healthcare,2025-04-13,2025-05-31,1581,5.8,DataVision Ltd +AI04189,Data Scientist,47064,USD,47064,EN,PT,Ireland,S,Ireland,0,"Python, Linux, Computer Vision, Azure",Master,1,Technology,2024-04-16,2024-05-26,941,9.6,TechCorp Inc +AI04190,NLP Engineer,133682,SGD,173787,SE,PT,Singapore,M,Singapore,100,"Data Visualization, Kubernetes, R, AWS, NLP",Master,6,Technology,2024-12-05,2025-02-11,1401,8.7,TechCorp Inc +AI04191,Machine Learning Researcher,104881,GBP,78661,SE,CT,United Kingdom,S,United Kingdom,0,"R, Scala, Linux",PhD,5,Real Estate,2024-12-20,2025-01-26,2075,7.9,Future Systems +AI04192,Data Scientist,93613,USD,93613,EX,FT,India,L,India,100,"Azure, PyTorch, Hadoop",Bachelor,11,Technology,2025-01-05,2025-02-06,672,5.7,AI Innovations +AI04193,AI Architect,207719,USD,207719,EX,FT,Sweden,S,Sweden,50,"Tableau, AWS, PyTorch",Associate,17,Consulting,2024-10-02,2024-12-12,1642,5.8,Autonomous Tech +AI04194,Data Scientist,169583,JPY,18654130,EX,FT,Japan,S,Japan,100,"Python, Statistics, Azure, Tableau, Scala",Associate,15,Transportation,2024-12-09,2025-02-18,2352,7.7,Digital Transformation LLC +AI04195,Data Scientist,102146,CHF,91931,EN,FT,Switzerland,M,Japan,0,"Python, Deep Learning, R",PhD,1,Technology,2025-01-07,2025-02-20,2109,5.2,Machine Intelligence Group +AI04196,AI Product Manager,171881,AUD,232039,SE,FL,Australia,L,Australia,50,"PyTorch, AWS, Data Visualization, Git, Deep Learning",PhD,6,Consulting,2024-05-12,2024-07-24,1188,8.1,AI Innovations +AI04197,Data Scientist,24066,USD,24066,EN,FT,India,S,France,0,"TensorFlow, Computer Vision, Python",Master,0,Finance,2024-12-26,2025-01-09,838,7.7,Cloud AI Solutions +AI04198,AI Architect,149018,EUR,126665,EX,PT,France,L,France,0,"TensorFlow, Docker, Spark, NLP",Associate,18,Finance,2024-09-03,2024-09-22,2468,7.6,Future Systems +AI04199,Principal Data Scientist,119622,AUD,161490,SE,PT,Australia,S,Australia,100,"AWS, Scala, Kubernetes, Mathematics",Bachelor,5,Consulting,2024-01-01,2024-03-14,1210,6.5,Smart Analytics +AI04200,Machine Learning Researcher,135418,USD,135418,SE,FT,Sweden,M,Sweden,0,"Kubernetes, GCP, Docker",PhD,8,Gaming,2024-02-15,2024-04-09,2215,6.1,Algorithmic Solutions +AI04201,Robotics Engineer,80410,GBP,60308,MI,PT,United Kingdom,M,United Kingdom,100,"Scala, PyTorch, NLP",Bachelor,2,Retail,2024-05-12,2024-07-04,2221,8,Predictive Systems +AI04202,AI Architect,158403,JPY,17424330,SE,PT,Japan,M,Netherlands,0,"R, Kubernetes, Git",PhD,6,Real Estate,2024-03-15,2024-05-05,2333,8.8,Machine Intelligence Group +AI04203,Deep Learning Engineer,143401,EUR,121891,EX,CT,Austria,M,Austria,50,"Git, Computer Vision, Statistics, Kubernetes, Java",PhD,18,Telecommunications,2024-01-26,2024-04-04,2218,9.7,Advanced Robotics +AI04204,NLP Engineer,72505,USD,72505,MI,CT,Israel,S,Israel,0,"SQL, Linux, Scala",Bachelor,2,Gaming,2025-04-26,2025-06-01,2155,6.3,Digital Transformation LLC +AI04205,Principal Data Scientist,101052,EUR,85894,MI,CT,France,L,France,100,"Java, Python, Mathematics, GCP, Spark",Bachelor,3,Real Estate,2024-09-09,2024-11-13,2376,6,Algorithmic Solutions +AI04206,Robotics Engineer,90464,CAD,113080,MI,FT,Canada,S,Canada,50,"Scala, Kubernetes, Mathematics, Tableau, Hadoop",Master,3,Finance,2024-11-29,2025-01-16,1450,5.1,DeepTech Ventures +AI04207,Machine Learning Engineer,155870,USD,155870,EX,CT,Finland,M,Finland,100,"GCP, SQL, PyTorch, Data Visualization",Bachelor,18,Technology,2024-06-03,2024-08-08,2068,8.4,TechCorp Inc +AI04208,Autonomous Systems Engineer,86105,USD,86105,EX,FL,India,M,India,100,"TensorFlow, Linux, Azure, Kubernetes, Spark",Associate,16,Finance,2025-01-30,2025-03-07,2236,7.9,Algorithmic Solutions +AI04209,AI Software Engineer,60304,EUR,51258,EN,PT,Germany,M,Germany,100,"SQL, Scala, Azure",Master,1,Media,2024-09-27,2024-12-04,1530,8.9,Algorithmic Solutions +AI04210,NLP Engineer,158258,USD,158258,SE,CT,Denmark,S,Denmark,50,"NLP, MLOps, Python, Deep Learning",Master,8,Finance,2024-07-18,2024-08-18,1416,9.5,Future Systems +AI04211,Robotics Engineer,139108,USD,139108,SE,FT,Denmark,M,Hungary,50,"GCP, R, Spark, Data Visualization, Docker",PhD,7,Healthcare,2024-05-05,2024-05-19,2202,7.9,Advanced Robotics +AI04212,Robotics Engineer,127647,GBP,95735,SE,FL,United Kingdom,L,United Kingdom,50,"SQL, Kubernetes, TensorFlow, AWS, R",Master,8,Gaming,2024-06-22,2024-07-14,1248,8.1,Smart Analytics +AI04213,NLP Engineer,113026,CAD,141283,SE,FT,Canada,L,Canada,50,"NLP, Linux, Python, Deep Learning, Java",Associate,8,Gaming,2025-01-09,2025-02-21,1025,8.4,AI Innovations +AI04214,NLP Engineer,160446,USD,160446,EX,FT,United States,M,United States,50,"Mathematics, SQL, MLOps, PyTorch",Associate,16,Manufacturing,2024-04-26,2024-07-07,2148,5.5,AI Innovations +AI04215,Research Scientist,170414,USD,170414,SE,FT,Denmark,S,Denmark,50,"Kubernetes, Azure, Computer Vision",Associate,5,Gaming,2024-08-14,2024-09-16,2394,8.1,Predictive Systems +AI04216,Robotics Engineer,153701,USD,153701,EX,FT,Finland,L,France,100,"Spark, Kubernetes, Statistics",PhD,15,Telecommunications,2024-08-04,2024-09-08,641,6.6,Neural Networks Co +AI04217,AI Research Scientist,66536,SGD,86497,EN,FT,Singapore,M,Singapore,50,"Mathematics, SQL, Kubernetes",Bachelor,1,Government,2024-03-17,2024-04-17,952,9.9,Cloud AI Solutions +AI04218,Autonomous Systems Engineer,144573,USD,144573,EX,CT,South Korea,S,South Korea,100,"Linux, Statistics, GCP, Python, Computer Vision",PhD,18,Energy,2024-11-30,2025-02-10,1931,8,Quantum Computing Inc +AI04219,Autonomous Systems Engineer,39124,USD,39124,SE,FT,India,M,India,0,"Deep Learning, MLOps, Statistics, Spark",Master,5,Manufacturing,2024-10-12,2024-11-15,2309,5.7,Quantum Computing Inc +AI04220,Machine Learning Researcher,148877,EUR,126545,SE,FL,Netherlands,L,Netherlands,50,"Hadoop, Docker, NLP",Associate,5,Consulting,2024-06-28,2024-08-17,1349,9.8,Smart Analytics +AI04221,Research Scientist,62439,AUD,84293,EN,FT,Australia,S,Australia,100,"Java, Python, Kubernetes, GCP",Bachelor,1,Technology,2024-06-05,2024-06-29,1944,7.9,DeepTech Ventures +AI04222,Data Analyst,70705,USD,70705,MI,PT,South Korea,M,South Korea,0,"Data Visualization, Hadoop, Tableau, Mathematics, Linux",PhD,4,Healthcare,2025-01-21,2025-03-04,2030,5.6,DataVision Ltd +AI04223,AI Software Engineer,136064,USD,136064,EX,PT,Israel,M,Israel,100,"SQL, Python, Tableau",Master,13,Energy,2024-12-26,2025-01-14,2276,9.4,DataVision Ltd +AI04224,Machine Learning Researcher,114102,GBP,85577,SE,CT,United Kingdom,S,United Kingdom,50,"GCP, AWS, NLP",Bachelor,9,Manufacturing,2025-02-20,2025-03-15,515,9.1,Neural Networks Co +AI04225,ML Ops Engineer,48875,USD,48875,SE,CT,China,S,Germany,0,"Spark, PyTorch, Java, NLP",Associate,7,Education,2024-05-15,2024-06-07,843,10,Neural Networks Co +AI04226,ML Ops Engineer,66920,USD,66920,EN,CT,Denmark,M,Kenya,0,"Deep Learning, Linux, Computer Vision",Bachelor,1,Gaming,2025-02-18,2025-04-04,1486,7,AI Innovations +AI04227,Deep Learning Engineer,60046,USD,60046,EN,FT,United States,S,Australia,0,"Git, Scala, NLP, SQL, Azure",Bachelor,1,Transportation,2025-04-27,2025-06-06,992,7.9,Machine Intelligence Group +AI04228,Machine Learning Engineer,65824,EUR,55950,MI,FL,France,S,France,0,"Azure, GCP, Mathematics, Scala, TensorFlow",Associate,4,Government,2024-03-31,2024-05-26,639,9.4,Predictive Systems +AI04229,Computer Vision Engineer,92205,USD,92205,MI,FL,Finland,M,Finland,0,"Git, Spark, Deep Learning, AWS",Bachelor,4,Transportation,2024-06-18,2024-08-03,1381,5.8,DataVision Ltd +AI04230,Principal Data Scientist,69016,EUR,58664,MI,FL,Germany,S,Germany,50,"Spark, Linux, Kubernetes, Mathematics",Associate,2,Finance,2024-03-20,2024-04-26,954,6,Machine Intelligence Group +AI04231,AI Consultant,71384,USD,71384,EN,FL,Ireland,M,Ireland,100,"Python, Java, Deep Learning",PhD,0,Finance,2024-01-12,2024-02-27,1060,7.8,DataVision Ltd +AI04232,Data Scientist,63659,EUR,54110,EN,PT,Germany,S,United States,100,"GCP, SQL, Tableau, MLOps",Associate,0,Technology,2024-11-29,2025-01-18,1082,9.9,DeepTech Ventures +AI04233,AI Research Scientist,117611,GBP,88208,SE,FL,United Kingdom,M,Vietnam,0,"PyTorch, Tableau, Hadoop, TensorFlow, Statistics",Associate,7,Media,2025-01-05,2025-01-24,1849,6.6,Digital Transformation LLC +AI04234,Deep Learning Engineer,48074,USD,48074,EN,FL,Sweden,S,Sweden,0,"PyTorch, Python, Spark, Azure, SQL",Bachelor,0,Government,2024-12-26,2025-01-23,606,7.4,Future Systems +AI04235,Principal Data Scientist,122232,EUR,103897,SE,CT,Germany,S,Colombia,0,"R, Java, GCP, Python, Hadoop",Associate,8,Automotive,2025-02-27,2025-03-13,1471,5,Digital Transformation LLC +AI04236,Head of AI,197539,EUR,167908,EX,FL,France,L,Turkey,0,"Kubernetes, PyTorch, Docker, TensorFlow, Python",Master,13,Consulting,2025-01-01,2025-02-26,904,7,Cloud AI Solutions +AI04237,AI Specialist,255683,EUR,217331,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Tableau, Azure",Associate,18,Telecommunications,2024-03-15,2024-04-25,1130,9,Cognitive Computing +AI04238,Machine Learning Engineer,77121,USD,77121,EN,FL,Israel,L,Hungary,100,"SQL, Azure, PyTorch",Associate,1,Consulting,2024-10-06,2024-12-18,2312,6.9,Predictive Systems +AI04239,ML Ops Engineer,52575,USD,52575,MI,FL,China,L,South Africa,50,"Hadoop, Git, Python, Kubernetes",Bachelor,4,Finance,2025-01-23,2025-03-16,624,9.7,Machine Intelligence Group +AI04240,Autonomous Systems Engineer,86907,EUR,73871,SE,CT,Austria,S,Austria,100,"Spark, Data Visualization, AWS, R",Associate,6,Retail,2024-01-18,2024-03-11,733,7.3,Advanced Robotics +AI04241,Computer Vision Engineer,148771,EUR,126455,SE,CT,Germany,M,Germany,0,"Spark, Kubernetes, Deep Learning",Associate,6,Retail,2025-02-12,2025-02-26,2370,9.4,Autonomous Tech +AI04242,Deep Learning Engineer,124742,EUR,106031,SE,FL,Netherlands,L,Netherlands,0,"Python, Scala, Linux, Tableau, TensorFlow",Bachelor,7,Media,2024-11-13,2025-01-07,972,5.2,Cognitive Computing +AI04243,AI Specialist,80538,USD,80538,MI,PT,Sweden,M,Sweden,0,"Hadoop, Azure, Computer Vision, SQL, R",Bachelor,3,Manufacturing,2024-05-26,2024-07-25,1372,7.4,TechCorp Inc +AI04244,Deep Learning Engineer,261998,CHF,235798,EX,FT,Switzerland,S,Switzerland,0,"NLP, R, Computer Vision, Python, Azure",Bachelor,13,Energy,2024-01-21,2024-03-29,751,8.6,Future Systems +AI04245,Data Scientist,161380,JPY,17751800,EX,FT,Japan,M,Japan,0,"Python, Scala, Computer Vision, Hadoop",Master,13,Media,2024-05-14,2024-06-26,1306,6.2,Digital Transformation LLC +AI04246,Research Scientist,114449,USD,114449,SE,PT,Ireland,S,Thailand,0,"Scala, Git, SQL, NLP",PhD,8,Telecommunications,2024-04-22,2024-06-30,683,7.6,Autonomous Tech +AI04247,Robotics Engineer,65542,AUD,88482,EN,FT,Australia,M,Malaysia,0,"Java, Deep Learning, PyTorch, Data Visualization, Tableau",Associate,1,Education,2024-06-29,2024-09-01,1053,7,Predictive Systems +AI04248,Machine Learning Researcher,177905,JPY,19569550,EX,CT,Japan,M,Japan,100,"Kubernetes, SQL, Deep Learning",Bachelor,10,Transportation,2024-01-12,2024-03-07,1848,9.9,Cloud AI Solutions +AI04249,NLP Engineer,89958,SGD,116945,EN,FL,Singapore,L,Singapore,0,"Java, Docker, Deep Learning",Bachelor,1,Automotive,2025-01-04,2025-03-08,993,7.6,AI Innovations +AI04250,Data Scientist,50166,USD,50166,EN,CT,South Korea,S,South Korea,100,"Deep Learning, R, MLOps, Tableau, Scala",Associate,0,Automotive,2024-09-20,2024-11-21,1812,6.3,Cognitive Computing +AI04251,Research Scientist,153548,USD,153548,MI,FT,Denmark,L,Denmark,50,"Statistics, Spark, SQL",PhD,3,Manufacturing,2024-12-03,2025-01-01,977,6,Neural Networks Co +AI04252,AI Research Scientist,199709,CHF,179738,SE,CT,Switzerland,M,Switzerland,100,"GCP, R, NLP, Deep Learning",Associate,9,Consulting,2024-09-29,2024-11-07,992,5.7,Digital Transformation LLC +AI04253,Research Scientist,106748,USD,106748,SE,PT,South Korea,M,South Korea,50,"Scala, Kubernetes, SQL, NLP",Associate,5,Finance,2024-08-11,2024-10-05,501,5.7,Predictive Systems +AI04254,AI Consultant,164745,CHF,148271,SE,PT,Switzerland,S,Switzerland,100,"Computer Vision, NLP, Kubernetes, Scala, Java",Associate,6,Consulting,2024-04-08,2024-05-09,2246,7.6,Cloud AI Solutions +AI04255,Principal Data Scientist,74190,EUR,63062,MI,FL,Austria,S,Austria,0,"Java, PyTorch, Docker, Computer Vision, GCP",Associate,4,Energy,2024-06-10,2024-06-28,1983,9.9,Digital Transformation LLC +AI04256,AI Specialist,77889,EUR,66206,EN,FT,Netherlands,L,Netherlands,100,"Linux, Mathematics, MLOps",Associate,1,Transportation,2024-05-29,2024-07-24,517,6.5,Autonomous Tech +AI04257,Autonomous Systems Engineer,172285,EUR,146442,EX,PT,Austria,S,Austria,100,"Python, Java, Git, AWS, TensorFlow",Master,10,Automotive,2024-05-20,2024-07-15,1924,7.6,Machine Intelligence Group +AI04258,Robotics Engineer,192684,JPY,21195240,EX,FL,Japan,S,Japan,100,"Mathematics, TensorFlow, Deep Learning, Git, Spark",Associate,17,Manufacturing,2024-04-02,2024-05-25,509,5.2,Advanced Robotics +AI04259,Machine Learning Engineer,62085,USD,62085,SE,PT,China,L,China,50,"NLP, PyTorch, Kubernetes, Linux, SQL",Bachelor,6,Technology,2024-11-25,2025-01-24,2146,9.1,AI Innovations +AI04260,Autonomous Systems Engineer,70641,USD,70641,SE,FT,China,M,China,50,"Statistics, R, Python, Git",Master,9,Retail,2024-02-10,2024-03-13,960,9.9,Neural Networks Co +AI04261,Deep Learning Engineer,57845,AUD,78091,EN,CT,Australia,S,Australia,50,"Statistics, Python, PyTorch, R, Spark",Associate,1,Technology,2025-04-19,2025-05-15,1260,5.4,Quantum Computing Inc +AI04262,Deep Learning Engineer,70641,USD,70641,EX,PT,India,S,India,0,"Statistics, Tableau, R, Spark, GCP",Associate,18,Government,2024-10-30,2024-11-19,623,9.6,Autonomous Tech +AI04263,NLP Engineer,266056,SGD,345873,EX,FL,Singapore,L,Singapore,50,"SQL, PyTorch, NLP, Python",Associate,13,Transportation,2024-02-02,2024-03-01,1761,9.8,Digital Transformation LLC +AI04264,AI Software Engineer,39810,USD,39810,MI,PT,China,L,India,100,"PyTorch, Spark, Data Visualization, Kubernetes",Master,3,Telecommunications,2024-10-30,2024-12-17,1598,7.4,Algorithmic Solutions +AI04265,ML Ops Engineer,46834,USD,46834,MI,FT,China,L,China,0,"Git, GCP, AWS, Mathematics",Bachelor,3,Media,2024-06-30,2024-08-02,2086,7.2,AI Innovations +AI04266,Autonomous Systems Engineer,151336,GBP,113502,SE,FT,United Kingdom,L,United Kingdom,100,"Kubernetes, Python, Scala, GCP",Bachelor,7,Technology,2025-03-26,2025-04-16,930,7.3,Cloud AI Solutions +AI04267,AI Consultant,76149,EUR,64727,EN,PT,Austria,L,Austria,0,"Linux, Hadoop, Statistics, Scala, Mathematics",PhD,0,Technology,2025-04-08,2025-06-09,2299,9.7,Cognitive Computing +AI04268,AI Specialist,132231,USD,132231,EX,PT,Israel,S,Israel,100,"Tableau, Python, TensorFlow",Master,11,Automotive,2024-09-20,2024-11-24,526,6.7,Cognitive Computing +AI04269,AI Consultant,163387,USD,163387,SE,CT,Denmark,M,Denmark,50,"R, AWS, Git, Data Visualization",Bachelor,7,Transportation,2024-08-19,2024-10-30,635,5.8,DataVision Ltd +AI04270,Deep Learning Engineer,63017,SGD,81922,EN,CT,Singapore,M,Singapore,50,"Spark, Python, Java, Docker, Scala",Associate,1,Media,2024-12-10,2025-02-10,2238,5.3,Predictive Systems +AI04271,NLP Engineer,33704,USD,33704,MI,FT,India,S,Austria,0,"Java, Python, Mathematics, Git",PhD,4,Technology,2024-10-13,2024-12-18,1957,9.6,Smart Analytics +AI04272,NLP Engineer,199909,USD,199909,EX,CT,Finland,M,Finland,100,"Spark, Git, Linux, Statistics",Master,10,Technology,2024-08-31,2024-09-21,2126,7.7,Future Systems +AI04273,AI Specialist,109037,USD,109037,MI,PT,United States,M,United States,0,"Kubernetes, Python, PyTorch",PhD,2,Consulting,2024-04-29,2024-06-25,1905,6.3,Algorithmic Solutions +AI04274,Data Analyst,79918,EUR,67930,EN,FT,France,L,France,50,"Spark, Computer Vision, AWS, SQL",Associate,0,Gaming,2024-03-12,2024-04-05,2142,6.6,DataVision Ltd +AI04275,Data Analyst,140756,EUR,119643,EX,CT,Austria,S,Romania,50,"MLOps, Python, Tableau",PhD,12,Education,2025-03-06,2025-03-28,1437,5.1,Autonomous Tech +AI04276,Research Scientist,193092,CAD,241365,EX,CT,Canada,S,France,0,"Scala, Git, Data Visualization, Mathematics, Tableau",Associate,14,Automotive,2024-10-29,2024-11-12,2415,9.2,Quantum Computing Inc +AI04277,Head of AI,152328,USD,152328,MI,FT,Norway,L,Norway,50,"Java, Python, AWS",Associate,4,Healthcare,2024-10-09,2024-12-07,1932,6.3,Advanced Robotics +AI04278,NLP Engineer,115808,USD,115808,MI,FL,Norway,L,Norway,100,"Python, TensorFlow, Mathematics, Scala",Bachelor,3,Telecommunications,2024-03-27,2024-04-29,1892,7.4,Cognitive Computing +AI04279,Head of AI,123117,EUR,104649,SE,CT,Austria,S,Austria,50,"Git, AWS, Docker",Bachelor,6,Automotive,2025-01-14,2025-03-02,951,6.4,DataVision Ltd +AI04280,AI Architect,48031,USD,48031,EN,CT,Israel,S,New Zealand,100,"PyTorch, Mathematics, MLOps, SQL, Deep Learning",PhD,1,Automotive,2024-05-15,2024-06-08,1171,6.9,DeepTech Ventures +AI04281,Research Scientist,267720,USD,267720,EX,FL,United States,S,United States,100,"Tableau, Scala, Hadoop, SQL, Kubernetes",Master,16,Technology,2024-07-19,2024-08-30,2497,9.6,Neural Networks Co +AI04282,Head of AI,130274,JPY,14330140,SE,FT,Japan,L,Luxembourg,50,"SQL, Docker, PyTorch, Git",Master,5,Government,2025-04-21,2025-06-04,2222,5.6,Neural Networks Co +AI04283,Deep Learning Engineer,217100,USD,217100,SE,CT,Norway,L,Hungary,0,"Java, Computer Vision, SQL, NLP, Linux",Master,9,Retail,2025-03-08,2025-04-15,593,5.2,Autonomous Tech +AI04284,AI Software Engineer,69518,USD,69518,EN,FT,Denmark,S,Denmark,100,"NLP, SQL, Linux, Scala",Bachelor,1,Education,2024-03-09,2024-03-25,1880,7.4,Cognitive Computing +AI04285,AI Specialist,149647,CAD,187059,EX,FL,Canada,S,Canada,0,"Spark, SQL, Python, Computer Vision",Associate,14,Finance,2025-03-12,2025-05-15,2155,9.2,Digital Transformation LLC +AI04286,NLP Engineer,56185,SGD,73041,EN,PT,Singapore,S,New Zealand,50,"Kubernetes, Data Visualization, Python, TensorFlow, GCP",Bachelor,1,Transportation,2025-04-11,2025-06-10,1919,5.2,Future Systems +AI04287,Head of AI,47695,USD,47695,EN,FT,Sweden,S,Sweden,50,"Spark, Kubernetes, NLP, TensorFlow, Deep Learning",PhD,0,Gaming,2024-01-14,2024-02-24,1378,7.9,DeepTech Ventures +AI04288,AI Specialist,100301,EUR,85256,SE,PT,Germany,S,Germany,50,"Hadoop, Kubernetes, Scala, Computer Vision",PhD,7,Retail,2024-07-17,2024-08-31,1403,9.4,Quantum Computing Inc +AI04289,Machine Learning Engineer,66736,USD,66736,MI,FL,South Korea,M,South Korea,100,"Linux, Kubernetes, Data Visualization, Hadoop, Computer Vision",PhD,4,Gaming,2024-08-25,2024-09-20,754,5.8,Future Systems +AI04290,Principal Data Scientist,71795,JPY,7897450,EN,FL,Japan,L,Egypt,50,"SQL, PyTorch, TensorFlow, Azure",PhD,1,Government,2024-03-21,2024-04-26,2175,5.4,Cognitive Computing +AI04291,ML Ops Engineer,40743,USD,40743,MI,FT,China,M,China,50,"SQL, PyTorch, Data Visualization, Scala",PhD,4,Consulting,2024-05-01,2024-06-09,1212,5.2,Quantum Computing Inc +AI04292,Deep Learning Engineer,50361,EUR,42807,EN,FT,France,M,Belgium,100,"Linux, SQL, Hadoop, Python, Computer Vision",Bachelor,1,Media,2024-09-02,2024-09-25,607,7.3,Algorithmic Solutions +AI04293,Computer Vision Engineer,25504,USD,25504,EN,CT,India,S,India,100,"Python, Deep Learning, NLP, Mathematics, Spark",Master,0,Manufacturing,2024-12-01,2025-01-31,1174,6.5,Algorithmic Solutions +AI04294,Robotics Engineer,100549,USD,100549,SE,FT,South Korea,S,Spain,50,"Kubernetes, Statistics, Spark",Master,5,Healthcare,2024-07-23,2024-09-25,1869,8.2,Autonomous Tech +AI04295,Machine Learning Engineer,96451,EUR,81983,SE,PT,Austria,S,Austria,50,"Deep Learning, Git, Python",Master,7,Transportation,2024-12-23,2025-02-16,1078,7.9,Quantum Computing Inc +AI04296,NLP Engineer,94478,USD,94478,SE,FL,Sweden,S,Sweden,0,"Data Visualization, Computer Vision, Kubernetes",Bachelor,9,Media,2024-04-18,2024-06-14,677,8.3,Autonomous Tech +AI04297,Data Analyst,69250,EUR,58863,EN,CT,Netherlands,S,Ukraine,100,"Linux, PyTorch, R, Java, Git",Master,1,Automotive,2025-01-17,2025-03-05,1851,5.7,DataVision Ltd +AI04298,Data Analyst,99816,USD,99816,MI,CT,Ireland,L,Estonia,100,"Docker, Python, MLOps, Linux, TensorFlow",PhD,2,Retail,2024-02-29,2024-04-10,1889,9.9,Advanced Robotics +AI04299,Data Scientist,151190,USD,151190,SE,FL,Sweden,M,Sweden,100,"Kubernetes, Hadoop, Scala",Bachelor,7,Automotive,2024-04-24,2024-05-23,1258,9.2,Algorithmic Solutions +AI04300,Principal Data Scientist,234904,JPY,25839440,EX,PT,Japan,S,Japan,50,"Kubernetes, Data Visualization, Spark, Docker",PhD,15,Manufacturing,2024-08-03,2024-09-25,1974,9.6,Autonomous Tech +AI04301,AI Architect,100583,CHF,90525,EN,CT,Switzerland,L,China,100,"Computer Vision, AWS, Scala",Bachelor,1,Government,2024-05-11,2024-07-03,1471,8,DeepTech Ventures +AI04302,Head of AI,193990,USD,193990,EX,PT,United States,L,Israel,0,"Python, Kubernetes, Tableau",Associate,15,Consulting,2024-12-25,2025-03-03,2132,8.8,Digital Transformation LLC +AI04303,AI Product Manager,138206,EUR,117475,SE,FL,France,L,United Kingdom,100,"Statistics, PyTorch, Computer Vision, Mathematics, TensorFlow",Associate,7,Education,2025-03-24,2025-05-05,2261,8.5,Neural Networks Co +AI04304,Data Analyst,130833,AUD,176625,SE,PT,Australia,M,Austria,50,"Git, Scala, TensorFlow, AWS, R",Associate,6,Telecommunications,2024-12-06,2025-02-08,1325,6.7,DataVision Ltd +AI04305,Data Scientist,178524,USD,178524,SE,PT,Denmark,M,Sweden,50,"Python, Azure, Tableau, Hadoop",PhD,9,Healthcare,2024-01-31,2024-03-14,1457,7,Quantum Computing Inc +AI04306,NLP Engineer,58009,USD,58009,EN,FT,South Korea,S,South Korea,0,"Data Visualization, Git, Hadoop, SQL",PhD,0,Finance,2024-04-12,2024-05-18,650,9.2,Predictive Systems +AI04307,Autonomous Systems Engineer,51134,USD,51134,MI,CT,China,L,China,100,"TensorFlow, Statistics, Deep Learning",Bachelor,2,Education,2024-09-22,2024-11-21,2371,9,Future Systems +AI04308,Data Engineer,121528,EUR,103299,SE,FT,Germany,M,Germany,100,"TensorFlow, Kubernetes, Computer Vision, Tableau, Data Visualization",Associate,7,Energy,2025-04-03,2025-06-07,1250,5.6,Advanced Robotics +AI04309,NLP Engineer,161005,USD,161005,SE,CT,Israel,L,Israel,50,"Spark, PyTorch, Tableau",Bachelor,8,Transportation,2024-09-14,2024-10-22,2281,8.4,DeepTech Ventures +AI04310,Head of AI,172723,GBP,129542,EX,FL,United Kingdom,M,Ireland,50,"SQL, Git, PyTorch, Linux, Data Visualization",Bachelor,11,Media,2024-03-12,2024-05-19,2264,8.2,Advanced Robotics +AI04311,AI Consultant,124515,EUR,105838,EX,CT,Austria,S,Latvia,100,"Docker, Linux, Data Visualization, SQL",PhD,13,Transportation,2025-02-24,2025-05-06,2164,6.2,Cloud AI Solutions +AI04312,AI Research Scientist,80001,CAD,100001,EN,CT,Canada,L,Canada,0,"Docker, Kubernetes, Spark",Bachelor,1,Manufacturing,2024-01-19,2024-02-02,827,6,Neural Networks Co +AI04313,ML Ops Engineer,106148,EUR,90226,SE,CT,Netherlands,S,Ghana,0,"SQL, TensorFlow, Hadoop",Master,8,Education,2024-12-05,2025-02-10,1912,5.4,Cognitive Computing +AI04314,Computer Vision Engineer,88162,EUR,74938,MI,FL,France,M,France,50,"Data Visualization, Scala, GCP, Python, PyTorch",Master,2,Real Estate,2025-04-16,2025-05-29,1187,5.3,DeepTech Ventures +AI04315,Principal Data Scientist,80965,USD,80965,MI,CT,Israel,S,Argentina,0,"Tableau, Linux, Azure",Master,3,Gaming,2025-03-16,2025-04-03,1786,6,Predictive Systems +AI04316,AI Software Engineer,102591,USD,102591,MI,FL,Sweden,L,Sweden,50,"Docker, SQL, Hadoop, PyTorch",Bachelor,3,Real Estate,2024-06-14,2024-07-17,1331,6.2,Autonomous Tech +AI04317,Data Analyst,83458,CAD,104323,EN,FL,Canada,L,Romania,0,"Mathematics, Kubernetes, MLOps, Hadoop",Bachelor,0,Consulting,2024-06-14,2024-08-21,1749,6.3,Quantum Computing Inc +AI04318,Machine Learning Engineer,131559,EUR,111825,SE,CT,Germany,S,Austria,0,"Hadoop, Linux, Docker",PhD,5,Transportation,2024-01-12,2024-02-25,1897,8.8,Predictive Systems +AI04319,Robotics Engineer,103944,USD,103944,MI,FT,Finland,M,Finland,100,"Linux, MLOps, Computer Vision",PhD,2,Government,2024-10-04,2024-12-14,661,5.1,Smart Analytics +AI04320,AI Specialist,92612,USD,92612,EX,FL,China,S,China,0,"Java, Kubernetes, Python, Git",Bachelor,18,Consulting,2024-12-05,2025-02-02,2154,8.7,Autonomous Tech +AI04321,AI Product Manager,91367,USD,91367,SE,PT,South Korea,M,Luxembourg,100,"Azure, TensorFlow, Tableau, Hadoop",Master,5,Healthcare,2024-03-16,2024-05-04,1310,9.8,TechCorp Inc +AI04322,Deep Learning Engineer,102393,CHF,92154,EN,FL,Switzerland,L,Romania,100,"Azure, Deep Learning, Linux, Tableau, SQL",PhD,1,Consulting,2025-04-29,2025-06-12,1531,7.9,Digital Transformation LLC +AI04323,Computer Vision Engineer,126897,EUR,107862,EX,PT,Austria,S,Austria,50,"Python, SQL, Linux",Bachelor,17,Transportation,2024-07-30,2024-08-21,2068,9.9,Future Systems +AI04324,Deep Learning Engineer,49677,USD,49677,EN,FL,Israel,S,Canada,50,"Tableau, Docker, Kubernetes, Scala, Deep Learning",Bachelor,0,Manufacturing,2024-07-04,2024-08-30,2192,9.4,DataVision Ltd +AI04325,Data Scientist,220260,USD,220260,EX,FT,Sweden,S,Sweden,100,"Data Visualization, TensorFlow, Java, Docker",Master,19,Real Estate,2024-06-24,2024-08-24,1627,5.8,Autonomous Tech +AI04326,NLP Engineer,124924,USD,124924,SE,FL,South Korea,M,Singapore,50,"Linux, SQL, PyTorch",Master,6,Consulting,2024-11-13,2024-12-11,2445,8.4,Machine Intelligence Group +AI04327,Autonomous Systems Engineer,221162,USD,221162,SE,FT,Denmark,L,Denmark,100,"PyTorch, Scala, TensorFlow",PhD,8,Government,2024-07-18,2024-09-24,2325,9.6,Predictive Systems +AI04328,Deep Learning Engineer,68143,EUR,57922,EN,FT,France,S,Colombia,100,"Scala, TensorFlow, Azure, Mathematics",PhD,0,Energy,2024-06-07,2024-06-28,504,7.4,DataVision Ltd +AI04329,Machine Learning Engineer,139571,USD,139571,MI,FL,Denmark,L,Germany,0,"Kubernetes, Spark, PyTorch, Docker, AWS",Associate,2,Healthcare,2024-03-23,2024-05-26,2296,8.7,Advanced Robotics +AI04330,Data Analyst,75216,EUR,63934,MI,CT,Austria,M,Austria,50,"Scala, SQL, PyTorch",Associate,4,Education,2024-05-30,2024-08-04,2468,5.5,TechCorp Inc +AI04331,Data Scientist,185001,USD,185001,EX,CT,Denmark,S,Denmark,100,"Mathematics, Python, NLP",Bachelor,16,Gaming,2025-01-16,2025-03-25,1924,8,Smart Analytics +AI04332,AI Software Engineer,92328,JPY,10156080,MI,CT,Japan,L,Japan,50,"Python, GCP, Docker, Data Visualization, Linux",Master,2,Gaming,2024-01-28,2024-04-10,914,8.2,Predictive Systems +AI04333,AI Product Manager,100927,USD,100927,MI,FT,Denmark,S,Canada,50,"Docker, Tableau, Python, Linux, Mathematics",Bachelor,4,Energy,2025-03-20,2025-04-04,787,8.1,AI Innovations +AI04334,Deep Learning Engineer,99845,SGD,129799,MI,CT,Singapore,L,Singapore,0,"Python, Computer Vision, Scala, Docker",PhD,4,Automotive,2024-08-31,2024-10-08,812,8.4,Neural Networks Co +AI04335,Autonomous Systems Engineer,77405,EUR,65794,EN,CT,Germany,L,Austria,0,"Data Visualization, R, Java, Spark, Linux",Bachelor,0,Consulting,2024-05-01,2024-06-13,649,6,Algorithmic Solutions +AI04336,Deep Learning Engineer,60738,GBP,45554,EN,PT,United Kingdom,S,United Kingdom,50,"Python, Docker, AWS, TensorFlow",Master,0,Automotive,2024-03-22,2024-04-26,555,5.7,Digital Transformation LLC +AI04337,AI Software Engineer,105471,JPY,11601810,MI,FL,Japan,L,Japan,0,"Git, Deep Learning, Statistics",Master,4,Energy,2024-06-18,2024-08-02,1116,6.6,Machine Intelligence Group +AI04338,Deep Learning Engineer,159419,USD,159419,EX,FL,Israel,S,Ghana,0,"Deep Learning, SQL, Tableau, Linux",Master,18,Healthcare,2024-01-03,2024-01-28,925,9.1,AI Innovations +AI04339,ML Ops Engineer,90738,SGD,117959,MI,PT,Singapore,M,Singapore,0,"Spark, GCP, Tableau",Bachelor,3,Energy,2024-12-14,2025-01-14,2148,9,Future Systems +AI04340,Machine Learning Engineer,90479,USD,90479,MI,FT,Finland,S,Austria,50,"Java, Python, GCP, Mathematics, TensorFlow",Bachelor,3,Media,2025-02-13,2025-04-22,2020,8.3,Advanced Robotics +AI04341,NLP Engineer,155058,USD,155058,SE,FL,Ireland,L,Ireland,100,"Data Visualization, Python, SQL",Associate,9,Manufacturing,2024-11-21,2024-12-28,1821,8.5,Machine Intelligence Group +AI04342,AI Research Scientist,85529,USD,85529,MI,CT,Israel,S,Israel,50,"Deep Learning, Mathematics, GCP, Kubernetes, Git",Master,2,Consulting,2024-01-12,2024-02-28,1458,7.7,Quantum Computing Inc +AI04343,AI Research Scientist,86082,SGD,111907,MI,FL,Singapore,S,Singapore,100,"Hadoop, Deep Learning, Computer Vision, PyTorch, R",Master,4,Transportation,2025-01-27,2025-03-26,1346,5.7,DataVision Ltd +AI04344,Autonomous Systems Engineer,96560,USD,96560,EN,FT,Norway,L,Norway,50,"R, Spark, SQL, Deep Learning, Python",PhD,1,Automotive,2024-09-22,2024-11-24,1139,8.2,Machine Intelligence Group +AI04345,Research Scientist,83531,EUR,71001,EN,PT,Austria,L,Ghana,100,"TensorFlow, Kubernetes, Mathematics, NLP",Bachelor,0,Gaming,2024-12-04,2025-01-15,1024,5.5,Predictive Systems +AI04346,AI Research Scientist,113892,EUR,96808,SE,FL,Germany,S,Singapore,100,"Data Visualization, Scala, Deep Learning, Docker",Bachelor,8,Automotive,2025-02-16,2025-03-05,863,8,DeepTech Ventures +AI04347,Data Engineer,261519,JPY,28767090,EX,CT,Japan,M,Japan,50,"R, PyTorch, Scala",PhD,18,Media,2024-07-10,2024-08-28,1671,5.4,Neural Networks Co +AI04348,AI Consultant,112036,USD,112036,MI,CT,Israel,L,Israel,50,"Python, MLOps, TensorFlow",PhD,4,Transportation,2025-02-11,2025-04-25,2093,6.4,Autonomous Tech +AI04349,Data Analyst,91847,USD,91847,EN,PT,Sweden,L,Sweden,100,"Deep Learning, Java, Tableau, PyTorch, Git",Associate,0,Government,2024-02-17,2024-03-15,1937,9.1,Cognitive Computing +AI04350,NLP Engineer,58336,USD,58336,EN,FL,Sweden,S,Sweden,0,"TensorFlow, Java, R",Associate,1,Consulting,2025-02-27,2025-05-03,1310,5.9,Digital Transformation LLC +AI04351,AI Research Scientist,66684,USD,66684,EN,CT,Ireland,M,Ireland,0,"SQL, Python, AWS, TensorFlow",Associate,1,Technology,2025-03-07,2025-04-19,533,7.4,Cloud AI Solutions +AI04352,Research Scientist,91813,USD,91813,MI,PT,Ireland,M,Ireland,0,"R, Mathematics, Tableau, NLP, Data Visualization",Bachelor,3,Gaming,2024-12-26,2025-02-18,1649,7.9,TechCorp Inc +AI04353,AI Consultant,138037,USD,138037,SE,CT,United States,M,United States,0,"Azure, TensorFlow, GCP",Master,7,Transportation,2024-03-25,2024-04-27,1243,7.5,Autonomous Tech +AI04354,Data Analyst,118721,USD,118721,EN,CT,Denmark,L,New Zealand,50,"Hadoop, Tableau, Azure, MLOps, PyTorch",Associate,1,Real Estate,2025-03-21,2025-04-15,2159,7.7,Digital Transformation LLC +AI04355,NLP Engineer,70536,USD,70536,EN,FL,Israel,L,Ghana,50,"Azure, Scala, Docker",Master,1,Technology,2024-04-20,2024-06-05,2136,8.6,Future Systems +AI04356,Research Scientist,96320,EUR,81872,MI,PT,France,L,France,0,"Kubernetes, TensorFlow, NLP",Associate,4,Gaming,2024-12-26,2025-02-28,1277,5.5,TechCorp Inc +AI04357,Head of AI,134322,EUR,114174,SE,FT,Austria,L,Austria,100,"GCP, Deep Learning, Git, Python",Bachelor,8,Consulting,2024-02-03,2024-04-13,848,6.9,Autonomous Tech +AI04358,Robotics Engineer,61853,USD,61853,EN,FL,United States,M,United States,100,"Spark, R, Data Visualization",Master,0,Finance,2024-04-10,2024-05-17,1366,7.6,TechCorp Inc +AI04359,Robotics Engineer,118786,EUR,100968,SE,CT,Austria,S,Austria,0,"Scala, SQL, Computer Vision",Bachelor,5,Consulting,2024-07-22,2024-08-19,818,8.3,Cognitive Computing +AI04360,Autonomous Systems Engineer,63582,USD,63582,EN,FL,Ireland,S,Ireland,50,"Spark, AWS, GCP",PhD,1,Media,2024-01-11,2024-03-21,2243,9.4,Cognitive Computing +AI04361,Machine Learning Engineer,120025,AUD,162034,SE,FT,Australia,L,Norway,50,"PyTorch, Kubernetes, Spark, Java, Mathematics",Bachelor,8,Transportation,2025-03-13,2025-04-02,2126,7.5,Quantum Computing Inc +AI04362,Data Analyst,69623,EUR,59180,MI,CT,France,S,France,0,"Python, SQL, Java, R, AWS",PhD,2,Real Estate,2024-12-02,2025-01-02,1244,9.6,Machine Intelligence Group +AI04363,AI Architect,84572,USD,84572,EN,CT,Denmark,M,Denmark,50,"NLP, Computer Vision, Data Visualization, Deep Learning",Master,0,Finance,2024-07-03,2024-08-31,1897,8,Machine Intelligence Group +AI04364,Machine Learning Engineer,75649,USD,75649,SE,CT,China,L,China,100,"TensorFlow, Linux, Spark, Python, Azure",PhD,8,Transportation,2024-07-23,2024-09-19,1102,5.3,Smart Analytics +AI04365,AI Software Engineer,101898,USD,101898,EN,FL,Norway,M,Netherlands,50,"Python, Scala, Docker, Mathematics, AWS",Bachelor,1,Automotive,2024-03-26,2024-04-18,2051,5.1,Smart Analytics +AI04366,AI Product Manager,146918,EUR,124880,SE,FT,Netherlands,M,Kenya,50,"R, MLOps, PyTorch, NLP",Master,6,Energy,2024-02-18,2024-03-08,770,10,Advanced Robotics +AI04367,Principal Data Scientist,48437,USD,48437,SE,PT,India,S,Norway,100,"Hadoop, Linux, Azure, Computer Vision",PhD,6,Government,2024-12-31,2025-01-23,1949,8.8,DeepTech Ventures +AI04368,AI Software Engineer,156021,USD,156021,EX,CT,Israel,L,Ireland,100,"Scala, Python, SQL",Associate,15,Energy,2024-10-16,2024-12-16,2144,9,DataVision Ltd +AI04369,Research Scientist,142101,USD,142101,SE,PT,Sweden,L,Sweden,100,"Kubernetes, Java, Data Visualization",Master,7,Energy,2024-01-16,2024-03-26,623,6.7,Advanced Robotics +AI04370,AI Research Scientist,85556,EUR,72723,MI,PT,Germany,L,Germany,0,"TensorFlow, Tableau, Python, GCP",Associate,4,Telecommunications,2024-11-06,2025-01-04,1206,8.4,Quantum Computing Inc +AI04371,AI Research Scientist,36647,USD,36647,MI,PT,China,S,Turkey,0,"Java, AWS, GCP, Computer Vision",PhD,2,Retail,2025-03-11,2025-04-20,2008,7.2,Digital Transformation LLC +AI04372,Data Scientist,82294,EUR,69950,MI,CT,Austria,L,Denmark,50,"Spark, Mathematics, Deep Learning, Computer Vision",Master,2,Finance,2024-02-01,2024-03-25,1644,7.3,Predictive Systems +AI04373,AI Specialist,91519,AUD,123551,MI,FL,Australia,L,Australia,100,"Data Visualization, GCP, AWS, Docker",Bachelor,2,Real Estate,2025-04-13,2025-06-10,2219,6.2,Digital Transformation LLC +AI04374,Data Analyst,67529,USD,67529,SE,CT,China,L,Kenya,0,"Spark, Linux, Data Visualization, Scala",Master,7,Consulting,2025-01-24,2025-02-13,1676,6,AI Innovations +AI04375,Data Engineer,194639,USD,194639,EX,FT,Ireland,L,Ireland,0,"Tableau, NLP, SQL",Bachelor,13,Manufacturing,2024-05-04,2024-07-13,1333,5.7,Algorithmic Solutions +AI04376,AI Product Manager,194962,USD,194962,EX,FL,South Korea,M,South Korea,0,"Tableau, Azure, PyTorch, AWS",PhD,17,Real Estate,2024-12-12,2025-02-01,513,6.2,TechCorp Inc +AI04377,Machine Learning Engineer,68003,CAD,85004,MI,FL,Canada,M,Canada,0,"PyTorch, Linux, TensorFlow, Spark",PhD,3,Gaming,2024-08-11,2024-08-26,534,6.1,Digital Transformation LLC +AI04378,Data Engineer,160113,USD,160113,SE,FL,United States,L,United States,100,"Python, Scala, Azure, AWS",Master,7,Automotive,2024-10-07,2024-11-30,1941,6.5,DeepTech Ventures +AI04379,Head of AI,51041,USD,51041,EN,FT,Ireland,S,Ireland,50,"Hadoop, Linux, Mathematics",Associate,0,Government,2025-01-06,2025-01-24,1849,7.6,Autonomous Tech +AI04380,Robotics Engineer,123576,USD,123576,MI,CT,Denmark,S,Denmark,0,"Java, R, Tableau, AWS",Bachelor,3,Healthcare,2024-04-11,2024-05-21,1068,8.6,Advanced Robotics +AI04381,Machine Learning Researcher,76765,EUR,65250,MI,FT,Netherlands,M,Australia,100,"R, SQL, Tableau, Docker, Deep Learning",Associate,2,Finance,2024-10-25,2024-12-25,1685,6.4,TechCorp Inc +AI04382,Data Scientist,212410,USD,212410,EX,CT,Israel,L,Israel,100,"Hadoop, Azure, Statistics",Bachelor,17,Retail,2024-09-28,2024-11-01,1414,9.4,Cognitive Computing +AI04383,Computer Vision Engineer,64240,USD,64240,SE,PT,China,M,China,50,"Hadoop, Scala, PyTorch",Bachelor,8,Retail,2024-09-01,2024-10-28,2324,6.4,Neural Networks Co +AI04384,Autonomous Systems Engineer,132240,USD,132240,EX,CT,Finland,M,Spain,0,"Tableau, Python, Spark, Statistics",PhD,16,Real Estate,2024-08-22,2024-10-19,1289,8.4,Quantum Computing Inc +AI04385,Machine Learning Engineer,90724,CAD,113405,MI,PT,Canada,S,Belgium,0,"Python, GCP, TensorFlow, Spark, AWS",Master,3,Telecommunications,2024-06-29,2024-08-26,1928,7.8,Cloud AI Solutions +AI04386,Machine Learning Researcher,210905,USD,210905,EX,FT,Norway,L,Norway,100,"PyTorch, TensorFlow, Tableau, Data Visualization, Python",Master,12,Real Estate,2024-03-24,2024-05-11,1507,8.1,Cloud AI Solutions +AI04387,AI Product Manager,113235,AUD,152867,SE,PT,Australia,S,Argentina,0,"Python, TensorFlow, Azure",Master,7,Gaming,2024-03-03,2024-04-25,617,8,Algorithmic Solutions +AI04388,AI Software Engineer,167568,EUR,142433,EX,PT,France,S,United States,50,"Mathematics, PyTorch, SQL, Git, Docker",PhD,19,Government,2025-04-20,2025-05-13,1087,6.4,Quantum Computing Inc +AI04389,Data Engineer,60687,USD,60687,EN,FL,Finland,M,Finland,0,"AWS, NLP, Statistics, Python, Deep Learning",PhD,1,Consulting,2024-07-28,2024-09-29,1930,5.3,Advanced Robotics +AI04390,Computer Vision Engineer,140330,USD,140330,EX,PT,Finland,S,Belgium,50,"Python, Scala, Hadoop, Computer Vision, TensorFlow",PhD,16,Technology,2024-08-13,2024-10-12,1619,7.5,DeepTech Ventures +AI04391,Machine Learning Researcher,87316,EUR,74219,MI,FL,Netherlands,S,Netherlands,50,"Data Visualization, Azure, Git",Bachelor,2,Automotive,2024-04-25,2024-06-13,558,7,Cloud AI Solutions +AI04392,AI Software Engineer,103223,USD,103223,EN,CT,United States,L,United States,50,"Linux, Docker, NLP, Computer Vision, Kubernetes",Bachelor,0,Real Estate,2024-12-01,2025-02-02,1214,5,Advanced Robotics +AI04393,Head of AI,259484,GBP,194613,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, Hadoop, TensorFlow, GCP",PhD,19,Energy,2025-01-04,2025-03-16,1671,5.7,Predictive Systems +AI04394,Machine Learning Researcher,83379,USD,83379,EN,FL,United States,S,United States,100,"Tableau, Scala, SQL",PhD,1,Energy,2024-04-16,2024-05-07,831,6.5,Predictive Systems +AI04395,ML Ops Engineer,108902,GBP,81677,MI,FT,United Kingdom,M,United Kingdom,0,"Linux, MLOps, Data Visualization",Bachelor,3,Technology,2024-04-27,2024-06-13,1500,9.9,Future Systems +AI04396,Data Engineer,56324,USD,56324,EN,FT,Finland,L,Finland,0,"R, SQL, MLOps, Linux",PhD,1,Gaming,2024-02-29,2024-03-16,1319,9.6,Cognitive Computing +AI04397,Principal Data Scientist,117902,EUR,100217,MI,FL,Netherlands,L,Netherlands,100,"Deep Learning, Python, NLP",Bachelor,4,Technology,2024-09-06,2024-10-22,2283,5.6,Algorithmic Solutions +AI04398,AI Software Engineer,113637,EUR,96591,MI,FT,Netherlands,L,Netherlands,50,"Scala, SQL, Statistics",Master,3,Retail,2025-02-15,2025-03-31,1625,7.6,Neural Networks Co +AI04399,AI Specialist,100672,EUR,85571,MI,PT,Germany,M,Israel,100,"R, SQL, TensorFlow",Associate,3,Retail,2024-12-11,2025-02-16,1012,8.1,Cognitive Computing +AI04400,Robotics Engineer,59217,JPY,6513870,EN,FL,Japan,S,Nigeria,100,"SQL, R, Data Visualization",Bachelor,0,Technology,2024-05-26,2024-07-02,1332,6.2,Cloud AI Solutions +AI04401,AI Specialist,180746,USD,180746,EX,FL,Ireland,L,Ireland,0,"Scala, Azure, NLP",Bachelor,18,Finance,2024-02-29,2024-04-12,778,9,Cognitive Computing +AI04402,NLP Engineer,76000,AUD,102600,EN,FT,Australia,M,Russia,50,"Azure, Hadoop, Tableau",Bachelor,1,Retail,2025-02-21,2025-03-30,1457,9,Digital Transformation LLC +AI04403,AI Consultant,158289,CAD,197861,EX,CT,Canada,S,Canada,50,"Azure, Python, AWS, TensorFlow",Associate,19,Finance,2024-03-29,2024-05-07,904,6.7,Autonomous Tech +AI04404,AI Software Engineer,210409,USD,210409,EX,CT,South Korea,L,Denmark,100,"Git, Statistics, Azure, SQL, Computer Vision",Bachelor,12,Telecommunications,2024-05-24,2024-06-13,1401,9.6,AI Innovations +AI04405,Data Analyst,72009,USD,72009,MI,CT,Ireland,S,Ireland,0,"Kubernetes, Tableau, TensorFlow, MLOps, Python",PhD,2,Healthcare,2025-01-15,2025-02-17,1726,7,AI Innovations +AI04406,Computer Vision Engineer,216981,SGD,282075,EX,FT,Singapore,L,Estonia,0,"SQL, MLOps, Git, Docker",Master,12,Government,2025-02-02,2025-02-20,884,5.1,Cognitive Computing +AI04407,AI Architect,125378,USD,125378,MI,FL,Denmark,M,Denmark,100,"Spark, Computer Vision, NLP, R",Bachelor,4,Consulting,2024-07-28,2024-08-17,1609,8.1,Advanced Robotics +AI04408,Machine Learning Researcher,80879,USD,80879,MI,CT,United States,S,United States,50,"AWS, Tableau, Linux",PhD,3,Automotive,2024-10-17,2024-12-25,1607,8.5,Cloud AI Solutions +AI04409,Data Scientist,304522,SGD,395879,EX,FT,Singapore,L,Vietnam,0,"TensorFlow, Python, Tableau, Docker",Master,10,Consulting,2025-03-09,2025-05-03,2161,9.3,Autonomous Tech +AI04410,Autonomous Systems Engineer,106646,USD,106646,MI,FT,Sweden,M,Sweden,50,"Java, Kubernetes, Tableau, SQL",PhD,3,Automotive,2025-02-15,2025-03-23,2468,7,Neural Networks Co +AI04411,AI Architect,91413,SGD,118837,MI,PT,Singapore,M,Spain,100,"Mathematics, Computer Vision, NLP, TensorFlow",PhD,4,Technology,2024-11-24,2025-01-13,881,9,Neural Networks Co +AI04412,Deep Learning Engineer,224651,USD,224651,EX,FL,Denmark,L,Denmark,100,"Git, Kubernetes, Python",Bachelor,19,Technology,2024-12-11,2025-02-14,1208,9.4,DataVision Ltd +AI04413,AI Architect,130860,USD,130860,EX,PT,South Korea,L,South Korea,50,"TensorFlow, Docker, MLOps, Kubernetes, Data Visualization",PhD,13,Education,2025-03-19,2025-04-27,1934,7.1,Smart Analytics +AI04414,Machine Learning Researcher,46877,USD,46877,EN,CT,Israel,S,Israel,100,"NLP, TensorFlow, Mathematics, MLOps",PhD,0,Consulting,2024-05-28,2024-06-13,2354,7,Digital Transformation LLC +AI04415,Deep Learning Engineer,179047,EUR,152190,EX,PT,France,M,France,0,"NLP, Docker, Mathematics, Computer Vision, PyTorch",Master,18,Media,2024-10-13,2024-10-27,2472,9.9,Machine Intelligence Group +AI04416,Data Engineer,104146,EUR,88524,SE,FL,Austria,M,Turkey,0,"Docker, Python, Mathematics",PhD,8,Technology,2024-03-15,2024-05-04,1388,5,Machine Intelligence Group +AI04417,AI Consultant,31567,USD,31567,MI,FL,India,S,India,0,"Kubernetes, Git, GCP, Linux",Bachelor,2,Manufacturing,2025-01-23,2025-03-27,1204,6.6,DataVision Ltd +AI04418,Principal Data Scientist,97690,USD,97690,SE,FL,South Korea,S,Kenya,100,"Linux, Computer Vision, Deep Learning, Kubernetes",PhD,7,Transportation,2024-08-22,2024-09-17,2486,6.6,Autonomous Tech +AI04419,Head of AI,62371,AUD,84201,EN,FT,Australia,M,Australia,50,"Azure, NLP, SQL",PhD,0,Technology,2024-09-13,2024-10-11,1120,7.4,DeepTech Ventures +AI04420,AI Product Manager,262516,CHF,236264,EX,FL,Switzerland,L,Switzerland,50,"Scala, Spark, Docker, Kubernetes",Bachelor,19,Media,2024-09-02,2024-10-15,614,9.1,Cognitive Computing +AI04421,AI Specialist,75844,CAD,94805,MI,FL,Canada,S,India,100,"TensorFlow, Kubernetes, Tableau",Associate,2,Energy,2024-05-27,2024-07-01,2116,9.7,Future Systems +AI04422,Data Scientist,131997,JPY,14519670,SE,FL,Japan,L,Thailand,0,"Kubernetes, PyTorch, Computer Vision",Master,5,Government,2024-07-10,2024-08-23,1204,6.1,Smart Analytics +AI04423,Principal Data Scientist,103953,EUR,88360,MI,FT,Netherlands,M,Netherlands,0,"SQL, NLP, PyTorch, Computer Vision, Hadoop",Master,3,Transportation,2024-12-25,2025-01-28,1919,5.8,TechCorp Inc +AI04424,AI Specialist,177676,USD,177676,SE,PT,Denmark,L,Denmark,0,"Azure, Java, Python, Linux, Statistics",Bachelor,8,Finance,2024-11-21,2024-12-30,2199,9.3,Algorithmic Solutions +AI04425,AI Product Manager,122946,AUD,165977,SE,PT,Australia,S,Australia,0,"Spark, Kubernetes, Git, Java, GCP",PhD,9,Education,2024-12-26,2025-02-23,835,7.1,TechCorp Inc +AI04426,Head of AI,202266,USD,202266,EX,CT,Israel,S,Israel,50,"GCP, Computer Vision, SQL, Azure",Associate,12,Healthcare,2024-08-02,2024-09-17,1550,5.9,AI Innovations +AI04427,Machine Learning Engineer,42862,USD,42862,SE,FL,India,S,Russia,100,"Git, Java, Kubernetes, R, Mathematics",Bachelor,5,Gaming,2024-11-08,2025-01-17,1330,6.6,DeepTech Ventures +AI04428,Data Scientist,221324,USD,221324,SE,FT,Norway,L,Spain,100,"Spark, R, Tableau, Python, Linux",Bachelor,7,Retail,2025-04-01,2025-04-29,1133,7.6,Predictive Systems +AI04429,Machine Learning Researcher,129064,SGD,167783,MI,CT,Singapore,L,Hungary,100,"Python, Hadoop, Statistics",Bachelor,4,Manufacturing,2024-07-07,2024-09-17,2002,5.8,TechCorp Inc +AI04430,Computer Vision Engineer,116116,CAD,145145,SE,FT,Canada,L,Singapore,100,"AWS, SQL, Deep Learning, Kubernetes",PhD,8,Manufacturing,2024-06-25,2024-07-12,849,8.3,Algorithmic Solutions +AI04431,Data Scientist,204614,AUD,276229,EX,CT,Australia,L,Australia,0,"Linux, MLOps, NLP, PyTorch",Associate,19,Telecommunications,2025-04-07,2025-04-23,1784,9.7,Neural Networks Co +AI04432,Data Engineer,44008,USD,44008,EX,FT,India,S,India,100,"TensorFlow, Python, Java, Scala, Azure",PhD,15,Transportation,2024-03-12,2024-04-08,1391,5.9,Smart Analytics +AI04433,AI Research Scientist,59937,USD,59937,SE,PT,China,M,Indonesia,100,"PyTorch, TensorFlow, Git",Bachelor,9,Technology,2024-08-21,2024-11-02,798,9.2,Predictive Systems +AI04434,AI Product Manager,86443,USD,86443,MI,PT,Israel,S,Belgium,50,"SQL, Java, MLOps",Master,4,Technology,2024-10-15,2024-11-10,1882,5.9,Digital Transformation LLC +AI04435,AI Specialist,104949,SGD,136434,SE,FL,Singapore,S,Singapore,50,"Java, Linux, Spark",Bachelor,6,Manufacturing,2024-06-07,2024-08-15,855,9.8,Digital Transformation LLC +AI04436,Principal Data Scientist,186813,USD,186813,EX,CT,Ireland,S,France,100,"NLP, Linux, Java",Bachelor,17,Healthcare,2024-01-03,2024-03-12,958,8.6,Algorithmic Solutions +AI04437,AI Specialist,211822,JPY,23300420,EX,FL,Japan,L,Indonesia,50,"Computer Vision, Hadoop, Python, SQL",Bachelor,13,Transportation,2024-03-23,2024-05-05,2204,9.4,Cognitive Computing +AI04438,AI Consultant,153646,SGD,199740,EX,FL,Singapore,M,Romania,100,"Mathematics, PyTorch, MLOps",Master,18,Real Estate,2024-01-07,2024-03-14,607,7.6,DeepTech Ventures +AI04439,Data Analyst,117982,USD,117982,SE,PT,Israel,M,Israel,0,"Python, Linux, R, TensorFlow",PhD,5,Gaming,2024-02-18,2024-04-23,752,9.9,Quantum Computing Inc +AI04440,Data Engineer,133740,SGD,173862,SE,FL,Singapore,S,Mexico,0,"Java, SQL, Mathematics, Deep Learning",Associate,9,Government,2025-01-10,2025-01-24,2271,7.8,Algorithmic Solutions +AI04441,Machine Learning Researcher,84175,USD,84175,EN,FL,Denmark,S,Chile,0,"Azure, Mathematics, MLOps, Scala, Git",Bachelor,1,Healthcare,2024-02-17,2024-04-07,2409,6.9,Smart Analytics +AI04442,Computer Vision Engineer,87366,GBP,65525,MI,CT,United Kingdom,S,Vietnam,0,"Azure, Python, Data Visualization, Mathematics, Computer Vision",Bachelor,2,Consulting,2024-11-26,2024-12-11,1180,10,Digital Transformation LLC +AI04443,Autonomous Systems Engineer,110287,USD,110287,MI,CT,Sweden,L,Vietnam,50,"GCP, Spark, Azure, PyTorch",Bachelor,4,Retail,2025-02-14,2025-03-21,674,7.8,Quantum Computing Inc +AI04444,Data Scientist,104258,USD,104258,SE,CT,South Korea,L,South Korea,0,"Statistics, Kubernetes, R, Java",Associate,8,Automotive,2024-10-26,2024-12-01,2028,9.2,Machine Intelligence Group +AI04445,AI Software Engineer,114211,USD,114211,EN,FT,Denmark,L,Ireland,100,"Python, Kubernetes, Docker",PhD,0,Healthcare,2025-01-07,2025-03-10,1349,9,DeepTech Ventures +AI04446,Head of AI,194011,EUR,164909,EX,PT,France,L,France,100,"PyTorch, Python, NLP, Hadoop",Master,18,Healthcare,2025-04-08,2025-06-06,814,8.4,Algorithmic Solutions +AI04447,Principal Data Scientist,293192,USD,293192,EX,FL,Sweden,L,Sweden,50,"Azure, AWS, Linux, Scala, R",Associate,13,Technology,2024-12-07,2025-01-29,2000,8.4,Future Systems +AI04448,Robotics Engineer,53874,EUR,45793,EN,FL,France,S,France,100,"GCP, R, Statistics",PhD,1,Manufacturing,2024-03-15,2024-04-01,503,6.9,TechCorp Inc +AI04449,Robotics Engineer,88454,USD,88454,SE,CT,Finland,S,Finland,0,"Docker, Hadoop, GCP, Java, Scala",PhD,7,Media,2025-04-25,2025-06-28,2354,5.2,Predictive Systems +AI04450,Robotics Engineer,161911,SGD,210484,EX,CT,Singapore,S,Singapore,50,"SQL, Scala, Linux, Azure",Associate,11,Healthcare,2024-11-04,2025-01-11,1397,8.7,DeepTech Ventures +AI04451,AI Consultant,64565,USD,64565,MI,FT,South Korea,S,South Korea,100,"Hadoop, Git, Tableau, NLP, Azure",PhD,4,Gaming,2024-09-13,2024-10-18,2397,8.1,DeepTech Ventures +AI04452,Data Scientist,47708,USD,47708,EN,CT,Israel,S,Philippines,100,"Python, TensorFlow, Azure, Linux",Bachelor,1,Technology,2024-06-13,2024-07-03,1203,9.5,DeepTech Ventures +AI04453,AI Product Manager,140313,SGD,182407,SE,FL,Singapore,M,Singapore,50,"Mathematics, Scala, Deep Learning",Master,6,Energy,2024-08-15,2024-09-27,1946,6.2,Neural Networks Co +AI04454,AI Software Engineer,94235,JPY,10365850,EN,FL,Japan,L,Spain,100,"R, Tableau, Python, Azure, TensorFlow",Associate,1,Consulting,2024-05-05,2024-07-07,2010,9.2,Machine Intelligence Group +AI04455,Data Engineer,57467,USD,57467,MI,CT,South Korea,S,South Korea,0,"Computer Vision, Spark, Docker, Hadoop, Python",PhD,3,Government,2024-07-21,2024-08-18,1968,8,Neural Networks Co +AI04456,AI Research Scientist,129225,SGD,167993,SE,PT,Singapore,M,Finland,0,"Hadoop, Python, PyTorch, Git",Associate,9,Healthcare,2025-03-22,2025-05-16,1335,5.9,DeepTech Ventures +AI04457,Data Scientist,157816,USD,157816,EX,PT,Ireland,M,Ireland,100,"Scala, GCP, AWS",Bachelor,12,Manufacturing,2025-04-22,2025-06-12,733,10,Neural Networks Co +AI04458,Data Engineer,77796,EUR,66127,MI,FL,Austria,S,Austria,50,"Python, TensorFlow, Tableau",Bachelor,2,Automotive,2024-01-09,2024-01-26,832,5.4,Predictive Systems +AI04459,Deep Learning Engineer,202840,EUR,172414,EX,FT,Netherlands,S,Netherlands,0,"Git, Spark, Computer Vision, Tableau, Java",Associate,17,Manufacturing,2025-02-22,2025-03-18,1954,8.6,Smart Analytics +AI04460,Data Scientist,77051,AUD,104019,EN,FL,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch",Master,0,Media,2024-09-30,2024-11-08,2129,5.6,Advanced Robotics +AI04461,AI Specialist,105395,AUD,142283,MI,FT,Australia,L,Australia,50,"Linux, Git, Kubernetes, NLP, Python",Master,2,Transportation,2024-06-25,2024-08-27,1203,7.1,TechCorp Inc +AI04462,AI Research Scientist,83359,EUR,70855,EN,FL,Netherlands,M,Netherlands,100,"Kubernetes, Java, Data Visualization",Bachelor,0,Real Estate,2025-01-21,2025-02-19,1507,5.4,Machine Intelligence Group +AI04463,Machine Learning Engineer,98213,CHF,88392,EN,CT,Switzerland,L,Switzerland,0,"Java, SQL, Kubernetes, PyTorch",Associate,1,Media,2024-12-23,2025-01-23,1844,8.8,Cognitive Computing +AI04464,AI Software Engineer,39868,USD,39868,MI,FL,China,S,China,100,"R, Docker, TensorFlow, Git",Master,2,Automotive,2024-09-25,2024-11-20,526,5.1,Future Systems +AI04465,Computer Vision Engineer,246512,USD,246512,EX,CT,Norway,M,Norway,0,"Data Visualization, Git, Linux",Bachelor,19,Manufacturing,2025-01-24,2025-03-24,2255,10,Quantum Computing Inc +AI04466,AI Software Engineer,77063,USD,77063,EX,CT,India,M,India,50,"MLOps, Git, Kubernetes",Associate,18,Media,2025-03-31,2025-05-21,680,9.8,Advanced Robotics +AI04467,Principal Data Scientist,60066,EUR,51056,EN,PT,Germany,L,Germany,50,"Deep Learning, Scala, Data Visualization",Associate,0,Media,2024-11-03,2024-11-25,1884,9.6,Quantum Computing Inc +AI04468,NLP Engineer,93900,USD,93900,MI,CT,Ireland,L,Ireland,50,"Linux, AWS, NLP, Git",Bachelor,3,Retail,2024-11-04,2024-12-02,918,5.8,DeepTech Ventures +AI04469,Machine Learning Engineer,132017,EUR,112214,SE,PT,Germany,L,China,50,"GCP, Statistics, SQL, TensorFlow",PhD,7,Technology,2025-03-15,2025-05-08,1645,9.5,Cognitive Computing +AI04470,Head of AI,94447,USD,94447,MI,CT,Norway,S,Norway,0,"Kubernetes, SQL, TensorFlow, PyTorch",Master,4,Education,2024-11-14,2025-01-04,1613,7.8,Cognitive Computing +AI04471,AI Software Engineer,65304,USD,65304,EX,FL,India,M,India,50,"MLOps, Python, TensorFlow, Docker",Associate,12,Finance,2024-07-19,2024-08-04,574,5.8,Cognitive Computing +AI04472,AI Software Engineer,172150,EUR,146328,SE,FL,Netherlands,L,Netherlands,100,"Spark, PyTorch, Data Visualization, Computer Vision",Associate,9,Transportation,2024-11-26,2024-12-10,2024,5.7,Digital Transformation LLC +AI04473,NLP Engineer,88827,USD,88827,MI,FT,Ireland,M,Ireland,50,"Computer Vision, R, Azure, Deep Learning, MLOps",Bachelor,4,Retail,2024-07-13,2024-09-06,2422,7.2,Future Systems +AI04474,Data Engineer,144886,AUD,195596,SE,FT,Australia,L,Australia,0,"Git, GCP, Linux, Computer Vision",Master,8,Manufacturing,2024-07-09,2024-09-11,1834,8.3,Future Systems +AI04475,Research Scientist,133043,USD,133043,EX,FL,Israel,S,France,0,"Python, Deep Learning, Java",PhD,16,Transportation,2024-04-05,2024-06-06,2319,8.8,Advanced Robotics +AI04476,AI Software Engineer,127811,EUR,108639,SE,FL,Netherlands,L,Ireland,50,"Scala, Azure, Docker, AWS, Mathematics",Associate,7,Automotive,2024-11-27,2024-12-24,1278,9.6,Quantum Computing Inc +AI04477,Computer Vision Engineer,103521,CAD,129401,SE,CT,Canada,S,Canada,50,"R, Java, Tableau, Docker",Associate,7,Real Estate,2024-01-04,2024-02-16,2044,5.6,Predictive Systems +AI04478,Research Scientist,54480,SGD,70824,EN,FL,Singapore,M,Singapore,50,"Spark, TensorFlow, MLOps, Python",Master,1,Education,2025-01-30,2025-02-17,1495,9.3,Autonomous Tech +AI04479,Principal Data Scientist,74709,EUR,63503,MI,FL,France,M,France,50,"Scala, Git, MLOps, Statistics",Bachelor,4,Technology,2024-09-11,2024-10-15,1967,5.8,Machine Intelligence Group +AI04480,Computer Vision Engineer,59379,USD,59379,EN,FL,Israel,S,Czech Republic,100,"Java, Computer Vision, MLOps",PhD,1,Government,2025-01-18,2025-02-14,2335,8,Advanced Robotics +AI04481,AI Product Manager,61440,USD,61440,SE,FT,China,M,Japan,0,"Scala, Mathematics, Java",PhD,5,Telecommunications,2024-08-17,2024-10-11,1501,8,Neural Networks Co +AI04482,Autonomous Systems Engineer,134360,GBP,100770,EX,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Python, NLP, TensorFlow, Java",Master,17,Gaming,2024-04-11,2024-05-05,2337,7,Autonomous Tech +AI04483,AI Product Manager,225183,JPY,24770130,EX,FL,Japan,S,Japan,50,"Data Visualization, MLOps, TensorFlow",PhD,13,Energy,2024-10-12,2024-12-17,729,8.6,Algorithmic Solutions +AI04484,Principal Data Scientist,262051,CAD,327564,EX,FT,Canada,L,Colombia,100,"R, Tableau, Statistics, Hadoop, SQL",Bachelor,18,Government,2025-01-30,2025-02-20,678,5.4,Digital Transformation LLC +AI04485,ML Ops Engineer,51148,USD,51148,MI,FL,China,L,Norway,50,"Docker, MLOps, Hadoop, R, Azure",Bachelor,3,Energy,2024-11-06,2024-12-17,1629,9.4,Smart Analytics +AI04486,Deep Learning Engineer,50384,USD,50384,SE,CT,India,L,Finland,100,"Azure, NLP, Spark, Tableau",Bachelor,9,Technology,2024-11-21,2024-12-31,1978,7.9,Algorithmic Solutions +AI04487,Autonomous Systems Engineer,45747,CAD,57184,EN,PT,Canada,S,Philippines,0,"Azure, Docker, Deep Learning, Data Visualization, Python",Master,1,Manufacturing,2024-09-27,2024-12-03,2476,8.3,AI Innovations +AI04488,AI Architect,27660,USD,27660,EN,CT,China,M,China,50,"PyTorch, Git, Hadoop",Master,0,Healthcare,2024-09-12,2024-10-31,2159,7.4,Future Systems +AI04489,Machine Learning Researcher,66412,USD,66412,EN,CT,Finland,L,Finland,0,"Python, Linux, Spark, NLP",Associate,1,Gaming,2024-10-27,2024-11-26,1366,7.1,Autonomous Tech +AI04490,Computer Vision Engineer,286005,USD,286005,EX,CT,Ireland,L,Ireland,100,"R, Python, TensorFlow, PyTorch",Associate,15,Telecommunications,2024-03-06,2024-05-04,1637,9.4,Digital Transformation LLC +AI04491,Data Scientist,162115,EUR,137798,EX,PT,Austria,S,South Africa,50,"Hadoop, PyTorch, Git, R",Master,15,Automotive,2024-09-21,2024-10-27,780,6.4,AI Innovations +AI04492,Autonomous Systems Engineer,179992,JPY,19799120,EX,FL,Japan,M,Japan,50,"Scala, Azure, Deep Learning, Data Visualization",Master,10,Media,2025-01-23,2025-02-12,2176,8.4,Future Systems +AI04493,Data Analyst,52604,USD,52604,EN,FL,Sweden,S,Finland,50,"NLP, Scala, Data Visualization, Kubernetes",Bachelor,1,Energy,2025-01-15,2025-02-20,2181,9.8,DataVision Ltd +AI04494,AI Consultant,135693,USD,135693,MI,FL,Norway,L,Switzerland,0,"Kubernetes, PyTorch, GCP, Scala",Bachelor,2,Healthcare,2024-05-16,2024-05-30,1410,7.8,Autonomous Tech +AI04495,Data Scientist,132806,USD,132806,SE,CT,Norway,M,Norway,100,"Java, PyTorch, Data Visualization, Deep Learning, GCP",PhD,5,Government,2024-08-09,2024-09-10,745,10,TechCorp Inc +AI04496,AI Consultant,119154,CHF,107239,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Tableau, PyTorch",PhD,3,Technology,2024-04-25,2024-07-05,1701,5.6,TechCorp Inc +AI04497,NLP Engineer,116153,CHF,104538,EN,FT,Switzerland,L,Switzerland,0,"PyTorch, SQL, Docker, Deep Learning",PhD,1,Telecommunications,2024-05-22,2024-07-08,2130,5.5,DataVision Ltd +AI04498,AI Product Manager,122285,USD,122285,SE,FL,Norway,S,South Africa,50,"Computer Vision, R, Java, Azure",PhD,7,Consulting,2024-08-05,2024-10-07,1831,8.3,Digital Transformation LLC +AI04499,AI Research Scientist,87146,USD,87146,SE,FL,South Korea,M,South Korea,0,"R, Linux, MLOps, Mathematics, Git",Bachelor,7,Retail,2025-01-06,2025-03-05,2199,5.7,AI Innovations +AI04500,Head of AI,101820,AUD,137457,MI,CT,Australia,M,Ukraine,50,"AWS, Statistics, Data Visualization",Associate,4,Technology,2025-03-18,2025-04-17,1073,6.2,AI Innovations +AI04501,AI Research Scientist,76032,EUR,64627,MI,FL,France,M,Netherlands,100,"PyTorch, GCP, TensorFlow, NLP, Python",Bachelor,3,Consulting,2024-09-08,2024-10-08,1911,8.6,Digital Transformation LLC +AI04502,AI Software Engineer,138064,JPY,15187040,SE,FL,Japan,L,Japan,100,"GCP, PyTorch, Spark",Bachelor,5,Government,2024-02-22,2024-03-17,1028,8.1,Smart Analytics +AI04503,Research Scientist,131574,AUD,177625,SE,FL,Australia,L,Philippines,0,"Python, Spark, Azure, Linux",Bachelor,6,Finance,2024-09-30,2024-11-24,1280,6.4,Digital Transformation LLC +AI04504,Head of AI,366922,CHF,330230,EX,FL,Switzerland,L,Malaysia,0,"TensorFlow, Computer Vision, Hadoop, Python, MLOps",Bachelor,14,Real Estate,2024-01-21,2024-02-06,2396,9.3,Quantum Computing Inc +AI04505,AI Consultant,113179,USD,113179,EN,FT,Denmark,L,Denmark,0,"Git, Docker, Hadoop",Bachelor,1,Automotive,2024-06-26,2024-07-25,1016,8.2,DeepTech Ventures +AI04506,Robotics Engineer,249140,AUD,336339,EX,FL,Australia,L,Australia,100,"Scala, Statistics, NLP",PhD,18,Transportation,2024-07-22,2024-08-22,1206,6.1,Algorithmic Solutions +AI04507,Principal Data Scientist,171609,EUR,145868,EX,FT,Netherlands,M,Germany,50,"Spark, SQL, Java, MLOps, Linux",Bachelor,10,Education,2024-04-27,2024-06-17,2287,7.4,Smart Analytics +AI04508,Machine Learning Engineer,105792,EUR,89923,SE,FL,France,S,Portugal,50,"Spark, NLP, Git, Computer Vision",Master,6,Telecommunications,2024-05-31,2024-07-25,2141,5.3,Cognitive Computing +AI04509,Machine Learning Researcher,173700,USD,173700,EX,FT,South Korea,M,Luxembourg,100,"MLOps, Python, Data Visualization, Mathematics, Linux",Bachelor,19,Finance,2024-01-18,2024-03-02,529,6.5,Predictive Systems +AI04510,Data Analyst,97074,EUR,82513,MI,PT,Netherlands,L,Netherlands,100,"Data Visualization, Linux, Python, MLOps, SQL",Associate,4,Automotive,2025-01-16,2025-02-09,1335,8.4,Smart Analytics +AI04511,Machine Learning Researcher,22207,USD,22207,EN,CT,India,M,India,100,"Deep Learning, Git, Mathematics",Master,1,Energy,2024-03-19,2024-05-08,602,9.6,TechCorp Inc +AI04512,Machine Learning Researcher,166711,USD,166711,SE,PT,Ireland,L,Ireland,100,"Spark, PyTorch, NLP, TensorFlow",Bachelor,8,Consulting,2024-12-01,2024-12-17,886,7.1,Advanced Robotics +AI04513,Machine Learning Researcher,91344,EUR,77642,MI,PT,Germany,S,Austria,100,"Spark, Python, Data Visualization",PhD,4,Telecommunications,2024-01-27,2024-03-30,1213,9.8,TechCorp Inc +AI04514,Data Scientist,171048,USD,171048,SE,FT,Denmark,L,Denmark,0,"PyTorch, SQL, Spark, TensorFlow, Data Visualization",PhD,7,Gaming,2024-12-19,2025-01-04,1329,7.1,Algorithmic Solutions +AI04515,AI Software Engineer,129514,USD,129514,EX,PT,Israel,M,Israel,0,"Python, AWS, GCP, R",Bachelor,14,Real Estate,2025-02-14,2025-04-06,2310,6.5,Future Systems +AI04516,AI Research Scientist,70909,USD,70909,MI,FL,Ireland,S,Ireland,100,"AWS, MLOps, PyTorch, TensorFlow",Master,4,Telecommunications,2024-11-09,2024-12-08,926,6.6,AI Innovations +AI04517,Deep Learning Engineer,55311,EUR,47014,EN,FT,France,M,France,0,"Java, MLOps, TensorFlow, Statistics",Master,1,Healthcare,2024-07-29,2024-09-25,1413,5.2,Smart Analytics +AI04518,Deep Learning Engineer,61598,USD,61598,EX,FT,India,M,India,50,"Linux, Deep Learning, NLP",Bachelor,18,Gaming,2024-04-06,2024-06-04,2247,7,Machine Intelligence Group +AI04519,AI Product Manager,129700,USD,129700,MI,CT,Norway,L,South Korea,0,"Tableau, SQL, Docker",Master,2,Consulting,2025-02-13,2025-03-25,1327,8.3,Autonomous Tech +AI04520,AI Specialist,135809,EUR,115438,SE,FT,Netherlands,S,Netherlands,0,"Scala, R, SQL, Data Visualization, Git",Associate,6,Consulting,2025-03-28,2025-04-22,695,7.3,Autonomous Tech +AI04521,Deep Learning Engineer,238500,EUR,202725,EX,FL,Netherlands,S,South Korea,0,"Linux, Computer Vision, Kubernetes",Associate,18,Transportation,2024-04-01,2024-05-27,1845,6,AI Innovations +AI04522,Head of AI,50048,SGD,65062,EN,FT,Singapore,S,Czech Republic,50,"PyTorch, TensorFlow, Docker",Associate,0,Energy,2024-05-14,2024-06-03,680,7.1,Algorithmic Solutions +AI04523,Autonomous Systems Engineer,164914,USD,164914,SE,PT,United States,L,United States,50,"Hadoop, TensorFlow, Linux, MLOps, GCP",Master,8,Consulting,2024-03-04,2024-04-22,917,7.1,Cloud AI Solutions +AI04524,AI Consultant,181134,CAD,226418,EX,CT,Canada,M,Canada,0,"Git, PyTorch, GCP, AWS, Mathematics",Master,19,Healthcare,2024-01-15,2024-02-05,2366,5.9,Machine Intelligence Group +AI04525,AI Specialist,81453,EUR,69235,EN,FL,Netherlands,L,Netherlands,50,"TensorFlow, Java, Deep Learning, Tableau",Associate,1,Education,2025-02-09,2025-03-27,2323,9.2,DataVision Ltd +AI04526,Machine Learning Researcher,52632,USD,52632,EN,FL,Israel,S,Israel,50,"SQL, Spark, Tableau, Scala",PhD,0,Retail,2024-03-15,2024-04-16,585,8.8,Neural Networks Co +AI04527,Data Analyst,77848,USD,77848,EN,FL,Denmark,L,Denmark,50,"SQL, GCP, PyTorch, Java",PhD,0,Government,2025-02-04,2025-03-16,1735,6.9,DataVision Ltd +AI04528,Autonomous Systems Engineer,117315,USD,117315,SE,PT,Sweden,M,Singapore,0,"Computer Vision, Java, MLOps, Kubernetes, Docker",PhD,5,Retail,2024-08-23,2024-10-07,1852,9,DeepTech Ventures +AI04529,AI Architect,166998,USD,166998,SE,CT,Denmark,S,Israel,100,"MLOps, Linux, Data Visualization, Computer Vision",Associate,7,Manufacturing,2025-02-18,2025-04-09,1054,7.3,Neural Networks Co +AI04530,Head of AI,174172,GBP,130629,SE,CT,United Kingdom,L,United Kingdom,50,"TensorFlow, Python, Linux, Hadoop, Statistics",Associate,8,Healthcare,2024-11-09,2024-12-24,574,5.7,Machine Intelligence Group +AI04531,ML Ops Engineer,93049,CAD,116311,MI,CT,Canada,M,Canada,100,"PyTorch, Data Visualization, SQL, Kubernetes",Bachelor,2,Consulting,2025-04-27,2025-05-12,812,7.4,DeepTech Ventures +AI04532,Robotics Engineer,139395,USD,139395,SE,FL,Sweden,L,Sweden,100,"Docker, SQL, Scala, MLOps, Kubernetes",Master,6,Retail,2024-01-08,2024-02-04,1681,6.5,Algorithmic Solutions +AI04533,AI Software Engineer,207936,USD,207936,SE,FT,Norway,L,Norway,100,"Hadoop, Python, AWS, Linux",Bachelor,6,Technology,2024-11-16,2024-12-12,2030,5,Cognitive Computing +AI04534,Machine Learning Engineer,188512,EUR,160235,EX,CT,Austria,M,Austria,50,"Docker, Git, SQL, Spark, Linux",Master,18,Healthcare,2024-04-03,2024-06-09,1323,9.7,Smart Analytics +AI04535,AI Specialist,176564,GBP,132423,EX,FT,United Kingdom,M,Egypt,0,"Azure, Kubernetes, Linux, SQL",PhD,11,Finance,2024-01-11,2024-02-21,631,7.3,Predictive Systems +AI04536,Research Scientist,156332,GBP,117249,SE,CT,United Kingdom,L,Denmark,100,"Kubernetes, Mathematics, Hadoop, MLOps",Bachelor,7,Manufacturing,2025-02-19,2025-04-25,1511,10,Cognitive Computing +AI04537,Data Scientist,113860,USD,113860,MI,FL,United States,M,United States,50,"Tableau, Kubernetes, Java, MLOps",Bachelor,4,Finance,2024-09-16,2024-11-20,1497,9,DeepTech Ventures +AI04538,Data Scientist,95951,USD,95951,MI,FL,Finland,L,Finland,0,"SQL, Mathematics, Kubernetes, Python",Master,2,Media,2024-10-14,2024-12-07,2141,8.2,AI Innovations +AI04539,Data Engineer,177286,CHF,159557,SE,CT,Switzerland,S,Switzerland,50,"Scala, GCP, SQL, MLOps",Associate,7,Manufacturing,2024-04-28,2024-06-22,2473,9.8,Predictive Systems +AI04540,AI Software Engineer,53681,CAD,67101,EN,CT,Canada,M,Canada,50,"Tableau, Azure, Java, Data Visualization",Associate,0,Energy,2024-05-04,2024-05-26,2123,8.3,AI Innovations +AI04541,AI Research Scientist,130939,AUD,176768,SE,FL,Australia,M,Ireland,100,"Data Visualization, GCP, SQL, NLP, Linux",Bachelor,5,Automotive,2024-07-18,2024-09-10,562,6.6,Autonomous Tech +AI04542,Principal Data Scientist,39395,USD,39395,SE,PT,India,M,India,0,"Spark, Data Visualization, Linux, Deep Learning",PhD,7,Transportation,2024-10-05,2024-10-28,1164,8.6,Algorithmic Solutions +AI04543,AI Architect,123582,USD,123582,MI,FL,Norway,M,Norway,0,"Scala, Java, Spark, Mathematics",PhD,3,Manufacturing,2025-03-21,2025-04-10,630,9.6,Predictive Systems +AI04544,AI Research Scientist,136808,EUR,116287,EX,CT,Netherlands,S,Netherlands,0,"Git, TensorFlow, Scala, GCP, Python",PhD,17,Manufacturing,2024-02-20,2024-03-10,2222,8.2,Advanced Robotics +AI04545,Computer Vision Engineer,38736,USD,38736,SE,FT,India,S,India,100,"Python, Java, TensorFlow, Computer Vision, AWS",Bachelor,5,Retail,2025-03-25,2025-04-29,544,9,TechCorp Inc +AI04546,Data Engineer,111692,USD,111692,SE,CT,Ireland,M,Ireland,0,"Python, Scala, Statistics, NLP, Git",Associate,8,Manufacturing,2025-01-27,2025-03-22,2475,5.5,AI Innovations +AI04547,Robotics Engineer,320350,CHF,288315,EX,FT,Switzerland,M,Switzerland,100,"MLOps, PyTorch, Python, Spark",Bachelor,16,Energy,2024-07-25,2024-09-30,2313,6.9,Digital Transformation LLC +AI04548,Data Scientist,148284,EUR,126041,EX,FL,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,14,Consulting,2024-01-26,2024-03-04,1188,5.7,TechCorp Inc +AI04549,AI Research Scientist,164350,USD,164350,EX,FL,Israel,S,Israel,50,"Java, Docker, Azure, Computer Vision, AWS",Master,19,Consulting,2025-04-20,2025-06-23,2272,9.9,Quantum Computing Inc +AI04550,AI Specialist,300752,CHF,270677,EX,FT,Switzerland,L,Switzerland,100,"Mathematics, Hadoop, Data Visualization, R",Associate,14,Retail,2024-08-16,2024-08-30,1923,9.1,Smart Analytics +AI04551,Research Scientist,71687,USD,71687,SE,CT,China,L,Singapore,0,"Docker, AWS, Computer Vision, Java",Associate,7,Education,2024-02-24,2024-04-25,1076,8,Cloud AI Solutions +AI04552,Robotics Engineer,78911,CAD,98639,MI,FL,Canada,S,Canada,100,"Data Visualization, Python, GCP",PhD,4,Government,2024-10-21,2024-11-17,1168,9.7,Machine Intelligence Group +AI04553,Machine Learning Researcher,85224,USD,85224,MI,CT,Israel,L,Israel,50,"NLP, Hadoop, GCP",Bachelor,4,Consulting,2024-12-18,2025-02-27,1115,7,Cloud AI Solutions +AI04554,AI Research Scientist,30653,USD,30653,MI,PT,India,S,India,100,"Java, TensorFlow, R, GCP",Bachelor,2,Media,2025-03-06,2025-04-14,2316,9.7,Neural Networks Co +AI04555,AI Consultant,125667,USD,125667,MI,FT,Sweden,L,Ireland,100,"Java, Computer Vision, MLOps, Tableau",Bachelor,3,Healthcare,2024-08-06,2024-09-08,1356,7.9,Quantum Computing Inc +AI04556,Data Scientist,59008,USD,59008,EN,FT,Finland,M,Argentina,100,"MLOps, Python, Java, AWS, TensorFlow",Bachelor,1,Education,2024-01-03,2024-03-02,816,8.3,Machine Intelligence Group +AI04557,Head of AI,87615,USD,87615,MI,FL,Norway,S,Norway,100,"Linux, Computer Vision, Statistics, Deep Learning",Bachelor,3,Education,2024-03-18,2024-04-27,2060,6.4,Algorithmic Solutions +AI04558,AI Specialist,64656,USD,64656,SE,FL,China,M,China,0,"NLP, SQL, Spark, TensorFlow, MLOps",PhD,7,Government,2024-11-29,2024-12-24,1692,5.7,TechCorp Inc +AI04559,NLP Engineer,236797,JPY,26047670,EX,CT,Japan,S,Turkey,50,"Scala, Java, Python, Kubernetes",Master,17,Automotive,2024-03-20,2024-05-11,1015,8.6,Autonomous Tech +AI04560,AI Research Scientist,69325,EUR,58926,EN,FT,Germany,L,United Kingdom,0,"SQL, MLOps, Spark, Computer Vision",Associate,0,Finance,2024-06-12,2024-08-02,1048,9.9,TechCorp Inc +AI04561,Research Scientist,100014,USD,100014,SE,FL,South Korea,S,South Korea,50,"Scala, Java, Deep Learning, NLP",Associate,7,Finance,2024-02-23,2024-03-14,1690,9.1,AI Innovations +AI04562,ML Ops Engineer,145257,EUR,123468,SE,FT,France,L,France,50,"SQL, MLOps, Python, NLP",Bachelor,5,Transportation,2025-04-21,2025-06-14,1793,7.5,Cloud AI Solutions +AI04563,Robotics Engineer,129098,SGD,167827,SE,CT,Singapore,M,Singapore,100,"AWS, TensorFlow, Python, Tableau, Statistics",Master,9,Real Estate,2024-04-25,2024-05-22,513,6.6,Autonomous Tech +AI04564,AI Research Scientist,58400,USD,58400,EX,FL,India,M,Australia,0,"R, Mathematics, Computer Vision",Master,15,Real Estate,2024-12-04,2025-01-23,1072,6.4,Machine Intelligence Group +AI04565,Data Engineer,146073,USD,146073,EX,CT,Israel,S,Israel,100,"Docker, Kubernetes, GCP",Bachelor,19,Manufacturing,2024-09-01,2024-09-23,2328,5.9,DataVision Ltd +AI04566,ML Ops Engineer,110488,EUR,93915,SE,FL,Germany,M,Germany,100,"MLOps, NLP, SQL",PhD,9,Manufacturing,2025-02-23,2025-05-05,2166,7.7,Cloud AI Solutions +AI04567,Data Analyst,71058,USD,71058,EN,FL,Norway,M,United States,100,"Computer Vision, SQL, NLP",Master,0,Consulting,2024-04-04,2024-06-14,1040,6.3,Cloud AI Solutions +AI04568,Machine Learning Engineer,231110,SGD,300443,EX,FT,Singapore,L,Singapore,100,"Hadoop, Scala, GCP, PyTorch",Associate,17,Energy,2024-12-14,2025-01-17,2122,8.3,TechCorp Inc +AI04569,Data Engineer,138306,EUR,117560,SE,CT,Germany,L,Germany,100,"Java, Kubernetes, AWS",Master,8,Finance,2025-04-27,2025-05-30,1642,9.6,Algorithmic Solutions +AI04570,Principal Data Scientist,187455,CHF,168710,EX,PT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Azure, Deep Learning, Tableau",PhD,12,Energy,2024-04-18,2024-06-05,2092,8.1,Autonomous Tech +AI04571,Autonomous Systems Engineer,94272,CHF,84845,EN,FT,Switzerland,L,Switzerland,100,"Statistics, SQL, Hadoop, Scala, Data Visualization",PhD,1,Government,2024-03-02,2024-04-04,1216,7.8,DeepTech Ventures +AI04572,ML Ops Engineer,136910,EUR,116374,EX,FT,Germany,S,Philippines,100,"Java, AWS, Computer Vision",Bachelor,17,Consulting,2024-10-15,2024-11-27,1487,5.6,Cloud AI Solutions +AI04573,AI Product Manager,155455,CAD,194319,EX,PT,Canada,L,Luxembourg,0,"Java, GCP, Kubernetes, AWS, NLP",Bachelor,16,Transportation,2024-06-01,2024-06-15,625,5.7,Predictive Systems +AI04574,Machine Learning Engineer,218908,JPY,24079880,EX,FT,Japan,S,Japan,100,"Tableau, AWS, MLOps",Associate,14,Finance,2025-01-11,2025-02-25,1370,6.6,Neural Networks Co +AI04575,AI Specialist,58456,EUR,49688,EN,FL,Austria,S,Austria,0,"Scala, Computer Vision, Statistics",Associate,1,Media,2024-12-27,2025-01-16,1460,6.5,Quantum Computing Inc +AI04576,ML Ops Engineer,79370,GBP,59528,EN,CT,United Kingdom,M,Chile,50,"PyTorch, TensorFlow, R",PhD,1,Technology,2025-01-12,2025-03-13,2208,5.9,DeepTech Ventures +AI04577,Head of AI,56598,USD,56598,SE,FT,China,L,China,50,"MLOps, Git, Java, TensorFlow",PhD,8,Retail,2024-02-18,2024-03-28,1009,8.7,DeepTech Ventures +AI04578,Machine Learning Researcher,164862,USD,164862,EX,FL,United States,M,United States,50,"NLP, Linux, Kubernetes, SQL, MLOps",Master,11,Manufacturing,2024-07-28,2024-09-18,1904,6.9,Algorithmic Solutions +AI04579,AI Consultant,78776,USD,78776,MI,PT,South Korea,L,Chile,100,"Data Visualization, MLOps, AWS",Associate,3,Technology,2025-01-11,2025-02-25,2434,7.7,Predictive Systems +AI04580,Principal Data Scientist,107481,GBP,80611,MI,FT,United Kingdom,M,Canada,50,"Linux, R, Python",Master,4,Manufacturing,2024-06-19,2024-08-24,2101,6.1,Cloud AI Solutions +AI04581,AI Specialist,165800,GBP,124350,EX,FL,United Kingdom,M,United Kingdom,50,"Git, Linux, Deep Learning, MLOps, AWS",Associate,11,Energy,2024-09-08,2024-09-26,883,8.3,AI Innovations +AI04582,Data Scientist,114567,EUR,97382,MI,FL,Netherlands,L,Netherlands,100,"Java, Linux, Python, Hadoop, MLOps",Bachelor,4,Technology,2024-10-23,2024-12-23,931,9.8,Digital Transformation LLC +AI04583,Research Scientist,45528,EUR,38699,EN,FL,France,S,France,100,"Python, Azure, Data Visualization, Deep Learning",Bachelor,1,Telecommunications,2024-12-24,2025-02-18,1363,8.7,Neural Networks Co +AI04584,Computer Vision Engineer,156683,GBP,117512,SE,FT,United Kingdom,M,Nigeria,100,"Computer Vision, AWS, Kubernetes, MLOps, Deep Learning",Bachelor,7,Finance,2024-01-22,2024-03-28,1328,8.6,Digital Transformation LLC +AI04585,Machine Learning Engineer,38720,USD,38720,SE,FL,India,S,India,50,"Kubernetes, Linux, Computer Vision, TensorFlow, NLP",PhD,8,Consulting,2024-04-12,2024-04-30,785,8.3,Cognitive Computing +AI04586,ML Ops Engineer,114629,AUD,154749,SE,FL,Australia,M,Australia,0,"R, Azure, SQL",Master,7,Technology,2025-04-19,2025-05-10,1688,5.4,Neural Networks Co +AI04587,Computer Vision Engineer,57392,CAD,71740,EN,FT,Canada,L,Canada,0,"Tableau, SQL, Kubernetes, Hadoop",Associate,1,Gaming,2024-11-30,2025-01-07,1624,6.3,Advanced Robotics +AI04588,Data Scientist,341117,USD,341117,EX,FL,Norway,L,Norway,50,"Linux, Docker, Kubernetes",Bachelor,18,Telecommunications,2024-01-06,2024-01-24,790,8.5,DataVision Ltd +AI04589,ML Ops Engineer,86046,GBP,64535,MI,CT,United Kingdom,S,United Kingdom,0,"Git, R, Spark, Deep Learning, Data Visualization",Bachelor,3,Transportation,2025-01-12,2025-02-21,1892,9.8,Algorithmic Solutions +AI04590,Computer Vision Engineer,149937,USD,149937,EX,PT,South Korea,S,South Korea,50,"Hadoop, Git, SQL",Master,18,Gaming,2024-07-31,2024-10-10,2454,5.1,Machine Intelligence Group +AI04591,Principal Data Scientist,80029,SGD,104038,EN,CT,Singapore,M,Ghana,0,"TensorFlow, MLOps, Data Visualization, Java",Associate,0,Technology,2025-02-26,2025-05-05,2367,9.5,Quantum Computing Inc +AI04592,Machine Learning Engineer,165691,GBP,124268,SE,PT,United Kingdom,L,Ukraine,0,"Scala, Tableau, SQL",Bachelor,9,Healthcare,2024-05-01,2024-06-09,1945,6,Advanced Robotics +AI04593,Autonomous Systems Engineer,141765,EUR,120500,SE,FL,Netherlands,M,Netherlands,0,"Python, PyTorch, Tableau",PhD,7,Telecommunications,2024-06-05,2024-07-31,1988,8.6,Algorithmic Solutions +AI04594,AI Research Scientist,47675,USD,47675,EN,PT,Ireland,S,Ireland,100,"Git, AWS, R, Mathematics, Kubernetes",Master,0,Energy,2024-02-08,2024-03-06,1872,8,Smart Analytics +AI04595,Data Analyst,114484,USD,114484,EX,CT,China,L,China,0,"Spark, PyTorch, Tableau",Bachelor,13,Consulting,2024-12-14,2025-02-08,2154,6.9,Neural Networks Co +AI04596,Machine Learning Engineer,88276,EUR,75035,MI,FT,Austria,S,Norway,100,"TensorFlow, SQL, R, Tableau",Master,4,Healthcare,2024-05-29,2024-06-26,2038,8.3,Cognitive Computing +AI04597,Autonomous Systems Engineer,174969,USD,174969,SE,FT,Sweden,L,Sweden,50,"Java, Azure, R",Associate,8,Telecommunications,2024-11-02,2024-11-18,2445,9.2,Digital Transformation LLC +AI04598,NLP Engineer,193261,USD,193261,EX,FT,South Korea,L,South Korea,50,"Data Visualization, Spark, R, Mathematics, Linux",Associate,10,Education,2024-12-23,2025-03-06,1301,8.7,DataVision Ltd +AI04599,Deep Learning Engineer,58905,USD,58905,EX,CT,India,S,Hungary,100,"SQL, NLP, PyTorch",PhD,12,Automotive,2024-03-26,2024-06-01,1885,5.1,DeepTech Ventures +AI04600,AI Software Engineer,155003,CAD,193754,SE,CT,Canada,L,South Korea,50,"Azure, AWS, Docker",Master,5,Education,2025-04-11,2025-06-16,1609,5.7,Autonomous Tech +AI04601,AI Research Scientist,137955,USD,137955,MI,PT,United States,L,Turkey,50,"TensorFlow, Python, PyTorch, Linux, NLP",PhD,2,Healthcare,2025-04-23,2025-05-24,1334,9.6,AI Innovations +AI04602,NLP Engineer,127644,USD,127644,SE,CT,Finland,M,Finland,100,"MLOps, SQL, Computer Vision",Master,6,Consulting,2024-08-08,2024-10-19,1112,7.2,Future Systems +AI04603,Data Scientist,131769,EUR,112004,SE,FT,France,M,Romania,0,"Python, AWS, MLOps, GCP, SQL",Associate,7,Education,2024-07-11,2024-09-04,1615,9.2,AI Innovations +AI04604,AI Consultant,69280,CAD,86600,MI,FL,Canada,S,Canada,100,"GCP, Azure, Spark",Associate,4,Education,2024-05-26,2024-08-04,2319,8.4,Cloud AI Solutions +AI04605,Computer Vision Engineer,298482,USD,298482,EX,FT,United States,M,United States,0,"Mathematics, Deep Learning, MLOps, PyTorch, AWS",PhD,10,Real Estate,2024-08-11,2024-09-03,2282,9.1,Cognitive Computing +AI04606,Principal Data Scientist,91961,USD,91961,SE,FT,Ireland,S,Ireland,0,"Scala, GCP, Spark, SQL, Mathematics",Master,5,Education,2024-09-08,2024-10-30,781,9,Quantum Computing Inc +AI04607,Research Scientist,108071,EUR,91860,MI,FL,France,L,France,0,"Docker, AWS, GCP, Computer Vision, Azure",Master,4,Education,2024-07-26,2024-09-28,843,8.8,DeepTech Ventures +AI04608,Principal Data Scientist,89067,USD,89067,MI,CT,Denmark,S,India,0,"Python, TensorFlow, AWS, Computer Vision, SQL",PhD,2,Telecommunications,2025-01-06,2025-03-05,1228,8.5,Neural Networks Co +AI04609,Data Engineer,80773,USD,80773,MI,FT,South Korea,S,South Korea,50,"Python, Kubernetes, NLP, Tableau",Master,2,Real Estate,2024-11-01,2024-11-16,1040,5,AI Innovations +AI04610,Machine Learning Researcher,246330,CHF,221697,EX,PT,Switzerland,M,Switzerland,100,"Scala, PyTorch, AWS",Master,17,Government,2025-01-11,2025-03-04,2363,6,Autonomous Tech +AI04611,AI Software Engineer,158632,USD,158632,EX,FL,Sweden,L,Australia,50,"AWS, Kubernetes, TensorFlow, Statistics, SQL",PhD,16,Automotive,2025-03-16,2025-04-19,969,9.8,Quantum Computing Inc +AI04612,Computer Vision Engineer,55191,GBP,41393,EN,FT,United Kingdom,M,United Kingdom,100,"Hadoop, Java, Computer Vision, Spark",Associate,0,Manufacturing,2025-04-03,2025-06-05,2166,6,Autonomous Tech +AI04613,Data Analyst,290447,USD,290447,EX,PT,Norway,L,Norway,100,"R, Mathematics, Scala, PyTorch",Bachelor,17,Energy,2025-03-16,2025-05-13,2278,6.3,Smart Analytics +AI04614,ML Ops Engineer,162470,EUR,138100,EX,PT,Germany,M,Germany,100,"NLP, Docker, GCP",PhD,16,Manufacturing,2024-03-01,2024-05-08,2135,8.3,DeepTech Ventures +AI04615,Data Engineer,237565,USD,237565,EX,CT,Sweden,L,Spain,0,"Spark, Docker, Scala, Computer Vision, Tableau",PhD,13,Energy,2024-09-17,2024-10-29,1692,7.5,Digital Transformation LLC +AI04616,NLP Engineer,74020,USD,74020,MI,FT,Finland,M,Indonesia,100,"SQL, Spark, NLP, Data Visualization, Computer Vision",Master,2,Automotive,2024-03-06,2024-05-13,553,8.5,TechCorp Inc +AI04617,Principal Data Scientist,184394,USD,184394,EX,CT,Sweden,M,Sweden,0,"Spark, Kubernetes, MLOps, NLP, PyTorch",Bachelor,16,Healthcare,2024-04-03,2024-06-08,659,7.3,Autonomous Tech +AI04618,Data Scientist,195735,USD,195735,EX,FT,Norway,M,Norway,0,"Kubernetes, SQL, NLP",Master,14,Real Estate,2024-02-01,2024-03-07,2095,5.8,Cognitive Computing +AI04619,Machine Learning Engineer,321668,USD,321668,EX,FT,Norway,M,Norway,50,"TensorFlow, Git, Python, R",Associate,17,Finance,2024-05-14,2024-06-13,1411,5.6,Quantum Computing Inc +AI04620,Data Analyst,132287,USD,132287,EX,FL,South Korea,L,South Korea,100,"R, Java, NLP",Associate,16,Energy,2025-03-08,2025-04-02,520,7.3,Neural Networks Co +AI04621,AI Architect,70147,CHF,63132,EN,PT,Switzerland,S,China,0,"TensorFlow, NLP, Linux",Master,1,Transportation,2024-05-17,2024-06-18,887,9.1,Autonomous Tech +AI04622,Head of AI,58977,USD,58977,SE,FL,China,L,China,50,"Docker, GCP, Tableau, Computer Vision, Statistics",PhD,7,Consulting,2025-03-15,2025-05-01,1835,6.9,DeepTech Ventures +AI04623,Head of AI,115529,GBP,86647,MI,FT,United Kingdom,M,United Kingdom,50,"Java, Data Visualization, AWS",Master,2,Automotive,2024-05-03,2024-05-30,1604,5.3,Predictive Systems +AI04624,AI Specialist,123402,USD,123402,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Mathematics",Bachelor,5,Gaming,2024-02-15,2024-03-13,697,8.5,DataVision Ltd +AI04625,Robotics Engineer,81236,USD,81236,MI,PT,Sweden,S,Italy,0,"Scala, Deep Learning, Tableau, R, Python",Bachelor,3,Automotive,2024-10-06,2024-11-13,1216,8.6,Predictive Systems +AI04626,Deep Learning Engineer,23762,USD,23762,EN,FT,China,S,China,50,"Computer Vision, Kubernetes, SQL",Associate,1,Automotive,2024-05-10,2024-06-11,1602,8.5,Quantum Computing Inc +AI04627,Head of AI,80966,USD,80966,EN,CT,Norway,M,Norway,0,"Git, Kubernetes, Hadoop",Associate,1,Education,2024-03-20,2024-05-14,2283,6.1,Quantum Computing Inc +AI04628,AI Product Manager,184463,USD,184463,EX,FT,Denmark,M,United Kingdom,0,"Spark, Statistics, Linux, Java, Deep Learning",Master,10,Finance,2024-07-10,2024-08-22,944,9.5,Future Systems +AI04629,Machine Learning Engineer,80922,CHF,72830,EN,FL,Switzerland,S,Switzerland,100,"R, Azure, MLOps, Tableau, AWS",Bachelor,0,Automotive,2024-10-08,2024-11-21,1763,6.1,TechCorp Inc +AI04630,Data Engineer,225786,SGD,293522,EX,FL,Singapore,L,Netherlands,50,"Python, Spark, Deep Learning, Statistics",Bachelor,12,Transportation,2024-11-20,2024-12-20,2261,5.7,Advanced Robotics +AI04631,AI Specialist,174292,USD,174292,EX,FT,Sweden,S,Colombia,50,"Kubernetes, R, Data Visualization",PhD,10,Energy,2024-07-05,2024-08-16,1578,5.5,Future Systems +AI04632,AI Architect,141209,USD,141209,SE,FL,Finland,M,Finland,50,"Java, PyTorch, Tableau",Associate,9,Government,2025-03-15,2025-03-31,1379,5.6,TechCorp Inc +AI04633,AI Architect,33494,USD,33494,EN,FT,China,M,Chile,0,"R, MLOps, SQL, NLP",PhD,1,Gaming,2025-04-18,2025-05-05,2021,8.1,Algorithmic Solutions +AI04634,Head of AI,102081,GBP,76561,MI,FL,United Kingdom,L,Romania,100,"TensorFlow, Git, Spark, Data Visualization",Master,4,Manufacturing,2024-08-05,2024-09-27,1236,5.9,Cloud AI Solutions +AI04635,Computer Vision Engineer,142338,EUR,120987,SE,PT,Netherlands,M,Netherlands,100,"Scala, Kubernetes, Azure, Python",Master,6,Real Estate,2024-04-29,2024-07-02,1165,5.7,Neural Networks Co +AI04636,Robotics Engineer,111416,USD,111416,MI,FL,United States,S,United States,50,"Linux, Java, MLOps, Azure",Bachelor,3,Telecommunications,2024-11-08,2024-12-21,1032,6.8,AI Innovations +AI04637,Data Analyst,171510,USD,171510,EX,CT,Sweden,S,Austria,0,"SQL, Git, PyTorch, TensorFlow, Tableau",Master,14,Gaming,2024-05-10,2024-07-02,845,6.8,Predictive Systems +AI04638,Robotics Engineer,32757,USD,32757,EN,CT,China,S,Philippines,0,"Spark, Linux, PyTorch, Mathematics, Python",PhD,0,Energy,2024-04-27,2024-06-13,1275,9.6,TechCorp Inc +AI04639,Data Analyst,78323,GBP,58742,MI,CT,United Kingdom,S,United States,0,"TensorFlow, GCP, Mathematics, Java, Linux",Bachelor,3,Real Estate,2025-04-17,2025-05-09,942,8.2,DataVision Ltd +AI04640,Robotics Engineer,68649,GBP,51487,EN,FL,United Kingdom,S,Austria,0,"Hadoop, Git, Spark, PyTorch, Linux",PhD,1,Finance,2024-11-02,2024-12-07,1578,9.7,AI Innovations +AI04641,Deep Learning Engineer,82078,AUD,110805,MI,FL,Australia,M,Australia,50,"PyTorch, Java, Scala, Computer Vision, R",Bachelor,2,Energy,2025-03-30,2025-05-07,1484,6.2,Future Systems +AI04642,AI Software Engineer,65931,USD,65931,EN,CT,Denmark,S,Denmark,0,"Kubernetes, PyTorch, Mathematics, Linux, Git",Master,1,Media,2024-06-24,2024-08-13,691,6.8,DataVision Ltd +AI04643,Research Scientist,207846,USD,207846,EX,PT,South Korea,L,South Korea,50,"Linux, MLOps, SQL, Scala",Bachelor,15,Gaming,2024-06-12,2024-07-11,1452,6.7,Autonomous Tech +AI04644,Principal Data Scientist,107642,GBP,80732,MI,PT,United Kingdom,M,United Kingdom,0,"PyTorch, TensorFlow, Python, R, Data Visualization",Bachelor,4,Healthcare,2024-06-30,2024-07-31,2023,5.9,Cloud AI Solutions +AI04645,Head of AI,51450,EUR,43733,EN,PT,Germany,M,Germany,100,"Kubernetes, SQL, Tableau, MLOps, Deep Learning",PhD,0,Finance,2024-08-13,2024-08-31,1211,8.3,DeepTech Ventures +AI04646,Data Scientist,79522,CAD,99403,EN,CT,Canada,L,Germany,100,"Hadoop, Data Visualization, GCP",PhD,0,Gaming,2024-09-24,2024-11-29,802,8.6,Cloud AI Solutions +AI04647,Machine Learning Engineer,100881,USD,100881,MI,FT,Sweden,L,Sweden,100,"R, Azure, Kubernetes, Hadoop",Bachelor,4,Real Estate,2024-03-22,2024-04-21,631,5.3,Advanced Robotics +AI04648,Research Scientist,89648,USD,89648,MI,PT,Ireland,L,Japan,50,"Data Visualization, NLP, Scala, Python",Bachelor,2,Healthcare,2025-03-22,2025-04-18,785,9.6,Neural Networks Co +AI04649,Principal Data Scientist,227077,JPY,24978470,EX,FT,Japan,S,Japan,50,"NLP, PyTorch, GCP, Azure, AWS",Associate,16,Healthcare,2024-06-07,2024-08-15,1178,6.9,Autonomous Tech +AI04650,Data Scientist,141613,EUR,120371,SE,CT,France,L,Mexico,50,"Git, SQL, AWS",Associate,5,Technology,2024-06-13,2024-07-05,1876,9.5,Advanced Robotics +AI04651,AI Specialist,197086,USD,197086,SE,PT,Denmark,L,Denmark,50,"AWS, Linux, PyTorch, Spark",Associate,8,Retail,2024-05-20,2024-06-18,2105,7.5,Smart Analytics +AI04652,Research Scientist,34933,USD,34933,MI,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, Linux, Java",PhD,2,Media,2025-03-20,2025-04-07,683,9.8,AI Innovations +AI04653,AI Consultant,57403,AUD,77494,EN,PT,Australia,M,Australia,0,"Computer Vision, Java, Git, Hadoop",Associate,0,Automotive,2024-09-11,2024-10-22,584,8,TechCorp Inc +AI04654,Robotics Engineer,217171,GBP,162878,EX,FL,United Kingdom,S,United Kingdom,0,"R, Java, Data Visualization, Git, TensorFlow",Master,16,Healthcare,2024-04-24,2024-07-01,836,6.2,AI Innovations +AI04655,Computer Vision Engineer,85086,USD,85086,EX,FL,China,L,China,50,"Tableau, GCP, Python, Azure",Associate,19,Finance,2024-05-03,2024-07-02,1158,9.4,Quantum Computing Inc +AI04656,AI Product Manager,77309,GBP,57982,EN,CT,United Kingdom,L,Netherlands,50,"Python, R, Computer Vision, NLP, Java",Associate,1,Healthcare,2024-07-30,2024-09-21,936,9.9,Advanced Robotics +AI04657,AI Software Engineer,152616,EUR,129724,SE,FT,Netherlands,M,Malaysia,0,"Git, Scala, Deep Learning, Linux, R",Bachelor,5,Education,2024-05-30,2024-07-22,801,9.5,Cloud AI Solutions +AI04658,AI Architect,80354,CAD,100443,MI,FT,Canada,M,Canada,100,"SQL, AWS, MLOps, Linux, Python",Bachelor,3,Government,2025-02-12,2025-03-25,2160,5.3,AI Innovations +AI04659,Principal Data Scientist,130383,USD,130383,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, TensorFlow, Mathematics, Python",PhD,9,Automotive,2024-04-16,2024-06-10,1167,5.6,TechCorp Inc +AI04660,AI Consultant,191150,AUD,258053,EX,PT,Australia,M,India,0,"Kubernetes, Linux, Tableau",Associate,11,Healthcare,2024-12-12,2025-02-09,2246,5,TechCorp Inc +AI04661,AI Specialist,77392,EUR,65783,MI,CT,Germany,S,Germany,50,"TensorFlow, Python, Azure, GCP",Master,4,Telecommunications,2024-05-07,2024-06-23,786,8.2,TechCorp Inc +AI04662,Data Scientist,72963,USD,72963,EN,CT,Israel,L,Israel,50,"Scala, TensorFlow, Deep Learning",Bachelor,0,Energy,2024-09-22,2024-10-31,1307,9.4,Smart Analytics +AI04663,AI Consultant,77791,AUD,105018,EN,FT,Australia,M,Australia,50,"Computer Vision, Git, Azure, Kubernetes, Statistics",Master,0,Real Estate,2024-04-06,2024-04-30,1900,7.2,DataVision Ltd +AI04664,Robotics Engineer,150499,EUR,127924,EX,CT,Austria,L,Russia,100,"Scala, Kubernetes, PyTorch, TensorFlow",Associate,17,Technology,2024-08-04,2024-10-07,1341,9.2,TechCorp Inc +AI04665,Principal Data Scientist,79579,USD,79579,MI,FT,Sweden,M,Sweden,0,"Linux, Python, GCP",PhD,4,Media,2025-01-16,2025-03-01,1594,6.1,DeepTech Ventures +AI04666,AI Software Engineer,251411,EUR,213699,EX,CT,Germany,L,Germany,100,"Python, Kubernetes, TensorFlow, GCP, Scala",Master,11,Retail,2024-02-07,2024-04-13,581,8.3,Autonomous Tech +AI04667,AI Specialist,54870,USD,54870,MI,FT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker, Linux",Master,3,Transportation,2024-05-24,2024-07-18,1639,8.5,Machine Intelligence Group +AI04668,ML Ops Engineer,104878,EUR,89146,SE,FL,France,S,France,0,"PyTorch, Mathematics, Linux, Git, Deep Learning",Master,9,Healthcare,2025-04-15,2025-05-31,597,9.6,Cognitive Computing +AI04669,Data Scientist,76528,USD,76528,MI,FL,South Korea,L,Sweden,50,"TensorFlow, PyTorch, Docker, NLP, Computer Vision",Master,2,Automotive,2024-05-09,2024-06-14,1549,5.7,Cognitive Computing +AI04670,Autonomous Systems Engineer,372494,CHF,335245,EX,FL,Switzerland,L,Switzerland,50,"Kubernetes, Scala, Java, Git, MLOps",Associate,18,Media,2024-01-15,2024-02-24,1253,8.8,Predictive Systems +AI04671,Machine Learning Engineer,135702,USD,135702,SE,PT,Finland,M,Belgium,100,"Scala, Git, Computer Vision",Bachelor,5,Telecommunications,2024-07-23,2024-08-21,563,8.4,Predictive Systems +AI04672,AI Software Engineer,75693,USD,75693,EN,FT,Denmark,S,Denmark,100,"PyTorch, Kubernetes, Azure",Associate,1,Automotive,2025-04-19,2025-06-09,690,9.8,Machine Intelligence Group +AI04673,Data Scientist,104982,USD,104982,EN,FL,Norway,L,Norway,50,"Java, Tableau, Mathematics, Scala",Bachelor,1,Transportation,2025-03-16,2025-04-20,1806,5.6,Advanced Robotics +AI04674,Research Scientist,244711,EUR,208004,EX,FT,Austria,L,Austria,50,"SQL, NLP, MLOps",Master,12,Government,2024-08-29,2024-10-07,2403,8.7,Future Systems +AI04675,Machine Learning Researcher,45500,USD,45500,EN,CT,South Korea,S,South Korea,50,"TensorFlow, Python, AWS",Master,1,Transportation,2024-01-09,2024-02-24,670,6.9,Autonomous Tech +AI04676,Machine Learning Engineer,117161,USD,117161,EX,FL,Israel,S,Russia,100,"R, Hadoop, Python",Bachelor,14,Automotive,2024-08-06,2024-08-26,1132,5.6,TechCorp Inc +AI04677,ML Ops Engineer,69868,CAD,87335,EN,CT,Canada,M,Turkey,100,"TensorFlow, SQL, Azure, AWS",Master,0,Manufacturing,2024-10-06,2024-11-05,1205,7.8,TechCorp Inc +AI04678,Data Engineer,64406,EUR,54745,EN,CT,Austria,M,Austria,50,"Deep Learning, Kubernetes, R",Bachelor,1,Healthcare,2024-09-07,2024-10-23,1125,9.2,Autonomous Tech +AI04679,AI Consultant,237645,EUR,201998,EX,FL,Netherlands,M,Netherlands,100,"Python, TensorFlow, Deep Learning, NLP",Associate,19,Technology,2025-03-22,2025-04-29,1161,5.5,Autonomous Tech +AI04680,AI Product Manager,49582,USD,49582,EN,FL,Finland,S,Finland,100,"GCP, Java, Python",Master,0,Manufacturing,2024-11-10,2024-11-25,1340,7.8,AI Innovations +AI04681,Data Scientist,83059,USD,83059,MI,PT,Ireland,S,Russia,100,"PyTorch, Data Visualization, Scala, GCP, Mathematics",Associate,3,Transportation,2024-01-02,2024-03-08,837,8.6,Cloud AI Solutions +AI04682,AI Specialist,136959,USD,136959,SE,FT,Ireland,L,Ireland,100,"Mathematics, Git, Statistics",Associate,6,Transportation,2024-02-22,2024-04-03,2084,7.6,Predictive Systems +AI04683,Autonomous Systems Engineer,107694,USD,107694,MI,FT,Denmark,S,Italy,0,"SQL, Mathematics, Tableau, Azure, MLOps",PhD,3,Retail,2024-12-24,2025-01-15,1759,8.1,TechCorp Inc +AI04684,AI Architect,179863,SGD,233822,EX,FT,Singapore,S,Singapore,0,"Data Visualization, Python, TensorFlow, Computer Vision",PhD,13,Telecommunications,2024-08-17,2024-10-29,1456,8.9,Future Systems +AI04685,Principal Data Scientist,138581,USD,138581,SE,CT,Sweden,L,Sweden,0,"Java, R, Linux, Git, MLOps",Master,5,Technology,2024-06-18,2024-08-29,602,9.3,Autonomous Tech +AI04686,Robotics Engineer,167250,GBP,125438,SE,FT,United Kingdom,L,Denmark,100,"Linux, Kubernetes, Computer Vision, Deep Learning, Data Visualization",Master,8,Finance,2024-02-26,2024-04-02,1324,6.9,TechCorp Inc +AI04687,ML Ops Engineer,73285,CAD,91606,MI,FL,Canada,S,Canada,0,"Statistics, AWS, SQL, MLOps",Bachelor,4,Telecommunications,2025-02-19,2025-04-19,1577,7.6,Digital Transformation LLC +AI04688,Machine Learning Researcher,90517,USD,90517,MI,PT,Finland,M,Sweden,50,"NLP, AWS, Scala",Master,3,Retail,2024-05-09,2024-07-02,1600,5.8,Future Systems +AI04689,AI Specialist,137917,USD,137917,EX,FT,Ireland,S,Spain,100,"TensorFlow, SQL, Linux, Python",PhD,17,Automotive,2025-01-01,2025-02-04,1945,6,Cloud AI Solutions +AI04690,AI Architect,113385,EUR,96377,MI,FL,Netherlands,M,Netherlands,100,"Data Visualization, SQL, Git",Bachelor,2,Real Estate,2024-08-12,2024-10-10,1861,7.3,Cognitive Computing +AI04691,Research Scientist,91903,USD,91903,MI,FL,South Korea,L,South Korea,0,"GCP, Git, Tableau",Master,4,Manufacturing,2024-10-24,2024-12-09,1403,5.4,Future Systems +AI04692,Autonomous Systems Engineer,62142,USD,62142,EN,FL,Denmark,S,Denmark,100,"SQL, R, Computer Vision, Statistics",Associate,1,Finance,2024-12-25,2025-02-19,897,8.4,Advanced Robotics +AI04693,Head of AI,162597,EUR,138207,EX,CT,Austria,M,Austria,0,"Computer Vision, MLOps, Python",Associate,13,Technology,2024-02-14,2024-04-04,2369,5,Cognitive Computing +AI04694,AI Product Manager,277090,CHF,249381,EX,PT,Switzerland,S,Switzerland,100,"PyTorch, Deep Learning, Azure",Associate,18,Gaming,2024-07-14,2024-08-10,1405,7.3,DeepTech Ventures +AI04695,AI Architect,111361,EUR,94657,SE,PT,Germany,S,Nigeria,100,"Linux, Scala, Statistics, Python, Computer Vision",Bachelor,7,Media,2024-12-28,2025-02-22,566,5.9,Digital Transformation LLC +AI04696,Data Engineer,124750,USD,124750,SE,CT,Sweden,S,Sweden,50,"Hadoop, Python, NLP",Master,9,Government,2024-03-08,2024-04-13,1770,9.3,Smart Analytics +AI04697,AI Architect,59624,USD,59624,MI,FL,South Korea,M,Netherlands,100,"SQL, Data Visualization, Java, Docker, Linux",PhD,3,Transportation,2024-05-13,2024-06-07,776,5.7,Neural Networks Co +AI04698,AI Consultant,176619,USD,176619,SE,FT,Norway,M,Norway,0,"Git, AWS, Kubernetes, Hadoop",PhD,6,Consulting,2024-08-25,2024-10-17,1981,7.1,Predictive Systems +AI04699,Head of AI,60007,USD,60007,EX,CT,China,S,China,0,"Python, Data Visualization, TensorFlow, Java, Mathematics",Master,17,Education,2025-03-16,2025-04-08,1337,8,Cloud AI Solutions +AI04700,Head of AI,76104,EUR,64688,EN,FL,Germany,M,Germany,0,"Spark, NLP, Deep Learning, Hadoop, Kubernetes",Bachelor,0,Government,2024-01-21,2024-02-26,1394,6.7,Algorithmic Solutions +AI04701,NLP Engineer,116281,USD,116281,SE,CT,Ireland,S,Ireland,100,"Data Visualization, Kubernetes, NLP, Python, Deep Learning",PhD,8,Energy,2024-10-26,2024-12-12,1894,7,Advanced Robotics +AI04702,Autonomous Systems Engineer,67934,USD,67934,EN,FL,Ireland,S,Ireland,0,"SQL, Kubernetes, Python",Associate,1,Transportation,2024-08-05,2024-09-09,946,7.4,Digital Transformation LLC +AI04703,Data Analyst,62548,EUR,53166,EN,FL,Netherlands,M,Singapore,100,"Data Visualization, PyTorch, AWS, Python, Hadoop",PhD,1,Government,2024-11-12,2025-01-21,1149,8.5,Cognitive Computing +AI04704,Machine Learning Researcher,32890,USD,32890,EN,CT,China,L,China,100,"Hadoop, Mathematics, Kubernetes",Bachelor,0,Energy,2025-02-15,2025-03-24,802,9,AI Innovations +AI04705,Computer Vision Engineer,82416,USD,82416,MI,PT,Sweden,S,Sweden,0,"Tableau, GCP, Docker, Kubernetes, Statistics",Master,2,Finance,2024-11-05,2025-01-05,1089,6.6,Predictive Systems +AI04706,Machine Learning Engineer,143048,CAD,178810,SE,PT,Canada,M,Nigeria,50,"R, SQL, AWS, GCP, Data Visualization",Associate,8,Manufacturing,2024-09-19,2024-10-29,571,9.8,Quantum Computing Inc +AI04707,Deep Learning Engineer,76432,USD,76432,EX,CT,India,M,India,100,"MLOps, Kubernetes, SQL, R",Bachelor,11,Technology,2024-11-14,2025-01-14,1773,5,Advanced Robotics +AI04708,ML Ops Engineer,91651,EUR,77903,MI,FT,Germany,L,Belgium,50,"Hadoop, Spark, Data Visualization, Statistics",Bachelor,2,Energy,2024-03-13,2024-04-21,2373,5.1,Autonomous Tech +AI04709,Data Engineer,119672,CHF,107705,EN,PT,Switzerland,L,Switzerland,50,"Mathematics, R, NLP",Associate,0,Energy,2025-02-25,2025-04-11,2305,6.2,Quantum Computing Inc +AI04710,AI Consultant,91372,USD,91372,SE,FL,Finland,S,Finland,0,"Python, GCP, Linux, TensorFlow, R",Master,9,Automotive,2024-04-06,2024-05-29,2201,9.8,Smart Analytics +AI04711,AI Specialist,136154,CHF,122539,MI,FT,Switzerland,M,Switzerland,0,"PyTorch, Docker, Kubernetes, SQL",Associate,2,Technology,2024-09-03,2024-11-05,2425,6.2,Autonomous Tech +AI04712,Robotics Engineer,48395,USD,48395,EX,CT,India,S,United Kingdom,50,"Deep Learning, Azure, Spark, Python",Associate,13,Education,2024-11-21,2024-12-20,2192,5.2,Algorithmic Solutions +AI04713,Machine Learning Engineer,105774,USD,105774,EN,FL,United States,L,United States,0,"PyTorch, MLOps, Docker",Associate,1,Automotive,2024-10-31,2025-01-05,2274,7.1,Digital Transformation LLC +AI04714,Data Analyst,160016,USD,160016,SE,FT,Denmark,S,Denmark,50,"Kubernetes, TensorFlow, Docker, Statistics, Computer Vision",Associate,8,Government,2024-01-31,2024-02-17,1543,8.7,Future Systems +AI04715,Autonomous Systems Engineer,206793,CHF,186114,SE,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Kubernetes",Bachelor,9,Retail,2024-09-04,2024-10-09,1451,7.9,Predictive Systems +AI04716,AI Architect,86168,USD,86168,EX,CT,India,L,India,100,"Mathematics, GCP, Data Visualization, Spark, Java",Bachelor,11,Technology,2024-12-08,2025-02-08,2468,7.7,Cloud AI Solutions +AI04717,AI Consultant,123853,USD,123853,SE,PT,Sweden,L,Sweden,100,"Computer Vision, Python, TensorFlow, Spark, Deep Learning",PhD,7,Retail,2024-04-27,2024-06-29,2048,8,Autonomous Tech +AI04718,AI Specialist,78399,SGD,101919,EN,PT,Singapore,L,Singapore,0,"SQL, GCP, MLOps, Deep Learning",Bachelor,0,Real Estate,2025-03-20,2025-05-19,962,9.3,Predictive Systems +AI04719,Machine Learning Engineer,138128,SGD,179566,SE,FL,Singapore,M,Ukraine,50,"Kubernetes, Deep Learning, TensorFlow",Master,6,Automotive,2025-02-15,2025-03-13,1918,8.5,Algorithmic Solutions +AI04720,Data Engineer,90321,CAD,112901,MI,FL,Canada,S,Canada,50,"Python, Linux, GCP, Hadoop",Master,2,Consulting,2024-06-05,2024-06-26,2352,9.8,Machine Intelligence Group +AI04721,NLP Engineer,90443,CAD,113054,MI,FT,Canada,L,Canada,0,"Git, Hadoop, Azure, Tableau, Java",Associate,2,Retail,2025-04-08,2025-06-15,1599,8.2,Smart Analytics +AI04722,ML Ops Engineer,121587,EUR,103349,SE,PT,Austria,M,Austria,50,"Docker, Python, MLOps, Git",Master,8,Government,2025-02-22,2025-04-16,1807,7.7,Autonomous Tech +AI04723,Principal Data Scientist,226775,CHF,204098,SE,PT,Switzerland,L,Switzerland,0,"Scala, Deep Learning, Statistics",Associate,8,Telecommunications,2024-11-30,2025-01-26,819,5.3,Future Systems +AI04724,AI Research Scientist,97958,USD,97958,SE,PT,Ireland,S,Ireland,50,"Kubernetes, Python, Data Visualization, MLOps",PhD,5,Gaming,2024-12-02,2025-02-11,1617,9.8,Predictive Systems +AI04725,Deep Learning Engineer,59895,SGD,77864,EN,CT,Singapore,S,Singapore,50,"Python, TensorFlow, Computer Vision, Azure",PhD,1,Real Estate,2024-08-03,2024-08-23,1154,6.8,Neural Networks Co +AI04726,Deep Learning Engineer,96051,USD,96051,MI,CT,Norway,S,Norway,50,"GCP, Hadoop, Deep Learning, Computer Vision",Bachelor,3,Telecommunications,2024-04-15,2024-05-15,1776,6.5,TechCorp Inc +AI04727,Data Analyst,194676,USD,194676,EX,FT,United States,S,Russia,100,"GCP, SQL, Statistics, Java",PhD,13,Transportation,2025-04-26,2025-06-26,1204,9.7,Machine Intelligence Group +AI04728,Principal Data Scientist,83606,SGD,108688,EN,CT,Singapore,M,Singapore,100,"Python, Kubernetes, Hadoop",Associate,0,Gaming,2025-02-24,2025-03-29,2429,5.2,Machine Intelligence Group +AI04729,AI Product Manager,35409,USD,35409,EN,FT,China,L,China,0,"Spark, Kubernetes, Deep Learning",Master,0,Technology,2024-06-13,2024-07-04,2134,5.4,Future Systems +AI04730,AI Product Manager,75374,USD,75374,MI,FL,Ireland,S,Kenya,50,"R, NLP, AWS, Java",Bachelor,2,Manufacturing,2025-02-09,2025-04-03,701,7.6,Cognitive Computing +AI04731,Principal Data Scientist,79994,USD,79994,EX,FT,China,L,China,0,"Hadoop, Python, NLP",Master,17,Real Estate,2024-05-02,2024-07-07,597,8,Autonomous Tech +AI04732,Deep Learning Engineer,78389,EUR,66631,MI,CT,France,S,France,50,"R, Java, Deep Learning, Statistics, Docker",Master,4,Energy,2025-04-30,2025-06-14,2477,5.9,DeepTech Ventures +AI04733,Head of AI,295681,USD,295681,EX,FT,Denmark,L,Denmark,100,"Tableau, Linux, Git",Master,10,Healthcare,2024-05-26,2024-06-27,524,9.4,Digital Transformation LLC +AI04734,AI Software Engineer,126906,EUR,107870,SE,PT,Germany,L,South Korea,100,"Spark, SQL, Azure",PhD,5,Real Estate,2025-04-29,2025-06-05,1181,9.6,Advanced Robotics +AI04735,AI Architect,158136,EUR,134416,EX,CT,Germany,M,Germany,50,"Kubernetes, Python, Linux, Docker",PhD,19,Manufacturing,2024-11-21,2024-12-17,1866,10,Advanced Robotics +AI04736,Computer Vision Engineer,147980,USD,147980,SE,FL,Norway,S,Norway,50,"Python, NLP, Azure",Master,9,Government,2024-07-06,2024-08-17,1488,6.4,Predictive Systems +AI04737,Head of AI,90573,USD,90573,MI,CT,Norway,S,Norway,0,"SQL, Kubernetes, Tableau",Associate,2,Gaming,2024-06-18,2024-08-07,883,5.2,Cloud AI Solutions +AI04738,Machine Learning Researcher,287295,USD,287295,EX,FL,Norway,L,Switzerland,100,"Azure, Data Visualization, Python, TensorFlow, AWS",PhD,10,Healthcare,2024-07-23,2024-08-08,1834,6,Cognitive Computing +AI04739,Deep Learning Engineer,206996,EUR,175947,EX,PT,Netherlands,L,Netherlands,50,"Mathematics, Data Visualization, Java, Docker",PhD,18,Real Estate,2024-08-09,2024-09-06,865,8.7,DataVision Ltd +AI04740,Autonomous Systems Engineer,122080,SGD,158704,SE,PT,Singapore,M,Romania,100,"Tableau, Mathematics, GCP",Bachelor,5,Transportation,2024-11-12,2024-11-28,1587,9.6,Digital Transformation LLC +AI04741,Computer Vision Engineer,70756,USD,70756,EN,FT,United States,S,United States,50,"NLP, TensorFlow, Azure",Associate,0,Finance,2024-01-04,2024-02-05,1760,7.6,Neural Networks Co +AI04742,AI Architect,97152,CHF,87437,EN,FT,Switzerland,L,Switzerland,0,"Python, Data Visualization, TensorFlow",Bachelor,0,Automotive,2024-07-27,2024-09-02,1520,6.2,Quantum Computing Inc +AI04743,Machine Learning Engineer,166402,EUR,141442,SE,CT,Netherlands,L,Netherlands,100,"Linux, R, Scala, Azure, SQL",Bachelor,6,Media,2024-08-30,2024-10-23,1184,8.5,AI Innovations +AI04744,AI Research Scientist,67835,JPY,7461850,EN,FT,Japan,L,Japan,0,"Spark, Docker, Python",Associate,1,Automotive,2024-12-22,2025-01-08,620,9.2,Digital Transformation LLC +AI04745,Data Scientist,149496,EUR,127072,EX,PT,Austria,M,Austria,100,"Computer Vision, AWS, Python, TensorFlow",PhD,13,Consulting,2024-09-02,2024-10-14,1813,10,Future Systems +AI04746,AI Software Engineer,261114,USD,261114,EX,FT,Finland,L,Finland,100,"Computer Vision, Python, Docker, Deep Learning, Linux",Bachelor,10,Government,2025-01-27,2025-03-29,573,5.6,AI Innovations +AI04747,Machine Learning Researcher,39992,USD,39992,EN,CT,China,L,China,0,"GCP, Computer Vision, Data Visualization, Python",PhD,1,Manufacturing,2025-02-24,2025-05-05,2160,6.3,Predictive Systems +AI04748,NLP Engineer,127090,JPY,13979900,SE,FT,Japan,M,Japan,100,"Tableau, Hadoop, Computer Vision, Azure, Deep Learning",Master,6,Automotive,2024-05-05,2024-05-20,1570,8.1,Cognitive Computing +AI04749,Data Analyst,25060,USD,25060,EN,FT,India,M,India,100,"Hadoop, Spark, SQL, NLP, Docker",PhD,1,Gaming,2024-04-14,2024-06-13,1845,9.4,Neural Networks Co +AI04750,NLP Engineer,121674,JPY,13384140,SE,CT,Japan,M,Indonesia,50,"Python, Tableau, Hadoop",Master,5,Real Estate,2024-02-03,2024-03-22,1668,8.7,Quantum Computing Inc +AI04751,AI Product Manager,60372,JPY,6640920,EN,FT,Japan,M,Japan,100,"GCP, Git, NLP, Python, SQL",Associate,0,Retail,2025-04-15,2025-05-23,1562,8.1,AI Innovations +AI04752,Data Engineer,277451,USD,277451,EX,FT,Norway,S,China,100,"Docker, SQL, PyTorch",Bachelor,11,Retail,2024-03-25,2024-06-03,2111,7.8,Future Systems +AI04753,Research Scientist,112653,JPY,12391830,MI,FL,Japan,L,Japan,100,"Python, SQL, Java, Spark",Bachelor,2,Energy,2024-12-25,2025-02-06,2007,8.1,Future Systems +AI04754,AI Consultant,65378,EUR,55571,EN,PT,Austria,S,Austria,100,"PyTorch, Git, MLOps, TensorFlow",Bachelor,0,Healthcare,2025-03-15,2025-05-12,990,7.1,Future Systems +AI04755,Data Engineer,70603,USD,70603,EN,FL,Ireland,M,Chile,50,"NLP, Deep Learning, Git, Kubernetes",PhD,1,Media,2025-01-03,2025-02-12,1881,7.6,Smart Analytics +AI04756,Head of AI,190525,USD,190525,EX,FT,Denmark,S,Estonia,0,"Python, Deep Learning, MLOps, Azure",Bachelor,15,Gaming,2025-02-21,2025-03-16,2332,7.2,Smart Analytics +AI04757,Research Scientist,61699,EUR,52444,EN,FT,Netherlands,M,Netherlands,50,"R, Tableau, Kubernetes",Bachelor,1,Automotive,2024-09-03,2024-10-30,594,8.8,Machine Intelligence Group +AI04758,AI Research Scientist,273689,GBP,205267,EX,FT,United Kingdom,L,Czech Republic,100,"Azure, Linux, Hadoop, Java, Python",PhD,10,Manufacturing,2025-02-02,2025-04-14,2382,6.3,DeepTech Ventures +AI04759,Machine Learning Researcher,99938,USD,99938,MI,CT,United States,M,United States,0,"Azure, Kubernetes, Deep Learning",PhD,3,Retail,2024-09-13,2024-11-02,2160,6.9,Future Systems +AI04760,Robotics Engineer,109758,USD,109758,MI,FT,Ireland,M,Ireland,0,"SQL, NLP, Tableau, Computer Vision, PyTorch",Bachelor,4,Retail,2024-08-14,2024-10-01,1696,5.1,Advanced Robotics +AI04761,AI Consultant,107303,USD,107303,MI,CT,Israel,L,Singapore,50,"TensorFlow, SQL, NLP, Git",PhD,3,Energy,2025-02-28,2025-04-29,1075,8.2,Algorithmic Solutions +AI04762,Data Analyst,89290,USD,89290,EN,FT,Ireland,L,Ireland,50,"Scala, Kubernetes, Tableau",PhD,0,Finance,2024-02-15,2024-04-01,2246,7,Autonomous Tech +AI04763,Data Scientist,172273,USD,172273,EX,PT,Israel,S,Israel,0,"Java, Tableau, Docker",Associate,10,Government,2025-01-26,2025-03-28,1270,9.4,Machine Intelligence Group +AI04764,AI Product Manager,98723,AUD,133276,MI,FL,Australia,L,Australia,50,"Data Visualization, GCP, Scala, MLOps",Master,4,Real Estate,2024-05-08,2024-05-22,824,5.3,Cloud AI Solutions +AI04765,Autonomous Systems Engineer,64219,USD,64219,EN,FT,Ireland,S,Ireland,0,"Linux, Spark, Tableau",PhD,1,Government,2024-01-12,2024-02-18,885,9.1,Predictive Systems +AI04766,Principal Data Scientist,163057,JPY,17936270,SE,FT,Japan,L,Japan,100,"Spark, SQL, Docker, Linux",Master,7,Government,2025-04-20,2025-05-09,1937,8.5,Quantum Computing Inc +AI04767,Machine Learning Engineer,175853,EUR,149475,EX,CT,Netherlands,L,Philippines,100,"PyTorch, AWS, SQL, Python",Master,16,Automotive,2024-02-11,2024-04-12,505,7.7,Cognitive Computing +AI04768,Computer Vision Engineer,24322,USD,24322,EN,PT,India,S,Canada,0,"Azure, MLOps, Python",Associate,1,Finance,2024-07-12,2024-08-28,631,10,Predictive Systems +AI04769,Autonomous Systems Engineer,296894,GBP,222671,EX,CT,United Kingdom,L,United Kingdom,0,"MLOps, SQL, Python, Tableau, Git",Associate,12,Education,2024-12-12,2025-01-04,1608,7.2,TechCorp Inc +AI04770,Deep Learning Engineer,102705,AUD,138652,MI,PT,Australia,M,Australia,0,"SQL, Azure, R",Bachelor,4,Government,2025-01-18,2025-03-27,2238,6.7,Advanced Robotics +AI04771,AI Software Engineer,80745,SGD,104969,MI,CT,Singapore,S,Singapore,50,"Kubernetes, Python, TensorFlow, Statistics",Associate,4,Technology,2024-01-28,2024-03-23,1996,6,Digital Transformation LLC +AI04772,AI Specialist,135774,USD,135774,EX,FT,Ireland,S,Ireland,50,"Computer Vision, Kubernetes, Git",PhD,14,Government,2024-02-27,2024-03-15,927,6.8,Predictive Systems +AI04773,AI Architect,66185,GBP,49639,EN,CT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow, PyTorch",PhD,0,Manufacturing,2024-04-03,2024-06-11,2185,7.8,Autonomous Tech +AI04774,Computer Vision Engineer,142177,USD,142177,MI,FL,Denmark,M,Denmark,0,"Kubernetes, TensorFlow, Docker",PhD,2,Telecommunications,2024-10-16,2024-12-09,2400,8.8,DeepTech Ventures +AI04775,Head of AI,85696,USD,85696,MI,CT,Israel,S,Denmark,100,"Data Visualization, Docker, PyTorch, MLOps, AWS",Master,3,Healthcare,2024-09-16,2024-10-25,1250,8.2,Predictive Systems +AI04776,Data Analyst,148270,GBP,111203,SE,FL,United Kingdom,M,United Kingdom,100,"TensorFlow, Hadoop, MLOps, Statistics",Associate,6,Media,2024-03-16,2024-04-12,583,9.5,Cognitive Computing +AI04777,NLP Engineer,133788,USD,133788,SE,FL,Denmark,S,Ukraine,100,"Linux, Azure, Docker, Computer Vision",PhD,8,Gaming,2025-04-15,2025-05-24,2156,6,Machine Intelligence Group +AI04778,AI Specialist,162677,GBP,122008,EX,FL,United Kingdom,S,United Kingdom,50,"R, Python, Linux",Master,17,Healthcare,2025-03-23,2025-04-20,2094,7.5,Advanced Robotics +AI04779,Autonomous Systems Engineer,152781,USD,152781,SE,CT,Finland,L,Egypt,0,"SQL, PyTorch, NLP, Computer Vision, Deep Learning",Master,9,Technology,2024-07-31,2024-08-21,1388,7.3,Neural Networks Co +AI04780,Research Scientist,91758,EUR,77994,EN,CT,Germany,L,Germany,0,"Scala, PyTorch, Spark",Bachelor,1,Telecommunications,2024-06-09,2024-07-29,2194,9.1,Autonomous Tech +AI04781,AI Architect,151164,CHF,136048,MI,FL,Switzerland,M,Switzerland,100,"Python, Linux, Computer Vision, Tableau",Associate,2,Finance,2024-09-17,2024-11-04,1670,7.9,DeepTech Ventures +AI04782,AI Product Manager,71129,GBP,53347,EN,CT,United Kingdom,S,Spain,50,"SQL, R, Kubernetes",Associate,1,Education,2025-04-22,2025-06-19,1826,7.3,Autonomous Tech +AI04783,Data Scientist,133851,GBP,100388,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, AWS, Hadoop",Master,8,Gaming,2024-07-27,2024-08-14,1570,9.4,Neural Networks Co +AI04784,Principal Data Scientist,60769,USD,60769,MI,FT,South Korea,S,Spain,0,"Data Visualization, Deep Learning, TensorFlow, SQL, Git",Associate,2,Retail,2024-10-03,2024-12-13,2176,7.5,DataVision Ltd +AI04785,AI Research Scientist,184176,EUR,156550,EX,CT,Netherlands,L,Netherlands,100,"Git, NLP, Tableau, SQL, Linux",Associate,15,Manufacturing,2024-06-04,2024-07-16,1994,5.6,TechCorp Inc +AI04786,NLP Engineer,225359,USD,225359,EX,FL,Israel,M,Indonesia,100,"R, Git, AWS",Associate,18,Healthcare,2024-10-25,2024-11-28,1608,6.1,AI Innovations +AI04787,Autonomous Systems Engineer,257030,USD,257030,EX,PT,United States,S,Romania,50,"Git, Linux, Python",PhD,18,Manufacturing,2025-01-20,2025-03-15,1880,6.3,Algorithmic Solutions +AI04788,Data Scientist,106616,SGD,138601,SE,FT,Singapore,S,Sweden,0,"Python, Mathematics, Java, Computer Vision",Associate,8,Retail,2024-02-22,2024-04-22,1948,6.5,DeepTech Ventures +AI04789,Machine Learning Engineer,28056,USD,28056,EN,CT,China,S,China,0,"NLP, Kubernetes, Java",Bachelor,0,Gaming,2024-03-29,2024-05-13,2016,7.1,DataVision Ltd +AI04790,AI Consultant,149551,EUR,127118,SE,CT,France,L,France,0,"Spark, R, SQL, Hadoop",Associate,9,Gaming,2025-01-09,2025-03-17,1387,8.7,Digital Transformation LLC +AI04791,Machine Learning Engineer,72604,AUD,98015,EN,PT,Australia,S,Australia,50,"Tableau, Mathematics, MLOps, Python, TensorFlow",Associate,1,Technology,2024-06-12,2024-07-08,1177,5.6,AI Innovations +AI04792,Principal Data Scientist,57678,USD,57678,EN,FT,Finland,L,Finland,0,"Spark, Java, Statistics, Linux",Bachelor,1,Consulting,2024-12-09,2025-02-20,1801,6.7,Machine Intelligence Group +AI04793,Robotics Engineer,56249,USD,56249,EN,FL,Israel,S,Israel,50,"Python, Tableau, TensorFlow, Data Visualization, Mathematics",Bachelor,1,Transportation,2024-03-01,2024-04-21,537,7.6,Machine Intelligence Group +AI04794,ML Ops Engineer,100701,USD,100701,EX,FL,China,L,France,0,"SQL, Git, Spark, Linux",Associate,13,Media,2024-12-18,2025-01-04,2279,9.3,DataVision Ltd +AI04795,Machine Learning Engineer,86400,USD,86400,EN,CT,United States,M,Kenya,100,"Scala, Deep Learning, Java",Master,0,Retail,2024-01-29,2024-02-21,1913,7.1,AI Innovations +AI04796,AI Specialist,161695,JPY,17786450,SE,CT,Japan,L,Japan,0,"NLP, Docker, Tableau, R",Bachelor,6,Finance,2024-10-12,2024-11-10,2341,7.2,Cognitive Computing +AI04797,AI Consultant,101102,JPY,11121220,MI,PT,Japan,L,Japan,100,"Linux, Data Visualization, PyTorch, Statistics",Master,3,Telecommunications,2024-03-14,2024-04-01,1091,8.8,DeepTech Ventures +AI04798,AI Architect,72270,USD,72270,EN,FL,Ireland,M,Ireland,0,"Deep Learning, R, PyTorch",Associate,1,Energy,2025-03-26,2025-04-25,913,7.9,TechCorp Inc +AI04799,Machine Learning Engineer,53789,USD,53789,EN,PT,South Korea,M,South Korea,0,"SQL, Spark, Tableau",Bachelor,0,Energy,2024-11-19,2025-01-20,1724,5.2,Future Systems +AI04800,Computer Vision Engineer,104468,USD,104468,MI,FL,South Korea,L,South Korea,100,"Java, SQL, Hadoop",Master,2,Retail,2024-09-08,2024-10-25,1169,7.9,Future Systems +AI04801,ML Ops Engineer,225913,USD,225913,EX,FT,Ireland,S,Ireland,100,"Azure, SQL, TensorFlow, Python",Associate,17,Energy,2025-01-30,2025-02-24,2216,6.7,Neural Networks Co +AI04802,AI Specialist,178459,USD,178459,SE,FL,Norway,L,France,100,"SQL, AWS, Computer Vision, GCP, Data Visualization",Master,8,Gaming,2024-05-21,2024-06-07,879,7.1,Quantum Computing Inc +AI04803,Principal Data Scientist,168120,USD,168120,EX,FT,United States,S,United States,0,"Computer Vision, Docker, AWS, Python",PhD,19,Education,2024-11-12,2024-12-16,996,6.9,Quantum Computing Inc +AI04804,AI Specialist,66095,USD,66095,EN,PT,United States,S,Egypt,100,"GCP, Git, Hadoop, Tableau, PyTorch",PhD,0,Manufacturing,2024-08-31,2024-10-07,2130,7.6,Predictive Systems +AI04805,AI Architect,288067,USD,288067,EX,PT,United States,L,United States,0,"SQL, MLOps, PyTorch, Azure",Associate,18,Telecommunications,2024-04-01,2024-05-22,1686,7.8,Autonomous Tech +AI04806,Deep Learning Engineer,18634,USD,18634,EN,FL,India,S,Ireland,50,"Java, Docker, GCP",Master,1,Transportation,2024-09-13,2024-11-20,1978,9.2,Advanced Robotics +AI04807,Research Scientist,66098,USD,66098,EX,FT,China,M,China,0,"Python, Azure, MLOps, TensorFlow, Docker",Master,18,Manufacturing,2025-01-09,2025-02-26,639,7.5,Machine Intelligence Group +AI04808,Computer Vision Engineer,43744,EUR,37182,EN,FL,Austria,S,Austria,0,"Azure, Linux, PyTorch",Bachelor,1,Government,2024-08-27,2024-11-05,1325,7.1,Future Systems +AI04809,Computer Vision Engineer,57278,EUR,48686,EN,PT,Netherlands,M,Netherlands,50,"Deep Learning, Hadoop, GCP",Bachelor,0,Transportation,2024-03-30,2024-05-29,1116,6.2,Cloud AI Solutions +AI04810,AI Product Manager,59918,GBP,44939,EN,FT,United Kingdom,S,United Kingdom,50,"Python, Spark, Git, Deep Learning",Associate,0,Real Estate,2024-07-10,2024-09-04,1899,5.1,Advanced Robotics +AI04811,Data Scientist,68180,EUR,57953,EN,FT,Austria,M,Austria,0,"Python, Azure, Scala",Master,1,Manufacturing,2025-04-16,2025-06-15,563,9.4,Neural Networks Co +AI04812,AI Software Engineer,97864,GBP,73398,SE,PT,United Kingdom,S,United Kingdom,100,"Linux, Spark, GCP",Associate,6,Finance,2024-09-25,2024-10-25,2473,5.3,Advanced Robotics +AI04813,Research Scientist,113546,USD,113546,MI,FT,Ireland,L,Ireland,100,"Azure, Kubernetes, Statistics",Master,3,Healthcare,2024-04-27,2024-05-22,2269,5.8,AI Innovations +AI04814,Deep Learning Engineer,237348,JPY,26108280,EX,PT,Japan,S,Japan,50,"MLOps, Java, Spark, Azure",Master,10,Manufacturing,2025-03-13,2025-03-30,803,9.1,TechCorp Inc +AI04815,AI Architect,251015,SGD,326320,EX,FL,Singapore,M,Singapore,0,"PyTorch, Statistics, Azure, SQL",Associate,11,Government,2024-02-03,2024-04-15,1783,6,Cognitive Computing +AI04816,Machine Learning Engineer,78579,CAD,98224,MI,CT,Canada,M,Canada,100,"MLOps, Hadoop, Statistics, PyTorch, Mathematics",Bachelor,4,Government,2024-02-09,2024-03-09,1867,5.4,Future Systems +AI04817,Principal Data Scientist,85161,USD,85161,MI,CT,Ireland,M,Ireland,0,"PyTorch, TensorFlow, Statistics",Master,4,Telecommunications,2025-02-24,2025-03-29,1322,8.9,Future Systems +AI04818,Machine Learning Researcher,190172,EUR,161646,EX,FL,Netherlands,M,Netherlands,0,"Java, Computer Vision, Spark, GCP, Kubernetes",Bachelor,19,Technology,2024-05-02,2024-07-13,1469,9,Cognitive Computing +AI04819,AI Specialist,100405,JPY,11044550,MI,PT,Japan,L,Japan,50,"Python, Git, Tableau",PhD,3,Energy,2024-09-02,2024-11-14,1833,7.2,DataVision Ltd +AI04820,AI Research Scientist,42239,USD,42239,MI,FT,China,L,China,100,"Git, PyTorch, Azure",Bachelor,2,Energy,2024-03-19,2024-05-07,1606,6.7,DataVision Ltd +AI04821,Research Scientist,287260,USD,287260,EX,CT,Ireland,L,Malaysia,50,"Docker, PyTorch, Computer Vision",Master,14,Manufacturing,2024-06-26,2024-07-18,1892,7.2,Future Systems +AI04822,Data Analyst,198733,AUD,268290,EX,FL,Australia,M,Australia,100,"PyTorch, Computer Vision, AWS, Scala, Kubernetes",Associate,11,Media,2024-04-01,2024-04-22,1667,6.9,Future Systems +AI04823,Robotics Engineer,258415,EUR,219653,EX,CT,France,L,France,0,"MLOps, Scala, Spark",Master,17,Gaming,2024-01-21,2024-02-10,1407,5.7,Neural Networks Co +AI04824,AI Specialist,82073,USD,82073,MI,PT,Finland,M,Finland,100,"Python, TensorFlow, MLOps",Bachelor,3,Finance,2024-07-20,2024-08-25,1654,7.1,Cognitive Computing +AI04825,Deep Learning Engineer,111443,USD,111443,SE,FT,Israel,S,Japan,100,"GCP, SQL, Kubernetes, AWS",PhD,8,Consulting,2024-07-26,2024-09-14,500,8.3,Autonomous Tech +AI04826,AI Architect,200094,JPY,22010340,EX,CT,Japan,L,Japan,0,"Java, PyTorch, Azure, SQL",Bachelor,14,Education,2025-04-11,2025-05-19,1610,8.3,Cloud AI Solutions +AI04827,AI Product Manager,248923,EUR,211585,EX,PT,Germany,M,Nigeria,100,"Linux, Deep Learning, Mathematics, Docker",Master,19,Government,2024-07-25,2024-08-18,555,8.8,Cognitive Computing +AI04828,Computer Vision Engineer,72550,GBP,54413,EN,PT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Computer Vision, Git",Bachelor,1,Media,2024-12-22,2025-01-18,702,9.9,Machine Intelligence Group +AI04829,Deep Learning Engineer,206051,EUR,175143,EX,FL,Austria,L,Austria,100,"GCP, Hadoop, Deep Learning",Associate,13,Retail,2024-11-09,2024-12-22,1120,8.1,Advanced Robotics +AI04830,AI Software Engineer,141826,USD,141826,SE,CT,Sweden,M,Sweden,100,"Java, Scala, Mathematics",Bachelor,7,Finance,2024-12-18,2025-02-07,1838,7.2,DataVision Ltd +AI04831,ML Ops Engineer,196522,EUR,167044,EX,FT,France,S,France,100,"Python, Docker, Statistics",Master,18,Finance,2025-01-18,2025-02-25,708,7.9,Neural Networks Co +AI04832,Machine Learning Researcher,104082,SGD,135307,MI,PT,Singapore,M,Portugal,0,"AWS, R, Azure, Python, Git",PhD,2,Automotive,2024-11-26,2024-12-30,765,6.5,TechCorp Inc +AI04833,ML Ops Engineer,256314,USD,256314,EX,FL,United States,S,United States,0,"Mathematics, R, Deep Learning",Bachelor,11,Consulting,2024-05-23,2024-07-23,2116,9.7,Predictive Systems +AI04834,Computer Vision Engineer,62614,USD,62614,EX,PT,India,M,India,100,"TensorFlow, Git, Java, Computer Vision, Scala",Associate,15,Manufacturing,2024-05-14,2024-07-21,1318,7.9,Cloud AI Solutions +AI04835,AI Product Manager,104089,JPY,11449790,MI,PT,Japan,S,Japan,100,"Git, Docker, Data Visualization, Kubernetes, Scala",Associate,3,Government,2024-06-24,2024-08-16,1828,6.6,DeepTech Ventures +AI04836,ML Ops Engineer,52607,USD,52607,SE,FL,China,S,Vietnam,0,"Python, Statistics, Deep Learning, Scala",PhD,7,Telecommunications,2024-08-29,2024-09-18,2113,7.1,TechCorp Inc +AI04837,ML Ops Engineer,131333,USD,131333,SE,FT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Computer Vision",Master,6,Energy,2025-01-09,2025-02-25,1082,7.7,Predictive Systems +AI04838,Data Engineer,369918,CHF,332926,EX,CT,Switzerland,L,Switzerland,0,"Scala, Java, Deep Learning",Associate,18,Finance,2025-03-23,2025-06-03,2322,6,Machine Intelligence Group +AI04839,Computer Vision Engineer,288629,USD,288629,EX,PT,Sweden,L,Sweden,50,"PyTorch, MLOps, GCP",Associate,19,Telecommunications,2024-04-02,2024-05-27,1934,5.5,TechCorp Inc +AI04840,AI Consultant,186990,EUR,158942,EX,CT,Germany,S,Germany,100,"SQL, Data Visualization, Linux, Scala",PhD,16,Automotive,2025-04-02,2025-05-12,1952,9.8,DataVision Ltd +AI04841,AI Specialist,122223,USD,122223,SE,FT,Sweden,S,Sweden,100,"Data Visualization, Linux, PyTorch",PhD,7,Transportation,2025-03-26,2025-05-22,2384,6.8,DataVision Ltd +AI04842,Computer Vision Engineer,116177,USD,116177,SE,PT,Ireland,S,Ireland,100,"Git, Mathematics, Computer Vision, Java, Deep Learning",PhD,8,Consulting,2024-05-28,2024-06-22,939,9.8,Quantum Computing Inc +AI04843,Research Scientist,155331,USD,155331,EX,FT,Israel,M,Israel,0,"Statistics, Computer Vision, NLP, SQL, Data Visualization",Bachelor,15,Consulting,2024-04-17,2024-05-19,1147,5.7,Autonomous Tech +AI04844,Computer Vision Engineer,157720,EUR,134062,EX,PT,Austria,L,United States,50,"Python, GCP, Tableau, TensorFlow",Bachelor,11,Real Estate,2024-10-24,2024-12-27,1805,6.7,Predictive Systems +AI04845,AI Consultant,80697,CHF,72627,EN,PT,Switzerland,M,Switzerland,100,"PyTorch, Azure, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-10-08,2024-12-02,2026,6.8,Machine Intelligence Group +AI04846,Data Analyst,95727,EUR,81368,EN,FT,Netherlands,L,Netherlands,50,"PyTorch, Spark, Computer Vision",PhD,0,Government,2024-01-15,2024-03-03,1960,6.1,DeepTech Ventures +AI04847,NLP Engineer,303364,USD,303364,EX,FL,Norway,L,Norway,50,"Java, R, Spark, Docker, Deep Learning",Bachelor,18,Manufacturing,2024-10-10,2024-11-12,930,5.4,Machine Intelligence Group +AI04848,Robotics Engineer,130193,JPY,14321230,SE,FL,Japan,M,Japan,0,"Spark, Python, R, AWS, Statistics",Bachelor,5,Government,2025-04-16,2025-06-03,1110,8.1,DeepTech Ventures +AI04849,Data Scientist,87100,CAD,108875,MI,PT,Canada,S,Canada,0,"R, GCP, Azure, Linux, Kubernetes",Associate,3,Automotive,2024-05-14,2024-06-03,2350,5.4,Quantum Computing Inc +AI04850,Principal Data Scientist,253609,SGD,329692,EX,CT,Singapore,M,Singapore,100,"Tableau, Deep Learning, Hadoop",PhD,13,Telecommunications,2024-01-09,2024-02-12,723,5.2,TechCorp Inc +AI04851,Deep Learning Engineer,111947,CAD,139934,MI,PT,Canada,L,Canada,0,"Spark, NLP, Python, Kubernetes, Mathematics",PhD,2,Transportation,2024-10-08,2024-12-08,1637,7.6,Advanced Robotics +AI04852,ML Ops Engineer,149929,SGD,194908,SE,FL,Singapore,L,Singapore,50,"Deep Learning, AWS, Mathematics, GCP, Python",Master,8,Media,2025-04-11,2025-05-06,2130,5.6,AI Innovations +AI04853,AI Product Manager,101866,SGD,132426,MI,FT,Singapore,L,Singapore,0,"SQL, NLP, R",PhD,3,Gaming,2024-04-24,2024-05-19,1461,8.5,Algorithmic Solutions +AI04854,Research Scientist,77165,AUD,104173,MI,PT,Australia,S,Australia,100,"Tableau, Git, Docker, PyTorch, Linux",Master,4,Media,2024-12-02,2025-01-21,1863,7.6,Machine Intelligence Group +AI04855,Computer Vision Engineer,121396,EUR,103187,SE,FL,Germany,M,Canada,50,"Data Visualization, PyTorch, TensorFlow, Statistics, Java",Master,7,Gaming,2024-07-01,2024-07-26,1567,8.8,Advanced Robotics +AI04856,Machine Learning Researcher,136213,USD,136213,SE,FT,Ireland,L,Ireland,50,"Deep Learning, TensorFlow, R, MLOps, Git",Associate,5,Retail,2024-06-23,2024-08-25,2377,8.5,Future Systems +AI04857,AI Architect,145362,USD,145362,SE,CT,Sweden,L,Sweden,50,"R, PyTorch, GCP",Associate,5,Manufacturing,2025-03-11,2025-04-21,939,5.6,Autonomous Tech +AI04858,Head of AI,53624,CAD,67030,EN,FL,Canada,S,Canada,100,"Spark, R, Computer Vision, Data Visualization",PhD,0,Energy,2024-06-02,2024-07-21,2033,6.9,Algorithmic Solutions +AI04859,NLP Engineer,85771,EUR,72905,MI,FT,Austria,L,Austria,0,"Kubernetes, Python, AWS, GCP, Linux",Associate,4,Retail,2024-01-09,2024-03-09,1532,5.3,Quantum Computing Inc +AI04860,Data Analyst,181719,EUR,154461,EX,FT,Germany,L,Germany,0,"Spark, NLP, Data Visualization, Statistics, R",PhD,16,Education,2024-01-20,2024-04-02,820,9,Smart Analytics +AI04861,AI Research Scientist,69580,EUR,59143,MI,PT,Austria,S,Austria,0,"Java, Docker, GCP, Computer Vision, Git",Master,2,Consulting,2025-03-31,2025-06-05,1398,9.3,AI Innovations +AI04862,Data Engineer,132740,EUR,112829,SE,FL,Austria,L,Austria,50,"Kubernetes, AWS, GCP, SQL",Bachelor,7,Gaming,2025-01-29,2025-04-09,1832,6.4,Quantum Computing Inc +AI04863,Principal Data Scientist,130258,CAD,162823,SE,CT,Canada,M,Canada,50,"Data Visualization, Python, TensorFlow",Master,7,Telecommunications,2025-04-28,2025-07-01,1257,6.4,Autonomous Tech +AI04864,Computer Vision Engineer,116709,USD,116709,SE,PT,Israel,S,Russia,50,"SQL, Python, R, AWS, Tableau",PhD,9,Manufacturing,2024-06-23,2024-08-31,1408,6.5,Predictive Systems +AI04865,Research Scientist,80310,EUR,68264,MI,CT,Netherlands,M,Netherlands,0,"SQL, Docker, AWS",Associate,3,Automotive,2024-07-07,2024-09-04,1673,7.5,TechCorp Inc +AI04866,Robotics Engineer,185837,EUR,157961,EX,FL,Austria,M,Austria,100,"Scala, Kubernetes, NLP",Associate,13,Media,2024-05-23,2024-07-09,2427,9.4,Machine Intelligence Group +AI04867,Data Engineer,73290,EUR,62297,EN,CT,Netherlands,M,Netherlands,0,"Java, Mathematics, R",Master,0,Media,2024-12-31,2025-02-03,2265,8.4,Advanced Robotics +AI04868,AI Research Scientist,115082,GBP,86312,MI,PT,United Kingdom,M,United Kingdom,100,"R, MLOps, Git, Linux",Bachelor,2,Finance,2024-12-17,2025-02-06,2229,5.5,Digital Transformation LLC +AI04869,Machine Learning Researcher,239030,AUD,322691,EX,PT,Australia,L,Australia,50,"SQL, TensorFlow, PyTorch, Computer Vision, Mathematics",Associate,11,Automotive,2025-04-09,2025-05-09,1765,6.8,Cloud AI Solutions +AI04870,AI Software Engineer,78991,EUR,67142,MI,CT,Austria,L,Austria,50,"Kubernetes, Java, SQL, Statistics",Bachelor,4,Telecommunications,2025-04-15,2025-05-24,1694,5.1,Predictive Systems +AI04871,Head of AI,174805,USD,174805,EX,PT,Sweden,S,Sweden,100,"Spark, Azure, Scala, Deep Learning",Master,19,Media,2025-01-06,2025-02-01,2055,6.3,DataVision Ltd +AI04872,Machine Learning Researcher,181104,CHF,162994,SE,CT,Switzerland,S,Switzerland,50,"Python, Docker, NLP, AWS, Computer Vision",PhD,9,Consulting,2024-08-23,2024-10-25,2359,7.1,Future Systems +AI04873,AI Architect,115681,USD,115681,SE,PT,Finland,L,Ghana,0,"GCP, Scala, Python",Master,9,Consulting,2024-02-18,2024-04-11,1305,6.7,DeepTech Ventures +AI04874,Robotics Engineer,43208,USD,43208,EN,PT,China,L,China,100,"Scala, Python, Kubernetes, Hadoop",PhD,1,Education,2024-10-29,2025-01-08,2363,5.3,Advanced Robotics +AI04875,AI Specialist,94668,USD,94668,MI,PT,Sweden,S,Sweden,100,"Spark, SQL, Python",Bachelor,4,Manufacturing,2024-12-25,2025-03-06,2189,5.5,Advanced Robotics +AI04876,Principal Data Scientist,88758,EUR,75444,EN,FL,Germany,L,Germany,0,"AWS, Computer Vision, Spark, Java",Master,1,Technology,2024-06-08,2024-07-04,1959,9,Future Systems +AI04877,Data Scientist,107851,EUR,91673,SE,FT,Austria,S,Austria,0,"Statistics, PyTorch, Mathematics",Associate,9,Consulting,2025-02-13,2025-03-24,952,8.1,Predictive Systems +AI04878,Research Scientist,77521,USD,77521,EN,PT,Denmark,L,Japan,0,"Hadoop, Git, Mathematics, Computer Vision",Bachelor,0,Manufacturing,2024-08-27,2024-10-18,1875,6.6,Predictive Systems +AI04879,NLP Engineer,48915,USD,48915,EN,FL,Finland,M,Finland,50,"Kubernetes, Docker, Statistics, Azure, SQL",PhD,0,Transportation,2025-01-15,2025-03-21,2032,8.8,TechCorp Inc +AI04880,AI Specialist,144329,USD,144329,EX,FL,Ireland,S,Ireland,50,"Azure, SQL, TensorFlow, R, Statistics",Master,12,Media,2024-05-03,2024-06-11,1802,9,Algorithmic Solutions +AI04881,Deep Learning Engineer,74868,AUD,101072,MI,CT,Australia,S,Australia,50,"Python, TensorFlow, Java, PyTorch",PhD,4,Retail,2025-04-04,2025-06-11,1782,5.1,Smart Analytics +AI04882,AI Consultant,173810,AUD,234644,SE,PT,Australia,L,Australia,50,"TensorFlow, SQL, Linux, Git",Bachelor,7,Government,2024-03-27,2024-05-04,703,9.5,Advanced Robotics +AI04883,Computer Vision Engineer,119626,USD,119626,SE,CT,Israel,S,Ukraine,50,"Kubernetes, Statistics, Scala",Master,5,Finance,2025-04-29,2025-07-07,1482,7.8,Algorithmic Solutions +AI04884,Head of AI,55331,USD,55331,EN,CT,Finland,S,Finland,50,"Git, Spark, Python",Associate,0,Technology,2024-12-23,2025-03-01,853,6.3,Digital Transformation LLC +AI04885,Research Scientist,126364,EUR,107409,MI,FL,Germany,L,Germany,0,"Statistics, Python, Computer Vision",Master,2,Finance,2024-06-22,2024-08-08,1656,5.6,DeepTech Ventures +AI04886,Autonomous Systems Engineer,193012,USD,193012,EX,PT,Sweden,M,Sweden,50,"Spark, Docker, MLOps, GCP, Kubernetes",PhD,12,Energy,2024-07-03,2024-08-30,1282,8.1,DataVision Ltd +AI04887,Machine Learning Engineer,50277,USD,50277,SE,CT,China,M,China,50,"GCP, Tableau, SQL, Git",PhD,7,Media,2024-07-23,2024-09-01,1771,9.9,AI Innovations +AI04888,Computer Vision Engineer,52691,USD,52691,EN,CT,Sweden,S,Italy,0,"PyTorch, Computer Vision, Tableau, TensorFlow",Bachelor,0,Education,2024-10-17,2024-11-05,1506,6.4,Machine Intelligence Group +AI04889,Head of AI,88745,EUR,75433,MI,CT,Austria,M,Austria,50,"AWS, Spark, Hadoop, Azure, Scala",Master,3,Energy,2025-03-19,2025-05-26,1029,8.9,Predictive Systems +AI04890,AI Research Scientist,69741,EUR,59280,EN,FL,France,M,France,0,"PyTorch, TensorFlow, Kubernetes, NLP, GCP",Bachelor,1,Technology,2024-05-15,2024-07-18,1172,6.8,Autonomous Tech +AI04891,Research Scientist,103812,SGD,134956,SE,PT,Singapore,S,Singapore,50,"GCP, Kubernetes, Docker, Mathematics",Bachelor,7,Energy,2024-06-25,2024-08-14,1953,9.6,Predictive Systems +AI04892,AI Product Manager,110207,USD,110207,EN,PT,Denmark,L,Denmark,0,"PyTorch, Hadoop, Data Visualization, AWS, SQL",PhD,1,Finance,2025-03-17,2025-04-11,1555,6.1,Autonomous Tech +AI04893,Data Engineer,90086,USD,90086,EN,CT,United States,L,United States,50,"Python, Data Visualization, Mathematics, TensorFlow",Master,1,Manufacturing,2024-01-30,2024-03-10,1449,5.4,Digital Transformation LLC +AI04894,Computer Vision Engineer,69149,USD,69149,MI,FT,Finland,M,Kenya,100,"Spark, Python, TensorFlow, GCP",Master,4,Telecommunications,2024-04-12,2024-06-21,1681,7.5,Predictive Systems +AI04895,Robotics Engineer,62098,USD,62098,EX,FL,India,M,India,0,"Deep Learning, MLOps, TensorFlow",Associate,16,Energy,2025-04-13,2025-04-28,2374,8.2,Autonomous Tech +AI04896,AI Research Scientist,58340,EUR,49589,EN,PT,Germany,S,Germany,50,"SQL, MLOps, Tableau, AWS, Azure",PhD,0,Automotive,2024-03-20,2024-05-01,1877,5,Advanced Robotics +AI04897,Machine Learning Researcher,27753,USD,27753,EN,FL,China,M,Chile,0,"SQL, Data Visualization, Python, Kubernetes",PhD,1,Telecommunications,2024-07-30,2024-10-05,853,8.1,DataVision Ltd +AI04898,Data Engineer,94238,EUR,80102,MI,FL,France,L,France,100,"Mathematics, Linux, Azure, Python, TensorFlow",Bachelor,2,Transportation,2024-07-19,2024-08-13,1185,6.9,Algorithmic Solutions +AI04899,AI Research Scientist,90515,USD,90515,SE,CT,South Korea,M,South Korea,0,"Python, TensorFlow, Data Visualization",PhD,6,Media,2024-03-04,2024-05-14,1338,9.1,Autonomous Tech +AI04900,Research Scientist,252088,USD,252088,EX,FL,Ireland,M,Ireland,100,"Mathematics, NLP, Scala, PyTorch, Docker",Master,12,Government,2024-03-11,2024-04-30,1589,7.5,DataVision Ltd +AI04901,Computer Vision Engineer,123498,AUD,166722,EX,FT,Australia,S,Australia,50,"Linux, PyTorch, TensorFlow, Data Visualization, SQL",PhD,19,Media,2025-01-02,2025-01-20,2319,7.5,Smart Analytics +AI04902,Machine Learning Engineer,97399,GBP,73049,SE,PT,United Kingdom,S,United Kingdom,0,"Kubernetes, SQL, R",Bachelor,8,Manufacturing,2024-12-24,2025-01-30,1269,7.4,Cognitive Computing +AI04903,AI Product Manager,122301,SGD,158991,MI,FL,Singapore,L,Singapore,100,"Scala, Python, TensorFlow, AWS",PhD,4,Education,2024-04-04,2024-05-22,2205,7.2,Future Systems +AI04904,Computer Vision Engineer,102239,SGD,132911,MI,PT,Singapore,S,Belgium,50,"Mathematics, Docker, AWS",Associate,4,Manufacturing,2024-07-20,2024-09-28,1780,9,AI Innovations +AI04905,Computer Vision Engineer,194401,JPY,21384110,EX,FL,Japan,S,Nigeria,0,"Java, Python, GCP, AWS",PhD,19,Real Estate,2024-10-12,2024-11-20,2140,5.9,AI Innovations +AI04906,Machine Learning Researcher,88107,USD,88107,EN,PT,Denmark,L,France,50,"Hadoop, Scala, Spark",PhD,0,Technology,2024-07-27,2024-09-15,889,6.7,Autonomous Tech +AI04907,AI Software Engineer,147607,USD,147607,SE,FL,Finland,L,Finland,0,"Python, NLP, GCP, Computer Vision",PhD,7,Automotive,2024-05-24,2024-06-26,2274,8.1,Advanced Robotics +AI04908,AI Product Manager,62399,USD,62399,EN,FT,South Korea,L,South Korea,100,"Python, Data Visualization, R",Master,1,Technology,2025-03-08,2025-05-04,1926,9.4,Machine Intelligence Group +AI04909,AI Consultant,178097,CHF,160287,EX,FL,Switzerland,S,Latvia,50,"Git, PyTorch, Hadoop",PhD,16,Education,2024-03-02,2024-03-22,1043,6.6,Digital Transformation LLC +AI04910,Autonomous Systems Engineer,121196,EUR,103017,SE,FL,Netherlands,S,Netherlands,100,"Docker, Linux, Computer Vision",Master,9,Automotive,2025-03-02,2025-04-27,639,6.4,Quantum Computing Inc +AI04911,ML Ops Engineer,196124,USD,196124,EX,CT,Ireland,L,Ireland,0,"PyTorch, R, AWS",Bachelor,11,Retail,2024-11-14,2024-12-18,1350,5.4,TechCorp Inc +AI04912,Deep Learning Engineer,133436,EUR,113421,EX,FL,Germany,S,United States,100,"Computer Vision, Python, Linux",Bachelor,12,Finance,2024-04-23,2024-06-06,708,5.6,Quantum Computing Inc +AI04913,Research Scientist,63143,JPY,6945730,EN,CT,Japan,S,Japan,0,"Git, Hadoop, Data Visualization, GCP",Bachelor,0,Consulting,2024-01-23,2024-02-09,844,9.7,Future Systems +AI04914,Data Engineer,101308,USD,101308,SE,CT,Finland,M,Finland,100,"SQL, NLP, Statistics, Hadoop",Master,9,Transportation,2024-01-28,2024-03-09,1781,9.5,TechCorp Inc +AI04915,Head of AI,129700,USD,129700,EX,PT,Israel,M,Israel,100,"Mathematics, PyTorch, Computer Vision, Azure, NLP",Bachelor,10,Education,2024-12-07,2025-02-11,819,7.3,Future Systems +AI04916,Data Scientist,82759,GBP,62069,MI,FT,United Kingdom,M,Italy,100,"Azure, Kubernetes, Docker",Associate,3,Technology,2024-09-08,2024-10-17,2024,9,AI Innovations +AI04917,Principal Data Scientist,58384,USD,58384,EN,CT,Sweden,S,Sweden,0,"R, MLOps, Hadoop, Computer Vision",PhD,0,Manufacturing,2024-11-21,2025-01-20,1210,9.6,Predictive Systems +AI04918,NLP Engineer,57840,USD,57840,SE,PT,China,M,China,50,"Kubernetes, PyTorch, Statistics, Docker, Azure",Master,7,Telecommunications,2024-08-17,2024-10-13,1991,5,Machine Intelligence Group +AI04919,AI Architect,67529,USD,67529,EN,FL,Ireland,M,Ireland,0,"Linux, GCP, Mathematics, Deep Learning",PhD,0,Energy,2024-09-27,2024-11-19,1391,5.9,Advanced Robotics +AI04920,Autonomous Systems Engineer,103319,EUR,87821,MI,CT,Netherlands,M,Spain,50,"Kubernetes, Tableau, Java, Computer Vision",Associate,2,Gaming,2024-05-04,2024-06-07,744,6.7,Machine Intelligence Group +AI04921,Data Analyst,264281,USD,264281,EX,FL,Israel,L,Israel,100,"Hadoop, Docker, PyTorch, Spark, Tableau",Associate,16,Healthcare,2024-02-19,2024-03-24,2369,8.6,Quantum Computing Inc +AI04922,Robotics Engineer,90375,USD,90375,EN,FT,Norway,S,Hungary,100,"Statistics, TensorFlow, R, MLOps",PhD,1,Energy,2025-03-11,2025-05-09,2386,9.1,Algorithmic Solutions +AI04923,Machine Learning Researcher,168030,CAD,210038,EX,FT,Canada,L,Canada,100,"GCP, Spark, Deep Learning, TensorFlow, Hadoop",PhD,18,Education,2024-08-02,2024-08-17,1548,9.9,Cognitive Computing +AI04924,AI Architect,144693,USD,144693,SE,CT,United States,S,United States,100,"AWS, Azure, PyTorch",PhD,7,Transportation,2025-01-19,2025-02-28,1380,8.6,Algorithmic Solutions +AI04925,NLP Engineer,169169,EUR,143794,EX,FT,Netherlands,S,Netherlands,100,"Scala, AWS, R",Bachelor,17,Government,2024-10-29,2024-12-16,1867,7.8,Cognitive Computing +AI04926,AI Research Scientist,97205,EUR,82624,MI,PT,Austria,L,Austria,100,"MLOps, Hadoop, Java",Bachelor,2,Automotive,2024-12-04,2025-01-05,1638,8.1,DeepTech Ventures +AI04927,AI Consultant,116462,USD,116462,SE,FL,United States,S,United States,100,"Hadoop, Docker, NLP, Kubernetes, Computer Vision",Master,5,Manufacturing,2024-12-17,2025-02-18,936,9.5,Advanced Robotics +AI04928,AI Research Scientist,161251,USD,161251,EX,CT,United States,S,United States,0,"Tableau, Statistics, TensorFlow, Data Visualization, AWS",Associate,13,Transportation,2024-11-04,2025-01-12,2473,10,Cognitive Computing +AI04929,AI Software Engineer,127524,USD,127524,SE,FL,Sweden,M,Sweden,50,"Deep Learning, SQL, MLOps",Bachelor,8,Gaming,2024-11-25,2025-01-10,845,5.6,TechCorp Inc +AI04930,Autonomous Systems Engineer,40391,USD,40391,MI,CT,India,L,Czech Republic,100,"AWS, PyTorch, Linux, Mathematics, Data Visualization",Master,4,Energy,2024-02-05,2024-04-02,1473,9.8,Neural Networks Co +AI04931,Data Engineer,125657,USD,125657,SE,FT,Finland,S,Hungary,50,"Python, Azure, SQL",PhD,9,Automotive,2024-03-11,2024-03-30,1378,9,Neural Networks Co +AI04932,Computer Vision Engineer,220521,GBP,165391,EX,FL,United Kingdom,S,Poland,100,"AWS, Python, TensorFlow, Statistics",PhD,15,Finance,2024-03-01,2024-04-05,1224,7.4,Autonomous Tech +AI04933,AI Software Engineer,75300,GBP,56475,EN,FL,United Kingdom,S,United Kingdom,50,"GCP, R, Mathematics, Hadoop",Bachelor,0,Real Estate,2025-02-13,2025-04-27,1543,7.5,Machine Intelligence Group +AI04934,Data Analyst,89549,USD,89549,MI,PT,Ireland,L,Vietnam,100,"PyTorch, TensorFlow, Mathematics, Docker",Master,3,Consulting,2025-02-01,2025-04-03,1192,6.1,Cognitive Computing +AI04935,AI Research Scientist,230750,GBP,173063,EX,FL,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Git",Master,18,Retail,2024-07-26,2024-08-25,828,5.6,TechCorp Inc +AI04936,Computer Vision Engineer,43742,USD,43742,MI,CT,China,M,China,100,"Kubernetes, GCP, Scala",PhD,4,Finance,2024-02-28,2024-04-03,568,8.1,Advanced Robotics +AI04937,Machine Learning Engineer,73505,USD,73505,EN,FT,Ireland,L,Israel,100,"Kubernetes, GCP, SQL, Azure",Master,1,Energy,2025-02-15,2025-04-19,1617,8.5,AI Innovations +AI04938,ML Ops Engineer,93032,USD,93032,MI,CT,Israel,S,Ireland,100,"SQL, R, Tableau",Bachelor,2,Real Estate,2024-09-23,2024-11-05,697,8.4,Smart Analytics +AI04939,Machine Learning Researcher,310945,CHF,279851,EX,FL,Switzerland,S,Poland,0,"Kubernetes, Scala, Azure",Bachelor,18,Retail,2024-09-03,2024-10-20,1636,7.5,Smart Analytics +AI04940,Principal Data Scientist,91705,USD,91705,MI,FL,Israel,S,Israel,0,"Computer Vision, Kubernetes, GCP, R",PhD,2,Gaming,2024-05-31,2024-08-09,1029,9.7,Cloud AI Solutions +AI04941,AI Consultant,84567,USD,84567,EN,FL,Norway,L,Norway,50,"R, SQL, Azure, Deep Learning, Linux",Associate,0,Education,2024-04-16,2024-06-03,1320,9.6,Digital Transformation LLC +AI04942,AI Architect,77592,EUR,65953,EN,FT,Austria,L,Vietnam,100,"Docker, Hadoop, Tableau",Master,1,Automotive,2024-07-22,2024-09-16,1129,8.7,DeepTech Ventures +AI04943,Head of AI,106660,USD,106660,SE,FL,Sweden,M,Chile,100,"MLOps, Statistics, AWS, NLP, Computer Vision",Associate,9,Retail,2024-06-15,2024-07-05,1054,9.8,AI Innovations +AI04944,Data Engineer,46462,USD,46462,MI,PT,China,L,China,100,"Kubernetes, Git, Statistics",Bachelor,3,Consulting,2024-12-02,2025-01-04,2365,6.6,Neural Networks Co +AI04945,Autonomous Systems Engineer,131368,GBP,98526,SE,PT,United Kingdom,M,Luxembourg,50,"Git, Azure, GCP, Python, AWS",Bachelor,9,Manufacturing,2024-08-10,2024-10-13,503,5,Cognitive Computing +AI04946,Data Scientist,78787,USD,78787,MI,PT,South Korea,S,South Korea,50,"Kubernetes, PyTorch, MLOps, SQL",Master,3,Retail,2024-11-25,2025-01-12,1588,6.4,Cloud AI Solutions +AI04947,ML Ops Engineer,57111,USD,57111,EN,PT,Sweden,M,Sweden,100,"Java, Azure, PyTorch, Scala",Master,1,Automotive,2025-02-24,2025-04-26,931,9,Quantum Computing Inc +AI04948,Deep Learning Engineer,70529,USD,70529,EN,FL,United States,L,United States,100,"Computer Vision, R, SQL",Master,0,Retail,2024-09-17,2024-11-05,1367,8.8,Cognitive Computing +AI04949,Principal Data Scientist,166422,USD,166422,SE,FT,Ireland,L,United States,100,"Spark, Tableau, R, SQL",PhD,6,Transportation,2024-07-20,2024-09-25,1832,5.5,Future Systems +AI04950,Deep Learning Engineer,132627,JPY,14588970,SE,CT,Japan,S,Japan,100,"R, Kubernetes, Python",Bachelor,9,Finance,2025-03-22,2025-05-06,2345,9.9,Advanced Robotics +AI04951,AI Product Manager,79266,USD,79266,EN,PT,Ireland,M,Ireland,0,"Statistics, Kubernetes, Computer Vision, Python, Git",PhD,0,Automotive,2025-04-29,2025-05-15,1442,6.4,AI Innovations +AI04952,Data Analyst,159779,EUR,135812,EX,CT,Germany,L,Portugal,50,"Azure, Python, Docker, Hadoop, Linux",PhD,12,Government,2024-10-14,2024-11-18,975,7.5,Digital Transformation LLC +AI04953,Principal Data Scientist,139290,USD,139290,SE,CT,United States,S,United States,0,"Tableau, SQL, Scala, Computer Vision, Java",Master,8,Education,2024-10-16,2024-11-17,1978,7.6,AI Innovations +AI04954,Robotics Engineer,231125,CHF,208013,EX,CT,Switzerland,S,Romania,100,"SQL, NLP, Tableau",Master,16,Healthcare,2024-05-05,2024-05-26,1244,9.1,Predictive Systems +AI04955,AI Architect,122595,GBP,91946,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Kubernetes, Scala, Deep Learning",Master,3,Energy,2024-09-02,2024-11-04,2102,8,Algorithmic Solutions +AI04956,Data Analyst,68427,USD,68427,EN,CT,Ireland,S,Ireland,0,"AWS, Linux, SQL",Bachelor,1,Retail,2024-07-20,2024-09-11,1893,6.4,Cognitive Computing +AI04957,Head of AI,202722,USD,202722,EX,FL,Finland,L,Finland,100,"AWS, Git, Python, Deep Learning, Spark",Bachelor,16,Healthcare,2024-06-27,2024-08-21,1923,6.2,Neural Networks Co +AI04958,Data Scientist,108147,EUR,91925,SE,FT,Austria,M,Latvia,50,"Data Visualization, PyTorch, MLOps",PhD,7,Finance,2024-09-26,2024-11-15,626,8.1,Machine Intelligence Group +AI04959,ML Ops Engineer,115437,AUD,155840,SE,FT,Australia,S,Australia,100,"TensorFlow, Hadoop, Mathematics, SQL",Master,6,Automotive,2024-12-13,2025-02-08,1204,9.8,Predictive Systems +AI04960,Head of AI,77217,GBP,57913,MI,PT,United Kingdom,S,United Kingdom,50,"Hadoop, Java, SQL, AWS",Bachelor,4,Finance,2024-10-16,2024-11-02,1484,9.7,DeepTech Ventures +AI04961,AI Software Engineer,57529,USD,57529,EN,CT,Israel,L,Kenya,100,"MLOps, TensorFlow, Kubernetes, Data Visualization",PhD,1,Manufacturing,2024-03-15,2024-03-29,928,8.4,Smart Analytics +AI04962,Principal Data Scientist,113427,EUR,96413,MI,PT,France,L,France,100,"SQL, Data Visualization, TensorFlow, Scala, R",Bachelor,4,Transportation,2024-01-13,2024-03-10,794,6.3,TechCorp Inc +AI04963,Autonomous Systems Engineer,71693,USD,71693,EN,PT,Denmark,M,Denmark,50,"Python, Deep Learning, Mathematics, PyTorch, AWS",PhD,0,Gaming,2024-06-08,2024-07-27,2047,7.3,Digital Transformation LLC +AI04964,ML Ops Engineer,151134,EUR,128464,SE,CT,Germany,M,Germany,0,"PyTorch, Git, TensorFlow",PhD,9,Healthcare,2024-12-05,2025-01-31,1045,9.7,DataVision Ltd +AI04965,AI Product Manager,135496,EUR,115172,EX,CT,France,M,France,0,"GCP, Data Visualization, Scala, Git",PhD,18,Consulting,2024-01-23,2024-02-15,938,7.3,Future Systems +AI04966,NLP Engineer,93530,USD,93530,EX,CT,India,L,India,100,"R, Tableau, Data Visualization, Python, PyTorch",Associate,10,Finance,2024-07-13,2024-08-22,1866,8.2,TechCorp Inc +AI04967,AI Research Scientist,194766,JPY,21424260,EX,PT,Japan,L,Japan,50,"Kubernetes, Spark, PyTorch, TensorFlow",PhD,17,Government,2024-02-20,2024-04-03,1832,7,Smart Analytics +AI04968,Data Engineer,214036,JPY,23543960,EX,PT,Japan,M,Netherlands,0,"Deep Learning, SQL, Spark",Associate,15,Healthcare,2025-02-27,2025-04-29,2309,5.8,Neural Networks Co +AI04969,AI Consultant,33244,USD,33244,EN,CT,China,M,China,50,"Deep Learning, Scala, Tableau, Computer Vision",Associate,0,Gaming,2024-08-03,2024-09-29,1665,7.8,Algorithmic Solutions +AI04970,AI Specialist,133388,USD,133388,SE,FL,Denmark,M,Denmark,100,"Computer Vision, Hadoop, Tableau, TensorFlow, Python",Bachelor,6,Telecommunications,2024-02-10,2024-03-09,623,8.1,Algorithmic Solutions +AI04971,Research Scientist,44185,USD,44185,EN,FT,Israel,S,New Zealand,0,"AWS, Scala, Mathematics, TensorFlow, Hadoop",Master,1,Technology,2024-10-07,2024-12-01,781,5.7,Future Systems +AI04972,AI Architect,89882,EUR,76400,SE,CT,Austria,S,Malaysia,50,"AWS, Azure, GCP, Statistics",Master,8,Healthcare,2024-05-14,2024-07-11,1075,8,Smart Analytics +AI04973,Data Engineer,167159,GBP,125369,EX,PT,United Kingdom,L,United Kingdom,100,"Computer Vision, Git, AWS",Associate,10,Telecommunications,2024-12-05,2025-01-08,1609,7.3,Advanced Robotics +AI04974,Autonomous Systems Engineer,110919,USD,110919,SE,FT,South Korea,M,Australia,50,"Scala, Mathematics, Deep Learning, Computer Vision",Associate,9,Technology,2024-08-09,2024-09-17,1747,6.7,Future Systems +AI04975,AI Consultant,153715,USD,153715,SE,FT,Israel,L,Turkey,0,"MLOps, Linux, Kubernetes",Associate,7,Energy,2024-12-09,2025-01-07,2330,6.8,Quantum Computing Inc +AI04976,AI Consultant,132249,USD,132249,SE,CT,Sweden,M,Ireland,50,"Kubernetes, Git, Spark",Associate,6,Retail,2024-06-21,2024-08-01,690,5.4,Smart Analytics +AI04977,NLP Engineer,231132,USD,231132,EX,FT,Denmark,S,Denmark,0,"Python, Git, Docker, Hadoop, Statistics",Bachelor,14,Media,2024-10-18,2024-12-24,1890,6.3,Neural Networks Co +AI04978,AI Consultant,85300,EUR,72505,EN,CT,France,L,France,50,"Java, Data Visualization, PyTorch, AWS",Associate,0,Energy,2024-04-24,2024-05-21,1221,6.4,Machine Intelligence Group +AI04979,AI Product Manager,128111,USD,128111,EX,CT,Sweden,S,Mexico,100,"Java, R, Computer Vision, Statistics, Kubernetes",Associate,15,Education,2025-03-22,2025-05-06,1631,7.6,Future Systems +AI04980,AI Architect,61852,SGD,80408,EN,FT,Singapore,S,Canada,50,"MLOps, SQL, Git, PyTorch",Bachelor,1,Energy,2024-09-11,2024-09-27,2061,5.6,DataVision Ltd +AI04981,Data Scientist,59300,USD,59300,EN,FL,Israel,S,Sweden,0,"PyTorch, Spark, Tableau, MLOps, SQL",Associate,0,Energy,2024-01-08,2024-03-18,1348,9.3,Machine Intelligence Group +AI04982,Machine Learning Researcher,126739,SGD,164761,SE,PT,Singapore,S,Singapore,50,"Git, TensorFlow, SQL",Associate,5,Media,2024-11-29,2025-01-31,554,8.3,Machine Intelligence Group +AI04983,Computer Vision Engineer,80800,USD,80800,EN,CT,Denmark,M,Denmark,50,"Python, Kubernetes, NLP, Statistics",Associate,0,Gaming,2024-03-25,2024-04-28,594,6,Quantum Computing Inc +AI04984,NLP Engineer,85451,AUD,115359,MI,FT,Australia,S,Luxembourg,50,"Kubernetes, Linux, Python",Bachelor,3,Government,2024-06-02,2024-08-05,2249,7.8,DeepTech Ventures +AI04985,AI Product Manager,82153,USD,82153,EN,CT,United States,M,Estonia,50,"Hadoop, TensorFlow, AWS",Associate,0,Telecommunications,2024-03-14,2024-05-17,927,6,DataVision Ltd +AI04986,Machine Learning Researcher,79663,USD,79663,MI,FL,Ireland,S,Ireland,100,"Java, R, MLOps, SQL, Statistics",Associate,2,Energy,2024-08-06,2024-08-21,1985,7.7,Future Systems +AI04987,Robotics Engineer,141209,EUR,120028,SE,PT,Austria,L,Austria,0,"Hadoop, Linux, PyTorch, Java, Mathematics",Master,8,Energy,2025-04-24,2025-05-10,2143,7.8,TechCorp Inc +AI04988,Machine Learning Researcher,47558,USD,47558,EX,FT,India,S,India,0,"NLP, Tableau, Spark, TensorFlow, Statistics",Bachelor,12,Healthcare,2024-02-03,2024-04-05,1793,9,Predictive Systems +AI04989,Machine Learning Researcher,134887,USD,134887,MI,FT,Denmark,L,Denmark,100,"Data Visualization, Scala, Java, R, Computer Vision",PhD,2,Government,2025-03-13,2025-04-23,2069,9.1,Machine Intelligence Group +AI04990,AI Research Scientist,216990,USD,216990,EX,PT,Finland,M,Finland,50,"Hadoop, SQL, Computer Vision, Scala",Master,19,Technology,2024-04-13,2024-05-19,2371,5.6,TechCorp Inc +AI04991,Machine Learning Engineer,270223,EUR,229690,EX,CT,France,L,France,50,"Linux, Python, Deep Learning, Hadoop",Associate,15,Consulting,2024-02-25,2024-05-08,820,8.2,Digital Transformation LLC +AI04992,AI Product Manager,123617,USD,123617,SE,PT,Sweden,S,Indonesia,50,"Python, Hadoop, TensorFlow, PyTorch",Bachelor,8,Technology,2024-11-14,2024-12-13,1367,9,Advanced Robotics +AI04993,Deep Learning Engineer,179200,CHF,161280,SE,CT,Switzerland,M,Switzerland,50,"Python, Linux, Git, R, TensorFlow",Master,6,Media,2024-10-31,2025-01-02,654,9.1,Quantum Computing Inc +AI04994,Robotics Engineer,123515,USD,123515,SE,FL,Finland,M,Finland,0,"Spark, Kubernetes, Scala, Mathematics, Linux",Master,5,Retail,2025-03-29,2025-05-08,736,9.6,Cloud AI Solutions +AI04995,AI Research Scientist,101862,AUD,137514,MI,PT,Australia,L,Ukraine,100,"Git, Python, Computer Vision, TensorFlow, PyTorch",Associate,3,Transportation,2024-04-13,2024-05-22,1831,5.3,Predictive Systems +AI04996,AI Consultant,183450,USD,183450,EX,PT,United States,S,United States,50,"GCP, Computer Vision, SQL",Bachelor,17,Government,2024-06-17,2024-07-12,902,6.3,Neural Networks Co +AI04997,Machine Learning Engineer,81041,SGD,105353,EN,PT,Singapore,L,Singapore,0,"MLOps, PyTorch, Python, TensorFlow",Associate,1,Finance,2024-06-29,2024-08-16,1494,9.3,Autonomous Tech +AI04998,AI Software Engineer,80467,USD,80467,EX,PT,India,S,India,0,"Mathematics, Linux, Git, PyTorch",Master,14,Manufacturing,2024-11-22,2024-12-25,2205,6.8,Predictive Systems +AI04999,AI Software Engineer,88669,AUD,119703,MI,CT,Australia,L,Australia,100,"Python, Hadoop, MLOps",Master,3,Real Estate,2024-05-30,2024-08-10,1427,5.5,DataVision Ltd +AI05000,Machine Learning Researcher,113313,USD,113313,MI,FT,Sweden,L,Sweden,100,"Scala, SQL, PyTorch, R",PhD,3,Education,2024-09-27,2024-11-25,1895,9.5,Digital Transformation LLC +AI05001,Research Scientist,306192,USD,306192,EX,FT,Denmark,L,Denmark,0,"PyTorch, Azure, Tableau, Scala",PhD,11,Automotive,2025-02-25,2025-03-20,2405,5.5,Smart Analytics +AI05002,Head of AI,190624,USD,190624,EX,CT,Denmark,S,Denmark,50,"Kubernetes, Tableau, Python, Hadoop",Bachelor,15,Automotive,2024-10-22,2024-12-06,1947,7.2,Cloud AI Solutions +AI05003,NLP Engineer,68152,SGD,88598,EN,FT,Singapore,L,Egypt,0,"R, Azure, Kubernetes, Linux",PhD,0,Telecommunications,2024-03-20,2024-05-06,1227,9.1,Algorithmic Solutions +AI05004,Principal Data Scientist,91590,USD,91590,EN,CT,United States,L,Kenya,0,"PyTorch, SQL, Kubernetes, Java, AWS",Associate,1,Media,2024-06-27,2024-07-19,578,6.6,Autonomous Tech +AI05005,AI Research Scientist,50730,EUR,43121,EN,FT,Netherlands,S,Netherlands,0,"R, Java, Data Visualization, NLP",PhD,1,Real Estate,2024-04-28,2024-05-15,1020,5.7,TechCorp Inc +AI05006,Robotics Engineer,57915,GBP,43436,EN,FL,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, AWS, Mathematics, Git",Associate,0,Finance,2025-03-02,2025-04-20,2451,8.9,Future Systems +AI05007,AI Architect,74536,AUD,100624,MI,FL,Australia,S,Turkey,0,"Kubernetes, Docker, Data Visualization",PhD,2,Retail,2025-02-19,2025-04-26,1612,9.3,Predictive Systems +AI05008,Data Engineer,179315,USD,179315,SE,FL,Denmark,L,Denmark,0,"Python, TensorFlow, Linux, PyTorch",PhD,8,Education,2024-09-14,2024-10-29,925,5.3,Digital Transformation LLC +AI05009,ML Ops Engineer,19776,USD,19776,EN,FT,India,M,Japan,50,"Docker, Scala, GCP, MLOps",Bachelor,0,Consulting,2024-07-30,2024-09-17,604,8.3,DataVision Ltd +AI05010,Data Analyst,73489,EUR,62466,EN,CT,Netherlands,S,Ireland,0,"Computer Vision, Tableau, Linux, Git, Deep Learning",Master,0,Education,2024-11-23,2025-01-04,1966,9.7,DeepTech Ventures +AI05011,AI Product Manager,67007,JPY,7370770,EN,CT,Japan,S,Japan,100,"SQL, TensorFlow, Data Visualization, NLP, Linux",Bachelor,1,Finance,2024-10-18,2024-12-25,1765,8.2,Advanced Robotics +AI05012,Machine Learning Engineer,26216,USD,26216,EN,PT,China,M,China,50,"Hadoop, Data Visualization, Python, Statistics, Mathematics",Associate,1,Gaming,2024-08-16,2024-10-25,2458,6.5,Cognitive Computing +AI05013,ML Ops Engineer,80593,CAD,100741,MI,CT,Canada,L,Canada,100,"Hadoop, SQL, Java",Associate,3,Government,2024-06-09,2024-07-02,714,5.3,Machine Intelligence Group +AI05014,Principal Data Scientist,251940,AUD,340119,EX,FL,Australia,L,Australia,50,"NLP, R, Statistics, SQL, Data Visualization",Master,12,Manufacturing,2025-01-01,2025-01-21,2150,7.3,Advanced Robotics +AI05015,Data Scientist,271778,USD,271778,EX,FT,Ireland,L,Ukraine,0,"AWS, Linux, Python, TensorFlow, Computer Vision",Bachelor,17,Automotive,2024-05-06,2024-06-18,1477,8.3,Algorithmic Solutions +AI05016,AI Research Scientist,136680,EUR,116178,SE,FT,Austria,M,Austria,100,"Linux, Scala, Mathematics, Hadoop, Java",Associate,7,Energy,2024-06-27,2024-07-24,1821,6.7,Digital Transformation LLC +AI05017,AI Architect,90736,USD,90736,MI,CT,South Korea,M,Colombia,50,"Data Visualization, Git, R",Bachelor,3,Finance,2025-02-04,2025-03-18,1998,7.6,Future Systems +AI05018,Machine Learning Engineer,176612,USD,176612,EX,FT,Norway,M,Norway,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,12,Real Estate,2025-01-06,2025-01-23,1705,9.6,Digital Transformation LLC +AI05019,NLP Engineer,86142,USD,86142,SE,PT,South Korea,M,Czech Republic,100,"Computer Vision, NLP, Tableau, Data Visualization, MLOps",Master,6,Technology,2024-05-29,2024-07-19,2196,5.1,Advanced Robotics +AI05020,AI Research Scientist,71454,SGD,92890,MI,PT,Singapore,S,Singapore,100,"Scala, Linux, Data Visualization",Bachelor,4,Gaming,2024-02-21,2024-03-23,1063,6.1,Advanced Robotics +AI05021,AI Software Engineer,70698,USD,70698,EN,FT,Norway,S,Norway,100,"TensorFlow, Data Visualization, SQL, Hadoop, R",PhD,0,Real Estate,2024-08-07,2024-10-12,515,9.9,Algorithmic Solutions +AI05022,Computer Vision Engineer,70125,EUR,59606,EN,CT,Germany,M,United States,0,"TensorFlow, Tableau, GCP, Spark, Linux",Associate,0,Manufacturing,2025-04-14,2025-06-25,525,7.9,Machine Intelligence Group +AI05023,AI Specialist,164581,AUD,222184,EX,CT,Australia,S,Australia,100,"Tableau, Linux, PyTorch, TensorFlow, Computer Vision",Bachelor,11,Automotive,2025-02-04,2025-03-02,1128,9.7,TechCorp Inc +AI05024,NLP Engineer,125674,GBP,94256,SE,FL,United Kingdom,L,United Kingdom,100,"Computer Vision, MLOps, Git",Bachelor,6,Media,2024-08-16,2024-10-22,1388,8.8,Quantum Computing Inc +AI05025,Robotics Engineer,108470,CHF,97623,EN,FL,Switzerland,L,Switzerland,100,"Spark, Tableau, Docker, Deep Learning, NLP",Master,1,Telecommunications,2024-04-30,2024-07-10,1708,6.5,Quantum Computing Inc +AI05026,AI Architect,68849,USD,68849,EN,PT,United States,S,United States,0,"PyTorch, AWS, Computer Vision",Associate,0,Healthcare,2024-04-12,2024-06-09,1204,10,TechCorp Inc +AI05027,Autonomous Systems Engineer,101825,JPY,11200750,SE,CT,Japan,S,Japan,50,"MLOps, Java, Data Visualization, Linux, Scala",Bachelor,8,Real Estate,2025-02-27,2025-04-05,960,9.7,Future Systems +AI05028,Deep Learning Engineer,351728,USD,351728,EX,CT,Norway,L,Norway,0,"Tableau, Spark, Python, SQL",Bachelor,17,Real Estate,2024-09-22,2024-10-13,1508,5.3,Quantum Computing Inc +AI05029,Machine Learning Researcher,97819,USD,97819,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Git, GCP, Linux",Bachelor,9,Retail,2024-08-28,2024-09-14,1494,7.2,AI Innovations +AI05030,Data Scientist,163331,USD,163331,SE,FL,United States,M,United States,50,"TensorFlow, Git, Data Visualization, Kubernetes",Master,6,Healthcare,2025-04-29,2025-05-21,1419,9.5,Advanced Robotics +AI05031,Head of AI,93720,USD,93720,MI,CT,United States,M,United States,100,"Linux, Spark, SQL, PyTorch",PhD,4,Government,2024-12-19,2025-01-19,1659,9.1,Machine Intelligence Group +AI05032,NLP Engineer,108820,EUR,92497,MI,PT,Netherlands,M,Netherlands,50,"Kubernetes, Computer Vision, R, GCP, Hadoop",Master,2,Gaming,2024-12-14,2025-02-09,2389,9.4,AI Innovations +AI05033,AI Consultant,23491,USD,23491,EN,FL,India,S,India,0,"R, PyTorch, TensorFlow, Statistics",Bachelor,0,Healthcare,2024-02-07,2024-03-31,1921,7,TechCorp Inc +AI05034,Robotics Engineer,38464,USD,38464,SE,CT,India,M,Israel,100,"Python, TensorFlow, Statistics, PyTorch, Mathematics",PhD,6,Real Estate,2024-09-16,2024-10-17,1319,6.5,TechCorp Inc +AI05035,Data Analyst,121725,USD,121725,SE,PT,South Korea,M,South Korea,0,"Linux, TensorFlow, MLOps, Git, NLP",Bachelor,5,Government,2024-11-20,2024-12-23,1624,7.8,TechCorp Inc +AI05036,Computer Vision Engineer,121877,CHF,109689,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Deep Learning, Data Visualization",Bachelor,3,Finance,2024-03-21,2024-06-01,1183,6.6,Future Systems +AI05037,Machine Learning Researcher,96000,USD,96000,EN,CT,Norway,M,Norway,50,"Scala, Deep Learning, Computer Vision, GCP, Git",Bachelor,0,Retail,2024-01-27,2024-02-24,1635,8,Advanced Robotics +AI05038,Robotics Engineer,46573,USD,46573,SE,FT,China,S,China,100,"AWS, Linux, PyTorch, GCP",PhD,9,Government,2024-03-22,2024-05-09,830,9.9,Predictive Systems +AI05039,AI Architect,203167,EUR,172692,EX,CT,Austria,M,Austria,50,"SQL, PyTorch, Java, Hadoop",Associate,17,Education,2024-09-14,2024-10-09,865,9.6,DeepTech Ventures +AI05040,Data Scientist,177459,CHF,159713,SE,CT,Switzerland,S,Switzerland,50,"Spark, R, Hadoop, Linux, Mathematics",Bachelor,6,Telecommunications,2024-09-15,2024-10-29,740,9.4,Future Systems +AI05041,Machine Learning Engineer,41556,USD,41556,MI,FT,China,S,China,50,"Python, TensorFlow, Azure, Kubernetes",Associate,3,Gaming,2024-01-04,2024-03-05,1652,6.1,Quantum Computing Inc +AI05042,Data Scientist,152796,USD,152796,EX,PT,Sweden,M,Sweden,100,"Linux, Hadoop, Python",Master,10,Automotive,2025-02-17,2025-04-09,2123,8.4,Cognitive Computing +AI05043,Robotics Engineer,70161,JPY,7717710,EN,PT,Japan,L,Japan,0,"Spark, PyTorch, GCP, Scala, Statistics",PhD,0,Manufacturing,2024-01-18,2024-02-05,1333,6.3,DataVision Ltd +AI05044,ML Ops Engineer,66092,CAD,82615,EN,PT,Canada,S,Sweden,100,"SQL, Scala, NLP",PhD,1,Transportation,2024-03-07,2024-03-31,2308,5.6,Future Systems +AI05045,Data Engineer,271475,SGD,352918,EX,FL,Singapore,L,Singapore,0,"Git, Docker, Hadoop",Associate,10,Media,2024-08-25,2024-10-08,1142,7.1,DataVision Ltd +AI05046,AI Architect,71751,JPY,7892610,EN,CT,Japan,L,Japan,0,"Java, MLOps, Git, Computer Vision, Kubernetes",Associate,1,Real Estate,2024-08-08,2024-09-24,1649,8.1,DeepTech Ventures +AI05047,Research Scientist,91975,USD,91975,EX,PT,China,S,China,0,"Azure, Docker, Mathematics, Statistics, GCP",Bachelor,10,Technology,2024-03-28,2024-05-08,735,8.1,Autonomous Tech +AI05048,Machine Learning Researcher,139317,EUR,118419,SE,FL,France,M,France,100,"Python, Kubernetes, Data Visualization",Bachelor,9,Consulting,2024-09-02,2024-10-04,2142,7.9,Future Systems +AI05049,Machine Learning Researcher,56279,EUR,47837,EN,CT,Netherlands,S,Indonesia,0,"Docker, Python, Data Visualization, Deep Learning",Bachelor,1,Technology,2024-05-07,2024-07-06,2433,7.6,Cloud AI Solutions +AI05050,Head of AI,212031,AUD,286242,EX,PT,Australia,M,Australia,100,"AWS, Statistics, Git, SQL",Associate,15,Gaming,2025-03-10,2025-04-16,1142,7.9,Autonomous Tech +AI05051,AI Research Scientist,261631,AUD,353202,EX,FT,Australia,L,New Zealand,50,"Computer Vision, NLP, GCP",Associate,10,Technology,2024-07-31,2024-08-18,982,6.6,Cognitive Computing +AI05052,Machine Learning Researcher,41755,USD,41755,MI,FL,China,M,China,100,"NLP, SQL, TensorFlow, Linux, Computer Vision",Associate,4,Gaming,2024-10-21,2024-11-30,1171,7.6,Advanced Robotics +AI05053,Computer Vision Engineer,78608,EUR,66817,EN,PT,Netherlands,M,Malaysia,50,"Data Visualization, Scala, Java, Computer Vision, Tableau",PhD,0,Energy,2025-01-20,2025-03-10,642,9.9,Digital Transformation LLC +AI05054,Head of AI,37889,USD,37889,SE,FT,India,M,India,100,"Scala, Deep Learning, MLOps, Python",Associate,8,Retail,2024-02-19,2024-04-03,856,8.9,DataVision Ltd +AI05055,Data Scientist,97397,USD,97397,EN,CT,United States,L,Brazil,50,"Git, Deep Learning, TensorFlow",PhD,1,Finance,2025-04-02,2025-05-05,1562,9.5,Cognitive Computing +AI05056,Data Analyst,265023,USD,265023,EX,CT,Denmark,S,Spain,50,"Git, Docker, Statistics",Master,16,Manufacturing,2024-12-15,2025-01-12,1294,7.7,DataVision Ltd +AI05057,Machine Learning Researcher,143323,AUD,193486,SE,FL,Australia,M,Australia,0,"Tableau, Java, Git",Bachelor,5,Energy,2024-10-31,2025-01-06,729,7,Machine Intelligence Group +AI05058,Head of AI,97000,EUR,82450,SE,CT,France,M,France,0,"Java, SQL, Python, Docker",Associate,5,Technology,2024-01-10,2024-02-03,2147,6.5,Neural Networks Co +AI05059,AI Software Engineer,46374,USD,46374,EN,CT,Ireland,S,United States,100,"PyTorch, Kubernetes, Docker",Bachelor,1,Telecommunications,2024-07-03,2024-09-10,2065,8.9,Smart Analytics +AI05060,AI Architect,229381,EUR,194974,EX,CT,France,M,France,50,"Python, TensorFlow, Scala",PhD,19,Technology,2024-10-01,2024-10-23,1365,9,Digital Transformation LLC +AI05061,Computer Vision Engineer,158873,JPY,17476030,SE,FL,Japan,M,Japan,50,"GCP, Java, Azure",Bachelor,6,Education,2024-06-07,2024-07-04,2166,9.1,Future Systems +AI05062,Machine Learning Engineer,69868,USD,69868,EN,PT,Norway,M,India,50,"Kubernetes, AWS, GCP",Associate,0,Education,2024-02-23,2024-03-26,1959,7.7,DeepTech Ventures +AI05063,AI Specialist,101000,CHF,90900,EN,PT,Switzerland,S,Switzerland,0,"PyTorch, TensorFlow, Python, Git",Bachelor,0,Consulting,2024-12-31,2025-02-13,2181,5.7,Digital Transformation LLC +AI05064,Data Engineer,81849,SGD,106404,EN,CT,Singapore,M,Singapore,100,"NLP, PyTorch, Statistics, Hadoop",PhD,1,Automotive,2024-07-21,2024-09-24,1881,7.7,Smart Analytics +AI05065,AI Architect,134380,GBP,100785,SE,CT,United Kingdom,L,United Kingdom,100,"Git, Azure, Statistics, NLP",PhD,5,Telecommunications,2025-03-04,2025-04-12,2293,5.6,TechCorp Inc +AI05066,Data Scientist,167829,CHF,151046,SE,PT,Switzerland,M,Switzerland,50,"Hadoop, PyTorch, Git, Data Visualization, Docker",Master,7,Government,2024-06-17,2024-08-09,1514,6.7,AI Innovations +AI05067,Machine Learning Engineer,24678,USD,24678,EN,PT,China,S,China,0,"Python, SQL, PyTorch",Master,0,Healthcare,2024-03-22,2024-04-05,1955,9,Predictive Systems +AI05068,Autonomous Systems Engineer,54248,SGD,70522,EN,CT,Singapore,S,Singapore,50,"Scala, Docker, MLOps, AWS, SQL",Bachelor,0,Technology,2024-10-14,2024-12-06,1096,5.5,DeepTech Ventures +AI05069,Head of AI,99288,EUR,84395,SE,CT,Austria,S,Austria,100,"Kubernetes, Spark, AWS",PhD,6,Healthcare,2024-04-04,2024-05-22,2422,7.6,Machine Intelligence Group +AI05070,AI Product Manager,189688,USD,189688,EX,FL,United States,S,United States,100,"Scala, TensorFlow, Mathematics, NLP, Linux",Master,11,Consulting,2024-06-01,2024-06-27,1807,9.8,Smart Analytics +AI05071,Machine Learning Engineer,89528,JPY,9848080,MI,CT,Japan,M,Russia,50,"SQL, Python, Tableau, Java, Docker",Bachelor,3,Government,2024-05-19,2024-06-26,1088,5.4,Advanced Robotics +AI05072,AI Consultant,88720,USD,88720,MI,FT,United States,S,United States,0,"Statistics, Python, TensorFlow, PyTorch, Hadoop",PhD,3,Finance,2025-04-27,2025-07-03,2198,5.6,Algorithmic Solutions +AI05073,NLP Engineer,72059,USD,72059,EN,FT,Sweden,S,Sweden,50,"Git, Scala, Tableau, Computer Vision",Associate,0,Technology,2024-04-26,2024-05-15,2043,8,Predictive Systems +AI05074,Machine Learning Researcher,50803,EUR,43183,EN,PT,France,S,France,0,"TensorFlow, Git, Statistics, SQL",Master,0,Finance,2024-02-18,2024-04-15,1539,9.3,Cloud AI Solutions +AI05075,AI Consultant,24223,USD,24223,EN,FL,India,S,India,100,"Statistics, Hadoop, MLOps, Azure",Associate,1,Gaming,2025-04-03,2025-04-29,2463,8,Cognitive Computing +AI05076,Deep Learning Engineer,121910,USD,121910,MI,FL,Denmark,M,Denmark,100,"Data Visualization, PyTorch, Spark, TensorFlow, SQL",PhD,2,Retail,2025-03-05,2025-05-11,1058,5.9,Machine Intelligence Group +AI05077,Autonomous Systems Engineer,27869,USD,27869,MI,FT,India,M,India,100,"NLP, Docker, Python, Azure",Bachelor,2,Retail,2024-12-03,2025-01-15,1498,9.5,Advanced Robotics +AI05078,Data Scientist,79781,USD,79781,SE,FL,China,L,China,100,"PyTorch, NLP, Data Visualization",PhD,7,Government,2024-05-27,2024-07-28,1915,7.4,Smart Analytics +AI05079,Computer Vision Engineer,94380,CAD,117975,MI,PT,Canada,L,Canada,100,"Git, Hadoop, Python",Master,3,Government,2024-11-23,2025-01-23,943,6.6,Neural Networks Co +AI05080,Deep Learning Engineer,57159,GBP,42869,EN,FL,United Kingdom,S,Netherlands,50,"R, Azure, Tableau, NLP, Linux",Master,1,Healthcare,2024-01-08,2024-02-25,766,6.6,Cloud AI Solutions +AI05081,AI Software Engineer,70183,USD,70183,EX,FT,China,S,China,100,"Statistics, NLP, TensorFlow, Git",Associate,18,Technology,2025-02-20,2025-04-14,1019,7.4,Predictive Systems +AI05082,AI Research Scientist,63741,USD,63741,EN,PT,Finland,L,Finland,0,"Java, Python, Hadoop",Bachelor,1,Healthcare,2024-01-27,2024-02-10,2032,6.1,AI Innovations +AI05083,AI Product Manager,125484,AUD,169403,SE,FT,Australia,L,Australia,100,"PyTorch, TensorFlow, NLP, Git, Spark",Master,6,Gaming,2024-11-29,2024-12-26,1576,8.1,TechCorp Inc +AI05084,Head of AI,165739,JPY,18231290,SE,FT,Japan,L,Japan,50,"R, Python, NLP, TensorFlow",Bachelor,5,Energy,2024-12-09,2025-02-16,2291,9.6,Digital Transformation LLC +AI05085,ML Ops Engineer,70983,EUR,60336,EN,PT,Austria,M,Austria,100,"Deep Learning, Python, MLOps, Java, TensorFlow",Associate,0,Finance,2024-04-05,2024-04-26,1418,5.4,Predictive Systems +AI05086,AI Specialist,110016,GBP,82512,MI,PT,United Kingdom,L,United Kingdom,0,"Python, Hadoop, TensorFlow",PhD,4,Real Estate,2025-04-30,2025-05-28,2127,8.4,Algorithmic Solutions +AI05087,Data Engineer,123436,CHF,111092,EN,PT,Switzerland,L,Switzerland,100,"Kubernetes, Java, Statistics, NLP, Docker",PhD,0,Technology,2025-02-26,2025-04-15,1329,9.2,Smart Analytics +AI05088,Deep Learning Engineer,81729,USD,81729,MI,CT,Ireland,M,Thailand,100,"Java, Azure, NLP, SQL, AWS",Associate,3,Technology,2024-03-06,2024-04-25,552,6.2,Machine Intelligence Group +AI05089,Principal Data Scientist,24353,USD,24353,EN,FT,China,S,China,100,"R, SQL, NLP",Bachelor,1,Finance,2024-02-16,2024-04-27,1050,8.8,DeepTech Ventures +AI05090,AI Consultant,48696,USD,48696,EN,CT,South Korea,L,Mexico,50,"Hadoop, Tableau, Spark, MLOps",PhD,1,Consulting,2025-02-26,2025-03-24,1665,7.6,Cloud AI Solutions +AI05091,AI Software Engineer,114364,CHF,102928,EN,PT,Switzerland,L,South Africa,100,"MLOps, PyTorch, NLP, Mathematics",PhD,0,Telecommunications,2024-01-11,2024-03-15,1731,8.4,Advanced Robotics +AI05092,AI Architect,93835,USD,93835,EN,CT,United States,M,Argentina,50,"Docker, MLOps, Git",Bachelor,1,Real Estate,2025-02-05,2025-03-06,1431,6.9,Autonomous Tech +AI05093,AI Architect,170109,USD,170109,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Computer Vision, Tableau, Python, Azure",Associate,8,Consulting,2025-03-14,2025-05-21,1430,8.9,Predictive Systems +AI05094,Principal Data Scientist,89443,JPY,9838730,EN,FT,Japan,L,Romania,0,"Git, AWS, R",PhD,0,Automotive,2025-02-09,2025-02-27,2366,7,Future Systems +AI05095,AI Specialist,252682,CHF,227414,EX,CT,Switzerland,L,Switzerland,50,"Git, SQL, GCP",Bachelor,12,Education,2025-03-28,2025-05-30,969,8.2,Machine Intelligence Group +AI05096,Machine Learning Engineer,133737,JPY,14711070,SE,CT,Japan,M,Japan,0,"Azure, GCP, Spark, MLOps, AWS",PhD,9,Retail,2024-12-23,2025-02-22,1774,6.6,Cognitive Computing +AI05097,NLP Engineer,73390,USD,73390,EN,CT,Israel,L,Brazil,0,"SQL, TensorFlow, Tableau, AWS",PhD,1,Consulting,2024-01-10,2024-03-08,2396,6.3,Algorithmic Solutions +AI05098,Deep Learning Engineer,215737,EUR,183376,EX,FT,Germany,M,Ghana,100,"Computer Vision, PyTorch, Python, AWS",Associate,13,Telecommunications,2024-07-14,2024-08-14,670,6.4,Machine Intelligence Group +AI05099,Data Analyst,154884,CHF,139396,MI,FL,Switzerland,L,Switzerland,100,"Scala, Java, AWS, PyTorch",PhD,3,Technology,2024-05-18,2024-06-26,1197,7.6,Autonomous Tech +AI05100,AI Specialist,63606,EUR,54065,MI,FT,France,S,India,0,"Scala, Spark, Git, Computer Vision",Associate,2,Media,2024-08-18,2024-09-29,1449,5.6,Machine Intelligence Group +AI05101,AI Software Engineer,26739,USD,26739,MI,FL,India,S,India,50,"Python, SQL, Linux",PhD,2,Automotive,2024-09-10,2024-10-28,2446,5.6,Smart Analytics +AI05102,AI Research Scientist,38550,USD,38550,SE,PT,India,S,Argentina,50,"Kubernetes, TensorFlow, Git",Master,7,Energy,2024-07-13,2024-09-09,503,9.6,Advanced Robotics +AI05103,Machine Learning Engineer,74739,USD,74739,MI,FT,South Korea,M,South Korea,0,"AWS, Computer Vision, R",PhD,3,Retail,2024-06-21,2024-08-02,1362,7.5,Digital Transformation LLC +AI05104,AI Architect,160816,CHF,144734,MI,FT,Switzerland,L,Switzerland,50,"Scala, Java, AWS, Computer Vision",PhD,3,Technology,2024-01-11,2024-02-23,1597,8.3,DeepTech Ventures +AI05105,Research Scientist,73482,USD,73482,EN,PT,United States,S,Colombia,100,"Computer Vision, Tableau, TensorFlow, GCP",PhD,0,Government,2024-05-17,2024-06-29,1698,8.2,Smart Analytics +AI05106,Deep Learning Engineer,53504,USD,53504,EN,PT,Finland,S,Finland,100,"Data Visualization, Azure, Tableau, Docker, PyTorch",PhD,1,Manufacturing,2025-03-01,2025-04-05,1171,6.5,Cognitive Computing +AI05107,AI Architect,58640,EUR,49844,EN,FL,Germany,S,Malaysia,50,"Mathematics, Linux, PyTorch",Associate,1,Manufacturing,2025-03-03,2025-04-21,2294,9.3,Advanced Robotics +AI05108,Principal Data Scientist,110169,EUR,93644,SE,CT,France,S,Switzerland,100,"Java, SQL, Mathematics, MLOps, Deep Learning",Bachelor,5,Energy,2024-04-23,2024-06-28,2276,6.2,Cloud AI Solutions +AI05109,Data Engineer,61539,EUR,52308,EN,FT,Netherlands,S,Netherlands,50,"PyTorch, Docker, Tableau, Mathematics, Azure",Master,0,Gaming,2024-12-15,2025-02-10,972,5.9,Advanced Robotics +AI05110,AI Product Manager,33132,USD,33132,EN,FT,China,M,China,0,"Deep Learning, TensorFlow, Linux, MLOps, Python",Master,0,Finance,2024-02-07,2024-04-04,1289,6,Smart Analytics +AI05111,NLP Engineer,50597,USD,50597,EN,FT,Ireland,S,Ireland,100,"Tableau, GCP, Git, MLOps, Java",Master,0,Healthcare,2025-02-25,2025-04-05,1056,8,Smart Analytics +AI05112,AI Product Manager,138723,SGD,180340,SE,CT,Singapore,S,Norway,0,"Spark, PyTorch, Mathematics",Associate,7,Technology,2025-04-16,2025-05-18,1946,5.5,Predictive Systems +AI05113,ML Ops Engineer,96580,USD,96580,EX,PT,China,L,China,50,"Computer Vision, GCP, Hadoop",Associate,17,Real Estate,2025-03-14,2025-05-13,608,5.5,DataVision Ltd +AI05114,Principal Data Scientist,75245,GBP,56434,EN,FL,United Kingdom,M,United Kingdom,100,"Deep Learning, Python, Linux, Kubernetes",Master,0,Finance,2025-02-21,2025-04-07,579,6.3,Cognitive Computing +AI05115,AI Research Scientist,100596,USD,100596,EN,FL,Denmark,L,Switzerland,100,"PyTorch, Java, MLOps",Bachelor,0,Real Estate,2025-02-17,2025-03-26,1945,7.3,DeepTech Ventures +AI05116,Principal Data Scientist,82608,USD,82608,EN,FT,Sweden,L,Sweden,50,"Data Visualization, Docker, Mathematics",Master,0,Healthcare,2024-01-14,2024-02-28,2416,7.5,DataVision Ltd +AI05117,Principal Data Scientist,86868,EUR,73838,MI,PT,Austria,M,Estonia,50,"Python, Deep Learning, Kubernetes, Statistics, Hadoop",PhD,3,Transportation,2024-06-12,2024-07-13,1798,8.4,Smart Analytics +AI05118,Data Engineer,92090,USD,92090,EN,FT,Denmark,M,Denmark,0,"Data Visualization, AWS, Azure",Associate,0,Gaming,2025-02-20,2025-04-19,2090,6.2,DataVision Ltd +AI05119,AI Research Scientist,125783,USD,125783,MI,PT,Denmark,M,Denmark,50,"Spark, TensorFlow, Deep Learning, Tableau",Master,2,Retail,2024-02-14,2024-04-27,2313,8.6,TechCorp Inc +AI05120,Machine Learning Researcher,168390,SGD,218907,EX,FT,Singapore,S,Singapore,50,"TensorFlow, NLP, Git, GCP, Spark",Master,18,Telecommunications,2024-06-25,2024-07-11,635,5.4,Future Systems +AI05121,AI Product Manager,193710,CHF,174339,SE,FT,Switzerland,L,Turkey,0,"Python, Kubernetes, Data Visualization",Bachelor,8,Finance,2024-09-20,2024-10-14,696,5.2,Neural Networks Co +AI05122,Robotics Engineer,86414,USD,86414,MI,CT,Ireland,S,Thailand,50,"Python, Linux, Data Visualization, Deep Learning",PhD,4,Energy,2024-09-09,2024-10-10,644,6.2,AI Innovations +AI05123,AI Software Engineer,136589,CAD,170736,SE,FT,Canada,M,Canada,100,"Java, Scala, MLOps, Statistics",Bachelor,8,Energy,2024-02-18,2024-04-17,2280,6.5,Neural Networks Co +AI05124,Research Scientist,116556,AUD,157351,MI,PT,Australia,L,Australia,0,"Hadoop, AWS, Java, Computer Vision",Bachelor,4,Government,2024-12-10,2025-01-17,1582,8.8,Advanced Robotics +AI05125,AI Research Scientist,147616,EUR,125474,SE,FT,France,L,France,50,"Git, Azure, MLOps, Python",Master,9,Telecommunications,2025-01-16,2025-03-05,1224,6.1,AI Innovations +AI05126,ML Ops Engineer,167103,JPY,18381330,EX,CT,Japan,L,Colombia,100,"PyTorch, Git, NLP",Master,19,Manufacturing,2024-01-10,2024-02-24,918,6.5,Digital Transformation LLC +AI05127,Research Scientist,187756,USD,187756,EX,PT,Norway,M,Norway,0,"Scala, SQL, MLOps, Kubernetes",PhD,13,Government,2025-03-21,2025-04-30,635,9.7,Neural Networks Co +AI05128,ML Ops Engineer,25560,USD,25560,EN,FL,India,S,India,0,"Git, Java, Hadoop, AWS",Bachelor,0,Finance,2024-12-17,2025-02-09,1801,9.3,Predictive Systems +AI05129,Data Analyst,64206,USD,64206,MI,CT,South Korea,S,South Korea,100,"SQL, R, Scala",Bachelor,3,Media,2024-10-15,2024-12-14,1941,9.9,Digital Transformation LLC +AI05130,AI Architect,118221,EUR,100488,MI,PT,Germany,L,Germany,100,"Statistics, GCP, Mathematics, R, NLP",Master,4,Consulting,2024-12-08,2025-01-22,2017,5.7,Digital Transformation LLC +AI05131,Data Analyst,104839,JPY,11532290,MI,CT,Japan,M,Japan,100,"Java, Linux, Data Visualization, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-25,1810,5.9,Autonomous Tech +AI05132,AI Architect,86714,USD,86714,MI,CT,South Korea,L,South Korea,0,"GCP, Linux, Hadoop, TensorFlow, Data Visualization",Master,2,Education,2024-10-25,2024-11-20,1338,6.7,Cloud AI Solutions +AI05133,AI Research Scientist,110353,USD,110353,MI,CT,Norway,S,Norway,50,"PyTorch, AWS, SQL, R, MLOps",Bachelor,4,Retail,2025-04-25,2025-06-10,877,9.9,Predictive Systems +AI05134,Machine Learning Researcher,61142,USD,61142,EN,PT,Finland,M,Germany,50,"Mathematics, Linux, R, Java",Bachelor,1,Consulting,2024-10-04,2024-10-29,933,7.5,DataVision Ltd +AI05135,ML Ops Engineer,155690,USD,155690,SE,CT,Norway,L,Ukraine,0,"R, Git, Data Visualization, Python, Spark",Bachelor,6,Education,2025-01-20,2025-02-16,619,6.5,AI Innovations +AI05136,Research Scientist,117303,USD,117303,EX,FL,China,L,China,0,"Python, Git, Azure, Deep Learning, TensorFlow",Master,17,Energy,2024-06-16,2024-08-14,1415,6.9,Quantum Computing Inc +AI05137,Data Scientist,55265,CAD,69081,EN,CT,Canada,M,Canada,100,"Java, Kubernetes, NLP, Spark",Master,1,Automotive,2024-12-12,2024-12-27,1241,9.6,Algorithmic Solutions +AI05138,Data Analyst,76310,USD,76310,EX,CT,India,L,India,100,"Git, Python, MLOps",Master,19,Telecommunications,2024-11-17,2024-12-27,786,8.4,Cloud AI Solutions +AI05139,Autonomous Systems Engineer,93083,SGD,121008,EN,FT,Singapore,L,Egypt,50,"Azure, AWS, Deep Learning, Git",Master,1,Technology,2024-08-06,2024-09-28,2421,6.5,Machine Intelligence Group +AI05140,Research Scientist,133350,USD,133350,SE,CT,Norway,S,Norway,100,"Computer Vision, Docker, PyTorch",PhD,7,Transportation,2025-02-25,2025-03-26,1457,8.7,Machine Intelligence Group +AI05141,Computer Vision Engineer,86337,USD,86337,MI,CT,Finland,S,United Kingdom,0,"Hadoop, SQL, Data Visualization, PyTorch",Master,2,Telecommunications,2025-01-18,2025-02-18,1291,8.2,DataVision Ltd +AI05142,Data Scientist,86313,USD,86313,MI,CT,Ireland,M,Ireland,100,"Data Visualization, R, GCP, Python, Computer Vision",PhD,2,Retail,2024-05-12,2024-06-19,2120,7.6,Neural Networks Co +AI05143,ML Ops Engineer,57198,USD,57198,SE,CT,China,M,China,0,"Mathematics, Scala, Kubernetes",PhD,7,Education,2024-05-14,2024-06-21,2017,5.4,DataVision Ltd +AI05144,AI Software Engineer,60582,JPY,6664020,EN,FT,Japan,S,Japan,0,"NLP, Deep Learning, Azure, Python",PhD,1,Education,2024-07-16,2024-08-21,1597,9.4,Advanced Robotics +AI05145,Head of AI,55380,EUR,47073,EN,CT,Austria,M,Austria,0,"Git, GCP, AWS, Mathematics",Bachelor,0,Gaming,2025-03-10,2025-03-26,1708,6.8,DeepTech Ventures +AI05146,AI Research Scientist,48341,USD,48341,SE,FL,India,M,India,0,"Kubernetes, GCP, MLOps, Docker",Associate,7,Technology,2024-06-11,2024-07-23,1819,7.5,AI Innovations +AI05147,AI Product Manager,251565,USD,251565,EX,FT,Norway,L,Norway,50,"GCP, Python, Statistics",Master,17,Healthcare,2024-05-10,2024-06-28,1282,8,Advanced Robotics +AI05148,Machine Learning Researcher,236217,CHF,212595,EX,PT,Switzerland,S,Switzerland,50,"Tableau, Kubernetes, AWS, Mathematics, Scala",Bachelor,13,Education,2025-04-16,2025-06-03,1026,9.3,Digital Transformation LLC +AI05149,Autonomous Systems Engineer,91231,USD,91231,SE,CT,South Korea,M,Colombia,100,"Spark, Scala, MLOps",Master,6,Healthcare,2024-02-04,2024-03-04,1711,7,Neural Networks Co +AI05150,Machine Learning Researcher,61130,USD,61130,EN,FL,Israel,S,Nigeria,0,"SQL, MLOps, Computer Vision, Python, GCP",Bachelor,0,Manufacturing,2024-11-24,2025-01-10,1637,9,AI Innovations +AI05151,Computer Vision Engineer,62398,CAD,77998,EN,CT,Canada,L,Canada,50,"Data Visualization, Linux, Spark",Master,1,Healthcare,2024-06-03,2024-07-05,1982,9.2,AI Innovations +AI05152,Research Scientist,176242,EUR,149806,EX,FL,France,M,South Africa,50,"Python, Hadoop, GCP",Bachelor,14,Education,2025-02-04,2025-04-05,1846,8.2,Neural Networks Co +AI05153,Data Analyst,153418,EUR,130405,EX,FL,France,M,France,100,"MLOps, R, Scala",Bachelor,13,Government,2025-03-26,2025-04-15,844,7.6,DeepTech Ventures +AI05154,Data Scientist,81657,CAD,102071,MI,CT,Canada,S,New Zealand,50,"Scala, Git, Python",Master,2,Energy,2024-08-31,2024-10-12,2064,6.7,Algorithmic Solutions +AI05155,Data Analyst,69844,USD,69844,EN,PT,Israel,L,Israel,100,"Java, SQL, PyTorch, Computer Vision, Hadoop",Bachelor,0,Technology,2025-04-16,2025-05-16,910,7.3,TechCorp Inc +AI05156,AI Consultant,91682,EUR,77930,MI,FT,Netherlands,M,Netherlands,50,"NLP, Linux, Azure, Deep Learning",Associate,4,Gaming,2024-10-02,2024-11-27,1604,5.1,Smart Analytics +AI05157,Computer Vision Engineer,69595,AUD,93953,MI,FT,Australia,S,Russia,50,"PyTorch, TensorFlow, Tableau, AWS, Hadoop",Bachelor,3,Transportation,2024-03-19,2024-04-14,774,8.7,Predictive Systems +AI05158,AI Software Engineer,101742,USD,101742,EN,CT,Norway,L,Spain,100,"Linux, SQL, Tableau, Java",Bachelor,0,Retail,2024-10-03,2024-11-20,1067,9.2,Algorithmic Solutions +AI05159,Head of AI,97961,USD,97961,MI,PT,Israel,L,Israel,0,"AWS, Azure, Git, Mathematics",PhD,4,Education,2024-02-14,2024-04-01,1688,8.1,Future Systems +AI05160,AI Consultant,106022,JPY,11662420,MI,FT,Japan,M,Romania,100,"R, SQL, Data Visualization",Master,3,Energy,2024-08-11,2024-09-29,1832,6.4,AI Innovations +AI05161,ML Ops Engineer,46651,USD,46651,MI,PT,China,M,China,50,"Java, Tableau, PyTorch, Computer Vision",Bachelor,2,Telecommunications,2025-03-15,2025-04-17,807,7.3,Algorithmic Solutions +AI05162,Robotics Engineer,124553,CAD,155691,SE,PT,Canada,L,Canada,0,"Mathematics, Linux, Python, Deep Learning, Kubernetes",PhD,9,Manufacturing,2024-06-03,2024-07-31,922,9.8,DeepTech Ventures +AI05163,ML Ops Engineer,104780,EUR,89063,SE,PT,Austria,S,Austria,100,"Git, Python, Spark",Bachelor,8,Education,2024-07-02,2024-09-06,926,6.4,Autonomous Tech +AI05164,AI Specialist,114730,AUD,154886,SE,CT,Australia,S,Brazil,100,"SQL, R, PyTorch",Master,5,Retail,2024-05-13,2024-06-27,787,6.3,Machine Intelligence Group +AI05165,Research Scientist,162856,EUR,138428,SE,CT,France,L,France,0,"Git, Spark, Kubernetes, Statistics, Azure",Bachelor,5,Telecommunications,2024-10-14,2024-11-15,635,9.7,TechCorp Inc +AI05166,Robotics Engineer,125641,USD,125641,SE,FL,Sweden,S,Vietnam,100,"PyTorch, Computer Vision, AWS, SQL, MLOps",Associate,5,Education,2024-11-09,2025-01-20,1422,8,Cognitive Computing +AI05167,Machine Learning Engineer,89881,CHF,80893,EN,CT,Switzerland,L,Australia,0,"Data Visualization, TensorFlow, Azure",Bachelor,1,Telecommunications,2024-12-14,2025-01-22,993,5.3,TechCorp Inc +AI05168,AI Consultant,289064,USD,289064,EX,FL,United States,L,United States,50,"R, SQL, Tableau, MLOps, Docker",Master,17,Education,2024-04-04,2024-05-13,581,6.2,Machine Intelligence Group +AI05169,AI Specialist,226888,USD,226888,EX,FT,Sweden,S,Denmark,0,"Java, SQL, Data Visualization, PyTorch, Computer Vision",Master,13,Technology,2024-09-15,2024-10-27,2487,8.4,Cloud AI Solutions +AI05170,Principal Data Scientist,153723,EUR,130665,EX,CT,Netherlands,M,Netherlands,50,"Statistics, Spark, Python",Associate,13,Retail,2024-12-28,2025-03-05,1731,8.8,DeepTech Ventures +AI05171,AI Research Scientist,220723,SGD,286940,EX,FT,Singapore,S,Canada,50,"Mathematics, Python, Tableau",Associate,13,Media,2024-02-29,2024-04-19,1833,8,Future Systems +AI05172,Data Analyst,93378,EUR,79371,MI,FT,France,L,South Africa,100,"Spark, GCP, Scala, Computer Vision, Deep Learning",Master,3,Gaming,2024-08-06,2024-08-21,1938,6,TechCorp Inc +AI05173,ML Ops Engineer,162034,GBP,121526,SE,FT,United Kingdom,L,United Kingdom,50,"SQL, TensorFlow, Data Visualization",PhD,5,Media,2024-07-28,2024-08-30,1441,10,Cloud AI Solutions +AI05174,Head of AI,117365,USD,117365,SE,PT,Ireland,S,Ireland,100,"Statistics, Data Visualization, Git",Bachelor,5,Retail,2024-07-25,2024-09-04,1472,7.2,Autonomous Tech +AI05175,Machine Learning Engineer,128624,USD,128624,MI,PT,Denmark,M,Denmark,50,"GCP, Java, Azure, Linux",Master,2,Consulting,2025-04-15,2025-05-24,527,8.9,Quantum Computing Inc +AI05176,Head of AI,112504,EUR,95628,SE,PT,France,M,Austria,50,"Deep Learning, Docker, Computer Vision, Azure, Kubernetes",Bachelor,9,Education,2024-02-16,2024-03-28,1791,5.2,Digital Transformation LLC +AI05177,Data Analyst,91750,USD,91750,MI,CT,Norway,S,Norway,0,"Mathematics, TensorFlow, Computer Vision",Master,4,Transportation,2025-02-08,2025-03-09,1374,10,Neural Networks Co +AI05178,Machine Learning Engineer,216192,USD,216192,EX,FT,South Korea,L,South Korea,100,"Hadoop, Spark, NLP, Computer Vision",Bachelor,15,Gaming,2024-03-03,2024-04-12,508,6.2,Advanced Robotics +AI05179,Principal Data Scientist,102086,USD,102086,SE,FT,Israel,S,Israel,50,"Scala, Java, Azure, Data Visualization, TensorFlow",Associate,5,Finance,2024-04-21,2024-06-10,1342,6.2,Machine Intelligence Group +AI05180,Machine Learning Engineer,150372,USD,150372,SE,PT,Israel,L,Israel,0,"Scala, R, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-08-12,2306,7,Algorithmic Solutions +AI05181,Data Analyst,132314,USD,132314,MI,FT,Norway,L,Turkey,100,"PyTorch, Scala, GCP, Mathematics",Bachelor,4,Automotive,2024-09-21,2024-10-14,1172,9.6,Cloud AI Solutions +AI05182,Data Analyst,103230,USD,103230,MI,PT,Sweden,M,Sweden,100,"Java, Scala, Kubernetes, NLP",Bachelor,2,Telecommunications,2024-03-27,2024-05-22,1418,9.9,Algorithmic Solutions +AI05183,AI Architect,120695,CAD,150869,SE,FL,Canada,L,Hungary,50,"GCP, NLP, Azure",Associate,8,Government,2024-08-16,2024-09-30,1328,5.8,Advanced Robotics +AI05184,Machine Learning Engineer,182121,USD,182121,EX,FT,Ireland,M,Austria,100,"Data Visualization, PyTorch, TensorFlow",Associate,19,Energy,2025-04-22,2025-05-07,2017,8.9,Neural Networks Co +AI05185,AI Architect,73616,CHF,66254,EN,PT,Switzerland,S,Argentina,100,"PyTorch, TensorFlow, Docker, Hadoop, Mathematics",PhD,0,Automotive,2024-03-06,2024-04-03,1044,9,Future Systems +AI05186,NLP Engineer,80112,USD,80112,EN,FT,Sweden,M,Denmark,50,"SQL, Python, Scala",Master,0,Telecommunications,2024-01-01,2024-02-06,2050,9.3,Algorithmic Solutions +AI05187,Data Scientist,95409,GBP,71557,MI,FL,United Kingdom,S,United Kingdom,100,"SQL, GCP, Computer Vision",Master,2,Automotive,2024-09-26,2024-11-25,1359,7.1,Predictive Systems +AI05188,NLP Engineer,120427,USD,120427,SE,FT,Israel,L,Israel,100,"Kubernetes, Spark, Java, TensorFlow, Statistics",Bachelor,5,Government,2024-08-12,2024-09-08,2168,9.9,Future Systems +AI05189,AI Research Scientist,38463,USD,38463,SE,CT,India,M,India,0,"Docker, Tableau, Java",Master,6,Gaming,2024-03-06,2024-05-09,2482,9.3,Algorithmic Solutions +AI05190,AI Software Engineer,38200,USD,38200,MI,FT,India,L,India,100,"PyTorch, Tableau, GCP",Bachelor,2,Media,2024-10-24,2024-12-03,1106,5.2,Smart Analytics +AI05191,Head of AI,74370,USD,74370,EN,CT,Ireland,M,Ireland,100,"Python, AWS, MLOps",Bachelor,0,Education,2025-01-10,2025-02-27,2007,9.1,Quantum Computing Inc +AI05192,AI Software Engineer,96885,EUR,82352,MI,FL,Germany,M,Germany,0,"R, Deep Learning, SQL, Statistics",Associate,3,Media,2024-01-17,2024-02-26,2017,5.8,Quantum Computing Inc +AI05193,AI Specialist,23564,USD,23564,EN,FL,India,M,Australia,0,"Linux, Python, Tableau, Hadoop",PhD,1,Healthcare,2025-04-19,2025-05-17,514,6.8,Neural Networks Co +AI05194,Machine Learning Engineer,135679,EUR,115327,SE,FL,Austria,M,Austria,50,"Python, Java, Computer Vision",Master,9,Media,2025-04-27,2025-06-17,1647,9.2,DeepTech Ventures +AI05195,ML Ops Engineer,85715,USD,85715,MI,CT,Finland,L,Ghana,100,"MLOps, Deep Learning, R",Master,2,Energy,2025-02-24,2025-05-03,2049,7.3,Digital Transformation LLC +AI05196,Machine Learning Researcher,127789,CAD,159736,SE,CT,Canada,S,Canada,100,"SQL, Python, NLP, Scala",PhD,6,Healthcare,2024-10-10,2024-12-14,1217,7.2,Algorithmic Solutions +AI05197,Data Engineer,186154,CHF,167539,SE,FT,Switzerland,S,Switzerland,100,"Statistics, Kubernetes, Linux",Bachelor,9,Energy,2025-01-08,2025-02-23,1306,7.4,Smart Analytics +AI05198,Research Scientist,202606,USD,202606,EX,CT,United States,L,United States,50,"Mathematics, TensorFlow, Linux, Docker, R",Master,17,Education,2024-10-15,2024-11-25,898,5.2,Machine Intelligence Group +AI05199,Data Engineer,80486,USD,80486,EX,FL,China,L,China,0,"Python, AWS, GCP, Java",Bachelor,13,Automotive,2024-08-24,2024-10-26,2297,8.4,Cloud AI Solutions +AI05200,Principal Data Scientist,23519,USD,23519,EN,FT,India,S,India,0,"Computer Vision, MLOps, Statistics",Bachelor,0,Real Estate,2024-04-23,2024-06-08,1217,7.9,DeepTech Ventures +AI05201,Head of AI,54022,CAD,67528,EN,CT,Canada,S,Colombia,50,"Spark, Tableau, Deep Learning, Python",Associate,0,Finance,2024-08-25,2024-10-09,1620,5.2,Future Systems +AI05202,Deep Learning Engineer,94661,USD,94661,MI,CT,South Korea,L,South Korea,0,"Spark, Python, Java, Linux",Bachelor,3,Transportation,2024-09-26,2024-10-30,1281,8.3,TechCorp Inc +AI05203,AI Architect,92817,JPY,10209870,EN,FL,Japan,L,Finland,50,"Scala, Git, GCP, Hadoop",Associate,0,Education,2024-01-19,2024-03-08,2205,8.7,Algorithmic Solutions +AI05204,AI Product Manager,183387,SGD,238403,EX,FL,Singapore,S,Singapore,50,"NLP, Tableau, Spark",Associate,14,Transportation,2024-04-28,2024-05-30,1925,5.2,Future Systems +AI05205,Research Scientist,39823,USD,39823,MI,FT,China,S,China,0,"R, Python, Kubernetes, GCP",Bachelor,3,Energy,2024-02-22,2024-04-06,1780,6.6,Quantum Computing Inc +AI05206,Principal Data Scientist,204455,USD,204455,EX,CT,Denmark,S,Denmark,50,"Java, Python, Data Visualization, Kubernetes",Associate,16,Gaming,2025-03-04,2025-03-29,1148,5.5,Autonomous Tech +AI05207,ML Ops Engineer,61232,USD,61232,SE,PT,China,L,Australia,100,"Spark, Azure, Computer Vision",Master,8,Education,2024-09-20,2024-11-17,544,7.3,Autonomous Tech +AI05208,Research Scientist,112367,EUR,95512,SE,FT,France,M,France,100,"Hadoop, Python, Linux, NLP",Bachelor,6,Manufacturing,2024-07-02,2024-08-26,547,6.7,Cognitive Computing +AI05209,Data Analyst,73735,EUR,62675,EN,FL,Germany,L,Germany,0,"Python, PyTorch, Java, Computer Vision",Master,1,Education,2024-06-08,2024-08-04,971,8.9,Autonomous Tech +AI05210,Robotics Engineer,294725,USD,294725,EX,FL,United States,M,United States,0,"Spark, PyTorch, NLP",PhD,11,Healthcare,2024-04-20,2024-05-16,1054,7.2,Autonomous Tech +AI05211,Data Analyst,242630,USD,242630,EX,CT,Denmark,M,Denmark,0,"Kubernetes, Python, Statistics, TensorFlow, Data Visualization",Bachelor,15,Consulting,2024-12-01,2024-12-26,2423,9,Quantum Computing Inc +AI05212,Data Engineer,86849,USD,86849,SE,FT,South Korea,S,South Korea,100,"Scala, Hadoop, Kubernetes, SQL",Associate,6,Education,2024-07-05,2024-08-24,1936,6.7,Cloud AI Solutions +AI05213,AI Specialist,48264,USD,48264,SE,FL,India,M,India,0,"Python, Deep Learning, TensorFlow, Docker",Bachelor,7,Media,2024-11-20,2025-01-24,1965,7.5,AI Innovations +AI05214,ML Ops Engineer,66226,JPY,7284860,EN,PT,Japan,S,Finland,0,"Python, Kubernetes, TensorFlow",Associate,1,Retail,2024-08-17,2024-10-28,584,8.5,Neural Networks Co +AI05215,AI Software Engineer,59484,USD,59484,EX,CT,India,S,France,0,"Linux, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-01-28,2024-02-26,528,6.2,TechCorp Inc +AI05216,AI Software Engineer,75033,GBP,56275,MI,FL,United Kingdom,S,United Kingdom,50,"Git, TensorFlow, Deep Learning",PhD,4,Manufacturing,2025-01-18,2025-02-05,1597,7.4,Cognitive Computing +AI05217,Principal Data Scientist,53070,USD,53070,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Java, GCP, Git",Master,1,Retail,2024-04-02,2024-06-14,2279,5.2,Algorithmic Solutions +AI05218,Autonomous Systems Engineer,80312,USD,80312,MI,PT,Ireland,S,Ireland,0,"Statistics, TensorFlow, Deep Learning, Kubernetes, Mathematics",Master,3,Automotive,2024-03-28,2024-05-26,1395,6.1,DataVision Ltd +AI05219,AI Research Scientist,61589,USD,61589,EN,PT,Finland,S,Finland,100,"Linux, Python, Docker, Deep Learning, MLOps",PhD,0,Education,2025-01-28,2025-04-09,682,7.7,DataVision Ltd +AI05220,Machine Learning Researcher,64464,USD,64464,EN,PT,South Korea,L,South Korea,50,"Kubernetes, Scala, Data Visualization",PhD,1,Retail,2024-02-29,2024-04-22,1904,8.9,Algorithmic Solutions +AI05221,Data Engineer,155127,CHF,139614,MI,PT,Switzerland,M,Switzerland,100,"AWS, Python, MLOps, TensorFlow, PyTorch",PhD,3,Transportation,2024-02-07,2024-03-24,644,6.3,DeepTech Ventures +AI05222,Research Scientist,218691,EUR,185887,EX,CT,Germany,S,Germany,100,"Linux, Statistics, Hadoop, Spark, MLOps",PhD,12,Technology,2024-01-23,2024-03-05,795,6,Future Systems +AI05223,Robotics Engineer,204587,CHF,184128,SE,PT,Switzerland,L,Switzerland,0,"Python, Computer Vision, TensorFlow, Linux",PhD,9,Telecommunications,2024-09-30,2024-10-20,1680,6.9,AI Innovations +AI05224,Robotics Engineer,113415,EUR,96403,SE,PT,Austria,S,Austria,0,"Kubernetes, Scala, Tableau, Mathematics, AWS",PhD,9,Telecommunications,2024-01-18,2024-02-22,2041,8.4,Smart Analytics +AI05225,AI Consultant,111108,USD,111108,SE,FT,South Korea,S,South Korea,0,"Linux, GCP, Mathematics, Computer Vision, MLOps",Associate,5,Automotive,2025-03-08,2025-04-14,2348,8.4,Advanced Robotics +AI05226,AI Product Manager,162371,GBP,121778,EX,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Azure, PyTorch",Associate,13,Consulting,2024-09-01,2024-11-13,2361,9.6,Smart Analytics +AI05227,Data Engineer,78542,USD,78542,EN,PT,Sweden,M,Sweden,100,"R, MLOps, SQL",Master,0,Technology,2024-07-25,2024-08-26,1736,9.6,Autonomous Tech +AI05228,Data Analyst,111272,CHF,100145,MI,CT,Switzerland,M,Italy,0,"R, Spark, Statistics, GCP",Master,2,Finance,2024-07-01,2024-08-04,584,6.6,Machine Intelligence Group +AI05229,Machine Learning Researcher,141413,USD,141413,SE,PT,United States,M,Nigeria,50,"PyTorch, NLP, Scala, GCP, Azure",Associate,9,Government,2025-01-01,2025-03-02,2468,8.9,Autonomous Tech +AI05230,Robotics Engineer,153448,USD,153448,MI,CT,Norway,L,Norway,0,"Scala, Java, MLOps",Associate,4,Telecommunications,2024-02-02,2024-02-24,1035,5.9,Predictive Systems +AI05231,AI Consultant,126522,EUR,107544,SE,CT,Austria,L,Austria,0,"Python, AWS, Data Visualization, Docker, Computer Vision",Bachelor,9,Government,2024-06-13,2024-08-08,1749,9.2,Autonomous Tech +AI05232,Data Analyst,75216,USD,75216,MI,PT,Finland,S,India,0,"Kubernetes, SQL, Scala, GCP, TensorFlow",Bachelor,2,Government,2025-03-04,2025-04-29,979,7,TechCorp Inc +AI05233,Data Analyst,157426,JPY,17316860,EX,FT,Japan,M,Ghana,0,"Deep Learning, Azure, Spark",Bachelor,19,Education,2024-05-10,2024-05-30,1193,5,TechCorp Inc +AI05234,Research Scientist,78696,USD,78696,EN,PT,United States,S,Sweden,0,"Azure, R, Git",Bachelor,1,Government,2024-10-04,2024-12-15,898,6.6,Digital Transformation LLC +AI05235,Robotics Engineer,113402,USD,113402,EX,CT,China,M,China,0,"SQL, Python, Git",Associate,18,Gaming,2025-03-27,2025-05-27,2353,6.1,Machine Intelligence Group +AI05236,Machine Learning Researcher,86790,CHF,78111,EN,CT,Switzerland,M,Switzerland,100,"Python, NLP, TensorFlow",Master,1,Real Estate,2024-11-12,2025-01-18,1071,9.3,DeepTech Ventures +AI05237,Machine Learning Researcher,85140,USD,85140,EN,PT,United States,S,Spain,100,"Git, Spark, Java, SQL, GCP",PhD,0,Education,2025-03-29,2025-05-18,2413,9.7,DataVision Ltd +AI05238,Robotics Engineer,80679,EUR,68577,EN,FT,Austria,L,Austria,100,"R, Git, Tableau",Bachelor,1,Telecommunications,2024-06-23,2024-08-14,1374,8.3,Cloud AI Solutions +AI05239,AI Specialist,207222,USD,207222,EX,CT,Ireland,S,Ireland,100,"Spark, GCP, Data Visualization, Kubernetes, Python",PhD,19,Finance,2024-09-07,2024-10-19,1846,5.3,Autonomous Tech +AI05240,Principal Data Scientist,121677,SGD,158180,MI,PT,Singapore,L,Singapore,50,"Python, R, SQL, Linux",Bachelor,3,Education,2024-03-18,2024-05-23,1099,8.9,Cloud AI Solutions +AI05241,AI Research Scientist,190049,USD,190049,EX,PT,Sweden,M,Sweden,100,"Statistics, Mathematics, Tableau",Master,18,Finance,2025-01-29,2025-03-21,1642,8.9,AI Innovations +AI05242,Data Engineer,77584,USD,77584,EN,PT,Norway,S,Malaysia,100,"Python, AWS, MLOps",Master,0,Government,2024-02-08,2024-04-04,2356,6.9,Future Systems +AI05243,AI Software Engineer,120788,USD,120788,EX,FT,Finland,S,Finland,50,"AWS, TensorFlow, Linux",Master,16,Consulting,2024-02-28,2024-05-05,1853,9.4,Autonomous Tech +AI05244,Deep Learning Engineer,46291,USD,46291,SE,CT,India,S,India,0,"Linux, Deep Learning, R",Bachelor,8,Telecommunications,2025-01-17,2025-03-07,1918,9.6,Quantum Computing Inc +AI05245,Computer Vision Engineer,74298,USD,74298,EN,PT,Israel,L,Israel,100,"Python, Computer Vision, TensorFlow, Linux, Statistics",Associate,0,Energy,2024-05-31,2024-07-12,2312,9.2,Cloud AI Solutions +AI05246,Machine Learning Researcher,166410,USD,166410,SE,FL,Denmark,S,Denmark,100,"Computer Vision, GCP, Scala, Statistics",Associate,7,Finance,2025-01-07,2025-03-06,1366,5.5,DeepTech Ventures +AI05247,Data Analyst,30796,USD,30796,EN,FL,China,S,China,0,"PyTorch, Hadoop, TensorFlow, Docker",PhD,0,Manufacturing,2024-09-30,2024-11-23,1747,5.9,Advanced Robotics +AI05248,Machine Learning Researcher,60780,USD,60780,EN,FT,Sweden,S,Sweden,0,"Azure, Tableau, Mathematics, Data Visualization, Python",PhD,1,Real Estate,2024-01-30,2024-03-11,546,7,AI Innovations +AI05249,Data Engineer,59678,USD,59678,EN,CT,South Korea,L,South Korea,0,"Azure, Kubernetes, Spark, Scala",Master,1,Retail,2024-02-03,2024-03-05,644,7.9,Neural Networks Co +AI05250,Principal Data Scientist,253960,USD,253960,EX,PT,Sweden,L,Sweden,100,"Linux, Git, R, SQL",Master,17,Healthcare,2024-10-24,2024-11-30,1172,6.9,DeepTech Ventures +AI05251,AI Specialist,87660,USD,87660,EN,CT,Sweden,L,Sweden,0,"Hadoop, TensorFlow, PyTorch, GCP, Linux",PhD,1,Energy,2024-07-05,2024-08-07,2016,5.3,DeepTech Ventures +AI05252,AI Architect,210655,USD,210655,EX,CT,Sweden,S,Sweden,50,"SQL, Spark, Tableau, AWS, Git",PhD,13,Automotive,2024-11-17,2025-01-18,1041,7.2,Neural Networks Co +AI05253,Principal Data Scientist,144360,USD,144360,SE,FL,Sweden,M,Sweden,50,"Kubernetes, Docker, Java",Master,9,Manufacturing,2024-04-18,2024-05-03,562,6.9,TechCorp Inc +AI05254,Computer Vision Engineer,57145,USD,57145,EN,FL,Israel,M,Austria,50,"Linux, R, SQL, PyTorch, Java",Associate,0,Retail,2024-02-29,2024-03-31,516,8,Cognitive Computing +AI05255,Computer Vision Engineer,196565,USD,196565,EX,FL,Denmark,S,Denmark,0,"Deep Learning, PyTorch, Linux",Associate,18,Government,2024-07-19,2024-09-08,1595,8.9,Cloud AI Solutions +AI05256,Computer Vision Engineer,78696,CHF,70826,EN,FL,Switzerland,S,Kenya,50,"Spark, Azure, Java, TensorFlow, Kubernetes",Bachelor,0,Real Estate,2024-04-13,2024-06-14,842,8.2,Quantum Computing Inc +AI05257,Autonomous Systems Engineer,69517,USD,69517,SE,PT,China,M,Thailand,50,"AWS, R, Tableau, Deep Learning",Bachelor,8,Healthcare,2025-03-26,2025-05-01,1621,9.5,Cognitive Computing +AI05258,Autonomous Systems Engineer,80960,USD,80960,MI,PT,Israel,S,Israel,50,"Kubernetes, Docker, Tableau, Java, NLP",Master,3,Healthcare,2024-12-31,2025-02-18,1893,9.3,Digital Transformation LLC +AI05259,Data Engineer,111422,EUR,94709,MI,CT,Germany,L,Germany,100,"Kubernetes, Docker, Java, R",PhD,2,Manufacturing,2024-06-15,2024-08-19,1824,5.3,DeepTech Ventures +AI05260,Robotics Engineer,112063,USD,112063,SE,CT,Israel,L,Israel,0,"Git, R, Computer Vision",Bachelor,9,Energy,2025-04-19,2025-06-13,1840,8.6,Machine Intelligence Group +AI05261,AI Architect,206889,USD,206889,EX,PT,United States,S,United States,100,"Scala, GCP, NLP, Python, Kubernetes",Bachelor,10,Telecommunications,2024-06-11,2024-08-11,979,6.2,Neural Networks Co +AI05262,Autonomous Systems Engineer,58383,EUR,49626,EN,CT,Austria,L,Austria,100,"Python, TensorFlow, Tableau, Data Visualization",Bachelor,0,Manufacturing,2024-05-11,2024-07-23,879,9.4,Machine Intelligence Group +AI05263,AI Consultant,176960,USD,176960,SE,CT,Denmark,S,Denmark,0,"Scala, Hadoop, SQL, Kubernetes, Azure",Master,7,Manufacturing,2024-06-14,2024-07-12,1584,5.3,Digital Transformation LLC +AI05264,Research Scientist,68995,EUR,58646,MI,FL,Austria,M,Netherlands,100,"R, Linux, Scala, SQL",Associate,4,Consulting,2025-04-24,2025-07-04,2408,9.5,AI Innovations +AI05265,ML Ops Engineer,130169,CAD,162711,SE,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Deep Learning",PhD,9,Transportation,2024-06-02,2024-08-02,747,8,DataVision Ltd +AI05266,Data Engineer,51950,USD,51950,SE,CT,China,S,China,0,"Java, Git, Kubernetes, Python",Bachelor,9,Government,2024-12-18,2025-02-26,1106,7.8,DataVision Ltd +AI05267,AI Software Engineer,95065,USD,95065,MI,FL,Norway,S,Norway,100,"Linux, Kubernetes, Scala, GCP, Statistics",Bachelor,2,Automotive,2024-02-12,2024-03-04,967,9.6,Quantum Computing Inc +AI05268,AI Product Manager,78158,USD,78158,EN,PT,Ireland,M,Ireland,50,"R, SQL, Scala, PyTorch",Associate,1,Education,2024-06-11,2024-07-27,571,8.1,Advanced Robotics +AI05269,AI Architect,156925,EUR,133386,EX,PT,Germany,L,Switzerland,0,"Git, Hadoop, SQL, Linux, Azure",Associate,14,Retail,2024-10-13,2024-12-17,1184,6.8,Machine Intelligence Group +AI05270,Machine Learning Engineer,57461,USD,57461,SE,PT,China,S,China,100,"Data Visualization, SQL, Tableau, Java, GCP",Bachelor,6,Real Estate,2024-05-15,2024-06-29,1779,5.4,Quantum Computing Inc +AI05271,AI Architect,178905,CHF,161015,MI,CT,Switzerland,L,Switzerland,100,"Java, Azure, SQL",Master,4,Telecommunications,2024-06-24,2024-08-11,1733,5.8,Cloud AI Solutions +AI05272,Deep Learning Engineer,72036,EUR,61231,MI,PT,France,M,France,50,"R, Scala, Java, Docker, Kubernetes",PhD,4,Government,2024-03-17,2024-04-28,2121,5.1,Cognitive Computing +AI05273,AI Software Engineer,28532,USD,28532,EN,CT,China,S,China,50,"Spark, Data Visualization, SQL",PhD,1,Energy,2025-01-14,2025-02-04,551,6.3,Smart Analytics +AI05274,Research Scientist,102165,USD,102165,MI,FL,Ireland,M,Australia,50,"SQL, Docker, Data Visualization, GCP",PhD,2,Consulting,2024-04-26,2024-07-03,907,6.1,Future Systems +AI05275,AI Specialist,54248,USD,54248,EN,FT,Sweden,M,Sweden,100,"SQL, Scala, Docker, Kubernetes, Computer Vision",PhD,0,Finance,2025-04-27,2025-06-05,1496,7.7,Cognitive Computing +AI05276,AI Architect,133384,USD,133384,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Scala, TensorFlow, Linux, Deep Learning",Associate,8,Automotive,2025-02-16,2025-03-08,1747,5.8,Digital Transformation LLC +AI05277,Head of AI,166944,JPY,18363840,SE,CT,Japan,L,Japan,0,"SQL, Git, Mathematics",PhD,9,Transportation,2024-12-14,2025-02-25,594,5.2,TechCorp Inc +AI05278,Data Engineer,72269,USD,72269,EN,PT,South Korea,L,Mexico,50,"GCP, Spark, Linux, Computer Vision",Bachelor,1,Technology,2024-05-14,2024-07-03,1113,6,Cloud AI Solutions +AI05279,AI Specialist,39537,USD,39537,SE,FT,India,M,Nigeria,50,"Git, AWS, MLOps, Data Visualization",Associate,5,Manufacturing,2024-07-12,2024-08-07,1801,9.6,Autonomous Tech +AI05280,AI Specialist,206054,USD,206054,EX,FT,Ireland,S,Nigeria,50,"Azure, Hadoop, TensorFlow",Bachelor,12,Manufacturing,2024-03-03,2024-03-19,1141,8.2,Cognitive Computing +AI05281,Autonomous Systems Engineer,94121,CAD,117651,SE,FL,Canada,S,Belgium,50,"Deep Learning, Docker, Scala, Tableau, TensorFlow",Associate,7,Transportation,2025-02-10,2025-02-24,2387,7.9,Advanced Robotics +AI05282,Deep Learning Engineer,110533,AUD,149220,SE,PT,Australia,M,Italy,0,"Linux, TensorFlow, Python",Master,7,Government,2025-01-13,2025-03-20,1907,7.1,Machine Intelligence Group +AI05283,Data Scientist,106010,CHF,95409,MI,CT,Switzerland,M,Switzerland,100,"PyTorch, Statistics, SQL, Deep Learning",PhD,3,Automotive,2024-11-22,2024-12-22,1805,8.2,Autonomous Tech +AI05284,AI Software Engineer,213187,EUR,181209,EX,CT,France,L,France,100,"Linux, Spark, MLOps",PhD,18,Real Estate,2025-01-29,2025-04-02,1803,7.3,Cognitive Computing +AI05285,Research Scientist,103681,USD,103681,EX,PT,China,L,China,100,"PyTorch, Hadoop, Scala, GCP",Associate,17,Gaming,2024-08-03,2024-09-04,2335,7.7,Cognitive Computing +AI05286,Deep Learning Engineer,350954,CHF,315859,EX,FT,Switzerland,L,Switzerland,50,"R, Statistics, PyTorch",PhD,18,Education,2024-09-03,2024-09-25,1159,5.3,Neural Networks Co +AI05287,Robotics Engineer,166456,USD,166456,SE,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Data Visualization, SQL, Statistics",Master,6,Government,2025-04-20,2025-05-26,747,8.1,TechCorp Inc +AI05288,Machine Learning Researcher,127694,USD,127694,SE,FT,Israel,M,Israel,100,"Java, Deep Learning, Statistics",Associate,5,Education,2024-07-27,2024-09-01,1919,9.3,TechCorp Inc +AI05289,AI Architect,44798,USD,44798,SE,CT,India,M,Norway,50,"PyTorch, Azure, Tableau, Spark",Bachelor,5,Technology,2025-01-25,2025-04-08,1375,9.5,Quantum Computing Inc +AI05290,Machine Learning Engineer,97713,USD,97713,MI,FL,Sweden,L,Germany,100,"R, Python, Deep Learning, Computer Vision, Mathematics",Bachelor,2,Gaming,2024-04-15,2024-06-18,2136,8.7,Future Systems +AI05291,AI Research Scientist,104377,EUR,88720,MI,CT,Netherlands,S,Vietnam,50,"Python, Data Visualization, TensorFlow",Master,3,Media,2024-10-28,2024-12-08,1813,6.8,Cloud AI Solutions +AI05292,AI Architect,50775,CAD,63469,EN,FL,Canada,S,Canada,50,"Mathematics, PyTorch, GCP",Master,1,Transportation,2025-04-03,2025-05-06,1795,6.7,Quantum Computing Inc +AI05293,NLP Engineer,212513,USD,212513,EX,FL,South Korea,L,India,50,"Python, AWS, Tableau",Associate,10,Technology,2024-06-28,2024-08-27,2002,7.1,DataVision Ltd +AI05294,Robotics Engineer,33907,USD,33907,MI,PT,India,S,Colombia,100,"MLOps, R, Docker",Bachelor,2,Education,2024-10-13,2024-12-02,1146,8.3,Future Systems +AI05295,AI Specialist,130049,AUD,175566,SE,FT,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch, AWS",Master,6,Consulting,2024-05-28,2024-07-26,1484,8,TechCorp Inc +AI05296,Research Scientist,214956,USD,214956,EX,FT,Norway,S,Thailand,50,"AWS, PyTorch, GCP, Statistics",Master,13,Energy,2025-01-05,2025-01-26,1776,9.6,Smart Analytics +AI05297,Data Scientist,131854,USD,131854,SE,CT,United States,M,United States,100,"Data Visualization, MLOps, Tableau, PyTorch",Associate,9,Manufacturing,2025-01-27,2025-04-02,533,9.5,DataVision Ltd +AI05298,Computer Vision Engineer,71723,JPY,7889530,EN,FT,Japan,L,Japan,100,"Computer Vision, NLP, Spark, GCP",Master,0,Technology,2024-09-02,2024-09-19,666,5.5,Digital Transformation LLC +AI05299,Principal Data Scientist,96917,USD,96917,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Git, Hadoop, PyTorch",Master,8,Transportation,2024-12-18,2025-01-28,1627,5.8,DataVision Ltd +AI05300,AI Product Manager,74302,USD,74302,MI,PT,South Korea,L,South Korea,100,"R, Python, Git",PhD,3,Finance,2025-04-24,2025-05-25,752,8.7,Machine Intelligence Group +AI05301,Computer Vision Engineer,284665,USD,284665,EX,CT,Denmark,M,France,50,"Data Visualization, Java, Scala, MLOps",Bachelor,14,Automotive,2024-06-22,2024-07-09,2464,7.9,Neural Networks Co +AI05302,AI Architect,83787,EUR,71219,MI,PT,France,S,France,0,"SQL, R, AWS, Deep Learning, Hadoop",PhD,3,Healthcare,2024-10-12,2024-11-17,2212,8,Future Systems +AI05303,Machine Learning Engineer,85475,GBP,64106,MI,CT,United Kingdom,M,Mexico,100,"Tableau, GCP, NLP, Spark, Java",PhD,2,Healthcare,2024-05-12,2024-07-13,536,8.5,DataVision Ltd +AI05304,Principal Data Scientist,173819,EUR,147746,EX,PT,Austria,S,Austria,100,"Kubernetes, Statistics, PyTorch, GCP, Linux",Master,14,Education,2024-12-08,2025-02-19,2412,9,Quantum Computing Inc +AI05305,Data Scientist,94067,EUR,79957,MI,PT,Germany,M,Germany,50,"NLP, R, Tableau, Docker, AWS",PhD,4,Healthcare,2025-02-13,2025-03-10,1782,6.6,Cognitive Computing +AI05306,AI Consultant,301786,JPY,33196460,EX,FL,Japan,L,Japan,0,"Deep Learning, Git, Scala, Python",PhD,11,Retail,2025-04-03,2025-04-18,902,9.6,Neural Networks Co +AI05307,AI Research Scientist,86235,EUR,73300,EN,CT,Netherlands,L,Netherlands,100,"SQL, Kubernetes, PyTorch",Associate,1,Retail,2024-02-15,2024-03-04,1324,8.2,DeepTech Ventures +AI05308,Head of AI,165965,USD,165965,EX,FT,Israel,S,Israel,0,"TensorFlow, Azure, Linux",Associate,12,Government,2024-03-01,2024-04-19,1525,5.6,Smart Analytics +AI05309,Machine Learning Engineer,85823,USD,85823,EN,CT,Denmark,M,Denmark,100,"PyTorch, Azure, Data Visualization",Associate,1,Education,2024-07-30,2024-10-08,1458,6.7,Smart Analytics +AI05310,AI Software Engineer,85037,USD,85037,EX,FL,China,L,China,0,"Mathematics, Hadoop, Data Visualization",Bachelor,16,Retail,2024-12-03,2025-01-16,1818,7.9,AI Innovations +AI05311,AI Research Scientist,61149,USD,61149,MI,PT,South Korea,M,Germany,0,"SQL, Kubernetes, PyTorch",Bachelor,2,Media,2024-03-25,2024-06-05,1921,9.4,Advanced Robotics +AI05312,AI Specialist,92493,CAD,115616,MI,CT,Canada,L,Canada,50,"Linux, PyTorch, Git",PhD,3,Consulting,2024-08-13,2024-09-12,1208,7.6,AI Innovations +AI05313,Principal Data Scientist,114033,JPY,12543630,MI,FT,Japan,L,Japan,100,"Tableau, R, MLOps",PhD,4,Automotive,2025-01-24,2025-03-31,1016,7.8,Predictive Systems +AI05314,NLP Engineer,53893,EUR,45809,EN,CT,Germany,S,United Kingdom,0,"Python, Spark, Hadoop",Bachelor,1,Gaming,2024-02-20,2024-03-07,2172,7.6,Machine Intelligence Group +AI05315,ML Ops Engineer,84318,USD,84318,EN,PT,Finland,L,Romania,100,"TensorFlow, Computer Vision, Tableau",PhD,1,Automotive,2024-11-02,2024-12-09,785,7.4,TechCorp Inc +AI05316,Deep Learning Engineer,102359,CAD,127949,SE,CT,Canada,S,Canada,50,"GCP, R, Git, Kubernetes",Bachelor,9,Education,2025-04-24,2025-05-27,1201,7.1,Quantum Computing Inc +AI05317,Data Analyst,37425,USD,37425,EN,CT,China,M,China,100,"SQL, R, Tableau, Azure, PyTorch",Master,1,Manufacturing,2024-04-03,2024-06-08,1464,9.5,Advanced Robotics +AI05318,AI Specialist,78231,USD,78231,EN,CT,Denmark,M,Thailand,100,"Deep Learning, GCP, Python, Data Visualization, Docker",Bachelor,0,Manufacturing,2024-06-01,2024-07-06,2337,5.8,Algorithmic Solutions +AI05319,Machine Learning Engineer,62558,EUR,53174,EN,CT,Netherlands,M,Norway,50,"R, SQL, AWS, MLOps, Docker",Master,1,Transportation,2025-03-30,2025-04-20,2055,7.8,Future Systems +AI05320,Deep Learning Engineer,123579,CAD,154474,SE,FL,Canada,L,Canada,0,"Hadoop, Tableau, GCP, Deep Learning",PhD,5,Technology,2024-10-24,2024-12-15,785,9.3,TechCorp Inc +AI05321,Deep Learning Engineer,83741,CAD,104676,MI,FL,Canada,M,Canada,100,"NLP, Docker, Git",Master,3,Automotive,2025-03-04,2025-05-06,2180,5.3,Quantum Computing Inc +AI05322,Principal Data Scientist,103613,USD,103613,SE,PT,Sweden,S,Spain,50,"Linux, TensorFlow, Hadoop, Computer Vision, Tableau",PhD,7,Automotive,2024-01-10,2024-02-11,1225,10,Algorithmic Solutions +AI05323,Deep Learning Engineer,122345,USD,122345,SE,FT,Israel,S,Israel,0,"SQL, Python, TensorFlow, Git, PyTorch",Associate,9,Manufacturing,2024-02-20,2024-04-15,563,8.7,Autonomous Tech +AI05324,AI Software Engineer,125817,CHF,113235,EN,FT,Switzerland,L,Singapore,0,"Tableau, Scala, Python",Associate,0,Finance,2024-06-25,2024-07-12,2037,6.9,Neural Networks Co +AI05325,AI Research Scientist,83848,USD,83848,MI,CT,Sweden,S,Nigeria,50,"Python, Git, TensorFlow, Deep Learning",Bachelor,2,Media,2024-04-21,2024-07-01,1561,8.1,Predictive Systems +AI05326,Data Analyst,126646,EUR,107649,SE,FT,Netherlands,L,Netherlands,100,"Hadoop, Spark, Linux",Associate,5,Manufacturing,2024-03-20,2024-04-09,2308,7.6,DataVision Ltd +AI05327,AI Product Manager,216544,USD,216544,EX,FT,United States,M,United States,100,"Kubernetes, SQL, Azure, Linux, PyTorch",Associate,14,Transportation,2024-07-25,2024-09-23,1367,5.1,Cloud AI Solutions +AI05328,AI Research Scientist,254248,EUR,216111,EX,FL,Austria,L,Austria,50,"R, Docker, Data Visualization, MLOps, Spark",PhD,13,Automotive,2024-11-17,2025-01-29,2380,8,Machine Intelligence Group +AI05329,Deep Learning Engineer,238603,GBP,178952,EX,FT,United Kingdom,L,United Kingdom,0,"R, Hadoop, SQL, Azure, Tableau",Bachelor,16,Energy,2024-05-10,2024-05-25,1566,8.9,Cloud AI Solutions +AI05330,NLP Engineer,71862,USD,71862,EN,FT,Sweden,M,Austria,50,"SQL, PyTorch, MLOps, NLP, GCP",PhD,1,Automotive,2024-12-15,2025-01-10,2276,9.3,Autonomous Tech +AI05331,Autonomous Systems Engineer,43525,USD,43525,SE,CT,China,S,Philippines,50,"Python, SQL, R, Git, TensorFlow",Master,6,Gaming,2024-09-23,2024-10-19,2248,7.1,Smart Analytics +AI05332,Computer Vision Engineer,133643,EUR,113597,SE,FL,Austria,L,Austria,0,"Python, MLOps, Kubernetes",Associate,5,Healthcare,2025-02-05,2025-03-08,1300,7,Digital Transformation LLC +AI05333,Machine Learning Researcher,209974,SGD,272966,EX,PT,Singapore,S,Singapore,0,"Python, GCP, Scala, SQL",Master,18,Consulting,2024-10-27,2024-11-24,2148,10,Quantum Computing Inc +AI05334,AI Consultant,188802,CAD,236003,EX,FT,Canada,L,Austria,50,"Kubernetes, NLP, PyTorch, Git",Bachelor,14,Automotive,2024-02-27,2024-04-15,1309,8.3,Machine Intelligence Group +AI05335,ML Ops Engineer,109423,USD,109423,MI,FT,Norway,S,Czech Republic,0,"Java, Linux, Computer Vision",Associate,4,Telecommunications,2025-01-05,2025-01-19,1573,5.2,Digital Transformation LLC +AI05336,Data Scientist,193402,SGD,251423,EX,CT,Singapore,L,Singapore,0,"Hadoop, Python, Kubernetes",Bachelor,13,Healthcare,2024-08-27,2024-09-23,1658,8.9,TechCorp Inc +AI05337,Deep Learning Engineer,68104,EUR,57888,EN,FL,France,L,France,100,"Scala, Docker, Mathematics, Spark",PhD,0,Real Estate,2025-01-01,2025-02-23,2350,5.2,Future Systems +AI05338,AI Consultant,115997,USD,115997,MI,FT,United States,M,United States,0,"Linux, Scala, Mathematics, GCP, Deep Learning",Bachelor,4,Gaming,2024-06-27,2024-07-13,2145,8.7,DataVision Ltd +AI05339,AI Specialist,87942,USD,87942,MI,FT,South Korea,M,New Zealand,50,"R, MLOps, SQL, AWS, Scala",PhD,4,Education,2024-03-10,2024-03-27,1259,6.9,Autonomous Tech +AI05340,Machine Learning Engineer,303218,USD,303218,EX,CT,Denmark,L,Denmark,50,"R, Git, Scala",PhD,18,Government,2024-12-15,2025-02-02,1087,9.7,DataVision Ltd +AI05341,Research Scientist,63427,USD,63427,MI,CT,South Korea,S,South Korea,100,"Spark, Hadoop, R",Bachelor,2,Finance,2024-04-14,2024-05-25,952,7.2,Machine Intelligence Group +AI05342,Principal Data Scientist,148375,GBP,111281,SE,FT,United Kingdom,L,United Kingdom,0,"Mathematics, Python, Linux, Hadoop, TensorFlow",Bachelor,6,Education,2025-02-24,2025-04-29,609,7.3,Machine Intelligence Group +AI05343,Machine Learning Researcher,91410,CAD,114263,MI,FL,Canada,M,Canada,0,"GCP, Python, Spark",PhD,2,Transportation,2024-02-11,2024-04-24,1107,5.9,AI Innovations +AI05344,Data Engineer,217295,USD,217295,EX,FL,United States,L,United States,50,"TensorFlow, Java, Scala",Associate,14,Education,2024-01-27,2024-02-23,1243,9.1,Future Systems +AI05345,AI Consultant,65815,AUD,88850,EN,PT,Australia,L,Kenya,50,"Scala, AWS, Git, Computer Vision, Azure",Bachelor,0,Consulting,2025-04-07,2025-05-17,2254,5.6,TechCorp Inc +AI05346,Research Scientist,185973,SGD,241765,EX,CT,Singapore,S,Singapore,0,"NLP, Deep Learning, Git",Associate,13,Real Estate,2025-04-29,2025-06-08,940,5.5,DeepTech Ventures +AI05347,Principal Data Scientist,113175,USD,113175,SE,PT,Finland,S,Finland,100,"TensorFlow, Deep Learning, PyTorch, MLOps, Hadoop",Master,7,Government,2024-08-28,2024-10-29,722,8.4,DeepTech Ventures +AI05348,Deep Learning Engineer,198579,USD,198579,EX,FT,Denmark,S,Denmark,50,"Data Visualization, Docker, Spark, Python, Java",Master,14,Healthcare,2025-03-29,2025-06-08,1705,8.2,Smart Analytics +AI05349,Machine Learning Researcher,25817,USD,25817,EN,CT,India,M,India,0,"MLOps, Scala, Linux, Azure",Bachelor,0,Media,2025-04-08,2025-04-23,1618,7.7,DeepTech Ventures +AI05350,Head of AI,81249,USD,81249,MI,CT,Sweden,M,Ukraine,50,"Computer Vision, R, GCP",Associate,3,Manufacturing,2024-04-08,2024-06-07,1936,9.5,Autonomous Tech +AI05351,Data Analyst,107111,AUD,144600,SE,CT,Australia,S,Australia,100,"Python, Docker, Linux, Statistics, GCP",Associate,7,Finance,2024-06-22,2024-09-01,671,5,Digital Transformation LLC +AI05352,AI Software Engineer,158552,USD,158552,SE,CT,Norway,M,United Kingdom,0,"Git, Python, GCP",Bachelor,7,Technology,2024-11-25,2025-01-14,2214,7.6,TechCorp Inc +AI05353,Autonomous Systems Engineer,209929,USD,209929,EX,CT,United States,M,United States,0,"Azure, Python, Spark, GCP",PhD,14,Transportation,2024-11-24,2025-02-01,1931,5.2,DeepTech Ventures +AI05354,AI Research Scientist,288133,GBP,216100,EX,CT,United Kingdom,L,United Kingdom,0,"Scala, Data Visualization, AWS, Computer Vision",Master,13,Real Estate,2025-02-02,2025-03-05,1068,8.8,Advanced Robotics +AI05355,Head of AI,243777,JPY,26815470,EX,FT,Japan,M,Japan,50,"Mathematics, R, NLP, Linux, SQL",Bachelor,13,Gaming,2025-01-29,2025-02-24,2295,7.8,Digital Transformation LLC +AI05356,Data Engineer,54043,AUD,72958,EN,FT,Australia,M,Germany,50,"Kubernetes, Deep Learning, Git, Hadoop",Associate,0,Manufacturing,2024-02-20,2024-03-05,855,9.4,Cognitive Computing +AI05357,Data Analyst,82069,USD,82069,MI,FL,Ireland,M,Ireland,100,"MLOps, PyTorch, TensorFlow",Associate,3,Retail,2025-01-27,2025-02-28,1505,9.7,Advanced Robotics +AI05358,ML Ops Engineer,65179,USD,65179,MI,CT,Ireland,S,Ireland,50,"SQL, Hadoop, Tableau",PhD,3,Telecommunications,2024-03-09,2024-04-08,2284,5.1,Future Systems +AI05359,AI Specialist,162962,USD,162962,SE,PT,Sweden,L,Poland,0,"Spark, Scala, PyTorch, NLP, GCP",Bachelor,8,Healthcare,2025-02-14,2025-04-26,1367,5.9,Smart Analytics +AI05360,AI Specialist,91928,USD,91928,EX,FT,China,L,China,50,"PyTorch, Scala, Tableau, Linux, NLP",Master,10,Government,2025-04-12,2025-05-07,1517,6.3,DeepTech Ventures +AI05361,AI Architect,134846,USD,134846,SE,PT,United States,M,United States,100,"PyTorch, Git, MLOps, SQL, Java",Master,6,Retail,2024-08-29,2024-09-13,1153,9.9,DataVision Ltd +AI05362,Data Analyst,22186,USD,22186,EN,PT,India,L,Spain,0,"Computer Vision, TensorFlow, NLP, SQL, Mathematics",Bachelor,1,Retail,2024-04-13,2024-06-15,512,8,Quantum Computing Inc +AI05363,Research Scientist,61335,USD,61335,SE,PT,China,L,China,0,"Java, PyTorch, Statistics",Associate,9,Retail,2024-03-05,2024-03-26,733,8.9,TechCorp Inc +AI05364,AI Specialist,246778,EUR,209761,EX,FT,Germany,L,New Zealand,100,"Kubernetes, PyTorch, NLP, TensorFlow",Master,15,Gaming,2025-01-20,2025-03-28,506,5.1,Quantum Computing Inc +AI05365,AI Architect,104343,GBP,78257,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Data Visualization, Java, GCP",Master,3,Retail,2024-05-21,2024-08-01,812,7.3,Autonomous Tech +AI05366,AI Architect,130307,USD,130307,MI,PT,Denmark,L,Denmark,50,"Linux, AWS, Java",PhD,2,Telecommunications,2024-08-05,2024-10-08,1924,6.6,DeepTech Ventures +AI05367,Computer Vision Engineer,83046,USD,83046,EN,FL,Norway,S,Norway,50,"SQL, Linux, Git, PyTorch, Deep Learning",Master,0,Retail,2025-03-05,2025-05-15,2443,6.4,Digital Transformation LLC +AI05368,AI Specialist,157446,USD,157446,MI,PT,Norway,L,Norway,100,"MLOps, Python, Tableau, Kubernetes, Data Visualization",Master,3,Healthcare,2024-08-29,2024-10-25,1804,5.7,Cognitive Computing +AI05369,Machine Learning Researcher,297092,JPY,32680120,EX,FL,Japan,L,Japan,0,"Spark, GCP, Python, Mathematics",Associate,16,Finance,2024-08-07,2024-10-07,989,8.6,Future Systems +AI05370,AI Product Manager,68384,USD,68384,MI,CT,Finland,S,Finland,100,"Python, Linux, MLOps, Kubernetes, TensorFlow",Master,2,Transportation,2025-01-17,2025-03-14,1050,6.4,DataVision Ltd +AI05371,ML Ops Engineer,92089,USD,92089,EX,FL,India,L,India,50,"Docker, Hadoop, SQL, Azure, Java",PhD,17,Automotive,2024-08-13,2024-09-04,764,6,Neural Networks Co +AI05372,Deep Learning Engineer,136227,EUR,115793,SE,FT,Netherlands,L,Netherlands,0,"Statistics, Scala, Deep Learning",PhD,6,Healthcare,2024-01-01,2024-02-29,1685,9.2,Neural Networks Co +AI05373,AI Product Manager,129513,USD,129513,SE,PT,Ireland,M,Australia,100,"Python, Docker, Mathematics",PhD,7,Government,2024-10-18,2024-11-29,1009,7.8,Cloud AI Solutions +AI05374,AI Specialist,135626,USD,135626,SE,PT,Israel,M,Vietnam,50,"Scala, Hadoop, Computer Vision, Deep Learning",PhD,7,Manufacturing,2025-03-27,2025-06-08,1852,8,Advanced Robotics +AI05375,AI Specialist,43215,USD,43215,SE,FL,China,S,Hungary,50,"PyTorch, Python, Linux",Master,9,Energy,2024-08-16,2024-10-05,714,8.1,Smart Analytics +AI05376,AI Research Scientist,70887,EUR,60254,MI,FT,Germany,S,Germany,50,"Python, Java, AWS, Scala, SQL",Associate,4,Retail,2025-02-15,2025-04-17,610,5.4,Smart Analytics +AI05377,ML Ops Engineer,288695,CHF,259826,EX,PT,Switzerland,L,Switzerland,0,"Spark, Linux, Statistics, Mathematics",Master,16,Transportation,2024-03-12,2024-05-19,1570,6,TechCorp Inc +AI05378,Data Engineer,85081,CHF,76573,EN,FT,Switzerland,S,Nigeria,50,"Java, PyTorch, AWS",PhD,1,Energy,2025-03-16,2025-05-10,1736,5.3,Advanced Robotics +AI05379,NLP Engineer,111446,USD,111446,MI,CT,Israel,L,Israel,100,"Spark, MLOps, Scala, AWS",Master,4,Energy,2024-06-17,2024-07-13,513,7.5,Predictive Systems +AI05380,Data Analyst,66898,USD,66898,MI,CT,Israel,S,Israel,50,"Git, Spark, R, PyTorch",Master,3,Gaming,2024-12-01,2025-01-02,1269,6.9,Predictive Systems +AI05381,AI Product Manager,37660,USD,37660,EN,FL,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-07-28,2024-09-17,835,8.5,Neural Networks Co +AI05382,Autonomous Systems Engineer,79062,EUR,67203,EN,PT,Netherlands,L,Finland,50,"NLP, SQL, TensorFlow, Scala, PyTorch",Master,0,Healthcare,2024-07-06,2024-08-07,2128,9.7,Predictive Systems +AI05383,Deep Learning Engineer,125125,SGD,162663,MI,PT,Singapore,L,Singapore,0,"Java, Git, Tableau, Scala",PhD,4,Healthcare,2024-03-03,2024-04-17,1935,6,Advanced Robotics +AI05384,Research Scientist,137554,JPY,15130940,SE,FT,Japan,M,Japan,0,"Data Visualization, Kubernetes, Computer Vision",Bachelor,8,Transportation,2024-09-23,2024-11-04,812,6.2,DeepTech Ventures +AI05385,AI Specialist,95923,EUR,81535,MI,FT,France,M,France,0,"NLP, Git, Mathematics",Associate,2,Transportation,2024-11-03,2024-11-21,667,9.2,DeepTech Ventures +AI05386,Autonomous Systems Engineer,126145,GBP,94609,SE,PT,United Kingdom,L,United Kingdom,50,"Git, Mathematics, NLP",PhD,7,Media,2024-01-15,2024-02-29,1112,6.3,Machine Intelligence Group +AI05387,Principal Data Scientist,98692,USD,98692,SE,PT,Ireland,S,Ireland,0,"Deep Learning, Scala, Computer Vision",Bachelor,5,Gaming,2025-02-02,2025-04-09,1354,6.7,Algorithmic Solutions +AI05388,Head of AI,200999,EUR,170849,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Computer Vision, PyTorch, Git",Master,16,Consulting,2025-03-29,2025-04-29,1230,6.6,Future Systems +AI05389,Head of AI,54737,GBP,41053,EN,CT,United Kingdom,M,South Africa,50,"Python, Kubernetes, Scala",Associate,1,Telecommunications,2024-12-10,2025-01-01,2060,9.6,Quantum Computing Inc +AI05390,Machine Learning Engineer,202067,SGD,262687,EX,FT,Singapore,M,Brazil,100,"R, Scala, Python",Associate,18,Technology,2024-09-02,2024-09-17,2350,7.9,Neural Networks Co +AI05391,AI Research Scientist,247645,CAD,309556,EX,PT,Canada,L,Canada,100,"R, Mathematics, Python, Statistics",Associate,12,Gaming,2024-06-08,2024-07-02,935,8,Future Systems +AI05392,Data Engineer,136820,GBP,102615,SE,PT,United Kingdom,L,United Kingdom,100,"TensorFlow, Tableau, Computer Vision, Scala",Master,9,Real Estate,2025-03-27,2025-05-27,1477,6.5,Machine Intelligence Group +AI05393,Robotics Engineer,118345,USD,118345,EX,PT,Israel,S,Israel,0,"MLOps, Data Visualization, Linux, Docker, GCP",Associate,15,Media,2024-02-13,2024-04-18,1177,9.5,Neural Networks Co +AI05394,Computer Vision Engineer,86939,JPY,9563290,EN,CT,Japan,L,Japan,100,"Kubernetes, R, Hadoop, SQL, Deep Learning",PhD,1,Automotive,2024-08-14,2024-09-28,1232,7.2,Digital Transformation LLC +AI05395,Research Scientist,85462,JPY,9400820,EN,PT,Japan,M,Japan,100,"Kubernetes, Docker, NLP, Statistics, GCP",Associate,0,Government,2025-02-25,2025-04-11,1813,6.4,Algorithmic Solutions +AI05396,AI Research Scientist,75148,CHF,67633,EN,FL,Switzerland,M,Colombia,0,"NLP, Java, Kubernetes, Git",Master,1,Gaming,2025-01-14,2025-02-08,1792,10,Machine Intelligence Group +AI05397,Principal Data Scientist,253163,USD,253163,EX,FL,Denmark,L,Denmark,50,"TensorFlow, Git, Data Visualization",PhD,19,Real Estate,2024-06-06,2024-08-16,1330,5.2,TechCorp Inc +AI05398,AI Architect,30114,USD,30114,EN,FL,China,L,Finland,100,"Statistics, PyTorch, Java, Azure, TensorFlow",Master,1,Telecommunications,2024-11-16,2025-01-19,2090,8,Smart Analytics +AI05399,Computer Vision Engineer,176415,USD,176415,EX,CT,Finland,M,Finland,0,"GCP, NLP, Deep Learning, Spark",PhD,12,Telecommunications,2025-02-20,2025-04-21,1544,8.9,TechCorp Inc +AI05400,AI Specialist,73489,EUR,62466,MI,FT,Germany,M,Germany,50,"SQL, Java, Spark, TensorFlow, R",Associate,4,Automotive,2024-06-02,2024-07-03,2185,8.2,TechCorp Inc +AI05401,ML Ops Engineer,115294,USD,115294,SE,FT,Finland,M,Canada,100,"Azure, MLOps, Scala",Master,7,Real Estate,2024-03-21,2024-04-21,1538,7.8,Neural Networks Co +AI05402,Data Engineer,74479,SGD,96823,EN,FL,Singapore,L,Singapore,100,"SQL, Python, Statistics, Git",Associate,0,Gaming,2024-11-10,2024-12-01,1859,7.7,Smart Analytics +AI05403,AI Software Engineer,97495,USD,97495,SE,FT,Sweden,S,Sweden,0,"Spark, Git, Scala, Computer Vision",Associate,8,Government,2024-09-29,2024-11-25,899,6.9,DeepTech Ventures +AI05404,Principal Data Scientist,63891,USD,63891,EN,FL,Norway,S,Norway,100,"MLOps, SQL, Scala, GCP, Python",Associate,0,Manufacturing,2024-05-15,2024-06-09,1557,6.1,Smart Analytics +AI05405,Data Analyst,49339,CAD,61674,EN,PT,Canada,S,Canada,50,"Kubernetes, MLOps, Git, NLP, Scala",Master,1,Transportation,2024-05-21,2024-06-05,1652,6.6,Advanced Robotics +AI05406,Autonomous Systems Engineer,114592,USD,114592,EX,FL,China,L,Estonia,0,"Scala, NLP, Kubernetes",Master,12,Media,2024-04-14,2024-06-26,967,5.2,DataVision Ltd +AI05407,Data Scientist,44734,USD,44734,SE,FT,India,M,India,50,"NLP, MLOps, Scala, Python, Java",Master,6,Media,2024-11-01,2024-12-12,2496,7.7,Predictive Systems +AI05408,AI Architect,191311,USD,191311,EX,FL,Israel,S,Israel,50,"SQL, Kubernetes, GCP",Master,14,Consulting,2025-03-28,2025-04-21,873,8.3,Predictive Systems +AI05409,Data Engineer,198417,USD,198417,EX,FT,Finland,L,Switzerland,0,"Statistics, Kubernetes, Spark, R",Bachelor,16,Consulting,2024-05-20,2024-07-21,2466,9,Quantum Computing Inc +AI05410,AI Specialist,104925,JPY,11541750,SE,PT,Japan,S,Nigeria,0,"Git, MLOps, Scala, Python",Master,6,Media,2024-04-10,2024-05-05,2391,7.8,Neural Networks Co +AI05411,Research Scientist,221209,EUR,188028,EX,FT,Austria,L,Austria,0,"PyTorch, Data Visualization, MLOps",Bachelor,12,Technology,2024-02-28,2024-04-13,1267,8.2,TechCorp Inc +AI05412,NLP Engineer,85694,EUR,72840,MI,FT,Austria,S,Austria,0,"PyTorch, TensorFlow, MLOps, Hadoop, Python",PhD,3,Technology,2025-02-15,2025-04-14,1832,8.5,Neural Networks Co +AI05413,Research Scientist,148534,USD,148534,SE,FT,United States,S,United States,0,"R, Scala, SQL, Azure",PhD,9,Energy,2024-11-06,2025-01-16,1625,5.3,Neural Networks Co +AI05414,Machine Learning Engineer,79799,USD,79799,MI,FT,Israel,L,Israel,0,"Mathematics, AWS, NLP, PyTorch",Master,2,Manufacturing,2024-02-27,2024-04-09,1588,5.1,DataVision Ltd +AI05415,Robotics Engineer,42345,USD,42345,MI,PT,China,S,China,100,"Python, TensorFlow, Deep Learning, Tableau, Azure",Associate,4,Media,2024-06-02,2024-07-11,1265,9.9,Quantum Computing Inc +AI05416,Deep Learning Engineer,120846,CHF,108761,MI,CT,Switzerland,L,Egypt,50,"PyTorch, Java, TensorFlow, Docker",Master,3,Telecommunications,2024-06-09,2024-08-03,1725,6,Algorithmic Solutions +AI05417,AI Specialist,23612,USD,23612,EN,FL,India,S,Thailand,50,"SQL, Kubernetes, Tableau, Git",Associate,1,Gaming,2024-08-18,2024-09-06,2269,8,Autonomous Tech +AI05418,Deep Learning Engineer,166613,GBP,124960,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, Tableau, PyTorch, Data Visualization",Master,12,Technology,2024-06-03,2024-06-28,1513,9.9,Machine Intelligence Group +AI05419,Principal Data Scientist,56615,AUD,76430,EN,CT,Australia,M,Australia,100,"Spark, Statistics, Computer Vision, Python, MLOps",PhD,0,Telecommunications,2025-04-20,2025-06-26,1809,5.8,Algorithmic Solutions +AI05420,AI Specialist,78519,AUD,106001,MI,FT,Australia,M,Australia,100,"TensorFlow, Kubernetes, Computer Vision, Docker",PhD,4,Consulting,2024-04-30,2024-06-08,1672,6,DeepTech Ventures +AI05421,Data Engineer,176102,CAD,220128,EX,FT,Canada,S,Canada,50,"Kubernetes, Docker, AWS",PhD,11,Media,2025-01-11,2025-03-05,2408,9.4,Cognitive Computing +AI05422,AI Product Manager,39202,USD,39202,MI,CT,China,L,China,100,"NLP, Docker, Azure, Hadoop",Bachelor,3,Gaming,2024-09-17,2024-10-20,2380,9.3,Machine Intelligence Group +AI05423,Machine Learning Engineer,52424,USD,52424,EN,CT,Finland,S,Finland,100,"R, Kubernetes, Java, SQL, Docker",Associate,1,Energy,2025-03-03,2025-04-26,1801,6.4,Smart Analytics +AI05424,AI Research Scientist,74687,SGD,97093,EN,PT,Singapore,S,United States,0,"AWS, Tableau, Docker, Computer Vision",PhD,1,Consulting,2025-03-08,2025-04-02,2295,8,Algorithmic Solutions +AI05425,Computer Vision Engineer,231540,CAD,289425,EX,PT,Canada,L,Canada,100,"Java, Kubernetes, Hadoop, Mathematics, Scala",Associate,12,Education,2025-03-21,2025-04-29,2222,7.1,Neural Networks Co +AI05426,Data Analyst,156641,USD,156641,SE,FT,Norway,S,China,50,"Statistics, TensorFlow, Python, GCP",PhD,6,Transportation,2024-12-20,2025-01-20,717,9.2,TechCorp Inc +AI05427,Data Engineer,119985,CAD,149981,SE,FT,Canada,M,Canada,100,"Git, Deep Learning, Hadoop, NLP, Kubernetes",Associate,9,Transportation,2024-09-07,2024-10-07,1933,9.6,Advanced Robotics +AI05428,Autonomous Systems Engineer,131450,AUD,177458,EX,FT,Australia,S,Australia,100,"Hadoop, Linux, Computer Vision, Deep Learning, Kubernetes",PhD,11,Telecommunications,2024-05-02,2024-06-20,962,8.7,Digital Transformation LLC +AI05429,Machine Learning Engineer,179649,CAD,224561,EX,CT,Canada,M,Canada,50,"Linux, Kubernetes, Data Visualization, AWS",PhD,16,Manufacturing,2024-02-14,2024-03-31,1284,6.3,DeepTech Ventures +AI05430,Deep Learning Engineer,113259,EUR,96270,SE,PT,Austria,L,Switzerland,50,"Java, TensorFlow, Azure, Computer Vision",Bachelor,9,Automotive,2024-07-16,2024-09-04,514,8,Predictive Systems +AI05431,Head of AI,90625,CAD,113281,MI,CT,Canada,M,Canada,50,"SQL, Hadoop, R, Java, Python",Bachelor,4,Consulting,2024-04-19,2024-07-01,2289,7.7,Digital Transformation LLC +AI05432,Computer Vision Engineer,115445,USD,115445,MI,FL,Ireland,L,Ireland,100,"AWS, Hadoop, Data Visualization",Bachelor,2,Gaming,2024-09-10,2024-10-03,1925,5.1,Predictive Systems +AI05433,Deep Learning Engineer,82908,EUR,70472,MI,FL,Austria,S,Austria,0,"Python, Spark, SQL, Hadoop, Mathematics",Associate,4,Transportation,2025-02-06,2025-03-17,2093,8.2,Machine Intelligence Group +AI05434,Machine Learning Engineer,104007,CHF,93606,EN,CT,Switzerland,L,India,0,"Python, Scala, Data Visualization, Hadoop, Linux",PhD,0,Finance,2024-09-04,2024-10-11,1160,5.5,Smart Analytics +AI05435,Research Scientist,90940,AUD,122769,MI,PT,Australia,M,Australia,50,"Hadoop, Python, GCP",Bachelor,3,Media,2024-01-04,2024-03-13,2095,5.1,Digital Transformation LLC +AI05436,AI Product Manager,28492,USD,28492,EN,FT,China,L,China,50,"Python, SQL, Statistics",Associate,1,Healthcare,2024-08-08,2024-09-20,2004,7.6,Future Systems +AI05437,ML Ops Engineer,84521,CHF,76069,EN,FL,Switzerland,S,Switzerland,100,"Git, AWS, Kubernetes, MLOps, Tableau",PhD,0,Media,2025-04-01,2025-06-07,740,7.9,Smart Analytics +AI05438,AI Software Engineer,125527,USD,125527,SE,PT,Finland,L,Argentina,0,"PyTorch, Kubernetes, Docker",Associate,6,Gaming,2024-01-20,2024-03-14,1985,8.9,Cognitive Computing +AI05439,Machine Learning Researcher,98155,SGD,127602,MI,FL,Singapore,S,Singapore,0,"Spark, NLP, Python, TensorFlow, Data Visualization",Associate,2,Finance,2025-03-10,2025-04-13,1473,6.1,Smart Analytics +AI05440,Computer Vision Engineer,54723,SGD,71140,EN,FT,Singapore,M,Singapore,0,"SQL, Git, Hadoop, PyTorch, AWS",Master,0,Real Estate,2024-08-14,2024-10-17,1181,6.8,Machine Intelligence Group +AI05441,AI Research Scientist,132179,GBP,99134,SE,FT,United Kingdom,L,United Kingdom,50,"Python, Linux, Deep Learning, Scala",Associate,9,Manufacturing,2025-02-05,2025-03-02,954,7.6,Smart Analytics +AI05442,Data Engineer,99414,JPY,10935540,MI,CT,Japan,S,South Africa,100,"SQL, Kubernetes, Linux, Hadoop",Associate,2,Real Estate,2025-03-25,2025-05-29,1582,6.3,Predictive Systems +AI05443,Computer Vision Engineer,162201,USD,162201,SE,PT,Israel,L,Ireland,50,"NLP, Azure, Hadoop, Python",PhD,6,Finance,2024-02-02,2024-03-30,1047,9.2,Digital Transformation LLC +AI05444,Data Engineer,61351,USD,61351,EN,PT,Israel,L,Israel,50,"AWS, GCP, MLOps, PyTorch, SQL",Master,0,Gaming,2024-09-01,2024-09-15,2430,8.2,Advanced Robotics +AI05445,Machine Learning Engineer,23989,USD,23989,EN,FL,India,S,India,100,"SQL, R, PyTorch, NLP, Computer Vision",Bachelor,1,Automotive,2024-10-13,2024-11-17,1139,9.5,DataVision Ltd +AI05446,Robotics Engineer,65446,USD,65446,MI,CT,Finland,S,Finland,50,"Python, Git, Mathematics",PhD,3,Education,2024-03-30,2024-04-19,879,6,Predictive Systems +AI05447,ML Ops Engineer,160753,USD,160753,MI,FL,Denmark,L,Denmark,100,"Tableau, Docker, Hadoop, MLOps, GCP",Bachelor,2,Telecommunications,2024-07-31,2024-09-15,1572,7.3,Cloud AI Solutions +AI05448,ML Ops Engineer,159740,AUD,215649,SE,CT,Australia,L,Australia,100,"GCP, Spark, PyTorch",Bachelor,5,Telecommunications,2024-05-29,2024-07-11,1719,5.4,Future Systems +AI05449,Research Scientist,86339,EUR,73388,EN,PT,Austria,L,Austria,100,"Data Visualization, Python, Git, TensorFlow",PhD,1,Manufacturing,2024-01-24,2024-04-03,2369,7.3,Machine Intelligence Group +AI05450,Principal Data Scientist,223810,USD,223810,EX,PT,Israel,M,New Zealand,100,"Statistics, Data Visualization, Python",Bachelor,13,Gaming,2024-08-06,2024-10-18,1937,10,Algorithmic Solutions +AI05451,Robotics Engineer,156078,EUR,132666,EX,FT,Austria,M,Austria,0,"Java, Hadoop, R, AWS",Bachelor,13,Finance,2024-08-23,2024-10-31,1683,9.4,Algorithmic Solutions +AI05452,Principal Data Scientist,95770,CHF,86193,EN,PT,Switzerland,M,Switzerland,100,"Kubernetes, Hadoop, Data Visualization",Bachelor,0,Government,2024-05-12,2024-07-06,1591,9.7,Predictive Systems +AI05453,Deep Learning Engineer,94666,JPY,10413260,EN,FT,Japan,L,Japan,50,"Mathematics, Spark, Python, TensorFlow, PyTorch",Bachelor,1,Consulting,2025-03-27,2025-05-14,2335,7.4,Digital Transformation LLC +AI05454,AI Software Engineer,74801,SGD,97241,EN,FL,Singapore,L,Philippines,50,"Git, GCP, Docker, Mathematics",Associate,0,Manufacturing,2025-02-20,2025-04-28,1151,6.9,Digital Transformation LLC +AI05455,Research Scientist,106506,EUR,90530,SE,FT,Austria,S,Austria,0,"Linux, R, Git",PhD,8,Transportation,2024-05-18,2024-07-12,734,9.2,Neural Networks Co +AI05456,Computer Vision Engineer,150029,SGD,195038,SE,FL,Singapore,L,Singapore,100,"GCP, Kubernetes, Java",Associate,7,Manufacturing,2025-01-24,2025-03-15,1856,7.4,Autonomous Tech +AI05457,NLP Engineer,200851,USD,200851,SE,FT,United States,L,Switzerland,50,"GCP, AWS, PyTorch",Bachelor,5,Transportation,2024-12-15,2025-01-10,2386,7,DeepTech Ventures +AI05458,Machine Learning Researcher,99863,GBP,74897,MI,PT,United Kingdom,S,United Kingdom,0,"AWS, Git, Spark",PhD,2,Transportation,2024-11-26,2024-12-29,2303,7.6,Digital Transformation LLC +AI05459,Head of AI,39799,USD,39799,SE,PT,India,S,Kenya,50,"Computer Vision, SQL, Kubernetes, GCP",Associate,5,Manufacturing,2024-07-26,2024-09-30,1362,7,AI Innovations +AI05460,Data Engineer,96455,USD,96455,MI,PT,Denmark,S,Italy,50,"Statistics, Kubernetes, Linux, SQL, Data Visualization",PhD,4,Education,2024-07-24,2024-09-05,1910,6.3,Algorithmic Solutions +AI05461,Data Analyst,158698,USD,158698,EX,PT,South Korea,S,South Korea,50,"Scala, R, MLOps, Spark",Associate,19,Telecommunications,2024-03-25,2024-04-10,1132,6.3,Future Systems +AI05462,Machine Learning Researcher,180104,EUR,153088,EX,FT,Germany,M,Germany,0,"R, GCP, Git, Statistics",PhD,11,Government,2025-01-04,2025-02-09,2103,6.5,Autonomous Tech +AI05463,ML Ops Engineer,60136,EUR,51116,EN,PT,Netherlands,M,Netherlands,50,"SQL, Linux, AWS",PhD,0,Healthcare,2024-05-23,2024-08-01,691,9.7,Advanced Robotics +AI05464,AI Product Manager,183029,USD,183029,EX,FL,Israel,S,Israel,100,"Scala, TensorFlow, Tableau, MLOps, Kubernetes",Bachelor,19,Manufacturing,2024-01-05,2024-01-23,1507,6.7,Machine Intelligence Group +AI05465,AI Product Manager,114370,EUR,97215,MI,FL,Netherlands,M,Romania,50,"Linux, Kubernetes, Statistics, Python",Master,4,Retail,2025-02-19,2025-03-14,1343,8.5,AI Innovations +AI05466,Head of AI,54599,USD,54599,MI,CT,China,L,Netherlands,100,"Statistics, Docker, Python",Bachelor,2,Gaming,2024-04-23,2024-07-02,1436,6.1,Cloud AI Solutions +AI05467,AI Consultant,149215,EUR,126833,EX,CT,Germany,S,Germany,100,"TensorFlow, Deep Learning, Computer Vision, Tableau, SQL",PhD,12,Technology,2024-09-30,2024-11-10,1897,7,AI Innovations +AI05468,Data Analyst,36117,USD,36117,MI,FT,China,S,China,0,"Python, Azure, SQL, R, Mathematics",PhD,2,Consulting,2024-06-03,2024-07-28,1999,5.4,Cognitive Computing +AI05469,NLP Engineer,58126,EUR,49407,EN,PT,Austria,L,Philippines,100,"Python, SQL, Tableau, AWS, Kubernetes",Master,0,Finance,2025-03-17,2025-05-04,1896,5.7,Advanced Robotics +AI05470,AI Specialist,72607,AUD,98019,MI,CT,Australia,M,Australia,0,"Python, TensorFlow, AWS",Master,2,Real Estate,2025-02-11,2025-03-01,1088,7.4,TechCorp Inc +AI05471,Data Analyst,71757,CAD,89696,MI,FL,Canada,S,Kenya,0,"Statistics, PyTorch, Computer Vision, R, Git",Master,2,Media,2024-03-01,2024-04-26,2146,6.5,Future Systems +AI05472,Deep Learning Engineer,105689,EUR,89836,SE,FL,Germany,M,Germany,50,"R, Kubernetes, Mathematics, NLP",Master,9,Real Estate,2024-11-28,2025-01-13,758,5.1,Quantum Computing Inc +AI05473,Head of AI,42540,USD,42540,MI,FL,India,L,Egypt,100,"Python, Data Visualization, R, Spark, Java",PhD,2,Healthcare,2024-03-08,2024-04-06,1622,5.5,Digital Transformation LLC +AI05474,AI Architect,123577,EUR,105040,EX,FT,Austria,S,Portugal,0,"Python, R, NLP",PhD,12,Government,2024-10-17,2024-12-03,1020,6.6,Machine Intelligence Group +AI05475,AI Architect,236155,CAD,295194,EX,FT,Canada,L,Canada,0,"Scala, Spark, SQL",Master,16,Retail,2024-08-16,2024-09-26,1079,5,TechCorp Inc +AI05476,Machine Learning Engineer,70398,EUR,59838,EN,CT,Austria,L,Romania,100,"PyTorch, Spark, SQL, Mathematics",Master,1,Healthcare,2024-09-24,2024-11-20,1778,8,Machine Intelligence Group +AI05477,Data Scientist,146441,USD,146441,EX,FT,Israel,S,Israel,100,"AWS, Scala, Data Visualization, Java",Master,18,Technology,2024-11-13,2024-11-30,551,8.3,Machine Intelligence Group +AI05478,AI Specialist,47127,USD,47127,SE,CT,India,M,India,0,"Statistics, Azure, Git",PhD,6,Finance,2025-01-31,2025-03-17,1325,8,Algorithmic Solutions +AI05479,AI Product Manager,142445,EUR,121078,EX,FT,Austria,M,Austria,0,"Java, Tableau, Docker, Statistics",Master,10,Telecommunications,2024-05-10,2024-06-08,1295,7.5,Advanced Robotics +AI05480,AI Consultant,67586,USD,67586,SE,FL,China,M,China,0,"Mathematics, MLOps, Python, PyTorch, Tableau",PhD,9,Automotive,2025-04-26,2025-06-04,1573,5.5,Smart Analytics +AI05481,Research Scientist,176023,USD,176023,SE,FL,Denmark,S,Denmark,0,"Azure, SQL, Python, Kubernetes, Deep Learning",PhD,6,Real Estate,2024-07-26,2024-09-18,749,6.7,Advanced Robotics +AI05482,Machine Learning Engineer,21634,USD,21634,EN,FT,China,S,China,100,"Azure, SQL, R, Mathematics",Associate,1,Consulting,2024-09-26,2024-12-04,1237,9.1,Digital Transformation LLC +AI05483,ML Ops Engineer,105516,USD,105516,SE,FT,South Korea,S,Malaysia,50,"Azure, SQL, GCP",Associate,9,Technology,2024-07-31,2024-08-27,2063,7.3,Digital Transformation LLC +AI05484,Research Scientist,144381,USD,144381,EX,PT,Ireland,M,Ireland,0,"R, SQL, Docker",PhD,17,Telecommunications,2024-03-27,2024-04-28,1007,9,Advanced Robotics +AI05485,Deep Learning Engineer,76971,USD,76971,MI,FT,Israel,S,Belgium,0,"Python, Scala, Deep Learning",Associate,3,Automotive,2024-07-08,2024-07-26,1221,6.3,DeepTech Ventures +AI05486,AI Research Scientist,69347,USD,69347,SE,FL,China,L,Austria,50,"Data Visualization, Computer Vision, TensorFlow",Associate,6,Retail,2024-09-16,2024-10-29,2123,5.3,Smart Analytics +AI05487,ML Ops Engineer,63587,JPY,6994570,EN,CT,Japan,S,Japan,50,"Computer Vision, PyTorch, Kubernetes, Java, Spark",Master,1,Finance,2025-01-01,2025-03-12,1372,9.2,Advanced Robotics +AI05488,AI Consultant,159882,EUR,135900,SE,CT,Germany,L,Finland,50,"PyTorch, Tableau, R, Data Visualization",Bachelor,9,Media,2024-11-26,2025-01-30,895,6,Predictive Systems +AI05489,Head of AI,63760,USD,63760,EN,FT,Ireland,M,Ireland,100,"Kubernetes, Python, Tableau",Master,0,Telecommunications,2024-12-18,2025-02-06,1750,9.6,Algorithmic Solutions +AI05490,AI Software Engineer,91323,JPY,10045530,MI,CT,Japan,S,Japan,0,"Linux, AWS, Python",Bachelor,3,Healthcare,2025-01-02,2025-03-10,2170,5.1,DataVision Ltd +AI05491,Principal Data Scientist,95852,SGD,124608,MI,CT,Singapore,S,Singapore,100,"TensorFlow, Azure, Git",Associate,2,Media,2024-04-18,2024-06-02,2250,9.5,Autonomous Tech +AI05492,AI Research Scientist,142643,USD,142643,EX,FT,Ireland,M,Germany,50,"Data Visualization, Statistics, Linux",PhD,19,Telecommunications,2024-09-19,2024-11-09,1075,8.6,Advanced Robotics +AI05493,AI Research Scientist,183011,USD,183011,EX,PT,Finland,S,Luxembourg,100,"SQL, MLOps, TensorFlow, AWS",Bachelor,18,Education,2025-01-01,2025-02-23,1368,5.2,Quantum Computing Inc +AI05494,AI Product Manager,60370,USD,60370,EN,PT,United States,S,United States,50,"NLP, R, Linux, SQL",PhD,0,Technology,2024-01-24,2024-03-07,1727,9.5,Future Systems +AI05495,AI Software Engineer,296283,JPY,32591130,EX,CT,Japan,L,Egypt,50,"Git, SQL, Computer Vision, Mathematics",PhD,13,Media,2024-07-26,2024-08-22,947,7.8,Neural Networks Co +AI05496,NLP Engineer,89935,JPY,9892850,EN,CT,Japan,L,Switzerland,100,"MLOps, Python, Computer Vision, Spark",Master,0,Government,2024-10-12,2024-11-04,2250,8.7,Future Systems +AI05497,Data Analyst,94666,CHF,85199,EN,CT,Switzerland,L,Switzerland,50,"Scala, Tableau, AWS, Computer Vision, TensorFlow",PhD,0,Media,2024-04-28,2024-05-24,1878,6.1,Neural Networks Co +AI05498,Machine Learning Engineer,86209,USD,86209,EN,CT,United States,M,United States,0,"Hadoop, Linux, SQL, NLP, Kubernetes",Bachelor,0,Real Estate,2025-01-12,2025-03-01,1116,8,Digital Transformation LLC +AI05499,Machine Learning Engineer,81814,GBP,61361,EN,FT,United Kingdom,M,United Kingdom,0,"Linux, Azure, Scala",Associate,1,Real Estate,2024-11-22,2024-12-06,1079,8.5,Predictive Systems +AI05500,Data Engineer,122880,EUR,104448,SE,FT,Austria,S,Japan,50,"Scala, Python, Data Visualization, Deep Learning, TensorFlow",PhD,5,Transportation,2024-03-02,2024-05-08,907,5.3,Smart Analytics +AI05501,Data Analyst,161377,CHF,145239,SE,PT,Switzerland,M,Switzerland,0,"Linux, Spark, TensorFlow, Python, Tableau",Associate,5,Government,2025-02-20,2025-03-31,900,9.9,Quantum Computing Inc +AI05502,AI Consultant,64242,JPY,7066620,EN,FL,Japan,S,Japan,0,"Computer Vision, Kubernetes, SQL",Bachelor,1,Real Estate,2024-09-25,2024-11-14,526,6,DeepTech Ventures +AI05503,Robotics Engineer,142995,EUR,121546,SE,CT,Netherlands,M,Ukraine,50,"Computer Vision, Statistics, Kubernetes",Bachelor,5,Government,2024-08-26,2024-10-05,1795,7.9,Autonomous Tech +AI05504,Autonomous Systems Engineer,108977,CAD,136221,SE,PT,Canada,S,Chile,50,"Azure, Computer Vision, NLP, SQL, Mathematics",PhD,7,Education,2025-04-17,2025-06-25,1497,5.4,Predictive Systems +AI05505,Deep Learning Engineer,32809,USD,32809,EN,PT,China,M,China,50,"Statistics, Python, Tableau, Docker, AWS",Bachelor,1,Transportation,2025-01-22,2025-03-08,1052,5.1,Machine Intelligence Group +AI05506,Computer Vision Engineer,236299,GBP,177224,EX,PT,United Kingdom,L,United Kingdom,0,"PyTorch, SQL, Data Visualization, Hadoop",Bachelor,13,Automotive,2024-05-20,2024-07-28,1337,9.6,Future Systems +AI05507,Machine Learning Engineer,133957,USD,133957,MI,CT,Norway,M,Norway,100,"Tableau, Kubernetes, Python, Deep Learning, Azure",Bachelor,3,Transportation,2024-04-29,2024-05-29,1599,8.3,AI Innovations +AI05508,Data Scientist,62909,GBP,47182,EN,PT,United Kingdom,L,United Kingdom,0,"Computer Vision, GCP, MLOps, Statistics, Deep Learning",Bachelor,0,Technology,2025-01-19,2025-03-07,928,8.7,Machine Intelligence Group +AI05509,Machine Learning Engineer,147022,SGD,191129,EX,CT,Singapore,S,Singapore,100,"SQL, PyTorch, NLP, Docker",PhD,15,Manufacturing,2024-12-03,2025-01-02,679,8.9,Neural Networks Co +AI05510,Machine Learning Engineer,144913,EUR,123176,SE,FL,France,L,France,50,"Data Visualization, Git, Spark, Computer Vision",Associate,8,Technology,2025-04-19,2025-06-05,578,8.9,Cognitive Computing +AI05511,AI Specialist,45877,USD,45877,SE,FT,India,M,India,0,"Python, Docker, GCP",PhD,7,Automotive,2024-08-28,2024-09-29,1780,9.7,Algorithmic Solutions +AI05512,Principal Data Scientist,33228,USD,33228,EN,FT,China,S,China,100,"Kubernetes, SQL, Git, Statistics",Associate,1,Media,2024-06-09,2024-07-03,642,6.8,Cloud AI Solutions +AI05513,Machine Learning Researcher,87357,USD,87357,MI,FL,South Korea,M,South Korea,0,"MLOps, Hadoop, NLP, Mathematics",Bachelor,2,Retail,2024-07-25,2024-09-09,1707,7.2,TechCorp Inc +AI05514,AI Product Manager,57116,USD,57116,EN,FT,Finland,M,Finland,100,"NLP, Java, Spark, Kubernetes",PhD,0,Real Estate,2024-06-16,2024-08-23,2471,8.4,Smart Analytics +AI05515,Machine Learning Engineer,67628,GBP,50721,EN,CT,United Kingdom,L,Philippines,0,"Kubernetes, Java, R, Deep Learning",PhD,1,Transportation,2024-04-22,2024-06-05,1168,6.2,Smart Analytics +AI05516,AI Specialist,51699,JPY,5686890,EN,PT,Japan,S,Japan,0,"Tableau, R, PyTorch",Master,0,Transportation,2024-12-30,2025-03-06,1456,6.5,Cloud AI Solutions +AI05517,AI Research Scientist,158696,USD,158696,EX,PT,Sweden,S,Singapore,0,"Git, TensorFlow, Computer Vision, Linux, Python",PhD,16,Automotive,2024-08-16,2024-09-28,1409,6.4,Predictive Systems +AI05518,AI Specialist,181010,EUR,153859,EX,CT,Austria,L,Austria,50,"Azure, Tableau, Python",Bachelor,18,Retail,2025-01-13,2025-01-31,1209,9.6,DeepTech Ventures +AI05519,ML Ops Engineer,143355,USD,143355,SE,FL,Ireland,M,United States,100,"Python, Kubernetes, NLP",Bachelor,8,Manufacturing,2025-03-02,2025-04-09,973,8.8,AI Innovations +AI05520,Data Scientist,94621,USD,94621,MI,CT,Israel,M,South Africa,100,"Data Visualization, Git, Linux, AWS",Master,2,Consulting,2024-09-25,2024-11-17,1804,6.1,Machine Intelligence Group +AI05521,Data Engineer,50440,USD,50440,SE,FT,China,M,China,100,"SQL, PyTorch, Mathematics, Git",Associate,6,Real Estate,2024-10-24,2024-11-17,1306,6.9,DeepTech Ventures +AI05522,Autonomous Systems Engineer,39850,USD,39850,MI,CT,China,L,China,50,"SQL, Computer Vision, Statistics",Master,4,Energy,2024-07-16,2024-08-30,1706,6.3,Neural Networks Co +AI05523,Data Analyst,129312,USD,129312,SE,CT,Finland,M,Finland,100,"Docker, MLOps, Python, Java, Tableau",PhD,9,Real Estate,2024-12-07,2025-02-11,2388,6.2,DeepTech Ventures +AI05524,ML Ops Engineer,262770,EUR,223355,EX,FT,France,L,Philippines,100,"Git, MLOps, Tableau, Scala, Kubernetes",Bachelor,11,Real Estate,2025-01-22,2025-03-31,942,9.9,Cognitive Computing +AI05525,Principal Data Scientist,95183,JPY,10470130,MI,FT,Japan,S,Japan,100,"Tableau, Python, AWS, TensorFlow, Deep Learning",Associate,3,Consulting,2024-07-23,2024-09-01,1428,9.6,Smart Analytics +AI05526,Data Analyst,40242,USD,40242,MI,PT,India,L,India,0,"PyTorch, Azure, Tableau, Kubernetes, TensorFlow",PhD,2,Telecommunications,2024-07-02,2024-07-24,1322,6.8,Autonomous Tech +AI05527,Machine Learning Researcher,164259,JPY,18068490,EX,FT,Japan,S,Colombia,100,"Docker, Kubernetes, NLP, PyTorch, TensorFlow",Associate,19,Gaming,2024-11-05,2024-11-27,2246,8.8,Advanced Robotics +AI05528,Machine Learning Engineer,102309,USD,102309,SE,FT,Finland,M,Finland,100,"Data Visualization, NLP, Python, Hadoop",Master,8,Education,2024-03-04,2024-05-11,939,7.1,Predictive Systems +AI05529,Head of AI,53973,USD,53973,EN,FL,Ireland,S,Thailand,0,"Python, TensorFlow, MLOps",PhD,0,Technology,2025-02-03,2025-03-05,611,7.2,Cognitive Computing +AI05530,AI Product Manager,54973,USD,54973,SE,FT,India,L,India,0,"Scala, Data Visualization, Azure, PyTorch",PhD,7,Automotive,2024-11-12,2024-12-08,1043,9.6,Digital Transformation LLC +AI05531,NLP Engineer,187522,USD,187522,EX,CT,Finland,S,Finland,0,"Scala, Linux, Spark, PyTorch, MLOps",Bachelor,10,Media,2024-11-27,2024-12-31,1802,7.4,Future Systems +AI05532,NLP Engineer,57683,EUR,49031,EN,CT,Austria,S,Austria,0,"R, GCP, Mathematics, Deep Learning",Bachelor,0,Finance,2024-04-04,2024-04-30,1641,5.4,Cloud AI Solutions +AI05533,AI Architect,78473,USD,78473,MI,FL,South Korea,L,South Korea,50,"Kubernetes, Deep Learning, R, Tableau",Bachelor,3,Automotive,2024-07-31,2024-10-03,1798,5.2,DataVision Ltd +AI05534,Computer Vision Engineer,55008,SGD,71510,EN,CT,Singapore,S,Portugal,100,"Mathematics, Azure, Computer Vision",Bachelor,1,Technology,2024-12-16,2025-02-20,1194,9.6,TechCorp Inc +AI05535,Computer Vision Engineer,76394,USD,76394,EN,FL,Norway,S,Norway,100,"Python, Computer Vision, SQL, Docker",PhD,0,Government,2024-01-16,2024-03-04,2400,8.2,Smart Analytics +AI05536,AI Research Scientist,102251,USD,102251,SE,CT,Finland,M,France,100,"MLOps, NLP, R, Data Visualization",Associate,6,Government,2025-01-07,2025-02-08,1801,6.7,Quantum Computing Inc +AI05537,Head of AI,225096,USD,225096,EX,FT,Ireland,L,Ireland,50,"PyTorch, AWS, TensorFlow, Mathematics, Scala",Master,15,Education,2024-05-01,2024-07-01,726,5.7,DeepTech Ventures +AI05538,Principal Data Scientist,204843,CHF,184359,SE,PT,Switzerland,L,Brazil,100,"PyTorch, Scala, Java",PhD,6,Finance,2025-01-06,2025-02-14,1120,7.8,TechCorp Inc +AI05539,Principal Data Scientist,138580,USD,138580,SE,CT,Norway,M,Norway,50,"R, SQL, PyTorch",Master,6,Education,2024-08-09,2024-10-11,944,6.5,DeepTech Ventures +AI05540,Head of AI,85499,EUR,72674,EN,FL,Netherlands,L,Netherlands,50,"PyTorch, TensorFlow, Hadoop",Associate,1,Finance,2024-03-02,2024-03-27,767,5.8,Algorithmic Solutions +AI05541,Machine Learning Researcher,83346,SGD,108350,EN,CT,Singapore,M,Singapore,100,"NLP, Kubernetes, TensorFlow, Docker",Master,0,Finance,2024-04-10,2024-05-23,723,9.1,DeepTech Ventures +AI05542,NLP Engineer,115766,USD,115766,MI,PT,Norway,S,Norway,50,"Tableau, SQL, Azure, PyTorch",PhD,2,Consulting,2024-08-11,2024-10-17,1493,7.2,DataVision Ltd +AI05543,Data Analyst,205113,USD,205113,SE,CT,Denmark,L,Denmark,50,"Java, Spark, NLP",PhD,7,Gaming,2025-03-18,2025-04-17,1640,7.7,AI Innovations +AI05544,AI Software Engineer,160912,USD,160912,SE,FT,Sweden,L,Sweden,100,"Git, GCP, Hadoop, Azure, Statistics",PhD,6,Finance,2024-02-27,2024-04-22,856,6,Predictive Systems +AI05545,AI Research Scientist,142229,USD,142229,SE,PT,Finland,L,Finland,50,"Statistics, Tableau, Computer Vision, Java, Python",Bachelor,6,Real Estate,2024-02-07,2024-03-19,1243,6,Predictive Systems +AI05546,Deep Learning Engineer,79913,USD,79913,MI,FT,Finland,S,Finland,0,"SQL, AWS, Scala",Bachelor,2,Gaming,2024-04-21,2024-05-21,1381,5.6,Digital Transformation LLC +AI05547,Data Scientist,105268,USD,105268,MI,CT,Denmark,M,Denmark,100,"Kubernetes, GCP, Mathematics, Computer Vision, Hadoop",Master,3,Telecommunications,2024-10-25,2024-12-11,1041,6.4,Neural Networks Co +AI05548,Research Scientist,222239,SGD,288911,EX,CT,Singapore,S,Singapore,100,"Spark, Python, R, Computer Vision",Master,11,Technology,2025-02-22,2025-03-08,1199,9.6,AI Innovations +AI05549,Computer Vision Engineer,95349,USD,95349,MI,PT,Sweden,S,Sweden,100,"R, Statistics, Hadoop",Master,3,Telecommunications,2024-05-08,2024-06-18,913,7.2,AI Innovations +AI05550,Machine Learning Engineer,276306,USD,276306,EX,CT,United States,L,United States,0,"TensorFlow, R, Azure",Associate,13,Government,2024-07-21,2024-09-08,880,7.6,DataVision Ltd +AI05551,Head of AI,86349,USD,86349,MI,FL,Finland,S,Finland,100,"Git, Java, Computer Vision, Mathematics, Spark",Master,2,Transportation,2024-06-24,2024-08-13,744,6.4,Autonomous Tech +AI05552,AI Product Manager,200534,USD,200534,EX,FT,United States,S,Luxembourg,50,"Linux, Kubernetes, Python, Mathematics",Bachelor,15,Manufacturing,2024-07-22,2024-09-01,1411,7.1,Autonomous Tech +AI05553,ML Ops Engineer,130848,GBP,98136,SE,PT,United Kingdom,M,United Kingdom,50,"Tableau, Spark, Python, Computer Vision",Associate,7,Transportation,2024-11-18,2025-01-19,506,8.6,Neural Networks Co +AI05554,ML Ops Engineer,137574,USD,137574,SE,FL,Denmark,M,Denmark,100,"Python, MLOps, Scala",Master,9,Gaming,2024-02-05,2024-03-25,2456,6,AI Innovations +AI05555,AI Research Scientist,64547,EUR,54865,MI,PT,France,S,France,100,"Data Visualization, SQL, Statistics",Bachelor,4,Real Estate,2024-10-06,2024-11-08,1689,5.6,Cloud AI Solutions +AI05556,AI Specialist,220582,CHF,198524,SE,FL,Switzerland,L,Switzerland,50,"Data Visualization, Python, Hadoop, MLOps, TensorFlow",Master,9,Education,2025-04-29,2025-05-30,1189,7.7,Autonomous Tech +AI05557,Machine Learning Engineer,68236,EUR,58001,EN,CT,France,M,France,100,"Docker, Deep Learning, Java",Associate,1,Manufacturing,2024-03-04,2024-04-25,2050,8.7,DeepTech Ventures +AI05558,Machine Learning Engineer,102411,CHF,92170,MI,FT,Switzerland,S,Switzerland,0,"Python, SQL, Linux, Azure",Bachelor,3,Real Estate,2024-03-20,2024-04-10,2337,8.1,Neural Networks Co +AI05559,Data Analyst,98866,JPY,10875260,MI,FL,Japan,S,Japan,50,"Python, Mathematics, Scala",Master,3,Real Estate,2025-04-23,2025-05-20,1232,8.7,DeepTech Ventures +AI05560,AI Research Scientist,71678,USD,71678,EN,CT,Norway,S,Norway,50,"Java, Kubernetes, TensorFlow, GCP, Spark",Bachelor,0,Education,2025-02-21,2025-03-23,2418,8.2,DeepTech Ventures +AI05561,Principal Data Scientist,38368,USD,38368,MI,PT,India,L,Ghana,50,"PyTorch, Java, Docker, Kubernetes, GCP",Master,4,Finance,2024-02-16,2024-04-22,1578,9.7,DataVision Ltd +AI05562,Autonomous Systems Engineer,53056,EUR,45098,EN,PT,Germany,M,Germany,100,"Python, MLOps, NLP, TensorFlow",Associate,0,Automotive,2024-12-27,2025-02-05,1918,6.2,Predictive Systems +AI05563,Research Scientist,77960,USD,77960,MI,FT,Finland,S,India,50,"NLP, Kubernetes, Git",PhD,3,Media,2024-08-25,2024-09-30,2354,5.9,DataVision Ltd +AI05564,Computer Vision Engineer,137750,USD,137750,EX,FL,Israel,S,Israel,50,"Hadoop, TensorFlow, Data Visualization, MLOps",Bachelor,15,Transportation,2024-12-13,2025-01-07,686,9.3,AI Innovations +AI05565,Deep Learning Engineer,70399,USD,70399,EN,PT,Finland,L,Singapore,0,"Spark, SQL, Kubernetes",Master,0,Media,2024-06-06,2024-07-02,885,5.8,TechCorp Inc +AI05566,Data Scientist,81497,USD,81497,EX,CT,China,L,China,50,"Azure, Java, Computer Vision, Kubernetes, R",Bachelor,16,Gaming,2024-06-17,2024-08-04,897,8.5,Future Systems +AI05567,Autonomous Systems Engineer,97979,USD,97979,SE,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, Statistics",Master,5,Education,2024-03-11,2024-05-04,1745,5.1,Cloud AI Solutions +AI05568,Machine Learning Engineer,74733,CHF,67260,EN,FT,Switzerland,M,Switzerland,0,"Linux, GCP, PyTorch",Bachelor,0,Retail,2025-04-07,2025-06-01,2308,9.4,Neural Networks Co +AI05569,AI Consultant,34474,USD,34474,MI,FL,India,S,India,100,"Scala, NLP, Java, R, Kubernetes",Associate,3,Education,2025-01-15,2025-02-05,2489,7.9,Quantum Computing Inc +AI05570,Machine Learning Researcher,138565,EUR,117780,EX,CT,France,S,Vietnam,0,"NLP, Docker, Java",Bachelor,11,Media,2024-05-07,2024-06-08,2445,7.8,Digital Transformation LLC +AI05571,Head of AI,91979,USD,91979,MI,FL,Finland,M,Finland,100,"SQL, Computer Vision, Git, Python, Azure",Master,4,Automotive,2024-01-31,2024-03-17,1365,6.3,Predictive Systems +AI05572,AI Product Manager,156226,CHF,140603,MI,FL,Switzerland,L,Philippines,50,"SQL, R, Python",PhD,3,Energy,2024-07-14,2024-09-15,563,7.9,DataVision Ltd +AI05573,Robotics Engineer,220616,SGD,286801,EX,FL,Singapore,S,United States,0,"Linux, NLP, Kubernetes, Scala, SQL",Master,18,Consulting,2024-04-03,2024-05-22,793,6.6,Neural Networks Co +AI05574,Data Engineer,125635,CHF,113072,MI,FL,Switzerland,S,Switzerland,100,"NLP, Python, Scala, GCP",Master,2,Technology,2024-04-24,2024-06-25,569,8.4,TechCorp Inc +AI05575,Data Scientist,141071,EUR,119910,SE,FL,France,L,Austria,0,"Spark, Azure, SQL",PhD,5,Education,2024-07-09,2024-08-16,1177,9.1,Advanced Robotics +AI05576,NLP Engineer,77457,USD,77457,EN,CT,Ireland,M,France,0,"Azure, Mathematics, Python",Bachelor,1,Real Estate,2025-02-26,2025-03-26,1430,6.1,Machine Intelligence Group +AI05577,Computer Vision Engineer,81274,EUR,69083,MI,FL,Austria,L,Austria,100,"Docker, AWS, GCP, PyTorch, Scala",Associate,4,Energy,2024-03-25,2024-04-22,1457,6.7,Neural Networks Co +AI05578,Robotics Engineer,123555,USD,123555,SE,FT,Ireland,S,Ireland,50,"TensorFlow, Git, NLP",Bachelor,7,Finance,2024-06-28,2024-08-29,2138,6.9,DeepTech Ventures +AI05579,AI Product Manager,107981,USD,107981,SE,PT,Finland,M,Finland,100,"Data Visualization, Python, GCP, MLOps, Deep Learning",Master,9,Finance,2024-09-21,2024-10-28,910,5.2,AI Innovations +AI05580,Research Scientist,91339,USD,91339,EN,PT,Sweden,L,Luxembourg,50,"Hadoop, Kubernetes, Computer Vision, TensorFlow, GCP",Bachelor,0,Finance,2025-01-25,2025-04-04,1507,7.5,DataVision Ltd +AI05581,Principal Data Scientist,137460,CHF,123714,MI,CT,Switzerland,L,Switzerland,50,"Python, Hadoop, Git, TensorFlow, PyTorch",Master,3,Healthcare,2025-04-19,2025-05-25,1966,7.9,Neural Networks Co +AI05582,Data Scientist,104465,USD,104465,MI,PT,Norway,M,Netherlands,0,"Statistics, Git, SQL",Bachelor,2,Finance,2024-10-03,2024-11-12,820,7.7,Autonomous Tech +AI05583,Robotics Engineer,77385,USD,77385,MI,FL,Sweden,S,Spain,100,"Git, GCP, MLOps, Deep Learning, Kubernetes",Associate,3,Transportation,2024-02-29,2024-04-20,1137,7.6,Advanced Robotics +AI05584,Machine Learning Engineer,26283,USD,26283,EN,FT,China,S,Colombia,50,"Python, TensorFlow, Kubernetes, PyTorch",PhD,0,Energy,2025-03-31,2025-05-10,714,8.6,Predictive Systems +AI05585,Data Scientist,132539,USD,132539,SE,PT,Denmark,M,Denmark,100,"Data Visualization, Kubernetes, Docker",Master,6,Media,2024-11-04,2024-12-05,2172,10,DeepTech Ventures +AI05586,AI Product Manager,59940,EUR,50949,EN,CT,Netherlands,M,Spain,100,"Python, R, Computer Vision, Git, Azure",Bachelor,0,Finance,2025-01-19,2025-03-25,953,6.9,AI Innovations +AI05587,NLP Engineer,308476,USD,308476,EX,FL,Denmark,M,Ukraine,100,"Data Visualization, TensorFlow, Python",Bachelor,13,Education,2024-05-14,2024-06-09,807,6.4,Future Systems +AI05588,Machine Learning Engineer,117756,GBP,88317,SE,FT,United Kingdom,M,United Kingdom,0,"Tableau, Python, Azure, Statistics, Scala",Master,7,Real Estate,2024-12-06,2025-01-28,1370,7.8,TechCorp Inc +AI05589,Robotics Engineer,95582,USD,95582,EN,PT,Norway,M,Norway,50,"TensorFlow, Statistics, Deep Learning",Master,0,Education,2025-01-13,2025-03-11,1148,5,DeepTech Ventures +AI05590,Deep Learning Engineer,152384,USD,152384,MI,CT,Norway,L,Norway,0,"AWS, PyTorch, Linux, GCP, Computer Vision",Associate,4,Energy,2024-08-23,2024-09-30,2279,7.3,Machine Intelligence Group +AI05591,Data Engineer,149481,USD,149481,SE,CT,Denmark,S,Indonesia,0,"MLOps, Tableau, Hadoop, SQL, R",Master,7,Automotive,2024-05-31,2024-08-10,1674,5.9,DataVision Ltd +AI05592,Robotics Engineer,133014,CHF,119713,MI,FT,Switzerland,M,Switzerland,0,"Hadoop, Scala, Data Visualization, PyTorch",Bachelor,4,Media,2024-04-24,2024-05-20,1451,6.1,Autonomous Tech +AI05593,Computer Vision Engineer,80242,SGD,104315,MI,FT,Singapore,M,Singapore,100,"SQL, Linux, Python, AWS",Master,3,Real Estate,2024-04-12,2024-06-01,956,7,Future Systems +AI05594,AI Product Manager,71080,USD,71080,EN,FL,United States,M,United States,100,"AWS, Kubernetes, TensorFlow",Bachelor,1,Energy,2024-03-04,2024-04-18,895,8.4,Neural Networks Co +AI05595,Robotics Engineer,158297,USD,158297,EX,FT,Sweden,M,Sweden,100,"MLOps, R, Python",PhD,16,Finance,2024-04-14,2024-06-08,1393,6.1,DataVision Ltd +AI05596,Computer Vision Engineer,64920,AUD,87642,EN,FL,Australia,M,Australia,50,"Deep Learning, Linux, Spark, GCP",Bachelor,1,Retail,2024-02-24,2024-04-02,1085,8.3,DeepTech Ventures +AI05597,AI Research Scientist,82287,USD,82287,SE,FT,South Korea,S,South Korea,0,"Kubernetes, TensorFlow, Deep Learning",Master,5,Energy,2024-08-23,2024-09-20,1089,9.3,DataVision Ltd +AI05598,Data Analyst,108508,USD,108508,MI,FT,Finland,L,Finland,50,"Python, GCP, NLP, Spark",PhD,2,Energy,2025-04-04,2025-06-09,929,9.3,DeepTech Ventures +AI05599,Data Analyst,86007,AUD,116109,MI,PT,Australia,M,Australia,50,"Spark, Docker, Data Visualization",Associate,3,Media,2024-07-25,2024-09-17,992,9.4,DeepTech Ventures +AI05600,Principal Data Scientist,157752,USD,157752,SE,CT,Denmark,M,Denmark,50,"R, Scala, PyTorch, Mathematics",Master,9,Real Estate,2024-08-09,2024-10-10,1080,5.6,Algorithmic Solutions +AI05601,Autonomous Systems Engineer,91594,USD,91594,MI,FL,Finland,M,Hungary,0,"Git, Hadoop, MLOps",Bachelor,3,Finance,2024-05-10,2024-06-11,1794,6.4,Predictive Systems +AI05602,Autonomous Systems Engineer,74217,USD,74217,MI,FL,Finland,M,India,50,"GCP, Tableau, Hadoop",PhD,2,Manufacturing,2024-02-22,2024-04-09,683,5.6,TechCorp Inc +AI05603,AI Research Scientist,284154,GBP,213116,EX,CT,United Kingdom,L,United Kingdom,50,"Linux, Java, Data Visualization",Bachelor,15,Consulting,2024-11-29,2025-01-28,725,6.4,AI Innovations +AI05604,AI Software Engineer,163958,USD,163958,EX,FT,South Korea,L,South Korea,50,"Scala, PyTorch, Data Visualization, MLOps",PhD,13,Manufacturing,2024-11-03,2024-11-23,596,8,TechCorp Inc +AI05605,ML Ops Engineer,62034,CAD,77543,EN,PT,Canada,S,Canada,0,"Linux, SQL, Docker, PyTorch, Deep Learning",Associate,1,Real Estate,2025-01-27,2025-02-18,1422,9.4,Advanced Robotics +AI05606,AI Software Engineer,166512,CAD,208140,EX,FT,Canada,S,Ireland,0,"Python, Java, Computer Vision",Master,10,Consulting,2024-02-19,2024-04-24,624,8.8,Future Systems +AI05607,AI Product Manager,209138,USD,209138,EX,PT,Ireland,L,Ireland,100,"Python, Spark, MLOps",Associate,10,Telecommunications,2024-12-17,2025-02-05,790,8.5,DataVision Ltd +AI05608,AI Product Manager,149550,USD,149550,SE,PT,United States,S,United States,100,"Computer Vision, PyTorch, Spark",PhD,7,Technology,2024-08-13,2024-09-02,2025,6.8,Machine Intelligence Group +AI05609,ML Ops Engineer,162213,EUR,137881,EX,FT,Germany,M,Germany,50,"R, Kubernetes, Docker, Tableau, TensorFlow",Bachelor,14,Government,2024-06-14,2024-08-01,979,6,Smart Analytics +AI05610,Robotics Engineer,179531,USD,179531,EX,CT,Norway,M,Latvia,50,"Kubernetes, Deep Learning, Computer Vision, Java",Bachelor,14,Manufacturing,2024-06-09,2024-08-15,1650,7.2,Algorithmic Solutions +AI05611,Data Analyst,206536,USD,206536,EX,FL,South Korea,M,South Korea,50,"Linux, Python, Git, TensorFlow",PhD,12,Healthcare,2024-01-21,2024-02-10,1380,5.6,DataVision Ltd +AI05612,AI Specialist,33744,USD,33744,SE,FT,India,S,India,100,"TensorFlow, Deep Learning, Computer Vision",Associate,7,Manufacturing,2024-12-16,2025-02-26,1221,5.4,Algorithmic Solutions +AI05613,AI Consultant,60562,USD,60562,EN,PT,Israel,L,France,0,"SQL, Statistics, PyTorch, Deep Learning, R",PhD,1,Healthcare,2025-01-07,2025-02-07,1322,7.6,Advanced Robotics +AI05614,AI Software Engineer,55911,AUD,75480,EN,FL,Australia,M,Australia,0,"Spark, Kubernetes, Linux, Hadoop",PhD,0,Manufacturing,2024-02-28,2024-03-26,1136,5.1,Neural Networks Co +AI05615,Autonomous Systems Engineer,95326,USD,95326,MI,FL,South Korea,L,South Korea,50,"R, Kubernetes, MLOps",Associate,4,Retail,2024-11-29,2025-01-29,953,7,AI Innovations +AI05616,Machine Learning Engineer,185388,JPY,20392680,EX,CT,Japan,L,Japan,0,"TensorFlow, Python, MLOps, Spark",PhD,17,Manufacturing,2024-07-28,2024-09-26,2466,9.2,Predictive Systems +AI05617,Research Scientist,150527,EUR,127948,SE,CT,Netherlands,M,Switzerland,100,"Linux, AWS, Tableau, Docker, Mathematics",PhD,7,Healthcare,2024-12-20,2025-02-10,545,5.5,Quantum Computing Inc +AI05618,ML Ops Engineer,119633,USD,119633,EX,FL,China,M,China,100,"Java, PyTorch, Hadoop, Git",Master,11,Finance,2024-07-22,2024-08-20,2109,7,TechCorp Inc +AI05619,Data Scientist,227078,USD,227078,SE,FL,Norway,L,Norway,50,"Git, Spark, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-06-21,2024-07-11,1035,8,Cloud AI Solutions +AI05620,AI Product Manager,195528,USD,195528,SE,FL,Denmark,M,Argentina,0,"PyTorch, Python, NLP, Azure, Spark",Associate,7,Media,2024-09-27,2024-10-22,532,8,TechCorp Inc +AI05621,Data Scientist,123024,CAD,153780,SE,FL,Canada,M,Canada,100,"Hadoop, Spark, Python, Git",Master,7,Finance,2024-12-21,2025-02-20,1417,5,Smart Analytics +AI05622,Research Scientist,151053,USD,151053,MI,FT,Denmark,L,Philippines,50,"AWS, Kubernetes, SQL",PhD,2,Technology,2024-06-13,2024-07-09,628,8.1,DataVision Ltd +AI05623,AI Architect,116626,JPY,12828860,SE,PT,Japan,S,Japan,50,"Scala, Kubernetes, NLP, Statistics, R",PhD,7,Telecommunications,2024-11-06,2024-12-30,791,7.1,Advanced Robotics +AI05624,ML Ops Engineer,97656,EUR,83008,MI,FL,Austria,M,Austria,100,"Kubernetes, Java, R",PhD,4,Retail,2025-02-20,2025-03-13,2400,8,Digital Transformation LLC +AI05625,Research Scientist,94494,EUR,80320,EN,PT,Netherlands,L,Netherlands,100,"Scala, Spark, Java, Computer Vision, Git",PhD,1,Consulting,2025-04-24,2025-05-13,1566,9.9,DeepTech Ventures +AI05626,ML Ops Engineer,43321,USD,43321,SE,PT,India,L,India,100,"TensorFlow, Azure, Git",Master,9,Telecommunications,2024-09-06,2024-10-04,1763,8.8,DataVision Ltd +AI05627,AI Software Engineer,58243,EUR,49507,EN,FL,Germany,S,Malaysia,100,"Kubernetes, GCP, Computer Vision, MLOps",PhD,0,Energy,2024-11-02,2024-12-16,535,8.6,TechCorp Inc +AI05628,Machine Learning Engineer,106076,USD,106076,SE,FT,Israel,M,Malaysia,0,"GCP, Azure, SQL, Docker",Associate,6,Government,2024-08-06,2024-10-14,830,7.9,DeepTech Ventures +AI05629,Head of AI,124280,USD,124280,SE,CT,Israel,M,Malaysia,100,"Git, Python, Kubernetes, MLOps",Associate,7,Automotive,2024-08-01,2024-08-16,1666,9.3,Machine Intelligence Group +AI05630,Robotics Engineer,237713,GBP,178285,EX,FT,United Kingdom,M,Denmark,50,"Java, TensorFlow, Tableau, NLP, Mathematics",Bachelor,18,Education,2025-02-05,2025-03-04,861,7.6,Autonomous Tech +AI05631,AI Product Manager,133896,USD,133896,SE,FL,Sweden,S,Sweden,50,"Spark, SQL, TensorFlow, Computer Vision, Python",PhD,5,Technology,2024-11-20,2024-12-16,2374,5.1,Algorithmic Solutions +AI05632,AI Software Engineer,116023,JPY,12762530,SE,PT,Japan,M,Japan,0,"Tableau, Hadoop, Python, TensorFlow, Deep Learning",Associate,7,Finance,2024-11-09,2025-01-15,2298,5.3,Cognitive Computing +AI05633,Computer Vision Engineer,96751,USD,96751,MI,CT,United States,S,Indonesia,50,"Data Visualization, Python, Java",Bachelor,4,Energy,2025-02-07,2025-03-04,1001,9,Digital Transformation LLC +AI05634,Computer Vision Engineer,134644,EUR,114447,SE,PT,Austria,L,Brazil,50,"Kubernetes, Data Visualization, Tableau, MLOps, Deep Learning",PhD,8,Media,2025-04-25,2025-06-22,1118,6.3,Advanced Robotics +AI05635,Principal Data Scientist,102778,JPY,11305580,MI,FT,Japan,M,Kenya,50,"Spark, SQL, TensorFlow, Azure",Bachelor,2,Healthcare,2025-01-07,2025-01-27,1080,6.1,AI Innovations +AI05636,AI Product Manager,103788,USD,103788,EN,FT,Norway,M,Norway,100,"Kubernetes, TensorFlow, Azure, Tableau",PhD,1,Transportation,2024-07-09,2024-09-17,2278,9.7,Quantum Computing Inc +AI05637,Machine Learning Researcher,43133,USD,43133,EN,CT,China,L,China,100,"AWS, Hadoop, Deep Learning, PyTorch",Associate,1,Gaming,2025-03-02,2025-05-04,1800,9.8,Quantum Computing Inc +AI05638,Research Scientist,186168,EUR,158243,EX,PT,Germany,S,Germany,100,"SQL, Python, MLOps",Master,10,Healthcare,2024-07-01,2024-08-26,655,7,Algorithmic Solutions +AI05639,AI Specialist,269018,GBP,201764,EX,FT,United Kingdom,M,United Kingdom,0,"Hadoop, Deep Learning, Azure, Python, NLP",Associate,18,Real Estate,2024-08-08,2024-09-02,2032,9,DataVision Ltd +AI05640,AI Software Engineer,168038,USD,168038,SE,FL,Denmark,L,Denmark,100,"Azure, Deep Learning, Python",PhD,6,Media,2024-08-24,2024-11-03,797,9.9,Smart Analytics +AI05641,Machine Learning Engineer,63639,USD,63639,EN,FL,South Korea,M,South Korea,100,"Python, Hadoop, Linux, Computer Vision",Associate,0,Manufacturing,2024-08-08,2024-09-23,816,9.5,Algorithmic Solutions +AI05642,AI Specialist,204416,USD,204416,EX,PT,Israel,L,Canada,50,"AWS, Java, TensorFlow, Azure, SQL",Bachelor,16,Consulting,2024-02-02,2024-03-17,1641,6.1,DataVision Ltd +AI05643,AI Research Scientist,28315,USD,28315,MI,CT,India,S,India,0,"AWS, Scala, R, Git",Bachelor,3,Transportation,2024-10-31,2024-12-09,2250,6.6,Algorithmic Solutions +AI05644,Autonomous Systems Engineer,69096,USD,69096,EN,FL,United States,L,United States,100,"Git, Mathematics, TensorFlow, Linux",Bachelor,0,Consulting,2024-07-01,2024-07-28,804,5.5,Smart Analytics +AI05645,Data Analyst,72148,USD,72148,MI,FL,South Korea,L,South Korea,100,"Kubernetes, Git, MLOps, R, Computer Vision",Associate,2,Education,2025-04-12,2025-05-02,1906,7.6,Cloud AI Solutions +AI05646,Research Scientist,155411,USD,155411,SE,PT,Norway,M,Norway,100,"TensorFlow, Scala, MLOps",Bachelor,9,Gaming,2025-04-17,2025-06-23,835,5.2,TechCorp Inc +AI05647,Autonomous Systems Engineer,119240,USD,119240,MI,FL,Ireland,L,Indonesia,0,"Computer Vision, Data Visualization, Hadoop, Kubernetes, Deep Learning",Master,4,Technology,2024-01-16,2024-02-11,674,6,Smart Analytics +AI05648,Autonomous Systems Engineer,57600,USD,57600,EX,CT,India,S,Vietnam,100,"Hadoop, PyTorch, Spark",Master,10,Real Estate,2025-01-18,2025-02-19,1769,9.1,DeepTech Ventures +AI05649,Computer Vision Engineer,53542,USD,53542,EN,CT,Ireland,S,Ireland,50,"Scala, Azure, Python",PhD,0,Consulting,2025-03-24,2025-04-19,2480,8.8,Smart Analytics +AI05650,AI Consultant,151442,USD,151442,EX,PT,Finland,L,Chile,0,"Python, Spark, Computer Vision",PhD,15,Technology,2024-12-17,2025-02-25,2014,9.9,Cognitive Computing +AI05651,Data Analyst,113037,USD,113037,SE,CT,South Korea,S,Vietnam,100,"Kubernetes, PyTorch, GCP",Associate,5,Telecommunications,2024-01-26,2024-03-05,1389,7,Smart Analytics +AI05652,AI Consultant,63321,AUD,85483,EN,PT,Australia,M,Australia,50,"Data Visualization, Computer Vision, Docker, R",PhD,0,Energy,2024-03-27,2024-05-19,2054,6.5,Cloud AI Solutions +AI05653,Head of AI,216696,EUR,184192,EX,PT,Netherlands,L,Argentina,100,"R, SQL, Deep Learning, Spark, Linux",Associate,10,Energy,2024-04-11,2024-05-08,2464,5.3,Autonomous Tech +AI05654,AI Consultant,68832,CAD,86040,MI,CT,Canada,S,Canada,0,"Tableau, Linux, TensorFlow, Data Visualization, Hadoop",Bachelor,3,Telecommunications,2024-01-13,2024-01-29,2000,8.1,Predictive Systems +AI05655,AI Product Manager,125853,JPY,13843830,SE,CT,Japan,L,Japan,50,"Scala, R, Docker, Computer Vision",Bachelor,7,Finance,2024-06-17,2024-08-17,645,5.4,Future Systems +AI05656,AI Architect,90307,USD,90307,MI,FL,South Korea,L,South Korea,100,"Git, SQL, GCP, Azure",PhD,2,Telecommunications,2024-03-06,2024-05-15,1785,8.2,Digital Transformation LLC +AI05657,AI Software Engineer,208536,USD,208536,EX,CT,Norway,L,Norway,0,"Computer Vision, MLOps, Git",Bachelor,11,Consulting,2024-11-30,2025-01-27,1876,9.1,Predictive Systems +AI05658,Data Engineer,79479,USD,79479,SE,PT,China,L,Finland,50,"MLOps, PyTorch, Kubernetes",Master,9,Education,2024-02-12,2024-03-25,861,6,Algorithmic Solutions +AI05659,AI Product Manager,145587,JPY,16014570,SE,FL,Japan,S,Japan,50,"SQL, PyTorch, TensorFlow, Hadoop, Tableau",Bachelor,7,Retail,2025-03-07,2025-03-22,1397,9.9,Autonomous Tech +AI05660,Robotics Engineer,237771,USD,237771,EX,PT,South Korea,L,South Korea,50,"Linux, Python, MLOps",Bachelor,15,Education,2025-02-06,2025-04-20,1107,5.9,Quantum Computing Inc +AI05661,AI Specialist,131882,CHF,118694,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Scala, R",Associate,4,Technology,2024-04-21,2024-05-13,1742,7.2,Predictive Systems +AI05662,Principal Data Scientist,194531,USD,194531,SE,PT,Denmark,L,South Korea,100,"PyTorch, Hadoop, Tableau, Azure, TensorFlow",Associate,5,Finance,2024-07-09,2024-08-12,2058,8.9,Smart Analytics +AI05663,Robotics Engineer,170274,CHF,153247,MI,FL,Switzerland,L,Switzerland,0,"SQL, Kubernetes, Scala, Data Visualization, PyTorch",PhD,3,Consulting,2024-04-28,2024-05-22,1146,9.7,DataVision Ltd +AI05664,AI Architect,238256,GBP,178692,EX,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Java, Tableau, Deep Learning",Master,18,Healthcare,2024-01-28,2024-03-03,1005,7.2,Machine Intelligence Group +AI05665,NLP Engineer,98574,USD,98574,MI,FL,United States,S,United States,50,"GCP, Statistics, Hadoop",PhD,4,Finance,2025-03-30,2025-05-12,916,9.1,Machine Intelligence Group +AI05666,Head of AI,84725,EUR,72016,MI,PT,Germany,L,Germany,50,"Java, Scala, Hadoop, Linux, AWS",Master,3,Energy,2024-06-14,2024-07-27,1296,6.4,Quantum Computing Inc +AI05667,AI Consultant,237420,USD,237420,EX,FL,United States,L,United States,50,"PyTorch, NLP, MLOps, Mathematics, Kubernetes",Associate,17,Energy,2025-04-20,2025-06-04,2368,7.6,DataVision Ltd +AI05668,Research Scientist,94852,SGD,123308,MI,CT,Singapore,M,Singapore,0,"TensorFlow, Scala, Kubernetes, NLP, Python",PhD,3,Media,2024-12-25,2025-01-12,1503,9.1,TechCorp Inc +AI05669,NLP Engineer,53187,EUR,45209,EN,PT,Austria,M,Austria,0,"Python, Docker, NLP",Bachelor,1,Government,2024-10-02,2024-11-02,2170,8.4,Cognitive Computing +AI05670,Head of AI,85325,USD,85325,EN,FT,Norway,L,Norway,100,"MLOps, GCP, Kubernetes, Hadoop, SQL",Bachelor,0,Transportation,2024-10-16,2024-11-24,2270,9.4,Autonomous Tech +AI05671,Data Analyst,84861,EUR,72132,MI,PT,France,M,France,100,"Scala, Hadoop, Computer Vision, Data Visualization",Associate,3,Technology,2025-02-26,2025-04-29,1644,8.7,Autonomous Tech +AI05672,Machine Learning Engineer,110677,EUR,94075,MI,CT,Netherlands,M,Netherlands,0,"PyTorch, Docker, Tableau",Master,4,Consulting,2024-06-30,2024-08-16,500,7.2,Digital Transformation LLC +AI05673,Machine Learning Engineer,55583,EUR,47246,EN,FL,France,S,France,0,"Statistics, PyTorch, R",PhD,0,Healthcare,2024-04-19,2024-05-14,602,8.8,Cloud AI Solutions +AI05674,Deep Learning Engineer,103137,SGD,134078,MI,CT,Singapore,S,United Kingdom,100,"R, GCP, SQL",PhD,3,Gaming,2025-03-18,2025-04-20,546,7.8,AI Innovations +AI05675,Autonomous Systems Engineer,94118,SGD,122353,MI,FT,Singapore,M,Singapore,100,"GCP, Docker, PyTorch, SQL",Bachelor,4,Real Estate,2024-05-23,2024-06-13,1065,6.1,Future Systems +AI05676,AI Product Manager,263320,USD,263320,EX,FL,Ireland,L,Ireland,100,"Data Visualization, Azure, Git, Python, Spark",Bachelor,12,Telecommunications,2025-03-11,2025-05-21,1510,8.9,Predictive Systems +AI05677,Principal Data Scientist,81751,USD,81751,EX,FT,China,S,Indonesia,50,"Statistics, Data Visualization, SQL, Python, Tableau",PhD,19,Real Estate,2024-01-16,2024-03-20,2349,9.8,DeepTech Ventures +AI05678,AI Product Manager,69515,USD,69515,EN,PT,Israel,M,Japan,100,"Python, SQL, Tableau, R, AWS",Master,1,Government,2024-05-14,2024-06-03,1662,6,TechCorp Inc +AI05679,AI Consultant,102539,USD,102539,SE,PT,Ireland,M,New Zealand,50,"Linux, TensorFlow, PyTorch, Data Visualization",Associate,7,Technology,2024-06-29,2024-08-26,1816,9.1,Neural Networks Co +AI05680,AI Consultant,83366,EUR,70861,MI,PT,Germany,M,Germany,50,"Python, Computer Vision, AWS",Associate,3,Telecommunications,2024-11-28,2025-01-28,1453,5.1,Digital Transformation LLC +AI05681,Data Analyst,103994,JPY,11439340,MI,CT,Japan,S,Japan,50,"Linux, Scala, R",Bachelor,3,Energy,2025-04-03,2025-05-27,1046,7.6,TechCorp Inc +AI05682,AI Specialist,63790,USD,63790,EN,PT,Ireland,M,Ireland,0,"SQL, Spark, Computer Vision",Associate,1,Technology,2024-05-14,2024-07-11,1573,8,Algorithmic Solutions +AI05683,Computer Vision Engineer,223100,EUR,189635,EX,PT,Netherlands,S,Thailand,100,"AWS, Data Visualization, Tableau, Hadoop, Statistics",Associate,12,Finance,2024-09-23,2024-11-18,698,6.7,Predictive Systems +AI05684,Robotics Engineer,60827,USD,60827,EN,FT,Sweden,S,Sweden,100,"Scala, Spark, Kubernetes, Docker, NLP",Associate,0,Manufacturing,2024-03-04,2024-03-21,1247,7.5,AI Innovations +AI05685,AI Architect,77717,USD,77717,MI,FT,United States,S,Mexico,0,"Hadoop, Scala, TensorFlow",Master,3,Transportation,2024-03-08,2024-05-13,1519,9.4,Machine Intelligence Group +AI05686,Machine Learning Engineer,97963,USD,97963,MI,CT,South Korea,L,Kenya,100,"Git, TensorFlow, Tableau, Data Visualization",Associate,3,Energy,2024-12-13,2025-01-05,2218,5.8,Cognitive Computing +AI05687,Data Engineer,214315,USD,214315,EX,PT,United States,M,United States,0,"PyTorch, Azure, Kubernetes, Deep Learning, TensorFlow",Associate,18,Media,2024-11-08,2024-12-25,1940,6.2,Quantum Computing Inc +AI05688,Autonomous Systems Engineer,71291,USD,71291,EN,FL,Denmark,M,Denmark,100,"Docker, Scala, AWS, Python",Master,0,Consulting,2024-07-27,2024-08-31,1540,9.6,Quantum Computing Inc +AI05689,Data Scientist,87518,USD,87518,EN,CT,United States,L,Vietnam,0,"AWS, PyTorch, Scala, Hadoop",Bachelor,1,Healthcare,2024-12-13,2025-01-04,906,5.9,AI Innovations +AI05690,Machine Learning Researcher,149558,USD,149558,SE,FL,United States,S,United States,0,"Azure, SQL, TensorFlow, Kubernetes",Bachelor,5,Media,2024-07-27,2024-09-12,2478,7.1,AI Innovations +AI05691,AI Consultant,107945,AUD,145726,MI,FT,Australia,M,Australia,0,"Hadoop, Computer Vision, Kubernetes, Tableau, Azure",PhD,2,Manufacturing,2024-04-25,2024-07-02,2267,5.8,Autonomous Tech +AI05692,Machine Learning Engineer,63957,USD,63957,EX,FT,China,S,Australia,50,"Linux, Tableau, TensorFlow, Computer Vision",PhD,12,Education,2024-02-01,2024-03-24,2482,9.6,Autonomous Tech +AI05693,AI Architect,93563,EUR,79529,MI,CT,Germany,S,Germany,0,"Data Visualization, Python, SQL, Kubernetes",Associate,3,Media,2024-06-24,2024-08-24,953,9,Cloud AI Solutions +AI05694,AI Research Scientist,161134,EUR,136964,SE,FT,France,L,France,100,"R, Data Visualization, Python, Docker",PhD,6,Real Estate,2024-08-04,2024-09-01,2303,5.8,Machine Intelligence Group +AI05695,Principal Data Scientist,212931,CAD,266164,EX,FT,Canada,S,New Zealand,0,"SQL, Linux, Python",Master,12,Technology,2024-04-13,2024-05-18,1452,6.8,TechCorp Inc +AI05696,AI Product Manager,119167,USD,119167,MI,CT,Denmark,M,Denmark,100,"Linux, Azure, MLOps, Kubernetes",Master,2,Automotive,2024-04-27,2024-06-12,1621,9.3,DataVision Ltd +AI05697,Head of AI,102382,USD,102382,EN,FT,Denmark,M,Denmark,100,"Tableau, Spark, NLP, PyTorch, Computer Vision",PhD,1,Government,2025-02-21,2025-05-02,1096,5.2,Predictive Systems +AI05698,AI Specialist,69931,USD,69931,MI,PT,Finland,S,Finland,100,"Kubernetes, GCP, Computer Vision, AWS",PhD,4,Transportation,2025-03-25,2025-05-23,1511,5.2,Predictive Systems +AI05699,Autonomous Systems Engineer,61743,SGD,80266,EN,CT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Tableau",PhD,1,Technology,2024-11-28,2025-01-03,1091,10,Predictive Systems +AI05700,AI Product Manager,70132,AUD,94678,MI,FT,Australia,S,Australia,50,"Scala, Data Visualization, Docker, R",Associate,4,Transportation,2024-01-12,2024-02-23,2242,5.7,Digital Transformation LLC +AI05701,Robotics Engineer,96886,JPY,10657460,MI,FT,Japan,S,Japan,0,"Git, Hadoop, SQL, Python, Kubernetes",Master,3,Consulting,2024-03-13,2024-05-22,1366,8.7,Future Systems +AI05702,AI Research Scientist,200782,EUR,170665,EX,PT,Netherlands,M,Switzerland,50,"Linux, Java, Kubernetes, TensorFlow",PhD,15,Consulting,2025-03-07,2025-05-13,840,5.2,Digital Transformation LLC +AI05703,Data Analyst,23579,USD,23579,EN,FL,India,L,India,50,"Java, PyTorch, Statistics, Deep Learning",Associate,0,Transportation,2025-02-04,2025-03-03,1565,9.2,Cloud AI Solutions +AI05704,NLP Engineer,55614,AUD,75079,EN,PT,Australia,M,Australia,0,"Java, Hadoop, NLP, Linux",Bachelor,1,Consulting,2024-12-16,2025-02-18,2492,8,Algorithmic Solutions +AI05705,AI Product Manager,150781,EUR,128164,SE,FL,Germany,M,Nigeria,100,"Spark, Tableau, Hadoop, Computer Vision",Master,5,Retail,2024-07-22,2024-09-02,1421,5.3,Cognitive Computing +AI05706,AI Specialist,131468,EUR,111748,SE,CT,Austria,L,Luxembourg,0,"Kubernetes, PyTorch, MLOps, GCP, R",Master,8,Technology,2024-12-27,2025-01-31,2220,8.5,Advanced Robotics +AI05707,Deep Learning Engineer,72393,EUR,61534,EN,FT,France,M,France,0,"PyTorch, Kubernetes, SQL, Scala",Bachelor,1,Energy,2024-02-10,2024-03-22,2211,9.4,Cloud AI Solutions +AI05708,NLP Engineer,139017,USD,139017,SE,PT,Sweden,L,Sweden,100,"MLOps, Computer Vision, R, PyTorch",Associate,5,Manufacturing,2025-02-27,2025-05-02,1808,9.8,Autonomous Tech +AI05709,Principal Data Scientist,112229,USD,112229,MI,FL,Denmark,S,Denmark,50,"Scala, GCP, SQL, Hadoop, Data Visualization",Bachelor,4,Technology,2024-03-03,2024-05-13,702,8.6,Digital Transformation LLC +AI05710,ML Ops Engineer,88643,USD,88643,MI,FL,South Korea,M,South Korea,100,"MLOps, Data Visualization, Azure, AWS",Associate,4,Manufacturing,2024-12-20,2025-01-16,2308,7.5,Cognitive Computing +AI05711,Head of AI,119522,USD,119522,MI,CT,Denmark,S,United States,0,"Deep Learning, Docker, Git, Mathematics",Associate,4,Finance,2025-01-09,2025-03-08,1799,5.9,Predictive Systems +AI05712,NLP Engineer,146464,EUR,124494,SE,CT,Netherlands,M,Denmark,100,"MLOps, AWS, SQL",PhD,6,Real Estate,2024-05-24,2024-07-21,2415,9.5,Cloud AI Solutions +AI05713,Data Scientist,98192,CAD,122740,SE,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP, R, Computer Vision",PhD,6,Telecommunications,2024-07-25,2024-08-11,1143,9.1,Cloud AI Solutions +AI05714,Machine Learning Engineer,80479,USD,80479,EN,FT,Norway,L,Norway,100,"Kubernetes, NLP, Spark, Deep Learning",Associate,1,Healthcare,2025-04-26,2025-07-02,1630,8.7,Future Systems +AI05715,Data Engineer,152265,EUR,129425,EX,FT,Netherlands,S,Netherlands,50,"MLOps, Python, Computer Vision, Linux, TensorFlow",Master,12,Media,2025-04-16,2025-05-25,1049,9.7,AI Innovations +AI05716,AI Software Engineer,77835,USD,77835,EN,FT,Norway,S,Norway,0,"Azure, Python, GCP, TensorFlow",PhD,1,Technology,2024-01-10,2024-03-11,1316,5.8,Quantum Computing Inc +AI05717,AI Architect,63922,JPY,7031420,EN,FT,Japan,L,Japan,50,"NLP, Python, TensorFlow, Linux",Master,1,Energy,2025-04-21,2025-05-12,1569,8.7,AI Innovations +AI05718,NLP Engineer,257100,JPY,28281000,EX,FL,Japan,L,Finland,0,"TensorFlow, Tableau, Docker, NLP",Associate,15,Automotive,2025-02-04,2025-04-12,876,9.3,DeepTech Ventures +AI05719,Deep Learning Engineer,88350,USD,88350,MI,FT,Finland,L,China,50,"Python, Linux, Statistics, Computer Vision",Associate,4,Transportation,2024-07-04,2024-08-20,986,7.7,Neural Networks Co +AI05720,AI Specialist,99465,USD,99465,MI,FL,Denmark,S,France,50,"GCP, Data Visualization, Spark, R",Bachelor,4,Government,2025-03-31,2025-05-09,1730,5.3,Algorithmic Solutions +AI05721,NLP Engineer,179088,USD,179088,EX,CT,Norway,S,Romania,50,"Python, SQL, Deep Learning, Git, Docker",Bachelor,14,Media,2024-07-11,2024-07-26,1923,8.1,Predictive Systems +AI05722,Data Engineer,159540,USD,159540,SE,FT,Denmark,L,Denmark,100,"Mathematics, Git, NLP",Associate,6,Energy,2024-10-06,2024-11-16,1350,9,AI Innovations +AI05723,Deep Learning Engineer,37477,USD,37477,MI,FT,India,M,India,50,"Spark, Scala, Linux, Deep Learning, SQL",PhD,2,Automotive,2024-05-24,2024-07-26,2369,9.3,Predictive Systems +AI05724,Research Scientist,133739,SGD,173861,MI,PT,Singapore,L,Russia,0,"Computer Vision, AWS, Kubernetes",Associate,4,Education,2025-02-08,2025-02-28,865,7.1,Advanced Robotics +AI05725,AI Research Scientist,373674,CHF,336307,EX,FT,Switzerland,L,Switzerland,50,"R, Python, Statistics, Scala, Deep Learning",Associate,16,Automotive,2024-04-19,2024-05-21,626,9.6,Cloud AI Solutions +AI05726,Head of AI,57593,USD,57593,MI,PT,South Korea,S,China,100,"Docker, Linux, AWS, Scala",Associate,3,Retail,2024-11-01,2024-12-15,1985,8.3,TechCorp Inc +AI05727,Machine Learning Researcher,62998,USD,62998,SE,FT,China,S,China,0,"Statistics, Scala, NLP, MLOps, Azure",Bachelor,7,Real Estate,2024-12-01,2025-02-01,1256,7.4,Machine Intelligence Group +AI05728,Research Scientist,99028,SGD,128736,SE,CT,Singapore,S,Singapore,100,"Docker, Spark, AWS",PhD,5,Retail,2024-12-26,2025-01-29,1673,9.8,Advanced Robotics +AI05729,Data Analyst,283076,USD,283076,EX,CT,Norway,S,Norway,50,"NLP, Deep Learning, Spark, MLOps",Master,15,Finance,2024-01-19,2024-02-05,1350,7.5,Cloud AI Solutions +AI05730,Data Scientist,77013,USD,77013,MI,FL,South Korea,L,South Korea,0,"Statistics, Mathematics, Java",Master,2,Retail,2024-10-12,2024-11-16,916,7.2,TechCorp Inc +AI05731,Computer Vision Engineer,88457,USD,88457,MI,FT,South Korea,L,South Korea,100,"Python, Kubernetes, Spark, GCP",Master,4,Healthcare,2024-09-01,2024-09-19,2182,5.6,Cognitive Computing +AI05732,Machine Learning Researcher,99330,USD,99330,MI,CT,South Korea,L,South Korea,0,"Computer Vision, GCP, Kubernetes, SQL",Bachelor,4,Government,2024-10-21,2024-11-27,2415,9.3,AI Innovations +AI05733,Data Scientist,65665,USD,65665,EN,CT,Israel,S,Israel,0,"Python, Azure, Statistics",PhD,1,Government,2024-10-29,2024-12-23,1506,7.6,Autonomous Tech +AI05734,AI Architect,92187,USD,92187,MI,FT,Israel,M,Israel,0,"Hadoop, NLP, MLOps",PhD,3,Manufacturing,2024-02-20,2024-04-23,1555,5.9,Smart Analytics +AI05735,ML Ops Engineer,72655,USD,72655,MI,FT,Israel,M,Israel,100,"GCP, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2024-11-02,2024-12-22,1742,6.7,DeepTech Ventures +AI05736,ML Ops Engineer,117047,CAD,146309,SE,FL,Canada,M,Canada,100,"Linux, SQL, Computer Vision, Kubernetes, PyTorch",Bachelor,6,Healthcare,2024-07-03,2024-09-06,2314,9,TechCorp Inc +AI05737,Data Analyst,66295,USD,66295,EN,FT,Israel,L,Israel,50,"GCP, Linux, Spark",Master,1,Media,2025-02-12,2025-04-10,1387,5.2,Neural Networks Co +AI05738,AI Specialist,159977,USD,159977,SE,CT,United States,L,United States,100,"SQL, Docker, Mathematics, Computer Vision, AWS",Associate,9,Finance,2025-04-13,2025-06-13,1434,9,Cognitive Computing +AI05739,ML Ops Engineer,213245,EUR,181258,EX,CT,Netherlands,S,Netherlands,100,"SQL, Hadoop, Tableau",Bachelor,17,Finance,2025-03-21,2025-04-22,1998,9,DeepTech Ventures +AI05740,Head of AI,119945,EUR,101953,EX,CT,Austria,S,United States,50,"Java, SQL, Git, Docker",PhD,10,Transportation,2024-02-13,2024-03-11,1193,6.3,Algorithmic Solutions +AI05741,Robotics Engineer,216153,USD,216153,EX,PT,Finland,L,Nigeria,100,"TensorFlow, Python, Data Visualization, Statistics",Master,10,Retail,2024-07-03,2024-07-22,2438,8.4,Smart Analytics +AI05742,Data Analyst,40020,USD,40020,MI,FT,India,L,India,50,"Python, SQL, Computer Vision, Git, Linux",Master,4,Healthcare,2025-03-14,2025-05-26,666,5.6,Neural Networks Co +AI05743,AI Architect,92086,CAD,115108,MI,CT,Canada,L,Switzerland,0,"NLP, Kubernetes, Python, Git",PhD,2,Consulting,2024-04-28,2024-06-23,1486,8.5,Predictive Systems +AI05744,AI Product Manager,200654,GBP,150491,EX,FT,United Kingdom,M,Luxembourg,100,"Git, Java, Scala",Master,19,Consulting,2024-12-13,2025-02-04,1872,9.7,TechCorp Inc +AI05745,Computer Vision Engineer,68829,USD,68829,EN,CT,United States,S,United States,100,"Scala, Hadoop, TensorFlow",PhD,1,Gaming,2024-10-27,2024-12-04,1492,9.3,Cognitive Computing +AI05746,Head of AI,197686,USD,197686,EX,CT,Norway,M,Norway,50,"Kubernetes, Docker, Data Visualization, Git, Hadoop",PhD,17,Energy,2024-03-03,2024-04-24,2251,5.2,Advanced Robotics +AI05747,AI Product Manager,165557,USD,165557,EX,PT,Finland,M,Finland,0,"TensorFlow, Spark, Tableau, Computer Vision, MLOps",Associate,12,Retail,2025-03-19,2025-05-30,1803,5.4,Smart Analytics +AI05748,AI Architect,66906,USD,66906,EN,CT,Ireland,S,Argentina,100,"Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-12-13,2025-02-19,1384,8.8,TechCorp Inc +AI05749,AI Software Engineer,59768,USD,59768,EX,FT,China,S,China,100,"SQL, Linux, Git, Mathematics",PhD,16,Consulting,2024-07-11,2024-08-27,793,8.3,Cognitive Computing +AI05750,AI Architect,139169,GBP,104377,SE,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, GCP, Computer Vision, Azure, Kubernetes",Associate,7,Transportation,2024-08-22,2024-09-10,1739,10,Future Systems +AI05751,NLP Engineer,177662,JPY,19542820,EX,FL,Japan,L,Japan,50,"MLOps, Statistics, PyTorch, Spark, Java",PhD,14,Transportation,2025-02-13,2025-03-14,1326,8.3,Machine Intelligence Group +AI05752,ML Ops Engineer,81894,JPY,9008340,MI,FL,Japan,S,Turkey,0,"Python, TensorFlow, Docker, Mathematics",PhD,2,Manufacturing,2024-12-30,2025-01-24,808,9.2,AI Innovations +AI05753,Computer Vision Engineer,213516,USD,213516,EX,PT,Israel,L,Japan,50,"AWS, Docker, Mathematics, Python",Associate,10,Automotive,2024-12-03,2025-02-11,907,7.4,Algorithmic Solutions +AI05754,Deep Learning Engineer,231165,EUR,196490,EX,FL,Austria,M,Sweden,0,"Python, SQL, Azure",Master,17,Energy,2025-02-03,2025-03-01,1994,9.8,Machine Intelligence Group +AI05755,AI Specialist,110726,AUD,149480,SE,PT,Australia,S,Estonia,50,"Deep Learning, Java, NLP",PhD,8,Transportation,2024-04-27,2024-05-14,2129,5.1,Neural Networks Co +AI05756,Research Scientist,83571,USD,83571,EX,PT,China,L,China,50,"MLOps, PyTorch, Git, Scala, Linux",Master,18,Finance,2024-02-25,2024-04-13,2311,8,Predictive Systems +AI05757,NLP Engineer,232736,USD,232736,EX,FT,Denmark,M,Denmark,0,"Hadoop, Deep Learning, NLP, Python, TensorFlow",Master,17,Healthcare,2024-10-06,2024-12-08,577,6.9,Neural Networks Co +AI05758,Robotics Engineer,127623,AUD,172291,SE,CT,Australia,S,Australia,50,"Data Visualization, Kubernetes, Java, Deep Learning, Docker",Bachelor,7,Transportation,2024-09-21,2024-11-05,2226,6.7,TechCorp Inc +AI05759,Computer Vision Engineer,120233,USD,120233,MI,CT,United States,M,United States,100,"Python, R, Tableau, AWS, Hadoop",Bachelor,4,Consulting,2025-01-25,2025-03-04,2398,8.8,Neural Networks Co +AI05760,NLP Engineer,138054,CAD,172568,EX,FL,Canada,M,Canada,0,"Spark, TensorFlow, PyTorch, NLP, Docker",Master,11,Manufacturing,2024-11-10,2024-12-08,2103,10,Machine Intelligence Group +AI05761,AI Specialist,217066,USD,217066,EX,FL,United States,M,Ukraine,100,"GCP, Scala, Data Visualization",PhD,14,Gaming,2025-01-09,2025-02-23,1157,8.5,Algorithmic Solutions +AI05762,Data Analyst,210737,USD,210737,EX,CT,Israel,S,Sweden,50,"Statistics, Mathematics, PyTorch, AWS, Computer Vision",PhD,10,Government,2024-01-22,2024-04-03,2498,8,Machine Intelligence Group +AI05763,Research Scientist,69613,SGD,90497,EN,PT,Singapore,L,Singapore,50,"Python, GCP, Azure",Master,1,Automotive,2024-03-22,2024-05-16,1729,8.4,Algorithmic Solutions +AI05764,AI Product Manager,93437,USD,93437,MI,FL,Finland,M,Finland,50,"Kubernetes, Python, Mathematics, Docker",PhD,3,Healthcare,2025-01-03,2025-02-24,1095,9.6,Future Systems +AI05765,AI Architect,111139,CHF,100025,MI,FT,Switzerland,M,Czech Republic,100,"Kubernetes, Azure, Data Visualization, Python",Bachelor,2,Retail,2024-01-28,2024-03-14,690,7.8,TechCorp Inc +AI05766,AI Architect,91789,EUR,78021,SE,CT,France,S,Belgium,50,"NLP, SQL, Python, TensorFlow",PhD,6,Manufacturing,2024-07-01,2024-07-21,2003,7.1,TechCorp Inc +AI05767,Deep Learning Engineer,103244,AUD,139379,SE,CT,Australia,M,Australia,50,"Python, TensorFlow, Spark, GCP",Bachelor,5,Finance,2024-07-21,2024-08-08,601,6.1,Future Systems +AI05768,Data Analyst,134116,USD,134116,SE,CT,South Korea,L,South Korea,50,"GCP, Git, Java",Associate,9,Retail,2024-07-27,2024-09-22,2148,9.4,Autonomous Tech +AI05769,Machine Learning Engineer,97581,USD,97581,EX,FT,China,M,China,50,"Spark, AWS, Deep Learning",Associate,10,Retail,2024-06-18,2024-07-12,1179,8.8,Neural Networks Co +AI05770,Autonomous Systems Engineer,62705,USD,62705,SE,FT,China,M,China,100,"Java, PyTorch, AWS, Spark",Associate,8,Media,2024-05-11,2024-06-07,1072,6.8,Autonomous Tech +AI05771,Principal Data Scientist,101330,EUR,86131,MI,CT,Netherlands,M,Netherlands,100,"Kubernetes, AWS, Spark, Computer Vision",Bachelor,2,Retail,2024-12-07,2025-02-01,2469,8.4,Algorithmic Solutions +AI05772,Deep Learning Engineer,96335,USD,96335,MI,FT,Norway,M,Norway,0,"Linux, AWS, Git, Scala",Associate,4,Gaming,2024-06-16,2024-08-18,1862,6.3,Digital Transformation LLC +AI05773,Research Scientist,139068,USD,139068,MI,CT,Norway,L,Norway,50,"PyTorch, Spark, TensorFlow, Deep Learning",Master,4,Telecommunications,2024-10-10,2024-10-25,1147,9.1,Algorithmic Solutions +AI05774,AI Architect,70157,USD,70157,EN,FL,United States,S,Vietnam,100,"Spark, Python, Docker, Tableau",PhD,0,Media,2024-08-31,2024-11-12,623,9.2,Algorithmic Solutions +AI05775,AI Specialist,74222,EUR,63089,MI,CT,Germany,M,Ireland,50,"Data Visualization, Tableau, Computer Vision",Associate,3,Consulting,2024-03-27,2024-04-20,1609,8.5,Quantum Computing Inc +AI05776,Autonomous Systems Engineer,53889,USD,53889,SE,CT,India,M,India,50,"NLP, Python, PyTorch, AWS",PhD,9,Manufacturing,2024-12-13,2025-02-06,1295,7.1,TechCorp Inc +AI05777,AI Consultant,59745,AUD,80656,EN,PT,Australia,S,Australia,0,"AWS, Data Visualization, Linux",PhD,1,Real Estate,2025-01-21,2025-03-04,2003,6.5,Smart Analytics +AI05778,Machine Learning Engineer,93809,USD,93809,MI,CT,Denmark,M,Denmark,0,"SQL, PyTorch, GCP, R, Linux",Bachelor,4,Government,2024-09-07,2024-10-10,500,8.2,Predictive Systems +AI05779,Research Scientist,56388,EUR,47930,EN,FL,Austria,L,South Korea,100,"Data Visualization, Computer Vision, GCP, TensorFlow, Tableau",Associate,1,Real Estate,2024-05-20,2024-07-16,733,8.8,Smart Analytics +AI05780,Machine Learning Researcher,73376,USD,73376,EX,FT,China,S,China,0,"Computer Vision, Git, Hadoop, NLP, Linux",PhD,16,Energy,2024-06-18,2024-07-02,1032,5.5,Digital Transformation LLC +AI05781,NLP Engineer,246014,USD,246014,EX,PT,Finland,L,Finland,0,"AWS, Kubernetes, Git, Java",Bachelor,11,Education,2024-03-09,2024-04-11,1900,8.7,DataVision Ltd +AI05782,Data Engineer,75181,CAD,93976,MI,FT,Canada,M,Canada,100,"Spark, NLP, Python, TensorFlow",Master,4,Finance,2024-12-06,2025-02-06,936,9.9,Cloud AI Solutions +AI05783,Research Scientist,175703,USD,175703,EX,PT,Israel,M,Thailand,0,"Git, Spark, Data Visualization, SQL",Bachelor,16,Retail,2024-07-18,2024-09-04,1971,8.4,TechCorp Inc +AI05784,Deep Learning Engineer,120364,CAD,150455,SE,FT,Canada,M,Portugal,100,"NLP, TensorFlow, Scala",PhD,7,Technology,2024-08-23,2024-10-24,635,5.7,DeepTech Ventures +AI05785,Computer Vision Engineer,76445,USD,76445,MI,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Hadoop, NLP, Statistics",Bachelor,2,Government,2024-06-30,2024-08-24,787,9.2,Digital Transformation LLC +AI05786,AI Software Engineer,93159,CHF,83843,EN,PT,Switzerland,M,Switzerland,50,"Scala, Azure, GCP, SQL, Mathematics",PhD,0,Government,2024-10-20,2024-12-20,1154,8.3,Advanced Robotics +AI05787,Machine Learning Researcher,157430,EUR,133816,SE,FT,Germany,L,Italy,0,"SQL, Spark, TensorFlow, Linux",PhD,5,Real Estate,2024-07-15,2024-09-09,1632,9.9,Predictive Systems +AI05788,NLP Engineer,97775,EUR,83109,MI,FL,Germany,L,Germany,100,"Spark, Statistics, Git",Associate,2,Education,2025-01-05,2025-03-17,1419,8.2,Quantum Computing Inc +AI05789,NLP Engineer,59315,USD,59315,EN,FT,Sweden,S,Thailand,50,"R, Linux, Tableau, Kubernetes, AWS",Bachelor,0,Education,2024-05-24,2024-08-01,2125,9.9,Neural Networks Co +AI05790,AI Product Manager,135321,EUR,115023,SE,FT,France,L,France,50,"Hadoop, Python, Mathematics, Data Visualization",Bachelor,8,Transportation,2024-04-17,2024-06-01,1089,8.6,Smart Analytics +AI05791,AI Software Engineer,54243,SGD,70516,EN,PT,Singapore,S,Czech Republic,100,"TensorFlow, Tableau, Mathematics",Bachelor,0,Telecommunications,2024-01-17,2024-02-11,1715,9,Algorithmic Solutions +AI05792,AI Architect,66510,SGD,86463,EN,PT,Singapore,L,Singapore,0,"NLP, Linux, Statistics",Bachelor,0,Government,2025-02-10,2025-04-16,890,8.8,Autonomous Tech +AI05793,Data Engineer,290571,USD,290571,EX,CT,Norway,M,Norway,50,"R, TensorFlow, Git",Bachelor,11,Healthcare,2024-07-26,2024-08-12,1050,5.6,Cognitive Computing +AI05794,Machine Learning Researcher,174210,USD,174210,SE,CT,United States,L,United States,50,"Java, GCP, Hadoop, Deep Learning",Associate,6,Telecommunications,2024-11-09,2024-12-17,718,5.2,DataVision Ltd +AI05795,Autonomous Systems Engineer,187877,USD,187877,SE,FL,United States,L,Latvia,100,"Git, Data Visualization, SQL",PhD,8,Technology,2024-06-23,2024-07-29,1005,7.8,Cognitive Computing +AI05796,AI Product Manager,238675,EUR,202874,EX,CT,Netherlands,M,Netherlands,100,"Git, Data Visualization, Spark, R, Computer Vision",PhD,12,Energy,2025-01-09,2025-02-26,1576,7.2,Algorithmic Solutions +AI05797,Machine Learning Researcher,115479,EUR,98157,SE,CT,France,L,France,100,"Deep Learning, Azure, PyTorch, Kubernetes",Associate,8,Government,2025-01-01,2025-01-19,883,8.1,Algorithmic Solutions +AI05798,AI Consultant,89054,USD,89054,MI,CT,United States,S,United States,0,"Git, SQL, PyTorch",Associate,3,Healthcare,2024-10-22,2024-11-23,1689,9.2,AI Innovations +AI05799,Deep Learning Engineer,161406,USD,161406,SE,CT,Israel,L,Israel,0,"AWS, Computer Vision, MLOps, Python, Mathematics",Master,5,Finance,2024-03-30,2024-06-04,911,6.6,Advanced Robotics +AI05800,AI Research Scientist,64215,GBP,48161,EN,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, Mathematics, GCP, Scala, NLP",Bachelor,0,Automotive,2024-03-30,2024-05-26,1193,5.7,Future Systems +AI05801,Autonomous Systems Engineer,64511,USD,64511,MI,FL,South Korea,M,Vietnam,100,"Python, TensorFlow, Spark, PyTorch",Associate,4,Real Estate,2024-02-19,2024-04-30,1416,8.6,Digital Transformation LLC +AI05802,Autonomous Systems Engineer,126060,USD,126060,EX,CT,China,L,China,50,"Scala, Docker, GCP, Git",Associate,18,Real Estate,2024-06-27,2024-09-04,2144,6.8,Algorithmic Solutions +AI05803,Autonomous Systems Engineer,54920,USD,54920,EN,CT,South Korea,S,Norway,0,"Data Visualization, Python, Docker, Java",PhD,1,Real Estate,2024-03-28,2024-04-22,510,9,DeepTech Ventures +AI05804,AI Research Scientist,266720,GBP,200040,EX,CT,United Kingdom,M,Hungary,0,"Kubernetes, SQL, Docker, Tableau",Bachelor,16,Telecommunications,2024-04-08,2024-05-19,1513,7.1,DeepTech Ventures +AI05805,Principal Data Scientist,54944,AUD,74174,EN,FL,Australia,M,Australia,50,"Azure, Spark, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-02-10,2024-03-08,708,6.3,DeepTech Ventures +AI05806,AI Product Manager,152987,USD,152987,SE,FL,Norway,S,Norway,100,"NLP, MLOps, Data Visualization",Associate,6,Government,2024-03-09,2024-04-10,1687,8.5,Quantum Computing Inc +AI05807,AI Consultant,158814,CHF,142933,SE,CT,Switzerland,M,Switzerland,50,"Azure, Kubernetes, Linux, Docker, Mathematics",Bachelor,8,Retail,2024-12-27,2025-03-10,1650,9.7,Advanced Robotics +AI05808,AI Software Engineer,92910,USD,92910,EX,CT,China,S,India,100,"MLOps, Hadoop, Spark, Deep Learning, Python",Bachelor,15,Consulting,2024-03-19,2024-04-26,1516,8.9,Machine Intelligence Group +AI05809,Autonomous Systems Engineer,209901,USD,209901,EX,CT,Denmark,L,Denmark,50,"Scala, Java, Azure, Deep Learning",Associate,13,Manufacturing,2024-01-05,2024-02-27,761,6.8,Smart Analytics +AI05810,Computer Vision Engineer,82999,AUD,112049,EN,FL,Australia,L,Australia,0,"Scala, Statistics, Data Visualization",Master,0,Telecommunications,2024-05-28,2024-06-23,2391,9.1,TechCorp Inc +AI05811,Computer Vision Engineer,28848,USD,28848,EN,CT,China,L,Ukraine,50,"Docker, Scala, Linux, Java",Bachelor,1,Energy,2024-03-13,2024-05-21,2267,6.6,Autonomous Tech +AI05812,Computer Vision Engineer,65556,AUD,88501,EN,PT,Australia,M,Latvia,100,"Kubernetes, Java, NLP, AWS",Master,1,Gaming,2024-03-11,2024-04-18,1984,7.5,DataVision Ltd +AI05813,Autonomous Systems Engineer,130176,USD,130176,SE,PT,United States,M,United States,0,"TensorFlow, Spark, Git, Java, AWS",Associate,6,Government,2025-01-31,2025-03-08,789,6.5,Predictive Systems +AI05814,Principal Data Scientist,101126,USD,101126,SE,FT,Finland,M,Philippines,0,"Kubernetes, Docker, SQL, PyTorch",Associate,9,Automotive,2025-01-29,2025-04-11,2420,8.2,Future Systems +AI05815,NLP Engineer,116327,USD,116327,SE,CT,United States,S,United States,100,"SQL, MLOps, Java, AWS, TensorFlow",Bachelor,7,Telecommunications,2024-03-03,2024-03-31,1709,7.6,Cloud AI Solutions +AI05816,AI Consultant,70463,EUR,59894,MI,PT,Austria,M,Japan,100,"Scala, Hadoop, Git, Azure, MLOps",Bachelor,3,Healthcare,2024-07-27,2024-08-23,1950,8.2,Autonomous Tech +AI05817,Machine Learning Engineer,66266,CAD,82833,EN,CT,Canada,M,Canada,0,"Tableau, Python, Kubernetes, Mathematics",Bachelor,1,Telecommunications,2024-12-16,2025-01-09,986,8.2,Quantum Computing Inc +AI05818,Head of AI,61462,EUR,52243,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Python, Spark",Associate,1,Manufacturing,2024-08-25,2024-10-14,1730,8.2,Digital Transformation LLC +AI05819,ML Ops Engineer,169366,USD,169366,EX,PT,Sweden,S,Brazil,50,"GCP, Spark, Tableau",Associate,18,Automotive,2024-12-15,2025-02-01,1988,9.5,Quantum Computing Inc +AI05820,Computer Vision Engineer,128994,JPY,14189340,SE,FL,Japan,L,Japan,100,"PyTorch, Mathematics, Azure",Associate,9,Technology,2024-09-19,2024-10-30,1049,7.5,Algorithmic Solutions +AI05821,Machine Learning Engineer,93837,USD,93837,EN,FT,Norway,M,Norway,50,"Scala, AWS, MLOps",PhD,0,Transportation,2025-02-16,2025-04-11,1859,8.1,Advanced Robotics +AI05822,Robotics Engineer,199989,AUD,269985,EX,FL,Australia,M,Australia,50,"Tableau, Azure, NLP, Linux, Python",Master,11,Technology,2024-10-20,2024-12-26,1214,9.7,Digital Transformation LLC +AI05823,Research Scientist,120387,EUR,102329,SE,FL,France,M,France,0,"Linux, SQL, NLP, PyTorch, Hadoop",Associate,8,Finance,2025-01-17,2025-03-22,2031,6.2,Algorithmic Solutions +AI05824,AI Consultant,73237,EUR,62251,EN,CT,Netherlands,M,Netherlands,100,"MLOps, Hadoop, Scala, Computer Vision, TensorFlow",PhD,1,Energy,2024-03-06,2024-04-10,898,7.5,Predictive Systems +AI05825,Robotics Engineer,201799,EUR,171529,EX,CT,Germany,M,Germany,0,"AWS, PyTorch, Mathematics, TensorFlow",Bachelor,19,Gaming,2024-07-28,2024-08-14,1838,9.7,AI Innovations +AI05826,Deep Learning Engineer,134094,USD,134094,EX,FL,South Korea,S,South Korea,100,"Spark, Tableau, SQL, PyTorch, Computer Vision",Bachelor,15,Education,2024-01-08,2024-02-16,1396,5.3,Algorithmic Solutions +AI05827,Machine Learning Engineer,93152,CHF,83837,MI,CT,Switzerland,S,Norway,0,"TensorFlow, AWS, Spark, Statistics",Associate,4,Finance,2024-08-30,2024-09-15,1329,7.2,Cognitive Computing +AI05828,AI Consultant,50681,CAD,63351,EN,FL,Canada,S,Canada,50,"MLOps, Deep Learning, Linux, Hadoop",PhD,0,Education,2024-03-18,2024-04-17,640,6.9,Smart Analytics +AI05829,Autonomous Systems Engineer,153066,EUR,130106,SE,CT,Netherlands,L,Netherlands,0,"Docker, Computer Vision, Azure, Tableau",Associate,7,Education,2025-02-06,2025-04-06,2226,7.4,Smart Analytics +AI05830,Data Scientist,113891,USD,113891,MI,FT,Norway,L,Germany,0,"Docker, Statistics, Git, Spark",Master,4,Healthcare,2024-01-30,2024-03-15,1612,9.8,Digital Transformation LLC +AI05831,Machine Learning Engineer,182667,CAD,228334,EX,FL,Canada,S,Canada,50,"Data Visualization, Scala, Python, Tableau",PhD,19,Education,2024-02-06,2024-03-27,693,8.4,DeepTech Ventures +AI05832,Deep Learning Engineer,85673,USD,85673,SE,CT,South Korea,M,Finland,0,"SQL, Linux, Python",Master,9,Energy,2024-10-15,2024-11-22,2316,8.3,Smart Analytics +AI05833,ML Ops Engineer,141382,USD,141382,MI,PT,Norway,M,South Korea,50,"TensorFlow, Azure, Kubernetes, Deep Learning, MLOps",Bachelor,4,Healthcare,2025-01-15,2025-02-23,1098,6.7,DeepTech Ventures +AI05834,Research Scientist,104303,CAD,130379,SE,FL,Canada,S,Canada,100,"Kubernetes, Git, Hadoop, TensorFlow",Associate,5,Gaming,2024-08-13,2024-09-14,2000,7,Algorithmic Solutions +AI05835,AI Consultant,105290,EUR,89497,SE,CT,Netherlands,S,Netherlands,0,"Java, PyTorch, Azure, GCP",PhD,6,Technology,2024-09-09,2024-10-16,2185,8.7,TechCorp Inc +AI05836,ML Ops Engineer,110705,EUR,94099,MI,FT,Netherlands,L,United Kingdom,50,"Docker, Data Visualization, PyTorch",Master,2,Automotive,2024-05-18,2024-07-20,1968,9.5,Digital Transformation LLC +AI05837,Autonomous Systems Engineer,98458,USD,98458,SE,FT,South Korea,S,South Korea,0,"Spark, R, Java, Mathematics, Azure",Associate,5,Real Estate,2024-08-21,2024-10-15,2455,6,AI Innovations +AI05838,Computer Vision Engineer,80189,CHF,72170,EN,CT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Azure, Hadoop",Associate,0,Automotive,2024-08-28,2024-10-11,2452,6.4,Advanced Robotics +AI05839,AI Consultant,152024,EUR,129220,EX,FT,France,L,Thailand,0,"Deep Learning, MLOps, Linux, Kubernetes",Bachelor,12,Finance,2024-01-17,2024-03-13,2051,6.3,Algorithmic Solutions +AI05840,Computer Vision Engineer,144136,USD,144136,EX,PT,Sweden,S,Egypt,0,"Git, Kubernetes, AWS",Master,15,Media,2024-10-17,2024-11-25,756,9.7,DataVision Ltd +AI05841,Head of AI,68248,USD,68248,EN,FT,Ireland,M,Ireland,100,"PyTorch, Scala, Computer Vision, AWS, Deep Learning",Bachelor,0,Technology,2025-02-24,2025-04-09,1649,6.8,Algorithmic Solutions +AI05842,Autonomous Systems Engineer,162400,CAD,203000,EX,CT,Canada,M,Canada,0,"R, Kubernetes, Linux, Tableau, Hadoop",PhD,18,Education,2024-06-05,2024-07-24,1538,7.5,Cloud AI Solutions +AI05843,Computer Vision Engineer,271814,EUR,231042,EX,CT,Austria,L,Austria,0,"MLOps, SQL, Linux",Bachelor,12,Energy,2024-11-30,2025-01-31,1677,5.9,Neural Networks Co +AI05844,Autonomous Systems Engineer,145196,USD,145196,SE,PT,Israel,L,Israel,50,"R, SQL, Java",Bachelor,7,Telecommunications,2024-04-26,2024-06-04,1164,6.3,Predictive Systems +AI05845,Machine Learning Researcher,204480,EUR,173808,EX,FT,Netherlands,S,Ghana,100,"Docker, Kubernetes, Spark",Master,16,Gaming,2024-08-08,2024-09-10,858,9.8,Digital Transformation LLC +AI05846,Head of AI,60712,EUR,51605,EN,CT,France,M,France,50,"MLOps, Python, Docker",Master,1,Government,2024-04-29,2024-06-30,579,6.3,Predictive Systems +AI05847,AI Research Scientist,142958,CAD,178698,SE,CT,Canada,L,Latvia,50,"Java, SQL, Data Visualization, Docker",Master,8,Education,2024-08-30,2024-10-14,649,5.9,Predictive Systems +AI05848,Deep Learning Engineer,73847,USD,73847,MI,FL,Ireland,S,Ireland,50,"Git, Deep Learning, Data Visualization, Computer Vision",Master,3,Energy,2024-01-17,2024-02-07,834,5.7,AI Innovations +AI05849,Deep Learning Engineer,44043,USD,44043,MI,PT,India,L,India,50,"Git, Azure, Spark, Kubernetes",Bachelor,3,Transportation,2024-06-19,2024-07-04,1303,5.9,Neural Networks Co +AI05850,AI Product Manager,230859,CHF,207773,SE,CT,Switzerland,L,Switzerland,50,"Azure, TensorFlow, Data Visualization, NLP",PhD,5,Retail,2025-04-23,2025-06-02,2335,7.8,Algorithmic Solutions +AI05851,Principal Data Scientist,31387,USD,31387,MI,FT,India,M,India,0,"Mathematics, Tableau, MLOps, SQL, Linux",Master,3,Government,2025-03-02,2025-03-28,1711,5.1,Quantum Computing Inc +AI05852,AI Consultant,69067,CAD,86334,EN,PT,Canada,M,Israel,100,"Python, TensorFlow, PyTorch, AWS",Master,0,Gaming,2024-05-02,2024-07-02,1204,8.2,Predictive Systems +AI05853,Principal Data Scientist,131432,USD,131432,SE,FT,Sweden,S,Canada,100,"Linux, PyTorch, Deep Learning, Python",Master,9,Gaming,2024-10-19,2024-12-12,2263,6.5,Autonomous Tech +AI05854,AI Consultant,83942,USD,83942,MI,CT,Ireland,M,Ireland,0,"Python, Docker, Linux, Kubernetes, Git",Master,4,Automotive,2024-11-29,2025-01-05,1333,9.9,Advanced Robotics +AI05855,AI Specialist,261743,JPY,28791730,EX,CT,Japan,M,Japan,0,"NLP, Scala, Linux",Bachelor,14,Transportation,2024-08-17,2024-09-14,1461,6.8,Machine Intelligence Group +AI05856,Autonomous Systems Engineer,81198,USD,81198,EN,FL,Finland,L,Finland,100,"Hadoop, SQL, Data Visualization, Tableau",PhD,0,Media,2024-08-27,2024-09-15,1880,10,Smart Analytics +AI05857,AI Consultant,99681,JPY,10964910,MI,PT,Japan,M,Japan,100,"Linux, PyTorch, SQL, Java",PhD,2,Consulting,2024-10-01,2024-11-26,2486,5.6,Future Systems +AI05858,Principal Data Scientist,116363,EUR,98909,MI,CT,Netherlands,L,Netherlands,100,"Java, Python, Computer Vision",Bachelor,4,Automotive,2025-02-26,2025-04-21,1595,6.8,Machine Intelligence Group +AI05859,AI Architect,167056,USD,167056,SE,CT,Denmark,S,Denmark,100,"Java, SQL, Data Visualization, Git, Deep Learning",Master,5,Consulting,2024-03-25,2024-04-11,2492,9.8,Machine Intelligence Group +AI05860,AI Architect,44476,EUR,37805,EN,FT,Austria,S,Austria,50,"Java, Kubernetes, Scala, Python",Bachelor,1,Government,2025-01-16,2025-03-04,1671,8.9,Quantum Computing Inc +AI05861,Data Scientist,85390,AUD,115277,EN,PT,Australia,L,Australia,0,"SQL, Azure, Mathematics, AWS",Master,0,Consulting,2024-04-28,2024-05-24,1172,5,Quantum Computing Inc +AI05862,NLP Engineer,151511,CHF,136360,SE,PT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Tableau, Docker",Bachelor,5,Manufacturing,2024-04-23,2024-06-24,2354,9.9,Advanced Robotics +AI05863,AI Product Manager,112471,JPY,12371810,MI,FT,Japan,L,Nigeria,100,"NLP, Azure, AWS",Associate,4,Healthcare,2025-03-30,2025-04-14,809,5.1,DataVision Ltd +AI05864,ML Ops Engineer,172627,CHF,155364,SE,CT,Switzerland,M,Switzerland,0,"NLP, Tableau, Mathematics",Associate,8,Telecommunications,2024-12-10,2024-12-27,1336,6,DeepTech Ventures +AI05865,NLP Engineer,233363,USD,233363,EX,FT,Finland,L,Finland,0,"SQL, Computer Vision, TensorFlow",Master,10,Retail,2024-04-08,2024-05-18,2008,6.6,Cognitive Computing +AI05866,Machine Learning Researcher,116985,EUR,99437,SE,PT,Austria,S,United Kingdom,100,"Mathematics, Git, Docker, SQL",Bachelor,5,Finance,2025-01-11,2025-02-19,2373,7.7,Algorithmic Solutions +AI05867,Computer Vision Engineer,184253,GBP,138190,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Java, Linux",Bachelor,6,Finance,2024-05-01,2024-07-05,2168,7.1,Cloud AI Solutions +AI05868,AI Specialist,118246,USD,118246,MI,FL,Norway,S,Sweden,50,"Linux, SQL, Mathematics",PhD,4,Education,2024-07-12,2024-08-04,1005,7.9,Machine Intelligence Group +AI05869,AI Software Engineer,173631,CHF,156268,SE,FT,Switzerland,L,Austria,100,"MLOps, Git, Azure, NLP, Statistics",Bachelor,5,Real Estate,2025-01-31,2025-03-19,1567,9.5,Digital Transformation LLC +AI05870,Computer Vision Engineer,105596,USD,105596,MI,PT,Finland,L,Finland,0,"Azure, Scala, Java, Kubernetes",Associate,2,Automotive,2024-12-26,2025-01-13,2408,9.6,Autonomous Tech +AI05871,AI Product Manager,239497,USD,239497,EX,CT,Finland,L,Finland,0,"R, Tableau, Kubernetes",PhD,18,Media,2024-04-12,2024-05-03,1848,7.6,Predictive Systems +AI05872,Research Scientist,60880,USD,60880,EN,FT,South Korea,M,Mexico,50,"SQL, Deep Learning, Hadoop, GCP, PyTorch",Master,0,Gaming,2024-02-14,2024-04-08,1842,6.6,Smart Analytics +AI05873,Machine Learning Researcher,192915,CHF,173624,EX,FT,Switzerland,S,Switzerland,50,"MLOps, Azure, Spark, Python, PyTorch",Associate,14,Government,2024-08-06,2024-09-05,1358,9.1,DataVision Ltd +AI05874,NLP Engineer,62398,USD,62398,MI,FT,Israel,S,Israel,0,"AWS, Linux, Deep Learning, R",Bachelor,2,Gaming,2025-03-18,2025-04-08,1025,9.2,Predictive Systems +AI05875,Machine Learning Researcher,87874,USD,87874,MI,CT,Sweden,S,Sweden,0,"Hadoop, NLP, SQL, Kubernetes",Bachelor,2,Healthcare,2024-02-13,2024-03-15,2305,7.8,Future Systems +AI05876,Computer Vision Engineer,76770,GBP,57578,EN,FL,United Kingdom,L,United Kingdom,0,"Python, Azure, SQL",PhD,0,Healthcare,2024-03-21,2024-05-20,669,9.3,Cognitive Computing +AI05877,AI Software Engineer,134200,EUR,114070,SE,CT,France,M,France,0,"Python, TensorFlow, Tableau, SQL",PhD,5,Real Estate,2024-04-15,2024-05-19,1184,8.2,Cloud AI Solutions +AI05878,Machine Learning Engineer,120552,EUR,102469,SE,CT,Netherlands,S,Netherlands,100,"R, Java, AWS, Computer Vision, GCP",Associate,7,Consulting,2024-05-11,2024-06-03,2434,6.5,Smart Analytics +AI05879,AI Specialist,52784,USD,52784,EN,FL,Sweden,S,Sweden,100,"NLP, Kubernetes, SQL, TensorFlow, Tableau",Associate,1,Gaming,2024-07-31,2024-09-23,1275,7.3,Neural Networks Co +AI05880,AI Product Manager,70428,USD,70428,EN,PT,Israel,L,Israel,0,"Hadoop, R, Deep Learning, NLP, GCP",PhD,1,Government,2024-04-25,2024-05-14,1514,8.1,Advanced Robotics +AI05881,Autonomous Systems Engineer,80363,JPY,8839930,MI,CT,Japan,M,France,100,"AWS, Spark, SQL",Associate,3,Transportation,2024-04-04,2024-05-15,1293,5.9,DeepTech Ventures +AI05882,Machine Learning Engineer,168502,CAD,210628,EX,CT,Canada,L,South Africa,0,"Hadoop, Kubernetes, Java, Mathematics",Master,16,Education,2024-08-17,2024-09-23,1036,9.5,Autonomous Tech +AI05883,NLP Engineer,95415,USD,95415,MI,FT,United States,S,United States,50,"Docker, Scala, Git, Tableau, GCP",Associate,2,Technology,2024-08-06,2024-09-26,1802,9.8,TechCorp Inc +AI05884,Principal Data Scientist,57820,GBP,43365,EN,FL,United Kingdom,S,United Kingdom,100,"GCP, SQL, PyTorch",Bachelor,1,Energy,2024-01-18,2024-02-03,1681,9.2,Autonomous Tech +AI05885,AI Consultant,274165,JPY,30158150,EX,FT,Japan,L,Ukraine,100,"Docker, Python, Spark, Git",Master,16,Automotive,2025-01-30,2025-03-16,2388,7.6,Future Systems +AI05886,ML Ops Engineer,242363,USD,242363,EX,FL,Israel,L,Israel,50,"PyTorch, SQL, Linux, Docker, Azure",Bachelor,16,Manufacturing,2024-10-03,2024-10-24,934,8.1,Future Systems +AI05887,AI Consultant,182784,SGD,237619,EX,CT,Singapore,L,Latvia,0,"MLOps, Kubernetes, NLP, Git, Hadoop",Bachelor,18,Media,2024-01-03,2024-02-27,972,5.2,Advanced Robotics +AI05888,AI Architect,76429,SGD,99358,MI,CT,Singapore,S,Singapore,100,"Computer Vision, Hadoop, Tableau, Spark, Data Visualization",Associate,3,Education,2024-05-11,2024-07-12,1395,8.9,Quantum Computing Inc +AI05889,AI Product Manager,66004,USD,66004,SE,FL,China,L,China,50,"Statistics, Python, Data Visualization, MLOps, TensorFlow",Bachelor,7,Media,2024-01-21,2024-02-19,503,6.2,Machine Intelligence Group +AI05890,Principal Data Scientist,151148,GBP,113361,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Docker, Data Visualization, Computer Vision, Azure",Bachelor,7,Manufacturing,2024-10-21,2024-12-30,1588,9.1,Predictive Systems +AI05891,Data Engineer,168460,USD,168460,EX,FT,South Korea,S,Argentina,100,"Docker, Hadoop, Git, PyTorch, Deep Learning",Bachelor,14,Real Estate,2025-01-01,2025-03-05,1317,8.4,Smart Analytics +AI05892,AI Architect,124855,USD,124855,EX,FT,Israel,S,Israel,0,"Git, Python, AWS",Master,16,Education,2024-07-16,2024-09-21,879,6,Machine Intelligence Group +AI05893,Autonomous Systems Engineer,154883,CHF,139395,MI,FT,Switzerland,M,Switzerland,50,"Python, Spark, Kubernetes",PhD,4,Media,2024-10-25,2025-01-05,1623,6.2,Digital Transformation LLC +AI05894,Robotics Engineer,241392,EUR,205183,EX,PT,Austria,L,Austria,50,"Git, GCP, Linux",Associate,18,Gaming,2025-01-11,2025-01-26,2393,7.9,Advanced Robotics +AI05895,AI Specialist,147818,EUR,125645,EX,CT,France,S,Czech Republic,50,"R, Tableau, Kubernetes, SQL, Deep Learning",Bachelor,16,Transportation,2024-05-11,2024-06-26,921,5.9,Quantum Computing Inc +AI05896,Computer Vision Engineer,89182,USD,89182,EN,CT,Ireland,L,Ireland,50,"PyTorch, Hadoop, Python, Deep Learning, MLOps",PhD,0,Media,2025-02-07,2025-03-25,575,6.5,Cognitive Computing +AI05897,Robotics Engineer,48483,USD,48483,EN,FT,South Korea,S,South Korea,50,"Python, Data Visualization, Spark",PhD,1,Automotive,2025-03-07,2025-04-02,1954,6.1,Advanced Robotics +AI05898,Machine Learning Engineer,39290,USD,39290,MI,CT,China,M,Argentina,100,"Scala, Hadoop, NLP",Master,4,Finance,2025-02-08,2025-03-07,2097,9.5,DataVision Ltd +AI05899,Data Analyst,60878,EUR,51746,EN,FT,Austria,L,Austria,50,"Git, Java, TensorFlow, Statistics",Bachelor,1,Energy,2024-09-18,2024-11-01,639,7.1,Autonomous Tech +AI05900,Computer Vision Engineer,232706,JPY,25597660,EX,PT,Japan,S,Japan,50,"Python, TensorFlow, Kubernetes, Azure, Data Visualization",PhD,14,Real Estate,2024-06-23,2024-08-05,1494,6.7,Quantum Computing Inc +AI05901,AI Research Scientist,52076,EUR,44265,EN,PT,Austria,M,Ireland,50,"Statistics, TensorFlow, SQL, MLOps",Bachelor,0,Technology,2024-09-19,2024-10-07,971,8.7,Future Systems +AI05902,Data Engineer,198461,CAD,248076,EX,PT,Canada,M,Canada,50,"Java, Kubernetes, PyTorch, Statistics",Associate,11,Finance,2024-04-16,2024-06-13,580,5.6,Predictive Systems +AI05903,Computer Vision Engineer,37606,USD,37606,EN,PT,China,L,China,100,"AWS, Git, SQL",PhD,0,Telecommunications,2024-04-03,2024-05-26,1982,7.8,Digital Transformation LLC +AI05904,AI Consultant,238598,EUR,202808,EX,FT,France,L,France,100,"Linux, Git, Spark",Master,13,Retail,2025-04-15,2025-05-12,567,9,TechCorp Inc +AI05905,AI Research Scientist,117613,EUR,99971,MI,FL,France,L,France,100,"Azure, Kubernetes, Tableau, Computer Vision, Deep Learning",Master,4,Energy,2024-11-25,2024-12-25,1812,8.4,Quantum Computing Inc +AI05906,AI Product Manager,296254,USD,296254,EX,FT,Norway,S,Norway,0,"Python, TensorFlow, PyTorch, Computer Vision",Bachelor,14,Consulting,2024-09-17,2024-11-04,2170,6.2,Quantum Computing Inc +AI05907,AI Product Manager,118508,EUR,100732,SE,FL,Netherlands,S,Netherlands,50,"Kubernetes, Linux, NLP",Associate,7,Government,2025-03-21,2025-05-21,1770,9.9,Digital Transformation LLC +AI05908,Research Scientist,90559,EUR,76975,MI,FT,Germany,M,Germany,50,"Spark, TensorFlow, Git, Mathematics",Bachelor,3,Telecommunications,2024-11-13,2024-12-23,1180,6.2,Machine Intelligence Group +AI05909,NLP Engineer,194311,JPY,21374210,EX,CT,Japan,M,Japan,0,"MLOps, GCP, AWS, Azure, Git",Associate,11,Retail,2025-02-19,2025-05-01,953,7.7,Advanced Robotics +AI05910,Robotics Engineer,96127,USD,96127,MI,FL,Ireland,S,Ireland,0,"Linux, SQL, Data Visualization, PyTorch",Master,3,Media,2025-01-02,2025-02-18,1209,7.8,Advanced Robotics +AI05911,Research Scientist,237774,AUD,320995,EX,FT,Australia,L,Australia,100,"R, Linux, Mathematics, Java",Bachelor,19,Finance,2025-01-23,2025-02-14,2373,7.3,TechCorp Inc +AI05912,AI Product Manager,114455,JPY,12590050,SE,PT,Japan,S,Russia,50,"GCP, Data Visualization, Scala, PyTorch",Associate,5,Gaming,2024-04-14,2024-06-19,1943,9,Quantum Computing Inc +AI05913,AI Specialist,70786,CHF,63707,EN,CT,Switzerland,S,Switzerland,0,"R, Java, Azure, Computer Vision",PhD,0,Finance,2025-03-20,2025-04-19,699,5.4,Autonomous Tech +AI05914,AI Software Engineer,38502,USD,38502,MI,FL,China,M,China,50,"GCP, PyTorch, Data Visualization, TensorFlow",Associate,3,Manufacturing,2024-07-19,2024-09-11,776,9.1,Neural Networks Co +AI05915,AI Architect,75059,USD,75059,MI,CT,South Korea,S,South Korea,50,"Git, SQL, MLOps, Mathematics",PhD,3,Education,2024-10-14,2024-12-16,988,5.1,Quantum Computing Inc +AI05916,AI Research Scientist,22820,USD,22820,EN,FL,India,M,India,100,"MLOps, PyTorch, Tableau, AWS, Scala",Associate,1,Consulting,2024-01-17,2024-03-15,2336,7.6,Autonomous Tech +AI05917,NLP Engineer,88433,USD,88433,MI,FL,Israel,S,Israel,0,"Computer Vision, Docker, Mathematics, AWS",PhD,4,Gaming,2024-11-30,2025-01-15,1395,5.4,TechCorp Inc +AI05918,AI Product Manager,202400,AUD,273240,EX,PT,Australia,S,Australia,50,"Python, Azure, Deep Learning",Master,14,Telecommunications,2024-12-06,2025-01-03,636,6,TechCorp Inc +AI05919,ML Ops Engineer,158886,EUR,135053,EX,FT,France,S,Chile,50,"Spark, Linux, NLP",Bachelor,15,Gaming,2024-11-08,2025-01-16,1540,9,Autonomous Tech +AI05920,AI Specialist,101963,EUR,86669,MI,CT,Netherlands,L,Netherlands,50,"Data Visualization, SQL, Python, Spark, Deep Learning",Master,2,Education,2025-04-20,2025-05-16,1011,5.9,Advanced Robotics +AI05921,AI Consultant,86650,USD,86650,MI,FT,Finland,M,Finland,50,"Kubernetes, Git, Azure, NLP, Scala",PhD,4,Manufacturing,2024-08-22,2024-10-31,1975,8.3,Smart Analytics +AI05922,AI Software Engineer,263809,AUD,356142,EX,FT,Australia,L,Ghana,50,"Scala, Python, Computer Vision",Master,13,Gaming,2025-04-28,2025-06-15,512,7.1,Algorithmic Solutions +AI05923,AI Architect,92448,USD,92448,MI,CT,United States,M,United States,0,"GCP, R, PyTorch, SQL",Bachelor,4,Gaming,2024-04-06,2024-04-21,501,6.8,Machine Intelligence Group +AI05924,Machine Learning Engineer,209496,JPY,23044560,EX,FL,Japan,S,Japan,100,"TensorFlow, Spark, Computer Vision, Linux",Master,18,Government,2025-02-07,2025-02-25,1382,7.2,Autonomous Tech +AI05925,Robotics Engineer,72371,AUD,97701,MI,CT,Australia,M,Australia,0,"TensorFlow, Docker, Computer Vision, Linux",Master,4,Telecommunications,2024-12-03,2025-01-12,899,6.9,Future Systems +AI05926,AI Consultant,21755,USD,21755,EN,FL,India,S,India,0,"Azure, TensorFlow, Tableau, Mathematics, PyTorch",Associate,0,Finance,2024-11-27,2025-01-21,1420,8.1,Autonomous Tech +AI05927,Data Engineer,92976,USD,92976,MI,PT,Sweden,M,Sweden,0,"Tableau, Mathematics, Scala, Computer Vision",PhD,3,Automotive,2025-03-01,2025-04-16,900,8.9,Algorithmic Solutions +AI05928,Machine Learning Engineer,148362,AUD,200289,SE,CT,Australia,L,Belgium,100,"Python, Deep Learning, Spark, Mathematics",Bachelor,6,Retail,2024-12-27,2025-01-25,841,6.3,DataVision Ltd +AI05929,Data Analyst,50796,AUD,68575,EN,FL,Australia,S,Australia,100,"SQL, Kubernetes, MLOps",PhD,0,Transportation,2025-04-28,2025-06-12,1502,7,Digital Transformation LLC +AI05930,Autonomous Systems Engineer,123224,AUD,166352,SE,CT,Australia,L,Australia,100,"Python, Kubernetes, Data Visualization, Java",PhD,5,Finance,2024-12-08,2025-01-05,2333,8.8,Predictive Systems +AI05931,Principal Data Scientist,230556,JPY,25361160,EX,FT,Japan,M,Japan,100,"Git, SQL, Scala, MLOps",PhD,18,Telecommunications,2025-02-08,2025-03-25,2163,7.1,Autonomous Tech +AI05932,AI Research Scientist,148164,USD,148164,SE,CT,Denmark,M,Denmark,100,"Java, Hadoop, Mathematics",Associate,6,Retail,2025-02-26,2025-03-31,606,8,Advanced Robotics +AI05933,AI Research Scientist,80479,USD,80479,MI,FL,Finland,S,Poland,0,"Linux, Docker, NLP, Kubernetes, Tableau",Master,4,Energy,2024-05-31,2024-07-12,2043,6.1,Machine Intelligence Group +AI05934,Machine Learning Engineer,109612,USD,109612,SE,PT,Sweden,M,Argentina,50,"Python, Data Visualization, Git, Spark, GCP",Bachelor,6,Transportation,2024-06-27,2024-08-13,1783,10,Neural Networks Co +AI05935,Research Scientist,194931,JPY,21442410,EX,FT,Japan,M,Japan,0,"Azure, Python, Computer Vision",Master,10,Media,2024-07-07,2024-09-13,799,5.7,Quantum Computing Inc +AI05936,Head of AI,111273,SGD,144655,SE,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Docker, Data Visualization",Associate,5,Healthcare,2024-10-12,2024-11-19,893,6.7,Cloud AI Solutions +AI05937,Computer Vision Engineer,52668,EUR,44768,EN,FT,Austria,S,Australia,100,"TensorFlow, Kubernetes, GCP",Associate,0,Education,2025-02-17,2025-03-17,2461,7.1,Algorithmic Solutions +AI05938,AI Specialist,190969,EUR,162324,EX,FL,Netherlands,S,Canada,0,"Docker, Java, Mathematics, PyTorch, TensorFlow",Master,14,Media,2024-02-13,2024-03-31,1311,6.6,Advanced Robotics +AI05939,Research Scientist,211110,CHF,189999,EX,FT,Switzerland,S,Switzerland,100,"SQL, Git, Tableau, Statistics",Associate,14,Energy,2025-03-04,2025-05-09,1747,8.1,Cloud AI Solutions +AI05940,Data Scientist,99999,CHF,89999,EN,FL,Switzerland,S,Switzerland,50,"PyTorch, Linux, Hadoop",Associate,0,Real Estate,2025-04-11,2025-05-13,788,9.6,Neural Networks Co +AI05941,AI Software Engineer,108942,USD,108942,MI,CT,Norway,L,Norway,50,"Linux, Kubernetes, Python, TensorFlow",Bachelor,4,Government,2024-12-09,2025-01-16,926,7.4,Neural Networks Co +AI05942,ML Ops Engineer,131962,AUD,178149,SE,CT,Australia,S,Australia,50,"Java, TensorFlow, Docker, GCP",Associate,9,Gaming,2024-03-14,2024-04-20,550,7.8,Predictive Systems +AI05943,Computer Vision Engineer,76651,EUR,65153,MI,FL,Austria,S,Austria,100,"AWS, Tableau, Kubernetes",Associate,2,Consulting,2024-10-07,2024-11-28,2276,9.3,DataVision Ltd +AI05944,Deep Learning Engineer,98325,USD,98325,EN,PT,Norway,L,Sweden,0,"MLOps, GCP, Python, Mathematics, TensorFlow",Master,1,Media,2024-02-23,2024-03-10,534,5.5,Quantum Computing Inc +AI05945,Robotics Engineer,62079,USD,62079,SE,FL,China,M,China,100,"Scala, Git, Kubernetes, SQL",Master,8,Healthcare,2024-03-28,2024-04-23,1221,8.8,Advanced Robotics +AI05946,ML Ops Engineer,95740,USD,95740,EN,CT,Denmark,L,Denmark,0,"NLP, Spark, SQL, Python",Bachelor,1,Gaming,2025-01-20,2025-03-21,1209,6.5,Future Systems +AI05947,AI Product Manager,105725,USD,105725,SE,CT,Finland,S,Norway,100,"Spark, Git, Linux",PhD,6,Telecommunications,2025-02-16,2025-03-11,615,10,Advanced Robotics +AI05948,Robotics Engineer,187160,CHF,168444,SE,PT,Switzerland,M,Sweden,0,"Python, Git, TensorFlow",PhD,9,Gaming,2024-03-19,2024-04-02,2451,8.5,Autonomous Tech +AI05949,Principal Data Scientist,222856,USD,222856,EX,CT,Ireland,M,Ireland,0,"Python, Data Visualization, TensorFlow, Scala",Bachelor,14,Government,2025-04-01,2025-05-13,1792,8.4,AI Innovations +AI05950,Head of AI,73259,USD,73259,MI,FT,South Korea,S,South Korea,0,"Git, Java, Python",Master,2,Finance,2024-04-16,2024-06-28,1797,5.5,DataVision Ltd +AI05951,Data Engineer,117240,USD,117240,SE,PT,Ireland,S,Ireland,50,"GCP, R, Deep Learning, Tableau",Associate,7,Technology,2024-09-19,2024-11-13,2169,6,Algorithmic Solutions +AI05952,AI Product Manager,124299,USD,124299,SE,FT,Finland,M,Finland,50,"TensorFlow, Python, Mathematics, Statistics, AWS",PhD,8,Finance,2024-04-16,2024-05-04,2498,7,Autonomous Tech +AI05953,Robotics Engineer,67930,EUR,57741,EN,PT,Netherlands,S,Netherlands,50,"SQL, AWS, Data Visualization, R",Master,0,Media,2024-11-19,2024-12-12,663,6.2,Machine Intelligence Group +AI05954,NLP Engineer,85388,EUR,72580,EN,FT,Germany,L,Germany,100,"Java, Azure, Hadoop, Spark",Bachelor,1,Finance,2024-03-16,2024-04-17,610,7.8,Advanced Robotics +AI05955,Machine Learning Researcher,42537,USD,42537,EN,CT,South Korea,S,South Korea,50,"GCP, Kubernetes, Python, Azure, Statistics",Bachelor,1,Manufacturing,2025-02-22,2025-04-25,2004,6.3,Neural Networks Co +AI05956,AI Software Engineer,109665,CAD,137081,SE,FT,Canada,M,Canada,100,"Java, Kubernetes, Mathematics",PhD,9,Real Estate,2024-10-03,2024-12-02,2250,7.3,Neural Networks Co +AI05957,Data Scientist,78478,USD,78478,EN,FT,Norway,M,China,50,"Mathematics, Kubernetes, Docker, Azure, Scala",Associate,1,Automotive,2024-06-28,2024-08-16,1775,6,DataVision Ltd +AI05958,Principal Data Scientist,127696,USD,127696,SE,FT,Finland,L,Finland,0,"Azure, Mathematics, Linux, MLOps, Tableau",Master,5,Gaming,2024-08-14,2024-09-26,610,9.3,Neural Networks Co +AI05959,AI Product Manager,75623,USD,75623,MI,PT,South Korea,S,South Korea,0,"Scala, Kubernetes, Git",PhD,3,Transportation,2024-03-03,2024-04-22,2215,9.3,Cognitive Computing +AI05960,Deep Learning Engineer,221113,AUD,298503,EX,FT,Australia,L,Australia,0,"AWS, Spark, MLOps, Python",Master,19,Gaming,2024-11-03,2024-12-24,1616,5.9,TechCorp Inc +AI05961,Deep Learning Engineer,171238,CAD,214048,EX,CT,Canada,L,Canada,50,"PyTorch, Spark, Tableau, MLOps",Bachelor,14,Automotive,2025-02-05,2025-04-08,1948,9.9,Digital Transformation LLC +AI05962,Robotics Engineer,201912,USD,201912,EX,FT,Israel,L,Israel,100,"GCP, R, PyTorch, Spark, Mathematics",PhD,18,Energy,2025-03-11,2025-04-03,1298,5.7,DataVision Ltd +AI05963,AI Research Scientist,205861,USD,205861,EX,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Kubernetes, Azure, Tableau",Bachelor,15,Media,2025-04-16,2025-06-02,1682,7,Cloud AI Solutions +AI05964,Deep Learning Engineer,302543,USD,302543,EX,PT,Norway,L,Norway,0,"Python, Azure, TensorFlow",PhD,12,Automotive,2024-04-26,2024-05-31,582,8.1,Machine Intelligence Group +AI05965,ML Ops Engineer,115521,EUR,98193,MI,PT,Austria,L,Austria,0,"Azure, Git, Scala, Java",PhD,4,Telecommunications,2024-05-11,2024-07-13,2101,9.5,Cognitive Computing +AI05966,Data Engineer,50057,USD,50057,SE,PT,China,M,China,100,"PyTorch, Tableau, TensorFlow, Azure",Bachelor,9,Retail,2024-03-05,2024-05-12,722,9.3,Cloud AI Solutions +AI05967,Computer Vision Engineer,139280,EUR,118388,SE,CT,Austria,M,Austria,0,"GCP, PyTorch, Data Visualization, Statistics, R",Associate,9,Real Estate,2024-07-06,2024-08-12,2434,6.5,Neural Networks Co +AI05968,AI Research Scientist,80202,USD,80202,EN,CT,Denmark,S,Denmark,0,"Spark, SQL, R, Deep Learning",PhD,1,Government,2024-01-15,2024-03-19,1892,8.2,TechCorp Inc +AI05969,Computer Vision Engineer,115152,USD,115152,SE,PT,Ireland,S,Ireland,100,"Spark, Git, NLP",Associate,7,Media,2024-01-15,2024-02-29,1179,7.3,AI Innovations +AI05970,Deep Learning Engineer,104936,SGD,136417,MI,FL,Singapore,M,Singapore,50,"Java, AWS, PyTorch",Associate,3,Automotive,2024-11-07,2025-01-05,1188,6.7,Future Systems +AI05971,Robotics Engineer,292055,USD,292055,EX,PT,Norway,L,Norway,100,"Kubernetes, Git, Computer Vision, Deep Learning, Mathematics",Master,10,Media,2025-01-20,2025-02-08,1589,9.8,Algorithmic Solutions +AI05972,ML Ops Engineer,129611,USD,129611,SE,PT,Sweden,S,Sweden,100,"AWS, Hadoop, NLP",Bachelor,8,Real Estate,2024-03-02,2024-04-23,1529,8.9,Autonomous Tech +AI05973,Computer Vision Engineer,56599,USD,56599,SE,CT,China,L,China,100,"Python, MLOps, Data Visualization, Deep Learning, R",Bachelor,9,Education,2024-11-23,2024-12-13,2269,7.7,Predictive Systems +AI05974,AI Software Engineer,66137,CAD,82671,MI,FL,Canada,S,Italy,0,"Kubernetes, AWS, Azure",PhD,3,Real Estate,2024-02-23,2024-04-28,508,5.8,DeepTech Ventures +AI05975,AI Specialist,83658,CAD,104573,MI,FT,Canada,L,Canada,0,"R, SQL, PyTorch, NLP",PhD,2,Gaming,2025-04-21,2025-05-23,1619,6.4,Autonomous Tech +AI05976,Autonomous Systems Engineer,197361,USD,197361,SE,FL,Denmark,L,Denmark,100,"Statistics, PyTorch, Kubernetes",PhD,7,Finance,2024-02-04,2024-03-26,1427,8.2,TechCorp Inc +AI05977,AI Architect,283431,EUR,240916,EX,PT,Germany,L,Germany,100,"Computer Vision, Kubernetes, R",Associate,19,Technology,2024-01-03,2024-02-29,2104,5,Machine Intelligence Group +AI05978,Head of AI,83530,JPY,9188300,EN,FT,Japan,L,Japan,0,"Spark, Java, Hadoop, Scala",Bachelor,1,Finance,2024-01-02,2024-02-01,629,8,Predictive Systems +AI05979,NLP Engineer,197715,EUR,168058,EX,FL,France,M,France,0,"Python, Linux, Hadoop",Associate,10,Energy,2025-03-05,2025-04-22,2465,8.4,DeepTech Ventures +AI05980,NLP Engineer,88355,EUR,75102,MI,FL,Netherlands,S,Portugal,100,"Data Visualization, Azure, R, MLOps",Master,3,Real Estate,2024-11-27,2024-12-26,2128,7.7,Autonomous Tech +AI05981,Data Analyst,30619,USD,30619,EN,PT,India,L,India,50,"AWS, Linux, Spark, Java",Master,1,Finance,2024-03-27,2024-05-02,1811,9.9,Cloud AI Solutions +AI05982,NLP Engineer,206289,EUR,175346,EX,FL,Austria,S,Netherlands,0,"Scala, MLOps, NLP",Associate,14,Education,2024-09-03,2024-10-03,1611,8.5,Autonomous Tech +AI05983,Head of AI,27137,USD,27137,EN,CT,China,M,Russia,100,"NLP, Git, Hadoop, Computer Vision, Scala",Master,0,Energy,2025-01-14,2025-03-11,1238,5.4,Advanced Robotics +AI05984,Data Engineer,107037,CAD,133796,SE,FL,Canada,M,Canada,0,"GCP, Scala, NLP, Spark",Bachelor,5,Retail,2025-04-30,2025-06-04,2340,6.8,Neural Networks Co +AI05985,NLP Engineer,134388,USD,134388,SE,FL,South Korea,L,Kenya,50,"GCP, Docker, Python",Associate,6,Manufacturing,2024-06-26,2024-08-27,1415,6.3,Cognitive Computing +AI05986,Data Analyst,154970,EUR,131725,SE,PT,Netherlands,M,Netherlands,0,"Tableau, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-02-17,2024-03-25,1795,5.9,Cloud AI Solutions +AI05987,Autonomous Systems Engineer,127560,USD,127560,MI,CT,United States,L,United States,0,"GCP, AWS, Hadoop",Bachelor,4,Healthcare,2024-02-01,2024-02-26,727,6.2,Digital Transformation LLC +AI05988,Head of AI,71171,AUD,96081,EN,FT,Australia,S,Belgium,100,"Git, SQL, Azure, Spark, Scala",PhD,0,Finance,2024-08-20,2024-09-17,608,8.1,Neural Networks Co +AI05989,ML Ops Engineer,249331,USD,249331,EX,FL,United States,M,United States,0,"Scala, Kubernetes, Mathematics, Python",Bachelor,12,Telecommunications,2024-02-20,2024-04-13,1618,8.7,DataVision Ltd +AI05990,Research Scientist,130515,SGD,169670,SE,PT,Singapore,S,Singapore,0,"NLP, Deep Learning, Statistics",Associate,6,Manufacturing,2025-04-01,2025-05-16,2354,7,TechCorp Inc +AI05991,ML Ops Engineer,57678,EUR,49026,EN,FT,Austria,M,Austria,0,"Statistics, TensorFlow, Data Visualization, Mathematics, Computer Vision",Bachelor,1,Government,2024-05-25,2024-07-05,1904,7.2,Cloud AI Solutions +AI05992,AI Product Manager,269938,USD,269938,EX,FL,Denmark,S,Denmark,50,"Python, Kubernetes, MLOps",Master,16,Transportation,2024-02-08,2024-02-28,789,9.6,Algorithmic Solutions +AI05993,Computer Vision Engineer,63932,USD,63932,SE,FL,China,S,China,0,"GCP, MLOps, Hadoop, NLP",Associate,5,Government,2024-09-13,2024-11-14,753,9.6,Smart Analytics +AI05994,Principal Data Scientist,151633,USD,151633,EX,PT,Sweden,S,Philippines,0,"Python, R, Git",PhD,14,Telecommunications,2024-03-24,2024-04-26,1334,6.4,Advanced Robotics +AI05995,AI Research Scientist,149659,EUR,127210,EX,FT,Austria,L,Poland,100,"TensorFlow, Hadoop, Data Visualization, Docker",Master,14,Energy,2024-10-02,2024-12-03,809,9.1,Cloud AI Solutions +AI05996,AI Architect,63919,USD,63919,EX,FL,China,S,Luxembourg,50,"SQL, MLOps, Kubernetes, Azure",PhD,17,Consulting,2025-04-01,2025-05-30,860,5.8,Algorithmic Solutions +AI05997,Head of AI,189843,USD,189843,EX,PT,Denmark,S,Sweden,100,"TensorFlow, Kubernetes, GCP, Statistics, PyTorch",Associate,11,Retail,2024-01-31,2024-03-21,2054,8.8,AI Innovations +AI05998,NLP Engineer,72310,EUR,61464,MI,PT,Germany,M,Philippines,0,"MLOps, SQL, PyTorch, AWS, Linux",Associate,4,Media,2024-04-24,2024-06-16,1435,8.2,Digital Transformation LLC +AI05999,Computer Vision Engineer,90085,GBP,67564,MI,CT,United Kingdom,M,United Kingdom,50,"Linux, Git, R, Python",Associate,3,Government,2024-03-06,2024-04-23,2417,5.2,Cognitive Computing +AI06000,Head of AI,84107,USD,84107,MI,CT,Israel,M,Israel,0,"R, SQL, Computer Vision",Master,3,Retail,2024-05-21,2024-06-30,1588,5.3,Neural Networks Co +AI06001,AI Architect,99493,USD,99493,MI,CT,United States,M,United States,0,"Python, Git, R",PhD,3,Manufacturing,2025-04-12,2025-06-02,1258,6.7,Algorithmic Solutions +AI06002,Computer Vision Engineer,76756,EUR,65243,MI,PT,Netherlands,S,Netherlands,0,"Deep Learning, Python, Linux, SQL",Bachelor,4,Media,2025-01-17,2025-03-16,1000,5.4,Autonomous Tech +AI06003,Robotics Engineer,74296,GBP,55722,EN,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Spark, R, Data Visualization, Git",Master,1,Automotive,2025-03-09,2025-05-16,2465,6.7,Cloud AI Solutions +AI06004,Machine Learning Engineer,139465,JPY,15341150,SE,FT,Japan,L,Japan,100,"Azure, Docker, Java, Computer Vision, AWS",PhD,5,Healthcare,2025-04-02,2025-05-28,1680,5.3,Neural Networks Co +AI06005,Deep Learning Engineer,124464,AUD,168026,MI,CT,Australia,L,Russia,100,"Python, Hadoop, Data Visualization, Scala, Kubernetes",Bachelor,3,Retail,2024-10-20,2024-12-14,2113,8.2,Advanced Robotics +AI06006,NLP Engineer,169364,SGD,220173,SE,FL,Singapore,L,Estonia,0,"PyTorch, SQL, Tableau, TensorFlow, R",Master,7,Consulting,2024-11-08,2025-01-13,2464,6,TechCorp Inc +AI06007,ML Ops Engineer,104092,EUR,88478,MI,FL,France,L,France,50,"NLP, Docker, TensorFlow, Python, Azure",PhD,2,Retail,2025-01-20,2025-03-18,1428,8.3,Algorithmic Solutions +AI06008,AI Architect,236270,SGD,307151,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization",Associate,14,Healthcare,2024-01-02,2024-03-13,1176,6.9,DeepTech Ventures +AI06009,Machine Learning Researcher,127297,EUR,108202,SE,FT,Germany,L,Germany,50,"TensorFlow, Statistics, Computer Vision",Bachelor,8,Healthcare,2024-10-26,2024-12-21,1450,8.5,TechCorp Inc +AI06010,AI Architect,59837,USD,59837,SE,CT,China,S,China,50,"R, Tableau, Python, TensorFlow",PhD,8,Healthcare,2024-12-01,2025-01-26,1409,7.7,Neural Networks Co +AI06011,Head of AI,101553,EUR,86320,MI,PT,Austria,M,Austria,50,"Kubernetes, Linux, Deep Learning, Mathematics, Tableau",PhD,2,Telecommunications,2024-04-20,2024-05-26,1360,8.4,Quantum Computing Inc +AI06012,Data Analyst,308290,USD,308290,EX,PT,United States,L,Singapore,50,"Scala, Linux, SQL, PyTorch",Master,17,Consulting,2025-02-20,2025-03-26,2200,8.4,Smart Analytics +AI06013,Deep Learning Engineer,151359,USD,151359,SE,PT,Sweden,L,Sweden,50,"R, Scala, Statistics, Kubernetes, SQL",Bachelor,5,Retail,2024-10-15,2024-12-18,1006,8.4,Neural Networks Co +AI06014,AI Research Scientist,130025,EUR,110521,SE,FT,Germany,L,Germany,0,"PyTorch, SQL, R, Hadoop, Git",Master,7,Media,2024-02-24,2024-03-09,841,6.9,Future Systems +AI06015,ML Ops Engineer,257725,USD,257725,EX,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Azure",Associate,14,Retail,2024-12-07,2025-01-22,666,5.9,Smart Analytics +AI06016,Data Scientist,71138,USD,71138,EN,FT,Norway,M,Norway,50,"SQL, Python, Data Visualization, Mathematics, Linux",Bachelor,0,Automotive,2024-03-07,2024-04-13,2470,7.2,AI Innovations +AI06017,AI Product Manager,148695,USD,148695,SE,CT,Denmark,S,Denmark,50,"MLOps, AWS, R",Associate,8,Energy,2024-03-12,2024-05-20,705,7.3,Quantum Computing Inc +AI06018,Research Scientist,141557,USD,141557,SE,FL,United States,S,United States,50,"Tableau, MLOps, R, SQL",Associate,8,Automotive,2024-04-22,2024-05-09,1135,6.6,Digital Transformation LLC +AI06019,Data Analyst,38669,USD,38669,SE,CT,India,S,United Kingdom,0,"Tableau, Java, Deep Learning, Python, Mathematics",Bachelor,6,Manufacturing,2024-04-23,2024-05-16,2029,5.5,DeepTech Ventures +AI06020,ML Ops Engineer,68663,USD,68663,MI,PT,Israel,M,Czech Republic,0,"PyTorch, Kubernetes, Git, TensorFlow",Master,4,Finance,2025-04-16,2025-05-28,676,6.5,Digital Transformation LLC +AI06021,AI Specialist,44333,USD,44333,MI,FL,India,L,Canada,50,"Scala, Linux, Python",Master,3,Consulting,2025-02-06,2025-02-27,566,9.2,Cloud AI Solutions +AI06022,AI Architect,142509,USD,142509,SE,CT,Denmark,S,Denmark,100,"Computer Vision, TensorFlow, Mathematics, NLP",Associate,5,Telecommunications,2024-08-23,2024-10-30,1296,6.9,Cloud AI Solutions +AI06023,Robotics Engineer,55014,USD,55014,MI,CT,China,L,Ireland,0,"R, Python, Tableau",PhD,2,Healthcare,2024-08-13,2024-10-02,2362,9.8,Autonomous Tech +AI06024,AI Consultant,195813,JPY,21539430,EX,FL,Japan,M,Turkey,100,"GCP, Python, AWS, SQL, TensorFlow",Associate,14,Automotive,2024-01-05,2024-01-29,2233,8.2,AI Innovations +AI06025,Data Scientist,43954,USD,43954,SE,FL,China,S,Romania,100,"Java, Linux, Mathematics, Data Visualization",PhD,6,Energy,2024-03-29,2024-06-03,1318,7.5,Machine Intelligence Group +AI06026,Autonomous Systems Engineer,99890,CAD,124863,MI,FL,Canada,L,Canada,50,"Git, SQL, Computer Vision",PhD,3,Media,2024-10-13,2024-11-23,1008,6.3,Algorithmic Solutions +AI06027,AI Specialist,178380,JPY,19621800,SE,CT,Japan,L,Japan,0,"Git, MLOps, TensorFlow, Python, Tableau",Bachelor,8,Media,2025-03-26,2025-04-22,1368,6.1,Neural Networks Co +AI06028,Principal Data Scientist,121764,USD,121764,SE,FT,Finland,S,South Africa,100,"GCP, Hadoop, Python, TensorFlow, Kubernetes",Master,8,Media,2024-12-17,2025-01-05,2150,5.6,AI Innovations +AI06029,AI Research Scientist,148778,JPY,16365580,EX,FT,Japan,M,Japan,100,"Linux, Java, Data Visualization, Tableau, Kubernetes",Associate,15,Media,2024-03-28,2024-05-07,966,5.3,Digital Transformation LLC +AI06030,ML Ops Engineer,139963,CHF,125967,SE,PT,Switzerland,S,Portugal,100,"Hadoop, NLP, Java, Computer Vision",Master,9,Real Estate,2024-08-31,2024-10-15,1961,7.4,AI Innovations +AI06031,Deep Learning Engineer,75640,GBP,56730,EN,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, Hadoop, Spark",PhD,1,Finance,2024-09-10,2024-11-13,2183,8,Cloud AI Solutions +AI06032,AI Research Scientist,78384,USD,78384,MI,FL,Ireland,M,Ireland,50,"GCP, Spark, Data Visualization",Associate,3,Transportation,2024-04-30,2024-06-01,712,6.2,DataVision Ltd +AI06033,AI Research Scientist,50999,USD,50999,MI,FL,China,L,China,100,"Python, NLP, Kubernetes",PhD,3,Manufacturing,2024-07-26,2024-08-22,1225,5.9,DeepTech Ventures +AI06034,AI Research Scientist,61119,EUR,51951,EN,FL,Germany,L,South Africa,50,"GCP, Scala, TensorFlow, Python, Mathematics",PhD,0,Media,2025-03-20,2025-04-11,1428,8.5,Neural Networks Co +AI06035,AI Architect,99511,SGD,129364,MI,FT,Singapore,L,Latvia,100,"R, Java, Tableau, Python, Linux",Bachelor,4,Finance,2024-04-19,2024-06-06,2368,6.8,Neural Networks Co +AI06036,Deep Learning Engineer,208119,EUR,176901,EX,PT,Germany,S,Germany,0,"PyTorch, Spark, Scala, Java",Associate,12,Technology,2024-05-13,2024-06-24,2228,7,Predictive Systems +AI06037,NLP Engineer,64737,USD,64737,EN,FL,South Korea,L,Egypt,0,"SQL, NLP, MLOps, GCP, Tableau",Associate,1,Real Estate,2024-09-08,2024-09-24,1189,6.3,Machine Intelligence Group +AI06038,Deep Learning Engineer,85166,USD,85166,EX,PT,China,L,China,0,"Java, PyTorch, Mathematics, AWS",PhD,12,Real Estate,2024-03-16,2024-05-04,1675,6.2,Quantum Computing Inc +AI06039,AI Specialist,132470,EUR,112600,MI,FT,Netherlands,L,Belgium,100,"Deep Learning, Kubernetes, GCP, Statistics, Computer Vision",Bachelor,2,Consulting,2024-10-15,2024-12-27,1763,7,Advanced Robotics +AI06040,AI Product Manager,27118,USD,27118,EN,FL,China,S,China,0,"Data Visualization, Python, TensorFlow, Spark",PhD,1,Consulting,2024-06-20,2024-08-19,2259,8.4,Neural Networks Co +AI06041,Head of AI,189995,EUR,161496,EX,FL,Germany,S,Denmark,100,"Scala, GCP, Java, Linux",PhD,13,Finance,2025-02-25,2025-03-13,2204,9,Machine Intelligence Group +AI06042,NLP Engineer,182291,CAD,227864,EX,FL,Canada,M,Turkey,50,"GCP, Java, SQL, NLP, Docker",PhD,15,Media,2025-04-25,2025-06-06,1075,6.7,DataVision Ltd +AI06043,AI Specialist,58125,AUD,78469,EN,FL,Australia,M,Argentina,100,"Python, Mathematics, TensorFlow, Azure, Linux",Associate,0,Technology,2024-07-24,2024-08-29,751,7.1,DataVision Ltd +AI06044,Deep Learning Engineer,304701,CHF,274231,EX,PT,Switzerland,M,Switzerland,100,"Git, Linux, Tableau",Associate,15,Energy,2024-08-08,2024-10-14,990,7.1,Digital Transformation LLC +AI06045,Machine Learning Engineer,28807,USD,28807,EN,PT,India,L,India,50,"R, Python, Docker",Master,0,Retail,2024-04-06,2024-06-09,2227,8.6,Algorithmic Solutions +AI06046,AI Research Scientist,119295,CHF,107366,MI,FT,Switzerland,S,Switzerland,100,"Mathematics, TensorFlow, NLP, Scala",Master,4,Government,2024-12-20,2025-01-05,1352,6.2,Neural Networks Co +AI06047,Data Engineer,75061,EUR,63802,MI,CT,Germany,S,Germany,100,"Python, Statistics, Linux, Spark, Deep Learning",Master,4,Gaming,2025-03-25,2025-05-31,2222,7.7,DeepTech Ventures +AI06048,Principal Data Scientist,134979,EUR,114732,SE,FL,Austria,M,Netherlands,50,"Mathematics, PyTorch, Tableau, Linux",Master,7,Government,2024-06-11,2024-08-07,1909,8.4,DeepTech Ventures +AI06049,Computer Vision Engineer,138134,GBP,103601,SE,FL,United Kingdom,S,United Kingdom,50,"SQL, Kubernetes, Python",Master,6,Real Estate,2024-02-01,2024-02-28,507,5.4,Smart Analytics +AI06050,Head of AI,71317,USD,71317,EN,PT,Ireland,M,Ireland,100,"Deep Learning, Data Visualization, Linux",Associate,1,Education,2025-04-20,2025-06-20,2132,9.6,AI Innovations +AI06051,Robotics Engineer,238482,JPY,26233020,EX,FL,Japan,S,Japan,100,"Data Visualization, Git, Kubernetes, NLP, Python",Master,17,Manufacturing,2024-02-06,2024-03-01,1858,8.4,Future Systems +AI06052,Computer Vision Engineer,217112,EUR,184545,EX,PT,France,L,France,100,"Mathematics, Python, Azure, Linux",Bachelor,17,Retail,2025-01-11,2025-02-09,2235,7.7,Predictive Systems +AI06053,AI Architect,91189,AUD,123105,MI,FT,Australia,S,Australia,50,"MLOps, Kubernetes, R, SQL",Master,4,Government,2025-03-19,2025-05-24,1179,6,Digital Transformation LLC +AI06054,AI Software Engineer,31432,USD,31432,MI,PT,India,M,India,0,"Python, Statistics, TensorFlow, Kubernetes, Azure",PhD,2,Finance,2025-03-14,2025-04-09,1250,7.7,Future Systems +AI06055,AI Software Engineer,203827,EUR,173253,EX,FL,Austria,L,Austria,100,"PyTorch, Python, TensorFlow, Statistics, Data Visualization",Associate,19,Finance,2024-07-13,2024-09-09,2138,7.5,Predictive Systems +AI06056,Data Engineer,78958,EUR,67114,MI,CT,France,M,Ukraine,50,"Mathematics, Azure, Tableau, NLP",Master,3,Education,2024-07-08,2024-08-17,2012,8.5,TechCorp Inc +AI06057,Robotics Engineer,100020,AUD,135027,SE,FT,Australia,S,Australia,50,"Kubernetes, NLP, R, Computer Vision",PhD,9,Finance,2024-08-15,2024-09-09,1515,8.7,Advanced Robotics +AI06058,AI Consultant,168504,USD,168504,EX,FT,Israel,L,Israel,100,"R, SQL, Hadoop, Docker",Bachelor,17,Government,2024-10-15,2024-11-07,1388,9.3,Machine Intelligence Group +AI06059,Deep Learning Engineer,59253,USD,59253,EN,CT,Finland,S,New Zealand,100,"Kubernetes, Computer Vision, TensorFlow",Bachelor,1,Finance,2024-04-02,2024-06-11,2238,6.6,DataVision Ltd +AI06060,Computer Vision Engineer,74984,USD,74984,EX,FT,China,S,Turkey,50,"Hadoop, Data Visualization, Git",PhD,15,Education,2024-07-14,2024-09-23,1980,8.3,Cloud AI Solutions +AI06061,Robotics Engineer,236625,USD,236625,EX,CT,Finland,M,Portugal,100,"Hadoop, Deep Learning, TensorFlow, SQL",Master,15,Energy,2024-09-07,2024-11-09,1087,6.7,Neural Networks Co +AI06062,AI Product Manager,111066,USD,111066,SE,FT,United States,S,United States,0,"SQL, Scala, MLOps",Master,6,Automotive,2025-03-28,2025-05-29,2442,7.6,Cloud AI Solutions +AI06063,AI Research Scientist,123116,USD,123116,MI,PT,Denmark,M,Denmark,100,"Git, Java, NLP",Master,4,Healthcare,2024-02-03,2024-02-26,694,5.7,Advanced Robotics +AI06064,AI Software Engineer,72971,EUR,62025,EN,CT,Netherlands,S,Finland,50,"Git, AWS, Data Visualization, Java",Bachelor,1,Gaming,2024-11-10,2024-11-28,1884,9,AI Innovations +AI06065,Head of AI,73070,CAD,91338,EN,FL,Canada,L,Canada,100,"Linux, Azure, Python",Bachelor,0,Retail,2024-03-06,2024-05-18,1253,6.3,Advanced Robotics +AI06066,Data Engineer,73301,USD,73301,EN,CT,Israel,M,Ukraine,50,"R, Git, Tableau",PhD,0,Manufacturing,2024-12-07,2025-01-16,1946,9.1,AI Innovations +AI06067,Research Scientist,46090,USD,46090,MI,FT,China,L,China,50,"TensorFlow, Kubernetes, Mathematics, PyTorch, AWS",PhD,3,Media,2024-09-03,2024-10-13,2485,8.4,Digital Transformation LLC +AI06068,Principal Data Scientist,268531,USD,268531,EX,FT,Sweden,L,Sweden,50,"SQL, GCP, Statistics",PhD,11,Media,2025-02-13,2025-04-20,1051,5.8,Autonomous Tech +AI06069,Robotics Engineer,116014,CHF,104413,MI,PT,Switzerland,M,Switzerland,100,"Docker, Hadoop, NLP, Kubernetes, Scala",PhD,3,Manufacturing,2024-08-14,2024-10-07,1865,6.8,Cloud AI Solutions +AI06070,Data Analyst,112161,USD,112161,MI,FT,Sweden,L,Sweden,0,"R, Spark, SQL, GCP",Bachelor,2,Gaming,2024-04-03,2024-05-16,2499,9.1,Predictive Systems +AI06071,AI Specialist,62287,USD,62287,EX,FT,India,L,Luxembourg,100,"Tableau, Computer Vision, GCP, Data Visualization",Associate,17,Automotive,2024-07-12,2024-08-10,2286,6.4,Quantum Computing Inc +AI06072,NLP Engineer,71300,USD,71300,EN,FL,Israel,M,Israel,50,"GCP, Spark, PyTorch",Bachelor,0,Consulting,2024-10-19,2024-11-26,2200,6.2,Future Systems +AI06073,Machine Learning Engineer,65583,USD,65583,MI,PT,Finland,S,Russia,0,"R, Kubernetes, Mathematics",Associate,2,Media,2025-02-21,2025-04-14,733,8.9,Future Systems +AI06074,Autonomous Systems Engineer,175971,EUR,149575,EX,PT,Austria,S,Austria,100,"Kubernetes, Computer Vision, GCP, SQL",Bachelor,11,Retail,2025-03-21,2025-05-23,1930,9.4,DeepTech Ventures +AI06075,Robotics Engineer,29541,USD,29541,MI,PT,India,M,India,0,"Python, Docker, Linux",Master,3,Gaming,2025-04-02,2025-04-20,1449,6.3,Advanced Robotics +AI06076,Computer Vision Engineer,76318,USD,76318,MI,PT,South Korea,M,Norway,0,"PyTorch, Java, TensorFlow",Master,2,Technology,2025-02-08,2025-03-07,1449,7.9,DeepTech Ventures +AI06077,AI Consultant,257587,USD,257587,EX,PT,Denmark,S,Denmark,50,"Hadoop, Linux, Deep Learning, Scala, R",Bachelor,11,Healthcare,2024-02-05,2024-03-09,1770,5.1,Smart Analytics +AI06078,Autonomous Systems Engineer,188465,EUR,160195,EX,CT,Austria,S,Austria,50,"Hadoop, Python, NLP",PhD,12,Healthcare,2024-02-06,2024-03-19,1220,8.7,Cloud AI Solutions +AI06079,Robotics Engineer,106976,USD,106976,MI,CT,Ireland,L,Ireland,50,"Java, Kubernetes, GCP, Deep Learning, MLOps",PhD,4,Consulting,2024-11-30,2025-01-12,1164,8.7,AI Innovations +AI06080,Autonomous Systems Engineer,142983,EUR,121536,EX,CT,Germany,M,Germany,50,"TensorFlow, Mathematics, GCP, Python",Master,13,Technology,2024-06-20,2024-08-16,1906,6.4,Predictive Systems +AI06081,AI Research Scientist,61577,USD,61577,EN,CT,Sweden,S,Israel,100,"Python, Tableau, Kubernetes, Scala",PhD,0,Finance,2025-04-13,2025-05-05,2097,5.8,Autonomous Tech +AI06082,Machine Learning Engineer,89159,AUD,120365,MI,FL,Australia,S,Australia,0,"Git, AWS, Data Visualization, Hadoop, Tableau",PhD,2,Government,2024-02-25,2024-04-05,2019,7.9,Algorithmic Solutions +AI06083,AI Research Scientist,98446,USD,98446,EN,FT,Denmark,M,Denmark,100,"Kubernetes, Linux, Scala, Mathematics, MLOps",Associate,0,Technology,2024-07-13,2024-09-22,2393,6.7,DataVision Ltd +AI06084,Machine Learning Engineer,50109,GBP,37582,EN,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, Kubernetes, NLP",Bachelor,1,Healthcare,2025-01-04,2025-02-18,2307,5.3,Cognitive Computing +AI06085,Machine Learning Researcher,78378,USD,78378,MI,FL,South Korea,S,South Korea,0,"Git, Deep Learning, Kubernetes, SQL",Master,4,Media,2024-06-25,2024-09-06,1328,9.3,DataVision Ltd +AI06086,Deep Learning Engineer,72771,CAD,90964,MI,CT,Canada,S,Canada,50,"PyTorch, TensorFlow, Data Visualization",Associate,4,Automotive,2025-03-24,2025-06-04,2063,6.6,Future Systems +AI06087,Data Engineer,269658,USD,269658,EX,CT,Finland,L,Finland,0,"SQL, Hadoop, R, GCP",Bachelor,18,Consulting,2024-09-14,2024-10-25,2037,5.7,Cognitive Computing +AI06088,ML Ops Engineer,94499,CAD,118124,SE,PT,Canada,S,United Kingdom,50,"Data Visualization, MLOps, Git",PhD,6,Media,2024-06-26,2024-08-21,2299,8.2,TechCorp Inc +AI06089,Autonomous Systems Engineer,98191,EUR,83462,MI,FT,France,M,France,0,"Scala, PyTorch, SQL",Master,2,Gaming,2024-10-23,2024-11-10,1994,6.3,Smart Analytics +AI06090,AI Software Engineer,52424,EUR,44560,EN,FL,France,M,Vietnam,50,"Kubernetes, Docker, Tableau, PyTorch, Java",Bachelor,1,Gaming,2024-02-28,2024-05-08,1715,8.9,DeepTech Ventures +AI06091,AI Consultant,58246,EUR,49509,EN,PT,Germany,M,Belgium,0,"Hadoop, Spark, NLP",Master,1,Transportation,2024-09-06,2024-11-12,859,8.7,Quantum Computing Inc +AI06092,Head of AI,267949,AUD,361731,EX,CT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, Python",Bachelor,10,Telecommunications,2024-03-12,2024-04-30,707,9.7,Machine Intelligence Group +AI06093,Machine Learning Engineer,70389,USD,70389,EN,FT,Sweden,S,Thailand,100,"Hadoop, Computer Vision, NLP, Azure, Spark",Master,0,Media,2025-02-27,2025-04-12,861,6.6,Cloud AI Solutions +AI06094,Computer Vision Engineer,189799,USD,189799,EX,FL,Denmark,M,Denmark,100,"Hadoop, Python, TensorFlow, MLOps",Bachelor,17,Energy,2024-08-16,2024-10-16,1028,8.6,Machine Intelligence Group +AI06095,Deep Learning Engineer,71097,USD,71097,EN,CT,South Korea,L,South Korea,0,"SQL, TensorFlow, GCP",Master,0,Media,2025-04-02,2025-06-13,1765,8.6,Cognitive Computing +AI06096,ML Ops Engineer,129008,GBP,96756,MI,CT,United Kingdom,L,United Kingdom,0,"SQL, Hadoop, MLOps, Git",Master,4,Government,2025-04-15,2025-05-30,1561,10,Algorithmic Solutions +AI06097,Robotics Engineer,75236,EUR,63951,MI,FL,Netherlands,S,Netherlands,0,"MLOps, Spark, Docker",Associate,3,Consulting,2024-08-04,2024-08-30,664,9.2,Machine Intelligence Group +AI06098,Autonomous Systems Engineer,169125,USD,169125,EX,CT,Denmark,S,Denmark,0,"Data Visualization, Spark, PyTorch, Hadoop, Python",Bachelor,11,Education,2025-02-13,2025-04-10,2098,8.5,Neural Networks Co +AI06099,AI Software Engineer,109880,USD,109880,SE,CT,Israel,M,Israel,100,"SQL, Hadoop, NLP, Deep Learning",Bachelor,9,Gaming,2024-10-11,2024-11-07,804,9.5,Smart Analytics +AI06100,NLP Engineer,122068,USD,122068,MI,PT,United States,L,United States,100,"Kubernetes, Tableau, SQL",PhD,3,Consulting,2024-04-07,2024-04-26,1213,7.9,Cognitive Computing +AI06101,AI Specialist,62513,USD,62513,SE,FL,China,S,Romania,0,"Python, Scala, R, Hadoop, SQL",Associate,8,Consulting,2025-02-28,2025-04-09,1022,8.5,Neural Networks Co +AI06102,AI Software Engineer,67497,USD,67497,EN,CT,Denmark,M,Denmark,100,"Scala, Spark, R",Master,1,Energy,2024-07-05,2024-09-03,1542,8,Digital Transformation LLC +AI06103,Robotics Engineer,68328,USD,68328,SE,FL,China,M,China,50,"R, Java, Tableau",Associate,9,Telecommunications,2024-02-06,2024-03-13,630,6.4,DeepTech Ventures +AI06104,Research Scientist,73887,CAD,92359,EN,PT,Canada,M,Canada,0,"NLP, SQL, R, PyTorch",Bachelor,0,Healthcare,2024-03-30,2024-06-03,2057,6.9,DataVision Ltd +AI06105,Deep Learning Engineer,85387,EUR,72579,MI,PT,France,M,France,50,"Azure, Python, Spark",Master,4,Technology,2024-02-27,2024-03-27,541,7.3,Digital Transformation LLC +AI06106,Data Engineer,81892,JPY,9008120,MI,FT,Japan,S,Japan,0,"NLP, Kubernetes, Data Visualization",PhD,3,Consulting,2024-06-30,2024-07-28,1150,7.3,DeepTech Ventures +AI06107,Autonomous Systems Engineer,125416,SGD,163041,SE,FL,Singapore,S,South Korea,0,"SQL, Python, Azure, Deep Learning",PhD,9,Energy,2024-10-23,2024-12-05,1037,5.6,Algorithmic Solutions +AI06108,Research Scientist,362104,USD,362104,EX,FL,Norway,L,Norway,0,"TensorFlow, Docker, PyTorch",Bachelor,14,Finance,2024-05-23,2024-07-24,2245,8.5,Algorithmic Solutions +AI06109,Machine Learning Engineer,109467,EUR,93047,SE,FT,France,S,France,0,"TensorFlow, Docker, Python",Bachelor,5,Government,2025-01-07,2025-03-12,1615,8.2,Neural Networks Co +AI06110,AI Software Engineer,74992,USD,74992,MI,FT,Israel,S,Denmark,100,"R, SQL, MLOps, AWS",Bachelor,2,Education,2024-10-09,2024-12-15,1285,7.3,Machine Intelligence Group +AI06111,AI Research Scientist,83813,USD,83813,EX,CT,China,S,China,50,"Python, Mathematics, TensorFlow, Data Visualization, Computer Vision",Bachelor,15,Education,2024-01-23,2024-03-07,1797,6.7,Quantum Computing Inc +AI06112,Data Scientist,98188,CHF,88369,EN,FT,Switzerland,S,Switzerland,100,"Spark, PyTorch, TensorFlow, Hadoop",Master,0,Gaming,2024-05-16,2024-06-11,1249,8.7,Advanced Robotics +AI06113,AI Architect,120407,USD,120407,EX,FT,Finland,S,Italy,0,"Deep Learning, R, MLOps, Computer Vision, Azure",PhD,17,Education,2024-11-17,2024-12-31,763,8.5,Algorithmic Solutions +AI06114,Deep Learning Engineer,187126,EUR,159057,EX,PT,France,M,France,0,"Linux, Docker, Computer Vision",Bachelor,18,Energy,2024-04-24,2024-06-23,2499,8.6,AI Innovations +AI06115,Autonomous Systems Engineer,55832,USD,55832,SE,FT,China,M,China,100,"Spark, Statistics, MLOps",PhD,9,Media,2025-03-27,2025-05-29,1242,5.5,Cognitive Computing +AI06116,Data Scientist,99693,USD,99693,MI,FL,Norway,S,Denmark,100,"TensorFlow, PyTorch, MLOps, GCP",Bachelor,2,Automotive,2024-03-06,2024-04-27,580,6.6,Smart Analytics +AI06117,Principal Data Scientist,111940,AUD,151119,SE,PT,Australia,M,South Korea,100,"Python, R, GCP, TensorFlow, Linux",Bachelor,8,Energy,2024-05-05,2024-06-15,601,9.9,Neural Networks Co +AI06118,AI Consultant,350058,USD,350058,EX,CT,Norway,L,Malaysia,50,"SQL, TensorFlow, Data Visualization, Hadoop",PhD,19,Healthcare,2024-02-19,2024-04-02,2435,8.6,Predictive Systems +AI06119,AI Product Manager,118196,EUR,100467,SE,PT,Germany,S,Germany,0,"Computer Vision, Tableau, SQL, Deep Learning, Linux",Bachelor,7,Technology,2024-07-15,2024-09-25,960,7.6,Advanced Robotics +AI06120,Data Analyst,149669,USD,149669,EX,FT,South Korea,L,South Korea,0,"AWS, GCP, Git, Computer Vision, Hadoop",Associate,18,Government,2025-01-14,2025-02-27,1730,7.8,Future Systems +AI06121,AI Architect,207625,CHF,186863,EX,PT,Switzerland,S,Switzerland,0,"GCP, Statistics, NLP, Computer Vision, Spark",Master,10,Transportation,2025-03-30,2025-05-02,2116,8.4,DeepTech Ventures +AI06122,AI Specialist,179611,CHF,161650,SE,PT,Switzerland,M,Switzerland,100,"Scala, TensorFlow, GCP",Associate,5,Media,2025-03-08,2025-04-07,1131,8.8,TechCorp Inc +AI06123,Deep Learning Engineer,72594,USD,72594,MI,FT,Israel,S,Israel,100,"PyTorch, Computer Vision, Tableau, AWS, SQL",Bachelor,4,Education,2024-04-01,2024-05-30,1372,7.6,TechCorp Inc +AI06124,Data Engineer,74990,USD,74990,MI,FL,Ireland,S,Ireland,100,"Spark, Statistics, Data Visualization, Linux",Associate,4,Transportation,2025-01-06,2025-03-19,1208,8.6,Digital Transformation LLC +AI06125,Principal Data Scientist,128233,USD,128233,SE,PT,United States,S,New Zealand,100,"AWS, MLOps, Mathematics",Bachelor,9,Automotive,2024-12-17,2025-01-26,505,9.1,DataVision Ltd +AI06126,AI Specialist,211020,USD,211020,EX,FT,Denmark,S,Denmark,100,"Git, Python, Deep Learning, Computer Vision",Bachelor,19,Technology,2024-08-17,2024-10-08,717,8.6,Quantum Computing Inc +AI06127,Data Engineer,81260,USD,81260,MI,FL,Sweden,S,Sweden,100,"Hadoop, Azure, Mathematics, TensorFlow, MLOps",Master,4,Gaming,2025-02-15,2025-03-05,733,9.9,DataVision Ltd +AI06128,Data Analyst,119633,EUR,101688,SE,PT,France,M,Thailand,50,"SQL, Kubernetes, Linux",Bachelor,7,Government,2024-01-18,2024-03-20,1998,7.5,Cognitive Computing +AI06129,Machine Learning Engineer,73814,USD,73814,MI,PT,Finland,M,Finland,100,"Python, Spark, TensorFlow, Data Visualization, AWS",PhD,4,Technology,2024-02-19,2024-04-20,1409,8.1,DataVision Ltd +AI06130,AI Specialist,288274,EUR,245033,EX,FT,Germany,L,Indonesia,0,"GCP, SQL, AWS",Associate,13,Automotive,2024-09-29,2024-11-30,1683,9.7,Cloud AI Solutions +AI06131,AI Architect,194644,USD,194644,EX,PT,United States,M,United States,100,"Python, Spark, R, Data Visualization, Scala",Master,19,Energy,2024-04-27,2024-06-20,585,9.8,Neural Networks Co +AI06132,AI Software Engineer,116370,JPY,12800700,MI,FL,Japan,M,Japan,100,"AWS, Scala, GCP",Master,4,Gaming,2025-04-07,2025-05-27,1512,9.3,AI Innovations +AI06133,Robotics Engineer,58648,USD,58648,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Mathematics, Spark",PhD,0,Retail,2024-09-14,2024-10-31,2333,7.3,Smart Analytics +AI06134,Head of AI,94136,EUR,80016,MI,FT,France,L,France,0,"SQL, PyTorch, Docker, Statistics",Associate,2,Technology,2024-08-17,2024-10-02,1740,5.9,Neural Networks Co +AI06135,ML Ops Engineer,60881,JPY,6696910,EN,FT,Japan,S,Japan,50,"SQL, AWS, Tableau, R, NLP",Associate,1,Retail,2024-05-13,2024-07-08,2420,9.3,Advanced Robotics +AI06136,NLP Engineer,134266,USD,134266,SE,CT,United States,S,United States,0,"Tableau, GCP, TensorFlow, Docker",PhD,6,Media,2024-04-22,2024-05-09,2340,9.2,Advanced Robotics +AI06137,Head of AI,61969,USD,61969,SE,PT,China,S,China,50,"Kubernetes, SQL, Deep Learning, Statistics, MLOps",Master,7,Energy,2024-08-05,2024-09-14,903,7,Algorithmic Solutions +AI06138,Machine Learning Engineer,122843,CAD,153554,SE,FT,Canada,S,Canada,0,"R, Java, Data Visualization, Python, AWS",Bachelor,9,Healthcare,2025-01-07,2025-02-14,1013,5.8,Quantum Computing Inc +AI06139,AI Specialist,127779,USD,127779,SE,CT,Finland,L,Finland,50,"Docker, Data Visualization, Python",Bachelor,8,Consulting,2025-03-06,2025-04-27,2111,5.8,Machine Intelligence Group +AI06140,AI Architect,27705,USD,27705,MI,FT,India,M,Spain,50,"Linux, Tableau, NLP, Azure",Master,2,Retail,2024-02-21,2024-04-12,1650,6.3,Digital Transformation LLC +AI06141,AI Architect,31007,USD,31007,MI,PT,India,S,India,50,"Python, Docker, Deep Learning, Java, NLP",Bachelor,3,Finance,2025-04-23,2025-05-30,1414,9.3,Cognitive Computing +AI06142,Head of AI,159103,USD,159103,SE,CT,Denmark,L,China,0,"GCP, Hadoop, SQL",PhD,9,Manufacturing,2024-08-25,2024-09-13,1683,6.3,Quantum Computing Inc +AI06143,AI Specialist,81172,USD,81172,MI,FT,Ireland,M,Ireland,50,"Python, Docker, Deep Learning, Azure, GCP",Associate,3,Consulting,2024-05-24,2024-07-10,710,8,TechCorp Inc +AI06144,Deep Learning Engineer,38128,USD,38128,EN,PT,China,L,Canada,100,"Docker, TensorFlow, Hadoop",Associate,0,Media,2024-04-09,2024-06-19,1299,6,AI Innovations +AI06145,Data Engineer,128255,EUR,109017,SE,FT,Germany,S,India,100,"Statistics, Kubernetes, R, GCP",Associate,6,Gaming,2024-03-16,2024-04-27,1216,7.4,TechCorp Inc +AI06146,ML Ops Engineer,101526,USD,101526,SE,FT,Finland,S,Finland,0,"Hadoop, PyTorch, Java, Statistics",Master,7,Media,2024-09-28,2024-10-20,1406,5.7,Algorithmic Solutions +AI06147,Robotics Engineer,46864,AUD,63266,EN,FL,Australia,S,Australia,100,"Azure, Kubernetes, Python, Deep Learning",PhD,1,Telecommunications,2024-11-04,2024-12-30,540,6.2,Smart Analytics +AI06148,Autonomous Systems Engineer,115707,CHF,104136,MI,CT,Switzerland,M,South Africa,50,"NLP, Python, SQL, TensorFlow",Master,3,Media,2024-04-07,2024-05-14,1458,6.7,DeepTech Ventures +AI06149,Data Engineer,94886,USD,94886,MI,FT,Sweden,L,Norway,100,"Statistics, Git, Spark",Bachelor,2,Automotive,2024-01-16,2024-01-31,1256,6.2,Neural Networks Co +AI06150,AI Research Scientist,66330,USD,66330,EN,FL,Ireland,M,Norway,50,"Python, AWS, Azure",Master,1,Real Estate,2024-01-16,2024-02-23,1111,8,Quantum Computing Inc +AI06151,Machine Learning Researcher,66467,EUR,56497,MI,PT,Austria,S,Austria,50,"Linux, SQL, Computer Vision, PyTorch",Bachelor,2,Education,2024-12-27,2025-02-15,1854,5.5,Neural Networks Co +AI06152,Data Scientist,112672,SGD,146474,MI,FT,Singapore,L,Singapore,100,"NLP, Python, Linux, GCP, Git",Associate,2,Education,2024-10-07,2024-11-28,1006,9.8,Digital Transformation LLC +AI06153,Deep Learning Engineer,92337,EUR,78486,MI,FT,Netherlands,M,Netherlands,50,"Mathematics, GCP, Computer Vision, Python",Bachelor,2,Gaming,2024-04-02,2024-05-15,1553,7.1,Smart Analytics +AI06154,ML Ops Engineer,77521,EUR,65893,EN,FL,Germany,L,Japan,100,"Deep Learning, Mathematics, Data Visualization, SQL, Azure",Associate,0,Telecommunications,2024-01-03,2024-03-15,573,7.7,Digital Transformation LLC +AI06155,AI Research Scientist,323583,CHF,291225,EX,FL,Switzerland,L,Kenya,0,"Azure, Java, AWS, Mathematics",Master,13,Manufacturing,2024-05-20,2024-07-29,1566,8.7,Cloud AI Solutions +AI06156,ML Ops Engineer,123796,GBP,92847,MI,FL,United Kingdom,L,Ukraine,0,"Python, Java, Azure",PhD,4,Media,2024-11-05,2024-12-27,2211,6.3,Advanced Robotics +AI06157,Data Engineer,191974,USD,191974,EX,FT,United States,L,United States,100,"Scala, Python, Git, AWS, Spark",Associate,15,Transportation,2024-06-12,2024-08-14,2068,8.2,Neural Networks Co +AI06158,Machine Learning Engineer,92459,USD,92459,MI,CT,Sweden,L,Sweden,0,"Deep Learning, Data Visualization, Statistics, Computer Vision, Azure",Bachelor,3,Energy,2024-03-03,2024-05-12,1148,5.1,Cognitive Computing +AI06159,Deep Learning Engineer,99147,EUR,84275,MI,FT,Germany,S,Germany,50,"Scala, TensorFlow, Spark",Associate,2,Gaming,2025-03-04,2025-04-08,1132,7.1,Machine Intelligence Group +AI06160,Principal Data Scientist,86412,CHF,77771,EN,CT,Switzerland,L,Turkey,0,"AWS, Azure, Git, Data Visualization, SQL",Master,0,Real Estate,2025-03-13,2025-04-06,2437,5.2,Algorithmic Solutions +AI06161,Machine Learning Engineer,208435,USD,208435,EX,FL,Finland,S,Czech Republic,100,"GCP, Scala, SQL",Master,19,Energy,2025-01-03,2025-02-18,2064,5.1,Algorithmic Solutions +AI06162,Head of AI,126593,CHF,113934,MI,FT,Switzerland,M,Switzerland,0,"Spark, Git, Linux",PhD,3,Education,2024-12-21,2025-01-12,1142,7,Neural Networks Co +AI06163,ML Ops Engineer,141683,USD,141683,SE,FL,Denmark,S,Denmark,100,"MLOps, NLP, Python, SQL, R",Associate,7,Finance,2024-02-21,2024-04-15,961,8.5,AI Innovations +AI06164,Data Engineer,72525,USD,72525,EN,PT,Norway,M,Austria,50,"Scala, Statistics, Git, SQL, Linux",PhD,1,Media,2024-04-11,2024-06-07,2328,5.4,Autonomous Tech +AI06165,Head of AI,210148,EUR,178626,EX,FL,Netherlands,S,Netherlands,50,"Git, Linux, Deep Learning, Data Visualization",Associate,16,Technology,2024-11-30,2025-01-04,1851,7.5,Algorithmic Solutions +AI06166,Data Engineer,100933,USD,100933,EX,CT,India,L,India,50,"Hadoop, MLOps, Docker, Git, Spark",Master,18,Government,2024-04-04,2024-05-21,1702,8,AI Innovations +AI06167,AI Product Manager,133499,USD,133499,SE,FT,Denmark,M,Denmark,100,"Spark, PyTorch, Linux",PhD,6,Manufacturing,2024-11-27,2024-12-29,1819,9.2,Algorithmic Solutions +AI06168,Computer Vision Engineer,143384,USD,143384,EX,PT,South Korea,S,South Korea,0,"MLOps, GCP, Docker, Statistics",PhD,19,Technology,2024-01-15,2024-02-23,1599,9.1,Cognitive Computing +AI06169,Head of AI,83098,USD,83098,EN,FL,Denmark,S,Denmark,50,"Linux, SQL, Spark",Associate,0,Telecommunications,2024-02-21,2024-03-12,1501,6.1,DeepTech Ventures +AI06170,ML Ops Engineer,58485,USD,58485,EN,CT,South Korea,S,South Korea,50,"NLP, Azure, Python",Master,1,Government,2024-09-02,2024-10-17,2191,7.2,Advanced Robotics +AI06171,AI Architect,43970,USD,43970,MI,PT,China,M,Luxembourg,0,"Computer Vision, MLOps, NLP, Statistics, PyTorch",PhD,4,Consulting,2025-01-29,2025-03-02,780,7.5,AI Innovations +AI06172,Head of AI,410273,CHF,369246,EX,FT,Switzerland,L,Switzerland,50,"Python, TensorFlow, Deep Learning",PhD,19,Education,2024-03-01,2024-03-28,1739,7,Machine Intelligence Group +AI06173,Principal Data Scientist,76227,SGD,99095,EN,CT,Singapore,L,Canada,50,"Python, Azure, TensorFlow, Java, Docker",Bachelor,0,Real Estate,2024-07-11,2024-09-12,1081,6.2,Predictive Systems +AI06174,Deep Learning Engineer,121236,CAD,151545,SE,FL,Canada,M,Canada,0,"TensorFlow, Linux, Python, MLOps",Bachelor,7,Energy,2024-02-10,2024-04-19,526,6.8,Cognitive Computing +AI06175,Computer Vision Engineer,82912,AUD,111931,EN,CT,Australia,L,Australia,50,"Python, Kubernetes, Tableau, TensorFlow, Deep Learning",Master,1,Consulting,2025-04-15,2025-05-28,1620,8.3,DeepTech Ventures +AI06176,Autonomous Systems Engineer,227232,AUD,306763,EX,FL,Australia,L,Australia,100,"Python, MLOps, SQL, Spark",Associate,14,Finance,2024-07-22,2024-09-21,1893,6,Cloud AI Solutions +AI06177,AI Specialist,46804,USD,46804,SE,FL,India,S,Italy,0,"Hadoop, Docker, Linux",Master,7,Real Estate,2024-06-02,2024-07-20,2125,6.9,Digital Transformation LLC +AI06178,Machine Learning Engineer,269514,USD,269514,EX,PT,Denmark,L,Denmark,50,"Java, Kubernetes, Data Visualization, Docker, GCP",PhD,16,Automotive,2024-07-21,2024-09-01,1570,9.7,Cloud AI Solutions +AI06179,NLP Engineer,37274,USD,37274,SE,CT,India,S,India,100,"GCP, R, Git, NLP",PhD,7,Technology,2024-01-29,2024-03-06,1576,8,TechCorp Inc +AI06180,Deep Learning Engineer,27007,USD,27007,EN,CT,China,M,China,50,"SQL, PyTorch, Git, Deep Learning, Azure",PhD,1,Finance,2024-12-06,2024-12-25,587,7.2,TechCorp Inc +AI06181,Research Scientist,80678,USD,80678,EX,PT,India,S,India,100,"R, Tableau, SQL",PhD,14,Gaming,2024-02-04,2024-04-11,1900,8.5,AI Innovations +AI06182,Data Engineer,270264,CHF,243238,EX,CT,Switzerland,M,Switzerland,0,"NLP, MLOps, Statistics, Scala",PhD,14,Retail,2024-10-28,2024-12-04,578,9.9,TechCorp Inc +AI06183,AI Product Manager,63878,EUR,54296,MI,FL,France,S,France,50,"Azure, Deep Learning, MLOps, TensorFlow, Kubernetes",PhD,3,Retail,2025-04-21,2025-05-16,2333,6,DataVision Ltd +AI06184,Research Scientist,280852,CHF,252767,EX,CT,Switzerland,L,Switzerland,0,"Git, Scala, Tableau, Linux, Statistics",Master,15,Transportation,2025-02-28,2025-05-04,562,9.8,Digital Transformation LLC +AI06185,Head of AI,103833,USD,103833,MI,FL,Ireland,M,Ireland,0,"PyTorch, Linux, Spark, Tableau, Deep Learning",Associate,3,Manufacturing,2024-05-18,2024-07-06,1743,7.9,Neural Networks Co +AI06186,AI Product Manager,200183,AUD,270247,EX,PT,Australia,S,Australia,50,"AWS, Python, Scala, Spark, Deep Learning",PhD,10,Retail,2024-06-06,2024-07-03,1737,6.9,Algorithmic Solutions +AI06187,Machine Learning Researcher,76963,USD,76963,EX,PT,India,M,India,100,"Kubernetes, Hadoop, Docker, Deep Learning, Statistics",PhD,15,Gaming,2025-04-01,2025-05-23,2228,6.1,TechCorp Inc +AI06188,NLP Engineer,119389,USD,119389,SE,PT,Sweden,M,Sweden,100,"Kubernetes, AWS, Python",Master,7,Healthcare,2024-04-06,2024-06-04,1618,6.8,AI Innovations +AI06189,Machine Learning Researcher,187897,EUR,159712,EX,FL,France,M,France,50,"Hadoop, GCP, Scala, Python, TensorFlow",Associate,18,Manufacturing,2024-04-02,2024-06-07,2109,5.5,TechCorp Inc +AI06190,AI Architect,82319,AUD,111131,MI,FL,Australia,M,Denmark,0,"Spark, Java, PyTorch, Docker, AWS",PhD,4,Manufacturing,2025-04-10,2025-06-01,2081,9.6,Predictive Systems +AI06191,Computer Vision Engineer,145319,USD,145319,SE,FT,Norway,M,Norway,100,"Java, MLOps, Linux, Python, GCP",Bachelor,7,Technology,2024-05-05,2024-05-27,549,7.3,Quantum Computing Inc +AI06192,Deep Learning Engineer,159987,EUR,135989,EX,FT,Germany,M,Germany,100,"Spark, Kubernetes, Deep Learning",PhD,15,Media,2024-11-22,2025-01-06,1827,8.1,DataVision Ltd +AI06193,AI Specialist,68999,USD,68999,EN,FT,United States,S,Russia,50,"Scala, Git, Data Visualization",Bachelor,0,Energy,2024-12-01,2025-02-10,2474,7.9,Predictive Systems +AI06194,Data Engineer,96411,JPY,10605210,MI,FT,Japan,M,Japan,100,"Statistics, Java, Git",Master,2,Education,2024-03-13,2024-05-24,1125,7.2,Advanced Robotics +AI06195,Robotics Engineer,262229,USD,262229,EX,PT,Sweden,L,Sweden,50,"Git, Kubernetes, Scala",PhD,17,Healthcare,2024-09-25,2024-12-05,1786,6,Advanced Robotics +AI06196,Data Analyst,77309,USD,77309,MI,CT,Israel,M,Israel,100,"SQL, Java, Python, Data Visualization",Associate,2,Automotive,2024-11-10,2025-01-19,823,6.1,Cloud AI Solutions +AI06197,Robotics Engineer,327821,USD,327821,EX,PT,Denmark,L,Denmark,0,"Azure, Python, MLOps, Scala",PhD,13,Gaming,2024-01-08,2024-02-17,2292,6.7,Future Systems +AI06198,NLP Engineer,97172,GBP,72879,EN,PT,United Kingdom,L,United Kingdom,100,"Statistics, Linux, Mathematics, Tableau, Kubernetes",PhD,0,Retail,2024-02-14,2024-04-02,819,7.2,DeepTech Ventures +AI06199,Autonomous Systems Engineer,58968,EUR,50123,EN,PT,Germany,L,Germany,50,"PyTorch, Java, TensorFlow, R, GCP",Associate,0,Telecommunications,2024-07-09,2024-08-09,2302,6.4,DataVision Ltd +AI06200,Machine Learning Researcher,209608,AUD,282971,EX,FL,Australia,M,Australia,0,"NLP, Python, Hadoop, Kubernetes",Master,18,Automotive,2025-03-04,2025-04-28,1596,5.5,Digital Transformation LLC +AI06201,Head of AI,47165,EUR,40090,EN,PT,Austria,S,Austria,0,"Python, TensorFlow, SQL",Bachelor,0,Finance,2025-02-12,2025-03-30,1483,6.5,Smart Analytics +AI06202,Data Engineer,95552,USD,95552,EN,FT,United States,L,United States,0,"Python, Computer Vision, Scala, TensorFlow, Git",Master,1,Media,2024-09-30,2024-11-30,1965,5.8,Cloud AI Solutions +AI06203,NLP Engineer,140834,EUR,119709,SE,PT,France,M,France,0,"NLP, TensorFlow, Java, Data Visualization, Mathematics",PhD,5,Finance,2024-01-21,2024-03-01,727,9.9,TechCorp Inc +AI06204,NLP Engineer,50964,USD,50964,EN,CT,Finland,M,Israel,100,"Docker, Azure, NLP, Linux",Associate,0,Consulting,2024-03-14,2024-03-31,1190,7.1,Cognitive Computing +AI06205,Machine Learning Researcher,141955,USD,141955,EX,FT,Israel,M,Israel,0,"TensorFlow, Spark, Hadoop, Python",PhD,12,Government,2024-11-10,2025-01-11,1814,6.9,DataVision Ltd +AI06206,Research Scientist,79587,USD,79587,MI,FT,Israel,M,Israel,50,"PyTorch, SQL, NLP",Associate,4,Transportation,2024-03-31,2024-06-03,1811,8.9,DataVision Ltd +AI06207,Data Engineer,114995,USD,114995,EX,PT,China,L,China,100,"Kubernetes, Data Visualization, SQL, Python",Bachelor,17,Consulting,2025-02-15,2025-04-23,566,6.2,DataVision Ltd +AI06208,ML Ops Engineer,65857,USD,65857,EN,PT,Israel,S,Malaysia,0,"Deep Learning, TensorFlow, Computer Vision",PhD,0,Media,2025-04-20,2025-06-08,1998,9.3,Predictive Systems +AI06209,AI Consultant,58926,USD,58926,EN,FT,Ireland,M,Portugal,100,"Scala, NLP, GCP, Hadoop",Associate,1,Manufacturing,2025-04-14,2025-05-12,597,9.8,Autonomous Tech +AI06210,AI Software Engineer,275093,USD,275093,EX,FL,Denmark,S,Denmark,100,"Git, Hadoop, Mathematics",Master,16,Government,2024-04-02,2024-06-11,2078,8.7,Neural Networks Co +AI06211,Machine Learning Engineer,220073,EUR,187062,EX,FL,Netherlands,L,Netherlands,50,"Python, Java, SQL, PyTorch",Bachelor,18,Energy,2024-11-23,2025-01-02,1489,5.1,Cloud AI Solutions +AI06212,Robotics Engineer,58905,GBP,44179,EN,FT,United Kingdom,S,New Zealand,50,"Python, Linux, Azure, AWS, Java",Associate,1,Finance,2024-06-06,2024-07-31,1625,7.1,Predictive Systems +AI06213,Principal Data Scientist,264666,USD,264666,EX,CT,Norway,M,Norway,100,"Git, NLP, SQL, PyTorch",PhD,11,Healthcare,2025-01-14,2025-02-27,1025,6.9,DeepTech Ventures +AI06214,Data Analyst,149181,EUR,126804,EX,PT,Austria,M,Austria,50,"SQL, Spark, Data Visualization, TensorFlow, GCP",Master,17,Healthcare,2024-07-24,2024-08-29,985,9.9,Future Systems +AI06215,ML Ops Engineer,92326,USD,92326,EN,FL,Sweden,L,Sweden,0,"Scala, Java, NLP",Associate,1,Gaming,2024-01-27,2024-04-04,2411,5.3,Autonomous Tech +AI06216,Autonomous Systems Engineer,103737,USD,103737,MI,FT,United States,S,United States,0,"Kubernetes, Docker, Deep Learning",Bachelor,4,Automotive,2024-10-21,2024-11-11,1472,8.1,TechCorp Inc +AI06217,AI Consultant,105787,EUR,89919,SE,PT,France,M,France,100,"Computer Vision, GCP, Deep Learning, PyTorch",Bachelor,9,Healthcare,2024-10-27,2025-01-03,1053,5.4,Digital Transformation LLC +AI06218,Data Engineer,121968,USD,121968,MI,FL,Denmark,M,Denmark,50,"SQL, TensorFlow, Linux",Associate,4,Retail,2025-03-22,2025-06-03,2484,7.9,Cloud AI Solutions +AI06219,Computer Vision Engineer,308831,CHF,277948,EX,FL,Switzerland,S,Switzerland,50,"GCP, Deep Learning, Python, Kubernetes, TensorFlow",PhD,17,Government,2025-01-03,2025-02-25,1901,8.6,Neural Networks Co +AI06220,AI Product Manager,52330,USD,52330,EN,PT,Sweden,M,Sweden,0,"GCP, Tableau, NLP",Associate,1,Gaming,2024-06-29,2024-08-27,623,9.9,Cloud AI Solutions +AI06221,NLP Engineer,105139,EUR,89368,MI,PT,Germany,M,Germany,0,"AWS, Java, Mathematics",Bachelor,2,Automotive,2024-01-09,2024-03-14,806,5.2,Predictive Systems +AI06222,AI Consultant,57833,USD,57833,MI,FT,China,L,Nigeria,100,"Java, Statistics, Tableau",PhD,3,Healthcare,2024-02-26,2024-03-23,1963,6.2,Quantum Computing Inc +AI06223,ML Ops Engineer,136814,CHF,123133,MI,FT,Switzerland,M,Switzerland,50,"GCP, Linux, Statistics, Mathematics",PhD,3,Manufacturing,2024-04-02,2024-05-02,1076,9.1,AI Innovations +AI06224,AI Architect,158438,USD,158438,EX,FL,South Korea,M,Malaysia,100,"Hadoop, MLOps, Java, Python, TensorFlow",Master,15,Retail,2025-03-16,2025-05-18,2329,5.3,AI Innovations +AI06225,NLP Engineer,45309,USD,45309,EN,PT,South Korea,M,South Korea,50,"PyTorch, Git, Kubernetes, Statistics, Deep Learning",Master,0,Finance,2024-03-18,2024-04-08,1552,6.5,Cloud AI Solutions +AI06226,AI Software Engineer,45432,USD,45432,EN,CT,Israel,S,Israel,100,"TensorFlow, Spark, Linux, Deep Learning, Java",Master,1,Manufacturing,2024-06-27,2024-08-22,555,6.4,DeepTech Ventures +AI06227,AI Product Manager,109543,CHF,98589,EN,FL,Switzerland,L,Estonia,100,"Docker, Git, Kubernetes, TensorFlow",PhD,0,Healthcare,2024-05-29,2024-07-02,1108,7.6,Cognitive Computing +AI06228,Head of AI,174342,USD,174342,EX,FT,Israel,M,Mexico,100,"Statistics, SQL, Data Visualization",Bachelor,13,Manufacturing,2024-05-14,2024-07-16,1145,6.4,Autonomous Tech +AI06229,Head of AI,52826,EUR,44902,EN,PT,Germany,M,Italy,0,"Linux, Computer Vision, SQL, Spark, PyTorch",Associate,1,Finance,2024-04-12,2024-05-09,1680,8.7,Predictive Systems +AI06230,AI Research Scientist,43403,USD,43403,MI,FT,China,S,China,0,"Git, NLP, Docker, TensorFlow, AWS",Bachelor,3,Technology,2024-01-20,2024-03-04,2127,5.5,Cognitive Computing +AI06231,AI Specialist,58657,AUD,79187,EN,FT,Australia,L,Australia,50,"Kubernetes, Scala, Linux, Spark",Associate,1,Finance,2024-03-10,2024-05-05,2476,6.8,Quantum Computing Inc +AI06232,ML Ops Engineer,334601,CHF,301141,EX,CT,Switzerland,L,Indonesia,0,"PyTorch, Azure, MLOps",Master,14,Gaming,2024-08-01,2024-09-21,1260,7.9,Predictive Systems +AI06233,Computer Vision Engineer,91169,AUD,123078,MI,FL,Australia,M,Australia,50,"SQL, PyTorch, R, Java",Master,2,Gaming,2024-06-07,2024-06-24,1508,6.8,DeepTech Ventures +AI06234,Machine Learning Engineer,89246,EUR,75859,MI,CT,France,S,France,0,"Spark, Hadoop, Git, SQL",Associate,3,Energy,2024-07-11,2024-09-11,817,7.5,Algorithmic Solutions +AI06235,AI Consultant,70820,AUD,95607,EN,CT,Australia,L,Australia,100,"Tableau, Linux, R, Azure, Scala",Master,1,Transportation,2024-08-24,2024-10-30,2272,9.1,Cognitive Computing +AI06236,Data Engineer,127145,SGD,165289,SE,CT,Singapore,L,Singapore,50,"NLP, Python, SQL, Docker, GCP",PhD,7,Retail,2025-04-29,2025-06-14,1599,6.3,Future Systems +AI06237,Computer Vision Engineer,74447,GBP,55835,EN,CT,United Kingdom,S,United Kingdom,100,"Linux, Data Visualization, TensorFlow",Bachelor,1,Technology,2024-01-21,2024-02-12,1024,9.2,DataVision Ltd +AI06238,AI Product Manager,85168,GBP,63876,MI,FT,United Kingdom,M,Austria,100,"Python, MLOps, Java, Computer Vision, Git",PhD,3,Energy,2024-08-04,2024-09-28,2129,6.1,Digital Transformation LLC +AI06239,AI Consultant,333929,CHF,300536,EX,CT,Switzerland,L,Switzerland,100,"SQL, PyTorch, MLOps, Computer Vision, AWS",PhD,14,Transportation,2024-03-31,2024-06-03,1031,9.5,Smart Analytics +AI06240,Deep Learning Engineer,119472,EUR,101551,SE,FT,Austria,M,Denmark,100,"Python, Spark, TensorFlow",Master,7,Retail,2024-03-17,2024-05-16,914,8.2,Neural Networks Co +AI06241,Machine Learning Engineer,185566,USD,185566,EX,CT,United States,M,Ireland,100,"Kubernetes, Statistics, R, Docker, Computer Vision",Associate,13,Real Estate,2024-01-09,2024-03-18,669,5.1,AI Innovations +AI06242,Deep Learning Engineer,98638,AUD,133161,SE,CT,Australia,S,Philippines,50,"Mathematics, Python, GCP, Azure",Associate,7,Healthcare,2024-10-07,2024-11-12,1188,5.6,Neural Networks Co +AI06243,Machine Learning Engineer,96950,EUR,82408,MI,PT,Netherlands,L,Netherlands,50,"Python, MLOps, Data Visualization",Master,2,Automotive,2024-06-22,2024-07-29,2329,7.2,Machine Intelligence Group +AI06244,AI Product Manager,55210,GBP,41408,EN,FT,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, Mathematics, Java",Associate,0,Healthcare,2024-04-23,2024-07-01,2059,6.1,Autonomous Tech +AI06245,Robotics Engineer,231279,USD,231279,EX,FL,South Korea,L,South Korea,0,"Git, TensorFlow, Python",Bachelor,19,Consulting,2024-10-07,2024-12-06,2187,8.7,Digital Transformation LLC +AI06246,ML Ops Engineer,125808,USD,125808,MI,FT,Denmark,L,Denmark,100,"NLP, Scala, Python",PhD,4,Education,2024-03-25,2024-05-16,532,6.3,Advanced Robotics +AI06247,Head of AI,201000,SGD,261300,EX,CT,Singapore,M,Singapore,100,"NLP, Java, Docker, Deep Learning",Bachelor,10,Education,2024-06-12,2024-08-13,598,5.9,Predictive Systems +AI06248,Machine Learning Researcher,235015,SGD,305520,EX,CT,Singapore,S,Singapore,0,"MLOps, Java, R, Kubernetes, Data Visualization",PhD,10,Finance,2024-10-18,2024-12-06,1281,8.8,Machine Intelligence Group +AI06249,Research Scientist,104461,AUD,141022,SE,PT,Australia,S,Australia,100,"PyTorch, SQL, AWS, Python, Deep Learning",Bachelor,7,Real Estate,2024-10-25,2024-12-24,949,6.9,TechCorp Inc +AI06250,AI Consultant,120951,USD,120951,MI,FT,Sweden,L,Sweden,100,"Deep Learning, Docker, R, Linux, MLOps",Associate,4,Education,2024-05-03,2024-06-20,1048,5.2,DeepTech Ventures +AI06251,Deep Learning Engineer,94126,USD,94126,MI,CT,Ireland,S,Ireland,100,"Statistics, Spark, Java, Deep Learning",Bachelor,4,Automotive,2024-09-30,2024-11-19,1008,5.6,Digital Transformation LLC +AI06252,Machine Learning Researcher,188011,USD,188011,EX,FL,Finland,S,Finland,100,"Git, Mathematics, Scala, PyTorch",Bachelor,16,Retail,2025-01-12,2025-03-08,2175,6.1,Digital Transformation LLC +AI06253,NLP Engineer,143061,USD,143061,SE,PT,Norway,M,China,0,"Statistics, Python, Tableau, Linux",PhD,9,Technology,2024-12-22,2025-02-05,1284,7.8,AI Innovations +AI06254,NLP Engineer,206350,EUR,175398,EX,CT,France,S,France,0,"Kubernetes, GCP, Hadoop, Statistics",Master,16,Gaming,2025-04-13,2025-05-21,919,6.7,Smart Analytics +AI06255,Data Analyst,60881,AUD,82189,EN,CT,Australia,S,Australia,0,"Scala, Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-03-26,2024-05-02,672,10,Smart Analytics +AI06256,Data Analyst,103178,EUR,87701,MI,FT,Austria,L,Austria,0,"Azure, Hadoop, AWS, Statistics",Bachelor,3,Finance,2025-04-08,2025-05-28,687,6.4,DataVision Ltd +AI06257,AI Software Engineer,81446,SGD,105880,MI,FL,Singapore,S,Singapore,100,"Docker, Hadoop, Data Visualization, Java, R",Bachelor,2,Healthcare,2025-01-28,2025-03-28,801,5.3,TechCorp Inc +AI06258,ML Ops Engineer,304317,GBP,228238,EX,FT,United Kingdom,L,Denmark,100,"GCP, Linux, Git",PhD,13,Transportation,2024-06-11,2024-07-10,1876,9.3,Cognitive Computing +AI06259,NLP Engineer,37648,USD,37648,SE,FL,India,S,India,50,"Spark, Scala, Git, Python, Azure",Bachelor,5,Technology,2024-09-29,2024-12-02,1398,5.8,Quantum Computing Inc +AI06260,AI Architect,88718,GBP,66539,EN,CT,United Kingdom,L,United Kingdom,50,"Linux, Scala, Computer Vision",Associate,1,Consulting,2024-02-03,2024-02-17,946,9.1,Smart Analytics +AI06261,AI Consultant,36001,USD,36001,MI,FL,China,M,Ukraine,100,"Git, Mathematics, Spark",PhD,4,Finance,2024-01-26,2024-03-22,986,5.3,Advanced Robotics +AI06262,ML Ops Engineer,78519,CAD,98149,MI,CT,Canada,L,Canada,0,"Linux, Deep Learning, Python, TensorFlow",Associate,2,Transportation,2024-09-30,2024-10-20,870,7.7,AI Innovations +AI06263,AI Product Manager,109953,CHF,98958,MI,FT,Switzerland,M,Switzerland,0,"Java, Docker, Kubernetes, Scala",Master,4,Consulting,2025-01-22,2025-03-11,852,6.5,Algorithmic Solutions +AI06264,Head of AI,105406,AUD,142298,SE,CT,Australia,S,Australia,100,"Docker, MLOps, NLP, Java, R",Master,7,Telecommunications,2024-01-19,2024-03-27,2213,7.6,Quantum Computing Inc +AI06265,AI Specialist,70408,USD,70408,EN,FT,Israel,L,South Korea,0,"Mathematics, AWS, Data Visualization, Docker",Bachelor,0,Gaming,2024-06-27,2024-07-12,562,8.7,AI Innovations +AI06266,AI Architect,220323,USD,220323,EX,PT,Sweden,S,Sweden,0,"PyTorch, Linux, Tableau, Computer Vision",Associate,13,Transportation,2025-04-26,2025-06-01,1088,8.3,Neural Networks Co +AI06267,AI Architect,163354,EUR,138851,EX,PT,France,M,France,0,"Azure, AWS, GCP",Associate,10,Telecommunications,2024-12-15,2024-12-29,814,8.2,AI Innovations +AI06268,Autonomous Systems Engineer,89007,SGD,115709,MI,CT,Singapore,L,Singapore,100,"SQL, Spark, Scala, Azure",Master,4,Finance,2024-01-04,2024-01-28,837,8.8,Quantum Computing Inc +AI06269,Computer Vision Engineer,89914,AUD,121384,EN,FT,Australia,L,Australia,50,"AWS, Scala, GCP",Associate,1,Technology,2024-12-16,2025-02-17,1937,5.5,Machine Intelligence Group +AI06270,NLP Engineer,117917,USD,117917,SE,FL,Israel,M,Israel,0,"Python, NLP, Git",Master,8,Consulting,2024-07-22,2024-09-06,701,9.3,Cognitive Computing +AI06271,AI Specialist,86279,AUD,116477,MI,FT,Australia,S,Australia,0,"AWS, Docker, Git, Data Visualization",Bachelor,3,Gaming,2025-01-25,2025-03-07,828,6.5,AI Innovations +AI06272,Computer Vision Engineer,232296,USD,232296,EX,CT,Denmark,S,Denmark,0,"Statistics, Kubernetes, Linux, NLP",Associate,15,Manufacturing,2024-05-31,2024-07-09,2320,5.7,AI Innovations +AI06273,Principal Data Scientist,84539,USD,84539,MI,PT,Israel,S,Israel,0,"R, Scala, Data Visualization, Java, Statistics",Associate,3,Consulting,2024-05-14,2024-07-11,1864,5.8,TechCorp Inc +AI06274,Autonomous Systems Engineer,191852,CHF,172667,SE,FT,Switzerland,S,Switzerland,50,"Spark, PyTorch, Mathematics, Data Visualization, MLOps",Associate,7,Government,2024-10-11,2024-11-16,1459,9.6,Cognitive Computing +AI06275,Head of AI,271790,USD,271790,EX,CT,Denmark,S,Denmark,50,"NLP, Scala, Git",Master,16,Finance,2024-12-15,2025-02-25,609,6.1,Cloud AI Solutions +AI06276,Head of AI,69511,USD,69511,EN,CT,Ireland,M,Ireland,50,"Python, Docker, Computer Vision, Statistics, GCP",PhD,1,Finance,2024-03-02,2024-03-24,2017,6.3,AI Innovations +AI06277,AI Research Scientist,92982,USD,92982,EN,PT,Denmark,M,Denmark,0,"Linux, PyTorch, Hadoop",PhD,1,Manufacturing,2025-03-18,2025-04-02,2141,7.1,Digital Transformation LLC +AI06278,Machine Learning Researcher,123526,EUR,104997,EX,FL,Germany,S,Germany,0,"Docker, Linux, Data Visualization, Statistics",PhD,10,Automotive,2024-03-03,2024-05-01,856,5.5,Smart Analytics +AI06279,AI Consultant,184103,SGD,239334,SE,PT,Singapore,L,Singapore,100,"Kubernetes, Spark, Tableau, Hadoop, Docker",Master,5,Gaming,2024-08-14,2024-09-25,2427,7.2,Cloud AI Solutions +AI06280,AI Research Scientist,58966,USD,58966,MI,FL,China,L,Estonia,50,"Spark, AWS, Azure, Mathematics",Associate,2,Technology,2024-02-12,2024-04-14,2263,8.1,Cognitive Computing +AI06281,Robotics Engineer,118203,USD,118203,SE,PT,Ireland,M,Ireland,50,"Docker, Kubernetes, Data Visualization, GCP, Deep Learning",PhD,6,Finance,2024-02-16,2024-03-31,1541,9.4,TechCorp Inc +AI06282,Machine Learning Researcher,307747,USD,307747,EX,PT,Norway,L,Norway,0,"PyTorch, Spark, Data Visualization, AWS",PhD,11,Transportation,2024-12-23,2025-02-04,1840,7.3,Advanced Robotics +AI06283,Computer Vision Engineer,180858,JPY,19894380,EX,PT,Japan,L,Japan,100,"TensorFlow, Java, NLP, Docker, Computer Vision",Associate,14,Healthcare,2024-08-31,2024-09-26,1599,6,Machine Intelligence Group +AI06284,NLP Engineer,93668,SGD,121768,EN,FL,Singapore,L,Singapore,0,"Docker, PyTorch, Statistics",PhD,0,Media,2025-03-21,2025-04-22,1615,5.8,AI Innovations +AI06285,Computer Vision Engineer,74686,USD,74686,MI,FL,Ireland,S,Ireland,50,"Python, PyTorch, GCP, Deep Learning",Master,4,Government,2024-01-20,2024-03-19,2252,8.7,Digital Transformation LLC +AI06286,ML Ops Engineer,116392,USD,116392,SE,FL,South Korea,M,South Korea,50,"Hadoop, Scala, Python, R, Statistics",PhD,6,Media,2025-01-25,2025-03-28,1578,7.9,DataVision Ltd +AI06287,AI Architect,76585,GBP,57439,EN,CT,United Kingdom,M,Russia,100,"Tableau, Deep Learning, Git, SQL",Bachelor,1,Retail,2025-03-05,2025-04-16,911,9.1,Neural Networks Co +AI06288,Computer Vision Engineer,178074,CAD,222593,EX,FL,Canada,S,Canada,0,"Linux, SQL, Hadoop, PyTorch, Kubernetes",Master,19,Gaming,2025-01-29,2025-02-12,1184,6.6,Smart Analytics +AI06289,AI Consultant,28737,USD,28737,EN,PT,China,M,China,100,"GCP, R, Data Visualization",PhD,1,Media,2025-04-03,2025-06-14,1804,5.1,AI Innovations +AI06290,AI Research Scientist,175508,USD,175508,EX,CT,Ireland,S,Norway,100,"Kubernetes, AWS, Deep Learning, MLOps, SQL",PhD,19,Finance,2025-03-02,2025-04-29,2085,6,DataVision Ltd +AI06291,AI Product Manager,52615,USD,52615,EN,FL,South Korea,M,South Korea,50,"Data Visualization, MLOps, SQL",Associate,1,Finance,2024-07-10,2024-08-02,1516,7.9,DataVision Ltd +AI06292,ML Ops Engineer,177787,USD,177787,SE,PT,Norway,M,Norway,100,"Python, MLOps, Scala, R",Master,7,Finance,2025-01-07,2025-03-17,1543,7.3,Smart Analytics +AI06293,Robotics Engineer,67831,EUR,57656,EN,FL,France,S,France,100,"Python, Git, Hadoop, Spark",Master,0,Real Estate,2024-01-05,2024-02-03,673,5.5,Autonomous Tech +AI06294,Data Engineer,79450,USD,79450,EN,PT,Sweden,L,Finland,100,"Mathematics, Java, Python",Master,1,Retail,2024-03-19,2024-05-21,873,8.6,Digital Transformation LLC +AI06295,AI Research Scientist,61213,USD,61213,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Tableau, Linux, Statistics",Bachelor,0,Consulting,2024-11-16,2025-01-14,842,8.2,Neural Networks Co +AI06296,ML Ops Engineer,142856,USD,142856,SE,FL,United States,M,United States,50,"Git, SQL, Data Visualization, Linux, AWS",Associate,6,Government,2024-09-16,2024-11-24,1332,6.9,Predictive Systems +AI06297,AI Architect,49252,CAD,61565,EN,FT,Canada,S,Canada,50,"Java, R, GCP, SQL, Docker",Master,0,Finance,2024-12-20,2025-01-24,2021,8.7,Neural Networks Co +AI06298,ML Ops Engineer,102093,USD,102093,EX,PT,China,S,Netherlands,0,"Kubernetes, Python, R, Java",Associate,13,Consulting,2024-02-24,2024-04-07,902,7.4,AI Innovations +AI06299,Data Scientist,152000,USD,152000,SE,PT,United States,S,United States,100,"Azure, Mathematics, Python, TensorFlow",PhD,8,Retail,2025-01-10,2025-02-20,839,7.6,AI Innovations +AI06300,AI Research Scientist,145423,AUD,196321,SE,FT,Australia,L,Australia,100,"Mathematics, Git, Python, TensorFlow",PhD,7,Manufacturing,2024-06-24,2024-08-22,1828,8.8,DeepTech Ventures +AI06301,AI Architect,65475,USD,65475,SE,FT,China,M,China,0,"Linux, Computer Vision, R, Statistics",PhD,7,Technology,2024-12-30,2025-03-04,2327,9.9,Neural Networks Co +AI06302,ML Ops Engineer,240444,GBP,180333,EX,CT,United Kingdom,M,United Kingdom,0,"Git, SQL, R, NLP",PhD,19,Education,2024-09-12,2024-11-02,2186,6,AI Innovations +AI06303,Autonomous Systems Engineer,82512,EUR,70135,EN,FT,Germany,L,Germany,50,"Azure, AWS, MLOps",Master,1,Consulting,2025-03-08,2025-04-01,609,9.9,DeepTech Ventures +AI06304,AI Software Engineer,130547,JPY,14360170,MI,CT,Japan,L,Japan,100,"PyTorch, GCP, Kubernetes, AWS",PhD,2,Media,2025-02-03,2025-03-02,1276,6.2,TechCorp Inc +AI06305,Data Engineer,88285,EUR,75042,EN,FL,Germany,L,Germany,50,"Azure, R, Deep Learning, Linux",PhD,0,Education,2024-12-07,2025-02-14,2151,5,Cloud AI Solutions +AI06306,AI Software Engineer,127722,USD,127722,EX,PT,South Korea,S,South Korea,50,"SQL, Kubernetes, MLOps, Computer Vision, NLP",Associate,16,Transportation,2024-07-02,2024-08-04,2126,5.6,Quantum Computing Inc +AI06307,AI Consultant,267077,USD,267077,EX,PT,Norway,M,Norway,50,"Python, Kubernetes, Azure",Bachelor,18,Telecommunications,2025-04-01,2025-05-14,766,8.4,DeepTech Ventures +AI06308,ML Ops Engineer,178106,EUR,151390,EX,CT,Germany,L,Germany,0,"Spark, Git, Tableau, Python",Associate,19,Energy,2025-03-29,2025-04-23,814,5.2,Autonomous Tech +AI06309,Principal Data Scientist,160177,USD,160177,SE,CT,Denmark,L,Israel,100,"AWS, Git, Python, Tableau, GCP",Master,7,Manufacturing,2024-08-28,2024-09-28,1921,6,Future Systems +AI06310,Data Engineer,123876,USD,123876,SE,FT,Israel,S,Israel,0,"SQL, Linux, MLOps, TensorFlow",PhD,9,Transportation,2024-03-30,2024-05-28,1307,8.5,Advanced Robotics +AI06311,Machine Learning Researcher,51598,USD,51598,EN,PT,Finland,M,Finland,0,"Data Visualization, Git, Python, Kubernetes",Associate,0,Telecommunications,2024-05-14,2024-07-13,2313,9.1,Cloud AI Solutions +AI06312,Deep Learning Engineer,127577,USD,127577,SE,FL,Israel,S,Israel,50,"Tableau, AWS, Azure, Python",Associate,6,Technology,2024-08-29,2024-09-20,2494,9.5,Digital Transformation LLC +AI06313,Machine Learning Researcher,64037,GBP,48028,EN,CT,United Kingdom,M,United Kingdom,100,"Spark, Python, Data Visualization",Associate,1,Gaming,2024-03-21,2024-05-16,1649,5.9,DeepTech Ventures +AI06314,AI Consultant,27121,USD,27121,EN,CT,India,L,India,50,"Tableau, Kubernetes, Azure, Scala",Bachelor,1,Retail,2024-09-21,2024-10-17,2379,7.9,AI Innovations +AI06315,AI Software Engineer,177989,USD,177989,SE,CT,United States,L,United States,100,"Python, Scala, TensorFlow, Linux, GCP",Master,6,Healthcare,2024-10-12,2024-11-07,522,7.8,Smart Analytics +AI06316,AI Software Engineer,84799,USD,84799,EN,FL,United States,S,United States,100,"NLP, R, Scala, Linux",Bachelor,0,Technology,2024-12-12,2025-02-14,809,6.8,Cognitive Computing +AI06317,ML Ops Engineer,130027,USD,130027,SE,PT,Israel,L,Israel,50,"R, TensorFlow, Tableau, Computer Vision",PhD,8,Real Estate,2024-04-18,2024-05-02,627,6.5,Future Systems +AI06318,Data Engineer,116389,CAD,145486,SE,PT,Canada,S,Canada,0,"Deep Learning, Java, Scala",Master,5,Automotive,2024-01-25,2024-03-27,583,9.2,Machine Intelligence Group +AI06319,AI Product Manager,16795,USD,16795,EN,FL,India,S,India,100,"R, Hadoop, SQL",Bachelor,0,Real Estate,2025-04-27,2025-06-12,1009,5.1,Algorithmic Solutions +AI06320,Research Scientist,79356,JPY,8729160,MI,FL,Japan,S,Japan,50,"Statistics, Git, MLOps",Associate,4,Real Estate,2024-05-07,2024-06-02,1580,7.1,Algorithmic Solutions +AI06321,AI Research Scientist,71342,SGD,92745,EN,PT,Singapore,L,Belgium,50,"Git, Kubernetes, GCP, Mathematics, Azure",Bachelor,0,Automotive,2024-05-19,2024-07-15,1611,9.4,Digital Transformation LLC +AI06322,Data Engineer,66947,GBP,50210,EN,FT,United Kingdom,M,United Kingdom,0,"R, Mathematics, Kubernetes, Deep Learning, NLP",Bachelor,0,Consulting,2024-02-24,2024-04-03,1935,8.7,Autonomous Tech +AI06323,Machine Learning Engineer,66042,USD,66042,EN,FT,Israel,S,Israel,0,"SQL, GCP, Linux, Tableau",Bachelor,1,Healthcare,2025-04-06,2025-05-09,521,9.6,DataVision Ltd +AI06324,AI Software Engineer,232173,CHF,208956,EX,FT,Switzerland,S,Switzerland,0,"Git, PyTorch, Mathematics, Hadoop, Azure",Bachelor,18,Technology,2024-03-31,2024-05-08,2066,8.1,TechCorp Inc +AI06325,Data Scientist,108812,GBP,81609,SE,FT,United Kingdom,S,Turkey,100,"SQL, R, Data Visualization, Azure",Associate,5,Technology,2025-01-05,2025-01-26,654,6.5,Digital Transformation LLC +AI06326,Research Scientist,96625,USD,96625,MI,PT,Ireland,S,Norway,0,"R, Computer Vision, Data Visualization",Master,2,Consulting,2024-06-30,2024-07-28,777,7.6,Quantum Computing Inc +AI06327,Data Scientist,256663,SGD,333662,EX,FL,Singapore,M,Singapore,0,"Python, Linux, TensorFlow, Mathematics",Master,14,Automotive,2024-07-19,2024-09-03,1871,9.5,Autonomous Tech +AI06328,Machine Learning Researcher,92568,USD,92568,MI,CT,Ireland,S,Ireland,0,"Azure, Python, MLOps, Kubernetes",Master,3,Manufacturing,2024-03-30,2024-05-28,2342,9.9,Advanced Robotics +AI06329,Computer Vision Engineer,85546,EUR,72714,MI,CT,France,M,Netherlands,50,"Spark, Python, SQL",Associate,3,Real Estate,2025-04-10,2025-05-17,1014,9.9,Future Systems +AI06330,Data Engineer,185667,USD,185667,EX,PT,Ireland,L,Ireland,0,"SQL, Deep Learning, Hadoop, TensorFlow, Mathematics",Master,15,Transportation,2025-03-07,2025-03-21,1512,9.8,Future Systems +AI06331,AI Research Scientist,94718,USD,94718,SE,CT,Israel,S,Israel,0,"PyTorch, NLP, GCP",Associate,9,Government,2024-03-05,2024-03-22,860,6.4,Algorithmic Solutions +AI06332,Research Scientist,153864,AUD,207716,SE,CT,Australia,L,Australia,100,"Linux, PyTorch, Spark, NLP",Bachelor,5,Energy,2024-03-17,2024-04-29,986,5.1,TechCorp Inc +AI06333,Computer Vision Engineer,49125,SGD,63863,EN,FL,Singapore,S,Singapore,100,"MLOps, Python, TensorFlow",Master,1,Energy,2025-02-20,2025-04-04,1236,8,TechCorp Inc +AI06334,AI Software Engineer,79549,SGD,103414,EN,PT,Singapore,M,Singapore,100,"Python, R, Kubernetes, Computer Vision",Master,1,Transportation,2024-08-03,2024-08-19,1979,8,Cognitive Computing +AI06335,AI Research Scientist,95354,USD,95354,MI,FL,Sweden,S,Sweden,0,"Scala, Kubernetes, Spark, Hadoop",Associate,3,Manufacturing,2024-06-18,2024-07-13,2489,9.8,DeepTech Ventures +AI06336,AI Architect,91154,CHF,82039,EN,FL,Switzerland,L,Switzerland,100,"AWS, Azure, Python, Java",Master,1,Finance,2024-05-19,2024-06-17,1997,7.1,Autonomous Tech +AI06337,AI Specialist,76991,GBP,57743,EN,PT,United Kingdom,M,United Kingdom,50,"Java, Scala, Azure, Hadoop, Computer Vision",PhD,1,Technology,2024-02-21,2024-03-13,2053,9,Machine Intelligence Group +AI06338,AI Software Engineer,64003,USD,64003,EN,FL,Israel,M,Israel,100,"R, Git, Statistics, MLOps",Bachelor,1,Energy,2024-12-19,2025-01-22,1438,9.1,Neural Networks Co +AI06339,AI Product Manager,107493,EUR,91369,MI,FT,Netherlands,M,Netherlands,100,"Scala, Spark, Deep Learning",Master,2,Gaming,2024-04-10,2024-05-24,1960,9.6,Machine Intelligence Group +AI06340,Machine Learning Researcher,54975,JPY,6047250,EN,CT,Japan,S,Japan,0,"Hadoop, Git, Python",PhD,1,Real Estate,2025-04-13,2025-05-24,702,7.9,Future Systems +AI06341,AI Research Scientist,157422,USD,157422,SE,PT,Norway,L,Norway,50,"Spark, Statistics, PyTorch, Kubernetes",Master,8,Telecommunications,2024-10-16,2024-12-09,616,5.9,Digital Transformation LLC +AI06342,Computer Vision Engineer,289891,USD,289891,EX,FL,Norway,L,Finland,100,"Kubernetes, TensorFlow, PyTorch",Associate,11,Finance,2024-08-01,2024-09-09,1979,9.5,Machine Intelligence Group +AI06343,AI Research Scientist,111548,CHF,100393,EN,PT,Switzerland,M,Australia,100,"NLP, R, Hadoop, Java",PhD,0,Gaming,2024-08-07,2024-09-14,1085,8.2,AI Innovations +AI06344,Computer Vision Engineer,89985,EUR,76487,MI,PT,Austria,L,Austria,50,"Computer Vision, Spark, MLOps",Bachelor,4,Real Estate,2024-04-19,2024-06-13,2089,8.6,TechCorp Inc +AI06345,Data Engineer,67846,USD,67846,EN,FL,Finland,S,Finland,100,"Hadoop, MLOps, Computer Vision, SQL, Java",Bachelor,1,Healthcare,2024-04-21,2024-06-19,2207,5.6,Algorithmic Solutions +AI06346,Autonomous Systems Engineer,54041,EUR,45935,EN,PT,Austria,S,Austria,0,"TensorFlow, Scala, Kubernetes, Tableau",PhD,1,Transportation,2024-11-28,2024-12-24,919,7,Neural Networks Co +AI06347,Autonomous Systems Engineer,72359,USD,72359,SE,PT,China,L,China,0,"PyTorch, Computer Vision, Java, AWS",PhD,7,Government,2025-03-13,2025-05-07,1032,6.8,Cognitive Computing +AI06348,NLP Engineer,123879,USD,123879,SE,PT,Finland,S,Austria,0,"AWS, Hadoop, Mathematics",Associate,8,Media,2025-04-30,2025-07-02,828,7.2,Predictive Systems +AI06349,AI Product Manager,166701,USD,166701,SE,FL,Ireland,L,Ghana,100,"NLP, Git, Hadoop, PyTorch",Associate,8,Transportation,2024-12-11,2024-12-30,2134,5.5,Quantum Computing Inc +AI06350,AI Product Manager,129156,CAD,161445,SE,PT,Canada,S,Nigeria,50,"PyTorch, SQL, TensorFlow, Kubernetes",Bachelor,8,Education,2024-02-11,2024-03-16,1419,8.9,Cloud AI Solutions +AI06351,NLP Engineer,120933,USD,120933,MI,FL,Denmark,M,Denmark,50,"Mathematics, Computer Vision, GCP, PyTorch, SQL",Bachelor,4,Media,2025-03-23,2025-05-09,1949,5.5,Advanced Robotics +AI06352,Computer Vision Engineer,81946,USD,81946,EN,PT,Finland,L,Indonesia,100,"Deep Learning, Data Visualization, PyTorch, MLOps, Computer Vision",PhD,0,Media,2024-06-12,2024-08-18,814,8.1,AI Innovations +AI06353,Machine Learning Engineer,70100,USD,70100,EN,FT,Sweden,L,Sweden,100,"R, Linux, Mathematics, TensorFlow",Master,1,Telecommunications,2024-08-28,2024-10-07,1311,6.1,Digital Transformation LLC +AI06354,Machine Learning Engineer,159640,CHF,143676,MI,CT,Switzerland,L,Mexico,50,"Hadoop, Python, Azure, Linux, Java",Associate,3,Government,2024-04-01,2024-05-10,915,8.4,Algorithmic Solutions +AI06355,AI Architect,137323,USD,137323,SE,CT,United States,S,United States,100,"Tableau, Deep Learning, Git",Bachelor,5,Media,2025-01-16,2025-03-10,2296,5.5,DataVision Ltd +AI06356,AI Specialist,173170,USD,173170,SE,FL,Norway,S,Germany,100,"Git, Linux, Python, Tableau",Master,6,Consulting,2024-02-12,2024-04-20,501,8.8,DataVision Ltd +AI06357,Data Engineer,72402,SGD,94123,EN,CT,Singapore,M,Argentina,0,"MLOps, Mathematics, Statistics, Scala",Bachelor,0,Telecommunications,2024-12-27,2025-03-08,1616,6.4,DataVision Ltd +AI06358,AI Software Engineer,138464,CAD,173080,SE,FL,Canada,L,Canada,100,"Azure, R, Statistics, Spark, TensorFlow",PhD,8,Automotive,2025-04-02,2025-05-28,2151,8.2,Machine Intelligence Group +AI06359,Research Scientist,132681,USD,132681,SE,FL,Israel,M,Japan,100,"Git, Java, AWS",Associate,6,Gaming,2024-05-25,2024-06-19,1871,9.8,Cognitive Computing +AI06360,Data Engineer,255255,USD,255255,EX,FL,Denmark,M,Nigeria,100,"Azure, GCP, Statistics, SQL, Deep Learning",Bachelor,16,Media,2025-03-12,2025-05-03,1099,6.1,Autonomous Tech +AI06361,Data Scientist,65881,EUR,55999,EN,FT,Netherlands,L,Netherlands,100,"Python, GCP, Data Visualization",PhD,1,Media,2025-01-08,2025-03-05,704,5.1,Advanced Robotics +AI06362,Data Analyst,100927,USD,100927,SE,FT,Israel,M,Israel,100,"Python, Data Visualization, Mathematics, SQL, Java",Bachelor,6,Telecommunications,2024-08-03,2024-08-21,1875,7.6,TechCorp Inc +AI06363,ML Ops Engineer,158295,USD,158295,EX,FL,Ireland,M,Finland,0,"Tableau, Docker, SQL",Associate,18,Telecommunications,2024-04-27,2024-05-18,1494,9.9,DataVision Ltd +AI06364,NLP Engineer,62963,GBP,47222,EN,FL,United Kingdom,M,United Kingdom,50,"Scala, Java, R, SQL",Master,0,Telecommunications,2024-02-06,2024-04-14,535,6.2,Neural Networks Co +AI06365,Machine Learning Researcher,100228,USD,100228,MI,FT,Israel,L,Israel,100,"Java, Mathematics, TensorFlow, Python",Bachelor,2,Consulting,2024-12-24,2025-01-12,1774,5.4,Quantum Computing Inc +AI06366,Computer Vision Engineer,74437,EUR,63271,EN,PT,France,M,Spain,0,"Kubernetes, Python, Spark, Linux, SQL",Bachelor,1,Energy,2024-07-30,2024-09-13,1328,6.8,Cognitive Computing +AI06367,Computer Vision Engineer,82236,USD,82236,EX,CT,China,M,China,50,"MLOps, SQL, Statistics, Scala",Associate,16,Healthcare,2024-08-21,2024-10-10,2143,5.8,Algorithmic Solutions +AI06368,Data Analyst,161597,EUR,137357,EX,FT,Germany,L,Portugal,100,"PyTorch, Mathematics, Hadoop, NLP",Master,10,Technology,2024-09-02,2024-10-16,1862,5.3,Smart Analytics +AI06369,Research Scientist,158726,USD,158726,EX,FT,United States,S,United States,0,"Kubernetes, R, Computer Vision, Deep Learning, Statistics",Associate,19,Energy,2024-06-24,2024-08-20,1436,7.4,Autonomous Tech +AI06370,Robotics Engineer,42660,USD,42660,SE,FT,India,M,India,0,"NLP, SQL, Git, PyTorch",Master,6,Consulting,2024-08-21,2024-09-14,1864,5.6,Cognitive Computing +AI06371,Head of AI,201912,CHF,181721,EX,FL,Switzerland,S,Switzerland,100,"Python, R, Data Visualization, Computer Vision",PhD,14,Healthcare,2024-10-19,2024-11-23,755,7.7,Predictive Systems +AI06372,AI Research Scientist,16975,USD,16975,EN,FL,India,S,India,50,"Deep Learning, SQL, MLOps, R, Docker",Bachelor,1,Telecommunications,2024-04-07,2024-05-27,1613,8.3,Quantum Computing Inc +AI06373,Data Analyst,65768,USD,65768,EN,FT,United States,M,Czech Republic,0,"Java, Hadoop, Kubernetes, Computer Vision, Statistics",Bachelor,1,Education,2024-06-05,2024-07-05,589,5.9,AI Innovations +AI06374,Machine Learning Engineer,31201,USD,31201,MI,FL,India,M,India,0,"Linux, GCP, Data Visualization",Bachelor,4,Retail,2024-01-18,2024-02-12,1186,6.2,Advanced Robotics +AI06375,AI Research Scientist,99393,EUR,84484,MI,FL,France,L,China,50,"Mathematics, Docker, Python, TensorFlow, Tableau",Master,2,Consulting,2024-08-13,2024-09-20,523,8.9,DeepTech Ventures +AI06376,Data Analyst,184065,EUR,156455,EX,FT,Germany,L,Germany,50,"Kubernetes, PyTorch, Tableau, Mathematics",PhD,12,Gaming,2025-04-03,2025-05-13,703,6.7,TechCorp Inc +AI06377,AI Specialist,173893,USD,173893,SE,CT,Norway,M,Norway,0,"AWS, Mathematics, Python",Master,6,Gaming,2024-05-27,2024-08-03,1454,5.5,Cloud AI Solutions +AI06378,NLP Engineer,112570,USD,112570,SE,FL,South Korea,S,Romania,50,"Spark, Git, MLOps, Scala",PhD,6,Technology,2025-01-29,2025-02-20,1131,8.1,TechCorp Inc +AI06379,AI Product Manager,86672,USD,86672,MI,CT,Finland,M,Finland,50,"Git, R, Docker, AWS",Bachelor,2,Automotive,2024-08-28,2024-10-27,849,7.3,Future Systems +AI06380,Data Scientist,225977,USD,225977,SE,FL,Norway,L,Argentina,50,"Linux, Data Visualization, Spark",PhD,9,Consulting,2024-11-21,2024-12-05,1561,5.2,Digital Transformation LLC +AI06381,AI Consultant,65278,AUD,88125,MI,CT,Australia,S,Austria,100,"AWS, Data Visualization, Tableau",Master,4,Real Estate,2024-02-20,2024-03-09,1960,5.2,Predictive Systems +AI06382,Robotics Engineer,103808,EUR,88237,SE,CT,Austria,S,Norway,100,"Data Visualization, MLOps, Tableau, PyTorch",PhD,7,Education,2024-06-21,2024-07-08,2354,8.6,TechCorp Inc +AI06383,Data Analyst,202963,CAD,253704,EX,FL,Canada,M,Canada,50,"Deep Learning, Scala, Python, Mathematics",Bachelor,11,Technology,2024-03-02,2024-04-12,568,5.6,Neural Networks Co +AI06384,ML Ops Engineer,85463,USD,85463,EX,FT,China,S,China,100,"Scala, Kubernetes, Deep Learning, NLP",Associate,15,Healthcare,2024-08-22,2024-10-15,1703,7.8,TechCorp Inc +AI06385,AI Consultant,104466,USD,104466,EN,FT,Norway,L,Norway,100,"Kubernetes, PyTorch, Hadoop, Computer Vision",PhD,1,Healthcare,2025-01-22,2025-03-04,1730,6.4,Algorithmic Solutions +AI06386,Machine Learning Engineer,63202,USD,63202,MI,FL,South Korea,M,Poland,50,"Python, SQL, Statistics, Spark",Bachelor,3,Telecommunications,2025-03-08,2025-04-10,2044,6.1,Neural Networks Co +AI06387,Head of AI,120132,USD,120132,SE,PT,Norway,S,Norway,0,"Java, SQL, Python, R, Linux",Bachelor,5,Education,2024-03-25,2024-05-09,1500,5,Autonomous Tech +AI06388,Robotics Engineer,83672,CHF,75305,EN,CT,Switzerland,S,India,100,"NLP, Data Visualization, Tableau",Bachelor,1,Automotive,2024-12-11,2024-12-25,2484,6,DeepTech Ventures +AI06389,Data Analyst,74974,USD,74974,EN,FT,Norway,S,Norway,0,"SQL, Computer Vision, R, Hadoop",PhD,1,Healthcare,2024-03-20,2024-05-27,899,8,DeepTech Ventures +AI06390,Research Scientist,70564,USD,70564,EN,CT,Sweden,S,Sweden,50,"SQL, Data Visualization, GCP, MLOps",Master,0,Government,2024-02-26,2024-05-08,2322,8.4,Neural Networks Co +AI06391,AI Consultant,181975,SGD,236568,SE,FL,Singapore,L,South Korea,0,"Azure, Java, Hadoop, PyTorch",Master,6,Transportation,2024-04-30,2024-06-30,2186,5.1,Digital Transformation LLC +AI06392,Data Scientist,125178,CHF,112660,EN,CT,Switzerland,L,Switzerland,100,"Docker, Azure, SQL, Computer Vision",Bachelor,1,Government,2025-03-10,2025-05-04,1828,8,Smart Analytics +AI06393,AI Software Engineer,118802,USD,118802,EX,FT,South Korea,M,Estonia,0,"GCP, Docker, Computer Vision",PhD,10,Education,2024-08-29,2024-10-17,2036,8.6,Cognitive Computing +AI06394,Autonomous Systems Engineer,96565,USD,96565,SE,FL,Ireland,S,Ireland,50,"Mathematics, Python, TensorFlow, Spark, Hadoop",Master,9,Healthcare,2025-03-24,2025-05-18,1179,6.5,Cognitive Computing +AI06395,NLP Engineer,31256,USD,31256,EN,FL,China,S,Singapore,0,"AWS, Docker, Linux, Kubernetes",PhD,1,Energy,2025-04-18,2025-06-06,1804,5.5,Future Systems +AI06396,Data Engineer,75314,USD,75314,EN,FL,Finland,M,Finland,50,"Tableau, PyTorch, Statistics, NLP",PhD,1,Media,2024-10-29,2024-11-12,1581,7.3,Smart Analytics +AI06397,Research Scientist,51533,USD,51533,EN,FT,Sweden,M,Nigeria,0,"Computer Vision, AWS, GCP, Kubernetes",Associate,1,Finance,2024-12-29,2025-01-13,2031,10,Cloud AI Solutions +AI06398,Data Engineer,121829,USD,121829,MI,CT,Ireland,L,Ireland,0,"Python, Docker, Mathematics, Kubernetes",Associate,2,Automotive,2024-07-10,2024-08-01,2140,6.7,Future Systems +AI06399,AI Research Scientist,138335,EUR,117585,EX,PT,Germany,M,Germany,100,"Kubernetes, Spark, Statistics",Associate,19,Transportation,2025-04-21,2025-05-13,808,6.3,Quantum Computing Inc +AI06400,Data Engineer,143264,EUR,121774,SE,CT,Netherlands,M,Netherlands,50,"Hadoop, GCP, NLP",Bachelor,9,Healthcare,2024-02-05,2024-03-21,1023,9.2,Autonomous Tech +AI06401,Principal Data Scientist,121815,EUR,103543,SE,CT,Germany,L,Germany,50,"Scala, Python, Spark, MLOps",Associate,7,Manufacturing,2024-10-11,2024-12-13,1914,9.1,Digital Transformation LLC +AI06402,AI Consultant,49981,USD,49981,EN,PT,Finland,S,Thailand,0,"Python, AWS, SQL, NLP",PhD,1,Energy,2024-12-12,2025-02-17,1018,9.2,DataVision Ltd +AI06403,AI Specialist,150416,EUR,127854,EX,FL,Germany,M,Germany,100,"AWS, Python, TensorFlow, PyTorch, GCP",PhD,13,Telecommunications,2024-05-02,2024-07-03,2420,5.3,Quantum Computing Inc +AI06404,AI Software Engineer,121297,CHF,109167,EN,PT,Switzerland,L,Switzerland,0,"Scala, Docker, Mathematics, AWS, Java",PhD,0,Consulting,2024-06-06,2024-06-27,2283,6.8,AI Innovations +AI06405,Deep Learning Engineer,213889,AUD,288750,EX,FL,Australia,S,Australia,50,"Git, Mathematics, PyTorch, Java",Associate,11,Technology,2024-04-30,2024-06-15,2273,7.6,Algorithmic Solutions +AI06406,Deep Learning Engineer,130442,USD,130442,MI,CT,United States,L,United States,50,"Statistics, Git, PyTorch",PhD,2,Gaming,2024-03-19,2024-05-10,1768,5.4,Algorithmic Solutions +AI06407,Computer Vision Engineer,206439,CAD,258049,EX,FT,Canada,S,Canada,0,"Linux, Deep Learning, NLP",Master,10,Government,2024-01-18,2024-02-03,1229,8.2,AI Innovations +AI06408,Data Analyst,34594,USD,34594,EN,PT,China,L,China,100,"NLP, AWS, Azure, Python",Associate,0,Automotive,2025-04-20,2025-06-24,624,7,AI Innovations +AI06409,Deep Learning Engineer,162384,USD,162384,SE,PT,Israel,L,Kenya,100,"GCP, SQL, Linux",PhD,6,Automotive,2024-12-10,2025-02-19,2298,7.3,Advanced Robotics +AI06410,Data Analyst,102488,CAD,128110,SE,FT,Canada,M,Canada,50,"Statistics, MLOps, TensorFlow, Data Visualization, Spark",Associate,5,Consulting,2024-10-13,2024-11-13,680,8.7,TechCorp Inc +AI06411,ML Ops Engineer,156199,USD,156199,EX,FL,Finland,S,Finland,50,"R, Data Visualization, Docker",PhD,17,Automotive,2024-12-11,2025-02-11,2456,7.6,AI Innovations +AI06412,AI Software Engineer,150000,USD,150000,EX,FT,South Korea,L,South Korea,100,"Kubernetes, Azure, Spark",Associate,16,Government,2025-04-01,2025-04-23,939,9.9,Autonomous Tech +AI06413,Data Scientist,111963,CAD,139954,SE,FT,Canada,L,Canada,100,"Statistics, Scala, Linux",Master,5,Finance,2024-09-15,2024-10-08,638,6.8,Cloud AI Solutions +AI06414,Data Engineer,67558,USD,67558,MI,FL,Sweden,S,Sweden,50,"NLP, Python, Mathematics, AWS, Scala",Bachelor,3,Education,2024-02-01,2024-02-27,2198,5.2,Future Systems +AI06415,Data Scientist,75401,EUR,64091,MI,FL,France,M,France,100,"SQL, Linux, Kubernetes, Java, PyTorch",Bachelor,3,Automotive,2024-01-06,2024-01-25,2376,5.6,AI Innovations +AI06416,AI Research Scientist,77098,CHF,69388,EN,FL,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, GCP, Statistics",Master,1,Healthcare,2024-02-10,2024-04-19,1408,5.9,Future Systems +AI06417,Data Engineer,129667,GBP,97250,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Git, NLP, AWS",Associate,4,Telecommunications,2024-04-08,2024-05-17,1925,9.2,AI Innovations +AI06418,Robotics Engineer,62417,EUR,53054,EN,FL,Netherlands,M,Netherlands,100,"Python, R, Docker",PhD,0,Government,2024-07-22,2024-08-11,1830,6.3,Machine Intelligence Group +AI06419,AI Consultant,161660,JPY,17782600,SE,PT,Japan,M,Romania,0,"Computer Vision, Python, GCP",PhD,6,Real Estate,2024-05-04,2024-05-18,1197,6.1,Advanced Robotics +AI06420,Computer Vision Engineer,85425,AUD,115324,MI,PT,Australia,S,Australia,0,"Spark, Git, Python, Computer Vision, NLP",Associate,4,Consulting,2024-08-12,2024-10-07,1642,8.8,DeepTech Ventures +AI06421,AI Product Manager,269941,CHF,242947,EX,PT,Switzerland,S,Switzerland,0,"SQL, GCP, NLP, Spark",PhD,17,Finance,2024-01-06,2024-03-12,2138,7.5,Advanced Robotics +AI06422,Data Analyst,349432,USD,349432,EX,FT,Denmark,L,Denmark,0,"SQL, Linux, GCP, Hadoop, R",Associate,17,Energy,2024-10-17,2024-12-13,1557,9.9,Quantum Computing Inc +AI06423,Autonomous Systems Engineer,52126,USD,52126,SE,CT,China,S,Brazil,100,"Hadoop, Git, Java",Master,9,Government,2024-09-18,2024-11-02,1709,8,Predictive Systems +AI06424,AI Product Manager,166822,EUR,141799,EX,PT,Germany,M,Germany,0,"Hadoop, Data Visualization, Scala",PhD,11,Consulting,2025-01-23,2025-02-17,2222,5.9,Digital Transformation LLC +AI06425,Robotics Engineer,136925,AUD,184849,EX,CT,Australia,S,Australia,100,"MLOps, AWS, Python, Scala",Associate,17,Healthcare,2024-09-08,2024-09-30,2197,7.5,Advanced Robotics +AI06426,Deep Learning Engineer,98877,CAD,123596,MI,FT,Canada,L,Canada,100,"TensorFlow, Azure, Linux, Git",Master,2,Energy,2024-01-06,2024-03-18,871,5.4,Digital Transformation LLC +AI06427,Deep Learning Engineer,168236,EUR,143001,EX,FT,France,M,France,100,"AWS, Kubernetes, PyTorch",Bachelor,18,Telecommunications,2024-04-08,2024-05-15,1463,7.3,Advanced Robotics +AI06428,Machine Learning Engineer,102521,CAD,128151,MI,PT,Canada,L,Canada,100,"Kubernetes, R, SQL, Python",Bachelor,3,Gaming,2024-04-24,2024-06-19,697,6.9,Machine Intelligence Group +AI06429,Robotics Engineer,106928,USD,106928,MI,PT,Norway,M,Vietnam,0,"TensorFlow, Statistics, Spark",Associate,4,Real Estate,2024-11-10,2025-01-18,829,7.9,DeepTech Ventures +AI06430,Data Scientist,76026,GBP,57020,EN,FL,United Kingdom,S,United Kingdom,100,"Python, Docker, AWS, TensorFlow",PhD,0,Healthcare,2024-02-06,2024-03-14,2063,8.2,Algorithmic Solutions +AI06431,AI Specialist,88213,USD,88213,EN,FT,Sweden,L,Sweden,100,"Linux, TensorFlow, Computer Vision, Python, Hadoop",PhD,1,Energy,2024-05-03,2024-05-19,1771,8.7,Quantum Computing Inc +AI06432,AI Architect,82027,USD,82027,EN,FL,Sweden,L,Romania,0,"Mathematics, Hadoop, Scala",Associate,0,Media,2025-01-10,2025-01-25,2035,6.7,Advanced Robotics +AI06433,Robotics Engineer,109435,USD,109435,EN,FT,Denmark,L,Denmark,100,"Mathematics, GCP, Linux, MLOps, Python",PhD,1,Real Estate,2024-01-10,2024-03-01,545,8.5,Cognitive Computing +AI06434,Autonomous Systems Engineer,123502,AUD,166728,MI,FL,Australia,L,Sweden,100,"Python, Kubernetes, Deep Learning, Computer Vision, Hadoop",Associate,2,Education,2024-07-29,2024-08-27,1793,8,DataVision Ltd +AI06435,Autonomous Systems Engineer,80462,USD,80462,EN,PT,United States,S,Brazil,100,"Kubernetes, AWS, Hadoop",Associate,1,Consulting,2024-12-24,2025-01-24,1904,7.9,Machine Intelligence Group +AI06436,Machine Learning Engineer,109229,USD,109229,MI,PT,Ireland,M,Ireland,50,"Statistics, TensorFlow, Azure, GCP",PhD,4,Telecommunications,2024-04-09,2024-05-02,2303,9.2,Advanced Robotics +AI06437,AI Consultant,159957,EUR,135963,SE,FL,Netherlands,L,Netherlands,50,"GCP, TensorFlow, SQL, Computer Vision, Hadoop",Associate,9,Consulting,2024-07-17,2024-09-06,1452,5.2,Cloud AI Solutions +AI06438,Head of AI,65788,USD,65788,MI,CT,Sweden,S,Portugal,0,"Git, Tableau, Python",PhD,2,Retail,2024-10-17,2024-12-20,1066,9,Predictive Systems +AI06439,AI Software Engineer,100348,USD,100348,MI,FT,Ireland,L,Ireland,100,"Hadoop, Python, Git, AWS, Docker",Bachelor,2,Retail,2024-07-02,2024-09-07,2267,8,Digital Transformation LLC +AI06440,Computer Vision Engineer,47408,USD,47408,SE,FT,China,S,China,50,"NLP, Tableau, Python",Master,6,Gaming,2024-06-14,2024-08-26,2076,6.8,Machine Intelligence Group +AI06441,ML Ops Engineer,104139,USD,104139,SE,FT,Finland,M,Romania,100,"Python, TensorFlow, Statistics, Git",Associate,7,Energy,2024-10-29,2024-12-22,2233,9.6,Autonomous Tech +AI06442,AI Product Manager,88730,JPY,9760300,EN,FL,Japan,L,Japan,0,"R, Spark, MLOps, TensorFlow",PhD,1,Media,2024-05-23,2024-06-30,888,7.2,DataVision Ltd +AI06443,AI Product Manager,352205,USD,352205,EX,FT,Denmark,L,Denmark,100,"Computer Vision, Python, Tableau, NLP",Bachelor,16,Media,2024-10-27,2024-11-28,1380,6.6,Neural Networks Co +AI06444,AI Research Scientist,98921,EUR,84083,MI,FT,Austria,L,Austria,0,"Kubernetes, TensorFlow, Computer Vision, Git, NLP",PhD,2,Finance,2024-11-25,2025-01-28,2210,6.2,DeepTech Ventures +AI06445,Robotics Engineer,183596,EUR,156057,EX,CT,Netherlands,S,Netherlands,100,"Hadoop, Scala, Mathematics",Bachelor,19,Energy,2024-01-01,2024-03-11,1209,8.8,DataVision Ltd +AI06446,AI Architect,80147,USD,80147,MI,CT,Sweden,M,Denmark,50,"Python, Spark, GCP, Deep Learning, MLOps",PhD,2,Automotive,2024-03-28,2024-04-27,2364,6.9,Cloud AI Solutions +AI06447,Head of AI,38802,USD,38802,EN,FL,South Korea,S,South Korea,50,"Data Visualization, Git, Spark",Master,0,Manufacturing,2024-12-28,2025-02-14,1953,9.4,Quantum Computing Inc +AI06448,Robotics Engineer,42256,USD,42256,EN,FT,South Korea,M,South Korea,50,"PyTorch, GCP, SQL, Data Visualization",Bachelor,1,Automotive,2024-04-04,2024-05-22,2290,7.2,DataVision Ltd +AI06449,Machine Learning Researcher,295649,JPY,32521390,EX,FL,Japan,L,Japan,100,"Git, Mathematics, R, Python, Azure",Associate,10,Technology,2024-11-14,2025-01-12,2439,7.2,Cloud AI Solutions +AI06450,Head of AI,139693,GBP,104770,SE,PT,United Kingdom,S,United Kingdom,0,"GCP, Git, Tableau, MLOps",Master,5,Media,2025-03-24,2025-04-22,1262,5,AI Innovations +AI06451,Deep Learning Engineer,252118,USD,252118,EX,FT,Norway,S,Norway,50,"Hadoop, Computer Vision, Python",Associate,12,Automotive,2024-12-02,2025-02-03,1914,5.3,DataVision Ltd +AI06452,Research Scientist,96310,USD,96310,MI,FL,South Korea,L,South Korea,100,"Python, NLP, TensorFlow",Master,3,Real Estate,2024-09-30,2024-10-15,880,7.3,Advanced Robotics +AI06453,Machine Learning Researcher,97905,USD,97905,EX,FL,China,M,United States,50,"Python, Git, Statistics, Computer Vision, Linux",Bachelor,11,Consulting,2024-08-08,2024-09-15,1148,8.1,Smart Analytics +AI06454,AI Product Manager,74082,GBP,55562,EN,PT,United Kingdom,L,United Kingdom,50,"Python, Spark, Tableau, Mathematics, Linux",Master,0,Automotive,2024-08-27,2024-10-01,1197,9.4,Cloud AI Solutions +AI06455,ML Ops Engineer,189768,CHF,170791,SE,FL,Switzerland,S,Switzerland,100,"AWS, Linux, MLOps",Associate,5,Consulting,2024-01-19,2024-03-23,1493,9.4,AI Innovations +AI06456,AI Software Engineer,66570,USD,66570,EN,CT,Sweden,S,Philippines,50,"Computer Vision, GCP, Tableau",Master,1,Telecommunications,2024-07-07,2024-09-08,1957,5.9,Digital Transformation LLC +AI06457,Machine Learning Researcher,326160,CHF,293544,EX,FL,Switzerland,M,Indonesia,100,"Python, Java, Azure",Associate,16,Gaming,2025-01-04,2025-03-02,902,5.9,Cognitive Computing +AI06458,AI Research Scientist,78922,JPY,8681420,EN,FT,Japan,M,Japan,50,"Deep Learning, Computer Vision, PyTorch",Associate,0,Retail,2024-10-15,2024-12-27,1123,5.8,Quantum Computing Inc +AI06459,Data Analyst,49976,USD,49976,MI,PT,China,M,China,100,"Python, GCP, Tableau, SQL",Bachelor,2,Government,2024-12-24,2025-02-03,2010,8.6,Quantum Computing Inc +AI06460,Machine Learning Researcher,64771,USD,64771,EX,CT,China,M,China,50,"Tableau, Python, AWS, Spark, TensorFlow",PhD,10,Government,2025-04-03,2025-05-02,2118,9.9,Neural Networks Co +AI06461,Data Scientist,77752,EUR,66089,EN,CT,Netherlands,M,Netherlands,0,"R, GCP, Tableau, Python, AWS",Master,1,Transportation,2024-01-15,2024-03-05,818,8.1,TechCorp Inc +AI06462,AI Consultant,101180,AUD,136593,SE,CT,Australia,S,India,100,"Java, Data Visualization, PyTorch, Kubernetes, TensorFlow",Associate,5,Telecommunications,2024-04-24,2024-05-13,1032,8.6,Future Systems +AI06463,Computer Vision Engineer,207576,EUR,176440,EX,FL,France,L,France,50,"Statistics, NLP, Scala, Data Visualization",Associate,10,Manufacturing,2025-04-30,2025-05-21,716,8.2,Advanced Robotics +AI06464,AI Software Engineer,30028,USD,30028,MI,FL,India,L,India,50,"Tableau, Kubernetes, GCP, R, Deep Learning",Bachelor,4,Media,2024-01-15,2024-03-04,1402,9.2,Smart Analytics +AI06465,Robotics Engineer,243505,CAD,304381,EX,FT,Canada,L,Canada,50,"Spark, Scala, SQL, Java",Bachelor,12,Finance,2024-07-29,2024-09-12,2274,5.4,TechCorp Inc +AI06466,Robotics Engineer,51214,USD,51214,EN,FT,Finland,S,Finland,0,"Azure, GCP, Java",Master,1,Retail,2024-06-22,2024-07-06,802,7.3,Quantum Computing Inc +AI06467,Data Scientist,76863,CHF,69177,EN,CT,Switzerland,M,Switzerland,0,"Scala, Git, Statistics",Associate,0,Energy,2024-02-05,2024-03-24,1557,7.6,Predictive Systems +AI06468,Machine Learning Engineer,179636,USD,179636,SE,FL,United States,L,United States,0,"Mathematics, Linux, Hadoop, Deep Learning",Master,8,Consulting,2024-12-16,2025-01-29,2432,6.7,Predictive Systems +AI06469,Robotics Engineer,30950,USD,30950,MI,PT,India,L,France,50,"R, SQL, Statistics",PhD,3,Consulting,2024-02-08,2024-03-15,1262,9.1,AI Innovations +AI06470,Principal Data Scientist,148429,USD,148429,SE,CT,Finland,L,South Africa,100,"PyTorch, Computer Vision, TensorFlow, SQL, Java",Associate,5,Manufacturing,2024-08-16,2024-09-13,717,8.9,TechCorp Inc +AI06471,AI Specialist,49035,EUR,41680,EN,FL,Austria,S,Netherlands,100,"Azure, Linux, MLOps",Master,1,Government,2024-11-20,2024-12-28,1457,8.6,Machine Intelligence Group +AI06472,AI Specialist,75189,SGD,97746,EN,CT,Singapore,M,Norway,0,"Mathematics, Azure, TensorFlow, Computer Vision, Hadoop",Master,0,Transportation,2024-12-02,2025-01-04,598,5.7,DeepTech Ventures +AI06473,Robotics Engineer,71967,GBP,53975,EN,PT,United Kingdom,L,United Kingdom,0,"Scala, Tableau, Hadoop, MLOps, NLP",Associate,0,Gaming,2024-05-18,2024-07-10,1985,8.9,Advanced Robotics +AI06474,NLP Engineer,190712,CAD,238390,EX,CT,Canada,S,Canada,50,"PyTorch, R, Kubernetes, Azure",Master,12,Media,2024-12-21,2025-01-10,1967,9.3,DataVision Ltd +AI06475,NLP Engineer,297771,GBP,223328,EX,FL,United Kingdom,L,United Kingdom,50,"AWS, Linux, PyTorch, Azure",PhD,14,Gaming,2025-02-24,2025-03-21,1502,5.7,Future Systems +AI06476,AI Specialist,156829,USD,156829,EX,FT,South Korea,S,South Korea,0,"SQL, Scala, Deep Learning, GCP",Associate,13,Consulting,2025-04-19,2025-05-17,762,7.6,AI Innovations +AI06477,ML Ops Engineer,143894,EUR,122310,EX,CT,France,M,Indonesia,0,"Python, TensorFlow, Computer Vision, Spark",PhD,18,Automotive,2025-04-21,2025-05-12,1614,7.7,Predictive Systems +AI06478,AI Software Engineer,150682,CHF,135614,MI,CT,Switzerland,M,Switzerland,100,"Java, PyTorch, Azure",Master,3,Education,2024-01-15,2024-02-13,1957,6.2,Algorithmic Solutions +AI06479,AI Product Manager,72926,USD,72926,EN,CT,United States,M,United States,0,"Python, Kubernetes, TensorFlow, Mathematics, Docker",PhD,1,Consulting,2024-08-26,2024-09-23,2383,9.7,Future Systems +AI06480,AI Specialist,50034,USD,50034,MI,FL,China,M,China,50,"Computer Vision, Azure, Kubernetes, Scala, MLOps",Associate,3,Healthcare,2025-04-14,2025-05-24,1718,9.8,DataVision Ltd +AI06481,Machine Learning Engineer,227301,USD,227301,EX,FL,Sweden,M,Sweden,0,"Linux, Tableau, R, Docker, Statistics",Bachelor,12,Manufacturing,2024-03-16,2024-05-07,1933,9.2,Future Systems +AI06482,Data Engineer,177520,GBP,133140,SE,FL,United Kingdom,L,Portugal,0,"Scala, Mathematics, Spark, Kubernetes",Associate,7,Retail,2024-12-03,2025-01-10,1975,8.3,Machine Intelligence Group +AI06483,AI Product Manager,290219,CHF,261197,EX,FT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Linux, TensorFlow",Associate,19,Finance,2024-07-22,2024-09-22,513,5.8,DataVision Ltd +AI06484,AI Research Scientist,178653,EUR,151855,EX,CT,Austria,L,Germany,0,"GCP, Kubernetes, Python",Master,18,Healthcare,2025-01-20,2025-02-14,1825,7.3,Autonomous Tech +AI06485,AI Product Manager,122006,EUR,103705,SE,CT,Germany,M,Germany,0,"Git, NLP, Linux, Scala, Data Visualization",Associate,8,Finance,2025-02-07,2025-04-09,1514,9.6,Neural Networks Co +AI06486,Robotics Engineer,168307,GBP,126230,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, SQL",Master,12,Finance,2024-12-01,2024-12-30,1505,9.9,DeepTech Ventures +AI06487,Principal Data Scientist,124629,USD,124629,EX,FT,South Korea,M,South Korea,50,"Git, Python, Azure",PhD,19,Real Estate,2024-12-02,2025-02-12,1102,8.1,Algorithmic Solutions +AI06488,Data Engineer,137796,EUR,117127,EX,CT,Austria,S,Austria,0,"Statistics, TensorFlow, Kubernetes, Linux",PhD,13,Government,2024-08-04,2024-08-28,1582,6.4,DeepTech Ventures +AI06489,AI Specialist,81533,EUR,69303,EN,CT,France,L,France,0,"Data Visualization, Docker, Tableau",Bachelor,1,Telecommunications,2025-04-08,2025-05-21,1781,5.6,Future Systems +AI06490,Principal Data Scientist,86860,USD,86860,EX,CT,China,S,Estonia,50,"SQL, Git, Kubernetes, Deep Learning",Master,18,Consulting,2024-09-02,2024-10-17,1805,7.6,AI Innovations +AI06491,Data Engineer,81781,EUR,69514,EN,FL,Netherlands,L,Netherlands,100,"PyTorch, Computer Vision, Deep Learning, TensorFlow, Azure",PhD,1,Telecommunications,2025-01-15,2025-03-04,2388,5.5,Predictive Systems +AI06492,AI Product Manager,140704,USD,140704,SE,FL,Finland,M,Finland,0,"PyTorch, SQL, Deep Learning, Tableau, NLP",Bachelor,8,Retail,2024-02-05,2024-03-24,1057,5.1,Cognitive Computing +AI06493,AI Specialist,61576,EUR,52340,EN,FL,Germany,S,Germany,50,"Spark, Linux, Git, R, Deep Learning",PhD,0,Consulting,2024-04-02,2024-04-25,698,9.1,Cloud AI Solutions +AI06494,AI Research Scientist,29955,USD,29955,EN,CT,China,M,Netherlands,50,"Hadoop, SQL, Azure, Kubernetes, Tableau",Associate,0,Transportation,2025-02-28,2025-03-26,1800,8.1,DataVision Ltd +AI06495,Computer Vision Engineer,107488,EUR,91365,SE,PT,Netherlands,S,Turkey,0,"Mathematics, Docker, Kubernetes, SQL, TensorFlow",Associate,6,Transportation,2024-03-27,2024-04-20,503,9.8,Autonomous Tech +AI06496,AI Specialist,18247,USD,18247,EN,PT,India,S,India,0,"Scala, Python, Computer Vision, Deep Learning, TensorFlow",Master,1,Gaming,2024-10-09,2024-10-30,1178,7.9,Algorithmic Solutions +AI06497,Machine Learning Engineer,141464,USD,141464,MI,FT,Norway,M,Norway,100,"Git, Java, AWS",PhD,2,Real Estate,2024-02-03,2024-03-11,1296,6.7,AI Innovations +AI06498,AI Product Manager,41759,USD,41759,SE,FL,India,S,India,100,"Mathematics, Scala, MLOps, Statistics, Linux",Master,6,Gaming,2024-01-26,2024-03-05,1858,7.6,Cloud AI Solutions +AI06499,Data Analyst,55004,JPY,6050440,EN,PT,Japan,M,Japan,100,"Git, Kubernetes, NLP",Associate,1,Gaming,2024-02-14,2024-03-20,2454,7,DeepTech Ventures +AI06500,AI Consultant,43128,USD,43128,MI,CT,China,M,China,100,"TensorFlow, Java, Azure, Mathematics, AWS",PhD,4,Transportation,2024-01-22,2024-02-20,871,7.8,Machine Intelligence Group +AI06501,AI Consultant,82614,EUR,70222,EN,CT,Germany,L,Vietnam,100,"Azure, Kubernetes, SQL",Bachelor,1,Real Estate,2024-03-17,2024-05-26,2454,7.5,Smart Analytics +AI06502,AI Research Scientist,306002,EUR,260102,EX,PT,Netherlands,L,Netherlands,100,"Linux, Hadoop, Azure, Deep Learning",Associate,17,Automotive,2024-12-17,2025-02-08,1412,9.2,Cloud AI Solutions +AI06503,Deep Learning Engineer,129451,USD,129451,SE,PT,Ireland,S,Austria,50,"Python, Linux, Deep Learning, Git, Computer Vision",Bachelor,8,Automotive,2024-10-15,2024-11-05,1411,10,Cognitive Computing +AI06504,AI Architect,192815,CHF,173534,EX,FL,Switzerland,M,Switzerland,50,"Git, SQL, TensorFlow",Master,11,Retail,2024-01-02,2024-01-29,2257,8.8,Autonomous Tech +AI06505,Research Scientist,133972,USD,133972,EX,FT,Israel,M,Singapore,0,"AWS, Kubernetes, Mathematics",Bachelor,12,Healthcare,2024-05-14,2024-06-12,1654,6.5,Digital Transformation LLC +AI06506,Data Scientist,77616,USD,77616,MI,FL,South Korea,S,South Korea,50,"AWS, TensorFlow, Scala, Tableau, Deep Learning",Master,4,Technology,2025-04-07,2025-06-12,665,5.5,Machine Intelligence Group +AI06507,Principal Data Scientist,47133,USD,47133,EN,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Spark, NLP, Java",Associate,1,Energy,2025-03-14,2025-04-03,533,5.1,Cognitive Computing +AI06508,Research Scientist,70801,USD,70801,MI,CT,South Korea,S,South Korea,100,"Tableau, Python, Java",Associate,3,Retail,2024-07-18,2024-08-10,1335,6.1,DeepTech Ventures +AI06509,AI Specialist,120997,USD,120997,SE,FL,Finland,M,Finland,50,"AWS, Deep Learning, SQL, Scala",Associate,9,Automotive,2024-05-03,2024-07-06,2203,6.7,Digital Transformation LLC +AI06510,AI Product Manager,263003,EUR,223553,EX,FL,Austria,L,Austria,100,"Scala, R, Hadoop, Deep Learning",Bachelor,15,Real Estate,2024-02-01,2024-03-18,851,6.6,Neural Networks Co +AI06511,AI Consultant,48759,GBP,36569,EN,PT,United Kingdom,S,Australia,50,"Azure, Java, Linux",PhD,0,Transportation,2024-08-30,2024-10-04,1794,7.8,Cognitive Computing +AI06512,Machine Learning Engineer,195629,GBP,146722,EX,CT,United Kingdom,S,United Kingdom,100,"R, GCP, Git",Associate,17,Energy,2024-12-30,2025-02-21,1765,8,Algorithmic Solutions +AI06513,AI Research Scientist,161173,USD,161173,SE,PT,Norway,L,Norway,0,"Computer Vision, AWS, Linux, Spark",Bachelor,9,Gaming,2024-10-01,2024-11-09,968,9.3,Digital Transformation LLC +AI06514,AI Consultant,94896,USD,94896,SE,CT,South Korea,S,South Korea,100,"Python, MLOps, Azure, Tableau",Associate,7,Finance,2024-02-05,2024-03-06,1668,5.9,Cognitive Computing +AI06515,AI Architect,47417,USD,47417,EN,FL,Israel,S,Israel,0,"Spark, Docker, Computer Vision",Bachelor,1,Retail,2025-02-14,2025-03-27,1934,6.2,AI Innovations +AI06516,Deep Learning Engineer,90359,AUD,121985,MI,FL,Australia,S,Australia,50,"Kubernetes, MLOps, Hadoop",Master,3,Government,2024-12-24,2025-02-05,1562,8.3,Advanced Robotics +AI06517,AI Research Scientist,123662,GBP,92747,MI,FL,United Kingdom,L,China,50,"Linux, Data Visualization, Hadoop",Master,2,Energy,2024-07-02,2024-07-21,2185,9,Predictive Systems +AI06518,Machine Learning Researcher,146667,AUD,198000,SE,PT,Australia,M,Australia,50,"R, PyTorch, Linux, Mathematics",Bachelor,5,Retail,2024-03-28,2024-04-18,2204,6.1,Digital Transformation LLC +AI06519,Data Scientist,66452,EUR,56484,EN,FT,Germany,S,Germany,50,"Java, Kubernetes, Tableau, NLP",Associate,0,Government,2024-12-04,2025-01-09,1711,8,Algorithmic Solutions +AI06520,Principal Data Scientist,50813,GBP,38110,EN,CT,United Kingdom,S,United Kingdom,0,"Python, Mathematics, Data Visualization, Spark, TensorFlow",Associate,1,Healthcare,2024-12-11,2025-01-30,880,6.1,DeepTech Ventures +AI06521,AI Research Scientist,226711,USD,226711,EX,PT,Sweden,L,Sweden,50,"SQL, Tableau, Python",Master,17,Consulting,2025-03-27,2025-04-14,1098,6.8,DeepTech Ventures +AI06522,AI Specialist,145967,EUR,124072,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Python, Hadoop, Docker",PhD,15,Education,2025-02-04,2025-02-24,913,5.1,Predictive Systems +AI06523,Machine Learning Engineer,214976,USD,214976,EX,CT,Sweden,S,Sweden,0,"Python, Kubernetes, PyTorch",Master,11,Manufacturing,2024-04-16,2024-06-01,2129,7,Cognitive Computing +AI06524,AI Specialist,60294,USD,60294,MI,CT,South Korea,S,South Korea,100,"R, SQL, Tableau",Associate,4,Transportation,2024-03-26,2024-05-28,1820,7.8,Algorithmic Solutions +AI06525,NLP Engineer,100722,USD,100722,MI,CT,Norway,S,Thailand,100,"Python, Azure, Computer Vision, Docker",Master,3,Real Estate,2024-08-20,2024-10-17,1877,6.2,Digital Transformation LLC +AI06526,Machine Learning Engineer,100577,EUR,85490,MI,FL,Netherlands,S,Netherlands,50,"SQL, Scala, Computer Vision, Data Visualization, PyTorch",Bachelor,3,Automotive,2024-04-12,2024-06-05,717,7.7,Future Systems +AI06527,Autonomous Systems Engineer,117696,USD,117696,MI,FL,United States,M,United States,0,"Linux, MLOps, Java, SQL, PyTorch",Associate,3,Energy,2024-12-30,2025-02-11,1640,5.8,Machine Intelligence Group +AI06528,Head of AI,184939,USD,184939,EX,PT,Finland,L,Finland,50,"R, SQL, PyTorch, TensorFlow, Tableau",Master,19,Gaming,2024-03-07,2024-04-18,1259,7.7,Autonomous Tech +AI06529,AI Software Engineer,279576,USD,279576,EX,PT,Norway,S,Netherlands,50,"SQL, PyTorch, Java, Data Visualization, AWS",Bachelor,13,Automotive,2024-03-12,2024-05-03,2005,6,Smart Analytics +AI06530,Data Analyst,223224,USD,223224,SE,PT,Norway,L,Norway,0,"Spark, Mathematics, R, TensorFlow, GCP",Bachelor,6,Government,2024-07-04,2024-09-09,2433,8.4,Cloud AI Solutions +AI06531,Robotics Engineer,154533,USD,154533,EX,FL,South Korea,M,South Korea,100,"Hadoop, AWS, Computer Vision, Azure",Bachelor,18,Gaming,2024-11-26,2025-01-27,2073,5,AI Innovations +AI06532,AI Architect,175373,SGD,227985,EX,FL,Singapore,M,Singapore,0,"SQL, Deep Learning, Kubernetes",Master,11,Healthcare,2024-11-29,2024-12-17,1476,7,Quantum Computing Inc +AI06533,Data Analyst,71134,USD,71134,SE,CT,China,M,China,0,"Linux, Deep Learning, Data Visualization",Bachelor,7,Real Estate,2024-06-29,2024-08-17,727,7.5,Predictive Systems +AI06534,AI Product Manager,61514,EUR,52287,EN,FL,Netherlands,S,Netherlands,100,"TensorFlow, Kubernetes, Data Visualization, Spark, SQL",PhD,0,Telecommunications,2024-10-15,2024-11-22,1193,7.5,Predictive Systems +AI06535,AI Architect,95381,USD,95381,MI,PT,Sweden,S,Sweden,50,"SQL, Scala, Data Visualization",Associate,4,Finance,2025-02-24,2025-03-14,1983,9,Neural Networks Co +AI06536,Machine Learning Researcher,190339,USD,190339,EX,PT,Norway,S,Norway,50,"Tableau, R, AWS",Bachelor,15,Transportation,2024-05-24,2024-07-12,2438,9,Smart Analytics +AI06537,AI Research Scientist,228266,GBP,171200,EX,FL,United Kingdom,M,Austria,0,"Tableau, Scala, Java, Azure",Master,15,Education,2024-04-01,2024-05-03,2081,7.6,Smart Analytics +AI06538,AI Specialist,201526,USD,201526,SE,PT,United States,L,Thailand,50,"Kubernetes, Spark, SQL, Statistics, Mathematics",Associate,5,Healthcare,2024-10-19,2024-11-21,2490,7.2,AI Innovations +AI06539,Data Engineer,165854,USD,165854,EX,FL,Denmark,S,Denmark,0,"Linux, Azure, Mathematics",PhD,18,Real Estate,2024-10-13,2024-11-22,2073,8,Advanced Robotics +AI06540,Head of AI,50399,USD,50399,MI,FT,China,M,Chile,50,"Linux, GCP, Data Visualization",Master,4,Energy,2024-03-30,2024-05-21,2432,7.6,TechCorp Inc +AI06541,Research Scientist,146895,USD,146895,SE,FL,Ireland,M,Ireland,0,"Git, PyTorch, SQL, AWS, Mathematics",PhD,5,Transportation,2024-03-03,2024-04-25,1660,6.8,Cognitive Computing +AI06542,Machine Learning Engineer,141242,USD,141242,EX,FL,Ireland,M,Ireland,0,"Hadoop, Java, PyTorch, TensorFlow",Associate,19,Finance,2025-03-30,2025-04-17,1744,7.6,Smart Analytics +AI06543,AI Research Scientist,227276,GBP,170457,EX,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, Computer Vision, Statistics, Python, R",Master,19,Media,2025-01-02,2025-01-30,640,8.4,Algorithmic Solutions +AI06544,AI Software Engineer,91381,EUR,77674,MI,PT,Netherlands,S,Netherlands,50,"SQL, Computer Vision, Java, R",Master,3,Gaming,2025-03-31,2025-06-04,1247,7.4,AI Innovations +AI06545,Data Analyst,127378,USD,127378,SE,PT,Israel,M,Israel,100,"Statistics, Kubernetes, Data Visualization, Git, PyTorch",Associate,6,Retail,2024-09-28,2024-10-24,2487,8.6,Machine Intelligence Group +AI06546,Principal Data Scientist,67976,USD,67976,EN,FL,Israel,S,Hungary,0,"Python, TensorFlow, Kubernetes",PhD,1,Automotive,2024-07-09,2024-08-06,1680,6.5,Future Systems +AI06547,AI Specialist,213311,CHF,191980,SE,FT,Switzerland,M,Switzerland,100,"Linux, Azure, Kubernetes",Associate,9,Manufacturing,2025-04-15,2025-05-12,2384,8.4,DeepTech Ventures +AI06548,Machine Learning Engineer,68136,EUR,57916,EN,CT,France,S,Nigeria,100,"Kubernetes, Git, Azure, NLP, Deep Learning",Master,0,Gaming,2024-04-01,2024-06-08,976,6.7,Autonomous Tech +AI06549,Robotics Engineer,137648,USD,137648,MI,CT,Norway,L,Norway,100,"SQL, Python, GCP, NLP, Mathematics",Master,2,Finance,2025-03-22,2025-05-07,1030,6.4,Neural Networks Co +AI06550,AI Software Engineer,176624,USD,176624,EX,FT,Sweden,S,Sweden,0,"SQL, Azure, Tableau",Master,18,Transportation,2024-02-02,2024-03-19,1038,7.1,TechCorp Inc +AI06551,Robotics Engineer,117861,USD,117861,EX,FL,Finland,S,Finland,0,"Python, Scala, Java",Bachelor,19,Energy,2024-12-17,2025-01-21,823,7.2,DeepTech Ventures +AI06552,Computer Vision Engineer,95983,USD,95983,MI,FL,Israel,L,Israel,100,"PyTorch, Docker, Tableau, MLOps, Linux",Associate,3,Media,2025-04-07,2025-04-27,678,5.9,Neural Networks Co +AI06553,Head of AI,127320,EUR,108222,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Deep Learning, Computer Vision, Python, R",PhD,8,Healthcare,2024-06-22,2024-08-24,980,6.6,Neural Networks Co +AI06554,Data Analyst,156695,EUR,133191,EX,FT,Austria,M,Japan,100,"Azure, Python, Scala",Associate,17,Telecommunications,2024-09-05,2024-10-05,1229,6.2,DeepTech Ventures +AI06555,ML Ops Engineer,70934,USD,70934,EN,PT,United States,S,United States,50,"AWS, Git, TensorFlow, SQL, Mathematics",Bachelor,0,Media,2024-09-14,2024-10-07,2413,8.2,Future Systems +AI06556,Research Scientist,160766,USD,160766,EX,FL,Israel,L,Israel,50,"Python, TensorFlow, Spark, Linux",PhD,19,Transportation,2024-08-07,2024-09-27,2169,9.9,AI Innovations +AI06557,Autonomous Systems Engineer,112463,USD,112463,SE,PT,Finland,M,Finland,0,"GCP, PyTorch, MLOps",Bachelor,8,Finance,2024-03-30,2024-05-13,1069,7.4,Predictive Systems +AI06558,NLP Engineer,143144,USD,143144,SE,PT,Sweden,M,Sweden,100,"Spark, Git, Tableau",Master,6,Finance,2025-01-13,2025-02-18,892,9.5,DataVision Ltd +AI06559,Principal Data Scientist,38842,USD,38842,MI,FL,China,M,China,50,"MLOps, Python, TensorFlow, PyTorch",Associate,3,Technology,2024-07-21,2024-08-21,2083,9,Algorithmic Solutions +AI06560,Machine Learning Engineer,64116,GBP,48087,EN,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Computer Vision, Kubernetes, Docker",Master,0,Media,2024-07-09,2024-08-12,2386,5.8,Cognitive Computing +AI06561,AI Software Engineer,88010,USD,88010,MI,CT,South Korea,L,South Korea,0,"Python, TensorFlow, Hadoop",Associate,2,Consulting,2024-07-12,2024-07-27,2443,7,Smart Analytics +AI06562,Head of AI,95648,USD,95648,MI,FT,Norway,S,Norway,0,"Scala, Hadoop, Docker, Computer Vision, GCP",Master,4,Healthcare,2024-11-04,2025-01-14,2231,5.3,AI Innovations +AI06563,Deep Learning Engineer,97522,SGD,126779,EN,FT,Singapore,L,Singapore,50,"Git, Python, Statistics, TensorFlow, Mathematics",Master,1,Media,2024-10-06,2024-10-31,1772,6.6,DeepTech Ventures +AI06564,Data Analyst,31058,USD,31058,EN,CT,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-06-07,2024-07-18,605,9.6,Advanced Robotics +AI06565,Research Scientist,278889,CHF,251000,EX,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, Kubernetes, Statistics, Docker",Associate,10,Transportation,2025-01-28,2025-03-16,724,5.2,DeepTech Ventures +AI06566,Data Scientist,83674,SGD,108776,EN,CT,Singapore,L,Singapore,100,"Kubernetes, Scala, Data Visualization, MLOps, GCP",Bachelor,0,Government,2024-11-02,2024-11-20,1581,6.9,Cloud AI Solutions +AI06567,AI Specialist,59348,JPY,6528280,EN,CT,Japan,M,Japan,0,"Hadoop, Java, Linux",Bachelor,0,Telecommunications,2024-12-27,2025-02-05,2315,7.8,Digital Transformation LLC +AI06568,Robotics Engineer,178661,CHF,160795,EX,FL,Switzerland,S,Netherlands,100,"AWS, Linux, NLP",Associate,18,Telecommunications,2024-07-11,2024-09-19,1704,7.8,Predictive Systems +AI06569,AI Specialist,150401,AUD,203041,EX,PT,Australia,M,Italy,0,"Mathematics, PyTorch, MLOps, AWS, TensorFlow",Master,13,Transportation,2024-05-10,2024-07-11,1135,6.6,Advanced Robotics +AI06570,AI Research Scientist,62718,EUR,53310,EN,FL,Austria,L,Austria,50,"MLOps, Scala, TensorFlow, SQL",Associate,1,Consulting,2025-04-12,2025-06-10,896,7,Cognitive Computing +AI06571,Deep Learning Engineer,68205,EUR,57974,EN,PT,Austria,L,Singapore,0,"Docker, GCP, SQL, Git, Statistics",Master,1,Telecommunications,2024-05-26,2024-08-01,2360,7.1,DeepTech Ventures +AI06572,Data Analyst,58067,USD,58067,EN,CT,Israel,L,Israel,50,"MLOps, R, Docker, Python, AWS",PhD,1,Retail,2024-03-26,2024-04-28,833,5.3,Cloud AI Solutions +AI06573,AI Product Manager,94059,SGD,122277,MI,CT,Singapore,S,Singapore,50,"Python, GCP, Statistics, Computer Vision, Kubernetes",Associate,4,Telecommunications,2024-06-27,2024-08-25,1033,9.2,AI Innovations +AI06574,Machine Learning Researcher,124056,USD,124056,SE,FL,Denmark,S,Denmark,100,"Python, Kubernetes, TensorFlow, Scala, Git",Master,5,Technology,2024-09-22,2024-10-06,1381,9.8,Cognitive Computing +AI06575,Principal Data Scientist,103972,USD,103972,EN,FT,Denmark,L,Denmark,100,"Kubernetes, Data Visualization, Hadoop",Associate,1,Healthcare,2024-01-03,2024-03-01,2122,8.4,Predictive Systems +AI06576,AI Research Scientist,120733,SGD,156953,SE,FL,Singapore,M,Singapore,50,"Hadoop, Git, Statistics",Bachelor,8,Automotive,2025-04-20,2025-05-10,2362,6,Advanced Robotics +AI06577,Autonomous Systems Engineer,49939,JPY,5493290,EN,PT,Japan,S,Poland,50,"Java, SQL, Tableau",Master,0,Gaming,2024-08-13,2024-10-22,1862,6.5,Predictive Systems +AI06578,Machine Learning Engineer,131946,USD,131946,EX,PT,Finland,M,Nigeria,0,"AWS, Python, GCP, Scala, Computer Vision",Master,17,Technology,2024-01-30,2024-03-10,1122,8.4,Cloud AI Solutions +AI06579,Principal Data Scientist,74473,CHF,67026,EN,CT,Switzerland,S,Russia,0,"GCP, Computer Vision, SQL, Deep Learning",PhD,1,Gaming,2024-06-19,2024-08-18,1120,6,Digital Transformation LLC +AI06580,ML Ops Engineer,42235,USD,42235,EN,FT,South Korea,M,South Korea,0,"TensorFlow, Tableau, SQL, NLP",Associate,0,Government,2024-02-10,2024-02-29,623,7.1,DeepTech Ventures +AI06581,AI Software Engineer,100391,USD,100391,EX,PT,China,S,China,100,"Python, R, Data Visualization",Master,16,Retail,2024-12-02,2025-02-05,2094,5.7,Autonomous Tech +AI06582,Data Analyst,224884,USD,224884,EX,CT,Ireland,L,Chile,50,"Linux, Python, TensorFlow",Master,17,Manufacturing,2025-03-29,2025-04-12,2203,7.8,Advanced Robotics +AI06583,AI Specialist,138421,USD,138421,SE,PT,Finland,L,Switzerland,0,"Deep Learning, Hadoop, PyTorch",Bachelor,8,Manufacturing,2024-05-10,2024-05-29,1120,8.3,Future Systems +AI06584,Data Analyst,73596,EUR,62557,MI,PT,Germany,S,Germany,50,"Scala, Kubernetes, Tableau, MLOps, GCP",Bachelor,3,Energy,2024-02-07,2024-03-02,783,6.4,Autonomous Tech +AI06585,AI Product Manager,118358,USD,118358,MI,CT,Ireland,L,Ireland,50,"Scala, Python, TensorFlow, AWS",Associate,4,Finance,2025-04-27,2025-06-29,1805,9.6,Autonomous Tech +AI06586,Autonomous Systems Engineer,60553,USD,60553,SE,CT,China,L,France,50,"Python, Data Visualization, Scala",PhD,5,Energy,2024-10-05,2024-12-01,688,6.9,Predictive Systems +AI06587,Principal Data Scientist,151705,EUR,128949,SE,FL,Netherlands,L,Kenya,0,"Deep Learning, Tableau, MLOps",Bachelor,9,Telecommunications,2024-06-10,2024-08-21,1911,9.3,Digital Transformation LLC +AI06588,AI Specialist,119879,EUR,101897,MI,FT,Germany,L,Germany,50,"Python, Java, Azure, Scala, R",Master,4,Manufacturing,2024-06-15,2024-07-29,1659,7.1,Autonomous Tech +AI06589,Head of AI,79545,EUR,67613,MI,FL,France,L,France,100,"Spark, Python, Computer Vision, Data Visualization, Docker",PhD,3,Consulting,2025-03-25,2025-05-06,2147,9.2,Quantum Computing Inc +AI06590,Data Analyst,59043,USD,59043,EN,FT,Finland,L,Ukraine,50,"Scala, Kubernetes, SQL, Linux",PhD,1,Real Estate,2024-06-01,2024-06-24,2127,7,AI Innovations +AI06591,ML Ops Engineer,103365,GBP,77524,MI,PT,United Kingdom,M,United Kingdom,50,"MLOps, Hadoop, Statistics",Master,3,Manufacturing,2024-05-12,2024-07-12,2256,9,Smart Analytics +AI06592,AI Software Engineer,94572,EUR,80386,MI,CT,Netherlands,M,Netherlands,0,"Java, SQL, Git, Hadoop",Master,3,Telecommunications,2025-03-24,2025-04-07,2391,6.5,DataVision Ltd +AI06593,AI Software Engineer,95620,CHF,86058,MI,CT,Switzerland,S,South Africa,100,"R, Tableau, Python, TensorFlow",Master,3,Energy,2024-09-08,2024-10-11,814,6.6,Quantum Computing Inc +AI06594,AI Consultant,333608,USD,333608,EX,FL,United States,L,United States,50,"Kubernetes, Java, NLP, R",Associate,13,Retail,2024-02-23,2024-03-17,677,6.6,Predictive Systems +AI06595,Data Analyst,125818,USD,125818,SE,FT,Norway,S,Norway,50,"SQL, TensorFlow, AWS, Python, Linux",Master,6,Telecommunications,2025-04-04,2025-05-14,2303,7.8,Quantum Computing Inc +AI06596,Robotics Engineer,79536,USD,79536,MI,CT,United States,S,United States,50,"Scala, Kubernetes, Deep Learning, Mathematics, Data Visualization",PhD,4,Telecommunications,2025-03-14,2025-05-18,2441,7.3,Predictive Systems +AI06597,Machine Learning Researcher,112134,USD,112134,MI,CT,Denmark,M,Denmark,0,"Scala, SQL, Mathematics, Java, Python",Associate,3,Consulting,2024-12-30,2025-02-18,1804,7.7,Cloud AI Solutions +AI06598,Robotics Engineer,286727,USD,286727,EX,FL,Ireland,L,Ireland,100,"Java, NLP, Data Visualization",PhD,11,Technology,2024-12-01,2025-01-07,2222,5.2,TechCorp Inc +AI06599,AI Product Manager,86549,EUR,73567,EN,PT,Netherlands,L,Netherlands,100,"Linux, Git, Data Visualization, Python, Computer Vision",PhD,0,Retail,2024-03-27,2024-05-18,1317,8.5,Neural Networks Co +AI06600,Computer Vision Engineer,137974,USD,137974,MI,PT,Norway,M,Norway,0,"Python, R, GCP, AWS, Kubernetes",PhD,2,Manufacturing,2024-10-15,2024-10-29,1016,5.2,Digital Transformation LLC +AI06601,Principal Data Scientist,48191,USD,48191,EN,FT,Israel,S,Israel,50,"R, Scala, TensorFlow, Git",Bachelor,0,Government,2024-03-19,2024-05-06,1811,6.9,DeepTech Ventures +AI06602,Robotics Engineer,137089,EUR,116526,EX,CT,Germany,S,Germany,50,"Java, PyTorch, Hadoop",Master,10,Manufacturing,2025-02-05,2025-04-07,523,9.5,Predictive Systems +AI06603,ML Ops Engineer,146050,JPY,16065500,EX,CT,Japan,S,Japan,50,"SQL, Hadoop, Statistics, PyTorch",Master,16,Gaming,2025-02-10,2025-04-20,1060,8.9,Future Systems +AI06604,Machine Learning Researcher,83076,EUR,70615,EN,CT,Austria,L,Ukraine,0,"Hadoop, Python, GCP",Associate,0,Government,2024-05-17,2024-06-23,1739,9.8,Neural Networks Co +AI06605,Data Scientist,184817,SGD,240262,EX,CT,Singapore,S,Singapore,0,"Python, Scala, Hadoop",Associate,11,Energy,2024-08-24,2024-10-13,1726,7.4,DataVision Ltd +AI06606,Head of AI,76584,EUR,65096,MI,CT,Austria,M,Poland,50,"Kubernetes, Statistics, AWS",Associate,4,Manufacturing,2025-02-04,2025-04-02,1410,5.8,Autonomous Tech +AI06607,NLP Engineer,79065,USD,79065,EN,PT,Sweden,L,Sweden,100,"Python, Scala, Linux",Associate,0,Finance,2024-07-23,2024-09-30,2099,9.3,Future Systems +AI06608,Data Scientist,118313,EUR,100566,MI,PT,France,L,France,100,"Mathematics, SQL, Python",Bachelor,3,Healthcare,2024-11-06,2024-12-21,554,5,DataVision Ltd +AI06609,Data Scientist,177046,USD,177046,EX,FT,Israel,M,Israel,100,"Git, Tableau, Linux, Python",Bachelor,17,Energy,2024-10-10,2024-11-12,2366,5.8,Future Systems +AI06610,Machine Learning Researcher,38680,USD,38680,MI,FL,China,S,China,100,"MLOps, PyTorch, GCP",Associate,2,Real Estate,2024-10-12,2024-12-05,2445,5.7,Machine Intelligence Group +AI06611,AI Architect,161186,EUR,137008,SE,FL,Netherlands,M,Sweden,100,"Python, TensorFlow, NLP, Deep Learning, Statistics",Associate,7,Healthcare,2024-09-22,2024-11-01,1454,8.9,Predictive Systems +AI06612,Data Scientist,121651,EUR,103403,SE,FL,Netherlands,M,Netherlands,100,"Hadoop, GCP, Tableau, Docker, PyTorch",Bachelor,9,Transportation,2024-07-09,2024-07-29,1405,6.6,Autonomous Tech +AI06613,Autonomous Systems Engineer,134960,JPY,14845600,SE,PT,Japan,S,Japan,50,"Java, Tableau, Azure",PhD,6,Energy,2024-06-22,2024-07-27,657,6.7,Advanced Robotics +AI06614,AI Research Scientist,52748,USD,52748,EN,CT,Israel,M,Israel,0,"SQL, Kubernetes, Python, AWS",Master,1,Manufacturing,2025-03-02,2025-05-08,1280,9.5,Cognitive Computing +AI06615,AI Software Engineer,77009,CAD,96261,MI,PT,Canada,M,Canada,100,"Deep Learning, Kubernetes, Mathematics",Bachelor,2,Media,2024-03-01,2024-04-06,2072,9,Smart Analytics +AI06616,Data Analyst,101929,SGD,132508,SE,FT,Singapore,S,Luxembourg,50,"MLOps, Java, Data Visualization",Master,5,Manufacturing,2024-02-22,2024-03-22,1996,9.2,Smart Analytics +AI06617,AI Software Engineer,118002,EUR,100302,SE,PT,France,L,Czech Republic,0,"Kubernetes, GCP, Azure, Java, R",Master,6,Real Estate,2024-09-19,2024-11-13,1549,9.7,Advanced Robotics +AI06618,Machine Learning Engineer,138903,SGD,180574,EX,PT,Singapore,S,Singapore,100,"Tableau, Java, Deep Learning",Associate,11,Energy,2024-03-13,2024-04-22,2245,9.3,DataVision Ltd +AI06619,AI Architect,279851,JPY,30783610,EX,PT,Japan,L,Japan,50,"Spark, SQL, Linux",Associate,10,Automotive,2024-02-01,2024-03-05,2260,8.4,AI Innovations +AI06620,Principal Data Scientist,168724,EUR,143415,EX,PT,Austria,L,Austria,0,"TensorFlow, Tableau, R, Java, Linux",PhD,18,Real Estate,2024-09-15,2024-11-07,942,7,DeepTech Ventures +AI06621,AI Software Engineer,305904,SGD,397675,EX,PT,Singapore,L,Australia,100,"Scala, Data Visualization, R",Master,10,Gaming,2024-01-15,2024-03-27,1819,8.8,Neural Networks Co +AI06622,Robotics Engineer,27196,USD,27196,EN,FT,China,M,China,100,"Linux, NLP, Tableau, Spark",Associate,1,Telecommunications,2025-04-22,2025-05-08,503,8.7,AI Innovations +AI06623,Machine Learning Engineer,108913,USD,108913,SE,CT,South Korea,M,Portugal,100,"GCP, Scala, Statistics, Python",Bachelor,5,Real Estate,2024-03-24,2024-04-24,1058,6.2,Autonomous Tech +AI06624,Computer Vision Engineer,133154,CAD,166443,EX,PT,Canada,M,Estonia,50,"Hadoop, Scala, PyTorch",Associate,10,Media,2024-12-19,2025-01-20,968,5.7,Autonomous Tech +AI06625,AI Research Scientist,253346,SGD,329350,EX,PT,Singapore,L,Estonia,50,"Spark, PyTorch, Kubernetes, Hadoop",Master,17,Gaming,2025-02-10,2025-04-16,1851,10,Cognitive Computing +AI06626,Autonomous Systems Engineer,257998,JPY,28379780,EX,CT,Japan,M,Nigeria,100,"MLOps, Mathematics, AWS, NLP, Linux",PhD,18,Manufacturing,2024-12-22,2025-02-23,1851,6.8,Predictive Systems +AI06627,AI Research Scientist,118724,USD,118724,SE,FL,South Korea,M,South Korea,0,"Hadoop, Docker, Mathematics, Computer Vision, Scala",Bachelor,6,Finance,2025-03-10,2025-03-25,1941,8,Cognitive Computing +AI06628,Data Scientist,88590,GBP,66443,EN,PT,United Kingdom,L,United Kingdom,100,"Data Visualization, Docker, Linux",PhD,0,Transportation,2024-08-13,2024-10-16,881,8.5,AI Innovations +AI06629,Data Scientist,45950,EUR,39058,EN,FT,Germany,S,Germany,100,"Linux, Java, Python, TensorFlow",Master,0,Manufacturing,2024-08-28,2024-11-04,1012,9.8,Autonomous Tech +AI06630,AI Consultant,202145,SGD,262789,EX,CT,Singapore,M,Singapore,50,"Spark, Python, Tableau, Git, TensorFlow",Associate,18,Retail,2025-03-04,2025-04-04,1103,9.7,Machine Intelligence Group +AI06631,ML Ops Engineer,354485,CHF,319037,EX,FL,Switzerland,M,Finland,50,"MLOps, Docker, AWS, SQL",Associate,12,Finance,2024-04-11,2024-05-15,1424,5.4,Quantum Computing Inc +AI06632,AI Architect,145381,EUR,123574,SE,FT,Netherlands,M,Netherlands,100,"TensorFlow, Python, Computer Vision, PyTorch, Git",Bachelor,6,Technology,2024-07-30,2024-09-08,2076,6.1,DeepTech Ventures +AI06633,AI Research Scientist,80273,USD,80273,SE,CT,China,L,China,50,"Azure, NLP, Scala",Associate,7,Energy,2024-09-12,2024-10-21,1925,8.7,Algorithmic Solutions +AI06634,Computer Vision Engineer,93627,CAD,117034,MI,CT,Canada,L,Netherlands,50,"Linux, Docker, Data Visualization",PhD,2,Retail,2024-03-21,2024-05-31,2091,8.7,DeepTech Ventures +AI06635,Machine Learning Researcher,101958,EUR,86664,MI,PT,Germany,L,Germany,50,"SQL, Docker, Java, NLP",Associate,4,Real Estate,2024-02-22,2024-03-17,1416,7.1,Smart Analytics +AI06636,Machine Learning Engineer,310491,EUR,263917,EX,PT,Netherlands,L,Netherlands,50,"SQL, Hadoop, PyTorch",Associate,14,Education,2024-05-13,2024-06-25,2239,7.4,Cloud AI Solutions +AI06637,Machine Learning Researcher,92455,GBP,69341,EN,PT,United Kingdom,L,Colombia,50,"Scala, Linux, Statistics, Java, Docker",Associate,1,Manufacturing,2025-04-09,2025-04-26,1369,7.4,Future Systems +AI06638,Data Engineer,106939,USD,106939,EX,PT,China,M,China,50,"Hadoop, Computer Vision, PyTorch, Data Visualization, R",Master,11,Manufacturing,2024-09-14,2024-11-18,1333,9.9,Digital Transformation LLC +AI06639,AI Product Manager,194351,EUR,165198,EX,FT,Austria,M,Austria,100,"GCP, Azure, SQL, TensorFlow, Statistics",Bachelor,16,Automotive,2025-01-03,2025-03-07,1968,7.8,Future Systems +AI06640,Machine Learning Engineer,110209,USD,110209,EX,PT,China,L,China,100,"R, Scala, Python",Associate,15,Education,2025-03-25,2025-06-01,951,9.1,Future Systems +AI06641,Data Engineer,274986,USD,274986,EX,FT,Finland,L,Finland,50,"Scala, Deep Learning, MLOps",Associate,10,Media,2024-01-31,2024-02-23,1539,6.5,Digital Transformation LLC +AI06642,Deep Learning Engineer,292272,AUD,394567,EX,CT,Australia,L,Luxembourg,0,"Computer Vision, GCP, Azure",Associate,17,Technology,2025-02-23,2025-04-11,1628,7.1,Machine Intelligence Group +AI06643,AI Specialist,70159,USD,70159,EN,PT,Finland,M,Finland,0,"Kubernetes, Spark, Python",PhD,1,Education,2024-03-27,2024-05-05,1064,8.9,Advanced Robotics +AI06644,NLP Engineer,57113,USD,57113,EN,PT,Ireland,M,Hungary,0,"Java, Tableau, Scala",Associate,0,Finance,2024-12-15,2025-02-08,1510,8.6,Cognitive Computing +AI06645,Machine Learning Engineer,67207,USD,67207,EN,CT,Israel,L,Israel,0,"Azure, Data Visualization, Git, Java, R",Associate,1,Automotive,2024-03-02,2024-04-27,1753,5.3,Neural Networks Co +AI06646,AI Product Manager,62513,USD,62513,EN,FT,Israel,M,Israel,50,"Java, MLOps, Azure",PhD,0,Education,2025-04-28,2025-05-15,935,7.3,Predictive Systems +AI06647,AI Software Engineer,120652,USD,120652,MI,PT,Norway,L,Ireland,50,"Kubernetes, Azure, Deep Learning, PyTorch, R",Associate,3,Media,2024-09-07,2024-11-15,2101,8.4,Machine Intelligence Group +AI06648,AI Research Scientist,28595,USD,28595,EN,CT,India,L,India,50,"SQL, Data Visualization, Kubernetes, Spark",Master,1,Gaming,2024-02-20,2024-03-21,588,8.7,Algorithmic Solutions +AI06649,Autonomous Systems Engineer,32487,USD,32487,MI,FT,India,L,India,50,"Spark, Azure, Statistics, Docker",Associate,2,Gaming,2024-07-11,2024-08-26,2166,6.5,TechCorp Inc +AI06650,ML Ops Engineer,124352,SGD,161658,MI,FT,Singapore,L,South Africa,100,"Python, Git, Tableau, TensorFlow, Deep Learning",Associate,2,Education,2024-03-11,2024-04-11,1805,6.1,Autonomous Tech +AI06651,Research Scientist,106533,USD,106533,MI,FT,Ireland,M,Czech Republic,0,"Hadoop, SQL, AWS, MLOps",Associate,2,Telecommunications,2024-01-20,2024-03-12,870,8.6,Advanced Robotics +AI06652,Robotics Engineer,207708,EUR,176552,EX,PT,Austria,L,Austria,50,"Tableau, GCP, AWS, MLOps, Data Visualization",Bachelor,15,Healthcare,2024-04-09,2024-05-01,2248,6.6,Autonomous Tech +AI06653,Machine Learning Engineer,66074,EUR,56163,EN,FL,Netherlands,L,Netherlands,100,"Docker, Git, Statistics, Python",PhD,0,Retail,2024-01-16,2024-01-30,2044,7.4,Quantum Computing Inc +AI06654,Head of AI,73696,USD,73696,EN,FT,Ireland,M,Ireland,0,"Java, GCP, Azure",PhD,0,Retail,2025-01-20,2025-02-25,1925,6.8,Advanced Robotics +AI06655,AI Product Manager,88897,GBP,66673,EN,PT,United Kingdom,L,United Kingdom,100,"Linux, Statistics, GCP, PyTorch",Master,1,Gaming,2025-03-06,2025-03-25,1828,7.3,Machine Intelligence Group +AI06656,AI Specialist,155437,USD,155437,EX,FL,Finland,M,Turkey,50,"Python, Azure, Git, GCP",Associate,15,Manufacturing,2024-05-22,2024-06-16,1408,8.5,Smart Analytics +AI06657,AI Software Engineer,64451,USD,64451,MI,PT,Finland,S,Finland,100,"Azure, PyTorch, Mathematics, GCP, TensorFlow",Bachelor,3,Real Estate,2024-09-05,2024-10-05,843,7.6,Autonomous Tech +AI06658,AI Specialist,105020,USD,105020,SE,PT,South Korea,M,South Korea,100,"Tableau, NLP, Scala",Bachelor,7,Finance,2024-04-28,2024-07-01,2434,5.1,Advanced Robotics +AI06659,AI Architect,116832,USD,116832,SE,FL,Finland,S,Finland,100,"Statistics, GCP, Azure, Hadoop, Mathematics",Master,9,Healthcare,2024-11-21,2024-12-27,885,8.7,Machine Intelligence Group +AI06660,AI Research Scientist,59624,USD,59624,SE,PT,India,L,Chile,0,"PyTorch, Docker, AWS, Tableau",Associate,9,Real Estate,2024-12-26,2025-02-08,597,5.3,DataVision Ltd +AI06661,Machine Learning Researcher,200837,EUR,170711,EX,CT,Germany,S,Vietnam,0,"Kubernetes, Azure, Computer Vision",Master,19,Telecommunications,2024-04-17,2024-05-17,629,9.9,TechCorp Inc +AI06662,Data Analyst,353742,USD,353742,EX,CT,Denmark,L,Denmark,100,"Data Visualization, Azure, Tableau",Associate,16,Consulting,2024-04-07,2024-05-22,1671,7.4,AI Innovations +AI06663,Machine Learning Researcher,118225,GBP,88669,SE,PT,United Kingdom,M,Singapore,0,"Git, Spark, AWS",Master,9,Transportation,2025-03-26,2025-05-25,2351,8.5,AI Innovations +AI06664,ML Ops Engineer,47080,USD,47080,MI,FL,China,M,China,100,"Spark, SQL, R, Docker",Bachelor,4,Media,2024-02-20,2024-03-09,2184,6.6,TechCorp Inc +AI06665,AI Specialist,51135,USD,51135,SE,CT,India,L,Czech Republic,0,"Data Visualization, Scala, PyTorch, Git",Associate,7,Retail,2024-12-23,2025-01-12,1475,8.4,Predictive Systems +AI06666,AI Research Scientist,155505,USD,155505,SE,CT,Israel,L,Israel,50,"R, Hadoop, SQL",PhD,6,Real Estate,2025-03-16,2025-04-30,2108,6.8,Future Systems +AI06667,Robotics Engineer,69674,JPY,7664140,MI,CT,Japan,S,Japan,100,"MLOps, AWS, Java",Bachelor,2,Consulting,2024-09-15,2024-10-05,2064,7,AI Innovations +AI06668,Computer Vision Engineer,124927,JPY,13741970,SE,CT,Japan,L,Brazil,0,"Python, Linux, Computer Vision",PhD,5,Manufacturing,2024-04-02,2024-04-17,1126,7.8,DataVision Ltd +AI06669,AI Architect,112130,USD,112130,MI,PT,United States,L,United States,50,"Statistics, AWS, Azure, MLOps, Java",Bachelor,3,Gaming,2024-06-01,2024-08-01,2120,9,Cognitive Computing +AI06670,AI Software Engineer,104109,USD,104109,EX,CT,China,L,China,100,"Kubernetes, Spark, Data Visualization, Docker",PhD,13,Technology,2025-01-28,2025-03-18,759,6.5,Algorithmic Solutions +AI06671,AI Architect,47100,EUR,40035,EN,FT,Austria,S,New Zealand,0,"Kubernetes, Deep Learning, Computer Vision",Master,0,Media,2025-04-01,2025-04-25,2189,8.6,DataVision Ltd +AI06672,Research Scientist,176096,USD,176096,EX,CT,Sweden,L,Sweden,0,"Python, TensorFlow, PyTorch, NLP, Spark",Bachelor,10,Education,2024-08-13,2024-10-08,2428,9.4,DeepTech Ventures +AI06673,Robotics Engineer,52718,EUR,44810,EN,CT,France,S,France,0,"R, Kubernetes, Spark, SQL",Associate,1,Manufacturing,2025-02-23,2025-03-28,1176,6.6,Cloud AI Solutions +AI06674,Deep Learning Engineer,103610,USD,103610,EN,FT,Norway,L,Norway,100,"Kubernetes, Scala, NLP, PyTorch",Associate,1,Consulting,2025-02-19,2025-03-11,1742,9.3,Autonomous Tech +AI06675,Robotics Engineer,121009,USD,121009,MI,FT,Denmark,L,Denmark,0,"MLOps, Spark, Computer Vision, Linux, AWS",Master,2,Telecommunications,2025-02-04,2025-04-18,2066,8.3,Machine Intelligence Group +AI06676,Research Scientist,41556,USD,41556,MI,FT,India,L,India,50,"Python, PyTorch, Git, Java, Mathematics",Bachelor,4,Manufacturing,2025-01-28,2025-03-30,1688,8.6,Future Systems +AI06677,AI Consultant,185304,GBP,138978,EX,FT,United Kingdom,L,Czech Republic,0,"SQL, Hadoop, MLOps",PhD,16,Automotive,2024-10-23,2024-12-27,1002,6.6,Autonomous Tech +AI06678,Data Engineer,53652,USD,53652,EN,CT,Israel,S,Israel,0,"Azure, TensorFlow, SQL, Java",Bachelor,0,Finance,2024-01-10,2024-03-06,1224,5.8,Machine Intelligence Group +AI06679,ML Ops Engineer,92383,USD,92383,EN,FT,Denmark,L,Denmark,0,"AWS, PyTorch, GCP, Statistics",Master,1,Automotive,2024-06-10,2024-07-11,1190,5.7,Future Systems +AI06680,Robotics Engineer,63352,EUR,53849,EN,FT,Austria,S,Brazil,0,"Tableau, Data Visualization, Docker",Bachelor,1,Real Estate,2024-12-21,2025-02-08,1985,9.5,Quantum Computing Inc +AI06681,Data Analyst,177446,EUR,150829,EX,PT,Netherlands,L,China,50,"SQL, Tableau, Mathematics, MLOps, R",Associate,14,Education,2024-08-22,2024-10-24,1232,5.4,Predictive Systems +AI06682,NLP Engineer,141780,USD,141780,SE,PT,Finland,M,Finland,50,"Python, TensorFlow, Hadoop, Computer Vision",Associate,8,Automotive,2024-09-11,2024-11-06,1148,5.2,DeepTech Ventures +AI06683,Data Scientist,106379,USD,106379,EX,CT,South Korea,S,South Korea,0,"Hadoop, Docker, NLP, MLOps",Master,19,Technology,2024-01-12,2024-03-23,1018,6,Advanced Robotics +AI06684,AI Architect,126231,EUR,107296,MI,PT,Netherlands,L,Netherlands,0,"Git, Deep Learning, Docker",Bachelor,2,Consulting,2024-06-18,2024-07-25,2285,7.4,Cloud AI Solutions +AI06685,NLP Engineer,98327,CHF,88494,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Linux, Mathematics, Data Visualization, Hadoop",Associate,0,Consulting,2024-07-13,2024-08-13,641,5.1,Machine Intelligence Group +AI06686,Robotics Engineer,48433,EUR,41168,EN,PT,France,S,France,0,"PyTorch, Mathematics, Spark, Data Visualization, Kubernetes",PhD,0,Education,2025-03-11,2025-04-01,995,5.1,Algorithmic Solutions +AI06687,NLP Engineer,98587,USD,98587,MI,FT,Sweden,M,Latvia,0,"PyTorch, Kubernetes, Java, TensorFlow, Mathematics",Associate,2,Telecommunications,2024-04-29,2024-07-10,1796,6.9,Quantum Computing Inc +AI06688,AI Consultant,126335,SGD,164236,MI,FL,Singapore,L,Estonia,100,"Kubernetes, GCP, MLOps",Master,4,Gaming,2024-05-02,2024-06-15,1252,5.6,Machine Intelligence Group +AI06689,Principal Data Scientist,155034,USD,155034,SE,FT,Sweden,L,Belgium,100,"AWS, Git, SQL, Scala",Associate,6,Automotive,2025-02-09,2025-03-07,1045,5.5,Autonomous Tech +AI06690,Machine Learning Researcher,68806,USD,68806,EN,FT,Denmark,S,Denmark,50,"Linux, Git, MLOps, R, NLP",PhD,0,Education,2024-01-10,2024-02-24,1873,8.9,Advanced Robotics +AI06691,Robotics Engineer,161126,EUR,136957,EX,FT,Germany,L,Australia,0,"R, AWS, SQL, Git",PhD,16,Manufacturing,2025-02-12,2025-04-01,1563,9.9,Cognitive Computing +AI06692,Principal Data Scientist,61977,USD,61977,EN,PT,South Korea,M,Netherlands,0,"Scala, Tableau, R, MLOps, Java",Master,1,Gaming,2025-02-03,2025-04-12,535,8.1,Cloud AI Solutions +AI06693,Robotics Engineer,92188,AUD,124454,SE,FT,Australia,S,Australia,100,"NLP, Docker, Scala, Azure",PhD,9,Real Estate,2025-04-28,2025-05-24,2170,5.3,Machine Intelligence Group +AI06694,Data Analyst,34860,USD,34860,SE,FT,India,S,Italy,100,"NLP, PyTorch, Kubernetes",Associate,7,Government,2025-03-11,2025-05-02,2487,7.3,Machine Intelligence Group +AI06695,Data Scientist,65877,USD,65877,EN,FT,Finland,M,Finland,0,"Computer Vision, Statistics, Linux, Git, Data Visualization",Bachelor,0,Government,2024-03-28,2024-05-23,1899,7.2,Future Systems +AI06696,Data Analyst,126854,AUD,171253,SE,CT,Australia,S,Australia,100,"TensorFlow, PyTorch, Statistics",Master,9,Retail,2024-09-02,2024-10-15,1528,6.9,Algorithmic Solutions +AI06697,Machine Learning Researcher,242745,USD,242745,EX,FT,Israel,L,Israel,0,"GCP, Python, NLP, SQL",Master,18,Media,2024-03-20,2024-04-14,1897,5.4,Autonomous Tech +AI06698,Research Scientist,91867,USD,91867,EX,CT,China,L,Ireland,0,"Kubernetes, Git, Linux, Computer Vision, Azure",Master,17,Media,2024-03-21,2024-05-10,1486,8.7,Quantum Computing Inc +AI06699,Computer Vision Engineer,134543,USD,134543,EX,PT,Israel,S,Israel,50,"SQL, Hadoop, Tableau, Deep Learning",Master,14,Education,2024-05-14,2024-07-20,2330,8.2,Smart Analytics +AI06700,AI Product Manager,193446,USD,193446,EX,PT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Mathematics",Master,13,Government,2024-04-09,2024-06-06,1027,6.2,AI Innovations +AI06701,Machine Learning Engineer,60381,USD,60381,SE,CT,China,S,China,100,"SQL, Docker, Statistics, Tableau",Master,5,Technology,2024-06-10,2024-07-10,2340,9,DataVision Ltd +AI06702,Data Engineer,163915,AUD,221285,SE,CT,Australia,L,Australia,50,"Scala, Azure, Tableau, Python",PhD,8,Real Estate,2024-09-18,2024-11-20,1260,9.1,Advanced Robotics +AI06703,AI Research Scientist,68470,EUR,58200,MI,FT,France,S,France,100,"Kubernetes, Git, Mathematics, PyTorch",PhD,4,Media,2024-03-20,2024-05-22,2278,7,Neural Networks Co +AI06704,AI Product Manager,161796,USD,161796,EX,FL,Norway,S,Switzerland,0,"Docker, PyTorch, Git, Deep Learning",Bachelor,13,Energy,2024-10-01,2024-11-28,529,5.1,Quantum Computing Inc +AI06705,Data Engineer,179771,USD,179771,EX,FL,Sweden,S,South Korea,0,"SQL, Hadoop, PyTorch",Master,12,Healthcare,2024-04-03,2024-05-12,508,7.4,Autonomous Tech +AI06706,AI Software Engineer,93524,USD,93524,EN,FT,Norway,M,Norway,100,"Computer Vision, Docker, Git, Spark",Bachelor,0,Retail,2024-03-09,2024-04-23,1533,7.2,DeepTech Ventures +AI06707,AI Architect,165207,USD,165207,SE,FL,Denmark,S,Germany,100,"Java, Kubernetes, Tableau, Scala, Computer Vision",Master,5,Automotive,2025-03-10,2025-04-07,946,6.8,TechCorp Inc +AI06708,Data Analyst,63790,GBP,47843,EN,PT,United Kingdom,M,United Kingdom,50,"Java, SQL, GCP, Docker",Associate,1,Government,2025-02-06,2025-03-28,644,8.1,Autonomous Tech +AI06709,Autonomous Systems Engineer,166660,USD,166660,EX,CT,Finland,S,Finland,50,"MLOps, Deep Learning, Linux",PhD,11,Government,2025-01-14,2025-02-21,715,9.7,Digital Transformation LLC +AI06710,AI Product Manager,65921,USD,65921,MI,PT,Finland,S,Finland,0,"AWS, Python, Deep Learning, Computer Vision, TensorFlow",Master,4,Retail,2025-01-22,2025-03-19,905,6.7,DataVision Ltd +AI06711,AI Product Manager,126851,EUR,107823,SE,FL,Austria,L,Austria,100,"Mathematics, Computer Vision, PyTorch",PhD,7,Consulting,2024-10-12,2024-11-06,2223,9.8,Neural Networks Co +AI06712,Machine Learning Researcher,90333,USD,90333,SE,FT,Israel,S,Nigeria,100,"SQL, Spark, Deep Learning, Computer Vision",Master,9,Real Estate,2024-10-07,2024-11-05,2265,8.1,Digital Transformation LLC +AI06713,AI Consultant,70882,CAD,88603,EN,FL,Canada,M,Canada,0,"Computer Vision, Scala, SQL, Azure",PhD,1,Media,2024-12-04,2025-02-09,598,7.2,DataVision Ltd +AI06714,AI Specialist,196013,EUR,166611,EX,FL,Austria,M,Austria,100,"PyTorch, Python, Computer Vision",Associate,13,Government,2024-06-22,2024-08-09,1413,8.6,TechCorp Inc +AI06715,AI Software Engineer,81980,EUR,69683,EN,FL,Austria,L,Chile,50,"Kubernetes, Data Visualization, Scala, MLOps, Docker",PhD,1,Media,2024-11-27,2024-12-14,1918,8.3,Cognitive Computing +AI06716,Data Engineer,58677,EUR,49875,EN,PT,Germany,S,Germany,100,"Hadoop, SQL, TensorFlow, Python, Tableau",Associate,1,Telecommunications,2024-07-11,2024-09-09,2173,9.9,AI Innovations +AI06717,Head of AI,73309,EUR,62313,EN,CT,France,M,France,100,"Docker, Computer Vision, MLOps, Python",Associate,0,Telecommunications,2024-02-18,2024-04-13,1884,6.2,Algorithmic Solutions +AI06718,Deep Learning Engineer,201876,CHF,181688,SE,FT,Switzerland,M,Switzerland,0,"SQL, Hadoop, Python, Computer Vision, Statistics",PhD,7,Media,2025-02-08,2025-04-19,2072,9.8,Algorithmic Solutions +AI06719,Computer Vision Engineer,65018,USD,65018,EN,CT,Ireland,S,Ireland,100,"Python, Java, Spark, Linux, Hadoop",Associate,0,Consulting,2024-10-22,2024-11-15,2365,9,DeepTech Ventures +AI06720,Robotics Engineer,161696,GBP,121272,SE,FT,United Kingdom,L,United Kingdom,50,"Hadoop, SQL, Linux, Java, AWS",Master,6,Manufacturing,2024-05-14,2024-06-09,1123,5.1,Cognitive Computing +AI06721,Head of AI,59865,USD,59865,SE,CT,China,S,China,0,"SQL, Python, Docker, TensorFlow, Statistics",Bachelor,7,Healthcare,2024-11-20,2025-01-26,1696,7,Advanced Robotics +AI06722,Principal Data Scientist,73349,GBP,55012,MI,PT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow",Master,3,Retail,2024-10-20,2024-12-16,1212,9.7,Predictive Systems +AI06723,AI Consultant,62324,CAD,77905,EN,FL,Canada,S,Canada,100,"Mathematics, SQL, Azure, PyTorch, Scala",PhD,1,Energy,2024-01-27,2024-02-20,1034,7.5,Autonomous Tech +AI06724,AI Software Engineer,125505,USD,125505,MI,FL,Denmark,M,Denmark,50,"PyTorch, Scala, AWS",Bachelor,2,Government,2024-09-21,2024-11-10,1131,7.5,Quantum Computing Inc +AI06725,Data Scientist,124940,USD,124940,MI,CT,Ireland,L,Ireland,100,"Computer Vision, Kubernetes, NLP, Hadoop, Mathematics",Associate,4,Technology,2025-04-06,2025-05-29,1172,8.8,Autonomous Tech +AI06726,Machine Learning Engineer,62978,EUR,53531,EN,CT,Germany,S,Germany,100,"Statistics, Linux, Computer Vision, Deep Learning",PhD,1,Energy,2024-10-20,2024-12-18,889,8.9,Autonomous Tech +AI06727,Head of AI,146869,CAD,183586,EX,FL,Canada,S,Indonesia,50,"Tableau, Scala, Kubernetes, Data Visualization",Master,18,Healthcare,2024-05-12,2024-07-14,595,6.9,Quantum Computing Inc +AI06728,Robotics Engineer,216474,AUD,292240,EX,FT,Australia,M,India,100,"AWS, Kubernetes, Hadoop, Tableau",Bachelor,10,Media,2024-08-23,2024-09-11,1460,7.9,Cognitive Computing +AI06729,Machine Learning Researcher,91542,GBP,68657,MI,FL,United Kingdom,S,Ukraine,50,"TensorFlow, Statistics, Mathematics",PhD,3,Consulting,2024-08-17,2024-09-05,2001,6.9,Quantum Computing Inc +AI06730,Research Scientist,104890,CAD,131113,MI,FL,Canada,L,Canada,0,"Scala, Kubernetes, MLOps, Computer Vision, Git",Associate,4,Automotive,2024-04-29,2024-07-08,1658,5.3,DataVision Ltd +AI06731,AI Product Manager,74588,EUR,63400,MI,FL,France,S,France,100,"Scala, Linux, Git, TensorFlow, Deep Learning",Bachelor,4,Finance,2024-09-16,2024-11-04,1680,5.4,Future Systems +AI06732,Data Scientist,142343,EUR,120992,EX,PT,Germany,S,Germany,50,"Hadoop, Spark, MLOps",PhD,19,Media,2024-08-21,2024-09-18,1251,9.5,Digital Transformation LLC +AI06733,Deep Learning Engineer,161000,GBP,120750,EX,CT,United Kingdom,S,United Kingdom,50,"Git, Statistics, SQL, Deep Learning",Bachelor,13,Government,2024-09-08,2024-10-13,1604,8,DeepTech Ventures +AI06734,Autonomous Systems Engineer,214330,AUD,289346,EX,FT,Australia,S,Spain,50,"Python, TensorFlow, SQL",Bachelor,16,Education,2024-04-04,2024-05-09,2467,6.7,Cloud AI Solutions +AI06735,Deep Learning Engineer,103678,EUR,88126,SE,CT,France,M,Denmark,100,"Python, Git, TensorFlow, SQL, MLOps",Bachelor,9,Energy,2024-06-25,2024-09-02,514,5.5,Predictive Systems +AI06736,Principal Data Scientist,54303,USD,54303,EN,FL,South Korea,M,Israel,100,"PyTorch, Data Visualization, Tableau, Deep Learning, Scala",PhD,0,Retail,2024-01-24,2024-03-27,1109,6.8,Advanced Robotics +AI06737,NLP Engineer,56474,USD,56474,EN,CT,Sweden,M,Sweden,50,"PyTorch, Kubernetes, Hadoop, Mathematics, SQL",Associate,0,Technology,2024-05-23,2024-08-02,1477,6,Neural Networks Co +AI06738,NLP Engineer,300349,GBP,225262,EX,PT,United Kingdom,L,United Kingdom,0,"Java, Data Visualization, Hadoop, Python",Bachelor,18,Media,2024-05-22,2024-07-11,827,7.5,Cloud AI Solutions +AI06739,AI Consultant,44528,EUR,37849,EN,FT,France,S,France,100,"R, MLOps, Data Visualization, Kubernetes",Master,1,Finance,2024-04-01,2024-05-07,1942,5.5,DeepTech Ventures +AI06740,Machine Learning Researcher,118343,USD,118343,SE,FT,Israel,M,Israel,100,"Mathematics, MLOps, Data Visualization",PhD,6,Healthcare,2024-07-30,2024-09-03,1236,8.3,Advanced Robotics +AI06741,AI Architect,125950,USD,125950,MI,FT,Denmark,L,Poland,50,"SQL, AWS, NLP",Bachelor,4,Technology,2025-01-30,2025-03-01,1563,6,Neural Networks Co +AI06742,AI Research Scientist,61502,USD,61502,EN,CT,Israel,M,Austria,50,"R, Python, Java, GCP",Master,1,Media,2025-01-01,2025-01-28,2019,9.1,Quantum Computing Inc +AI06743,Head of AI,44859,EUR,38130,EN,CT,France,S,France,0,"Azure, Tableau, GCP",PhD,1,Healthcare,2024-11-21,2024-12-31,1364,5.3,Advanced Robotics +AI06744,Autonomous Systems Engineer,119175,JPY,13109250,MI,CT,Japan,L,Japan,100,"Kubernetes, Python, MLOps",Bachelor,4,Automotive,2025-04-21,2025-06-27,1528,6.9,Algorithmic Solutions +AI06745,Research Scientist,90723,USD,90723,MI,PT,United States,M,United States,0,"Hadoop, Mathematics, Tableau",Master,3,Government,2024-07-23,2024-10-01,1136,5.5,Quantum Computing Inc +AI06746,Robotics Engineer,239693,EUR,203739,EX,CT,France,L,China,100,"AWS, Scala, Statistics, Spark",PhD,11,Healthcare,2025-02-06,2025-03-01,2160,5.9,DeepTech Ventures +AI06747,Autonomous Systems Engineer,89947,CHF,80952,EN,FT,Switzerland,L,Australia,0,"AWS, Python, MLOps",Bachelor,0,Energy,2024-03-01,2024-05-02,1832,5.7,DataVision Ltd +AI06748,AI Architect,78388,USD,78388,MI,CT,Finland,S,Finland,50,"MLOps, Tableau, Python",Associate,3,Consulting,2024-08-23,2024-10-11,1416,9,TechCorp Inc +AI06749,Deep Learning Engineer,205050,USD,205050,SE,FL,United States,L,United States,100,"Kubernetes, Deep Learning, PyTorch, TensorFlow, SQL",Bachelor,7,Retail,2024-02-28,2024-04-22,2190,5.3,Autonomous Tech +AI06750,Data Scientist,91998,EUR,78198,MI,FL,Netherlands,M,Netherlands,0,"Data Visualization, Python, GCP",PhD,4,Education,2024-03-25,2024-05-20,1349,5.6,Cloud AI Solutions +AI06751,Data Engineer,226755,USD,226755,EX,PT,Finland,L,Finland,0,"Git, PyTorch, SQL, TensorFlow",Master,13,Gaming,2024-12-27,2025-02-28,564,6.4,Algorithmic Solutions +AI06752,NLP Engineer,123422,USD,123422,MI,FT,Denmark,S,Denmark,100,"Python, AWS, TensorFlow, Data Visualization, GCP",Associate,4,Telecommunications,2024-11-16,2024-12-12,2296,6.2,Cloud AI Solutions +AI06753,Data Engineer,206557,USD,206557,SE,FT,Norway,L,Norway,0,"PyTorch, Kubernetes, AWS, Azure, Computer Vision",PhD,9,Automotive,2025-02-18,2025-03-25,2426,6.9,TechCorp Inc +AI06754,Computer Vision Engineer,97955,USD,97955,EN,PT,Denmark,L,Kenya,100,"SQL, Linux, Azure, Spark, Deep Learning",Associate,1,Consulting,2024-07-05,2024-09-01,2218,9.7,Neural Networks Co +AI06755,Robotics Engineer,113968,AUD,153857,SE,CT,Australia,M,Australia,0,"Docker, Java, Python, Azure",Bachelor,9,Telecommunications,2024-06-12,2024-07-17,1975,5.5,Predictive Systems +AI06756,Autonomous Systems Engineer,73215,CAD,91519,EN,PT,Canada,M,Canada,0,"Scala, Python, Tableau",Master,0,Education,2024-06-28,2024-09-06,1660,7.5,Machine Intelligence Group +AI06757,Data Analyst,79628,CAD,99535,EN,FT,Canada,L,Japan,50,"Python, Docker, Computer Vision, Mathematics, Statistics",Bachelor,0,Technology,2024-06-02,2024-06-26,913,9.9,DataVision Ltd +AI06758,Data Engineer,177463,USD,177463,SE,CT,Norway,L,Norway,50,"Kubernetes, Mathematics, NLP, TensorFlow, Computer Vision",PhD,7,Technology,2025-02-24,2025-04-13,849,5.5,Future Systems +AI06759,AI Architect,126055,SGD,163872,SE,PT,Singapore,L,Luxembourg,50,"PyTorch, Scala, Tableau",PhD,5,Education,2024-11-03,2024-12-26,1623,6.6,AI Innovations +AI06760,AI Consultant,41096,USD,41096,SE,PT,India,M,Japan,0,"Scala, Java, Docker, Deep Learning",Associate,7,Real Estate,2024-05-14,2024-07-13,629,8.5,Machine Intelligence Group +AI06761,Principal Data Scientist,141579,AUD,191132,EX,FL,Australia,S,Australia,100,"R, Kubernetes, NLP, SQL",Master,10,Energy,2024-07-28,2024-10-09,608,7.9,Advanced Robotics +AI06762,Principal Data Scientist,117805,CAD,147256,EX,PT,Canada,S,Israel,50,"Python, Scala, MLOps, Linux",Associate,17,Media,2024-04-12,2024-06-08,1141,8.5,Advanced Robotics +AI06763,ML Ops Engineer,76368,USD,76368,SE,FT,China,L,Portugal,50,"Computer Vision, Java, Kubernetes, MLOps, Deep Learning",Bachelor,6,Healthcare,2024-07-06,2024-09-11,2307,9.9,TechCorp Inc +AI06764,NLP Engineer,66318,USD,66318,EN,FL,South Korea,M,Finland,0,"Hadoop, SQL, Computer Vision",Associate,1,Technology,2024-09-28,2024-12-07,548,5.5,Neural Networks Co +AI06765,AI Research Scientist,170692,USD,170692,EX,CT,Ireland,S,Ireland,0,"GCP, AWS, Deep Learning, PyTorch",PhD,15,Transportation,2024-05-15,2024-07-16,706,6.8,Machine Intelligence Group +AI06766,Computer Vision Engineer,289060,SGD,375778,EX,FL,Singapore,L,Singapore,0,"SQL, Git, Computer Vision, Statistics",Master,15,Real Estate,2024-04-28,2024-06-17,2412,8.6,DataVision Ltd +AI06767,Data Analyst,120746,USD,120746,SE,CT,Sweden,S,Sweden,0,"PyTorch, Python, Deep Learning, GCP, NLP",Associate,9,Technology,2024-12-21,2025-01-06,2167,5.5,Machine Intelligence Group +AI06768,Principal Data Scientist,97475,JPY,10722250,MI,FT,Japan,S,Japan,0,"Java, Kubernetes, SQL, Python",Bachelor,4,Finance,2025-01-02,2025-03-11,627,6.8,DataVision Ltd +AI06769,Computer Vision Engineer,228776,USD,228776,EX,FL,Israel,M,Israel,100,"TensorFlow, Python, Scala, Java",Bachelor,18,Manufacturing,2024-04-15,2024-06-22,1406,5.1,Digital Transformation LLC +AI06770,AI Specialist,224210,CAD,280263,EX,FL,Canada,M,Canada,100,"Statistics, Spark, Python, PyTorch",PhD,10,Manufacturing,2024-07-13,2024-09-02,1369,8.2,Quantum Computing Inc +AI06771,Head of AI,71016,USD,71016,EN,CT,Finland,L,Finland,50,"Git, Linux, Tableau",Master,0,Energy,2024-08-26,2024-10-26,2128,5.4,DataVision Ltd +AI06772,AI Product Manager,157055,USD,157055,MI,FT,Norway,L,Latvia,50,"PyTorch, Kubernetes, Statistics",Master,4,Energy,2024-02-13,2024-03-07,679,6.4,Digital Transformation LLC +AI06773,AI Specialist,78910,USD,78910,MI,FL,Israel,S,Latvia,0,"Azure, Deep Learning, Computer Vision",Associate,4,Telecommunications,2025-02-26,2025-04-19,913,5.8,DataVision Ltd +AI06774,AI Product Manager,133220,USD,133220,EX,FT,Finland,S,Estonia,50,"Hadoop, Docker, NLP, Git, PyTorch",PhD,10,Government,2024-02-16,2024-03-28,960,5.1,Quantum Computing Inc +AI06775,Machine Learning Engineer,102537,EUR,87156,MI,FL,France,M,France,100,"Spark, Java, Mathematics",Bachelor,3,Gaming,2025-02-27,2025-04-25,2295,7.7,Cognitive Computing +AI06776,Autonomous Systems Engineer,95026,USD,95026,EN,FT,United States,L,Latvia,50,"Git, Python, Azure",Master,0,Real Estate,2024-06-02,2024-07-14,968,8.4,Neural Networks Co +AI06777,AI Research Scientist,163095,USD,163095,EX,FT,Finland,L,Finland,50,"Git, AWS, MLOps, Statistics",Bachelor,17,Retail,2024-02-15,2024-03-01,1932,8,Algorithmic Solutions +AI06778,Data Scientist,86115,JPY,9472650,MI,FT,Japan,S,Japan,50,"R, Spark, Linux, Data Visualization",Associate,2,Education,2024-10-15,2024-11-03,2194,6.4,Cloud AI Solutions +AI06779,Robotics Engineer,81518,EUR,69290,MI,PT,France,S,France,50,"Computer Vision, Docker, Azure",PhD,2,Finance,2024-03-26,2024-04-23,724,5.6,Autonomous Tech +AI06780,Head of AI,112582,EUR,95695,SE,PT,Austria,S,Austria,100,"Spark, AWS, Docker",PhD,5,Media,2025-01-11,2025-03-09,569,5.7,Digital Transformation LLC +AI06781,Data Engineer,179222,USD,179222,SE,PT,Norway,L,Argentina,100,"Spark, Statistics, PyTorch, SQL, TensorFlow",PhD,8,Retail,2024-03-07,2024-05-02,619,7.4,Algorithmic Solutions +AI06782,AI Research Scientist,267085,CHF,240377,EX,FL,Switzerland,L,Argentina,0,"AWS, PyTorch, Statistics",PhD,14,Transportation,2024-11-18,2025-01-06,591,6.7,DeepTech Ventures +AI06783,AI Specialist,72647,USD,72647,EN,FL,South Korea,L,Estonia,50,"Azure, Spark, Scala, Linux",Bachelor,0,Manufacturing,2024-07-03,2024-07-21,2440,8,Algorithmic Solutions +AI06784,Principal Data Scientist,157364,SGD,204573,EX,CT,Singapore,M,Singapore,0,"Azure, MLOps, Data Visualization, Hadoop",Bachelor,18,Finance,2024-01-23,2024-03-16,2250,9.9,Future Systems +AI06785,Research Scientist,147887,GBP,110915,SE,PT,United Kingdom,L,Chile,100,"Linux, Spark, NLP, Python",Bachelor,7,Education,2024-09-22,2024-11-26,1467,9.6,Advanced Robotics +AI06786,AI Specialist,93908,JPY,10329880,MI,PT,Japan,L,Japan,0,"Hadoop, Deep Learning, Java, Kubernetes",Bachelor,4,Technology,2025-03-28,2025-05-27,1495,6.4,DataVision Ltd +AI06787,Data Scientist,221005,USD,221005,SE,FL,Norway,L,New Zealand,0,"SQL, NLP, Statistics, Deep Learning, R",Associate,9,Energy,2024-07-11,2024-08-06,1072,6.3,Neural Networks Co +AI06788,AI Consultant,188472,USD,188472,SE,FL,Denmark,M,Denmark,0,"Git, AWS, Mathematics, NLP",PhD,8,Finance,2024-04-16,2024-06-13,769,8,DataVision Ltd +AI06789,AI Research Scientist,134644,USD,134644,SE,FL,South Korea,L,South Korea,100,"Scala, TensorFlow, Kubernetes, Statistics, R",PhD,9,Real Estate,2024-10-22,2024-12-15,1688,7.9,DataVision Ltd +AI06790,ML Ops Engineer,158617,AUD,214133,EX,CT,Australia,L,Australia,50,"Python, AWS, TensorFlow",Bachelor,11,Healthcare,2024-06-16,2024-08-11,2165,8.6,Quantum Computing Inc +AI06791,ML Ops Engineer,80635,USD,80635,MI,FT,Israel,L,Canada,50,"Spark, Azure, Data Visualization, Computer Vision",PhD,3,Consulting,2024-12-26,2025-01-23,2490,9.8,Predictive Systems +AI06792,Machine Learning Researcher,186187,SGD,242043,EX,PT,Singapore,M,Singapore,50,"Computer Vision, Git, Python, Deep Learning",Associate,18,Technology,2025-02-26,2025-04-05,1822,5.2,Machine Intelligence Group +AI06793,Computer Vision Engineer,101105,EUR,85939,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP",Bachelor,4,Real Estate,2024-01-19,2024-03-25,888,9.7,Machine Intelligence Group +AI06794,Data Scientist,178163,USD,178163,EX,FT,Ireland,L,Ireland,0,"GCP, TensorFlow, Linux",PhD,15,Manufacturing,2024-06-04,2024-08-07,979,8.8,Cloud AI Solutions +AI06795,ML Ops Engineer,63735,EUR,54175,EN,PT,France,L,France,0,"SQL, PyTorch, Data Visualization",Master,0,Healthcare,2024-05-04,2024-06-12,2161,9.4,Autonomous Tech +AI06796,AI Consultant,148327,CHF,133494,MI,FL,Switzerland,M,Canada,0,"Azure, Scala, Linux",Master,3,Energy,2024-03-23,2024-04-07,1743,8.7,Algorithmic Solutions +AI06797,Computer Vision Engineer,70092,USD,70092,MI,PT,Finland,S,Chile,100,"Java, SQL, Tableau",Bachelor,2,Technology,2025-01-23,2025-03-03,899,5.8,Cognitive Computing +AI06798,AI Research Scientist,168805,USD,168805,SE,PT,Sweden,L,Sweden,50,"AWS, SQL, Data Visualization, Computer Vision",Bachelor,5,Energy,2024-05-07,2024-06-08,1562,10,Algorithmic Solutions +AI06799,AI Product Manager,167702,CAD,209628,EX,PT,Canada,S,Germany,50,"Python, MLOps, TensorFlow, NLP",Associate,16,Gaming,2024-06-26,2024-08-11,1409,9.6,TechCorp Inc +AI06800,Robotics Engineer,77196,EUR,65617,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Spark, Computer Vision, SQL, GCP",Master,3,Energy,2025-01-17,2025-02-05,566,9.7,Quantum Computing Inc +AI06801,AI Product Manager,60668,EUR,51568,EN,FL,Austria,M,Austria,0,"Python, Java, NLP, Azure",Bachelor,0,Telecommunications,2024-07-03,2024-07-22,934,8.5,Autonomous Tech +AI06802,Machine Learning Researcher,238168,AUD,321527,EX,FL,Australia,L,Australia,0,"SQL, Git, Deep Learning",Master,14,Energy,2024-04-05,2024-05-07,1426,7.2,Cognitive Computing +AI06803,Principal Data Scientist,80987,SGD,105283,MI,PT,Singapore,S,Singapore,0,"SQL, Git, NLP, Deep Learning",Bachelor,4,Manufacturing,2024-12-08,2025-02-11,1153,8.3,Autonomous Tech +AI06804,Autonomous Systems Engineer,58908,USD,58908,EN,FL,United States,S,Hungary,100,"PyTorch, TensorFlow, R",Bachelor,1,Gaming,2024-02-06,2024-04-08,1768,5.7,Algorithmic Solutions +AI06805,Machine Learning Engineer,56978,GBP,42734,EN,PT,United Kingdom,S,United Kingdom,0,"NLP, Spark, Python, Hadoop",PhD,1,Manufacturing,2025-01-16,2025-02-20,1809,6.3,Algorithmic Solutions +AI06806,Autonomous Systems Engineer,149583,USD,149583,EX,PT,Israel,M,Israel,50,"TensorFlow, Azure, PyTorch",Master,12,Manufacturing,2024-08-16,2024-10-27,1499,9.5,Digital Transformation LLC +AI06807,Robotics Engineer,275970,USD,275970,EX,CT,Ireland,L,Ireland,50,"Tableau, Scala, R",Bachelor,16,Real Estate,2025-02-18,2025-04-26,2306,5.3,Autonomous Tech +AI06808,Head of AI,154006,EUR,130905,EX,CT,Germany,M,Germany,100,"TensorFlow, Hadoop, AWS, SQL",PhD,12,Energy,2024-07-26,2024-08-17,1303,7.7,Advanced Robotics +AI06809,Principal Data Scientist,131751,JPY,14492610,MI,FT,Japan,L,Japan,0,"Kubernetes, Python, R",Master,4,Automotive,2024-11-12,2024-12-29,2127,6.3,Future Systems +AI06810,Robotics Engineer,163158,JPY,17947380,SE,FL,Japan,L,Mexico,50,"Mathematics, Tableau, Kubernetes",Master,7,Transportation,2024-01-27,2024-03-08,885,6.8,Digital Transformation LLC +AI06811,Principal Data Scientist,52986,USD,52986,EN,PT,Sweden,M,Thailand,0,"SQL, Hadoop, MLOps",Associate,1,Real Estate,2024-09-08,2024-10-02,1605,5.5,Digital Transformation LLC +AI06812,NLP Engineer,326359,CHF,293723,EX,PT,Switzerland,L,Switzerland,0,"Linux, Python, Data Visualization, Computer Vision, Scala",Bachelor,11,Government,2024-05-27,2024-07-26,904,6.1,Cognitive Computing +AI06813,NLP Engineer,78523,USD,78523,EN,FT,Israel,L,United States,100,"Deep Learning, PyTorch, SQL",Associate,1,Technology,2024-10-13,2024-11-24,1039,5.8,AI Innovations +AI06814,NLP Engineer,104203,SGD,135464,MI,FL,Singapore,M,Singapore,100,"Statistics, Python, NLP, Spark, Data Visualization",Bachelor,4,Government,2024-03-19,2024-05-01,937,8,AI Innovations +AI06815,Data Engineer,39561,USD,39561,SE,PT,India,S,India,100,"TensorFlow, Git, Data Visualization",PhD,9,Automotive,2024-08-04,2024-09-18,1448,7.4,Predictive Systems +AI06816,AI Research Scientist,80731,EUR,68621,EN,PT,Austria,L,Austria,100,"Kubernetes, GCP, Java",Bachelor,0,Education,2024-02-07,2024-04-19,2243,9.4,Advanced Robotics +AI06817,Research Scientist,138085,EUR,117372,EX,FT,Austria,M,Austria,100,"SQL, NLP, Kubernetes, R",Associate,14,Transportation,2024-08-10,2024-09-30,875,5.5,Advanced Robotics +AI06818,ML Ops Engineer,77251,GBP,57938,EN,PT,United Kingdom,M,United Kingdom,50,"Data Visualization, Tableau, Python, TensorFlow, Linux",Master,0,Finance,2024-05-02,2024-06-08,1189,7.5,Future Systems +AI06819,Data Engineer,82330,JPY,9056300,EN,CT,Japan,L,Brazil,0,"Azure, PyTorch, Tableau, Data Visualization, Scala",PhD,0,Media,2024-11-10,2025-01-06,988,7.9,Neural Networks Co +AI06820,Data Engineer,78143,EUR,66422,EN,FT,Netherlands,L,India,0,"PyTorch, Hadoop, Tableau, MLOps",PhD,0,Consulting,2024-01-05,2024-03-12,1227,7.5,Algorithmic Solutions +AI06821,Computer Vision Engineer,143711,USD,143711,SE,PT,Israel,M,Israel,100,"Computer Vision, GCP, Statistics, Python, Mathematics",Bachelor,8,Finance,2025-03-22,2025-05-08,1997,7.8,Neural Networks Co +AI06822,Autonomous Systems Engineer,33586,USD,33586,EN,FL,China,S,China,0,"PyTorch, Computer Vision, Linux, Deep Learning, NLP",Bachelor,0,Retail,2024-05-27,2024-07-23,942,7.2,Algorithmic Solutions +AI06823,Research Scientist,22293,USD,22293,EN,FL,India,L,India,50,"SQL, MLOps, PyTorch",PhD,1,Gaming,2024-07-14,2024-09-22,753,8.4,DeepTech Ventures +AI06824,ML Ops Engineer,98076,JPY,10788360,MI,CT,Japan,L,Japan,0,"Docker, Kubernetes, Data Visualization, TensorFlow, Azure",Master,4,Media,2025-04-22,2025-06-27,1933,7.9,Cloud AI Solutions +AI06825,Machine Learning Engineer,98006,EUR,83305,SE,FL,Netherlands,S,Netherlands,100,"SQL, Spark, PyTorch, R, TensorFlow",Bachelor,5,Consulting,2024-03-24,2024-04-14,1977,8.6,Autonomous Tech +AI06826,Data Scientist,66357,USD,66357,EN,FL,South Korea,M,New Zealand,100,"Java, SQL, Tableau",Associate,1,Gaming,2024-08-31,2024-09-16,2478,8.7,DeepTech Ventures +AI06827,AI Architect,193061,CHF,173755,SE,PT,Switzerland,L,Romania,50,"Computer Vision, Statistics, MLOps, NLP, Kubernetes",Master,5,Finance,2024-08-18,2024-10-16,1911,5.8,Autonomous Tech +AI06828,AI Software Engineer,220816,USD,220816,EX,CT,Sweden,M,Sweden,100,"AWS, Hadoop, Deep Learning",PhD,16,Transportation,2024-10-03,2024-11-03,610,5.9,Predictive Systems +AI06829,AI Software Engineer,130692,USD,130692,SE,FL,Sweden,L,Sweden,0,"Python, Linux, Tableau, Java, NLP",Master,9,Finance,2024-12-28,2025-03-08,1297,9.7,Algorithmic Solutions +AI06830,Machine Learning Researcher,207792,CHF,187013,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, SQL, Java",Associate,9,Gaming,2024-06-17,2024-08-10,1818,6.8,Advanced Robotics +AI06831,Data Scientist,65685,USD,65685,EN,PT,United States,S,United States,100,"Azure, SQL, NLP, Python",Master,1,Consulting,2024-01-01,2024-03-10,1366,9.2,Neural Networks Co +AI06832,AI Architect,125757,EUR,106893,SE,CT,Germany,L,Germany,0,"PyTorch, Computer Vision, GCP, Linux",Associate,6,Real Estate,2025-03-02,2025-04-24,1445,6.4,Quantum Computing Inc +AI06833,Head of AI,85426,EUR,72612,EN,CT,Netherlands,L,Netherlands,50,"Java, Python, Tableau",PhD,0,Real Estate,2024-03-22,2024-04-16,551,8.8,Autonomous Tech +AI06834,AI Specialist,25694,USD,25694,EN,FT,India,L,India,100,"AWS, Hadoop, NLP, Java",Bachelor,1,Technology,2025-02-10,2025-03-30,2280,8.3,Algorithmic Solutions +AI06835,Deep Learning Engineer,175415,CHF,157874,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, SQL, Azure",PhD,8,Telecommunications,2025-02-18,2025-03-09,1460,8.6,Neural Networks Co +AI06836,AI Product Manager,123361,USD,123361,SE,PT,Sweden,S,Estonia,50,"Spark, Python, Computer Vision, Kubernetes",Master,5,Consulting,2024-10-15,2024-10-30,1859,6.3,Quantum Computing Inc +AI06837,Robotics Engineer,158738,JPY,17461180,EX,FT,Japan,S,Japan,50,"Docker, Deep Learning, Scala, Spark",PhD,14,Media,2024-04-04,2024-05-13,1906,6,Digital Transformation LLC +AI06838,AI Research Scientist,83310,EUR,70814,EN,PT,Netherlands,L,Netherlands,50,"Linux, Statistics, TensorFlow",Master,0,Gaming,2025-02-04,2025-03-26,1650,10,DeepTech Ventures +AI06839,AI Architect,90940,EUR,77299,MI,FT,Germany,L,Germany,0,"Hadoop, Python, Deep Learning",PhD,3,Finance,2024-06-06,2024-07-03,2371,7,Neural Networks Co +AI06840,Principal Data Scientist,78709,USD,78709,EN,FL,Finland,L,Finland,50,"Tableau, Python, Scala",Master,1,Automotive,2024-10-08,2024-10-28,505,8,Predictive Systems +AI06841,Principal Data Scientist,23429,USD,23429,MI,CT,India,S,India,50,"Python, Azure, Deep Learning, Java, Scala",Bachelor,3,Media,2025-01-26,2025-03-18,2362,9,Autonomous Tech +AI06842,Data Scientist,56096,USD,56096,SE,PT,China,L,France,50,"Deep Learning, Python, Data Visualization, Statistics, Linux",Bachelor,5,Media,2024-05-20,2024-06-07,1141,6.5,Algorithmic Solutions +AI06843,Machine Learning Researcher,79608,USD,79608,MI,FL,South Korea,S,South Korea,100,"GCP, Linux, NLP, Data Visualization, Mathematics",Associate,2,Finance,2024-04-11,2024-05-28,1325,8,Neural Networks Co +AI06844,ML Ops Engineer,62288,USD,62288,EN,FL,Finland,M,Finland,100,"Spark, Scala, GCP",Bachelor,1,Government,2025-01-05,2025-01-29,1712,7.1,Quantum Computing Inc +AI06845,NLP Engineer,231007,AUD,311859,EX,FL,Australia,L,Australia,0,"TensorFlow, Linux, PyTorch, Spark, SQL",Bachelor,15,Automotive,2024-03-26,2024-05-04,1826,8.5,Digital Transformation LLC +AI06846,Principal Data Scientist,100308,USD,100308,EN,FT,United States,L,Australia,100,"Computer Vision, Scala, MLOps, NLP",Master,0,Energy,2024-03-18,2024-04-05,2263,9.2,TechCorp Inc +AI06847,AI Consultant,106652,EUR,90654,MI,PT,Austria,L,Austria,100,"Python, Hadoop, Linux, TensorFlow",PhD,4,Transportation,2025-01-24,2025-03-04,897,9.5,Cognitive Computing +AI06848,Research Scientist,75358,USD,75358,MI,FL,South Korea,M,South Korea,100,"Data Visualization, Python, TensorFlow, Git, Computer Vision",PhD,4,Retail,2024-07-22,2024-09-30,2175,7.9,Autonomous Tech +AI06849,ML Ops Engineer,20791,USD,20791,EN,FL,India,S,India,0,"Computer Vision, MLOps, Data Visualization",Bachelor,0,Automotive,2025-02-22,2025-04-20,946,6.2,Autonomous Tech +AI06850,Principal Data Scientist,97537,EUR,82906,SE,FL,Germany,S,Germany,100,"Deep Learning, Computer Vision, Azure",Associate,6,Gaming,2024-11-09,2025-01-11,704,5.2,Cloud AI Solutions +AI06851,Autonomous Systems Engineer,137228,AUD,185258,SE,CT,Australia,S,Australia,0,"Computer Vision, Azure, AWS",Master,7,Healthcare,2024-03-29,2024-05-14,2399,8.3,DeepTech Ventures +AI06852,AI Consultant,130679,AUD,176417,EX,FL,Australia,S,France,100,"Hadoop, Data Visualization, Python",PhD,19,Telecommunications,2024-05-03,2024-07-06,2270,7.7,Cloud AI Solutions +AI06853,Research Scientist,212506,EUR,180630,EX,CT,Germany,M,Indonesia,50,"Scala, SQL, Linux, AWS",Bachelor,11,Media,2024-05-10,2024-07-13,2220,5.3,Quantum Computing Inc +AI06854,AI Research Scientist,107510,CHF,96759,EN,PT,Switzerland,M,Romania,0,"Kubernetes, MLOps, Docker, AWS",PhD,0,Energy,2024-12-06,2024-12-20,1845,9.5,Algorithmic Solutions +AI06855,Autonomous Systems Engineer,75716,EUR,64359,EN,FL,France,L,Indonesia,100,"SQL, Hadoop, PyTorch",Associate,0,Government,2024-04-30,2024-06-08,2217,5,Autonomous Tech +AI06856,AI Software Engineer,86830,EUR,73806,SE,CT,France,S,France,100,"Statistics, AWS, R, GCP, Azure",Master,6,Automotive,2024-07-14,2024-08-18,1611,5.3,Cognitive Computing +AI06857,Research Scientist,148673,USD,148673,SE,FL,Norway,S,Hungary,100,"Data Visualization, Spark, Python",Bachelor,6,Automotive,2024-07-03,2024-07-19,1209,7.6,Cognitive Computing +AI06858,Data Analyst,128336,USD,128336,EX,FT,Israel,M,Israel,0,"Python, TensorFlow, Mathematics",Associate,18,Gaming,2024-01-08,2024-02-08,1804,5.6,Smart Analytics +AI06859,Data Scientist,281503,USD,281503,EX,CT,United States,M,United States,0,"Deep Learning, GCP, Statistics, Kubernetes, PyTorch",PhD,11,Gaming,2024-11-17,2024-12-02,1099,6.8,Future Systems +AI06860,Robotics Engineer,59139,EUR,50268,EN,CT,Austria,S,Austria,50,"R, MLOps, Azure, NLP, Linux",Associate,1,Finance,2024-10-10,2024-11-25,685,7.9,Algorithmic Solutions +AI06861,Data Engineer,76076,AUD,102703,EN,PT,Australia,L,Australia,0,"TensorFlow, Docker, Kubernetes",Master,1,Energy,2025-01-16,2025-02-11,544,8.6,DataVision Ltd +AI06862,Deep Learning Engineer,116557,USD,116557,SE,FT,South Korea,M,South Korea,50,"Git, SQL, PyTorch",Master,7,Energy,2024-11-26,2025-01-18,1024,9.1,DataVision Ltd +AI06863,Research Scientist,153326,USD,153326,SE,CT,Israel,L,Israel,0,"Data Visualization, Deep Learning, MLOps, Python",Associate,9,Automotive,2024-04-30,2024-06-25,1225,5.5,Cognitive Computing +AI06864,Principal Data Scientist,145710,CHF,131139,SE,FT,Switzerland,S,Finland,100,"Hadoop, GCP, Linux, Kubernetes",Bachelor,7,Consulting,2024-11-06,2024-11-30,1025,6.8,Cloud AI Solutions +AI06865,AI Software Engineer,208806,EUR,177485,EX,FT,Netherlands,L,Poland,100,"Tableau, Scala, Python",Associate,15,Education,2024-09-03,2024-10-09,833,8.3,Digital Transformation LLC +AI06866,Robotics Engineer,59495,USD,59495,EN,FL,Norway,S,Norway,100,"Statistics, GCP, Computer Vision",PhD,1,Consulting,2024-06-27,2024-08-16,2122,8.7,Smart Analytics +AI06867,Research Scientist,161310,AUD,217769,EX,PT,Australia,M,Australia,50,"Deep Learning, Computer Vision, Data Visualization",PhD,12,Technology,2024-12-09,2025-01-05,2010,8.5,Quantum Computing Inc +AI06868,Research Scientist,63732,EUR,54172,EN,FT,Austria,M,China,100,"Spark, Python, Docker, TensorFlow",PhD,1,Manufacturing,2025-03-19,2025-04-08,2143,8.2,DataVision Ltd +AI06869,Data Analyst,144081,USD,144081,SE,PT,Sweden,M,Sweden,0,"Docker, TensorFlow, GCP",Master,6,Telecommunications,2024-10-15,2024-11-12,1553,8.2,Cloud AI Solutions +AI06870,Computer Vision Engineer,81528,USD,81528,MI,FT,South Korea,L,South Korea,50,"Python, Java, Mathematics, Linux",PhD,4,Telecommunications,2024-03-26,2024-04-28,605,6.9,DataVision Ltd +AI06871,Machine Learning Researcher,23844,USD,23844,EN,FL,India,L,India,0,"GCP, AWS, Data Visualization, Statistics, Spark",Bachelor,1,Automotive,2024-08-23,2024-09-25,2315,6.8,Machine Intelligence Group +AI06872,Deep Learning Engineer,46652,USD,46652,MI,CT,China,M,China,100,"Spark, Scala, Git, NLP, Hadoop",PhD,2,Government,2024-06-21,2024-08-28,632,6.8,Quantum Computing Inc +AI06873,Robotics Engineer,63871,USD,63871,MI,CT,Finland,S,Finland,100,"PyTorch, Statistics, Kubernetes",Master,3,Finance,2025-03-13,2025-05-09,2415,7.8,AI Innovations +AI06874,Head of AI,86503,USD,86503,MI,PT,Ireland,M,Ireland,0,"Python, TensorFlow, Computer Vision",Master,2,Transportation,2025-01-16,2025-02-07,1848,6,Machine Intelligence Group +AI06875,Data Engineer,68882,AUD,92991,EN,CT,Australia,M,Australia,100,"Hadoop, Deep Learning, Spark, PyTorch, Statistics",Associate,0,Transportation,2024-08-30,2024-10-11,2401,5.3,Future Systems +AI06876,ML Ops Engineer,120496,EUR,102422,SE,FT,Germany,S,Germany,0,"Data Visualization, Mathematics, R",Master,6,Automotive,2024-12-31,2025-01-26,2097,7,Machine Intelligence Group +AI06877,Data Scientist,67737,EUR,57576,EN,FL,Germany,S,Denmark,50,"Linux, Data Visualization, Docker",Bachelor,0,Consulting,2024-01-31,2024-03-30,1686,7.3,Cloud AI Solutions +AI06878,Head of AI,58637,EUR,49841,EN,FL,Netherlands,S,Thailand,50,"Statistics, Computer Vision, NLP, Git, Kubernetes",Master,1,Technology,2024-06-29,2024-09-04,540,10,Neural Networks Co +AI06879,AI Specialist,130820,EUR,111197,SE,FL,Austria,M,Sweden,0,"Computer Vision, SQL, Statistics, Git",Associate,7,Healthcare,2024-06-24,2024-08-22,913,9.1,Digital Transformation LLC +AI06880,Deep Learning Engineer,101122,USD,101122,MI,CT,Sweden,M,Sweden,0,"Git, Kubernetes, SQL",PhD,3,Automotive,2024-11-20,2025-01-11,1832,7,DeepTech Ventures +AI06881,AI Architect,130892,USD,130892,SE,PT,Finland,L,Finland,0,"Git, R, TensorFlow, Python, PyTorch",PhD,6,Real Estate,2024-07-07,2024-08-29,2367,5.1,Smart Analytics +AI06882,AI Product Manager,26937,USD,26937,EN,CT,India,L,Portugal,0,"R, AWS, Python, Mathematics",Associate,1,Government,2025-04-30,2025-05-25,1341,9.1,Smart Analytics +AI06883,AI Research Scientist,90590,GBP,67943,MI,FT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Azure, Hadoop",Master,3,Real Estate,2024-05-27,2024-08-03,1264,6.8,Quantum Computing Inc +AI06884,AI Consultant,121858,USD,121858,SE,FT,Sweden,S,Sweden,50,"Kubernetes, PyTorch, Statistics, R, Java",Associate,7,Manufacturing,2024-02-09,2024-02-23,1435,6.9,Cognitive Computing +AI06885,Research Scientist,102740,EUR,87329,SE,CT,Netherlands,S,Netherlands,100,"PyTorch, SQL, Linux, Statistics",Bachelor,8,Automotive,2024-05-29,2024-07-23,1550,8.3,DataVision Ltd +AI06886,Data Scientist,250788,USD,250788,EX,FL,Denmark,S,United States,0,"Spark, Tableau, Python, Scala, GCP",Bachelor,11,Consulting,2024-03-25,2024-05-26,626,6.3,DeepTech Ventures +AI06887,Research Scientist,45176,USD,45176,SE,FL,India,S,United Kingdom,0,"Python, Spark, NLP, Data Visualization",PhD,6,Gaming,2024-01-06,2024-01-25,1783,8.5,DeepTech Ventures +AI06888,AI Specialist,107442,USD,107442,SE,FT,South Korea,M,South Korea,0,"Mathematics, Kubernetes, Python, Docker, Data Visualization",Associate,7,Telecommunications,2024-04-22,2024-06-28,1030,5.7,Advanced Robotics +AI06889,Computer Vision Engineer,193572,EUR,164536,EX,FT,Austria,M,Singapore,0,"PyTorch, SQL, GCP",Associate,11,Healthcare,2024-12-13,2025-01-02,1285,6,Future Systems +AI06890,AI Consultant,93956,USD,93956,EX,PT,India,L,India,0,"Azure, PyTorch, TensorFlow, Docker, Git",Master,16,Automotive,2024-03-18,2024-04-07,1868,9.9,DataVision Ltd +AI06891,Autonomous Systems Engineer,77210,EUR,65629,EN,FT,Netherlands,M,Netherlands,0,"Data Visualization, Java, Linux",Associate,1,Technology,2024-08-21,2024-10-04,1539,6.8,Algorithmic Solutions +AI06892,AI Consultant,59058,USD,59058,EX,CT,India,L,Malaysia,50,"NLP, Kubernetes, PyTorch, Git, Tableau",Bachelor,12,Gaming,2024-06-20,2024-08-30,1756,9.9,DeepTech Ventures +AI06893,Machine Learning Researcher,285291,CHF,256762,EX,FT,Switzerland,M,Switzerland,50,"PyTorch, Linux, TensorFlow, Mathematics",Bachelor,12,Technology,2024-03-17,2024-04-25,2134,8.6,Digital Transformation LLC +AI06894,Data Analyst,92251,USD,92251,MI,FT,Sweden,S,Sweden,100,"Python, Tableau, Java, Statistics",PhD,3,Government,2024-09-25,2024-11-26,1721,5.4,Autonomous Tech +AI06895,Machine Learning Engineer,138851,CAD,173564,SE,PT,Canada,L,Canada,50,"Python, Azure, Statistics, Linux",Master,7,Manufacturing,2024-08-14,2024-10-03,2484,5.7,Cloud AI Solutions +AI06896,Deep Learning Engineer,208953,EUR,177610,EX,FT,Netherlands,S,Netherlands,0,"Git, Docker, Scala",PhD,12,Government,2024-02-16,2024-03-28,2051,9.4,Quantum Computing Inc +AI06897,NLP Engineer,187224,CHF,168502,SE,FT,Switzerland,M,Switzerland,100,"Git, Scala, Java",Bachelor,8,Healthcare,2025-02-15,2025-04-14,1158,9.9,Machine Intelligence Group +AI06898,Principal Data Scientist,266395,USD,266395,EX,PT,Sweden,L,Sweden,0,"SQL, Spark, PyTorch, Linux",Bachelor,12,Automotive,2024-03-05,2024-04-05,936,8.4,Smart Analytics +AI06899,AI Specialist,88761,USD,88761,MI,FT,Sweden,S,Brazil,0,"AWS, Linux, Deep Learning, Mathematics",Master,2,Media,2024-01-06,2024-01-28,2134,7.1,Predictive Systems +AI06900,Machine Learning Engineer,81928,USD,81928,EX,CT,China,M,China,50,"Git, Tableau, SQL, Mathematics, Kubernetes",Bachelor,10,Government,2024-08-05,2024-08-25,1453,9.6,Neural Networks Co +AI06901,Machine Learning Researcher,127931,SGD,166310,SE,CT,Singapore,L,Singapore,50,"MLOps, Python, Kubernetes",Master,7,Finance,2024-07-23,2024-10-02,1159,6.3,Predictive Systems +AI06902,Data Analyst,107379,CHF,96641,EN,FT,Switzerland,L,Switzerland,0,"R, Git, Tableau, Azure",Associate,0,Real Estate,2024-09-29,2024-11-23,890,8.2,Smart Analytics +AI06903,Principal Data Scientist,82295,USD,82295,SE,PT,China,L,China,0,"Java, Kubernetes, PyTorch, MLOps",Associate,9,Manufacturing,2024-11-29,2025-02-10,1560,8.6,Neural Networks Co +AI06904,AI Product Manager,91254,EUR,77566,MI,FL,Netherlands,M,Netherlands,100,"Python, Azure, Tableau, SQL",PhD,3,Consulting,2024-02-28,2024-04-28,1098,6.6,Smart Analytics +AI06905,Data Engineer,139532,USD,139532,MI,CT,Denmark,L,Italy,100,"Tableau, TensorFlow, Kubernetes",Associate,2,Telecommunications,2025-04-23,2025-05-19,1554,7.5,Predictive Systems +AI06906,Data Scientist,105160,JPY,11567600,MI,FT,Japan,L,Japan,50,"Scala, AWS, Data Visualization, NLP",Master,2,Energy,2024-03-16,2024-05-11,2229,5.2,Cognitive Computing +AI06907,Research Scientist,123788,JPY,13616680,MI,FT,Japan,L,Japan,100,"Python, SQL, Linux, Deep Learning, Mathematics",Master,3,Real Estate,2025-01-17,2025-02-01,651,8.2,TechCorp Inc +AI06908,Research Scientist,108313,EUR,92066,MI,FL,Netherlands,L,Netherlands,0,"PyTorch, SQL, Kubernetes, R",Bachelor,2,Manufacturing,2025-01-21,2025-02-27,2052,5.7,Predictive Systems +AI06909,Robotics Engineer,105151,USD,105151,SE,CT,Ireland,M,Ireland,50,"Git, TensorFlow, Tableau, SQL, Deep Learning",Bachelor,9,Government,2024-09-09,2024-10-11,1671,6.4,Neural Networks Co +AI06910,Principal Data Scientist,55680,USD,55680,EX,PT,India,M,India,50,"Computer Vision, Hadoop, Azure",Master,12,Manufacturing,2024-08-30,2024-09-17,1329,7.2,DataVision Ltd +AI06911,AI Consultant,141286,JPY,15541460,SE,FL,Japan,S,Japan,100,"Kubernetes, Git, Hadoop",Bachelor,6,Education,2024-06-10,2024-08-07,1364,9.3,TechCorp Inc +AI06912,Machine Learning Engineer,87004,CAD,108755,SE,PT,Canada,S,Norway,0,"Linux, Data Visualization, TensorFlow",Master,8,Retail,2024-09-02,2024-11-02,581,7.4,Advanced Robotics +AI06913,Data Analyst,101540,USD,101540,MI,FL,Sweden,M,India,0,"Linux, Python, R, Java",Master,3,Gaming,2024-12-25,2025-02-06,1662,5.5,Autonomous Tech +AI06914,Research Scientist,176009,USD,176009,SE,PT,Norway,L,Norway,50,"Azure, Java, Scala, Kubernetes",Associate,6,Education,2024-06-02,2024-07-24,2272,6.3,Autonomous Tech +AI06915,Deep Learning Engineer,85561,GBP,64171,EN,PT,United Kingdom,L,Switzerland,50,"R, Kubernetes, Data Visualization",Bachelor,0,Healthcare,2024-12-18,2025-01-04,826,9.2,Smart Analytics +AI06916,Deep Learning Engineer,102426,USD,102426,MI,CT,Ireland,L,Ireland,50,"Computer Vision, Tableau, Linux",Master,3,Automotive,2024-10-13,2024-12-08,1346,8.4,AI Innovations +AI06917,Data Analyst,103962,USD,103962,EN,FT,Norway,L,Norway,0,"SQL, Java, Git, Deep Learning",Associate,1,Retail,2024-05-17,2024-06-20,1235,9.3,Cognitive Computing +AI06918,Head of AI,81801,USD,81801,MI,CT,Israel,M,Israel,50,"MLOps, Kubernetes, SQL, PyTorch",PhD,4,Real Estate,2024-11-03,2025-01-06,1081,6.7,AI Innovations +AI06919,Deep Learning Engineer,141646,USD,141646,SE,FL,Ireland,L,Ireland,0,"Java, SQL, MLOps, Azure",Associate,5,Automotive,2024-08-21,2024-10-11,1664,5.9,Digital Transformation LLC +AI06920,Machine Learning Engineer,197459,USD,197459,EX,CT,Israel,L,Israel,50,"Java, PyTorch, Tableau, Deep Learning",Master,12,Healthcare,2025-03-03,2025-03-23,1470,6.1,Quantum Computing Inc +AI06921,Deep Learning Engineer,86119,EUR,73201,MI,CT,Austria,L,Italy,0,"Azure, Python, Computer Vision, NLP, Tableau",PhD,2,Healthcare,2024-12-06,2024-12-31,665,9.6,Smart Analytics +AI06922,Autonomous Systems Engineer,54196,EUR,46067,EN,CT,Germany,S,Germany,50,"Kubernetes, Statistics, NLP, Azure",Master,1,Real Estate,2025-01-10,2025-02-27,1458,6.9,DataVision Ltd +AI06923,Machine Learning Engineer,83714,USD,83714,EN,FL,Denmark,M,France,100,"Hadoop, TensorFlow, Kubernetes, PyTorch, Git",PhD,1,Finance,2024-09-01,2024-09-25,1593,7,Future Systems +AI06924,Deep Learning Engineer,156483,GBP,117362,SE,CT,United Kingdom,M,United Kingdom,50,"Spark, Hadoop, Linux",Master,7,Technology,2024-10-10,2024-10-30,1052,7.2,TechCorp Inc +AI06925,AI Architect,147145,USD,147145,SE,FT,Norway,S,Norway,0,"Deep Learning, Python, Git, TensorFlow, AWS",PhD,8,Transportation,2024-12-30,2025-02-28,2183,5.1,Smart Analytics +AI06926,NLP Engineer,278709,EUR,236903,EX,FL,Netherlands,L,Brazil,50,"PyTorch, SQL, AWS, R, Java",Associate,18,Transportation,2025-01-24,2025-03-26,2323,6.1,Cloud AI Solutions +AI06927,Computer Vision Engineer,163345,EUR,138843,EX,PT,Austria,S,Austria,100,"Hadoop, Git, Python",Bachelor,14,Automotive,2024-07-23,2024-08-24,2230,9.2,Cloud AI Solutions +AI06928,AI Product Manager,97503,AUD,131629,SE,CT,Australia,S,Australia,50,"Deep Learning, Docker, Java, AWS",Bachelor,6,Manufacturing,2025-01-01,2025-01-20,2440,5.6,Quantum Computing Inc +AI06929,Machine Learning Researcher,173549,CHF,156194,SE,FL,Switzerland,L,Germany,50,"Kubernetes, Scala, Spark",Bachelor,9,Consulting,2025-01-20,2025-03-03,2076,8.6,Advanced Robotics +AI06930,AI Product Manager,229619,GBP,172214,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Hadoop, Java",Associate,18,Government,2025-01-19,2025-02-07,1585,9.7,DeepTech Ventures +AI06931,Computer Vision Engineer,197390,USD,197390,SE,PT,Denmark,M,Denmark,0,"GCP, MLOps, Git, Computer Vision, Java",Master,5,Government,2024-10-20,2024-12-21,1655,9.9,Digital Transformation LLC +AI06932,Computer Vision Engineer,53391,EUR,45382,EN,FL,Austria,S,Romania,50,"Kubernetes, Linux, Tableau, SQL, Statistics",Bachelor,0,Government,2024-11-17,2024-12-18,2141,6.9,Smart Analytics +AI06933,AI Software Engineer,70421,EUR,59858,MI,FL,France,S,Colombia,0,"SQL, Scala, NLP",Associate,3,Energy,2024-12-25,2025-02-04,2200,7.2,Digital Transformation LLC +AI06934,Machine Learning Engineer,82065,USD,82065,EN,PT,Sweden,L,Romania,0,"Docker, Java, Tableau, Hadoop, NLP",Bachelor,1,Automotive,2025-02-21,2025-04-23,1455,9.8,DataVision Ltd +AI06935,NLP Engineer,114605,USD,114605,SE,FL,Israel,L,Israel,0,"GCP, MLOps, R",Master,6,Gaming,2024-06-27,2024-08-24,1238,5.2,DeepTech Ventures +AI06936,AI Architect,209622,CAD,262028,EX,PT,Canada,M,Ireland,0,"Tableau, PyTorch, Kubernetes",Master,17,Manufacturing,2024-06-09,2024-07-10,1344,6.2,Neural Networks Co +AI06937,Computer Vision Engineer,159369,USD,159369,MI,PT,Denmark,L,Denmark,0,"TensorFlow, SQL, R",Bachelor,2,Education,2024-03-18,2024-05-10,1590,7.7,Cognitive Computing +AI06938,Head of AI,287596,USD,287596,EX,FT,Sweden,L,Sweden,0,"Hadoop, Linux, Docker, Data Visualization",Associate,11,Energy,2024-01-01,2024-02-18,714,9.1,Digital Transformation LLC +AI06939,AI Product Manager,145099,EUR,123334,SE,PT,Germany,L,Germany,100,"TensorFlow, Scala, Linux",Associate,5,Government,2024-04-29,2024-06-28,1557,6.3,Predictive Systems +AI06940,ML Ops Engineer,265723,EUR,225865,EX,PT,Germany,L,Germany,0,"Kubernetes, Mathematics, Data Visualization",Master,16,Real Estate,2025-04-30,2025-06-25,645,5.8,Advanced Robotics +AI06941,Data Scientist,146927,EUR,124888,SE,PT,Germany,L,Germany,0,"TensorFlow, Hadoop, Linux, AWS, Computer Vision",Bachelor,5,Healthcare,2024-01-14,2024-03-16,927,7.7,Advanced Robotics +AI06942,AI Research Scientist,55638,USD,55638,MI,CT,China,L,China,50,"Scala, GCP, Data Visualization, Computer Vision",Associate,2,Transportation,2025-01-09,2025-03-18,2069,7.5,Smart Analytics +AI06943,Head of AI,147236,USD,147236,SE,FT,Norway,M,Norway,100,"TensorFlow, Linux, Java",Bachelor,8,Automotive,2024-11-03,2024-12-23,1031,8.6,Advanced Robotics +AI06944,AI Research Scientist,195009,EUR,165758,EX,FL,France,S,New Zealand,100,"Java, Data Visualization, Python",PhD,18,Energy,2025-02-25,2025-05-07,2121,5.3,Advanced Robotics +AI06945,AI Consultant,75991,EUR,64592,EN,FL,France,L,France,50,"Git, SQL, Java",Bachelor,1,Transportation,2024-02-08,2024-03-13,550,8.8,Predictive Systems +AI06946,Research Scientist,188727,USD,188727,EX,CT,Ireland,M,Ireland,0,"Scala, R, PyTorch",Bachelor,12,Telecommunications,2025-01-23,2025-03-28,1066,8.6,Autonomous Tech +AI06947,Machine Learning Researcher,122620,USD,122620,MI,FT,Denmark,L,Denmark,0,"Kubernetes, Spark, Python, Tableau, Linux",Master,3,Consulting,2024-03-03,2024-05-10,1623,8.8,Predictive Systems +AI06948,Computer Vision Engineer,169343,USD,169343,SE,CT,Ireland,L,Hungary,0,"Mathematics, Git, Java",Bachelor,8,Gaming,2024-01-10,2024-03-05,630,7.5,Future Systems +AI06949,AI Architect,76731,CAD,95914,EN,FT,Canada,L,Canada,100,"Azure, Kubernetes, Git",Associate,0,Real Estate,2024-03-12,2024-04-19,1818,8.1,Machine Intelligence Group +AI06950,Machine Learning Researcher,257911,USD,257911,EX,FL,Ireland,L,Mexico,100,"Python, Kubernetes, AWS, Azure, GCP",Bachelor,10,Real Estate,2024-02-02,2024-02-19,1181,9.7,Smart Analytics +AI06951,Head of AI,163774,AUD,221095,EX,FT,Australia,S,Australia,50,"Computer Vision, R, Tableau",Associate,18,Transportation,2024-07-14,2024-08-29,1817,7.5,Cognitive Computing +AI06952,Computer Vision Engineer,31330,USD,31330,EN,FL,China,M,China,0,"R, Spark, Statistics",Master,1,Education,2024-09-25,2024-10-18,2401,10,TechCorp Inc +AI06953,Data Scientist,145202,USD,145202,SE,FT,Israel,L,Poland,0,"Spark, AWS, Deep Learning",Bachelor,6,Gaming,2025-04-21,2025-06-20,728,5,Autonomous Tech +AI06954,Robotics Engineer,89064,SGD,115783,EN,PT,Singapore,L,Singapore,100,"SQL, Python, Computer Vision, Deep Learning",Bachelor,0,Retail,2025-04-13,2025-05-21,1888,7.8,Algorithmic Solutions +AI06955,Data Analyst,132621,USD,132621,SE,PT,Finland,L,Finland,50,"Scala, Docker, Spark, Statistics",Master,7,Education,2025-02-03,2025-03-11,1598,7.3,Quantum Computing Inc +AI06956,NLP Engineer,84808,USD,84808,EN,CT,Sweden,L,Sweden,100,"SQL, NLP, Spark, Hadoop",Bachelor,0,Government,2024-01-04,2024-01-24,2408,8.7,Machine Intelligence Group +AI06957,AI Consultant,59952,USD,59952,EN,FT,Norway,S,Norway,100,"Kubernetes, NLP, Data Visualization",Associate,1,Media,2025-01-31,2025-04-13,1048,5.1,DataVision Ltd +AI06958,Deep Learning Engineer,100845,USD,100845,MI,FT,Finland,M,Germany,0,"TensorFlow, Mathematics, Java, Linux",Master,2,Media,2024-11-25,2024-12-31,1984,9.4,TechCorp Inc +AI06959,Machine Learning Engineer,98597,EUR,83807,MI,CT,Netherlands,M,Japan,100,"GCP, Scala, R",Bachelor,3,Retail,2024-12-24,2025-01-13,1549,8.5,Future Systems +AI06960,Data Engineer,142965,EUR,121520,SE,FT,Germany,M,Nigeria,0,"Kubernetes, Linux, Azure, GCP, Git",PhD,5,Automotive,2024-06-24,2024-08-13,2341,6.4,TechCorp Inc +AI06961,Machine Learning Researcher,84811,GBP,63608,EN,PT,United Kingdom,L,United Kingdom,100,"Tableau, MLOps, NLP, Linux",PhD,1,Retail,2024-08-10,2024-09-11,1114,6.6,Neural Networks Co +AI06962,AI Software Engineer,150732,USD,150732,SE,CT,Denmark,M,Italy,100,"MLOps, Git, GCP, R, Python",Associate,5,Automotive,2025-01-23,2025-02-20,1915,6.6,Cloud AI Solutions +AI06963,AI Research Scientist,146631,AUD,197952,SE,FT,Australia,M,Australia,50,"Scala, Data Visualization, Linux, SQL",Master,8,Gaming,2024-01-23,2024-03-01,1304,5.2,Digital Transformation LLC +AI06964,AI Consultant,87006,CAD,108758,EN,FT,Canada,L,Canada,100,"Docker, Statistics, Computer Vision, Linux, Deep Learning",PhD,1,Education,2024-11-20,2025-01-03,1023,7.8,Cognitive Computing +AI06965,ML Ops Engineer,93917,AUD,126788,SE,CT,Australia,S,France,100,"Git, Python, NLP",Master,5,Manufacturing,2024-06-17,2024-07-07,1248,9.7,Smart Analytics +AI06966,Data Analyst,168686,EUR,143383,EX,FL,Netherlands,S,Netherlands,50,"Statistics, Python, Git, Linux, SQL",Bachelor,12,Real Estate,2025-01-09,2025-02-01,2404,7.4,AI Innovations +AI06967,Research Scientist,128330,GBP,96248,SE,PT,United Kingdom,S,South Africa,50,"Azure, Mathematics, Kubernetes, Deep Learning",Associate,6,Gaming,2025-02-28,2025-05-05,1920,6.8,TechCorp Inc +AI06968,Data Engineer,111839,SGD,145391,SE,PT,Singapore,S,Singapore,50,"Scala, MLOps, Docker, Hadoop, Statistics",PhD,9,Retail,2024-03-02,2024-03-21,2328,7.3,Predictive Systems +AI06969,AI Software Engineer,187884,USD,187884,EX,PT,South Korea,L,Malaysia,50,"TensorFlow, SQL, Mathematics",Master,18,Consulting,2025-01-31,2025-03-09,675,9,AI Innovations +AI06970,AI Specialist,50117,USD,50117,MI,FT,China,M,China,0,"Python, AWS, Kubernetes, MLOps",Bachelor,4,Consulting,2024-05-19,2024-07-15,1362,6.3,Advanced Robotics +AI06971,Data Scientist,355672,CHF,320105,EX,CT,Switzerland,L,Philippines,0,"Tableau, SQL, Kubernetes, PyTorch",Master,16,Automotive,2025-04-25,2025-05-27,776,8.2,Machine Intelligence Group +AI06972,Deep Learning Engineer,114352,AUD,154375,MI,PT,Australia,L,Australia,0,"PyTorch, Scala, Azure, AWS, TensorFlow",Master,4,Gaming,2025-01-23,2025-03-12,2361,9.8,Quantum Computing Inc +AI06973,Data Engineer,167395,USD,167395,EX,CT,United States,M,United States,0,"Spark, Git, Computer Vision, Data Visualization",Bachelor,17,Retail,2024-02-18,2024-04-03,683,8.9,Cloud AI Solutions +AI06974,Autonomous Systems Engineer,172621,JPY,18988310,SE,PT,Japan,L,Japan,100,"Python, SQL, R",Associate,6,Energy,2025-04-30,2025-06-08,813,9.7,Algorithmic Solutions +AI06975,AI Architect,64356,USD,64356,MI,CT,Finland,S,Finland,100,"Deep Learning, MLOps, PyTorch, Tableau",Master,2,Finance,2024-11-09,2025-01-14,1866,6.1,Machine Intelligence Group +AI06976,Data Scientist,54970,USD,54970,EX,PT,India,M,Belgium,50,"SQL, TensorFlow, Linux, Tableau, Java",PhD,13,Transportation,2024-09-02,2024-10-04,821,7.6,Autonomous Tech +AI06977,Deep Learning Engineer,101375,CHF,91238,EN,CT,Switzerland,L,Switzerland,100,"R, PyTorch, Mathematics, Hadoop, Azure",Associate,1,Government,2025-02-09,2025-02-28,1818,7.6,Algorithmic Solutions +AI06978,Computer Vision Engineer,162080,USD,162080,EX,CT,Finland,S,Finland,50,"TensorFlow, Docker, Mathematics, Linux, AWS",PhD,11,Telecommunications,2025-01-01,2025-03-02,688,9.3,DataVision Ltd +AI06979,AI Product Manager,81146,USD,81146,SE,FT,South Korea,S,South Korea,100,"Tableau, Git, Docker, PyTorch, Data Visualization",Associate,5,Manufacturing,2024-05-31,2024-06-29,540,8.6,Quantum Computing Inc +AI06980,Autonomous Systems Engineer,144815,USD,144815,SE,PT,United States,S,United States,50,"R, NLP, Java",PhD,8,Transportation,2025-02-02,2025-02-23,1685,7.9,Future Systems +AI06981,ML Ops Engineer,145112,USD,145112,SE,FT,Ireland,M,Ireland,100,"Kubernetes, Git, Deep Learning, PyTorch, Docker",PhD,9,Transportation,2024-12-23,2025-02-09,1411,5.7,Digital Transformation LLC +AI06982,Principal Data Scientist,66759,USD,66759,EX,FL,China,S,China,100,"TensorFlow, Git, Azure, Spark",PhD,12,Finance,2024-11-29,2025-01-31,1327,9.9,Advanced Robotics +AI06983,Machine Learning Engineer,163174,EUR,138698,EX,PT,Germany,S,United Kingdom,100,"Linux, PyTorch, Git, Mathematics, Deep Learning",PhD,11,Energy,2024-05-04,2024-05-22,2045,5.1,AI Innovations +AI06984,Deep Learning Engineer,112919,CHF,101627,EN,CT,Switzerland,L,Switzerland,100,"R, SQL, Azure",Master,1,Transportation,2025-03-31,2025-06-10,625,6.7,Predictive Systems +AI06985,Principal Data Scientist,113118,SGD,147053,MI,PT,Singapore,M,Japan,50,"Git, Data Visualization, Scala, Azure, Kubernetes",Associate,4,Manufacturing,2024-02-20,2024-03-27,1777,8.6,Machine Intelligence Group +AI06986,Robotics Engineer,64270,USD,64270,EN,FL,Sweden,L,Sweden,0,"NLP, Git, Java",Associate,0,Healthcare,2024-07-19,2024-08-27,598,9.2,AI Innovations +AI06987,Deep Learning Engineer,167528,USD,167528,SE,CT,Denmark,M,Denmark,50,"Scala, Azure, Mathematics, PyTorch, Statistics",Master,5,Retail,2024-09-21,2024-10-11,1659,5.8,Smart Analytics +AI06988,ML Ops Engineer,82676,CAD,103345,MI,FL,Canada,S,Sweden,100,"Data Visualization, Spark, R, SQL",Master,4,Technology,2024-02-23,2024-03-21,1707,6.4,Cloud AI Solutions +AI06989,Computer Vision Engineer,148614,EUR,126322,SE,CT,Austria,L,Austria,50,"PyTorch, Kubernetes, Git",Associate,9,Gaming,2024-04-05,2024-05-24,1048,7.8,Autonomous Tech +AI06990,Machine Learning Engineer,75332,USD,75332,MI,CT,Finland,M,Australia,100,"TensorFlow, SQL, R, Deep Learning, NLP",Associate,3,Energy,2024-12-09,2025-01-18,2177,5.7,Quantum Computing Inc +AI06991,Head of AI,170124,CHF,153112,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, MLOps, Kubernetes, PyTorch, NLP",PhD,4,Consulting,2025-01-16,2025-03-25,2424,6.5,DataVision Ltd +AI06992,Principal Data Scientist,103653,USD,103653,MI,FT,Israel,M,Israel,0,"R, Git, Statistics",PhD,2,Automotive,2024-08-22,2024-09-26,1801,6.7,Future Systems +AI06993,AI Architect,30142,USD,30142,MI,FL,India,L,India,0,"TensorFlow, Git, SQL, Hadoop",Associate,4,Telecommunications,2025-01-27,2025-03-03,1476,7.8,Digital Transformation LLC +AI06994,Machine Learning Researcher,54940,USD,54940,EN,CT,South Korea,M,Brazil,100,"Git, R, Computer Vision, Java",Master,1,Government,2024-09-06,2024-09-30,2122,9.9,Machine Intelligence Group +AI06995,Principal Data Scientist,84125,USD,84125,MI,FL,United States,S,United States,0,"Hadoop, Linux, Data Visualization, Tableau",Master,3,Media,2024-05-24,2024-06-23,1222,7.4,Cloud AI Solutions +AI06996,NLP Engineer,221441,EUR,188225,EX,FT,France,L,Nigeria,100,"Git, SQL, Spark, Tableau, Kubernetes",Bachelor,19,Media,2024-11-02,2025-01-11,1718,5.9,Future Systems +AI06997,AI Software Engineer,64993,EUR,55244,EN,FT,Netherlands,S,Hungary,0,"Git, Java, Kubernetes",Bachelor,0,Media,2024-01-23,2024-03-24,2180,5.8,Future Systems +AI06998,Research Scientist,114387,CAD,142984,MI,FL,Canada,L,Canada,100,"Java, Scala, Tableau, NLP",Associate,2,Retail,2024-09-04,2024-10-21,2379,5.8,Quantum Computing Inc +AI06999,Data Analyst,87162,SGD,113311,EN,PT,Singapore,L,Luxembourg,50,"GCP, PyTorch, Python",Master,1,Gaming,2024-08-04,2024-09-10,2232,8.4,Autonomous Tech +AI07000,Head of AI,117970,USD,117970,MI,FL,United States,L,Philippines,100,"Mathematics, Java, Python",Bachelor,2,Finance,2024-03-27,2024-04-27,2075,5.6,AI Innovations +AI07001,AI Research Scientist,111336,USD,111336,SE,CT,Ireland,S,Ireland,0,"Tableau, TensorFlow, Scala, Git, Azure",PhD,7,Telecommunications,2024-03-14,2024-05-02,1486,5.5,Algorithmic Solutions +AI07002,Machine Learning Researcher,86134,GBP,64601,MI,FL,United Kingdom,S,United Kingdom,0,"TensorFlow, AWS, Azure",Associate,4,Energy,2024-10-31,2024-11-26,2104,6.7,Neural Networks Co +AI07003,Data Engineer,159132,USD,159132,EX,CT,Finland,M,Finland,50,"R, MLOps, SQL",PhD,18,Manufacturing,2024-08-31,2024-10-04,1832,9,DataVision Ltd +AI07004,Autonomous Systems Engineer,88313,USD,88313,EN,CT,United States,M,United States,0,"PyTorch, TensorFlow, Azure, AWS",Associate,1,Telecommunications,2024-12-10,2025-02-12,2142,7.1,DeepTech Ventures +AI07005,AI Product Manager,147619,USD,147619,EX,FL,United States,S,United States,0,"Java, SQL, Hadoop, Git, GCP",Associate,17,Education,2024-06-29,2024-07-15,1756,5.6,Quantum Computing Inc +AI07006,Machine Learning Engineer,41968,USD,41968,MI,CT,India,L,India,50,"Data Visualization, Kubernetes, Azure",PhD,4,Media,2025-03-13,2025-05-10,2229,9.9,Neural Networks Co +AI07007,Data Scientist,68997,USD,68997,EN,CT,South Korea,L,New Zealand,50,"TensorFlow, Python, Tableau, GCP",Bachelor,1,Manufacturing,2024-08-04,2024-10-07,2237,6.6,Advanced Robotics +AI07008,Data Scientist,81660,USD,81660,EN,FL,Israel,L,Israel,50,"Git, Deep Learning, SQL, Linux, Kubernetes",Master,0,Government,2024-03-15,2024-03-30,2337,5.7,Future Systems +AI07009,Autonomous Systems Engineer,151107,GBP,113330,SE,CT,United Kingdom,M,United Kingdom,100,"Deep Learning, AWS, MLOps",Master,7,Government,2024-07-07,2024-09-18,1900,5.9,Algorithmic Solutions +AI07010,Deep Learning Engineer,54435,USD,54435,EN,FT,Sweden,M,Egypt,50,"MLOps, SQL, PyTorch, GCP",PhD,0,Healthcare,2025-01-25,2025-03-20,1222,8.2,Cloud AI Solutions +AI07011,NLP Engineer,295862,EUR,251483,EX,FT,Netherlands,L,Netherlands,0,"Hadoop, GCP, Tableau, Docker, Scala",PhD,16,Technology,2024-04-07,2024-05-18,1139,8,TechCorp Inc +AI07012,AI Product Manager,110402,EUR,93842,SE,FL,France,M,France,100,"R, SQL, Mathematics",Master,9,Energy,2024-06-24,2024-07-29,2427,7.1,Algorithmic Solutions +AI07013,Data Scientist,97747,CAD,122184,MI,PT,Canada,M,Finland,0,"TensorFlow, Mathematics, Python",PhD,4,Manufacturing,2024-07-21,2024-09-12,1776,9.7,Cognitive Computing +AI07014,AI Consultant,57591,EUR,48952,EN,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Spark, Deep Learning, Statistics",Associate,1,Retail,2024-10-31,2025-01-06,1101,9.9,Machine Intelligence Group +AI07015,Autonomous Systems Engineer,202829,USD,202829,EX,FT,Finland,S,Finland,100,"Kubernetes, Python, Linux, GCP",Associate,11,Finance,2024-02-07,2024-03-12,840,6.5,Machine Intelligence Group +AI07016,Autonomous Systems Engineer,49667,CAD,62084,EN,FT,Canada,M,Canada,0,"Data Visualization, Git, R, AWS",Bachelor,0,Education,2024-10-04,2024-11-11,1038,6.7,DataVision Ltd +AI07017,Principal Data Scientist,107663,CHF,96897,EN,PT,Switzerland,L,Switzerland,50,"PyTorch, SQL, NLP",Bachelor,0,Retail,2025-02-26,2025-04-14,1016,6.2,Neural Networks Co +AI07018,Data Engineer,114200,USD,114200,SE,CT,Israel,S,Singapore,100,"Hadoop, Computer Vision, Java, R, Statistics",Associate,6,Retail,2024-05-17,2024-06-11,2297,6.9,Cloud AI Solutions +AI07019,NLP Engineer,195219,GBP,146414,EX,CT,United Kingdom,L,United Kingdom,50,"PyTorch, Hadoop, R, Linux",Associate,11,Consulting,2024-08-13,2024-08-29,1251,9.3,Quantum Computing Inc +AI07020,Principal Data Scientist,174084,JPY,19149240,EX,CT,Japan,M,Japan,100,"Git, NLP, Tableau, Hadoop",Master,10,Transportation,2024-07-07,2024-08-04,877,5.5,Predictive Systems +AI07021,Computer Vision Engineer,86465,EUR,73495,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Hadoop, Scala",PhD,1,Energy,2025-01-19,2025-03-16,1607,9.6,Smart Analytics +AI07022,Head of AI,112857,USD,112857,MI,FL,United States,M,United States,50,"Kubernetes, TensorFlow, NLP, MLOps, Git",Master,3,Telecommunications,2024-08-15,2024-10-06,1126,8.7,TechCorp Inc +AI07023,Robotics Engineer,122484,EUR,104111,MI,CT,Netherlands,L,Indonesia,50,"Git, Mathematics, Python, Data Visualization",Associate,2,Transportation,2024-08-19,2024-10-27,814,5.7,Machine Intelligence Group +AI07024,NLP Engineer,165700,USD,165700,SE,CT,United States,M,United States,0,"Git, Tableau, R, SQL, Scala",Associate,7,Gaming,2024-12-28,2025-02-21,656,7.1,Predictive Systems +AI07025,Principal Data Scientist,168066,USD,168066,SE,PT,Denmark,S,Denmark,50,"Spark, MLOps, Python, Tableau",Master,6,Technology,2024-10-29,2024-12-28,1679,7.2,Autonomous Tech +AI07026,AI Software Engineer,76293,SGD,99181,EN,PT,Singapore,S,Singapore,0,"MLOps, Azure, Docker, AWS, NLP",Associate,1,Manufacturing,2024-03-07,2024-03-28,567,7.6,TechCorp Inc +AI07027,Principal Data Scientist,52755,AUD,71219,EN,FL,Australia,S,Nigeria,50,"PyTorch, Docker, Mathematics",Master,1,Telecommunications,2024-11-14,2025-01-10,2140,7.9,DataVision Ltd +AI07028,NLP Engineer,194324,SGD,252621,EX,CT,Singapore,S,Singapore,100,"Java, Python, Statistics",Master,12,Finance,2024-12-08,2025-01-19,1413,5.9,Machine Intelligence Group +AI07029,Deep Learning Engineer,118307,CAD,147884,SE,FT,Canada,M,Canada,100,"TensorFlow, Java, Git",Bachelor,9,Manufacturing,2024-04-03,2024-06-09,977,7.9,Cognitive Computing +AI07030,ML Ops Engineer,96881,AUD,130789,MI,PT,Australia,M,Egypt,0,"Mathematics, Kubernetes, R",Master,4,Consulting,2025-04-08,2025-06-05,628,8.5,Smart Analytics +AI07031,Autonomous Systems Engineer,57804,USD,57804,SE,FT,China,M,China,50,"Git, Python, Statistics, Azure",Bachelor,5,Government,2024-03-12,2024-04-09,1288,6.5,Cloud AI Solutions +AI07032,Autonomous Systems Engineer,51971,USD,51971,EN,PT,Ireland,S,Ireland,100,"Azure, Kubernetes, SQL, PyTorch",Master,0,Government,2025-04-28,2025-06-03,1884,5.3,Predictive Systems +AI07033,Machine Learning Researcher,175177,SGD,227730,SE,PT,Singapore,L,Singapore,50,"MLOps, Mathematics, SQL, Computer Vision, Kubernetes",Bachelor,8,Media,2024-04-08,2024-05-22,1954,7.7,Quantum Computing Inc +AI07034,Deep Learning Engineer,119721,USD,119721,SE,CT,Norway,S,Russia,0,"TensorFlow, Python, Azure, Kubernetes",Master,7,Media,2024-04-28,2024-06-30,812,8.4,Autonomous Tech +AI07035,AI Product Manager,227954,USD,227954,EX,FT,Israel,L,Israel,0,"Java, R, GCP",Associate,17,Education,2024-04-20,2024-06-22,859,8.5,Machine Intelligence Group +AI07036,Autonomous Systems Engineer,78211,USD,78211,EN,PT,United States,L,United States,0,"TensorFlow, MLOps, Hadoop",PhD,1,Transportation,2025-02-01,2025-03-05,1038,8.4,Cloud AI Solutions +AI07037,AI Research Scientist,175370,EUR,149065,SE,FL,Netherlands,L,Netherlands,0,"Statistics, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-03-13,2024-05-23,1321,8.8,Digital Transformation LLC +AI07038,AI Product Manager,74020,CAD,92525,MI,PT,Canada,S,Canada,50,"PyTorch, Spark, SQL",Bachelor,2,Media,2024-06-29,2024-08-27,932,5.7,Autonomous Tech +AI07039,AI Consultant,66966,GBP,50225,EN,CT,United Kingdom,L,France,0,"SQL, Deep Learning, PyTorch, Java",PhD,0,Education,2024-05-20,2024-07-14,1481,7.2,Advanced Robotics +AI07040,NLP Engineer,73557,EUR,62523,EN,FT,Germany,M,Germany,50,"R, Data Visualization, Linux",Associate,0,Automotive,2024-04-08,2024-05-06,2105,7.3,Future Systems +AI07041,AI Architect,73095,SGD,95024,EN,PT,Singapore,M,Egypt,50,"MLOps, Git, R",Bachelor,1,Healthcare,2024-11-22,2025-01-17,2409,8.5,Advanced Robotics +AI07042,Research Scientist,57811,USD,57811,EN,FL,South Korea,M,South Korea,100,"Python, Linux, Data Visualization, Tableau, R",Master,1,Healthcare,2025-01-01,2025-02-07,1723,7.7,AI Innovations +AI07043,Machine Learning Researcher,235424,EUR,200110,EX,FL,Netherlands,M,Netherlands,100,"Java, Python, Tableau",Master,19,Education,2025-01-26,2025-03-26,1778,9.9,Algorithmic Solutions +AI07044,Robotics Engineer,140023,AUD,189031,SE,FT,Australia,L,Australia,50,"Java, Git, Mathematics",PhD,5,Consulting,2025-04-11,2025-05-25,1371,5.5,AI Innovations +AI07045,Data Engineer,142826,USD,142826,SE,CT,Norway,M,Norway,50,"Deep Learning, Python, TensorFlow, Computer Vision",PhD,9,Energy,2024-02-15,2024-03-20,1317,7.4,Machine Intelligence Group +AI07046,Autonomous Systems Engineer,89624,USD,89624,MI,FL,South Korea,M,Netherlands,0,"Scala, Python, Azure, NLP",Bachelor,3,Transportation,2025-01-13,2025-03-19,1805,5.6,TechCorp Inc +AI07047,Computer Vision Engineer,80501,USD,80501,EN,PT,Denmark,M,Portugal,50,"Deep Learning, Data Visualization, R",Bachelor,0,Finance,2025-03-01,2025-05-01,1126,5.3,Machine Intelligence Group +AI07048,Data Engineer,95043,USD,95043,EN,FT,United States,L,United States,100,"SQL, AWS, Deep Learning, Linux",Associate,0,Finance,2024-04-25,2024-06-03,1627,6.6,Future Systems +AI07049,Deep Learning Engineer,134255,SGD,174532,MI,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning",PhD,2,Automotive,2024-06-30,2024-09-07,913,6.3,Predictive Systems +AI07050,Machine Learning Researcher,108386,CHF,97547,EN,FT,Switzerland,M,Switzerland,100,"Statistics, Tableau, Java, SQL, Python",PhD,0,Transportation,2024-10-25,2024-11-18,1501,5.8,Cloud AI Solutions +AI07051,Robotics Engineer,205581,USD,205581,EX,FL,Israel,M,Israel,50,"Spark, SQL, Python, Statistics",PhD,13,Transportation,2024-12-31,2025-02-20,2163,5.2,Cloud AI Solutions +AI07052,Deep Learning Engineer,115712,EUR,98355,MI,PT,France,L,France,100,"AWS, TensorFlow, Mathematics, SQL",PhD,2,Energy,2024-09-15,2024-10-19,1798,8.3,Predictive Systems +AI07053,AI Software Engineer,41871,USD,41871,MI,FT,China,S,China,0,"Scala, Python, Java, Hadoop",Bachelor,4,Real Estate,2025-03-21,2025-04-04,2356,6.7,DataVision Ltd +AI07054,ML Ops Engineer,89638,CAD,112048,SE,FL,Canada,S,Canada,0,"R, Java, GCP, Spark, Mathematics",Associate,5,Technology,2024-12-15,2025-02-16,2116,8.6,Algorithmic Solutions +AI07055,Machine Learning Engineer,62796,USD,62796,EN,FT,South Korea,L,South Korea,100,"SQL, Tableau, PyTorch",Associate,0,Transportation,2024-01-31,2024-02-28,539,6.6,Algorithmic Solutions +AI07056,AI Product Manager,174278,JPY,19170580,EX,PT,Japan,L,Japan,0,"Python, MLOps, TensorFlow, Git",PhD,13,Media,2024-08-08,2024-10-16,1840,8.2,Neural Networks Co +AI07057,AI Product Manager,236382,JPY,26002020,EX,PT,Japan,M,Argentina,50,"Scala, Tableau, Python, Computer Vision, Deep Learning",PhD,15,Technology,2024-04-06,2024-04-24,821,8.4,Future Systems +AI07058,Computer Vision Engineer,119050,USD,119050,EX,FL,Finland,S,Finland,50,"Spark, Statistics, Computer Vision, Git",Bachelor,15,Technology,2024-09-24,2024-11-06,850,7.1,TechCorp Inc +AI07059,Autonomous Systems Engineer,139306,SGD,181098,SE,PT,Singapore,L,Singapore,50,"Spark, SQL, PyTorch",Bachelor,8,Real Estate,2025-01-10,2025-03-21,723,8,DeepTech Ventures +AI07060,AI Research Scientist,146203,USD,146203,SE,CT,Denmark,M,Denmark,0,"Linux, GCP, Python, Data Visualization, Mathematics",Master,6,Energy,2024-05-06,2024-07-05,1191,8.2,Predictive Systems +AI07061,Research Scientist,91867,EUR,78087,MI,PT,Austria,M,Ireland,100,"Scala, MLOps, Docker",Associate,3,Retail,2024-08-26,2024-10-10,623,7.2,Cloud AI Solutions +AI07062,NLP Engineer,139325,USD,139325,SE,PT,Norway,M,Norway,100,"NLP, PyTorch, TensorFlow",Master,5,Automotive,2024-08-29,2024-11-03,1668,9.3,Predictive Systems +AI07063,Robotics Engineer,368470,USD,368470,EX,PT,Norway,L,Australia,0,"Docker, Deep Learning, SQL",Associate,11,Technology,2024-08-31,2024-10-09,1117,8.5,Digital Transformation LLC +AI07064,AI Research Scientist,79264,USD,79264,MI,FL,South Korea,M,Germany,50,"Java, Python, Kubernetes, Mathematics",Master,2,Technology,2025-04-16,2025-06-02,1050,6,Future Systems +AI07065,Robotics Engineer,213820,USD,213820,EX,CT,Finland,L,Sweden,0,"Kubernetes, Linux, Mathematics, Java",Associate,17,Consulting,2024-06-11,2024-07-05,1605,8.6,Future Systems +AI07066,AI Consultant,91365,AUD,123343,MI,CT,Australia,S,Ireland,100,"Git, Scala, GCP, Computer Vision",Bachelor,2,Consulting,2024-10-05,2024-11-11,634,7.6,Predictive Systems +AI07067,Machine Learning Researcher,135173,EUR,114897,SE,PT,Germany,L,Germany,100,"PyTorch, Linux, Java",Associate,6,Finance,2025-01-21,2025-03-27,1073,6,Smart Analytics +AI07068,Deep Learning Engineer,68488,AUD,92459,EN,FT,Australia,S,Australia,50,"R, Docker, Scala, Statistics, MLOps",Bachelor,0,Government,2024-07-16,2024-09-04,1631,6.4,Cloud AI Solutions +AI07069,AI Software Engineer,117333,EUR,99733,SE,CT,Austria,S,Austria,100,"Scala, TensorFlow, Python, PyTorch",Associate,9,Transportation,2024-09-15,2024-10-05,1294,5.1,Digital Transformation LLC +AI07070,Deep Learning Engineer,99292,USD,99292,MI,PT,Finland,L,Finland,0,"Kubernetes, Scala, Statistics",Associate,3,Healthcare,2024-07-13,2024-09-08,939,8.4,Cloud AI Solutions +AI07071,NLP Engineer,215599,USD,215599,SE,CT,Denmark,L,Denmark,100,"MLOps, Git, PyTorch, Java, Scala",Associate,8,Transportation,2024-09-25,2024-11-01,1492,7,TechCorp Inc +AI07072,ML Ops Engineer,159635,USD,159635,EX,FL,South Korea,M,South Korea,0,"Kubernetes, PyTorch, Docker",PhD,10,Real Estate,2024-05-27,2024-07-16,1395,9,Autonomous Tech +AI07073,AI Product Manager,108321,AUD,146233,MI,FL,Australia,L,Brazil,0,"Computer Vision, Hadoop, Git, Kubernetes",Master,2,Real Estate,2024-05-07,2024-06-10,1705,5.7,Smart Analytics +AI07074,Computer Vision Engineer,76476,CAD,95595,MI,FT,Canada,M,Canada,100,"SQL, Python, Docker, AWS",Associate,2,Consulting,2025-01-28,2025-03-03,543,8.9,AI Innovations +AI07075,Head of AI,83952,AUD,113335,MI,PT,Australia,M,Australia,50,"Kubernetes, Azure, AWS, Deep Learning, Java",Associate,2,Real Estate,2025-03-03,2025-04-06,2076,6.5,Advanced Robotics +AI07076,AI Research Scientist,235700,USD,235700,EX,FT,Israel,L,Ghana,0,"Kubernetes, Python, NLP",Associate,12,Energy,2024-04-21,2024-06-12,1601,8.1,Predictive Systems +AI07077,AI Specialist,131627,USD,131627,SE,FT,United States,M,United States,100,"Hadoop, Kubernetes, Statistics",PhD,6,Real Estate,2024-07-22,2024-08-30,758,7.7,Smart Analytics +AI07078,AI Architect,178535,EUR,151755,EX,CT,Austria,M,Japan,0,"MLOps, Git, Java, Kubernetes, Computer Vision",PhD,12,Automotive,2024-11-13,2025-01-13,1594,5.8,Advanced Robotics +AI07079,AI Architect,209551,USD,209551,EX,PT,Denmark,S,Denmark,0,"Hadoop, Python, Statistics, Linux, Data Visualization",Master,11,Real Estate,2024-03-14,2024-05-04,772,9.6,Machine Intelligence Group +AI07080,AI Software Engineer,84533,EUR,71853,MI,CT,Austria,L,Austria,100,"Python, GCP, TensorFlow",Associate,4,Healthcare,2024-09-07,2024-10-12,860,6.1,Neural Networks Co +AI07081,AI Architect,25457,USD,25457,EN,FL,China,M,Chile,0,"NLP, Linux, SQL",Bachelor,0,Finance,2024-11-01,2024-12-12,1856,5.6,DataVision Ltd +AI07082,Data Analyst,91380,USD,91380,EN,PT,Denmark,M,Denmark,0,"Scala, Tableau, Java, SQL",Associate,0,Media,2024-10-13,2024-11-04,925,7.6,Predictive Systems +AI07083,NLP Engineer,60940,GBP,45705,EN,FT,United Kingdom,S,United Kingdom,50,"Scala, GCP, Tableau, Mathematics",Bachelor,1,Real Estate,2024-11-10,2025-01-20,867,7.8,Smart Analytics +AI07084,Machine Learning Researcher,86902,USD,86902,MI,FL,United States,M,India,50,"R, GCP, Azure, SQL",Associate,3,Consulting,2024-05-04,2024-05-31,538,5.8,Smart Analytics +AI07085,AI Product Manager,119818,USD,119818,MI,PT,United States,M,China,50,"NLP, Data Visualization, Java",Master,3,Energy,2024-11-25,2024-12-30,1964,6.1,Quantum Computing Inc +AI07086,Autonomous Systems Engineer,35047,USD,35047,MI,FT,India,L,India,50,"Python, SQL, TensorFlow, NLP, Deep Learning",Bachelor,3,Real Estate,2024-05-15,2024-06-24,1946,7.6,DataVision Ltd +AI07087,Machine Learning Researcher,175805,GBP,131854,EX,CT,United Kingdom,M,United Kingdom,100,"Statistics, Hadoop, NLP",Bachelor,10,Healthcare,2024-07-02,2024-08-24,1033,7.7,DeepTech Ventures +AI07088,AI Research Scientist,45668,EUR,38818,EN,PT,France,S,France,100,"Azure, MLOps, Scala",Associate,1,Real Estate,2024-05-28,2024-06-20,1406,6.6,Predictive Systems +AI07089,Research Scientist,149817,CAD,187271,EX,PT,Canada,S,Canada,50,"R, Hadoop, MLOps, Java",Bachelor,18,Finance,2024-05-02,2024-06-25,957,6.3,Machine Intelligence Group +AI07090,ML Ops Engineer,82947,GBP,62210,EN,FT,United Kingdom,M,Hungary,50,"Python, Java, Data Visualization, Statistics, Tableau",PhD,0,Education,2024-08-15,2024-09-15,2320,8.3,Algorithmic Solutions +AI07091,AI Research Scientist,85406,CHF,76865,EN,CT,Switzerland,S,Latvia,50,"SQL, AWS, NLP, Scala",Bachelor,1,Healthcare,2024-10-15,2024-11-06,1504,5.9,TechCorp Inc +AI07092,Autonomous Systems Engineer,87146,USD,87146,MI,FL,Ireland,M,Ireland,0,"MLOps, Scala, R, Azure, Computer Vision",PhD,3,Healthcare,2024-06-08,2024-08-16,2101,6.4,Predictive Systems +AI07093,NLP Engineer,69088,AUD,93269,EN,PT,Australia,S,Australia,0,"SQL, Mathematics, Spark, Kubernetes, Git",Associate,0,Gaming,2024-04-07,2024-05-01,1029,7.1,Neural Networks Co +AI07094,AI Consultant,37599,USD,37599,MI,FL,China,S,Romania,100,"Python, TensorFlow, Git, AWS",PhD,3,Government,2024-06-10,2024-08-03,1308,7.8,Cognitive Computing +AI07095,Computer Vision Engineer,87778,USD,87778,EX,FL,China,S,China,0,"NLP, Data Visualization, Tableau, Linux, PyTorch",Bachelor,12,Government,2024-07-03,2024-09-07,578,7.8,Smart Analytics +AI07096,AI Research Scientist,141646,USD,141646,SE,FL,Israel,L,Israel,0,"Azure, Java, R, Data Visualization, Computer Vision",Master,8,Telecommunications,2024-10-11,2024-11-10,784,8,DeepTech Ventures +AI07097,Head of AI,64214,USD,64214,EN,FL,Finland,S,Poland,0,"Docker, Azure, Deep Learning",Bachelor,1,Consulting,2025-02-10,2025-04-06,2117,5.9,DataVision Ltd +AI07098,Data Engineer,167315,GBP,125486,EX,PT,United Kingdom,M,United Kingdom,50,"Git, Data Visualization, Kubernetes, Mathematics, PyTorch",Master,17,Finance,2024-08-14,2024-10-19,1552,5.7,Digital Transformation LLC +AI07099,AI Consultant,48070,USD,48070,SE,PT,India,L,Poland,50,"SQL, AWS, Data Visualization, Docker, PyTorch",PhD,5,Consulting,2024-10-13,2024-10-27,1908,5.6,Quantum Computing Inc +AI07100,Autonomous Systems Engineer,274846,USD,274846,EX,PT,Norway,M,Norway,0,"Scala, Kubernetes, Data Visualization",Master,11,Media,2024-12-05,2025-01-30,855,9.1,Predictive Systems +AI07101,Deep Learning Engineer,116699,SGD,151709,MI,FT,Singapore,M,Brazil,100,"Kubernetes, Python, Spark, Data Visualization, Deep Learning",Bachelor,2,Automotive,2024-02-10,2024-04-14,1991,8.2,Cloud AI Solutions +AI07102,AI Architect,192135,GBP,144101,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Linux, Docker, Spark",Master,15,Government,2024-04-27,2024-05-20,1558,8.3,Neural Networks Co +AI07103,Computer Vision Engineer,129329,EUR,109930,SE,PT,Netherlands,L,Ireland,100,"SQL, Scala, Computer Vision",Bachelor,5,Healthcare,2024-09-21,2024-10-17,1464,7,Cognitive Computing +AI07104,AI Architect,119619,USD,119619,SE,FL,Norway,S,New Zealand,100,"Docker, Kubernetes, Tableau, Mathematics",PhD,9,Automotive,2024-01-30,2024-03-17,1182,5.4,Smart Analytics +AI07105,Machine Learning Researcher,164906,CHF,148415,SE,FL,Switzerland,M,Switzerland,50,"R, SQL, TensorFlow, Tableau, NLP",PhD,7,Retail,2025-04-22,2025-06-10,1394,8.5,Cloud AI Solutions +AI07106,Data Analyst,93246,EUR,79259,SE,PT,Germany,S,Australia,50,"Python, MLOps, Deep Learning, Computer Vision, GCP",Bachelor,7,Education,2024-12-17,2025-01-07,2269,9.7,Digital Transformation LLC +AI07107,Data Engineer,84575,USD,84575,EX,FL,India,L,Argentina,50,"Python, Computer Vision, Java",Associate,13,Transportation,2025-03-25,2025-05-15,1161,5.1,Advanced Robotics +AI07108,AI Specialist,120060,CAD,150075,SE,FL,Canada,M,Canada,0,"Data Visualization, Hadoop, Python, Git",Bachelor,9,Real Estate,2025-04-25,2025-07-07,907,6,Cognitive Computing +AI07109,Deep Learning Engineer,122916,USD,122916,SE,FT,Israel,S,South Korea,100,"Data Visualization, GCP, Linux, PyTorch, Git",Bachelor,5,Manufacturing,2025-02-16,2025-04-20,1429,6.1,Digital Transformation LLC +AI07110,Autonomous Systems Engineer,86361,SGD,112269,MI,CT,Singapore,M,Romania,0,"Python, GCP, Scala, R",Associate,4,Finance,2024-11-16,2024-12-14,741,8.5,Digital Transformation LLC +AI07111,Robotics Engineer,114870,CAD,143588,SE,CT,Canada,S,Canada,100,"PyTorch, Azure, AWS",Associate,8,Education,2025-04-11,2025-05-31,671,9.5,Cognitive Computing +AI07112,Autonomous Systems Engineer,174174,JPY,19159140,EX,FL,Japan,L,Vietnam,100,"Azure, Python, TensorFlow",Bachelor,15,Healthcare,2025-02-06,2025-03-21,1297,6.4,Future Systems +AI07113,Robotics Engineer,174611,USD,174611,EX,CT,Finland,M,Czech Republic,0,"Azure, Git, PyTorch",PhD,18,Technology,2025-04-13,2025-05-02,2132,9.4,Cloud AI Solutions +AI07114,AI Product Manager,79305,USD,79305,MI,FT,Ireland,S,China,100,"R, MLOps, Scala, Mathematics",Associate,4,Government,2024-08-13,2024-09-02,2145,8.8,Neural Networks Co +AI07115,AI Product Manager,104456,USD,104456,SE,FT,South Korea,M,South Korea,50,"Python, Deep Learning, MLOps, TensorFlow",PhD,5,Government,2024-04-09,2024-05-26,1561,9.2,Predictive Systems +AI07116,AI Product Manager,134807,USD,134807,SE,FT,Israel,M,Romania,100,"SQL, AWS, PyTorch",Bachelor,6,Transportation,2025-03-14,2025-04-18,1452,9.1,TechCorp Inc +AI07117,AI Architect,149312,USD,149312,MI,FT,Denmark,L,Denmark,100,"Deep Learning, PyTorch, Mathematics",Master,2,Education,2024-06-26,2024-07-13,549,9.2,DataVision Ltd +AI07118,Research Scientist,138822,USD,138822,MI,CT,Denmark,L,Denmark,100,"Scala, Docker, Azure, Python",Master,4,Telecommunications,2024-04-08,2024-06-11,1428,6.6,Smart Analytics +AI07119,AI Research Scientist,87558,AUD,118203,EN,CT,Australia,L,Australia,0,"NLP, Kubernetes, AWS",PhD,1,Transportation,2024-06-11,2024-08-23,1979,7.5,Neural Networks Co +AI07120,AI Software Engineer,48577,EUR,41290,EN,PT,France,S,Russia,50,"TensorFlow, Scala, Deep Learning, Git",Associate,0,Gaming,2024-09-26,2024-10-11,617,7.6,AI Innovations +AI07121,Machine Learning Engineer,247655,EUR,210507,EX,PT,Germany,M,Germany,50,"Azure, Git, Python",PhD,14,Automotive,2024-07-28,2024-08-16,1618,6.5,Quantum Computing Inc +AI07122,Robotics Engineer,108278,GBP,81209,MI,PT,United Kingdom,M,United Kingdom,50,"Scala, R, SQL, AWS, Tableau",Master,2,Manufacturing,2024-05-03,2024-06-19,799,9.8,TechCorp Inc +AI07123,NLP Engineer,78812,EUR,66990,EN,FL,Germany,L,Germany,0,"R, AWS, Linux",Associate,0,Finance,2025-03-22,2025-05-11,1619,6.9,AI Innovations +AI07124,AI Specialist,116018,USD,116018,MI,PT,Sweden,L,Sweden,0,"PyTorch, Scala, Computer Vision, Mathematics",Bachelor,3,Automotive,2024-04-25,2024-06-25,2267,6.5,Algorithmic Solutions +AI07125,AI Research Scientist,27858,USD,27858,EN,FL,India,M,India,0,"SQL, R, PyTorch",Master,1,Gaming,2024-11-22,2025-01-20,1457,7.7,Cloud AI Solutions +AI07126,AI Consultant,60002,JPY,6600220,EN,CT,Japan,S,Japan,50,"Scala, PyTorch, Statistics, Spark",PhD,0,Government,2025-03-31,2025-05-08,660,6,DeepTech Ventures +AI07127,AI Specialist,167636,CHF,150872,SE,CT,Switzerland,L,Switzerland,0,"Python, Linux, Hadoop, Statistics, Mathematics",Associate,5,Real Estate,2024-02-19,2024-04-15,2370,7.1,Cloud AI Solutions +AI07128,AI Research Scientist,89617,USD,89617,MI,PT,Norway,S,Norway,0,"SQL, GCP, Python, Java, Git",Master,4,Media,2024-10-28,2024-12-24,2284,6.2,Cognitive Computing +AI07129,AI Consultant,133164,EUR,113189,SE,PT,France,L,Germany,100,"Computer Vision, Python, MLOps",Associate,7,Government,2025-03-09,2025-03-25,1886,9.1,Machine Intelligence Group +AI07130,ML Ops Engineer,91502,USD,91502,MI,PT,Finland,M,Finland,0,"Scala, Hadoop, AWS, Spark",Associate,2,Education,2024-04-01,2024-06-05,2387,5.4,Digital Transformation LLC +AI07131,AI Specialist,127869,USD,127869,SE,CT,South Korea,L,South Korea,0,"AWS, Python, Scala, Data Visualization",PhD,7,Manufacturing,2025-02-18,2025-04-04,773,9.6,Predictive Systems +AI07132,AI Architect,127426,CHF,114683,EN,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, NLP",Bachelor,0,Finance,2024-07-27,2024-10-02,1623,6.4,Neural Networks Co +AI07133,Data Analyst,210284,SGD,273369,EX,CT,Singapore,L,Singapore,50,"Java, TensorFlow, Statistics",Master,15,Gaming,2024-06-15,2024-08-07,2166,8.8,Machine Intelligence Group +AI07134,Machine Learning Engineer,78163,USD,78163,EN,PT,Ireland,M,Ireland,50,"SQL, Python, TensorFlow, PyTorch",Bachelor,1,Manufacturing,2024-07-27,2024-08-17,510,9.5,Predictive Systems +AI07135,AI Software Engineer,134757,USD,134757,MI,PT,Norway,L,China,50,"Scala, Mathematics, Git",Associate,4,Manufacturing,2024-08-27,2024-10-09,1181,8.6,TechCorp Inc +AI07136,Autonomous Systems Engineer,71562,CAD,89453,MI,PT,Canada,S,Canada,0,"Hadoop, R, Linux, Computer Vision",Bachelor,4,Gaming,2024-08-25,2024-09-20,2480,6.7,DeepTech Ventures +AI07137,Machine Learning Engineer,47242,CAD,59053,EN,FL,Canada,S,Canada,100,"AWS, Docker, GCP",Master,1,Automotive,2024-06-05,2024-07-01,1580,5.9,DataVision Ltd +AI07138,Head of AI,57033,USD,57033,EX,FT,India,M,Mexico,0,"Scala, PyTorch, Statistics",Bachelor,16,Transportation,2025-02-19,2025-04-04,1212,7,Quantum Computing Inc +AI07139,Data Analyst,119717,USD,119717,SE,PT,Sweden,S,Sweden,100,"GCP, TensorFlow, Python, Kubernetes",PhD,5,Healthcare,2024-03-04,2024-04-11,1807,7.8,Digital Transformation LLC +AI07140,Data Analyst,127727,USD,127727,SE,FL,Sweden,S,Sweden,0,"AWS, PyTorch, Java",Associate,9,Transportation,2024-03-12,2024-05-05,1142,5.6,DeepTech Ventures +AI07141,Machine Learning Engineer,78754,USD,78754,EN,CT,Finland,L,Finland,50,"NLP, SQL, Mathematics, MLOps, PyTorch",Bachelor,1,Energy,2024-10-05,2024-11-27,1435,9.9,Advanced Robotics +AI07142,Autonomous Systems Engineer,76900,USD,76900,MI,FL,Finland,M,Finland,50,"Kubernetes, PyTorch, Git, Linux",Bachelor,3,Government,2024-01-01,2024-01-16,1848,9.7,Algorithmic Solutions +AI07143,NLP Engineer,140463,USD,140463,SE,FT,Ireland,L,Ireland,50,"Data Visualization, TensorFlow, SQL, Git, Scala",PhD,8,Government,2024-04-01,2024-05-10,2156,6.9,Cognitive Computing +AI07144,AI Software Engineer,107972,AUD,145762,SE,FL,Australia,S,Romania,0,"TensorFlow, SQL, Mathematics, Linux",Associate,5,Retail,2025-02-04,2025-02-26,1598,9.4,Machine Intelligence Group +AI07145,Deep Learning Engineer,210162,USD,210162,EX,PT,United States,L,United States,100,"Java, Computer Vision, Python, Hadoop, Scala",Associate,12,Manufacturing,2025-03-06,2025-05-12,2178,9.7,Quantum Computing Inc +AI07146,Data Analyst,199015,CAD,248769,EX,PT,Canada,S,Egypt,50,"Git, TensorFlow, Mathematics, Spark",Master,13,Retail,2024-12-08,2025-02-05,722,7.8,DeepTech Ventures +AI07147,Data Analyst,214251,USD,214251,EX,PT,Ireland,M,Argentina,0,"Python, MLOps, GCP, Statistics, Linux",Master,14,Automotive,2024-04-13,2024-05-26,838,6.6,DataVision Ltd +AI07148,AI Research Scientist,200251,USD,200251,EX,FT,Sweden,M,Sweden,50,"MLOps, Hadoop, NLP, Data Visualization, R",Master,17,Government,2025-02-01,2025-04-09,693,10,Predictive Systems +AI07149,Machine Learning Engineer,56919,AUD,76841,EN,CT,Australia,S,Australia,0,"R, SQL, Git, Mathematics, Kubernetes",Bachelor,1,Technology,2024-06-07,2024-07-31,605,8.9,Quantum Computing Inc +AI07150,ML Ops Engineer,52483,USD,52483,EN,FT,Sweden,M,Sweden,0,"Spark, Mathematics, Data Visualization",Associate,1,Retail,2025-03-01,2025-03-18,2260,8.9,DataVision Ltd +AI07151,Computer Vision Engineer,124533,USD,124533,SE,CT,United States,S,South Africa,0,"Python, TensorFlow, Hadoop, Java",PhD,9,Telecommunications,2024-01-03,2024-01-19,1465,5.4,Future Systems +AI07152,NLP Engineer,122990,AUD,166037,MI,FT,Australia,L,Australia,100,"MLOps, Scala, Statistics",Associate,2,Finance,2025-02-01,2025-03-26,1567,9.2,Predictive Systems +AI07153,Head of AI,149199,USD,149199,EX,PT,Sweden,M,Chile,0,"PyTorch, Scala, Statistics",Bachelor,12,Energy,2024-10-24,2024-11-07,1675,6.6,Neural Networks Co +AI07154,NLP Engineer,82914,EUR,70477,MI,CT,Germany,S,Latvia,100,"Tableau, PyTorch, Kubernetes, GCP, AWS",Bachelor,3,Government,2024-02-19,2024-04-08,1754,5.9,Advanced Robotics +AI07155,Data Scientist,73131,EUR,62161,EN,PT,Austria,M,New Zealand,100,"Azure, Deep Learning, Git, Hadoop",Bachelor,1,Automotive,2024-03-26,2024-04-14,1533,5.3,Algorithmic Solutions +AI07156,AI Software Engineer,84202,JPY,9262220,EN,PT,Japan,M,Japan,50,"Spark, Docker, GCP, AWS, Hadoop",Bachelor,0,Real Estate,2024-11-15,2024-12-02,1057,8.8,Predictive Systems +AI07157,Autonomous Systems Engineer,196071,GBP,147053,EX,PT,United Kingdom,S,Kenya,0,"Linux, SQL, Deep Learning, Python, R",Associate,17,Transportation,2024-06-19,2024-08-27,741,8.2,Algorithmic Solutions +AI07158,AI Software Engineer,56307,USD,56307,EN,PT,Israel,M,Israel,100,"Python, Docker, Hadoop, Git",Bachelor,0,Real Estate,2025-01-27,2025-03-14,1013,6.1,Algorithmic Solutions +AI07159,Robotics Engineer,118127,USD,118127,EX,PT,China,L,China,0,"Python, Docker, MLOps",PhD,10,Energy,2024-12-20,2025-01-15,788,6.3,Cloud AI Solutions +AI07160,Deep Learning Engineer,286081,AUD,386209,EX,CT,Australia,L,Australia,0,"Statistics, Spark, TensorFlow, Linux, Docker",PhD,10,Automotive,2025-01-01,2025-02-22,1102,7.4,DataVision Ltd +AI07161,Data Analyst,38151,USD,38151,MI,FT,China,S,China,0,"PyTorch, TensorFlow, Statistics, Mathematics",Associate,4,Media,2024-10-09,2024-11-24,633,5.2,Cloud AI Solutions +AI07162,AI Product Manager,51436,JPY,5657960,EN,PT,Japan,S,Japan,0,"SQL, GCP, Kubernetes, Docker, Mathematics",Master,1,Manufacturing,2025-02-04,2025-02-20,1703,5.6,Future Systems +AI07163,Head of AI,179375,CHF,161438,MI,PT,Switzerland,L,New Zealand,0,"Python, Computer Vision, Linux, Azure, Deep Learning",Bachelor,3,Real Estate,2024-10-28,2024-12-07,501,9.2,Neural Networks Co +AI07164,AI Research Scientist,224945,USD,224945,EX,FL,Israel,M,Israel,100,"Docker, SQL, PyTorch, Java",PhD,16,Education,2024-08-28,2024-10-23,2317,9.1,Machine Intelligence Group +AI07165,AI Architect,199077,USD,199077,EX,FT,Sweden,S,India,100,"Computer Vision, Tableau, Data Visualization",Associate,14,Retail,2024-11-14,2024-12-25,2448,6.7,Cognitive Computing +AI07166,Data Engineer,154017,USD,154017,SE,PT,United States,L,United States,50,"Python, SQL, Spark, MLOps, TensorFlow",Associate,9,Transportation,2024-08-07,2024-09-11,1991,6.4,AI Innovations +AI07167,Data Engineer,187633,JPY,20639630,EX,CT,Japan,S,Japan,100,"Tableau, Scala, NLP, TensorFlow",Bachelor,17,Consulting,2024-09-28,2024-10-12,1306,8.4,Cloud AI Solutions +AI07168,Research Scientist,113467,USD,113467,MI,FL,Norway,M,Norway,50,"Azure, AWS, NLP, Deep Learning, GCP",Associate,4,Manufacturing,2024-02-16,2024-03-31,1916,8.6,Future Systems +AI07169,AI Product Manager,97170,USD,97170,MI,FL,Sweden,M,Sweden,100,"Kubernetes, GCP, SQL",PhD,4,Consulting,2024-07-01,2024-08-18,1337,6,Autonomous Tech +AI07170,AI Specialist,117600,USD,117600,MI,FT,Norway,S,Norway,50,"Java, Azure, Kubernetes",PhD,2,Technology,2024-09-11,2024-11-01,536,5.1,Neural Networks Co +AI07171,ML Ops Engineer,175430,CAD,219288,EX,CT,Canada,S,Canada,100,"Hadoop, R, SQL",Master,13,Finance,2025-03-17,2025-05-12,2082,9.2,Advanced Robotics +AI07172,Research Scientist,92546,EUR,78664,MI,FL,Netherlands,L,Netherlands,0,"R, Java, SQL",PhD,4,Transportation,2025-03-03,2025-03-17,1865,5.2,Cloud AI Solutions +AI07173,NLP Engineer,78042,USD,78042,MI,FL,United States,S,United States,100,"Python, GCP, TensorFlow, AWS, Deep Learning",Associate,2,Automotive,2024-03-21,2024-04-07,1251,6.2,DataVision Ltd +AI07174,Head of AI,60141,USD,60141,SE,FT,China,S,China,0,"Azure, AWS, Deep Learning, Computer Vision, GCP",PhD,5,Education,2025-01-03,2025-02-16,834,9.5,DeepTech Ventures +AI07175,Computer Vision Engineer,74219,EUR,63086,MI,FT,France,M,France,100,"Spark, NLP, Scala, PyTorch",Master,4,Gaming,2024-11-06,2025-01-03,577,5.7,Future Systems +AI07176,Data Scientist,117670,USD,117670,SE,PT,Finland,M,Finland,0,"Azure, TensorFlow, SQL, Tableau, Deep Learning",Associate,9,Manufacturing,2024-03-07,2024-03-25,585,9.5,Predictive Systems +AI07177,AI Product Manager,43045,USD,43045,EN,PT,South Korea,S,South Korea,100,"Mathematics, Data Visualization, Git, Linux",Associate,0,Healthcare,2024-05-22,2024-06-18,1964,5.9,Future Systems +AI07178,Computer Vision Engineer,204977,USD,204977,EX,FT,Israel,L,Israel,0,"NLP, Docker, Tableau, TensorFlow",Master,13,Retail,2024-01-23,2024-04-01,1912,8.8,Autonomous Tech +AI07179,Data Scientist,99117,USD,99117,MI,PT,Sweden,S,Sweden,50,"Azure, TensorFlow, AWS, Linux",Associate,3,Technology,2024-08-07,2024-08-30,1543,7.4,Autonomous Tech +AI07180,AI Product Manager,71043,USD,71043,EN,FT,Ireland,L,Ireland,50,"Data Visualization, Python, Spark, MLOps",Associate,1,Healthcare,2024-04-28,2024-07-01,2161,9.5,Algorithmic Solutions +AI07181,Machine Learning Engineer,245455,SGD,319092,EX,FL,Singapore,M,Singapore,0,"Git, Azure, Scala",PhD,19,Government,2025-04-25,2025-05-26,1625,7.6,Future Systems +AI07182,NLP Engineer,100152,USD,100152,MI,FL,South Korea,L,South Korea,50,"Java, Spark, Kubernetes",Bachelor,2,Government,2025-03-14,2025-04-16,529,6.5,Advanced Robotics +AI07183,Machine Learning Researcher,184471,EUR,156800,SE,PT,Netherlands,L,Singapore,100,"Python, MLOps, Statistics, Mathematics, Kubernetes",Associate,5,Gaming,2025-02-09,2025-04-13,1628,6.2,Future Systems +AI07184,Research Scientist,192741,EUR,163830,EX,FL,Austria,L,India,100,"Scala, Tableau, SQL, AWS",PhD,14,Real Estate,2024-12-25,2025-01-21,893,6.8,Neural Networks Co +AI07185,Autonomous Systems Engineer,130456,USD,130456,SE,FT,Norway,S,Norway,0,"Mathematics, Spark, NLP, Linux, Git",PhD,7,Healthcare,2025-03-21,2025-04-26,1191,8,Neural Networks Co +AI07186,ML Ops Engineer,131122,USD,131122,MI,CT,Denmark,M,Denmark,50,"Scala, Docker, Kubernetes",Associate,3,Gaming,2024-06-15,2024-08-08,2321,6.7,TechCorp Inc +AI07187,AI Research Scientist,92768,USD,92768,MI,FT,Ireland,S,Ireland,0,"Mathematics, R, SQL",Master,4,Finance,2024-08-20,2024-10-19,774,9.9,DeepTech Ventures +AI07188,AI Architect,117822,USD,117822,SE,FL,Israel,M,Israel,0,"Python, Spark, NLP, SQL, AWS",Associate,7,Telecommunications,2024-07-06,2024-09-11,690,9.3,Future Systems +AI07189,Data Scientist,220795,EUR,187676,EX,CT,Austria,L,Austria,100,"Kubernetes, Python, Tableau",Master,15,Transportation,2024-07-06,2024-08-04,1166,8.1,Digital Transformation LLC +AI07190,AI Specialist,71908,CAD,89885,MI,CT,Canada,M,Canada,0,"Python, TensorFlow, MLOps, Linux, Hadoop",Bachelor,4,Telecommunications,2024-06-19,2024-07-25,1717,9,DeepTech Ventures +AI07191,AI Consultant,217854,USD,217854,EX,FL,Denmark,L,Denmark,0,"Statistics, AWS, Hadoop, Docker, GCP",PhD,19,Media,2024-05-24,2024-07-28,2421,9.4,Machine Intelligence Group +AI07192,Head of AI,50633,JPY,5569630,EN,CT,Japan,S,Japan,0,"R, PyTorch, GCP",Master,0,Manufacturing,2024-05-15,2024-07-20,1102,7,Digital Transformation LLC +AI07193,Data Scientist,67836,CAD,84795,EN,CT,Canada,S,Indonesia,100,"Azure, Python, NLP, Docker",Bachelor,0,Telecommunications,2025-02-13,2025-04-05,2052,7.7,Autonomous Tech +AI07194,Deep Learning Engineer,120724,AUD,162977,MI,PT,Australia,L,Australia,50,"Scala, Java, Kubernetes, Mathematics",PhD,2,Government,2024-11-22,2025-01-30,1133,6.4,Quantum Computing Inc +AI07195,Head of AI,117611,USD,117611,MI,FL,Denmark,S,Denmark,50,"SQL, Mathematics, R, PyTorch",Bachelor,4,Consulting,2024-11-01,2025-01-04,2446,9.4,Autonomous Tech +AI07196,Autonomous Systems Engineer,143600,USD,143600,EX,CT,Ireland,S,Ireland,50,"MLOps, Python, Statistics",Master,12,Automotive,2024-11-11,2025-01-08,907,7.1,Advanced Robotics +AI07197,Deep Learning Engineer,54479,SGD,70823,EN,FL,Singapore,M,Singapore,50,"MLOps, Linux, Azure",Bachelor,0,Manufacturing,2024-06-15,2024-07-18,1974,6.7,Future Systems +AI07198,AI Research Scientist,234608,JPY,25806880,EX,FL,Japan,S,Japan,50,"Spark, Python, Docker, GCP",Associate,17,Telecommunications,2024-10-08,2024-12-16,558,8,Cognitive Computing +AI07199,Computer Vision Engineer,58879,EUR,50047,EN,FL,Germany,L,Germany,100,"TensorFlow, Spark, PyTorch, Git",Master,0,Government,2025-01-03,2025-02-24,1177,7.5,Cloud AI Solutions +AI07200,Principal Data Scientist,94161,USD,94161,MI,FT,Denmark,S,Denmark,50,"Java, SQL, Tableau, Azure, Spark",Associate,3,Energy,2024-06-30,2024-09-02,1398,5.2,Autonomous Tech +AI07201,Head of AI,83285,USD,83285,MI,FL,Ireland,S,Ireland,50,"R, Java, Spark, TensorFlow, Kubernetes",Master,3,Retail,2025-03-07,2025-04-21,2452,8.8,Neural Networks Co +AI07202,AI Software Engineer,203713,AUD,275013,EX,FL,Australia,M,Australia,50,"Mathematics, Kubernetes, MLOps",PhD,14,Transportation,2024-11-21,2025-01-04,594,7.1,Autonomous Tech +AI07203,Data Scientist,31793,USD,31793,MI,PT,China,S,China,100,"MLOps, Docker, Linux, Tableau, Data Visualization",Master,2,Government,2024-05-21,2024-06-24,718,5.4,DataVision Ltd +AI07204,Principal Data Scientist,48887,USD,48887,SE,PT,India,L,India,50,"PyTorch, Tableau, Hadoop, AWS",PhD,9,Technology,2025-04-24,2025-06-04,1126,8.2,Digital Transformation LLC +AI07205,Principal Data Scientist,106359,AUD,143585,MI,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, SQL, GCP",Master,4,Technology,2025-03-20,2025-05-19,905,5.7,TechCorp Inc +AI07206,Deep Learning Engineer,115364,USD,115364,SE,CT,Israel,M,Australia,50,"Python, Java, Deep Learning, TensorFlow",Master,8,Manufacturing,2024-03-05,2024-05-01,844,6.7,Quantum Computing Inc +AI07207,Research Scientist,135236,EUR,114951,SE,CT,Germany,S,Germany,0,"MLOps, Spark, Python, Git",Bachelor,5,Education,2024-08-20,2024-10-31,2100,7.1,Advanced Robotics +AI07208,Data Analyst,196882,EUR,167350,EX,FL,Netherlands,L,Netherlands,100,"Computer Vision, Hadoop, Statistics, TensorFlow",Master,11,Real Estate,2024-05-06,2024-06-26,2375,8.3,DeepTech Ventures +AI07209,AI Specialist,52592,GBP,39444,EN,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Scala, SQL, NLP",PhD,0,Transportation,2024-12-26,2025-02-02,1544,8.8,Future Systems +AI07210,Machine Learning Researcher,130809,JPY,14388990,SE,CT,Japan,L,Japan,0,"PyTorch, SQL, Git, Hadoop, Mathematics",Associate,7,Healthcare,2024-02-15,2024-03-25,897,6.4,AI Innovations +AI07211,Data Engineer,83254,EUR,70766,EN,FL,Germany,L,Germany,50,"PyTorch, NLP, Deep Learning, Python, MLOps",Master,1,Technology,2024-01-01,2024-02-27,798,9.4,Predictive Systems +AI07212,Deep Learning Engineer,116639,USD,116639,MI,PT,Denmark,S,Denmark,50,"Tableau, Java, MLOps, Hadoop, Azure",Associate,3,Retail,2024-06-28,2024-07-14,892,6,Cloud AI Solutions +AI07213,Data Engineer,188382,CHF,169544,SE,FL,Switzerland,M,Portugal,0,"MLOps, PyTorch, Mathematics, TensorFlow",Bachelor,6,Consulting,2024-06-02,2024-07-11,2297,6.8,Cognitive Computing +AI07214,AI Software Engineer,126123,SGD,163960,SE,PT,Singapore,L,Romania,100,"Scala, Tableau, Python, Data Visualization",Master,7,Healthcare,2025-04-22,2025-06-26,686,8.1,Quantum Computing Inc +AI07215,AI Product Manager,108451,USD,108451,SE,FT,South Korea,M,South Korea,0,"NLP, Docker, SQL, Git",PhD,6,Technology,2024-06-15,2024-08-19,2311,6.2,Future Systems +AI07216,Computer Vision Engineer,241452,EUR,205234,EX,FL,Netherlands,L,Netherlands,0,"Python, Tableau, Deep Learning",Master,11,Finance,2024-09-23,2024-10-15,1584,6.5,Advanced Robotics +AI07217,Robotics Engineer,95945,EUR,81553,MI,CT,Netherlands,S,Netherlands,0,"SQL, Linux, Tableau",Master,2,Consulting,2024-01-02,2024-02-23,1803,10,Machine Intelligence Group +AI07218,Data Scientist,92299,AUD,124604,MI,PT,Australia,L,Portugal,50,"Deep Learning, Scala, SQL, Git",Associate,3,Finance,2024-07-08,2024-08-16,1353,7.7,Neural Networks Co +AI07219,Data Engineer,92328,USD,92328,MI,FT,Israel,M,Ukraine,0,"Java, Python, Hadoop, Spark",Associate,4,Automotive,2024-01-02,2024-02-02,1233,5,AI Innovations +AI07220,AI Consultant,63650,USD,63650,EN,FT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, Mathematics",Associate,1,Government,2024-05-17,2024-06-07,2110,7.3,Quantum Computing Inc +AI07221,AI Consultant,240627,EUR,204533,EX,FT,Netherlands,M,Netherlands,0,"Data Visualization, Spark, Scala, Deep Learning",PhD,18,Retail,2024-06-26,2024-07-19,1850,5.1,AI Innovations +AI07222,AI Specialist,113824,USD,113824,MI,PT,Norway,L,Norway,100,"AWS, Docker, Azure, Computer Vision",PhD,4,Consulting,2024-11-18,2025-01-06,2039,8.2,Algorithmic Solutions +AI07223,Data Analyst,102248,CHF,92023,MI,CT,Switzerland,S,Spain,0,"AWS, Mathematics, Hadoop",PhD,2,Real Estate,2024-03-09,2024-03-30,1863,9.9,Smart Analytics +AI07224,Machine Learning Researcher,72700,USD,72700,MI,PT,South Korea,S,South Korea,100,"Python, Hadoop, Linux, Scala, Java",PhD,4,Consulting,2024-11-18,2024-12-04,1842,5.6,Advanced Robotics +AI07225,AI Product Manager,101760,USD,101760,MI,FL,Ireland,L,Ireland,50,"Scala, Git, Statistics, Computer Vision, Kubernetes",Associate,3,Retail,2024-02-19,2024-03-13,2062,6.9,Digital Transformation LLC +AI07226,Machine Learning Researcher,75850,USD,75850,MI,PT,Israel,S,Israel,0,"Deep Learning, Java, Git, Mathematics, R",Bachelor,4,Retail,2024-05-03,2024-06-26,969,8.4,Cloud AI Solutions +AI07227,Robotics Engineer,54596,EUR,46407,EN,FL,Austria,M,Austria,100,"NLP, Python, Deep Learning",Bachelor,1,Technology,2025-01-12,2025-03-13,1823,9.4,Algorithmic Solutions +AI07228,AI Research Scientist,133583,AUD,180337,EX,PT,Australia,S,Australia,100,"Hadoop, SQL, Spark",Bachelor,11,Retail,2024-10-04,2024-10-18,1642,6.8,Digital Transformation LLC +AI07229,Autonomous Systems Engineer,75968,CAD,94960,MI,FL,Canada,M,Canada,100,"Mathematics, Docker, Python, Hadoop",Master,4,Manufacturing,2024-07-11,2024-08-17,1020,8,Quantum Computing Inc +AI07230,AI Product Manager,142238,AUD,192021,SE,FT,Australia,L,Australia,50,"GCP, R, Mathematics",PhD,7,Government,2024-07-03,2024-08-16,978,6.3,AI Innovations +AI07231,Machine Learning Engineer,211317,USD,211317,EX,FL,Israel,L,Israel,0,"MLOps, Mathematics, SQL, AWS",Master,13,Consulting,2025-01-18,2025-03-18,990,6.7,Autonomous Tech +AI07232,Data Engineer,260422,EUR,221359,EX,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Data Visualization, Spark",PhD,15,Education,2024-06-17,2024-08-13,2056,9.5,Machine Intelligence Group +AI07233,Autonomous Systems Engineer,203781,CAD,254726,EX,FL,Canada,S,Canada,0,"Linux, Java, Data Visualization, MLOps, Hadoop",PhD,11,Healthcare,2024-11-19,2024-12-19,1698,10,Neural Networks Co +AI07234,Machine Learning Engineer,53311,USD,53311,SE,PT,India,M,India,0,"Spark, SQL, Kubernetes, Python, Computer Vision",Associate,8,Transportation,2025-04-19,2025-06-15,727,5.4,Cloud AI Solutions +AI07235,AI Product Manager,111471,JPY,12261810,SE,FL,Japan,S,Japan,100,"SQL, Java, R, Scala",Bachelor,6,Healthcare,2024-05-15,2024-07-21,597,7.5,Predictive Systems +AI07236,Robotics Engineer,195168,EUR,165893,EX,PT,Germany,S,Spain,50,"Python, Docker, AWS",Master,11,Government,2024-12-29,2025-02-03,1452,8.2,Advanced Robotics +AI07237,AI Product Manager,48863,USD,48863,EN,FL,Finland,S,Finland,50,"Python, SQL, Hadoop",Bachelor,0,Transportation,2025-03-31,2025-05-22,870,7.7,Advanced Robotics +AI07238,AI Consultant,272513,CHF,245262,EX,CT,Switzerland,L,Switzerland,50,"PyTorch, AWS, NLP, SQL",Master,16,Real Estate,2024-10-19,2024-12-16,2456,9.1,AI Innovations +AI07239,ML Ops Engineer,180571,USD,180571,EX,CT,Sweden,L,Turkey,0,"GCP, TensorFlow, NLP, SQL, Tableau",Bachelor,19,Gaming,2025-03-18,2025-05-26,642,7.3,Algorithmic Solutions +AI07240,Data Scientist,177014,USD,177014,SE,FT,Denmark,L,Denmark,50,"Data Visualization, R, Deep Learning",Master,7,Automotive,2024-12-17,2024-12-31,2171,6.1,Predictive Systems +AI07241,Research Scientist,105629,USD,105629,EN,FL,United States,L,Finland,50,"SQL, NLP, Git, PyTorch",Bachelor,0,Real Estate,2024-10-28,2024-11-19,1188,8.6,Cognitive Computing +AI07242,NLP Engineer,201624,USD,201624,EX,FL,Ireland,S,Latvia,50,"Scala, Spark, Kubernetes, TensorFlow, Statistics",Bachelor,11,Technology,2024-10-09,2024-12-13,1376,7.5,Predictive Systems +AI07243,NLP Engineer,131783,EUR,112016,SE,CT,France,L,South Africa,100,"Java, GCP, Tableau, Scala",Associate,5,Gaming,2025-04-30,2025-07-04,548,8.6,DeepTech Ventures +AI07244,NLP Engineer,75289,USD,75289,EN,FL,Sweden,L,Sweden,100,"Linux, PyTorch, R, Python, Mathematics",Bachelor,0,Energy,2024-03-02,2024-04-28,1011,8.3,Quantum Computing Inc +AI07245,Data Scientist,336868,USD,336868,EX,PT,Norway,L,Norway,100,"Spark, NLP, Tableau, Docker",Master,14,Media,2024-06-21,2024-08-03,902,8.1,Digital Transformation LLC +AI07246,AI Research Scientist,163534,EUR,139004,SE,FL,Germany,L,Germany,0,"GCP, Hadoop, Docker, Deep Learning, SQL",Master,7,Consulting,2024-07-13,2024-08-06,1179,6.7,Machine Intelligence Group +AI07247,Data Engineer,116592,USD,116592,SE,FT,Finland,S,China,100,"Git, Spark, NLP, Kubernetes",PhD,9,Healthcare,2025-03-10,2025-04-17,2130,8.6,Cloud AI Solutions +AI07248,AI Consultant,124845,JPY,13732950,SE,FL,Japan,L,New Zealand,0,"Kubernetes, Data Visualization, Python, AWS, MLOps",Bachelor,9,Technology,2024-10-16,2024-12-10,1028,7.3,Machine Intelligence Group +AI07249,Robotics Engineer,130238,USD,130238,EX,PT,Sweden,S,Sweden,100,"SQL, Kubernetes, PyTorch, Git",Master,10,Consulting,2024-07-01,2024-07-16,1080,8.9,Digital Transformation LLC +AI07250,Data Engineer,190431,CAD,238039,EX,PT,Canada,M,Canada,50,"Spark, Scala, SQL",Master,19,Healthcare,2024-10-22,2024-11-19,2125,7.1,Quantum Computing Inc +AI07251,Research Scientist,21657,USD,21657,EN,CT,India,L,India,50,"TensorFlow, Java, PyTorch, GCP",Bachelor,0,Real Estate,2024-01-08,2024-02-04,790,5.1,DataVision Ltd +AI07252,Data Engineer,120635,USD,120635,MI,PT,Ireland,L,Ireland,100,"Linux, R, SQL, Deep Learning",PhD,4,Media,2025-02-26,2025-03-18,1761,7,Machine Intelligence Group +AI07253,AI Research Scientist,86185,USD,86185,MI,FL,Israel,L,Israel,50,"Statistics, Computer Vision, Data Visualization, Scala, MLOps",Bachelor,4,Government,2024-09-06,2024-11-18,552,5.6,Neural Networks Co +AI07254,AI Software Engineer,165333,CAD,206666,SE,FL,Canada,L,Australia,0,"Linux, Spark, TensorFlow",Associate,9,Energy,2024-09-01,2024-10-26,2165,6.6,Autonomous Tech +AI07255,Head of AI,160948,USD,160948,EX,FL,Finland,L,Finland,50,"Deep Learning, Kubernetes, Java, Hadoop",Master,15,Finance,2024-12-08,2025-01-19,726,6.3,DeepTech Ventures +AI07256,Deep Learning Engineer,74480,CHF,67032,EN,CT,Switzerland,M,Switzerland,50,"Java, Linux, TensorFlow, AWS, NLP",PhD,1,Energy,2024-04-23,2024-06-30,1898,7.9,Predictive Systems +AI07257,Data Scientist,64243,CAD,80304,EN,PT,Canada,L,Canada,0,"Computer Vision, Python, TensorFlow",Bachelor,0,Finance,2024-10-26,2024-12-21,1629,5.5,DeepTech Ventures +AI07258,Data Engineer,86729,USD,86729,MI,CT,Sweden,S,Switzerland,100,"Computer Vision, Mathematics, Kubernetes, Tableau",Bachelor,4,Manufacturing,2024-08-16,2024-10-01,1998,7.1,Algorithmic Solutions +AI07259,AI Specialist,72797,JPY,8007670,EN,PT,Japan,M,Japan,50,"SQL, GCP, Tableau, TensorFlow, Data Visualization",Master,1,Consulting,2024-09-28,2024-11-02,1471,8,DeepTech Ventures +AI07260,Research Scientist,124502,SGD,161853,SE,PT,Singapore,S,Singapore,100,"Deep Learning, Scala, Computer Vision, SQL, PyTorch",Associate,6,Education,2024-01-02,2024-01-28,619,9.5,Advanced Robotics +AI07261,AI Software Engineer,271059,AUD,365930,EX,CT,Australia,L,Philippines,100,"Git, Azure, Python, TensorFlow",Bachelor,12,Finance,2025-01-19,2025-02-15,1510,5.3,Cognitive Computing +AI07262,AI Product Manager,108790,EUR,92472,MI,CT,Netherlands,M,United States,0,"Kubernetes, Python, Tableau",PhD,3,Media,2024-05-04,2024-05-23,1626,9.1,Predictive Systems +AI07263,AI Product Manager,259708,AUD,350606,EX,PT,Australia,L,Australia,0,"Spark, Kubernetes, Statistics",PhD,17,Healthcare,2025-02-20,2025-03-17,2391,6.6,AI Innovations +AI07264,ML Ops Engineer,83606,USD,83606,EN,CT,United States,S,Germany,100,"TensorFlow, Tableau, Python, Computer Vision",Master,1,Consulting,2025-03-22,2025-05-14,1408,9.1,Cloud AI Solutions +AI07265,Robotics Engineer,160120,AUD,216162,SE,FT,Australia,L,Australia,50,"R, GCP, Deep Learning",Master,5,Manufacturing,2024-06-07,2024-07-16,1221,8.2,Cloud AI Solutions +AI07266,Robotics Engineer,97279,USD,97279,MI,PT,Israel,M,Israel,0,"Kubernetes, Python, Deep Learning, Data Visualization, Java",Master,2,Gaming,2024-05-10,2024-06-19,1144,6.4,Quantum Computing Inc +AI07267,AI Research Scientist,120260,USD,120260,SE,PT,Sweden,S,Sweden,50,"Computer Vision, MLOps, Deep Learning, Spark, PyTorch",Associate,9,Consulting,2024-03-07,2024-04-21,1969,5.4,DataVision Ltd +AI07268,Research Scientist,70585,AUD,95290,EN,FT,Australia,L,Estonia,50,"Mathematics, Hadoop, GCP, PyTorch",Associate,1,Retail,2024-08-18,2024-10-20,1909,6,TechCorp Inc +AI07269,Machine Learning Engineer,88166,AUD,119024,MI,CT,Australia,S,Australia,100,"Python, TensorFlow, Linux",Associate,2,Finance,2024-03-22,2024-05-21,1056,6.5,Smart Analytics +AI07270,Machine Learning Researcher,112078,USD,112078,MI,PT,United States,S,Japan,50,"Hadoop, GCP, Kubernetes, Tableau",Master,3,Technology,2025-03-16,2025-04-25,2346,5.1,Cognitive Computing +AI07271,AI Product Manager,33267,USD,33267,MI,CT,China,S,China,50,"Spark, AWS, Deep Learning",Master,2,Media,2024-06-08,2024-07-27,773,6.7,AI Innovations +AI07272,Machine Learning Researcher,118202,USD,118202,MI,PT,Norway,M,Norway,100,"Docker, Deep Learning, PyTorch",Bachelor,4,Media,2024-02-23,2024-04-29,1741,7,Future Systems +AI07273,Machine Learning Researcher,83199,USD,83199,MI,FT,Ireland,S,Ireland,0,"Kubernetes, Docker, Python, Computer Vision",PhD,4,Automotive,2025-03-20,2025-04-17,1720,7.2,Digital Transformation LLC +AI07274,Deep Learning Engineer,64159,CAD,80199,EN,PT,Canada,M,Canada,0,"Python, Kubernetes, AWS",Bachelor,1,Education,2024-03-28,2024-05-04,1069,5.8,Autonomous Tech +AI07275,ML Ops Engineer,67930,USD,67930,MI,FL,South Korea,S,South Korea,100,"Statistics, TensorFlow, R, Deep Learning, Tableau",Master,4,Real Estate,2024-06-18,2024-08-19,618,7.1,Future Systems +AI07276,Principal Data Scientist,118438,GBP,88829,SE,FT,United Kingdom,M,United Kingdom,50,"Spark, Kubernetes, Mathematics, Tableau",Master,9,Automotive,2024-02-10,2024-04-03,1557,6.5,Cognitive Computing +AI07277,AI Product Manager,49451,USD,49451,SE,PT,India,L,India,0,"SQL, Python, PyTorch",Master,5,Media,2024-04-25,2024-05-28,1974,7,Machine Intelligence Group +AI07278,Head of AI,199445,USD,199445,SE,PT,Norway,L,Norway,0,"NLP, Azure, Spark, Scala, Tableau",PhD,5,Healthcare,2024-12-29,2025-01-14,2056,7,Smart Analytics +AI07279,AI Software Engineer,151206,USD,151206,EX,CT,Sweden,S,Sweden,100,"NLP, R, Kubernetes, Mathematics",Master,14,Energy,2024-12-23,2025-02-15,1491,8.2,Predictive Systems +AI07280,AI Product Manager,129233,JPY,14215630,SE,PT,Japan,S,Japan,50,"SQL, Tableau, Spark",Master,6,Telecommunications,2024-11-17,2024-12-30,1828,6,Cloud AI Solutions +AI07281,Data Engineer,126854,EUR,107826,MI,PT,Germany,L,Denmark,50,"Linux, Kubernetes, Docker, Hadoop",Bachelor,4,Retail,2024-01-23,2024-04-02,1955,6.9,Predictive Systems +AI07282,NLP Engineer,85718,CAD,107148,MI,PT,Canada,M,Canada,50,"GCP, Linux, Spark, PyTorch, R",Bachelor,3,Automotive,2025-01-23,2025-03-28,2152,5.8,Neural Networks Co +AI07283,ML Ops Engineer,79085,USD,79085,MI,FT,South Korea,L,Vietnam,100,"Data Visualization, Mathematics, Python, Git",PhD,4,Consulting,2025-02-11,2025-04-01,2363,5.5,Future Systems +AI07284,Robotics Engineer,95382,USD,95382,MI,FL,Sweden,M,Sweden,100,"Git, TensorFlow, Tableau, Docker, PyTorch",Bachelor,2,Education,2025-03-17,2025-04-21,1788,8.1,TechCorp Inc +AI07285,AI Consultant,114244,GBP,85683,MI,CT,United Kingdom,L,United Kingdom,100,"SQL, Scala, Deep Learning, Tableau",Bachelor,3,Manufacturing,2024-10-28,2024-12-12,1445,6.4,DeepTech Ventures +AI07286,Principal Data Scientist,86971,SGD,113062,EN,FT,Singapore,L,Singapore,0,"Docker, Git, MLOps",Associate,1,Gaming,2024-08-10,2024-09-24,2324,5,AI Innovations +AI07287,AI Product Manager,113959,SGD,148147,SE,PT,Singapore,M,Czech Republic,50,"Python, Mathematics, SQL",Bachelor,7,Consulting,2024-08-13,2024-10-08,1989,8.8,Algorithmic Solutions +AI07288,ML Ops Engineer,138785,USD,138785,SE,FL,South Korea,L,South Korea,0,"Deep Learning, Computer Vision, PyTorch, Java, MLOps",Master,9,Retail,2024-10-20,2024-12-07,1829,7.1,TechCorp Inc +AI07289,Robotics Engineer,122279,GBP,91709,MI,FT,United Kingdom,L,Ukraine,100,"Hadoop, AWS, MLOps, Scala",Associate,4,Retail,2024-06-13,2024-08-01,1295,8.6,DataVision Ltd +AI07290,NLP Engineer,46233,EUR,39298,EN,PT,Austria,S,Austria,100,"Computer Vision, AWS, Git, Tableau",Bachelor,0,Education,2024-07-16,2024-08-11,1131,7.3,Smart Analytics +AI07291,Machine Learning Researcher,298282,USD,298282,EX,FT,Denmark,L,Denmark,50,"Kubernetes, SQL, GCP, PyTorch, Mathematics",Associate,17,Telecommunications,2024-01-30,2024-03-27,1484,5.5,Machine Intelligence Group +AI07292,AI Architect,20587,USD,20587,EN,FL,India,M,Estonia,0,"Kubernetes, R, Computer Vision, Deep Learning",Associate,1,Energy,2024-12-05,2024-12-22,773,8.9,Algorithmic Solutions +AI07293,Data Scientist,85412,USD,85412,MI,PT,Ireland,L,Indonesia,100,"Deep Learning, Statistics, NLP, Kubernetes",Master,2,Government,2025-03-28,2025-06-06,2482,9.8,TechCorp Inc +AI07294,Deep Learning Engineer,164904,EUR,140168,SE,CT,Netherlands,L,Netherlands,100,"SQL, PyTorch, AWS, Scala, Java",Bachelor,9,Healthcare,2024-06-17,2024-08-03,2150,7.8,DataVision Ltd +AI07295,Principal Data Scientist,153719,EUR,130661,EX,FT,Austria,M,Austria,50,"SQL, AWS, Deep Learning, NLP, PyTorch",Associate,10,Healthcare,2024-10-21,2024-12-01,757,9,Predictive Systems +AI07296,Data Analyst,128775,EUR,109459,MI,CT,Netherlands,L,China,0,"Hadoop, PyTorch, Data Visualization, NLP",Master,3,Education,2025-01-07,2025-03-08,2131,7.3,Advanced Robotics +AI07297,AI Architect,74122,EUR,63004,MI,FT,Netherlands,S,Netherlands,50,"Azure, Kubernetes, GCP",Bachelor,3,Technology,2024-01-30,2024-02-28,1960,5.7,Cloud AI Solutions +AI07298,NLP Engineer,153979,USD,153979,EX,CT,Sweden,M,Sweden,50,"Python, Docker, MLOps",PhD,14,Automotive,2025-04-30,2025-07-04,698,9.7,AI Innovations +AI07299,Data Scientist,130397,CHF,117357,SE,CT,Switzerland,S,Switzerland,50,"Statistics, Hadoop, Azure, Java",PhD,9,Manufacturing,2025-02-27,2025-03-25,897,5.8,TechCorp Inc +AI07300,Autonomous Systems Engineer,79354,GBP,59516,EN,FT,United Kingdom,M,Ireland,0,"TensorFlow, Statistics, Docker",PhD,1,Media,2025-02-22,2025-03-12,1379,7.5,Quantum Computing Inc +AI07301,Data Scientist,120736,USD,120736,MI,FL,Ireland,L,Israel,0,"Azure, Linux, NLP",Associate,3,Energy,2024-11-08,2025-01-02,2417,6,Autonomous Tech +AI07302,Research Scientist,92591,USD,92591,SE,FT,Finland,S,Portugal,0,"Deep Learning, Python, GCP",Bachelor,6,Real Estate,2024-06-13,2024-07-23,1341,6.6,Smart Analytics +AI07303,Robotics Engineer,167422,USD,167422,SE,FL,Denmark,S,Denmark,100,"Python, Mathematics, Tableau, Deep Learning, SQL",Master,7,Gaming,2024-11-11,2024-12-18,1682,5.5,Cloud AI Solutions +AI07304,Research Scientist,43875,USD,43875,SE,CT,China,S,China,0,"Statistics, Kubernetes, SQL",Master,6,Healthcare,2024-11-25,2025-01-11,2385,9.1,Algorithmic Solutions +AI07305,Data Engineer,154370,EUR,131215,SE,PT,Austria,L,Austria,0,"Python, Spark, Statistics, Deep Learning, Java",Master,7,Education,2024-10-31,2024-12-07,1667,6,Future Systems +AI07306,Computer Vision Engineer,89756,CAD,112195,MI,PT,Canada,S,Canada,0,"Data Visualization, SQL, Azure, Kubernetes, Mathematics",PhD,2,Energy,2024-08-10,2024-09-19,2415,7.2,Advanced Robotics +AI07307,AI Specialist,58025,EUR,49321,EN,CT,Germany,S,Luxembourg,100,"R, SQL, NLP, Hadoop",Bachelor,1,Government,2024-10-08,2024-12-10,1563,7.1,DataVision Ltd +AI07308,Computer Vision Engineer,52365,EUR,44510,EN,PT,Netherlands,S,Netherlands,0,"Tableau, Linux, SQL, PyTorch",PhD,1,Manufacturing,2025-04-17,2025-05-03,1878,6.7,Machine Intelligence Group +AI07309,Research Scientist,252611,EUR,214719,EX,FL,Netherlands,L,Netherlands,100,"AWS, Data Visualization, MLOps, Spark",Associate,18,Media,2024-05-22,2024-06-28,787,9.3,DeepTech Ventures +AI07310,AI Consultant,292045,JPY,32124950,EX,FT,Japan,L,Japan,50,"Python, Scala, Hadoop, Linux, GCP",Bachelor,15,Telecommunications,2024-12-17,2025-02-16,1701,5.5,Autonomous Tech +AI07311,Research Scientist,180417,SGD,234542,EX,FL,Singapore,S,Singapore,100,"TensorFlow, Java, Tableau",Master,15,Transportation,2025-04-08,2025-04-23,1308,8.1,DataVision Ltd +AI07312,Deep Learning Engineer,65703,USD,65703,EN,FT,Ireland,S,United States,100,"Hadoop, Computer Vision, SQL, R, PyTorch",PhD,1,Gaming,2024-08-24,2024-09-07,1472,9.4,DataVision Ltd +AI07313,ML Ops Engineer,33627,USD,33627,MI,FT,India,L,India,0,"Hadoop, AWS, Kubernetes, NLP, Azure",Master,3,Automotive,2024-12-06,2025-01-03,1675,9.2,Neural Networks Co +AI07314,NLP Engineer,117069,CHF,105362,MI,PT,Switzerland,M,Nigeria,50,"PyTorch, GCP, Deep Learning, Docker, Tableau",Master,3,Automotive,2024-02-03,2024-03-01,1738,8.6,Predictive Systems +AI07315,Deep Learning Engineer,109443,EUR,93027,SE,CT,France,S,France,50,"Kubernetes, Python, Scala",PhD,8,Healthcare,2025-01-11,2025-03-04,2280,8.7,Digital Transformation LLC +AI07316,AI Software Engineer,114421,EUR,97258,MI,FL,Austria,L,Luxembourg,0,"Python, Tableau, Linux, Hadoop",Master,3,Manufacturing,2024-05-10,2024-07-14,1941,5.7,Neural Networks Co +AI07317,Head of AI,297806,USD,297806,EX,FT,United States,M,China,0,"Data Visualization, PyTorch, Tableau, GCP",Bachelor,15,Media,2024-11-07,2024-12-13,1644,9.3,DataVision Ltd +AI07318,Autonomous Systems Engineer,96103,JPY,10571330,MI,FL,Japan,M,Japan,0,"Java, Scala, Hadoop",Master,2,Technology,2024-08-30,2024-10-13,993,6.2,Advanced Robotics +AI07319,AI Consultant,104183,EUR,88556,MI,PT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, Scala",PhD,4,Automotive,2024-05-30,2024-07-27,1802,8.3,Quantum Computing Inc +AI07320,Research Scientist,203843,CHF,183459,SE,FT,Switzerland,L,Switzerland,100,"Docker, GCP, Hadoop, Computer Vision",Master,6,Transportation,2025-03-31,2025-05-17,1710,8.4,TechCorp Inc +AI07321,AI Specialist,159445,CHF,143501,SE,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Java, GCP",Master,9,Consulting,2025-04-17,2025-06-21,823,7.8,DeepTech Ventures +AI07322,Computer Vision Engineer,98252,USD,98252,SE,CT,Finland,S,Finland,50,"Azure, Tableau, AWS, Linux",Bachelor,7,Gaming,2024-12-14,2025-01-24,1131,6.2,Advanced Robotics +AI07323,Data Engineer,140598,USD,140598,SE,FL,Sweden,L,Switzerland,50,"Python, PyTorch, Docker",PhD,5,Energy,2024-02-08,2024-04-07,1530,6.6,Quantum Computing Inc +AI07324,Data Engineer,122530,USD,122530,SE,FT,Ireland,S,Ireland,0,"SQL, Tableau, Deep Learning",Master,5,Consulting,2025-03-06,2025-03-30,1123,8.1,Advanced Robotics +AI07325,AI Specialist,79216,USD,79216,EN,FT,United States,S,United States,100,"Kubernetes, Java, MLOps",Associate,0,Government,2024-11-24,2025-01-16,1296,5.6,Autonomous Tech +AI07326,AI Software Engineer,208065,USD,208065,EX,FT,South Korea,M,South Korea,100,"Azure, TensorFlow, R, Tableau",Master,14,Real Estate,2025-02-06,2025-04-03,1320,7.5,Digital Transformation LLC +AI07327,Data Engineer,212005,EUR,180204,EX,PT,Germany,M,Germany,0,"GCP, R, Python",PhD,10,Retail,2024-06-10,2024-07-16,1605,5.2,TechCorp Inc +AI07328,Computer Vision Engineer,142069,EUR,120759,SE,PT,Netherlands,L,Netherlands,0,"Data Visualization, Kubernetes, Scala, Python, Mathematics",Bachelor,7,Consulting,2024-11-23,2024-12-18,2476,5.3,Algorithmic Solutions +AI07329,NLP Engineer,189432,USD,189432,EX,PT,Israel,S,Nigeria,50,"GCP, R, SQL, TensorFlow, Java",Master,17,Manufacturing,2024-06-21,2024-08-15,1030,6.3,AI Innovations +AI07330,AI Architect,148090,USD,148090,EX,PT,United States,S,United States,100,"Mathematics, MLOps, Data Visualization, TensorFlow",Associate,13,Media,2025-01-26,2025-04-03,1491,8.1,Cognitive Computing +AI07331,Autonomous Systems Engineer,90214,AUD,121789,MI,FL,Australia,M,Singapore,100,"R, AWS, MLOps, Git",Bachelor,2,Government,2025-02-01,2025-03-13,1301,5.2,Algorithmic Solutions +AI07332,Autonomous Systems Engineer,179077,CAD,223846,EX,FT,Canada,M,Austria,100,"SQL, Data Visualization, MLOps, Mathematics, Java",Bachelor,11,Telecommunications,2024-01-21,2024-02-18,1876,5.3,DeepTech Ventures +AI07333,NLP Engineer,49419,AUD,66716,EN,PT,Australia,S,Australia,50,"AWS, Linux, Kubernetes, Git",Associate,1,Transportation,2025-03-31,2025-05-20,1252,7.8,Algorithmic Solutions +AI07334,Robotics Engineer,121147,USD,121147,SE,FL,Sweden,S,Sweden,50,"SQL, TensorFlow, Java, Scala",Associate,8,Retail,2025-02-22,2025-03-28,1565,9.6,Algorithmic Solutions +AI07335,AI Architect,246001,USD,246001,EX,FL,Ireland,M,Ireland,100,"Mathematics, GCP, SQL",Associate,17,Technology,2025-01-31,2025-03-07,955,6.3,Neural Networks Co +AI07336,Principal Data Scientist,52336,USD,52336,EN,PT,Israel,M,Israel,0,"Data Visualization, Statistics, NLP, Python, Computer Vision",Master,1,Government,2024-12-20,2025-02-01,1645,8.1,Machine Intelligence Group +AI07337,ML Ops Engineer,43262,EUR,36773,EN,PT,France,S,France,100,"Java, Git, Kubernetes, Python",Master,0,Transportation,2024-11-14,2025-01-11,639,5,Cloud AI Solutions +AI07338,Research Scientist,107059,EUR,91000,MI,PT,France,L,France,50,"Python, Java, NLP, AWS",Bachelor,4,Real Estate,2024-05-04,2024-05-18,654,5.4,Machine Intelligence Group +AI07339,Autonomous Systems Engineer,77881,EUR,66199,MI,CT,France,S,Sweden,0,"GCP, Java, Python, Deep Learning",Bachelor,3,Consulting,2024-08-15,2024-09-21,1815,5.6,Cognitive Computing +AI07340,Head of AI,77351,CAD,96689,MI,PT,Canada,M,Italy,0,"PyTorch, TensorFlow, MLOps",Associate,2,Finance,2024-03-15,2024-04-25,1356,9.2,Cloud AI Solutions +AI07341,Principal Data Scientist,148317,USD,148317,EX,FT,United States,S,China,0,"MLOps, Tableau, Python, Docker, Linux",Bachelor,10,Government,2024-01-12,2024-02-04,1930,9.4,Neural Networks Co +AI07342,AI Research Scientist,185184,CHF,166666,SE,FL,Switzerland,M,Switzerland,0,"MLOps, Mathematics, Python, TensorFlow",PhD,9,Healthcare,2024-11-01,2024-12-22,1638,6.6,Quantum Computing Inc +AI07343,AI Consultant,215064,EUR,182804,EX,CT,Austria,L,Austria,50,"PyTorch, SQL, Spark, Computer Vision, Mathematics",PhD,11,Telecommunications,2024-07-12,2024-07-26,581,8.7,Algorithmic Solutions +AI07344,Deep Learning Engineer,38054,USD,38054,EN,FL,South Korea,S,South Korea,100,"Computer Vision, Kubernetes, Mathematics",Associate,0,Government,2024-12-07,2024-12-23,1966,7.2,Predictive Systems +AI07345,Data Engineer,297668,SGD,386968,EX,FT,Singapore,L,Ireland,50,"Kubernetes, SQL, Docker",Master,16,Healthcare,2025-04-16,2025-05-04,1714,7.5,Digital Transformation LLC +AI07346,Machine Learning Engineer,72953,SGD,94839,EN,FT,Singapore,S,Russia,0,"Deep Learning, Data Visualization, Hadoop",Bachelor,1,Consulting,2024-08-17,2024-10-20,706,8.1,AI Innovations +AI07347,ML Ops Engineer,145761,EUR,123897,SE,FT,Netherlands,L,Netherlands,50,"Linux, Hadoop, Mathematics",PhD,8,Healthcare,2024-03-16,2024-04-01,756,5.4,DeepTech Ventures +AI07348,Computer Vision Engineer,203224,USD,203224,SE,PT,Norway,L,Norway,0,"AWS, Azure, Hadoop, Spark",Associate,6,Energy,2024-07-26,2024-08-27,1287,7.6,DataVision Ltd +AI07349,Computer Vision Engineer,242702,EUR,206297,EX,CT,Netherlands,L,Netherlands,0,"SQL, AWS, Computer Vision, Kubernetes, Spark",Associate,14,Finance,2024-05-31,2024-08-10,882,8.1,Smart Analytics +AI07350,Machine Learning Engineer,46733,CAD,58416,EN,FT,Canada,S,Canada,0,"GCP, Linux, Hadoop",Master,0,Automotive,2024-09-16,2024-11-07,698,9.2,Digital Transformation LLC +AI07351,Machine Learning Researcher,85044,USD,85044,MI,CT,Norway,S,Norway,0,"Computer Vision, Linux, SQL, TensorFlow",Master,2,Transportation,2024-09-14,2024-09-28,933,5.4,Machine Intelligence Group +AI07352,AI Specialist,90679,EUR,77077,MI,PT,France,L,Sweden,0,"PyTorch, Deep Learning, Azure, Computer Vision",Associate,4,Technology,2024-09-25,2024-11-05,2118,6.7,Quantum Computing Inc +AI07353,ML Ops Engineer,81449,EUR,69232,MI,CT,Netherlands,M,Netherlands,0,"Linux, Java, Computer Vision",Associate,2,Transportation,2024-09-17,2024-11-27,1721,8.7,Autonomous Tech +AI07354,ML Ops Engineer,79173,EUR,67297,EN,CT,France,L,France,50,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Energy,2025-01-10,2025-03-19,1994,7.1,Quantum Computing Inc +AI07355,Machine Learning Researcher,266789,USD,266789,EX,FL,Denmark,M,Denmark,100,"Kubernetes, Linux, Tableau, TensorFlow",PhD,16,Government,2024-08-28,2024-10-23,693,9.9,Machine Intelligence Group +AI07356,Machine Learning Researcher,170028,CHF,153025,SE,FL,Switzerland,S,Switzerland,50,"Azure, Deep Learning, Tableau, R",Associate,8,Gaming,2024-10-10,2024-12-10,1166,7.2,Predictive Systems +AI07357,AI Software Engineer,26042,USD,26042,EN,PT,India,L,Vietnam,50,"Kubernetes, Git, Mathematics, Python",PhD,0,Transportation,2025-01-01,2025-02-25,2059,5.7,Cognitive Computing +AI07358,NLP Engineer,192917,EUR,163979,EX,PT,France,M,France,50,"Kubernetes, Linux, GCP, Java, R",Bachelor,15,Consulting,2025-04-16,2025-05-10,1803,9.1,DataVision Ltd +AI07359,Head of AI,106638,USD,106638,MI,CT,Finland,L,Czech Republic,100,"Kubernetes, MLOps, Deep Learning, Python",Bachelor,2,Finance,2024-07-26,2024-08-09,1911,9.4,DataVision Ltd +AI07360,Machine Learning Researcher,76474,USD,76474,EX,FL,India,M,India,50,"Git, Statistics, Computer Vision, Deep Learning, R",Bachelor,10,Energy,2024-01-14,2024-02-27,585,7.9,Quantum Computing Inc +AI07361,AI Architect,177950,USD,177950,SE,FT,United States,M,United States,50,"TensorFlow, R, AWS, Mathematics, Computer Vision",PhD,5,Media,2024-11-04,2024-12-09,2298,6.1,Advanced Robotics +AI07362,Machine Learning Researcher,104483,CHF,94035,MI,FL,Switzerland,S,Switzerland,50,"MLOps, Kubernetes, Tableau, Hadoop, Mathematics",Associate,2,Healthcare,2024-10-19,2024-12-13,2315,6.7,Smart Analytics +AI07363,ML Ops Engineer,64384,JPY,7082240,EN,FL,Japan,L,Turkey,0,"Python, TensorFlow, MLOps, GCP",Associate,1,Education,2024-12-06,2024-12-20,1208,6.2,Cognitive Computing +AI07364,AI Consultant,50482,SGD,65627,EN,PT,Singapore,S,Singapore,100,"PyTorch, Hadoop, Deep Learning",Associate,1,Real Estate,2024-09-22,2024-11-01,2204,7.6,Algorithmic Solutions +AI07365,Data Scientist,151120,EUR,128452,SE,FL,Germany,L,Germany,50,"Linux, R, SQL, Spark, TensorFlow",Bachelor,5,Healthcare,2024-08-11,2024-09-26,1422,8.1,Autonomous Tech +AI07366,AI Research Scientist,145148,USD,145148,MI,FL,Norway,L,Norway,50,"TensorFlow, Spark, Computer Vision, Linux",Associate,3,Media,2025-03-06,2025-04-15,2298,8,Algorithmic Solutions +AI07367,Machine Learning Researcher,46232,CAD,57790,EN,PT,Canada,S,Canada,100,"Data Visualization, Azure, PyTorch",Master,0,Telecommunications,2024-07-28,2024-09-01,1275,8.8,Quantum Computing Inc +AI07368,Data Engineer,192522,CAD,240653,EX,FT,Canada,L,Canada,100,"Kubernetes, GCP, AWS, Git, NLP",Master,10,Finance,2024-10-19,2024-12-31,2175,8.2,Algorithmic Solutions +AI07369,Machine Learning Researcher,227433,USD,227433,EX,FT,Sweden,L,Sweden,0,"Python, R, SQL",Associate,18,Government,2024-10-07,2024-11-11,543,7.2,DeepTech Ventures +AI07370,Data Analyst,104134,USD,104134,SE,PT,Finland,M,Finland,0,"AWS, Git, Java, Azure, Python",Associate,5,Energy,2024-11-17,2024-12-20,1295,7.5,Cloud AI Solutions +AI07371,Computer Vision Engineer,193260,USD,193260,SE,PT,Norway,L,Norway,0,"Computer Vision, Data Visualization, Python",Master,7,Finance,2024-06-01,2024-08-04,1662,8.4,Digital Transformation LLC +AI07372,AI Research Scientist,215088,EUR,182825,EX,CT,Germany,M,Germany,50,"Scala, NLP, R, GCP, Python",Associate,15,Gaming,2024-01-20,2024-03-26,1288,6.2,Machine Intelligence Group +AI07373,Autonomous Systems Engineer,74692,USD,74692,MI,FT,Sweden,M,Sweden,0,"SQL, Linux, Statistics",Associate,4,Technology,2024-05-28,2024-08-05,1682,7.3,DataVision Ltd +AI07374,Deep Learning Engineer,89378,EUR,75971,MI,FT,France,S,France,50,"Linux, GCP, Computer Vision",Bachelor,2,Technology,2024-10-01,2024-12-05,2365,5,Advanced Robotics +AI07375,AI Consultant,222964,USD,222964,EX,FL,Finland,L,Colombia,0,"R, Spark, Linux, Java",Bachelor,17,Finance,2024-10-15,2024-12-04,1826,6.1,Machine Intelligence Group +AI07376,Robotics Engineer,219494,USD,219494,EX,CT,Ireland,L,Hungary,50,"AWS, Azure, SQL, Statistics, Git",Associate,17,Transportation,2024-07-05,2024-08-21,996,5.5,Neural Networks Co +AI07377,AI Research Scientist,132643,EUR,112747,SE,CT,Netherlands,M,Netherlands,50,"TensorFlow, NLP, Linux, GCP, Data Visualization",Associate,9,Telecommunications,2024-07-08,2024-09-03,920,8.3,AI Innovations +AI07378,Data Engineer,54621,USD,54621,EX,PT,India,M,Brazil,0,"Hadoop, Python, R, SQL",Associate,18,Real Estate,2024-07-08,2024-08-09,1912,5.8,DataVision Ltd +AI07379,Deep Learning Engineer,149274,GBP,111956,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, Java, PyTorch, Spark, Docker",PhD,5,Energy,2024-11-02,2025-01-09,834,5.2,Cloud AI Solutions +AI07380,AI Software Engineer,79871,SGD,103832,EN,FL,Singapore,L,Singapore,50,"MLOps, SQL, Azure, Mathematics",PhD,0,Retail,2025-04-30,2025-05-18,2489,5.3,Algorithmic Solutions +AI07381,Data Engineer,240902,USD,240902,EX,PT,Sweden,M,Philippines,100,"GCP, Data Visualization, Python",PhD,12,Automotive,2025-01-05,2025-01-23,1762,7.9,DeepTech Ventures +AI07382,Principal Data Scientist,88819,CAD,111024,MI,FL,Canada,M,Canada,100,"Kubernetes, PyTorch, Git",PhD,3,Gaming,2025-01-26,2025-03-13,1594,8.5,Smart Analytics +AI07383,AI Software Engineer,245168,JPY,26968480,EX,FT,Japan,L,Norway,100,"SQL, AWS, Linux, Spark",PhD,11,Telecommunications,2024-10-04,2024-11-17,1753,7,Machine Intelligence Group +AI07384,Research Scientist,226851,USD,226851,EX,FL,Finland,L,Finland,50,"Azure, Linux, Data Visualization, Git, Kubernetes",Associate,17,Consulting,2025-01-17,2025-03-15,1652,9.6,DataVision Ltd +AI07385,AI Architect,65693,USD,65693,MI,PT,South Korea,M,Russia,50,"Linux, Hadoop, Computer Vision",Bachelor,2,Energy,2024-02-22,2024-03-10,910,8.2,Cloud AI Solutions +AI07386,Computer Vision Engineer,173491,EUR,147467,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, Mathematics, Statistics",PhD,9,Gaming,2025-04-01,2025-06-09,515,8.3,AI Innovations +AI07387,Head of AI,78460,CAD,98075,MI,PT,Canada,M,Argentina,50,"Scala, Hadoop, Deep Learning",Bachelor,3,Automotive,2025-01-16,2025-03-30,2303,5.9,Cloud AI Solutions +AI07388,AI Specialist,87156,USD,87156,MI,FT,Sweden,M,Czech Republic,0,"Computer Vision, Scala, Python, TensorFlow",PhD,2,Transportation,2024-03-27,2024-05-18,2028,8.5,AI Innovations +AI07389,Data Engineer,251231,CHF,226108,EX,PT,Switzerland,S,Switzerland,100,"Docker, Linux, Python, Data Visualization, TensorFlow",PhD,17,Media,2024-03-28,2024-05-17,1025,8.3,AI Innovations +AI07390,Data Engineer,75609,USD,75609,EN,FT,Denmark,M,Denmark,50,"Docker, Spark, R, Hadoop",PhD,1,Gaming,2025-04-20,2025-06-25,1240,9.5,Predictive Systems +AI07391,Data Scientist,85774,USD,85774,MI,CT,Sweden,M,Latvia,50,"MLOps, Linux, Mathematics",Bachelor,4,Telecommunications,2024-05-04,2024-07-03,1310,6.9,Smart Analytics +AI07392,Robotics Engineer,270769,USD,270769,EX,PT,Israel,L,Israel,100,"Kubernetes, R, MLOps",PhD,14,Gaming,2025-01-07,2025-03-21,1665,9.4,DataVision Ltd +AI07393,Data Scientist,56999,USD,56999,EN,CT,United States,S,United States,50,"Spark, Data Visualization, AWS, Kubernetes, Hadoop",Associate,1,Transportation,2024-07-25,2024-08-28,1690,5.6,Smart Analytics +AI07394,ML Ops Engineer,95205,EUR,80924,SE,PT,Germany,S,Germany,0,"Python, Scala, MLOps, Statistics",Associate,5,Real Estate,2024-01-19,2024-02-09,923,7.5,Future Systems +AI07395,Data Analyst,116878,USD,116878,SE,FL,South Korea,L,South Korea,100,"Python, TensorFlow, Data Visualization, Computer Vision, Azure",PhD,8,Telecommunications,2024-07-27,2024-10-03,1058,8.2,DataVision Ltd +AI07396,Autonomous Systems Engineer,92083,CAD,115104,MI,FT,Canada,S,Canada,0,"Kubernetes, Linux, R",Bachelor,3,Finance,2024-05-25,2024-07-02,1467,7,Digital Transformation LLC +AI07397,Head of AI,89908,USD,89908,EN,FT,Denmark,L,Denmark,50,"Git, Azure, SQL, Kubernetes",Bachelor,1,Media,2024-01-26,2024-03-01,989,9.4,AI Innovations +AI07398,AI Architect,82155,EUR,69832,MI,CT,France,M,France,50,"Linux, Git, Computer Vision, PyTorch",Associate,2,Real Estate,2024-05-16,2024-06-21,2168,5.9,Future Systems +AI07399,Research Scientist,250839,USD,250839,EX,FT,Finland,L,Finland,100,"SQL, Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,15,Real Estate,2024-02-08,2024-03-25,1727,6.1,Future Systems +AI07400,Autonomous Systems Engineer,141610,USD,141610,SE,FT,United States,L,United States,100,"Python, TensorFlow, Data Visualization, MLOps",PhD,7,Manufacturing,2025-02-07,2025-03-15,2115,8.5,Predictive Systems +AI07401,ML Ops Engineer,134017,USD,134017,SE,FT,Denmark,S,Denmark,0,"Linux, SQL, Statistics, R",PhD,9,Government,2025-02-14,2025-03-31,1735,5.1,Advanced Robotics +AI07402,AI Specialist,287847,EUR,244670,EX,FL,Netherlands,L,Netherlands,100,"SQL, TensorFlow, PyTorch",Master,19,Manufacturing,2024-09-22,2024-10-20,1149,5.7,DataVision Ltd +AI07403,AI Research Scientist,72341,USD,72341,EX,FT,India,M,Turkey,100,"GCP, Computer Vision, Spark, Java, R",Bachelor,15,Telecommunications,2024-08-11,2024-09-10,2228,8,AI Innovations +AI07404,ML Ops Engineer,196644,EUR,167147,EX,CT,France,S,Turkey,0,"GCP, Computer Vision, Data Visualization, Scala",Bachelor,16,Finance,2024-07-11,2024-08-16,2103,5.2,DataVision Ltd +AI07405,AI Consultant,80695,GBP,60521,MI,FT,United Kingdom,M,United Kingdom,100,"NLP, Computer Vision, PyTorch, TensorFlow",Bachelor,4,Manufacturing,2025-02-13,2025-03-05,1974,5.5,Autonomous Tech +AI07406,Robotics Engineer,112650,USD,112650,EN,FL,Denmark,L,Denmark,50,"Kubernetes, Hadoop, Mathematics, Git",Associate,0,Transportation,2024-03-12,2024-04-20,1124,7,Algorithmic Solutions +AI07407,AI Product Manager,138862,USD,138862,MI,FT,United States,L,United States,50,"Hadoop, Mathematics, MLOps",Associate,3,Transportation,2024-07-18,2024-08-03,1894,6.7,Quantum Computing Inc +AI07408,Machine Learning Engineer,92680,CHF,83412,EN,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, MLOps, SQL, Deep Learning",Bachelor,1,Real Estate,2024-05-10,2024-07-01,974,8.1,Cognitive Computing +AI07409,AI Software Engineer,106542,USD,106542,EN,CT,United States,L,United States,0,"Scala, PyTorch, Data Visualization, Tableau",Bachelor,0,Healthcare,2024-05-16,2024-06-19,1892,5.1,Advanced Robotics +AI07410,Machine Learning Engineer,57987,EUR,49289,EN,CT,Germany,S,United States,0,"Docker, Mathematics, TensorFlow",PhD,0,Manufacturing,2025-04-15,2025-05-07,2129,8.9,DeepTech Ventures +AI07411,Machine Learning Engineer,224659,USD,224659,EX,PT,Finland,L,Vietnam,50,"SQL, PyTorch, Kubernetes",Associate,15,Education,2024-08-30,2024-09-14,585,6.2,Quantum Computing Inc +AI07412,AI Consultant,223546,CHF,201191,EX,FT,Switzerland,M,South Korea,100,"TensorFlow, Azure, AWS, GCP, MLOps",PhD,12,Retail,2024-07-08,2024-08-07,1511,9,Digital Transformation LLC +AI07413,AI Research Scientist,151758,CHF,136582,MI,CT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Azure, Computer Vision, NLP",Master,3,Education,2024-04-09,2024-05-05,946,9.4,Quantum Computing Inc +AI07414,AI Specialist,46742,USD,46742,EN,CT,Sweden,S,Italy,50,"NLP, Deep Learning, SQL, Tableau, Hadoop",Master,1,Retail,2024-04-24,2024-07-06,1123,6.7,Algorithmic Solutions +AI07415,AI Software Engineer,159242,USD,159242,EX,PT,Finland,S,Finland,100,"Kubernetes, Deep Learning, Data Visualization, GCP",Associate,10,Real Estate,2024-12-31,2025-02-08,1926,6.1,Future Systems +AI07416,Data Analyst,87254,USD,87254,EN,FT,Norway,S,Brazil,0,"Hadoop, Scala, Data Visualization, SQL",Associate,1,Retail,2024-08-12,2024-10-08,992,6.8,Cloud AI Solutions +AI07417,AI Research Scientist,62366,USD,62366,EN,CT,Finland,M,Singapore,50,"Spark, SQL, Hadoop, AWS",PhD,1,Gaming,2024-02-21,2024-04-02,1969,5.4,Cognitive Computing +AI07418,Data Scientist,194278,USD,194278,SE,FL,Norway,L,Israel,50,"Java, Statistics, Deep Learning, Tableau",Master,7,Media,2024-10-24,2024-12-09,809,8.9,Autonomous Tech +AI07419,AI Product Manager,107060,SGD,139178,SE,CT,Singapore,S,Singapore,100,"Statistics, R, Spark, Deep Learning, Linux",PhD,9,Retail,2025-01-31,2025-04-09,884,9.5,Machine Intelligence Group +AI07420,AI Product Manager,125649,USD,125649,SE,FL,Ireland,L,Ireland,50,"Linux, Spark, Data Visualization, NLP",PhD,5,Automotive,2025-03-29,2025-06-06,1974,10,Machine Intelligence Group +AI07421,AI Architect,151908,USD,151908,EX,PT,Sweden,M,Sweden,100,"Tableau, Computer Vision, PyTorch, SQL, Python",Bachelor,10,Gaming,2024-02-24,2024-05-01,1600,9.1,Machine Intelligence Group +AI07422,ML Ops Engineer,207008,CHF,186307,SE,CT,Switzerland,M,Switzerland,0,"Hadoop, MLOps, Deep Learning, GCP",PhD,7,Retail,2024-05-05,2024-06-01,1235,9,Smart Analytics +AI07423,Data Scientist,93359,CHF,84023,EN,CT,Switzerland,S,Switzerland,100,"Linux, Kubernetes, SQL, Java, Deep Learning",Bachelor,1,Telecommunications,2025-01-02,2025-02-02,1179,9.9,TechCorp Inc +AI07424,AI Research Scientist,102494,AUD,138367,MI,FL,Australia,L,Australia,0,"SQL, R, Mathematics, Linux",Master,4,Automotive,2024-07-18,2024-08-23,1974,5.4,Cloud AI Solutions +AI07425,NLP Engineer,82281,EUR,69939,MI,FL,France,M,France,50,"SQL, Spark, Hadoop",PhD,4,Technology,2024-08-16,2024-09-18,828,6,Algorithmic Solutions +AI07426,Deep Learning Engineer,148607,USD,148607,SE,FT,Finland,L,Finland,0,"Git, Spark, NLP, Computer Vision",Bachelor,9,Finance,2024-10-18,2024-11-04,1627,8.7,AI Innovations +AI07427,Autonomous Systems Engineer,97107,USD,97107,MI,FL,Finland,M,Finland,50,"PyTorch, NLP, Kubernetes, Azure",PhD,4,Finance,2025-01-23,2025-03-19,596,7.2,Neural Networks Co +AI07428,Data Engineer,156750,USD,156750,SE,CT,Norway,S,Norway,50,"Java, Tableau, Scala",PhD,6,Gaming,2024-06-24,2024-07-20,617,6.3,Future Systems +AI07429,Data Scientist,43046,USD,43046,MI,CT,China,M,Mexico,100,"Hadoop, Kubernetes, NLP",Master,4,Telecommunications,2024-07-28,2024-09-04,532,7.9,Advanced Robotics +AI07430,Autonomous Systems Engineer,259249,CAD,324061,EX,FL,Canada,L,Canada,50,"Data Visualization, Linux, SQL, R",Master,13,Real Estate,2024-11-16,2025-01-19,1880,8.9,Neural Networks Co +AI07431,Research Scientist,76203,USD,76203,MI,FT,Sweden,S,Sweden,0,"TensorFlow, R, Git, AWS, Computer Vision",PhD,2,Government,2024-01-09,2024-03-20,2304,9,Predictive Systems +AI07432,Data Engineer,145647,USD,145647,SE,PT,Denmark,M,Philippines,100,"Data Visualization, TensorFlow, Kubernetes, NLP, Deep Learning",PhD,8,Transportation,2024-07-05,2024-09-09,1327,8.5,Algorithmic Solutions +AI07433,AI Specialist,61066,EUR,51906,EN,CT,Netherlands,S,Portugal,0,"Scala, Computer Vision, Python, Docker, TensorFlow",Master,1,Technology,2024-03-15,2024-05-11,2259,6.9,Digital Transformation LLC +AI07434,AI Specialist,186576,USD,186576,SE,CT,Norway,M,Norway,100,"Git, Azure, Data Visualization, PyTorch",PhD,6,Automotive,2025-04-15,2025-06-04,1906,8.8,TechCorp Inc +AI07435,Machine Learning Researcher,132277,USD,132277,SE,CT,Ireland,L,Ireland,0,"Docker, GCP, Linux",Bachelor,9,Telecommunications,2024-04-04,2024-05-05,820,8.4,Machine Intelligence Group +AI07436,NLP Engineer,170334,USD,170334,SE,FL,United States,M,Poland,50,"Spark, R, Git",Bachelor,7,Retail,2025-02-01,2025-03-04,807,6,Cognitive Computing +AI07437,AI Research Scientist,124463,USD,124463,SE,CT,South Korea,M,South Korea,100,"TensorFlow, SQL, NLP, MLOps, Deep Learning",PhD,8,Finance,2024-04-24,2024-05-19,2246,6.2,Cognitive Computing +AI07438,AI Specialist,82706,USD,82706,MI,CT,Sweden,S,Sweden,50,"MLOps, Deep Learning, TensorFlow, NLP",PhD,4,Healthcare,2024-11-15,2025-01-18,756,9,Cognitive Computing +AI07439,AI Architect,250961,CHF,225865,EX,FL,Switzerland,M,Switzerland,100,"Spark, MLOps, Kubernetes, Linux",Bachelor,13,Real Estate,2024-04-07,2024-05-06,1666,9.8,Neural Networks Co +AI07440,AI Consultant,77065,EUR,65505,EN,CT,Germany,L,Denmark,50,"TensorFlow, SQL, AWS",PhD,0,Automotive,2025-04-28,2025-06-26,2078,5.5,Autonomous Tech +AI07441,AI Consultant,60980,AUD,82323,EN,FL,Australia,M,Norway,100,"Python, NLP, TensorFlow, Deep Learning",PhD,1,Energy,2024-10-27,2024-11-30,1528,7.9,Algorithmic Solutions +AI07442,Principal Data Scientist,122642,JPY,13490620,SE,FT,Japan,M,Canada,0,"MLOps, Java, Data Visualization, Hadoop, Python",Associate,6,Automotive,2024-09-04,2024-11-04,1486,8.7,Smart Analytics +AI07443,Machine Learning Researcher,126416,USD,126416,MI,FT,Norway,S,Norway,0,"Spark, Mathematics, Python",Master,2,Retail,2024-06-03,2024-07-07,1354,7.2,DataVision Ltd +AI07444,Data Analyst,43069,USD,43069,EN,FT,China,L,China,50,"Java, Python, Git, Spark, TensorFlow",Bachelor,1,Real Estate,2024-05-15,2024-07-09,2034,8.9,Autonomous Tech +AI07445,AI Product Manager,191754,SGD,249280,EX,FL,Singapore,L,Singapore,0,"Spark, MLOps, Docker, NLP, TensorFlow",Master,19,Manufacturing,2024-01-26,2024-03-13,1056,6.3,Future Systems +AI07446,Principal Data Scientist,89978,SGD,116971,MI,PT,Singapore,S,Singapore,100,"PyTorch, TensorFlow, Data Visualization, Computer Vision",PhD,4,Gaming,2025-03-19,2025-05-31,2223,6.2,Predictive Systems +AI07447,Deep Learning Engineer,69497,SGD,90346,EN,CT,Singapore,M,Singapore,0,"Tableau, Python, TensorFlow, NLP, Computer Vision",Associate,1,Education,2024-11-02,2024-12-27,2304,7,Digital Transformation LLC +AI07448,NLP Engineer,68144,CAD,85180,EN,CT,Canada,L,Poland,100,"Kubernetes, Scala, GCP, Docker, Hadoop",PhD,0,Gaming,2024-09-03,2024-11-09,1002,5.6,Predictive Systems +AI07449,Machine Learning Researcher,245939,JPY,27053290,EX,FL,Japan,L,Japan,50,"SQL, Data Visualization, Python",PhD,15,Retail,2025-04-07,2025-06-19,1029,6.1,Cloud AI Solutions +AI07450,Computer Vision Engineer,143618,EUR,122075,EX,CT,France,M,France,100,"Docker, GCP, NLP, Azure, Kubernetes",Master,12,Energy,2024-01-11,2024-03-02,1998,6.3,Cloud AI Solutions +AI07451,AI Software Engineer,118901,EUR,101066,MI,FL,Netherlands,L,Netherlands,100,"Linux, Java, Statistics",Bachelor,4,Transportation,2024-02-11,2024-03-09,2248,5.5,Algorithmic Solutions +AI07452,AI Research Scientist,31907,USD,31907,MI,PT,India,S,India,0,"MLOps, Spark, Linux, Data Visualization, NLP",PhD,4,Real Estate,2025-03-26,2025-05-25,2009,8.9,Quantum Computing Inc +AI07453,AI Specialist,165521,USD,165521,EX,PT,Sweden,M,Sweden,0,"Computer Vision, R, Linux",Master,16,Healthcare,2024-02-17,2024-03-09,993,9.5,Neural Networks Co +AI07454,Principal Data Scientist,143655,USD,143655,SE,FL,Finland,L,Finland,100,"MLOps, Spark, Java, NLP, SQL",Associate,7,Media,2024-01-01,2024-02-16,1009,5.6,DeepTech Ventures +AI07455,Data Engineer,18305,USD,18305,EN,CT,India,M,India,0,"SQL, AWS, Spark",Bachelor,1,Finance,2024-01-02,2024-01-18,1652,5.8,Autonomous Tech +AI07456,Principal Data Scientist,103388,CHF,93049,EN,PT,Switzerland,L,Israel,0,"SQL, Mathematics, Spark, TensorFlow",Associate,0,Education,2025-04-26,2025-07-06,1717,5.4,Digital Transformation LLC +AI07457,Autonomous Systems Engineer,216271,USD,216271,EX,FL,Israel,M,Israel,100,"Python, Linux, Java, TensorFlow",Master,14,Energy,2024-10-25,2024-12-10,666,6.3,Future Systems +AI07458,Autonomous Systems Engineer,54685,JPY,6015350,EN,PT,Japan,M,Japan,50,"Python, Linux, Hadoop, Data Visualization",Master,0,Media,2024-08-28,2024-11-03,1196,6.3,Neural Networks Co +AI07459,ML Ops Engineer,101910,USD,101910,SE,FT,South Korea,M,Canada,50,"Tableau, GCP, Azure",Master,6,Real Estate,2025-04-15,2025-06-11,1897,7.4,Algorithmic Solutions +AI07460,Deep Learning Engineer,232335,JPY,25556850,EX,FL,Japan,M,Japan,100,"Scala, Spark, Java, SQL",Master,19,Technology,2024-10-18,2024-12-11,606,9.1,Machine Intelligence Group +AI07461,Machine Learning Engineer,196676,GBP,147507,EX,PT,United Kingdom,S,United Kingdom,50,"Linux, Azure, TensorFlow, Tableau, PyTorch",Associate,18,Technology,2024-02-11,2024-02-29,1568,8.1,AI Innovations +AI07462,Machine Learning Engineer,97001,USD,97001,MI,PT,United States,M,Singapore,100,"PyTorch, Java, Mathematics, Deep Learning",Associate,2,Healthcare,2024-07-30,2024-08-17,1730,8.6,DeepTech Ventures +AI07463,AI Software Engineer,141916,EUR,120629,SE,FL,Germany,L,Germany,100,"Python, TensorFlow, Azure",Master,9,Manufacturing,2024-10-20,2024-11-28,2447,6.7,Advanced Robotics +AI07464,Machine Learning Engineer,58453,USD,58453,EN,FT,United States,S,Malaysia,0,"Linux, Azure, Statistics",PhD,1,Gaming,2024-01-25,2024-02-08,524,9.4,TechCorp Inc +AI07465,AI Architect,65377,EUR,55570,EN,FT,Germany,M,Germany,0,"SQL, Statistics, AWS, Docker",Master,0,Technology,2024-04-17,2024-06-19,1603,5.8,DeepTech Ventures +AI07466,Machine Learning Engineer,84606,SGD,109988,MI,FL,Singapore,S,Singapore,100,"GCP, NLP, Python, Data Visualization, Spark",Master,3,Government,2024-10-21,2024-11-08,2113,9.1,TechCorp Inc +AI07467,ML Ops Engineer,61087,EUR,51924,EN,FT,France,M,France,0,"NLP, R, MLOps",Master,0,Automotive,2025-04-26,2025-06-18,2334,6.1,Quantum Computing Inc +AI07468,NLP Engineer,66540,AUD,89829,EN,FL,Australia,M,China,0,"Spark, Docker, PyTorch, Computer Vision",PhD,0,Healthcare,2024-06-28,2024-08-14,2020,7.2,DeepTech Ventures +AI07469,Machine Learning Researcher,148528,USD,148528,SE,FT,Israel,L,Israel,0,"MLOps, Java, AWS, Deep Learning",Master,9,Telecommunications,2025-01-23,2025-03-09,874,7.4,Smart Analytics +AI07470,Deep Learning Engineer,126440,USD,126440,EX,FT,South Korea,S,South Korea,100,"R, Computer Vision, Scala, Java",Associate,18,Transportation,2024-09-04,2024-09-23,764,5.9,DataVision Ltd +AI07471,Research Scientist,117780,CHF,106002,EN,FT,Switzerland,L,Switzerland,0,"Computer Vision, Data Visualization, Linux, MLOps",Bachelor,1,Finance,2025-04-28,2025-05-21,2477,6.3,DataVision Ltd +AI07472,AI Research Scientist,129661,USD,129661,EX,FT,Finland,M,Ukraine,50,"NLP, MLOps, Python, Spark, Mathematics",Master,10,Real Estate,2024-03-02,2024-04-02,914,6.2,Smart Analytics +AI07473,Robotics Engineer,46753,EUR,39740,EN,PT,Austria,S,Austria,0,"SQL, Hadoop, Statistics, Spark",Associate,0,Manufacturing,2024-05-25,2024-07-06,1228,6.7,TechCorp Inc +AI07474,Computer Vision Engineer,43491,USD,43491,EX,FL,India,S,Vietnam,0,"Azure, TensorFlow, Scala",Bachelor,12,Healthcare,2024-10-16,2024-12-15,1489,7.5,Autonomous Tech +AI07475,AI Architect,120298,SGD,156387,MI,PT,Singapore,L,Singapore,0,"Kubernetes, Git, Spark, Linux, SQL",PhD,3,Gaming,2024-02-25,2024-04-24,890,5.4,DataVision Ltd +AI07476,ML Ops Engineer,260872,USD,260872,EX,FT,Norway,S,Norway,0,"Java, Data Visualization, MLOps",Associate,13,Education,2025-03-23,2025-04-20,1870,5.4,AI Innovations +AI07477,Robotics Engineer,71601,AUD,96661,EN,FT,Australia,S,Australia,50,"Linux, Hadoop, AWS, Python, Deep Learning",Master,0,Education,2025-04-25,2025-06-10,1267,5.9,Algorithmic Solutions +AI07478,Machine Learning Engineer,49525,USD,49525,EX,FL,India,M,Portugal,50,"Docker, Git, GCP, Scala",PhD,15,Manufacturing,2024-04-28,2024-05-20,1446,8.2,AI Innovations +AI07479,AI Research Scientist,82352,USD,82352,EN,FL,Ireland,L,Ireland,50,"GCP, Python, Computer Vision",PhD,1,Healthcare,2024-04-25,2024-05-30,1036,9.6,Neural Networks Co +AI07480,Machine Learning Researcher,238897,USD,238897,EX,CT,Norway,M,Norway,0,"Git, Linux, Statistics",Bachelor,12,Transportation,2024-05-05,2024-06-11,638,7.1,Neural Networks Co +AI07481,AI Research Scientist,64610,USD,64610,EN,CT,Israel,L,Israel,100,"Spark, Kubernetes, Linux, GCP, AWS",PhD,1,Retail,2024-06-04,2024-07-04,552,6.9,Future Systems +AI07482,Principal Data Scientist,121207,USD,121207,EX,FL,Finland,S,Finland,50,"GCP, Git, Statistics",Associate,12,Healthcare,2024-08-10,2024-09-07,1835,8.7,AI Innovations +AI07483,AI Specialist,118359,JPY,13019490,SE,FL,Japan,M,Japan,50,"MLOps, Linux, Java, TensorFlow, Python",Associate,7,Media,2024-11-13,2024-12-24,1107,6.4,Algorithmic Solutions +AI07484,NLP Engineer,176333,CHF,158700,SE,FL,Switzerland,L,Switzerland,0,"Scala, Kubernetes, Deep Learning",Bachelor,8,Education,2024-11-03,2024-11-30,1123,5.5,Cognitive Computing +AI07485,AI Consultant,137799,USD,137799,SE,CT,Ireland,M,Ireland,50,"Spark, Python, Hadoop",Associate,8,Real Estate,2024-06-20,2024-08-31,1243,7.2,Quantum Computing Inc +AI07486,AI Architect,147983,USD,147983,EX,CT,Sweden,S,Russia,50,"SQL, TensorFlow, Tableau, AWS, Mathematics",Master,16,Energy,2025-02-06,2025-04-01,1503,8.1,Quantum Computing Inc +AI07487,AI Research Scientist,44458,USD,44458,EN,FT,Finland,S,Finland,0,"Azure, Scala, Tableau",Bachelor,0,Telecommunications,2024-03-26,2024-06-06,2344,5.6,Algorithmic Solutions +AI07488,ML Ops Engineer,182046,EUR,154739,EX,CT,Netherlands,M,Netherlands,0,"Python, Java, Linux, Statistics, Deep Learning",Bachelor,17,Retail,2024-02-02,2024-04-12,2221,6,DeepTech Ventures +AI07489,Robotics Engineer,89818,SGD,116763,EN,FL,Singapore,L,Singapore,100,"Java, PyTorch, GCP, Tableau",Master,0,Gaming,2024-03-29,2024-05-26,636,5.7,Machine Intelligence Group +AI07490,NLP Engineer,154108,GBP,115581,SE,CT,United Kingdom,M,New Zealand,0,"PyTorch, Kubernetes, Computer Vision",PhD,8,Manufacturing,2025-02-15,2025-04-01,1863,9.1,Machine Intelligence Group +AI07491,Autonomous Systems Engineer,77976,USD,77976,EN,FT,Ireland,M,Ireland,0,"SQL, GCP, Java, Hadoop, Data Visualization",Associate,1,Retail,2024-06-14,2024-07-24,2169,6.7,AI Innovations +AI07492,Computer Vision Engineer,158800,AUD,214380,SE,FT,Australia,L,Australia,100,"Kubernetes, Python, NLP, R",Associate,5,Technology,2024-08-04,2024-09-29,895,5.4,Digital Transformation LLC +AI07493,AI Software Engineer,269552,CHF,242597,EX,FL,Switzerland,L,Switzerland,50,"NLP, Kubernetes, Spark",Associate,16,Retail,2024-09-26,2024-11-21,1202,8.9,Cloud AI Solutions +AI07494,ML Ops Engineer,40777,USD,40777,SE,FT,India,M,India,50,"AWS, MLOps, Java, Scala",Associate,6,Telecommunications,2024-04-21,2024-05-20,1471,9.3,Future Systems +AI07495,Data Scientist,40524,USD,40524,EN,FL,China,L,China,0,"TensorFlow, Azure, MLOps, Linux",Master,1,Government,2024-01-20,2024-03-08,1447,7.8,DeepTech Ventures +AI07496,AI Product Manager,104604,USD,104604,SE,PT,Finland,S,Mexico,100,"NLP, Docker, Data Visualization, Python",Master,8,Retail,2024-03-17,2024-05-24,1519,7.1,Neural Networks Co +AI07497,Research Scientist,108828,GBP,81621,SE,FL,United Kingdom,S,Indonesia,50,"Python, Kubernetes, MLOps, Linux, Mathematics",Bachelor,7,Real Estate,2024-11-22,2024-12-14,2377,5.6,Digital Transformation LLC +AI07498,AI Product Manager,332899,USD,332899,EX,FL,Denmark,L,Denmark,0,"GCP, SQL, PyTorch",PhD,10,Telecommunications,2024-09-23,2024-10-12,786,8.8,Digital Transformation LLC +AI07499,AI Product Manager,282331,USD,282331,EX,FL,United States,M,United States,0,"Statistics, Tableau, Python, Computer Vision, TensorFlow",PhD,17,Media,2024-09-01,2024-10-17,2115,9.5,Predictive Systems +AI07500,Robotics Engineer,50649,USD,50649,MI,FT,China,L,China,0,"Computer Vision, Git, Hadoop",PhD,3,Government,2024-05-04,2024-07-05,754,7.3,Cognitive Computing +AI07501,AI Product Manager,74786,JPY,8226460,EN,FL,Japan,S,Ukraine,100,"AWS, Statistics, R, Hadoop, TensorFlow",Associate,1,Real Estate,2024-01-11,2024-01-30,1792,8,Cognitive Computing +AI07502,Machine Learning Engineer,246647,USD,246647,EX,CT,Denmark,L,Colombia,50,"Git, Linux, Python, Deep Learning, MLOps",Bachelor,11,Telecommunications,2024-05-12,2024-06-24,1926,8.9,Neural Networks Co +AI07503,Machine Learning Engineer,219909,USD,219909,EX,CT,Norway,S,Norway,0,"SQL, Java, Scala, Spark",Bachelor,17,Media,2024-09-06,2024-10-21,798,7.7,Quantum Computing Inc +AI07504,AI Research Scientist,137360,SGD,178568,EX,PT,Singapore,S,Norway,100,"MLOps, Azure, Scala, AWS",Master,13,Media,2025-03-29,2025-05-29,1811,9.3,DeepTech Ventures +AI07505,Data Analyst,80377,USD,80377,EN,CT,Sweden,M,United States,50,"PyTorch, Hadoop, TensorFlow, Computer Vision",Master,1,Healthcare,2024-05-15,2024-06-13,1584,6,Neural Networks Co +AI07506,AI Software Engineer,150710,JPY,16578100,SE,PT,Japan,L,Japan,100,"Mathematics, Spark, Docker, Statistics",PhD,6,Automotive,2024-06-13,2024-08-14,2040,5.4,Cognitive Computing +AI07507,Head of AI,165703,USD,165703,EX,CT,Israel,L,Ireland,50,"Kubernetes, GCP, Computer Vision",Master,16,Transportation,2025-03-29,2025-05-05,1006,6,AI Innovations +AI07508,AI Product Manager,89181,USD,89181,EN,FL,Denmark,S,Singapore,0,"Python, Azure, Mathematics",PhD,0,Energy,2025-02-18,2025-03-20,875,7.7,Smart Analytics +AI07509,Robotics Engineer,179770,CHF,161793,SE,FL,Switzerland,S,Switzerland,0,"NLP, GCP, Docker, Git, Azure",Associate,6,Manufacturing,2024-09-15,2024-10-17,2220,8.3,DataVision Ltd +AI07510,Machine Learning Researcher,148095,USD,148095,SE,FL,Sweden,M,Sweden,0,"Spark, Scala, Deep Learning, Hadoop",Associate,8,Media,2024-06-17,2024-08-16,784,9.3,Predictive Systems +AI07511,AI Software Engineer,86619,USD,86619,MI,PT,United States,S,Sweden,0,"Spark, GCP, Java, R",Bachelor,4,Government,2024-01-19,2024-03-27,1171,7.7,DeepTech Ventures +AI07512,Data Engineer,94298,USD,94298,SE,FL,South Korea,S,South Korea,100,"Scala, Computer Vision, Docker, Java",Associate,6,Energy,2024-11-06,2024-12-28,1362,6.9,Predictive Systems +AI07513,Computer Vision Engineer,196323,USD,196323,SE,CT,Norway,M,Norway,0,"PyTorch, SQL, Spark, TensorFlow",Master,8,Automotive,2024-12-13,2025-01-04,1981,6.6,Predictive Systems +AI07514,Robotics Engineer,21114,USD,21114,EN,CT,India,L,India,100,"Computer Vision, SQL, Tableau",PhD,0,Energy,2025-03-21,2025-04-15,2127,5.5,Autonomous Tech +AI07515,NLP Engineer,149569,EUR,127134,SE,FL,Austria,L,Austria,100,"Kubernetes, Git, SQL",Bachelor,5,Retail,2024-04-30,2024-06-24,2372,8.1,Future Systems +AI07516,Machine Learning Engineer,103038,USD,103038,MI,FL,Sweden,M,Sweden,0,"Computer Vision, Python, Java, Tableau",PhD,2,Energy,2025-03-14,2025-05-03,1504,7.8,Smart Analytics +AI07517,Head of AI,118703,USD,118703,SE,PT,Israel,M,Israel,50,"GCP, PyTorch, Docker",Associate,5,Gaming,2024-10-09,2024-12-04,536,5.4,Smart Analytics +AI07518,AI Consultant,65083,USD,65083,EN,FL,South Korea,L,Vietnam,50,"Linux, Deep Learning, Data Visualization, TensorFlow, Kubernetes",Bachelor,1,Media,2024-05-31,2024-07-21,2356,7.8,Autonomous Tech +AI07519,Data Analyst,143495,USD,143495,SE,PT,Norway,M,Norway,100,"PyTorch, AWS, Scala, Java",PhD,8,Gaming,2024-12-31,2025-01-18,811,7.4,Autonomous Tech +AI07520,Autonomous Systems Engineer,158654,USD,158654,SE,FL,Norway,L,Norway,50,"AWS, Git, Python, GCP, Scala",Bachelor,7,Gaming,2024-10-28,2024-12-21,1527,6.8,Advanced Robotics +AI07521,Head of AI,76071,EUR,64660,MI,FL,Netherlands,S,Netherlands,100,"Kubernetes, Git, Scala, Computer Vision, Python",PhD,2,Education,2024-07-08,2024-08-14,688,8.4,TechCorp Inc +AI07522,Data Analyst,70355,USD,70355,MI,FL,Finland,M,Finland,50,"Java, Spark, Hadoop, Mathematics",Associate,2,Technology,2024-07-25,2024-08-24,2367,5.2,DeepTech Ventures +AI07523,Data Analyst,100575,CAD,125719,MI,CT,Canada,M,Canada,100,"Spark, Tableau, Azure, NLP, Mathematics",PhD,2,Manufacturing,2025-01-04,2025-01-24,1421,6.6,Advanced Robotics +AI07524,Machine Learning Researcher,137502,GBP,103127,SE,FL,United Kingdom,M,United Kingdom,50,"PyTorch, SQL, NLP",PhD,9,Manufacturing,2024-07-24,2024-09-02,1538,5.6,Quantum Computing Inc +AI07525,Data Analyst,76419,AUD,103166,EN,FT,Australia,M,Australia,0,"Python, Deep Learning, Linux, Mathematics, Kubernetes",PhD,0,Education,2024-10-13,2024-12-25,925,9.2,Algorithmic Solutions +AI07526,AI Research Scientist,76902,USD,76902,MI,PT,Finland,M,Finland,50,"TensorFlow, Kubernetes, Spark, Azure, Git",PhD,4,Education,2024-09-20,2024-10-23,2336,8.8,AI Innovations +AI07527,AI Product Manager,89926,USD,89926,EN,CT,Denmark,S,China,50,"Azure, Git, NLP, GCP, Scala",PhD,1,Retail,2024-06-11,2024-07-23,1513,7.4,Future Systems +AI07528,Research Scientist,213625,EUR,181581,EX,FT,Netherlands,S,Philippines,50,"Docker, Java, Data Visualization, TensorFlow, MLOps",Master,14,Manufacturing,2024-09-14,2024-11-13,2394,9.8,Cognitive Computing +AI07529,AI Architect,160222,EUR,136189,EX,FL,Austria,L,Austria,50,"GCP, Linux, Azure, Git",PhD,14,Transportation,2024-01-07,2024-03-03,885,8.1,Smart Analytics +AI07530,Machine Learning Engineer,35947,USD,35947,MI,FL,India,M,Spain,50,"SQL, GCP, Deep Learning",PhD,4,Finance,2024-11-28,2024-12-18,2230,5,Predictive Systems +AI07531,Research Scientist,53653,SGD,69749,EN,CT,Singapore,S,Brazil,0,"Git, Data Visualization, R, Java, GCP",Associate,1,Government,2024-10-16,2024-12-23,2404,6.5,Machine Intelligence Group +AI07532,NLP Engineer,108963,EUR,92619,SE,CT,Netherlands,M,Portugal,0,"Python, TensorFlow, NLP",Associate,7,Telecommunications,2025-01-20,2025-03-09,1210,8.2,Autonomous Tech +AI07533,AI Software Engineer,77378,USD,77378,MI,CT,South Korea,S,Estonia,0,"Spark, Computer Vision, Scala, SQL",PhD,4,Energy,2024-06-16,2024-08-12,1392,5.7,Advanced Robotics +AI07534,Machine Learning Engineer,84375,EUR,71719,MI,CT,Germany,S,Germany,0,"NLP, Data Visualization, Python, Tableau",PhD,4,Healthcare,2025-03-30,2025-05-07,2486,7.8,Advanced Robotics +AI07535,AI Architect,212229,CAD,265286,EX,CT,Canada,L,Canada,0,"NLP, Mathematics, Git, TensorFlow",Bachelor,18,Media,2024-09-30,2024-11-27,1563,8.4,TechCorp Inc +AI07536,Machine Learning Researcher,122917,USD,122917,EX,FT,Israel,S,Israel,0,"Docker, MLOps, TensorFlow, Data Visualization, Linux",PhD,14,Technology,2024-05-31,2024-07-02,1245,8,Advanced Robotics +AI07537,AI Product Manager,75040,EUR,63784,EN,CT,France,L,France,50,"Azure, Python, Linux, Java",Bachelor,0,Technology,2024-01-03,2024-01-24,843,6.2,Autonomous Tech +AI07538,Data Scientist,302015,USD,302015,EX,CT,Denmark,M,Turkey,50,"Computer Vision, GCP, Git, SQL, Hadoop",Master,11,Transportation,2024-08-11,2024-09-09,1447,5.2,TechCorp Inc +AI07539,Data Scientist,100206,EUR,85175,MI,CT,Germany,M,Germany,0,"NLP, Kubernetes, Mathematics",Bachelor,3,Finance,2024-03-24,2024-05-28,1544,6.6,TechCorp Inc +AI07540,Machine Learning Researcher,74112,CAD,92640,EN,FL,Canada,M,Turkey,100,"SQL, PyTorch, AWS, TensorFlow",Master,0,Retail,2024-06-06,2024-07-31,1498,5.6,Digital Transformation LLC +AI07541,Data Engineer,52847,USD,52847,SE,FL,India,L,India,0,"Statistics, Azure, Computer Vision, Deep Learning, SQL",Associate,9,Consulting,2024-04-22,2024-05-15,614,8.4,Future Systems +AI07542,AI Research Scientist,121952,EUR,103659,SE,CT,Austria,M,Austria,0,"Java, Scala, Spark",PhD,9,Retail,2024-02-03,2024-04-08,808,10,Smart Analytics +AI07543,AI Specialist,22932,USD,22932,EN,FT,India,M,India,0,"SQL, Kubernetes, Tableau",Bachelor,1,Technology,2024-06-08,2024-08-12,1556,7.3,Cloud AI Solutions +AI07544,Robotics Engineer,185551,USD,185551,EX,FL,Ireland,L,Sweden,50,"Azure, SQL, Data Visualization, Linux",Bachelor,12,Real Estate,2024-03-13,2024-05-13,608,6.6,Quantum Computing Inc +AI07545,NLP Engineer,144980,USD,144980,EX,FL,South Korea,M,Poland,50,"Python, Linux, AWS, Deep Learning",PhD,12,Manufacturing,2025-04-20,2025-05-24,1125,8.2,Smart Analytics +AI07546,NLP Engineer,137887,USD,137887,MI,CT,United States,L,United States,100,"NLP, Linux, Tableau",Master,4,Government,2024-04-09,2024-05-12,642,10,AI Innovations +AI07547,Principal Data Scientist,26422,USD,26422,EN,FT,China,S,Latvia,100,"Hadoop, Spark, Java, Scala",Master,0,Technology,2025-01-14,2025-01-30,1300,8.4,Future Systems +AI07548,ML Ops Engineer,92812,USD,92812,EN,FL,United States,M,United States,100,"NLP, Computer Vision, Linux",Master,0,Media,2024-12-18,2025-02-20,1521,7.3,TechCorp Inc +AI07549,AI Software Engineer,60930,USD,60930,MI,FT,South Korea,S,South Korea,0,"SQL, TensorFlow, Statistics, Git",Bachelor,3,Healthcare,2024-11-25,2025-01-23,1040,7.5,Autonomous Tech +AI07550,ML Ops Engineer,218956,USD,218956,EX,PT,Finland,M,Finland,50,"SQL, Java, Azure",PhD,18,Education,2024-01-21,2024-03-13,1594,8.8,Digital Transformation LLC +AI07551,Data Scientist,75273,USD,75273,MI,CT,Israel,M,Israel,50,"MLOps, Tableau, Spark",PhD,4,Transportation,2024-09-16,2024-10-18,801,6,Algorithmic Solutions +AI07552,Autonomous Systems Engineer,49221,USD,49221,MI,CT,China,M,China,0,"PyTorch, Hadoop, Python, SQL",Associate,2,Energy,2024-08-28,2024-10-03,1967,5.6,AI Innovations +AI07553,Robotics Engineer,199243,EUR,169357,EX,FT,Germany,L,Indonesia,0,"Docker, TensorFlow, Tableau, SQL",Bachelor,13,Energy,2024-12-31,2025-01-16,1820,9.5,Advanced Robotics +AI07554,NLP Engineer,98108,USD,98108,SE,CT,Ireland,S,Ireland,0,"Tableau, Deep Learning, Git, Python, Scala",PhD,8,Healthcare,2024-10-19,2024-12-17,710,7.6,AI Innovations +AI07555,Principal Data Scientist,251392,EUR,213683,EX,FT,France,L,France,0,"Kubernetes, PyTorch, GCP",PhD,13,Gaming,2025-04-02,2025-06-01,1365,6.9,Smart Analytics +AI07556,Head of AI,102675,SGD,133478,SE,CT,Singapore,S,South Africa,50,"Spark, Hadoop, SQL, Tableau",Associate,8,Automotive,2024-05-30,2024-06-14,2253,8.5,Machine Intelligence Group +AI07557,NLP Engineer,289291,JPY,31822010,EX,PT,Japan,L,Japan,50,"Scala, Kubernetes, R, MLOps",Master,16,Government,2024-12-13,2025-01-18,537,5.7,Quantum Computing Inc +AI07558,AI Consultant,58763,SGD,76392,EN,FT,Singapore,S,Singapore,100,"Scala, PyTorch, AWS",Master,1,Manufacturing,2024-11-21,2024-12-30,1146,8.1,Algorithmic Solutions +AI07559,Machine Learning Engineer,119668,USD,119668,SE,PT,Israel,M,Italy,0,"NLP, Kubernetes, Scala, GCP",Bachelor,8,Finance,2024-09-26,2024-11-12,986,6.9,Machine Intelligence Group +AI07560,Data Scientist,50856,AUD,68656,EN,FT,Australia,S,New Zealand,0,"Azure, NLP, Kubernetes, Scala",Associate,1,Government,2024-11-11,2024-12-02,1490,7.7,Digital Transformation LLC +AI07561,ML Ops Engineer,98859,USD,98859,MI,FT,Norway,S,Norway,50,"Computer Vision, Java, Scala",Master,3,Media,2025-04-26,2025-07-08,932,7,Predictive Systems +AI07562,Principal Data Scientist,276933,USD,276933,EX,FT,Denmark,M,Denmark,50,"Deep Learning, R, MLOps",PhD,14,Manufacturing,2024-09-28,2024-12-03,2353,9.2,Neural Networks Co +AI07563,AI Research Scientist,154287,USD,154287,SE,FT,Norway,S,Norway,0,"Linux, Statistics, NLP",PhD,7,Gaming,2024-02-06,2024-04-09,1675,5.1,Smart Analytics +AI07564,AI Product Manager,185605,EUR,157764,EX,FL,Germany,M,India,0,"SQL, Scala, Kubernetes, MLOps, Spark",Master,11,Healthcare,2024-10-13,2024-11-02,2420,7.4,Autonomous Tech +AI07565,Computer Vision Engineer,147217,AUD,198743,EX,PT,Australia,M,Australia,50,"PyTorch, Scala, Mathematics",Bachelor,13,Real Estate,2024-12-03,2025-01-23,1945,6.1,Cognitive Computing +AI07566,Machine Learning Engineer,84531,USD,84531,MI,PT,Norway,S,Norway,0,"Linux, Python, Scala, Computer Vision",Master,2,Telecommunications,2024-02-13,2024-03-23,967,8.9,Autonomous Tech +AI07567,AI Specialist,188423,GBP,141317,EX,CT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Git, NLP",Bachelor,13,Manufacturing,2024-10-22,2024-11-23,2357,6.3,Advanced Robotics +AI07568,Machine Learning Engineer,93853,USD,93853,EN,PT,United States,L,Norway,50,"Docker, Kubernetes, AWS, Tableau",Associate,1,Real Estate,2025-01-22,2025-03-03,1530,9.7,Smart Analytics +AI07569,AI Software Engineer,173348,USD,173348,EX,FL,South Korea,L,South Korea,100,"NLP, Linux, SQL",Master,13,Gaming,2025-02-23,2025-04-19,786,6.3,TechCorp Inc +AI07570,Computer Vision Engineer,81621,EUR,69378,MI,CT,France,S,Ghana,100,"Java, NLP, R, Docker, Tableau",PhD,4,Technology,2024-08-04,2024-09-11,2069,7.6,DeepTech Ventures +AI07571,Machine Learning Researcher,171427,USD,171427,EX,FL,Finland,S,Chile,0,"Python, Spark, Docker, Computer Vision",Master,12,Retail,2024-08-07,2024-09-19,1068,9.8,Machine Intelligence Group +AI07572,AI Architect,124261,USD,124261,MI,CT,United States,M,United States,100,"Computer Vision, Java, PyTorch, Git, Linux",PhD,4,Technology,2025-03-02,2025-05-12,1411,8.5,TechCorp Inc +AI07573,Autonomous Systems Engineer,78038,GBP,58529,MI,CT,United Kingdom,M,United Kingdom,100,"Mathematics, Hadoop, R",Master,3,Technology,2024-01-16,2024-02-19,1335,9.3,AI Innovations +AI07574,NLP Engineer,84616,JPY,9307760,MI,FL,Japan,S,Japan,50,"Statistics, R, Computer Vision",PhD,2,Automotive,2025-03-09,2025-03-26,757,6.8,AI Innovations +AI07575,Deep Learning Engineer,56130,USD,56130,EN,CT,Ireland,S,Ireland,50,"NLP, Deep Learning, R, SQL, MLOps",PhD,1,Transportation,2025-04-04,2025-06-12,984,7.1,Algorithmic Solutions +AI07576,Principal Data Scientist,180941,EUR,153800,EX,FL,Austria,L,Vietnam,50,"Deep Learning, NLP, Python",Master,15,Education,2024-12-22,2025-01-15,1773,5.9,Smart Analytics +AI07577,Robotics Engineer,36195,USD,36195,MI,PT,India,M,Spain,0,"Kubernetes, Linux, Git, Python",PhD,2,Technology,2024-02-04,2024-02-22,1586,9.2,Quantum Computing Inc +AI07578,Machine Learning Researcher,74934,USD,74934,EN,FT,Denmark,M,Denmark,100,"GCP, PyTorch, Tableau, Deep Learning",Associate,1,Finance,2024-01-30,2024-02-16,2411,6.4,Neural Networks Co +AI07579,Data Analyst,92668,EUR,78768,MI,FL,France,S,France,0,"Python, Hadoop, Data Visualization, Git, Docker",Bachelor,3,Gaming,2024-05-03,2024-06-03,2476,7.3,Digital Transformation LLC +AI07580,ML Ops Engineer,106319,AUD,143531,MI,PT,Australia,M,Australia,0,"SQL, NLP, MLOps, Hadoop",Associate,4,Media,2025-02-19,2025-04-25,655,5.5,Cognitive Computing +AI07581,AI Product Manager,119428,USD,119428,SE,FT,Finland,L,Finland,50,"Java, GCP, Hadoop, Data Visualization, R",Bachelor,5,Technology,2024-01-10,2024-01-24,2417,9.7,Neural Networks Co +AI07582,Research Scientist,148430,JPY,16327300,EX,CT,Japan,S,Japan,100,"Git, Spark, TensorFlow, SQL, Deep Learning",PhD,18,Automotive,2024-04-18,2024-06-23,907,8.3,Neural Networks Co +AI07583,AI Software Engineer,97277,EUR,82685,SE,FT,France,S,India,0,"Mathematics, Kubernetes, Tableau, NLP",Master,5,Technology,2024-07-22,2024-08-26,2242,5.7,Cloud AI Solutions +AI07584,Head of AI,22873,USD,22873,EN,PT,India,S,India,0,"Python, Computer Vision, Git, TensorFlow",Associate,0,Telecommunications,2025-01-15,2025-02-08,1699,8,Digital Transformation LLC +AI07585,Principal Data Scientist,78064,EUR,66354,MI,PT,Germany,M,Germany,100,"Hadoop, Git, Statistics",Master,4,Technology,2025-01-25,2025-02-08,974,8.5,AI Innovations +AI07586,AI Research Scientist,29207,USD,29207,EN,FL,China,S,China,50,"SQL, Kubernetes, MLOps",Associate,1,Energy,2024-02-19,2024-04-11,893,8.4,DeepTech Ventures +AI07587,ML Ops Engineer,171296,EUR,145602,SE,CT,Netherlands,L,Kenya,0,"Hadoop, Spark, Docker, Azure, Scala",Master,7,Automotive,2024-10-22,2024-11-10,1712,6.6,Machine Intelligence Group +AI07588,Data Engineer,60437,USD,60437,EN,CT,Israel,L,Israel,100,"Java, TensorFlow, Docker, Computer Vision",Associate,1,Transportation,2024-03-28,2024-04-18,975,8.4,Algorithmic Solutions +AI07589,AI Specialist,106204,SGD,138065,SE,PT,Singapore,S,Singapore,100,"Python, Kubernetes, AWS",Bachelor,5,Retail,2024-07-01,2024-09-01,1199,7.2,Advanced Robotics +AI07590,NLP Engineer,30321,USD,30321,MI,FT,India,M,India,100,"Data Visualization, Java, Docker, Python",Bachelor,4,Consulting,2024-08-27,2024-09-13,1329,9.5,Cloud AI Solutions +AI07591,Head of AI,189953,EUR,161460,EX,CT,Austria,L,Austria,0,"Spark, SQL, Data Visualization, Deep Learning",Associate,10,Real Estate,2025-01-01,2025-02-04,1500,8.9,Smart Analytics +AI07592,Machine Learning Researcher,54381,EUR,46224,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, Statistics, Azure, Scala",Bachelor,0,Automotive,2024-06-23,2024-08-30,942,5.9,Cognitive Computing +AI07593,Machine Learning Researcher,88330,JPY,9716300,EN,FT,Japan,L,Japan,0,"MLOps, Hadoop, SQL, Git, AWS",Associate,0,Healthcare,2025-03-10,2025-04-29,1145,8.1,Cognitive Computing +AI07594,AI Product Manager,154426,USD,154426,SE,FT,Sweden,L,Thailand,100,"Computer Vision, Tableau, MLOps, SQL",Bachelor,7,Education,2024-02-16,2024-03-09,1855,7.6,Digital Transformation LLC +AI07595,AI Software Engineer,119526,EUR,101597,SE,PT,Netherlands,S,Netherlands,50,"Java, Kubernetes, Spark, Mathematics",Master,6,Media,2025-03-21,2025-04-19,2244,8,Cognitive Computing +AI07596,AI Architect,137197,USD,137197,SE,FT,Denmark,M,Vietnam,0,"Java, Docker, PyTorch, AWS, Hadoop",Associate,6,Healthcare,2024-12-25,2025-02-19,1065,6.7,Smart Analytics +AI07597,Head of AI,117462,USD,117462,SE,CT,Israel,M,Colombia,50,"Data Visualization, PyTorch, NLP, Docker",Associate,8,Transportation,2024-09-27,2024-10-24,2441,6.3,DeepTech Ventures +AI07598,Data Analyst,163257,EUR,138768,SE,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Statistics, Scala",Master,7,Healthcare,2024-11-18,2024-12-09,840,7.3,Neural Networks Co +AI07599,Data Analyst,185659,USD,185659,EX,PT,Israel,L,Israel,50,"Data Visualization, Docker, Computer Vision, NLP",PhD,10,Education,2024-08-29,2024-11-03,1965,7.2,DeepTech Ventures +AI07600,AI Architect,266642,CAD,333303,EX,CT,Canada,L,Germany,0,"PyTorch, GCP, Azure, Mathematics, Statistics",Bachelor,16,Energy,2025-04-16,2025-05-08,1518,5.8,Smart Analytics +AI07601,ML Ops Engineer,73310,USD,73310,EN,FT,Norway,S,Brazil,0,"SQL, Statistics, MLOps, R",Associate,1,Retail,2024-04-26,2024-05-31,530,10,Machine Intelligence Group +AI07602,AI Software Engineer,175822,CHF,158240,MI,FT,Switzerland,L,Portugal,100,"Computer Vision, GCP, Linux, AWS, Tableau",PhD,3,Healthcare,2024-06-05,2024-07-13,1150,5,Neural Networks Co +AI07603,Machine Learning Researcher,82893,USD,82893,EN,FT,Israel,L,Romania,50,"Azure, MLOps, Kubernetes, Docker",PhD,0,Real Estate,2025-02-24,2025-04-14,1318,9.8,Advanced Robotics +AI07604,Computer Vision Engineer,121156,USD,121156,SE,PT,Finland,M,United States,100,"Mathematics, GCP, MLOps, Docker",Associate,7,Technology,2025-04-15,2025-05-01,1153,5.6,Machine Intelligence Group +AI07605,Machine Learning Engineer,85501,USD,85501,MI,CT,Ireland,S,Ireland,100,"Scala, NLP, Java, R",PhD,2,Energy,2024-05-01,2024-06-17,1409,9.7,Cloud AI Solutions +AI07606,Deep Learning Engineer,200592,USD,200592,EX,FL,Sweden,L,Sweden,100,"Scala, PyTorch, Tableau, Mathematics, Kubernetes",PhD,19,Automotive,2024-12-02,2024-12-17,714,6.3,DeepTech Ventures +AI07607,Data Analyst,157367,USD,157367,EX,FL,United States,S,Hungary,50,"MLOps, PyTorch, Kubernetes",PhD,18,Finance,2025-01-09,2025-02-05,1308,8.7,Digital Transformation LLC +AI07608,AI Architect,96408,USD,96408,MI,FL,Norway,S,Norway,50,"R, TensorFlow, SQL, Azure, Spark",Bachelor,4,Automotive,2024-03-23,2024-04-25,574,9,Cloud AI Solutions +AI07609,AI Research Scientist,41086,USD,41086,MI,CT,China,M,China,100,"TensorFlow, Docker, GCP",Bachelor,4,Telecommunications,2025-01-18,2025-03-03,1587,8.9,Quantum Computing Inc +AI07610,AI Architect,87699,EUR,74544,MI,CT,France,L,France,100,"R, PyTorch, Docker, TensorFlow, SQL",Bachelor,2,Government,2024-10-18,2024-11-29,2105,8.6,Predictive Systems +AI07611,AI Architect,173811,CHF,156430,SE,PT,Switzerland,S,Switzerland,0,"Python, PyTorch, Linux",Associate,7,Retail,2025-04-24,2025-05-21,1883,6.7,Cognitive Computing +AI07612,AI Product Manager,126276,EUR,107335,SE,FL,France,S,France,0,"Statistics, GCP, R, Git",Master,5,Government,2024-12-13,2025-01-13,1695,5.4,Quantum Computing Inc +AI07613,Computer Vision Engineer,242933,EUR,206493,EX,FL,Netherlands,M,Finland,100,"Spark, TensorFlow, Linux",PhD,11,Consulting,2024-12-16,2025-01-23,2045,6.3,AI Innovations +AI07614,Robotics Engineer,62515,USD,62515,EN,FL,United States,S,United States,50,"PyTorch, SQL, TensorFlow",Master,1,Media,2025-03-29,2025-04-14,871,7.3,Cognitive Computing +AI07615,AI Software Engineer,96579,USD,96579,SE,FT,Israel,M,Israel,100,"Scala, TensorFlow, Deep Learning",PhD,9,Telecommunications,2024-09-15,2024-11-10,1055,8.3,DataVision Ltd +AI07616,Machine Learning Researcher,66417,USD,66417,EN,FT,Norway,M,Norway,0,"R, NLP, Azure, Git, SQL",Master,0,Consulting,2024-11-07,2024-12-12,795,6.6,TechCorp Inc +AI07617,AI Product Manager,66775,USD,66775,EN,PT,Ireland,M,Mexico,100,"Computer Vision, Git, MLOps, NLP, TensorFlow",Master,0,Education,2024-02-29,2024-04-29,550,9.8,Predictive Systems +AI07618,Autonomous Systems Engineer,112618,SGD,146403,MI,PT,Singapore,L,Singapore,100,"AWS, PyTorch, Docker, TensorFlow, Scala",Associate,4,Finance,2025-02-04,2025-03-31,1936,6.3,Digital Transformation LLC +AI07619,AI Consultant,172134,USD,172134,SE,FT,Norway,M,Brazil,0,"Hadoop, Computer Vision, Python, Docker, GCP",Master,9,Finance,2024-08-12,2024-08-28,2319,6.3,Algorithmic Solutions +AI07620,Research Scientist,89513,EUR,76086,SE,FL,France,S,France,0,"Scala, Git, Python, Azure",Associate,6,Telecommunications,2024-08-08,2024-09-27,2056,6.2,Machine Intelligence Group +AI07621,Head of AI,124617,USD,124617,SE,FL,Denmark,S,Denmark,100,"Azure, NLP, Spark, Hadoop",Associate,9,Gaming,2025-03-19,2025-04-03,1175,7.2,Machine Intelligence Group +AI07622,NLP Engineer,211681,USD,211681,EX,FL,Sweden,S,Colombia,100,"Spark, Tableau, Kubernetes",Bachelor,13,Real Estate,2024-06-25,2024-07-23,2078,6.8,Digital Transformation LLC +AI07623,AI Architect,70756,USD,70756,EN,CT,Sweden,L,Czech Republic,100,"Python, NLP, AWS",PhD,1,Media,2025-03-21,2025-04-29,2181,8.7,Algorithmic Solutions +AI07624,AI Consultant,124712,EUR,106005,SE,PT,Germany,S,Germany,100,"Kubernetes, Tableau, Mathematics, MLOps, Git",Associate,8,Real Estate,2024-01-23,2024-03-07,2333,8,Digital Transformation LLC +AI07625,Research Scientist,81724,USD,81724,EN,FT,Ireland,L,Ireland,0,"Python, Azure, Mathematics, GCP, Statistics",Bachelor,0,Real Estate,2024-10-25,2024-11-21,2292,9.4,TechCorp Inc +AI07626,Data Scientist,98773,USD,98773,MI,FT,Ireland,L,Ireland,50,"TensorFlow, NLP, Git, Hadoop",Bachelor,4,Transportation,2024-04-20,2024-06-29,640,6.3,Future Systems +AI07627,NLP Engineer,123212,SGD,160176,SE,PT,Singapore,S,Singapore,0,"Azure, PyTorch, GCP",PhD,5,Transportation,2024-01-23,2024-03-03,1509,5.9,Future Systems +AI07628,AI Consultant,158235,EUR,134500,EX,CT,France,M,France,100,"Scala, Git, Data Visualization, AWS",PhD,11,Healthcare,2025-04-04,2025-05-28,2070,6.1,Machine Intelligence Group +AI07629,Robotics Engineer,243378,USD,243378,EX,FL,Finland,L,Japan,50,"Linux, Deep Learning, Python, SQL",Master,17,Manufacturing,2024-01-23,2024-03-15,1771,8.9,Smart Analytics +AI07630,Data Engineer,72159,SGD,93807,EN,CT,Singapore,L,Sweden,100,"GCP, Docker, MLOps",Associate,1,Education,2025-04-26,2025-06-29,1183,9,Machine Intelligence Group +AI07631,Computer Vision Engineer,117447,CAD,146809,SE,FT,Canada,M,Canada,50,"Git, Python, TensorFlow",Bachelor,7,Gaming,2025-02-25,2025-04-03,907,6.4,Predictive Systems +AI07632,Data Engineer,93398,EUR,79388,EN,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Data Visualization, Spark",PhD,0,Telecommunications,2024-09-21,2024-10-15,595,6.4,DeepTech Ventures +AI07633,Head of AI,130830,USD,130830,SE,FL,Sweden,L,Latvia,0,"Kubernetes, Python, Hadoop",Associate,5,Technology,2024-04-19,2024-05-25,1607,8.3,Quantum Computing Inc +AI07634,Data Engineer,226889,USD,226889,EX,PT,United States,S,Sweden,50,"GCP, Kubernetes, Data Visualization, Deep Learning, Hadoop",Bachelor,12,Retail,2025-02-02,2025-03-11,792,9,Cognitive Computing +AI07635,Data Engineer,81702,JPY,8987220,EN,FT,Japan,M,Japan,50,"SQL, GCP, Statistics",Associate,0,Consulting,2024-06-12,2024-07-20,504,5.3,Quantum Computing Inc +AI07636,AI Product Manager,111373,EUR,94667,SE,FL,Germany,S,Germany,0,"Mathematics, Python, Tableau, TensorFlow, PyTorch",Bachelor,6,Consulting,2025-01-05,2025-02-08,2037,6.3,Neural Networks Co +AI07637,Robotics Engineer,57310,USD,57310,MI,FL,South Korea,S,Switzerland,50,"Docker, NLP, Python, Kubernetes, Mathematics",Master,4,Telecommunications,2024-05-03,2024-06-27,1556,7.6,Smart Analytics +AI07638,Principal Data Scientist,43322,USD,43322,MI,FL,China,S,China,50,"Spark, Python, TensorFlow, Linux",PhD,3,Real Estate,2024-11-02,2024-12-10,1131,7.2,Predictive Systems +AI07639,Computer Vision Engineer,95292,CHF,85763,EN,PT,Switzerland,L,Switzerland,100,"Git, Hadoop, SQL, Computer Vision",Master,0,Education,2024-02-12,2024-03-25,1940,5.2,DataVision Ltd +AI07640,NLP Engineer,174223,GBP,130667,EX,FT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, Azure",Master,10,Telecommunications,2024-05-26,2024-06-19,981,7.2,DeepTech Ventures +AI07641,Machine Learning Engineer,84562,AUD,114159,MI,FT,Australia,M,Australia,100,"Linux, GCP, TensorFlow, Kubernetes, Statistics",Master,3,Technology,2024-11-09,2024-12-11,1796,5.3,DataVision Ltd +AI07642,Data Analyst,166804,AUD,225185,SE,FL,Australia,L,Philippines,100,"Tableau, Python, TensorFlow, Mathematics",Associate,7,Retail,2024-05-09,2024-07-10,745,5.4,Algorithmic Solutions +AI07643,AI Consultant,32768,USD,32768,EN,PT,China,L,China,50,"Python, SQL, Docker, Mathematics",Bachelor,1,Real Estate,2025-04-30,2025-05-24,1770,7.9,Cognitive Computing +AI07644,Head of AI,217646,EUR,184999,EX,PT,Netherlands,S,Brazil,50,"Spark, TensorFlow, Scala, Hadoop, MLOps",PhD,10,Healthcare,2024-12-10,2025-01-15,2225,8.5,TechCorp Inc +AI07645,Computer Vision Engineer,144258,EUR,122619,SE,FL,Netherlands,S,Netherlands,50,"PyTorch, R, Hadoop",Bachelor,5,Media,2025-01-25,2025-02-18,2300,9.7,DeepTech Ventures +AI07646,AI Architect,104597,USD,104597,SE,FL,South Korea,M,South Korea,100,"GCP, SQL, PyTorch, R",Bachelor,8,Transportation,2024-06-27,2024-07-28,1106,8.2,Neural Networks Co +AI07647,AI Specialist,95849,USD,95849,MI,FL,South Korea,L,South Korea,50,"Tableau, Kubernetes, PyTorch",Bachelor,4,Automotive,2024-11-06,2024-11-22,1076,6,DeepTech Ventures +AI07648,Computer Vision Engineer,265185,EUR,225407,EX,FT,Netherlands,L,Netherlands,50,"Python, PyTorch, Java, Computer Vision",Master,18,Energy,2024-12-14,2025-01-29,674,6.9,Predictive Systems +AI07649,AI Specialist,63417,EUR,53904,EN,CT,Austria,L,South Africa,50,"Linux, Scala, Kubernetes, GCP, Mathematics",PhD,1,Media,2024-10-09,2024-11-20,1572,9.6,Algorithmic Solutions +AI07650,Robotics Engineer,162111,USD,162111,SE,PT,Ireland,L,Thailand,50,"Docker, Statistics, GCP, Mathematics, PyTorch",PhD,8,Real Estate,2024-08-04,2024-10-06,1021,7,AI Innovations +AI07651,AI Architect,51830,USD,51830,EN,CT,South Korea,M,South Korea,0,"GCP, Scala, Tableau, PyTorch, Statistics",Bachelor,1,Energy,2024-08-04,2024-09-22,2067,9.2,Cloud AI Solutions +AI07652,AI Architect,80660,USD,80660,EN,CT,Denmark,L,Denmark,0,"Docker, AWS, MLOps",Bachelor,0,Energy,2024-11-03,2024-12-22,1825,5.3,Cognitive Computing +AI07653,Research Scientist,183478,USD,183478,SE,FT,Denmark,M,New Zealand,0,"Python, TensorFlow, Computer Vision, MLOps",PhD,8,Automotive,2024-02-24,2024-03-11,2350,9.6,Machine Intelligence Group +AI07654,Data Scientist,93839,EUR,79763,EN,FT,Netherlands,L,Netherlands,0,"TensorFlow, Spark, Computer Vision",Associate,1,Manufacturing,2024-01-22,2024-02-08,1415,5.5,Smart Analytics +AI07655,Machine Learning Engineer,63882,JPY,7027020,EN,FT,Japan,L,Japan,0,"Git, AWS, Python, Tableau, Linux",Associate,1,Technology,2024-02-27,2024-04-24,2251,6.2,DeepTech Ventures +AI07656,Data Analyst,126076,GBP,94557,SE,FT,United Kingdom,L,Ghana,50,"Data Visualization, SQL, Azure",Master,6,Finance,2024-02-11,2024-04-05,2026,9.8,DeepTech Ventures +AI07657,Principal Data Scientist,91813,JPY,10099430,MI,FL,Japan,S,Australia,100,"Scala, Data Visualization, Kubernetes, SQL, AWS",Master,3,Education,2024-07-23,2024-08-08,1170,7.6,DataVision Ltd +AI07658,AI Architect,44127,USD,44127,EN,PT,Finland,S,Finland,100,"SQL, Java, Data Visualization",Master,1,Media,2024-05-09,2024-06-05,2336,5,Predictive Systems +AI07659,AI Research Scientist,70724,CAD,88405,EN,FT,Canada,M,Canada,50,"Data Visualization, MLOps, SQL",Associate,0,Automotive,2024-01-20,2024-02-05,541,8,Advanced Robotics +AI07660,Data Analyst,306380,GBP,229785,EX,FT,United Kingdom,L,United Kingdom,50,"PyTorch, TensorFlow, Mathematics, Azure, R",Bachelor,16,Finance,2024-06-16,2024-07-03,1441,9.6,Digital Transformation LLC +AI07661,Data Scientist,59061,EUR,50202,EN,PT,Germany,S,Germany,100,"Scala, SQL, Data Visualization, TensorFlow, Git",Associate,0,Gaming,2024-08-28,2024-10-12,2199,5.2,Future Systems +AI07662,Data Scientist,127372,USD,127372,SE,PT,Denmark,S,Hungary,100,"GCP, AWS, Python, Linux",PhD,6,Telecommunications,2025-04-02,2025-06-10,1330,5.6,DataVision Ltd +AI07663,AI Software Engineer,324728,CHF,292255,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, Python, TensorFlow, Linux",PhD,13,Retail,2024-08-03,2024-09-23,1682,5.2,Smart Analytics +AI07664,AI Consultant,132294,USD,132294,SE,FT,Denmark,S,Denmark,100,"Data Visualization, Python, GCP",Master,7,Manufacturing,2024-01-22,2024-03-09,1383,7.8,AI Innovations +AI07665,Data Engineer,110217,EUR,93684,SE,FL,Germany,S,Germany,50,"R, Tableau, Azure, Python, Hadoop",Associate,7,Finance,2024-08-09,2024-08-29,2475,7.2,Smart Analytics +AI07666,Deep Learning Engineer,108463,USD,108463,MI,FL,Denmark,M,Brazil,50,"Statistics, SQL, Linux, NLP, Hadoop",PhD,4,Consulting,2024-04-24,2024-07-05,1652,8.4,AI Innovations +AI07667,AI Consultant,60083,USD,60083,MI,FL,South Korea,M,Italy,100,"AWS, Scala, Docker, NLP, Linux",PhD,2,Transportation,2025-02-19,2025-03-18,1564,8.2,Machine Intelligence Group +AI07668,NLP Engineer,74921,USD,74921,EX,CT,India,L,India,0,"TensorFlow, NLP, R, Python",PhD,11,Government,2024-02-28,2024-03-26,1818,6.1,Digital Transformation LLC +AI07669,AI Consultant,229930,CHF,206937,EX,FT,Switzerland,S,Kenya,0,"Java, GCP, Statistics, Python, TensorFlow",Associate,13,Retail,2024-05-12,2024-06-24,1945,9.9,Advanced Robotics +AI07670,Research Scientist,134348,CAD,167935,SE,FL,Canada,M,Canada,50,"NLP, Kubernetes, MLOps, Java",Bachelor,9,Transportation,2024-11-21,2025-01-17,2441,6.7,Neural Networks Co +AI07671,AI Research Scientist,84844,GBP,63633,MI,FT,United Kingdom,S,United Kingdom,50,"Scala, Hadoop, Data Visualization, Git, Python",Bachelor,2,Media,2024-12-14,2025-01-13,1273,8.1,Smart Analytics +AI07672,Computer Vision Engineer,75519,CAD,94399,MI,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP",PhD,2,Energy,2024-08-15,2024-09-15,2158,8.4,Machine Intelligence Group +AI07673,AI Specialist,83770,USD,83770,MI,FT,Finland,M,Switzerland,100,"Kubernetes, Scala, Statistics, PyTorch, NLP",PhD,4,Education,2024-12-21,2025-01-11,1827,6,Future Systems +AI07674,Computer Vision Engineer,99649,USD,99649,EN,PT,United States,L,Romania,100,"GCP, R, Data Visualization, SQL, Linux",Associate,1,Energy,2025-04-25,2025-05-14,1620,7.7,DeepTech Ventures +AI07675,Data Engineer,288454,USD,288454,EX,FT,Denmark,M,Denmark,100,"AWS, MLOps, GCP, Scala",Master,18,Consulting,2024-06-27,2024-08-26,1751,5.5,Cognitive Computing +AI07676,Research Scientist,185909,EUR,158023,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, TensorFlow, GCP, Statistics, Java",Associate,15,Telecommunications,2024-11-06,2024-12-19,1477,5.7,Digital Transformation LLC +AI07677,Robotics Engineer,82676,USD,82676,EN,FL,United States,M,United States,100,"AWS, Git, Data Visualization",Associate,0,Automotive,2024-03-03,2024-03-28,2443,6,Cognitive Computing +AI07678,Deep Learning Engineer,180023,USD,180023,EX,FT,South Korea,S,China,0,"Scala, GCP, Deep Learning, Data Visualization, Hadoop",Associate,11,Real Estate,2024-06-08,2024-07-05,2224,10,Quantum Computing Inc +AI07679,AI Consultant,85630,USD,85630,EN,PT,Ireland,L,Ireland,0,"Java, Kubernetes, Scala, Deep Learning, Computer Vision",Bachelor,0,Media,2025-04-02,2025-06-01,1688,9.3,Cognitive Computing +AI07680,AI Research Scientist,91309,EUR,77613,MI,FT,France,L,France,0,"Java, NLP, Linux, TensorFlow",Associate,4,Education,2024-08-20,2024-10-08,1703,7.9,Digital Transformation LLC +AI07681,AI Consultant,73734,EUR,62674,EN,FL,Austria,M,Austria,0,"Python, MLOps, PyTorch, R",PhD,1,Gaming,2024-04-15,2024-05-12,577,7.4,Predictive Systems +AI07682,Research Scientist,180469,USD,180469,EX,FT,Sweden,S,Sweden,50,"SQL, Python, MLOps, AWS",PhD,17,Government,2025-02-24,2025-05-08,2313,5.1,Smart Analytics +AI07683,Machine Learning Researcher,55451,EUR,47133,EN,CT,Austria,L,Austria,50,"Spark, Kubernetes, Statistics, Computer Vision, PyTorch",Master,1,Finance,2025-01-05,2025-02-21,1493,9.2,DeepTech Ventures +AI07684,Deep Learning Engineer,113073,USD,113073,EN,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Data Visualization, Python, R",PhD,0,Automotive,2024-11-28,2025-01-28,2139,9.3,Neural Networks Co +AI07685,Computer Vision Engineer,68363,EUR,58109,EN,FT,France,M,France,50,"Hadoop, Linux, Mathematics, Python",Master,0,Government,2024-08-12,2024-08-29,1755,9.5,Advanced Robotics +AI07686,Robotics Engineer,62860,USD,62860,EX,CT,China,S,China,50,"Hadoop, SQL, NLP",Associate,16,Real Estate,2024-06-30,2024-07-19,540,5.1,Predictive Systems +AI07687,NLP Engineer,176108,USD,176108,EX,PT,Ireland,S,Israel,50,"Python, Hadoop, Kubernetes, Scala, Git",Bachelor,11,Telecommunications,2024-05-30,2024-07-11,1478,5.2,TechCorp Inc +AI07688,AI Software Engineer,86453,EUR,73485,MI,FT,France,L,France,0,"Azure, GCP, Spark, Scala, Hadoop",Master,2,Real Estate,2024-07-20,2024-09-24,1547,8.2,Advanced Robotics +AI07689,Head of AI,170116,EUR,144599,EX,FL,Netherlands,L,Czech Republic,0,"Kubernetes, Java, Git, AWS, Computer Vision",PhD,17,Government,2025-02-23,2025-04-03,1237,5.5,Smart Analytics +AI07690,Principal Data Scientist,79589,EUR,67651,EN,CT,Netherlands,L,Sweden,50,"Python, TensorFlow, SQL, Linux",PhD,1,Government,2025-02-01,2025-02-20,1924,7.6,Cloud AI Solutions +AI07691,AI Architect,190789,USD,190789,EX,PT,Finland,S,Finland,50,"PyTorch, Tableau, SQL, Git",Bachelor,10,Education,2024-04-21,2024-06-12,659,9.9,Smart Analytics +AI07692,Data Engineer,79062,USD,79062,EN,PT,United States,M,United States,0,"Data Visualization, Docker, Mathematics",Bachelor,0,Telecommunications,2024-05-15,2024-07-10,1269,8.7,Algorithmic Solutions +AI07693,Deep Learning Engineer,212322,GBP,159242,EX,FL,United Kingdom,M,United Kingdom,0,"Python, Linux, SQL",Bachelor,14,Retail,2024-11-16,2025-01-19,651,8.2,TechCorp Inc +AI07694,Machine Learning Engineer,126710,CAD,158388,SE,FT,Canada,M,Turkey,0,"Git, Kubernetes, GCP, Spark, NLP",Bachelor,6,Healthcare,2024-03-20,2024-05-14,804,8.2,Autonomous Tech +AI07695,Deep Learning Engineer,135567,SGD,176237,SE,FT,Singapore,S,Singapore,100,"Python, Hadoop, SQL, Data Visualization, NLP",Associate,5,Transportation,2024-08-28,2024-09-22,1554,5.1,AI Innovations +AI07696,Autonomous Systems Engineer,77684,GBP,58263,MI,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, AWS, Azure, R",Associate,2,Finance,2024-02-19,2024-03-31,1848,6.3,Quantum Computing Inc +AI07697,Head of AI,87101,CHF,78391,EN,FT,Switzerland,S,Switzerland,50,"TensorFlow, AWS, Mathematics, NLP",PhD,1,Automotive,2024-04-24,2024-05-21,1700,6.2,Quantum Computing Inc +AI07698,Head of AI,65182,USD,65182,EN,FL,Ireland,L,Ireland,100,"NLP, Statistics, SQL, Data Visualization",Master,0,Manufacturing,2024-05-12,2024-06-23,1768,7.2,Predictive Systems +AI07699,Research Scientist,155741,JPY,17131510,SE,CT,Japan,L,Sweden,50,"SQL, Tableau, NLP, Data Visualization, Azure",Master,8,Automotive,2024-06-02,2024-06-19,590,9.5,Advanced Robotics +AI07700,Computer Vision Engineer,35630,USD,35630,MI,PT,India,M,Russia,100,"Scala, R, Deep Learning, Computer Vision, GCP",PhD,2,Gaming,2024-04-07,2024-05-14,501,7.2,Cognitive Computing +AI07701,Machine Learning Engineer,92685,EUR,78782,EN,PT,Netherlands,L,Philippines,50,"Hadoop, Statistics, Scala, TensorFlow, NLP",Master,0,Automotive,2025-03-28,2025-05-08,1696,9.5,Digital Transformation LLC +AI07702,Machine Learning Engineer,63966,EUR,54371,EN,FT,France,S,France,50,"Spark, Python, Statistics",Associate,0,Government,2024-03-03,2024-03-19,562,6.7,TechCorp Inc +AI07703,Data Scientist,193308,AUD,260966,EX,FL,Australia,L,Italy,50,"Azure, Hadoop, SQL, Python",Associate,19,Media,2024-10-08,2024-11-08,2482,8.6,Quantum Computing Inc +AI07704,AI Architect,68810,JPY,7569100,EN,PT,Japan,M,Japan,50,"Linux, Statistics, Python",Bachelor,0,Technology,2024-01-09,2024-02-05,1000,5.1,DataVision Ltd +AI07705,Head of AI,133424,CHF,120082,MI,PT,Switzerland,S,Switzerland,50,"R, Deep Learning, SQL",Associate,2,Finance,2025-03-19,2025-05-25,2253,8.2,Cloud AI Solutions +AI07706,Head of AI,99725,CHF,89753,MI,PT,Switzerland,S,Switzerland,0,"Python, Statistics, Java, TensorFlow",Associate,3,Telecommunications,2024-03-25,2024-05-07,1474,9,Cognitive Computing +AI07707,Principal Data Scientist,92186,USD,92186,MI,CT,Finland,M,Finland,100,"Mathematics, Python, MLOps, Kubernetes, Linux",Associate,3,Consulting,2025-02-12,2025-02-27,1793,6.8,Advanced Robotics +AI07708,AI Consultant,67420,EUR,57307,MI,CT,France,S,France,0,"Scala, AWS, Tableau",Master,4,Telecommunications,2025-04-17,2025-06-03,1056,7.9,Future Systems +AI07709,ML Ops Engineer,63821,CAD,79776,EN,CT,Canada,L,South Korea,50,"TensorFlow, Tableau, Statistics, Java, Linux",PhD,0,Finance,2025-03-14,2025-04-14,1786,7.2,TechCorp Inc +AI07710,ML Ops Engineer,79858,JPY,8784380,MI,PT,Japan,M,Finland,100,"Tableau, Statistics, Hadoop, Scala, Python",Bachelor,2,Media,2024-08-07,2024-08-22,1849,9.5,AI Innovations +AI07711,Autonomous Systems Engineer,92037,GBP,69028,MI,CT,United Kingdom,S,United Kingdom,50,"Python, MLOps, GCP, TensorFlow, Tableau",PhD,3,Telecommunications,2024-05-26,2024-07-15,1867,7.2,Future Systems +AI07712,Deep Learning Engineer,145429,JPY,15997190,SE,CT,Japan,L,Japan,0,"NLP, PyTorch, SQL, R, Kubernetes",Bachelor,6,Healthcare,2024-04-17,2024-05-27,1406,7.6,DeepTech Ventures +AI07713,ML Ops Engineer,49642,USD,49642,EN,FT,South Korea,M,South Korea,50,"Git, Data Visualization, Scala, Python",Bachelor,1,Healthcare,2024-07-27,2024-09-05,1285,5.5,Quantum Computing Inc +AI07714,NLP Engineer,123567,SGD,160637,SE,FT,Singapore,M,Singapore,0,"Git, Java, Tableau",Associate,9,Transportation,2025-01-07,2025-02-19,2046,8.7,Autonomous Tech +AI07715,AI Architect,110776,CHF,99698,EN,FL,Switzerland,M,Switzerland,50,"SQL, Java, Hadoop, Azure, Python",Associate,1,Transportation,2024-10-17,2024-11-13,1304,8.6,Neural Networks Co +AI07716,Principal Data Scientist,173372,AUD,234052,EX,PT,Australia,M,Australia,50,"Deep Learning, Python, Spark, Hadoop, Mathematics",Bachelor,16,Transportation,2024-11-01,2024-12-28,519,9.9,DataVision Ltd +AI07717,Autonomous Systems Engineer,66211,EUR,56279,EN,CT,Germany,L,Germany,100,"Git, Hadoop, Spark, TensorFlow, Java",PhD,1,Gaming,2024-11-22,2024-12-28,2210,9.7,Cognitive Computing +AI07718,Data Scientist,152011,SGD,197614,SE,FT,Singapore,L,Japan,0,"Docker, Linux, Computer Vision, SQL, PyTorch",PhD,5,Transportation,2024-05-29,2024-06-30,501,5.5,Algorithmic Solutions +AI07719,ML Ops Engineer,227332,SGD,295532,EX,FL,Singapore,S,Singapore,50,"Python, Hadoop, SQL, Azure",Bachelor,19,Education,2025-01-15,2025-03-15,1975,8.9,TechCorp Inc +AI07720,Robotics Engineer,124845,CAD,156056,EX,FT,Canada,S,Romania,100,"SQL, NLP, Azure, Statistics, Python",Associate,15,Retail,2024-03-05,2024-05-14,1059,6.6,Machine Intelligence Group +AI07721,NLP Engineer,88027,SGD,114435,MI,FT,Singapore,M,Singapore,0,"PyTorch, Computer Vision, MLOps, Docker",PhD,3,Real Estate,2024-07-28,2024-09-23,652,8.2,Autonomous Tech +AI07722,Head of AI,160105,USD,160105,SE,PT,Ireland,L,Ireland,50,"Python, Kubernetes, Linux",Master,6,Real Estate,2024-01-31,2024-03-13,1280,9,Machine Intelligence Group +AI07723,AI Research Scientist,45928,USD,45928,SE,FT,India,M,India,0,"Linux, Git, Tableau, Data Visualization",Bachelor,7,Media,2024-10-08,2024-12-05,2291,7.7,Smart Analytics +AI07724,Head of AI,71793,USD,71793,EN,CT,Denmark,M,Denmark,100,"Linux, PyTorch, Computer Vision, Git",Bachelor,1,Automotive,2024-12-08,2024-12-23,1035,6.7,Algorithmic Solutions +AI07725,AI Research Scientist,250916,USD,250916,EX,FT,Norway,L,Norway,0,"Deep Learning, Linux, MLOps, NLP, Tableau",PhD,12,Manufacturing,2024-10-26,2024-11-21,1614,6.4,Future Systems +AI07726,Data Scientist,174103,USD,174103,SE,FL,Denmark,L,Denmark,0,"Git, Linux, NLP, Spark",Associate,6,Manufacturing,2024-04-07,2024-06-14,2322,5.4,Advanced Robotics +AI07727,Principal Data Scientist,109543,GBP,82157,MI,PT,United Kingdom,L,United Kingdom,50,"Azure, Python, GCP, Deep Learning, TensorFlow",Associate,2,Healthcare,2024-10-22,2024-12-07,2284,5.4,TechCorp Inc +AI07728,Robotics Engineer,87605,USD,87605,EN,PT,Ireland,L,Ireland,0,"Azure, Python, Kubernetes, Tableau, TensorFlow",PhD,0,Manufacturing,2024-11-23,2024-12-12,1772,5,Predictive Systems +AI07729,AI Software Engineer,146983,EUR,124936,SE,CT,Germany,M,Germany,0,"Spark, AWS, Git, MLOps",Master,9,Real Estate,2024-04-24,2024-05-16,2162,6.3,Cognitive Computing +AI07730,Deep Learning Engineer,102384,USD,102384,SE,CT,Sweden,M,Brazil,50,"R, Deep Learning, Data Visualization, Hadoop, AWS",Master,8,Technology,2024-06-17,2024-08-22,846,6.4,Predictive Systems +AI07731,AI Research Scientist,261474,JPY,28762140,EX,CT,Japan,L,Japan,50,"Computer Vision, GCP, NLP, Kubernetes, Java",Associate,18,Transportation,2024-04-29,2024-05-21,1030,8.1,Advanced Robotics +AI07732,Data Analyst,74595,CAD,93244,EN,FL,Canada,L,Canada,0,"SQL, Computer Vision, PyTorch, Statistics, Kubernetes",Associate,0,Government,2024-02-17,2024-04-28,736,9,DeepTech Ventures +AI07733,Head of AI,96835,USD,96835,EX,CT,China,L,United Kingdom,0,"Kubernetes, Hadoop, Computer Vision",PhD,18,Government,2024-05-01,2024-06-28,1151,6,Quantum Computing Inc +AI07734,Machine Learning Researcher,136419,USD,136419,MI,PT,Denmark,L,Denmark,0,"Python, Hadoop, Deep Learning, TensorFlow",Master,2,Manufacturing,2024-05-11,2024-06-22,1928,6.7,Digital Transformation LLC +AI07735,Autonomous Systems Engineer,62698,USD,62698,SE,FL,China,L,China,100,"Hadoop, Python, Tableau",Associate,9,Energy,2024-01-01,2024-02-07,512,7,Machine Intelligence Group +AI07736,AI Architect,82570,GBP,61928,MI,PT,United Kingdom,M,Turkey,50,"Scala, Git, Tableau, Computer Vision",Bachelor,4,Retail,2024-04-22,2024-05-06,1986,5.6,Predictive Systems +AI07737,Autonomous Systems Engineer,63993,EUR,54394,EN,FT,France,S,Chile,50,"Scala, SQL, Git, Linux",PhD,1,Energy,2024-04-22,2024-07-02,2119,5.6,Quantum Computing Inc +AI07738,Deep Learning Engineer,117183,USD,117183,MI,FT,Israel,L,Israel,0,"TensorFlow, AWS, PyTorch",Master,4,Technology,2024-03-29,2024-05-15,615,8.3,Smart Analytics +AI07739,NLP Engineer,228120,SGD,296556,EX,CT,Singapore,S,Estonia,50,"Kubernetes, Data Visualization, GCP, Scala, Computer Vision",PhD,18,Media,2024-05-29,2024-07-11,982,6.3,Predictive Systems +AI07740,Autonomous Systems Engineer,168150,USD,168150,EX,FL,Ireland,S,Ireland,100,"SQL, Docker, NLP, Mathematics, Computer Vision",Bachelor,10,Telecommunications,2024-07-10,2024-08-22,2461,7.6,DataVision Ltd +AI07741,Data Engineer,251868,EUR,214088,EX,PT,Netherlands,L,Netherlands,0,"Java, Spark, TensorFlow",PhD,10,Energy,2025-02-27,2025-05-01,2060,6,Future Systems +AI07742,AI Consultant,134610,EUR,114419,SE,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, PyTorch, Linux",Associate,9,Healthcare,2024-01-03,2024-02-22,2155,9.1,DeepTech Ventures +AI07743,Data Scientist,39473,USD,39473,MI,PT,China,M,Poland,0,"Hadoop, Linux, R, Git, SQL",PhD,2,Government,2024-03-09,2024-04-07,1821,7.2,DataVision Ltd +AI07744,Data Engineer,59378,EUR,50471,EN,FT,Germany,S,Germany,50,"Python, AWS, Java",Bachelor,1,Telecommunications,2025-04-22,2025-06-15,1884,5.9,Cognitive Computing +AI07745,AI Research Scientist,126770,EUR,107755,SE,CT,Austria,L,Austria,0,"Docker, Kubernetes, Azure, MLOps",Master,6,Retail,2024-04-12,2024-06-15,1519,5.6,Cloud AI Solutions +AI07746,AI Research Scientist,78592,CAD,98240,MI,CT,Canada,S,Canada,100,"R, TensorFlow, Deep Learning, Git, Docker",Bachelor,2,Retail,2024-11-13,2024-12-29,1997,8,Quantum Computing Inc +AI07747,Deep Learning Engineer,29559,USD,29559,MI,CT,India,L,India,0,"Hadoop, Deep Learning, Java, Tableau",Associate,2,Healthcare,2024-10-04,2024-11-04,754,7,Cloud AI Solutions +AI07748,AI Software Engineer,223895,USD,223895,EX,CT,Sweden,L,Brazil,100,"SQL, AWS, Deep Learning, Statistics, Data Visualization",Master,12,Gaming,2025-01-02,2025-02-11,793,9.4,AI Innovations +AI07749,Principal Data Scientist,170881,AUD,230689,SE,PT,Australia,L,Japan,0,"PyTorch, MLOps, TensorFlow",Bachelor,8,Technology,2024-09-07,2024-10-26,1484,8.9,AI Innovations +AI07750,AI Architect,77100,SGD,100230,MI,FL,Singapore,M,Vietnam,0,"SQL, Git, Data Visualization, PyTorch",Associate,4,Telecommunications,2024-11-01,2024-12-03,1851,8.6,Smart Analytics +AI07751,AI Research Scientist,61337,EUR,52136,EN,PT,France,L,France,0,"Linux, Statistics, Computer Vision",Bachelor,1,Energy,2025-04-29,2025-06-14,1576,9.8,Machine Intelligence Group +AI07752,Data Engineer,90203,AUD,121774,MI,FT,Australia,M,Australia,0,"Linux, Python, Data Visualization, MLOps",Bachelor,2,Manufacturing,2024-07-18,2024-09-13,1980,9.1,Smart Analytics +AI07753,AI Software Engineer,95206,USD,95206,EX,CT,India,L,India,0,"GCP, Scala, Java, Azure",Master,19,Finance,2024-12-17,2025-02-12,1590,8.3,Smart Analytics +AI07754,Machine Learning Engineer,143694,CHF,129325,SE,CT,Switzerland,S,Switzerland,100,"PyTorch, Java, SQL, MLOps, Deep Learning",Associate,7,Transportation,2024-07-13,2024-09-02,1769,5.7,Neural Networks Co +AI07755,AI Software Engineer,205240,CAD,256550,EX,FT,Canada,S,Canada,0,"TensorFlow, Kubernetes, Statistics, R, MLOps",PhD,19,Technology,2024-10-05,2024-11-02,2041,7.4,Future Systems +AI07756,Principal Data Scientist,130858,CAD,163573,SE,FL,Canada,L,Canada,100,"Computer Vision, SQL, PyTorch",Bachelor,5,Consulting,2024-01-14,2024-03-11,835,9.6,DataVision Ltd +AI07757,AI Specialist,109839,USD,109839,MI,PT,Norway,M,Norway,0,"Tableau, AWS, Python",PhD,2,Energy,2025-01-19,2025-03-22,2213,5.6,Digital Transformation LLC +AI07758,AI Architect,234658,EUR,199459,EX,CT,Germany,L,Germany,0,"Computer Vision, GCP, TensorFlow, Deep Learning, Java",Associate,14,Gaming,2025-03-18,2025-05-21,1240,7.2,Cloud AI Solutions +AI07759,Computer Vision Engineer,212824,USD,212824,EX,FL,Israel,S,United States,50,"AWS, GCP, Data Visualization, Computer Vision",Associate,18,Technology,2024-08-27,2024-10-08,1963,9.2,Smart Analytics +AI07760,Computer Vision Engineer,89614,EUR,76172,MI,FT,France,S,France,100,"TensorFlow, Linux, MLOps, R",Master,4,Gaming,2024-09-11,2024-09-26,1242,7.8,DeepTech Ventures +AI07761,AI Research Scientist,230152,EUR,195629,EX,PT,Germany,L,Germany,50,"Python, AWS, Computer Vision, TensorFlow, Mathematics",Bachelor,16,Real Estate,2025-04-05,2025-05-20,2279,5.6,Algorithmic Solutions +AI07762,Machine Learning Engineer,138749,USD,138749,EX,FT,Finland,M,Philippines,0,"Data Visualization, MLOps, Java, R, NLP",Bachelor,17,Retail,2024-06-28,2024-08-19,997,5.1,TechCorp Inc +AI07763,Data Scientist,151433,USD,151433,SE,FL,Denmark,M,Denmark,0,"Linux, Git, AWS, Tableau, SQL",PhD,6,Manufacturing,2024-05-09,2024-07-12,698,7.8,Cognitive Computing +AI07764,Head of AI,113027,USD,113027,MI,FL,United States,M,United States,50,"Scala, Spark, Computer Vision",Master,2,Government,2024-11-12,2025-01-13,522,5.4,Smart Analytics +AI07765,AI Architect,75238,USD,75238,EN,PT,United States,M,Sweden,0,"MLOps, Data Visualization, Statistics, PyTorch",PhD,0,Government,2024-12-04,2024-12-19,2206,6.3,DeepTech Ventures +AI07766,Data Scientist,181300,SGD,235690,EX,CT,Singapore,M,Singapore,0,"Python, GCP, Computer Vision",Bachelor,12,Consulting,2024-04-23,2024-05-28,1081,6.4,DeepTech Ventures +AI07767,Data Analyst,180520,USD,180520,EX,FL,Israel,S,Israel,0,"NLP, Spark, Git",Bachelor,16,Real Estate,2025-03-25,2025-04-14,2169,9.4,Digital Transformation LLC +AI07768,AI Research Scientist,60195,GBP,45146,EN,CT,United Kingdom,S,United Kingdom,100,"R, Python, Tableau, Scala",Bachelor,1,Government,2025-03-01,2025-05-12,2478,7.9,TechCorp Inc +AI07769,Deep Learning Engineer,85237,SGD,110808,EN,FL,Singapore,L,Ghana,50,"Python, Kubernetes, Docker, TensorFlow, SQL",PhD,1,Retail,2024-03-03,2024-05-06,2404,9.4,Advanced Robotics +AI07770,Computer Vision Engineer,120221,USD,120221,SE,FL,Norway,S,New Zealand,100,"Scala, PyTorch, Hadoop, Git, GCP",PhD,8,Government,2024-10-03,2024-12-12,651,7,Cognitive Computing +AI07771,Data Engineer,196214,USD,196214,EX,FT,Finland,M,Finland,50,"Linux, Java, GCP, TensorFlow, NLP",Master,14,Automotive,2024-02-01,2024-03-09,1141,9.8,Advanced Robotics +AI07772,AI Consultant,132988,CAD,166235,SE,FT,Canada,M,Canada,0,"Python, Hadoop, MLOps, TensorFlow, Mathematics",Bachelor,6,Media,2024-06-08,2024-08-09,2131,7.3,Digital Transformation LLC +AI07773,Data Analyst,77664,USD,77664,EN,PT,Ireland,M,Ireland,0,"NLP, Docker, Tableau",PhD,0,Energy,2025-03-06,2025-04-14,2381,6.8,Future Systems +AI07774,Robotics Engineer,148890,CAD,186113,SE,FT,Canada,L,Canada,50,"Scala, Linux, MLOps, Spark, Git",Master,9,Automotive,2025-01-27,2025-03-22,1437,8.6,Machine Intelligence Group +AI07775,Head of AI,95335,USD,95335,MI,PT,Israel,L,China,100,"Python, Hadoop, MLOps",Bachelor,2,Finance,2025-04-12,2025-04-30,2096,9.5,Machine Intelligence Group +AI07776,AI Software Engineer,60390,USD,60390,SE,FT,China,M,China,100,"SQL, GCP, PyTorch, Java",Master,5,Healthcare,2024-02-02,2024-03-19,1377,5.8,TechCorp Inc +AI07777,AI Specialist,113740,CHF,102366,EN,FT,Switzerland,L,Switzerland,50,"Kubernetes, TensorFlow, Python, Linux, Computer Vision",Associate,1,Manufacturing,2024-03-30,2024-05-12,646,7.9,DeepTech Ventures +AI07778,Research Scientist,107116,EUR,91049,SE,PT,France,S,Russia,0,"NLP, PyTorch, AWS, Linux, Computer Vision",Bachelor,5,Automotive,2024-05-31,2024-06-18,1158,9.5,Future Systems +AI07779,Data Scientist,116275,USD,116275,EX,PT,China,L,China,50,"Scala, Java, Spark, Docker",Master,17,Media,2024-03-16,2024-04-07,1611,9,DeepTech Ventures +AI07780,AI Product Manager,75695,EUR,64341,MI,FT,Austria,S,South Korea,50,"Linux, Hadoop, SQL, Spark, Java",Master,4,Education,2024-11-06,2025-01-05,984,5.6,Predictive Systems +AI07781,ML Ops Engineer,123821,EUR,105248,SE,FT,Austria,M,Austria,50,"Kubernetes, Spark, MLOps, NLP",Bachelor,8,Technology,2024-03-08,2024-05-09,2226,8.8,AI Innovations +AI07782,Data Engineer,220673,USD,220673,EX,CT,Ireland,L,Switzerland,50,"Docker, Hadoop, PyTorch, Git",PhD,19,Telecommunications,2024-11-27,2025-02-03,2497,5.6,Smart Analytics +AI07783,ML Ops Engineer,69580,EUR,59143,MI,CT,Netherlands,S,Netherlands,0,"NLP, Git, Kubernetes, Tableau",Master,3,Media,2024-01-10,2024-02-25,752,6.3,Digital Transformation LLC +AI07784,NLP Engineer,64614,USD,64614,EN,CT,Finland,S,Finland,0,"Git, R, Spark, Data Visualization",Master,1,Telecommunications,2024-11-29,2025-01-05,1789,6.1,Cognitive Computing +AI07785,Data Engineer,100944,EUR,85802,SE,CT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch",Master,8,Healthcare,2024-04-10,2024-06-15,1527,6.9,Advanced Robotics +AI07786,Machine Learning Engineer,35266,USD,35266,MI,PT,India,M,India,0,"AWS, SQL, Hadoop, Docker, Computer Vision",PhD,4,Automotive,2024-11-16,2024-11-30,761,7.4,Advanced Robotics +AI07787,AI Software Engineer,79263,AUD,107005,EN,FL,Australia,M,Vietnam,50,"Git, Hadoop, PyTorch",Master,1,Gaming,2024-06-11,2024-07-04,1102,7.8,Smart Analytics +AI07788,Data Scientist,94630,USD,94630,MI,CT,Sweden,S,Sweden,0,"Data Visualization, Azure, Kubernetes, GCP, SQL",PhD,4,Government,2025-02-15,2025-04-03,680,7.7,Neural Networks Co +AI07789,AI Research Scientist,290745,EUR,247133,EX,FT,Netherlands,L,Netherlands,0,"Docker, Linux, AWS",Bachelor,16,Energy,2024-11-05,2024-11-27,2383,7.5,Cloud AI Solutions +AI07790,Computer Vision Engineer,177261,USD,177261,SE,FL,Denmark,M,Vietnam,0,"Azure, PyTorch, SQL, Docker, R",Associate,9,Energy,2024-08-05,2024-10-13,1377,10,Future Systems +AI07791,AI Consultant,79754,SGD,103680,MI,FT,Singapore,S,Singapore,0,"Spark, Computer Vision, Linux, AWS, Statistics",Master,3,Telecommunications,2024-02-15,2024-03-21,970,5.9,AI Innovations +AI07792,AI Specialist,179275,USD,179275,EX,FL,Finland,L,United States,50,"R, AWS, Deep Learning",Master,17,Media,2024-12-11,2025-02-05,2187,5.7,Smart Analytics +AI07793,AI Consultant,120982,CHF,108884,MI,FT,Switzerland,L,Switzerland,0,"Statistics, MLOps, TensorFlow, Java",Master,4,Transportation,2024-01-14,2024-03-19,1448,8,Machine Intelligence Group +AI07794,Data Scientist,56033,USD,56033,EN,FL,Israel,L,Israel,100,"Deep Learning, TensorFlow, Data Visualization, PyTorch",Associate,1,Education,2025-01-20,2025-03-11,1633,8.3,Smart Analytics +AI07795,AI Product Manager,43195,USD,43195,SE,CT,India,L,India,0,"R, Java, Python, Statistics, TensorFlow",Bachelor,6,Technology,2024-06-11,2024-08-05,1479,9.9,Predictive Systems +AI07796,AI Software Engineer,95245,USD,95245,EN,FL,United States,L,Ukraine,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,0,Technology,2024-01-18,2024-03-21,1994,6.3,TechCorp Inc +AI07797,Deep Learning Engineer,68796,USD,68796,MI,PT,South Korea,L,South Korea,0,"Hadoop, Python, Tableau, MLOps, Computer Vision",PhD,4,Education,2024-09-23,2024-10-28,1211,5.1,Future Systems +AI07798,AI Architect,236279,CHF,212651,SE,PT,Switzerland,L,Israel,50,"Kubernetes, SQL, Linux, PyTorch",Master,9,Education,2025-03-05,2025-05-07,1087,6.4,TechCorp Inc +AI07799,Deep Learning Engineer,67944,AUD,91724,EN,CT,Australia,M,Australia,50,"Deep Learning, Kubernetes, Spark, Git",Associate,0,Retail,2025-04-04,2025-05-10,2112,5.6,Predictive Systems +AI07800,Computer Vision Engineer,89810,USD,89810,MI,CT,Denmark,S,Malaysia,100,"Deep Learning, TensorFlow, SQL, Hadoop",Bachelor,4,Media,2024-10-02,2024-11-17,1632,8.6,Machine Intelligence Group +AI07801,Computer Vision Engineer,153315,CAD,191644,EX,FL,Canada,L,Portugal,0,"Java, R, SQL, Deep Learning, Docker",Associate,13,Consulting,2024-11-22,2024-12-17,1764,7.7,TechCorp Inc +AI07802,Machine Learning Researcher,205401,USD,205401,EX,FT,Denmark,M,Denmark,100,"R, TensorFlow, Mathematics",PhD,10,Healthcare,2024-03-18,2024-05-24,1464,8.4,Smart Analytics +AI07803,Robotics Engineer,57780,CAD,72225,EN,PT,Canada,S,Canada,100,"Java, NLP, Mathematics",PhD,1,Retail,2024-10-31,2025-01-10,2381,9.8,TechCorp Inc +AI07804,AI Research Scientist,110762,USD,110762,MI,CT,Norway,L,Sweden,100,"R, Data Visualization, Git, Docker",PhD,2,Real Estate,2024-11-03,2024-12-19,777,6.8,Cognitive Computing +AI07805,Deep Learning Engineer,157791,EUR,134122,SE,FL,France,L,France,50,"Git, Java, GCP, SQL, AWS",PhD,9,Gaming,2024-10-16,2024-11-01,1818,7.8,Cognitive Computing +AI07806,AI Software Engineer,146629,USD,146629,SE,PT,Denmark,S,Denmark,50,"Git, TensorFlow, Deep Learning",Associate,8,Manufacturing,2025-04-25,2025-06-02,1219,8.6,Autonomous Tech +AI07807,AI Consultant,67825,USD,67825,MI,FT,Sweden,S,Poland,100,"Java, Scala, R, SQL, Kubernetes",PhD,3,Education,2025-03-26,2025-06-03,1845,7.4,Autonomous Tech +AI07808,Autonomous Systems Engineer,53522,USD,53522,SE,FL,China,S,China,0,"PyTorch, GCP, Mathematics",Associate,9,Gaming,2025-04-19,2025-05-20,1898,8.6,Future Systems +AI07809,Robotics Engineer,96556,CAD,120695,MI,FT,Canada,L,Portugal,100,"PyTorch, Statistics, Deep Learning",Associate,4,Gaming,2024-10-10,2024-11-19,1150,9.1,DataVision Ltd +AI07810,AI Consultant,161008,USD,161008,SE,CT,Israel,L,Israel,0,"Docker, Deep Learning, Python, Git, Kubernetes",Master,9,Education,2025-03-25,2025-05-08,1648,5.7,Cognitive Computing +AI07811,Head of AI,71917,JPY,7910870,EN,PT,Japan,M,Hungary,100,"Tableau, PyTorch, GCP",Master,1,Media,2024-11-04,2024-12-29,2269,9.6,Neural Networks Co +AI07812,AI Research Scientist,143195,CAD,178994,EX,FL,Canada,S,Canada,50,"Java, Linux, Scala, NLP, Tableau",PhD,13,Healthcare,2025-04-12,2025-06-07,510,5.3,Neural Networks Co +AI07813,Robotics Engineer,135878,SGD,176641,SE,FT,Singapore,S,Singapore,0,"Azure, Kubernetes, Tableau",Bachelor,9,Technology,2024-12-28,2025-02-13,772,8.2,AI Innovations +AI07814,AI Consultant,58123,USD,58123,EN,PT,Finland,L,Finland,50,"Linux, AWS, GCP",Master,1,Manufacturing,2025-01-22,2025-02-10,1596,7.8,Digital Transformation LLC +AI07815,Principal Data Scientist,85459,USD,85459,EX,FT,India,M,Estonia,0,"Scala, Spark, AWS, Statistics",Master,16,Technology,2024-09-10,2024-11-20,1167,7.5,Advanced Robotics +AI07816,AI Consultant,188011,EUR,159809,EX,FL,Germany,S,Germany,0,"SQL, Kubernetes, Tableau",Bachelor,10,Transportation,2024-05-26,2024-07-10,2353,5.7,TechCorp Inc +AI07817,NLP Engineer,76608,USD,76608,EN,CT,United States,M,United States,100,"Hadoop, Spark, Python, GCP, SQL",Associate,1,Transportation,2024-11-19,2025-01-29,617,6.1,AI Innovations +AI07818,Computer Vision Engineer,87288,GBP,65466,MI,PT,United Kingdom,M,Egypt,50,"Statistics, Kubernetes, Tableau, Linux",Master,4,Energy,2024-08-22,2024-09-09,1983,8.5,Cloud AI Solutions +AI07819,AI Specialist,114472,JPY,12591920,SE,CT,Japan,S,France,50,"Mathematics, Hadoop, Spark, Tableau, GCP",Bachelor,5,Education,2024-10-03,2024-11-30,1545,8.3,DeepTech Ventures +AI07820,AI Research Scientist,115293,GBP,86470,MI,CT,United Kingdom,M,Romania,0,"PyTorch, Kubernetes, Deep Learning, Git",Associate,4,Finance,2024-01-17,2024-03-21,1165,6.1,AI Innovations +AI07821,Deep Learning Engineer,85770,USD,85770,SE,PT,South Korea,S,South Korea,50,"GCP, Computer Vision, Hadoop, Azure",PhD,7,Government,2024-08-30,2024-10-31,2128,9.5,Digital Transformation LLC +AI07822,Computer Vision Engineer,153843,EUR,130767,EX,FT,France,M,France,50,"Python, Tableau, SQL, PyTorch, Hadoop",Bachelor,16,Education,2025-02-23,2025-03-23,1151,9.8,DeepTech Ventures +AI07823,NLP Engineer,119824,CHF,107842,MI,FL,Switzerland,M,Switzerland,50,"Linux, Computer Vision, R, Python",PhD,3,Technology,2025-04-25,2025-05-13,2109,8.8,Neural Networks Co +AI07824,Data Engineer,88480,EUR,75208,MI,FL,Germany,M,Finland,100,"PyTorch, Kubernetes, MLOps, Scala, Java",Master,4,Energy,2024-02-16,2024-04-08,1029,9.3,DeepTech Ventures +AI07825,AI Research Scientist,86607,USD,86607,SE,PT,Finland,S,Finland,100,"GCP, AWS, MLOps",PhD,7,Consulting,2024-04-24,2024-05-12,2162,8.8,Digital Transformation LLC +AI07826,AI Research Scientist,185098,EUR,157333,EX,FL,Netherlands,M,Netherlands,50,"Docker, Azure, Git, Deep Learning",Bachelor,18,Gaming,2024-04-11,2024-05-28,902,5.8,AI Innovations +AI07827,AI Specialist,42629,USD,42629,EN,FT,South Korea,S,Sweden,0,"Spark, Hadoop, Tableau",Bachelor,0,Energy,2024-07-06,2024-07-21,1250,5.1,Cloud AI Solutions +AI07828,AI Architect,73796,EUR,62727,EN,FL,France,L,France,100,"Deep Learning, SQL, PyTorch",Bachelor,0,Government,2024-06-09,2024-07-23,2437,5.8,Cognitive Computing +AI07829,AI Consultant,145709,USD,145709,EX,FT,United States,S,Mexico,100,"Python, Azure, Tableau, Statistics",Bachelor,18,Energy,2024-09-11,2024-09-26,1740,7.9,TechCorp Inc +AI07830,Principal Data Scientist,153383,CHF,138045,MI,FT,Switzerland,M,Switzerland,100,"Kubernetes, SQL, Tableau",Associate,4,Consulting,2024-02-21,2024-03-08,686,7.6,Quantum Computing Inc +AI07831,Data Analyst,138997,USD,138997,SE,CT,Israel,L,Israel,50,"Python, Git, Computer Vision, Java, GCP",Bachelor,5,Telecommunications,2024-11-15,2024-12-13,1685,6.3,Algorithmic Solutions +AI07832,ML Ops Engineer,52674,USD,52674,EN,CT,Israel,S,Italy,50,"Git, Tableau, Computer Vision, SQL",Master,0,Gaming,2024-01-12,2024-02-08,1383,7.3,Cloud AI Solutions +AI07833,NLP Engineer,46073,USD,46073,EN,PT,Sweden,S,France,0,"Python, MLOps, R",Bachelor,0,Manufacturing,2024-04-23,2024-06-29,1299,5.1,Advanced Robotics +AI07834,AI Architect,143115,EUR,121648,SE,FT,Austria,M,Austria,50,"Python, Data Visualization, TensorFlow, Statistics",Associate,9,Retail,2024-06-26,2024-08-20,1232,9.1,Smart Analytics +AI07835,Machine Learning Engineer,133093,EUR,113129,EX,CT,Austria,S,Austria,100,"Tableau, Docker, Hadoop, Scala, R",PhD,11,Media,2024-07-25,2024-09-09,1717,5.9,Neural Networks Co +AI07836,Autonomous Systems Engineer,99958,USD,99958,MI,CT,Sweden,M,Romania,50,"Data Visualization, Java, NLP",Associate,2,Retail,2024-10-20,2024-11-14,655,5.9,Autonomous Tech +AI07837,AI Consultant,100906,JPY,11099660,MI,PT,Japan,M,Nigeria,0,"Mathematics, R, Deep Learning",Associate,3,Finance,2024-11-23,2025-01-08,1322,9.6,DeepTech Ventures +AI07838,Principal Data Scientist,73621,USD,73621,EN,PT,Ireland,L,Ireland,0,"Java, Scala, Python",Master,0,Finance,2024-12-14,2025-01-19,1999,7.3,DeepTech Ventures +AI07839,ML Ops Engineer,131785,AUD,177910,SE,CT,Australia,M,Mexico,0,"PyTorch, Linux, Computer Vision, Azure",Master,5,Real Estate,2025-02-03,2025-02-17,785,5.8,Predictive Systems +AI07840,NLP Engineer,302166,USD,302166,EX,FT,United States,L,United States,100,"Python, Linux, Hadoop, MLOps, Azure",PhD,15,Consulting,2024-05-16,2024-07-06,1539,8.4,Cognitive Computing +AI07841,AI Specialist,230443,USD,230443,EX,CT,United States,L,United States,50,"Git, R, AWS, SQL",Associate,11,Gaming,2024-05-24,2024-06-14,589,7.7,Digital Transformation LLC +AI07842,Machine Learning Engineer,52678,USD,52678,EN,PT,Sweden,S,Romania,0,"Kubernetes, SQL, Computer Vision, MLOps, Deep Learning",Master,0,Technology,2025-02-09,2025-04-21,2097,8.8,DataVision Ltd +AI07843,Data Scientist,219188,CHF,197269,EX,PT,Switzerland,M,Switzerland,0,"Kubernetes, Docker, Linux, Azure, Scala",Associate,19,Government,2024-07-05,2024-08-08,1009,8.2,Smart Analytics +AI07844,AI Specialist,63772,USD,63772,SE,PT,China,M,China,0,"PyTorch, Java, GCP, Mathematics",PhD,8,Retail,2024-10-24,2024-12-14,1928,8.2,Advanced Robotics +AI07845,NLP Engineer,63461,EUR,53942,MI,FT,Austria,S,Austria,50,"Computer Vision, Git, Python",Bachelor,2,Telecommunications,2025-01-12,2025-03-25,1638,7.5,Future Systems +AI07846,AI Consultant,125077,USD,125077,MI,PT,Norway,L,Norway,100,"Data Visualization, TensorFlow, Java, Deep Learning",PhD,4,Automotive,2024-02-15,2024-04-06,1340,7.5,Cloud AI Solutions +AI07847,Computer Vision Engineer,157223,EUR,133640,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Scala",Master,7,Manufacturing,2024-03-24,2024-04-12,1193,6.3,AI Innovations +AI07848,Data Scientist,216895,EUR,184361,EX,CT,Netherlands,L,India,100,"Tableau, Scala, AWS",Bachelor,19,Automotive,2024-02-08,2024-02-27,1605,9,Advanced Robotics +AI07849,AI Architect,133507,USD,133507,SE,FT,Sweden,S,Vietnam,50,"TensorFlow, Git, AWS, GCP, Deep Learning",Master,5,Finance,2024-02-28,2024-04-29,1863,6.8,Advanced Robotics +AI07850,Data Engineer,207722,USD,207722,EX,FL,South Korea,L,South Korea,100,"Statistics, Git, Spark, R",Bachelor,17,Media,2024-08-08,2024-09-20,1585,8.9,DataVision Ltd +AI07851,Machine Learning Engineer,91743,EUR,77982,MI,CT,Netherlands,L,Netherlands,50,"Hadoop, Tableau, Scala",Associate,2,Retail,2024-07-16,2024-09-19,1685,7,AI Innovations +AI07852,ML Ops Engineer,87600,USD,87600,MI,FT,Denmark,S,Denmark,100,"GCP, Docker, Python, Spark, NLP",PhD,2,Education,2025-02-18,2025-03-07,881,6.5,Cloud AI Solutions +AI07853,AI Product Manager,78893,USD,78893,MI,PT,South Korea,M,Israel,50,"Docker, PyTorch, Kubernetes, MLOps",PhD,4,Healthcare,2024-09-19,2024-10-29,1284,9.5,Machine Intelligence Group +AI07854,Research Scientist,139691,USD,139691,EX,PT,Israel,S,Israel,100,"Linux, Python, Data Visualization",Master,15,Media,2024-10-24,2024-11-13,800,6.9,Quantum Computing Inc +AI07855,Principal Data Scientist,71086,USD,71086,MI,FL,Finland,S,Finland,0,"Hadoop, Azure, NLP, PyTorch, TensorFlow",Associate,2,Telecommunications,2025-04-12,2025-06-07,2412,6.7,TechCorp Inc +AI07856,AI Consultant,38307,USD,38307,SE,FL,India,M,India,50,"Hadoop, PyTorch, Computer Vision, SQL",Master,7,Education,2024-08-13,2024-10-13,1489,5.8,AI Innovations +AI07857,Principal Data Scientist,236250,USD,236250,EX,FT,Norway,L,Norway,50,"SQL, Mathematics, Java",PhD,15,Automotive,2024-02-24,2024-03-27,1164,7.3,Algorithmic Solutions +AI07858,NLP Engineer,94410,CHF,84969,MI,CT,Switzerland,S,Switzerland,50,"Hadoop, Linux, Computer Vision, Spark, PyTorch",PhD,4,Automotive,2024-03-26,2024-05-03,1633,9.5,Cloud AI Solutions +AI07859,ML Ops Engineer,239612,EUR,203670,EX,PT,Austria,L,Israel,100,"Docker, Scala, Java, Deep Learning, R",Associate,10,Healthcare,2024-05-07,2024-05-29,1636,5.3,Algorithmic Solutions +AI07860,Data Analyst,49846,USD,49846,EN,FT,South Korea,L,South Korea,50,"TensorFlow, SQL, Mathematics",Bachelor,1,Manufacturing,2024-09-12,2024-11-07,602,9.6,Cloud AI Solutions +AI07861,Data Scientist,90589,SGD,117766,MI,CT,Singapore,M,Singapore,50,"Computer Vision, Linux, MLOps, Scala, Kubernetes",Master,3,Real Estate,2024-10-29,2024-11-30,2105,8.8,Cloud AI Solutions +AI07862,Machine Learning Researcher,75857,USD,75857,EN,FT,Denmark,S,Denmark,100,"R, Spark, GCP",Associate,0,Transportation,2025-04-05,2025-06-04,1331,7.5,Future Systems +AI07863,Machine Learning Engineer,229106,USD,229106,EX,PT,United States,S,United States,0,"Python, MLOps, Data Visualization, Deep Learning",Associate,10,Transportation,2024-06-03,2024-06-28,703,8.9,DeepTech Ventures +AI07864,Robotics Engineer,226048,EUR,192141,EX,FT,Germany,M,Germany,100,"Java, PyTorch, TensorFlow, SQL",PhD,15,Media,2025-01-28,2025-02-17,1648,8.8,Cloud AI Solutions +AI07865,Robotics Engineer,74551,EUR,63368,MI,PT,Austria,S,Austria,0,"R, Statistics, Mathematics, Data Visualization",Associate,3,Finance,2024-06-09,2024-08-20,1298,5.1,Autonomous Tech +AI07866,Deep Learning Engineer,209614,EUR,178172,EX,CT,Netherlands,S,Netherlands,100,"Scala, NLP, Kubernetes",Associate,18,Automotive,2024-03-08,2024-04-28,1958,7.1,Algorithmic Solutions +AI07867,Research Scientist,62202,USD,62202,EN,PT,Ireland,S,Hungary,100,"Statistics, Spark, Scala, Linux",Master,1,Technology,2024-09-13,2024-10-19,2499,8.3,Digital Transformation LLC +AI07868,Data Engineer,76226,SGD,99094,EN,CT,Singapore,L,Singapore,100,"Spark, SQL, Python, Scala, Deep Learning",Master,1,Government,2024-10-30,2024-12-11,1269,5.5,DataVision Ltd +AI07869,Principal Data Scientist,186638,CHF,167974,SE,FL,Switzerland,M,Switzerland,100,"Spark, Linux, Python",PhD,9,Consulting,2024-03-01,2024-05-07,1062,8.2,Smart Analytics +AI07870,AI Research Scientist,275375,USD,275375,EX,FT,Ireland,L,Ireland,50,"Mathematics, Azure, Scala",Associate,15,Healthcare,2024-07-29,2024-09-19,1842,6,Autonomous Tech +AI07871,Autonomous Systems Engineer,59693,JPY,6566230,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, SQL, Deep Learning",Associate,1,Finance,2024-11-15,2025-01-22,765,5.1,Cloud AI Solutions +AI07872,Research Scientist,72671,USD,72671,EN,FT,Sweden,L,Sweden,100,"Kubernetes, Scala, Linux, Docker, NLP",Bachelor,1,Retail,2024-10-18,2024-11-25,827,8.9,Cognitive Computing +AI07873,AI Architect,103897,AUD,140261,MI,PT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, SQL, Deep Learning",Master,3,Telecommunications,2024-12-29,2025-03-02,547,9.2,TechCorp Inc +AI07874,Head of AI,101567,AUD,137115,SE,FL,Australia,S,Australia,0,"Linux, Hadoop, MLOps",Master,6,Real Estate,2024-09-11,2024-10-07,1857,9.1,Predictive Systems +AI07875,Head of AI,74940,USD,74940,EN,PT,Sweden,L,Sweden,50,"GCP, Computer Vision, Python",PhD,1,Real Estate,2024-01-16,2024-03-22,2286,6.1,Algorithmic Solutions +AI07876,Machine Learning Researcher,204444,GBP,153333,EX,PT,United Kingdom,M,United Kingdom,50,"MLOps, Azure, TensorFlow, Python",Bachelor,13,Finance,2024-11-19,2024-12-19,1862,7,Autonomous Tech +AI07877,Deep Learning Engineer,264606,CAD,330758,EX,CT,Canada,L,Canada,100,"GCP, SQL, Azure, R",PhD,11,Government,2024-02-07,2024-04-10,2308,6.4,Digital Transformation LLC +AI07878,AI Product Manager,170883,EUR,145251,EX,CT,Germany,S,Germany,50,"Python, Git, Tableau, TensorFlow, Statistics",Master,17,Media,2024-03-23,2024-05-24,1102,7.6,Smart Analytics +AI07879,Data Analyst,152247,USD,152247,MI,FT,Denmark,L,Denmark,100,"SQL, Scala, Statistics",PhD,2,Transportation,2024-05-15,2024-06-06,529,8.5,Machine Intelligence Group +AI07880,AI Specialist,75029,AUD,101289,MI,FT,Australia,M,Australia,100,"Hadoop, MLOps, Tableau, GCP",Bachelor,4,Manufacturing,2024-09-09,2024-10-06,2288,8.7,DeepTech Ventures +AI07881,Machine Learning Engineer,44910,USD,44910,SE,FL,India,M,India,50,"Azure, R, Statistics, NLP",Master,8,Transportation,2024-06-09,2024-07-10,1285,6.9,TechCorp Inc +AI07882,Autonomous Systems Engineer,57794,GBP,43346,EN,FT,United Kingdom,M,United Kingdom,0,"NLP, AWS, R, Python, TensorFlow",Master,0,Finance,2024-03-01,2024-05-11,1515,10,Future Systems +AI07883,AI Research Scientist,155551,USD,155551,SE,FT,Denmark,S,Netherlands,50,"GCP, Linux, MLOps",Master,9,Finance,2024-12-08,2025-01-14,2040,8.3,TechCorp Inc +AI07884,Computer Vision Engineer,185612,USD,185612,EX,FL,Ireland,L,Ireland,50,"Scala, PyTorch, NLP",Master,13,Manufacturing,2025-04-27,2025-06-28,1410,9.3,Cognitive Computing +AI07885,Deep Learning Engineer,69810,JPY,7679100,EN,FL,Japan,M,Japan,50,"Docker, Scala, Python, Statistics, Hadoop",Master,0,Retail,2024-04-20,2024-06-12,874,5.9,Future Systems +AI07886,Machine Learning Engineer,108934,EUR,92594,MI,PT,Netherlands,L,Philippines,0,"Hadoop, Linux, NLP",PhD,3,Real Estate,2024-10-04,2024-10-31,2217,8.1,TechCorp Inc +AI07887,Robotics Engineer,116867,USD,116867,MI,FL,United States,M,United States,100,"Python, Deep Learning, Hadoop, Docker",Bachelor,4,Technology,2024-05-29,2024-07-30,1731,9.8,TechCorp Inc +AI07888,Principal Data Scientist,107417,EUR,91304,MI,FL,Austria,L,Czech Republic,100,"Spark, Computer Vision, Azure, SQL, Scala",Bachelor,2,Manufacturing,2024-12-12,2025-01-29,581,8.2,Quantum Computing Inc +AI07889,Autonomous Systems Engineer,60938,EUR,51797,EN,FT,Austria,S,Austria,50,"Tableau, Python, TensorFlow",Bachelor,1,Telecommunications,2024-04-06,2024-04-24,1259,6.8,AI Innovations +AI07890,Computer Vision Engineer,228287,GBP,171215,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Azure, Scala, SQL, Git",Master,14,Education,2024-04-17,2024-05-28,1740,9.3,DataVision Ltd +AI07891,AI Consultant,149332,USD,149332,SE,PT,Norway,M,Norway,50,"Deep Learning, R, Kubernetes",PhD,7,Energy,2024-07-02,2024-07-31,1673,8.9,Smart Analytics +AI07892,Autonomous Systems Engineer,101212,CAD,126515,SE,PT,Canada,M,Canada,100,"NLP, Scala, Python, PyTorch",Master,6,Media,2024-03-02,2024-03-21,1825,9.5,Algorithmic Solutions +AI07893,AI Architect,136111,USD,136111,MI,PT,Denmark,L,Denmark,0,"Scala, AWS, Hadoop, Python, Git",Associate,2,Automotive,2025-03-24,2025-05-11,1343,5.9,Future Systems +AI07894,Autonomous Systems Engineer,106323,GBP,79742,MI,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, Scala",Bachelor,3,Technology,2024-12-23,2025-02-28,2392,8.7,DeepTech Ventures +AI07895,Computer Vision Engineer,156650,AUD,211478,EX,FT,Australia,M,Netherlands,50,"Data Visualization, Azure, SQL, Hadoop, Java",Master,12,Transportation,2024-08-19,2024-10-15,763,5.7,Algorithmic Solutions +AI07896,Data Scientist,137174,EUR,116598,SE,PT,France,M,Philippines,0,"Java, Python, Data Visualization, AWS",Bachelor,5,Consulting,2025-04-16,2025-05-09,1132,7.2,Cognitive Computing +AI07897,AI Product Manager,106794,USD,106794,MI,CT,Finland,L,South Korea,100,"MLOps, AWS, Tableau, SQL, Python",Associate,2,Retail,2025-04-06,2025-05-12,1189,6.1,Quantum Computing Inc +AI07898,Autonomous Systems Engineer,229594,CAD,286993,EX,PT,Canada,M,Canada,0,"Python, Linux, MLOps",PhD,15,Energy,2024-11-24,2024-12-23,1826,7.1,Quantum Computing Inc +AI07899,Autonomous Systems Engineer,72245,EUR,61408,EN,PT,Netherlands,M,Netherlands,50,"SQL, PyTorch, AWS, Linux",PhD,0,Finance,2024-10-30,2024-12-09,2296,7.6,Autonomous Tech +AI07900,AI Architect,154453,USD,154453,SE,PT,Ireland,L,Ireland,0,"Data Visualization, Linux, R, Python, Azure",Associate,6,Retail,2024-12-25,2025-03-07,1418,8.6,Algorithmic Solutions +AI07901,AI Specialist,64086,EUR,54473,EN,CT,Germany,S,Romania,50,"Java, R, SQL, Git, Deep Learning",Bachelor,1,Technology,2024-07-23,2024-08-17,2472,5.1,Autonomous Tech +AI07902,ML Ops Engineer,101108,EUR,85942,MI,PT,France,L,France,100,"Statistics, Linux, Mathematics",Bachelor,3,Energy,2025-04-03,2025-06-05,2003,6.3,Machine Intelligence Group +AI07903,Head of AI,88469,USD,88469,EN,FL,Denmark,L,Denmark,100,"Python, Linux, MLOps",PhD,1,Gaming,2024-12-01,2025-02-07,626,6,Digital Transformation LLC +AI07904,Data Engineer,111556,USD,111556,EX,CT,China,M,China,50,"SQL, GCP, Kubernetes",Master,15,Telecommunications,2024-11-05,2024-12-19,1737,5.5,Quantum Computing Inc +AI07905,AI Research Scientist,95017,EUR,80764,MI,FT,Netherlands,S,Thailand,100,"Azure, SQL, Computer Vision, R",Bachelor,2,Transportation,2025-03-23,2025-04-09,1717,7.8,Cognitive Computing +AI07906,Data Analyst,98367,AUD,132795,SE,PT,Australia,S,Mexico,50,"Docker, Statistics, Python, NLP, Tableau",PhD,7,Gaming,2024-02-04,2024-04-07,1534,8.7,Smart Analytics +AI07907,AI Product Manager,92735,EUR,78825,EN,PT,Germany,L,Chile,0,"Tableau, SQL, TensorFlow",PhD,0,Finance,2025-04-28,2025-05-30,1976,5.2,TechCorp Inc +AI07908,Principal Data Scientist,135039,USD,135039,SE,FL,Ireland,M,Ireland,0,"Python, Azure, Data Visualization, SQL",Master,7,Media,2024-04-06,2024-05-24,1236,8.6,Machine Intelligence Group +AI07909,Machine Learning Engineer,205457,EUR,174638,EX,FT,Netherlands,M,Netherlands,50,"Git, Kubernetes, Hadoop",Bachelor,10,Technology,2025-03-30,2025-04-17,1285,9.3,Future Systems +AI07910,Deep Learning Engineer,86892,JPY,9558120,MI,FL,Japan,S,Japan,50,"MLOps, Python, Linux, TensorFlow, GCP",PhD,2,Technology,2024-06-24,2024-07-20,1287,5.6,Neural Networks Co +AI07911,AI Product Manager,100067,EUR,85057,MI,FL,Netherlands,L,Netherlands,100,"AWS, Deep Learning, Computer Vision",PhD,4,Healthcare,2024-12-18,2025-02-04,1780,5.7,Advanced Robotics +AI07912,Autonomous Systems Engineer,86435,USD,86435,EN,CT,Sweden,L,Sweden,50,"Kubernetes, NLP, Tableau, Python, Computer Vision",PhD,1,Education,2024-12-18,2025-01-04,2053,6.1,Machine Intelligence Group +AI07913,AI Product Manager,69261,SGD,90039,MI,FL,Singapore,S,Singapore,100,"Python, SQL, Docker",Associate,2,Automotive,2024-05-26,2024-07-27,1673,7,Cloud AI Solutions +AI07914,Computer Vision Engineer,187635,CHF,168872,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, AWS, MLOps, R, GCP",PhD,5,Consulting,2024-06-23,2024-08-21,2261,8.7,Neural Networks Co +AI07915,Data Engineer,150751,CHF,135676,MI,FT,Switzerland,M,Switzerland,50,"Statistics, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2025-02-21,2025-04-12,1563,7.4,Machine Intelligence Group +AI07916,AI Product Manager,117003,AUD,157954,SE,FL,Australia,M,Australia,100,"TensorFlow, AWS, MLOps, Azure, Linux",PhD,8,Manufacturing,2025-02-25,2025-05-09,533,8.4,DataVision Ltd +AI07917,Machine Learning Engineer,81733,EUR,69473,EN,FL,France,L,Belgium,50,"Azure, TensorFlow, Tableau, Python",Associate,0,Real Estate,2024-04-03,2024-05-06,1383,8.5,AI Innovations +AI07918,AI Architect,187345,USD,187345,EX,CT,Ireland,S,Ireland,0,"R, Data Visualization, SQL, Docker",Master,11,Gaming,2024-03-22,2024-05-05,1543,8.3,Cognitive Computing +AI07919,Robotics Engineer,143200,USD,143200,MI,PT,Denmark,L,Denmark,100,"Spark, Computer Vision, Data Visualization, GCP, AWS",PhD,3,Transportation,2025-02-15,2025-03-26,1646,7.2,Smart Analytics +AI07920,AI Product Manager,68868,EUR,58538,EN,FL,Germany,S,Finland,0,"NLP, TensorFlow, Azure",PhD,1,Education,2024-09-02,2024-10-25,571,6.7,Predictive Systems +AI07921,Autonomous Systems Engineer,79844,USD,79844,MI,CT,Sweden,M,Mexico,0,"Kubernetes, AWS, NLP",Master,2,Telecommunications,2024-01-20,2024-02-28,1962,5.4,Smart Analytics +AI07922,Research Scientist,158799,USD,158799,SE,FT,Denmark,L,Denmark,0,"Scala, R, Git",PhD,9,Education,2024-12-30,2025-02-02,1832,6.6,Quantum Computing Inc +AI07923,AI Architect,125614,EUR,106772,SE,FT,Netherlands,L,Argentina,100,"PyTorch, Python, GCP",Bachelor,5,Automotive,2024-05-23,2024-07-05,2140,5.6,Predictive Systems +AI07924,AI Software Engineer,104482,USD,104482,MI,FT,United States,L,United States,0,"Java, SQL, Statistics",PhD,3,Gaming,2024-11-22,2024-12-09,1939,5.3,Neural Networks Co +AI07925,Deep Learning Engineer,196895,EUR,167361,EX,FT,Austria,M,Austria,50,"Scala, Spark, PyTorch",Bachelor,16,Gaming,2024-07-30,2024-10-08,751,6.9,AI Innovations +AI07926,Computer Vision Engineer,133125,EUR,113156,SE,PT,Germany,M,Germany,50,"MLOps, R, Statistics",Master,8,Consulting,2025-03-17,2025-04-28,1400,6.3,DeepTech Ventures +AI07927,AI Specialist,182420,USD,182420,EX,CT,South Korea,L,South Korea,50,"PyTorch, Data Visualization, Spark",Master,17,Energy,2024-07-03,2024-07-26,1745,8.9,Predictive Systems +AI07928,AI Architect,151509,CHF,136358,SE,CT,Switzerland,M,Switzerland,100,"TensorFlow, Python, Kubernetes, AWS",Master,8,Transportation,2024-01-07,2024-02-26,1536,5.8,Advanced Robotics +AI07929,Head of AI,69352,USD,69352,MI,CT,Finland,M,Finland,0,"Data Visualization, TensorFlow, Azure",PhD,3,Manufacturing,2024-12-25,2025-02-02,1882,6.8,Advanced Robotics +AI07930,NLP Engineer,45522,USD,45522,SE,PT,India,S,India,0,"Computer Vision, Hadoop, Git, MLOps",PhD,9,Automotive,2024-04-08,2024-05-06,1194,6.9,Future Systems +AI07931,Data Engineer,43570,USD,43570,SE,PT,India,S,India,100,"MLOps, Hadoop, Spark, NLP, Mathematics",Associate,9,Energy,2024-08-05,2024-09-23,1359,8.8,AI Innovations +AI07932,AI Software Engineer,98915,USD,98915,MI,CT,Israel,M,Israel,0,"Docker, Git, TensorFlow, GCP",Associate,3,Real Estate,2025-03-02,2025-04-18,2083,7.5,Machine Intelligence Group +AI07933,Research Scientist,132893,USD,132893,MI,FT,Norway,M,Thailand,50,"Computer Vision, SQL, Tableau",Bachelor,2,Real Estate,2024-10-23,2024-11-16,1749,6.9,TechCorp Inc +AI07934,ML Ops Engineer,97204,CHF,87484,EN,PT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Docker",Bachelor,1,Finance,2025-03-31,2025-04-29,816,9.8,Predictive Systems +AI07935,Machine Learning Engineer,127523,USD,127523,MI,FL,United States,M,United States,0,"Hadoop, Mathematics, Docker, Data Visualization, Kubernetes",Bachelor,2,Education,2024-04-13,2024-04-27,634,5.7,Quantum Computing Inc +AI07936,AI Product Manager,89735,USD,89735,EN,CT,Norway,L,Norway,50,"Java, Python, Git",Associate,0,Government,2025-03-10,2025-04-14,757,6.2,TechCorp Inc +AI07937,Research Scientist,97385,USD,97385,MI,PT,Norway,S,Norway,0,"Docker, PyTorch, NLP, Python",PhD,4,Education,2024-12-16,2025-02-13,1489,5.8,Autonomous Tech +AI07938,Machine Learning Researcher,52180,USD,52180,EN,CT,Sweden,S,Egypt,100,"PyTorch, Java, Statistics",Associate,0,Finance,2024-12-05,2025-01-07,2313,7.8,DataVision Ltd +AI07939,Robotics Engineer,233176,USD,233176,EX,FT,Denmark,L,Denmark,0,"Hadoop, Python, Azure, TensorFlow",Bachelor,18,Media,2024-07-09,2024-08-04,2378,6.6,Digital Transformation LLC +AI07940,NLP Engineer,151930,AUD,205106,EX,FT,Australia,M,Australia,100,"NLP, Java, PyTorch, TensorFlow",PhD,17,Energy,2024-05-05,2024-07-01,543,9.3,DeepTech Ventures +AI07941,Data Analyst,166632,SGD,216622,EX,PT,Singapore,M,Singapore,100,"Linux, MLOps, Python",Bachelor,15,Media,2025-02-14,2025-03-25,1476,5.7,Cloud AI Solutions +AI07942,Data Analyst,100715,USD,100715,MI,CT,United States,M,United States,0,"SQL, Statistics, Git, Data Visualization, Java",Associate,2,Consulting,2024-06-25,2024-08-27,1320,6,DeepTech Ventures +AI07943,Computer Vision Engineer,74580,JPY,8203800,EN,CT,Japan,S,Japan,0,"Git, Computer Vision, Tableau",Associate,0,Telecommunications,2024-03-02,2024-04-17,616,5.5,DataVision Ltd +AI07944,AI Architect,120355,SGD,156462,SE,FT,Singapore,M,Philippines,50,"Scala, Python, MLOps, SQL",Master,5,Gaming,2024-03-11,2024-03-25,1771,5.8,Neural Networks Co +AI07945,AI Specialist,129835,USD,129835,EX,CT,Ireland,S,Ireland,100,"Deep Learning, Spark, Tableau, Python",Bachelor,11,Media,2025-01-24,2025-03-28,1977,7.4,Cognitive Computing +AI07946,AI Product Manager,143095,EUR,121631,SE,FT,Netherlands,L,Russia,0,"MLOps, Kubernetes, Tableau",Bachelor,5,Media,2024-08-04,2024-10-13,1147,8.4,Predictive Systems +AI07947,AI Consultant,162582,CHF,146324,SE,CT,Switzerland,M,Malaysia,100,"Data Visualization, Docker, Computer Vision, Git",PhD,9,Healthcare,2025-04-30,2025-05-18,558,6.1,Neural Networks Co +AI07948,Deep Learning Engineer,66995,USD,66995,EX,CT,India,M,India,100,"Python, MLOps, TensorFlow",Bachelor,13,Finance,2025-04-30,2025-05-22,1661,6,Cognitive Computing +AI07949,AI Specialist,99477,JPY,10942470,MI,PT,Japan,L,Japan,100,"Hadoop, R, Scala, Azure",Bachelor,2,Government,2024-10-18,2024-12-14,594,8.8,Algorithmic Solutions +AI07950,AI Architect,159574,USD,159574,SE,FT,Denmark,L,Ghana,50,"Python, Data Visualization, Git, PyTorch",Master,9,Finance,2025-04-07,2025-04-29,998,5.3,Predictive Systems +AI07951,AI Product Manager,23228,USD,23228,EN,PT,India,S,India,0,"MLOps, Hadoop, R, TensorFlow, Tableau",Associate,1,Technology,2024-03-01,2024-04-02,1213,7.5,DataVision Ltd +AI07952,AI Architect,173217,USD,173217,SE,CT,United States,M,United States,50,"Statistics, Linux, Docker, Deep Learning",Bachelor,5,Real Estate,2024-02-10,2024-03-18,1019,6.8,DataVision Ltd +AI07953,AI Research Scientist,80075,USD,80075,MI,PT,Finland,L,Finland,100,"SQL, AWS, TensorFlow, Mathematics, Linux",Bachelor,4,Healthcare,2024-05-31,2024-07-03,2425,8.4,Cognitive Computing +AI07954,Data Scientist,55361,JPY,6089710,EN,PT,Japan,S,Japan,100,"SQL, PyTorch, Hadoop, Kubernetes",Bachelor,1,Telecommunications,2024-07-09,2024-09-04,2030,5.8,Quantum Computing Inc +AI07955,Research Scientist,93720,USD,93720,MI,FL,Israel,M,Israel,50,"PyTorch, TensorFlow, MLOps",Master,4,Manufacturing,2024-10-22,2024-11-12,1971,5.9,Future Systems +AI07956,Data Engineer,103590,USD,103590,MI,FT,Finland,M,Ghana,0,"Python, AWS, Azure, Linux",Bachelor,3,Transportation,2024-10-28,2024-11-26,1170,6,Digital Transformation LLC +AI07957,Head of AI,166505,JPY,18315550,EX,PT,Japan,L,Japan,100,"Git, Docker, Python, GCP, Linux",PhD,17,Real Estate,2024-12-13,2025-01-02,858,5.3,Future Systems +AI07958,Deep Learning Engineer,150946,CHF,135851,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, Azure, Deep Learning",Associate,2,Transportation,2024-06-14,2024-08-26,1490,9.1,Cognitive Computing +AI07959,ML Ops Engineer,218604,AUD,295115,EX,PT,Australia,L,Ghana,50,"Tableau, Azure, AWS, Kubernetes, Java",PhD,17,Education,2024-04-17,2024-05-09,1976,5.3,Cognitive Computing +AI07960,Data Analyst,201864,USD,201864,EX,CT,Sweden,S,Sweden,100,"Computer Vision, Java, R",Associate,16,Transportation,2024-09-06,2024-10-26,523,6,Algorithmic Solutions +AI07961,AI Research Scientist,77414,AUD,104509,MI,PT,Australia,M,Argentina,100,"Scala, Java, Tableau",Bachelor,3,Energy,2024-01-13,2024-02-13,1416,5.2,TechCorp Inc +AI07962,Machine Learning Researcher,128494,EUR,109220,EX,FL,Austria,S,Austria,0,"Kubernetes, PyTorch, R",PhD,12,Transportation,2024-05-25,2024-08-04,730,5.5,Cognitive Computing +AI07963,AI Research Scientist,120539,USD,120539,EX,CT,China,L,China,0,"Python, GCP, Docker",Bachelor,10,Real Estate,2025-03-27,2025-06-06,572,8.7,Advanced Robotics +AI07964,AI Software Engineer,60570,USD,60570,EN,PT,Finland,L,Finland,0,"MLOps, Spark, TensorFlow, Kubernetes, SQL",Associate,1,Healthcare,2024-03-25,2024-04-16,1857,5.9,TechCorp Inc +AI07965,Research Scientist,88260,USD,88260,EN,PT,Denmark,S,Philippines,100,"Git, Statistics, Linux, Azure",Bachelor,0,Real Estate,2024-12-09,2025-01-01,1245,8.8,Smart Analytics +AI07966,Deep Learning Engineer,78518,USD,78518,MI,FT,Israel,S,Israel,50,"Hadoop, Kubernetes, Python, Deep Learning, Mathematics",Master,2,Real Estate,2024-09-12,2024-09-27,2279,8.7,TechCorp Inc +AI07967,Machine Learning Engineer,97759,EUR,83095,MI,FT,Netherlands,S,Netherlands,50,"PyTorch, GCP, Statistics, Docker",Master,2,Manufacturing,2025-03-11,2025-05-18,1358,6.1,TechCorp Inc +AI07968,Data Analyst,92686,EUR,78783,MI,FT,Germany,M,Israel,50,"Computer Vision, MLOps, TensorFlow, Python, PyTorch",PhD,2,Gaming,2025-02-10,2025-03-25,1588,9.7,Neural Networks Co +AI07969,Deep Learning Engineer,109730,CHF,98757,EN,CT,Switzerland,M,Switzerland,0,"Python, Spark, Tableau",Master,1,Manufacturing,2024-07-15,2024-09-05,1812,6.5,Neural Networks Co +AI07970,Computer Vision Engineer,61314,USD,61314,EX,FT,India,L,India,100,"Kubernetes, TensorFlow, MLOps",Bachelor,18,Telecommunications,2024-04-01,2024-05-20,953,5.8,Future Systems +AI07971,AI Research Scientist,34450,USD,34450,MI,CT,China,M,Switzerland,0,"Python, TensorFlow, Scala, Kubernetes, Java",Master,3,Retail,2024-07-06,2024-09-15,1840,8,Predictive Systems +AI07972,Deep Learning Engineer,104797,USD,104797,SE,CT,Ireland,S,Ireland,50,"Python, Data Visualization, Spark, SQL, Java",PhD,5,Retail,2025-01-28,2025-02-24,1987,8.8,Cognitive Computing +AI07973,NLP Engineer,143973,AUD,194364,SE,PT,Australia,L,Australia,100,"PyTorch, SQL, Hadoop",Bachelor,7,Education,2024-02-18,2024-04-18,683,9.4,Digital Transformation LLC +AI07974,Data Engineer,60516,USD,60516,EN,FL,Sweden,M,Sweden,50,"Java, PyTorch, Scala, Statistics",Master,0,Automotive,2024-09-13,2024-10-18,818,5.6,Machine Intelligence Group +AI07975,Autonomous Systems Engineer,110800,CHF,99720,MI,PT,Switzerland,M,Switzerland,50,"Python, Computer Vision, Kubernetes, R, TensorFlow",PhD,3,Healthcare,2024-05-13,2024-07-21,1718,5.9,TechCorp Inc +AI07976,Data Scientist,83576,USD,83576,SE,FT,South Korea,S,Norway,0,"Deep Learning, NLP, Data Visualization, Scala, Mathematics",Bachelor,5,Real Estate,2025-02-27,2025-05-03,1461,5.4,Advanced Robotics +AI07977,AI Consultant,150796,USD,150796,SE,CT,Finland,L,Finland,100,"Hadoop, NLP, Linux, Scala, Python",PhD,9,Media,2024-12-03,2024-12-23,766,5.7,Autonomous Tech +AI07978,Head of AI,67072,USD,67072,EN,PT,Israel,L,Israel,0,"Deep Learning, AWS, NLP, Docker, GCP",Associate,1,Telecommunications,2024-03-26,2024-05-01,1888,10,Cloud AI Solutions +AI07979,Robotics Engineer,51985,USD,51985,EN,FT,Sweden,S,Sweden,100,"AWS, R, MLOps, Azure",Master,0,Technology,2024-03-25,2024-05-18,2215,6.4,AI Innovations +AI07980,AI Product Manager,110993,USD,110993,SE,CT,Finland,M,Finland,100,"Linux, Tableau, SQL, Spark, Scala",PhD,5,Education,2024-04-12,2024-04-29,2320,5.5,Cloud AI Solutions +AI07981,Head of AI,94069,USD,94069,EN,FT,Norway,M,Norway,100,"R, TensorFlow, Java, Git, Python",Associate,1,Telecommunications,2024-09-14,2024-10-16,1036,7.7,DeepTech Ventures +AI07982,AI Architect,146889,CHF,132200,MI,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, Mathematics",PhD,4,Telecommunications,2025-03-04,2025-04-15,726,5.8,Advanced Robotics +AI07983,Principal Data Scientist,155346,USD,155346,SE,FL,United States,S,United States,0,"Computer Vision, Java, Git, Docker",Bachelor,9,Telecommunications,2025-01-01,2025-02-27,1994,9.9,TechCorp Inc +AI07984,Data Scientist,124124,EUR,105505,SE,CT,France,S,France,50,"TensorFlow, PyTorch, Tableau, Computer Vision",PhD,6,Gaming,2024-05-28,2024-08-07,1082,9.7,Cloud AI Solutions +AI07985,Deep Learning Engineer,137231,CAD,171539,EX,FT,Canada,S,Canada,100,"Docker, AWS, PyTorch, SQL",Associate,15,Consulting,2024-01-22,2024-03-22,1011,7.7,Advanced Robotics +AI07986,AI Architect,45728,CAD,57160,EN,CT,Canada,S,Canada,0,"MLOps, Docker, SQL",Master,1,Gaming,2024-04-21,2024-07-03,2066,5.7,Advanced Robotics +AI07987,Machine Learning Researcher,61291,EUR,52097,EN,FL,France,L,France,100,"SQL, MLOps, AWS, Hadoop",Bachelor,0,Education,2024-06-27,2024-08-09,1539,8.3,Neural Networks Co +AI07988,AI Architect,64443,EUR,54777,EN,FL,France,M,France,100,"Git, Kubernetes, Computer Vision",PhD,0,Media,2025-02-01,2025-04-11,2228,6.7,Future Systems +AI07989,Deep Learning Engineer,66409,USD,66409,EN,FL,United States,M,Colombia,50,"MLOps, Azure, Python, Kubernetes, Data Visualization",Bachelor,1,Healthcare,2024-11-05,2025-01-09,1753,8.3,Advanced Robotics +AI07990,NLP Engineer,76025,USD,76025,EX,CT,China,S,China,0,"Deep Learning, PyTorch, Linux",Associate,10,Retail,2024-05-14,2024-06-05,1627,5,Cloud AI Solutions +AI07991,Machine Learning Researcher,211009,USD,211009,EX,FL,Ireland,L,Ireland,100,"SQL, Computer Vision, Tableau",Master,10,Manufacturing,2025-04-11,2025-05-31,1249,5.6,Algorithmic Solutions +AI07992,AI Product Manager,154995,EUR,131746,SE,FL,Germany,L,Poland,50,"Scala, NLP, Mathematics, Docker, Java",PhD,6,Government,2025-03-26,2025-05-17,1985,7.3,Cloud AI Solutions +AI07993,AI Consultant,44675,USD,44675,SE,FL,India,L,Singapore,0,"Docker, Scala, MLOps, Linux, SQL",PhD,7,Finance,2024-11-11,2025-01-21,782,8.5,AI Innovations +AI07994,Research Scientist,87124,SGD,113261,EN,PT,Singapore,L,Singapore,0,"Scala, Java, TensorFlow, GCP, Deep Learning",Bachelor,1,Healthcare,2024-03-10,2024-04-25,1861,5.7,Cognitive Computing +AI07995,Robotics Engineer,122808,USD,122808,MI,PT,Sweden,L,Sweden,0,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,4,Consulting,2024-03-23,2024-05-16,1697,9,Predictive Systems +AI07996,Data Engineer,133625,JPY,14698750,SE,PT,Japan,L,Ireland,50,"Azure, Python, Mathematics",Associate,8,Government,2024-11-17,2024-12-03,1052,9.2,AI Innovations +AI07997,Autonomous Systems Engineer,71366,USD,71366,EN,CT,Israel,M,Israel,0,"TensorFlow, NLP, Kubernetes, Data Visualization, AWS",Bachelor,0,Energy,2024-10-28,2024-11-22,2129,7.3,Neural Networks Co +AI07998,AI Consultant,123920,USD,123920,SE,CT,Sweden,S,Brazil,50,"Docker, AWS, Hadoop, Java, Azure",Bachelor,5,Automotive,2025-01-23,2025-03-18,972,8.5,Autonomous Tech +AI07999,AI Product Manager,134233,JPY,14765630,MI,CT,Japan,L,Japan,50,"GCP, SQL, Tableau, Kubernetes",PhD,4,Finance,2024-09-13,2024-11-05,1135,6.4,Machine Intelligence Group +AI08000,Machine Learning Researcher,109561,USD,109561,MI,FT,Sweden,L,Netherlands,0,"Python, Java, NLP, Linux",Bachelor,4,Finance,2024-04-09,2024-06-13,1402,8.9,AI Innovations +AI08001,Data Scientist,71713,SGD,93227,EN,PT,Singapore,L,Thailand,50,"GCP, Statistics, Tableau, Scala",Associate,0,Government,2024-05-02,2024-07-10,2238,5.7,Quantum Computing Inc +AI08002,Robotics Engineer,58752,CAD,73440,EN,PT,Canada,M,Canada,100,"SQL, TensorFlow, Git, AWS",Master,0,Automotive,2024-12-13,2025-01-06,878,8,Digital Transformation LLC +AI08003,Autonomous Systems Engineer,118460,USD,118460,MI,FL,Norway,M,Norway,50,"NLP, Mathematics, Deep Learning, Python",Bachelor,4,Retail,2024-06-25,2024-07-30,1000,8.5,DataVision Ltd +AI08004,Machine Learning Researcher,82449,EUR,70082,EN,FL,Netherlands,M,Norway,0,"NLP, Spark, TensorFlow",Bachelor,0,Telecommunications,2024-05-25,2024-06-19,1871,8,Advanced Robotics +AI08005,Machine Learning Engineer,80025,SGD,104033,MI,FT,Singapore,S,Singapore,100,"Hadoop, Tableau, Spark, GCP",PhD,4,Real Estate,2024-04-18,2024-06-12,1556,8.2,Quantum Computing Inc +AI08006,Robotics Engineer,221861,USD,221861,EX,FL,Ireland,S,Ireland,100,"Kubernetes, GCP, Linux, SQL, Data Visualization",Bachelor,10,Manufacturing,2024-11-13,2025-01-24,818,7.2,TechCorp Inc +AI08007,AI Consultant,284268,USD,284268,EX,FT,Ireland,L,Ireland,50,"Data Visualization, AWS, PyTorch, Spark, Hadoop",Master,18,Technology,2024-05-23,2024-06-07,2236,5.1,Autonomous Tech +AI08008,Deep Learning Engineer,171547,SGD,223011,EX,PT,Singapore,S,Singapore,50,"Linux, Java, Tableau, GCP, Kubernetes",PhD,12,Retail,2025-04-09,2025-04-25,1173,9.2,Cloud AI Solutions +AI08009,AI Software Engineer,323208,CHF,290887,EX,FL,Switzerland,L,Switzerland,100,"Tableau, Deep Learning, Data Visualization, SQL, Linux",Master,14,Energy,2024-05-24,2024-07-04,1871,5.7,Cognitive Computing +AI08010,AI Product Manager,113656,USD,113656,MI,FT,United States,M,Ireland,50,"Statistics, SQL, MLOps",Master,2,Government,2024-10-04,2024-11-20,1427,7,Digital Transformation LLC +AI08011,Principal Data Scientist,77152,USD,77152,MI,FL,Ireland,M,Ireland,50,"AWS, TensorFlow, GCP, Deep Learning, SQL",PhD,4,Technology,2025-02-01,2025-04-01,2268,8.4,Algorithmic Solutions +AI08012,NLP Engineer,222207,SGD,288869,EX,FT,Singapore,L,Singapore,100,"Statistics, Tableau, Scala",Associate,13,Telecommunications,2025-01-18,2025-02-28,1899,6.6,Smart Analytics +AI08013,AI Consultant,196407,USD,196407,EX,PT,Denmark,S,Denmark,100,"Java, SQL, Deep Learning, Computer Vision, Spark",Bachelor,17,Government,2024-11-01,2025-01-03,2236,7.5,Autonomous Tech +AI08014,Research Scientist,27068,USD,27068,MI,PT,India,M,India,100,"Spark, Statistics, PyTorch",Bachelor,4,Retail,2024-08-27,2024-11-08,2145,9.7,Neural Networks Co +AI08015,AI Research Scientist,99789,USD,99789,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Statistics, GCP",PhD,7,Automotive,2025-03-14,2025-05-09,564,6.7,Predictive Systems +AI08016,Research Scientist,157360,CHF,141624,SE,CT,Switzerland,S,Czech Republic,50,"Java, Scala, MLOps, NLP",Bachelor,7,Education,2024-12-28,2025-02-03,2474,5,Algorithmic Solutions +AI08017,Data Engineer,73368,CHF,66031,EN,CT,Switzerland,S,Switzerland,0,"Spark, Linux, Python",Bachelor,1,Healthcare,2024-08-03,2024-09-29,764,6.3,Smart Analytics +AI08018,AI Specialist,130971,CHF,117874,EN,FL,Switzerland,L,Switzerland,0,"TensorFlow, Python, Mathematics",Master,1,Transportation,2024-07-09,2024-09-09,2002,8.4,DataVision Ltd +AI08019,Autonomous Systems Engineer,42371,USD,42371,MI,FT,China,S,China,100,"SQL, Scala, Git",Associate,3,Consulting,2024-02-08,2024-03-16,2063,6.8,Machine Intelligence Group +AI08020,AI Architect,96446,USD,96446,EN,PT,United States,L,Denmark,50,"PyTorch, Linux, Statistics",Master,1,Energy,2024-02-11,2024-03-22,1721,8.2,DeepTech Ventures +AI08021,Data Scientist,253346,USD,253346,EX,FT,United States,M,United States,50,"NLP, Linux, Azure",PhD,15,Manufacturing,2024-11-12,2025-01-14,1765,5.8,Smart Analytics +AI08022,AI Specialist,210688,JPY,23175680,EX,FT,Japan,M,Japan,50,"MLOps, Hadoop, Python",Associate,14,Transportation,2024-01-04,2024-02-16,1448,5.1,Algorithmic Solutions +AI08023,Data Analyst,20088,USD,20088,EN,CT,India,S,India,50,"R, Azure, TensorFlow, Tableau, Git",Master,1,Healthcare,2024-11-06,2024-12-07,1065,6.7,AI Innovations +AI08024,AI Research Scientist,115869,EUR,98489,MI,FT,France,L,France,100,"Kubernetes, Azure, TensorFlow, Java, Scala",Bachelor,4,Gaming,2024-12-01,2025-01-14,890,5.5,Neural Networks Co +AI08025,Computer Vision Engineer,27041,USD,27041,MI,FL,India,M,Argentina,0,"Git, GCP, Scala, Deep Learning, TensorFlow",Associate,2,Manufacturing,2024-05-08,2024-07-11,631,8.4,Future Systems +AI08026,AI Research Scientist,133722,USD,133722,SE,FL,Ireland,S,Ireland,50,"Mathematics, Statistics, Java",Master,8,Government,2025-04-11,2025-05-30,2432,6.4,Advanced Robotics +AI08027,Autonomous Systems Engineer,75208,USD,75208,EN,PT,United States,S,Ukraine,0,"PyTorch, Azure, Java, Spark",PhD,0,Finance,2024-07-15,2024-08-15,980,5.1,Future Systems +AI08028,Machine Learning Researcher,109705,EUR,93249,MI,FT,Germany,M,Russia,0,"Python, Linux, NLP",PhD,4,Real Estate,2024-12-18,2025-01-13,2235,7.4,AI Innovations +AI08029,AI Consultant,55926,USD,55926,EN,FT,South Korea,M,Poland,50,"Python, SQL, MLOps",Master,1,Consulting,2024-05-08,2024-06-17,538,7,Advanced Robotics +AI08030,Data Analyst,154681,USD,154681,SE,PT,Denmark,L,Denmark,50,"Git, Hadoop, Tableau, Data Visualization",Associate,7,Government,2025-02-09,2025-04-17,975,9.4,Digital Transformation LLC +AI08031,NLP Engineer,72975,USD,72975,EX,PT,India,M,India,0,"GCP, Tableau, Scala",PhD,14,Technology,2024-04-10,2024-05-03,556,9.2,Machine Intelligence Group +AI08032,Deep Learning Engineer,122344,USD,122344,SE,CT,Sweden,M,Brazil,50,"Spark, AWS, Git, PyTorch",Bachelor,8,Real Estate,2024-05-16,2024-07-25,1732,7,DeepTech Ventures +AI08033,Machine Learning Researcher,78706,EUR,66900,MI,FT,Germany,M,Germany,0,"Data Visualization, AWS, Python, Spark, TensorFlow",PhD,2,Retail,2024-05-22,2024-07-24,737,9.5,Machine Intelligence Group +AI08034,Data Analyst,87488,EUR,74365,SE,FT,Austria,S,Austria,50,"Kubernetes, PyTorch, TensorFlow, Statistics",Bachelor,8,Automotive,2024-11-30,2024-12-30,2075,6.2,DeepTech Ventures +AI08035,Data Scientist,109945,GBP,82459,SE,PT,United Kingdom,S,Australia,50,"AWS, Data Visualization, Scala, Tableau, MLOps",Associate,5,Telecommunications,2025-02-20,2025-03-10,1706,6.6,Algorithmic Solutions +AI08036,Autonomous Systems Engineer,128555,USD,128555,SE,FT,United States,S,Ireland,0,"SQL, Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,9,Automotive,2024-09-23,2024-11-10,2140,6.4,DataVision Ltd +AI08037,Data Engineer,83558,USD,83558,EX,FL,China,M,Portugal,0,"Java, GCP, Tableau, Deep Learning",Associate,13,Healthcare,2024-11-22,2025-01-12,1439,8.8,Advanced Robotics +AI08038,Autonomous Systems Engineer,59257,USD,59257,SE,CT,China,L,China,50,"R, Mathematics, Tableau",Bachelor,8,Education,2024-02-09,2024-04-11,1925,9.6,DeepTech Ventures +AI08039,Research Scientist,211226,USD,211226,EX,CT,Sweden,L,Sweden,50,"Hadoop, Scala, GCP, Docker, R",PhD,10,Real Estate,2024-10-18,2024-12-08,1516,8.5,Cloud AI Solutions +AI08040,Data Engineer,58429,EUR,49665,EN,FT,Austria,S,Austria,50,"Linux, Python, Computer Vision, AWS",Master,0,Healthcare,2024-05-11,2024-07-10,1024,8.5,AI Innovations +AI08041,AI Specialist,30008,USD,30008,EN,CT,India,L,India,100,"Linux, PyTorch, Git, Computer Vision",Master,1,Real Estate,2024-10-29,2024-11-23,799,6.5,Machine Intelligence Group +AI08042,Principal Data Scientist,63440,USD,63440,EX,PT,India,M,India,0,"Hadoop, Java, SQL, Computer Vision",PhD,18,Energy,2024-10-19,2024-12-06,1042,9.3,DataVision Ltd +AI08043,AI Architect,75902,USD,75902,EN,PT,United States,S,United States,50,"AWS, Data Visualization, Tableau, Scala",Associate,0,Real Estate,2024-02-05,2024-03-03,1077,8.2,Algorithmic Solutions +AI08044,AI Consultant,212552,GBP,159414,EX,FL,United Kingdom,S,Austria,100,"SQL, Spark, MLOps",Associate,11,Finance,2025-03-20,2025-05-02,516,7.9,Neural Networks Co +AI08045,AI Product Manager,105830,EUR,89956,MI,FL,France,L,France,100,"Hadoop, GCP, Scala, Tableau",Bachelor,3,Healthcare,2024-08-16,2024-10-12,878,9.8,Autonomous Tech +AI08046,Head of AI,82250,USD,82250,MI,PT,Sweden,M,Sweden,0,"Azure, MLOps, Statistics, R, GCP",Associate,2,Consulting,2024-07-15,2024-08-29,1795,7.2,DataVision Ltd +AI08047,AI Product Manager,106488,EUR,90515,SE,PT,Germany,M,Germany,0,"PyTorch, Kubernetes, Computer Vision, TensorFlow, Spark",Bachelor,9,Telecommunications,2024-12-20,2025-01-31,960,7.2,Quantum Computing Inc +AI08048,Head of AI,147509,USD,147509,SE,CT,Sweden,L,Sweden,0,"Python, Mathematics, Linux, TensorFlow, Deep Learning",Master,6,Healthcare,2024-12-18,2025-01-25,1965,6,Cognitive Computing +AI08049,AI Specialist,107129,EUR,91060,MI,CT,Netherlands,L,Netherlands,0,"R, PyTorch, GCP, Computer Vision, Git",Bachelor,2,Automotive,2024-04-19,2024-05-30,1355,9.2,Machine Intelligence Group +AI08050,AI Research Scientist,263994,CHF,237595,EX,FT,Switzerland,S,Switzerland,100,"Azure, Python, MLOps, Kubernetes, Hadoop",Bachelor,19,Consulting,2024-12-11,2025-01-16,1088,6.4,Quantum Computing Inc +AI08051,NLP Engineer,115888,SGD,150654,MI,FT,Singapore,L,Australia,50,"Kubernetes, Docker, Spark, Linux, Computer Vision",Associate,2,Energy,2024-05-03,2024-06-29,2345,5.2,Autonomous Tech +AI08052,Research Scientist,183653,SGD,238749,EX,PT,Singapore,M,Singapore,100,"Statistics, Computer Vision, Python",Master,14,Government,2024-10-22,2024-12-06,2176,8.6,DeepTech Ventures +AI08053,Autonomous Systems Engineer,136651,SGD,177646,EX,FT,Singapore,S,Singapore,50,"Statistics, Python, AWS, PyTorch",Master,18,Real Estate,2024-12-20,2025-01-29,1776,8.5,Autonomous Tech +AI08054,AI Product Manager,138663,USD,138663,EX,CT,Finland,M,New Zealand,100,"Git, Python, Mathematics, Linux",Associate,13,Gaming,2024-06-16,2024-08-04,2319,6.5,Future Systems +AI08055,AI Software Engineer,156452,GBP,117339,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, Tableau, Statistics",Bachelor,10,Gaming,2024-03-26,2024-05-10,1929,7.2,Neural Networks Co +AI08056,Computer Vision Engineer,91988,USD,91988,MI,CT,United States,M,United States,50,"Git, Scala, Data Visualization",PhD,4,Healthcare,2024-07-23,2024-10-02,1514,8.5,TechCorp Inc +AI08057,AI Product Manager,170809,GBP,128107,EX,CT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, AWS, Computer Vision",Master,11,Telecommunications,2024-08-23,2024-09-06,1384,9.9,Digital Transformation LLC +AI08058,NLP Engineer,102306,EUR,86960,MI,PT,Netherlands,L,Indonesia,100,"SQL, NLP, Python",Master,4,Automotive,2024-10-19,2024-12-24,1838,8.7,Machine Intelligence Group +AI08059,Computer Vision Engineer,66585,EUR,56597,EN,CT,France,S,France,0,"NLP, PyTorch, MLOps, Kubernetes, TensorFlow",Associate,0,Education,2024-02-03,2024-02-27,1482,7.9,Predictive Systems +AI08060,Machine Learning Researcher,207692,CHF,186923,SE,CT,Switzerland,M,Switzerland,100,"Python, Spark, TensorFlow, Tableau, PyTorch",PhD,5,Transportation,2024-03-28,2024-06-02,1924,9.6,Quantum Computing Inc +AI08061,Data Analyst,129361,USD,129361,SE,CT,Sweden,M,Sweden,100,"PyTorch, Spark, Hadoop",Master,8,Finance,2024-06-01,2024-07-16,1043,10,Algorithmic Solutions +AI08062,Head of AI,97125,USD,97125,EN,CT,Denmark,L,Denmark,100,"Scala, Tableau, Kubernetes",PhD,0,Energy,2024-01-18,2024-03-28,760,9.3,Algorithmic Solutions +AI08063,Principal Data Scientist,97060,USD,97060,MI,PT,Finland,M,Finland,0,"R, AWS, Statistics, Linux, Deep Learning",PhD,3,Transportation,2024-12-16,2025-01-03,1883,9.8,Future Systems +AI08064,AI Software Engineer,69840,USD,69840,SE,FT,China,L,Spain,50,"Java, AWS, Computer Vision, Docker, Deep Learning",Master,9,Energy,2024-03-12,2024-04-04,2372,7.1,Machine Intelligence Group +AI08065,ML Ops Engineer,86753,EUR,73740,MI,PT,France,L,France,0,"Java, Hadoop, Linux",Associate,3,Real Estate,2024-11-28,2024-12-30,1934,6.7,Quantum Computing Inc +AI08066,Research Scientist,120164,USD,120164,EN,PT,Norway,L,Norway,50,"Computer Vision, Scala, SQL",Associate,1,Telecommunications,2024-02-21,2024-04-14,2276,8.7,Digital Transformation LLC +AI08067,Deep Learning Engineer,63400,USD,63400,EN,PT,Finland,M,Finland,100,"GCP, Tableau, PyTorch",Master,0,Telecommunications,2025-02-17,2025-04-30,1004,8.3,Neural Networks Co +AI08068,Deep Learning Engineer,195225,AUD,263554,EX,FL,Australia,L,Hungary,50,"Git, Python, Azure",Master,17,Automotive,2024-03-06,2024-04-24,1304,7.9,Neural Networks Co +AI08069,AI Specialist,121448,USD,121448,SE,PT,South Korea,L,Luxembourg,50,"Hadoop, Linux, Git, Scala, Java",Master,9,Finance,2024-09-22,2024-10-19,1260,5.3,Autonomous Tech +AI08070,Autonomous Systems Engineer,127574,CHF,114817,MI,CT,Switzerland,S,Canada,0,"TensorFlow, Azure, Spark, Kubernetes",Master,4,Finance,2024-09-18,2024-10-23,733,9.1,Quantum Computing Inc +AI08071,NLP Engineer,28917,USD,28917,EN,FL,China,L,China,50,"SQL, PyTorch, Java, Docker, Linux",PhD,1,Finance,2024-11-08,2024-11-29,2062,8.5,Advanced Robotics +AI08072,NLP Engineer,175601,USD,175601,SE,CT,Denmark,S,Denmark,100,"Python, Scala, AWS, Spark",Master,5,Technology,2024-05-27,2024-06-16,1276,8.5,Quantum Computing Inc +AI08073,Principal Data Scientist,110916,JPY,12200760,SE,CT,Japan,S,United States,100,"Python, Linux, SQL, R, Statistics",Master,9,Retail,2024-03-07,2024-03-30,2208,9.7,Algorithmic Solutions +AI08074,Research Scientist,93983,CAD,117479,MI,PT,Canada,L,Canada,0,"Data Visualization, Kubernetes, Mathematics",Bachelor,4,Healthcare,2024-03-17,2024-03-31,2013,5.2,DeepTech Ventures +AI08075,NLP Engineer,323422,USD,323422,EX,PT,Norway,M,Norway,0,"Docker, R, Data Visualization, Deep Learning, Git",Associate,10,Education,2024-09-25,2024-11-06,1045,7.1,Smart Analytics +AI08076,Robotics Engineer,179355,USD,179355,SE,CT,United States,L,United States,50,"NLP, Python, Data Visualization, Azure, Java",PhD,5,Finance,2024-02-20,2024-04-12,2445,9.2,Advanced Robotics +AI08077,AI Product Manager,85532,USD,85532,EN,FT,Denmark,S,Denmark,50,"Docker, Kubernetes, AWS",Master,0,Telecommunications,2024-11-03,2024-12-30,837,5.9,Machine Intelligence Group +AI08078,Autonomous Systems Engineer,44071,USD,44071,MI,FT,India,L,India,0,"Java, PyTorch, NLP, R, TensorFlow",Associate,3,Government,2025-01-18,2025-03-02,974,8.9,Autonomous Tech +AI08079,Robotics Engineer,130737,USD,130737,SE,FL,Ireland,M,Ireland,50,"Linux, PyTorch, Java, Tableau, TensorFlow",Master,9,Automotive,2024-10-18,2024-11-29,1011,6.9,Cognitive Computing +AI08080,Deep Learning Engineer,147663,CHF,132897,MI,CT,Switzerland,L,Switzerland,50,"SQL, Computer Vision, Scala, GCP",Master,4,Energy,2025-02-18,2025-03-29,2092,7.6,AI Innovations +AI08081,Machine Learning Engineer,269175,USD,269175,EX,FL,Denmark,M,Argentina,100,"AWS, Hadoop, Java, Statistics, Deep Learning",Master,18,Real Estate,2024-02-26,2024-04-05,2398,6.5,AI Innovations +AI08082,Computer Vision Engineer,152150,EUR,129328,SE,FT,France,L,France,50,"Linux, Python, Data Visualization, Java",PhD,5,Consulting,2024-04-07,2024-05-17,1392,9.8,Autonomous Tech +AI08083,AI Consultant,18965,USD,18965,EN,FL,India,S,India,50,"Python, GCP, Deep Learning",Master,0,Automotive,2025-03-07,2025-03-28,2011,7.6,Cloud AI Solutions +AI08084,NLP Engineer,293774,USD,293774,EX,FT,Norway,S,Norway,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,14,Media,2024-06-15,2024-07-21,2330,9.2,Cognitive Computing +AI08085,Head of AI,116082,USD,116082,SE,CT,South Korea,M,United Kingdom,50,"Tableau, Deep Learning, SQL",PhD,9,Consulting,2025-03-02,2025-04-03,1469,6.8,Machine Intelligence Group +AI08086,AI Consultant,55542,USD,55542,EN,FT,South Korea,S,Argentina,100,"Kubernetes, Tableau, MLOps",Master,1,Real Estate,2024-02-20,2024-04-13,1159,8,Quantum Computing Inc +AI08087,AI Consultant,136996,USD,136996,SE,CT,Norway,M,Norway,100,"Linux, SQL, Deep Learning, PyTorch, Hadoop",Bachelor,6,Retail,2024-02-21,2024-03-08,2025,9.8,Cloud AI Solutions +AI08088,ML Ops Engineer,79319,EUR,67421,MI,PT,France,L,France,0,"MLOps, SQL, TensorFlow, Hadoop",Bachelor,3,Media,2024-02-05,2024-03-31,1325,9.7,DataVision Ltd +AI08089,Computer Vision Engineer,105493,CAD,131866,SE,CT,Canada,S,Canada,0,"PyTorch, Linux, Python, Statistics, GCP",Master,9,Education,2025-01-02,2025-01-23,902,9.8,Cloud AI Solutions +AI08090,AI Research Scientist,58931,USD,58931,EN,CT,Israel,S,Israel,50,"Computer Vision, R, SQL",Associate,0,Transportation,2024-09-03,2024-09-21,1976,8.9,DataVision Ltd +AI08091,AI Specialist,269865,USD,269865,EX,CT,Ireland,L,Ireland,100,"Linux, Azure, Deep Learning",Bachelor,18,Technology,2025-03-30,2025-06-07,729,5.7,Autonomous Tech +AI08092,Head of AI,94339,USD,94339,MI,CT,Norway,S,Norway,50,"Kubernetes, TensorFlow, Azure, Tableau, MLOps",Associate,3,Government,2024-04-14,2024-05-02,1970,5.9,Autonomous Tech +AI08093,AI Product Manager,295017,JPY,32451870,EX,CT,Japan,L,Estonia,50,"Kubernetes, Java, Git, SQL",Master,14,Media,2024-09-22,2024-11-04,1295,6.3,Digital Transformation LLC +AI08094,Machine Learning Engineer,101293,SGD,131681,MI,CT,Singapore,S,Singapore,100,"NLP, SQL, Azure, Scala",PhD,2,Healthcare,2025-01-20,2025-03-07,2199,7.9,Machine Intelligence Group +AI08095,AI Specialist,32078,USD,32078,EN,FT,India,L,India,100,"Computer Vision, Tableau, GCP",Associate,0,Consulting,2025-04-16,2025-06-14,2105,5.5,Autonomous Tech +AI08096,Head of AI,99238,GBP,74429,MI,FT,United Kingdom,M,United Kingdom,0,"NLP, R, Kubernetes",Associate,3,Healthcare,2024-09-01,2024-09-23,956,8.2,DeepTech Ventures +AI08097,Data Analyst,87032,USD,87032,MI,FL,Finland,S,Finland,100,"Python, Kubernetes, Tableau",Bachelor,4,Consulting,2024-04-22,2024-05-17,1298,8.2,DeepTech Ventures +AI08098,Data Scientist,156773,USD,156773,SE,FT,Israel,L,Israel,100,"Statistics, Kubernetes, NLP, Linux",Master,5,Technology,2024-02-16,2024-04-03,2324,9.8,Smart Analytics +AI08099,AI Research Scientist,61019,AUD,82376,EN,FT,Australia,L,Australia,100,"Statistics, Git, NLP, Python",Bachelor,0,Real Estate,2024-11-10,2024-11-24,1197,8.6,DeepTech Ventures +AI08100,AI Research Scientist,70543,EUR,59962,EN,PT,Germany,M,Malaysia,0,"TensorFlow, Linux, Tableau, Hadoop, Kubernetes",Bachelor,1,Automotive,2025-03-20,2025-05-19,1099,8,Cloud AI Solutions +AI08101,Deep Learning Engineer,65930,AUD,89006,EN,CT,Australia,S,Australia,50,"GCP, NLP, Hadoop",Master,0,Gaming,2025-02-13,2025-03-07,1258,9.7,Digital Transformation LLC +AI08102,Data Scientist,61443,EUR,52227,EN,CT,France,M,France,0,"SQL, Hadoop, MLOps",Master,1,Healthcare,2024-08-06,2024-10-08,793,7,Algorithmic Solutions +AI08103,Deep Learning Engineer,389007,CHF,350106,EX,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, Hadoop, Deep Learning, Spark",PhD,17,Gaming,2025-01-06,2025-02-22,1261,9.2,Smart Analytics +AI08104,Data Engineer,76813,EUR,65291,MI,PT,Germany,S,Germany,50,"Kubernetes, Spark, NLP, Statistics",Associate,2,Energy,2024-04-22,2024-06-14,1138,8.4,Future Systems +AI08105,ML Ops Engineer,98906,EUR,84070,MI,CT,Austria,L,Austria,0,"Computer Vision, Python, NLP, Spark, TensorFlow",Associate,4,Manufacturing,2025-01-23,2025-03-19,1508,7,DeepTech Ventures +AI08106,Data Scientist,74348,GBP,55761,MI,FL,United Kingdom,S,Singapore,100,"MLOps, Kubernetes, Deep Learning",PhD,3,Government,2025-01-30,2025-04-01,860,6,TechCorp Inc +AI08107,Data Analyst,91122,CHF,82010,EN,FL,Switzerland,M,Switzerland,100,"Mathematics, Deep Learning, Computer Vision, PyTorch, Kubernetes",PhD,0,Government,2024-02-12,2024-04-11,1786,8.6,Advanced Robotics +AI08108,Data Scientist,185096,EUR,157332,EX,FT,France,S,France,100,"Git, Azure, Linux",Bachelor,14,Consulting,2024-01-16,2024-03-06,2314,9.5,Quantum Computing Inc +AI08109,NLP Engineer,94648,EUR,80451,MI,FT,France,M,France,50,"GCP, R, Kubernetes",PhD,3,Automotive,2024-04-14,2024-05-28,2479,7.7,Digital Transformation LLC +AI08110,AI Architect,81723,EUR,69465,MI,PT,France,S,France,0,"Java, R, Spark, SQL, MLOps",Master,3,Gaming,2024-03-14,2024-03-28,724,6.2,Autonomous Tech +AI08111,Autonomous Systems Engineer,249442,GBP,187082,EX,FT,United Kingdom,M,United Kingdom,50,"Deep Learning, R, Tableau, GCP",Bachelor,11,Finance,2025-01-28,2025-03-16,1202,9.4,Digital Transformation LLC +AI08112,Robotics Engineer,111472,CAD,139340,SE,PT,Canada,M,Ghana,100,"Scala, Git, Computer Vision, NLP, AWS",PhD,8,Healthcare,2025-01-04,2025-01-26,2448,6.5,Machine Intelligence Group +AI08113,Data Analyst,107982,USD,107982,MI,PT,Norway,S,Norway,100,"Java, R, Azure, Hadoop, Git",Master,2,Finance,2025-04-03,2025-06-02,2009,8.4,Cognitive Computing +AI08114,NLP Engineer,106322,USD,106322,SE,FT,South Korea,L,South Korea,50,"Kubernetes, TensorFlow, Azure",PhD,5,Technology,2024-03-16,2024-04-16,2356,8.8,Cognitive Computing +AI08115,Data Scientist,97096,USD,97096,MI,PT,South Korea,L,Luxembourg,0,"Linux, NLP, Tableau, Scala",Master,2,Automotive,2025-03-13,2025-05-11,2414,6.3,Advanced Robotics +AI08116,Machine Learning Engineer,71329,USD,71329,SE,FL,China,L,China,0,"GCP, PyTorch, TensorFlow, Kubernetes, AWS",Bachelor,7,Education,2024-10-14,2024-10-31,2022,6.6,DataVision Ltd +AI08117,Machine Learning Researcher,204502,USD,204502,EX,FT,Israel,L,Canada,0,"Computer Vision, Deep Learning, SQL, Linux, Python",Associate,17,Automotive,2024-05-22,2024-06-12,636,7.7,Quantum Computing Inc +AI08118,AI Software Engineer,78540,AUD,106029,EN,PT,Australia,L,Canada,0,"Linux, Deep Learning, Spark, Hadoop",PhD,1,Real Estate,2024-06-27,2024-07-17,1984,8.4,Machine Intelligence Group +AI08119,AI Specialist,102696,USD,102696,MI,FL,Norway,M,Norway,50,"GCP, Statistics, Linux, PyTorch",Bachelor,3,Technology,2024-10-01,2024-11-24,2251,8.7,Digital Transformation LLC +AI08120,Machine Learning Engineer,140672,USD,140672,SE,FL,Ireland,M,Ireland,0,"SQL, Kubernetes, Data Visualization",Master,6,Energy,2025-04-16,2025-05-15,1303,5.4,Smart Analytics +AI08121,AI Consultant,306231,JPY,33685410,EX,FT,Japan,L,Japan,50,"SQL, Linux, Spark, Azure, Hadoop",PhD,11,Transportation,2024-11-09,2025-01-13,2186,7.7,DeepTech Ventures +AI08122,Research Scientist,79751,USD,79751,MI,FT,Israel,L,Israel,0,"Linux, PyTorch, R, NLP",Associate,3,Consulting,2025-01-12,2025-02-10,1412,6.5,Future Systems +AI08123,Data Analyst,59536,AUD,80374,EN,PT,Australia,S,Australia,0,"Python, SQL, AWS",Master,1,Real Estate,2024-03-14,2024-04-17,905,7.5,DeepTech Ventures +AI08124,Data Analyst,217273,USD,217273,EX,CT,Sweden,M,Sweden,100,"GCP, Deep Learning, PyTorch",Bachelor,14,Retail,2024-09-05,2024-10-15,1637,8.5,DataVision Ltd +AI08125,AI Software Engineer,61375,USD,61375,EN,CT,Finland,M,Finland,0,"MLOps, Data Visualization, Python",Associate,1,Technology,2024-04-07,2024-05-06,1196,5.2,Cognitive Computing +AI08126,AI Research Scientist,84104,CHF,75694,EN,PT,Switzerland,S,Switzerland,100,"MLOps, Mathematics, Linux",Associate,0,Energy,2024-12-07,2025-01-11,1663,9.1,Predictive Systems +AI08127,Machine Learning Researcher,119885,JPY,13187350,SE,FT,Japan,M,Japan,50,"Hadoop, Statistics, Git",Master,8,Consulting,2024-04-15,2024-05-15,1847,5.7,Advanced Robotics +AI08128,Head of AI,49872,USD,49872,EN,CT,Finland,M,Germany,100,"GCP, Deep Learning, MLOps, Linux, SQL",Bachelor,1,Telecommunications,2024-03-06,2024-03-30,2282,8.6,AI Innovations +AI08129,AI Product Manager,83785,USD,83785,EX,PT,India,L,Hungary,100,"Scala, R, Statistics",Bachelor,16,Real Estate,2024-12-11,2025-01-24,970,5.9,Cloud AI Solutions +AI08130,Principal Data Scientist,47263,AUD,63805,EN,PT,Australia,S,Australia,100,"AWS, Kubernetes, PyTorch",Associate,1,Education,2025-02-23,2025-05-05,2397,9.9,DataVision Ltd +AI08131,Machine Learning Researcher,82949,CAD,103686,EN,FT,Canada,L,Canada,50,"Mathematics, Git, NLP, Python",PhD,1,Media,2025-04-14,2025-06-10,1455,5.5,Smart Analytics +AI08132,AI Architect,85674,USD,85674,MI,FL,Sweden,M,China,0,"SQL, Python, GCP, Azure",Associate,4,Automotive,2025-04-19,2025-06-25,2146,5.6,Predictive Systems +AI08133,Research Scientist,66353,USD,66353,MI,FL,South Korea,S,South Korea,100,"Python, Hadoop, Deep Learning, SQL",PhD,4,Transportation,2024-08-10,2024-10-12,507,5.8,AI Innovations +AI08134,AI Product Manager,169078,USD,169078,EX,FT,Sweden,S,Sweden,100,"GCP, Statistics, Tableau",Bachelor,18,Automotive,2025-03-05,2025-04-16,814,6.9,Cognitive Computing +AI08135,Autonomous Systems Engineer,181932,EUR,154642,EX,CT,Germany,M,Germany,100,"Docker, Spark, Scala",Master,17,Education,2024-01-02,2024-01-28,1918,7.7,Cognitive Computing +AI08136,Autonomous Systems Engineer,93368,EUR,79363,SE,CT,Germany,S,Germany,50,"R, Scala, Data Visualization",Master,6,Healthcare,2024-08-02,2024-09-01,705,5.2,Neural Networks Co +AI08137,AI Specialist,112677,USD,112677,SE,CT,Israel,S,Israel,50,"Data Visualization, Linux, SQL, R",Bachelor,9,Automotive,2025-02-26,2025-04-06,1251,6.3,Digital Transformation LLC +AI08138,Computer Vision Engineer,145606,EUR,123765,EX,CT,Germany,M,Germany,50,"Java, SQL, Hadoop, Kubernetes",PhD,12,Real Estate,2024-09-20,2024-11-09,1136,6.7,Quantum Computing Inc +AI08139,AI Specialist,60885,USD,60885,EN,FL,Ireland,S,Argentina,50,"Python, SQL, Linux",PhD,0,Manufacturing,2025-03-07,2025-05-08,640,7.1,Digital Transformation LLC +AI08140,Robotics Engineer,53376,AUD,72058,EN,FL,Australia,M,China,100,"Deep Learning, GCP, Kubernetes",Bachelor,0,Technology,2024-08-24,2024-09-26,1725,7,Algorithmic Solutions +AI08141,AI Consultant,75818,EUR,64445,EN,CT,Netherlands,L,Netherlands,0,"Python, Spark, Scala, AWS, R",Master,0,Gaming,2024-10-28,2025-01-08,544,8.3,Quantum Computing Inc +AI08142,Principal Data Scientist,99061,EUR,84202,MI,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, Tableau",Associate,3,Gaming,2025-02-19,2025-04-17,1973,7,Quantum Computing Inc +AI08143,Data Analyst,107756,EUR,91593,MI,FT,Germany,L,Germany,50,"Azure, SQL, Java",Associate,4,Healthcare,2024-10-30,2024-12-10,661,8.1,Cognitive Computing +AI08144,Computer Vision Engineer,75125,USD,75125,SE,FL,China,L,China,0,"Tableau, Azure, Kubernetes, Mathematics",PhD,9,Automotive,2024-01-07,2024-02-08,1592,7.2,Smart Analytics +AI08145,Machine Learning Researcher,96840,CHF,87156,EN,CT,Switzerland,S,Switzerland,50,"Python, TensorFlow, PyTorch, Tableau, Mathematics",Bachelor,0,Finance,2024-12-25,2025-02-03,578,9.1,DataVision Ltd +AI08146,NLP Engineer,78676,USD,78676,EN,CT,Sweden,M,Sweden,100,"Mathematics, Hadoop, Python, Spark",PhD,0,Gaming,2024-07-03,2024-08-25,1565,9.9,Autonomous Tech +AI08147,Computer Vision Engineer,206627,CHF,185964,EX,FL,Switzerland,S,South Korea,100,"TensorFlow, Deep Learning, Tableau, Kubernetes, SQL",Bachelor,10,Transportation,2025-04-14,2025-05-26,767,7.4,Predictive Systems +AI08148,Principal Data Scientist,74509,USD,74509,SE,CT,China,L,Vietnam,100,"TensorFlow, Docker, Kubernetes, GCP, Data Visualization",Bachelor,9,Education,2024-07-17,2024-08-22,2330,7.3,Autonomous Tech +AI08149,Data Engineer,147081,EUR,125019,SE,FL,Germany,L,Malaysia,50,"R, SQL, Statistics",PhD,5,Government,2024-11-05,2024-12-17,1029,7.6,Autonomous Tech +AI08150,AI Consultant,148813,CAD,186016,EX,PT,Canada,M,Canada,0,"Tableau, GCP, Scala, NLP",Bachelor,15,Government,2024-08-22,2024-10-21,2385,8.7,Algorithmic Solutions +AI08151,Deep Learning Engineer,194557,AUD,262652,EX,CT,Australia,M,Australia,100,"Mathematics, Hadoop, Data Visualization, AWS",Master,18,Energy,2024-11-09,2025-01-16,1321,6.4,Quantum Computing Inc +AI08152,Data Analyst,220707,EUR,187601,EX,PT,Germany,S,Germany,100,"Mathematics, SQL, AWS, Kubernetes, Linux",PhD,18,Manufacturing,2024-01-08,2024-02-19,1499,6.4,Cognitive Computing +AI08153,AI Architect,83907,EUR,71321,EN,FT,Austria,L,Brazil,0,"R, Deep Learning, Tableau, PyTorch, Mathematics",PhD,0,Automotive,2024-09-29,2024-10-30,1079,8.8,DataVision Ltd +AI08154,NLP Engineer,203429,CHF,183086,SE,CT,Switzerland,M,China,100,"Kubernetes, AWS, GCP",PhD,5,Technology,2024-06-26,2024-07-22,1030,7.1,Advanced Robotics +AI08155,Head of AI,121903,USD,121903,SE,CT,South Korea,M,South Korea,0,"Python, Hadoop, Mathematics, Tableau, Computer Vision",Master,8,Media,2025-02-28,2025-03-18,667,6.9,Advanced Robotics +AI08156,Computer Vision Engineer,97513,CAD,121891,MI,PT,Canada,L,Canada,50,"Docker, Python, Statistics",Master,3,Real Estate,2024-05-11,2024-07-03,2187,7.1,Machine Intelligence Group +AI08157,AI Consultant,229343,CHF,206409,SE,FL,Switzerland,L,Switzerland,100,"PyTorch, Scala, MLOps, Computer Vision",PhD,6,Automotive,2024-06-20,2024-08-17,548,9.6,Autonomous Tech +AI08158,Data Scientist,135831,SGD,176580,SE,CT,Singapore,S,New Zealand,50,"AWS, Docker, Data Visualization, Deep Learning",Master,8,Manufacturing,2024-10-14,2024-11-18,1245,7.3,Algorithmic Solutions +AI08159,AI Specialist,229897,CHF,206907,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Computer Vision, Hadoop",PhD,9,Gaming,2024-07-14,2024-09-23,1540,5.1,Digital Transformation LLC +AI08160,Data Scientist,75572,AUD,102022,MI,FL,Australia,S,Australia,100,"Tableau, Python, Hadoop",Master,4,Healthcare,2024-09-10,2024-10-03,1850,9.3,Neural Networks Co +AI08161,AI Product Manager,160993,JPY,17709230,EX,FL,Japan,S,Japan,0,"Python, Kubernetes, Git, Linux",PhD,15,Real Estate,2024-05-11,2024-06-24,1652,6.6,Algorithmic Solutions +AI08162,Data Engineer,81776,SGD,106309,MI,CT,Singapore,S,Singapore,50,"R, PyTorch, Spark, Statistics",PhD,3,Consulting,2024-02-11,2024-04-17,820,5.6,Machine Intelligence Group +AI08163,Head of AI,81570,USD,81570,EN,PT,Finland,L,Finland,50,"Linux, Data Visualization, Hadoop, Azure, Tableau",Bachelor,0,Energy,2024-05-11,2024-06-12,507,7.4,Smart Analytics +AI08164,Autonomous Systems Engineer,93162,EUR,79188,MI,CT,Germany,S,Germany,100,"Data Visualization, Git, Python, Scala, Computer Vision",Master,4,Energy,2024-02-23,2024-04-27,535,7.2,Predictive Systems +AI08165,Machine Learning Researcher,227631,AUD,307302,EX,FT,Australia,S,Argentina,100,"SQL, GCP, Git",PhD,19,Gaming,2024-07-21,2024-09-26,640,6.2,AI Innovations +AI08166,AI Architect,131380,USD,131380,SE,FL,Sweden,L,Poland,100,"SQL, Deep Learning, Scala, Computer Vision, PyTorch",Bachelor,5,Telecommunications,2025-02-25,2025-05-01,2251,6.9,Algorithmic Solutions +AI08167,Data Analyst,33242,USD,33242,EN,FT,China,L,Estonia,0,"Kubernetes, SQL, Tableau",Associate,0,Healthcare,2024-08-07,2024-08-24,552,8.7,Cloud AI Solutions +AI08168,Data Scientist,336599,USD,336599,EX,FT,Denmark,L,Denmark,50,"PyTorch, Linux, Statistics, GCP, Python",Bachelor,14,Retail,2024-11-14,2025-01-14,1602,7,Smart Analytics +AI08169,AI Software Engineer,132545,SGD,172309,MI,FT,Singapore,L,United Kingdom,0,"AWS, Kubernetes, NLP, Azure",Bachelor,4,Consulting,2025-02-03,2025-02-21,2499,5.5,Smart Analytics +AI08170,AI Specialist,300635,USD,300635,EX,CT,United States,L,United States,100,"PyTorch, Python, Computer Vision, Scala",Associate,10,Energy,2024-06-18,2024-07-24,1527,7.8,Quantum Computing Inc +AI08171,AI Specialist,94953,USD,94953,MI,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Scala, Linux, TensorFlow",Bachelor,2,Healthcare,2024-01-04,2024-02-03,999,7.1,Machine Intelligence Group +AI08172,AI Architect,178775,AUD,241346,EX,FT,Australia,S,Denmark,0,"Java, Tableau, R, Statistics, GCP",Associate,11,Retail,2024-08-21,2024-10-13,1289,5,Machine Intelligence Group +AI08173,Data Analyst,74369,CAD,92961,MI,FT,Canada,S,Canada,100,"Statistics, Data Visualization, GCP, Hadoop",Associate,3,Real Estate,2024-11-10,2024-11-27,1659,7.9,Digital Transformation LLC +AI08174,Computer Vision Engineer,75798,USD,75798,EN,FL,Norway,M,Norway,0,"Statistics, R, Mathematics",Associate,1,Media,2024-04-28,2024-05-25,1617,6.8,DeepTech Ventures +AI08175,Autonomous Systems Engineer,186114,EUR,158197,EX,FL,Austria,L,Austria,100,"NLP, SQL, Data Visualization, Azure",Associate,19,Consulting,2024-12-15,2025-02-19,762,9.2,Cognitive Computing +AI08176,AI Product Manager,95648,USD,95648,MI,CT,Ireland,M,Austria,50,"Linux, Python, Java, Spark",Bachelor,4,Energy,2024-10-04,2024-11-29,1137,6.4,Digital Transformation LLC +AI08177,AI Research Scientist,359202,CHF,323282,EX,CT,Switzerland,M,Switzerland,0,"Python, MLOps, Computer Vision",Associate,13,Finance,2025-01-26,2025-03-29,1430,7.7,DataVision Ltd +AI08178,Head of AI,76073,GBP,57055,MI,FL,United Kingdom,S,United Kingdom,50,"Python, Git, TensorFlow, MLOps",Master,2,Technology,2024-09-17,2024-11-11,1703,7.3,Advanced Robotics +AI08179,NLP Engineer,49705,USD,49705,EN,FT,Finland,M,Indonesia,50,"Spark, Tableau, Azure, GCP",Bachelor,0,Telecommunications,2024-07-25,2024-08-30,1697,5.1,DataVision Ltd +AI08180,AI Consultant,98961,EUR,84117,MI,FL,Netherlands,S,Ireland,100,"R, PyTorch, Docker, Linux",Master,4,Technology,2025-01-16,2025-02-18,1231,6.1,Cloud AI Solutions +AI08181,Data Scientist,73832,USD,73832,EN,FL,United States,M,United States,0,"NLP, Spark, Deep Learning, MLOps",PhD,0,Healthcare,2025-04-28,2025-06-20,1551,5.2,Cloud AI Solutions +AI08182,NLP Engineer,209012,USD,209012,EX,FL,Sweden,M,Sweden,0,"Python, Kubernetes, Spark",Bachelor,16,Government,2024-10-04,2024-11-26,2115,7.8,DataVision Ltd +AI08183,AI Research Scientist,114933,JPY,12642630,MI,CT,Japan,M,Russia,0,"Kubernetes, Git, SQL",Associate,3,Automotive,2024-03-18,2024-05-29,608,6.3,Digital Transformation LLC +AI08184,Data Analyst,127420,CHF,114678,MI,FL,Switzerland,M,Switzerland,0,"Docker, Python, TensorFlow",PhD,3,Consulting,2024-04-30,2024-05-27,987,9.7,Smart Analytics +AI08185,Machine Learning Engineer,144510,EUR,122834,SE,PT,France,L,France,50,"Computer Vision, Hadoop, Mathematics",Master,5,Retail,2025-02-05,2025-02-24,2346,8.4,Digital Transformation LLC +AI08186,Autonomous Systems Engineer,99445,AUD,134251,SE,FT,Australia,S,Australia,50,"MLOps, Tableau, SQL, Data Visualization, R",PhD,9,Consulting,2024-08-30,2024-09-21,1691,8.9,Autonomous Tech +AI08187,AI Research Scientist,101862,EUR,86583,MI,FT,Netherlands,L,Netherlands,50,"Deep Learning, PyTorch, TensorFlow, GCP",Bachelor,4,Automotive,2024-09-04,2024-10-04,2009,7.1,Future Systems +AI08188,Computer Vision Engineer,54758,USD,54758,EN,CT,Israel,S,Ghana,0,"TensorFlow, SQL, MLOps, GCP",Bachelor,0,Transportation,2024-12-08,2025-02-18,1157,8.2,Neural Networks Co +AI08189,Robotics Engineer,93957,EUR,79863,MI,PT,Netherlands,S,Mexico,50,"GCP, SQL, Azure",PhD,4,Energy,2024-11-03,2025-01-03,569,6.7,Quantum Computing Inc +AI08190,Machine Learning Researcher,184257,EUR,156618,EX,PT,Austria,L,Austria,0,"SQL, Docker, Data Visualization",Associate,17,Telecommunications,2025-02-08,2025-04-17,1806,6.3,Cognitive Computing +AI08191,Head of AI,65196,EUR,55417,MI,PT,France,S,France,50,"SQL, TensorFlow, Data Visualization, Linux",PhD,2,Government,2024-09-16,2024-10-20,909,8.6,Future Systems +AI08192,Data Analyst,121164,USD,121164,EX,FL,South Korea,S,South Korea,50,"GCP, Git, Deep Learning, Docker",Bachelor,12,Education,2024-05-09,2024-06-11,1313,5.9,Machine Intelligence Group +AI08193,Machine Learning Engineer,93873,AUD,126729,SE,PT,Australia,S,Australia,50,"Mathematics, Data Visualization, Tableau, Linux, Hadoop",Bachelor,7,Retail,2024-06-04,2024-06-27,1816,9.2,Digital Transformation LLC +AI08194,Computer Vision Engineer,148307,USD,148307,MI,FL,Denmark,L,Denmark,50,"Java, Computer Vision, Python, Tableau, Data Visualization",PhD,3,Healthcare,2024-10-08,2024-11-09,2328,6.2,AI Innovations +AI08195,AI Specialist,145377,GBP,109033,EX,PT,United Kingdom,S,United Kingdom,100,"Git, Deep Learning, Data Visualization",PhD,10,Technology,2024-03-08,2024-05-14,1526,9.6,DataVision Ltd +AI08196,Autonomous Systems Engineer,42525,USD,42525,EN,PT,South Korea,M,Estonia,50,"SQL, Deep Learning, Java, Python",Associate,1,Finance,2024-10-26,2024-11-25,862,9.3,Cognitive Computing +AI08197,AI Software Engineer,282434,USD,282434,EX,CT,Denmark,S,Denmark,100,"Azure, Java, MLOps, SQL, R",PhD,18,Telecommunications,2024-06-07,2024-06-26,1490,8.2,DeepTech Ventures +AI08198,AI Research Scientist,209133,USD,209133,EX,FT,Norway,L,Germany,50,"Scala, Git, Computer Vision, Spark",Associate,15,Energy,2024-01-01,2024-01-26,2279,8.1,Cognitive Computing +AI08199,Principal Data Scientist,250333,GBP,187750,EX,FT,United Kingdom,L,United Kingdom,0,"Linux, Statistics, PyTorch, Mathematics, Tableau",Bachelor,18,Healthcare,2024-01-23,2024-03-22,1827,8,Predictive Systems +AI08200,Research Scientist,174979,USD,174979,EX,FL,Norway,S,Indonesia,100,"Deep Learning, AWS, Computer Vision, Scala",Bachelor,18,Technology,2024-03-16,2024-03-30,2275,7.5,Smart Analytics +AI08201,Data Scientist,101837,USD,101837,SE,CT,Sweden,S,Sweden,100,"Azure, Scala, PyTorch",Bachelor,6,Government,2024-10-03,2024-10-20,600,6.6,Quantum Computing Inc +AI08202,Machine Learning Researcher,109223,USD,109223,SE,FT,Finland,M,Estonia,100,"TensorFlow, Azure, Mathematics, Kubernetes, AWS",Bachelor,5,Gaming,2024-07-28,2024-08-16,1615,8.2,Algorithmic Solutions +AI08203,Machine Learning Researcher,160180,USD,160180,SE,CT,Norway,S,Norway,50,"Linux, Scala, Mathematics, Kubernetes, Tableau",PhD,8,Real Estate,2024-11-06,2025-01-07,1020,6.1,Autonomous Tech +AI08204,Principal Data Scientist,52809,USD,52809,EN,PT,South Korea,L,South Korea,0,"Tableau, PyTorch, Git",Bachelor,1,Retail,2024-05-04,2024-05-30,1410,6.8,Autonomous Tech +AI08205,Computer Vision Engineer,218360,USD,218360,EX,FT,Norway,M,Norway,0,"Kubernetes, R, AWS, Mathematics, Statistics",Bachelor,12,Healthcare,2025-04-06,2025-04-26,2264,9.8,Digital Transformation LLC +AI08206,AI Consultant,99844,EUR,84867,MI,FT,Austria,L,India,0,"Hadoop, TensorFlow, Java, GCP, Docker",Bachelor,2,Retail,2024-07-28,2024-10-05,1801,8.3,Algorithmic Solutions +AI08207,AI Research Scientist,191537,SGD,248998,EX,FL,Singapore,L,Ireland,0,"Data Visualization, Hadoop, Computer Vision",Associate,12,Finance,2024-03-25,2024-04-29,928,6.4,Algorithmic Solutions +AI08208,Machine Learning Researcher,225775,USD,225775,EX,CT,Israel,M,Israel,0,"Python, Java, Hadoop, GCP, NLP",Bachelor,14,Finance,2024-05-13,2024-06-02,1054,5.5,AI Innovations +AI08209,Data Scientist,83618,USD,83618,EN,FL,Finland,L,Finland,0,"TensorFlow, Python, Hadoop, Tableau",Master,0,Automotive,2024-11-14,2025-01-21,1114,8.9,Neural Networks Co +AI08210,ML Ops Engineer,167785,EUR,142617,EX,FT,Germany,S,Germany,100,"Git, Deep Learning, Azure",Master,14,Manufacturing,2024-09-30,2024-10-29,1951,8.1,Machine Intelligence Group +AI08211,AI Research Scientist,25456,USD,25456,EN,CT,India,S,India,0,"AWS, Mathematics, Python",Bachelor,0,Government,2024-10-05,2024-10-19,1184,6.8,Neural Networks Co +AI08212,Data Analyst,109322,USD,109322,SE,CT,South Korea,L,South Korea,50,"Python, SQL, TensorFlow, AWS, Java",PhD,6,Gaming,2024-03-05,2024-05-03,2326,9.2,TechCorp Inc +AI08213,AI Architect,100260,USD,100260,SE,FL,Finland,M,Belgium,50,"PyTorch, Hadoop, Docker, Computer Vision",PhD,9,Manufacturing,2024-09-07,2024-10-14,1995,10,Smart Analytics +AI08214,Data Analyst,111999,USD,111999,SE,PT,Israel,M,Israel,50,"PyTorch, Python, Java, NLP, Hadoop",PhD,5,Automotive,2025-03-02,2025-05-09,833,5,AI Innovations +AI08215,Robotics Engineer,70798,JPY,7787780,EN,FT,Japan,M,Japan,100,"Tableau, TensorFlow, Python",PhD,1,Finance,2024-12-17,2025-01-04,1022,6.7,DataVision Ltd +AI08216,Robotics Engineer,75569,AUD,102018,MI,PT,Australia,S,Australia,50,"AWS, PyTorch, SQL",Bachelor,4,Gaming,2025-03-15,2025-05-06,1557,6.9,Neural Networks Co +AI08217,Autonomous Systems Engineer,173910,USD,173910,EX,PT,Israel,L,Israel,0,"TensorFlow, Deep Learning, Azure",Master,10,Healthcare,2025-01-18,2025-03-06,1685,5.6,Smart Analytics +AI08218,AI Software Engineer,234620,USD,234620,EX,PT,United States,M,United States,50,"Data Visualization, Git, GCP",Master,11,Consulting,2024-03-19,2024-05-30,2246,5.6,TechCorp Inc +AI08219,Data Scientist,54313,EUR,46166,EN,FL,Netherlands,S,Netherlands,50,"Azure, R, Scala, SQL, Git",Associate,1,Transportation,2024-04-04,2024-05-14,626,5.5,Predictive Systems +AI08220,Machine Learning Engineer,223033,GBP,167275,EX,FL,United Kingdom,S,Mexico,50,"Java, Computer Vision, SQL",Bachelor,14,Telecommunications,2024-05-05,2024-06-16,531,9.2,Autonomous Tech +AI08221,ML Ops Engineer,235007,USD,235007,EX,FT,South Korea,L,South Korea,0,"SQL, Kubernetes, NLP",Master,16,Healthcare,2024-10-22,2024-12-18,2222,9.2,TechCorp Inc +AI08222,AI Specialist,68349,EUR,58097,EN,PT,Netherlands,S,Netherlands,100,"Docker, NLP, Data Visualization, Linux",Master,0,Finance,2025-04-19,2025-06-14,2333,8.6,Future Systems +AI08223,AI Consultant,88924,USD,88924,MI,CT,Israel,L,Israel,100,"SQL, PyTorch, Deep Learning, Azure, AWS",Master,4,Real Estate,2024-03-23,2024-05-25,1368,5.8,Predictive Systems +AI08224,AI Specialist,107723,USD,107723,SE,FT,South Korea,L,South Korea,50,"R, Python, Statistics, Spark, GCP",Associate,5,Energy,2025-04-13,2025-06-23,664,8.2,Machine Intelligence Group +AI08225,AI Architect,100120,USD,100120,MI,FL,Denmark,S,Denmark,100,"Python, Git, Spark",Associate,4,Technology,2024-02-17,2024-04-07,2445,5.5,Neural Networks Co +AI08226,AI Specialist,52959,USD,52959,EN,CT,Israel,S,Israel,50,"Python, Tableau, Git",Master,1,Retail,2024-12-09,2025-01-28,645,5.7,DataVision Ltd +AI08227,ML Ops Engineer,88552,EUR,75269,EN,CT,Germany,L,Portugal,50,"MLOps, Tableau, SQL",PhD,0,Consulting,2025-03-02,2025-04-08,1539,5.8,AI Innovations +AI08228,AI Research Scientist,152649,CHF,137384,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, Kubernetes, MLOps",Bachelor,6,Transportation,2025-04-20,2025-06-07,963,5.9,Cloud AI Solutions +AI08229,Computer Vision Engineer,89988,USD,89988,EX,FL,China,L,China,100,"TensorFlow, Spark, Data Visualization, SQL, Docker",Bachelor,19,Healthcare,2024-12-31,2025-01-23,686,6.8,Algorithmic Solutions +AI08230,Principal Data Scientist,91107,USD,91107,MI,PT,United States,S,Japan,0,"R, Data Visualization, Linux",PhD,4,Retail,2025-04-05,2025-04-23,2056,8.4,Digital Transformation LLC +AI08231,AI Software Engineer,144476,USD,144476,MI,FT,United States,L,Mexico,100,"Python, SQL, Tableau, Git, Java",Master,2,Manufacturing,2024-11-04,2024-12-02,1950,6.9,Advanced Robotics +AI08232,Data Engineer,161347,CHF,145212,SE,PT,Switzerland,M,Switzerland,0,"Data Visualization, Spark, PyTorch, Git, Statistics",Bachelor,6,Telecommunications,2024-11-24,2025-01-11,1879,9.9,DataVision Ltd +AI08233,Principal Data Scientist,140235,AUD,189317,EX,FT,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau",Master,11,Energy,2024-05-27,2024-06-13,2013,9.6,Algorithmic Solutions +AI08234,Data Analyst,148219,USD,148219,EX,CT,Sweden,S,Sweden,100,"Java, Azure, Tableau, Python",Associate,16,Manufacturing,2024-10-26,2024-12-31,1949,8.6,Smart Analytics +AI08235,AI Architect,105601,SGD,137281,SE,FT,Singapore,S,France,100,"Git, Python, Hadoop",Master,7,Media,2024-01-23,2024-03-30,2256,5.8,AI Innovations +AI08236,AI Architect,64809,JPY,7128990,EN,CT,Japan,L,Portugal,0,"Docker, R, NLP",Bachelor,1,Technology,2025-01-14,2025-02-15,1701,7.2,Algorithmic Solutions +AI08237,Machine Learning Researcher,78106,EUR,66390,EN,FT,Austria,L,Germany,50,"Spark, PyTorch, R, Computer Vision",Master,1,Consulting,2025-04-25,2025-06-26,2113,9.1,Advanced Robotics +AI08238,Data Analyst,60250,SGD,78325,EN,FL,Singapore,M,Singapore,100,"SQL, Scala, Kubernetes, Deep Learning",PhD,1,Retail,2025-04-01,2025-05-30,1424,7.3,Cloud AI Solutions +AI08239,Machine Learning Researcher,54773,GBP,41080,EN,CT,United Kingdom,S,United Kingdom,100,"SQL, TensorFlow, Computer Vision, Statistics",Bachelor,0,Automotive,2024-02-22,2024-04-25,2397,7.9,TechCorp Inc +AI08240,Machine Learning Researcher,111174,USD,111174,EN,FL,Denmark,L,Japan,50,"Data Visualization, Hadoop, Python, R",Master,0,Automotive,2024-08-12,2024-09-08,1329,5.9,Cognitive Computing +AI08241,AI Software Engineer,67798,CAD,84748,EN,PT,Canada,L,Malaysia,100,"PyTorch, Python, Docker, Mathematics, SQL",Master,1,Finance,2024-03-10,2024-04-20,631,7.1,Autonomous Tech +AI08242,AI Specialist,124429,USD,124429,SE,FT,Sweden,M,Sweden,50,"Python, Data Visualization, SQL, Computer Vision, Hadoop",Associate,5,Finance,2024-11-02,2024-12-03,1318,8.1,DeepTech Ventures +AI08243,Deep Learning Engineer,61446,EUR,52229,EN,PT,Austria,S,Austria,50,"Statistics, Git, MLOps, GCP",PhD,0,Real Estate,2024-09-06,2024-09-24,1899,6.2,AI Innovations +AI08244,Research Scientist,166025,EUR,141121,EX,CT,Germany,S,Germany,0,"Hadoop, Kubernetes, Git, PyTorch, Linux",PhD,14,Finance,2024-08-11,2024-10-17,782,7.7,Cognitive Computing +AI08245,Deep Learning Engineer,200365,AUD,270493,EX,CT,Australia,M,Australia,100,"Java, SQL, Data Visualization",Bachelor,10,Energy,2024-02-02,2024-03-17,1775,5.6,Cognitive Computing +AI08246,AI Consultant,68661,USD,68661,EN,CT,Denmark,M,Denmark,0,"Python, Git, TensorFlow, Computer Vision",Master,0,Education,2025-03-26,2025-04-10,1038,6.4,Cognitive Computing +AI08247,Research Scientist,128591,USD,128591,MI,CT,United States,L,United States,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,2,Government,2024-06-15,2024-08-08,1680,6.5,Predictive Systems +AI08248,Machine Learning Researcher,90540,USD,90540,MI,FT,Norway,S,Chile,100,"Data Visualization, R, Python, TensorFlow",Associate,2,Education,2024-11-11,2024-12-27,2176,9.9,Quantum Computing Inc +AI08249,AI Software Engineer,98359,USD,98359,MI,FL,United States,M,Spain,100,"Git, AWS, Hadoop, R",Associate,2,Real Estate,2024-10-13,2024-12-22,628,7.9,Cognitive Computing +AI08250,Deep Learning Engineer,60172,USD,60172,EN,FT,Finland,M,Finland,50,"Python, Azure, Tableau",Associate,1,Automotive,2024-01-17,2024-02-14,2166,9.6,Cloud AI Solutions +AI08251,Data Engineer,59702,USD,59702,MI,CT,South Korea,S,South Korea,0,"Statistics, Data Visualization, AWS, Mathematics, Python",Bachelor,4,Real Estate,2024-06-30,2024-08-30,2287,8,AI Innovations +AI08252,Research Scientist,231158,USD,231158,EX,CT,United States,M,Belgium,0,"GCP, Java, Hadoop, Scala",Associate,11,Government,2024-09-01,2024-11-09,1335,5.6,Cognitive Computing +AI08253,Principal Data Scientist,56253,EUR,47815,EN,PT,France,S,Sweden,0,"Tableau, Git, PyTorch, TensorFlow",Associate,1,Real Estate,2024-08-26,2024-09-26,1976,6.2,Autonomous Tech +AI08254,AI Product Manager,66100,USD,66100,EN,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Tableau, Hadoop",Master,1,Government,2024-09-23,2024-11-15,1415,9.7,AI Innovations +AI08255,AI Software Engineer,43269,USD,43269,MI,FT,China,M,China,100,"SQL, MLOps, PyTorch, Statistics, Python",Associate,3,Finance,2024-09-20,2024-10-05,2402,8.5,DeepTech Ventures +AI08256,AI Software Engineer,87445,SGD,113679,EN,PT,Singapore,L,Singapore,0,"Scala, Python, TensorFlow, AWS, Mathematics",Associate,0,Consulting,2025-01-13,2025-03-16,2260,6.9,Cloud AI Solutions +AI08257,Deep Learning Engineer,125861,EUR,106982,SE,FL,Netherlands,L,Netherlands,0,"AWS, Java, Python",Bachelor,9,Technology,2025-02-15,2025-03-06,574,7,Machine Intelligence Group +AI08258,AI Specialist,218971,GBP,164228,EX,PT,United Kingdom,S,Ukraine,0,"PyTorch, Hadoop, Kubernetes, Azure",Master,14,Telecommunications,2024-08-27,2024-11-07,2328,5.7,AI Innovations +AI08259,AI Software Engineer,192168,USD,192168,EX,FL,Ireland,L,Ireland,100,"SQL, Azure, Kubernetes, GCP, NLP",Master,13,Finance,2024-08-18,2024-10-01,1469,7.6,Quantum Computing Inc +AI08260,AI Product Manager,159792,EUR,135823,EX,FL,Austria,M,Austria,100,"R, NLP, Data Visualization, Kubernetes",PhD,19,Healthcare,2024-07-01,2024-07-24,576,8.3,AI Innovations +AI08261,Autonomous Systems Engineer,228879,EUR,194547,EX,FT,Germany,L,Australia,100,"Tableau, Java, Python",Master,13,Real Estate,2024-12-20,2025-01-12,1732,7.4,Machine Intelligence Group +AI08262,AI Product Manager,213850,GBP,160388,EX,FT,United Kingdom,S,United Kingdom,50,"Python, Docker, Hadoop, Statistics",Associate,13,Real Estate,2024-12-05,2025-01-07,1984,6.2,Digital Transformation LLC +AI08263,Machine Learning Engineer,161935,USD,161935,EX,CT,Sweden,S,Spain,50,"AWS, Azure, Deep Learning, Python",Bachelor,14,Finance,2025-01-12,2025-02-12,2282,6.1,AI Innovations +AI08264,NLP Engineer,46071,USD,46071,EN,FT,Finland,S,Finland,50,"Python, Kubernetes, R",Associate,1,Finance,2024-09-11,2024-11-23,1573,8.8,AI Innovations +AI08265,Head of AI,138140,SGD,179582,SE,PT,Singapore,M,Singapore,0,"Python, Statistics, Mathematics",Associate,9,Technology,2024-02-11,2024-03-10,1215,5.5,Advanced Robotics +AI08266,NLP Engineer,40218,USD,40218,MI,FT,India,L,India,0,"Deep Learning, Mathematics, Data Visualization",Master,2,Education,2024-01-01,2024-01-23,1620,7.2,Future Systems +AI08267,Robotics Engineer,69695,CAD,87119,EN,CT,Canada,L,Canada,0,"Hadoop, Java, Scala, Azure",Associate,1,Media,2024-06-03,2024-06-22,1729,6.4,Autonomous Tech +AI08268,Machine Learning Researcher,87123,EUR,74055,MI,PT,Germany,L,Germany,100,"Scala, Data Visualization, Statistics",Associate,4,Energy,2025-03-20,2025-05-13,1316,6.3,Cloud AI Solutions +AI08269,Data Engineer,88198,USD,88198,MI,PT,Israel,S,Israel,100,"Spark, PyTorch, Tableau",PhD,3,Energy,2025-01-22,2025-03-21,715,7.3,Smart Analytics +AI08270,AI Product Manager,64179,USD,64179,EN,PT,Sweden,S,Sweden,100,"Java, Git, AWS, Linux, Computer Vision",Associate,0,Consulting,2024-07-13,2024-08-11,1398,9.8,DataVision Ltd +AI08271,ML Ops Engineer,85336,USD,85336,MI,CT,Ireland,M,Ireland,100,"Kubernetes, TensorFlow, Tableau, MLOps, Data Visualization",Master,4,Manufacturing,2024-11-05,2024-12-23,754,6.4,TechCorp Inc +AI08272,Head of AI,83626,AUD,112895,MI,FL,Australia,L,Hungary,0,"Linux, Kubernetes, Scala, Java",PhD,2,Government,2025-03-28,2025-04-18,1439,8.6,Future Systems +AI08273,AI Product Manager,103151,USD,103151,MI,PT,United States,L,United States,50,"Data Visualization, Scala, Tableau",PhD,4,Gaming,2024-11-10,2024-12-04,1252,6.1,Quantum Computing Inc +AI08274,Principal Data Scientist,71248,USD,71248,MI,CT,South Korea,L,South Korea,0,"Data Visualization, Tableau, SQL, NLP, Python",PhD,3,Real Estate,2025-03-01,2025-04-26,1534,10,Advanced Robotics +AI08275,Data Scientist,85197,USD,85197,EN,FL,Ireland,L,Ireland,0,"Docker, Git, Data Visualization",PhD,1,Energy,2024-07-26,2024-09-25,590,6.8,TechCorp Inc +AI08276,AI Consultant,48680,USD,48680,EN,FL,South Korea,S,South Korea,0,"Hadoop, Computer Vision, AWS, PyTorch",Associate,0,Retail,2024-10-05,2024-12-07,1515,9.8,Quantum Computing Inc +AI08277,Head of AI,104442,USD,104442,EN,FL,Norway,M,Norway,50,"Hadoop, R, SQL, MLOps, NLP",PhD,0,Manufacturing,2025-03-21,2025-04-10,1557,8.3,Algorithmic Solutions +AI08278,AI Software Engineer,108808,EUR,92487,SE,FT,Germany,M,Germany,50,"Data Visualization, PyTorch, Scala, AWS",Bachelor,7,Energy,2024-11-29,2025-01-17,851,5.9,DeepTech Ventures +AI08279,Head of AI,222268,EUR,188928,EX,CT,France,L,France,0,"Azure, Kubernetes, Statistics",Associate,12,Automotive,2024-11-20,2024-12-13,1598,8.2,TechCorp Inc +AI08280,AI Research Scientist,69400,USD,69400,MI,CT,Finland,M,Turkey,0,"Deep Learning, Data Visualization, Tableau, Spark, Computer Vision",PhD,2,Real Estate,2024-04-27,2024-06-19,909,6.3,Smart Analytics +AI08281,ML Ops Engineer,146017,JPY,16061870,EX,CT,Japan,S,Colombia,0,"Linux, Deep Learning, SQL",PhD,17,Gaming,2024-02-07,2024-03-10,551,8.4,Advanced Robotics +AI08282,AI Architect,128715,SGD,167330,SE,CT,Singapore,M,Singapore,50,"Python, Deep Learning, Java, SQL",Bachelor,7,Technology,2024-11-05,2024-11-22,1880,6,Smart Analytics +AI08283,Principal Data Scientist,291772,CHF,262595,EX,PT,Switzerland,M,Switzerland,50,"Kubernetes, Docker, SQL, Tableau",Associate,15,Telecommunications,2024-01-02,2024-02-19,1924,6.9,Future Systems +AI08284,Robotics Engineer,88229,USD,88229,SE,FT,South Korea,M,Germany,50,"Docker, Azure, Mathematics, Java",Associate,5,Telecommunications,2024-03-12,2024-04-26,2075,5.3,Cognitive Computing +AI08285,Head of AI,125238,AUD,169071,SE,PT,Australia,S,Japan,0,"Deep Learning, AWS, R, Python",Master,5,Gaming,2024-01-16,2024-02-18,2338,6,Digital Transformation LLC +AI08286,Autonomous Systems Engineer,59375,USD,59375,EN,FL,Finland,S,Finland,0,"R, Tableau, Scala",Bachelor,0,Technology,2024-11-20,2024-12-16,2109,9.5,Advanced Robotics +AI08287,Computer Vision Engineer,200898,USD,200898,EX,FL,Sweden,L,Sweden,100,"MLOps, Git, SQL",Bachelor,16,Automotive,2024-10-11,2024-10-26,2127,9.4,Advanced Robotics +AI08288,AI Architect,70777,USD,70777,EX,CT,India,L,India,0,"Linux, Hadoop, Kubernetes",Associate,18,Retail,2024-10-07,2024-11-10,1846,8.8,DataVision Ltd +AI08289,Head of AI,174280,GBP,130710,EX,PT,United Kingdom,M,Singapore,0,"Git, GCP, MLOps, Python, Azure",PhD,11,Real Estate,2024-10-06,2024-12-05,1269,8.2,DataVision Ltd +AI08290,Autonomous Systems Engineer,83034,CAD,103793,MI,FL,Canada,M,Canada,50,"Azure, PyTorch, Scala, Git, TensorFlow",Bachelor,3,Real Estate,2025-01-07,2025-02-17,2323,7.6,Autonomous Tech +AI08291,Machine Learning Engineer,80523,USD,80523,MI,FT,South Korea,L,South Korea,100,"Statistics, PyTorch, NLP, Azure",Master,3,Real Estate,2025-04-06,2025-05-22,2395,6.7,Quantum Computing Inc +AI08292,Machine Learning Engineer,85363,USD,85363,EN,CT,Sweden,L,Turkey,50,"Python, SQL, Linux, GCP, Hadoop",Bachelor,0,Media,2024-03-19,2024-04-07,601,9.8,Machine Intelligence Group +AI08293,NLP Engineer,84635,USD,84635,EN,CT,Denmark,M,Denmark,0,"Tableau, SQL, Scala",PhD,1,Retail,2024-04-02,2024-04-19,1101,8.4,Machine Intelligence Group +AI08294,AI Research Scientist,92637,EUR,78741,SE,PT,Germany,S,Germany,0,"GCP, Mathematics, Git, SQL",Associate,7,Real Estate,2024-10-31,2024-12-12,716,7.4,AI Innovations +AI08295,AI Research Scientist,135123,SGD,175660,SE,FT,Singapore,S,Singapore,0,"MLOps, Spark, Deep Learning, AWS, R",Associate,7,Telecommunications,2024-08-25,2024-09-10,596,9.9,Future Systems +AI08296,Principal Data Scientist,73693,USD,73693,EX,CT,China,S,China,50,"R, Deep Learning, Statistics, Python, TensorFlow",Associate,13,Healthcare,2024-01-01,2024-02-25,1055,9.1,Cloud AI Solutions +AI08297,AI Specialist,62151,USD,62151,SE,FL,China,M,China,100,"TensorFlow, Python, Java",Bachelor,6,Government,2024-03-16,2024-04-17,1507,7.1,AI Innovations +AI08298,Data Engineer,107829,CHF,97046,MI,FL,Switzerland,S,Switzerland,0,"Spark, TensorFlow, Python, Git",Bachelor,3,Government,2024-07-27,2024-09-17,815,5.8,Cloud AI Solutions +AI08299,Robotics Engineer,149913,GBP,112435,SE,FT,United Kingdom,M,Mexico,100,"Kubernetes, SQL, Statistics, MLOps, Azure",Associate,8,Manufacturing,2024-12-15,2025-01-22,1153,5.7,Neural Networks Co +AI08300,Head of AI,147367,USD,147367,SE,PT,United States,M,Denmark,50,"Data Visualization, Scala, AWS, Computer Vision, SQL",Bachelor,9,Automotive,2025-04-13,2025-06-11,2235,5.2,Cloud AI Solutions +AI08301,Research Scientist,143496,USD,143496,EX,FT,Finland,M,Finland,50,"Linux, Kubernetes, Docker, Tableau",PhD,15,Consulting,2024-01-29,2024-02-23,962,7.3,Machine Intelligence Group +AI08302,AI Architect,265331,USD,265331,EX,FT,Norway,L,Netherlands,50,"Deep Learning, Hadoop, R, SQL, NLP",Master,10,Healthcare,2024-05-25,2024-06-21,605,6.3,Quantum Computing Inc +AI08303,AI Product Manager,72261,EUR,61422,EN,PT,Germany,S,Germany,0,"Data Visualization, Python, Hadoop, Linux, Java",Associate,1,Manufacturing,2024-06-18,2024-08-14,2384,5.7,DataVision Ltd +AI08304,AI Specialist,255237,CHF,229713,EX,CT,Switzerland,S,Mexico,50,"Azure, TensorFlow, Tableau, Data Visualization, GCP",Bachelor,12,Gaming,2024-02-16,2024-03-30,969,7.7,TechCorp Inc +AI08305,AI Specialist,61670,USD,61670,EN,PT,Ireland,M,Ireland,0,"Kubernetes, Python, Spark, Data Visualization",Associate,1,Retail,2024-10-05,2024-12-07,567,8,Smart Analytics +AI08306,AI Product Manager,92113,USD,92113,MI,PT,Ireland,M,Ireland,50,"Azure, Python, Data Visualization, Java, GCP",Master,3,Automotive,2024-05-05,2024-07-02,2339,6.7,Neural Networks Co +AI08307,Head of AI,291884,EUR,248101,EX,PT,Germany,L,Philippines,100,"Data Visualization, Mathematics, SQL",Bachelor,17,Consulting,2025-01-13,2025-02-14,859,7.4,Advanced Robotics +AI08308,Autonomous Systems Engineer,180243,JPY,19826730,EX,PT,Japan,L,Japan,0,"AWS, Hadoop, Java",Bachelor,18,Retail,2025-01-20,2025-03-27,2024,9.9,DeepTech Ventures +AI08309,AI Product Manager,57135,USD,57135,EX,CT,India,M,India,0,"PyTorch, Git, Data Visualization, Scala, Hadoop",Bachelor,10,Automotive,2025-02-07,2025-03-09,1222,8.6,Autonomous Tech +AI08310,Deep Learning Engineer,109488,SGD,142334,SE,FT,Singapore,S,Chile,100,"Linux, SQL, NLP",Bachelor,7,Healthcare,2024-05-13,2024-06-30,1770,5.8,Algorithmic Solutions +AI08311,Head of AI,124520,USD,124520,MI,FT,Denmark,S,Mexico,0,"Git, AWS, Kubernetes",Associate,4,Media,2024-03-09,2024-05-12,922,6.9,DataVision Ltd +AI08312,Deep Learning Engineer,127767,USD,127767,MI,CT,United States,M,United States,50,"Spark, GCP, PyTorch, Mathematics",Associate,4,Transportation,2024-05-01,2024-07-08,1260,7.7,Autonomous Tech +AI08313,Robotics Engineer,80406,USD,80406,MI,FT,Sweden,M,Sweden,0,"MLOps, Azure, Deep Learning",PhD,3,Media,2024-11-01,2024-11-26,1697,6.8,Predictive Systems +AI08314,AI Consultant,82023,CAD,102529,MI,CT,Canada,L,Canada,50,"Linux, Python, TensorFlow, PyTorch",Associate,4,Media,2024-04-14,2024-06-25,1382,9.6,TechCorp Inc +AI08315,Research Scientist,128543,SGD,167106,SE,CT,Singapore,M,Singapore,50,"Python, Spark, PyTorch, Kubernetes",Master,8,Energy,2024-08-05,2024-09-25,514,8,Advanced Robotics +AI08316,Deep Learning Engineer,75558,USD,75558,MI,PT,Sweden,M,Sweden,100,"Spark, Python, SQL, GCP",Associate,2,Transportation,2024-12-21,2025-01-27,1422,6.4,Quantum Computing Inc +AI08317,NLP Engineer,72192,GBP,54144,EN,PT,United Kingdom,M,Poland,50,"Kubernetes, Java, Hadoop",Master,0,Manufacturing,2024-09-08,2024-09-26,501,7.4,Cognitive Computing +AI08318,Data Scientist,68382,EUR,58125,EN,PT,Germany,S,Germany,0,"Deep Learning, Git, Java, SQL",PhD,1,Automotive,2024-03-23,2024-04-26,2001,8.9,Digital Transformation LLC +AI08319,Machine Learning Engineer,37162,USD,37162,SE,FT,India,S,China,100,"Scala, Mathematics, Deep Learning",Master,5,Retail,2024-12-14,2025-02-04,1613,7.5,Algorithmic Solutions +AI08320,Data Engineer,90745,EUR,77133,MI,CT,Netherlands,S,Netherlands,50,"Tableau, SQL, Scala, PyTorch, Python",Master,2,Automotive,2024-08-28,2024-11-03,2203,9.5,AI Innovations +AI08321,Data Engineer,68389,USD,68389,EN,CT,Finland,M,Finland,50,"Hadoop, Python, TensorFlow",Bachelor,1,Automotive,2024-05-27,2024-07-04,1625,8.4,Machine Intelligence Group +AI08322,Deep Learning Engineer,52150,USD,52150,EX,CT,India,S,Japan,50,"PyTorch, MLOps, SQL",Master,16,Telecommunications,2024-02-15,2024-03-10,839,8.4,AI Innovations +AI08323,Machine Learning Engineer,70856,USD,70856,MI,CT,Israel,M,Israel,0,"Kubernetes, Git, Spark, Scala",Bachelor,2,Manufacturing,2024-03-08,2024-05-13,1675,6.1,Cognitive Computing +AI08324,AI Product Manager,70901,USD,70901,EN,FT,Sweden,L,Sweden,0,"AWS, Python, Git, Deep Learning, TensorFlow",Bachelor,0,Education,2024-03-22,2024-04-23,1246,8,Cloud AI Solutions +AI08325,Machine Learning Engineer,18392,USD,18392,EN,CT,India,S,Colombia,100,"Spark, Git, R, Java",PhD,0,Manufacturing,2024-02-18,2024-03-09,1206,9.7,Machine Intelligence Group +AI08326,Machine Learning Engineer,72083,GBP,54062,MI,CT,United Kingdom,S,United Kingdom,100,"Scala, Git, Kubernetes, SQL, AWS",Master,4,Energy,2024-02-27,2024-04-26,1006,9.8,Advanced Robotics +AI08327,Data Engineer,80363,EUR,68309,EN,FL,Netherlands,M,United States,0,"Computer Vision, Spark, Deep Learning, SQL",Bachelor,1,Education,2025-04-30,2025-06-13,2448,8.5,Future Systems +AI08328,Deep Learning Engineer,81508,USD,81508,EX,PT,India,L,India,50,"Hadoop, NLP, Deep Learning, Tableau, Kubernetes",Master,10,Healthcare,2024-07-16,2024-09-17,1183,9.4,Cognitive Computing +AI08329,Computer Vision Engineer,58680,CAD,73350,EN,FT,Canada,M,Ghana,100,"Docker, Scala, SQL, Kubernetes",Bachelor,1,Real Estate,2025-03-24,2025-05-02,1626,5.9,DeepTech Ventures +AI08330,Deep Learning Engineer,127110,EUR,108044,SE,PT,Netherlands,L,Switzerland,100,"NLP, SQL, Linux, Git, GCP",PhD,6,Education,2024-10-21,2024-12-27,1388,9.8,DataVision Ltd +AI08331,Deep Learning Engineer,35777,USD,35777,EN,PT,China,L,China,0,"Hadoop, Java, Data Visualization, NLP",Master,1,Consulting,2024-02-04,2024-03-12,2081,6,Digital Transformation LLC +AI08332,AI Architect,137961,EUR,117267,SE,FL,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Kubernetes",Master,7,Finance,2025-02-23,2025-04-23,1015,8.2,Quantum Computing Inc +AI08333,Data Analyst,93307,CHF,83976,EN,FL,Switzerland,L,Switzerland,50,"SQL, PyTorch, TensorFlow, Linux",Master,0,Manufacturing,2024-03-30,2024-05-22,1208,6.4,Machine Intelligence Group +AI08334,Autonomous Systems Engineer,90828,AUD,122618,EN,FL,Australia,L,Australia,100,"Git, MLOps, Data Visualization",Bachelor,0,Education,2024-02-15,2024-03-30,1635,7.5,Cognitive Computing +AI08335,Data Engineer,42637,USD,42637,SE,PT,India,M,India,0,"SQL, PyTorch, Linux, Scala",PhD,8,Retail,2024-07-27,2024-10-03,1949,7.8,DataVision Ltd +AI08336,Machine Learning Engineer,183463,USD,183463,EX,CT,Denmark,S,Denmark,50,"Python, Computer Vision, Tableau, TensorFlow, Git",Associate,19,Automotive,2024-04-18,2024-05-24,674,5.9,Future Systems +AI08337,Machine Learning Engineer,110858,AUD,149658,MI,CT,Australia,L,Ireland,100,"PyTorch, Java, Tableau, Docker, Statistics",Associate,2,Manufacturing,2025-04-03,2025-05-15,1345,8.7,Cloud AI Solutions +AI08338,AI Consultant,187012,USD,187012,EX,CT,Finland,S,Finland,0,"Git, Azure, Computer Vision, Kubernetes",Master,13,Government,2024-03-21,2024-04-07,640,8.1,Algorithmic Solutions +AI08339,AI Software Engineer,267395,USD,267395,EX,PT,United States,L,United States,0,"Python, TensorFlow, Computer Vision, Statistics",Associate,17,Retail,2024-04-05,2024-05-03,2448,5.1,TechCorp Inc +AI08340,AI Software Engineer,49037,JPY,5394070,EN,PT,Japan,S,Sweden,50,"Computer Vision, Azure, Statistics, SQL, Spark",Bachelor,0,Government,2024-07-25,2024-08-29,2046,8.4,Machine Intelligence Group +AI08341,Deep Learning Engineer,231031,USD,231031,EX,FL,Ireland,L,Ireland,100,"NLP, AWS, SQL, Computer Vision",PhD,16,Automotive,2025-02-18,2025-04-10,1911,8.1,Future Systems +AI08342,AI Specialist,265453,USD,265453,EX,CT,Ireland,L,Ireland,50,"MLOps, AWS, Kubernetes, Scala, Hadoop",Master,14,Automotive,2024-12-24,2025-01-14,1989,7.9,Machine Intelligence Group +AI08343,AI Consultant,82540,USD,82540,MI,CT,Israel,S,Israel,100,"Git, AWS, Python, Computer Vision, Statistics",Bachelor,2,Gaming,2025-02-05,2025-04-01,2265,7.7,Cloud AI Solutions +AI08344,AI Specialist,126029,USD,126029,SE,FL,Israel,S,Israel,50,"Spark, Docker, Computer Vision, Statistics, Python",Master,6,Automotive,2025-02-23,2025-04-07,1666,8.1,Predictive Systems +AI08345,AI Architect,224510,JPY,24696100,EX,PT,Japan,S,Japan,50,"PyTorch, Docker, Git",Bachelor,14,Technology,2025-02-07,2025-04-17,2078,8.4,AI Innovations +AI08346,Research Scientist,76405,USD,76405,EN,FT,Denmark,L,Denmark,0,"Data Visualization, AWS, Spark, Mathematics",Bachelor,1,Gaming,2024-04-13,2024-05-03,1596,7.1,Algorithmic Solutions +AI08347,Machine Learning Researcher,57273,USD,57273,EN,FL,Israel,L,Israel,0,"Kubernetes, SQL, Mathematics",Bachelor,1,Transportation,2025-01-20,2025-03-23,984,7.8,Neural Networks Co +AI08348,Robotics Engineer,78816,USD,78816,MI,FL,South Korea,L,South Korea,50,"Linux, Computer Vision, R, Statistics",Associate,2,Gaming,2024-01-23,2024-02-19,1491,7,DataVision Ltd +AI08349,AI Specialist,129597,USD,129597,EX,FL,Ireland,S,Thailand,50,"Kubernetes, SQL, Statistics, Computer Vision, Java",Master,19,Real Estate,2024-09-25,2024-11-11,1470,7.5,DeepTech Ventures +AI08350,Robotics Engineer,78527,USD,78527,EX,PT,India,L,India,50,"SQL, Tableau, Linux",PhD,16,Energy,2025-01-12,2025-02-13,1545,6.5,Neural Networks Co +AI08351,AI Consultant,147701,GBP,110776,SE,FT,United Kingdom,L,Finland,50,"Computer Vision, Spark, Statistics, Python",Associate,7,Finance,2024-08-08,2024-09-20,623,8,Autonomous Tech +AI08352,Machine Learning Researcher,124500,USD,124500,SE,PT,Israel,L,Israel,100,"Git, Data Visualization, NLP",Associate,6,Consulting,2024-09-22,2024-11-26,2444,7.1,DataVision Ltd +AI08353,Data Engineer,30093,USD,30093,MI,FT,India,L,India,100,"Python, Computer Vision, Statistics",PhD,2,Real Estate,2024-07-08,2024-07-23,1079,5.6,DeepTech Ventures +AI08354,Computer Vision Engineer,95154,USD,95154,MI,CT,Sweden,M,Sweden,100,"Git, NLP, GCP",Bachelor,4,Gaming,2024-03-22,2024-04-23,755,5.8,Future Systems +AI08355,Machine Learning Researcher,125964,USD,125964,EX,FT,Ireland,S,Brazil,0,"SQL, AWS, Mathematics, NLP",Bachelor,14,Media,2025-01-25,2025-02-18,2241,6.7,Cloud AI Solutions +AI08356,Data Engineer,234668,EUR,199468,EX,FL,France,M,China,50,"Linux, NLP, Kubernetes, AWS, Python",PhD,15,Finance,2024-07-17,2024-08-18,1680,9,TechCorp Inc +AI08357,Head of AI,72375,EUR,61519,MI,FL,France,S,Philippines,0,"GCP, Mathematics, SQL, Scala, Deep Learning",Master,4,Consulting,2024-04-07,2024-04-30,759,6.9,DataVision Ltd +AI08358,Data Engineer,199511,USD,199511,EX,CT,Finland,L,Finland,50,"Statistics, NLP, SQL, Kubernetes",Master,15,Consulting,2024-12-19,2025-01-15,523,7.5,AI Innovations +AI08359,AI Specialist,82707,USD,82707,MI,FL,Ireland,S,Ireland,100,"Spark, NLP, Python",Bachelor,4,Manufacturing,2024-07-03,2024-08-19,538,8.9,Predictive Systems +AI08360,AI Architect,49846,USD,49846,EN,CT,Ireland,S,Ireland,50,"Mathematics, Spark, Deep Learning, NLP",Bachelor,0,Transportation,2025-04-03,2025-05-02,1323,5.9,Future Systems +AI08361,AI Research Scientist,231076,SGD,300399,EX,CT,Singapore,S,Singapore,50,"Python, Spark, Statistics, Data Visualization",Bachelor,14,Technology,2024-08-15,2024-09-28,1757,6.8,Neural Networks Co +AI08362,Research Scientist,150796,USD,150796,SE,CT,Denmark,M,Denmark,50,"Python, Mathematics, Kubernetes, Hadoop",Bachelor,7,Telecommunications,2024-05-28,2024-07-20,2287,6.2,Quantum Computing Inc +AI08363,Machine Learning Researcher,116702,USD,116702,SE,CT,Ireland,S,Ireland,50,"NLP, TensorFlow, Java, Linux, R",Bachelor,8,Technology,2025-03-01,2025-03-19,1076,8.3,Advanced Robotics +AI08364,Computer Vision Engineer,127076,CHF,114368,EN,PT,Switzerland,L,Switzerland,0,"NLP, Java, Mathematics, Python",Associate,0,Technology,2024-10-18,2024-12-09,1891,7.8,Quantum Computing Inc +AI08365,Machine Learning Researcher,138133,JPY,15194630,SE,CT,Japan,S,Philippines,100,"MLOps, Python, Data Visualization",PhD,9,Finance,2024-06-12,2024-08-15,1650,8,Cognitive Computing +AI08366,Data Scientist,72519,USD,72519,EN,FT,Finland,M,Switzerland,50,"Java, PyTorch, Spark",Bachelor,1,Manufacturing,2024-11-10,2025-01-22,1763,7.2,Predictive Systems +AI08367,AI Software Engineer,202605,USD,202605,EX,FL,Israel,L,Israel,100,"R, Deep Learning, TensorFlow",Master,19,Energy,2025-04-07,2025-05-04,950,9.1,Neural Networks Co +AI08368,ML Ops Engineer,147327,USD,147327,EX,PT,Finland,L,Vietnam,50,"Scala, GCP, Hadoop, SQL",Associate,12,Transportation,2025-01-07,2025-03-02,1715,5.9,DataVision Ltd +AI08369,AI Specialist,35455,USD,35455,MI,CT,India,M,India,100,"Kubernetes, Deep Learning, Data Visualization, Spark",Associate,4,Media,2025-03-05,2025-05-09,810,8.6,Machine Intelligence Group +AI08370,ML Ops Engineer,85603,USD,85603,MI,FL,Ireland,M,Ireland,100,"Data Visualization, Scala, Spark, Computer Vision",Bachelor,4,Gaming,2025-03-22,2025-05-19,1079,7,Cloud AI Solutions +AI08371,Data Scientist,174323,USD,174323,EX,FL,Israel,M,Spain,100,"Deep Learning, Kubernetes, NLP, Spark",PhD,11,Technology,2025-01-05,2025-01-22,2480,8.9,Autonomous Tech +AI08372,Head of AI,138386,CHF,124547,SE,FL,Switzerland,S,Switzerland,100,"Tableau, Azure, Hadoop, R, NLP",Master,5,Retail,2025-01-21,2025-03-15,2000,8.5,Future Systems +AI08373,AI Specialist,86425,USD,86425,MI,PT,Finland,S,Australia,100,"Python, Statistics, Git",Bachelor,4,Manufacturing,2024-10-24,2024-12-04,1636,9.1,Future Systems +AI08374,AI Architect,79209,EUR,67328,MI,FT,France,M,France,50,"Java, MLOps, TensorFlow",PhD,2,Gaming,2024-05-03,2024-05-22,2438,9.2,Future Systems +AI08375,Robotics Engineer,93206,GBP,69905,MI,PT,United Kingdom,L,United Kingdom,0,"Linux, Mathematics, Deep Learning",Bachelor,2,Consulting,2025-03-19,2025-04-09,692,6.2,Cloud AI Solutions +AI08376,Head of AI,183144,EUR,155672,EX,PT,Germany,S,Germany,50,"Data Visualization, GCP, Spark, TensorFlow",Associate,11,Gaming,2024-04-03,2024-05-12,1696,5.9,Smart Analytics +AI08377,Computer Vision Engineer,115035,USD,115035,MI,FL,United States,L,Poland,50,"Computer Vision, Linux, Mathematics, Git, Kubernetes",PhD,3,Telecommunications,2024-10-05,2024-12-14,1758,8.1,Advanced Robotics +AI08378,Robotics Engineer,52046,USD,52046,EN,PT,Ireland,M,Ireland,0,"Python, Java, Git, Linux, GCP",Master,0,Consulting,2024-04-21,2024-06-18,2451,7.5,Advanced Robotics +AI08379,Data Engineer,27042,USD,27042,MI,FT,India,M,India,0,"Scala, NLP, Java, Hadoop",Associate,3,Retail,2024-08-29,2024-10-21,1230,9.1,Quantum Computing Inc +AI08380,Principal Data Scientist,69140,EUR,58769,MI,FL,Germany,S,Philippines,100,"Java, Computer Vision, R",Associate,4,Education,2024-11-05,2024-11-23,2300,9.2,AI Innovations +AI08381,Principal Data Scientist,54144,USD,54144,SE,FL,China,M,South Korea,50,"Hadoop, Java, AWS, R, MLOps",Bachelor,5,Education,2024-04-07,2024-05-15,1069,8,Digital Transformation LLC +AI08382,Autonomous Systems Engineer,102140,GBP,76605,MI,PT,United Kingdom,M,United Kingdom,50,"Azure, Linux, Deep Learning",PhD,3,Real Estate,2024-09-02,2024-10-26,920,6.4,Smart Analytics +AI08383,Machine Learning Researcher,159981,EUR,135984,SE,PT,Germany,L,Germany,100,"Python, Computer Vision, Deep Learning",Associate,9,Retail,2024-01-16,2024-02-17,1058,7.1,DeepTech Ventures +AI08384,Research Scientist,52315,USD,52315,EN,FT,South Korea,M,South Korea,50,"Hadoop, SQL, Linux, Data Visualization, GCP",PhD,1,Media,2024-05-07,2024-06-17,944,6.2,Quantum Computing Inc +AI08385,AI Research Scientist,174231,AUD,235212,SE,PT,Australia,L,Australia,50,"NLP, Scala, Java, Linux",Associate,7,Manufacturing,2025-02-17,2025-03-14,2270,9.9,Cognitive Computing +AI08386,AI Specialist,97169,GBP,72877,MI,CT,United Kingdom,L,United Kingdom,0,"MLOps, AWS, Java, SQL, Git",Master,3,Government,2024-09-24,2024-10-09,2310,6.1,Predictive Systems +AI08387,Autonomous Systems Engineer,143744,CAD,179680,SE,PT,Canada,M,Poland,0,"Linux, Statistics, Deep Learning, MLOps",Bachelor,9,Energy,2024-12-17,2025-02-03,1811,5.8,Smart Analytics +AI08388,Data Scientist,112243,USD,112243,MI,CT,United States,S,Hungary,100,"Data Visualization, Scala, SQL, AWS",Master,2,Finance,2024-05-28,2024-07-18,978,7.8,Cognitive Computing +AI08389,ML Ops Engineer,127387,USD,127387,MI,FL,Denmark,M,China,0,"Deep Learning, PyTorch, MLOps",Bachelor,3,Technology,2025-04-02,2025-06-08,2393,7.7,Autonomous Tech +AI08390,Machine Learning Researcher,131304,EUR,111608,SE,PT,Austria,M,Austria,0,"SQL, PyTorch, GCP, Hadoop",PhD,6,Consulting,2024-12-16,2025-01-24,1299,8.4,Cognitive Computing +AI08391,Machine Learning Engineer,71777,AUD,96899,EN,FL,Australia,L,Ireland,50,"Java, R, Python, Azure, Mathematics",Master,0,Media,2025-01-03,2025-02-16,1167,8.2,Cognitive Computing +AI08392,Machine Learning Researcher,116676,SGD,151679,SE,PT,Singapore,S,Singapore,100,"Kubernetes, Hadoop, Java",Bachelor,7,Finance,2024-03-06,2024-04-09,764,7.6,AI Innovations +AI08393,AI Consultant,126226,GBP,94670,SE,FL,United Kingdom,S,Mexico,50,"Spark, Java, PyTorch, GCP",Master,6,Technology,2024-10-02,2024-12-11,901,9.1,Advanced Robotics +AI08394,ML Ops Engineer,82894,AUD,111907,MI,CT,Australia,S,Australia,100,"R, GCP, Computer Vision, Spark, SQL",Master,4,Government,2025-02-04,2025-02-18,624,7.8,TechCorp Inc +AI08395,Machine Learning Researcher,38746,USD,38746,EN,FT,China,L,South Korea,0,"Hadoop, Statistics, SQL, Tableau",Bachelor,0,Energy,2025-01-27,2025-02-26,1600,8.4,Quantum Computing Inc +AI08396,AI Consultant,92661,USD,92661,MI,FT,Norway,S,Japan,100,"SQL, Python, Git, Kubernetes",Master,2,Government,2024-04-26,2024-06-25,511,9.4,TechCorp Inc +AI08397,AI Research Scientist,62143,USD,62143,MI,PT,South Korea,M,Czech Republic,100,"Python, TensorFlow, NLP",Associate,4,Media,2025-01-31,2025-02-23,854,5.1,Autonomous Tech +AI08398,AI Software Engineer,176385,GBP,132289,EX,PT,United Kingdom,S,United Kingdom,100,"SQL, Scala, Azure, Computer Vision, GCP",Bachelor,14,Real Estate,2025-02-06,2025-02-21,2442,5.3,Machine Intelligence Group +AI08399,AI Software Engineer,81358,EUR,69154,MI,FL,France,M,France,0,"SQL, Docker, Data Visualization, Hadoop, Deep Learning",Associate,3,Media,2024-04-06,2024-04-28,836,5.3,DeepTech Ventures +AI08400,Robotics Engineer,78489,USD,78489,MI,FL,Israel,M,Israel,0,"Docker, AWS, NLP",PhD,2,Telecommunications,2025-04-02,2025-05-04,712,9,Advanced Robotics +AI08401,Autonomous Systems Engineer,157109,EUR,133543,SE,CT,Germany,L,Portugal,100,"Java, MLOps, R, NLP",PhD,5,Automotive,2025-01-12,2025-01-26,1530,8,Smart Analytics +AI08402,AI Software Engineer,154305,AUD,208312,EX,FL,Australia,S,Ghana,0,"TensorFlow, R, Statistics",Master,17,Telecommunications,2025-01-15,2025-02-19,2485,8,TechCorp Inc +AI08403,Machine Learning Engineer,61309,AUD,82767,EN,PT,Australia,S,India,50,"SQL, Python, Deep Learning, AWS, Statistics",Associate,0,Real Estate,2025-02-06,2025-03-11,820,6.9,DataVision Ltd +AI08404,Data Scientist,189613,AUD,255978,EX,FT,Australia,M,Australia,50,"Java, R, Hadoop",Associate,13,Media,2024-10-29,2024-11-22,1473,9.1,Cloud AI Solutions +AI08405,AI Product Manager,214403,USD,214403,EX,PT,United States,S,United States,0,"Docker, Linux, Azure, Statistics, Tableau",Associate,18,Retail,2025-03-18,2025-04-05,1843,6.3,TechCorp Inc +AI08406,AI Consultant,133222,EUR,113239,SE,PT,Austria,M,Argentina,0,"Scala, PyTorch, GCP, Spark, Computer Vision",Master,7,Transportation,2024-07-03,2024-08-09,1185,8.9,DataVision Ltd +AI08407,Data Engineer,62909,USD,62909,EN,PT,Israel,L,Israel,100,"Tableau, Java, Scala, Data Visualization, TensorFlow",PhD,1,Government,2024-08-19,2024-10-13,2330,5.2,DeepTech Ventures +AI08408,AI Product Manager,19343,USD,19343,EN,FT,India,S,India,50,"GCP, Git, PyTorch",Associate,1,Transportation,2025-01-05,2025-02-08,2174,9.3,Quantum Computing Inc +AI08409,Robotics Engineer,222547,USD,222547,EX,PT,Ireland,S,Ireland,0,"Linux, PyTorch, Data Visualization",Bachelor,14,Manufacturing,2024-02-19,2024-03-09,1579,5.6,Smart Analytics +AI08410,AI Consultant,234130,JPY,25754300,EX,FT,Japan,S,Japan,100,"Linux, Azure, MLOps, Git",Bachelor,11,Real Estate,2025-02-08,2025-02-23,1013,5.8,Cognitive Computing +AI08411,Deep Learning Engineer,215309,USD,215309,EX,CT,Finland,S,Finland,100,"Computer Vision, MLOps, GCP",Master,13,Media,2024-06-30,2024-09-09,1203,7.3,Cognitive Computing +AI08412,AI Product Manager,72372,USD,72372,MI,CT,Israel,S,Chile,50,"Scala, SQL, Spark, GCP",PhD,4,Technology,2024-04-13,2024-05-14,764,8.2,Smart Analytics +AI08413,Deep Learning Engineer,167429,AUD,226029,EX,CT,Australia,L,Austria,100,"SQL, AWS, Scala, GCP, Azure",Bachelor,11,Transportation,2024-04-17,2024-05-05,1020,6.5,Algorithmic Solutions +AI08414,AI Consultant,171432,USD,171432,EX,PT,Israel,L,Israel,50,"Spark, PyTorch, Java, TensorFlow",Bachelor,16,Energy,2024-06-06,2024-07-18,1921,6.1,Predictive Systems +AI08415,AI Research Scientist,162301,USD,162301,SE,FL,Sweden,L,United Kingdom,50,"SQL, Hadoop, Azure",Master,6,Telecommunications,2025-02-03,2025-04-02,1728,6.4,Cognitive Computing +AI08416,Computer Vision Engineer,106745,USD,106745,MI,CT,Sweden,M,Luxembourg,50,"Python, GCP, Azure, SQL, TensorFlow",Bachelor,3,Healthcare,2024-06-27,2024-07-23,2005,9.2,Advanced Robotics +AI08417,AI Specialist,169009,EUR,143658,EX,FL,Netherlands,L,Netherlands,0,"Computer Vision, PyTorch, Tableau",PhD,18,Government,2024-03-24,2024-05-26,1702,6.2,Algorithmic Solutions +AI08418,AI Architect,233941,SGD,304123,EX,PT,Singapore,M,Italy,50,"MLOps, SQL, AWS, NLP, Data Visualization",Bachelor,15,Energy,2024-06-13,2024-07-22,1480,6.3,Machine Intelligence Group +AI08419,AI Software Engineer,179620,EUR,152677,EX,PT,Austria,L,Sweden,50,"Python, Kubernetes, Statistics, AWS",Master,13,Technology,2024-01-28,2024-03-11,1610,9.6,Quantum Computing Inc +AI08420,ML Ops Engineer,128589,JPY,14144790,SE,PT,Japan,S,Japan,50,"PyTorch, TensorFlow, Docker",PhD,6,Gaming,2024-10-13,2024-11-08,2114,9,AI Innovations +AI08421,Deep Learning Engineer,76779,EUR,65262,EN,PT,Netherlands,L,Netherlands,0,"Mathematics, PyTorch, Scala",Associate,1,Retail,2024-12-16,2025-01-12,2438,7,Neural Networks Co +AI08422,AI Specialist,114807,EUR,97586,SE,FL,France,S,Norway,100,"Azure, Java, Git",Master,6,Automotive,2024-06-06,2024-07-31,1526,6.6,DataVision Ltd +AI08423,Autonomous Systems Engineer,126904,AUD,171320,SE,PT,Australia,S,Australia,50,"Scala, Kubernetes, R, GCP, Hadoop",Master,8,Consulting,2024-12-05,2025-01-11,2035,6.8,Neural Networks Co +AI08424,ML Ops Engineer,23823,USD,23823,EN,CT,India,L,India,50,"GCP, Python, TensorFlow, Deep Learning",PhD,0,Media,2024-08-10,2024-09-06,1222,6.2,Cloud AI Solutions +AI08425,Robotics Engineer,91085,USD,91085,MI,FL,United States,S,United States,50,"Computer Vision, Statistics, NLP, Kubernetes",Master,4,Consulting,2025-03-09,2025-05-09,1623,9.9,Cloud AI Solutions +AI08426,AI Software Engineer,123889,EUR,105306,SE,CT,Netherlands,M,Netherlands,0,"Python, Hadoop, R, Linux",Associate,6,Retail,2024-02-10,2024-04-04,1683,8.9,Quantum Computing Inc +AI08427,Machine Learning Engineer,116702,USD,116702,SE,CT,South Korea,M,South Korea,50,"Hadoop, Tableau, AWS, PyTorch",Master,9,Technology,2024-07-14,2024-09-04,1427,6,Predictive Systems +AI08428,Research Scientist,114453,USD,114453,MI,PT,Sweden,L,Argentina,0,"Spark, SQL, Azure, MLOps",PhD,2,Government,2024-06-06,2024-08-04,2473,5.2,TechCorp Inc +AI08429,Data Analyst,127753,GBP,95815,MI,FT,United Kingdom,L,United Kingdom,50,"TensorFlow, Docker, Tableau, Java",Master,4,Technology,2025-01-13,2025-03-14,665,5.1,Smart Analytics +AI08430,AI Research Scientist,279320,SGD,363116,EX,FT,Singapore,L,Turkey,50,"Computer Vision, MLOps, Statistics",Associate,14,Telecommunications,2024-02-28,2024-04-01,1660,8.8,DeepTech Ventures +AI08431,Computer Vision Engineer,193375,EUR,164369,EX,FT,Germany,M,Czech Republic,50,"Tableau, Python, NLP, Spark, Computer Vision",Master,10,Education,2024-06-21,2024-07-06,2499,9.3,Machine Intelligence Group +AI08432,AI Consultant,199737,CHF,179763,SE,FT,Switzerland,M,Switzerland,0,"Java, Scala, MLOps",Master,8,Telecommunications,2025-01-28,2025-02-27,2100,7.8,Cloud AI Solutions +AI08433,AI Software Engineer,53228,USD,53228,EN,CT,Finland,S,Finland,0,"TensorFlow, SQL, Data Visualization, Mathematics",Master,0,Energy,2024-03-06,2024-05-13,1656,9.8,Smart Analytics +AI08434,Autonomous Systems Engineer,124669,EUR,105969,SE,CT,Austria,L,Austria,100,"Deep Learning, Python, Linux",Master,6,Real Estate,2025-02-09,2025-03-21,1166,8.1,Algorithmic Solutions +AI08435,AI Research Scientist,139094,USD,139094,SE,CT,Norway,S,Singapore,50,"SQL, Docker, PyTorch, Hadoop, Scala",Bachelor,5,Education,2024-10-30,2024-11-20,842,9.6,Algorithmic Solutions +AI08436,AI Research Scientist,103028,CHF,92725,EN,FL,Switzerland,L,Portugal,100,"Computer Vision, Tableau, Scala, Deep Learning, Azure",Associate,1,Retail,2024-10-21,2024-11-06,1091,8,Advanced Robotics +AI08437,Data Analyst,140713,USD,140713,SE,PT,Ireland,L,Sweden,50,"Data Visualization, Python, TensorFlow",Associate,5,Automotive,2024-12-10,2025-01-27,2280,9,Cognitive Computing +AI08438,AI Software Engineer,93762,USD,93762,EN,CT,Norway,M,Norway,100,"GCP, Python, Deep Learning, TensorFlow",PhD,1,Education,2025-01-05,2025-03-09,1924,9.2,AI Innovations +AI08439,Machine Learning Engineer,60042,USD,60042,EN,CT,United States,M,United States,50,"Scala, Azure, Tableau",Associate,0,Automotive,2024-06-20,2024-08-16,905,5.2,Neural Networks Co +AI08440,Deep Learning Engineer,125462,USD,125462,SE,FL,Israel,M,Norway,0,"Mathematics, SQL, Data Visualization, Linux",Master,8,Manufacturing,2024-09-18,2024-10-20,1182,9.1,Future Systems +AI08441,Autonomous Systems Engineer,79766,EUR,67801,MI,PT,Germany,M,Germany,0,"Spark, Hadoop, Tableau",Associate,4,Automotive,2025-02-13,2025-03-29,769,7.3,Algorithmic Solutions +AI08442,AI Architect,63995,USD,63995,SE,CT,China,S,China,50,"Java, SQL, Kubernetes, AWS",Associate,9,Energy,2024-05-05,2024-07-09,1467,8,Cognitive Computing +AI08443,Deep Learning Engineer,67575,EUR,57439,EN,CT,France,S,France,0,"R, Scala, GCP, Linux",Bachelor,0,Real Estate,2024-12-28,2025-02-15,2065,9.8,DeepTech Ventures +AI08444,Machine Learning Engineer,180825,GBP,135619,SE,FT,United Kingdom,L,Russia,0,"SQL, Scala, NLP, Statistics, PyTorch",Master,5,Healthcare,2024-02-07,2024-03-17,2210,7.4,Neural Networks Co +AI08445,Autonomous Systems Engineer,46588,USD,46588,SE,CT,China,S,China,0,"Hadoop, Mathematics, NLP, AWS",Bachelor,7,Government,2024-12-04,2025-01-10,1897,8.6,Machine Intelligence Group +AI08446,AI Specialist,70840,USD,70840,EN,FT,Sweden,S,Sweden,0,"SQL, Data Visualization, Linux",Master,0,Telecommunications,2024-06-08,2024-07-21,2485,9,Predictive Systems +AI08447,AI Research Scientist,40656,USD,40656,MI,PT,China,M,China,50,"Python, Mathematics, GCP, AWS",PhD,3,Retail,2025-01-17,2025-03-15,1534,5.3,Advanced Robotics +AI08448,Research Scientist,50149,EUR,42627,EN,PT,Austria,S,Austria,50,"Data Visualization, AWS, SQL, Statistics",Associate,0,Finance,2024-10-15,2024-12-12,1516,6.1,TechCorp Inc +AI08449,Research Scientist,128622,AUD,173640,SE,FL,Australia,M,Australia,100,"Deep Learning, Scala, PyTorch, Mathematics, GCP",Associate,9,Education,2024-12-05,2025-01-22,1434,7.4,Cloud AI Solutions +AI08450,Machine Learning Engineer,100866,GBP,75650,MI,FL,United Kingdom,S,United Kingdom,0,"Java, Scala, Linux, Deep Learning",Bachelor,4,Telecommunications,2024-03-18,2024-04-26,1156,5.5,Quantum Computing Inc +AI08451,AI Architect,98292,GBP,73719,MI,FT,United Kingdom,L,United Kingdom,0,"Scala, Hadoop, Statistics, TensorFlow",Associate,2,Automotive,2024-07-18,2024-09-04,2349,8.4,Quantum Computing Inc +AI08452,Machine Learning Engineer,77362,AUD,104439,MI,FT,Australia,M,Australia,50,"SQL, Linux, Java, PyTorch",Bachelor,4,Gaming,2025-03-18,2025-04-24,834,7.9,DataVision Ltd +AI08453,Data Analyst,78850,AUD,106448,MI,FT,Australia,M,Australia,100,"Tableau, GCP, TensorFlow, PyTorch, Azure",Associate,2,Government,2025-03-06,2025-05-18,1560,5.7,Predictive Systems +AI08454,Computer Vision Engineer,87737,GBP,65803,EN,FT,United Kingdom,L,United Kingdom,0,"R, AWS, NLP, MLOps, Spark",PhD,1,Education,2025-02-09,2025-04-16,552,8.6,Predictive Systems +AI08455,AI Architect,91614,USD,91614,MI,FL,Ireland,L,Ireland,0,"Python, NLP, Kubernetes, Computer Vision",Associate,4,Technology,2024-12-21,2025-02-12,1349,5.5,AI Innovations +AI08456,Computer Vision Engineer,186919,USD,186919,EX,CT,Norway,S,Norway,0,"Java, Linux, SQL, Deep Learning",Bachelor,14,Healthcare,2024-05-16,2024-07-05,1629,9.9,Quantum Computing Inc +AI08457,Data Scientist,70265,CAD,87831,EN,PT,Canada,M,Estonia,50,"Kubernetes, SQL, Tableau, TensorFlow, Mathematics",Bachelor,0,Transportation,2024-07-23,2024-08-07,1608,7.5,AI Innovations +AI08458,Autonomous Systems Engineer,45732,USD,45732,EN,FT,Finland,S,Finland,100,"Kubernetes, SQL, Data Visualization",PhD,1,Energy,2025-02-23,2025-04-05,1157,7.4,DataVision Ltd +AI08459,Machine Learning Researcher,36182,USD,36182,SE,FT,India,M,India,100,"NLP, Data Visualization, PyTorch, MLOps, TensorFlow",Master,6,Automotive,2024-12-03,2025-01-24,2302,7.7,Future Systems +AI08460,AI Software Engineer,64887,EUR,55154,MI,PT,Austria,S,Austria,50,"Linux, Tableau, PyTorch",Associate,4,Consulting,2024-02-26,2024-04-09,1763,7.4,Predictive Systems +AI08461,AI Product Manager,309181,USD,309181,EX,FT,Denmark,L,Estonia,50,"GCP, Python, Spark",Master,15,Government,2025-01-01,2025-02-10,1074,7.6,Smart Analytics +AI08462,Data Analyst,93055,USD,93055,MI,FT,United States,M,United States,100,"Statistics, Kubernetes, Java, GCP, Scala",Master,3,Retail,2024-04-04,2024-05-23,1929,7.2,Cloud AI Solutions +AI08463,Data Analyst,186453,CHF,167808,SE,FL,Switzerland,M,Sweden,100,"Scala, Hadoop, Java, Mathematics, Statistics",Associate,6,Energy,2025-04-06,2025-04-26,567,6.9,DataVision Ltd +AI08464,Computer Vision Engineer,83203,USD,83203,EN,FT,United States,M,United States,100,"SQL, PyTorch, Data Visualization",Associate,0,Gaming,2024-01-27,2024-02-14,1842,6.9,DataVision Ltd +AI08465,Machine Learning Researcher,188584,EUR,160296,EX,FT,Germany,M,Germany,50,"SQL, Kubernetes, Spark, Hadoop",Bachelor,17,Technology,2025-02-16,2025-03-29,1547,9.3,Algorithmic Solutions +AI08466,Data Analyst,121863,USD,121863,MI,FL,Norway,S,Norway,100,"AWS, Linux, Scala",Associate,4,Real Estate,2024-05-16,2024-06-06,2163,9.1,AI Innovations +AI08467,Computer Vision Engineer,53043,CAD,66304,EN,CT,Canada,M,Canada,0,"SQL, Tableau, Java, Kubernetes",PhD,0,Consulting,2024-10-18,2024-11-11,1508,9.8,Predictive Systems +AI08468,Deep Learning Engineer,105766,USD,105766,MI,FL,Norway,S,Norway,50,"TensorFlow, SQL, Scala, Azure",Master,2,Retail,2024-04-03,2024-04-28,1624,9.9,Quantum Computing Inc +AI08469,AI Specialist,127422,EUR,108309,SE,FT,Austria,S,Austria,0,"Statistics, Hadoop, Computer Vision",PhD,6,Healthcare,2024-08-11,2024-10-13,1126,7.4,Future Systems +AI08470,NLP Engineer,274301,CHF,246871,EX,PT,Switzerland,M,Switzerland,0,"Computer Vision, Mathematics, NLP",Bachelor,13,Technology,2024-08-25,2024-09-15,987,5.4,Quantum Computing Inc +AI08471,Machine Learning Engineer,107589,USD,107589,SE,FL,Sweden,S,Sweden,0,"Linux, Docker, Data Visualization, Git",Master,7,Real Estate,2024-07-31,2024-09-23,568,7.7,Quantum Computing Inc +AI08472,ML Ops Engineer,68293,EUR,58049,EN,PT,France,M,France,0,"Git, Scala, Deep Learning, R, Azure",PhD,1,Education,2024-05-15,2024-06-24,2321,7.3,Future Systems +AI08473,Computer Vision Engineer,257050,JPY,28275500,EX,FT,Japan,M,Japan,100,"Deep Learning, Java, Mathematics, Hadoop, PyTorch",Associate,17,Finance,2025-04-27,2025-05-23,2319,9.9,Predictive Systems +AI08474,Deep Learning Engineer,154708,USD,154708,EX,FL,Sweden,M,Hungary,50,"PyTorch, GCP, SQL",Master,13,Healthcare,2024-09-03,2024-09-25,2285,6.8,AI Innovations +AI08475,Machine Learning Researcher,80788,USD,80788,MI,FL,Sweden,S,Sweden,0,"Python, Deep Learning, Docker",PhD,3,Transportation,2024-07-25,2024-09-02,1268,6.9,Digital Transformation LLC +AI08476,Head of AI,117314,USD,117314,SE,FT,Finland,L,Finland,0,"Data Visualization, Python, SQL, Git",Associate,7,Technology,2024-07-05,2024-08-01,1317,5.2,Advanced Robotics +AI08477,Machine Learning Researcher,117690,AUD,158882,SE,CT,Australia,M,Australia,0,"PyTorch, Python, Git",PhD,8,Consulting,2025-04-13,2025-05-08,989,5.6,TechCorp Inc +AI08478,AI Architect,214411,USD,214411,EX,PT,United States,L,United States,50,"NLP, Java, Git, Kubernetes",PhD,11,Finance,2024-11-04,2024-12-13,2395,8.6,Cloud AI Solutions +AI08479,Machine Learning Researcher,155700,USD,155700,SE,PT,United States,S,United States,0,"Python, Statistics, Docker",Bachelor,7,Healthcare,2024-10-15,2024-12-27,1971,9.8,DeepTech Ventures +AI08480,Autonomous Systems Engineer,111686,EUR,94933,SE,CT,Netherlands,M,Colombia,50,"Docker, MLOps, AWS, Deep Learning",Master,7,Finance,2024-08-05,2024-10-04,1018,9.4,Algorithmic Solutions +AI08481,AI Research Scientist,65656,AUD,88636,MI,PT,Australia,S,Malaysia,50,"Computer Vision, SQL, PyTorch, Mathematics, AWS",Master,4,Finance,2024-04-29,2024-07-11,2396,5.1,DataVision Ltd +AI08482,Principal Data Scientist,85926,USD,85926,EX,CT,India,M,India,0,"Data Visualization, R, Java, MLOps",PhD,10,Automotive,2025-02-28,2025-05-12,906,7.2,AI Innovations +AI08483,AI Research Scientist,130166,GBP,97625,EX,FL,United Kingdom,S,United Kingdom,0,"Mathematics, Deep Learning, Hadoop, Docker, Java",Master,11,Education,2024-01-29,2024-03-26,1014,5.4,Machine Intelligence Group +AI08484,Autonomous Systems Engineer,132900,USD,132900,MI,FT,Denmark,L,Denmark,100,"Git, SQL, Python, NLP, Deep Learning",Bachelor,4,Finance,2024-11-06,2024-12-13,660,7.8,DeepTech Ventures +AI08485,Deep Learning Engineer,156100,EUR,132685,SE,PT,Netherlands,L,Netherlands,50,"Python, Java, MLOps",Associate,7,Technology,2024-02-12,2024-03-28,2028,5.2,DataVision Ltd +AI08486,Data Engineer,133627,USD,133627,SE,FT,Norway,M,Norway,100,"Azure, SQL, Kubernetes, Computer Vision, Statistics",Bachelor,9,Education,2024-09-26,2024-11-10,1712,6.4,Cognitive Computing +AI08487,AI Architect,88478,EUR,75206,SE,FT,France,S,France,100,"Hadoop, Linux, AWS, PyTorch, MLOps",Associate,5,Transportation,2024-04-07,2024-06-15,1496,7.5,Smart Analytics +AI08488,Machine Learning Engineer,212608,EUR,180717,EX,PT,Austria,M,Austria,50,"Azure, Computer Vision, Git, AWS, Docker",PhD,12,Telecommunications,2024-07-06,2024-08-09,519,6.5,Quantum Computing Inc +AI08489,AI Architect,58073,USD,58073,EN,FT,Israel,S,Israel,50,"Java, TensorFlow, Mathematics",Master,0,Media,2024-12-23,2025-02-28,903,9.7,DeepTech Ventures +AI08490,AI Consultant,91448,USD,91448,EN,PT,Ireland,L,Czech Republic,50,"PyTorch, MLOps, Spark",PhD,1,Automotive,2025-01-17,2025-02-16,1090,5.6,Digital Transformation LLC +AI08491,Head of AI,95900,USD,95900,MI,PT,Sweden,L,Sweden,0,"TensorFlow, Tableau, R",PhD,4,Transportation,2024-08-14,2024-09-11,647,7.6,Future Systems +AI08492,Principal Data Scientist,179096,AUD,241780,EX,FT,Australia,M,Australia,100,"Spark, SQL, PyTorch, Deep Learning",Associate,18,Transportation,2025-01-25,2025-04-08,1108,6.7,DeepTech Ventures +AI08493,AI Product Manager,59907,USD,59907,EN,FT,Israel,M,Israel,50,"Mathematics, AWS, MLOps, Java",PhD,0,Government,2024-06-23,2024-07-31,1306,9.4,DeepTech Ventures +AI08494,Research Scientist,67233,AUD,90765,EN,FT,Australia,L,Australia,0,"Python, Java, Mathematics, Spark",PhD,1,Automotive,2024-03-15,2024-05-25,943,5.8,Cognitive Computing +AI08495,Data Engineer,203674,CHF,183307,SE,FL,Switzerland,M,Switzerland,50,"Scala, Spark, Azure, Tableau, Kubernetes",Bachelor,9,Real Estate,2024-11-29,2025-01-07,2130,6,Neural Networks Co +AI08496,AI Software Engineer,113013,EUR,96061,SE,FL,Austria,M,Colombia,50,"Python, AWS, Data Visualization, NLP",Bachelor,7,Retail,2025-03-26,2025-05-24,1018,9.9,TechCorp Inc +AI08497,AI Architect,239650,AUD,323528,EX,PT,Australia,M,Australia,50,"Scala, Computer Vision, SQL, Data Visualization",Bachelor,17,Transportation,2024-03-16,2024-05-19,1926,9.1,Neural Networks Co +AI08498,Computer Vision Engineer,237855,CAD,297319,EX,CT,Canada,L,Japan,50,"NLP, Hadoop, MLOps, Scala",PhD,14,Healthcare,2025-01-09,2025-03-17,2032,8.2,DataVision Ltd +AI08499,Machine Learning Researcher,90048,EUR,76541,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Docker, TensorFlow, Scala, AWS",Bachelor,3,Transportation,2025-03-14,2025-05-14,1034,8.4,AI Innovations +AI08500,Robotics Engineer,103593,USD,103593,SE,PT,South Korea,S,South Korea,0,"Spark, Scala, Kubernetes, Hadoop, Java",Master,5,Retail,2024-08-31,2024-09-30,1593,10,Neural Networks Co +AI08501,AI Software Engineer,118005,SGD,153407,SE,PT,Singapore,S,Singapore,0,"Azure, Scala, Deep Learning",Master,9,Media,2024-11-18,2025-01-09,1227,7.1,Predictive Systems +AI08502,Machine Learning Engineer,102645,CHF,92381,EN,FT,Switzerland,M,Switzerland,0,"Hadoop, Kubernetes, Python, Linux",Associate,1,Transportation,2024-09-27,2024-11-30,1269,6,Predictive Systems +AI08503,Research Scientist,213544,AUD,288284,EX,FL,Australia,S,Australia,0,"PyTorch, SQL, MLOps, Spark",Master,16,Telecommunications,2024-05-22,2024-06-21,2216,8.2,Autonomous Tech +AI08504,Autonomous Systems Engineer,99231,EUR,84346,MI,FT,Germany,S,Germany,100,"Azure, SQL, Mathematics, Docker, AWS",Bachelor,2,Finance,2025-03-08,2025-05-04,1765,6.3,Neural Networks Co +AI08505,AI Specialist,189940,CAD,237425,EX,FL,Canada,M,Canada,50,"Azure, Hadoop, SQL, PyTorch",Bachelor,15,Energy,2024-09-09,2024-10-28,949,6.5,Quantum Computing Inc +AI08506,Head of AI,97410,USD,97410,EN,FT,Denmark,M,Denmark,0,"Python, TensorFlow, Linux, PyTorch, Deep Learning",Associate,0,Telecommunications,2025-01-18,2025-02-13,678,8.7,TechCorp Inc +AI08507,AI Specialist,115419,GBP,86564,SE,PT,United Kingdom,M,United Kingdom,0,"Python, Docker, Mathematics",PhD,9,Government,2024-11-06,2024-12-15,2448,9.3,Autonomous Tech +AI08508,Deep Learning Engineer,55421,USD,55421,EN,PT,South Korea,M,South Korea,100,"Python, R, Mathematics, TensorFlow",Bachelor,1,Education,2024-07-09,2024-08-01,2257,8.5,DeepTech Ventures +AI08509,Principal Data Scientist,174114,EUR,147997,SE,FL,Germany,L,Germany,100,"GCP, Python, MLOps",Associate,9,Education,2024-09-02,2024-10-05,1057,7.6,Cloud AI Solutions +AI08510,Data Analyst,223978,USD,223978,EX,PT,Sweden,M,Sweden,0,"R, TensorFlow, Scala, Linux, Mathematics",Master,14,Government,2024-09-15,2024-10-23,1841,7.9,Cloud AI Solutions +AI08511,Principal Data Scientist,239199,GBP,179399,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, Python, Data Visualization",PhD,16,Government,2024-09-24,2024-10-28,2389,6.4,Predictive Systems +AI08512,AI Research Scientist,82844,CHF,74560,EN,FT,Switzerland,M,United Kingdom,0,"Data Visualization, Azure, GCP, Java",PhD,1,Media,2024-06-12,2024-08-18,2214,7.1,Neural Networks Co +AI08513,AI Specialist,122977,USD,122977,SE,PT,Finland,L,Finland,50,"Python, Azure, Spark",Associate,9,Government,2025-02-09,2025-04-12,2372,7.1,Algorithmic Solutions +AI08514,Deep Learning Engineer,113326,USD,113326,MI,PT,Denmark,M,Denmark,50,"Kubernetes, Scala, Git, Azure, AWS",Associate,4,Government,2024-04-16,2024-06-18,850,5,Autonomous Tech +AI08515,Research Scientist,90965,CAD,113706,MI,CT,Canada,S,Turkey,0,"Linux, Kubernetes, Python, TensorFlow, Scala",Associate,3,Education,2025-04-19,2025-05-13,1326,6,Cloud AI Solutions +AI08516,Data Engineer,134158,USD,134158,SE,FL,Finland,L,Finland,50,"Java, SQL, Kubernetes, Hadoop",Associate,5,Media,2024-02-28,2024-04-26,670,5.9,Advanced Robotics +AI08517,Data Engineer,62279,CAD,77849,EN,PT,Canada,M,Canada,50,"Statistics, Python, Computer Vision, Spark, Kubernetes",Master,0,Retail,2024-07-16,2024-08-03,2107,6.4,Neural Networks Co +AI08518,Principal Data Scientist,201716,USD,201716,SE,CT,United States,L,Germany,100,"Spark, NLP, GCP, Tableau",Associate,6,Healthcare,2024-08-06,2024-08-29,572,9.8,AI Innovations +AI08519,AI Software Engineer,165043,USD,165043,EX,PT,Finland,L,Finland,50,"NLP, SQL, Java, GCP",Master,13,Automotive,2024-02-15,2024-03-06,1770,9.4,Predictive Systems +AI08520,NLP Engineer,95834,USD,95834,MI,FT,Denmark,M,Denmark,100,"Python, TensorFlow, Statistics, Azure, GCP",PhD,4,Healthcare,2025-01-03,2025-03-06,1278,7.7,Neural Networks Co +AI08521,AI Architect,131818,USD,131818,SE,FT,South Korea,L,Brazil,0,"Kubernetes, Python, Azure, TensorFlow",Master,5,Energy,2025-03-01,2025-04-03,1547,7,Digital Transformation LLC +AI08522,Robotics Engineer,86510,USD,86510,MI,FT,Denmark,S,South Africa,0,"Deep Learning, Azure, Python",Bachelor,2,Retail,2024-07-23,2024-08-19,2077,6.9,TechCorp Inc +AI08523,AI Software Engineer,83243,USD,83243,EN,PT,Israel,L,United Kingdom,50,"Python, Computer Vision, Linux, TensorFlow, Kubernetes",PhD,1,Gaming,2025-02-25,2025-03-11,1789,5.2,Future Systems +AI08524,AI Software Engineer,76490,CHF,68841,EN,PT,Switzerland,M,United Kingdom,50,"Scala, GCP, Python, Statistics, MLOps",Master,0,Education,2024-01-20,2024-02-08,1601,7.4,Advanced Robotics +AI08525,Head of AI,239503,EUR,203578,EX,CT,Germany,M,Germany,0,"Kubernetes, Hadoop, GCP, TensorFlow, Python",PhD,12,Finance,2025-03-04,2025-03-20,717,9.5,Machine Intelligence Group +AI08526,AI Specialist,159699,AUD,215594,SE,CT,Australia,L,Australia,50,"Scala, Tableau, Azure, Docker",PhD,5,Technology,2024-07-14,2024-08-31,1429,8.8,DeepTech Ventures +AI08527,Machine Learning Engineer,127190,SGD,165347,MI,CT,Singapore,L,Portugal,100,"Linux, NLP, Docker, Hadoop, Computer Vision",Master,2,Technology,2024-06-21,2024-08-27,1630,8.3,Digital Transformation LLC +AI08528,Autonomous Systems Engineer,61030,SGD,79339,EN,FT,Singapore,M,Singapore,50,"Statistics, TensorFlow, Scala, Python",Master,1,Automotive,2024-03-02,2024-04-16,2268,8.9,Future Systems +AI08529,Computer Vision Engineer,30719,USD,30719,MI,FT,India,S,Switzerland,0,"Python, Linux, MLOps, Statistics, Git",Master,2,Healthcare,2024-06-08,2024-06-22,1519,5.4,Neural Networks Co +AI08530,Robotics Engineer,322323,USD,322323,EX,FL,Denmark,M,Denmark,100,"PyTorch, Mathematics, Deep Learning",Bachelor,15,Government,2025-04-11,2025-06-10,1717,7.2,Predictive Systems +AI08531,Data Engineer,239858,CHF,215872,SE,FL,Switzerland,L,Switzerland,0,"TensorFlow, Docker, Linux",PhD,9,Media,2024-01-16,2024-02-12,850,6.6,Smart Analytics +AI08532,AI Specialist,90256,USD,90256,EN,FL,Ireland,L,Norway,100,"TensorFlow, GCP, Statistics, Python",PhD,1,Manufacturing,2025-01-23,2025-02-16,2232,6.8,Quantum Computing Inc +AI08533,Data Scientist,96346,GBP,72260,EN,FT,United Kingdom,L,United Kingdom,50,"MLOps, Spark, GCP",PhD,1,Transportation,2024-11-20,2025-01-15,1593,6.8,Future Systems +AI08534,AI Architect,227082,GBP,170312,EX,FT,United Kingdom,S,United Kingdom,0,"Git, Hadoop, Tableau, AWS",Associate,18,Media,2024-03-18,2024-05-08,1054,8.4,Quantum Computing Inc +AI08535,AI Consultant,174649,USD,174649,EX,FL,Sweden,S,Sweden,100,"PyTorch, GCP, Deep Learning",PhD,19,Telecommunications,2025-01-07,2025-02-01,2161,9.6,Autonomous Tech +AI08536,Principal Data Scientist,244243,EUR,207607,EX,PT,Austria,L,Austria,50,"Mathematics, SQL, Docker, TensorFlow",Master,14,Manufacturing,2025-04-17,2025-05-29,881,5.9,DataVision Ltd +AI08537,AI Software Engineer,140294,GBP,105221,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Scala, MLOps",Master,6,Automotive,2025-01-23,2025-03-30,2467,6.9,AI Innovations +AI08538,AI Consultant,125410,CAD,156763,SE,CT,Canada,L,Ghana,100,"Scala, Hadoop, AWS",Master,5,Real Estate,2024-11-23,2025-01-04,2245,8.1,Cognitive Computing +AI08539,AI Specialist,102002,CAD,127503,MI,CT,Canada,M,Netherlands,0,"Linux, Mathematics, MLOps",Associate,2,Transportation,2024-02-22,2024-04-04,1720,9.7,Autonomous Tech +AI08540,Machine Learning Researcher,70722,AUD,95475,EN,CT,Australia,M,Belgium,100,"Mathematics, Linux, AWS, Docker, SQL",Master,1,Manufacturing,2025-04-25,2025-05-17,1856,8.8,Machine Intelligence Group +AI08541,AI Product Manager,92261,GBP,69196,MI,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, NLP",PhD,3,Government,2024-01-10,2024-01-29,2021,6.4,Quantum Computing Inc +AI08542,AI Architect,84465,CHF,76019,EN,PT,Switzerland,L,Switzerland,100,"Data Visualization, Spark, Deep Learning",Associate,0,Consulting,2025-01-02,2025-02-15,2374,5,Future Systems +AI08543,Machine Learning Engineer,73370,EUR,62365,EN,PT,Germany,M,Germany,50,"Linux, Docker, Kubernetes",PhD,0,Technology,2024-04-21,2024-06-05,2319,6.5,Algorithmic Solutions +AI08544,Data Scientist,125995,EUR,107096,EX,PT,France,S,United Kingdom,0,"SQL, Spark, PyTorch, Hadoop",PhD,12,Transportation,2024-03-21,2024-04-30,1217,9.4,DataVision Ltd +AI08545,Machine Learning Researcher,109740,SGD,142662,MI,CT,Singapore,L,Singapore,100,"Java, Deep Learning, TensorFlow, Statistics",Bachelor,4,Education,2024-02-25,2024-03-14,1024,9.7,Predictive Systems +AI08546,Principal Data Scientist,126186,USD,126186,MI,FL,Norway,S,Norway,50,"Git, Linux, Python, Kubernetes",PhD,3,Energy,2024-04-12,2024-06-04,2446,7.8,DeepTech Ventures +AI08547,AI Product Manager,114618,EUR,97425,SE,FL,Austria,S,Austria,50,"Git, AWS, Azure, Statistics, Scala",Master,8,Manufacturing,2024-11-01,2025-01-09,543,9.3,Advanced Robotics +AI08548,AI Consultant,194158,EUR,165034,EX,PT,France,L,France,100,"Linux, Azure, TensorFlow, Git",PhD,15,Media,2024-09-14,2024-10-18,971,9.5,Future Systems +AI08549,Machine Learning Engineer,68896,USD,68896,EN,CT,Ireland,L,Ireland,0,"TensorFlow, PyTorch, AWS, Statistics",Associate,1,Energy,2024-12-28,2025-01-19,903,6.7,TechCorp Inc +AI08550,AI Product Manager,179602,JPY,19756220,SE,PT,Japan,L,Japan,50,"Docker, Python, NLP, MLOps",Bachelor,8,Gaming,2024-10-22,2024-11-24,2386,7.6,Predictive Systems +AI08551,Machine Learning Engineer,197099,EUR,167534,EX,CT,Netherlands,S,Netherlands,0,"SQL, Spark, Python, R",PhD,17,Finance,2024-10-01,2024-12-09,874,6.6,Autonomous Tech +AI08552,AI Architect,63579,USD,63579,MI,FT,Israel,S,Israel,50,"Hadoop, Linux, GCP, Tableau, Mathematics",Master,3,Gaming,2024-03-16,2024-05-07,2455,7.2,Algorithmic Solutions +AI08553,Machine Learning Researcher,141152,USD,141152,EX,CT,South Korea,S,South Korea,0,"Spark, Linux, Python, Azure",Master,16,Government,2024-10-01,2024-12-12,1492,5.1,Machine Intelligence Group +AI08554,NLP Engineer,96134,SGD,124974,MI,PT,Singapore,M,Singapore,0,"TensorFlow, Mathematics, Data Visualization",Associate,4,Transportation,2024-09-23,2024-11-17,1025,9.4,AI Innovations +AI08555,Research Scientist,127024,GBP,95268,SE,FT,United Kingdom,L,United Kingdom,100,"R, SQL, MLOps, Statistics, Hadoop",Master,9,Energy,2024-05-14,2024-06-30,1870,6.8,Cognitive Computing +AI08556,Machine Learning Researcher,145838,USD,145838,SE,FL,Denmark,M,Denmark,50,"Docker, NLP, Kubernetes, Statistics, Mathematics",Associate,7,Consulting,2024-02-26,2024-03-29,1533,5.2,DataVision Ltd +AI08557,Robotics Engineer,130985,EUR,111337,SE,FL,Germany,M,Germany,50,"Data Visualization, Linux, Python, TensorFlow, AWS",Master,5,Telecommunications,2024-12-29,2025-02-05,2324,6.5,Cloud AI Solutions +AI08558,Robotics Engineer,154058,EUR,130949,SE,PT,France,L,France,0,"Python, TensorFlow, MLOps, Hadoop",PhD,5,Finance,2024-02-08,2024-03-19,2052,5.5,Smart Analytics +AI08559,Machine Learning Researcher,97591,USD,97591,MI,PT,Norway,S,Russia,0,"R, Git, Kubernetes, Computer Vision",Master,2,Government,2025-02-26,2025-04-24,1877,6.9,AI Innovations +AI08560,Machine Learning Engineer,271305,SGD,352697,EX,FL,Singapore,L,New Zealand,100,"Git, PyTorch, AWS, Data Visualization",Associate,19,Transportation,2024-10-04,2024-10-22,638,9.3,Algorithmic Solutions +AI08561,ML Ops Engineer,98409,EUR,83648,MI,CT,Netherlands,L,Netherlands,100,"TensorFlow, MLOps, Scala",PhD,3,Consulting,2024-01-05,2024-02-14,1500,7.7,Machine Intelligence Group +AI08562,AI Research Scientist,148798,JPY,16367780,SE,CT,Japan,L,Japan,100,"Scala, PyTorch, AWS, TensorFlow",Associate,6,Government,2024-11-21,2024-12-31,747,8.3,Cognitive Computing +AI08563,AI Product Manager,279602,GBP,209702,EX,FL,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, Statistics, Docker, Scala",Associate,16,Education,2025-01-23,2025-02-18,1232,7.6,AI Innovations +AI08564,NLP Engineer,95686,SGD,124392,MI,CT,Singapore,S,Luxembourg,50,"Tableau, TensorFlow, Java, Kubernetes",Bachelor,3,Healthcare,2024-11-18,2024-12-10,582,9.9,Future Systems +AI08565,AI Consultant,64322,USD,64322,EN,FT,Israel,M,Israel,0,"NLP, GCP, Docker",PhD,1,Telecommunications,2025-02-16,2025-04-22,2144,5.5,Smart Analytics +AI08566,NLP Engineer,136594,USD,136594,MI,PT,Denmark,M,Nigeria,0,"Java, Computer Vision, Python, AWS, TensorFlow",PhD,2,Energy,2024-05-03,2024-05-29,1479,6.7,AI Innovations +AI08567,Robotics Engineer,82693,EUR,70289,EN,FL,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure",PhD,0,Energy,2025-04-13,2025-05-14,1302,8.8,DataVision Ltd +AI08568,AI Specialist,153976,USD,153976,EX,CT,United States,S,Argentina,50,"Scala, R, Tableau, TensorFlow, Docker",PhD,19,Retail,2024-09-18,2024-10-19,591,6.5,Autonomous Tech +AI08569,Data Scientist,139600,USD,139600,SE,FL,Norway,M,Japan,0,"GCP, Kubernetes, SQL, Computer Vision",Master,6,Media,2024-12-20,2025-02-13,1575,5.5,Cognitive Computing +AI08570,Robotics Engineer,249090,GBP,186818,EX,FT,United Kingdom,L,Poland,50,"Java, Python, Deep Learning",PhD,17,Energy,2024-04-24,2024-06-13,1346,5.6,Cloud AI Solutions +AI08571,Data Analyst,40276,USD,40276,SE,FT,India,S,India,100,"Computer Vision, Linux, GCP, Statistics",Associate,9,Consulting,2024-11-09,2025-01-19,1140,7.5,Digital Transformation LLC +AI08572,Robotics Engineer,72904,USD,72904,MI,FL,Finland,S,Finland,100,"Python, Java, Docker",Master,4,Healthcare,2024-04-10,2024-05-07,920,5,Quantum Computing Inc +AI08573,Research Scientist,64042,SGD,83255,EN,CT,Singapore,S,Singapore,100,"Linux, SQL, Git, MLOps, Hadoop",Bachelor,1,Consulting,2024-10-11,2024-11-12,1592,8.3,DataVision Ltd +AI08574,Machine Learning Researcher,305717,JPY,33628870,EX,PT,Japan,L,Luxembourg,50,"Kubernetes, Git, GCP, NLP, SQL",PhD,15,Technology,2024-08-03,2024-09-04,1529,9.7,DeepTech Ventures +AI08575,Research Scientist,85542,USD,85542,EN,FL,Norway,S,Norway,100,"TensorFlow, Tableau, Python",Bachelor,0,Gaming,2024-07-12,2024-08-11,620,8.6,Digital Transformation LLC +AI08576,Computer Vision Engineer,62229,USD,62229,MI,FL,South Korea,M,Ukraine,100,"Scala, R, NLP, Linux, Deep Learning",Associate,2,Manufacturing,2025-01-20,2025-03-03,2251,6.6,Predictive Systems +AI08577,Data Scientist,183034,CAD,228793,EX,FT,Canada,S,Canada,100,"Azure, SQL, Scala, Data Visualization, Git",Master,15,Technology,2024-04-02,2024-05-25,1927,7.5,AI Innovations +AI08578,Robotics Engineer,77261,CAD,96576,EN,FT,Canada,L,Canada,100,"Hadoop, PyTorch, Java",PhD,0,Technology,2025-02-21,2025-03-10,1539,7.2,Quantum Computing Inc +AI08579,AI Software Engineer,101020,USD,101020,MI,CT,Ireland,L,Thailand,0,"R, Tableau, Azure",Associate,2,Healthcare,2024-09-04,2024-11-16,661,6.9,Predictive Systems +AI08580,AI Consultant,76948,USD,76948,MI,PT,Finland,S,Hungary,100,"Hadoop, Git, PyTorch, AWS, Linux",Bachelor,4,Consulting,2024-02-28,2024-04-01,1102,7.8,Cognitive Computing +AI08581,AI Specialist,81536,USD,81536,EX,FT,China,M,China,0,"Kubernetes, Python, Azure, Spark",Bachelor,13,Gaming,2024-11-02,2024-12-12,2087,5.4,AI Innovations +AI08582,Principal Data Scientist,95198,USD,95198,SE,FL,Finland,S,Finland,0,"Git, R, Tableau",Bachelor,9,Consulting,2024-03-09,2024-04-10,1619,6.4,Predictive Systems +AI08583,AI Consultant,164093,GBP,123070,SE,PT,United Kingdom,L,Ghana,50,"TensorFlow, AWS, Tableau, Kubernetes, NLP",Master,9,Media,2024-04-02,2024-05-23,2074,9.8,DataVision Ltd +AI08584,Research Scientist,140767,USD,140767,SE,CT,United States,L,Hungary,0,"Tableau, Python, TensorFlow, PyTorch",Bachelor,8,Automotive,2024-08-11,2024-10-16,1142,9.1,Algorithmic Solutions +AI08585,Machine Learning Researcher,102336,USD,102336,EX,FL,China,L,China,50,"PyTorch, Hadoop, Git",Master,19,Consulting,2025-04-27,2025-05-11,662,5.8,Advanced Robotics +AI08586,Research Scientist,58994,EUR,50145,EN,FT,Austria,L,Austria,50,"Spark, Linux, Git, Azure",Master,0,Automotive,2025-02-16,2025-03-15,1940,7,DeepTech Ventures +AI08587,NLP Engineer,51117,AUD,69008,EN,FL,Australia,M,Australia,50,"Python, Java, MLOps",Master,0,Real Estate,2024-09-07,2024-11-02,2071,7,Machine Intelligence Group +AI08588,Data Scientist,82013,USD,82013,EN,FT,United States,L,United States,100,"SQL, Statistics, PyTorch, R",PhD,1,Real Estate,2024-06-09,2024-07-24,1950,8.5,AI Innovations +AI08589,AI Product Manager,204881,USD,204881,EX,PT,Finland,S,Finland,50,"Python, Spark, NLP",Master,10,Manufacturing,2024-01-20,2024-02-05,936,8.9,Future Systems +AI08590,AI Software Engineer,78751,USD,78751,EX,CT,India,M,India,100,"NLP, GCP, Spark, Kubernetes",Bachelor,13,Retail,2024-12-20,2025-01-12,1019,6.5,AI Innovations +AI08591,Head of AI,130461,GBP,97846,MI,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Kubernetes, SQL, GCP",PhD,3,Education,2024-08-14,2024-09-10,1707,9,Digital Transformation LLC +AI08592,AI Product Manager,83311,JPY,9164210,MI,PT,Japan,S,Japan,0,"Docker, Spark, Data Visualization, Git, Python",PhD,4,Consulting,2024-01-16,2024-02-17,1419,5.3,AI Innovations +AI08593,AI Research Scientist,57136,GBP,42852,EN,PT,United Kingdom,M,Sweden,100,"AWS, R, SQL, Deep Learning",Associate,0,Retail,2024-02-06,2024-02-25,2040,8.5,TechCorp Inc +AI08594,Head of AI,109478,USD,109478,MI,CT,Sweden,L,Sweden,0,"GCP, Azure, Tableau, Computer Vision, Git",Bachelor,2,Energy,2024-05-12,2024-07-03,1628,9.1,Autonomous Tech +AI08595,NLP Engineer,86990,USD,86990,MI,PT,Israel,L,Romania,0,"TensorFlow, GCP, NLP, Spark, Scala",Associate,3,Consulting,2024-11-05,2024-12-05,2421,6.1,Predictive Systems +AI08596,Machine Learning Engineer,241562,USD,241562,EX,CT,Ireland,M,Ireland,50,"R, Python, Mathematics, NLP",PhD,11,Government,2025-03-21,2025-05-28,1893,5.8,DataVision Ltd +AI08597,Principal Data Scientist,21704,USD,21704,EN,PT,India,M,India,50,"GCP, Deep Learning, Tableau",Associate,1,Telecommunications,2024-10-18,2024-12-25,1489,7.5,Autonomous Tech +AI08598,ML Ops Engineer,88065,EUR,74855,MI,FT,Netherlands,S,Netherlands,50,"Kubernetes, PyTorch, Azure, GCP, MLOps",Bachelor,3,Retail,2025-04-19,2025-05-13,779,5.9,Predictive Systems +AI08599,Research Scientist,52913,USD,52913,MI,PT,China,L,Ghana,0,"Data Visualization, Spark, Kubernetes, Java, Statistics",Associate,2,Education,2024-05-22,2024-06-05,1036,7.7,DataVision Ltd +AI08600,Robotics Engineer,60550,EUR,51468,EN,CT,Netherlands,M,Poland,0,"SQL, Statistics, Spark, Git",Bachelor,1,Energy,2025-03-23,2025-05-17,1973,6.4,Neural Networks Co +AI08601,Computer Vision Engineer,57164,USD,57164,EN,FT,Israel,L,Israel,50,"Azure, Java, Git, Computer Vision, Python",Master,1,Government,2024-05-08,2024-06-05,1916,9.1,DeepTech Ventures +AI08602,Principal Data Scientist,196044,USD,196044,EX,FL,Finland,L,Finland,100,"Java, Python, R, Docker, AWS",Master,19,Automotive,2025-01-13,2025-03-06,1055,6.4,Future Systems +AI08603,Deep Learning Engineer,205349,CAD,256686,EX,CT,Canada,M,Canada,50,"Kubernetes, NLP, Statistics, Deep Learning",Bachelor,10,Finance,2025-02-13,2025-04-19,1523,7.2,Smart Analytics +AI08604,Machine Learning Engineer,141845,CHF,127661,MI,FL,Switzerland,L,Switzerland,50,"AWS, Statistics, Tableau",PhD,2,Real Estate,2024-07-30,2024-09-23,2215,5.3,Quantum Computing Inc +AI08605,AI Specialist,111688,USD,111688,MI,PT,United States,L,Vietnam,50,"Git, Kubernetes, Statistics, Tableau",Bachelor,4,Media,2024-06-12,2024-08-17,1284,6.3,DeepTech Ventures +AI08606,Head of AI,68031,JPY,7483410,EN,FL,Japan,M,Japan,0,"AWS, Linux, Python, TensorFlow, Java",Bachelor,1,Consulting,2024-11-06,2025-01-07,2344,10,Machine Intelligence Group +AI08607,AI Product Manager,107527,CHF,96774,EN,FT,Switzerland,L,Switzerland,100,"Hadoop, MLOps, TensorFlow",PhD,1,Retail,2024-03-14,2024-05-09,2383,6.7,Advanced Robotics +AI08608,AI Consultant,181374,EUR,154168,EX,FL,Germany,M,Germany,50,"Hadoop, GCP, PyTorch, SQL, Linux",Master,13,Energy,2025-03-02,2025-04-14,865,7.3,Algorithmic Solutions +AI08609,Data Engineer,118961,EUR,101117,SE,PT,Germany,S,Portugal,0,"Kubernetes, AWS, R",PhD,8,Retail,2024-09-04,2024-11-16,1248,9.6,Algorithmic Solutions +AI08610,ML Ops Engineer,52835,USD,52835,MI,FT,China,L,China,50,"Spark, Kubernetes, Deep Learning",Bachelor,4,Education,2025-04-14,2025-05-09,1169,8.6,Smart Analytics +AI08611,Machine Learning Engineer,70673,USD,70673,SE,FT,China,M,China,50,"Java, Kubernetes, Tableau",Master,7,Telecommunications,2024-04-28,2024-05-17,1371,9.1,Quantum Computing Inc +AI08612,ML Ops Engineer,94570,AUD,127670,SE,CT,Australia,S,Australia,0,"Python, TensorFlow, Docker, R, Computer Vision",PhD,8,Transportation,2024-09-09,2024-10-10,1297,5.5,Digital Transformation LLC +AI08613,AI Research Scientist,64693,USD,64693,EN,FT,Israel,L,Israel,0,"AWS, MLOps, GCP, Mathematics",Bachelor,0,Consulting,2024-05-17,2024-07-21,2215,6.2,Quantum Computing Inc +AI08614,Head of AI,191853,USD,191853,SE,PT,Denmark,M,Denmark,0,"Scala, Git, Kubernetes, PyTorch, Python",PhD,8,Media,2025-01-30,2025-03-22,900,7.4,Autonomous Tech +AI08615,Data Analyst,114269,SGD,148550,SE,FT,Singapore,M,Singapore,0,"AWS, Statistics, NLP, Tableau",Bachelor,9,Energy,2024-12-16,2025-01-29,2116,9,Machine Intelligence Group +AI08616,Machine Learning Researcher,269818,JPY,29679980,EX,PT,Japan,M,Japan,50,"Computer Vision, PyTorch, Python, Azure, AWS",Bachelor,15,Real Estate,2024-02-05,2024-03-07,935,9.8,TechCorp Inc +AI08617,AI Software Engineer,120069,USD,120069,SE,CT,Norway,S,Norway,50,"AWS, R, Statistics, PyTorch",PhD,5,Manufacturing,2024-07-10,2024-08-18,1887,7.3,Cognitive Computing +AI08618,Data Analyst,86504,USD,86504,MI,FT,South Korea,M,South Korea,0,"Python, Hadoop, Git, TensorFlow",Bachelor,3,Media,2025-01-13,2025-03-02,2433,6.4,Future Systems +AI08619,Machine Learning Researcher,120570,USD,120570,EX,CT,China,L,China,50,"Python, SQL, AWS, Computer Vision",Bachelor,17,Telecommunications,2024-02-11,2024-03-10,1747,5.2,DeepTech Ventures +AI08620,Data Scientist,184942,USD,184942,EX,CT,Ireland,L,Latvia,50,"Computer Vision, Docker, R",Master,17,Automotive,2024-07-09,2024-08-24,600,9.6,AI Innovations +AI08621,Data Scientist,89220,EUR,75837,EN,PT,Germany,L,Germany,50,"Linux, Git, Computer Vision, Hadoop, Java",PhD,0,Real Estate,2024-03-08,2024-04-13,1551,5.3,Future Systems +AI08622,AI Product Manager,134492,JPY,14794120,SE,FL,Japan,M,Japan,100,"R, Statistics, NLP, Spark",Associate,8,Transportation,2024-10-31,2024-12-23,2443,8.6,DeepTech Ventures +AI08623,Machine Learning Researcher,137903,EUR,117218,EX,FL,France,S,France,50,"Java, Hadoop, NLP",Associate,16,Manufacturing,2024-11-10,2024-12-10,796,7.2,Smart Analytics +AI08624,Deep Learning Engineer,139031,GBP,104273,EX,FT,United Kingdom,S,Norway,0,"Linux, Azure, Mathematics, SQL, Hadoop",PhD,16,Energy,2024-12-15,2025-01-03,1916,5.9,Autonomous Tech +AI08625,AI Software Engineer,202153,USD,202153,EX,FT,South Korea,L,South Korea,50,"Scala, Computer Vision, Linux, Python, Kubernetes",Associate,17,Consulting,2025-03-05,2025-04-09,1250,6.2,DeepTech Ventures +AI08626,AI Architect,71668,USD,71668,MI,PT,Israel,S,South Africa,100,"Kubernetes, Git, R, PyTorch",Associate,3,Retail,2025-01-19,2025-04-02,1593,6,Cloud AI Solutions +AI08627,AI Product Manager,89404,USD,89404,EN,CT,Denmark,L,Denmark,0,"PyTorch, Tableau, TensorFlow",Bachelor,0,Finance,2024-11-04,2024-12-09,1637,8,DeepTech Ventures +AI08628,Head of AI,145615,USD,145615,SE,FT,Sweden,M,Sweden,0,"Linux, MLOps, Data Visualization, Python, NLP",Associate,8,Consulting,2024-10-10,2024-11-09,2127,9.5,Cloud AI Solutions +AI08629,Data Analyst,207813,USD,207813,EX,FL,Finland,L,Finland,0,"R, Linux, Deep Learning",Associate,13,Transportation,2024-12-30,2025-02-17,1223,5.3,Cloud AI Solutions +AI08630,AI Architect,142528,EUR,121149,SE,FT,Netherlands,M,Netherlands,50,"Git, Scala, Statistics, MLOps, SQL",Master,8,Technology,2025-03-21,2025-05-22,1866,6.3,Autonomous Tech +AI08631,AI Specialist,68097,USD,68097,MI,FT,Finland,M,Finland,50,"Kubernetes, Python, GCP",Bachelor,3,Manufacturing,2025-03-11,2025-04-08,1548,7.5,Machine Intelligence Group +AI08632,Data Engineer,224311,SGD,291604,EX,CT,Singapore,S,Singapore,50,"Java, Linux, Mathematics, Azure, Scala",Associate,17,Transportation,2025-01-16,2025-01-30,659,8.8,AI Innovations +AI08633,Autonomous Systems Engineer,114501,CAD,143126,SE,FT,Canada,L,Canada,50,"Tableau, PyTorch, Git, Python, Linux",Bachelor,7,Consulting,2024-10-26,2024-11-11,880,6.1,Autonomous Tech +AI08634,NLP Engineer,65825,USD,65825,SE,FL,China,L,China,0,"AWS, Java, Azure",Bachelor,5,Finance,2024-10-04,2024-10-24,1602,9.2,Autonomous Tech +AI08635,AI Specialist,196121,CAD,245151,EX,PT,Canada,S,Canada,0,"Spark, Kubernetes, GCP, Tableau",Associate,18,Education,2025-04-30,2025-06-18,954,7.6,AI Innovations +AI08636,Principal Data Scientist,94824,USD,94824,EN,PT,United States,M,United States,100,"Hadoop, Linux, Kubernetes",Associate,1,Manufacturing,2024-01-02,2024-03-03,922,5,Machine Intelligence Group +AI08637,AI Software Engineer,48808,USD,48808,SE,PT,China,M,China,100,"Linux, Docker, R, Mathematics",Master,8,Government,2024-04-09,2024-06-16,2216,8.1,Autonomous Tech +AI08638,Robotics Engineer,119252,EUR,101364,SE,CT,Netherlands,M,Finland,0,"PyTorch, TensorFlow, Mathematics, Java, Spark",Master,5,Finance,2024-11-28,2025-02-05,1993,7.6,Machine Intelligence Group +AI08639,AI Architect,77771,CHF,69994,EN,FL,Switzerland,M,Switzerland,50,"Scala, Tableau, Deep Learning",Master,0,Education,2024-02-11,2024-03-05,1677,8.1,Future Systems +AI08640,ML Ops Engineer,106474,USD,106474,SE,CT,Ireland,S,Ireland,0,"PyTorch, SQL, AWS, Docker",Master,6,Consulting,2024-09-22,2024-10-06,1764,6.9,Algorithmic Solutions +AI08641,Computer Vision Engineer,233835,AUD,315677,EX,CT,Australia,M,Australia,100,"R, GCP, Mathematics",Associate,17,Government,2024-12-30,2025-02-18,2214,8.9,Future Systems +AI08642,Data Analyst,95754,SGD,124480,MI,CT,Singapore,M,Singapore,100,"Tableau, TensorFlow, NLP, SQL",Bachelor,2,Telecommunications,2024-07-21,2024-09-24,1939,8.9,AI Innovations +AI08643,Data Engineer,111708,CAD,139635,SE,CT,Canada,S,Russia,0,"Python, TensorFlow, Kubernetes, Hadoop, Docker",Bachelor,5,Government,2024-09-08,2024-11-12,2019,5.3,Quantum Computing Inc +AI08644,Principal Data Scientist,263271,JPY,28959810,EX,CT,Japan,M,Kenya,100,"Kubernetes, TensorFlow, Mathematics, AWS, PyTorch",Bachelor,14,Healthcare,2024-01-07,2024-03-11,1071,9.6,Quantum Computing Inc +AI08645,Robotics Engineer,201498,USD,201498,SE,PT,Norway,L,Norway,100,"Spark, Java, Docker, GCP, Statistics",Master,6,Telecommunications,2024-03-04,2024-04-17,1970,8.9,Cognitive Computing +AI08646,Machine Learning Researcher,98345,USD,98345,EN,PT,Norway,M,Norway,100,"R, Linux, Java",Bachelor,0,Automotive,2024-11-01,2024-11-27,1920,5.9,TechCorp Inc +AI08647,Data Engineer,47321,USD,47321,MI,PT,China,M,China,50,"GCP, Java, Tableau, Statistics",Associate,4,Manufacturing,2024-03-11,2024-04-06,1151,8.8,DataVision Ltd +AI08648,Data Analyst,76662,USD,76662,MI,FT,South Korea,S,Romania,100,"Statistics, Python, NLP",Associate,3,Retail,2025-04-06,2025-05-16,1934,9.5,Quantum Computing Inc +AI08649,Data Scientist,135115,USD,135115,SE,CT,Israel,L,Egypt,100,"Docker, Spark, R, MLOps, Azure",Associate,6,Manufacturing,2024-06-24,2024-08-29,1019,5.6,Cloud AI Solutions +AI08650,Computer Vision Engineer,95343,EUR,81042,MI,PT,France,M,France,100,"SQL, GCP, Docker, Computer Vision, Hadoop",Master,4,Technology,2024-07-08,2024-08-12,2321,7.6,TechCorp Inc +AI08651,Principal Data Scientist,19877,USD,19877,EN,FL,India,S,India,0,"R, Python, Computer Vision",PhD,1,Government,2024-10-25,2024-12-23,1853,6.7,Machine Intelligence Group +AI08652,AI Consultant,120340,SGD,156442,SE,FL,Singapore,M,Singapore,50,"Linux, Java, Python, Kubernetes, Deep Learning",Bachelor,8,Automotive,2024-07-20,2024-08-24,2341,9.6,Autonomous Tech +AI08653,Data Analyst,105495,SGD,137144,SE,CT,Singapore,S,Singapore,0,"Java, GCP, AWS",PhD,8,Transportation,2024-03-04,2024-05-16,715,7.8,Machine Intelligence Group +AI08654,Data Scientist,23760,USD,23760,EN,FL,China,S,China,50,"TensorFlow, Linux, Computer Vision",Associate,0,Telecommunications,2024-09-05,2024-10-10,2121,8.5,Neural Networks Co +AI08655,Research Scientist,81420,JPY,8956200,EN,FT,Japan,M,Japan,50,"PyTorch, Tableau, Scala",Bachelor,1,Technology,2024-08-07,2024-10-08,2240,6.8,Autonomous Tech +AI08656,Machine Learning Researcher,117907,SGD,153279,SE,PT,Singapore,M,Singapore,100,"Python, Git, R, TensorFlow, Statistics",Associate,6,Government,2024-02-08,2024-04-14,2148,7.7,Future Systems +AI08657,Machine Learning Engineer,96703,JPY,10637330,MI,FT,Japan,S,Japan,100,"Azure, Java, GCP, TensorFlow, MLOps",Associate,2,Healthcare,2025-04-06,2025-06-15,1390,8.5,Cloud AI Solutions +AI08658,Data Analyst,64544,AUD,87134,EN,CT,Australia,S,Australia,100,"SQL, Java, Mathematics, PyTorch",Bachelor,1,Transportation,2025-03-27,2025-04-17,1219,5.6,TechCorp Inc +AI08659,Principal Data Scientist,113782,JPY,12516020,SE,FL,Japan,M,Japan,100,"Scala, Azure, PyTorch, SQL",Bachelor,5,Media,2024-04-05,2024-05-10,1092,9.9,Predictive Systems +AI08660,Machine Learning Researcher,128270,USD,128270,MI,FT,United States,L,United States,100,"R, Git, Python, NLP, TensorFlow",Master,2,Telecommunications,2025-02-20,2025-03-25,2100,5.6,Machine Intelligence Group +AI08661,Head of AI,65592,USD,65592,MI,FL,Sweden,S,Sweden,100,"Python, Git, Scala",Master,3,Media,2024-03-04,2024-04-14,2111,9.3,Advanced Robotics +AI08662,AI Software Engineer,54617,CAD,68271,EN,FT,Canada,M,Canada,100,"MLOps, Java, Python",Bachelor,0,Manufacturing,2024-02-12,2024-04-24,993,8.7,Predictive Systems +AI08663,AI Consultant,82192,USD,82192,MI,FT,South Korea,M,Italy,50,"Kubernetes, Scala, Spark",Associate,2,Automotive,2024-03-05,2024-04-18,994,6.1,Advanced Robotics +AI08664,Principal Data Scientist,81981,EUR,69684,MI,FT,France,L,France,50,"Python, NLP, TensorFlow, Git, Java",Master,4,Media,2024-07-08,2024-09-08,1850,6.7,Neural Networks Co +AI08665,AI Research Scientist,76034,EUR,64629,MI,PT,Austria,S,Austria,0,"R, Computer Vision, Python, Kubernetes, MLOps",Bachelor,3,Manufacturing,2024-06-06,2024-07-30,1652,8,Future Systems +AI08666,AI Architect,24952,USD,24952,EN,CT,India,M,India,50,"Linux, PyTorch, Python, Hadoop",Bachelor,0,Manufacturing,2025-01-16,2025-03-24,2290,9.1,Cloud AI Solutions +AI08667,Data Engineer,44314,USD,44314,MI,CT,China,S,Switzerland,0,"PyTorch, GCP, SQL, Data Visualization, Tableau",PhD,2,Telecommunications,2024-09-05,2024-11-17,1117,7.4,Predictive Systems +AI08668,AI Product Manager,160046,CAD,200058,EX,CT,Canada,L,Canada,0,"Tableau, R, Git, Data Visualization, Computer Vision",Associate,10,Technology,2025-02-26,2025-04-08,1302,6.3,DataVision Ltd +AI08669,Data Scientist,224937,EUR,191196,EX,FL,Netherlands,M,China,0,"SQL, PyTorch, Mathematics",Master,13,Real Estate,2025-04-27,2025-06-14,2360,7.6,Predictive Systems +AI08670,Deep Learning Engineer,69057,SGD,89774,MI,PT,Singapore,S,Singapore,50,"R, AWS, Azure, Deep Learning",Associate,3,Technology,2024-01-25,2024-02-10,991,6.4,Cognitive Computing +AI08671,AI Consultant,65525,EUR,55696,EN,FL,Germany,M,Germany,100,"Hadoop, SQL, Computer Vision",PhD,0,Technology,2024-12-31,2025-01-27,1022,5.6,AI Innovations +AI08672,Data Engineer,231770,CHF,208593,EX,FT,Switzerland,M,Switzerland,0,"Kubernetes, Spark, GCP",PhD,10,Telecommunications,2024-03-09,2024-03-24,946,6.2,Quantum Computing Inc +AI08673,Autonomous Systems Engineer,189743,GBP,142307,EX,CT,United Kingdom,S,United Kingdom,0,"Python, Linux, TensorFlow, Data Visualization",Bachelor,11,Education,2024-11-11,2025-01-04,1985,7.6,DeepTech Ventures +AI08674,AI Consultant,84046,CAD,105058,MI,CT,Canada,L,Brazil,50,"NLP, GCP, Python, Tableau",Associate,2,Finance,2024-11-03,2025-01-11,1018,5.7,DeepTech Ventures +AI08675,Robotics Engineer,58018,USD,58018,SE,FL,China,M,China,100,"Computer Vision, Hadoop, Python",Associate,7,Media,2024-02-15,2024-03-11,2304,8,Neural Networks Co +AI08676,Head of AI,82096,USD,82096,EX,FT,China,L,Finland,50,"Git, Linux, Hadoop, GCP, Kubernetes",Associate,10,Finance,2025-02-10,2025-03-14,2277,5.1,Advanced Robotics +AI08677,AI Research Scientist,228962,EUR,194618,EX,FL,France,L,France,50,"Hadoop, SQL, Python",PhD,14,Energy,2024-10-15,2024-12-24,601,9.5,Quantum Computing Inc +AI08678,Head of AI,59789,EUR,50821,EN,CT,Netherlands,S,Netherlands,100,"R, Hadoop, Kubernetes, GCP",PhD,0,Finance,2024-10-26,2024-12-13,1908,7.9,Autonomous Tech +AI08679,AI Product Manager,65661,JPY,7222710,EN,CT,Japan,S,Japan,0,"Spark, Linux, PyTorch",Bachelor,0,Education,2024-09-27,2024-11-06,1374,6.3,Advanced Robotics +AI08680,Head of AI,192079,USD,192079,EX,FT,South Korea,L,South Korea,0,"Spark, Java, TensorFlow, Statistics, AWS",PhD,11,Telecommunications,2025-01-02,2025-03-05,2192,5.7,Predictive Systems +AI08681,Computer Vision Engineer,98259,EUR,83520,MI,FL,Germany,S,Germany,100,"Java, Spark, Mathematics, R",Associate,3,Telecommunications,2025-01-14,2025-03-21,639,8.4,Algorithmic Solutions +AI08682,Data Analyst,152980,SGD,198874,EX,FL,Singapore,M,Singapore,100,"R, Tableau, SQL",Associate,18,Transportation,2024-04-16,2024-05-07,1446,7,Autonomous Tech +AI08683,AI Product Manager,52672,EUR,44771,EN,FL,Austria,S,Austria,0,"R, Statistics, Data Visualization",Bachelor,0,Manufacturing,2024-07-12,2024-08-21,2084,9.1,Algorithmic Solutions +AI08684,ML Ops Engineer,22389,USD,22389,EN,FL,India,S,Luxembourg,0,"Mathematics, Tableau, GCP",Bachelor,1,Manufacturing,2024-10-17,2024-11-01,2404,9.6,Quantum Computing Inc +AI08685,ML Ops Engineer,62477,AUD,84344,EN,CT,Australia,M,Australia,0,"Hadoop, Git, Python",Master,1,Manufacturing,2024-02-07,2024-02-25,797,8.8,DataVision Ltd +AI08686,Principal Data Scientist,76545,USD,76545,MI,CT,Ireland,M,Ireland,100,"PyTorch, NLP, Java, Mathematics",Bachelor,3,Healthcare,2024-12-09,2025-02-01,1782,6.9,Cognitive Computing +AI08687,AI Software Engineer,86947,USD,86947,SE,FL,South Korea,M,Canada,100,"Kubernetes, TensorFlow, Python",PhD,6,Energy,2024-08-24,2024-10-19,976,6.5,Cloud AI Solutions +AI08688,Deep Learning Engineer,83441,GBP,62581,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, Python, TensorFlow, Git, PyTorch",Master,4,Media,2024-01-16,2024-03-19,555,7.4,Algorithmic Solutions +AI08689,AI Architect,300340,GBP,225255,EX,FT,United Kingdom,L,United Kingdom,100,"Git, Kubernetes, R, NLP, Deep Learning",Master,11,Real Estate,2025-03-16,2025-04-09,2004,6.7,Predictive Systems +AI08690,AI Research Scientist,149207,USD,149207,SE,CT,United States,S,United States,100,"Statistics, Azure, Computer Vision",Bachelor,6,Consulting,2024-01-12,2024-03-04,656,5.1,AI Innovations +AI08691,Principal Data Scientist,160666,EUR,136566,SE,PT,Netherlands,L,Nigeria,0,"GCP, Scala, Data Visualization, Spark, Mathematics",Master,9,Energy,2025-01-08,2025-01-30,2146,5.6,Algorithmic Solutions +AI08692,Machine Learning Researcher,150614,EUR,128022,SE,FL,Germany,L,Japan,0,"Python, Git, Spark",Master,7,Consulting,2024-07-28,2024-10-03,1729,8,DataVision Ltd +AI08693,AI Consultant,55468,EUR,47148,EN,CT,Germany,S,Germany,50,"Hadoop, Data Visualization, Git",Master,1,Technology,2024-05-18,2024-07-03,1912,9.4,Algorithmic Solutions +AI08694,Autonomous Systems Engineer,106627,USD,106627,MI,FL,Norway,M,Singapore,50,"Linux, Data Visualization, Python, Deep Learning",Associate,4,Automotive,2025-02-17,2025-04-03,2132,8.7,Future Systems +AI08695,Computer Vision Engineer,151032,SGD,196342,SE,CT,Singapore,M,Singapore,0,"Scala, Computer Vision, Linux, Spark",PhD,6,Automotive,2025-02-17,2025-04-16,2187,9.4,Algorithmic Solutions +AI08696,AI Architect,62996,USD,62996,EN,PT,South Korea,M,Mexico,100,"Scala, Data Visualization, Python, Statistics",PhD,0,Manufacturing,2024-12-15,2025-01-11,710,5.4,Quantum Computing Inc +AI08697,ML Ops Engineer,124463,AUD,168025,SE,PT,Australia,S,Ireland,100,"Spark, AWS, R, Computer Vision, PyTorch",PhD,6,Energy,2024-02-21,2024-04-05,2212,5.3,Predictive Systems +AI08698,Data Engineer,84011,EUR,71409,MI,FT,Germany,L,China,50,"SQL, Python, NLP, Statistics, Deep Learning",Bachelor,2,Healthcare,2024-10-16,2024-11-29,2444,8.4,Digital Transformation LLC +AI08699,Machine Learning Engineer,108909,USD,108909,SE,FL,South Korea,M,South Korea,0,"AWS, SQL, MLOps",PhD,6,Technology,2025-04-07,2025-06-06,2373,9.7,Machine Intelligence Group +AI08700,Autonomous Systems Engineer,117099,AUD,158084,SE,PT,Australia,M,Australia,50,"Azure, Tableau, SQL, Git",Bachelor,7,Telecommunications,2024-06-29,2024-07-16,1572,8.5,AI Innovations +AI08701,AI Architect,243649,CHF,219284,SE,CT,Switzerland,L,Switzerland,50,"R, NLP, Python, Azure",Bachelor,6,Telecommunications,2024-11-25,2024-12-22,734,7,Future Systems +AI08702,AI Consultant,85139,USD,85139,MI,CT,Sweden,S,Sweden,0,"Python, SQL, Computer Vision, Statistics",Bachelor,4,Manufacturing,2024-11-10,2024-12-25,746,9.7,Future Systems +AI08703,AI Architect,149890,CHF,134901,SE,PT,Switzerland,S,South Africa,50,"NLP, GCP, Spark, Linux",Associate,9,Retail,2024-10-04,2024-10-19,933,6.5,DeepTech Ventures +AI08704,Head of AI,72866,USD,72866,MI,FL,South Korea,M,South Korea,50,"Python, TensorFlow, NLP, Deep Learning, MLOps",Master,3,Finance,2024-07-12,2024-07-28,2089,9.4,Digital Transformation LLC +AI08705,AI Specialist,26722,USD,26722,EN,CT,India,L,India,50,"Azure, SQL, Java, PyTorch",Bachelor,1,Education,2024-07-12,2024-08-09,1064,6.8,TechCorp Inc +AI08706,AI Specialist,169001,USD,169001,SE,FT,Norway,L,Czech Republic,100,"Python, R, Computer Vision, Hadoop",Master,8,Finance,2024-09-14,2024-10-06,2184,5.4,Advanced Robotics +AI08707,Principal Data Scientist,71514,USD,71514,MI,PT,South Korea,S,South Korea,50,"Scala, Kubernetes, Azure, Deep Learning, SQL",Bachelor,3,Government,2025-01-30,2025-03-01,708,9.3,Algorithmic Solutions +AI08708,Machine Learning Researcher,128232,EUR,108997,SE,FT,Netherlands,M,Japan,50,"Spark, Data Visualization, TensorFlow, Mathematics, Azure",Master,6,Energy,2024-06-07,2024-07-01,883,6.9,Future Systems +AI08709,AI Software Engineer,58091,USD,58091,EN,FL,Israel,M,Austria,0,"Python, Mathematics, NLP, TensorFlow, Spark",Bachelor,1,Consulting,2025-04-07,2025-06-11,674,7.4,DataVision Ltd +AI08710,Deep Learning Engineer,63424,JPY,6976640,EN,CT,Japan,S,Japan,100,"Kubernetes, R, Hadoop, Azure",Associate,0,Real Estate,2024-08-27,2024-10-23,1625,8.8,Smart Analytics +AI08711,Computer Vision Engineer,65363,USD,65363,SE,FL,China,M,South Africa,0,"Hadoop, Tableau, GCP, Java",Associate,5,Telecommunications,2024-02-21,2024-03-19,2347,6.6,Smart Analytics +AI08712,Robotics Engineer,54587,USD,54587,EX,FL,India,M,India,0,"Python, TensorFlow, Docker, Mathematics, Java",Bachelor,18,Automotive,2024-10-04,2024-12-03,1159,6.4,Quantum Computing Inc +AI08713,Data Scientist,248642,CHF,223778,EX,FT,Switzerland,M,Switzerland,0,"AWS, MLOps, Docker",Master,11,Technology,2024-07-27,2024-09-02,1616,8.6,Algorithmic Solutions +AI08714,AI Software Engineer,64401,USD,64401,EX,FL,China,S,China,50,"Deep Learning, Kubernetes, Tableau, Python",PhD,17,Finance,2025-03-28,2025-04-12,1565,7.8,DeepTech Ventures +AI08715,AI Product Manager,92513,USD,92513,SE,PT,Finland,S,Belgium,50,"Kubernetes, TensorFlow, SQL, Deep Learning, Hadoop",Associate,5,Transportation,2024-10-14,2024-11-26,1362,9.3,Advanced Robotics +AI08716,Robotics Engineer,238453,USD,238453,EX,FT,United States,M,United States,0,"Java, Python, TensorFlow",Associate,11,Media,2025-03-27,2025-05-16,1106,7.8,Machine Intelligence Group +AI08717,Data Engineer,99160,AUD,133866,MI,PT,Australia,M,Australia,50,"Java, Scala, Python",PhD,3,Media,2024-11-29,2025-01-25,2447,7.6,Advanced Robotics +AI08718,Data Scientist,248599,USD,248599,EX,PT,Finland,L,Finland,0,"SQL, PyTorch, Tableau, Docker",Bachelor,13,Finance,2024-05-12,2024-06-26,2240,6.5,TechCorp Inc +AI08719,NLP Engineer,236767,USD,236767,EX,CT,Ireland,M,Ireland,100,"GCP, NLP, AWS, SQL, Kubernetes",Associate,13,Transportation,2024-10-12,2024-12-03,1905,5,AI Innovations +AI08720,Deep Learning Engineer,110782,GBP,83087,MI,FL,United Kingdom,L,United Kingdom,0,"GCP, Data Visualization, Linux, Computer Vision, Kubernetes",Associate,2,Gaming,2024-11-09,2024-12-16,609,8.5,Cloud AI Solutions +AI08721,AI Research Scientist,302161,GBP,226621,EX,CT,United Kingdom,L,United Kingdom,100,"Mathematics, Java, Data Visualization, R",PhD,18,Energy,2025-04-05,2025-05-01,2008,9.9,DataVision Ltd +AI08722,AI Architect,146187,SGD,190043,EX,FL,Singapore,S,Thailand,0,"Kubernetes, GCP, MLOps, Statistics, Git",Associate,12,Technology,2025-01-10,2025-03-23,1238,9.7,Advanced Robotics +AI08723,AI Specialist,94634,EUR,80439,MI,CT,France,L,France,0,"R, Scala, Computer Vision, Mathematics, Python",Master,3,Media,2024-08-26,2024-10-05,712,6.2,Neural Networks Co +AI08724,AI Consultant,115988,USD,115988,SE,FL,Finland,M,Finland,50,"Hadoop, SQL, R, NLP, Scala",Associate,8,Retail,2025-01-16,2025-03-25,1191,5.4,Future Systems +AI08725,Autonomous Systems Engineer,192776,EUR,163860,EX,PT,Austria,L,Chile,100,"Computer Vision, Kubernetes, Mathematics",PhD,12,Retail,2025-04-22,2025-06-07,1757,7.2,DataVision Ltd +AI08726,ML Ops Engineer,33869,USD,33869,EN,PT,China,L,China,0,"Computer Vision, Git, Python, Spark",Master,1,Consulting,2024-02-10,2024-03-09,2019,7.9,Cognitive Computing +AI08727,AI Research Scientist,77360,JPY,8509600,EN,PT,Japan,M,Kenya,100,"SQL, Mathematics, MLOps, Statistics, Azure",PhD,0,Media,2025-01-18,2025-02-24,1156,8.5,TechCorp Inc +AI08728,Data Engineer,236119,JPY,25973090,EX,CT,Japan,L,Japan,50,"AWS, Python, TensorFlow, NLP",PhD,13,Consulting,2024-11-22,2024-12-14,602,5.4,Cloud AI Solutions +AI08729,Machine Learning Researcher,99743,USD,99743,EX,FT,China,M,China,100,"Hadoop, Python, Deep Learning, Linux, Mathematics",Master,17,Healthcare,2024-07-03,2024-07-26,1081,5.7,Quantum Computing Inc +AI08730,Data Scientist,92399,USD,92399,EN,FT,Denmark,S,Germany,0,"Spark, Python, MLOps",PhD,1,Education,2025-04-24,2025-06-25,1223,5.8,TechCorp Inc +AI08731,Computer Vision Engineer,110170,USD,110170,MI,CT,Sweden,M,India,100,"Linux, Docker, R, Git, AWS",PhD,4,Gaming,2025-01-06,2025-02-21,2429,7.4,DataVision Ltd +AI08732,Machine Learning Researcher,198925,USD,198925,EX,CT,Ireland,S,Nigeria,0,"Scala, R, SQL",Master,13,Gaming,2024-03-05,2024-05-09,1898,5.9,Algorithmic Solutions +AI08733,Data Engineer,170795,EUR,145176,EX,PT,Austria,M,Austria,50,"Java, SQL, GCP",PhD,17,Gaming,2025-04-29,2025-05-14,2240,8.1,Quantum Computing Inc +AI08734,Machine Learning Researcher,152232,EUR,129397,EX,FL,Netherlands,M,Netherlands,100,"Java, Hadoop, Tableau, Statistics, Spark",Master,19,Telecommunications,2024-12-19,2025-02-23,1989,7.5,AI Innovations +AI08735,AI Architect,308244,USD,308244,EX,FL,Norway,M,Portugal,0,"Spark, Java, PyTorch, Azure, Linux",Associate,10,Energy,2025-04-07,2025-05-19,1331,6.8,DeepTech Ventures +AI08736,AI Product Manager,58771,USD,58771,SE,CT,India,L,India,50,"Deep Learning, Hadoop, Computer Vision",PhD,7,Government,2024-02-05,2024-03-08,1849,6.6,Algorithmic Solutions +AI08737,Machine Learning Engineer,69542,EUR,59111,EN,CT,Netherlands,M,New Zealand,50,"Azure, Java, AWS, Python",Associate,1,Government,2024-06-04,2024-06-27,680,7.1,Advanced Robotics +AI08738,Principal Data Scientist,99141,USD,99141,MI,FL,Ireland,L,Hungary,50,"AWS, Linux, R, NLP, Docker",Bachelor,2,Government,2024-04-22,2024-05-07,1798,7.7,Autonomous Tech +AI08739,Machine Learning Engineer,115731,AUD,156237,MI,CT,Australia,L,Australia,0,"Git, Kubernetes, R, Spark, Deep Learning",PhD,4,Automotive,2025-02-24,2025-03-17,1199,8.8,AI Innovations +AI08740,AI Architect,73001,SGD,94901,EN,FL,Singapore,L,Singapore,50,"PyTorch, Scala, Docker",PhD,0,Technology,2024-06-13,2024-07-21,1492,9.9,Predictive Systems +AI08741,ML Ops Engineer,354384,USD,354384,EX,CT,Denmark,L,Portugal,100,"Deep Learning, Azure, Data Visualization",Associate,17,Media,2024-08-28,2024-09-28,1776,7.6,Machine Intelligence Group +AI08742,AI Software Engineer,89933,JPY,9892630,MI,PT,Japan,M,Japan,100,"Python, Docker, Azure, AWS",PhD,3,Telecommunications,2024-04-09,2024-04-25,1282,8.2,DeepTech Ventures +AI08743,AI Specialist,165985,JPY,18258350,EX,FL,Japan,L,Japan,0,"Git, Scala, Computer Vision, PyTorch",Associate,11,Real Estate,2024-07-31,2024-09-05,2297,8.6,Machine Intelligence Group +AI08744,Machine Learning Engineer,84231,EUR,71596,MI,PT,France,M,Philippines,100,"Scala, Kubernetes, R, Mathematics",Bachelor,4,Automotive,2024-11-24,2025-01-01,663,7.3,Cloud AI Solutions +AI08745,AI Research Scientist,123845,USD,123845,SE,CT,United States,S,New Zealand,50,"AWS, Deep Learning, Git, Docker, Azure",Bachelor,6,Transportation,2024-01-13,2024-02-15,686,6.2,Algorithmic Solutions +AI08746,Data Scientist,272008,USD,272008,EX,FL,Norway,S,Romania,100,"Python, Kubernetes, Tableau, Deep Learning, Docker",Bachelor,19,Retail,2024-09-07,2024-10-12,1953,9.3,Smart Analytics +AI08747,ML Ops Engineer,338395,USD,338395,EX,PT,United States,L,United States,50,"Linux, Python, Spark, Scala, Deep Learning",PhD,15,Technology,2025-03-16,2025-04-19,2070,6.4,Cognitive Computing +AI08748,AI Consultant,104347,EUR,88695,MI,FL,Germany,M,Netherlands,100,"Spark, Mathematics, Deep Learning, Computer Vision, AWS",Associate,4,Manufacturing,2024-02-18,2024-04-02,821,9.4,Machine Intelligence Group +AI08749,ML Ops Engineer,129907,JPY,14289770,SE,PT,Japan,S,Japan,100,"Data Visualization, Java, Tableau, TensorFlow, GCP",PhD,8,Real Estate,2024-12-04,2025-01-17,2013,5.7,Machine Intelligence Group +AI08750,Robotics Engineer,75071,EUR,63810,EN,CT,Austria,L,Austria,50,"Tableau, Mathematics, Python, TensorFlow, Deep Learning",PhD,1,Finance,2024-03-17,2024-05-28,2359,7.6,TechCorp Inc +AI08751,Data Scientist,89718,USD,89718,EN,FL,Ireland,L,Ireland,0,"SQL, Python, PyTorch",PhD,1,Healthcare,2024-12-28,2025-01-13,883,6.6,Predictive Systems +AI08752,Head of AI,123663,JPY,13602930,SE,CT,Japan,S,Japan,50,"Kubernetes, AWS, Statistics, Computer Vision",Associate,6,Education,2024-03-31,2024-05-07,522,6.3,DataVision Ltd +AI08753,AI Architect,232491,EUR,197617,EX,CT,France,M,France,50,"GCP, AWS, Hadoop, Tableau, Statistics",Bachelor,18,Healthcare,2024-03-27,2024-05-09,1496,9.3,Machine Intelligence Group +AI08754,Machine Learning Researcher,54167,USD,54167,SE,PT,India,L,Norway,0,"Git, Linux, Spark, Mathematics",Master,7,Education,2024-01-31,2024-03-30,2248,8.6,DataVision Ltd +AI08755,AI Product Manager,89079,CAD,111349,MI,CT,Canada,L,Canada,100,"MLOps, SQL, Python",Associate,2,Manufacturing,2024-08-25,2024-09-15,2460,6.6,Smart Analytics +AI08756,Data Scientist,194970,GBP,146228,EX,PT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, R, NLP, Deep Learning",Master,19,Government,2024-10-02,2024-10-16,961,8.8,Smart Analytics +AI08757,ML Ops Engineer,228547,USD,228547,EX,FL,Sweden,S,Sweden,0,"Tableau, Spark, GCP",PhD,13,Government,2025-01-10,2025-02-18,1740,7.2,Digital Transformation LLC +AI08758,Robotics Engineer,52055,USD,52055,SE,FL,India,L,India,50,"Linux, Hadoop, SQL",Bachelor,7,Automotive,2024-03-14,2024-04-05,2193,8.6,Advanced Robotics +AI08759,Head of AI,57328,USD,57328,EX,CT,India,M,India,50,"Python, R, Deep Learning, NLP, AWS",Associate,12,Education,2025-03-02,2025-03-31,1122,8.4,TechCorp Inc +AI08760,Autonomous Systems Engineer,52301,USD,52301,EN,PT,Sweden,S,Sweden,0,"Hadoop, Python, Kubernetes, Computer Vision, TensorFlow",Master,1,Telecommunications,2025-04-04,2025-04-23,1291,7.4,Cloud AI Solutions +AI08761,Robotics Engineer,23552,USD,23552,EN,PT,India,L,India,50,"Azure, Java, NLP, R, Deep Learning",PhD,0,Manufacturing,2025-03-20,2025-04-14,953,9.5,Quantum Computing Inc +AI08762,AI Product Manager,135585,EUR,115247,SE,FT,Netherlands,S,Netherlands,50,"Java, SQL, PyTorch, Deep Learning, Docker",Bachelor,8,Government,2024-10-09,2024-11-29,2293,6.8,Advanced Robotics +AI08763,AI Software Engineer,281620,USD,281620,EX,FT,Ireland,L,Ireland,50,"Git, Kubernetes, Scala, Spark, Computer Vision",Bachelor,13,Gaming,2024-06-15,2024-08-10,770,8.7,Digital Transformation LLC +AI08764,NLP Engineer,158612,SGD,206196,SE,CT,Singapore,M,Singapore,0,"Spark, Data Visualization, Java, MLOps, Linux",Master,5,Retail,2024-07-17,2024-09-15,836,6.9,Advanced Robotics +AI08765,AI Specialist,104480,USD,104480,MI,CT,Ireland,L,Ireland,100,"TensorFlow, Python, Tableau, SQL",PhD,4,Energy,2024-01-29,2024-04-03,734,8.8,Machine Intelligence Group +AI08766,Machine Learning Engineer,50599,EUR,43009,EN,FT,Germany,S,Romania,50,"Python, Hadoop, Data Visualization, Scala",Master,1,Government,2024-09-22,2024-11-07,857,5.1,Future Systems +AI08767,AI Consultant,74316,EUR,63169,MI,FT,Netherlands,S,Netherlands,100,"Linux, Tableau, SQL, Kubernetes",Master,3,Technology,2024-11-05,2024-12-04,763,5.8,Predictive Systems +AI08768,Robotics Engineer,91016,CAD,113770,MI,CT,Canada,L,Switzerland,50,"Hadoop, Spark, Deep Learning, Python",Associate,3,Transportation,2025-04-14,2025-05-10,1257,6.5,Cloud AI Solutions +AI08769,AI Product Manager,83508,USD,83508,MI,FT,Finland,L,Finland,50,"Linux, Git, PyTorch, Hadoop",Bachelor,3,Technology,2024-12-11,2025-01-29,725,7.6,Machine Intelligence Group +AI08770,AI Research Scientist,54579,USD,54579,EN,PT,Israel,S,Luxembourg,100,"Tableau, GCP, Git",Associate,0,Government,2025-04-01,2025-05-12,1489,6.9,Machine Intelligence Group +AI08771,NLP Engineer,147819,EUR,125646,EX,PT,Netherlands,S,Netherlands,50,"Data Visualization, PyTorch, Hadoop",Master,13,Automotive,2025-03-22,2025-04-10,1636,10,Future Systems +AI08772,Autonomous Systems Engineer,85094,USD,85094,MI,FT,Sweden,S,Finland,100,"Scala, Azure, Spark",Master,3,Consulting,2024-10-17,2024-12-04,801,7.3,Digital Transformation LLC +AI08773,AI Product Manager,18730,USD,18730,EN,CT,India,S,India,100,"Data Visualization, R, SQL",Associate,0,Real Estate,2024-08-01,2024-08-18,1893,6,Smart Analytics +AI08774,Deep Learning Engineer,89305,EUR,75909,MI,FT,Netherlands,S,South Korea,100,"AWS, Python, MLOps, TensorFlow, Hadoop",Master,3,Manufacturing,2024-04-16,2024-06-22,659,6.6,Smart Analytics +AI08775,Data Engineer,67597,USD,67597,MI,FT,South Korea,S,South Korea,100,"Deep Learning, Kubernetes, GCP",PhD,2,Telecommunications,2024-11-08,2025-01-03,1645,6.6,Future Systems +AI08776,NLP Engineer,67427,SGD,87655,EN,PT,Singapore,M,Singapore,0,"Linux, Mathematics, Hadoop",Master,0,Automotive,2024-04-20,2024-06-22,563,7.4,Autonomous Tech +AI08777,Machine Learning Engineer,80525,CAD,100656,MI,CT,Canada,S,Canada,0,"Mathematics, Kubernetes, SQL",PhD,3,Technology,2024-04-12,2024-06-24,533,8.2,Cloud AI Solutions +AI08778,Machine Learning Researcher,73119,USD,73119,EN,CT,Israel,M,Australia,100,"R, Kubernetes, Docker",Associate,0,Technology,2024-08-30,2024-11-11,2228,9.9,Smart Analytics +AI08779,Data Engineer,76899,USD,76899,EN,FT,Norway,L,Norway,50,"MLOps, NLP, Docker, Git",PhD,1,Finance,2024-03-06,2024-05-18,728,9.6,Machine Intelligence Group +AI08780,AI Specialist,71826,EUR,61052,EN,CT,Austria,M,Brazil,100,"Docker, Git, Hadoop, SQL, Computer Vision",Master,0,Transportation,2024-11-24,2024-12-20,1285,5.3,Quantum Computing Inc +AI08781,Autonomous Systems Engineer,101327,USD,101327,EN,PT,Norway,M,Norway,50,"Java, GCP, Python",Associate,1,Telecommunications,2024-11-18,2024-12-23,1879,6,Algorithmic Solutions +AI08782,Robotics Engineer,69083,USD,69083,MI,CT,Israel,M,Israel,100,"Python, Kubernetes, Docker",Master,2,Technology,2024-07-22,2024-08-08,1075,5.2,Algorithmic Solutions +AI08783,ML Ops Engineer,90930,EUR,77291,MI,PT,Austria,M,Austria,0,"Scala, TensorFlow, MLOps, Python",Master,2,Media,2024-09-10,2024-09-27,2010,7.2,DeepTech Ventures +AI08784,Autonomous Systems Engineer,124784,USD,124784,SE,PT,South Korea,M,Mexico,100,"Linux, Azure, Python",Bachelor,8,Media,2024-08-10,2024-10-12,632,5.8,DataVision Ltd +AI08785,Deep Learning Engineer,112554,USD,112554,MI,FT,Norway,M,Norway,50,"Python, Computer Vision, TensorFlow, Java, Hadoop",Master,4,Technology,2024-03-26,2024-04-17,644,7.1,Neural Networks Co +AI08786,AI Consultant,138859,EUR,118030,SE,FT,France,M,France,0,"NLP, Git, Azure, R, Python",Master,6,Retail,2024-03-25,2024-05-02,2136,7.2,Future Systems +AI08787,Data Scientist,155807,EUR,132436,EX,CT,France,L,Singapore,100,"AWS, R, Python, Git, Scala",PhD,18,Consulting,2024-11-14,2024-12-10,1084,6.8,Digital Transformation LLC +AI08788,Computer Vision Engineer,70709,EUR,60103,EN,CT,Germany,S,Canada,50,"TensorFlow, SQL, AWS",Master,1,Automotive,2024-05-10,2024-07-16,1987,8.1,Advanced Robotics +AI08789,NLP Engineer,20948,USD,20948,EN,FL,India,S,India,50,"Scala, Spark, Docker",Associate,1,Technology,2025-03-14,2025-05-08,505,9.5,Smart Analytics +AI08790,Head of AI,128719,EUR,109411,SE,PT,Netherlands,M,Turkey,100,"R, GCP, Python, Java, Mathematics",PhD,7,Energy,2024-06-13,2024-08-06,1872,9.6,Neural Networks Co +AI08791,AI Product Manager,73053,USD,73053,EN,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Azure",PhD,1,Telecommunications,2024-07-18,2024-08-03,1480,6.1,DataVision Ltd +AI08792,Research Scientist,127282,USD,127282,MI,PT,Denmark,S,Denmark,50,"Tableau, Spark, Python, Linux",PhD,4,Telecommunications,2024-07-24,2024-09-01,2464,8.9,DeepTech Ventures +AI08793,AI Product Manager,195816,SGD,254561,EX,FT,Singapore,S,Singapore,0,"Git, R, Deep Learning, Mathematics, Java",Master,13,Telecommunications,2024-01-03,2024-02-25,1036,6.2,Autonomous Tech +AI08794,NLP Engineer,169752,USD,169752,EX,CT,United States,M,United States,0,"MLOps, Java, Statistics, Data Visualization",Associate,14,Healthcare,2025-04-23,2025-06-24,956,5.7,Predictive Systems +AI08795,AI Consultant,105502,USD,105502,EX,FT,China,L,China,0,"SQL, Linux, Tableau, Computer Vision",Master,10,Transportation,2025-01-09,2025-02-24,1935,5.5,TechCorp Inc +AI08796,Data Engineer,112014,USD,112014,SE,PT,Ireland,S,Ireland,100,"TensorFlow, Scala, Python, Docker, R",Associate,6,Finance,2025-01-19,2025-03-09,1596,9.5,Machine Intelligence Group +AI08797,Machine Learning Engineer,247688,JPY,27245680,EX,FT,Japan,L,Japan,50,"PyTorch, SQL, Kubernetes, R",Master,18,Real Estate,2025-02-20,2025-05-03,1479,8.2,Autonomous Tech +AI08798,ML Ops Engineer,74961,EUR,63717,EN,PT,France,M,France,0,"TensorFlow, Data Visualization, Linux",PhD,1,Gaming,2024-10-24,2024-12-19,1666,6.3,Neural Networks Co +AI08799,ML Ops Engineer,115927,USD,115927,SE,PT,South Korea,L,Latvia,50,"Kubernetes, Data Visualization, PyTorch, GCP",PhD,8,Real Estate,2024-09-19,2024-10-10,2021,9.5,AI Innovations +AI08800,AI Consultant,60784,EUR,51666,EN,FT,France,S,France,50,"Tableau, NLP, Computer Vision, R",Master,0,Transportation,2025-04-01,2025-05-24,2418,5.9,Advanced Robotics +AI08801,Research Scientist,88808,EUR,75487,MI,FL,Germany,S,Germany,50,"GCP, PyTorch, Computer Vision",Master,2,Telecommunications,2025-04-04,2025-05-14,865,9.4,DeepTech Ventures +AI08802,AI Research Scientist,147363,EUR,125259,SE,CT,Austria,L,Austria,100,"Python, GCP, Computer Vision, TensorFlow, Azure",Associate,6,Manufacturing,2024-10-25,2025-01-02,651,8.3,Digital Transformation LLC +AI08803,AI Specialist,49188,USD,49188,EX,FT,India,S,India,100,"R, Azure, Linux, Computer Vision, Java",Associate,17,Healthcare,2024-07-25,2024-08-18,1743,9.3,Cloud AI Solutions +AI08804,Principal Data Scientist,159673,AUD,215559,EX,PT,Australia,M,Australia,0,"Hadoop, Linux, Java",PhD,18,Transportation,2025-03-01,2025-04-14,594,7.9,Future Systems +AI08805,AI Specialist,113403,EUR,96393,SE,CT,Germany,M,Germany,50,"Spark, Java, Tableau, Python, Statistics",Bachelor,7,Energy,2024-12-18,2025-03-01,2388,7.3,Smart Analytics +AI08806,Deep Learning Engineer,101965,USD,101965,MI,PT,Denmark,M,Denmark,0,"Scala, Python, Spark, Data Visualization",Bachelor,2,Media,2025-02-21,2025-03-26,1964,9.9,Advanced Robotics +AI08807,Head of AI,75727,USD,75727,MI,FL,Ireland,M,Ireland,50,"Data Visualization, Python, Deep Learning",Bachelor,4,Real Estate,2024-04-11,2024-06-07,2012,7.1,Machine Intelligence Group +AI08808,Principal Data Scientist,64011,EUR,54409,MI,CT,France,S,France,0,"R, Scala, NLP",PhD,2,Retail,2024-12-19,2025-01-03,528,5.5,AI Innovations +AI08809,Machine Learning Engineer,108796,JPY,11967560,MI,FL,Japan,L,Brazil,50,"R, Deep Learning, GCP, Computer Vision, Scala",Bachelor,4,Automotive,2024-06-13,2024-08-07,877,7.6,TechCorp Inc +AI08810,Robotics Engineer,235070,JPY,25857700,EX,CT,Japan,L,Japan,100,"Data Visualization, Scala, Linux, Python, Hadoop",Bachelor,11,Technology,2025-04-17,2025-05-07,1540,5.5,AI Innovations +AI08811,Data Engineer,180679,USD,180679,EX,FT,South Korea,M,Netherlands,100,"SQL, Linux, Java, Git",PhD,15,Healthcare,2024-03-17,2024-05-29,2493,8.8,Advanced Robotics +AI08812,Robotics Engineer,151818,EUR,129045,EX,FL,Germany,S,Thailand,0,"SQL, Java, R",PhD,19,Technology,2024-12-21,2025-01-19,887,7.9,Digital Transformation LLC +AI08813,Autonomous Systems Engineer,106856,USD,106856,MI,CT,Israel,L,Portugal,0,"Statistics, R, Tableau",PhD,4,Consulting,2024-02-27,2024-04-09,1290,6.3,Cloud AI Solutions +AI08814,Robotics Engineer,108490,JPY,11933900,MI,PT,Japan,M,Mexico,100,"Azure, Python, Deep Learning",PhD,2,Education,2024-04-06,2024-04-22,1077,6,Smart Analytics +AI08815,ML Ops Engineer,71874,EUR,61093,MI,CT,France,M,France,0,"Kubernetes, Python, SQL, MLOps, Statistics",PhD,3,Real Estate,2024-09-18,2024-11-30,1725,5.5,Quantum Computing Inc +AI08816,AI Consultant,202910,EUR,172474,EX,FL,France,S,Hungary,50,"PyTorch, Tableau, TensorFlow, Computer Vision",Bachelor,19,Real Estate,2025-01-26,2025-03-15,1807,8.3,DataVision Ltd +AI08817,AI Product Manager,118893,EUR,101059,SE,FL,Austria,L,Australia,50,"Deep Learning, Linux, GCP, Mathematics",Master,9,Retail,2024-03-16,2024-04-03,718,5.9,Digital Transformation LLC +AI08818,Data Analyst,90747,USD,90747,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Java, Git",Associate,4,Technology,2024-12-17,2025-02-23,1975,7.1,Digital Transformation LLC +AI08819,AI Software Engineer,55913,USD,55913,EN,FT,Ireland,M,Estonia,50,"Tableau, Spark, PyTorch, SQL, Data Visualization",Master,0,Consulting,2024-01-27,2024-02-27,936,5.8,Future Systems +AI08820,Data Scientist,321130,CHF,289017,EX,PT,Switzerland,S,Finland,100,"AWS, Docker, MLOps, SQL, Kubernetes",Bachelor,16,Telecommunications,2024-01-31,2024-04-03,572,9.1,Cognitive Computing +AI08821,Data Scientist,48284,USD,48284,EN,CT,Finland,S,Finland,50,"Python, Git, Linux, AWS",Master,0,Education,2024-04-26,2024-06-29,1758,7,DataVision Ltd +AI08822,Machine Learning Engineer,93069,USD,93069,EN,PT,Denmark,L,Denmark,0,"Data Visualization, Mathematics, Python, NLP",Bachelor,1,Education,2025-03-20,2025-05-22,1265,9.3,DataVision Ltd +AI08823,AI Architect,154216,USD,154216,SE,CT,Norway,L,Norway,0,"Scala, Git, Mathematics, Spark",Bachelor,5,Finance,2024-09-08,2024-11-01,652,8.7,TechCorp Inc +AI08824,Autonomous Systems Engineer,212745,AUD,287206,EX,PT,Australia,M,Australia,50,"NLP, Data Visualization, Docker, Python, Spark",PhD,10,Automotive,2025-03-11,2025-04-22,1584,9,Cloud AI Solutions +AI08825,ML Ops Engineer,148725,AUD,200779,EX,FT,Australia,M,Australia,50,"Computer Vision, Docker, TensorFlow",PhD,16,Automotive,2025-04-25,2025-05-30,1977,5.7,Predictive Systems +AI08826,Deep Learning Engineer,214868,AUD,290072,EX,CT,Australia,S,South Africa,100,"SQL, Computer Vision, Java, Mathematics, AWS",Master,17,Consulting,2024-12-07,2025-01-17,613,6.9,Neural Networks Co +AI08827,AI Consultant,48192,USD,48192,EN,CT,Sweden,S,Luxembourg,100,"SQL, TensorFlow, Git",Associate,0,Manufacturing,2024-02-11,2024-03-09,1626,7.6,Digital Transformation LLC +AI08828,Autonomous Systems Engineer,53715,USD,53715,EN,FT,Israel,S,Israel,50,"Python, TensorFlow, Linux, AWS, R",Associate,1,Education,2024-07-18,2024-08-02,1454,6.6,AI Innovations +AI08829,Data Engineer,79419,EUR,67506,MI,FL,Netherlands,S,Chile,100,"Python, Java, Computer Vision, AWS",PhD,3,Retail,2024-03-22,2024-05-07,2420,9.3,Quantum Computing Inc +AI08830,ML Ops Engineer,189251,EUR,160863,EX,FL,Austria,M,Austria,100,"Kubernetes, Computer Vision, Python, GCP, Statistics",Bachelor,12,Energy,2024-07-28,2024-08-22,1299,8.1,Cognitive Computing +AI08831,AI Product Manager,82862,USD,82862,MI,FT,United States,S,United States,50,"Tableau, Spark, Python",PhD,2,Technology,2024-03-14,2024-04-21,1366,9.2,TechCorp Inc +AI08832,Research Scientist,312798,CHF,281518,EX,CT,Switzerland,S,Portugal,100,"PyTorch, Mathematics, Deep Learning, TensorFlow",Associate,12,Retail,2024-06-06,2024-06-27,1963,5.8,Cloud AI Solutions +AI08833,ML Ops Engineer,104615,CHF,94154,EN,FL,Switzerland,L,United States,0,"Linux, Spark, Git, SQL, Hadoop",Master,0,Media,2024-06-22,2024-07-29,2231,9.5,Smart Analytics +AI08834,Deep Learning Engineer,42852,USD,42852,MI,FL,China,L,China,50,"R, Java, Azure, Deep Learning, AWS",Bachelor,2,Automotive,2024-05-03,2024-07-04,934,6.3,Smart Analytics +AI08835,Principal Data Scientist,83129,CAD,103911,MI,FT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Linux",Bachelor,3,Real Estate,2024-04-15,2024-05-03,810,5.5,Digital Transformation LLC +AI08836,Robotics Engineer,64763,SGD,84192,EN,PT,Singapore,S,Singapore,50,"R, SQL, Deep Learning",PhD,0,Government,2024-04-30,2024-07-10,1126,9.1,Neural Networks Co +AI08837,Data Scientist,140525,SGD,182683,SE,PT,Singapore,L,China,0,"Docker, Spark, Python, AWS",Associate,6,Automotive,2024-05-15,2024-07-25,816,8.2,TechCorp Inc +AI08838,AI Software Engineer,164731,AUD,222387,SE,FT,Australia,L,Australia,0,"Linux, PyTorch, Data Visualization, SQL",Bachelor,8,Automotive,2024-11-18,2024-12-17,1758,6.2,DataVision Ltd +AI08839,Machine Learning Researcher,58860,USD,58860,MI,CT,China,L,China,100,"Python, R, TensorFlow",PhD,4,Transportation,2024-10-13,2024-12-15,1321,9.7,Cloud AI Solutions +AI08840,AI Specialist,117441,USD,117441,MI,CT,Norway,M,Norway,100,"Mathematics, Kubernetes, NLP, Computer Vision, Linux",Master,4,Automotive,2025-03-10,2025-05-04,1794,8.9,DataVision Ltd +AI08841,Computer Vision Engineer,72350,EUR,61498,EN,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, PyTorch, Tableau",Bachelor,1,Energy,2024-06-22,2024-07-12,504,6.1,TechCorp Inc +AI08842,Deep Learning Engineer,92337,AUD,124655,SE,PT,Australia,S,South Africa,100,"AWS, Spark, Computer Vision, Docker, Mathematics",Bachelor,7,Healthcare,2024-07-16,2024-08-26,1201,5.5,Advanced Robotics +AI08843,Autonomous Systems Engineer,53864,EUR,45784,EN,CT,Austria,M,Mexico,0,"Deep Learning, Hadoop, Linux",PhD,0,Transportation,2024-10-12,2024-12-11,2012,7.7,Machine Intelligence Group +AI08844,AI Architect,33665,USD,33665,MI,CT,India,L,India,0,"Mathematics, Kubernetes, Docker, Scala",Associate,4,Finance,2024-03-13,2024-04-13,1806,9.4,Advanced Robotics +AI08845,Machine Learning Researcher,182110,EUR,154794,EX,PT,France,M,France,50,"Python, Git, Tableau, NLP",Associate,13,Energy,2025-03-18,2025-04-08,1774,9.6,Future Systems +AI08846,Head of AI,115234,SGD,149804,MI,FL,Singapore,L,Singapore,0,"Kubernetes, Computer Vision, Azure",Master,4,Energy,2024-01-16,2024-02-03,2189,8.7,Neural Networks Co +AI08847,Data Analyst,163943,SGD,213126,EX,FL,Singapore,M,Singapore,100,"MLOps, Linux, NLP",PhD,12,Energy,2024-04-04,2024-06-05,843,8,DeepTech Ventures +AI08848,Autonomous Systems Engineer,153511,JPY,16886210,SE,PT,Japan,M,Argentina,50,"Spark, Git, Python, TensorFlow",PhD,9,Education,2024-12-30,2025-02-12,1650,6.8,DataVision Ltd +AI08849,NLP Engineer,110442,SGD,143575,MI,FT,Singapore,L,Singapore,100,"Spark, Python, TensorFlow, R",Master,4,Healthcare,2025-03-17,2025-05-20,894,5.7,TechCorp Inc +AI08850,Research Scientist,136904,USD,136904,EX,FL,Israel,M,Israel,0,"Spark, Linux, Kubernetes",Master,14,Technology,2024-10-31,2024-12-17,2225,9.7,Future Systems +AI08851,ML Ops Engineer,83201,USD,83201,EN,FT,Finland,L,Thailand,50,"Hadoop, NLP, Python",Master,1,Real Estate,2025-02-21,2025-03-27,543,7.2,Predictive Systems +AI08852,Robotics Engineer,134018,CAD,167523,SE,PT,Canada,L,Thailand,50,"Python, Java, Data Visualization",Associate,6,Media,2024-01-08,2024-03-14,889,6.6,Predictive Systems +AI08853,Principal Data Scientist,88509,EUR,75233,MI,PT,France,M,France,100,"PyTorch, R, Computer Vision, Scala",Associate,2,Healthcare,2024-01-14,2024-03-05,2308,8.5,Digital Transformation LLC +AI08854,Research Scientist,126724,USD,126724,MI,PT,Denmark,L,Denmark,100,"Git, Python, TensorFlow, PyTorch",PhD,2,Technology,2024-05-19,2024-06-12,1390,7.3,Future Systems +AI08855,Principal Data Scientist,281410,EUR,239199,EX,FL,Netherlands,L,Egypt,0,"Statistics, Mathematics, NLP, Docker, Computer Vision",Master,15,Government,2024-04-19,2024-05-12,1403,5.5,Digital Transformation LLC +AI08856,Head of AI,162401,CAD,203001,EX,PT,Canada,M,Ghana,0,"PyTorch, Mathematics, MLOps, TensorFlow, NLP",Associate,17,Healthcare,2025-04-20,2025-06-18,1233,7.2,Autonomous Tech +AI08857,Machine Learning Engineer,180046,CHF,162041,SE,FT,Switzerland,M,Ghana,0,"Statistics, R, Java",Associate,8,Consulting,2024-07-23,2024-09-21,740,6.3,Neural Networks Co +AI08858,Data Scientist,73927,USD,73927,MI,CT,Sweden,S,Mexico,0,"Hadoop, MLOps, Linux, Spark, Git",Associate,2,Healthcare,2024-07-31,2024-09-05,2041,5.5,TechCorp Inc +AI08859,Data Engineer,109990,EUR,93492,MI,FL,Germany,M,United States,50,"Python, Java, Hadoop, Statistics, Computer Vision",Master,3,Real Estate,2024-06-28,2024-08-22,2199,5.8,Machine Intelligence Group +AI08860,Data Scientist,126474,USD,126474,SE,CT,Israel,L,Russia,100,"Tableau, Java, Kubernetes",Master,6,Consulting,2025-02-20,2025-04-07,1834,5.9,AI Innovations +AI08861,AI Research Scientist,160685,EUR,136582,EX,PT,Netherlands,M,Netherlands,0,"R, GCP, Git, Spark",PhD,13,Media,2024-05-28,2024-06-13,2083,6,Machine Intelligence Group +AI08862,Deep Learning Engineer,317312,CHF,285581,EX,CT,Switzerland,S,United Kingdom,50,"Git, R, GCP, Kubernetes, Java",Bachelor,16,Technology,2024-09-15,2024-11-12,1711,7.7,Advanced Robotics +AI08863,AI Consultant,85129,USD,85129,EN,PT,Denmark,L,Denmark,0,"NLP, PyTorch, TensorFlow",Bachelor,0,Energy,2024-09-29,2024-12-06,1340,8.8,Quantum Computing Inc +AI08864,AI Consultant,162063,USD,162063,EX,FL,Finland,L,Poland,50,"Deep Learning, Docker, AWS, SQL",Bachelor,16,Gaming,2024-05-05,2024-06-11,1974,8.3,Machine Intelligence Group +AI08865,Computer Vision Engineer,50185,USD,50185,EN,CT,Finland,M,India,50,"AWS, R, Deep Learning",Master,1,Education,2024-06-16,2024-07-02,1048,7.8,AI Innovations +AI08866,Autonomous Systems Engineer,212146,EUR,180324,EX,FT,Austria,L,Austria,50,"Java, TensorFlow, Mathematics, Tableau",Master,12,Technology,2025-03-07,2025-04-18,1448,5.2,DataVision Ltd +AI08867,AI Specialist,205751,JPY,22632610,EX,PT,Japan,M,Norway,50,"TensorFlow, Azure, Scala",Associate,19,Education,2024-04-13,2024-05-12,1542,7.7,DataVision Ltd +AI08868,AI Software Engineer,144178,USD,144178,SE,CT,Sweden,L,Indonesia,50,"PyTorch, GCP, Spark",Associate,5,Energy,2024-01-24,2024-02-18,2406,5.2,Quantum Computing Inc +AI08869,Machine Learning Researcher,154217,CHF,138795,SE,CT,Switzerland,M,Switzerland,0,"Scala, Computer Vision, Kubernetes, Deep Learning, Docker",Master,5,Gaming,2024-10-30,2024-12-09,2011,8.5,Cognitive Computing +AI08870,Data Analyst,118300,USD,118300,SE,FL,Israel,L,Israel,0,"Statistics, MLOps, Spark, Computer Vision, TensorFlow",Associate,6,Retail,2024-03-22,2024-04-14,1823,6.4,Cognitive Computing +AI08871,Data Analyst,164623,USD,164623,SE,CT,Norway,L,Norway,0,"Python, SQL, Computer Vision, Mathematics, TensorFlow",Master,5,Education,2024-12-11,2025-01-19,2283,7.2,Advanced Robotics +AI08872,Data Engineer,209872,USD,209872,EX,PT,Denmark,M,Denmark,0,"Kubernetes, Azure, Tableau, R, NLP",PhD,12,Energy,2025-04-03,2025-05-14,1604,9.2,Quantum Computing Inc +AI08873,Deep Learning Engineer,140537,EUR,119456,SE,CT,France,L,France,100,"Linux, MLOps, TensorFlow, PyTorch, Mathematics",Master,6,Finance,2024-06-08,2024-07-29,1729,5.8,Neural Networks Co +AI08874,Principal Data Scientist,72674,USD,72674,MI,FT,Israel,S,Vietnam,0,"Linux, Java, SQL, Kubernetes, PyTorch",PhD,2,Consulting,2025-04-10,2025-06-22,1258,7.7,TechCorp Inc +AI08875,AI Product Manager,96117,EUR,81699,MI,FT,France,L,Australia,100,"Linux, Java, Scala",Master,2,Education,2025-04-21,2025-06-20,1684,7.7,AI Innovations +AI08876,Data Scientist,132251,EUR,112413,SE,FL,Netherlands,L,Canada,0,"SQL, Kubernetes, Azure, Computer Vision",Master,7,Gaming,2024-08-03,2024-08-22,1336,9.3,Advanced Robotics +AI08877,Robotics Engineer,180163,SGD,234212,SE,PT,Singapore,L,Singapore,100,"Kubernetes, SQL, Linux",Associate,9,Technology,2024-09-26,2024-10-14,2472,6,Machine Intelligence Group +AI08878,AI Software Engineer,64220,GBP,48165,EN,FL,United Kingdom,S,United Kingdom,0,"Data Visualization, Azure, NLP",Associate,0,Media,2024-10-13,2024-11-25,947,8.6,Digital Transformation LLC +AI08879,Computer Vision Engineer,70080,AUD,94608,EN,CT,Australia,L,Australia,0,"Scala, PyTorch, TensorFlow, Tableau, Deep Learning",PhD,1,Real Estate,2025-01-18,2025-03-27,2308,8.5,Algorithmic Solutions +AI08880,Head of AI,72201,USD,72201,MI,PT,Finland,M,Israel,50,"NLP, Deep Learning, MLOps, PyTorch",PhD,3,Manufacturing,2025-03-31,2025-04-16,1516,9.5,Advanced Robotics +AI08881,AI Research Scientist,150170,CAD,187713,EX,FL,Canada,S,Canada,50,"Computer Vision, Java, TensorFlow",PhD,11,Government,2025-02-27,2025-03-29,2288,9,Digital Transformation LLC +AI08882,NLP Engineer,68586,USD,68586,EN,FL,Sweden,M,Estonia,50,"Deep Learning, Spark, GCP",Bachelor,1,Telecommunications,2024-03-21,2024-04-21,2215,9.5,Future Systems +AI08883,AI Specialist,58484,EUR,49711,EN,PT,France,L,France,0,"Docker, Python, Spark, Hadoop",Master,1,Automotive,2024-01-31,2024-04-01,1875,5.3,AI Innovations +AI08884,Data Analyst,53494,USD,53494,EN,FL,South Korea,S,South Korea,0,"MLOps, Docker, Linux, Computer Vision",Master,0,Telecommunications,2024-09-20,2024-11-04,1820,9.5,Smart Analytics +AI08885,AI Software Engineer,175512,USD,175512,SE,FL,Norway,L,Norway,0,"Linux, Computer Vision, PyTorch, Azure, TensorFlow",Associate,7,Automotive,2025-02-11,2025-03-26,2244,9.9,Cloud AI Solutions +AI08886,AI Product Manager,124719,USD,124719,MI,PT,Norway,M,Argentina,100,"Python, Kubernetes, PyTorch",Associate,2,Automotive,2025-01-27,2025-02-27,2326,6.6,Autonomous Tech +AI08887,Machine Learning Researcher,65569,USD,65569,EN,CT,Israel,S,Israel,0,"AWS, Tableau, Mathematics",Bachelor,0,Gaming,2025-02-14,2025-03-04,2433,6.3,AI Innovations +AI08888,AI Software Engineer,184461,USD,184461,EX,CT,Denmark,M,Israel,0,"Python, R, Data Visualization",Associate,13,Education,2024-06-25,2024-08-11,2438,5.9,Neural Networks Co +AI08889,AI Software Engineer,176661,CHF,158995,SE,FL,Switzerland,L,Finland,0,"PyTorch, Mathematics, AWS, Azure, Deep Learning",Associate,8,Media,2024-04-15,2024-05-08,1040,6.3,Algorithmic Solutions +AI08890,Research Scientist,113468,GBP,85101,MI,FT,United Kingdom,L,United Kingdom,50,"Python, Computer Vision, Statistics, Tableau",Associate,3,Transportation,2024-11-24,2025-01-22,1859,7.7,Cognitive Computing +AI08891,Robotics Engineer,94278,EUR,80136,MI,FL,France,M,Belgium,50,"Git, Kubernetes, Computer Vision, Python",PhD,3,Automotive,2024-07-25,2024-08-31,2395,8.6,Quantum Computing Inc +AI08892,AI Research Scientist,124121,EUR,105503,MI,FT,Netherlands,L,Netherlands,0,"Git, PyTorch, TensorFlow",PhD,3,Manufacturing,2025-01-15,2025-02-07,1523,5.8,Smart Analytics +AI08893,ML Ops Engineer,118336,EUR,100586,SE,FL,Netherlands,S,Netherlands,0,"Computer Vision, Git, Docker, Azure, TensorFlow",Bachelor,7,Manufacturing,2024-07-04,2024-08-11,1467,6.5,Algorithmic Solutions +AI08894,AI Consultant,63446,JPY,6979060,EN,CT,Japan,M,Japan,100,"PyTorch, Docker, GCP",Associate,1,Education,2024-08-14,2024-09-07,2327,8.5,Smart Analytics +AI08895,Data Analyst,88302,GBP,66227,MI,CT,United Kingdom,M,United Kingdom,100,"SQL, Git, Docker, Deep Learning",Master,4,Energy,2025-04-18,2025-05-12,1494,7.8,Smart Analytics +AI08896,Data Engineer,69937,CAD,87421,EN,CT,Canada,L,South Korea,0,"Tableau, Git, Java, NLP, Mathematics",PhD,1,Healthcare,2024-07-08,2024-09-03,1246,6.4,Cloud AI Solutions +AI08897,Data Scientist,76500,USD,76500,MI,PT,South Korea,S,South Korea,50,"Python, Kubernetes, Azure",Associate,3,Manufacturing,2025-03-21,2025-05-09,1141,5.4,TechCorp Inc +AI08898,Data Analyst,133991,USD,133991,MI,PT,Denmark,L,Spain,100,"Deep Learning, SQL, TensorFlow, Computer Vision",PhD,2,Automotive,2025-02-27,2025-04-30,1018,7.6,DeepTech Ventures +AI08899,Research Scientist,37472,USD,37472,EN,CT,China,M,China,0,"SQL, Mathematics, Docker, Python, Linux",Master,1,Media,2024-07-30,2024-08-23,597,7.8,Neural Networks Co +AI08900,NLP Engineer,55334,GBP,41501,EN,PT,United Kingdom,S,United Kingdom,50,"SQL, Docker, Hadoop, GCP, Azure",Master,0,Retail,2024-11-01,2024-12-28,1928,8.9,Digital Transformation LLC +AI08901,Data Engineer,118965,CHF,107069,MI,FT,Switzerland,M,Switzerland,0,"SQL, Scala, PyTorch, TensorFlow",Master,4,Finance,2024-11-08,2024-12-10,1082,5.3,TechCorp Inc +AI08902,ML Ops Engineer,59325,EUR,50426,EN,PT,France,M,France,0,"Data Visualization, Git, Computer Vision",Bachelor,0,Retail,2024-03-24,2024-04-26,2308,8.2,DataVision Ltd +AI08903,AI Research Scientist,79037,EUR,67181,MI,FT,Austria,M,United Kingdom,0,"Tableau, R, Deep Learning, Computer Vision, Azure",PhD,3,Healthcare,2025-03-29,2025-05-20,566,8.8,Digital Transformation LLC +AI08904,Computer Vision Engineer,149385,EUR,126977,EX,FT,Austria,L,Belgium,50,"Python, TensorFlow, Git, Spark",Bachelor,15,Real Estate,2024-06-18,2024-07-05,586,6.5,Neural Networks Co +AI08905,AI Product Manager,76318,EUR,64870,MI,CT,Austria,M,Austria,100,"Python, Computer Vision, Linux",PhD,2,Government,2024-03-15,2024-05-03,1441,6.9,DeepTech Ventures +AI08906,Research Scientist,189385,AUD,255670,EX,FT,Australia,M,Australia,50,"Hadoop, GCP, Tableau, Java, Azure",Master,18,Transportation,2024-04-17,2024-05-05,1029,6.1,Cognitive Computing +AI08907,Autonomous Systems Engineer,130219,EUR,110686,SE,CT,Germany,M,Germany,100,"Python, SQL, Java",PhD,9,Government,2024-09-01,2024-11-04,1562,5.4,Smart Analytics +AI08908,NLP Engineer,150596,JPY,16565560,EX,CT,Japan,S,Japan,0,"TensorFlow, Hadoop, SQL, Scala, Python",Associate,16,Education,2024-03-14,2024-05-07,1265,8.4,Digital Transformation LLC +AI08909,Head of AI,144363,USD,144363,EX,PT,Sweden,S,Kenya,0,"Mathematics, Deep Learning, R, SQL, Linux",Master,14,Media,2024-05-19,2024-06-29,1823,7.6,Digital Transformation LLC +AI08910,AI Software Engineer,21072,USD,21072,EN,FT,India,L,India,100,"Kubernetes, GCP, NLP, MLOps",Bachelor,1,Technology,2024-12-15,2025-01-26,905,6.9,Future Systems +AI08911,ML Ops Engineer,186827,USD,186827,EX,FT,Israel,S,Israel,0,"Java, TensorFlow, NLP, Mathematics, PyTorch",Associate,14,Retail,2024-05-12,2024-06-03,1583,6.1,Machine Intelligence Group +AI08912,Principal Data Scientist,143167,USD,143167,SE,PT,South Korea,L,South Korea,100,"PyTorch, Python, NLP",Associate,9,Education,2025-01-19,2025-02-13,1955,8.8,Quantum Computing Inc +AI08913,ML Ops Engineer,128988,USD,128988,SE,CT,Israel,M,Estonia,100,"PyTorch, Data Visualization, Linux, MLOps",PhD,6,Government,2024-09-08,2024-11-01,960,6.1,Quantum Computing Inc +AI08914,Deep Learning Engineer,276188,EUR,234760,EX,FL,Germany,L,Germany,50,"GCP, Git, Data Visualization",Associate,13,Finance,2024-08-23,2024-10-28,1647,8.1,Digital Transformation LLC +AI08915,Autonomous Systems Engineer,41148,USD,41148,MI,PT,India,L,Portugal,100,"SQL, Hadoop, PyTorch, Docker, Git",Master,2,Consulting,2024-10-21,2024-12-28,2149,9.3,TechCorp Inc +AI08916,AI Consultant,79365,USD,79365,EX,FT,India,M,Czech Republic,0,"Data Visualization, Git, R",Master,10,Media,2025-03-02,2025-05-09,2308,5.8,TechCorp Inc +AI08917,Data Scientist,60786,USD,60786,EX,FL,India,M,India,100,"TensorFlow, PyTorch, Linux, Statistics",PhD,17,Manufacturing,2024-06-09,2024-07-14,1544,9.1,Cloud AI Solutions +AI08918,ML Ops Engineer,85296,USD,85296,MI,CT,Finland,S,India,100,"Deep Learning, Data Visualization, Python, Hadoop",PhD,3,Finance,2024-11-10,2024-12-17,2034,7.6,Future Systems +AI08919,Computer Vision Engineer,111246,SGD,144620,MI,FT,Singapore,L,Singapore,50,"Docker, Java, Data Visualization, Azure",Master,2,Consulting,2024-12-09,2025-01-03,1316,9.1,Cognitive Computing +AI08920,Robotics Engineer,89925,USD,89925,MI,PT,Ireland,L,Ireland,100,"Tableau, MLOps, Kubernetes, Hadoop, Computer Vision",PhD,2,Gaming,2024-12-27,2025-01-10,2334,6.3,AI Innovations +AI08921,Computer Vision Engineer,90696,USD,90696,MI,PT,United States,M,Israel,100,"Deep Learning, Statistics, Git, Kubernetes, NLP",Associate,2,Media,2024-08-23,2024-09-27,2447,6.3,Smart Analytics +AI08922,Robotics Engineer,131512,AUD,177541,SE,PT,Australia,S,Australia,0,"PyTorch, Scala, Spark, Deep Learning, Azure",Associate,8,Technology,2024-07-25,2024-09-13,1710,9.6,Cloud AI Solutions +AI08923,AI Product Manager,198409,AUD,267852,EX,CT,Australia,S,Australia,50,"PyTorch, GCP, MLOps, Spark",PhD,15,Healthcare,2025-04-26,2025-06-15,710,9.5,Autonomous Tech +AI08924,Data Analyst,157473,USD,157473,SE,FT,Sweden,L,Sweden,0,"Deep Learning, Tableau, R, NLP",Master,6,Finance,2024-10-24,2024-12-04,1694,7.5,Algorithmic Solutions +AI08925,NLP Engineer,126003,EUR,107103,SE,FL,France,M,France,0,"Java, Statistics, Spark, Computer Vision, TensorFlow",Bachelor,7,Energy,2024-08-04,2024-09-21,703,5.6,DeepTech Ventures +AI08926,AI Research Scientist,119850,USD,119850,SE,FT,South Korea,M,South Korea,0,"MLOps, Linux, Scala",Associate,5,Education,2024-03-29,2024-05-03,2346,9.8,DataVision Ltd +AI08927,AI Specialist,95591,CHF,86032,EN,FL,Switzerland,M,Ireland,100,"TensorFlow, PyTorch, Docker",Bachelor,1,Healthcare,2024-05-18,2024-06-03,618,8.3,TechCorp Inc +AI08928,Data Scientist,73865,GBP,55399,EN,PT,United Kingdom,M,United Kingdom,100,"Java, R, Kubernetes, Git",PhD,0,Transportation,2024-06-13,2024-07-26,2249,5.5,DeepTech Ventures +AI08929,Principal Data Scientist,71155,GBP,53366,EN,CT,United Kingdom,S,United Kingdom,0,"Java, PyTorch, NLP",PhD,0,Education,2025-01-05,2025-01-21,2184,8.6,DeepTech Ventures +AI08930,Robotics Engineer,69945,SGD,90929,MI,FL,Singapore,S,Singapore,50,"Scala, Kubernetes, Docker, Java",Associate,2,Real Estate,2024-08-15,2024-10-07,1353,9.3,Cognitive Computing +AI08931,Computer Vision Engineer,24897,USD,24897,EN,CT,China,M,China,100,"GCP, Azure, AWS",Master,0,Manufacturing,2025-04-01,2025-05-01,1147,5.1,DataVision Ltd +AI08932,Research Scientist,67162,AUD,90669,EN,FL,Australia,L,Australia,100,"Scala, Statistics, Java",Associate,0,Government,2024-08-29,2024-10-24,1973,9.2,Cloud AI Solutions +AI08933,Principal Data Scientist,57928,GBP,43446,EN,PT,United Kingdom,S,United Kingdom,50,"Java, Git, Python",PhD,1,Manufacturing,2024-02-27,2024-04-21,526,7.1,Machine Intelligence Group +AI08934,Autonomous Systems Engineer,153211,CHF,137890,MI,PT,Switzerland,M,Switzerland,50,"TensorFlow, Linux, Mathematics, Kubernetes",Bachelor,4,Transportation,2024-04-30,2024-06-21,891,8.8,Future Systems +AI08935,AI Software Engineer,111274,USD,111274,MI,CT,Denmark,S,Denmark,100,"AWS, Hadoop, Scala",Associate,2,Automotive,2024-09-20,2024-11-19,2435,8.2,Smart Analytics +AI08936,AI Specialist,119212,USD,119212,SE,CT,Israel,M,Kenya,50,"Kubernetes, Azure, Scala, SQL",Associate,5,Telecommunications,2025-03-24,2025-05-03,952,5.4,Neural Networks Co +AI08937,AI Software Engineer,167862,USD,167862,EX,FL,Israel,S,Israel,50,"Mathematics, Spark, NLP, R, Python",Bachelor,15,Automotive,2024-05-17,2024-06-03,622,9.8,Neural Networks Co +AI08938,AI Research Scientist,73151,EUR,62178,MI,PT,Germany,M,Finland,100,"Deep Learning, SQL, PyTorch, AWS",Master,4,Retail,2024-10-06,2024-10-26,1228,9.5,Cloud AI Solutions +AI08939,Research Scientist,159226,CHF,143303,MI,FT,Switzerland,L,China,0,"Linux, MLOps, Data Visualization",Master,4,Gaming,2024-05-26,2024-07-29,794,8.2,Future Systems +AI08940,AI Software Engineer,62380,USD,62380,EN,PT,Ireland,M,Romania,0,"Scala, Kubernetes, SQL, MLOps, Spark",PhD,1,Healthcare,2025-03-02,2025-03-28,1960,6.9,AI Innovations +AI08941,AI Product Manager,113996,JPY,12539560,SE,FL,Japan,M,Japan,50,"AWS, Linux, Java, Hadoop",Master,9,Consulting,2025-01-10,2025-03-06,2463,8.9,DeepTech Ventures +AI08942,NLP Engineer,51094,USD,51094,EN,CT,Ireland,M,Ireland,0,"NLP, MLOps, Statistics",Bachelor,1,Gaming,2025-04-21,2025-05-29,2239,9,TechCorp Inc +AI08943,AI Specialist,69394,USD,69394,EN,FT,Israel,L,Israel,100,"Kubernetes, Python, MLOps, Azure",PhD,1,Automotive,2025-01-08,2025-02-09,571,5.3,Future Systems +AI08944,AI Specialist,105999,CHF,95399,EN,PT,Switzerland,L,Ghana,50,"R, GCP, Hadoop, Kubernetes",Master,0,Consulting,2024-12-04,2025-02-09,1844,8,DeepTech Ventures +AI08945,ML Ops Engineer,99978,EUR,84981,SE,CT,Austria,M,Italy,0,"Kubernetes, NLP, Git, Mathematics, Hadoop",Associate,8,Energy,2025-04-29,2025-05-26,2222,8.3,DeepTech Ventures +AI08946,Data Scientist,52184,USD,52184,EN,FL,South Korea,L,South Korea,50,"SQL, Hadoop, GCP",Bachelor,0,Retail,2024-05-22,2024-06-15,1923,8.4,Digital Transformation LLC +AI08947,Data Scientist,76210,EUR,64779,MI,FL,Germany,M,Germany,50,"Java, Kubernetes, Data Visualization, NLP",PhD,2,Transportation,2024-02-02,2024-03-29,977,5.7,Predictive Systems +AI08948,AI Product Manager,67505,USD,67505,MI,FT,Israel,S,Israel,0,"PyTorch, TensorFlow, Data Visualization, Kubernetes, AWS",Bachelor,4,Consulting,2024-11-02,2024-12-17,1324,9.8,Digital Transformation LLC +AI08949,Robotics Engineer,70420,USD,70420,MI,PT,Israel,S,India,100,"Python, Scala, MLOps, AWS, NLP",PhD,4,Manufacturing,2025-01-22,2025-03-06,1191,8,Machine Intelligence Group +AI08950,AI Consultant,23683,USD,23683,EN,CT,India,L,India,50,"R, Kubernetes, Git",Master,0,Education,2024-08-04,2024-10-12,1085,8.9,Quantum Computing Inc +AI08951,Computer Vision Engineer,120220,USD,120220,MI,PT,United States,M,United States,0,"Python, Scala, Computer Vision, SQL",PhD,3,Telecommunications,2024-09-26,2024-12-01,785,5.1,Advanced Robotics +AI08952,AI Software Engineer,185311,USD,185311,EX,PT,Finland,M,Finland,50,"Hadoop, GCP, NLP, AWS, Tableau",PhD,15,Gaming,2024-09-07,2024-10-11,1773,8.5,Smart Analytics +AI08953,Robotics Engineer,140225,EUR,119191,SE,CT,Netherlands,S,Netherlands,0,"SQL, Kubernetes, Mathematics, Linux, Deep Learning",Associate,6,Real Estate,2024-04-23,2024-06-01,755,8,TechCorp Inc +AI08954,AI Specialist,126983,USD,126983,SE,FL,Israel,L,Israel,0,"Kubernetes, SQL, PyTorch, Git",PhD,9,Telecommunications,2024-12-09,2025-02-12,2196,5.3,AI Innovations +AI08955,Head of AI,198792,USD,198792,EX,FL,Finland,L,Thailand,50,"Git, PyTorch, R",Associate,11,Manufacturing,2024-05-09,2024-07-02,1864,8.1,Autonomous Tech +AI08956,AI Consultant,84341,EUR,71690,MI,FL,Austria,L,Austria,50,"Spark, Hadoop, Azure, Tableau",Bachelor,3,Finance,2024-09-29,2024-12-05,1673,6.8,Advanced Robotics +AI08957,Principal Data Scientist,59341,EUR,50440,EN,FT,Netherlands,M,Netherlands,50,"MLOps, Java, R",Associate,1,Healthcare,2024-04-22,2024-06-02,2363,7.2,Digital Transformation LLC +AI08958,Machine Learning Engineer,26028,USD,26028,MI,FT,India,M,India,0,"R, MLOps, SQL",Bachelor,3,Finance,2024-01-06,2024-02-17,991,6.9,TechCorp Inc +AI08959,AI Architect,146559,JPY,16121490,SE,PT,Japan,L,Denmark,100,"Azure, Hadoop, Python",Bachelor,9,Real Estate,2025-04-18,2025-05-11,550,9.9,Future Systems +AI08960,NLP Engineer,258425,USD,258425,EX,FT,Denmark,M,Mexico,100,"SQL, Deep Learning, AWS, Kubernetes, Mathematics",Master,12,Education,2024-07-28,2024-08-17,964,8.4,Neural Networks Co +AI08961,AI Research Scientist,158120,EUR,134402,SE,FT,Netherlands,L,South Korea,50,"Data Visualization, PyTorch, Kubernetes, Statistics",PhD,7,Real Estate,2024-09-22,2024-11-04,953,7.7,Algorithmic Solutions +AI08962,AI Specialist,77719,USD,77719,EN,CT,United States,M,United States,0,"Azure, Spark, Tableau, NLP",Master,0,Media,2024-07-29,2024-08-27,2030,6.2,Cognitive Computing +AI08963,AI Specialist,28039,USD,28039,EN,PT,China,S,China,0,"AWS, Tableau, Computer Vision, Hadoop, NLP",Master,0,Automotive,2024-08-24,2024-10-09,636,8.7,TechCorp Inc +AI08964,Robotics Engineer,96472,SGD,125414,MI,FT,Singapore,M,Ireland,50,"Python, SQL, GCP",Master,2,Government,2024-06-12,2024-07-20,724,8,Cloud AI Solutions +AI08965,Principal Data Scientist,89844,USD,89844,SE,PT,South Korea,M,Singapore,0,"Computer Vision, Hadoop, AWS, Scala, Spark",Bachelor,5,Finance,2024-02-05,2024-04-16,1977,7.1,Quantum Computing Inc +AI08966,AI Research Scientist,79472,SGD,103314,EN,PT,Singapore,L,Nigeria,0,"Scala, Kubernetes, MLOps, NLP, Mathematics",Bachelor,0,Gaming,2025-02-12,2025-02-28,1571,7,Predictive Systems +AI08967,AI Product Manager,92695,USD,92695,MI,PT,South Korea,L,South Korea,100,"Python, Docker, GCP, TensorFlow",Master,3,Government,2025-04-29,2025-06-19,802,5.6,Quantum Computing Inc +AI08968,NLP Engineer,105477,JPY,11602470,MI,PT,Japan,M,South Africa,0,"Spark, Deep Learning, Mathematics",PhD,2,Finance,2025-03-28,2025-04-16,1334,5.1,Algorithmic Solutions +AI08969,AI Consultant,59744,USD,59744,EN,FT,Finland,S,Finland,100,"Mathematics, Data Visualization, PyTorch, MLOps",Master,0,Consulting,2025-01-11,2025-03-23,1224,6.8,Neural Networks Co +AI08970,NLP Engineer,75054,JPY,8255940,EN,PT,Japan,M,Israel,0,"Data Visualization, Git, R, Scala",Master,0,Technology,2024-01-07,2024-01-26,1701,6.7,Smart Analytics +AI08971,AI Product Manager,75503,USD,75503,MI,FT,South Korea,M,South Korea,100,"Scala, Java, Data Visualization, Git",Associate,4,Education,2024-10-01,2024-10-25,1856,5.5,Cognitive Computing +AI08972,AI Specialist,86929,USD,86929,MI,FT,Israel,L,Israel,100,"R, Deep Learning, Spark",PhD,4,Technology,2024-03-16,2024-04-11,918,8.8,Predictive Systems +AI08973,Data Scientist,80667,EUR,68567,MI,FL,France,L,France,0,"TensorFlow, AWS, Statistics, Mathematics, Spark",Bachelor,4,Real Estate,2024-09-17,2024-10-20,1916,5.3,Predictive Systems +AI08974,Robotics Engineer,142450,USD,142450,EX,FT,South Korea,S,South Korea,50,"R, Scala, Python",Master,11,Education,2025-01-19,2025-03-27,2181,9,DataVision Ltd +AI08975,AI Software Engineer,145577,USD,145577,EX,FL,Ireland,S,Ireland,50,"Scala, Tableau, Spark, Statistics",Bachelor,11,Telecommunications,2024-07-19,2024-08-19,1784,7.6,Machine Intelligence Group +AI08976,Principal Data Scientist,138782,CHF,124904,MI,FT,Switzerland,L,Switzerland,100,"PyTorch, Git, GCP",Associate,2,Government,2024-04-10,2024-06-14,1512,5.7,Digital Transformation LLC +AI08977,Data Scientist,148776,AUD,200848,SE,FL,Australia,M,Australia,100,"R, Tableau, Python, Statistics",PhD,8,Gaming,2025-01-15,2025-03-21,1573,9.5,DeepTech Ventures +AI08978,Data Engineer,150654,USD,150654,MI,PT,Norway,L,Thailand,100,"AWS, Computer Vision, Data Visualization, R",Bachelor,4,Consulting,2024-02-29,2024-03-27,760,7.4,Advanced Robotics +AI08979,AI Consultant,262984,USD,262984,EX,CT,Ireland,L,Ireland,0,"Linux, Java, Spark, Scala, Computer Vision",Bachelor,11,Transportation,2024-12-06,2025-01-22,2032,5.7,Neural Networks Co +AI08980,AI Specialist,82698,GBP,62024,MI,CT,United Kingdom,S,United Kingdom,50,"Docker, Data Visualization, Spark",Master,2,Consulting,2025-03-22,2025-05-04,1128,5.7,Neural Networks Co +AI08981,Robotics Engineer,78355,GBP,58766,MI,FT,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, Statistics, Computer Vision",Master,3,Automotive,2024-02-22,2024-04-23,1032,7,Machine Intelligence Group +AI08982,AI Product Manager,83880,EUR,71298,MI,FL,France,L,France,100,"Hadoop, PyTorch, Tableau, TensorFlow, NLP",PhD,2,Technology,2024-08-08,2024-09-19,1316,9.3,Cloud AI Solutions +AI08983,Data Analyst,67262,GBP,50447,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Scala, R",Master,0,Automotive,2024-06-07,2024-07-05,1330,7.3,Predictive Systems +AI08984,Computer Vision Engineer,65253,USD,65253,SE,FT,China,M,China,0,"NLP, TensorFlow, Spark",Bachelor,5,Consulting,2025-03-22,2025-05-21,882,7.4,AI Innovations +AI08985,ML Ops Engineer,100727,USD,100727,SE,PT,Israel,S,Israel,0,"Tableau, TensorFlow, GCP, Statistics",Master,5,Automotive,2024-01-23,2024-02-23,2081,6,Cloud AI Solutions +AI08986,Principal Data Scientist,201256,CAD,251570,EX,CT,Canada,S,Italy,0,"Azure, Python, Computer Vision",Master,17,Media,2025-03-15,2025-05-14,999,6.2,DataVision Ltd +AI08987,Deep Learning Engineer,98333,CHF,88500,EN,CT,Switzerland,S,Poland,100,"GCP, R, SQL, Statistics, Data Visualization",Bachelor,1,Healthcare,2024-10-04,2024-10-27,1743,6.8,Cognitive Computing +AI08988,AI Product Manager,238048,GBP,178536,EX,CT,United Kingdom,S,Switzerland,100,"Scala, R, Computer Vision, Kubernetes",PhD,19,Automotive,2024-11-09,2024-12-01,696,8,Algorithmic Solutions +AI08989,Computer Vision Engineer,111723,USD,111723,SE,PT,South Korea,S,Ukraine,0,"R, Statistics, Computer Vision, GCP",PhD,6,Transportation,2024-06-15,2024-08-23,909,9.7,Autonomous Tech +AI08990,ML Ops Engineer,62271,EUR,52930,EN,FL,Germany,S,Germany,50,"Linux, R, Git, Hadoop, Docker",Associate,0,Manufacturing,2024-08-25,2024-11-02,1742,7.1,TechCorp Inc +AI08991,Machine Learning Researcher,186844,CAD,233555,EX,FL,Canada,L,Canada,100,"Kubernetes, Statistics, Mathematics, Linux, Java",Associate,18,Retail,2024-08-26,2024-10-11,1541,9.1,Machine Intelligence Group +AI08992,AI Software Engineer,151803,USD,151803,SE,FL,United States,S,United States,0,"Computer Vision, Data Visualization, R, NLP, Deep Learning",Master,9,Manufacturing,2024-07-07,2024-07-25,2344,8,Neural Networks Co +AI08993,AI Product Manager,86780,USD,86780,MI,FL,Norway,S,Estonia,50,"Kubernetes, NLP, SQL",Associate,3,Telecommunications,2024-05-26,2024-06-22,2178,9,Quantum Computing Inc +AI08994,Deep Learning Engineer,92335,USD,92335,EN,FT,Ireland,L,Ireland,100,"AWS, Kubernetes, SQL, Scala",Bachelor,0,Retail,2024-09-08,2024-10-31,1318,8,Algorithmic Solutions +AI08995,Data Analyst,79908,USD,79908,MI,CT,South Korea,L,South Korea,100,"Hadoop, GCP, Computer Vision, Mathematics",Master,4,Technology,2024-06-21,2024-07-17,597,5.5,Autonomous Tech +AI08996,AI Consultant,139660,USD,139660,MI,CT,Denmark,L,Denmark,100,"Deep Learning, Python, MLOps",Master,4,Government,2025-02-01,2025-04-13,2451,6.1,Cognitive Computing +AI08997,Head of AI,55908,CAD,69885,EN,FL,Canada,S,Canada,50,"Linux, SQL, MLOps, Mathematics, Spark",PhD,0,Technology,2025-01-31,2025-03-22,1148,6.3,Cognitive Computing +AI08998,Data Engineer,88659,EUR,75360,MI,CT,Austria,L,Austria,100,"AWS, R, NLP, Data Visualization, Tableau",Bachelor,4,Telecommunications,2024-03-05,2024-04-16,2403,7.5,Neural Networks Co +AI08999,Machine Learning Engineer,205613,USD,205613,SE,PT,Norway,L,Australia,100,"Deep Learning, TensorFlow, R",Bachelor,8,Real Estate,2024-10-01,2024-11-06,1407,5.6,Digital Transformation LLC +AI09000,AI Software Engineer,90371,EUR,76815,EN,FT,Germany,L,Germany,100,"Kubernetes, Java, Mathematics, Scala, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-12-06,1818,7.1,DeepTech Ventures +AI09001,Data Analyst,88134,USD,88134,EN,FT,Sweden,L,Sweden,100,"Hadoop, Git, Computer Vision",Associate,0,Automotive,2025-02-11,2025-03-15,587,7.3,Autonomous Tech +AI09002,Computer Vision Engineer,42049,USD,42049,EN,FT,South Korea,M,South Korea,50,"TensorFlow, Statistics, SQL, Git",Associate,1,Government,2024-08-30,2024-11-05,2280,9.8,Cognitive Computing +AI09003,AI Consultant,53035,USD,53035,SE,PT,India,M,India,50,"SQL, Computer Vision, Tableau",PhD,8,Media,2024-03-28,2024-06-01,2121,9.3,Advanced Robotics +AI09004,Autonomous Systems Engineer,24765,USD,24765,EN,FL,India,S,India,100,"Docker, Python, Mathematics, Kubernetes",PhD,1,Energy,2024-12-11,2024-12-28,1299,10,Quantum Computing Inc +AI09005,Data Analyst,162474,USD,162474,SE,FT,Denmark,S,Colombia,100,"Computer Vision, R, Scala",Master,5,Transportation,2024-04-30,2024-06-30,1769,6.3,Predictive Systems +AI09006,Computer Vision Engineer,156947,USD,156947,EX,FT,Finland,M,Finland,100,"Mathematics, AWS, Deep Learning, Computer Vision",PhD,15,Transportation,2024-07-29,2024-10-05,820,7.6,Neural Networks Co +AI09007,Deep Learning Engineer,174776,USD,174776,EX,CT,Ireland,M,Ireland,50,"Computer Vision, GCP, Scala, Linux, PyTorch",Master,13,Real Estate,2024-08-16,2024-09-27,652,6.6,Future Systems +AI09008,AI Architect,70304,USD,70304,MI,FT,South Korea,L,South Korea,0,"Java, AWS, Tableau",Associate,3,Technology,2024-09-26,2024-11-04,610,9.5,Quantum Computing Inc +AI09009,ML Ops Engineer,172841,USD,172841,EX,PT,Israel,S,Israel,100,"Spark, PyTorch, Git",Master,16,Government,2024-06-24,2024-08-07,2356,8.7,Autonomous Tech +AI09010,AI Software Engineer,130736,EUR,111126,SE,FL,Austria,L,Austria,100,"Spark, R, Hadoop, Statistics, SQL",Master,6,Education,2024-04-28,2024-06-21,1538,9.1,Machine Intelligence Group +AI09011,AI Research Scientist,250854,EUR,213226,EX,PT,Austria,L,Austria,0,"Deep Learning, Kubernetes, Python, Git",PhD,17,Manufacturing,2025-03-10,2025-04-15,2094,6.8,TechCorp Inc +AI09012,AI Consultant,143001,SGD,185901,SE,PT,Singapore,L,Singapore,100,"MLOps, Java, Python, Computer Vision, Docker",Master,7,Healthcare,2024-02-08,2024-03-15,935,6.8,Future Systems +AI09013,AI Product Manager,248777,USD,248777,EX,FL,Sweden,M,Sweden,100,"Tableau, PyTorch, Docker, GCP, TensorFlow",Associate,11,Finance,2024-03-09,2024-04-05,1927,9.3,Future Systems +AI09014,AI Software Engineer,287219,SGD,373385,EX,FL,Singapore,L,Netherlands,50,"AWS, Scala, Mathematics, GCP, Docker",Bachelor,11,Transportation,2024-03-18,2024-05-26,1759,5.1,Autonomous Tech +AI09015,NLP Engineer,116645,USD,116645,MI,CT,Norway,S,Norway,100,"NLP, SQL, Tableau, AWS",Associate,2,Telecommunications,2024-09-28,2024-11-28,1035,10,Future Systems +AI09016,AI Product Manager,52061,USD,52061,EN,FL,South Korea,L,South Korea,100,"Computer Vision, SQL, Kubernetes, Git",PhD,0,Gaming,2024-05-10,2024-07-21,1489,7.8,Cloud AI Solutions +AI09017,AI Architect,104358,EUR,88704,SE,PT,France,S,Philippines,100,"Linux, R, Spark",Associate,5,Media,2024-12-07,2025-02-14,2437,6.8,DeepTech Ventures +AI09018,Machine Learning Engineer,64123,USD,64123,SE,PT,China,S,United States,50,"Computer Vision, Spark, Tableau",Master,7,Real Estate,2024-06-28,2024-08-14,715,7.3,Advanced Robotics +AI09019,AI Specialist,149941,USD,149941,SE,FT,Sweden,L,Ukraine,100,"Hadoop, SQL, TensorFlow, Spark",PhD,6,Gaming,2024-11-13,2024-12-14,1278,5.6,TechCorp Inc +AI09020,Deep Learning Engineer,56400,CAD,70500,EN,FL,Canada,M,Canada,50,"Tableau, NLP, PyTorch, Kubernetes",PhD,0,Technology,2024-01-08,2024-03-12,1632,8.3,DataVision Ltd +AI09021,AI Research Scientist,95750,USD,95750,SE,CT,Ireland,S,Thailand,0,"Docker, Python, Kubernetes, MLOps, Mathematics",Bachelor,6,Real Estate,2024-12-21,2025-01-08,2016,9.2,Predictive Systems +AI09022,AI Research Scientist,64039,EUR,54433,EN,FL,Germany,M,Germany,100,"SQL, Deep Learning, Git, PyTorch",PhD,0,Government,2025-03-24,2025-05-01,778,7.7,Cognitive Computing +AI09023,Data Engineer,56110,EUR,47694,EN,FL,Germany,M,Ireland,50,"Azure, Tableau, TensorFlow, Data Visualization, Deep Learning",PhD,1,Telecommunications,2024-12-23,2025-02-01,1111,7,Future Systems +AI09024,AI Specialist,124462,USD,124462,MI,PT,Denmark,S,Denmark,50,"NLP, AWS, Computer Vision, Python",Associate,4,Energy,2025-03-29,2025-05-26,1940,7.4,Neural Networks Co +AI09025,AI Consultant,190189,EUR,161661,EX,PT,Austria,M,Brazil,50,"Scala, Hadoop, Java, Linux",Master,11,Government,2024-02-21,2024-03-29,1380,9.4,Neural Networks Co +AI09026,AI Research Scientist,110339,USD,110339,SE,FL,United States,S,United States,100,"Kubernetes, PyTorch, TensorFlow, Python",Associate,9,Retail,2024-08-29,2024-10-12,1207,6.2,Quantum Computing Inc +AI09027,Data Engineer,198685,USD,198685,EX,CT,Israel,M,Israel,0,"MLOps, TensorFlow, Kubernetes",PhD,18,Retail,2024-09-11,2024-10-07,2290,8.6,Algorithmic Solutions +AI09028,Robotics Engineer,118424,USD,118424,MI,CT,United States,M,Egypt,100,"Statistics, NLP, Deep Learning",Master,4,Healthcare,2024-04-11,2024-05-28,1308,9.3,TechCorp Inc +AI09029,Research Scientist,77664,CHF,69898,EN,PT,Switzerland,M,Canada,50,"Azure, Spark, Python, MLOps, Computer Vision",Associate,0,Consulting,2024-09-09,2024-11-21,2200,5.3,Future Systems +AI09030,Research Scientist,60040,USD,60040,EN,FL,Israel,M,Israel,0,"Docker, Python, Azure, Hadoop, Deep Learning",Master,1,Education,2024-12-03,2025-01-08,1776,6.9,Machine Intelligence Group +AI09031,NLP Engineer,79791,USD,79791,EN,FL,Denmark,L,Denmark,100,"TensorFlow, Java, Scala, Statistics",Associate,0,Retail,2024-11-20,2024-12-10,1808,9.2,DeepTech Ventures +AI09032,AI Product Manager,124008,USD,124008,MI,FT,Denmark,L,Denmark,50,"GCP, Java, TensorFlow, Deep Learning, Computer Vision",Associate,2,Gaming,2024-02-13,2024-04-16,741,7.2,Cognitive Computing +AI09033,AI Consultant,35031,USD,35031,MI,FT,India,S,India,50,"Java, Mathematics, Deep Learning, Data Visualization, TensorFlow",Associate,4,Energy,2024-12-23,2025-02-18,699,7.6,AI Innovations +AI09034,Head of AI,67240,USD,67240,EN,FL,Norway,S,Norway,0,"AWS, Scala, Data Visualization",Bachelor,0,Education,2024-06-23,2024-08-27,1817,9.8,Quantum Computing Inc +AI09035,AI Specialist,94732,USD,94732,SE,PT,South Korea,M,South Korea,100,"Statistics, R, Deep Learning",PhD,8,Energy,2024-05-05,2024-05-21,1209,9.9,Advanced Robotics +AI09036,Autonomous Systems Engineer,129130,CHF,116217,MI,FT,Switzerland,L,Belgium,0,"Kubernetes, Java, AWS, Azure",Associate,3,Energy,2025-03-16,2025-05-07,1250,5.6,DataVision Ltd +AI09037,Data Analyst,228742,EUR,194431,EX,CT,Austria,L,Chile,50,"PyTorch, SQL, Java",PhD,19,Transportation,2025-04-19,2025-05-31,1839,5.5,DataVision Ltd +AI09038,Machine Learning Engineer,96859,SGD,125917,MI,FL,Singapore,M,Singapore,100,"Kubernetes, SQL, Deep Learning, Hadoop, PyTorch",Master,4,Education,2024-08-17,2024-10-14,2037,9,Machine Intelligence Group +AI09039,AI Software Engineer,86548,JPY,9520280,EN,FL,Japan,L,Japan,0,"TensorFlow, Spark, NLP, PyTorch, Data Visualization",Associate,1,Education,2024-04-29,2024-05-30,2115,5.4,DataVision Ltd +AI09040,Deep Learning Engineer,145427,EUR,123613,SE,CT,France,L,France,0,"Git, Spark, Computer Vision",Associate,9,Telecommunications,2024-01-10,2024-01-30,1730,7.9,AI Innovations +AI09041,Head of AI,144726,USD,144726,SE,FL,South Korea,L,South Korea,0,"Computer Vision, AWS, Docker, PyTorch, Hadoop",Associate,7,Healthcare,2024-04-17,2024-06-28,2490,6.8,Neural Networks Co +AI09042,Data Scientist,118275,USD,118275,MI,FL,Finland,L,France,100,"R, Linux, Computer Vision",Master,2,Real Estate,2024-09-11,2024-11-04,556,7.7,Algorithmic Solutions +AI09043,Head of AI,90563,CHF,81507,EN,FL,Switzerland,L,Switzerland,100,"Git, Linux, AWS, Statistics, Hadoop",Bachelor,0,Healthcare,2024-09-14,2024-11-16,1631,7.9,Quantum Computing Inc +AI09044,Head of AI,107754,USD,107754,SE,PT,South Korea,S,South Korea,100,"Python, Scala, Linux",Master,9,Energy,2024-08-20,2024-09-20,1052,8.4,Cognitive Computing +AI09045,AI Research Scientist,63613,USD,63613,EN,FT,Sweden,S,Sweden,50,"Linux, PyTorch, TensorFlow",Bachelor,1,Finance,2024-04-23,2024-06-13,2070,5.3,Neural Networks Co +AI09046,Research Scientist,185435,USD,185435,EX,CT,Ireland,M,Canada,0,"Spark, Docker, Python",Bachelor,15,Technology,2024-09-11,2024-10-08,1991,8.2,Advanced Robotics +AI09047,Autonomous Systems Engineer,46410,USD,46410,SE,PT,India,M,India,0,"Scala, Spark, Git, Azure",Associate,9,Energy,2024-08-19,2024-09-09,1622,6.3,Smart Analytics +AI09048,ML Ops Engineer,143416,USD,143416,EX,PT,Sweden,S,Sweden,100,"MLOps, R, Computer Vision",PhD,18,Real Estate,2024-11-09,2024-12-08,2151,5.3,Digital Transformation LLC +AI09049,AI Consultant,76825,USD,76825,EN,CT,Norway,S,Norway,100,"Computer Vision, R, SQL, Linux, Docker",Associate,0,Real Estate,2024-04-05,2024-06-02,1986,5.8,Digital Transformation LLC +AI09050,NLP Engineer,198466,CHF,178619,SE,FL,Switzerland,M,Switzerland,0,"SQL, Tableau, Computer Vision, MLOps",Bachelor,7,Government,2024-04-26,2024-07-05,716,9.7,Future Systems +AI09051,Data Analyst,130066,CHF,117059,MI,CT,Switzerland,S,Switzerland,50,"Mathematics, Hadoop, Python",Master,2,Education,2024-06-02,2024-07-05,916,7.7,Advanced Robotics +AI09052,AI Specialist,112733,EUR,95823,MI,FL,Germany,L,Germany,50,"AWS, Git, PyTorch",PhD,4,Government,2024-03-13,2024-05-14,2111,6.3,Quantum Computing Inc +AI09053,Data Scientist,46914,USD,46914,EN,PT,Finland,S,United States,100,"Python, Linux, Spark, Deep Learning",Master,1,Finance,2024-02-26,2024-03-27,2063,5.8,Smart Analytics +AI09054,AI Specialist,275297,USD,275297,EX,FL,Israel,L,Vietnam,50,"Tableau, Python, Kubernetes, Computer Vision",Associate,19,Transportation,2025-01-22,2025-04-03,2364,7.2,Cloud AI Solutions +AI09055,AI Product Manager,161001,GBP,120751,EX,PT,United Kingdom,S,United Kingdom,50,"Deep Learning, Azure, Kubernetes, Java, SQL",Bachelor,10,Technology,2024-03-16,2024-04-11,1985,9.6,Algorithmic Solutions +AI09056,Data Analyst,73717,SGD,95832,EN,PT,Singapore,M,Ukraine,0,"Python, Hadoop, Data Visualization",Master,0,Government,2025-03-05,2025-03-22,2321,8.3,Cognitive Computing +AI09057,Data Engineer,173430,AUD,234131,EX,FL,Australia,S,Indonesia,100,"Azure, Spark, Computer Vision",Associate,16,Media,2024-11-01,2024-12-24,1601,6.3,TechCorp Inc +AI09058,Data Analyst,289418,USD,289418,EX,FT,Sweden,L,Sweden,50,"Hadoop, Spark, TensorFlow, Linux",Associate,10,Healthcare,2024-07-13,2024-08-25,1193,5.4,AI Innovations +AI09059,Autonomous Systems Engineer,25689,USD,25689,MI,FL,India,M,India,0,"Scala, GCP, Tableau, Kubernetes, Java",Associate,4,Automotive,2024-05-19,2024-06-18,1208,9.6,TechCorp Inc +AI09060,Data Engineer,60503,USD,60503,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, Computer Vision, R, SQL",PhD,1,Transportation,2024-02-25,2024-03-17,2322,9.1,DataVision Ltd +AI09061,AI Architect,278853,USD,278853,EX,PT,Sweden,L,Sweden,50,"Python, Tableau, SQL",Associate,16,Manufacturing,2025-03-05,2025-05-04,1316,9.2,Machine Intelligence Group +AI09062,NLP Engineer,84797,EUR,72077,MI,CT,France,L,France,50,"TensorFlow, Python, Hadoop, Kubernetes",Bachelor,4,Real Estate,2025-04-08,2025-05-29,1787,5.1,TechCorp Inc +AI09063,Data Engineer,112505,EUR,95629,SE,FT,France,S,France,50,"Data Visualization, Scala, AWS, TensorFlow, Kubernetes",Associate,5,Healthcare,2024-05-19,2024-06-28,2296,6.5,DeepTech Ventures +AI09064,Autonomous Systems Engineer,322176,USD,322176,EX,FL,United States,L,United States,100,"Python, Hadoop, SQL",PhD,19,Finance,2024-09-04,2024-09-23,2234,9.4,Smart Analytics +AI09065,Machine Learning Engineer,153151,USD,153151,SE,PT,Sweden,L,Sweden,100,"SQL, Spark, MLOps, Data Visualization",Associate,9,Manufacturing,2024-08-26,2024-10-02,2125,7.7,Advanced Robotics +AI09066,AI Software Engineer,89864,USD,89864,EN,CT,Norway,L,Hungary,100,"Python, Docker, Tableau, AWS",PhD,0,Technology,2025-04-02,2025-04-19,2399,9.8,Digital Transformation LLC +AI09067,Data Scientist,103238,SGD,134209,MI,PT,Singapore,M,Japan,100,"Azure, Statistics, Hadoop, R",Master,3,Consulting,2025-01-26,2025-04-06,924,5.3,Autonomous Tech +AI09068,AI Specialist,62237,USD,62237,MI,FT,South Korea,S,Hungary,100,"Statistics, Tableau, SQL, Spark, Data Visualization",Master,4,Energy,2025-03-10,2025-04-13,1059,9.5,Autonomous Tech +AI09069,ML Ops Engineer,250692,EUR,213088,EX,FL,Netherlands,M,Netherlands,50,"Linux, GCP, Python, Mathematics, Azure",PhD,11,Healthcare,2024-12-11,2024-12-28,1030,8,Machine Intelligence Group +AI09070,ML Ops Engineer,75599,USD,75599,MI,PT,Ireland,M,South Africa,0,"Java, Kubernetes, Mathematics, SQL",Master,2,Consulting,2024-05-01,2024-07-12,1978,8.9,Advanced Robotics +AI09071,AI Product Manager,170126,CHF,153113,SE,FT,Switzerland,M,Switzerland,0,"Data Visualization, Statistics, NLP, MLOps",Associate,9,Healthcare,2024-03-14,2024-05-15,1405,5.6,Digital Transformation LLC +AI09072,Machine Learning Engineer,112438,EUR,95572,MI,CT,France,L,France,100,"Python, Statistics, AWS, Kubernetes, NLP",Master,4,Government,2024-04-26,2024-06-06,1829,9.3,DataVision Ltd +AI09073,AI Specialist,202327,USD,202327,EX,PT,Israel,M,Israel,0,"PyTorch, Linux, R",Associate,17,Retail,2024-05-20,2024-06-24,520,7.9,Quantum Computing Inc +AI09074,Head of AI,49609,EUR,42168,EN,CT,France,S,France,100,"Python, Java, NLP",Associate,1,Retail,2024-01-11,2024-03-08,1480,6.9,Machine Intelligence Group +AI09075,Data Analyst,101267,USD,101267,EX,FL,South Korea,S,Indonesia,100,"GCP, Azure, NLP, SQL, R",Bachelor,12,Retail,2024-05-01,2024-06-13,1534,8.8,DataVision Ltd +AI09076,Data Engineer,175412,EUR,149100,EX,FT,Germany,S,Germany,100,"Statistics, MLOps, Java",Associate,17,Manufacturing,2025-03-25,2025-05-04,2138,7.7,Cloud AI Solutions +AI09077,Robotics Engineer,132763,SGD,172592,SE,CT,Singapore,S,Singapore,50,"Hadoop, Tableau, R, Deep Learning",Associate,6,Manufacturing,2024-03-19,2024-05-10,1912,7.5,DeepTech Ventures +AI09078,Head of AI,146012,EUR,124110,EX,CT,Austria,S,United States,50,"Tableau, Linux, Java, R",Master,19,Retail,2025-02-15,2025-04-14,955,9.4,TechCorp Inc +AI09079,AI Architect,128830,USD,128830,SE,PT,Finland,S,Finland,0,"Python, TensorFlow, GCP, Java",Bachelor,9,Consulting,2024-01-15,2024-03-10,2249,6.9,AI Innovations +AI09080,Data Analyst,73935,EUR,62845,MI,PT,Germany,S,Germany,50,"PyTorch, Scala, MLOps",Master,2,Technology,2024-09-13,2024-11-07,1797,8.9,Cognitive Computing +AI09081,Machine Learning Researcher,20704,USD,20704,EN,FL,India,S,India,100,"Hadoop, Linux, GCP, Statistics",Master,0,Education,2024-02-22,2024-03-18,1935,5.9,Digital Transformation LLC +AI09082,AI Software Engineer,106038,USD,106038,EN,PT,United States,L,United States,50,"Spark, R, Deep Learning",Bachelor,1,Telecommunications,2024-03-24,2024-04-15,1621,5.5,Smart Analytics +AI09083,Machine Learning Researcher,256638,USD,256638,EX,FT,United States,L,United States,0,"Docker, Scala, Statistics, Data Visualization",Associate,18,Transportation,2024-04-13,2024-05-09,1801,9.7,DeepTech Ventures +AI09084,ML Ops Engineer,160139,CHF,144125,MI,FL,Switzerland,L,Japan,0,"Azure, Scala, NLP, Deep Learning, Git",Master,4,Automotive,2024-07-12,2024-09-06,1577,7.8,Smart Analytics +AI09085,Data Engineer,125643,USD,125643,MI,CT,United States,L,United States,100,"Linux, Mathematics, Deep Learning, Python, Statistics",Master,2,Media,2024-12-12,2025-02-05,2246,9.7,Machine Intelligence Group +AI09086,Research Scientist,33763,USD,33763,EN,FT,China,M,South Africa,50,"Java, Tableau, AWS, Scala, Linux",Associate,1,Automotive,2024-08-19,2024-09-26,1405,7.1,TechCorp Inc +AI09087,Computer Vision Engineer,51407,USD,51407,EN,PT,Sweden,M,Sweden,100,"Linux, Mathematics, SQL, MLOps",Associate,0,Gaming,2024-07-22,2024-09-28,1140,8.2,Autonomous Tech +AI09088,Data Scientist,93819,USD,93819,SE,FL,Finland,S,Finland,50,"Kubernetes, Java, MLOps, Scala, GCP",Bachelor,9,Manufacturing,2024-06-01,2024-06-18,1272,8.9,DataVision Ltd +AI09089,Data Engineer,108668,USD,108668,MI,PT,United States,S,United States,100,"Kubernetes, TensorFlow, GCP",Associate,3,Energy,2024-06-12,2024-08-13,2463,9,Predictive Systems +AI09090,AI Consultant,128578,AUD,173580,EX,PT,Australia,S,Australia,0,"Kubernetes, SQL, NLP",PhD,19,Technology,2024-11-24,2024-12-16,853,9.9,Predictive Systems +AI09091,AI Specialist,34167,USD,34167,MI,FL,China,M,China,50,"Linux, Scala, Spark, Git",PhD,2,Automotive,2024-09-11,2024-11-02,1155,6.7,Smart Analytics +AI09092,Deep Learning Engineer,82557,JPY,9081270,MI,FL,Japan,S,Colombia,50,"MLOps, NLP, R",Master,3,Manufacturing,2024-01-02,2024-02-29,1336,5.5,Cloud AI Solutions +AI09093,Machine Learning Engineer,73184,EUR,62206,EN,FL,Austria,M,Austria,100,"Python, SQL, GCP",Master,0,Automotive,2024-10-20,2024-12-10,2376,7.1,Predictive Systems +AI09094,Research Scientist,185487,EUR,157664,EX,PT,France,L,France,50,"Python, Deep Learning, Data Visualization, Java",PhD,10,Gaming,2024-07-21,2024-08-18,2304,8.6,TechCorp Inc +AI09095,Computer Vision Engineer,184041,JPY,20244510,EX,PT,Japan,M,Sweden,0,"TensorFlow, Java, Linux",PhD,13,Energy,2024-10-28,2024-12-13,1131,6.9,Machine Intelligence Group +AI09096,Data Analyst,63990,USD,63990,EN,PT,South Korea,L,Czech Republic,0,"Linux, Mathematics, Tableau, MLOps",PhD,0,Real Estate,2024-07-18,2024-09-08,1360,8.4,Autonomous Tech +AI09097,Deep Learning Engineer,77439,USD,77439,EN,FT,Denmark,L,Denmark,100,"Tableau, Git, Linux",PhD,1,Technology,2024-08-13,2024-09-08,526,10,Predictive Systems +AI09098,Machine Learning Researcher,54169,CAD,67711,EN,PT,Canada,S,Switzerland,100,"Spark, Azure, SQL, Hadoop, Statistics",PhD,0,Gaming,2024-08-28,2024-10-20,1818,7.1,Predictive Systems +AI09099,Deep Learning Engineer,97993,EUR,83294,SE,PT,Germany,S,Germany,0,"Kubernetes, Python, TensorFlow, Statistics",Master,6,Government,2024-09-24,2024-11-25,1849,6.6,Cognitive Computing +AI09100,Data Scientist,79820,JPY,8780200,EN,PT,Japan,L,Japan,100,"Azure, Git, R, Java, Scala",Master,1,Technology,2024-10-12,2024-12-04,1735,6.9,DataVision Ltd +AI09101,Principal Data Scientist,104484,USD,104484,EN,FT,United States,L,United States,0,"PyTorch, TensorFlow, R, Scala",Master,1,Automotive,2024-03-14,2024-03-29,1370,5.8,Smart Analytics +AI09102,Machine Learning Researcher,103925,USD,103925,MI,FL,Sweden,M,United Kingdom,0,"R, PyTorch, Mathematics",Master,3,Telecommunications,2024-06-17,2024-08-25,1236,8.4,TechCorp Inc +AI09103,AI Architect,99884,EUR,84901,SE,FL,Germany,S,Germany,0,"Spark, Azure, NLP, Mathematics, SQL",Associate,9,Manufacturing,2025-03-13,2025-05-11,2448,7.6,TechCorp Inc +AI09104,Machine Learning Researcher,153139,JPY,16845290,SE,FL,Japan,L,Japan,0,"Linux, Python, Deep Learning, Statistics, Computer Vision",Associate,5,Technology,2025-04-25,2025-06-21,2037,7.4,Future Systems +AI09105,ML Ops Engineer,61944,EUR,52652,EN,FL,France,L,France,50,"Deep Learning, Hadoop, PyTorch, NLP",Master,0,Retail,2024-09-28,2024-10-18,2126,6.7,TechCorp Inc +AI09106,Data Engineer,65282,EUR,55490,EN,PT,Austria,M,Austria,50,"Docker, Tableau, NLP",Master,1,Automotive,2024-05-21,2024-08-02,837,8.6,Quantum Computing Inc +AI09107,NLP Engineer,96292,EUR,81848,SE,CT,Germany,S,Germany,100,"NLP, Deep Learning, Scala",Bachelor,9,Consulting,2024-05-18,2024-07-17,1311,6.3,Algorithmic Solutions +AI09108,ML Ops Engineer,157918,CHF,142126,MI,CT,Switzerland,L,Switzerland,100,"Docker, Git, Mathematics",PhD,4,Technology,2024-07-16,2024-08-28,1630,5.3,Cloud AI Solutions +AI09109,Robotics Engineer,68722,AUD,92775,EN,FT,Australia,M,Australia,100,"Python, Spark, Java",Master,0,Education,2024-04-17,2024-05-18,2294,7,Neural Networks Co +AI09110,Computer Vision Engineer,34572,USD,34572,MI,FT,India,S,Austria,50,"Statistics, Python, TensorFlow",PhD,4,Manufacturing,2025-04-13,2025-05-02,1135,5.9,Predictive Systems +AI09111,AI Research Scientist,46646,USD,46646,MI,CT,China,L,China,50,"Deep Learning, MLOps, GCP, NLP",PhD,4,Telecommunications,2025-04-10,2025-05-23,1392,5.4,TechCorp Inc +AI09112,AI Architect,235688,EUR,200335,EX,PT,France,M,Argentina,0,"AWS, Git, Data Visualization, Statistics",Master,15,Transportation,2025-03-24,2025-05-18,2377,6.6,Autonomous Tech +AI09113,NLP Engineer,273202,USD,273202,EX,FT,Israel,L,Russia,100,"Scala, R, Azure, SQL",PhD,17,Transportation,2024-04-04,2024-05-13,717,5.6,DataVision Ltd +AI09114,Principal Data Scientist,191484,CAD,239355,EX,FT,Canada,S,Canada,0,"NLP, Spark, Scala, TensorFlow, Deep Learning",Associate,11,Manufacturing,2025-03-03,2025-04-29,674,9.1,AI Innovations +AI09115,AI Research Scientist,59597,USD,59597,EX,CT,India,M,Israel,0,"MLOps, Scala, TensorFlow",Bachelor,12,Manufacturing,2024-04-19,2024-06-24,1996,7,Smart Analytics +AI09116,Autonomous Systems Engineer,152712,USD,152712,EX,FL,Ireland,S,Ireland,50,"Deep Learning, Python, Data Visualization, Git, R",Master,12,Transportation,2024-05-13,2024-07-23,2066,7.7,DataVision Ltd +AI09117,Machine Learning Engineer,260073,EUR,221062,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, TensorFlow, Computer Vision, Data Visualization",Associate,14,Government,2024-04-27,2024-06-16,2072,9.8,Digital Transformation LLC +AI09118,Principal Data Scientist,21379,USD,21379,EN,PT,India,M,India,50,"Computer Vision, GCP, Hadoop, Python, Data Visualization",PhD,1,Healthcare,2024-06-02,2024-07-05,785,5.4,Machine Intelligence Group +AI09119,Machine Learning Researcher,39561,USD,39561,MI,FT,China,L,China,100,"Computer Vision, TensorFlow, Hadoop",Bachelor,4,Retail,2024-09-21,2024-11-03,930,8.7,Smart Analytics +AI09120,AI Software Engineer,126547,EUR,107565,MI,CT,Germany,L,Germany,50,"Linux, Docker, PyTorch",Bachelor,4,Telecommunications,2025-04-24,2025-07-06,1681,7,Algorithmic Solutions +AI09121,Autonomous Systems Engineer,187489,USD,187489,EX,PT,South Korea,S,South Korea,50,"Java, Kubernetes, Tableau",PhD,17,Energy,2024-08-20,2024-10-06,2373,10,TechCorp Inc +AI09122,NLP Engineer,131267,USD,131267,SE,FL,United States,M,United States,0,"SQL, R, Linux, GCP",Bachelor,8,Finance,2024-01-24,2024-03-11,1746,9,Autonomous Tech +AI09123,AI Architect,77519,USD,77519,EN,FL,Finland,L,Finland,0,"Azure, Kubernetes, Scala",Associate,0,Finance,2025-03-21,2025-05-12,1803,6.2,DeepTech Ventures +AI09124,ML Ops Engineer,108940,AUD,147069,MI,PT,Australia,L,Kenya,100,"Hadoop, Java, Tableau",Bachelor,2,Government,2024-02-24,2024-04-24,2250,8.3,DataVision Ltd +AI09125,Machine Learning Researcher,151325,GBP,113494,EX,FL,United Kingdom,M,Ukraine,0,"Hadoop, PyTorch, Deep Learning",PhD,12,Real Estate,2025-01-05,2025-02-23,2290,8.5,TechCorp Inc +AI09126,Head of AI,164274,USD,164274,EX,FL,Ireland,L,Finland,50,"Python, TensorFlow, PyTorch, Deep Learning",Master,13,Automotive,2024-11-15,2024-12-17,930,6.2,Future Systems +AI09127,Principal Data Scientist,96078,AUD,129705,MI,CT,Australia,S,Australia,0,"Scala, AWS, Azure, R",Master,2,Telecommunications,2024-02-19,2024-03-15,2296,6.6,TechCorp Inc +AI09128,Principal Data Scientist,234097,EUR,198982,EX,FT,Netherlands,S,Luxembourg,100,"Hadoop, Scala, Deep Learning, R, AWS",PhD,17,Manufacturing,2024-09-16,2024-11-26,1852,5.8,Advanced Robotics +AI09129,Research Scientist,285597,USD,285597,EX,CT,Norway,M,Mexico,50,"Kubernetes, Deep Learning, TensorFlow, Scala",Associate,17,Energy,2024-04-09,2024-06-11,1210,7.6,Future Systems +AI09130,Autonomous Systems Engineer,273922,USD,273922,EX,FT,Norway,L,Norway,100,"Python, Docker, Hadoop, Deep Learning, Mathematics",Associate,16,Energy,2024-04-13,2024-05-11,1232,5.6,Quantum Computing Inc +AI09131,AI Software Engineer,61758,EUR,52494,MI,PT,Austria,S,Austria,50,"MLOps, Deep Learning, PyTorch, GCP",PhD,4,Energy,2025-03-06,2025-05-03,2361,7.4,Predictive Systems +AI09132,Autonomous Systems Engineer,216376,EUR,183920,EX,PT,Austria,L,Austria,100,"SQL, Azure, Kubernetes, Docker",Master,15,Transportation,2024-05-28,2024-07-21,2425,6.2,Autonomous Tech +AI09133,Data Engineer,137572,USD,137572,SE,PT,Denmark,S,Kenya,50,"Data Visualization, Azure, Python",Bachelor,7,Education,2025-04-29,2025-07-11,1115,8.3,Neural Networks Co +AI09134,Machine Learning Researcher,206544,JPY,22719840,EX,CT,Japan,S,Japan,50,"MLOps, SQL, TensorFlow, Data Visualization, Statistics",Master,16,Gaming,2024-06-13,2024-07-10,2087,6.2,DataVision Ltd +AI09135,ML Ops Engineer,141517,USD,141517,SE,FT,South Korea,L,Colombia,0,"Kubernetes, Python, AWS",Associate,6,Gaming,2024-04-07,2024-06-11,822,6.1,DeepTech Ventures +AI09136,Research Scientist,87198,EUR,74118,MI,PT,Austria,L,Austria,50,"Kubernetes, Spark, SQL, NLP",Master,4,Automotive,2025-04-11,2025-05-31,1541,9.8,Predictive Systems +AI09137,Machine Learning Researcher,87108,EUR,74042,EN,PT,Netherlands,L,Netherlands,0,"PyTorch, Java, Scala, Docker, TensorFlow",Bachelor,0,Gaming,2024-09-06,2024-11-16,2018,7.6,TechCorp Inc +AI09138,Robotics Engineer,214335,EUR,182185,EX,CT,Austria,S,Denmark,0,"Hadoop, AWS, SQL",Associate,15,Education,2024-10-30,2024-12-27,1232,9.5,Machine Intelligence Group +AI09139,AI Specialist,153507,CAD,191884,EX,FT,Canada,S,Canada,100,"SQL, Docker, Data Visualization, MLOps",PhD,15,Consulting,2024-09-04,2024-11-09,2064,8.6,Cloud AI Solutions +AI09140,Data Analyst,73451,EUR,62433,MI,PT,Austria,S,Austria,0,"Git, Python, Data Visualization, Azure, Tableau",PhD,2,Energy,2024-11-23,2024-12-26,2401,7.7,DeepTech Ventures +AI09141,Robotics Engineer,141812,SGD,184356,SE,PT,Singapore,M,Singapore,0,"Mathematics, Spark, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-02-17,2364,8.8,Future Systems +AI09142,AI Software Engineer,185928,USD,185928,EX,PT,South Korea,M,China,50,"Spark, Scala, Statistics, Hadoop",Master,11,Consulting,2024-05-08,2024-07-17,1047,8.2,Algorithmic Solutions +AI09143,Machine Learning Engineer,114515,USD,114515,SE,PT,Israel,S,Israel,50,"Tableau, NLP, GCP, Computer Vision",Bachelor,7,Education,2024-02-02,2024-03-01,961,7.9,AI Innovations +AI09144,Data Analyst,175467,EUR,149147,EX,CT,Germany,S,Germany,0,"Git, Statistics, Tableau, TensorFlow",Master,15,Retail,2025-02-10,2025-03-05,2273,6.5,DeepTech Ventures +AI09145,Head of AI,88766,EUR,75451,MI,CT,Netherlands,L,Netherlands,0,"R, AWS, Data Visualization",Associate,2,Transportation,2024-10-14,2024-11-16,850,9,Digital Transformation LLC +AI09146,Computer Vision Engineer,111355,JPY,12249050,MI,FL,Japan,M,Poland,0,"Python, PyTorch, Deep Learning, GCP",PhD,4,Telecommunications,2025-01-16,2025-02-20,2186,7.2,Future Systems +AI09147,Machine Learning Engineer,128271,CAD,160339,SE,FT,Canada,S,Canada,100,"Data Visualization, NLP, Tableau",Bachelor,5,Government,2024-11-15,2024-12-07,837,7.7,Advanced Robotics +AI09148,Machine Learning Engineer,123580,EUR,105043,SE,FT,France,M,France,0,"NLP, Spark, Deep Learning",Master,9,Education,2025-03-13,2025-05-21,1067,8.3,AI Innovations +AI09149,ML Ops Engineer,77084,AUD,104063,EN,CT,Australia,L,Australia,0,"Data Visualization, NLP, TensorFlow, Azure",Bachelor,1,Consulting,2024-07-02,2024-07-20,1859,7.6,DataVision Ltd +AI09150,AI Specialist,46762,USD,46762,EN,PT,Ireland,S,Ireland,100,"PyTorch, SQL, Deep Learning, Scala, Tableau",Associate,1,Government,2025-03-26,2025-05-25,1596,9.3,Machine Intelligence Group +AI09151,AI Consultant,218952,USD,218952,EX,PT,Ireland,M,Ireland,50,"MLOps, AWS, SQL, Mathematics, Azure",Bachelor,13,Government,2025-01-30,2025-03-21,628,7.9,Advanced Robotics +AI09152,AI Product Manager,61455,SGD,79892,EN,FT,Singapore,S,Australia,50,"Hadoop, Tableau, Spark, Linux, Computer Vision",Bachelor,1,Finance,2024-04-19,2024-06-14,1344,5.6,Predictive Systems +AI09153,Machine Learning Engineer,66187,USD,66187,EX,PT,China,M,China,100,"Azure, Git, Tableau, SQL",Bachelor,17,Finance,2024-11-22,2024-12-11,1180,6.7,Cloud AI Solutions +AI09154,NLP Engineer,130172,SGD,169224,SE,FT,Singapore,S,Japan,50,"GCP, Java, MLOps, Computer Vision",PhD,8,Automotive,2025-03-01,2025-05-09,1102,9.1,TechCorp Inc +AI09155,Machine Learning Engineer,77763,JPY,8553930,EN,FT,Japan,L,Japan,100,"SQL, PyTorch, Mathematics, Docker",Associate,1,Real Estate,2025-03-15,2025-05-08,648,5.8,Autonomous Tech +AI09156,Research Scientist,100848,USD,100848,MI,CT,Norway,M,Norway,100,"Docker, Git, AWS",PhD,2,Energy,2024-08-19,2024-09-28,752,6.5,Smart Analytics +AI09157,Machine Learning Engineer,144916,JPY,15940760,EX,FT,Japan,S,Japan,50,"PyTorch, Scala, Python",PhD,18,Retail,2025-02-06,2025-03-23,1976,5.7,Quantum Computing Inc +AI09158,Autonomous Systems Engineer,241167,SGD,313517,EX,PT,Singapore,S,Israel,100,"Spark, Statistics, Computer Vision, Git",Associate,17,Technology,2024-06-11,2024-07-22,2278,8.5,Algorithmic Solutions +AI09159,Head of AI,122631,GBP,91973,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, SQL, Deep Learning, MLOps",Associate,3,Healthcare,2025-03-21,2025-05-10,1649,7.5,AI Innovations +AI09160,ML Ops Engineer,52113,USD,52113,SE,FL,India,M,India,50,"Computer Vision, GCP, Tableau, NLP",Master,9,Telecommunications,2024-05-01,2024-05-19,1707,5.2,Digital Transformation LLC +AI09161,AI Specialist,131239,AUD,177173,SE,PT,Australia,S,Latvia,0,"Spark, Hadoop, TensorFlow, MLOps",Associate,8,Consulting,2024-12-07,2025-02-16,1374,6.6,Autonomous Tech +AI09162,AI Architect,39306,USD,39306,SE,CT,India,S,India,100,"Linux, MLOps, Tableau, AWS, Git",PhD,7,Automotive,2025-04-23,2025-05-24,703,6.6,Smart Analytics +AI09163,Machine Learning Engineer,55092,EUR,46828,EN,FT,Austria,M,Austria,100,"Python, GCP, Mathematics, MLOps",Bachelor,0,Automotive,2024-07-24,2024-09-15,1765,7.5,Quantum Computing Inc +AI09164,Research Scientist,155977,AUD,210569,SE,CT,Australia,L,Australia,50,"Azure, Mathematics, Data Visualization",PhD,7,Real Estate,2024-12-22,2025-02-15,564,9.6,AI Innovations +AI09165,AI Architect,92563,USD,92563,EN,FL,United States,M,United States,100,"Python, Kubernetes, Computer Vision, NLP",Associate,0,Education,2024-09-29,2024-10-17,2497,9.7,Cloud AI Solutions +AI09166,Data Scientist,56883,USD,56883,EN,FL,Finland,M,Finland,50,"Tableau, Hadoop, Python",PhD,1,Energy,2024-08-25,2024-10-24,2304,5.1,Advanced Robotics +AI09167,AI Research Scientist,63119,USD,63119,EN,FT,Norway,S,Norway,0,"Docker, MLOps, Scala, Computer Vision, Azure",Associate,1,Finance,2024-04-17,2024-05-28,1624,9.1,Algorithmic Solutions +AI09168,Robotics Engineer,124054,USD,124054,SE,CT,Finland,S,Argentina,0,"Python, GCP, Computer Vision",Bachelor,7,Energy,2024-09-10,2024-10-17,1475,8.2,DataVision Ltd +AI09169,Head of AI,70626,AUD,95345,EN,CT,Australia,S,Australia,100,"GCP, TensorFlow, MLOps, Python",Master,0,Government,2025-03-21,2025-04-13,2467,9.3,DataVision Ltd +AI09170,AI Consultant,95105,EUR,80839,MI,PT,Germany,M,China,50,"Spark, SQL, MLOps, Hadoop, Statistics",Master,3,Gaming,2024-02-26,2024-03-18,1527,5.9,Smart Analytics +AI09171,AI Architect,142966,GBP,107225,SE,FL,United Kingdom,M,Canada,0,"Computer Vision, SQL, Deep Learning, Git, Hadoop",Bachelor,6,Energy,2024-02-27,2024-04-18,1558,8.4,Machine Intelligence Group +AI09172,Autonomous Systems Engineer,30269,USD,30269,EN,FL,India,L,Israel,50,"NLP, Kubernetes, TensorFlow, MLOps, Git",Master,1,Retail,2024-12-02,2024-12-23,1413,6.7,Future Systems +AI09173,Computer Vision Engineer,172669,USD,172669,SE,FL,Norway,M,Norway,0,"Docker, PyTorch, Java, Python, Scala",Bachelor,8,Real Estate,2024-07-22,2024-08-16,1753,9.4,Future Systems +AI09174,Robotics Engineer,129725,USD,129725,EX,PT,Ireland,S,Ireland,50,"Scala, Azure, Tableau, NLP",Master,14,Media,2024-06-24,2024-09-02,1349,8.5,Digital Transformation LLC +AI09175,Computer Vision Engineer,63167,SGD,82117,EN,CT,Singapore,S,Singapore,100,"NLP, GCP, Deep Learning, Python, Hadoop",Master,0,Retail,2024-09-27,2024-12-09,686,8.7,Neural Networks Co +AI09176,AI Specialist,258786,USD,258786,EX,FL,Norway,S,Norway,50,"Linux, Kubernetes, PyTorch",Master,10,Technology,2024-04-22,2024-05-08,1899,5.4,Cognitive Computing +AI09177,AI Research Scientist,44253,USD,44253,MI,CT,China,S,Finland,50,"Hadoop, Python, Azure, Kubernetes, Scala",Bachelor,2,Energy,2025-01-02,2025-02-15,1158,8.5,Quantum Computing Inc +AI09178,AI Consultant,130321,GBP,97741,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, MLOps, SQL",Master,7,Technology,2024-04-29,2024-05-18,2064,8.7,Advanced Robotics +AI09179,Research Scientist,163239,EUR,138753,EX,FT,France,M,France,0,"Linux, Git, Data Visualization, Deep Learning",Master,13,Healthcare,2024-09-06,2024-11-17,766,9,Smart Analytics +AI09180,Research Scientist,88353,CAD,110441,MI,FL,Canada,S,Philippines,100,"R, Linux, SQL, Git, AWS",Bachelor,4,Manufacturing,2024-05-06,2024-05-31,1684,7.6,Algorithmic Solutions +AI09181,Machine Learning Engineer,99421,CAD,124276,MI,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Tableau",Master,4,Retail,2024-04-20,2024-05-16,1672,6.4,Machine Intelligence Group +AI09182,Deep Learning Engineer,92458,EUR,78589,SE,FL,Germany,S,Germany,0,"Scala, PyTorch, Hadoop",PhD,7,Transportation,2024-05-10,2024-07-15,1982,9.8,Cloud AI Solutions +AI09183,Autonomous Systems Engineer,176930,JPY,19462300,SE,FL,Japan,L,Japan,50,"Kubernetes, Deep Learning, MLOps, Azure",Master,7,Healthcare,2024-03-24,2024-04-25,1765,6.9,DeepTech Ventures +AI09184,Machine Learning Engineer,87956,USD,87956,MI,CT,Israel,S,Israel,50,"Spark, Python, Data Visualization",Master,4,Telecommunications,2024-01-16,2024-02-22,1350,9.5,Algorithmic Solutions +AI09185,Data Scientist,178060,USD,178060,SE,FT,Norway,L,Norway,100,"Spark, Git, NLP, Statistics",Master,7,Energy,2025-01-28,2025-04-11,2470,7.7,Algorithmic Solutions +AI09186,Robotics Engineer,274887,USD,274887,EX,FT,Finland,L,Finland,50,"Python, TensorFlow, Git, Linux, Azure",Bachelor,18,Media,2025-03-19,2025-05-06,524,5.2,Quantum Computing Inc +AI09187,AI Software Engineer,111752,USD,111752,MI,PT,Ireland,L,Ireland,100,"Docker, Spark, NLP, Kubernetes, Computer Vision",Bachelor,4,Gaming,2024-01-05,2024-01-20,1344,8.3,Cloud AI Solutions +AI09188,AI Specialist,58945,CAD,73681,EN,FL,Canada,L,South Africa,100,"R, SQL, Linux",Master,0,Education,2024-12-30,2025-02-24,1925,8.9,Machine Intelligence Group +AI09189,AI Specialist,192129,USD,192129,SE,FL,Denmark,L,Denmark,50,"Linux, Python, Tableau",Master,6,Education,2024-03-30,2024-06-03,1867,9.3,TechCorp Inc +AI09190,Data Analyst,111169,AUD,150078,SE,PT,Australia,M,Canada,50,"PyTorch, Linux, MLOps",Master,8,Education,2024-10-10,2024-10-26,726,6.8,DataVision Ltd +AI09191,Machine Learning Researcher,92985,GBP,69739,MI,PT,United Kingdom,L,United Kingdom,50,"AWS, TensorFlow, SQL, Azure",Master,3,Gaming,2024-07-23,2024-08-21,1875,6.4,Machine Intelligence Group +AI09192,AI Consultant,96505,CHF,86855,EN,PT,Switzerland,S,Switzerland,50,"SQL, TensorFlow, NLP, AWS, Tableau",Bachelor,0,Manufacturing,2024-02-29,2024-04-30,2394,7,Cognitive Computing +AI09193,AI Software Engineer,158342,USD,158342,EX,FT,South Korea,L,South Korea,0,"GCP, TensorFlow, NLP, Statistics, Computer Vision",Master,12,Consulting,2025-03-12,2025-04-27,1649,6.4,Cognitive Computing +AI09194,AI Specialist,93578,JPY,10293580,EN,CT,Japan,L,Japan,0,"Java, TensorFlow, Azure, Tableau, Kubernetes",Associate,1,Gaming,2024-10-26,2024-11-30,2036,9.3,Smart Analytics +AI09195,Data Engineer,214274,USD,214274,EX,CT,United States,M,Czech Republic,100,"Java, Data Visualization, PyTorch",Master,13,Technology,2024-11-12,2024-12-31,743,8,Digital Transformation LLC +AI09196,AI Consultant,178303,CAD,222879,EX,CT,Canada,M,Canada,50,"Mathematics, Computer Vision, Spark, Hadoop, SQL",Associate,17,Government,2025-03-03,2025-04-19,1070,8.9,Advanced Robotics +AI09197,Head of AI,36007,USD,36007,SE,FT,India,M,India,50,"AWS, Tableau, TensorFlow, Git",Associate,7,Finance,2024-02-07,2024-03-03,730,6,Advanced Robotics +AI09198,Deep Learning Engineer,171051,EUR,145393,EX,PT,Austria,S,Canada,50,"Python, AWS, TensorFlow",Bachelor,13,Consulting,2024-05-21,2024-07-03,1012,8.5,Algorithmic Solutions +AI09199,Head of AI,198950,EUR,169108,EX,FT,Austria,S,Austria,50,"Spark, SQL, Statistics",Associate,14,Government,2025-03-12,2025-04-20,2381,9.2,DeepTech Ventures +AI09200,Robotics Engineer,124387,EUR,105729,SE,FT,France,M,France,100,"PyTorch, TensorFlow, Deep Learning, Scala, Java",Associate,8,Gaming,2024-10-15,2024-12-06,911,5,Neural Networks Co +AI09201,Computer Vision Engineer,106704,USD,106704,MI,FL,Ireland,L,Ireland,100,"R, Git, Azure, Scala, Python",PhD,3,Telecommunications,2024-01-15,2024-02-03,1956,5.7,DeepTech Ventures +AI09202,Research Scientist,149562,USD,149562,EX,FL,Finland,L,Finland,0,"Scala, Tableau, Python, SQL, Kubernetes",Associate,16,Education,2024-10-12,2024-12-08,1386,7.2,Cloud AI Solutions +AI09203,AI Software Engineer,112666,USD,112666,SE,FL,Finland,L,Japan,50,"Azure, Java, Computer Vision",PhD,8,Telecommunications,2024-04-27,2024-06-01,1069,7.2,Cloud AI Solutions +AI09204,Data Analyst,102655,USD,102655,MI,CT,Norway,S,Norway,100,"PyTorch, Computer Vision, Git",Master,2,Telecommunications,2024-12-02,2025-02-12,721,5.4,TechCorp Inc +AI09205,Research Scientist,60391,CAD,75489,EN,FT,Canada,M,Canada,50,"SQL, Spark, PyTorch",PhD,1,Manufacturing,2024-01-31,2024-04-13,1304,6.9,DeepTech Ventures +AI09206,Data Analyst,93418,USD,93418,SE,PT,South Korea,S,Estonia,0,"Git, SQL, Hadoop, Mathematics, Scala",Associate,9,Education,2024-04-04,2024-06-10,2248,9.4,Cloud AI Solutions +AI09207,AI Architect,64099,EUR,54484,MI,PT,France,S,Japan,100,"Scala, Spark, Java, Computer Vision, Docker",Associate,4,Education,2024-11-15,2024-12-08,2247,5.1,Cognitive Computing +AI09208,Head of AI,170894,JPY,18798340,SE,FL,Japan,L,Japan,0,"Data Visualization, PyTorch, SQL",Bachelor,8,Real Estate,2024-03-13,2024-05-15,2021,6.9,Algorithmic Solutions +AI09209,Autonomous Systems Engineer,26067,USD,26067,EN,CT,India,M,Russia,100,"Hadoop, Python, TensorFlow, Git",Bachelor,0,Consulting,2024-01-23,2024-03-07,892,7.1,Advanced Robotics +AI09210,AI Specialist,87803,EUR,74633,EN,PT,Germany,L,Germany,100,"TensorFlow, Python, GCP",Master,1,Media,2024-11-08,2024-12-04,822,8.7,Algorithmic Solutions +AI09211,AI Consultant,73822,CAD,92278,EN,FL,Canada,M,Netherlands,0,"Tableau, TensorFlow, Scala, Statistics",Master,1,Technology,2024-10-03,2024-10-20,1230,5.2,Predictive Systems +AI09212,Machine Learning Engineer,92932,CHF,83639,EN,FT,Switzerland,M,Switzerland,100,"AWS, NLP, SQL",Bachelor,0,Education,2024-07-23,2024-09-05,608,6.4,Neural Networks Co +AI09213,AI Consultant,68084,EUR,57871,EN,PT,Netherlands,L,France,100,"Linux, Tableau, Spark, AWS, Azure",PhD,0,Technology,2025-02-23,2025-04-28,1068,8.9,Cloud AI Solutions +AI09214,AI Specialist,207439,SGD,269671,EX,FL,Singapore,M,Singapore,100,"Java, Spark, NLP",Associate,18,Media,2024-03-19,2024-04-21,1904,5.8,Machine Intelligence Group +AI09215,Data Analyst,96026,USD,96026,EX,FL,China,S,China,100,"SQL, PyTorch, Data Visualization, MLOps",Bachelor,10,Telecommunications,2025-04-16,2025-05-31,868,9.4,Digital Transformation LLC +AI09216,Research Scientist,59680,EUR,50728,EN,FT,France,M,France,0,"Hadoop, MLOps, TensorFlow, Mathematics",Associate,1,Retail,2025-03-12,2025-05-20,2217,6.3,DataVision Ltd +AI09217,AI Specialist,56599,USD,56599,EN,CT,Israel,M,Israel,50,"Azure, AWS, Docker",Master,1,Retail,2025-03-09,2025-04-18,2056,7.5,Future Systems +AI09218,Principal Data Scientist,76244,USD,76244,EN,PT,United States,M,Nigeria,50,"PyTorch, Statistics, TensorFlow",Bachelor,1,Government,2024-09-24,2024-11-27,2133,5.8,Cloud AI Solutions +AI09219,Research Scientist,79160,EUR,67286,MI,FT,France,S,France,100,"Kubernetes, PyTorch, MLOps, SQL",Associate,4,Consulting,2024-11-09,2024-12-14,1801,9.4,Quantum Computing Inc +AI09220,Data Scientist,60957,USD,60957,EN,CT,Ireland,L,Ireland,50,"Git, Python, GCP",PhD,0,Gaming,2025-03-31,2025-05-04,1384,8.1,Future Systems +AI09221,Autonomous Systems Engineer,155548,USD,155548,SE,FL,Israel,L,India,100,"MLOps, Python, TensorFlow, PyTorch, Data Visualization",Master,5,Consulting,2024-08-12,2024-09-22,1725,6.7,Algorithmic Solutions +AI09222,AI Product Manager,123088,JPY,13539680,MI,PT,Japan,L,Japan,0,"Statistics, Scala, Python, GCP, R",Master,2,Manufacturing,2024-05-23,2024-06-09,1989,9,Algorithmic Solutions +AI09223,Research Scientist,121682,USD,121682,MI,FL,Norway,L,Vietnam,100,"Hadoop, Tableau, Spark, Mathematics, Scala",Associate,4,Finance,2024-12-25,2025-02-05,1174,5.7,Cognitive Computing +AI09224,AI Consultant,169915,EUR,144428,EX,PT,Germany,L,Germany,0,"GCP, Hadoop, Git, Computer Vision, R",Associate,14,Media,2025-01-19,2025-02-24,852,5.2,Autonomous Tech +AI09225,AI Specialist,119381,CAD,149226,MI,PT,Canada,L,Canada,100,"Java, MLOps, AWS",PhD,4,Manufacturing,2024-09-22,2024-11-04,2129,8.6,Digital Transformation LLC +AI09226,Deep Learning Engineer,133384,GBP,100038,SE,PT,United Kingdom,M,United Kingdom,0,"SQL, TensorFlow, AWS",Associate,6,Government,2024-04-07,2024-05-07,575,9.1,Machine Intelligence Group +AI09227,AI Architect,122154,USD,122154,SE,FT,United States,S,Colombia,100,"Python, Spark, Mathematics",Master,8,Technology,2024-07-25,2024-09-20,2343,6.7,DeepTech Ventures +AI09228,AI Specialist,66659,EUR,56660,EN,FL,Netherlands,S,Netherlands,100,"Kubernetes, PyTorch, TensorFlow, Spark, Computer Vision",PhD,1,Finance,2024-03-02,2024-04-15,2386,6.7,Cloud AI Solutions +AI09229,Data Analyst,92410,EUR,78549,MI,PT,Germany,L,Germany,100,"Hadoop, SQL, AWS",Bachelor,2,Technology,2024-03-28,2024-05-25,2078,8.7,Algorithmic Solutions +AI09230,Principal Data Scientist,81950,USD,81950,SE,FT,South Korea,S,South Korea,50,"Azure, SQL, Python, TensorFlow",Associate,9,Real Estate,2025-01-27,2025-03-31,1513,6.6,Predictive Systems +AI09231,AI Research Scientist,192330,EUR,163481,EX,CT,Netherlands,L,Netherlands,100,"GCP, Spark, Data Visualization, SQL",Bachelor,19,Government,2025-04-30,2025-05-28,1050,6.7,Cloud AI Solutions +AI09232,AI Specialist,194139,CHF,174725,SE,CT,Switzerland,M,Romania,50,"Deep Learning, Java, MLOps, Kubernetes, AWS",Associate,7,Retail,2024-06-18,2024-07-23,2017,9.3,Cognitive Computing +AI09233,Machine Learning Researcher,287100,USD,287100,EX,PT,Denmark,S,Denmark,0,"R, Python, Spark",Master,14,Technology,2025-03-18,2025-04-23,505,7,DataVision Ltd +AI09234,AI Consultant,192660,USD,192660,EX,FT,Finland,S,Finland,50,"GCP, PyTorch, TensorFlow, SQL",Associate,18,Healthcare,2024-06-29,2024-08-24,1758,7,AI Innovations +AI09235,AI Specialist,79472,USD,79472,MI,CT,Israel,M,Kenya,0,"Python, Spark, Kubernetes, PyTorch, Tableau",Master,3,Technology,2024-07-21,2024-09-07,1228,5.5,Advanced Robotics +AI09236,Autonomous Systems Engineer,118867,USD,118867,MI,FL,Norway,L,Norway,0,"MLOps, TensorFlow, Python",PhD,2,Telecommunications,2024-10-11,2024-12-13,2362,9.9,Algorithmic Solutions +AI09237,Research Scientist,123406,USD,123406,SE,PT,South Korea,L,Colombia,100,"SQL, PyTorch, AWS, Kubernetes",Associate,7,Automotive,2024-12-14,2025-02-20,1950,9.1,AI Innovations +AI09238,NLP Engineer,122245,USD,122245,SE,PT,Denmark,S,Denmark,100,"Git, Data Visualization, AWS",Master,5,Gaming,2024-10-30,2024-11-15,1775,9.5,Machine Intelligence Group +AI09239,ML Ops Engineer,191922,EUR,163134,EX,PT,France,S,France,0,"MLOps, Java, Docker, Scala",Associate,14,Gaming,2024-12-15,2025-01-12,2390,6,Cognitive Computing +AI09240,Data Engineer,68565,SGD,89135,EN,PT,Singapore,L,Singapore,50,"Kubernetes, Statistics, Data Visualization, Azure, Computer Vision",Master,0,Retail,2024-03-05,2024-04-21,2290,6.2,Quantum Computing Inc +AI09241,ML Ops Engineer,102495,JPY,11274450,MI,PT,Japan,S,Estonia,0,"Linux, Scala, Java, Azure",PhD,3,Manufacturing,2024-12-06,2025-01-21,1059,9.7,Predictive Systems +AI09242,Research Scientist,69321,SGD,90117,EN,CT,Singapore,L,Singapore,50,"AWS, Scala, Statistics, R",Master,0,Telecommunications,2024-08-31,2024-11-01,1292,8,Autonomous Tech +AI09243,Autonomous Systems Engineer,100703,AUD,135949,MI,FT,Australia,L,Australia,100,"Kubernetes, Tableau, Docker",PhD,4,Education,2024-07-05,2024-09-04,2102,7.8,Cognitive Computing +AI09244,AI Product Manager,87600,AUD,118260,EN,FT,Australia,L,Norway,0,"R, Mathematics, PyTorch, Deep Learning",Associate,1,Gaming,2024-01-06,2024-02-17,2084,7.9,Cloud AI Solutions +AI09245,AI Product Manager,104439,USD,104439,EN,FT,Denmark,M,Denmark,100,"Data Visualization, Linux, Computer Vision, Kubernetes, Mathematics",PhD,1,Real Estate,2024-03-19,2024-04-02,765,5.1,Smart Analytics +AI09246,Machine Learning Engineer,114869,CHF,103382,MI,CT,Switzerland,M,Switzerland,50,"GCP, Python, SQL, Kubernetes, Docker",Bachelor,4,Healthcare,2024-02-02,2024-04-04,1465,6.6,Machine Intelligence Group +AI09247,AI Consultant,77038,USD,77038,MI,CT,South Korea,S,South Korea,50,"Deep Learning, Kubernetes, Tableau, NLP",Master,4,Consulting,2024-03-17,2024-05-05,590,9.9,Autonomous Tech +AI09248,Machine Learning Engineer,115588,USD,115588,SE,FL,Sweden,S,New Zealand,50,"Docker, Mathematics, Tableau, GCP",Associate,7,Gaming,2025-02-23,2025-03-10,1018,7.5,DataVision Ltd +AI09249,Computer Vision Engineer,124933,CAD,156166,SE,FL,Canada,S,Canada,0,"GCP, Python, Data Visualization, Computer Vision, Deep Learning",Associate,8,Gaming,2024-07-16,2024-09-02,2228,6.4,Smart Analytics +AI09250,Robotics Engineer,105467,EUR,89647,MI,FT,Germany,L,Germany,0,"TensorFlow, Computer Vision, PyTorch, Deep Learning, Statistics",Associate,2,Healthcare,2024-11-03,2024-12-29,743,9.4,TechCorp Inc +AI09251,Research Scientist,108242,USD,108242,MI,FT,Ireland,L,Germany,100,"Computer Vision, GCP, Git, Tableau",Master,2,Manufacturing,2024-09-10,2024-09-26,682,9.8,Advanced Robotics +AI09252,AI Architect,92353,AUD,124677,SE,CT,Australia,S,Australia,100,"Mathematics, Azure, Tableau, TensorFlow, Java",Bachelor,6,Consulting,2024-02-04,2024-04-17,1028,9.1,Cloud AI Solutions +AI09253,Head of AI,137894,USD,137894,SE,PT,South Korea,L,Argentina,100,"Mathematics, Docker, GCP, Spark",Bachelor,5,Healthcare,2025-01-25,2025-02-22,1638,8.3,Autonomous Tech +AI09254,AI Specialist,80356,SGD,104463,EN,FL,Singapore,L,India,0,"Python, GCP, Kubernetes, Scala, Linux",Associate,0,Telecommunications,2024-04-19,2024-06-05,512,5.1,Smart Analytics +AI09255,Data Analyst,97471,USD,97471,MI,PT,Ireland,L,New Zealand,0,"Linux, AWS, Hadoop",Bachelor,3,Manufacturing,2024-01-25,2024-03-27,610,9.8,Future Systems +AI09256,Data Scientist,157922,USD,157922,EX,CT,Finland,M,Singapore,50,"R, Python, Statistics, Docker, Deep Learning",Associate,13,Consulting,2024-10-26,2024-12-05,2233,5.2,Cognitive Computing +AI09257,NLP Engineer,86054,CAD,107568,MI,FL,Canada,L,India,0,"Kubernetes, Python, Azure, TensorFlow, PyTorch",Bachelor,3,Real Estate,2024-07-08,2024-08-17,680,5.3,Cognitive Computing +AI09258,Data Scientist,133023,JPY,14632530,SE,FL,Japan,L,Colombia,50,"Azure, Docker, Deep Learning, SQL, MLOps",PhD,8,Real Estate,2025-03-03,2025-04-23,936,7.5,Algorithmic Solutions +AI09259,NLP Engineer,96262,GBP,72197,EN,CT,United Kingdom,L,United Kingdom,0,"Scala, Kubernetes, Git, GCP, Hadoop",PhD,0,Consulting,2024-12-03,2025-01-25,1844,6.4,Digital Transformation LLC +AI09260,Machine Learning Engineer,33333,USD,33333,MI,PT,India,L,India,50,"Hadoop, Scala, Java",Master,4,Technology,2024-05-26,2024-07-21,1580,8.4,DataVision Ltd +AI09261,Deep Learning Engineer,87092,USD,87092,MI,CT,Ireland,L,Ireland,50,"Hadoop, Git, R, GCP",Bachelor,4,Consulting,2025-02-27,2025-03-31,1789,9,Digital Transformation LLC +AI09262,Research Scientist,146551,USD,146551,EX,FL,Ireland,M,Ireland,0,"AWS, Hadoop, R",Master,16,Energy,2024-10-11,2024-12-16,2266,7,Digital Transformation LLC +AI09263,Robotics Engineer,66231,CAD,82789,EN,PT,Canada,L,Canada,0,"Deep Learning, Spark, TensorFlow",Master,1,Energy,2025-02-03,2025-04-13,1660,5.5,Autonomous Tech +AI09264,Robotics Engineer,145114,AUD,195904,SE,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, NLP",Associate,5,Telecommunications,2024-12-01,2025-02-09,1103,9.5,Autonomous Tech +AI09265,Autonomous Systems Engineer,146269,USD,146269,SE,PT,Sweden,M,Malaysia,0,"NLP, Hadoop, MLOps",Master,7,Finance,2024-12-01,2025-02-05,683,5.6,Quantum Computing Inc +AI09266,Research Scientist,125674,CAD,157093,SE,CT,Canada,L,Ukraine,50,"MLOps, TensorFlow, Mathematics, AWS",Bachelor,9,Government,2025-03-24,2025-05-16,871,8.6,Neural Networks Co +AI09267,Machine Learning Engineer,127447,JPY,14019170,SE,PT,Japan,S,Japan,100,"Java, Kubernetes, SQL",Associate,8,Transportation,2024-02-26,2024-03-27,1801,7.2,Advanced Robotics +AI09268,NLP Engineer,61294,EUR,52100,EN,CT,France,M,France,0,"SQL, Hadoop, Scala, Data Visualization",Bachelor,0,Energy,2024-09-29,2024-10-28,1878,7.2,Cloud AI Solutions +AI09269,ML Ops Engineer,135156,USD,135156,SE,FL,Sweden,S,Sweden,50,"AWS, Linux, SQL",PhD,6,Education,2024-11-09,2024-12-20,1976,8.2,DeepTech Ventures +AI09270,Autonomous Systems Engineer,67394,EUR,57285,EN,FL,Austria,L,Portugal,50,"GCP, PyTorch, SQL",PhD,1,Consulting,2024-06-24,2024-07-31,1455,5.6,DeepTech Ventures +AI09271,Data Scientist,90125,EUR,76606,MI,FL,Germany,M,Germany,0,"Deep Learning, Computer Vision, Linux, SQL",PhD,3,Manufacturing,2024-02-27,2024-03-27,2164,6.7,Machine Intelligence Group +AI09272,Data Engineer,136268,USD,136268,SE,CT,Ireland,L,Ireland,50,"Kubernetes, PyTorch, SQL",PhD,5,Healthcare,2024-04-09,2024-05-26,521,8.3,DataVision Ltd +AI09273,Data Scientist,69814,USD,69814,MI,FL,Finland,M,Portugal,100,"Kubernetes, Linux, Azure, Scala, PyTorch",PhD,2,Healthcare,2024-08-16,2024-10-14,2026,7,TechCorp Inc +AI09274,Robotics Engineer,295783,USD,295783,EX,FT,Denmark,S,Germany,50,"Spark, NLP, Java, PyTorch",Associate,12,Energy,2024-06-03,2024-07-17,2053,10,Cloud AI Solutions +AI09275,Head of AI,85810,JPY,9439100,MI,FL,Japan,M,Japan,100,"Data Visualization, Azure, Python, Kubernetes, Linux",Associate,4,Automotive,2024-10-27,2024-11-23,2108,7.2,Cognitive Computing +AI09276,AI Research Scientist,197095,USD,197095,EX,FL,Finland,S,Finland,0,"R, Statistics, Java",PhD,10,Technology,2025-03-19,2025-04-05,1049,6.7,Advanced Robotics +AI09277,Head of AI,122788,USD,122788,SE,CT,Ireland,S,China,100,"Python, Scala, GCP, TensorFlow",PhD,7,Retail,2024-04-19,2024-06-19,2250,9.2,Algorithmic Solutions +AI09278,Research Scientist,124194,USD,124194,SE,PT,Sweden,S,Sweden,0,"Scala, Git, Docker, Data Visualization, NLP",Master,8,Gaming,2024-01-05,2024-02-24,1663,7.6,DataVision Ltd +AI09279,AI Consultant,58846,USD,58846,MI,CT,South Korea,S,New Zealand,100,"PyTorch, Kubernetes, Linux",PhD,3,Technology,2024-09-02,2024-10-29,1711,5.3,DataVision Ltd +AI09280,Data Engineer,106557,CHF,95901,MI,PT,Switzerland,M,Switzerland,100,"GCP, TensorFlow, Java",Bachelor,3,Telecommunications,2024-11-22,2024-12-10,2401,7.1,Autonomous Tech +AI09281,Research Scientist,128421,EUR,109158,SE,FL,France,S,Germany,0,"PyTorch, Linux, Tableau",Bachelor,9,Gaming,2025-02-26,2025-04-03,2027,7.1,Predictive Systems +AI09282,AI Product Manager,117576,EUR,99940,SE,FL,France,L,Philippines,0,"Python, Deep Learning, Tableau, Kubernetes, GCP",Associate,8,Energy,2024-09-30,2024-11-13,636,9.7,Future Systems +AI09283,AI Specialist,57593,USD,57593,EN,CT,Israel,L,Ukraine,100,"Python, Kubernetes, AWS",Bachelor,0,Real Estate,2024-09-14,2024-09-30,912,6.9,Algorithmic Solutions +AI09284,AI Software Engineer,212215,USD,212215,EX,FL,United States,S,United States,50,"Azure, Git, Hadoop, Spark",Bachelor,16,Finance,2024-10-06,2024-10-21,2111,8.6,TechCorp Inc +AI09285,AI Consultant,135399,CHF,121859,MI,CT,Switzerland,L,Switzerland,100,"Spark, TensorFlow, NLP, Kubernetes",PhD,3,Consulting,2024-04-04,2024-05-28,1618,9.2,Future Systems +AI09286,Machine Learning Researcher,166176,USD,166176,EX,FL,South Korea,L,South Korea,0,"Git, Python, Azure",Associate,15,Gaming,2024-08-08,2024-10-06,1302,7.1,DeepTech Ventures +AI09287,Machine Learning Engineer,144034,GBP,108026,SE,CT,United Kingdom,S,United Kingdom,0,"Git, Docker, R, Statistics",Associate,9,Finance,2024-06-15,2024-07-19,1279,9.7,Neural Networks Co +AI09288,Head of AI,61774,USD,61774,SE,FL,India,L,India,100,"R, Hadoop, Tableau, Java",Master,6,Real Estate,2024-12-05,2025-02-15,2230,7.1,Autonomous Tech +AI09289,Deep Learning Engineer,103881,EUR,88299,SE,FT,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,5,Consulting,2024-07-07,2024-07-27,893,5.4,TechCorp Inc +AI09290,Data Analyst,59689,EUR,50736,EN,CT,France,L,France,100,"Git, R, MLOps, Python",Associate,0,Retail,2024-11-04,2024-11-26,1476,6.6,DeepTech Ventures +AI09291,AI Architect,191160,SGD,248508,EX,FL,Singapore,S,Singapore,50,"R, TensorFlow, Spark, Git",PhD,12,Retail,2024-07-27,2024-09-14,928,6.8,Digital Transformation LLC +AI09292,Data Engineer,89134,USD,89134,MI,CT,United States,S,Netherlands,50,"PyTorch, NLP, Kubernetes, Deep Learning, GCP",Bachelor,3,Technology,2024-10-06,2024-12-08,2234,5.7,Future Systems +AI09293,AI Software Engineer,142040,CAD,177550,EX,CT,Canada,M,Canada,50,"Mathematics, R, Data Visualization, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-04-18,2024-05-31,1401,6.1,Digital Transformation LLC +AI09294,Computer Vision Engineer,67255,USD,67255,MI,PT,Sweden,S,Sweden,100,"Hadoop, Docker, Java, Tableau",PhD,2,Media,2025-04-24,2025-06-12,1670,6.1,Digital Transformation LLC +AI09295,Deep Learning Engineer,186135,USD,186135,EX,FT,Israel,M,Singapore,50,"Hadoop, R, Python, TensorFlow, PyTorch",Master,14,Retail,2024-03-17,2024-04-16,1967,9.8,DeepTech Ventures +AI09296,Machine Learning Engineer,53611,USD,53611,EN,FT,Finland,M,United States,0,"Scala, Python, Deep Learning, Spark, Git",Bachelor,0,Automotive,2024-07-22,2024-08-24,1846,6,Predictive Systems +AI09297,Deep Learning Engineer,94103,USD,94103,MI,FL,Sweden,M,Sweden,100,"Scala, SQL, MLOps, Data Visualization",PhD,3,Gaming,2025-04-20,2025-05-23,1959,8.2,AI Innovations +AI09298,AI Specialist,87733,SGD,114053,EN,FT,Singapore,L,Singapore,100,"Spark, Linux, SQL",Associate,0,Finance,2024-01-02,2024-02-29,632,5.9,Algorithmic Solutions +AI09299,Data Engineer,128376,USD,128376,MI,PT,Denmark,M,Denmark,100,"Python, SQL, PyTorch",Master,2,Healthcare,2024-01-22,2024-03-01,985,8.7,Machine Intelligence Group +AI09300,Head of AI,85553,EUR,72720,MI,FL,Germany,L,Germany,0,"Spark, TensorFlow, Tableau",Master,2,Media,2025-04-23,2025-05-27,934,6.8,DeepTech Ventures +AI09301,Robotics Engineer,165398,EUR,140588,EX,PT,Germany,S,Germany,0,"GCP, Kubernetes, SQL, Deep Learning",Master,10,Real Estate,2025-04-05,2025-05-31,2215,9.7,Autonomous Tech +AI09302,AI Product Manager,111102,GBP,83327,SE,FT,United Kingdom,S,United Kingdom,50,"GCP, Scala, Linux",Bachelor,9,Finance,2024-12-25,2025-01-18,2257,5.5,Cloud AI Solutions +AI09303,Machine Learning Researcher,259032,EUR,220177,EX,FT,Netherlands,L,Netherlands,50,"Python, SQL, R",Associate,18,Government,2025-04-20,2025-07-01,2247,9.6,TechCorp Inc +AI09304,Machine Learning Researcher,64774,EUR,55058,MI,FL,Austria,S,Austria,0,"PyTorch, Hadoop, Computer Vision",PhD,3,Education,2025-02-25,2025-05-06,1421,7.3,Neural Networks Co +AI09305,Data Engineer,221161,EUR,187987,EX,FT,Germany,M,Australia,50,"Computer Vision, TensorFlow, Kubernetes",Bachelor,19,Healthcare,2024-12-24,2025-01-19,725,6.8,Cognitive Computing +AI09306,Deep Learning Engineer,240461,AUD,324622,EX,FT,Australia,L,Australia,50,"Git, SQL, Statistics, Linux",Bachelor,18,Healthcare,2025-03-13,2025-05-14,1914,9,Smart Analytics +AI09307,Data Scientist,95043,SGD,123556,MI,FL,Singapore,S,Singapore,50,"Python, TensorFlow, Tableau",PhD,2,Manufacturing,2024-08-02,2024-10-14,2189,9.3,Advanced Robotics +AI09308,AI Consultant,39308,USD,39308,EN,PT,South Korea,S,Poland,0,"Kubernetes, Git, Deep Learning, TensorFlow, Spark",Associate,1,Transportation,2024-05-06,2024-06-20,1885,7.6,Predictive Systems +AI09309,Machine Learning Engineer,118281,USD,118281,SE,FT,South Korea,L,South Korea,100,"Docker, R, Statistics, Hadoop, GCP",Associate,9,Real Estate,2024-06-06,2024-08-05,2323,7.8,DataVision Ltd +AI09310,Data Analyst,107506,EUR,91380,MI,FT,Netherlands,M,Ireland,100,"Docker, Python, Data Visualization",PhD,3,Education,2024-07-29,2024-09-08,2123,5.7,Smart Analytics +AI09311,AI Architect,161533,USD,161533,EX,FL,Ireland,L,Ireland,100,"Data Visualization, TensorFlow, Git, Deep Learning",Bachelor,14,Energy,2024-08-20,2024-09-29,2120,8,Smart Analytics +AI09312,Machine Learning Researcher,106952,EUR,90909,MI,FL,Germany,M,Germany,0,"Tableau, TensorFlow, Git, Kubernetes, Docker",Bachelor,4,Technology,2025-04-07,2025-05-12,1647,5,TechCorp Inc +AI09313,Machine Learning Researcher,117619,JPY,12938090,MI,PT,Japan,L,Japan,100,"NLP, Python, GCP, Deep Learning, MLOps",Associate,3,Manufacturing,2024-04-17,2024-06-20,1171,7.2,Predictive Systems +AI09314,AI Research Scientist,164714,USD,164714,SE,FT,United States,L,United States,50,"Tableau, Java, Kubernetes",Bachelor,7,Real Estate,2024-07-06,2024-08-17,511,8.5,Machine Intelligence Group +AI09315,AI Software Engineer,55967,USD,55967,EN,FT,South Korea,M,South Korea,50,"Python, NLP, Mathematics",Associate,1,Media,2025-04-21,2025-05-15,2102,5.3,Autonomous Tech +AI09316,Research Scientist,48225,EUR,40991,EN,FT,Germany,S,Germany,100,"Azure, AWS, GCP, Git",PhD,1,Transportation,2024-04-11,2024-05-03,1919,5.3,Machine Intelligence Group +AI09317,Machine Learning Researcher,99314,USD,99314,MI,CT,United States,S,United States,50,"Statistics, Git, Kubernetes",Master,2,Automotive,2024-08-26,2024-10-06,1365,7,Quantum Computing Inc +AI09318,Research Scientist,61925,CAD,77406,MI,FT,Canada,S,Canada,50,"Git, Azure, Tableau, MLOps",Master,4,Finance,2024-08-06,2024-09-29,2038,9.6,Future Systems +AI09319,AI Research Scientist,64161,SGD,83409,EN,CT,Singapore,M,Singapore,100,"GCP, Hadoop, Docker, Computer Vision",Bachelor,0,Government,2024-09-17,2024-10-15,1222,7.1,Machine Intelligence Group +AI09320,Machine Learning Engineer,59904,USD,59904,SE,CT,China,L,China,100,"Kubernetes, Scala, Tableau",Bachelor,8,Manufacturing,2024-12-26,2025-02-28,942,9.9,Digital Transformation LLC +AI09321,AI Architect,84843,EUR,72117,MI,CT,Austria,L,Austria,50,"PyTorch, Git, Scala",Master,2,Media,2024-02-17,2024-03-11,1296,7.5,Autonomous Tech +AI09322,NLP Engineer,116882,EUR,99350,MI,FL,Netherlands,M,Ukraine,100,"Java, Kubernetes, Azure, Computer Vision",Associate,2,Transportation,2024-03-22,2024-05-14,893,7.7,Autonomous Tech +AI09323,Robotics Engineer,41992,USD,41992,MI,FT,India,L,India,0,"PyTorch, Deep Learning, Mathematics, Spark",Bachelor,4,Finance,2024-11-26,2025-01-09,556,6.6,Algorithmic Solutions +AI09324,Data Scientist,83559,USD,83559,MI,FT,Ireland,L,Singapore,100,"TensorFlow, SQL, Mathematics, Tableau, AWS",Bachelor,3,Government,2025-01-06,2025-02-19,1509,8.9,Advanced Robotics +AI09325,Machine Learning Engineer,165796,USD,165796,EX,FL,Ireland,L,Ireland,100,"Kubernetes, Docker, R, Tableau",Master,15,Government,2025-04-02,2025-04-28,1526,6.8,Quantum Computing Inc +AI09326,Data Scientist,27209,USD,27209,MI,PT,India,S,India,50,"Python, Computer Vision, Data Visualization, TensorFlow, Docker",PhD,2,Transportation,2024-06-06,2024-07-31,627,6.7,Neural Networks Co +AI09327,AI Specialist,238785,EUR,202967,EX,FT,France,L,Ghana,50,"Azure, Python, TensorFlow, MLOps, Computer Vision",PhD,19,Automotive,2024-05-14,2024-06-21,1303,9.7,Predictive Systems +AI09328,AI Specialist,36971,USD,36971,SE,PT,India,S,Argentina,0,"AWS, Tableau, Spark, Mathematics, Computer Vision",PhD,5,Education,2024-03-14,2024-04-06,1849,5.7,Cloud AI Solutions +AI09329,Deep Learning Engineer,281022,USD,281022,EX,FT,Norway,S,Netherlands,100,"Python, Data Visualization, Spark",PhD,12,Retail,2025-04-18,2025-06-15,1583,7,Predictive Systems +AI09330,AI Architect,69740,JPY,7671400,EN,CT,Japan,S,Japan,0,"NLP, GCP, Mathematics, Kubernetes",PhD,1,Education,2024-02-13,2024-04-14,1821,9.8,Algorithmic Solutions +AI09331,AI Architect,117773,USD,117773,MI,FT,United States,M,United States,100,"Hadoop, PyTorch, GCP, AWS",PhD,4,Real Estate,2025-02-28,2025-03-25,1720,6.3,Machine Intelligence Group +AI09332,Research Scientist,149573,USD,149573,EX,FT,Israel,S,Israel,0,"Python, GCP, Hadoop",Master,17,Government,2024-08-06,2024-10-03,1603,8,DeepTech Ventures +AI09333,Machine Learning Researcher,115785,GBP,86839,MI,CT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, Kubernetes, Scala, Hadoop",PhD,4,Automotive,2024-09-18,2024-10-09,1354,5,Predictive Systems +AI09334,Head of AI,155051,JPY,17055610,EX,FT,Japan,S,Estonia,0,"Hadoop, GCP, Linux",Bachelor,14,Technology,2025-04-04,2025-06-02,2362,8,Autonomous Tech +AI09335,AI Software Engineer,69683,SGD,90588,EN,CT,Singapore,M,Singapore,50,"NLP, SQL, Kubernetes",Bachelor,0,Gaming,2024-05-20,2024-06-10,860,5.3,Autonomous Tech +AI09336,Machine Learning Engineer,63898,USD,63898,EN,CT,Ireland,S,Ireland,100,"Mathematics, MLOps, GCP",Associate,0,Technology,2024-07-13,2024-08-04,1335,6.3,Digital Transformation LLC +AI09337,NLP Engineer,91901,USD,91901,MI,FL,Sweden,M,Sweden,0,"PyTorch, Mathematics, Kubernetes",PhD,4,Finance,2024-06-28,2024-09-07,641,7.8,Autonomous Tech +AI09338,AI Consultant,59695,EUR,50741,EN,FT,France,S,Ghana,100,"R, GCP, PyTorch, AWS",Master,1,Automotive,2024-10-04,2024-10-29,1315,7,Future Systems +AI09339,Data Engineer,65038,GBP,48779,EN,PT,United Kingdom,S,United Kingdom,50,"Docker, Python, Computer Vision, R",Master,0,Real Estate,2024-06-03,2024-08-10,1902,8.5,AI Innovations +AI09340,AI Consultant,86847,USD,86847,MI,FT,Finland,M,Finland,100,"Scala, MLOps, Java",Bachelor,2,Real Estate,2025-03-20,2025-05-08,2066,9,Advanced Robotics +AI09341,Deep Learning Engineer,34236,USD,34236,MI,FT,China,M,China,0,"TensorFlow, R, Linux",Associate,4,Telecommunications,2024-04-18,2024-06-01,2369,5.6,AI Innovations +AI09342,AI Consultant,160503,EUR,136428,SE,FL,France,L,Australia,50,"AWS, Python, Data Visualization",Bachelor,8,Government,2024-12-05,2025-01-07,1991,7,Algorithmic Solutions +AI09343,Machine Learning Engineer,120317,USD,120317,SE,FT,Israel,M,Israel,50,"SQL, Docker, TensorFlow, Linux, Tableau",Bachelor,6,Education,2025-01-05,2025-02-20,1725,9.6,Neural Networks Co +AI09344,Principal Data Scientist,79295,EUR,67401,EN,PT,France,L,France,100,"GCP, SQL, Scala, Python",Master,0,Real Estate,2024-04-13,2024-06-15,2373,6.9,Quantum Computing Inc +AI09345,Principal Data Scientist,57136,EUR,48566,EN,PT,Austria,M,United States,50,"Linux, Scala, TensorFlow",Master,0,Real Estate,2024-02-23,2024-04-03,1669,6.7,Autonomous Tech +AI09346,Research Scientist,109133,USD,109133,SE,PT,Israel,M,Israel,0,"Java, R, Statistics, SQL",PhD,8,Telecommunications,2025-03-17,2025-05-02,2042,8.7,Smart Analytics +AI09347,Machine Learning Engineer,226278,CHF,203650,EX,FT,Switzerland,M,Switzerland,50,"Mathematics, Scala, Azure",PhD,15,Media,2025-01-20,2025-03-29,1514,9.2,Autonomous Tech +AI09348,ML Ops Engineer,67762,USD,67762,EN,FT,Finland,S,Finland,100,"Kubernetes, Data Visualization, MLOps, Python",Associate,0,Gaming,2024-11-21,2024-12-10,1779,8.1,DeepTech Ventures +AI09349,Research Scientist,158626,USD,158626,SE,FT,Norway,S,Norway,0,"Python, Scala, Java, TensorFlow",PhD,9,Government,2024-06-23,2024-07-12,1918,5.6,Smart Analytics +AI09350,Research Scientist,35902,USD,35902,MI,FT,India,M,Philippines,0,"Linux, Spark, Data Visualization, Java, Mathematics",Bachelor,2,Finance,2024-05-30,2024-08-04,2143,6.3,Future Systems +AI09351,AI Specialist,199630,EUR,169686,EX,FL,France,S,France,100,"Linux, Hadoop, Data Visualization, MLOps",Associate,19,Retail,2024-03-14,2024-04-28,2431,6.4,Cognitive Computing +AI09352,ML Ops Engineer,34288,USD,34288,MI,PT,India,L,Austria,0,"Python, AWS, SQL, Data Visualization",Associate,3,Telecommunications,2024-12-29,2025-02-20,688,8.8,Autonomous Tech +AI09353,AI Consultant,64165,USD,64165,EN,PT,Finland,L,Finland,100,"Kubernetes, Deep Learning, Data Visualization, Python",Master,0,Healthcare,2024-02-23,2024-04-20,2185,5.9,Quantum Computing Inc +AI09354,AI Architect,68161,CAD,85201,EN,CT,Canada,L,Canada,100,"Scala, Azure, Statistics, Linux, PyTorch",PhD,1,Transportation,2024-08-25,2024-10-29,1318,5.2,Machine Intelligence Group +AI09355,Deep Learning Engineer,190540,AUD,257229,EX,PT,Australia,S,Australia,100,"SQL, Azure, Scala, Tableau, Spark",Associate,17,Automotive,2025-01-23,2025-02-11,1879,5.1,Digital Transformation LLC +AI09356,AI Consultant,145966,USD,145966,EX,FT,South Korea,S,South Korea,50,"PyTorch, TensorFlow, Python",Bachelor,13,Media,2024-10-09,2024-12-02,2054,8.6,Autonomous Tech +AI09357,AI Research Scientist,64339,USD,64339,MI,PT,South Korea,S,Belgium,0,"Java, R, Python, AWS",Associate,2,Consulting,2024-07-13,2024-08-18,632,6.7,Advanced Robotics +AI09358,Computer Vision Engineer,72089,GBP,54067,EN,FT,United Kingdom,L,Ireland,50,"Deep Learning, Scala, Statistics, Computer Vision, Docker",PhD,0,Finance,2025-02-18,2025-04-30,2314,6.2,TechCorp Inc +AI09359,Data Scientist,121917,USD,121917,MI,PT,Sweden,L,China,100,"PyTorch, Hadoop, Java, Kubernetes, MLOps",PhD,4,Finance,2024-01-15,2024-02-28,794,9.3,Advanced Robotics +AI09360,Computer Vision Engineer,62465,EUR,53095,EN,CT,Netherlands,M,Japan,0,"Python, AWS, Mathematics, SQL, Java",Associate,1,Energy,2024-01-29,2024-03-21,595,8.6,Autonomous Tech +AI09361,AI Consultant,120168,JPY,13218480,SE,PT,Japan,S,Japan,50,"Statistics, Computer Vision, Kubernetes, TensorFlow",Associate,9,Healthcare,2025-02-18,2025-04-10,781,9.7,Predictive Systems +AI09362,Data Scientist,74225,EUR,63091,MI,FL,France,S,France,100,"R, Git, Scala, Kubernetes",PhD,4,Manufacturing,2024-12-20,2025-02-05,524,7,DeepTech Ventures +AI09363,Head of AI,86630,USD,86630,SE,CT,Israel,S,Czech Republic,100,"Statistics, R, Kubernetes, Computer Vision, SQL",Bachelor,8,Education,2024-09-16,2024-11-19,2024,5.3,AI Innovations +AI09364,Data Analyst,45119,USD,45119,MI,FT,China,S,New Zealand,100,"Kubernetes, Python, Statistics, GCP",Master,4,Gaming,2024-09-15,2024-11-23,2360,5.9,DataVision Ltd +AI09365,Data Analyst,70424,USD,70424,SE,FL,China,M,China,100,"AWS, Docker, GCP, Python",Master,6,Manufacturing,2024-08-11,2024-09-30,1551,5.1,DeepTech Ventures +AI09366,Data Scientist,124107,EUR,105491,SE,PT,France,S,France,0,"Spark, Java, NLP, Computer Vision",Bachelor,7,Finance,2024-02-14,2024-03-08,1939,6.9,Machine Intelligence Group +AI09367,Machine Learning Researcher,104599,CHF,94139,MI,FL,Switzerland,S,Israel,0,"Hadoop, Scala, Deep Learning, NLP, TensorFlow",Master,2,Government,2024-07-05,2024-08-23,1948,9,TechCorp Inc +AI09368,AI Product Manager,130443,SGD,169576,SE,PT,Singapore,M,Singapore,50,"Deep Learning, MLOps, Git, SQL, Kubernetes",Bachelor,7,Finance,2024-09-18,2024-10-02,947,8.5,Cognitive Computing +AI09369,Machine Learning Engineer,51380,USD,51380,SE,PT,China,M,Turkey,100,"Linux, Spark, Kubernetes",Bachelor,7,Manufacturing,2024-04-27,2024-06-30,1994,7.2,Algorithmic Solutions +AI09370,ML Ops Engineer,55972,EUR,47576,EN,PT,France,S,Egypt,100,"Linux, Python, Deep Learning, AWS",Associate,0,Telecommunications,2024-01-13,2024-03-01,1786,6.9,Machine Intelligence Group +AI09371,AI Specialist,140112,EUR,119095,EX,PT,Austria,M,Kenya,100,"Linux, R, Data Visualization",PhD,10,Real Estate,2024-07-03,2024-08-18,991,6.3,DeepTech Ventures +AI09372,Research Scientist,77842,EUR,66166,EN,FL,Netherlands,M,Netherlands,100,"Statistics, Hadoop, Python",Master,1,Healthcare,2024-05-09,2024-07-14,1380,5,Cloud AI Solutions +AI09373,Data Analyst,143720,USD,143720,EX,FL,South Korea,M,Ukraine,50,"Scala, AWS, Azure, Computer Vision, Statistics",Associate,16,Technology,2024-06-09,2024-07-23,566,6.9,Cognitive Computing +AI09374,Machine Learning Engineer,93910,USD,93910,MI,CT,South Korea,L,Netherlands,100,"GCP, NLP, Data Visualization, Python, Linux",Master,2,Consulting,2024-12-31,2025-02-27,748,9.8,Autonomous Tech +AI09375,NLP Engineer,92622,JPY,10188420,MI,CT,Japan,M,Estonia,50,"Statistics, Kubernetes, R, Scala",Associate,2,Healthcare,2024-05-09,2024-06-26,508,8.6,Cognitive Computing +AI09376,Data Analyst,207950,USD,207950,EX,FL,Ireland,S,Portugal,0,"Hadoop, GCP, Statistics, Deep Learning",Bachelor,16,Gaming,2024-05-17,2024-06-21,823,5.1,Cognitive Computing +AI09377,AI Research Scientist,52390,CAD,65488,EN,FT,Canada,S,Ireland,50,"Deep Learning, Python, Docker",Master,0,Finance,2024-06-29,2024-08-19,818,8.7,Smart Analytics +AI09378,NLP Engineer,72765,EUR,61850,MI,FT,Germany,S,Germany,50,"AWS, Kubernetes, GCP, NLP",PhD,4,Telecommunications,2024-06-13,2024-08-25,604,9.9,Quantum Computing Inc +AI09379,Robotics Engineer,95125,EUR,80856,SE,PT,France,S,Turkey,0,"Python, Java, Kubernetes, TensorFlow, Docker",Master,7,Media,2024-09-06,2024-11-12,1188,6.3,DataVision Ltd +AI09380,Data Analyst,86783,USD,86783,EX,CT,China,S,China,50,"Kubernetes, Java, MLOps",Associate,10,Real Estate,2025-01-16,2025-02-23,1979,5.6,Predictive Systems +AI09381,Principal Data Scientist,195942,SGD,254725,EX,CT,Singapore,S,Singapore,50,"PyTorch, Python, Linux, Mathematics",Bachelor,18,Automotive,2024-02-24,2024-05-05,2119,9.8,Algorithmic Solutions +AI09382,AI Architect,88045,USD,88045,SE,PT,Finland,S,Finland,0,"AWS, Kubernetes, Java, GCP, Azure",Master,8,Media,2024-05-24,2024-06-10,1613,6.5,DataVision Ltd +AI09383,ML Ops Engineer,34080,USD,34080,EN,PT,China,S,China,100,"Python, Tableau, Statistics, Deep Learning",Associate,0,Telecommunications,2024-08-15,2024-08-30,858,6.4,Algorithmic Solutions +AI09384,Machine Learning Researcher,159791,AUD,215718,SE,CT,Australia,L,Australia,0,"TensorFlow, Mathematics, Data Visualization, Linux",Associate,9,Media,2024-11-05,2025-01-12,1415,5.4,Smart Analytics +AI09385,Computer Vision Engineer,82207,EUR,69876,MI,CT,Germany,M,Germany,100,"Kubernetes, Java, Docker, R, Statistics",Master,2,Telecommunications,2024-08-18,2024-10-28,2049,6.4,DataVision Ltd +AI09386,Computer Vision Engineer,121634,USD,121634,SE,CT,South Korea,M,Argentina,50,"R, SQL, Data Visualization",Master,6,Healthcare,2025-02-04,2025-03-25,1979,8.6,Smart Analytics +AI09387,AI Research Scientist,29142,USD,29142,EN,CT,India,L,India,0,"Linux, Hadoop, Data Visualization, Spark",Bachelor,1,Technology,2024-10-18,2024-11-13,2226,5.3,Advanced Robotics +AI09388,AI Software Engineer,62502,JPY,6875220,EN,PT,Japan,L,Japan,100,"Kubernetes, Python, Spark, Docker, Git",Bachelor,0,Gaming,2025-01-22,2025-03-06,1769,6.4,DeepTech Ventures +AI09389,NLP Engineer,106016,USD,106016,EX,PT,South Korea,S,South Korea,100,"Mathematics, Python, Statistics, Git, TensorFlow",Master,18,Energy,2025-03-19,2025-05-26,658,9,Algorithmic Solutions +AI09390,Machine Learning Engineer,223388,USD,223388,EX,FT,United States,S,United States,0,"Python, Spark, TensorFlow, GCP, PyTorch",Bachelor,13,Retail,2024-04-13,2024-05-02,776,7.7,Autonomous Tech +AI09391,AI Product Manager,260456,JPY,28650160,EX,CT,Japan,L,Poland,50,"Hadoop, Deep Learning, Tableau",Bachelor,13,Manufacturing,2024-04-11,2024-05-12,1344,6.3,Advanced Robotics +AI09392,Deep Learning Engineer,122043,AUD,164758,SE,FL,Australia,S,Malaysia,100,"SQL, R, Python, Statistics",PhD,9,Government,2025-04-14,2025-05-26,528,8.4,Autonomous Tech +AI09393,AI Software Engineer,79246,EUR,67359,MI,CT,Germany,S,Germany,50,"Kubernetes, Deep Learning, Java, Azure, R",Associate,4,Media,2025-01-18,2025-03-04,1975,8.8,AI Innovations +AI09394,AI Specialist,200872,GBP,150654,EX,PT,United Kingdom,L,Sweden,100,"Computer Vision, Statistics, Docker",Associate,14,Technology,2024-06-26,2024-09-05,2354,5.4,TechCorp Inc +AI09395,Head of AI,103261,AUD,139402,SE,FL,Australia,M,Australia,0,"Docker, SQL, Azure, AWS",Bachelor,5,Gaming,2025-03-11,2025-04-08,1989,10,Cloud AI Solutions +AI09396,AI Software Engineer,56852,USD,56852,EN,FT,Sweden,S,Sweden,50,"Git, Computer Vision, Data Visualization",Associate,1,Consulting,2024-02-26,2024-04-12,1249,8,Digital Transformation LLC +AI09397,Data Engineer,87803,AUD,118534,MI,CT,Australia,L,Australia,100,"PyTorch, GCP, Java, Docker, Tableau",Associate,4,Automotive,2024-10-23,2024-12-02,1156,7.5,TechCorp Inc +AI09398,ML Ops Engineer,63510,USD,63510,EN,FL,Israel,L,Israel,50,"SQL, Azure, TensorFlow, Computer Vision, R",Associate,1,Consulting,2025-04-14,2025-04-28,1830,7.1,DataVision Ltd +AI09399,Deep Learning Engineer,92068,USD,92068,EN,PT,United States,M,United States,50,"MLOps, Kubernetes, Python",Associate,1,Telecommunications,2024-10-03,2024-11-21,2475,6.3,Algorithmic Solutions +AI09400,NLP Engineer,75818,GBP,56864,MI,FL,United Kingdom,S,United States,100,"PyTorch, Java, AWS, GCP, TensorFlow",Associate,4,Technology,2025-01-17,2025-03-13,2063,6.9,Autonomous Tech +AI09401,Deep Learning Engineer,120141,USD,120141,SE,PT,Ireland,S,Malaysia,0,"Java, GCP, Python, Linux, MLOps",PhD,6,Media,2024-04-14,2024-06-16,2469,7.6,Quantum Computing Inc +AI09402,Principal Data Scientist,77151,USD,77151,MI,PT,Sweden,S,Sweden,50,"Linux, Statistics, Java",PhD,2,Automotive,2025-03-17,2025-05-05,1385,5.3,AI Innovations +AI09403,Principal Data Scientist,69108,USD,69108,MI,CT,South Korea,S,Turkey,0,"Python, GCP, TensorFlow, Data Visualization",Master,4,Consulting,2024-04-28,2024-05-23,2108,6.2,Quantum Computing Inc +AI09404,Machine Learning Researcher,209966,EUR,178471,EX,PT,France,L,Finland,100,"Linux, Azure, Kubernetes, Docker, Git",PhD,19,Real Estate,2024-06-30,2024-08-14,937,9,Algorithmic Solutions +AI09405,Robotics Engineer,75780,USD,75780,EN,PT,Ireland,M,Ireland,0,"MLOps, PyTorch, Mathematics, Kubernetes",Associate,1,Retail,2024-03-28,2024-05-03,1240,9.9,Future Systems +AI09406,AI Product Manager,59033,AUD,79695,EN,PT,Australia,L,Egypt,50,"Python, NLP, Tableau, TensorFlow",Master,0,Gaming,2025-02-01,2025-03-29,1668,8.1,Future Systems +AI09407,Data Engineer,173659,USD,173659,EX,CT,Ireland,M,Ireland,100,"Hadoop, Statistics, TensorFlow, Spark",PhD,15,Technology,2024-11-21,2025-01-29,1737,7.4,DataVision Ltd +AI09408,AI Architect,218617,USD,218617,EX,FT,Ireland,S,Ireland,50,"MLOps, Git, AWS, Docker",Bachelor,18,Consulting,2025-04-13,2025-06-08,878,6.9,AI Innovations +AI09409,AI Consultant,51900,USD,51900,SE,PT,India,M,South Africa,100,"Git, Python, MLOps",Bachelor,6,Gaming,2024-04-11,2024-06-06,1782,8.4,Digital Transformation LLC +AI09410,Autonomous Systems Engineer,83722,EUR,71164,MI,FT,Germany,S,Germany,100,"Git, Linux, Data Visualization",PhD,4,Real Estate,2025-04-14,2025-06-16,1176,9.3,TechCorp Inc +AI09411,ML Ops Engineer,64831,CAD,81039,EN,FL,Canada,S,Kenya,50,"NLP, Python, SQL, Linux, GCP",Master,1,Transportation,2024-05-16,2024-07-20,1981,5.5,Algorithmic Solutions +AI09412,AI Research Scientist,80478,JPY,8852580,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, GCP, Java, PyTorch",Master,1,Telecommunications,2024-06-15,2024-08-12,1157,9.6,AI Innovations +AI09413,Machine Learning Engineer,152682,CHF,137414,MI,FL,Switzerland,M,Switzerland,100,"Linux, Docker, R",Bachelor,2,Education,2025-01-22,2025-02-08,2221,7.8,Neural Networks Co +AI09414,Research Scientist,73388,USD,73388,EN,FT,Israel,M,Israel,0,"Hadoop, GCP, Data Visualization, Java, MLOps",Bachelor,0,Education,2025-01-22,2025-03-13,998,7.2,Advanced Robotics +AI09415,Head of AI,191472,AUD,258487,EX,FL,Australia,S,Belgium,0,"Azure, Java, TensorFlow, Linux, Git",Master,18,Automotive,2024-12-07,2025-02-06,654,9.3,Cognitive Computing +AI09416,AI Architect,111011,USD,111011,SE,FT,South Korea,M,South Korea,0,"Data Visualization, Linux, Python, Statistics, Mathematics",Master,5,Energy,2025-03-16,2025-05-28,2347,6.7,Digital Transformation LLC +AI09417,Machine Learning Researcher,61781,JPY,6795910,EN,FT,Japan,M,Singapore,100,"Linux, GCP, MLOps",Bachelor,0,Retail,2025-04-08,2025-05-21,548,8.5,DataVision Ltd +AI09418,NLP Engineer,194729,EUR,165520,EX,FT,France,M,France,50,"Mathematics, Java, Data Visualization",Master,13,Consulting,2024-08-04,2024-09-18,510,8.4,Quantum Computing Inc +AI09419,AI Product Manager,100526,EUR,85447,MI,CT,Netherlands,S,Netherlands,100,"Scala, Docker, Data Visualization",Master,3,Media,2024-06-04,2024-07-03,1421,7.6,DataVision Ltd +AI09420,Data Analyst,92755,USD,92755,MI,CT,Israel,L,Israel,0,"SQL, PyTorch, Azure, Git, R",Master,4,Finance,2024-08-15,2024-10-19,2437,9.7,Cloud AI Solutions +AI09421,Robotics Engineer,97289,GBP,72967,SE,PT,United Kingdom,S,United Kingdom,50,"NLP, AWS, Java",Bachelor,8,Automotive,2024-09-12,2024-09-30,1299,5.1,Autonomous Tech +AI09422,Machine Learning Engineer,153741,USD,153741,EX,FL,South Korea,L,South Korea,100,"Java, Deep Learning, Data Visualization",Bachelor,10,Retail,2024-09-19,2024-10-23,1707,6.7,DeepTech Ventures +AI09423,Head of AI,157987,SGD,205383,EX,CT,Singapore,M,Singapore,50,"Azure, Docker, Tableau",Bachelor,18,Healthcare,2024-02-18,2024-03-14,2161,9.1,Advanced Robotics +AI09424,AI Architect,120516,CHF,108464,MI,PT,Switzerland,M,Norway,50,"Linux, SQL, Computer Vision, Kubernetes",Master,3,Telecommunications,2024-08-26,2024-09-20,657,5.5,DataVision Ltd +AI09425,AI Specialist,203853,EUR,173275,EX,PT,Netherlands,L,Netherlands,50,"Spark, Scala, GCP",PhD,18,Real Estate,2024-03-20,2024-04-27,1169,7.2,Future Systems +AI09426,Data Scientist,142413,USD,142413,SE,CT,Finland,M,Finland,100,"TensorFlow, Python, Scala, Azure, MLOps",Associate,7,Retail,2024-12-04,2025-01-10,1806,8.3,Neural Networks Co +AI09427,Head of AI,173201,CHF,155881,SE,FL,Switzerland,S,Switzerland,100,"Computer Vision, Hadoop, Python",PhD,6,Finance,2024-07-02,2024-07-28,1290,8.9,Machine Intelligence Group +AI09428,Autonomous Systems Engineer,204387,CAD,255484,EX,FL,Canada,S,Thailand,50,"Computer Vision, TensorFlow, NLP, Python, Data Visualization",Associate,13,Government,2025-01-08,2025-02-03,1275,5.7,Algorithmic Solutions +AI09429,AI Specialist,24626,USD,24626,EN,PT,India,S,India,50,"Azure, Spark, SQL, Docker, Hadoop",Bachelor,0,Energy,2024-10-25,2024-12-14,2213,6.7,Cognitive Computing +AI09430,Data Engineer,30632,USD,30632,MI,FL,China,S,United States,100,"Docker, Python, GCP, TensorFlow, AWS",Bachelor,3,Technology,2025-02-03,2025-03-09,2442,7.1,Cognitive Computing +AI09431,Data Scientist,51880,CAD,64850,EN,FT,Canada,S,Canada,0,"R, PyTorch, Hadoop",PhD,1,Government,2024-11-23,2025-01-16,1334,8.9,Quantum Computing Inc +AI09432,Autonomous Systems Engineer,105546,USD,105546,SE,CT,Ireland,M,Ireland,0,"Data Visualization, Mathematics, Java, Computer Vision, Scala",Bachelor,5,Manufacturing,2024-07-06,2024-08-07,1958,9.4,TechCorp Inc +AI09433,AI Product Manager,156352,EUR,132899,EX,FT,France,S,France,100,"R, Scala, Computer Vision",Associate,18,Consulting,2024-09-17,2024-10-20,1481,7.5,TechCorp Inc +AI09434,Autonomous Systems Engineer,82869,USD,82869,MI,PT,Sweden,S,Sweden,0,"Hadoop, MLOps, Git",Master,4,Gaming,2024-04-10,2024-06-07,2048,5.3,AI Innovations +AI09435,Robotics Engineer,249284,EUR,211891,EX,PT,Germany,L,Finland,50,"Data Visualization, Hadoop, Statistics",Master,10,Education,2025-02-17,2025-04-19,1549,6.4,DeepTech Ventures +AI09436,AI Consultant,143332,EUR,121832,EX,FT,France,S,South Africa,50,"TensorFlow, Computer Vision, MLOps, Tableau, Kubernetes",Master,12,Telecommunications,2024-03-27,2024-05-14,1786,5.1,Cognitive Computing +AI09437,Data Analyst,102445,USD,102445,MI,CT,Denmark,S,Denmark,50,"SQL, Scala, AWS",Master,3,Consulting,2024-12-01,2025-02-06,1144,8.9,Predictive Systems +AI09438,Computer Vision Engineer,95141,CAD,118926,SE,PT,Canada,S,Netherlands,0,"SQL, PyTorch, R, Mathematics",Bachelor,5,Gaming,2024-07-05,2024-08-10,1531,9.4,Autonomous Tech +AI09439,Computer Vision Engineer,85527,EUR,72698,MI,FL,France,S,France,0,"Linux, R, Statistics, Kubernetes",Bachelor,2,Healthcare,2024-02-19,2024-04-28,543,9.9,DataVision Ltd +AI09440,Autonomous Systems Engineer,84275,EUR,71634,MI,CT,Austria,L,Austria,100,"Git, Linux, Python",Master,4,Healthcare,2024-11-01,2024-11-23,1865,6.5,Digital Transformation LLC +AI09441,Data Analyst,171765,USD,171765,EX,FL,Finland,S,Finland,100,"Tableau, NLP, Hadoop, Python",Master,10,Manufacturing,2024-07-29,2024-08-21,2398,6.2,Cognitive Computing +AI09442,Robotics Engineer,47657,USD,47657,MI,FT,China,L,China,0,"Computer Vision, Kubernetes, Java",Bachelor,4,Transportation,2025-04-26,2025-07-06,1427,6.5,Cloud AI Solutions +AI09443,Robotics Engineer,54748,USD,54748,EN,PT,Israel,S,Israel,50,"PyTorch, AWS, Data Visualization, GCP",Master,0,Education,2024-05-28,2024-07-31,2405,7.4,Future Systems +AI09444,Data Scientist,47134,AUD,63631,EN,FL,Australia,S,United Kingdom,50,"NLP, Statistics, Kubernetes, Python, GCP",PhD,0,Healthcare,2024-06-28,2024-08-26,613,6.1,DataVision Ltd +AI09445,ML Ops Engineer,84635,AUD,114257,MI,CT,Australia,L,Australia,100,"Kubernetes, SQL, Java, Git",PhD,3,Technology,2024-03-25,2024-05-30,1487,5.6,Future Systems +AI09446,ML Ops Engineer,84203,EUR,71573,MI,FL,France,L,France,100,"PyTorch, Mathematics, Scala",PhD,3,Real Estate,2025-02-26,2025-04-17,2353,6.5,Predictive Systems +AI09447,AI Product Manager,105870,EUR,89990,MI,PT,Netherlands,L,Netherlands,100,"Python, Linux, TensorFlow, Hadoop, PyTorch",Bachelor,4,Automotive,2024-07-29,2024-10-04,1615,5.4,DataVision Ltd +AI09448,AI Architect,66252,USD,66252,EX,CT,China,M,Russia,0,"Statistics, PyTorch, Tableau",Master,16,Healthcare,2024-11-30,2024-12-26,897,9.8,Neural Networks Co +AI09449,Data Engineer,91263,USD,91263,MI,FT,Finland,M,Finland,0,"GCP, PyTorch, Deep Learning, Mathematics, Computer Vision",Master,4,Finance,2024-10-01,2024-11-09,1366,7.7,Digital Transformation LLC +AI09450,Machine Learning Researcher,69243,USD,69243,EN,FT,Israel,M,Israel,50,"Azure, Python, SQL, Tableau, TensorFlow",Master,0,Manufacturing,2024-10-10,2024-12-16,689,6.2,TechCorp Inc +AI09451,Principal Data Scientist,137522,USD,137522,SE,PT,Ireland,M,France,100,"AWS, Tableau, Python",Bachelor,7,Government,2024-07-07,2024-07-28,709,6.8,Digital Transformation LLC +AI09452,NLP Engineer,266422,GBP,199817,EX,FT,United Kingdom,L,United Kingdom,50,"R, AWS, Data Visualization",PhD,11,Gaming,2024-03-29,2024-05-03,817,7.1,DeepTech Ventures +AI09453,Machine Learning Researcher,199823,EUR,169850,EX,PT,France,S,France,50,"Java, MLOps, GCP, AWS, PyTorch",Associate,12,Media,2024-02-25,2024-03-31,2329,6.6,Machine Intelligence Group +AI09454,NLP Engineer,69686,USD,69686,EN,CT,Ireland,M,Ireland,100,"Data Visualization, SQL, NLP, Kubernetes, Python",Associate,0,Real Estate,2025-01-25,2025-02-15,1109,7,Autonomous Tech +AI09455,Principal Data Scientist,173317,USD,173317,EX,FT,Denmark,S,Denmark,50,"TensorFlow, Scala, Statistics",PhD,18,Technology,2024-12-17,2025-02-23,1801,8.7,Future Systems +AI09456,Robotics Engineer,181014,EUR,153862,EX,FT,Austria,S,Austria,0,"Kubernetes, GCP, Python, Mathematics",PhD,18,Retail,2024-11-16,2025-01-05,1255,6,Predictive Systems +AI09457,AI Research Scientist,262405,USD,262405,EX,PT,Finland,L,Finland,0,"Deep Learning, Python, Azure, SQL",Master,19,Finance,2024-03-31,2024-05-27,2116,8.8,Machine Intelligence Group +AI09458,Data Engineer,109773,JPY,12075030,MI,FT,Japan,M,Vietnam,50,"Python, Tableau, Computer Vision",Bachelor,2,Gaming,2025-01-06,2025-02-25,2433,5.7,TechCorp Inc +AI09459,Data Scientist,81338,CAD,101673,EN,FL,Canada,L,Canada,0,"MLOps, Data Visualization, AWS, Python, TensorFlow",Bachelor,1,Healthcare,2025-01-23,2025-03-30,550,7.2,DataVision Ltd +AI09460,AI Research Scientist,147302,SGD,191493,SE,PT,Singapore,M,Singapore,0,"SQL, AWS, Kubernetes, Hadoop",Associate,5,Education,2024-05-27,2024-07-17,1214,7.5,Advanced Robotics +AI09461,Data Scientist,89314,CAD,111643,MI,PT,Canada,L,Romania,0,"Python, TensorFlow, Data Visualization, Git, Statistics",PhD,3,Technology,2024-01-25,2024-03-12,590,9.3,DataVision Ltd +AI09462,Head of AI,131205,USD,131205,SE,CT,Ireland,L,Ireland,0,"R, Python, TensorFlow, Java",Associate,8,Finance,2024-10-17,2024-12-12,1799,7.1,Cognitive Computing +AI09463,ML Ops Engineer,236960,EUR,201416,EX,FT,Netherlands,S,Netherlands,50,"Data Visualization, R, Linux, Tableau",Associate,12,Media,2024-05-12,2024-07-10,1716,9.1,Neural Networks Co +AI09464,Research Scientist,70521,EUR,59943,EN,FL,Netherlands,M,Nigeria,50,"Git, Python, TensorFlow",Bachelor,1,Telecommunications,2024-09-23,2024-11-21,2406,9.2,Advanced Robotics +AI09465,NLP Engineer,22718,USD,22718,EN,CT,India,M,India,100,"Computer Vision, SQL, Python",PhD,1,Consulting,2025-04-28,2025-06-01,2464,6.6,AI Innovations +AI09466,Autonomous Systems Engineer,302715,USD,302715,EX,PT,Norway,L,New Zealand,0,"Tableau, Python, NLP, Git, MLOps",PhD,12,Technology,2025-01-28,2025-02-21,655,8.2,Future Systems +AI09467,Data Engineer,148771,USD,148771,SE,FL,Finland,L,Finland,100,"PyTorch, GCP, TensorFlow, AWS, Deep Learning",Master,8,Education,2024-12-09,2025-01-28,1688,9.1,Autonomous Tech +AI09468,Principal Data Scientist,168216,USD,168216,SE,CT,United States,M,United States,50,"GCP, Linux, Docker, Hadoop",Bachelor,6,Telecommunications,2024-12-07,2024-12-27,1732,8.8,DataVision Ltd +AI09469,AI Architect,83184,USD,83184,MI,FL,Sweden,L,Sweden,0,"MLOps, Data Visualization, Hadoop, Java, TensorFlow",Master,4,Real Estate,2024-06-03,2024-08-08,1248,8.2,Cloud AI Solutions +AI09470,Machine Learning Researcher,98439,USD,98439,SE,CT,South Korea,L,South Korea,100,"Python, Git, Computer Vision, NLP, R",Associate,8,Manufacturing,2024-07-25,2024-09-29,1463,7.7,TechCorp Inc +AI09471,ML Ops Engineer,164239,USD,164239,MI,PT,Denmark,L,Denmark,0,"Spark, Computer Vision, Kubernetes, Python, Linux",Bachelor,4,Gaming,2024-06-04,2024-07-26,802,8.3,Digital Transformation LLC +AI09472,AI Product Manager,96933,USD,96933,EN,PT,Norway,L,Nigeria,50,"Data Visualization, AWS, Hadoop, Computer Vision",Bachelor,1,Government,2025-04-21,2025-05-19,1741,8.3,Advanced Robotics +AI09473,Data Analyst,108451,USD,108451,EN,CT,Denmark,L,Denmark,0,"Python, Tableau, Azure",Bachelor,0,Retail,2024-03-30,2024-06-03,620,9,TechCorp Inc +AI09474,Robotics Engineer,63644,AUD,85919,EN,PT,Australia,S,Australia,100,"Docker, Azure, GCP, Python",Master,0,Manufacturing,2024-12-29,2025-02-06,886,6.7,DeepTech Ventures +AI09475,AI Specialist,199800,USD,199800,SE,PT,Norway,L,Norway,100,"GCP, Git, Java",PhD,8,Technology,2024-04-09,2024-05-30,716,6.2,AI Innovations +AI09476,Robotics Engineer,158584,USD,158584,SE,FL,Denmark,L,Denmark,100,"PyTorch, GCP, Scala, Linux, Deep Learning",Associate,8,Real Estate,2024-10-11,2024-11-13,1060,8.8,Future Systems +AI09477,Head of AI,200639,USD,200639,EX,FT,Israel,M,Israel,50,"Docker, Tableau, Python, GCP, Azure",Bachelor,17,Energy,2024-02-10,2024-04-03,2424,6.2,Quantum Computing Inc +AI09478,Research Scientist,76094,USD,76094,EX,FT,China,M,China,50,"GCP, R, NLP, Deep Learning",PhD,19,Automotive,2025-03-28,2025-06-06,612,9.8,Cloud AI Solutions +AI09479,AI Research Scientist,24147,USD,24147,MI,FT,India,S,India,50,"GCP, Computer Vision, Kubernetes, Linux, Data Visualization",Bachelor,3,Retail,2024-10-31,2024-12-02,950,9.5,Machine Intelligence Group +AI09480,AI Research Scientist,50123,EUR,42605,EN,PT,France,M,France,50,"Python, Spark, NLP, R",PhD,1,Manufacturing,2024-01-06,2024-03-10,540,5.5,Smart Analytics +AI09481,Robotics Engineer,110573,USD,110573,SE,CT,South Korea,L,South Korea,0,"NLP, GCP, Hadoop",Associate,7,Retail,2024-07-27,2024-09-07,798,5.2,DeepTech Ventures +AI09482,NLP Engineer,108897,USD,108897,MI,CT,Sweden,M,Norway,0,"Kubernetes, Python, TensorFlow, Docker, PyTorch",PhD,4,Automotive,2024-03-10,2024-05-06,715,8.6,Advanced Robotics +AI09483,Principal Data Scientist,330519,USD,330519,EX,PT,Norway,L,Norway,50,"Statistics, Azure, PyTorch, MLOps, SQL",Master,11,Consulting,2025-02-04,2025-03-03,544,5.8,Cloud AI Solutions +AI09484,Deep Learning Engineer,64196,JPY,7061560,EN,FL,Japan,S,Egypt,0,"Statistics, SQL, Data Visualization",Associate,0,Media,2025-03-23,2025-05-14,911,8,Machine Intelligence Group +AI09485,Data Analyst,112869,USD,112869,EX,FT,China,M,Latvia,50,"Scala, Python, NLP",PhD,19,Media,2025-04-28,2025-06-13,588,5.9,Quantum Computing Inc +AI09486,AI Software Engineer,64664,EUR,54964,EN,FL,Germany,M,Germany,100,"SQL, Hadoop, Kubernetes, PyTorch, AWS",Bachelor,0,Automotive,2024-11-30,2025-01-27,1161,7.8,Algorithmic Solutions +AI09487,AI Consultant,175674,JPY,19324140,SE,PT,Japan,L,Japan,0,"Hadoop, Java, PyTorch",Associate,7,Manufacturing,2024-01-31,2024-03-23,723,6.4,AI Innovations +AI09488,Data Analyst,95581,SGD,124255,MI,CT,Singapore,L,Hungary,0,"Git, Azure, Statistics, TensorFlow, Kubernetes",Associate,2,Manufacturing,2024-08-06,2024-09-03,1006,9.8,Advanced Robotics +AI09489,AI Software Engineer,158682,EUR,134880,SE,CT,Austria,L,Romania,50,"Data Visualization, Spark, Hadoop, MLOps, Scala",Associate,7,Telecommunications,2025-04-09,2025-05-22,2434,6.5,Advanced Robotics +AI09490,NLP Engineer,145879,SGD,189643,SE,PT,Singapore,M,Singapore,0,"Statistics, GCP, Azure",Associate,9,Energy,2024-06-29,2024-07-16,1866,6.5,Predictive Systems +AI09491,AI Specialist,196139,USD,196139,EX,CT,Israel,S,Denmark,50,"R, Mathematics, PyTorch, Kubernetes, Azure",PhD,11,Consulting,2024-11-13,2024-12-27,1979,9.4,AI Innovations +AI09492,Deep Learning Engineer,334470,USD,334470,EX,FL,Denmark,L,Denmark,100,"Git, Computer Vision, Deep Learning, Python, TensorFlow",PhD,13,Media,2025-01-26,2025-02-10,1594,7.8,Machine Intelligence Group +AI09493,Computer Vision Engineer,87626,USD,87626,MI,FT,Ireland,S,Ireland,100,"Java, Data Visualization, Hadoop, R",PhD,3,Technology,2024-12-15,2025-02-15,2127,6.5,Algorithmic Solutions +AI09494,Research Scientist,98110,USD,98110,EX,PT,China,S,China,0,"Azure, Python, Deep Learning",Associate,18,Healthcare,2024-06-23,2024-07-27,774,9.5,Predictive Systems +AI09495,AI Research Scientist,125951,CAD,157439,SE,PT,Canada,S,Brazil,100,"Linux, PyTorch, Kubernetes, Tableau, Git",Bachelor,9,Education,2024-05-31,2024-07-27,2495,7.2,DeepTech Ventures +AI09496,Data Analyst,86390,USD,86390,SE,FL,South Korea,M,Philippines,0,"Kubernetes, Mathematics, Scala, Docker",Bachelor,6,Healthcare,2024-06-06,2024-08-03,1154,7.5,Smart Analytics +AI09497,Data Engineer,28282,USD,28282,EN,FT,India,M,India,0,"R, Statistics, SQL, Azure",Associate,0,Technology,2025-04-05,2025-05-29,1646,5.6,Smart Analytics +AI09498,Data Scientist,145712,CHF,131141,MI,CT,Switzerland,M,South Africa,50,"Scala, Docker, NLP",Bachelor,2,Media,2024-11-01,2024-12-13,1336,6.5,Cognitive Computing +AI09499,Machine Learning Engineer,90645,EUR,77048,MI,CT,Germany,L,Germany,50,"Docker, SQL, GCP, TensorFlow",PhD,4,Healthcare,2025-02-08,2025-03-28,2137,8.3,Autonomous Tech +AI09500,Head of AI,82283,SGD,106968,EN,CT,Singapore,M,Singapore,0,"Spark, Hadoop, AWS, Data Visualization, Java",Associate,1,Gaming,2024-11-27,2024-12-20,1536,7.8,Algorithmic Solutions +AI09501,AI Architect,71045,USD,71045,EX,CT,India,M,India,100,"SQL, TensorFlow, MLOps, Docker, Python",Master,19,Manufacturing,2024-01-20,2024-03-20,717,5.9,Smart Analytics +AI09502,Data Scientist,62430,USD,62430,SE,CT,China,L,China,0,"Scala, Statistics, Python",Master,6,Technology,2024-10-23,2025-01-02,1617,9.3,Algorithmic Solutions +AI09503,Principal Data Scientist,106555,USD,106555,SE,FL,Finland,S,Finland,0,"R, Python, Hadoop",PhD,9,Finance,2024-04-07,2024-04-26,2418,7.8,DeepTech Ventures +AI09504,AI Software Engineer,71729,USD,71729,EN,PT,Finland,L,Finland,100,"SQL, Python, Azure",Master,0,Real Estate,2024-10-03,2024-11-30,1129,7.5,Autonomous Tech +AI09505,AI Architect,50504,EUR,42928,EN,FT,France,S,France,100,"TensorFlow, Statistics, MLOps, Tableau, Linux",Master,0,Telecommunications,2024-01-16,2024-03-05,808,9.4,Neural Networks Co +AI09506,Data Scientist,113850,AUD,153698,SE,CT,Australia,M,Australia,50,"SQL, Hadoop, Data Visualization",Master,9,Manufacturing,2024-11-18,2025-01-26,2066,9.5,TechCorp Inc +AI09507,NLP Engineer,315569,USD,315569,EX,PT,United States,L,United States,50,"Tableau, Scala, R, Statistics, TensorFlow",Associate,14,Technology,2024-04-22,2024-05-08,644,8,Future Systems +AI09508,Machine Learning Engineer,235397,GBP,176548,EX,FT,United Kingdom,L,Israel,0,"Java, SQL, Mathematics, Kubernetes",Master,15,Telecommunications,2025-02-05,2025-04-14,503,8.8,Cloud AI Solutions +AI09509,Machine Learning Engineer,126375,USD,126375,MI,FT,Denmark,L,Argentina,50,"Java, Kubernetes, TensorFlow, NLP",Master,4,Telecommunications,2024-03-02,2024-04-10,1297,9.7,DeepTech Ventures +AI09510,Research Scientist,64708,SGD,84120,EN,CT,Singapore,M,Switzerland,0,"Python, TensorFlow, Mathematics",Master,0,Education,2024-12-29,2025-03-06,2203,8.8,TechCorp Inc +AI09511,Research Scientist,128518,GBP,96389,SE,PT,United Kingdom,M,United Kingdom,100,"Hadoop, Data Visualization, Kubernetes, MLOps, AWS",Bachelor,7,Manufacturing,2024-10-15,2024-11-20,2401,7.7,Neural Networks Co +AI09512,Machine Learning Researcher,103052,USD,103052,SE,FL,South Korea,M,Vietnam,0,"Computer Vision, Spark, Tableau, Python",Associate,9,Telecommunications,2024-10-19,2024-12-15,1990,5.6,Future Systems +AI09513,Data Engineer,98700,EUR,83895,SE,FL,Netherlands,S,Finland,0,"Python, TensorFlow, Azure, Kubernetes",Master,8,Transportation,2024-01-29,2024-03-26,663,8.9,TechCorp Inc +AI09514,Principal Data Scientist,36797,USD,36797,MI,CT,India,L,Philippines,100,"AWS, Python, Kubernetes, Mathematics, Deep Learning",Bachelor,4,Energy,2024-11-23,2025-01-13,1780,8.4,Algorithmic Solutions +AI09515,Head of AI,171574,USD,171574,EX,PT,South Korea,S,South Korea,50,"NLP, Python, Spark, Linux, Java",Master,10,Finance,2024-04-17,2024-06-01,1404,8.9,DataVision Ltd +AI09516,Autonomous Systems Engineer,156283,JPY,17191130,SE,FT,Japan,M,Japan,50,"Data Visualization, R, PyTorch",Master,8,Real Estate,2024-11-29,2025-01-15,939,7.9,TechCorp Inc +AI09517,Robotics Engineer,66972,JPY,7366920,EN,FT,Japan,L,Argentina,50,"Scala, Git, Python, Mathematics, Azure",Associate,0,Consulting,2025-03-20,2025-04-27,769,8.7,Smart Analytics +AI09518,Computer Vision Engineer,122877,CHF,110589,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, MLOps, SQL, Java, PyTorch",PhD,2,Real Estate,2024-08-12,2024-10-19,1550,5.4,Neural Networks Co +AI09519,Data Analyst,245072,USD,245072,EX,FL,United States,L,United States,100,"Mathematics, R, Scala, Hadoop",Master,15,Technology,2024-12-27,2025-02-16,1935,7.8,Quantum Computing Inc +AI09520,Data Engineer,43038,USD,43038,MI,FT,China,S,China,100,"Spark, SQL, MLOps",PhD,2,Telecommunications,2024-04-08,2024-05-23,1670,8.3,Future Systems +AI09521,Autonomous Systems Engineer,111598,EUR,94858,MI,CT,France,L,France,0,"Computer Vision, Linux, SQL",Associate,4,Consulting,2025-02-18,2025-04-11,2363,8.2,Predictive Systems +AI09522,NLP Engineer,251849,JPY,27703390,EX,PT,Japan,L,Japan,0,"Scala, Docker, GCP",PhD,15,Transportation,2024-04-06,2024-05-17,2248,6.3,Digital Transformation LLC +AI09523,Data Analyst,110989,USD,110989,MI,CT,Norway,M,Hungary,0,"Mathematics, Azure, SQL",PhD,3,Government,2024-06-23,2024-08-23,1859,7.8,Autonomous Tech +AI09524,Data Engineer,127024,USD,127024,SE,CT,United States,S,Chile,0,"Java, MLOps, Spark",PhD,8,Gaming,2024-06-21,2024-08-02,1861,7.6,Quantum Computing Inc +AI09525,Research Scientist,332546,USD,332546,EX,FL,Denmark,L,Denmark,100,"MLOps, Azure, Tableau, Python, TensorFlow",Bachelor,14,Energy,2024-01-11,2024-03-04,1609,8.8,Future Systems +AI09526,Head of AI,133295,AUD,179948,SE,CT,Australia,M,Australia,0,"Python, AWS, NLP",Master,5,Consulting,2024-03-09,2024-05-05,2345,7.6,AI Innovations +AI09527,AI Research Scientist,86259,CAD,107824,MI,PT,Canada,L,Canada,50,"Tableau, Computer Vision, PyTorch",Associate,3,Education,2024-04-23,2024-06-08,1409,6.3,Predictive Systems +AI09528,Research Scientist,110503,USD,110503,MI,FL,Norway,M,Norway,0,"AWS, SQL, Tableau",Associate,3,Real Estate,2025-03-27,2025-04-11,1252,9,Algorithmic Solutions +AI09529,AI Architect,108797,EUR,92477,MI,CT,Netherlands,M,Netherlands,50,"AWS, Docker, Mathematics",Bachelor,4,Transportation,2024-08-13,2024-10-08,1802,8.4,Autonomous Tech +AI09530,Data Analyst,184018,USD,184018,EX,PT,South Korea,L,South Korea,0,"Statistics, Data Visualization, Azure, Linux",Master,17,Real Estate,2024-04-13,2024-05-21,1346,6.3,Digital Transformation LLC +AI09531,AI Software Engineer,147794,SGD,192132,SE,PT,Singapore,M,Singapore,100,"Python, TensorFlow, Kubernetes, Hadoop",Associate,6,Government,2024-08-27,2024-09-29,815,9.6,Future Systems +AI09532,Autonomous Systems Engineer,71774,JPY,7895140,MI,FL,Japan,S,Japan,50,"SQL, Git, Tableau",PhD,3,Manufacturing,2024-01-28,2024-03-05,1074,5.2,Cognitive Computing +AI09533,Data Scientist,219834,EUR,186859,EX,PT,Austria,M,Austria,0,"Linux, Statistics, MLOps",Master,18,Retail,2025-04-22,2025-05-12,1865,6.1,AI Innovations +AI09534,ML Ops Engineer,186565,USD,186565,EX,FL,South Korea,M,South Korea,100,"MLOps, Statistics, Python",PhD,17,Manufacturing,2024-07-10,2024-09-19,538,5.1,Digital Transformation LLC +AI09535,Data Analyst,27602,USD,27602,EN,FT,China,M,China,0,"R, Scala, SQL, PyTorch",Bachelor,1,Real Estate,2024-08-26,2024-09-10,885,6.1,Cognitive Computing +AI09536,Robotics Engineer,57129,USD,57129,EN,PT,Israel,S,Israel,50,"Spark, Python, SQL, Azure",PhD,1,Manufacturing,2025-03-20,2025-05-21,1666,8.3,Predictive Systems +AI09537,AI Consultant,22217,USD,22217,EN,FT,India,S,India,100,"SQL, GCP, Statistics, Mathematics, PyTorch",Master,0,Real Estate,2024-12-05,2025-01-06,1760,9.9,AI Innovations +AI09538,Head of AI,67864,USD,67864,EX,PT,China,S,Turkey,0,"Hadoop, Deep Learning, Docker, Mathematics, Scala",Associate,19,Retail,2024-04-21,2024-06-06,501,7.2,Autonomous Tech +AI09539,AI Research Scientist,84278,EUR,71636,EN,FT,Germany,L,Germany,50,"Git, Data Visualization, Scala, Azure, Statistics",PhD,0,Media,2024-08-12,2024-10-18,1838,9.5,Advanced Robotics +AI09540,Machine Learning Researcher,116369,USD,116369,SE,FL,South Korea,M,South Korea,0,"Docker, Linux, Spark, Mathematics, NLP",Associate,5,Technology,2024-11-02,2024-12-15,2197,7.7,Machine Intelligence Group +AI09541,AI Specialist,110779,USD,110779,SE,FT,Israel,M,Israel,0,"PyTorch, NLP, Java, R, Computer Vision",Associate,7,Government,2025-02-15,2025-04-23,1776,6.2,Neural Networks Co +AI09542,Data Scientist,285402,USD,285402,EX,FL,Denmark,S,Denmark,50,"TensorFlow, R, Docker, Mathematics, Data Visualization",Bachelor,11,Real Estate,2024-12-30,2025-01-13,1349,6,Quantum Computing Inc +AI09543,NLP Engineer,169619,USD,169619,SE,FT,Norway,M,Norway,100,"GCP, Linux, Docker, Python",PhD,9,Consulting,2024-03-19,2024-05-03,1063,9.2,Quantum Computing Inc +AI09544,Data Scientist,119460,USD,119460,EX,CT,South Korea,S,South Korea,50,"Scala, Kubernetes, Hadoop, Git, Computer Vision",Master,16,Government,2025-02-05,2025-03-06,1333,8.1,Quantum Computing Inc +AI09545,Data Engineer,141162,USD,141162,MI,CT,Denmark,M,Kenya,0,"MLOps, Python, TensorFlow, Kubernetes",PhD,2,Technology,2024-04-21,2024-06-06,947,8.8,Future Systems +AI09546,AI Specialist,125984,USD,125984,SE,PT,Israel,S,Israel,0,"Scala, Tableau, Mathematics, Azure",Associate,9,Gaming,2025-03-20,2025-05-22,1335,8,Future Systems +AI09547,Robotics Engineer,121116,EUR,102949,SE,FL,France,L,France,50,"GCP, Scala, MLOps",Bachelor,8,Media,2025-02-02,2025-03-16,2159,8.7,Cognitive Computing +AI09548,Robotics Engineer,116096,SGD,150925,MI,CT,Singapore,L,Malaysia,100,"Tableau, Python, Linux, Hadoop, TensorFlow",Associate,3,Energy,2024-03-28,2024-05-08,1044,5,Autonomous Tech +AI09549,AI Architect,120313,USD,120313,SE,PT,Ireland,M,Ireland,50,"Python, Docker, Data Visualization",PhD,6,Consulting,2024-06-23,2024-07-22,1587,8.8,TechCorp Inc +AI09550,AI Software Engineer,136464,USD,136464,SE,FT,Ireland,L,Ireland,100,"Tableau, Linux, TensorFlow",Master,9,Transportation,2024-10-11,2024-12-03,1255,9.4,Digital Transformation LLC +AI09551,AI Research Scientist,95934,USD,95934,MI,FT,Israel,M,Israel,50,"Python, Data Visualization, Java, Azure",Bachelor,2,Government,2024-12-20,2025-01-10,2205,9.7,Autonomous Tech +AI09552,AI Software Engineer,85570,CHF,77013,EN,FT,Switzerland,S,Switzerland,50,"Kubernetes, Computer Vision, Scala, Python",Master,0,Finance,2024-06-16,2024-07-11,2114,6.6,Autonomous Tech +AI09553,AI Research Scientist,61645,AUD,83221,EN,CT,Australia,L,Singapore,50,"Kubernetes, Python, Scala, Computer Vision, TensorFlow",Bachelor,1,Gaming,2024-11-06,2024-11-22,2038,5.6,Algorithmic Solutions +AI09554,NLP Engineer,83872,EUR,71291,MI,FL,Austria,S,Austria,100,"GCP, Scala, Deep Learning, SQL, Computer Vision",Associate,4,Consulting,2024-12-21,2025-01-07,1490,8.8,Quantum Computing Inc +AI09555,Computer Vision Engineer,102899,EUR,87464,MI,FL,Austria,L,Austria,50,"Spark, Scala, Deep Learning, Data Visualization, TensorFlow",PhD,3,Real Estate,2024-11-08,2024-11-30,2454,5.4,Algorithmic Solutions +AI09556,Data Engineer,71513,SGD,92967,EN,FL,Singapore,S,United Kingdom,100,"Scala, Linux, Computer Vision, Kubernetes, Git",Master,0,Manufacturing,2024-10-29,2024-12-10,1345,8.4,Predictive Systems +AI09557,Machine Learning Engineer,115012,USD,115012,SE,FT,South Korea,M,China,0,"Java, R, Kubernetes, Docker",Associate,9,Technology,2024-09-26,2024-11-16,984,5.2,Neural Networks Co +AI09558,Machine Learning Engineer,47215,CAD,59019,EN,PT,Canada,S,Canada,100,"Kubernetes, TensorFlow, Docker",Bachelor,0,Technology,2024-06-11,2024-08-20,1165,6.6,AI Innovations +AI09559,AI Specialist,118372,EUR,100616,SE,FL,France,L,Belgium,100,"Linux, Spark, AWS, Deep Learning",PhD,8,Energy,2025-04-08,2025-05-18,1304,5,Cloud AI Solutions +AI09560,Computer Vision Engineer,147836,AUD,199579,SE,CT,Australia,L,Australia,50,"Git, Kubernetes, SQL, GCP, Azure",Bachelor,8,Manufacturing,2024-04-16,2024-05-11,1611,5.6,DataVision Ltd +AI09561,Data Analyst,224535,EUR,190855,EX,FT,Germany,M,Germany,0,"Statistics, SQL, Azure, Python",Associate,15,Education,2025-02-06,2025-03-10,1882,6.8,Predictive Systems +AI09562,AI Software Engineer,138016,USD,138016,SE,CT,Denmark,M,Denmark,50,"Python, Scala, NLP, Git",Associate,8,Government,2024-08-27,2024-10-11,2108,9.4,Future Systems +AI09563,AI Consultant,93538,USD,93538,EN,PT,Norway,S,Norway,0,"Kubernetes, PyTorch, Statistics",PhD,0,Manufacturing,2024-10-26,2024-12-02,2026,9.3,TechCorp Inc +AI09564,Computer Vision Engineer,120674,USD,120674,SE,PT,United States,S,United States,50,"NLP, Docker, Git",PhD,9,Transportation,2024-10-26,2024-12-23,634,6.2,Autonomous Tech +AI09565,AI Architect,299206,CHF,269285,EX,CT,Switzerland,S,Chile,50,"PyTorch, Linux, MLOps, TensorFlow",PhD,11,Telecommunications,2025-04-22,2025-06-13,1150,8.1,Future Systems +AI09566,AI Specialist,128478,AUD,173445,SE,CT,Australia,L,Australia,50,"Python, TensorFlow, Azure",Master,6,Government,2024-04-17,2024-05-17,1949,7.9,Digital Transformation LLC +AI09567,Machine Learning Researcher,60265,AUD,81358,EN,PT,Australia,M,Australia,50,"Computer Vision, Java, MLOps",Master,1,Gaming,2024-03-16,2024-05-17,773,6.6,Autonomous Tech +AI09568,Computer Vision Engineer,279290,USD,279290,EX,PT,Denmark,S,Hungary,50,"Git, R, Scala, Docker, MLOps",Master,16,Government,2024-06-24,2024-07-23,1099,7.6,DataVision Ltd +AI09569,Computer Vision Engineer,110511,CAD,138139,SE,FT,Canada,L,Estonia,0,"Python, TensorFlow, Linux",Associate,9,Telecommunications,2025-01-08,2025-01-30,2403,9.4,Smart Analytics +AI09570,Data Analyst,108968,USD,108968,SE,CT,South Korea,S,South Korea,100,"PyTorch, Spark, Git, Kubernetes",Associate,8,Technology,2025-04-02,2025-04-22,1818,6.1,Machine Intelligence Group +AI09571,Data Engineer,81290,GBP,60968,MI,FT,United Kingdom,S,Switzerland,0,"Kubernetes, R, PyTorch",Bachelor,3,Consulting,2025-02-27,2025-04-14,1907,6.4,Predictive Systems +AI09572,Robotics Engineer,191881,CHF,172693,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, MLOps, Python, Spark",Bachelor,5,Transportation,2024-12-16,2025-01-19,1266,5.1,Predictive Systems +AI09573,Robotics Engineer,106589,CHF,95930,MI,FT,Switzerland,M,Switzerland,100,"Mathematics, AWS, Computer Vision, TensorFlow",Master,2,Manufacturing,2024-09-28,2024-10-21,1384,6.9,Cognitive Computing +AI09574,Machine Learning Engineer,97626,USD,97626,MI,PT,Ireland,L,Austria,100,"Scala, PyTorch, MLOps",Bachelor,3,Telecommunications,2024-10-04,2024-11-26,2239,8.1,Autonomous Tech +AI09575,AI Architect,141618,USD,141618,MI,FT,Denmark,L,Italy,0,"Data Visualization, Scala, Docker, Python, TensorFlow",Master,2,Government,2024-02-18,2024-04-10,1654,5.2,Digital Transformation LLC +AI09576,Autonomous Systems Engineer,95458,EUR,81139,MI,FL,Netherlands,L,Argentina,0,"Linux, SQL, Java",Bachelor,4,Education,2025-03-25,2025-04-22,2104,6.8,AI Innovations +AI09577,Robotics Engineer,105315,CHF,94784,MI,FL,Switzerland,S,Vietnam,100,"Azure, Python, Linux",PhD,3,Technology,2025-03-22,2025-04-23,507,6.3,DataVision Ltd +AI09578,AI Specialist,71116,EUR,60449,MI,PT,Austria,S,Austria,50,"Mathematics, TensorFlow, Python, Computer Vision, Azure",Master,3,Finance,2025-01-11,2025-03-22,2210,6.9,DeepTech Ventures +AI09579,Autonomous Systems Engineer,82679,EUR,70277,EN,FT,Netherlands,L,China,0,"Scala, NLP, GCP",Associate,0,Automotive,2024-03-14,2024-04-12,1625,8.7,Algorithmic Solutions +AI09580,Machine Learning Engineer,177922,EUR,151234,EX,FT,Germany,S,Germany,0,"Data Visualization, Git, TensorFlow",Associate,12,Healthcare,2024-12-05,2025-01-23,1334,9.3,DeepTech Ventures +AI09581,Data Scientist,31465,USD,31465,EN,FT,India,L,India,0,"Scala, Linux, SQL, PyTorch",Master,1,Transportation,2024-05-23,2024-06-11,1808,6.1,DeepTech Ventures +AI09582,AI Specialist,114364,USD,114364,EN,FL,Denmark,L,Denmark,0,"AWS, NLP, Tableau, Docker",Bachelor,1,Finance,2024-08-24,2024-10-02,582,7.7,DeepTech Ventures +AI09583,Data Scientist,206549,USD,206549,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, MLOps",Associate,15,Gaming,2024-05-04,2024-06-07,2093,8,Neural Networks Co +AI09584,Computer Vision Engineer,112749,EUR,95837,SE,FL,Germany,M,Turkey,100,"Hadoop, Git, Computer Vision, R, Java",PhD,6,Education,2024-09-09,2024-11-10,2317,7.4,DataVision Ltd +AI09585,Machine Learning Researcher,97146,EUR,82574,MI,CT,France,M,France,50,"PyTorch, AWS, Hadoop, Azure, Deep Learning",PhD,2,Real Estate,2025-01-13,2025-01-27,1832,7.3,DeepTech Ventures +AI09586,Research Scientist,35698,USD,35698,SE,FL,India,S,India,0,"Linux, GCP, PyTorch, NLP, Scala",Associate,5,Media,2024-02-02,2024-04-10,2048,5.7,Future Systems +AI09587,AI Research Scientist,64209,USD,64209,EN,CT,Israel,M,Israel,100,"Tableau, GCP, Java",Master,1,Telecommunications,2024-07-22,2024-09-02,1711,6.1,Advanced Robotics +AI09588,Robotics Engineer,108749,USD,108749,EN,FT,United States,L,United States,100,"Mathematics, Python, TensorFlow, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-11-09,1228,7.8,DeepTech Ventures +AI09589,AI Research Scientist,78664,USD,78664,MI,CT,Sweden,M,Australia,50,"TensorFlow, Python, GCP, Deep Learning, NLP",Associate,4,Finance,2024-11-26,2024-12-31,1225,9.1,Predictive Systems +AI09590,Autonomous Systems Engineer,72106,SGD,93738,MI,CT,Singapore,S,Singapore,0,"Data Visualization, Python, AWS, GCP, TensorFlow",Associate,4,Government,2024-01-04,2024-03-10,2323,9.6,TechCorp Inc +AI09591,Deep Learning Engineer,41945,USD,41945,MI,FL,China,S,China,0,"TensorFlow, Deep Learning, Data Visualization, Hadoop",PhD,2,Technology,2024-11-01,2025-01-07,2002,5.6,DataVision Ltd +AI09592,AI Consultant,135711,USD,135711,SE,FL,Sweden,S,Sweden,100,"Docker, Tableau, GCP, PyTorch, Statistics",Master,8,Government,2024-11-23,2024-12-07,2244,7.9,Advanced Robotics +AI09593,NLP Engineer,311228,USD,311228,EX,FL,United States,L,United States,50,"Python, Computer Vision, Linux, Spark, TensorFlow",Bachelor,17,Gaming,2024-05-19,2024-06-25,1679,5.7,Neural Networks Co +AI09594,Deep Learning Engineer,80311,USD,80311,EN,FL,Denmark,S,Denmark,50,"TensorFlow, Kubernetes, Git",Master,1,Telecommunications,2024-07-30,2024-09-14,663,6.3,Advanced Robotics +AI09595,Computer Vision Engineer,140434,USD,140434,EX,CT,Finland,M,Finland,100,"Azure, Python, Docker",Associate,17,Real Estate,2024-04-03,2024-05-17,1737,8.8,Autonomous Tech +AI09596,AI Architect,242982,USD,242982,EX,FT,Norway,S,Norway,100,"Spark, NLP, Python, TensorFlow",Associate,10,Retail,2024-03-31,2024-06-11,2335,6.4,Digital Transformation LLC +AI09597,Deep Learning Engineer,71755,USD,71755,EN,PT,Finland,L,Finland,100,"Tableau, PyTorch, Deep Learning, Git, TensorFlow",PhD,1,Retail,2024-08-04,2024-10-03,2271,8.7,DeepTech Ventures +AI09598,AI Software Engineer,31328,USD,31328,MI,CT,India,L,India,100,"Git, Scala, Computer Vision",Master,2,Telecommunications,2024-09-25,2024-11-07,1426,6,TechCorp Inc +AI09599,Data Engineer,108210,USD,108210,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Deep Learning, Spark",Bachelor,9,Energy,2024-04-26,2024-06-04,925,8.1,AI Innovations +AI09600,NLP Engineer,127242,GBP,95432,SE,PT,United Kingdom,M,United Kingdom,100,"SQL, Kubernetes, Scala, AWS",Associate,9,Healthcare,2025-01-21,2025-04-03,1609,9.1,Algorithmic Solutions +AI09601,AI Software Engineer,122440,USD,122440,SE,CT,Finland,L,Finland,100,"Kubernetes, Spark, Hadoop, Git",Bachelor,7,Finance,2024-05-25,2024-06-20,1905,9.4,Smart Analytics +AI09602,Data Analyst,163000,USD,163000,EX,FT,Ireland,M,Belgium,100,"Scala, Linux, MLOps",Associate,17,Gaming,2025-01-09,2025-02-02,502,7.4,DataVision Ltd +AI09603,Machine Learning Researcher,238582,JPY,26244020,EX,FL,Japan,M,Japan,0,"Azure, Scala, Hadoop, Git",Master,12,Finance,2025-01-08,2025-02-10,773,7.3,AI Innovations +AI09604,ML Ops Engineer,56341,USD,56341,EN,PT,South Korea,M,South Korea,0,"SQL, Tableau, PyTorch",Bachelor,1,Media,2024-10-31,2024-12-01,815,7.9,TechCorp Inc +AI09605,ML Ops Engineer,82286,GBP,61715,EN,FL,United Kingdom,L,United Kingdom,50,"Java, Computer Vision, SQL, Deep Learning, PyTorch",Associate,1,Telecommunications,2025-02-24,2025-04-02,1160,7.2,TechCorp Inc +AI09606,ML Ops Engineer,206792,USD,206792,EX,FL,Norway,M,Norway,0,"Scala, GCP, PyTorch",Associate,10,Manufacturing,2024-08-27,2024-10-21,550,7.3,Smart Analytics +AI09607,Data Engineer,111725,EUR,94966,MI,PT,France,L,Russia,100,"Mathematics, MLOps, Data Visualization, Kubernetes",PhD,4,Real Estate,2024-07-24,2024-08-15,1981,5.9,Cloud AI Solutions +AI09608,Principal Data Scientist,256576,USD,256576,EX,FL,Finland,L,Ukraine,0,"Git, R, Computer Vision",Master,14,Finance,2024-04-28,2024-05-29,2329,8.6,Machine Intelligence Group +AI09609,NLP Engineer,157172,EUR,133596,EX,CT,France,S,France,100,"TensorFlow, Docker, Git",PhD,10,Manufacturing,2024-12-17,2025-02-24,703,7.4,AI Innovations +AI09610,Data Analyst,38565,USD,38565,MI,CT,India,L,India,50,"AWS, Computer Vision, SQL",Associate,3,Transportation,2024-09-16,2024-11-19,551,10,Cloud AI Solutions +AI09611,Principal Data Scientist,93643,CHF,84279,EN,FT,Switzerland,S,Egypt,0,"Python, Git, Computer Vision, Deep Learning, Linux",Associate,1,Healthcare,2024-11-15,2025-01-01,651,8.2,Cognitive Computing +AI09612,AI Product Manager,349386,CHF,314447,EX,PT,Switzerland,L,Switzerland,100,"Git, Tableau, TensorFlow",Associate,11,Retail,2024-10-02,2024-12-13,2214,9.4,Cloud AI Solutions +AI09613,ML Ops Engineer,135479,EUR,115157,EX,FT,Austria,S,Austria,50,"SQL, TensorFlow, Tableau, Hadoop, Spark",Bachelor,19,Telecommunications,2025-02-12,2025-04-19,2223,6.1,TechCorp Inc +AI09614,AI Architect,18474,USD,18474,EN,FL,India,S,Netherlands,50,"Git, Deep Learning, Scala, Java, Tableau",Master,1,Technology,2024-03-21,2024-05-07,1106,6.3,Quantum Computing Inc +AI09615,Deep Learning Engineer,84485,USD,84485,SE,FT,South Korea,M,South Korea,50,"TensorFlow, Python, Spark, SQL, AWS",Master,9,Telecommunications,2024-06-08,2024-06-25,1760,8.1,TechCorp Inc +AI09616,Data Engineer,108371,USD,108371,EN,PT,Denmark,L,Denmark,0,"AWS, Tableau, Hadoop",Bachelor,1,Energy,2024-07-29,2024-10-04,710,9.1,Algorithmic Solutions +AI09617,Data Analyst,115972,EUR,98576,SE,FL,Austria,L,Austria,0,"Deep Learning, GCP, Data Visualization, MLOps, NLP",Master,7,Government,2024-09-09,2024-10-17,1584,9.2,Quantum Computing Inc +AI09618,Computer Vision Engineer,107070,USD,107070,MI,CT,Norway,M,Norway,100,"Python, Docker, Azure, Spark",Bachelor,3,Retail,2024-02-09,2024-03-11,642,9.4,DataVision Ltd +AI09619,AI Consultant,63084,USD,63084,EN,FT,Sweden,L,Sweden,50,"Hadoop, Azure, Data Visualization, NLP",Master,0,Automotive,2024-06-20,2024-07-22,1427,5,Digital Transformation LLC +AI09620,Head of AI,152429,USD,152429,MI,CT,Denmark,L,Denmark,0,"TensorFlow, Mathematics, Azure, SQL",Associate,3,Retail,2024-09-18,2024-11-01,2456,9.6,Quantum Computing Inc +AI09621,Computer Vision Engineer,61740,USD,61740,SE,FT,India,L,Estonia,0,"Azure, Java, Deep Learning",PhD,6,Education,2024-05-26,2024-07-17,1435,7.1,Neural Networks Co +AI09622,Autonomous Systems Engineer,135651,USD,135651,SE,CT,Sweden,S,Sweden,50,"Mathematics, Python, TensorFlow, Tableau",Bachelor,5,Retail,2025-04-29,2025-06-07,626,7,Autonomous Tech +AI09623,Computer Vision Engineer,91734,USD,91734,MI,FT,Israel,L,Israel,50,"Scala, SQL, PyTorch, Spark",Associate,3,Transportation,2024-03-07,2024-04-03,2414,7.9,Digital Transformation LLC +AI09624,ML Ops Engineer,178754,USD,178754,SE,PT,United States,L,United States,0,"Python, Kubernetes, Spark, TensorFlow",Associate,7,Gaming,2024-03-28,2024-04-15,2228,9.3,DataVision Ltd +AI09625,Data Analyst,141292,USD,141292,SE,FL,Denmark,S,Denmark,50,"AWS, SQL, Data Visualization, Statistics, Git",Master,5,Energy,2024-12-03,2025-01-22,1969,7.3,Cloud AI Solutions +AI09626,Data Scientist,63976,CAD,79970,EN,FT,Canada,S,Egypt,0,"Spark, PyTorch, Statistics, Data Visualization, R",Associate,1,Technology,2024-08-20,2024-09-20,1847,6.2,Machine Intelligence Group +AI09627,Principal Data Scientist,172992,USD,172992,SE,FT,United States,L,United States,100,"TensorFlow, Python, Deep Learning",Bachelor,6,Healthcare,2024-01-05,2024-02-22,802,7,DeepTech Ventures +AI09628,Data Engineer,274237,USD,274237,EX,PT,Ireland,L,Ireland,50,"Docker, AWS, PyTorch, GCP",Master,12,Gaming,2024-08-27,2024-10-15,1234,8.1,AI Innovations +AI09629,Deep Learning Engineer,191469,USD,191469,EX,FT,Israel,M,Israel,50,"Python, Azure, Data Visualization, TensorFlow",PhD,13,Retail,2025-01-29,2025-02-12,543,6.7,Predictive Systems +AI09630,Research Scientist,203503,EUR,172978,EX,FT,Netherlands,L,Netherlands,50,"Python, AWS, Computer Vision, Linux, TensorFlow",Bachelor,19,Consulting,2025-02-27,2025-05-04,552,7.5,Digital Transformation LLC +AI09631,NLP Engineer,101614,EUR,86372,SE,PT,Austria,S,Austria,100,"Hadoop, Java, NLP, Deep Learning",PhD,6,Retail,2025-04-24,2025-06-07,1662,7.3,TechCorp Inc +AI09632,Machine Learning Engineer,72890,SGD,94757,EN,PT,Singapore,M,Chile,100,"TensorFlow, Kubernetes, Git",Master,0,Retail,2024-02-06,2024-04-12,2204,9.7,Smart Analytics +AI09633,Deep Learning Engineer,241369,USD,241369,EX,CT,Israel,L,Israel,50,"Computer Vision, Git, Mathematics",Master,11,Technology,2024-05-25,2024-08-03,1757,9.2,Algorithmic Solutions +AI09634,Data Analyst,80985,JPY,8908350,EN,PT,Japan,M,Japan,50,"Python, PyTorch, Spark, Mathematics, AWS",PhD,0,Technology,2024-03-16,2024-04-12,749,6.3,Machine Intelligence Group +AI09635,Computer Vision Engineer,48693,USD,48693,SE,FL,China,S,China,0,"Git, Python, NLP, Data Visualization",PhD,6,Healthcare,2024-02-09,2024-04-17,2083,8.9,Predictive Systems +AI09636,AI Software Engineer,120364,USD,120364,SE,FT,Ireland,M,Ireland,100,"Python, Tableau, MLOps, Azure, Computer Vision",PhD,6,Telecommunications,2024-08-20,2024-09-28,632,6.3,Cognitive Computing +AI09637,Data Analyst,119327,EUR,101428,SE,FL,France,M,Nigeria,100,"Mathematics, AWS, Tableau",Master,9,Education,2025-02-17,2025-04-26,1137,7.8,Autonomous Tech +AI09638,ML Ops Engineer,52959,USD,52959,EN,FL,Finland,S,Finland,0,"Java, MLOps, Python, Linux",Associate,1,Telecommunications,2024-11-07,2024-11-23,2153,9.6,DataVision Ltd +AI09639,Principal Data Scientist,44848,USD,44848,EN,PT,South Korea,S,South Korea,0,"Python, TensorFlow, Deep Learning, Linux, Computer Vision",Bachelor,1,Real Estate,2025-03-10,2025-05-20,615,8.8,Future Systems +AI09640,AI Software Engineer,279410,JPY,30735100,EX,CT,Japan,L,Japan,0,"R, Tableau, SQL, Computer Vision, Linux",Master,19,Healthcare,2024-09-30,2024-11-15,898,9.2,Neural Networks Co +AI09641,AI Product Manager,276943,USD,276943,EX,FL,Norway,S,Norway,0,"PyTorch, GCP, Statistics, Tableau",PhD,18,Automotive,2024-12-21,2025-02-03,1529,8.8,Future Systems +AI09642,Autonomous Systems Engineer,190274,USD,190274,SE,FT,Denmark,M,Denmark,0,"AWS, SQL, Kubernetes",Associate,9,Telecommunications,2024-01-12,2024-01-27,1114,9.4,AI Innovations +AI09643,Data Scientist,98262,JPY,10808820,EN,FL,Japan,L,France,0,"Python, SQL, Hadoop, Statistics",PhD,1,Manufacturing,2024-04-03,2024-04-28,1441,5.3,Future Systems +AI09644,AI Research Scientist,70103,USD,70103,EN,PT,South Korea,L,South Korea,100,"Mathematics, Computer Vision, Spark",Bachelor,1,Automotive,2024-02-20,2024-03-20,2351,5.5,Digital Transformation LLC +AI09645,Deep Learning Engineer,244222,USD,244222,EX,CT,Sweden,M,Israel,100,"PyTorch, TensorFlow, Deep Learning, Data Visualization, SQL",PhD,14,Energy,2024-03-18,2024-05-15,909,6.5,DataVision Ltd +AI09646,AI Software Engineer,98207,USD,98207,MI,FL,Sweden,S,Sweden,50,"R, Hadoop, Tableau, SQL, GCP",Associate,4,Real Estate,2024-09-26,2024-11-20,2490,8.4,Predictive Systems +AI09647,Machine Learning Engineer,74097,USD,74097,MI,CT,Finland,S,Brazil,50,"Hadoop, Python, MLOps",Master,4,Healthcare,2024-04-21,2024-05-11,2339,9.1,Quantum Computing Inc +AI09648,AI Specialist,57153,JPY,6286830,EN,CT,Japan,M,Japan,100,"TensorFlow, Scala, Docker, Hadoop",Master,1,Telecommunications,2024-09-12,2024-10-21,2307,8.8,DeepTech Ventures +AI09649,Research Scientist,99157,EUR,84283,MI,CT,France,M,Switzerland,0,"SQL, Hadoop, PyTorch",Master,3,Education,2024-04-23,2024-06-29,1974,9.2,Cloud AI Solutions +AI09650,AI Product Manager,104851,USD,104851,SE,CT,Israel,S,Israel,50,"Git, R, Python, Deep Learning, Java",Master,8,Automotive,2024-02-15,2024-04-26,2450,5.3,Quantum Computing Inc +AI09651,AI Specialist,70704,USD,70704,EN,CT,United States,M,United States,50,"Data Visualization, MLOps, Scala, Statistics, R",Master,1,Real Estate,2024-10-06,2024-12-11,513,5.8,Autonomous Tech +AI09652,AI Research Scientist,86595,AUD,116903,MI,FT,Australia,M,Australia,100,"Spark, TensorFlow, NLP",Master,4,Transportation,2025-01-04,2025-03-02,1800,5.7,Cognitive Computing +AI09653,Autonomous Systems Engineer,139992,USD,139992,SE,PT,Ireland,M,Egypt,0,"Mathematics, Python, Kubernetes",Master,5,Telecommunications,2024-04-30,2024-06-11,1651,8.9,Machine Intelligence Group +AI09654,AI Consultant,69365,EUR,58960,MI,CT,Germany,S,Germany,100,"Scala, Deep Learning, MLOps, Hadoop",PhD,2,Government,2024-01-25,2024-03-31,2284,7.6,Future Systems +AI09655,Data Engineer,98050,USD,98050,MI,FT,Finland,L,Finland,0,"Kubernetes, R, MLOps, Deep Learning, Scala",PhD,2,Telecommunications,2024-06-10,2024-07-19,1741,7,Smart Analytics +AI09656,AI Architect,20880,USD,20880,EN,CT,India,M,India,50,"Spark, Git, Kubernetes, Python",Bachelor,1,Finance,2024-05-11,2024-07-15,603,6.6,Cloud AI Solutions +AI09657,AI Research Scientist,80608,SGD,104790,EN,CT,Singapore,L,Singapore,0,"Scala, R, Hadoop, Deep Learning",PhD,0,Government,2025-04-04,2025-06-08,1483,5.4,Algorithmic Solutions +AI09658,Research Scientist,121634,CHF,109471,EN,PT,Switzerland,L,Czech Republic,50,"Python, Hadoop, AWS",Associate,1,Gaming,2024-03-08,2024-05-19,2259,8.4,Advanced Robotics +AI09659,Principal Data Scientist,200363,EUR,170309,EX,CT,Austria,L,Austria,100,"Tableau, Statistics, TensorFlow, Python",Bachelor,19,Technology,2025-01-07,2025-01-26,2480,7.7,Smart Analytics +AI09660,Machine Learning Researcher,65086,USD,65086,EN,FL,United States,S,United States,0,"Python, Linux, Tableau",PhD,1,Technology,2024-10-04,2024-11-23,2294,6.6,Predictive Systems +AI09661,Machine Learning Engineer,76722,USD,76722,EN,FT,Norway,S,Argentina,50,"Computer Vision, Spark, R, Hadoop, Docker",PhD,0,Government,2024-02-28,2024-05-05,1503,9.2,DataVision Ltd +AI09662,Data Engineer,136698,EUR,116193,SE,FL,Germany,M,Australia,0,"Statistics, Scala, SQL, Hadoop",Master,5,Healthcare,2024-07-28,2024-09-29,1467,8.3,TechCorp Inc +AI09663,Head of AI,89233,AUD,120465,MI,FT,Australia,S,Australia,100,"Azure, Statistics, Python, Data Visualization",Bachelor,3,Automotive,2025-01-11,2025-02-05,1410,9.4,Algorithmic Solutions +AI09664,AI Specialist,51178,AUD,69090,EN,FL,Australia,S,Egypt,50,"PyTorch, GCP, TensorFlow",Associate,1,Manufacturing,2024-01-25,2024-02-19,1458,9.7,Advanced Robotics +AI09665,AI Software Engineer,66263,EUR,56324,EN,FL,Germany,M,Argentina,0,"R, Tableau, Java",Associate,0,Transportation,2024-07-23,2024-09-13,558,9.3,Machine Intelligence Group +AI09666,Data Engineer,173476,USD,173476,EX,FL,Finland,S,Finland,100,"Linux, Kubernetes, Deep Learning, SQL, Git",Master,17,Government,2025-04-07,2025-04-30,2135,6.3,Machine Intelligence Group +AI09667,AI Software Engineer,161253,SGD,209629,EX,PT,Singapore,S,Singapore,100,"NLP, SQL, Statistics, Tableau",PhD,15,Real Estate,2024-03-21,2024-05-18,2353,9,AI Innovations +AI09668,AI Consultant,261254,EUR,222066,EX,PT,Germany,L,Germany,100,"Hadoop, Python, Kubernetes, Statistics, TensorFlow",Associate,12,Education,2025-04-26,2025-07-02,739,5.5,Advanced Robotics +AI09669,ML Ops Engineer,199726,USD,199726,EX,FT,Finland,M,Canada,0,"R, GCP, Deep Learning",Master,14,Technology,2024-09-05,2024-11-06,654,6.1,Smart Analytics +AI09670,Computer Vision Engineer,155809,AUD,210342,SE,PT,Australia,L,Australia,50,"PyTorch, Git, GCP",Master,8,Automotive,2024-04-25,2024-06-11,1358,5.6,Future Systems +AI09671,AI Specialist,27270,USD,27270,EN,FT,China,M,Vietnam,100,"Scala, Git, Azure",Associate,1,Transportation,2025-01-07,2025-02-06,2070,9.8,Smart Analytics +AI09672,NLP Engineer,123021,JPY,13532310,SE,CT,Japan,S,Japan,0,"Python, Scala, NLP, Docker, Kubernetes",Master,5,Finance,2024-10-29,2024-11-24,825,7.1,Neural Networks Co +AI09673,Robotics Engineer,218828,USD,218828,EX,FL,Ireland,S,Ireland,100,"PyTorch, TensorFlow, Azure, Kubernetes, Git",PhD,13,Telecommunications,2025-02-27,2025-05-08,1379,9.3,DeepTech Ventures +AI09674,Data Scientist,96009,USD,96009,EN,PT,Denmark,M,Denmark,100,"Spark, Statistics, SQL, Git",PhD,1,Real Estate,2024-04-02,2024-06-01,1154,7.4,Cloud AI Solutions +AI09675,AI Research Scientist,105293,USD,105293,EX,FT,China,L,China,100,"Tableau, Computer Vision, PyTorch, Linux, Mathematics",Associate,11,Automotive,2024-04-09,2024-06-02,1914,8,AI Innovations +AI09676,Machine Learning Researcher,140098,SGD,182127,SE,CT,Singapore,S,Singapore,50,"PyTorch, Java, GCP",Associate,6,Finance,2025-01-29,2025-03-07,951,6.5,Future Systems +AI09677,AI Product Manager,109453,CHF,98508,EN,FL,Switzerland,L,Switzerland,50,"Python, Scala, TensorFlow, Statistics, Computer Vision",Bachelor,1,Real Estate,2024-09-14,2024-10-27,2333,9.4,Cognitive Computing +AI09678,Data Engineer,135675,USD,135675,SE,FT,Ireland,S,Ghana,0,"Scala, GCP, Python",Associate,5,Real Estate,2025-03-27,2025-04-28,513,5.8,Cognitive Computing +AI09679,Data Analyst,55854,USD,55854,EN,FL,South Korea,S,South Korea,50,"Scala, TensorFlow, NLP",Bachelor,1,Government,2025-01-10,2025-03-03,2440,8.4,Quantum Computing Inc +AI09680,Data Analyst,95094,EUR,80830,SE,FT,Austria,S,Brazil,50,"Kubernetes, Python, Azure",Associate,5,Real Estate,2024-06-14,2024-08-02,2045,10,Smart Analytics +AI09681,Autonomous Systems Engineer,218586,USD,218586,EX,CT,Finland,L,Finland,0,"Linux, Hadoop, GCP, Tableau, Computer Vision",Bachelor,12,Media,2024-11-24,2025-01-25,1646,5.6,Quantum Computing Inc +AI09682,AI Specialist,49538,USD,49538,EN,CT,Finland,S,Finland,0,"Linux, Computer Vision, Docker, SQL",Master,1,Finance,2024-08-01,2024-09-10,1675,8.2,Cognitive Computing +AI09683,AI Software Engineer,133909,EUR,113823,EX,FT,France,S,Spain,50,"Data Visualization, GCP, MLOps, NLP",Associate,15,Manufacturing,2024-03-26,2024-04-24,1593,7.6,Cognitive Computing +AI09684,Principal Data Scientist,48444,EUR,41177,EN,CT,France,M,Hungary,100,"Azure, Scala, Python",Bachelor,1,Transportation,2024-02-02,2024-04-02,561,5.1,TechCorp Inc +AI09685,AI Research Scientist,256902,EUR,218367,EX,CT,Netherlands,M,Netherlands,100,"PyTorch, Tableau, Hadoop",Master,17,Gaming,2024-10-12,2024-11-27,1394,8.3,Autonomous Tech +AI09686,AI Architect,57022,USD,57022,SE,CT,China,M,China,0,"MLOps, Python, Docker",Master,9,Education,2024-05-16,2024-06-16,1314,9.5,Cognitive Computing +AI09687,AI Specialist,26272,USD,26272,EN,FL,India,M,Argentina,100,"Kubernetes, Tableau, Scala",Bachelor,1,Energy,2025-03-18,2025-04-08,1146,7.7,Advanced Robotics +AI09688,Deep Learning Engineer,191403,GBP,143552,EX,FL,United Kingdom,S,Philippines,50,"Tableau, Data Visualization, Computer Vision",PhD,13,Technology,2024-02-27,2024-05-05,2261,6.8,Cognitive Computing +AI09689,Machine Learning Researcher,102609,USD,102609,MI,CT,Ireland,M,Ireland,0,"Python, Linux, TensorFlow, Hadoop, Azure",PhD,3,Government,2024-04-25,2024-06-18,1130,9.7,Future Systems +AI09690,Machine Learning Engineer,86953,USD,86953,MI,PT,South Korea,M,Brazil,100,"R, SQL, TensorFlow, GCP, Computer Vision",Master,2,Energy,2024-01-07,2024-01-25,1942,9.5,DeepTech Ventures +AI09691,AI Architect,220260,EUR,187221,EX,FL,France,M,France,0,"Docker, Azure, Computer Vision, AWS, GCP",Bachelor,19,Automotive,2024-10-27,2025-01-01,2461,9.6,Autonomous Tech +AI09692,Robotics Engineer,129728,SGD,168646,SE,PT,Singapore,S,Singapore,100,"SQL, NLP, Hadoop",Bachelor,7,Gaming,2024-12-01,2025-01-12,2243,9.7,Cloud AI Solutions +AI09693,Principal Data Scientist,140854,USD,140854,SE,FL,Ireland,L,Ireland,0,"Python, Spark, Data Visualization",Bachelor,5,Transportation,2024-07-03,2024-09-14,1262,6.5,Cognitive Computing +AI09694,Data Analyst,247679,JPY,27244690,EX,FL,Japan,L,Japan,100,"PyTorch, NLP, Computer Vision, Java",Associate,19,Healthcare,2024-04-26,2024-06-02,1484,5.7,Predictive Systems +AI09695,Machine Learning Researcher,159898,JPY,17588780,SE,FL,Japan,M,Japan,50,"Spark, PyTorch, Tableau",PhD,9,Education,2024-11-30,2025-01-18,1577,7.7,Future Systems +AI09696,Data Engineer,119549,EUR,101617,SE,FT,Austria,M,Austria,0,"GCP, Docker, Tableau, Git",Bachelor,7,Telecommunications,2024-06-11,2024-08-11,1379,7.3,Cognitive Computing +AI09697,Data Scientist,141626,USD,141626,SE,PT,Finland,L,Finland,100,"MLOps, Docker, Kubernetes, R",PhD,9,Retail,2024-08-31,2024-10-31,688,8.3,Advanced Robotics +AI09698,Machine Learning Engineer,83010,EUR,70559,EN,CT,Germany,L,Malaysia,100,"Hadoop, SQL, Java",Bachelor,0,Retail,2024-12-21,2025-02-03,2456,9.9,Smart Analytics +AI09699,Machine Learning Engineer,102708,JPY,11297880,MI,CT,Japan,L,Japan,100,"TensorFlow, Linux, Tableau, SQL",Associate,2,Gaming,2024-03-24,2024-04-11,1512,7.6,Digital Transformation LLC +AI09700,NLP Engineer,108628,JPY,11949080,MI,FT,Japan,L,Japan,0,"NLP, Hadoop, GCP",Bachelor,3,Energy,2024-01-18,2024-02-26,667,9.1,Algorithmic Solutions +AI09701,Data Analyst,74902,JPY,8239220,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, NLP, GCP, Scala",Associate,0,Manufacturing,2024-07-01,2024-09-12,2409,8,Quantum Computing Inc +AI09702,Data Engineer,87428,CHF,78685,EN,FT,Switzerland,S,Switzerland,0,"Python, AWS, Deep Learning",Bachelor,0,Transportation,2024-03-27,2024-05-09,1937,6,Machine Intelligence Group +AI09703,Robotics Engineer,76047,AUD,102663,MI,PT,Australia,M,Australia,0,"R, AWS, MLOps, Scala, Deep Learning",PhD,3,Energy,2024-08-21,2024-09-08,1513,6.2,TechCorp Inc +AI09704,Deep Learning Engineer,260148,USD,260148,EX,FT,United States,S,Turkey,50,"Git, Scala, Data Visualization",Bachelor,18,Telecommunications,2025-01-10,2025-02-12,2240,8,Digital Transformation LLC +AI09705,Robotics Engineer,74496,USD,74496,MI,CT,Sweden,S,Sweden,0,"Java, Spark, TensorFlow",PhD,2,Energy,2025-04-23,2025-06-29,1834,6.9,Predictive Systems +AI09706,NLP Engineer,79118,EUR,67250,MI,PT,Germany,S,United States,0,"Azure, Tableau, Git",PhD,3,Manufacturing,2024-04-06,2024-05-11,1883,8.8,Advanced Robotics +AI09707,ML Ops Engineer,115756,EUR,98393,SE,FL,Germany,S,Germany,50,"Git, SQL, Kubernetes, Deep Learning, Hadoop",Bachelor,5,Transportation,2025-04-19,2025-05-27,1471,7.4,AI Innovations +AI09708,AI Software Engineer,86602,EUR,73612,SE,PT,France,S,Brazil,0,"SQL, Data Visualization, Scala, Azure",Associate,6,Education,2025-02-22,2025-03-18,1378,9.6,Machine Intelligence Group +AI09709,Principal Data Scientist,125719,AUD,169721,SE,CT,Australia,M,Australia,100,"Scala, Kubernetes, Docker",Master,6,Consulting,2024-03-02,2024-04-01,1265,7.2,Cloud AI Solutions +AI09710,NLP Engineer,18481,USD,18481,EN,CT,India,S,India,50,"Python, TensorFlow, Scala, PyTorch",Associate,0,Automotive,2024-05-11,2024-05-31,2012,6.4,Predictive Systems +AI09711,ML Ops Engineer,88351,USD,88351,SE,CT,Finland,S,Ghana,100,"SQL, Statistics, GCP, Hadoop, Deep Learning",Associate,6,Manufacturing,2024-07-10,2024-07-30,2256,5.5,Quantum Computing Inc +AI09712,AI Consultant,40280,USD,40280,MI,PT,India,L,India,50,"Statistics, PyTorch, Hadoop, Scala, AWS",Master,3,Automotive,2024-08-23,2024-09-27,1701,5.9,AI Innovations +AI09713,Deep Learning Engineer,87759,USD,87759,MI,FL,Ireland,L,Russia,100,"Hadoop, R, Tableau, GCP, Kubernetes",Bachelor,3,Finance,2024-05-29,2024-07-25,1034,6.2,Algorithmic Solutions +AI09714,AI Consultant,140279,USD,140279,SE,FT,Israel,L,Israel,100,"Data Visualization, SQL, Docker, TensorFlow",Bachelor,7,Media,2024-03-27,2024-05-16,725,9.6,Cognitive Computing +AI09715,Data Engineer,113020,EUR,96067,SE,CT,Austria,L,Austria,0,"Data Visualization, Kubernetes, Deep Learning",Associate,5,Consulting,2024-12-27,2025-01-23,753,9.3,Machine Intelligence Group +AI09716,Machine Learning Engineer,213625,USD,213625,EX,FT,Norway,M,Norway,100,"AWS, SQL, Git, Kubernetes",Master,15,Finance,2024-01-08,2024-03-09,562,7.3,Machine Intelligence Group +AI09717,Autonomous Systems Engineer,127115,EUR,108048,SE,FT,Austria,L,Brazil,100,"Spark, MLOps, Python, Tableau",PhD,5,Finance,2024-12-02,2025-02-07,1020,9,Advanced Robotics +AI09718,AI Software Engineer,53464,SGD,69503,EN,PT,Singapore,S,Colombia,0,"Hadoop, Statistics, Mathematics, Docker, AWS",Associate,1,Automotive,2025-04-18,2025-05-21,1121,5.5,Machine Intelligence Group +AI09719,Research Scientist,105947,USD,105947,EN,FT,Denmark,L,Denmark,50,"Kubernetes, Scala, Git",Bachelor,1,Consulting,2024-07-06,2024-08-05,1834,7.7,Cloud AI Solutions +AI09720,AI Research Scientist,389066,CHF,350159,EX,FT,Switzerland,L,Switzerland,0,"Hadoop, SQL, Docker",PhD,10,Finance,2024-08-13,2024-10-19,1479,6.6,Autonomous Tech +AI09721,AI Architect,162534,EUR,138154,EX,FT,Netherlands,S,Chile,100,"Scala, Tableau, Data Visualization, Deep Learning",Bachelor,13,Manufacturing,2024-01-07,2024-02-12,2180,6.9,Neural Networks Co +AI09722,Deep Learning Engineer,67954,EUR,57761,EN,CT,Austria,M,Austria,100,"Mathematics, TensorFlow, MLOps, NLP",Master,1,Transportation,2024-02-23,2024-04-27,2132,9.3,Predictive Systems +AI09723,Machine Learning Researcher,236172,AUD,318832,EX,PT,Australia,M,Australia,0,"SQL, Python, Deep Learning, NLP, Spark",Associate,16,Technology,2025-03-10,2025-04-22,1099,6.6,Cloud AI Solutions +AI09724,AI Architect,235127,EUR,199858,EX,CT,France,L,France,100,"Scala, R, Data Visualization, Azure",Associate,11,Finance,2024-02-14,2024-04-16,1353,7.4,Digital Transformation LLC +AI09725,Robotics Engineer,122654,EUR,104256,MI,FT,Netherlands,L,Netherlands,0,"Azure, Git, GCP, TensorFlow",Master,3,Transportation,2024-03-01,2024-04-29,1111,7.1,Advanced Robotics +AI09726,AI Research Scientist,205223,AUD,277051,EX,FT,Australia,S,Egypt,50,"Deep Learning, Kubernetes, Computer Vision, Hadoop, Data Visualization",Master,15,Transportation,2024-08-03,2024-10-12,2209,5.5,Advanced Robotics +AI09727,Robotics Engineer,148358,SGD,192865,SE,PT,Singapore,M,Egypt,100,"Scala, Statistics, AWS, TensorFlow",Bachelor,6,Healthcare,2024-05-10,2024-06-18,1848,6.6,Quantum Computing Inc +AI09728,Data Scientist,220353,USD,220353,EX,FL,Norway,L,Norway,100,"Python, Azure, Docker",Master,10,Finance,2025-02-25,2025-03-20,648,6.8,Algorithmic Solutions +AI09729,Deep Learning Engineer,189506,EUR,161080,EX,CT,Netherlands,L,Netherlands,50,"Python, MLOps, TensorFlow, AWS, Deep Learning",Associate,17,Healthcare,2024-10-04,2024-10-30,1498,7,Smart Analytics +AI09730,AI Software Engineer,69812,JPY,7679320,EN,FT,Japan,M,Brazil,50,"R, Java, Docker",Master,0,Gaming,2024-06-25,2024-09-04,1792,8.4,Machine Intelligence Group +AI09731,Data Scientist,61754,USD,61754,SE,PT,India,L,India,100,"R, PyTorch, Tableau, Computer Vision",Bachelor,5,Energy,2024-10-30,2025-01-09,993,9.9,Digital Transformation LLC +AI09732,Data Engineer,87674,USD,87674,MI,PT,Finland,S,Finland,0,"Tableau, TensorFlow, Linux, AWS, Computer Vision",Bachelor,3,Automotive,2024-01-27,2024-03-08,1229,8.2,Cloud AI Solutions +AI09733,AI Research Scientist,100642,USD,100642,MI,CT,Norway,S,Vietnam,100,"Scala, SQL, MLOps",PhD,4,Media,2024-08-01,2024-09-25,1487,7.8,Smart Analytics +AI09734,ML Ops Engineer,179394,AUD,242182,EX,FT,Australia,S,Australia,50,"Python, TensorFlow, Statistics",Associate,19,Real Estate,2024-03-19,2024-04-21,1973,7.1,Cognitive Computing +AI09735,AI Consultant,177616,USD,177616,SE,FL,United States,L,United States,50,"Scala, R, Data Visualization",Master,6,Transportation,2024-06-14,2024-08-07,1656,7.7,Cognitive Computing +AI09736,Deep Learning Engineer,31495,USD,31495,EN,CT,China,L,China,100,"NLP, Python, Statistics, SQL",PhD,1,Government,2024-06-21,2024-08-15,1654,6,Predictive Systems +AI09737,AI Consultant,44106,USD,44106,SE,PT,China,S,Nigeria,100,"Computer Vision, PyTorch, Git",Bachelor,9,Government,2024-10-06,2024-10-31,2386,7.4,Neural Networks Co +AI09738,Computer Vision Engineer,60523,EUR,51445,EN,CT,Netherlands,S,Netherlands,100,"SQL, PyTorch, Spark, TensorFlow, Tableau",PhD,0,Manufacturing,2025-02-15,2025-03-29,2025,7.3,Neural Networks Co +AI09739,Deep Learning Engineer,149499,SGD,194349,SE,FT,Singapore,M,Estonia,100,"MLOps, NLP, Tableau, TensorFlow, Java",Bachelor,5,Gaming,2024-09-21,2024-11-16,730,9,Machine Intelligence Group +AI09740,AI Architect,99163,USD,99163,SE,CT,South Korea,L,South Korea,50,"TensorFlow, SQL, Statistics",Bachelor,8,Energy,2024-12-22,2025-02-22,1266,9.5,Predictive Systems +AI09741,Computer Vision Engineer,295991,USD,295991,EX,CT,United States,L,Luxembourg,100,"Spark, TensorFlow, R",PhD,19,Education,2024-05-01,2024-07-04,1775,6.2,Cognitive Computing +AI09742,AI Architect,136129,USD,136129,MI,FL,Norway,L,Norway,100,"PyTorch, Hadoop, Statistics, Git, Deep Learning",PhD,2,Finance,2024-11-04,2024-11-19,1746,5.3,Smart Analytics +AI09743,Deep Learning Engineer,113701,EUR,96646,SE,FT,Austria,S,Austria,100,"R, Linux, Java",Master,5,Automotive,2024-04-06,2024-05-14,1949,7.4,Future Systems +AI09744,AI Architect,81106,CHF,72995,EN,PT,Switzerland,S,Switzerland,0,"Python, Spark, Statistics, Linux",PhD,1,Gaming,2025-02-11,2025-02-25,629,5.7,Advanced Robotics +AI09745,Data Analyst,69980,USD,69980,EX,FL,India,M,India,0,"PyTorch, TensorFlow, Docker, SQL, Statistics",Associate,14,Retail,2025-03-18,2025-04-23,1445,7.7,Digital Transformation LLC +AI09746,ML Ops Engineer,326836,USD,326836,EX,FT,Norway,M,Norway,0,"TensorFlow, SQL, Data Visualization",Bachelor,12,Finance,2024-09-14,2024-11-19,840,6.8,Algorithmic Solutions +AI09747,Data Engineer,99357,EUR,84453,SE,FL,Austria,M,Austria,50,"Python, Java, Azure, AWS",Bachelor,7,Automotive,2024-10-08,2024-11-16,560,6.6,DataVision Ltd +AI09748,Machine Learning Researcher,147291,USD,147291,EX,PT,Israel,L,Israel,50,"PyTorch, Spark, R, Git, Tableau",PhD,16,Manufacturing,2024-11-06,2024-11-27,1962,9.5,Digital Transformation LLC +AI09749,AI Research Scientist,241227,USD,241227,EX,FT,Norway,S,Norway,100,"Python, Spark, Tableau, TensorFlow, Deep Learning",Master,12,Media,2025-04-01,2025-05-12,667,7.5,TechCorp Inc +AI09750,Research Scientist,75529,USD,75529,EN,FL,Finland,L,Argentina,50,"Java, PyTorch, NLP, SQL, Scala",Bachelor,0,Manufacturing,2024-07-30,2024-08-24,1470,9.2,Future Systems +AI09751,Machine Learning Engineer,68543,USD,68543,EN,CT,Norway,S,Norway,100,"MLOps, Deep Learning, Data Visualization",Master,1,Telecommunications,2024-03-08,2024-04-16,2407,8.8,Cognitive Computing +AI09752,Principal Data Scientist,69686,USD,69686,EN,CT,United States,S,Czech Republic,100,"PyTorch, SQL, Data Visualization, Deep Learning",Bachelor,0,Telecommunications,2024-03-26,2024-05-18,1978,6.3,Advanced Robotics +AI09753,AI Architect,240290,EUR,204247,EX,CT,Netherlands,M,Netherlands,0,"Scala, Python, Azure",PhD,18,Retail,2024-04-14,2024-06-26,1249,8.2,Neural Networks Co +AI09754,Robotics Engineer,152827,CHF,137544,MI,CT,Switzerland,M,Poland,100,"Kubernetes, Docker, Mathematics",PhD,4,Automotive,2025-04-09,2025-05-17,2154,9.7,DeepTech Ventures +AI09755,AI Software Engineer,124396,EUR,105737,EX,CT,Germany,S,Germany,0,"PyTorch, Deep Learning, Hadoop, Computer Vision, Linux",PhD,15,Retail,2024-08-18,2024-10-09,708,6.3,Smart Analytics +AI09756,Machine Learning Engineer,246978,EUR,209931,EX,FL,Netherlands,M,Netherlands,100,"Azure, Java, PyTorch, Deep Learning, AWS",Bachelor,13,Transportation,2024-04-17,2024-05-26,605,8.1,TechCorp Inc +AI09757,Research Scientist,102797,JPY,11307670,MI,CT,Japan,M,Japan,0,"PyTorch, TensorFlow, Kubernetes",Associate,3,Manufacturing,2024-02-10,2024-04-23,522,7,Machine Intelligence Group +AI09758,Head of AI,67987,SGD,88383,EN,FL,Singapore,S,Singapore,0,"Python, Hadoop, SQL, Git, AWS",Bachelor,1,Consulting,2024-02-27,2024-05-01,761,7.4,Advanced Robotics +AI09759,Data Analyst,283056,USD,283056,EX,FL,Norway,L,Colombia,100,"Hadoop, Tableau, Python, Kubernetes, Mathematics",Master,15,Gaming,2024-10-17,2024-12-10,1021,7.7,Cloud AI Solutions +AI09760,Principal Data Scientist,362848,USD,362848,EX,CT,Norway,L,Norway,100,"GCP, Statistics, MLOps",Associate,13,Media,2025-01-08,2025-02-20,697,5.8,Predictive Systems +AI09761,Data Engineer,63275,SGD,82258,EN,PT,Singapore,M,Singapore,0,"Linux, Kubernetes, Hadoop, Docker, R",Associate,1,Media,2025-01-26,2025-02-13,1719,9.9,Cognitive Computing +AI09762,Data Scientist,61622,GBP,46217,EN,CT,United Kingdom,S,United Kingdom,50,"R, NLP, SQL",PhD,1,Telecommunications,2024-01-28,2024-03-25,1936,9.8,Predictive Systems +AI09763,Principal Data Scientist,82457,CHF,74211,EN,FL,Switzerland,M,Norway,0,"Python, Git, Computer Vision, TensorFlow",PhD,1,Automotive,2024-01-12,2024-02-13,1591,9,Neural Networks Co +AI09764,Head of AI,71625,EUR,60881,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch, Data Visualization, Azure",Associate,4,Gaming,2024-10-08,2024-12-10,1383,8.7,Advanced Robotics +AI09765,NLP Engineer,119422,EUR,101509,MI,FL,Germany,L,Ukraine,50,"PyTorch, TensorFlow, AWS",PhD,3,Media,2024-09-06,2024-10-02,2426,9.7,Quantum Computing Inc +AI09766,Deep Learning Engineer,54944,EUR,46702,EN,CT,Austria,S,Austria,50,"Python, SQL, Mathematics, Java",Associate,1,Finance,2024-10-17,2024-11-24,722,5,Quantum Computing Inc +AI09767,Robotics Engineer,52068,EUR,44258,EN,CT,France,M,France,100,"Python, SQL, Mathematics",Bachelor,1,Technology,2024-11-23,2025-01-20,908,6.3,Neural Networks Co +AI09768,Data Analyst,34503,USD,34503,EN,PT,China,L,Norway,50,"Statistics, Python, TensorFlow, PyTorch",Associate,0,Education,2025-04-01,2025-05-19,2330,7.6,TechCorp Inc +AI09769,Deep Learning Engineer,95396,USD,95396,SE,CT,Sweden,S,Sweden,100,"TensorFlow, SQL, Docker, Statistics",Bachelor,5,Telecommunications,2024-05-06,2024-06-09,1419,5.9,DeepTech Ventures +AI09770,AI Specialist,143291,EUR,121797,EX,CT,France,S,France,50,"PyTorch, R, TensorFlow, Computer Vision, GCP",PhD,14,Education,2025-02-27,2025-04-06,751,9.6,Cognitive Computing +AI09771,NLP Engineer,66180,USD,66180,EN,PT,Sweden,M,South Korea,50,"PyTorch, Git, Tableau",Bachelor,1,Government,2024-03-25,2024-05-15,1216,6.1,Digital Transformation LLC +AI09772,AI Product Manager,142280,USD,142280,SE,CT,Finland,M,Finland,0,"Python, Scala, Computer Vision, Tableau",Bachelor,9,Education,2024-11-23,2024-12-14,947,9.6,Cognitive Computing +AI09773,Principal Data Scientist,72824,USD,72824,MI,FT,South Korea,S,South Korea,50,"Computer Vision, GCP, Linux",Bachelor,3,Automotive,2024-09-14,2024-10-31,1124,6.5,Quantum Computing Inc +AI09774,AI Software Engineer,91337,JPY,10047070,MI,FT,Japan,M,Japan,0,"PyTorch, Docker, SQL, Deep Learning",PhD,3,Government,2024-07-15,2024-09-01,653,6.4,Quantum Computing Inc +AI09775,Machine Learning Researcher,59812,USD,59812,EN,FT,Israel,S,Hungary,0,"Python, Kubernetes, TensorFlow",PhD,1,Transportation,2024-10-02,2024-12-10,2279,9.5,Machine Intelligence Group +AI09776,Machine Learning Engineer,94416,CAD,118020,MI,PT,Canada,M,Canada,100,"Linux, Spark, Scala, Python",Associate,4,Retail,2024-01-31,2024-04-05,1742,5.1,TechCorp Inc +AI09777,Principal Data Scientist,162702,CHF,146432,MI,FL,Switzerland,L,China,100,"Computer Vision, Java, MLOps, Spark",Bachelor,4,Transportation,2024-08-24,2024-09-15,1799,5.4,Future Systems +AI09778,ML Ops Engineer,208539,CAD,260674,EX,FL,Canada,L,Canada,0,"SQL, Python, Git",PhD,16,Consulting,2024-07-13,2024-08-02,1191,5.7,Neural Networks Co +AI09779,Data Engineer,293805,USD,293805,EX,PT,Norway,L,Norway,100,"Java, Linux, Kubernetes, Deep Learning, Git",Master,13,Retail,2025-03-18,2025-05-24,1990,7.4,Digital Transformation LLC +AI09780,Robotics Engineer,109663,USD,109663,MI,FT,Norway,L,Norway,100,"NLP, Hadoop, Spark, PyTorch",Bachelor,4,Consulting,2024-04-05,2024-06-15,1177,6.5,Smart Analytics +AI09781,AI Product Manager,62003,USD,62003,EX,PT,India,M,Belgium,50,"Kubernetes, Data Visualization, Linux, Python, Scala",PhD,10,Government,2025-04-28,2025-07-07,1364,8.1,TechCorp Inc +AI09782,Deep Learning Engineer,110601,USD,110601,MI,PT,Denmark,S,Denmark,100,"MLOps, Docker, Kubernetes, Tableau, PyTorch",Master,4,Transportation,2024-07-21,2024-08-27,1275,6.7,AI Innovations +AI09783,Machine Learning Engineer,97802,USD,97802,SE,FL,Finland,S,Finland,100,"PyTorch, SQL, GCP, Docker",Master,7,Technology,2025-01-05,2025-03-01,1277,8.1,Future Systems +AI09784,AI Research Scientist,31409,USD,31409,EN,FL,China,S,China,100,"Scala, MLOps, SQL, Hadoop",Bachelor,0,Manufacturing,2024-02-28,2024-04-05,987,7,DataVision Ltd +AI09785,Data Analyst,217049,USD,217049,EX,CT,Ireland,S,Ireland,100,"Scala, Spark, Computer Vision, AWS",Bachelor,15,Energy,2025-01-02,2025-02-14,527,5.7,Future Systems +AI09786,AI Consultant,113873,USD,113873,SE,FL,Finland,L,Finland,0,"Statistics, MLOps, Python, Hadoop",Bachelor,5,Gaming,2024-02-15,2024-04-22,929,6.8,AI Innovations +AI09787,Data Scientist,154501,CHF,139051,MI,CT,Switzerland,M,France,50,"Python, TensorFlow, Linux, PyTorch, Scala",Associate,4,Technology,2024-07-05,2024-08-07,2288,8.3,Cloud AI Solutions +AI09788,Data Analyst,65431,CAD,81789,EN,PT,Canada,S,Belgium,100,"AWS, NLP, Git",Bachelor,1,Finance,2024-11-24,2024-12-11,2365,7.8,Cognitive Computing +AI09789,AI Consultant,182995,CAD,228744,EX,FL,Canada,S,Canada,0,"PyTorch, Hadoop, Mathematics, NLP",Bachelor,14,Transportation,2024-07-11,2024-09-11,1806,8.5,DataVision Ltd +AI09790,Data Engineer,69850,JPY,7683500,EN,FL,Japan,S,Japan,100,"SQL, NLP, Docker",PhD,1,Transportation,2025-01-26,2025-03-23,736,6.1,Neural Networks Co +AI09791,Data Engineer,204758,EUR,174044,EX,FL,Germany,S,Romania,100,"Scala, Kubernetes, Deep Learning",Associate,14,Gaming,2024-01-24,2024-02-07,2040,7.5,DataVision Ltd +AI09792,Robotics Engineer,118924,USD,118924,SE,CT,South Korea,M,South Korea,50,"Kubernetes, Git, TensorFlow",Master,9,Manufacturing,2025-02-14,2025-04-06,2190,8,Algorithmic Solutions +AI09793,AI Specialist,140720,GBP,105540,SE,CT,United Kingdom,M,Austria,50,"Spark, Hadoop, Linux, Scala",Bachelor,7,Technology,2024-10-21,2024-11-09,899,8.4,Cognitive Computing +AI09794,AI Consultant,83079,EUR,70617,MI,FT,Germany,S,Germany,100,"R, SQL, Statistics",Associate,4,Manufacturing,2025-04-08,2025-05-28,2250,9.7,DataVision Ltd +AI09795,Head of AI,160182,SGD,208237,SE,CT,Singapore,L,Canada,50,"Git, NLP, AWS",Bachelor,7,Consulting,2024-10-21,2024-11-07,2076,8.2,Predictive Systems +AI09796,AI Consultant,64536,USD,64536,EN,FL,Ireland,M,Ireland,0,"SQL, Hadoop, Mathematics",Bachelor,0,Healthcare,2024-01-22,2024-03-28,2158,9.8,Neural Networks Co +AI09797,Machine Learning Engineer,250363,AUD,337990,EX,FT,Australia,L,Australia,50,"MLOps, SQL, TensorFlow, R",Master,18,Consulting,2024-02-12,2024-04-03,1816,9.1,Quantum Computing Inc +AI09798,Data Engineer,45433,USD,45433,SE,PT,India,L,India,100,"Computer Vision, Spark, Statistics",Bachelor,7,Education,2024-08-28,2024-10-05,1982,7.3,Advanced Robotics +AI09799,Data Analyst,63135,CAD,78919,EN,FT,Canada,L,Sweden,0,"SQL, MLOps, Scala, TensorFlow",Associate,1,Manufacturing,2025-04-28,2025-07-10,2401,5.4,Neural Networks Co +AI09800,Data Scientist,72576,USD,72576,EX,FL,China,S,Italy,50,"Git, AWS, Scala, Data Visualization",Associate,10,Real Estate,2024-03-25,2024-05-12,678,8.2,DeepTech Ventures +AI09801,Research Scientist,137937,USD,137937,EX,CT,South Korea,M,South Korea,100,"Python, Statistics, Spark",Master,18,Energy,2024-07-11,2024-08-15,1878,8.4,Algorithmic Solutions +AI09802,Autonomous Systems Engineer,137663,EUR,117014,SE,CT,France,L,France,50,"Java, Spark, Mathematics, PyTorch",Bachelor,6,Consulting,2025-02-11,2025-03-12,1432,7,Machine Intelligence Group +AI09803,AI Consultant,201971,USD,201971,EX,FL,Sweden,L,Sweden,50,"Python, Data Visualization, Linux, GCP",Associate,19,Energy,2024-03-02,2024-04-18,1265,7.5,Digital Transformation LLC +AI09804,Data Scientist,49095,USD,49095,MI,CT,China,M,Egypt,0,"Tableau, Java, Azure, NLP, Python",PhD,4,Media,2024-10-20,2024-11-24,1490,6.8,Cognitive Computing +AI09805,Research Scientist,210286,USD,210286,EX,FT,United States,L,Czech Republic,0,"Spark, Linux, Scala",PhD,17,Transportation,2024-11-16,2024-12-02,2014,8.8,TechCorp Inc +AI09806,AI Specialist,196218,USD,196218,SE,PT,Denmark,M,Ghana,50,"Hadoop, Docker, Deep Learning, GCP, SQL",Associate,8,Energy,2024-08-22,2024-10-07,2279,8.6,Future Systems +AI09807,Machine Learning Engineer,18616,USD,18616,EN,FT,India,S,India,50,"Git, Tableau, Kubernetes, Data Visualization",Associate,0,Media,2024-07-20,2024-09-07,894,5.4,Machine Intelligence Group +AI09808,Autonomous Systems Engineer,118826,USD,118826,MI,FT,Finland,L,Finland,0,"Kubernetes, Docker, R",Associate,4,Education,2024-05-17,2024-06-12,1146,8.2,DataVision Ltd +AI09809,Computer Vision Engineer,277649,USD,277649,EX,FT,United States,L,Japan,100,"Statistics, SQL, Deep Learning",Associate,15,Media,2024-10-15,2024-12-11,2120,9.6,Advanced Robotics +AI09810,AI Research Scientist,67075,EUR,57014,MI,PT,France,S,France,50,"Linux, Scala, Computer Vision, PyTorch",Associate,2,Manufacturing,2024-08-24,2024-09-26,669,6.5,Autonomous Tech +AI09811,Machine Learning Engineer,62913,JPY,6920430,EN,FT,Japan,L,Japan,100,"SQL, Java, Mathematics",Bachelor,0,Media,2025-03-09,2025-03-25,1843,5.3,TechCorp Inc +AI09812,AI Software Engineer,95618,CHF,86056,MI,CT,Switzerland,S,India,50,"Computer Vision, Statistics, Kubernetes, Java",PhD,4,Education,2024-03-27,2024-06-01,1596,5.5,Future Systems +AI09813,Head of AI,219644,USD,219644,SE,PT,Norway,L,United States,100,"Git, Deep Learning, Python, Computer Vision",Bachelor,9,Education,2025-02-01,2025-03-18,1841,8.8,Quantum Computing Inc +AI09814,AI Research Scientist,183702,CHF,165332,SE,FT,Switzerland,L,Switzerland,50,"Computer Vision, Tableau, Git, MLOps, NLP",PhD,8,Telecommunications,2024-08-06,2024-08-28,1473,9.6,DeepTech Ventures +AI09815,Computer Vision Engineer,68877,AUD,92984,EN,PT,Australia,S,Australia,100,"SQL, PyTorch, Git, AWS, TensorFlow",Bachelor,1,Telecommunications,2025-03-03,2025-04-29,2430,5.8,Machine Intelligence Group +AI09816,AI Specialist,130605,EUR,111014,EX,CT,Austria,M,Austria,100,"Spark, R, Kubernetes",PhD,13,Consulting,2024-04-21,2024-05-18,1198,5.8,Advanced Robotics +AI09817,Machine Learning Researcher,204630,AUD,276251,EX,FT,Australia,S,Australia,50,"Azure, PyTorch, Linux",Associate,17,Consulting,2024-03-23,2024-05-13,1441,6.7,TechCorp Inc +AI09818,Machine Learning Researcher,52908,USD,52908,SE,PT,China,S,Ghana,0,"Python, Azure, Deep Learning, NLP",PhD,9,Manufacturing,2024-11-07,2024-12-03,1769,5.9,Predictive Systems +AI09819,AI Consultant,94508,CHF,85057,EN,FT,Switzerland,L,Russia,50,"Computer Vision, MLOps, Tableau",PhD,0,Retail,2024-04-23,2024-06-11,970,8.7,Machine Intelligence Group +AI09820,AI Consultant,129697,GBP,97273,SE,PT,United Kingdom,L,Denmark,50,"Hadoop, PyTorch, AWS, Linux, NLP",Associate,6,Consulting,2025-03-07,2025-03-30,895,8.6,Future Systems +AI09821,Computer Vision Engineer,114261,EUR,97122,SE,FT,France,S,France,0,"Computer Vision, Python, Mathematics",Bachelor,8,Retail,2024-10-15,2024-12-24,1576,7.1,Cloud AI Solutions +AI09822,Principal Data Scientist,66838,AUD,90231,EN,CT,Australia,L,Ukraine,50,"Azure, Linux, MLOps, Scala",Master,1,Transportation,2024-04-06,2024-06-15,2404,8,DeepTech Ventures +AI09823,Data Engineer,74558,CHF,67102,EN,CT,Switzerland,S,Switzerland,0,"Mathematics, GCP, Docker, AWS",Bachelor,0,Healthcare,2024-06-05,2024-08-15,1416,8.9,Autonomous Tech +AI09824,Autonomous Systems Engineer,77135,JPY,8484850,EN,FT,Japan,L,Japan,100,"Kubernetes, Statistics, PyTorch",Associate,1,Healthcare,2024-11-19,2025-01-27,805,6.4,Cognitive Computing +AI09825,AI Architect,186851,USD,186851,EX,FL,Norway,M,Norway,50,"Mathematics, R, Spark, Computer Vision",Bachelor,12,Media,2025-03-31,2025-05-03,804,9.9,Machine Intelligence Group +AI09826,AI Product Manager,77859,USD,77859,EN,FT,Sweden,M,Sweden,100,"Spark, Java, Statistics, Mathematics",Master,1,Government,2024-02-14,2024-03-12,1780,9.3,Cognitive Computing +AI09827,Deep Learning Engineer,90139,USD,90139,EN,FT,Denmark,M,Turkey,0,"TensorFlow, SQL, Python, NLP, AWS",Associate,0,Healthcare,2024-09-11,2024-10-03,852,8.2,Cognitive Computing +AI09828,AI Specialist,149714,USD,149714,MI,CT,Denmark,L,Denmark,0,"Python, SQL, NLP, Hadoop",Bachelor,2,Government,2025-04-05,2025-06-09,1519,8.6,Cloud AI Solutions +AI09829,Autonomous Systems Engineer,176198,EUR,149768,EX,CT,Austria,M,Latvia,50,"Deep Learning, Spark, Java, Computer Vision",Master,19,Government,2024-03-12,2024-05-07,1526,8.8,DeepTech Ventures +AI09830,AI Consultant,228336,CHF,205502,EX,FT,Switzerland,M,South Africa,0,"Java, Spark, Azure, Linux",Bachelor,19,Real Estate,2024-08-31,2024-09-16,805,5.5,Digital Transformation LLC +AI09831,Computer Vision Engineer,17942,USD,17942,EN,FL,India,S,South Korea,50,"Data Visualization, PyTorch, TensorFlow, SQL",PhD,1,Technology,2024-08-22,2024-10-28,1023,8.8,DataVision Ltd +AI09832,Autonomous Systems Engineer,140214,USD,140214,SE,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch, Azure",Bachelor,5,Real Estate,2024-09-22,2024-11-15,609,9.5,DeepTech Ventures +AI09833,AI Specialist,234802,USD,234802,EX,CT,Ireland,M,Ireland,0,"Spark, Kubernetes, Tableau, R, Linux",Master,12,Healthcare,2024-05-15,2024-07-25,906,8.3,Cognitive Computing +AI09834,AI Architect,54715,SGD,71130,EN,FL,Singapore,M,Singapore,50,"Data Visualization, Scala, NLP, Python, Mathematics",Master,1,Government,2025-01-29,2025-04-03,2046,6,Algorithmic Solutions +AI09835,AI Architect,288436,USD,288436,EX,FL,Norway,L,Singapore,100,"Java, Computer Vision, PyTorch, TensorFlow",Master,17,Healthcare,2025-01-21,2025-04-01,1751,8.3,Future Systems +AI09836,Robotics Engineer,77512,EUR,65885,MI,PT,Germany,S,Brazil,0,"Scala, R, Kubernetes",Master,3,Finance,2024-01-25,2024-02-29,704,5.5,DataVision Ltd +AI09837,Research Scientist,230817,GBP,173113,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, Hadoop, Spark",Bachelor,16,Healthcare,2025-01-14,2025-03-08,1547,8.9,Smart Analytics +AI09838,Data Analyst,126549,EUR,107567,SE,PT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, MLOps, AWS, Azure",Associate,7,Media,2025-03-07,2025-05-03,634,6.9,Digital Transformation LLC +AI09839,AI Specialist,55058,JPY,6056380,EN,CT,Japan,S,Japan,100,"Python, Mathematics, TensorFlow",Bachelor,0,Consulting,2024-06-15,2024-08-19,1925,6.1,Future Systems +AI09840,Data Engineer,123391,USD,123391,EX,PT,Israel,S,Mexico,50,"Java, Kubernetes, Tableau",Associate,11,Healthcare,2024-06-07,2024-06-23,2028,8.8,Autonomous Tech +AI09841,NLP Engineer,322051,USD,322051,EX,PT,Norway,L,Norway,100,"Git, R, Python, Computer Vision",Associate,11,Healthcare,2024-12-14,2025-01-08,2432,9.6,Quantum Computing Inc +AI09842,Research Scientist,37366,USD,37366,EN,FL,China,L,United Kingdom,0,"Git, SQL, NLP, PyTorch, Computer Vision",Master,0,Consulting,2024-01-24,2024-03-07,979,7.4,Autonomous Tech +AI09843,NLP Engineer,243682,EUR,207130,EX,FT,Netherlands,M,Netherlands,0,"Git, Python, TensorFlow",PhD,11,Manufacturing,2024-05-07,2024-06-26,1216,7.7,Predictive Systems +AI09844,Robotics Engineer,159124,CHF,143212,MI,FT,Switzerland,L,Switzerland,50,"Linux, GCP, Data Visualization",PhD,3,Media,2024-06-20,2024-07-07,2172,8,Algorithmic Solutions +AI09845,Computer Vision Engineer,49586,SGD,64462,EN,FT,Singapore,S,South Africa,0,"AWS, Git, PyTorch, Deep Learning",Associate,1,Finance,2024-02-20,2024-04-16,2441,9.9,Advanced Robotics +AI09846,Research Scientist,307401,USD,307401,EX,FL,United States,L,United States,50,"AWS, MLOps, Azure",PhD,10,Energy,2024-06-07,2024-07-08,1586,7.7,Neural Networks Co +AI09847,Robotics Engineer,173982,USD,173982,EX,CT,South Korea,S,South Korea,100,"Scala, Computer Vision, Python, Git, NLP",Associate,13,Manufacturing,2025-02-12,2025-03-20,725,7.4,Smart Analytics +AI09848,AI Product Manager,143207,USD,143207,SE,CT,Israel,M,Germany,0,"Python, NLP, TensorFlow",PhD,7,Telecommunications,2024-11-05,2024-11-25,1967,8.9,Algorithmic Solutions +AI09849,AI Research Scientist,144621,SGD,188007,EX,CT,Singapore,S,Singapore,0,"Linux, GCP, Scala",Associate,12,Healthcare,2024-05-31,2024-07-01,1397,6.9,Autonomous Tech +AI09850,AI Consultant,80428,EUR,68364,EN,FT,Germany,M,India,0,"SQL, Tableau, Scala, Git",PhD,0,Manufacturing,2024-11-19,2025-01-19,1987,8.8,Autonomous Tech +AI09851,ML Ops Engineer,306456,SGD,398393,EX,FL,Singapore,L,France,0,"Tableau, AWS, TensorFlow, Python, SQL",PhD,17,Manufacturing,2024-02-27,2024-03-27,2234,9.5,TechCorp Inc +AI09852,Data Scientist,123489,USD,123489,MI,PT,Denmark,M,Sweden,0,"Hadoop, Python, Data Visualization, Kubernetes",Associate,3,Gaming,2025-03-05,2025-04-21,761,8.1,Predictive Systems +AI09853,Machine Learning Researcher,131962,USD,131962,EX,CT,China,L,China,100,"Hadoop, SQL, Data Visualization",Bachelor,18,Retail,2024-01-03,2024-03-12,1973,8.6,Predictive Systems +AI09854,Principal Data Scientist,115511,CAD,144389,SE,FT,Canada,L,Canada,0,"Linux, Kubernetes, GCP, NLP",PhD,6,Technology,2024-06-30,2024-08-27,2363,6.6,Cloud AI Solutions +AI09855,Data Analyst,144101,EUR,122486,SE,PT,Netherlands,M,Netherlands,100,"R, Git, SQL, Java, Data Visualization",Master,9,Healthcare,2024-09-29,2024-10-14,961,5.2,Future Systems +AI09856,Data Engineer,187329,GBP,140497,EX,FT,United Kingdom,L,Russia,0,"Python, Java, Tableau, TensorFlow",Master,10,Energy,2024-12-03,2025-02-09,2026,9.2,Algorithmic Solutions +AI09857,Autonomous Systems Engineer,113840,CAD,142300,SE,CT,Canada,S,Canada,50,"Linux, Python, Tableau, Data Visualization",PhD,7,Technology,2024-11-20,2025-01-01,926,9.2,Digital Transformation LLC +AI09858,Principal Data Scientist,246771,USD,246771,EX,CT,Norway,M,Ghana,100,"R, Deep Learning, Azure, Linux, Kubernetes",Bachelor,19,Government,2024-04-29,2024-07-07,1293,7.2,Advanced Robotics +AI09859,AI Software Engineer,126469,SGD,164410,MI,PT,Singapore,L,Singapore,0,"Azure, R, Java, Python, SQL",Associate,4,Education,2024-01-22,2024-04-04,1395,8.6,Machine Intelligence Group +AI09860,Data Scientist,23821,USD,23821,MI,FL,India,S,India,100,"Git, Java, R",Bachelor,4,Gaming,2024-04-07,2024-06-03,1821,9.8,Cloud AI Solutions +AI09861,Research Scientist,165461,EUR,140642,SE,FT,Netherlands,L,Netherlands,100,"Mathematics, Data Visualization, Linux",Associate,8,Media,2024-11-25,2024-12-14,2016,9.1,Machine Intelligence Group +AI09862,AI Consultant,24465,USD,24465,EN,CT,India,L,India,50,"SQL, Scala, Deep Learning",Bachelor,1,Media,2024-12-15,2025-01-16,1653,7,DeepTech Ventures +AI09863,Machine Learning Researcher,83518,EUR,70990,MI,FT,Germany,M,Germany,100,"Python, NLP, Git, Kubernetes",Associate,4,Healthcare,2024-06-10,2024-07-29,1380,5.1,Neural Networks Co +AI09864,AI Software Engineer,172981,USD,172981,EX,PT,Sweden,S,Luxembourg,50,"Git, Linux, Computer Vision",Associate,16,Retail,2024-02-11,2024-04-13,673,7,Smart Analytics +AI09865,AI Specialist,68862,EUR,58533,MI,CT,Austria,M,Austria,0,"Linux, SQL, Tableau",Master,4,Technology,2024-09-03,2024-11-08,1318,6,Cognitive Computing +AI09866,Computer Vision Engineer,126859,USD,126859,SE,PT,Israel,S,Israel,50,"AWS, Git, Java",Master,7,Consulting,2024-09-13,2024-10-13,626,8.2,Smart Analytics +AI09867,Robotics Engineer,71219,CHF,64097,EN,FT,Switzerland,S,Switzerland,100,"SQL, Scala, Data Visualization, Linux, TensorFlow",PhD,0,Transportation,2024-09-07,2024-10-11,1446,7.2,Quantum Computing Inc +AI09868,AI Consultant,125998,EUR,107098,SE,CT,Austria,L,Austria,50,"SQL, Git, R, PyTorch, Computer Vision",Master,6,Media,2024-10-09,2024-11-27,2170,9.9,Cognitive Computing +AI09869,Head of AI,178944,USD,178944,SE,CT,Denmark,M,Denmark,50,"Kubernetes, Hadoop, MLOps",Bachelor,7,Real Estate,2024-02-29,2024-04-12,1915,7.6,Algorithmic Solutions +AI09870,Deep Learning Engineer,147376,USD,147376,EX,PT,Ireland,M,Ireland,0,"Java, Computer Vision, NLP, PyTorch, Statistics",Bachelor,17,Manufacturing,2024-05-03,2024-06-08,947,9,Predictive Systems +AI09871,Data Analyst,76399,USD,76399,MI,FL,Israel,S,Ukraine,50,"R, Azure, SQL, Computer Vision",Master,2,Manufacturing,2024-04-20,2024-05-31,1191,9.2,Machine Intelligence Group +AI09872,AI Research Scientist,136519,EUR,116041,EX,PT,Germany,M,Austria,100,"Scala, Java, Python, Mathematics, AWS",PhD,19,Manufacturing,2024-08-11,2024-10-16,1833,5.1,DataVision Ltd +AI09873,Deep Learning Engineer,116176,EUR,98750,MI,FL,Austria,L,Austria,50,"Spark, Azure, R, AWS",Master,4,Media,2025-04-06,2025-05-30,2202,5.3,Neural Networks Co +AI09874,AI Research Scientist,114218,AUD,154194,MI,CT,Australia,L,Australia,50,"Hadoop, Kubernetes, SQL",Bachelor,4,Gaming,2025-04-27,2025-05-22,1916,7.5,Digital Transformation LLC +AI09875,Data Analyst,79786,USD,79786,EN,PT,Israel,L,Israel,50,"Spark, Data Visualization, MLOps, Kubernetes, Scala",Bachelor,1,Transportation,2024-03-04,2024-04-12,1711,8.5,TechCorp Inc +AI09876,NLP Engineer,102654,USD,102654,MI,FL,United States,S,United States,50,"PyTorch, MLOps, Deep Learning",Bachelor,3,Telecommunications,2024-10-29,2024-12-28,1731,6.8,Cloud AI Solutions +AI09877,AI Consultant,110047,JPY,12105170,MI,FT,Japan,L,Japan,0,"Scala, Azure, Deep Learning, Linux",PhD,3,Education,2024-08-23,2024-10-11,2493,7.8,TechCorp Inc +AI09878,Robotics Engineer,43437,USD,43437,SE,FT,China,S,China,50,"Java, R, Azure, Data Visualization",PhD,9,Consulting,2024-01-24,2024-02-23,1497,8.3,Digital Transformation LLC +AI09879,AI Architect,197171,CHF,177454,SE,FT,Switzerland,M,Switzerland,100,"AWS, R, Tableau, Mathematics",Bachelor,6,Media,2024-02-18,2024-03-16,1025,5.1,DeepTech Ventures +AI09880,AI Software Engineer,174106,USD,174106,EX,FT,Ireland,L,Ireland,100,"Kubernetes, NLP, TensorFlow, GCP, AWS",PhD,12,Technology,2024-07-15,2024-08-17,1972,9.7,Smart Analytics +AI09881,NLP Engineer,88358,USD,88358,MI,CT,Finland,M,Finland,50,"Docker, MLOps, Python, Mathematics, R",PhD,4,Healthcare,2024-09-27,2024-10-14,2123,7.1,Algorithmic Solutions +AI09882,Head of AI,93787,USD,93787,SE,PT,South Korea,M,India,50,"Computer Vision, PyTorch, Data Visualization",Master,5,Manufacturing,2025-03-02,2025-04-09,1784,6.5,DataVision Ltd +AI09883,Research Scientist,116502,USD,116502,MI,FT,United States,L,United States,100,"NLP, Azure, Data Visualization",PhD,3,Education,2024-02-09,2024-03-30,2387,9.2,Algorithmic Solutions +AI09884,AI Consultant,35301,USD,35301,MI,FT,China,S,Italy,0,"GCP, Deep Learning, Tableau, AWS",PhD,2,Finance,2024-10-18,2024-11-18,820,6.5,DeepTech Ventures +AI09885,Computer Vision Engineer,130851,USD,130851,SE,PT,Denmark,S,Ukraine,0,"TensorFlow, Hadoop, Linux, Kubernetes",Bachelor,5,Retail,2025-03-18,2025-04-05,649,8.2,Digital Transformation LLC +AI09886,AI Research Scientist,122176,USD,122176,SE,FL,Sweden,M,Sweden,100,"Python, Git, Scala, TensorFlow",PhD,9,Government,2024-09-15,2024-10-31,2241,9.2,Future Systems +AI09887,AI Specialist,175333,SGD,227933,SE,FL,Singapore,L,Singapore,50,"Spark, Python, TensorFlow, Tableau",Associate,6,Education,2024-11-19,2025-01-16,826,9,TechCorp Inc +AI09888,Data Scientist,113930,USD,113930,SE,CT,Israel,M,Israel,0,"MLOps, Linux, AWS, Deep Learning, PyTorch",PhD,9,Transportation,2024-03-02,2024-04-27,1764,8.6,Autonomous Tech +AI09889,Data Engineer,122929,USD,122929,MI,FL,Ireland,L,Ireland,100,"PyTorch, R, Java, Python, Spark",Bachelor,2,Automotive,2024-07-09,2024-09-15,1307,8.3,Algorithmic Solutions +AI09890,Research Scientist,188908,EUR,160572,EX,FL,Netherlands,M,Netherlands,100,"Docker, Tableau, Python",PhD,16,Retail,2024-01-20,2024-02-11,1747,7.4,TechCorp Inc +AI09891,AI Architect,66033,USD,66033,EN,PT,South Korea,L,South Korea,50,"Deep Learning, SQL, Mathematics, AWS",PhD,1,Media,2024-06-27,2024-07-20,1478,9.1,Machine Intelligence Group +AI09892,Deep Learning Engineer,148648,AUD,200675,SE,PT,Australia,M,Australia,0,"R, SQL, TensorFlow, Azure, Tableau",Associate,6,Government,2024-08-31,2024-09-28,754,8.7,Smart Analytics +AI09893,Research Scientist,142225,EUR,120891,SE,PT,Germany,M,Germany,50,"Kubernetes, Git, NLP, Mathematics, GCP",Bachelor,9,Transportation,2025-03-03,2025-04-09,1697,9.9,Smart Analytics +AI09894,AI Product Manager,163931,USD,163931,EX,FL,Finland,M,Finland,50,"SQL, Kubernetes, Python, Spark, R",Master,13,Real Estate,2024-11-08,2025-01-08,1318,8.9,DataVision Ltd +AI09895,Autonomous Systems Engineer,71392,EUR,60683,EN,FT,Austria,M,Austria,50,"GCP, Java, Kubernetes, Spark",PhD,1,Finance,2024-02-23,2024-04-28,1661,5.7,Neural Networks Co +AI09896,Machine Learning Researcher,111415,JPY,12255650,SE,FL,Japan,S,Sweden,100,"Deep Learning, Kubernetes, R, TensorFlow, Java",Bachelor,6,Retail,2024-04-04,2024-05-16,742,8,Algorithmic Solutions +AI09897,NLP Engineer,67040,CAD,83800,EN,FL,Canada,M,Canada,0,"MLOps, Linux, Docker, Kubernetes",Master,1,Media,2024-10-25,2025-01-05,1056,8.1,Smart Analytics +AI09898,Research Scientist,336020,USD,336020,EX,CT,Denmark,L,Denmark,0,"Java, Git, PyTorch, AWS, Kubernetes",Master,16,Media,2024-01-25,2024-03-09,1964,6.8,DataVision Ltd +AI09899,AI Consultant,194195,USD,194195,SE,FL,Norway,L,Israel,50,"Scala, Python, NLP",Master,6,Retail,2025-02-12,2025-03-31,2305,7.2,DataVision Ltd +AI09900,AI Software Engineer,110004,EUR,93503,MI,FT,Germany,L,Germany,0,"AWS, Computer Vision, Kubernetes, Java, Spark",Bachelor,2,Consulting,2024-08-08,2024-09-03,1401,5.7,Cognitive Computing +AI09901,NLP Engineer,65717,USD,65717,EN,PT,Finland,S,Finland,0,"Data Visualization, Deep Learning, Spark, AWS",Master,1,Telecommunications,2024-10-08,2024-11-06,2155,8.5,Predictive Systems +AI09902,Data Engineer,80715,GBP,60536,EN,CT,United Kingdom,L,United Kingdom,100,"Azure, NLP, SQL, GCP, Docker",Bachelor,1,Healthcare,2025-01-04,2025-02-25,806,7.6,DataVision Ltd +AI09903,Data Scientist,225112,USD,225112,EX,PT,Ireland,M,Canada,100,"Git, Python, AWS, GCP",Master,19,Retail,2025-03-19,2025-05-21,2392,6,Neural Networks Co +AI09904,Data Engineer,206433,EUR,175468,EX,FL,France,L,Nigeria,50,"Mathematics, Linux, Tableau, Azure",Bachelor,16,Transportation,2025-02-13,2025-02-28,2389,8.6,Algorithmic Solutions +AI09905,Research Scientist,163201,USD,163201,SE,CT,Denmark,S,Denmark,0,"Statistics, NLP, SQL, PyTorch",PhD,8,Automotive,2025-03-20,2025-05-25,1445,9.2,Future Systems +AI09906,Robotics Engineer,210688,EUR,179085,EX,CT,Austria,S,Austria,50,"Java, SQL, Linux, AWS",Bachelor,17,Healthcare,2024-11-03,2024-12-21,1482,6,Algorithmic Solutions +AI09907,AI Specialist,135482,USD,135482,SE,CT,Denmark,S,Denmark,0,"Java, Kubernetes, Hadoop",Master,5,Healthcare,2024-09-03,2024-09-17,1042,5.9,Cloud AI Solutions +AI09908,ML Ops Engineer,80264,SGD,104343,EN,FT,Singapore,M,Netherlands,0,"Azure, GCP, SQL, TensorFlow, Data Visualization",PhD,0,Transportation,2025-01-23,2025-04-03,690,9.9,Smart Analytics +AI09909,AI Consultant,121140,USD,121140,SE,PT,Finland,M,Finland,50,"Mathematics, MLOps, Azure, Linux, SQL",Master,8,Technology,2024-06-30,2024-07-16,689,5.9,Machine Intelligence Group +AI09910,Data Scientist,210071,EUR,178560,EX,PT,Germany,M,Germany,0,"Spark, Statistics, PyTorch, Azure, Mathematics",Bachelor,13,Healthcare,2024-06-21,2024-08-24,1513,5.3,Future Systems +AI09911,Autonomous Systems Engineer,252427,EUR,214563,EX,CT,France,L,Thailand,50,"Python, Linux, TensorFlow",Bachelor,10,Manufacturing,2024-09-26,2024-11-01,2275,7.6,Neural Networks Co +AI09912,AI Architect,211690,USD,211690,EX,PT,Israel,M,Israel,100,"Tableau, Computer Vision, Python, AWS",Associate,11,Real Estate,2024-11-26,2025-01-19,1954,9.6,Advanced Robotics +AI09913,Principal Data Scientist,89052,USD,89052,MI,PT,Ireland,M,Japan,50,"NLP, PyTorch, TensorFlow",Master,2,Media,2025-02-10,2025-04-23,1301,6.4,Machine Intelligence Group +AI09914,Autonomous Systems Engineer,105815,USD,105815,MI,FT,Norway,M,Indonesia,50,"Linux, PyTorch, Kubernetes",Associate,2,Government,2025-02-17,2025-04-07,1594,6.6,DeepTech Ventures +AI09915,AI Research Scientist,107540,USD,107540,SE,FT,Israel,S,Israel,50,"NLP, Hadoop, Kubernetes",Bachelor,7,Manufacturing,2025-02-23,2025-04-09,2336,9.3,DeepTech Ventures +AI09916,ML Ops Engineer,95240,USD,95240,EN,FL,Denmark,M,Denmark,0,"SQL, Data Visualization, PyTorch, Linux",PhD,0,Gaming,2024-06-09,2024-07-06,2323,7.3,DeepTech Ventures +AI09917,Research Scientist,191684,USD,191684,EX,FL,Sweden,S,Sweden,100,"Java, Computer Vision, Git",Master,11,Transportation,2024-02-06,2024-03-04,1230,8.8,Advanced Robotics +AI09918,Principal Data Scientist,59242,USD,59242,EN,FT,South Korea,M,South Korea,50,"Spark, Hadoop, Mathematics, TensorFlow",Associate,1,Consulting,2024-04-08,2024-06-12,1353,6.7,Predictive Systems +AI09919,Machine Learning Researcher,83529,USD,83529,MI,FT,Finland,S,Finland,0,"TensorFlow, Docker, MLOps, Git, GCP",PhD,2,Government,2025-01-20,2025-03-02,1757,6.5,Advanced Robotics +AI09920,Machine Learning Engineer,139067,USD,139067,SE,FT,Finland,M,Finland,50,"Hadoop, Git, Kubernetes, AWS, Python",PhD,9,Technology,2024-03-08,2024-04-13,1871,8.2,Cloud AI Solutions +AI09921,AI Architect,49440,SGD,64272,EN,FT,Singapore,S,Turkey,50,"Data Visualization, NLP, Java, SQL, TensorFlow",Associate,0,Media,2025-04-10,2025-04-26,2447,7.1,Future Systems +AI09922,AI Software Engineer,18220,USD,18220,EN,FT,India,M,India,50,"SQL, TensorFlow, Python, R, Data Visualization",Master,0,Education,2024-04-06,2024-06-15,1271,5.5,Algorithmic Solutions +AI09923,NLP Engineer,65418,USD,65418,EN,FT,Israel,M,Israel,50,"Git, Mathematics, Linux",Bachelor,0,Finance,2024-11-02,2025-01-04,1374,5.7,Cloud AI Solutions +AI09924,Data Analyst,157206,USD,157206,EX,FT,Sweden,M,Sweden,0,"Python, NLP, Mathematics, Spark",Master,14,Automotive,2024-07-16,2024-07-31,2023,9.7,DeepTech Ventures +AI09925,AI Consultant,125227,CHF,112704,EN,PT,Switzerland,L,Switzerland,0,"Docker, Python, Computer Vision, SQL, Linux",Master,1,Manufacturing,2024-02-27,2024-04-03,536,8.5,AI Innovations +AI09926,Data Scientist,99081,USD,99081,SE,FT,Israel,M,Israel,100,"Java, Computer Vision, Kubernetes, Spark",PhD,8,Retail,2024-03-02,2024-04-20,1832,8.1,Neural Networks Co +AI09927,AI Architect,137965,USD,137965,SE,CT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, SQL, Docker, Linux",PhD,7,Retail,2024-09-26,2024-10-26,938,6.3,Cloud AI Solutions +AI09928,AI Product Manager,79335,USD,79335,EN,FT,Sweden,L,Indonesia,100,"MLOps, SQL, Azure, PyTorch",Bachelor,0,Energy,2024-03-04,2024-05-13,2184,7.5,Neural Networks Co +AI09929,Computer Vision Engineer,88458,USD,88458,EX,PT,China,S,China,50,"AWS, R, Tableau, Hadoop",Bachelor,16,Real Estate,2024-12-17,2025-02-24,1991,6.2,Neural Networks Co +AI09930,NLP Engineer,122917,USD,122917,SE,PT,Sweden,S,Sweden,100,"Python, R, GCP, MLOps, Deep Learning",Master,6,Manufacturing,2025-01-18,2025-03-15,763,8.6,Advanced Robotics +AI09931,Autonomous Systems Engineer,51646,JPY,5681060,EN,FT,Japan,S,Poland,0,"Spark, GCP, Docker, R, Kubernetes",Master,1,Transportation,2024-08-09,2024-09-20,1648,6.9,Smart Analytics +AI09932,AI Product Manager,105874,USD,105874,SE,FT,South Korea,S,South Korea,50,"Tableau, Linux, GCP, TensorFlow, Spark",Master,7,Transportation,2024-08-16,2024-09-28,1716,5.8,Machine Intelligence Group +AI09933,AI Specialist,52597,USD,52597,SE,PT,China,S,China,100,"AWS, R, Deep Learning, Computer Vision",Master,8,Telecommunications,2024-12-18,2025-02-25,1975,7.7,Algorithmic Solutions +AI09934,Data Scientist,90978,GBP,68234,MI,PT,United Kingdom,S,United Kingdom,100,"Scala, MLOps, TensorFlow",PhD,4,Healthcare,2024-01-09,2024-01-25,1444,6.4,Algorithmic Solutions +AI09935,Data Analyst,170390,USD,170390,EX,CT,Finland,M,Singapore,0,"Tableau, Azure, SQL, Statistics, AWS",Bachelor,18,Technology,2024-07-20,2024-08-26,650,6.9,Cloud AI Solutions +AI09936,Research Scientist,104491,EUR,88817,MI,CT,Germany,M,Germany,0,"Deep Learning, Linux, Computer Vision, GCP, Docker",PhD,2,Consulting,2024-01-17,2024-02-10,832,8,DeepTech Ventures +AI09937,AI Product Manager,89899,USD,89899,EX,FT,China,M,China,50,"R, AWS, Azure, Deep Learning, Python",Master,12,Real Estate,2025-02-28,2025-04-20,1332,5.4,Neural Networks Co +AI09938,Data Scientist,81953,EUR,69660,EN,PT,Germany,L,Germany,50,"Hadoop, Python, GCP, Deep Learning",Bachelor,0,Manufacturing,2024-12-21,2025-01-18,967,7.3,Neural Networks Co +AI09939,AI Product Manager,63919,GBP,47939,EN,FL,United Kingdom,S,United Kingdom,50,"Docker, SQL, AWS, Mathematics",PhD,0,Finance,2024-05-29,2024-07-25,2267,7,Cognitive Computing +AI09940,AI Software Engineer,251077,USD,251077,EX,PT,Sweden,L,Sweden,50,"Python, GCP, Mathematics, AWS",Bachelor,16,Retail,2024-04-16,2024-05-30,1188,7.2,Future Systems +AI09941,Research Scientist,154431,EUR,131266,EX,CT,Netherlands,M,Israel,0,"Scala, Tableau, Hadoop, Linux",Associate,11,Transportation,2024-09-10,2024-10-31,690,7.3,Machine Intelligence Group +AI09942,Data Scientist,84206,CAD,105258,MI,PT,Canada,S,Canada,0,"Hadoop, Java, SQL, Computer Vision, Azure",Bachelor,3,Real Estate,2024-12-02,2024-12-22,2097,6.3,AI Innovations +AI09943,AI Research Scientist,94103,USD,94103,EX,CT,India,L,Hungary,0,"Hadoop, SQL, Kubernetes",Master,10,Consulting,2024-04-30,2024-06-14,1596,8.2,Quantum Computing Inc +AI09944,Robotics Engineer,172742,EUR,146831,EX,FL,Netherlands,M,Netherlands,100,"Data Visualization, GCP, PyTorch, AWS",Associate,14,Media,2024-05-01,2024-06-22,1002,5.4,DeepTech Ventures +AI09945,AI Consultant,202350,AUD,273173,EX,FL,Australia,S,Australia,0,"Hadoop, Kubernetes, GCP",PhD,18,Media,2024-08-30,2024-10-09,2174,8.1,Predictive Systems +AI09946,AI Product Manager,220924,JPY,24301640,EX,PT,Japan,M,Japan,50,"TensorFlow, Deep Learning, Data Visualization",Associate,18,Government,2025-02-24,2025-04-14,717,6.1,Machine Intelligence Group +AI09947,Machine Learning Engineer,202063,EUR,171754,EX,FL,Germany,L,Germany,100,"Python, TensorFlow, SQL, Linux, Hadoop",Associate,16,Consulting,2024-05-29,2024-08-09,2230,8.7,Digital Transformation LLC +AI09948,NLP Engineer,156925,SGD,204003,SE,PT,Singapore,L,New Zealand,50,"Azure, Spark, Hadoop, Linux, SQL",Bachelor,8,Energy,2025-04-13,2025-05-26,679,8.6,DeepTech Ventures +AI09949,Machine Learning Researcher,127958,USD,127958,SE,FT,United States,S,United States,0,"AWS, SQL, Azure",PhD,6,Consulting,2024-11-25,2025-01-14,2152,9.7,Autonomous Tech +AI09950,AI Architect,88010,USD,88010,MI,PT,Finland,M,Finland,50,"SQL, Data Visualization, Spark, MLOps, Statistics",Bachelor,4,Education,2024-03-04,2024-05-05,2274,9.1,Predictive Systems +AI09951,Data Engineer,73299,USD,73299,EX,CT,India,S,India,0,"Python, Spark, SQL, Deep Learning, Linux",Associate,11,Media,2024-04-15,2024-06-03,668,7.4,Machine Intelligence Group +AI09952,Data Analyst,38886,USD,38886,MI,FT,India,L,India,0,"R, Python, Git, Statistics, Azure",Associate,3,Media,2025-01-14,2025-03-03,2418,5.1,Advanced Robotics +AI09953,Research Scientist,87404,EUR,74293,EN,CT,Netherlands,L,Norway,100,"TensorFlow, GCP, Python, Linux",Bachelor,0,Manufacturing,2024-12-19,2025-02-02,1258,8.5,Future Systems +AI09954,AI Product Manager,50608,EUR,43017,EN,FL,Netherlands,S,Denmark,100,"Spark, MLOps, Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-01-19,2024-03-04,2364,5.5,Advanced Robotics +AI09955,Data Analyst,87958,USD,87958,MI,FL,Sweden,S,Sweden,0,"Java, AWS, Mathematics, Deep Learning",Bachelor,4,Transportation,2024-07-12,2024-09-13,1500,7.9,Cloud AI Solutions +AI09956,NLP Engineer,65492,USD,65492,MI,CT,South Korea,M,Russia,100,"Deep Learning, Python, TensorFlow",Bachelor,2,Gaming,2024-07-06,2024-09-01,1987,9.6,Advanced Robotics +AI09957,Research Scientist,260160,USD,260160,EX,FL,Norway,M,Norway,0,"Linux, Computer Vision, R",Master,17,Finance,2024-03-14,2024-04-12,1484,9.1,AI Innovations +AI09958,Research Scientist,70254,GBP,52691,EN,CT,United Kingdom,M,United Kingdom,0,"Statistics, Tableau, GCP",Master,0,Healthcare,2024-08-06,2024-08-24,1063,7.7,Cognitive Computing +AI09959,NLP Engineer,159037,AUD,214700,EX,FT,Australia,L,Australia,50,"Kubernetes, Docker, Spark",PhD,19,Finance,2025-02-18,2025-03-16,858,6.7,Future Systems +AI09960,Data Scientist,117550,EUR,99918,SE,CT,France,S,France,100,"Computer Vision, Data Visualization, Kubernetes, Scala, Tableau",Master,9,Media,2024-04-08,2024-06-13,1552,7.1,Cognitive Computing +AI09961,Machine Learning Researcher,138817,USD,138817,MI,PT,United States,L,Estonia,50,"R, Deep Learning, TensorFlow, Docker",Master,2,Finance,2025-01-09,2025-03-13,1358,9.7,Neural Networks Co +AI09962,Machine Learning Researcher,233912,AUD,315781,EX,CT,Australia,L,Australia,50,"Hadoop, Linux, Docker",PhD,16,Real Estate,2024-09-26,2024-11-26,1830,8.5,AI Innovations +AI09963,AI Architect,83523,JPY,9187530,EN,FT,Japan,M,Japan,50,"AWS, Docker, Java, R",Associate,1,Transportation,2024-05-26,2024-07-09,1334,8.7,Digital Transformation LLC +AI09964,AI Consultant,49711,USD,49711,SE,CT,India,M,India,0,"PyTorch, Computer Vision, Linux",Bachelor,8,Education,2025-01-13,2025-02-22,1029,7.5,Advanced Robotics +AI09965,AI Product Manager,116921,CAD,146151,SE,FL,Canada,L,Canada,100,"Java, MLOps, SQL",Bachelor,6,Manufacturing,2024-05-09,2024-07-19,2433,8.1,Machine Intelligence Group +AI09966,Data Analyst,213255,CHF,191930,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Linux, Computer Vision, Python, Spark",Associate,8,Healthcare,2024-03-12,2024-04-16,749,7.6,DeepTech Ventures +AI09967,Principal Data Scientist,102306,USD,102306,MI,FL,United States,S,Denmark,0,"Python, NLP, Statistics, Spark, Mathematics",PhD,2,Manufacturing,2024-05-02,2024-05-23,2478,6,Digital Transformation LLC +AI09968,ML Ops Engineer,86619,CAD,108274,MI,CT,Canada,L,Canada,100,"Python, Java, Spark, Computer Vision, TensorFlow",Master,2,Retail,2024-02-08,2024-03-06,1030,7.9,AI Innovations +AI09969,ML Ops Engineer,66607,EUR,56616,EN,FL,Germany,M,Czech Republic,100,"PyTorch, Tableau, Python, Docker, AWS",Bachelor,1,Media,2024-02-14,2024-03-11,2276,9.9,Digital Transformation LLC +AI09970,Head of AI,103856,USD,103856,MI,CT,Ireland,M,Ireland,50,"Computer Vision, Azure, Python, Linux",PhD,3,Retail,2024-10-25,2024-12-04,928,6.4,Digital Transformation LLC +AI09971,AI Consultant,128302,GBP,96227,MI,FT,United Kingdom,L,United Kingdom,100,"Spark, GCP, Deep Learning, Python",Bachelor,2,Transportation,2024-06-22,2024-08-20,648,9.9,Quantum Computing Inc +AI09972,ML Ops Engineer,99518,EUR,84590,MI,PT,Germany,L,Germany,0,"Statistics, MLOps, AWS",Associate,4,Transportation,2024-06-04,2024-06-18,2181,5.9,Cognitive Computing +AI09973,Research Scientist,225083,USD,225083,EX,CT,United States,M,Malaysia,0,"Scala, TensorFlow, Tableau, R",PhD,19,Real Estate,2025-01-09,2025-01-30,1316,7,Quantum Computing Inc +AI09974,Data Scientist,76078,EUR,64666,MI,FL,Austria,S,Austria,100,"R, Java, Linux",Associate,2,Manufacturing,2024-11-29,2024-12-23,871,6,Future Systems +AI09975,Data Analyst,208198,USD,208198,EX,FL,United States,L,China,100,"GCP, R, Spark, SQL",PhD,17,Energy,2024-11-26,2024-12-10,2426,6.8,Machine Intelligence Group +AI09976,Machine Learning Researcher,115497,SGD,150146,SE,FL,Singapore,S,France,50,"Python, Git, Computer Vision, Tableau",Associate,6,Manufacturing,2024-03-23,2024-05-27,1337,7,Advanced Robotics +AI09977,Data Analyst,30191,USD,30191,EN,FL,China,S,South Africa,50,"Python, Computer Vision, Docker, Kubernetes, Git",Master,0,Automotive,2024-06-28,2024-08-09,1509,6.8,Cloud AI Solutions +AI09978,Robotics Engineer,122452,USD,122452,MI,CT,Norway,S,Norway,0,"Spark, PyTorch, Kubernetes, Deep Learning, Tableau",Master,2,Telecommunications,2024-09-10,2024-11-17,1088,7,AI Innovations +AI09979,Robotics Engineer,80064,JPY,8807040,EN,CT,Japan,M,New Zealand,100,"Scala, SQL, Kubernetes, Tableau",Associate,1,Media,2024-12-28,2025-01-16,2318,7.6,Smart Analytics +AI09980,AI Architect,156844,USD,156844,SE,FL,United States,S,United States,50,"Docker, Spark, NLP, SQL, R",Master,8,Telecommunications,2024-01-05,2024-02-18,1084,5.8,Digital Transformation LLC +AI09981,AI Consultant,204204,CHF,183784,SE,CT,Switzerland,L,Switzerland,50,"Spark, AWS, Python",Master,8,Technology,2025-02-24,2025-05-02,1083,6.1,Cloud AI Solutions +AI09982,Principal Data Scientist,33152,USD,33152,MI,PT,India,L,India,100,"Deep Learning, Azure, Scala",Associate,3,Real Estate,2025-02-27,2025-03-31,1465,9.2,TechCorp Inc +AI09983,Data Engineer,65768,USD,65768,SE,FL,China,M,France,100,"R, Statistics, Scala, AWS, Azure",PhD,9,Gaming,2024-12-04,2024-12-25,2408,6.3,Machine Intelligence Group +AI09984,Data Scientist,73194,USD,73194,MI,PT,Sweden,M,Sweden,100,"Docker, Data Visualization, Linux",Associate,3,Retail,2024-08-23,2024-09-08,1618,8.2,AI Innovations +AI09985,AI Architect,55370,SGD,71981,EN,FL,Singapore,S,Singapore,50,"Mathematics, AWS, Hadoop",Associate,0,Retail,2024-11-08,2024-12-07,2104,8.3,Advanced Robotics +AI09986,Deep Learning Engineer,210307,GBP,157730,EX,FT,United Kingdom,M,United Kingdom,0,"GCP, Linux, Computer Vision, Java, Deep Learning",PhD,18,Retail,2024-04-30,2024-06-16,1090,5.3,Digital Transformation LLC +AI09987,AI Research Scientist,84436,USD,84436,EN,FT,United States,M,United States,100,"Java, NLP, GCP, Kubernetes",Master,1,Consulting,2024-04-24,2024-05-12,1654,7.3,Cognitive Computing +AI09988,ML Ops Engineer,54161,AUD,73117,EN,FT,Australia,S,Australia,0,"Azure, Scala, Java",PhD,1,Healthcare,2024-10-22,2024-11-13,1338,8.3,Neural Networks Co +AI09989,AI Software Engineer,205169,USD,205169,EX,CT,United States,M,United States,100,"Python, Tableau, NLP, Computer Vision",Master,12,Transportation,2024-09-27,2024-11-13,2197,5.7,DeepTech Ventures +AI09990,Data Engineer,38591,USD,38591,MI,PT,China,M,Colombia,50,"Python, Statistics, MLOps, TensorFlow, Computer Vision",Master,4,Transportation,2025-01-01,2025-02-12,1506,9.6,Neural Networks Co +AI09991,Research Scientist,68630,EUR,58336,EN,FT,France,L,United Kingdom,50,"R, Python, NLP, Data Visualization",PhD,0,Finance,2025-04-30,2025-06-24,2243,6.6,DeepTech Ventures +AI09992,Autonomous Systems Engineer,43605,USD,43605,SE,CT,China,S,China,0,"PyTorch, Deep Learning, TensorFlow",Bachelor,9,Consulting,2025-03-28,2025-05-18,969,7,Advanced Robotics +AI09993,ML Ops Engineer,161575,USD,161575,EX,CT,Finland,M,Finland,0,"Docker, Scala, Hadoop, TensorFlow, NLP",Master,16,Consulting,2024-11-16,2024-12-06,2224,9.9,Cognitive Computing +AI09994,Autonomous Systems Engineer,45084,USD,45084,MI,FL,China,M,China,50,"Linux, SQL, GCP",Bachelor,3,Telecommunications,2024-05-10,2024-05-29,1998,8.6,Neural Networks Co +AI09995,AI Product Manager,88847,USD,88847,SE,CT,South Korea,S,South Korea,100,"Hadoop, Scala, Tableau",Associate,5,Media,2024-07-09,2024-09-19,1406,5.1,Smart Analytics +AI09996,Data Analyst,273652,USD,273652,EX,PT,Norway,L,Norway,50,"Docker, Statistics, Linux, Python",Master,12,Real Estate,2024-04-28,2024-06-03,1723,8.9,Cognitive Computing +AI09997,AI Specialist,77815,JPY,8559650,EN,CT,Japan,M,Japan,50,"Python, SQL, Data Visualization, MLOps",Bachelor,1,Technology,2024-10-14,2024-12-14,1183,8.1,Cognitive Computing +AI09998,Head of AI,71265,USD,71265,MI,CT,Sweden,S,Ireland,100,"PyTorch, GCP, Kubernetes",Associate,2,Transportation,2024-08-02,2024-09-08,937,7.6,Algorithmic Solutions +AI09999,ML Ops Engineer,206399,USD,206399,EX,CT,United States,L,United States,0,"PyTorch, R, Tableau",Master,18,Automotive,2024-12-04,2024-12-27,1313,9,Neural Networks Co +AI10000,AI Consultant,199903,JPY,21989330,EX,FL,Japan,L,France,0,"Git, Python, Docker",PhD,16,Education,2025-04-27,2025-05-11,2171,7.3,Advanced Robotics +AI10001,AI Specialist,167578,USD,167578,SE,FT,Denmark,S,Denmark,100,"Linux, Python, Hadoop",PhD,6,Healthcare,2024-08-07,2024-09-16,996,9.6,Autonomous Tech +AI10002,AI Architect,154721,CHF,139249,SE,CT,Switzerland,M,Sweden,0,"Python, TensorFlow, MLOps, Azure",Bachelor,6,Government,2024-09-15,2024-10-05,1917,8.6,Future Systems +AI10003,AI Consultant,122754,EUR,104341,SE,FT,Netherlands,S,Czech Republic,100,"Spark, MLOps, TensorFlow, NLP, Mathematics",Master,7,Transportation,2025-01-20,2025-03-05,1738,5.5,Autonomous Tech +AI10004,Data Analyst,68729,USD,68729,EN,FL,Israel,M,Israel,0,"Computer Vision, Statistics, SQL, Python",Master,0,Automotive,2025-03-07,2025-04-07,1313,5.1,Cognitive Computing +AI10005,AI Software Engineer,85966,SGD,111756,EN,FT,Singapore,L,Singapore,100,"Hadoop, Docker, Data Visualization, Python",Associate,0,Education,2025-04-01,2025-04-22,1119,9.4,DataVision Ltd +AI10006,Data Analyst,131244,JPY,14436840,SE,FL,Japan,L,Japan,50,"Git, Scala, Java, Computer Vision",Master,8,Media,2024-03-24,2024-04-26,960,8.3,Autonomous Tech +AI10007,Computer Vision Engineer,122218,USD,122218,SE,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Hadoop, MLOps",Associate,7,Automotive,2024-05-12,2024-07-18,2497,8.8,Quantum Computing Inc +AI10008,Research Scientist,79816,USD,79816,EN,PT,Norway,S,Canada,0,"Python, GCP, AWS",Bachelor,1,Manufacturing,2024-04-19,2024-06-25,546,6.3,Cognitive Computing +AI10009,Machine Learning Engineer,76709,EUR,65203,MI,PT,Netherlands,S,Netherlands,0,"TensorFlow, Azure, Kubernetes, Python, MLOps",Bachelor,2,Media,2024-04-28,2024-06-14,531,8.4,DeepTech Ventures +AI10010,Data Analyst,53982,USD,53982,EN,FT,Ireland,S,South Africa,0,"SQL, Scala, Tableau",Bachelor,0,Government,2024-06-29,2024-09-01,1371,8.3,Future Systems +AI10011,ML Ops Engineer,192615,EUR,163723,EX,FL,France,M,France,0,"Kubernetes, Tableau, Python",PhD,11,Energy,2025-01-29,2025-03-17,505,9.4,DataVision Ltd +AI10012,AI Architect,145605,JPY,16016550,SE,PT,Japan,L,Japan,100,"R, GCP, Java",Bachelor,8,Technology,2025-03-10,2025-04-10,2336,7.4,Neural Networks Co +AI10013,Autonomous Systems Engineer,97274,USD,97274,MI,PT,Denmark,S,Denmark,50,"PyTorch, Azure, Git",Bachelor,2,Technology,2024-10-18,2024-11-27,1260,9,TechCorp Inc +AI10014,AI Specialist,244858,USD,244858,EX,FL,Norway,S,Norway,100,"PyTorch, R, SQL, Statistics",Associate,15,Media,2024-03-14,2024-05-20,1932,7.1,Autonomous Tech +AI10015,Data Engineer,104413,EUR,88751,MI,PT,Netherlands,L,Netherlands,0,"GCP, MLOps, Scala, Kubernetes",Associate,4,Healthcare,2025-03-26,2025-05-18,1269,6.8,AI Innovations +AI10016,AI Specialist,213972,USD,213972,SE,CT,Norway,L,Norway,100,"AWS, Docker, Data Visualization, Deep Learning",Bachelor,6,Education,2024-05-04,2024-07-09,2063,5.1,Advanced Robotics +AI10017,Machine Learning Engineer,163739,USD,163739,EX,CT,Finland,S,Finland,0,"AWS, Kubernetes, Statistics, R",Associate,18,Real Estate,2024-12-11,2025-01-28,1031,8.2,Quantum Computing Inc +AI10018,Head of AI,54758,USD,54758,EN,CT,South Korea,S,Chile,0,"Tableau, Linux, AWS, TensorFlow, Deep Learning",Master,0,Technology,2024-12-13,2025-02-18,1502,6.9,DataVision Ltd +AI10019,Principal Data Scientist,90479,EUR,76907,MI,PT,France,M,Ireland,100,"Docker, R, MLOps, Kubernetes",Associate,4,Telecommunications,2024-03-19,2024-05-02,1148,9.7,Future Systems +AI10020,Deep Learning Engineer,159487,USD,159487,SE,PT,Norway,L,Singapore,100,"Docker, MLOps, Tableau, Python, Kubernetes",PhD,7,Real Estate,2024-09-25,2024-11-25,2469,6.3,Future Systems +AI10021,Computer Vision Engineer,64591,EUR,54902,EN,FT,Netherlands,L,Netherlands,0,"Scala, AWS, SQL, Python",Bachelor,1,Finance,2024-03-15,2024-04-23,2168,6.5,Neural Networks Co +AI10022,AI Product Manager,186453,GBP,139840,EX,CT,United Kingdom,M,Philippines,100,"TensorFlow, Hadoop, AWS, Java, Deep Learning",Bachelor,19,Technology,2024-09-17,2024-11-04,1428,5.1,DataVision Ltd +AI10023,Principal Data Scientist,367782,USD,367782,EX,FT,Denmark,L,Switzerland,0,"Data Visualization, Python, Git",Bachelor,16,Finance,2024-08-20,2024-10-12,1285,8.6,Future Systems +AI10024,Data Scientist,122924,AUD,165947,MI,FL,Australia,L,Spain,0,"Java, Linux, TensorFlow, SQL, MLOps",Master,4,Healthcare,2024-09-05,2024-09-19,797,7.6,Neural Networks Co +AI10025,Autonomous Systems Engineer,243749,AUD,329061,EX,PT,Australia,L,Australia,100,"GCP, Data Visualization, Linux, Computer Vision, SQL",PhD,19,Retail,2025-02-08,2025-03-22,2447,6.4,AI Innovations +AI10026,Computer Vision Engineer,78463,JPY,8630930,MI,CT,Japan,S,Japan,50,"Scala, Data Visualization, Git",Associate,3,Manufacturing,2024-04-17,2024-06-10,2462,9.4,TechCorp Inc +AI10027,Machine Learning Engineer,177410,USD,177410,SE,FT,Norway,M,Norway,0,"Linux, Python, PyTorch, Scala, AWS",Master,6,Consulting,2024-06-25,2024-08-15,1228,9.4,Machine Intelligence Group +AI10028,Robotics Engineer,85282,USD,85282,MI,FL,Israel,M,Israel,0,"Scala, Linux, TensorFlow, GCP, Statistics",PhD,2,Manufacturing,2024-07-04,2024-07-20,607,5.8,Digital Transformation LLC +AI10029,AI Consultant,54574,USD,54574,EN,CT,United States,S,United States,100,"Scala, Docker, Computer Vision, SQL",Master,1,Technology,2024-07-18,2024-08-21,1471,9.1,Algorithmic Solutions +AI10030,AI Architect,99684,JPY,10965240,MI,FL,Japan,M,Malaysia,100,"R, SQL, Kubernetes",Master,4,Transportation,2024-12-14,2025-02-25,1017,7,AI Innovations +AI10031,Autonomous Systems Engineer,107913,EUR,91726,SE,FT,France,S,France,100,"Spark, TensorFlow, Kubernetes",PhD,9,Government,2024-04-05,2024-06-09,769,9.3,Quantum Computing Inc +AI10032,Deep Learning Engineer,110437,SGD,143568,MI,FL,Singapore,L,Singapore,100,"Docker, MLOps, GCP, Python",Associate,2,Technology,2024-03-16,2024-05-18,1027,5.6,Cognitive Computing +AI10033,Data Scientist,32139,USD,32139,MI,FL,China,S,China,0,"Git, Python, Mathematics",Bachelor,2,Real Estate,2024-06-18,2024-07-31,1820,7.2,TechCorp Inc +AI10034,Research Scientist,78757,USD,78757,MI,FL,Ireland,M,Thailand,0,"Python, Tableau, NLP, MLOps",PhD,3,Government,2024-06-24,2024-08-26,1381,9.5,Algorithmic Solutions +AI10035,AI Architect,264042,AUD,356457,EX,FT,Australia,L,Australia,0,"Kubernetes, Statistics, MLOps, R",Associate,12,Telecommunications,2024-02-29,2024-05-01,2038,9.1,Autonomous Tech +AI10036,Data Engineer,208291,USD,208291,EX,PT,Ireland,L,Ireland,50,"Linux, AWS, Python, TensorFlow, Deep Learning",Master,11,Retail,2024-03-06,2024-05-15,1662,7.2,Cloud AI Solutions +AI10037,AI Architect,100038,USD,100038,MI,CT,Denmark,M,Egypt,100,"Kubernetes, Computer Vision, Git, NLP, Deep Learning",PhD,4,Retail,2024-01-23,2024-02-06,2234,6.8,DataVision Ltd +AI10038,NLP Engineer,77060,USD,77060,EN,PT,Norway,L,Israel,0,"Kubernetes, PyTorch, Mathematics",Associate,0,Government,2024-12-25,2025-01-08,1416,6.7,DeepTech Ventures +AI10039,Autonomous Systems Engineer,222150,USD,222150,EX,PT,Denmark,L,Switzerland,50,"Statistics, R, Python, Mathematics, Data Visualization",PhD,16,Gaming,2024-07-07,2024-09-10,1253,6.1,DataVision Ltd +AI10040,Robotics Engineer,163117,USD,163117,EX,CT,Israel,S,France,100,"SQL, Mathematics, Java",Bachelor,15,Education,2025-02-09,2025-04-20,584,6.3,Future Systems +AI10041,Research Scientist,221296,JPY,24342560,EX,PT,Japan,S,Austria,50,"AWS, Scala, GCP",PhD,10,Government,2024-02-06,2024-02-25,616,7.2,Advanced Robotics +AI10042,NLP Engineer,75240,USD,75240,MI,PT,Sweden,M,Sweden,50,"MLOps, NLP, TensorFlow",Bachelor,3,Technology,2024-01-03,2024-01-27,2150,9.7,Algorithmic Solutions +AI10043,AI Specialist,190468,GBP,142851,EX,PT,United Kingdom,S,United Kingdom,100,"R, Azure, Tableau, SQL",Associate,10,Gaming,2024-04-07,2024-05-11,2175,6,AI Innovations +AI10044,Machine Learning Engineer,229205,USD,229205,EX,FL,Norway,L,Norway,0,"Mathematics, PyTorch, Docker",Master,19,Government,2024-07-30,2024-08-27,702,5.6,Machine Intelligence Group +AI10045,AI Product Manager,158082,JPY,17389020,EX,FL,Japan,S,Japan,100,"Linux, Data Visualization, Spark",Bachelor,17,Retail,2024-04-13,2024-06-02,1116,6.2,Neural Networks Co +AI10046,Autonomous Systems Engineer,158388,EUR,134630,SE,PT,Austria,L,Austria,50,"MLOps, Azure, Tableau, Data Visualization",PhD,7,Transportation,2024-09-03,2024-11-15,1409,9.8,DataVision Ltd +AI10047,Deep Learning Engineer,270701,USD,270701,EX,CT,Norway,M,Norway,0,"GCP, Kubernetes, Python",Bachelor,10,Technology,2024-04-22,2024-06-02,673,9.5,AI Innovations +AI10048,AI Specialist,106640,EUR,90644,MI,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Statistics, Docker",PhD,4,Education,2024-12-18,2025-02-15,1432,8.5,TechCorp Inc +AI10049,AI Research Scientist,69424,EUR,59010,MI,FT,France,M,France,50,"GCP, AWS, Docker, Computer Vision, Python",Associate,2,Government,2024-05-11,2024-07-08,848,7,Cloud AI Solutions +AI10050,AI Research Scientist,93528,USD,93528,EN,FT,United States,L,United States,50,"Kubernetes, Docker, Statistics, Scala, Mathematics",Master,0,Transportation,2025-03-09,2025-05-15,1627,6,Autonomous Tech +AI10051,AI Software Engineer,114025,SGD,148233,MI,CT,Singapore,L,Singapore,50,"Scala, Python, Git, GCP, Computer Vision",Bachelor,3,Energy,2025-01-12,2025-02-16,2470,8.2,Cognitive Computing +AI10052,Machine Learning Engineer,91997,EUR,78197,MI,FL,France,S,France,100,"Python, Spark, Git, TensorFlow, Java",Associate,4,Transportation,2025-01-24,2025-02-13,505,8.6,DataVision Ltd +AI10053,Deep Learning Engineer,120244,SGD,156317,SE,PT,Singapore,S,Argentina,0,"Mathematics, Python, Hadoop, Tableau",Master,7,Gaming,2024-04-17,2024-05-07,721,7.3,DataVision Ltd +AI10054,Data Analyst,132194,USD,132194,EX,CT,China,L,China,50,"SQL, PyTorch, MLOps, TensorFlow",PhD,18,Telecommunications,2024-04-22,2024-06-24,1300,5.8,DataVision Ltd +AI10055,AI Specialist,108571,USD,108571,EX,CT,China,M,Kenya,100,"SQL, Linux, TensorFlow, Deep Learning",Bachelor,11,Media,2024-04-30,2024-05-17,1016,7.8,Predictive Systems +AI10056,Autonomous Systems Engineer,75698,USD,75698,EN,FL,Israel,M,Israel,100,"SQL, AWS, Hadoop, Python",Master,1,Technology,2025-03-25,2025-05-09,1791,8.2,AI Innovations +AI10057,Principal Data Scientist,39365,USD,39365,MI,CT,China,L,China,100,"Statistics, Git, GCP, Azure",Associate,3,Transportation,2024-01-19,2024-03-24,2176,8.1,Advanced Robotics +AI10058,Robotics Engineer,183526,EUR,155997,EX,PT,Germany,L,Germany,0,"NLP, Git, Java",Bachelor,10,Automotive,2024-10-10,2024-11-28,974,7.4,DataVision Ltd +AI10059,AI Consultant,143337,EUR,121836,EX,PT,Germany,M,Poland,100,"Data Visualization, SQL, PyTorch",Master,14,Technology,2024-06-16,2024-07-05,1608,5.2,DeepTech Ventures +AI10060,AI Software Engineer,63211,GBP,47408,EN,FL,United Kingdom,M,United Kingdom,50,"NLP, Git, MLOps",Associate,1,Gaming,2024-07-29,2024-09-17,2029,6.6,TechCorp Inc +AI10061,AI Architect,60718,GBP,45539,EN,FL,United Kingdom,S,United Kingdom,0,"GCP, Tableau, Scala, Java, AWS",Associate,0,Consulting,2024-03-05,2024-04-25,1108,9.2,DeepTech Ventures +AI10062,Robotics Engineer,93597,USD,93597,MI,FL,Finland,L,Poland,100,"Python, Scala, Tableau, MLOps, Azure",Bachelor,2,Government,2024-02-26,2024-03-16,1084,9.8,Quantum Computing Inc +AI10063,Deep Learning Engineer,92670,USD,92670,SE,FL,Israel,S,Israel,0,"Spark, Statistics, Linux, Mathematics",Master,9,Energy,2024-02-20,2024-04-18,674,5.5,Digital Transformation LLC +AI10064,Principal Data Scientist,52329,AUD,70644,EN,FL,Australia,M,Australia,100,"Linux, TensorFlow, Azure",Bachelor,1,Gaming,2025-02-07,2025-03-14,648,9.2,Autonomous Tech +AI10065,Autonomous Systems Engineer,110402,CHF,99362,MI,FT,Switzerland,M,Switzerland,100,"SQL, PyTorch, Azure",Bachelor,4,Finance,2024-02-11,2024-03-08,1722,5.9,Digital Transformation LLC +AI10066,Head of AI,79269,EUR,67379,EN,CT,France,L,France,100,"Python, TensorFlow, AWS",PhD,0,Transportation,2024-08-18,2024-10-10,1318,9.9,Cloud AI Solutions +AI10067,Deep Learning Engineer,147090,AUD,198572,SE,CT,Australia,L,Australia,0,"Statistics, GCP, NLP, MLOps",Bachelor,8,Media,2024-08-23,2024-10-13,1890,7.2,Digital Transformation LLC +AI10068,Research Scientist,95456,CAD,119320,SE,CT,Canada,S,Canada,0,"Scala, R, Hadoop, GCP",PhD,7,Technology,2024-01-06,2024-01-26,2009,9.3,Digital Transformation LLC +AI10069,AI Software Engineer,86713,GBP,65035,MI,CT,United Kingdom,S,United Kingdom,0,"R, Data Visualization, PyTorch, Java, Statistics",Associate,2,Real Estate,2024-06-09,2024-07-18,795,9.6,Cloud AI Solutions +AI10070,Robotics Engineer,267784,EUR,227616,EX,PT,Germany,L,Germany,0,"SQL, Java, Statistics, Computer Vision, GCP",PhD,17,Real Estate,2024-01-04,2024-02-25,2268,9,AI Innovations +AI10071,Autonomous Systems Engineer,107929,EUR,91740,MI,FL,Germany,M,Israel,0,"SQL, R, Data Visualization",PhD,4,Healthcare,2025-01-30,2025-03-16,608,9.1,Algorithmic Solutions +AI10072,Data Engineer,187961,USD,187961,SE,FT,Denmark,M,Denmark,50,"Mathematics, Java, Scala",PhD,5,Healthcare,2024-10-26,2024-11-17,887,8.6,Future Systems +AI10073,Research Scientist,79425,USD,79425,EN,CT,United States,S,Portugal,0,"Spark, R, Scala",Bachelor,0,Retail,2024-04-16,2024-05-04,2159,6.3,Machine Intelligence Group +AI10074,Autonomous Systems Engineer,69795,EUR,59326,MI,FL,France,M,France,50,"Java, Mathematics, Kubernetes, TensorFlow",Master,4,Finance,2025-02-19,2025-03-21,1831,9.8,Algorithmic Solutions +AI10075,NLP Engineer,91415,SGD,118840,MI,FT,Singapore,S,Singapore,0,"Computer Vision, Linux, Statistics",Associate,3,Media,2024-06-17,2024-08-24,607,6,Algorithmic Solutions +AI10076,AI Software Engineer,69308,EUR,58912,EN,PT,France,L,France,100,"R, PyTorch, Statistics, Git",Bachelor,0,Healthcare,2024-09-21,2024-11-28,1355,9.4,TechCorp Inc +AI10077,AI Software Engineer,262289,GBP,196717,EX,FT,United Kingdom,L,United Kingdom,100,"Computer Vision, Deep Learning, Data Visualization",Bachelor,12,Government,2025-03-26,2025-05-15,1644,9,Future Systems +AI10078,Research Scientist,117333,USD,117333,MI,PT,Ireland,L,Ireland,50,"Hadoop, Tableau, Java, Deep Learning",PhD,3,Education,2024-03-06,2024-05-10,1796,8,Digital Transformation LLC +AI10079,AI Architect,109771,USD,109771,MI,FT,United States,M,United States,100,"Linux, R, Kubernetes, Deep Learning",Associate,2,Finance,2024-01-09,2024-03-21,2490,5,Algorithmic Solutions +AI10080,NLP Engineer,150367,USD,150367,MI,FT,Norway,L,Romania,50,"SQL, TensorFlow, Computer Vision, AWS, Tableau",Associate,3,Technology,2024-05-15,2024-06-27,1894,5.2,AI Innovations +AI10081,Deep Learning Engineer,88240,EUR,75004,MI,PT,France,M,United Kingdom,100,"Data Visualization, TensorFlow, Docker, GCP, Deep Learning",Bachelor,2,Government,2025-03-26,2025-05-09,2369,9.8,Autonomous Tech +AI10082,NLP Engineer,158509,JPY,17435990,EX,FL,Japan,M,Japan,0,"PyTorch, Git, Scala, GCP",Master,19,Healthcare,2024-08-08,2024-09-13,2335,7.4,Digital Transformation LLC +AI10083,Computer Vision Engineer,95690,CHF,86121,EN,PT,Switzerland,M,Switzerland,100,"NLP, Spark, Python, Mathematics",Associate,0,Healthcare,2024-11-22,2025-01-23,2223,9.4,Digital Transformation LLC +AI10084,Research Scientist,65431,GBP,49073,EN,FL,United Kingdom,S,United Kingdom,100,"Docker, Tableau, Linux, Kubernetes",Associate,0,Transportation,2025-04-16,2025-05-05,1112,8,Cloud AI Solutions +AI10085,Research Scientist,41112,USD,41112,MI,FT,India,L,India,100,"Hadoop, Kubernetes, Python",PhD,4,Media,2024-05-12,2024-06-04,2195,8.7,Cognitive Computing +AI10086,AI Software Engineer,59137,EUR,50266,EN,FT,Netherlands,M,Netherlands,100,"Hadoop, Java, Azure",PhD,0,Transportation,2024-06-10,2024-08-02,514,9.7,Smart Analytics +AI10087,Autonomous Systems Engineer,78995,EUR,67146,MI,FT,Germany,S,Colombia,50,"Scala, Java, AWS",Bachelor,4,Real Estate,2024-06-15,2024-08-07,1977,5.2,DataVision Ltd +AI10088,Computer Vision Engineer,48283,USD,48283,SE,FL,China,S,Austria,0,"AWS, Deep Learning, Spark, SQL, Scala",Master,7,Technology,2024-05-10,2024-06-15,1845,5.8,Algorithmic Solutions +AI10089,Autonomous Systems Engineer,151012,USD,151012,SE,CT,Denmark,S,Australia,50,"Java, Kubernetes, Linux",Master,6,Healthcare,2025-01-29,2025-04-04,621,9.2,Neural Networks Co +AI10090,Deep Learning Engineer,225202,USD,225202,EX,FL,Norway,S,New Zealand,0,"R, Docker, Deep Learning",Associate,10,Technology,2024-01-15,2024-03-12,2018,7,Predictive Systems +AI10091,Computer Vision Engineer,172242,USD,172242,EX,FT,Denmark,S,Denmark,50,"MLOps, NLP, Spark",Associate,18,Telecommunications,2024-08-15,2024-10-24,500,6.8,Algorithmic Solutions +AI10092,AI Consultant,99624,JPY,10958640,MI,PT,Japan,S,Colombia,100,"R, GCP, Computer Vision, Data Visualization, Hadoop",PhD,3,Technology,2025-03-12,2025-04-17,2365,7.9,Neural Networks Co +AI10093,AI Software Engineer,116417,EUR,98954,SE,CT,Netherlands,M,Netherlands,100,"Kubernetes, GCP, AWS, Tableau",Associate,7,Automotive,2024-12-20,2025-02-26,1379,6.9,DeepTech Ventures +AI10094,Deep Learning Engineer,181783,EUR,154516,EX,PT,France,S,Romania,100,"Python, Mathematics, Hadoop, Java",PhD,19,Education,2024-05-01,2024-06-29,557,5.8,DataVision Ltd +AI10095,AI Research Scientist,150971,AUD,203811,SE,CT,Australia,L,Australia,50,"SQL, Hadoop, Mathematics, Git, Docker",Associate,7,Real Estate,2025-01-16,2025-02-04,2333,7.3,Autonomous Tech +AI10096,ML Ops Engineer,94318,USD,94318,MI,PT,Norway,S,Mexico,50,"Scala, GCP, Java, Git",Bachelor,2,Automotive,2024-03-02,2024-05-07,1541,7.2,Algorithmic Solutions +AI10097,AI Research Scientist,95368,GBP,71526,MI,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, AWS, Docker",Bachelor,2,Finance,2025-04-19,2025-05-17,2341,7,TechCorp Inc +AI10098,AI Product Manager,190518,AUD,257199,EX,FT,Australia,M,Australia,100,"Hadoop, Spark, PyTorch",Associate,15,Energy,2024-01-19,2024-02-10,880,9.8,Machine Intelligence Group +AI10099,Computer Vision Engineer,55407,USD,55407,SE,CT,China,L,China,100,"Statistics, NLP, Scala",Master,5,Government,2024-03-02,2024-03-19,2404,7.2,Neural Networks Co +AI10100,ML Ops Engineer,21909,USD,21909,EN,FL,India,S,India,100,"Spark, Kubernetes, Tableau, Linux, Scala",Master,1,Healthcare,2024-07-27,2024-09-24,2258,6.6,Quantum Computing Inc +AI10101,AI Product Manager,92434,EUR,78569,MI,FL,France,M,South Africa,50,"Spark, SQL, Kubernetes, Deep Learning, Mathematics",PhD,3,Retail,2024-02-18,2024-04-04,562,9.3,Advanced Robotics +AI10102,Data Engineer,161210,USD,161210,SE,PT,Denmark,S,Denmark,100,"SQL, GCP, Statistics, Docker",Associate,6,Manufacturing,2024-02-09,2024-03-15,1008,5.9,Future Systems +AI10103,Head of AI,67818,USD,67818,SE,PT,China,L,Belgium,100,"Git, PyTorch, Tableau, R",Bachelor,5,Education,2024-12-28,2025-03-04,972,6.6,Machine Intelligence Group +AI10104,Computer Vision Engineer,93012,EUR,79060,MI,CT,Netherlands,M,Netherlands,0,"MLOps, Scala, Statistics",PhD,3,Finance,2024-03-20,2024-05-18,1313,5.2,Quantum Computing Inc +AI10105,Data Scientist,44243,USD,44243,MI,FL,China,L,China,100,"Python, Spark, MLOps",Associate,4,Education,2025-04-03,2025-06-01,1470,7.3,Algorithmic Solutions +AI10106,Deep Learning Engineer,73792,CAD,92240,EN,CT,Canada,L,South Korea,50,"MLOps, TensorFlow, Scala, Hadoop",PhD,0,Healthcare,2024-07-27,2024-09-16,1612,7.8,TechCorp Inc +AI10107,Deep Learning Engineer,82816,USD,82816,EX,FL,China,L,China,0,"Java, AWS, Azure, Python",Master,17,Energy,2024-04-16,2024-06-26,1824,5.1,DeepTech Ventures +AI10108,Robotics Engineer,153795,EUR,130726,SE,FT,Netherlands,L,Austria,50,"MLOps, TensorFlow, Docker",PhD,5,Technology,2025-04-25,2025-05-26,1033,5.1,TechCorp Inc +AI10109,Machine Learning Researcher,86614,USD,86614,MI,FT,Finland,L,Finland,0,"Python, TensorFlow, AWS",PhD,3,Education,2025-01-09,2025-02-10,827,8.6,Cloud AI Solutions +AI10110,Autonomous Systems Engineer,75523,EUR,64195,EN,FT,France,L,Russia,100,"R, SQL, Docker, MLOps, PyTorch",Master,1,Transportation,2024-06-18,2024-08-12,1776,6.4,Advanced Robotics +AI10111,Principal Data Scientist,105311,USD,105311,SE,PT,Israel,M,Israel,0,"Java, PyTorch, Statistics",PhD,5,Media,2024-07-16,2024-08-13,1714,8.6,Autonomous Tech +AI10112,Machine Learning Engineer,49131,JPY,5404410,EN,CT,Japan,S,Belgium,50,"Hadoop, GCP, Scala, TensorFlow",Master,1,Healthcare,2024-07-30,2024-09-22,1387,6.7,Machine Intelligence Group +AI10113,Head of AI,26483,USD,26483,EN,FL,China,S,China,50,"Java, Computer Vision, Data Visualization, GCP, PyTorch",PhD,1,Consulting,2024-08-06,2024-10-05,1235,8.1,TechCorp Inc +AI10114,Data Engineer,107269,USD,107269,SE,FT,Israel,S,Australia,100,"PyTorch, Spark, SQL, Linux",Associate,9,Energy,2024-10-02,2024-11-22,1007,6,Future Systems +AI10115,AI Product Manager,78026,USD,78026,EN,FL,Denmark,S,Denmark,100,"Git, Python, Linux, Azure",Bachelor,1,Retail,2024-05-22,2024-07-07,2242,6.5,TechCorp Inc +AI10116,ML Ops Engineer,98849,USD,98849,MI,PT,United States,L,Poland,100,"PyTorch, SQL, Data Visualization, Computer Vision",Associate,4,Consulting,2024-11-04,2024-12-28,540,5.1,DataVision Ltd +AI10117,Machine Learning Engineer,246511,USD,246511,EX,PT,Denmark,S,Russia,50,"Hadoop, Python, Tableau",Master,16,Real Estate,2024-02-18,2024-03-26,812,8.6,Algorithmic Solutions +AI10118,Head of AI,108146,CHF,97331,EN,FL,Switzerland,M,Switzerland,0,"Python, AWS, TensorFlow",PhD,0,Telecommunications,2024-03-07,2024-04-06,794,8.1,Algorithmic Solutions +AI10119,Machine Learning Researcher,66740,JPY,7341400,EN,CT,Japan,M,Canada,50,"Tableau, Linux, Kubernetes, PyTorch, Mathematics",Associate,1,Government,2024-04-25,2024-07-03,1062,5,Machine Intelligence Group +AI10120,Machine Learning Engineer,253573,USD,253573,EX,FT,Norway,L,Norway,50,"PyTorch, Python, Java, Tableau, R",Bachelor,17,Government,2024-05-05,2024-06-14,1950,9.2,Cloud AI Solutions +AI10121,Data Engineer,79168,AUD,106877,MI,FL,Australia,S,Australia,100,"Mathematics, Python, R, Git, TensorFlow",PhD,2,Telecommunications,2024-08-05,2024-09-19,993,6.4,Autonomous Tech +AI10122,Data Analyst,139622,EUR,118679,SE,PT,Netherlands,L,Netherlands,50,"Deep Learning, Mathematics, Hadoop, PyTorch",Master,9,Consulting,2025-04-03,2025-06-01,2392,6.5,Cognitive Computing +AI10123,Machine Learning Engineer,43943,USD,43943,SE,FT,India,S,India,50,"SQL, Scala, Python",PhD,9,Telecommunications,2024-04-13,2024-05-31,1723,7.5,TechCorp Inc +AI10124,AI Research Scientist,162422,GBP,121817,EX,FT,United Kingdom,S,United Kingdom,0,"Git, SQL, NLP, Azure, Linux",Master,17,Education,2024-05-16,2024-07-05,1442,5.3,Advanced Robotics +AI10125,ML Ops Engineer,43406,USD,43406,EN,CT,South Korea,S,Mexico,50,"Kubernetes, Java, R, SQL",Bachelor,0,Consulting,2024-09-10,2024-10-02,2472,9.5,Cloud AI Solutions +AI10126,Data Analyst,95920,JPY,10551200,MI,FT,Japan,L,Japan,100,"Python, TensorFlow, Mathematics",Master,2,Transportation,2024-12-02,2025-01-08,2081,9.2,Neural Networks Co +AI10127,AI Consultant,197698,EUR,168043,EX,FT,Germany,S,Germany,100,"GCP, Azure, Python, PyTorch, Java",Master,13,Finance,2024-10-22,2024-12-02,718,5.8,Future Systems +AI10128,AI Specialist,173515,AUD,234245,EX,FT,Australia,L,Nigeria,0,"Python, Scala, AWS, TensorFlow, Linux",Bachelor,16,Finance,2024-02-11,2024-03-27,1432,5.6,AI Innovations +AI10129,AI Specialist,192426,AUD,259775,EX,FL,Australia,L,Philippines,50,"Statistics, Hadoop, SQL",PhD,11,Gaming,2024-04-02,2024-05-30,1928,8.3,Cognitive Computing +AI10130,Research Scientist,212764,USD,212764,SE,CT,Denmark,L,Denmark,50,"Linux, Kubernetes, Data Visualization",Bachelor,8,Technology,2024-09-05,2024-10-01,2235,8.8,Machine Intelligence Group +AI10131,Autonomous Systems Engineer,50136,USD,50136,EN,PT,Finland,M,Finland,0,"AWS, Git, SQL, Azure, Linux",Master,0,Education,2024-10-12,2024-11-30,1646,5.1,Algorithmic Solutions +AI10132,AI Consultant,199327,EUR,169428,EX,FL,Austria,S,Latvia,50,"Python, SQL, Mathematics, Deep Learning",Bachelor,14,Real Estate,2024-04-05,2024-05-26,1617,5.3,AI Innovations +AI10133,AI Architect,104098,CHF,93688,EN,FL,Switzerland,L,Indonesia,100,"Git, Java, Python, TensorFlow, Mathematics",Associate,0,Manufacturing,2024-03-05,2024-04-23,1488,7.5,Quantum Computing Inc +AI10134,Research Scientist,89534,USD,89534,MI,FT,Finland,S,Finland,0,"Kubernetes, Docker, R, Hadoop, PyTorch",PhD,2,Finance,2024-07-07,2024-09-10,2258,8.5,Cloud AI Solutions +AI10135,NLP Engineer,72126,CAD,90158,EN,CT,Canada,L,Canada,0,"Spark, Git, Computer Vision, PyTorch, Kubernetes",PhD,0,Education,2024-09-06,2024-11-11,679,9.5,DataVision Ltd +AI10136,Autonomous Systems Engineer,120139,USD,120139,SE,FL,Sweden,S,Netherlands,100,"Mathematics, Python, Linux, SQL",Master,6,Healthcare,2024-03-05,2024-03-22,1834,8.2,Smart Analytics +AI10137,NLP Engineer,209827,CHF,188844,EX,CT,Switzerland,M,Switzerland,0,"Python, Tableau, Data Visualization, NLP",Master,17,Government,2024-01-31,2024-03-24,1007,5.5,Machine Intelligence Group +AI10138,NLP Engineer,63620,JPY,6998200,EN,FL,Japan,M,Japan,50,"Computer Vision, R, MLOps, SQL, PyTorch",Master,0,Healthcare,2025-04-13,2025-06-21,696,8.1,Autonomous Tech +AI10139,Robotics Engineer,43464,USD,43464,EN,CT,China,L,China,0,"PyTorch, AWS, Hadoop, NLP, Spark",PhD,0,Retail,2025-02-06,2025-04-15,1875,8.6,DeepTech Ventures +AI10140,Machine Learning Researcher,81847,USD,81847,SE,PT,China,L,Czech Republic,0,"MLOps, Data Visualization, AWS, Scala",PhD,9,Technology,2024-05-22,2024-08-01,799,8.2,Neural Networks Co +AI10141,ML Ops Engineer,125011,GBP,93758,SE,CT,United Kingdom,S,Germany,50,"Linux, Azure, Git, Computer Vision, TensorFlow",Master,9,Gaming,2024-09-08,2024-09-25,977,7,Algorithmic Solutions +AI10142,Deep Learning Engineer,253282,CAD,316603,EX,FT,Canada,L,Kenya,0,"Python, Git, TensorFlow, Azure, PyTorch",Associate,18,Finance,2024-10-09,2024-12-10,1585,6.8,DataVision Ltd +AI10143,Data Analyst,163715,USD,163715,EX,FL,Finland,S,Finland,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Media,2025-01-19,2025-02-05,1900,8.5,Advanced Robotics +AI10144,Head of AI,71407,EUR,60696,EN,FL,Germany,S,Indonesia,50,"SQL, Tableau, PyTorch",Master,0,Energy,2024-12-08,2025-02-12,1897,6.3,Quantum Computing Inc +AI10145,Deep Learning Engineer,66634,USD,66634,EN,PT,Ireland,L,Ireland,100,"AWS, Deep Learning, SQL, Azure, PyTorch",Associate,0,Media,2024-02-24,2024-03-23,1775,9.5,Digital Transformation LLC +AI10146,Autonomous Systems Engineer,160350,EUR,136298,EX,PT,Germany,M,Germany,50,"Spark, Kubernetes, MLOps, Python, Computer Vision",Associate,10,Energy,2025-04-20,2025-05-08,681,7.6,AI Innovations +AI10147,Deep Learning Engineer,119141,EUR,101270,SE,FT,Netherlands,M,Chile,50,"Hadoop, Azure, Git, Computer Vision, Scala",PhD,7,Finance,2024-04-04,2024-05-30,923,7.7,AI Innovations +AI10148,Machine Learning Engineer,92580,USD,92580,MI,FL,Israel,L,Israel,100,"GCP, Kubernetes, Computer Vision",Associate,4,Education,2024-07-19,2024-09-18,2309,9.4,Autonomous Tech +AI10149,Data Engineer,145627,AUD,196596,SE,PT,Australia,L,Australia,50,"Scala, Deep Learning, Computer Vision",PhD,5,Government,2024-08-16,2024-10-08,530,5.3,Algorithmic Solutions +AI10150,AI Specialist,213045,EUR,181088,EX,PT,Germany,M,Thailand,50,"Docker, MLOps, Kubernetes",Bachelor,12,Manufacturing,2025-03-18,2025-05-01,1675,7.7,Cognitive Computing +AI10151,Computer Vision Engineer,297403,SGD,386624,EX,FT,Singapore,L,Singapore,50,"Computer Vision, Python, Azure, Data Visualization",Bachelor,14,Finance,2024-05-18,2024-06-13,964,5.2,TechCorp Inc +AI10152,Data Analyst,69197,EUR,58817,MI,FT,France,S,France,0,"TensorFlow, MLOps, Java",Master,3,Gaming,2024-11-24,2024-12-30,2362,7.6,Smart Analytics +AI10153,Data Analyst,132689,USD,132689,SE,FT,Israel,L,Israel,100,"Computer Vision, Spark, Python, Mathematics, MLOps",Bachelor,7,Gaming,2024-04-14,2024-05-01,1072,6,Neural Networks Co +AI10154,Computer Vision Engineer,83336,GBP,62502,MI,FL,United Kingdom,S,Italy,50,"PyTorch, MLOps, SQL, Spark",PhD,2,Real Estate,2024-12-17,2025-01-23,2268,5.4,Predictive Systems +AI10155,AI Consultant,172090,JPY,18929900,SE,FT,Japan,L,Japan,0,"NLP, SQL, TensorFlow, Spark",Associate,5,Media,2024-10-30,2024-11-30,1316,8.8,DeepTech Ventures +AI10156,AI Product Manager,24926,USD,24926,EN,PT,China,M,China,0,"Mathematics, NLP, Data Visualization, Deep Learning, Hadoop",Associate,0,Healthcare,2025-04-13,2025-06-19,853,9.2,Advanced Robotics +AI10157,Data Analyst,211550,EUR,179818,EX,FL,Austria,L,Austria,100,"AWS, Kubernetes, NLP",Bachelor,17,Gaming,2025-01-31,2025-04-07,1102,5.6,Digital Transformation LLC +AI10158,NLP Engineer,104635,USD,104635,SE,PT,Finland,S,Finland,100,"Deep Learning, Scala, Tableau",Master,6,Real Estate,2024-10-17,2024-12-18,623,6.9,Digital Transformation LLC +AI10159,Data Scientist,67458,USD,67458,EN,FT,Finland,S,Finland,50,"Python, Azure, Tableau, Java",Master,1,Government,2024-03-05,2024-04-03,2364,5.5,Predictive Systems +AI10160,Research Scientist,137160,USD,137160,SE,CT,Sweden,L,Sweden,100,"Docker, Tableau, GCP, R",Associate,8,Retail,2024-01-04,2024-03-13,839,7.5,Cloud AI Solutions +AI10161,Head of AI,68285,USD,68285,EN,PT,Norway,S,Norway,50,"Java, Azure, AWS, Statistics, Computer Vision",Bachelor,0,Automotive,2025-03-24,2025-04-15,1170,9.8,Quantum Computing Inc +AI10162,Machine Learning Researcher,74005,CHF,66605,EN,FT,Switzerland,S,Philippines,100,"Hadoop, R, NLP",Associate,0,Manufacturing,2024-03-18,2024-04-09,1639,6.8,Cognitive Computing +AI10163,AI Architect,127491,JPY,14024010,SE,PT,Japan,M,Czech Republic,0,"SQL, Docker, Data Visualization, Mathematics",Associate,5,Real Estate,2024-08-26,2024-09-24,990,7.8,DeepTech Ventures +AI10164,Principal Data Scientist,64002,USD,64002,EX,FL,China,S,China,0,"Python, GCP, Data Visualization, MLOps",Master,14,Real Estate,2024-04-29,2024-05-31,1479,9.6,Advanced Robotics +AI10165,Data Analyst,87641,USD,87641,MI,FT,South Korea,L,South Korea,100,"SQL, NLP, Statistics, GCP, Java",PhD,4,Media,2024-03-28,2024-06-03,2285,8.9,DataVision Ltd +AI10166,Autonomous Systems Engineer,54064,JPY,5947040,EN,PT,Japan,S,Poland,0,"PyTorch, Docker, R, Deep Learning, Java",Master,0,Retail,2025-01-02,2025-03-06,1094,6.7,Machine Intelligence Group +AI10167,Research Scientist,92164,USD,92164,MI,CT,Denmark,S,Denmark,100,"Azure, NLP, Python, Statistics, Scala",PhD,4,Real Estate,2024-03-28,2024-06-01,2147,9.1,Autonomous Tech +AI10168,AI Product Manager,303272,USD,303272,EX,FT,Norway,L,Norway,0,"SQL, Spark, Tableau, PyTorch, Hadoop",PhD,11,Real Estate,2025-04-02,2025-04-20,1007,8.3,Cognitive Computing +AI10169,Data Analyst,125114,USD,125114,EX,FT,Sweden,S,Sweden,50,"Kubernetes, Git, Deep Learning, Computer Vision, Scala",Bachelor,12,Technology,2024-08-12,2024-09-08,2065,9.5,AI Innovations +AI10170,Deep Learning Engineer,54317,USD,54317,EN,CT,Ireland,M,Egypt,50,"Deep Learning, Spark, TensorFlow, PyTorch, Azure",Bachelor,1,Education,2025-03-20,2025-05-11,1082,6.1,DataVision Ltd +AI10171,Principal Data Scientist,75401,GBP,56551,MI,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, Data Visualization, Java",Bachelor,4,Healthcare,2024-08-02,2024-09-25,1106,8.8,DeepTech Ventures +AI10172,ML Ops Engineer,125780,USD,125780,SE,FL,Ireland,L,Ireland,0,"TensorFlow, Python, Computer Vision, SQL, Scala",Master,5,Real Estate,2024-08-25,2024-09-09,1249,8.9,Quantum Computing Inc +AI10173,Machine Learning Researcher,92433,USD,92433,EN,PT,Denmark,M,Denmark,0,"Python, TensorFlow, Azure, Computer Vision",Associate,0,Finance,2025-03-31,2025-05-24,2132,5.2,Cloud AI Solutions +AI10174,AI Specialist,64856,GBP,48642,EN,CT,United Kingdom,L,Ukraine,50,"Java, R, Tableau",PhD,1,Gaming,2024-07-14,2024-08-09,1592,6.5,TechCorp Inc +AI10175,Autonomous Systems Engineer,403493,CHF,363144,EX,FL,Switzerland,L,Switzerland,100,"Git, SQL, Spark, PyTorch",PhD,14,Gaming,2025-03-15,2025-05-05,1045,5.5,Cognitive Computing +AI10176,NLP Engineer,68862,USD,68862,EX,CT,India,L,India,100,"PyTorch, SQL, Tableau",PhD,17,Manufacturing,2024-10-20,2024-11-11,988,5.2,Machine Intelligence Group +AI10177,AI Consultant,210010,GBP,157508,EX,CT,United Kingdom,S,United Kingdom,0,"Spark, GCP, Linux",Bachelor,18,Media,2025-04-16,2025-06-14,1217,7.5,Neural Networks Co +AI10178,Machine Learning Researcher,123778,AUD,167100,SE,FT,Australia,L,Turkey,0,"Linux, Python, Tableau, Mathematics",Bachelor,5,Healthcare,2024-03-26,2024-06-04,1700,10,Cognitive Computing +AI10179,Machine Learning Researcher,70793,SGD,92031,MI,FT,Singapore,S,Singapore,100,"R, SQL, Azure",Associate,2,Gaming,2025-02-04,2025-03-15,739,8,DataVision Ltd +AI10180,Autonomous Systems Engineer,135779,EUR,115412,EX,PT,Germany,S,Indonesia,50,"Deep Learning, Git, Spark, GCP, Azure",Master,18,Telecommunications,2024-05-03,2024-07-09,1937,5.3,AI Innovations +AI10181,AI Specialist,70351,USD,70351,MI,CT,Finland,S,Finland,100,"SQL, NLP, TensorFlow",Master,4,Healthcare,2024-03-07,2024-03-25,1223,7.8,AI Innovations +AI10182,AI Architect,168478,CHF,151630,MI,FL,Switzerland,L,Switzerland,50,"Git, Kubernetes, PyTorch, R, SQL",Master,2,Education,2024-06-03,2024-08-06,1027,8,DeepTech Ventures +AI10183,Robotics Engineer,132893,USD,132893,EX,FT,Israel,S,Israel,0,"Computer Vision, Python, TensorFlow, Mathematics, Linux",Bachelor,17,Real Estate,2024-11-17,2024-12-02,2289,9.3,Future Systems +AI10184,Data Engineer,277707,GBP,208280,EX,FT,United Kingdom,L,United Kingdom,50,"Git, R, Statistics, Data Visualization",Associate,13,Retail,2024-12-21,2025-01-09,1010,7.9,DataVision Ltd +AI10185,NLP Engineer,131380,USD,131380,MI,FT,United States,L,United States,100,"PyTorch, TensorFlow, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-02-17,2024-04-04,604,10,TechCorp Inc +AI10186,AI Specialist,104109,USD,104109,SE,FT,South Korea,S,Brazil,100,"Deep Learning, AWS, Kubernetes, SQL, PyTorch",Associate,7,Real Estate,2024-04-29,2024-07-08,1705,6.8,Cloud AI Solutions +AI10187,Autonomous Systems Engineer,144897,EUR,123162,SE,PT,Netherlands,L,Netherlands,100,"Spark, Computer Vision, Hadoop",Associate,7,Manufacturing,2024-10-07,2024-11-07,1202,5.7,DataVision Ltd +AI10188,Machine Learning Engineer,234506,SGD,304858,EX,FL,Singapore,S,Singapore,100,"Python, Kubernetes, Spark, Mathematics",Associate,12,Education,2024-12-28,2025-03-08,1410,6.5,Future Systems +AI10189,NLP Engineer,138684,USD,138684,MI,PT,Denmark,M,Denmark,50,"Python, Tableau, Azure, PyTorch",Master,4,Manufacturing,2024-07-25,2024-08-28,1314,7.5,Cloud AI Solutions +AI10190,Machine Learning Engineer,91626,USD,91626,MI,FL,Ireland,S,Ireland,0,"Data Visualization, Deep Learning, MLOps, Spark",Associate,3,Government,2024-06-30,2024-08-10,1506,6.3,Smart Analytics +AI10191,AI Consultant,227796,USD,227796,EX,FT,United States,S,Germany,100,"R, Hadoop, Docker",Master,11,Finance,2024-10-07,2024-10-22,728,6.8,Quantum Computing Inc +AI10192,Machine Learning Engineer,237622,EUR,201979,EX,FT,Germany,M,Germany,100,"TensorFlow, Python, Scala",Associate,11,Technology,2024-06-30,2024-07-27,788,9.8,Digital Transformation LLC +AI10193,Autonomous Systems Engineer,59553,JPY,6550830,EN,CT,Japan,M,Japan,100,"SQL, GCP, PyTorch, Java",Associate,1,Government,2024-11-02,2024-11-25,2408,5.6,Machine Intelligence Group +AI10194,Data Engineer,75248,EUR,63961,MI,FT,Austria,S,Austria,50,"Spark, TensorFlow, Linux",Bachelor,4,Finance,2024-02-08,2024-04-17,1561,6.8,Cloud AI Solutions +AI10195,AI Product Manager,44563,USD,44563,SE,FT,India,M,Hungary,0,"Java, Linux, Python, Spark",Master,5,Automotive,2024-12-17,2025-02-25,1663,7.9,Quantum Computing Inc +AI10196,AI Consultant,186290,CHF,167661,SE,CT,Switzerland,M,Switzerland,0,"Tableau, Kubernetes, Git",Master,8,Real Estate,2025-04-30,2025-05-31,1747,5.6,DataVision Ltd +AI10197,AI Consultant,130662,EUR,111063,EX,CT,France,S,France,100,"Python, Azure, Tableau, Linux",Master,13,Technology,2024-09-06,2024-10-29,2453,6.7,DeepTech Ventures +AI10198,Principal Data Scientist,202772,USD,202772,EX,CT,Ireland,S,Ireland,100,"Computer Vision, Docker, Statistics",Associate,11,Telecommunications,2025-02-06,2025-04-08,514,5.3,Digital Transformation LLC +AI10199,AI Product Manager,190276,USD,190276,EX,CT,Sweden,L,Sweden,50,"Kubernetes, Docker, Python",Master,18,Gaming,2025-04-02,2025-04-25,1339,5.8,Smart Analytics +AI10200,AI Architect,99498,EUR,84573,SE,CT,Netherlands,S,Switzerland,100,"Mathematics, Tableau, R, Java",Associate,6,Automotive,2024-04-03,2024-04-23,1999,9.7,Cognitive Computing +AI10201,AI Product Manager,190361,AUD,256987,EX,FT,Australia,M,Australia,0,"GCP, Deep Learning, Python, Linux",Master,15,Gaming,2024-12-24,2025-02-04,1361,7.6,Autonomous Tech +AI10202,Head of AI,62384,USD,62384,EN,FT,United States,M,United States,0,"Git, Azure, Deep Learning",Master,1,Energy,2024-09-14,2024-11-17,541,8,Smart Analytics +AI10203,AI Research Scientist,139626,USD,139626,SE,FT,Norway,M,Norway,100,"Scala, Python, NLP, Docker, AWS",Associate,8,Media,2024-12-04,2025-01-11,1764,8.7,AI Innovations +AI10204,AI Software Engineer,76788,USD,76788,EX,FL,India,S,India,50,"NLP, Kubernetes, GCP, Python, Java",Master,17,Manufacturing,2024-08-19,2024-09-07,2043,6.8,TechCorp Inc +AI10205,Robotics Engineer,177449,USD,177449,SE,CT,Norway,L,Norway,0,"Docker, Statistics, Python, Tableau",Bachelor,8,Healthcare,2024-06-08,2024-07-10,2020,8.5,AI Innovations +AI10206,Data Analyst,61915,USD,61915,EN,FL,Finland,L,Finland,0,"Mathematics, R, NLP",PhD,0,Energy,2025-02-24,2025-04-05,2439,7.3,Machine Intelligence Group +AI10207,Research Scientist,59769,SGD,77700,EN,CT,Singapore,S,Singapore,0,"R, AWS, Linux",Bachelor,0,Transportation,2024-09-05,2024-09-26,796,8.3,Cognitive Computing +AI10208,Autonomous Systems Engineer,102469,CHF,92222,MI,CT,Switzerland,M,Germany,0,"PyTorch, Kubernetes, Docker, SQL",PhD,2,Transportation,2024-10-17,2024-11-14,1833,6.8,TechCorp Inc +AI10209,Autonomous Systems Engineer,144818,USD,144818,MI,CT,Denmark,L,Denmark,0,"R, Hadoop, Scala, PyTorch",PhD,2,Technology,2024-09-03,2024-10-10,812,6.3,Digital Transformation LLC +AI10210,Principal Data Scientist,151885,CAD,189856,SE,PT,Canada,L,Canada,50,"Docker, Tableau, Data Visualization",Associate,7,Media,2025-03-27,2025-05-17,1140,9.6,Smart Analytics +AI10211,AI Consultant,76782,USD,76782,EN,PT,United States,L,United States,0,"GCP, Mathematics, AWS",PhD,1,Education,2024-04-03,2024-04-25,1697,5.3,Algorithmic Solutions +AI10212,Head of AI,76167,USD,76167,MI,CT,Sweden,M,Sweden,0,"Spark, Scala, SQL",Bachelor,3,Government,2024-08-09,2024-10-19,1139,7.8,Quantum Computing Inc +AI10213,Research Scientist,109222,SGD,141989,MI,PT,Singapore,M,Singapore,0,"Python, TensorFlow, Java",PhD,3,Automotive,2024-09-26,2024-11-13,1852,8.3,Algorithmic Solutions +AI10214,Robotics Engineer,112535,CAD,140669,SE,FT,Canada,L,Vietnam,50,"Kubernetes, GCP, Data Visualization, SQL",PhD,7,Transportation,2025-03-16,2025-05-24,1174,8.7,Quantum Computing Inc +AI10215,Principal Data Scientist,283415,USD,283415,EX,FT,Sweden,L,Japan,50,"Computer Vision, Statistics, Docker",PhD,19,Automotive,2024-10-10,2024-12-22,1359,5.2,Algorithmic Solutions +AI10216,Data Scientist,75965,EUR,64570,MI,FT,Germany,M,Germany,50,"AWS, Linux, Hadoop, R, MLOps",PhD,4,Government,2024-10-16,2024-11-12,2301,8.4,Machine Intelligence Group +AI10217,NLP Engineer,91675,EUR,77924,MI,FL,Austria,M,Austria,0,"TensorFlow, AWS, Statistics",Bachelor,4,Consulting,2024-12-24,2025-02-16,515,8.9,Quantum Computing Inc +AI10218,Data Scientist,142668,CAD,178335,EX,PT,Canada,S,Canada,0,"Python, Java, Git, Spark, Azure",Associate,15,Consulting,2024-11-03,2024-11-27,2152,6.1,AI Innovations +AI10219,AI Specialist,65229,CAD,81536,EN,FL,Canada,S,Russia,100,"Python, Kubernetes, TensorFlow, Hadoop",Associate,1,Media,2024-01-02,2024-02-16,1513,7.5,Machine Intelligence Group +AI10220,Machine Learning Engineer,80835,CAD,101044,MI,FL,Canada,S,Singapore,100,"Data Visualization, Scala, Kubernetes, Deep Learning, GCP",PhD,2,Healthcare,2024-11-28,2025-01-01,1934,5.8,Autonomous Tech +AI10221,Deep Learning Engineer,250293,SGD,325381,EX,FL,Singapore,M,Singapore,100,"Kubernetes, Java, SQL, PyTorch, Azure",Associate,13,Finance,2024-03-10,2024-04-25,2222,7.5,Algorithmic Solutions +AI10222,AI Architect,162995,CHF,146696,MI,FT,Switzerland,L,Switzerland,0,"Git, Java, Spark, Python, GCP",Master,2,Retail,2025-01-07,2025-02-23,2411,9.5,DataVision Ltd +AI10223,AI Consultant,247822,USD,247822,EX,FL,Norway,M,Norway,100,"Git, Tableau, Deep Learning, Docker",Bachelor,19,Gaming,2024-02-26,2024-04-14,573,8.5,Cloud AI Solutions +AI10224,Machine Learning Engineer,168577,AUD,227579,SE,FL,Australia,L,Indonesia,100,"Hadoop, Kubernetes, Scala, Azure",Bachelor,6,Transportation,2024-06-01,2024-06-22,1731,6.2,Cognitive Computing +AI10225,Deep Learning Engineer,86183,USD,86183,EN,PT,Ireland,L,Ireland,100,"Data Visualization, Linux, PyTorch, TensorFlow",Associate,1,Government,2024-03-24,2024-04-13,929,6.4,Machine Intelligence Group +AI10226,AI Product Manager,95435,USD,95435,EN,FT,Norway,M,Ukraine,50,"SQL, Tableau, AWS, Java, R",PhD,0,Government,2024-09-16,2024-10-25,882,9.1,Advanced Robotics +AI10227,Robotics Engineer,86159,JPY,9477490,MI,FL,Japan,S,Japan,50,"GCP, NLP, PyTorch, Python",Bachelor,4,Education,2024-03-31,2024-05-05,1672,5.1,Advanced Robotics +AI10228,Deep Learning Engineer,30009,USD,30009,EN,CT,China,L,China,100,"Java, Linux, NLP, Git, Spark",Bachelor,0,Retail,2025-01-06,2025-02-09,1576,9.5,Advanced Robotics +AI10229,Robotics Engineer,65632,USD,65632,EN,PT,Finland,S,Finland,100,"Git, Python, SQL, GCP",Bachelor,1,Government,2025-03-24,2025-06-04,911,5.5,Cloud AI Solutions +AI10230,Data Engineer,161846,USD,161846,SE,PT,Israel,L,Israel,50,"GCP, Spark, Linux",PhD,6,Healthcare,2024-11-20,2024-12-15,2142,6.7,Quantum Computing Inc +AI10231,AI Research Scientist,67413,EUR,57301,EN,CT,Netherlands,S,Netherlands,0,"Azure, SQL, Data Visualization",PhD,1,Automotive,2024-06-26,2024-08-10,624,5.2,Digital Transformation LLC +AI10232,AI Architect,95990,USD,95990,SE,FL,Finland,S,Finland,0,"Tableau, TensorFlow, Kubernetes, SQL, GCP",PhD,9,Consulting,2024-02-15,2024-04-20,1850,9.3,TechCorp Inc +AI10233,Research Scientist,80350,CAD,100438,MI,CT,Canada,S,Canada,100,"NLP, SQL, PyTorch, Deep Learning, MLOps",Associate,4,Gaming,2024-10-15,2024-12-27,2154,6.5,Advanced Robotics +AI10234,Robotics Engineer,135564,USD,135564,EX,PT,China,L,China,50,"PyTorch, Kubernetes, TensorFlow, Linux",Master,16,Healthcare,2024-12-06,2025-02-01,586,8.8,Smart Analytics +AI10235,AI Software Engineer,218274,JPY,24010140,EX,PT,Japan,L,Japan,0,"GCP, Spark, Data Visualization",Bachelor,12,Healthcare,2024-12-04,2025-01-27,1162,5.3,Cognitive Computing +AI10236,NLP Engineer,79956,USD,79956,MI,FT,Israel,L,Israel,50,"SQL, Statistics, AWS, Docker",Associate,3,Manufacturing,2024-05-16,2024-07-06,2101,5.8,DeepTech Ventures +AI10237,AI Product Manager,210360,USD,210360,EX,PT,Ireland,L,Hungary,50,"Python, Computer Vision, Mathematics",Master,11,Government,2024-10-08,2024-12-06,1305,7.1,DeepTech Ventures +AI10238,AI Software Engineer,203510,USD,203510,EX,PT,Finland,M,France,50,"Python, Hadoop, Linux",Associate,14,Finance,2024-06-29,2024-08-26,1073,7.3,TechCorp Inc +AI10239,Principal Data Scientist,54946,USD,54946,MI,FL,China,L,Norway,0,"Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,2,Energy,2024-04-27,2024-06-21,761,6.2,TechCorp Inc +AI10240,Deep Learning Engineer,301525,USD,301525,EX,FT,Norway,M,Norway,0,"Tableau, Kubernetes, Linux, AWS",PhD,15,Media,2024-10-16,2024-12-26,1359,9,TechCorp Inc +AI10241,Data Engineer,54730,AUD,73886,EN,CT,Australia,M,Australia,50,"Scala, Kubernetes, Deep Learning, GCP, SQL",Bachelor,0,Automotive,2024-09-07,2024-10-31,641,6.1,TechCorp Inc +AI10242,Data Engineer,70076,USD,70076,MI,CT,South Korea,M,South Korea,0,"Git, Hadoop, GCP",Bachelor,3,Transportation,2024-03-25,2024-05-26,1249,7,Predictive Systems +AI10243,Robotics Engineer,140236,USD,140236,EX,FL,South Korea,M,South Korea,0,"Spark, R, Java, Data Visualization, Tableau",Associate,14,Energy,2025-04-14,2025-06-15,1958,9.3,Machine Intelligence Group +AI10244,AI Consultant,76319,CHF,68687,EN,CT,Switzerland,S,South Africa,0,"Spark, Git, SQL",Associate,1,Gaming,2024-02-18,2024-03-10,1721,7.5,Quantum Computing Inc +AI10245,Principal Data Scientist,117897,USD,117897,EN,PT,Denmark,L,Philippines,0,"Spark, Tableau, Java",Bachelor,1,Retail,2024-12-02,2025-01-09,1874,6,AI Innovations +AI10246,Principal Data Scientist,67144,USD,67144,EX,FT,India,M,India,0,"Git, Python, NLP, Deep Learning, R",Associate,18,Finance,2024-02-13,2024-02-27,849,5.1,Predictive Systems +AI10247,Computer Vision Engineer,77616,EUR,65974,EN,CT,France,L,France,50,"AWS, Computer Vision, Data Visualization, MLOps, Statistics",Bachelor,0,Government,2024-04-04,2024-06-02,1095,6.9,Machine Intelligence Group +AI10248,Research Scientist,141826,USD,141826,MI,CT,Norway,L,Norway,0,"Python, Kubernetes, SQL, Linux, Hadoop",Associate,3,Real Estate,2024-11-12,2025-01-11,2171,5.3,DeepTech Ventures +AI10249,Data Engineer,73463,JPY,8080930,EN,FT,Japan,S,Japan,100,"Python, Git, NLP, GCP, Hadoop",Bachelor,1,Manufacturing,2024-07-11,2024-08-05,1343,6.1,Machine Intelligence Group +AI10250,AI Research Scientist,109715,USD,109715,MI,CT,Denmark,M,Denmark,0,"Docker, SQL, PyTorch, Spark",Bachelor,4,Finance,2024-02-05,2024-03-04,2237,7,DeepTech Ventures +AI10251,Robotics Engineer,69994,EUR,59495,MI,FT,Austria,M,Austria,0,"Statistics, Azure, Python",Bachelor,2,Manufacturing,2025-04-15,2025-05-07,1393,5.8,Predictive Systems +AI10252,NLP Engineer,117074,CHF,105367,MI,CT,Switzerland,S,Colombia,100,"GCP, Azure, NLP, TensorFlow",Master,4,Manufacturing,2025-02-13,2025-03-17,1001,6.5,DataVision Ltd +AI10253,Computer Vision Engineer,105296,GBP,78972,MI,FL,United Kingdom,S,United Kingdom,100,"Scala, Computer Vision, GCP, NLP, Git",Associate,3,Gaming,2024-05-09,2024-07-20,1754,8.6,DeepTech Ventures +AI10254,Head of AI,165753,CHF,149178,SE,FL,Switzerland,S,Netherlands,50,"Deep Learning, Hadoop, Java",Associate,9,Real Estate,2024-07-11,2024-08-17,1737,9.4,Cloud AI Solutions +AI10255,Deep Learning Engineer,136546,SGD,177510,SE,CT,Singapore,L,Japan,50,"SQL, R, NLP",Associate,5,Finance,2024-10-14,2024-11-05,1371,6.2,Cloud AI Solutions +AI10256,ML Ops Engineer,61219,USD,61219,EN,CT,Israel,M,Indonesia,0,"Kubernetes, MLOps, Scala",Master,0,Consulting,2025-01-01,2025-03-09,1568,8.3,DeepTech Ventures +AI10257,Head of AI,86631,EUR,73636,MI,FT,Austria,M,Austria,0,"Docker, SQL, Mathematics",PhD,2,Manufacturing,2024-01-20,2024-03-17,1632,7,Autonomous Tech +AI10258,AI Consultant,226414,USD,226414,EX,PT,Ireland,M,Ireland,100,"NLP, Azure, Deep Learning",Associate,13,Education,2024-07-26,2024-09-18,666,9.4,Neural Networks Co +AI10259,AI Research Scientist,113616,EUR,96574,SE,FT,Netherlands,S,Netherlands,50,"Scala, Hadoop, Computer Vision, Deep Learning",Master,7,Retail,2025-04-09,2025-06-14,1885,6,Smart Analytics +AI10260,Principal Data Scientist,191958,USD,191958,SE,FL,Norway,L,Norway,0,"Mathematics, Computer Vision, Kubernetes",Bachelor,6,Healthcare,2025-04-12,2025-05-03,1954,8.1,AI Innovations +AI10261,AI Research Scientist,50163,CAD,62704,EN,CT,Canada,S,Brazil,50,"Git, PyTorch, TensorFlow",PhD,1,Telecommunications,2025-03-03,2025-03-27,2229,8.6,TechCorp Inc +AI10262,Robotics Engineer,337422,USD,337422,EX,FL,United States,L,Sweden,100,"Linux, NLP, TensorFlow, Docker, Mathematics",PhD,12,Government,2024-04-21,2024-05-20,1783,9.7,Cognitive Computing +AI10263,AI Architect,67566,USD,67566,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Data Visualization, Git",Associate,1,Telecommunications,2024-10-21,2025-01-01,1563,6.5,Cloud AI Solutions +AI10264,AI Specialist,59923,EUR,50935,EN,FL,Netherlands,M,Australia,100,"Docker, Python, Deep Learning, SQL, Statistics",Bachelor,0,Education,2025-03-06,2025-04-26,2410,5.9,DataVision Ltd +AI10265,Data Engineer,238139,EUR,202418,EX,CT,France,M,France,50,"Deep Learning, Hadoop, Python, Docker, Git",Associate,12,Education,2024-01-19,2024-02-27,786,9.9,Advanced Robotics +AI10266,Research Scientist,231140,USD,231140,EX,PT,Israel,L,Israel,100,"SQL, PyTorch, R, Spark",Bachelor,16,Transportation,2024-02-02,2024-04-12,1351,6.2,Neural Networks Co +AI10267,Principal Data Scientist,124660,JPY,13712600,SE,PT,Japan,M,Japan,0,"Scala, Azure, Linux",Bachelor,7,Retail,2024-02-22,2024-05-02,1365,6.9,Cloud AI Solutions +AI10268,AI Product Manager,147934,USD,147934,SE,FL,Sweden,L,Finland,50,"R, SQL, PyTorch, Hadoop, Mathematics",Associate,5,Retail,2024-05-04,2024-07-15,2042,8.7,Digital Transformation LLC +AI10269,NLP Engineer,154109,USD,154109,SE,PT,Sweden,L,Argentina,0,"Python, Kubernetes, MLOps, NLP, TensorFlow",Bachelor,5,Technology,2024-06-14,2024-08-06,652,9.6,Machine Intelligence Group +AI10270,Head of AI,182664,SGD,237463,SE,PT,Singapore,L,Singapore,100,"SQL, PyTorch, NLP, TensorFlow, Statistics",Associate,8,Education,2024-08-08,2024-10-05,1732,5.8,AI Innovations +AI10271,AI Research Scientist,106779,GBP,80084,MI,PT,United Kingdom,L,Thailand,0,"Mathematics, SQL, Git",Associate,2,Retail,2024-03-22,2024-05-25,2379,7.7,TechCorp Inc +AI10272,Principal Data Scientist,76695,SGD,99704,EN,PT,Singapore,S,Indonesia,0,"Data Visualization, TensorFlow, MLOps",Bachelor,0,Manufacturing,2024-08-27,2024-10-30,1852,6.8,Machine Intelligence Group +AI10273,Deep Learning Engineer,33529,USD,33529,EN,CT,China,M,China,50,"Kubernetes, Deep Learning, GCP",PhD,1,Consulting,2024-10-11,2024-11-07,1608,7.6,Advanced Robotics +AI10274,Machine Learning Researcher,92400,EUR,78540,EN,CT,Germany,L,Germany,100,"Linux, Mathematics, Hadoop, Spark, Java",Associate,0,Government,2024-05-15,2024-07-12,1559,8.9,Cognitive Computing +AI10275,Autonomous Systems Engineer,222418,USD,222418,EX,FT,United States,M,United States,100,"Azure, Kubernetes, Deep Learning",Bachelor,17,Media,2025-03-01,2025-04-25,1951,9.3,Quantum Computing Inc +AI10276,AI Product Manager,86393,EUR,73434,EN,CT,Netherlands,L,Ukraine,50,"TensorFlow, Azure, Computer Vision",Associate,1,Automotive,2025-01-02,2025-02-15,1735,5.6,Quantum Computing Inc +AI10277,AI Software Engineer,122637,USD,122637,SE,PT,Norway,S,Norway,100,"NLP, Scala, R, Azure",PhD,8,Automotive,2024-04-15,2024-05-14,1246,9,Algorithmic Solutions +AI10278,ML Ops Engineer,190440,AUD,257094,EX,PT,Australia,L,Brazil,100,"Azure, TensorFlow, Data Visualization",Associate,16,Manufacturing,2024-12-26,2025-03-01,1381,6.6,Neural Networks Co +AI10279,Machine Learning Researcher,72783,CHF,65505,EN,FL,Switzerland,S,Switzerland,50,"AWS, SQL, Hadoop",Bachelor,1,Telecommunications,2024-06-17,2024-07-14,2348,9.5,Predictive Systems +AI10280,AI Software Engineer,191481,EUR,162759,EX,FL,Germany,S,Germany,0,"Docker, Python, Data Visualization",Master,10,Healthcare,2024-05-31,2024-07-08,1695,5.6,Predictive Systems +AI10281,AI Software Engineer,119141,USD,119141,MI,FL,Denmark,S,Denmark,50,"Scala, Python, Deep Learning, Azure, Linux",Bachelor,2,Manufacturing,2024-04-25,2024-06-14,1185,8.7,Neural Networks Co +AI10282,Autonomous Systems Engineer,61294,SGD,79682,EN,FT,Singapore,M,Czech Republic,0,"Docker, Spark, R, Linux",Bachelor,1,Energy,2024-04-16,2024-06-17,1547,8.3,Predictive Systems +AI10283,Machine Learning Researcher,112748,EUR,95836,SE,FT,Austria,L,South Africa,50,"Scala, Python, MLOps",PhD,9,Consulting,2024-01-05,2024-02-24,1639,6.8,Smart Analytics +AI10284,AI Specialist,69817,CAD,87271,MI,FL,Canada,M,Philippines,0,"Git, Statistics, Mathematics, Spark, Azure",Bachelor,2,Technology,2024-04-15,2024-06-11,1463,9.8,Quantum Computing Inc +AI10285,Data Engineer,162528,CAD,203160,EX,PT,Canada,S,Canada,0,"Git, Hadoop, TensorFlow, Scala",Bachelor,16,Energy,2024-09-24,2024-11-22,1815,9.5,Autonomous Tech +AI10286,Principal Data Scientist,80432,USD,80432,EN,PT,Denmark,L,Denmark,0,"Kubernetes, AWS, Java",PhD,1,Telecommunications,2024-11-13,2024-12-01,2443,6.2,DeepTech Ventures +AI10287,Robotics Engineer,263161,CHF,236845,EX,CT,Switzerland,L,Switzerland,0,"Kubernetes, Python, Computer Vision, TensorFlow",Bachelor,15,Government,2025-01-04,2025-02-06,1699,6.4,Predictive Systems +AI10288,AI Research Scientist,70408,CAD,88010,EN,CT,Canada,L,Canada,100,"PyTorch, Computer Vision, Statistics",PhD,0,Gaming,2024-03-29,2024-05-25,643,9.9,AI Innovations +AI10289,Machine Learning Researcher,84533,EUR,71853,MI,FL,France,S,Latvia,100,"Scala, Linux, Kubernetes",Associate,3,Automotive,2024-04-10,2024-04-28,2027,6.5,Quantum Computing Inc +AI10290,Machine Learning Researcher,94145,USD,94145,MI,CT,South Korea,L,South Korea,0,"Java, GCP, R",PhD,4,Energy,2024-04-20,2024-05-26,1087,7.6,Autonomous Tech +AI10291,Research Scientist,52193,USD,52193,EN,PT,Finland,M,Finland,100,"Azure, Spark, Git",Bachelor,0,Telecommunications,2024-12-31,2025-03-12,2340,8.1,Predictive Systems +AI10292,AI Consultant,153253,USD,153253,EX,CT,Ireland,M,Ireland,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,10,Media,2024-01-18,2024-03-30,1495,9.8,Smart Analytics +AI10293,Machine Learning Engineer,87192,USD,87192,MI,CT,Israel,L,Australia,100,"Computer Vision, R, Tableau, Data Visualization",Bachelor,4,Retail,2024-08-20,2024-10-04,1220,9.7,DeepTech Ventures +AI10294,AI Specialist,214211,CHF,192790,EX,PT,Switzerland,S,Turkey,100,"Java, AWS, Statistics, Hadoop",PhD,19,Gaming,2024-01-10,2024-02-05,746,5.5,Algorithmic Solutions +AI10295,AI Product Manager,203264,JPY,22359040,EX,CT,Japan,M,Poland,50,"SQL, Hadoop, Git, Linux",Bachelor,16,Finance,2025-01-19,2025-03-14,1961,5.2,Predictive Systems +AI10296,Autonomous Systems Engineer,172259,JPY,18948490,EX,PT,Japan,M,Russia,100,"Deep Learning, MLOps, Python, Tableau, Scala",Associate,16,Gaming,2024-02-03,2024-03-02,1017,7.4,Algorithmic Solutions +AI10297,Research Scientist,109363,SGD,142172,SE,CT,Singapore,S,Singapore,100,"Deep Learning, Java, Python",Associate,6,Energy,2024-11-02,2024-12-08,1270,7.9,Predictive Systems +AI10298,AI Software Engineer,50885,USD,50885,EX,FL,India,S,India,100,"AWS, Python, Git, Statistics, TensorFlow",Bachelor,17,Government,2025-04-08,2025-05-19,1119,9.6,Algorithmic Solutions +AI10299,ML Ops Engineer,108450,USD,108450,MI,FL,Norway,L,Norway,100,"Linux, PyTorch, TensorFlow, Docker, Mathematics",Associate,2,Media,2025-04-24,2025-07-04,1495,7,Digital Transformation LLC +AI10300,AI Specialist,57880,USD,57880,MI,FL,China,L,China,100,"Python, Spark, Tableau, Scala, Mathematics",Master,3,Transportation,2024-05-27,2024-07-02,2363,9.2,Neural Networks Co +AI10301,AI Software Engineer,113212,USD,113212,SE,FT,South Korea,S,South Korea,100,"GCP, Spark, NLP, TensorFlow, MLOps",PhD,7,Consulting,2024-01-04,2024-02-11,1158,8.9,Advanced Robotics +AI10302,AI Architect,161719,USD,161719,SE,PT,Norway,L,Norway,0,"R, Git, Kubernetes",Associate,8,Finance,2024-05-18,2024-07-18,653,7.1,Digital Transformation LLC +AI10303,Data Engineer,71629,USD,71629,EN,PT,South Korea,L,China,0,"Tableau, GCP, Linux",Bachelor,1,Telecommunications,2024-09-26,2024-11-24,1646,5.5,Smart Analytics +AI10304,Deep Learning Engineer,257527,USD,257527,EX,FL,Ireland,L,Ireland,50,"Linux, Deep Learning, MLOps, PyTorch",Master,10,Technology,2024-03-26,2024-05-21,1258,9.4,Cognitive Computing +AI10305,Computer Vision Engineer,174720,USD,174720,EX,FT,United States,M,Ireland,0,"Kubernetes, Spark, Computer Vision, TensorFlow, Scala",Associate,15,Finance,2024-03-19,2024-04-13,722,6.4,AI Innovations +AI10306,AI Software Engineer,163238,USD,163238,SE,FL,Ireland,L,Ireland,50,"Python, AWS, Scala",Master,7,Healthcare,2024-12-14,2025-01-11,1790,9.2,Algorithmic Solutions +AI10307,AI Consultant,212985,EUR,181037,EX,PT,Netherlands,M,Netherlands,50,"Spark, Deep Learning, Data Visualization",PhD,10,Energy,2024-07-06,2024-07-23,1464,8.8,Predictive Systems +AI10308,AI Specialist,115588,AUD,156044,SE,PT,Australia,S,Australia,0,"PyTorch, Mathematics, NLP, Kubernetes",PhD,8,Education,2025-03-03,2025-03-25,581,7.5,DeepTech Ventures +AI10309,AI Architect,76351,USD,76351,EN,FL,Ireland,L,Ireland,50,"SQL, Python, Tableau, Scala, Statistics",PhD,1,Gaming,2024-06-13,2024-08-05,1297,7.4,Machine Intelligence Group +AI10310,Robotics Engineer,127693,CAD,159616,EX,FL,Canada,S,Canada,100,"Python, TensorFlow, Mathematics, Azure, PyTorch",Associate,16,Gaming,2025-03-14,2025-03-31,1790,7.1,TechCorp Inc +AI10311,Autonomous Systems Engineer,199789,USD,199789,EX,CT,Sweden,L,Chile,50,"Linux, Java, R",Master,10,Government,2024-12-17,2025-01-16,2344,7.5,Neural Networks Co +AI10312,AI Specialist,60987,USD,60987,EN,PT,Ireland,M,Mexico,100,"Deep Learning, Data Visualization, Scala, AWS, Linux",PhD,1,Consulting,2024-07-17,2024-08-05,2185,9.7,Autonomous Tech +AI10313,AI Product Manager,86536,USD,86536,MI,CT,Finland,M,Finland,0,"Scala, R, AWS",Associate,4,Telecommunications,2024-01-06,2024-01-27,1328,9.6,Predictive Systems +AI10314,Data Analyst,96169,EUR,81744,MI,CT,Austria,L,Austria,100,"Scala, Hadoop, Docker, Deep Learning",Bachelor,3,Government,2024-03-16,2024-05-04,1754,8.9,DataVision Ltd +AI10315,Autonomous Systems Engineer,192529,CAD,240661,EX,FT,Canada,M,Canada,50,"AWS, Kubernetes, R, Computer Vision, Statistics",PhD,16,Automotive,2024-01-15,2024-02-16,1373,6.7,DeepTech Ventures +AI10316,Data Analyst,100410,USD,100410,EX,CT,India,L,India,50,"MLOps, Data Visualization, Mathematics, Azure, Java",PhD,19,Manufacturing,2024-11-18,2025-01-04,1798,9.5,Quantum Computing Inc +AI10317,Machine Learning Researcher,52644,USD,52644,EN,PT,Sweden,M,Sweden,0,"SQL, Git, R, Deep Learning",Associate,1,Transportation,2024-04-04,2024-06-08,1491,6.1,Digital Transformation LLC +AI10318,AI Consultant,141234,USD,141234,SE,FT,United States,S,United States,0,"SQL, Kubernetes, GCP",Bachelor,5,Government,2024-11-18,2024-12-08,1135,5.6,Advanced Robotics +AI10319,AI Research Scientist,110559,USD,110559,MI,FL,Denmark,M,Spain,0,"Hadoop, Docker, MLOps, Linux, Data Visualization",Associate,4,Consulting,2024-11-07,2025-01-17,1542,9,DataVision Ltd +AI10320,AI Consultant,217485,USD,217485,EX,PT,Ireland,L,Luxembourg,0,"Scala, Statistics, Python, Mathematics",PhD,11,Government,2024-03-12,2024-04-19,1730,5.2,Predictive Systems +AI10321,Research Scientist,71252,USD,71252,EN,CT,Norway,M,Norway,0,"R, TensorFlow, PyTorch, Spark",Master,0,Retail,2024-12-09,2025-01-19,2090,6.6,DeepTech Ventures +AI10322,Data Scientist,53971,EUR,45875,EN,FL,France,S,France,0,"TensorFlow, Python, Git, Computer Vision, AWS",Master,0,Technology,2025-01-01,2025-02-12,523,7.5,Algorithmic Solutions +AI10323,Machine Learning Engineer,220263,AUD,297355,EX,CT,Australia,L,Australia,0,"NLP, Data Visualization, TensorFlow, Hadoop",Associate,11,Media,2025-03-10,2025-03-27,1532,5.9,Cloud AI Solutions +AI10324,ML Ops Engineer,277182,USD,277182,EX,FL,Norway,M,Norway,50,"Azure, Linux, NLP, GCP",Bachelor,15,Technology,2024-11-16,2025-01-10,652,7.6,Advanced Robotics +AI10325,Computer Vision Engineer,66175,USD,66175,EN,FT,Finland,M,Turkey,0,"Kubernetes, Statistics, Docker, Spark",Bachelor,1,Gaming,2024-07-09,2024-09-19,1983,5.4,DeepTech Ventures +AI10326,Principal Data Scientist,87331,USD,87331,EN,FT,Norway,L,Norway,100,"Hadoop, SQL, MLOps, Statistics, PyTorch",PhD,0,Retail,2024-07-06,2024-08-26,1817,7.5,Neural Networks Co +AI10327,ML Ops Engineer,139322,USD,139322,MI,CT,Norway,M,Norway,100,"Git, MLOps, Java, GCP",Master,4,Manufacturing,2024-10-17,2024-11-29,1376,9.3,Cloud AI Solutions +AI10328,Autonomous Systems Engineer,111301,EUR,94606,SE,FT,Germany,M,Germany,0,"TensorFlow, R, GCP",Master,5,Transportation,2024-08-09,2024-10-07,1598,6.4,TechCorp Inc +AI10329,AI Architect,132825,GBP,99619,EX,FT,United Kingdom,S,United Kingdom,0,"Statistics, R, AWS, PyTorch, TensorFlow",PhD,17,Gaming,2024-12-16,2025-02-20,708,5.1,AI Innovations +AI10330,AI Consultant,169505,AUD,228832,EX,CT,Australia,M,Australia,0,"SQL, Hadoop, PyTorch, Scala, Kubernetes",PhD,14,Media,2024-02-25,2024-04-17,790,8.8,Machine Intelligence Group +AI10331,Machine Learning Researcher,88530,AUD,119516,MI,CT,Australia,L,Australia,0,"SQL, Scala, Docker, Azure, Mathematics",Master,4,Transportation,2024-04-05,2024-05-26,1421,9.5,Cognitive Computing +AI10332,Machine Learning Researcher,127006,EUR,107955,SE,FT,Austria,S,Austria,50,"GCP, Data Visualization, PyTorch, Computer Vision, Deep Learning",Bachelor,6,Energy,2025-01-02,2025-03-03,2400,6.2,Digital Transformation LLC +AI10333,Computer Vision Engineer,244361,AUD,329887,EX,FT,Australia,M,Australia,100,"Java, Deep Learning, Hadoop",Associate,10,Automotive,2025-03-25,2025-06-03,1476,6.4,Cloud AI Solutions +AI10334,Computer Vision Engineer,74201,CAD,92751,EN,PT,Canada,L,Canada,0,"PyTorch, Python, GCP, TensorFlow, Hadoop",Associate,1,Gaming,2024-11-23,2025-01-20,661,6.4,Machine Intelligence Group +AI10335,Robotics Engineer,166881,USD,166881,SE,PT,Norway,S,United Kingdom,0,"Java, PyTorch, Tableau, TensorFlow, Deep Learning",PhD,8,Healthcare,2024-11-09,2024-11-27,2036,5.9,TechCorp Inc +AI10336,Research Scientist,28173,USD,28173,EN,CT,India,L,India,50,"Python, NLP, Hadoop, Computer Vision",Bachelor,1,Real Estate,2024-08-03,2024-09-17,1891,5.5,Autonomous Tech +AI10337,AI Software Engineer,73010,USD,73010,EN,CT,United States,L,United States,100,"Docker, Tableau, Data Visualization, Azure",PhD,1,Government,2025-02-04,2025-04-15,2119,8,Future Systems +AI10338,Computer Vision Engineer,102446,EUR,87079,MI,CT,Austria,L,Argentina,100,"NLP, MLOps, SQL",Master,3,Telecommunications,2024-10-06,2024-11-16,1801,9.8,Predictive Systems +AI10339,Principal Data Scientist,89214,USD,89214,SE,CT,Finland,S,Finland,0,"Statistics, Azure, Python, SQL",Master,8,Education,2024-12-08,2025-01-30,1097,5.2,Autonomous Tech +AI10340,NLP Engineer,203849,USD,203849,EX,FT,South Korea,L,South Korea,0,"Scala, PyTorch, Git, Linux",Master,12,Finance,2024-07-13,2024-09-04,645,6.1,Future Systems +AI10341,AI Consultant,231925,EUR,197136,EX,CT,Austria,L,Austria,100,"TensorFlow, R, Linux, Hadoop",Associate,16,Transportation,2025-04-01,2025-06-12,2122,9.3,TechCorp Inc +AI10342,Principal Data Scientist,135857,CAD,169821,SE,PT,Canada,L,Czech Republic,50,"Mathematics, Spark, Data Visualization",Bachelor,7,Automotive,2025-04-02,2025-05-23,1584,6.5,Cloud AI Solutions +AI10343,AI Research Scientist,135341,SGD,175943,SE,FL,Singapore,L,Singapore,0,"GCP, Linux, Deep Learning",Bachelor,7,Finance,2024-03-20,2024-04-07,1590,7.7,Quantum Computing Inc +AI10344,AI Architect,131968,EUR,112173,SE,CT,France,L,France,0,"Python, Computer Vision, R, Deep Learning",Master,9,Technology,2025-04-03,2025-05-27,1288,9.7,Predictive Systems +AI10345,AI Software Engineer,123858,GBP,92894,SE,FL,United Kingdom,S,Ukraine,0,"Linux, GCP, R, AWS",Bachelor,5,Media,2025-03-02,2025-04-10,2322,5.5,Cognitive Computing +AI10346,NLP Engineer,348262,CHF,313436,EX,CT,Switzerland,M,Ireland,100,"AWS, Python, Kubernetes",Associate,16,Retail,2024-06-26,2024-08-22,720,6.2,Algorithmic Solutions +AI10347,AI Product Manager,139444,USD,139444,SE,CT,Sweden,L,Sweden,50,"Python, Docker, Data Visualization, MLOps, Statistics",Associate,8,Manufacturing,2024-07-20,2024-09-20,1968,5.5,DataVision Ltd +AI10348,Machine Learning Engineer,149870,USD,149870,SE,FL,Denmark,S,Denmark,50,"SQL, Data Visualization, Tableau, Spark, Java",Master,9,Healthcare,2024-01-26,2024-03-10,763,9.5,Machine Intelligence Group +AI10349,Computer Vision Engineer,71964,USD,71964,EN,PT,Sweden,S,Sweden,50,"NLP, MLOps, Python, Scala, Docker",Master,1,Finance,2024-05-07,2024-07-08,1882,9.7,Advanced Robotics +AI10350,Robotics Engineer,27319,USD,27319,EN,FL,India,L,India,0,"Linux, Scala, Python, PyTorch",Associate,0,Automotive,2024-11-16,2025-01-10,1675,7,Algorithmic Solutions +AI10351,Deep Learning Engineer,150456,GBP,112842,EX,FT,United Kingdom,M,United Kingdom,0,"Kubernetes, R, Statistics, Tableau, MLOps",Associate,12,Telecommunications,2025-03-27,2025-04-16,1274,9,AI Innovations +AI10352,AI Specialist,305568,USD,305568,EX,FL,Norway,L,Norway,50,"SQL, PyTorch, Java, Computer Vision, Deep Learning",PhD,12,Transportation,2024-10-01,2024-11-28,1211,9.1,Digital Transformation LLC +AI10353,Data Scientist,181656,EUR,154408,EX,PT,Austria,S,Austria,100,"SQL, Spark, PyTorch",Bachelor,11,Healthcare,2024-01-25,2024-04-04,2218,5,Smart Analytics +AI10354,AI Specialist,83544,CAD,104430,MI,FT,Canada,L,Canada,0,"TensorFlow, Linux, Git, Kubernetes, Mathematics",PhD,4,Energy,2024-05-10,2024-05-27,1605,5.3,Machine Intelligence Group +AI10355,Data Scientist,85383,SGD,110998,EN,CT,Singapore,L,Singapore,0,"MLOps, Statistics, AWS",Master,1,Telecommunications,2024-05-01,2024-07-06,920,8,Cognitive Computing +AI10356,Data Analyst,118808,USD,118808,MI,FL,Israel,L,Portugal,50,"MLOps, TensorFlow, Scala",Master,3,Transportation,2024-05-31,2024-08-06,837,7.5,Smart Analytics +AI10357,Research Scientist,110158,GBP,82619,MI,CT,United Kingdom,M,Belgium,100,"Java, Computer Vision, Data Visualization, MLOps",PhD,3,Finance,2025-03-28,2025-05-05,1881,9.2,AI Innovations +AI10358,Principal Data Scientist,68395,AUD,92333,EN,FT,Australia,M,Australia,50,"AWS, Python, Docker, Deep Learning, Hadoop",Associate,0,Automotive,2024-10-18,2024-11-04,985,9.6,Digital Transformation LLC +AI10359,AI Consultant,83740,EUR,71179,MI,FL,Austria,L,Austria,0,"Hadoop, Linux, Python, Deep Learning",Associate,2,Transportation,2025-03-21,2025-05-24,655,5.2,Cloud AI Solutions +AI10360,Data Scientist,52109,USD,52109,EX,PT,India,S,India,0,"Python, Kubernetes, Tableau, TensorFlow",Bachelor,15,Education,2025-02-03,2025-04-09,1995,6.1,DeepTech Ventures +AI10361,Machine Learning Researcher,103993,AUD,140391,SE,FT,Australia,S,Sweden,100,"Tableau, Java, Python, SQL, AWS",PhD,9,Education,2024-06-14,2024-07-17,1523,9.9,Predictive Systems +AI10362,Machine Learning Researcher,183121,GBP,137341,EX,FT,United Kingdom,L,United Kingdom,50,"Linux, Kubernetes, R, AWS",Bachelor,11,Telecommunications,2024-03-05,2024-03-28,1413,8.2,Advanced Robotics +AI10363,Data Scientist,76735,USD,76735,SE,PT,South Korea,S,New Zealand,0,"NLP, Kubernetes, AWS, SQL",PhD,8,Energy,2024-08-25,2024-09-23,1994,9.6,Future Systems +AI10364,NLP Engineer,206350,GBP,154763,EX,PT,United Kingdom,L,United Kingdom,100,"Tableau, SQL, Spark, Computer Vision",PhD,18,Telecommunications,2024-06-23,2024-08-09,2468,7.2,TechCorp Inc +AI10365,Autonomous Systems Engineer,105977,GBP,79483,MI,PT,United Kingdom,M,United Kingdom,50,"NLP, Java, TensorFlow",PhD,4,Media,2024-05-20,2024-07-02,2109,5.6,Cloud AI Solutions +AI10366,NLP Engineer,216215,JPY,23783650,EX,CT,Japan,L,Japan,100,"NLP, Hadoop, Kubernetes",Bachelor,19,Retail,2024-06-28,2024-07-30,1784,8,Predictive Systems +AI10367,NLP Engineer,75477,EUR,64155,MI,CT,Germany,M,Germany,0,"NLP, Scala, Spark, PyTorch, Linux",Associate,2,Media,2024-03-21,2024-05-21,1501,6.6,Smart Analytics +AI10368,Principal Data Scientist,48875,USD,48875,SE,FT,China,M,China,100,"Linux, Java, Computer Vision, Kubernetes, Mathematics",Associate,5,Healthcare,2024-12-11,2024-12-27,1022,9.1,Neural Networks Co +AI10369,Principal Data Scientist,104599,CHF,94139,EN,PT,Switzerland,M,Switzerland,50,"Python, Git, Linux, TensorFlow, R",Bachelor,1,Consulting,2025-04-10,2025-04-25,991,9.1,Future Systems +AI10370,Machine Learning Engineer,48610,GBP,36458,EN,PT,United Kingdom,S,United Kingdom,100,"MLOps, SQL, Azure, TensorFlow, GCP",Master,0,Education,2024-09-30,2024-11-05,527,8.4,DataVision Ltd +AI10371,Autonomous Systems Engineer,63371,USD,63371,EN,FT,Ireland,M,Ireland,0,"Docker, Tableau, Data Visualization, Python, Statistics",Associate,1,Finance,2024-12-26,2025-01-24,2265,6.7,AI Innovations +AI10372,Head of AI,62938,EUR,53497,EN,FL,Germany,S,Germany,0,"Java, Hadoop, R",PhD,0,Media,2025-01-17,2025-02-08,1240,6.9,Neural Networks Co +AI10373,AI Specialist,90753,EUR,77140,MI,CT,France,M,New Zealand,100,"Linux, Hadoop, Tableau",Master,4,Manufacturing,2024-12-15,2025-01-24,2436,6.4,Future Systems +AI10374,AI Specialist,82651,USD,82651,MI,FL,South Korea,M,South Korea,100,"Python, TensorFlow, Computer Vision, AWS, Java",Master,3,Education,2024-08-29,2024-10-04,794,5.4,DataVision Ltd +AI10375,Principal Data Scientist,76895,EUR,65361,MI,FT,Netherlands,S,Netherlands,0,"Azure, NLP, Python, Computer Vision, Docker",PhD,2,Finance,2024-02-29,2024-05-08,2416,7.8,AI Innovations +AI10376,NLP Engineer,180262,CAD,225328,EX,CT,Canada,L,Canada,100,"MLOps, Spark, Data Visualization, R",Bachelor,13,Government,2025-02-08,2025-04-19,2351,9.9,TechCorp Inc +AI10377,Head of AI,113460,USD,113460,SE,CT,Finland,S,Kenya,100,"Hadoop, Linux, PyTorch",Bachelor,7,Gaming,2024-06-03,2024-08-03,1972,5.3,DataVision Ltd +AI10378,NLP Engineer,153403,USD,153403,SE,PT,Sweden,L,Sweden,50,"GCP, Azure, Mathematics",Bachelor,7,Healthcare,2024-07-23,2024-09-05,2006,5.7,Autonomous Tech +AI10379,Data Engineer,84780,CAD,105975,MI,PT,Canada,S,Canada,100,"Kubernetes, Docker, Tableau, Azure, Git",PhD,4,Education,2024-08-25,2024-10-21,1131,5.2,AI Innovations +AI10380,AI Consultant,157851,JPY,17363610,EX,CT,Japan,M,Belgium,100,"Scala, TensorFlow, Kubernetes, SQL, PyTorch",Bachelor,12,Telecommunications,2024-12-25,2025-01-19,1496,6,DeepTech Ventures +AI10381,ML Ops Engineer,161328,JPY,17746080,EX,PT,Japan,S,Japan,50,"R, Scala, Mathematics, Deep Learning",Associate,12,Automotive,2024-01-01,2024-03-12,1229,7.1,Machine Intelligence Group +AI10382,AI Research Scientist,180015,CAD,225019,EX,FL,Canada,S,Canada,0,"Deep Learning, Statistics, Scala, Azure",Associate,15,Government,2024-06-11,2024-07-21,856,10,Cloud AI Solutions +AI10383,Machine Learning Researcher,169051,USD,169051,SE,PT,United States,L,United States,50,"R, Java, Deep Learning",PhD,6,Retail,2024-11-02,2025-01-01,2205,7.5,Cloud AI Solutions +AI10384,Robotics Engineer,47369,USD,47369,SE,PT,India,L,India,50,"Linux, Docker, AWS, R",Bachelor,7,Energy,2024-09-12,2024-09-30,2206,9.3,Future Systems +AI10385,Computer Vision Engineer,59893,EUR,50909,EN,FT,Austria,L,Luxembourg,50,"Docker, TensorFlow, NLP, GCP",Bachelor,1,Gaming,2025-01-17,2025-03-08,630,7.8,Cognitive Computing +AI10386,AI Research Scientist,77568,JPY,8532480,EN,FT,Japan,M,Japan,0,"Linux, Python, Deep Learning, TensorFlow, Git",PhD,0,Energy,2024-03-12,2024-05-03,2286,7.8,Advanced Robotics +AI10387,Robotics Engineer,65205,USD,65205,SE,PT,China,M,Kenya,100,"PyTorch, TensorFlow, Deep Learning",PhD,9,Finance,2024-03-10,2024-04-06,766,9.5,DataVision Ltd +AI10388,Robotics Engineer,123050,CHF,110745,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Hadoop, MLOps, SQL",Master,0,Transportation,2024-02-18,2024-03-24,961,9.9,Algorithmic Solutions +AI10389,AI Specialist,59751,USD,59751,EN,FL,Finland,M,Finland,50,"Kubernetes, Linux, GCP, Spark",PhD,0,Gaming,2024-01-08,2024-01-27,2237,7.2,TechCorp Inc +AI10390,AI Product Manager,158205,USD,158205,EX,PT,South Korea,S,South Korea,100,"Kubernetes, Spark, Python, Git, AWS",Master,12,Finance,2024-05-12,2024-06-04,1898,5.2,Future Systems +AI10391,Data Scientist,104978,USD,104978,MI,CT,Ireland,M,Netherlands,50,"AWS, Tableau, Java, Azure, Python",Associate,4,Technology,2024-02-14,2024-03-25,1561,5.3,Predictive Systems +AI10392,AI Product Manager,51383,JPY,5652130,EN,FL,Japan,S,Japan,50,"SQL, Kubernetes, Deep Learning, NLP",PhD,1,Gaming,2024-07-26,2024-08-17,1313,5.5,Quantum Computing Inc +AI10393,Head of AI,133639,CHF,120275,MI,FT,Switzerland,L,Switzerland,0,"Linux, AWS, Deep Learning",PhD,2,Education,2025-01-28,2025-03-05,1763,6.2,Predictive Systems +AI10394,NLP Engineer,70113,JPY,7712430,EN,FL,Japan,M,Japan,0,"Deep Learning, GCP, Scala",PhD,0,Gaming,2024-02-20,2024-04-30,2186,6.7,Quantum Computing Inc +AI10395,AI Product Manager,104072,EUR,88461,MI,FL,Germany,M,Germany,50,"Deep Learning, Python, TensorFlow, Mathematics, PyTorch",Bachelor,4,Retail,2024-05-30,2024-08-08,1966,9.8,TechCorp Inc +AI10396,AI Specialist,71642,AUD,96717,EN,PT,Australia,S,Australia,0,"SQL, Scala, Computer Vision, PyTorch, TensorFlow",Bachelor,0,Gaming,2024-10-08,2024-10-30,1976,6.4,DeepTech Ventures +AI10397,Deep Learning Engineer,140288,USD,140288,SE,FT,Sweden,L,Sweden,50,"Python, Mathematics, TensorFlow",Bachelor,8,Government,2024-06-28,2024-09-07,1002,7,Machine Intelligence Group +AI10398,Data Scientist,134675,EUR,114474,SE,CT,Netherlands,S,Argentina,100,"Python, Git, Statistics",Bachelor,8,Technology,2024-03-11,2024-03-27,1466,7.1,Neural Networks Co +AI10399,AI Consultant,22938,USD,22938,EN,FT,India,M,India,100,"GCP, Tableau, Azure, Mathematics, Spark",Associate,0,Education,2024-05-07,2024-06-09,1943,8.4,Cloud AI Solutions +AI10400,Deep Learning Engineer,141684,EUR,120431,SE,FT,France,L,France,0,"AWS, R, PyTorch, Docker, Tableau",Master,7,Retail,2024-05-11,2024-07-20,2266,5.2,AI Innovations +AI10401,Principal Data Scientist,83033,USD,83033,SE,FL,South Korea,S,South Korea,100,"NLP, Python, TensorFlow, Hadoop, Spark",Bachelor,8,Education,2024-10-28,2024-12-03,2458,6.5,Future Systems +AI10402,Data Engineer,222353,EUR,189000,EX,FT,Netherlands,M,Netherlands,50,"R, Tableau, NLP, MLOps, Docker",Bachelor,18,Telecommunications,2025-01-26,2025-04-09,2350,8.2,TechCorp Inc +AI10403,AI Specialist,89362,EUR,75958,MI,PT,Netherlands,L,Netherlands,0,"TensorFlow, PyTorch, Deep Learning",Master,4,Retail,2024-01-19,2024-03-03,906,9.7,AI Innovations +AI10404,AI Specialist,199765,USD,199765,EX,FL,South Korea,M,South Korea,100,"Python, Git, Docker, GCP, Tableau",Master,19,Real Estate,2024-09-30,2024-11-01,2156,8.1,Future Systems +AI10405,Head of AI,102081,AUD,137809,SE,PT,Australia,M,Australia,50,"Mathematics, Scala, R, Kubernetes",Master,9,Retail,2024-07-07,2024-08-26,2167,8.5,Cloud AI Solutions +AI10406,AI Research Scientist,221776,USD,221776,EX,FL,Norway,S,Norway,0,"SQL, Python, NLP",Bachelor,10,Finance,2024-03-30,2024-05-01,801,5.5,Cloud AI Solutions +AI10407,Deep Learning Engineer,95606,USD,95606,EX,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, GCP, Statistics",Associate,14,Retail,2025-04-12,2025-05-04,609,8.6,Advanced Robotics +AI10408,Data Scientist,102808,EUR,87387,MI,PT,Austria,M,Austria,100,"SQL, Linux, NLP, Scala",PhD,4,Real Estate,2024-07-06,2024-08-14,1703,5.2,Digital Transformation LLC +AI10409,ML Ops Engineer,104905,USD,104905,MI,CT,Norway,S,Norway,50,"Spark, AWS, Statistics",Master,4,Healthcare,2024-08-18,2024-10-02,1678,7.7,DataVision Ltd +AI10410,Computer Vision Engineer,133598,CHF,120238,MI,FT,Switzerland,S,Switzerland,0,"Spark, Kubernetes, Data Visualization",Bachelor,3,Energy,2024-10-11,2024-12-05,2492,6.9,Machine Intelligence Group +AI10411,Autonomous Systems Engineer,282463,JPY,31070930,EX,CT,Japan,L,Japan,0,"MLOps, Java, Python",Associate,19,Education,2024-12-22,2025-01-08,1949,9.9,Cloud AI Solutions +AI10412,Data Engineer,146803,EUR,124783,EX,PT,Germany,M,Germany,100,"SQL, Git, Computer Vision, AWS",Master,13,Finance,2025-02-09,2025-04-21,2291,6.2,Predictive Systems +AI10413,AI Product Manager,226731,USD,226731,EX,FT,Ireland,L,Ireland,0,"Linux, Computer Vision, R, Python",Associate,17,Consulting,2024-05-01,2024-06-25,2395,10,Predictive Systems +AI10414,Data Scientist,85796,EUR,72927,MI,FT,France,L,France,0,"Python, TensorFlow, Mathematics",Associate,3,Transportation,2024-06-16,2024-08-01,2131,9.4,Machine Intelligence Group +AI10415,Head of AI,67219,AUD,90746,EN,FT,Australia,L,Australia,50,"MLOps, Deep Learning, TensorFlow, Python, Computer Vision",PhD,0,Telecommunications,2025-03-29,2025-05-16,2183,5.8,Digital Transformation LLC +AI10416,Deep Learning Engineer,19495,USD,19495,EN,CT,India,M,India,50,"Azure, Python, Linux",Associate,1,Manufacturing,2024-11-20,2025-01-18,1129,6.5,Predictive Systems +AI10417,Machine Learning Engineer,143665,USD,143665,SE,CT,Sweden,M,Sweden,0,"Git, Deep Learning, MLOps, PyTorch",Bachelor,8,Manufacturing,2024-08-21,2024-09-04,951,6.9,DeepTech Ventures +AI10418,Computer Vision Engineer,54072,AUD,72997,EN,PT,Australia,S,Germany,100,"SQL, Tableau, PyTorch, AWS, MLOps",Master,0,Media,2024-09-01,2024-11-02,1394,7.4,DataVision Ltd +AI10419,Data Scientist,93668,EUR,79618,SE,FT,Austria,S,Austria,100,"Mathematics, Git, MLOps, Kubernetes",Bachelor,6,Finance,2024-04-26,2024-05-11,2402,5,Predictive Systems +AI10420,ML Ops Engineer,238158,USD,238158,EX,PT,Norway,L,Norway,50,"Git, SQL, Python, GCP",Master,19,Real Estate,2024-06-15,2024-07-29,1932,8.7,Quantum Computing Inc +AI10421,Computer Vision Engineer,71023,GBP,53267,EN,CT,United Kingdom,S,South Africa,100,"Hadoop, Git, R, Java",Master,1,Real Estate,2024-06-14,2024-07-12,1434,9.5,Digital Transformation LLC +AI10422,AI Specialist,86841,EUR,73815,MI,CT,Germany,L,Australia,100,"PyTorch, TensorFlow, MLOps",PhD,2,Media,2024-01-19,2024-03-24,806,9.9,Cognitive Computing +AI10423,ML Ops Engineer,154195,CAD,192744,EX,PT,Canada,S,Belgium,50,"NLP, PyTorch, R, Java",Master,15,Consulting,2024-10-09,2024-10-31,695,5.8,Future Systems +AI10424,Robotics Engineer,92933,SGD,120813,MI,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Scala",PhD,3,Education,2024-06-03,2024-07-30,1876,7.2,DataVision Ltd +AI10425,Deep Learning Engineer,122175,SGD,158828,SE,PT,Singapore,S,Nigeria,50,"NLP, Scala, Statistics, Deep Learning",Master,8,Technology,2024-05-18,2024-07-22,2133,5.2,Smart Analytics +AI10426,AI Software Engineer,123306,EUR,104810,EX,CT,France,S,France,100,"Python, TensorFlow, GCP",PhD,15,Education,2024-11-15,2025-01-06,1729,6.4,AI Innovations +AI10427,AI Research Scientist,103528,EUR,87999,MI,PT,Austria,L,Austria,100,"GCP, AWS, MLOps",Bachelor,4,Government,2024-08-05,2024-09-24,926,5.8,DataVision Ltd +AI10428,AI Specialist,98123,EUR,83405,SE,FT,Netherlands,S,Netherlands,0,"PyTorch, NLP, Docker, AWS",Associate,6,Telecommunications,2024-08-22,2024-10-12,1172,6.8,Predictive Systems +AI10429,AI Research Scientist,75392,USD,75392,EN,FL,South Korea,L,South Korea,0,"Python, Java, Azure, Kubernetes, Git",Bachelor,1,Finance,2024-02-08,2024-03-21,1380,8.2,Future Systems +AI10430,AI Architect,47588,CAD,59485,EN,FL,Canada,S,Canada,50,"Kubernetes, Git, Tableau",PhD,0,Real Estate,2024-08-23,2024-10-20,2296,6.1,Future Systems +AI10431,Data Engineer,64925,JPY,7141750,EN,CT,Japan,S,Estonia,50,"Scala, Mathematics, SQL, Azure, Data Visualization",Bachelor,1,Manufacturing,2024-10-13,2024-12-11,1706,8.8,DeepTech Ventures +AI10432,AI Consultant,59060,USD,59060,MI,CT,China,L,China,0,"Computer Vision, Java, PyTorch",Master,3,Government,2024-03-23,2024-05-12,2496,6.8,Quantum Computing Inc +AI10433,Machine Learning Researcher,206097,USD,206097,SE,CT,Denmark,L,Denmark,100,"Python, Data Visualization, Spark",Master,8,Energy,2024-10-08,2024-11-26,2416,8.5,AI Innovations +AI10434,Data Engineer,61098,USD,61098,EN,FL,South Korea,M,Indonesia,0,"Statistics, PyTorch, MLOps",Master,1,Telecommunications,2024-05-20,2024-06-27,1175,8,Quantum Computing Inc +AI10435,Data Scientist,63567,USD,63567,EN,CT,Ireland,M,Ireland,0,"AWS, R, Data Visualization",Bachelor,0,Gaming,2024-07-12,2024-07-31,2154,9.2,Quantum Computing Inc +AI10436,Machine Learning Engineer,247728,CHF,222955,SE,FL,Switzerland,L,Indonesia,0,"Hadoop, Kubernetes, NLP",Associate,9,Telecommunications,2024-08-22,2024-09-21,1912,5.7,TechCorp Inc +AI10437,Research Scientist,125206,GBP,93905,SE,CT,United Kingdom,M,Indonesia,50,"Deep Learning, Tableau, Kubernetes, Git",Master,7,Media,2024-09-26,2024-10-16,1042,8.2,Digital Transformation LLC +AI10438,Robotics Engineer,72094,EUR,61280,EN,PT,France,M,France,100,"Linux, Java, Mathematics, Computer Vision, PyTorch",Associate,1,Healthcare,2025-03-31,2025-05-23,2433,5.9,TechCorp Inc +AI10439,AI Research Scientist,85942,CAD,107428,EN,PT,Canada,L,Canada,100,"Linux, Kubernetes, Hadoop, Statistics",Associate,0,Consulting,2024-05-09,2024-06-25,2072,7.1,TechCorp Inc +AI10440,ML Ops Engineer,191299,USD,191299,EX,CT,Ireland,M,Spain,100,"Azure, SQL, PyTorch",Bachelor,17,Telecommunications,2024-05-14,2024-06-24,1221,5.6,Autonomous Tech +AI10441,Computer Vision Engineer,145582,USD,145582,SE,CT,Israel,L,Israel,50,"Deep Learning, Kubernetes, R",Associate,5,Technology,2024-08-24,2024-10-21,1743,7.9,AI Innovations +AI10442,AI Architect,91181,AUD,123094,MI,PT,Australia,S,Australia,100,"Git, Docker, SQL, Kubernetes",Master,4,Media,2024-12-18,2025-02-24,1535,5.8,Smart Analytics +AI10443,NLP Engineer,100215,USD,100215,EX,CT,China,S,Indonesia,0,"Docker, R, Java",Bachelor,11,Manufacturing,2024-03-11,2024-05-09,2088,9.3,Quantum Computing Inc +AI10444,AI Consultant,47259,USD,47259,EX,FT,India,S,India,100,"TensorFlow, Spark, NLP",PhD,14,Energy,2024-11-15,2024-12-28,1642,6.1,Quantum Computing Inc +AI10445,AI Architect,244995,USD,244995,EX,CT,Norway,M,Norway,0,"TensorFlow, Docker, R",PhD,14,Education,2024-09-19,2024-11-18,1936,9.3,TechCorp Inc +AI10446,Data Analyst,131732,AUD,177838,SE,CT,Australia,L,Australia,50,"TensorFlow, Java, Deep Learning, Linux",Associate,7,Government,2024-06-16,2024-08-09,943,6.1,Quantum Computing Inc +AI10447,Autonomous Systems Engineer,142453,SGD,185189,SE,CT,Singapore,M,Singapore,100,"Mathematics, Docker, Python, Scala, Computer Vision",Master,8,Transportation,2024-12-23,2025-02-02,846,6.6,DataVision Ltd +AI10448,Data Scientist,114905,EUR,97669,MI,FL,France,L,France,100,"Python, GCP, Spark",Bachelor,4,Real Estate,2024-03-30,2024-05-07,972,5.5,Smart Analytics +AI10449,Machine Learning Engineer,94309,USD,94309,MI,CT,Sweden,L,Sweden,0,"Python, Git, TensorFlow, Docker, PyTorch",Associate,2,Retail,2024-09-24,2024-12-03,1036,7.7,DeepTech Ventures +AI10450,AI Consultant,269435,CHF,242492,EX,PT,Switzerland,M,Switzerland,100,"MLOps, Java, Azure",Bachelor,18,Manufacturing,2025-02-26,2025-04-08,1393,9.2,Advanced Robotics +AI10451,Machine Learning Engineer,64365,EUR,54710,EN,FL,Germany,S,Germany,0,"Spark, GCP, Mathematics",Associate,1,Gaming,2024-04-26,2024-07-01,1828,10,TechCorp Inc +AI10452,AI Specialist,105348,USD,105348,EN,PT,Norway,L,Norway,100,"NLP, Python, Kubernetes, AWS",Master,0,Technology,2024-12-18,2025-01-13,1099,9.1,Cloud AI Solutions +AI10453,Machine Learning Engineer,157110,GBP,117833,SE,FL,United Kingdom,L,United Kingdom,50,"Scala, Deep Learning, MLOps, Data Visualization",Bachelor,6,Technology,2024-03-26,2024-05-22,1108,9.9,Autonomous Tech +AI10454,Computer Vision Engineer,312583,USD,312583,EX,FL,Denmark,L,United States,0,"SQL, Deep Learning, NLP",Master,19,Manufacturing,2024-08-16,2024-09-16,536,8.6,Digital Transformation LLC +AI10455,Autonomous Systems Engineer,74526,USD,74526,EX,FT,China,M,Canada,0,"TensorFlow, R, Data Visualization",Master,12,Education,2024-07-22,2024-09-24,1101,10,Cognitive Computing +AI10456,Robotics Engineer,172413,JPY,18965430,SE,FL,Japan,L,Japan,100,"Python, Docker, TensorFlow, SQL, AWS",Associate,5,Media,2025-03-02,2025-03-30,1199,5.3,TechCorp Inc +AI10457,Machine Learning Researcher,163535,EUR,139005,SE,PT,Austria,L,Austria,50,"Statistics, Spark, Tableau",Master,8,Government,2024-08-19,2024-10-10,1823,9,TechCorp Inc +AI10458,Data Analyst,132082,USD,132082,EX,FL,South Korea,M,South Korea,50,"SQL, NLP, Azure, Scala, Python",Master,17,Media,2024-06-13,2024-08-15,1298,9.2,Digital Transformation LLC +AI10459,Research Scientist,261749,USD,261749,EX,CT,Norway,S,Finland,100,"Computer Vision, Statistics, PyTorch, Java",PhD,12,Government,2024-02-19,2024-03-06,1489,8.4,Cognitive Computing +AI10460,Head of AI,68534,USD,68534,SE,FL,China,M,China,50,"Deep Learning, GCP, Computer Vision",Master,8,Media,2024-03-08,2024-03-26,1951,6.7,Machine Intelligence Group +AI10461,AI Consultant,95396,EUR,81087,MI,CT,Germany,M,Germany,100,"Linux, SQL, Kubernetes, GCP",Bachelor,4,Retail,2024-06-11,2024-07-03,1007,7.8,Predictive Systems +AI10462,Data Scientist,74131,AUD,100077,EN,CT,Australia,M,Australia,50,"Spark, Hadoop, Tableau, Mathematics",Master,1,Transportation,2024-01-15,2024-03-05,951,8.9,Neural Networks Co +AI10463,Computer Vision Engineer,115232,USD,115232,MI,CT,Denmark,M,Denmark,50,"Tableau, NLP, Scala, Deep Learning, PyTorch",Master,3,Technology,2024-12-25,2025-02-25,667,6.9,Digital Transformation LLC +AI10464,Machine Learning Engineer,58227,SGD,75695,EN,FL,Singapore,S,Singapore,100,"Kubernetes, Deep Learning, NLP, TensorFlow",Bachelor,1,Healthcare,2024-01-03,2024-01-19,2113,9.1,Machine Intelligence Group +AI10465,Data Analyst,188430,CHF,169587,SE,FT,Switzerland,L,Switzerland,100,"Python, Scala, Hadoop, Docker, TensorFlow",Associate,6,Technology,2025-03-01,2025-03-25,955,6.4,Quantum Computing Inc +AI10466,Head of AI,72415,SGD,94140,EN,PT,Singapore,M,Singapore,0,"Git, Scala, Linux, SQL",Associate,0,Retail,2024-05-12,2024-06-18,2310,7.2,DeepTech Ventures +AI10467,AI Consultant,49041,GBP,36781,EN,FT,United Kingdom,S,United Kingdom,100,"Docker, Spark, Deep Learning, TensorFlow, PyTorch",Master,1,Manufacturing,2024-10-28,2024-11-18,660,8.4,Neural Networks Co +AI10468,Research Scientist,78075,USD,78075,MI,FL,Finland,M,Finland,0,"Statistics, Hadoop, Tableau, Kubernetes",Master,3,Automotive,2025-03-27,2025-05-28,657,9,Neural Networks Co +AI10469,Autonomous Systems Engineer,96725,USD,96725,EN,PT,Denmark,L,Denmark,100,"Git, PyTorch, Scala, Azure",Associate,1,Technology,2025-01-26,2025-02-20,1553,5.6,Cloud AI Solutions +AI10470,AI Architect,116451,CAD,145564,MI,FL,Canada,L,Canada,0,"Kubernetes, Azure, SQL, Java, Spark",Bachelor,3,Automotive,2024-06-17,2024-08-24,883,9.6,Autonomous Tech +AI10471,AI Research Scientist,96459,SGD,125397,EN,FT,Singapore,L,Austria,100,"Data Visualization, Azure, Mathematics, PyTorch",PhD,0,Manufacturing,2024-03-26,2024-06-04,1160,7.4,DataVision Ltd +AI10472,AI Research Scientist,254343,CHF,228909,EX,FT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Hadoop, Statistics",Associate,18,Real Estate,2024-02-28,2024-04-15,1326,8.1,Autonomous Tech +AI10473,Autonomous Systems Engineer,131234,EUR,111549,SE,FL,Germany,S,Germany,100,"Java, Spark, Statistics, Mathematics",PhD,6,Manufacturing,2024-08-13,2024-09-24,701,9.5,Future Systems +AI10474,Autonomous Systems Engineer,53585,USD,53585,EN,CT,South Korea,S,South Korea,100,"Tableau, NLP, MLOps, Data Visualization",PhD,0,Media,2025-01-01,2025-03-09,1610,6.6,Future Systems +AI10475,AI Consultant,156371,USD,156371,SE,PT,Denmark,M,Denmark,0,"NLP, Hadoop, GCP, Azure, Java",Bachelor,8,Telecommunications,2025-01-21,2025-02-24,686,6.6,DataVision Ltd +AI10476,NLP Engineer,166022,GBP,124517,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, Docker",PhD,19,Consulting,2024-10-31,2024-12-31,2259,9.8,Predictive Systems +AI10477,AI Software Engineer,87583,SGD,113858,MI,FL,Singapore,M,Belgium,100,"Data Visualization, Docker, Kubernetes, Scala",Bachelor,2,Manufacturing,2024-08-12,2024-09-07,1779,9.8,Predictive Systems +AI10478,Robotics Engineer,131350,USD,131350,SE,FL,Ireland,M,Ireland,100,"NLP, Java, Kubernetes",Bachelor,7,Education,2024-10-07,2024-11-16,1324,5.1,Algorithmic Solutions +AI10479,Robotics Engineer,25847,USD,25847,EN,FL,China,M,China,100,"R, TensorFlow, Docker, Data Visualization",Master,1,Manufacturing,2024-05-13,2024-07-19,567,7.3,Smart Analytics +AI10480,Data Scientist,70279,USD,70279,EN,CT,Sweden,M,Sweden,0,"Docker, Kubernetes, AWS, Tableau, Git",Master,0,Transportation,2025-04-16,2025-05-18,2431,5.9,Quantum Computing Inc +AI10481,Principal Data Scientist,83967,USD,83967,MI,FL,Sweden,L,Sweden,50,"Data Visualization, Git, Scala",Associate,4,Consulting,2024-06-26,2024-07-30,533,5.8,Advanced Robotics +AI10482,Data Analyst,117772,USD,117772,SE,FT,Israel,S,Israel,50,"AWS, GCP, Statistics, Java",PhD,5,Government,2025-04-30,2025-07-02,1085,7,Predictive Systems +AI10483,Data Engineer,77901,USD,77901,MI,PT,Finland,S,Finland,100,"Scala, Spark, AWS, PyTorch, Linux",PhD,4,Government,2024-02-16,2024-04-19,2164,9.6,Digital Transformation LLC +AI10484,Robotics Engineer,251299,USD,251299,EX,FT,Israel,L,Israel,100,"Kubernetes, Scala, GCP",PhD,17,Retail,2024-02-17,2024-03-10,2304,9.5,Quantum Computing Inc +AI10485,ML Ops Engineer,56632,CAD,70790,EN,FL,Canada,S,Canada,0,"Computer Vision, AWS, NLP",Master,1,Media,2025-04-10,2025-06-08,1669,8.2,Cloud AI Solutions +AI10486,Data Scientist,89248,EUR,75861,SE,FT,Austria,S,Austria,0,"PyTorch, MLOps, Python, R",Master,6,Technology,2025-04-03,2025-06-01,819,6.8,Machine Intelligence Group +AI10487,ML Ops Engineer,159129,CHF,143216,SE,FL,Switzerland,S,Switzerland,0,"TensorFlow, SQL, R",Associate,8,Government,2024-09-09,2024-10-10,2320,5.5,Cognitive Computing +AI10488,Deep Learning Engineer,121563,USD,121563,SE,CT,Finland,S,Norway,100,"Python, GCP, Git, TensorFlow, Statistics",Associate,9,Government,2024-11-11,2024-12-16,1300,5.6,Future Systems +AI10489,Computer Vision Engineer,60861,EUR,51732,EN,CT,Austria,L,Austria,0,"Azure, PyTorch, Mathematics, Python",Bachelor,0,Telecommunications,2024-03-13,2024-05-24,1422,8.3,DeepTech Ventures +AI10490,Research Scientist,118967,CHF,107070,MI,CT,Switzerland,L,Canada,50,"Java, MLOps, Python, R",PhD,4,Technology,2024-08-31,2024-10-28,1605,9.3,DataVision Ltd +AI10491,AI Research Scientist,233392,EUR,198383,EX,FT,Germany,L,Germany,100,"Statistics, Java, PyTorch, Deep Learning",Bachelor,16,Government,2024-02-29,2024-05-07,2030,7.7,AI Innovations +AI10492,Data Analyst,132254,EUR,112416,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, Computer Vision, Tableau",Master,9,Education,2024-06-18,2024-07-04,2009,7.7,DataVision Ltd +AI10493,Data Analyst,64661,USD,64661,EN,FL,Finland,L,Finland,100,"Statistics, TensorFlow, Hadoop, GCP, Deep Learning",PhD,1,Finance,2024-09-08,2024-10-18,621,8.1,Smart Analytics +AI10494,Head of AI,113314,USD,113314,MI,CT,United States,M,Australia,50,"Python, SQL, Linux, GCP, Scala",Master,4,Media,2024-06-26,2024-08-09,936,9.4,AI Innovations +AI10495,Autonomous Systems Engineer,114505,SGD,148857,SE,CT,Singapore,S,Singapore,100,"Java, R, GCP, Mathematics, Hadoop",Associate,8,Media,2024-03-25,2024-04-16,1103,9.3,Smart Analytics +AI10496,AI Software Engineer,176423,EUR,149960,EX,CT,Austria,L,Ghana,100,"PyTorch, Hadoop, Linux, Azure, Scala",PhD,17,Government,2024-11-18,2024-12-08,2133,6.2,Smart Analytics +AI10497,Deep Learning Engineer,47416,EUR,40304,EN,PT,Austria,S,Austria,0,"Linux, AWS, Computer Vision",Associate,0,Telecommunications,2024-10-10,2024-12-09,1205,5.9,DeepTech Ventures +AI10498,Data Scientist,273664,GBP,205248,EX,FL,United Kingdom,L,United Kingdom,100,"Azure, Python, GCP",Bachelor,18,Technology,2024-08-21,2024-10-14,1518,6.8,Predictive Systems +AI10499,AI Product Manager,158106,SGD,205538,SE,PT,Singapore,L,Singapore,100,"Python, Kubernetes, Computer Vision, Hadoop",Bachelor,9,Telecommunications,2024-06-16,2024-07-05,576,8.1,Autonomous Tech +AI10500,Deep Learning Engineer,134252,EUR,114114,SE,CT,Austria,M,Austria,50,"Azure, Scala, AWS",Associate,7,Education,2025-04-01,2025-04-28,821,9.3,Smart Analytics +AI10501,Research Scientist,39883,USD,39883,EN,CT,South Korea,S,Australia,100,"Tableau, PyTorch, AWS, Statistics, Git",Bachelor,0,Real Estate,2024-09-18,2024-11-19,2465,6.2,Quantum Computing Inc +AI10502,AI Architect,86586,USD,86586,MI,FL,Ireland,S,Ireland,100,"SQL, Scala, Statistics, Kubernetes, GCP",Bachelor,4,Transportation,2024-11-26,2024-12-16,1516,8.2,Cognitive Computing +AI10503,NLP Engineer,158006,JPY,17380660,SE,PT,Japan,L,Switzerland,50,"Kubernetes, Spark, R, Deep Learning",Bachelor,9,Finance,2024-09-02,2024-11-12,2181,9.5,Quantum Computing Inc +AI10504,Research Scientist,160380,USD,160380,EX,FL,Israel,L,Israel,50,"Python, Azure, NLP, TensorFlow, AWS",Master,18,Government,2024-10-19,2024-11-29,2304,5.4,Advanced Robotics +AI10505,NLP Engineer,178755,USD,178755,SE,CT,Norway,L,Norway,100,"Hadoop, Spark, Computer Vision",PhD,6,Energy,2025-01-29,2025-02-20,1020,6.4,Predictive Systems +AI10506,Principal Data Scientist,99536,USD,99536,MI,CT,United States,M,United States,100,"Linux, PyTorch, SQL, Statistics, MLOps",Bachelor,2,Manufacturing,2025-04-07,2025-06-13,1184,6.2,Predictive Systems +AI10507,AI Research Scientist,124279,AUD,167777,MI,FT,Australia,L,Australia,50,"Java, PyTorch, R, Tableau",Bachelor,2,Retail,2025-04-27,2025-06-06,862,5.8,DeepTech Ventures +AI10508,Machine Learning Engineer,64888,EUR,55155,EN,FL,Germany,L,Germany,50,"Spark, Linux, PyTorch, Java",Associate,1,Technology,2025-02-11,2025-03-06,1392,5.1,Cloud AI Solutions +AI10509,AI Product Manager,102390,EUR,87032,SE,FL,Germany,S,Germany,0,"GCP, Deep Learning, R, TensorFlow",PhD,9,Gaming,2024-06-27,2024-08-12,1601,5.7,Future Systems +AI10510,Research Scientist,43363,USD,43363,MI,PT,China,L,China,100,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Master,3,Government,2024-05-10,2024-07-19,1250,9.1,Algorithmic Solutions +AI10511,Machine Learning Engineer,82118,AUD,110859,EN,CT,Australia,L,Australia,50,"Deep Learning, Mathematics, Data Visualization",PhD,0,Transportation,2024-05-22,2024-07-11,2347,9,Machine Intelligence Group +AI10512,Deep Learning Engineer,138768,USD,138768,SE,FL,Ireland,L,Ireland,50,"Hadoop, Kubernetes, Data Visualization, NLP, Spark",Associate,7,Media,2024-08-09,2024-09-26,2439,6.6,Neural Networks Co +AI10513,Computer Vision Engineer,48876,AUD,65983,EN,FL,Australia,S,Australia,50,"NLP, GCP, Tableau, Azure, Docker",Master,1,Gaming,2024-06-01,2024-07-29,1711,7.9,DataVision Ltd +AI10514,Machine Learning Researcher,72281,USD,72281,EN,FT,Ireland,S,Ireland,0,"SQL, Hadoop, Data Visualization",Bachelor,0,Consulting,2024-09-22,2024-10-09,1577,8.4,Neural Networks Co +AI10515,AI Research Scientist,136114,AUD,183754,SE,PT,Australia,S,Australia,100,"Python, Scala, Java, Deep Learning",Bachelor,8,Consulting,2024-01-04,2024-02-22,901,5.5,Predictive Systems +AI10516,Data Analyst,47355,USD,47355,SE,FL,India,S,Israel,100,"Tableau, Spark, AWS, Scala, SQL",Bachelor,6,Gaming,2024-11-09,2024-11-24,1396,6.4,Autonomous Tech +AI10517,AI Architect,116538,USD,116538,MI,FT,Israel,L,Israel,0,"Statistics, Spark, Mathematics",Bachelor,2,Finance,2024-09-06,2024-10-24,1791,9.1,Machine Intelligence Group +AI10518,Data Engineer,101215,USD,101215,MI,CT,Ireland,M,Ireland,0,"Git, Python, NLP, Statistics, Kubernetes",PhD,4,Energy,2024-06-25,2024-08-08,1775,9.3,Smart Analytics +AI10519,Computer Vision Engineer,120939,CHF,108845,MI,CT,Switzerland,L,Switzerland,0,"Git, Java, SQL, Azure",Associate,3,Media,2024-12-16,2025-02-17,1891,8,Smart Analytics +AI10520,AI Consultant,53345,JPY,5867950,EN,PT,Japan,S,Netherlands,50,"Python, TensorFlow, Kubernetes, Linux, MLOps",Master,1,Telecommunications,2024-05-28,2024-07-13,605,7.9,Quantum Computing Inc +AI10521,Machine Learning Researcher,49297,USD,49297,EN,FT,Israel,M,Israel,0,"Kubernetes, PyTorch, GCP",Master,0,Manufacturing,2024-06-15,2024-07-19,2343,8.2,Predictive Systems +AI10522,Data Engineer,85313,SGD,110907,EN,FL,Singapore,M,Singapore,100,"SQL, PyTorch, NLP, Hadoop, MLOps",PhD,1,Gaming,2024-02-03,2024-02-17,960,6.9,Future Systems +AI10523,Computer Vision Engineer,165378,CAD,206723,EX,FT,Canada,S,Canada,50,"Java, Git, Tableau, GCP",Bachelor,18,Real Estate,2024-01-26,2024-03-25,1637,9.5,Algorithmic Solutions +AI10524,AI Product Manager,78358,USD,78358,EN,PT,Israel,L,Israel,0,"Java, SQL, Computer Vision, R",Bachelor,0,Government,2024-01-24,2024-03-07,723,6.1,DeepTech Ventures +AI10525,NLP Engineer,23160,USD,23160,EN,FL,India,S,India,100,"Docker, Git, Statistics, R",Bachelor,1,Manufacturing,2024-05-09,2024-06-14,936,9.7,Quantum Computing Inc +AI10526,Research Scientist,85575,USD,85575,MI,PT,Israel,M,Israel,0,"Python, Kubernetes, Linux, NLP, PyTorch",Bachelor,2,Education,2025-03-28,2025-06-04,2322,7.1,TechCorp Inc +AI10527,AI Specialist,188461,JPY,20730710,EX,FL,Japan,S,Japan,50,"Scala, Spark, Tableau, MLOps",Master,18,Consulting,2025-01-19,2025-03-26,988,5.7,Digital Transformation LLC +AI10528,Autonomous Systems Engineer,16621,USD,16621,EN,CT,India,S,India,0,"Kubernetes, Python, AWS",Master,0,Manufacturing,2025-02-24,2025-04-29,1724,7.9,Advanced Robotics +AI10529,Machine Learning Researcher,154393,CAD,192991,SE,FL,Canada,L,Canada,100,"Kubernetes, Python, TensorFlow, Java",Master,7,Retail,2024-10-23,2024-11-26,2475,6.9,Quantum Computing Inc +AI10530,Machine Learning Researcher,115524,USD,115524,SE,FT,Finland,S,Finland,50,"R, SQL, Data Visualization, Linux, Deep Learning",Associate,6,Education,2024-01-27,2024-03-29,1229,6.9,Advanced Robotics +AI10531,AI Software Engineer,20633,USD,20633,EN,PT,India,S,India,100,"SQL, GCP, Azure",PhD,1,Real Estate,2024-03-02,2024-04-17,1824,6.9,Cognitive Computing +AI10532,Robotics Engineer,190066,GBP,142550,EX,FL,United Kingdom,S,Romania,50,"PyTorch, Docker, AWS, Deep Learning",Associate,11,Government,2024-08-17,2024-10-08,1342,9.3,Quantum Computing Inc +AI10533,Head of AI,296126,JPY,32573860,EX,FT,Japan,L,Japan,0,"PyTorch, Statistics, TensorFlow, NLP, Deep Learning",Associate,18,Gaming,2024-07-21,2024-09-18,775,9.6,Predictive Systems +AI10534,Autonomous Systems Engineer,187800,USD,187800,SE,FL,Norway,L,Norway,100,"Tableau, Git, Deep Learning, Python, SQL",PhD,7,Real Estate,2024-12-30,2025-03-13,1720,9.5,Autonomous Tech +AI10535,Data Scientist,206562,USD,206562,EX,CT,Ireland,S,Ireland,100,"GCP, Java, NLP, Data Visualization",Associate,17,Gaming,2024-06-10,2024-07-15,1196,7.1,Algorithmic Solutions +AI10536,AI Specialist,188230,JPY,20705300,EX,FL,Japan,S,Japan,0,"Python, Computer Vision, Tableau, Linux",PhD,11,Manufacturing,2024-08-20,2024-10-17,1097,7.5,TechCorp Inc +AI10537,Machine Learning Engineer,151183,USD,151183,SE,FT,Norway,S,Norway,50,"Hadoop, SQL, TensorFlow, NLP",PhD,5,Retail,2024-12-27,2025-01-31,1674,6,DeepTech Ventures +AI10538,Principal Data Scientist,84340,JPY,9277400,EN,PT,Japan,L,Japan,0,"MLOps, Git, Java, Kubernetes",Bachelor,1,Transportation,2024-06-05,2024-08-03,1477,7.1,Machine Intelligence Group +AI10539,Head of AI,130206,SGD,169268,SE,CT,Singapore,S,Singapore,100,"R, Scala, SQL, Data Visualization",Bachelor,7,Media,2024-10-05,2024-11-13,566,6,TechCorp Inc +AI10540,Machine Learning Researcher,59063,AUD,79735,EN,CT,Australia,M,Australia,0,"Azure, Python, GCP, Scala",Bachelor,0,Gaming,2024-06-07,2024-07-23,696,8.6,Cloud AI Solutions +AI10541,Data Engineer,105416,CHF,94874,EN,CT,Switzerland,M,Switzerland,50,"R, Python, Data Visualization, TensorFlow, Git",PhD,1,Consulting,2024-01-28,2024-03-11,2392,6.7,DeepTech Ventures +AI10542,Head of AI,116299,USD,116299,EX,PT,China,M,China,100,"Hadoop, Linux, SQL",Bachelor,17,Transportation,2025-01-03,2025-03-15,615,5.2,AI Innovations +AI10543,Data Analyst,123542,USD,123542,SE,FT,Sweden,M,Sweden,50,"Git, Python, AWS",Bachelor,8,Healthcare,2024-03-27,2024-05-07,2113,5.1,Cloud AI Solutions +AI10544,Computer Vision Engineer,268891,CHF,242002,EX,FL,Switzerland,L,Switzerland,50,"Statistics, R, Tableau",Master,19,Consulting,2024-10-05,2024-12-05,1722,5.8,Digital Transformation LLC +AI10545,Robotics Engineer,184006,USD,184006,EX,PT,South Korea,M,France,0,"Spark, Deep Learning, Computer Vision, Python",Bachelor,11,Telecommunications,2024-10-01,2024-11-25,1949,9.3,Future Systems +AI10546,Head of AI,253222,JPY,27854420,EX,CT,Japan,L,Japan,0,"PyTorch, Data Visualization, TensorFlow, GCP, Python",Master,17,Energy,2024-05-03,2024-06-01,1021,8.7,TechCorp Inc +AI10547,AI Software Engineer,117179,USD,117179,EN,PT,Norway,L,Thailand,100,"Data Visualization, Linux, Python",Master,1,Real Estate,2024-05-10,2024-07-06,2212,6.9,Digital Transformation LLC +AI10548,Machine Learning Engineer,267272,GBP,200454,EX,FT,United Kingdom,L,Portugal,0,"Git, Data Visualization, Java, NLP",PhD,10,Real Estate,2024-02-01,2024-03-15,503,8.8,DataVision Ltd +AI10549,Deep Learning Engineer,58015,EUR,49313,EN,FL,France,M,France,50,"Linux, NLP, Mathematics",PhD,0,Retail,2025-03-13,2025-05-25,2176,9,Smart Analytics +AI10550,Computer Vision Engineer,134945,EUR,114703,SE,FL,France,M,Philippines,100,"MLOps, Python, Hadoop, TensorFlow, Git",Master,5,Government,2024-05-20,2024-07-23,935,7.1,Machine Intelligence Group +AI10551,Data Analyst,171640,GBP,128730,SE,CT,United Kingdom,L,United Kingdom,100,"TensorFlow, Linux, Hadoop",PhD,7,Government,2024-03-26,2024-04-22,2475,9.2,Advanced Robotics +AI10552,NLP Engineer,188053,USD,188053,EX,PT,Sweden,S,Sweden,50,"Scala, Deep Learning, Java, PyTorch",Associate,18,Retail,2024-02-24,2024-03-21,2223,6.9,Machine Intelligence Group +AI10553,Research Scientist,174050,EUR,147943,SE,PT,Netherlands,L,Netherlands,100,"Linux, Statistics, Spark",Bachelor,5,Gaming,2024-07-08,2024-09-19,712,8.2,Digital Transformation LLC +AI10554,Machine Learning Researcher,162350,USD,162350,EX,CT,South Korea,S,South Korea,100,"SQL, AWS, MLOps, Azure",Master,15,Consulting,2024-06-01,2024-08-11,1094,7.6,Digital Transformation LLC +AI10555,NLP Engineer,48857,USD,48857,EN,FL,Sweden,S,Singapore,0,"Scala, Java, Computer Vision, Python, TensorFlow",Bachelor,1,Technology,2025-01-17,2025-03-10,2343,9.3,Neural Networks Co +AI10556,Autonomous Systems Engineer,81741,SGD,106263,EN,FT,Singapore,M,Singapore,100,"Mathematics, Git, NLP, SQL",Associate,0,Healthcare,2025-01-16,2025-03-25,2261,6.9,Cognitive Computing +AI10557,Data Scientist,93881,EUR,79799,MI,FT,Austria,M,Austria,100,"Scala, MLOps, Java, TensorFlow",Bachelor,3,Healthcare,2024-07-16,2024-08-24,1606,7.5,Machine Intelligence Group +AI10558,AI Research Scientist,52800,USD,52800,EN,FL,Finland,S,Finland,0,"MLOps, Docker, Data Visualization, R",PhD,0,Finance,2024-08-14,2024-10-18,551,6.8,Predictive Systems +AI10559,AI Consultant,164719,CHF,148247,MI,FL,Switzerland,L,Switzerland,100,"Hadoop, Data Visualization, Scala, Docker",Associate,4,Consulting,2024-06-24,2024-08-24,1239,5.3,Autonomous Tech +AI10560,Research Scientist,89861,GBP,67396,MI,CT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Python, Tableau",Master,2,Education,2024-07-03,2024-07-19,1058,6.4,AI Innovations +AI10561,Autonomous Systems Engineer,182265,USD,182265,EX,FL,Israel,S,Israel,100,"Kubernetes, TensorFlow, Mathematics, AWS",Bachelor,19,Manufacturing,2024-10-28,2025-01-04,1922,7.1,Quantum Computing Inc +AI10562,Head of AI,119526,USD,119526,SE,PT,Israel,M,Austria,100,"Spark, Mathematics, Python",Bachelor,6,Technology,2025-03-05,2025-04-23,1562,7,Cognitive Computing +AI10563,Deep Learning Engineer,167797,USD,167797,EX,FL,Sweden,S,United Kingdom,100,"Computer Vision, NLP, Statistics",Master,19,Healthcare,2024-12-19,2025-02-14,1184,7.9,Algorithmic Solutions +AI10564,Machine Learning Researcher,338875,USD,338875,EX,FT,United States,L,United States,100,"Statistics, PyTorch, Deep Learning, TensorFlow",Master,16,Automotive,2024-07-24,2024-08-10,2085,7.1,Smart Analytics +AI10565,NLP Engineer,191360,EUR,162656,EX,FT,Austria,S,Austria,50,"Mathematics, Hadoop, Git, Computer Vision, Data Visualization",Bachelor,16,Telecommunications,2025-04-06,2025-06-01,2448,6.5,Future Systems +AI10566,Machine Learning Researcher,134565,USD,134565,SE,FL,United States,S,United States,0,"Statistics, Linux, Python, Git, Tableau",PhD,6,Real Estate,2024-09-04,2024-10-21,653,9.5,TechCorp Inc +AI10567,AI Consultant,75173,JPY,8269030,EN,FL,Japan,S,Belgium,100,"Python, TensorFlow, Mathematics, Git",Associate,0,Real Estate,2024-11-01,2024-12-04,2083,5.4,Cloud AI Solutions +AI10568,Machine Learning Engineer,123862,EUR,105283,SE,FL,France,S,France,0,"NLP, Tableau, Computer Vision",PhD,7,Finance,2024-02-29,2024-03-18,1232,5.4,Algorithmic Solutions +AI10569,Research Scientist,118839,AUD,160433,MI,FL,Australia,L,Australia,50,"PyTorch, TensorFlow, GCP, Spark",Master,4,Automotive,2024-04-22,2024-05-25,963,8,TechCorp Inc +AI10570,Robotics Engineer,72716,EUR,61809,EN,FL,Germany,L,Germany,100,"GCP, Python, Data Visualization, TensorFlow, Computer Vision",Bachelor,0,Transportation,2024-07-03,2024-07-27,501,7.8,Smart Analytics +AI10571,Data Scientist,126408,USD,126408,MI,FT,United States,L,Nigeria,0,"R, Python, NLP, Hadoop, Deep Learning",Master,4,Retail,2024-08-10,2024-10-13,1126,5.1,Neural Networks Co +AI10572,AI Research Scientist,116295,EUR,98851,MI,CT,Netherlands,M,Netherlands,100,"SQL, Deep Learning, PyTorch, Git, GCP",Bachelor,4,Telecommunications,2024-06-04,2024-07-25,991,7.3,Digital Transformation LLC +AI10573,AI Architect,104716,EUR,89009,MI,CT,Germany,L,New Zealand,50,"Kubernetes, Docker, Git",Master,3,Media,2025-02-07,2025-04-15,688,7.5,Advanced Robotics +AI10574,AI Product Manager,130494,JPY,14354340,MI,FT,Japan,L,Japan,0,"Kubernetes, TensorFlow, Python",Bachelor,4,Technology,2025-01-27,2025-04-06,1863,7.8,Quantum Computing Inc +AI10575,ML Ops Engineer,150085,AUD,202615,SE,CT,Australia,L,Australia,100,"AWS, Azure, Python, Java, MLOps",Master,5,Automotive,2024-05-03,2024-07-07,523,8.6,DataVision Ltd +AI10576,Deep Learning Engineer,45879,USD,45879,SE,PT,India,S,Latvia,50,"R, GCP, PyTorch, Computer Vision, Statistics",Bachelor,6,Government,2024-01-29,2024-02-25,2273,7.7,Cloud AI Solutions +AI10577,Data Scientist,108528,USD,108528,MI,CT,Denmark,L,Latvia,50,"Git, Kubernetes, Java",PhD,3,Consulting,2024-10-30,2025-01-04,1012,10,DeepTech Ventures +AI10578,Autonomous Systems Engineer,191897,EUR,163112,EX,FL,Austria,L,China,100,"R, SQL, Deep Learning",PhD,19,Automotive,2025-02-18,2025-04-19,1240,5.1,Algorithmic Solutions +AI10579,AI Software Engineer,93358,USD,93358,MI,PT,Norway,S,Norway,50,"Statistics, Kubernetes, NLP, GCP",Associate,4,Technology,2024-04-08,2024-05-16,909,6.4,Predictive Systems +AI10580,Data Engineer,31111,USD,31111,MI,CT,India,M,Argentina,100,"Spark, Kubernetes, Mathematics",PhD,3,Gaming,2024-09-21,2024-11-08,2004,5.8,Predictive Systems +AI10581,NLP Engineer,275338,AUD,371706,EX,CT,Australia,L,Australia,50,"Docker, Data Visualization, Java, Spark",PhD,19,Media,2024-06-14,2024-08-08,784,8.5,AI Innovations +AI10582,AI Consultant,147650,USD,147650,SE,FL,Ireland,L,Ireland,100,"GCP, Kubernetes, PyTorch, Scala, Deep Learning",Master,8,Automotive,2024-09-15,2024-10-03,1084,5.9,Predictive Systems +AI10583,Data Scientist,204393,GBP,153295,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, GCP, Data Visualization",Bachelor,18,Gaming,2025-01-17,2025-02-02,1818,5.9,Cognitive Computing +AI10584,Data Engineer,63051,USD,63051,EN,CT,South Korea,M,South Korea,0,"Git, Java, NLP",Master,1,Energy,2024-10-26,2024-11-24,509,6.6,Smart Analytics +AI10585,Computer Vision Engineer,68170,JPY,7498700,EN,FT,Japan,M,Singapore,0,"Kubernetes, TensorFlow, GCP",Associate,1,Telecommunications,2025-01-08,2025-03-12,2423,6.7,Future Systems +AI10586,Principal Data Scientist,63760,GBP,47820,EN,PT,United Kingdom,L,United Kingdom,0,"Python, Kubernetes, TensorFlow, Scala",Associate,0,Technology,2024-02-04,2024-03-05,1911,6.2,Future Systems +AI10587,Machine Learning Engineer,93851,USD,93851,MI,FL,United States,S,Switzerland,0,"TensorFlow, Scala, GCP, SQL",Master,3,Gaming,2025-04-23,2025-06-22,2028,8.4,Smart Analytics +AI10588,Data Scientist,125553,USD,125553,SE,PT,United States,S,United States,50,"Java, GCP, Azure",Master,6,Education,2024-10-31,2024-11-29,1036,8.1,AI Innovations +AI10589,Computer Vision Engineer,56723,CAD,70904,EN,FT,Canada,L,Canada,100,"Tableau, Python, Kubernetes, Scala",Associate,1,Gaming,2024-11-08,2024-11-25,1997,6.6,Digital Transformation LLC +AI10590,AI Product Manager,78007,USD,78007,EN,CT,United States,S,United States,50,"Azure, Spark, MLOps, Tableau",Bachelor,1,Finance,2024-03-01,2024-03-17,2122,9.3,Advanced Robotics +AI10591,Data Scientist,230768,USD,230768,EX,CT,Finland,L,Spain,50,"MLOps, Scala, TensorFlow, Mathematics",PhD,17,Media,2024-06-26,2024-07-29,1798,8.4,Cognitive Computing +AI10592,Data Scientist,61453,USD,61453,EN,CT,Israel,S,Israel,100,"Java, Python, Git",Bachelor,0,Energy,2024-07-09,2024-08-07,671,9.4,Predictive Systems +AI10593,Robotics Engineer,86143,CAD,107679,MI,PT,Canada,S,Canada,50,"Hadoop, NLP, Scala",Master,2,Manufacturing,2025-01-03,2025-03-05,1242,6.6,TechCorp Inc +AI10594,Head of AI,60433,CAD,75541,EN,FT,Canada,L,Brazil,50,"Java, Kubernetes, MLOps, Computer Vision",Associate,0,Education,2024-08-29,2024-09-21,613,5.9,Quantum Computing Inc +AI10595,AI Architect,71504,EUR,60778,MI,FL,Austria,M,Austria,50,"PyTorch, Git, Kubernetes, Deep Learning, Scala",Bachelor,2,Finance,2024-11-17,2025-01-23,1193,5.3,Autonomous Tech +AI10596,Deep Learning Engineer,141331,CAD,176664,SE,FT,Canada,M,Canada,0,"SQL, Python, GCP, Java, TensorFlow",PhD,9,Consulting,2024-08-25,2024-11-06,2124,5.7,Machine Intelligence Group +AI10597,Data Scientist,182504,JPY,20075440,SE,PT,Japan,L,Finland,100,"Spark, Tableau, Deep Learning, SQL",Associate,5,Finance,2024-09-24,2024-11-09,2236,8.1,Advanced Robotics +AI10598,Data Analyst,32356,USD,32356,MI,FT,China,S,China,50,"NLP, SQL, Scala",PhD,2,Retail,2024-06-06,2024-06-24,1316,8,Neural Networks Co +AI10599,AI Specialist,212698,AUD,287142,EX,FL,Australia,S,Australia,50,"Scala, Git, SQL",Associate,16,Gaming,2024-06-28,2024-08-26,1759,5.3,Future Systems +AI10600,AI Software Engineer,159697,EUR,135742,EX,PT,France,M,France,0,"Linux, Python, R",Bachelor,11,Media,2024-06-17,2024-08-23,2236,9.1,Predictive Systems +AI10601,Principal Data Scientist,104312,USD,104312,EN,CT,United States,L,Australia,0,"Docker, Linux, PyTorch, Data Visualization",Associate,1,Education,2024-09-07,2024-10-06,1298,7.9,Smart Analytics +AI10602,Machine Learning Researcher,80606,USD,80606,EN,FL,Sweden,M,Sweden,50,"Scala, Git, Data Visualization, Mathematics, SQL",PhD,1,Energy,2024-08-06,2024-09-03,721,6.8,Digital Transformation LLC +AI10603,AI Specialist,123309,EUR,104813,SE,FT,Germany,M,United Kingdom,0,"Java, Docker, GCP",Master,7,Media,2024-11-26,2025-01-27,1603,9.3,Future Systems +AI10604,AI Architect,278484,AUD,375953,EX,FL,Australia,L,Norway,0,"Linux, Scala, Git, Python, TensorFlow",Bachelor,14,Education,2025-04-29,2025-05-24,605,8.6,DataVision Ltd +AI10605,NLP Engineer,88219,USD,88219,MI,FT,Ireland,L,Ireland,50,"Python, Linux, Kubernetes",PhD,2,Education,2025-03-04,2025-04-25,963,9.6,Cloud AI Solutions +AI10606,ML Ops Engineer,85752,CHF,77177,EN,FL,Switzerland,S,Canada,100,"Python, TensorFlow, Git, PyTorch, NLP",Master,1,Retail,2024-04-26,2024-06-06,1245,7.8,AI Innovations +AI10607,ML Ops Engineer,152528,USD,152528,SE,FT,Sweden,M,Argentina,100,"NLP, Azure, Java",Associate,5,Healthcare,2024-11-28,2024-12-19,1606,9.8,Advanced Robotics +AI10608,Principal Data Scientist,79883,EUR,67901,MI,PT,Austria,S,Austria,0,"Python, MLOps, TensorFlow, Computer Vision, Statistics",PhD,3,Real Estate,2024-01-25,2024-03-31,635,6.9,Future Systems +AI10609,Data Analyst,71938,USD,71938,MI,PT,Israel,M,United Kingdom,100,"Azure, Spark, Scala, Mathematics, Python",Bachelor,4,Media,2025-02-15,2025-03-31,1038,5.6,Smart Analytics +AI10610,AI Architect,187859,USD,187859,EX,PT,South Korea,M,South Korea,100,"Hadoop, R, PyTorch, SQL",PhD,13,Government,2025-03-13,2025-04-30,991,8.2,TechCorp Inc +AI10611,Research Scientist,80473,USD,80473,SE,FL,South Korea,S,South Korea,100,"NLP, AWS, Java, Computer Vision, Python",Bachelor,6,Consulting,2024-04-15,2024-05-04,2365,7.2,DataVision Ltd +AI10612,Machine Learning Engineer,150968,EUR,128323,SE,FL,Germany,L,Turkey,100,"Python, Scala, TensorFlow, Deep Learning, Java",Master,8,Gaming,2024-03-14,2024-05-18,953,6,Cognitive Computing +AI10613,AI Software Engineer,117941,USD,117941,MI,CT,Finland,L,Denmark,100,"R, Spark, Data Visualization, Deep Learning, Azure",PhD,4,Energy,2024-04-10,2024-06-03,786,9.1,Autonomous Tech +AI10614,AI Software Engineer,67317,USD,67317,EN,CT,Denmark,S,Russia,50,"Docker, Spark, R, GCP",Bachelor,0,Healthcare,2024-01-02,2024-03-04,2454,7.2,AI Innovations +AI10615,Data Engineer,120964,EUR,102819,SE,PT,Netherlands,M,Luxembourg,0,"R, Java, SQL",PhD,8,Healthcare,2024-01-24,2024-02-29,1395,8.5,TechCorp Inc +AI10616,Head of AI,147747,CHF,132972,MI,CT,Switzerland,L,Switzerland,50,"Scala, Spark, Data Visualization",Master,4,Transportation,2024-03-04,2024-03-26,1292,5.9,Algorithmic Solutions +AI10617,Computer Vision Engineer,144492,AUD,195064,SE,PT,Australia,L,Australia,50,"Java, Spark, TensorFlow, Hadoop, Scala",Associate,9,Manufacturing,2025-04-06,2025-06-12,2186,5.3,Algorithmic Solutions +AI10618,Machine Learning Engineer,245526,USD,245526,EX,FT,United States,S,Israel,100,"Python, Git, Kubernetes",Bachelor,12,Manufacturing,2025-02-28,2025-03-19,1919,5.4,Autonomous Tech +AI10619,Machine Learning Researcher,118930,GBP,89198,SE,FL,United Kingdom,S,United Kingdom,100,"GCP, NLP, Hadoop, Python, Scala",Master,8,Technology,2024-02-06,2024-03-12,2485,6.4,Autonomous Tech +AI10620,Data Scientist,173914,USD,173914,SE,PT,United States,L,United States,100,"Scala, Java, NLP, PyTorch, SQL",Bachelor,9,Telecommunications,2024-01-06,2024-02-15,1015,8.9,AI Innovations +AI10621,AI Architect,46392,EUR,39433,EN,FT,Germany,S,Latvia,100,"NLP, Azure, Linux, Kubernetes, Data Visualization",PhD,1,Finance,2024-06-08,2024-06-27,2495,7.9,DeepTech Ventures +AI10622,AI Product Manager,97856,USD,97856,SE,FT,Ireland,S,Ireland,50,"Python, Scala, Spark, GCP, Linux",Bachelor,8,Gaming,2024-06-17,2024-07-05,938,9.4,DeepTech Ventures +AI10623,Machine Learning Engineer,118261,EUR,100522,SE,FT,Germany,S,Germany,0,"MLOps, Git, Kubernetes, NLP",Master,6,Energy,2024-04-25,2024-05-24,1937,8.4,AI Innovations +AI10624,Deep Learning Engineer,85135,EUR,72365,MI,PT,France,M,France,50,"Scala, Spark, Git",Bachelor,3,Technology,2024-07-10,2024-08-30,967,7.4,Cognitive Computing +AI10625,Machine Learning Researcher,178627,AUD,241146,EX,FL,Australia,L,Austria,0,"Python, Deep Learning, Tableau",Bachelor,12,Transportation,2025-02-27,2025-04-23,1070,7.9,Quantum Computing Inc +AI10626,AI Specialist,95464,USD,95464,MI,FL,Sweden,S,Germany,100,"Scala, Java, AWS",Bachelor,3,Finance,2024-12-19,2025-02-11,629,9.5,Predictive Systems +AI10627,Deep Learning Engineer,91229,AUD,123159,EN,PT,Australia,L,Australia,0,"Azure, SQL, Tableau",Associate,0,Energy,2024-08-15,2024-09-26,1126,9.2,Cloud AI Solutions +AI10628,Research Scientist,192344,USD,192344,EX,FL,Sweden,S,Sweden,100,"TensorFlow, GCP, SQL, Docker, Git",Master,14,Automotive,2024-02-19,2024-03-10,2148,9.4,Predictive Systems +AI10629,Data Analyst,47789,USD,47789,EN,CT,Israel,S,Israel,100,"SQL, Linux, PyTorch, Git",Associate,0,Finance,2025-01-05,2025-01-26,1422,6,Predictive Systems +AI10630,Machine Learning Engineer,129729,EUR,110270,SE,FT,Germany,M,Germany,50,"Docker, Linux, Spark, Python",Associate,8,Technology,2024-02-05,2024-03-31,1715,7.5,TechCorp Inc +AI10631,AI Software Engineer,72974,USD,72974,MI,FT,South Korea,S,Canada,50,"Linux, Spark, Python, NLP, TensorFlow",PhD,2,Transportation,2024-03-07,2024-04-28,2093,9.4,Advanced Robotics +AI10632,Computer Vision Engineer,140615,EUR,119523,SE,FT,France,L,France,50,"PyTorch, Computer Vision, R, Scala, AWS",Bachelor,8,Manufacturing,2025-01-30,2025-02-27,876,5.4,Autonomous Tech +AI10633,Data Engineer,111490,SGD,144937,MI,FL,Singapore,M,Singapore,0,"Python, NLP, TensorFlow",PhD,4,Retail,2024-08-30,2024-10-18,1663,6.3,Predictive Systems +AI10634,Deep Learning Engineer,61103,GBP,45827,EN,FL,United Kingdom,S,United Kingdom,50,"Spark, Docker, Python, Deep Learning",PhD,1,Media,2025-01-23,2025-02-23,1769,5.6,Algorithmic Solutions +AI10635,AI Product Manager,116733,USD,116733,EX,CT,Israel,S,Israel,100,"Azure, Scala, MLOps, Python",Master,18,Media,2025-04-25,2025-05-14,1365,6.7,Machine Intelligence Group +AI10636,AI Specialist,283444,USD,283444,EX,PT,Ireland,L,Latvia,0,"SQL, Scala, R, Docker, Deep Learning",Associate,12,Government,2025-04-11,2025-05-02,2143,7.8,AI Innovations +AI10637,AI Architect,107069,EUR,91009,MI,FT,Netherlands,M,South Korea,100,"Python, TensorFlow, GCP",Master,2,Energy,2025-03-05,2025-04-09,1179,8.7,TechCorp Inc +AI10638,AI Consultant,73972,USD,73972,EN,PT,Israel,M,Israel,100,"Docker, MLOps, Mathematics, Linux",Master,0,Media,2024-06-10,2024-07-28,1551,9.9,DataVision Ltd +AI10639,AI Product Manager,52290,JPY,5751900,EN,PT,Japan,S,Japan,0,"NLP, Azure, Mathematics",Bachelor,1,Energy,2024-07-09,2024-09-10,1815,5.8,Advanced Robotics +AI10640,AI Product Manager,204367,CAD,255459,EX,CT,Canada,M,Canada,100,"AWS, Java, Azure, TensorFlow, Linux",Bachelor,15,Healthcare,2024-10-25,2024-11-23,1798,5.2,Smart Analytics +AI10641,Autonomous Systems Engineer,91739,JPY,10091290,MI,CT,Japan,M,Japan,50,"Statistics, R, Python, MLOps, GCP",Bachelor,3,Gaming,2025-01-25,2025-03-08,902,5.1,Autonomous Tech +AI10642,AI Specialist,52164,SGD,67813,EN,PT,Singapore,S,Singapore,100,"R, GCP, Computer Vision",Master,1,Retail,2024-10-23,2024-11-22,2141,5.9,Cognitive Computing +AI10643,Data Analyst,135990,EUR,115592,SE,FL,France,L,France,0,"Tableau, Java, SQL, Azure",Associate,7,Government,2024-10-23,2024-12-17,1398,8.2,Cloud AI Solutions +AI10644,Autonomous Systems Engineer,180546,GBP,135410,SE,CT,United Kingdom,L,United Kingdom,0,"Hadoop, SQL, Spark, Kubernetes",Bachelor,9,Gaming,2025-02-18,2025-03-06,1432,8.4,TechCorp Inc +AI10645,Data Analyst,173391,EUR,147382,EX,PT,France,S,Luxembourg,100,"Java, Python, Mathematics, GCP, Linux",Associate,16,Government,2024-08-24,2024-11-02,2082,8.5,Digital Transformation LLC +AI10646,AI Consultant,131162,JPY,14427820,SE,CT,Japan,S,India,100,"GCP, Azure, Spark, Data Visualization",PhD,5,Technology,2024-05-01,2024-07-03,2200,5.5,DeepTech Ventures +AI10647,Autonomous Systems Engineer,83876,USD,83876,EN,CT,Israel,L,Israel,100,"Python, GCP, Deep Learning, TensorFlow, Data Visualization",Master,1,Consulting,2024-12-27,2025-02-21,524,9.9,DeepTech Ventures +AI10648,AI Product Manager,120528,USD,120528,SE,CT,Denmark,S,Ghana,0,"Java, Python, Linux",Bachelor,5,Consulting,2024-09-05,2024-10-28,675,8.1,Advanced Robotics +AI10649,Head of AI,20105,USD,20105,EN,PT,India,S,India,100,"Java, PyTorch, MLOps, Data Visualization, Linux",Associate,1,Energy,2025-01-08,2025-01-28,926,9.6,Autonomous Tech +AI10650,Computer Vision Engineer,99524,EUR,84595,MI,PT,Austria,M,Austria,0,"GCP, SQL, Tableau, PyTorch",Master,2,Government,2025-01-24,2025-02-08,2434,9.2,Algorithmic Solutions +AI10651,Research Scientist,97168,EUR,82593,EN,FT,Netherlands,L,Australia,0,"Python, TensorFlow, Docker, Statistics, SQL",Bachelor,1,Manufacturing,2025-02-22,2025-04-26,1604,9.4,Advanced Robotics +AI10652,Machine Learning Researcher,79501,AUD,107326,MI,PT,Australia,S,Austria,0,"R, Hadoop, AWS, Docker",Master,3,Energy,2024-05-09,2024-05-23,1453,8.1,DeepTech Ventures +AI10653,NLP Engineer,80406,GBP,60305,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Python",Associate,0,Technology,2025-02-15,2025-04-28,1482,6,DataVision Ltd +AI10654,Principal Data Scientist,179168,SGD,232918,SE,FL,Singapore,L,Singapore,50,"SQL, PyTorch, Java, GCP",Master,5,Manufacturing,2024-07-30,2024-09-23,2303,5.6,Smart Analytics +AI10655,Machine Learning Researcher,117302,USD,117302,SE,FT,United States,S,United States,50,"Docker, Deep Learning, Kubernetes, R, SQL",Bachelor,7,Finance,2025-04-07,2025-06-05,1833,8.9,Predictive Systems +AI10656,Machine Learning Researcher,24496,USD,24496,EN,CT,China,S,Netherlands,0,"Java, Computer Vision, Kubernetes",Associate,1,Telecommunications,2024-04-07,2024-06-16,1991,9.8,Advanced Robotics +AI10657,AI Consultant,136071,GBP,102053,EX,CT,United Kingdom,S,United Kingdom,100,"Python, SQL, GCP, Hadoop, Spark",Associate,16,Real Estate,2025-03-27,2025-04-18,965,7.4,Cognitive Computing +AI10658,Robotics Engineer,238120,USD,238120,EX,PT,Sweden,L,Sweden,50,"Java, Docker, Mathematics, Git, Data Visualization",Master,16,Education,2024-02-25,2024-03-13,1211,8,DeepTech Ventures +AI10659,ML Ops Engineer,156352,JPY,17198720,SE,CT,Japan,M,Belgium,100,"Java, Kubernetes, GCP, Mathematics, TensorFlow",Associate,7,Finance,2024-12-10,2025-01-30,1328,7.7,Cognitive Computing +AI10660,Computer Vision Engineer,36448,USD,36448,EN,FL,China,L,China,0,"TensorFlow, Git, Python, GCP, SQL",Master,0,Healthcare,2024-02-06,2024-04-06,501,7.3,Smart Analytics +AI10661,ML Ops Engineer,225966,USD,225966,EX,FL,South Korea,L,South Korea,50,"R, Git, Tableau",Associate,14,Media,2024-09-11,2024-11-14,661,7,Quantum Computing Inc +AI10662,AI Specialist,30284,USD,30284,MI,CT,India,M,India,0,"Hadoop, Spark, MLOps, Git, Linux",PhD,3,Healthcare,2024-09-21,2024-11-24,2167,8.6,Autonomous Tech +AI10663,Research Scientist,202712,USD,202712,EX,FL,Denmark,S,Chile,100,"GCP, Kubernetes, AWS, R, Spark",Bachelor,12,Automotive,2024-08-20,2024-10-13,1609,5.7,TechCorp Inc +AI10664,AI Research Scientist,166959,USD,166959,EX,FT,Finland,M,Canada,50,"PyTorch, AWS, Azure",Associate,10,Finance,2024-12-21,2025-02-20,850,5.5,Quantum Computing Inc +AI10665,AI Consultant,122284,EUR,103941,SE,PT,France,S,South Africa,100,"MLOps, Python, TensorFlow",PhD,6,Telecommunications,2024-09-30,2024-11-21,1211,8.9,Algorithmic Solutions +AI10666,Head of AI,116235,USD,116235,SE,CT,Ireland,S,Brazil,100,"R, Java, Tableau, MLOps",Master,8,Healthcare,2024-10-27,2024-11-16,973,8.6,Advanced Robotics +AI10667,Head of AI,202957,USD,202957,EX,PT,Sweden,M,Sweden,0,"Git, Docker, Deep Learning, TensorFlow",PhD,19,Energy,2024-08-13,2024-09-02,2052,5.2,Algorithmic Solutions +AI10668,AI Consultant,79718,JPY,8768980,MI,FT,Japan,S,Portugal,100,"Tableau, Spark, Hadoop",Master,3,Real Estate,2024-11-22,2025-01-06,1868,5.3,Cognitive Computing +AI10669,Robotics Engineer,125746,GBP,94310,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, PyTorch, Mathematics",Master,9,Real Estate,2024-02-26,2024-03-16,919,7,Neural Networks Co +AI10670,AI Specialist,154306,GBP,115730,SE,FT,United Kingdom,M,United Kingdom,0,"Docker, MLOps, PyTorch, Spark",Bachelor,9,Transportation,2024-08-31,2024-09-17,987,9.6,Cloud AI Solutions +AI10671,AI Consultant,86374,EUR,73418,MI,CT,Netherlands,M,Norway,100,"MLOps, Git, GCP",Bachelor,4,Finance,2024-10-01,2024-11-08,558,6.8,DataVision Ltd +AI10672,ML Ops Engineer,113235,USD,113235,SE,FT,Finland,M,Switzerland,0,"GCP, Mathematics, Computer Vision",Master,8,Manufacturing,2024-03-08,2024-05-01,1365,7.5,Digital Transformation LLC +AI10673,Data Analyst,266149,USD,266149,EX,FT,Denmark,S,Denmark,100,"Data Visualization, Spark, NLP, Hadoop, Deep Learning",Master,16,Telecommunications,2024-02-10,2024-03-25,595,6.4,Algorithmic Solutions +AI10674,Head of AI,77319,JPY,8505090,MI,FL,Japan,S,Japan,0,"Git, MLOps, TensorFlow, Kubernetes",PhD,3,Transportation,2024-06-20,2024-07-17,1217,7.9,Algorithmic Solutions +AI10675,Data Engineer,74543,USD,74543,MI,FT,South Korea,M,South Korea,0,"Java, Python, Tableau, Azure, Hadoop",Bachelor,4,Finance,2024-11-18,2025-01-30,1362,9.3,TechCorp Inc +AI10676,AI Specialist,51768,SGD,67298,EN,FL,Singapore,S,Singapore,100,"Docker, AWS, Kubernetes, Tableau",PhD,0,Energy,2025-04-30,2025-06-05,1526,9.2,AI Innovations +AI10677,Autonomous Systems Engineer,213531,USD,213531,EX,PT,Norway,S,Norway,50,"AWS, Data Visualization, Docker, GCP, Python",Master,18,Consulting,2024-05-30,2024-07-20,885,8.5,AI Innovations +AI10678,AI Research Scientist,195386,GBP,146540,EX,FT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, SQL, Linux",Bachelor,14,Telecommunications,2025-01-05,2025-03-05,2185,5.4,Machine Intelligence Group +AI10679,Data Engineer,91835,USD,91835,EX,CT,China,L,China,50,"Linux, Mathematics, NLP, Python",PhD,19,Gaming,2024-10-21,2024-12-01,985,6.2,Cloud AI Solutions +AI10680,AI Research Scientist,95351,EUR,81048,SE,PT,Germany,S,Germany,50,"Spark, SQL, Deep Learning, NLP",Associate,9,Healthcare,2024-08-05,2024-10-13,2260,5,DataVision Ltd +AI10681,Robotics Engineer,89630,USD,89630,MI,CT,Finland,L,Finland,0,"Deep Learning, SQL, Computer Vision",PhD,2,Government,2024-07-21,2024-08-27,1413,9.3,Future Systems +AI10682,Computer Vision Engineer,70678,EUR,60076,MI,PT,Germany,S,Germany,0,"TensorFlow, AWS, Linux, MLOps, Azure",Associate,3,Automotive,2024-04-30,2024-06-18,2104,8,DataVision Ltd +AI10683,Computer Vision Engineer,134959,JPY,14845490,SE,CT,Japan,M,Kenya,100,"GCP, Java, Linux",Bachelor,9,Finance,2024-10-29,2025-01-07,1173,6,Advanced Robotics +AI10684,Head of AI,38645,USD,38645,SE,FL,India,S,India,100,"TensorFlow, Docker, SQL, MLOps",PhD,7,Transportation,2025-01-25,2025-03-26,2358,6.5,DataVision Ltd +AI10685,Machine Learning Engineer,156721,JPY,17239310,EX,FT,Japan,M,Japan,50,"NLP, Git, Deep Learning, Python",PhD,18,Education,2024-03-30,2024-06-10,1357,7.7,Machine Intelligence Group +AI10686,Computer Vision Engineer,60173,USD,60173,EN,PT,Sweden,S,Sweden,50,"TensorFlow, Scala, Java, Statistics",Master,1,Government,2024-06-25,2024-07-26,2352,8.5,AI Innovations +AI10687,Machine Learning Researcher,61314,USD,61314,MI,FT,South Korea,S,South Korea,50,"Python, Docker, Tableau",PhD,2,Manufacturing,2024-02-18,2024-04-27,1801,9.7,Cloud AI Solutions +AI10688,Autonomous Systems Engineer,151060,USD,151060,EX,CT,Israel,S,Israel,100,"Azure, Docker, Python",Master,13,Technology,2025-03-28,2025-05-27,2382,9,Quantum Computing Inc +AI10689,Robotics Engineer,78798,SGD,102437,MI,FL,Singapore,M,Singapore,50,"Data Visualization, PyTorch, Git, Docker",Associate,2,Government,2024-10-22,2024-12-02,2429,7.9,Predictive Systems +AI10690,Principal Data Scientist,28501,USD,28501,MI,FL,India,M,India,100,"Data Visualization, TensorFlow, Python, Scala",Bachelor,3,Gaming,2024-09-26,2024-10-16,2203,7.1,Advanced Robotics +AI10691,Data Scientist,147112,USD,147112,SE,FL,Denmark,M,Denmark,0,"SQL, GCP, Java, Statistics",Associate,7,Retail,2024-02-24,2024-03-23,2407,5.9,Future Systems +AI10692,Machine Learning Engineer,57860,EUR,49181,EN,FT,Austria,L,Finland,50,"Data Visualization, Tableau, Spark, Python, Hadoop",Master,0,Transportation,2024-03-13,2024-04-01,2104,5.7,Neural Networks Co +AI10693,Autonomous Systems Engineer,124336,JPY,13676960,SE,CT,Japan,L,Norway,100,"Docker, GCP, MLOps",Bachelor,6,Transportation,2024-04-02,2024-05-23,1518,6.2,AI Innovations +AI10694,Machine Learning Researcher,52712,EUR,44805,EN,FT,France,M,France,50,"Scala, Hadoop, Statistics, Azure, PyTorch",PhD,0,Energy,2024-08-21,2024-11-01,1117,5.2,TechCorp Inc +AI10695,NLP Engineer,151816,CHF,136634,SE,FL,Switzerland,S,Switzerland,100,"R, Scala, Statistics",PhD,8,Automotive,2024-12-18,2025-02-09,680,7.8,Autonomous Tech +AI10696,Data Engineer,136528,USD,136528,EX,PT,China,L,China,0,"Kubernetes, Java, MLOps",Associate,14,Transportation,2024-05-12,2024-06-17,2317,7.3,Advanced Robotics +AI10697,AI Software Engineer,117912,EUR,100225,SE,PT,France,L,France,50,"SQL, Docker, NLP, Statistics",Bachelor,6,Finance,2025-02-02,2025-04-04,2357,8.2,Machine Intelligence Group +AI10698,AI Consultant,152584,EUR,129696,EX,FT,Austria,S,Austria,0,"PyTorch, Docker, Data Visualization, AWS",PhD,16,Technology,2024-09-16,2024-10-23,1903,6.7,Neural Networks Co +AI10699,AI Software Engineer,148386,USD,148386,MI,FL,United States,L,Kenya,50,"AWS, Python, Statistics",PhD,4,Government,2025-03-01,2025-05-06,832,9.3,Neural Networks Co +AI10700,NLP Engineer,170113,USD,170113,SE,FT,United States,M,United States,100,"Data Visualization, Azure, Java, NLP, Hadoop",PhD,5,Automotive,2024-04-09,2024-05-30,2437,9.4,Algorithmic Solutions +AI10701,Data Engineer,76774,EUR,65258,MI,FL,Germany,M,Hungary,0,"Kubernetes, Statistics, Azure, Deep Learning, SQL",Associate,4,Healthcare,2025-03-29,2025-04-20,876,8.2,DeepTech Ventures +AI10702,AI Software Engineer,104215,USD,104215,EN,FT,Norway,L,Norway,50,"PyTorch, TensorFlow, Tableau, Java, Mathematics",Master,1,Government,2024-05-17,2024-06-26,869,9,Cognitive Computing +AI10703,NLP Engineer,214317,USD,214317,EX,FL,Denmark,S,Russia,50,"Statistics, Scala, Kubernetes, GCP",Bachelor,19,Transportation,2025-04-04,2025-06-10,1517,6.9,DeepTech Ventures +AI10704,Data Scientist,134618,EUR,114425,SE,PT,Austria,M,Austria,0,"Mathematics, GCP, PyTorch, TensorFlow",Master,5,Energy,2025-03-25,2025-05-15,1450,9.9,AI Innovations +AI10705,AI Software Engineer,73195,USD,73195,EN,CT,Ireland,L,Vietnam,100,"GCP, Scala, Mathematics",Associate,1,Finance,2024-08-03,2024-10-09,1283,8,Digital Transformation LLC +AI10706,Computer Vision Engineer,116013,USD,116013,SE,PT,Sweden,S,Austria,0,"Spark, PyTorch, NLP, Java",Bachelor,6,Gaming,2024-02-09,2024-03-20,2305,9.4,TechCorp Inc +AI10707,AI Specialist,129732,JPY,14270520,SE,PT,Japan,L,Japan,50,"Computer Vision, Deep Learning, Linux",Master,8,Real Estate,2024-06-01,2024-06-15,2326,6,Cloud AI Solutions +AI10708,AI Specialist,250954,GBP,188216,EX,FT,United Kingdom,L,United Kingdom,100,"Scala, MLOps, Linux, Kubernetes",Master,19,Media,2025-04-23,2025-05-11,1862,5.9,Autonomous Tech +AI10709,Data Scientist,64591,CAD,80739,EN,CT,Canada,L,Canada,100,"Azure, Scala, R",Bachelor,1,Retail,2024-01-21,2024-02-15,2126,9,Autonomous Tech +AI10710,Data Engineer,117699,USD,117699,SE,FT,Ireland,M,Ireland,100,"Docker, Python, SQL",Associate,7,Retail,2024-08-08,2024-10-07,1819,9.9,Future Systems +AI10711,NLP Engineer,111868,USD,111868,EX,FT,China,L,China,50,"Linux, Git, R, Docker",Master,13,Gaming,2024-06-05,2024-07-18,1727,5.4,Autonomous Tech +AI10712,Research Scientist,143592,USD,143592,SE,PT,United States,S,United States,50,"Computer Vision, Hadoop, Tableau",PhD,5,Finance,2024-01-10,2024-03-23,2454,7.9,Autonomous Tech +AI10713,AI Specialist,112805,EUR,95884,MI,FL,Austria,L,Austria,100,"Python, Hadoop, AWS, Statistics",PhD,4,Education,2024-01-04,2024-01-30,2148,8.7,TechCorp Inc +AI10714,AI Architect,161399,USD,161399,EX,FT,Israel,L,Israel,0,"Java, NLP, SQL",PhD,10,Manufacturing,2024-09-19,2024-11-24,1789,7.8,Autonomous Tech +AI10715,AI Architect,243356,USD,243356,EX,FL,Norway,S,Norway,0,"NLP, Scala, R",Master,14,Transportation,2024-05-12,2024-06-12,1489,5.6,Cognitive Computing +AI10716,Principal Data Scientist,91224,USD,91224,MI,CT,Israel,L,Canada,50,"PyTorch, GCP, AWS",Bachelor,2,Manufacturing,2024-07-30,2024-10-10,1336,8.1,Neural Networks Co +AI10717,Data Engineer,42308,USD,42308,MI,FL,China,M,China,50,"Java, SQL, Docker",PhD,2,Gaming,2024-11-19,2025-01-08,764,7.9,AI Innovations +AI10718,AI Research Scientist,44344,USD,44344,MI,PT,China,L,China,100,"Scala, Mathematics, Deep Learning, Data Visualization, PyTorch",Associate,2,Transportation,2025-01-27,2025-03-06,1050,7.7,Quantum Computing Inc +AI10719,AI Consultant,176796,EUR,150277,EX,FT,France,M,France,50,"Python, Docker, Deep Learning, TensorFlow, NLP",Associate,12,Manufacturing,2024-02-26,2024-04-14,1400,9.1,Neural Networks Co +AI10720,Data Analyst,128958,JPY,14185380,SE,CT,Japan,L,Ireland,100,"Python, Git, Docker, Mathematics, Tableau",PhD,5,Retail,2024-06-05,2024-07-24,1906,5.9,Predictive Systems +AI10721,AI Research Scientist,38734,USD,38734,SE,CT,India,S,India,50,"Azure, MLOps, Statistics, Docker",PhD,9,Retail,2024-09-11,2024-09-25,698,9.4,AI Innovations +AI10722,Robotics Engineer,139670,GBP,104753,SE,CT,United Kingdom,M,Canada,0,"Python, Scala, MLOps, AWS",PhD,6,Media,2024-06-22,2024-07-07,1717,6.3,Algorithmic Solutions +AI10723,Principal Data Scientist,151422,EUR,128709,EX,CT,Germany,S,Germany,0,"PyTorch, TensorFlow, R, Linux, Mathematics",PhD,14,Automotive,2025-02-08,2025-03-20,590,7.3,Digital Transformation LLC +AI10724,Computer Vision Engineer,59521,EUR,50593,EN,CT,Netherlands,S,Netherlands,50,"Scala, R, NLP, MLOps",Bachelor,0,Real Estate,2024-09-08,2024-09-26,1095,7.3,DeepTech Ventures +AI10725,ML Ops Engineer,71064,USD,71064,MI,FT,South Korea,M,South Korea,50,"Java, Python, R, Mathematics, PyTorch",PhD,2,Consulting,2024-06-22,2024-08-18,1716,8.6,Future Systems +AI10726,Data Scientist,226728,EUR,192719,EX,CT,France,L,France,100,"Java, MLOps, TensorFlow, Computer Vision",Associate,16,Transportation,2024-06-02,2024-06-18,971,7.2,Cognitive Computing +AI10727,Machine Learning Researcher,112137,CAD,140171,MI,FL,Canada,L,Canada,50,"TensorFlow, Linux, Computer Vision, Git, Java",Associate,4,Retail,2025-04-21,2025-05-21,2367,7.8,AI Innovations +AI10728,Machine Learning Engineer,127819,CAD,159774,SE,CT,Canada,L,Germany,100,"Python, SQL, Scala, Computer Vision",PhD,5,Healthcare,2025-04-05,2025-05-31,2077,9.2,DataVision Ltd +AI10729,Data Analyst,96910,JPY,10660100,MI,FL,Japan,M,Japan,0,"SQL, AWS, GCP",Associate,2,Consulting,2024-02-23,2024-04-02,1569,7.9,Machine Intelligence Group +AI10730,Autonomous Systems Engineer,80604,USD,80604,EX,CT,India,L,Singapore,50,"Python, Mathematics, Tableau",Associate,11,Media,2024-04-19,2024-06-17,897,5.4,DataVision Ltd +AI10731,Head of AI,104712,USD,104712,SE,CT,Ireland,S,Argentina,0,"Kubernetes, Python, AWS, Deep Learning",PhD,9,Real Estate,2024-12-10,2024-12-31,643,6.7,Neural Networks Co +AI10732,Data Engineer,76848,CAD,96060,MI,FT,Canada,M,Canada,0,"Kubernetes, Tableau, Hadoop",Bachelor,4,Energy,2024-09-23,2024-11-14,1993,7.5,Cognitive Computing +AI10733,Deep Learning Engineer,155320,AUD,209682,EX,CT,Australia,M,Australia,0,"SQL, Scala, Computer Vision, Tableau, Linux",Master,14,Government,2025-01-05,2025-02-21,1624,6.7,DataVision Ltd +AI10734,AI Consultant,197617,GBP,148213,EX,PT,United Kingdom,S,United Kingdom,50,"AWS, PyTorch, Deep Learning",Associate,18,Finance,2024-11-11,2024-12-24,1858,7.2,Future Systems +AI10735,AI Research Scientist,49891,EUR,42407,EN,FT,Netherlands,S,Netherlands,0,"NLP, R, Computer Vision, Azure",Associate,0,Media,2024-03-30,2024-05-03,1695,9.3,DataVision Ltd +AI10736,Principal Data Scientist,117730,EUR,100071,SE,FL,Germany,L,Germany,0,"AWS, MLOps, Mathematics, Tableau",Master,5,Automotive,2024-12-21,2025-02-13,1009,5.6,Cognitive Computing +AI10737,AI Architect,115851,USD,115851,SE,PT,South Korea,M,South Korea,100,"Git, Python, Kubernetes, Statistics, Data Visualization",Associate,8,Media,2024-10-08,2024-11-09,990,7,Cloud AI Solutions +AI10738,Machine Learning Engineer,73670,CAD,92088,EN,CT,Canada,M,Egypt,100,"Linux, PyTorch, SQL, Java, Statistics",Associate,0,Government,2024-09-01,2024-10-17,1315,7.8,Predictive Systems +AI10739,AI Software Engineer,214568,CHF,193111,SE,FL,Switzerland,M,Switzerland,50,"AWS, Linux, Computer Vision",Master,7,Retail,2024-08-10,2024-09-15,937,6.8,Algorithmic Solutions +AI10740,AI Architect,258181,USD,258181,EX,CT,United States,L,Mexico,0,"MLOps, Spark, Data Visualization, GCP, Computer Vision",PhD,19,Retail,2024-05-24,2024-07-22,1825,7.1,AI Innovations +AI10741,Deep Learning Engineer,39478,USD,39478,EN,FL,South Korea,S,South Korea,50,"Git, Deep Learning, Spark, Java",Master,0,Automotive,2024-07-01,2024-08-10,922,7.9,DataVision Ltd +AI10742,Robotics Engineer,54274,USD,54274,MI,FT,China,L,China,0,"R, Java, AWS",Master,4,Manufacturing,2024-06-25,2024-07-15,723,7.2,Machine Intelligence Group +AI10743,Data Analyst,48788,USD,48788,SE,FT,China,S,China,0,"SQL, Deep Learning, Java, Computer Vision",Master,5,Healthcare,2025-01-09,2025-01-31,1444,7.1,Algorithmic Solutions +AI10744,NLP Engineer,232286,CHF,209057,SE,PT,Switzerland,L,Switzerland,50,"AWS, Python, GCP",Associate,8,Healthcare,2024-08-26,2024-09-19,637,9.9,Neural Networks Co +AI10745,AI Specialist,251960,USD,251960,EX,FT,United States,S,United States,100,"SQL, Scala, Python, MLOps, R",Master,13,Gaming,2024-04-11,2024-06-03,2323,6.1,Digital Transformation LLC +AI10746,Data Engineer,100923,CHF,90831,MI,FL,Switzerland,S,Malaysia,100,"Kubernetes, Scala, Azure, TensorFlow, SQL",Master,4,Healthcare,2024-07-01,2024-09-09,2073,5.9,Cognitive Computing +AI10747,Robotics Engineer,101479,AUD,136997,MI,CT,Australia,M,Australia,100,"Spark, Git, Computer Vision, AWS",PhD,4,Government,2025-04-16,2025-06-08,867,5.2,Quantum Computing Inc +AI10748,AI Software Engineer,238738,USD,238738,EX,FT,Israel,L,Israel,50,"Python, TensorFlow, Tableau",Associate,18,Retail,2024-09-22,2024-11-14,851,6.6,TechCorp Inc +AI10749,ML Ops Engineer,63999,EUR,54399,EN,CT,Netherlands,L,Kenya,100,"SQL, Python, Kubernetes, Data Visualization",Associate,0,Media,2024-11-25,2025-01-13,2084,7.3,Algorithmic Solutions +AI10750,Deep Learning Engineer,89374,USD,89374,MI,PT,Ireland,M,Ireland,0,"SQL, Spark, Scala, Python, Data Visualization",Master,4,Gaming,2025-04-20,2025-05-06,2047,9.6,AI Innovations +AI10751,NLP Engineer,71485,USD,71485,MI,FL,Sweden,S,France,50,"R, Scala, Data Visualization",Bachelor,4,Gaming,2024-08-21,2024-09-14,979,7.1,AI Innovations +AI10752,AI Software Engineer,173599,CAD,216999,EX,FL,Canada,M,Canada,50,"Deep Learning, SQL, PyTorch",PhD,13,Media,2025-04-16,2025-06-19,876,8.2,Cognitive Computing +AI10753,AI Product Manager,44067,USD,44067,EX,FT,India,S,India,50,"Statistics, NLP, Hadoop, Linux, Deep Learning",Bachelor,11,Consulting,2024-08-13,2024-09-30,778,9.1,Cloud AI Solutions +AI10754,AI Software Engineer,103357,EUR,87853,MI,FT,Netherlands,L,Netherlands,100,"AWS, Linux, Mathematics",PhD,3,Education,2024-08-11,2024-08-31,600,8.9,DataVision Ltd +AI10755,Data Scientist,95805,EUR,81434,MI,FL,Netherlands,M,Netherlands,50,"Linux, Hadoop, Deep Learning",PhD,2,Energy,2025-04-17,2025-06-13,2304,5,Machine Intelligence Group +AI10756,Data Scientist,286492,USD,286492,EX,FT,Norway,M,Norway,0,"R, NLP, Python, Docker",Bachelor,10,Energy,2024-06-02,2024-06-22,746,8.7,Machine Intelligence Group +AI10757,Head of AI,64481,EUR,54809,EN,FL,France,S,Italy,50,"Spark, Linux, Deep Learning, MLOps, PyTorch",Master,0,Energy,2024-03-15,2024-05-16,2443,8.7,Cloud AI Solutions +AI10758,Autonomous Systems Engineer,206801,USD,206801,EX,CT,Israel,M,Israel,100,"NLP, AWS, Scala, Azure, Python",Bachelor,18,Gaming,2024-04-28,2024-06-10,747,8.5,Autonomous Tech +AI10759,AI Specialist,161515,JPY,17766650,SE,FT,Japan,M,Canada,100,"Data Visualization, R, Scala, MLOps",Bachelor,5,Media,2024-03-20,2024-05-15,1508,9.6,Cognitive Computing +AI10760,Machine Learning Engineer,129002,USD,129002,EX,FL,Israel,S,Israel,100,"Statistics, R, Git",PhD,13,Retail,2024-09-03,2024-09-20,1993,7.1,AI Innovations +AI10761,Computer Vision Engineer,77898,CAD,97373,MI,FL,Canada,M,Canada,100,"Azure, Spark, Scala, Java, Git",Associate,2,Automotive,2024-06-21,2024-07-22,984,7.4,Quantum Computing Inc +AI10762,Data Engineer,117229,EUR,99645,SE,FL,Netherlands,S,Norway,100,"Spark, Mathematics, Linux",Master,9,Automotive,2025-04-13,2025-05-18,1881,8.1,Autonomous Tech +AI10763,Machine Learning Researcher,81371,EUR,69165,MI,FL,Netherlands,S,Netherlands,0,"SQL, R, Java, Kubernetes, Git",Associate,3,Manufacturing,2024-01-28,2024-03-02,1429,8.7,Algorithmic Solutions +AI10764,Data Engineer,72322,USD,72322,EN,PT,South Korea,L,South Korea,0,"MLOps, Azure, Python",Bachelor,1,Automotive,2024-09-06,2024-11-18,2024,7.9,Cloud AI Solutions +AI10765,ML Ops Engineer,94388,USD,94388,EX,FT,India,L,India,0,"Azure, SQL, Spark, Statistics, R",Master,12,Media,2024-06-24,2024-08-24,1661,7.3,Advanced Robotics +AI10766,ML Ops Engineer,202122,USD,202122,EX,CT,Denmark,M,Australia,50,"GCP, R, Git, TensorFlow",PhD,16,Energy,2024-09-23,2024-12-01,1479,9.8,Smart Analytics +AI10767,AI Software Engineer,86254,CAD,107818,MI,FL,Canada,L,Canada,50,"TensorFlow, NLP, Linux",PhD,4,Government,2025-04-06,2025-06-05,2494,9.7,Quantum Computing Inc +AI10768,Machine Learning Researcher,83507,SGD,108559,MI,CT,Singapore,S,Singapore,100,"Tableau, Computer Vision, GCP",Bachelor,2,Education,2024-08-19,2024-10-16,2354,6.4,Quantum Computing Inc +AI10769,Research Scientist,173027,EUR,147073,SE,CT,Germany,L,Brazil,100,"Tableau, Git, Hadoop, Spark, PyTorch",PhD,8,Education,2024-12-05,2024-12-21,690,5.5,Advanced Robotics +AI10770,Data Engineer,116393,EUR,98934,SE,FT,Germany,M,Germany,100,"MLOps, Scala, Azure, GCP, Kubernetes",Associate,8,Finance,2024-08-03,2024-09-12,2354,6.9,Cloud AI Solutions +AI10771,AI Software Engineer,99131,CHF,89218,MI,PT,Switzerland,S,Switzerland,100,"Kubernetes, Docker, Tableau, Hadoop, Java",Associate,3,Government,2024-05-07,2024-06-19,2068,6.1,Digital Transformation LLC +AI10772,Autonomous Systems Engineer,50959,USD,50959,EN,PT,Israel,M,Israel,100,"Hadoop, Kubernetes, SQL, Java, R",Bachelor,0,Consulting,2024-04-29,2024-06-16,2134,8.9,AI Innovations +AI10773,Data Analyst,107661,USD,107661,MI,CT,Denmark,S,Denmark,100,"Docker, Hadoop, Kubernetes, Python",Master,2,Finance,2025-01-03,2025-03-15,922,7.6,Cognitive Computing +AI10774,AI Specialist,174458,EUR,148289,EX,CT,Netherlands,M,Netherlands,100,"Python, Git, Kubernetes, Tableau",Bachelor,15,Media,2024-10-04,2024-11-05,1151,9,DataVision Ltd +AI10775,AI Specialist,126182,SGD,164037,SE,FT,Singapore,L,Singapore,0,"Linux, Python, Java, Git",PhD,7,Gaming,2024-03-23,2024-06-04,2236,9.7,Machine Intelligence Group +AI10776,Computer Vision Engineer,293038,CHF,263734,EX,CT,Switzerland,L,Switzerland,100,"Python, TensorFlow, R, Java, Computer Vision",PhD,13,Education,2024-05-12,2024-07-04,872,7.7,Future Systems +AI10777,AI Consultant,171137,EUR,145466,EX,CT,Austria,L,Austria,0,"Statistics, Linux, Scala",PhD,19,Gaming,2024-09-18,2024-10-26,1784,8.5,Smart Analytics +AI10778,AI Architect,106675,CHF,96008,MI,FT,Switzerland,S,Switzerland,0,"MLOps, Git, Deep Learning, Mathematics",PhD,3,Energy,2025-01-19,2025-03-01,1725,8.7,Quantum Computing Inc +AI10779,ML Ops Engineer,266812,USD,266812,EX,CT,Denmark,S,Denmark,100,"Python, NLP, Mathematics, TensorFlow",Bachelor,11,Retail,2024-09-23,2024-12-03,675,5.9,AI Innovations +AI10780,Data Scientist,85605,USD,85605,MI,FT,Finland,M,Estonia,100,"Kubernetes, Python, Computer Vision",Associate,3,Healthcare,2024-04-30,2024-06-10,2427,7.2,Smart Analytics +AI10781,NLP Engineer,201964,USD,201964,EX,CT,Israel,L,Czech Republic,0,"Scala, Python, Kubernetes, Computer Vision, SQL",Bachelor,13,Government,2024-01-29,2024-02-22,1295,7,Smart Analytics +AI10782,AI Specialist,137083,USD,137083,SE,FT,Israel,L,Israel,50,"AWS, Hadoop, Python, Scala, Spark",Bachelor,8,Gaming,2025-04-28,2025-05-18,1859,9,Neural Networks Co +AI10783,Data Analyst,75000,EUR,63750,EN,FL,Netherlands,S,Mexico,100,"R, Hadoop, Deep Learning, Java",Master,0,Finance,2024-02-24,2024-03-16,1353,7.8,AI Innovations +AI10784,Principal Data Scientist,200686,USD,200686,EX,CT,Sweden,L,Sweden,0,"Tableau, Python, NLP, TensorFlow, Scala",Associate,16,Telecommunications,2024-11-02,2024-12-31,1499,9.9,Predictive Systems +AI10785,Principal Data Scientist,129291,JPY,14222010,SE,FL,Japan,L,Japan,50,"R, Computer Vision, Azure, GCP",Associate,8,Transportation,2024-10-01,2024-10-19,1209,6.7,DeepTech Ventures +AI10786,Data Engineer,86101,EUR,73186,MI,PT,France,S,France,50,"SQL, Scala, Hadoop",PhD,4,Gaming,2024-02-20,2024-04-17,1586,5.3,Digital Transformation LLC +AI10787,AI Architect,61948,USD,61948,EN,PT,Sweden,L,Sweden,100,"SQL, PyTorch, Java, Azure",Associate,0,Education,2025-03-18,2025-05-18,1004,9.5,DeepTech Ventures +AI10788,Machine Learning Researcher,53377,USD,53377,MI,PT,China,L,China,0,"Python, Java, TensorFlow",Associate,2,Consulting,2025-01-16,2025-03-02,633,6.6,Digital Transformation LLC +AI10789,Robotics Engineer,125096,CHF,112586,MI,PT,Switzerland,S,Brazil,50,"Kubernetes, Git, Data Visualization, Python, Linux",Bachelor,3,Education,2025-01-05,2025-02-12,567,5.3,Future Systems +AI10790,AI Specialist,303813,CHF,273432,EX,FT,Switzerland,S,Switzerland,100,"SQL, Tableau, NLP, PyTorch, Mathematics",Associate,14,Government,2024-09-14,2024-09-28,1178,8.9,Quantum Computing Inc +AI10791,Machine Learning Researcher,52898,USD,52898,EN,CT,South Korea,M,South Korea,0,"Tableau, Kubernetes, Computer Vision",Bachelor,0,Healthcare,2024-11-19,2024-12-27,1927,6.2,DeepTech Ventures +AI10792,Data Scientist,91033,JPY,10013630,MI,PT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization",PhD,3,Energy,2024-07-25,2024-09-30,1290,6.4,Quantum Computing Inc +AI10793,AI Architect,87585,USD,87585,EN,FL,United States,L,United States,100,"Hadoop, NLP, Linux, GCP, SQL",Bachelor,0,Energy,2025-02-01,2025-04-12,2491,6.7,AI Innovations +AI10794,AI Architect,136182,GBP,102137,SE,FT,United Kingdom,S,United Kingdom,100,"Computer Vision, NLP, Tableau, GCP",Bachelor,9,Automotive,2024-10-18,2024-11-20,1243,5.5,Quantum Computing Inc +AI10795,Data Engineer,132993,EUR,113044,SE,FT,Germany,M,Nigeria,100,"Python, TensorFlow, PyTorch, Spark, Kubernetes",Bachelor,7,Retail,2024-10-21,2024-11-06,2207,5.7,Digital Transformation LLC +AI10796,Autonomous Systems Engineer,165196,EUR,140417,EX,FT,Austria,S,Austria,100,"Python, TensorFlow, Kubernetes, Spark, AWS",Master,13,Education,2024-01-18,2024-02-19,551,9.2,Neural Networks Co +AI10797,AI Research Scientist,171750,GBP,128813,SE,CT,United Kingdom,L,United Kingdom,0,"Spark, NLP, Kubernetes, Data Visualization, Computer Vision",Master,5,Real Estate,2024-02-01,2024-04-04,1748,6.4,Smart Analytics +AI10798,AI Research Scientist,117335,EUR,99735,SE,FT,France,M,France,100,"Linux, GCP, Spark, MLOps",Associate,7,Real Estate,2024-05-23,2024-06-19,1923,8,Neural Networks Co +AI10799,Data Scientist,137278,GBP,102959,SE,PT,United Kingdom,S,United Kingdom,0,"R, SQL, Java, Kubernetes",Bachelor,9,Gaming,2025-01-19,2025-03-29,1473,6.4,Quantum Computing Inc +AI10800,Machine Learning Engineer,147147,USD,147147,EX,CT,Sweden,M,Sweden,100,"TensorFlow, Hadoop, Tableau, Docker, GCP",Master,14,Consulting,2024-08-29,2024-10-19,1580,7.2,Machine Intelligence Group +AI10801,Data Engineer,71205,EUR,60524,MI,FT,Austria,M,China,100,"NLP, SQL, PyTorch",Master,3,Retail,2024-07-10,2024-09-12,1566,8,Smart Analytics +AI10802,Machine Learning Researcher,134161,CAD,167701,SE,PT,Canada,M,Canada,0,"Linux, Hadoop, Kubernetes, Python",Master,6,Automotive,2024-12-15,2025-01-31,2485,5.4,Algorithmic Solutions +AI10803,Autonomous Systems Engineer,82237,USD,82237,MI,PT,Sweden,S,Australia,50,"Python, TensorFlow, Statistics",PhD,4,Retail,2024-10-19,2024-11-27,1074,5.8,Predictive Systems +AI10804,Autonomous Systems Engineer,38622,USD,38622,MI,FT,India,M,India,100,"Git, Linux, AWS, TensorFlow",Associate,3,Technology,2024-05-02,2024-05-22,2055,6.7,Cloud AI Solutions +AI10805,Robotics Engineer,55769,USD,55769,EN,FL,Sweden,M,India,100,"Scala, NLP, Computer Vision",Master,1,Retail,2024-12-22,2025-02-05,2420,7.4,TechCorp Inc +AI10806,ML Ops Engineer,67249,CHF,60524,EN,FL,Switzerland,S,Switzerland,100,"Scala, Java, Deep Learning",Associate,0,Automotive,2024-02-29,2024-04-04,523,7.5,Cloud AI Solutions +AI10807,AI Specialist,42394,USD,42394,MI,CT,China,M,China,0,"MLOps, Kubernetes, Git",Associate,3,Consulting,2024-08-17,2024-09-15,2406,7.8,AI Innovations +AI10808,AI Product Manager,22136,USD,22136,EN,FL,China,S,China,100,"SQL, Mathematics, Tableau, MLOps",Bachelor,1,Consulting,2024-11-10,2025-01-08,1809,8.3,Machine Intelligence Group +AI10809,Computer Vision Engineer,134580,SGD,174954,SE,CT,Singapore,S,Turkey,0,"MLOps, Computer Vision, Python, TensorFlow, Git",Associate,7,Retail,2024-12-27,2025-03-06,1655,6.9,Machine Intelligence Group +AI10810,AI Architect,65961,CAD,82451,EN,CT,Canada,M,Canada,0,"GCP, Spark, Scala, Kubernetes",PhD,1,Education,2024-12-29,2025-03-01,1771,6.4,Neural Networks Co +AI10811,AI Product Manager,117629,USD,117629,MI,CT,Norway,M,Norway,0,"Python, Deep Learning, Computer Vision, R",Associate,4,Transportation,2024-02-08,2024-02-22,795,8.7,Future Systems +AI10812,Machine Learning Researcher,87716,EUR,74559,MI,FT,Germany,S,Finland,50,"Linux, Mathematics, GCP",PhD,3,Energy,2025-01-27,2025-03-06,986,9.1,DeepTech Ventures +AI10813,AI Research Scientist,18861,USD,18861,EN,CT,India,M,India,50,"R, Linux, SQL",Bachelor,0,Manufacturing,2025-04-07,2025-06-04,1425,7.6,Autonomous Tech +AI10814,Robotics Engineer,122512,USD,122512,MI,FT,Norway,M,Norway,0,"PyTorch, R, Linux, Hadoop",Bachelor,2,Consulting,2024-10-09,2024-10-26,2292,6.8,Autonomous Tech +AI10815,Deep Learning Engineer,180159,CAD,225199,EX,FT,Canada,L,Canada,50,"Statistics, Azure, Python, Tableau, Scala",PhD,16,Manufacturing,2024-12-09,2025-01-12,2370,5.4,Neural Networks Co +AI10816,AI Architect,168620,EUR,143327,EX,CT,Austria,L,Austria,100,"Git, PyTorch, NLP, GCP",PhD,15,Real Estate,2025-03-21,2025-05-17,658,6.1,Cloud AI Solutions +AI10817,NLP Engineer,72274,USD,72274,SE,FT,China,L,China,0,"Mathematics, Computer Vision, Statistics, SQL, Spark",PhD,5,Telecommunications,2025-04-12,2025-05-03,1316,6.9,Future Systems +AI10818,Autonomous Systems Engineer,67126,USD,67126,EN,CT,Israel,L,Israel,100,"Mathematics, Kubernetes, Azure, Java",Associate,1,Manufacturing,2024-10-13,2024-12-03,2387,6.5,Advanced Robotics +AI10819,NLP Engineer,94449,EUR,80282,MI,PT,France,L,France,50,"Azure, Scala, Linux",PhD,4,Gaming,2024-06-15,2024-08-26,2175,7.3,Autonomous Tech +AI10820,Machine Learning Engineer,112859,EUR,95930,SE,PT,France,L,France,50,"NLP, SQL, PyTorch, Data Visualization",Master,5,Energy,2024-06-22,2024-08-28,2162,8.8,Advanced Robotics +AI10821,Data Engineer,144547,SGD,187911,SE,FT,Singapore,M,Switzerland,0,"NLP, SQL, PyTorch, AWS",PhD,6,Manufacturing,2024-07-15,2024-09-15,1374,7.1,Digital Transformation LLC +AI10822,Machine Learning Researcher,80627,EUR,68533,MI,FL,Austria,M,Austria,100,"Scala, Python, Docker, Kubernetes, TensorFlow",PhD,3,Education,2024-07-23,2024-08-25,2061,6.9,DataVision Ltd +AI10823,Deep Learning Engineer,151439,EUR,128723,EX,FT,Austria,L,Austria,50,"TensorFlow, Azure, Java, Docker, Git",PhD,11,Education,2024-09-13,2024-11-11,782,9.8,Machine Intelligence Group +AI10824,ML Ops Engineer,43069,USD,43069,MI,FT,China,M,China,50,"PyTorch, Spark, SQL, GCP, AWS",Bachelor,4,Technology,2024-01-03,2024-02-16,2356,6.4,Cognitive Computing +AI10825,AI Specialist,137861,USD,137861,EX,CT,Finland,M,China,0,"NLP, Scala, SQL, PyTorch",PhD,14,Government,2024-11-04,2025-01-13,703,9,Quantum Computing Inc +AI10826,AI Product Manager,192829,USD,192829,EX,CT,Denmark,S,Denmark,0,"Java, Mathematics, Git",Bachelor,10,Real Estate,2024-08-11,2024-09-17,971,7.4,AI Innovations +AI10827,AI Specialist,108163,EUR,91939,SE,FT,Austria,M,Austria,0,"Computer Vision, Linux, PyTorch, SQL, TensorFlow",Associate,7,Gaming,2024-09-16,2024-10-10,1127,7.5,Cognitive Computing +AI10828,ML Ops Engineer,65216,EUR,55434,MI,PT,Austria,S,Colombia,50,"SQL, Linux, Azure, NLP, Git",Master,3,Education,2024-01-08,2024-02-14,2280,9.4,Future Systems +AI10829,Machine Learning Researcher,80149,CAD,100186,MI,PT,Canada,M,Canada,0,"Python, Data Visualization, Docker, Hadoop",PhD,4,Retail,2025-03-26,2025-06-05,1233,5.3,TechCorp Inc +AI10830,ML Ops Engineer,205835,SGD,267586,EX,FT,Singapore,S,Singapore,50,"TensorFlow, Git, Hadoop",Master,12,Technology,2025-04-23,2025-06-15,2294,9.8,Autonomous Tech +AI10831,Head of AI,105584,USD,105584,EN,FT,Norway,L,Norway,100,"Git, Computer Vision, Python",Bachelor,0,Finance,2024-10-21,2024-12-10,2375,8.7,Neural Networks Co +AI10832,Data Scientist,134679,USD,134679,SE,FT,South Korea,L,South Korea,100,"Spark, Data Visualization, Deep Learning, NLP, Scala",PhD,7,Transportation,2025-04-12,2025-05-02,1266,6.8,Future Systems +AI10833,Data Analyst,63653,GBP,47740,EN,FT,United Kingdom,M,China,50,"Scala, Deep Learning, NLP, PyTorch",PhD,0,Government,2024-10-06,2024-11-21,1421,7.2,Digital Transformation LLC +AI10834,AI Architect,116733,EUR,99223,MI,FT,Germany,L,Germany,100,"Hadoop, SQL, Python",Associate,3,Real Estate,2025-04-13,2025-06-15,1457,5.1,Digital Transformation LLC +AI10835,Computer Vision Engineer,171496,USD,171496,EX,FL,Norway,S,Norway,50,"Mathematics, TensorFlow, Statistics, Linux, GCP",Master,18,Finance,2024-04-22,2024-06-09,897,9.1,Quantum Computing Inc +AI10836,Machine Learning Engineer,179259,SGD,233037,EX,FT,Singapore,L,Singapore,0,"PyTorch, Java, R, Statistics, Linux",Associate,16,Technology,2024-03-23,2024-05-04,1256,7.5,Cognitive Computing +AI10837,Data Scientist,222335,USD,222335,SE,FL,Denmark,L,Denmark,0,"PyTorch, AWS, NLP, Linux",Bachelor,8,Telecommunications,2024-11-25,2024-12-14,2295,6.2,Predictive Systems +AI10838,Head of AI,182726,USD,182726,EX,CT,Norway,M,Norway,0,"TensorFlow, Hadoop, PyTorch, Data Visualization, Spark",Bachelor,17,Telecommunications,2024-06-04,2024-07-28,2321,9.9,DeepTech Ventures +AI10839,Data Scientist,59545,USD,59545,SE,CT,China,L,China,100,"R, NLP, Kubernetes, Python, Docker",PhD,5,Education,2024-12-10,2025-01-26,1221,8.6,Algorithmic Solutions +AI10840,Autonomous Systems Engineer,159516,USD,159516,MI,CT,Norway,L,Philippines,0,"Hadoop, Kubernetes, Docker",Associate,3,Gaming,2024-03-30,2024-05-29,1823,7,Machine Intelligence Group +AI10841,Robotics Engineer,61743,USD,61743,EN,CT,Ireland,S,Ireland,0,"NLP, Azure, Spark, Deep Learning, GCP",PhD,1,Education,2024-10-04,2024-12-10,1963,6.5,Quantum Computing Inc +AI10842,Head of AI,68105,USD,68105,MI,FT,Finland,M,Ireland,50,"Python, Docker, Azure",Master,2,Retail,2025-01-08,2025-03-17,1930,6.6,Digital Transformation LLC +AI10843,Data Scientist,199352,EUR,169449,EX,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure, PyTorch",Associate,11,Real Estate,2024-06-17,2024-07-25,621,5.7,Algorithmic Solutions +AI10844,AI Specialist,177487,USD,177487,EX,CT,Denmark,M,Denmark,0,"Scala, Kubernetes, R",Bachelor,10,Manufacturing,2025-04-03,2025-06-14,878,8.6,Digital Transformation LLC +AI10845,Robotics Engineer,62199,EUR,52869,EN,CT,Germany,S,Russia,50,"Data Visualization, Python, Deep Learning, Computer Vision",Bachelor,0,Retail,2025-02-26,2025-05-02,1586,5.9,DataVision Ltd +AI10846,Head of AI,89631,USD,89631,EN,FL,Ireland,L,Ireland,0,"Git, R, Tableau, PyTorch",Associate,1,Education,2025-02-13,2025-04-16,1377,6.1,DataVision Ltd +AI10847,Data Engineer,73376,CAD,91720,MI,PT,Canada,S,Canada,100,"R, PyTorch, NLP",Associate,4,Media,2024-03-22,2024-05-16,1147,5.2,DeepTech Ventures +AI10848,Research Scientist,94533,USD,94533,MI,FT,Denmark,S,Denmark,50,"Linux, Scala, TensorFlow, Data Visualization, Python",Master,2,Finance,2024-01-12,2024-02-16,1115,8.8,Predictive Systems +AI10849,AI Software Engineer,193687,EUR,164634,EX,PT,Austria,M,Austria,100,"AWS, Scala, R, Tableau",Master,18,Retail,2024-04-19,2024-06-20,901,9.5,Smart Analytics +AI10850,Robotics Engineer,53931,USD,53931,SE,FL,India,L,Kenya,0,"MLOps, Python, Data Visualization, Azure",Associate,9,Retail,2024-12-30,2025-01-21,2014,8.9,TechCorp Inc +AI10851,Machine Learning Engineer,116512,USD,116512,EX,PT,China,M,China,100,"TensorFlow, SQL, MLOps, Deep Learning",PhD,19,Healthcare,2025-03-17,2025-04-24,1614,7.3,Predictive Systems +AI10852,ML Ops Engineer,99823,USD,99823,MI,PT,Denmark,S,Denmark,0,"Git, MLOps, SQL",Associate,2,Telecommunications,2024-03-29,2024-05-25,593,6.8,Future Systems +AI10853,AI Research Scientist,87180,CAD,108975,EN,FL,Canada,L,Canada,100,"GCP, Tableau, Data Visualization, PyTorch",Master,0,Real Estate,2024-04-18,2024-05-08,1341,8.3,Smart Analytics +AI10854,Data Analyst,47973,USD,47973,MI,FL,China,M,China,50,"Hadoop, PyTorch, GCP, Computer Vision",PhD,2,Telecommunications,2024-06-11,2024-08-06,776,8,Quantum Computing Inc +AI10855,Head of AI,313259,USD,313259,EX,FT,Denmark,M,Romania,100,"Python, R, Spark, Linux",Associate,10,Finance,2024-09-23,2024-11-28,2488,6.8,Predictive Systems +AI10856,AI Specialist,199489,USD,199489,SE,FT,Denmark,L,Denmark,50,"SQL, MLOps, Python, Data Visualization, Azure",Associate,8,Government,2024-02-16,2024-03-21,2398,5.9,DeepTech Ventures +AI10857,Autonomous Systems Engineer,32228,USD,32228,EN,CT,China,S,China,50,"Statistics, GCP, SQL, Python, Azure",PhD,1,Gaming,2024-02-17,2024-03-18,1063,6.4,Cloud AI Solutions +AI10858,Principal Data Scientist,113385,USD,113385,MI,PT,Denmark,M,Egypt,50,"GCP, Kubernetes, Tableau",Associate,2,Technology,2024-09-21,2024-11-22,1831,9.4,DataVision Ltd +AI10859,AI Specialist,252641,USD,252641,EX,FT,Ireland,L,Ireland,100,"Tableau, Scala, NLP, Python, Java",Master,17,Transportation,2024-08-30,2024-10-14,2301,7.9,TechCorp Inc +AI10860,Data Engineer,90555,USD,90555,MI,FT,Denmark,S,Denmark,50,"PyTorch, TensorFlow, Linux",Bachelor,4,Finance,2024-03-05,2024-04-18,1969,8.3,Algorithmic Solutions +AI10861,Research Scientist,77655,USD,77655,EN,FT,Norway,M,Norway,50,"Deep Learning, Linux, GCP, Python",Master,1,Manufacturing,2024-03-17,2024-04-15,2224,8.3,Neural Networks Co +AI10862,Data Engineer,141801,USD,141801,MI,FL,Norway,L,Thailand,0,"Spark, Git, Data Visualization, Azure",Bachelor,2,Consulting,2024-06-09,2024-08-15,937,5.9,Future Systems +AI10863,NLP Engineer,163767,USD,163767,SE,FT,Denmark,S,Denmark,100,"SQL, Hadoop, AWS",Bachelor,9,Healthcare,2024-06-13,2024-07-29,1267,6.5,TechCorp Inc +AI10864,Principal Data Scientist,59859,USD,59859,EN,FL,South Korea,L,South Korea,0,"Docker, SQL, Deep Learning, NLP",Associate,1,Healthcare,2025-02-19,2025-03-18,2208,6.4,Quantum Computing Inc +AI10865,Principal Data Scientist,90290,USD,90290,MI,PT,Israel,L,Israel,0,"Python, NLP, Kubernetes, Docker",PhD,3,Media,2024-07-02,2024-09-08,886,6.5,Cognitive Computing +AI10866,Research Scientist,114206,EUR,97075,SE,FT,France,L,France,100,"Python, Docker, Computer Vision, SQL, Kubernetes",PhD,6,Gaming,2025-01-07,2025-03-20,1772,9.1,Smart Analytics +AI10867,Head of AI,99967,USD,99967,SE,PT,Sweden,S,Sweden,50,"R, Java, AWS",Associate,6,Media,2024-12-31,2025-03-06,516,8.1,Neural Networks Co +AI10868,ML Ops Engineer,208430,USD,208430,EX,CT,Sweden,M,Sweden,100,"Azure, Data Visualization, Tableau, Git",PhD,16,Manufacturing,2025-02-18,2025-03-09,883,8.8,Neural Networks Co +AI10869,ML Ops Engineer,88936,GBP,66702,MI,CT,United Kingdom,S,United Kingdom,0,"NLP, Deep Learning, Spark, Git",Master,2,Manufacturing,2024-01-21,2024-04-02,882,7.3,Predictive Systems +AI10870,AI Specialist,172753,USD,172753,SE,CT,Norway,S,Norway,100,"Python, R, GCP, Scala, TensorFlow",Bachelor,6,Gaming,2024-06-04,2024-06-30,892,7.1,Autonomous Tech +AI10871,Robotics Engineer,172661,USD,172661,EX,CT,Finland,L,Finland,50,"SQL, Kubernetes, MLOps, Deep Learning",PhD,10,Telecommunications,2025-02-17,2025-03-03,795,9.9,TechCorp Inc +AI10872,Robotics Engineer,61484,EUR,52261,EN,FL,France,L,France,50,"Docker, SQL, AWS",Bachelor,1,Healthcare,2024-02-23,2024-04-08,2272,6.2,TechCorp Inc +AI10873,Robotics Engineer,71875,EUR,61094,EN,FT,Germany,S,Ukraine,0,"Mathematics, Tableau, Hadoop, Java",PhD,0,Telecommunications,2024-05-18,2024-06-13,1647,6.7,Cloud AI Solutions +AI10874,Data Engineer,79797,USD,79797,MI,FL,Sweden,S,Sweden,50,"Kubernetes, Python, TensorFlow, AWS, NLP",Bachelor,3,Telecommunications,2025-03-21,2025-05-08,527,9.2,Advanced Robotics +AI10875,AI Consultant,91965,USD,91965,EX,FT,India,L,India,50,"Computer Vision, Docker, Python, GCP, Linux",Bachelor,15,Manufacturing,2024-10-03,2024-11-10,1418,7.3,Smart Analytics +AI10876,Robotics Engineer,128584,EUR,109296,SE,FL,Austria,S,Austria,100,"Git, Data Visualization, SQL, Computer Vision",Master,5,Energy,2024-04-07,2024-06-11,2097,6.6,Machine Intelligence Group +AI10877,AI Product Manager,92990,USD,92990,EN,CT,United States,M,United States,100,"Kubernetes, R, GCP, Statistics",Master,0,Telecommunications,2024-12-07,2025-02-18,2231,9.9,DeepTech Ventures +AI10878,AI Architect,85862,USD,85862,EN,FT,Norway,M,Norway,0,"Hadoop, Docker, AWS, Data Visualization",PhD,1,Manufacturing,2024-05-19,2024-07-01,1306,8.6,Cloud AI Solutions +AI10879,AI Product Manager,96557,CAD,120696,MI,CT,Canada,M,Portugal,100,"Git, NLP, Tableau, Data Visualization",Bachelor,3,Telecommunications,2024-01-13,2024-03-13,1805,6.4,Digital Transformation LLC +AI10880,AI Research Scientist,136056,USD,136056,SE,CT,Sweden,S,Austria,50,"AWS, Computer Vision, Mathematics, R",Associate,8,Retail,2024-04-08,2024-05-16,884,9.7,Digital Transformation LLC +AI10881,Principal Data Scientist,191877,EUR,163095,EX,FT,Austria,L,Austria,0,"Spark, GCP, Deep Learning, Scala",Bachelor,15,Transportation,2024-07-08,2024-07-29,2481,7.8,DeepTech Ventures +AI10882,Deep Learning Engineer,58995,USD,58995,EN,CT,Sweden,L,Portugal,0,"Linux, Spark, R",Associate,1,Telecommunications,2025-03-01,2025-03-26,1543,9.8,Smart Analytics +AI10883,Robotics Engineer,171771,USD,171771,SE,FL,Denmark,L,Denmark,50,"AWS, Computer Vision, SQL, Spark",Master,7,Finance,2024-09-14,2024-10-08,1457,9.4,Cognitive Computing +AI10884,AI Software Engineer,124350,USD,124350,SE,PT,United States,M,Netherlands,100,"SQL, Deep Learning, NLP",Master,7,Media,2024-04-04,2024-05-14,1461,9,Autonomous Tech +AI10885,Autonomous Systems Engineer,264027,USD,264027,EX,FT,United States,S,Indonesia,50,"Scala, R, Data Visualization, Python, TensorFlow",Associate,13,Transportation,2024-08-31,2024-09-20,1916,6.7,Future Systems +AI10886,Machine Learning Engineer,254261,EUR,216122,EX,PT,Austria,L,Belgium,50,"Git, TensorFlow, Mathematics",Associate,18,Manufacturing,2024-03-12,2024-05-19,965,5.7,Algorithmic Solutions +AI10887,Head of AI,95509,GBP,71632,MI,FL,United Kingdom,L,United Kingdom,0,"Hadoop, GCP, Data Visualization, Statistics, MLOps",Master,4,Real Estate,2024-11-03,2024-11-24,1264,7.5,DataVision Ltd +AI10888,ML Ops Engineer,144757,CAD,180946,SE,FT,Canada,L,Canada,100,"Hadoop, TensorFlow, NLP",PhD,9,Government,2024-07-08,2024-08-09,1528,5.7,Quantum Computing Inc +AI10889,AI Specialist,80856,USD,80856,EN,FL,Norway,S,Norway,50,"NLP, Scala, Java",Bachelor,0,Energy,2024-11-29,2025-01-14,2142,8.8,DeepTech Ventures +AI10890,Data Engineer,170023,SGD,221030,EX,CT,Singapore,S,Singapore,50,"Mathematics, NLP, Git, Computer Vision, Deep Learning",Bachelor,14,Technology,2024-03-18,2024-05-29,1846,9.5,DataVision Ltd +AI10891,Data Scientist,67573,USD,67573,MI,PT,Israel,S,Kenya,100,"Python, SQL, Java, MLOps",Master,2,Transportation,2024-01-08,2024-03-12,1770,8.9,Cognitive Computing +AI10892,Deep Learning Engineer,43295,USD,43295,MI,FL,India,L,India,0,"Kubernetes, Azure, SQL, Computer Vision",Master,4,Finance,2024-07-25,2024-09-01,1342,7.4,DataVision Ltd +AI10893,Principal Data Scientist,138506,CAD,173133,SE,CT,Canada,L,Canada,0,"Java, Git, Tableau, Kubernetes, R",Bachelor,5,Consulting,2024-08-01,2024-09-17,971,9.6,Cognitive Computing +AI10894,AI Specialist,83927,SGD,109105,EN,FL,Singapore,L,Mexico,0,"Tableau, Kubernetes, Linux",PhD,0,Manufacturing,2024-08-25,2024-11-01,2240,9.8,Cloud AI Solutions +AI10895,AI Product Manager,77484,GBP,58113,EN,FT,United Kingdom,M,United Kingdom,50,"Spark, GCP, Scala, Docker, Hadoop",Bachelor,1,Retail,2025-04-29,2025-05-22,1818,8.7,DeepTech Ventures +AI10896,Deep Learning Engineer,149388,USD,149388,SE,FL,Ireland,M,Ireland,100,"Tableau, Azure, PyTorch, NLP, SQL",PhD,6,Government,2024-06-07,2024-07-30,855,9.9,Autonomous Tech +AI10897,AI Specialist,220434,EUR,187369,EX,PT,Netherlands,S,Netherlands,50,"Kubernetes, Git, Data Visualization, Python",PhD,14,Retail,2024-04-25,2024-05-14,1114,8.6,DataVision Ltd +AI10898,Head of AI,79212,GBP,59409,EN,FL,United Kingdom,M,Romania,100,"AWS, Data Visualization, Git",Associate,1,Finance,2025-03-13,2025-05-04,1636,5.9,Algorithmic Solutions +AI10899,Machine Learning Researcher,169031,EUR,143676,SE,FL,Germany,L,Germany,50,"Linux, Python, NLP, Java",Bachelor,7,Automotive,2024-10-07,2024-11-23,2421,9.2,Advanced Robotics +AI10900,AI Product Manager,165582,USD,165582,SE,CT,Norway,L,Norway,50,"Scala, Data Visualization, Python",PhD,8,Education,2024-02-12,2024-03-04,1890,6.5,Digital Transformation LLC +AI10901,NLP Engineer,323522,CHF,291170,EX,FL,Switzerland,L,Switzerland,100,"Docker, MLOps, Kubernetes, GCP",Bachelor,18,Energy,2025-04-27,2025-05-15,1564,10,Cognitive Computing +AI10902,ML Ops Engineer,89783,USD,89783,EN,FL,United States,L,United States,100,"Azure, MLOps, Statistics",Master,1,Gaming,2024-07-29,2024-10-08,1060,6.7,Advanced Robotics +AI10903,Head of AI,172737,USD,172737,EX,PT,Denmark,S,Denmark,50,"AWS, Linux, Mathematics, Data Visualization, NLP",Master,13,Telecommunications,2025-01-29,2025-03-10,1381,8.9,Algorithmic Solutions +AI10904,Data Scientist,118389,USD,118389,SE,FT,Ireland,M,Ireland,50,"GCP, Linux, SQL, Kubernetes",Associate,5,Consulting,2025-03-18,2025-05-12,1971,6.7,Algorithmic Solutions +AI10905,AI Research Scientist,77597,GBP,58198,EN,FL,United Kingdom,M,United Kingdom,100,"Java, Deep Learning, R, Docker",Associate,0,Gaming,2024-08-11,2024-09-03,2061,9.5,Advanced Robotics +AI10906,Data Scientist,139624,SGD,181511,SE,PT,Singapore,S,Singapore,50,"Python, TensorFlow, Statistics",Associate,7,Media,2024-10-02,2024-11-07,1774,9.6,Smart Analytics +AI10907,Data Scientist,118666,SGD,154266,SE,PT,Singapore,M,Singapore,100,"Linux, Scala, Data Visualization, Kubernetes",Master,5,Media,2025-01-14,2025-01-28,964,5.3,Autonomous Tech +AI10908,Data Scientist,74287,EUR,63144,EN,CT,Netherlands,S,Russia,100,"SQL, Kubernetes, Data Visualization, Deep Learning",PhD,1,Education,2024-04-04,2024-05-24,1947,7.1,DataVision Ltd +AI10909,AI Product Manager,208649,GBP,156487,EX,CT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Java",Associate,13,Finance,2024-12-13,2025-01-16,1064,8.1,Machine Intelligence Group +AI10910,Data Analyst,123996,EUR,105397,SE,FL,France,L,United Kingdom,0,"Kubernetes, Scala, Spark, PyTorch, Java",Bachelor,8,Healthcare,2024-04-07,2024-05-19,1805,8,Quantum Computing Inc +AI10911,Data Analyst,229871,EUR,195390,EX,PT,Germany,L,Germany,50,"PyTorch, Deep Learning, Computer Vision",PhD,15,Healthcare,2025-03-02,2025-04-05,2477,9.5,Cloud AI Solutions +AI10912,Machine Learning Engineer,92771,SGD,120602,MI,FL,Singapore,S,Singapore,50,"Docker, SQL, Azure, TensorFlow",Associate,2,Automotive,2024-08-02,2024-10-14,910,7.1,Autonomous Tech +AI10913,Data Scientist,31230,USD,31230,EN,FL,China,M,Vietnam,100,"Azure, Python, Data Visualization, R, Statistics",Bachelor,1,Consulting,2025-03-26,2025-05-15,1660,8.5,TechCorp Inc +AI10914,AI Specialist,120411,USD,120411,SE,CT,Israel,S,Turkey,50,"Python, AWS, Linux, Git",Associate,7,Energy,2025-02-02,2025-03-25,2299,6.3,Autonomous Tech +AI10915,Computer Vision Engineer,219663,EUR,186714,EX,FT,Germany,S,Germany,100,"Python, R, TensorFlow, Docker",Bachelor,16,Automotive,2024-01-05,2024-02-25,1906,7.1,DeepTech Ventures +AI10916,Research Scientist,62748,EUR,53336,MI,FT,Austria,S,Austria,50,"Tableau, Mathematics, Python, SQL, AWS",Master,3,Real Estate,2024-07-16,2024-08-12,1479,5.8,TechCorp Inc +AI10917,AI Software Engineer,60299,GBP,45224,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Data Visualization, PyTorch",Master,1,Education,2024-12-06,2025-02-05,1779,7.8,Smart Analytics +AI10918,Head of AI,266091,EUR,226177,EX,PT,Netherlands,M,Netherlands,50,"NLP, Kubernetes, Scala, Statistics, TensorFlow",Associate,13,Media,2025-04-02,2025-04-27,990,5.7,Algorithmic Solutions +AI10919,AI Specialist,252940,AUD,341469,EX,FT,Australia,L,Austria,0,"SQL, GCP, Python, Hadoop",PhD,16,Healthcare,2025-03-07,2025-04-07,2229,8.7,Algorithmic Solutions +AI10920,Principal Data Scientist,100217,JPY,11023870,MI,FT,Japan,L,New Zealand,50,"Scala, SQL, Git, Deep Learning",Associate,3,Gaming,2025-04-25,2025-06-30,1851,6.8,Neural Networks Co +AI10921,Deep Learning Engineer,197325,USD,197325,EX,FL,United States,S,United States,100,"Scala, Java, R",PhD,14,Manufacturing,2024-03-26,2024-06-06,1769,5,Cognitive Computing +AI10922,Head of AI,23752,USD,23752,EN,FT,India,M,India,0,"SQL, Linux, MLOps, GCP",Master,0,Technology,2024-10-22,2024-12-11,1459,6.8,Machine Intelligence Group +AI10923,Machine Learning Researcher,61586,GBP,46190,EN,FL,United Kingdom,S,United Kingdom,50,"Kubernetes, Tableau, Python, Docker, Java",Associate,0,Telecommunications,2024-10-21,2024-11-22,970,9.3,TechCorp Inc +AI10924,AI Software Engineer,32487,USD,32487,MI,FL,India,S,Latvia,100,"SQL, Git, R",Associate,2,Energy,2024-07-23,2024-09-21,2404,7,DataVision Ltd +AI10925,Deep Learning Engineer,71388,USD,71388,EN,FT,Ireland,S,Ireland,100,"SQL, Scala, Statistics, NLP",Associate,1,Transportation,2024-03-15,2024-04-02,2180,8,DataVision Ltd +AI10926,NLP Engineer,218351,CHF,196516,SE,FL,Switzerland,L,Switzerland,50,"SQL, Hadoop, Deep Learning",Bachelor,8,Government,2024-08-26,2024-09-23,1062,9.4,DataVision Ltd +AI10927,AI Specialist,166329,GBP,124747,EX,PT,United Kingdom,L,United Kingdom,100,"Statistics, Git, PyTorch",Master,14,Retail,2024-05-06,2024-06-02,1104,9.6,AI Innovations +AI10928,AI Software Engineer,75044,GBP,56283,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Java, MLOps, Scala",Master,0,Gaming,2024-12-01,2024-12-15,933,8.6,Cloud AI Solutions +AI10929,AI Consultant,206933,SGD,269013,EX,CT,Singapore,L,Switzerland,0,"Docker, Python, GCP",Bachelor,19,Real Estate,2025-03-11,2025-04-07,1194,7.7,Smart Analytics +AI10930,Machine Learning Engineer,195026,EUR,165772,EX,CT,Germany,M,Germany,100,"SQL, Spark, AWS",Master,10,Media,2025-03-18,2025-05-15,1217,7.7,Machine Intelligence Group +AI10931,Head of AI,104858,USD,104858,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, AWS, PyTorch",PhD,8,Transportation,2024-07-30,2024-09-27,1048,7.3,Future Systems +AI10932,Autonomous Systems Engineer,118890,USD,118890,SE,CT,Israel,S,Israel,0,"Scala, MLOps, Tableau, Kubernetes, Mathematics",Bachelor,6,Retail,2024-08-31,2024-10-02,1165,8.9,Quantum Computing Inc +AI10933,Deep Learning Engineer,87321,EUR,74223,MI,CT,Germany,L,Germany,50,"Git, Computer Vision, Java",PhD,3,Healthcare,2024-01-11,2024-03-01,2443,10,Smart Analytics +AI10934,AI Product Manager,104724,USD,104724,SE,CT,Ireland,S,Ireland,100,"Linux, Data Visualization, Tableau, MLOps, Kubernetes",PhD,9,Gaming,2024-06-02,2024-06-24,1259,8.3,Cloud AI Solutions +AI10935,AI Research Scientist,65970,EUR,56075,MI,FL,Austria,S,Austria,50,"PyTorch, Python, Linux, Scala",PhD,3,Energy,2024-07-01,2024-09-10,2200,5.2,AI Innovations +AI10936,AI Specialist,102652,USD,102652,SE,CT,South Korea,M,South Korea,100,"Data Visualization, Mathematics, GCP",Bachelor,5,Consulting,2024-04-02,2024-04-17,927,6.8,Quantum Computing Inc +AI10937,Data Scientist,120871,EUR,102740,SE,PT,Netherlands,M,Netherlands,100,"Linux, Hadoop, AWS, Data Visualization, GCP",Associate,6,Healthcare,2024-07-24,2024-10-01,1764,7.3,DataVision Ltd +AI10938,NLP Engineer,91506,JPY,10065660,EN,FT,Japan,L,Japan,100,"SQL, Linux, Mathematics",PhD,1,Energy,2025-03-16,2025-04-29,1817,7,Future Systems +AI10939,Data Scientist,156607,CAD,195759,EX,PT,Canada,L,Canada,0,"Spark, Python, Docker",PhD,12,Energy,2024-04-24,2024-06-02,1016,6.4,Autonomous Tech +AI10940,Computer Vision Engineer,114380,USD,114380,MI,FT,Israel,L,Israel,100,"R, GCP, PyTorch",Associate,4,Retail,2025-01-01,2025-02-01,646,7.1,Smart Analytics +AI10941,NLP Engineer,47258,EUR,40169,EN,FT,Austria,S,Austria,0,"Python, Scala, Computer Vision",Associate,1,Gaming,2024-10-28,2024-12-15,1295,6.9,Smart Analytics +AI10942,Computer Vision Engineer,63033,SGD,81943,EN,PT,Singapore,S,Singapore,100,"Python, GCP, Computer Vision, Azure",Associate,1,Retail,2024-11-23,2025-01-01,961,9.4,Machine Intelligence Group +AI10943,Data Analyst,51890,USD,51890,EX,CT,India,S,India,50,"Scala, Computer Vision, Kubernetes, GCP",Master,18,Finance,2025-01-31,2025-04-02,1200,9.1,Advanced Robotics +AI10944,NLP Engineer,114029,EUR,96925,MI,FL,France,L,Philippines,100,"GCP, Java, NLP",PhD,4,Technology,2025-02-07,2025-04-13,2083,5.4,Autonomous Tech +AI10945,Data Engineer,97612,USD,97612,MI,PT,Ireland,L,Ireland,100,"PyTorch, Kubernetes, GCP, NLP",PhD,4,Retail,2024-12-29,2025-01-20,912,6.7,TechCorp Inc +AI10946,Research Scientist,99042,EUR,84186,MI,PT,France,M,France,100,"Docker, Hadoop, Computer Vision",Bachelor,4,Government,2024-01-17,2024-03-19,1864,6,Predictive Systems +AI10947,Deep Learning Engineer,143114,EUR,121647,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Kubernetes",Master,8,Government,2024-08-07,2024-09-02,592,9.3,TechCorp Inc +AI10948,AI Consultant,246283,USD,246283,EX,CT,Norway,S,Norway,0,"R, PyTorch, Mathematics, TensorFlow",Bachelor,13,Healthcare,2025-01-06,2025-02-26,1469,7.7,Algorithmic Solutions +AI10949,NLP Engineer,83037,JPY,9134070,MI,PT,Japan,M,Germany,50,"Python, Data Visualization, TensorFlow, Hadoop",Associate,3,Government,2024-05-28,2024-07-26,1776,8.6,Digital Transformation LLC +AI10950,NLP Engineer,64015,USD,64015,EN,PT,Sweden,L,Sweden,0,"Python, Kubernetes, Docker",Bachelor,1,Technology,2024-10-01,2024-10-20,1023,7.3,AI Innovations +AI10951,Data Scientist,121642,USD,121642,EX,CT,Finland,S,Finland,0,"Kubernetes, NLP, Python, Mathematics",Associate,17,Education,2024-03-26,2024-05-23,549,10,Autonomous Tech +AI10952,AI Software Engineer,76327,GBP,57245,EN,PT,United Kingdom,S,Indonesia,50,"Tableau, GCP, Git, Azure, Kubernetes",Associate,0,Energy,2024-05-17,2024-07-19,1246,8.7,DeepTech Ventures +AI10953,Robotics Engineer,165749,EUR,140887,EX,CT,Austria,S,Austria,0,"Hadoop, Python, TensorFlow",Bachelor,16,Technology,2024-01-19,2024-02-07,1686,6.2,Cloud AI Solutions +AI10954,Data Analyst,137659,USD,137659,SE,FL,Sweden,L,Sweden,100,"Statistics, Docker, TensorFlow",PhD,7,Energy,2025-04-18,2025-06-08,1577,7.6,Machine Intelligence Group +AI10955,AI Specialist,105624,GBP,79218,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, R, Azure, Linux",Master,4,Healthcare,2024-08-18,2024-10-30,641,8.8,TechCorp Inc +AI10956,Autonomous Systems Engineer,146967,USD,146967,MI,CT,Norway,L,Norway,100,"Spark, GCP, Hadoop",Bachelor,4,Technology,2024-04-11,2024-05-09,2256,8.4,Smart Analytics +AI10957,Machine Learning Engineer,76091,USD,76091,EN,PT,Ireland,L,Ireland,100,"Docker, Computer Vision, Git, R, GCP",Bachelor,1,Government,2024-02-08,2024-04-05,1762,5.2,Machine Intelligence Group +AI10958,Machine Learning Researcher,79160,USD,79160,EN,FT,Denmark,M,Luxembourg,50,"Kubernetes, Python, TensorFlow",Bachelor,0,Transportation,2024-01-18,2024-03-14,2020,7.1,Cloud AI Solutions +AI10959,Robotics Engineer,176142,CHF,158528,MI,FT,Switzerland,L,Luxembourg,0,"AWS, R, Data Visualization",PhD,3,Education,2024-03-24,2024-04-10,1000,6.3,Cloud AI Solutions +AI10960,Computer Vision Engineer,85509,EUR,72683,MI,PT,Germany,S,Germany,100,"Data Visualization, MLOps, Kubernetes, SQL, Python",Associate,3,Education,2024-11-01,2025-01-06,610,9.4,Cloud AI Solutions +AI10961,Data Analyst,66853,USD,66853,MI,FL,Finland,S,Finland,100,"R, Mathematics, Linux",PhD,4,Finance,2024-08-02,2024-08-21,1589,5.9,Machine Intelligence Group +AI10962,Research Scientist,26651,USD,26651,MI,FL,India,S,India,100,"Java, SQL, Azure, Git, GCP",Bachelor,4,Transportation,2024-01-18,2024-02-23,1808,8.2,Digital Transformation LLC +AI10963,Machine Learning Engineer,60811,USD,60811,EN,FT,United States,M,United States,0,"MLOps, Tableau, Scala, Hadoop, AWS",Bachelor,0,Gaming,2024-02-14,2024-03-30,997,8.2,Future Systems +AI10964,Data Engineer,65850,USD,65850,EN,CT,South Korea,M,South Korea,0,"Hadoop, GCP, Tableau",Associate,0,Retail,2024-12-05,2025-02-09,580,5.1,Future Systems +AI10965,Deep Learning Engineer,159852,EUR,135874,EX,FL,France,M,France,100,"Kubernetes, Hadoop, Python, AWS",Bachelor,12,Technology,2024-02-26,2024-04-15,694,9,Cloud AI Solutions +AI10966,AI Software Engineer,117072,CHF,105365,MI,CT,Switzerland,M,Luxembourg,100,"Data Visualization, TensorFlow, Python",Master,4,Education,2024-02-01,2024-04-06,1043,9,TechCorp Inc +AI10967,Head of AI,73513,USD,73513,EX,FT,India,S,India,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Consulting,2024-12-31,2025-03-03,2106,5.9,AI Innovations +AI10968,AI Specialist,158422,EUR,134659,EX,PT,Germany,M,Germany,50,"Python, Mathematics, TensorFlow",PhD,19,Consulting,2024-06-19,2024-08-12,732,7.7,Quantum Computing Inc +AI10969,AI Consultant,52063,USD,52063,EN,PT,South Korea,M,South Korea,0,"Computer Vision, MLOps, Mathematics, Docker",PhD,1,Finance,2025-04-04,2025-05-02,2052,5.9,TechCorp Inc +AI10970,AI Architect,87999,USD,87999,EN,PT,Norway,L,Norway,50,"Azure, Python, Computer Vision",PhD,0,Consulting,2025-01-25,2025-03-04,2011,9.3,Cognitive Computing +AI10971,Robotics Engineer,65735,AUD,88742,EN,FL,Australia,S,Vietnam,100,"Scala, Git, Statistics",Associate,1,Real Estate,2025-02-02,2025-03-04,776,9.9,AI Innovations +AI10972,Machine Learning Researcher,79748,USD,79748,EX,FT,India,M,India,100,"NLP, Python, Mathematics, GCP",Master,17,Education,2025-02-02,2025-03-10,998,9.9,DeepTech Ventures +AI10973,Machine Learning Engineer,153047,CHF,137742,MI,FT,Switzerland,L,New Zealand,0,"SQL, Python, R",Master,3,Retail,2024-07-25,2024-09-26,1468,5.9,Future Systems +AI10974,Data Analyst,82660,GBP,61995,EN,PT,United Kingdom,L,United Kingdom,100,"Java, R, Mathematics",Bachelor,1,Retail,2024-09-09,2024-10-07,599,9.5,Smart Analytics +AI10975,Computer Vision Engineer,245036,USD,245036,EX,CT,United States,S,United States,100,"Git, Linux, Kubernetes, Deep Learning, NLP",Bachelor,17,Technology,2024-05-15,2024-07-22,804,9.9,Smart Analytics +AI10976,AI Research Scientist,223802,AUD,302133,EX,PT,Australia,S,Australia,100,"AWS, Kubernetes, Computer Vision",Bachelor,11,Energy,2024-11-04,2025-01-10,964,7.1,Cloud AI Solutions +AI10977,Machine Learning Researcher,83891,AUD,113253,MI,FL,Australia,M,Australia,50,"Git, MLOps, Scala, GCP, Spark",Master,3,Real Estate,2025-02-23,2025-04-21,852,6.8,Advanced Robotics +AI10978,Machine Learning Researcher,98442,GBP,73832,SE,PT,United Kingdom,S,United Kingdom,50,"SQL, Git, TensorFlow, Python",PhD,5,Education,2024-03-31,2024-04-21,1604,9.9,Advanced Robotics +AI10979,NLP Engineer,128077,JPY,14088470,SE,FL,Japan,M,Japan,100,"TensorFlow, Python, MLOps, Git",Associate,6,Energy,2024-03-06,2024-04-22,1539,5.5,TechCorp Inc +AI10980,Data Scientist,186264,USD,186264,EX,FT,Sweden,M,Sweden,0,"SQL, Computer Vision, Scala",Bachelor,15,Finance,2024-07-16,2024-09-10,612,7.4,Advanced Robotics +AI10981,AI Research Scientist,110728,USD,110728,MI,CT,Norway,M,Norway,0,"TensorFlow, Python, Kubernetes, R",PhD,3,Technology,2025-03-23,2025-04-11,1637,8.5,Algorithmic Solutions +AI10982,Robotics Engineer,215988,USD,215988,EX,PT,Denmark,M,Denmark,0,"PyTorch, Deep Learning, NLP, Git",Associate,15,Manufacturing,2024-06-09,2024-06-23,508,9.8,Cognitive Computing +AI10983,Autonomous Systems Engineer,125459,USD,125459,SE,CT,Israel,S,Indonesia,50,"Python, Scala, Kubernetes, Deep Learning, AWS",PhD,6,Automotive,2024-03-23,2024-05-26,1423,7.2,AI Innovations +AI10984,ML Ops Engineer,247115,USD,247115,EX,FL,United States,L,United States,0,"TensorFlow, R, Deep Learning, GCP, Git",Associate,19,Consulting,2024-12-03,2025-01-24,1894,5.5,Digital Transformation LLC +AI10985,Machine Learning Engineer,311593,USD,311593,EX,FL,Norway,L,Norway,0,"Linux, Python, TensorFlow",Master,16,Finance,2025-01-23,2025-03-08,1712,7.9,Future Systems +AI10986,Data Analyst,129554,USD,129554,EX,FT,China,L,China,0,"Data Visualization, Kubernetes, Java",Associate,18,Consulting,2025-03-23,2025-05-28,705,9.2,Cloud AI Solutions +AI10987,Deep Learning Engineer,284164,USD,284164,EX,PT,Norway,L,Norway,100,"R, Statistics, SQL, Python, Linux",Master,14,Telecommunications,2024-02-03,2024-02-28,2259,6.5,Cognitive Computing +AI10988,Deep Learning Engineer,144657,EUR,122958,SE,FT,Netherlands,L,Netherlands,0,"SQL, Statistics, Linux",Master,5,Government,2025-02-23,2025-04-30,586,5.7,Predictive Systems +AI10989,Computer Vision Engineer,178156,CAD,222695,EX,FT,Canada,M,Canada,0,"Kubernetes, SQL, Azure, Hadoop",PhD,19,Automotive,2025-02-03,2025-03-22,1702,7.2,Neural Networks Co +AI10990,Data Scientist,86173,CAD,107716,MI,FL,Canada,M,Canada,100,"MLOps, Git, PyTorch, Mathematics",Associate,2,Healthcare,2024-08-09,2024-10-03,1035,8.4,Cloud AI Solutions +AI10991,Data Scientist,106280,SGD,138164,MI,PT,Singapore,L,Czech Republic,100,"Java, SQL, Kubernetes, AWS",Associate,2,Energy,2024-11-26,2025-01-07,779,5.8,TechCorp Inc +AI10992,Data Scientist,80053,AUD,108072,MI,FL,Australia,M,Australia,50,"Deep Learning, Linux, MLOps, SQL, Kubernetes",Master,4,Healthcare,2025-03-05,2025-03-20,1525,9.8,TechCorp Inc +AI10993,AI Architect,91642,CAD,114553,MI,CT,Canada,M,Canada,50,"Git, Docker, Spark, R, Mathematics",Master,2,Real Estate,2024-11-17,2024-12-09,1599,5.7,AI Innovations +AI10994,Data Analyst,72487,EUR,61614,EN,FL,Germany,S,Netherlands,0,"PyTorch, Tableau, Mathematics, MLOps",PhD,1,Education,2025-02-01,2025-02-19,2284,6,Future Systems +AI10995,Data Analyst,40355,USD,40355,EN,FT,China,L,Denmark,0,"Python, TensorFlow, PyTorch, AWS",PhD,0,Gaming,2024-12-21,2025-01-26,1733,5.1,Cognitive Computing +AI10996,AI Architect,185648,USD,185648,EX,FL,Denmark,M,Denmark,50,"Tableau, TensorFlow, Git, Statistics",PhD,18,Education,2024-11-08,2025-01-11,711,7.2,Quantum Computing Inc +AI10997,NLP Engineer,177709,USD,177709,EX,PT,Ireland,M,Ireland,100,"AWS, MLOps, Deep Learning",Master,13,Real Estate,2024-04-13,2024-06-02,1165,6.5,Predictive Systems +AI10998,Computer Vision Engineer,60113,EUR,51096,EN,CT,Netherlands,S,Netherlands,100,"AWS, Data Visualization, Linux, TensorFlow",Associate,0,Consulting,2024-12-01,2025-01-06,1214,6.7,AI Innovations +AI10999,Data Engineer,170719,USD,170719,EX,FL,Norway,S,Norway,100,"Hadoop, Python, TensorFlow",PhD,13,Consulting,2025-01-31,2025-04-04,2355,6.2,AI Innovations +AI11000,Principal Data Scientist,94395,USD,94395,MI,CT,South Korea,L,South Korea,0,"R, SQL, Kubernetes",PhD,4,Telecommunications,2024-11-11,2024-12-13,1904,6.7,Digital Transformation LLC +AI11001,Robotics Engineer,170094,EUR,144580,EX,FL,Netherlands,L,Netherlands,50,"Kubernetes, Git, PyTorch, SQL, Deep Learning",Associate,12,Automotive,2025-02-25,2025-04-07,1931,9,Predictive Systems +AI11002,Robotics Engineer,44187,USD,44187,MI,FT,China,S,China,100,"TensorFlow, Docker, Scala",Associate,4,Manufacturing,2025-04-07,2025-05-06,1790,5.4,Predictive Systems +AI11003,NLP Engineer,199463,USD,199463,EX,FT,Ireland,S,Chile,0,"Tableau, TensorFlow, Linux, Python",Bachelor,16,Manufacturing,2024-10-06,2024-11-13,833,6.1,TechCorp Inc +AI11004,Machine Learning Researcher,103266,CAD,129083,SE,PT,Canada,M,Canada,100,"Python, Kubernetes, Docker",Master,9,Education,2024-10-12,2024-12-17,1567,8.5,Quantum Computing Inc +AI11005,Head of AI,74247,EUR,63110,MI,PT,Austria,M,Poland,100,"SQL, Deep Learning, Python, Hadoop",PhD,2,Finance,2025-03-10,2025-04-26,1921,7.6,DeepTech Ventures +AI11006,Robotics Engineer,267617,GBP,200713,EX,FL,United Kingdom,M,Egypt,100,"Python, TensorFlow, PyTorch, Tableau, Docker",Associate,12,Technology,2024-02-04,2024-04-16,1058,8.6,Future Systems +AI11007,AI Product Manager,170750,EUR,145138,SE,PT,Netherlands,L,Hungary,0,"Python, Data Visualization, MLOps, Hadoop, AWS",Associate,5,Finance,2024-07-14,2024-08-11,1811,7.5,Predictive Systems +AI11008,AI Architect,151644,EUR,128897,EX,FT,Germany,S,Germany,0,"TensorFlow, Tableau, GCP, PyTorch, Statistics",Associate,10,Automotive,2025-02-22,2025-04-29,1657,6.4,DeepTech Ventures +AI11009,Head of AI,19668,USD,19668,EN,CT,India,M,India,50,"MLOps, Scala, GCP, AWS, Kubernetes",Bachelor,0,Real Estate,2024-08-28,2024-09-13,1898,7.2,Advanced Robotics +AI11010,AI Specialist,133233,USD,133233,SE,FT,Sweden,M,Sweden,50,"SQL, PyTorch, Linux, Deep Learning",Master,8,Manufacturing,2024-08-20,2024-10-19,1836,6.2,Advanced Robotics +AI11011,AI Consultant,62844,USD,62844,EN,PT,Ireland,S,Ireland,50,"Git, PyTorch, TensorFlow, Docker",Bachelor,1,Media,2024-03-26,2024-05-17,987,8.8,Machine Intelligence Group +AI11012,Data Scientist,144621,USD,144621,SE,FL,Norway,S,Norway,50,"Spark, Kubernetes, Computer Vision, AWS",Associate,6,Transportation,2024-10-31,2024-11-29,2429,5.4,Digital Transformation LLC +AI11013,AI Product Manager,121548,USD,121548,SE,FT,United States,M,United States,50,"Hadoop, Deep Learning, Kubernetes, Spark, Python",Master,6,Real Estate,2024-11-28,2025-01-20,959,6.8,Algorithmic Solutions +AI11014,ML Ops Engineer,355399,CHF,319859,EX,FT,Switzerland,M,Switzerland,0,"GCP, Git, Computer Vision",Bachelor,14,Technology,2024-07-25,2024-08-29,1808,8.8,Digital Transformation LLC +AI11015,AI Research Scientist,261652,USD,261652,EX,PT,Norway,S,Norway,0,"SQL, AWS, GCP",Bachelor,10,Transportation,2024-12-24,2025-02-12,536,6,Quantum Computing Inc +AI11016,Principal Data Scientist,135239,USD,135239,SE,FL,United States,M,United States,0,"Python, Data Visualization, Hadoop, Scala",Bachelor,9,Automotive,2024-10-13,2024-11-21,941,5.3,AI Innovations +AI11017,AI Research Scientist,136136,USD,136136,SE,FL,United States,M,United States,0,"GCP, Data Visualization, PyTorch, R, Spark",Master,7,Real Estate,2024-02-17,2024-03-04,2020,9.3,Predictive Systems +AI11018,Computer Vision Engineer,162399,USD,162399,EX,FT,Ireland,S,Ireland,100,"R, GCP, MLOps, Python",Associate,16,Media,2025-04-10,2025-05-26,1549,5.8,DataVision Ltd +AI11019,Data Scientist,250763,GBP,188072,EX,FL,United Kingdom,L,Czech Republic,100,"Data Visualization, TensorFlow, NLP, Statistics",Associate,12,Transportation,2024-09-21,2024-10-27,1830,7.4,Cognitive Computing +AI11020,Deep Learning Engineer,63767,EUR,54202,EN,PT,Germany,S,Germany,50,"Hadoop, Data Visualization, GCP",Master,1,Consulting,2025-04-17,2025-05-08,1518,9.1,Cloud AI Solutions +AI11021,Research Scientist,74764,EUR,63549,MI,FL,Austria,M,Austria,50,"Python, TensorFlow, NLP",Master,2,Telecommunications,2024-12-05,2025-02-06,2011,5.2,Quantum Computing Inc +AI11022,Research Scientist,46031,USD,46031,EN,FT,Israel,S,Hungary,50,"Kubernetes, Java, Scala",PhD,1,Transportation,2024-10-28,2024-12-28,648,8.6,Cognitive Computing +AI11023,AI Consultant,52060,EUR,44251,EN,FL,Austria,M,Austria,50,"R, Hadoop, SQL",PhD,0,Automotive,2024-12-10,2025-01-19,1945,5.2,DataVision Ltd +AI11024,Autonomous Systems Engineer,138305,EUR,117559,SE,CT,France,M,France,50,"Java, Hadoop, NLP, Computer Vision",PhD,8,Consulting,2025-01-09,2025-02-16,1084,5.7,AI Innovations +AI11025,AI Product Manager,82393,USD,82393,MI,PT,United States,S,United States,100,"Docker, PyTorch, R, Azure",Bachelor,2,Government,2025-04-07,2025-05-14,2069,8.7,Quantum Computing Inc +AI11026,AI Product Manager,174517,USD,174517,EX,CT,Sweden,L,Sweden,100,"TensorFlow, Docker, R",PhD,16,Telecommunications,2024-10-06,2024-11-22,1820,9.2,TechCorp Inc +AI11027,Robotics Engineer,133855,USD,133855,MI,PT,Norway,L,Norway,0,"SQL, MLOps, Data Visualization",Bachelor,4,Automotive,2024-12-12,2024-12-30,1909,8.8,Future Systems +AI11028,Data Analyst,114683,EUR,97481,SE,FL,Austria,L,Ukraine,50,"Git, Hadoop, Java",PhD,7,Consulting,2025-03-06,2025-04-15,1203,8.5,Cloud AI Solutions +AI11029,Data Analyst,144927,CHF,130434,MI,FL,Switzerland,M,Ghana,50,"R, SQL, Java, Hadoop, Git",Master,3,Government,2025-02-18,2025-04-26,1093,5.9,Smart Analytics +AI11030,AI Software Engineer,125273,AUD,169119,SE,CT,Australia,S,Australia,100,"AWS, Python, GCP, Spark, TensorFlow",PhD,7,Finance,2024-04-14,2024-05-01,2128,9.5,Predictive Systems +AI11031,AI Consultant,147687,EUR,125534,SE,PT,Netherlands,L,Ireland,0,"Hadoop, Spark, PyTorch, Scala",Associate,5,Education,2024-10-21,2024-11-04,2008,7.1,Future Systems +AI11032,Data Scientist,50116,USD,50116,EN,CT,Finland,M,Vietnam,0,"Java, Kubernetes, Data Visualization, GCP, NLP",Bachelor,1,Education,2024-12-25,2025-01-26,1419,7.3,Algorithmic Solutions +AI11033,Data Analyst,104932,EUR,89192,MI,PT,Netherlands,S,Netherlands,100,"Linux, Scala, MLOps",Associate,2,Consulting,2024-12-16,2025-01-17,2408,7.1,Predictive Systems +AI11034,Machine Learning Engineer,109091,CAD,136364,SE,FL,Canada,M,Canada,0,"PyTorch, R, GCP, Tableau",PhD,8,Government,2024-08-31,2024-09-19,1227,7.5,Advanced Robotics +AI11035,Machine Learning Engineer,108563,GBP,81422,MI,CT,United Kingdom,L,Japan,50,"Python, PyTorch, Scala, SQL",Associate,4,Finance,2024-08-20,2024-10-19,663,6.6,Digital Transformation LLC +AI11036,AI Research Scientist,69383,SGD,90198,EN,FT,Singapore,M,Singapore,100,"Kubernetes, Statistics, GCP",Associate,0,Media,2024-04-15,2024-05-30,643,5.7,AI Innovations +AI11037,Principal Data Scientist,83302,JPY,9163220,MI,FL,Japan,S,Japan,0,"Java, MLOps, Tableau",Master,2,Automotive,2024-03-01,2024-04-30,1368,5.8,Algorithmic Solutions +AI11038,NLP Engineer,253256,EUR,215268,EX,FL,Netherlands,M,Netherlands,50,"Scala, Docker, Computer Vision, Python, Mathematics",Associate,14,Education,2024-12-01,2025-01-10,2350,9.3,DeepTech Ventures +AI11039,Autonomous Systems Engineer,247403,USD,247403,EX,PT,United States,M,United States,50,"Tableau, Docker, Python, Git",Bachelor,19,Education,2024-10-06,2024-12-04,2319,6.1,Smart Analytics +AI11040,Computer Vision Engineer,75025,USD,75025,MI,FL,Ireland,S,Canada,0,"PyTorch, R, Spark, MLOps, Git",Associate,2,Transportation,2024-10-06,2024-11-29,1591,8,TechCorp Inc +AI11041,AI Consultant,60929,USD,60929,EN,FT,Israel,M,Israel,0,"Hadoop, Git, Data Visualization",PhD,1,Retail,2025-03-20,2025-04-13,1691,9.7,Algorithmic Solutions +AI11042,AI Consultant,55166,GBP,41375,EN,FT,United Kingdom,M,United Kingdom,50,"Kubernetes, Statistics, Deep Learning, Tableau, MLOps",PhD,0,Media,2024-01-16,2024-03-22,1296,6,Cognitive Computing +AI11043,Data Engineer,70004,USD,70004,EN,PT,Sweden,M,Sweden,0,"R, Git, Java, Linux",Associate,0,Healthcare,2024-05-30,2024-08-02,2277,8.2,Future Systems +AI11044,AI Specialist,275697,USD,275697,EX,CT,Norway,L,Norway,0,"AWS, PyTorch, SQL, TensorFlow",Master,19,Government,2025-02-28,2025-05-04,951,8.6,Smart Analytics +AI11045,Principal Data Scientist,52725,EUR,44816,EN,PT,Germany,M,Ukraine,100,"Python, Computer Vision, Azure",Bachelor,0,Media,2024-08-11,2024-09-10,1030,5.1,Quantum Computing Inc +AI11046,Computer Vision Engineer,268365,USD,268365,EX,FL,Norway,M,United States,0,"Python, Azure, Data Visualization",Associate,11,Gaming,2025-03-04,2025-04-12,1695,9.3,DataVision Ltd +AI11047,Principal Data Scientist,76596,JPY,8425560,MI,PT,Japan,M,China,50,"Java, Linux, Python",Associate,2,Retail,2024-11-08,2024-12-05,623,7.5,Smart Analytics +AI11048,Computer Vision Engineer,285551,AUD,385494,EX,FL,Australia,L,Australia,50,"Python, NLP, Mathematics, PyTorch, Spark",Bachelor,12,Automotive,2024-02-28,2024-03-21,570,5.4,TechCorp Inc +AI11049,Robotics Engineer,118954,CAD,148693,SE,PT,Canada,L,Canada,100,"Python, PyTorch, Statistics",PhD,5,Government,2025-04-25,2025-05-15,2402,8.9,Cloud AI Solutions +AI11050,ML Ops Engineer,153938,CAD,192423,EX,CT,Canada,S,Canada,0,"PyTorch, Kubernetes, Scala, R, Data Visualization",Associate,16,Real Estate,2024-11-11,2024-12-29,1553,8.6,Advanced Robotics +AI11051,Deep Learning Engineer,131972,GBP,98979,MI,PT,United Kingdom,L,United Kingdom,100,"NLP, GCP, Python, Linux, Azure",Master,2,Manufacturing,2024-11-18,2024-12-21,2189,5.1,Advanced Robotics +AI11052,AI Product Manager,123154,USD,123154,EX,PT,Israel,S,Israel,50,"Data Visualization, Linux, Java",Bachelor,18,Energy,2024-07-29,2024-09-27,1275,7.4,Future Systems +AI11053,ML Ops Engineer,84249,JPY,9267390,MI,FL,Japan,M,Italy,50,"Java, NLP, Azure",Associate,4,Education,2024-04-25,2024-06-22,857,6.5,Smart Analytics +AI11054,Principal Data Scientist,93431,USD,93431,MI,PT,Sweden,S,Vietnam,50,"GCP, Tableau, Computer Vision, Linux",Associate,2,Finance,2025-02-04,2025-02-18,939,5,DataVision Ltd +AI11055,Computer Vision Engineer,135625,EUR,115281,EX,FL,France,M,France,0,"MLOps, Scala, NLP, PyTorch",Master,17,Gaming,2024-07-04,2024-08-28,1870,9.5,TechCorp Inc +AI11056,AI Product Manager,218295,EUR,185551,EX,PT,Austria,L,Austria,50,"SQL, Kubernetes, Docker, Tableau",Master,14,Gaming,2024-06-29,2024-08-03,1091,9.3,Predictive Systems +AI11057,ML Ops Engineer,99582,USD,99582,EN,FL,Denmark,L,Netherlands,100,"Linux, Data Visualization, PyTorch",Associate,1,Consulting,2025-03-29,2025-04-25,1168,9.6,Autonomous Tech +AI11058,Robotics Engineer,262079,GBP,196559,EX,FL,United Kingdom,L,United Kingdom,100,"Python, Java, Spark",Master,15,Technology,2024-02-06,2024-03-22,811,9.7,Smart Analytics +AI11059,AI Research Scientist,124785,USD,124785,SE,FT,Israel,M,Israel,50,"GCP, Scala, NLP, Kubernetes",Bachelor,7,Government,2024-12-19,2025-01-07,820,5.3,Cognitive Computing +AI11060,Autonomous Systems Engineer,78762,USD,78762,MI,FT,South Korea,S,South Korea,100,"TensorFlow, Python, Docker",Associate,3,Transportation,2024-01-05,2024-01-28,1893,8.9,Autonomous Tech +AI11061,Computer Vision Engineer,116968,JPY,12866480,MI,PT,Japan,M,Japan,50,"Java, R, Mathematics, Data Visualization, NLP",Bachelor,4,Manufacturing,2024-09-14,2024-10-25,2019,6.7,Machine Intelligence Group +AI11062,Machine Learning Researcher,82720,EUR,70312,MI,FT,Netherlands,M,Netherlands,0,"Data Visualization, Kubernetes, Azure",PhD,2,Telecommunications,2024-12-30,2025-03-08,812,9.1,DeepTech Ventures +AI11063,Data Analyst,105375,USD,105375,MI,FL,United States,M,United States,50,"TensorFlow, GCP, Azure, Hadoop",Master,3,Retail,2024-06-04,2024-07-24,1249,6.6,Algorithmic Solutions +AI11064,Computer Vision Engineer,123190,EUR,104712,EX,PT,Austria,S,Austria,50,"Data Visualization, AWS, Linux, Computer Vision, Statistics",Master,10,Real Estate,2024-07-11,2024-08-26,1042,9.7,DataVision Ltd +AI11065,ML Ops Engineer,277393,EUR,235784,EX,FL,Germany,L,Germany,0,"Kubernetes, Computer Vision, Git, Mathematics",Bachelor,17,Finance,2024-09-07,2024-11-01,996,5.5,DataVision Ltd +AI11066,Robotics Engineer,106542,EUR,90561,SE,FL,Germany,S,Germany,100,"Tableau, Java, Computer Vision",Bachelor,6,Media,2024-07-24,2024-09-12,547,8.7,DataVision Ltd +AI11067,NLP Engineer,94499,EUR,80324,MI,FL,France,L,Kenya,50,"Git, Java, MLOps, Computer Vision",Bachelor,2,Gaming,2024-02-12,2024-04-15,821,7.8,Quantum Computing Inc +AI11068,Autonomous Systems Engineer,189283,CHF,170355,SE,PT,Switzerland,M,Latvia,0,"Scala, GCP, Deep Learning",Master,8,Education,2024-06-16,2024-07-24,1321,9.7,Cloud AI Solutions +AI11069,Computer Vision Engineer,157133,EUR,133563,SE,FL,Germany,L,Germany,100,"Python, Git, Kubernetes, Deep Learning, R",Master,9,Finance,2024-08-07,2024-09-30,913,6.6,Algorithmic Solutions +AI11070,Robotics Engineer,258931,USD,258931,EX,FT,Denmark,S,Argentina,100,"Python, AWS, Docker",Associate,15,Government,2024-06-22,2024-07-31,1270,5.5,AI Innovations +AI11071,AI Specialist,94485,CAD,118106,MI,CT,Canada,M,Canada,50,"Java, Hadoop, SQL, Mathematics, GCP",Bachelor,3,Technology,2025-02-28,2025-03-23,1538,8.3,DataVision Ltd +AI11072,AI Architect,53437,USD,53437,EN,PT,Sweden,S,Sweden,50,"SQL, Hadoop, Linux",Bachelor,1,Government,2024-01-07,2024-02-08,980,9.9,Predictive Systems +AI11073,Computer Vision Engineer,81989,EUR,69691,MI,FT,France,S,Russia,100,"TensorFlow, Tableau, Mathematics, Java",Associate,2,Automotive,2024-03-08,2024-04-05,1163,7.1,Quantum Computing Inc +AI11074,AI Software Engineer,53872,GBP,40404,EN,PT,United Kingdom,S,Vietnam,100,"Python, SQL, Hadoop",PhD,1,Real Estate,2024-08-01,2024-09-27,1286,5.1,Predictive Systems +AI11075,AI Product Manager,112299,USD,112299,MI,PT,Finland,L,Finland,100,"Python, TensorFlow, Docker, PyTorch, Scala",Bachelor,4,Manufacturing,2024-05-06,2024-06-02,2011,8.1,AI Innovations +AI11076,Head of AI,148344,EUR,126092,EX,PT,Austria,M,Nigeria,50,"Git, Kubernetes, GCP, Tableau, MLOps",Associate,17,Education,2024-09-28,2024-11-09,1791,6.3,Future Systems +AI11077,AI Consultant,149732,AUD,202138,EX,PT,Australia,M,Australia,50,"Python, Git, NLP, Scala",PhD,19,Retail,2024-03-31,2024-04-28,1510,9.2,Cloud AI Solutions +AI11078,Research Scientist,86366,USD,86366,MI,FL,United States,S,United States,0,"Git, Scala, MLOps, R",PhD,4,Manufacturing,2025-04-23,2025-05-07,2253,7.7,Digital Transformation LLC +AI11079,AI Specialist,126508,USD,126508,MI,FL,Norway,S,Malaysia,0,"GCP, AWS, Data Visualization, Python, TensorFlow",Bachelor,3,Finance,2024-01-17,2024-03-07,1652,9.3,AI Innovations +AI11080,Data Scientist,88565,USD,88565,MI,FT,Israel,M,Malaysia,0,"MLOps, Mathematics, TensorFlow, GCP, AWS",Master,3,Media,2024-01-27,2024-02-19,1483,9.6,Future Systems +AI11081,AI Software Engineer,67656,USD,67656,EN,FT,Ireland,L,Czech Republic,0,"Python, Azure, Kubernetes",Associate,0,Retail,2024-06-20,2024-08-08,2044,6.3,Neural Networks Co +AI11082,AI Architect,112374,EUR,95518,MI,FT,Netherlands,L,Netherlands,50,"Scala, R, Spark",Associate,4,Retail,2025-01-11,2025-02-20,1000,6.6,DeepTech Ventures +AI11083,AI Research Scientist,117883,JPY,12967130,MI,PT,Japan,L,Japan,0,"Data Visualization, Hadoop, Linux",Master,3,Transportation,2024-01-15,2024-01-29,727,9.2,Autonomous Tech +AI11084,AI Software Engineer,121000,USD,121000,SE,FL,United States,M,China,100,"Java, Deep Learning, MLOps, Git",Bachelor,5,Media,2025-04-16,2025-05-28,2140,6.8,DeepTech Ventures +AI11085,Data Engineer,207170,CAD,258963,EX,FL,Canada,L,Canada,0,"TensorFlow, Statistics, Spark, SQL",Master,17,Healthcare,2024-10-28,2024-12-06,766,9.4,Smart Analytics +AI11086,AI Architect,116459,USD,116459,SE,FT,South Korea,L,South Korea,50,"Tableau, Azure, Java, NLP, R",Associate,5,Education,2025-04-25,2025-05-31,502,9.5,Predictive Systems +AI11087,Autonomous Systems Engineer,122703,CHF,110433,MI,FL,Switzerland,L,Switzerland,0,"Linux, Azure, Mathematics",PhD,2,Government,2024-12-26,2025-03-03,2270,8.4,Future Systems +AI11088,Computer Vision Engineer,97199,USD,97199,EN,CT,Norway,L,Norway,50,"Deep Learning, TensorFlow, Scala, Computer Vision, Linux",Bachelor,0,Gaming,2024-06-12,2024-07-22,2472,9,Future Systems +AI11089,Principal Data Scientist,290472,GBP,217854,EX,FT,United Kingdom,L,Italy,100,"Tableau, AWS, TensorFlow",Master,16,Media,2024-09-15,2024-10-23,1094,7.3,TechCorp Inc +AI11090,AI Specialist,81583,EUR,69346,EN,FL,France,L,France,100,"Spark, MLOps, Linux",Bachelor,1,Manufacturing,2024-04-08,2024-06-20,1025,9.5,Neural Networks Co +AI11091,Robotics Engineer,96594,USD,96594,MI,FT,Finland,L,Finland,50,"Linux, GCP, Tableau",Master,4,Media,2024-11-23,2025-01-26,1434,5.8,Algorithmic Solutions +AI11092,AI Consultant,64211,USD,64211,SE,FT,China,S,China,100,"R, Kubernetes, Tableau, Computer Vision, Azure",Master,7,Transportation,2024-01-19,2024-03-19,629,7,Future Systems +AI11093,Data Analyst,155715,EUR,132358,EX,CT,France,L,France,100,"Statistics, Mathematics, Data Visualization, Hadoop, Python",Master,18,Government,2024-04-25,2024-07-07,749,9.6,TechCorp Inc +AI11094,NLP Engineer,114469,USD,114469,MI,FT,Ireland,L,Switzerland,50,"Docker, Kubernetes, GCP",Associate,4,Media,2024-06-23,2024-07-09,556,8.2,Smart Analytics +AI11095,Autonomous Systems Engineer,90803,USD,90803,MI,FT,Ireland,S,India,100,"R, GCP, Computer Vision, Statistics",Bachelor,2,Gaming,2024-10-05,2024-10-29,983,7.6,Machine Intelligence Group +AI11096,Autonomous Systems Engineer,52790,USD,52790,EN,PT,Finland,S,Finland,0,"Kubernetes, R, Computer Vision, Java, Git",Associate,1,Gaming,2024-02-20,2024-04-06,637,9.2,Quantum Computing Inc +AI11097,AI Product Manager,123158,EUR,104684,SE,FL,Germany,S,Germany,50,"Linux, Tableau, Docker, Deep Learning",Bachelor,9,Gaming,2024-09-26,2024-11-06,1797,9.5,Predictive Systems +AI11098,NLP Engineer,136173,USD,136173,EX,FL,Ireland,M,Ireland,0,"Mathematics, Git, Scala",Bachelor,15,Finance,2024-03-06,2024-03-22,1892,9.9,AI Innovations +AI11099,AI Product Manager,33349,USD,33349,EN,FT,China,S,China,50,"AWS, Hadoop, MLOps, TensorFlow",PhD,1,Education,2025-02-15,2025-04-19,1995,9.9,Advanced Robotics +AI11100,Robotics Engineer,109691,USD,109691,EX,FL,China,L,China,100,"Git, PyTorch, SQL",PhD,12,Retail,2024-12-10,2025-01-27,542,8.7,Advanced Robotics +AI11101,AI Software Engineer,154172,USD,154172,SE,PT,Sweden,L,Sweden,50,"Scala, Deep Learning, Data Visualization, Tableau, Docker",Master,7,Real Estate,2024-12-03,2025-02-02,870,8.2,Quantum Computing Inc +AI11102,NLP Engineer,62316,AUD,84127,EN,FT,Australia,S,United States,100,"Python, AWS, Deep Learning, Kubernetes, Statistics",Associate,1,Finance,2024-09-14,2024-10-28,1518,7.6,Digital Transformation LLC +AI11103,Data Scientist,100179,USD,100179,SE,FT,Sweden,S,Finland,100,"Computer Vision, Mathematics, Linux, AWS",PhD,7,Transportation,2024-12-15,2025-01-25,722,9.9,Cognitive Computing +AI11104,Research Scientist,165296,SGD,214885,EX,FT,Singapore,S,Singapore,0,"NLP, SQL, Java, PyTorch",PhD,10,Consulting,2024-10-06,2024-11-08,1218,8.4,Predictive Systems +AI11105,Research Scientist,199699,AUD,269594,EX,FL,Australia,S,Australia,100,"Data Visualization, Python, Kubernetes, Deep Learning, Tableau",Associate,11,Technology,2024-11-10,2024-11-28,1954,8.6,Digital Transformation LLC +AI11106,Autonomous Systems Engineer,199230,USD,199230,SE,FL,Norway,L,Norway,0,"Azure, TensorFlow, Scala, Python, Java",Associate,8,Media,2025-04-19,2025-05-28,1359,8.2,Quantum Computing Inc +AI11107,Data Analyst,60772,AUD,82042,EN,PT,Australia,L,Australia,50,"Deep Learning, Linux, Data Visualization",Associate,0,Real Estate,2024-04-25,2024-06-22,2427,5.6,Machine Intelligence Group +AI11108,Head of AI,35534,USD,35534,MI,CT,China,S,China,50,"Python, TensorFlow, NLP, Scala",Bachelor,3,Finance,2024-01-16,2024-03-12,1054,7.2,Neural Networks Co +AI11109,Principal Data Scientist,127355,EUR,108252,SE,CT,France,S,Colombia,50,"GCP, Java, Scala, Data Visualization, Computer Vision",Associate,7,Healthcare,2025-02-09,2025-04-11,1012,7.9,Smart Analytics +AI11110,AI Research Scientist,150163,USD,150163,SE,PT,Sweden,M,Sweden,100,"Docker, Azure, Data Visualization, Spark, Kubernetes",Bachelor,8,Media,2025-03-16,2025-04-23,1933,6.9,Cognitive Computing +AI11111,Deep Learning Engineer,34278,USD,34278,SE,CT,India,S,India,0,"Data Visualization, Kubernetes, Scala, Statistics",Associate,8,Real Estate,2024-05-23,2024-06-29,550,8.4,Autonomous Tech +AI11112,Robotics Engineer,50385,JPY,5542350,EN,PT,Japan,S,Japan,0,"GCP, Kubernetes, Java, Spark",Bachelor,1,Energy,2024-01-17,2024-02-08,851,8.2,AI Innovations +AI11113,AI Software Engineer,127626,USD,127626,MI,FL,Norway,S,Nigeria,0,"Python, TensorFlow, Data Visualization",Bachelor,2,Technology,2024-09-05,2024-10-01,782,5.9,Predictive Systems +AI11114,Robotics Engineer,87121,USD,87121,EN,FL,Ireland,L,Ireland,0,"Python, Java, AWS, MLOps, Statistics",Master,0,Transportation,2024-07-14,2024-09-22,1394,6.5,AI Innovations +AI11115,Computer Vision Engineer,242532,EUR,206152,EX,FL,Austria,L,Czech Republic,50,"TensorFlow, GCP, Statistics, AWS",PhD,19,Transportation,2024-02-22,2024-04-09,2387,6.6,DataVision Ltd +AI11116,Autonomous Systems Engineer,42882,USD,42882,EN,PT,South Korea,S,Chile,50,"Data Visualization, Docker, Computer Vision, Hadoop",Master,0,Energy,2024-01-31,2024-03-28,2147,8.2,TechCorp Inc +AI11117,AI Software Engineer,63065,USD,63065,MI,CT,South Korea,S,Portugal,50,"SQL, Scala, Mathematics, R",PhD,2,Energy,2024-12-28,2025-02-24,1177,7.8,Smart Analytics +AI11118,Autonomous Systems Engineer,54039,USD,54039,SE,FL,China,S,China,100,"Spark, TensorFlow, Data Visualization",Associate,8,Healthcare,2025-02-05,2025-04-18,1353,5.6,Cognitive Computing +AI11119,Robotics Engineer,184798,JPY,20327780,EX,PT,Japan,L,South Africa,0,"Mathematics, Statistics, Python",Associate,18,Telecommunications,2025-02-07,2025-02-27,1660,9.1,TechCorp Inc +AI11120,Research Scientist,238260,USD,238260,EX,PT,Sweden,L,Sweden,100,"Python, TensorFlow, R, Computer Vision",Associate,12,Media,2025-04-16,2025-06-01,1703,5.3,Quantum Computing Inc +AI11121,Autonomous Systems Engineer,261853,USD,261853,EX,FL,Denmark,S,Denmark,100,"Docker, Linux, PyTorch",PhD,19,Finance,2024-01-28,2024-03-08,1113,8.7,Predictive Systems +AI11122,Data Engineer,239826,SGD,311774,EX,PT,Singapore,S,Singapore,0,"PyTorch, Linux, TensorFlow, SQL",Associate,16,Technology,2025-02-04,2025-02-18,2109,7.7,Predictive Systems +AI11123,Research Scientist,201246,EUR,171059,EX,CT,Germany,M,Germany,50,"Docker, Azure, Data Visualization",Associate,10,Transportation,2025-04-15,2025-05-27,2412,9.3,Machine Intelligence Group +AI11124,Data Engineer,109684,USD,109684,SE,CT,Finland,M,Finland,100,"Hadoop, R, Linux, Java, SQL",Associate,8,Manufacturing,2024-07-18,2024-09-07,876,5.8,Smart Analytics +AI11125,Data Analyst,83819,EUR,71246,MI,FT,Germany,L,Czech Republic,50,"R, Java, MLOps, Kubernetes",Master,2,Gaming,2024-02-25,2024-04-24,988,9.9,Cloud AI Solutions +AI11126,AI Software Engineer,61837,GBP,46378,EN,FT,United Kingdom,S,United Kingdom,50,"Python, GCP, Tableau, R",Bachelor,0,Telecommunications,2024-07-12,2024-09-14,2451,8,TechCorp Inc +AI11127,AI Architect,75517,GBP,56638,EN,FT,United Kingdom,S,Finland,50,"Data Visualization, TensorFlow, MLOps, Python",Bachelor,1,Retail,2024-11-24,2025-01-21,1177,7.3,AI Innovations +AI11128,NLP Engineer,131115,USD,131115,SE,CT,United States,S,United States,0,"TensorFlow, Python, PyTorch",Master,7,Energy,2024-11-27,2025-02-01,673,9.3,DataVision Ltd +AI11129,Data Engineer,169966,EUR,144471,EX,FL,France,S,Poland,50,"Hadoop, PyTorch, Statistics, Mathematics, Deep Learning",Bachelor,15,Consulting,2024-01-20,2024-02-27,529,6.3,DeepTech Ventures +AI11130,Head of AI,79201,USD,79201,EX,FT,India,S,India,50,"Docker, Python, Data Visualization, Scala",Master,10,Finance,2025-02-08,2025-03-08,2200,10,Predictive Systems +AI11131,AI Consultant,71991,EUR,61192,EN,FL,France,L,Israel,50,"Mathematics, GCP, Deep Learning",Bachelor,0,Transportation,2024-03-03,2024-04-05,2377,9.1,Cloud AI Solutions +AI11132,Data Engineer,211340,GBP,158505,EX,CT,United Kingdom,S,Nigeria,50,"NLP, Java, Kubernetes, Git",PhD,11,Automotive,2025-02-17,2025-04-27,921,9.3,TechCorp Inc +AI11133,Machine Learning Engineer,121942,USD,121942,SE,PT,Israel,S,Israel,100,"Kubernetes, GCP, SQL, Git",Associate,5,Healthcare,2024-06-08,2024-07-29,859,8.9,DataVision Ltd +AI11134,Principal Data Scientist,133708,CAD,167135,SE,FL,Canada,M,Canada,50,"Tableau, PyTorch, NLP",Associate,5,Education,2025-03-01,2025-04-24,1145,9.5,Advanced Robotics +AI11135,Data Scientist,128594,GBP,96446,MI,FT,United Kingdom,L,United Kingdom,0,"Statistics, R, PyTorch, TensorFlow",Associate,2,Automotive,2024-11-03,2024-11-19,895,9.7,Digital Transformation LLC +AI11136,Machine Learning Researcher,90783,EUR,77166,MI,PT,France,L,France,100,"R, Scala, NLP",Associate,4,Retail,2024-09-19,2024-11-13,1985,9.1,Neural Networks Co +AI11137,AI Product Manager,241386,GBP,181040,EX,CT,United Kingdom,S,United Kingdom,50,"Scala, Java, R",PhD,13,Technology,2024-03-19,2024-05-02,1706,6.4,Advanced Robotics +AI11138,Data Scientist,50199,USD,50199,EN,FL,South Korea,M,South Korea,50,"Azure, Hadoop, SQL",Master,0,Automotive,2025-03-05,2025-05-12,1284,9.4,TechCorp Inc +AI11139,Head of AI,69589,AUD,93945,EN,FL,Australia,S,Australia,0,"R, SQL, Data Visualization, Git",Bachelor,1,Transportation,2024-02-04,2024-04-10,2397,7.6,Autonomous Tech +AI11140,Data Analyst,249049,USD,249049,EX,FT,United States,L,United States,50,"Azure, Python, Tableau",Bachelor,19,Finance,2024-10-02,2024-11-20,708,5,Neural Networks Co +AI11141,Data Engineer,74973,USD,74973,EN,FT,United States,M,United States,0,"SQL, Kubernetes, AWS",PhD,1,Technology,2025-02-05,2025-03-23,2354,5.3,DeepTech Ventures +AI11142,AI Specialist,86870,USD,86870,MI,FL,Denmark,S,Australia,100,"NLP, SQL, R",PhD,4,Finance,2024-06-22,2024-08-11,1019,7.6,Cloud AI Solutions +AI11143,Robotics Engineer,132380,USD,132380,SE,FL,Israel,M,Israel,0,"Data Visualization, MLOps, SQL, R",Master,5,Energy,2024-08-18,2024-09-03,883,8.3,DeepTech Ventures +AI11144,AI Specialist,134074,EUR,113963,SE,FT,Germany,M,Germany,100,"Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,7,Manufacturing,2024-05-13,2024-06-13,1001,9.2,TechCorp Inc +AI11145,Autonomous Systems Engineer,29783,USD,29783,MI,PT,India,M,Australia,50,"Java, TensorFlow, AWS, Linux",Bachelor,2,Government,2024-11-25,2024-12-21,567,8.8,Neural Networks Co +AI11146,Autonomous Systems Engineer,129656,JPY,14262160,SE,FT,Japan,M,Japan,50,"Python, Kubernetes, Mathematics, MLOps",Associate,8,Media,2024-02-25,2024-05-03,1544,9.7,Smart Analytics +AI11147,AI Research Scientist,101315,USD,101315,SE,CT,Sweden,S,Sweden,50,"R, PyTorch, Azure, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-03-22,1720,8.1,Cognitive Computing +AI11148,Head of AI,154178,USD,154178,EX,FT,Israel,M,Austria,50,"Hadoop, Java, Mathematics",Bachelor,18,Government,2025-01-13,2025-03-16,2287,6.1,Cloud AI Solutions +AI11149,Data Scientist,71943,EUR,61152,EN,PT,Austria,L,Austria,50,"Docker, SQL, Python, AWS",Bachelor,0,Automotive,2024-03-13,2024-05-12,2360,5.5,Predictive Systems +AI11150,AI Research Scientist,187201,USD,187201,EX,FL,South Korea,M,Netherlands,50,"GCP, NLP, AWS",PhD,17,Gaming,2025-03-02,2025-05-12,1532,8.8,Machine Intelligence Group +AI11151,AI Software Engineer,69671,AUD,94056,MI,CT,Australia,S,Australia,100,"Python, Tableau, TensorFlow",Master,3,Healthcare,2024-08-18,2024-10-12,2262,6.6,Algorithmic Solutions +AI11152,Deep Learning Engineer,119940,AUD,161919,SE,CT,Australia,M,Australia,50,"SQL, PyTorch, TensorFlow, Deep Learning, Statistics",PhD,7,Gaming,2024-01-03,2024-03-14,1693,6.3,Future Systems +AI11153,Principal Data Scientist,102411,CHF,92170,MI,FL,Switzerland,S,Mexico,100,"Java, Hadoop, SQL, Computer Vision, Mathematics",Master,3,Healthcare,2024-08-23,2024-09-13,762,9.4,Neural Networks Co +AI11154,ML Ops Engineer,94579,CAD,118224,MI,FL,Canada,L,Canada,50,"PyTorch, GCP, Scala, Hadoop",Associate,4,Real Estate,2024-10-21,2024-12-09,813,8.3,Advanced Robotics +AI11155,Head of AI,93077,GBP,69808,EN,CT,United Kingdom,L,United Kingdom,100,"R, Deep Learning, Python, Statistics, Computer Vision",Associate,1,Finance,2024-06-19,2024-07-08,1504,5.2,Digital Transformation LLC +AI11156,AI Architect,215780,USD,215780,EX,FL,Denmark,L,Denmark,0,"Linux, Computer Vision, GCP, Azure",Master,15,Energy,2024-07-20,2024-09-13,2054,7.2,DataVision Ltd +AI11157,Machine Learning Researcher,123240,EUR,104754,SE,PT,Austria,M,Austria,0,"Kubernetes, Deep Learning, Docker, Statistics, Java",Bachelor,5,Education,2024-09-13,2024-10-09,1895,6.2,Predictive Systems +AI11158,Head of AI,172179,USD,172179,SE,PT,Denmark,M,Egypt,50,"GCP, R, MLOps, TensorFlow",Bachelor,6,Consulting,2024-08-30,2024-10-12,987,8.1,Digital Transformation LLC +AI11159,AI Software Engineer,211756,USD,211756,EX,PT,Sweden,L,Sweden,0,"Data Visualization, NLP, GCP",Master,10,Manufacturing,2024-07-04,2024-07-30,1708,7.2,Neural Networks Co +AI11160,Machine Learning Researcher,68820,USD,68820,MI,FL,South Korea,S,South Korea,50,"NLP, GCP, R, Data Visualization, Computer Vision",Master,4,Automotive,2025-01-03,2025-03-10,1419,9.4,Algorithmic Solutions +AI11161,Machine Learning Researcher,40630,USD,40630,EN,CT,South Korea,S,South Korea,0,"Git, Kubernetes, Hadoop, Java",PhD,1,Gaming,2025-02-28,2025-03-28,692,9.2,TechCorp Inc +AI11162,AI Product Manager,79533,EUR,67603,MI,FL,Austria,S,Israel,0,"NLP, SQL, PyTorch, Tableau, Docker",Associate,4,Manufacturing,2025-03-18,2025-05-02,1282,6.9,AI Innovations +AI11163,Data Engineer,85375,CHF,76838,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Scala, Linux, Docker, MLOps",PhD,0,Transportation,2024-09-14,2024-11-21,2017,7.8,DataVision Ltd +AI11164,Machine Learning Researcher,34517,USD,34517,MI,CT,China,S,China,50,"PyTorch, TensorFlow, MLOps, Java, R",Associate,3,Transportation,2024-02-18,2024-04-19,2242,9.2,AI Innovations +AI11165,Robotics Engineer,169364,USD,169364,EX,PT,Sweden,M,Sweden,0,"Data Visualization, PyTorch, TensorFlow, Statistics, Azure",Master,14,Real Estate,2025-01-06,2025-03-01,1951,9.6,Cognitive Computing +AI11166,AI Architect,118975,CAD,148719,SE,CT,Canada,L,Canada,50,"Python, Mathematics, Git, Computer Vision",PhD,6,Telecommunications,2024-11-26,2025-01-13,1063,7,Machine Intelligence Group +AI11167,AI Specialist,53965,USD,53965,SE,FL,India,L,India,100,"SQL, Java, PyTorch",Bachelor,5,Consulting,2024-01-13,2024-02-21,581,7.6,Neural Networks Co +AI11168,Principal Data Scientist,163916,USD,163916,EX,CT,Sweden,L,Sweden,0,"Data Visualization, Java, Tableau",Associate,19,Education,2024-03-01,2024-03-30,1789,8.4,Machine Intelligence Group +AI11169,Deep Learning Engineer,82346,USD,82346,MI,FT,Israel,M,New Zealand,0,"Azure, GCP, Deep Learning, Scala",Bachelor,2,Transportation,2024-03-31,2024-05-30,522,8.2,TechCorp Inc +AI11170,AI Specialist,124224,JPY,13664640,SE,FT,Japan,S,Japan,50,"Computer Vision, Python, Azure",Associate,8,Manufacturing,2024-01-18,2024-03-08,965,7.5,DataVision Ltd +AI11171,AI Consultant,141596,USD,141596,SE,CT,Finland,M,Denmark,100,"MLOps, Linux, Kubernetes, Python, Statistics",Bachelor,8,Healthcare,2025-04-29,2025-07-09,1133,8.3,Algorithmic Solutions +AI11172,AI Research Scientist,36117,USD,36117,MI,PT,India,L,Colombia,50,"Mathematics, Git, Python",Bachelor,2,Manufacturing,2024-04-04,2024-05-22,684,5.2,Smart Analytics +AI11173,Data Engineer,72859,USD,72859,MI,FT,Ireland,S,Thailand,100,"Deep Learning, TensorFlow, Git, SQL, Java",Bachelor,4,Real Estate,2024-06-19,2024-08-27,1261,7.3,Autonomous Tech +AI11174,AI Software Engineer,145568,GBP,109176,SE,FT,United Kingdom,S,Estonia,50,"AWS, Python, Tableau, Git",Associate,9,Finance,2024-05-03,2024-05-28,595,6.6,Predictive Systems +AI11175,NLP Engineer,81162,GBP,60872,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, Statistics, NLP, R",Master,4,Transportation,2024-01-29,2024-03-10,1900,7,Quantum Computing Inc +AI11176,NLP Engineer,222942,EUR,189501,EX,PT,Netherlands,M,Netherlands,100,"Docker, Scala, Computer Vision, Linux",Associate,13,Manufacturing,2024-09-15,2024-10-15,1315,8.7,Digital Transformation LLC +AI11177,Computer Vision Engineer,241236,AUD,325669,EX,FL,Australia,M,India,50,"Statistics, Python, R, Linux, SQL",Bachelor,11,Transportation,2024-09-22,2024-11-29,1590,9.6,Autonomous Tech +AI11178,Data Analyst,79043,CAD,98804,EN,FL,Canada,L,Canada,0,"R, Linux, Python, Java",Associate,1,Healthcare,2025-04-10,2025-05-19,556,6.3,Neural Networks Co +AI11179,AI Specialist,118334,USD,118334,MI,PT,United States,M,Chile,50,"GCP, MLOps, Scala, Python",Bachelor,4,Gaming,2024-12-23,2025-01-25,616,9.6,Autonomous Tech +AI11180,Head of AI,90117,USD,90117,SE,PT,Israel,S,Israel,0,"Linux, NLP, PyTorch, Git",PhD,7,Government,2024-08-16,2024-09-24,971,9.9,Neural Networks Co +AI11181,AI Software Engineer,174435,USD,174435,SE,PT,Denmark,L,Denmark,0,"Computer Vision, Kubernetes, Tableau, Linux, Mathematics",PhD,7,Retail,2025-03-17,2025-05-07,2391,6.2,Machine Intelligence Group +AI11182,Machine Learning Researcher,118598,USD,118598,SE,PT,Sweden,L,Sweden,100,"Azure, Python, Mathematics, Kubernetes, AWS",PhD,6,Manufacturing,2024-05-11,2024-07-23,2052,9,Quantum Computing Inc +AI11183,Robotics Engineer,37061,USD,37061,MI,PT,China,S,Argentina,0,"SQL, Docker, Kubernetes, MLOps",PhD,4,Transportation,2025-01-28,2025-02-19,2380,6,Algorithmic Solutions +AI11184,AI Product Manager,229849,EUR,195372,EX,FT,Netherlands,S,Netherlands,100,"Kubernetes, SQL, Computer Vision, Mathematics",Master,17,Technology,2024-10-03,2024-11-08,1912,6.5,Cloud AI Solutions +AI11185,AI Research Scientist,178162,CHF,160346,MI,PT,Switzerland,L,Switzerland,50,"Python, Kubernetes, TensorFlow",Bachelor,4,Education,2024-12-15,2025-01-26,1263,7.9,Advanced Robotics +AI11186,Data Engineer,175805,GBP,131854,EX,CT,United Kingdom,L,Canada,100,"Spark, AWS, Azure, GCP",Bachelor,10,Healthcare,2025-04-22,2025-06-03,984,7.2,DeepTech Ventures +AI11187,Autonomous Systems Engineer,105402,USD,105402,MI,FT,Sweden,L,New Zealand,50,"Computer Vision, Data Visualization, Java",Bachelor,3,Finance,2024-05-11,2024-07-02,2493,9.7,DeepTech Ventures +AI11188,AI Software Engineer,33884,USD,33884,MI,PT,India,M,Luxembourg,50,"PyTorch, GCP, TensorFlow, Scala, Kubernetes",PhD,2,Retail,2024-09-03,2024-11-12,1283,9.6,Machine Intelligence Group +AI11189,Computer Vision Engineer,60249,USD,60249,EN,FL,Ireland,M,Ireland,50,"Data Visualization, Azure, Tableau, TensorFlow, Statistics",Master,0,Education,2024-01-02,2024-02-24,1904,6.3,Digital Transformation LLC +AI11190,NLP Engineer,81942,USD,81942,MI,FT,Finland,M,Finland,100,"Data Visualization, Hadoop, Scala, Tableau",PhD,2,Finance,2025-01-25,2025-03-18,1325,8.5,Smart Analytics +AI11191,ML Ops Engineer,76583,AUD,103387,EN,FT,Australia,M,Belgium,0,"Docker, Spark, TensorFlow, AWS, Computer Vision",Master,1,Government,2024-06-22,2024-08-06,2483,8.6,Algorithmic Solutions +AI11192,AI Specialist,61080,USD,61080,SE,PT,India,L,India,50,"Java, MLOps, Data Visualization, Spark, Statistics",PhD,5,Consulting,2024-03-22,2024-05-14,2326,9.5,Cloud AI Solutions +AI11193,Data Engineer,129718,GBP,97289,SE,CT,United Kingdom,S,United Kingdom,0,"Python, TensorFlow, Docker",Associate,9,Consulting,2024-04-30,2024-07-07,1768,5.2,Cloud AI Solutions +AI11194,AI Specialist,89873,GBP,67405,MI,CT,United Kingdom,S,United Kingdom,100,"Azure, Linux, Tableau, Docker",Master,3,Consulting,2025-03-05,2025-04-11,692,5.9,Neural Networks Co +AI11195,Data Scientist,203419,USD,203419,EX,PT,Finland,S,Finland,100,"Python, Kubernetes, TensorFlow, MLOps, Tableau",Master,10,Manufacturing,2025-04-27,2025-05-27,1819,9.1,Machine Intelligence Group +AI11196,Machine Learning Engineer,154964,CHF,139468,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, Git, Computer Vision, TensorFlow",Bachelor,7,Manufacturing,2024-12-01,2025-01-13,1378,9.5,Autonomous Tech +AI11197,ML Ops Engineer,127404,USD,127404,EX,CT,Israel,S,Austria,100,"TensorFlow, Git, Python, Java",Bachelor,16,Transportation,2024-07-24,2024-09-08,2469,5.1,AI Innovations +AI11198,Head of AI,112946,EUR,96004,MI,PT,Austria,L,Austria,100,"Kubernetes, Linux, Scala, Java, Mathematics",Master,2,Real Estate,2024-10-23,2024-11-15,1555,5.3,AI Innovations +AI11199,Head of AI,166982,CHF,150284,SE,FL,Switzerland,L,Switzerland,0,"GCP, Kubernetes, Mathematics, AWS, Statistics",Master,5,Consulting,2024-04-18,2024-06-19,1128,7,Future Systems +AI11200,AI Architect,79897,USD,79897,EN,FT,Ireland,L,Ireland,0,"Java, Python, R, Kubernetes",Associate,1,Technology,2024-04-11,2024-04-29,1307,6,Algorithmic Solutions +AI11201,Machine Learning Researcher,199034,CHF,179131,EX,CT,Switzerland,S,Switzerland,0,"Linux, Deep Learning, Computer Vision, GCP, Git",PhD,13,Energy,2024-05-27,2024-06-14,2002,7.9,Advanced Robotics +AI11202,Robotics Engineer,121505,USD,121505,MI,CT,United States,L,Mexico,0,"Deep Learning, PyTorch, Kubernetes, Docker, TensorFlow",Bachelor,3,Transportation,2024-12-20,2025-02-22,505,9.6,Neural Networks Co +AI11203,AI Specialist,98949,EUR,84107,SE,FT,Austria,S,Austria,0,"SQL, Git, Docker, TensorFlow, NLP",Bachelor,9,Media,2024-03-12,2024-05-14,2235,7.3,Predictive Systems +AI11204,Autonomous Systems Engineer,175782,USD,175782,EX,PT,Sweden,S,Sweden,50,"Hadoop, GCP, NLP",Master,10,Automotive,2025-03-12,2025-05-08,909,7.6,Cloud AI Solutions +AI11205,Data Engineer,204328,EUR,173679,EX,CT,Netherlands,L,Russia,50,"Linux, R, Azure, Deep Learning",Associate,13,Automotive,2024-08-26,2024-10-17,747,7.8,Quantum Computing Inc +AI11206,Machine Learning Researcher,47111,USD,47111,EN,PT,Ireland,S,Ireland,50,"Python, Git, Hadoop, GCP, Deep Learning",Master,0,Transportation,2024-04-08,2024-05-01,2498,7.9,Smart Analytics +AI11207,Data Analyst,97477,GBP,73108,MI,PT,United Kingdom,S,United Kingdom,100,"Python, Docker, TensorFlow, Statistics, Java",Associate,3,Real Estate,2024-08-05,2024-09-09,1609,5.2,DeepTech Ventures +AI11208,ML Ops Engineer,45439,USD,45439,SE,CT,India,S,India,0,"Mathematics, SQL, Deep Learning, PyTorch",Associate,5,Manufacturing,2024-11-16,2024-12-24,1674,9.8,Quantum Computing Inc +AI11209,ML Ops Engineer,268419,GBP,201314,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, Spark, Python",Master,11,Technology,2024-07-12,2024-08-31,2445,5.6,DeepTech Ventures +AI11210,Head of AI,42030,USD,42030,MI,FT,India,L,Germany,50,"Git, Statistics, Data Visualization, Python, Deep Learning",Bachelor,2,Real Estate,2025-04-11,2025-06-18,1712,6.3,Quantum Computing Inc +AI11211,Research Scientist,134524,USD,134524,SE,FT,Finland,M,Finland,100,"PyTorch, MLOps, Deep Learning",Master,9,Real Estate,2024-03-21,2024-05-13,2193,9,Future Systems +AI11212,AI Research Scientist,178034,USD,178034,EX,FT,Israel,M,Chile,0,"PyTorch, Deep Learning, MLOps, Hadoop, Linux",Bachelor,19,Healthcare,2024-01-17,2024-03-28,2436,9.8,DeepTech Ventures +AI11213,AI Product Manager,79119,USD,79119,MI,PT,Sweden,S,Sweden,100,"Spark, Git, Statistics, Deep Learning, PyTorch",Associate,4,Manufacturing,2024-03-20,2024-05-11,1637,7.7,TechCorp Inc +AI11214,AI Product Manager,168770,USD,168770,EX,PT,Ireland,L,India,50,"PyTorch, TensorFlow, Docker, Mathematics",Associate,15,Transportation,2024-11-09,2024-12-28,1740,6.8,Cognitive Computing +AI11215,Machine Learning Researcher,65252,AUD,88090,EN,FT,Australia,M,Australia,100,"Computer Vision, Mathematics, NLP, Git, MLOps",Bachelor,1,Education,2025-01-15,2025-02-26,1035,6.7,DataVision Ltd +AI11216,Autonomous Systems Engineer,163792,GBP,122844,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, SQL, TensorFlow, Azure, Statistics",Associate,14,Retail,2024-07-25,2024-08-25,664,8.4,Cognitive Computing +AI11217,Machine Learning Engineer,196273,USD,196273,SE,FT,Norway,M,Thailand,0,"Mathematics, PyTorch, Scala, Azure",Master,5,Consulting,2024-09-30,2024-10-16,1052,7,Advanced Robotics +AI11218,Machine Learning Researcher,50242,EUR,42706,EN,CT,France,M,Australia,50,"Python, Java, NLP",Associate,0,Government,2025-03-31,2025-04-29,690,7.3,DeepTech Ventures +AI11219,Machine Learning Engineer,262801,USD,262801,EX,FL,Sweden,L,Sweden,50,"Data Visualization, SQL, Hadoop, MLOps",Associate,19,Transportation,2024-05-07,2024-06-14,1769,6.1,Advanced Robotics +AI11220,Data Analyst,61263,EUR,52074,EN,FL,Germany,L,Singapore,0,"Spark, Hadoop, Statistics, Linux, Python",PhD,0,Real Estate,2024-09-20,2024-10-22,892,9.5,Autonomous Tech +AI11221,ML Ops Engineer,146528,CHF,131875,MI,PT,Switzerland,M,Switzerland,50,"Azure, Python, TensorFlow, Docker",Associate,3,Consulting,2025-02-07,2025-03-22,2279,9.9,Predictive Systems +AI11222,AI Product Manager,163758,USD,163758,SE,FT,Norway,S,Norway,50,"Kubernetes, MLOps, Scala, AWS",Master,9,Media,2024-11-19,2024-12-18,1651,7.6,Algorithmic Solutions +AI11223,AI Research Scientist,166269,JPY,18289590,EX,CT,Japan,L,Japan,0,"Git, Python, Hadoop",Associate,16,Manufacturing,2024-04-18,2024-06-11,2443,8.9,Machine Intelligence Group +AI11224,Autonomous Systems Engineer,233000,EUR,198050,EX,CT,France,M,France,50,"Mathematics, Docker, Kubernetes",PhD,10,Healthcare,2025-01-02,2025-01-17,778,8,DeepTech Ventures +AI11225,AI Research Scientist,91649,USD,91649,MI,PT,United States,S,Ireland,50,"Java, Statistics, Data Visualization, Git, SQL",Associate,4,Media,2024-02-06,2024-03-14,1886,9.4,TechCorp Inc +AI11226,Machine Learning Researcher,152617,CHF,137355,SE,CT,Switzerland,M,Denmark,50,"Java, Mathematics, Kubernetes, Python, Scala",Bachelor,5,Transportation,2024-03-01,2024-04-18,2489,9,Autonomous Tech +AI11227,Deep Learning Engineer,111739,USD,111739,SE,FT,Finland,S,Finland,0,"TensorFlow, Tableau, Spark, GCP, SQL",Bachelor,5,Healthcare,2024-04-14,2024-05-19,2451,7.4,Algorithmic Solutions +AI11228,NLP Engineer,66659,EUR,56660,EN,PT,France,M,Mexico,50,"Tableau, Python, Scala",Bachelor,0,Automotive,2024-01-07,2024-01-22,1040,7.9,Cognitive Computing +AI11229,Machine Learning Engineer,186273,AUD,251469,EX,CT,Australia,L,Australia,50,"Data Visualization, Docker, Tableau, Java",Bachelor,14,Consulting,2024-05-25,2024-07-13,1691,5.6,Algorithmic Solutions +AI11230,AI Specialist,165955,USD,165955,EX,CT,Finland,L,India,100,"TensorFlow, Data Visualization, Tableau, Statistics, AWS",Bachelor,15,Education,2024-10-23,2024-11-29,603,8.8,AI Innovations +AI11231,Data Scientist,206355,EUR,175402,EX,CT,Germany,M,Germany,50,"Linux, Computer Vision, PyTorch, TensorFlow",PhD,14,Government,2024-09-09,2024-10-19,1908,5.4,Digital Transformation LLC +AI11232,Data Analyst,28132,USD,28132,EN,CT,India,M,Argentina,100,"Computer Vision, PyTorch, Spark",Bachelor,1,Energy,2025-01-05,2025-03-18,1774,7.4,Cloud AI Solutions +AI11233,Research Scientist,105432,USD,105432,EX,CT,China,M,China,0,"Spark, Kubernetes, Java, Statistics, TensorFlow",Bachelor,17,Energy,2024-07-19,2024-08-24,2474,7.7,Digital Transformation LLC +AI11234,Machine Learning Engineer,84482,USD,84482,EN,CT,United States,S,Malaysia,100,"Docker, Scala, NLP, AWS",Associate,1,Media,2024-06-27,2024-07-17,2399,5.2,Advanced Robotics +AI11235,Data Analyst,207967,USD,207967,EX,PT,Finland,S,Estonia,0,"Statistics, Mathematics, PyTorch",Master,11,Telecommunications,2024-02-17,2024-04-04,586,7.5,Machine Intelligence Group +AI11236,AI Product Manager,105835,USD,105835,MI,FT,Ireland,M,Ireland,0,"Azure, GCP, Git, AWS",PhD,4,Energy,2024-05-14,2024-07-20,1077,5.6,Predictive Systems +AI11237,Data Scientist,90084,USD,90084,MI,CT,Ireland,L,Japan,50,"R, SQL, Python, Spark, Deep Learning",Associate,3,Transportation,2025-03-24,2025-05-04,1376,5.1,Machine Intelligence Group +AI11238,AI Architect,70560,AUD,95256,EN,FT,Australia,M,Australia,50,"Python, TensorFlow, Java, Spark",Bachelor,0,Finance,2024-01-11,2024-03-09,1687,7.2,Neural Networks Co +AI11239,Data Scientist,119651,EUR,101703,SE,FL,France,S,France,0,"Linux, Python, Statistics, Kubernetes",Master,5,Media,2024-12-29,2025-03-11,1854,7.6,Digital Transformation LLC +AI11240,Deep Learning Engineer,81359,EUR,69155,EN,PT,Netherlands,L,Estonia,100,"Linux, Python, Spark, Computer Vision, Statistics",Bachelor,1,Consulting,2025-03-24,2025-05-11,607,8,Neural Networks Co +AI11241,Head of AI,94506,USD,94506,MI,CT,Ireland,M,Spain,0,"PyTorch, Deep Learning, MLOps",Master,3,Manufacturing,2024-02-08,2024-02-24,854,8.2,Digital Transformation LLC +AI11242,AI Consultant,57555,CAD,71944,EN,FT,Canada,S,Canada,0,"Git, Java, SQL",Bachelor,1,Gaming,2025-01-14,2025-03-01,993,8.6,TechCorp Inc +AI11243,AI Architect,58309,USD,58309,MI,FL,China,L,China,50,"Java, Linux, Tableau, Mathematics",Bachelor,4,Healthcare,2024-07-20,2024-09-03,671,7.1,Cognitive Computing +AI11244,Data Analyst,104581,USD,104581,MI,FT,United States,L,United States,100,"Python, Tableau, AWS",Associate,3,Retail,2024-02-07,2024-03-08,1281,9.1,Smart Analytics +AI11245,AI Architect,51087,USD,51087,SE,FT,China,M,China,50,"Data Visualization, Git, Kubernetes, Spark, R",PhD,8,Government,2024-01-22,2024-02-24,1657,7.2,Autonomous Tech +AI11246,Robotics Engineer,163866,CHF,147479,MI,FT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Deep Learning, AWS, Linux",PhD,3,Media,2024-04-01,2024-05-04,1667,5.9,DataVision Ltd +AI11247,Data Analyst,48310,USD,48310,EN,CT,Finland,M,Finland,50,"Data Visualization, Kubernetes, Scala",Associate,1,Transportation,2025-04-24,2025-05-29,1452,8.1,Digital Transformation LLC +AI11248,Machine Learning Engineer,189402,USD,189402,SE,FT,Denmark,L,Denmark,100,"Hadoop, GCP, Tableau, Computer Vision",Associate,8,Automotive,2025-03-05,2025-03-30,1720,6.8,Smart Analytics +AI11249,Robotics Engineer,30514,USD,30514,MI,FT,India,L,Czech Republic,0,"Python, Git, TensorFlow, Deep Learning, PyTorch",Bachelor,4,Media,2025-03-30,2025-04-13,1193,5.6,Predictive Systems +AI11250,AI Consultant,69642,GBP,52232,EN,PT,United Kingdom,L,Kenya,50,"Spark, Python, Computer Vision, Data Visualization, TensorFlow",Bachelor,0,Telecommunications,2024-09-17,2024-11-25,1878,10,Future Systems +AI11251,Head of AI,117224,JPY,12894640,SE,FT,Japan,S,South Africa,100,"AWS, R, PyTorch, Java, SQL",Bachelor,5,Media,2024-05-22,2024-06-16,2113,7.6,Digital Transformation LLC +AI11252,Computer Vision Engineer,100484,CAD,125605,MI,FL,Canada,L,Canada,50,"Java, Hadoop, PyTorch, AWS, TensorFlow",PhD,3,Consulting,2024-02-20,2024-04-02,2263,6.1,DeepTech Ventures +AI11253,AI Software Engineer,124618,CHF,112156,EN,PT,Switzerland,L,Switzerland,50,"Git, Python, R, Statistics",PhD,0,Transportation,2024-09-14,2024-10-05,1843,9.9,Future Systems +AI11254,AI Product Manager,191724,USD,191724,EX,FL,Ireland,S,Ireland,50,"Python, Hadoop, Spark, Docker",PhD,18,Education,2024-03-26,2024-06-01,2039,9.3,Machine Intelligence Group +AI11255,ML Ops Engineer,97569,USD,97569,EN,CT,Denmark,M,Denmark,100,"NLP, Statistics, SQL, PyTorch, Linux",Master,0,Education,2024-02-12,2024-03-25,2263,9.5,TechCorp Inc +AI11256,Computer Vision Engineer,118684,USD,118684,SE,CT,Finland,L,Finland,100,"Scala, Python, Statistics, Linux",PhD,9,Manufacturing,2024-08-29,2024-10-17,1785,6,DeepTech Ventures +AI11257,Deep Learning Engineer,80305,CHF,72275,EN,FL,Switzerland,S,Switzerland,50,"Git, GCP, SQL, Spark, Docker",PhD,1,Healthcare,2024-10-22,2024-12-02,1862,6.3,Machine Intelligence Group +AI11258,Principal Data Scientist,214921,USD,214921,EX,CT,Sweden,S,India,100,"Kubernetes, AWS, GCP, Git, Spark",PhD,17,Retail,2024-02-01,2024-03-15,1894,6,Predictive Systems +AI11259,AI Architect,178983,CHF,161085,SE,PT,Switzerland,L,Germany,100,"Java, TensorFlow, Hadoop",Associate,9,Transportation,2024-11-26,2024-12-30,1204,9.5,Algorithmic Solutions +AI11260,AI Product Manager,78327,USD,78327,MI,PT,Finland,L,Finland,50,"Spark, AWS, SQL, Tableau",Associate,4,Finance,2025-02-14,2025-03-28,2387,6.1,Predictive Systems +AI11261,Robotics Engineer,85793,USD,85793,EN,FL,Denmark,S,Denmark,0,"AWS, Java, GCP, PyTorch",Associate,0,Telecommunications,2024-07-25,2024-09-09,866,7.7,Predictive Systems +AI11262,AI Specialist,80644,EUR,68547,EN,FT,Netherlands,L,Netherlands,50,"Git, GCP, Java, Python, Computer Vision",Master,1,Energy,2025-04-08,2025-05-24,2017,6,DataVision Ltd +AI11263,AI Specialist,123929,SGD,161108,MI,CT,Singapore,L,Singapore,50,"PyTorch, TensorFlow, Mathematics, Deep Learning, Git",Bachelor,2,Automotive,2024-05-08,2024-06-25,1499,8.7,Algorithmic Solutions +AI11264,AI Research Scientist,108923,USD,108923,MI,FT,Finland,L,New Zealand,0,"Linux, Docker, Deep Learning, PyTorch",Master,4,Media,2024-09-28,2024-11-21,2273,9.3,AI Innovations +AI11265,Machine Learning Engineer,140940,USD,140940,SE,FL,South Korea,L,South Korea,50,"R, PyTorch, Computer Vision",Bachelor,9,Media,2024-10-03,2024-11-11,1587,8.4,Cognitive Computing +AI11266,NLP Engineer,315420,CHF,283878,EX,PT,Switzerland,L,Switzerland,100,"MLOps, SQL, PyTorch, Linux",PhD,13,Education,2024-10-14,2024-12-14,1791,9.4,TechCorp Inc +AI11267,Head of AI,71258,CAD,89073,EN,FL,Canada,M,Thailand,50,"GCP, Spark, Azure, PyTorch",Master,1,Technology,2024-05-29,2024-07-22,2017,5.9,Digital Transformation LLC +AI11268,Data Engineer,105428,JPY,11597080,MI,PT,Japan,L,Japan,0,"SQL, Python, Java, Tableau, TensorFlow",Associate,4,Technology,2025-03-29,2025-04-29,1302,5.6,Future Systems +AI11269,Data Scientist,167067,EUR,142007,EX,PT,France,L,Hungary,50,"Linux, PyTorch, Git, AWS, Java",Associate,12,Retail,2025-03-24,2025-04-15,1311,9.3,DeepTech Ventures +AI11270,Computer Vision Engineer,75062,USD,75062,EN,FT,Denmark,S,Denmark,50,"AWS, TensorFlow, Computer Vision, NLP",PhD,0,Gaming,2024-04-26,2024-06-17,2110,7,Cognitive Computing +AI11271,Computer Vision Engineer,54168,USD,54168,EX,FL,India,M,India,100,"Scala, PyTorch, Computer Vision, TensorFlow",PhD,10,Education,2024-04-09,2024-05-17,1658,7.9,Cognitive Computing +AI11272,Data Analyst,61930,SGD,80509,EN,PT,Singapore,M,Singapore,0,"Git, Computer Vision, SQL, Python, MLOps",Master,0,Consulting,2024-11-25,2025-01-08,1655,7.3,AI Innovations +AI11273,AI Product Manager,148519,EUR,126241,EX,PT,Austria,M,Austria,100,"Computer Vision, Data Visualization, Python",Master,11,Gaming,2025-04-27,2025-05-21,669,7.5,Smart Analytics +AI11274,Deep Learning Engineer,199528,USD,199528,EX,PT,Norway,S,Norway,100,"Python, Git, Computer Vision, TensorFlow",PhD,12,Finance,2024-02-08,2024-03-17,544,6.2,Quantum Computing Inc +AI11275,AI Architect,53596,USD,53596,EX,FL,India,S,India,50,"Azure, MLOps, Statistics, PyTorch, Computer Vision",Associate,11,Gaming,2024-11-09,2024-12-30,2407,9.4,Autonomous Tech +AI11276,Head of AI,97034,USD,97034,EN,CT,Denmark,M,Denmark,50,"PyTorch, Kubernetes, Deep Learning, Linux, Azure",Master,0,Media,2024-05-24,2024-07-01,1585,5.5,Cognitive Computing +AI11277,ML Ops Engineer,102547,AUD,138438,SE,FT,Australia,S,Australia,100,"Deep Learning, Python, Hadoop",Bachelor,5,Telecommunications,2024-05-07,2024-07-10,1872,7.2,Smart Analytics +AI11278,Machine Learning Engineer,63599,SGD,82679,EN,FT,Singapore,M,Singapore,50,"NLP, SQL, MLOps",Bachelor,1,Manufacturing,2024-10-17,2024-12-12,1319,6.6,Cloud AI Solutions +AI11279,Computer Vision Engineer,93730,EUR,79671,MI,FL,Austria,L,Austria,100,"Scala, Python, Mathematics, Kubernetes, Spark",Bachelor,4,Automotive,2024-11-08,2024-12-08,1254,6.8,DataVision Ltd +AI11280,AI Architect,205424,USD,205424,SE,FL,United States,L,Austria,100,"Data Visualization, Hadoop, Scala, PyTorch, Spark",Associate,7,Gaming,2024-04-03,2024-05-20,2330,8.7,Cognitive Computing +AI11281,Computer Vision Engineer,88065,USD,88065,EN,FL,Denmark,S,Denmark,100,"Linux, R, PyTorch, TensorFlow, Spark",Bachelor,1,Gaming,2025-03-23,2025-04-28,2085,5.6,Cloud AI Solutions +AI11282,ML Ops Engineer,115890,USD,115890,SE,FL,Israel,M,Israel,50,"PyTorch, GCP, Git",Master,9,Transportation,2024-11-04,2024-12-13,1762,7.5,AI Innovations +AI11283,Data Analyst,233264,SGD,303243,EX,CT,Singapore,S,Singapore,100,"Kubernetes, Scala, Tableau, Deep Learning",Associate,11,Telecommunications,2024-06-15,2024-08-03,814,6.1,Digital Transformation LLC +AI11284,AI Consultant,85232,EUR,72447,MI,FT,France,M,France,100,"Linux, Scala, Statistics, Python",PhD,3,Energy,2024-10-01,2024-11-26,2152,9.3,Predictive Systems +AI11285,AI Product Manager,125339,CHF,112805,MI,CT,Switzerland,M,Switzerland,0,"Python, Mathematics, Docker",PhD,2,Retail,2025-02-19,2025-05-02,1397,9.6,DataVision Ltd +AI11286,Research Scientist,185360,USD,185360,EX,CT,Ireland,L,Ireland,50,"NLP, Kubernetes, Docker, Python",Master,16,Retail,2024-01-23,2024-02-18,1618,7.8,Neural Networks Co +AI11287,Head of AI,106629,EUR,90635,MI,CT,France,L,France,0,"Data Visualization, Python, Azure, Scala",Bachelor,3,Retail,2025-02-06,2025-04-10,1496,8.7,Cloud AI Solutions +AI11288,Computer Vision Engineer,97894,USD,97894,EX,PT,India,L,India,0,"Scala, Java, Linux, R, SQL",PhD,13,Gaming,2025-01-01,2025-01-26,1062,9.3,Digital Transformation LLC +AI11289,Research Scientist,79189,USD,79189,EX,PT,India,M,Canada,50,"Java, Kubernetes, Scala",Master,12,Consulting,2024-05-06,2024-07-03,2204,9,Advanced Robotics +AI11290,AI Consultant,89489,JPY,9843790,MI,CT,Japan,L,Japan,50,"Docker, SQL, PyTorch",PhD,3,Retail,2024-11-24,2025-01-17,1809,6.4,AI Innovations +AI11291,Head of AI,119280,USD,119280,MI,CT,Israel,L,Netherlands,0,"Docker, Spark, Kubernetes, Scala, Mathematics",PhD,2,Manufacturing,2024-02-28,2024-05-05,716,7.1,DeepTech Ventures +AI11292,Robotics Engineer,219065,EUR,186205,EX,FT,Germany,S,Germany,0,"Python, Spark, Tableau",Associate,16,Manufacturing,2024-02-21,2024-03-13,800,7.6,TechCorp Inc +AI11293,Head of AI,218346,SGD,283850,EX,PT,Singapore,S,Singapore,50,"TensorFlow, Linux, GCP, Computer Vision, Deep Learning",Master,15,Finance,2024-05-22,2024-07-24,1652,9.7,Algorithmic Solutions +AI11294,AI Specialist,154420,SGD,200746,SE,CT,Singapore,M,Singapore,100,"Python, Git, Spark, Scala, Azure",Associate,7,Technology,2024-04-21,2024-06-29,645,8.8,Neural Networks Co +AI11295,AI Specialist,126566,USD,126566,SE,PT,Denmark,S,Norway,50,"Python, Data Visualization, Statistics",Bachelor,6,Consulting,2025-01-05,2025-01-28,1877,6.3,Cognitive Computing +AI11296,NLP Engineer,67525,AUD,91159,EN,FT,Australia,S,Australia,100,"Python, TensorFlow, Linux, AWS",Master,0,Gaming,2024-02-07,2024-04-03,1711,9.2,Digital Transformation LLC +AI11297,Research Scientist,130551,SGD,169716,SE,PT,Singapore,M,Singapore,0,"SQL, Kubernetes, Python, MLOps, Scala",Master,8,Telecommunications,2025-02-03,2025-03-04,890,7.7,Machine Intelligence Group +AI11298,Robotics Engineer,67815,USD,67815,EN,FL,Sweden,L,Sweden,0,"GCP, Scala, Kubernetes, Deep Learning",Master,1,Real Estate,2024-06-15,2024-07-30,2103,9.3,TechCorp Inc +AI11299,Data Scientist,26237,USD,26237,MI,CT,India,S,India,50,"MLOps, Git, SQL, Azure, Statistics",PhD,3,Transportation,2024-09-28,2024-11-27,850,5.9,Machine Intelligence Group +AI11300,Data Scientist,285608,SGD,371290,EX,PT,Singapore,L,Singapore,0,"PyTorch, Statistics, Computer Vision, GCP, Mathematics",PhD,10,Media,2025-01-09,2025-02-21,953,5.4,Autonomous Tech +AI11301,Machine Learning Engineer,73386,USD,73386,EN,FT,South Korea,L,South Korea,0,"Scala, Python, TensorFlow, Git, Hadoop",Associate,0,Manufacturing,2024-05-15,2024-07-03,1736,9.8,Autonomous Tech +AI11302,AI Specialist,24994,USD,24994,EN,CT,China,S,China,0,"Java, Kubernetes, GCP, Docker",Bachelor,0,Media,2024-04-08,2024-05-15,1010,7.6,Advanced Robotics +AI11303,Machine Learning Researcher,84205,AUD,113677,MI,FL,Australia,M,Australia,100,"Hadoop, MLOps, PyTorch, Scala, Kubernetes",Master,3,Energy,2024-06-17,2024-07-02,2481,9,Smart Analytics +AI11304,Deep Learning Engineer,167419,USD,167419,EX,FL,Israel,S,Australia,100,"AWS, Mathematics, Scala",Bachelor,11,Consulting,2024-08-10,2024-09-19,2109,6.1,Neural Networks Co +AI11305,Data Engineer,83819,EUR,71246,EN,CT,Austria,L,Austria,50,"Spark, Deep Learning, TensorFlow, Python, Git",Bachelor,1,Telecommunications,2025-04-05,2025-06-08,2018,7.8,Autonomous Tech +AI11306,Data Scientist,71467,USD,71467,EX,CT,China,M,China,100,"Python, Kubernetes, Tableau, Computer Vision",Master,11,Telecommunications,2024-09-05,2024-09-23,1673,5.8,Predictive Systems +AI11307,AI Specialist,150771,EUR,128155,SE,PT,Netherlands,L,Finland,0,"PyTorch, Kubernetes, Mathematics, Git",Master,5,Media,2025-02-08,2025-02-24,835,7.9,Cloud AI Solutions +AI11308,Autonomous Systems Engineer,187205,USD,187205,EX,FT,Finland,S,Finland,0,"Python, Scala, Git",Bachelor,15,Manufacturing,2024-05-09,2024-05-31,1333,9.2,Quantum Computing Inc +AI11309,AI Architect,25891,USD,25891,EN,FT,China,M,China,50,"SQL, Scala, Deep Learning",PhD,1,Automotive,2024-10-04,2024-12-05,2089,5.4,Cloud AI Solutions +AI11310,Machine Learning Researcher,62044,USD,62044,SE,CT,China,M,France,0,"Deep Learning, Statistics, SQL",Bachelor,5,Automotive,2025-02-13,2025-03-18,2477,6.4,DeepTech Ventures +AI11311,Data Scientist,155807,USD,155807,SE,CT,Israel,L,Israel,100,"Computer Vision, MLOps, Linux, TensorFlow",PhD,6,Real Estate,2024-07-22,2024-09-07,1354,9.4,Advanced Robotics +AI11312,Autonomous Systems Engineer,75916,EUR,64529,EN,FL,Netherlands,S,Netherlands,50,"TensorFlow, Mathematics, Java, MLOps, SQL",Associate,1,Gaming,2024-01-30,2024-03-29,708,7.8,Machine Intelligence Group +AI11313,Autonomous Systems Engineer,93324,SGD,121321,EN,FL,Singapore,L,Singapore,50,"Azure, GCP, Computer Vision, Deep Learning",PhD,1,Manufacturing,2024-04-18,2024-05-19,1592,9.6,Digital Transformation LLC +AI11314,Research Scientist,176161,EUR,149737,EX,FL,France,M,France,50,"Scala, Computer Vision, Azure",Bachelor,11,Real Estate,2024-12-10,2025-02-04,1294,9.5,Autonomous Tech +AI11315,ML Ops Engineer,135633,CAD,169541,SE,CT,Canada,L,Canada,100,"Python, GCP, TensorFlow",PhD,9,Manufacturing,2025-04-11,2025-05-30,2051,8,Future Systems +AI11316,Computer Vision Engineer,96084,USD,96084,MI,FT,Ireland,S,Thailand,50,"Kubernetes, Java, R, Deep Learning",Master,4,Real Estate,2024-06-19,2024-07-20,2346,9.6,AI Innovations +AI11317,AI Product Manager,229922,CHF,206930,EX,FT,Switzerland,M,Switzerland,50,"Python, TensorFlow, Scala, Kubernetes",Associate,15,Transportation,2025-01-14,2025-02-24,1777,7.5,Neural Networks Co +AI11318,AI Research Scientist,92771,USD,92771,EN,CT,Denmark,L,Denmark,50,"Git, Kubernetes, Python",Bachelor,1,Transportation,2024-09-10,2024-10-17,1267,9.4,Predictive Systems +AI11319,Machine Learning Engineer,137444,JPY,15118840,SE,FL,Japan,L,Japan,100,"Docker, Linux, Tableau, NLP, Mathematics",Associate,6,Energy,2024-01-14,2024-03-05,2117,5.1,Neural Networks Co +AI11320,Research Scientist,72988,CAD,91235,EN,FL,Canada,L,Canada,100,"Git, Python, Java, AWS, Scala",Associate,0,Automotive,2024-05-16,2024-06-12,1189,7.7,Smart Analytics +AI11321,Autonomous Systems Engineer,129227,USD,129227,SE,PT,Denmark,S,Denmark,0,"Python, TensorFlow, Git, Deep Learning",Bachelor,8,Automotive,2024-09-05,2024-10-31,1294,6.7,Future Systems +AI11322,ML Ops Engineer,84467,USD,84467,EN,FT,Ireland,L,Ireland,0,"SQL, Docker, Computer Vision",Master,0,Transportation,2025-01-15,2025-03-20,1191,9.7,Predictive Systems +AI11323,Data Analyst,98088,GBP,73566,MI,FL,United Kingdom,L,United Kingdom,0,"PyTorch, Mathematics, Git, Kubernetes, Python",Master,3,Government,2024-05-09,2024-07-11,988,7.3,Cloud AI Solutions +AI11324,Research Scientist,119116,USD,119116,SE,PT,Sweden,S,Sweden,100,"Docker, Linux, Mathematics, Deep Learning",PhD,9,Consulting,2024-03-26,2024-04-21,1723,6.2,Predictive Systems +AI11325,Autonomous Systems Engineer,181037,USD,181037,EX,FL,Ireland,M,Ireland,100,"Linux, Spark, NLP",PhD,18,Energy,2024-09-11,2024-11-23,1753,5.3,Digital Transformation LLC +AI11326,AI Consultant,79650,JPY,8761500,EN,FT,Japan,M,Thailand,50,"Tableau, GCP, PyTorch, MLOps, TensorFlow",PhD,1,Telecommunications,2025-04-06,2025-06-07,1950,9.7,Cognitive Computing +AI11327,Robotics Engineer,81235,CHF,73112,EN,FL,Switzerland,M,Switzerland,50,"R, Spark, Python, Azure",Bachelor,0,Government,2024-04-01,2024-06-08,1105,7.9,Neural Networks Co +AI11328,AI Architect,71268,EUR,60578,EN,CT,Netherlands,M,Netherlands,50,"Tableau, MLOps, Kubernetes, Scala, Mathematics",PhD,1,Telecommunications,2025-03-14,2025-04-10,630,5.3,Autonomous Tech +AI11329,AI Product Manager,227826,CAD,284783,EX,PT,Canada,M,Canada,50,"R, Scala, PyTorch, Python, Linux",Master,13,Technology,2024-08-30,2024-10-07,1875,6.1,Future Systems +AI11330,Robotics Engineer,96577,USD,96577,MI,PT,Ireland,L,Romania,50,"Deep Learning, Spark, Computer Vision, Scala",PhD,3,Energy,2025-04-18,2025-06-01,1204,7.4,Cognitive Computing +AI11331,Data Analyst,32109,USD,32109,EN,CT,China,L,China,0,"Git, NLP, Data Visualization, Mathematics, Linux",Associate,1,Transportation,2024-02-12,2024-03-10,2181,7.1,Smart Analytics +AI11332,AI Architect,125192,USD,125192,EX,PT,China,L,China,0,"MLOps, Deep Learning, R, SQL",Master,14,Manufacturing,2025-03-17,2025-04-21,1763,9.2,Quantum Computing Inc +AI11333,Machine Learning Researcher,70652,JPY,7771720,EN,FL,Japan,L,Japan,100,"Computer Vision, SQL, Linux, Tableau, Git",Bachelor,1,Transportation,2024-12-25,2025-01-15,2207,6,Quantum Computing Inc +AI11334,NLP Engineer,114477,USD,114477,SE,FT,South Korea,L,South Korea,100,"MLOps, Data Visualization, Azure, Docker",Master,7,Gaming,2024-07-12,2024-09-13,2184,7.6,TechCorp Inc +AI11335,Robotics Engineer,46341,USD,46341,EN,CT,South Korea,S,South Korea,100,"Kubernetes, Tableau, NLP, Spark, Linux",Associate,1,Technology,2024-04-05,2024-05-09,2226,7.3,Cognitive Computing +AI11336,Research Scientist,68397,USD,68397,MI,PT,Israel,M,Israel,50,"Tableau, Scala, GCP",Master,4,Automotive,2024-05-05,2024-06-27,1629,7.2,AI Innovations +AI11337,Machine Learning Researcher,87051,USD,87051,MI,FL,Finland,S,Finland,100,"Linux, Java, Data Visualization, Computer Vision",PhD,4,Government,2025-03-20,2025-04-11,1691,9.9,AI Innovations +AI11338,AI Architect,79887,USD,79887,EN,FT,United States,L,United States,0,"Computer Vision, SQL, R",Bachelor,0,Automotive,2025-02-24,2025-04-28,1084,8.7,Smart Analytics +AI11339,Deep Learning Engineer,134547,EUR,114365,EX,FT,France,S,Turkey,50,"Computer Vision, Python, Tableau, TensorFlow, Statistics",Associate,19,Consulting,2024-05-13,2024-07-07,2369,9.9,Algorithmic Solutions +AI11340,Deep Learning Engineer,108427,EUR,92163,MI,FL,Austria,L,Austria,0,"Tableau, GCP, Linux",Associate,2,Real Estate,2024-01-16,2024-02-05,2062,8.8,Smart Analytics +AI11341,Research Scientist,45769,EUR,38904,EN,FL,Austria,S,Canada,50,"Data Visualization, Hadoop, Mathematics, Kubernetes",Bachelor,1,Technology,2024-07-09,2024-08-09,2381,5.1,Digital Transformation LLC +AI11342,Research Scientist,65686,EUR,55833,EN,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, Git, Scala, MLOps",PhD,1,Telecommunications,2024-10-01,2024-12-09,1542,7.1,Future Systems +AI11343,AI Research Scientist,134629,USD,134629,EX,PT,Israel,M,Israel,0,"R, GCP, Docker, Kubernetes",Bachelor,16,Consulting,2025-04-07,2025-05-25,1542,8.7,Quantum Computing Inc +AI11344,Machine Learning Engineer,105266,USD,105266,EN,FT,Norway,L,Romania,100,"Python, TensorFlow, Kubernetes, PyTorch",Bachelor,0,Government,2024-10-01,2024-11-13,1447,8.2,AI Innovations +AI11345,ML Ops Engineer,111826,CAD,139783,SE,CT,Canada,L,New Zealand,0,"Linux, Python, AWS, SQL",Associate,9,Automotive,2025-02-26,2025-04-29,949,8.1,Advanced Robotics +AI11346,Robotics Engineer,97870,USD,97870,SE,FL,Sweden,S,Norway,0,"Spark, Deep Learning, R",Associate,8,Energy,2024-01-26,2024-03-14,582,9.6,Future Systems +AI11347,NLP Engineer,56233,USD,56233,SE,CT,China,S,China,50,"Tableau, SQL, PyTorch, MLOps, Docker",PhD,9,Manufacturing,2024-05-14,2024-07-03,710,6,TechCorp Inc +AI11348,Data Scientist,136380,AUD,184113,SE,CT,Australia,M,Australia,100,"Hadoop, Docker, Scala",Bachelor,5,Real Estate,2025-02-05,2025-03-17,711,8.6,Cloud AI Solutions +AI11349,Machine Learning Engineer,129432,USD,129432,SE,PT,Sweden,M,Sweden,0,"Linux, Azure, NLP, Statistics, AWS",Associate,7,Gaming,2025-04-13,2025-05-13,2032,8.1,AI Innovations +AI11350,Deep Learning Engineer,274081,USD,274081,EX,FT,Denmark,S,Luxembourg,0,"SQL, Spark, Statistics, Git, Python",Associate,17,Real Estate,2024-12-26,2025-02-23,1154,8.8,DataVision Ltd +AI11351,Data Engineer,70458,USD,70458,MI,PT,Finland,S,Finland,50,"Scala, SQL, Python, Spark, GCP",Bachelor,3,Telecommunications,2024-12-28,2025-01-25,1865,7.4,DataVision Ltd +AI11352,Deep Learning Engineer,54782,CAD,68478,EN,FT,Canada,S,Canada,50,"Hadoop, Data Visualization, AWS, TensorFlow",PhD,0,Government,2024-07-12,2024-08-29,2043,9.8,Advanced Robotics +AI11353,AI Research Scientist,64330,EUR,54681,EN,FT,Austria,M,Austria,100,"Deep Learning, Tableau, Python, Azure",Bachelor,0,Media,2024-03-05,2024-03-25,1355,7.6,Digital Transformation LLC +AI11354,Head of AI,253257,USD,253257,EX,PT,United States,L,United States,100,"GCP, Python, AWS",PhD,12,Transportation,2025-03-31,2025-05-04,950,7.9,Future Systems +AI11355,AI Research Scientist,72157,JPY,7937270,EN,CT,Japan,S,Japan,50,"Azure, Linux, R, Tableau",Associate,1,Gaming,2025-03-29,2025-04-21,1647,6.3,Digital Transformation LLC +AI11356,AI Specialist,79437,EUR,67521,EN,PT,Netherlands,M,Netherlands,100,"Tableau, Hadoop, Java",Master,0,Finance,2025-03-12,2025-03-29,566,6.8,Cognitive Computing +AI11357,AI Research Scientist,89807,USD,89807,EN,PT,Norway,S,Norway,100,"Docker, Spark, MLOps, Scala",Bachelor,0,Consulting,2024-02-28,2024-04-21,987,7.5,TechCorp Inc +AI11358,Data Engineer,223811,USD,223811,EX,FL,Norway,L,Norway,100,"Deep Learning, TensorFlow, NLP, Hadoop",Associate,13,Government,2025-02-10,2025-03-06,1630,6.3,Cloud AI Solutions +AI11359,Principal Data Scientist,43079,USD,43079,SE,CT,India,M,India,100,"MLOps, GCP, Java, PyTorch, Azure",Bachelor,7,Energy,2024-08-23,2024-10-24,781,9.2,Autonomous Tech +AI11360,Data Engineer,171228,SGD,222596,SE,FL,Singapore,L,Singapore,0,"Data Visualization, Hadoop, Python",Bachelor,7,Automotive,2024-12-23,2025-01-25,1585,7.1,DataVision Ltd +AI11361,AI Software Engineer,320305,USD,320305,EX,FT,United States,L,United States,50,"Scala, Hadoop, Tableau, MLOps, Spark",Associate,11,Healthcare,2025-03-05,2025-04-07,2126,9.8,Advanced Robotics +AI11362,AI Specialist,265506,CAD,331883,EX,FT,Canada,L,Canada,100,"AWS, Data Visualization, GCP, Linux",Bachelor,16,Retail,2025-03-18,2025-05-28,1455,7.6,Machine Intelligence Group +AI11363,AI Product Manager,191096,CHF,171986,SE,CT,Switzerland,S,Switzerland,100,"AWS, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-04-21,2025-06-06,1793,9.5,Machine Intelligence Group +AI11364,Computer Vision Engineer,46630,USD,46630,MI,PT,China,L,China,100,"Computer Vision, Mathematics, TensorFlow, Python",PhD,4,Healthcare,2024-01-19,2024-03-24,531,5.1,Cloud AI Solutions +AI11365,AI Specialist,97986,USD,97986,SE,FL,Ireland,S,Russia,100,"Python, GCP, TensorFlow, Java",PhD,5,Healthcare,2025-02-26,2025-03-27,686,8,AI Innovations +AI11366,ML Ops Engineer,136685,USD,136685,SE,PT,South Korea,L,South Korea,0,"PyTorch, AWS, Linux",Bachelor,5,Technology,2024-10-14,2024-11-27,784,6.5,Cloud AI Solutions +AI11367,ML Ops Engineer,90657,CAD,113321,MI,PT,Canada,M,Canada,0,"PyTorch, SQL, Mathematics",Bachelor,2,Automotive,2024-10-09,2024-12-10,991,9.8,AI Innovations +AI11368,Research Scientist,170307,USD,170307,SE,FT,United States,L,United States,100,"Azure, Git, AWS",PhD,9,Technology,2025-01-02,2025-03-08,2456,9,Advanced Robotics +AI11369,Deep Learning Engineer,137251,USD,137251,MI,CT,Denmark,L,Denmark,0,"Java, SQL, PyTorch, AWS",Bachelor,2,Telecommunications,2025-02-12,2025-03-07,2401,9.2,Future Systems +AI11370,Data Scientist,175338,USD,175338,EX,PT,Finland,L,Finland,100,"TensorFlow, R, Mathematics, GCP, Deep Learning",Associate,10,Government,2025-02-19,2025-03-09,602,9.1,Digital Transformation LLC +AI11371,Deep Learning Engineer,81903,JPY,9009330,EN,PT,Japan,L,Japan,100,"Scala, Java, GCP",PhD,1,Energy,2024-11-10,2024-11-27,2492,8.8,Predictive Systems +AI11372,Data Engineer,119281,SGD,155065,SE,FT,Singapore,S,Singapore,0,"SQL, Python, Tableau, Deep Learning, AWS",Bachelor,7,Transportation,2024-05-06,2024-07-01,579,6.1,Machine Intelligence Group +AI11373,Machine Learning Researcher,59467,USD,59467,EN,FT,South Korea,L,South Korea,100,"SQL, Git, PyTorch, Kubernetes, Java",PhD,1,Finance,2024-12-08,2025-01-06,1293,9.8,Neural Networks Co +AI11374,Head of AI,136127,EUR,115708,SE,FT,Germany,M,Germany,100,"Git, Computer Vision, Spark",Associate,8,Healthcare,2024-04-18,2024-06-18,1980,7.5,Algorithmic Solutions +AI11375,Deep Learning Engineer,150034,USD,150034,EX,FT,Israel,S,Israel,100,"AWS, Git, Python, TensorFlow, R",Master,19,Government,2025-02-12,2025-04-21,1236,8.8,Autonomous Tech +AI11376,Research Scientist,293963,EUR,249869,EX,FT,Netherlands,L,Netherlands,50,"Scala, NLP, AWS, Azure, Git",Bachelor,12,Manufacturing,2024-06-26,2024-07-24,1473,8,Cognitive Computing +AI11377,NLP Engineer,93910,USD,93910,EN,PT,Norway,M,South Korea,50,"R, Deep Learning, Git, Python, Docker",PhD,1,Energy,2024-11-19,2025-01-20,782,7.6,Predictive Systems +AI11378,AI Specialist,106154,CAD,132693,SE,FL,Canada,S,Canada,100,"Mathematics, Python, Statistics",PhD,9,Retail,2024-09-22,2024-11-24,869,7.9,AI Innovations +AI11379,Principal Data Scientist,83026,EUR,70572,EN,CT,Germany,L,Germany,100,"Java, R, Hadoop, Scala",Associate,1,Education,2025-02-15,2025-04-11,924,6.6,AI Innovations +AI11380,AI Consultant,62488,USD,62488,EX,FL,India,S,India,0,"Git, NLP, Kubernetes, AWS, Computer Vision",Master,10,Healthcare,2024-05-21,2024-07-22,1404,6.3,Cognitive Computing +AI11381,Data Engineer,82469,JPY,9071590,EN,FL,Japan,L,Japan,100,"PyTorch, TensorFlow, Mathematics, Deep Learning, Data Visualization",Associate,0,Telecommunications,2024-07-21,2024-09-18,1642,5.3,DeepTech Ventures +AI11382,AI Research Scientist,37153,USD,37153,MI,FL,India,M,India,100,"Java, R, GCP, MLOps, Docker",PhD,4,Energy,2024-02-14,2024-04-04,2213,8.1,Cloud AI Solutions +AI11383,Head of AI,100902,USD,100902,SE,PT,South Korea,L,South Korea,50,"Python, Java, Linux, TensorFlow",PhD,8,Education,2024-05-27,2024-07-13,1402,9.1,Predictive Systems +AI11384,Data Engineer,61167,SGD,79517,EN,FT,Singapore,S,Singapore,0,"Python, Java, SQL, Linux, NLP",Associate,1,Real Estate,2024-07-25,2024-09-17,1081,8,Advanced Robotics +AI11385,NLP Engineer,72149,USD,72149,EX,PT,India,L,Ukraine,100,"Python, GCP, Tableau",PhD,16,Education,2024-09-13,2024-11-18,917,8.4,Future Systems +AI11386,Machine Learning Engineer,145674,USD,145674,SE,FL,Finland,L,Finland,0,"Python, Docker, Hadoop",PhD,9,Finance,2025-03-06,2025-04-14,1983,9.4,Neural Networks Co +AI11387,NLP Engineer,121414,CAD,151768,SE,FL,Canada,M,Canada,50,"Linux, Hadoop, Tableau, SQL, Python",Bachelor,7,Education,2024-08-23,2024-10-12,890,6.6,Digital Transformation LLC +AI11388,ML Ops Engineer,78140,EUR,66419,EN,PT,France,L,France,100,"SQL, Git, Scala, Hadoop, NLP",Associate,1,Automotive,2024-12-14,2025-02-06,826,8.9,Digital Transformation LLC +AI11389,Head of AI,141442,USD,141442,SE,FL,United States,M,United States,50,"Kubernetes, AWS, Data Visualization",PhD,9,Real Estate,2025-03-26,2025-05-28,1718,8.5,Smart Analytics +AI11390,Machine Learning Researcher,96067,USD,96067,MI,CT,Israel,L,Israel,50,"Tableau, Spark, Hadoop",PhD,2,Healthcare,2025-04-20,2025-06-26,1870,7.7,Cloud AI Solutions +AI11391,Data Scientist,388535,CHF,349682,EX,CT,Switzerland,L,Egypt,50,"MLOps, Azure, Data Visualization, Scala, SQL",Master,16,Transportation,2024-06-20,2024-07-06,929,9.4,Predictive Systems +AI11392,Deep Learning Engineer,132494,CAD,165618,SE,FL,Canada,L,Canada,100,"Python, Kubernetes, Azure",PhD,6,Transportation,2024-01-25,2024-03-10,1687,8.1,Smart Analytics +AI11393,Machine Learning Engineer,66690,EUR,56687,MI,FT,Austria,S,New Zealand,50,"Docker, Statistics, Deep Learning, Azure, Scala",Bachelor,3,Automotive,2024-02-09,2024-03-23,868,9.6,DataVision Ltd +AI11394,Data Scientist,122287,GBP,91715,MI,PT,United Kingdom,L,United Kingdom,100,"AWS, Python, Spark",Bachelor,2,Retail,2024-09-12,2024-10-29,1159,6,Quantum Computing Inc +AI11395,Machine Learning Engineer,81923,USD,81923,EN,CT,Ireland,L,Ireland,0,"Python, TensorFlow, Git, Docker",Master,0,Real Estate,2025-03-05,2025-05-10,2422,7.5,Future Systems +AI11396,ML Ops Engineer,317576,USD,317576,EX,FL,Denmark,L,United States,100,"NLP, Tableau, SQL",Associate,16,Media,2024-10-17,2024-11-26,1252,8.1,TechCorp Inc +AI11397,AI Architect,111218,EUR,94535,SE,FT,Austria,S,Austria,0,"Mathematics, R, Computer Vision",Bachelor,6,Technology,2025-03-05,2025-03-20,2285,9,AI Innovations +AI11398,Data Engineer,137824,AUD,186062,EX,PT,Australia,S,Australia,0,"Java, SQL, Deep Learning, Azure, Computer Vision",Associate,13,Consulting,2025-02-14,2025-03-07,1942,6.7,Digital Transformation LLC +AI11399,Computer Vision Engineer,124975,EUR,106229,MI,PT,Netherlands,L,Netherlands,0,"Python, Linux, Scala, Data Visualization",Master,3,Automotive,2025-01-04,2025-02-02,1299,6,Digital Transformation LLC +AI11400,AI Product Manager,202807,SGD,263649,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Tableau",Bachelor,10,Finance,2024-05-11,2024-07-05,1842,7.1,Cognitive Computing +AI11401,AI Product Manager,225578,CHF,203020,EX,CT,Switzerland,S,Switzerland,50,"Docker, Azure, Python",Master,12,Technology,2025-01-06,2025-02-02,2234,5.7,Quantum Computing Inc +AI11402,Data Analyst,67004,EUR,56953,EN,CT,Austria,M,South Africa,0,"R, SQL, GCP, Computer Vision",Associate,1,Retail,2024-05-07,2024-06-07,1313,5.1,Smart Analytics +AI11403,NLP Engineer,91436,USD,91436,MI,PT,Finland,M,Ireland,0,"Data Visualization, Spark, SQL",PhD,4,Telecommunications,2024-12-14,2025-02-10,889,7.2,Machine Intelligence Group +AI11404,Data Engineer,190150,USD,190150,SE,CT,Denmark,M,Denmark,100,"Git, SQL, Tableau",Bachelor,5,Telecommunications,2024-10-10,2024-12-19,1116,6,AI Innovations +AI11405,Research Scientist,190516,AUD,257197,EX,CT,Australia,L,Australia,50,"AWS, SQL, Kubernetes, Python",Master,17,Healthcare,2024-01-22,2024-03-25,1876,8.5,Predictive Systems +AI11406,Machine Learning Engineer,113403,EUR,96393,MI,CT,Netherlands,L,Netherlands,100,"GCP, Computer Vision, Mathematics, SQL, Scala",Bachelor,3,Real Estate,2024-05-05,2024-07-10,2473,9.6,Smart Analytics +AI11407,AI Product Manager,206127,USD,206127,EX,FL,United States,M,Sweden,0,"Java, R, Computer Vision, Git",Master,16,Energy,2025-02-09,2025-03-15,1636,5.7,Predictive Systems +AI11408,Machine Learning Engineer,164366,USD,164366,SE,CT,Sweden,L,Sweden,100,"Scala, Data Visualization, Spark",Bachelor,8,Telecommunications,2024-09-16,2024-11-23,2292,5.6,TechCorp Inc +AI11409,Machine Learning Engineer,135548,CAD,169435,EX,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, GCP, Data Visualization",PhD,14,Automotive,2024-08-21,2024-10-29,731,8.5,Neural Networks Co +AI11410,Robotics Engineer,81926,EUR,69637,EN,CT,Netherlands,L,Singapore,0,"Data Visualization, Scala, AWS, Linux",Associate,1,Retail,2024-08-05,2024-10-07,1080,8.9,DeepTech Ventures +AI11411,NLP Engineer,61432,CAD,76790,MI,FT,Canada,S,Canada,0,"Python, NLP, Linux",Bachelor,4,Retail,2025-01-25,2025-03-22,1959,5.6,Quantum Computing Inc +AI11412,Data Engineer,82350,SGD,107055,EN,CT,Singapore,M,Austria,50,"Hadoop, Deep Learning, Kubernetes, Spark, NLP",PhD,1,Gaming,2024-03-29,2024-04-20,1918,8.6,Machine Intelligence Group +AI11413,Robotics Engineer,91758,USD,91758,EN,PT,Norway,L,Norway,0,"GCP, Docker, R",PhD,1,Media,2025-01-23,2025-02-24,1382,8.3,DataVision Ltd +AI11414,Head of AI,26320,USD,26320,MI,PT,India,M,India,100,"Scala, Python, Mathematics, SQL",Associate,4,Automotive,2024-11-16,2024-12-11,678,8.9,Digital Transformation LLC +AI11415,AI Research Scientist,181477,GBP,136108,SE,CT,United Kingdom,L,United Kingdom,100,"NLP, Python, Linux, Deep Learning, Scala",PhD,5,Finance,2024-07-14,2024-09-10,1750,9.9,DeepTech Ventures +AI11416,AI Product Manager,119031,CAD,148789,SE,FT,Canada,S,Canada,100,"R, PyTorch, Python, MLOps",Bachelor,7,Technology,2024-04-08,2024-05-15,1777,9,Advanced Robotics +AI11417,AI Consultant,199896,JPY,21988560,EX,CT,Japan,S,Japan,100,"Tableau, Computer Vision, Statistics",Associate,10,Healthcare,2024-06-16,2024-08-02,1371,8,Advanced Robotics +AI11418,Machine Learning Researcher,143700,CAD,179625,EX,FL,Canada,M,Norway,100,"Docker, MLOps, GCP, R",PhD,11,Technology,2025-04-17,2025-05-28,2111,5.4,Advanced Robotics +AI11419,Machine Learning Engineer,257865,GBP,193399,EX,CT,United Kingdom,M,United Kingdom,50,"AWS, Spark, TensorFlow, Docker",Bachelor,18,Retail,2025-03-28,2025-06-01,2455,6.7,DeepTech Ventures +AI11420,Data Engineer,88557,SGD,115124,MI,FL,Singapore,S,New Zealand,0,"Kubernetes, Git, Data Visualization",PhD,3,Finance,2024-09-11,2024-10-26,520,6.5,TechCorp Inc +AI11421,Computer Vision Engineer,170140,CAD,212675,EX,FT,Canada,S,Canada,0,"Tableau, PyTorch, Kubernetes, R, Linux",PhD,11,Healthcare,2024-09-27,2024-11-25,1734,5.4,DeepTech Ventures +AI11422,Data Engineer,78293,CAD,97866,MI,FL,Canada,L,Canada,100,"Python, SQL, Statistics, Docker, Java",Associate,2,Healthcare,2024-05-04,2024-06-06,2239,5.1,Machine Intelligence Group +AI11423,AI Product Manager,95607,USD,95607,EN,CT,Norway,M,Norway,0,"GCP, Git, Java, Azure",Bachelor,0,Consulting,2024-07-28,2024-08-16,1686,8.9,Smart Analytics +AI11424,Data Analyst,75288,USD,75288,EN,FT,United States,L,Ghana,50,"Git, Hadoop, Tableau, Linux",Master,1,Healthcare,2024-05-05,2024-06-29,1636,7.1,Advanced Robotics +AI11425,Data Engineer,99770,CHF,89793,MI,FT,Switzerland,S,Switzerland,100,"Tableau, Docker, Deep Learning, Python, Hadoop",Master,2,Retail,2024-08-13,2024-09-16,2414,6.4,Predictive Systems +AI11426,AI Product Manager,107307,EUR,91211,SE,PT,Germany,S,Germany,0,"Tableau, Hadoop, NLP, GCP",Associate,5,Government,2024-03-01,2024-04-25,1825,8.6,DataVision Ltd +AI11427,NLP Engineer,80388,CAD,100485,MI,PT,Canada,S,Australia,0,"Java, SQL, AWS",Master,4,Automotive,2024-03-17,2024-05-17,2261,5.8,AI Innovations +AI11428,AI Consultant,43320,USD,43320,MI,FL,India,L,India,0,"Java, SQL, Scala, Statistics, AWS",Associate,3,Gaming,2024-02-01,2024-04-05,1139,6.7,Digital Transformation LLC +AI11429,AI Product Manager,49686,USD,49686,EX,FL,India,S,India,0,"Spark, Mathematics, Linux, Python",Associate,14,Media,2024-07-22,2024-09-30,1729,5.2,Smart Analytics +AI11430,AI Consultant,41656,USD,41656,MI,FT,China,S,Romania,100,"Python, Java, MLOps, Git",Bachelor,4,Gaming,2024-02-09,2024-03-01,1449,9.6,DataVision Ltd +AI11431,Data Engineer,149191,USD,149191,EX,FT,South Korea,S,South Korea,50,"SQL, Mathematics, MLOps",Bachelor,13,Real Estate,2025-02-25,2025-04-05,2473,6.1,DataVision Ltd +AI11432,Data Analyst,70858,USD,70858,MI,FL,South Korea,S,Canada,100,"Python, PyTorch, Statistics, Data Visualization",Bachelor,4,Government,2024-02-23,2024-05-02,1997,7,TechCorp Inc +AI11433,AI Software Engineer,112994,EUR,96045,SE,FT,France,S,France,100,"TensorFlow, NLP, SQL, Hadoop, Spark",Bachelor,8,Technology,2024-06-16,2024-08-08,1673,5.6,Neural Networks Co +AI11434,NLP Engineer,81456,USD,81456,MI,FL,South Korea,L,South Korea,100,"Tableau, TensorFlow, PyTorch",Bachelor,2,Finance,2024-11-08,2024-11-22,515,5.2,TechCorp Inc +AI11435,Head of AI,54011,EUR,45909,EN,CT,Austria,M,Austria,0,"Deep Learning, PyTorch, Statistics, Computer Vision, R",Master,1,Consulting,2024-10-20,2024-11-08,1295,7.9,Algorithmic Solutions +AI11436,AI Specialist,85091,USD,85091,EN,PT,Denmark,M,Denmark,100,"Mathematics, Spark, Kubernetes",Associate,1,Energy,2024-02-15,2024-04-03,780,6.5,TechCorp Inc +AI11437,AI Software Engineer,115899,USD,115899,EN,PT,Norway,L,Norway,50,"PyTorch, Mathematics, Tableau, Spark",PhD,0,Media,2025-01-11,2025-03-10,2231,6,AI Innovations +AI11438,Research Scientist,89371,JPY,9830810,MI,FL,Japan,M,Japan,0,"GCP, Azure, Tableau, MLOps",PhD,2,Manufacturing,2025-02-13,2025-03-21,1803,8.4,Future Systems +AI11439,Principal Data Scientist,125683,EUR,106831,SE,FT,Netherlands,M,Netherlands,50,"SQL, Java, Python, Azure, R",PhD,9,Education,2025-02-08,2025-03-27,1423,8.8,AI Innovations +AI11440,AI Research Scientist,349284,CHF,314356,EX,PT,Switzerland,L,Switzerland,100,"Python, TensorFlow, Docker, Deep Learning",Bachelor,13,Retail,2025-04-05,2025-04-25,1937,5.4,Cognitive Computing +AI11441,Data Scientist,140809,EUR,119688,EX,PT,Netherlands,S,Denmark,0,"Python, TensorFlow, MLOps, Scala, Java",Associate,18,Government,2024-03-19,2024-05-05,1264,6.7,Algorithmic Solutions +AI11442,Machine Learning Engineer,69956,USD,69956,MI,CT,Finland,S,Finland,100,"R, PyTorch, NLP, Scala",Master,4,Media,2024-03-14,2024-05-13,841,9.4,Digital Transformation LLC +AI11443,Autonomous Systems Engineer,71681,EUR,60929,EN,FL,France,M,Belgium,0,"Deep Learning, Computer Vision, Tableau, Python, Azure",PhD,0,Transportation,2025-04-18,2025-05-09,1084,7.6,AI Innovations +AI11444,NLP Engineer,215291,CAD,269114,EX,FL,Canada,L,Canada,50,"R, SQL, Computer Vision, GCP, Kubernetes",Associate,15,Technology,2024-08-14,2024-09-27,2204,9.3,DataVision Ltd +AI11445,Computer Vision Engineer,22321,USD,22321,EN,FL,India,S,India,0,"Deep Learning, Java, Statistics, Hadoop, Scala",PhD,1,Gaming,2024-09-09,2024-11-01,1646,9.2,TechCorp Inc +AI11446,Machine Learning Researcher,107424,USD,107424,MI,FT,United States,S,United States,100,"Git, Docker, Python, Azure, Computer Vision",PhD,2,Finance,2025-01-17,2025-02-01,759,7.8,Digital Transformation LLC +AI11447,AI Product Manager,97858,AUD,132108,MI,FT,Australia,S,Sweden,100,"Git, Kubernetes, MLOps, Tableau, GCP",PhD,2,Telecommunications,2024-11-12,2024-12-27,948,5.5,DeepTech Ventures +AI11448,Head of AI,131805,USD,131805,SE,PT,Finland,L,Finland,100,"Kubernetes, MLOps, Azure, Deep Learning, Scala",Master,9,Manufacturing,2024-11-12,2024-12-13,1137,7.9,Cloud AI Solutions +AI11449,AI Product Manager,168977,EUR,143630,SE,FL,Germany,L,Norway,0,"Data Visualization, MLOps, PyTorch, Deep Learning",PhD,5,Media,2024-08-24,2024-10-29,1876,6.1,DeepTech Ventures +AI11450,Computer Vision Engineer,112692,USD,112692,SE,CT,Israel,M,Israel,100,"Scala, Kubernetes, Azure",Associate,5,Energy,2024-06-25,2024-08-20,2010,7.9,DataVision Ltd +AI11451,NLP Engineer,24819,USD,24819,EN,FL,India,S,India,100,"Spark, Deep Learning, Tableau",Bachelor,0,Retail,2024-10-01,2024-11-24,916,6.4,Cognitive Computing +AI11452,Autonomous Systems Engineer,50429,USD,50429,MI,CT,China,M,China,0,"AWS, Azure, R, Computer Vision",PhD,4,Transportation,2024-05-08,2024-07-17,2418,7.6,Algorithmic Solutions +AI11453,AI Product Manager,92616,CAD,115770,MI,PT,Canada,L,Canada,100,"TensorFlow, Mathematics, Tableau",PhD,4,Energy,2024-08-22,2024-09-17,1475,6.8,Predictive Systems +AI11454,AI Architect,149371,USD,149371,MI,PT,United States,L,Spain,100,"PyTorch, Azure, Kubernetes, TensorFlow",Bachelor,3,Healthcare,2025-01-02,2025-02-23,2177,6.7,Autonomous Tech +AI11455,Machine Learning Engineer,235873,CHF,212286,EX,PT,Switzerland,S,Brazil,100,"Java, Git, Docker, MLOps",Master,10,Consulting,2024-06-26,2024-09-03,1795,8.8,Smart Analytics +AI11456,AI Consultant,46440,USD,46440,EN,FT,South Korea,S,South Korea,0,"Kubernetes, Spark, NLP, Git, Python",Associate,0,Transportation,2024-05-04,2024-05-27,536,5.3,Neural Networks Co +AI11457,Computer Vision Engineer,227078,EUR,193016,EX,PT,Netherlands,M,Romania,0,"R, Spark, Scala, Python",PhD,14,Media,2024-12-27,2025-01-28,937,7.2,Autonomous Tech +AI11458,Robotics Engineer,63953,EUR,54360,EN,FL,Netherlands,M,Netherlands,100,"AWS, Python, Tableau, TensorFlow",Associate,0,Manufacturing,2024-11-13,2024-12-05,662,5.3,Cloud AI Solutions +AI11459,AI Software Engineer,77328,EUR,65729,MI,FL,Germany,S,Germany,0,"Spark, Scala, PyTorch, Linux",Bachelor,2,Technology,2024-05-01,2024-05-22,2423,7.8,Neural Networks Co +AI11460,AI Product Manager,64672,USD,64672,EN,CT,Sweden,L,Latvia,50,"TensorFlow, R, Spark, Python, Azure",PhD,0,Real Estate,2024-11-21,2024-12-14,1484,7.3,Digital Transformation LLC +AI11461,AI Product Manager,103343,GBP,77507,MI,CT,United Kingdom,S,Switzerland,100,"TensorFlow, Data Visualization, Linux, Mathematics, Kubernetes",PhD,3,Finance,2024-03-05,2024-05-08,1183,8.8,Quantum Computing Inc +AI11462,NLP Engineer,99987,EUR,84989,MI,CT,Netherlands,S,Netherlands,50,"Spark, Linux, Data Visualization, Python",Master,3,Education,2025-01-12,2025-01-26,2303,6.5,Machine Intelligence Group +AI11463,NLP Engineer,37144,USD,37144,MI,PT,China,M,China,0,"Mathematics, Scala, SQL, Python",Master,3,Media,2024-04-01,2024-05-23,2408,5.5,Predictive Systems +AI11464,Head of AI,239050,JPY,26295500,EX,FL,Japan,M,Japan,50,"Azure, SQL, Hadoop",Master,17,Government,2024-11-03,2024-12-21,1181,6.4,DataVision Ltd +AI11465,Research Scientist,63804,USD,63804,EN,FL,Ireland,M,Ireland,50,"MLOps, Mathematics, Statistics, AWS",Bachelor,1,Finance,2024-10-02,2024-10-22,1980,8,Predictive Systems +AI11466,AI Research Scientist,121719,USD,121719,MI,PT,Sweden,L,Germany,50,"Statistics, Hadoop, Deep Learning, R",Master,2,Automotive,2024-11-23,2024-12-15,1865,5.7,DataVision Ltd +AI11467,Robotics Engineer,318346,USD,318346,EX,FL,Norway,M,Norway,50,"Python, TensorFlow, Java",Associate,10,Telecommunications,2024-04-10,2024-06-17,1715,9.3,AI Innovations +AI11468,NLP Engineer,113713,JPY,12508430,SE,PT,Japan,M,Philippines,0,"Java, SQL, Python, TensorFlow, PyTorch",Associate,9,Technology,2024-07-22,2024-09-19,2127,9.1,TechCorp Inc +AI11469,Research Scientist,129110,CAD,161388,SE,FL,Canada,M,Canada,100,"Scala, AWS, Computer Vision, Statistics, Mathematics",Associate,6,Real Estate,2024-04-24,2024-06-15,1850,8.8,Quantum Computing Inc +AI11470,Research Scientist,76550,USD,76550,EN,FT,United States,S,France,0,"SQL, Statistics, R",Associate,1,Telecommunications,2024-03-21,2024-05-01,972,7.6,Neural Networks Co +AI11471,AI Software Engineer,160981,JPY,17707910,EX,CT,Japan,S,Japan,100,"Kubernetes, Computer Vision, NLP",Associate,19,Retail,2024-09-04,2024-10-19,2152,9.3,Cloud AI Solutions +AI11472,AI Software Engineer,249798,CHF,224818,EX,FL,Switzerland,L,Switzerland,100,"Azure, Deep Learning, Spark, Linux, NLP",PhD,13,Real Estate,2024-08-29,2024-10-23,854,7.2,Cloud AI Solutions +AI11473,AI Specialist,110277,USD,110277,MI,CT,Ireland,L,Ireland,0,"Python, Java, Tableau, Spark",PhD,4,Telecommunications,2024-09-11,2024-10-19,1386,5.6,Quantum Computing Inc +AI11474,AI Architect,314219,USD,314219,EX,CT,Denmark,M,Denmark,100,"Python, Azure, Scala",Bachelor,19,Transportation,2025-02-02,2025-03-29,1389,7.3,Quantum Computing Inc +AI11475,Data Analyst,335263,CHF,301737,EX,FL,Switzerland,L,Switzerland,100,"Statistics, SQL, GCP",Master,14,Consulting,2024-09-25,2024-11-23,1870,7.4,Quantum Computing Inc +AI11476,Machine Learning Engineer,124417,CHF,111975,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, SQL, MLOps, Linux",PhD,2,Gaming,2024-04-26,2024-05-25,2021,8.9,DataVision Ltd +AI11477,AI Research Scientist,124130,USD,124130,SE,FL,Finland,M,Finland,0,"Scala, Hadoop, R, Linux, NLP",Associate,8,Education,2024-06-03,2024-07-07,1239,6.5,Machine Intelligence Group +AI11478,Machine Learning Researcher,80925,USD,80925,EN,FL,United States,S,Netherlands,50,"Python, Kubernetes, Data Visualization, Azure",Master,0,Finance,2024-10-06,2024-11-03,1923,8.3,Quantum Computing Inc +AI11479,Head of AI,79342,USD,79342,MI,CT,Ireland,M,Colombia,100,"Linux, Java, Scala",Master,3,Healthcare,2024-03-18,2024-05-25,1291,9.5,Digital Transformation LLC +AI11480,Autonomous Systems Engineer,97152,USD,97152,EN,CT,United States,L,United States,0,"PyTorch, Scala, Tableau",Bachelor,0,Technology,2025-02-08,2025-04-13,2187,7,Machine Intelligence Group +AI11481,Machine Learning Engineer,142004,EUR,120703,SE,FT,France,L,France,0,"SQL, Computer Vision, AWS",Associate,6,Automotive,2024-02-25,2024-05-05,731,8.5,Future Systems +AI11482,Computer Vision Engineer,147965,USD,147965,SE,PT,United States,M,United States,50,"Azure, Java, GCP",PhD,7,Consulting,2024-03-21,2024-05-08,2334,7.9,Predictive Systems +AI11483,Deep Learning Engineer,192037,USD,192037,EX,CT,Ireland,L,Ireland,50,"Java, Docker, NLP",Bachelor,10,Real Estate,2024-01-11,2024-02-08,1028,5.9,DeepTech Ventures +AI11484,Data Scientist,127383,EUR,108276,SE,FL,France,M,South Korea,0,"Kubernetes, Hadoop, Linux, GCP",PhD,9,Finance,2024-10-29,2024-12-30,1853,8.4,DeepTech Ventures +AI11485,Principal Data Scientist,85256,EUR,72468,MI,CT,Netherlands,S,Netherlands,50,"Scala, Mathematics, Python, Spark, GCP",PhD,3,Healthcare,2024-05-31,2024-08-06,899,5.5,Cloud AI Solutions +AI11486,Data Analyst,191885,USD,191885,SE,CT,Norway,L,Norway,50,"PyTorch, Python, Data Visualization",Bachelor,7,Consulting,2024-04-19,2024-06-15,2006,8.6,DataVision Ltd +AI11487,Data Engineer,106706,USD,106706,SE,FL,Israel,S,Israel,100,"Docker, Git, NLP, MLOps",Bachelor,6,Gaming,2025-03-24,2025-05-22,1323,7.6,Advanced Robotics +AI11488,AI Product Manager,144625,USD,144625,SE,FT,Ireland,L,Ireland,50,"Scala, Python, SQL, Mathematics",Bachelor,6,Government,2025-02-07,2025-04-08,2418,6.6,Machine Intelligence Group +AI11489,NLP Engineer,89096,GBP,66822,MI,CT,United Kingdom,L,United Kingdom,0,"R, SQL, Tableau, Statistics, Azure",PhD,4,Government,2025-02-17,2025-04-27,944,8.8,Predictive Systems +AI11490,AI Product Manager,113094,USD,113094,MI,FL,Denmark,M,Denmark,50,"Java, R, Statistics",Master,3,Real Estate,2024-03-15,2024-05-22,1878,7.7,DeepTech Ventures +AI11491,Machine Learning Researcher,44438,USD,44438,EN,FL,South Korea,S,South Korea,50,"Hadoop, Tableau, GCP, MLOps",PhD,0,Government,2024-03-11,2024-03-25,2149,8.8,Advanced Robotics +AI11492,AI Research Scientist,74828,EUR,63604,EN,CT,Netherlands,S,Netherlands,0,"Computer Vision, Python, Kubernetes, SQL",Master,1,Manufacturing,2024-09-12,2024-10-21,1386,6.3,Quantum Computing Inc +AI11493,Principal Data Scientist,79856,AUD,107806,MI,PT,Australia,M,Australia,0,"Hadoop, Scala, Git, Deep Learning, Java",PhD,2,Retail,2024-05-22,2024-07-24,1575,6.9,Quantum Computing Inc +AI11494,AI Specialist,155247,USD,155247,EX,FT,Ireland,M,Ireland,100,"Python, Mathematics, Git, Hadoop, Computer Vision",Master,17,Consulting,2025-02-04,2025-02-18,1759,9.4,Algorithmic Solutions +AI11495,AI Research Scientist,86084,EUR,73171,EN,PT,France,L,Poland,100,"Java, GCP, Data Visualization, Kubernetes, Python",Bachelor,1,Healthcare,2025-02-05,2025-04-03,1866,5.1,AI Innovations +AI11496,AI Specialist,121255,USD,121255,MI,PT,Norway,L,Norway,0,"SQL, Scala, AWS, GCP",PhD,4,Telecommunications,2024-03-28,2024-06-03,2180,8.1,TechCorp Inc +AI11497,AI Consultant,120964,USD,120964,SE,CT,Denmark,S,Nigeria,50,"Spark, SQL, Deep Learning",Associate,9,Healthcare,2024-05-10,2024-07-02,511,9.3,TechCorp Inc +AI11498,Autonomous Systems Engineer,170957,GBP,128218,SE,FL,United Kingdom,L,United Kingdom,100,"Azure, Hadoop, Python",Associate,6,Retail,2024-11-16,2024-12-12,1965,8.5,DataVision Ltd +AI11499,Machine Learning Engineer,80134,JPY,8814740,MI,FL,Japan,M,Ireland,0,"Java, AWS, TensorFlow, Spark, Tableau",Associate,2,Manufacturing,2024-04-11,2024-06-07,936,6.7,Smart Analytics +AI11500,AI Consultant,139486,JPY,15343460,EX,FT,Japan,S,Canada,50,"NLP, Python, Data Visualization",Associate,13,Finance,2024-09-07,2024-11-17,1203,6.6,Neural Networks Co +AI11501,Deep Learning Engineer,65381,SGD,84995,EN,FT,Singapore,L,Singapore,50,"Linux, R, Docker, Python",Bachelor,0,Education,2024-11-21,2025-01-17,1622,6.9,TechCorp Inc +AI11502,Data Engineer,171324,USD,171324,EX,CT,Norway,S,Norway,0,"Statistics, SQL, Scala, Kubernetes, Data Visualization",Bachelor,15,Education,2024-07-02,2024-08-11,1183,7.5,Advanced Robotics +AI11503,AI Specialist,87775,USD,87775,SE,FL,South Korea,M,South Korea,100,"MLOps, SQL, Python, Scala, Git",Master,6,Media,2024-07-07,2024-08-04,2349,6.3,Cognitive Computing +AI11504,Deep Learning Engineer,172632,EUR,146737,EX,FL,Austria,S,Austria,0,"Tableau, Kubernetes, AWS",Master,11,Manufacturing,2024-11-10,2024-12-30,2272,5.6,Neural Networks Co +AI11505,Data Analyst,88588,USD,88588,MI,PT,Denmark,S,Denmark,50,"Hadoop, Docker, Mathematics",Bachelor,4,Real Estate,2024-10-02,2024-10-18,572,6.8,DeepTech Ventures +AI11506,Data Scientist,168771,EUR,143455,EX,FT,Netherlands,M,Netherlands,0,"TensorFlow, NLP, Python, GCP",Associate,15,Retail,2025-03-16,2025-05-06,1787,5.7,DeepTech Ventures +AI11507,AI Product Manager,90000,USD,90000,MI,FT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, Data Visualization, SQL",Associate,4,Real Estate,2024-04-12,2024-04-29,1336,5.1,Quantum Computing Inc +AI11508,NLP Engineer,38919,USD,38919,MI,PT,China,M,Belgium,0,"R, Hadoop, NLP",Bachelor,3,Finance,2025-03-02,2025-03-24,1440,7.8,Predictive Systems +AI11509,Deep Learning Engineer,63396,EUR,53887,EN,CT,France,M,France,50,"Hadoop, GCP, AWS, Scala, Azure",Bachelor,0,Government,2024-07-03,2024-08-24,1182,5.9,DataVision Ltd +AI11510,AI Software Engineer,127703,USD,127703,EX,FL,South Korea,S,Indonesia,50,"Hadoop, Scala, TensorFlow, GCP",PhD,14,Retail,2024-11-18,2025-01-03,1976,6.3,Algorithmic Solutions +AI11511,Research Scientist,136930,USD,136930,MI,FT,Norway,M,Norway,50,"Azure, SQL, Computer Vision, Spark, Statistics",PhD,2,Manufacturing,2024-02-05,2024-03-06,2481,9.8,Cognitive Computing +AI11512,Machine Learning Researcher,62653,EUR,53255,EN,FL,Austria,S,Austria,0,"SQL, Scala, GCP",Bachelor,0,Media,2024-02-07,2024-04-07,1111,5.1,Smart Analytics +AI11513,AI Consultant,238158,USD,238158,EX,FL,Sweden,L,Sweden,0,"Mathematics, Data Visualization, GCP, Python, Git",PhD,19,Telecommunications,2025-02-03,2025-02-26,2232,7.3,Advanced Robotics +AI11514,AI Specialist,67273,AUD,90819,MI,FL,Australia,S,Australia,100,"AWS, Computer Vision, Linux, NLP",Bachelor,2,Telecommunications,2024-12-05,2024-12-25,1782,8.6,Cloud AI Solutions +AI11515,AI Software Engineer,296408,USD,296408,EX,FL,Denmark,L,Denmark,50,"Azure, Git, Statistics",PhD,12,Real Estate,2024-01-07,2024-02-03,1976,8.8,DeepTech Ventures +AI11516,Deep Learning Engineer,82078,EUR,69766,MI,FT,Netherlands,S,Netherlands,100,"AWS, Statistics, Tableau",Associate,3,Media,2025-03-27,2025-05-19,2475,9.3,Algorithmic Solutions +AI11517,Data Analyst,62170,EUR,52845,MI,CT,France,S,Australia,0,"AWS, Git, Python, GCP",PhD,2,Telecommunications,2025-04-17,2025-05-30,2294,6.8,AI Innovations +AI11518,Principal Data Scientist,156317,GBP,117238,SE,FL,United Kingdom,L,Thailand,100,"SQL, Scala, Kubernetes, Git",Bachelor,8,Government,2025-02-15,2025-03-20,2149,5.3,Algorithmic Solutions +AI11519,Principal Data Scientist,222260,CHF,200034,EX,FL,Switzerland,S,Switzerland,0,"SQL, PyTorch, Linux",Bachelor,11,Transportation,2024-08-15,2024-09-29,1557,8.8,Machine Intelligence Group +AI11520,Deep Learning Engineer,37876,USD,37876,SE,FL,India,S,India,0,"Data Visualization, Scala, R",Associate,5,Manufacturing,2024-09-05,2024-11-03,1333,8.7,Smart Analytics +AI11521,AI Consultant,78486,USD,78486,MI,PT,Sweden,M,Sweden,50,"Java, PyTorch, Linux",Associate,4,Energy,2024-10-03,2024-12-07,2117,9.1,DataVision Ltd +AI11522,Deep Learning Engineer,192938,EUR,163997,EX,CT,Netherlands,S,Kenya,100,"AWS, Scala, Deep Learning",Master,14,Transportation,2024-10-18,2024-12-29,1316,9.7,Predictive Systems +AI11523,Principal Data Scientist,43359,USD,43359,SE,PT,India,L,India,50,"Statistics, MLOps, Mathematics, Data Visualization",PhD,8,Healthcare,2025-01-27,2025-02-27,2445,8.8,Cognitive Computing +AI11524,Principal Data Scientist,118994,EUR,101145,SE,PT,Germany,M,Germany,100,"Spark, GCP, TensorFlow",Associate,9,Technology,2024-08-25,2024-10-07,1049,5.6,Neural Networks Co +AI11525,NLP Engineer,97478,CHF,87730,MI,FL,Switzerland,S,Switzerland,0,"Hadoop, SQL, Scala, Data Visualization, AWS",PhD,4,Telecommunications,2025-03-30,2025-05-01,1307,9.6,Digital Transformation LLC +AI11526,Head of AI,88392,EUR,75133,MI,FT,France,S,France,50,"Data Visualization, R, GCP, SQL",PhD,2,Energy,2024-11-28,2024-12-26,1526,5.8,Smart Analytics +AI11527,Machine Learning Researcher,134966,USD,134966,SE,FL,Sweden,S,Austria,50,"Kubernetes, Hadoop, PyTorch, Data Visualization, Computer Vision",Associate,6,Energy,2024-05-24,2024-06-14,1182,6,Cognitive Computing +AI11528,AI Specialist,106203,AUD,143374,MI,FL,Australia,M,Australia,0,"Azure, Computer Vision, SQL, Kubernetes, Statistics",Master,3,Telecommunications,2024-02-03,2024-02-24,1658,9.8,Predictive Systems +AI11529,AI Software Engineer,202928,USD,202928,EX,CT,Ireland,S,Ireland,0,"R, PyTorch, Git, Java",Bachelor,18,Gaming,2024-06-26,2024-07-24,2250,6.3,TechCorp Inc +AI11530,NLP Engineer,127991,USD,127991,MI,FT,Norway,S,Norway,100,"Mathematics, Data Visualization, R, Computer Vision",Bachelor,3,Real Estate,2024-11-18,2025-01-25,1062,8,AI Innovations +AI11531,AI Architect,92358,EUR,78504,SE,FL,Austria,S,Finland,50,"GCP, Kubernetes, AWS, Computer Vision",Associate,8,Manufacturing,2024-10-03,2024-12-02,2090,9,DataVision Ltd +AI11532,Data Engineer,272629,USD,272629,EX,FL,Norway,S,Russia,50,"MLOps, Docker, Java, Mathematics, PyTorch",Master,19,Retail,2025-02-17,2025-03-27,1463,8.6,Future Systems +AI11533,AI Architect,221472,JPY,24361920,EX,PT,Japan,S,Japan,50,"Tableau, Java, Docker, Scala",PhD,10,Media,2024-09-28,2024-10-19,1044,8.7,Neural Networks Co +AI11534,Autonomous Systems Engineer,73577,CAD,91971,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, MLOps, Java, PyTorch",PhD,1,Automotive,2024-03-30,2024-05-03,1561,7.1,DeepTech Ventures +AI11535,ML Ops Engineer,58063,EUR,49354,EN,CT,Germany,M,Germany,0,"Data Visualization, Scala, Linux, NLP",Master,0,Consulting,2024-09-04,2024-11-05,2249,9.1,DeepTech Ventures +AI11536,Computer Vision Engineer,219400,AUD,296190,EX,FL,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau, Azure, GCP",PhD,17,Transportation,2024-04-27,2024-07-03,1931,5.6,DeepTech Ventures +AI11537,Machine Learning Engineer,103961,GBP,77971,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Docker, Hadoop, Mathematics",Associate,2,Real Estate,2024-10-26,2024-12-20,1011,9.3,Algorithmic Solutions +AI11538,Data Scientist,82413,USD,82413,EX,PT,India,M,India,0,"Python, Spark, TensorFlow, GCP, PyTorch",Master,13,Finance,2024-03-18,2024-05-21,1591,8.7,Machine Intelligence Group +AI11539,Computer Vision Engineer,172900,CHF,155610,SE,FL,Switzerland,L,Switzerland,50,"SQL, Deep Learning, Tableau, TensorFlow, Statistics",Master,6,Media,2024-05-28,2024-06-15,2243,7.4,Quantum Computing Inc +AI11540,Research Scientist,189271,EUR,160880,EX,CT,Netherlands,M,Netherlands,0,"TensorFlow, GCP, Mathematics, Docker",Bachelor,10,Transportation,2024-10-02,2024-11-15,1545,5.3,Advanced Robotics +AI11541,AI Product Manager,111442,EUR,94726,MI,CT,France,L,France,100,"Python, Statistics, NLP",Bachelor,3,Government,2024-05-07,2024-07-01,1973,7.6,Predictive Systems +AI11542,NLP Engineer,67863,GBP,50897,EN,PT,United Kingdom,S,United Kingdom,100,"GCP, Deep Learning, NLP",Bachelor,0,Automotive,2024-07-06,2024-08-11,751,8.8,Cognitive Computing +AI11543,NLP Engineer,37216,USD,37216,MI,FT,India,M,India,100,"Scala, Spark, Tableau, Mathematics, Python",Associate,2,Consulting,2025-01-12,2025-02-18,1396,8.8,Autonomous Tech +AI11544,ML Ops Engineer,146138,USD,146138,SE,FT,Ireland,M,Ireland,0,"Deep Learning, Scala, Tableau, SQL, Computer Vision",Master,9,Media,2024-10-06,2024-11-11,1436,8.5,Cognitive Computing +AI11545,Data Scientist,45328,CAD,56660,EN,PT,Canada,S,Hungary,50,"Deep Learning, R, MLOps, SQL, Spark",Bachelor,0,Automotive,2024-10-18,2024-11-19,2424,8.9,TechCorp Inc +AI11546,Data Scientist,100310,USD,100310,MI,PT,Israel,L,Estonia,50,"Linux, Kubernetes, Scala, Python",PhD,4,Consulting,2024-04-22,2024-05-30,1423,7.2,Quantum Computing Inc +AI11547,Principal Data Scientist,147245,EUR,125158,SE,CT,France,L,France,50,"MLOps, Linux, Data Visualization, Spark",Associate,6,Media,2024-10-23,2024-11-18,729,6.4,Autonomous Tech +AI11548,Autonomous Systems Engineer,88089,EUR,74876,MI,FT,Germany,S,Germany,0,"Git, Azure, Python, Hadoop",PhD,3,Automotive,2024-01-17,2024-02-18,2100,7.4,Digital Transformation LLC +AI11549,Principal Data Scientist,72575,USD,72575,EN,CT,South Korea,L,South Korea,50,"TensorFlow, AWS, Deep Learning, Python, MLOps",Bachelor,0,Media,2024-11-06,2025-01-17,753,9.5,DeepTech Ventures +AI11550,AI Research Scientist,85617,USD,85617,MI,FL,Finland,S,Finland,50,"SQL, GCP, PyTorch, AWS",Bachelor,4,Healthcare,2025-04-26,2025-07-02,911,5.5,Cloud AI Solutions +AI11551,AI Consultant,89607,CAD,112009,MI,PT,Canada,S,Canada,50,"Computer Vision, AWS, SQL",Associate,2,Government,2024-10-17,2024-12-10,851,5.1,AI Innovations +AI11552,Robotics Engineer,51322,EUR,43624,EN,FL,Austria,S,Austria,50,"Git, Hadoop, SQL, NLP",PhD,1,Transportation,2025-01-05,2025-02-16,1864,7.7,Cognitive Computing +AI11553,Computer Vision Engineer,93109,EUR,79143,SE,PT,France,S,France,0,"Docker, Hadoop, Tableau, Statistics, GCP",Bachelor,9,Real Estate,2024-05-09,2024-06-23,1392,5.4,DeepTech Ventures +AI11554,Robotics Engineer,39952,USD,39952,MI,PT,China,S,China,100,"Statistics, R, Docker, Deep Learning",Master,4,Manufacturing,2024-12-22,2025-01-12,2188,7.8,TechCorp Inc +AI11555,Head of AI,53528,USD,53528,SE,CT,China,M,China,100,"TensorFlow, Python, Data Visualization",Bachelor,6,Media,2024-08-30,2024-10-28,1322,5.8,Predictive Systems +AI11556,Data Engineer,87394,EUR,74285,MI,FL,Netherlands,M,Netherlands,0,"Mathematics, GCP, Scala, NLP",Master,3,Healthcare,2024-03-12,2024-05-19,2338,9.7,Smart Analytics +AI11557,Deep Learning Engineer,172148,EUR,146326,EX,PT,Netherlands,S,Netherlands,50,"SQL, Python, Git",Bachelor,19,Manufacturing,2024-07-31,2024-08-24,712,5.6,TechCorp Inc +AI11558,AI Research Scientist,63353,EUR,53850,EN,FT,France,S,France,50,"Linux, PyTorch, R, MLOps, Statistics",Associate,1,Finance,2025-04-04,2025-04-23,1231,7.1,TechCorp Inc +AI11559,Machine Learning Researcher,65724,USD,65724,EN,FL,South Korea,L,South Korea,50,"Git, MLOps, GCP",Bachelor,0,Transportation,2024-02-04,2024-03-14,1883,7.4,Machine Intelligence Group +AI11560,ML Ops Engineer,114291,EUR,97147,SE,PT,Austria,S,Austria,100,"SQL, Kubernetes, Tableau, Linux",Associate,8,Education,2024-09-27,2024-11-09,666,8.2,DataVision Ltd +AI11561,Machine Learning Engineer,85594,USD,85594,EN,PT,Ireland,L,Ireland,50,"Git, Data Visualization, Hadoop, NLP, Deep Learning",Bachelor,0,Automotive,2024-04-04,2024-05-15,2034,7.9,DataVision Ltd +AI11562,AI Specialist,123737,JPY,13611070,SE,PT,Japan,M,Japan,50,"Python, AWS, Computer Vision, TensorFlow",Bachelor,5,Education,2024-09-01,2024-09-25,2237,5,Predictive Systems +AI11563,Deep Learning Engineer,240031,EUR,204026,EX,PT,Germany,M,Germany,0,"Java, Mathematics, TensorFlow",Master,11,Technology,2024-09-07,2024-10-18,683,8.7,Autonomous Tech +AI11564,Research Scientist,31490,USD,31490,MI,PT,India,M,Sweden,100,"Linux, SQL, Computer Vision, Data Visualization",Master,2,Telecommunications,2025-01-14,2025-02-12,1008,7.5,TechCorp Inc +AI11565,AI Specialist,60618,EUR,51525,EN,CT,Germany,L,South Korea,0,"R, Tableau, Deep Learning, Kubernetes",Master,0,Retail,2024-10-29,2024-12-02,1489,7.3,Predictive Systems +AI11566,AI Architect,78418,USD,78418,EN,CT,Israel,L,Israel,100,"Python, NLP, MLOps",Associate,0,Manufacturing,2024-09-05,2024-09-30,846,9.3,AI Innovations +AI11567,Data Scientist,269385,JPY,29632350,EX,CT,Japan,M,Japan,50,"NLP, Kubernetes, Spark, Mathematics, Python",Associate,13,Automotive,2025-01-31,2025-04-09,1439,8,Autonomous Tech +AI11568,Autonomous Systems Engineer,97601,USD,97601,MI,PT,United States,S,Ireland,100,"PyTorch, Azure, Linux, GCP",Bachelor,2,Finance,2024-09-08,2024-10-29,1430,6.3,AI Innovations +AI11569,AI Software Engineer,195834,USD,195834,EX,FL,Finland,S,Argentina,50,"TensorFlow, GCP, SQL",Associate,15,Consulting,2024-09-22,2024-11-15,987,9.9,Cognitive Computing +AI11570,AI Consultant,136182,USD,136182,EX,CT,South Korea,M,South Korea,100,"Scala, Deep Learning, Azure, Statistics, Data Visualization",Master,18,Transportation,2025-02-06,2025-03-05,1479,6.8,Smart Analytics +AI11571,AI Software Engineer,210024,CAD,262530,EX,FT,Canada,S,Switzerland,50,"Scala, Python, Hadoop, Git",Bachelor,11,Healthcare,2025-02-21,2025-03-22,1133,9.1,DeepTech Ventures +AI11572,Principal Data Scientist,54381,USD,54381,EN,FT,Israel,S,Israel,0,"Spark, PyTorch, Azure, R, Scala",Associate,1,Manufacturing,2024-12-06,2024-12-22,1312,5.1,DataVision Ltd +AI11573,AI Product Manager,190082,USD,190082,SE,CT,Denmark,M,Denmark,0,"Docker, GCP, Java, PyTorch, Deep Learning",Bachelor,9,Manufacturing,2024-08-23,2024-10-19,945,6.2,Cloud AI Solutions +AI11574,AI Software Engineer,84428,JPY,9287080,MI,FT,Japan,S,Japan,50,"Hadoop, TensorFlow, GCP",Associate,2,Media,2024-03-14,2024-04-14,1969,6.7,Cognitive Computing +AI11575,Robotics Engineer,111780,SGD,145314,SE,CT,Singapore,S,Singapore,0,"Python, GCP, AWS, Mathematics, TensorFlow",PhD,5,Transportation,2025-03-13,2025-03-30,746,5.1,Machine Intelligence Group +AI11576,Principal Data Scientist,103260,USD,103260,EN,FT,Norway,M,Norway,0,"R, Python, Spark, Java, GCP",Bachelor,0,Education,2024-12-21,2025-02-17,714,8.4,Digital Transformation LLC +AI11577,AI Specialist,129654,USD,129654,MI,CT,Denmark,L,France,50,"Docker, SQL, Data Visualization",Master,2,Gaming,2024-04-03,2024-06-07,815,6.6,Neural Networks Co +AI11578,AI Product Manager,37250,USD,37250,EN,PT,China,M,Indonesia,50,"Python, Scala, TensorFlow, Tableau",Associate,0,Telecommunications,2024-06-22,2024-09-03,1594,5.3,Advanced Robotics +AI11579,Data Scientist,287770,USD,287770,EX,PT,Ireland,L,Ireland,50,"Hadoop, PyTorch, Kubernetes",Master,13,Energy,2025-01-10,2025-03-14,761,5.5,Digital Transformation LLC +AI11580,Data Scientist,65359,JPY,7189490,EN,PT,Japan,M,Colombia,100,"Data Visualization, Git, Scala, Computer Vision",PhD,0,Gaming,2025-03-25,2025-04-14,1483,8.7,Smart Analytics +AI11581,NLP Engineer,122773,USD,122773,SE,FT,Ireland,M,Ireland,100,"SQL, Tableau, Spark",Associate,8,Government,2024-03-14,2024-04-05,1698,9.2,DataVision Ltd +AI11582,Data Engineer,60408,USD,60408,EN,PT,Finland,L,Finland,100,"Git, PyTorch, GCP, Spark, Tableau",Bachelor,1,Manufacturing,2024-08-13,2024-10-01,1351,6.5,TechCorp Inc +AI11583,AI Software Engineer,150096,USD,150096,SE,FT,Sweden,L,Sweden,50,"Python, TensorFlow, Spark",Associate,6,Telecommunications,2024-02-05,2024-04-08,1653,7.2,Future Systems +AI11584,Data Scientist,205206,EUR,174425,EX,FL,France,L,France,100,"SQL, Kubernetes, PyTorch",Bachelor,17,Gaming,2024-05-19,2024-06-11,1708,5.6,TechCorp Inc +AI11585,Data Scientist,26000,USD,26000,MI,FT,India,M,India,100,"PyTorch, Azure, NLP",PhD,4,Consulting,2024-10-17,2024-12-02,1250,9.1,Advanced Robotics +AI11586,Data Engineer,65860,USD,65860,EN,CT,South Korea,L,South Korea,100,"Mathematics, Scala, Python, Git, Computer Vision",Associate,0,Manufacturing,2024-09-19,2024-11-09,1493,7.8,Future Systems +AI11587,Computer Vision Engineer,94548,GBP,70911,MI,FT,United Kingdom,L,United Kingdom,50,"Hadoop, Tableau, Computer Vision",PhD,2,Telecommunications,2024-09-22,2024-11-27,848,9.5,Cognitive Computing +AI11588,Robotics Engineer,139420,USD,139420,SE,CT,Finland,L,Kenya,0,"GCP, Computer Vision, NLP",PhD,6,Automotive,2024-02-08,2024-03-11,1488,7.9,Neural Networks Co +AI11589,AI Consultant,96731,USD,96731,EN,FL,United States,L,United States,50,"Java, R, SQL, Docker",Associate,0,Real Estate,2024-07-19,2024-08-13,2423,5.2,Algorithmic Solutions +AI11590,Data Engineer,166302,EUR,141357,SE,FT,Netherlands,L,Switzerland,50,"Hadoop, Computer Vision, Python, Java, Kubernetes",Bachelor,6,Real Estate,2024-09-08,2024-09-25,622,6.3,Autonomous Tech +AI11591,AI Research Scientist,169852,USD,169852,EX,PT,South Korea,M,South Korea,100,"SQL, Git, Docker, PyTorch",Bachelor,19,Automotive,2024-05-04,2024-06-04,2138,5.4,Future Systems +AI11592,Autonomous Systems Engineer,50112,USD,50112,EN,PT,Ireland,S,Ireland,50,"Data Visualization, Computer Vision, SQL, Hadoop",PhD,0,Energy,2024-10-13,2024-12-03,1750,9.7,Autonomous Tech +AI11593,Data Engineer,25790,USD,25790,EN,FT,India,L,Romania,50,"TensorFlow, SQL, Hadoop, Tableau",Master,0,Media,2024-07-29,2024-08-27,1971,8,Cognitive Computing +AI11594,Robotics Engineer,111118,SGD,144453,SE,PT,Singapore,M,Singapore,50,"AWS, Docker, NLP, Kubernetes, Azure",Associate,7,Telecommunications,2025-03-23,2025-05-02,960,8.7,Cloud AI Solutions +AI11595,Data Engineer,63655,GBP,47741,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, Python, R, TensorFlow",PhD,0,Consulting,2024-03-16,2024-04-29,2498,6.2,Algorithmic Solutions +AI11596,AI Product Manager,180875,USD,180875,EX,CT,Ireland,L,Sweden,0,"Scala, Kubernetes, Python",Master,11,Finance,2024-11-07,2024-12-25,649,8.2,Algorithmic Solutions +AI11597,AI Software Engineer,59927,EUR,50938,EN,CT,France,S,Czech Republic,50,"Mathematics, Computer Vision, Data Visualization",Bachelor,0,Real Estate,2024-03-06,2024-05-12,794,9.5,Machine Intelligence Group +AI11598,AI Research Scientist,254962,EUR,216718,EX,FT,France,L,France,0,"SQL, NLP, Docker",Bachelor,15,Finance,2024-11-30,2025-01-07,1476,9.7,Autonomous Tech +AI11599,Machine Learning Researcher,173503,CHF,156153,SE,CT,Switzerland,S,Kenya,50,"Mathematics, Computer Vision, AWS",Associate,5,Retail,2024-06-02,2024-07-05,2001,7.4,Neural Networks Co +AI11600,Data Engineer,33680,USD,33680,EN,FL,China,M,China,100,"Statistics, AWS, PyTorch, Kubernetes, TensorFlow",Associate,0,Gaming,2024-10-14,2024-11-16,555,6.4,TechCorp Inc +AI11601,Machine Learning Researcher,115942,USD,115942,MI,FL,United States,L,United States,0,"Scala, AWS, Data Visualization, Computer Vision",Bachelor,3,Finance,2024-07-20,2024-09-09,1811,7.7,AI Innovations +AI11602,AI Architect,77384,AUD,104468,EN,FL,Australia,L,Australia,0,"R, Tableau, Linux, GCP",PhD,1,Real Estate,2025-02-28,2025-04-10,593,5.3,DeepTech Ventures +AI11603,Data Analyst,331419,CHF,298277,EX,FT,Switzerland,M,Switzerland,0,"Git, NLP, R",Associate,18,Manufacturing,2024-05-05,2024-06-17,2175,5.8,DeepTech Ventures +AI11604,Data Scientist,131344,USD,131344,SE,CT,Sweden,L,Australia,100,"Statistics, MLOps, Hadoop, Kubernetes, Docker",PhD,6,Government,2025-01-23,2025-03-23,2206,6.1,Advanced Robotics +AI11605,Autonomous Systems Engineer,81352,USD,81352,EX,PT,India,M,Kenya,50,"Python, TensorFlow, Deep Learning, Hadoop, Linux",Master,11,Telecommunications,2024-01-27,2024-03-15,1582,6.7,Quantum Computing Inc +AI11606,NLP Engineer,75140,EUR,63869,EN,FT,Netherlands,S,Netherlands,100,"Java, Spark, Kubernetes",Associate,0,Real Estate,2025-04-26,2025-05-23,2246,9.4,Cloud AI Solutions +AI11607,AI Specialist,57023,USD,57023,EN,FL,Ireland,M,United Kingdom,100,"NLP, Statistics, AWS, Kubernetes",Bachelor,0,Education,2024-03-23,2024-04-25,1207,8,Future Systems +AI11608,Principal Data Scientist,76910,JPY,8460100,EN,FL,Japan,S,Japan,50,"Python, Azure, Tableau, SQL, Deep Learning",Associate,1,Transportation,2025-02-24,2025-04-05,1100,5.5,Machine Intelligence Group +AI11609,Data Engineer,86816,USD,86816,EN,FT,Norway,S,Norway,50,"Hadoop, Python, MLOps, Docker, Tableau",Bachelor,1,Automotive,2024-12-28,2025-02-16,1200,7.4,Predictive Systems +AI11610,Head of AI,177419,EUR,150806,EX,FL,Austria,L,Austria,50,"PyTorch, Hadoop, Kubernetes, TensorFlow, Java",Master,14,Telecommunications,2024-11-19,2025-01-27,1430,7.7,DataVision Ltd +AI11611,Principal Data Scientist,143077,USD,143077,EX,FT,Israel,M,Italy,50,"R, Spark, AWS, Scala, NLP",Master,12,Real Estate,2024-12-05,2025-02-02,2272,5.8,Cognitive Computing +AI11612,Robotics Engineer,55124,SGD,71661,EN,FT,Singapore,S,United Kingdom,50,"Statistics, Scala, Hadoop, Spark",Associate,1,Government,2024-03-23,2024-05-01,792,7,Digital Transformation LLC +AI11613,Data Analyst,202411,USD,202411,EX,FL,Sweden,S,Sweden,100,"SQL, R, Tableau, PyTorch, Java",PhD,16,Healthcare,2024-09-05,2024-10-26,2074,6.4,AI Innovations +AI11614,Deep Learning Engineer,84402,EUR,71742,MI,PT,Austria,S,Belgium,50,"AWS, Git, TensorFlow, R",PhD,2,Healthcare,2024-04-20,2024-05-29,1385,10,Autonomous Tech +AI11615,Machine Learning Engineer,194046,GBP,145535,EX,PT,United Kingdom,L,United Kingdom,100,"Linux, Azure, Statistics, PyTorch",PhD,12,Manufacturing,2024-12-10,2024-12-26,2089,9.9,Smart Analytics +AI11616,Research Scientist,59744,AUD,80654,EN,PT,Australia,S,Australia,100,"MLOps, Computer Vision, Deep Learning, R",Associate,0,Healthcare,2024-04-18,2024-05-12,1076,7.2,Future Systems +AI11617,ML Ops Engineer,102625,USD,102625,SE,FL,Israel,M,Israel,50,"Azure, SQL, GCP",Master,5,Government,2024-01-27,2024-03-18,751,7.9,Neural Networks Co +AI11618,Computer Vision Engineer,56790,EUR,48272,EN,FT,France,S,South Korea,100,"Git, GCP, Java",Master,1,Manufacturing,2024-01-28,2024-04-05,1966,5.2,Autonomous Tech +AI11619,AI Specialist,56948,USD,56948,EN,PT,Ireland,M,Ireland,50,"SQL, Mathematics, TensorFlow, AWS",Master,0,Transportation,2024-01-25,2024-04-04,1345,6.9,Quantum Computing Inc +AI11620,AI Product Manager,124698,USD,124698,MI,FT,United States,M,Chile,50,"Java, R, Scala, Linux",PhD,3,Gaming,2024-10-11,2024-11-24,600,5.1,AI Innovations +AI11621,Principal Data Scientist,158637,USD,158637,SE,PT,Norway,L,Indonesia,50,"Data Visualization, Docker, Azure, R, PyTorch",Associate,6,Real Estate,2024-02-22,2024-04-23,1254,7.8,Quantum Computing Inc +AI11622,AI Product Manager,104750,USD,104750,MI,CT,Israel,L,Switzerland,100,"PyTorch, Spark, Tableau, Computer Vision, Azure",Associate,4,Technology,2024-12-11,2025-01-23,2141,6.4,Autonomous Tech +AI11623,AI Software Engineer,149617,JPY,16457870,EX,CT,Japan,S,Japan,50,"Kubernetes, Scala, Java",PhD,13,Consulting,2024-03-03,2024-03-20,523,6.7,DataVision Ltd +AI11624,Data Analyst,54122,SGD,70359,EN,CT,Singapore,M,Singapore,100,"Spark, PyTorch, Statistics, Docker, Mathematics",Bachelor,1,Real Estate,2024-04-30,2024-07-11,851,7.3,Smart Analytics +AI11625,Deep Learning Engineer,103462,JPY,11380820,MI,PT,Japan,S,Germany,100,"SQL, Kubernetes, Computer Vision, Java",Bachelor,3,Gaming,2024-05-07,2024-05-24,1539,5.1,Future Systems +AI11626,Data Analyst,200620,USD,200620,EX,PT,Denmark,S,Denmark,100,"TensorFlow, NLP, GCP, AWS, PyTorch",PhD,10,Energy,2024-09-26,2024-11-05,1152,9.5,Digital Transformation LLC +AI11627,Deep Learning Engineer,63203,GBP,47402,EN,FT,United Kingdom,S,Israel,0,"NLP, Python, AWS",Bachelor,1,Technology,2024-09-21,2024-10-21,1794,5.4,Advanced Robotics +AI11628,Machine Learning Researcher,92506,EUR,78630,EN,FL,Netherlands,L,Netherlands,50,"Scala, Python, Mathematics",Bachelor,0,Manufacturing,2024-09-26,2024-10-10,565,6.2,Predictive Systems +AI11629,AI Research Scientist,78404,USD,78404,MI,FT,South Korea,S,South Korea,50,"Mathematics, TensorFlow, Tableau, MLOps, Kubernetes",PhD,4,Real Estate,2025-01-19,2025-02-25,2407,9.3,Future Systems +AI11630,AI Product Manager,155868,EUR,132488,SE,FT,Netherlands,L,Netherlands,0,"Hadoop, TensorFlow, NLP",Master,6,Technology,2024-12-05,2025-01-17,2008,5.3,Predictive Systems +AI11631,AI Research Scientist,156517,USD,156517,SE,FL,United States,M,United States,50,"SQL, Linux, Data Visualization",PhD,8,Healthcare,2024-10-11,2024-12-17,1487,6.4,Algorithmic Solutions +AI11632,Data Analyst,212507,USD,212507,EX,FT,United States,S,Estonia,100,"AWS, Scala, Java, Statistics",Associate,12,Finance,2025-03-30,2025-05-04,1171,9.9,Advanced Robotics +AI11633,Machine Learning Researcher,171831,JPY,18901410,SE,CT,Japan,L,Japan,0,"TensorFlow, Hadoop, NLP",Bachelor,5,Technology,2024-03-30,2024-05-12,1514,6.1,AI Innovations +AI11634,Computer Vision Engineer,208009,USD,208009,EX,FT,United States,S,Chile,50,"Spark, PyTorch, SQL",Bachelor,14,Transportation,2024-07-28,2024-10-06,2490,5.8,Quantum Computing Inc +AI11635,Data Scientist,193197,EUR,164217,EX,FL,Germany,L,Germany,50,"Tableau, Python, Spark, Mathematics",Associate,19,Telecommunications,2024-05-18,2024-06-24,1462,5.7,Smart Analytics +AI11636,AI Architect,105371,USD,105371,MI,FT,Norway,S,Colombia,100,"R, MLOps, Spark, PyTorch, GCP",Bachelor,4,Finance,2024-10-16,2024-11-21,797,9.7,Algorithmic Solutions +AI11637,Deep Learning Engineer,166349,CAD,207936,EX,CT,Canada,L,Canada,0,"Spark, NLP, Scala",Bachelor,14,Telecommunications,2024-04-13,2024-06-17,1478,7.6,Autonomous Tech +AI11638,Research Scientist,141464,USD,141464,SE,FT,Denmark,M,Denmark,100,"MLOps, Git, Scala, GCP",Bachelor,6,Manufacturing,2024-12-27,2025-02-09,1520,7.4,Cognitive Computing +AI11639,AI Consultant,28009,USD,28009,EN,CT,China,M,China,100,"Linux, SQL, MLOps",Master,1,Telecommunications,2024-03-04,2024-03-26,2322,5.1,Digital Transformation LLC +AI11640,Head of AI,173041,USD,173041,EX,FL,Finland,S,Finland,100,"NLP, Kubernetes, Deep Learning, Git",Master,10,Government,2024-01-14,2024-02-17,730,8,Autonomous Tech +AI11641,Robotics Engineer,239925,USD,239925,EX,CT,Finland,L,Finland,100,"Python, Linux, Data Visualization, Scala, Mathematics",PhD,10,Manufacturing,2024-08-23,2024-10-29,2431,7.9,TechCorp Inc +AI11642,Deep Learning Engineer,36984,USD,36984,EN,FT,China,L,China,0,"Hadoop, Java, R, Data Visualization, Kubernetes",Associate,0,Government,2024-06-13,2024-07-21,1370,8.3,Predictive Systems +AI11643,AI Consultant,251261,USD,251261,EX,PT,Denmark,L,Poland,100,"Azure, Git, Linux",Bachelor,18,Real Estate,2024-12-13,2025-02-11,593,7.8,Neural Networks Co +AI11644,AI Consultant,139815,USD,139815,EX,PT,South Korea,L,Turkey,0,"NLP, SQL, Java, Deep Learning",Bachelor,13,Gaming,2024-09-26,2024-11-25,969,8.3,DataVision Ltd +AI11645,Deep Learning Engineer,51437,EUR,43721,EN,PT,France,M,France,50,"MLOps, AWS, Python, Hadoop, Statistics",Master,0,Media,2025-01-11,2025-03-08,830,8.6,Quantum Computing Inc +AI11646,AI Software Engineer,89863,USD,89863,SE,CT,South Korea,S,South Korea,50,"Git, Hadoop, Python, Linux, Kubernetes",Master,6,Healthcare,2024-02-06,2024-03-30,1952,8.7,Cloud AI Solutions +AI11647,Machine Learning Researcher,65048,USD,65048,EN,PT,Denmark,S,Denmark,50,"Computer Vision, Scala, R, Mathematics, Azure",PhD,0,Healthcare,2024-12-12,2025-01-30,1762,7,AI Innovations +AI11648,Machine Learning Researcher,136806,USD,136806,SE,PT,Sweden,L,Sweden,100,"TensorFlow, R, NLP",Associate,6,Media,2024-04-21,2024-05-06,952,9,Future Systems +AI11649,Deep Learning Engineer,104749,SGD,136174,SE,FT,Singapore,S,Singapore,0,"GCP, TensorFlow, Deep Learning, Python, Git",Associate,7,Retail,2024-02-29,2024-03-17,1742,6.4,Machine Intelligence Group +AI11650,Robotics Engineer,96999,USD,96999,MI,PT,South Korea,L,South Korea,0,"Python, Deep Learning, NLP",Associate,4,Finance,2024-06-25,2024-08-18,1657,5.2,Advanced Robotics +AI11651,Principal Data Scientist,243815,USD,243815,EX,FL,Norway,S,Ukraine,100,"Scala, Java, AWS, R, NLP",Master,18,Healthcare,2024-08-06,2024-09-04,1774,9.8,Neural Networks Co +AI11652,AI Product Manager,76637,GBP,57478,MI,FL,United Kingdom,S,Australia,100,"R, PyTorch, Mathematics, Kubernetes",PhD,4,Education,2025-03-08,2025-05-18,2173,7.5,Digital Transformation LLC +AI11653,ML Ops Engineer,85502,USD,85502,EN,PT,Denmark,L,Denmark,100,"PyTorch, Data Visualization, Spark, Scala, Deep Learning",Bachelor,1,Education,2025-04-12,2025-06-06,2375,6.9,Advanced Robotics +AI11654,Research Scientist,120897,JPY,13298670,SE,CT,Japan,M,Japan,50,"Python, Java, Mathematics",Master,6,Consulting,2024-11-25,2024-12-11,2364,8.5,Machine Intelligence Group +AI11655,Robotics Engineer,91013,USD,91013,EN,FL,Denmark,M,Denmark,0,"Python, Docker, Linux, Git, Scala",Bachelor,0,Media,2024-01-15,2024-01-29,2453,9.9,Predictive Systems +AI11656,Data Engineer,85335,EUR,72535,MI,FL,Austria,S,Austria,50,"Git, PyTorch, MLOps, Computer Vision",PhD,3,Energy,2024-09-09,2024-11-16,1556,5.4,Cognitive Computing +AI11657,AI Consultant,163644,USD,163644,SE,FL,Ireland,L,Ireland,0,"Git, GCP, Deep Learning, Python",Master,7,Finance,2024-10-14,2024-12-16,2454,7.4,Digital Transformation LLC +AI11658,Autonomous Systems Engineer,95444,USD,95444,EN,FT,Norway,M,Luxembourg,0,"Hadoop, PyTorch, TensorFlow",PhD,0,Media,2025-03-31,2025-05-28,1706,8.3,Neural Networks Co +AI11659,Computer Vision Engineer,246523,EUR,209545,EX,PT,Netherlands,M,Netherlands,0,"Scala, PyTorch, Statistics, SQL, Spark",Associate,11,Healthcare,2024-09-23,2024-11-08,1759,6.4,DataVision Ltd +AI11660,Research Scientist,65060,USD,65060,EN,CT,Finland,S,Finland,50,"Data Visualization, Hadoop, Azure",Master,1,Healthcare,2025-01-24,2025-02-24,2176,5.5,Cloud AI Solutions +AI11661,Principal Data Scientist,78657,GBP,58993,EN,PT,United Kingdom,M,United Kingdom,50,"Docker, Tableau, R",Bachelor,1,Gaming,2025-02-25,2025-04-10,545,6.9,Predictive Systems +AI11662,AI Specialist,138491,JPY,15234010,EX,PT,Japan,S,Denmark,0,"Hadoop, Azure, Python",Master,17,Telecommunications,2024-11-01,2024-12-04,749,8.7,Autonomous Tech +AI11663,AI Research Scientist,78736,SGD,102357,EN,PT,Singapore,L,Singapore,0,"Computer Vision, Data Visualization, Scala",PhD,1,Transportation,2024-09-20,2024-11-22,1390,8.7,Autonomous Tech +AI11664,Research Scientist,72680,EUR,61778,EN,PT,France,L,France,0,"Tableau, Git, Computer Vision, TensorFlow",Master,1,Automotive,2024-08-22,2024-10-16,1594,5.2,Cloud AI Solutions +AI11665,Data Scientist,46963,CAD,58704,EN,FL,Canada,S,Canada,100,"NLP, Python, Azure, TensorFlow, PyTorch",PhD,0,Finance,2024-05-26,2024-07-23,2231,6.8,Algorithmic Solutions +AI11666,AI Software Engineer,196455,AUD,265214,EX,PT,Australia,M,Egypt,0,"TensorFlow, Mathematics, Kubernetes",Master,16,Healthcare,2024-04-15,2024-06-10,714,7.7,Smart Analytics +AI11667,Data Scientist,150699,GBP,113024,SE,FT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Scala",PhD,7,Consulting,2024-05-07,2024-07-14,1491,8.2,Neural Networks Co +AI11668,Robotics Engineer,225713,EUR,191856,EX,PT,Netherlands,M,Netherlands,100,"Tableau, Kubernetes, Mathematics",Master,18,Real Estate,2024-02-23,2024-03-09,764,7.6,Predictive Systems +AI11669,Robotics Engineer,89546,USD,89546,EX,PT,India,M,Indonesia,100,"Java, NLP, Hadoop, SQL, Mathematics",Associate,10,Energy,2024-06-28,2024-08-30,2223,7.3,Autonomous Tech +AI11670,Data Scientist,38039,USD,38039,SE,PT,India,M,India,100,"Deep Learning, Git, Kubernetes, GCP",PhD,6,Media,2024-06-30,2024-07-23,1391,6.2,Machine Intelligence Group +AI11671,Data Analyst,157935,CHF,142142,SE,PT,Switzerland,M,Switzerland,50,"Docker, Statistics, NLP, Scala, Python",PhD,6,Consulting,2024-05-13,2024-07-05,2149,8.2,Cognitive Computing +AI11672,Data Analyst,87759,SGD,114087,MI,PT,Singapore,S,Singapore,100,"Git, AWS, Docker, SQL",Bachelor,3,Telecommunications,2024-01-09,2024-03-10,1228,6.9,Advanced Robotics +AI11673,AI Architect,155389,GBP,116542,SE,FL,United Kingdom,L,United Kingdom,0,"Tableau, Hadoop, PyTorch, NLP, Mathematics",Master,7,Manufacturing,2024-05-22,2024-07-04,1487,9.3,Predictive Systems +AI11674,Machine Learning Engineer,73343,EUR,62342,EN,CT,France,M,France,50,"Java, Deep Learning, NLP, SQL, Python",PhD,1,Automotive,2024-08-11,2024-10-04,2451,8.6,Autonomous Tech +AI11675,NLP Engineer,24357,USD,24357,EN,FT,India,L,India,50,"Deep Learning, Hadoop, Kubernetes, Java",Master,1,Automotive,2024-06-03,2024-06-18,950,7.8,Future Systems +AI11676,Autonomous Systems Engineer,69149,USD,69149,EN,FL,Israel,M,Israel,50,"Data Visualization, Java, SQL",PhD,1,Retail,2024-07-30,2024-09-10,2197,8.5,DeepTech Ventures +AI11677,AI Specialist,65314,EUR,55517,EN,PT,France,S,France,50,"Linux, R, PyTorch, GCP, Git",Associate,1,Media,2024-06-20,2024-07-27,1963,5.8,AI Innovations +AI11678,Deep Learning Engineer,133224,USD,133224,SE,PT,Sweden,L,Sweden,50,"TensorFlow, Git, Python, Deep Learning",Master,7,Gaming,2024-07-18,2024-08-18,2306,6.3,Cloud AI Solutions +AI11679,Head of AI,38105,USD,38105,EN,CT,South Korea,S,Italy,0,"AWS, Python, Statistics, TensorFlow",Associate,1,Real Estate,2025-03-17,2025-04-03,563,7.8,Cloud AI Solutions +AI11680,Deep Learning Engineer,63981,USD,63981,EN,FL,Israel,L,Israel,0,"SQL, NLP, Tableau, Computer Vision",PhD,1,Retail,2024-01-09,2024-02-14,1632,8.7,Cognitive Computing +AI11681,AI Software Engineer,231463,GBP,173597,EX,PT,United Kingdom,L,United Kingdom,50,"Data Visualization, Scala, R",Master,12,Education,2024-04-17,2024-06-04,1661,7.4,DataVision Ltd +AI11682,Data Engineer,303234,USD,303234,EX,FL,United States,L,United States,0,"Python, MLOps, Java, TensorFlow, Git",Bachelor,10,Finance,2024-03-14,2024-04-19,2490,6.8,Cognitive Computing +AI11683,Data Analyst,57839,USD,57839,EN,FT,Ireland,S,Ireland,100,"Git, Python, Java, Computer Vision, Scala",PhD,1,Manufacturing,2024-07-04,2024-09-15,746,5.9,DeepTech Ventures +AI11684,Head of AI,105737,USD,105737,MI,FL,Norway,M,Norway,100,"Computer Vision, Kubernetes, TensorFlow, Hadoop, Statistics",Associate,4,Education,2024-11-10,2024-12-31,746,7.9,TechCorp Inc +AI11685,NLP Engineer,83703,GBP,62777,EN,CT,United Kingdom,M,United Kingdom,0,"NLP, Deep Learning, Spark",PhD,1,Technology,2025-01-14,2025-03-14,1926,7,Quantum Computing Inc +AI11686,Research Scientist,374078,USD,374078,EX,FL,Denmark,L,Denmark,100,"Docker, Kubernetes, Deep Learning",PhD,18,Media,2024-04-04,2024-04-27,617,8.4,Predictive Systems +AI11687,AI Consultant,73845,USD,73845,MI,PT,Sweden,S,Sweden,50,"Mathematics, R, AWS",Associate,3,Transportation,2025-03-13,2025-05-22,1960,8.4,Predictive Systems +AI11688,Autonomous Systems Engineer,199570,USD,199570,EX,PT,South Korea,M,South Korea,0,"MLOps, Java, AWS",Master,18,Real Estate,2024-10-29,2024-11-24,1566,5.8,Predictive Systems +AI11689,ML Ops Engineer,59456,USD,59456,EN,FL,Ireland,S,Ireland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Retail,2024-06-23,2024-09-01,765,5.6,Cloud AI Solutions +AI11690,Principal Data Scientist,46874,USD,46874,MI,CT,China,M,China,50,"PyTorch, GCP, Computer Vision, NLP, AWS",Associate,2,Education,2024-06-09,2024-08-11,730,9.2,Quantum Computing Inc +AI11691,Machine Learning Researcher,264204,USD,264204,EX,PT,United States,M,United States,100,"Kubernetes, Hadoop, NLP",Master,12,Education,2025-04-19,2025-05-21,1029,5.7,Advanced Robotics +AI11692,Autonomous Systems Engineer,92702,USD,92702,MI,CT,Denmark,S,Denmark,100,"Linux, MLOps, Deep Learning, Hadoop",Bachelor,4,Energy,2024-04-13,2024-05-31,803,6,Digital Transformation LLC +AI11693,Machine Learning Engineer,127152,USD,127152,SE,FT,Ireland,M,Ireland,100,"Kubernetes, PyTorch, Git, Hadoop",Master,9,Media,2024-03-11,2024-04-17,821,8.2,Future Systems +AI11694,AI Product Manager,97952,USD,97952,EX,FL,India,L,India,0,"Linux, Data Visualization, Git, Deep Learning",Master,15,Finance,2024-07-17,2024-09-18,957,5.7,Algorithmic Solutions +AI11695,Deep Learning Engineer,119734,EUR,101774,SE,CT,Austria,L,Australia,100,"Scala, Python, NLP, Azure",Master,6,Gaming,2025-02-21,2025-05-03,2012,5.1,Neural Networks Co +AI11696,Head of AI,52313,USD,52313,SE,FL,India,L,India,100,"GCP, NLP, Git, Azure, MLOps",PhD,8,Education,2025-04-03,2025-05-24,2225,6,Algorithmic Solutions +AI11697,Principal Data Scientist,150527,USD,150527,SE,PT,Norway,S,Norway,100,"Tableau, Python, TensorFlow, Spark, Scala",PhD,6,Energy,2025-04-10,2025-05-09,1649,6.3,TechCorp Inc +AI11698,Research Scientist,102071,EUR,86760,SE,CT,Austria,M,Austria,100,"Data Visualization, PyTorch, Tableau, Spark",Bachelor,8,Transportation,2024-09-29,2024-10-24,750,6.4,Digital Transformation LLC +AI11699,AI Specialist,120049,JPY,13205390,SE,FL,Japan,M,Australia,100,"Python, GCP, TensorFlow, Docker, Mathematics",Master,8,Healthcare,2024-09-12,2024-10-31,2407,6.7,Advanced Robotics +AI11700,Data Scientist,57666,USD,57666,EN,FT,United States,S,Germany,0,"Python, TensorFlow, MLOps",Master,1,Telecommunications,2025-02-12,2025-03-09,664,6.4,AI Innovations +AI11701,Research Scientist,48186,USD,48186,EN,FT,South Korea,M,Egypt,0,"Data Visualization, Tableau, Linux, MLOps",Associate,1,Technology,2024-01-18,2024-02-28,1545,7.3,Advanced Robotics +AI11702,Research Scientist,105485,EUR,89662,SE,PT,Germany,S,Germany,0,"Statistics, Azure, Python",PhD,7,Manufacturing,2024-10-31,2025-01-10,2359,8.1,Cloud AI Solutions +AI11703,NLP Engineer,131219,SGD,170585,SE,PT,Singapore,S,Singapore,50,"Azure, NLP, Scala",Bachelor,7,Media,2025-03-22,2025-04-18,1790,9.4,Advanced Robotics +AI11704,Robotics Engineer,51061,AUD,68932,EN,CT,Australia,M,Switzerland,50,"Java, Linux, PyTorch, Azure, Spark",Bachelor,1,Retail,2025-03-07,2025-05-16,900,8.2,Digital Transformation LLC +AI11705,AI Research Scientist,118577,USD,118577,MI,PT,Israel,L,Singapore,0,"Hadoop, Spark, TensorFlow, Mathematics, NLP",Master,3,Telecommunications,2024-11-17,2024-12-08,915,9.3,TechCorp Inc +AI11706,Robotics Engineer,123562,JPY,13591820,MI,PT,Japan,L,Canada,0,"NLP, Computer Vision, Linux",Bachelor,4,Healthcare,2024-01-08,2024-02-17,2221,8.1,Advanced Robotics +AI11707,AI Research Scientist,51487,GBP,38615,EN,FT,United Kingdom,S,United Kingdom,50,"Tableau, Docker, MLOps, R, Kubernetes",Associate,0,Education,2024-05-08,2024-05-29,1828,6.3,Advanced Robotics +AI11708,AI Research Scientist,48045,EUR,40838,EN,CT,Austria,M,South Africa,0,"NLP, Git, PyTorch",PhD,1,Healthcare,2025-01-04,2025-01-22,2067,6.2,Quantum Computing Inc +AI11709,Principal Data Scientist,107844,USD,107844,SE,FT,Sweden,M,India,0,"Hadoop, Linux, Data Visualization",PhD,5,Telecommunications,2024-02-19,2024-03-09,2493,6.6,TechCorp Inc +AI11710,Machine Learning Engineer,39178,USD,39178,EN,FT,South Korea,S,India,50,"R, SQL, MLOps, Statistics, GCP",Bachelor,1,Consulting,2024-02-25,2024-04-07,2194,8.4,Machine Intelligence Group +AI11711,AI Architect,222589,SGD,289366,EX,FL,Singapore,S,Singapore,100,"Scala, R, MLOps, AWS, Tableau",Associate,19,Technology,2025-04-01,2025-04-19,1448,7.8,AI Innovations +AI11712,AI Software Engineer,103634,EUR,88089,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, Data Visualization, Tableau, TensorFlow, Docker",PhD,2,Education,2024-03-26,2024-04-13,1772,6.2,Smart Analytics +AI11713,AI Consultant,144301,SGD,187591,SE,FT,Singapore,M,Singapore,0,"Spark, R, TensorFlow, Computer Vision",Bachelor,6,Healthcare,2024-12-17,2025-02-21,2482,8.9,Predictive Systems +AI11714,AI Specialist,99374,EUR,84468,SE,PT,Austria,M,Austria,0,"Git, Scala, Java",Associate,7,Transportation,2024-04-05,2024-04-22,2414,6.5,Quantum Computing Inc +AI11715,AI Software Engineer,182255,USD,182255,EX,FL,Sweden,M,Sweden,0,"Data Visualization, Spark, Python, TensorFlow",Associate,18,Manufacturing,2024-10-22,2024-11-13,846,8,TechCorp Inc +AI11716,Data Engineer,64006,USD,64006,MI,CT,Finland,S,Finland,100,"Java, Kubernetes, Data Visualization, Scala, AWS",PhD,2,Retail,2025-04-12,2025-06-07,1653,6.9,Autonomous Tech +AI11717,Autonomous Systems Engineer,240322,CHF,216290,SE,FL,Switzerland,L,Switzerland,100,"Docker, Mathematics, PyTorch",Bachelor,7,Government,2024-06-28,2024-08-10,2379,7.5,AI Innovations +AI11718,Computer Vision Engineer,90893,USD,90893,MI,PT,Ireland,M,Ireland,50,"MLOps, Python, Azure, Statistics",Bachelor,4,Automotive,2025-04-26,2025-07-07,1506,5.3,Cognitive Computing +AI11719,AI Research Scientist,126730,GBP,95048,SE,PT,United Kingdom,M,United Kingdom,50,"Java, Python, R, TensorFlow, Kubernetes",Associate,6,Automotive,2024-01-27,2024-03-25,760,8.2,TechCorp Inc +AI11720,Deep Learning Engineer,90617,USD,90617,MI,FT,Ireland,S,Ireland,50,"Deep Learning, Git, Java",PhD,4,Media,2024-12-31,2025-02-16,2047,8.8,DataVision Ltd +AI11721,Head of AI,67532,CAD,84415,EN,FT,Canada,M,Luxembourg,100,"Computer Vision, Git, R, Kubernetes",Associate,0,Education,2024-05-11,2024-07-04,1673,5.8,Cloud AI Solutions +AI11722,AI Product Manager,81482,USD,81482,EN,CT,United States,M,United States,50,"AWS, Scala, Kubernetes, NLP",Associate,0,Finance,2024-12-16,2025-02-01,1186,7.6,Advanced Robotics +AI11723,Data Engineer,100637,JPY,11070070,MI,CT,Japan,M,Japan,0,"Java, Scala, Tableau",Master,2,Manufacturing,2024-06-07,2024-08-09,2037,8.2,Smart Analytics +AI11724,Autonomous Systems Engineer,182186,USD,182186,SE,CT,United States,L,United States,50,"Linux, AWS, NLP, TensorFlow",Master,7,Media,2024-06-11,2024-07-20,1317,6.9,Autonomous Tech +AI11725,Research Scientist,124119,USD,124119,MI,CT,Denmark,S,Belgium,0,"Java, Data Visualization, Scala, TensorFlow",Master,2,Government,2024-12-04,2025-01-23,1255,9.6,Advanced Robotics +AI11726,Robotics Engineer,75711,EUR,64354,EN,FL,France,M,South Korea,0,"R, Scala, GCP",PhD,0,Government,2024-04-26,2024-05-29,1596,7.8,DataVision Ltd +AI11727,AI Specialist,105178,USD,105178,EX,CT,China,L,Indonesia,50,"AWS, Azure, Tableau, SQL",Master,17,Consulting,2024-02-21,2024-05-02,1551,8.1,Advanced Robotics +AI11728,Data Engineer,245876,USD,245876,EX,FL,United States,M,United States,0,"Hadoop, Data Visualization, SQL, AWS",Associate,13,Government,2024-02-17,2024-04-20,1530,5.7,Cognitive Computing +AI11729,Principal Data Scientist,60817,USD,60817,SE,PT,China,M,New Zealand,0,"Kubernetes, PyTorch, Java, Spark, Computer Vision",Bachelor,6,Energy,2025-04-04,2025-06-08,2238,5.3,AI Innovations +AI11730,Autonomous Systems Engineer,159519,AUD,215351,EX,CT,Australia,S,Australia,100,"Linux, Java, Spark",Bachelor,13,Finance,2025-04-30,2025-07-09,686,8.6,TechCorp Inc +AI11731,AI Software Engineer,62606,USD,62606,EN,FL,Norway,S,Norway,100,"Tableau, TensorFlow, Git, Python",PhD,1,Real Estate,2024-09-27,2024-10-24,2295,7.1,TechCorp Inc +AI11732,ML Ops Engineer,87179,USD,87179,MI,FL,Sweden,S,Denmark,50,"Python, GCP, PyTorch, MLOps, AWS",Associate,4,Education,2024-07-30,2024-09-02,2230,5.6,Neural Networks Co +AI11733,Autonomous Systems Engineer,248988,GBP,186741,EX,PT,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, AWS, SQL",PhD,18,Healthcare,2024-01-30,2024-02-15,2260,8.5,DeepTech Ventures +AI11734,Research Scientist,85390,EUR,72582,EN,CT,Austria,L,Austria,50,"Linux, Hadoop, Docker, Python, Kubernetes",Master,0,Manufacturing,2025-03-19,2025-04-19,1718,7.1,Machine Intelligence Group +AI11735,Machine Learning Researcher,85050,USD,85050,EN,FT,Norway,L,Ukraine,0,"TensorFlow, Java, AWS",PhD,0,Healthcare,2024-03-08,2024-05-10,1927,5.7,Machine Intelligence Group +AI11736,Machine Learning Researcher,162248,USD,162248,SE,FL,Denmark,M,China,50,"Python, NLP, TensorFlow",Master,7,Media,2024-11-27,2025-01-11,1029,5.6,Autonomous Tech +AI11737,Machine Learning Engineer,89020,USD,89020,MI,FT,Ireland,M,Ireland,50,"Kubernetes, Data Visualization, Computer Vision, MLOps, NLP",Master,3,Energy,2024-12-05,2024-12-24,1355,7.9,Cloud AI Solutions +AI11738,Head of AI,197899,EUR,168214,EX,FL,Netherlands,L,Netherlands,0,"MLOps, Hadoop, AWS, Scala, TensorFlow",Bachelor,17,Consulting,2024-08-06,2024-10-06,1178,7.4,DataVision Ltd +AI11739,AI Software Engineer,300946,USD,300946,EX,CT,Denmark,L,Denmark,50,"MLOps, Azure, SQL, Kubernetes",Master,11,Gaming,2024-01-05,2024-03-13,949,6.2,Cloud AI Solutions +AI11740,ML Ops Engineer,128716,AUD,173767,SE,FT,Australia,L,Chile,100,"Azure, Scala, SQL, Spark",Associate,6,Technology,2025-01-16,2025-02-04,704,7.8,Autonomous Tech +AI11741,Machine Learning Researcher,69635,USD,69635,MI,FL,Ireland,S,Austria,50,"Mathematics, TensorFlow, Hadoop",Master,4,Energy,2024-04-17,2024-06-02,2256,10,DataVision Ltd +AI11742,Robotics Engineer,75013,USD,75013,EN,FL,Sweden,M,Latvia,0,"Kubernetes, Docker, Hadoop, MLOps",Bachelor,1,Government,2024-01-20,2024-03-25,2410,6.2,Cognitive Computing +AI11743,Head of AI,55579,USD,55579,EX,CT,India,L,India,100,"Spark, Git, R, Computer Vision",PhD,15,Finance,2024-10-15,2024-11-28,2417,8.1,Autonomous Tech +AI11744,Data Engineer,296991,EUR,252442,EX,PT,Netherlands,L,Netherlands,0,"Computer Vision, Python, TensorFlow, Mathematics, GCP",PhD,14,Retail,2024-01-02,2024-02-13,2415,8.6,Algorithmic Solutions +AI11745,Autonomous Systems Engineer,112545,JPY,12379950,MI,PT,Japan,M,Japan,0,"Python, NLP, SQL",PhD,3,Retail,2025-01-21,2025-03-06,1781,7.6,Quantum Computing Inc +AI11746,Computer Vision Engineer,69324,USD,69324,EX,PT,China,M,Colombia,0,"NLP, SQL, Java, R, Tableau",PhD,14,Education,2024-10-24,2024-12-23,519,7.5,DeepTech Ventures +AI11747,AI Research Scientist,98287,USD,98287,SE,FT,South Korea,S,South Korea,100,"R, Hadoop, Java, GCP, NLP",Bachelor,8,Retail,2024-12-05,2024-12-27,2317,7.2,DataVision Ltd +AI11748,AI Research Scientist,115628,SGD,150316,MI,CT,Singapore,L,Singapore,100,"Computer Vision, Python, GCP",Bachelor,2,Energy,2025-04-23,2025-07-03,2069,6.6,TechCorp Inc +AI11749,AI Research Scientist,61446,USD,61446,EN,PT,Finland,L,Finland,50,"Docker, Linux, Tableau",Master,0,Education,2025-02-08,2025-02-26,1567,8.6,Neural Networks Co +AI11750,AI Consultant,120919,USD,120919,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, AWS",Associate,3,Healthcare,2025-03-20,2025-04-13,1792,8.8,Cloud AI Solutions +AI11751,Research Scientist,145685,SGD,189391,SE,FL,Singapore,L,Chile,50,"AWS, Hadoop, NLP",Bachelor,5,Education,2024-11-30,2025-01-18,1182,7.2,DataVision Ltd +AI11752,Autonomous Systems Engineer,67265,USD,67265,EN,FL,South Korea,L,South Africa,100,"SQL, Kubernetes, Mathematics, PyTorch",Master,0,Transportation,2024-03-06,2024-04-05,927,9.6,DeepTech Ventures +AI11753,Principal Data Scientist,93562,CAD,116953,MI,CT,Canada,S,Canada,100,"Tableau, Linux, Kubernetes, GCP, Spark",Bachelor,4,Government,2024-02-26,2024-04-26,1548,5.6,DataVision Ltd +AI11754,AI Software Engineer,128363,EUR,109109,SE,CT,Germany,L,Germany,0,"Azure, Linux, Python, SQL",PhD,9,Media,2024-09-28,2024-12-10,591,5.6,Cognitive Computing +AI11755,Data Scientist,142169,EUR,120844,SE,FL,Netherlands,M,Netherlands,50,"Tableau, NLP, Scala, Java",Master,9,Transportation,2024-10-01,2024-12-03,1840,8.7,Autonomous Tech +AI11756,Data Analyst,82106,EUR,69790,MI,FL,Germany,M,Germany,0,"Java, Git, Computer Vision, Statistics, Data Visualization",PhD,4,Consulting,2024-02-01,2024-04-04,1738,5.8,Cognitive Computing +AI11757,AI Software Engineer,349865,CHF,314879,EX,FL,Switzerland,M,Switzerland,50,"Mathematics, Hadoop, Data Visualization",Associate,17,Automotive,2024-03-27,2024-06-06,661,9.9,Algorithmic Solutions +AI11758,Data Engineer,105787,USD,105787,SE,FL,South Korea,M,South Korea,100,"R, SQL, PyTorch, Mathematics",PhD,5,Telecommunications,2024-12-23,2025-01-18,2347,9.8,Smart Analytics +AI11759,Data Scientist,123402,USD,123402,MI,CT,Sweden,L,Ukraine,100,"NLP, AWS, PyTorch",Master,3,Gaming,2024-11-27,2024-12-22,592,7.6,Autonomous Tech +AI11760,Machine Learning Researcher,239675,USD,239675,EX,FT,Israel,M,Malaysia,100,"Tableau, MLOps, SQL, Mathematics, Git",Associate,12,Transportation,2024-01-13,2024-02-09,1523,8.8,Advanced Robotics +AI11761,Principal Data Scientist,241965,AUD,326653,EX,FT,Australia,L,Australia,100,"Hadoop, Data Visualization, Tableau, Deep Learning, Python",Bachelor,19,Telecommunications,2024-11-07,2024-11-24,853,8.5,Smart Analytics +AI11762,Machine Learning Engineer,76847,USD,76847,MI,FT,Sweden,M,Sweden,50,"MLOps, Computer Vision, SQL, Mathematics",Bachelor,4,Transportation,2024-07-17,2024-09-23,1659,7.9,Cloud AI Solutions +AI11763,Computer Vision Engineer,200851,USD,200851,SE,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Python, Azure",PhD,7,Gaming,2024-11-29,2025-01-11,2272,7.8,Cognitive Computing +AI11764,Research Scientist,130522,USD,130522,MI,FL,Denmark,L,Denmark,50,"Linux, Data Visualization, Hadoop, Git",Associate,3,Automotive,2024-11-22,2025-02-03,1442,5.3,DataVision Ltd +AI11765,AI Research Scientist,68149,USD,68149,EN,PT,South Korea,L,Thailand,50,"GCP, Linux, Spark, Computer Vision, Mathematics",Master,0,Manufacturing,2024-05-29,2024-07-05,673,6.1,Future Systems +AI11766,Principal Data Scientist,61452,EUR,52234,EN,FL,Netherlands,M,Singapore,0,"Python, AWS, Data Visualization, PyTorch, Kubernetes",Associate,0,Education,2025-01-15,2025-03-07,1472,9.6,Neural Networks Co +AI11767,Head of AI,86593,SGD,112571,MI,FL,Singapore,S,Singapore,100,"Mathematics, Computer Vision, Tableau, MLOps, Hadoop",Master,2,Transportation,2024-06-17,2024-08-04,766,9.4,Smart Analytics +AI11768,AI Consultant,62600,USD,62600,EN,FL,Norway,S,Norway,0,"AWS, R, MLOps, SQL",Master,1,Education,2025-03-29,2025-04-29,851,8,TechCorp Inc +AI11769,Machine Learning Researcher,77533,USD,77533,EN,FT,Denmark,M,Denmark,0,"Statistics, SQL, Python",Master,0,Telecommunications,2025-04-18,2025-05-20,2403,6.5,Autonomous Tech +AI11770,Deep Learning Engineer,212689,EUR,180786,EX,PT,Austria,L,Norway,50,"SQL, Git, Hadoop, Docker, GCP",Master,13,Telecommunications,2024-05-17,2024-06-20,2432,9.3,Advanced Robotics +AI11771,Data Scientist,118889,USD,118889,MI,FL,Israel,L,Netherlands,50,"Hadoop, SQL, Scala",PhD,2,Media,2024-08-18,2024-10-17,669,5.3,Advanced Robotics +AI11772,AI Software Engineer,145546,GBP,109160,SE,FT,United Kingdom,M,United Kingdom,100,"Statistics, Python, NLP, Deep Learning, R",Master,7,Telecommunications,2024-09-06,2024-11-05,1299,7.1,Quantum Computing Inc +AI11773,Deep Learning Engineer,91754,EUR,77991,MI,FL,Netherlands,S,Netherlands,100,"Hadoop, TensorFlow, PyTorch",Associate,3,Transportation,2024-07-27,2024-08-18,745,6.8,Autonomous Tech +AI11774,Research Scientist,144229,GBP,108172,EX,FL,United Kingdom,M,Germany,100,"Kubernetes, GCP, SQL",PhD,18,Real Estate,2024-02-16,2024-03-10,1543,8,Neural Networks Co +AI11775,Robotics Engineer,109199,EUR,92819,SE,PT,Austria,S,Austria,0,"Kubernetes, Statistics, Scala, PyTorch",Master,7,Automotive,2025-02-03,2025-03-08,2168,8.3,Quantum Computing Inc +AI11776,Head of AI,56909,USD,56909,EN,CT,Finland,M,Finland,100,"SQL, Scala, PyTorch, GCP, Java",PhD,1,Real Estate,2024-04-16,2024-05-27,1343,7,Algorithmic Solutions +AI11777,AI Consultant,117496,USD,117496,EX,PT,China,M,China,100,"Deep Learning, Docker, Data Visualization, Tableau, R",Associate,19,Transportation,2024-01-09,2024-02-01,1773,6.1,Predictive Systems +AI11778,Machine Learning Researcher,115487,USD,115487,MI,FL,Denmark,L,Denmark,100,"Kubernetes, PyTorch, Azure, Spark",Associate,4,Telecommunications,2024-01-02,2024-03-15,980,7.2,Cognitive Computing +AI11779,Computer Vision Engineer,115188,EUR,97910,MI,FT,Netherlands,M,India,0,"Data Visualization, NLP, SQL",PhD,4,Telecommunications,2024-08-07,2024-09-06,609,6.4,Cognitive Computing +AI11780,ML Ops Engineer,192782,USD,192782,EX,FL,Ireland,M,Ireland,50,"MLOps, Statistics, Mathematics, Scala, Data Visualization",Associate,16,Media,2025-03-21,2025-04-24,648,9.1,DeepTech Ventures +AI11781,Principal Data Scientist,158600,EUR,134810,EX,CT,Netherlands,S,Netherlands,100,"Python, Linux, Deep Learning",PhD,14,Automotive,2024-09-23,2024-11-18,582,5.5,Smart Analytics +AI11782,Robotics Engineer,64447,GBP,48335,EN,CT,United Kingdom,M,United Kingdom,100,"Computer Vision, Git, Tableau",Master,0,Finance,2024-07-25,2024-09-05,1713,6.5,Future Systems +AI11783,Research Scientist,189773,CHF,170796,SE,FL,Switzerland,M,Ukraine,100,"Computer Vision, Python, TensorFlow",Associate,8,Transportation,2024-05-28,2024-07-24,1824,6.1,Predictive Systems +AI11784,ML Ops Engineer,136525,CAD,170656,SE,CT,Canada,L,Canada,100,"Docker, Azure, Mathematics",Bachelor,9,Healthcare,2024-09-22,2024-11-21,1768,5.3,Algorithmic Solutions +AI11785,Head of AI,108746,USD,108746,EX,FT,South Korea,S,South Korea,50,"Azure, R, Scala, Tableau, Statistics",Master,16,Technology,2025-03-14,2025-05-24,2133,6.3,TechCorp Inc +AI11786,Robotics Engineer,79890,USD,79890,EX,PT,China,S,United States,50,"Computer Vision, Hadoop, GCP, Statistics",PhD,15,Automotive,2024-11-29,2024-12-20,1445,5.3,Predictive Systems +AI11787,AI Architect,128508,USD,128508,EX,FT,Finland,S,Nigeria,50,"Kubernetes, Docker, Spark",Master,16,Technology,2024-11-28,2025-01-05,1335,10,Algorithmic Solutions +AI11788,Computer Vision Engineer,149717,EUR,127259,SE,FT,Netherlands,M,Netherlands,0,"Mathematics, GCP, SQL",Master,6,Consulting,2024-05-22,2024-07-12,893,5.5,Cognitive Computing +AI11789,ML Ops Engineer,74780,CHF,67302,EN,CT,Switzerland,M,Italy,100,"Computer Vision, Mathematics, Tableau, Data Visualization",Master,0,Automotive,2025-03-26,2025-04-11,846,8.7,Autonomous Tech +AI11790,Data Analyst,86855,EUR,73827,EN,FT,France,L,France,50,"PyTorch, Deep Learning, NLP, R, AWS",Associate,1,Gaming,2024-03-06,2024-04-30,577,9.1,Cloud AI Solutions +AI11791,AI Research Scientist,153299,AUD,206954,SE,CT,Australia,L,Egypt,0,"TensorFlow, Python, Deep Learning",Master,9,Energy,2024-04-26,2024-05-11,1120,5.6,DeepTech Ventures +AI11792,Head of AI,53256,USD,53256,EN,PT,Ireland,S,Ireland,100,"GCP, R, Data Visualization, Hadoop, Kubernetes",Associate,1,Gaming,2024-03-29,2024-04-27,1989,7.5,Digital Transformation LLC +AI11793,ML Ops Engineer,104761,USD,104761,EN,CT,Norway,L,Norway,0,"Computer Vision, Git, GCP, Data Visualization",Associate,1,Automotive,2024-09-08,2024-11-13,1927,5.5,DeepTech Ventures +AI11794,AI Product Manager,257772,JPY,28354920,EX,CT,Japan,L,United States,0,"Java, R, Linux, SQL, NLP",Bachelor,11,Education,2024-02-19,2024-04-22,1495,7.6,Smart Analytics +AI11795,Data Analyst,113051,USD,113051,SE,FL,Israel,M,Thailand,50,"Mathematics, Deep Learning, Data Visualization",Master,5,Telecommunications,2024-01-04,2024-03-06,728,5.4,AI Innovations +AI11796,AI Architect,184356,JPY,20279160,SE,PT,Japan,L,Japan,100,"AWS, Tableau, Python",Bachelor,9,Consulting,2024-04-03,2024-04-24,1525,6.7,DeepTech Ventures +AI11797,AI Research Scientist,48522,CAD,60653,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, Tableau",Bachelor,1,Education,2024-05-25,2024-07-20,1523,6.9,Machine Intelligence Group +AI11798,Data Engineer,57358,SGD,74565,EN,CT,Singapore,M,Singapore,100,"Kubernetes, Docker, MLOps, Scala, Mathematics",Associate,0,Education,2025-04-18,2025-05-03,1292,8.7,Future Systems +AI11799,AI Architect,92877,CAD,116096,SE,FT,Canada,S,Canada,0,"Statistics, AWS, Deep Learning",Associate,8,Manufacturing,2024-01-06,2024-03-13,2113,9.1,Cloud AI Solutions +AI11800,Data Engineer,64999,USD,64999,MI,FT,Israel,S,Israel,0,"GCP, Mathematics, Data Visualization, Python",Associate,3,Transportation,2024-03-22,2024-04-16,2159,9.7,Neural Networks Co +AI11801,Deep Learning Engineer,216255,EUR,183817,EX,PT,Germany,L,Germany,50,"SQL, AWS, Tableau",Bachelor,14,Technology,2024-05-01,2024-07-07,742,8.8,DataVision Ltd +AI11802,AI Software Engineer,139600,CAD,174500,SE,FT,Canada,L,Canada,50,"PyTorch, Kubernetes, Computer Vision, Python, Tableau",PhD,9,Gaming,2024-05-08,2024-07-01,1981,9.8,Machine Intelligence Group +AI11803,AI Specialist,214259,USD,214259,SE,FT,Norway,L,Norway,50,"Python, Docker, Azure, Mathematics, Java",PhD,9,Automotive,2025-04-27,2025-05-11,2008,5.9,Predictive Systems +AI11804,Machine Learning Engineer,90613,USD,90613,EX,FL,India,L,India,0,"SQL, Git, Deep Learning, AWS",PhD,12,Education,2024-07-17,2024-09-06,1898,5.4,Future Systems +AI11805,AI Software Engineer,237611,AUD,320775,EX,PT,Australia,M,Australia,0,"Java, Computer Vision, Python, Mathematics",Associate,18,Automotive,2024-09-15,2024-11-23,2125,7.3,Quantum Computing Inc +AI11806,AI Specialist,85520,USD,85520,MI,CT,Israel,L,Israel,50,"Linux, SQL, Python, Scala",Master,2,Technology,2025-02-25,2025-03-11,1858,8.4,Digital Transformation LLC +AI11807,Computer Vision Engineer,120980,CAD,151225,EX,CT,Canada,S,Ukraine,0,"Computer Vision, Azure, Spark",Bachelor,10,Healthcare,2024-04-19,2024-05-31,940,7,Cognitive Computing +AI11808,Autonomous Systems Engineer,91834,EUR,78059,MI,PT,Austria,S,Portugal,50,"PyTorch, Scala, Data Visualization",Master,4,Government,2024-02-27,2024-04-21,516,7.9,DeepTech Ventures +AI11809,Computer Vision Engineer,197241,USD,197241,EX,FT,United States,M,Nigeria,0,"Deep Learning, TensorFlow, Hadoop, GCP",Bachelor,19,Education,2024-11-07,2024-12-28,652,7.3,Predictive Systems +AI11810,Machine Learning Researcher,26172,USD,26172,MI,FL,India,S,India,100,"Linux, NLP, Scala, Statistics",PhD,2,Consulting,2025-02-09,2025-03-14,603,5,Smart Analytics +AI11811,ML Ops Engineer,95730,USD,95730,SE,FT,Israel,S,Israel,0,"Tableau, Kubernetes, TensorFlow, Data Visualization, NLP",Master,5,Consulting,2024-02-26,2024-04-07,1257,6.2,Quantum Computing Inc +AI11812,Machine Learning Engineer,269491,USD,269491,EX,FT,United States,S,United States,50,"Tableau, R, Azure",Associate,15,Consulting,2024-11-04,2024-11-29,2469,8.9,Digital Transformation LLC +AI11813,Research Scientist,103816,CHF,93434,EN,FL,Switzerland,M,Switzerland,0,"GCP, R, Mathematics",Master,1,Government,2025-01-21,2025-02-25,1061,9.4,DataVision Ltd +AI11814,Data Analyst,120743,USD,120743,SE,PT,South Korea,M,Nigeria,100,"PyTorch, Java, Data Visualization",Bachelor,8,Education,2024-08-20,2024-10-07,2458,8.4,TechCorp Inc +AI11815,Data Scientist,23025,USD,23025,MI,FT,India,S,Denmark,100,"Linux, Hadoop, Python, Computer Vision",Associate,4,Consulting,2024-04-04,2024-05-15,1444,5.5,Machine Intelligence Group +AI11816,Autonomous Systems Engineer,44505,USD,44505,SE,FT,India,L,Romania,50,"Hadoop, Data Visualization, Git",Associate,6,Telecommunications,2024-10-04,2024-11-23,2406,8.7,Cognitive Computing +AI11817,Head of AI,105183,JPY,11570130,MI,PT,Japan,L,South Korea,100,"GCP, Spark, Deep Learning",PhD,3,Gaming,2024-09-03,2024-09-30,633,5.8,Autonomous Tech +AI11818,Machine Learning Engineer,137294,USD,137294,EX,PT,Israel,S,Mexico,0,"R, Scala, Docker, GCP",Master,12,Finance,2024-02-03,2024-03-05,1274,8.3,DeepTech Ventures +AI11819,ML Ops Engineer,101696,GBP,76272,SE,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Azure, PyTorch, Statistics, Mathematics",Associate,6,Telecommunications,2024-04-08,2024-06-15,766,7.1,Autonomous Tech +AI11820,Data Analyst,64069,EUR,54459,MI,PT,Austria,S,Austria,50,"Docker, NLP, Mathematics, Data Visualization",Bachelor,3,Energy,2024-02-28,2024-03-14,748,5.4,TechCorp Inc +AI11821,AI Product Manager,111264,USD,111264,SE,PT,South Korea,M,South Korea,100,"Data Visualization, Linux, SQL, R, Deep Learning",PhD,6,Media,2024-09-16,2024-10-28,2399,8.8,Smart Analytics +AI11822,Principal Data Scientist,109807,USD,109807,MI,PT,Denmark,M,Denmark,50,"Python, Spark, Deep Learning",Associate,4,Telecommunications,2024-10-04,2024-11-24,1800,7.9,Cloud AI Solutions +AI11823,AI Research Scientist,92835,EUR,78910,MI,CT,Netherlands,M,Netherlands,100,"Spark, Computer Vision, PyTorch, Tableau",Associate,3,Retail,2025-02-04,2025-03-07,2441,6.1,Neural Networks Co +AI11824,AI Product Manager,203369,EUR,172864,EX,CT,France,M,France,0,"PyTorch, Docker, Deep Learning",Bachelor,13,Retail,2024-09-09,2024-10-29,1041,7.4,Future Systems +AI11825,Head of AI,177370,USD,177370,EX,CT,Israel,S,Israel,100,"Git, AWS, Python, TensorFlow",Master,17,Telecommunications,2024-10-29,2024-12-16,1070,9.3,Quantum Computing Inc +AI11826,AI Software Engineer,244805,CHF,220325,EX,PT,Switzerland,L,Switzerland,100,"Docker, Python, Data Visualization, TensorFlow",PhD,18,Retail,2024-05-25,2024-07-11,1889,8.5,Algorithmic Solutions +AI11827,AI Product Manager,35462,USD,35462,MI,FT,India,L,India,100,"Tableau, AWS, Mathematics, Linux",Bachelor,3,Healthcare,2024-11-22,2024-12-07,1136,9.7,Future Systems +AI11828,Data Scientist,68404,CAD,85505,EN,FL,Canada,L,Romania,100,"Azure, Scala, SQL, PyTorch, Spark",Associate,0,Real Estate,2024-07-18,2024-09-20,2166,6.5,Cognitive Computing +AI11829,Autonomous Systems Engineer,128996,AUD,174145,SE,FT,Australia,L,Ukraine,100,"GCP, Spark, MLOps, NLP, SQL",Bachelor,7,Healthcare,2024-10-08,2024-12-04,1539,5,Machine Intelligence Group +AI11830,Data Analyst,72807,EUR,61886,EN,FT,Austria,M,Austria,100,"Git, R, Scala, Deep Learning, SQL",PhD,0,Energy,2024-03-02,2024-04-10,2177,7.5,Autonomous Tech +AI11831,Deep Learning Engineer,107118,USD,107118,MI,CT,Denmark,M,Denmark,100,"PyTorch, Data Visualization, GCP, TensorFlow, Linux",Bachelor,4,Automotive,2025-04-11,2025-05-01,2040,8.1,Cognitive Computing +AI11832,Principal Data Scientist,27731,USD,27731,MI,FT,India,M,India,0,"Python, Linux, TensorFlow",Master,4,Consulting,2024-09-04,2024-10-14,976,8.5,Autonomous Tech +AI11833,AI Research Scientist,74228,USD,74228,EN,PT,Norway,M,Norway,100,"Mathematics, Kubernetes, R, Spark, Scala",PhD,0,Automotive,2025-03-29,2025-05-21,2187,9.4,Digital Transformation LLC +AI11834,AI Consultant,77712,USD,77712,EN,FL,Sweden,M,Sweden,0,"Hadoop, PyTorch, Git, Computer Vision",Associate,1,Manufacturing,2024-02-25,2024-05-01,826,6.1,AI Innovations +AI11835,AI Specialist,94668,USD,94668,EX,PT,China,S,China,50,"SQL, NLP, Kubernetes, PyTorch, GCP",PhD,19,Consulting,2024-03-18,2024-04-22,1984,5.4,Cloud AI Solutions +AI11836,AI Architect,212705,USD,212705,EX,FT,South Korea,L,Luxembourg,100,"R, GCP, Tableau",Master,16,Manufacturing,2024-01-15,2024-03-28,2206,6.1,Quantum Computing Inc +AI11837,AI Research Scientist,200761,CHF,180685,EX,PT,Switzerland,S,Switzerland,50,"Kubernetes, SQL, PyTorch, R",Master,11,Real Estate,2024-05-02,2024-06-07,1090,7.1,DeepTech Ventures +AI11838,Machine Learning Engineer,85039,AUD,114803,MI,CT,Australia,M,Australia,100,"Statistics, Tableau, MLOps, Java",Bachelor,2,Manufacturing,2024-08-10,2024-09-22,1756,9.5,Predictive Systems +AI11839,AI Product Manager,62080,USD,62080,EX,CT,India,L,India,50,"Scala, Git, Tableau, Kubernetes, Azure",Bachelor,12,Real Estate,2024-10-03,2024-10-30,987,5.1,Cognitive Computing +AI11840,AI Architect,196292,USD,196292,EX,CT,Sweden,M,Argentina,100,"R, SQL, Deep Learning",Associate,18,Education,2024-03-22,2024-04-29,1280,9.4,Quantum Computing Inc +AI11841,AI Specialist,158220,USD,158220,EX,CT,Sweden,M,Sweden,0,"SQL, TensorFlow, Deep Learning",PhD,19,Gaming,2024-03-13,2024-04-13,1358,7.8,Cognitive Computing +AI11842,AI Architect,29068,USD,29068,MI,FT,India,M,Indonesia,100,"Computer Vision, Hadoop, Linux",Master,4,Gaming,2024-09-14,2024-10-28,913,7.7,DataVision Ltd +AI11843,Data Scientist,61344,GBP,46008,EN,CT,United Kingdom,M,France,0,"TensorFlow, Java, Mathematics, GCP",PhD,1,Transportation,2024-06-15,2024-08-16,1521,7.4,Smart Analytics +AI11844,AI Architect,192580,CHF,173322,SE,FL,Switzerland,M,Switzerland,50,"TensorFlow, NLP, Linux",PhD,5,Technology,2024-01-20,2024-02-12,1743,9.7,Predictive Systems +AI11845,Data Engineer,69295,SGD,90084,EN,PT,Singapore,L,Singapore,100,"SQL, GCP, Computer Vision",Master,0,Retail,2024-09-16,2024-11-18,2296,8.5,TechCorp Inc +AI11846,Computer Vision Engineer,132554,EUR,112671,SE,CT,France,M,France,50,"Kubernetes, Scala, Computer Vision, Java, Docker",Associate,7,Real Estate,2024-05-10,2024-07-04,826,8.8,Quantum Computing Inc +AI11847,AI Consultant,172103,EUR,146288,EX,FL,France,S,Czech Republic,0,"R, SQL, Statistics, Azure, Computer Vision",Master,14,Manufacturing,2024-02-10,2024-03-01,1648,7.4,DeepTech Ventures +AI11848,AI Specialist,113947,GBP,85460,SE,FT,United Kingdom,M,United Kingdom,50,"Git, Deep Learning, R",Bachelor,8,Energy,2025-04-13,2025-05-21,1447,9.4,Cognitive Computing +AI11849,AI Consultant,38972,USD,38972,MI,CT,China,M,China,50,"Tableau, Hadoop, Deep Learning, Spark, GCP",Associate,2,Retail,2024-07-28,2024-08-19,2480,9.4,Future Systems +AI11850,Robotics Engineer,129198,EUR,109818,SE,PT,Austria,L,Canada,100,"SQL, Git, NLP, Python, Kubernetes",Associate,9,Healthcare,2024-11-20,2025-01-20,2336,7.3,DataVision Ltd +AI11851,Machine Learning Researcher,85968,USD,85968,EN,FL,Sweden,L,Sweden,0,"R, Azure, NLP, SQL, Data Visualization",Bachelor,1,Government,2024-03-21,2024-04-10,2330,5.2,Cognitive Computing +AI11852,AI Specialist,89602,USD,89602,EN,PT,Denmark,M,Portugal,50,"Computer Vision, Java, Python, Scala",PhD,1,Finance,2024-11-17,2025-01-06,2474,5.5,Digital Transformation LLC +AI11853,AI Software Engineer,75324,USD,75324,EN,PT,United States,S,United States,50,"GCP, Scala, Data Visualization, Spark",PhD,1,Real Estate,2025-02-06,2025-02-26,830,9.3,AI Innovations +AI11854,AI Consultant,89924,USD,89924,MI,CT,Finland,S,Finland,0,"Azure, Docker, Deep Learning",Master,3,Media,2024-11-17,2025-01-10,844,9.8,Digital Transformation LLC +AI11855,Machine Learning Engineer,65329,USD,65329,EN,PT,South Korea,M,Switzerland,100,"R, Hadoop, Spark, Mathematics, Computer Vision",Bachelor,0,Healthcare,2024-04-30,2024-05-28,547,5.2,DataVision Ltd +AI11856,AI Software Engineer,93470,AUD,126185,MI,CT,Australia,M,Australia,0,"MLOps, R, Tableau",Master,4,Media,2024-11-29,2024-12-22,1805,8.1,Digital Transformation LLC +AI11857,Research Scientist,95936,JPY,10552960,EN,PT,Japan,L,Japan,100,"Git, Python, MLOps",Master,0,Finance,2024-08-17,2024-10-26,1297,8.2,Predictive Systems +AI11858,Machine Learning Researcher,112418,SGD,146143,MI,PT,Singapore,M,Singapore,0,"Linux, R, Hadoop, Statistics, MLOps",Associate,4,Consulting,2024-08-31,2024-09-30,1676,9.9,AI Innovations +AI11859,AI Architect,210662,USD,210662,EX,CT,Sweden,S,Sweden,0,"SQL, Hadoop, TensorFlow, Spark",Bachelor,16,Gaming,2024-09-10,2024-10-07,1986,7.4,DataVision Ltd +AI11860,Machine Learning Engineer,55827,USD,55827,EN,FT,South Korea,M,South Korea,0,"SQL, Docker, MLOps, Azure",Associate,1,Real Estate,2024-07-09,2024-08-20,2250,5.2,Neural Networks Co +AI11861,Deep Learning Engineer,174827,USD,174827,SE,PT,Denmark,M,Denmark,50,"Computer Vision, SQL, Kubernetes, Mathematics",Bachelor,5,Healthcare,2024-07-18,2024-09-25,1268,5.9,Machine Intelligence Group +AI11862,Head of AI,222968,USD,222968,EX,FT,South Korea,L,Nigeria,100,"PyTorch, Hadoop, TensorFlow",PhD,17,Energy,2024-10-30,2024-12-18,1644,6,Autonomous Tech +AI11863,Data Analyst,250630,USD,250630,EX,FL,Denmark,L,Estonia,50,"Python, Docker, MLOps, Azure",Bachelor,15,Telecommunications,2024-07-29,2024-09-02,606,6.1,Cloud AI Solutions +AI11864,AI Product Manager,188795,CHF,169916,SE,FT,Switzerland,M,Switzerland,0,"R, Docker, Tableau, Azure, PyTorch",Associate,5,Technology,2025-01-24,2025-02-22,1357,7.6,AI Innovations +AI11865,Data Scientist,116184,EUR,98756,SE,FT,France,S,Italy,50,"Linux, Java, Scala, Kubernetes, MLOps",PhD,5,Automotive,2025-02-15,2025-03-26,2428,5.5,Digital Transformation LLC +AI11866,Deep Learning Engineer,85463,USD,85463,EN,FL,Israel,L,Switzerland,100,"Deep Learning, MLOps, Statistics, NLP",Associate,1,Government,2024-04-16,2024-05-04,2237,6.5,Smart Analytics +AI11867,Robotics Engineer,62097,EUR,52782,EN,PT,Netherlands,S,Netherlands,0,"Hadoop, Kubernetes, Python",Associate,1,Energy,2024-11-30,2025-02-04,1363,9.3,Cognitive Computing +AI11868,Data Scientist,77625,USD,77625,EN,FL,Israel,L,Israel,50,"AWS, Kubernetes, PyTorch, Docker",Bachelor,1,Technology,2025-01-14,2025-03-07,1422,5.7,Digital Transformation LLC +AI11869,Data Engineer,89334,JPY,9826740,MI,CT,Japan,M,Canada,100,"Linux, GCP, Statistics, AWS, Hadoop",Bachelor,2,Manufacturing,2024-09-21,2024-10-19,733,9.5,Neural Networks Co +AI11870,Deep Learning Engineer,115065,EUR,97805,SE,CT,Austria,M,Austria,0,"SQL, Git, Tableau, Linux",Master,7,Consulting,2024-02-05,2024-03-02,1057,6.6,Quantum Computing Inc +AI11871,NLP Engineer,29565,USD,29565,MI,CT,India,M,India,100,"Python, Linux, Tableau, TensorFlow",PhD,2,Manufacturing,2025-03-21,2025-05-10,2038,8.4,Neural Networks Co +AI11872,Autonomous Systems Engineer,151856,USD,151856,SE,FL,Denmark,M,Denmark,0,"PyTorch, Docker, Tableau, Spark, GCP",PhD,6,Real Estate,2024-01-03,2024-03-04,795,6.1,Algorithmic Solutions +AI11873,Principal Data Scientist,59832,USD,59832,EN,FL,Israel,L,Australia,100,"Git, TensorFlow, SQL, NLP",Associate,1,Government,2024-03-07,2024-04-25,2026,9.5,Cloud AI Solutions +AI11874,Data Scientist,100061,USD,100061,SE,FT,Finland,S,Finland,0,"Docker, Python, TensorFlow, Tableau, Kubernetes",Bachelor,7,Gaming,2024-09-16,2024-11-15,2469,8.8,Autonomous Tech +AI11875,Computer Vision Engineer,55729,EUR,47370,EN,FL,France,S,France,50,"Docker, R, GCP, SQL",PhD,0,Education,2024-02-06,2024-02-29,1845,7.7,Quantum Computing Inc +AI11876,Machine Learning Researcher,47262,EUR,40173,EN,FT,France,S,France,50,"Python, TensorFlow, MLOps, Deep Learning, Java",Master,1,Education,2025-03-20,2025-05-04,1036,9,AI Innovations +AI11877,AI Product Manager,126583,USD,126583,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Linux, Java",Master,19,Automotive,2025-04-04,2025-06-11,1998,8.7,Autonomous Tech +AI11878,NLP Engineer,46601,EUR,39611,EN,PT,France,S,France,50,"Scala, Statistics, Linux, TensorFlow, MLOps",Master,0,Consulting,2024-05-26,2024-06-17,1646,7.1,AI Innovations +AI11879,AI Research Scientist,53772,GBP,40329,EN,PT,United Kingdom,S,United Kingdom,100,"Tableau, Git, Computer Vision",PhD,1,Technology,2025-03-20,2025-05-25,1581,5.1,Smart Analytics +AI11880,Data Scientist,203974,USD,203974,EX,FL,Ireland,L,Ireland,100,"Git, Python, Scala",Bachelor,17,Consulting,2024-09-04,2024-10-29,2278,7.8,AI Innovations +AI11881,AI Product Manager,23558,USD,23558,EN,FT,China,S,China,100,"Linux, Scala, Mathematics, Computer Vision",PhD,0,Gaming,2025-01-23,2025-04-01,1696,9.1,Smart Analytics +AI11882,Head of AI,195265,USD,195265,EX,FT,Finland,M,Finland,0,"Kubernetes, PyTorch, Scala, Git, AWS",Bachelor,12,Media,2025-03-21,2025-04-29,2425,9.6,Quantum Computing Inc +AI11883,AI Consultant,125170,USD,125170,MI,PT,United States,L,United States,0,"Tableau, Hadoop, PyTorch",Master,2,Energy,2025-03-05,2025-04-29,574,5.3,Autonomous Tech +AI11884,Machine Learning Researcher,154524,USD,154524,MI,PT,Norway,L,Norway,0,"Python, Scala, GCP, Computer Vision, AWS",Master,4,Gaming,2024-12-19,2025-02-23,1061,6.8,Future Systems +AI11885,Principal Data Scientist,78129,EUR,66410,MI,FT,Germany,M,Switzerland,100,"Mathematics, TensorFlow, Kubernetes",Master,4,Education,2024-12-15,2025-02-02,1911,6.1,AI Innovations +AI11886,AI Specialist,82474,USD,82474,EN,FL,Denmark,L,Denmark,100,"AWS, Linux, Tableau",Master,0,Government,2024-10-31,2024-11-29,1015,6.7,Digital Transformation LLC +AI11887,Data Analyst,60195,USD,60195,EN,CT,Ireland,S,Ireland,50,"Hadoop, NLP, Scala, Azure, Spark",Associate,0,Manufacturing,2025-03-11,2025-04-08,535,7.4,TechCorp Inc +AI11888,Computer Vision Engineer,85391,JPY,9393010,EN,FL,Japan,M,Japan,50,"Scala, Python, Mathematics, GCP",Master,0,Consulting,2025-02-05,2025-02-24,2183,8.4,DeepTech Ventures +AI11889,AI Product Manager,138187,GBP,103640,SE,PT,United Kingdom,M,United Kingdom,0,"NLP, PyTorch, SQL",Associate,7,Government,2025-04-01,2025-05-16,1041,7.6,Future Systems +AI11890,AI Research Scientist,90522,USD,90522,MI,CT,United States,S,Brazil,50,"SQL, Docker, PyTorch",PhD,4,Consulting,2025-02-18,2025-04-13,1067,8.7,TechCorp Inc +AI11891,Data Scientist,118016,EUR,100314,SE,FL,France,S,France,100,"Deep Learning, Spark, Python, Computer Vision, Linux",Bachelor,5,Media,2024-05-20,2024-06-20,2461,7.7,Quantum Computing Inc +AI11892,Principal Data Scientist,45677,USD,45677,MI,FT,China,L,China,50,"TensorFlow, Statistics, Git, MLOps",Master,2,Real Estate,2024-04-06,2024-05-06,1862,7.3,DataVision Ltd +AI11893,AI Specialist,80735,USD,80735,MI,PT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, SQL, MLOps",Associate,3,Energy,2024-10-09,2024-11-16,2497,6.8,Smart Analytics +AI11894,Data Engineer,174749,EUR,148537,SE,FT,Netherlands,L,Nigeria,50,"Kubernetes, SQL, Python",Master,6,Media,2024-01-28,2024-03-02,2235,5.5,DataVision Ltd +AI11895,Autonomous Systems Engineer,153986,USD,153986,EX,FL,South Korea,S,South Korea,50,"GCP, Python, Data Visualization",Master,19,Government,2024-07-05,2024-09-07,1093,6.4,Digital Transformation LLC +AI11896,AI Consultant,239879,GBP,179909,EX,PT,United Kingdom,S,United Kingdom,100,"Java, TensorFlow, Docker, SQL, AWS",Associate,10,Gaming,2025-01-25,2025-02-15,814,7.5,Algorithmic Solutions +AI11897,AI Product Manager,113202,JPY,12452220,MI,PT,Japan,L,Japan,0,"NLP, Spark, Python, TensorFlow, Git",Bachelor,3,Government,2024-05-24,2024-06-15,618,5.6,Quantum Computing Inc +AI11898,Deep Learning Engineer,176289,USD,176289,EX,FT,Sweden,M,Sweden,0,"Data Visualization, GCP, Linux",Associate,19,Real Estate,2024-08-14,2024-10-16,1171,7.7,Quantum Computing Inc +AI11899,AI Specialist,74877,CAD,93596,EN,FL,Canada,M,Romania,100,"Hadoop, Data Visualization, AWS, Java",Master,0,Transportation,2024-04-05,2024-05-19,1958,5.7,Autonomous Tech +AI11900,Deep Learning Engineer,121054,USD,121054,SE,PT,Israel,M,South Africa,50,"GCP, AWS, Mathematics, Tableau",Bachelor,9,Manufacturing,2024-11-17,2025-01-18,2146,7.1,Predictive Systems +AI11901,Head of AI,121862,CAD,152328,SE,FL,Canada,M,Chile,0,"Git, GCP, Spark, R, AWS",Bachelor,8,Finance,2025-04-11,2025-05-05,2480,8.7,Neural Networks Co +AI11902,AI Product Manager,68676,USD,68676,MI,PT,South Korea,L,South Korea,50,"Tableau, Kubernetes, Python",PhD,3,Manufacturing,2024-04-05,2024-05-28,951,7.4,Cognitive Computing +AI11903,AI Specialist,140355,CAD,175444,SE,CT,Canada,L,Canada,100,"Spark, SQL, Computer Vision",Bachelor,7,Automotive,2024-06-20,2024-07-21,738,5.6,Neural Networks Co +AI11904,Data Scientist,107343,EUR,91242,SE,CT,Austria,S,United States,100,"Linux, R, SQL, Spark, GCP",Master,6,Retail,2025-01-17,2025-02-24,1393,5.6,Advanced Robotics +AI11905,Data Analyst,124289,USD,124289,SE,PT,Ireland,M,Ireland,100,"Statistics, Tableau, SQL, Data Visualization, Python",Master,6,Telecommunications,2024-01-19,2024-03-30,1647,7.1,Cloud AI Solutions +AI11906,Deep Learning Engineer,111588,USD,111588,MI,FL,Ireland,L,Ireland,50,"Mathematics, TensorFlow, Tableau, Computer Vision",Associate,2,Consulting,2024-04-17,2024-06-23,2381,5.5,Advanced Robotics +AI11907,NLP Engineer,140602,AUD,189813,SE,PT,Australia,M,Australia,50,"SQL, Azure, AWS",Master,7,Technology,2024-05-08,2024-07-12,583,6.9,Autonomous Tech +AI11908,Deep Learning Engineer,220576,USD,220576,SE,PT,Norway,L,Norway,0,"Deep Learning, Data Visualization, Java, GCP",Master,6,Real Estate,2024-09-12,2024-10-13,1736,5.6,Neural Networks Co +AI11909,Data Scientist,63791,USD,63791,EX,FT,India,L,India,50,"Java, Spark, GCP, Tableau, Computer Vision",PhD,16,Retail,2025-01-06,2025-02-17,1610,9.6,Predictive Systems +AI11910,Robotics Engineer,115544,EUR,98212,SE,FT,Austria,S,Italy,100,"PyTorch, TensorFlow, Computer Vision, GCP, Spark",PhD,5,Gaming,2024-11-21,2024-12-28,2140,6.8,Digital Transformation LLC +AI11911,Computer Vision Engineer,141470,USD,141470,SE,FL,Finland,L,Canada,50,"Java, Python, Kubernetes",Bachelor,7,Transportation,2024-04-17,2024-05-11,1095,5.5,Machine Intelligence Group +AI11912,Robotics Engineer,119546,USD,119546,SE,FL,Sweden,M,Switzerland,100,"Kubernetes, AWS, Computer Vision",Associate,8,Energy,2024-09-13,2024-11-23,1690,7.2,TechCorp Inc +AI11913,Robotics Engineer,70709,SGD,91922,EN,PT,Singapore,L,Singapore,0,"Spark, Linux, Scala, Docker",PhD,0,Technology,2024-05-01,2024-06-11,984,8.9,Cognitive Computing +AI11914,Autonomous Systems Engineer,139969,AUD,188958,SE,FT,Australia,M,Australia,100,"Python, Spark, TensorFlow, MLOps, AWS",Bachelor,7,Gaming,2025-03-01,2025-03-18,1633,6,Machine Intelligence Group +AI11915,Computer Vision Engineer,249239,USD,249239,EX,CT,United States,M,United States,100,"Data Visualization, AWS, TensorFlow",Bachelor,19,Healthcare,2024-11-12,2024-12-16,1154,6.6,DataVision Ltd +AI11916,Data Scientist,72005,EUR,61204,EN,FL,France,M,France,0,"PyTorch, Scala, Data Visualization, Statistics, AWS",Master,1,Real Estate,2024-05-07,2024-05-25,1077,7.7,Digital Transformation LLC +AI11917,Head of AI,82315,USD,82315,MI,FL,Finland,M,Finland,0,"Java, Computer Vision, Tableau, Python",PhD,2,Media,2025-01-19,2025-03-24,653,5.4,DataVision Ltd +AI11918,AI Product Manager,172045,USD,172045,SE,PT,Sweden,L,Sweden,100,"GCP, Linux, Deep Learning, Scala, MLOps",Associate,6,Consulting,2024-12-20,2025-02-20,1852,8.2,Quantum Computing Inc +AI11919,Data Engineer,227310,EUR,193214,EX,CT,Germany,M,Germany,100,"Data Visualization, Python, R",PhD,19,Technology,2025-02-23,2025-04-07,560,9,AI Innovations +AI11920,Head of AI,84752,GBP,63564,MI,FL,United Kingdom,M,United Kingdom,50,"Azure, Tableau, Linux",Bachelor,3,Energy,2024-04-16,2024-06-06,789,5.7,Autonomous Tech +AI11921,Principal Data Scientist,141732,USD,141732,SE,FL,Finland,L,Brazil,50,"MLOps, Scala, TensorFlow, Deep Learning, GCP",PhD,7,Transportation,2024-12-08,2025-01-04,734,9.6,Autonomous Tech +AI11922,AI Architect,169211,USD,169211,SE,PT,Denmark,S,Argentina,100,"Java, Python, MLOps, TensorFlow, Kubernetes",Bachelor,8,Transportation,2025-03-07,2025-04-21,1516,9.5,Machine Intelligence Group +AI11923,Research Scientist,247914,GBP,185936,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, Python, GCP, R, Hadoop",Master,17,Automotive,2024-02-19,2024-03-13,849,7.8,TechCorp Inc +AI11924,Deep Learning Engineer,66536,CAD,83170,EN,FT,Canada,S,Malaysia,0,"PyTorch, Azure, MLOps",PhD,1,Energy,2024-05-29,2024-06-13,1642,5.4,DeepTech Ventures +AI11925,Robotics Engineer,133785,CHF,120407,MI,FL,Switzerland,M,Switzerland,50,"Spark, MLOps, GCP, Docker, Java",PhD,4,Finance,2025-02-01,2025-04-14,1364,5.8,Digital Transformation LLC +AI11926,Data Analyst,65022,GBP,48767,EN,CT,United Kingdom,L,United Kingdom,100,"Spark, GCP, SQL, NLP",Master,1,Real Estate,2025-04-21,2025-05-22,1446,6.4,Cognitive Computing +AI11927,NLP Engineer,247285,USD,247285,EX,FL,Norway,M,Norway,50,"NLP, SQL, Azure",Master,11,Government,2025-01-11,2025-03-04,767,9.8,Neural Networks Co +AI11928,NLP Engineer,51541,USD,51541,EN,FL,Finland,M,Finland,0,"Java, Kubernetes, Data Visualization, Docker",PhD,0,Manufacturing,2024-01-27,2024-02-26,1836,8.4,Digital Transformation LLC +AI11929,AI Consultant,186164,GBP,139623,SE,PT,United Kingdom,L,New Zealand,0,"Linux, Scala, Mathematics, R, Azure",Master,6,Telecommunications,2024-09-01,2024-11-09,2042,7.3,Quantum Computing Inc +AI11930,NLP Engineer,80116,USD,80116,MI,CT,Ireland,S,Ireland,0,"Python, Hadoop, GCP, TensorFlow",PhD,4,Media,2025-01-02,2025-01-21,1716,5.6,Neural Networks Co +AI11931,AI Consultant,62190,EUR,52862,EN,CT,Austria,M,Netherlands,100,"Hadoop, Git, NLP, TensorFlow",PhD,0,Gaming,2024-04-08,2024-04-25,1587,5.8,Cognitive Computing +AI11932,Principal Data Scientist,99982,USD,99982,MI,PT,Sweden,M,Italy,50,"Git, Azure, Kubernetes",Bachelor,3,Finance,2024-03-18,2024-05-28,2079,6.7,Smart Analytics +AI11933,AI Architect,126992,CAD,158740,SE,PT,Canada,L,Austria,100,"Git, Scala, Data Visualization, Python",PhD,5,Consulting,2024-11-05,2024-12-12,1638,6.9,Quantum Computing Inc +AI11934,NLP Engineer,283236,USD,283236,EX,FL,Denmark,M,Denmark,0,"Mathematics, Linux, Git",PhD,12,Real Estate,2024-10-07,2024-11-14,1479,8.2,AI Innovations +AI11935,Machine Learning Engineer,211425,CHF,190283,SE,PT,Switzerland,L,Singapore,100,"Linux, Data Visualization, Hadoop",PhD,8,Manufacturing,2024-07-10,2024-09-08,2048,7.7,Cloud AI Solutions +AI11936,Data Scientist,44730,CAD,55913,EN,PT,Canada,S,Israel,0,"Linux, GCP, R, Hadoop, SQL",Associate,0,Retail,2024-10-24,2024-12-23,1274,8.7,Digital Transformation LLC +AI11937,Data Analyst,34838,USD,34838,MI,PT,China,S,China,50,"Scala, AWS, Docker",Associate,4,Finance,2024-02-18,2024-03-21,2184,6.9,Smart Analytics +AI11938,AI Software Engineer,225196,USD,225196,EX,FL,United States,S,United States,0,"Java, R, Hadoop, Kubernetes, PyTorch",PhD,12,Transportation,2024-03-07,2024-04-13,1541,7.1,Neural Networks Co +AI11939,Head of AI,122390,USD,122390,MI,FT,United States,M,United States,0,"PyTorch, TensorFlow, Computer Vision, Docker, Mathematics",Associate,2,Media,2024-09-02,2024-10-09,1198,6.3,TechCorp Inc +AI11940,Deep Learning Engineer,134314,USD,134314,SE,FL,Finland,M,Finland,100,"AWS, SQL, PyTorch",Master,9,Government,2024-05-03,2024-05-19,2257,9.4,Machine Intelligence Group +AI11941,Autonomous Systems Engineer,63509,USD,63509,EN,PT,Israel,M,Israel,100,"Hadoop, Deep Learning, Scala, Python",Master,1,Transportation,2024-08-10,2024-09-13,1368,6.5,Algorithmic Solutions +AI11942,AI Software Engineer,179124,JPY,19703640,SE,CT,Japan,L,Japan,50,"Spark, SQL, R, Scala",Bachelor,6,Gaming,2024-10-09,2024-12-13,2235,7.7,DataVision Ltd +AI11943,AI Architect,128394,GBP,96296,MI,PT,United Kingdom,L,Poland,100,"SQL, Tableau, Mathematics, Data Visualization",PhD,3,Manufacturing,2024-12-16,2025-02-07,1582,6.4,TechCorp Inc +AI11944,Deep Learning Engineer,126623,CHF,113961,MI,FL,Switzerland,L,Brazil,0,"SQL, Scala, MLOps, R, Git",PhD,3,Energy,2024-05-23,2024-07-18,2276,6.4,Algorithmic Solutions +AI11945,AI Architect,113817,EUR,96744,SE,PT,Germany,M,Germany,50,"TensorFlow, Docker, Kubernetes",Master,8,Finance,2024-02-03,2024-02-24,1339,8,Quantum Computing Inc +AI11946,AI Architect,139320,USD,139320,EX,CT,South Korea,L,South Korea,100,"MLOps, Scala, Linux, Deep Learning, Computer Vision",Master,16,Technology,2025-04-05,2025-06-13,2440,7.6,Advanced Robotics +AI11947,AI Product Manager,123195,EUR,104716,SE,FL,Germany,S,Germany,100,"Python, MLOps, Tableau, TensorFlow, GCP",Master,6,Transportation,2024-01-02,2024-03-03,1983,8.6,Quantum Computing Inc +AI11948,AI Architect,59966,CAD,74958,EN,PT,Canada,M,Ireland,0,"Computer Vision, NLP, GCP, Linux, Azure",PhD,0,Finance,2024-01-24,2024-02-14,1953,5.8,Digital Transformation LLC +AI11949,AI Research Scientist,32241,USD,32241,EN,CT,India,L,India,100,"Kubernetes, Data Visualization, Azure",Bachelor,1,Energy,2024-12-07,2025-02-02,1441,6.2,Cognitive Computing +AI11950,Autonomous Systems Engineer,125879,CAD,157349,EX,FT,Canada,S,Canada,0,"Git, GCP, MLOps",Bachelor,13,Retail,2024-04-20,2024-05-25,1270,8.7,Quantum Computing Inc +AI11951,Head of AI,63170,USD,63170,MI,FL,Israel,S,Israel,0,"SQL, PyTorch, Azure, MLOps, Git",Bachelor,2,Media,2025-03-23,2025-04-21,1528,5.1,Digital Transformation LLC +AI11952,NLP Engineer,155126,JPY,17063860,EX,CT,Japan,M,New Zealand,50,"Python, TensorFlow, NLP",Associate,16,Real Estate,2024-09-30,2024-12-04,2446,10,Neural Networks Co +AI11953,AI Architect,86565,CAD,108206,MI,CT,Canada,M,Canada,100,"SQL, Python, Spark, Scala",Bachelor,2,Manufacturing,2024-03-29,2024-05-19,1589,6.7,Quantum Computing Inc +AI11954,Principal Data Scientist,103951,EUR,88358,MI,CT,Germany,L,Germany,100,"TensorFlow, Data Visualization, Python, Mathematics, Kubernetes",PhD,4,Retail,2024-04-23,2024-05-07,955,9.4,Algorithmic Solutions +AI11955,Data Engineer,121572,USD,121572,SE,FL,Ireland,L,Ireland,100,"Linux, TensorFlow, Docker",Associate,8,Real Estate,2024-07-01,2024-08-10,1827,8.3,TechCorp Inc +AI11956,Deep Learning Engineer,80289,USD,80289,EN,CT,Denmark,M,Denmark,50,"R, Azure, AWS",Associate,0,Transportation,2024-11-04,2025-01-06,1019,9.5,Smart Analytics +AI11957,Head of AI,142312,USD,142312,SE,FL,United States,L,United States,100,"NLP, Hadoop, Scala, Tableau",Bachelor,9,Media,2024-08-18,2024-10-13,1326,7.4,Future Systems +AI11958,ML Ops Engineer,45228,USD,45228,MI,PT,China,L,China,100,"Deep Learning, Kubernetes, Spark, NLP",Associate,3,Government,2025-01-01,2025-03-10,994,5.3,Algorithmic Solutions +AI11959,AI Architect,105421,SGD,137047,MI,FL,Singapore,M,Singapore,50,"NLP, TensorFlow, Tableau",Associate,3,Transportation,2025-03-20,2025-04-19,1425,7,Cognitive Computing +AI11960,Autonomous Systems Engineer,253979,CHF,228581,EX,FL,Switzerland,M,Thailand,100,"Hadoop, Scala, PyTorch, AWS, Data Visualization",Associate,11,Government,2025-04-18,2025-05-21,1367,7.3,Neural Networks Co +AI11961,Autonomous Systems Engineer,80682,EUR,68580,MI,PT,Netherlands,S,Chile,50,"NLP, Git, Spark, AWS, Hadoop",Bachelor,4,Education,2025-04-09,2025-05-09,1274,6.8,Machine Intelligence Group +AI11962,Machine Learning Engineer,58564,USD,58564,SE,PT,China,L,China,0,"Java, GCP, Deep Learning",Master,5,Energy,2024-08-17,2024-09-08,1669,7.7,Future Systems +AI11963,ML Ops Engineer,165885,EUR,141002,EX,FL,France,M,France,0,"Python, Deep Learning, Data Visualization",PhD,19,Media,2024-08-07,2024-09-19,783,10,Digital Transformation LLC +AI11964,Data Engineer,190838,USD,190838,SE,PT,Denmark,M,Austria,100,"Deep Learning, AWS, Statistics",Bachelor,6,Telecommunications,2024-02-14,2024-04-06,2414,9.6,Predictive Systems +AI11965,AI Specialist,55369,USD,55369,EX,FL,India,M,India,0,"Docker, GCP, Data Visualization, Mathematics, Tableau",Associate,17,Automotive,2024-01-09,2024-02-27,1164,10,AI Innovations +AI11966,Data Scientist,71105,EUR,60439,EN,FL,Netherlands,L,Netherlands,0,"Spark, PyTorch, Mathematics",Master,0,Telecommunications,2024-03-25,2024-05-30,1018,7.5,Quantum Computing Inc +AI11967,Deep Learning Engineer,75264,USD,75264,EN,FL,Sweden,M,Sweden,0,"GCP, Tableau, Python, Data Visualization, TensorFlow",Associate,0,Retail,2024-07-03,2024-07-22,1393,6.1,Smart Analytics +AI11968,Autonomous Systems Engineer,164799,USD,164799,SE,FT,Norway,M,Norway,100,"Hadoop, Kubernetes, Python, R, SQL",Master,9,Gaming,2024-05-10,2024-06-23,518,6.2,Neural Networks Co +AI11969,Machine Learning Engineer,76924,EUR,65385,MI,FT,Austria,M,Portugal,50,"Spark, Azure, Kubernetes",PhD,3,Telecommunications,2024-11-09,2024-12-18,913,6.5,Cognitive Computing +AI11970,Principal Data Scientist,43350,USD,43350,MI,PT,India,L,Ireland,50,"Git, Azure, Hadoop",Associate,3,Healthcare,2025-04-15,2025-06-19,1003,9.3,Predictive Systems +AI11971,AI Product Manager,61506,EUR,52280,EN,FL,Austria,S,Austria,0,"Kubernetes, Hadoop, PyTorch, Git, Data Visualization",Associate,0,Education,2025-03-18,2025-05-22,1927,6.3,Cognitive Computing +AI11972,AI Architect,102342,AUD,138162,MI,PT,Australia,M,Australia,100,"Python, SQL, Hadoop",PhD,4,Consulting,2024-04-13,2024-05-08,1056,9.6,Digital Transformation LLC +AI11973,AI Product Manager,167315,CHF,150584,SE,CT,Switzerland,L,Switzerland,50,"Scala, Computer Vision, SQL, GCP, MLOps",PhD,8,Transportation,2024-12-07,2025-01-08,1876,6.2,Quantum Computing Inc +AI11974,AI Consultant,128451,EUR,109183,EX,PT,France,M,France,0,"Spark, Python, Statistics, Java, TensorFlow",Master,19,Real Estate,2024-08-06,2024-09-04,2292,9.4,Autonomous Tech +AI11975,Robotics Engineer,71957,GBP,53968,EN,FT,United Kingdom,S,United Kingdom,0,"Scala, GCP, Computer Vision, Docker",Master,0,Healthcare,2024-04-15,2024-05-17,529,6.3,DataVision Ltd +AI11976,ML Ops Engineer,117836,AUD,159079,SE,PT,Australia,L,Argentina,50,"Python, PyTorch, Git, Computer Vision, Statistics",PhD,6,Education,2024-06-29,2024-07-16,2090,5.9,Algorithmic Solutions +AI11977,Data Engineer,121319,SGD,157715,MI,PT,Singapore,L,New Zealand,50,"GCP, Git, Mathematics, Computer Vision, TensorFlow",Bachelor,4,Real Estate,2024-05-16,2024-07-28,1785,8.7,TechCorp Inc +AI11978,Machine Learning Researcher,118151,EUR,100428,EX,FL,France,S,France,100,"TensorFlow, SQL, MLOps",Associate,13,Retail,2025-04-12,2025-06-22,1142,6.1,Cognitive Computing +AI11979,AI Software Engineer,82974,GBP,62231,MI,FL,United Kingdom,S,United Kingdom,0,"Linux, AWS, Deep Learning, Scala",Bachelor,3,Telecommunications,2024-01-09,2024-02-03,662,7.9,Future Systems +AI11980,Data Analyst,91372,USD,91372,EN,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-10-03,2024-10-26,2231,9.5,Predictive Systems +AI11981,AI Product Manager,33654,USD,33654,EN,FL,China,M,China,0,"Spark, SQL, Linux, Hadoop",Associate,0,Healthcare,2025-03-07,2025-05-19,1924,5.9,Neural Networks Co +AI11982,Head of AI,156264,EUR,132824,SE,FL,France,L,South Africa,50,"Kubernetes, SQL, PyTorch, Data Visualization, Computer Vision",PhD,8,Education,2024-11-24,2025-01-21,1009,7.4,Cognitive Computing +AI11983,Data Analyst,84928,CAD,106160,MI,FL,Canada,M,Canada,50,"PyTorch, Spark, Data Visualization, SQL, Docker",Master,4,Technology,2024-11-12,2024-12-15,574,9.6,DataVision Ltd +AI11984,Research Scientist,129254,CAD,161568,SE,PT,Canada,M,Canada,0,"Python, Azure, Statistics, Java, Computer Vision",Master,9,Consulting,2024-12-28,2025-02-11,2081,9.1,Autonomous Tech +AI11985,AI Consultant,206297,USD,206297,EX,CT,Finland,M,Finland,50,"AWS, Spark, Mathematics, Hadoop, GCP",Master,10,Real Estate,2024-06-25,2024-08-25,2117,6.1,Algorithmic Solutions +AI11986,Data Analyst,105092,EUR,89328,MI,CT,Austria,L,Austria,0,"Linux, TensorFlow, Scala, Azure",Master,3,Government,2024-04-25,2024-05-27,2118,6.5,DataVision Ltd +AI11987,Deep Learning Engineer,216314,USD,216314,EX,PT,Denmark,L,Denmark,0,"TensorFlow, Scala, GCP, R, Tableau",PhD,19,Media,2025-03-05,2025-04-18,2302,8.6,Quantum Computing Inc +AI11988,AI Software Engineer,114139,EUR,97018,SE,FT,France,S,France,0,"Java, NLP, Git, Statistics",Master,6,Gaming,2024-11-06,2025-01-18,2402,8.2,DataVision Ltd +AI11989,Autonomous Systems Engineer,253207,GBP,189905,EX,FT,United Kingdom,L,United Kingdom,0,"R, Mathematics, SQL, Java",Bachelor,12,Manufacturing,2024-11-08,2024-12-27,534,9.6,Cloud AI Solutions +AI11990,Data Engineer,117195,CHF,105476,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Docker, NLP, PyTorch",PhD,4,Technology,2024-03-28,2024-04-27,998,5.9,Quantum Computing Inc +AI11991,AI Research Scientist,75215,USD,75215,EN,FT,United States,S,United States,100,"TensorFlow, GCP, Java, Scala, Python",Master,1,Energy,2025-03-13,2025-03-30,2257,8.4,AI Innovations +AI11992,Data Scientist,91308,USD,91308,MI,CT,Ireland,S,Ireland,100,"Azure, Linux, Scala",PhD,2,Telecommunications,2024-05-29,2024-07-03,1125,9.7,Cloud AI Solutions +AI11993,NLP Engineer,101994,USD,101994,MI,FT,United States,L,United States,50,"Python, R, PyTorch, Deep Learning",Master,3,Healthcare,2025-03-09,2025-04-03,1316,7.3,Digital Transformation LLC +AI11994,AI Consultant,63814,SGD,82958,EN,FT,Singapore,M,Singapore,0,"Java, AWS, PyTorch",PhD,1,Gaming,2024-12-23,2025-02-07,1775,5.5,Predictive Systems +AI11995,AI Software Engineer,82096,CHF,73886,EN,FL,Switzerland,M,Switzerland,50,"SQL, Tableau, TensorFlow, Docker",PhD,1,Manufacturing,2024-01-26,2024-03-03,2046,7.2,Future Systems +AI11996,Data Analyst,139446,USD,139446,SE,FL,United States,L,United States,0,"Python, Data Visualization, Kubernetes",Associate,8,Consulting,2025-04-27,2025-05-31,1178,5.2,Cognitive Computing +AI11997,AI Consultant,50489,CAD,63111,EN,PT,Canada,S,Canada,0,"Mathematics, SQL, AWS, Deep Learning",Master,1,Healthcare,2024-07-07,2024-08-30,1144,8.2,Autonomous Tech +AI11998,AI Architect,202463,EUR,172094,EX,CT,France,L,France,50,"R, Statistics, Tableau",Associate,18,Retail,2024-05-07,2024-06-08,2361,5.1,TechCorp Inc +AI11999,AI Consultant,257007,USD,257007,EX,FL,Israel,L,Israel,0,"SQL, Git, Spark",Associate,16,Healthcare,2025-03-29,2025-06-02,2113,8.4,Future Systems +AI12000,Data Analyst,165859,JPY,18244490,SE,FL,Japan,L,Japan,50,"Kubernetes, Mathematics, MLOps",PhD,5,Education,2024-11-04,2025-01-12,1168,5.2,Quantum Computing Inc +AI12001,NLP Engineer,269890,USD,269890,EX,FL,Norway,S,Norway,0,"PyTorch, Python, Git, Kubernetes",Associate,19,Technology,2024-03-09,2024-03-25,1218,5.8,Algorithmic Solutions +AI12002,AI Product Manager,249468,EUR,212048,EX,FL,Netherlands,M,Netherlands,100,"Azure, Tableau, Statistics",PhD,16,Telecommunications,2024-06-14,2024-07-15,534,5,Cognitive Computing +AI12003,Robotics Engineer,146512,SGD,190466,SE,FT,Singapore,M,Singapore,100,"Python, Deep Learning, Computer Vision, Scala",Master,7,Manufacturing,2024-12-29,2025-01-27,728,5.8,Smart Analytics +AI12004,Robotics Engineer,74373,EUR,63217,MI,CT,Austria,S,Austria,0,"NLP, Docker, PyTorch, Azure, Mathematics",Master,4,Gaming,2024-11-09,2025-01-16,1187,8.1,Cognitive Computing +AI12005,AI Consultant,191280,USD,191280,EX,CT,Israel,M,Ukraine,100,"SQL, R, MLOps, Docker",Associate,18,Gaming,2024-03-28,2024-05-16,789,5.7,Algorithmic Solutions +AI12006,Machine Learning Engineer,122748,EUR,104336,SE,CT,Germany,M,Germany,100,"Java, R, NLP, Computer Vision, Azure",Bachelor,8,Healthcare,2024-11-22,2025-02-03,1419,5.3,Autonomous Tech +AI12007,Deep Learning Engineer,40909,USD,40909,SE,PT,India,M,India,50,"NLP, Hadoop, MLOps",Associate,7,Government,2024-08-07,2024-09-08,2498,9.3,TechCorp Inc +AI12008,Principal Data Scientist,51031,USD,51031,EX,CT,India,M,India,0,"Kubernetes, Docker, Azure",PhD,12,Telecommunications,2025-01-21,2025-02-12,1890,10,Advanced Robotics +AI12009,Deep Learning Engineer,111269,CHF,100142,MI,PT,Switzerland,M,Switzerland,0,"Java, TensorFlow, Linux",Associate,4,Automotive,2024-09-13,2024-10-07,1949,6.5,Machine Intelligence Group +AI12010,AI Architect,68234,EUR,57999,EN,FT,Austria,L,Switzerland,100,"Scala, Python, Docker, SQL, Statistics",Associate,1,Transportation,2024-12-05,2025-02-01,2202,5.9,Cognitive Computing +AI12011,Deep Learning Engineer,138852,USD,138852,MI,FT,Denmark,L,Romania,50,"Deep Learning, Python, Scala, GCP, SQL",Bachelor,2,Retail,2024-03-29,2024-05-12,2392,8.3,TechCorp Inc +AI12012,AI Research Scientist,112322,USD,112322,SE,PT,Israel,M,Israel,0,"Java, Git, Mathematics, Statistics",Bachelor,8,Government,2024-03-31,2024-04-21,1766,5.1,Autonomous Tech +AI12013,AI Consultant,172547,AUD,232938,EX,PT,Australia,L,Australia,0,"Python, PyTorch, Mathematics, Java, Tableau",Bachelor,19,Energy,2025-01-13,2025-02-03,1606,5.6,TechCorp Inc +AI12014,Machine Learning Engineer,210775,CHF,189698,SE,CT,Switzerland,M,Switzerland,50,"Docker, R, Computer Vision, Hadoop, MLOps",Associate,7,Education,2025-02-25,2025-03-24,891,6.1,Cognitive Computing +AI12015,ML Ops Engineer,42437,USD,42437,SE,CT,India,M,India,0,"Hadoop, R, Statistics, Git, Docker",Master,5,Education,2025-02-20,2025-03-15,1846,7.9,Predictive Systems +AI12016,Research Scientist,75457,USD,75457,MI,FT,South Korea,M,South Korea,0,"Docker, Tableau, Computer Vision, Java, Hadoop",Master,2,Technology,2024-01-16,2024-03-09,510,5.1,Cognitive Computing +AI12017,AI Architect,81055,AUD,109424,MI,FT,Australia,S,Israel,0,"Data Visualization, TensorFlow, Tableau",Associate,3,Manufacturing,2025-03-19,2025-04-30,1842,8.3,Autonomous Tech +AI12018,Data Analyst,158028,GBP,118521,EX,CT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Mathematics, Hadoop, MLOps",Associate,13,Telecommunications,2024-11-20,2025-01-02,2151,6.6,Quantum Computing Inc +AI12019,Computer Vision Engineer,85667,EUR,72817,MI,FT,Austria,L,Austria,100,"Scala, Mathematics, MLOps, Java",Associate,3,Automotive,2025-03-06,2025-04-14,1455,7.1,Neural Networks Co +AI12020,AI Consultant,92565,USD,92565,MI,FL,South Korea,L,South Korea,100,"Mathematics, AWS, MLOps, R, Java",Bachelor,2,Media,2024-02-15,2024-04-03,2106,7.6,Cloud AI Solutions +AI12021,Data Scientist,218585,USD,218585,EX,FL,United States,S,United States,0,"Azure, SQL, Linux",Master,19,Technology,2025-02-21,2025-04-29,1692,7.1,Smart Analytics +AI12022,Machine Learning Engineer,135669,CHF,122102,MI,FT,Switzerland,S,Switzerland,100,"Kubernetes, SQL, Computer Vision, PyTorch",Bachelor,4,Transportation,2024-06-19,2024-07-10,1965,5.8,Autonomous Tech +AI12023,Machine Learning Engineer,161267,SGD,209647,SE,FT,Singapore,M,Canada,50,"Scala, Python, Docker, Kubernetes, Tableau",Associate,5,Consulting,2024-08-07,2024-09-11,1851,5.4,Digital Transformation LLC +AI12024,Machine Learning Researcher,161659,EUR,137410,EX,PT,Austria,L,Austria,100,"Python, AWS, Azure, Deep Learning, R",Associate,12,Finance,2024-01-06,2024-02-24,730,5.1,Digital Transformation LLC +AI12025,ML Ops Engineer,84538,GBP,63404,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Java, Tableau, Statistics",Bachelor,0,Media,2024-02-18,2024-03-04,1481,8.2,Cloud AI Solutions +AI12026,AI Consultant,123396,EUR,104887,SE,CT,Germany,S,Poland,100,"Git, SQL, Kubernetes",Master,7,Finance,2025-03-17,2025-05-03,1628,9.6,Cognitive Computing +AI12027,NLP Engineer,94740,USD,94740,SE,FT,Sweden,S,Sweden,50,"SQL, NLP, Azure, Mathematics, Python",Bachelor,7,Automotive,2024-09-21,2024-11-21,1527,9.1,DataVision Ltd +AI12028,Machine Learning Engineer,237856,USD,237856,EX,PT,Denmark,M,Denmark,100,"Scala, NLP, Java, Data Visualization",Master,11,Technology,2024-10-29,2024-12-31,1067,9.5,Digital Transformation LLC +AI12029,Computer Vision Engineer,144410,USD,144410,EX,PT,South Korea,L,South Korea,100,"Data Visualization, Python, Tableau, Docker, Deep Learning",PhD,11,Technology,2024-08-16,2024-10-08,1659,7.5,TechCorp Inc +AI12030,Autonomous Systems Engineer,62979,EUR,53532,EN,FL,Netherlands,S,Latvia,50,"R, Deep Learning, Tableau",Bachelor,0,Gaming,2024-12-04,2024-12-27,1609,6.9,Smart Analytics +AI12031,AI Consultant,134825,CHF,121343,MI,FL,Switzerland,L,Argentina,50,"PyTorch, Computer Vision, TensorFlow",Master,4,Gaming,2024-01-15,2024-03-22,853,7.2,Machine Intelligence Group +AI12032,Deep Learning Engineer,115226,USD,115226,MI,PT,Ireland,L,Ireland,50,"Docker, Tableau, Statistics, GCP, Deep Learning",Master,4,Media,2024-02-19,2024-03-12,1816,5.4,Smart Analytics +AI12033,AI Consultant,128090,JPY,14089900,MI,FL,Japan,L,Japan,100,"Statistics, Spark, PyTorch, Data Visualization",Master,3,Education,2024-10-11,2024-12-12,2013,5.1,TechCorp Inc +AI12034,Machine Learning Engineer,148729,USD,148729,EX,FT,Sweden,S,Sweden,100,"Data Visualization, Git, PyTorch, Hadoop",Master,11,Media,2024-02-10,2024-03-19,1419,5.6,Smart Analytics +AI12035,AI Research Scientist,42922,USD,42922,MI,FL,China,L,China,100,"Computer Vision, Tableau, GCP, Spark, PyTorch",Bachelor,3,Telecommunications,2024-01-25,2024-03-15,582,6,Algorithmic Solutions +AI12036,Robotics Engineer,97362,USD,97362,EN,CT,Norway,L,Norway,100,"Computer Vision, Data Visualization, MLOps, Tableau, NLP",Associate,0,Healthcare,2024-09-09,2024-09-29,1851,9.7,DeepTech Ventures +AI12037,Machine Learning Researcher,59118,USD,59118,SE,CT,China,M,China,0,"Hadoop, Linux, SQL",Bachelor,7,Consulting,2024-07-02,2024-08-19,871,7.8,Advanced Robotics +AI12038,Computer Vision Engineer,73489,CAD,91861,EN,PT,Canada,M,Israel,50,"AWS, Azure, SQL, PyTorch, NLP",PhD,0,Gaming,2024-01-07,2024-02-24,2056,5.3,Smart Analytics +AI12039,Deep Learning Engineer,111684,CAD,139605,SE,PT,Canada,L,Brazil,50,"Linux, Hadoop, Data Visualization, Kubernetes",PhD,7,Automotive,2024-04-02,2024-05-09,957,7.3,Cloud AI Solutions +AI12040,AI Research Scientist,64479,EUR,54807,EN,FT,France,S,Switzerland,100,"PyTorch, NLP, Deep Learning",PhD,0,Energy,2025-02-25,2025-04-11,1960,5.1,Predictive Systems +AI12041,AI Specialist,175295,USD,175295,SE,CT,United States,M,United States,0,"Hadoop, Tableau, Linux, Scala, Python",Master,8,Technology,2024-09-16,2024-11-24,2420,5.5,Neural Networks Co +AI12042,Deep Learning Engineer,29310,USD,29310,EN,FL,China,L,China,100,"Java, R, NLP, GCP, Tableau",Associate,0,Real Estate,2024-08-06,2024-10-11,1524,7.3,DataVision Ltd +AI12043,Data Engineer,109138,EUR,92767,MI,FL,Germany,M,Canada,50,"Data Visualization, TensorFlow, PyTorch",Bachelor,3,Technology,2024-07-28,2024-09-08,1065,6.9,Future Systems +AI12044,AI Software Engineer,74590,USD,74590,EX,FT,India,L,India,0,"GCP, Java, Linux",Master,11,Manufacturing,2024-10-05,2024-12-16,1788,8.5,Neural Networks Co +AI12045,AI Consultant,137100,USD,137100,MI,CT,United States,L,Egypt,100,"Tableau, Java, Mathematics, SQL, R",Associate,3,Media,2024-05-21,2024-07-26,1922,7.8,Advanced Robotics +AI12046,AI Research Scientist,169631,USD,169631,EX,FL,Ireland,L,Ireland,50,"SQL, Git, Mathematics, AWS",Master,15,Manufacturing,2024-05-25,2024-07-31,2372,5.4,Digital Transformation LLC +AI12047,Machine Learning Engineer,182100,USD,182100,SE,PT,Norway,L,Norway,0,"TensorFlow, SQL, Java, Computer Vision, Git",Master,6,Retail,2025-03-10,2025-04-11,1534,6.7,Neural Networks Co +AI12048,Robotics Engineer,30598,USD,30598,EN,FT,India,L,India,50,"Data Visualization, Kubernetes, Scala",Associate,0,Consulting,2025-04-20,2025-05-24,707,5.7,Smart Analytics +AI12049,AI Research Scientist,59506,EUR,50580,EN,CT,France,S,France,50,"Computer Vision, NLP, Git, Kubernetes",Bachelor,0,Healthcare,2025-02-24,2025-05-06,2354,5.9,Machine Intelligence Group +AI12050,AI Consultant,176984,CAD,221230,EX,FT,Canada,S,Belgium,50,"Computer Vision, Java, Spark, Statistics, Deep Learning",Bachelor,19,Transportation,2025-04-06,2025-05-11,753,5.1,Machine Intelligence Group +AI12051,Head of AI,76635,USD,76635,MI,FL,Finland,M,Argentina,0,"PyTorch, Python, MLOps",PhD,3,Transportation,2024-10-21,2024-11-09,2223,5.7,Cognitive Computing +AI12052,ML Ops Engineer,142757,USD,142757,SE,CT,Israel,M,Israel,0,"Tableau, NLP, Mathematics",PhD,6,Gaming,2024-10-27,2024-11-28,2278,9.3,Cloud AI Solutions +AI12053,Machine Learning Engineer,157767,AUD,212985,SE,FL,Australia,L,Australia,100,"NLP, Linux, Mathematics",Associate,5,Transportation,2025-01-19,2025-03-14,1357,10,Smart Analytics +AI12054,Data Scientist,155133,JPY,17064630,SE,FL,Japan,M,Japan,50,"MLOps, AWS, R",Associate,8,Education,2024-04-22,2024-05-14,679,8.7,Machine Intelligence Group +AI12055,AI Consultant,103814,USD,103814,MI,FL,Finland,M,Indonesia,50,"Mathematics, AWS, Linux",Associate,3,Finance,2024-02-21,2024-05-04,619,7.6,Smart Analytics +AI12056,NLP Engineer,126742,CHF,114068,MI,PT,Switzerland,M,Switzerland,0,"AWS, Kubernetes, Tableau",Associate,3,Real Estate,2024-09-05,2024-10-20,1227,7.1,Advanced Robotics +AI12057,Machine Learning Engineer,149642,SGD,194535,EX,PT,Singapore,S,Singapore,0,"Python, NLP, SQL, AWS, TensorFlow",Associate,14,Telecommunications,2024-04-11,2024-06-04,599,5.6,Quantum Computing Inc +AI12058,Machine Learning Engineer,119639,GBP,89729,SE,PT,United Kingdom,S,United Kingdom,50,"Tableau, Python, Data Visualization",Bachelor,9,Retail,2025-01-06,2025-02-27,1845,5.5,Quantum Computing Inc +AI12059,AI Architect,94779,CAD,118474,SE,FT,Canada,S,Canada,100,"Scala, Java, Docker, Kubernetes, Data Visualization",Master,7,Media,2024-05-15,2024-07-19,2195,7.1,Advanced Robotics +AI12060,Data Scientist,289132,USD,289132,EX,FT,Norway,S,Norway,100,"TensorFlow, R, NLP",Associate,12,Automotive,2025-01-12,2025-02-15,1149,7.1,Cloud AI Solutions +AI12061,NLP Engineer,81914,EUR,69627,EN,CT,Germany,L,Germany,0,"Linux, Git, SQL",Master,1,Government,2024-08-06,2024-10-05,2272,6.8,DataVision Ltd +AI12062,Autonomous Systems Engineer,143423,EUR,121910,SE,FT,Austria,L,Austria,100,"Python, Java, Deep Learning",Associate,5,Healthcare,2024-03-01,2024-04-12,2001,7.8,Predictive Systems +AI12063,Autonomous Systems Engineer,67712,EUR,57555,EN,CT,Austria,S,Austria,0,"Scala, Linux, Python, AWS, Docker",Bachelor,0,Government,2025-01-18,2025-03-03,2191,5.6,Autonomous Tech +AI12064,Robotics Engineer,119637,GBP,89728,SE,FT,United Kingdom,S,Spain,50,"Python, AWS, Data Visualization",PhD,9,Education,2024-04-23,2024-06-03,787,5.7,Digital Transformation LLC +AI12065,Computer Vision Engineer,95673,EUR,81322,MI,FL,Netherlands,L,South Korea,0,"Tableau, TensorFlow, Python, Linux",PhD,3,Finance,2024-08-30,2024-10-22,1692,6.9,Predictive Systems +AI12066,ML Ops Engineer,206540,EUR,175559,EX,FT,Germany,M,Germany,50,"R, Mathematics, TensorFlow",PhD,11,Media,2025-02-23,2025-04-21,1614,9.8,TechCorp Inc +AI12067,ML Ops Engineer,251443,USD,251443,EX,FT,United States,S,United States,0,"Python, Scala, Docker, Deep Learning, NLP",Associate,10,Automotive,2024-03-08,2024-04-10,620,7.3,DataVision Ltd +AI12068,Data Engineer,116790,CAD,145988,SE,CT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Computer Vision, R",Associate,7,Education,2025-01-18,2025-03-12,1376,5.8,Algorithmic Solutions +AI12069,Computer Vision Engineer,113165,EUR,96190,SE,FT,Germany,S,Portugal,0,"Docker, Python, NLP, Computer Vision",Master,6,Consulting,2024-09-18,2024-11-17,1378,5.3,Digital Transformation LLC +AI12070,AI Research Scientist,117256,CHF,105530,MI,PT,Switzerland,S,Switzerland,100,"AWS, Scala, Computer Vision",PhD,3,Healthcare,2024-06-12,2024-07-14,1082,8.6,Algorithmic Solutions +AI12071,AI Specialist,300778,USD,300778,EX,PT,Norway,M,Norway,0,"Java, Python, GCP, Spark, TensorFlow",Bachelor,12,Technology,2025-02-04,2025-04-13,867,7.6,Predictive Systems +AI12072,Robotics Engineer,141137,SGD,183478,SE,CT,Singapore,L,Singapore,100,"Git, Linux, GCP, Spark",Associate,6,Finance,2024-02-12,2024-03-12,975,6.3,Advanced Robotics +AI12073,Robotics Engineer,46660,USD,46660,MI,CT,China,S,China,0,"AWS, Kubernetes, Docker",Bachelor,4,Consulting,2024-06-19,2024-08-01,2391,8.2,Autonomous Tech +AI12074,Principal Data Scientist,167557,USD,167557,EX,PT,Israel,L,Israel,0,"Azure, SQL, Data Visualization, Deep Learning",Associate,10,Consulting,2024-06-19,2024-08-16,820,5,Digital Transformation LLC +AI12075,Data Engineer,152794,USD,152794,SE,PT,United States,L,United States,100,"Scala, GCP, Docker",Associate,9,Automotive,2024-05-24,2024-06-07,1160,7.9,Neural Networks Co +AI12076,AI Consultant,96217,USD,96217,EX,FL,China,L,Romania,100,"R, SQL, Linux, Docker",Master,18,Healthcare,2024-12-25,2025-02-03,1390,8.2,Digital Transformation LLC +AI12077,AI Architect,93192,CHF,83873,EN,CT,Switzerland,L,Switzerland,50,"Azure, Python, MLOps, Scala, R",Master,0,Education,2024-03-12,2024-04-16,2202,6.2,Autonomous Tech +AI12078,Robotics Engineer,104902,USD,104902,MI,FL,Ireland,L,Ireland,0,"Azure, NLP, Spark, AWS",Master,4,Real Estate,2024-01-09,2024-03-22,1676,9.4,Future Systems +AI12079,AI Software Engineer,77869,USD,77869,MI,PT,South Korea,S,South Korea,100,"GCP, Kubernetes, Tableau, Mathematics, SQL",Associate,4,Finance,2024-05-23,2024-06-22,2322,9.6,DataVision Ltd +AI12080,AI Software Engineer,61860,USD,61860,SE,FT,China,M,China,100,"Kubernetes, Python, Computer Vision, TensorFlow, Linux",Master,6,Transportation,2024-10-05,2024-11-14,2429,6.5,Predictive Systems +AI12081,ML Ops Engineer,149417,USD,149417,SE,FT,Ireland,L,Ireland,0,"Docker, Azure, Linux, GCP, Java",PhD,9,Government,2024-11-12,2024-12-01,1510,7.5,Smart Analytics +AI12082,Head of AI,46702,USD,46702,MI,PT,China,M,China,100,"Kubernetes, R, SQL",Bachelor,2,Media,2024-11-09,2024-12-11,850,9.8,Quantum Computing Inc +AI12083,Data Scientist,65493,USD,65493,EN,PT,Ireland,L,Ireland,50,"Data Visualization, Linux, Mathematics, Python, Computer Vision",Associate,0,Finance,2024-09-02,2024-10-04,1196,9.4,DeepTech Ventures +AI12084,Head of AI,84582,JPY,9304020,MI,FL,Japan,M,Japan,100,"Scala, Spark, TensorFlow, AWS",Associate,4,Government,2024-07-14,2024-08-05,922,9.1,Smart Analytics +AI12085,AI Software Engineer,168343,JPY,18517730,SE,FT,Japan,L,Japan,0,"Git, Scala, Statistics, Mathematics",Associate,7,Education,2024-02-01,2024-04-04,1613,5.8,DataVision Ltd +AI12086,Machine Learning Researcher,122314,USD,122314,EX,FT,South Korea,S,Portugal,50,"R, Java, AWS, Deep Learning",PhD,10,Manufacturing,2025-04-18,2025-06-13,1322,7.9,DeepTech Ventures +AI12087,Autonomous Systems Engineer,177998,USD,177998,SE,CT,United States,L,United States,50,"Deep Learning, Mathematics, NLP",PhD,9,Energy,2024-12-30,2025-03-07,1399,5.9,Digital Transformation LLC +AI12088,Data Analyst,53354,USD,53354,EN,PT,South Korea,S,South Korea,100,"TensorFlow, Python, MLOps",Associate,0,Real Estate,2024-05-15,2024-07-05,1721,7.6,Digital Transformation LLC +AI12089,Head of AI,160257,USD,160257,MI,CT,Norway,L,Italy,100,"PyTorch, AWS, Mathematics, Docker",Master,4,Retail,2024-02-05,2024-03-04,2077,6.3,Future Systems +AI12090,Robotics Engineer,47255,USD,47255,EN,CT,South Korea,S,Poland,100,"R, Docker, Statistics, GCP, Git",Bachelor,1,Media,2024-12-07,2025-02-05,1532,7.3,Advanced Robotics +AI12091,AI Research Scientist,244976,SGD,318469,EX,CT,Singapore,M,Singapore,100,"Java, AWS, MLOps, Computer Vision",Associate,15,Gaming,2024-01-12,2024-02-17,730,6.1,TechCorp Inc +AI12092,Principal Data Scientist,18580,USD,18580,EN,FL,India,S,India,50,"Spark, NLP, Statistics, Linux, Python",Master,0,Real Estate,2025-02-24,2025-03-10,1215,9.6,Digital Transformation LLC +AI12093,Robotics Engineer,92541,GBP,69406,EN,FT,United Kingdom,L,Spain,50,"NLP, GCP, MLOps",Bachelor,1,Finance,2024-09-11,2024-10-10,1775,7.6,Predictive Systems +AI12094,AI Software Engineer,136851,USD,136851,SE,FT,United States,S,United States,100,"R, GCP, Scala",Bachelor,5,Finance,2024-07-29,2024-09-06,1209,5.3,Machine Intelligence Group +AI12095,AI Specialist,74577,GBP,55933,EN,FL,United Kingdom,L,Russia,0,"Git, Spark, Computer Vision, Hadoop, AWS",PhD,1,Education,2025-02-16,2025-03-16,1122,8,Machine Intelligence Group +AI12096,Data Engineer,130249,SGD,169324,MI,PT,Singapore,L,Hungary,0,"Mathematics, Statistics, Tableau, Spark",PhD,3,Consulting,2024-12-27,2025-02-11,1095,9.4,Autonomous Tech +AI12097,Machine Learning Researcher,279715,USD,279715,EX,FL,Denmark,S,Singapore,50,"Docker, SQL, Hadoop, AWS",Master,10,Telecommunications,2024-01-12,2024-01-28,2016,9.8,Digital Transformation LLC +AI12098,Data Analyst,25917,USD,25917,MI,CT,India,S,India,0,"SQL, GCP, MLOps",Associate,2,Retail,2024-05-29,2024-06-28,2476,5.5,Cognitive Computing +AI12099,Deep Learning Engineer,192954,EUR,164011,EX,CT,Netherlands,S,Netherlands,50,"AWS, Kubernetes, Scala",Bachelor,10,Retail,2024-06-16,2024-07-23,1690,6.4,DeepTech Ventures +AI12100,Machine Learning Engineer,151696,USD,151696,EX,FT,United States,S,United States,0,"Python, Computer Vision, Git",Master,19,Education,2024-05-28,2024-06-27,1075,5.5,AI Innovations +AI12101,Computer Vision Engineer,181487,USD,181487,EX,CT,United States,M,United States,100,"Python, TensorFlow, Tableau",PhD,15,Manufacturing,2024-09-05,2024-10-20,729,9.3,Neural Networks Co +AI12102,Machine Learning Engineer,290032,CHF,261029,EX,FL,Switzerland,S,Switzerland,100,"AWS, Spark, R, Statistics, Mathematics",Master,18,Gaming,2024-12-07,2025-01-10,1549,5.5,Algorithmic Solutions +AI12103,Principal Data Scientist,88078,USD,88078,MI,PT,Israel,L,Israel,100,"Kubernetes, TensorFlow, SQL, Spark",Bachelor,2,Automotive,2024-03-31,2024-04-24,1515,8.7,Machine Intelligence Group +AI12104,Robotics Engineer,120897,USD,120897,MI,FT,Ireland,L,Ireland,100,"SQL, Java, PyTorch",PhD,3,Gaming,2024-05-11,2024-06-25,830,5.6,Neural Networks Co +AI12105,Head of AI,99552,GBP,74664,MI,CT,United Kingdom,L,United Kingdom,100,"Azure, TensorFlow, GCP, Kubernetes, Computer Vision",PhD,3,Manufacturing,2024-06-16,2024-07-10,1141,7.8,Predictive Systems +AI12106,AI Architect,229166,EUR,194791,EX,FT,Germany,S,Canada,50,"Scala, Linux, PyTorch",Master,15,Healthcare,2025-02-12,2025-03-20,1754,5.9,DataVision Ltd +AI12107,Data Engineer,65688,EUR,55835,EN,CT,Netherlands,S,Netherlands,0,"SQL, PyTorch, Azure, Computer Vision",Bachelor,0,Healthcare,2024-10-29,2024-12-09,586,9.5,Digital Transformation LLC +AI12108,Data Analyst,94258,GBP,70694,MI,FT,United Kingdom,S,Vietnam,100,"Java, Deep Learning, R",Bachelor,4,Manufacturing,2024-05-15,2024-06-18,2486,7.2,Autonomous Tech +AI12109,Machine Learning Researcher,61046,EUR,51889,EN,CT,France,S,South Korea,50,"Spark, Tableau, R, AWS",Associate,0,Real Estate,2024-08-25,2024-10-20,2285,8.2,Future Systems +AI12110,AI Research Scientist,200891,AUD,271203,EX,FT,Australia,S,Estonia,50,"Spark, TensorFlow, PyTorch, Computer Vision, Docker",PhD,12,Gaming,2024-12-01,2025-01-01,2100,7.9,Algorithmic Solutions +AI12111,AI Software Engineer,135505,JPY,14905550,SE,FL,Japan,L,Japan,0,"AWS, MLOps, Tableau, Statistics, Computer Vision",Bachelor,7,Education,2025-03-20,2025-05-29,664,8.6,Predictive Systems +AI12112,Computer Vision Engineer,98227,USD,98227,MI,CT,Norway,S,Switzerland,0,"Python, Git, Tableau, Computer Vision",Associate,3,Retail,2024-07-31,2024-10-10,1973,7.5,TechCorp Inc +AI12113,Principal Data Scientist,156496,USD,156496,EX,PT,South Korea,M,South Korea,0,"AWS, R, Python, Statistics",PhD,15,Retail,2024-05-28,2024-08-01,1858,7.7,Future Systems +AI12114,Machine Learning Researcher,102263,AUD,138055,MI,FL,Australia,M,Australia,0,"AWS, Tableau, Hadoop, TensorFlow, Azure",Associate,4,Retail,2024-06-28,2024-07-23,1553,6.3,Algorithmic Solutions +AI12115,Data Scientist,82355,GBP,61766,MI,FL,United Kingdom,S,United Kingdom,50,"Scala, Kubernetes, MLOps, SQL",Associate,4,Government,2024-11-04,2024-12-31,1044,7.3,Algorithmic Solutions +AI12116,AI Software Engineer,102312,USD,102312,EX,CT,China,M,China,100,"AWS, Scala, PyTorch",Master,14,Government,2025-03-24,2025-05-07,1376,9.9,DataVision Ltd +AI12117,Machine Learning Engineer,213639,USD,213639,EX,FL,Sweden,S,Hungary,50,"R, SQL, Docker, Computer Vision",Associate,14,Transportation,2024-12-04,2025-01-07,2256,7.8,Algorithmic Solutions +AI12118,Autonomous Systems Engineer,79347,USD,79347,EN,FT,Denmark,M,Denmark,0,"Python, Mathematics, Spark",Master,1,Healthcare,2024-11-12,2024-12-03,2385,9.2,Cloud AI Solutions +AI12119,Machine Learning Engineer,378082,USD,378082,EX,PT,Denmark,L,Denmark,100,"Scala, Statistics, R, Linux",PhD,14,Transportation,2024-12-21,2025-01-17,1551,8.5,DataVision Ltd +AI12120,AI Specialist,90690,USD,90690,MI,FL,Israel,M,Netherlands,0,"R, SQL, Python, TensorFlow",Bachelor,3,Telecommunications,2024-01-27,2024-03-19,2135,8.9,Advanced Robotics +AI12121,AI Software Engineer,183050,USD,183050,EX,CT,Israel,L,Philippines,50,"Deep Learning, NLP, PyTorch, GCP",Master,19,Retail,2024-09-11,2024-11-03,562,7.9,Autonomous Tech +AI12122,AI Research Scientist,106292,EUR,90348,MI,FT,France,L,France,0,"GCP, Python, PyTorch, Tableau",Associate,2,Gaming,2025-02-13,2025-03-12,2000,7.8,DataVision Ltd +AI12123,Data Engineer,281331,CHF,253198,EX,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Mathematics",Associate,19,Automotive,2025-04-15,2025-05-08,1116,5.1,Advanced Robotics +AI12124,Deep Learning Engineer,269789,JPY,29676790,EX,PT,Japan,M,Brazil,50,"SQL, Python, Kubernetes, Computer Vision, Data Visualization",PhD,18,Transportation,2025-01-03,2025-02-14,1006,9.3,DataVision Ltd +AI12125,Principal Data Scientist,55691,EUR,47337,EN,PT,Germany,M,Germany,0,"Azure, Tableau, Spark, Git",Bachelor,1,Energy,2024-06-14,2024-07-04,1510,5.8,Predictive Systems +AI12126,AI Research Scientist,162401,EUR,138041,EX,FL,Netherlands,M,Netherlands,50,"Deep Learning, Linux, SQL, MLOps",PhD,19,Education,2024-04-29,2024-06-03,2255,5.9,Cognitive Computing +AI12127,Robotics Engineer,185193,CHF,166674,SE,FT,Switzerland,S,Switzerland,50,"Data Visualization, Spark, SQL, Java, Deep Learning",Associate,8,Government,2024-04-05,2024-05-31,1191,5.6,Quantum Computing Inc +AI12128,AI Product Manager,288184,EUR,244956,EX,FT,Germany,L,Germany,100,"Docker, MLOps, R, Hadoop",Bachelor,13,Manufacturing,2024-11-25,2024-12-20,1153,5.8,Algorithmic Solutions +AI12129,Machine Learning Researcher,124643,CAD,155804,SE,CT,Canada,L,Ghana,0,"MLOps, Scala, Java",PhD,9,Automotive,2025-04-30,2025-05-21,1770,9.9,Neural Networks Co +AI12130,AI Software Engineer,43362,USD,43362,EN,FT,Israel,S,Israel,0,"GCP, PyTorch, Kubernetes, AWS, Docker",Master,0,Consulting,2025-02-13,2025-04-10,597,5,DataVision Ltd +AI12131,ML Ops Engineer,79374,USD,79374,SE,PT,South Korea,S,South Korea,50,"GCP, Mathematics, TensorFlow, Python",Bachelor,5,Telecommunications,2024-12-21,2025-01-14,1133,8.1,Neural Networks Co +AI12132,AI Consultant,316394,CHF,284755,EX,FT,Switzerland,S,Switzerland,50,"Azure, SQL, Git",Bachelor,10,Finance,2024-07-24,2024-10-04,891,5.4,Advanced Robotics +AI12133,Autonomous Systems Engineer,96744,EUR,82232,SE,PT,Germany,S,Germany,50,"AWS, Docker, GCP, Tableau, PyTorch",Master,8,Real Estate,2024-11-05,2024-12-12,1905,9,Cloud AI Solutions +AI12134,Head of AI,95183,SGD,123738,EN,FT,Singapore,L,Singapore,0,"PyTorch, Kubernetes, GCP",PhD,1,Finance,2024-11-17,2025-01-08,1001,8,Algorithmic Solutions +AI12135,Machine Learning Researcher,121586,USD,121586,SE,PT,United States,M,United States,100,"Scala, PyTorch, Mathematics, MLOps, Git",Bachelor,9,Consulting,2024-06-23,2024-07-25,1663,9.6,DeepTech Ventures +AI12136,Machine Learning Researcher,64380,SGD,83694,EN,FL,Singapore,M,Singapore,50,"Spark, Data Visualization, Java, TensorFlow",Bachelor,1,Healthcare,2024-11-11,2024-12-27,579,5.6,Predictive Systems +AI12137,Computer Vision Engineer,142065,GBP,106549,SE,PT,United Kingdom,S,United Kingdom,0,"R, Computer Vision, Data Visualization, NLP",PhD,9,Transportation,2024-09-14,2024-11-07,1555,5.9,Quantum Computing Inc +AI12138,Autonomous Systems Engineer,30742,USD,30742,EN,FT,China,S,China,0,"Azure, TensorFlow, GCP, Deep Learning",Bachelor,0,Media,2025-04-19,2025-05-17,1319,7.5,Smart Analytics +AI12139,Head of AI,207496,CHF,186746,SE,FL,Switzerland,L,Switzerland,50,"Git, Scala, Docker, Tableau",Master,5,Consulting,2024-03-27,2024-04-18,1801,6.2,Advanced Robotics +AI12140,AI Research Scientist,89982,USD,89982,MI,CT,Israel,S,Brazil,0,"Deep Learning, Kubernetes, Scala",Associate,4,Transportation,2025-03-29,2025-06-04,2083,5.7,Machine Intelligence Group +AI12141,Deep Learning Engineer,116355,USD,116355,SE,FT,Ireland,S,Luxembourg,50,"Python, TensorFlow, MLOps, Deep Learning",Bachelor,9,Gaming,2024-07-26,2024-08-23,2384,8.5,Advanced Robotics +AI12142,AI Architect,87703,USD,87703,MI,FT,Israel,L,Israel,0,"Docker, Tableau, R",Master,4,Manufacturing,2025-02-15,2025-03-14,1525,5.7,Cognitive Computing +AI12143,Data Scientist,75219,CHF,67697,EN,FT,Switzerland,M,Switzerland,100,"Git, R, Tableau, NLP",Associate,0,Government,2024-07-03,2024-07-20,1775,9.1,Future Systems +AI12144,Deep Learning Engineer,71478,EUR,60756,EN,FT,France,L,France,0,"Docker, PyTorch, Spark",PhD,0,Education,2024-09-11,2024-11-12,622,7.3,Digital Transformation LLC +AI12145,AI Research Scientist,132922,GBP,99692,SE,FL,United Kingdom,L,United Kingdom,0,"Linux, Spark, MLOps, Mathematics, Python",Bachelor,9,Automotive,2025-03-13,2025-05-04,721,9.8,Machine Intelligence Group +AI12146,Robotics Engineer,155903,CAD,194879,SE,PT,Canada,L,Canada,100,"Scala, MLOps, Data Visualization",Bachelor,5,Finance,2025-01-05,2025-02-28,1869,5.4,DeepTech Ventures +AI12147,AI Research Scientist,176781,USD,176781,EX,FL,South Korea,S,Singapore,0,"PyTorch, Statistics, Java, GCP",Bachelor,16,Manufacturing,2024-04-05,2024-05-08,2499,8.8,Cloud AI Solutions +AI12148,ML Ops Engineer,125692,AUD,169684,SE,FT,Australia,S,Australia,50,"SQL, Python, Git, Deep Learning",Associate,8,Consulting,2024-11-23,2025-01-19,2471,9.8,Cognitive Computing +AI12149,AI Product Manager,118577,USD,118577,EX,PT,South Korea,M,South Korea,50,"SQL, AWS, Java, Azure, R",PhD,10,Media,2024-10-24,2024-11-14,1747,9.7,AI Innovations +AI12150,AI Product Manager,56555,USD,56555,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Java, Data Visualization",Associate,1,Real Estate,2024-12-30,2025-01-13,2499,7.3,DeepTech Ventures +AI12151,Research Scientist,60065,USD,60065,EN,FT,Finland,L,Finland,0,"Mathematics, PyTorch, Spark",PhD,0,Manufacturing,2024-12-26,2025-02-14,859,9.9,Future Systems +AI12152,Research Scientist,139198,USD,139198,SE,CT,Sweden,L,France,0,"Spark, Hadoop, GCP, Java, Mathematics",Associate,6,Gaming,2024-07-26,2024-09-19,879,8.4,Algorithmic Solutions +AI12153,Machine Learning Researcher,143607,USD,143607,SE,FT,Ireland,M,Ireland,0,"Azure, Hadoop, Python, GCP",Associate,6,Retail,2025-03-20,2025-04-04,1532,10,Digital Transformation LLC +AI12154,Data Analyst,176811,USD,176811,EX,CT,South Korea,L,South Korea,50,"Kubernetes, Scala, Git, Java, GCP",Associate,16,Consulting,2024-11-04,2025-01-09,1133,10,Advanced Robotics +AI12155,Principal Data Scientist,166590,EUR,141602,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Docker, Azure, Scala, Python",Bachelor,5,Media,2024-07-20,2024-09-09,2307,7,Quantum Computing Inc +AI12156,Computer Vision Engineer,34463,USD,34463,MI,FL,India,M,India,100,"PyTorch, Python, Kubernetes, AWS",PhD,2,Technology,2024-07-20,2024-08-26,2225,6.4,Neural Networks Co +AI12157,AI Software Engineer,195880,USD,195880,EX,FL,Finland,S,Finland,0,"Hadoop, Python, TensorFlow, GCP, R",PhD,18,Retail,2024-01-17,2024-03-05,1179,5.6,Neural Networks Co +AI12158,Research Scientist,41697,USD,41697,MI,PT,China,M,China,50,"Azure, Python, TensorFlow",PhD,3,Manufacturing,2024-12-11,2025-02-07,1376,5.2,AI Innovations +AI12159,Research Scientist,61900,USD,61900,EN,CT,Norway,S,Norway,50,"TensorFlow, Scala, Deep Learning",Master,1,Healthcare,2024-11-20,2024-12-30,665,6.2,DataVision Ltd +AI12160,AI Consultant,32827,USD,32827,MI,FL,China,S,China,100,"Python, Kubernetes, SQL, Linux, Docker",Associate,2,Manufacturing,2024-11-03,2024-12-09,2369,7,DataVision Ltd +AI12161,Research Scientist,71766,CAD,89708,EN,FL,Canada,L,Canada,50,"Spark, Java, Mathematics, PyTorch, Computer Vision",Bachelor,1,Technology,2024-06-17,2024-07-07,1130,8.3,DeepTech Ventures +AI12162,ML Ops Engineer,221363,EUR,188159,EX,CT,Austria,M,Austria,0,"PyTorch, TensorFlow, Spark, Hadoop, Azure",Associate,16,Telecommunications,2024-04-08,2024-05-14,2389,5.5,Machine Intelligence Group +AI12163,Autonomous Systems Engineer,125926,AUD,170000,MI,FT,Australia,L,Australia,50,"Spark, Python, Mathematics, TensorFlow, Data Visualization",PhD,2,Gaming,2025-03-11,2025-04-16,1021,8.7,Autonomous Tech +AI12164,Deep Learning Engineer,121421,USD,121421,MI,FL,Denmark,M,Denmark,0,"Docker, AWS, Azure, Tableau, Spark",PhD,3,Telecommunications,2024-06-25,2024-07-18,824,9.4,Quantum Computing Inc +AI12165,Machine Learning Engineer,252757,AUD,341222,EX,FL,Australia,L,Australia,50,"Deep Learning, Scala, PyTorch, GCP, Azure",Associate,15,Automotive,2024-08-13,2024-09-04,2321,6.6,Autonomous Tech +AI12166,Data Scientist,132931,USD,132931,SE,PT,United States,S,United States,50,"Azure, Deep Learning, SQL",Associate,7,Finance,2024-09-07,2024-11-12,792,9.2,Autonomous Tech +AI12167,NLP Engineer,76358,GBP,57269,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, SQL, Computer Vision",Bachelor,1,Telecommunications,2024-12-28,2025-02-05,2476,7.7,Advanced Robotics +AI12168,Research Scientist,243166,AUD,328274,EX,CT,Australia,M,Estonia,0,"PyTorch, Mathematics, NLP, Computer Vision, TensorFlow",Bachelor,17,Automotive,2024-08-22,2024-11-01,2356,6.4,Smart Analytics +AI12169,Principal Data Scientist,101437,USD,101437,EN,CT,Norway,L,Israel,100,"SQL, Docker, Scala",Bachelor,0,Automotive,2024-07-28,2024-09-09,2330,9,Machine Intelligence Group +AI12170,Deep Learning Engineer,99518,USD,99518,MI,CT,United States,L,Luxembourg,100,"Python, TensorFlow, Git, Tableau",PhD,3,Retail,2024-06-25,2024-07-30,600,5.5,Advanced Robotics +AI12171,Deep Learning Engineer,240736,USD,240736,EX,PT,South Korea,L,Vietnam,100,"Scala, Kubernetes, Computer Vision",PhD,17,Telecommunications,2024-02-15,2024-04-24,1757,9.6,Future Systems +AI12172,Data Scientist,296026,SGD,384834,EX,FT,Singapore,L,India,100,"AWS, Scala, Data Visualization, MLOps",Master,12,Transportation,2025-02-05,2025-02-26,1392,5.6,Neural Networks Co +AI12173,Data Engineer,229184,JPY,25210240,EX,FT,Japan,L,Japan,0,"Java, SQL, GCP, NLP",Associate,17,Real Estate,2025-04-24,2025-06-01,1733,9.9,Smart Analytics +AI12174,ML Ops Engineer,151494,USD,151494,SE,FL,Ireland,M,Brazil,0,"Git, Python, MLOps, Java",Associate,7,Automotive,2024-12-04,2025-01-06,1744,6.3,Cloud AI Solutions +AI12175,NLP Engineer,237805,USD,237805,EX,CT,Sweden,L,Sweden,100,"PyTorch, Scala, Git, Mathematics",Master,10,Government,2024-08-03,2024-10-13,1883,5.1,Digital Transformation LLC +AI12176,Autonomous Systems Engineer,71970,AUD,97160,EN,FT,Australia,S,Australia,100,"R, Hadoop, NLP, SQL, Java",Master,0,Consulting,2025-03-22,2025-05-05,1066,6.9,Future Systems +AI12177,AI Architect,142468,SGD,185208,SE,CT,Singapore,S,Singapore,100,"PyTorch, Hadoop, AWS, R, Statistics",PhD,9,Automotive,2024-09-18,2024-10-09,2447,7.8,Predictive Systems +AI12178,NLP Engineer,88665,GBP,66499,MI,FT,United Kingdom,L,Kenya,100,"TensorFlow, Computer Vision, Scala, Tableau, Linux",Bachelor,4,Education,2024-04-12,2024-04-28,2448,7.7,Quantum Computing Inc +AI12179,AI Research Scientist,30066,USD,30066,EN,FL,China,L,China,50,"Azure, Python, Kubernetes, Deep Learning",Associate,1,Finance,2024-04-18,2024-05-10,2492,8.4,Predictive Systems +AI12180,AI Product Manager,90082,EUR,76570,MI,FL,France,S,France,0,"Linux, Docker, Statistics",Bachelor,4,Finance,2025-01-19,2025-02-12,1737,5.8,TechCorp Inc +AI12181,Research Scientist,101851,SGD,132406,MI,CT,Singapore,S,Singapore,0,"Kubernetes, SQL, PyTorch, MLOps",Bachelor,2,Automotive,2024-10-19,2024-12-14,1603,5.2,DeepTech Ventures +AI12182,ML Ops Engineer,246833,USD,246833,EX,FL,United States,S,United States,0,"Spark, AWS, MLOps",Associate,11,Government,2024-01-14,2024-01-28,1238,7.5,DataVision Ltd +AI12183,AI Software Engineer,89470,CHF,80523,EN,PT,Switzerland,S,Switzerland,0,"AWS, Python, GCP, Hadoop",PhD,1,Retail,2024-03-07,2024-05-02,2108,9.5,AI Innovations +AI12184,Deep Learning Engineer,71297,CAD,89121,EN,FT,Canada,M,Luxembourg,0,"SQL, Data Visualization, R",Bachelor,1,Finance,2024-06-28,2024-07-17,1898,9.1,Future Systems +AI12185,Data Scientist,86039,GBP,64529,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Scala, NLP, Computer Vision, Deep Learning",Master,2,Education,2024-05-30,2024-07-07,1586,9.9,Future Systems +AI12186,Data Scientist,34424,USD,34424,MI,CT,India,L,India,50,"GCP, Linux, Statistics",PhD,3,Technology,2024-08-22,2024-10-29,521,9.1,Predictive Systems +AI12187,Machine Learning Researcher,29840,USD,29840,MI,FT,India,M,India,0,"Python, Scala, Tableau, GCP",Master,4,Education,2025-03-20,2025-05-26,1867,8.5,Advanced Robotics +AI12188,Machine Learning Researcher,82805,AUD,111787,MI,PT,Australia,M,Ukraine,100,"TensorFlow, AWS, MLOps",Master,4,Government,2024-07-09,2024-08-15,1520,9.1,Neural Networks Co +AI12189,AI Specialist,90863,USD,90863,MI,CT,Ireland,M,Ireland,100,"Scala, R, Data Visualization",Bachelor,3,Telecommunications,2025-02-05,2025-02-19,928,7.1,Cloud AI Solutions +AI12190,AI Software Engineer,75880,USD,75880,EN,FL,Finland,L,Finland,100,"NLP, TensorFlow, AWS, Tableau, Java",PhD,1,Government,2025-01-11,2025-02-01,2354,8.3,DeepTech Ventures +AI12191,AI Specialist,90998,USD,90998,MI,CT,Norway,S,Norway,100,"Linux, Python, Kubernetes, Spark, Hadoop",PhD,2,Real Estate,2024-10-01,2024-10-15,1560,8.3,AI Innovations +AI12192,AI Product Manager,83633,EUR,71088,MI,CT,Netherlands,S,Netherlands,0,"PyTorch, GCP, Mathematics, Linux",Associate,2,Real Estate,2024-05-25,2024-07-09,2074,5.8,Algorithmic Solutions +AI12193,Deep Learning Engineer,64326,USD,64326,EN,FL,Israel,M,Israel,100,"Computer Vision, Linux, GCP",PhD,0,Finance,2024-07-02,2024-08-21,2230,8.7,Smart Analytics +AI12194,Computer Vision Engineer,111239,CHF,100115,MI,CT,Switzerland,S,Switzerland,50,"PyTorch, SQL, Computer Vision, Java",Bachelor,4,Real Estate,2024-07-08,2024-08-11,2220,7.8,Cognitive Computing +AI12195,AI Product Manager,193976,USD,193976,EX,FL,Norway,M,Belgium,100,"Mathematics, Python, SQL, GCP",PhD,17,Healthcare,2024-12-01,2025-02-03,636,5.3,Smart Analytics +AI12196,AI Architect,252737,USD,252737,EX,CT,Sweden,L,Sweden,0,"Java, Scala, MLOps, Python, Computer Vision",Master,11,Media,2024-08-30,2024-10-12,729,6.4,Quantum Computing Inc +AI12197,AI Specialist,83997,EUR,71397,MI,FL,France,M,France,0,"Kubernetes, Spark, PyTorch",Master,3,Real Estate,2025-02-25,2025-03-30,1849,7.4,Autonomous Tech +AI12198,AI Research Scientist,243739,EUR,207178,EX,PT,Germany,M,Germany,0,"Tableau, Mathematics, MLOps, Hadoop, Python",PhD,16,Technology,2024-07-27,2024-09-28,1990,9.4,Smart Analytics +AI12199,AI Consultant,169734,USD,169734,EX,FL,South Korea,M,South Korea,0,"Scala, Mathematics, Docker, Kubernetes",PhD,17,Energy,2024-12-07,2025-02-15,829,6.6,Algorithmic Solutions +AI12200,Machine Learning Researcher,59827,EUR,50853,EN,FL,Netherlands,S,China,0,"Git, Java, PyTorch, MLOps",Master,0,Finance,2024-04-20,2024-07-02,1072,5.9,Cloud AI Solutions +AI12201,Machine Learning Engineer,107719,SGD,140035,MI,PT,Singapore,L,Singapore,100,"AWS, Deep Learning, Hadoop, Linux",Master,4,Media,2024-04-16,2024-06-15,1335,8.5,AI Innovations +AI12202,AI Software Engineer,75575,JPY,8313250,EN,FT,Japan,M,Japan,50,"Computer Vision, Tableau, Deep Learning, MLOps",PhD,0,Media,2024-12-18,2025-02-17,1152,9.3,Autonomous Tech +AI12203,Autonomous Systems Engineer,281411,GBP,211058,EX,PT,United Kingdom,L,Russia,0,"Git, Spark, TensorFlow, Docker",Bachelor,13,Technology,2024-06-06,2024-07-22,1091,8.9,Cognitive Computing +AI12204,Deep Learning Engineer,88523,USD,88523,MI,FT,Ireland,L,Ireland,50,"Java, Python, Mathematics, Azure, Deep Learning",Bachelor,3,Automotive,2025-04-08,2025-06-13,1762,6.7,Digital Transformation LLC +AI12205,Deep Learning Engineer,61599,USD,61599,EN,PT,South Korea,L,South Korea,0,"Java, Spark, Tableau, Mathematics",Master,1,Government,2024-03-21,2024-05-06,794,7.6,Neural Networks Co +AI12206,Robotics Engineer,74511,SGD,96864,EN,CT,Singapore,L,Singapore,50,"NLP, Statistics, Python",Bachelor,1,Telecommunications,2024-09-22,2024-10-29,2068,6.3,DeepTech Ventures +AI12207,AI Research Scientist,23318,USD,23318,MI,FL,India,S,Thailand,50,"Scala, GCP, Python",Master,3,Government,2025-01-04,2025-02-14,1584,6.2,Quantum Computing Inc +AI12208,Computer Vision Engineer,136734,USD,136734,SE,CT,Finland,L,Finland,100,"Java, Scala, GCP, Kubernetes",Master,7,Telecommunications,2024-06-16,2024-07-24,1494,8,Predictive Systems +AI12209,Deep Learning Engineer,21533,USD,21533,EN,FL,India,L,India,100,"TensorFlow, Python, Data Visualization, Azure",Master,0,Transportation,2024-06-20,2024-07-27,759,9.6,Predictive Systems +AI12210,AI Consultant,69344,EUR,58942,EN,PT,France,M,France,50,"Kubernetes, AWS, Deep Learning",PhD,1,Automotive,2024-11-21,2024-12-21,760,6.5,Quantum Computing Inc +AI12211,Data Engineer,77016,USD,77016,EN,CT,Denmark,M,Thailand,50,"R, GCP, Kubernetes",PhD,0,Consulting,2024-12-05,2024-12-21,1323,7.8,Advanced Robotics +AI12212,AI Product Manager,79033,AUD,106695,MI,FT,Australia,M,Australia,50,"NLP, GCP, Spark",PhD,3,Manufacturing,2024-12-07,2025-01-30,1300,7.2,Future Systems +AI12213,AI Research Scientist,98816,CHF,88934,EN,FT,Switzerland,M,Switzerland,100,"Spark, Statistics, TensorFlow, Tableau",Master,1,Telecommunications,2024-06-05,2024-08-08,1929,7.3,Digital Transformation LLC +AI12214,Robotics Engineer,149985,USD,149985,SE,PT,Israel,L,Hungary,0,"TensorFlow, SQL, GCP, NLP, AWS",Master,6,Government,2024-08-14,2024-09-22,658,5.7,DataVision Ltd +AI12215,Data Scientist,129162,EUR,109788,SE,CT,Netherlands,S,Netherlands,0,"Mathematics, Git, R, SQL",Master,8,Retail,2024-03-24,2024-06-04,1376,8.6,Quantum Computing Inc +AI12216,Robotics Engineer,162024,CAD,202530,EX,CT,Canada,M,Canada,0,"Spark, SQL, Mathematics, PyTorch",Bachelor,14,Healthcare,2024-09-24,2024-11-28,2158,7.9,Algorithmic Solutions +AI12217,AI Consultant,72727,USD,72727,MI,PT,South Korea,S,South Korea,50,"MLOps, GCP, Scala, Computer Vision",Associate,4,Healthcare,2024-11-19,2025-01-02,914,5.4,Machine Intelligence Group +AI12218,Machine Learning Researcher,74894,USD,74894,EN,FL,Ireland,L,Ireland,100,"Kubernetes, MLOps, Linux, PyTorch, Git",PhD,0,Transportation,2025-02-13,2025-04-20,619,6.5,Advanced Robotics +AI12219,AI Specialist,106226,CAD,132783,SE,CT,Canada,M,Canada,100,"Scala, PyTorch, Docker",Associate,5,Energy,2024-12-02,2025-01-14,1075,9.4,Future Systems +AI12220,Computer Vision Engineer,103330,USD,103330,SE,FT,South Korea,L,South Korea,0,"NLP, AWS, Python",Associate,7,Finance,2024-01-07,2024-02-22,1951,6.2,Smart Analytics +AI12221,AI Software Engineer,228843,GBP,171632,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, Python, Computer Vision",Bachelor,18,Manufacturing,2024-10-31,2024-12-16,2231,7.7,Neural Networks Co +AI12222,Deep Learning Engineer,129776,USD,129776,MI,FT,Denmark,M,Vietnam,50,"Hadoop, Linux, SQL",Associate,3,Healthcare,2025-01-30,2025-03-07,1368,8.4,Quantum Computing Inc +AI12223,Research Scientist,146735,USD,146735,SE,FL,Norway,S,United States,50,"Computer Vision, TensorFlow, GCP",Associate,6,Automotive,2024-05-05,2024-05-20,623,8,DeepTech Ventures +AI12224,AI Research Scientist,128592,USD,128592,MI,CT,Denmark,S,Poland,50,"Hadoop, Deep Learning, Spark, AWS",Associate,4,Automotive,2024-06-11,2024-06-26,1115,6.1,TechCorp Inc +AI12225,AI Architect,166057,USD,166057,SE,PT,United States,L,United States,50,"R, MLOps, PyTorch, TensorFlow, Azure",PhD,9,Real Estate,2025-02-05,2025-03-11,2164,6.4,TechCorp Inc +AI12226,Principal Data Scientist,183692,CHF,165323,EX,FT,Switzerland,S,Switzerland,0,"R, Statistics, Git, Mathematics, GCP",Associate,10,Energy,2024-10-19,2024-11-15,2045,7,Machine Intelligence Group +AI12227,AI Software Engineer,43783,USD,43783,EN,FT,South Korea,M,South Korea,50,"SQL, Kubernetes, AWS, R",PhD,0,Education,2024-03-23,2024-04-12,2327,6.8,Quantum Computing Inc +AI12228,Data Scientist,131756,SGD,171283,SE,CT,Singapore,S,Singapore,100,"Mathematics, Deep Learning, Python, Java",Associate,7,Media,2024-01-01,2024-01-27,967,5.1,DeepTech Ventures +AI12229,AI Product Manager,93277,EUR,79285,MI,CT,Germany,S,Nigeria,100,"SQL, Azure, Computer Vision, Scala",PhD,4,Automotive,2024-03-16,2024-03-31,764,5.9,Machine Intelligence Group +AI12230,NLP Engineer,75614,SGD,98298,MI,FT,Singapore,S,Singapore,50,"Kubernetes, R, GCP, MLOps, Docker",Master,2,Government,2024-12-02,2025-01-19,2241,9.1,Cognitive Computing +AI12231,AI Consultant,247382,USD,247382,EX,FT,Ireland,M,Ireland,50,"TensorFlow, Docker, Deep Learning, Python",Master,15,Consulting,2024-10-29,2024-12-25,2013,6,Cloud AI Solutions +AI12232,AI Architect,106997,SGD,139096,MI,CT,Singapore,M,Singapore,50,"MLOps, Data Visualization, R",PhD,2,Healthcare,2024-11-27,2025-01-31,2177,8.8,Cognitive Computing +AI12233,Data Scientist,138109,GBP,103582,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Hadoop, Docker",Bachelor,6,Manufacturing,2024-02-24,2024-04-07,1495,6.9,Machine Intelligence Group +AI12234,Computer Vision Engineer,138794,USD,138794,EX,FT,Ireland,M,Ireland,100,"Statistics, Computer Vision, PyTorch, Azure, Deep Learning",Master,16,Media,2024-02-04,2024-04-09,2355,7.7,DataVision Ltd +AI12235,Autonomous Systems Engineer,168757,USD,168757,EX,CT,South Korea,L,Mexico,0,"TensorFlow, Hadoop, Linux, Docker",Master,11,Media,2024-06-03,2024-07-19,2255,9.6,Digital Transformation LLC +AI12236,AI Consultant,124514,USD,124514,MI,FT,Sweden,L,Spain,0,"Linux, R, Spark, Python, GCP",Associate,4,Government,2024-08-28,2024-10-03,587,9.7,Advanced Robotics +AI12237,Head of AI,59609,GBP,44707,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Computer Vision",Master,0,Retail,2024-05-19,2024-06-03,1917,7.4,Autonomous Tech +AI12238,Computer Vision Engineer,96741,JPY,10641510,MI,PT,Japan,S,Japan,0,"Computer Vision, Azure, Git, TensorFlow, Mathematics",Associate,4,Energy,2024-02-11,2024-04-18,2132,6.9,Quantum Computing Inc +AI12239,Data Analyst,263387,EUR,223879,EX,FL,Netherlands,L,Czech Republic,0,"Statistics, PyTorch, Java, MLOps, Deep Learning",PhD,16,Education,2024-08-08,2024-10-12,2083,6.1,TechCorp Inc +AI12240,Computer Vision Engineer,98959,GBP,74219,MI,PT,United Kingdom,S,United Kingdom,50,"Computer Vision, Hadoop, R, Scala",Bachelor,2,Healthcare,2025-02-15,2025-03-20,1818,7.3,Future Systems +AI12241,Data Scientist,120653,USD,120653,MI,FL,United States,L,United States,100,"Mathematics, Python, Tableau, Data Visualization",Associate,3,Government,2025-04-28,2025-05-19,2337,7.3,DeepTech Ventures +AI12242,AI Architect,157279,AUD,212327,EX,PT,Australia,S,India,100,"Scala, Python, Computer Vision",PhD,18,Real Estate,2024-08-03,2024-09-05,2318,7.4,Cloud AI Solutions +AI12243,AI Specialist,252708,EUR,214802,EX,PT,France,L,France,100,"GCP, Azure, Scala, Data Visualization",Master,18,Government,2024-07-16,2024-09-12,1823,5.1,Advanced Robotics +AI12244,Computer Vision Engineer,98348,USD,98348,EN,FT,Denmark,M,Denmark,0,"NLP, MLOps, Git",PhD,1,Retail,2024-11-22,2024-12-13,1969,7,Smart Analytics +AI12245,AI Architect,195438,USD,195438,EX,FT,Denmark,M,Denmark,50,"Scala, Kubernetes, NLP, Statistics, Python",Associate,11,Gaming,2024-11-18,2024-12-13,1555,9.1,TechCorp Inc +AI12246,Deep Learning Engineer,118243,USD,118243,SE,FT,Israel,M,Luxembourg,50,"Git, MLOps, R, Data Visualization",Master,8,Automotive,2024-09-19,2024-10-11,1355,8.2,Digital Transformation LLC +AI12247,Principal Data Scientist,70867,SGD,92127,MI,CT,Singapore,S,Estonia,100,"R, SQL, Deep Learning",Associate,4,Real Estate,2024-11-03,2024-12-09,715,5.6,Advanced Robotics +AI12248,Data Scientist,108015,USD,108015,SE,PT,South Korea,L,Spain,50,"Hadoop, Python, GCP",PhD,7,Manufacturing,2024-02-22,2024-03-07,2082,5.4,AI Innovations +AI12249,Computer Vision Engineer,68609,USD,68609,MI,FT,South Korea,S,South Korea,50,"Kubernetes, Linux, Docker",Master,3,Transportation,2024-02-01,2024-03-29,652,7.1,Smart Analytics +AI12250,Research Scientist,138450,USD,138450,SE,FL,Norway,M,France,100,"Azure, Java, MLOps, Computer Vision",Bachelor,7,Healthcare,2024-06-18,2024-08-17,1731,5.6,Neural Networks Co +AI12251,Autonomous Systems Engineer,129185,USD,129185,SE,PT,Israel,L,Israel,0,"GCP, Python, Git, Java",PhD,8,Telecommunications,2024-05-18,2024-07-11,2162,8.2,Cognitive Computing +AI12252,Data Engineer,62912,EUR,53475,EN,PT,Austria,L,Austria,50,"SQL, Docker, Linux",PhD,0,Transportation,2024-08-06,2024-09-25,926,6.4,Machine Intelligence Group +AI12253,Machine Learning Engineer,185718,USD,185718,EX,PT,Israel,L,Israel,50,"Python, Mathematics, MLOps, TensorFlow, Deep Learning",Bachelor,11,Manufacturing,2024-02-08,2024-04-04,2195,5.2,DataVision Ltd +AI12254,Machine Learning Engineer,159827,USD,159827,EX,FL,Israel,M,Israel,100,"Python, GCP, Linux, Statistics, Hadoop",Master,19,Finance,2024-12-09,2024-12-28,963,5.4,Autonomous Tech +AI12255,Computer Vision Engineer,93928,SGD,122106,MI,FT,Singapore,M,China,0,"Computer Vision, Python, TensorFlow, Docker, Statistics",Master,3,Media,2024-11-11,2024-11-30,870,6.1,Digital Transformation LLC +AI12256,Research Scientist,75790,GBP,56843,EN,FL,United Kingdom,S,Japan,0,"Java, Scala, GCP, Spark",Bachelor,1,Energy,2024-01-24,2024-03-03,1431,6.5,Neural Networks Co +AI12257,AI Consultant,34200,USD,34200,EN,FT,China,L,China,0,"NLP, Mathematics, Tableau, R, MLOps",Associate,0,Media,2024-04-13,2024-06-24,912,8.4,AI Innovations +AI12258,AI Software Engineer,90286,USD,90286,EN,FT,Denmark,M,Denmark,50,"Deep Learning, Spark, Azure, Tableau, AWS",Master,0,Telecommunications,2024-08-27,2024-10-29,1571,5.3,Digital Transformation LLC +AI12259,Robotics Engineer,146547,CAD,183184,EX,FL,Canada,S,Canada,100,"Kubernetes, Spark, Deep Learning, Statistics, PyTorch",PhD,17,Automotive,2025-03-30,2025-06-01,1978,8.4,TechCorp Inc +AI12260,Computer Vision Engineer,31797,USD,31797,MI,FT,India,M,Belgium,50,"Linux, Kubernetes, Statistics, Deep Learning, R",Associate,3,Gaming,2024-07-10,2024-09-18,923,8.9,Predictive Systems +AI12261,Machine Learning Engineer,54017,CAD,67521,EN,FT,Canada,M,Canada,50,"Git, Python, Spark, Scala",Associate,0,Transportation,2024-09-12,2024-10-08,513,9.2,Quantum Computing Inc +AI12262,Head of AI,272906,EUR,231970,EX,FT,Netherlands,L,India,50,"Python, Spark, Java, Data Visualization",Associate,16,Automotive,2025-03-10,2025-04-11,1833,7.6,Smart Analytics +AI12263,Machine Learning Engineer,43901,CAD,54876,EN,FT,Canada,S,Romania,100,"Deep Learning, AWS, Docker",Master,1,Energy,2024-01-11,2024-03-13,1700,6.7,Advanced Robotics +AI12264,Data Engineer,127644,AUD,172319,SE,FT,Australia,L,India,50,"Mathematics, Python, Computer Vision",Master,8,Finance,2024-07-14,2024-08-25,1260,5.1,Cognitive Computing +AI12265,AI Product Manager,128688,USD,128688,MI,PT,Denmark,L,Ireland,0,"R, Azure, Statistics",Master,4,Automotive,2024-06-28,2024-08-30,2202,9.9,Cognitive Computing +AI12266,AI Product Manager,94657,USD,94657,SE,FT,South Korea,S,South Korea,100,"SQL, TensorFlow, Deep Learning, Hadoop",PhD,8,Government,2025-04-09,2025-05-28,1489,8.8,TechCorp Inc +AI12267,AI Architect,109965,USD,109965,EN,PT,Denmark,L,Mexico,50,"Java, PyTorch, Docker, TensorFlow",Master,1,Gaming,2024-03-07,2024-04-29,752,7,Future Systems +AI12268,Head of AI,206612,USD,206612,EX,CT,Denmark,S,Denmark,0,"Java, R, SQL",Associate,17,Finance,2024-11-19,2025-01-18,1979,9.5,Autonomous Tech +AI12269,Data Engineer,181402,USD,181402,EX,FL,Sweden,S,China,100,"Statistics, SQL, Linux, Spark, Computer Vision",Associate,10,Transportation,2024-09-09,2024-11-09,1526,5,DataVision Ltd +AI12270,Machine Learning Engineer,193935,CHF,174542,SE,FT,Switzerland,L,Switzerland,100,"Git, Docker, Python",Associate,8,Finance,2024-12-22,2025-02-01,671,8.6,Advanced Robotics +AI12271,AI Architect,59622,USD,59622,SE,FT,China,L,China,100,"PyTorch, GCP, Scala",Master,8,Retail,2024-08-19,2024-09-10,616,6.9,DeepTech Ventures +AI12272,Data Engineer,82962,EUR,70518,MI,FL,Netherlands,S,Luxembourg,50,"Hadoop, AWS, NLP",Associate,4,Telecommunications,2024-03-05,2024-05-03,2217,6.5,AI Innovations +AI12273,AI Research Scientist,179005,USD,179005,EX,PT,Sweden,S,New Zealand,50,"Python, TensorFlow, Deep Learning, AWS, Statistics",Master,13,Consulting,2024-02-09,2024-03-09,1916,9.8,Cloud AI Solutions +AI12274,NLP Engineer,45061,USD,45061,EN,FL,South Korea,M,South Korea,50,"Java, SQL, GCP, Deep Learning",PhD,1,Gaming,2024-02-07,2024-02-24,2265,7.7,Future Systems +AI12275,Robotics Engineer,183033,USD,183033,EX,PT,Israel,L,Israel,100,"Git, GCP, MLOps, Computer Vision",PhD,18,Healthcare,2024-10-31,2025-01-03,1456,6.2,DataVision Ltd +AI12276,AI Architect,85926,USD,85926,EN,FL,United States,L,United States,50,"Linux, R, Mathematics, SQL",PhD,0,Technology,2024-02-14,2024-03-31,724,7.7,Cognitive Computing +AI12277,AI Specialist,90585,EUR,76997,SE,FL,Austria,S,United Kingdom,0,"Python, Azure, TensorFlow, Statistics",Bachelor,8,Finance,2024-12-16,2025-01-28,694,7.3,Cognitive Computing +AI12278,ML Ops Engineer,175783,CHF,158205,SE,CT,Switzerland,L,Austria,100,"Docker, Tableau, NLP, Linux, AWS",Associate,7,Gaming,2025-02-12,2025-03-25,1058,8.5,Machine Intelligence Group +AI12279,AI Consultant,136939,USD,136939,SE,FT,Denmark,M,Denmark,0,"Java, GCP, Python, R, Computer Vision",Master,5,Education,2024-12-16,2025-02-04,2284,6.8,Autonomous Tech +AI12280,Computer Vision Engineer,91436,USD,91436,MI,FL,Israel,M,Denmark,50,"Kubernetes, Spark, Tableau",Bachelor,3,Telecommunications,2024-12-28,2025-03-06,596,7.2,TechCorp Inc +AI12281,Computer Vision Engineer,149033,CHF,134130,MI,FT,Switzerland,M,Switzerland,0,"Git, TensorFlow, Data Visualization, Computer Vision, Docker",PhD,4,Media,2024-02-01,2024-04-01,1269,9.8,Advanced Robotics +AI12282,Machine Learning Engineer,66306,USD,66306,EN,CT,Denmark,M,Denmark,100,"SQL, TensorFlow, NLP, Linux",Master,0,Consulting,2024-02-25,2024-05-01,939,5.2,DataVision Ltd +AI12283,AI Software Engineer,59399,USD,59399,SE,CT,China,M,China,100,"Python, TensorFlow, Deep Learning, Git",PhD,5,Healthcare,2024-06-27,2024-08-24,2474,6.1,TechCorp Inc +AI12284,Data Analyst,99702,USD,99702,SE,CT,Sweden,S,Sweden,100,"Python, TensorFlow, Data Visualization",Bachelor,7,Transportation,2025-04-01,2025-05-15,874,9.5,TechCorp Inc +AI12285,AI Architect,100196,USD,100196,SE,CT,South Korea,S,South Korea,50,"Docker, Scala, Python",Master,6,Healthcare,2024-04-04,2024-05-03,600,9.7,Machine Intelligence Group +AI12286,AI Architect,247639,CAD,309549,EX,CT,Canada,L,Spain,100,"R, GCP, Python, Mathematics",Master,10,Media,2024-11-25,2024-12-11,1628,9.1,Digital Transformation LLC +AI12287,Autonomous Systems Engineer,98862,USD,98862,MI,FT,Norway,S,Chile,50,"Python, Computer Vision, GCP, Java, MLOps",Master,4,Manufacturing,2024-05-22,2024-07-16,1346,9.2,Cloud AI Solutions +AI12288,AI Software Engineer,100088,EUR,85075,MI,FL,Netherlands,S,Colombia,100,"Java, Azure, GCP, R",Associate,4,Gaming,2025-01-31,2025-03-12,677,9,Digital Transformation LLC +AI12289,ML Ops Engineer,67854,USD,67854,MI,FL,Israel,S,Israel,50,"Data Visualization, Computer Vision, PyTorch, Spark, GCP",Bachelor,2,Finance,2024-03-28,2024-06-07,1834,7.5,AI Innovations +AI12290,Research Scientist,133071,USD,133071,SE,CT,Finland,M,Finland,0,"Python, Linux, MLOps, Statistics",PhD,8,Healthcare,2024-03-17,2024-05-18,859,8.6,AI Innovations +AI12291,AI Research Scientist,94334,SGD,122634,MI,FL,Singapore,L,Singapore,0,"NLP, Docker, Mathematics, Hadoop",Bachelor,3,Healthcare,2024-12-19,2025-01-24,871,6,Digital Transformation LLC +AI12292,AI Research Scientist,79114,USD,79114,EX,PT,China,L,China,50,"NLP, SQL, Python, Kubernetes",Bachelor,14,Real Estate,2024-08-07,2024-09-27,1681,9.1,Machine Intelligence Group +AI12293,Autonomous Systems Engineer,140641,USD,140641,SE,FL,Sweden,M,Sweden,50,"Python, Kubernetes, GCP, Statistics, Tableau",Master,7,Telecommunications,2024-05-01,2024-05-21,2152,9.2,DeepTech Ventures +AI12294,Computer Vision Engineer,108378,CHF,97540,MI,FT,Switzerland,S,Switzerland,0,"R, Azure, MLOps, Spark, Python",Master,2,Gaming,2024-05-13,2024-06-08,2394,8.6,Autonomous Tech +AI12295,Deep Learning Engineer,66720,USD,66720,EN,FL,Denmark,M,Thailand,0,"Python, TensorFlow, MLOps",Bachelor,0,Technology,2024-04-28,2024-06-22,2040,6.9,Algorithmic Solutions +AI12296,AI Architect,103843,EUR,88267,MI,PT,Germany,L,Germany,100,"Linux, R, Azure, Python",PhD,3,Healthcare,2025-04-03,2025-05-26,789,8.4,Predictive Systems +AI12297,Principal Data Scientist,180949,USD,180949,SE,FL,Norway,M,Norway,0,"SQL, Java, Spark",Associate,7,Real Estate,2024-04-29,2024-06-17,740,8.6,TechCorp Inc +AI12298,Robotics Engineer,320986,USD,320986,EX,CT,United States,L,United States,100,"NLP, Azure, Scala",Bachelor,11,Media,2025-02-28,2025-03-15,1339,8.7,Neural Networks Co +AI12299,AI Product Manager,164065,SGD,213285,SE,PT,Singapore,L,Singapore,100,"Statistics, GCP, Linux, Hadoop",Bachelor,9,Technology,2024-09-19,2024-11-02,1815,8.8,TechCorp Inc +AI12300,Data Analyst,84134,USD,84134,MI,FT,Sweden,S,Sweden,0,"Python, Java, Tableau",PhD,3,Healthcare,2024-01-29,2024-02-19,2364,8.2,Algorithmic Solutions +AI12301,AI Product Manager,59000,USD,59000,EN,FT,Ireland,L,Ireland,0,"Spark, Mathematics, R",Master,0,Energy,2024-11-17,2025-01-16,975,6.3,AI Innovations +AI12302,Data Analyst,184365,USD,184365,EX,FL,Sweden,M,Sweden,50,"SQL, Python, Linux, Docker, Java",Bachelor,17,Automotive,2024-03-21,2024-04-05,2378,5.9,Cognitive Computing +AI12303,AI Architect,74246,CAD,92808,MI,PT,Canada,S,Thailand,100,"PyTorch, SQL, Docker, Computer Vision, R",Master,2,Automotive,2024-08-11,2024-10-22,819,5.2,Cloud AI Solutions +AI12304,Machine Learning Researcher,116928,USD,116928,SE,PT,Ireland,S,Ireland,0,"Docker, MLOps, Scala, Python, AWS",PhD,7,Finance,2024-03-31,2024-04-22,1068,5.2,AI Innovations +AI12305,Principal Data Scientist,64457,USD,64457,SE,FT,China,L,China,50,"Statistics, Scala, Kubernetes",PhD,7,Finance,2024-03-27,2024-05-17,915,9.4,Autonomous Tech +AI12306,AI Architect,34017,USD,34017,EN,CT,China,S,China,50,"Git, Docker, Azure, Tableau, Python",Associate,1,Government,2025-03-01,2025-04-15,1811,8.1,Cognitive Computing +AI12307,Principal Data Scientist,86245,USD,86245,EN,FL,Ireland,L,Ireland,0,"Deep Learning, R, SQL, PyTorch",Master,1,Technology,2024-05-14,2024-06-24,1477,6.9,Predictive Systems +AI12308,Data Analyst,304034,USD,304034,EX,CT,Denmark,M,Denmark,50,"MLOps, Linux, Hadoop, PyTorch",Master,11,Retail,2024-01-06,2024-01-23,683,9,Machine Intelligence Group +AI12309,Machine Learning Researcher,207016,USD,207016,EX,FT,Finland,S,Finland,100,"Hadoop, R, PyTorch, Java, Docker",Associate,11,Media,2024-12-11,2025-01-06,593,5.3,AI Innovations +AI12310,AI Research Scientist,192387,GBP,144290,EX,FL,United Kingdom,M,Singapore,50,"Java, Python, R",PhD,17,Consulting,2024-09-18,2024-11-22,2353,8.6,Future Systems +AI12311,Data Analyst,23733,USD,23733,MI,FT,India,S,Switzerland,100,"Git, Python, MLOps, Tableau",Master,3,Gaming,2024-08-25,2024-09-15,628,8.6,Advanced Robotics +AI12312,AI Architect,154274,USD,154274,SE,PT,Denmark,L,United States,0,"Deep Learning, Mathematics, Scala, AWS",PhD,9,Retail,2024-02-13,2024-03-27,1673,6,DeepTech Ventures +AI12313,NLP Engineer,43529,USD,43529,MI,CT,China,S,Colombia,50,"Scala, Kubernetes, R, Computer Vision",Master,4,Education,2025-01-04,2025-02-27,855,8.4,Future Systems +AI12314,AI Product Manager,214849,EUR,182622,EX,FL,Austria,M,Austria,50,"Git, Hadoop, Mathematics, PyTorch, Statistics",Bachelor,11,Government,2024-10-25,2024-11-09,2133,8.4,Algorithmic Solutions +AI12315,AI Research Scientist,49530,USD,49530,MI,PT,China,M,China,50,"Kubernetes, GCP, Python",PhD,3,Transportation,2024-12-16,2025-02-12,1247,5.3,Algorithmic Solutions +AI12316,AI Product Manager,90866,USD,90866,EN,FL,Denmark,S,Denmark,0,"Tableau, TensorFlow, Linux, Java",PhD,1,Education,2024-09-04,2024-11-03,2019,9.6,Neural Networks Co +AI12317,Principal Data Scientist,38519,USD,38519,EN,CT,South Korea,S,South Korea,0,"Tableau, AWS, SQL, Computer Vision",PhD,1,Healthcare,2024-07-04,2024-09-02,1845,5.3,DeepTech Ventures +AI12318,Principal Data Scientist,190560,SGD,247728,EX,PT,Singapore,L,Singapore,50,"Kubernetes, Spark, TensorFlow, Data Visualization, Mathematics",PhD,14,Automotive,2024-01-07,2024-03-06,1253,8.5,Future Systems +AI12319,Data Scientist,111397,USD,111397,SE,FL,Sweden,M,Sweden,0,"NLP, Java, Git, SQL",Bachelor,9,Healthcare,2024-04-21,2024-05-27,2032,9.6,DeepTech Ventures +AI12320,Head of AI,100635,USD,100635,MI,CT,Finland,M,Finland,0,"Linux, Java, SQL, Mathematics",PhD,2,Automotive,2025-04-28,2025-05-20,2219,9,Quantum Computing Inc +AI12321,Robotics Engineer,108577,USD,108577,SE,FT,Finland,M,Finland,100,"Statistics, GCP, Docker, Git, Computer Vision",Associate,7,Healthcare,2024-07-23,2024-09-11,641,5,TechCorp Inc +AI12322,AI Product Manager,34193,USD,34193,MI,PT,India,L,India,0,"Scala, GCP, Linux, SQL, Hadoop",Bachelor,3,Healthcare,2024-06-08,2024-07-20,679,6.1,Quantum Computing Inc +AI12323,AI Software Engineer,110241,EUR,93705,SE,PT,Austria,M,Indonesia,50,"GCP, Computer Vision, TensorFlow, Tableau",Bachelor,6,Real Estate,2024-06-06,2024-07-21,1072,8.8,DeepTech Ventures +AI12324,Data Scientist,184497,USD,184497,EX,PT,Denmark,S,Denmark,50,"Tableau, Azure, Java, Kubernetes, MLOps",Master,16,Real Estate,2024-07-24,2024-09-07,1516,5.3,DeepTech Ventures +AI12325,AI Architect,84774,USD,84774,EN,FL,Finland,L,Finland,50,"Hadoop, PyTorch, Git, Azure, TensorFlow",Bachelor,0,Manufacturing,2024-09-12,2024-11-17,1470,6.4,Cloud AI Solutions +AI12326,Robotics Engineer,235792,USD,235792,EX,CT,United States,L,Philippines,0,"MLOps, Java, Docker",Bachelor,14,Finance,2024-10-20,2024-11-03,1360,6,Advanced Robotics +AI12327,Autonomous Systems Engineer,54131,USD,54131,EX,FL,India,M,India,0,"Computer Vision, GCP, Scala, Git",Master,15,Government,2024-07-09,2024-07-25,1390,7,Cognitive Computing +AI12328,Research Scientist,154810,CAD,193513,EX,FT,Canada,L,Canada,100,"Computer Vision, Kubernetes, NLP, R, Scala",Bachelor,15,Media,2024-09-03,2024-10-30,1652,6,DataVision Ltd +AI12329,AI Software Engineer,86911,EUR,73874,EN,PT,Netherlands,L,Netherlands,0,"Python, Spark, GCP, AWS, Azure",PhD,0,Telecommunications,2024-03-02,2024-05-11,2154,5.1,Digital Transformation LLC +AI12330,Machine Learning Engineer,83432,JPY,9177520,MI,CT,Japan,S,Austria,0,"Kubernetes, Git, MLOps, GCP",PhD,3,Media,2024-11-03,2024-12-08,1132,8.1,AI Innovations +AI12331,Data Analyst,104994,USD,104994,EX,CT,China,M,China,100,"Deep Learning, PyTorch, Data Visualization, TensorFlow, MLOps",PhD,11,Healthcare,2025-02-05,2025-03-22,1601,9.4,Cloud AI Solutions +AI12332,Principal Data Scientist,114869,EUR,97639,SE,PT,France,L,France,50,"Scala, Git, PyTorch",PhD,6,Consulting,2024-06-12,2024-07-28,1537,6.3,Predictive Systems +AI12333,AI Consultant,108366,USD,108366,SE,FT,South Korea,M,South Korea,100,"Azure, AWS, Data Visualization, Git, Computer Vision",Associate,7,Transportation,2024-04-07,2024-06-17,1379,8.2,Future Systems +AI12334,Machine Learning Engineer,112203,USD,112203,MI,FL,Ireland,L,Ireland,50,"SQL, R, Python, AWS",PhD,2,Media,2024-12-04,2025-01-07,1218,8.6,Smart Analytics +AI12335,Data Analyst,152809,EUR,129888,EX,FL,France,S,France,100,"Spark, Python, Tableau, Statistics",Master,19,Retail,2024-05-07,2024-06-07,1099,6.6,Autonomous Tech +AI12336,AI Consultant,55945,USD,55945,MI,CT,China,L,Finland,0,"Azure, Scala, Python, Statistics, Mathematics",Bachelor,4,Gaming,2024-01-01,2024-01-23,2346,6.7,Machine Intelligence Group +AI12337,Research Scientist,139128,USD,139128,SE,PT,Finland,L,Finland,100,"Hadoop, Scala, Computer Vision, TensorFlow, Docker",PhD,8,Media,2024-09-19,2024-10-07,761,6.9,Quantum Computing Inc +AI12338,NLP Engineer,74433,USD,74433,MI,PT,Ireland,S,Ireland,50,"R, GCP, Hadoop",Master,2,Real Estate,2024-05-15,2024-07-04,888,6.7,Predictive Systems +AI12339,Deep Learning Engineer,62585,USD,62585,EN,PT,Finland,L,Russia,100,"GCP, SQL, NLP, Statistics",PhD,1,Real Estate,2024-03-14,2024-04-09,1943,8.9,Cognitive Computing +AI12340,Deep Learning Engineer,64130,JPY,7054300,EN,PT,Japan,S,Japan,50,"Hadoop, Tableau, AWS, Java, Data Visualization",PhD,1,Telecommunications,2025-01-16,2025-01-31,2403,8.8,DataVision Ltd +AI12341,Head of AI,24000,USD,24000,EN,FL,India,M,India,50,"Spark, Hadoop, Statistics, Python",PhD,1,Retail,2024-06-20,2024-08-19,1168,9.5,Advanced Robotics +AI12342,ML Ops Engineer,63740,EUR,54179,EN,FL,France,L,Belgium,100,"Computer Vision, MLOps, Deep Learning, Python",Associate,0,Telecommunications,2024-12-15,2025-01-26,2452,5,Cognitive Computing +AI12343,AI Architect,75688,EUR,64335,EN,FT,Netherlands,M,Netherlands,100,"TensorFlow, Spark, Tableau, Data Visualization, Scala",PhD,0,Retail,2024-12-01,2025-02-10,1406,6.3,Smart Analytics +AI12344,Autonomous Systems Engineer,91038,USD,91038,EN,CT,Sweden,L,Sweden,0,"Python, Java, AWS, Mathematics",Associate,1,Consulting,2024-02-05,2024-03-18,908,5.5,Predictive Systems +AI12345,Autonomous Systems Engineer,171871,USD,171871,EX,FT,Israel,M,Malaysia,50,"PyTorch, R, Mathematics, MLOps",Associate,10,Real Estate,2024-06-03,2024-07-14,2018,8.2,Predictive Systems +AI12346,ML Ops Engineer,92855,USD,92855,EN,FL,Norway,S,Ukraine,0,"Python, Data Visualization, TensorFlow, Spark, Hadoop",Associate,1,Education,2024-08-01,2024-09-11,1286,9.5,Future Systems +AI12347,AI Specialist,138709,USD,138709,MI,PT,Norway,M,Norway,100,"Scala, MLOps, TensorFlow, Hadoop",Master,2,Government,2025-04-27,2025-06-27,1095,7.7,Predictive Systems +AI12348,AI Product Manager,89902,USD,89902,EX,CT,India,L,India,50,"Java, Statistics, Tableau, NLP, PyTorch",Bachelor,12,Telecommunications,2024-03-08,2024-04-04,791,9.8,TechCorp Inc +AI12349,Machine Learning Engineer,172633,USD,172633,SE,CT,United States,M,Poland,50,"Python, R, Git, GCP, Deep Learning",Associate,8,Retail,2024-10-08,2024-12-08,645,6.9,TechCorp Inc +AI12350,Robotics Engineer,113910,USD,113910,SE,FT,Israel,M,Israel,0,"Azure, Scala, Data Visualization, Java, Spark",Bachelor,5,Retail,2024-08-20,2024-10-17,1576,5.7,Neural Networks Co +AI12351,Robotics Engineer,145181,USD,145181,SE,FT,United States,S,United Kingdom,50,"Spark, Tableau, MLOps, R, Computer Vision",Associate,8,Gaming,2024-06-23,2024-07-19,1128,5.5,Smart Analytics +AI12352,Data Scientist,126932,CAD,158665,SE,FL,Canada,S,Canada,0,"Computer Vision, Scala, Azure, SQL, Hadoop",PhD,7,Education,2024-11-02,2025-01-14,1822,6.6,Algorithmic Solutions +AI12353,Data Engineer,237969,EUR,202274,EX,FT,Austria,L,Austria,100,"Computer Vision, Azure, Hadoop, Git",Bachelor,13,Manufacturing,2024-03-22,2024-04-19,1312,9.3,Cloud AI Solutions +AI12354,ML Ops Engineer,70164,USD,70164,EX,CT,China,S,China,50,"Kubernetes, Scala, GCP",PhD,12,Energy,2024-02-05,2024-02-25,1714,6.4,Algorithmic Solutions +AI12355,Principal Data Scientist,91580,USD,91580,MI,PT,Sweden,L,Sweden,50,"Java, TensorFlow, NLP, R, Linux",Associate,2,Retail,2025-04-17,2025-05-30,1576,8.7,Algorithmic Solutions +AI12356,Data Scientist,210798,SGD,274037,EX,CT,Singapore,L,Czech Republic,50,"Azure, Python, TensorFlow",Bachelor,16,Automotive,2025-04-27,2025-06-03,1488,5.4,Advanced Robotics +AI12357,Data Scientist,172275,SGD,223958,EX,FL,Singapore,S,Norway,100,"PyTorch, MLOps, Scala, Mathematics, Computer Vision",Associate,11,Telecommunications,2024-01-22,2024-03-26,1642,5.1,DeepTech Ventures +AI12358,Data Scientist,181539,GBP,136154,SE,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, AWS",Bachelor,5,Gaming,2024-03-29,2024-04-30,849,9.6,AI Innovations +AI12359,Principal Data Scientist,83912,JPY,9230320,EN,FT,Japan,L,Japan,100,"Docker, Data Visualization, Computer Vision",Master,0,Automotive,2024-09-05,2024-10-07,1372,5.8,Predictive Systems +AI12360,AI Product Manager,126540,USD,126540,MI,PT,Sweden,L,Sweden,0,"Deep Learning, Kubernetes, Python, Git",Bachelor,3,Government,2024-11-17,2024-12-20,747,8.2,Future Systems +AI12361,Machine Learning Researcher,136341,USD,136341,MI,FL,Denmark,L,South Africa,100,"SQL, NLP, MLOps",Master,2,Finance,2024-08-19,2024-10-08,2113,7.4,Machine Intelligence Group +AI12362,Principal Data Scientist,134759,EUR,114545,SE,FT,Germany,S,Germany,50,"NLP, Spark, Azure, Python",Bachelor,6,Energy,2024-08-24,2024-10-23,901,5.4,Digital Transformation LLC +AI12363,AI Research Scientist,71946,EUR,61154,MI,FT,Netherlands,S,Turkey,100,"Spark, Hadoop, TensorFlow, MLOps",Master,3,Healthcare,2024-08-14,2024-10-03,1113,7.5,Quantum Computing Inc +AI12364,NLP Engineer,93601,EUR,79561,MI,PT,France,L,France,50,"Python, GCP, Kubernetes, TensorFlow, Git",Master,2,Telecommunications,2025-01-18,2025-02-19,986,5.6,Predictive Systems +AI12365,Autonomous Systems Engineer,96130,CAD,120163,SE,FL,Canada,M,Canada,50,"Scala, AWS, Tableau, TensorFlow, Spark",Bachelor,7,Transportation,2024-08-16,2024-09-13,547,5.1,Neural Networks Co +AI12366,AI Consultant,62895,CAD,78619,EN,FT,Canada,L,Canada,0,"Hadoop, SQL, TensorFlow, Python",Associate,0,Telecommunications,2025-04-07,2025-05-17,903,7.6,Predictive Systems +AI12367,ML Ops Engineer,71053,USD,71053,EN,FT,Finland,M,Finland,50,"Scala, Java, GCP, Spark",Bachelor,1,Finance,2024-04-25,2024-05-17,626,5.2,Algorithmic Solutions +AI12368,Data Scientist,235335,USD,235335,EX,CT,Ireland,M,Ireland,100,"Scala, R, NLP",PhD,10,Finance,2024-12-12,2025-01-02,826,7.7,Neural Networks Co +AI12369,Data Analyst,189502,EUR,161077,EX,CT,Austria,S,Australia,50,"Hadoop, PyTorch, SQL, GCP",Bachelor,15,Finance,2025-02-24,2025-04-25,2412,8.9,Algorithmic Solutions +AI12370,Deep Learning Engineer,60818,USD,60818,SE,FT,China,M,China,50,"Scala, Data Visualization, SQL, TensorFlow",PhD,7,Education,2024-11-13,2024-12-05,1109,6.7,Quantum Computing Inc +AI12371,Data Analyst,139977,EUR,118980,SE,CT,Netherlands,L,Norway,50,"Java, GCP, Azure, Tableau, AWS",PhD,5,Energy,2024-02-25,2024-03-24,1555,6,DeepTech Ventures +AI12372,Autonomous Systems Engineer,305019,GBP,228764,EX,FT,United Kingdom,L,United Kingdom,0,"Kubernetes, Spark, Python, Java",PhD,19,Gaming,2024-08-06,2024-08-24,907,6.5,Autonomous Tech +AI12373,AI Architect,74292,EUR,63148,MI,FT,Austria,M,Philippines,0,"Python, Mathematics, PyTorch, SQL, Deep Learning",Associate,3,Finance,2025-02-24,2025-04-25,2408,8.3,Cloud AI Solutions +AI12374,ML Ops Engineer,65497,USD,65497,EN,FL,Finland,L,Finland,0,"Linux, Deep Learning, Python, Mathematics, Git",PhD,1,Media,2024-11-18,2025-01-05,1132,9.1,Advanced Robotics +AI12375,Principal Data Scientist,17450,USD,17450,EN,FT,India,S,India,50,"MLOps, Azure, Git",Bachelor,0,Real Estate,2024-12-03,2025-02-13,517,6.4,Neural Networks Co +AI12376,Machine Learning Engineer,56393,CAD,70491,EN,FL,Canada,S,Canada,100,"R, Tableau, Docker",Bachelor,0,Real Estate,2024-08-28,2024-10-25,2498,6.7,Algorithmic Solutions +AI12377,Machine Learning Researcher,28903,USD,28903,EN,FT,India,L,India,0,"Python, Deep Learning, Computer Vision",Associate,0,Finance,2025-03-14,2025-05-09,2425,5.8,Cognitive Computing +AI12378,Machine Learning Researcher,204225,JPY,22464750,EX,FL,Japan,M,Japan,100,"NLP, SQL, PyTorch",Bachelor,14,Manufacturing,2025-02-25,2025-03-16,735,9.2,Neural Networks Co +AI12379,Head of AI,182487,EUR,155114,EX,CT,Austria,M,Italy,100,"Python, PyTorch, Linux, Java, GCP",Associate,13,Consulting,2024-03-12,2024-04-02,891,6.2,AI Innovations +AI12380,Robotics Engineer,122104,USD,122104,SE,PT,United States,M,South Africa,50,"R, Data Visualization, Linux",PhD,8,Transportation,2024-05-09,2024-05-30,933,5.6,Neural Networks Co +AI12381,Data Engineer,107231,USD,107231,SE,CT,Sweden,S,Sweden,100,"Git, Kubernetes, PyTorch",Bachelor,9,Telecommunications,2024-06-15,2024-08-14,643,9.2,Quantum Computing Inc +AI12382,Deep Learning Engineer,37458,USD,37458,MI,PT,India,M,Czech Republic,50,"Tableau, Hadoop, Java, Azure",Bachelor,4,Consulting,2024-12-02,2024-12-22,1953,5.2,AI Innovations +AI12383,AI Architect,145761,USD,145761,EX,CT,Israel,S,Israel,100,"Java, Statistics, Python, Tableau",Master,13,Media,2024-06-05,2024-07-08,2475,9.1,Predictive Systems +AI12384,Data Engineer,200170,CHF,180153,EX,FL,Switzerland,S,Switzerland,0,"Git, PyTorch, Tableau, Data Visualization, Docker",Master,13,Manufacturing,2025-04-24,2025-06-27,780,5.6,Future Systems +AI12385,ML Ops Engineer,82455,CAD,103069,MI,PT,Canada,S,Canada,50,"Deep Learning, Git, MLOps",Bachelor,4,Retail,2024-01-29,2024-04-09,1588,6,AI Innovations +AI12386,Principal Data Scientist,77760,AUD,104976,EN,PT,Australia,M,Australia,50,"Hadoop, Mathematics, TensorFlow, R",PhD,1,Government,2024-05-01,2024-06-01,1392,8.5,Algorithmic Solutions +AI12387,AI Architect,142182,USD,142182,SE,FT,Finland,M,Finland,100,"Statistics, Kubernetes, Python, Computer Vision, TensorFlow",Associate,5,Government,2024-04-24,2024-05-10,853,9.9,Cloud AI Solutions +AI12388,Robotics Engineer,132350,USD,132350,SE,CT,Ireland,L,Ireland,100,"Data Visualization, Scala, Python, Azure",Associate,9,Real Estate,2025-01-28,2025-02-21,2147,8.2,Advanced Robotics +AI12389,Data Engineer,141077,USD,141077,SE,FL,South Korea,L,South Korea,100,"Docker, Linux, Spark, Deep Learning",Master,7,Government,2025-01-14,2025-02-13,1331,7.2,DeepTech Ventures +AI12390,Research Scientist,237360,CHF,213624,EX,FT,Switzerland,M,Switzerland,100,"MLOps, Statistics, Hadoop",Bachelor,13,Real Estate,2024-12-24,2025-01-21,1615,8.4,Future Systems +AI12391,Data Engineer,138254,JPY,15207940,EX,CT,Japan,S,Japan,50,"Spark, Kubernetes, Data Visualization, SQL",PhD,15,Healthcare,2024-11-01,2025-01-07,1803,9.5,TechCorp Inc +AI12392,AI Consultant,181342,EUR,154141,EX,FL,Netherlands,S,Netherlands,50,"Mathematics, PyTorch, Data Visualization, Scala, Spark",PhD,16,Technology,2025-03-11,2025-05-20,2346,6.8,Autonomous Tech +AI12393,Deep Learning Engineer,154049,JPY,16945390,SE,PT,Japan,M,Japan,100,"Git, Hadoop, Tableau",PhD,8,Healthcare,2024-04-27,2024-05-25,830,6.3,Advanced Robotics +AI12394,Machine Learning Researcher,57960,EUR,49266,EN,FT,Netherlands,S,Netherlands,0,"Python, Azure, Scala, Linux",Master,1,Education,2024-06-01,2024-07-07,1746,5.7,Machine Intelligence Group +AI12395,Principal Data Scientist,281214,USD,281214,EX,CT,Sweden,L,Russia,50,"Data Visualization, Tableau, Python",Bachelor,11,Manufacturing,2024-12-13,2025-01-05,775,8,Autonomous Tech +AI12396,ML Ops Engineer,78328,EUR,66579,EN,CT,Austria,L,Italy,100,"Linux, Scala, Azure, Statistics, Kubernetes",Associate,0,Transportation,2024-03-20,2024-04-12,662,6,Cloud AI Solutions +AI12397,Deep Learning Engineer,253374,CAD,316718,EX,FT,Canada,L,Canada,50,"SQL, Spark, Hadoop",Bachelor,16,Energy,2024-09-16,2024-10-24,1534,8.8,Algorithmic Solutions +AI12398,Autonomous Systems Engineer,168477,USD,168477,SE,CT,Norway,M,Norway,0,"Spark, Linux, PyTorch, SQL",Master,8,Gaming,2024-07-30,2024-08-24,1899,9.6,Autonomous Tech +AI12399,Machine Learning Engineer,87035,USD,87035,MI,FT,United States,S,United States,0,"Data Visualization, Computer Vision, Java, Spark, Statistics",PhD,3,Healthcare,2025-04-22,2025-06-14,2493,8.2,Future Systems +AI12400,AI Specialist,152751,SGD,198576,EX,FL,Singapore,S,Australia,50,"Azure, Scala, Python, TensorFlow, Spark",Associate,16,Energy,2024-02-06,2024-02-21,1240,8,DeepTech Ventures +AI12401,Data Engineer,92050,USD,92050,MI,FT,Sweden,S,Sweden,0,"Docker, MLOps, Python, R, Statistics",Bachelor,4,Automotive,2025-01-28,2025-02-16,1432,6.2,Autonomous Tech +AI12402,Data Scientist,55016,EUR,46764,EN,FT,France,M,Indonesia,0,"Statistics, Python, PyTorch",Associate,1,Retail,2024-06-07,2024-06-21,1512,9.1,Autonomous Tech +AI12403,Computer Vision Engineer,135145,GBP,101359,SE,PT,United Kingdom,M,United Kingdom,100,"AWS, Linux, TensorFlow",Associate,9,Consulting,2024-05-16,2024-06-04,711,10,DeepTech Ventures +AI12404,Head of AI,118429,GBP,88822,SE,CT,United Kingdom,S,Egypt,100,"Spark, Mathematics, Linux, Deep Learning, TensorFlow",Master,7,Consulting,2025-01-19,2025-03-13,995,8.6,Autonomous Tech +AI12405,NLP Engineer,57898,GBP,43424,EN,FL,United Kingdom,M,United Kingdom,50,"Java, Spark, Tableau, MLOps",Master,0,Energy,2024-02-16,2024-03-25,717,7.3,Quantum Computing Inc +AI12406,AI Architect,51180,EUR,43503,EN,CT,Austria,S,Italy,0,"Python, NLP, Data Visualization",Associate,0,Media,2024-11-22,2024-12-06,698,5.5,Quantum Computing Inc +AI12407,Data Scientist,103458,USD,103458,EX,PT,India,L,India,0,"AWS, Docker, Spark, Java, Tableau",Master,19,Media,2024-06-16,2024-08-12,2212,5.5,Future Systems +AI12408,Data Scientist,102748,USD,102748,EX,CT,China,L,China,0,"AWS, Azure, PyTorch, Scala",Bachelor,10,Finance,2025-02-08,2025-04-08,1986,8.1,Smart Analytics +AI12409,Data Analyst,151467,USD,151467,SE,PT,Ireland,M,Ireland,0,"Statistics, TensorFlow, NLP, Mathematics, Java",Bachelor,8,Real Estate,2024-03-12,2024-04-02,1772,9.7,Cognitive Computing +AI12410,Data Scientist,74836,USD,74836,MI,PT,South Korea,M,Singapore,100,"Statistics, NLP, GCP",Associate,2,Telecommunications,2024-08-19,2024-09-23,571,8.7,Neural Networks Co +AI12411,Machine Learning Engineer,169620,EUR,144177,EX,CT,Netherlands,S,Hungary,100,"Java, Git, Hadoop, Docker",PhD,14,Education,2024-10-07,2024-12-17,2161,6,Cognitive Computing +AI12412,AI Software Engineer,113721,CHF,102349,EN,CT,Switzerland,L,Russia,100,"Java, Python, Statistics, Azure",PhD,1,Automotive,2025-03-08,2025-04-10,2083,8.3,Cognitive Computing +AI12413,Head of AI,127743,CHF,114969,MI,FT,Switzerland,S,Austria,0,"SQL, Mathematics, NLP, Spark, Python",PhD,4,Consulting,2024-11-21,2024-12-07,527,8.6,Quantum Computing Inc +AI12414,Principal Data Scientist,305463,USD,305463,EX,FL,Norway,M,Belgium,50,"Scala, Linux, Computer Vision, Tableau, Java",PhD,13,Media,2024-11-13,2024-12-16,1809,5.9,DataVision Ltd +AI12415,AI Specialist,75828,USD,75828,SE,FT,South Korea,S,Indonesia,100,"Scala, GCP, Spark, Java, Mathematics",PhD,6,Education,2024-03-12,2024-04-26,909,8.5,DeepTech Ventures +AI12416,Data Scientist,116542,GBP,87407,SE,FT,United Kingdom,S,United Kingdom,0,"Docker, Linux, AWS, GCP",Master,7,Technology,2024-05-31,2024-07-31,749,5.4,Machine Intelligence Group +AI12417,Deep Learning Engineer,53985,USD,53985,EN,CT,Finland,M,Finland,0,"Java, Tableau, SQL, GCP",Master,0,Retail,2024-05-19,2024-07-09,1864,5.6,Machine Intelligence Group +AI12418,Computer Vision Engineer,60582,EUR,51495,EN,FT,Netherlands,S,Netherlands,100,"Python, Kubernetes, PyTorch, MLOps",Associate,1,Media,2024-04-10,2024-05-02,2394,6.1,Cognitive Computing +AI12419,Machine Learning Engineer,135425,USD,135425,SE,FL,Norway,S,Norway,100,"PyTorch, Linux, Java, R, Git",Associate,6,Energy,2024-07-24,2024-10-04,1969,5.9,Neural Networks Co +AI12420,AI Specialist,62590,JPY,6884900,EN,CT,Japan,L,Japan,100,"Kubernetes, Java, Hadoop",Bachelor,0,Technology,2024-01-07,2024-02-26,2155,9.5,Smart Analytics +AI12421,AI Architect,231935,GBP,173951,EX,PT,United Kingdom,S,United Kingdom,0,"Scala, Spark, R",Bachelor,11,Retail,2024-03-18,2024-05-29,1567,8.6,Neural Networks Co +AI12422,Machine Learning Researcher,71430,USD,71430,EN,FL,Norway,S,Singapore,0,"Python, Statistics, Data Visualization, AWS",Associate,0,Education,2024-03-30,2024-06-01,1777,6.7,Advanced Robotics +AI12423,Computer Vision Engineer,220600,EUR,187510,EX,FT,France,L,France,0,"Java, TensorFlow, Statistics, Computer Vision",PhD,10,Healthcare,2024-10-19,2024-12-04,1423,9.7,Predictive Systems +AI12424,Head of AI,82694,USD,82694,EN,FT,Norway,S,Norway,50,"Python, Mathematics, Azure",Bachelor,1,Gaming,2024-04-06,2024-05-10,1192,9.6,DeepTech Ventures +AI12425,Robotics Engineer,123932,USD,123932,MI,PT,Sweden,L,Belgium,100,"Python, PyTorch, GCP",Master,3,Education,2024-10-30,2024-12-07,1401,6.8,Smart Analytics +AI12426,AI Consultant,137592,EUR,116953,SE,FT,Germany,M,Germany,100,"Kubernetes, AWS, Data Visualization",Associate,7,Automotive,2025-01-18,2025-03-07,1087,9.8,Predictive Systems +AI12427,Machine Learning Engineer,57950,USD,57950,EN,FL,South Korea,S,South Korea,100,"Tableau, Scala, Python, Deep Learning",PhD,1,Energy,2025-03-05,2025-04-08,2003,8.6,Neural Networks Co +AI12428,AI Architect,126435,USD,126435,SE,FT,Israel,S,Israel,0,"PyTorch, SQL, Linux",Bachelor,5,Real Estate,2024-12-21,2025-02-08,2132,5.6,Algorithmic Solutions +AI12429,Machine Learning Researcher,128267,JPY,14109370,SE,CT,Japan,M,Japan,50,"PyTorch, GCP, TensorFlow, Azure, Python",Bachelor,8,Transportation,2025-04-10,2025-05-17,2324,5.4,Autonomous Tech +AI12430,AI Research Scientist,309048,SGD,401762,EX,PT,Singapore,L,Singapore,50,"MLOps, Data Visualization, Java, Linux, R",PhD,12,Finance,2025-04-07,2025-05-31,1545,8.1,Neural Networks Co +AI12431,Data Analyst,134105,JPY,14751550,SE,FL,Japan,L,Japan,0,"Python, MLOps, Spark, NLP, Kubernetes",Bachelor,6,Education,2024-03-17,2024-05-23,2363,10,DeepTech Ventures +AI12432,AI Software Engineer,84521,USD,84521,MI,FT,Israel,S,Israel,0,"GCP, AWS, NLP, Python, Spark",PhD,4,Retail,2024-02-20,2024-04-29,1050,8.6,Smart Analytics +AI12433,Research Scientist,61395,SGD,79814,EN,CT,Singapore,M,Singapore,50,"Statistics, Tableau, NLP",Master,1,Real Estate,2024-04-29,2024-07-05,1577,9.7,Machine Intelligence Group +AI12434,NLP Engineer,152906,USD,152906,SE,CT,Norway,S,Norway,50,"R, GCP, Computer Vision, Linux",Master,6,Technology,2025-04-27,2025-06-19,2345,6.9,TechCorp Inc +AI12435,AI Research Scientist,150492,USD,150492,EX,FT,Israel,S,Switzerland,50,"Linux, TensorFlow, SQL, Deep Learning",Bachelor,18,Transportation,2024-10-24,2024-11-26,2445,5.1,DataVision Ltd +AI12436,Head of AI,261388,SGD,339804,EX,FT,Singapore,M,Singapore,0,"Java, Python, NLP, Docker",Master,10,Healthcare,2025-02-23,2025-04-23,1326,8.3,AI Innovations +AI12437,AI Software Engineer,181176,USD,181176,EX,CT,Finland,S,South Africa,50,"Computer Vision, Linux, Hadoop, Kubernetes, Scala",Bachelor,11,Real Estate,2024-11-22,2025-01-08,1295,6.7,Cognitive Computing +AI12438,Robotics Engineer,185060,EUR,157301,EX,FT,Germany,M,Germany,100,"R, Spark, SQL, Mathematics, Java",Bachelor,12,Media,2024-07-13,2024-08-14,1670,7.3,Neural Networks Co +AI12439,Data Scientist,128763,SGD,167392,SE,PT,Singapore,L,Singapore,100,"Python, Statistics, PyTorch, Spark",Associate,5,Education,2024-11-10,2024-12-24,1042,9,Cloud AI Solutions +AI12440,AI Software Engineer,125753,USD,125753,MI,FL,Denmark,M,Malaysia,50,"Scala, R, Kubernetes, Git, Python",Master,3,Education,2024-11-24,2024-12-11,2160,6.6,Neural Networks Co +AI12441,Data Scientist,121075,USD,121075,SE,FT,Israel,S,Israel,0,"PyTorch, Scala, Deep Learning, MLOps",PhD,6,Consulting,2024-12-24,2025-01-29,1737,5.8,Autonomous Tech +AI12442,ML Ops Engineer,27334,USD,27334,EN,CT,India,M,India,0,"Kubernetes, PyTorch, Statistics, Computer Vision, TensorFlow",PhD,1,Education,2025-04-01,2025-06-09,1734,8.9,Quantum Computing Inc +AI12443,Computer Vision Engineer,234245,CHF,210821,SE,FT,Switzerland,L,Egypt,50,"PyTorch, SQL, Git, Statistics, GCP",Associate,5,Media,2024-02-08,2024-04-13,2405,9.8,DataVision Ltd +AI12444,AI Software Engineer,79787,USD,79787,EN,FT,Norway,S,Norway,50,"TensorFlow, Tableau, AWS, MLOps",Associate,0,Government,2025-04-27,2025-06-17,695,6.3,Algorithmic Solutions +AI12445,Head of AI,46395,USD,46395,EN,FT,Sweden,S,Sweden,100,"PyTorch, Java, Git, Azure",Bachelor,0,Manufacturing,2024-10-19,2024-12-23,1792,5.6,Cognitive Computing +AI12446,AI Consultant,82377,EUR,70020,EN,CT,Austria,L,Poland,50,"TensorFlow, Python, Tableau",Bachelor,0,Healthcare,2024-02-20,2024-05-02,1384,7.5,Smart Analytics +AI12447,Machine Learning Engineer,63540,CAD,79425,EN,CT,Canada,M,Canada,0,"SQL, NLP, Kubernetes, Git",Associate,0,Energy,2024-12-19,2025-01-08,1756,6.7,Advanced Robotics +AI12448,NLP Engineer,90047,USD,90047,EX,PT,China,M,China,100,"SQL, Deep Learning, Spark, R, Tableau",Bachelor,18,Telecommunications,2025-04-22,2025-06-01,1548,9.9,Predictive Systems +AI12449,Head of AI,108278,USD,108278,SE,PT,Sweden,M,Sweden,50,"PyTorch, Git, Mathematics, Scala",Bachelor,5,Manufacturing,2024-05-13,2024-05-31,1662,8.1,Cognitive Computing +AI12450,Machine Learning Engineer,255205,JPY,28072550,EX,CT,Japan,L,Japan,100,"R, Mathematics, Linux",Bachelor,17,Technology,2024-09-12,2024-10-16,1755,5.2,Algorithmic Solutions +AI12451,Machine Learning Engineer,63780,USD,63780,SE,PT,China,M,China,100,"PyTorch, Computer Vision, Tableau",Associate,8,Energy,2024-08-13,2024-10-04,1419,6.3,Predictive Systems +AI12452,Machine Learning Researcher,57335,GBP,43001,EN,FT,United Kingdom,S,Belgium,50,"Git, Mathematics, MLOps, Deep Learning, R",PhD,0,Retail,2024-01-31,2024-03-11,814,10,Neural Networks Co +AI12453,AI Consultant,68846,USD,68846,EN,PT,Finland,M,Finland,50,"Scala, Tableau, Deep Learning",PhD,1,Gaming,2025-02-18,2025-03-12,2445,7.5,DataVision Ltd +AI12454,Autonomous Systems Engineer,127642,EUR,108496,SE,CT,Netherlands,L,India,50,"MLOps, TensorFlow, AWS, Hadoop",Master,6,Technology,2025-04-24,2025-07-04,1015,7.5,Machine Intelligence Group +AI12455,Data Engineer,119425,USD,119425,SE,PT,Ireland,M,Nigeria,0,"Hadoop, Python, MLOps",Associate,9,Education,2025-04-15,2025-05-14,1732,5.9,Advanced Robotics +AI12456,Data Scientist,29224,USD,29224,EN,PT,China,S,China,0,"Data Visualization, Scala, Kubernetes, SQL, R",Associate,0,Finance,2024-12-08,2024-12-28,2189,9.1,Predictive Systems +AI12457,Computer Vision Engineer,198486,EUR,168713,EX,PT,Austria,M,Austria,100,"TensorFlow, Azure, NLP, Computer Vision",Associate,13,Telecommunications,2024-07-25,2024-09-25,1275,8.2,Advanced Robotics +AI12458,Machine Learning Engineer,203533,CHF,183180,EX,FT,Switzerland,S,Switzerland,0,"GCP, SQL, PyTorch, Kubernetes, Statistics",Bachelor,14,Technology,2025-04-24,2025-05-20,696,6.6,TechCorp Inc +AI12459,AI Product Manager,194939,EUR,165698,EX,FL,France,L,France,50,"Linux, Mathematics, NLP, PyTorch",Bachelor,10,Telecommunications,2024-03-26,2024-05-07,1719,6.7,Algorithmic Solutions +AI12460,Data Analyst,61708,EUR,52452,EN,PT,Germany,S,Germany,50,"Hadoop, Python, Git",Bachelor,1,Manufacturing,2024-05-22,2024-06-14,629,7.5,DataVision Ltd +AI12461,AI Research Scientist,100793,USD,100793,MI,FL,Ireland,L,Ireland,50,"Linux, Hadoop, R, Computer Vision, Statistics",Master,4,Gaming,2024-05-29,2024-08-09,2070,9,Advanced Robotics +AI12462,AI Architect,75694,GBP,56771,EN,PT,United Kingdom,M,Austria,0,"Statistics, PyTorch, Docker, Azure, SQL",Associate,0,Manufacturing,2025-01-06,2025-02-11,2171,8.3,Cognitive Computing +AI12463,Data Scientist,115446,EUR,98129,MI,FL,Netherlands,L,Netherlands,50,"Docker, Python, Deep Learning, Spark",Associate,2,Transportation,2024-07-21,2024-08-23,2121,7.9,Smart Analytics +AI12464,Research Scientist,49167,EUR,41792,EN,FT,Austria,S,Austria,100,"R, Mathematics, Hadoop",Associate,0,Automotive,2024-07-10,2024-08-10,614,8.4,DataVision Ltd +AI12465,AI Product Manager,70180,USD,70180,EN,FL,Sweden,S,Sweden,0,"Docker, R, Deep Learning, SQL",Master,1,Government,2024-03-23,2024-05-12,580,7.5,DeepTech Ventures +AI12466,Data Analyst,19503,USD,19503,EN,CT,India,S,India,0,"PyTorch, Azure, R, SQL",Bachelor,0,Education,2025-03-12,2025-03-26,2448,5.9,Digital Transformation LLC +AI12467,Data Engineer,92958,USD,92958,SE,FT,South Korea,M,South Korea,0,"Azure, SQL, Kubernetes, Spark, Linux",Associate,7,Government,2024-03-19,2024-04-03,1193,6.8,AI Innovations +AI12468,ML Ops Engineer,46075,USD,46075,EX,CT,India,S,India,50,"Scala, NLP, Git",Bachelor,17,Media,2024-10-06,2024-11-30,1655,10,Algorithmic Solutions +AI12469,Data Engineer,31356,USD,31356,MI,FT,China,S,China,0,"Mathematics, Python, Tableau, Computer Vision, SQL",Bachelor,4,Real Estate,2025-03-05,2025-04-06,857,7.5,AI Innovations +AI12470,Data Engineer,169277,EUR,143885,EX,FL,Austria,M,Vietnam,0,"SQL, Git, PyTorch, NLP",Master,12,Media,2024-08-17,2024-10-27,664,7.8,Smart Analytics +AI12471,Machine Learning Engineer,34533,USD,34533,MI,CT,China,M,China,100,"AWS, Tableau, TensorFlow, Spark",PhD,3,Government,2024-04-18,2024-05-15,1855,8.2,DataVision Ltd +AI12472,Deep Learning Engineer,72285,JPY,7951350,EN,FL,Japan,S,Japan,50,"Linux, MLOps, Git, Java",PhD,0,Healthcare,2024-09-24,2024-10-28,1564,7.9,Machine Intelligence Group +AI12473,Machine Learning Researcher,212718,USD,212718,EX,CT,Finland,S,Finland,50,"SQL, Python, Hadoop, Mathematics, Computer Vision",PhD,17,Education,2025-04-05,2025-06-06,2270,8.6,Machine Intelligence Group +AI12474,Machine Learning Engineer,202624,EUR,172230,EX,CT,France,S,France,50,"PyTorch, Hadoop, TensorFlow, SQL",PhD,16,Finance,2024-12-30,2025-01-13,1686,7.2,Machine Intelligence Group +AI12475,ML Ops Engineer,71740,USD,71740,MI,CT,South Korea,L,South Korea,50,"SQL, AWS, Computer Vision, Spark, Linux",Associate,3,Automotive,2025-04-06,2025-05-13,756,9.9,Cloud AI Solutions +AI12476,Autonomous Systems Engineer,232339,CHF,209105,EX,CT,Switzerland,L,Switzerland,0,"AWS, Python, Kubernetes",Master,18,Retail,2024-12-07,2025-01-25,1266,7.2,AI Innovations +AI12477,Machine Learning Engineer,147817,USD,147817,EX,CT,Israel,S,India,0,"Scala, R, SQL",Bachelor,15,Telecommunications,2024-12-13,2025-01-18,1399,6.3,Future Systems +AI12478,Data Engineer,73011,EUR,62059,MI,PT,Germany,S,Germany,50,"SQL, Scala, Tableau",Associate,3,Education,2024-11-22,2024-12-16,1245,7.3,Cognitive Computing +AI12479,ML Ops Engineer,69151,USD,69151,EN,CT,Israel,M,Israel,100,"PyTorch, Python, Statistics",PhD,0,Technology,2024-06-09,2024-08-07,1621,6.5,Digital Transformation LLC +AI12480,Machine Learning Engineer,200050,CHF,180045,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Data Visualization, Statistics, Git",Associate,5,Transportation,2024-05-24,2024-07-16,982,5.5,Autonomous Tech +AI12481,Data Engineer,68571,AUD,92571,MI,FL,Australia,S,Romania,0,"MLOps, Azure, Tableau",Bachelor,3,Consulting,2025-04-10,2025-05-15,578,9.6,DataVision Ltd +AI12482,AI Specialist,27494,USD,27494,EN,FL,China,S,Brazil,50,"Python, Azure, Git, R, Computer Vision",PhD,0,Finance,2024-10-05,2024-11-07,1180,9.1,Cloud AI Solutions +AI12483,AI Research Scientist,54178,USD,54178,SE,CT,China,M,United States,100,"Linux, Scala, PyTorch",PhD,5,Healthcare,2025-04-02,2025-05-31,1625,7.5,Advanced Robotics +AI12484,Robotics Engineer,147943,USD,147943,SE,CT,Denmark,M,Denmark,0,"GCP, Python, Mathematics, Linux",Bachelor,9,Finance,2025-03-19,2025-04-15,1829,6.6,Cloud AI Solutions +AI12485,Research Scientist,246165,CHF,221549,SE,FT,Switzerland,L,Switzerland,50,"Deep Learning, Data Visualization, Docker",Associate,8,Transportation,2024-08-13,2024-09-19,1412,6.4,DataVision Ltd +AI12486,Autonomous Systems Engineer,31203,USD,31203,MI,FT,India,M,India,50,"Data Visualization, SQL, Scala, Tableau, Git",Bachelor,2,Energy,2024-02-27,2024-04-03,1073,5.4,Digital Transformation LLC +AI12487,Head of AI,109051,USD,109051,SE,PT,South Korea,S,South Korea,100,"Scala, AWS, Python",Master,7,Technology,2024-11-09,2024-12-11,1828,7.7,DataVision Ltd +AI12488,AI Consultant,76767,EUR,65252,EN,FL,Netherlands,M,Romania,100,"Tableau, Scala, Docker",Associate,0,Transportation,2024-08-22,2024-10-22,1011,5.9,TechCorp Inc +AI12489,Computer Vision Engineer,64846,GBP,48635,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Scala, TensorFlow",Master,0,Gaming,2024-10-08,2024-12-06,621,6.9,TechCorp Inc +AI12490,Data Engineer,126205,AUD,170377,SE,FT,Australia,L,Australia,100,"Spark, Linux, GCP",Associate,7,Real Estate,2024-01-19,2024-03-08,2036,6.5,Future Systems +AI12491,Data Engineer,162483,USD,162483,MI,PT,Norway,L,Norway,100,"Java, Statistics, R, Docker, Scala",Master,3,Consulting,2024-12-17,2025-02-02,1825,8.3,DeepTech Ventures +AI12492,Machine Learning Engineer,77554,USD,77554,MI,CT,Israel,S,Israel,50,"Azure, AWS, TensorFlow, Linux, Mathematics",Master,3,Education,2024-10-26,2024-11-30,807,5.5,Algorithmic Solutions +AI12493,AI Product Manager,216415,JPY,23805650,EX,FT,Japan,L,Japan,0,"Scala, Python, Hadoop, Git",Master,14,Transportation,2024-01-20,2024-02-15,1804,7.5,Future Systems +AI12494,AI Architect,130182,EUR,110655,SE,FL,Germany,S,Germany,50,"SQL, TensorFlow, GCP",Bachelor,9,Education,2025-03-27,2025-05-17,662,5.9,Machine Intelligence Group +AI12495,Data Scientist,187797,SGD,244136,EX,FL,Singapore,S,Singapore,100,"R, MLOps, Kubernetes, Statistics, Deep Learning",PhD,18,Healthcare,2024-06-30,2024-09-03,799,5.2,Advanced Robotics +AI12496,AI Software Engineer,123365,USD,123365,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Mathematics, TensorFlow, AWS",Associate,4,Manufacturing,2025-01-20,2025-03-24,1723,5.6,Quantum Computing Inc +AI12497,Data Analyst,69926,EUR,59437,EN,FT,Austria,L,Austria,50,"GCP, MLOps, Statistics",Master,1,Real Estate,2024-04-23,2024-06-20,2381,7.5,Cognitive Computing +AI12498,AI Architect,80574,GBP,60431,EN,FT,United Kingdom,M,Poland,50,"Python, Deep Learning, Kubernetes",Associate,0,Finance,2024-07-31,2024-08-23,2300,6.7,Neural Networks Co +AI12499,Computer Vision Engineer,80148,USD,80148,EN,CT,United States,S,United States,50,"Kubernetes, TensorFlow, Computer Vision, Hadoop, Linux",PhD,1,Transportation,2024-10-28,2024-12-23,1220,6.7,DataVision Ltd +AI12500,Machine Learning Engineer,270850,EUR,230223,EX,CT,Germany,L,Indonesia,100,"Statistics, Python, Data Visualization, Scala",Associate,11,Gaming,2025-02-04,2025-03-09,1919,9.5,Neural Networks Co +AI12501,Deep Learning Engineer,160933,CHF,144840,SE,CT,Switzerland,M,Switzerland,100,"Docker, R, Mathematics, Spark, Azure",PhD,7,Energy,2024-03-19,2024-04-19,2404,8,DataVision Ltd +AI12502,Machine Learning Researcher,165119,USD,165119,EX,FT,Ireland,M,Ireland,0,"Data Visualization, Hadoop, Python, Linux",Bachelor,16,Energy,2024-02-05,2024-02-27,709,5.5,Cognitive Computing +AI12503,Deep Learning Engineer,145099,EUR,123334,SE,PT,Germany,L,Germany,50,"GCP, Linux, Tableau, Spark, Data Visualization",Master,7,Media,2025-03-11,2025-05-07,717,6.9,Smart Analytics +AI12504,NLP Engineer,51742,JPY,5691620,EN,FL,Japan,S,Japan,100,"Kubernetes, Python, Data Visualization, Git",PhD,1,Education,2024-02-28,2024-03-19,1536,8.3,Autonomous Tech +AI12505,AI Software Engineer,109327,USD,109327,SE,CT,Sweden,M,Sweden,50,"Docker, MLOps, AWS",PhD,9,Consulting,2024-07-03,2024-07-24,1297,9,DataVision Ltd +AI12506,AI Specialist,151570,CHF,136413,MI,PT,Switzerland,M,Switzerland,100,"Tableau, Kubernetes, TensorFlow, Spark",Master,2,Government,2024-05-27,2024-07-18,2059,7.2,Advanced Robotics +AI12507,Deep Learning Engineer,214037,USD,214037,EX,PT,Sweden,S,Sweden,0,"Mathematics, Computer Vision, Linux",Master,19,Government,2024-03-18,2024-04-11,1865,9.1,Advanced Robotics +AI12508,AI Product Manager,238972,USD,238972,EX,CT,Finland,L,Finland,0,"GCP, Hadoop, Tableau, Deep Learning",Master,18,Healthcare,2024-01-10,2024-02-29,1350,9.8,Predictive Systems +AI12509,Data Analyst,120788,EUR,102670,SE,PT,Germany,L,Germany,50,"Spark, Linux, Deep Learning, Git, TensorFlow",Associate,7,Retail,2024-07-24,2024-09-15,606,8.3,Cognitive Computing +AI12510,AI Product Manager,161084,USD,161084,SE,FT,United States,L,Spain,0,"Linux, Tableau, Data Visualization, Hadoop",Bachelor,7,Telecommunications,2024-01-23,2024-03-16,1681,8,Future Systems +AI12511,AI Specialist,224471,CAD,280589,EX,PT,Canada,M,Canada,100,"SQL, NLP, Azure",Master,17,Government,2024-12-04,2025-02-02,2031,5.4,Neural Networks Co +AI12512,Robotics Engineer,162992,AUD,220039,SE,CT,Australia,L,South Korea,100,"R, NLP, Linux, SQL",Bachelor,8,Government,2024-08-22,2024-09-27,746,6.8,Future Systems +AI12513,Data Analyst,30696,USD,30696,EN,CT,China,S,Portugal,0,"GCP, NLP, Linux, R",Master,0,Media,2024-10-08,2024-11-14,1377,9.1,Algorithmic Solutions +AI12514,Research Scientist,98339,EUR,83588,SE,CT,Austria,M,Austria,0,"PyTorch, R, TensorFlow",Associate,5,Retail,2025-03-28,2025-06-07,1314,5.7,Neural Networks Co +AI12515,Research Scientist,129262,EUR,109873,SE,CT,Austria,M,Austria,0,"Python, Azure, Docker, R, Git",PhD,7,Energy,2024-01-08,2024-02-05,2298,8.5,Autonomous Tech +AI12516,Machine Learning Engineer,112931,CAD,141164,SE,PT,Canada,L,Canada,0,"Python, Tableau, Docker",Associate,8,Consulting,2024-12-14,2025-01-25,2110,6.5,Cognitive Computing +AI12517,AI Product Manager,109950,USD,109950,MI,FT,Ireland,L,Estonia,0,"Azure, AWS, Linux, Docker",Associate,3,Media,2024-07-25,2024-09-12,1158,8.2,Autonomous Tech +AI12518,Computer Vision Engineer,84503,EUR,71828,EN,FT,Germany,L,Germany,0,"R, Linux, NLP",PhD,1,Gaming,2024-04-19,2024-06-20,1765,5.6,Smart Analytics +AI12519,Principal Data Scientist,89243,USD,89243,MI,FL,Sweden,M,South Africa,100,"Azure, Data Visualization, Kubernetes, Docker",PhD,3,Retail,2024-11-09,2024-12-14,592,8,Predictive Systems +AI12520,Data Analyst,194683,CHF,175215,SE,FL,Switzerland,M,Switzerland,100,"Hadoop, SQL, Linux, Scala",PhD,8,Real Estate,2024-03-03,2024-05-11,2107,7.7,Autonomous Tech +AI12521,Data Scientist,34111,USD,34111,MI,PT,China,S,China,50,"Statistics, AWS, R",Master,2,Telecommunications,2024-08-10,2024-09-03,870,6.5,AI Innovations +AI12522,NLP Engineer,104286,SGD,135572,MI,PT,Singapore,L,Singapore,100,"MLOps, Docker, Java, Spark",PhD,4,Finance,2024-04-19,2024-06-07,2023,8.2,Cognitive Computing +AI12523,Research Scientist,87236,EUR,74151,MI,FL,Germany,M,Germany,100,"Java, Hadoop, Python, Spark, TensorFlow",Associate,3,Technology,2024-02-23,2024-04-13,1927,9.6,DataVision Ltd +AI12524,Head of AI,61002,EUR,51852,EN,PT,Germany,L,Germany,50,"Computer Vision, Kubernetes, Hadoop",Master,1,Media,2024-07-14,2024-07-31,2002,5.9,Advanced Robotics +AI12525,Autonomous Systems Engineer,131108,GBP,98331,MI,FL,United Kingdom,L,United Kingdom,100,"AWS, MLOps, Tableau",PhD,3,Government,2024-02-18,2024-04-21,1902,5.8,TechCorp Inc +AI12526,NLP Engineer,109470,GBP,82103,MI,PT,United Kingdom,L,Egypt,100,"Python, TensorFlow, Statistics",Master,3,Media,2025-03-03,2025-05-01,1242,6.5,Autonomous Tech +AI12527,AI Consultant,63355,GBP,47516,EN,FT,United Kingdom,S,United Kingdom,50,"PyTorch, Linux, Python, Scala",Bachelor,0,Healthcare,2024-07-12,2024-09-09,1354,9.1,DataVision Ltd +AI12528,Data Engineer,199949,EUR,169957,EX,PT,Austria,M,Austria,50,"Git, Spark, GCP",Master,17,Retail,2024-08-30,2024-11-10,1410,8.9,TechCorp Inc +AI12529,Principal Data Scientist,59401,CAD,74251,EN,FL,Canada,S,Portugal,50,"Git, SQL, Scala",PhD,0,Energy,2024-04-27,2024-05-16,2043,9.9,Algorithmic Solutions +AI12530,Head of AI,100922,USD,100922,MI,PT,South Korea,L,South Korea,100,"Python, Git, SQL, Java, Computer Vision",PhD,3,Real Estate,2024-12-21,2025-02-20,2101,8,Machine Intelligence Group +AI12531,Data Analyst,64014,USD,64014,EN,FT,Israel,M,Israel,50,"SQL, PyTorch, Computer Vision, Git",Master,1,Finance,2024-08-01,2024-08-16,2168,8.9,Predictive Systems +AI12532,AI Consultant,164409,AUD,221952,SE,CT,Australia,L,Canada,0,"Kubernetes, PyTorch, Mathematics, SQL, Tableau",Master,6,Gaming,2024-08-30,2024-11-01,2111,7.2,Digital Transformation LLC +AI12533,NLP Engineer,214487,EUR,182314,EX,FL,France,M,France,100,"Kubernetes, SQL, PyTorch",Master,11,Government,2024-09-29,2024-11-04,1748,8.5,Cloud AI Solutions +AI12534,Autonomous Systems Engineer,133642,USD,133642,MI,PT,Norway,L,Norway,100,"Scala, Statistics, Spark",Master,4,Manufacturing,2024-05-25,2024-07-13,850,7.5,Predictive Systems +AI12535,AI Software Engineer,93357,USD,93357,EN,CT,United States,L,United States,0,"Computer Vision, NLP, Tableau, Python",PhD,1,Healthcare,2024-06-28,2024-08-07,1914,7.6,TechCorp Inc +AI12536,Robotics Engineer,68512,USD,68512,SE,FL,China,M,China,0,"Linux, MLOps, AWS, Statistics",PhD,9,Technology,2024-12-11,2025-01-29,1339,8,Algorithmic Solutions +AI12537,AI Specialist,134492,USD,134492,MI,PT,Denmark,M,Denmark,50,"MLOps, GCP, Java, Hadoop",Master,4,Retail,2024-02-21,2024-03-23,2035,5.2,AI Innovations +AI12538,Autonomous Systems Engineer,131311,JPY,14444210,SE,CT,Japan,M,Vietnam,0,"Scala, R, Azure, Git, Kubernetes",Associate,5,Manufacturing,2024-08-10,2024-09-23,1940,8.9,DeepTech Ventures +AI12539,Principal Data Scientist,255914,GBP,191936,EX,PT,United Kingdom,M,South Korea,0,"Git, Kubernetes, NLP",PhD,15,Gaming,2025-01-29,2025-03-25,1748,7.6,Machine Intelligence Group +AI12540,ML Ops Engineer,49654,USD,49654,EN,FT,Ireland,S,Ireland,100,"Scala, Linux, SQL, Statistics",PhD,0,Real Estate,2024-04-14,2024-06-16,2019,7.4,Predictive Systems +AI12541,AI Architect,47136,USD,47136,EN,CT,Israel,S,Israel,0,"PyTorch, SQL, Docker, AWS, Linux",PhD,1,Technology,2024-05-06,2024-06-21,721,9,Quantum Computing Inc +AI12542,AI Research Scientist,42011,USD,42011,MI,FT,India,L,India,50,"Computer Vision, Java, Python, Azure, Git",Master,3,Real Estate,2024-01-15,2024-02-12,1652,8.1,DataVision Ltd +AI12543,AI Consultant,119147,USD,119147,MI,FL,Finland,L,Russia,100,"Java, PyTorch, MLOps, Hadoop, NLP",Associate,4,Consulting,2024-04-21,2024-05-23,1670,7.3,DeepTech Ventures +AI12544,ML Ops Engineer,98976,USD,98976,MI,CT,United States,S,Mexico,50,"Computer Vision, TensorFlow, Python, Git, R",Bachelor,2,Consulting,2024-10-22,2024-12-31,613,6.7,Smart Analytics +AI12545,Autonomous Systems Engineer,50267,EUR,42727,EN,FT,Germany,S,Philippines,100,"Spark, TensorFlow, Kubernetes, Java, Mathematics",Master,1,Real Estate,2025-04-25,2025-05-25,1081,8.6,Machine Intelligence Group +AI12546,Robotics Engineer,26722,USD,26722,EN,FT,China,S,China,0,"Git, SQL, R, GCP",Bachelor,0,Consulting,2024-10-13,2024-11-11,2251,6.1,Digital Transformation LLC +AI12547,ML Ops Engineer,131283,GBP,98462,SE,CT,United Kingdom,M,Thailand,50,"Tableau, TensorFlow, Docker, GCP, Scala",Bachelor,6,Telecommunications,2024-04-07,2024-05-30,2032,8.5,Cognitive Computing +AI12548,AI Product Manager,117952,SGD,153338,SE,FL,Singapore,M,France,50,"MLOps, SQL, Python, Computer Vision",PhD,5,Technology,2024-04-25,2024-06-10,2174,5.7,AI Innovations +AI12549,Deep Learning Engineer,25607,USD,25607,MI,PT,India,M,Ukraine,100,"PyTorch, Linux, Tableau, GCP",Bachelor,2,Media,2024-12-30,2025-01-17,518,6.9,Digital Transformation LLC +AI12550,Deep Learning Engineer,233172,USD,233172,EX,PT,United States,M,Netherlands,50,"SQL, Tableau, Deep Learning, Java",PhD,18,Telecommunications,2024-04-30,2024-06-19,802,6,TechCorp Inc +AI12551,Data Analyst,74780,AUD,100953,EN,PT,Australia,L,Australia,100,"AWS, GCP, Kubernetes",Bachelor,1,Consulting,2025-03-04,2025-03-24,1215,8.9,Quantum Computing Inc +AI12552,AI Research Scientist,166556,CHF,149900,SE,FT,Switzerland,L,Australia,0,"NLP, R, Scala",Bachelor,7,Finance,2024-09-15,2024-10-14,911,7.1,Advanced Robotics +AI12553,AI Research Scientist,332451,USD,332451,EX,CT,United States,L,United States,50,"Spark, Hadoop, PyTorch",Associate,17,Technology,2024-12-15,2025-01-03,1752,8.2,Advanced Robotics +AI12554,Research Scientist,226551,CHF,203896,SE,FL,Switzerland,L,Switzerland,0,"R, Python, Tableau, Deep Learning",Bachelor,9,Retail,2024-02-08,2024-03-21,1144,9,Advanced Robotics +AI12555,AI Consultant,182206,USD,182206,EX,PT,Sweden,M,Sweden,50,"SQL, Java, Tableau, Statistics, PyTorch",Master,18,Media,2024-09-21,2024-11-02,1591,7.5,Machine Intelligence Group +AI12556,AI Consultant,155691,EUR,132337,SE,CT,Austria,L,Brazil,100,"Hadoop, TensorFlow, GCP, Spark",PhD,6,Telecommunications,2025-01-12,2025-02-16,568,7.4,Smart Analytics +AI12557,Machine Learning Researcher,69981,USD,69981,EN,PT,Sweden,S,Sweden,50,"Python, Deep Learning, TensorFlow, Scala",Master,0,Technology,2024-03-27,2024-06-04,809,5.3,Cognitive Computing +AI12558,Computer Vision Engineer,115602,USD,115602,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Git, Tableau, Statistics, Scala",Associate,2,Consulting,2024-07-31,2024-09-20,2388,7.9,Autonomous Tech +AI12559,Data Analyst,65661,GBP,49246,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, NLP, Kubernetes",Associate,1,Automotive,2024-03-10,2024-04-01,2178,6.6,Future Systems +AI12560,ML Ops Engineer,54988,EUR,46740,EN,FL,France,M,France,100,"Hadoop, SQL, Deep Learning",Bachelor,1,Energy,2024-06-20,2024-08-16,904,5.6,Machine Intelligence Group +AI12561,Deep Learning Engineer,255127,GBP,191345,EX,FT,United Kingdom,L,United Kingdom,0,"Git, PyTorch, Java",Associate,13,Healthcare,2024-01-15,2024-03-25,2312,7.5,Quantum Computing Inc +AI12562,NLP Engineer,60129,USD,60129,EN,CT,Finland,L,Finland,50,"AWS, PyTorch, TensorFlow",Associate,0,Real Estate,2024-01-12,2024-03-12,1811,6.7,Smart Analytics +AI12563,NLP Engineer,151050,USD,151050,EX,FT,Finland,M,Romania,100,"Git, PyTorch, Statistics, R",Bachelor,13,Technology,2024-07-08,2024-09-04,1605,7.8,Smart Analytics +AI12564,NLP Engineer,102467,EUR,87097,MI,FL,France,L,France,0,"PyTorch, Hadoop, Deep Learning, Statistics",PhD,3,Healthcare,2024-05-19,2024-07-26,2339,8.1,Future Systems +AI12565,AI Software Engineer,91655,USD,91655,MI,FL,Sweden,M,Sweden,50,"R, Linux, Spark, Scala, Python",Associate,3,Gaming,2024-09-13,2024-11-11,598,9.4,Digital Transformation LLC +AI12566,Machine Learning Engineer,114161,EUR,97037,MI,FT,France,L,France,50,"Java, Python, Spark",Master,2,Government,2024-11-30,2025-01-30,521,9.2,DeepTech Ventures +AI12567,Data Analyst,73257,EUR,62268,MI,CT,Austria,M,Austria,100,"AWS, PyTorch, Spark, Statistics",Bachelor,2,Education,2024-05-28,2024-07-25,1845,9.4,AI Innovations +AI12568,Computer Vision Engineer,108618,USD,108618,MI,FL,Israel,L,Israel,0,"Java, Docker, GCP, R",PhD,3,Finance,2024-01-18,2024-02-22,581,7.5,Predictive Systems +AI12569,AI Specialist,62843,USD,62843,EN,FL,Denmark,S,Denmark,50,"AWS, Azure, Mathematics, Docker, Kubernetes",Bachelor,1,Education,2024-02-23,2024-04-25,2065,6.3,Quantum Computing Inc +AI12570,Research Scientist,178712,EUR,151905,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, NLP, Docker, Spark",Bachelor,8,Finance,2025-02-22,2025-03-23,1151,8.8,Cloud AI Solutions +AI12571,Machine Learning Researcher,66399,USD,66399,EN,FT,Sweden,M,Sweden,0,"Deep Learning, Python, SQL, GCP, Hadoop",Bachelor,0,Consulting,2024-05-05,2024-06-23,1774,6.6,Algorithmic Solutions +AI12572,Deep Learning Engineer,26206,USD,26206,MI,PT,India,S,Australia,50,"PyTorch, Scala, Git, Data Visualization, Spark",Master,4,Gaming,2024-05-02,2024-06-25,2135,9.7,Smart Analytics +AI12573,Autonomous Systems Engineer,132926,CAD,166158,SE,CT,Canada,M,Canada,100,"R, Deep Learning, Hadoop",Bachelor,9,Healthcare,2024-12-05,2025-01-30,779,6.3,Advanced Robotics +AI12574,Machine Learning Researcher,212788,USD,212788,SE,FT,Norway,L,Spain,100,"Python, Statistics, TensorFlow, Tableau",PhD,9,Consulting,2025-02-24,2025-04-01,743,5.6,Algorithmic Solutions +AI12575,AI Specialist,38991,USD,38991,EN,FL,South Korea,S,South Korea,100,"Docker, Python, TensorFlow",Master,1,Telecommunications,2024-07-02,2024-08-15,955,9.8,Machine Intelligence Group +AI12576,AI Product Manager,50232,USD,50232,EN,PT,Israel,S,Israel,100,"Statistics, R, Data Visualization, Tableau, Deep Learning",PhD,1,Manufacturing,2025-01-07,2025-02-06,2141,7.2,Algorithmic Solutions +AI12577,AI Software Engineer,134499,USD,134499,EX,PT,Finland,M,Finland,50,"SQL, NLP, Spark, Python",PhD,13,Real Estate,2024-11-15,2024-12-05,1800,7.2,DataVision Ltd +AI12578,Research Scientist,148779,USD,148779,EX,PT,South Korea,L,South Korea,100,"R, Azure, Tableau, Docker",Associate,17,Telecommunications,2025-04-24,2025-05-20,2101,9.9,Future Systems +AI12579,Principal Data Scientist,70847,USD,70847,EN,FL,Norway,S,Norway,100,"R, Data Visualization, GCP",Associate,1,Energy,2024-10-23,2024-11-13,1102,9.5,Autonomous Tech +AI12580,AI Software Engineer,62204,USD,62204,EN,FT,Ireland,L,New Zealand,0,"AWS, NLP, Kubernetes, R",Associate,0,Manufacturing,2024-10-06,2024-12-09,1579,5.9,Algorithmic Solutions +AI12581,AI Software Engineer,129841,SGD,168793,EX,FT,Singapore,S,Singapore,100,"R, SQL, NLP, Azure, Python",Master,17,Finance,2024-01-01,2024-03-14,591,9.3,DataVision Ltd +AI12582,Data Analyst,155034,EUR,131779,SE,FT,Netherlands,M,Mexico,50,"TensorFlow, Python, MLOps, PyTorch, Tableau",Master,9,Healthcare,2024-11-14,2024-12-31,2353,9.2,Cognitive Computing +AI12583,AI Software Engineer,187509,JPY,20625990,EX,FL,Japan,S,Israel,100,"R, MLOps, Java, Statistics, TensorFlow",Master,15,Automotive,2024-05-13,2024-05-31,2287,9.4,Algorithmic Solutions +AI12584,AI Consultant,177222,EUR,150639,EX,FL,France,M,Colombia,50,"AWS, Git, NLP, Linux",Bachelor,10,Automotive,2025-02-25,2025-04-07,1455,7.7,DataVision Ltd +AI12585,ML Ops Engineer,333553,USD,333553,EX,FL,Norway,L,Norway,100,"TensorFlow, Python, MLOps, Java, R",PhD,17,Healthcare,2025-04-16,2025-06-27,638,9,Predictive Systems +AI12586,AI Product Manager,51703,EUR,43948,EN,PT,Germany,S,Luxembourg,100,"Linux, Docker, Git, R",Associate,1,Retail,2025-02-26,2025-04-15,914,6.4,Future Systems +AI12587,Data Analyst,161634,USD,161634,SE,FL,Israel,L,Israel,50,"Python, Azure, Mathematics",Bachelor,7,Retail,2025-02-22,2025-03-31,2194,7,AI Innovations +AI12588,AI Product Manager,166572,JPY,18322920,SE,FL,Japan,L,Japan,100,"Docker, Java, R, SQL, AWS",PhD,8,Retail,2024-09-17,2024-10-27,2063,9.2,Predictive Systems +AI12589,NLP Engineer,208798,USD,208798,EX,CT,Sweden,L,Indonesia,50,"Kubernetes, Data Visualization, TensorFlow",Master,19,Automotive,2024-12-02,2025-01-28,1995,5.2,AI Innovations +AI12590,Data Analyst,86613,USD,86613,MI,FL,Finland,L,Finland,100,"Git, GCP, Computer Vision, AWS, Hadoop",PhD,2,Manufacturing,2024-11-16,2024-12-04,1178,6.7,Neural Networks Co +AI12591,Machine Learning Engineer,117597,CHF,105837,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, Docker, Java",Bachelor,4,Automotive,2024-03-30,2024-04-20,2021,5.2,Machine Intelligence Group +AI12592,Data Analyst,22513,USD,22513,EN,CT,India,L,India,0,"Deep Learning, GCP, Mathematics, R",Associate,0,Telecommunications,2024-05-05,2024-06-20,1160,7.9,Future Systems +AI12593,Machine Learning Engineer,105654,SGD,137350,MI,CT,Singapore,L,Singapore,0,"Mathematics, Git, Scala, Linux",Bachelor,4,Education,2025-01-15,2025-02-03,938,9.7,Quantum Computing Inc +AI12594,AI Consultant,224641,SGD,292033,EX,FT,Singapore,L,Israel,100,"Linux, Java, Mathematics, Hadoop, SQL",Associate,12,Education,2024-09-20,2024-10-09,1957,6.6,Autonomous Tech +AI12595,Computer Vision Engineer,92817,USD,92817,MI,CT,Denmark,S,Denmark,100,"PyTorch, Linux, TensorFlow, R, Mathematics",Associate,4,Finance,2024-06-05,2024-06-23,1419,8.8,Neural Networks Co +AI12596,Deep Learning Engineer,87012,EUR,73960,EN,PT,Austria,L,Austria,100,"Linux, PyTorch, Computer Vision",Bachelor,1,Retail,2025-01-26,2025-02-20,2106,9.6,Autonomous Tech +AI12597,AI Product Manager,176978,USD,176978,EX,PT,Finland,S,New Zealand,100,"Hadoop, Docker, Linux",PhD,19,Automotive,2024-07-11,2024-08-06,776,8.9,Digital Transformation LLC +AI12598,AI Software Engineer,31871,USD,31871,MI,CT,India,L,India,0,"Statistics, Mathematics, TensorFlow",Associate,4,Transportation,2024-04-08,2024-06-08,905,7.7,Future Systems +AI12599,Data Engineer,111513,USD,111513,MI,FL,United States,S,Finland,0,"Kubernetes, Azure, Deep Learning, Data Visualization, SQL",Associate,3,Healthcare,2024-06-09,2024-06-23,901,7.5,AI Innovations +AI12600,Data Scientist,124502,EUR,105827,SE,CT,Austria,M,Austria,100,"Linux, Tableau, Python, Computer Vision, TensorFlow",Master,7,Retail,2024-03-07,2024-03-30,1777,6,DeepTech Ventures +AI12601,AI Architect,143750,EUR,122188,SE,CT,France,M,Brazil,50,"Java, AWS, Git",PhD,9,Finance,2024-06-10,2024-07-15,1569,9.6,Predictive Systems +AI12602,Deep Learning Engineer,107546,EUR,91414,SE,PT,Germany,M,Czech Republic,0,"Tableau, Python, PyTorch",Master,9,Finance,2025-02-20,2025-04-09,641,8.7,Quantum Computing Inc +AI12603,Research Scientist,208493,EUR,177219,EX,FL,Germany,L,Germany,100,"R, SQL, PyTorch",PhD,19,Manufacturing,2024-10-07,2024-11-03,615,6.4,AI Innovations +AI12604,Computer Vision Engineer,290203,USD,290203,EX,CT,Norway,M,Norway,100,"GCP, Python, SQL",Bachelor,18,Real Estate,2024-10-06,2024-11-20,1734,5.3,Autonomous Tech +AI12605,AI Product Manager,79948,USD,79948,MI,CT,Ireland,S,Israel,100,"Scala, Kubernetes, Computer Vision, Tableau, Docker",Bachelor,4,Healthcare,2025-02-15,2025-03-30,1869,9,AI Innovations +AI12606,AI Research Scientist,139049,CHF,125144,MI,FL,Switzerland,M,Canada,50,"Scala, Java, TensorFlow, Tableau",Master,3,Healthcare,2024-02-23,2024-04-12,1656,6.1,DeepTech Ventures +AI12607,NLP Engineer,123828,USD,123828,MI,FL,United States,L,Belgium,100,"Spark, Azure, MLOps, R, GCP",Bachelor,4,Automotive,2025-04-13,2025-05-20,1675,5.3,Quantum Computing Inc +AI12608,Research Scientist,125635,USD,125635,MI,PT,Norway,L,Norway,100,"PyTorch, Tableau, SQL, NLP",Master,4,Government,2024-07-30,2024-08-27,681,7.2,Neural Networks Co +AI12609,Data Scientist,102852,USD,102852,MI,PT,United States,S,United States,100,"Scala, Linux, Python, AWS",Associate,2,Automotive,2024-06-14,2024-07-13,1842,9.2,Smart Analytics +AI12610,Autonomous Systems Engineer,126788,EUR,107770,SE,CT,France,S,France,100,"Tableau, Computer Vision, Kubernetes, R",Bachelor,9,Government,2024-03-12,2024-04-21,1769,9,Smart Analytics +AI12611,Research Scientist,140019,GBP,105014,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, TensorFlow, Hadoop",PhD,15,Consulting,2024-04-05,2024-06-17,1104,7.8,Cloud AI Solutions +AI12612,ML Ops Engineer,225786,JPY,24836460,EX,FL,Japan,M,Japan,100,"Git, Kubernetes, Computer Vision, Python, Deep Learning",Master,13,Gaming,2024-09-03,2024-11-04,859,9.1,Algorithmic Solutions +AI12613,Principal Data Scientist,126761,EUR,107747,SE,FL,Austria,S,Austria,0,"Java, Kubernetes, Python, Computer Vision, TensorFlow",Associate,9,Energy,2024-08-23,2024-09-20,1014,8.6,DeepTech Ventures +AI12614,AI Specialist,97895,USD,97895,SE,FT,Israel,S,Israel,0,"Python, Scala, Docker, Azure, Deep Learning",Master,6,Transportation,2024-05-06,2024-06-24,1202,5.6,Neural Networks Co +AI12615,AI Architect,234625,EUR,199431,EX,PT,Netherlands,L,Norway,50,"Git, Python, NLP, TensorFlow, AWS",Bachelor,15,Healthcare,2024-09-17,2024-11-25,1955,6.4,Quantum Computing Inc +AI12616,Data Engineer,118185,GBP,88639,SE,PT,United Kingdom,M,Germany,100,"Computer Vision, Git, Hadoop, Java",Associate,8,Gaming,2025-01-17,2025-02-13,1198,9.1,Advanced Robotics +AI12617,Deep Learning Engineer,66948,USD,66948,EN,FL,Denmark,S,Denmark,100,"Deep Learning, Scala, Data Visualization",Master,0,Healthcare,2024-09-27,2024-11-26,1683,5.1,Digital Transformation LLC +AI12618,Autonomous Systems Engineer,64481,EUR,54809,EN,FL,France,S,Mexico,100,"Python, Hadoop, GCP",PhD,1,Consulting,2024-05-02,2024-05-22,1179,6.6,Future Systems +AI12619,Research Scientist,153732,CHF,138359,MI,FT,Switzerland,L,Switzerland,0,"MLOps, Spark, Scala, Java, Azure",PhD,3,Consulting,2025-03-10,2025-05-03,789,6.4,Algorithmic Solutions +AI12620,Computer Vision Engineer,130492,USD,130492,SE,FT,Ireland,S,Egypt,50,"Python, Data Visualization, Kubernetes",Associate,8,Education,2024-02-16,2024-03-26,1900,7.4,Neural Networks Co +AI12621,NLP Engineer,116529,USD,116529,MI,FT,Sweden,L,Sweden,50,"SQL, MLOps, Computer Vision, Data Visualization",Bachelor,2,Gaming,2024-12-12,2025-01-19,926,6.1,Algorithmic Solutions +AI12622,Autonomous Systems Engineer,125193,AUD,169011,SE,FT,Australia,L,Australia,100,"AWS, Java, Docker",Bachelor,6,Government,2025-03-21,2025-05-16,1239,7.8,Smart Analytics +AI12623,ML Ops Engineer,153136,EUR,130166,SE,PT,Netherlands,L,Netherlands,0,"Python, Kubernetes, Mathematics, Data Visualization, AWS",Associate,9,Media,2024-08-28,2024-11-01,1464,7.7,Advanced Robotics +AI12624,Data Analyst,174479,USD,174479,EX,FT,United States,S,United States,50,"Python, Hadoop, Linux, Tableau, Computer Vision",Bachelor,12,Government,2024-01-24,2024-03-18,2121,7.5,Machine Intelligence Group +AI12625,Machine Learning Researcher,137316,AUD,185377,SE,PT,Australia,M,Austria,50,"Deep Learning, Spark, AWS, Azure",Bachelor,8,Gaming,2024-05-04,2024-06-13,2081,9.3,DeepTech Ventures +AI12626,Deep Learning Engineer,160330,USD,160330,SE,FL,Norway,S,Norway,100,"R, Statistics, Scala, AWS, Computer Vision",Bachelor,7,Government,2024-04-05,2024-05-14,1371,5.6,TechCorp Inc +AI12627,AI Architect,41342,USD,41342,MI,FL,China,L,Denmark,100,"Python, Git, Scala, GCP, Kubernetes",Bachelor,3,Education,2025-03-18,2025-05-15,1068,6.3,DataVision Ltd +AI12628,Autonomous Systems Engineer,31869,USD,31869,EN,CT,China,S,China,100,"SQL, Linux, PyTorch, GCP, R",Associate,1,Education,2024-11-11,2025-01-20,2218,5.2,Cloud AI Solutions +AI12629,Autonomous Systems Engineer,190329,USD,190329,SE,FL,United States,L,Ghana,0,"R, Python, Docker, SQL",PhD,5,Media,2024-05-18,2024-06-04,615,8,DataVision Ltd +AI12630,Research Scientist,80831,USD,80831,EN,FT,Finland,L,Finland,50,"Git, R, MLOps",Bachelor,1,Gaming,2024-07-01,2024-07-20,1907,7.2,Cloud AI Solutions +AI12631,AI Product Manager,102054,USD,102054,SE,FT,Sweden,S,Sweden,100,"Docker, Linux, MLOps, SQL, Deep Learning",Bachelor,7,Media,2025-03-22,2025-04-19,1223,9.2,Future Systems +AI12632,Computer Vision Engineer,198047,USD,198047,EX,PT,South Korea,M,South Korea,100,"Kubernetes, Tableau, Python",Bachelor,12,Healthcare,2024-05-27,2024-07-15,1391,6.6,Predictive Systems +AI12633,NLP Engineer,70324,USD,70324,EN,CT,United States,M,United States,0,"Linux, Docker, PyTorch, Spark",Master,0,Education,2024-03-24,2024-06-02,578,9.9,Future Systems +AI12634,AI Consultant,61593,USD,61593,EN,FL,Ireland,M,Ireland,0,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-07-15,2024-08-30,2459,7.4,Smart Analytics +AI12635,NLP Engineer,225178,EUR,191401,EX,FL,Austria,M,Austria,100,"Python, Data Visualization, Tableau, Java",Master,17,Healthcare,2024-07-10,2024-08-13,1008,7.2,Algorithmic Solutions +AI12636,Machine Learning Engineer,119102,CAD,148878,SE,FL,Canada,M,Canada,50,"Statistics, Linux, Python, Java, Scala",PhD,9,Telecommunications,2025-03-13,2025-05-11,687,8.1,Smart Analytics +AI12637,AI Architect,188552,USD,188552,EX,CT,Finland,S,Finland,0,"Docker, Computer Vision, Python",Associate,10,Automotive,2025-04-16,2025-05-28,1801,7.3,Algorithmic Solutions +AI12638,Head of AI,226063,CHF,203457,SE,CT,Switzerland,L,Romania,0,"Scala, Hadoop, Deep Learning",Master,5,Technology,2025-02-23,2025-04-07,1020,5.1,DataVision Ltd +AI12639,AI Product Manager,62015,USD,62015,MI,CT,Israel,S,Israel,50,"Python, Scala, PyTorch, Statistics",PhD,3,Technology,2024-11-08,2024-12-28,1879,9.2,Cognitive Computing +AI12640,Computer Vision Engineer,93014,CAD,116268,MI,FT,Canada,M,Canada,0,"MLOps, SQL, PyTorch, Mathematics",PhD,3,Energy,2024-10-12,2024-11-05,1673,8.5,Cloud AI Solutions +AI12641,Machine Learning Researcher,128718,SGD,167333,SE,PT,Singapore,M,Singapore,50,"Mathematics, Hadoop, AWS, Statistics",Associate,7,Manufacturing,2024-12-15,2025-02-03,669,9.6,Autonomous Tech +AI12642,Data Engineer,66805,EUR,56784,EN,CT,Austria,M,Italy,0,"Spark, Git, Deep Learning, Statistics",Associate,1,Real Estate,2024-01-23,2024-02-23,554,5.2,Autonomous Tech +AI12643,ML Ops Engineer,90978,USD,90978,EN,FT,Norway,S,Norway,50,"Python, AWS, Data Visualization, Spark, MLOps",Bachelor,1,Finance,2024-06-14,2024-08-04,2462,8.6,Advanced Robotics +AI12644,Data Scientist,139567,USD,139567,SE,PT,Ireland,L,Ireland,0,"PyTorch, Azure, Docker, GCP",Associate,5,Healthcare,2024-11-17,2024-12-05,1020,9.1,Neural Networks Co +AI12645,Machine Learning Engineer,133001,USD,133001,MI,FL,Denmark,M,Denmark,100,"Git, Linux, Python",Master,3,Healthcare,2024-04-02,2024-06-01,731,7.5,Advanced Robotics +AI12646,AI Product Manager,117366,EUR,99761,SE,FT,Netherlands,S,Netherlands,100,"Statistics, TensorFlow, AWS",Bachelor,5,Retail,2025-02-07,2025-03-23,1523,8.1,Quantum Computing Inc +AI12647,Machine Learning Engineer,56948,USD,56948,EN,PT,South Korea,S,South Korea,100,"Statistics, SQL, Scala, PyTorch, Git",Associate,1,Retail,2025-04-04,2025-05-18,2302,7.3,Digital Transformation LLC +AI12648,AI Product Manager,271210,SGD,352573,EX,PT,Singapore,L,Switzerland,100,"Computer Vision, Scala, SQL, PyTorch, R",Master,11,Media,2024-06-23,2024-07-15,583,9.2,Cloud AI Solutions +AI12649,NLP Engineer,108474,EUR,92203,MI,CT,France,L,Australia,0,"Git, SQL, Tableau, Deep Learning",Master,3,Government,2024-10-09,2024-11-12,966,7.2,TechCorp Inc +AI12650,Data Engineer,74225,USD,74225,MI,PT,Ireland,M,Ireland,0,"PyTorch, Statistics, Docker, Kubernetes",Associate,2,Education,2024-08-21,2024-10-13,1353,8.7,DataVision Ltd +AI12651,AI Research Scientist,97911,CAD,122389,SE,PT,Canada,S,Canada,0,"SQL, R, Tableau, Kubernetes",Master,9,Education,2024-02-28,2024-03-31,2122,9.1,Cognitive Computing +AI12652,Deep Learning Engineer,87471,USD,87471,MI,PT,Finland,L,Finland,50,"Git, Azure, Statistics",Master,3,Technology,2024-06-05,2024-06-19,831,5.3,Digital Transformation LLC +AI12653,AI Consultant,66358,USD,66358,MI,FL,South Korea,M,Poland,0,"Kubernetes, Deep Learning, Python, Data Visualization, Mathematics",Master,3,Transportation,2024-05-18,2024-07-25,1793,8.5,Predictive Systems +AI12654,AI Research Scientist,67502,USD,67502,EN,CT,Ireland,L,Ireland,50,"Statistics, Docker, Python, Hadoop, Git",Associate,0,Healthcare,2024-01-09,2024-01-30,2491,7,Cognitive Computing +AI12655,AI Architect,84581,USD,84581,MI,FL,Ireland,M,Ireland,50,"Linux, Java, R",PhD,2,Energy,2024-10-10,2024-12-21,1998,10,Machine Intelligence Group +AI12656,Autonomous Systems Engineer,94615,USD,94615,EN,FT,United States,M,United States,0,"PyTorch, Scala, Linux",Associate,0,Consulting,2024-09-20,2024-11-27,2355,5.3,Algorithmic Solutions +AI12657,Computer Vision Engineer,126277,EUR,107335,SE,FL,Netherlands,S,Philippines,100,"Python, TensorFlow, Tableau, Azure, Statistics",Master,9,Manufacturing,2025-03-28,2025-05-13,1919,6.5,Smart Analytics +AI12658,Autonomous Systems Engineer,108046,EUR,91839,MI,FT,Netherlands,M,Netherlands,100,"Deep Learning, AWS, Hadoop",Master,4,Consulting,2024-10-22,2024-12-19,2301,9.5,Predictive Systems +AI12659,Machine Learning Researcher,214302,EUR,182157,EX,FT,Netherlands,S,Netherlands,50,"Spark, Docker, Data Visualization, NLP",Associate,16,Retail,2025-04-23,2025-05-19,1213,8.9,Predictive Systems +AI12660,Head of AI,60614,USD,60614,EN,FL,Finland,S,Portugal,100,"Linux, Docker, MLOps",PhD,0,Education,2024-02-24,2024-04-28,2024,7,Advanced Robotics +AI12661,Robotics Engineer,126247,SGD,164121,SE,FT,Singapore,S,Singapore,100,"PyTorch, Python, Docker",Master,8,Finance,2024-10-11,2024-11-08,1708,6.3,Smart Analytics +AI12662,Research Scientist,153207,USD,153207,SE,CT,Denmark,S,Denmark,0,"Python, Java, Git",Bachelor,9,Transportation,2024-11-07,2025-01-02,1270,5.6,DataVision Ltd +AI12663,NLP Engineer,91093,EUR,77429,MI,CT,Austria,M,Austria,0,"Deep Learning, Mathematics, Java, Spark, NLP",PhD,4,Technology,2024-06-13,2024-08-02,1465,7.1,Advanced Robotics +AI12664,Data Analyst,177639,USD,177639,EX,FL,Denmark,S,Denmark,100,"Deep Learning, Linux, Kubernetes",PhD,13,Real Estate,2024-11-11,2024-12-28,1835,7.9,Neural Networks Co +AI12665,AI Architect,72729,EUR,61820,EN,PT,Netherlands,M,Netherlands,50,"Docker, Kubernetes, Scala, Git, Mathematics",Bachelor,1,Real Estate,2024-08-17,2024-09-07,1687,5.5,Predictive Systems +AI12666,ML Ops Engineer,231764,EUR,196999,EX,PT,Netherlands,S,South Korea,50,"Kubernetes, Spark, Scala, Data Visualization",Master,14,Manufacturing,2024-07-28,2024-08-25,1535,7.3,Cloud AI Solutions +AI12667,Robotics Engineer,91852,USD,91852,MI,FT,Israel,M,South Korea,50,"Deep Learning, TensorFlow, Azure",Bachelor,2,Energy,2024-02-09,2024-02-27,876,6.7,Smart Analytics +AI12668,Data Scientist,108220,USD,108220,EN,CT,Denmark,L,Ukraine,50,"Tableau, Computer Vision, AWS, Git",PhD,1,Finance,2024-12-09,2025-02-12,2251,8.5,Smart Analytics +AI12669,NLP Engineer,44513,USD,44513,EN,FL,Israel,S,Israel,100,"Scala, Azure, Statistics",Master,0,Education,2024-01-27,2024-02-16,1799,6.1,Quantum Computing Inc +AI12670,Autonomous Systems Engineer,115978,USD,115978,MI,PT,Finland,L,Germany,50,"Azure, Spark, Mathematics, Java",PhD,4,Government,2024-08-19,2024-10-25,2133,8,DeepTech Ventures +AI12671,AI Architect,60623,USD,60623,EN,FT,Ireland,L,Ireland,0,"Git, Python, TensorFlow, GCP, Linux",Associate,0,Manufacturing,2024-05-10,2024-06-12,1778,8.5,AI Innovations +AI12672,Machine Learning Researcher,193676,USD,193676,SE,FT,Denmark,M,Denmark,100,"Docker, Mathematics, Python",Associate,6,Technology,2024-03-05,2024-05-13,1107,6.2,Cloud AI Solutions +AI12673,Computer Vision Engineer,101827,USD,101827,MI,CT,Norway,S,Norway,100,"Kubernetes, Git, Deep Learning, Python",Bachelor,2,Real Estate,2025-03-06,2025-05-05,1206,9.4,Autonomous Tech +AI12674,AI Consultant,90586,SGD,117762,EN,FT,Singapore,L,Hungary,0,"Statistics, AWS, Python",PhD,0,Real Estate,2024-01-22,2024-03-16,1090,5.1,Cognitive Computing +AI12675,AI Specialist,194601,CAD,243251,EX,PT,Canada,M,Canada,50,"SQL, Kubernetes, GCP",PhD,11,Transportation,2024-09-21,2024-10-16,1795,5.7,Future Systems +AI12676,Data Engineer,382222,CHF,344000,EX,FL,Switzerland,L,Thailand,50,"R, PyTorch, Java, GCP, Deep Learning",Associate,15,Government,2024-05-24,2024-08-04,674,9.9,Algorithmic Solutions +AI12677,AI Specialist,111690,CAD,139613,SE,CT,Canada,L,Canada,100,"Git, Python, Spark",Master,5,Transportation,2024-04-04,2024-05-23,1034,6.3,Future Systems +AI12678,Machine Learning Researcher,74807,EUR,63586,MI,CT,France,S,France,100,"Scala, Python, Mathematics, GCP, Linux",Bachelor,3,Automotive,2024-09-19,2024-11-05,2286,8.2,Predictive Systems +AI12679,Machine Learning Researcher,68533,AUD,92520,EN,FT,Australia,S,Colombia,100,"GCP, R, Linux, Mathematics, Java",PhD,0,Gaming,2024-08-14,2024-10-10,1038,7.9,Quantum Computing Inc +AI12680,Robotics Engineer,130226,EUR,110692,SE,CT,Netherlands,L,Netherlands,100,"PyTorch, Docker, TensorFlow, Java, AWS",Bachelor,5,Healthcare,2024-05-24,2024-06-22,513,5.1,Future Systems +AI12681,AI Specialist,112790,GBP,84593,MI,PT,United Kingdom,L,United Kingdom,50,"TensorFlow, Java, Tableau, Computer Vision, R",Associate,4,Manufacturing,2025-02-28,2025-04-25,1695,6,Cloud AI Solutions +AI12682,Data Scientist,189996,CAD,237495,EX,PT,Canada,L,France,100,"Python, Azure, Scala, Statistics, PyTorch",Associate,11,Retail,2024-12-15,2025-01-28,1151,9.4,DataVision Ltd +AI12683,AI Research Scientist,114387,USD,114387,MI,CT,Norway,M,Norway,50,"Tableau, Spark, Linux, Python",PhD,4,Media,2024-06-10,2024-07-15,640,6.5,Autonomous Tech +AI12684,Machine Learning Engineer,185728,CHF,167155,SE,FL,Switzerland,S,Switzerland,50,"Spark, Java, Scala, AWS",PhD,7,Technology,2024-01-25,2024-02-08,2147,8.7,AI Innovations +AI12685,Computer Vision Engineer,142898,EUR,121463,EX,PT,France,M,France,50,"SQL, Hadoop, Scala",PhD,16,Real Estate,2024-07-13,2024-08-14,1190,9.6,TechCorp Inc +AI12686,Autonomous Systems Engineer,84890,USD,84890,EN,FT,Finland,L,Finland,100,"Kubernetes, Python, Git",Associate,1,Retail,2024-08-01,2024-09-07,772,8.7,AI Innovations +AI12687,Machine Learning Researcher,95220,JPY,10474200,EN,CT,Japan,L,Luxembourg,0,"Scala, Spark, NLP, Tableau",Associate,1,Technology,2025-03-11,2025-04-23,536,9.8,Neural Networks Co +AI12688,Machine Learning Engineer,73529,USD,73529,EN,FT,Norway,M,Russia,0,"Linux, Data Visualization, Spark, SQL",Bachelor,0,Consulting,2024-12-10,2025-01-27,979,9,Advanced Robotics +AI12689,AI Specialist,96565,EUR,82080,MI,FT,Netherlands,S,Netherlands,100,"Python, SQL, PyTorch, Deep Learning",Bachelor,4,Technology,2025-04-05,2025-05-14,713,9.1,Quantum Computing Inc +AI12690,AI Research Scientist,81266,USD,81266,EN,PT,Israel,L,Israel,100,"GCP, Kubernetes, Java, Python, SQL",Master,1,Consulting,2024-01-20,2024-03-02,2055,7.2,Cloud AI Solutions +AI12691,Deep Learning Engineer,120489,CAD,150611,SE,FL,Canada,L,Canada,100,"GCP, Linux, R, SQL",Master,8,Retail,2024-07-17,2024-09-15,1009,9.3,TechCorp Inc +AI12692,ML Ops Engineer,160293,SGD,208381,SE,CT,Singapore,L,Chile,100,"Docker, Deep Learning, NLP, PyTorch, Scala",Associate,7,Transportation,2024-04-29,2024-07-11,2163,6.5,DataVision Ltd +AI12693,Research Scientist,259694,CAD,324618,EX,FL,Canada,L,Canada,100,"R, Deep Learning, Mathematics, Statistics",Bachelor,16,Healthcare,2025-02-20,2025-04-04,2352,6.2,TechCorp Inc +AI12694,NLP Engineer,134216,AUD,181192,SE,PT,Australia,M,Ghana,50,"Linux, Spark, MLOps, PyTorch",Associate,7,Government,2025-01-05,2025-03-15,1073,5.1,DeepTech Ventures +AI12695,Machine Learning Engineer,70756,USD,70756,MI,FL,South Korea,M,South Korea,50,"Linux, Scala, Mathematics",PhD,3,Healthcare,2024-06-09,2024-08-01,1480,8.6,DataVision Ltd +AI12696,AI Software Engineer,74648,USD,74648,MI,CT,Israel,M,Israel,50,"Scala, Tableau, R, SQL",Associate,2,Healthcare,2024-08-05,2024-09-18,581,5.5,TechCorp Inc +AI12697,Deep Learning Engineer,62208,EUR,52877,EN,FT,France,M,Singapore,100,"Java, Scala, MLOps, NLP, TensorFlow",Bachelor,0,Technology,2024-02-06,2024-04-03,1324,9.7,Cognitive Computing +AI12698,AI Research Scientist,127798,USD,127798,SE,PT,Ireland,M,Ireland,0,"Kubernetes, Scala, MLOps",Associate,6,Government,2024-12-16,2025-02-18,2486,9.1,Machine Intelligence Group +AI12699,Research Scientist,44314,USD,44314,MI,FT,China,L,China,0,"Statistics, R, Git, Computer Vision",Bachelor,3,Transportation,2024-03-22,2024-04-18,2342,5.3,Autonomous Tech +AI12700,Machine Learning Researcher,112441,USD,112441,SE,FT,Sweden,S,Sweden,100,"Scala, Azure, NLP, Deep Learning",Master,5,Finance,2025-01-16,2025-02-24,1319,9.8,Cloud AI Solutions +AI12701,AI Architect,67815,EUR,57643,EN,PT,Netherlands,S,United States,0,"Statistics, Docker, R, GCP",Associate,0,Technology,2024-01-16,2024-02-19,1170,9.4,Advanced Robotics +AI12702,AI Software Engineer,116101,USD,116101,MI,FT,Norway,L,Norway,50,"MLOps, Python, Data Visualization, NLP, TensorFlow",Master,4,Manufacturing,2024-07-11,2024-08-14,527,6.6,DeepTech Ventures +AI12703,AI Software Engineer,142224,EUR,120890,EX,PT,Germany,M,Germany,50,"Data Visualization, MLOps, R, Spark",Associate,15,Transportation,2024-08-17,2024-09-12,1792,5.2,Cloud AI Solutions +AI12704,Data Engineer,122247,USD,122247,SE,PT,United States,M,United States,50,"SQL, PyTorch, MLOps, Java, TensorFlow",Master,5,Healthcare,2024-02-18,2024-04-16,507,6.7,Algorithmic Solutions +AI12705,Data Analyst,68996,USD,68996,SE,PT,China,L,China,100,"SQL, Linux, GCP",Bachelor,5,Energy,2024-06-10,2024-07-22,1239,5.9,Cloud AI Solutions +AI12706,AI Research Scientist,58278,GBP,43709,EN,CT,United Kingdom,S,Norway,100,"TensorFlow, Kubernetes, Linux, Tableau",Associate,1,Retail,2024-08-16,2024-09-16,1495,8.6,Digital Transformation LLC +AI12707,AI Product Manager,161500,AUD,218025,SE,CT,Australia,L,Colombia,100,"Kubernetes, R, SQL",Associate,8,Technology,2024-11-14,2025-01-07,1847,8.2,TechCorp Inc +AI12708,Data Analyst,97036,USD,97036,EN,PT,Denmark,L,United Kingdom,0,"Python, NLP, Docker",PhD,0,Transportation,2024-12-20,2025-02-20,1466,6.7,Smart Analytics +AI12709,AI Product Manager,97890,USD,97890,MI,PT,Finland,L,Finland,100,"Statistics, Mathematics, Deep Learning, Linux",PhD,2,Media,2024-09-14,2024-10-07,1422,9.9,DataVision Ltd +AI12710,AI Product Manager,192865,EUR,163935,EX,CT,France,L,France,0,"SQL, Statistics, Mathematics, NLP",Associate,11,Manufacturing,2024-07-12,2024-09-07,1150,9.7,DeepTech Ventures +AI12711,Computer Vision Engineer,19662,USD,19662,EN,FL,India,M,India,0,"Linux, AWS, SQL, Data Visualization",Master,1,Manufacturing,2024-01-08,2024-02-15,2190,8.7,Algorithmic Solutions +AI12712,Research Scientist,95674,USD,95674,SE,CT,Sweden,S,Czech Republic,0,"NLP, Git, Kubernetes, Azure, AWS",PhD,7,Finance,2024-08-24,2024-09-16,855,8.1,Autonomous Tech +AI12713,Head of AI,83952,EUR,71359,EN,CT,Netherlands,L,Netherlands,50,"Statistics, R, Azure, GCP",Bachelor,1,Healthcare,2025-01-22,2025-03-12,798,8.3,Neural Networks Co +AI12714,Autonomous Systems Engineer,70247,USD,70247,EN,PT,Ireland,S,Ireland,0,"Spark, Tableau, Azure",Associate,1,Gaming,2025-02-10,2025-04-16,2099,7.3,Cloud AI Solutions +AI12715,Computer Vision Engineer,194385,GBP,145789,EX,FL,United Kingdom,S,Poland,50,"Python, Tableau, AWS, Azure",Bachelor,14,Transportation,2025-04-07,2025-05-11,1896,8.8,Autonomous Tech +AI12716,Machine Learning Researcher,50464,USD,50464,MI,FT,China,M,China,100,"NLP, Python, Kubernetes, Docker",Associate,2,Telecommunications,2024-11-11,2024-12-17,792,5.9,Neural Networks Co +AI12717,AI Architect,71270,EUR,60580,EN,FL,Netherlands,S,Netherlands,0,"GCP, Linux, MLOps",Bachelor,0,Energy,2024-03-05,2024-03-28,2402,6.4,Autonomous Tech +AI12718,AI Specialist,243177,AUD,328289,EX,FT,Australia,M,Australia,50,"Mathematics, Python, SQL",Bachelor,12,Automotive,2024-11-04,2024-11-26,1744,9.4,Cloud AI Solutions +AI12719,Data Scientist,239543,EUR,203612,EX,FL,Austria,M,India,0,"MLOps, SQL, Deep Learning, Kubernetes",Bachelor,15,Manufacturing,2025-01-08,2025-03-18,2258,6.6,Cognitive Computing +AI12720,Machine Learning Engineer,53499,USD,53499,EN,PT,South Korea,S,South Korea,0,"Data Visualization, AWS, Mathematics, Tableau, Deep Learning",Master,1,Energy,2025-04-03,2025-05-08,1026,5.8,Advanced Robotics +AI12721,Computer Vision Engineer,150607,USD,150607,EX,FT,Israel,M,Israel,50,"R, SQL, PyTorch",Associate,18,Government,2024-01-27,2024-04-08,2485,5.7,Cognitive Computing +AI12722,AI Specialist,79623,USD,79623,EN,FL,United States,L,Australia,0,"Computer Vision, Tableau, Kubernetes, Linux",Master,1,Transportation,2024-06-12,2024-08-09,1144,7.7,Autonomous Tech +AI12723,AI Architect,81308,USD,81308,EN,PT,United States,L,United States,50,"R, Python, Tableau",Associate,0,Media,2025-02-23,2025-03-09,749,6.6,Cloud AI Solutions +AI12724,Head of AI,123946,AUD,167327,SE,FT,Australia,S,Australia,100,"Tableau, Data Visualization, Mathematics",PhD,9,Government,2024-01-19,2024-03-29,2481,8.6,Digital Transformation LLC +AI12725,ML Ops Engineer,42381,USD,42381,SE,CT,India,S,Romania,0,"Python, NLP, Azure, TensorFlow",Associate,9,Retail,2025-01-24,2025-03-22,1466,5.4,Autonomous Tech +AI12726,Data Analyst,35803,USD,35803,MI,CT,China,S,China,0,"Git, TensorFlow, Python, AWS, Kubernetes",Associate,4,Education,2024-06-04,2024-07-16,2091,6.4,Algorithmic Solutions +AI12727,Data Analyst,126100,EUR,107185,SE,FT,Netherlands,L,Netherlands,50,"PyTorch, Tableau, Hadoop, Kubernetes",Bachelor,7,Government,2024-04-10,2024-05-24,2184,7.4,Digital Transformation LLC +AI12728,NLP Engineer,138184,USD,138184,SE,FT,Norway,M,Norway,100,"PyTorch, Hadoop, MLOps, Azure",Master,9,Gaming,2025-03-30,2025-04-25,516,5.2,Algorithmic Solutions +AI12729,AI Architect,38303,USD,38303,MI,FT,India,M,India,50,"Python, TensorFlow, Docker, Mathematics, Hadoop",Master,3,Telecommunications,2024-07-21,2024-08-27,1857,7.1,Neural Networks Co +AI12730,Autonomous Systems Engineer,41682,USD,41682,MI,PT,India,L,India,0,"Python, SQL, Mathematics",Bachelor,4,Manufacturing,2024-08-04,2024-10-16,2045,6.4,Algorithmic Solutions +AI12731,AI Specialist,255802,USD,255802,EX,PT,Israel,L,Romania,100,"Hadoop, Git, GCP, Computer Vision",Associate,12,Telecommunications,2024-04-20,2024-05-05,1123,9.5,Cloud AI Solutions +AI12732,Machine Learning Researcher,80108,CAD,100135,MI,PT,Canada,L,Canada,0,"Kubernetes, Docker, R, Linux, Statistics",Master,3,Telecommunications,2025-03-07,2025-04-06,1393,6.1,Quantum Computing Inc +AI12733,Autonomous Systems Engineer,60460,CAD,75575,EN,PT,Canada,M,Canada,100,"Java, Kubernetes, Data Visualization",PhD,1,Energy,2024-09-25,2024-12-03,1853,10,DataVision Ltd +AI12734,Principal Data Scientist,110481,USD,110481,SE,PT,Sweden,S,Sweden,100,"Kubernetes, Hadoop, Data Visualization, Scala, Java",Bachelor,6,Technology,2024-01-30,2024-03-10,1762,9.4,Digital Transformation LLC +AI12735,AI Research Scientist,181707,EUR,154451,EX,PT,Germany,L,Germany,50,"MLOps, Linux, Hadoop",Bachelor,17,Automotive,2024-07-29,2024-08-19,500,9.7,Autonomous Tech +AI12736,AI Architect,171315,CAD,214144,EX,CT,Canada,S,Colombia,100,"SQL, Java, PyTorch",Bachelor,18,Consulting,2025-01-14,2025-02-22,2115,6,AI Innovations +AI12737,Machine Learning Researcher,186907,EUR,158871,EX,PT,France,S,France,0,"NLP, Hadoop, SQL, Statistics, R",Master,12,Real Estate,2025-04-10,2025-05-12,952,9.4,Cloud AI Solutions +AI12738,Computer Vision Engineer,197246,GBP,147935,EX,FL,United Kingdom,S,United Kingdom,50,"SQL, TensorFlow, Linux, Java",PhD,12,Technology,2024-12-10,2024-12-31,2123,6.2,Future Systems +AI12739,AI Research Scientist,62903,AUD,84919,EN,FL,Australia,M,Australia,0,"Python, Tableau, Scala",Bachelor,0,Media,2024-10-09,2024-12-06,834,6.6,Autonomous Tech +AI12740,Robotics Engineer,168184,CAD,210230,EX,PT,Canada,L,Canada,0,"Hadoop, Mathematics, Spark, Computer Vision, Python",Bachelor,10,Finance,2024-04-05,2024-05-31,2000,5.3,Smart Analytics +AI12741,AI Software Engineer,147859,CAD,184824,EX,FL,Canada,M,Germany,100,"SQL, Tableau, Statistics, Linux, Mathematics",Master,10,Gaming,2024-11-02,2025-01-09,858,8.9,Neural Networks Co +AI12742,Machine Learning Researcher,87226,EUR,74142,MI,FT,Netherlands,S,Romania,50,"Azure, R, SQL, AWS",PhD,2,Education,2024-08-09,2024-09-21,1357,5.7,Predictive Systems +AI12743,Machine Learning Engineer,138319,EUR,117571,SE,FL,France,L,France,0,"Computer Vision, Python, TensorFlow",PhD,9,Manufacturing,2024-11-03,2025-01-06,824,9.1,Future Systems +AI12744,Autonomous Systems Engineer,103507,GBP,77630,MI,CT,United Kingdom,M,Luxembourg,0,"Azure, Data Visualization, Python",PhD,4,Media,2024-04-16,2024-05-29,2078,8,Advanced Robotics +AI12745,Data Engineer,223904,EUR,190318,EX,FT,France,M,France,100,"Azure, PyTorch, Hadoop, Kubernetes, Spark",Associate,11,Transportation,2024-04-12,2024-05-29,581,6.1,Neural Networks Co +AI12746,ML Ops Engineer,142980,USD,142980,EX,FL,Finland,M,Austria,100,"R, SQL, Scala, AWS",Bachelor,15,Telecommunications,2024-10-10,2024-11-15,1600,7.9,DataVision Ltd +AI12747,Head of AI,64103,EUR,54488,EN,FL,Austria,M,Austria,100,"Scala, NLP, Java, GCP, Azure",Master,1,Technology,2025-01-14,2025-02-12,1817,6,Algorithmic Solutions +AI12748,Autonomous Systems Engineer,91062,EUR,77403,MI,PT,Austria,S,Austria,100,"Statistics, PyTorch, Spark, Git, Data Visualization",Master,4,Healthcare,2024-02-14,2024-04-27,1057,9.1,DataVision Ltd +AI12749,Robotics Engineer,78579,EUR,66792,EN,CT,Netherlands,L,Germany,100,"Python, Azure, Scala, Tableau",Bachelor,1,Telecommunications,2024-04-29,2024-05-16,1050,5,Advanced Robotics +AI12750,Deep Learning Engineer,115061,EUR,97802,MI,FL,France,L,France,50,"Linux, Java, R, Mathematics, Kubernetes",Bachelor,4,Manufacturing,2024-02-20,2024-03-05,1225,8.8,Cognitive Computing +AI12751,AI Software Engineer,61569,SGD,80040,EN,PT,Singapore,S,Colombia,0,"Azure, NLP, GCP, Java, Mathematics",PhD,0,Retail,2025-03-05,2025-05-06,1412,5.4,Machine Intelligence Group +AI12752,Principal Data Scientist,106803,SGD,138844,SE,CT,Singapore,S,Singapore,100,"Mathematics, Spark, Java, PyTorch",Associate,7,Finance,2024-09-24,2024-10-27,2223,7.5,Neural Networks Co +AI12753,Data Scientist,88775,USD,88775,MI,FT,Ireland,M,Ireland,50,"Python, Scala, NLP, Kubernetes, TensorFlow",Bachelor,4,Manufacturing,2024-07-23,2024-08-08,677,9.9,Cognitive Computing +AI12754,Principal Data Scientist,143329,CAD,179161,EX,FT,Canada,M,Indonesia,100,"Kubernetes, SQL, PyTorch",Associate,16,Consulting,2024-12-06,2025-01-24,1069,8,Machine Intelligence Group +AI12755,Machine Learning Researcher,83311,CHF,74980,EN,CT,Switzerland,S,China,50,"Git, Mathematics, SQL, PyTorch, Azure",Bachelor,0,Consulting,2025-02-01,2025-02-22,1003,8.6,Algorithmic Solutions +AI12756,Machine Learning Engineer,200496,GBP,150372,EX,FT,United Kingdom,S,United Kingdom,50,"R, Java, Computer Vision, Kubernetes",Associate,18,Finance,2024-04-07,2024-05-03,2129,5.8,Future Systems +AI12757,Principal Data Scientist,60235,SGD,78306,EN,CT,Singapore,S,Singapore,100,"Spark, SQL, R, Scala",Master,1,Media,2024-10-15,2024-12-08,963,6.9,Future Systems +AI12758,Head of AI,74675,USD,74675,EN,FT,Sweden,L,Netherlands,50,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-10-02,2024-11-06,1444,5.8,Cloud AI Solutions +AI12759,AI Consultant,61377,EUR,52170,EN,FT,Austria,S,Austria,100,"SQL, NLP, Spark, MLOps",Associate,1,Transportation,2024-08-06,2024-10-02,1373,6.2,AI Innovations +AI12760,AI Specialist,23390,USD,23390,MI,PT,India,S,India,100,"Linux, R, SQL, Data Visualization, NLP",Associate,2,Telecommunications,2025-02-05,2025-03-01,882,7,TechCorp Inc +AI12761,Machine Learning Researcher,91528,EUR,77799,EN,CT,Netherlands,L,Netherlands,100,"Spark, Python, R, Linux",Master,1,Real Estate,2024-08-22,2024-09-25,2097,7.1,DataVision Ltd +AI12762,Robotics Engineer,146429,USD,146429,SE,PT,Denmark,S,Portugal,50,"Docker, AWS, Tableau, Computer Vision, Kubernetes",Associate,6,Retail,2025-02-08,2025-03-12,1796,5.6,DeepTech Ventures +AI12763,Machine Learning Engineer,44242,USD,44242,SE,FT,India,L,New Zealand,50,"Python, Hadoop, AWS, Statistics",Associate,6,Telecommunications,2025-01-07,2025-01-25,1911,6.5,Quantum Computing Inc +AI12764,Principal Data Scientist,141895,USD,141895,MI,PT,United States,L,United States,50,"Statistics, MLOps, Python",PhD,4,Finance,2025-04-15,2025-06-22,1539,6.5,DataVision Ltd +AI12765,Head of AI,172701,EUR,146796,EX,FT,France,L,Estonia,100,"TensorFlow, Git, Computer Vision, Tableau",Bachelor,16,Media,2024-11-21,2024-12-13,1649,6.9,Machine Intelligence Group +AI12766,AI Research Scientist,122947,JPY,13524170,SE,CT,Japan,S,Switzerland,50,"GCP, Git, Statistics",Master,6,Education,2024-11-02,2024-12-17,1589,8.2,Future Systems +AI12767,Data Analyst,76332,EUR,64882,EN,PT,Netherlands,M,Japan,50,"Java, Docker, PyTorch, Computer Vision, Azure",PhD,1,Energy,2024-09-19,2024-11-09,572,5.1,Predictive Systems +AI12768,ML Ops Engineer,165380,EUR,140573,EX,PT,Austria,S,China,100,"Kubernetes, NLP, GCP, Computer Vision",Associate,17,Education,2024-11-17,2024-12-18,551,5.7,Smart Analytics +AI12769,Head of AI,142751,EUR,121338,EX,FT,Austria,M,Austria,0,"Data Visualization, PyTorch, Tableau, Kubernetes",Bachelor,15,Technology,2024-06-24,2024-08-10,848,9.7,Algorithmic Solutions +AI12770,AI Architect,62156,USD,62156,EX,FL,India,M,India,100,"Java, R, NLP, Computer Vision, Kubernetes",Bachelor,14,Gaming,2024-10-21,2024-12-30,539,5.8,Smart Analytics +AI12771,AI Product Manager,152270,USD,152270,SE,FT,United States,M,United States,50,"Linux, AWS, Data Visualization",Associate,5,Media,2025-03-15,2025-04-17,1162,7.3,Autonomous Tech +AI12772,AI Software Engineer,86405,EUR,73444,MI,CT,Netherlands,M,Denmark,0,"NLP, Mathematics, SQL",Master,2,Automotive,2024-06-04,2024-06-27,1890,10,Cloud AI Solutions +AI12773,Machine Learning Engineer,82630,JPY,9089300,MI,FL,Japan,M,Japan,50,"Python, GCP, Data Visualization",PhD,3,Government,2024-10-04,2024-11-27,1829,7.5,Autonomous Tech +AI12774,AI Specialist,57873,USD,57873,EX,CT,China,S,Malaysia,100,"AWS, Azure, Mathematics",Associate,13,Telecommunications,2024-06-07,2024-07-12,1519,6.3,Digital Transformation LLC +AI12775,Robotics Engineer,28348,USD,28348,EN,FL,India,M,India,0,"Statistics, Spark, Python, Computer Vision, Git",PhD,0,Technology,2024-09-22,2024-11-17,723,8.3,Cognitive Computing +AI12776,Computer Vision Engineer,87180,SGD,113334,MI,FT,Singapore,M,Czech Republic,100,"Linux, Data Visualization, GCP, TensorFlow",PhD,2,Consulting,2024-07-15,2024-09-09,1059,9.7,Cloud AI Solutions +AI12777,Head of AI,91044,GBP,68283,EN,PT,United Kingdom,L,United Kingdom,0,"R, PyTorch, Spark, Git, SQL",Master,0,Retail,2025-03-04,2025-04-03,596,5.4,Digital Transformation LLC +AI12778,NLP Engineer,76331,USD,76331,MI,FT,South Korea,L,South Korea,100,"GCP, Kubernetes, Mathematics, Python",PhD,4,Retail,2025-02-17,2025-03-29,1303,5.6,Digital Transformation LLC +AI12779,Robotics Engineer,118613,EUR,100821,SE,CT,France,L,France,0,"Linux, AWS, Deep Learning",Bachelor,8,Telecommunications,2025-01-19,2025-03-09,615,5.2,DataVision Ltd +AI12780,Machine Learning Researcher,92441,GBP,69331,EN,FL,United Kingdom,L,United Kingdom,50,"R, Computer Vision, Linux, Hadoop, SQL",Associate,0,Retail,2024-01-28,2024-03-27,1260,8.2,Advanced Robotics +AI12781,Data Analyst,268946,CHF,242051,EX,CT,Switzerland,M,Switzerland,50,"Data Visualization, Linux, R, Tableau, NLP",Associate,11,Gaming,2024-05-10,2024-07-03,1285,6.6,Quantum Computing Inc +AI12782,Robotics Engineer,32200,USD,32200,EN,FT,China,S,Estonia,100,"SQL, Git, Azure",Bachelor,1,Finance,2024-10-15,2024-12-11,1756,8.6,AI Innovations +AI12783,Robotics Engineer,138675,GBP,104006,SE,FL,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes",PhD,8,Energy,2024-12-09,2025-02-01,1248,8.5,TechCorp Inc +AI12784,Robotics Engineer,68778,EUR,58461,EN,PT,Germany,L,Germany,100,"TensorFlow, Scala, PyTorch, MLOps",PhD,0,Automotive,2025-02-04,2025-03-16,693,6.4,Future Systems +AI12785,Machine Learning Engineer,209006,CHF,188105,SE,CT,Switzerland,M,Switzerland,100,"PyTorch, Python, NLP, Azure",Associate,9,Transportation,2024-06-10,2024-07-04,2219,8.9,Smart Analytics +AI12786,Machine Learning Engineer,131992,CAD,164990,EX,PT,Canada,M,Canada,0,"Python, NLP, Linux, MLOps, AWS",Associate,15,Gaming,2024-09-22,2024-11-16,1295,6.1,Cognitive Computing +AI12787,Data Engineer,94712,USD,94712,MI,FL,Sweden,L,Sweden,50,"Mathematics, PyTorch, Tableau",PhD,2,Technology,2024-03-28,2024-06-07,1216,8.4,Advanced Robotics +AI12788,NLP Engineer,134256,USD,134256,SE,FL,Sweden,S,Sweden,100,"Kubernetes, TensorFlow, GCP",PhD,5,Media,2025-04-24,2025-06-26,1279,7.7,AI Innovations +AI12789,Deep Learning Engineer,103820,USD,103820,MI,PT,Israel,M,Israel,50,"Python, Tableau, Statistics, TensorFlow, Spark",Bachelor,2,Real Estate,2025-03-01,2025-04-10,1980,6.8,Smart Analytics +AI12790,Research Scientist,90645,USD,90645,MI,PT,United States,M,Portugal,0,"PyTorch, Statistics, Kubernetes, NLP",Master,3,Media,2024-05-09,2024-07-02,585,8.9,Smart Analytics +AI12791,ML Ops Engineer,119424,USD,119424,MI,PT,Finland,L,Canada,100,"SQL, Deep Learning, AWS, PyTorch, Spark",PhD,2,Retail,2024-11-11,2024-12-03,2449,5.3,DeepTech Ventures +AI12792,AI Specialist,100887,USD,100887,MI,FL,Ireland,M,Ireland,100,"Git, GCP, Scala, Linux, PyTorch",Master,3,Manufacturing,2024-07-28,2024-09-22,2297,6.9,Quantum Computing Inc +AI12793,NLP Engineer,99370,USD,99370,EX,FT,China,S,China,0,"Python, Java, AWS",PhD,19,Education,2024-04-06,2024-05-03,1851,7.8,Advanced Robotics +AI12794,Deep Learning Engineer,136900,AUD,184815,EX,FT,Australia,M,Australia,100,"MLOps, Kubernetes, Scala",PhD,19,Finance,2024-11-07,2025-01-14,2396,7.5,Cognitive Computing +AI12795,Autonomous Systems Engineer,46438,USD,46438,EN,PT,South Korea,M,South Korea,0,"Kubernetes, SQL, Hadoop, GCP, Computer Vision",Bachelor,1,Manufacturing,2024-02-01,2024-03-09,2305,5.7,Predictive Systems +AI12796,Machine Learning Engineer,49841,USD,49841,MI,FL,China,M,China,0,"Scala, Git, Spark, SQL, Data Visualization",Associate,2,Gaming,2024-07-09,2024-08-19,2197,8.9,DataVision Ltd +AI12797,AI Research Scientist,87830,USD,87830,EX,FL,China,M,China,0,"Spark, Statistics, Python, Docker, Scala",Associate,12,Education,2024-04-02,2024-06-02,2416,9.3,Neural Networks Co +AI12798,Autonomous Systems Engineer,78608,EUR,66817,MI,CT,Austria,M,Austria,0,"R, Scala, TensorFlow, Java",PhD,3,Education,2024-02-26,2024-03-20,2454,5.2,TechCorp Inc +AI12799,Principal Data Scientist,76299,USD,76299,EN,FL,South Korea,L,Estonia,100,"Scala, Java, GCP",Master,0,Media,2024-07-24,2024-09-17,1410,6.9,TechCorp Inc +AI12800,Machine Learning Engineer,70823,USD,70823,MI,FT,Sweden,S,Sweden,100,"SQL, Hadoop, Git",Master,2,Transportation,2024-04-28,2024-06-09,1116,9,Neural Networks Co +AI12801,Head of AI,161626,USD,161626,SE,PT,Norway,L,Norway,50,"PyTorch, SQL, TensorFlow, Python, Deep Learning",Bachelor,7,Finance,2024-11-10,2024-12-06,2400,5.1,Quantum Computing Inc +AI12802,AI Specialist,94357,GBP,70768,MI,PT,United Kingdom,L,United Kingdom,0,"Scala, Spark, Mathematics, Git",PhD,3,Energy,2024-01-11,2024-03-21,1784,8.3,Future Systems +AI12803,AI Architect,154775,USD,154775,EX,CT,Sweden,M,Sweden,50,"Python, Hadoop, Mathematics",Master,15,Telecommunications,2024-04-16,2024-05-30,2227,8.8,Predictive Systems +AI12804,AI Software Engineer,81393,EUR,69184,MI,PT,France,M,France,100,"Deep Learning, SQL, Azure",Associate,4,Consulting,2025-02-09,2025-03-25,1445,6.4,DeepTech Ventures +AI12805,AI Software Engineer,64623,USD,64623,EN,PT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",Master,1,Energy,2024-06-21,2024-08-28,1928,5.5,DeepTech Ventures +AI12806,Autonomous Systems Engineer,53147,USD,53147,EN,CT,Finland,S,Egypt,100,"AWS, Python, Statistics, Tableau, Hadoop",PhD,1,Technology,2024-08-03,2024-10-07,1518,6.8,DeepTech Ventures +AI12807,Data Scientist,95590,USD,95590,SE,PT,Israel,S,Israel,100,"MLOps, AWS, GCP, NLP, Azure",Bachelor,5,Telecommunications,2024-07-03,2024-08-05,1154,6,Machine Intelligence Group +AI12808,Robotics Engineer,72897,USD,72897,EN,CT,Norway,S,Norway,0,"Spark, MLOps, Kubernetes, Linux, TensorFlow",Associate,1,Telecommunications,2024-06-07,2024-07-16,2207,6.8,Neural Networks Co +AI12809,AI Consultant,150728,USD,150728,EX,PT,United States,S,India,100,"Docker, Java, Statistics, SQL, Hadoop",Associate,14,Government,2024-08-13,2024-09-23,2349,8.2,Cognitive Computing +AI12810,ML Ops Engineer,117055,USD,117055,MI,CT,Norway,M,Norway,100,"Git, Docker, Python, Tableau, Azure",PhD,4,Manufacturing,2024-10-09,2024-12-19,794,5.6,Algorithmic Solutions +AI12811,Machine Learning Researcher,87825,EUR,74651,MI,FL,Austria,M,Austria,50,"SQL, Hadoop, TensorFlow, AWS",Bachelor,2,Media,2024-01-07,2024-02-23,2030,9.6,Algorithmic Solutions +AI12812,Data Analyst,199854,AUD,269803,EX,PT,Australia,S,United States,100,"Tableau, Hadoop, SQL, Data Visualization",Bachelor,13,Media,2024-08-28,2024-10-20,1378,6.7,Quantum Computing Inc +AI12813,Deep Learning Engineer,159183,EUR,135306,SE,FL,Netherlands,L,Netherlands,0,"Docker, Python, Tableau",Master,6,Transportation,2024-11-30,2025-01-19,1835,8,Digital Transformation LLC +AI12814,AI Specialist,64547,GBP,48410,EN,PT,United Kingdom,S,United Kingdom,100,"TensorFlow, SQL, Deep Learning, Docker, NLP",Master,0,Energy,2024-08-12,2024-10-21,666,5.8,Autonomous Tech +AI12815,Data Analyst,95432,CHF,85889,EN,FL,Switzerland,S,Switzerland,100,"Linux, SQL, Azure, Hadoop",Associate,0,Education,2024-08-22,2024-10-27,2451,7.1,Cloud AI Solutions +AI12816,AI Research Scientist,38213,USD,38213,MI,FT,India,M,India,50,"Hadoop, Python, Java",Master,2,Finance,2024-10-09,2024-11-24,2359,5.3,Cloud AI Solutions +AI12817,Computer Vision Engineer,122719,USD,122719,SE,PT,Finland,L,Finland,0,"Python, Data Visualization, Kubernetes, Docker, Linux",Bachelor,7,Gaming,2024-09-18,2024-11-22,1724,7.1,DeepTech Ventures +AI12818,Computer Vision Engineer,126604,CHF,113944,MI,PT,Switzerland,L,Switzerland,0,"AWS, Spark, Statistics, SQL, R",Associate,2,Consulting,2024-10-26,2024-11-29,605,8.4,Neural Networks Co +AI12819,Autonomous Systems Engineer,27641,USD,27641,MI,FT,India,S,India,50,"Git, TensorFlow, AWS",PhD,3,Education,2024-05-21,2024-07-16,1784,7.8,Predictive Systems +AI12820,Data Analyst,106504,USD,106504,EN,CT,Denmark,L,Denmark,0,"TensorFlow, Git, Statistics, Tableau, MLOps",Master,1,Finance,2025-04-29,2025-07-02,2091,8.6,TechCorp Inc +AI12821,AI Product Manager,211310,EUR,179614,EX,PT,Netherlands,M,Netherlands,50,"Git, NLP, AWS, Hadoop",Associate,13,Energy,2024-11-07,2024-11-24,1971,6.2,DeepTech Ventures +AI12822,Autonomous Systems Engineer,55929,USD,55929,MI,CT,China,L,China,0,"Java, Linux, Python, GCP",Associate,3,Telecommunications,2024-03-26,2024-05-25,2125,8.5,Cognitive Computing +AI12823,Principal Data Scientist,189125,GBP,141844,EX,FT,United Kingdom,L,Singapore,0,"AWS, PyTorch, Java, TensorFlow, Statistics",Master,16,Education,2024-06-21,2024-07-30,2004,5.9,TechCorp Inc +AI12824,AI Product Manager,232230,JPY,25545300,EX,FT,Japan,L,Japan,50,"Scala, Docker, Linux, Azure",PhD,14,Consulting,2024-02-10,2024-03-25,719,7.2,Cloud AI Solutions +AI12825,AI Architect,92533,AUD,124920,MI,FT,Australia,M,Australia,100,"Kubernetes, SQL, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-30,1982,5.1,Advanced Robotics +AI12826,Head of AI,170727,USD,170727,EX,CT,South Korea,S,France,0,"TensorFlow, Java, Computer Vision",Associate,15,Real Estate,2024-09-04,2024-11-03,829,5.8,DeepTech Ventures +AI12827,Machine Learning Researcher,64528,USD,64528,EN,CT,Finland,M,Finland,0,"Git, Java, Statistics",Bachelor,0,Consulting,2025-03-14,2025-04-02,1203,9.1,Quantum Computing Inc +AI12828,Robotics Engineer,86994,GBP,65246,EN,PT,United Kingdom,L,Malaysia,50,"Azure, AWS, GCP, Linux",Master,1,Automotive,2025-04-13,2025-05-02,1858,8.6,Cloud AI Solutions +AI12829,AI Architect,195324,USD,195324,EX,FL,Israel,L,Canada,50,"GCP, Spark, SQL, PyTorch, Computer Vision",Master,11,Technology,2024-06-13,2024-07-28,511,9.3,Digital Transformation LLC +AI12830,AI Architect,107212,EUR,91130,SE,CT,Netherlands,S,Germany,50,"Docker, Java, Mathematics",Associate,9,Education,2025-04-30,2025-05-28,1555,7.1,DataVision Ltd +AI12831,Data Scientist,63595,USD,63595,EN,CT,Ireland,M,Ireland,50,"Scala, Python, TensorFlow, Mathematics",Bachelor,0,Gaming,2024-01-14,2024-03-16,2066,7.9,Algorithmic Solutions +AI12832,Data Engineer,146168,USD,146168,SE,PT,United States,M,United States,50,"Tableau, Java, Azure, SQL, PyTorch",Associate,7,Media,2025-04-18,2025-05-15,1733,8.2,Smart Analytics +AI12833,AI Product Manager,23158,USD,23158,EN,FT,China,S,China,0,"Git, NLP, SQL",Master,1,Government,2024-03-17,2024-04-18,1055,8.3,Digital Transformation LLC +AI12834,Data Engineer,74146,EUR,63024,EN,FT,Austria,M,Austria,0,"Linux, Tableau, Git, R, Statistics",Bachelor,1,Media,2024-11-16,2024-12-24,2186,9.8,Future Systems +AI12835,NLP Engineer,244490,SGD,317837,EX,FL,Singapore,M,Vietnam,50,"Python, TensorFlow, AWS, Scala, PyTorch",Master,16,Consulting,2024-08-20,2024-09-05,1520,7.4,DeepTech Ventures +AI12836,Data Analyst,135650,USD,135650,MI,FT,United States,L,Czech Republic,0,"Scala, Azure, PyTorch, Deep Learning, Tableau",Master,2,Technology,2025-02-25,2025-03-23,1602,6.2,Machine Intelligence Group +AI12837,AI Product Manager,161057,EUR,136898,SE,PT,France,L,France,0,"Deep Learning, NLP, MLOps, Scala, TensorFlow",Associate,8,Retail,2025-02-26,2025-04-30,873,5.7,Future Systems +AI12838,AI Research Scientist,95999,SGD,124799,MI,FL,Singapore,L,Australia,50,"SQL, R, MLOps, NLP",Associate,4,Transportation,2024-03-27,2024-06-02,897,5.7,AI Innovations +AI12839,Autonomous Systems Engineer,75071,USD,75071,EN,CT,Sweden,L,Sweden,50,"Tableau, TensorFlow, PyTorch",Associate,0,Manufacturing,2025-04-25,2025-06-11,2289,8,Cloud AI Solutions +AI12840,AI Research Scientist,80156,USD,80156,EN,CT,Sweden,L,Sweden,100,"Scala, SQL, MLOps",Bachelor,0,Manufacturing,2024-04-21,2024-06-27,2425,5.1,Algorithmic Solutions +AI12841,NLP Engineer,77757,CHF,69981,EN,FL,Switzerland,M,Switzerland,0,"SQL, Kubernetes, TensorFlow, Git",PhD,0,Media,2024-01-07,2024-03-20,964,8.7,AI Innovations +AI12842,Machine Learning Engineer,56236,USD,56236,EN,PT,South Korea,M,South Korea,50,"Python, R, Data Visualization, Java, MLOps",Bachelor,1,Consulting,2025-03-15,2025-05-07,2054,9.7,Machine Intelligence Group +AI12843,Computer Vision Engineer,240245,JPY,26426950,EX,CT,Japan,M,Japan,100,"Scala, Java, R, Computer Vision, Git",PhD,14,Technology,2025-01-31,2025-04-01,1258,8.5,Future Systems +AI12844,Data Analyst,275028,USD,275028,EX,PT,Ireland,L,Ireland,100,"Deep Learning, Azure, GCP",Master,12,Manufacturing,2024-02-22,2024-04-02,1031,6.5,Digital Transformation LLC +AI12845,AI Consultant,186213,EUR,158281,EX,CT,Austria,L,Austria,100,"Data Visualization, Linux, SQL, Deep Learning",Bachelor,18,Media,2024-01-25,2024-03-19,2022,7.2,Algorithmic Solutions +AI12846,Data Engineer,287124,USD,287124,EX,FT,Norway,S,Norway,50,"Linux, Tableau, Hadoop, Computer Vision",Bachelor,15,Transportation,2025-02-11,2025-04-13,2175,6.8,Digital Transformation LLC +AI12847,Data Scientist,135404,CHF,121864,MI,PT,Switzerland,M,Switzerland,100,"SQL, Kubernetes, Tableau, Linux",Master,3,Transportation,2025-02-14,2025-04-05,2281,8.1,Quantum Computing Inc +AI12848,Principal Data Scientist,159276,EUR,135385,SE,PT,France,L,France,50,"Hadoop, Docker, Kubernetes, MLOps",PhD,8,Consulting,2024-11-12,2025-01-08,673,8.6,AI Innovations +AI12849,Data Engineer,93350,USD,93350,SE,FL,Sweden,S,Sweden,100,"Linux, Data Visualization, Python",Associate,8,Government,2025-01-28,2025-04-02,533,6.7,AI Innovations +AI12850,AI Product Manager,264276,USD,264276,EX,PT,Ireland,L,Nigeria,50,"Java, SQL, Deep Learning, Hadoop, Spark",Associate,10,Consulting,2025-01-09,2025-02-28,2452,7.7,Machine Intelligence Group +AI12851,ML Ops Engineer,31006,USD,31006,MI,CT,India,S,India,50,"Deep Learning, Python, AWS, Tableau, Spark",Bachelor,4,Manufacturing,2025-04-17,2025-05-19,1090,7.9,Advanced Robotics +AI12852,AI Architect,132059,USD,132059,SE,FT,Israel,M,Israel,50,"Spark, SQL, MLOps",PhD,8,Automotive,2025-01-23,2025-02-12,1688,7,Cloud AI Solutions +AI12853,NLP Engineer,85658,AUD,115638,MI,FL,Australia,L,Japan,50,"Python, NLP, Computer Vision, Git",Bachelor,2,Manufacturing,2024-04-03,2024-05-21,1069,8.1,Neural Networks Co +AI12854,Data Scientist,107273,EUR,91182,SE,PT,Germany,S,Germany,0,"Python, Git, Hadoop",Bachelor,6,Government,2024-07-11,2024-08-21,1704,8.7,Algorithmic Solutions +AI12855,Data Scientist,120446,EUR,102379,SE,CT,Netherlands,S,Netherlands,0,"Linux, Java, Git, Tableau",Bachelor,7,Manufacturing,2024-02-22,2024-04-23,1512,5.8,Future Systems +AI12856,Principal Data Scientist,92064,USD,92064,MI,FL,Israel,L,Israel,100,"Python, GCP, Computer Vision, TensorFlow",Bachelor,2,Real Estate,2025-04-30,2025-05-29,779,7.7,AI Innovations +AI12857,ML Ops Engineer,170651,USD,170651,EX,PT,Finland,S,Brazil,100,"AWS, Azure, Python, TensorFlow",Associate,17,Gaming,2024-05-08,2024-05-29,1131,8.1,DeepTech Ventures +AI12858,Principal Data Scientist,209732,USD,209732,EX,FL,United States,L,United States,0,"Python, Docker, Data Visualization, Azure",PhD,13,Healthcare,2024-09-09,2024-10-09,1392,8.9,Autonomous Tech +AI12859,Data Scientist,90595,EUR,77006,MI,FL,France,M,France,100,"Data Visualization, Docker, Tableau, SQL",Bachelor,2,Retail,2025-04-17,2025-05-23,1909,9.4,Cognitive Computing +AI12860,ML Ops Engineer,134103,GBP,100577,SE,PT,United Kingdom,L,United Kingdom,0,"GCP, Spark, Tableau",Associate,6,Telecommunications,2024-09-05,2024-10-15,2247,5.8,Predictive Systems +AI12861,AI Software Engineer,328767,USD,328767,EX,CT,Norway,M,Norway,50,"Git, Mathematics, Deep Learning, PyTorch",PhD,14,Gaming,2024-03-27,2024-04-23,813,8.1,TechCorp Inc +AI12862,Head of AI,201006,USD,201006,EX,CT,Israel,M,Denmark,0,"TensorFlow, Python, Docker",PhD,14,Transportation,2025-02-28,2025-04-20,999,5.7,DataVision Ltd +AI12863,Research Scientist,127726,JPY,14049860,SE,PT,Japan,S,Japan,50,"Mathematics, AWS, PyTorch, Deep Learning, Java",PhD,8,Gaming,2025-04-10,2025-04-30,742,6.3,Predictive Systems +AI12864,Computer Vision Engineer,269096,USD,269096,EX,FL,United States,L,United States,50,"TensorFlow, MLOps, Tableau",Associate,17,Education,2024-10-04,2024-11-24,1224,7.5,Cognitive Computing +AI12865,Data Engineer,149753,EUR,127290,SE,FT,Austria,L,China,100,"GCP, Spark, Scala, Data Visualization, Python",Master,7,Education,2024-11-28,2025-01-08,637,5.5,Future Systems +AI12866,ML Ops Engineer,145711,SGD,189424,SE,PT,Singapore,M,Singapore,100,"Scala, Docker, Statistics, Deep Learning, Computer Vision",Bachelor,5,Real Estate,2025-02-18,2025-04-01,2320,9.4,Predictive Systems +AI12867,AI Consultant,20533,USD,20533,EN,FT,India,S,India,100,"Scala, Kubernetes, Hadoop",Associate,0,Technology,2025-01-16,2025-02-02,1142,9.7,Future Systems +AI12868,NLP Engineer,80896,USD,80896,EN,CT,United States,L,United States,0,"Python, TensorFlow, Azure, Java, Tableau",PhD,0,Telecommunications,2024-02-09,2024-04-07,1088,6.5,Digital Transformation LLC +AI12869,Autonomous Systems Engineer,128356,EUR,109103,SE,FT,Netherlands,L,Netherlands,0,"NLP, TensorFlow, R, Computer Vision, Scala",Bachelor,5,Consulting,2024-12-27,2025-02-25,520,9.3,Cloud AI Solutions +AI12870,Data Engineer,118886,USD,118886,SE,FL,United States,S,Kenya,50,"Java, MLOps, Computer Vision, AWS, Azure",PhD,7,Education,2024-03-06,2024-03-26,1504,8.8,Future Systems +AI12871,AI Architect,115314,USD,115314,MI,FT,Denmark,S,Denmark,100,"Linux, Python, NLP, Git",Associate,2,Consulting,2024-11-16,2024-12-24,777,6,Quantum Computing Inc +AI12872,Data Scientist,132602,CHF,119342,MI,CT,Switzerland,S,Switzerland,100,"Python, Spark, Deep Learning",PhD,2,Consulting,2024-07-23,2024-08-12,2381,9.1,Advanced Robotics +AI12873,AI Software Engineer,145255,GBP,108941,EX,CT,United Kingdom,S,United Kingdom,50,"MLOps, Mathematics, Docker, PyTorch, TensorFlow",Associate,17,Automotive,2024-10-21,2024-11-20,2468,5.5,Cloud AI Solutions +AI12874,ML Ops Engineer,139099,USD,139099,SE,PT,South Korea,L,South Korea,0,"Spark, Azure, Data Visualization, GCP",Bachelor,8,Transportation,2025-03-16,2025-04-18,2132,7.1,Machine Intelligence Group +AI12875,AI Architect,112407,CHF,101166,MI,FL,Switzerland,M,Netherlands,100,"Hadoop, NLP, Tableau",Bachelor,3,Government,2025-01-10,2025-02-26,1032,8,Advanced Robotics +AI12876,Data Scientist,113716,USD,113716,MI,FL,Ireland,L,Ireland,100,"PyTorch, GCP, Statistics",Associate,4,Real Estate,2024-11-24,2024-12-16,2045,5.2,Machine Intelligence Group +AI12877,Data Scientist,45202,USD,45202,EN,FT,South Korea,S,South Korea,50,"Tableau, Java, Kubernetes, Azure, Scala",Master,0,Education,2024-02-17,2024-03-13,1242,6.1,Cloud AI Solutions +AI12878,Autonomous Systems Engineer,131630,USD,131630,EX,PT,Israel,M,Israel,50,"Git, Java, Linux, TensorFlow, Deep Learning",Master,13,Automotive,2025-01-24,2025-03-21,1311,5,TechCorp Inc +AI12879,Computer Vision Engineer,130641,JPY,14370510,MI,FT,Japan,L,Japan,50,"Python, Spark, Scala, Data Visualization, SQL",Associate,3,Real Estate,2024-12-18,2025-01-23,2057,6.3,TechCorp Inc +AI12880,Deep Learning Engineer,270691,GBP,203018,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Azure, Java, SQL, Computer Vision",Master,16,Education,2025-03-14,2025-04-22,1824,6.9,Neural Networks Co +AI12881,AI Product Manager,90830,USD,90830,MI,PT,United States,M,United States,100,"MLOps, Data Visualization, Python, SQL, GCP",Master,3,Education,2025-01-14,2025-02-11,1273,6.8,Smart Analytics +AI12882,AI Architect,155288,USD,155288,EX,CT,South Korea,S,Canada,50,"Python, Deep Learning, TensorFlow, Java, Statistics",PhD,18,Manufacturing,2025-01-27,2025-03-23,1295,7.8,Algorithmic Solutions +AI12883,NLP Engineer,55458,USD,55458,EN,CT,Finland,M,Finland,0,"Python, TensorFlow, Statistics",Associate,0,Healthcare,2024-02-11,2024-02-25,1132,6.2,Cloud AI Solutions +AI12884,Research Scientist,142729,USD,142729,MI,FL,Norway,M,Norway,100,"Kubernetes, MLOps, Scala, Computer Vision",Master,2,Transportation,2024-03-24,2024-05-13,2222,6.5,Smart Analytics +AI12885,Data Engineer,72858,USD,72858,EN,CT,Denmark,M,Switzerland,100,"SQL, R, Tableau, AWS, Computer Vision",Bachelor,0,Retail,2025-01-12,2025-02-06,1491,5.6,Future Systems +AI12886,Robotics Engineer,107428,AUD,145028,MI,FT,Australia,L,Australia,0,"Computer Vision, Python, Git, Kubernetes, Docker",Associate,3,Telecommunications,2024-06-09,2024-07-13,1024,9.4,Machine Intelligence Group +AI12887,Data Scientist,86669,EUR,73669,MI,FT,Netherlands,M,Netherlands,0,"Docker, Hadoop, MLOps, Git",Bachelor,3,Finance,2025-02-07,2025-03-21,1124,9.1,Digital Transformation LLC +AI12888,Research Scientist,128076,CAD,160095,EX,CT,Canada,M,Singapore,50,"Deep Learning, NLP, Data Visualization, Kubernetes",PhD,13,Media,2025-01-16,2025-03-10,923,9.5,DeepTech Ventures +AI12889,Machine Learning Engineer,106104,USD,106104,SE,PT,Israel,M,Israel,0,"Azure, SQL, Data Visualization, Python",Associate,5,Transportation,2024-03-23,2024-04-15,1567,9.3,Algorithmic Solutions +AI12890,Deep Learning Engineer,68721,USD,68721,MI,FL,Sweden,S,South Korea,50,"Scala, Spark, MLOps",Master,2,Energy,2024-05-15,2024-07-17,771,6.1,Future Systems +AI12891,NLP Engineer,86559,CAD,108199,MI,CT,Canada,M,Canada,50,"SQL, Kubernetes, Mathematics, Computer Vision, Azure",Associate,4,Gaming,2024-04-18,2024-06-28,2191,5,DeepTech Ventures +AI12892,ML Ops Engineer,61330,USD,61330,EN,FL,Israel,S,Israel,100,"NLP, PyTorch, Tableau, Scala, Java",PhD,1,Government,2024-03-06,2024-04-27,2174,5.7,Algorithmic Solutions +AI12893,Research Scientist,119858,AUD,161808,MI,PT,Australia,L,China,50,"Tableau, Statistics, Azure",Master,3,Media,2024-10-30,2024-11-13,1341,8.4,Quantum Computing Inc +AI12894,Robotics Engineer,118666,USD,118666,EN,FL,Norway,L,United States,0,"Scala, GCP, MLOps",PhD,1,Real Estate,2024-05-18,2024-07-03,1551,7.1,Digital Transformation LLC +AI12895,Autonomous Systems Engineer,25726,USD,25726,EN,FL,China,S,China,50,"TensorFlow, Linux, MLOps, R",Master,0,Transportation,2025-03-03,2025-03-22,2314,7.6,Machine Intelligence Group +AI12896,AI Specialist,29930,USD,29930,EN,CT,India,L,India,50,"Linux, Python, Tableau",Bachelor,0,Gaming,2024-04-21,2024-06-12,2416,7.5,DeepTech Ventures +AI12897,AI Architect,37505,USD,37505,MI,PT,India,M,India,0,"Mathematics, MLOps, Data Visualization",Bachelor,2,Media,2024-01-01,2024-01-22,1487,6.2,Predictive Systems +AI12898,Head of AI,116283,USD,116283,MI,CT,United States,S,Nigeria,0,"Git, Computer Vision, PyTorch, Hadoop",PhD,2,Automotive,2024-10-10,2024-12-09,1497,9.3,Neural Networks Co +AI12899,AI Product Manager,45147,USD,45147,SE,CT,India,S,India,0,"Python, TensorFlow, GCP",Associate,5,Real Estate,2024-05-06,2024-07-13,1498,5.7,Machine Intelligence Group +AI12900,Principal Data Scientist,66746,USD,66746,EN,CT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",PhD,0,Technology,2025-02-23,2025-04-21,1410,9.4,AI Innovations +AI12901,Data Analyst,61929,CAD,77411,EN,CT,Canada,M,Canada,100,"Git, Computer Vision, Statistics, Data Visualization, Java",Master,1,Retail,2024-06-06,2024-07-29,1877,6.8,Quantum Computing Inc +AI12902,Head of AI,210982,USD,210982,EX,FT,Sweden,M,Sweden,50,"Data Visualization, Tableau, Linux, TensorFlow, Java",Associate,11,Media,2024-03-04,2024-05-01,2082,9.4,Smart Analytics +AI12903,NLP Engineer,82621,SGD,107407,EN,FL,Singapore,L,Germany,100,"Tableau, PyTorch, TensorFlow, Python",Associate,1,Telecommunications,2025-03-15,2025-04-29,1755,7.7,AI Innovations +AI12904,Machine Learning Engineer,227131,EUR,193061,EX,FT,Germany,L,Germany,50,"Spark, PyTorch, Azure",Master,16,Automotive,2024-12-17,2025-01-21,640,7,Digital Transformation LLC +AI12905,Machine Learning Researcher,113462,USD,113462,MI,FL,United States,S,United States,0,"Azure, Tableau, Scala",Associate,2,Technology,2024-11-30,2024-12-19,2147,6,Algorithmic Solutions +AI12906,Machine Learning Researcher,146522,USD,146522,SE,PT,Denmark,M,Denmark,50,"Data Visualization, MLOps, Docker, Scala, R",Bachelor,7,Consulting,2024-12-31,2025-01-22,2267,8.2,Cloud AI Solutions +AI12907,AI Architect,310444,USD,310444,EX,FL,Denmark,M,Denmark,0,"NLP, TensorFlow, Java",PhD,17,Gaming,2025-02-07,2025-03-14,1768,5.4,Future Systems +AI12908,Machine Learning Engineer,212270,CAD,265338,EX,FL,Canada,S,Canada,50,"Scala, AWS, Computer Vision",PhD,10,Consulting,2024-12-01,2024-12-15,821,9.7,Autonomous Tech +AI12909,Principal Data Scientist,55426,USD,55426,MI,PT,South Korea,S,South Korea,0,"NLP, TensorFlow, PyTorch, Linux",Master,3,Technology,2025-01-25,2025-03-15,2111,9.6,Autonomous Tech +AI12910,NLP Engineer,284645,USD,284645,EX,PT,Denmark,M,Denmark,0,"SQL, Hadoop, Mathematics, MLOps, AWS",Bachelor,17,Automotive,2025-04-30,2025-05-15,1964,5.2,Advanced Robotics +AI12911,Machine Learning Engineer,91905,EUR,78119,MI,PT,France,M,France,100,"Kubernetes, MLOps, Linux, Java",Associate,3,Real Estate,2024-09-04,2024-10-07,1258,8.4,Neural Networks Co +AI12912,AI Consultant,46252,USD,46252,EN,FT,South Korea,S,South Korea,100,"Mathematics, Spark, MLOps, Computer Vision",Associate,1,Education,2024-07-15,2024-08-06,596,5.6,Digital Transformation LLC +AI12913,Data Engineer,140999,EUR,119849,SE,CT,Germany,L,Germany,0,"TensorFlow, Python, Hadoop",Master,6,Government,2024-04-19,2024-05-24,969,5.3,DataVision Ltd +AI12914,AI Architect,61460,USD,61460,EN,FT,Ireland,L,Philippines,100,"MLOps, Python, TensorFlow",PhD,0,Transportation,2024-12-28,2025-02-06,1746,8.3,TechCorp Inc +AI12915,AI Product Manager,107693,USD,107693,EN,FT,United States,L,United States,0,"Data Visualization, Kubernetes, NLP, AWS",Master,1,Telecommunications,2024-01-18,2024-02-22,1186,5.5,DataVision Ltd +AI12916,Deep Learning Engineer,202576,CAD,253220,EX,FT,Canada,L,Canada,100,"Azure, Deep Learning, GCP, Docker",Associate,15,Telecommunications,2024-09-09,2024-10-15,1817,9.4,DataVision Ltd +AI12917,AI Architect,61666,USD,61666,EN,FT,Israel,S,Israel,0,"Hadoop, R, Mathematics",Associate,1,Energy,2024-08-31,2024-09-15,2378,8.5,Cloud AI Solutions +AI12918,Data Scientist,40597,USD,40597,MI,FT,China,M,China,0,"R, MLOps, PyTorch",Master,4,Real Estate,2024-12-25,2025-03-01,1634,6.4,Cloud AI Solutions +AI12919,AI Research Scientist,136441,SGD,177373,SE,FL,Singapore,L,Singapore,0,"Docker, GCP, MLOps",Master,8,Automotive,2024-02-03,2024-04-05,1625,5.8,Predictive Systems +AI12920,Principal Data Scientist,64127,USD,64127,SE,PT,China,L,China,50,"Scala, TensorFlow, Kubernetes",Master,8,Gaming,2024-09-04,2024-10-11,581,7.2,Machine Intelligence Group +AI12921,ML Ops Engineer,104753,AUD,141417,SE,FL,Australia,M,Turkey,0,"GCP, Spark, Statistics",Bachelor,5,Gaming,2024-07-07,2024-08-15,1289,9.6,Quantum Computing Inc +AI12922,Principal Data Scientist,122222,USD,122222,MI,PT,Denmark,M,United Kingdom,50,"Docker, Deep Learning, Scala",Bachelor,2,Education,2024-07-30,2024-09-01,584,9.3,Predictive Systems +AI12923,NLP Engineer,101788,EUR,86520,SE,FL,France,M,France,50,"Data Visualization, Python, SQL, R, Java",Bachelor,9,Consulting,2024-08-30,2024-10-18,2421,9.7,AI Innovations +AI12924,Autonomous Systems Engineer,341521,CHF,307369,EX,FT,Switzerland,L,Australia,50,"Linux, Docker, SQL, GCP",Bachelor,11,Consulting,2024-11-01,2024-11-24,736,5.9,Cloud AI Solutions +AI12925,AI Specialist,63658,USD,63658,EN,PT,Israel,M,Israel,0,"Data Visualization, MLOps, Python, Java",PhD,0,Education,2024-04-18,2024-05-13,1176,9,Neural Networks Co +AI12926,Data Engineer,172241,USD,172241,EX,PT,Finland,M,Finland,50,"Scala, Hadoop, Data Visualization, NLP",Bachelor,11,Energy,2025-03-25,2025-04-20,1125,7.9,Algorithmic Solutions +AI12927,Data Engineer,80284,EUR,68241,MI,CT,Netherlands,M,Netherlands,100,"Linux, PyTorch, SQL",PhD,3,Energy,2024-11-19,2025-01-10,2146,8.8,Autonomous Tech +AI12928,Head of AI,82705,USD,82705,EN,FT,Sweden,L,Sweden,0,"Mathematics, Tableau, Hadoop, PyTorch",PhD,0,Finance,2024-03-09,2024-04-10,1351,8.1,Neural Networks Co +AI12929,ML Ops Engineer,82163,USD,82163,EN,PT,Finland,L,Finland,0,"Docker, MLOps, Deep Learning, Kubernetes, GCP",Associate,1,Manufacturing,2025-04-24,2025-06-19,1669,8.8,Algorithmic Solutions +AI12930,Principal Data Scientist,134609,USD,134609,SE,FT,Ireland,S,Ireland,100,"R, TensorFlow, Hadoop",Associate,9,Transportation,2025-02-10,2025-03-15,2238,7.6,Future Systems +AI12931,Machine Learning Researcher,50356,EUR,42803,EN,PT,Germany,S,Germany,0,"Git, TensorFlow, Data Visualization",Bachelor,1,Education,2025-04-13,2025-06-15,777,6.3,Digital Transformation LLC +AI12932,Robotics Engineer,100882,USD,100882,MI,CT,United States,S,United States,100,"Hadoop, Tableau, Git",Associate,3,Media,2024-11-07,2025-01-13,1996,6,Cloud AI Solutions +AI12933,AI Software Engineer,97133,USD,97133,SE,CT,Finland,M,Finland,100,"Computer Vision, Python, SQL, Docker",Associate,6,Education,2024-04-20,2024-05-18,2044,7.9,Cognitive Computing +AI12934,Data Engineer,169587,USD,169587,SE,PT,United States,L,United States,50,"R, GCP, SQL",Bachelor,6,Retail,2025-04-07,2025-05-13,612,7.6,Neural Networks Co +AI12935,AI Consultant,218131,EUR,185411,EX,CT,France,M,Turkey,0,"Hadoop, SQL, GCP, Git",Bachelor,10,Education,2025-02-18,2025-03-22,2034,8.5,Machine Intelligence Group +AI12936,NLP Engineer,103226,USD,103226,MI,CT,United States,M,Turkey,0,"Python, Hadoop, MLOps, Data Visualization, PyTorch",Bachelor,4,Retail,2024-09-23,2024-10-30,1512,6.2,AI Innovations +AI12937,Principal Data Scientist,100052,USD,100052,EN,PT,United States,L,United States,50,"PyTorch, R, Linux, Kubernetes, Scala",PhD,0,Consulting,2025-01-27,2025-04-08,1611,6.2,Algorithmic Solutions +AI12938,Deep Learning Engineer,166634,USD,166634,SE,FL,Norway,M,United States,0,"GCP, Python, Scala, Docker",Bachelor,8,Real Estate,2024-02-04,2024-02-29,673,9.3,Future Systems +AI12939,AI Consultant,116226,USD,116226,SE,FT,Sweden,M,Sweden,50,"PyTorch, Java, TensorFlow",Bachelor,6,Finance,2024-05-14,2024-07-11,1881,6.1,DeepTech Ventures +AI12940,NLP Engineer,95173,EUR,80897,SE,FL,Germany,S,Canada,0,"Scala, Java, Mathematics, Linux, Git",Master,6,Gaming,2024-08-21,2024-10-31,1306,9.8,Future Systems +AI12941,Data Scientist,164965,EUR,140220,EX,CT,Germany,S,Germany,0,"TensorFlow, Docker, Deep Learning, Python, Git",Bachelor,17,Consulting,2025-02-06,2025-03-09,1669,7.8,AI Innovations +AI12942,AI Architect,110208,CHF,99187,MI,CT,Switzerland,S,Switzerland,0,"SQL, Hadoop, R",PhD,4,Technology,2024-05-28,2024-07-06,712,9.8,AI Innovations +AI12943,AI Consultant,66541,USD,66541,EN,FT,United States,S,Brazil,100,"Kubernetes, Mathematics, NLP, SQL, Tableau",Bachelor,0,Consulting,2025-04-07,2025-05-14,2176,8.2,Digital Transformation LLC +AI12944,Computer Vision Engineer,349894,USD,349894,EX,FT,Norway,L,Norway,100,"SQL, Python, MLOps, Statistics",Master,14,Technology,2025-02-07,2025-03-15,1449,8.7,AI Innovations +AI12945,Machine Learning Engineer,186739,CHF,168065,SE,FT,Switzerland,S,Switzerland,0,"Deep Learning, Git, Java",PhD,9,Manufacturing,2024-05-22,2024-07-01,1850,7.5,Digital Transformation LLC +AI12946,Machine Learning Researcher,239337,SGD,311138,EX,FT,Singapore,S,Singapore,50,"Tableau, Java, NLP",Master,19,Education,2024-04-03,2024-04-29,2231,9.4,Algorithmic Solutions +AI12947,Machine Learning Researcher,36462,USD,36462,MI,FL,India,M,India,100,"TensorFlow, PyTorch, MLOps, GCP",PhD,4,Finance,2024-05-15,2024-07-10,2444,5.7,Machine Intelligence Group +AI12948,Data Analyst,91501,USD,91501,EN,CT,Denmark,M,Denmark,0,"Mathematics, R, Python",Master,1,Real Estate,2024-09-28,2024-10-18,747,5.5,DataVision Ltd +AI12949,Head of AI,112775,USD,112775,SE,CT,South Korea,L,Austria,0,"SQL, Computer Vision, Linux",Bachelor,5,Manufacturing,2024-10-03,2024-11-23,1899,8.5,Machine Intelligence Group +AI12950,Principal Data Scientist,114451,CAD,143064,SE,PT,Canada,L,Denmark,50,"Java, Hadoop, Tableau, Computer Vision, Statistics",PhD,9,Consulting,2024-02-04,2024-02-24,1992,8.1,Predictive Systems +AI12951,AI Specialist,106509,SGD,138462,SE,PT,Singapore,S,Singapore,0,"Kubernetes, SQL, Azure, PyTorch, TensorFlow",Associate,5,Consulting,2024-03-26,2024-05-09,2482,5.1,Future Systems +AI12952,AI Research Scientist,122296,JPY,13452560,SE,FL,Japan,S,Japan,50,"Kubernetes, SQL, Git, Data Visualization, NLP",Master,7,Retail,2024-06-17,2024-08-08,1647,9.2,DeepTech Ventures +AI12953,ML Ops Engineer,105130,USD,105130,EX,FL,South Korea,S,Egypt,0,"PyTorch, NLP, Python, Hadoop, GCP",Associate,18,Finance,2025-02-07,2025-04-21,1519,6,Advanced Robotics +AI12954,AI Consultant,54001,USD,54001,EN,PT,Israel,S,Israel,0,"SQL, Mathematics, TensorFlow, Python, Kubernetes",PhD,0,Gaming,2024-08-06,2024-09-01,2349,9.3,Digital Transformation LLC +AI12955,Data Scientist,48008,USD,48008,EN,FL,Finland,M,Singapore,50,"Data Visualization, Linux, Deep Learning, MLOps",Bachelor,1,Government,2024-02-20,2024-04-03,1739,8.7,Future Systems +AI12956,AI Software Engineer,48486,CAD,60608,EN,FT,Canada,S,Canada,0,"Spark, TensorFlow, SQL, Data Visualization, Kubernetes",Bachelor,1,Media,2025-01-18,2025-02-09,1337,10,Smart Analytics +AI12957,Machine Learning Researcher,270112,EUR,229595,EX,CT,Germany,L,Germany,0,"AWS, Python, Computer Vision",PhD,14,Manufacturing,2024-05-16,2024-07-01,855,7.7,DataVision Ltd +AI12958,AI Research Scientist,90538,EUR,76957,MI,FL,Germany,S,India,100,"Kubernetes, Hadoop, TensorFlow, Computer Vision",PhD,2,Real Estate,2024-02-03,2024-02-29,1388,9.1,Advanced Robotics +AI12959,Principal Data Scientist,151418,USD,151418,SE,FL,Israel,L,Israel,100,"Computer Vision, SQL, Scala, GCP, Spark",Master,8,Telecommunications,2024-06-07,2024-08-17,2032,10,Quantum Computing Inc +AI12960,Data Engineer,198647,CHF,178782,EX,FT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, Hadoop, SQL, AWS",PhD,10,Telecommunications,2025-02-12,2025-03-07,909,8.2,Autonomous Tech +AI12961,Deep Learning Engineer,156122,CAD,195153,SE,FT,Canada,L,Canada,100,"Spark, Tableau, Java, Data Visualization",Bachelor,5,Automotive,2025-01-16,2025-02-09,585,9.2,Predictive Systems +AI12962,ML Ops Engineer,164345,USD,164345,EX,PT,Israel,S,Israel,100,"Git, Kubernetes, Statistics",Associate,14,Education,2025-01-23,2025-02-09,2343,6.5,DataVision Ltd +AI12963,Computer Vision Engineer,156737,USD,156737,MI,CT,Denmark,L,Denmark,50,"Spark, R, SQL, Java, Mathematics",Master,2,Gaming,2024-10-24,2024-11-12,860,9.5,Quantum Computing Inc +AI12964,Research Scientist,134102,EUR,113987,SE,PT,Netherlands,M,Netherlands,50,"Data Visualization, Computer Vision, AWS, GCP, Statistics",Bachelor,9,Government,2024-10-06,2024-12-18,847,8.9,Future Systems +AI12965,Head of AI,112325,USD,112325,SE,FL,Israel,M,Israel,50,"Tableau, Azure, Python, Hadoop, Docker",PhD,9,Automotive,2025-02-07,2025-04-12,1786,5.7,Predictive Systems +AI12966,ML Ops Engineer,92446,USD,92446,EX,FT,China,S,New Zealand,50,"Spark, Python, Tableau, TensorFlow, GCP",Master,12,Technology,2025-03-05,2025-03-27,996,5.8,Cloud AI Solutions +AI12967,AI Research Scientist,262159,USD,262159,EX,FT,Ireland,L,Ireland,0,"Python, Spark, TensorFlow",Bachelor,18,Media,2025-04-27,2025-05-12,639,8.4,Predictive Systems +AI12968,Data Engineer,44890,USD,44890,MI,FL,China,M,China,0,"Hadoop, Data Visualization, MLOps, Deep Learning",PhD,4,Finance,2024-09-04,2024-11-04,1790,8.9,DeepTech Ventures +AI12969,AI Product Manager,217707,USD,217707,EX,PT,Ireland,S,Belgium,100,"Docker, Python, AWS, TensorFlow",Master,12,Telecommunications,2024-03-22,2024-04-05,1857,8.4,Autonomous Tech +AI12970,AI Product Manager,154903,USD,154903,EX,FT,Sweden,M,Brazil,50,"Scala, PyTorch, Spark, MLOps, Git",Bachelor,17,Energy,2025-02-03,2025-04-11,1604,7.5,Digital Transformation LLC +AI12971,Computer Vision Engineer,224171,USD,224171,EX,FL,United States,L,United States,50,"Deep Learning, Linux, Java, Python, SQL",Master,16,Education,2024-02-11,2024-04-24,1888,7.7,Autonomous Tech +AI12972,Principal Data Scientist,193696,USD,193696,EX,FL,Norway,M,Norway,100,"Mathematics, Deep Learning, Git, Spark",Associate,10,Manufacturing,2024-09-22,2024-11-11,1564,8.1,Cognitive Computing +AI12973,Robotics Engineer,75949,EUR,64557,EN,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, Docker",Master,0,Education,2024-07-07,2024-08-17,743,9.4,Cloud AI Solutions +AI12974,Data Scientist,54686,USD,54686,EN,FL,Ireland,S,Netherlands,50,"Scala, AWS, Python",Bachelor,1,Healthcare,2024-08-16,2024-10-05,1467,6.8,Machine Intelligence Group +AI12975,Principal Data Scientist,103836,EUR,88261,MI,CT,France,M,Argentina,0,"Azure, Python, Deep Learning",Bachelor,3,Manufacturing,2025-03-15,2025-04-14,2314,9.8,Machine Intelligence Group +AI12976,Machine Learning Researcher,80675,USD,80675,MI,FT,Ireland,S,Ireland,50,"Scala, Java, Kubernetes, Spark, Statistics",Bachelor,4,Retail,2024-05-18,2024-06-01,1182,6.5,DeepTech Ventures +AI12977,Computer Vision Engineer,96576,USD,96576,MI,FT,United States,S,Argentina,50,"GCP, Hadoop, SQL",PhD,4,Government,2024-09-16,2024-10-05,1345,7,Machine Intelligence Group +AI12978,AI Architect,186491,CAD,233114,EX,CT,Canada,L,Canada,0,"NLP, Docker, Tableau, Computer Vision",Associate,19,Consulting,2024-08-15,2024-10-07,912,9.7,DataVision Ltd +AI12979,ML Ops Engineer,112803,CHF,101523,EN,FL,Switzerland,M,Switzerland,0,"R, Tableau, Scala",Associate,1,Transportation,2025-04-13,2025-05-17,1292,5.9,Smart Analytics +AI12980,Data Scientist,66258,CAD,82823,EN,FL,Canada,S,Canada,50,"Scala, Python, Statistics",PhD,1,Manufacturing,2025-04-02,2025-06-01,1933,7.8,Smart Analytics +AI12981,AI Architect,122843,GBP,92132,MI,FL,United Kingdom,L,Ukraine,0,"SQL, Java, Python",PhD,4,Media,2024-01-28,2024-02-12,786,5.7,Autonomous Tech +AI12982,AI Research Scientist,70436,USD,70436,EX,PT,India,M,India,100,"NLP, PyTorch, Statistics, Linux",PhD,12,Finance,2024-10-06,2024-11-30,1345,6.4,Digital Transformation LLC +AI12983,Head of AI,111112,USD,111112,MI,FL,Sweden,L,United States,100,"Python, Tableau, SQL",Bachelor,2,Education,2024-08-27,2024-10-01,1822,8.5,Digital Transformation LLC +AI12984,NLP Engineer,62688,USD,62688,EN,FT,Ireland,S,Mexico,100,"Java, Docker, Statistics, Linux",Bachelor,0,Technology,2025-03-11,2025-03-31,1549,7.4,TechCorp Inc +AI12985,Principal Data Scientist,109993,AUD,148491,MI,FT,Australia,M,Australia,50,"MLOps, Git, NLP, Computer Vision",PhD,3,Energy,2024-01-04,2024-02-26,891,9,Quantum Computing Inc +AI12986,Robotics Engineer,90739,AUD,122498,MI,PT,Australia,M,Malaysia,100,"Computer Vision, NLP, MLOps, PyTorch, Docker",PhD,2,Retail,2024-09-13,2024-10-23,1603,8,TechCorp Inc +AI12987,NLP Engineer,116788,EUR,99270,SE,FL,France,M,France,50,"R, Kubernetes, Computer Vision, Hadoop, Docker",Associate,5,Education,2025-02-14,2025-03-14,2471,9.7,Quantum Computing Inc +AI12988,Data Scientist,89119,EUR,75751,MI,FL,Germany,M,Germany,100,"Hadoop, Linux, Tableau, Docker, Kubernetes",Bachelor,4,Telecommunications,2024-09-23,2024-11-23,2175,6.7,TechCorp Inc +AI12989,Machine Learning Engineer,80678,SGD,104881,MI,FT,Singapore,S,Singapore,100,"Git, SQL, Azure",Master,3,Real Estate,2025-04-23,2025-05-12,1070,9.1,Future Systems +AI12990,Head of AI,146187,EUR,124259,SE,PT,Austria,L,Austria,100,"SQL, MLOps, R",Associate,5,Education,2025-02-17,2025-04-21,1463,8.1,DataVision Ltd +AI12991,Machine Learning Engineer,77845,USD,77845,EX,CT,India,S,India,0,"GCP, Java, Data Visualization",PhD,12,Transportation,2024-02-29,2024-04-30,720,8.2,AI Innovations +AI12992,Autonomous Systems Engineer,73922,USD,73922,EN,FT,United States,M,United Kingdom,50,"TensorFlow, Python, Computer Vision, R, Hadoop",Bachelor,0,Healthcare,2024-01-13,2024-02-19,1487,5.1,Cloud AI Solutions +AI12993,Data Scientist,103867,EUR,88287,MI,PT,Netherlands,S,Netherlands,100,"Linux, Java, R",Master,2,Gaming,2024-06-24,2024-08-24,1252,5.4,DeepTech Ventures +AI12994,AI Research Scientist,125902,EUR,107017,EX,PT,France,S,France,50,"SQL, MLOps, Kubernetes, Mathematics, Computer Vision",PhD,13,Transportation,2025-02-07,2025-04-18,593,9.1,TechCorp Inc +AI12995,AI Architect,29129,USD,29129,MI,FT,India,M,India,0,"Spark, R, Hadoop",Associate,4,Automotive,2025-03-13,2025-04-11,1097,9.8,Digital Transformation LLC +AI12996,AI Software Engineer,43029,USD,43029,EN,PT,South Korea,S,South Korea,100,"Docker, Tableau, SQL",Bachelor,0,Healthcare,2024-02-03,2024-03-06,610,7.4,DeepTech Ventures +AI12997,Machine Learning Engineer,79088,USD,79088,EN,FT,Sweden,L,Sweden,0,"Data Visualization, Tableau, SQL, Mathematics",Bachelor,0,Media,2024-02-17,2024-04-13,1246,8.9,Advanced Robotics +AI12998,AI Specialist,49171,USD,49171,EN,FT,Sweden,S,Turkey,50,"Computer Vision, Python, MLOps",Bachelor,0,Automotive,2024-08-19,2024-09-27,1611,5.5,Digital Transformation LLC +AI12999,Data Analyst,62847,SGD,81701,EN,CT,Singapore,L,Singapore,100,"Git, TensorFlow, Tableau, Scala",PhD,1,Transportation,2024-01-01,2024-02-24,1985,7,Cognitive Computing +AI13000,AI Specialist,80522,USD,80522,SE,CT,South Korea,S,Ghana,100,"PyTorch, Docker, Azure, TensorFlow",Associate,6,Gaming,2025-03-11,2025-03-28,978,8.9,Quantum Computing Inc +AI13001,AI Consultant,64623,EUR,54930,EN,PT,Netherlands,S,Netherlands,50,"Mathematics, AWS, Docker, Statistics",PhD,0,Telecommunications,2024-04-15,2024-06-18,764,9.8,Quantum Computing Inc +AI13002,Machine Learning Engineer,138114,USD,138114,SE,CT,United States,S,United States,0,"MLOps, Linux, Kubernetes",PhD,8,Telecommunications,2024-07-17,2024-09-09,1795,5.7,Digital Transformation LLC +AI13003,AI Consultant,175938,AUD,237516,EX,FL,Australia,L,Australia,100,"Linux, Tableau, Git",Bachelor,12,Gaming,2024-05-23,2024-06-12,1700,9.3,Algorithmic Solutions +AI13004,Data Engineer,58622,USD,58622,EX,PT,China,S,Indonesia,0,"Hadoop, SQL, Computer Vision",Bachelor,17,Automotive,2025-04-30,2025-06-14,807,7.7,Future Systems +AI13005,Data Engineer,79766,GBP,59825,MI,FT,United Kingdom,M,United Kingdom,50,"Statistics, Java, TensorFlow, PyTorch, Computer Vision",PhD,4,Manufacturing,2024-05-13,2024-06-04,905,5.8,AI Innovations +AI13006,Machine Learning Researcher,89995,USD,89995,MI,CT,Norway,S,Norway,0,"TensorFlow, Statistics, R, Docker, Java",Bachelor,2,Government,2024-04-21,2024-06-17,641,5.6,Neural Networks Co +AI13007,NLP Engineer,160586,USD,160586,SE,FL,Ireland,L,Portugal,0,"Git, AWS, Mathematics",Master,7,Transportation,2024-06-17,2024-08-09,2063,6.9,Smart Analytics +AI13008,AI Specialist,109290,USD,109290,EX,FL,China,M,Switzerland,0,"Java, Python, Statistics, GCP, NLP",Master,11,Energy,2025-04-23,2025-05-13,2189,9.8,Cognitive Computing +AI13009,Robotics Engineer,222632,EUR,189237,EX,FL,Netherlands,M,Netherlands,0,"Azure, Kubernetes, GCP, SQL, Hadoop",Master,19,Finance,2024-11-13,2024-12-28,881,5.7,AI Innovations +AI13010,Research Scientist,154841,CHF,139357,MI,CT,Switzerland,L,Australia,0,"Hadoop, MLOps, Kubernetes, Java",Bachelor,4,Automotive,2024-06-24,2024-07-10,1923,6.5,Predictive Systems +AI13011,Machine Learning Engineer,350148,CHF,315133,EX,CT,Switzerland,M,Switzerland,0,"Java, Git, Azure",Associate,15,Finance,2024-08-24,2024-10-06,691,7.7,Smart Analytics +AI13012,AI Research Scientist,85240,USD,85240,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Hadoop, Mathematics",Bachelor,2,Finance,2025-01-09,2025-02-16,731,9.7,Future Systems +AI13013,Robotics Engineer,129453,GBP,97090,SE,FT,United Kingdom,M,United Kingdom,0,"MLOps, Git, Mathematics, Spark",Bachelor,7,Retail,2024-01-19,2024-03-26,2363,6.9,Predictive Systems +AI13014,Data Engineer,269378,SGD,350191,EX,FT,Singapore,M,Singapore,0,"NLP, Python, SQL, Data Visualization",Master,15,Energy,2024-07-27,2024-08-19,2033,8.8,AI Innovations +AI13015,Deep Learning Engineer,280599,USD,280599,EX,PT,Ireland,L,Ireland,0,"Linux, SQL, NLP, GCP",Master,16,Retail,2024-04-22,2024-07-02,893,7.5,DataVision Ltd +AI13016,Machine Learning Engineer,71137,EUR,60466,MI,FL,Netherlands,S,Netherlands,50,"Kubernetes, Computer Vision, SQL, Deep Learning, PyTorch",PhD,3,Education,2024-02-20,2024-03-14,676,9.4,Advanced Robotics +AI13017,Data Scientist,174913,EUR,148676,EX,CT,Netherlands,M,France,0,"NLP, Statistics, Hadoop",Bachelor,19,Manufacturing,2024-08-10,2024-09-04,840,5.5,Digital Transformation LLC +AI13018,Deep Learning Engineer,115630,USD,115630,SE,PT,Israel,S,Estonia,50,"Java, Data Visualization, Scala, Azure, GCP",Master,9,Gaming,2024-09-15,2024-10-26,2138,9.3,DataVision Ltd +AI13019,Robotics Engineer,70395,SGD,91514,EN,PT,Singapore,M,Singapore,100,"SQL, TensorFlow, Java, MLOps",Bachelor,0,Real Estate,2024-12-30,2025-01-20,1089,5.6,DeepTech Ventures +AI13020,Deep Learning Engineer,53458,EUR,45439,EN,FT,Austria,S,Austria,50,"TensorFlow, Python, MLOps, Statistics",Associate,0,Retail,2024-06-19,2024-07-15,1120,8.6,Smart Analytics +AI13021,AI Architect,28054,USD,28054,MI,FT,India,S,Nigeria,0,"Python, Java, TensorFlow",PhD,2,Technology,2024-04-12,2024-05-27,530,6.3,Machine Intelligence Group +AI13022,Head of AI,162934,EUR,138494,SE,CT,Germany,L,Philippines,0,"SQL, Data Visualization, Python, Azure",Master,7,Transportation,2024-09-18,2024-10-30,2064,7.5,Neural Networks Co +AI13023,NLP Engineer,111667,USD,111667,MI,FL,Norway,L,Norway,0,"NLP, Tableau, Azure, Git, Linux",Associate,3,Transportation,2025-01-06,2025-02-25,1817,9.1,Smart Analytics +AI13024,ML Ops Engineer,219405,EUR,186494,EX,FL,Netherlands,L,Netherlands,0,"Java, MLOps, TensorFlow, NLP, SQL",Master,14,Automotive,2024-03-05,2024-04-28,1117,6.1,Future Systems +AI13025,ML Ops Engineer,111552,USD,111552,MI,FL,Sweden,L,Sweden,50,"Scala, Python, GCP",Bachelor,2,Automotive,2024-05-15,2024-06-11,841,6.9,Advanced Robotics +AI13026,AI Consultant,123560,USD,123560,MI,PT,Norway,L,Norway,100,"Spark, Data Visualization, Azure, Java, Docker",Associate,2,Media,2024-04-24,2024-05-09,2045,7.7,Algorithmic Solutions +AI13027,AI Specialist,304170,USD,304170,EX,CT,Norway,M,Spain,50,"Python, Data Visualization, AWS, Docker, TensorFlow",Associate,17,Manufacturing,2024-04-28,2024-06-17,1464,8.9,Digital Transformation LLC +AI13028,AI Software Engineer,151323,USD,151323,EX,FL,South Korea,L,South Korea,0,"Python, TensorFlow, Data Visualization, Scala, AWS",PhD,10,Media,2024-11-14,2025-01-13,1035,5.6,Algorithmic Solutions +AI13029,Head of AI,57091,USD,57091,EN,FT,United States,S,United States,50,"R, Linux, Tableau, Git",PhD,1,Gaming,2024-03-13,2024-05-21,2015,7.2,Algorithmic Solutions +AI13030,Research Scientist,160113,USD,160113,SE,FL,Finland,L,Finland,0,"Kubernetes, Tableau, Computer Vision",Associate,6,Education,2024-09-02,2024-09-25,1518,5.5,Predictive Systems +AI13031,AI Consultant,69137,JPY,7605070,EN,PT,Japan,L,Japan,50,"Git, MLOps, Data Visualization, PyTorch, Azure",PhD,0,Consulting,2024-03-07,2024-05-15,1334,5.5,Future Systems +AI13032,Computer Vision Engineer,52465,AUD,70828,EN,FL,Australia,S,Canada,100,"Scala, Linux, AWS",PhD,0,Transportation,2025-02-12,2025-03-07,1863,7.9,TechCorp Inc +AI13033,Machine Learning Researcher,74221,JPY,8164310,MI,FT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization, Computer Vision",Associate,4,Retail,2025-02-17,2025-04-02,1139,5.2,AI Innovations +AI13034,Robotics Engineer,73237,USD,73237,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2024-02-22,2024-04-08,644,5.8,Quantum Computing Inc +AI13035,Data Scientist,116610,USD,116610,MI,FT,Finland,L,Finland,50,"Hadoop, SQL, Mathematics",PhD,2,Consulting,2024-06-17,2024-08-10,2042,5.3,Autonomous Tech +AI13036,AI Product Manager,155471,CAD,194339,SE,PT,Canada,L,Canada,50,"GCP, PyTorch, Java",Bachelor,8,Energy,2024-12-25,2025-01-17,1576,5.5,AI Innovations +AI13037,Robotics Engineer,53502,USD,53502,SE,CT,India,M,Finland,0,"PyTorch, TensorFlow, Tableau, AWS, Linux",Master,6,Government,2025-02-14,2025-04-24,2130,9.6,Machine Intelligence Group +AI13038,Autonomous Systems Engineer,174189,USD,174189,EX,PT,Ireland,L,United States,50,"R, Mathematics, Hadoop",PhD,16,Consulting,2024-10-05,2024-11-02,1656,8.7,Advanced Robotics +AI13039,Machine Learning Engineer,140960,SGD,183248,SE,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning, Java, R",PhD,9,Finance,2025-01-28,2025-03-07,2233,7.5,Smart Analytics +AI13040,Deep Learning Engineer,65603,SGD,85284,EN,PT,Singapore,S,Singapore,50,"Linux, AWS, Python",Associate,0,Finance,2024-08-01,2024-08-21,1584,5.1,Smart Analytics +AI13041,AI Specialist,280472,EUR,238401,EX,CT,Netherlands,L,Thailand,50,"R, NLP, Java, Data Visualization, Scala",PhD,17,Consulting,2024-07-30,2024-09-25,1827,6.7,Autonomous Tech +AI13042,Research Scientist,194338,EUR,165187,EX,CT,Germany,L,Philippines,100,"SQL, Hadoop, Kubernetes, Java, NLP",Master,17,Manufacturing,2025-01-31,2025-03-20,2167,5.9,Future Systems +AI13043,Autonomous Systems Engineer,162690,USD,162690,MI,FL,Norway,L,Norway,50,"Git, Linux, Docker",Associate,3,Real Estate,2025-04-08,2025-06-18,2084,6.3,TechCorp Inc +AI13044,Machine Learning Researcher,178197,USD,178197,SE,PT,Denmark,M,Colombia,0,"MLOps, Python, TensorFlow",Master,7,Media,2024-05-29,2024-07-07,2093,8.1,Cognitive Computing +AI13045,Machine Learning Researcher,75976,USD,75976,EX,FL,China,S,China,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,15,Transportation,2024-05-16,2024-07-28,1108,6,DeepTech Ventures +AI13046,Machine Learning Engineer,129457,JPY,14240270,SE,CT,Japan,S,Luxembourg,0,"Linux, Python, Git",Associate,8,Education,2024-01-04,2024-01-26,1084,9.9,Advanced Robotics +AI13047,Data Analyst,116495,CAD,145619,EX,FL,Canada,S,Canada,50,"Git, Python, SQL, Data Visualization, Spark",Bachelor,16,Consulting,2025-02-08,2025-03-31,1552,9.2,Neural Networks Co +AI13048,Head of AI,148839,USD,148839,EX,PT,Sweden,S,Sweden,0,"Hadoop, Spark, Deep Learning",Bachelor,17,Media,2024-03-17,2024-04-03,1358,5.5,DataVision Ltd +AI13049,AI Architect,123589,CHF,111230,MI,CT,Switzerland,M,Ireland,50,"Linux, Mathematics, Data Visualization, Docker, PyTorch",PhD,3,Government,2024-06-25,2024-08-22,1871,9.7,Advanced Robotics +AI13050,Deep Learning Engineer,83978,EUR,71381,EN,FT,France,L,France,50,"Python, Mathematics, Scala, Java, TensorFlow",PhD,1,Real Estate,2024-11-18,2024-12-21,1434,9.3,Algorithmic Solutions +AI13051,Principal Data Scientist,66441,EUR,56475,EN,PT,Germany,L,Germany,50,"Spark, Java, Statistics, R",PhD,0,Gaming,2024-08-28,2024-10-13,1565,6.3,TechCorp Inc +AI13052,Machine Learning Researcher,282786,EUR,240368,EX,PT,Netherlands,L,Netherlands,50,"Git, Python, TensorFlow",Master,14,Retail,2024-01-24,2024-03-14,1684,9.8,Predictive Systems +AI13053,Robotics Engineer,102501,CHF,92251,EN,FL,Switzerland,M,Switzerland,0,"SQL, GCP, Data Visualization, PyTorch, R",Master,1,Gaming,2024-09-07,2024-10-01,975,7.9,Cognitive Computing +AI13054,AI Software Engineer,71975,USD,71975,EN,FT,United States,M,Turkey,50,"AWS, Mathematics, Scala, Hadoop",Bachelor,1,Real Estate,2025-03-11,2025-04-05,2168,9.1,Smart Analytics +AI13055,Robotics Engineer,66498,USD,66498,MI,CT,South Korea,M,South Korea,0,"MLOps, PyTorch, Spark, NLP",PhD,3,Manufacturing,2024-07-07,2024-07-22,1418,7.1,Predictive Systems +AI13056,Research Scientist,88009,EUR,74808,EN,FT,Germany,L,Germany,0,"R, SQL, Azure",PhD,1,Technology,2025-03-09,2025-04-20,2288,5.1,DeepTech Ventures +AI13057,AI Consultant,163347,USD,163347,MI,CT,Norway,L,Ireland,100,"GCP, Python, Java, Docker",Master,4,Energy,2024-11-02,2024-11-25,984,8.5,Advanced Robotics +AI13058,Principal Data Scientist,80967,GBP,60725,EN,CT,United Kingdom,L,Luxembourg,100,"Deep Learning, Linux, Python, Hadoop",Associate,1,Technology,2024-11-01,2024-12-16,2453,5,Advanced Robotics +AI13059,AI Architect,108015,EUR,91813,MI,FL,Germany,M,Hungary,0,"Kubernetes, SQL, MLOps, Docker",Associate,4,Telecommunications,2024-08-15,2024-10-11,549,10,Future Systems +AI13060,AI Research Scientist,237965,USD,237965,EX,FT,Norway,L,Norway,100,"Tableau, MLOps, SQL, Linux, Java",Associate,12,Automotive,2024-09-18,2024-10-30,760,9.4,DeepTech Ventures +AI13061,Computer Vision Engineer,48996,USD,48996,MI,FL,China,L,China,100,"Java, Linux, Python",Associate,3,Manufacturing,2024-12-13,2025-01-22,2075,6.9,DeepTech Ventures +AI13062,Machine Learning Engineer,293914,CHF,264523,EX,CT,Switzerland,L,Estonia,50,"Statistics, Python, Linux",Bachelor,16,Manufacturing,2025-03-04,2025-04-15,1936,8.8,Algorithmic Solutions +AI13063,Research Scientist,68050,USD,68050,EN,FT,Ireland,M,Ireland,0,"Statistics, GCP, Deep Learning, Java, Python",Master,1,Healthcare,2024-12-29,2025-01-13,620,7,Digital Transformation LLC +AI13064,Machine Learning Researcher,66356,USD,66356,EN,PT,Ireland,M,Ireland,100,"Data Visualization, Docker, Python",Associate,0,Real Estate,2024-03-31,2024-05-26,1050,6.3,Cognitive Computing +AI13065,Data Analyst,68146,USD,68146,EN,FL,Finland,L,Thailand,0,"Python, Scala, Tableau",Associate,1,Real Estate,2024-09-20,2024-11-21,733,5.9,TechCorp Inc +AI13066,Data Scientist,133642,CAD,167053,SE,PT,Canada,L,Canada,50,"PyTorch, Statistics, Azure, Python",Bachelor,8,Technology,2025-04-27,2025-05-15,1623,5.8,Machine Intelligence Group +AI13067,AI Software Engineer,53834,USD,53834,SE,FT,China,M,China,0,"Git, GCP, Docker",Master,9,Government,2025-04-01,2025-06-03,2469,7.3,Cloud AI Solutions +AI13068,Head of AI,38246,USD,38246,EN,CT,South Korea,S,Turkey,100,"Git, Docker, SQL, Deep Learning, GCP",Master,1,Automotive,2024-06-15,2024-07-29,2133,7.9,Future Systems +AI13069,NLP Engineer,87601,JPY,9636110,EN,FL,Japan,L,Malaysia,0,"Spark, Git, Kubernetes",Master,1,Retail,2024-02-26,2024-04-05,521,6.7,AI Innovations +AI13070,AI Research Scientist,83658,AUD,112938,MI,FT,Australia,L,Australia,0,"Linux, TensorFlow, Hadoop, PyTorch",Associate,3,Healthcare,2024-06-30,2024-08-28,2162,5.8,Predictive Systems +AI13071,Robotics Engineer,109147,AUD,147348,SE,CT,Australia,S,Australia,0,"Mathematics, Git, Deep Learning, Spark, Linux",Associate,9,Transportation,2024-09-15,2024-10-26,1351,5.6,AI Innovations +AI13072,AI Specialist,61946,USD,61946,EN,PT,Israel,L,Vietnam,100,"Linux, Kubernetes, PyTorch",Associate,1,Technology,2025-04-19,2025-05-16,1210,6.7,AI Innovations +AI13073,Data Scientist,343823,CHF,309441,EX,CT,Switzerland,L,United Kingdom,0,"SQL, Docker, TensorFlow",PhD,16,Manufacturing,2024-07-14,2024-09-24,1773,6.3,Future Systems +AI13074,Data Analyst,109859,USD,109859,MI,PT,Norway,L,Denmark,50,"GCP, Docker, Computer Vision, Kubernetes, Linux",Master,4,Automotive,2024-05-04,2024-06-20,1533,7.7,Machine Intelligence Group +AI13075,Machine Learning Researcher,186936,EUR,158896,EX,CT,Germany,S,Germany,100,"GCP, AWS, MLOps, TensorFlow, Deep Learning",Bachelor,14,Automotive,2024-06-01,2024-06-16,1693,6,Quantum Computing Inc +AI13076,AI Specialist,56525,EUR,48046,EN,PT,France,M,France,50,"GCP, SQL, Data Visualization, Hadoop",Associate,1,Real Estate,2024-09-21,2024-10-26,715,5.9,Neural Networks Co +AI13077,Data Scientist,65610,CAD,82013,EN,FT,Canada,S,Canada,100,"Azure, Kubernetes, SQL, Docker",PhD,1,Education,2025-01-22,2025-02-18,642,6.6,Advanced Robotics +AI13078,Research Scientist,66543,USD,66543,EN,CT,Sweden,L,Sweden,50,"Data Visualization, Spark, TensorFlow, Java",Master,1,Education,2025-02-12,2025-03-17,1971,5.9,Cloud AI Solutions +AI13079,Head of AI,95195,GBP,71396,EN,CT,United Kingdom,L,Switzerland,50,"Statistics, PyTorch, SQL, GCP, Docker",Master,1,Education,2024-07-27,2024-08-27,1362,8.4,Predictive Systems +AI13080,Data Engineer,88191,USD,88191,MI,CT,Norway,S,Norway,0,"Java, Deep Learning, Python",PhD,2,Telecommunications,2024-09-30,2024-12-08,788,7.8,Machine Intelligence Group +AI13081,AI Software Engineer,85673,USD,85673,MI,FL,Finland,S,Finland,0,"Python, Hadoop, TensorFlow, Linux",PhD,4,Healthcare,2024-10-02,2024-10-17,917,5.6,Advanced Robotics +AI13082,Computer Vision Engineer,250835,USD,250835,EX,FT,Finland,L,Finland,0,"Hadoop, MLOps, R, Python",Master,14,Retail,2025-04-22,2025-07-03,918,9.8,Machine Intelligence Group +AI13083,Machine Learning Engineer,65750,EUR,55888,MI,FT,Austria,S,Austria,50,"Tableau, TensorFlow, Python, NLP, R",PhD,3,Automotive,2025-04-03,2025-05-27,2456,8.9,Future Systems +AI13084,Principal Data Scientist,96483,USD,96483,MI,PT,Norway,M,Norway,0,"Python, Kubernetes, Azure, Statistics, Linux",PhD,2,Media,2024-02-05,2024-02-28,605,8.1,TechCorp Inc +AI13085,Principal Data Scientist,111619,EUR,94876,MI,PT,Germany,L,Japan,0,"Computer Vision, PyTorch, NLP, TensorFlow, Kubernetes",Associate,3,Consulting,2025-03-10,2025-04-05,967,5.3,Machine Intelligence Group +AI13086,Data Analyst,68910,USD,68910,MI,FT,Sweden,S,France,100,"SQL, GCP, Tableau, TensorFlow",Associate,2,Technology,2024-04-12,2024-05-02,2143,6.5,Quantum Computing Inc +AI13087,Research Scientist,32232,USD,32232,MI,FL,India,M,Finland,0,"Linux, AWS, Hadoop, SQL",Master,4,Energy,2024-08-15,2024-10-12,1713,8.9,Digital Transformation LLC +AI13088,AI Product Manager,85895,USD,85895,MI,PT,South Korea,L,South Korea,100,"MLOps, Scala, Docker, AWS, Spark",Associate,4,Gaming,2024-07-16,2024-09-18,1126,5,Machine Intelligence Group +AI13089,AI Research Scientist,151896,EUR,129112,EX,PT,Netherlands,S,United Kingdom,100,"Kubernetes, Java, Scala",Associate,18,Media,2024-07-14,2024-09-15,2330,6.7,Advanced Robotics +AI13090,Computer Vision Engineer,282442,USD,282442,EX,CT,United States,M,United States,100,"SQL, Spark, Python, Docker",Master,15,Technology,2024-02-23,2024-03-25,1246,9.6,Autonomous Tech +AI13091,Data Analyst,132020,USD,132020,SE,PT,United States,M,United States,100,"SQL, Java, AWS, Spark",PhD,9,Transportation,2024-10-22,2024-12-30,1902,8.7,TechCorp Inc +AI13092,AI Research Scientist,118211,EUR,100479,SE,PT,Austria,S,Austria,50,"Hadoop, Mathematics, Python, Scala, TensorFlow",Associate,7,Government,2024-11-04,2024-12-26,1773,8.1,Neural Networks Co +AI13093,Machine Learning Engineer,95484,USD,95484,MI,FT,Sweden,L,Sweden,50,"Linux, Azure, Kubernetes, AWS, SQL",PhD,3,Media,2024-12-31,2025-02-19,2495,8,Cloud AI Solutions +AI13094,Deep Learning Engineer,211850,SGD,275405,EX,PT,Singapore,M,Singapore,50,"Tableau, Python, Linux, Computer Vision, TensorFlow",Master,11,Technology,2024-05-22,2024-06-19,1157,5.6,Advanced Robotics +AI13095,Research Scientist,120477,USD,120477,MI,PT,Denmark,S,Canada,0,"GCP, Kubernetes, TensorFlow, Spark, Data Visualization",PhD,4,Telecommunications,2024-11-21,2024-12-15,701,7.1,Predictive Systems +AI13096,NLP Engineer,218123,USD,218123,EX,FT,Ireland,M,Vietnam,0,"GCP, Azure, Python",Bachelor,17,Energy,2025-03-17,2025-04-24,1056,5.3,Advanced Robotics +AI13097,AI Software Engineer,98570,USD,98570,MI,FT,Sweden,M,Russia,100,"Scala, Computer Vision, Azure, Mathematics, Data Visualization",Master,2,Technology,2024-06-21,2024-08-03,672,8.2,Autonomous Tech +AI13098,AI Architect,81790,USD,81790,MI,FL,Israel,L,Thailand,50,"SQL, Kubernetes, Hadoop, PyTorch, GCP",Bachelor,4,Media,2024-06-30,2024-08-17,830,7.7,Digital Transformation LLC +AI13099,NLP Engineer,91536,CAD,114420,MI,FT,Canada,L,Canada,100,"Spark, Linux, TensorFlow, MLOps, Java",PhD,2,Real Estate,2024-04-11,2024-05-08,1728,9.3,Cognitive Computing +AI13100,AI Specialist,116205,EUR,98774,SE,PT,Austria,M,Austria,0,"Java, SQL, Data Visualization",Bachelor,8,Media,2025-01-23,2025-03-26,2388,9.5,Predictive Systems +AI13101,Principal Data Scientist,58576,EUR,49790,EN,CT,France,M,Hungary,100,"Docker, Linux, Data Visualization, GCP",PhD,0,Transportation,2024-09-13,2024-10-14,2244,7.6,Advanced Robotics +AI13102,AI Software Engineer,106840,CHF,96156,MI,PT,Switzerland,S,Switzerland,0,"Spark, Scala, SQL, Statistics, Deep Learning",Bachelor,4,Transportation,2024-10-09,2024-12-14,862,9.3,Future Systems +AI13103,Computer Vision Engineer,123259,CAD,154074,SE,FL,Canada,L,Canada,50,"Data Visualization, NLP, R",Associate,9,Automotive,2024-07-12,2024-08-10,1202,9.9,Predictive Systems +AI13104,Deep Learning Engineer,88273,JPY,9710030,MI,PT,Japan,M,Australia,50,"NLP, Docker, Computer Vision, SQL",Master,2,Real Estate,2024-04-08,2024-05-04,775,8.3,Cloud AI Solutions +AI13105,AI Specialist,133522,USD,133522,SE,PT,Denmark,M,Turkey,100,"Mathematics, R, Linux, Java",Associate,9,Finance,2024-12-28,2025-02-08,1878,6.2,Predictive Systems +AI13106,AI Consultant,159549,USD,159549,EX,FL,Finland,L,Finland,100,"Linux, PyTorch, MLOps, Java, Kubernetes",PhD,13,Media,2024-03-04,2024-04-15,1430,8.6,Machine Intelligence Group +AI13107,ML Ops Engineer,106103,CAD,132629,SE,FT,Canada,M,Canada,50,"Hadoop, PyTorch, MLOps",PhD,5,Automotive,2024-10-23,2024-12-21,1229,7.9,TechCorp Inc +AI13108,AI Consultant,98258,EUR,83519,SE,FL,France,M,France,50,"Docker, AWS, Tableau, Git",Associate,5,Telecommunications,2024-03-24,2024-05-25,2457,5.9,Cognitive Computing +AI13109,Autonomous Systems Engineer,125492,USD,125492,EX,FT,Ireland,S,Ireland,100,"Spark, Scala, MLOps, Linux",PhD,14,Retail,2025-03-27,2025-05-12,1351,8.2,Predictive Systems +AI13110,AI Research Scientist,166393,EUR,141434,EX,PT,Austria,S,Egypt,100,"AWS, Kubernetes, MLOps",Associate,15,Finance,2025-02-09,2025-04-20,1894,5.5,Neural Networks Co +AI13111,ML Ops Engineer,86105,EUR,73189,MI,FT,Austria,M,Austria,0,"Linux, Java, R, GCP",Bachelor,4,Healthcare,2024-08-27,2024-10-28,2399,7.6,Cloud AI Solutions +AI13112,Data Engineer,125111,USD,125111,SE,FT,Finland,S,Finland,0,"Scala, SQL, Mathematics, Statistics, Linux",Associate,5,Manufacturing,2024-01-14,2024-03-27,1070,5,DataVision Ltd +AI13113,ML Ops Engineer,103754,USD,103754,MI,FT,Sweden,M,Egypt,100,"Docker, Deep Learning, Python, Computer Vision, Git",Associate,2,Consulting,2025-04-22,2025-05-20,731,5.5,Machine Intelligence Group +AI13114,Research Scientist,65132,USD,65132,EN,PT,Sweden,M,Mexico,100,"Docker, Statistics, R, PyTorch, TensorFlow",Bachelor,1,Education,2025-04-16,2025-05-22,1489,9.5,DataVision Ltd +AI13115,AI Architect,195654,CHF,176089,EX,FT,Switzerland,S,Switzerland,100,"SQL, MLOps, Scala",Bachelor,11,Consulting,2024-06-08,2024-07-12,658,6.5,Autonomous Tech +AI13116,Data Engineer,65035,EUR,55280,EN,FL,Austria,S,Philippines,0,"TensorFlow, Data Visualization, Tableau, Scala",Associate,0,Energy,2024-11-12,2025-01-23,1952,9.1,Cognitive Computing +AI13117,AI Product Manager,248091,EUR,210877,EX,CT,France,L,France,50,"Statistics, Spark, SQL, Hadoop",PhD,15,Energy,2024-10-10,2024-12-10,860,5.9,Autonomous Tech +AI13118,Robotics Engineer,141327,EUR,120128,SE,FL,Austria,M,Philippines,0,"GCP, PyTorch, TensorFlow",Bachelor,9,Media,2024-07-29,2024-08-29,1588,7.3,Cloud AI Solutions +AI13119,Data Engineer,343050,USD,343050,EX,PT,Denmark,L,Denmark,100,"MLOps, Kubernetes, SQL",Associate,13,Media,2024-10-26,2024-11-26,1308,5.8,Cloud AI Solutions +AI13120,NLP Engineer,169592,USD,169592,SE,FL,Norway,M,Estonia,0,"Spark, SQL, Data Visualization, Deep Learning",Master,6,Education,2024-12-23,2025-01-27,1423,8.5,Quantum Computing Inc +AI13121,Computer Vision Engineer,73049,EUR,62092,EN,PT,Germany,M,Canada,0,"Mathematics, AWS, SQL",Master,0,Transportation,2024-09-25,2024-11-30,1971,5.8,Quantum Computing Inc +AI13122,Data Analyst,107795,USD,107795,MI,FT,United States,L,United States,0,"R, SQL, AWS",PhD,3,Education,2024-11-18,2024-12-29,1861,9.3,DataVision Ltd +AI13123,Principal Data Scientist,103946,AUD,140327,SE,FT,Australia,M,Australia,100,"Tableau, Python, Statistics",Master,6,Education,2024-10-15,2024-11-09,645,6.3,AI Innovations +AI13124,AI Specialist,141419,JPY,15556090,SE,PT,Japan,S,Japan,100,"Python, MLOps, TensorFlow, Kubernetes, Docker",Master,5,Finance,2024-09-20,2024-10-14,1712,5.6,Neural Networks Co +AI13125,Robotics Engineer,56273,USD,56273,SE,FT,China,S,China,0,"Linux, Python, TensorFlow, Computer Vision",Associate,8,Healthcare,2024-03-03,2024-03-21,1241,8.3,Cloud AI Solutions +AI13126,ML Ops Engineer,225699,AUD,304694,EX,FL,Australia,S,Australia,50,"Linux, Spark, Git, Mathematics, Python",Bachelor,18,Transportation,2024-06-09,2024-07-01,834,7.2,Cognitive Computing +AI13127,Autonomous Systems Engineer,191962,USD,191962,EX,FT,Israel,S,Israel,100,"Tableau, AWS, Statistics",Master,12,Technology,2025-03-15,2025-05-19,1939,9.3,DataVision Ltd +AI13128,Robotics Engineer,65172,EUR,55396,EN,PT,Austria,L,Austria,100,"Docker, Kubernetes, Java, R, Hadoop",PhD,0,Consulting,2024-05-13,2024-07-13,2202,6.3,DataVision Ltd +AI13129,Data Engineer,152054,AUD,205273,SE,FL,Australia,L,Australia,50,"Python, Kubernetes, R, Mathematics",Bachelor,8,Finance,2024-06-24,2024-08-02,685,10,Smart Analytics +AI13130,AI Product Manager,27800,USD,27800,EN,FT,India,M,Kenya,100,"AWS, Git, Python, SQL, Statistics",PhD,1,Media,2024-06-19,2024-08-28,2359,5.1,DataVision Ltd +AI13131,ML Ops Engineer,87373,AUD,117954,MI,PT,Australia,S,Australia,0,"Linux, Git, Scala, R",Master,3,Education,2024-03-01,2024-04-23,1287,9.8,DataVision Ltd +AI13132,AI Product Manager,121517,USD,121517,EX,FL,China,L,China,50,"Computer Vision, Git, MLOps, Tableau",Bachelor,17,Retail,2024-01-02,2024-01-26,714,5.2,Neural Networks Co +AI13133,Principal Data Scientist,95651,USD,95651,MI,FL,Sweden,S,Turkey,100,"GCP, Tableau, Spark",Master,4,Retail,2024-05-05,2024-06-09,1097,6.3,Quantum Computing Inc +AI13134,NLP Engineer,135229,EUR,114945,SE,CT,Germany,S,Singapore,0,"GCP, Docker, Tableau, Linux",Associate,5,Finance,2024-03-03,2024-04-19,1628,7.6,Predictive Systems +AI13135,Machine Learning Researcher,59742,USD,59742,EN,CT,South Korea,L,Italy,0,"Docker, Python, NLP, Kubernetes, Data Visualization",Associate,1,Automotive,2025-03-08,2025-05-01,2448,6.7,Predictive Systems +AI13136,Head of AI,285325,AUD,385189,EX,CT,Australia,L,Ireland,100,"Scala, Spark, GCP, Deep Learning, MLOps",Associate,14,Finance,2024-02-01,2024-03-18,1668,5.3,Cognitive Computing +AI13137,Machine Learning Engineer,177700,GBP,133275,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Python",PhD,14,Retail,2024-03-13,2024-05-11,504,8.2,Quantum Computing Inc +AI13138,AI Architect,129173,USD,129173,MI,PT,United States,L,United States,50,"Scala, MLOps, Spark, NLP",PhD,2,Technology,2024-08-20,2024-10-29,1608,6,Predictive Systems +AI13139,AI Product Manager,124365,EUR,105710,SE,FL,Germany,L,Germany,100,"Statistics, AWS, Java",Master,5,Real Estate,2025-03-21,2025-05-30,2132,9.4,Digital Transformation LLC +AI13140,Data Scientist,28510,USD,28510,EN,CT,India,L,India,100,"TensorFlow, Scala, Java, Python",Associate,0,Manufacturing,2024-01-19,2024-04-01,514,7.1,Future Systems +AI13141,Autonomous Systems Engineer,147366,AUD,198944,SE,CT,Australia,L,India,50,"PyTorch, AWS, TensorFlow, SQL",Master,8,Government,2024-05-16,2024-06-30,2032,9.6,Smart Analytics +AI13142,Data Engineer,54967,EUR,46722,EN,PT,Netherlands,S,Netherlands,0,"Linux, SQL, TensorFlow, Deep Learning, AWS",Master,1,Education,2024-03-17,2024-04-05,1683,6.5,AI Innovations +AI13143,Machine Learning Researcher,56049,EUR,47642,EN,PT,France,S,France,50,"Kubernetes, Linux, Git, Azure, Mathematics",Bachelor,0,Government,2024-09-14,2024-10-18,1354,8.9,Machine Intelligence Group +AI13144,Data Scientist,50627,USD,50627,EN,CT,Ireland,S,Ireland,100,"AWS, Git, Python",Bachelor,0,Finance,2024-09-29,2024-10-22,767,7,Quantum Computing Inc +AI13145,Principal Data Scientist,129562,JPY,14251820,SE,PT,Japan,L,Japan,100,"Deep Learning, Azure, NLP, Python",PhD,7,Media,2024-12-02,2024-12-22,1863,7.5,Smart Analytics +AI13146,Autonomous Systems Engineer,86193,USD,86193,MI,FL,Finland,M,Finland,50,"Kubernetes, Statistics, Python",Bachelor,2,Automotive,2024-03-16,2024-04-19,855,8.9,Quantum Computing Inc +AI13147,AI Research Scientist,242707,CAD,303384,EX,PT,Canada,L,Canada,50,"Python, Spark, PyTorch, R",Associate,13,Telecommunications,2025-02-19,2025-03-22,1183,5.7,Quantum Computing Inc +AI13148,Data Engineer,22180,USD,22180,EN,FL,China,S,China,100,"Statistics, Data Visualization, Git, Linux",Bachelor,1,Energy,2024-05-22,2024-08-01,2339,8.8,Digital Transformation LLC +AI13149,Computer Vision Engineer,144736,CHF,130262,MI,CT,Switzerland,L,Switzerland,50,"Git, Docker, Azure",Associate,2,Telecommunications,2024-10-23,2024-12-31,2474,8.9,Predictive Systems +AI13150,Data Scientist,89075,EUR,75714,MI,FT,Netherlands,M,Brazil,100,"Mathematics, SQL, NLP, Computer Vision",Associate,4,Telecommunications,2024-02-06,2024-04-17,1369,8.4,Algorithmic Solutions +AI13151,Research Scientist,146125,JPY,16073750,SE,CT,Japan,M,Vietnam,100,"Scala, Statistics, Azure",Bachelor,5,Manufacturing,2024-01-11,2024-02-22,1903,8.1,Quantum Computing Inc +AI13152,Data Analyst,57872,EUR,49191,EN,FT,France,S,Czech Republic,50,"Scala, Docker, Statistics, Spark",Master,1,Healthcare,2024-12-22,2025-01-06,1208,9.7,Cognitive Computing +AI13153,Machine Learning Researcher,49720,USD,49720,EX,PT,India,M,Finland,100,"Deep Learning, Python, Tableau",Master,16,Retail,2024-10-19,2024-11-05,1858,8.1,AI Innovations +AI13154,AI Architect,94893,USD,94893,EX,FL,China,S,Germany,50,"Docker, Python, AWS, TensorFlow",Master,11,Manufacturing,2024-08-29,2024-11-07,1073,6.1,AI Innovations +AI13155,NLP Engineer,124615,EUR,105923,SE,PT,Austria,S,Austria,100,"Git, SQL, Java",Bachelor,6,Retail,2025-01-30,2025-04-03,911,5.3,DeepTech Ventures +AI13156,Data Analyst,136314,CHF,122683,SE,CT,Switzerland,S,Switzerland,50,"Docker, R, AWS",PhD,7,Telecommunications,2024-04-19,2024-06-25,1481,6,Advanced Robotics +AI13157,Deep Learning Engineer,60206,EUR,51175,EN,FL,France,S,Philippines,50,"Data Visualization, Linux, Tableau",Associate,0,Consulting,2024-12-01,2025-01-06,912,8.4,DataVision Ltd +AI13158,AI Product Manager,99753,USD,99753,MI,FT,Ireland,M,Denmark,100,"SQL, Scala, Linux",Associate,2,Consulting,2025-04-13,2025-05-07,1352,9.4,DataVision Ltd +AI13159,Machine Learning Engineer,93871,AUD,126726,SE,FL,Australia,S,Australia,100,"Scala, Java, AWS",Bachelor,5,Finance,2025-04-15,2025-05-10,2344,9.1,Cognitive Computing +AI13160,Data Scientist,116623,EUR,99130,EX,PT,France,S,India,100,"AWS, NLP, MLOps, Linux, GCP",Bachelor,14,Retail,2024-07-12,2024-08-02,825,8.8,Quantum Computing Inc +AI13161,Robotics Engineer,102693,SGD,133501,SE,CT,Singapore,S,Singapore,100,"Tableau, R, Linux, Java, PyTorch",Master,5,Automotive,2024-05-27,2024-06-21,1700,8,Predictive Systems +AI13162,Head of AI,62122,USD,62122,EN,PT,Finland,M,Finland,100,"Spark, Scala, Azure, Statistics, MLOps",Bachelor,1,Gaming,2024-04-08,2024-06-05,854,8.2,Autonomous Tech +AI13163,NLP Engineer,58719,USD,58719,SE,CT,China,L,China,100,"Python, MLOps, Scala, Computer Vision, Statistics",Master,8,Real Estate,2025-03-01,2025-05-03,2172,9.7,Machine Intelligence Group +AI13164,AI Software Engineer,59864,USD,59864,EN,CT,Sweden,M,Mexico,50,"Deep Learning, SQL, Data Visualization, MLOps, PyTorch",PhD,1,Real Estate,2024-09-30,2024-10-16,906,9.1,DataVision Ltd +AI13165,Data Engineer,248769,CHF,223892,EX,CT,Switzerland,L,Switzerland,50,"Python, TensorFlow, SQL, Docker, AWS",Associate,12,Real Estate,2025-04-23,2025-05-09,1869,9.4,Algorithmic Solutions +AI13166,Head of AI,100787,USD,100787,MI,FL,Israel,L,Colombia,0,"Hadoop, Kubernetes, SQL, Computer Vision",Master,2,Media,2024-03-18,2024-04-12,878,9.6,Predictive Systems +AI13167,Deep Learning Engineer,90501,EUR,76926,MI,PT,Germany,L,Germany,50,"GCP, MLOps, Azure",Associate,4,Finance,2025-03-13,2025-04-12,1900,7.7,Advanced Robotics +AI13168,AI Product Manager,98721,USD,98721,MI,FT,Sweden,M,Belgium,50,"Data Visualization, PyTorch, NLP",Associate,3,Automotive,2024-09-17,2024-10-20,1279,6.1,Quantum Computing Inc +AI13169,ML Ops Engineer,216873,USD,216873,EX,FT,Sweden,L,Sweden,0,"TensorFlow, Linux, MLOps, Computer Vision",PhD,11,Automotive,2024-04-17,2024-06-14,500,9.5,Quantum Computing Inc +AI13170,AI Consultant,51793,EUR,44024,EN,PT,Austria,S,South Africa,50,"Statistics, Mathematics, GCP, Spark",Bachelor,1,Healthcare,2024-10-12,2024-11-27,625,9.8,Quantum Computing Inc +AI13171,Machine Learning Engineer,89005,EUR,75654,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Mathematics, NLP",Master,3,Telecommunications,2025-04-02,2025-04-29,1954,5.2,DeepTech Ventures +AI13172,Data Analyst,112200,USD,112200,SE,FL,Israel,M,Israel,100,"TensorFlow, Scala, Mathematics",Associate,9,Consulting,2025-01-13,2025-03-09,1087,5.2,TechCorp Inc +AI13173,AI Product Manager,93493,USD,93493,MI,FL,Ireland,S,Switzerland,50,"TensorFlow, Python, Tableau, Deep Learning",Bachelor,4,Technology,2024-09-14,2024-09-29,1688,5.5,TechCorp Inc +AI13174,Machine Learning Researcher,150175,AUD,202736,EX,PT,Australia,M,Australia,100,"Java, R, SQL",Master,17,Government,2024-12-20,2025-02-24,2485,8.3,TechCorp Inc +AI13175,AI Research Scientist,66666,CAD,83333,EN,CT,Canada,L,China,100,"Linux, TensorFlow, Deep Learning, Python",Associate,0,Finance,2024-07-05,2024-09-02,1773,6.9,Future Systems +AI13176,Robotics Engineer,101266,USD,101266,MI,FT,Finland,L,Finland,100,"MLOps, Git, Python, Statistics, Linux",PhD,4,Education,2024-09-13,2024-10-30,1769,5.8,Digital Transformation LLC +AI13177,Autonomous Systems Engineer,76613,USD,76613,EN,FT,United States,M,United States,50,"Linux, Java, TensorFlow, MLOps",Master,1,Telecommunications,2024-08-02,2024-09-02,1973,8.5,Digital Transformation LLC +AI13178,Machine Learning Researcher,49536,USD,49536,EX,PT,India,S,Austria,50,"Spark, Docker, R, Deep Learning",PhD,18,Real Estate,2024-11-24,2024-12-24,2071,8.5,Digital Transformation LLC +AI13179,Deep Learning Engineer,61260,USD,61260,SE,CT,China,L,China,0,"Scala, R, Python",Master,9,Automotive,2025-01-07,2025-03-04,859,6.5,Cognitive Computing +AI13180,AI Specialist,149430,USD,149430,EX,PT,Finland,L,Argentina,100,"R, Python, Java, PyTorch, Tableau",Associate,14,Media,2024-12-09,2024-12-29,1331,7.2,Neural Networks Co +AI13181,Data Scientist,123078,EUR,104616,SE,FT,Austria,L,Austria,0,"Docker, Git, Deep Learning, Statistics, Hadoop",Bachelor,6,Education,2024-08-21,2024-10-24,1714,9.4,Advanced Robotics +AI13182,Machine Learning Engineer,70132,EUR,59612,MI,FL,Austria,S,Thailand,0,"Computer Vision, NLP, Python",Bachelor,2,Automotive,2025-04-22,2025-05-12,1803,9.6,Future Systems +AI13183,Data Analyst,141806,USD,141806,MI,PT,United States,L,United States,100,"MLOps, Kubernetes, GCP, R",Associate,2,Energy,2025-01-03,2025-03-08,818,5.4,Smart Analytics +AI13184,AI Specialist,111124,USD,111124,EX,PT,China,M,Germany,50,"Python, Data Visualization, TensorFlow, Java",Associate,10,Consulting,2024-04-15,2024-05-07,1584,5.1,Predictive Systems +AI13185,Deep Learning Engineer,152448,EUR,129581,EX,FL,Germany,S,Germany,100,"GCP, Hadoop, NLP, Tableau, Computer Vision",PhD,10,Gaming,2024-06-20,2024-08-06,1048,6.7,Cloud AI Solutions +AI13186,ML Ops Engineer,147859,EUR,125680,EX,FL,Germany,S,Germany,0,"Kubernetes, Tableau, AWS, Computer Vision",PhD,13,Energy,2024-03-20,2024-04-04,1994,5.9,AI Innovations +AI13187,AI Architect,71833,CAD,89791,MI,FT,Canada,M,Belgium,100,"Java, SQL, Spark",Master,4,Telecommunications,2024-09-15,2024-11-25,2415,8.3,Predictive Systems +AI13188,Autonomous Systems Engineer,265945,USD,265945,EX,CT,Denmark,L,Denmark,0,"Data Visualization, AWS, Tableau",PhD,13,Real Estate,2024-02-05,2024-04-10,1051,8.5,Smart Analytics +AI13189,Deep Learning Engineer,182312,EUR,154965,EX,PT,Austria,L,Austria,100,"Python, Data Visualization, Statistics, MLOps",PhD,18,Telecommunications,2024-11-19,2024-12-11,1525,7.7,Smart Analytics +AI13190,Robotics Engineer,81783,USD,81783,MI,FL,Ireland,M,Israel,0,"Hadoop, Mathematics, MLOps",Master,2,Energy,2024-11-18,2025-01-03,1787,5.5,Cognitive Computing +AI13191,Computer Vision Engineer,283095,JPY,31140450,EX,PT,Japan,L,Japan,50,"Computer Vision, Python, MLOps, PyTorch",Bachelor,12,Manufacturing,2024-08-02,2024-08-28,2074,5.4,Future Systems +AI13192,AI Research Scientist,140169,EUR,119144,SE,CT,Austria,M,Austria,100,"PyTorch, Data Visualization, SQL",PhD,5,Retail,2025-01-20,2025-02-22,1103,7.7,Cognitive Computing +AI13193,Deep Learning Engineer,55566,EUR,47231,EN,CT,France,S,France,50,"Hadoop, Scala, Java",PhD,0,Energy,2024-06-03,2024-07-12,2240,7.9,Advanced Robotics +AI13194,ML Ops Engineer,312518,CHF,281266,EX,PT,Switzerland,L,New Zealand,50,"Python, GCP, NLP, SQL",Master,17,Finance,2024-09-23,2024-12-01,2430,5.9,Cloud AI Solutions +AI13195,Data Analyst,42317,USD,42317,EN,PT,South Korea,S,Russia,0,"GCP, Python, Git",Associate,0,Education,2025-02-05,2025-03-17,1394,10,Smart Analytics +AI13196,Autonomous Systems Engineer,115876,USD,115876,SE,CT,Finland,S,United States,0,"Git, Data Visualization, Deep Learning, MLOps",Bachelor,9,Energy,2025-03-20,2025-05-19,925,6,Cloud AI Solutions +AI13197,AI Software Engineer,59246,AUD,79982,EN,FT,Australia,L,Australia,0,"Docker, Spark, Data Visualization",PhD,0,Healthcare,2024-07-11,2024-08-30,830,9,Machine Intelligence Group +AI13198,Data Scientist,138647,GBP,103985,SE,PT,United Kingdom,M,Poland,50,"NLP, Docker, Kubernetes, Statistics",Master,7,Telecommunications,2024-03-21,2024-05-27,1264,6.5,Cloud AI Solutions +AI13199,AI Consultant,28360,USD,28360,EN,FL,China,M,Luxembourg,0,"Python, TensorFlow, PyTorch",Associate,0,Retail,2024-04-14,2024-05-08,1103,9.6,Cognitive Computing +AI13200,Autonomous Systems Engineer,197908,JPY,21769880,EX,FL,Japan,M,Japan,50,"Git, Linux, Azure, Data Visualization",Associate,16,Real Estate,2025-02-18,2025-04-15,1951,6.4,AI Innovations +AI13201,AI Software Engineer,181959,AUD,245645,EX,CT,Australia,S,Australia,50,"SQL, GCP, Azure, NLP, Spark",Associate,17,Consulting,2024-11-09,2024-12-19,1213,8.5,Machine Intelligence Group +AI13202,ML Ops Engineer,27691,USD,27691,EN,FL,India,M,India,100,"Kubernetes, TensorFlow, GCP, Statistics, Azure",Associate,1,Healthcare,2025-03-15,2025-04-13,1099,7.8,Quantum Computing Inc +AI13203,Research Scientist,142866,JPY,15715260,SE,CT,Japan,M,Japan,50,"Azure, AWS, Statistics, Scala",PhD,9,Government,2025-01-08,2025-01-24,2332,7.9,Smart Analytics +AI13204,Data Engineer,79744,CAD,99680,MI,PT,Canada,L,Japan,100,"Python, R, GCP, Azure, Spark",Bachelor,4,Real Estate,2024-01-13,2024-02-03,574,8.8,Autonomous Tech +AI13205,AI Architect,198736,USD,198736,EX,PT,United States,S,United States,0,"Linux, Mathematics, Git, NLP, Spark",Associate,18,Government,2024-09-01,2024-10-20,1551,7.1,Digital Transformation LLC +AI13206,Research Scientist,104891,USD,104891,MI,CT,Denmark,M,South Korea,100,"Data Visualization, Azure, GCP, SQL",Associate,2,Retail,2024-05-08,2024-07-17,1911,8.8,Machine Intelligence Group +AI13207,Data Scientist,61269,USD,61269,SE,FL,India,L,India,100,"PyTorch, TensorFlow, GCP",Bachelor,6,Real Estate,2024-01-08,2024-03-12,1695,6.8,AI Innovations +AI13208,Research Scientist,25071,USD,25071,MI,CT,India,S,India,50,"Linux, Deep Learning, Spark",Associate,2,Technology,2025-01-13,2025-03-08,1449,7.7,DeepTech Ventures +AI13209,Data Engineer,84490,CHF,76041,EN,FT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Tableau",PhD,0,Transportation,2024-06-22,2024-08-22,1823,7.3,Algorithmic Solutions +AI13210,AI Architect,58087,USD,58087,MI,PT,South Korea,S,Luxembourg,50,"NLP, Statistics, AWS, Kubernetes",Bachelor,2,Real Estate,2024-08-19,2024-09-29,2017,8.8,Future Systems +AI13211,Autonomous Systems Engineer,50417,EUR,42854,EN,CT,Austria,M,Austria,0,"Azure, Java, Data Visualization",PhD,0,Manufacturing,2024-05-04,2024-06-09,1748,7.7,Cloud AI Solutions +AI13212,AI Software Engineer,149113,SGD,193847,SE,CT,Singapore,M,Singapore,0,"Java, Docker, NLP, Statistics, Scala",Associate,7,Education,2025-01-17,2025-02-18,1353,8.8,Cognitive Computing +AI13213,AI Consultant,94092,EUR,79978,SE,PT,Austria,S,Austria,100,"Hadoop, Tableau, Computer Vision, Python",Bachelor,9,Finance,2024-07-03,2024-08-25,1449,8.6,TechCorp Inc +AI13214,Head of AI,185420,USD,185420,SE,PT,United States,L,Mexico,0,"SQL, Scala, Data Visualization",Associate,6,Consulting,2024-04-25,2024-07-03,1896,9.4,Autonomous Tech +AI13215,Data Analyst,93085,EUR,79122,MI,PT,Netherlands,M,Ghana,100,"Statistics, MLOps, Computer Vision, Java, AWS",Associate,3,Government,2025-01-13,2025-02-28,2006,10,Cognitive Computing +AI13216,NLP Engineer,102367,GBP,76775,MI,FL,United Kingdom,M,United Kingdom,0,"Azure, Spark, Docker",Master,3,Healthcare,2025-02-11,2025-04-14,2318,9.9,Advanced Robotics +AI13217,Machine Learning Engineer,213126,AUD,287720,EX,FT,Australia,L,Australia,100,"Python, Data Visualization, SQL, AWS",Master,18,Gaming,2025-02-17,2025-03-10,1670,5.7,Cognitive Computing +AI13218,Data Engineer,70624,USD,70624,MI,PT,South Korea,S,South Korea,100,"Linux, TensorFlow, Data Visualization",Associate,3,Transportation,2024-07-08,2024-09-13,511,7.5,Cognitive Computing +AI13219,Machine Learning Engineer,48905,EUR,41569,EN,FL,Netherlands,S,Vietnam,0,"Docker, Tableau, PyTorch, TensorFlow, NLP",Associate,1,Real Estate,2024-01-25,2024-03-01,847,9.9,Advanced Robotics +AI13220,Research Scientist,98101,JPY,10791110,SE,FL,Japan,S,Portugal,50,"SQL, Linux, R",PhD,8,Consulting,2024-05-23,2024-06-22,1283,7.4,Neural Networks Co +AI13221,AI Consultant,141464,EUR,120244,SE,PT,Austria,M,Austria,50,"MLOps, Data Visualization, Python, TensorFlow, Docker",Master,9,Automotive,2024-02-13,2024-04-10,1489,8.7,DeepTech Ventures +AI13222,AI Specialist,140338,USD,140338,SE,CT,United States,S,Colombia,0,"Hadoop, Kubernetes, MLOps, SQL",Bachelor,6,Education,2024-12-05,2025-01-05,1117,8,Quantum Computing Inc +AI13223,AI Research Scientist,102674,JPY,11294140,SE,FT,Japan,S,Japan,50,"Python, AWS, R",PhD,5,Automotive,2024-07-31,2024-10-02,503,9.4,Smart Analytics +AI13224,AI Consultant,50281,CAD,62851,EN,FL,Canada,M,Czech Republic,100,"Spark, TensorFlow, Python",PhD,1,Media,2024-05-19,2024-06-23,2064,6.4,AI Innovations +AI13225,ML Ops Engineer,126345,SGD,164249,SE,CT,Singapore,L,Singapore,0,"Python, Linux, Git, Computer Vision",Associate,6,Consulting,2025-01-09,2025-03-04,1300,6.5,Algorithmic Solutions +AI13226,Head of AI,310457,USD,310457,EX,FL,Denmark,M,Denmark,100,"Linux, Kubernetes, PyTorch, Hadoop, Azure",Bachelor,19,Energy,2024-08-04,2024-09-29,693,8,DataVision Ltd +AI13227,AI Architect,133886,USD,133886,SE,CT,Denmark,M,Mexico,100,"Python, NLP, Scala, Computer Vision",Associate,7,Real Estate,2024-07-06,2024-08-23,796,8.3,Cognitive Computing +AI13228,Research Scientist,266548,USD,266548,EX,FL,Finland,L,Finland,100,"Kubernetes, Azure, SQL, AWS",PhD,14,Real Estate,2024-03-04,2024-03-20,1603,5.2,Machine Intelligence Group +AI13229,ML Ops Engineer,45522,USD,45522,MI,FT,China,L,China,50,"Scala, Statistics, Data Visualization, Java, Mathematics",Bachelor,2,Telecommunications,2024-07-29,2024-09-04,534,9.7,Predictive Systems +AI13230,Principal Data Scientist,110658,GBP,82994,MI,PT,United Kingdom,L,United Kingdom,100,"Scala, Kubernetes, Spark, Docker",Associate,4,Transportation,2024-03-24,2024-06-01,2049,8.3,Digital Transformation LLC +AI13231,Research Scientist,80074,USD,80074,EN,FL,Denmark,L,Denmark,50,"Data Visualization, Linux, SQL",Bachelor,1,Manufacturing,2025-02-08,2025-03-10,1335,8,Machine Intelligence Group +AI13232,AI Architect,135856,USD,135856,SE,FL,Sweden,S,Sweden,100,"Azure, R, PyTorch, AWS",Associate,9,Government,2024-09-18,2024-10-02,2285,7.6,DeepTech Ventures +AI13233,Principal Data Scientist,116833,CAD,146041,SE,CT,Canada,S,Canada,50,"Tableau, Linux, AWS, MLOps",Bachelor,8,Consulting,2025-03-02,2025-05-07,1983,9.1,Quantum Computing Inc +AI13234,AI Architect,134634,USD,134634,MI,CT,United States,L,United States,0,"Kubernetes, Statistics, Spark",Master,2,Healthcare,2024-04-03,2024-05-07,1639,9.1,Cognitive Computing +AI13235,ML Ops Engineer,129280,CHF,116352,MI,FL,Switzerland,L,Switzerland,100,"Computer Vision, Tableau, TensorFlow, Python, Statistics",Master,4,Automotive,2024-06-19,2024-08-16,1739,9,AI Innovations +AI13236,Data Engineer,246914,USD,246914,EX,FL,Denmark,L,Thailand,50,"Java, PyTorch, Mathematics, NLP",Bachelor,17,Consulting,2024-11-09,2024-12-15,2011,5.5,Future Systems +AI13237,Research Scientist,94188,JPY,10360680,MI,FL,Japan,M,Turkey,100,"Linux, Python, MLOps, Hadoop, TensorFlow",PhD,4,Gaming,2024-03-17,2024-04-04,2004,6.4,Autonomous Tech +AI13238,Deep Learning Engineer,114774,AUD,154945,MI,FT,Australia,L,Australia,100,"Python, TensorFlow, NLP, Hadoop",Associate,4,Technology,2024-05-31,2024-08-05,1786,5.2,Smart Analytics +AI13239,ML Ops Engineer,59249,USD,59249,EN,CT,Ireland,L,Ireland,0,"SQL, R, Kubernetes",Master,1,Retail,2024-08-14,2024-08-28,516,8.2,DataVision Ltd +AI13240,Principal Data Scientist,81389,USD,81389,MI,PT,South Korea,L,Turkey,0,"SQL, Hadoop, Tableau, Data Visualization",Associate,2,Technology,2024-03-02,2024-05-04,892,7.9,DataVision Ltd +AI13241,Deep Learning Engineer,60315,USD,60315,EN,PT,United States,S,China,50,"Git, PyTorch, Kubernetes",Bachelor,1,Healthcare,2024-02-27,2024-03-25,902,7.3,Algorithmic Solutions +AI13242,Research Scientist,187520,SGD,243776,EX,PT,Singapore,M,Ghana,100,"Azure, Docker, SQL, Python",PhD,17,Finance,2025-04-09,2025-06-03,1424,6.4,AI Innovations +AI13243,Data Analyst,137040,USD,137040,MI,CT,Denmark,M,Denmark,0,"NLP, TensorFlow, Docker, GCP, Python",Master,3,Consulting,2024-08-30,2024-10-22,1172,5.7,DataVision Ltd +AI13244,Computer Vision Engineer,180365,SGD,234475,SE,FL,Singapore,L,Spain,0,"SQL, PyTorch, Tableau, MLOps",PhD,5,Healthcare,2024-08-04,2024-10-12,1304,6.4,AI Innovations +AI13245,AI Research Scientist,40180,USD,40180,EN,PT,China,L,China,50,"GCP, TensorFlow, Hadoop, Python, Kubernetes",Bachelor,1,Real Estate,2024-08-09,2024-09-10,1172,7.6,DeepTech Ventures +AI13246,AI Research Scientist,93313,JPY,10264430,MI,FL,Japan,S,Japan,50,"Python, Spark, Statistics, AWS, Mathematics",Master,2,Telecommunications,2025-01-12,2025-03-03,1062,6.3,Algorithmic Solutions +AI13247,Machine Learning Engineer,106766,SGD,138796,MI,FT,Singapore,M,Singapore,50,"Kubernetes, R, Docker, PyTorch, Git",Associate,3,Government,2024-01-27,2024-03-06,2237,6.4,Algorithmic Solutions +AI13248,Machine Learning Engineer,210437,USD,210437,EX,PT,Israel,L,Israel,100,"Tableau, Kubernetes, Java, Python",Bachelor,14,Telecommunications,2024-05-29,2024-07-18,2171,8,Cognitive Computing +AI13249,AI Product Manager,75988,JPY,8358680,MI,FT,Japan,S,Japan,100,"Kubernetes, NLP, Tableau, Data Visualization",PhD,2,Telecommunications,2024-03-05,2024-04-02,1882,5.4,Cognitive Computing +AI13250,Computer Vision Engineer,144385,JPY,15882350,SE,PT,Japan,S,Japan,50,"Deep Learning, Docker, Tableau, Kubernetes, Spark",Associate,6,Manufacturing,2024-09-04,2024-11-14,1730,7.3,Quantum Computing Inc +AI13251,NLP Engineer,90091,USD,90091,SE,CT,Israel,S,Japan,100,"TensorFlow, MLOps, AWS, Java",Bachelor,8,Finance,2024-06-28,2024-07-24,1937,5.9,Digital Transformation LLC +AI13252,Deep Learning Engineer,105779,USD,105779,SE,PT,Sweden,S,Sweden,0,"Azure, AWS, Computer Vision, Python, Docker",Bachelor,6,Transportation,2025-02-16,2025-04-04,2095,5.7,Quantum Computing Inc +AI13253,NLP Engineer,306666,USD,306666,EX,PT,Norway,L,Belgium,100,"Git, Mathematics, Spark, PyTorch, Statistics",PhD,15,Manufacturing,2024-12-16,2025-01-07,2167,6.7,DeepTech Ventures +AI13254,Machine Learning Researcher,53085,USD,53085,EN,PT,Finland,S,Finland,50,"Java, Tableau, Kubernetes",PhD,1,Telecommunications,2024-07-23,2024-09-23,1112,9.7,Future Systems +AI13255,AI Research Scientist,100104,EUR,85088,SE,FL,Austria,M,Denmark,0,"Python, Statistics, Hadoop",Master,5,Energy,2024-03-23,2024-04-24,1623,7,Predictive Systems +AI13256,NLP Engineer,271861,USD,271861,EX,FL,Norway,L,Norway,50,"Azure, Python, Java",Bachelor,15,Technology,2024-12-06,2025-02-01,2332,9.2,DeepTech Ventures +AI13257,Data Engineer,49399,USD,49399,EN,FT,South Korea,M,South Korea,50,"MLOps, Python, Tableau, AWS, Java",Associate,1,Energy,2024-06-19,2024-08-18,675,8.6,Smart Analytics +AI13258,Data Analyst,103468,JPY,11381480,SE,FT,Japan,S,Japan,100,"Hadoop, R, Scala",Associate,5,Technology,2024-08-24,2024-09-23,1561,9.3,Quantum Computing Inc +AI13259,Machine Learning Engineer,93578,USD,93578,MI,CT,United States,M,United States,50,"TensorFlow, AWS, Spark, Kubernetes, SQL",Associate,3,Retail,2024-11-07,2024-12-18,1889,9.3,Quantum Computing Inc +AI13260,Machine Learning Engineer,84233,EUR,71598,EN,CT,France,L,France,0,"Python, TensorFlow, Deep Learning, Statistics",PhD,1,Media,2024-07-11,2024-07-25,742,5.7,Cloud AI Solutions +AI13261,AI Consultant,112337,USD,112337,EN,CT,Denmark,L,Denmark,0,"Tableau, Linux, Kubernetes",PhD,1,Government,2024-07-11,2024-09-02,1248,9,Advanced Robotics +AI13262,AI Consultant,239391,USD,239391,EX,FT,Denmark,M,Sweden,50,"Hadoop, Scala, MLOps, R, Git",Bachelor,12,Energy,2025-04-29,2025-06-29,2480,5,DataVision Ltd +AI13263,Computer Vision Engineer,45215,USD,45215,EN,PT,South Korea,S,South Korea,0,"GCP, Linux, NLP, Hadoop",PhD,0,Media,2024-07-13,2024-09-13,1982,5.5,Neural Networks Co +AI13264,Machine Learning Researcher,48795,EUR,41476,EN,FT,France,S,Romania,50,"TensorFlow, Python, SQL, Kubernetes",Bachelor,1,Real Estate,2025-01-23,2025-03-11,1982,8.7,DataVision Ltd +AI13265,AI Consultant,119095,CHF,107186,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, Hadoop, GCP, Computer Vision, Azure",PhD,2,Telecommunications,2024-04-13,2024-05-30,958,8.9,Smart Analytics +AI13266,ML Ops Engineer,98669,GBP,74002,SE,CT,United Kingdom,S,United Kingdom,100,"MLOps, Python, Data Visualization",Master,9,Automotive,2024-05-10,2024-07-06,1095,8.3,TechCorp Inc +AI13267,AI Architect,128617,SGD,167202,SE,CT,Singapore,M,Netherlands,100,"Computer Vision, SQL, Data Visualization, Kubernetes, Docker",PhD,6,Retail,2024-08-17,2024-09-09,2213,8.5,DataVision Ltd +AI13268,Robotics Engineer,95556,USD,95556,MI,FT,Sweden,M,Sweden,0,"Kubernetes, Deep Learning, Linux",PhD,2,Manufacturing,2024-12-13,2025-01-31,1250,6.2,Advanced Robotics +AI13269,Machine Learning Engineer,200162,SGD,260211,EX,FL,Singapore,L,Singapore,50,"R, Spark, MLOps, Mathematics",PhD,11,Manufacturing,2025-01-23,2025-02-09,840,8.3,Autonomous Tech +AI13270,Principal Data Scientist,109357,EUR,92953,MI,PT,Netherlands,L,Norway,0,"NLP, Git, Java, MLOps",Associate,4,Government,2025-02-01,2025-03-30,2304,6.7,Quantum Computing Inc +AI13271,Head of AI,122021,USD,122021,MI,FT,Norway,M,United Kingdom,0,"Kubernetes, Python, Tableau",Master,2,Manufacturing,2024-08-19,2024-10-07,669,5.3,DataVision Ltd +AI13272,Head of AI,325087,CHF,292578,EX,PT,Switzerland,L,Ghana,100,"Python, Git, Tableau",Associate,11,Retail,2025-03-25,2025-05-21,2055,5.5,DataVision Ltd +AI13273,Machine Learning Engineer,168996,JPY,18589560,EX,FT,Japan,M,Chile,0,"Deep Learning, Scala, Spark, Python",Associate,16,Healthcare,2024-01-30,2024-03-25,1234,6.2,Digital Transformation LLC +AI13274,ML Ops Engineer,43570,USD,43570,EN,FT,South Korea,S,South Korea,50,"Java, SQL, Git, Data Visualization, Python",Master,0,Manufacturing,2024-03-31,2024-05-26,1032,6.9,Algorithmic Solutions +AI13275,AI Architect,149909,USD,149909,SE,PT,United States,L,United States,50,"GCP, Python, TensorFlow, Deep Learning, Tableau",PhD,9,Gaming,2025-03-25,2025-05-05,1503,5.8,Future Systems +AI13276,Computer Vision Engineer,82164,USD,82164,EN,FL,United States,S,Sweden,50,"TensorFlow, NLP, Linux, Statistics, Deep Learning",Bachelor,1,Transportation,2024-01-04,2024-01-27,1031,6,Digital Transformation LLC +AI13277,AI Consultant,92430,USD,92430,MI,CT,Israel,S,Brazil,100,"Data Visualization, Tableau, PyTorch, Python, Mathematics",Associate,4,Real Estate,2025-01-29,2025-02-12,1295,8.4,Autonomous Tech +AI13278,AI Specialist,49758,USD,49758,EN,FT,South Korea,S,South Korea,100,"R, Statistics, Hadoop, Git",Master,0,Healthcare,2024-11-03,2025-01-07,2206,7.6,Neural Networks Co +AI13279,AI Product Manager,74628,GBP,55971,EN,CT,United Kingdom,L,Russia,100,"Git, Hadoop, MLOps",PhD,1,Healthcare,2024-02-16,2024-03-14,1505,5.7,Cloud AI Solutions +AI13280,Robotics Engineer,128025,GBP,96019,MI,FT,United Kingdom,L,South Africa,50,"Python, Linux, Azure, Deep Learning",Master,2,Education,2024-03-30,2024-04-23,2160,7.1,Cognitive Computing +AI13281,Data Engineer,100244,EUR,85207,SE,CT,Germany,S,Netherlands,50,"R, SQL, Scala, Python",Master,8,Education,2024-08-14,2024-09-05,865,7,Future Systems +AI13282,Autonomous Systems Engineer,34992,USD,34992,MI,FL,India,S,Belgium,100,"PyTorch, Java, NLP",Associate,3,Retail,2024-02-17,2024-04-08,1855,9.9,DataVision Ltd +AI13283,AI Research Scientist,94904,EUR,80668,MI,CT,France,L,Israel,100,"GCP, Linux, Hadoop, Java",PhD,2,Healthcare,2024-05-04,2024-06-17,1361,9.8,Digital Transformation LLC +AI13284,Data Analyst,134647,JPY,14811170,EX,CT,Japan,S,Japan,0,"Kubernetes, Python, TensorFlow, Deep Learning",Associate,19,Automotive,2025-01-31,2025-03-28,1051,8.8,DataVision Ltd +AI13285,AI Consultant,47733,USD,47733,EN,FL,Finland,S,Argentina,50,"NLP, Python, Java, R, GCP",PhD,1,Transportation,2024-11-14,2024-12-17,2101,5.6,Neural Networks Co +AI13286,AI Research Scientist,126186,GBP,94640,SE,FT,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Deep Learning, Python, NLP",PhD,8,Manufacturing,2024-04-25,2024-06-21,706,5.2,Cloud AI Solutions +AI13287,Robotics Engineer,178018,USD,178018,EX,FL,Finland,M,Finland,50,"GCP, NLP, Scala, Java",Master,11,Education,2024-05-21,2024-06-30,600,6.7,AI Innovations +AI13288,Computer Vision Engineer,58807,EUR,49986,EN,FL,France,L,France,100,"Computer Vision, R, Python, Kubernetes, MLOps",Associate,1,Media,2024-06-09,2024-07-29,713,6.8,Cognitive Computing +AI13289,ML Ops Engineer,78517,EUR,66739,EN,FT,France,L,France,100,"GCP, Deep Learning, Linux",Master,0,Technology,2024-12-31,2025-02-15,692,9.8,Machine Intelligence Group +AI13290,Computer Vision Engineer,152471,EUR,129600,SE,FT,Germany,L,Germany,0,"Git, Statistics, Kubernetes, Linux, PyTorch",PhD,9,Automotive,2024-05-12,2024-05-28,632,6.8,DataVision Ltd +AI13291,AI Research Scientist,83053,USD,83053,EN,FT,Ireland,L,Ireland,0,"Kubernetes, Python, AWS, TensorFlow, Data Visualization",PhD,1,Transportation,2024-12-18,2025-02-03,1920,7.4,TechCorp Inc +AI13292,Deep Learning Engineer,55419,EUR,47106,EN,FL,Austria,S,Czech Republic,100,"Data Visualization, GCP, Kubernetes, R",Master,1,Real Estate,2025-01-19,2025-02-18,2179,8.7,Machine Intelligence Group +AI13293,Data Analyst,226088,CAD,282610,EX,CT,Canada,M,Latvia,0,"Tableau, Hadoop, Kubernetes, Mathematics, Scala",PhD,13,Retail,2024-02-24,2024-03-19,777,9.9,Cognitive Computing +AI13294,Machine Learning Researcher,140926,GBP,105695,SE,FT,United Kingdom,S,United Kingdom,100,"MLOps, PyTorch, Docker, Mathematics",Bachelor,5,Consulting,2024-03-17,2024-04-10,566,7.9,DataVision Ltd +AI13295,Machine Learning Researcher,97767,EUR,83102,SE,FT,Netherlands,S,Netherlands,50,"Linux, Git, MLOps, Computer Vision, Python",Associate,9,Automotive,2024-01-07,2024-02-23,1471,5.5,Neural Networks Co +AI13296,Data Scientist,100990,GBP,75743,SE,FL,United Kingdom,S,United Kingdom,100,"Python, Deep Learning, SQL, GCP",Associate,8,Technology,2024-10-31,2024-11-22,904,8.7,DeepTech Ventures +AI13297,Data Analyst,136795,GBP,102596,SE,PT,United Kingdom,M,United Kingdom,100,"MLOps, Hadoop, Scala, Linux, Java",Master,7,Telecommunications,2024-06-13,2024-06-29,2464,6.1,AI Innovations +AI13298,AI Architect,76815,USD,76815,MI,FT,Sweden,S,Sweden,100,"Mathematics, AWS, Hadoop, Deep Learning",Bachelor,3,Manufacturing,2024-09-24,2024-10-11,1123,5.5,Smart Analytics +AI13299,Head of AI,80644,USD,80644,EN,PT,United States,M,United States,50,"Python, TensorFlow, Tableau",PhD,1,Gaming,2024-08-17,2024-09-20,1924,10,TechCorp Inc +AI13300,Deep Learning Engineer,90240,JPY,9926400,MI,FL,Japan,S,Japan,50,"SQL, PyTorch, MLOps",Associate,3,Government,2024-09-16,2024-11-26,591,9.1,Machine Intelligence Group +AI13301,Machine Learning Engineer,199372,USD,199372,EX,PT,Norway,S,Luxembourg,0,"Python, Scala, NLP, Azure, Kubernetes",PhD,17,Technology,2024-07-05,2024-09-07,1177,8.6,Quantum Computing Inc +AI13302,Robotics Engineer,232839,EUR,197913,EX,CT,France,M,France,100,"Linux, GCP, R, Spark, Python",Master,10,Media,2024-12-12,2025-02-11,1555,6.9,Cloud AI Solutions +AI13303,AI Research Scientist,120541,USD,120541,MI,CT,Denmark,M,Denmark,100,"PyTorch, Kubernetes, Hadoop, NLP, GCP",Master,2,Consulting,2025-01-02,2025-01-30,2358,6.2,Predictive Systems +AI13304,ML Ops Engineer,94694,USD,94694,EN,CT,Norway,M,Romania,0,"Spark, Computer Vision, SQL",Associate,1,Gaming,2024-02-19,2024-05-02,1701,8.5,TechCorp Inc +AI13305,NLP Engineer,69183,AUD,93397,EN,PT,Australia,M,Japan,50,"Azure, Linux, PyTorch",Master,0,Finance,2024-08-25,2024-11-03,657,7.3,AI Innovations +AI13306,AI Software Engineer,101698,EUR,86443,SE,FT,Austria,M,China,100,"Linux, Python, Azure, TensorFlow, AWS",Master,6,Real Estate,2024-05-15,2024-06-20,976,7.9,Quantum Computing Inc +AI13307,Head of AI,131365,USD,131365,SE,FL,Israel,M,Israel,50,"Data Visualization, Spark, GCP, Docker",PhD,7,Gaming,2024-02-14,2024-04-15,1663,6.3,Quantum Computing Inc +AI13308,AI Consultant,130237,GBP,97678,SE,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, R, AWS",PhD,8,Finance,2024-01-14,2024-03-15,1184,10,TechCorp Inc +AI13309,AI Architect,171976,USD,171976,SE,FT,Ireland,L,Ireland,100,"Deep Learning, Azure, Spark",Associate,6,Energy,2024-04-23,2024-05-26,811,6.3,Quantum Computing Inc +AI13310,AI Product Manager,219348,USD,219348,EX,FT,Denmark,L,Denmark,50,"Python, TensorFlow, PyTorch, Docker, Statistics",Associate,18,Telecommunications,2024-02-28,2024-04-28,629,5.6,Autonomous Tech +AI13311,AI Research Scientist,215507,USD,215507,EX,FL,Israel,M,Israel,100,"Scala, TensorFlow, Azure, Python, PyTorch",PhD,19,Education,2024-07-10,2024-08-07,2042,7.6,Digital Transformation LLC +AI13312,Data Analyst,168512,USD,168512,SE,FL,Sweden,L,Canada,100,"GCP, Data Visualization, Python",PhD,7,Transportation,2024-04-23,2024-06-29,1881,9.1,Algorithmic Solutions +AI13313,AI Research Scientist,121328,JPY,13346080,SE,FL,Japan,S,Japan,0,"SQL, PyTorch, GCP, Tableau",Master,8,Real Estate,2024-04-18,2024-05-21,733,7.3,Machine Intelligence Group +AI13314,AI Software Engineer,289498,USD,289498,EX,PT,Denmark,M,Denmark,0,"Scala, GCP, Deep Learning, R",Associate,10,Healthcare,2024-12-23,2025-01-15,670,9.1,Digital Transformation LLC +AI13315,AI Research Scientist,109391,AUD,147678,SE,CT,Australia,S,Australia,50,"AWS, Kubernetes, Mathematics, Java",Bachelor,5,Technology,2024-07-09,2024-09-04,571,8.7,Neural Networks Co +AI13316,Head of AI,92796,USD,92796,MI,PT,South Korea,L,South Korea,100,"Data Visualization, TensorFlow, NLP, Kubernetes",Associate,4,Telecommunications,2024-02-15,2024-04-14,1608,9.6,Future Systems +AI13317,Computer Vision Engineer,254375,SGD,330688,EX,FT,Singapore,M,Singapore,0,"GCP, Scala, Git, R",Associate,19,Education,2024-05-08,2024-05-29,1024,6.5,Smart Analytics +AI13318,Machine Learning Researcher,64737,CAD,80921,MI,FL,Canada,S,Canada,0,"Git, Tableau, Python, Data Visualization, TensorFlow",Bachelor,2,Gaming,2024-01-31,2024-04-05,1165,6.2,Future Systems +AI13319,Robotics Engineer,101753,EUR,86490,SE,PT,Netherlands,S,Netherlands,50,"Kubernetes, NLP, Data Visualization, GCP, Linux",PhD,9,Real Estate,2025-04-07,2025-05-07,1334,7.5,Predictive Systems +AI13320,Autonomous Systems Engineer,208375,EUR,177119,EX,FT,Netherlands,M,Netherlands,100,"Git, Mathematics, Computer Vision",Bachelor,11,Education,2025-04-21,2025-06-24,977,9.1,Quantum Computing Inc +AI13321,Autonomous Systems Engineer,127596,AUD,172255,SE,FL,Australia,S,Netherlands,50,"SQL, PyTorch, Java",Master,6,Healthcare,2024-09-01,2024-11-02,2402,6.6,Digital Transformation LLC +AI13322,Data Analyst,231910,EUR,197124,EX,FL,France,L,France,50,"MLOps, PyTorch, Hadoop",Associate,12,Automotive,2024-09-29,2024-11-15,1309,9.4,Neural Networks Co +AI13323,ML Ops Engineer,40030,USD,40030,SE,FL,India,M,India,0,"GCP, Deep Learning, Kubernetes",Bachelor,5,Transportation,2024-11-08,2024-12-02,1632,5.6,Cloud AI Solutions +AI13324,AI Architect,108886,USD,108886,EX,FT,China,L,China,100,"NLP, Scala, SQL",Master,11,Technology,2024-03-22,2024-04-27,1355,6,DeepTech Ventures +AI13325,Data Scientist,25902,USD,25902,EN,PT,China,M,Romania,50,"TensorFlow, Linux, Hadoop",Bachelor,0,Technology,2024-12-03,2025-01-12,1563,6,Algorithmic Solutions +AI13326,AI Research Scientist,86757,AUD,117122,MI,CT,Australia,L,Australia,100,"Kubernetes, GCP, Data Visualization, Mathematics, SQL",Bachelor,3,Retail,2025-01-15,2025-03-04,1437,7,Smart Analytics +AI13327,Data Analyst,38963,USD,38963,MI,FT,China,M,China,0,"Kubernetes, Spark, Python, Linux, Mathematics",Associate,3,Automotive,2024-11-17,2024-12-02,1495,6.7,Machine Intelligence Group +AI13328,AI Architect,308292,CHF,277463,EX,FL,Switzerland,L,Switzerland,100,"Kubernetes, Spark, Tableau, Hadoop, Git",PhD,11,Education,2024-06-07,2024-07-04,1113,7.9,DeepTech Ventures +AI13329,AI Software Engineer,194259,CHF,174833,SE,FL,Switzerland,L,Ukraine,50,"Kubernetes, Scala, Statistics, Tableau, Spark",Associate,7,Gaming,2024-06-11,2024-07-30,2266,7.6,Algorithmic Solutions +AI13330,Machine Learning Researcher,90499,AUD,122174,EN,CT,Australia,L,Kenya,100,"Linux, Python, Mathematics, Kubernetes, Hadoop",PhD,0,Government,2025-02-01,2025-03-16,1479,7.1,Cognitive Computing +AI13331,AI Research Scientist,152866,EUR,129936,EX,FT,Netherlands,S,Nigeria,0,"Git, Linux, Kubernetes, Python",PhD,14,Consulting,2024-02-13,2024-04-24,1604,5.9,Future Systems +AI13332,AI Consultant,207262,USD,207262,EX,FT,Norway,M,United States,0,"PyTorch, TensorFlow, Spark, Python, Hadoop",Master,19,Media,2025-04-07,2025-06-18,1968,9,Quantum Computing Inc +AI13333,Autonomous Systems Engineer,97380,CAD,121725,MI,FT,Canada,L,Russia,100,"R, MLOps, Data Visualization, SQL, Mathematics",Bachelor,4,Consulting,2024-06-21,2024-07-13,2191,5.9,Algorithmic Solutions +AI13334,AI Software Engineer,163759,USD,163759,SE,PT,Denmark,L,Denmark,0,"Kubernetes, Docker, Scala, Hadoop, Statistics",Associate,5,Real Estate,2024-03-04,2024-04-02,2380,6.1,Digital Transformation LLC +AI13335,Machine Learning Researcher,121421,EUR,103208,SE,FL,France,S,France,0,"Java, Linux, Tableau, MLOps, Statistics",Associate,6,Telecommunications,2025-04-01,2025-05-06,595,7.4,Future Systems +AI13336,Data Engineer,43568,EUR,37033,EN,PT,France,S,China,50,"Statistics, GCP, Data Visualization, Java",Bachelor,0,Technology,2024-04-02,2024-06-09,880,9.1,Machine Intelligence Group +AI13337,Research Scientist,119350,USD,119350,EX,FT,China,L,China,0,"Java, NLP, Python, Kubernetes",Associate,10,Healthcare,2024-02-11,2024-03-29,1105,9.2,Predictive Systems +AI13338,Computer Vision Engineer,95494,USD,95494,SE,PT,South Korea,S,South Korea,50,"Python, TensorFlow, Java",Associate,6,Energy,2024-04-16,2024-05-16,2058,6,Predictive Systems +AI13339,Deep Learning Engineer,62202,EUR,52872,EN,CT,Germany,S,Germany,50,"Scala, SQL, Python, Java, NLP",Master,1,Media,2025-04-17,2025-06-22,997,6.6,TechCorp Inc +AI13340,AI Consultant,88967,USD,88967,EN,PT,Sweden,L,Turkey,50,"TensorFlow, Azure, Deep Learning, Computer Vision, Linux",PhD,1,Real Estate,2024-12-20,2025-02-09,2438,7.1,Autonomous Tech +AI13341,Robotics Engineer,63313,CAD,79141,EN,FT,Canada,M,Canada,100,"Kubernetes, PyTorch, Mathematics, Computer Vision, GCP",Bachelor,1,Telecommunications,2024-12-24,2025-02-28,1312,7.3,Quantum Computing Inc +AI13342,Autonomous Systems Engineer,59228,CAD,74035,EN,PT,Canada,S,Canada,0,"TensorFlow, Python, Java, Spark, Kubernetes",Associate,0,Retail,2024-07-23,2024-09-19,924,8.8,Algorithmic Solutions +AI13343,Autonomous Systems Engineer,125001,USD,125001,SE,CT,Israel,S,Israel,100,"AWS, Spark, Data Visualization, Git",Associate,8,Energy,2024-08-01,2024-09-07,1524,6.6,TechCorp Inc +AI13344,Principal Data Scientist,36642,USD,36642,EN,PT,China,L,China,100,"Python, Scala, Java",Master,0,Telecommunications,2024-10-28,2024-12-27,1096,5.9,Neural Networks Co +AI13345,Principal Data Scientist,113963,USD,113963,MI,PT,Denmark,M,Denmark,100,"Python, Data Visualization, AWS, Spark",PhD,2,Energy,2024-07-20,2024-09-26,1472,8.2,Autonomous Tech +AI13346,Machine Learning Engineer,135609,USD,135609,SE,FT,Denmark,M,Luxembourg,100,"R, Tableau, Statistics, NLP",Master,8,Healthcare,2024-01-29,2024-03-21,1855,8.7,AI Innovations +AI13347,Deep Learning Engineer,129508,GBP,97131,SE,FT,United Kingdom,M,United Kingdom,0,"Linux, Docker, PyTorch, R",Master,9,Transportation,2024-09-28,2024-11-13,1340,9,AI Innovations +AI13348,Head of AI,222566,JPY,24482260,EX,PT,Japan,S,Japan,0,"Docker, Deep Learning, SQL, MLOps",PhD,11,Gaming,2024-05-13,2024-07-15,766,6.3,Machine Intelligence Group +AI13349,AI Architect,263402,JPY,28974220,EX,PT,Japan,L,Japan,0,"Kubernetes, Java, R, Statistics",Associate,11,Education,2024-09-18,2024-10-15,2271,6.6,AI Innovations +AI13350,Computer Vision Engineer,60120,GBP,45090,EN,FL,United Kingdom,S,Ukraine,0,"MLOps, Computer Vision, GCP, Kubernetes",PhD,1,Telecommunications,2025-03-03,2025-05-10,1798,6.9,Autonomous Tech +AI13351,Machine Learning Engineer,76589,USD,76589,MI,FT,Finland,S,Finland,100,"Kubernetes, Git, SQL",Associate,2,Real Estate,2024-08-18,2024-10-29,2474,9.2,Algorithmic Solutions +AI13352,Deep Learning Engineer,73963,USD,73963,EN,FL,United States,L,United States,50,"Python, TensorFlow, Azure, Spark, PyTorch",Master,1,Finance,2024-09-24,2024-10-19,714,9.9,Quantum Computing Inc +AI13353,Machine Learning Researcher,320290,USD,320290,EX,FT,Denmark,L,Denmark,100,"Hadoop, Python, Scala, AWS",Bachelor,13,Media,2024-11-02,2024-12-29,1220,5.6,DeepTech Ventures +AI13354,Deep Learning Engineer,148841,JPY,16372510,SE,FL,Japan,L,Russia,0,"Kubernetes, Scala, Java, Spark, R",Associate,8,Real Estate,2024-07-22,2024-08-20,828,6.6,Neural Networks Co +AI13355,Head of AI,111086,USD,111086,EN,FL,Denmark,L,Denmark,100,"Computer Vision, Azure, Python, TensorFlow, GCP",Master,1,Automotive,2024-06-01,2024-07-19,2404,7,AI Innovations +AI13356,Computer Vision Engineer,259096,USD,259096,EX,FL,United States,M,United States,50,"Spark, Statistics, NLP, Python",Bachelor,17,Telecommunications,2024-07-23,2024-08-08,1084,7,Quantum Computing Inc +AI13357,Computer Vision Engineer,90325,CAD,112906,MI,PT,Canada,L,New Zealand,100,"Kubernetes, Deep Learning, Python, Data Visualization",Bachelor,4,Healthcare,2024-09-05,2024-10-04,1127,5.4,TechCorp Inc +AI13358,AI Product Manager,92718,SGD,120533,MI,CT,Singapore,L,Singapore,0,"Python, MLOps, Tableau, TensorFlow",Associate,2,Manufacturing,2024-07-11,2024-09-07,893,9.6,DeepTech Ventures +AI13359,Deep Learning Engineer,124245,USD,124245,SE,PT,Israel,M,Israel,0,"PyTorch, TensorFlow, Mathematics",Bachelor,6,Energy,2025-01-10,2025-02-16,2472,5,Cloud AI Solutions +AI13360,Data Scientist,235413,GBP,176560,EX,FT,United Kingdom,S,United Kingdom,0,"Java, Hadoop, Tableau",Bachelor,12,Education,2025-02-11,2025-03-15,1436,8,Quantum Computing Inc +AI13361,Machine Learning Engineer,137922,EUR,117234,SE,PT,France,L,France,0,"AWS, Kubernetes, MLOps, Scala, Python",Bachelor,9,Telecommunications,2024-09-11,2024-11-20,2186,9.5,Future Systems +AI13362,Data Scientist,123420,USD,123420,MI,FT,United States,M,United States,100,"Mathematics, SQL, PyTorch, GCP",Bachelor,3,Energy,2024-10-30,2024-12-31,855,8.3,Advanced Robotics +AI13363,AI Software Engineer,234411,USD,234411,EX,PT,Israel,L,Russia,50,"Spark, Computer Vision, Docker, Data Visualization, R",Bachelor,16,Manufacturing,2024-08-28,2024-09-24,2452,6.8,DataVision Ltd +AI13364,Deep Learning Engineer,28209,USD,28209,MI,PT,India,S,India,100,"Azure, Scala, Mathematics, Linux, SQL",Master,3,Transportation,2025-02-06,2025-03-31,1105,9.3,Future Systems +AI13365,Machine Learning Engineer,77044,USD,77044,EN,FL,Norway,S,France,100,"Azure, AWS, Git",PhD,1,Transportation,2025-01-31,2025-03-24,852,5.4,Autonomous Tech +AI13366,Principal Data Scientist,126485,JPY,13913350,SE,FT,Japan,M,Japan,50,"SQL, Kubernetes, PyTorch, Tableau, Deep Learning",Associate,8,Technology,2024-10-05,2024-12-04,2474,5.5,Neural Networks Co +AI13367,NLP Engineer,75977,USD,75977,EN,FL,Ireland,L,Ireland,50,"R, Git, TensorFlow, Computer Vision, Spark",PhD,1,Media,2024-10-09,2024-12-10,1540,7.5,AI Innovations +AI13368,Data Engineer,53042,EUR,45086,EN,CT,Austria,M,Mexico,0,"Python, TensorFlow, Scala, Azure",Associate,0,Education,2024-01-28,2024-03-09,1094,8.1,Digital Transformation LLC +AI13369,AI Product Manager,88798,EUR,75478,MI,FL,Netherlands,M,Nigeria,0,"Deep Learning, Azure, MLOps",Bachelor,3,Technology,2024-07-01,2024-07-26,2121,5.7,Cloud AI Solutions +AI13370,Autonomous Systems Engineer,133645,EUR,113598,EX,PT,Austria,S,Austria,0,"Spark, Python, TensorFlow",Bachelor,18,Retail,2024-06-05,2024-06-24,2153,9.9,Cloud AI Solutions +AI13371,Machine Learning Engineer,123940,USD,123940,SE,CT,Sweden,L,Sweden,50,"Computer Vision, NLP, Scala, Python, Kubernetes",Associate,8,Transportation,2024-03-08,2024-03-25,2348,8.9,Smart Analytics +AI13372,AI Product Manager,250927,USD,250927,EX,FL,Finland,L,Finland,50,"Python, Kubernetes, Tableau, Hadoop, Data Visualization",Master,11,Healthcare,2025-02-12,2025-03-07,1895,7.2,Algorithmic Solutions +AI13373,AI Research Scientist,68177,SGD,88630,EN,FL,Singapore,S,Singapore,0,"Tableau, SQL, Statistics, TensorFlow, Docker",Bachelor,0,Finance,2024-05-18,2024-07-12,1152,7.8,TechCorp Inc +AI13374,AI Software Engineer,92501,USD,92501,MI,FL,Israel,L,Israel,100,"Python, TensorFlow, Scala, Hadoop",Associate,2,Real Estate,2025-02-24,2025-04-21,535,7.1,Neural Networks Co +AI13375,Computer Vision Engineer,117573,EUR,99937,SE,CT,Netherlands,M,Indonesia,50,"Azure, GCP, Scala, Mathematics, Spark",Master,5,Real Estate,2024-09-24,2024-10-13,1801,7.8,Autonomous Tech +AI13376,AI Software Engineer,48867,USD,48867,EN,FL,South Korea,M,South Korea,100,"Data Visualization, Linux, AWS, PyTorch, Java",Master,1,Gaming,2024-04-10,2024-05-06,1455,8.8,Quantum Computing Inc +AI13377,AI Product Manager,65451,AUD,88359,EN,CT,Australia,S,Australia,50,"Hadoop, Data Visualization, TensorFlow, Mathematics, Azure",Associate,1,Transportation,2025-02-28,2025-04-18,973,8.5,Smart Analytics +AI13378,NLP Engineer,96257,EUR,81818,SE,CT,Austria,M,Thailand,100,"Scala, Linux, Tableau, Data Visualization",Bachelor,9,Technology,2024-11-22,2025-01-31,2016,9.9,DeepTech Ventures +AI13379,Computer Vision Engineer,64758,USD,64758,MI,FL,Israel,S,Israel,50,"Tableau, Spark, GCP, PyTorch, Data Visualization",Associate,4,Telecommunications,2024-07-17,2024-08-06,1475,9.7,Cognitive Computing +AI13380,AI Architect,76008,EUR,64607,EN,CT,Germany,M,Hungary,50,"Tableau, Kubernetes, Data Visualization",PhD,0,Manufacturing,2024-02-26,2024-04-03,2311,7.7,Future Systems +AI13381,ML Ops Engineer,61682,EUR,52430,EN,CT,Netherlands,S,Netherlands,50,"Python, Docker, Hadoop",PhD,0,Energy,2024-02-28,2024-03-27,1643,9.9,Cloud AI Solutions +AI13382,AI Specialist,193425,USD,193425,EX,FL,Ireland,S,Ireland,0,"NLP, PyTorch, Statistics, Spark, Mathematics",Bachelor,19,Media,2024-11-23,2024-12-24,1129,9.6,Advanced Robotics +AI13383,Computer Vision Engineer,96082,EUR,81670,SE,FL,France,M,France,0,"PyTorch, Mathematics, Python",Master,9,Energy,2024-08-15,2024-10-24,2178,6.7,Cloud AI Solutions +AI13384,AI Research Scientist,118266,CHF,106439,MI,CT,Switzerland,M,Turkey,50,"SQL, Mathematics, Spark, Kubernetes",Bachelor,3,Finance,2024-07-29,2024-09-22,1546,10,TechCorp Inc +AI13385,Head of AI,92143,AUD,124393,EN,FT,Australia,L,Australia,100,"Git, Docker, Kubernetes, Spark, GCP",Associate,1,Government,2024-03-27,2024-04-11,1750,5.5,Neural Networks Co +AI13386,Computer Vision Engineer,53657,SGD,69754,EN,FL,Singapore,S,Singapore,100,"PyTorch, GCP, Python",PhD,1,Gaming,2024-10-03,2024-11-27,1961,6.1,Predictive Systems +AI13387,AI Software Engineer,219960,USD,219960,EX,FT,United States,M,United States,100,"SQL, PyTorch, Kubernetes",Bachelor,17,Automotive,2024-03-14,2024-04-01,1905,8.2,Digital Transformation LLC +AI13388,AI Software Engineer,227427,USD,227427,EX,FT,Ireland,S,Ireland,0,"Scala, Git, Hadoop",Bachelor,15,Finance,2025-03-05,2025-03-23,1930,7.2,Machine Intelligence Group +AI13389,AI Research Scientist,140704,USD,140704,EX,PT,South Korea,L,South Korea,100,"SQL, Python, PyTorch, Azure, Mathematics",Bachelor,19,Retail,2024-10-08,2024-11-30,1659,6,Predictive Systems +AI13390,AI Architect,90170,USD,90170,EN,FL,Denmark,S,Norway,0,"R, Hadoop, Mathematics",PhD,1,Automotive,2025-01-27,2025-02-18,1589,7.9,Smart Analytics +AI13391,AI Architect,75174,AUD,101485,MI,FT,Australia,S,Australia,100,"GCP, Python, Tableau, MLOps",Associate,2,Consulting,2024-06-18,2024-07-25,2007,7.6,Digital Transformation LLC +AI13392,Data Scientist,98977,EUR,84130,MI,CT,Germany,S,Germany,100,"Deep Learning, Spark, Python",Associate,2,Retail,2025-02-10,2025-04-06,760,6.2,Advanced Robotics +AI13393,Data Engineer,92614,USD,92614,EN,PT,Norway,L,Norway,100,"SQL, Linux, MLOps, Python, GCP",Bachelor,1,Real Estate,2024-04-27,2024-06-06,2066,8,Advanced Robotics +AI13394,Research Scientist,24682,USD,24682,EN,CT,China,S,China,0,"AWS, Linux, TensorFlow",Bachelor,0,Government,2024-07-20,2024-09-27,1943,8.2,Neural Networks Co +AI13395,Head of AI,169552,USD,169552,EX,FT,Finland,S,Finland,100,"TensorFlow, Python, Tableau",Bachelor,11,Finance,2024-08-15,2024-10-27,1956,7.4,Digital Transformation LLC +AI13396,ML Ops Engineer,152388,EUR,129530,EX,PT,Germany,M,Germany,0,"PyTorch, GCP, Azure, SQL, Mathematics",Bachelor,14,Government,2024-05-28,2024-06-13,1778,7.6,Cognitive Computing +AI13397,Research Scientist,56108,EUR,47692,EN,FL,Netherlands,S,Netherlands,50,"NLP, Python, Java",Master,0,Automotive,2025-02-17,2025-04-14,576,5.4,Machine Intelligence Group +AI13398,AI Consultant,185781,USD,185781,SE,CT,Norway,M,Norway,100,"Computer Vision, Kubernetes, NLP, Java, TensorFlow",Bachelor,6,Real Estate,2024-03-26,2024-05-19,1329,9.7,AI Innovations +AI13399,ML Ops Engineer,175075,SGD,227598,EX,PT,Singapore,S,Singapore,0,"Spark, PyTorch, Docker, SQL",Associate,18,Telecommunications,2025-03-27,2025-05-23,588,6.2,DataVision Ltd +AI13400,AI Specialist,69174,USD,69174,EN,PT,United States,M,United States,100,"Kubernetes, Spark, Python, Java",PhD,0,Telecommunications,2024-03-20,2024-04-08,1954,9.9,Cognitive Computing +AI13401,Data Engineer,114304,CHF,102874,EN,FT,Switzerland,L,Switzerland,50,"R, Python, Mathematics, Java",Associate,0,Energy,2024-06-02,2024-06-16,634,7.5,Neural Networks Co +AI13402,AI Specialist,205622,EUR,174779,EX,FL,Netherlands,M,Netherlands,100,"Mathematics, SQL, Data Visualization",PhD,18,Healthcare,2025-04-11,2025-05-27,501,8,Quantum Computing Inc +AI13403,Computer Vision Engineer,162908,EUR,138472,SE,FT,France,L,Argentina,100,"Scala, Docker, Statistics",PhD,7,Consulting,2024-07-19,2024-09-19,2059,7,Autonomous Tech +AI13404,Principal Data Scientist,357781,USD,357781,EX,PT,Denmark,L,Denmark,100,"Python, TensorFlow, AWS, Computer Vision, Statistics",Associate,10,Government,2025-03-02,2025-03-25,994,10,DeepTech Ventures +AI13405,ML Ops Engineer,204495,USD,204495,EX,CT,Sweden,M,Sweden,0,"Python, Docker, Data Visualization",PhD,10,Telecommunications,2024-06-16,2024-07-08,2403,9.1,DeepTech Ventures +AI13406,AI Software Engineer,70678,GBP,53009,EN,FL,United Kingdom,M,United Kingdom,100,"Python, Hadoop, Git, TensorFlow, Statistics",Associate,0,Automotive,2025-04-30,2025-06-01,1363,7.6,Machine Intelligence Group +AI13407,Machine Learning Engineer,114963,EUR,97719,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Data Visualization, SQL, TensorFlow, Java",Master,4,Telecommunications,2024-09-17,2024-10-16,905,6.7,Future Systems +AI13408,Research Scientist,67163,USD,67163,EX,FL,India,S,India,100,"TensorFlow, Deep Learning, Tableau",Bachelor,17,Education,2025-04-03,2025-05-16,1435,8.1,Autonomous Tech +AI13409,Machine Learning Engineer,211419,SGD,274845,EX,FL,Singapore,S,Switzerland,100,"Hadoop, Java, NLP, TensorFlow, Kubernetes",PhD,12,Technology,2024-12-17,2025-01-05,1204,9.8,DataVision Ltd +AI13410,AI Software Engineer,134096,USD,134096,SE,FT,Sweden,L,Sweden,50,"Deep Learning, Docker, GCP, Data Visualization, AWS",Bachelor,6,Gaming,2025-01-27,2025-03-15,2282,5.1,Autonomous Tech +AI13411,AI Architect,146850,USD,146850,SE,PT,Finland,L,Finland,100,"Mathematics, PyTorch, Hadoop, Spark, TensorFlow",Master,8,Automotive,2024-04-28,2024-05-15,1904,7.5,Autonomous Tech +AI13412,Robotics Engineer,67285,JPY,7401350,EN,CT,Japan,M,Egypt,100,"NLP, Deep Learning, Hadoop, Computer Vision",Associate,0,Energy,2024-06-10,2024-07-11,1776,9.8,Future Systems +AI13413,Data Scientist,287563,USD,287563,EX,FL,United States,M,Spain,50,"Python, TensorFlow, Git, Hadoop",PhD,10,Energy,2024-10-21,2024-12-06,1959,5.3,DataVision Ltd +AI13414,Data Analyst,86376,USD,86376,MI,FT,Israel,L,Israel,50,"TensorFlow, Data Visualization, Statistics",Associate,3,Telecommunications,2024-04-21,2024-06-24,821,5.2,Digital Transformation LLC +AI13415,Data Engineer,78208,USD,78208,SE,FL,South Korea,S,South Korea,50,"GCP, PyTorch, NLP, MLOps, Java",Bachelor,7,Government,2024-06-13,2024-08-21,2037,6.7,Predictive Systems +AI13416,AI Research Scientist,83692,USD,83692,MI,CT,United States,S,Poland,100,"Git, Tableau, Data Visualization, Kubernetes",Master,2,Real Estate,2024-03-31,2024-05-15,1315,8.6,Autonomous Tech +AI13417,Robotics Engineer,143315,USD,143315,EX,FT,Ireland,M,Ireland,100,"Linux, Data Visualization, Docker",Associate,16,Healthcare,2024-10-09,2024-10-29,1430,8.1,Cognitive Computing +AI13418,AI Architect,75949,AUD,102531,EN,FL,Australia,L,Australia,0,"R, PyTorch, Docker",Bachelor,0,Technology,2024-11-21,2025-01-14,1323,5.7,Smart Analytics +AI13419,AI Architect,124751,EUR,106038,SE,FL,France,M,France,50,"Python, TensorFlow, Data Visualization, Hadoop",PhD,7,Healthcare,2024-10-23,2024-12-08,866,5.4,AI Innovations +AI13420,NLP Engineer,189998,EUR,161498,EX,FT,Netherlands,L,Ghana,50,"Kubernetes, SQL, Data Visualization, MLOps, PyTorch",Associate,17,Real Estate,2024-08-31,2024-09-23,1284,6.9,Advanced Robotics +AI13421,Data Engineer,193193,EUR,164214,EX,CT,France,L,France,50,"Linux, Azure, SQL, R, Java",Associate,14,Healthcare,2024-06-21,2024-07-10,1148,8.1,Digital Transformation LLC +AI13422,AI Consultant,180069,SGD,234090,EX,PT,Singapore,L,Singapore,50,"PyTorch, GCP, Hadoop",Master,11,Consulting,2024-09-29,2024-11-16,2011,7.2,Digital Transformation LLC +AI13423,Deep Learning Engineer,202205,USD,202205,EX,FT,Israel,L,Israel,0,"PyTorch, Spark, Python",PhD,14,Energy,2024-12-20,2025-01-21,1805,8.6,Advanced Robotics +AI13424,NLP Engineer,84851,USD,84851,EN,FL,Sweden,L,Sweden,50,"Kubernetes, Tableau, TensorFlow, GCP, Python",PhD,1,Gaming,2024-01-23,2024-02-26,691,7.6,Quantum Computing Inc +AI13425,Autonomous Systems Engineer,100135,GBP,75101,MI,FL,United Kingdom,S,United Kingdom,0,"Computer Vision, Scala, PyTorch, Linux",Associate,4,Retail,2024-06-22,2024-07-08,942,5.8,Smart Analytics +AI13426,Principal Data Scientist,149157,EUR,126783,SE,FT,Netherlands,L,Netherlands,0,"GCP, Docker, Data Visualization, Scala",Associate,9,Energy,2024-07-08,2024-09-14,2036,5.2,Quantum Computing Inc +AI13427,Data Engineer,255277,CAD,319096,EX,CT,Canada,L,Canada,50,"Kubernetes, NLP, R, Deep Learning",Bachelor,17,Retail,2024-08-22,2024-09-28,530,5,Advanced Robotics +AI13428,NLP Engineer,118601,CHF,106741,EN,CT,Switzerland,L,Switzerland,50,"Kubernetes, Git, SQL, TensorFlow",Master,1,Government,2024-07-25,2024-09-22,2069,5.3,TechCorp Inc +AI13429,AI Specialist,204430,AUD,275981,EX,FL,Australia,M,South Africa,0,"TensorFlow, Python, NLP, AWS, Git",Bachelor,16,Gaming,2024-05-25,2024-07-13,2183,8.1,Neural Networks Co +AI13430,AI Specialist,148777,USD,148777,SE,FT,Norway,S,India,0,"Java, Linux, PyTorch, NLP, Kubernetes",Master,5,Telecommunications,2025-04-24,2025-06-11,1673,8.5,Digital Transformation LLC +AI13431,AI Software Engineer,280124,USD,280124,EX,PT,Norway,L,Turkey,50,"Tableau, Data Visualization, Java, TensorFlow",PhD,19,Automotive,2024-12-15,2025-01-22,617,5.6,Advanced Robotics +AI13432,AI Software Engineer,68849,EUR,58522,EN,PT,Germany,L,Germany,100,"MLOps, Hadoop, Spark",Master,1,Energy,2025-03-14,2025-04-03,2099,8.6,Machine Intelligence Group +AI13433,AI Research Scientist,29926,USD,29926,MI,FT,India,L,India,50,"Statistics, Azure, Spark, PyTorch, Deep Learning",Master,4,Education,2024-05-06,2024-07-01,1172,7.6,Future Systems +AI13434,ML Ops Engineer,70863,USD,70863,EN,FT,Israel,L,Israel,50,"R, MLOps, SQL",PhD,0,Manufacturing,2025-02-23,2025-04-18,1950,7.9,Quantum Computing Inc +AI13435,Research Scientist,63834,USD,63834,EN,CT,Israel,M,Israel,0,"Java, GCP, MLOps, Deep Learning",Master,0,Transportation,2024-04-30,2024-07-09,922,9.3,Digital Transformation LLC +AI13436,Deep Learning Engineer,332210,CHF,298989,EX,FT,Switzerland,M,South Africa,100,"GCP, Deep Learning, Git",PhD,15,Energy,2025-02-03,2025-03-22,2134,10,Quantum Computing Inc +AI13437,AI Product Manager,67710,USD,67710,EN,PT,Denmark,S,Sweden,0,"Statistics, Linux, Data Visualization",Master,0,Manufacturing,2024-12-29,2025-02-24,1974,9.9,Future Systems +AI13438,Data Scientist,129621,EUR,110178,EX,CT,Austria,M,Argentina,0,"Git, Docker, Java, R, Hadoop",Bachelor,15,Real Estate,2024-01-25,2024-03-27,2066,9.4,Advanced Robotics +AI13439,Research Scientist,84399,USD,84399,MI,FL,Ireland,L,Switzerland,0,"AWS, MLOps, Python",Bachelor,4,Energy,2024-05-01,2024-07-01,1456,8.2,Machine Intelligence Group +AI13440,Research Scientist,140977,GBP,105733,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, PyTorch, Java",PhD,9,Media,2024-07-26,2024-10-04,1604,7.4,TechCorp Inc +AI13441,Research Scientist,130649,CHF,117584,EN,CT,Switzerland,L,Switzerland,0,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Retail,2024-04-03,2024-05-07,1426,5.7,Machine Intelligence Group +AI13442,AI Product Manager,94972,EUR,80726,MI,PT,France,L,New Zealand,100,"SQL, MLOps, Computer Vision, Linux, GCP",Bachelor,4,Consulting,2024-05-18,2024-06-12,1705,7.4,Predictive Systems +AI13443,AI Specialist,176030,EUR,149626,EX,PT,Austria,S,Finland,50,"Git, Scala, AWS",Master,18,Real Estate,2024-04-14,2024-06-13,1595,7.6,DeepTech Ventures +AI13444,Research Scientist,101314,USD,101314,SE,PT,Israel,M,Israel,100,"Linux, Spark, Computer Vision, MLOps, Python",PhD,9,Telecommunications,2024-10-10,2024-11-28,1405,6,Cloud AI Solutions +AI13445,AI Consultant,59806,EUR,50835,EN,PT,Germany,S,Germany,0,"Docker, Scala, Statistics",Associate,1,Consulting,2025-01-08,2025-01-24,965,6.3,Neural Networks Co +AI13446,Data Analyst,106748,USD,106748,SE,PT,Israel,S,Netherlands,100,"Scala, Python, Computer Vision, Tableau",Bachelor,5,Education,2024-04-23,2024-06-05,1187,7.4,TechCorp Inc +AI13447,Autonomous Systems Engineer,49405,CAD,61756,EN,PT,Canada,M,Canada,0,"Linux, Python, Tableau",PhD,0,Automotive,2025-01-10,2025-02-22,2350,5,Digital Transformation LLC +AI13448,Data Scientist,230116,SGD,299151,EX,PT,Singapore,L,Turkey,100,"Python, Java, Computer Vision, TensorFlow, GCP",Bachelor,18,Energy,2024-12-25,2025-02-15,1605,8,Autonomous Tech +AI13449,AI Specialist,155786,EUR,132418,SE,FL,Netherlands,M,United States,50,"NLP, SQL, MLOps",Bachelor,8,Education,2024-01-02,2024-01-26,1425,8.5,AI Innovations +AI13450,Data Scientist,78295,EUR,66551,MI,PT,Germany,M,Germany,0,"Scala, Python, Tableau, NLP, MLOps",Master,4,Technology,2024-08-02,2024-08-31,2422,6.2,Machine Intelligence Group +AI13451,ML Ops Engineer,116184,USD,116184,MI,CT,Ireland,L,Czech Republic,0,"SQL, MLOps, TensorFlow, Git, Data Visualization",PhD,4,Gaming,2024-03-22,2024-05-06,1048,8.4,DeepTech Ventures +AI13452,Machine Learning Engineer,70480,USD,70480,EN,FT,United States,S,United States,50,"Mathematics, Statistics, TensorFlow, PyTorch",Master,1,Media,2024-02-26,2024-03-24,1238,9.2,Quantum Computing Inc +AI13453,Machine Learning Engineer,257142,EUR,218571,EX,FL,France,L,South Korea,50,"Python, Kubernetes, GCP, R",PhD,10,Retail,2024-04-19,2024-05-06,2218,9.8,Advanced Robotics +AI13454,Head of AI,75895,CHF,68306,EN,PT,Switzerland,M,Spain,0,"Hadoop, AWS, Tableau",PhD,0,Energy,2024-10-11,2024-11-27,1842,7.3,DataVision Ltd +AI13455,Autonomous Systems Engineer,130146,JPY,14316060,MI,FL,Japan,L,Japan,0,"GCP, Docker, MLOps, Tableau, Hadoop",Bachelor,2,Telecommunications,2024-09-28,2024-10-18,2259,6.4,Quantum Computing Inc +AI13456,Head of AI,62607,USD,62607,SE,PT,China,S,China,0,"Spark, R, Linux, SQL",Bachelor,9,Media,2024-08-08,2024-10-04,2050,5.1,DataVision Ltd +AI13457,AI Specialist,213739,USD,213739,SE,CT,Denmark,L,Denmark,50,"SQL, Scala, Data Visualization, Linux, AWS",Associate,5,Energy,2024-03-28,2024-06-04,561,5.3,AI Innovations +AI13458,Research Scientist,239862,AUD,323814,EX,CT,Australia,L,Australia,50,"GCP, Hadoop, R",Bachelor,18,Government,2024-06-03,2024-07-22,713,5.4,AI Innovations +AI13459,Deep Learning Engineer,85775,EUR,72909,EN,FT,Austria,L,Colombia,50,"Spark, Data Visualization, Hadoop, Docker",Master,0,Retail,2024-06-15,2024-07-07,1378,6.3,Cognitive Computing +AI13460,Head of AI,52732,CAD,65915,EN,FL,Canada,M,Canada,100,"GCP, TensorFlow, Python, NLP",Bachelor,1,Finance,2025-02-04,2025-03-01,2406,6.5,AI Innovations +AI13461,Data Scientist,134420,SGD,174746,SE,FT,Singapore,M,Singapore,100,"Hadoop, SQL, Kubernetes",Bachelor,8,Education,2025-01-17,2025-03-06,1438,8.8,Quantum Computing Inc +AI13462,Robotics Engineer,261477,CHF,235329,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Python, GCP",Associate,12,Retail,2024-10-29,2024-12-02,1127,7,Cognitive Computing +AI13463,AI Consultant,163591,CHF,147232,SE,CT,Switzerland,M,Switzerland,100,"SQL, Hadoop, Scala, Deep Learning",Bachelor,9,Telecommunications,2024-09-24,2024-10-20,1728,8.4,Quantum Computing Inc +AI13464,AI Architect,140181,AUD,189244,SE,PT,Australia,M,Chile,0,"Azure, Tableau, Linux, Docker",Bachelor,9,Media,2024-03-23,2024-05-13,2319,6.6,Autonomous Tech +AI13465,Deep Learning Engineer,142202,AUD,191973,SE,PT,Australia,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, Statistics",Master,6,Real Estate,2024-03-20,2024-05-09,1741,9.8,Predictive Systems +AI13466,Research Scientist,157835,GBP,118376,EX,CT,United Kingdom,S,Italy,50,"GCP, AWS, Linux, Deep Learning, SQL",Master,16,Consulting,2024-02-25,2024-04-11,620,9.3,Cognitive Computing +AI13467,Deep Learning Engineer,186913,USD,186913,SE,FL,United States,L,United States,50,"TensorFlow, GCP, Deep Learning",Associate,8,Government,2024-02-04,2024-04-08,1879,9.4,Predictive Systems +AI13468,Machine Learning Engineer,133440,USD,133440,SE,FT,Sweden,S,Sweden,0,"Hadoop, Scala, Kubernetes, Mathematics, Python",Bachelor,9,Telecommunications,2025-03-15,2025-04-21,1873,5.5,DeepTech Ventures +AI13469,Robotics Engineer,138149,USD,138149,EX,CT,Ireland,S,New Zealand,50,"Deep Learning, Kubernetes, Computer Vision",PhD,10,Technology,2024-03-27,2024-05-11,617,6.3,AI Innovations +AI13470,Principal Data Scientist,130691,EUR,111087,SE,FL,Austria,L,Austria,0,"Kubernetes, Deep Learning, Java, AWS, Computer Vision",PhD,9,Media,2024-09-13,2024-10-24,1605,5.8,Machine Intelligence Group +AI13471,AI Research Scientist,87469,USD,87469,MI,PT,Israel,M,Israel,100,"Hadoop, SQL, Tableau, Azure, Kubernetes",Master,3,Government,2024-10-23,2024-11-28,2305,9.2,TechCorp Inc +AI13472,AI Specialist,106777,GBP,80083,MI,FL,United Kingdom,L,United Kingdom,0,"Deep Learning, SQL, Spark",PhD,3,Finance,2024-12-08,2024-12-26,1723,10,Neural Networks Co +AI13473,NLP Engineer,50461,USD,50461,SE,PT,China,M,China,100,"Data Visualization, Hadoop, Computer Vision",Associate,7,Finance,2024-04-01,2024-05-03,2354,5.8,Algorithmic Solutions +AI13474,Computer Vision Engineer,159609,EUR,135668,EX,FL,Austria,M,Indonesia,0,"Python, Git, TensorFlow",Associate,11,Consulting,2024-03-14,2024-03-29,1071,8.5,Predictive Systems +AI13475,Machine Learning Researcher,154149,EUR,131027,EX,PT,France,M,France,0,"Python, SQL, Linux, GCP",Master,18,Manufacturing,2024-07-14,2024-09-09,1775,8.5,Autonomous Tech +AI13476,AI Software Engineer,64819,GBP,48614,EN,FL,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Azure",Associate,1,Consulting,2024-05-16,2024-07-22,2036,5.7,TechCorp Inc +AI13477,Principal Data Scientist,125314,SGD,162908,MI,FL,Singapore,L,Singapore,100,"AWS, Azure, Spark, Computer Vision",Bachelor,2,Manufacturing,2024-11-03,2024-11-17,2038,9.1,Algorithmic Solutions +AI13478,AI Specialist,55051,USD,55051,EN,PT,Israel,S,Australia,100,"Scala, SQL, Azure",PhD,0,Technology,2024-11-01,2024-12-01,1137,7.1,Algorithmic Solutions +AI13479,AI Specialist,32595,USD,32595,MI,FT,India,L,India,100,"Hadoop, Java, NLP",Associate,4,Media,2024-04-13,2024-05-19,548,9.6,Digital Transformation LLC +AI13480,AI Architect,71110,EUR,60444,MI,FL,Netherlands,S,Belgium,100,"Git, R, TensorFlow",PhD,2,Finance,2024-06-25,2024-09-04,2334,7.8,Cognitive Computing +AI13481,AI Software Engineer,169547,JPY,18650170,EX,PT,Japan,S,Japan,100,"NLP, GCP, Tableau, PyTorch",Master,18,Finance,2024-03-09,2024-05-04,848,5.8,Algorithmic Solutions +AI13482,ML Ops Engineer,178084,CHF,160276,SE,CT,Switzerland,S,Switzerland,100,"Python, TensorFlow, AWS",Master,8,Real Estate,2025-03-29,2025-05-13,1319,8.4,Autonomous Tech +AI13483,AI Architect,62829,GBP,47122,EN,FL,United Kingdom,S,Romania,50,"NLP, Hadoop, Scala, SQL, GCP",PhD,1,Finance,2025-01-03,2025-01-24,1496,5.4,Neural Networks Co +AI13484,AI Research Scientist,159514,USD,159514,EX,CT,South Korea,M,South Korea,50,"Python, NLP, Mathematics, Git",Associate,17,Healthcare,2025-02-06,2025-04-13,2270,6.4,AI Innovations +AI13485,AI Architect,127374,USD,127374,MI,PT,Norway,S,Chile,50,"Python, MLOps, NLP, Linux, AWS",PhD,2,Finance,2024-04-24,2024-05-13,2290,6.2,Quantum Computing Inc +AI13486,ML Ops Engineer,123377,USD,123377,MI,FT,Sweden,L,Ireland,100,"Hadoop, Scala, Mathematics, Linux",Master,2,Automotive,2024-10-31,2024-12-05,603,5.5,TechCorp Inc +AI13487,AI Product Manager,131293,JPY,14442230,SE,CT,Japan,M,Japan,0,"Deep Learning, AWS, Python, Mathematics, Hadoop",Master,5,Retail,2024-06-16,2024-08-22,760,8,AI Innovations +AI13488,Data Engineer,69197,EUR,58817,EN,PT,Germany,M,Germany,50,"SQL, Docker, MLOps, Hadoop",Associate,0,Energy,2025-02-20,2025-03-25,1451,7.2,Advanced Robotics +AI13489,ML Ops Engineer,96379,EUR,81922,MI,FL,France,M,Argentina,100,"Tableau, Computer Vision, Docker",Associate,3,Transportation,2024-04-06,2024-06-07,557,7.9,Autonomous Tech +AI13490,Robotics Engineer,57105,USD,57105,EN,CT,Israel,L,Spain,50,"R, Tableau, SQL, Deep Learning",Associate,1,Media,2024-10-16,2024-12-07,2426,6.8,Machine Intelligence Group +AI13491,AI Consultant,41328,USD,41328,MI,FL,China,M,New Zealand,50,"Docker, SQL, Azure, Python, Mathematics",Master,2,Government,2024-02-10,2024-02-27,576,9.9,Machine Intelligence Group +AI13492,Data Scientist,119623,USD,119623,MI,CT,Denmark,L,Denmark,0,"Python, TensorFlow, Deep Learning, SQL",Bachelor,2,Technology,2025-04-29,2025-06-22,1740,6.8,DataVision Ltd +AI13493,Robotics Engineer,158417,USD,158417,EX,PT,Ireland,M,Ireland,50,"Python, Azure, TensorFlow",Associate,10,Technology,2025-01-18,2025-03-01,2083,8,Autonomous Tech +AI13494,Data Scientist,82345,AUD,111166,MI,FT,Australia,S,Australia,100,"Deep Learning, Tableau, Statistics",Bachelor,4,Gaming,2025-04-15,2025-05-22,2475,5.6,DataVision Ltd +AI13495,Computer Vision Engineer,28336,USD,28336,EN,CT,India,M,India,50,"Statistics, Mathematics, AWS",Bachelor,0,Telecommunications,2024-12-21,2025-02-04,2180,6.9,TechCorp Inc +AI13496,Computer Vision Engineer,176246,USD,176246,EX,FT,South Korea,S,South Korea,50,"Docker, Kubernetes, MLOps, Deep Learning",Bachelor,15,Retail,2025-01-16,2025-03-29,1879,5.4,Smart Analytics +AI13497,NLP Engineer,47000,USD,47000,SE,FL,India,S,India,100,"Python, NLP, TensorFlow, GCP",Master,7,Transportation,2025-03-26,2025-04-12,1770,8.1,AI Innovations +AI13498,ML Ops Engineer,47164,USD,47164,EN,FL,South Korea,M,South Korea,50,"Computer Vision, Deep Learning, Scala, Python",PhD,1,Media,2025-04-08,2025-05-29,2331,5.5,DataVision Ltd +AI13499,Principal Data Scientist,132818,SGD,172663,SE,CT,Singapore,M,Singapore,0,"Linux, MLOps, Scala, Data Visualization",PhD,5,Real Estate,2024-12-06,2025-01-29,1896,8.9,Neural Networks Co +AI13500,AI Specialist,85866,EUR,72986,MI,CT,Germany,L,Germany,100,"PyTorch, Deep Learning, Kubernetes, AWS, Computer Vision",PhD,3,Media,2024-11-23,2025-01-19,2172,8,Neural Networks Co +AI13501,NLP Engineer,92368,EUR,78513,SE,FL,Germany,S,Germany,100,"AWS, Linux, Spark",Master,8,Automotive,2024-06-05,2024-06-25,1291,6.5,Autonomous Tech +AI13502,Computer Vision Engineer,100531,USD,100531,SE,PT,South Korea,L,South Korea,0,"SQL, Docker, Python, MLOps",Associate,6,Consulting,2024-07-17,2024-08-12,988,6.4,Algorithmic Solutions +AI13503,Data Analyst,87818,USD,87818,MI,PT,Finland,S,Argentina,50,"Kubernetes, Azure, Java, Data Visualization, GCP",Associate,3,Energy,2025-04-15,2025-06-10,1287,9.1,Digital Transformation LLC +AI13504,Robotics Engineer,214112,AUD,289051,EX,CT,Australia,S,Australia,100,"Python, Mathematics, Hadoop, Scala, Azure",PhD,16,Telecommunications,2025-03-02,2025-03-24,1204,7.7,Future Systems +AI13505,Data Engineer,137081,JPY,15078910,SE,FL,Japan,L,Switzerland,100,"Tableau, Python, Scala, Spark",Bachelor,7,Automotive,2024-01-28,2024-03-22,1876,5.3,DataVision Ltd +AI13506,Data Analyst,53421,USD,53421,SE,PT,India,M,India,0,"Kubernetes, Git, NLP, TensorFlow, PyTorch",Associate,8,Healthcare,2024-08-02,2024-09-04,931,5.6,Autonomous Tech +AI13507,AI Architect,75794,GBP,56846,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Docker, Spark, Computer Vision, PyTorch",Associate,0,Gaming,2025-03-24,2025-04-24,1153,6.2,Cognitive Computing +AI13508,NLP Engineer,175103,EUR,148838,EX,CT,Austria,L,Austria,50,"Java, Scala, GCP",PhD,17,Telecommunications,2024-06-03,2024-07-02,1294,5.3,Neural Networks Co +AI13509,ML Ops Engineer,175669,CHF,158102,SE,FL,Switzerland,S,Switzerland,100,"TensorFlow, Git, SQL",PhD,6,Media,2024-08-29,2024-09-28,1991,7.7,Autonomous Tech +AI13510,AI Architect,152942,USD,152942,EX,CT,Israel,L,Israel,0,"Kubernetes, Java, Git",PhD,14,Transportation,2024-10-04,2024-10-25,2411,8.4,Future Systems +AI13511,AI Architect,115652,USD,115652,MI,PT,Finland,L,Finland,100,"Linux, SQL, PyTorch, GCP, TensorFlow",Master,4,Gaming,2025-04-16,2025-05-09,691,5.9,Cognitive Computing +AI13512,AI Product Manager,254643,EUR,216447,EX,CT,Netherlands,L,Netherlands,0,"Hadoop, Statistics, Linux, Data Visualization",Associate,17,Gaming,2024-03-05,2024-05-17,1152,6.3,Autonomous Tech +AI13513,Machine Learning Researcher,113576,EUR,96540,MI,PT,Germany,L,Latvia,0,"SQL, Linux, R, Hadoop, Computer Vision",Master,4,Media,2024-10-20,2024-11-21,1737,7.2,Smart Analytics +AI13514,Data Engineer,82775,USD,82775,EN,FL,Norway,M,Norway,100,"Mathematics, R, Docker, Spark, SQL",PhD,1,Telecommunications,2024-02-14,2024-03-18,1834,9.4,Quantum Computing Inc +AI13515,AI Architect,166158,USD,166158,SE,PT,Norway,S,Norway,100,"Java, MLOps, NLP, Git, Mathematics",PhD,5,Transportation,2024-11-05,2024-12-28,604,9.8,AI Innovations +AI13516,Computer Vision Engineer,128965,USD,128965,MI,FT,United States,L,United States,0,"GCP, TensorFlow, Mathematics, Computer Vision, AWS",PhD,4,Consulting,2024-10-04,2024-11-27,871,8,Autonomous Tech +AI13517,Data Scientist,117391,USD,117391,SE,CT,South Korea,M,South Korea,50,"Spark, TensorFlow, GCP",Associate,9,Telecommunications,2024-11-06,2025-01-14,1903,8.8,Autonomous Tech +AI13518,Data Analyst,270558,USD,270558,EX,FL,Norway,S,Norway,0,"GCP, Python, MLOps, Tableau, Kubernetes",Master,17,Media,2025-01-07,2025-03-07,2124,9.3,Neural Networks Co +AI13519,Data Engineer,190549,CAD,238186,EX,FL,Canada,S,Spain,50,"Python, Git, MLOps",Bachelor,10,Education,2024-08-18,2024-10-22,1395,6.6,AI Innovations +AI13520,Computer Vision Engineer,53483,USD,53483,EN,CT,South Korea,S,Thailand,0,"Python, Deep Learning, SQL",Bachelor,1,Gaming,2024-04-20,2024-06-01,1095,6.2,DataVision Ltd +AI13521,Computer Vision Engineer,119338,USD,119338,SE,FT,United States,S,Kenya,50,"TensorFlow, R, MLOps, Java, AWS",PhD,6,Gaming,2024-09-06,2024-11-05,2370,6.9,Cloud AI Solutions +AI13522,AI Architect,66333,USD,66333,MI,PT,South Korea,S,Thailand,100,"Statistics, Hadoop, Tableau, GCP",PhD,4,Education,2024-10-09,2024-11-12,1271,7.9,Predictive Systems +AI13523,Machine Learning Researcher,102503,GBP,76877,MI,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Scala, Docker, Java, Deep Learning",Master,4,Media,2024-01-23,2024-03-11,1799,6.3,Cloud AI Solutions +AI13524,AI Architect,135092,USD,135092,SE,CT,Finland,M,Finland,0,"Scala, SQL, PyTorch, Spark",Bachelor,8,Healthcare,2024-11-29,2024-12-25,2206,5.5,Cloud AI Solutions +AI13525,Machine Learning Engineer,102919,USD,102919,SE,CT,South Korea,S,South Korea,100,"GCP, Python, Java, Docker",PhD,5,Government,2024-06-09,2024-08-01,897,9.4,Cognitive Computing +AI13526,Principal Data Scientist,135359,SGD,175967,SE,CT,Singapore,M,Singapore,100,"TensorFlow, SQL, GCP, Java, Statistics",Bachelor,9,Transportation,2024-12-16,2025-02-11,1370,6.7,AI Innovations +AI13527,Machine Learning Engineer,125939,USD,125939,MI,CT,Norway,L,Norway,50,"Mathematics, Linux, Hadoop, TensorFlow",PhD,2,Retail,2025-01-19,2025-03-22,674,6.3,Autonomous Tech +AI13528,Research Scientist,187712,CHF,168941,SE,CT,Switzerland,S,Switzerland,0,"MLOps, R, Azure",Associate,8,Retail,2024-10-31,2024-12-06,1040,8,Advanced Robotics +AI13529,AI Research Scientist,243121,SGD,316057,EX,PT,Singapore,M,Singapore,50,"Java, SQL, Data Visualization",Associate,11,Transportation,2024-01-06,2024-03-04,716,5.8,AI Innovations +AI13530,AI Software Engineer,53273,USD,53273,SE,FT,India,M,India,50,"Python, Statistics, Hadoop, TensorFlow",PhD,6,Government,2024-12-27,2025-02-09,2149,7.2,Neural Networks Co +AI13531,Data Analyst,34231,USD,34231,EN,PT,China,L,China,0,"Kubernetes, Python, Git",Master,0,Education,2024-01-25,2024-03-09,2443,8.8,Algorithmic Solutions +AI13532,Research Scientist,64663,GBP,48497,EN,FT,United Kingdom,S,United Kingdom,0,"MLOps, Azure, TensorFlow, Deep Learning, Python",PhD,1,Manufacturing,2024-12-11,2025-02-16,2320,7.7,Cognitive Computing +AI13533,Robotics Engineer,145887,CHF,131298,SE,FL,Switzerland,S,Switzerland,50,"Deep Learning, SQL, PyTorch, Linux",Associate,7,Manufacturing,2024-12-23,2025-01-08,2106,6,Quantum Computing Inc +AI13534,Robotics Engineer,225404,GBP,169053,EX,FL,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning",Master,16,Technology,2025-03-07,2025-03-31,1137,8.3,Future Systems +AI13535,Machine Learning Researcher,118211,USD,118211,SE,FL,South Korea,M,South Korea,0,"Spark, GCP, SQL, MLOps",Master,5,Healthcare,2024-04-01,2024-05-24,817,8,DeepTech Ventures +AI13536,AI Product Manager,121319,USD,121319,MI,CT,Norway,M,Romania,50,"R, Tableau, Java, Git, Computer Vision",Associate,4,Consulting,2024-03-10,2024-05-14,737,7.2,Autonomous Tech +AI13537,Robotics Engineer,83754,JPY,9212940,MI,FL,Japan,S,Denmark,50,"Computer Vision, Kubernetes, Deep Learning",Bachelor,4,Manufacturing,2024-08-23,2024-10-25,2217,8.4,Neural Networks Co +AI13538,Head of AI,41420,USD,41420,SE,CT,India,M,India,100,"Java, Azure, MLOps, Hadoop, Spark",PhD,7,Retail,2024-03-24,2024-04-13,511,8.4,Advanced Robotics +AI13539,ML Ops Engineer,167184,USD,167184,SE,CT,Denmark,L,Nigeria,50,"Computer Vision, SQL, Python, Azure",Associate,7,Energy,2025-04-05,2025-05-14,1470,5.7,TechCorp Inc +AI13540,Data Engineer,79973,USD,79973,EN,FL,Norway,S,Norway,0,"Scala, Kubernetes, PyTorch",Associate,0,Retail,2024-02-29,2024-04-20,1710,7.4,DataVision Ltd +AI13541,Machine Learning Engineer,215068,USD,215068,SE,CT,Norway,L,Norway,50,"Python, TensorFlow, Computer Vision, Git, Linux",Master,5,Manufacturing,2024-07-15,2024-09-14,1303,9.2,Cloud AI Solutions +AI13542,AI Research Scientist,61811,USD,61811,EN,FT,Israel,S,Estonia,0,"Python, Tableau, Kubernetes",Master,0,Media,2025-02-18,2025-04-21,1234,8.9,DeepTech Ventures +AI13543,AI Architect,105290,SGD,136877,SE,FL,Singapore,S,Singapore,0,"SQL, Spark, Scala, Git, Azure",Associate,6,Telecommunications,2025-03-12,2025-05-21,1211,5.4,Quantum Computing Inc +AI13544,AI Consultant,87480,SGD,113724,MI,FL,Singapore,M,Singapore,100,"SQL, Tableau, Spark, PyTorch",Associate,3,Education,2024-12-24,2025-01-25,1963,7.2,Advanced Robotics +AI13545,Computer Vision Engineer,100005,CAD,125006,MI,FL,Canada,M,Romania,0,"Computer Vision, R, Linux, PyTorch, Git",PhD,3,Education,2024-11-14,2024-12-19,1834,6.6,Cognitive Computing +AI13546,Robotics Engineer,162358,CHF,146122,MI,CT,Switzerland,L,Switzerland,50,"SQL, Python, Tableau, MLOps, Spark",Bachelor,3,Finance,2024-01-23,2024-03-14,504,9.3,AI Innovations +AI13547,Machine Learning Researcher,158769,USD,158769,EX,FL,South Korea,S,Ireland,0,"MLOps, NLP, R, Python, Tableau",Associate,10,Government,2025-02-24,2025-03-31,1856,9,Cognitive Computing +AI13548,Machine Learning Engineer,231743,EUR,196982,EX,CT,Netherlands,S,Netherlands,100,"SQL, Scala, Docker, Mathematics, Computer Vision",Associate,12,Healthcare,2025-04-04,2025-05-12,1675,8.3,Advanced Robotics +AI13549,Robotics Engineer,198048,EUR,168341,EX,FL,Germany,L,Germany,100,"Java, MLOps, Git, Spark, Scala",PhD,14,Retail,2025-02-17,2025-04-30,2389,7.9,Neural Networks Co +AI13550,Computer Vision Engineer,170409,USD,170409,SE,FT,Norway,M,Norway,50,"Python, Data Visualization, PyTorch, Tableau, AWS",Bachelor,8,Technology,2024-03-22,2024-05-18,1565,8.9,Predictive Systems +AI13551,Data Scientist,137317,JPY,15104870,SE,FT,Japan,M,Japan,100,"Kubernetes, Spark, GCP, Python, Mathematics",Master,7,Real Estate,2025-04-16,2025-06-17,506,9.5,TechCorp Inc +AI13552,Data Analyst,215252,USD,215252,EX,FT,Norway,L,Norway,50,"Spark, Python, Data Visualization",PhD,16,Government,2025-03-02,2025-05-08,1376,7.6,DeepTech Ventures +AI13553,NLP Engineer,115357,AUD,155732,SE,PT,Australia,S,Colombia,100,"R, Kubernetes, SQL, Hadoop, Statistics",Master,6,Education,2025-02-13,2025-03-17,737,7.6,Smart Analytics +AI13554,NLP Engineer,78765,EUR,66950,MI,CT,Netherlands,M,Netherlands,100,"TensorFlow, Hadoop, Scala",Associate,2,Gaming,2025-01-01,2025-03-11,1847,6.3,Autonomous Tech +AI13555,Deep Learning Engineer,111065,CHF,99959,EN,CT,Switzerland,M,Switzerland,50,"Git, NLP, Scala, Computer Vision",Bachelor,0,Gaming,2024-02-06,2024-03-28,1593,7.4,Machine Intelligence Group +AI13556,Data Scientist,79550,USD,79550,SE,PT,China,L,China,100,"Tableau, Data Visualization, AWS",Associate,8,Government,2024-05-13,2024-07-24,2221,5.3,TechCorp Inc +AI13557,Data Analyst,155394,USD,155394,EX,PT,South Korea,S,New Zealand,50,"R, Tableau, Computer Vision",Associate,12,Healthcare,2025-01-03,2025-02-28,2068,7.5,Advanced Robotics +AI13558,Deep Learning Engineer,92899,USD,92899,MI,FL,Israel,L,Israel,100,"Java, MLOps, AWS",Bachelor,4,Manufacturing,2024-09-14,2024-10-24,1009,9.6,Digital Transformation LLC +AI13559,Data Engineer,94215,GBP,70661,MI,CT,United Kingdom,S,Argentina,50,"NLP, Mathematics, Kubernetes, MLOps",Bachelor,3,Technology,2024-12-30,2025-03-07,1513,8.3,Quantum Computing Inc +AI13560,Robotics Engineer,80817,AUD,109103,MI,PT,Australia,M,Nigeria,50,"Computer Vision, Linux, MLOps",PhD,3,Gaming,2024-09-29,2024-10-14,1084,8.4,DeepTech Ventures +AI13561,Machine Learning Researcher,142421,EUR,121058,EX,FT,Austria,S,Austria,100,"Spark, Scala, Deep Learning, TensorFlow, Azure",Associate,16,Healthcare,2024-07-13,2024-09-16,1113,5.2,Neural Networks Co +AI13562,AI Software Engineer,162016,SGD,210621,EX,FL,Singapore,M,France,50,"NLP, Python, TensorFlow, Spark",Bachelor,10,Gaming,2025-02-15,2025-03-29,2037,9,Quantum Computing Inc +AI13563,AI Specialist,240723,USD,240723,EX,CT,Ireland,M,Ireland,100,"Computer Vision, AWS, Kubernetes, Data Visualization, Git",PhD,17,Consulting,2024-02-07,2024-04-13,624,7.6,Cloud AI Solutions +AI13564,Computer Vision Engineer,177202,USD,177202,EX,FT,Denmark,M,United States,0,"Kubernetes, R, SQL, Java",Associate,11,Telecommunications,2025-01-09,2025-02-20,713,9.7,Digital Transformation LLC +AI13565,AI Software Engineer,19994,USD,19994,EN,PT,India,S,India,0,"Deep Learning, Mathematics, Scala",Associate,1,Consulting,2024-12-07,2025-01-07,1936,6.2,AI Innovations +AI13566,Research Scientist,87827,GBP,65870,MI,CT,United Kingdom,M,China,100,"Scala, R, AWS",Bachelor,4,Government,2025-03-13,2025-05-19,859,5.3,Digital Transformation LLC +AI13567,Data Engineer,246485,SGD,320431,EX,CT,Singapore,L,Singapore,50,"Kubernetes, Azure, Deep Learning, R",PhD,17,Real Estate,2025-01-02,2025-03-16,561,9,TechCorp Inc +AI13568,AI Architect,185718,JPY,20428980,EX,FL,Japan,S,Japan,50,"Scala, R, SQL, GCP, Mathematics",Associate,12,Technology,2024-01-31,2024-02-25,2094,7.8,Digital Transformation LLC +AI13569,AI Consultant,80076,USD,80076,SE,FT,China,L,Portugal,100,"Docker, Java, Statistics, Git",PhD,9,Manufacturing,2024-01-15,2024-02-12,1429,8.4,Advanced Robotics +AI13570,AI Software Engineer,184303,GBP,138227,SE,FL,United Kingdom,L,Mexico,0,"Python, Deep Learning, TensorFlow, Computer Vision, Kubernetes",Associate,5,Gaming,2024-10-28,2025-01-07,1685,6.5,TechCorp Inc +AI13571,Computer Vision Engineer,144334,CAD,180418,EX,CT,Canada,S,Canada,50,"Data Visualization, Java, Deep Learning",Associate,10,Government,2024-08-16,2024-10-01,1155,5.5,DeepTech Ventures +AI13572,Principal Data Scientist,136225,EUR,115791,SE,CT,Austria,L,Austria,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,9,Energy,2025-01-05,2025-03-08,1676,8.4,Smart Analytics +AI13573,Machine Learning Researcher,132186,USD,132186,SE,CT,Finland,M,Finland,100,"Java, NLP, AWS, Statistics",Associate,7,Manufacturing,2025-01-30,2025-03-03,1939,5.3,Advanced Robotics +AI13574,Deep Learning Engineer,125855,USD,125855,MI,CT,Sweden,L,Sweden,50,"R, TensorFlow, Kubernetes",Bachelor,3,Media,2024-12-21,2025-01-05,1426,9.5,Machine Intelligence Group +AI13575,Head of AI,56288,USD,56288,EN,FT,South Korea,S,South Korea,100,"Data Visualization, Java, Scala, Python, TensorFlow",PhD,0,Retail,2024-10-27,2024-12-20,2134,9.3,DataVision Ltd +AI13576,Data Scientist,249001,EUR,211651,EX,CT,Austria,L,Austria,0,"Tableau, Kubernetes, TensorFlow, Scala, AWS",Master,12,Telecommunications,2024-09-17,2024-11-26,1570,6.3,Predictive Systems +AI13577,Principal Data Scientist,132994,EUR,113045,EX,PT,Netherlands,S,Netherlands,100,"R, Computer Vision, NLP",Master,13,Healthcare,2025-04-22,2025-07-02,2196,8.9,TechCorp Inc +AI13578,AI Architect,108206,AUD,146078,MI,PT,Australia,M,Australia,50,"Tableau, Mathematics, Data Visualization, Python, Spark",Associate,2,Consulting,2024-06-30,2024-07-18,579,8.4,Quantum Computing Inc +AI13579,AI Consultant,55261,GBP,41446,EN,CT,United Kingdom,M,United Kingdom,100,"Python, Java, PyTorch",PhD,1,Telecommunications,2024-11-09,2024-12-14,831,5.7,Smart Analytics +AI13580,Head of AI,212757,EUR,180843,EX,FL,France,S,France,50,"Spark, Tableau, Scala, Linux",Master,10,Manufacturing,2024-05-19,2024-07-09,2126,7.6,Machine Intelligence Group +AI13581,Principal Data Scientist,115527,USD,115527,MI,PT,Denmark,S,United States,50,"SQL, Git, NLP, GCP, PyTorch",Associate,4,Education,2024-03-10,2024-05-20,785,5.8,Digital Transformation LLC +AI13582,Research Scientist,90576,USD,90576,EX,FT,China,S,Spain,50,"Linux, Hadoop, GCP",Associate,17,Telecommunications,2024-04-29,2024-07-01,652,5.8,Autonomous Tech +AI13583,NLP Engineer,68314,EUR,58067,EN,FL,Austria,S,Austria,50,"SQL, Linux, Computer Vision, Scala",Bachelor,0,Consulting,2024-02-02,2024-03-24,1389,9.8,Future Systems +AI13584,Data Analyst,80632,USD,80632,EN,FT,Norway,S,Norway,100,"Tableau, GCP, Linux",PhD,1,Media,2024-01-09,2024-02-12,845,9.2,Advanced Robotics +AI13585,Head of AI,85732,USD,85732,MI,PT,South Korea,L,South Korea,0,"Scala, MLOps, Tableau, SQL",Associate,4,Education,2024-03-17,2024-05-11,888,6.3,Digital Transformation LLC +AI13586,Machine Learning Engineer,89212,USD,89212,EN,CT,Denmark,M,Denmark,0,"TensorFlow, Data Visualization, Linux, PyTorch",Bachelor,1,Healthcare,2024-01-12,2024-02-27,2145,5.6,AI Innovations +AI13587,AI Product Manager,58528,USD,58528,SE,FL,India,L,India,50,"Hadoop, Git, PyTorch, Azure",PhD,5,Consulting,2024-10-31,2024-12-19,2079,9.9,Advanced Robotics +AI13588,Data Engineer,111013,EUR,94361,SE,PT,Netherlands,M,Mexico,100,"Scala, AWS, Java, Kubernetes, Deep Learning",Associate,5,Transportation,2025-03-11,2025-03-28,2267,9.5,Advanced Robotics +AI13589,ML Ops Engineer,161974,EUR,137678,SE,PT,France,L,Austria,0,"Statistics, R, Tableau",Bachelor,9,Finance,2024-02-26,2024-03-31,1545,6.2,Quantum Computing Inc +AI13590,AI Consultant,100290,USD,100290,MI,FT,Denmark,S,Denmark,0,"Kubernetes, Hadoop, PyTorch",Bachelor,2,Consulting,2024-04-13,2024-05-20,1342,5.8,Digital Transformation LLC +AI13591,Machine Learning Engineer,66642,USD,66642,EN,FL,Norway,M,Germany,50,"SQL, Hadoop, Tableau, Git, Scala",Associate,1,Finance,2025-02-23,2025-05-04,2080,5.4,Neural Networks Co +AI13592,Head of AI,162695,USD,162695,EX,PT,South Korea,M,Finland,0,"R, NLP, SQL",Associate,12,Government,2024-10-29,2024-12-06,2391,9.4,Smart Analytics +AI13593,AI Specialist,137077,EUR,116515,SE,FL,Austria,M,Austria,0,"Statistics, SQL, PyTorch, Deep Learning, Python",Associate,5,Transportation,2024-01-06,2024-03-17,1084,6.5,Advanced Robotics +AI13594,AI Software Engineer,132459,GBP,99344,SE,FL,United Kingdom,S,France,50,"Linux, Computer Vision, Deep Learning",Associate,8,Transportation,2024-08-25,2024-09-29,1483,5.4,AI Innovations +AI13595,Computer Vision Engineer,19457,USD,19457,EN,CT,India,S,India,0,"Scala, Kubernetes, Azure",PhD,0,Gaming,2025-04-09,2025-05-29,2272,8.1,TechCorp Inc +AI13596,Machine Learning Researcher,38912,USD,38912,MI,PT,India,L,India,50,"Mathematics, PyTorch, Python, Java, TensorFlow",PhD,2,Media,2024-10-30,2024-12-19,505,9.7,Advanced Robotics +AI13597,Data Scientist,111322,CAD,139153,MI,CT,Canada,L,Canada,100,"Docker, PyTorch, Computer Vision, AWS",Bachelor,4,Healthcare,2024-03-06,2024-05-02,1667,6.7,Machine Intelligence Group +AI13598,NLP Engineer,39729,USD,39729,MI,FL,China,S,China,100,"Python, Java, Docker",Bachelor,4,Education,2024-01-16,2024-02-08,820,7.6,Quantum Computing Inc +AI13599,Data Analyst,64601,USD,64601,EN,CT,Sweden,M,Sweden,100,"Java, MLOps, Kubernetes, Mathematics",Bachelor,1,Media,2024-09-14,2024-10-21,1542,5.8,Algorithmic Solutions +AI13600,Head of AI,199532,USD,199532,EX,PT,Ireland,S,Ireland,100,"Statistics, Hadoop, Spark",Associate,17,Finance,2024-10-17,2024-12-20,1422,9.4,Cloud AI Solutions +AI13601,ML Ops Engineer,204827,USD,204827,EX,PT,Norway,M,Malaysia,100,"MLOps, Mathematics, SQL",PhD,13,Education,2024-06-13,2024-08-11,1453,5.2,Algorithmic Solutions +AI13602,AI Software Engineer,131492,USD,131492,MI,CT,Norway,L,Norway,100,"Python, Linux, Docker, Git",PhD,3,Automotive,2025-01-26,2025-03-11,1257,5.2,Machine Intelligence Group +AI13603,Head of AI,200548,USD,200548,EX,CT,Ireland,M,Thailand,100,"SQL, NLP, PyTorch",PhD,17,Media,2024-05-22,2024-06-30,657,9,DeepTech Ventures +AI13604,Research Scientist,109537,SGD,142398,MI,PT,Singapore,L,Philippines,100,"PyTorch, Scala, NLP, Tableau",Master,3,Real Estate,2024-06-20,2024-07-08,1744,8.9,Autonomous Tech +AI13605,Deep Learning Engineer,169432,USD,169432,SE,PT,Ireland,L,Ireland,50,"Kubernetes, Python, Computer Vision",Master,6,Automotive,2024-09-12,2024-10-19,1222,6.2,Future Systems +AI13606,NLP Engineer,166233,USD,166233,EX,PT,United States,M,United States,0,"GCP, Azure, Computer Vision",Master,12,Government,2025-01-20,2025-02-05,1119,7.8,Machine Intelligence Group +AI13607,AI Consultant,67397,AUD,90986,MI,FT,Australia,S,Australia,50,"Scala, PyTorch, SQL",PhD,2,Technology,2025-03-16,2025-04-30,2214,8.1,DataVision Ltd +AI13608,AI Consultant,56703,USD,56703,SE,FT,China,S,China,0,"Git, R, Computer Vision",Bachelor,8,Manufacturing,2024-11-11,2024-12-21,2219,8.7,DeepTech Ventures +AI13609,Research Scientist,26374,USD,26374,EN,CT,China,S,China,0,"Kubernetes, Python, Scala, Deep Learning, Computer Vision",Associate,1,Government,2024-10-18,2024-11-24,575,9.3,Digital Transformation LLC +AI13610,AI Architect,45657,USD,45657,SE,CT,India,L,India,0,"Computer Vision, Deep Learning, R",Bachelor,9,Gaming,2024-01-16,2024-03-03,624,7.4,Digital Transformation LLC +AI13611,Computer Vision Engineer,39452,USD,39452,EN,CT,South Korea,S,Norway,50,"Git, NLP, Python",Associate,0,Education,2025-01-25,2025-02-28,1967,7.1,Machine Intelligence Group +AI13612,Data Analyst,123631,USD,123631,SE,PT,Sweden,S,Sweden,100,"TensorFlow, Mathematics, GCP",Bachelor,9,Healthcare,2024-02-25,2024-04-28,1819,7.7,DataVision Ltd +AI13613,ML Ops Engineer,102463,SGD,133202,MI,CT,Singapore,S,Singapore,100,"MLOps, Statistics, Scala, Data Visualization",Associate,2,Healthcare,2024-08-21,2024-09-15,799,7.2,Neural Networks Co +AI13614,Data Engineer,38458,USD,38458,MI,FT,China,M,China,100,"Azure, Computer Vision, Docker, PyTorch",Master,3,Manufacturing,2025-04-05,2025-05-30,2158,6,Autonomous Tech +AI13615,AI Software Engineer,50577,EUR,42990,EN,PT,Germany,S,Germany,50,"TensorFlow, R, Azure, AWS, NLP",Associate,0,Technology,2024-10-21,2024-12-28,1836,8.4,DeepTech Ventures +AI13616,Machine Learning Engineer,91272,AUD,123217,EN,FL,Australia,L,Malaysia,50,"Python, TensorFlow, Data Visualization",Master,0,Real Estate,2025-03-05,2025-04-03,1752,8.1,Quantum Computing Inc +AI13617,AI Software Engineer,92478,USD,92478,EN,CT,United States,L,United States,100,"Computer Vision, Statistics, MLOps",PhD,0,Automotive,2024-05-03,2024-06-24,1054,5.5,Cloud AI Solutions +AI13618,NLP Engineer,213025,USD,213025,EX,CT,Sweden,S,Sweden,100,"Python, Linux, GCP, Hadoop, PyTorch",Bachelor,10,Government,2025-02-15,2025-03-14,534,6.2,Algorithmic Solutions +AI13619,Autonomous Systems Engineer,240149,USD,240149,EX,FT,United States,L,United States,100,"SQL, GCP, Azure, NLP",PhD,15,Government,2024-10-28,2024-12-15,1242,5.9,Machine Intelligence Group +AI13620,Data Analyst,97727,EUR,83068,MI,PT,Austria,L,Austria,50,"Deep Learning, SQL, Data Visualization, PyTorch",Associate,3,Gaming,2025-04-25,2025-06-22,1949,9.7,Autonomous Tech +AI13621,Robotics Engineer,81590,CAD,101988,MI,CT,Canada,S,Netherlands,50,"Hadoop, Kubernetes, Mathematics",Associate,3,Government,2024-09-05,2024-11-03,1546,7.3,Cloud AI Solutions +AI13622,NLP Engineer,80741,AUD,109000,MI,FT,Australia,M,Colombia,100,"SQL, Python, MLOps",Bachelor,2,Technology,2024-08-29,2024-11-08,2250,7.9,DeepTech Ventures +AI13623,Head of AI,207242,USD,207242,EX,PT,Israel,S,Argentina,50,"Linux, Hadoop, Tableau",Associate,14,Manufacturing,2024-11-11,2024-12-18,2227,5.1,Cloud AI Solutions +AI13624,Principal Data Scientist,162118,USD,162118,EX,FL,Israel,S,Israel,100,"AWS, Docker, Mathematics",Associate,13,Telecommunications,2024-03-18,2024-05-07,1676,8.7,Autonomous Tech +AI13625,AI Software Engineer,95549,USD,95549,MI,FL,Israel,L,Israel,0,"Java, AWS, NLP, Tableau, Azure",Master,2,Gaming,2025-04-05,2025-06-14,1519,6.8,Advanced Robotics +AI13626,Autonomous Systems Engineer,22852,USD,22852,EN,PT,China,S,China,50,"Java, Spark, TensorFlow, Kubernetes",Master,0,Transportation,2024-11-11,2024-12-15,2127,7.1,Digital Transformation LLC +AI13627,Robotics Engineer,99707,USD,99707,EN,FT,United States,L,United States,0,"NLP, GCP, AWS, Git, Hadoop",Bachelor,1,Transportation,2024-03-02,2024-04-20,1827,5.9,Smart Analytics +AI13628,Autonomous Systems Engineer,82711,USD,82711,EN,FL,Finland,L,Finland,100,"Kubernetes, Python, Statistics, GCP, Java",Associate,1,Telecommunications,2024-03-23,2024-05-25,832,5.9,Autonomous Tech +AI13629,Data Analyst,114447,USD,114447,MI,PT,Norway,M,Norway,100,"Tableau, Linux, AWS",Associate,3,Transportation,2024-01-24,2024-02-27,2294,6.1,Predictive Systems +AI13630,Principal Data Scientist,80841,CAD,101051,MI,FL,Canada,S,Canada,50,"Hadoop, Git, MLOps, Statistics",Bachelor,3,Gaming,2025-01-10,2025-02-08,1943,7.7,DataVision Ltd +AI13631,Data Scientist,75011,USD,75011,EN,PT,Israel,L,Israel,100,"Tableau, Statistics, Computer Vision",Master,0,Transportation,2025-02-10,2025-03-21,1721,8.4,Neural Networks Co +AI13632,AI Specialist,48013,USD,48013,EX,PT,India,S,India,0,"TensorFlow, Scala, PyTorch, Statistics, Data Visualization",Bachelor,10,Healthcare,2024-03-05,2024-05-06,965,6.6,Cloud AI Solutions +AI13633,Head of AI,210553,EUR,178970,EX,CT,Germany,L,Germany,50,"Kubernetes, Scala, Data Visualization, Hadoop",Master,19,Consulting,2025-04-13,2025-05-07,956,7,Cloud AI Solutions +AI13634,Principal Data Scientist,68238,EUR,58002,EN,FT,Germany,S,Austria,100,"Kubernetes, Hadoop, PyTorch, AWS",Associate,0,Finance,2024-11-05,2025-01-16,1327,7.8,TechCorp Inc +AI13635,Autonomous Systems Engineer,211620,CHF,190458,SE,CT,Switzerland,M,Switzerland,50,"Java, Scala, SQL, Git",Bachelor,6,Telecommunications,2025-02-22,2025-04-19,709,8.4,Cloud AI Solutions +AI13636,AI Research Scientist,200684,USD,200684,EX,PT,Sweden,M,Sweden,50,"SQL, AWS, Hadoop",Associate,19,Telecommunications,2025-04-06,2025-06-08,1175,7.6,AI Innovations +AI13637,AI Software Engineer,91715,USD,91715,SE,PT,South Korea,S,Netherlands,100,"Tableau, Deep Learning, R, Python, TensorFlow",PhD,7,Education,2025-01-23,2025-02-06,1869,8.6,Neural Networks Co +AI13638,Principal Data Scientist,93185,JPY,10250350,EN,FL,Japan,L,Japan,50,"Python, AWS, Azure",Master,0,Technology,2025-04-13,2025-05-20,1885,9,AI Innovations +AI13639,Machine Learning Researcher,87268,USD,87268,EN,FT,Denmark,M,Denmark,100,"Azure, Java, SQL",Associate,1,Education,2025-01-31,2025-02-22,2387,6.9,Algorithmic Solutions +AI13640,Data Scientist,267540,CHF,240786,EX,PT,Switzerland,S,Switzerland,50,"MLOps, Tableau, Scala",Master,11,Telecommunications,2024-11-06,2024-11-29,2360,7.7,Autonomous Tech +AI13641,Data Engineer,126759,USD,126759,SE,FL,Sweden,M,Sweden,50,"Python, Docker, Data Visualization, PyTorch",Bachelor,7,Media,2024-02-08,2024-03-09,1723,6,Cognitive Computing +AI13642,Data Scientist,129742,USD,129742,SE,FT,Ireland,L,Ireland,50,"Linux, Mathematics, MLOps",Bachelor,9,Healthcare,2024-07-20,2024-08-23,1374,7.2,Digital Transformation LLC +AI13643,NLP Engineer,78149,GBP,58612,EN,FL,United Kingdom,M,United Kingdom,0,"R, AWS, TensorFlow, Mathematics",Master,0,Gaming,2024-04-24,2024-05-13,897,7.2,Cloud AI Solutions +AI13644,AI Consultant,84880,USD,84880,MI,FL,Norway,S,Norway,50,"SQL, GCP, NLP",Master,3,Finance,2024-03-22,2024-04-08,1412,8.2,Neural Networks Co +AI13645,Data Scientist,106468,USD,106468,EX,CT,China,L,China,50,"Linux, Docker, Tableau, Scala, GCP",Master,17,Finance,2024-03-09,2024-04-05,1740,9.2,DataVision Ltd +AI13646,AI Specialist,77051,USD,77051,EN,PT,Denmark,L,Mexico,50,"Hadoop, Docker, Kubernetes",PhD,1,Telecommunications,2024-12-28,2025-02-07,2495,6.8,TechCorp Inc +AI13647,AI Consultant,54386,AUD,73421,EN,FT,Australia,M,Australia,0,"PyTorch, TensorFlow, Git",Bachelor,1,Technology,2024-12-10,2025-01-19,561,9.2,Neural Networks Co +AI13648,Research Scientist,241352,SGD,313758,EX,CT,Singapore,L,Singapore,50,"Mathematics, Azure, Hadoop",Associate,12,Healthcare,2024-10-10,2024-11-02,1924,8.7,Algorithmic Solutions +AI13649,Computer Vision Engineer,122023,USD,122023,MI,CT,Denmark,S,Denmark,100,"Kubernetes, NLP, R, PyTorch, Docker",PhD,3,Finance,2024-10-11,2024-11-08,955,5.7,Neural Networks Co +AI13650,Computer Vision Engineer,69776,SGD,90709,MI,FT,Singapore,S,Ireland,0,"Java, Tableau, Hadoop, Scala, AWS",Master,4,Energy,2024-01-09,2024-03-11,602,8.3,DeepTech Ventures +AI13651,ML Ops Engineer,150163,USD,150163,SE,FL,Ireland,L,Ireland,100,"Kubernetes, Deep Learning, Azure",PhD,5,Transportation,2024-10-16,2024-12-22,868,7.7,Autonomous Tech +AI13652,Data Analyst,46451,CAD,58064,EN,CT,Canada,S,Canada,50,"NLP, Kubernetes, R, Java",Master,0,Manufacturing,2024-10-29,2024-11-15,718,8.2,Cognitive Computing +AI13653,Data Scientist,78071,AUD,105396,MI,PT,Australia,S,Australia,50,"Spark, Tableau, Java, Python",Associate,4,Consulting,2025-02-15,2025-04-21,648,9.9,Advanced Robotics +AI13654,Machine Learning Engineer,141974,USD,141974,SE,FL,South Korea,L,South Korea,100,"Spark, Tableau, PyTorch, Deep Learning, GCP",Associate,8,Finance,2024-03-15,2024-04-14,2050,8.6,Digital Transformation LLC +AI13655,Robotics Engineer,101301,JPY,11143110,MI,FT,Japan,L,Japan,50,"Tableau, SQL, GCP, Java",Bachelor,2,Automotive,2024-02-08,2024-02-27,1956,9.6,Cloud AI Solutions +AI13656,AI Architect,147615,USD,147615,SE,FL,Israel,L,Israel,100,"Docker, SQL, Kubernetes",Master,7,Healthcare,2024-12-01,2025-01-24,2115,5.3,Algorithmic Solutions +AI13657,Robotics Engineer,59247,USD,59247,EX,FT,India,M,Italy,100,"TensorFlow, PyTorch, Deep Learning",Associate,12,Gaming,2024-01-27,2024-03-09,1303,8.7,Digital Transformation LLC +AI13658,Computer Vision Engineer,68387,AUD,92322,EN,CT,Australia,S,Australia,0,"Scala, Git, SQL, Python, R",Associate,1,Real Estate,2025-03-29,2025-05-15,2393,9.4,Cognitive Computing +AI13659,Machine Learning Engineer,94339,SGD,122641,EN,FL,Singapore,L,Malaysia,50,"Git, SQL, GCP, Mathematics",Bachelor,1,Education,2024-02-27,2024-04-21,1382,6.9,Machine Intelligence Group +AI13660,Machine Learning Engineer,246518,SGD,320473,EX,FL,Singapore,L,Mexico,0,"Python, Kubernetes, Azure",Master,18,Consulting,2024-03-31,2024-05-07,594,8.7,TechCorp Inc +AI13661,Data Analyst,102322,USD,102322,MI,FT,Finland,M,Finland,100,"R, PyTorch, TensorFlow, Git",Master,2,Transportation,2024-03-19,2024-04-17,1537,9,Algorithmic Solutions +AI13662,Autonomous Systems Engineer,209756,USD,209756,EX,FT,United States,M,United States,100,"Tableau, Java, Kubernetes",PhD,10,Healthcare,2025-03-31,2025-05-19,1441,6.2,Advanced Robotics +AI13663,Data Scientist,130034,SGD,169044,SE,FT,Singapore,M,South Korea,100,"SQL, Linux, Git, Deep Learning, Statistics",Master,6,Gaming,2024-12-19,2025-02-15,1705,6.3,Predictive Systems +AI13664,AI Specialist,112402,EUR,95542,SE,PT,Germany,M,Germany,0,"Git, Python, Scala",Associate,7,Gaming,2024-12-30,2025-02-04,1356,5.6,AI Innovations +AI13665,Data Analyst,111935,USD,111935,SE,FL,Sweden,M,Sweden,50,"Deep Learning, Linux, Data Visualization, Statistics, Tableau",Bachelor,7,Real Estate,2024-10-26,2024-12-26,1616,7.5,AI Innovations +AI13666,ML Ops Engineer,210290,USD,210290,EX,PT,Finland,S,Finland,0,"Hadoop, Scala, Spark, Computer Vision",Bachelor,17,Real Estate,2024-04-15,2024-05-27,1321,6.2,Future Systems +AI13667,Data Engineer,156011,USD,156011,SE,PT,Norway,S,Norway,0,"Spark, Linux, Computer Vision, Python, Azure",Associate,9,Manufacturing,2024-09-28,2024-11-18,1382,8.2,AI Innovations +AI13668,Machine Learning Researcher,72835,USD,72835,EN,PT,United States,S,Italy,50,"Java, Scala, Deep Learning, Docker",Master,1,Healthcare,2024-01-03,2024-03-10,1536,9,Advanced Robotics +AI13669,Data Analyst,182390,USD,182390,SE,FL,Norway,M,Japan,50,"Tableau, Data Visualization, Azure, Docker",Associate,7,Real Estate,2024-04-23,2024-06-03,1277,5.7,Predictive Systems +AI13670,Machine Learning Researcher,69023,CAD,86279,EN,FL,Canada,M,Canada,50,"Scala, Python, Azure",Bachelor,1,Energy,2024-10-10,2024-11-03,2005,9.1,Cloud AI Solutions +AI13671,NLP Engineer,92468,GBP,69351,MI,FL,United Kingdom,M,United Kingdom,50,"Spark, Java, Data Visualization, GCP",PhD,3,Automotive,2024-06-13,2024-06-28,1890,8.1,Smart Analytics +AI13672,Research Scientist,65251,USD,65251,EN,CT,Israel,L,Israel,50,"PyTorch, Deep Learning, Spark",Master,0,Real Estate,2025-01-07,2025-02-15,651,5.6,Cognitive Computing +AI13673,AI Specialist,217187,USD,217187,EX,FL,Ireland,M,Ireland,100,"R, PyTorch, Data Visualization",Associate,15,Education,2024-03-17,2024-04-08,1446,8.3,Smart Analytics +AI13674,Autonomous Systems Engineer,54380,EUR,46223,EN,PT,Germany,S,Germany,0,"Linux, Python, Git, Statistics",Master,0,Finance,2025-01-01,2025-02-03,1960,9.6,DataVision Ltd +AI13675,AI Consultant,295717,EUR,251359,EX,CT,Netherlands,L,Netherlands,100,"Java, Data Visualization, Spark",Master,11,Finance,2024-12-19,2025-01-16,1535,9,Algorithmic Solutions +AI13676,NLP Engineer,122502,AUD,165378,SE,FT,Australia,M,Hungary,100,"NLP, TensorFlow, Hadoop",Associate,6,Consulting,2025-04-24,2025-05-09,2498,6.8,Algorithmic Solutions +AI13677,Deep Learning Engineer,109823,USD,109823,MI,CT,Sweden,L,Sweden,100,"Hadoop, AWS, Java, Statistics, Azure",Bachelor,3,Energy,2024-05-16,2024-07-01,976,8.4,Smart Analytics +AI13678,Autonomous Systems Engineer,82666,USD,82666,EN,FT,Finland,L,Finland,100,"Spark, Python, Azure, Java",PhD,0,Automotive,2025-04-08,2025-05-07,1809,7.3,Machine Intelligence Group +AI13679,Robotics Engineer,69269,GBP,51952,EN,FT,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python, Data Visualization",Master,1,Retail,2024-10-19,2024-12-20,1443,7.5,Smart Analytics +AI13680,AI Specialist,193819,USD,193819,EX,PT,Sweden,S,Sweden,50,"Linux, TensorFlow, Git, Kubernetes",PhD,11,Finance,2025-04-28,2025-05-28,630,7.4,Machine Intelligence Group +AI13681,Head of AI,104297,SGD,135586,MI,PT,Singapore,M,Singapore,100,"Java, R, AWS, Computer Vision, Statistics",PhD,4,Manufacturing,2025-02-23,2025-03-28,1501,8.7,Algorithmic Solutions +AI13682,NLP Engineer,64787,EUR,55069,EN,FL,France,S,France,0,"Hadoop, MLOps, Docker, Linux, TensorFlow",PhD,1,Energy,2025-02-08,2025-04-20,2254,7.7,DeepTech Ventures +AI13683,AI Architect,321641,USD,321641,EX,FT,Norway,M,Norway,100,"Git, TensorFlow, Scala",Bachelor,11,Education,2025-04-14,2025-06-22,1672,7.7,AI Innovations +AI13684,Computer Vision Engineer,55628,SGD,72316,EN,CT,Singapore,M,Turkey,100,"Azure, Java, R, Computer Vision, Hadoop",PhD,1,Healthcare,2025-04-18,2025-06-28,1517,5.8,Future Systems +AI13685,AI Architect,45870,USD,45870,MI,FT,China,S,Colombia,100,"AWS, Java, R, MLOps, SQL",Associate,3,Finance,2024-09-25,2024-11-27,530,5.4,Quantum Computing Inc +AI13686,AI Architect,152656,USD,152656,MI,FT,Denmark,L,Denmark,100,"MLOps, Kubernetes, PyTorch",Bachelor,3,Education,2024-03-03,2024-05-07,1022,7.1,Future Systems +AI13687,AI Software Engineer,26656,USD,26656,MI,FT,India,M,India,100,"Java, R, Data Visualization, Scala",Master,2,Retail,2025-01-27,2025-03-22,717,9.5,Advanced Robotics +AI13688,Data Analyst,146759,USD,146759,SE,PT,United States,L,United Kingdom,50,"R, Spark, Kubernetes, Python, AWS",Associate,7,Government,2024-08-10,2024-09-20,1615,8.4,TechCorp Inc +AI13689,AI Specialist,44241,CAD,55301,EN,FL,Canada,S,Canada,0,"Python, TensorFlow, PyTorch",Master,0,Finance,2025-01-01,2025-02-28,1287,6.1,TechCorp Inc +AI13690,Principal Data Scientist,124494,CHF,112045,EN,CT,Switzerland,L,Switzerland,50,"Linux, Hadoop, SQL, PyTorch, GCP",Bachelor,1,Media,2024-02-14,2024-03-12,1057,7.4,Cognitive Computing +AI13691,AI Specialist,83827,USD,83827,EX,PT,India,M,India,100,"Azure, Linux, Java, SQL",Bachelor,18,Automotive,2024-11-17,2024-12-01,1223,6.5,Advanced Robotics +AI13692,Machine Learning Researcher,133335,EUR,113335,SE,FL,Germany,M,Germany,100,"MLOps, Kubernetes, PyTorch, Statistics, SQL",PhD,8,Real Estate,2024-08-10,2024-09-29,1968,8.7,Future Systems +AI13693,Autonomous Systems Engineer,161531,EUR,137301,SE,FL,France,L,France,0,"Hadoop, Python, SQL, NLP",PhD,7,Retail,2024-12-06,2025-01-24,2300,5.5,Future Systems +AI13694,Deep Learning Engineer,80194,USD,80194,EN,FT,Ireland,M,Ireland,0,"SQL, R, Data Visualization",Master,0,Consulting,2024-12-28,2025-02-11,924,5.9,DataVision Ltd +AI13695,Data Scientist,181350,GBP,136013,EX,PT,United Kingdom,M,United Kingdom,0,"Tableau, Scala, NLP, TensorFlow",Bachelor,18,Consulting,2024-11-25,2025-01-11,2264,6.7,Predictive Systems +AI13696,AI Software Engineer,102985,USD,102985,MI,FT,Finland,M,Finland,50,"SQL, NLP, Git",PhD,3,Transportation,2025-02-20,2025-03-30,1591,8.7,Quantum Computing Inc +AI13697,AI Consultant,70147,USD,70147,EN,FT,Norway,M,Norway,0,"SQL, Scala, Git",Master,0,Education,2024-03-25,2024-04-30,598,9.5,Algorithmic Solutions +AI13698,Machine Learning Researcher,95188,SGD,123744,MI,PT,Singapore,L,Singapore,0,"Azure, PyTorch, Statistics, Hadoop, Java",Associate,3,Media,2024-12-04,2024-12-22,1227,9.4,Quantum Computing Inc +AI13699,Robotics Engineer,274623,USD,274623,EX,FL,United States,L,United States,50,"Python, PyTorch, Git, Azure, Java",Associate,14,Government,2024-02-08,2024-03-11,2135,6.4,Quantum Computing Inc +AI13700,Robotics Engineer,79001,EUR,67151,EN,CT,Germany,L,Germany,50,"Python, TensorFlow, NLP, Java",Master,1,Real Estate,2024-06-01,2024-07-07,1648,7.8,Digital Transformation LLC +AI13701,Autonomous Systems Engineer,133645,AUD,180421,SE,FL,Australia,M,Estonia,50,"Tableau, AWS, NLP, Docker",Bachelor,8,Education,2025-03-18,2025-05-26,706,9.9,AI Innovations +AI13702,Machine Learning Researcher,63052,USD,63052,SE,CT,China,S,China,0,"Computer Vision, Tableau, Data Visualization, NLP",Associate,5,Manufacturing,2024-08-12,2024-08-29,1774,6.5,Quantum Computing Inc +AI13703,AI Research Scientist,150556,AUD,203251,SE,PT,Australia,M,Australia,100,"SQL, Hadoop, Computer Vision, R",Associate,6,Technology,2024-11-02,2024-12-24,1164,8.4,Advanced Robotics +AI13704,AI Specialist,44619,USD,44619,SE,FL,China,S,China,50,"Java, TensorFlow, Git, AWS",PhD,6,Automotive,2025-04-15,2025-05-09,1572,7.6,AI Innovations +AI13705,Autonomous Systems Engineer,243017,USD,243017,EX,CT,Israel,L,Israel,0,"Scala, Data Visualization, Kubernetes, Computer Vision, Spark",Associate,12,Gaming,2024-03-09,2024-03-28,2181,8.1,Predictive Systems +AI13706,AI Specialist,201305,EUR,171109,EX,FT,Germany,L,Germany,0,"GCP, Git, PyTorch, SQL, Mathematics",Master,15,Automotive,2024-04-26,2024-06-08,1686,9.2,Quantum Computing Inc +AI13707,AI Research Scientist,94123,SGD,122360,EN,FL,Singapore,L,Singapore,50,"Java, SQL, Azure, MLOps, PyTorch",Master,0,Media,2024-01-05,2024-03-12,1613,5.4,Digital Transformation LLC +AI13708,Data Engineer,52016,GBP,39012,EN,FT,United Kingdom,S,Switzerland,100,"Azure, Kubernetes, Docker, AWS, Scala",PhD,0,Manufacturing,2024-10-14,2024-11-09,2014,6.2,Predictive Systems +AI13709,Computer Vision Engineer,48238,EUR,41002,EN,PT,France,S,Ireland,100,"Java, PyTorch, GCP",Master,0,Manufacturing,2024-03-23,2024-05-24,710,5.1,DataVision Ltd +AI13710,Data Analyst,189852,USD,189852,EX,CT,Ireland,M,Ireland,100,"Azure, Spark, SQL, Python",Master,12,Automotive,2024-07-21,2024-09-03,2343,8.2,AI Innovations +AI13711,Autonomous Systems Engineer,71233,CAD,89041,MI,FT,Canada,M,Vietnam,0,"Kubernetes, Computer Vision, Data Visualization, Azure, R",PhD,4,Transportation,2024-03-05,2024-05-04,979,8,Digital Transformation LLC +AI13712,Research Scientist,152809,EUR,129888,SE,PT,Germany,M,Germany,50,"Git, Java, R, NLP, Kubernetes",Associate,8,Real Estate,2025-01-17,2025-02-07,855,9.3,DataVision Ltd +AI13713,Principal Data Scientist,79844,USD,79844,MI,FL,Sweden,M,Sweden,50,"GCP, TensorFlow, Data Visualization, PyTorch, MLOps",Master,4,Retail,2024-11-04,2024-12-22,2002,5.7,DeepTech Ventures +AI13714,AI Specialist,90766,USD,90766,EN,CT,Sweden,L,Sweden,0,"Hadoop, Git, Spark, TensorFlow, GCP",PhD,1,Retail,2024-02-19,2024-04-22,2059,7.7,Neural Networks Co +AI13715,AI Specialist,94607,EUR,80416,MI,CT,France,M,France,50,"Linux, Spark, Azure",Associate,3,Education,2024-10-22,2024-12-14,1778,8.7,Smart Analytics +AI13716,Machine Learning Engineer,155537,JPY,17109070,SE,FT,Japan,L,Ireland,50,"Spark, Kubernetes, SQL, NLP",PhD,7,Gaming,2024-01-26,2024-02-14,1465,9.6,Algorithmic Solutions +AI13717,Principal Data Scientist,84059,GBP,63044,MI,FL,United Kingdom,M,Indonesia,0,"Spark, Python, TensorFlow, Hadoop",Bachelor,3,Media,2024-10-18,2024-12-03,1930,6.4,Smart Analytics +AI13718,Head of AI,214035,USD,214035,EX,FL,Israel,S,Israel,50,"Linux, MLOps, Hadoop, GCP, Python",PhD,12,Retail,2024-02-02,2024-02-22,1111,10,AI Innovations +AI13719,Machine Learning Engineer,62794,USD,62794,SE,FT,China,M,China,100,"Hadoop, Git, Docker, NLP",Associate,9,Telecommunications,2024-09-09,2024-09-24,858,10,Autonomous Tech +AI13720,Principal Data Scientist,78666,USD,78666,MI,FT,Sweden,S,Sweden,0,"Git, SQL, Python, R",Master,4,Automotive,2025-04-16,2025-05-18,1482,8.3,TechCorp Inc +AI13721,Head of AI,73536,JPY,8088960,EN,FT,Japan,M,Turkey,100,"Scala, Kubernetes, Java, PyTorch",PhD,0,Media,2024-08-15,2024-09-25,1805,8.9,Cloud AI Solutions +AI13722,Research Scientist,35544,USD,35544,MI,PT,China,M,Luxembourg,50,"Deep Learning, PyTorch, Java",Master,4,Education,2024-08-11,2024-10-22,1603,5.9,DeepTech Ventures +AI13723,AI Research Scientist,49579,USD,49579,EN,PT,South Korea,L,South Korea,50,"AWS, PyTorch, Scala, Linux",Associate,1,Automotive,2024-06-14,2024-08-20,2298,8.8,Digital Transformation LLC +AI13724,Data Engineer,37102,USD,37102,SE,PT,India,M,India,100,"Spark, Java, Git, Data Visualization, R",PhD,7,Finance,2024-07-23,2024-10-01,1467,5.6,Machine Intelligence Group +AI13725,Data Engineer,151791,CHF,136612,SE,FL,Switzerland,S,Switzerland,0,"Kubernetes, Mathematics, PyTorch, Spark",PhD,7,Media,2025-02-09,2025-04-23,1366,6.5,Cognitive Computing +AI13726,Head of AI,114945,USD,114945,SE,FT,Sweden,M,Sweden,100,"Computer Vision, Mathematics, NLP, PyTorch",Associate,7,Automotive,2025-02-01,2025-03-28,2374,9.5,AI Innovations +AI13727,Machine Learning Engineer,74998,CAD,93748,EN,FT,Canada,M,Canada,100,"Scala, Java, Docker",Associate,0,Transportation,2024-03-22,2024-05-02,1851,8.3,Digital Transformation LLC +AI13728,AI Software Engineer,119208,USD,119208,SE,FT,Israel,S,Israel,0,"Python, TensorFlow, Git",PhD,5,Gaming,2024-09-10,2024-11-12,762,6.6,Digital Transformation LLC +AI13729,Data Engineer,215124,USD,215124,EX,FL,Finland,M,Canada,100,"Data Visualization, Scala, AWS",Master,16,Manufacturing,2024-02-06,2024-02-26,626,8,Quantum Computing Inc +AI13730,Data Engineer,111381,JPY,12251910,SE,PT,Japan,M,Japan,50,"Scala, GCP, TensorFlow",PhD,6,Government,2024-01-05,2024-02-28,545,8.7,Future Systems +AI13731,AI Specialist,62659,EUR,53260,EN,FL,Germany,M,Germany,100,"Linux, Hadoop, Data Visualization, Python",PhD,0,Healthcare,2024-08-05,2024-09-19,1980,9.3,DeepTech Ventures +AI13732,Data Scientist,174509,EUR,148333,EX,PT,Austria,M,Austria,0,"Deep Learning, Hadoop, SQL",Associate,10,Manufacturing,2025-03-12,2025-04-12,1714,6.1,Cloud AI Solutions +AI13733,Principal Data Scientist,76295,USD,76295,SE,PT,China,L,China,0,"Python, SQL, AWS, Computer Vision",PhD,6,Real Estate,2024-09-30,2024-10-15,1025,6.9,TechCorp Inc +AI13734,Computer Vision Engineer,82190,CHF,73971,EN,CT,Switzerland,M,Malaysia,50,"Scala, Tableau, Python, Linux",Bachelor,1,Transportation,2024-06-27,2024-08-18,2364,5.3,Future Systems +AI13735,Data Scientist,60176,USD,60176,SE,FT,China,S,China,50,"R, Git, SQL",Bachelor,6,Finance,2024-07-30,2024-08-19,1300,9.1,Smart Analytics +AI13736,Computer Vision Engineer,91041,USD,91041,SE,FL,South Korea,S,Ukraine,100,"Computer Vision, Kubernetes, Git, Scala, Azure",Bachelor,8,Consulting,2024-10-06,2024-11-24,913,6.3,Quantum Computing Inc +AI13737,Robotics Engineer,51392,USD,51392,MI,FT,China,L,China,100,"Deep Learning, Hadoop, GCP",Master,2,Government,2024-01-03,2024-03-04,1175,8.8,Algorithmic Solutions +AI13738,Autonomous Systems Engineer,291795,USD,291795,EX,PT,Denmark,M,Denmark,50,"Scala, Statistics, AWS",Associate,13,Education,2025-03-18,2025-04-02,1768,7.8,Smart Analytics +AI13739,Head of AI,95963,USD,95963,EX,FL,India,L,India,0,"Kubernetes, Tableau, Hadoop",Bachelor,16,Energy,2024-10-21,2025-01-02,652,6.2,DeepTech Ventures +AI13740,AI Product Manager,48317,USD,48317,EN,FT,Ireland,S,Indonesia,50,"Python, TensorFlow, Mathematics",PhD,1,Media,2025-02-22,2025-04-20,1696,9.4,Quantum Computing Inc +AI13741,Machine Learning Researcher,66508,USD,66508,EN,FL,United States,S,Australia,100,"Docker, Python, PyTorch, Linux",PhD,1,Manufacturing,2025-02-04,2025-03-17,1858,6.4,Future Systems +AI13742,AI Architect,160872,EUR,136741,SE,FT,Germany,L,Israel,0,"AWS, Scala, SQL",Bachelor,5,Manufacturing,2024-02-02,2024-04-14,769,9.8,Cognitive Computing +AI13743,Autonomous Systems Engineer,170265,EUR,144725,EX,CT,Netherlands,S,Netherlands,0,"PyTorch, R, Deep Learning, Mathematics, NLP",PhD,14,Healthcare,2024-05-10,2024-07-21,2311,8.8,Algorithmic Solutions +AI13744,Computer Vision Engineer,67378,AUD,90960,EN,FT,Australia,M,Portugal,100,"Mathematics, PyTorch, Deep Learning, Data Visualization",Associate,0,Healthcare,2024-05-19,2024-07-26,2047,6.8,Digital Transformation LLC +AI13745,AI Consultant,201053,EUR,170895,EX,FL,Germany,L,Germany,0,"TensorFlow, Scala, SQL",Master,14,Gaming,2024-02-13,2024-04-08,793,5.1,Quantum Computing Inc +AI13746,Autonomous Systems Engineer,61127,EUR,51958,EN,FT,Germany,M,Germany,100,"Python, Azure, Tableau, MLOps, Computer Vision",Bachelor,0,Media,2025-04-04,2025-05-20,736,8.2,Predictive Systems +AI13747,Head of AI,132422,USD,132422,SE,CT,Ireland,M,Ireland,50,"Data Visualization, Python, Azure, Linux, R",Associate,7,Manufacturing,2024-12-16,2025-01-23,1166,9.4,Autonomous Tech +AI13748,Computer Vision Engineer,99521,EUR,84593,MI,CT,Netherlands,L,Netherlands,0,"Spark, SQL, Tableau, NLP, GCP",Master,3,Retail,2024-03-01,2024-04-05,1557,5.4,Advanced Robotics +AI13749,Data Engineer,187640,EUR,159494,EX,FT,France,M,United States,0,"MLOps, AWS, R",Associate,12,Manufacturing,2025-02-14,2025-03-09,1734,8.2,Cognitive Computing +AI13750,ML Ops Engineer,79512,CHF,71561,EN,FT,Switzerland,M,Switzerland,50,"SQL, GCP, Mathematics",Bachelor,1,Gaming,2024-11-03,2025-01-04,1933,6.2,Machine Intelligence Group +AI13751,ML Ops Engineer,76070,USD,76070,EN,FT,United States,M,United States,50,"SQL, Statistics, PyTorch, Spark, Kubernetes",Master,0,Energy,2025-04-30,2025-07-09,502,9.2,TechCorp Inc +AI13752,Research Scientist,214448,CHF,193003,SE,PT,Switzerland,M,Germany,0,"MLOps, PyTorch, TensorFlow, Docker",Master,6,Retail,2024-04-27,2024-06-01,1168,8.2,Smart Analytics +AI13753,ML Ops Engineer,197364,SGD,256573,EX,PT,Singapore,S,Singapore,100,"Linux, Docker, GCP, Hadoop, R",Master,13,Retail,2024-05-20,2024-07-04,689,9.1,Autonomous Tech +AI13754,Deep Learning Engineer,106426,EUR,90462,SE,CT,Netherlands,S,Kenya,100,"AWS, Kubernetes, Computer Vision, Python, Data Visualization",Associate,6,Energy,2024-08-26,2024-09-29,978,5.9,Cognitive Computing +AI13755,Computer Vision Engineer,64010,EUR,54409,MI,PT,France,S,France,100,"Data Visualization, PyTorch, Python, Azure, Docker",Master,3,Energy,2024-07-03,2024-09-10,1583,7.7,Predictive Systems +AI13756,AI Software Engineer,208320,USD,208320,EX,PT,Israel,L,Vietnam,50,"Kubernetes, Linux, TensorFlow",Bachelor,19,Energy,2024-10-06,2024-11-06,1807,6,Future Systems +AI13757,AI Product Manager,93335,USD,93335,MI,PT,Ireland,S,Ireland,0,"PyTorch, Kubernetes, Java, Deep Learning, Spark",Bachelor,4,Gaming,2025-04-08,2025-05-03,1110,5.6,Digital Transformation LLC +AI13758,AI Consultant,102368,USD,102368,SE,FT,Israel,S,Israel,0,"TensorFlow, Python, Data Visualization, Git, Hadoop",PhD,7,Gaming,2024-02-18,2024-04-18,1249,7.6,AI Innovations +AI13759,AI Product Manager,64929,EUR,55190,EN,PT,Netherlands,S,Netherlands,50,"Git, Java, Hadoop, SQL, Spark",Associate,0,Consulting,2025-01-18,2025-03-09,1113,5.9,AI Innovations +AI13760,AI Software Engineer,206784,USD,206784,EX,FL,Sweden,M,Sweden,100,"AWS, Linux, Scala, Statistics",Bachelor,17,Transportation,2024-04-06,2024-06-03,2115,6.2,DataVision Ltd +AI13761,Research Scientist,203979,USD,203979,EX,FT,South Korea,L,Latvia,100,"Git, Spark, MLOps, Docker",PhD,14,Real Estate,2024-03-30,2024-05-25,1655,7,Digital Transformation LLC +AI13762,Research Scientist,124710,CHF,112239,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, PyTorch, SQL, Deep Learning",PhD,2,Technology,2024-01-03,2024-02-05,1509,5.3,Cloud AI Solutions +AI13763,AI Software Engineer,60824,USD,60824,EN,FT,South Korea,L,Mexico,0,"PyTorch, Tableau, Deep Learning",Master,1,Automotive,2025-04-06,2025-06-12,1468,7,AI Innovations +AI13764,Robotics Engineer,133068,EUR,113108,EX,FT,France,S,France,0,"Hadoop, NLP, Mathematics, GCP",Associate,13,Finance,2024-08-25,2024-09-28,1755,7,Quantum Computing Inc +AI13765,Data Scientist,122346,USD,122346,SE,PT,Denmark,S,Chile,0,"Java, Kubernetes, GCP, SQL",Master,6,Gaming,2025-04-23,2025-06-25,1865,9.7,Future Systems +AI13766,Principal Data Scientist,180133,EUR,153113,EX,FT,Netherlands,L,Netherlands,100,"Python, Git, Kubernetes",Bachelor,14,Technology,2024-01-11,2024-03-01,1372,5.9,AI Innovations +AI13767,AI Product Manager,79220,USD,79220,MI,FT,Israel,L,Spain,0,"Mathematics, Kubernetes, Scala, Spark, TensorFlow",Associate,3,Transportation,2024-02-20,2024-03-12,2424,7.9,Algorithmic Solutions +AI13768,AI Research Scientist,129587,USD,129587,SE,FT,Israel,L,Israel,0,"AWS, Java, TensorFlow",Master,5,Consulting,2024-11-02,2025-01-11,2071,6.8,Cognitive Computing +AI13769,NLP Engineer,58088,USD,58088,EN,FT,South Korea,S,South Korea,0,"Hadoop, Computer Vision, Azure",Master,1,Transportation,2024-06-26,2024-07-22,1400,8.5,Machine Intelligence Group +AI13770,Computer Vision Engineer,202346,USD,202346,EX,CT,Norway,M,Spain,0,"Linux, NLP, Mathematics, Tableau, Spark",Bachelor,12,Technology,2024-03-18,2024-04-29,2120,8.8,Autonomous Tech +AI13771,Data Scientist,242484,USD,242484,EX,PT,Israel,L,Israel,100,"Computer Vision, PyTorch, Deep Learning, TensorFlow, MLOps",PhD,19,Government,2024-06-12,2024-07-02,938,9.3,AI Innovations +AI13772,AI Consultant,89975,GBP,67481,EN,FL,United Kingdom,L,United Kingdom,0,"SQL, Kubernetes, TensorFlow",Bachelor,1,Gaming,2024-11-05,2025-01-16,2206,8.6,TechCorp Inc +AI13773,NLP Engineer,89837,GBP,67378,MI,FL,United Kingdom,M,Finland,100,"NLP, Java, Data Visualization, Python, Deep Learning",Master,3,Energy,2024-10-08,2024-11-25,1152,8.9,Quantum Computing Inc +AI13774,NLP Engineer,218325,EUR,185576,EX,FT,Germany,M,Germany,100,"NLP, Scala, Git",Master,15,Manufacturing,2024-04-01,2024-06-11,2033,5.6,TechCorp Inc +AI13775,Robotics Engineer,75754,EUR,64391,EN,PT,Germany,M,Germany,100,"Git, Docker, Azure, GCP, Java",Bachelor,1,Government,2024-05-24,2024-08-03,1675,8.8,Future Systems +AI13776,Machine Learning Engineer,117509,EUR,99883,MI,FL,Austria,L,Australia,100,"Java, R, MLOps, Linux",Associate,4,Education,2024-04-20,2024-06-04,1885,7.8,Cloud AI Solutions +AI13777,Data Scientist,84791,USD,84791,EX,FT,India,M,Poland,0,"Python, Java, NLP, GCP",Bachelor,13,Retail,2024-07-03,2024-08-18,925,9.1,Predictive Systems +AI13778,Machine Learning Engineer,55644,USD,55644,EN,FL,South Korea,M,South Korea,100,"Statistics, Kubernetes, R, Linux",PhD,0,Education,2024-01-17,2024-03-23,800,7.5,Advanced Robotics +AI13779,Data Scientist,32651,USD,32651,MI,PT,India,L,India,50,"Computer Vision, NLP, Data Visualization, Python",Bachelor,3,Technology,2024-10-25,2024-12-28,1578,5.3,Neural Networks Co +AI13780,AI Software Engineer,207687,EUR,176534,EX,FT,Germany,M,Israel,50,"Python, Mathematics, Kubernetes",Bachelor,17,Finance,2024-04-19,2024-06-03,707,6.2,Cognitive Computing +AI13781,Machine Learning Engineer,251818,GBP,188864,EX,FT,United Kingdom,L,Latvia,100,"Deep Learning, Linux, Tableau, AWS",PhD,12,Telecommunications,2025-03-18,2025-05-13,775,6.7,Cognitive Computing +AI13782,Computer Vision Engineer,117307,USD,117307,MI,FL,Denmark,S,Denmark,0,"Git, Data Visualization, PyTorch, NLP, Java",PhD,4,Media,2024-08-30,2024-09-29,1371,7.6,Cloud AI Solutions +AI13783,Data Analyst,67912,JPY,7470320,EN,FT,Japan,S,Japan,0,"Scala, SQL, AWS, Docker",Master,0,Technology,2025-04-10,2025-05-14,2390,6,DataVision Ltd +AI13784,Data Engineer,221812,JPY,24399320,EX,FT,Japan,M,Japan,50,"Python, PyTorch, R, Mathematics",Bachelor,19,Gaming,2025-01-21,2025-03-24,1380,7.3,Autonomous Tech +AI13785,NLP Engineer,67496,USD,67496,SE,FT,China,M,Malaysia,100,"R, Hadoop, Computer Vision, Python, Scala",PhD,6,Transportation,2024-11-19,2024-12-15,862,8.1,Cognitive Computing +AI13786,Robotics Engineer,75744,CAD,94680,EN,CT,Canada,M,Canada,0,"Java, Linux, Mathematics",PhD,1,Energy,2024-07-28,2024-09-08,1383,9.6,AI Innovations +AI13787,Deep Learning Engineer,78980,SGD,102674,MI,CT,Singapore,S,Singapore,0,"SQL, PyTorch, Azure, R",PhD,4,Finance,2025-03-17,2025-04-15,1515,7.6,Neural Networks Co +AI13788,AI Consultant,138142,EUR,117421,SE,FL,Netherlands,S,South Africa,0,"Java, MLOps, Scala",PhD,6,Healthcare,2025-04-13,2025-06-14,1676,7.4,Smart Analytics +AI13789,ML Ops Engineer,183795,USD,183795,EX,CT,Sweden,M,Sweden,50,"Spark, Python, Tableau, Azure, GCP",Master,16,Energy,2024-06-20,2024-08-15,858,5.3,Digital Transformation LLC +AI13790,Autonomous Systems Engineer,181750,JPY,19992500,SE,FL,Japan,L,Japan,0,"GCP, Linux, Kubernetes, Scala",PhD,6,Consulting,2024-07-23,2024-09-07,1634,6.1,TechCorp Inc +AI13791,Autonomous Systems Engineer,122129,AUD,164874,SE,FT,Australia,S,Romania,100,"Spark, Kubernetes, MLOps",Master,6,Healthcare,2024-03-14,2024-04-03,685,5.9,Machine Intelligence Group +AI13792,Data Engineer,227275,CHF,204548,EX,CT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Deep Learning, Scala",Bachelor,16,Government,2024-04-10,2024-06-22,768,7.7,Neural Networks Co +AI13793,Machine Learning Engineer,164834,USD,164834,SE,FT,Denmark,S,Czech Republic,50,"SQL, Scala, Hadoop",PhD,9,Education,2024-01-01,2024-01-16,1996,7.8,Cognitive Computing +AI13794,Data Scientist,86870,CHF,78183,EN,FT,Switzerland,M,Brazil,50,"Java, Kubernetes, NLP",PhD,1,Consulting,2024-11-12,2025-01-21,983,5.4,Algorithmic Solutions +AI13795,ML Ops Engineer,75356,USD,75356,EN,FL,Sweden,L,Sweden,50,"Docker, PyTorch, Data Visualization, Azure",Associate,1,Consulting,2024-05-20,2024-07-06,845,9.2,Autonomous Tech +AI13796,AI Research Scientist,70888,USD,70888,MI,FT,Finland,M,Finland,100,"Spark, Mathematics, SQL, AWS",Bachelor,4,Healthcare,2024-11-22,2024-12-10,2303,5.4,DataVision Ltd +AI13797,Research Scientist,85683,AUD,115672,MI,FL,Australia,L,Philippines,100,"Scala, Python, Java, Docker, Data Visualization",Associate,3,Finance,2024-09-13,2024-11-22,1167,9.8,Future Systems +AI13798,Robotics Engineer,136342,EUR,115891,SE,CT,Austria,M,Australia,100,"TensorFlow, Java, MLOps",Bachelor,5,Energy,2024-06-07,2024-07-11,922,8.1,AI Innovations +AI13799,Deep Learning Engineer,308880,CHF,277992,EX,FT,Switzerland,S,Switzerland,0,"Deep Learning, Docker, AWS, Mathematics, Statistics",Associate,15,Automotive,2024-05-29,2024-07-01,1649,9.1,Smart Analytics +AI13800,Machine Learning Engineer,163206,USD,163206,EX,PT,United States,S,United States,50,"PyTorch, Linux, Azure, Hadoop, Kubernetes",Bachelor,19,Energy,2024-02-20,2024-04-18,2044,6.7,Cloud AI Solutions +AI13801,Data Engineer,268727,AUD,362781,EX,FT,Australia,L,Australia,100,"Kubernetes, SQL, Data Visualization, Tableau, Spark",Bachelor,13,Technology,2025-04-26,2025-06-21,1933,6.1,DeepTech Ventures +AI13802,AI Consultant,158218,CAD,197773,EX,PT,Canada,L,Canada,50,"GCP, Python, Computer Vision, Kubernetes, MLOps",Master,19,Technology,2024-03-23,2024-04-08,1759,7,AI Innovations +AI13803,Robotics Engineer,90014,GBP,67511,MI,FT,United Kingdom,S,United Kingdom,0,"Hadoop, Deep Learning, Linux, Java",PhD,3,Real Estate,2024-03-17,2024-04-30,2183,8.9,Cloud AI Solutions +AI13804,Deep Learning Engineer,350601,CHF,315541,EX,FL,Switzerland,M,Switzerland,50,"R, Computer Vision, Hadoop",Bachelor,17,Finance,2024-10-24,2025-01-05,674,7.5,Autonomous Tech +AI13805,Machine Learning Researcher,162040,USD,162040,EX,PT,Denmark,S,Denmark,0,"Statistics, Linux, Deep Learning",Bachelor,11,Government,2024-07-06,2024-08-25,808,6.6,Autonomous Tech +AI13806,AI Research Scientist,195569,CAD,244461,EX,FT,Canada,L,Canada,0,"Scala, TensorFlow, Java, Docker, SQL",Bachelor,14,Telecommunications,2024-01-26,2024-02-21,1230,5,DataVision Ltd +AI13807,AI Consultant,65095,USD,65095,EX,PT,China,S,China,50,"GCP, Mathematics, Python",Associate,14,Consulting,2024-08-05,2024-10-06,1770,5.3,Cognitive Computing +AI13808,Principal Data Scientist,135374,AUD,182755,SE,PT,Australia,S,Estonia,0,"Git, NLP, Linux, Hadoop",Master,6,Manufacturing,2025-02-14,2025-04-10,1991,6.5,Neural Networks Co +AI13809,Machine Learning Engineer,114011,USD,114011,SE,CT,South Korea,M,South Korea,0,"Kubernetes, Python, Linux, NLP",Associate,7,Gaming,2024-11-07,2024-12-28,1423,8.7,Machine Intelligence Group +AI13810,Data Engineer,67057,EUR,56998,MI,FT,Austria,S,Mexico,100,"NLP, Python, Hadoop, Linux, Azure",Associate,2,Education,2024-06-16,2024-08-01,1249,9.3,DeepTech Ventures +AI13811,AI Specialist,59067,EUR,50207,EN,FL,France,L,France,50,"Linux, MLOps, Spark, Python, Git",Bachelor,1,Retail,2024-10-07,2024-10-31,1401,9.7,Quantum Computing Inc +AI13812,AI Architect,178851,USD,178851,SE,FL,United States,L,United States,0,"Python, TensorFlow, GCP, Tableau",Associate,8,Consulting,2024-09-14,2024-11-01,2079,5.4,Neural Networks Co +AI13813,Robotics Engineer,91673,USD,91673,EX,FL,China,S,Spain,0,"Docker, Java, Linux",Master,12,Automotive,2025-03-26,2025-05-18,896,9.3,Machine Intelligence Group +AI13814,Machine Learning Researcher,176800,USD,176800,SE,FL,Norway,M,Austria,100,"Linux, NLP, Scala, Java",Bachelor,6,Manufacturing,2024-06-17,2024-08-03,807,8.2,Cognitive Computing +AI13815,AI Product Manager,56994,GBP,42746,EN,FL,United Kingdom,S,Spain,50,"Docker, Statistics, Scala, Java",Associate,1,Technology,2024-07-07,2024-08-16,1916,5.5,DeepTech Ventures +AI13816,AI Consultant,152056,EUR,129248,SE,CT,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Linux, GCP",Bachelor,7,Automotive,2024-03-08,2024-03-23,711,6.9,Predictive Systems +AI13817,Principal Data Scientist,77428,SGD,100656,MI,PT,Singapore,S,Singapore,100,"PyTorch, Linux, SQL, Data Visualization",Master,4,Government,2024-09-09,2024-10-03,994,9.7,Machine Intelligence Group +AI13818,Computer Vision Engineer,232854,AUD,314353,EX,PT,Australia,M,Turkey,50,"TensorFlow, AWS, Python, NLP",Master,14,Gaming,2024-03-27,2024-05-23,2158,5.8,Autonomous Tech +AI13819,AI Software Engineer,198603,CHF,178743,SE,FL,Switzerland,L,Turkey,100,"Spark, Git, Docker",Master,7,Technology,2025-01-28,2025-04-07,1864,8.2,Cognitive Computing +AI13820,AI Specialist,119402,USD,119402,SE,CT,Finland,L,Finland,100,"GCP, Scala, SQL, Tableau",Master,7,Telecommunications,2024-10-25,2024-12-17,742,8.4,Future Systems +AI13821,Machine Learning Engineer,62647,AUD,84573,EN,FL,Australia,M,Australia,50,"Azure, Git, Computer Vision, Tableau, Docker",Associate,1,Transportation,2024-03-19,2024-04-06,2182,5.9,TechCorp Inc +AI13822,AI Software Engineer,226045,USD,226045,EX,FL,Denmark,S,Latvia,100,"Hadoop, Scala, PyTorch",Associate,17,Education,2024-05-28,2024-07-25,664,7.2,Neural Networks Co +AI13823,Head of AI,220671,AUD,297906,EX,FL,Australia,L,Australia,0,"Kubernetes, MLOps, Mathematics, SQL",Bachelor,10,Energy,2024-10-29,2024-12-11,900,6,TechCorp Inc +AI13824,Principal Data Scientist,88695,CHF,79826,EN,PT,Switzerland,S,Switzerland,50,"NLP, SQL, R, Computer Vision, Docker",Associate,0,Real Estate,2024-07-31,2024-09-18,1805,5.8,DataVision Ltd +AI13825,NLP Engineer,55419,USD,55419,SE,PT,India,L,India,0,"Kubernetes, Computer Vision, Spark, Python, Docker",PhD,9,Energy,2024-04-17,2024-06-28,2238,9.1,AI Innovations +AI13826,AI Architect,121382,USD,121382,MI,FT,Norway,M,Finland,100,"SQL, Scala, Git, Computer Vision",Associate,4,Technology,2024-02-20,2024-03-05,1592,9.6,Digital Transformation LLC +AI13827,AI Research Scientist,80405,EUR,68344,EN,FL,Austria,L,Finland,0,"Azure, Git, Tableau, TensorFlow",Master,1,Education,2024-12-16,2025-01-09,2261,7.1,Predictive Systems +AI13828,NLP Engineer,234097,EUR,198982,EX,CT,France,L,Turkey,0,"Spark, Hadoop, SQL",Master,13,Gaming,2024-05-04,2024-06-14,1819,5.9,Future Systems +AI13829,Robotics Engineer,122139,USD,122139,SE,PT,Finland,M,Turkey,100,"GCP, Kubernetes, Hadoop, MLOps, Scala",Bachelor,8,Consulting,2024-09-08,2024-11-16,1113,9.6,Smart Analytics +AI13830,Autonomous Systems Engineer,61146,EUR,51974,EN,PT,Germany,L,Italy,100,"Computer Vision, Hadoop, Linux, SQL, Statistics",Bachelor,1,Education,2024-12-22,2025-03-03,2096,8.7,Autonomous Tech +AI13831,AI Research Scientist,72035,USD,72035,EN,FL,United States,S,United States,100,"Python, NLP, Docker, Kubernetes, Git",Associate,0,Gaming,2025-02-14,2025-04-22,2448,7,DeepTech Ventures +AI13832,Computer Vision Engineer,224347,USD,224347,EX,FT,Sweden,M,Belgium,50,"TensorFlow, GCP, Scala, R",Associate,19,Government,2025-04-03,2025-06-15,1747,8,Predictive Systems +AI13833,Principal Data Scientist,54240,USD,54240,SE,CT,China,S,Canada,100,"Spark, Python, PyTorch, SQL",Bachelor,5,Telecommunications,2024-08-16,2024-10-22,1611,7.8,Machine Intelligence Group +AI13834,Principal Data Scientist,153995,USD,153995,SE,FL,Denmark,M,Denmark,0,"GCP, Data Visualization, R",Associate,5,Retail,2024-09-07,2024-10-26,1386,9.7,Predictive Systems +AI13835,Autonomous Systems Engineer,196504,USD,196504,SE,FT,United States,L,United Kingdom,0,"Hadoop, Docker, TensorFlow, Mathematics, Git",Associate,6,Real Estate,2024-09-22,2024-10-06,2223,8.4,Predictive Systems +AI13836,Deep Learning Engineer,164839,GBP,123629,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, MLOps, R, GCP",Bachelor,10,Government,2024-12-24,2025-01-08,2256,10,AI Innovations +AI13837,NLP Engineer,57984,USD,57984,EN,PT,South Korea,M,South Korea,50,"Python, Mathematics, TensorFlow",Bachelor,0,Energy,2025-02-20,2025-05-03,2117,7.1,Advanced Robotics +AI13838,AI Architect,269893,EUR,229409,EX,PT,Netherlands,L,Germany,100,"Azure, Data Visualization, Git",PhD,13,Education,2025-03-24,2025-04-08,2342,5.2,Cloud AI Solutions +AI13839,Data Analyst,72103,EUR,61288,EN,FT,Netherlands,S,Netherlands,100,"Mathematics, Computer Vision, SQL, Kubernetes",Bachelor,1,Education,2025-02-13,2025-04-19,1864,5.7,Neural Networks Co +AI13840,Principal Data Scientist,130093,JPY,14310230,SE,PT,Japan,S,Japan,50,"Data Visualization, Git, Mathematics, Deep Learning, NLP",Master,7,Media,2024-12-05,2025-01-30,1903,8.2,Algorithmic Solutions +AI13841,AI Specialist,68572,USD,68572,EN,FT,Ireland,L,Ireland,100,"Kubernetes, Java, GCP, Mathematics, Scala",Associate,0,Technology,2024-12-15,2024-12-31,663,7.8,Cloud AI Solutions +AI13842,AI Architect,55431,EUR,47116,EN,FT,Germany,M,Germany,0,"PyTorch, Java, Statistics",Bachelor,1,Gaming,2024-05-01,2024-05-27,585,5.5,Future Systems +AI13843,AI Consultant,104409,AUD,140952,MI,FT,Australia,L,Hungary,100,"R, Python, GCP",Master,2,Finance,2024-07-06,2024-08-17,1477,6.3,Smart Analytics +AI13844,AI Product Manager,98179,USD,98179,MI,CT,Norway,S,Norway,100,"PyTorch, TensorFlow, Java, Hadoop",PhD,2,Technology,2024-10-30,2024-12-28,1392,9.2,Smart Analytics +AI13845,AI Product Manager,138780,USD,138780,EX,FT,Finland,S,New Zealand,0,"Deep Learning, Data Visualization, Python",PhD,11,Retail,2024-03-19,2024-05-12,2161,5.6,AI Innovations +AI13846,Principal Data Scientist,222699,CHF,200429,SE,PT,Switzerland,L,Switzerland,50,"Python, Linux, SQL",Bachelor,9,Retail,2025-01-22,2025-03-10,849,6.4,DeepTech Ventures +AI13847,AI Architect,50170,USD,50170,EN,PT,South Korea,L,South Korea,0,"PyTorch, Python, MLOps",Master,1,Retail,2025-04-16,2025-05-10,2460,7.6,Advanced Robotics +AI13848,Research Scientist,38746,USD,38746,MI,FT,China,S,Philippines,0,"R, Git, Tableau, Scala, Docker",PhD,4,Manufacturing,2025-03-10,2025-05-08,2240,5.9,Predictive Systems +AI13849,Principal Data Scientist,74319,USD,74319,EN,PT,Israel,M,Canada,100,"Python, Scala, AWS",Associate,0,Education,2025-02-20,2025-03-06,1598,9.8,Cognitive Computing +AI13850,Data Engineer,273668,JPY,30103480,EX,PT,Japan,L,Ghana,100,"Tableau, Spark, Deep Learning, GCP, Python",Bachelor,10,Education,2024-08-18,2024-09-08,2356,7.9,Cloud AI Solutions +AI13851,Data Engineer,66041,USD,66041,EN,PT,Denmark,M,Ukraine,100,"Mathematics, TensorFlow, Git, Python, Linux",Master,0,Telecommunications,2024-11-18,2024-12-30,1290,5.5,Advanced Robotics +AI13852,AI Product Manager,75268,EUR,63978,EN,PT,Germany,M,Germany,100,"Data Visualization, Scala, Statistics, NLP",Bachelor,1,Transportation,2024-12-18,2025-01-24,1933,7.4,Future Systems +AI13853,Robotics Engineer,177163,EUR,150589,EX,CT,Germany,M,Russia,100,"Java, Spark, Computer Vision, Docker",Master,13,Retail,2025-01-01,2025-02-11,1434,9.5,Advanced Robotics +AI13854,AI Software Engineer,169340,JPY,18627400,EX,CT,Japan,L,Japan,50,"Kubernetes, Computer Vision, Python, Scala",Master,16,Retail,2024-12-16,2025-02-18,903,9,DeepTech Ventures +AI13855,Research Scientist,150295,SGD,195384,SE,FT,Singapore,M,Malaysia,50,"R, Python, Data Visualization",Associate,5,Real Estate,2024-02-24,2024-04-01,1181,5.5,Neural Networks Co +AI13856,AI Product Manager,154260,CHF,138834,SE,FL,Switzerland,M,Germany,50,"GCP, Python, Tableau, Statistics, Mathematics",Associate,6,Gaming,2024-06-26,2024-07-13,1751,7.1,Predictive Systems +AI13857,AI Specialist,100497,CAD,125621,MI,CT,Canada,M,Canada,50,"TensorFlow, Python, Java",PhD,2,Retail,2024-12-24,2025-02-12,2099,6.5,DeepTech Ventures +AI13858,Machine Learning Engineer,193134,USD,193134,EX,FL,Sweden,L,South Korea,50,"Kubernetes, GCP, Python",Associate,14,Consulting,2024-08-13,2024-10-23,786,6.8,Algorithmic Solutions +AI13859,ML Ops Engineer,170026,CHF,153023,MI,FL,Switzerland,L,Switzerland,50,"Hadoop, Azure, Tableau, Data Visualization, Git",Bachelor,3,Automotive,2024-09-18,2024-11-07,2419,7.7,AI Innovations +AI13860,Data Analyst,237130,USD,237130,EX,FL,Finland,M,Hungary,50,"AWS, Hadoop, Tableau, Git",Associate,13,Technology,2024-01-23,2024-03-02,1588,7.8,Algorithmic Solutions +AI13861,Principal Data Scientist,122855,CHF,110570,MI,CT,Switzerland,S,Switzerland,100,"AWS, R, Git",PhD,4,Healthcare,2024-09-08,2024-11-18,1670,8.5,Smart Analytics +AI13862,AI Consultant,73055,CHF,65750,EN,FL,Switzerland,S,Egypt,50,"TensorFlow, Python, Docker, Statistics",PhD,0,Media,2024-08-22,2024-10-22,1510,8.9,Future Systems +AI13863,Research Scientist,38444,USD,38444,SE,CT,India,S,India,100,"PyTorch, Linux, TensorFlow, Data Visualization",Associate,9,Transportation,2024-06-14,2024-07-23,1791,9.6,Machine Intelligence Group +AI13864,Data Scientist,174441,USD,174441,EX,PT,Ireland,M,Romania,50,"Data Visualization, Azure, Python",Bachelor,11,Real Estate,2025-02-26,2025-03-27,1148,9.5,Future Systems +AI13865,AI Research Scientist,120189,USD,120189,SE,FL,Denmark,S,Denmark,0,"Python, SQL, Scala, TensorFlow, AWS",Master,5,Telecommunications,2025-04-06,2025-06-12,953,9.9,Future Systems +AI13866,Principal Data Scientist,112460,USD,112460,SE,PT,Ireland,S,Ireland,100,"Azure, Python, GCP, Scala, Mathematics",Associate,8,Technology,2024-08-17,2024-09-22,2399,9.8,Autonomous Tech +AI13867,AI Architect,230551,AUD,311244,EX,CT,Australia,M,Australia,100,"Spark, Statistics, Scala, Computer Vision, SQL",Bachelor,17,Education,2024-03-28,2024-05-17,1060,5.4,Neural Networks Co +AI13868,AI Research Scientist,143999,EUR,122399,SE,FL,Netherlands,L,Netherlands,0,"Deep Learning, Python, NLP, Hadoop, Java",PhD,6,Consulting,2024-05-05,2024-06-29,2418,8.8,Quantum Computing Inc +AI13869,AI Specialist,181922,CHF,163730,SE,CT,Switzerland,L,Hungary,50,"AWS, Git, Java",PhD,7,Transportation,2025-04-08,2025-06-03,1333,9.8,Cloud AI Solutions +AI13870,Autonomous Systems Engineer,121801,USD,121801,SE,FL,South Korea,L,France,0,"Python, TensorFlow, Computer Vision",Bachelor,8,Telecommunications,2024-04-09,2024-04-25,739,10,AI Innovations +AI13871,Research Scientist,158462,GBP,118847,SE,PT,United Kingdom,M,United Kingdom,0,"R, Python, PyTorch, Git, SQL",Master,9,Manufacturing,2024-04-12,2024-05-03,2349,9.4,Future Systems +AI13872,NLP Engineer,113678,USD,113678,SE,CT,Finland,L,Finland,0,"Python, Computer Vision, Linux, Azure",Bachelor,7,Education,2024-12-07,2025-02-04,1789,9.6,Future Systems +AI13873,ML Ops Engineer,151647,GBP,113735,SE,CT,United Kingdom,M,United Kingdom,50,"Git, R, Java",Bachelor,7,Telecommunications,2024-08-05,2024-09-18,1696,8.9,Quantum Computing Inc +AI13874,AI Software Engineer,111894,USD,111894,SE,FL,United States,S,United States,0,"Deep Learning, Kubernetes, Scala",PhD,8,Energy,2024-04-04,2024-04-22,1512,7.9,Advanced Robotics +AI13875,Autonomous Systems Engineer,99898,USD,99898,MI,PT,Sweden,M,Sweden,100,"Linux, Python, TensorFlow, Scala",PhD,3,Gaming,2024-08-24,2024-10-23,2166,7.9,TechCorp Inc +AI13876,Computer Vision Engineer,88708,USD,88708,MI,PT,Sweden,M,Egypt,50,"Computer Vision, MLOps, Java, Kubernetes, Docker",Master,2,Retail,2025-01-23,2025-04-02,788,8.2,Quantum Computing Inc +AI13877,AI Specialist,101550,JPY,11170500,MI,CT,Japan,M,Russia,0,"AWS, R, Deep Learning, Python",Master,4,Transportation,2024-05-27,2024-07-19,2250,7.9,TechCorp Inc +AI13878,ML Ops Engineer,69360,CAD,86700,EN,CT,Canada,L,Canada,100,"Kubernetes, Scala, Computer Vision",PhD,1,Retail,2024-05-19,2024-06-15,540,7.1,TechCorp Inc +AI13879,Robotics Engineer,124351,SGD,161656,SE,PT,Singapore,S,Singapore,100,"MLOps, SQL, Data Visualization, TensorFlow",Bachelor,6,Healthcare,2024-05-22,2024-06-11,2292,7.5,Quantum Computing Inc +AI13880,AI Specialist,174613,GBP,130960,EX,CT,United Kingdom,S,Finland,100,"SQL, Azure, NLP, Hadoop",Bachelor,17,Healthcare,2024-09-26,2024-10-15,2365,5.6,Machine Intelligence Group +AI13881,AI Software Engineer,164314,GBP,123236,SE,FT,United Kingdom,L,United Kingdom,0,"Git, Deep Learning, MLOps, Java",Bachelor,7,Healthcare,2025-01-11,2025-03-25,1645,8.6,TechCorp Inc +AI13882,NLP Engineer,33496,USD,33496,MI,FT,India,M,India,100,"PyTorch, Kubernetes, Deep Learning, MLOps, GCP",Associate,4,Telecommunications,2024-04-21,2024-07-01,1093,8,Advanced Robotics +AI13883,NLP Engineer,90700,USD,90700,EN,CT,United States,M,United States,50,"Tableau, Data Visualization, SQL, Python, GCP",Master,0,Government,2024-11-18,2025-01-20,1192,9.6,Neural Networks Co +AI13884,Machine Learning Researcher,43580,USD,43580,SE,PT,India,L,India,0,"Python, Computer Vision, Data Visualization",Associate,6,Healthcare,2025-01-19,2025-02-10,725,9.1,Future Systems +AI13885,Autonomous Systems Engineer,134932,USD,134932,SE,PT,United States,S,United States,0,"GCP, Python, PyTorch, Computer Vision, Hadoop",Master,8,Media,2024-04-05,2024-04-24,1152,5.6,TechCorp Inc +AI13886,Machine Learning Researcher,97649,USD,97649,MI,PT,Denmark,S,Denmark,100,"Python, Azure, GCP, Scala, Docker",Associate,2,Transportation,2024-02-26,2024-04-26,1846,9.1,Algorithmic Solutions +AI13887,Data Scientist,150764,EUR,128149,EX,FT,Germany,S,Ukraine,100,"Azure, Data Visualization, AWS, Python, Computer Vision",Bachelor,15,Healthcare,2024-10-24,2024-12-25,1536,9.2,Machine Intelligence Group +AI13888,Machine Learning Engineer,136387,GBP,102290,SE,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Statistics",PhD,9,Gaming,2025-01-20,2025-02-10,2089,9.9,Advanced Robotics +AI13889,AI Research Scientist,99958,USD,99958,MI,CT,United States,M,United States,100,"Linux, Kubernetes, Java, Computer Vision, NLP",Master,3,Government,2024-06-03,2024-07-14,1509,5.7,Neural Networks Co +AI13890,Autonomous Systems Engineer,98300,CAD,122875,SE,PT,Canada,S,Canada,0,"Python, Data Visualization, TensorFlow",Associate,7,Technology,2025-01-04,2025-03-07,566,5.5,Advanced Robotics +AI13891,Machine Learning Researcher,22579,USD,22579,EN,FT,India,S,India,100,"TensorFlow, SQL, Azure",Associate,0,Telecommunications,2024-05-19,2024-06-05,548,5.6,Future Systems +AI13892,Data Engineer,159778,USD,159778,SE,CT,Ireland,L,Romania,100,"Spark, Kubernetes, SQL, PyTorch",Bachelor,8,Manufacturing,2024-12-02,2025-02-11,1797,9.3,Autonomous Tech +AI13893,Autonomous Systems Engineer,52353,USD,52353,EX,CT,India,M,India,50,"R, Computer Vision, MLOps, Spark",Master,19,Government,2024-05-01,2024-06-16,2384,6.8,TechCorp Inc +AI13894,Data Scientist,82987,EUR,70539,MI,FT,Netherlands,M,Netherlands,0,"PyTorch, TensorFlow, NLP, R, Python",Master,2,Automotive,2025-02-09,2025-03-28,2186,9.1,Cognitive Computing +AI13895,Machine Learning Engineer,76339,USD,76339,SE,FL,South Korea,S,South Korea,50,"Python, GCP, Computer Vision",Associate,5,Healthcare,2025-02-19,2025-04-15,521,7.2,DeepTech Ventures +AI13896,Research Scientist,100750,USD,100750,EN,FL,Norway,L,Norway,50,"Azure, R, Docker",Master,1,Gaming,2024-09-26,2024-11-10,1045,7.3,Quantum Computing Inc +AI13897,Principal Data Scientist,73199,SGD,95159,EN,FT,Singapore,S,Singapore,50,"Python, PyTorch, Hadoop, Java",PhD,1,Government,2024-09-24,2024-11-02,668,5.6,Algorithmic Solutions +AI13898,Computer Vision Engineer,76495,USD,76495,EN,FT,United States,M,United States,100,"R, Docker, Data Visualization, NLP, PyTorch",Master,1,Automotive,2025-01-19,2025-03-12,1924,7.5,Algorithmic Solutions +AI13899,Machine Learning Researcher,101641,USD,101641,EN,FT,Norway,M,Norway,100,"Azure, NLP, SQL, Computer Vision, PyTorch",Bachelor,0,Technology,2024-01-03,2024-01-18,1481,5.7,Advanced Robotics +AI13900,Head of AI,66025,EUR,56121,EN,PT,Germany,M,Germany,50,"Python, R, TensorFlow, Statistics, AWS",Bachelor,1,Transportation,2024-07-20,2024-08-03,908,9,Machine Intelligence Group +AI13901,AI Product Manager,55150,USD,55150,SE,FT,India,L,India,100,"Hadoop, Tableau, Scala",Master,6,Energy,2025-02-20,2025-04-07,2055,9.2,DeepTech Ventures +AI13902,Data Engineer,132349,GBP,99262,EX,FT,United Kingdom,S,United Kingdom,50,"Spark, Tableau, AWS, Java",Master,17,Healthcare,2024-08-31,2024-10-30,750,5.6,Algorithmic Solutions +AI13903,AI Software Engineer,84903,EUR,72168,MI,PT,Netherlands,M,Netherlands,0,"Kubernetes, PyTorch, Data Visualization, Computer Vision",Bachelor,3,Manufacturing,2024-02-06,2024-04-15,761,5.5,Autonomous Tech +AI13904,Robotics Engineer,172144,JPY,18935840,SE,FT,Japan,L,Kenya,50,"Git, PyTorch, Java, Spark",Master,9,Telecommunications,2025-01-04,2025-02-06,710,6.3,TechCorp Inc +AI13905,AI Software Engineer,83302,SGD,108293,EN,PT,Singapore,M,Singapore,50,"Mathematics, Deep Learning, Python, Kubernetes, Azure",Bachelor,1,Media,2025-04-10,2025-05-09,2257,7.8,Cloud AI Solutions +AI13906,NLP Engineer,109085,CHF,98177,MI,CT,Switzerland,S,Australia,50,"SQL, Data Visualization, AWS, MLOps",Bachelor,3,Retail,2024-01-01,2024-02-09,1601,7.5,Neural Networks Co +AI13907,Machine Learning Engineer,354720,CHF,319248,EX,FT,Switzerland,M,Denmark,100,"SQL, Java, Linux",Master,17,Finance,2024-06-27,2024-07-19,1806,5.9,DeepTech Ventures +AI13908,Data Engineer,106171,EUR,90245,SE,PT,France,M,Ukraine,0,"Scala, Deep Learning, Computer Vision",Bachelor,5,Finance,2024-08-13,2024-09-08,1723,8.6,Cloud AI Solutions +AI13909,AI Specialist,86810,USD,86810,EX,PT,India,M,Germany,50,"Spark, PyTorch, Git, Data Visualization",Master,15,Energy,2024-05-29,2024-07-01,1002,8.6,Algorithmic Solutions +AI13910,Machine Learning Engineer,131624,USD,131624,SE,CT,Sweden,M,Ireland,50,"Docker, Linux, Kubernetes, NLP",PhD,8,Transportation,2024-02-11,2024-04-22,1531,9,DeepTech Ventures +AI13911,AI Research Scientist,68905,SGD,89577,EN,FL,Singapore,S,Singapore,50,"Kubernetes, R, TensorFlow, Statistics, Hadoop",Bachelor,0,Government,2024-03-06,2024-04-17,775,6.6,Predictive Systems +AI13912,Machine Learning Engineer,134463,GBP,100847,SE,FL,United Kingdom,M,Netherlands,0,"Spark, Linux, TensorFlow, Java",Bachelor,5,Manufacturing,2025-04-11,2025-05-04,1935,5.3,Quantum Computing Inc +AI13913,Principal Data Scientist,98904,USD,98904,EX,FL,India,L,India,0,"Git, GCP, Tableau, Spark, Scala",Master,14,Energy,2024-02-25,2024-04-09,1310,9.9,Digital Transformation LLC +AI13914,Data Engineer,257480,USD,257480,EX,FT,Norway,S,Japan,0,"GCP, Statistics, Linux, Scala, R",Master,13,Energy,2024-11-24,2025-01-09,890,5.5,Digital Transformation LLC +AI13915,AI Architect,117881,SGD,153245,SE,FL,Singapore,S,Singapore,0,"SQL, Git, Data Visualization, PyTorch, MLOps",Master,7,Government,2025-04-03,2025-06-01,680,9.4,Future Systems +AI13916,ML Ops Engineer,131840,EUR,112064,EX,CT,France,M,France,50,"Kubernetes, Java, Azure, Python, TensorFlow",PhD,13,Consulting,2024-07-24,2024-08-17,1098,8.7,AI Innovations +AI13917,Machine Learning Researcher,235864,SGD,306623,EX,PT,Singapore,S,Romania,0,"R, Data Visualization, GCP, Tableau",PhD,12,Technology,2024-12-30,2025-02-10,1394,8.7,DataVision Ltd +AI13918,Robotics Engineer,151764,EUR,128999,SE,FL,Germany,M,Germany,100,"Python, TensorFlow, Java, PyTorch, Mathematics",Associate,6,Media,2024-12-08,2025-01-21,2196,7.8,Future Systems +AI13919,AI Consultant,120897,USD,120897,MI,CT,Norway,L,Turkey,0,"GCP, Spark, Deep Learning",PhD,3,Retail,2025-03-16,2025-05-03,1528,5.6,DataVision Ltd +AI13920,Deep Learning Engineer,319778,USD,319778,EX,CT,Denmark,M,Denmark,0,"MLOps, Tableau, Linux, Git",Bachelor,18,Energy,2024-10-18,2024-11-05,1330,7.2,Cloud AI Solutions +AI13921,Data Engineer,213125,EUR,181156,EX,CT,Germany,M,Philippines,100,"TensorFlow, MLOps, GCP, Java",PhD,16,Energy,2025-01-11,2025-03-14,1895,8.2,TechCorp Inc +AI13922,AI Specialist,99994,EUR,84995,MI,PT,Netherlands,L,Czech Republic,50,"Computer Vision, AWS, TensorFlow, Python, R",Bachelor,2,Retail,2025-04-14,2025-06-13,1090,5.2,Algorithmic Solutions +AI13923,Deep Learning Engineer,42397,USD,42397,EN,FT,China,L,China,0,"TensorFlow, AWS, Azure, PyTorch",Master,1,Gaming,2024-03-01,2024-04-13,2322,6.3,AI Innovations +AI13924,Data Engineer,268816,GBP,201612,EX,CT,United Kingdom,M,United Kingdom,50,"Tableau, SQL, R, Docker, Kubernetes",Master,11,Telecommunications,2025-01-07,2025-03-02,1846,7.4,Cloud AI Solutions +AI13925,Machine Learning Engineer,146336,USD,146336,MI,CT,Denmark,L,United States,0,"PyTorch, R, Mathematics",Bachelor,4,Automotive,2024-11-15,2024-12-13,1227,8.2,Digital Transformation LLC +AI13926,ML Ops Engineer,163963,EUR,139369,EX,PT,Germany,M,Israel,100,"SQL, Data Visualization, Hadoop",PhD,15,Government,2024-08-13,2024-10-15,916,6.7,Predictive Systems +AI13927,Research Scientist,50533,USD,50533,SE,PT,India,M,India,0,"Statistics, R, Computer Vision, Hadoop, Git",Bachelor,5,Energy,2024-03-31,2024-05-29,1703,5.5,Smart Analytics +AI13928,AI Architect,82127,SGD,106765,EN,FT,Singapore,L,Colombia,50,"AWS, Spark, Linux, TensorFlow, Python",Master,0,Energy,2024-12-25,2025-01-23,2258,5.2,Cloud AI Solutions +AI13929,AI Consultant,116006,GBP,87005,SE,FT,United Kingdom,S,United Kingdom,50,"Python, PyTorch, Tableau, Mathematics, MLOps",Master,9,Education,2024-08-12,2024-10-10,1582,8,Algorithmic Solutions +AI13930,Robotics Engineer,126184,USD,126184,MI,PT,Norway,M,Norway,100,"Java, Linux, TensorFlow, R, Data Visualization",Master,4,Transportation,2024-11-14,2024-12-31,1710,5.6,Predictive Systems +AI13931,Machine Learning Researcher,160147,EUR,136125,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, TensorFlow, NLP, Statistics, Data Visualization",Master,7,Manufacturing,2024-04-13,2024-06-12,1699,5.9,Predictive Systems +AI13932,AI Product Manager,107865,SGD,140225,MI,CT,Singapore,M,Vietnam,100,"Python, Data Visualization, TensorFlow, PyTorch",Master,4,Gaming,2025-01-11,2025-02-26,1084,9.1,DeepTech Ventures +AI13933,AI Architect,187028,CHF,168325,SE,FT,Switzerland,S,Switzerland,0,"Python, Docker, Hadoop, Azure",Master,7,Transportation,2024-04-15,2024-06-12,1931,9,Machine Intelligence Group +AI13934,ML Ops Engineer,110875,CHF,99788,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, Python, Data Visualization",Master,3,Education,2024-12-13,2025-01-14,1288,7.1,Autonomous Tech +AI13935,Data Engineer,206757,USD,206757,EX,FL,United States,S,Ghana,0,"Scala, PyTorch, Data Visualization, GCP",PhD,13,Technology,2024-11-09,2024-12-02,1852,8.6,Advanced Robotics +AI13936,Machine Learning Engineer,56474,USD,56474,EN,FT,Ireland,M,Ireland,50,"Python, R, PyTorch",Bachelor,0,Government,2024-08-11,2024-09-09,1099,8.2,Cognitive Computing +AI13937,AI Specialist,85570,USD,85570,EX,FL,India,M,Italy,0,"PyTorch, TensorFlow, Linux, NLP",Bachelor,15,Automotive,2024-02-19,2024-04-21,689,7.9,Digital Transformation LLC +AI13938,Autonomous Systems Engineer,212458,CHF,191212,SE,FL,Switzerland,L,Switzerland,100,"Scala, Python, TensorFlow",Bachelor,6,Manufacturing,2024-06-06,2024-07-22,889,9.5,Advanced Robotics +AI13939,AI Architect,70580,SGD,91754,EN,PT,Singapore,S,Chile,100,"Azure, GCP, Python",Associate,1,Media,2024-01-16,2024-02-12,1169,9.8,AI Innovations +AI13940,Data Engineer,36309,USD,36309,SE,CT,India,S,Norway,100,"Linux, Git, Kubernetes, PyTorch, SQL",Master,9,Consulting,2024-05-21,2024-07-06,747,6.6,DeepTech Ventures +AI13941,Deep Learning Engineer,64560,USD,64560,EN,FT,Israel,M,Turkey,50,"Python, Data Visualization, Linux, Kubernetes, Computer Vision",Bachelor,0,Technology,2024-12-18,2025-02-16,1314,6,Smart Analytics +AI13942,Deep Learning Engineer,94949,EUR,80707,MI,CT,France,L,France,100,"R, Computer Vision, Data Visualization, Java",Bachelor,4,Transportation,2024-08-19,2024-09-25,979,6,Cloud AI Solutions +AI13943,Research Scientist,74347,USD,74347,MI,PT,South Korea,M,South Korea,50,"PyTorch, GCP, Scala, Java",Bachelor,3,Media,2024-10-04,2024-12-01,1926,7.9,AI Innovations +AI13944,AI Product Manager,321456,USD,321456,EX,FL,United States,L,United States,100,"Docker, GCP, Statistics",Master,15,Automotive,2024-10-25,2024-12-06,1311,8.6,Quantum Computing Inc +AI13945,Head of AI,72159,EUR,61335,EN,FT,Germany,L,Germany,0,"R, Spark, Mathematics",PhD,0,Retail,2024-04-16,2024-06-08,1412,8.4,Advanced Robotics +AI13946,Machine Learning Researcher,185190,USD,185190,EX,PT,Finland,S,Finland,100,"GCP, Scala, MLOps, Python, Azure",Bachelor,12,Automotive,2024-07-10,2024-09-20,977,8.5,Autonomous Tech +AI13947,AI Product Manager,150333,EUR,127783,SE,FT,Germany,L,Poland,0,"R, Azure, Git, Python",PhD,9,Automotive,2025-01-18,2025-02-24,1452,9.1,Quantum Computing Inc +AI13948,Research Scientist,265558,AUD,358503,EX,PT,Australia,L,Australia,0,"Java, Deep Learning, NLP",Master,12,Education,2024-06-07,2024-07-09,874,9.9,Cognitive Computing +AI13949,Machine Learning Researcher,82299,EUR,69954,MI,FT,Austria,L,Kenya,0,"Data Visualization, Deep Learning, Java",Master,2,Consulting,2024-11-14,2024-12-25,981,8.1,Cloud AI Solutions +AI13950,AI Specialist,148281,JPY,16310910,SE,FL,Japan,L,Japan,50,"Linux, Java, R, Kubernetes",PhD,5,Healthcare,2025-03-02,2025-03-17,892,7.8,Cognitive Computing +AI13951,AI Product Manager,33202,USD,33202,MI,FT,China,S,China,0,"Java, Python, Data Visualization, TensorFlow, Git",Bachelor,2,Education,2024-05-18,2024-07-19,821,8.5,Algorithmic Solutions +AI13952,AI Software Engineer,67300,USD,67300,EN,CT,Israel,M,Israel,0,"TensorFlow, Python, Linux, Statistics",Bachelor,0,Finance,2024-05-23,2024-06-25,2327,7.1,Cloud AI Solutions +AI13953,AI Product Manager,120081,USD,120081,MI,FL,Ireland,L,Ireland,100,"Data Visualization, R, Azure",Master,4,Real Estate,2024-01-15,2024-02-21,2086,7.6,Cognitive Computing +AI13954,Machine Learning Engineer,73036,EUR,62081,MI,CT,France,S,France,0,"Python, MLOps, Tableau",PhD,2,Technology,2025-04-08,2025-05-05,1365,9.2,AI Innovations +AI13955,Robotics Engineer,87908,USD,87908,EN,FT,Norway,S,Norway,100,"Kubernetes, Data Visualization, NLP, R, TensorFlow",Associate,0,Consulting,2024-11-29,2025-01-21,609,8.3,Quantum Computing Inc +AI13956,Machine Learning Researcher,70146,USD,70146,EX,PT,India,S,India,0,"Git, Python, Data Visualization, Linux, Scala",Bachelor,14,Education,2024-05-14,2024-07-25,669,5.5,DeepTech Ventures +AI13957,Principal Data Scientist,32133,USD,32133,MI,FL,India,S,India,100,"Azure, Python, Tableau, GCP",Bachelor,3,Media,2024-10-21,2024-12-25,1969,8.9,Algorithmic Solutions +AI13958,Data Scientist,108840,JPY,11972400,SE,CT,Japan,S,Japan,50,"TensorFlow, Kubernetes, GCP, Spark",Associate,8,Consulting,2024-06-17,2024-07-06,1758,7.5,Neural Networks Co +AI13959,Machine Learning Researcher,122926,EUR,104487,SE,PT,Netherlands,M,United States,0,"Kubernetes, Scala, Tableau",Master,9,Retail,2024-03-17,2024-04-03,1477,8.5,Autonomous Tech +AI13960,AI Product Manager,287863,CHF,259077,EX,PT,Switzerland,M,Norway,50,"Scala, Deep Learning, Hadoop",PhD,19,Automotive,2024-04-07,2024-05-24,1944,6.5,Predictive Systems +AI13961,Machine Learning Engineer,99266,USD,99266,SE,FT,Ireland,S,Ireland,50,"MLOps, Spark, PyTorch",Associate,7,Finance,2024-07-15,2024-08-10,2461,5.3,Neural Networks Co +AI13962,NLP Engineer,228899,JPY,25178890,EX,FT,Japan,M,China,50,"MLOps, Docker, Kubernetes, Python, AWS",PhD,18,Real Estate,2024-06-05,2024-07-28,2258,8.4,Advanced Robotics +AI13963,Data Scientist,162574,USD,162574,EX,PT,Ireland,M,Ireland,100,"Kubernetes, Spark, Tableau, Deep Learning",Bachelor,16,Real Estate,2024-10-29,2024-12-21,2146,6.7,AI Innovations +AI13964,Data Engineer,225255,USD,225255,EX,PT,Finland,L,Finland,100,"Deep Learning, Computer Vision, Tableau, Azure, Docker",PhD,13,Manufacturing,2024-06-12,2024-08-12,632,5.5,Autonomous Tech +AI13965,Head of AI,132938,CHF,119644,MI,FL,Switzerland,S,Switzerland,0,"Git, Azure, MLOps, Linux, R",PhD,2,Education,2025-02-04,2025-03-01,551,9.9,Smart Analytics +AI13966,AI Consultant,90671,USD,90671,SE,FT,Israel,S,Poland,50,"PyTorch, Kubernetes, TensorFlow, SQL",PhD,7,Finance,2025-02-08,2025-02-25,2316,9.8,Algorithmic Solutions +AI13967,AI Architect,179691,SGD,233598,EX,CT,Singapore,L,Singapore,0,"Scala, MLOps, Python",Bachelor,13,Telecommunications,2024-10-13,2024-12-18,1094,7.5,Cognitive Computing +AI13968,AI Specialist,80674,USD,80674,EX,FL,India,L,India,0,"Git, PyTorch, Hadoop",PhD,13,Real Estate,2024-06-30,2024-07-27,1834,9.6,Quantum Computing Inc +AI13969,Research Scientist,96450,CAD,120563,SE,PT,Canada,S,Canada,50,"Hadoop, Python, TensorFlow, Computer Vision",Master,9,Transportation,2024-03-17,2024-05-05,1744,5.3,TechCorp Inc +AI13970,AI Research Scientist,132495,USD,132495,SE,FL,Sweden,L,Sweden,50,"Kubernetes, Docker, NLP",Bachelor,9,Automotive,2024-10-12,2024-12-04,1918,8.9,Cloud AI Solutions +AI13971,Machine Learning Engineer,70645,CAD,88306,EN,CT,Canada,L,Canada,50,"Linux, Tableau, Python, PyTorch",Associate,1,Media,2025-03-27,2025-05-11,1527,9.3,Machine Intelligence Group +AI13972,Robotics Engineer,24476,USD,24476,EN,PT,China,S,China,50,"Statistics, Scala, Java, MLOps, Deep Learning",Associate,1,Telecommunications,2024-12-18,2025-01-21,996,7.5,Neural Networks Co +AI13973,Machine Learning Engineer,219297,SGD,285086,EX,FL,Singapore,L,Singapore,50,"Kubernetes, Scala, Spark, Deep Learning, Statistics",Associate,15,Automotive,2024-06-27,2024-07-25,705,6.6,Machine Intelligence Group +AI13974,Computer Vision Engineer,139564,GBP,104673,EX,PT,United Kingdom,S,United Kingdom,100,"Linux, GCP, Scala",PhD,15,Telecommunications,2025-03-10,2025-04-17,1455,9.2,Machine Intelligence Group +AI13975,NLP Engineer,232693,USD,232693,EX,FT,United States,S,United States,50,"Computer Vision, Python, TensorFlow, Java, R",PhD,14,Gaming,2024-06-29,2024-08-03,2116,7.7,AI Innovations +AI13976,Machine Learning Engineer,97324,USD,97324,MI,PT,Ireland,S,Sweden,50,"AWS, Linux, NLP, Kubernetes",PhD,3,Energy,2024-01-31,2024-04-01,970,6.7,Autonomous Tech +AI13977,AI Specialist,83572,USD,83572,MI,FT,South Korea,L,Italy,0,"Docker, Hadoop, Kubernetes, Statistics, R",Bachelor,3,Real Estate,2024-01-03,2024-03-13,2121,8.2,Cloud AI Solutions +AI13978,Computer Vision Engineer,119106,USD,119106,MI,FL,United States,M,Nigeria,100,"Tableau, Java, Python",Bachelor,2,Government,2025-04-19,2025-06-14,1345,7.8,Machine Intelligence Group +AI13979,Deep Learning Engineer,107752,SGD,140078,MI,PT,Singapore,L,Singapore,100,"AWS, Docker, Data Visualization, GCP, Kubernetes",Master,2,Energy,2024-06-08,2024-06-28,2045,5.3,Cloud AI Solutions +AI13980,AI Consultant,62312,SGD,81006,EN,FL,Singapore,M,Singapore,0,"Deep Learning, Data Visualization, Python, Tableau, MLOps",PhD,1,Education,2024-05-02,2024-05-26,1829,7.8,Neural Networks Co +AI13981,Principal Data Scientist,118029,USD,118029,SE,FT,Ireland,L,Ireland,0,"TensorFlow, SQL, Tableau",PhD,7,Retail,2024-05-14,2024-07-25,1262,7.4,TechCorp Inc +AI13982,Computer Vision Engineer,204810,AUD,276494,EX,FL,Australia,S,Australia,0,"AWS, Data Visualization, R, NLP",Master,18,Retail,2024-01-28,2024-03-03,727,6.1,Neural Networks Co +AI13983,Research Scientist,79470,EUR,67550,MI,FT,Netherlands,M,Portugal,100,"Deep Learning, Mathematics, MLOps, Java, GCP",Associate,3,Finance,2024-09-06,2024-10-18,2268,9.1,Future Systems +AI13984,Data Analyst,86228,AUD,116408,MI,CT,Australia,M,Switzerland,100,"Statistics, Spark, GCP, Git",PhD,2,Real Estate,2024-06-17,2024-07-02,1626,6.6,Neural Networks Co +AI13985,Data Engineer,118142,CAD,147678,MI,FT,Canada,L,Canada,100,"NLP, Python, Tableau",PhD,3,Retail,2024-02-16,2024-03-02,984,5.8,Smart Analytics +AI13986,Principal Data Scientist,149989,USD,149989,EX,CT,Israel,S,Israel,100,"AWS, PyTorch, Deep Learning, Mathematics",Bachelor,11,Energy,2024-09-14,2024-10-04,1455,6.8,TechCorp Inc +AI13987,Data Scientist,59094,USD,59094,EN,CT,South Korea,M,United States,0,"Kubernetes, Data Visualization, Git",Master,1,Retail,2024-07-09,2024-07-29,1869,8,Cognitive Computing +AI13988,Machine Learning Engineer,177285,USD,177285,SE,FL,Norway,L,Norway,0,"Scala, MLOps, Tableau, Data Visualization, R",Associate,8,Government,2024-03-30,2024-04-29,1226,8.2,Quantum Computing Inc +AI13989,Autonomous Systems Engineer,86720,USD,86720,EN,PT,Denmark,M,Denmark,0,"Computer Vision, Tableau, Scala",Master,1,Education,2024-04-01,2024-06-07,1124,6.8,Advanced Robotics +AI13990,Data Scientist,86353,USD,86353,EX,CT,China,L,China,0,"Computer Vision, Statistics, NLP, Tableau, Scala",Associate,17,Real Estate,2024-11-30,2025-01-08,1182,9.3,Cognitive Computing +AI13991,AI Specialist,43936,USD,43936,SE,PT,India,M,India,50,"Data Visualization, PyTorch, Docker, Hadoop, AWS",PhD,8,Real Estate,2025-03-07,2025-05-17,1226,6.7,Neural Networks Co +AI13992,Computer Vision Engineer,143556,USD,143556,EX,FT,Finland,M,Spain,100,"Data Visualization, Statistics, Python, Git",Master,16,Education,2025-03-05,2025-04-16,2169,8.9,Predictive Systems +AI13993,Robotics Engineer,78380,USD,78380,EX,PT,India,M,China,50,"Python, Java, PyTorch, Mathematics",PhD,18,Government,2024-12-24,2025-01-20,768,5.9,Predictive Systems +AI13994,AI Consultant,72730,EUR,61821,MI,FL,Austria,S,Austria,100,"GCP, SQL, Kubernetes, Data Visualization",Bachelor,2,Energy,2024-08-03,2024-09-03,519,7.1,Digital Transformation LLC +AI13995,Head of AI,290341,USD,290341,EX,CT,Sweden,L,Sweden,0,"Computer Vision, Python, MLOps",Associate,16,Retail,2024-06-15,2024-08-25,618,5.1,DataVision Ltd +AI13996,Data Engineer,217967,USD,217967,EX,CT,Ireland,S,Brazil,50,"PyTorch, AWS, TensorFlow",Master,17,Media,2024-09-18,2024-11-03,1350,8.7,Digital Transformation LLC +AI13997,Data Engineer,102309,USD,102309,EX,FL,India,L,India,100,"SQL, Python, Computer Vision, Mathematics",Bachelor,11,Technology,2024-05-17,2024-06-25,1370,8.2,Neural Networks Co +AI13998,Research Scientist,80525,EUR,68446,MI,FT,Netherlands,M,Indonesia,0,"Java, R, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-09,2180,7.3,Advanced Robotics +AI13999,Data Scientist,202160,USD,202160,SE,FT,United States,L,United States,100,"MLOps, Git, Tableau, Scala",Bachelor,6,Transportation,2025-04-12,2025-06-24,1769,7,Algorithmic Solutions +AI14000,Head of AI,220964,USD,220964,EX,FT,Sweden,S,Sweden,100,"PyTorch, Computer Vision, Hadoop, Python, Spark",PhD,19,Automotive,2024-11-14,2025-01-15,2217,8.3,Quantum Computing Inc +AI14001,AI Specialist,56149,USD,56149,EN,PT,Israel,L,Israel,100,"TensorFlow, NLP, Data Visualization, Scala",Master,0,Technology,2025-03-06,2025-04-20,2102,8.5,Algorithmic Solutions +AI14002,Principal Data Scientist,145157,CAD,181446,SE,FT,Canada,L,Canada,100,"Azure, Data Visualization, AWS, Kubernetes",PhD,9,Education,2025-01-16,2025-02-09,2214,5.6,Neural Networks Co +AI14003,Data Engineer,172667,USD,172667,SE,PT,Sweden,L,Mexico,0,"SQL, GCP, Java, Deep Learning",Bachelor,6,Education,2024-12-28,2025-01-17,1466,5.4,AI Innovations +AI14004,NLP Engineer,138247,AUD,186633,EX,FL,Australia,M,Chile,100,"SQL, Python, Computer Vision, NLP, Spark",Master,12,Consulting,2024-12-28,2025-02-25,1737,6,Machine Intelligence Group +AI14005,Robotics Engineer,129293,USD,129293,MI,PT,Norway,M,South Africa,0,"Mathematics, Linux, MLOps",Master,4,Media,2024-04-10,2024-05-06,1752,7,TechCorp Inc +AI14006,AI Specialist,106869,CAD,133586,SE,FT,Canada,M,New Zealand,100,"SQL, Python, Statistics, GCP, Kubernetes",Master,7,Media,2024-08-21,2024-10-15,1926,5.1,Machine Intelligence Group +AI14007,NLP Engineer,57671,EUR,49020,EN,FT,France,L,France,50,"Azure, Git, Hadoop",Associate,1,Healthcare,2025-04-02,2025-05-01,1741,6.8,DataVision Ltd +AI14008,AI Product Manager,279242,GBP,209432,EX,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Linux, Computer Vision",Master,12,Transportation,2024-10-21,2024-11-15,1138,6.9,Machine Intelligence Group +AI14009,Data Scientist,204632,JPY,22509520,EX,FT,Japan,L,Japan,100,"Scala, Spark, Deep Learning, Git, PyTorch",Associate,14,Retail,2025-02-27,2025-04-07,1462,9.9,AI Innovations +AI14010,Data Engineer,203509,EUR,172983,EX,FT,Germany,M,Germany,100,"Python, MLOps, Data Visualization, Scala, Tableau",Associate,11,Real Estate,2024-03-29,2024-05-25,1317,6.1,Machine Intelligence Group +AI14011,AI Research Scientist,76433,EUR,64968,EN,CT,Netherlands,S,Netherlands,50,"Python, Data Visualization, Hadoop, GCP",Associate,1,Technology,2025-04-23,2025-06-06,1324,7.1,TechCorp Inc +AI14012,Machine Learning Engineer,143395,CAD,179244,EX,FL,Canada,M,Singapore,0,"NLP, Data Visualization, Python",Associate,15,Energy,2025-01-28,2025-03-27,1767,7.8,AI Innovations +AI14013,Data Scientist,190317,USD,190317,EX,PT,United States,M,United States,0,"Tableau, Spark, R",PhD,13,Gaming,2024-10-23,2024-11-17,1196,6.9,Machine Intelligence Group +AI14014,Deep Learning Engineer,18052,USD,18052,EN,FL,India,M,Russia,50,"AWS, SQL, Computer Vision, NLP, Azure",Associate,0,Finance,2024-09-24,2024-11-05,1104,5,Machine Intelligence Group +AI14015,Data Analyst,157903,EUR,134218,SE,FL,Germany,L,Germany,50,"Hadoop, Linux, R",Associate,7,Energy,2024-02-29,2024-04-23,766,5.4,DataVision Ltd +AI14016,Deep Learning Engineer,208955,USD,208955,EX,FL,United States,L,United States,100,"Computer Vision, PyTorch, Git",Master,19,Consulting,2024-04-18,2024-06-22,2055,8.9,Autonomous Tech +AI14017,Research Scientist,34807,USD,34807,EN,CT,China,L,China,100,"Linux, R, Statistics, Kubernetes",Bachelor,1,Education,2025-02-23,2025-04-28,1827,7.1,Future Systems +AI14018,Research Scientist,81021,AUD,109378,MI,FT,Australia,S,Australia,100,"Linux, GCP, Mathematics, NLP",PhD,2,Energy,2024-12-18,2025-01-16,1620,9.9,Machine Intelligence Group +AI14019,Data Analyst,64631,EUR,54936,EN,CT,France,L,France,50,"Azure, Deep Learning, Scala, Computer Vision",Master,1,Healthcare,2024-07-28,2024-09-18,665,9.9,Smart Analytics +AI14020,AI Specialist,92162,USD,92162,EN,FT,Denmark,S,Denmark,0,"GCP, Data Visualization, Spark",PhD,0,Gaming,2024-06-16,2024-08-26,1011,9.5,Future Systems +AI14021,AI Product Manager,110327,USD,110327,MI,FT,Ireland,M,Ireland,100,"Tableau, Hadoop, Java, Spark, Deep Learning",Bachelor,2,Consulting,2024-09-18,2024-10-29,1272,7.4,Quantum Computing Inc +AI14022,Robotics Engineer,102765,USD,102765,MI,FL,Denmark,S,Denmark,0,"Linux, Git, Tableau",Bachelor,3,Technology,2025-02-10,2025-03-29,1076,8.5,DataVision Ltd +AI14023,Deep Learning Engineer,91759,USD,91759,EN,CT,United States,M,South Africa,100,"R, SQL, Hadoop",PhD,0,Automotive,2024-01-09,2024-03-01,2033,5,Digital Transformation LLC +AI14024,AI Product Manager,159836,USD,159836,EX,CT,Ireland,L,United States,50,"GCP, SQL, Hadoop",PhD,17,Consulting,2024-09-19,2024-11-09,2184,5.4,DataVision Ltd +AI14025,AI Software Engineer,120984,CHF,108886,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Kubernetes, AWS, MLOps, SQL",Associate,1,Real Estate,2024-12-20,2025-02-11,658,5.3,Predictive Systems +AI14026,Data Scientist,159881,USD,159881,SE,PT,Ireland,L,Ireland,0,"Scala, PyTorch, Azure, AWS, Statistics",Bachelor,5,Telecommunications,2025-04-07,2025-05-31,2464,6.7,Digital Transformation LLC +AI14027,NLP Engineer,89150,JPY,9806500,EN,FL,Japan,L,Japan,0,"Git, GCP, Mathematics, PyTorch, TensorFlow",Master,1,Gaming,2024-02-13,2024-04-24,691,5.7,Autonomous Tech +AI14028,AI Consultant,67892,EUR,57708,MI,CT,France,S,France,100,"Kubernetes, Docker, Java",Master,3,Finance,2025-03-14,2025-04-01,1181,5.6,Quantum Computing Inc +AI14029,ML Ops Engineer,92548,GBP,69411,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Mathematics, Computer Vision, R",Master,1,Transportation,2024-09-14,2024-11-16,1462,5.9,Neural Networks Co +AI14030,Head of AI,53496,USD,53496,EN,FT,South Korea,S,Israel,0,"Deep Learning, Python, Tableau",Master,1,Energy,2024-11-03,2024-11-21,1703,9,Cognitive Computing +AI14031,Computer Vision Engineer,70599,EUR,60009,MI,FL,Austria,S,Colombia,50,"Java, Scala, Azure",Associate,3,Gaming,2025-02-16,2025-04-22,661,6.9,Quantum Computing Inc +AI14032,ML Ops Engineer,61691,EUR,52437,MI,CT,Austria,S,Austria,100,"Kubernetes, Computer Vision, Java",Master,4,Finance,2024-06-22,2024-08-10,1223,9,TechCorp Inc +AI14033,Data Analyst,128526,USD,128526,SE,FL,Ireland,L,Ireland,50,"AWS, SQL, GCP, Java",Master,9,Gaming,2024-01-21,2024-02-16,2257,5.5,Smart Analytics +AI14034,Autonomous Systems Engineer,211888,JPY,23307680,EX,FT,Japan,M,Japan,50,"Linux, MLOps, Azure, Hadoop, Spark",Associate,14,Energy,2024-09-08,2024-10-15,2247,6.9,Predictive Systems +AI14035,Robotics Engineer,111691,CAD,139614,SE,FL,Canada,S,Canada,50,"Scala, Git, R, AWS",Bachelor,6,Telecommunications,2025-03-28,2025-05-12,1360,10,AI Innovations +AI14036,Data Scientist,38446,USD,38446,SE,PT,India,S,India,100,"Docker, Python, TensorFlow, GCP",Associate,9,Government,2024-10-08,2024-11-18,1097,5.3,TechCorp Inc +AI14037,NLP Engineer,90939,CAD,113674,MI,CT,Canada,L,Canada,50,"SQL, Data Visualization, MLOps, Git, Kubernetes",Master,4,Finance,2024-05-03,2024-06-16,592,9.7,Neural Networks Co +AI14038,AI Software Engineer,89119,CAD,111399,MI,FL,Canada,S,Canada,100,"R, Data Visualization, Statistics, Scala",Master,2,Real Estate,2024-03-15,2024-05-22,805,6.7,AI Innovations +AI14039,Principal Data Scientist,334067,USD,334067,EX,FT,Norway,L,Norway,50,"Python, Statistics, Git",Master,11,Media,2025-02-20,2025-03-12,929,9.1,Digital Transformation LLC +AI14040,Head of AI,168122,USD,168122,EX,FT,South Korea,S,South Korea,0,"Mathematics, Linux, Scala, Statistics, SQL",PhD,12,Manufacturing,2025-01-15,2025-03-21,2195,6.3,Neural Networks Co +AI14041,ML Ops Engineer,130674,CHF,117607,SE,PT,Switzerland,S,Switzerland,0,"Azure, Python, Tableau, GCP",Associate,9,Telecommunications,2025-01-05,2025-02-15,2192,5.3,TechCorp Inc +AI14042,Research Scientist,147848,EUR,125671,EX,CT,Austria,S,Austria,50,"Java, Azure, GCP",PhD,19,Automotive,2024-01-23,2024-02-11,1992,9.4,Neural Networks Co +AI14043,Data Engineer,206878,CHF,186190,EX,PT,Switzerland,M,United States,50,"Linux, TensorFlow, Python, Deep Learning",PhD,10,Telecommunications,2024-02-25,2024-03-27,2374,9.9,Neural Networks Co +AI14044,ML Ops Engineer,120770,USD,120770,MI,FT,Denmark,S,Denmark,0,"Statistics, Python, Computer Vision, PyTorch",Bachelor,4,Manufacturing,2025-02-20,2025-03-08,1180,7.4,Cloud AI Solutions +AI14045,ML Ops Engineer,209060,CAD,261325,EX,CT,Canada,S,Canada,50,"TensorFlow, Kubernetes, Scala",Associate,17,Technology,2024-12-02,2025-01-27,600,9.1,Predictive Systems +AI14046,Robotics Engineer,55846,USD,55846,EN,PT,Ireland,S,Ireland,0,"Deep Learning, Data Visualization, Tableau, Mathematics",Associate,1,Consulting,2024-12-05,2025-01-12,1994,6.8,TechCorp Inc +AI14047,Autonomous Systems Engineer,96258,USD,96258,MI,FL,Ireland,M,Ireland,50,"Scala, Data Visualization, Azure, NLP, Git",Associate,3,Manufacturing,2025-01-12,2025-01-28,1073,8,Machine Intelligence Group +AI14048,Principal Data Scientist,76228,AUD,102908,EN,CT,Australia,L,Australia,100,"SQL, Git, PyTorch, Tableau, Kubernetes",Bachelor,1,Government,2024-05-08,2024-06-03,1156,7.1,Autonomous Tech +AI14049,AI Research Scientist,202209,USD,202209,SE,PT,Norway,L,Estonia,100,"TensorFlow, Computer Vision, SQL, Java, Linux",Bachelor,6,Gaming,2025-04-17,2025-06-21,1599,6.4,TechCorp Inc +AI14050,Autonomous Systems Engineer,106972,CHF,96275,MI,PT,Switzerland,S,Egypt,100,"MLOps, Linux, Tableau, PyTorch, Hadoop",PhD,4,Finance,2024-01-09,2024-03-09,636,7.1,Advanced Robotics +AI14051,Computer Vision Engineer,79068,USD,79068,EX,FT,China,S,China,50,"Tableau, Deep Learning, PyTorch",PhD,16,Energy,2024-01-06,2024-02-04,1101,9.8,Quantum Computing Inc +AI14052,Autonomous Systems Engineer,101691,CHF,91522,MI,PT,Switzerland,S,Switzerland,50,"Java, Scala, Git, Statistics",Bachelor,2,Transportation,2024-09-01,2024-10-13,1488,5.8,Autonomous Tech +AI14053,AI Software Engineer,113366,SGD,147376,MI,PT,Singapore,L,Singapore,100,"Java, NLP, Spark, TensorFlow, Azure",Master,4,Manufacturing,2024-11-11,2024-12-04,772,8.5,Quantum Computing Inc +AI14054,ML Ops Engineer,309967,GBP,232475,EX,FL,United Kingdom,L,United Kingdom,50,"SQL, Java, Data Visualization, Hadoop, Computer Vision",Bachelor,18,Technology,2025-01-08,2025-02-20,830,6.8,Quantum Computing Inc +AI14055,AI Research Scientist,137461,EUR,116842,SE,CT,Netherlands,S,Luxembourg,50,"GCP, Python, TensorFlow, R",Associate,9,Healthcare,2025-01-06,2025-03-09,1144,8.2,AI Innovations +AI14056,AI Software Engineer,87443,USD,87443,EN,CT,United States,L,United States,0,"Computer Vision, Hadoop, Python, Kubernetes, Docker",Associate,0,Finance,2024-11-12,2024-12-06,2171,8.1,Digital Transformation LLC +AI14057,ML Ops Engineer,116059,SGD,150877,MI,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Azure, Computer Vision, Git",PhD,4,Retail,2024-07-05,2024-08-28,810,9.1,Advanced Robotics +AI14058,Principal Data Scientist,82475,USD,82475,EN,CT,Denmark,S,Netherlands,0,"GCP, SQL, Spark, Java, Mathematics",Associate,1,Retail,2025-02-19,2025-03-24,1099,9.4,Neural Networks Co +AI14059,Machine Learning Researcher,134959,USD,134959,SE,PT,Ireland,M,Ireland,50,"Git, Azure, MLOps, Linux",Bachelor,8,Finance,2024-02-26,2024-04-03,1639,9.7,AI Innovations +AI14060,NLP Engineer,295543,USD,295543,EX,FL,United States,L,Portugal,0,"SQL, Scala, Mathematics, Azure, Hadoop",Associate,14,Manufacturing,2024-03-10,2024-04-19,739,8.7,Smart Analytics +AI14061,Head of AI,69846,USD,69846,EN,FL,United States,M,Estonia,100,"Java, PyTorch, Scala, SQL",Associate,1,Finance,2024-11-09,2024-12-29,2048,8.7,DataVision Ltd +AI14062,Data Analyst,129073,JPY,14198030,SE,CT,Japan,L,Japan,100,"Linux, Data Visualization, Kubernetes, NLP, R",Bachelor,6,Transportation,2024-03-12,2024-04-27,1605,8.8,Machine Intelligence Group +AI14063,Principal Data Scientist,60030,EUR,51026,EN,CT,France,L,France,0,"Python, Java, Azure",PhD,1,Healthcare,2024-02-09,2024-04-13,810,5.2,Smart Analytics +AI14064,Machine Learning Engineer,90890,CAD,113613,MI,FL,Canada,L,Romania,50,"Statistics, Kubernetes, Python, TensorFlow",Master,2,Real Estate,2024-04-19,2024-06-12,1477,5.8,Neural Networks Co +AI14065,AI Architect,166381,USD,166381,SE,PT,Ireland,L,Germany,100,"Java, Data Visualization, AWS, Docker, Computer Vision",Bachelor,7,Media,2024-08-24,2024-09-19,2450,7.8,Smart Analytics +AI14066,AI Product Manager,281704,USD,281704,EX,FL,Ireland,L,New Zealand,100,"Computer Vision, Azure, Spark, AWS",Master,17,Energy,2024-09-24,2024-11-10,2033,9.6,DeepTech Ventures +AI14067,Computer Vision Engineer,132917,USD,132917,SE,FT,Ireland,S,Ireland,50,"SQL, Git, Python",Associate,7,Real Estate,2024-10-05,2024-11-07,980,5.5,AI Innovations +AI14068,AI Product Manager,29350,USD,29350,MI,FL,India,S,India,100,"Kubernetes, PyTorch, Hadoop, MLOps, Spark",Master,3,Education,2024-07-19,2024-09-18,1755,8.1,Quantum Computing Inc +AI14069,Data Analyst,72631,USD,72631,EN,FL,Norway,S,Norway,0,"Mathematics, Statistics, Kubernetes, Azure",PhD,0,Energy,2025-03-23,2025-04-09,1392,6.1,DataVision Ltd +AI14070,AI Research Scientist,57268,USD,57268,SE,FT,China,M,China,50,"TensorFlow, SQL, Data Visualization, GCP, Azure",Master,5,Retail,2024-02-18,2024-04-01,1414,7.5,Autonomous Tech +AI14071,AI Research Scientist,83126,CHF,74813,EN,FL,Switzerland,L,Sweden,0,"Python, TensorFlow, Scala, Kubernetes, Computer Vision",PhD,1,Transportation,2024-09-19,2024-10-28,1399,7.1,Advanced Robotics +AI14072,AI Product Manager,114645,USD,114645,MI,FL,Norway,M,Norway,0,"Git, SQL, MLOps",Master,4,Transportation,2024-11-23,2024-12-10,2416,6,DeepTech Ventures +AI14073,ML Ops Engineer,63688,USD,63688,EN,FT,Israel,S,Israel,50,"Data Visualization, Git, Computer Vision",PhD,1,Real Estate,2024-03-03,2024-04-06,1831,8.3,Advanced Robotics +AI14074,Research Scientist,122807,EUR,104386,SE,FT,Germany,S,Switzerland,0,"GCP, Docker, Statistics",Master,8,Healthcare,2025-02-26,2025-04-20,1672,6.2,Quantum Computing Inc +AI14075,Deep Learning Engineer,102173,USD,102173,SE,PT,Ireland,S,Ireland,100,"Azure, Linux, Git, Java, TensorFlow",Associate,7,Automotive,2024-07-29,2024-09-13,795,8.7,Quantum Computing Inc +AI14076,Computer Vision Engineer,139906,GBP,104930,SE,FT,United Kingdom,S,United Kingdom,0,"Git, Data Visualization, AWS, Computer Vision",PhD,8,Transportation,2024-12-23,2025-02-17,1359,8.9,DeepTech Ventures +AI14077,AI Architect,161399,JPY,17753890,EX,PT,Japan,S,Japan,100,"PyTorch, R, Kubernetes",Associate,15,Transportation,2024-12-26,2025-02-07,945,8.9,Advanced Robotics +AI14078,Principal Data Scientist,104420,EUR,88757,SE,PT,Austria,S,Netherlands,50,"Data Visualization, Statistics, Tableau",PhD,9,Healthcare,2025-04-11,2025-04-30,624,7.7,Quantum Computing Inc +AI14079,AI Software Engineer,88018,EUR,74815,MI,FT,Austria,L,Austria,100,"Spark, GCP, Scala",Bachelor,4,Gaming,2024-08-17,2024-09-12,1130,5.3,Smart Analytics +AI14080,AI Consultant,65855,USD,65855,SE,PT,China,M,China,0,"Java, Linux, MLOps",Associate,6,Automotive,2024-10-08,2024-11-26,2119,8.8,Cognitive Computing +AI14081,AI Software Engineer,153926,JPY,16931860,SE,PT,Japan,L,Japan,0,"Java, GCP, Mathematics, Docker, Python",Bachelor,7,Gaming,2024-02-27,2024-03-31,1128,8.4,Cloud AI Solutions +AI14082,Autonomous Systems Engineer,133543,SGD,173606,MI,FT,Singapore,L,Singapore,0,"NLP, GCP, Azure, Scala, Statistics",Bachelor,3,Real Estate,2024-10-18,2024-12-25,653,7.3,Machine Intelligence Group +AI14083,Machine Learning Researcher,132804,USD,132804,SE,PT,United States,M,United States,50,"Linux, Python, SQL, NLP, Computer Vision",Master,8,Transportation,2024-11-19,2024-12-14,965,8.5,Cloud AI Solutions +AI14084,Head of AI,185999,SGD,241799,EX,FT,Singapore,M,Singapore,0,"Git, Python, Statistics",Associate,11,Consulting,2024-03-07,2024-05-07,1393,8.7,Quantum Computing Inc +AI14085,Data Scientist,160037,USD,160037,SE,FT,Denmark,M,Denmark,100,"Java, Spark, Computer Vision",Bachelor,5,Real Estate,2024-06-11,2024-07-20,2246,5.4,Algorithmic Solutions +AI14086,Data Scientist,71318,SGD,92713,MI,FT,Singapore,S,Singapore,50,"Spark, Linux, NLP, AWS",Master,2,Energy,2024-10-28,2024-11-21,1534,9.5,Cloud AI Solutions +AI14087,Data Analyst,210874,GBP,158156,EX,CT,United Kingdom,L,United Kingdom,100,"SQL, PyTorch, Azure, Scala, Java",Bachelor,14,Manufacturing,2024-05-18,2024-07-18,551,9.9,Quantum Computing Inc +AI14088,Head of AI,171409,EUR,145698,SE,FT,Netherlands,L,Netherlands,0,"Tableau, Git, Kubernetes, AWS, GCP",Bachelor,7,Gaming,2025-01-28,2025-03-20,2499,7,Advanced Robotics +AI14089,Deep Learning Engineer,41300,USD,41300,EN,FL,South Korea,S,Chile,100,"Scala, Hadoop, Data Visualization, Spark",Associate,0,Automotive,2024-02-10,2024-03-28,1754,8.5,DeepTech Ventures +AI14090,NLP Engineer,61734,USD,61734,SE,FT,China,M,China,50,"Kubernetes, Scala, AWS",Associate,6,Automotive,2024-12-19,2025-01-07,2073,7.4,Smart Analytics +AI14091,Machine Learning Engineer,171718,CAD,214648,EX,FL,Canada,L,Romania,0,"GCP, PyTorch, Statistics, Spark",PhD,19,Media,2024-03-27,2024-04-11,1548,6.2,Advanced Robotics +AI14092,Research Scientist,72603,JPY,7986330,EN,FT,Japan,S,Japan,100,"NLP, Kubernetes, Data Visualization",Master,1,Telecommunications,2024-02-27,2024-04-23,1185,8.5,TechCorp Inc +AI14093,AI Research Scientist,147559,SGD,191827,SE,FT,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization, MLOps, NLP",PhD,7,Telecommunications,2025-03-05,2025-04-17,2433,6.6,Advanced Robotics +AI14094,Principal Data Scientist,117163,JPY,12887930,MI,PT,Japan,L,Spain,50,"SQL, Python, Data Visualization",Bachelor,4,Gaming,2024-01-27,2024-02-15,2052,7.4,Quantum Computing Inc +AI14095,Research Scientist,112263,EUR,95424,MI,FL,Netherlands,M,Netherlands,0,"Hadoop, R, TensorFlow",PhD,2,Energy,2024-12-21,2025-02-02,2463,9.3,Cloud AI Solutions +AI14096,AI Software Engineer,29429,USD,29429,EN,FL,China,M,China,0,"GCP, R, Statistics, Spark",Bachelor,1,Gaming,2024-12-16,2025-01-21,1928,8.6,Cloud AI Solutions +AI14097,Head of AI,125096,USD,125096,MI,FL,United States,L,United States,50,"Tableau, Scala, Kubernetes",PhD,4,Healthcare,2025-04-16,2025-06-12,896,6.1,Digital Transformation LLC +AI14098,Autonomous Systems Engineer,290902,JPY,31999220,EX,FT,Japan,L,Japan,50,"Hadoop, Java, R, Kubernetes",Bachelor,12,Education,2024-06-04,2024-07-30,2175,5.4,Neural Networks Co +AI14099,Deep Learning Engineer,139674,USD,139674,SE,FL,Sweden,M,Egypt,100,"TensorFlow, PyTorch, Tableau, Statistics, Mathematics",PhD,8,Transportation,2024-05-19,2024-07-31,978,5.3,Digital Transformation LLC +AI14100,Data Engineer,112288,USD,112288,SE,FT,Ireland,S,Singapore,50,"Linux, Deep Learning, Kubernetes",PhD,7,Manufacturing,2024-12-20,2025-01-27,544,8.8,Machine Intelligence Group +AI14101,AI Specialist,55248,USD,55248,EX,CT,India,M,Mexico,50,"Tableau, Python, TensorFlow, AWS",PhD,16,Technology,2025-02-12,2025-03-02,1131,7,Smart Analytics +AI14102,Data Engineer,222488,USD,222488,SE,PT,Norway,L,Norway,0,"Scala, Computer Vision, Mathematics, R, NLP",Master,5,Technology,2025-02-12,2025-04-21,854,5.3,Quantum Computing Inc +AI14103,AI Software Engineer,186626,USD,186626,SE,PT,Norway,L,Denmark,100,"MLOps, SQL, Kubernetes",Associate,9,Education,2024-03-30,2024-05-07,1277,8.1,Quantum Computing Inc +AI14104,Deep Learning Engineer,262649,JPY,28891390,EX,FT,Japan,L,Japan,0,"Python, Kubernetes, Docker, TensorFlow",Master,17,Gaming,2024-10-01,2024-11-01,773,7.2,Machine Intelligence Group +AI14105,ML Ops Engineer,103455,USD,103455,MI,CT,United States,S,United States,50,"Azure, GCP, Statistics, MLOps, Python",Bachelor,3,Education,2024-07-06,2024-09-16,2487,6.3,DataVision Ltd +AI14106,Data Scientist,122416,USD,122416,MI,FL,Norway,M,Norway,0,"Kubernetes, Java, PyTorch, SQL, Spark",Bachelor,3,Education,2024-12-12,2025-01-02,1535,9.5,Autonomous Tech +AI14107,AI Product Manager,126398,SGD,164317,SE,FT,Singapore,L,Belgium,50,"GCP, Statistics, Hadoop, TensorFlow",Associate,9,Real Estate,2024-06-13,2024-07-11,2140,6.6,Machine Intelligence Group +AI14108,Deep Learning Engineer,104577,USD,104577,EN,PT,Denmark,L,Denmark,0,"SQL, Docker, Azure, R",Bachelor,0,Transportation,2025-02-06,2025-02-24,2202,8.4,Future Systems +AI14109,Machine Learning Researcher,222225,GBP,166669,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, PyTorch, Scala, Kubernetes",PhD,12,Automotive,2024-11-03,2025-01-11,2381,8.1,DataVision Ltd +AI14110,Head of AI,153799,EUR,130729,EX,CT,Netherlands,S,Netherlands,100,"AWS, Spark, Kubernetes, SQL, Linux",Associate,12,Consulting,2025-03-24,2025-05-08,508,7.2,Predictive Systems +AI14111,Machine Learning Engineer,77712,GBP,58284,EN,CT,United Kingdom,L,Hungary,0,"Python, Kubernetes, Computer Vision, Deep Learning, Tableau",Bachelor,1,Automotive,2024-01-31,2024-04-08,938,7.4,Cognitive Computing +AI14112,Data Analyst,68332,USD,68332,EN,CT,Finland,M,Indonesia,0,"Docker, PyTorch, Data Visualization, Linux, Git",Associate,1,Government,2024-03-11,2024-03-25,1373,9.4,Digital Transformation LLC +AI14113,AI Consultant,81904,USD,81904,SE,FT,China,L,China,50,"GCP, Git, Mathematics, Data Visualization",Master,7,Technology,2024-11-08,2024-11-26,832,8.5,Machine Intelligence Group +AI14114,ML Ops Engineer,67175,GBP,50381,EN,PT,United Kingdom,M,United Kingdom,50,"Python, Kubernetes, SQL",Associate,1,Gaming,2024-10-29,2024-12-24,2341,6.8,Machine Intelligence Group +AI14115,Computer Vision Engineer,71427,USD,71427,EN,PT,Finland,L,South Africa,0,"Azure, PyTorch, Tableau",PhD,0,Healthcare,2024-01-21,2024-03-15,1801,7.8,Cloud AI Solutions +AI14116,Principal Data Scientist,163454,AUD,220663,EX,PT,Australia,S,Thailand,50,"Python, GCP, NLP",PhD,10,Automotive,2024-03-24,2024-05-30,2143,9.6,Algorithmic Solutions +AI14117,Robotics Engineer,70727,EUR,60118,MI,FL,Germany,S,Germany,0,"Linux, Computer Vision, Tableau, Azure, Python",PhD,4,Manufacturing,2025-04-21,2025-06-28,1474,8.3,Cognitive Computing +AI14118,Machine Learning Researcher,136745,SGD,177769,EX,PT,Singapore,S,Singapore,0,"Scala, Hadoop, Python, TensorFlow",PhD,14,Telecommunications,2024-01-26,2024-03-28,1093,5.3,DeepTech Ventures +AI14119,Autonomous Systems Engineer,122312,USD,122312,SE,PT,United States,M,Canada,50,"SQL, Git, AWS, GCP",Master,8,Manufacturing,2024-02-11,2024-04-21,2457,9.7,Quantum Computing Inc +AI14120,ML Ops Engineer,88018,SGD,114423,EN,CT,Singapore,L,Singapore,50,"Mathematics, Deep Learning, Java, Python, AWS",PhD,1,Education,2024-08-14,2024-10-25,2109,8.2,Predictive Systems +AI14121,AI Architect,107618,EUR,91475,SE,FT,France,S,France,0,"SQL, PyTorch, Tableau, Hadoop, Azure",PhD,8,Healthcare,2024-08-30,2024-10-27,2427,5.6,Advanced Robotics +AI14122,NLP Engineer,82542,GBP,61907,EN,PT,United Kingdom,L,United Kingdom,50,"Linux, Java, Scala, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-02,954,5.8,Future Systems +AI14123,NLP Engineer,37476,USD,37476,EN,PT,China,L,China,50,"Java, PyTorch, TensorFlow, Deep Learning",Associate,1,Consulting,2024-08-13,2024-09-10,2224,9.9,DeepTech Ventures +AI14124,Principal Data Scientist,24095,USD,24095,EN,PT,India,M,India,100,"Kubernetes, PyTorch, TensorFlow, Mathematics",Master,1,Healthcare,2024-05-30,2024-07-16,2200,6.9,Cognitive Computing +AI14125,Research Scientist,295505,GBP,221629,EX,FL,United Kingdom,L,Italy,50,"Python, Deep Learning, Java, Azure, GCP",Bachelor,19,Automotive,2024-08-27,2024-09-17,1366,7,Autonomous Tech +AI14126,Deep Learning Engineer,85346,JPY,9388060,EN,PT,Japan,L,Japan,100,"Scala, Java, Python, MLOps, TensorFlow",Associate,1,Manufacturing,2024-09-14,2024-11-16,1248,8.7,DeepTech Ventures +AI14127,Principal Data Scientist,142448,USD,142448,SE,PT,Finland,L,Finland,50,"Kubernetes, SQL, AWS, Git",Bachelor,7,Consulting,2024-08-21,2024-09-18,559,7.9,Predictive Systems +AI14128,ML Ops Engineer,60149,USD,60149,EN,CT,Sweden,L,Sweden,100,"Azure, SQL, TensorFlow",Associate,1,Government,2024-08-19,2024-10-11,2102,6,Future Systems +AI14129,Principal Data Scientist,92230,USD,92230,MI,FL,Israel,M,Israel,100,"Azure, Python, Java, Computer Vision",PhD,3,Gaming,2024-11-15,2024-12-01,1355,5.7,Smart Analytics +AI14130,Data Engineer,93635,EUR,79590,SE,CT,Austria,S,Austria,100,"Scala, GCP, Hadoop, Statistics",Associate,9,Consulting,2024-11-01,2024-11-26,568,7.3,Advanced Robotics +AI14131,NLP Engineer,109810,GBP,82358,SE,FT,United Kingdom,M,United Kingdom,50,"Mathematics, AWS, NLP",Master,9,Transportation,2024-09-29,2024-10-15,1683,9.8,Algorithmic Solutions +AI14132,Data Scientist,268003,EUR,227803,EX,CT,Austria,L,Austria,0,"R, Hadoop, Scala",PhD,14,Media,2024-04-12,2024-06-15,1657,6.2,Quantum Computing Inc +AI14133,AI Consultant,241976,EUR,205680,EX,FT,France,L,France,100,"Kubernetes, SQL, NLP, Java, Hadoop",Master,11,Gaming,2025-02-01,2025-03-26,2290,6.1,Predictive Systems +AI14134,Data Scientist,60314,GBP,45236,EN,PT,United Kingdom,M,Ireland,50,"Kubernetes, Git, Computer Vision, Hadoop",Master,0,Telecommunications,2024-10-28,2024-12-16,2263,8.5,Cloud AI Solutions +AI14135,Autonomous Systems Engineer,34598,USD,34598,MI,FT,China,M,Russia,100,"Linux, Mathematics, Java",Bachelor,2,Consulting,2025-03-08,2025-04-17,1270,6.7,Quantum Computing Inc +AI14136,Data Analyst,174612,USD,174612,EX,CT,Israel,M,Israel,100,"R, Git, Scala, Python, Mathematics",Associate,17,Healthcare,2024-04-20,2024-06-14,1197,9.4,Neural Networks Co +AI14137,AI Research Scientist,119374,USD,119374,SE,CT,Denmark,S,India,50,"Java, R, Data Visualization, Azure",Master,9,Transportation,2024-09-25,2024-10-15,1604,6.3,Smart Analytics +AI14138,Research Scientist,121158,GBP,90869,SE,PT,United Kingdom,M,Kenya,0,"PyTorch, TensorFlow, Computer Vision, Azure, Git",PhD,9,Manufacturing,2025-03-19,2025-05-25,1718,8.2,AI Innovations +AI14139,Robotics Engineer,126193,USD,126193,SE,FL,Ireland,M,Kenya,50,"TensorFlow, Linux, Java",Bachelor,5,Consulting,2024-10-05,2024-11-22,530,9.7,Predictive Systems +AI14140,ML Ops Engineer,41111,USD,41111,MI,FT,China,M,China,100,"SQL, Java, Git, Kubernetes, PyTorch",PhD,2,Consulting,2024-01-17,2024-03-01,2487,9.7,DataVision Ltd +AI14141,Autonomous Systems Engineer,22562,USD,22562,EN,CT,India,S,India,0,"Tableau, TensorFlow, Kubernetes",Bachelor,0,Retail,2024-12-16,2025-01-11,1698,7.5,TechCorp Inc +AI14142,Data Scientist,219263,USD,219263,EX,FT,Sweden,S,Sweden,50,"Azure, Mathematics, Data Visualization, Git",Master,14,Manufacturing,2024-11-06,2024-12-18,1340,5.1,TechCorp Inc +AI14143,Data Analyst,96400,SGD,125320,MI,CT,Singapore,S,Singapore,0,"Tableau, Scala, Python, TensorFlow",Bachelor,4,Telecommunications,2024-12-06,2024-12-29,927,6,Autonomous Tech +AI14144,Autonomous Systems Engineer,128818,USD,128818,SE,PT,Ireland,M,Norway,0,"GCP, Data Visualization, Computer Vision",Master,7,Telecommunications,2024-02-07,2024-03-05,1702,7.8,Neural Networks Co +AI14145,NLP Engineer,216334,USD,216334,EX,PT,Israel,M,Israel,50,"PyTorch, SQL, MLOps, TensorFlow, AWS",Bachelor,12,Real Estate,2024-02-04,2024-02-19,1082,6.2,Quantum Computing Inc +AI14146,Machine Learning Researcher,94530,USD,94530,MI,FT,United States,S,United States,100,"Git, Docker, Data Visualization",Bachelor,2,Manufacturing,2025-04-23,2025-06-24,2094,6.1,AI Innovations +AI14147,Head of AI,89370,EUR,75965,MI,FL,Germany,M,Germany,0,"TensorFlow, Java, Mathematics",PhD,3,Retail,2024-11-14,2025-01-26,650,8.2,Cloud AI Solutions +AI14148,Data Engineer,127066,AUD,171539,SE,FL,Australia,M,Kenya,50,"Python, AWS, Scala, TensorFlow, Git",PhD,6,Transportation,2025-01-12,2025-03-13,1023,7.8,Cognitive Computing +AI14149,Principal Data Scientist,110035,EUR,93530,MI,FT,Netherlands,L,Netherlands,100,"SQL, Python, Scala",Associate,4,Automotive,2024-09-15,2024-11-14,1887,7.8,TechCorp Inc +AI14150,Machine Learning Researcher,139926,USD,139926,EX,FT,South Korea,M,South Korea,100,"PyTorch, Git, TensorFlow, R, Computer Vision",Master,12,Education,2024-01-04,2024-02-04,1739,6.9,Smart Analytics +AI14151,Machine Learning Engineer,77667,USD,77667,MI,FL,Finland,S,Finland,0,"Statistics, GCP, NLP",Associate,4,Gaming,2024-08-16,2024-10-20,1023,8.6,Algorithmic Solutions +AI14152,Deep Learning Engineer,178132,USD,178132,EX,FT,Finland,M,United States,50,"Linux, Data Visualization, Kubernetes, TensorFlow, Python",Associate,16,Finance,2024-01-04,2024-01-27,505,5.8,Autonomous Tech +AI14153,AI Research Scientist,86792,EUR,73773,MI,PT,Austria,S,Austria,0,"Data Visualization, PyTorch, Spark, Kubernetes",Associate,3,Telecommunications,2025-02-25,2025-04-13,1744,7.6,Advanced Robotics +AI14154,Autonomous Systems Engineer,316782,CHF,285104,EX,FT,Switzerland,L,Argentina,50,"MLOps, Linux, Java",Associate,16,Real Estate,2024-06-11,2024-08-12,579,5.9,Predictive Systems +AI14155,Machine Learning Engineer,96906,USD,96906,MI,FT,Ireland,L,Ireland,50,"Linux, GCP, Kubernetes, AWS",Master,4,Real Estate,2024-09-21,2024-11-23,2050,7.7,Predictive Systems +AI14156,Computer Vision Engineer,69233,SGD,90003,EN,PT,Singapore,M,Singapore,50,"Linux, Docker, Tableau",Master,0,Gaming,2024-02-26,2024-04-03,1093,6.5,Future Systems +AI14157,Data Engineer,108244,EUR,92007,SE,FT,Netherlands,S,Netherlands,50,"R, NLP, Azure",Bachelor,8,Telecommunications,2024-03-02,2024-03-29,1838,7.9,Digital Transformation LLC +AI14158,Deep Learning Engineer,93348,EUR,79346,MI,FT,Austria,L,Austria,100,"Linux, Java, Spark, Python",Bachelor,2,Finance,2024-03-20,2024-04-12,1098,8.3,Autonomous Tech +AI14159,AI Product Manager,79789,USD,79789,EN,CT,United States,M,India,0,"Spark, Linux, Tableau, Computer Vision",Associate,1,Healthcare,2024-07-17,2024-09-15,618,8.8,Cloud AI Solutions +AI14160,Machine Learning Engineer,69277,JPY,7620470,EN,PT,Japan,L,Hungary,100,"Kubernetes, Scala, Spark",Master,1,Automotive,2024-04-20,2024-06-03,1022,7,Predictive Systems +AI14161,AI Research Scientist,182548,USD,182548,EX,PT,Norway,S,Vietnam,0,"Python, GCP, MLOps, Scala, Hadoop",Master,17,Telecommunications,2024-08-07,2024-09-01,1375,5.5,Autonomous Tech +AI14162,Head of AI,80971,EUR,68825,MI,CT,Netherlands,S,Norway,100,"GCP, Mathematics, Azure, Linux, NLP",Associate,2,Automotive,2025-03-11,2025-04-24,554,9.9,Quantum Computing Inc +AI14163,Deep Learning Engineer,84774,USD,84774,EN,FT,Norway,S,Spain,0,"MLOps, Python, SQL, Statistics, Azure",PhD,1,Real Estate,2024-07-25,2024-09-06,1881,5.2,DataVision Ltd +AI14164,ML Ops Engineer,88260,EUR,75021,MI,PT,Austria,M,Austria,100,"Docker, Mathematics, Scala, Statistics, Linux",Master,3,Consulting,2024-06-15,2024-08-14,2124,8.7,Future Systems +AI14165,Research Scientist,105933,USD,105933,EN,FL,Norway,L,Norway,100,"Git, Mathematics, Data Visualization, AWS",PhD,0,Technology,2025-03-14,2025-05-15,2088,6.2,Algorithmic Solutions +AI14166,AI Product Manager,252207,USD,252207,EX,FT,Norway,M,Norway,0,"Kubernetes, Azure, MLOps, Computer Vision, NLP",Master,15,Automotive,2025-02-08,2025-02-22,1166,8.9,Algorithmic Solutions +AI14167,AI Consultant,24594,USD,24594,EN,PT,India,L,India,0,"Python, AWS, SQL",Master,0,Transportation,2024-05-11,2024-07-01,1973,8.1,AI Innovations +AI14168,Head of AI,133353,SGD,173359,MI,FT,Singapore,L,Singapore,50,"Mathematics, Computer Vision, NLP, Tableau, Python",Master,2,Media,2024-06-25,2024-07-29,1940,8.6,Machine Intelligence Group +AI14169,ML Ops Engineer,116932,USD,116932,SE,FT,Israel,M,Israel,100,"Tableau, TensorFlow, Computer Vision, Spark, Statistics",Bachelor,6,Gaming,2025-02-03,2025-03-05,898,6.2,Algorithmic Solutions +AI14170,AI Research Scientist,169884,USD,169884,EX,FL,South Korea,L,South Korea,0,"Kubernetes, R, Python",PhD,16,Technology,2024-07-12,2024-07-30,1070,7.1,Machine Intelligence Group +AI14171,AI Specialist,171722,JPY,18889420,EX,PT,Japan,M,Estonia,50,"Kubernetes, Git, Computer Vision, Deep Learning, Spark",Associate,12,Education,2024-02-26,2024-04-11,2486,9.9,Cloud AI Solutions +AI14172,AI Consultant,303831,USD,303831,EX,FL,Norway,M,Norway,0,"AWS, MLOps, R",Bachelor,18,Automotive,2025-03-30,2025-06-04,1522,8.3,Cognitive Computing +AI14173,NLP Engineer,28602,USD,28602,EN,FL,China,S,China,100,"Python, Spark, Docker",Associate,1,Gaming,2024-08-01,2024-09-28,1209,5.2,Autonomous Tech +AI14174,AI Specialist,267508,EUR,227382,EX,FL,Netherlands,M,Netherlands,100,"Kubernetes, Scala, Statistics, Azure, Tableau",Master,16,Retail,2025-03-05,2025-03-23,1209,9.6,Future Systems +AI14175,ML Ops Engineer,115925,EUR,98536,SE,FL,Austria,L,Russia,100,"Python, TensorFlow, Mathematics, PyTorch, Spark",Bachelor,8,Consulting,2024-02-12,2024-03-26,1614,9.3,Future Systems +AI14176,Data Analyst,80656,USD,80656,MI,PT,Finland,S,Kenya,100,"Python, Deep Learning, Azure, SQL, Git",PhD,2,Real Estate,2024-02-22,2024-04-10,1277,8.1,Future Systems +AI14177,Machine Learning Engineer,27562,USD,27562,EN,FL,India,M,India,0,"TensorFlow, Deep Learning, Tableau, Kubernetes",Master,1,Manufacturing,2024-07-29,2024-08-22,1304,6.8,Advanced Robotics +AI14178,Principal Data Scientist,192999,EUR,164049,EX,PT,Austria,S,Austria,50,"MLOps, NLP, Linux, TensorFlow",PhD,19,Gaming,2024-12-18,2025-02-07,701,8.5,Advanced Robotics +AI14179,AI Consultant,254016,JPY,27941760,EX,FT,Japan,M,Japan,0,"Python, Kubernetes, Mathematics, Deep Learning",Bachelor,17,Energy,2024-03-14,2024-05-22,1852,9.1,Future Systems +AI14180,Data Analyst,63794,EUR,54225,EN,FT,Austria,S,Austria,50,"PyTorch, R, NLP, Python",Master,1,Healthcare,2024-08-25,2024-10-24,1738,8.1,Autonomous Tech +AI14181,Machine Learning Engineer,82068,GBP,61551,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, PyTorch, Spark, Deep Learning, Computer Vision",PhD,1,Consulting,2024-09-09,2024-10-21,1023,6.7,Autonomous Tech +AI14182,AI Product Manager,68103,CAD,85129,EN,CT,Canada,S,Canada,50,"Data Visualization, Docker, Python, Computer Vision, Hadoop",Bachelor,1,Automotive,2024-01-07,2024-02-29,2000,6.3,DataVision Ltd +AI14183,NLP Engineer,108322,USD,108322,SE,FT,Israel,S,Israel,100,"Python, TensorFlow, MLOps",Associate,5,Government,2024-02-23,2024-04-06,1554,8.9,Predictive Systems +AI14184,Principal Data Scientist,80835,USD,80835,EN,FT,Norway,M,Norway,0,"Statistics, Scala, Linux",Bachelor,0,Automotive,2024-07-20,2024-08-17,1986,5.4,AI Innovations +AI14185,Head of AI,114660,USD,114660,SE,CT,Ireland,S,Ireland,50,"R, Git, Deep Learning, SQL",Associate,8,Automotive,2025-02-08,2025-03-25,2061,9.5,TechCorp Inc +AI14186,AI Consultant,106582,GBP,79937,MI,CT,United Kingdom,L,Ukraine,100,"Hadoop, Scala, Computer Vision, Python",Master,3,Consulting,2024-09-12,2024-11-02,2032,8.1,Digital Transformation LLC +AI14187,Machine Learning Engineer,96014,EUR,81612,MI,CT,Germany,S,Germany,50,"Scala, Java, TensorFlow, Statistics, Deep Learning",PhD,4,Media,2024-09-16,2024-11-02,1645,8.4,Predictive Systems +AI14188,Robotics Engineer,91689,USD,91689,MI,CT,Ireland,M,Ireland,100,"PyTorch, TensorFlow, Mathematics, Statistics",Master,3,Technology,2024-02-18,2024-04-18,996,7,Future Systems +AI14189,Machine Learning Researcher,64501,SGD,83851,EN,FT,Singapore,S,Singapore,0,"Linux, Deep Learning, PyTorch, Mathematics, NLP",PhD,1,Real Estate,2024-05-01,2024-06-12,1800,9.5,DataVision Ltd +AI14190,NLP Engineer,75701,CAD,94626,EN,PT,Canada,L,Canada,50,"AWS, Git, Statistics",PhD,0,Finance,2024-04-19,2024-05-03,1321,5.8,Neural Networks Co +AI14191,Head of AI,45437,USD,45437,EN,PT,Israel,S,Israel,50,"Git, Deep Learning, Kubernetes",PhD,0,Automotive,2025-04-27,2025-06-06,1697,6.6,Cloud AI Solutions +AI14192,Machine Learning Researcher,74737,USD,74737,EN,PT,Finland,M,Germany,0,"GCP, Java, R, Docker",PhD,0,Media,2024-05-13,2024-07-15,2338,9.9,DataVision Ltd +AI14193,Computer Vision Engineer,57174,USD,57174,EN,FL,Finland,L,Finland,0,"NLP, SQL, Java, AWS",Master,1,Retail,2024-05-01,2024-07-06,1347,6.9,Cloud AI Solutions +AI14194,Research Scientist,152694,USD,152694,EX,PT,Sweden,M,Sweden,0,"Data Visualization, AWS, Java, SQL",Associate,14,Healthcare,2024-03-28,2024-05-23,776,9.2,Algorithmic Solutions +AI14195,Head of AI,118599,EUR,100809,SE,PT,France,L,Philippines,100,"Kubernetes, Scala, Tableau, GCP, Data Visualization",Bachelor,9,Automotive,2024-10-30,2024-11-20,1006,5.2,TechCorp Inc +AI14196,Research Scientist,87706,CHF,78935,EN,FL,Switzerland,S,Switzerland,0,"Kubernetes, NLP, GCP, Linux, Computer Vision",Associate,0,Energy,2025-02-11,2025-03-29,1980,6,Quantum Computing Inc +AI14197,Machine Learning Researcher,88238,EUR,75002,MI,FT,France,M,France,0,"Azure, PyTorch, AWS, GCP",Associate,3,Telecommunications,2024-11-27,2024-12-19,1198,8.9,Future Systems +AI14198,AI Specialist,92582,USD,92582,SE,FT,South Korea,S,South Korea,0,"NLP, Statistics, Hadoop",PhD,5,Healthcare,2025-03-16,2025-04-14,1582,9.9,Algorithmic Solutions +AI14199,Data Analyst,38341,USD,38341,MI,FT,China,M,China,100,"Kubernetes, Python, Deep Learning, MLOps",Associate,3,Automotive,2024-10-29,2024-12-08,2212,7.7,Cloud AI Solutions +AI14200,AI Architect,40454,USD,40454,SE,FT,India,M,India,0,"R, Azure, Java",PhD,9,Automotive,2025-04-20,2025-06-07,1755,6.9,Future Systems +AI14201,Robotics Engineer,67022,SGD,87129,EN,CT,Singapore,M,Singapore,50,"SQL, Java, AWS",Master,1,Healthcare,2025-02-09,2025-03-16,1201,8.7,Quantum Computing Inc +AI14202,Research Scientist,46195,USD,46195,EN,CT,South Korea,S,Norway,50,"Python, Linux, Java, Docker",PhD,0,Real Estate,2024-01-31,2024-03-23,1062,9.5,Neural Networks Co +AI14203,Machine Learning Engineer,184717,USD,184717,EX,FT,Sweden,L,Sweden,100,"Java, R, SQL, Spark, Mathematics",Master,16,Consulting,2024-11-13,2024-12-11,1866,7.5,Predictive Systems +AI14204,Machine Learning Researcher,84313,SGD,109607,EN,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Linux, Azure",Bachelor,0,Government,2024-11-20,2025-01-22,1994,7.4,Machine Intelligence Group +AI14205,Research Scientist,171948,JPY,18914280,EX,PT,Japan,M,China,0,"GCP, Spark, Docker, NLP, PyTorch",Bachelor,17,Telecommunications,2024-08-12,2024-10-04,938,7.8,Quantum Computing Inc +AI14206,Data Scientist,65079,EUR,55317,EN,PT,Netherlands,L,Sweden,50,"Scala, SQL, PyTorch, Hadoop, Azure",Bachelor,0,Consulting,2025-03-01,2025-05-02,507,6.6,TechCorp Inc +AI14207,Machine Learning Researcher,257240,USD,257240,EX,CT,United States,S,United States,100,"PyTorch, MLOps, NLP, Python",Master,15,Media,2025-04-29,2025-06-28,2003,5.1,Algorithmic Solutions +AI14208,Deep Learning Engineer,71462,AUD,96474,EN,PT,Australia,M,Colombia,100,"SQL, Linux, Mathematics",PhD,0,Healthcare,2024-04-23,2024-05-26,859,8.6,Digital Transformation LLC +AI14209,NLP Engineer,123699,USD,123699,MI,PT,United States,M,Ghana,100,"Git, PyTorch, TensorFlow, Kubernetes",Bachelor,3,Retail,2024-06-19,2024-08-02,1773,5.6,Autonomous Tech +AI14210,AI Architect,72589,USD,72589,EN,FL,Finland,M,Finland,100,"Linux, Python, Hadoop, TensorFlow",Associate,1,Energy,2024-02-29,2024-05-01,596,7,Quantum Computing Inc +AI14211,Data Engineer,128822,AUD,173910,SE,PT,Australia,S,Australia,50,"Data Visualization, Python, Git",Master,5,Manufacturing,2025-03-12,2025-04-02,1922,9.9,Algorithmic Solutions +AI14212,AI Consultant,76617,USD,76617,EN,FL,Sweden,M,Sweden,0,"Mathematics, Linux, Computer Vision, PyTorch",Associate,1,Automotive,2024-08-12,2024-09-19,1012,5.6,TechCorp Inc +AI14213,AI Specialist,93353,USD,93353,EN,PT,Norway,S,Norway,100,"Linux, Kubernetes, Scala",Associate,0,Retail,2025-02-09,2025-04-04,537,5.6,Autonomous Tech +AI14214,Deep Learning Engineer,128582,CHF,115724,MI,FT,Switzerland,L,Switzerland,50,"GCP, Python, Mathematics",Master,4,Transportation,2024-03-02,2024-05-14,1475,8,Machine Intelligence Group +AI14215,Data Analyst,105420,USD,105420,SE,CT,Israel,S,Israel,50,"Python, Kubernetes, Deep Learning, AWS, R",Master,8,Energy,2024-10-22,2024-12-12,1192,8.9,AI Innovations +AI14216,AI Specialist,158281,JPY,17410910,SE,FL,Japan,L,Japan,0,"Linux, AWS, GCP, Mathematics, Docker",Bachelor,5,Real Estate,2024-06-21,2024-08-03,2371,5.4,Neural Networks Co +AI14217,Robotics Engineer,90700,USD,90700,EN,PT,United States,M,United States,50,"PyTorch, TensorFlow, Computer Vision",PhD,1,Energy,2024-03-06,2024-03-27,1800,8.6,Quantum Computing Inc +AI14218,NLP Engineer,163549,USD,163549,SE,FL,Israel,L,Israel,100,"Java, MLOps, GCP",Master,9,Technology,2024-07-16,2024-09-05,1715,6.7,Machine Intelligence Group +AI14219,AI Architect,91126,USD,91126,EN,FL,Denmark,M,Denmark,50,"GCP, Kubernetes, Linux, Computer Vision, Python",PhD,0,Transportation,2024-05-01,2024-05-21,1952,5.9,Cognitive Computing +AI14220,AI Specialist,197097,USD,197097,SE,FL,Norway,L,Norway,0,"Java, Hadoop, TensorFlow",Associate,5,Healthcare,2024-05-28,2024-06-12,2047,5.8,Future Systems +AI14221,AI Architect,130848,USD,130848,SE,PT,Ireland,S,Ireland,50,"Python, Mathematics, Computer Vision, NLP, TensorFlow",PhD,7,Education,2024-09-10,2024-11-02,1856,9.1,DataVision Ltd +AI14222,Machine Learning Engineer,115185,EUR,97907,SE,PT,France,L,Switzerland,100,"Data Visualization, Python, TensorFlow, PyTorch",Bachelor,7,Education,2025-03-14,2025-03-31,1921,9.2,DeepTech Ventures +AI14223,AI Specialist,74184,USD,74184,MI,FT,Finland,S,Philippines,50,"Hadoop, Linux, Git, SQL, Java",PhD,2,Education,2025-03-27,2025-06-05,1287,7.9,AI Innovations +AI14224,Machine Learning Engineer,85351,EUR,72548,EN,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, GCP, NLP, Git",Bachelor,1,Real Estate,2024-12-04,2024-12-22,761,8.2,DataVision Ltd +AI14225,Autonomous Systems Engineer,65593,USD,65593,EN,PT,United States,S,United States,50,"Computer Vision, Azure, Data Visualization",Master,1,Media,2024-09-12,2024-10-22,2483,6,Predictive Systems +AI14226,Robotics Engineer,123894,USD,123894,SE,CT,Ireland,S,Ireland,50,"Spark, Azure, Tableau, SQL, PyTorch",Master,6,Government,2024-02-12,2024-02-27,1054,5.9,DataVision Ltd +AI14227,AI Architect,152751,USD,152751,MI,PT,Denmark,L,Denmark,100,"Scala, Computer Vision, SQL, Git, PyTorch",PhD,2,Energy,2024-04-14,2024-05-04,1986,9.9,Cloud AI Solutions +AI14228,AI Software Engineer,94949,USD,94949,MI,CT,Norway,S,Norway,0,"Python, MLOps, Spark, Scala, TensorFlow",Associate,3,Gaming,2024-01-03,2024-01-18,1610,9.6,Neural Networks Co +AI14229,Machine Learning Researcher,199664,USD,199664,EX,FL,South Korea,L,South Korea,0,"Kubernetes, Python, Linux",Associate,18,Healthcare,2024-10-11,2024-11-15,538,6.3,Future Systems +AI14230,Research Scientist,51090,USD,51090,EN,PT,South Korea,L,South Korea,50,"Git, Scala, Kubernetes, Statistics",Master,1,Manufacturing,2024-06-29,2024-08-26,1607,7.1,Predictive Systems +AI14231,Head of AI,80797,EUR,68677,MI,FL,Germany,S,Germany,100,"PyTorch, Azure, Hadoop, Tableau",Associate,4,Telecommunications,2024-01-20,2024-03-22,1039,9.1,Cognitive Computing +AI14232,AI Product Manager,148078,EUR,125866,SE,PT,France,L,India,100,"Data Visualization, Tableau, Azure, Python, GCP",Associate,5,Government,2024-09-27,2024-11-01,1476,5,DataVision Ltd +AI14233,Research Scientist,241116,EUR,204949,EX,CT,Netherlands,L,Netherlands,50,"Hadoop, Python, Spark, Kubernetes",Bachelor,15,Technology,2024-12-27,2025-02-03,1545,9.9,Cloud AI Solutions +AI14234,AI Specialist,71525,CAD,89406,MI,FL,Canada,M,Canada,100,"GCP, Azure, R, Data Visualization",Bachelor,4,Transportation,2024-01-05,2024-03-13,852,8.8,Cognitive Computing +AI14235,Machine Learning Researcher,228052,USD,228052,EX,FL,Denmark,S,Denmark,0,"Hadoop, Python, Computer Vision, Git, Scala",Bachelor,13,Real Estate,2025-02-07,2025-04-06,1439,7,TechCorp Inc +AI14236,Deep Learning Engineer,92722,SGD,120539,MI,FL,Singapore,L,Singapore,100,"MLOps, Spark, Data Visualization",Bachelor,3,Consulting,2024-03-20,2024-05-18,1536,9.8,Future Systems +AI14237,Principal Data Scientist,177606,JPY,19536660,SE,FL,Japan,L,Japan,50,"Scala, Spark, PyTorch, TensorFlow",Master,5,Government,2024-04-05,2024-05-02,2385,7.5,DataVision Ltd +AI14238,Deep Learning Engineer,65911,USD,65911,EN,CT,South Korea,L,South Korea,50,"PyTorch, Tableau, TensorFlow",PhD,1,Energy,2024-02-19,2024-03-30,1306,9.3,Autonomous Tech +AI14239,Machine Learning Engineer,91391,GBP,68543,MI,FT,United Kingdom,S,Mexico,0,"Scala, Python, MLOps, Kubernetes, TensorFlow",Bachelor,2,Healthcare,2024-01-11,2024-02-05,1946,9.2,Algorithmic Solutions +AI14240,Machine Learning Researcher,201317,USD,201317,EX,FT,Israel,M,Israel,50,"Hadoop, PyTorch, R, Tableau",Master,17,Gaming,2024-08-13,2024-10-07,2364,6.2,Neural Networks Co +AI14241,AI Research Scientist,63528,EUR,53999,EN,FT,France,M,France,50,"Scala, Python, PyTorch",PhD,1,Gaming,2025-01-11,2025-03-08,1363,8.2,Smart Analytics +AI14242,AI Consultant,74903,EUR,63668,EN,PT,Austria,L,Austria,0,"Git, Tableau, Python",Master,1,Education,2024-02-15,2024-04-27,1458,9.9,Algorithmic Solutions +AI14243,Computer Vision Engineer,33431,USD,33431,EN,PT,China,S,Latvia,0,"SQL, Spark, PyTorch, Deep Learning, Git",Associate,0,Automotive,2024-04-14,2024-05-30,1801,8.1,DataVision Ltd +AI14244,AI Software Engineer,58058,AUD,78378,EN,PT,Australia,S,Australia,50,"Git, TensorFlow, Deep Learning, MLOps, Scala",Bachelor,1,Energy,2025-03-09,2025-04-04,2334,5,Neural Networks Co +AI14245,NLP Engineer,125186,USD,125186,SE,FL,Ireland,L,Colombia,100,"R, Java, TensorFlow, Computer Vision, Hadoop",PhD,5,Manufacturing,2024-11-02,2025-01-13,2404,5.2,Neural Networks Co +AI14246,AI Research Scientist,157137,USD,157137,SE,CT,Denmark,L,Singapore,100,"Computer Vision, Linux, SQL",Associate,7,Automotive,2024-03-14,2024-03-30,644,6,Quantum Computing Inc +AI14247,Data Scientist,32212,USD,32212,MI,PT,India,M,India,0,"Scala, PyTorch, Azure, Hadoop, Linux",Bachelor,3,Energy,2024-05-04,2024-06-08,2216,6.5,Future Systems +AI14248,Head of AI,96262,USD,96262,MI,CT,Finland,L,Romania,0,"Spark, SQL, Kubernetes, Git, AWS",Bachelor,2,Manufacturing,2025-04-19,2025-06-02,749,8.3,DeepTech Ventures +AI14249,AI Specialist,87709,USD,87709,SE,CT,South Korea,M,Vietnam,100,"PyTorch, Kubernetes, Hadoop, AWS, SQL",Associate,7,Media,2024-07-24,2024-08-10,1821,6.8,Predictive Systems +AI14250,Robotics Engineer,150226,JPY,16524860,EX,FL,Japan,M,Japan,100,"Git, NLP, Data Visualization",Master,17,Government,2024-02-05,2024-03-15,642,9.7,Algorithmic Solutions +AI14251,AI Product Manager,68640,USD,68640,EN,PT,South Korea,L,South Korea,100,"Spark, Python, Tableau, MLOps, TensorFlow",PhD,0,Technology,2024-01-03,2024-03-07,1794,8.8,TechCorp Inc +AI14252,Data Analyst,54111,EUR,45994,EN,PT,France,M,Germany,0,"GCP, Data Visualization, Java, Computer Vision",PhD,0,Energy,2025-03-16,2025-04-30,2028,6.2,AI Innovations +AI14253,Computer Vision Engineer,144317,SGD,187612,EX,FT,Singapore,S,Ghana,50,"GCP, Git, Kubernetes, AWS",Associate,15,Gaming,2024-08-07,2024-10-10,969,6.8,Smart Analytics +AI14254,Principal Data Scientist,136724,AUD,184577,SE,FL,Australia,L,Australia,50,"Linux, Data Visualization, Python, Scala",Associate,8,Gaming,2024-11-08,2024-12-07,1981,9.5,Cognitive Computing +AI14255,Robotics Engineer,100385,EUR,85327,MI,CT,Austria,L,Russia,50,"Docker, Python, MLOps, TensorFlow, SQL",Bachelor,4,Technology,2024-02-10,2024-04-12,811,6.8,Autonomous Tech +AI14256,AI Specialist,90275,EUR,76734,EN,PT,Germany,L,Italy,100,"Git, Linux, TensorFlow, R, Computer Vision",Bachelor,0,Education,2025-01-08,2025-03-22,1806,6,DataVision Ltd +AI14257,Principal Data Scientist,180652,EUR,153554,EX,PT,Netherlands,S,Poland,100,"Deep Learning, AWS, Data Visualization, TensorFlow",Master,17,Real Estate,2024-07-31,2024-09-30,2331,7.9,Neural Networks Co +AI14258,Research Scientist,51128,EUR,43459,EN,FT,Germany,M,Germany,0,"SQL, Kubernetes, MLOps, GCP, Azure",Bachelor,0,Government,2024-09-23,2024-11-20,1099,6.9,Digital Transformation LLC +AI14259,Computer Vision Engineer,129737,EUR,110276,SE,FL,Austria,L,Austria,50,"Scala, Git, Kubernetes, TensorFlow, Python",PhD,9,Healthcare,2025-01-09,2025-02-11,1980,8.9,Autonomous Tech +AI14260,Machine Learning Researcher,81423,SGD,105850,EN,CT,Singapore,L,Canada,100,"Python, Kubernetes, Deep Learning, Docker",Associate,1,Healthcare,2024-11-20,2025-01-16,2142,5.5,Autonomous Tech +AI14261,Data Engineer,171399,CHF,154259,MI,FL,Switzerland,L,Poland,0,"PyTorch, SQL, TensorFlow, Tableau, Computer Vision",Master,2,Energy,2024-08-30,2024-11-02,1386,7.1,Algorithmic Solutions +AI14262,Principal Data Scientist,299540,USD,299540,EX,CT,Norway,L,Norway,100,"Spark, Linux, Data Visualization, Scala, PyTorch",PhD,16,Media,2024-07-29,2024-09-12,971,6.9,Machine Intelligence Group +AI14263,ML Ops Engineer,23079,USD,23079,MI,FL,India,S,India,50,"TensorFlow, Tableau, PyTorch",Associate,2,Real Estate,2024-12-15,2025-01-01,1015,6.9,Predictive Systems +AI14264,AI Software Engineer,160236,USD,160236,MI,PT,Norway,L,Mexico,0,"Deep Learning, Git, Kubernetes, Azure, Java",Associate,2,Gaming,2024-08-23,2024-10-26,2377,6.8,Machine Intelligence Group +AI14265,Machine Learning Researcher,75808,USD,75808,EN,FT,Sweden,L,Sweden,100,"Tableau, MLOps, Kubernetes, Hadoop, Azure",Associate,1,Media,2024-03-28,2024-05-31,1175,8.2,Future Systems +AI14266,Machine Learning Engineer,109582,USD,109582,MI,PT,Finland,L,Russia,50,"Computer Vision, Python, Java, R",PhD,3,Consulting,2025-01-10,2025-02-28,1714,8.8,Smart Analytics +AI14267,Robotics Engineer,85941,CAD,107426,MI,PT,Canada,M,Canada,0,"Scala, R, Data Visualization, Linux",Associate,2,Automotive,2025-01-17,2025-02-16,1525,7.9,DeepTech Ventures +AI14268,Computer Vision Engineer,160982,SGD,209277,SE,CT,Singapore,L,Turkey,100,"SQL, Azure, Statistics",Associate,5,Healthcare,2025-04-10,2025-05-05,642,9.5,Cognitive Computing +AI14269,AI Specialist,111319,GBP,83489,SE,CT,United Kingdom,S,United Kingdom,0,"Java, Azure, AWS, Spark, TensorFlow",Bachelor,7,Healthcare,2024-12-20,2025-02-26,913,8.1,TechCorp Inc +AI14270,NLP Engineer,99974,EUR,84978,SE,FT,France,M,France,0,"Python, Computer Vision, Tableau, Scala, Azure",Master,9,Finance,2024-01-11,2024-03-02,1351,8.9,TechCorp Inc +AI14271,AI Research Scientist,103001,CAD,128751,MI,PT,Canada,M,Finland,50,"Java, Kubernetes, PyTorch",Bachelor,4,Retail,2024-12-17,2025-01-01,963,9.7,Neural Networks Co +AI14272,AI Software Engineer,207251,EUR,176163,EX,PT,Austria,S,United States,100,"PyTorch, Computer Vision, Python, TensorFlow",Master,11,Technology,2024-08-17,2024-10-18,1504,9.1,Cloud AI Solutions +AI14273,ML Ops Engineer,65060,USD,65060,EN,FT,Finland,L,Finland,0,"AWS, Data Visualization, Hadoop",Master,1,Media,2025-03-15,2025-04-09,1904,7.6,TechCorp Inc +AI14274,AI Consultant,90343,EUR,76792,MI,CT,Austria,M,Austria,50,"Python, TensorFlow, Git",Master,3,Gaming,2024-05-26,2024-07-10,1702,6.8,Neural Networks Co +AI14275,AI Specialist,99304,USD,99304,SE,PT,Israel,M,Poland,50,"PyTorch, Git, Kubernetes",Bachelor,7,Manufacturing,2025-03-15,2025-04-23,1905,6.7,Machine Intelligence Group +AI14276,Robotics Engineer,79942,USD,79942,EN,PT,Sweden,M,Sweden,50,"Computer Vision, SQL, Kubernetes, Docker",PhD,1,Education,2024-10-29,2025-01-07,1330,9.8,Smart Analytics +AI14277,Computer Vision Engineer,105304,GBP,78978,SE,PT,United Kingdom,S,United Kingdom,50,"Azure, Linux, Hadoop, Mathematics, Kubernetes",Associate,8,Manufacturing,2025-01-18,2025-02-23,619,8.7,Future Systems +AI14278,Data Engineer,118101,USD,118101,SE,FL,Finland,M,Denmark,50,"TensorFlow, Spark, Statistics, Linux, AWS",Associate,7,Gaming,2024-11-06,2025-01-06,1101,5,Cloud AI Solutions +AI14279,AI Product Manager,64827,USD,64827,SE,FL,China,L,China,0,"Scala, Python, MLOps, Hadoop",Master,8,Finance,2025-02-11,2025-03-16,855,9.2,Algorithmic Solutions +AI14280,Head of AI,136792,USD,136792,MI,FL,Norway,L,United Kingdom,0,"Hadoop, Azure, Statistics",Master,4,Education,2024-11-15,2025-01-23,2468,8.3,Smart Analytics +AI14281,Deep Learning Engineer,125716,EUR,106859,SE,FL,France,L,France,0,"SQL, Python, Java, NLP, Spark",PhD,8,Education,2024-12-05,2025-01-07,1744,7.8,Algorithmic Solutions +AI14282,ML Ops Engineer,74299,USD,74299,EN,CT,Sweden,M,Sweden,0,"Java, Python, NLP",PhD,0,Consulting,2024-02-26,2024-05-05,2071,9.9,Digital Transformation LLC +AI14283,Machine Learning Engineer,279034,USD,279034,EX,FL,United States,L,Egypt,0,"Computer Vision, GCP, MLOps, NLP",Associate,19,Consulting,2024-09-05,2024-10-30,1323,6.5,Digital Transformation LLC +AI14284,Data Scientist,84474,GBP,63356,EN,FL,United Kingdom,M,United Kingdom,0,"Spark, NLP, TensorFlow",Associate,1,Education,2024-01-08,2024-02-02,1232,5.6,Neural Networks Co +AI14285,NLP Engineer,105225,USD,105225,EX,FL,China,L,Mexico,0,"MLOps, Azure, Kubernetes, NLP",Bachelor,17,Media,2024-02-17,2024-04-30,2011,9.9,Algorithmic Solutions +AI14286,Machine Learning Researcher,140938,USD,140938,SE,PT,South Korea,L,Romania,0,"Docker, Linux, Hadoop, NLP, R",PhD,6,Healthcare,2025-03-26,2025-05-04,804,7.2,TechCorp Inc +AI14287,Autonomous Systems Engineer,51274,USD,51274,EN,FT,South Korea,L,South Korea,50,"GCP, Azure, AWS, Deep Learning, Mathematics",Master,1,Technology,2024-10-08,2024-11-14,1708,9.1,DeepTech Ventures +AI14288,Data Scientist,78815,JPY,8669650,MI,PT,Japan,S,Japan,100,"Computer Vision, Java, NLP, Mathematics, Linux",PhD,3,Telecommunications,2024-04-07,2024-05-18,2219,9.4,Cloud AI Solutions +AI14289,Robotics Engineer,62675,USD,62675,EN,PT,Israel,L,Israel,50,"MLOps, Git, GCP",Associate,1,Healthcare,2025-01-10,2025-02-13,767,5.8,DeepTech Ventures +AI14290,Head of AI,44043,USD,44043,SE,FL,India,S,India,50,"Kubernetes, Scala, GCP, Python",Master,8,Media,2025-02-10,2025-04-17,1249,9.5,DataVision Ltd +AI14291,Machine Learning Engineer,91908,GBP,68931,MI,PT,United Kingdom,S,United Kingdom,100,"Data Visualization, Kubernetes, GCP, Scala",PhD,2,Real Estate,2024-06-08,2024-07-23,1802,9.7,DataVision Ltd +AI14292,Machine Learning Researcher,161960,EUR,137666,EX,CT,Austria,M,Austria,0,"Docker, Java, MLOps",PhD,14,Telecommunications,2024-10-31,2024-11-15,633,9.2,Future Systems +AI14293,AI Product Manager,59982,USD,59982,EN,FL,Israel,S,Indonesia,0,"AWS, Kubernetes, SQL, GCP, Data Visualization",PhD,0,Energy,2024-11-03,2024-12-06,1024,5.5,Neural Networks Co +AI14294,Data Analyst,73332,USD,73332,MI,FT,Israel,S,Malaysia,100,"Data Visualization, Statistics, Spark, Tableau",Associate,3,Energy,2024-01-17,2024-03-26,1881,6.4,Advanced Robotics +AI14295,Machine Learning Engineer,235865,USD,235865,EX,FT,Israel,M,Israel,0,"Hadoop, Linux, Kubernetes",PhD,17,Telecommunications,2024-12-15,2025-02-16,1931,7.2,DeepTech Ventures +AI14296,Computer Vision Engineer,62646,EUR,53249,EN,CT,France,L,Japan,50,"Hadoop, Statistics, Git",Bachelor,0,Government,2024-05-03,2024-05-21,2160,8.5,Autonomous Tech +AI14297,ML Ops Engineer,81857,USD,81857,MI,PT,United States,S,Finland,0,"TensorFlow, Linux, Python, Hadoop",Associate,2,Government,2025-03-31,2025-05-26,2393,9.2,Quantum Computing Inc +AI14298,Computer Vision Engineer,98405,AUD,132847,MI,PT,Australia,S,Denmark,0,"PyTorch, Computer Vision, Kubernetes, GCP, AWS",Master,4,Telecommunications,2025-02-17,2025-03-20,2240,8,Cognitive Computing +AI14299,Principal Data Scientist,52393,USD,52393,EN,FL,Sweden,S,Thailand,0,"Python, Kubernetes, TensorFlow",PhD,0,Transportation,2024-10-06,2024-11-27,969,9.3,Neural Networks Co +AI14300,Computer Vision Engineer,51076,USD,51076,EN,FL,Ireland,S,Ireland,0,"PyTorch, Deep Learning, SQL, GCP",Associate,0,Retail,2025-03-16,2025-05-19,1948,5.6,Quantum Computing Inc +AI14301,Data Engineer,109859,CHF,98873,EN,FT,Switzerland,L,Switzerland,0,"Mathematics, Scala, Tableau",Bachelor,0,Energy,2024-07-10,2024-09-16,620,7.6,DataVision Ltd +AI14302,Machine Learning Researcher,140133,SGD,182173,SE,PT,Singapore,S,Poland,50,"Scala, Java, Docker",Master,9,Healthcare,2024-05-15,2024-06-10,1824,8.6,Autonomous Tech +AI14303,Head of AI,233979,USD,233979,EX,FT,United States,S,United States,50,"MLOps, R, GCP, Linux",Bachelor,19,Gaming,2024-08-06,2024-10-18,1936,7.7,Quantum Computing Inc +AI14304,AI Architect,61640,EUR,52394,EN,FL,France,S,France,100,"Java, PyTorch, Azure",Associate,1,Manufacturing,2025-01-26,2025-03-09,1512,7.2,Advanced Robotics +AI14305,NLP Engineer,162855,EUR,138427,SE,PT,Germany,L,Germany,100,"Python, Spark, TensorFlow, Statistics, Git",Master,8,Healthcare,2024-11-29,2025-01-24,1320,5.5,Quantum Computing Inc +AI14306,Autonomous Systems Engineer,102016,EUR,86714,MI,FT,Austria,L,Austria,0,"Azure, Git, Python, Linux",Bachelor,2,Consulting,2024-04-10,2024-05-10,1178,7.1,AI Innovations +AI14307,Data Scientist,65504,CAD,81880,EN,PT,Canada,L,Canada,100,"Docker, Data Visualization, Tableau, TensorFlow, Mathematics",Associate,0,Technology,2024-12-08,2025-02-10,678,5.2,Digital Transformation LLC +AI14308,AI Product Manager,75588,USD,75588,MI,FT,South Korea,S,South Korea,0,"GCP, R, NLP",Bachelor,4,Technology,2024-04-17,2024-05-28,1720,8,TechCorp Inc +AI14309,AI Architect,112458,CAD,140573,SE,FL,Canada,M,Canada,50,"Docker, Computer Vision, PyTorch",Associate,6,Education,2024-01-23,2024-03-11,1021,8.7,Cloud AI Solutions +AI14310,Computer Vision Engineer,124536,EUR,105856,EX,PT,Austria,S,Denmark,100,"TensorFlow, Deep Learning, Data Visualization, Computer Vision, Java",PhD,10,Media,2024-10-01,2024-11-07,550,9.6,Cognitive Computing +AI14311,Head of AI,175373,EUR,149067,EX,FL,Germany,L,Germany,50,"Statistics, PyTorch, Deep Learning",Master,17,Transportation,2024-07-03,2024-08-29,1193,10,Neural Networks Co +AI14312,AI Architect,116773,USD,116773,MI,CT,Ireland,L,Argentina,100,"Java, Hadoop, MLOps",PhD,3,Finance,2024-11-21,2024-12-26,502,6.2,Smart Analytics +AI14313,Machine Learning Engineer,81273,EUR,69082,EN,CT,Netherlands,M,Japan,0,"R, SQL, NLP, Git, GCP",Master,0,Media,2024-07-06,2024-08-16,862,9.9,Predictive Systems +AI14314,Machine Learning Engineer,90934,USD,90934,MI,PT,United States,S,United States,50,"Linux, GCP, Statistics, Deep Learning",Master,2,Manufacturing,2024-09-10,2024-10-19,2041,6.1,DataVision Ltd +AI14315,Computer Vision Engineer,141213,SGD,183577,SE,FL,Singapore,S,Philippines,100,"AWS, Python, Statistics, TensorFlow",PhD,9,Telecommunications,2024-07-23,2024-08-26,661,6.1,Cognitive Computing +AI14316,Head of AI,275394,SGD,358012,EX,FL,Singapore,L,Romania,100,"Python, Spark, Git, TensorFlow",Bachelor,18,Healthcare,2024-05-24,2024-07-29,874,6.6,Digital Transformation LLC +AI14317,Principal Data Scientist,107900,CAD,134875,SE,PT,Canada,S,Canada,0,"PyTorch, Azure, Spark",Bachelor,6,Government,2025-01-04,2025-01-19,1643,6,Future Systems +AI14318,Research Scientist,94985,JPY,10448350,EN,FT,Japan,L,Germany,100,"Python, Git, Deep Learning, PyTorch",PhD,1,Transportation,2024-03-03,2024-03-23,675,7.4,Autonomous Tech +AI14319,Computer Vision Engineer,123657,JPY,13602270,SE,FL,Japan,M,Italy,0,"Git, PyTorch, TensorFlow",PhD,8,Transportation,2024-06-07,2024-07-05,1062,8.8,Cloud AI Solutions +AI14320,AI Specialist,18446,USD,18446,EN,FL,India,S,India,100,"PyTorch, Scala, Git, NLP",Master,1,Transportation,2024-01-03,2024-02-01,2179,7.4,TechCorp Inc +AI14321,Robotics Engineer,125558,USD,125558,EX,FL,China,L,Romania,50,"Spark, MLOps, SQL, Hadoop",Bachelor,14,Technology,2024-04-09,2024-04-23,1998,7,DataVision Ltd +AI14322,Data Engineer,55209,EUR,46928,EN,FT,France,L,France,0,"Deep Learning, Kubernetes, Git, Statistics",Bachelor,1,Media,2024-12-14,2025-01-29,1887,6.6,Algorithmic Solutions +AI14323,AI Research Scientist,233676,EUR,198625,EX,FL,France,L,France,50,"SQL, Hadoop, PyTorch, Tableau",PhD,11,Manufacturing,2024-04-26,2024-07-01,2101,6.6,Cognitive Computing +AI14324,Principal Data Scientist,30081,USD,30081,MI,FT,India,L,India,0,"SQL, Git, Docker",PhD,2,Education,2024-09-03,2024-10-21,2325,5.8,Autonomous Tech +AI14325,Robotics Engineer,155252,EUR,131964,EX,CT,Austria,M,Austria,50,"Kubernetes, Hadoop, Spark, Docker, Git",Associate,11,Real Estate,2024-01-24,2024-03-31,1042,9.8,Predictive Systems +AI14326,Machine Learning Researcher,132368,CAD,165460,SE,FT,Canada,M,Canada,100,"SQL, Git, Data Visualization, Java, Spark",Master,7,Finance,2025-02-24,2025-04-04,1828,5.2,DeepTech Ventures +AI14327,Computer Vision Engineer,84373,USD,84373,MI,CT,South Korea,M,South Korea,0,"SQL, Computer Vision, Kubernetes, MLOps, Python",PhD,2,Telecommunications,2024-07-26,2024-10-07,2348,6.8,Digital Transformation LLC +AI14328,AI Architect,264528,USD,264528,EX,CT,Denmark,M,Denmark,100,"GCP, Linux, Computer Vision",Associate,11,Gaming,2024-09-15,2024-11-27,2001,7.5,AI Innovations +AI14329,Data Engineer,29715,USD,29715,EN,CT,India,L,India,0,"Mathematics, Scala, Python, AWS, Data Visualization",PhD,0,Automotive,2025-04-06,2025-06-07,2490,9.3,Advanced Robotics +AI14330,AI Specialist,164165,EUR,139540,SE,CT,Germany,L,Germany,50,"Java, MLOps, Linux, Deep Learning",Bachelor,9,Consulting,2024-01-14,2024-02-05,1341,9.4,TechCorp Inc +AI14331,Research Scientist,223621,USD,223621,EX,FL,Denmark,L,Czech Republic,0,"Scala, Tableau, Kubernetes, R",PhD,11,Manufacturing,2024-12-14,2025-02-06,705,6,Neural Networks Co +AI14332,AI Architect,226374,SGD,294286,EX,FL,Singapore,S,Singapore,100,"Kubernetes, Python, Data Visualization",Bachelor,16,Finance,2024-01-11,2024-03-22,1812,8.8,AI Innovations +AI14333,Machine Learning Engineer,76615,USD,76615,EN,FT,Sweden,M,Norway,50,"Scala, Tableau, R, Azure, Linux",Master,0,Gaming,2024-08-01,2024-08-20,1375,5.9,Algorithmic Solutions +AI14334,AI Consultant,85551,CHF,76996,EN,PT,Switzerland,L,Switzerland,100,"PyTorch, Linux, TensorFlow",Master,0,Telecommunications,2024-12-19,2025-01-18,2033,8.9,TechCorp Inc +AI14335,AI Consultant,156675,GBP,117506,EX,FT,United Kingdom,M,France,50,"Hadoop, Scala, Linux, Computer Vision",Master,18,Finance,2024-09-03,2024-10-07,1584,9,Predictive Systems +AI14336,Principal Data Scientist,55271,EUR,46980,EN,FL,France,M,France,50,"Git, TensorFlow, PyTorch, Scala",Bachelor,0,Finance,2024-05-15,2024-06-11,1717,8.4,Cloud AI Solutions +AI14337,AI Software Engineer,166389,USD,166389,EX,FL,Finland,M,Ghana,50,"R, Python, Hadoop",Bachelor,12,Retail,2025-03-11,2025-04-15,2042,7.1,Predictive Systems +AI14338,NLP Engineer,82549,SGD,107314,EN,FL,Singapore,L,United States,0,"MLOps, Azure, Kubernetes, Tableau, Docker",Master,1,Consulting,2025-01-21,2025-03-24,1901,6.8,Smart Analytics +AI14339,Principal Data Scientist,76753,GBP,57565,EN,CT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, PyTorch",Master,1,Real Estate,2024-02-20,2024-04-02,975,9.2,Neural Networks Co +AI14340,AI Research Scientist,73157,EUR,62183,MI,PT,Netherlands,S,Netherlands,50,"Scala, SQL, Data Visualization, GCP, PyTorch",PhD,4,Finance,2025-01-21,2025-03-29,678,8,Cognitive Computing +AI14341,Data Analyst,116897,USD,116897,SE,FL,South Korea,M,Belgium,100,"PyTorch, TensorFlow, Git, GCP, Linux",PhD,6,Retail,2024-11-19,2025-01-26,1136,6.6,Future Systems +AI14342,AI Software Engineer,130794,USD,130794,SE,FL,Finland,L,Vietnam,0,"Python, AWS, Statistics, Computer Vision",PhD,9,Media,2024-08-25,2024-10-23,1247,8.4,DataVision Ltd +AI14343,Deep Learning Engineer,102032,JPY,11223520,MI,FL,Japan,M,Japan,100,"Kubernetes, Computer Vision, AWS, Azure",Associate,4,Healthcare,2025-01-30,2025-03-25,2399,8.4,AI Innovations +AI14344,AI Product Manager,142857,EUR,121428,SE,FT,Austria,L,South Africa,50,"SQL, Python, AWS, Java, TensorFlow",PhD,7,Consulting,2024-03-29,2024-05-11,2479,9.5,Cognitive Computing +AI14345,AI Research Scientist,187842,SGD,244195,EX,PT,Singapore,M,Singapore,50,"Hadoop, TensorFlow, Computer Vision, MLOps",PhD,14,Media,2025-01-24,2025-02-10,1075,7.9,Neural Networks Co +AI14346,AI Research Scientist,157194,SGD,204352,EX,FL,Singapore,S,Poland,100,"Python, Java, SQL",Bachelor,17,Automotive,2025-01-20,2025-02-05,2120,5.7,Cloud AI Solutions +AI14347,Deep Learning Engineer,104641,EUR,88945,MI,CT,Netherlands,S,Belgium,0,"SQL, Git, Kubernetes",Master,4,Transportation,2025-03-17,2025-04-25,2022,9.4,Advanced Robotics +AI14348,Machine Learning Engineer,70047,USD,70047,EN,CT,United States,S,Indonesia,100,"Deep Learning, Scala, AWS",Master,1,Manufacturing,2024-07-12,2024-08-14,1560,6.3,Algorithmic Solutions +AI14349,AI Consultant,174437,USD,174437,SE,CT,Norway,S,Egypt,0,"AWS, Docker, SQL, Git, Scala",Associate,5,Energy,2024-02-12,2024-04-05,1526,8.2,Algorithmic Solutions +AI14350,Head of AI,291903,AUD,394069,EX,FT,Australia,L,Australia,50,"Statistics, Scala, Deep Learning, Data Visualization, Mathematics",Bachelor,17,Government,2024-10-26,2024-11-10,2021,8.3,Machine Intelligence Group +AI14351,Data Engineer,257612,USD,257612,EX,CT,United States,S,Japan,50,"R, Deep Learning, Azure",Associate,19,Telecommunications,2024-04-01,2024-05-13,1277,9.2,Cloud AI Solutions +AI14352,ML Ops Engineer,138666,USD,138666,MI,FT,Norway,M,India,50,"Linux, Data Visualization, TensorFlow, Mathematics",Master,2,Telecommunications,2024-12-07,2025-02-04,1782,6.3,Cognitive Computing +AI14353,Autonomous Systems Engineer,139390,SGD,181207,SE,PT,Singapore,M,Singapore,50,"Python, TensorFlow, PyTorch, Azure, Linux",PhD,9,Retail,2025-01-21,2025-04-03,2156,9,Cloud AI Solutions +AI14354,Data Engineer,137009,EUR,116458,SE,CT,Austria,L,Austria,100,"Java, Spark, Computer Vision",Associate,9,Gaming,2024-03-21,2024-04-25,1105,9.6,Advanced Robotics +AI14355,AI Architect,154759,USD,154759,EX,FL,Ireland,M,Ireland,100,"SQL, PyTorch, GCP",Bachelor,17,Automotive,2024-04-06,2024-05-03,1786,7.4,Cognitive Computing +AI14356,Data Engineer,132746,SGD,172570,SE,CT,Singapore,M,Sweden,100,"Python, NLP, TensorFlow, PyTorch, Git",PhD,6,Technology,2024-02-14,2024-03-01,2443,7.7,Neural Networks Co +AI14357,Data Engineer,100856,GBP,75642,MI,FT,United Kingdom,L,United Kingdom,100,"SQL, Kubernetes, Deep Learning, Python",PhD,3,Government,2024-02-16,2024-04-09,763,8,AI Innovations +AI14358,Machine Learning Engineer,49761,GBP,37321,EN,FL,United Kingdom,S,Romania,50,"R, Tableau, SQL",Master,0,Education,2024-02-02,2024-02-23,1476,5.9,DeepTech Ventures +AI14359,Research Scientist,77665,GBP,58249,EN,CT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning, Hadoop",PhD,0,Education,2024-01-08,2024-02-20,654,7.7,Digital Transformation LLC +AI14360,Data Scientist,71610,USD,71610,EN,FT,Ireland,L,Italy,0,"Spark, AWS, SQL",PhD,0,Finance,2024-09-20,2024-10-13,1560,5.9,Cloud AI Solutions +AI14361,Head of AI,57686,CAD,72108,EN,FT,Canada,M,Canada,100,"Git, Mathematics, SQL, TensorFlow, Computer Vision",Master,1,Energy,2024-06-11,2024-08-06,2351,8.3,Smart Analytics +AI14362,Machine Learning Researcher,131219,EUR,111536,SE,CT,Netherlands,M,Netherlands,50,"Docker, PyTorch, Azure, Hadoop, TensorFlow",Master,6,Transportation,2024-06-12,2024-07-12,1918,7.8,Cognitive Computing +AI14363,Robotics Engineer,104036,AUD,140449,MI,FT,Australia,M,Australia,100,"Kubernetes, Computer Vision, NLP",Bachelor,3,Media,2024-12-11,2025-02-06,1735,7.2,Smart Analytics +AI14364,NLP Engineer,154548,USD,154548,EX,FT,Finland,L,India,50,"PyTorch, TensorFlow, Java",Master,18,Retail,2024-02-04,2024-03-05,1766,8.9,Autonomous Tech +AI14365,ML Ops Engineer,189083,USD,189083,EX,PT,Sweden,L,Sweden,50,"SQL, Linux, Statistics, Hadoop",PhD,19,Healthcare,2024-10-27,2024-11-11,1412,7.5,TechCorp Inc +AI14366,Head of AI,107559,USD,107559,SE,PT,Sweden,S,Sweden,0,"Azure, Kubernetes, Mathematics, Docker",Associate,6,Energy,2024-03-13,2024-05-05,1206,8.8,Quantum Computing Inc +AI14367,Machine Learning Engineer,197070,CAD,246338,EX,FT,Canada,S,Canada,100,"PyTorch, Hadoop, Python, Git",Bachelor,10,Government,2024-07-20,2024-09-10,1688,10,Digital Transformation LLC +AI14368,Data Analyst,158181,CAD,197726,SE,PT,Canada,L,Egypt,0,"Linux, R, MLOps",Bachelor,8,Telecommunications,2024-04-26,2024-06-18,799,6.6,Cloud AI Solutions +AI14369,Data Analyst,118102,EUR,100387,SE,FL,France,S,France,100,"R, Mathematics, Scala, Statistics",Bachelor,9,Healthcare,2024-04-13,2024-05-05,1809,6.9,AI Innovations +AI14370,Data Engineer,112990,USD,112990,MI,CT,Norway,S,Norway,0,"Linux, Java, PyTorch, Git, MLOps",Master,4,Transportation,2025-04-02,2025-04-26,2482,6.6,AI Innovations +AI14371,ML Ops Engineer,147657,JPY,16242270,EX,PT,Japan,M,Japan,50,"Spark, MLOps, Azure, SQL, Docker",Master,11,Education,2024-05-16,2024-06-25,1666,5.6,Machine Intelligence Group +AI14372,Machine Learning Engineer,145533,EUR,123703,SE,PT,Netherlands,M,China,100,"Python, TensorFlow, Docker",Associate,6,Education,2024-01-10,2024-02-28,730,7.6,Cognitive Computing +AI14373,Data Scientist,128282,USD,128282,MI,CT,Denmark,M,Russia,0,"Python, Scala, SQL",Bachelor,2,Retail,2024-10-04,2024-10-24,1809,8.2,DataVision Ltd +AI14374,Principal Data Scientist,118956,EUR,101113,SE,PT,Germany,L,Germany,50,"NLP, Deep Learning, Kubernetes",PhD,9,Consulting,2024-12-07,2024-12-30,1671,7.2,Future Systems +AI14375,AI Consultant,64457,USD,64457,EX,FT,China,M,China,50,"R, Python, Linux, Docker, MLOps",Bachelor,12,Finance,2024-08-06,2024-09-15,2061,6.6,DeepTech Ventures +AI14376,ML Ops Engineer,75849,EUR,64472,EN,CT,Netherlands,M,Netherlands,100,"Data Visualization, TensorFlow, Deep Learning, Tableau, Hadoop",Master,0,Automotive,2024-03-01,2024-03-23,1079,5.1,Neural Networks Co +AI14377,Data Engineer,137657,USD,137657,EX,FT,China,L,New Zealand,0,"Docker, Data Visualization, Tableau, R",Bachelor,18,Media,2024-10-31,2024-12-05,1668,7.7,Predictive Systems +AI14378,Robotics Engineer,144216,USD,144216,SE,PT,Sweden,M,Sweden,0,"Git, GCP, Tableau, PyTorch, Java",Bachelor,6,Consulting,2024-11-17,2025-01-07,2242,7.7,Cognitive Computing +AI14379,AI Consultant,113094,SGD,147022,SE,PT,Singapore,M,Singapore,0,"NLP, Kubernetes, GCP",Bachelor,5,Gaming,2024-07-30,2024-10-11,2205,5.1,Future Systems +AI14380,Data Engineer,138816,GBP,104112,SE,FT,United Kingdom,S,United Kingdom,100,"Data Visualization, R, Python",Bachelor,7,Gaming,2024-12-11,2025-02-10,1227,9.5,Cloud AI Solutions +AI14381,AI Research Scientist,105524,EUR,89695,SE,FT,France,S,France,50,"Python, Data Visualization, GCP, Mathematics",Bachelor,5,Telecommunications,2024-06-11,2024-08-17,1248,6.9,Future Systems +AI14382,Machine Learning Engineer,235370,JPY,25890700,EX,CT,Japan,L,Estonia,50,"Python, Azure, SQL, Spark, AWS",Master,19,Automotive,2024-02-07,2024-03-18,960,8.3,DataVision Ltd +AI14383,Machine Learning Engineer,53545,USD,53545,EN,FT,Finland,M,Finland,0,"Docker, Linux, Computer Vision",Master,0,Retail,2025-01-24,2025-03-25,520,9.6,Quantum Computing Inc +AI14384,Principal Data Scientist,246044,AUD,332159,EX,FL,Australia,L,Australia,50,"Statistics, R, Kubernetes, PyTorch",Master,10,Transportation,2024-04-06,2024-05-07,1758,5.3,TechCorp Inc +AI14385,Machine Learning Engineer,79749,EUR,67787,MI,FL,Austria,S,Austria,100,"Deep Learning, Data Visualization, Java, Tableau",Bachelor,3,Healthcare,2025-04-16,2025-06-05,2163,7.1,Digital Transformation LLC +AI14386,AI Product Manager,45513,USD,45513,MI,FL,China,S,China,50,"GCP, Spark, PyTorch, MLOps",PhD,2,Education,2024-11-09,2024-12-03,1131,9.9,Machine Intelligence Group +AI14387,ML Ops Engineer,147346,SGD,191550,SE,FT,Singapore,L,Singapore,50,"Kubernetes, Azure, Linux, Statistics, Spark",Associate,8,Telecommunications,2024-04-09,2024-05-03,1332,9.2,Advanced Robotics +AI14388,Autonomous Systems Engineer,96801,EUR,82281,MI,FL,Austria,M,Romania,50,"Statistics, PyTorch, Azure, Spark",Master,4,Government,2024-03-22,2024-05-26,616,7.2,Cognitive Computing +AI14389,Data Scientist,112083,USD,112083,MI,CT,Ireland,L,Ireland,50,"Tableau, SQL, Kubernetes, PyTorch",Bachelor,3,Transportation,2024-07-26,2024-09-25,1774,5.2,Advanced Robotics +AI14390,Computer Vision Engineer,119874,AUD,161830,MI,PT,Australia,L,Australia,50,"Git, PyTorch, Tableau, AWS",Bachelor,2,Healthcare,2025-04-12,2025-05-20,681,5.9,Advanced Robotics +AI14391,AI Product Manager,37440,USD,37440,SE,FT,India,M,India,0,"SQL, PyTorch, R, Statistics",Bachelor,5,Consulting,2024-07-03,2024-08-02,1668,8.8,Cognitive Computing +AI14392,AI Software Engineer,156018,USD,156018,SE,PT,United States,S,United States,100,"Spark, TensorFlow, Computer Vision",Master,7,Education,2024-01-01,2024-02-28,1438,8.6,Future Systems +AI14393,AI Architect,77323,USD,77323,MI,FT,Finland,S,Finland,100,"MLOps, AWS, GCP, Spark, Tableau",Master,3,Consulting,2024-03-05,2024-04-12,2405,7,Predictive Systems +AI14394,Machine Learning Researcher,157671,USD,157671,EX,PT,South Korea,S,South Korea,0,"GCP, R, Kubernetes",Master,11,Real Estate,2024-10-13,2024-11-17,1026,7.5,Digital Transformation LLC +AI14395,Deep Learning Engineer,107434,SGD,139664,MI,FT,Singapore,M,Singapore,50,"Hadoop, Docker, AWS, PyTorch",PhD,3,Energy,2024-07-25,2024-09-19,2130,7.5,Cloud AI Solutions +AI14396,Robotics Engineer,69805,EUR,59334,MI,FT,France,M,France,50,"SQL, Data Visualization, Azure, Spark",PhD,2,Media,2024-10-02,2024-10-16,1607,9.8,Advanced Robotics +AI14397,AI Research Scientist,80668,EUR,68568,MI,FL,Austria,L,Austria,100,"Hadoop, Tableau, SQL, NLP",PhD,4,Consulting,2025-02-06,2025-04-05,594,6,Digital Transformation LLC +AI14398,Head of AI,140967,EUR,119822,EX,FT,Germany,M,Philippines,100,"Data Visualization, R, SQL",Master,11,Finance,2024-04-10,2024-04-29,1541,6.4,Algorithmic Solutions +AI14399,Principal Data Scientist,112216,USD,112216,SE,PT,Sweden,M,Belgium,0,"Python, TensorFlow, Docker",Master,7,Real Estate,2024-08-12,2024-09-20,1853,7.9,TechCorp Inc +AI14400,Autonomous Systems Engineer,210828,JPY,23191080,EX,PT,Japan,S,Japan,50,"SQL, Python, R",Bachelor,19,Healthcare,2025-04-16,2025-06-28,2384,6.5,TechCorp Inc +AI14401,Principal Data Scientist,44332,USD,44332,SE,FL,India,S,India,0,"Git, MLOps, Tableau, Kubernetes, Computer Vision",Master,9,Manufacturing,2024-08-28,2024-09-21,942,9.8,AI Innovations +AI14402,Data Engineer,68896,EUR,58562,EN,FL,France,M,France,50,"Computer Vision, SQL, Kubernetes, Linux",Bachelor,1,Education,2024-09-01,2024-11-04,847,8,Future Systems +AI14403,Data Scientist,165554,CHF,148999,MI,FL,Switzerland,L,Netherlands,50,"SQL, Kubernetes, MLOps, Hadoop",Bachelor,4,Consulting,2024-06-05,2024-06-19,1740,8.3,Digital Transformation LLC +AI14404,AI Architect,114670,USD,114670,MI,PT,Denmark,S,Denmark,100,"Python, TensorFlow, MLOps, Docker",PhD,4,Government,2024-05-19,2024-06-09,1820,9.2,Algorithmic Solutions +AI14405,Data Analyst,97405,JPY,10714550,EN,PT,Japan,L,Ireland,50,"Spark, Linux, Data Visualization, Git",Master,1,Energy,2024-05-02,2024-06-27,2381,7.8,DataVision Ltd +AI14406,AI Specialist,92003,EUR,78203,SE,PT,France,S,Hungary,0,"SQL, Linux, Scala, Docker, Kubernetes",Master,8,Consulting,2024-07-03,2024-07-28,1265,6.2,Digital Transformation LLC +AI14407,Principal Data Scientist,85732,USD,85732,EN,FT,Denmark,S,Denmark,0,"Scala, Computer Vision, R, SQL",Master,0,Healthcare,2024-07-01,2024-08-01,2168,9,DataVision Ltd +AI14408,Data Analyst,158515,EUR,134738,EX,FT,Netherlands,M,Netherlands,50,"Java, Spark, Data Visualization, MLOps, Mathematics",PhD,16,Consulting,2024-08-10,2024-09-21,1073,8.2,Predictive Systems +AI14409,AI Specialist,119601,USD,119601,SE,CT,Sweden,M,Sweden,50,"Python, Hadoop, Data Visualization, Docker, Computer Vision",Associate,9,Consulting,2025-03-05,2025-05-04,1855,5.6,Machine Intelligence Group +AI14410,NLP Engineer,72330,EUR,61481,EN,PT,France,M,France,0,"Computer Vision, GCP, Docker",Bachelor,0,Transportation,2024-02-22,2024-04-01,1518,5.4,Machine Intelligence Group +AI14411,AI Specialist,109208,GBP,81906,SE,PT,United Kingdom,M,United Kingdom,100,"Tableau, Git, GCP, PyTorch",PhD,7,Energy,2024-02-01,2024-02-26,1993,7,Predictive Systems +AI14412,Computer Vision Engineer,59992,USD,59992,EX,PT,India,M,Turkey,100,"NLP, PyTorch, AWS, GCP, Java",Master,11,Consulting,2025-03-26,2025-05-29,901,8,Cognitive Computing +AI14413,Data Scientist,81724,USD,81724,EN,FL,Sweden,L,Sweden,0,"Java, Hadoop, Azure, Computer Vision, Git",PhD,1,Manufacturing,2024-05-20,2024-07-27,1347,8.9,TechCorp Inc +AI14414,Autonomous Systems Engineer,152556,USD,152556,SE,PT,Norway,S,Norway,0,"Deep Learning, SQL, Computer Vision, Scala, Azure",Master,5,Automotive,2025-02-27,2025-03-17,563,5.3,Advanced Robotics +AI14415,AI Consultant,93627,SGD,121715,MI,CT,Singapore,M,Singapore,50,"Data Visualization, TensorFlow, Scala",Bachelor,2,Media,2024-12-22,2025-01-18,2345,6.4,Predictive Systems +AI14416,AI Consultant,368934,USD,368934,EX,PT,Norway,L,Norway,0,"TensorFlow, Azure, PyTorch, Tableau, Python",Associate,12,Energy,2024-11-07,2025-01-03,594,8.8,Smart Analytics +AI14417,ML Ops Engineer,62871,USD,62871,EN,FT,Ireland,M,Thailand,100,"AWS, SQL, Python",Master,1,Media,2025-04-02,2025-04-24,2391,6.5,Machine Intelligence Group +AI14418,AI Software Engineer,163945,SGD,213129,EX,FT,Singapore,M,Germany,100,"GCP, Data Visualization, AWS",Associate,13,Technology,2024-01-10,2024-03-02,2184,8.1,Predictive Systems +AI14419,AI Software Engineer,282346,CHF,254111,EX,PT,Switzerland,S,Ireland,0,"Scala, TensorFlow, AWS, R",Bachelor,18,Finance,2025-02-06,2025-04-10,949,7.3,Neural Networks Co +AI14420,AI Architect,198337,USD,198337,EX,FT,Finland,L,Israel,100,"Kubernetes, Azure, Statistics, Git",Bachelor,17,Real Estate,2024-03-03,2024-03-25,2005,6.5,AI Innovations +AI14421,Data Analyst,75384,USD,75384,SE,FT,China,L,Turkey,50,"Kubernetes, Linux, Data Visualization",Master,9,Consulting,2024-10-06,2024-11-05,1413,9.4,Cloud AI Solutions +AI14422,NLP Engineer,209294,EUR,177900,EX,PT,Germany,M,Germany,100,"R, Python, AWS",Master,17,Energy,2024-10-27,2024-11-25,1635,8.9,Neural Networks Co +AI14423,Robotics Engineer,61021,USD,61021,EN,PT,Israel,M,Israel,100,"Tableau, Azure, Spark, Java",PhD,1,Telecommunications,2025-03-09,2025-04-03,715,6.4,Neural Networks Co +AI14424,AI Software Engineer,132259,GBP,99194,SE,FT,United Kingdom,S,United Kingdom,0,"Python, AWS, Data Visualization, Linux, GCP",Bachelor,8,Media,2024-06-09,2024-07-27,711,9.2,TechCorp Inc +AI14425,AI Specialist,131957,USD,131957,SE,PT,Sweden,S,Sweden,100,"Python, AWS, TensorFlow",PhD,9,Media,2024-09-19,2024-10-08,694,5.3,Machine Intelligence Group +AI14426,Deep Learning Engineer,87003,USD,87003,EN,PT,United States,L,United States,100,"Tableau, Docker, Hadoop, PyTorch, R",Bachelor,0,Education,2024-07-07,2024-08-17,1928,5.9,Smart Analytics +AI14427,AI Product Manager,220540,EUR,187459,EX,CT,Netherlands,S,Netherlands,50,"AWS, Linux, Kubernetes, Statistics, Mathematics",Associate,11,Education,2024-08-16,2024-09-06,1340,10,Algorithmic Solutions +AI14428,Data Analyst,167769,CHF,150992,SE,PT,Switzerland,L,Switzerland,50,"Hadoop, Java, NLP, Mathematics, Deep Learning",Associate,7,Government,2024-01-26,2024-03-16,1036,5.7,Machine Intelligence Group +AI14429,Head of AI,187950,USD,187950,EX,FL,South Korea,S,China,50,"Data Visualization, AWS, TensorFlow, Hadoop, Azure",Associate,19,Gaming,2024-12-24,2025-02-17,920,5.7,DeepTech Ventures +AI14430,ML Ops Engineer,58695,EUR,49891,EN,FT,Germany,S,Singapore,0,"Linux, Kubernetes, NLP, Mathematics",Master,0,Automotive,2024-02-21,2024-03-29,588,7.4,DeepTech Ventures +AI14431,Machine Learning Engineer,265749,USD,265749,EX,CT,Ireland,L,Ireland,0,"PyTorch, Java, MLOps, Scala, Azure",Bachelor,11,Gaming,2024-10-23,2024-11-23,697,8.8,DataVision Ltd +AI14432,Research Scientist,110493,EUR,93919,SE,PT,Germany,S,Germany,100,"R, NLP, Python",PhD,7,Healthcare,2025-01-11,2025-03-17,2345,6.9,Quantum Computing Inc +AI14433,Computer Vision Engineer,20337,USD,20337,EN,FT,India,S,Switzerland,0,"GCP, SQL, PyTorch",PhD,0,Consulting,2025-04-08,2025-05-31,1553,9.3,Algorithmic Solutions +AI14434,Computer Vision Engineer,123983,JPY,13638130,MI,CT,Japan,L,Japan,100,"Python, Kubernetes, Spark, Data Visualization",Associate,2,Gaming,2025-01-20,2025-02-19,830,9.8,Machine Intelligence Group +AI14435,AI Software Engineer,206076,USD,206076,EX,FL,United States,L,United States,0,"GCP, Scala, R",Master,14,Transportation,2025-01-22,2025-02-27,1893,5.4,Predictive Systems +AI14436,Computer Vision Engineer,76678,CAD,95848,MI,FT,Canada,S,Canada,100,"Linux, Deep Learning, Docker, TensorFlow",PhD,4,Media,2024-05-27,2024-07-02,1571,6.1,Autonomous Tech +AI14437,AI Specialist,108696,USD,108696,EX,CT,China,L,China,50,"SQL, Python, Git, Tableau",Associate,13,Education,2024-04-14,2024-05-10,1504,9.3,DataVision Ltd +AI14438,NLP Engineer,124557,CAD,155696,SE,FT,Canada,S,Canada,100,"Scala, PyTorch, SQL, Data Visualization",Associate,9,Technology,2024-10-08,2024-10-26,2225,9.7,Cloud AI Solutions +AI14439,Research Scientist,95689,EUR,81336,MI,PT,Germany,S,South Africa,0,"GCP, Azure, PyTorch, TensorFlow, AWS",Bachelor,4,Transportation,2024-05-16,2024-07-15,1331,7.1,Autonomous Tech +AI14440,AI Specialist,295651,SGD,384346,EX,FT,Singapore,L,Vietnam,0,"Python, GCP, Tableau, TensorFlow, Spark",PhD,15,Telecommunications,2024-10-10,2024-11-30,1805,6.3,DataVision Ltd +AI14441,AI Software Engineer,219218,CAD,274023,EX,PT,Canada,L,Canada,100,"Data Visualization, Scala, Mathematics, Java, AWS",Associate,10,Energy,2025-03-13,2025-04-26,2212,5.1,Predictive Systems +AI14442,Machine Learning Engineer,125323,CAD,156654,SE,CT,Canada,M,Canada,50,"PyTorch, TensorFlow, Scala, AWS, Java",Master,5,Telecommunications,2025-01-23,2025-03-22,1414,6,Smart Analytics +AI14443,Data Scientist,62189,EUR,52861,EN,CT,France,L,Ghana,0,"Python, TensorFlow, Linux, Azure",PhD,0,Healthcare,2025-03-02,2025-03-20,779,9.4,Cognitive Computing +AI14444,Research Scientist,82731,USD,82731,EN,FT,United States,M,Argentina,50,"Spark, MLOps, Scala",Master,1,Finance,2025-02-14,2025-03-10,2269,9.3,Digital Transformation LLC +AI14445,Data Engineer,104548,SGD,135912,SE,CT,Singapore,S,Singapore,100,"Python, TensorFlow, Deep Learning, MLOps",Associate,9,Real Estate,2024-02-06,2024-03-11,1024,6.9,Smart Analytics +AI14446,AI Research Scientist,186864,SGD,242923,EX,CT,Singapore,S,China,0,"Python, TensorFlow, Data Visualization, R",Associate,10,Retail,2024-12-30,2025-02-12,1927,8.8,Advanced Robotics +AI14447,Computer Vision Engineer,90839,CHF,81755,EN,PT,Switzerland,M,Switzerland,50,"Java, Azure, Deep Learning, Scala",PhD,0,Real Estate,2025-03-31,2025-05-22,1877,9,Advanced Robotics +AI14448,AI Consultant,70876,USD,70876,SE,CT,China,L,China,0,"Python, GCP, Git, Deep Learning",PhD,8,Retail,2024-09-18,2024-11-18,1534,8.4,AI Innovations +AI14449,Robotics Engineer,124242,EUR,105606,EX,FT,France,S,Spain,0,"Spark, Git, Python",Associate,13,Consulting,2025-02-17,2025-03-16,919,5.2,Autonomous Tech +AI14450,Deep Learning Engineer,82268,USD,82268,MI,PT,United States,S,United States,100,"R, MLOps, Hadoop, GCP",Master,4,Retail,2025-01-16,2025-03-19,2139,6.8,Cognitive Computing +AI14451,Data Scientist,108994,EUR,92645,MI,FL,Germany,L,Germany,100,"Deep Learning, NLP, Python",Bachelor,4,Media,2024-05-24,2024-06-12,777,5.2,Algorithmic Solutions +AI14452,Principal Data Scientist,88271,USD,88271,MI,FL,Israel,M,Israel,50,"SQL, R, Linux, Docker",Associate,3,Government,2024-12-21,2025-02-05,1348,5.6,Advanced Robotics +AI14453,Deep Learning Engineer,141697,GBP,106273,SE,FL,United Kingdom,M,United Kingdom,0,"Java, AWS, MLOps, Python, Computer Vision",PhD,8,Transportation,2024-10-20,2024-12-04,1060,6,Advanced Robotics +AI14454,AI Software Engineer,77206,CAD,96508,MI,FL,Canada,M,Canada,100,"Spark, Hadoop, Kubernetes, SQL",Master,2,Transportation,2024-03-17,2024-04-28,1765,6,DataVision Ltd +AI14455,Deep Learning Engineer,63781,USD,63781,EN,FT,Ireland,M,Ireland,0,"Scala, GCP, MLOps, Computer Vision, Linux",PhD,1,Consulting,2024-09-06,2024-09-22,2327,7.3,DataVision Ltd +AI14456,Autonomous Systems Engineer,107579,GBP,80684,MI,CT,United Kingdom,L,United Kingdom,0,"Linux, NLP, Spark, Python",Associate,2,Technology,2024-11-08,2024-12-27,654,6.3,DeepTech Ventures +AI14457,AI Architect,210771,CHF,189694,SE,FT,Switzerland,M,Switzerland,50,"Scala, Hadoop, Docker, Computer Vision, Spark",PhD,8,Technology,2024-02-17,2024-04-09,1854,8,Digital Transformation LLC +AI14458,Principal Data Scientist,71437,JPY,7858070,MI,CT,Japan,S,Poland,100,"Kubernetes, Scala, Docker",PhD,4,Healthcare,2024-06-23,2024-08-29,1933,5.2,Machine Intelligence Group +AI14459,Computer Vision Engineer,57340,USD,57340,EN,CT,Sweden,S,Sweden,0,"PyTorch, Python, Mathematics",Associate,1,Manufacturing,2025-03-10,2025-04-22,2221,6.5,TechCorp Inc +AI14460,Robotics Engineer,89880,CAD,112350,MI,CT,Canada,L,Japan,0,"GCP, Hadoop, Git, Tableau, PyTorch",Master,2,Technology,2024-09-28,2024-11-06,1323,8.9,AI Innovations +AI14461,ML Ops Engineer,68307,USD,68307,MI,CT,Israel,S,Israel,100,"AWS, Python, TensorFlow, PyTorch",PhD,4,Real Estate,2025-02-06,2025-03-01,2079,7.2,Cloud AI Solutions +AI14462,Autonomous Systems Engineer,149703,CAD,187129,EX,PT,Canada,S,Canada,0,"Hadoop, Java, Linux",Associate,15,Automotive,2024-05-15,2024-07-27,2181,6.4,AI Innovations +AI14463,ML Ops Engineer,31779,USD,31779,EN,CT,India,L,India,0,"Scala, Azure, Statistics, Python",Associate,1,Automotive,2024-12-22,2025-02-13,533,9.4,TechCorp Inc +AI14464,AI Product Manager,131531,GBP,98648,MI,PT,United Kingdom,L,United Kingdom,50,"Git, Data Visualization, Hadoop",PhD,4,Education,2024-03-01,2024-04-14,1022,5.8,Smart Analytics +AI14465,AI Product Manager,200424,CAD,250530,EX,PT,Canada,M,Canada,0,"MLOps, Python, Kubernetes, TensorFlow, Java",Master,17,Transportation,2024-11-15,2024-12-29,2202,6.9,Quantum Computing Inc +AI14466,Robotics Engineer,129718,GBP,97289,MI,FL,United Kingdom,L,Ukraine,100,"Statistics, SQL, MLOps, Hadoop, Scala",PhD,3,Retail,2024-06-15,2024-07-12,1936,6.9,Cloud AI Solutions +AI14467,AI Software Engineer,84762,USD,84762,MI,FL,Finland,S,Hungary,100,"Python, Computer Vision, Java, Deep Learning",Bachelor,3,Gaming,2024-03-06,2024-05-06,1062,6.3,Digital Transformation LLC +AI14468,Data Analyst,143526,CAD,179408,SE,FL,Canada,L,Austria,100,"Java, Kubernetes, AWS, PyTorch",Master,9,Education,2024-06-19,2024-07-05,1739,8.8,Algorithmic Solutions +AI14469,AI Consultant,134652,USD,134652,EX,PT,Finland,S,Finland,50,"MLOps, AWS, Git, SQL",Associate,18,Media,2024-03-21,2024-04-10,2226,7.2,AI Innovations +AI14470,Principal Data Scientist,72770,USD,72770,EN,FL,Finland,M,Finland,50,"SQL, PyTorch, Deep Learning, GCP, Mathematics",Master,1,Telecommunications,2025-02-01,2025-03-28,2147,8.6,Cloud AI Solutions +AI14471,Data Scientist,165036,CHF,148532,SE,FT,Switzerland,S,Switzerland,50,"Azure, Git, Data Visualization, TensorFlow, Kubernetes",Associate,9,Finance,2024-03-14,2024-04-18,973,8.5,Machine Intelligence Group +AI14472,Machine Learning Researcher,277879,USD,277879,EX,PT,Denmark,L,Denmark,50,"Data Visualization, Azure, R, SQL",Bachelor,10,Energy,2024-01-25,2024-03-31,2242,7.7,Cloud AI Solutions +AI14473,AI Specialist,292246,USD,292246,EX,FL,Ireland,L,Ireland,100,"AWS, Scala, Mathematics, MLOps",PhD,16,Consulting,2024-07-01,2024-08-04,1417,8.9,Machine Intelligence Group +AI14474,AI Software Engineer,122288,EUR,103945,MI,PT,Netherlands,L,Netherlands,50,"TensorFlow, Kubernetes, Scala",PhD,4,Consulting,2024-08-16,2024-09-22,1424,7,Autonomous Tech +AI14475,AI Architect,185384,USD,185384,EX,CT,Denmark,M,Denmark,100,"Spark, Deep Learning, Python",Associate,18,Telecommunications,2024-12-22,2025-01-09,734,9.1,AI Innovations +AI14476,AI Architect,204233,EUR,173598,EX,FL,Austria,S,Austria,0,"Git, Computer Vision, Tableau",Master,14,Finance,2024-03-22,2024-04-16,1045,7.6,Cognitive Computing +AI14477,AI Consultant,57991,CAD,72489,EN,CT,Canada,L,Austria,50,"Computer Vision, Python, Data Visualization",Bachelor,1,Telecommunications,2024-02-09,2024-04-01,2183,8.7,Advanced Robotics +AI14478,Autonomous Systems Engineer,235868,USD,235868,EX,FL,Finland,L,Finland,100,"Deep Learning, Scala, SQL",PhD,11,Technology,2025-01-30,2025-02-15,1745,5.8,Cognitive Computing +AI14479,Research Scientist,150822,EUR,128199,SE,FT,Netherlands,L,Netherlands,50,"Kubernetes, Scala, MLOps, Mathematics, Statistics",Master,7,Government,2024-05-20,2024-06-18,526,8.5,Machine Intelligence Group +AI14480,Machine Learning Researcher,112953,USD,112953,EN,FL,Denmark,L,Denmark,50,"Tableau, Statistics, Spark, MLOps, Git",Bachelor,0,Manufacturing,2024-01-25,2024-02-19,876,8.4,Algorithmic Solutions +AI14481,ML Ops Engineer,201083,AUD,271462,EX,PT,Australia,S,Colombia,0,"Java, Hadoop, SQL, Git, Docker",Associate,14,Real Estate,2024-07-03,2024-08-11,1486,7.3,Future Systems +AI14482,Machine Learning Engineer,63962,CAD,79953,MI,CT,Canada,S,Canada,50,"Azure, PyTorch, SQL, Computer Vision, Mathematics",Bachelor,2,Consulting,2025-02-08,2025-04-02,1369,8.1,Cognitive Computing +AI14483,AI Consultant,124552,CHF,112097,MI,CT,Switzerland,M,Switzerland,100,"SQL, Azure, Scala, Python",PhD,4,Telecommunications,2025-01-26,2025-03-02,1392,9,Predictive Systems +AI14484,Data Analyst,65428,USD,65428,EN,FL,Israel,M,Chile,50,"SQL, Hadoop, Mathematics, Computer Vision, Deep Learning",Associate,0,Real Estate,2025-04-06,2025-06-14,1254,6.9,DeepTech Ventures +AI14485,Computer Vision Engineer,122062,CHF,109856,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, TensorFlow, Statistics, R, Deep Learning",Bachelor,2,Telecommunications,2024-05-11,2024-06-15,2116,7.8,Smart Analytics +AI14486,AI Research Scientist,111469,AUD,150483,SE,FL,Australia,S,Brazil,0,"MLOps, Git, Kubernetes, NLP",PhD,8,Media,2025-03-25,2025-05-16,581,5.9,Machine Intelligence Group +AI14487,Deep Learning Engineer,181761,USD,181761,EX,FT,South Korea,M,South Korea,50,"Tableau, Computer Vision, Kubernetes",PhD,10,Government,2025-01-17,2025-02-08,1234,9.5,Cloud AI Solutions +AI14488,Data Analyst,116229,GBP,87172,SE,PT,United Kingdom,M,Latvia,100,"Kubernetes, Docker, MLOps, Git",Bachelor,8,Finance,2025-01-03,2025-02-16,1852,9.8,DataVision Ltd +AI14489,Data Scientist,82622,USD,82622,EN,CT,Finland,L,Finland,100,"SQL, Kubernetes, Statistics, Deep Learning, PyTorch",Master,0,Gaming,2025-01-20,2025-03-16,1749,8.5,Autonomous Tech +AI14490,AI Research Scientist,96369,USD,96369,EN,FL,Norway,L,Norway,50,"MLOps, Git, Python",PhD,0,Consulting,2024-01-30,2024-03-08,1367,9.4,Cognitive Computing +AI14491,Research Scientist,53103,USD,53103,EN,CT,Israel,M,Israel,0,"Tableau, Kubernetes, Scala, R, Mathematics",Bachelor,1,Consulting,2024-04-27,2024-07-04,1971,9.2,Algorithmic Solutions +AI14492,NLP Engineer,57126,EUR,48557,EN,PT,France,S,United Kingdom,50,"Python, Spark, NLP",Master,0,Media,2024-08-11,2024-10-23,1473,7.3,Machine Intelligence Group +AI14493,Machine Learning Engineer,94857,JPY,10434270,EN,PT,Japan,L,Japan,0,"AWS, Java, Scala, Spark",Bachelor,0,Automotive,2025-03-30,2025-05-04,1942,8.4,Advanced Robotics +AI14494,Research Scientist,99850,EUR,84873,SE,PT,Austria,S,Germany,100,"NLP, Java, Tableau, GCP",Master,7,Automotive,2024-10-14,2024-12-12,1764,9.5,Autonomous Tech +AI14495,Machine Learning Researcher,26941,USD,26941,EN,FT,India,L,India,50,"Kubernetes, Docker, Data Visualization, GCP",Bachelor,1,Healthcare,2024-01-29,2024-03-18,929,5.2,Autonomous Tech +AI14496,Principal Data Scientist,37543,USD,37543,MI,FT,India,L,Romania,100,"Data Visualization, Hadoop, TensorFlow",PhD,4,Manufacturing,2025-02-09,2025-03-27,1623,9.6,Cognitive Computing +AI14497,Head of AI,145765,USD,145765,SE,PT,Israel,L,Israel,50,"Python, TensorFlow, PyTorch",Associate,9,Energy,2024-07-07,2024-08-09,1970,7.4,Machine Intelligence Group +AI14498,Data Analyst,109358,USD,109358,SE,FT,Sweden,M,Ukraine,100,"Data Visualization, SQL, Kubernetes",Associate,6,Education,2025-03-23,2025-05-26,1121,6,Quantum Computing Inc +AI14499,Computer Vision Engineer,85375,USD,85375,EX,CT,China,M,Vietnam,0,"Hadoop, Java, Azure, GCP, Scala",Associate,16,Energy,2024-02-13,2024-04-14,1288,9.6,Autonomous Tech +AI14500,AI Research Scientist,34369,USD,34369,MI,FT,China,S,China,50,"Java, Kubernetes, Hadoop, Statistics",Associate,2,Finance,2024-10-24,2024-12-15,2200,8.1,Smart Analytics +AI14501,Head of AI,101172,USD,101172,MI,FT,United States,S,United States,100,"Python, NLP, TensorFlow, GCP",PhD,3,Finance,2024-10-26,2024-12-02,1033,5.6,AI Innovations +AI14502,Robotics Engineer,100350,USD,100350,EN,FT,Denmark,L,Denmark,50,"SQL, AWS, GCP",Bachelor,0,Manufacturing,2024-12-20,2025-03-03,1176,7.2,Cloud AI Solutions +AI14503,Computer Vision Engineer,53409,SGD,69432,EN,FL,Singapore,S,Singapore,50,"Hadoop, Java, PyTorch",PhD,1,Media,2024-06-25,2024-09-03,2077,7.7,Future Systems +AI14504,Head of AI,109264,USD,109264,MI,PT,Finland,L,Czech Republic,0,"Java, Linux, AWS",Bachelor,3,Finance,2024-03-29,2024-06-06,677,6.5,Digital Transformation LLC +AI14505,Research Scientist,67190,USD,67190,EN,FL,United States,M,United States,0,"SQL, Spark, Computer Vision",Master,0,Energy,2024-06-12,2024-07-13,1965,8.4,TechCorp Inc +AI14506,AI Architect,68547,JPY,7540170,EN,FT,Japan,S,Argentina,0,"Mathematics, PyTorch, Computer Vision",PhD,0,Automotive,2025-02-05,2025-03-18,1778,5.3,Cloud AI Solutions +AI14507,Machine Learning Researcher,86075,USD,86075,MI,PT,Israel,S,Israel,50,"Hadoop, Java, Mathematics",Master,2,Gaming,2024-05-15,2024-06-18,1624,9.5,Advanced Robotics +AI14508,ML Ops Engineer,71794,USD,71794,SE,FL,China,M,China,50,"GCP, Java, Python, Git, NLP",Master,8,Telecommunications,2024-07-21,2024-08-14,1256,8.3,Quantum Computing Inc +AI14509,AI Product Manager,89033,EUR,75678,MI,CT,Netherlands,S,Netherlands,0,"Data Visualization, R, SQL, Computer Vision",Bachelor,2,Media,2024-09-30,2024-10-17,1062,5.3,Digital Transformation LLC +AI14510,Principal Data Scientist,241780,GBP,181335,EX,FT,United Kingdom,S,United Kingdom,50,"SQL, Java, GCP, PyTorch",Associate,13,Gaming,2025-03-26,2025-06-02,1804,5.4,Advanced Robotics +AI14511,Head of AI,90029,GBP,67522,MI,PT,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, TensorFlow, Kubernetes",Associate,2,Media,2024-07-29,2024-08-25,1922,8.2,Machine Intelligence Group +AI14512,NLP Engineer,125238,USD,125238,SE,FL,Israel,S,Israel,0,"Hadoop, Spark, Kubernetes",Bachelor,9,Retail,2024-07-16,2024-09-27,764,8.6,AI Innovations +AI14513,ML Ops Engineer,60541,USD,60541,MI,FL,South Korea,S,South Korea,50,"Git, Linux, NLP",Bachelor,2,Automotive,2024-08-17,2024-09-17,1236,8.7,DataVision Ltd +AI14514,AI Specialist,45630,EUR,38786,EN,FT,France,S,France,0,"TensorFlow, GCP, Linux",Associate,1,Healthcare,2024-07-04,2024-07-29,676,6.1,Smart Analytics +AI14515,AI Consultant,159534,CHF,143581,SE,FL,Switzerland,M,Switzerland,0,"Deep Learning, GCP, R",Bachelor,6,Finance,2024-11-09,2025-01-21,1441,7.5,Algorithmic Solutions +AI14516,Data Analyst,68523,USD,68523,EN,FL,Ireland,M,Ireland,0,"Kubernetes, Deep Learning, Hadoop, Statistics",Bachelor,0,Energy,2024-11-15,2025-01-23,836,6.5,TechCorp Inc +AI14517,Computer Vision Engineer,93997,EUR,79897,MI,FT,Austria,M,Austria,50,"GCP, PyTorch, Data Visualization, SQL",Master,3,Transportation,2025-01-27,2025-03-02,1646,6.8,DeepTech Ventures +AI14518,Robotics Engineer,61638,EUR,52392,MI,FL,France,S,United Kingdom,100,"Java, Mathematics, AWS, Computer Vision",PhD,3,Automotive,2025-02-07,2025-03-14,2027,6.3,DeepTech Ventures +AI14519,Data Engineer,111944,USD,111944,SE,FL,Finland,L,Finland,100,"Hadoop, Spark, Java, Linux, MLOps",Associate,9,Consulting,2024-02-19,2024-04-24,1783,9.6,DataVision Ltd +AI14520,Computer Vision Engineer,99102,JPY,10901220,SE,FL,Japan,S,Japan,100,"Hadoop, MLOps, Git, Statistics",Associate,6,Government,2024-06-26,2024-08-05,2283,9.9,Smart Analytics +AI14521,AI Product Manager,66373,USD,66373,EN,FL,Ireland,S,Ireland,0,"Python, Docker, Git",Bachelor,0,Gaming,2024-12-27,2025-02-22,2425,6.7,DataVision Ltd +AI14522,Machine Learning Engineer,286837,USD,286837,EX,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Linux, PyTorch, GCP",Bachelor,10,Government,2024-01-06,2024-03-19,737,6.3,AI Innovations +AI14523,Computer Vision Engineer,163282,EUR,138790,EX,CT,France,M,France,100,"Scala, Python, Deep Learning, TensorFlow, AWS",PhD,12,Consulting,2025-01-27,2025-02-16,1004,6.4,Machine Intelligence Group +AI14524,Machine Learning Engineer,116441,USD,116441,SE,FT,South Korea,M,South Korea,100,"TensorFlow, Azure, Data Visualization",Master,9,Manufacturing,2025-02-28,2025-03-30,1732,5.6,Future Systems +AI14525,AI Software Engineer,72672,CAD,90840,EN,FT,Canada,M,China,0,"Scala, AWS, Computer Vision",Master,1,Media,2024-09-13,2024-10-15,789,5.4,Cloud AI Solutions +AI14526,Principal Data Scientist,125105,USD,125105,SE,FT,Sweden,S,Sweden,0,"R, Kubernetes, MLOps",PhD,8,Healthcare,2024-09-01,2024-10-22,623,5.4,Future Systems +AI14527,AI Architect,160966,SGD,209256,SE,CT,Singapore,L,Singapore,50,"Data Visualization, Docker, Statistics, Azure, MLOps",Bachelor,5,Manufacturing,2024-08-09,2024-10-12,1920,7.8,Cloud AI Solutions +AI14528,NLP Engineer,87326,CAD,109158,MI,CT,Canada,S,Canada,50,"Kubernetes, TensorFlow, SQL",PhD,4,Energy,2024-05-15,2024-06-07,754,7,Smart Analytics +AI14529,AI Product Manager,135601,USD,135601,SE,PT,Ireland,M,China,50,"Linux, Python, Statistics, AWS",Master,8,Gaming,2024-03-17,2024-04-17,1413,6.1,Algorithmic Solutions +AI14530,Principal Data Scientist,217533,CHF,195780,EX,PT,Switzerland,M,Romania,0,"GCP, Docker, SQL",Master,17,Finance,2025-03-26,2025-06-01,633,8.2,Cloud AI Solutions +AI14531,Head of AI,98113,EUR,83396,MI,FL,Austria,M,France,50,"Python, Tableau, Kubernetes, Linux, Java",Associate,3,Automotive,2024-10-30,2024-11-16,2184,8.1,DeepTech Ventures +AI14532,Autonomous Systems Engineer,81244,USD,81244,EN,PT,Israel,L,Hungary,50,"Spark, PyTorch, R, AWS, MLOps",Associate,1,Gaming,2024-02-01,2024-03-22,628,6.4,Autonomous Tech +AI14533,AI Architect,89895,EUR,76411,EN,CT,Netherlands,L,Italy,100,"Scala, Statistics, Java, Azure",PhD,0,Healthcare,2024-06-24,2024-08-11,1131,8,Autonomous Tech +AI14534,Research Scientist,171139,USD,171139,EX,FL,Sweden,M,Latvia,100,"TensorFlow, Git, SQL, Java, Python",Master,15,Technology,2024-06-10,2024-07-11,1799,9.7,Neural Networks Co +AI14535,Robotics Engineer,62756,SGD,81583,EN,FL,Singapore,M,Singapore,50,"Tableau, PyTorch, MLOps, TensorFlow, Linux",Master,0,Education,2024-06-04,2024-07-10,918,7.3,Smart Analytics +AI14536,Deep Learning Engineer,335964,CHF,302368,EX,CT,Switzerland,M,Switzerland,50,"R, Hadoop, Azure, GCP",PhD,11,Consulting,2025-02-20,2025-05-03,707,7.6,DataVision Ltd +AI14537,Data Scientist,106920,EUR,90882,MI,FT,Germany,M,United Kingdom,50,"Linux, AWS, Mathematics",Master,3,Healthcare,2024-09-17,2024-11-29,2132,7.3,Digital Transformation LLC +AI14538,Deep Learning Engineer,119575,EUR,101639,MI,CT,Austria,L,Austria,100,"Kubernetes, Java, Python, NLP, Spark",Bachelor,4,Energy,2024-12-04,2024-12-24,2163,6.1,AI Innovations +AI14539,Computer Vision Engineer,84559,USD,84559,EX,FT,China,M,China,50,"TensorFlow, SQL, Mathematics",PhD,10,Gaming,2025-04-15,2025-05-18,1877,8.6,Predictive Systems +AI14540,Head of AI,101252,USD,101252,MI,FL,Norway,M,Norway,100,"NLP, SQL, R, Docker",Associate,2,Media,2024-01-05,2024-03-01,1702,9.2,Digital Transformation LLC +AI14541,Deep Learning Engineer,236723,CHF,213051,EX,FL,Switzerland,L,Switzerland,0,"SQL, Scala, TensorFlow, GCP, Git",Master,17,Real Estate,2024-10-13,2024-11-13,2464,9.2,Machine Intelligence Group +AI14542,Data Analyst,244256,USD,244256,EX,FL,United States,S,United States,0,"Tableau, PyTorch, R",Bachelor,16,Finance,2024-07-03,2024-07-20,2238,5.9,Machine Intelligence Group +AI14543,Machine Learning Engineer,158103,EUR,134388,EX,FT,Germany,M,Denmark,50,"Hadoop, SQL, Java, GCP, PyTorch",PhD,11,Transportation,2025-01-30,2025-02-26,955,5.6,AI Innovations +AI14544,Head of AI,130549,EUR,110967,SE,CT,Germany,S,Germany,50,"R, GCP, Scala",Bachelor,5,Manufacturing,2025-03-06,2025-04-19,2156,7,TechCorp Inc +AI14545,AI Product Manager,175962,USD,175962,SE,FT,Denmark,M,Denmark,100,"Data Visualization, Docker, AWS, SQL, Linux",Master,7,Education,2025-03-23,2025-05-10,2102,5.9,Future Systems +AI14546,Head of AI,140334,USD,140334,EX,PT,Ireland,M,Ireland,100,"TensorFlow, Linux, Azure",PhD,13,Healthcare,2025-01-26,2025-03-27,1612,5.6,Cloud AI Solutions +AI14547,Machine Learning Engineer,83160,CHF,74844,EN,PT,Switzerland,M,Switzerland,50,"Docker, Linux, Deep Learning, TensorFlow, Git",Associate,0,Consulting,2024-12-10,2025-01-21,1282,9,Algorithmic Solutions +AI14548,Computer Vision Engineer,195354,AUD,263728,EX,CT,Australia,L,Indonesia,100,"Kubernetes, Scala, NLP, GCP, Tableau",Associate,19,Education,2025-04-21,2025-05-31,2365,9.6,AI Innovations +AI14549,AI Product Manager,62596,AUD,84505,EN,FL,Australia,L,Canada,100,"Python, Scala, Statistics",Bachelor,1,Consulting,2024-10-21,2024-12-22,1983,5.5,Algorithmic Solutions +AI14550,Machine Learning Engineer,246772,EUR,209756,EX,PT,Austria,L,Austria,100,"Deep Learning, Git, Scala, Java, Computer Vision",Associate,13,Energy,2024-10-24,2024-11-28,770,9.6,Cognitive Computing +AI14551,Data Engineer,59096,USD,59096,EN,CT,South Korea,S,South Korea,100,"Java, Hadoop, Data Visualization, Linux, Tableau",Master,1,Energy,2024-06-14,2024-08-19,2494,8,Predictive Systems +AI14552,Principal Data Scientist,144657,USD,144657,EX,FT,Sweden,S,Portugal,50,"NLP, Deep Learning, Data Visualization, Hadoop, SQL",Bachelor,12,Gaming,2024-02-12,2024-03-29,2372,9.8,AI Innovations +AI14553,Research Scientist,98312,USD,98312,EX,FT,China,L,China,100,"Scala, Python, NLP, R",Associate,17,Retail,2024-10-08,2024-11-24,574,9.4,Advanced Robotics +AI14554,Machine Learning Researcher,268721,EUR,228413,EX,CT,Germany,L,Germany,100,"Python, SQL, AWS",Master,10,Transportation,2024-12-16,2025-01-21,2163,5.8,Machine Intelligence Group +AI14555,Robotics Engineer,24804,USD,24804,EN,CT,China,S,Ukraine,50,"Python, Azure, TensorFlow, R",PhD,1,Real Estate,2024-06-09,2024-07-22,563,6.5,Cognitive Computing +AI14556,Robotics Engineer,116955,AUD,157889,SE,FT,Australia,S,Australia,100,"Python, Kubernetes, Data Visualization",Associate,8,Automotive,2025-03-15,2025-05-19,1300,9.5,Digital Transformation LLC +AI14557,Computer Vision Engineer,102088,EUR,86775,MI,CT,France,L,France,100,"Azure, GCP, SQL, Deep Learning, PyTorch",Associate,3,Healthcare,2025-04-02,2025-06-03,1698,6.4,Advanced Robotics +AI14558,Autonomous Systems Engineer,150619,EUR,128026,SE,CT,Germany,L,Germany,50,"Scala, Python, Mathematics, Deep Learning",Associate,7,Technology,2025-02-28,2025-03-30,1410,8.2,Neural Networks Co +AI14559,AI Specialist,110839,CAD,138549,MI,PT,Canada,L,Malaysia,50,"SQL, NLP, Kubernetes, Mathematics",Bachelor,4,Gaming,2025-04-15,2025-05-02,1293,6,Cloud AI Solutions +AI14560,Computer Vision Engineer,201264,CHF,181138,EX,PT,Switzerland,M,Germany,0,"GCP, Scala, SQL, Computer Vision",Master,15,Manufacturing,2024-11-01,2024-12-17,2398,9.8,Cloud AI Solutions +AI14561,Autonomous Systems Engineer,87432,USD,87432,EN,PT,United States,M,United States,100,"TensorFlow, GCP, MLOps",Master,0,Transportation,2024-09-30,2024-12-02,1262,5.5,Future Systems +AI14562,AI Software Engineer,63493,EUR,53969,EN,PT,Netherlands,L,Netherlands,50,"NLP, SQL, Linux",Associate,0,Real Estate,2024-10-14,2024-12-24,2168,9.5,Digital Transformation LLC +AI14563,Research Scientist,184467,JPY,20291370,EX,FL,Japan,L,Japan,50,"Mathematics, Kubernetes, Azure, Deep Learning",PhD,18,Government,2024-05-23,2024-06-11,872,5.7,Advanced Robotics +AI14564,AI Research Scientist,209096,EUR,177732,EX,FT,Germany,M,Germany,100,"Kubernetes, Azure, Spark, GCP, Java",PhD,19,Real Estate,2024-02-29,2024-04-25,1107,8.6,Algorithmic Solutions +AI14565,Research Scientist,98677,SGD,128280,MI,PT,Singapore,S,Singapore,100,"NLP, AWS, Kubernetes, SQL, GCP",Associate,2,Retail,2024-02-23,2024-03-20,741,5.5,Advanced Robotics +AI14566,ML Ops Engineer,99800,CAD,124750,SE,FL,Canada,M,Canada,50,"PyTorch, Spark, TensorFlow, Kubernetes",PhD,5,Real Estate,2024-11-10,2025-01-21,1041,9.6,Digital Transformation LLC +AI14567,AI Research Scientist,109379,USD,109379,MI,CT,Finland,L,Finland,100,"Java, SQL, Linux",PhD,3,Transportation,2025-01-01,2025-03-06,1690,6.2,TechCorp Inc +AI14568,Data Analyst,68608,USD,68608,SE,CT,China,L,China,0,"Hadoop, Python, TensorFlow",Associate,5,Telecommunications,2024-08-01,2024-09-10,2444,8.5,TechCorp Inc +AI14569,Head of AI,70451,USD,70451,EX,CT,India,S,India,100,"Linux, Azure, Deep Learning, GCP",Bachelor,19,Consulting,2024-02-28,2024-03-21,985,8.7,DataVision Ltd +AI14570,NLP Engineer,127444,USD,127444,SE,FT,Norway,S,Norway,0,"Python, TensorFlow, Mathematics, AWS",Bachelor,6,Healthcare,2024-10-08,2024-11-11,1031,9.7,Neural Networks Co +AI14571,AI Research Scientist,59585,GBP,44689,EN,CT,United Kingdom,M,Spain,0,"Linux, PyTorch, Statistics, Scala",Associate,1,Transportation,2024-10-02,2024-12-05,2342,7.6,TechCorp Inc +AI14572,Principal Data Scientist,129467,GBP,97100,MI,CT,United Kingdom,L,New Zealand,50,"R, Computer Vision, Mathematics, SQL",Bachelor,2,Technology,2024-12-27,2025-02-02,983,5.9,Machine Intelligence Group +AI14573,AI Architect,89818,CHF,80836,EN,FL,Switzerland,S,Romania,50,"Git, Python, AWS, Deep Learning",PhD,1,Energy,2024-04-01,2024-06-03,1846,5.6,Algorithmic Solutions +AI14574,AI Specialist,168508,USD,168508,EX,FL,Israel,S,Kenya,50,"Hadoop, PyTorch, SQL",Associate,18,Telecommunications,2024-07-26,2024-09-09,2122,5.1,Autonomous Tech +AI14575,Machine Learning Researcher,139480,GBP,104610,SE,PT,United Kingdom,L,Colombia,100,"Azure, Scala, NLP, Mathematics, PyTorch",Master,8,Healthcare,2024-01-04,2024-02-01,2378,8.2,TechCorp Inc +AI14576,Machine Learning Researcher,192002,EUR,163202,EX,FL,Austria,L,Austria,50,"GCP, TensorFlow, Deep Learning, Data Visualization, SQL",Bachelor,18,Education,2024-07-12,2024-08-08,559,7.7,Autonomous Tech +AI14577,NLP Engineer,58121,USD,58121,MI,CT,China,L,China,0,"Mathematics, R, Tableau, SQL",PhD,2,Healthcare,2025-01-12,2025-02-15,1764,8,DeepTech Ventures +AI14578,Research Scientist,134623,EUR,114430,EX,FL,France,S,France,0,"NLP, Data Visualization, Java, R",Associate,15,Education,2025-04-08,2025-05-05,1864,9.3,TechCorp Inc +AI14579,AI Architect,97785,USD,97785,MI,CT,Norway,S,Norway,0,"Java, PyTorch, TensorFlow, Python",PhD,4,Gaming,2024-03-28,2024-05-26,807,7.5,AI Innovations +AI14580,Principal Data Scientist,219292,AUD,296044,EX,FL,Australia,L,Australia,100,"SQL, Mathematics, GCP",Master,11,Real Estate,2024-01-16,2024-03-12,974,6.3,DeepTech Ventures +AI14581,Principal Data Scientist,52713,USD,52713,MI,CT,China,L,China,100,"MLOps, Python, Spark, Scala",Bachelor,2,Telecommunications,2024-05-13,2024-07-10,1083,9.5,Autonomous Tech +AI14582,AI Architect,318665,USD,318665,EX,FT,Denmark,M,Denmark,50,"AWS, PyTorch, Deep Learning",Bachelor,13,Healthcare,2024-11-02,2024-11-19,1618,8.7,Digital Transformation LLC +AI14583,Data Analyst,150768,CHF,135691,MI,FL,Switzerland,M,Switzerland,50,"Statistics, Scala, R, Kubernetes, Python",Master,4,Telecommunications,2024-09-28,2024-11-19,1321,9.3,Predictive Systems +AI14584,Robotics Engineer,130419,USD,130419,MI,CT,Denmark,M,Denmark,50,"Spark, Scala, Deep Learning, TensorFlow, NLP",PhD,2,Manufacturing,2024-11-10,2024-12-18,1361,5.6,Autonomous Tech +AI14585,Machine Learning Researcher,134257,USD,134257,MI,FL,Denmark,L,Sweden,50,"Python, AWS, Computer Vision, Azure",Associate,2,Telecommunications,2025-03-12,2025-05-06,1297,8.8,Digital Transformation LLC +AI14586,Robotics Engineer,88859,GBP,66644,MI,PT,United Kingdom,L,Latvia,50,"Java, R, MLOps, GCP, Scala",PhD,2,Finance,2024-09-12,2024-10-09,1916,6.4,Machine Intelligence Group +AI14587,Head of AI,124958,USD,124958,SE,FT,South Korea,M,South Korea,50,"Python, Scala, AWS, TensorFlow, Java",Master,8,Telecommunications,2024-09-10,2024-10-13,2029,9.9,Smart Analytics +AI14588,Data Engineer,173410,GBP,130058,SE,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,9,Healthcare,2024-02-11,2024-03-13,2108,8.5,Neural Networks Co +AI14589,AI Specialist,119770,EUR,101805,SE,PT,France,M,France,50,"Python, Mathematics, Azure, TensorFlow",Associate,7,Automotive,2025-04-17,2025-06-29,648,7.8,DeepTech Ventures +AI14590,Data Scientist,57438,EUR,48822,EN,FT,Netherlands,M,Netherlands,50,"Kubernetes, Deep Learning, Computer Vision, GCP",Master,1,Transportation,2024-08-16,2024-10-23,717,8.2,Digital Transformation LLC +AI14591,Machine Learning Engineer,168237,CAD,210296,EX,PT,Canada,S,Canada,100,"AWS, Java, R, Data Visualization",Associate,10,Government,2024-03-14,2024-05-09,2119,9.1,DeepTech Ventures +AI14592,Principal Data Scientist,198127,USD,198127,EX,FT,Sweden,M,Ireland,100,"Linux, Git, MLOps, Tableau, Computer Vision",PhD,19,Retail,2025-04-26,2025-05-10,2065,6.7,Advanced Robotics +AI14593,AI Software Engineer,91754,USD,91754,SE,FT,South Korea,S,South Korea,0,"Computer Vision, Tableau, AWS, Data Visualization, Python",Bachelor,5,Education,2024-10-23,2024-12-28,2354,9.8,Autonomous Tech +AI14594,AI Research Scientist,59433,CAD,74291,EN,FL,Canada,L,Romania,0,"Linux, Data Visualization, Deep Learning",PhD,1,Media,2025-01-12,2025-01-30,1618,9,Quantum Computing Inc +AI14595,AI Consultant,128719,EUR,109411,SE,CT,Germany,M,Germany,100,"Scala, SQL, Linux, Azure",Master,5,Consulting,2025-03-18,2025-05-26,1435,8.1,DataVision Ltd +AI14596,NLP Engineer,225590,CHF,203031,EX,FT,Switzerland,M,Switzerland,50,"Data Visualization, Statistics, SQL, Deep Learning, Mathematics",PhD,10,Healthcare,2024-08-17,2024-10-03,832,9.9,Machine Intelligence Group +AI14597,Data Engineer,327266,USD,327266,EX,FL,Norway,M,Norway,0,"Deep Learning, Python, Java, Computer Vision, SQL",Master,19,Consulting,2024-06-19,2024-08-03,1607,9.6,Quantum Computing Inc +AI14598,Computer Vision Engineer,77377,USD,77377,MI,FL,Ireland,M,Italy,100,"TensorFlow, Scala, Mathematics",Master,3,Manufacturing,2024-09-09,2024-11-13,1176,9.6,Autonomous Tech +AI14599,Research Scientist,172505,USD,172505,SE,FL,Norway,M,Norway,0,"Linux, Azure, Deep Learning, Python",Master,5,Automotive,2025-03-18,2025-04-29,789,5.2,Advanced Robotics +AI14600,Head of AI,97488,GBP,73116,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, Java, Kubernetes, TensorFlow",Master,4,Healthcare,2024-02-23,2024-04-12,506,9.9,Future Systems +AI14601,Head of AI,71688,USD,71688,EN,CT,Ireland,M,Ireland,100,"Data Visualization, Python, SQL, TensorFlow",Master,0,Telecommunications,2024-08-13,2024-09-13,518,9,Autonomous Tech +AI14602,Machine Learning Researcher,177939,USD,177939,EX,PT,Finland,L,United Kingdom,50,"Java, Hadoop, Computer Vision",Master,15,Government,2024-07-13,2024-08-31,2444,8.5,DeepTech Ventures +AI14603,Deep Learning Engineer,176846,CHF,159161,EX,CT,Switzerland,S,Switzerland,100,"Computer Vision, Docker, Data Visualization, Linux, Statistics",PhD,16,Consulting,2024-04-01,2024-06-05,1132,8.3,DataVision Ltd +AI14604,AI Consultant,75786,EUR,64418,MI,FL,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP, Java, Scala",PhD,2,Consulting,2024-12-22,2025-02-12,517,8.1,Algorithmic Solutions +AI14605,AI Consultant,57729,USD,57729,EN,CT,Finland,L,Finland,50,"Scala, Hadoop, Git, Data Visualization",Bachelor,1,Gaming,2024-01-05,2024-02-26,1690,5.2,Cloud AI Solutions +AI14606,Head of AI,103984,USD,103984,SE,FT,South Korea,S,South Africa,50,"Tableau, Azure, SQL, Java, Spark",Associate,8,Government,2024-11-24,2024-12-08,1783,9.7,Cognitive Computing +AI14607,NLP Engineer,109857,GBP,82393,SE,FL,United Kingdom,M,United Kingdom,50,"Kubernetes, Java, NLP",Master,8,Telecommunications,2024-02-25,2024-04-07,814,6,Cloud AI Solutions +AI14608,Data Analyst,211073,USD,211073,EX,CT,Ireland,S,Ireland,0,"GCP, Git, MLOps",PhD,11,Technology,2024-10-18,2024-11-02,674,9,Quantum Computing Inc +AI14609,Data Engineer,134522,USD,134522,SE,CT,Sweden,L,Sweden,0,"AWS, Hadoop, MLOps, Python",Master,5,Education,2025-03-14,2025-04-04,1612,5.7,Predictive Systems +AI14610,AI Architect,161100,CHF,144990,SE,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, AWS, MLOps, Scala",Associate,6,Transportation,2025-01-31,2025-03-14,1781,8,DeepTech Ventures +AI14611,Autonomous Systems Engineer,122301,EUR,103956,SE,FL,Germany,M,Germany,50,"Kubernetes, Python, Computer Vision",Associate,6,Government,2024-09-07,2024-10-23,2201,5.8,Autonomous Tech +AI14612,NLP Engineer,85699,EUR,72844,MI,FT,Germany,S,Mexico,50,"Kubernetes, Java, R, Docker, Statistics",PhD,2,Healthcare,2024-06-12,2024-07-09,1286,9.8,Quantum Computing Inc +AI14613,AI Consultant,70435,CAD,88044,EN,FL,Canada,M,India,0,"Linux, PyTorch, MLOps, R",Associate,1,Consulting,2025-02-02,2025-03-08,889,8.9,DeepTech Ventures +AI14614,Machine Learning Researcher,83577,EUR,71040,MI,FT,Austria,L,Austria,0,"Scala, Tableau, Python",PhD,2,Transportation,2024-05-12,2024-07-13,880,10,Digital Transformation LLC +AI14615,Machine Learning Researcher,224546,USD,224546,EX,CT,Denmark,L,Denmark,100,"PyTorch, AWS, TensorFlow",Associate,18,Real Estate,2024-11-18,2024-12-17,1647,5.1,Advanced Robotics +AI14616,AI Consultant,164191,JPY,18061010,SE,CT,Japan,L,Japan,100,"R, Linux, SQL, PyTorch, AWS",Bachelor,7,Technology,2024-01-02,2024-03-03,1513,7.5,DataVision Ltd +AI14617,AI Architect,234520,SGD,304876,EX,CT,Singapore,S,Singapore,0,"Tableau, Hadoop, Kubernetes, SQL, NLP",Master,14,Manufacturing,2024-03-23,2024-04-26,2487,8.6,Cloud AI Solutions +AI14618,Deep Learning Engineer,50375,USD,50375,SE,CT,China,S,China,100,"Python, Docker, Linux, Mathematics, Kubernetes",Bachelor,8,Technology,2024-08-29,2024-09-29,1638,9.7,Digital Transformation LLC +AI14619,Research Scientist,60031,EUR,51026,EN,CT,France,L,Vietnam,50,"Tableau, Data Visualization, AWS, Azure",Associate,1,Finance,2025-03-17,2025-05-24,1254,9.6,Quantum Computing Inc +AI14620,Computer Vision Engineer,38594,USD,38594,MI,FL,China,M,Hungary,100,"AWS, PyTorch, MLOps, NLP, Kubernetes",PhD,4,Automotive,2025-04-19,2025-06-06,2450,8.4,DeepTech Ventures +AI14621,AI Architect,115790,EUR,98422,SE,PT,Germany,M,Germany,0,"Scala, Python, AWS",Master,5,Gaming,2024-10-12,2024-12-11,2193,7.6,Advanced Robotics +AI14622,AI Product Manager,134490,USD,134490,SE,PT,Denmark,M,Denmark,50,"Python, Mathematics, Deep Learning, Git",PhD,7,Manufacturing,2024-02-22,2024-03-21,1593,7,Future Systems +AI14623,ML Ops Engineer,80936,USD,80936,MI,CT,United States,S,United States,100,"Docker, Python, AWS",PhD,3,Gaming,2024-11-01,2024-12-27,1341,8.3,TechCorp Inc +AI14624,Computer Vision Engineer,142227,USD,142227,SE,CT,Finland,M,Finland,0,"Spark, Tableau, Linux",PhD,5,Retail,2024-04-03,2024-05-13,2195,6.1,Quantum Computing Inc +AI14625,Data Analyst,301196,USD,301196,EX,FT,Norway,M,Australia,100,"Spark, TensorFlow, Azure, Docker, Tableau",Master,11,Education,2025-04-09,2025-05-24,664,7.3,Digital Transformation LLC +AI14626,AI Specialist,42683,USD,42683,SE,FL,India,M,India,0,"Mathematics, Kubernetes, Python",PhD,5,Telecommunications,2025-03-12,2025-05-06,527,9.5,TechCorp Inc +AI14627,Data Scientist,104271,USD,104271,SE,FT,South Korea,L,Chile,50,"R, Tableau, Scala, Deep Learning",PhD,9,Automotive,2024-10-09,2024-10-28,2307,7.7,Machine Intelligence Group +AI14628,Deep Learning Engineer,53911,USD,53911,SE,FT,India,L,India,50,"Java, Scala, Statistics, Azure, Python",PhD,9,Healthcare,2024-02-10,2024-04-15,1406,6.8,Advanced Robotics +AI14629,Data Scientist,119029,GBP,89272,MI,CT,United Kingdom,L,United Kingdom,50,"Java, PyTorch, Tableau, Deep Learning",Bachelor,3,Transportation,2024-10-27,2024-11-21,1815,8,Advanced Robotics +AI14630,Data Engineer,213288,EUR,181295,EX,CT,Germany,S,Germany,50,"SQL, Docker, GCP, AWS, R",Master,10,Government,2024-02-28,2024-04-02,879,8.5,Autonomous Tech +AI14631,AI Product Manager,109524,USD,109524,MI,PT,Denmark,S,Canada,50,"SQL, Docker, Statistics, Python",Master,3,Manufacturing,2024-05-03,2024-07-06,1628,6.9,Algorithmic Solutions +AI14632,AI Product Manager,58198,USD,58198,MI,CT,China,L,China,50,"Scala, Hadoop, Computer Vision, Java, Python",PhD,4,Automotive,2024-04-13,2024-06-11,1765,6.8,Quantum Computing Inc +AI14633,AI Research Scientist,113671,USD,113671,MI,CT,United States,L,Mexico,100,"Python, PyTorch, GCP, R",Master,3,Technology,2024-06-26,2024-09-05,1239,7.3,Digital Transformation LLC +AI14634,Head of AI,49824,USD,49824,SE,CT,India,M,India,0,"TensorFlow, GCP, SQL, Scala",Bachelor,6,Government,2024-12-28,2025-01-28,2279,9.9,Cloud AI Solutions +AI14635,Autonomous Systems Engineer,89500,EUR,76075,EN,PT,Netherlands,L,Netherlands,100,"Docker, Scala, Tableau",PhD,0,Gaming,2024-09-30,2024-11-12,935,5.9,Smart Analytics +AI14636,AI Research Scientist,224343,USD,224343,EX,FT,South Korea,L,South Korea,0,"Mathematics, AWS, Python, Deep Learning, Azure",Master,13,Technology,2024-11-12,2024-12-16,572,7.9,AI Innovations +AI14637,AI Consultant,175920,SGD,228696,EX,FT,Singapore,M,Singapore,50,"PyTorch, Azure, Mathematics, GCP",Master,14,Retail,2024-07-05,2024-07-25,956,8.7,Digital Transformation LLC +AI14638,Data Engineer,158352,AUD,213775,SE,FL,Australia,L,Australia,50,"TensorFlow, Python, Statistics, Git, Computer Vision",PhD,8,Gaming,2025-01-21,2025-03-21,1254,9,Cognitive Computing +AI14639,NLP Engineer,99340,USD,99340,EX,FT,China,S,China,0,"Computer Vision, Mathematics, PyTorch, TensorFlow",Master,19,Healthcare,2024-09-11,2024-10-11,535,7.4,Autonomous Tech +AI14640,Research Scientist,62050,JPY,6825500,EN,CT,Japan,M,Japan,50,"MLOps, PyTorch, Data Visualization, Docker",Bachelor,0,Education,2025-04-19,2025-06-13,2134,5.1,Machine Intelligence Group +AI14641,Head of AI,73299,USD,73299,EN,CT,United States,L,Argentina,100,"Python, Docker, SQL, Statistics",Master,1,Finance,2024-05-02,2024-06-12,2290,6.4,DeepTech Ventures +AI14642,AI Research Scientist,127142,EUR,108071,SE,CT,Austria,L,Austria,50,"Kubernetes, Java, Python, AWS",Bachelor,6,Transportation,2024-08-13,2024-10-23,1104,8.6,Predictive Systems +AI14643,AI Research Scientist,103463,USD,103463,SE,CT,Israel,S,Israel,100,"R, AWS, Computer Vision",Bachelor,6,Media,2024-03-16,2024-04-23,1690,6,Cloud AI Solutions +AI14644,Research Scientist,81210,USD,81210,MI,CT,South Korea,S,South Korea,100,"Kubernetes, Linux, Data Visualization",Associate,3,Telecommunications,2024-07-10,2024-07-27,1925,9,AI Innovations +AI14645,Data Engineer,26249,USD,26249,EN,CT,India,M,India,50,"R, SQL, Computer Vision, Hadoop, PyTorch",PhD,0,Finance,2025-01-09,2025-02-05,2316,9.9,DataVision Ltd +AI14646,Research Scientist,92398,AUD,124737,MI,CT,Australia,L,Australia,0,"Kubernetes, Spark, TensorFlow",Bachelor,4,Gaming,2024-06-09,2024-06-26,1440,5.3,Cognitive Computing +AI14647,Deep Learning Engineer,81062,GBP,60797,EN,FL,United Kingdom,L,United Kingdom,50,"Kubernetes, Azure, MLOps, Git, Statistics",Bachelor,1,Technology,2025-03-10,2025-05-05,2360,7.4,AI Innovations +AI14648,AI Software Engineer,194332,CHF,174899,SE,FT,Switzerland,L,Switzerland,50,"Python, Git, TensorFlow, SQL",Bachelor,9,Government,2024-06-15,2024-07-09,2134,9.5,TechCorp Inc +AI14649,AI Research Scientist,166789,JPY,18346790,SE,FL,Japan,L,United Kingdom,0,"Python, Scala, Statistics, GCP, Computer Vision",Bachelor,5,Telecommunications,2024-06-11,2024-07-08,989,8.4,Neural Networks Co +AI14650,AI Product Manager,271121,USD,271121,EX,FL,United States,L,United States,50,"Azure, Mathematics, NLP, Spark",Bachelor,19,Government,2024-11-10,2025-01-15,2193,9.6,DeepTech Ventures +AI14651,Principal Data Scientist,121488,EUR,103265,SE,FL,Germany,S,Germany,100,"Python, Kubernetes, Git, Deep Learning",PhD,6,Automotive,2024-07-31,2024-10-07,799,8,Smart Analytics +AI14652,Machine Learning Engineer,146495,AUD,197768,EX,CT,Australia,S,Australia,0,"GCP, Deep Learning, SQL, Kubernetes, Linux",Associate,13,Consulting,2024-12-08,2025-01-19,1963,5.9,Quantum Computing Inc +AI14653,AI Consultant,113007,USD,113007,MI,CT,Denmark,S,Estonia,100,"Python, Tableau, SQL",Bachelor,2,Media,2025-01-11,2025-03-12,1510,5.2,DataVision Ltd +AI14654,AI Research Scientist,79500,USD,79500,EN,CT,United States,L,Luxembourg,100,"SQL, Scala, Hadoop, Deep Learning",PhD,0,Government,2024-04-12,2024-05-16,1217,6.4,Autonomous Tech +AI14655,Autonomous Systems Engineer,84593,SGD,109971,MI,PT,Singapore,M,Singapore,0,"Linux, Git, SQL",Associate,2,Transportation,2024-12-03,2025-02-08,2411,7.9,TechCorp Inc +AI14656,Head of AI,87458,EUR,74339,MI,FL,France,L,France,50,"Deep Learning, Linux, NLP, Computer Vision, SQL",Master,3,Automotive,2024-06-16,2024-08-05,2258,8.2,DataVision Ltd +AI14657,AI Specialist,207998,USD,207998,EX,CT,Norway,L,Norway,100,"Kubernetes, MLOps, Python, Data Visualization, Docker",Bachelor,19,Media,2025-04-26,2025-07-01,2207,7.6,Machine Intelligence Group +AI14658,ML Ops Engineer,53800,GBP,40350,EN,FL,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, MLOps, NLP",PhD,1,Telecommunications,2024-10-05,2024-11-01,1568,9.7,Smart Analytics +AI14659,Machine Learning Researcher,56084,EUR,47671,EN,CT,Netherlands,M,Netherlands,50,"Tableau, Linux, Statistics",PhD,0,Media,2024-05-21,2024-07-31,1910,6.7,Digital Transformation LLC +AI14660,Robotics Engineer,92516,USD,92516,EN,FT,Norway,S,Norway,0,"Python, Kubernetes, MLOps, GCP, Spark",Bachelor,0,Retail,2025-02-16,2025-03-04,1766,9.7,Predictive Systems +AI14661,AI Product Manager,119724,USD,119724,EX,FL,China,M,China,0,"Docker, Python, MLOps",Associate,14,Telecommunications,2024-04-04,2024-05-04,1543,6.6,Cognitive Computing +AI14662,Machine Learning Researcher,104136,USD,104136,EX,FL,China,S,China,100,"Java, Computer Vision, NLP, R, MLOps",Bachelor,13,Manufacturing,2024-11-14,2025-01-02,647,8.6,Neural Networks Co +AI14663,Machine Learning Researcher,96383,USD,96383,MI,FT,Sweden,M,Sweden,0,"Spark, Git, Deep Learning, Computer Vision, Python",Associate,2,Media,2024-07-18,2024-09-26,543,8.5,Future Systems +AI14664,Robotics Engineer,75403,USD,75403,EN,FL,United States,L,United States,0,"Python, Data Visualization, TensorFlow, Computer Vision, Deep Learning",Bachelor,0,Transportation,2024-04-25,2024-05-26,2493,7.1,DataVision Ltd +AI14665,Machine Learning Researcher,100534,USD,100534,EN,FL,Denmark,M,Mexico,0,"Tableau, Git, Data Visualization",Master,1,Manufacturing,2024-09-15,2024-11-09,2459,7.8,Machine Intelligence Group +AI14666,Research Scientist,97918,USD,97918,MI,CT,Norway,S,Norway,0,"PyTorch, Python, Statistics, Git, Tableau",Associate,3,Government,2025-03-16,2025-04-15,1112,5.9,Machine Intelligence Group +AI14667,Principal Data Scientist,46643,USD,46643,EN,FL,Finland,S,Finland,50,"Data Visualization, Kubernetes, Python, Spark, NLP",Bachelor,1,Manufacturing,2024-08-22,2024-10-02,1297,9.3,DeepTech Ventures +AI14668,AI Product Manager,161683,EUR,137431,EX,FT,Germany,L,Germany,50,"Hadoop, SQL, Python, TensorFlow, MLOps",PhD,19,Energy,2024-04-30,2024-06-28,819,9.5,Cognitive Computing +AI14669,Data Scientist,78579,USD,78579,MI,CT,Israel,S,Israel,0,"Java, Data Visualization, MLOps, R, AWS",Associate,2,Telecommunications,2024-02-15,2024-04-20,1410,8.9,Predictive Systems +AI14670,AI Architect,98927,EUR,84088,MI,FT,Netherlands,S,Netherlands,0,"Tableau, GCP, Azure, Hadoop, Scala",Associate,3,Government,2024-01-29,2024-03-14,1021,8.2,Future Systems +AI14671,Computer Vision Engineer,74384,JPY,8182240,EN,FL,Japan,M,Japan,50,"Data Visualization, PyTorch, Deep Learning, NLP",Associate,1,Manufacturing,2024-08-08,2024-08-31,1730,8.2,Advanced Robotics +AI14672,AI Product Manager,203594,AUD,274852,EX,FT,Australia,L,Australia,0,"Java, Data Visualization, MLOps, SQL",Master,17,Technology,2024-01-13,2024-03-17,2249,9.3,TechCorp Inc +AI14673,Head of AI,304108,SGD,395340,EX,CT,Singapore,L,Singapore,0,"Python, TensorFlow, Kubernetes, Spark, Statistics",Bachelor,11,Retail,2024-12-25,2025-03-02,2030,7.1,Cloud AI Solutions +AI14674,AI Architect,128907,CAD,161134,SE,CT,Canada,M,Canada,0,"SQL, Azure, Python",Master,8,Energy,2025-02-19,2025-03-08,1987,6.9,DeepTech Ventures +AI14675,Machine Learning Researcher,103434,EUR,87919,MI,PT,Austria,M,Austria,100,"TensorFlow, Mathematics, Linux, SQL",PhD,2,Finance,2024-04-19,2024-05-27,1328,5.4,Digital Transformation LLC +AI14676,AI Specialist,126930,USD,126930,MI,FL,Norway,S,Norway,0,"Linux, Python, Computer Vision",Bachelor,2,Media,2025-02-11,2025-04-05,1625,7.2,Machine Intelligence Group +AI14677,Research Scientist,150089,EUR,127576,EX,FL,Germany,M,Germany,100,"Python, R, Java, Git, Tableau",Bachelor,19,Transportation,2025-02-22,2025-04-15,1964,7.4,Machine Intelligence Group +AI14678,Machine Learning Engineer,84084,CAD,105105,MI,FL,Canada,M,Singapore,0,"Java, PyTorch, Kubernetes, Azure, R",PhD,4,Media,2024-06-30,2024-09-01,1516,9.8,Algorithmic Solutions +AI14679,NLP Engineer,137388,USD,137388,SE,CT,South Korea,L,South Korea,100,"Docker, PyTorch, Kubernetes",Bachelor,8,Technology,2024-07-18,2024-09-02,2379,6.2,Advanced Robotics +AI14680,AI Consultant,70308,USD,70308,MI,PT,Finland,M,Finland,100,"SQL, Scala, Git, PyTorch",PhD,4,Real Estate,2024-07-21,2024-09-02,1317,8,TechCorp Inc +AI14681,AI Product Manager,121990,SGD,158587,MI,PT,Singapore,L,Ireland,50,"SQL, Linux, TensorFlow",Master,2,Technology,2024-03-06,2024-04-16,926,9,DataVision Ltd +AI14682,ML Ops Engineer,69409,USD,69409,EN,CT,Sweden,L,Sweden,0,"AWS, Mathematics, GCP, Azure",Master,1,Consulting,2024-06-09,2024-08-19,594,5.5,Future Systems +AI14683,AI Research Scientist,89827,USD,89827,EN,CT,Denmark,M,Denmark,0,"Tableau, Java, Data Visualization, Python",Master,1,Consulting,2024-10-17,2024-11-20,1703,9.2,Smart Analytics +AI14684,Head of AI,48806,USD,48806,SE,PT,China,S,China,50,"Python, Computer Vision, Hadoop, Scala, Git",Bachelor,6,Retail,2024-10-27,2024-12-17,1758,6.4,AI Innovations +AI14685,Head of AI,94120,CAD,117650,SE,FT,Canada,S,Canada,0,"PyTorch, SQL, NLP",Associate,6,Finance,2024-11-13,2025-01-19,2290,5.4,Quantum Computing Inc +AI14686,Data Analyst,175493,USD,175493,SE,FL,United States,L,United States,100,"Kubernetes, NLP, Scala, MLOps, Spark",PhD,5,Media,2024-05-26,2024-06-28,2336,5.7,Predictive Systems +AI14687,Data Scientist,257356,EUR,218753,EX,CT,Austria,L,Austria,50,"Python, Spark, Mathematics, Git",Master,16,Energy,2024-01-20,2024-02-12,2229,8.3,TechCorp Inc +AI14688,Computer Vision Engineer,200799,CAD,250999,EX,FL,Canada,M,Canada,50,"Linux, Tableau, Docker",Bachelor,15,Healthcare,2024-06-14,2024-07-05,1406,6.5,AI Innovations +AI14689,Data Scientist,210158,EUR,178634,EX,PT,Austria,M,Czech Republic,0,"SQL, PyTorch, Mathematics",Bachelor,15,Transportation,2024-11-22,2025-01-24,1727,8.6,Smart Analytics +AI14690,Autonomous Systems Engineer,46770,USD,46770,EN,FL,Sweden,S,Switzerland,0,"AWS, Kubernetes, Tableau, GCP, Linux",Associate,0,Healthcare,2024-11-28,2025-01-25,1620,5.6,TechCorp Inc +AI14691,Data Engineer,114132,CHF,102719,MI,CT,Switzerland,M,Switzerland,50,"Java, TensorFlow, SQL, Deep Learning",Associate,4,Real Estate,2024-05-24,2024-06-30,2162,7.2,AI Innovations +AI14692,Computer Vision Engineer,71064,USD,71064,EN,FT,Ireland,S,Ireland,0,"Docker, Python, TensorFlow, R",Master,1,Automotive,2024-06-11,2024-08-15,2497,5.7,Cloud AI Solutions +AI14693,Data Scientist,181541,SGD,236003,SE,FT,Singapore,L,Singapore,50,"Tableau, Hadoop, SQL, MLOps, Git",Master,5,Finance,2024-04-19,2024-05-06,1193,8.1,Future Systems +AI14694,Research Scientist,24046,USD,24046,EN,PT,China,S,China,100,"SQL, Python, Java, GCP, Computer Vision",PhD,0,Automotive,2025-02-24,2025-04-05,2443,7.6,Neural Networks Co +AI14695,AI Specialist,107262,USD,107262,SE,CT,South Korea,M,South Korea,50,"Java, Computer Vision, Mathematics",PhD,5,Government,2024-12-02,2024-12-30,2342,9.6,Neural Networks Co +AI14696,Head of AI,120857,USD,120857,SE,FL,South Korea,L,South Korea,50,"Python, TensorFlow, Deep Learning",PhD,9,Finance,2024-06-05,2024-07-05,1291,5.6,Algorithmic Solutions +AI14697,Head of AI,71387,CAD,89234,EN,CT,Canada,M,Canada,0,"Docker, Git, Python",Master,0,Finance,2024-02-11,2024-03-29,2059,5.9,Neural Networks Co +AI14698,Data Engineer,64859,USD,64859,MI,PT,South Korea,S,South Korea,0,"MLOps, Git, Python",PhD,4,Energy,2025-04-24,2025-06-14,2136,5.9,Neural Networks Co +AI14699,AI Consultant,69368,JPY,7630480,EN,FT,Japan,M,Japan,0,"Kubernetes, Computer Vision, Git",PhD,0,Consulting,2024-03-16,2024-04-22,550,8,Advanced Robotics +AI14700,AI Product Manager,57640,EUR,48994,EN,PT,Netherlands,M,Netherlands,50,"Java, Linux, Spark, Azure",Bachelor,0,Real Estate,2024-07-20,2024-08-11,2226,8,Cloud AI Solutions +AI14701,Research Scientist,100171,CAD,125214,SE,FT,Canada,S,Canada,0,"Git, MLOps, Linux, Data Visualization, Azure",Bachelor,5,Transportation,2024-02-08,2024-03-07,1994,5,Advanced Robotics +AI14702,Deep Learning Engineer,66219,SGD,86085,EN,CT,Singapore,S,Singapore,100,"GCP, Data Visualization, Azure, AWS",PhD,0,Retail,2024-12-23,2025-02-25,1170,6.5,Cognitive Computing +AI14703,Deep Learning Engineer,133384,EUR,113376,EX,PT,Austria,S,Austria,0,"Python, TensorFlow, Tableau",Master,11,Real Estate,2024-01-07,2024-03-03,1888,8.8,TechCorp Inc +AI14704,Machine Learning Researcher,133208,EUR,113227,SE,FL,Netherlands,L,Japan,100,"Git, Data Visualization, SQL",Bachelor,8,Media,2024-06-06,2024-08-17,640,7.6,Advanced Robotics +AI14705,AI Consultant,179309,USD,179309,EX,FT,Ireland,S,Ireland,0,"Data Visualization, R, Linux",Associate,15,Telecommunications,2024-01-18,2024-02-18,1899,8,DeepTech Ventures +AI14706,Principal Data Scientist,85394,JPY,9393340,MI,FL,Japan,S,Japan,0,"Azure, Scala, Deep Learning, GCP, AWS",PhD,4,Transportation,2024-09-29,2024-11-01,557,7.1,Digital Transformation LLC +AI14707,NLP Engineer,150883,AUD,203692,SE,FT,Australia,L,Australia,0,"Hadoop, Git, Spark, SQL, Python",PhD,5,Education,2024-12-26,2025-01-16,2237,7.9,Autonomous Tech +AI14708,Research Scientist,140306,JPY,15433660,EX,FL,Japan,S,Turkey,100,"Kubernetes, PyTorch, Data Visualization, Hadoop, Docker",Master,15,Finance,2025-03-04,2025-04-07,2469,8.7,Quantum Computing Inc +AI14709,ML Ops Engineer,132345,USD,132345,MI,CT,Norway,L,Switzerland,100,"MLOps, PyTorch, Data Visualization, Scala",Associate,3,Retail,2025-01-29,2025-03-14,1930,7.7,DataVision Ltd +AI14710,AI Specialist,81632,EUR,69387,EN,CT,Germany,L,Netherlands,0,"Scala, Python, NLP, Tableau, Git",PhD,0,Healthcare,2024-04-09,2024-04-26,1361,7.6,Future Systems +AI14711,Robotics Engineer,145334,SGD,188934,SE,FT,Singapore,M,Singapore,0,"NLP, Java, Python, Statistics, Deep Learning",PhD,9,Energy,2025-03-28,2025-05-21,2432,8.3,AI Innovations +AI14712,AI Product Manager,103134,CHF,92821,EN,CT,Switzerland,M,Switzerland,100,"Spark, R, GCP, TensorFlow, PyTorch",Master,0,Media,2024-09-14,2024-11-23,679,6.6,Digital Transformation LLC +AI14713,Machine Learning Engineer,73844,USD,73844,EN,PT,Denmark,M,Denmark,50,"SQL, Statistics, MLOps, Mathematics",Associate,0,Transportation,2024-04-03,2024-05-20,1162,7,DataVision Ltd +AI14714,NLP Engineer,53224,USD,53224,EN,PT,Israel,S,Israel,50,"Python, Mathematics, Kubernetes",Associate,0,Telecommunications,2024-11-29,2025-01-30,1152,7.7,TechCorp Inc +AI14715,NLP Engineer,96148,USD,96148,EN,FL,Norway,L,Norway,50,"SQL, GCP, Kubernetes, PyTorch",Associate,0,Transportation,2025-02-18,2025-05-02,1244,9.6,Advanced Robotics +AI14716,AI Research Scientist,61479,USD,61479,MI,FL,South Korea,M,South Korea,50,"Docker, Hadoop, TensorFlow, Spark",Master,3,Finance,2024-06-19,2024-07-15,1985,6,Predictive Systems +AI14717,AI Product Manager,89485,CHF,80537,EN,FL,Switzerland,L,Switzerland,50,"Scala, GCP, Statistics, Python",Master,1,Automotive,2025-03-13,2025-05-08,660,5.9,TechCorp Inc +AI14718,AI Specialist,119054,AUD,160723,MI,FT,Australia,L,Australia,100,"Git, Python, R",PhD,2,Manufacturing,2024-10-02,2024-11-15,1819,8.1,Neural Networks Co +AI14719,Data Scientist,39720,USD,39720,SE,FT,India,S,India,0,"R, Kubernetes, Python",Bachelor,9,Automotive,2024-01-14,2024-03-07,580,7.3,DeepTech Ventures +AI14720,Deep Learning Engineer,148540,GBP,111405,SE,FT,United Kingdom,L,United Kingdom,100,"Hadoop, Computer Vision, Git, Azure, Tableau",Master,5,Retail,2025-04-11,2025-05-09,643,6.5,Advanced Robotics +AI14721,AI Architect,67388,USD,67388,EN,PT,Ireland,S,Ireland,0,"MLOps, SQL, Linux, Git",Master,1,Media,2024-04-11,2024-05-19,835,5.6,Advanced Robotics +AI14722,Machine Learning Researcher,71198,USD,71198,MI,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, AWS",PhD,3,Government,2024-09-26,2024-10-28,2030,5.2,TechCorp Inc +AI14723,Computer Vision Engineer,114413,USD,114413,MI,PT,United States,L,United States,0,"MLOps, PyTorch, Kubernetes, TensorFlow, AWS",PhD,4,Real Estate,2024-07-12,2024-09-12,1436,7.9,Digital Transformation LLC +AI14724,AI Research Scientist,75404,USD,75404,EN,PT,United States,M,United States,50,"Python, Hadoop, Java, TensorFlow, Computer Vision",Associate,0,Transportation,2024-10-17,2024-11-16,2155,5.8,Quantum Computing Inc +AI14725,Data Scientist,72723,USD,72723,MI,FL,South Korea,M,South Korea,0,"Computer Vision, Python, SQL, R",Bachelor,3,Technology,2024-01-18,2024-02-13,2430,9.7,Predictive Systems +AI14726,Data Analyst,87914,USD,87914,EX,CT,China,M,China,100,"Spark, Python, Git, Docker",PhD,14,Technology,2024-08-22,2024-09-13,1342,6.6,Smart Analytics +AI14727,Machine Learning Engineer,121462,EUR,103243,SE,CT,Germany,L,Germany,0,"Kubernetes, Java, Computer Vision",Associate,7,Healthcare,2024-03-08,2024-04-08,1728,8.5,Future Systems +AI14728,AI Specialist,28481,USD,28481,EN,FL,China,S,China,50,"Scala, Spark, Git",Associate,0,Energy,2025-01-04,2025-02-12,2191,7.9,Advanced Robotics +AI14729,AI Consultant,168933,SGD,219613,EX,CT,Singapore,L,Singapore,0,"Linux, MLOps, Python, TensorFlow, NLP",Bachelor,11,Automotive,2024-05-22,2024-07-08,2084,9.9,Neural Networks Co +AI14730,AI Consultant,116189,USD,116189,MI,CT,Sweden,L,Sweden,50,"Python, GCP, Tableau, Deep Learning",PhD,3,Education,2024-05-04,2024-06-15,1686,6.9,Neural Networks Co +AI14731,Autonomous Systems Engineer,162901,USD,162901,EX,FL,Norway,S,Nigeria,0,"Scala, Kubernetes, Linux, NLP",PhD,12,Retail,2024-04-21,2024-05-14,1580,7.4,AI Innovations +AI14732,Data Scientist,312986,USD,312986,EX,CT,Norway,M,Norway,0,"Git, Docker, Deep Learning, Hadoop",Associate,17,Technology,2024-05-23,2024-07-21,2326,6.7,Autonomous Tech +AI14733,Data Engineer,118449,EUR,100682,SE,PT,France,L,France,100,"Python, TensorFlow, Azure, Computer Vision",Associate,8,Manufacturing,2024-02-27,2024-05-07,2232,6.7,DataVision Ltd +AI14734,AI Research Scientist,105386,EUR,89578,MI,PT,Germany,M,Germany,0,"Java, Mathematics, Kubernetes",Bachelor,2,Finance,2024-06-08,2024-08-14,1140,8.7,TechCorp Inc +AI14735,AI Specialist,79025,EUR,67171,MI,FL,Netherlands,S,Netherlands,50,"Python, MLOps, Git, TensorFlow",Bachelor,3,Technology,2024-02-05,2024-04-09,686,5.1,Predictive Systems +AI14736,Research Scientist,102196,USD,102196,MI,PT,Sweden,M,Russia,100,"Python, Spark, Hadoop, Statistics",Master,2,Gaming,2024-01-15,2024-03-10,1781,6.5,DeepTech Ventures +AI14737,NLP Engineer,67175,EUR,57099,EN,FL,Austria,S,Austria,50,"Deep Learning, PyTorch, Linux, Java, AWS",Bachelor,1,Retail,2024-08-25,2024-10-23,782,9.3,Machine Intelligence Group +AI14738,ML Ops Engineer,59042,AUD,79707,EN,CT,Australia,S,Australia,0,"Data Visualization, SQL, Statistics, MLOps, Spark",PhD,1,Manufacturing,2024-06-19,2024-08-02,1419,6.6,Machine Intelligence Group +AI14739,AI Consultant,245998,CHF,221398,EX,PT,Switzerland,S,Russia,100,"Python, Mathematics, Scala, GCP",Associate,15,Consulting,2024-04-12,2024-05-24,1628,9.4,Future Systems +AI14740,AI Specialist,48852,SGD,63508,EN,CT,Singapore,S,Singapore,0,"Docker, TensorFlow, Git, GCP, AWS",Master,0,Finance,2025-01-18,2025-02-25,2134,8.4,Digital Transformation LLC +AI14741,AI Software Engineer,133871,EUR,113790,SE,CT,Netherlands,S,Netherlands,100,"Python, TensorFlow, Statistics, PyTorch, Git",Master,9,Technology,2024-03-13,2024-05-22,736,5.1,Quantum Computing Inc +AI14742,Machine Learning Researcher,210751,CHF,189676,EX,FT,Switzerland,S,Switzerland,100,"SQL, GCP, Spark",Associate,16,Government,2024-09-12,2024-09-29,506,5,Cognitive Computing +AI14743,Machine Learning Researcher,178193,CHF,160374,SE,PT,Switzerland,S,South Africa,0,"Python, SQL, Azure, TensorFlow, Git",Associate,5,Consulting,2024-11-29,2025-01-11,2214,5.5,TechCorp Inc +AI14744,Robotics Engineer,119308,USD,119308,SE,FL,Sweden,M,Sweden,100,"Scala, R, Azure",Master,5,Manufacturing,2024-01-20,2024-02-26,857,7.9,Future Systems +AI14745,Robotics Engineer,153010,EUR,130059,EX,FT,Austria,L,Austria,50,"Python, SQL, Java, Docker",Master,17,Consulting,2024-07-12,2024-08-24,2272,9.5,Neural Networks Co +AI14746,Principal Data Scientist,52312,AUD,70621,EN,FL,Australia,S,Australia,50,"SQL, Kubernetes, Docker",Master,1,Transportation,2024-06-28,2024-08-29,1897,9.4,Quantum Computing Inc +AI14747,NLP Engineer,240647,AUD,324873,EX,FL,Australia,M,Sweden,0,"Docker, NLP, Linux, Python",Bachelor,17,Government,2025-03-06,2025-05-05,1227,9,Digital Transformation LLC +AI14748,Autonomous Systems Engineer,68811,EUR,58489,EN,FT,Germany,M,Germany,0,"Spark, Linux, GCP, Scala",Associate,1,Energy,2025-02-18,2025-03-05,791,9.9,Digital Transformation LLC +AI14749,Data Engineer,133800,SGD,173940,MI,FT,Singapore,L,Belgium,100,"SQL, Docker, Java, R",Bachelor,2,Manufacturing,2024-05-08,2024-06-23,944,5.6,DeepTech Ventures +AI14750,AI Research Scientist,110037,AUD,148550,MI,PT,Australia,L,Australia,50,"SQL, Kubernetes, Tableau, Hadoop",Associate,2,Telecommunications,2025-04-13,2025-05-29,1320,6,Autonomous Tech +AI14751,Machine Learning Researcher,43790,USD,43790,SE,PT,India,L,Chile,50,"R, SQL, GCP",Associate,6,Education,2024-05-16,2024-07-25,850,10,Cloud AI Solutions +AI14752,AI Specialist,101457,USD,101457,MI,CT,Ireland,M,Argentina,50,"Python, SQL, Azure",PhD,4,Education,2024-05-12,2024-06-29,2256,7.5,DataVision Ltd +AI14753,AI Specialist,82442,SGD,107175,MI,FL,Singapore,S,Singapore,100,"AWS, TensorFlow, Git",Associate,3,Transportation,2024-02-28,2024-03-16,2365,8.8,Machine Intelligence Group +AI14754,AI Product Manager,76359,USD,76359,EN,CT,Israel,L,Israel,0,"Hadoop, MLOps, Java, Computer Vision, Mathematics",PhD,0,Education,2024-01-31,2024-03-19,1856,9.6,Advanced Robotics +AI14755,AI Specialist,166212,USD,166212,SE,PT,Sweden,L,Sweden,100,"Linux, Spark, Computer Vision, Data Visualization, Python",PhD,7,Manufacturing,2024-04-24,2024-06-27,1511,7.3,Future Systems +AI14756,Head of AI,74070,EUR,62960,MI,FL,Austria,M,Austria,0,"Python, Statistics, Computer Vision",Master,4,Media,2024-01-01,2024-02-25,708,9.8,Cognitive Computing +AI14757,Machine Learning Researcher,23662,USD,23662,EN,FT,India,S,India,0,"SQL, Data Visualization, PyTorch",PhD,0,Real Estate,2024-10-02,2024-10-25,2397,7.1,Machine Intelligence Group +AI14758,Data Scientist,68764,EUR,58449,EN,FL,France,M,Estonia,0,"GCP, TensorFlow, Azure",Bachelor,1,Consulting,2024-09-09,2024-10-14,1164,7,Quantum Computing Inc +AI14759,Research Scientist,55947,USD,55947,EN,CT,Sweden,M,Sweden,100,"Mathematics, Java, PyTorch, Azure",Associate,0,Real Estate,2025-04-21,2025-05-19,806,9,Future Systems +AI14760,AI Product Manager,174977,CHF,157479,SE,PT,Switzerland,L,Switzerland,50,"Tableau, Computer Vision, Spark, Azure, SQL",Master,7,Automotive,2024-08-21,2024-10-11,1609,9.6,Predictive Systems +AI14761,Principal Data Scientist,141796,SGD,184335,SE,PT,Singapore,S,Singapore,50,"Scala, Spark, Python, TensorFlow, Computer Vision",Bachelor,8,Government,2024-04-05,2024-05-09,1338,8.1,AI Innovations +AI14762,Machine Learning Researcher,72370,USD,72370,EX,FL,China,S,China,0,"SQL, Python, Spark, Deep Learning, MLOps",Associate,11,Technology,2024-07-26,2024-08-23,1131,6.9,Autonomous Tech +AI14763,NLP Engineer,90342,EUR,76791,EN,FL,Germany,L,Argentina,50,"Kubernetes, NLP, SQL, PyTorch, R",Associate,0,Manufacturing,2024-08-19,2024-09-03,810,7.3,TechCorp Inc +AI14764,AI Software Engineer,65389,AUD,88275,EN,CT,Australia,S,Poland,0,"Java, Spark, Python, Azure, AWS",PhD,1,Energy,2024-03-02,2024-04-13,848,6.3,TechCorp Inc +AI14765,Robotics Engineer,191753,AUD,258867,EX,FT,Australia,S,Argentina,50,"R, Kubernetes, Scala, Deep Learning, Mathematics",Associate,18,Government,2024-05-06,2024-06-07,1998,5.8,Machine Intelligence Group +AI14766,Computer Vision Engineer,87202,GBP,65402,MI,FT,United Kingdom,S,United Kingdom,50,"Docker, SQL, Java, TensorFlow",Associate,4,Education,2024-04-20,2024-06-22,726,6.4,DeepTech Ventures +AI14767,Research Scientist,78313,USD,78313,MI,FL,Finland,M,Finland,50,"SQL, Data Visualization, Java",Associate,4,Education,2024-09-19,2024-11-04,1662,6.6,Neural Networks Co +AI14768,Principal Data Scientist,65799,USD,65799,EN,FT,United States,M,United States,0,"NLP, R, Kubernetes",PhD,0,Real Estate,2025-01-10,2025-03-14,1239,9.1,Advanced Robotics +AI14769,Research Scientist,29517,USD,29517,EN,CT,China,M,Mexico,50,"GCP, SQL, MLOps, NLP",Associate,0,Technology,2024-08-26,2024-11-05,2343,8.9,Digital Transformation LLC +AI14770,AI Product Manager,81826,USD,81826,EX,CT,India,L,India,0,"PyTorch, SQL, Kubernetes, Statistics",Associate,13,Transportation,2025-02-11,2025-04-07,1718,5.1,DeepTech Ventures +AI14771,Principal Data Scientist,117961,AUD,159247,MI,CT,Australia,L,Australia,100,"Data Visualization, GCP, Hadoop, MLOps",Bachelor,4,Education,2024-12-18,2025-01-01,1811,6.5,DeepTech Ventures +AI14772,AI Specialist,120810,USD,120810,EX,CT,China,L,Japan,100,"Mathematics, Python, Tableau",Bachelor,17,Automotive,2025-01-13,2025-01-27,2403,8.4,Cognitive Computing +AI14773,Data Analyst,43667,USD,43667,MI,FT,China,M,Israel,50,"Spark, Python, Docker, Git",Master,4,Education,2024-05-17,2024-06-22,1403,8.6,Predictive Systems +AI14774,Head of AI,128893,USD,128893,SE,FT,Finland,M,Finland,50,"Java, Linux, Deep Learning, Spark, Mathematics",Master,6,Transportation,2024-06-26,2024-07-13,1199,6.7,Quantum Computing Inc +AI14775,ML Ops Engineer,119069,CAD,148836,SE,FT,Canada,M,Canada,50,"PyTorch, GCP, TensorFlow",Bachelor,8,Energy,2024-07-24,2024-09-30,2205,7.6,Machine Intelligence Group +AI14776,NLP Engineer,66333,AUD,89550,EN,FL,Australia,M,Australia,100,"SQL, Kubernetes, Hadoop",Bachelor,1,Retail,2024-09-30,2024-10-21,2227,6.8,Algorithmic Solutions +AI14777,Machine Learning Researcher,89432,USD,89432,MI,FT,South Korea,L,South Korea,0,"GCP, Data Visualization, Kubernetes, Docker",Associate,2,Education,2025-02-28,2025-04-17,1204,8.6,Predictive Systems +AI14778,AI Consultant,56324,EUR,47875,EN,FL,Netherlands,S,Latvia,100,"Git, Mathematics, R",Associate,1,Retail,2024-01-18,2024-03-15,853,9.1,Machine Intelligence Group +AI14779,Research Scientist,145285,USD,145285,MI,FT,United States,L,United States,100,"R, Mathematics, Kubernetes, NLP",Associate,3,Gaming,2024-04-04,2024-05-07,1091,6.9,Future Systems +AI14780,AI Product Manager,227003,USD,227003,EX,FL,Israel,L,China,50,"SQL, AWS, GCP, Kubernetes",Associate,19,Education,2024-01-21,2024-03-23,858,5,Cloud AI Solutions +AI14781,Deep Learning Engineer,123976,EUR,105380,EX,CT,Germany,S,Germany,0,"Linux, Hadoop, Spark, Python",Bachelor,12,Education,2024-09-08,2024-11-08,742,7.2,Quantum Computing Inc +AI14782,Principal Data Scientist,63982,USD,63982,EN,PT,Sweden,S,Sweden,100,"Scala, TensorFlow, MLOps, Git, Computer Vision",Associate,1,Telecommunications,2024-07-08,2024-08-23,1255,8.9,TechCorp Inc +AI14783,Data Scientist,26617,USD,26617,EN,CT,India,M,India,0,"GCP, Kubernetes, Mathematics, NLP",Associate,0,Gaming,2025-04-21,2025-05-16,1994,8.2,Autonomous Tech +AI14784,Data Scientist,213307,CHF,191976,EX,FT,Switzerland,S,Switzerland,50,"Computer Vision, Python, TensorFlow, Linux",Bachelor,19,Education,2024-12-12,2025-02-21,2249,6.8,Cognitive Computing +AI14785,Machine Learning Engineer,68856,USD,68856,MI,CT,Finland,M,Finland,0,"GCP, Python, Spark",Associate,4,Government,2024-10-16,2024-10-31,1095,9.7,Autonomous Tech +AI14786,Head of AI,75179,USD,75179,EN,FT,United States,S,United States,0,"Kubernetes, Python, Linux, AWS, Deep Learning",PhD,0,Healthcare,2024-12-03,2025-01-22,1923,8.3,Autonomous Tech +AI14787,ML Ops Engineer,164858,AUD,222558,SE,FT,Australia,L,Australia,0,"AWS, Azure, PyTorch, Data Visualization",Bachelor,6,Gaming,2024-08-26,2024-10-31,1342,8.6,Autonomous Tech +AI14788,AI Software Engineer,70806,USD,70806,SE,FL,China,M,Germany,50,"Tableau, Spark, Scala",PhD,6,Manufacturing,2024-06-24,2024-08-16,1063,8.6,Digital Transformation LLC +AI14789,ML Ops Engineer,118788,USD,118788,SE,FT,Finland,L,Mexico,50,"Hadoop, Python, SQL",Master,7,Education,2025-04-29,2025-05-26,1420,9.1,Neural Networks Co +AI14790,AI Software Engineer,60352,AUD,81475,EN,FT,Australia,M,New Zealand,50,"Kubernetes, Java, MLOps, Azure",PhD,1,Energy,2024-01-29,2024-02-22,808,9.6,Digital Transformation LLC +AI14791,AI Software Engineer,87016,CAD,108770,MI,PT,Canada,L,South Korea,50,"Tableau, Docker, Java, GCP",Master,4,Healthcare,2024-02-16,2024-04-13,1869,6,Quantum Computing Inc +AI14792,Principal Data Scientist,192474,AUD,259840,EX,FL,Australia,M,Turkey,50,"Linux, R, Tableau",PhD,11,Finance,2024-01-21,2024-04-01,1558,7.5,Cloud AI Solutions +AI14793,Head of AI,83774,JPY,9215140,MI,FT,Japan,S,Japan,0,"NLP, TensorFlow, Scala, Docker",Associate,3,Energy,2024-10-06,2024-11-18,1800,6.6,Machine Intelligence Group +AI14794,Data Scientist,177589,CHF,159830,SE,CT,Switzerland,S,Switzerland,50,"Kubernetes, Python, TensorFlow, PyTorch, R",Associate,7,Education,2024-01-28,2024-04-03,1582,5.6,DeepTech Ventures +AI14795,Computer Vision Engineer,63063,USD,63063,EN,FT,Sweden,L,Argentina,50,"R, Hadoop, Linux, Statistics, Spark",PhD,1,Healthcare,2025-04-02,2025-04-24,557,7.9,Cognitive Computing +AI14796,AI Specialist,32842,USD,32842,MI,FT,India,L,Romania,100,"Python, Git, Data Visualization, Java, Statistics",Master,3,Telecommunications,2024-07-20,2024-08-26,2406,5.8,Cognitive Computing +AI14797,Robotics Engineer,307133,USD,307133,EX,FT,Norway,M,Norway,0,"PyTorch, Hadoop, Scala",Master,18,Manufacturing,2025-03-06,2025-05-11,1874,5.8,Neural Networks Co +AI14798,Deep Learning Engineer,260543,JPY,28659730,EX,CT,Japan,M,Latvia,100,"R, Mathematics, Deep Learning",PhD,17,Manufacturing,2025-01-16,2025-03-29,1213,5.5,Quantum Computing Inc +AI14799,AI Specialist,44958,USD,44958,SE,PT,China,S,China,0,"GCP, Azure, NLP",Associate,9,Gaming,2024-11-22,2025-01-17,684,6.2,Smart Analytics +AI14800,Head of AI,131487,AUD,177507,SE,CT,Australia,S,Australia,50,"Python, R, TensorFlow, Deep Learning",PhD,8,Real Estate,2025-04-24,2025-06-18,1130,7.6,Advanced Robotics +AI14801,AI Architect,59373,EUR,50467,EN,PT,Netherlands,M,Netherlands,100,"Python, Mathematics, TensorFlow, Kubernetes",Master,0,Consulting,2024-11-30,2025-01-05,1456,8.2,Smart Analytics +AI14802,Machine Learning Engineer,142471,USD,142471,SE,FT,Finland,M,Finland,50,"TensorFlow, Hadoop, Data Visualization, NLP",Associate,9,Technology,2024-11-18,2024-12-24,1489,6.2,Digital Transformation LLC +AI14803,AI Specialist,33282,USD,33282,MI,PT,India,L,India,50,"SQL, Azure, Kubernetes, Deep Learning",PhD,3,Energy,2024-12-21,2025-01-30,2210,6.1,Autonomous Tech +AI14804,AI Architect,70038,EUR,59532,MI,FL,Austria,M,Austria,50,"Git, PyTorch, Deep Learning",Associate,3,Finance,2024-03-12,2024-03-28,1625,8.5,Machine Intelligence Group +AI14805,Machine Learning Engineer,74946,USD,74946,EN,CT,Denmark,M,Austria,100,"SQL, Java, Azure",Bachelor,0,Government,2024-12-16,2025-02-02,2150,9.3,Algorithmic Solutions +AI14806,Data Scientist,45967,USD,45967,MI,FL,China,S,Ghana,50,"SQL, Computer Vision, AWS",PhD,3,Gaming,2024-11-19,2024-12-21,1627,7.2,Future Systems +AI14807,Principal Data Scientist,292646,SGD,380440,EX,PT,Singapore,L,Singapore,50,"GCP, Git, Azure",PhD,14,Energy,2024-04-23,2024-05-11,846,7.6,Neural Networks Co +AI14808,Data Scientist,133770,USD,133770,MI,PT,United States,L,United States,100,"Java, Mathematics, SQL, PyTorch, Docker",Bachelor,2,Retail,2024-05-19,2024-07-15,2117,7.4,Predictive Systems +AI14809,Principal Data Scientist,103086,USD,103086,MI,CT,Sweden,M,Sweden,0,"Mathematics, SQL, Tableau",Associate,3,Consulting,2024-03-10,2024-04-13,2029,5.9,Cognitive Computing +AI14810,Data Scientist,151977,USD,151977,EX,FT,Israel,S,Israel,100,"Java, PyTorch, Mathematics, Docker, Spark",Bachelor,18,Energy,2024-10-02,2024-10-24,792,7.3,Autonomous Tech +AI14811,AI Software Engineer,42791,USD,42791,MI,FL,India,L,Singapore,100,"Statistics, SQL, PyTorch, AWS",Master,2,Automotive,2024-06-29,2024-08-01,1814,6.1,Cognitive Computing +AI14812,Robotics Engineer,145130,USD,145130,EX,CT,Finland,M,Finland,50,"Java, Linux, Git, AWS",Associate,16,Transportation,2024-03-15,2024-04-30,1409,8.8,DataVision Ltd +AI14813,AI Specialist,50395,USD,50395,EN,CT,Finland,M,Thailand,0,"Git, NLP, Java, Python",PhD,1,Media,2024-12-28,2025-01-12,2037,9.8,TechCorp Inc +AI14814,Deep Learning Engineer,164649,EUR,139952,EX,FL,France,M,France,100,"Git, Python, Spark, Deep Learning",Associate,18,Energy,2025-03-20,2025-04-23,2316,9.6,Quantum Computing Inc +AI14815,Deep Learning Engineer,269435,EUR,229020,EX,PT,Netherlands,L,Netherlands,100,"Git, TensorFlow, Data Visualization",Associate,13,Real Estate,2024-10-23,2024-12-26,2295,9.9,Advanced Robotics +AI14816,Data Engineer,224881,USD,224881,SE,CT,Denmark,L,Denmark,0,"PyTorch, R, Docker, Statistics, Computer Vision",Bachelor,5,Technology,2024-05-16,2024-07-16,1110,9.6,AI Innovations +AI14817,Research Scientist,75931,JPY,8352410,EN,CT,Japan,S,Japan,50,"Azure, PyTorch, Mathematics, SQL, Python",Bachelor,1,Healthcare,2025-04-29,2025-07-02,1616,6.2,Algorithmic Solutions +AI14818,Machine Learning Researcher,138815,EUR,117993,SE,FT,Germany,M,Germany,100,"Statistics, Git, Data Visualization",Master,8,Energy,2025-04-13,2025-05-30,589,7.8,DataVision Ltd +AI14819,Head of AI,302646,CHF,272381,EX,PT,Switzerland,L,Switzerland,100,"Git, R, Hadoop",Associate,13,Finance,2024-03-08,2024-04-17,1931,7.7,Neural Networks Co +AI14820,Data Analyst,84254,AUD,113743,MI,PT,Australia,S,Australia,0,"Git, PyTorch, SQL",Bachelor,2,Education,2024-03-20,2024-05-22,1957,7,Cloud AI Solutions +AI14821,Robotics Engineer,91671,GBP,68753,MI,CT,United Kingdom,L,United Kingdom,100,"Spark, Tableau, Git, GCP",Associate,3,Retail,2024-08-29,2024-10-06,2086,5.6,AI Innovations +AI14822,NLP Engineer,140621,JPY,15468310,SE,PT,Japan,L,Japan,100,"Data Visualization, Python, Java, Statistics",Bachelor,8,Energy,2024-12-04,2025-01-11,1005,5.2,Neural Networks Co +AI14823,Robotics Engineer,93091,USD,93091,MI,PT,Israel,S,Israel,50,"Scala, AWS, Azure, Python",PhD,4,Telecommunications,2024-11-29,2024-12-20,2271,8,Cognitive Computing +AI14824,AI Architect,69964,USD,69964,MI,PT,Israel,S,Malaysia,100,"MLOps, PyTorch, Kubernetes, NLP, Mathematics",Bachelor,2,Consulting,2024-11-15,2025-01-24,2121,6.5,AI Innovations +AI14825,Deep Learning Engineer,235481,GBP,176611,EX,FL,United Kingdom,S,France,100,"Tableau, Linux, MLOps, Python",Master,14,Telecommunications,2024-02-01,2024-04-10,1339,7.5,Algorithmic Solutions +AI14826,Principal Data Scientist,104957,GBP,78718,MI,PT,United Kingdom,M,United Kingdom,0,"Computer Vision, PyTorch, SQL",PhD,3,Manufacturing,2024-06-09,2024-06-23,1178,7.2,Algorithmic Solutions +AI14827,AI Product Manager,70827,EUR,60203,EN,CT,Netherlands,L,Netherlands,0,"Scala, Hadoop, Python",Master,1,Gaming,2024-10-20,2024-12-06,1126,7.9,TechCorp Inc +AI14828,Data Engineer,125048,CAD,156310,SE,FL,Canada,M,Canada,0,"Python, Java, Docker",Master,8,Media,2025-04-26,2025-06-12,2044,7.3,DeepTech Ventures +AI14829,Research Scientist,212816,CAD,266020,EX,CT,Canada,M,Canada,50,"PyTorch, Python, Data Visualization, Kubernetes",Associate,15,Real Estate,2024-08-12,2024-09-29,658,6.7,Predictive Systems +AI14830,Head of AI,58316,USD,58316,EN,FT,Sweden,S,Germany,50,"Spark, Scala, GCP, Java, SQL",PhD,0,Gaming,2024-05-17,2024-07-18,2200,6.5,Future Systems +AI14831,NLP Engineer,100481,EUR,85409,MI,PT,Netherlands,L,Netherlands,100,"TensorFlow, Kubernetes, Spark",Associate,4,Manufacturing,2024-03-04,2024-04-20,2061,6.4,Cognitive Computing +AI14832,Head of AI,49599,USD,49599,MI,PT,China,L,China,100,"SQL, Kubernetes, GCP, Statistics, Hadoop",Master,2,Real Estate,2024-10-31,2024-12-15,708,5.8,DeepTech Ventures +AI14833,Data Analyst,79810,USD,79810,EN,PT,United States,S,Italy,50,"Python, Linux, NLP, TensorFlow, Hadoop",PhD,1,Healthcare,2025-03-24,2025-05-08,2386,6.8,DataVision Ltd +AI14834,AI Architect,57873,USD,57873,SE,FT,China,L,Luxembourg,50,"Kubernetes, Data Visualization, Java, PyTorch, NLP",Associate,9,Government,2024-07-13,2024-08-26,2487,5.4,Digital Transformation LLC +AI14835,Autonomous Systems Engineer,135214,SGD,175778,SE,CT,Singapore,S,Singapore,50,"R, SQL, Computer Vision, Java, Deep Learning",PhD,9,Education,2024-01-28,2024-03-01,2415,8.2,DataVision Ltd +AI14836,Principal Data Scientist,44068,USD,44068,EN,FL,South Korea,S,South Korea,50,"Git, Azure, Computer Vision",Associate,0,Energy,2024-05-30,2024-07-18,1291,6.8,Cloud AI Solutions +AI14837,ML Ops Engineer,218509,USD,218509,EX,CT,United States,S,Malaysia,100,"GCP, TensorFlow, Hadoop, Mathematics, SQL",PhD,19,Finance,2024-08-15,2024-09-04,2459,5.5,Autonomous Tech +AI14838,NLP Engineer,210813,CHF,189732,EX,CT,Switzerland,S,Switzerland,100,"NLP, Git, Data Visualization",Associate,10,Telecommunications,2024-03-25,2024-04-18,857,7.3,Digital Transformation LLC +AI14839,AI Architect,55157,SGD,71704,EN,FL,Singapore,S,Singapore,0,"Python, TensorFlow, Azure, Computer Vision",PhD,0,Finance,2024-06-01,2024-07-01,1582,9.5,Smart Analytics +AI14840,Deep Learning Engineer,70464,EUR,59894,EN,CT,France,M,France,0,"Mathematics, SQL, Tableau, PyTorch",Bachelor,1,Telecommunications,2025-04-27,2025-05-21,643,5.5,Smart Analytics +AI14841,Head of AI,55034,GBP,41276,EN,FL,United Kingdom,M,Sweden,100,"PyTorch, Docker, Data Visualization, Java, Spark",Bachelor,1,Government,2024-09-09,2024-10-05,1608,7,Digital Transformation LLC +AI14842,Machine Learning Engineer,278029,CHF,250226,EX,CT,Switzerland,M,Switzerland,100,"GCP, NLP, SQL, Python, Hadoop",Bachelor,10,Technology,2024-07-17,2024-08-17,1027,9,Smart Analytics +AI14843,ML Ops Engineer,100795,EUR,85676,SE,FT,Austria,S,France,100,"Python, SQL, NLP, Linux",Associate,7,Automotive,2025-04-26,2025-06-28,1660,5.5,AI Innovations +AI14844,Machine Learning Researcher,75234,USD,75234,MI,FL,South Korea,S,Malaysia,50,"Computer Vision, Python, Hadoop, AWS",PhD,3,Telecommunications,2024-05-28,2024-07-27,1864,5.6,DeepTech Ventures +AI14845,Machine Learning Researcher,149192,USD,149192,EX,FL,Sweden,S,Sweden,100,"Linux, Python, Data Visualization, TensorFlow",Master,16,Real Estate,2024-07-27,2024-09-08,646,5.8,Autonomous Tech +AI14846,AI Consultant,182753,USD,182753,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, AWS",Master,11,Real Estate,2025-02-27,2025-04-10,2315,10,DeepTech Ventures +AI14847,Principal Data Scientist,134537,EUR,114356,SE,PT,Austria,M,Austria,0,"Python, Tableau, Java, GCP, TensorFlow",Associate,7,Government,2025-04-03,2025-05-05,965,8.4,Predictive Systems +AI14848,ML Ops Engineer,97397,EUR,82787,MI,FT,Netherlands,L,Netherlands,0,"SQL, Kubernetes, Git",Associate,4,Transportation,2025-01-22,2025-03-29,549,10,AI Innovations +AI14849,AI Product Manager,37126,USD,37126,MI,PT,India,M,India,50,"R, Python, Statistics, Docker",PhD,2,Education,2024-05-30,2024-08-08,1709,8.7,Neural Networks Co +AI14850,AI Research Scientist,67086,USD,67086,MI,FT,South Korea,S,Egypt,50,"Computer Vision, Scala, NLP",Bachelor,3,Education,2024-02-27,2024-04-30,821,5.6,Future Systems +AI14851,AI Specialist,62522,USD,62522,EX,FT,India,S,Germany,100,"Spark, AWS, Scala",Associate,14,Consulting,2025-03-11,2025-04-27,1422,9.7,Future Systems +AI14852,AI Product Manager,107430,AUD,145031,SE,FT,Australia,S,Australia,0,"Git, NLP, Docker, Scala",Master,7,Healthcare,2024-09-02,2024-10-12,1641,9.6,Advanced Robotics +AI14853,AI Architect,115217,CAD,144021,SE,FT,Canada,S,Canada,0,"Kubernetes, SQL, Docker",Bachelor,7,Manufacturing,2024-10-18,2024-11-20,753,9.3,Digital Transformation LLC +AI14854,Head of AI,142120,USD,142120,SE,FT,Denmark,S,Denmark,0,"Scala, Python, AWS, TensorFlow",Associate,6,Healthcare,2024-09-29,2024-10-31,2135,5.2,Cognitive Computing +AI14855,AI Consultant,92445,CAD,115556,MI,FT,Canada,M,Canada,0,"R, TensorFlow, Scala, Git, Computer Vision",Master,4,Real Estate,2024-11-29,2025-01-06,2134,8.9,Digital Transformation LLC +AI14856,Data Scientist,41824,USD,41824,SE,CT,India,L,New Zealand,50,"MLOps, GCP, R, Azure",Associate,6,Retail,2024-05-17,2024-07-21,994,8.6,Autonomous Tech +AI14857,ML Ops Engineer,51207,CAD,64009,EN,FL,Canada,M,Canada,50,"SQL, PyTorch, Git, AWS",PhD,0,Healthcare,2025-01-10,2025-02-06,745,6.5,Cognitive Computing +AI14858,AI Software Engineer,96900,CHF,87210,MI,PT,Switzerland,S,Switzerland,100,"TensorFlow, Mathematics, Hadoop, Data Visualization",PhD,3,Consulting,2024-07-17,2024-08-28,2381,9.4,Smart Analytics +AI14859,Machine Learning Engineer,139440,EUR,118524,SE,FT,Austria,L,Portugal,50,"SQL, Deep Learning, Tableau, GCP",PhD,7,Education,2024-10-01,2024-11-07,898,8,AI Innovations +AI14860,Data Engineer,149725,USD,149725,SE,FT,Finland,L,Finland,100,"MLOps, Computer Vision, SQL, Mathematics, Data Visualization",Bachelor,5,Healthcare,2024-11-12,2025-01-01,1796,8.6,Quantum Computing Inc +AI14861,AI Software Engineer,95613,CHF,86052,EN,FL,Switzerland,S,Switzerland,100,"SQL, PyTorch, Data Visualization, Deep Learning",PhD,0,Manufacturing,2024-01-14,2024-02-05,2410,8.1,Machine Intelligence Group +AI14862,Deep Learning Engineer,84360,EUR,71706,MI,PT,Austria,M,Austria,50,"TensorFlow, Scala, Statistics",Bachelor,2,Media,2025-04-23,2025-05-31,1028,5,TechCorp Inc +AI14863,Principal Data Scientist,109354,EUR,92951,MI,CT,Austria,L,Austria,100,"Statistics, PyTorch, NLP, AWS, Linux",Master,3,Finance,2025-01-13,2025-02-17,1507,6.5,Predictive Systems +AI14864,AI Product Manager,49153,USD,49153,EN,FL,South Korea,M,South Korea,0,"TensorFlow, Deep Learning, Docker",Bachelor,0,Automotive,2024-02-26,2024-03-16,1274,6.4,Predictive Systems +AI14865,AI Specialist,79494,USD,79494,MI,FT,South Korea,M,Vietnam,100,"Kubernetes, SQL, Data Visualization, Mathematics",Bachelor,4,Government,2024-05-30,2024-08-05,1674,5.1,Future Systems +AI14866,AI Architect,99985,JPY,10998350,MI,PT,Japan,L,Japan,100,"Git, SQL, Hadoop",PhD,3,Real Estate,2024-09-14,2024-11-16,2196,8.1,Autonomous Tech +AI14867,Data Scientist,82532,JPY,9078520,EN,PT,Japan,L,Japan,50,"Hadoop, Python, Docker, Mathematics",Bachelor,0,Healthcare,2024-07-11,2024-08-09,1231,9.1,Autonomous Tech +AI14868,Autonomous Systems Engineer,295948,USD,295948,EX,FT,Norway,M,Romania,50,"SQL, Scala, Python",PhD,12,Healthcare,2024-05-01,2024-06-05,630,9.7,Quantum Computing Inc +AI14869,AI Architect,62843,USD,62843,MI,CT,Finland,S,Finland,50,"R, SQL, TensorFlow, AWS, Python",PhD,3,Manufacturing,2024-07-16,2024-07-30,2195,9.7,Predictive Systems +AI14870,Data Scientist,209564,CHF,188608,EX,FT,Switzerland,M,Switzerland,100,"TensorFlow, Git, Scala",Associate,17,Manufacturing,2024-08-23,2024-09-11,1446,5.4,Algorithmic Solutions +AI14871,NLP Engineer,152425,USD,152425,MI,FT,Denmark,L,Denmark,50,"Spark, R, SQL, Python",Bachelor,4,Manufacturing,2024-09-18,2024-11-29,911,5.9,Machine Intelligence Group +AI14872,Robotics Engineer,84147,USD,84147,MI,CT,South Korea,L,South Korea,50,"SQL, Python, Java, Git",PhD,4,Education,2024-10-08,2024-11-09,2252,8.4,Autonomous Tech +AI14873,Data Scientist,119112,USD,119112,MI,CT,Ireland,L,Ireland,100,"Scala, TensorFlow, Mathematics, Java",Associate,2,Consulting,2024-01-24,2024-03-24,945,8.6,Machine Intelligence Group +AI14874,Data Engineer,49882,USD,49882,SE,PT,China,S,China,50,"Java, PyTorch, Kubernetes",Master,8,Manufacturing,2024-06-02,2024-07-18,966,5.4,DeepTech Ventures +AI14875,Data Scientist,223969,USD,223969,EX,CT,Denmark,S,Russia,100,"SQL, Kubernetes, TensorFlow",Master,18,Real Estate,2024-08-30,2024-10-28,1774,6.1,Advanced Robotics +AI14876,Head of AI,118219,USD,118219,MI,PT,Norway,L,Norway,50,"Mathematics, Tableau, Python, Deep Learning, Kubernetes",PhD,2,Telecommunications,2024-07-14,2024-08-15,819,8.8,DataVision Ltd +AI14877,Research Scientist,53669,EUR,45619,EN,CT,Netherlands,S,Netherlands,100,"Scala, Mathematics, MLOps, Java",Master,1,Education,2025-01-28,2025-03-30,820,9.6,Machine Intelligence Group +AI14878,Research Scientist,103628,USD,103628,MI,FT,Ireland,L,Japan,50,"PyTorch, Mathematics, Spark, TensorFlow",Associate,4,Media,2024-12-27,2025-02-16,1923,5.3,Predictive Systems +AI14879,AI Specialist,56178,CAD,70223,EN,FT,Canada,S,Canada,0,"Linux, MLOps, Hadoop, PyTorch",Bachelor,0,Telecommunications,2024-05-02,2024-06-04,2267,9.5,Machine Intelligence Group +AI14880,AI Software Engineer,146442,USD,146442,SE,PT,United States,L,United States,50,"Spark, TensorFlow, Mathematics, MLOps, Data Visualization",Bachelor,9,Healthcare,2024-05-01,2024-06-12,2052,6.5,Cognitive Computing +AI14881,Computer Vision Engineer,63769,GBP,47827,EN,CT,United Kingdom,L,Norway,50,"PyTorch, Python, Data Visualization, SQL, Docker",Associate,1,Gaming,2024-01-30,2024-03-23,1175,8.2,Smart Analytics +AI14882,AI Software Engineer,24026,USD,24026,EN,FT,India,L,India,50,"Java, SQL, Hadoop, GCP",Master,0,Energy,2024-11-20,2025-01-31,1643,7.3,Cloud AI Solutions +AI14883,Deep Learning Engineer,128886,EUR,109553,SE,FL,France,S,France,0,"Kubernetes, Scala, Linux",Master,7,Healthcare,2025-02-11,2025-03-04,559,9.1,Future Systems +AI14884,Data Engineer,86675,EUR,73674,EN,CT,Netherlands,L,Ukraine,50,"Python, TensorFlow, MLOps, PyTorch, Spark",Master,0,Media,2025-03-19,2025-05-12,954,7.9,Smart Analytics +AI14885,Principal Data Scientist,112837,USD,112837,SE,FT,Finland,L,Ukraine,100,"Python, Java, Scala, AWS",Master,7,Government,2025-02-26,2025-03-25,1527,7.3,AI Innovations +AI14886,AI Specialist,79915,CAD,99894,MI,CT,Canada,L,Ireland,100,"PyTorch, Spark, Scala, SQL, TensorFlow",PhD,3,Government,2024-06-15,2024-07-24,1978,9.8,Algorithmic Solutions +AI14887,Principal Data Scientist,55583,EUR,47246,EN,CT,Germany,S,Germany,0,"SQL, Java, Statistics",Master,0,Government,2025-02-14,2025-03-04,1427,8.5,Quantum Computing Inc +AI14888,AI Consultant,102567,EUR,87182,MI,FL,France,L,France,0,"Scala, Mathematics, R, Hadoop, Computer Vision",PhD,2,Consulting,2024-01-15,2024-03-07,1168,7.6,Autonomous Tech +AI14889,Data Scientist,63765,EUR,54200,EN,FL,Austria,S,Austria,50,"Scala, Linux, NLP, Tableau",Associate,1,Healthcare,2024-11-23,2024-12-22,926,9.6,Quantum Computing Inc +AI14890,Research Scientist,109816,JPY,12079760,SE,PT,Japan,M,Japan,100,"Tableau, Python, Kubernetes, NLP",Bachelor,7,Gaming,2024-04-24,2024-06-23,2297,9.3,Predictive Systems +AI14891,Machine Learning Engineer,147705,EUR,125549,SE,FT,Austria,L,Turkey,100,"Spark, Kubernetes, Data Visualization",Associate,7,Telecommunications,2024-01-08,2024-02-19,1790,5.3,Machine Intelligence Group +AI14892,NLP Engineer,180262,USD,180262,EX,CT,South Korea,L,South Korea,100,"SQL, PyTorch, AWS, Deep Learning, TensorFlow",Master,14,Healthcare,2024-04-04,2024-05-06,984,8.7,Digital Transformation LLC +AI14893,Research Scientist,26108,USD,26108,MI,CT,India,M,Nigeria,50,"MLOps, Python, PyTorch, Java, SQL",Master,3,Retail,2024-01-12,2024-03-18,2323,7.5,TechCorp Inc +AI14894,Data Scientist,85429,AUD,115329,MI,FL,Australia,S,Portugal,50,"Computer Vision, TensorFlow, Python",Associate,2,Finance,2024-02-07,2024-03-04,1715,8.6,Digital Transformation LLC +AI14895,Data Scientist,85824,GBP,64368,EN,PT,United Kingdom,L,Sweden,0,"SQL, Spark, PyTorch, Mathematics",Associate,1,Healthcare,2024-01-15,2024-03-12,1941,7.1,Advanced Robotics +AI14896,Deep Learning Engineer,36761,USD,36761,MI,PT,China,S,China,0,"Python, Scala, Git",PhD,4,Government,2025-03-03,2025-03-22,1141,6.6,DeepTech Ventures +AI14897,Machine Learning Researcher,178346,USD,178346,SE,FL,United States,M,United States,50,"Java, NLP, MLOps",PhD,8,Technology,2025-01-22,2025-02-28,1669,10,Quantum Computing Inc +AI14898,Principal Data Scientist,210345,USD,210345,EX,FT,Denmark,L,Norway,0,"Mathematics, Hadoop, Kubernetes, Linux, Azure",PhD,19,Finance,2024-02-22,2024-05-01,1614,7,DeepTech Ventures +AI14899,AI Product Manager,219044,CAD,273805,EX,CT,Canada,L,Belgium,50,"Hadoop, R, Scala, Data Visualization",Master,18,Education,2024-01-26,2024-03-29,1456,7.7,Quantum Computing Inc +AI14900,Principal Data Scientist,64885,CAD,81106,EN,CT,Canada,L,South Africa,0,"AWS, Hadoop, R, Kubernetes",Associate,1,Retail,2024-06-10,2024-07-13,1036,8.2,Neural Networks Co +AI14901,Machine Learning Researcher,98266,JPY,10809260,EN,FT,Japan,L,Russia,0,"Linux, Statistics, Mathematics, Hadoop, PyTorch",PhD,0,Real Estate,2025-01-27,2025-04-05,1598,5.5,Advanced Robotics +AI14902,Head of AI,104995,USD,104995,SE,PT,Ireland,S,Ireland,50,"Scala, MLOps, Azure, Git, Computer Vision",PhD,6,Government,2025-04-04,2025-05-30,1420,9.8,Machine Intelligence Group +AI14903,Head of AI,150009,USD,150009,SE,PT,United States,S,United States,0,"Java, Deep Learning, TensorFlow",Associate,8,Gaming,2024-05-20,2024-07-31,1122,5.1,Autonomous Tech +AI14904,AI Architect,213345,USD,213345,SE,FL,Denmark,L,Ghana,50,"Python, Tableau, Azure, Spark, Kubernetes",Master,8,Telecommunications,2024-08-09,2024-09-30,1207,8.6,Neural Networks Co +AI14905,Machine Learning Engineer,105646,EUR,89799,MI,PT,Germany,M,Kenya,50,"Scala, Hadoop, AWS, Python, Statistics",Master,2,Consulting,2025-03-17,2025-04-19,884,8.6,Neural Networks Co +AI14906,Deep Learning Engineer,155943,EUR,132552,SE,PT,Germany,L,Germany,50,"Deep Learning, Spark, Git, Kubernetes",PhD,9,Gaming,2024-02-19,2024-03-20,1251,9.1,Future Systems +AI14907,Autonomous Systems Engineer,108937,EUR,92596,SE,FL,Germany,M,Ghana,0,"Python, TensorFlow, Kubernetes, Data Visualization, Computer Vision",Bachelor,7,Real Estate,2024-11-11,2024-11-29,2247,9.5,Predictive Systems +AI14908,Computer Vision Engineer,107249,CHF,96524,EN,PT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, SQL, Java, Scala",PhD,0,Consulting,2025-02-19,2025-04-02,2331,7.7,Neural Networks Co +AI14909,Machine Learning Engineer,92023,USD,92023,MI,FL,Ireland,S,Ireland,50,"TensorFlow, Java, SQL, R",PhD,3,Education,2025-03-06,2025-04-02,1052,5.7,DeepTech Ventures +AI14910,AI Architect,67935,USD,67935,MI,FT,Finland,S,Canada,100,"SQL, PyTorch, GCP",PhD,3,Energy,2024-01-06,2024-02-15,1292,5.1,Cognitive Computing +AI14911,AI Architect,35800,USD,35800,MI,CT,India,L,India,100,"TensorFlow, Mathematics, Azure, Scala, Java",Master,4,Technology,2024-10-26,2024-12-10,2131,9.1,DataVision Ltd +AI14912,Computer Vision Engineer,35601,USD,35601,SE,PT,India,S,India,50,"Python, MLOps, R, Statistics, Hadoop",Bachelor,6,Technology,2024-05-31,2024-07-15,729,7.6,AI Innovations +AI14913,Data Scientist,122019,EUR,103716,SE,PT,Netherlands,M,Netherlands,0,"Spark, PyTorch, GCP, Azure, Statistics",Master,7,Manufacturing,2024-05-13,2024-06-20,770,8.6,DataVision Ltd +AI14914,Data Analyst,65215,AUD,88040,EN,PT,Australia,S,Australia,50,"SQL, Scala, Computer Vision, Deep Learning",PhD,0,Manufacturing,2024-07-17,2024-08-19,1315,7.7,Future Systems +AI14915,Robotics Engineer,151010,USD,151010,SE,CT,Norway,S,Norway,50,"Hadoop, Spark, Data Visualization, SQL",Bachelor,9,Finance,2024-01-24,2024-02-22,2036,7.2,AI Innovations +AI14916,NLP Engineer,90626,USD,90626,MI,FT,Israel,L,Israel,0,"PyTorch, Docker, Deep Learning, GCP",Bachelor,4,Gaming,2024-10-06,2024-10-20,2024,7.5,Predictive Systems +AI14917,AI Research Scientist,114235,EUR,97100,MI,FT,Austria,L,Austria,100,"Hadoop, Python, NLP",Master,2,Transportation,2024-11-06,2024-12-21,1677,7.6,Advanced Robotics +AI14918,AI Consultant,99643,USD,99643,EN,FT,Norway,M,Norway,0,"TensorFlow, Kubernetes, GCP, Linux",Bachelor,0,Media,2024-08-02,2024-08-29,1430,5.1,TechCorp Inc +AI14919,Machine Learning Researcher,114099,USD,114099,SE,FT,United States,S,United States,0,"Hadoop, MLOps, SQL, Data Visualization",Bachelor,9,Automotive,2024-12-05,2025-02-11,589,5,Cloud AI Solutions +AI14920,Robotics Engineer,187262,SGD,243441,EX,FL,Singapore,M,Singapore,100,"Kubernetes, AWS, Git, Data Visualization",PhD,14,Automotive,2025-01-09,2025-03-14,1439,7.9,Advanced Robotics +AI14921,Data Scientist,41245,USD,41245,SE,FL,India,M,India,0,"GCP, Spark, Java, Data Visualization",Bachelor,8,Finance,2024-10-22,2024-12-30,2167,6.3,Algorithmic Solutions +AI14922,Autonomous Systems Engineer,60902,USD,60902,EN,FL,Denmark,S,Denmark,100,"GCP, SQL, Azure, Mathematics",PhD,1,Technology,2025-04-10,2025-05-31,1742,5.4,TechCorp Inc +AI14923,Data Engineer,57892,EUR,49208,EN,PT,France,M,France,0,"GCP, Spark, Git",Bachelor,1,Automotive,2024-11-18,2025-01-18,2050,7.4,Quantum Computing Inc +AI14924,AI Consultant,127852,CAD,159815,EX,PT,Canada,S,Ghana,100,"Azure, AWS, NLP, Computer Vision, TensorFlow",Associate,18,Transportation,2024-02-03,2024-03-01,1403,8.6,DataVision Ltd +AI14925,Data Analyst,214783,JPY,23626130,EX,CT,Japan,S,Japan,50,"R, Linux, Mathematics, MLOps, SQL",Master,12,Energy,2024-02-26,2024-04-23,2345,6.1,Predictive Systems +AI14926,Data Engineer,87394,EUR,74285,MI,PT,France,S,France,0,"Python, NLP, Deep Learning, Hadoop, Computer Vision",Associate,2,Automotive,2024-09-10,2024-11-05,1737,7.3,Autonomous Tech +AI14927,Autonomous Systems Engineer,98451,USD,98451,EN,FT,Norway,M,Norway,0,"SQL, Linux, Kubernetes, Azure, NLP",Associate,0,Real Estate,2024-10-04,2024-10-18,2299,6,Digital Transformation LLC +AI14928,NLP Engineer,74127,GBP,55595,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Hadoop, Data Visualization, NLP",Bachelor,0,Automotive,2024-12-18,2025-01-04,2454,7.4,Quantum Computing Inc +AI14929,Machine Learning Researcher,51492,USD,51492,EX,PT,India,S,India,50,"Docker, GCP, Computer Vision, Kubernetes",Bachelor,10,Media,2024-07-28,2024-10-06,2116,5.7,Advanced Robotics +AI14930,Head of AI,168869,SGD,219530,EX,PT,Singapore,S,Singapore,0,"Deep Learning, Docker, PyTorch, AWS",Associate,11,Automotive,2024-01-20,2024-02-28,956,8.3,AI Innovations +AI14931,AI Software Engineer,104543,JPY,11499730,SE,CT,Japan,S,Japan,0,"R, Azure, TensorFlow, MLOps",Master,9,Transportation,2024-09-20,2024-10-22,1456,6.1,Digital Transformation LLC +AI14932,AI Product Manager,88186,SGD,114642,MI,PT,Singapore,M,Mexico,50,"Java, Computer Vision, Linux, Data Visualization, PyTorch",Associate,4,Transportation,2024-06-11,2024-07-09,1523,9.3,Advanced Robotics +AI14933,Data Scientist,135656,USD,135656,EX,FT,Finland,S,Latvia,0,"Linux, SQL, Git, Python",PhD,12,Telecommunications,2024-08-17,2024-09-18,1864,5.9,AI Innovations +AI14934,AI Software Engineer,124876,EUR,106145,EX,FT,Germany,S,Germany,0,"Statistics, MLOps, AWS, Computer Vision, Linux",PhD,12,Government,2024-04-22,2024-06-29,540,5.8,Smart Analytics +AI14935,Data Engineer,75356,CAD,94195,EN,FT,Canada,M,Canada,100,"PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2025-04-25,2025-06-14,1057,9.3,Algorithmic Solutions +AI14936,Data Engineer,95193,EUR,80914,SE,CT,France,S,France,0,"Linux, Computer Vision, Git, Spark, TensorFlow",Associate,5,Technology,2025-03-22,2025-05-31,2416,9.1,Cloud AI Solutions +AI14937,Autonomous Systems Engineer,203347,SGD,264351,EX,PT,Singapore,L,Singapore,50,"Data Visualization, Python, Git, NLP",PhD,16,Energy,2024-08-31,2024-10-13,2016,5.3,Predictive Systems +AI14938,Machine Learning Researcher,95262,GBP,71447,MI,PT,United Kingdom,M,South Africa,100,"Kubernetes, Data Visualization, Spark",Associate,2,Retail,2024-02-01,2024-04-01,1027,8.3,Machine Intelligence Group +AI14939,Computer Vision Engineer,162617,USD,162617,MI,PT,Denmark,L,Denmark,50,"Hadoop, Kubernetes, Linux, Scala, Azure",Associate,2,Automotive,2024-12-05,2024-12-27,2086,5.3,Autonomous Tech +AI14940,AI Research Scientist,119770,GBP,89828,SE,FL,United Kingdom,S,Malaysia,100,"Java, Azure, AWS, Hadoop",Associate,9,Technology,2025-01-27,2025-04-02,2470,7.5,Autonomous Tech +AI14941,Data Scientist,220001,CAD,275001,EX,PT,Canada,L,Canada,100,"Java, Scala, MLOps, Kubernetes",Bachelor,19,Telecommunications,2024-06-15,2024-08-07,757,5.3,AI Innovations +AI14942,AI Consultant,64943,EUR,55202,EN,FL,France,S,France,100,"PyTorch, AWS, MLOps, Tableau",Master,1,Manufacturing,2024-08-11,2024-10-11,1367,8.7,Machine Intelligence Group +AI14943,Data Scientist,218883,EUR,186051,EX,FL,Netherlands,S,Netherlands,0,"Hadoop, Docker, Spark, Deep Learning",Master,10,Energy,2024-04-06,2024-05-03,1713,9.4,Autonomous Tech +AI14944,AI Research Scientist,86404,USD,86404,MI,FL,Israel,M,Switzerland,50,"Computer Vision, Docker, Python",Master,2,Manufacturing,2024-02-14,2024-03-16,2410,7.7,Quantum Computing Inc +AI14945,AI Architect,175545,SGD,228209,EX,PT,Singapore,S,Singapore,100,"Git, Statistics, Python, Mathematics, Scala",Master,13,Automotive,2024-07-30,2024-09-12,571,9.1,Autonomous Tech +AI14946,AI Product Manager,148458,USD,148458,MI,FL,Norway,L,Norway,100,"Azure, Python, Statistics",Master,4,Gaming,2024-06-10,2024-08-06,1292,6,Advanced Robotics +AI14947,Deep Learning Engineer,104899,EUR,89164,MI,CT,Austria,L,Austria,50,"Computer Vision, Python, Spark, R",Associate,2,Healthcare,2024-01-12,2024-03-25,1839,5.6,Future Systems +AI14948,Data Engineer,101094,USD,101094,SE,FL,Finland,S,Finland,0,"Spark, SQL, Linux",Master,5,Finance,2025-04-12,2025-05-06,723,6.3,Predictive Systems +AI14949,AI Product Manager,125424,USD,125424,SE,FL,Finland,M,Finland,50,"Linux, SQL, Python, Git",PhD,7,Consulting,2024-10-27,2025-01-02,2396,6.3,Advanced Robotics +AI14950,Autonomous Systems Engineer,82744,JPY,9101840,MI,PT,Japan,M,South Africa,0,"GCP, Docker, Java, SQL",PhD,4,Gaming,2024-01-23,2024-02-19,1773,7.4,Machine Intelligence Group +AI14951,Computer Vision Engineer,117343,USD,117343,MI,PT,Norway,L,Norway,100,"Docker, Computer Vision, MLOps",Associate,2,Energy,2024-04-02,2024-06-01,515,6.7,AI Innovations +AI14952,ML Ops Engineer,118354,USD,118354,MI,CT,Sweden,L,Sweden,0,"Python, TensorFlow, R",Master,2,Education,2024-11-27,2025-01-31,1583,5.6,Predictive Systems +AI14953,Autonomous Systems Engineer,124093,USD,124093,EX,CT,South Korea,S,South Korea,100,"SQL, TensorFlow, Data Visualization",Bachelor,14,Real Estate,2024-09-28,2024-11-21,1677,6.8,DeepTech Ventures +AI14954,Deep Learning Engineer,63367,SGD,82377,EN,CT,Singapore,S,Singapore,0,"Data Visualization, GCP, Mathematics, Statistics, Scala",Bachelor,0,Retail,2025-04-29,2025-06-07,2329,5.4,Future Systems +AI14955,Machine Learning Researcher,161652,USD,161652,SE,FL,Norway,M,France,50,"MLOps, Deep Learning, NLP, PyTorch",Bachelor,5,Healthcare,2024-03-02,2024-05-07,1578,8.2,Cloud AI Solutions +AI14956,AI Research Scientist,104435,USD,104435,SE,FT,South Korea,M,South Korea,50,"Python, TensorFlow, AWS, PyTorch, SQL",PhD,5,Education,2024-11-17,2025-01-21,1555,7.3,Future Systems +AI14957,Data Scientist,140824,EUR,119700,SE,CT,Netherlands,S,Australia,50,"Statistics, Mathematics, Python",Bachelor,7,Government,2025-01-24,2025-03-17,2252,5.9,Future Systems +AI14958,NLP Engineer,33429,USD,33429,MI,PT,China,S,China,0,"SQL, MLOps, Mathematics, TensorFlow, GCP",Master,4,Education,2025-04-20,2025-05-06,628,9.8,Cloud AI Solutions +AI14959,Data Engineer,56924,USD,56924,EX,FL,India,L,India,100,"Kubernetes, Scala, Mathematics, TensorFlow, Linux",Master,12,Media,2025-02-13,2025-02-27,632,8.4,Cognitive Computing +AI14960,AI Specialist,108996,USD,108996,EN,FT,Norway,L,India,50,"GCP, Spark, Python",PhD,1,Government,2024-07-04,2024-08-23,1049,6.1,Future Systems +AI14961,AI Specialist,159001,USD,159001,SE,FL,United States,M,United States,50,"Data Visualization, NLP, AWS, R",Master,9,Transportation,2024-02-25,2024-04-03,1217,7.9,AI Innovations +AI14962,Machine Learning Researcher,186143,USD,186143,EX,FL,Norway,S,Norway,50,"Linux, Spark, Data Visualization",Associate,10,Healthcare,2024-07-18,2024-08-29,1432,8.4,Machine Intelligence Group +AI14963,AI Specialist,67937,USD,67937,SE,CT,China,L,China,0,"GCP, NLP, Scala, R, Java",PhD,6,Healthcare,2024-03-11,2024-04-02,2287,7.1,Cognitive Computing +AI14964,Machine Learning Engineer,62318,USD,62318,EN,PT,South Korea,L,South Korea,0,"Linux, TensorFlow, Deep Learning, Scala",PhD,1,Energy,2024-07-06,2024-08-10,1687,8.4,TechCorp Inc +AI14965,Deep Learning Engineer,92518,USD,92518,MI,FL,Israel,M,Israel,50,"Python, Data Visualization, Linux, Azure",Bachelor,2,Gaming,2024-11-17,2024-12-04,1191,6.2,Cognitive Computing +AI14966,Research Scientist,212794,AUD,287272,EX,FL,Australia,M,Australia,50,"Tableau, Kubernetes, TensorFlow, Mathematics",Bachelor,11,Consulting,2024-12-25,2025-02-26,1380,9.5,Neural Networks Co +AI14967,Research Scientist,116954,USD,116954,EX,FL,South Korea,M,Czech Republic,0,"SQL, Python, Docker",Master,12,Finance,2024-06-11,2024-07-26,1484,7.9,Quantum Computing Inc +AI14968,AI Specialist,146064,USD,146064,SE,PT,Sweden,L,Sweden,0,"Kubernetes, SQL, Linux",Associate,8,Healthcare,2024-12-29,2025-02-06,1882,6.3,DeepTech Ventures +AI14969,Principal Data Scientist,105890,SGD,137657,MI,FL,Singapore,L,Luxembourg,100,"Python, Computer Vision, Tableau",PhD,4,Real Estate,2024-05-10,2024-06-04,2107,7.7,Neural Networks Co +AI14970,Data Analyst,62944,AUD,84974,EN,FL,Australia,S,Malaysia,100,"Docker, TensorFlow, Mathematics, AWS, SQL",Master,0,Automotive,2024-04-01,2024-06-12,1846,6.4,Machine Intelligence Group +AI14971,AI Research Scientist,142892,USD,142892,MI,FL,Denmark,L,Denmark,0,"Data Visualization, Scala, SQL, Kubernetes",Bachelor,4,Automotive,2024-09-20,2024-10-18,770,5.7,Neural Networks Co +AI14972,Data Engineer,182144,USD,182144,EX,FL,Denmark,M,Nigeria,100,"Python, NLP, TensorFlow, Docker",Associate,17,Telecommunications,2024-11-20,2025-01-24,1514,6.3,DataVision Ltd +AI14973,Computer Vision Engineer,184474,USD,184474,EX,PT,Finland,S,Finland,0,"Java, GCP, SQL, Docker, PyTorch",PhD,11,Real Estate,2024-03-31,2024-05-20,921,6.9,Cloud AI Solutions +AI14974,AI Architect,105686,USD,105686,SE,CT,South Korea,L,Japan,0,"Data Visualization, Docker, Spark",PhD,8,Technology,2024-09-07,2024-11-01,2269,6.3,Cloud AI Solutions +AI14975,Computer Vision Engineer,40256,USD,40256,EN,FL,South Korea,S,South Korea,100,"Tableau, 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2AI00003Data Engineer128890EUR109557EXCTGermanySGermany100Spark, Scala, Hadoop, PyTorch, GCPBachelor12Automotive2025-01-192025-03-2813295.5Quantum Computing Inc
3AI00004Computer Vision Engineer96349USD96349MIFLFinlandLFinland50MLOps, Linux, Tableau, PythonPhD2Automotive2024-07-202024-09-0611326.8Cognitive Computing
4AI00005Robotics Engineer63065EUR53605ENFTFranceSFrance100R, Scala, SQL, GCP, PythonAssociate0Finance2025-03-162025-05-0920119.3Advanced Robotics
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14996AI14997AI Product Manager77555EUR65922ENCTNetherlandsMNetherlands50Python, TensorFlow, Mathematics, AWS, Computer...PhD0Energy2024-12-222025-02-1218709.7Autonomous Tech
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14999AI15000Principal Data Scientist58623USD58623SEFTChinaMChina0AWS, Spark, Computer Vision, Data Visualizatio...PhD6Transportation2024-11-232024-12-1510349.7Quantum Computing Inc
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" + ], + "text/plain": [ + " salary_usd salary_local remote_ratio years_experience \\\n", + "count 15000.000000 1.500000e+04 15000.000000 15000.000000 \n", + "mean 121991.938267 8.292366e+05 50.196667 6.365667 \n", + "std 63968.361846 3.425325e+06 40.844084 5.598551 \n", + "min 16621.000000 1.662100e+04 0.000000 0.000000 \n", + "25% 74978.500000 7.383075e+04 0.000000 2.000000 \n", + "50% 107261.500000 1.090355e+05 50.000000 5.000000 \n", + "75% 155752.250000 1.673278e+05 100.000000 10.000000 \n", + "max 410273.000000 3.368541e+07 100.000000 19.000000 \n", + "\n", + " job_description_length benefits_score \n", + "count 15000.000000 15000.000000 \n", + "mean 1500.852600 7.499540 \n", + "std 574.724647 1.444202 \n", + "min 500.000000 5.000000 \n", + "25% 998.750000 6.300000 \n", + "50% 1512.000000 7.500000 \n", + "75% 1994.000000 8.800000 \n", + "max 2499.000000 10.000000 " + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a4498be2-3f6d-463b-bede-2cb9cc7bbe9d", + "metadata": {}, + "outputs": [], + "source": [ + "df[" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 41f4fba6286ba17babe8f0efed73536b073564da Mon Sep 17 00:00:00 2001 From: Charles Mensah Date: Mon, 8 Dec 2025 15:55:59 +0100 Subject: [PATCH 05/26] Charles Monday --- ai_job_dataset1.csv | 15001 +++++++++++++++++++++++++++++++++++++ first_project_data.ipynb | 666 ++ 2 files changed, 15667 insertions(+) create mode 100644 ai_job_dataset1.csv create mode 100644 first_project_data.ipynb diff --git a/ai_job_dataset1.csv b/ai_job_dataset1.csv new file mode 100644 index 00000000..5c9e5669 --- /dev/null +++ b/ai_job_dataset1.csv @@ -0,0 +1,15001 @@ +job_id,job_title,salary_usd,salary_currency,salary_local,experience_level,employment_type,company_location,company_size,employee_residence,remote_ratio,required_skills,education_required,years_experience,industry,posting_date,application_deadline,job_description_length,benefits_score,company_name +AI00001,Data Scientist,219728,USD,219728,EX,PT,Sweden,M,Sweden,0,"Python, Computer Vision, R, Docker",Associate,13,Transportation,2024-09-23,2024-10-31,1132,6.6,TechCorp Inc +AI00002,Head of AI,230237,JPY,25326070,EX,PT,Japan,L,Japan,50,"Kubernetes, MLOps, Tableau, Python",Bachelor,10,Transportation,2024-07-26,2024-09-12,2299,8.5,Cloud AI Solutions +AI00003,Data Engineer,128890,EUR,109557,EX,CT,Germany,S,Germany,100,"Spark, Scala, Hadoop, PyTorch, GCP",Bachelor,12,Automotive,2025-01-19,2025-03-28,1329,5.5,Quantum Computing Inc +AI00004,Computer Vision Engineer,96349,USD,96349,MI,FL,Finland,L,Finland,50,"MLOps, Linux, Tableau, Python",PhD,2,Automotive,2024-07-20,2024-09-06,1132,6.8,Cognitive Computing +AI00005,Robotics Engineer,63065,EUR,53605,EN,FT,France,S,France,100,"R, Scala, SQL, GCP, Python",Associate,0,Finance,2025-03-16,2025-05-09,2011,9.3,Advanced Robotics +AI00006,Data Scientist,111794,SGD,145332,SE,CT,Singapore,S,Norway,50,"NLP, MLOps, TensorFlow",Master,7,Technology,2024-11-10,2025-01-20,1021,5.1,Cloud AI Solutions +AI00007,AI Consultant,113897,CAD,142371,SE,PT,Canada,L,Poland,50,"PyTorch, Linux, NLP",Associate,9,Gaming,2024-02-29,2024-04-21,2268,7.4,AI Innovations +AI00008,Head of AI,168639,AUD,227663,SE,FT,Australia,L,Vietnam,100,"Spark, SQL, Tableau, Computer Vision, Linux",Associate,9,Consulting,2024-02-26,2024-03-17,1497,5.5,TechCorp Inc +AI00009,Data Scientist,92624,JPY,10188640,MI,FT,Japan,L,Japan,50,"Kubernetes, SQL, Docker, Deep Learning",Bachelor,4,Government,2024-08-18,2024-10-03,1724,9.5,DataVision Ltd +AI00010,Machine Learning Engineer,215627,GBP,161720,EX,FT,United Kingdom,M,United Kingdom,50,"Git, Scala, GCP",PhD,10,Government,2025-01-18,2025-03-20,902,7.8,DeepTech Ventures +AI00011,Data Engineer,129706,USD,129706,MI,CT,Denmark,L,Denmark,0,"SQL, PyTorch, Statistics, TensorFlow, NLP",Bachelor,3,Consulting,2024-03-10,2024-05-17,2247,5.2,Cloud AI Solutions +AI00012,Deep Learning Engineer,76559,USD,76559,EN,FL,United States,S,United States,100,"Data Visualization, Mathematics, PyTorch, GCP",Bachelor,1,Government,2025-02-09,2025-04-14,694,8.3,Machine Intelligence Group +AI00013,Principal Data Scientist,185834,USD,185834,EX,CT,United States,L,United States,100,"Linux, Data Visualization, Python, TensorFlow",Associate,14,Telecommunications,2024-03-27,2024-06-03,1710,8.9,Autonomous Tech +AI00014,Principal Data Scientist,89801,USD,89801,MI,PT,Sweden,M,Belgium,100,"Linux, MLOps, Deep Learning",Master,3,Healthcare,2024-10-30,2025-01-06,1361,8.7,Cloud AI Solutions +AI00015,Principal Data Scientist,252601,USD,252601,EX,PT,Norway,L,Norway,100,"Kubernetes, SQL, AWS, Git, Computer Vision",Master,19,Gaming,2024-07-24,2024-08-14,572,5.1,TechCorp Inc +AI00016,AI Product Manager,20520,USD,20520,EN,FT,India,S,India,0,"Hadoop, Git, Computer Vision, Kubernetes, Data Visualization",Master,0,Gaming,2024-08-22,2024-10-05,2455,7.5,Predictive Systems +AI00017,Robotics Engineer,192789,CHF,173510,SE,PT,Switzerland,S,Switzerland,100,"Tableau, Git, Python, Java",Master,5,Healthcare,2024-03-27,2024-06-08,524,5.9,Quantum Computing Inc +AI00018,Machine Learning Researcher,107184,SGD,139339,SE,FL,Singapore,S,Singapore,50,"Azure, GCP, Computer Vision",Master,7,Automotive,2024-05-07,2024-05-28,2111,9.2,DeepTech Ventures +AI00019,Robotics Engineer,141909,EUR,120623,SE,FT,Netherlands,M,Netherlands,0,"Git, Kubernetes, MLOps, Spark",Associate,6,Healthcare,2024-12-22,2025-01-20,1601,7.8,Cloud AI Solutions +AI00020,Data Engineer,118238,USD,118238,SE,FL,Ireland,M,Ireland,100,"AWS, Python, Azure, SQL, Computer Vision",Associate,7,Education,2024-11-07,2025-01-02,2431,8.2,TechCorp Inc +AI00021,Data Scientist,155210,AUD,209534,SE,PT,Australia,L,Argentina,0,"Spark, NLP, AWS",Master,7,Energy,2025-01-24,2025-03-18,595,9.7,Neural Networks Co +AI00022,Data Engineer,96699,AUD,130544,SE,FT,Australia,S,Australia,0,"GCP, Linux, Mathematics",PhD,5,Technology,2025-03-29,2025-04-13,582,9.7,TechCorp Inc +AI00023,AI Software Engineer,161477,EUR,137255,SE,FT,France,L,France,50,"Mathematics, Spark, Linux",Bachelor,8,Real Estate,2025-02-04,2025-03-03,1861,9.5,DataVision Ltd +AI00024,AI Software Engineer,316709,USD,316709,EX,CT,Denmark,L,Denmark,50,"Data Visualization, Azure, Statistics",PhD,18,Transportation,2025-04-29,2025-06-21,1284,7.6,Autonomous Tech +AI00025,ML Ops Engineer,62089,CAD,77611,MI,CT,Canada,S,Singapore,50,"Python, GCP, Linux, SQL, Deep Learning",PhD,3,Media,2024-03-18,2024-04-25,2264,9.7,Predictive Systems +AI00026,Principal Data Scientist,77985,USD,77985,EN,CT,Denmark,S,Denmark,0,"SQL, TensorFlow, Computer Vision, Kubernetes",Associate,0,Automotive,2025-03-07,2025-04-03,655,9.4,Neural Networks Co +AI00027,Robotics Engineer,55315,EUR,47018,EN,PT,Austria,S,Austria,0,"Spark, Deep Learning, SQL, NLP, Python",PhD,0,Media,2025-01-09,2025-03-22,1107,9.5,Future Systems +AI00028,AI Architect,246647,SGD,320641,EX,PT,Singapore,M,Singapore,50,"Scala, Mathematics, SQL",Master,16,Telecommunications,2024-08-08,2024-08-26,2347,6.6,DeepTech Ventures +AI00029,Deep Learning Engineer,29050,USD,29050,EN,FT,China,S,Germany,0,"PyTorch, Kubernetes, Deep Learning, Hadoop",Associate,1,Consulting,2025-02-06,2025-03-19,555,5.2,AI Innovations +AI00030,Head of AI,120599,GBP,90449,MI,CT,United Kingdom,L,United Kingdom,50,"Linux, AWS, Python",Master,4,Energy,2024-09-21,2024-11-07,699,6.4,Quantum Computing Inc +AI00031,AI Specialist,277727,SGD,361045,EX,PT,Singapore,L,Singapore,50,"Python, Git, TensorFlow",Associate,13,Healthcare,2024-10-04,2024-11-05,529,9,Future Systems +AI00032,Data Engineer,158734,CAD,198418,EX,PT,Canada,S,South Korea,50,"Data Visualization, NLP, Computer Vision",Master,16,Retail,2024-05-20,2024-07-29,1607,6.2,Future Systems +AI00033,Data Engineer,139438,JPY,15338180,SE,FL,Japan,L,Japan,0,"Python, Spark, Git, Data Visualization, Docker",PhD,9,Retail,2025-03-16,2025-05-12,1826,9.9,Cognitive Computing +AI00034,Head of AI,131432,SGD,170862,SE,PT,Singapore,M,Sweden,50,"Kubernetes, Data Visualization, Deep Learning, Azure, Computer Vision",Master,5,Manufacturing,2024-05-03,2024-07-15,1134,5.3,Cognitive Computing +AI00035,Data Analyst,140290,USD,140290,MI,PT,Denmark,L,Denmark,50,"PyTorch, SQL, R, Azure",Associate,4,Real Estate,2024-07-18,2024-09-26,2437,5.7,DeepTech Ventures +AI00036,Research Scientist,90858,EUR,77229,MI,CT,France,L,France,50,"Scala, PyTorch, Deep Learning, Kubernetes, Java",Bachelor,2,Real Estate,2024-08-13,2024-09-13,1793,7.1,DataVision Ltd +AI00037,Autonomous Systems Engineer,126597,GBP,94948,SE,FL,United Kingdom,L,Singapore,50,"PyTorch, Java, TensorFlow, Computer Vision, SQL",Master,6,Government,2024-03-30,2024-04-13,2236,7.8,Machine Intelligence Group +AI00038,AI Architect,53274,USD,53274,EN,FL,Finland,M,Finland,100,"Spark, Python, Statistics, Hadoop, TensorFlow",Associate,0,Automotive,2025-03-22,2025-04-12,1444,6,Autonomous Tech +AI00039,Machine Learning Researcher,155357,USD,155357,EX,FL,Sweden,S,France,100,"TensorFlow, SQL, Computer Vision, Kubernetes",Bachelor,17,Real Estate,2024-12-11,2025-01-01,830,5.2,Cloud AI Solutions +AI00040,Principal Data Scientist,116292,EUR,98848,MI,FL,Netherlands,M,Hungary,50,"Java, Docker, Python",Bachelor,4,Gaming,2024-07-28,2024-09-06,2404,7.9,Quantum Computing Inc +AI00041,Computer Vision Engineer,140363,EUR,119309,SE,CT,Austria,L,Austria,100,"MLOps, Hadoop, TensorFlow, Kubernetes",Master,6,Manufacturing,2025-01-31,2025-04-06,1852,9.8,TechCorp Inc +AI00042,Research Scientist,162306,USD,162306,SE,CT,Israel,L,Luxembourg,0,"Statistics, SQL, Tableau, Hadoop, R",Master,9,Energy,2024-11-12,2024-12-08,1066,5.6,Neural Networks Co +AI00043,Data Analyst,134224,USD,134224,EX,FT,China,L,China,0,"Python, SQL, Git",Master,16,Technology,2024-10-13,2024-11-15,1743,6.6,Quantum Computing Inc +AI00044,Research Scientist,77500,GBP,58125,MI,CT,United Kingdom,S,Norway,0,"Mathematics, Hadoop, TensorFlow",PhD,3,Technology,2024-08-20,2024-10-29,811,10,Machine Intelligence Group +AI00045,Computer Vision Engineer,154083,USD,154083,SE,PT,Ireland,L,Ireland,50,"Hadoop, Python, Deep Learning",Associate,7,Manufacturing,2024-01-09,2024-02-16,1969,7.7,Neural Networks Co +AI00046,Machine Learning Engineer,79445,USD,79445,MI,FL,Ireland,M,Ireland,50,"Python, Statistics, TensorFlow, Computer Vision",Bachelor,4,Real Estate,2024-09-28,2024-10-16,511,7.2,Cloud AI Solutions +AI00047,Head of AI,157466,CHF,141719,SE,FL,Switzerland,M,Switzerland,100,"Git, Data Visualization, Spark, Computer Vision, Azure",Associate,8,Automotive,2024-01-21,2024-03-03,547,5.2,Future Systems +AI00048,Head of AI,38972,USD,38972,MI,FT,India,L,India,0,"Kubernetes, Mathematics, TensorFlow, MLOps",PhD,4,Real Estate,2024-01-28,2024-03-09,2163,7.1,AI Innovations +AI00049,Deep Learning Engineer,66090,CAD,82613,MI,PT,Canada,S,Canada,0,"AWS, SQL, R, Scala",PhD,3,Technology,2025-04-10,2025-04-29,1901,5.3,DeepTech Ventures +AI00050,Data Analyst,47943,USD,47943,MI,PT,China,L,China,50,"TensorFlow, Mathematics, NLP, Docker",PhD,2,Finance,2024-11-23,2025-01-13,2483,6.2,Smart Analytics +AI00051,ML Ops Engineer,217318,USD,217318,EX,PT,Ireland,M,Malaysia,100,"SQL, PyTorch, Hadoop",Bachelor,17,Finance,2024-11-14,2024-12-22,1647,7.8,Cognitive Computing +AI00052,AI Architect,84705,USD,84705,MI,CT,Norway,S,Norway,50,"Scala, Spark, PyTorch",PhD,3,Government,2024-12-19,2025-01-11,879,6.6,Autonomous Tech +AI00053,NLP Engineer,36076,USD,36076,SE,FT,India,M,India,50,"Python, TensorFlow, Data Visualization",Master,7,Media,2024-08-14,2024-09-23,580,7.5,Cognitive Computing +AI00054,AI Consultant,160216,USD,160216,EX,FT,Israel,L,Israel,100,"Deep Learning, Linux, Python, SQL",Master,15,Education,2024-05-09,2024-05-29,941,6,Predictive Systems +AI00055,Deep Learning Engineer,60826,GBP,45620,EN,FT,United Kingdom,S,United Kingdom,0,"SQL, Kubernetes, Azure",Bachelor,0,Energy,2024-11-02,2024-11-30,1731,6.3,Autonomous Tech +AI00056,Deep Learning Engineer,237320,GBP,177990,EX,PT,United Kingdom,M,United Kingdom,0,"Kubernetes, MLOps, Scala",Bachelor,16,Real Estate,2024-11-12,2024-12-28,991,7.7,DataVision Ltd +AI00057,Robotics Engineer,60243,EUR,51207,EN,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Linux, Mathematics",Master,1,Healthcare,2024-12-05,2024-12-20,1661,8.8,Future Systems +AI00058,Head of AI,74091,JPY,8150010,EN,PT,Japan,M,Japan,50,"Deep Learning, NLP, R, Linux, SQL",Bachelor,1,Consulting,2025-01-18,2025-03-23,1295,7.2,Quantum Computing Inc +AI00059,AI Specialist,68535,EUR,58255,EN,FT,France,L,France,100,"SQL, Scala, PyTorch",Associate,1,Media,2024-05-01,2024-06-17,1943,5.5,Machine Intelligence Group +AI00060,Robotics Engineer,99401,USD,99401,MI,FL,Norway,S,Norway,50,"Hadoop, Kubernetes, Data Visualization, Python, Linux",Bachelor,3,Healthcare,2024-03-20,2024-04-20,1371,9.4,Quantum Computing Inc +AI00061,Machine Learning Researcher,67632,USD,67632,EN,FT,Ireland,L,Ireland,0,"Linux, GCP, Deep Learning",Master,0,Government,2024-07-13,2024-08-10,2133,8.9,Advanced Robotics +AI00062,ML Ops Engineer,133163,EUR,113189,SE,CT,Netherlands,M,Netherlands,0,"SQL, Statistics, MLOps, PyTorch, Kubernetes",Associate,6,Media,2025-01-03,2025-01-21,2141,7.9,Neural Networks Co +AI00063,Robotics Engineer,125752,USD,125752,MI,FT,Norway,S,Norway,0,"NLP, Statistics, Scala",Master,4,Automotive,2024-05-17,2024-06-24,2390,6,Machine Intelligence Group +AI00064,AI Product Manager,70927,JPY,7801970,EN,CT,Japan,M,Japan,0,"Git, Computer Vision, Docker, SQL, Hadoop",Associate,1,Technology,2024-03-07,2024-04-05,1847,9.3,Quantum Computing Inc +AI00065,Data Engineer,80810,GBP,60608,EN,PT,United Kingdom,L,United Kingdom,0,"Azure, MLOps, Python, Linux, TensorFlow",Master,1,Energy,2024-10-30,2025-01-01,1476,5.4,Algorithmic Solutions +AI00066,Machine Learning Engineer,59614,SGD,77498,EN,CT,Singapore,S,Singapore,100,"Java, Kubernetes, GCP, Linux, Data Visualization",Associate,1,Healthcare,2024-11-07,2024-12-19,1581,7.3,Quantum Computing Inc +AI00067,Robotics Engineer,151907,EUR,129121,EX,FT,Germany,S,Ghana,50,"Python, R, MLOps",Associate,16,Media,2024-09-21,2024-10-16,1433,6.1,Quantum Computing Inc +AI00068,Data Scientist,76317,USD,76317,EX,CT,India,M,India,0,"TensorFlow, Deep Learning, Spark",Bachelor,14,Energy,2024-06-19,2024-07-15,1228,9.1,DataVision Ltd +AI00069,AI Research Scientist,160534,USD,160534,SE,FL,Denmark,M,Denmark,100,"GCP, SQL, MLOps",Master,9,Gaming,2024-06-10,2024-07-07,1651,8.3,Advanced Robotics +AI00070,AI Consultant,40687,USD,40687,MI,FT,India,L,India,50,"SQL, R, GCP, PyTorch, AWS",Master,3,Transportation,2024-07-16,2024-08-25,804,7.3,Algorithmic Solutions +AI00071,Computer Vision Engineer,129265,AUD,174508,SE,FL,Australia,S,Australia,0,"Java, Scala, TensorFlow",Master,5,Consulting,2025-04-06,2025-05-07,2410,6.9,DataVision Ltd +AI00072,NLP Engineer,94396,USD,94396,EX,PT,China,M,China,100,"Scala, Python, Tableau, Mathematics",Master,18,Government,2024-07-30,2024-08-18,1033,9.5,Advanced Robotics +AI00073,NLP Engineer,158237,USD,158237,EX,CT,South Korea,L,South Korea,0,"Python, NLP, GCP",Master,11,Finance,2025-01-24,2025-03-29,1676,6,Quantum Computing Inc +AI00074,Robotics Engineer,239068,USD,239068,EX,PT,Denmark,L,Denmark,50,"TensorFlow, Java, NLP, Hadoop, GCP",PhD,18,Media,2024-08-26,2024-10-30,1321,6.8,Autonomous Tech +AI00075,Robotics Engineer,81401,USD,81401,MI,FL,Finland,M,Belgium,0,"Java, Spark, Data Visualization, AWS, Git",Associate,2,Retail,2025-02-07,2025-04-11,1930,6.3,Future Systems +AI00076,AI Specialist,144229,CHF,129806,MI,FT,Switzerland,M,Japan,0,"Python, TensorFlow, MLOps, PyTorch",PhD,2,Media,2024-01-02,2024-03-02,1213,9.5,DeepTech Ventures +AI00077,AI Consultant,78936,EUR,67096,MI,FL,Germany,S,Germany,0,"Mathematics, Tableau, R, NLP, SQL",Bachelor,4,Consulting,2024-11-30,2025-01-03,697,6.9,Cloud AI Solutions +AI00078,AI Consultant,101054,USD,101054,SE,PT,South Korea,L,United Kingdom,0,"PyTorch, Python, TensorFlow",Bachelor,6,Healthcare,2025-02-04,2025-03-20,2396,8.8,DeepTech Ventures +AI00079,AI Specialist,91807,EUR,78036,SE,FT,Austria,S,Austria,50,"Linux, Azure, Scala, Python",Master,9,Education,2024-07-21,2024-09-13,1519,8.3,TechCorp Inc +AI00080,Machine Learning Engineer,49858,EUR,42379,EN,CT,Austria,S,Singapore,100,"PyTorch, Spark, Linux",Bachelor,1,Healthcare,2024-01-25,2024-04-02,1215,9.2,AI Innovations +AI00081,Robotics Engineer,80596,EUR,68507,EN,FT,Austria,L,Switzerland,0,"Kubernetes, Scala, PyTorch, Mathematics",Master,1,Education,2024-06-27,2024-08-26,1512,6.8,Digital Transformation LLC +AI00082,Head of AI,76026,USD,76026,MI,FT,Sweden,M,Sweden,50,"Tableau, SQL, R, Scala",PhD,4,Healthcare,2025-02-12,2025-03-24,1079,8,Predictive Systems +AI00083,Deep Learning Engineer,84841,USD,84841,MI,CT,Sweden,L,Sweden,0,"Azure, Linux, TensorFlow, GCP",Associate,4,Transportation,2024-11-18,2025-01-05,2456,5.7,Cognitive Computing +AI00084,Data Scientist,158900,CHF,143010,SE,FL,Switzerland,M,Switzerland,50,"Python, Statistics, Mathematics, Docker, TensorFlow",Associate,8,Finance,2024-06-14,2024-07-05,2367,6,Quantum Computing Inc +AI00085,Autonomous Systems Engineer,153858,EUR,130779,EX,CT,Germany,S,Germany,50,"MLOps, Azure, Java",Master,13,Gaming,2025-04-29,2025-06-21,2133,5.1,Cloud AI Solutions +AI00086,Data Scientist,115314,USD,115314,MI,CT,Denmark,M,Finland,0,"Java, Git, R, Azure",Bachelor,3,Real Estate,2024-06-01,2024-06-27,1783,7.9,Smart Analytics +AI00087,Machine Learning Engineer,181068,USD,181068,EX,FT,Israel,S,Israel,100,"R, Java, Hadoop, Mathematics",PhD,13,Transportation,2024-01-26,2024-03-25,1322,8.5,Machine Intelligence Group +AI00088,AI Software Engineer,119021,USD,119021,EN,FT,Denmark,L,Portugal,0,"Computer Vision, Docker, Linux, GCP",PhD,1,Transportation,2025-03-07,2025-05-10,1461,7.3,DataVision Ltd +AI00089,Data Analyst,219746,USD,219746,EX,FL,Israel,M,Czech Republic,100,"R, Python, Scala, TensorFlow",PhD,15,Finance,2024-07-02,2024-09-12,1485,7,Smart Analytics +AI00090,AI Consultant,115774,USD,115774,EX,FL,China,L,China,50,"Hadoop, Scala, NLP, PyTorch, SQL",Associate,10,Real Estate,2024-02-04,2024-03-09,1618,5.3,DataVision Ltd +AI00091,AI Consultant,130984,CHF,117886,EN,PT,Switzerland,L,Philippines,50,"MLOps, Deep Learning, Kubernetes, Azure, GCP",Bachelor,1,Retail,2024-01-08,2024-03-20,1774,5.3,DataVision Ltd +AI00092,ML Ops Engineer,191223,CHF,172101,EX,FT,Switzerland,S,Germany,0,"NLP, Azure, SQL",PhD,18,Healthcare,2024-04-07,2024-06-07,1926,6.8,Neural Networks Co +AI00093,AI Consultant,155502,USD,155502,SE,FT,Norway,M,Italy,50,"Python, NLP, AWS, Spark",PhD,9,Consulting,2025-01-29,2025-02-22,2449,7.6,Future Systems +AI00094,AI Specialist,86140,EUR,73219,MI,PT,Germany,L,South Korea,50,"Scala, Kubernetes, Deep Learning, AWS",Master,4,Real Estate,2025-03-11,2025-04-12,1816,7.3,Predictive Systems +AI00095,AI Architect,96028,GBP,72021,MI,FL,United Kingdom,L,Australia,0,"Data Visualization, MLOps, GCP, PyTorch",Bachelor,4,Healthcare,2025-03-09,2025-03-28,1878,6.6,Future Systems +AI00096,Principal Data Scientist,134920,USD,134920,SE,PT,United States,S,United States,0,"SQL, Mathematics, Data Visualization, Kubernetes",Associate,7,Consulting,2025-04-03,2025-05-12,1930,6.7,Predictive Systems +AI00097,Research Scientist,107694,USD,107694,SE,FL,Ireland,M,Estonia,50,"Spark, Linux, MLOps, R",Associate,5,Retail,2024-03-20,2024-04-22,2292,5.1,Future Systems +AI00098,Deep Learning Engineer,114301,USD,114301,MI,FT,Finland,L,Finland,0,"Tableau, MLOps, Python",Bachelor,4,Real Estate,2025-02-08,2025-03-05,1506,7.5,Digital Transformation LLC +AI00099,Machine Learning Researcher,92728,GBP,69546,MI,FT,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes, Azure",Bachelor,4,Transportation,2024-12-25,2025-02-05,1948,9.3,Cognitive Computing +AI00100,NLP Engineer,76826,SGD,99874,EN,PT,Singapore,M,Singapore,50,"Git, R, Statistics, PyTorch, Deep Learning",Bachelor,1,Government,2025-04-08,2025-05-10,804,7.4,Predictive Systems +AI00101,AI Consultant,48870,USD,48870,SE,PT,India,L,India,0,"Hadoop, Java, Azure, Spark, Statistics",Associate,7,Healthcare,2025-03-26,2025-05-16,1108,5.6,Cognitive Computing +AI00102,Data Scientist,89527,AUD,120861,MI,FT,Australia,L,United States,50,"Linux, Azure, SQL, R, Java",Master,4,Finance,2024-12-09,2024-12-30,1299,5.8,Predictive Systems +AI00103,Autonomous Systems Engineer,81103,AUD,109489,EN,CT,Australia,L,Australia,0,"Mathematics, SQL, Kubernetes",Master,0,Media,2024-05-26,2024-08-07,2055,7,Digital Transformation LLC +AI00104,Machine Learning Engineer,283428,USD,283428,EX,CT,Denmark,L,Denmark,0,"Python, TensorFlow, MLOps, Data Visualization",Associate,13,Healthcare,2025-03-10,2025-05-11,1275,5.1,Smart Analytics +AI00105,AI Product Manager,104906,USD,104906,MI,FL,United States,S,Portugal,50,"PyTorch, Java, Spark, Statistics",Bachelor,3,Technology,2025-01-26,2025-03-28,2101,8,Cognitive Computing +AI00106,AI Software Engineer,231496,USD,231496,EX,PT,Finland,L,Finland,50,"Tableau, R, Kubernetes",Master,18,Automotive,2025-02-13,2025-04-10,895,5.5,DataVision Ltd +AI00107,Robotics Engineer,147402,JPY,16214220,SE,FT,Japan,L,Japan,100,"Azure, GCP, Scala, R, Python",Bachelor,8,Automotive,2024-12-11,2025-02-01,593,7,Algorithmic Solutions +AI00108,Data Scientist,69331,EUR,58931,EN,FT,Austria,L,Austria,100,"AWS, Git, NLP, Java, Computer Vision",Master,1,Healthcare,2025-04-11,2025-05-21,639,8.8,AI Innovations +AI00109,AI Consultant,215842,EUR,183466,EX,CT,France,S,France,0,"Deep Learning, TensorFlow, Spark, Python",Bachelor,12,Healthcare,2024-12-19,2025-01-28,2098,6.7,Machine Intelligence Group +AI00110,Data Scientist,79833,USD,79833,SE,PT,South Korea,S,South Korea,0,"Java, SQL, PyTorch, TensorFlow, AWS",PhD,6,Healthcare,2024-01-04,2024-01-18,1284,5.7,Predictive Systems +AI00111,Data Scientist,304859,USD,304859,EX,FT,Norway,L,Norway,100,"Linux, SQL, Mathematics",Bachelor,15,Media,2025-03-22,2025-05-05,2460,6,Advanced Robotics +AI00112,Research Scientist,112217,EUR,95384,SE,CT,Germany,S,Israel,0,"Spark, Scala, Azure",Associate,8,Technology,2025-03-07,2025-04-23,1679,10,Digital Transformation LLC +AI00113,Head of AI,45738,USD,45738,EN,FL,South Korea,M,South Korea,100,"TensorFlow, Hadoop, Spark",Associate,0,Manufacturing,2024-03-17,2024-04-05,1481,9.5,DeepTech Ventures +AI00114,Machine Learning Researcher,195309,EUR,166013,EX,PT,Germany,S,Germany,50,"SQL, Tableau, PyTorch, NLP",Bachelor,18,Consulting,2024-12-14,2025-02-23,1277,5.3,DeepTech Ventures +AI00115,Data Scientist,141439,USD,141439,SE,FL,United States,L,United States,50,"Kubernetes, GCP, Git, SQL",PhD,9,Retail,2024-06-24,2024-07-13,1021,6.3,Digital Transformation LLC +AI00116,AI Consultant,125836,USD,125836,MI,FT,Norway,L,Norway,100,"Statistics, Kubernetes, Spark, GCP",Master,2,Transportation,2024-12-27,2025-02-22,1650,10,Predictive Systems +AI00117,Machine Learning Researcher,58213,USD,58213,EN,FT,Israel,S,Thailand,50,"Azure, Linux, Kubernetes",PhD,0,Telecommunications,2025-04-13,2025-06-08,1087,5.5,Cloud AI Solutions +AI00118,ML Ops Engineer,82191,EUR,69862,MI,CT,Germany,M,Germany,0,"Spark, GCP, Hadoop",Bachelor,2,Media,2024-08-05,2024-10-16,1906,9.5,Quantum Computing Inc +AI00119,Machine Learning Researcher,207975,AUD,280766,EX,CT,Australia,S,Colombia,0,"SQL, Azure, Computer Vision",Master,13,Telecommunications,2025-02-21,2025-04-07,1475,9.9,Future Systems +AI00120,Computer Vision Engineer,115664,USD,115664,SE,PT,Ireland,M,Ireland,0,"TensorFlow, R, Data Visualization",Bachelor,7,Automotive,2024-03-27,2024-05-15,1449,7.8,Smart Analytics +AI00121,AI Software Engineer,109337,USD,109337,SE,PT,Ireland,M,Ireland,50,"Data Visualization, PyTorch, Python, Mathematics, Git",Associate,9,Government,2025-04-26,2025-05-13,901,8.1,Predictive Systems +AI00122,Data Analyst,115386,USD,115386,SE,PT,Finland,M,Finland,100,"MLOps, Statistics, Hadoop, SQL",Associate,7,Energy,2024-09-02,2024-11-03,2387,6.7,Smart Analytics +AI00123,Autonomous Systems Engineer,64431,GBP,48323,EN,FT,United Kingdom,L,United Kingdom,50,"Git, Deep Learning, Python, Statistics, TensorFlow",Bachelor,1,Automotive,2025-01-25,2025-02-25,825,9,DeepTech Ventures +AI00124,Data Engineer,108088,USD,108088,SE,FL,United States,S,United States,100,"Tableau, Python, Docker, Azure",Bachelor,9,Consulting,2024-10-07,2024-12-15,1769,8,Smart Analytics +AI00125,ML Ops Engineer,228314,GBP,171236,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Hadoop, SQL, Statistics, TensorFlow",Master,16,Telecommunications,2024-10-18,2024-12-04,1005,6.5,Cognitive Computing +AI00126,Data Scientist,153260,AUD,206901,SE,CT,Australia,L,Australia,0,"MLOps, Java, NLP",Master,9,Education,2025-04-02,2025-05-04,1768,9.7,DataVision Ltd +AI00127,Data Scientist,63667,USD,63667,MI,CT,Israel,S,Norway,100,"R, Data Visualization, SQL, NLP",PhD,4,Energy,2025-03-20,2025-05-12,1336,7.9,Algorithmic Solutions +AI00128,Research Scientist,31185,USD,31185,MI,FL,China,S,Colombia,100,"AWS, GCP, NLP, SQL, Statistics",Associate,3,Healthcare,2025-03-11,2025-04-07,1510,9.2,Neural Networks Co +AI00129,Machine Learning Engineer,132167,EUR,112342,SE,PT,Germany,M,Germany,50,"MLOps, Docker, Linux, Computer Vision",Bachelor,9,Education,2024-08-04,2024-10-12,1110,6.2,Quantum Computing Inc +AI00130,AI Research Scientist,223349,JPY,24568390,EX,FL,Japan,L,Japan,100,"PyTorch, Mathematics, TensorFlow",Bachelor,11,Gaming,2024-07-31,2024-09-27,1489,5.9,Smart Analytics +AI00131,AI Architect,26957,USD,26957,EN,CT,India,M,India,100,"Azure, Computer Vision, Statistics",Bachelor,1,Transportation,2025-03-23,2025-04-17,2335,9.5,DataVision Ltd +AI00132,AI Software Engineer,93564,USD,93564,MI,CT,Sweden,S,Sweden,0,"PyTorch, Docker, Data Visualization, Scala, Computer Vision",Associate,2,Transportation,2025-03-25,2025-04-13,515,9.7,Advanced Robotics +AI00133,Computer Vision Engineer,113846,EUR,96769,SE,PT,France,S,France,100,"SQL, Git, R, Hadoop, Docker",Associate,6,Energy,2024-09-02,2024-10-30,2447,7.8,DataVision Ltd +AI00134,AI Specialist,147580,EUR,125443,EX,FL,France,M,France,0,"Linux, Deep Learning, Hadoop, Kubernetes, Docker",PhD,17,Telecommunications,2024-11-13,2025-01-10,2416,5.9,Cloud AI Solutions +AI00135,Data Engineer,50514,CAD,63143,EN,PT,Canada,M,Philippines,100,"SQL, PyTorch, Tableau, NLP",PhD,1,Automotive,2024-08-04,2024-08-28,2384,9,Cognitive Computing +AI00136,AI Product Manager,94158,EUR,80034,MI,FL,Germany,M,Vietnam,100,"PyTorch, R, Scala",Master,2,Education,2024-09-01,2024-10-10,867,5.5,Future Systems +AI00137,Principal Data Scientist,161009,EUR,136858,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, AWS, GCP",Associate,19,Transportation,2024-02-17,2024-03-17,1247,7.1,Cognitive Computing +AI00138,Data Analyst,91911,USD,91911,EX,FT,India,L,India,100,"PyTorch, SQL, Azure, Docker",Associate,15,Technology,2024-06-15,2024-08-15,2149,5.9,Cloud AI Solutions +AI00139,AI Specialist,248071,EUR,210860,EX,FL,Germany,M,Czech Republic,50,"Kubernetes, R, GCP",Bachelor,15,Consulting,2025-04-13,2025-04-29,616,7.6,Future Systems +AI00140,Autonomous Systems Engineer,150204,EUR,127673,SE,PT,Germany,M,Germany,50,"Docker, Linux, Kubernetes, Data Visualization",Bachelor,9,Transportation,2025-03-18,2025-04-12,1478,6.3,Neural Networks Co +AI00141,AI Product Manager,181517,EUR,154289,SE,CT,Netherlands,L,Netherlands,50,"SQL, Kubernetes, NLP, MLOps",PhD,9,Government,2024-08-13,2024-09-05,981,8.9,TechCorp Inc +AI00142,Data Analyst,64573,EUR,54887,EN,PT,France,L,France,100,"Kubernetes, GCP, Mathematics, Python",Master,1,Government,2024-07-19,2024-09-30,1495,9.2,AI Innovations +AI00143,ML Ops Engineer,89332,USD,89332,MI,CT,United States,S,United States,100,"Python, TensorFlow, Deep Learning, Docker, PyTorch",Bachelor,4,Finance,2024-08-20,2024-10-23,2011,6,Predictive Systems +AI00144,Machine Learning Engineer,118239,USD,118239,SE,FL,Sweden,S,Indonesia,50,"AWS, Hadoop, PyTorch, Statistics, Azure",PhD,9,Energy,2024-08-03,2024-09-22,576,8.1,Future Systems +AI00145,AI Specialist,103715,JPY,11408650,MI,FT,Japan,S,Japan,50,"Python, Azure, Statistics",Bachelor,4,Automotive,2024-12-11,2025-01-20,2224,9.3,Neural Networks Co +AI00146,AI Consultant,151680,AUD,204768,EX,FL,Australia,S,Australia,100,"Computer Vision, AWS, Kubernetes",Associate,14,Manufacturing,2024-06-20,2024-07-31,2439,6.9,Cognitive Computing +AI00147,Data Analyst,142589,EUR,121201,SE,FT,Netherlands,L,Netherlands,0,"Docker, Tableau, Kubernetes, Data Visualization, GCP",Master,8,Government,2024-10-25,2024-11-11,2431,6,Predictive Systems +AI00148,Research Scientist,63062,USD,63062,EN,PT,Sweden,L,Sweden,50,"PyTorch, R, Mathematics, Kubernetes",Associate,1,Real Estate,2024-09-05,2024-10-18,1558,6.7,Smart Analytics +AI00149,Data Engineer,80691,JPY,8876010,EN,CT,Japan,L,Japan,100,"Deep Learning, Computer Vision, PyTorch, Statistics, Spark",Master,1,Retail,2024-12-21,2025-01-04,624,8.1,DataVision Ltd +AI00150,Data Analyst,171580,JPY,18873800,SE,PT,Japan,L,Kenya,100,"SQL, Spark, MLOps",PhD,7,Manufacturing,2024-10-14,2024-12-09,1931,6.7,Predictive Systems +AI00151,Autonomous Systems Engineer,58331,USD,58331,SE,PT,China,M,Chile,0,"Hadoop, Java, NLP, Mathematics, Python",Master,5,Transportation,2024-11-23,2025-01-24,2002,6.1,Cognitive Computing +AI00152,Head of AI,85620,CAD,107025,MI,FT,Canada,L,Canada,100,"TensorFlow, GCP, MLOps, NLP",Associate,4,Healthcare,2025-01-22,2025-02-23,848,5.8,Quantum Computing Inc +AI00153,AI Consultant,220871,EUR,187740,EX,FT,Austria,M,Austria,0,"Linux, Tableau, Spark, Scala",Associate,14,Automotive,2024-06-28,2024-07-31,821,5.2,DeepTech Ventures +AI00154,ML Ops Engineer,93007,EUR,79056,MI,CT,France,M,France,50,"Docker, SQL, MLOps, GCP, Hadoop",Bachelor,4,Energy,2024-06-05,2024-07-23,1595,6.4,Cognitive Computing +AI00155,AI Specialist,191783,SGD,249318,EX,FT,Singapore,S,Singapore,100,"Java, GCP, PyTorch",PhD,14,Healthcare,2024-10-04,2024-10-27,2352,5.6,Advanced Robotics +AI00156,Head of AI,83683,USD,83683,MI,FL,Israel,S,Czech Republic,50,"Mathematics, Computer Vision, MLOps, Git, Deep Learning",Bachelor,3,Education,2024-05-15,2024-06-07,818,5.3,Smart Analytics +AI00157,Research Scientist,107869,USD,107869,SE,FL,Ireland,S,Ireland,50,"SQL, Linux, GCP",Associate,8,Finance,2024-02-17,2024-04-01,2148,7.3,Predictive Systems +AI00158,Autonomous Systems Engineer,73528,USD,73528,MI,PT,Sweden,S,Poland,0,"NLP, R, Git, MLOps",Associate,2,Finance,2024-03-01,2024-05-05,557,8,Algorithmic Solutions +AI00159,NLP Engineer,47642,USD,47642,MI,FL,China,L,Sweden,100,"Python, TensorFlow, NLP",PhD,3,Telecommunications,2024-11-22,2025-01-13,2171,8,DeepTech Ventures +AI00160,AI Software Engineer,179937,EUR,152946,SE,PT,Netherlands,L,Netherlands,50,"Python, TensorFlow, NLP, Kubernetes",Associate,6,Real Estate,2024-06-01,2024-07-29,774,8.1,Machine Intelligence Group +AI00161,Data Engineer,157066,CHF,141359,MI,PT,Switzerland,L,Sweden,0,"GCP, Docker, NLP, Data Visualization",PhD,2,Transportation,2024-05-01,2024-05-26,887,9,Neural Networks Co +AI00162,Data Scientist,57299,USD,57299,EN,CT,Israel,M,Israel,0,"PyTorch, Spark, TensorFlow",Bachelor,1,Retail,2024-01-17,2024-02-19,794,7.8,DataVision Ltd +AI00163,Data Engineer,176844,CAD,221055,EX,FL,Canada,L,France,50,"Linux, Scala, Tableau",PhD,10,Telecommunications,2024-06-08,2024-07-19,577,5.4,Digital Transformation LLC +AI00164,AI Research Scientist,64892,CAD,81115,EN,CT,Canada,M,Canada,50,"Kubernetes, Scala, Azure, Computer Vision",Associate,1,Transportation,2024-11-05,2025-01-03,1645,5.7,Algorithmic Solutions +AI00165,AI Specialist,63024,EUR,53570,EN,CT,Austria,L,Austria,0,"Git, Statistics, Data Visualization",Bachelor,1,Gaming,2024-04-04,2024-05-05,1745,9.2,Algorithmic Solutions +AI00166,Principal Data Scientist,136695,CHF,123026,MI,FL,Switzerland,S,Switzerland,50,"Linux, GCP, Tableau, Java",Bachelor,2,Gaming,2024-12-10,2024-12-27,1424,5.9,Algorithmic Solutions +AI00167,Data Scientist,69744,USD,69744,EN,PT,South Korea,L,South Korea,50,"Python, Docker, Tableau",Associate,1,Telecommunications,2024-12-30,2025-01-22,1077,8.4,Autonomous Tech +AI00168,AI Specialist,135137,EUR,114866,EX,FL,Austria,M,Austria,0,"Kubernetes, GCP, Data Visualization",PhD,18,Finance,2024-04-06,2024-05-17,1590,5.4,TechCorp Inc +AI00169,Computer Vision Engineer,143037,USD,143037,EX,FL,Sweden,S,Sweden,0,"Data Visualization, Linux, Azure, Java",PhD,13,Manufacturing,2024-05-24,2024-07-07,775,9.5,Autonomous Tech +AI00170,Machine Learning Engineer,113068,GBP,84801,SE,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, Java, Data Visualization, Kubernetes",Master,9,Gaming,2024-06-10,2024-07-05,1805,6.6,Machine Intelligence Group +AI00171,AI Software Engineer,113917,GBP,85438,SE,PT,United Kingdom,S,Russia,0,"SQL, Kubernetes, GCP",Master,9,Government,2024-10-07,2024-10-26,1720,7.3,Future Systems +AI00172,Head of AI,80311,USD,80311,EX,PT,India,M,India,50,"Git, GCP, Computer Vision, Kubernetes, Docker",Bachelor,13,Finance,2025-01-17,2025-03-11,1052,5,Smart Analytics +AI00173,Autonomous Systems Engineer,160261,EUR,136222,SE,CT,Germany,L,Germany,50,"AWS, Linux, Scala, GCP, Python",Associate,6,Education,2024-02-26,2024-04-16,748,9.9,Smart Analytics +AI00174,Research Scientist,152241,CHF,137017,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, SQL, Git, PyTorch, Computer Vision",Bachelor,8,Gaming,2024-04-05,2024-06-05,1807,5.9,AI Innovations +AI00175,Research Scientist,74172,USD,74172,MI,CT,Israel,M,Israel,100,"Statistics, Kubernetes, GCP, Spark",PhD,2,Government,2024-01-24,2024-03-22,1780,7.5,Algorithmic Solutions +AI00176,Computer Vision Engineer,105632,USD,105632,MI,FL,Finland,L,Norway,100,"AWS, R, MLOps",Bachelor,3,Government,2025-01-03,2025-01-30,2376,9.4,Machine Intelligence Group +AI00177,Principal Data Scientist,89515,SGD,116370,MI,CT,Singapore,L,South Africa,100,"PyTorch, NLP, Computer Vision",Associate,4,Gaming,2025-01-17,2025-03-29,2328,7.4,DataVision Ltd +AI00178,AI Software Engineer,102319,USD,102319,MI,FL,Denmark,M,Colombia,50,"Deep Learning, Mathematics, Data Visualization, NLP",Associate,4,Energy,2024-07-14,2024-08-01,1939,6.2,Cognitive Computing +AI00179,AI Software Engineer,110536,USD,110536,MI,CT,Denmark,M,France,50,"SQL, Spark, Mathematics, Linux, TensorFlow",Associate,2,Real Estate,2024-05-01,2024-06-22,1559,5.4,DeepTech Ventures +AI00180,NLP Engineer,176372,USD,176372,SE,FL,Denmark,S,Denmark,0,"SQL, AWS, Computer Vision",Bachelor,5,Technology,2024-05-02,2024-07-05,729,8,AI Innovations +AI00181,AI Software Engineer,58111,EUR,49394,EN,FT,Austria,S,Austria,100,"Docker, Linux, Java",Bachelor,0,Finance,2024-01-20,2024-02-17,889,5.6,Digital Transformation LLC +AI00182,AI Product Manager,39802,USD,39802,SE,PT,India,M,Spain,100,"Git, Hadoop, Linux",Associate,8,Consulting,2024-02-05,2024-03-06,2046,8.3,Digital Transformation LLC +AI00183,Head of AI,147385,EUR,125277,SE,FL,France,L,Denmark,50,"Java, Statistics, AWS, Scala",Master,9,Consulting,2024-03-08,2024-03-25,1576,8.6,Cloud AI Solutions +AI00184,Research Scientist,118122,USD,118122,EN,FT,Denmark,L,Denmark,0,"Git, Scala, MLOps, Docker, Hadoop",Associate,0,Automotive,2024-07-20,2024-09-06,2018,9.3,Cloud AI Solutions +AI00185,AI Architect,75225,AUD,101554,EN,FT,Australia,L,Russia,100,"Deep Learning, MLOps, Linux",Master,0,Real Estate,2024-10-10,2024-11-26,2399,7.5,Machine Intelligence Group +AI00186,AI Research Scientist,48325,CAD,60406,EN,FL,Canada,M,Canada,100,"Spark, TensorFlow, Hadoop",Associate,0,Manufacturing,2025-03-26,2025-06-07,1523,6.2,Algorithmic Solutions +AI00187,Data Scientist,64973,USD,64973,EN,CT,Sweden,L,Sweden,0,"Git, Spark, NLP, MLOps",Master,0,Energy,2024-03-08,2024-04-24,1016,6.4,AI Innovations +AI00188,Computer Vision Engineer,78182,AUD,105546,MI,PT,Australia,M,Australia,50,"Hadoop, Docker, Computer Vision, Linux",Associate,4,Retail,2024-03-22,2024-05-22,1582,7.9,Cloud AI Solutions +AI00189,Data Analyst,357875,USD,357875,EX,PT,Norway,L,Norway,50,"Git, AWS, Linux, Tableau, Java",Associate,10,Retail,2024-01-19,2024-02-27,1044,8,Advanced Robotics +AI00190,AI Software Engineer,61953,USD,61953,SE,FT,India,L,India,50,"AWS, NLP, Tableau, SQL, PyTorch",Associate,8,Finance,2024-08-20,2024-10-14,1469,6.3,Advanced Robotics +AI00191,AI Product Manager,236982,USD,236982,EX,FL,Denmark,L,Poland,0,"AWS, Kubernetes, Tableau",Master,10,Gaming,2025-03-20,2025-04-03,597,5.1,Smart Analytics +AI00192,Principal Data Scientist,90203,EUR,76673,MI,PT,Austria,S,Austria,50,"Python, R, MLOps, GCP",PhD,3,Finance,2025-03-08,2025-05-12,1774,7.5,Autonomous Tech +AI00193,NLP Engineer,109984,JPY,12098240,SE,CT,Japan,S,Switzerland,0,"Data Visualization, Linux, SQL",Associate,7,Energy,2024-08-07,2024-08-31,1535,8,DeepTech Ventures +AI00194,AI Specialist,146371,CAD,182964,EX,PT,Canada,S,Ireland,100,"MLOps, Python, Scala, Docker",PhD,14,Healthcare,2024-11-15,2024-12-17,2313,5.4,Machine Intelligence Group +AI00195,Deep Learning Engineer,268088,EUR,227875,EX,PT,Netherlands,M,Netherlands,0,"NLP, AWS, Tableau, Scala, Computer Vision",Associate,10,Finance,2024-11-04,2024-12-21,1385,9.5,Predictive Systems +AI00196,Data Engineer,97647,GBP,73235,MI,CT,United Kingdom,S,Norway,50,"Java, Data Visualization, Scala, R",PhD,4,Government,2024-02-27,2024-04-08,1305,6.2,DeepTech Ventures +AI00197,Principal Data Scientist,221711,EUR,188454,EX,FT,Germany,S,Turkey,0,"TensorFlow, Kubernetes, NLP, PyTorch",Bachelor,17,Gaming,2025-01-14,2025-03-16,1652,8.9,Machine Intelligence Group +AI00198,Data Scientist,78716,EUR,66909,EN,PT,Germany,L,Germany,100,"Azure, Statistics, Kubernetes, Java",Bachelor,0,Automotive,2024-07-12,2024-08-13,2401,8.2,DataVision Ltd +AI00199,Principal Data Scientist,169717,CHF,152745,SE,CT,Switzerland,S,Switzerland,50,"Spark, Scala, PyTorch, Statistics",Master,5,Education,2024-03-07,2024-04-03,1003,9.5,DeepTech Ventures +AI00200,Data Analyst,92798,EUR,78878,MI,CT,Austria,L,Austria,50,"Linux, Kubernetes, SQL, Git",PhD,4,Consulting,2024-09-07,2024-11-12,1685,6.4,Neural Networks Co +AI00201,AI Product Manager,37177,USD,37177,MI,FL,China,S,China,0,"R, AWS, Hadoop, Spark",Associate,2,Automotive,2024-06-13,2024-08-25,869,6.1,Digital Transformation LLC +AI00202,Data Analyst,85505,USD,85505,MI,CT,Israel,S,Israel,50,"Java, Linux, R",Bachelor,4,Gaming,2025-01-21,2025-03-28,1983,5.1,Future Systems +AI00203,Robotics Engineer,113625,EUR,96581,MI,FT,France,L,France,100,"R, Python, Data Visualization, Scala",Associate,3,Automotive,2024-12-13,2025-01-02,2036,5.8,Advanced Robotics +AI00204,ML Ops Engineer,121846,AUD,164492,SE,PT,Australia,L,Australia,50,"NLP, AWS, Docker, Python",Master,6,Retail,2025-02-06,2025-04-20,2213,7.4,DeepTech Ventures +AI00205,Robotics Engineer,115136,JPY,12664960,MI,FT,Japan,M,Japan,50,"Scala, Python, Mathematics",Bachelor,3,Finance,2024-08-09,2024-09-03,1542,6.3,Neural Networks Co +AI00206,Data Scientist,265646,EUR,225799,EX,FT,France,L,Canada,0,"PyTorch, Computer Vision, SQL, AWS",Bachelor,16,Healthcare,2024-12-28,2025-01-11,1473,9.4,Predictive Systems +AI00207,AI Consultant,92726,CHF,83453,EN,FT,Switzerland,L,Switzerland,0,"Kubernetes, R, GCP, MLOps, Mathematics",Bachelor,0,Telecommunications,2024-09-22,2024-11-17,2013,9.8,AI Innovations +AI00208,Research Scientist,50607,USD,50607,EN,FL,Israel,S,Israel,100,"Azure, Tableau, Kubernetes, Deep Learning, Computer Vision",Bachelor,0,Telecommunications,2024-06-10,2024-08-05,1801,8.6,Autonomous Tech +AI00209,Machine Learning Researcher,219875,USD,219875,EX,PT,Sweden,L,Sweden,50,"NLP, Kubernetes, Tableau, Linux, R",Master,15,Automotive,2024-09-12,2024-11-15,1609,8.4,TechCorp Inc +AI00210,Robotics Engineer,93342,USD,93342,EX,CT,China,M,China,100,"Spark, Python, Azure",Master,11,Transportation,2025-02-15,2025-04-02,1345,7.2,AI Innovations +AI00211,Data Scientist,99132,EUR,84262,MI,FL,Netherlands,L,Netherlands,50,"Python, Linux, R",PhD,3,Government,2024-05-17,2024-06-15,2121,9.7,Advanced Robotics +AI00212,Data Analyst,148775,SGD,193408,SE,CT,Singapore,L,France,0,"Java, PyTorch, Scala",Associate,5,Real Estate,2024-01-07,2024-01-26,1222,6.3,Smart Analytics +AI00213,Data Scientist,63090,USD,63090,EN,CT,Denmark,S,Denmark,100,"AWS, MLOps, Python, Tableau, Azure",Master,0,Retail,2024-01-25,2024-03-18,1913,5.4,Neural Networks Co +AI00214,Robotics Engineer,39782,USD,39782,EN,CT,China,L,China,0,"Data Visualization, NLP, Python, R, Computer Vision",Bachelor,1,Transportation,2024-10-30,2025-01-04,2183,8.9,Quantum Computing Inc +AI00215,AI Architect,240915,CAD,301144,EX,PT,Canada,L,Canada,0,"TensorFlow, Java, MLOps",Master,14,Energy,2024-02-23,2024-04-17,1222,7.3,Advanced Robotics +AI00216,Robotics Engineer,69061,SGD,89779,MI,FL,Singapore,S,France,100,"Data Visualization, Linux, Tableau, Mathematics, Kubernetes",Master,4,Real Estate,2024-12-17,2025-02-01,1319,6.9,Future Systems +AI00217,Machine Learning Engineer,146403,EUR,124443,SE,PT,Netherlands,L,Netherlands,100,"Python, Scala, Java, Computer Vision, Azure",PhD,5,Gaming,2024-01-04,2024-02-07,1031,8.4,Algorithmic Solutions +AI00218,AI Consultant,56884,USD,56884,EN,CT,Finland,M,Finland,100,"Python, Mathematics, Tableau, Kubernetes",Bachelor,1,Government,2024-08-08,2024-08-24,532,9.1,Autonomous Tech +AI00219,AI Consultant,172277,CHF,155049,SE,PT,Switzerland,L,Switzerland,0,"Hadoop, Spark, Kubernetes, PyTorch, Azure",Bachelor,9,Technology,2024-08-09,2024-08-26,1725,9.7,Quantum Computing Inc +AI00220,Data Engineer,254054,EUR,215946,EX,CT,Austria,L,Austria,100,"R, Tableau, Data Visualization, Spark",Bachelor,17,Education,2024-09-26,2024-11-08,1518,9.8,Digital Transformation LLC +AI00221,Machine Learning Researcher,97442,EUR,82826,SE,FT,Germany,S,Germany,50,"Computer Vision, Linux, TensorFlow",PhD,5,Retail,2024-07-07,2024-08-01,1164,5.5,DataVision Ltd +AI00222,NLP Engineer,84037,USD,84037,EX,PT,China,S,China,50,"Computer Vision, NLP, GCP",Bachelor,19,Retail,2024-01-24,2024-02-12,2292,6,Autonomous Tech +AI00223,Principal Data Scientist,104614,EUR,88922,MI,CT,Netherlands,S,Netherlands,50,"SQL, Python, Linux, Computer Vision, Hadoop",Bachelor,4,Telecommunications,2024-10-10,2024-12-09,1895,7.9,Digital Transformation LLC +AI00224,Data Scientist,103566,USD,103566,SE,CT,Finland,S,Finland,100,"Git, Linux, Java, Statistics",Bachelor,7,Manufacturing,2024-01-09,2024-03-04,1777,8,Predictive Systems +AI00225,Autonomous Systems Engineer,69417,USD,69417,EN,CT,Ireland,L,Canada,50,"Data Visualization, Java, Docker, Kubernetes",Master,0,Energy,2024-04-22,2024-05-12,1887,9.4,Cloud AI Solutions +AI00226,AI Product Manager,27748,USD,27748,EN,FT,China,S,Israel,100,"NLP, Java, TensorFlow",Master,0,Automotive,2024-12-09,2025-02-03,1984,5.8,Autonomous Tech +AI00227,NLP Engineer,245370,USD,245370,EX,FL,Sweden,M,Sweden,100,"Tableau, Java, TensorFlow",Master,14,Real Estate,2024-03-17,2024-04-03,2030,8.4,Cognitive Computing +AI00228,AI Software Engineer,86794,JPY,9547340,MI,FL,Japan,S,Japan,50,"Scala, SQL, Hadoop, Statistics, GCP",Bachelor,4,Finance,2025-02-25,2025-04-25,1875,8.2,Cloud AI Solutions +AI00229,Computer Vision Engineer,58554,USD,58554,EN,FT,Ireland,S,Ireland,0,"Linux, Java, R, SQL, Mathematics",Master,1,Healthcare,2024-11-20,2024-12-22,2448,9.3,Cognitive Computing +AI00230,AI Specialist,152077,GBP,114058,SE,FT,United Kingdom,L,Canada,50,"Kubernetes, Git, Statistics",PhD,6,Automotive,2024-01-30,2024-03-20,2336,9.6,Cognitive Computing +AI00231,Data Scientist,152349,JPY,16758390,EX,FT,Japan,S,Japan,50,"MLOps, Scala, Java",Associate,10,Healthcare,2024-08-04,2024-09-30,1703,5.5,Quantum Computing Inc +AI00232,Deep Learning Engineer,155935,USD,155935,EX,FL,Israel,S,Ghana,50,"Python, Hadoop, Git",Associate,17,Retail,2025-03-25,2025-04-27,661,8.8,Predictive Systems +AI00233,Deep Learning Engineer,299354,CHF,269419,EX,FL,Switzerland,S,Switzerland,100,"MLOps, Scala, Docker",Bachelor,14,Retail,2024-06-16,2024-07-31,572,6.8,Advanced Robotics +AI00234,Autonomous Systems Engineer,112130,JPY,12334300,SE,FT,Japan,M,Japan,100,"SQL, Azure, Deep Learning",Associate,5,Energy,2024-03-14,2024-05-14,2021,9.4,Cognitive Computing +AI00235,AI Product Manager,299005,GBP,224254,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, MLOps, Statistics, Computer Vision",Master,16,Transportation,2024-06-17,2024-08-17,687,9.5,Cloud AI Solutions +AI00236,AI Product Manager,57697,JPY,6346670,EN,FL,Japan,M,Japan,100,"Python, TensorFlow, Deep Learning, MLOps",PhD,1,Energy,2024-03-23,2024-05-01,1370,9.7,DataVision Ltd +AI00237,Deep Learning Engineer,140199,SGD,182259,EX,FT,Singapore,S,Singapore,0,"Docker, Data Visualization, Python",Associate,18,Manufacturing,2025-03-26,2025-04-22,568,6.7,Predictive Systems +AI00238,Computer Vision Engineer,107028,USD,107028,EX,CT,China,M,Ghana,50,"Git, Linux, Statistics, Mathematics",PhD,11,Education,2024-10-29,2025-01-01,1172,5.8,Future Systems +AI00239,Data Analyst,48978,USD,48978,EN,FL,South Korea,M,Switzerland,50,"Computer Vision, Kubernetes, Git",Associate,1,Gaming,2024-02-21,2024-04-21,647,7.3,Future Systems +AI00240,Principal Data Scientist,101366,EUR,86161,MI,FL,France,M,France,100,"Python, Data Visualization, Linux, Azure",Master,3,Manufacturing,2025-01-04,2025-01-20,1292,6.7,DataVision Ltd +AI00241,AI Research Scientist,79125,EUR,67256,MI,CT,Netherlands,S,Netherlands,100,"Computer Vision, GCP, NLP, Statistics",PhD,4,Media,2024-03-05,2024-05-14,510,7.8,Smart Analytics +AI00242,Machine Learning Engineer,51110,USD,51110,SE,FL,China,S,China,50,"TensorFlow, Mathematics, Deep Learning, Computer Vision, R",Master,6,Automotive,2024-03-22,2024-05-06,1861,9.8,Cloud AI Solutions +AI00243,Data Scientist,96374,EUR,81918,MI,PT,Germany,S,Germany,0,"Deep Learning, SQL, Git, PyTorch",Associate,3,Retail,2024-05-08,2024-06-08,744,8.8,TechCorp Inc +AI00244,Autonomous Systems Engineer,92286,SGD,119972,EN,PT,Singapore,L,Singapore,100,"AWS, Java, Python, Mathematics",PhD,0,Energy,2025-02-04,2025-04-05,830,8.3,Advanced Robotics +AI00245,Data Scientist,102456,USD,102456,SE,FL,Sweden,S,Sweden,100,"PyTorch, Git, R, Azure",PhD,7,Education,2024-08-31,2024-11-12,552,6.9,Algorithmic Solutions +AI00246,ML Ops Engineer,138420,USD,138420,EX,CT,Sweden,M,Sweden,50,"PyTorch, Docker, Data Visualization, GCP, TensorFlow",PhD,17,Transportation,2024-02-13,2024-03-21,1582,5.3,DataVision Ltd +AI00247,AI Software Engineer,203654,CAD,254568,EX,PT,Canada,L,Canada,100,"SQL, Kubernetes, Computer Vision, GCP",PhD,12,Retail,2024-01-19,2024-03-23,1049,8.1,Advanced Robotics +AI00248,Robotics Engineer,121706,EUR,103450,SE,FT,Austria,L,Austria,50,"Hadoop, Data Visualization, Python, TensorFlow, Mathematics",PhD,8,Real Estate,2024-12-31,2025-02-23,2066,9.1,Neural Networks Co +AI00249,AI Software Engineer,112939,SGD,146821,SE,CT,Singapore,S,Netherlands,0,"R, Azure, Computer Vision, Deep Learning",PhD,9,Consulting,2024-10-30,2024-11-21,2008,10,Smart Analytics +AI00250,AI Software Engineer,223145,EUR,189673,EX,CT,Germany,L,Brazil,50,"Kubernetes, Scala, MLOps, Statistics",Bachelor,19,Energy,2024-01-02,2024-01-26,2356,7.1,AI Innovations +AI00251,Data Engineer,198959,AUD,268595,EX,FT,Australia,M,Australia,0,"Spark, Python, Deep Learning, TensorFlow, Mathematics",Master,11,Telecommunications,2025-03-11,2025-04-04,1821,7.1,Neural Networks Co +AI00252,Machine Learning Engineer,249841,USD,249841,EX,CT,United States,M,United States,100,"Scala, Linux, Java, Data Visualization",Associate,14,Healthcare,2024-01-08,2024-01-29,2130,7,Machine Intelligence Group +AI00253,AI Architect,81300,CHF,73170,EN,CT,Switzerland,S,Switzerland,0,"SQL, Python, Scala",Master,0,Energy,2024-04-26,2024-06-02,1225,9,AI Innovations +AI00254,Machine Learning Engineer,89201,USD,89201,EX,CT,China,L,Colombia,0,"Kubernetes, Mathematics, Data Visualization, SQL",Master,16,Gaming,2025-02-15,2025-03-15,1146,5.7,TechCorp Inc +AI00255,Robotics Engineer,123827,CHF,111444,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, GCP, AWS, SQL, NLP",Master,4,Telecommunications,2025-01-14,2025-03-11,543,8.3,Quantum Computing Inc +AI00256,AI Product Manager,321014,USD,321014,EX,FL,Denmark,M,Denmark,100,"Hadoop, Scala, MLOps",Master,16,Finance,2024-04-02,2024-06-13,1990,5.3,Neural Networks Co +AI00257,ML Ops Engineer,195690,USD,195690,EX,PT,Ireland,L,Ireland,100,"Azure, Kubernetes, PyTorch",Associate,11,Education,2024-01-15,2024-03-12,1481,6.2,Neural Networks Co +AI00258,AI Software Engineer,88109,SGD,114542,MI,FL,Singapore,M,South Korea,100,"SQL, Hadoop, Tableau, Spark",Bachelor,2,Government,2025-03-24,2025-06-01,2164,9.9,AI Innovations +AI00259,Deep Learning Engineer,93310,EUR,79314,SE,PT,Germany,S,Germany,0,"TensorFlow, Statistics, Mathematics",Associate,8,Retail,2024-08-24,2024-10-22,1732,5.5,Smart Analytics +AI00260,Deep Learning Engineer,180162,EUR,153138,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, Java, Spark, NLP",Associate,12,Technology,2024-03-06,2024-04-29,2049,9.7,Autonomous Tech +AI00261,Deep Learning Engineer,324764,CHF,292288,EX,PT,Switzerland,M,Switzerland,0,"TensorFlow, Kubernetes, Docker, Tableau, Scala",Associate,14,Manufacturing,2024-08-05,2024-10-03,1915,8.2,Quantum Computing Inc +AI00262,AI Consultant,57105,SGD,74237,EN,FT,Singapore,M,India,0,"Scala, Data Visualization, Python, GCP",Associate,1,Telecommunications,2024-05-26,2024-08-01,2453,6.9,DataVision Ltd +AI00263,Research Scientist,131121,USD,131121,EX,PT,Finland,M,South Africa,100,"Data Visualization, R, Kubernetes",Bachelor,11,Education,2024-10-02,2024-12-04,1707,7.3,Digital Transformation LLC +AI00264,NLP Engineer,87993,USD,87993,SE,FL,Israel,S,Netherlands,50,"MLOps, Deep Learning, Azure, Kubernetes",Associate,6,Real Estate,2024-11-10,2025-01-04,1598,9.4,Cognitive Computing +AI00265,Data Analyst,77654,EUR,66006,EN,CT,Austria,L,Austria,50,"PyTorch, Hadoop, Tableau, Docker",Associate,1,Retail,2024-10-11,2024-12-03,1681,7.7,Neural Networks Co +AI00266,Machine Learning Engineer,47769,AUD,64488,EN,PT,Australia,S,Australia,50,"Java, Python, Data Visualization, Docker",Master,1,Transportation,2024-02-24,2024-04-01,2173,5.2,Neural Networks Co +AI00267,NLP Engineer,112750,GBP,84563,SE,PT,United Kingdom,S,United Kingdom,100,"Git, Statistics, Spark",Master,8,Real Estate,2024-04-14,2024-05-15,529,5.5,Predictive Systems +AI00268,AI Architect,63413,USD,63413,EN,PT,Denmark,S,Denmark,0,"Tableau, Hadoop, Statistics, MLOps",Associate,0,Gaming,2024-06-11,2024-08-09,2014,7.5,DataVision Ltd +AI00269,Robotics Engineer,96518,EUR,82040,SE,FT,Austria,S,Norway,0,"GCP, Deep Learning, Java, Statistics, Spark",Bachelor,5,Automotive,2024-02-20,2024-04-23,702,8.4,TechCorp Inc +AI00270,AI Research Scientist,136768,USD,136768,MI,PT,Norway,M,Norway,50,"Python, Java, SQL",Bachelor,4,Healthcare,2025-03-08,2025-04-01,2160,9.5,Smart Analytics +AI00271,Research Scientist,143660,CAD,179575,SE,FL,Canada,L,Canada,100,"Statistics, Java, Data Visualization, Azure",Master,8,Education,2024-01-22,2024-03-07,1728,6.7,Algorithmic Solutions +AI00272,Data Engineer,122612,SGD,159396,SE,FT,Singapore,S,Singapore,50,"GCP, Azure, Tableau, Computer Vision, Scala",Associate,9,Media,2024-10-26,2024-11-12,1794,5.8,TechCorp Inc +AI00273,Principal Data Scientist,224629,AUD,303249,EX,FL,Australia,S,Australia,100,"R, SQL, Kubernetes, Statistics, Linux",Master,15,Healthcare,2024-07-14,2024-07-31,2418,9.6,Cognitive Computing +AI00274,Computer Vision Engineer,110517,EUR,93939,SE,FT,France,L,France,50,"Python, TensorFlow, Hadoop, R",PhD,7,Manufacturing,2024-10-17,2024-11-27,2208,8.2,Advanced Robotics +AI00275,Robotics Engineer,78533,SGD,102093,EN,CT,Singapore,M,Singapore,100,"Deep Learning, Spark, Git",Bachelor,0,Government,2024-10-22,2024-12-24,1972,5.7,Future Systems +AI00276,Head of AI,282152,CHF,253937,EX,CT,Switzerland,S,United Kingdom,50,"Spark, Kubernetes, SQL",PhD,15,Energy,2024-03-23,2024-06-03,678,7,DeepTech Ventures +AI00277,Data Scientist,240352,CHF,216317,EX,CT,Switzerland,M,Switzerland,50,"TensorFlow, Spark, Computer Vision",PhD,18,Automotive,2024-06-24,2024-08-02,886,6.8,Cognitive Computing +AI00278,Computer Vision Engineer,87353,CHF,78618,EN,FL,Switzerland,M,Switzerland,50,"Java, Git, AWS",Associate,0,Technology,2025-03-17,2025-04-01,2072,7.5,DataVision Ltd +AI00279,Research Scientist,201368,EUR,171163,EX,FL,Austria,M,Austria,100,"Git, PyTorch, NLP",Associate,10,Transportation,2024-02-16,2024-03-15,2032,6.4,Cognitive Computing +AI00280,AI Consultant,102371,USD,102371,MI,FT,Sweden,M,Sweden,50,"Scala, Java, Linux, AWS",Associate,3,Telecommunications,2024-12-29,2025-02-22,2442,6.5,Cloud AI Solutions +AI00281,Machine Learning Engineer,160729,USD,160729,MI,FT,Denmark,L,Denmark,50,"Python, TensorFlow, Kubernetes, Mathematics, MLOps",PhD,3,Government,2024-03-22,2024-04-12,660,7.8,Cognitive Computing +AI00282,Data Analyst,127341,USD,127341,SE,CT,Ireland,L,Finland,0,"Python, Linux, TensorFlow, Java",Associate,8,Manufacturing,2025-01-07,2025-01-28,1241,6.4,Cognitive Computing +AI00283,AI Product Manager,132125,EUR,112306,SE,FT,Netherlands,L,Netherlands,50,"Deep Learning, Computer Vision, Tableau",Associate,6,Manufacturing,2024-06-13,2024-08-11,1042,7,Advanced Robotics +AI00284,Data Scientist,106892,CAD,133615,MI,PT,Canada,L,Canada,100,"MLOps, Python, Computer Vision, AWS",PhD,2,Gaming,2025-01-18,2025-03-19,2323,5.5,Digital Transformation LLC +AI00285,Machine Learning Researcher,101740,EUR,86479,MI,CT,Germany,L,Germany,100,"Scala, Python, Tableau",Master,3,Finance,2024-08-22,2024-09-18,1429,8.8,DeepTech Ventures +AI00286,Machine Learning Researcher,48965,USD,48965,MI,PT,China,M,China,0,"Python, TensorFlow, Spark, GCP",Bachelor,2,Automotive,2024-11-01,2024-12-26,1541,5.9,Future Systems +AI00287,Autonomous Systems Engineer,53173,USD,53173,EN,FL,Sweden,S,Sweden,50,"TensorFlow, Kubernetes, Python, Data Visualization, GCP",Master,0,Telecommunications,2024-02-09,2024-04-20,1299,8.3,Machine Intelligence Group +AI00288,Computer Vision Engineer,201645,EUR,171398,EX,PT,Netherlands,S,Netherlands,100,"Scala, Kubernetes, Data Visualization",Associate,17,Real Estate,2024-12-11,2025-01-11,1871,9.2,DataVision Ltd +AI00289,Robotics Engineer,47718,USD,47718,MI,FT,China,L,China,100,"R, Kubernetes, AWS, SQL, TensorFlow",Master,3,Retail,2025-01-03,2025-02-09,649,6.2,Neural Networks Co +AI00290,AI Architect,358613,USD,358613,EX,FL,Norway,L,Norway,0,"AWS, Java, Statistics",PhD,16,Telecommunications,2024-08-06,2024-09-17,1555,9.6,Autonomous Tech +AI00291,AI Product Manager,96280,USD,96280,EN,FL,United States,L,United States,50,"Spark, MLOps, SQL, PyTorch, Computer Vision",Bachelor,0,Technology,2024-10-13,2024-12-15,2353,6.2,Digital Transformation LLC +AI00292,ML Ops Engineer,87032,USD,87032,SE,PT,South Korea,S,Netherlands,50,"PyTorch, Linux, Deep Learning",Master,7,Manufacturing,2024-11-13,2025-01-02,1397,5.5,Algorithmic Solutions +AI00293,AI Architect,112059,JPY,12326490,SE,FT,Japan,S,Japan,50,"Docker, Python, Kubernetes, GCP, TensorFlow",Bachelor,9,Education,2024-06-21,2024-08-23,1799,7.3,Machine Intelligence Group +AI00294,AI Specialist,115102,EUR,97837,SE,FT,Austria,L,Austria,100,"Python, Linux, Kubernetes, Hadoop",PhD,7,Automotive,2024-05-10,2024-07-19,2334,9.2,DeepTech Ventures +AI00295,AI Specialist,271779,USD,271779,EX,CT,Ireland,L,Ireland,50,"Computer Vision, Azure, Data Visualization, NLP",Master,11,Automotive,2025-02-06,2025-03-23,1247,9,Cloud AI Solutions +AI00296,AI Research Scientist,66364,CAD,82955,MI,PT,Canada,S,Colombia,50,"Python, SQL, NLP",Bachelor,3,Gaming,2024-08-18,2024-09-01,1891,6.6,AI Innovations +AI00297,Deep Learning Engineer,131466,USD,131466,MI,PT,Norway,L,Norway,50,"R, AWS, Hadoop, NLP, Spark",PhD,2,Automotive,2024-01-02,2024-01-25,1013,7.9,TechCorp Inc +AI00298,Head of AI,42235,USD,42235,EN,FT,South Korea,S,Ghana,100,"Python, Data Visualization, Kubernetes",PhD,1,Government,2024-04-19,2024-06-27,2078,6.4,DeepTech Ventures +AI00299,Deep Learning Engineer,55844,EUR,47467,EN,FL,Netherlands,M,Estonia,50,"Java, NLP, Python, Deep Learning, Computer Vision",PhD,1,Transportation,2024-05-04,2024-07-10,976,7.9,Quantum Computing Inc +AI00300,Machine Learning Researcher,75499,USD,75499,EN,FT,Sweden,L,Sweden,0,"GCP, Linux, Deep Learning, Java, Kubernetes",PhD,1,Education,2024-10-02,2024-10-27,2054,9.6,Future Systems +AI00301,AI Architect,84962,SGD,110451,EN,CT,Singapore,L,Israel,50,"GCP, Data Visualization, Azure",Associate,1,Finance,2024-05-15,2024-06-29,1804,6.2,TechCorp Inc +AI00302,Data Analyst,144336,CHF,129902,MI,CT,Switzerland,M,Switzerland,0,"Data Visualization, Java, Mathematics, AWS",Bachelor,3,Gaming,2025-02-06,2025-03-30,1336,7.8,Machine Intelligence Group +AI00303,AI Consultant,52300,USD,52300,SE,PT,China,S,China,100,"Docker, TensorFlow, GCP",Bachelor,8,Consulting,2024-03-10,2024-04-19,800,9.1,DataVision Ltd +AI00304,Data Engineer,157426,EUR,133812,EX,PT,Austria,S,Turkey,100,"Scala, Tableau, Java",PhD,13,Manufacturing,2025-04-07,2025-05-16,1741,6.2,Cloud AI Solutions +AI00305,Deep Learning Engineer,174692,USD,174692,EX,CT,South Korea,M,Portugal,100,"Linux, Python, TensorFlow",PhD,12,Automotive,2025-04-20,2025-06-27,731,7.9,Autonomous Tech +AI00306,NLP Engineer,142293,USD,142293,MI,PT,Norway,L,Sweden,50,"Git, Java, Deep Learning, Linux, Mathematics",Master,2,Energy,2025-04-05,2025-06-01,1398,7.1,Quantum Computing Inc +AI00307,AI Architect,109818,USD,109818,SE,FL,South Korea,S,South Korea,0,"GCP, Git, Statistics",PhD,9,Consulting,2024-01-04,2024-02-02,2344,5,Advanced Robotics +AI00308,AI Research Scientist,69642,USD,69642,EN,FT,Norway,M,Norway,0,"Java, SQL, Scala, PyTorch, NLP",Master,0,Automotive,2024-01-19,2024-03-31,583,7.9,AI Innovations +AI00309,Principal Data Scientist,70652,EUR,60054,MI,FL,Netherlands,S,Netherlands,50,"Computer Vision, Scala, Mathematics",Master,2,Media,2024-10-30,2024-12-30,1086,9.1,Advanced Robotics +AI00310,Data Analyst,242235,GBP,181676,EX,FL,United Kingdom,L,United Kingdom,100,"R, PyTorch, Docker",Master,12,Education,2024-12-18,2025-03-01,2038,6,Machine Intelligence Group +AI00311,AI Architect,211982,SGD,275577,EX,FT,Singapore,S,Singapore,50,"Hadoop, AWS, Docker",PhD,19,Manufacturing,2024-01-12,2024-02-18,1352,6.8,Machine Intelligence Group +AI00312,Principal Data Scientist,88077,EUR,74865,EN,FL,Germany,L,Germany,100,"Python, GCP, TensorFlow, Mathematics, PyTorch",Bachelor,1,Transportation,2024-02-20,2024-04-18,986,8.2,Machine Intelligence Group +AI00313,Robotics Engineer,107261,EUR,91172,MI,CT,Germany,L,Germany,50,"Hadoop, Tableau, Java, Git",Associate,3,Manufacturing,2024-10-19,2024-11-04,1617,9.7,AI Innovations +AI00314,Computer Vision Engineer,284132,USD,284132,EX,FT,United States,M,United States,0,"Deep Learning, Docker, Hadoop, Data Visualization",Master,10,Government,2025-04-24,2025-07-06,1832,5.1,Autonomous Tech +AI00315,AI Software Engineer,105482,USD,105482,SE,CT,South Korea,M,South Korea,100,"SQL, Git, AWS",PhD,5,Consulting,2025-02-13,2025-04-25,1845,5.9,Cognitive Computing +AI00316,AI Architect,161728,GBP,121296,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, PyTorch",PhD,15,Finance,2025-03-03,2025-04-19,1932,8.6,DataVision Ltd +AI00317,Data Engineer,131352,USD,131352,SE,PT,Norway,S,Sweden,0,"Scala, MLOps, GCP, Java",Bachelor,9,Retail,2024-11-02,2024-12-13,1802,5.8,Machine Intelligence Group +AI00318,Data Analyst,161727,EUR,137468,SE,FT,Austria,L,Finland,100,"Docker, GCP, SQL",PhD,6,Technology,2025-01-26,2025-04-04,1940,5.9,Cognitive Computing +AI00319,Data Analyst,151527,USD,151527,SE,FL,United States,L,Romania,0,"Java, SQL, Kubernetes, Git",PhD,7,Retail,2024-07-18,2024-09-02,845,7.1,Machine Intelligence Group +AI00320,Machine Learning Researcher,112476,USD,112476,SE,FT,Israel,L,Israel,50,"Hadoop, Git, Statistics",Master,6,Consulting,2024-04-20,2024-05-10,2413,8.7,TechCorp Inc +AI00321,ML Ops Engineer,72913,CAD,91141,MI,FT,Canada,M,Canada,0,"R, SQL, Mathematics",PhD,3,Telecommunications,2025-04-01,2025-05-31,941,7,Cognitive Computing +AI00322,Data Analyst,68734,CAD,85918,EN,FT,Canada,L,Malaysia,100,"Computer Vision, Python, TensorFlow, Docker",PhD,1,Finance,2024-08-28,2024-10-24,805,8.5,Algorithmic Solutions +AI00323,NLP Engineer,179564,EUR,152629,EX,FL,Netherlands,S,Netherlands,50,"Python, AWS, Git",Bachelor,11,Government,2024-01-24,2024-03-17,654,9.1,Quantum Computing Inc +AI00324,Data Scientist,71265,GBP,53449,EN,PT,United Kingdom,S,United Kingdom,0,"PyTorch, TensorFlow, Azure, Computer Vision, Java",Bachelor,1,Automotive,2024-03-27,2024-05-12,2172,9.5,DeepTech Ventures +AI00325,Deep Learning Engineer,143064,USD,143064,SE,FL,South Korea,L,Denmark,100,"Scala, Python, TensorFlow",Master,8,Telecommunications,2024-02-26,2024-04-13,1887,7.2,DataVision Ltd +AI00326,Deep Learning Engineer,196042,EUR,166636,EX,CT,Austria,L,Italy,0,"Kubernetes, PyTorch, Tableau, Docker, Computer Vision",PhD,14,Consulting,2025-02-14,2025-03-20,911,7.3,Advanced Robotics +AI00327,Data Engineer,101946,USD,101946,SE,FL,Ireland,S,Ireland,0,"SQL, PyTorch, Data Visualization, Computer Vision",Bachelor,7,Finance,2025-02-14,2025-04-20,1521,7.1,Digital Transformation LLC +AI00328,Autonomous Systems Engineer,89020,GBP,66765,MI,FL,United Kingdom,S,Brazil,50,"Kubernetes, R, Git, AWS",PhD,4,Media,2024-09-06,2024-10-27,1497,9.2,Algorithmic Solutions +AI00329,Autonomous Systems Engineer,134011,JPY,14741210,SE,PT,Japan,S,Israel,100,"Deep Learning, Statistics, Spark",PhD,9,Energy,2024-08-10,2024-09-15,2405,8.8,TechCorp Inc +AI00330,Data Analyst,97657,SGD,126954,MI,CT,Singapore,M,Singapore,100,"Scala, Git, MLOps",Master,2,Gaming,2024-08-28,2024-09-15,2240,8.9,Predictive Systems +AI00331,Deep Learning Engineer,153990,USD,153990,EX,PT,South Korea,M,Luxembourg,50,"Scala, Git, Deep Learning, SQL, Kubernetes",Bachelor,14,Consulting,2024-06-29,2024-08-12,1020,5.7,Algorithmic Solutions +AI00332,Robotics Engineer,124696,EUR,105992,SE,FT,Netherlands,S,Argentina,100,"PyTorch, Python, Computer Vision",PhD,6,Automotive,2024-05-17,2024-07-09,1117,5.5,TechCorp Inc +AI00333,Robotics Engineer,94884,USD,94884,MI,PT,Ireland,S,Ireland,0,"Linux, Hadoop, GCP",Bachelor,2,Retail,2024-11-06,2024-12-19,961,9.2,Cognitive Computing +AI00334,AI Architect,101192,CHF,91073,EN,FT,Switzerland,M,Switzerland,50,"R, Scala, Kubernetes, Git",PhD,0,Transportation,2024-12-28,2025-01-28,1793,5.8,DeepTech Ventures +AI00335,AI Product Manager,106624,USD,106624,SE,FT,Ireland,M,Ireland,100,"Git, Statistics, Azure",Associate,6,Telecommunications,2025-02-02,2025-02-25,2175,5.2,Cognitive Computing +AI00336,Data Scientist,187401,GBP,140551,EX,FT,United Kingdom,M,Germany,100,"TensorFlow, Docker, Spark, Python",Bachelor,12,Energy,2024-10-24,2024-11-11,1400,9.5,TechCorp Inc +AI00337,Data Analyst,165694,USD,165694,EX,FL,United States,M,United States,100,"Python, Kubernetes, MLOps",Associate,15,Retail,2024-01-04,2024-03-15,2434,8.8,DataVision Ltd +AI00338,Machine Learning Engineer,122206,USD,122206,SE,FL,United States,M,United States,50,"Spark, AWS, Linux, SQL, PyTorch",Bachelor,6,Healthcare,2024-01-31,2024-03-06,2282,9.2,Algorithmic Solutions +AI00339,Data Engineer,91226,SGD,118594,MI,PT,Singapore,L,India,0,"Python, TensorFlow, PyTorch, SQL",Bachelor,2,Transportation,2024-12-06,2025-01-16,519,7.7,Autonomous Tech +AI00340,AI Product Manager,110449,CHF,99404,MI,FL,Switzerland,S,Switzerland,100,"Mathematics, Linux, NLP",Bachelor,3,Energy,2025-02-01,2025-02-19,1970,5.9,Algorithmic Solutions +AI00341,AI Architect,275705,EUR,234349,EX,FT,Netherlands,L,Netherlands,100,"MLOps, SQL, Kubernetes, Spark, Java",Bachelor,16,Finance,2024-04-25,2024-05-29,2299,5.4,Future Systems +AI00342,ML Ops Engineer,161670,USD,161670,EX,PT,Finland,M,Brazil,0,"MLOps, Python, TensorFlow, GCP",Associate,11,Technology,2024-08-13,2024-09-18,1061,5.9,Machine Intelligence Group +AI00343,Computer Vision Engineer,95328,GBP,71496,MI,PT,United Kingdom,S,United Kingdom,50,"MLOps, Spark, Git, Deep Learning",PhD,3,Technology,2025-03-25,2025-04-26,734,8.5,Smart Analytics +AI00344,AI Consultant,68548,EUR,58266,EN,PT,Germany,M,Germany,0,"Hadoop, Spark, Statistics, Tableau",Associate,1,Transportation,2025-02-24,2025-03-26,1762,7.8,Digital Transformation LLC +AI00345,AI Consultant,378502,USD,378502,EX,FT,Denmark,L,Denmark,0,"SQL, Mathematics, Scala, Hadoop",Bachelor,12,Consulting,2024-09-29,2024-12-01,2234,8.4,Future Systems +AI00346,NLP Engineer,76682,USD,76682,SE,CT,South Korea,S,South Korea,0,"PyTorch, Kubernetes, Azure, GCP",Master,7,Gaming,2024-09-25,2024-11-12,643,10,Machine Intelligence Group +AI00347,Deep Learning Engineer,108478,USD,108478,MI,CT,Sweden,L,Sweden,0,"Hadoop, Java, Docker, Deep Learning",Master,2,Transportation,2024-04-24,2024-05-10,1436,9.4,Cognitive Computing +AI00348,Research Scientist,114526,JPY,12597860,MI,FL,Japan,M,Belgium,0,"Python, TensorFlow, SQL, NLP",Associate,3,Real Estate,2024-02-16,2024-03-05,1095,5.8,Future Systems +AI00349,AI Specialist,75609,USD,75609,EN,PT,Norway,S,Norway,0,"AWS, Python, Git, Statistics",PhD,0,Government,2024-09-19,2024-11-30,2109,9.9,Algorithmic Solutions +AI00350,Data Analyst,214389,USD,214389,SE,FL,Denmark,L,Denmark,100,"Java, Kubernetes, Python, SQL",Associate,6,Retail,2025-04-29,2025-06-13,2348,8.8,Smart Analytics +AI00351,NLP Engineer,104396,USD,104396,SE,CT,Finland,S,Finland,100,"SQL, Azure, Data Visualization, NLP",Master,7,Telecommunications,2024-08-13,2024-10-15,1398,5.3,Quantum Computing Inc +AI00352,Principal Data Scientist,53469,EUR,45449,EN,PT,France,M,United Kingdom,50,"Docker, Statistics, Data Visualization",PhD,0,Government,2024-01-10,2024-02-20,1249,6,Smart Analytics +AI00353,Head of AI,327929,USD,327929,EX,FL,Denmark,L,Denmark,0,"TensorFlow, Python, Data Visualization, NLP, Tableau",PhD,14,Transportation,2024-02-19,2024-04-14,1000,6.5,Smart Analytics +AI00354,Data Scientist,87984,JPY,9678240,MI,PT,Japan,S,Japan,100,"Computer Vision, Git, Tableau, Data Visualization",Bachelor,2,Consulting,2024-01-08,2024-02-19,560,7.4,Algorithmic Solutions +AI00355,AI Architect,127823,JPY,14060530,SE,CT,Japan,S,Japan,0,"Linux, MLOps, Tableau",Associate,8,Automotive,2025-04-17,2025-05-24,1762,7.3,Future Systems +AI00356,Machine Learning Researcher,93295,AUD,125948,MI,FL,Australia,M,Australia,0,"Spark, Mathematics, Linux",Associate,4,Education,2024-02-10,2024-04-04,582,5.1,Algorithmic Solutions +AI00357,NLP Engineer,25560,USD,25560,MI,PT,India,M,India,50,"Kubernetes, Linux, Tableau, Mathematics",Master,2,Transportation,2024-02-29,2024-04-02,1775,7.5,Cognitive Computing +AI00358,Deep Learning Engineer,110777,GBP,83083,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, Python, GCP",PhD,3,Transportation,2024-07-10,2024-08-31,1446,8.5,Quantum Computing Inc +AI00359,AI Specialist,253223,EUR,215240,EX,FL,Germany,M,Germany,0,"Scala, Kubernetes, SQL, Hadoop, Docker",Bachelor,17,Retail,2024-07-24,2024-08-27,1970,5,Algorithmic Solutions +AI00360,ML Ops Engineer,234867,EUR,199637,EX,PT,Netherlands,M,Israel,0,"Spark, Statistics, MLOps, R",PhD,10,Automotive,2024-11-18,2024-12-27,826,5.1,Digital Transformation LLC +AI00361,AI Consultant,49385,USD,49385,EN,FT,Finland,S,Finland,50,"NLP, Statistics, Hadoop",Master,0,Media,2025-03-28,2025-04-13,1111,6.6,Advanced Robotics +AI00362,Data Scientist,59557,USD,59557,SE,CT,China,L,Denmark,100,"PyTorch, GCP, NLP, Spark",Bachelor,8,Telecommunications,2024-03-26,2024-06-06,977,6.3,TechCorp Inc +AI00363,AI Product Manager,95864,EUR,81484,SE,PT,France,S,France,0,"SQL, Hadoop, Tableau, Data Visualization",Master,6,Energy,2024-01-22,2024-03-27,1764,7.6,Predictive Systems +AI00364,AI Product Manager,217693,USD,217693,EX,PT,Israel,L,Israel,0,"GCP, MLOps, Scala, Kubernetes, Docker",Associate,18,Transportation,2024-04-15,2024-05-19,1099,9.7,Digital Transformation LLC +AI00365,ML Ops Engineer,108994,EUR,92645,MI,FL,France,L,France,100,"Kubernetes, Mathematics, Scala",Associate,2,Energy,2024-07-24,2024-08-31,1864,9.9,AI Innovations +AI00366,AI Software Engineer,75633,USD,75633,MI,FT,South Korea,S,Ghana,100,"Scala, Linux, NLP, R, Computer Vision",Associate,4,Gaming,2024-06-07,2024-06-27,1965,8.1,Advanced Robotics +AI00367,AI Research Scientist,62810,EUR,53389,EN,FL,Germany,S,Germany,100,"Deep Learning, Python, Tableau, Computer Vision, Statistics",Associate,0,Automotive,2025-02-13,2025-04-05,1004,9.7,Predictive Systems +AI00368,Data Engineer,151628,EUR,128884,EX,FT,France,S,France,100,"Python, TensorFlow, Java",Bachelor,15,Real Estate,2024-08-02,2024-09-30,539,8.3,AI Innovations +AI00369,AI Research Scientist,125355,SGD,162962,SE,FL,Singapore,M,Singapore,100,"Docker, NLP, AWS",Master,9,Transportation,2025-02-27,2025-05-07,2194,9.7,Quantum Computing Inc +AI00370,Principal Data Scientist,136102,USD,136102,SE,PT,Denmark,M,Denmark,100,"Linux, PyTorch, Tableau, Mathematics",PhD,7,Telecommunications,2024-03-08,2024-04-08,1973,5.1,Machine Intelligence Group +AI00371,Deep Learning Engineer,56934,EUR,48394,EN,PT,France,L,France,0,"Git, SQL, NLP, PyTorch",PhD,0,Automotive,2024-02-07,2024-03-26,1672,6.9,Advanced Robotics +AI00372,ML Ops Engineer,67190,EUR,57112,MI,FL,France,S,Italy,50,"Scala, Tableau, Python, Docker, Hadoop",Master,4,Gaming,2024-02-18,2024-04-06,1470,8.3,AI Innovations +AI00373,AI Software Engineer,125164,EUR,106389,SE,FL,Austria,L,Austria,50,"Azure, Deep Learning, MLOps, Linux",PhD,9,Transportation,2024-06-26,2024-08-24,2025,5.1,TechCorp Inc +AI00374,NLP Engineer,85407,SGD,111029,EN,PT,Singapore,L,Singapore,50,"Statistics, GCP, AWS, SQL",Master,1,Media,2024-07-08,2024-09-17,646,8.2,Autonomous Tech +AI00375,ML Ops Engineer,112057,JPY,12326270,SE,FL,Japan,S,Japan,0,"Python, TensorFlow, PyTorch, SQL, Deep Learning",Master,7,Manufacturing,2025-03-13,2025-04-03,789,8.5,Neural Networks Co +AI00376,ML Ops Engineer,95078,USD,95078,MI,CT,Denmark,M,Denmark,0,"SQL, MLOps, Scala",Bachelor,3,Automotive,2025-02-26,2025-04-21,1839,5.7,Quantum Computing Inc +AI00377,AI Product Manager,198651,USD,198651,EX,CT,Norway,M,Norway,100,"SQL, Spark, TensorFlow, Deep Learning, Kubernetes",Bachelor,18,Retail,2024-05-08,2024-05-27,2463,5.7,DeepTech Ventures +AI00378,AI Software Engineer,220998,JPY,24309780,EX,CT,Japan,S,India,50,"SQL, Linux, Tableau, Azure, Scala",Bachelor,12,Education,2024-05-04,2024-06-16,731,7.3,Cloud AI Solutions +AI00379,NLP Engineer,74126,USD,74126,EX,FT,India,S,India,100,"Scala, PyTorch, Docker, Deep Learning, SQL",PhD,12,Government,2024-09-22,2024-10-29,1926,7.5,Predictive Systems +AI00380,Machine Learning Engineer,75172,EUR,63896,MI,CT,Austria,S,Austria,100,"SQL, Kubernetes, Docker, NLP",Associate,4,Media,2024-09-09,2024-11-15,2261,8.5,Cognitive Computing +AI00381,Deep Learning Engineer,60975,EUR,51829,EN,FT,Austria,L,Austria,100,"SQL, Hadoop, Tableau, Kubernetes",Master,1,Transportation,2024-11-21,2025-01-29,620,9.6,Cloud AI Solutions +AI00382,Principal Data Scientist,89175,EUR,75799,MI,FT,Germany,L,Singapore,0,"Computer Vision, AWS, GCP, Deep Learning, Spark",PhD,2,Manufacturing,2024-01-11,2024-02-21,2215,8.9,Digital Transformation LLC +AI00383,Computer Vision Engineer,149285,EUR,126892,SE,FL,Netherlands,L,Netherlands,50,"Python, Mathematics, Kubernetes",PhD,5,Education,2025-01-06,2025-03-02,1359,5.4,Predictive Systems +AI00384,AI Product Manager,192204,EUR,163373,EX,FT,Germany,M,Germany,0,"Mathematics, Linux, SQL",Bachelor,13,Media,2025-02-01,2025-03-10,1161,6.7,Future Systems +AI00385,NLP Engineer,94197,CHF,84777,MI,PT,Switzerland,S,Norway,100,"Spark, TensorFlow, Deep Learning, GCP",Associate,4,Finance,2024-09-28,2024-10-28,1172,5.3,Future Systems +AI00386,Autonomous Systems Engineer,90408,EUR,76847,EN,FL,Germany,L,Czech Republic,100,"Linux, SQL, Git",PhD,1,Technology,2024-01-25,2024-03-10,892,7.1,Autonomous Tech +AI00387,ML Ops Engineer,72940,USD,72940,MI,FT,Ireland,S,Czech Republic,0,"GCP, Hadoop, Java",PhD,3,Technology,2024-03-24,2024-05-07,1913,8.1,DeepTech Ventures +AI00388,Machine Learning Engineer,140696,JPY,15476560,SE,PT,Japan,S,Japan,0,"AWS, Java, GCP",Master,9,Real Estate,2024-04-03,2024-04-25,1774,5.6,Neural Networks Co +AI00389,Robotics Engineer,210902,CHF,189812,EX,FT,Switzerland,S,Switzerland,0,"Java, NLP, TensorFlow, PyTorch, Git",Bachelor,12,Real Estate,2024-09-25,2024-11-28,982,9.8,Cognitive Computing +AI00390,Computer Vision Engineer,78559,SGD,102127,EN,FL,Singapore,M,Singapore,100,"Python, PyTorch, Computer Vision",Bachelor,0,Automotive,2024-12-03,2025-01-13,586,5,AI Innovations +AI00391,AI Consultant,32923,USD,32923,MI,FT,India,M,India,50,"Kubernetes, MLOps, PyTorch, Linux, AWS",Master,4,Gaming,2024-01-20,2024-03-26,1442,9.2,AI Innovations +AI00392,Research Scientist,112363,JPY,12359930,SE,FL,Japan,S,Ukraine,0,"Python, TensorFlow, Azure, NLP, Data Visualization",Bachelor,9,Finance,2024-04-26,2024-05-12,843,9.4,Autonomous Tech +AI00393,AI Consultant,188028,USD,188028,EX,CT,United States,L,United States,50,"Scala, SQL, NLP",Associate,11,Retail,2025-04-25,2025-06-22,852,8.9,Quantum Computing Inc +AI00394,AI Product Manager,165794,USD,165794,EX,FT,Norway,S,United States,100,"Python, Azure, R, Kubernetes",Bachelor,16,Gaming,2025-01-26,2025-03-16,903,8.6,Advanced Robotics +AI00395,ML Ops Engineer,109778,EUR,93311,MI,FL,Netherlands,L,Netherlands,50,"Scala, GCP, Mathematics",PhD,3,Media,2024-02-11,2024-02-28,2366,8.9,Smart Analytics +AI00396,Head of AI,162918,USD,162918,EX,FL,Ireland,L,Ireland,0,"Hadoop, AWS, Scala",Bachelor,17,Consulting,2024-10-16,2024-12-12,721,5.5,TechCorp Inc +AI00397,Autonomous Systems Engineer,219603,USD,219603,EX,PT,United States,M,United States,0,"Python, Mathematics, Data Visualization",PhD,12,Transportation,2024-05-06,2024-06-16,894,8.5,DeepTech Ventures +AI00398,Head of AI,304991,CHF,274492,EX,FT,Switzerland,L,Switzerland,100,"Azure, PyTorch, Kubernetes, NLP, Java",Associate,17,Manufacturing,2024-03-08,2024-04-15,2314,6.5,Algorithmic Solutions +AI00399,AI Research Scientist,99431,AUD,134232,SE,FL,Australia,S,Estonia,50,"Kubernetes, TensorFlow, SQL",Associate,5,Retail,2024-04-09,2024-05-19,1227,6.7,DeepTech Ventures +AI00400,Data Scientist,92131,USD,92131,MI,CT,Sweden,L,Sweden,0,"SQL, Git, Statistics",Bachelor,3,Retail,2024-04-29,2024-07-01,1590,6.2,Digital Transformation LLC +AI00401,Research Scientist,111236,JPY,12235960,MI,FL,Japan,M,Japan,100,"Python, Spark, Linux, TensorFlow, Java",Master,3,Media,2025-03-05,2025-04-08,1407,6.1,Cloud AI Solutions +AI00402,AI Research Scientist,263705,USD,263705,EX,CT,Norway,M,Norway,0,"SQL, Scala, Linux",Bachelor,10,Technology,2024-12-16,2025-01-24,870,6.3,Cognitive Computing +AI00403,Head of AI,37401,USD,37401,MI,CT,China,S,Colombia,0,"Linux, Deep Learning, Statistics",Bachelor,2,Real Estate,2025-03-27,2025-06-04,728,8.3,Smart Analytics +AI00404,ML Ops Engineer,122481,GBP,91861,MI,FT,United Kingdom,L,Mexico,50,"MLOps, Tableau, Hadoop, AWS",Bachelor,3,Healthcare,2025-02-03,2025-03-11,1575,8,DeepTech Ventures +AI00405,Deep Learning Engineer,29050,USD,29050,EN,FL,India,L,India,50,"Spark, Azure, TensorFlow, Mathematics",Master,0,Real Estate,2024-05-24,2024-06-10,1106,6.7,Neural Networks Co +AI00406,Principal Data Scientist,142280,GBP,106710,SE,FT,United Kingdom,L,United Kingdom,100,"NLP, SQL, GCP, Kubernetes",Bachelor,9,Transportation,2024-08-30,2024-10-04,1311,9.9,TechCorp Inc +AI00407,AI Consultant,75989,USD,75989,EN,PT,United States,L,United States,0,"SQL, Java, TensorFlow, MLOps",PhD,0,Healthcare,2024-09-25,2024-11-19,2338,6.3,TechCorp Inc +AI00408,Computer Vision Engineer,103477,SGD,134520,SE,PT,Singapore,S,Singapore,100,"Scala, Data Visualization, TensorFlow, Azure, Statistics",Associate,6,Gaming,2024-02-11,2024-03-28,2343,8.9,Advanced Robotics +AI00409,ML Ops Engineer,111121,USD,111121,MI,FT,United States,S,United States,100,"Docker, Scala, Git, R",Associate,3,Healthcare,2024-03-05,2024-03-22,1349,7.6,Algorithmic Solutions +AI00410,Data Engineer,357359,CHF,321623,EX,CT,Switzerland,M,Switzerland,100,"PyTorch, MLOps, R, Scala, Tableau",PhD,19,Consulting,2024-06-28,2024-08-06,1855,7.3,Machine Intelligence Group +AI00411,ML Ops Engineer,107663,CAD,134579,MI,FT,Canada,L,Canada,100,"Docker, SQL, AWS, Computer Vision, Deep Learning",Bachelor,2,Education,2024-08-06,2024-09-10,683,5.3,Algorithmic Solutions +AI00412,Data Scientist,83352,GBP,62514,MI,PT,United Kingdom,S,United Kingdom,0,"PyTorch, SQL, GCP, AWS, TensorFlow",Bachelor,2,Education,2024-10-12,2024-11-07,1599,6.6,Future Systems +AI00413,Deep Learning Engineer,55431,GBP,41573,EN,CT,United Kingdom,S,United Kingdom,100,"Data Visualization, Git, Computer Vision, Kubernetes",Master,0,Retail,2024-03-08,2024-04-26,721,9.9,Cognitive Computing +AI00414,Data Scientist,149644,EUR,127197,SE,CT,Germany,M,Germany,100,"Git, Kubernetes, Linux",Associate,9,Education,2024-03-19,2024-04-18,825,7.7,Algorithmic Solutions +AI00415,AI Software Engineer,94453,USD,94453,MI,FT,Ireland,S,Ireland,50,"Computer Vision, Spark, SQL, GCP",PhD,2,Gaming,2025-04-05,2025-06-01,1352,5.2,Machine Intelligence Group +AI00416,Robotics Engineer,40773,USD,40773,MI,FT,China,M,China,0,"Python, Kubernetes, Docker, GCP",Bachelor,2,Finance,2024-05-26,2024-06-14,2359,6,Neural Networks Co +AI00417,AI Consultant,94832,CAD,118540,MI,CT,Canada,L,Australia,50,"GCP, TensorFlow, Linux",PhD,2,Education,2025-03-21,2025-05-18,1023,8.7,Advanced Robotics +AI00418,AI Specialist,66884,EUR,56851,EN,CT,Austria,L,Austria,100,"TensorFlow, AWS, Python, Mathematics, Deep Learning",Master,1,Transportation,2024-10-28,2024-12-18,1927,7.9,Quantum Computing Inc +AI00419,ML Ops Engineer,222209,USD,222209,SE,FL,Norway,L,Norway,50,"TensorFlow, SQL, Deep Learning",PhD,7,Finance,2024-03-15,2024-05-07,1846,6.3,Autonomous Tech +AI00420,Robotics Engineer,181591,JPY,19975010,EX,FL,Japan,S,Romania,50,"Python, TensorFlow, Java, Linux",Associate,15,Real Estate,2024-06-06,2024-07-19,2025,7.4,Cognitive Computing +AI00421,AI Research Scientist,70146,USD,70146,EN,PT,Sweden,M,Sweden,0,"Python, Azure, Deep Learning, TensorFlow, Data Visualization",Bachelor,1,Healthcare,2025-03-29,2025-05-17,1790,7,Quantum Computing Inc +AI00422,AI Software Engineer,77528,USD,77528,MI,CT,Ireland,M,Ireland,100,"Python, Spark, TensorFlow, Statistics, Java",Bachelor,2,Gaming,2024-01-12,2024-03-05,950,6.7,Future Systems +AI00423,AI Software Engineer,133696,CAD,167120,EX,FL,Canada,M,Canada,50,"AWS, Deep Learning, R, Computer Vision",Master,15,Government,2024-09-21,2024-11-28,2050,6.5,Neural Networks Co +AI00424,Deep Learning Engineer,266317,USD,266317,EX,FL,Norway,M,Norway,0,"R, GCP, MLOps, Azure, Python",Associate,19,Technology,2024-05-16,2024-07-07,970,5.3,Predictive Systems +AI00425,Head of AI,171903,USD,171903,EX,CT,Israel,L,India,100,"Kubernetes, Spark, Docker, Scala, Hadoop",Master,19,Healthcare,2024-07-27,2024-09-03,2156,9.3,Advanced Robotics +AI00426,Research Scientist,134807,CAD,168509,EX,FL,Canada,M,Denmark,0,"GCP, Kubernetes, SQL, Azure, Computer Vision",Bachelor,17,Manufacturing,2024-08-22,2024-09-05,1624,8.8,Digital Transformation LLC +AI00427,AI Product Manager,123091,EUR,104627,SE,FL,France,S,France,0,"Scala, TensorFlow, Spark, SQL",Bachelor,6,Consulting,2025-02-13,2025-03-31,2071,6,Digital Transformation LLC +AI00428,Data Engineer,55885,USD,55885,SE,FT,China,S,China,50,"Python, R, MLOps, Kubernetes",Bachelor,9,Education,2024-08-30,2024-09-19,875,8,Neural Networks Co +AI00429,Robotics Engineer,190416,USD,190416,EX,PT,Israel,S,Israel,100,"Linux, Hadoop, Kubernetes, Computer Vision, Deep Learning",Master,11,Finance,2024-10-11,2024-11-20,1500,9.8,Quantum Computing Inc +AI00430,Deep Learning Engineer,155137,USD,155137,SE,FL,Norway,S,Argentina,100,"Git, PyTorch, TensorFlow, SQL, Python",Master,6,Real Estate,2025-02-20,2025-03-22,2010,6.3,Predictive Systems +AI00431,Deep Learning Engineer,233502,SGD,303553,EX,FL,Singapore,L,Singapore,0,"Azure, Hadoop, R",Bachelor,14,Gaming,2025-02-13,2025-02-27,1261,9.1,Neural Networks Co +AI00432,Autonomous Systems Engineer,106241,USD,106241,SE,FT,South Korea,L,South Korea,100,"SQL, NLP, Python, Java",Associate,7,Consulting,2024-04-19,2024-06-12,1827,8.3,Advanced Robotics +AI00433,Principal Data Scientist,170331,JPY,18736410,EX,PT,Japan,L,China,100,"Kubernetes, Python, Computer Vision, Deep Learning",Master,17,Transportation,2025-01-11,2025-02-01,602,5.6,Autonomous Tech +AI00434,Machine Learning Researcher,190752,USD,190752,SE,PT,Denmark,M,Denmark,100,"TensorFlow, Spark, Deep Learning",Master,9,Gaming,2025-01-05,2025-02-01,1336,7.6,DeepTech Ventures +AI00435,Machine Learning Engineer,57858,JPY,6364380,EN,FL,Japan,S,Japan,0,"SQL, Hadoop, AWS, Mathematics",Bachelor,0,Consulting,2024-10-15,2024-11-10,1143,8.3,DataVision Ltd +AI00436,AI Consultant,60290,EUR,51247,EN,FT,Germany,M,Germany,50,"Computer Vision, MLOps, R",Associate,0,Real Estate,2024-09-01,2024-09-22,1266,9.6,Autonomous Tech +AI00437,Machine Learning Researcher,78662,USD,78662,MI,CT,South Korea,L,Norway,0,"Spark, Computer Vision, Mathematics",PhD,2,Technology,2024-02-09,2024-04-12,1998,9.9,Cloud AI Solutions +AI00438,Deep Learning Engineer,68057,USD,68057,EN,CT,Denmark,S,Denmark,0,"R, MLOps, AWS, Python",Master,1,Real Estate,2024-03-15,2024-05-12,2060,6.3,Cognitive Computing +AI00439,Data Engineer,152822,USD,152822,SE,CT,United States,M,India,50,"Git, Mathematics, Docker",Master,5,Healthcare,2025-03-29,2025-04-14,1541,5.8,Advanced Robotics +AI00440,Head of AI,168351,USD,168351,SE,FL,Sweden,L,Sweden,100,"Docker, Spark, Data Visualization, GCP",Bachelor,7,Energy,2025-03-03,2025-03-17,1746,9.3,TechCorp Inc +AI00441,Machine Learning Researcher,280392,USD,280392,EX,FT,United States,M,United States,0,"Docker, Hadoop, Azure, Python, Scala",Associate,15,Government,2024-10-17,2024-12-06,1427,5.8,Neural Networks Co +AI00442,AI Specialist,165716,USD,165716,EX,FL,Finland,L,Norway,50,"Data Visualization, R, Java",PhD,18,Media,2025-04-18,2025-05-22,2251,6.2,Quantum Computing Inc +AI00443,Computer Vision Engineer,187794,USD,187794,EX,FT,Finland,M,Finland,0,"Git, AWS, SQL, Kubernetes",PhD,11,Energy,2024-09-17,2024-10-02,1284,9,Quantum Computing Inc +AI00444,NLP Engineer,245697,EUR,208842,EX,FT,Germany,L,Germany,0,"GCP, Python, Mathematics",PhD,10,Healthcare,2024-08-22,2024-09-07,2112,9,Cognitive Computing +AI00445,Data Analyst,79411,CAD,99264,MI,CT,Canada,S,Canada,0,"SQL, Linux, Git, PyTorch, NLP",Master,3,Retail,2025-01-16,2025-02-27,2121,7.8,DeepTech Ventures +AI00446,AI Software Engineer,117847,USD,117847,SE,FT,South Korea,L,South Korea,100,"Scala, Python, Hadoop, Docker",Associate,7,Finance,2024-12-03,2024-12-17,1511,5.3,Cloud AI Solutions +AI00447,Principal Data Scientist,112962,GBP,84722,SE,FT,United Kingdom,M,Canada,100,"SQL, Python, Kubernetes, TensorFlow, Docker",Associate,9,Media,2024-06-04,2024-06-29,905,6.9,Machine Intelligence Group +AI00448,AI Product Manager,166397,AUD,224636,SE,FT,Australia,L,Australia,100,"Git, NLP, GCP, TensorFlow, Python",Master,7,Real Estate,2024-11-10,2024-12-01,2239,5,DeepTech Ventures +AI00449,Machine Learning Engineer,135988,USD,135988,SE,PT,Denmark,M,Israel,100,"Azure, Scala, GCP, MLOps",Bachelor,5,Media,2024-01-09,2024-03-08,1645,9.9,Neural Networks Co +AI00450,AI Specialist,30929,USD,30929,MI,FT,India,M,India,100,"Git, Azure, Kubernetes, R, SQL",PhD,2,Consulting,2024-04-14,2024-05-07,1963,9.6,DataVision Ltd +AI00451,Machine Learning Engineer,112165,EUR,95340,SE,FL,Germany,M,Germany,50,"Azure, AWS, Spark",Master,5,Technology,2024-02-11,2024-03-05,2021,8.9,Smart Analytics +AI00452,Data Scientist,100758,EUR,85644,MI,FL,Germany,M,Germany,100,"Python, Scala, NLP, Spark",Associate,4,Telecommunications,2024-04-21,2024-05-24,1162,9.1,Predictive Systems +AI00453,Principal Data Scientist,83754,USD,83754,EN,PT,Norway,L,United Kingdom,100,"Mathematics, Computer Vision, Git",Master,0,Finance,2025-01-15,2025-02-06,2164,7.8,Cloud AI Solutions +AI00454,Head of AI,109895,CHF,98906,MI,PT,Switzerland,S,Switzerland,100,"Tableau, Scala, Python",Associate,4,Consulting,2024-03-08,2024-04-25,2487,8.9,AI Innovations +AI00455,Machine Learning Engineer,160760,EUR,136646,EX,FT,Netherlands,M,Netherlands,50,"NLP, Linux, TensorFlow, Data Visualization",Bachelor,11,Energy,2024-02-23,2024-04-19,1258,7.1,Algorithmic Solutions +AI00456,Machine Learning Engineer,167415,AUD,226010,SE,PT,Australia,L,Australia,100,"Linux, Python, TensorFlow",Bachelor,5,Energy,2024-11-15,2024-12-04,2488,6.7,DataVision Ltd +AI00457,Data Scientist,58948,AUD,79580,EN,CT,Australia,L,Australia,100,"Azure, NLP, PyTorch",Master,1,Healthcare,2024-07-13,2024-09-09,515,7.4,Cloud AI Solutions +AI00458,ML Ops Engineer,73406,USD,73406,MI,CT,South Korea,L,South Korea,0,"Mathematics, Java, R",Bachelor,3,Retail,2024-12-28,2025-01-15,677,6,DeepTech Ventures +AI00459,AI Software Engineer,153534,EUR,130504,EX,FT,Austria,L,Austria,100,"MLOps, Linux, Docker, PyTorch",Associate,19,Gaming,2024-06-04,2024-07-16,1625,7.5,Predictive Systems +AI00460,Data Scientist,81787,JPY,8996570,MI,PT,Japan,M,Japan,50,"Java, Spark, AWS, Linux, MLOps",PhD,4,Manufacturing,2025-03-08,2025-05-11,577,5.9,Predictive Systems +AI00461,Computer Vision Engineer,121967,USD,121967,MI,PT,Ireland,L,Ireland,0,"AWS, TensorFlow, Statistics, Mathematics",Master,4,Finance,2024-06-30,2024-08-19,914,6.5,Algorithmic Solutions +AI00462,Data Analyst,181438,JPY,19958180,EX,CT,Japan,S,Japan,50,"Java, Spark, TensorFlow",Associate,14,Real Estate,2025-01-25,2025-03-04,2075,5.5,Quantum Computing Inc +AI00463,Autonomous Systems Engineer,60296,USD,60296,EN,PT,Ireland,L,Ireland,50,"Spark, Azure, PyTorch, Python, TensorFlow",Master,1,Retail,2025-01-21,2025-02-26,635,7.3,Algorithmic Solutions +AI00464,AI Specialist,64191,USD,64191,EN,PT,Sweden,M,Vietnam,50,"Kubernetes, Linux, Data Visualization, PyTorch",Master,1,Healthcare,2024-11-26,2024-12-11,2243,5.6,Future Systems +AI00465,AI Research Scientist,96896,CHF,87206,EN,FL,Switzerland,S,Italy,50,"Python, Scala, Azure, Hadoop",PhD,0,Gaming,2024-09-25,2024-12-05,1137,7.4,Algorithmic Solutions +AI00466,Principal Data Scientist,78105,USD,78105,MI,PT,South Korea,M,South Korea,50,"Scala, SQL, Data Visualization",Bachelor,2,Healthcare,2025-02-14,2025-03-24,2258,5.2,Predictive Systems +AI00467,Robotics Engineer,71686,EUR,60933,EN,PT,Germany,S,Germany,50,"Kubernetes, PyTorch, Linux",Master,0,Retail,2024-09-21,2024-10-20,1282,8,Cognitive Computing +AI00468,AI Research Scientist,148827,EUR,126503,SE,PT,Germany,M,Australia,0,"Python, Spark, NLP, R",Associate,9,Finance,2024-11-27,2025-01-31,1119,5,Neural Networks Co +AI00469,Data Analyst,92179,CAD,115224,SE,FL,Canada,S,Canada,100,"Python, Tableau, TensorFlow, GCP",Associate,8,Transportation,2025-03-01,2025-05-01,2487,8.2,Cognitive Computing +AI00470,Computer Vision Engineer,75460,EUR,64141,MI,FL,Austria,M,Austria,50,"Computer Vision, NLP, Kubernetes",Bachelor,3,Retail,2024-09-27,2024-11-17,1175,6.1,Advanced Robotics +AI00471,AI Architect,146580,EUR,124593,EX,PT,Netherlands,M,Netherlands,50,"Git, Docker, Mathematics, SQL",Associate,17,Education,2024-10-23,2024-12-20,1494,9.8,DataVision Ltd +AI00472,Data Analyst,68722,USD,68722,EN,FL,United States,S,Finland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Technology,2025-01-11,2025-03-06,1575,6.3,Neural Networks Co +AI00473,ML Ops Engineer,60841,USD,60841,EN,CT,United States,S,United States,50,"NLP, Scala, AWS, SQL, Hadoop",PhD,1,Automotive,2025-03-22,2025-05-27,2340,5.4,Machine Intelligence Group +AI00474,Deep Learning Engineer,49130,USD,49130,EN,FL,Sweden,S,Luxembourg,50,"TensorFlow, Python, Data Visualization, Deep Learning, AWS",Master,0,Education,2025-04-12,2025-05-16,2022,9.1,Advanced Robotics +AI00475,AI Product Manager,162683,USD,162683,SE,FT,Finland,L,Finland,50,"Python, TensorFlow, NLP, Kubernetes, Statistics",Master,9,Consulting,2024-12-30,2025-03-07,1100,9.1,Algorithmic Solutions +AI00476,Data Analyst,151676,EUR,128925,SE,PT,Germany,M,Germany,50,"Java, Hadoop, Data Visualization, MLOps, TensorFlow",Master,8,Government,2024-12-07,2025-01-15,1822,8.9,Advanced Robotics +AI00477,Head of AI,140928,USD,140928,MI,CT,Norway,M,Philippines,50,"Linux, TensorFlow, Hadoop, Docker",Master,4,Education,2024-04-10,2024-06-22,1543,8.9,DeepTech Ventures +AI00478,AI Specialist,140382,AUD,189516,SE,FL,Australia,M,Colombia,100,"Mathematics, GCP, Python, TensorFlow, NLP",Associate,8,Finance,2024-09-26,2024-11-22,2458,6.8,Cloud AI Solutions +AI00479,Machine Learning Engineer,179691,USD,179691,EX,CT,Ireland,S,Egypt,0,"TensorFlow, PyTorch, Scala, AWS",Bachelor,18,Energy,2024-09-29,2024-10-26,2128,6.7,Predictive Systems +AI00480,Principal Data Scientist,132280,EUR,112438,SE,FL,France,L,France,100,"Docker, Linux, Tableau, Git",PhD,8,Retail,2024-10-24,2024-12-14,599,8.1,Future Systems +AI00481,Computer Vision Engineer,90861,USD,90861,MI,FL,Norway,S,Norway,0,"Linux, SQL, R, Git, AWS",Associate,4,Telecommunications,2024-05-23,2024-07-14,783,7.9,Predictive Systems +AI00482,Data Engineer,102239,USD,102239,EX,PT,China,L,China,50,"Hadoop, Linux, R",Master,11,Technology,2025-04-16,2025-05-04,1574,9.5,Predictive Systems +AI00483,Machine Learning Engineer,71795,EUR,61026,EN,CT,Germany,M,Germany,0,"Python, Computer Vision, Hadoop, GCP, SQL",Master,1,Energy,2024-06-17,2024-08-13,2350,5.4,AI Innovations +AI00484,NLP Engineer,55230,EUR,46946,EN,FL,France,L,France,0,"Tableau, Data Visualization, Git, Linux, Hadoop",PhD,1,Media,2024-03-17,2024-04-02,840,9,Cognitive Computing +AI00485,AI Consultant,56030,EUR,47626,EN,PT,Germany,M,United States,50,"Docker, Deep Learning, Kubernetes, Spark",Bachelor,1,Government,2024-07-22,2024-08-20,1612,7.1,Autonomous Tech +AI00486,Head of AI,99246,USD,99246,EX,PT,India,L,India,100,"Spark, SQL, PyTorch, Java",Associate,17,Real Estate,2024-09-15,2024-11-02,1339,7.8,Predictive Systems +AI00487,AI Product Manager,130136,CAD,162670,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, TensorFlow, Computer Vision, Hadoop",PhD,11,Consulting,2025-01-05,2025-01-31,2026,6.3,DeepTech Ventures +AI00488,AI Research Scientist,51311,JPY,5644210,EN,FL,Japan,S,Japan,100,"Tableau, Linux, TensorFlow, Data Visualization",PhD,1,Telecommunications,2025-01-15,2025-03-09,856,6.7,Digital Transformation LLC +AI00489,Machine Learning Engineer,59010,USD,59010,EN,FL,South Korea,S,South Korea,100,"Hadoop, Computer Vision, Mathematics, GCP, Git",Associate,1,Real Estate,2024-12-27,2025-02-09,1203,9.1,Quantum Computing Inc +AI00490,AI Research Scientist,139257,USD,139257,SE,CT,United States,L,United States,50,"Azure, TensorFlow, Kubernetes, Computer Vision, Hadoop",Master,5,Manufacturing,2024-02-27,2024-03-25,1275,7.4,DataVision Ltd +AI00491,Data Analyst,50920,USD,50920,EN,FL,Finland,S,Finland,0,"Git, Scala, SQL",Master,0,Manufacturing,2024-11-05,2024-12-13,2039,8.6,Smart Analytics +AI00492,AI Specialist,116377,CHF,104739,EN,CT,Switzerland,L,Indonesia,100,"Azure, Scala, Deep Learning, Computer Vision, Statistics",Associate,0,Finance,2025-01-16,2025-02-01,1586,7,DeepTech Ventures +AI00493,Principal Data Scientist,101911,CHF,91720,EN,FT,Switzerland,M,France,0,"Linux, GCP, NLP",Associate,0,Education,2024-11-06,2024-12-23,1975,7.1,Cognitive Computing +AI00494,Data Analyst,92714,EUR,78807,EN,PT,Netherlands,L,Portugal,50,"Java, Mathematics, Tableau, Spark, PyTorch",Master,1,Technology,2024-03-17,2024-03-31,1305,9.3,Neural Networks Co +AI00495,Head of AI,83757,GBP,62818,EN,CT,United Kingdom,L,United Kingdom,0,"Statistics, Mathematics, Data Visualization",Bachelor,0,Media,2024-08-09,2024-09-20,1023,5,Advanced Robotics +AI00496,AI Specialist,88018,CAD,110023,MI,PT,Canada,L,Canada,50,"MLOps, NLP, SQL, Data Visualization",Master,2,Energy,2025-04-03,2025-04-29,1955,5.2,DataVision Ltd +AI00497,Data Scientist,51864,USD,51864,EN,FT,Finland,S,Finland,100,"Computer Vision, Scala, Data Visualization",Master,1,Transportation,2024-03-05,2024-05-02,2470,6.3,Cloud AI Solutions +AI00498,Head of AI,96976,SGD,126069,MI,CT,Singapore,L,Indonesia,50,"Spark, Hadoop, Scala, Linux",Associate,4,Manufacturing,2024-06-03,2024-07-08,1038,9.4,Predictive Systems +AI00499,Computer Vision Engineer,120263,USD,120263,EX,FT,South Korea,M,Chile,100,"Python, GCP, Spark",Bachelor,13,Retail,2024-10-23,2024-12-08,2046,6.7,Predictive Systems +AI00500,Data Scientist,178114,CHF,160303,SE,PT,Switzerland,S,Colombia,0,"AWS, Java, GCP",PhD,9,Consulting,2024-11-17,2024-12-31,1369,5.7,Cognitive Computing +AI00501,AI Research Scientist,94379,AUD,127412,MI,CT,Australia,L,Australia,50,"TensorFlow, GCP, PyTorch",Master,3,Finance,2025-01-05,2025-01-28,784,7.9,DeepTech Ventures +AI00502,AI Software Engineer,268149,USD,268149,EX,FT,Norway,M,Norway,0,"Git, Python, Azure, Statistics, AWS",PhD,17,Media,2024-02-03,2024-03-15,1961,5.6,Machine Intelligence Group +AI00503,NLP Engineer,90472,CAD,113090,MI,CT,Canada,L,Canada,0,"Mathematics, AWS, Git, Kubernetes, SQL",Master,3,Finance,2024-10-07,2024-11-18,1473,8.7,Quantum Computing Inc +AI00504,AI Product Manager,86547,USD,86547,SE,FT,Israel,S,Israel,0,"Git, Computer Vision, NLP, R",PhD,7,Healthcare,2024-11-08,2025-01-02,1978,8.8,Machine Intelligence Group +AI00505,AI Consultant,150700,EUR,128095,SE,CT,France,L,India,0,"Computer Vision, Azure, Data Visualization, Scala",PhD,6,Retail,2024-06-08,2024-07-06,2425,8.1,Predictive Systems +AI00506,AI Specialist,216740,USD,216740,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Azure, Python, Linux, Docker",Bachelor,14,Healthcare,2025-04-14,2025-05-01,1701,5.3,TechCorp Inc +AI00507,AI Software Engineer,59227,EUR,50343,EN,FL,Netherlands,M,Netherlands,0,"Docker, Tableau, Kubernetes",PhD,1,Healthcare,2025-01-22,2025-02-19,624,9.7,TechCorp Inc +AI00508,AI Software Engineer,163281,CAD,204101,SE,PT,Canada,L,Canada,0,"Git, TensorFlow, Tableau",PhD,5,Transportation,2025-01-20,2025-02-18,2007,7.3,Advanced Robotics +AI00509,Data Engineer,66305,USD,66305,EN,FT,United States,S,Estonia,100,"GCP, Java, AWS, Data Visualization",PhD,1,Transportation,2024-11-09,2024-12-30,1348,6.9,Smart Analytics +AI00510,AI Consultant,126408,CAD,158010,SE,PT,Canada,L,Canada,100,"Spark, Python, GCP, SQL",Bachelor,6,Automotive,2024-08-11,2024-09-18,1300,6.6,Machine Intelligence Group +AI00511,NLP Engineer,144024,EUR,122420,SE,FL,Netherlands,L,Netherlands,100,"AWS, R, Deep Learning, Kubernetes",Associate,7,Automotive,2024-07-03,2024-08-09,1552,9.6,Smart Analytics +AI00512,AI Software Engineer,108805,USD,108805,SE,FT,South Korea,M,South Korea,0,"AWS, Azure, Linux, Mathematics",Master,6,Transportation,2024-12-25,2025-02-08,2105,8.1,Cognitive Computing +AI00513,Data Analyst,79093,EUR,67229,MI,PT,France,M,Ireland,50,"Linux, Java, Tableau",PhD,3,Energy,2024-08-11,2024-09-03,837,8.9,Cloud AI Solutions +AI00514,Machine Learning Engineer,295893,USD,295893,EX,PT,Denmark,S,Denmark,50,"Spark, Python, Java, NLP, TensorFlow",Bachelor,15,Retail,2024-04-13,2024-06-18,1210,7.9,Algorithmic Solutions +AI00515,AI Specialist,83000,JPY,9130000,MI,FT,Japan,M,Japan,50,"TensorFlow, Hadoop, Data Visualization",PhD,2,Education,2024-12-12,2025-01-23,1006,5.2,Quantum Computing Inc +AI00516,AI Software Engineer,80124,USD,80124,EN,CT,United States,M,United States,0,"R, AWS, Hadoop, Kubernetes",Master,0,Education,2024-11-07,2024-12-14,665,9.8,Autonomous Tech +AI00517,Data Engineer,69336,EUR,58936,EN,FL,Germany,L,Vietnam,0,"Mathematics, Spark, Python",Bachelor,1,Gaming,2024-12-28,2025-01-30,1975,9.8,Autonomous Tech +AI00518,Data Engineer,42380,USD,42380,SE,FL,India,L,United States,0,"Azure, Docker, Java, MLOps",Master,5,Telecommunications,2024-08-02,2024-09-18,1526,6.9,TechCorp Inc +AI00519,Data Scientist,149450,EUR,127033,EX,PT,Germany,M,Philippines,0,"Mathematics, Spark, Docker, Hadoop",Bachelor,18,Telecommunications,2024-09-10,2024-11-01,1201,7.7,Smart Analytics +AI00520,AI Software Engineer,285891,CHF,257302,EX,FT,Switzerland,S,Singapore,50,"Java, Python, MLOps, Linux, Azure",Master,16,Consulting,2024-08-22,2024-09-29,1105,5.8,Neural Networks Co +AI00521,Computer Vision Engineer,75240,USD,75240,EN,CT,South Korea,L,South Korea,100,"Mathematics, Hadoop, Docker",PhD,1,Telecommunications,2024-01-20,2024-02-03,1921,9.3,Algorithmic Solutions +AI00522,Data Scientist,124786,JPY,13726460,SE,FL,Japan,M,Japan,0,"NLP, AWS, Data Visualization, MLOps",Bachelor,7,Education,2024-03-20,2024-05-24,1442,8.3,Algorithmic Solutions +AI00523,Machine Learning Researcher,109043,CHF,98139,MI,FL,Switzerland,S,Switzerland,0,"GCP, Azure, Linux",Associate,3,Government,2025-03-08,2025-05-15,1570,5.6,Machine Intelligence Group +AI00524,Machine Learning Engineer,89035,USD,89035,SE,CT,Finland,S,Ireland,50,"SQL, Docker, NLP, Python",Associate,5,Telecommunications,2024-08-29,2024-09-20,864,6.6,Quantum Computing Inc +AI00525,Machine Learning Engineer,190529,USD,190529,EX,FL,Finland,M,Finland,50,"Linux, Spark, Tableau, Mathematics, Azure",Bachelor,19,Technology,2024-10-11,2024-11-03,1090,10,Neural Networks Co +AI00526,Machine Learning Engineer,169009,USD,169009,SE,PT,United States,M,Finland,100,"Docker, Kubernetes, Azure",Master,9,Healthcare,2024-11-21,2025-01-25,1366,9.7,TechCorp Inc +AI00527,Autonomous Systems Engineer,48714,USD,48714,EN,FT,Israel,S,Israel,100,"Git, R, Python, Mathematics",Master,1,Energy,2025-03-15,2025-04-01,530,8.6,Advanced Robotics +AI00528,ML Ops Engineer,97541,EUR,82910,SE,FT,Netherlands,S,Netherlands,0,"MLOps, Python, Kubernetes, TensorFlow",PhD,5,Manufacturing,2024-12-16,2025-01-21,1792,9.2,Predictive Systems +AI00529,Robotics Engineer,144493,EUR,122819,SE,CT,Germany,M,Germany,0,"Spark, Java, Deep Learning, R",PhD,5,Education,2025-04-18,2025-05-26,2224,7.1,TechCorp Inc +AI00530,Computer Vision Engineer,185421,USD,185421,EX,CT,Denmark,S,Nigeria,0,"PyTorch, SQL, Docker, TensorFlow",Associate,11,Media,2024-06-18,2024-08-03,1524,9.7,DeepTech Ventures +AI00531,Principal Data Scientist,287164,USD,287164,EX,FL,Sweden,L,Sweden,0,"Azure, TensorFlow, Statistics, PyTorch, R",Bachelor,18,Consulting,2024-08-31,2024-10-03,1681,8.4,AI Innovations +AI00532,AI Consultant,120968,JPY,13306480,SE,PT,Japan,S,Japan,0,"Azure, Hadoop, Scala, Computer Vision, Python",PhD,8,Healthcare,2024-10-25,2024-11-30,952,7.3,Advanced Robotics +AI00533,AI Research Scientist,135171,USD,135171,EX,CT,Sweden,S,Sweden,50,"Azure, Deep Learning, GCP, TensorFlow",Associate,14,Healthcare,2024-05-14,2024-05-31,1460,6.7,Cognitive Computing +AI00534,AI Architect,129545,CHF,116591,EN,PT,Switzerland,L,Finland,100,"Scala, Python, Computer Vision, Deep Learning",Master,1,Government,2024-03-14,2024-04-20,561,9.3,TechCorp Inc +AI00535,Data Analyst,97794,SGD,127132,MI,CT,Singapore,L,Singapore,50,"PyTorch, R, Data Visualization",PhD,2,Gaming,2024-04-04,2024-06-12,984,6.1,Autonomous Tech +AI00536,Deep Learning Engineer,145395,CAD,181744,EX,FL,Canada,M,Brazil,100,"Computer Vision, Data Visualization, Python, Spark, TensorFlow",PhD,18,Automotive,2024-07-27,2024-09-08,1959,7.5,TechCorp Inc +AI00537,Computer Vision Engineer,204217,USD,204217,EX,CT,Sweden,M,Kenya,50,"GCP, Deep Learning, R",Associate,11,Education,2024-09-28,2024-11-16,1581,7.2,Future Systems +AI00538,Autonomous Systems Engineer,98702,USD,98702,EN,FT,Denmark,L,Denmark,0,"Statistics, Kubernetes, R, SQL",Bachelor,0,Telecommunications,2025-02-17,2025-03-11,1517,9.4,Machine Intelligence Group +AI00539,Deep Learning Engineer,99895,GBP,74921,MI,CT,United Kingdom,S,New Zealand,0,"R, PyTorch, GCP, NLP, Git",Bachelor,3,Finance,2025-01-27,2025-03-20,2257,10,Machine Intelligence Group +AI00540,NLP Engineer,135571,EUR,115235,SE,FL,Netherlands,S,Netherlands,100,"Git, Spark, R, SQL, Tableau",PhD,8,Telecommunications,2024-07-13,2024-09-01,2391,8.7,Advanced Robotics +AI00541,AI Specialist,119266,USD,119266,SE,PT,Ireland,L,Ireland,50,"SQL, Python, Data Visualization",PhD,6,Government,2024-04-04,2024-05-21,1518,9.2,Digital Transformation LLC +AI00542,Research Scientist,110844,EUR,94217,SE,CT,Austria,L,Austria,50,"Scala, Statistics, MLOps, Deep Learning",Associate,8,Transportation,2025-02-07,2025-03-09,1353,9.6,DeepTech Ventures +AI00543,NLP Engineer,145736,EUR,123876,SE,FT,Netherlands,L,Ghana,50,"Linux, Python, NLP, TensorFlow",Master,9,Transportation,2025-01-16,2025-03-05,2348,6.1,Cloud AI Solutions +AI00544,AI Software Engineer,232735,EUR,197825,EX,PT,France,M,France,0,"Spark, PyTorch, TensorFlow, Deep Learning, Azure",Bachelor,11,Manufacturing,2025-04-15,2025-06-25,1449,9.7,Future Systems +AI00545,Machine Learning Researcher,56990,USD,56990,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Hadoop",PhD,1,Telecommunications,2024-02-17,2024-03-25,2274,6.2,Algorithmic Solutions +AI00546,AI Software Engineer,169605,USD,169605,EX,FT,Israel,M,Israel,0,"Data Visualization, AWS, TensorFlow, R, Linux",PhD,15,Real Estate,2024-05-17,2024-06-16,1672,6,Digital Transformation LLC +AI00547,Machine Learning Engineer,145138,USD,145138,SE,PT,Finland,L,United Kingdom,0,"PyTorch, Git, Python, AWS",PhD,8,Real Estate,2024-12-25,2025-02-16,793,5.2,AI Innovations +AI00548,Data Scientist,139121,EUR,118253,SE,FL,Germany,L,Germany,50,"Git, Kubernetes, Python, Linux",Bachelor,5,Finance,2024-10-20,2024-11-17,587,9.2,Cloud AI Solutions +AI00549,AI Product Manager,178631,USD,178631,EX,PT,Israel,S,Malaysia,100,"TensorFlow, Spark, Computer Vision, NLP",Bachelor,13,Automotive,2024-09-28,2024-11-18,1081,6.8,Machine Intelligence Group +AI00550,NLP Engineer,90723,SGD,117940,MI,PT,Singapore,S,New Zealand,0,"Linux, Scala, Git",Bachelor,4,Retail,2024-12-28,2025-01-20,2414,7.3,DataVision Ltd +AI00551,ML Ops Engineer,49069,USD,49069,MI,CT,China,M,China,100,"Python, Docker, TensorFlow",PhD,4,Automotive,2024-11-26,2025-02-06,1659,7.2,Autonomous Tech +AI00552,Deep Learning Engineer,68202,JPY,7502220,EN,FL,Japan,L,Japan,50,"TensorFlow, Java, AWS, R",Master,0,Automotive,2025-04-08,2025-05-08,1446,5.6,Cloud AI Solutions +AI00553,Data Analyst,116676,EUR,99175,MI,FL,Germany,L,Germany,0,"R, TensorFlow, Kubernetes, Scala, Statistics",Associate,3,Media,2024-03-25,2024-04-26,1460,5.8,Smart Analytics +AI00554,AI Specialist,153139,USD,153139,SE,FT,Finland,L,Finland,100,"Python, Spark, Scala, Deep Learning, Mathematics",PhD,7,Real Estate,2025-04-28,2025-05-21,609,6.8,Autonomous Tech +AI00555,Computer Vision Engineer,131402,EUR,111692,EX,FL,Netherlands,S,Netherlands,50,"MLOps, Tableau, SQL",Master,13,Media,2024-12-31,2025-03-14,1147,5.1,DeepTech Ventures +AI00556,Machine Learning Engineer,54607,EUR,46416,EN,CT,Austria,M,Austria,50,"Git, Java, Hadoop",Associate,1,Real Estate,2024-08-11,2024-10-18,1342,6.4,Advanced Robotics +AI00557,Autonomous Systems Engineer,71774,JPY,7895140,MI,CT,Japan,S,Egypt,100,"Java, Data Visualization, Deep Learning, MLOps, Spark",PhD,4,Government,2024-02-04,2024-03-17,2022,9.7,DataVision Ltd +AI00558,Data Engineer,110765,EUR,94150,SE,FL,Germany,S,China,0,"PyTorch, GCP, TensorFlow",PhD,6,Technology,2024-03-02,2024-03-21,721,5.4,AI Innovations +AI00559,Data Analyst,265991,USD,265991,EX,PT,United States,L,Vietnam,100,"AWS, Git, Docker, Azure, Computer Vision",Master,13,Finance,2024-07-24,2024-09-24,1528,7.7,DataVision Ltd +AI00560,AI Research Scientist,83839,USD,83839,MI,FL,Israel,L,Israel,50,"Scala, Spark, GCP, Azure, NLP",Bachelor,4,Real Estate,2024-03-09,2024-03-29,1589,7.2,DataVision Ltd +AI00561,Machine Learning Engineer,236251,SGD,307126,EX,PT,Singapore,L,Singapore,100,"Tableau, Mathematics, AWS, NLP, Deep Learning",Bachelor,13,Healthcare,2024-09-04,2024-10-08,678,8,Future Systems +AI00562,AI Research Scientist,241129,AUD,325524,EX,FT,Australia,M,Australia,100,"Python, Computer Vision, Git, Scala",Bachelor,16,Manufacturing,2025-02-27,2025-03-15,962,7.5,Cloud AI Solutions +AI00563,Machine Learning Researcher,159083,USD,159083,SE,PT,Israel,L,Israel,100,"Linux, Computer Vision, Data Visualization",Bachelor,7,Education,2024-11-27,2024-12-25,1205,6.5,Quantum Computing Inc +AI00564,Computer Vision Engineer,103506,USD,103506,SE,FL,South Korea,L,South Korea,0,"Tableau, Azure, AWS",Master,8,Healthcare,2024-09-05,2024-11-10,1490,9.1,Future Systems +AI00565,Principal Data Scientist,232495,USD,232495,EX,PT,Denmark,M,Denmark,0,"Deep Learning, AWS, Azure",Master,10,Real Estate,2025-02-01,2025-04-11,2289,8.2,Future Systems +AI00566,AI Research Scientist,112744,CHF,101470,EN,CT,Switzerland,L,Switzerland,50,"AWS, Kubernetes, Hadoop, Spark",Associate,1,Gaming,2025-01-20,2025-03-28,779,5.1,Cloud AI Solutions +AI00567,Autonomous Systems Engineer,129622,USD,129622,SE,PT,South Korea,L,South Korea,0,"GCP, R, Computer Vision, PyTorch, Git",PhD,5,Energy,2024-05-21,2024-07-30,1268,5.7,TechCorp Inc +AI00568,Machine Learning Engineer,100903,EUR,85768,SE,CT,Austria,S,Austria,0,"Docker, Python, AWS, Spark, TensorFlow",Bachelor,5,Education,2024-06-21,2024-08-28,683,8.2,Future Systems +AI00569,Principal Data Scientist,238019,EUR,202316,EX,FL,Austria,M,Estonia,0,"Python, Kubernetes, TensorFlow, Azure",Bachelor,11,Telecommunications,2025-02-18,2025-03-12,1577,9.7,Future Systems +AI00570,Machine Learning Engineer,41302,USD,41302,EN,PT,China,L,China,100,"GCP, Azure, NLP",Bachelor,0,Manufacturing,2024-02-09,2024-02-29,991,8,DataVision Ltd +AI00571,Deep Learning Engineer,128647,USD,128647,EX,CT,Ireland,S,Ireland,100,"SQL, Computer Vision, Python, AWS, Java",Associate,17,Real Estate,2025-01-16,2025-02-23,1579,7.8,Advanced Robotics +AI00572,AI Software Engineer,52696,EUR,44792,EN,FL,France,S,France,50,"Docker, Kubernetes, Python, GCP",PhD,0,Government,2024-06-06,2024-06-20,1102,5.6,Machine Intelligence Group +AI00573,Principal Data Scientist,229071,GBP,171803,EX,FT,United Kingdom,L,United Kingdom,0,"Java, Python, Data Visualization, MLOps",Associate,19,Education,2024-07-16,2024-08-19,629,8.8,Quantum Computing Inc +AI00574,Autonomous Systems Engineer,215282,USD,215282,EX,FL,Denmark,M,Denmark,50,"MLOps, NLP, Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-06-17,2024-08-13,528,7.8,Algorithmic Solutions +AI00575,Principal Data Scientist,199110,EUR,169244,EX,FT,France,S,Ukraine,0,"TensorFlow, Hadoop, Kubernetes, SQL",Master,10,Finance,2024-05-01,2024-06-16,908,5.5,Future Systems +AI00576,NLP Engineer,75004,USD,75004,EN,FT,United States,L,United States,50,"Computer Vision, Linux, Spark, Hadoop",Bachelor,1,Technology,2024-08-30,2024-09-27,786,8.5,Smart Analytics +AI00577,Research Scientist,149575,USD,149575,SE,PT,Israel,L,Israel,50,"Linux, PyTorch, Git, R",Master,6,Transportation,2024-03-11,2024-04-21,821,9.5,Cloud AI Solutions +AI00578,Deep Learning Engineer,138904,USD,138904,EX,CT,Israel,S,Israel,50,"Scala, Python, Deep Learning",Master,15,Telecommunications,2025-04-06,2025-05-31,1452,5.4,Autonomous Tech +AI00579,Computer Vision Engineer,133658,SGD,173755,SE,FL,Singapore,L,Singapore,50,"Kubernetes, R, Mathematics",Master,7,Telecommunications,2025-01-30,2025-04-09,1637,8.8,Cognitive Computing +AI00580,Research Scientist,148968,EUR,126623,EX,FT,Austria,S,Mexico,0,"Spark, Scala, Hadoop, Computer Vision",PhD,10,Education,2024-12-01,2025-01-28,2122,5.7,Neural Networks Co +AI00581,AI Product Manager,87661,JPY,9642710,MI,PT,Japan,S,Japan,100,"Data Visualization, Hadoop, PyTorch, NLP",Master,3,Finance,2024-04-30,2024-05-25,885,5.9,Cognitive Computing +AI00582,Data Analyst,235575,CAD,294469,EX,PT,Canada,L,Japan,0,"Scala, Tableau, Linux, PyTorch, Spark",Master,12,Technology,2024-02-13,2024-03-13,2033,6.8,Machine Intelligence Group +AI00583,Computer Vision Engineer,195175,USD,195175,EX,PT,Israel,S,Israel,100,"AWS, Spark, PyTorch, Kubernetes, Tableau",Master,14,Real Estate,2025-02-19,2025-03-28,1435,7.1,AI Innovations +AI00584,Data Engineer,143318,CAD,179148,SE,PT,Canada,M,Canada,100,"GCP, PyTorch, Tableau, Git",Master,8,Energy,2024-07-18,2024-08-01,2002,9.3,AI Innovations +AI00585,Machine Learning Engineer,102959,CHF,92663,EN,FL,Switzerland,L,Switzerland,100,"Scala, Hadoop, Docker",Master,1,Finance,2024-07-15,2024-08-26,1849,7.7,Advanced Robotics +AI00586,ML Ops Engineer,90379,AUD,122012,MI,FL,Australia,S,Italy,100,"Data Visualization, Docker, Python, TensorFlow",Master,4,Finance,2025-04-20,2025-07-02,1029,7.5,Predictive Systems +AI00587,Principal Data Scientist,71203,CAD,89004,EN,FT,Canada,M,Canada,100,"TensorFlow, Git, SQL, Kubernetes, Java",Associate,0,Energy,2025-03-24,2025-04-27,1537,6.2,Advanced Robotics +AI00588,AI Consultant,177188,EUR,150610,EX,FL,Netherlands,S,Netherlands,100,"Scala, AWS, Git",Bachelor,13,Manufacturing,2025-01-06,2025-01-23,1619,8.6,Machine Intelligence Group +AI00589,Machine Learning Engineer,95416,USD,95416,MI,CT,Sweden,M,Brazil,100,"Java, Docker, Computer Vision, Linux, Mathematics",Master,2,Technology,2024-05-24,2024-06-09,938,5.6,Cognitive Computing +AI00590,Head of AI,89044,USD,89044,EN,CT,Norway,L,Czech Republic,50,"SQL, PyTorch, Tableau",PhD,1,Government,2024-04-11,2024-06-19,1762,7.2,Quantum Computing Inc +AI00591,NLP Engineer,78263,EUR,66524,EN,PT,Netherlands,M,Ireland,100,"Python, TensorFlow, GCP",PhD,0,Energy,2024-07-10,2024-09-21,1563,6.9,Predictive Systems +AI00592,ML Ops Engineer,231654,JPY,25481940,EX,PT,Japan,M,Japan,0,"Python, Mathematics, GCP, Computer Vision, AWS",PhD,11,Finance,2024-09-08,2024-09-28,1880,10,Digital Transformation LLC +AI00593,NLP Engineer,149046,USD,149046,SE,PT,Sweden,L,Sweden,0,"Python, Kubernetes, TensorFlow, Computer Vision, PyTorch",Associate,9,Technology,2024-08-19,2024-09-30,2359,5.5,Predictive Systems +AI00594,Machine Learning Researcher,84232,CAD,105290,MI,CT,Canada,S,Canada,100,"GCP, Scala, Azure, Statistics",Master,4,Gaming,2024-12-23,2025-01-29,537,7,Machine Intelligence Group +AI00595,ML Ops Engineer,94348,CAD,117935,SE,FT,Canada,S,Canada,50,"GCP, SQL, Spark, Linux",Master,7,Energy,2024-03-02,2024-04-12,527,7.4,DataVision Ltd +AI00596,Data Engineer,128839,USD,128839,SE,FL,Finland,M,Finland,50,"Mathematics, Statistics, Deep Learning, Java, Kubernetes",PhD,6,Retail,2024-11-05,2025-01-13,2263,8.5,Algorithmic Solutions +AI00597,AI Architect,166829,EUR,141805,SE,FL,Netherlands,L,Netherlands,100,"AWS, Kubernetes, Deep Learning",Associate,5,Consulting,2024-11-02,2024-11-30,2187,9.3,Cloud AI Solutions +AI00598,AI Software Engineer,67959,GBP,50969,EN,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, NLP, TensorFlow, Spark",PhD,1,Real Estate,2024-01-02,2024-01-20,599,7.4,Machine Intelligence Group +AI00599,AI Architect,80303,AUD,108409,MI,FT,Australia,M,Australia,50,"Python, GCP, Git, Java, Mathematics",Bachelor,4,Healthcare,2024-08-09,2024-10-07,812,9.3,Smart Analytics +AI00600,Data Engineer,104350,EUR,88698,MI,FL,Netherlands,S,Netherlands,50,"MLOps, Mathematics, Git",Bachelor,2,Transportation,2024-02-04,2024-04-04,2112,7.4,Algorithmic Solutions +AI00601,AI Consultant,146664,EUR,124664,SE,PT,Netherlands,L,Netherlands,50,"Python, SQL, Computer Vision, Java",PhD,8,Automotive,2024-04-04,2024-05-29,589,8.1,Machine Intelligence Group +AI00602,AI Software Engineer,119423,EUR,101510,SE,PT,Germany,M,Germany,50,"GCP, TensorFlow, Computer Vision, AWS",Master,9,Gaming,2024-11-19,2024-12-31,1840,9,Algorithmic Solutions +AI00603,AI Consultant,31988,USD,31988,EN,PT,China,M,China,50,"Docker, Mathematics, Scala",PhD,0,Automotive,2024-01-14,2024-02-20,2450,6.1,Future Systems +AI00604,AI Architect,94563,GBP,70922,EN,FT,United Kingdom,L,United Kingdom,50,"Git, TensorFlow, Deep Learning, Azure, Computer Vision",Bachelor,1,Finance,2024-01-05,2024-03-01,1461,9.7,DeepTech Ventures +AI00605,Autonomous Systems Engineer,85269,USD,85269,EN,FL,Ireland,L,Ireland,50,"MLOps, Deep Learning, PyTorch",Bachelor,0,Technology,2024-02-11,2024-03-30,953,7.9,DeepTech Ventures +AI00606,AI Architect,87092,USD,87092,EN,PT,Israel,L,Israel,50,"Kubernetes, Statistics, Scala",PhD,0,Healthcare,2024-02-25,2024-04-14,1931,9.9,Predictive Systems +AI00607,Machine Learning Researcher,75721,USD,75721,EN,FT,Finland,L,China,100,"Docker, Git, Python, Mathematics",PhD,1,Manufacturing,2024-07-05,2024-09-12,2487,5.1,DeepTech Ventures +AI00608,Research Scientist,158003,USD,158003,SE,FT,Sweden,L,Sweden,0,"Python, SQL, Tableau, Data Visualization",Master,7,Government,2025-04-20,2025-06-22,634,5.9,Future Systems +AI00609,Autonomous Systems Engineer,189198,JPY,20811780,EX,FL,Japan,M,Japan,0,"Computer Vision, Spark, Data Visualization, Java",Associate,18,Finance,2024-03-27,2024-06-01,2153,6.9,AI Innovations +AI00610,Research Scientist,57287,EUR,48694,EN,FL,France,M,France,100,"AWS, PyTorch, Computer Vision, GCP, Scala",Associate,1,Technology,2024-10-15,2024-12-08,1413,7.1,Machine Intelligence Group +AI00611,AI Specialist,116891,GBP,87668,MI,FT,United Kingdom,L,Japan,0,"TensorFlow, PyTorch, GCP, NLP",Bachelor,2,Education,2024-12-31,2025-03-11,865,8.1,Autonomous Tech +AI00612,Autonomous Systems Engineer,86678,USD,86678,MI,FT,Sweden,S,Hungary,50,"AWS, Mathematics, GCP, Git",Associate,4,Telecommunications,2025-04-08,2025-05-19,1812,6.6,Autonomous Tech +AI00613,Research Scientist,237261,EUR,201672,EX,PT,Germany,L,Germany,50,"Mathematics, Scala, PyTorch",Bachelor,16,Government,2024-06-04,2024-07-26,686,7.1,Neural Networks Co +AI00614,Data Engineer,340350,CHF,306315,EX,FT,Switzerland,L,France,0,"Python, Spark, Deep Learning, Azure, TensorFlow",PhD,17,Gaming,2024-07-14,2024-08-13,2373,7.2,Algorithmic Solutions +AI00615,Data Scientist,143376,USD,143376,SE,FL,Norway,S,Norway,50,"PyTorch, Mathematics, Deep Learning, Linux, AWS",Associate,8,Transportation,2025-04-06,2025-05-25,1159,7.7,Advanced Robotics +AI00616,Robotics Engineer,212213,CHF,190992,SE,FL,Switzerland,M,Switzerland,0,"Azure, SQL, Kubernetes, NLP",Associate,9,Consulting,2024-03-19,2024-04-30,1213,6.8,Autonomous Tech +AI00617,Principal Data Scientist,147392,SGD,191610,SE,CT,Singapore,L,Finland,100,"NLP, MLOps, SQL, Linux",Associate,5,Automotive,2025-03-03,2025-03-23,1701,5.8,AI Innovations +AI00618,Machine Learning Engineer,93630,USD,93630,SE,PT,Finland,S,Finland,50,"Kubernetes, SQL, PyTorch",Master,6,Energy,2025-02-27,2025-03-24,1022,6.5,Neural Networks Co +AI00619,AI Software Engineer,99867,CHF,89880,EN,FT,Switzerland,M,Switzerland,0,"Python, Git, TensorFlow",Master,0,Healthcare,2024-06-27,2024-08-09,1864,6.4,Advanced Robotics +AI00620,NLP Engineer,167900,CHF,151110,MI,FL,Switzerland,L,India,100,"Python, AWS, TensorFlow, Data Visualization, Computer Vision",Bachelor,3,Automotive,2025-03-25,2025-05-22,2095,5,DeepTech Ventures +AI00621,Computer Vision Engineer,113585,USD,113585,MI,FL,Norway,S,Egypt,50,"Computer Vision, Python, Statistics, TensorFlow",Associate,4,Government,2024-12-12,2025-01-27,1077,8.5,Digital Transformation LLC +AI00622,AI Software Engineer,88040,GBP,66030,MI,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, AWS, PyTorch, Deep Learning, Data Visualization",PhD,2,Finance,2024-08-03,2024-10-04,1715,8.2,Quantum Computing Inc +AI00623,Autonomous Systems Engineer,234891,USD,234891,EX,CT,South Korea,L,South Korea,0,"Spark, Scala, Statistics, Computer Vision",Master,19,Retail,2024-08-26,2024-09-22,2055,7,Future Systems +AI00624,Machine Learning Researcher,55689,EUR,47336,EN,PT,Austria,L,Austria,50,"Python, Mathematics, Deep Learning, Linux, GCP",Master,1,Government,2024-11-28,2025-01-27,1296,7.5,Predictive Systems +AI00625,Deep Learning Engineer,192002,EUR,163202,EX,FT,France,S,Japan,50,"MLOps, Java, Linux, Hadoop, PyTorch",PhD,15,Education,2024-08-21,2024-09-19,1600,8.8,DataVision Ltd +AI00626,Research Scientist,88478,USD,88478,EX,CT,India,L,India,100,"R, AWS, Mathematics",Bachelor,12,Education,2024-02-05,2024-03-18,703,6.5,Neural Networks Co +AI00627,ML Ops Engineer,233768,EUR,198703,EX,FT,Austria,M,Austria,50,"Python, Azure, Scala, AWS",Master,13,Manufacturing,2024-10-06,2024-11-12,2390,5.4,Autonomous Tech +AI00628,Autonomous Systems Engineer,394510,CHF,355059,EX,PT,Switzerland,L,Switzerland,0,"MLOps, Java, Statistics, Deep Learning, SQL",Master,18,Finance,2024-02-15,2024-04-28,1628,9.6,Smart Analytics +AI00629,AI Research Scientist,96275,CHF,86648,EN,FT,Switzerland,S,Switzerland,0,"Python, NLP, GCP, Docker, Java",PhD,0,Gaming,2024-01-09,2024-02-16,2313,7.4,Neural Networks Co +AI00630,Data Scientist,67084,USD,67084,SE,PT,China,M,Japan,100,"SQL, MLOps, Java",Associate,5,Government,2024-06-21,2024-07-18,852,8.7,AI Innovations +AI00631,Head of AI,87326,USD,87326,MI,PT,South Korea,M,South Africa,100,"PyTorch, NLP, MLOps",PhD,3,Retail,2024-06-17,2024-07-21,1777,7,Future Systems +AI00632,Research Scientist,88829,USD,88829,MI,PT,Finland,M,Belgium,50,"SQL, Linux, Deep Learning, Scala",Master,3,Consulting,2024-04-23,2024-07-05,1733,7.3,Cognitive Computing +AI00633,Autonomous Systems Engineer,110532,USD,110532,MI,FL,Denmark,M,Denmark,50,"Computer Vision, Mathematics, NLP",PhD,3,Manufacturing,2024-09-27,2024-11-05,2039,8.5,Future Systems +AI00634,AI Product Manager,60357,USD,60357,EN,CT,South Korea,L,Belgium,0,"Azure, TensorFlow, NLP, Python, PyTorch",Associate,0,Media,2024-03-06,2024-04-05,562,9.6,DataVision Ltd +AI00635,AI Research Scientist,315064,CHF,283558,EX,FL,Switzerland,S,Switzerland,0,"NLP, Git, Scala, Hadoop, Docker",Bachelor,18,Real Estate,2024-04-15,2024-05-18,1191,9.6,Cognitive Computing +AI00636,AI Software Engineer,70097,USD,70097,EN,PT,Denmark,S,Denmark,100,"Git, Python, TensorFlow",PhD,0,Finance,2025-04-13,2025-06-10,2054,5.4,Quantum Computing Inc +AI00637,Principal Data Scientist,117235,USD,117235,SE,FL,Ireland,M,Ireland,50,"Scala, Git, Azure",PhD,6,Government,2025-01-24,2025-03-30,1962,7.4,Autonomous Tech +AI00638,Principal Data Scientist,65851,USD,65851,EN,FT,Sweden,S,Turkey,100,"Hadoop, Python, Statistics, Scala",Associate,0,Energy,2025-01-03,2025-03-06,692,8.3,Quantum Computing Inc +AI00639,Computer Vision Engineer,84191,JPY,9261010,MI,FL,Japan,M,Japan,100,"R, Docker, Git, GCP, Statistics",Master,2,Consulting,2024-07-20,2024-09-06,1495,8.2,TechCorp Inc +AI00640,NLP Engineer,134590,USD,134590,MI,FT,Norway,M,Norway,0,"Python, SQL, Docker, TensorFlow, Tableau",PhD,2,Manufacturing,2024-04-12,2024-06-07,1564,8.4,AI Innovations +AI00641,AI Product Manager,139686,AUD,188576,SE,FL,Australia,M,Australia,100,"NLP, SQL, GCP, Tableau",Master,6,Education,2024-03-25,2024-04-28,2364,8.3,Smart Analytics +AI00642,AI Software Engineer,115226,USD,115226,SE,PT,South Korea,L,South Korea,0,"Python, Kubernetes, TensorFlow",Bachelor,5,Telecommunications,2025-04-19,2025-05-03,1761,5.9,Quantum Computing Inc +AI00643,Deep Learning Engineer,262115,EUR,222798,EX,PT,Netherlands,L,Netherlands,0,"Java, GCP, Computer Vision",Associate,12,Consulting,2024-05-08,2024-07-07,736,9.2,Algorithmic Solutions +AI00644,Data Scientist,111532,EUR,94802,SE,FL,Austria,S,Austria,50,"NLP, Java, Computer Vision, R, Deep Learning",Master,6,Gaming,2024-07-03,2024-07-17,517,5.4,Algorithmic Solutions +AI00645,Research Scientist,267795,SGD,348134,EX,CT,Singapore,M,Egypt,50,"Java, Azure, Kubernetes, PyTorch, Docker",Associate,11,Transportation,2024-10-07,2024-11-10,1026,5.4,DeepTech Ventures +AI00646,AI Software Engineer,63052,EUR,53594,EN,FT,France,M,United Kingdom,100,"Scala, Python, MLOps",Master,0,Retail,2024-02-05,2024-03-22,1183,6.6,Cognitive Computing +AI00647,AI Architect,54424,USD,54424,EN,FL,United States,S,Austria,0,"R, Kubernetes, Mathematics, Hadoop, SQL",PhD,1,Energy,2024-01-02,2024-01-21,1220,9.2,DeepTech Ventures +AI00648,AI Software Engineer,67908,USD,67908,SE,FT,China,M,Colombia,100,"Git, Spark, AWS, Scala",Bachelor,6,Gaming,2024-01-21,2024-02-28,2163,9.4,Smart Analytics +AI00649,ML Ops Engineer,115395,GBP,86546,SE,FL,United Kingdom,S,United Kingdom,100,"R, Kubernetes, Data Visualization",Bachelor,6,Government,2024-10-28,2024-12-30,1312,7.8,Predictive Systems +AI00650,Data Scientist,122516,AUD,165397,SE,FT,Australia,S,South Africa,100,"Deep Learning, Python, Git, Kubernetes, GCP",Master,9,Transportation,2024-07-23,2024-10-03,2397,8.7,AI Innovations +AI00651,Machine Learning Researcher,118846,EUR,101019,SE,FL,France,S,France,50,"SQL, AWS, NLP, PyTorch, Computer Vision",PhD,5,Manufacturing,2024-10-06,2024-11-11,1725,9.3,Machine Intelligence Group +AI00652,Machine Learning Engineer,98835,USD,98835,MI,FT,Sweden,M,Sweden,0,"AWS, Deep Learning, TensorFlow",Bachelor,2,Consulting,2024-02-06,2024-03-15,705,9.3,Neural Networks Co +AI00653,Data Engineer,295640,USD,295640,EX,FT,United States,M,United States,0,"AWS, GCP, Git, SQL",Master,11,Media,2024-01-08,2024-02-14,1782,8.3,Machine Intelligence Group +AI00654,Machine Learning Engineer,136359,SGD,177267,SE,CT,Singapore,M,Singapore,50,"R, Deep Learning, MLOps",Bachelor,9,Telecommunications,2024-08-30,2024-09-28,769,9.6,TechCorp Inc +AI00655,Principal Data Scientist,187425,USD,187425,EX,CT,Sweden,L,Sweden,0,"SQL, TensorFlow, Docker, Python, GCP",PhD,13,Consulting,2025-02-05,2025-02-25,1415,9.3,Cognitive Computing +AI00656,Machine Learning Engineer,91932,USD,91932,MI,FL,Sweden,M,Sweden,50,"MLOps, Kubernetes, Tableau, Scala",PhD,2,Manufacturing,2024-09-06,2024-10-18,1272,6.8,TechCorp Inc +AI00657,AI Software Engineer,71409,USD,71409,EN,FT,United States,L,United States,0,"Git, Linux, Data Visualization, Deep Learning",PhD,0,Telecommunications,2024-01-23,2024-03-17,1482,9.7,Neural Networks Co +AI00658,Machine Learning Engineer,48739,USD,48739,EN,FL,Ireland,S,Latvia,50,"Python, TensorFlow, Linux, PyTorch",PhD,0,Retail,2024-03-28,2024-05-11,1628,5.1,Predictive Systems +AI00659,AI Architect,61632,EUR,52387,EN,CT,Germany,S,Colombia,50,"Spark, Kubernetes, Data Visualization, Hadoop",Bachelor,1,Real Estate,2025-02-05,2025-02-19,910,6.1,Cloud AI Solutions +AI00660,Machine Learning Researcher,98216,JPY,10803760,MI,CT,Japan,S,New Zealand,0,"Spark, Deep Learning, NLP, PyTorch, Data Visualization",PhD,4,Energy,2024-04-16,2024-06-22,1612,6.4,DataVision Ltd +AI00661,AI Product Manager,104633,EUR,88938,SE,FL,Germany,S,Germany,100,"PyTorch, Spark, Tableau, Data Visualization",Master,6,Education,2024-08-06,2024-10-17,1922,7.3,Digital Transformation LLC +AI00662,AI Software Engineer,41990,USD,41990,MI,CT,China,L,India,100,"Scala, Azure, Deep Learning, Spark, Git",Associate,2,Government,2024-07-30,2024-09-24,1928,9.8,Autonomous Tech +AI00663,Data Analyst,238728,SGD,310346,EX,CT,Singapore,S,Singapore,0,"Python, MLOps, TensorFlow, NLP, Tableau",Master,12,Gaming,2024-08-25,2024-10-04,2000,7.7,Algorithmic Solutions +AI00664,AI Consultant,329444,CHF,296500,EX,FL,Switzerland,M,Switzerland,100,"Hadoop, Scala, Linux, Python",Bachelor,14,Real Estate,2024-12-27,2025-02-10,1268,8,Smart Analytics +AI00665,Research Scientist,70081,USD,70081,EN,FT,Israel,L,Israel,100,"Hadoop, R, Tableau, Python",Bachelor,1,Government,2024-04-20,2024-06-20,1280,7.4,AI Innovations +AI00666,Head of AI,288084,USD,288084,EX,FT,Denmark,L,Denmark,0,"Docker, Hadoop, Linux",Associate,15,Education,2024-10-06,2024-12-15,1022,7.1,Autonomous Tech +AI00667,AI Consultant,65282,USD,65282,MI,FL,Israel,S,Israel,100,"Scala, Tableau, NLP",Associate,2,Consulting,2024-03-22,2024-05-19,2126,5.5,TechCorp Inc +AI00668,Machine Learning Engineer,126052,SGD,163868,SE,PT,Singapore,S,Singapore,50,"Java, Scala, MLOps, R, Linux",PhD,6,Consulting,2024-07-23,2024-09-18,1915,7.4,DataVision Ltd +AI00669,Data Scientist,247685,USD,247685,EX,PT,Ireland,M,South Africa,100,"Data Visualization, SQL, Linux, Scala",PhD,12,Automotive,2025-03-28,2025-05-31,1375,7.5,Cognitive Computing +AI00670,AI Software Engineer,80022,GBP,60017,MI,FL,United Kingdom,M,United Kingdom,0,"Linux, PyTorch, Python, Statistics, Deep Learning",Master,3,Energy,2024-03-11,2024-04-21,603,5.5,Smart Analytics +AI00671,Data Analyst,96062,SGD,124881,EN,CT,Singapore,L,Singapore,0,"SQL, Scala, Data Visualization",Associate,1,Finance,2024-09-11,2024-11-08,2460,8.6,Algorithmic Solutions +AI00672,Principal Data Scientist,174460,USD,174460,SE,FL,Denmark,L,Denmark,100,"R, Mathematics, Python, Data Visualization, Docker",Master,9,Media,2025-02-27,2025-04-16,960,8.7,Smart Analytics +AI00673,AI Software Engineer,183335,EUR,155835,EX,PT,Austria,M,Austria,100,"NLP, PyTorch, Hadoop, Tableau, SQL",PhD,12,Education,2024-04-24,2024-05-30,897,8.4,Neural Networks Co +AI00674,Data Engineer,223437,USD,223437,EX,FL,Sweden,M,Sweden,100,"Linux, R, SQL, AWS",Bachelor,18,Gaming,2025-02-14,2025-03-24,2274,6.2,Neural Networks Co +AI00675,AI Specialist,177360,USD,177360,SE,PT,Denmark,L,Turkey,50,"Azure, TensorFlow, SQL",Bachelor,6,Consulting,2024-07-23,2024-09-18,1564,7.1,AI Innovations +AI00676,AI Consultant,206532,JPY,22718520,EX,FT,Japan,M,Canada,100,"SQL, Deep Learning, MLOps, Linux",Bachelor,10,Technology,2024-02-22,2024-03-09,1130,6.4,Cloud AI Solutions +AI00677,Robotics Engineer,112216,EUR,95384,MI,CT,Austria,L,Austria,100,"Deep Learning, TensorFlow, Kubernetes",PhD,4,Energy,2024-12-10,2024-12-25,715,6.3,Algorithmic Solutions +AI00678,AI Software Engineer,55817,CAD,69771,EN,PT,Canada,S,Canada,100,"Python, Azure, Deep Learning, SQL",Associate,0,Technology,2025-01-24,2025-03-23,1550,6.1,Autonomous Tech +AI00679,AI Specialist,324267,USD,324267,EX,CT,Norway,L,Norway,50,"Scala, Java, Mathematics",PhD,11,Finance,2024-04-05,2024-06-05,1346,6.5,Predictive Systems +AI00680,NLP Engineer,76065,JPY,8367150,MI,FT,Japan,S,Japan,50,"R, SQL, Kubernetes, Java",PhD,4,Education,2025-02-21,2025-04-10,1473,5.6,Predictive Systems +AI00681,Machine Learning Researcher,146849,CHF,132164,SE,PT,Switzerland,M,Spain,0,"Azure, SQL, MLOps",PhD,8,Education,2024-07-17,2024-08-17,1337,7.4,Predictive Systems +AI00682,Head of AI,81041,SGD,105353,EN,FL,Singapore,M,India,50,"Kubernetes, SQL, PyTorch",PhD,0,Healthcare,2025-02-12,2025-04-21,722,5.5,Advanced Robotics +AI00683,Computer Vision Engineer,106945,USD,106945,EN,PT,United States,L,Malaysia,100,"Tableau, Java, AWS, Data Visualization, Scala",PhD,0,Government,2024-02-11,2024-04-01,615,9.4,Quantum Computing Inc +AI00684,Robotics Engineer,329543,USD,329543,EX,PT,Denmark,L,Singapore,100,"Data Visualization, Scala, Statistics, NLP, Hadoop",Associate,18,Technology,2024-08-01,2024-09-21,553,8.4,Neural Networks Co +AI00685,Machine Learning Engineer,92316,USD,92316,SE,CT,Israel,S,United States,100,"Kubernetes, Deep Learning, Scala, PyTorch, R",Associate,6,Transportation,2024-12-27,2025-03-08,834,7.2,Cognitive Computing +AI00686,AI Research Scientist,209495,JPY,23044450,EX,FL,Japan,S,Japan,100,"TensorFlow, AWS, Kubernetes",PhD,19,Government,2025-03-15,2025-05-18,1511,6.9,AI Innovations +AI00687,Data Analyst,201545,USD,201545,EX,CT,Ireland,L,Australia,0,"Scala, Mathematics, Spark, Kubernetes",PhD,17,Telecommunications,2024-09-16,2024-11-23,1552,6.7,Cloud AI Solutions +AI00688,Principal Data Scientist,122321,CAD,152901,SE,PT,Canada,S,Canada,0,"Hadoop, Python, Deep Learning",Master,6,Consulting,2024-09-28,2024-12-05,2048,6.1,Cloud AI Solutions +AI00689,Machine Learning Researcher,120647,CHF,108582,EN,CT,Switzerland,L,Switzerland,50,"Tableau, MLOps, Data Visualization",Bachelor,0,Manufacturing,2024-07-26,2024-10-04,1544,9.1,Algorithmic Solutions +AI00690,Data Analyst,56584,USD,56584,EN,FL,South Korea,S,Sweden,100,"Tableau, Mathematics, Kubernetes, Git",Bachelor,0,Consulting,2024-02-10,2024-04-17,1670,5.3,AI Innovations +AI00691,AI Architect,143314,CHF,128983,SE,CT,Switzerland,S,Australia,50,"Hadoop, Java, GCP",Bachelor,8,Finance,2024-09-02,2024-10-31,2319,8,Autonomous Tech +AI00692,NLP Engineer,130879,JPY,14396690,SE,PT,Japan,M,Japan,0,"Python, Azure, MLOps",Master,6,Real Estate,2024-04-12,2024-06-19,2280,5.4,Cloud AI Solutions +AI00693,Machine Learning Engineer,79223,AUD,106951,MI,FL,Australia,S,Egypt,100,"Java, Kubernetes, R, Azure",Associate,4,Government,2024-11-15,2024-12-29,1232,5.5,Quantum Computing Inc +AI00694,Deep Learning Engineer,145545,USD,145545,SE,FL,Norway,M,Norway,100,"Docker, Tableau, Hadoop, Computer Vision",Bachelor,5,Retail,2025-01-21,2025-03-14,1802,8.8,TechCorp Inc +AI00695,Computer Vision Engineer,100393,JPY,11043230,MI,PT,Japan,L,Japan,50,"Java, Spark, AWS",Master,3,Education,2024-09-07,2024-10-21,947,9.2,Neural Networks Co +AI00696,AI Software Engineer,197280,USD,197280,EX,FT,Ireland,S,Ireland,100,"TensorFlow, Kubernetes, Linux, NLP",Master,16,Telecommunications,2024-08-05,2024-09-08,777,6,Autonomous Tech +AI00697,Computer Vision Engineer,88090,USD,88090,MI,FT,South Korea,M,South Korea,100,"Python, Computer Vision, Scala, Spark, TensorFlow",Associate,3,Retail,2025-01-02,2025-02-08,1674,10,AI Innovations +AI00698,Computer Vision Engineer,69911,USD,69911,MI,FT,South Korea,S,South Korea,100,"Kubernetes, TensorFlow, GCP",Master,3,Automotive,2024-09-12,2024-11-16,582,7.3,DataVision Ltd +AI00699,ML Ops Engineer,218971,CHF,197074,EX,FL,Switzerland,M,Switzerland,0,"Mathematics, Python, Tableau, AWS",Associate,18,Telecommunications,2025-03-22,2025-04-06,1989,6.5,Digital Transformation LLC +AI00700,AI Product Manager,79860,EUR,67881,EN,FT,Austria,L,Austria,50,"Mathematics, NLP, Tableau, Java",Bachelor,0,Government,2025-04-26,2025-05-23,2214,7.6,TechCorp Inc +AI00701,AI Architect,118343,CAD,147929,SE,CT,Canada,M,Indonesia,100,"GCP, PyTorch, AWS, Tableau, Kubernetes",Master,9,Automotive,2024-11-03,2024-11-29,2230,5.7,Advanced Robotics +AI00702,Research Scientist,142832,USD,142832,SE,FL,Finland,L,Finland,100,"Spark, Deep Learning, Python, AWS",Bachelor,6,Consulting,2024-12-14,2025-02-24,2222,6,Neural Networks Co +AI00703,Computer Vision Engineer,103304,EUR,87808,SE,CT,France,S,South Korea,0,"Deep Learning, SQL, Mathematics, Kubernetes, Tableau",Master,9,Media,2024-08-06,2024-09-15,1382,9.6,Neural Networks Co +AI00704,NLP Engineer,51555,USD,51555,SE,FT,India,M,India,50,"Java, R, NLP",PhD,6,Technology,2024-12-15,2025-01-17,1452,8,AI Innovations +AI00705,Robotics Engineer,33564,USD,33564,MI,FT,India,L,Israel,0,"Scala, Tableau, Kubernetes, Deep Learning",Associate,4,Media,2024-03-30,2024-05-06,562,5.8,DataVision Ltd +AI00706,AI Specialist,46733,USD,46733,MI,FT,China,S,Ireland,50,"Scala, PyTorch, Data Visualization, SQL, Java",Associate,3,Media,2024-12-20,2025-02-09,777,9.4,Digital Transformation LLC +AI00707,AI Architect,163489,EUR,138966,SE,FL,Germany,L,Germany,50,"Spark, Python, TensorFlow, NLP",Bachelor,8,Technology,2024-11-16,2025-01-24,1573,9.4,Machine Intelligence Group +AI00708,AI Consultant,127499,SGD,165749,SE,CT,Singapore,M,Singapore,100,"Docker, R, GCP, Scala, Hadoop",Master,9,Government,2024-11-29,2025-01-22,830,9.8,AI Innovations +AI00709,Head of AI,169543,EUR,144112,SE,FT,Germany,L,Germany,50,"Statistics, Git, Linux, Hadoop, Kubernetes",PhD,8,Energy,2024-09-24,2024-10-28,1703,5.1,DeepTech Ventures +AI00710,AI Specialist,252321,EUR,214473,EX,FT,France,L,France,100,"Statistics, AWS, Azure",Bachelor,14,Education,2024-04-05,2024-05-07,966,9.9,Smart Analytics +AI00711,Robotics Engineer,83888,GBP,62916,MI,FT,United Kingdom,M,United Kingdom,100,"MLOps, Deep Learning, Docker, Spark",Master,2,Technology,2025-03-04,2025-04-02,1553,6.1,Quantum Computing Inc +AI00712,NLP Engineer,117983,AUD,159277,SE,FT,Australia,M,Finland,50,"Computer Vision, Data Visualization, Java",Associate,5,Media,2024-03-08,2024-04-07,2450,7.8,DeepTech Ventures +AI00713,Research Scientist,153305,SGD,199297,EX,FL,Singapore,M,Singapore,100,"R, Docker, Scala, Mathematics, PyTorch",PhD,19,Education,2025-03-03,2025-03-22,824,7.7,Smart Analytics +AI00714,Deep Learning Engineer,112643,JPY,12390730,SE,FT,Japan,S,Japan,50,"PyTorch, Python, TensorFlow, Mathematics, AWS",Associate,9,Gaming,2024-12-31,2025-03-13,1976,6.1,Predictive Systems +AI00715,AI Product Manager,64605,USD,64605,EN,FT,Norway,S,Norway,50,"Deep Learning, MLOps, Python",Associate,1,Gaming,2025-02-26,2025-03-14,875,8.6,Cloud AI Solutions +AI00716,Autonomous Systems Engineer,62679,EUR,53277,MI,CT,France,S,Ireland,50,"R, SQL, Kubernetes, Azure, TensorFlow",PhD,3,Consulting,2024-08-13,2024-09-08,819,7,Cognitive Computing +AI00717,AI Consultant,161602,EUR,137362,EX,PT,France,L,France,100,"Hadoop, Kubernetes, Git, Docker",Associate,11,Automotive,2024-02-20,2024-03-20,2361,9,Advanced Robotics +AI00718,Computer Vision Engineer,124703,GBP,93527,SE,PT,United Kingdom,M,Latvia,0,"AWS, PyTorch, Tableau",Bachelor,6,Healthcare,2024-09-30,2024-11-13,1138,8.4,Cognitive Computing +AI00719,Head of AI,200853,USD,200853,EX,FT,Israel,M,Israel,50,"R, Statistics, SQL, Deep Learning",Master,13,Technology,2024-11-11,2025-01-17,1274,7.5,Algorithmic Solutions +AI00720,ML Ops Engineer,34021,USD,34021,MI,PT,India,S,India,50,"Git, Python, GCP, SQL, Java",PhD,2,Energy,2024-02-15,2024-03-25,2324,5.3,Cognitive Computing +AI00721,Robotics Engineer,90355,EUR,76802,MI,CT,Germany,M,Germany,50,"Deep Learning, Data Visualization, NLP, R",Bachelor,2,Energy,2024-11-17,2024-12-20,2458,9.4,Future Systems +AI00722,Machine Learning Engineer,63360,USD,63360,EN,FL,Ireland,M,Ireland,100,"Computer Vision, MLOps, SQL, Docker, PyTorch",Master,1,Telecommunications,2024-10-22,2024-11-19,1383,5.1,DataVision Ltd +AI00723,Data Analyst,185352,USD,185352,EX,PT,Ireland,S,New Zealand,0,"Scala, MLOps, Data Visualization",Bachelor,10,Government,2024-09-27,2024-11-06,1306,6.1,Advanced Robotics +AI00724,AI Software Engineer,85462,SGD,111101,EN,FT,Singapore,L,Switzerland,50,"NLP, Kubernetes, Git",Master,1,Transportation,2024-05-11,2024-06-27,591,9.9,Predictive Systems +AI00725,AI Product Manager,119183,EUR,101306,SE,PT,Austria,L,Austria,100,"Git, MLOps, Spark, Linux, Hadoop",Associate,9,Telecommunications,2025-01-16,2025-02-23,2480,9.5,Digital Transformation LLC +AI00726,Machine Learning Engineer,116244,EUR,98807,SE,CT,Austria,M,Austria,50,"R, Kubernetes, Spark",Bachelor,6,Technology,2024-02-02,2024-03-04,1029,6.1,Algorithmic Solutions +AI00727,Machine Learning Researcher,287291,USD,287291,EX,FT,Norway,S,Norway,50,"Scala, R, Tableau",Master,19,Manufacturing,2024-08-27,2024-10-31,1944,9.3,Quantum Computing Inc +AI00728,Data Engineer,160191,EUR,136162,EX,FL,Germany,S,Germany,50,"Linux, Git, Statistics, Deep Learning, Java",PhD,17,Automotive,2024-11-28,2025-01-24,688,9.9,TechCorp Inc +AI00729,AI Architect,207916,USD,207916,EX,FL,South Korea,M,South Korea,100,"Kubernetes, Mathematics, Hadoop, Deep Learning",Master,15,Retail,2024-10-17,2024-11-25,1085,8.7,Algorithmic Solutions +AI00730,Deep Learning Engineer,215737,USD,215737,EX,CT,Israel,S,Israel,50,"Linux, Scala, Git, SQL",PhD,15,Manufacturing,2024-06-29,2024-08-27,1269,5.2,Neural Networks Co +AI00731,Principal Data Scientist,89008,USD,89008,EN,CT,Denmark,L,New Zealand,0,"PyTorch, AWS, MLOps",Master,0,Telecommunications,2024-01-04,2024-02-12,1540,8.3,Future Systems +AI00732,Principal Data Scientist,122155,GBP,91616,SE,PT,United Kingdom,S,United Kingdom,100,"PyTorch, Hadoop, Computer Vision",Bachelor,9,Media,2024-02-16,2024-03-27,1762,5.3,TechCorp Inc +AI00733,Data Scientist,40715,USD,40715,EN,FL,China,L,South Korea,0,"Python, NLP, Hadoop, Docker, Tableau",PhD,1,Technology,2024-07-06,2024-08-10,1018,7.9,Cloud AI Solutions +AI00734,Robotics Engineer,188499,CHF,169649,SE,PT,Switzerland,S,India,0,"Git, Data Visualization, Hadoop",Bachelor,9,Finance,2024-10-31,2024-11-18,870,6.6,Digital Transformation LLC +AI00735,AI Specialist,181167,GBP,135875,EX,PT,United Kingdom,M,Thailand,100,"Azure, MLOps, Mathematics, Docker",Bachelor,16,Transportation,2024-11-30,2025-01-25,1237,9.7,DataVision Ltd +AI00736,AI Software Engineer,137580,USD,137580,SE,CT,Denmark,M,Denmark,50,"Deep Learning, Kubernetes, AWS, Mathematics, GCP",PhD,7,Healthcare,2024-07-02,2024-09-06,1646,7.9,Neural Networks Co +AI00737,Autonomous Systems Engineer,81092,CAD,101365,EN,CT,Canada,L,India,0,"NLP, SQL, Statistics, Data Visualization, Scala",PhD,0,Finance,2025-04-27,2025-05-23,623,8.2,Digital Transformation LLC +AI00738,Principal Data Scientist,167011,EUR,141959,EX,PT,Germany,M,Russia,0,"Azure, MLOps, Python, Data Visualization, Mathematics",Master,16,Healthcare,2024-05-15,2024-06-12,2468,7.6,DeepTech Ventures +AI00739,Data Analyst,115690,SGD,150397,MI,CT,Singapore,M,Singapore,50,"Python, MLOps, Git",Master,2,Consulting,2024-11-25,2024-12-20,1357,6.2,Future Systems +AI00740,Head of AI,85081,JPY,9358910,MI,CT,Japan,M,Japan,100,"Docker, Git, Hadoop",Associate,3,Energy,2024-11-15,2024-11-29,1877,9.6,Smart Analytics +AI00741,AI Product Manager,204925,USD,204925,EX,CT,Norway,S,New Zealand,100,"TensorFlow, Azure, Scala, Kubernetes, Spark",PhD,13,Manufacturing,2025-03-10,2025-04-18,2392,5.3,Autonomous Tech +AI00742,NLP Engineer,71330,USD,71330,EN,FT,Ireland,M,Ireland,100,"Statistics, Kubernetes, Deep Learning, Scala, AWS",Master,1,Finance,2025-01-12,2025-02-03,1304,5.3,Smart Analytics +AI00743,ML Ops Engineer,147961,CHF,133165,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, Git, SQL",PhD,2,Gaming,2024-11-18,2025-01-27,2488,7,Digital Transformation LLC +AI00744,AI Architect,81537,EUR,69306,MI,PT,Germany,M,France,100,"GCP, Linux, Kubernetes",Associate,2,Media,2025-02-21,2025-03-08,1123,8.1,Quantum Computing Inc +AI00745,Autonomous Systems Engineer,169303,EUR,143908,EX,FL,Germany,M,Germany,0,"Linux, Kubernetes, AWS, Data Visualization",PhD,14,Transportation,2024-05-08,2024-07-09,1444,7,Machine Intelligence Group +AI00746,Autonomous Systems Engineer,79345,USD,79345,EN,FL,United States,L,United States,100,"Spark, Kubernetes, SQL, AWS",Associate,1,Gaming,2024-01-01,2024-03-03,2459,7.1,Cognitive Computing +AI00747,NLP Engineer,141710,EUR,120454,EX,FT,Austria,S,Argentina,100,"Azure, Python, Git, Docker",Master,12,Real Estate,2025-04-28,2025-06-20,975,7.4,AI Innovations +AI00748,Research Scientist,176540,USD,176540,EX,FT,Sweden,S,United States,0,"TensorFlow, Kubernetes, Git, Java, Docker",Master,16,Healthcare,2024-09-17,2024-11-19,738,5.5,Algorithmic Solutions +AI00749,Deep Learning Engineer,75872,SGD,98634,EN,FT,Singapore,S,Netherlands,0,"Hadoop, MLOps, Python, Computer Vision, Docker",Associate,0,Retail,2025-01-06,2025-01-30,1818,8.4,Digital Transformation LLC +AI00750,Machine Learning Researcher,39100,USD,39100,MI,CT,China,M,Netherlands,100,"SQL, Docker, Python, Mathematics",PhD,3,Energy,2025-04-08,2025-04-22,1101,5.7,DeepTech Ventures +AI00751,Data Analyst,60610,USD,60610,MI,PT,South Korea,S,South Korea,50,"PyTorch, Computer Vision, Mathematics, R",Associate,3,Finance,2025-03-23,2025-05-24,748,5.4,Digital Transformation LLC +AI00752,NLP Engineer,64997,USD,64997,EN,CT,Finland,L,Finland,50,"Computer Vision, TensorFlow, Java",PhD,0,Automotive,2024-12-01,2025-01-01,1749,7.9,Autonomous Tech +AI00753,Principal Data Scientist,79831,USD,79831,MI,FT,Finland,S,Finland,0,"Scala, Java, Kubernetes, Data Visualization, Git",Bachelor,4,Retail,2024-05-09,2024-06-22,1863,9.6,Autonomous Tech +AI00754,Data Analyst,75434,JPY,8297740,EN,FT,Japan,L,Austria,100,"Computer Vision, SQL, Linux, AWS, Mathematics",PhD,1,Technology,2025-04-23,2025-05-12,2180,7.3,DataVision Ltd +AI00755,NLP Engineer,135956,USD,135956,SE,PT,Israel,M,Israel,100,"Kubernetes, Scala, Computer Vision",Master,8,Transportation,2024-02-11,2024-04-20,1899,5.7,TechCorp Inc +AI00756,Machine Learning Engineer,91194,CAD,113993,MI,PT,Canada,S,Canada,0,"Azure, Spark, Linux, Scala, SQL",PhD,3,Media,2024-08-13,2024-09-20,689,9.9,Neural Networks Co +AI00757,Research Scientist,182045,USD,182045,EX,CT,Israel,S,India,100,"Computer Vision, Hadoop, Kubernetes, Spark, Statistics",PhD,10,Technology,2024-11-25,2025-01-26,1620,10,Digital Transformation LLC +AI00758,Data Engineer,143858,USD,143858,EX,FT,Israel,M,Israel,50,"Deep Learning, Kubernetes, Hadoop, Linux",Associate,10,Automotive,2025-01-03,2025-02-05,1182,7.8,Digital Transformation LLC +AI00759,Data Analyst,135781,USD,135781,SE,FT,Finland,M,Finland,100,"Linux, R, Hadoop, Computer Vision, Python",Master,7,Retail,2024-11-26,2025-02-03,1587,6.2,Cloud AI Solutions +AI00760,AI Product Manager,151948,USD,151948,MI,FL,Denmark,L,Germany,100,"Statistics, Computer Vision, NLP, Python, TensorFlow",Bachelor,3,Manufacturing,2024-11-11,2024-12-10,1738,6.3,Predictive Systems +AI00761,AI Research Scientist,97414,CAD,121768,SE,FL,Canada,S,Canada,0,"Tableau, R, SQL, GCP, Docker",Master,6,Healthcare,2024-08-04,2024-08-30,748,9.3,Autonomous Tech +AI00762,Autonomous Systems Engineer,44257,USD,44257,MI,PT,China,M,China,50,"Kubernetes, Hadoop, GCP, Scala, Azure",PhD,4,Manufacturing,2024-11-28,2024-12-23,1984,6.4,Autonomous Tech +AI00763,Machine Learning Researcher,183099,USD,183099,SE,FT,Denmark,M,Denmark,100,"GCP, Docker, MLOps, Tableau, PyTorch",Master,9,Manufacturing,2025-01-21,2025-02-11,542,8.9,Cloud AI Solutions +AI00764,AI Product Manager,66978,EUR,56931,EN,FT,France,M,France,50,"Azure, Linux, Statistics, NLP",Associate,0,Gaming,2025-04-06,2025-05-07,721,9.4,Cloud AI Solutions +AI00765,Computer Vision Engineer,58844,USD,58844,EN,PT,United States,S,Kenya,100,"SQL, Python, Mathematics",PhD,1,Technology,2024-03-15,2024-04-20,874,7.2,Digital Transformation LLC +AI00766,Data Scientist,86679,EUR,73677,EN,PT,France,L,France,50,"Scala, Docker, Spark, MLOps, NLP",PhD,1,Gaming,2024-04-09,2024-04-24,865,5.7,Cognitive Computing +AI00767,Research Scientist,102607,EUR,87216,MI,FL,Austria,L,Austria,50,"Scala, Python, Tableau, Statistics",Associate,4,Telecommunications,2025-04-16,2025-05-16,2191,8.4,Autonomous Tech +AI00768,AI Research Scientist,117860,USD,117860,MI,FL,Norway,S,Norway,0,"Linux, Python, Scala",Master,3,Consulting,2024-02-21,2024-03-23,1949,9.6,Cloud AI Solutions +AI00769,Data Engineer,53776,AUD,72598,EN,PT,Australia,M,Mexico,50,"PyTorch, Spark, TensorFlow",PhD,1,Energy,2025-03-31,2025-05-21,1959,10,Advanced Robotics +AI00770,Autonomous Systems Engineer,22245,USD,22245,EN,FL,India,S,India,100,"R, AWS, Mathematics, Deep Learning, MLOps",Bachelor,1,Automotive,2025-03-07,2025-04-27,2075,7.7,TechCorp Inc +AI00771,Deep Learning Engineer,86753,USD,86753,EN,CT,Denmark,S,Hungary,50,"Kubernetes, MLOps, SQL, Python",Bachelor,0,Consulting,2025-01-27,2025-03-19,527,8.3,Quantum Computing Inc +AI00772,Data Scientist,59445,CAD,74306,EN,PT,Canada,S,Canada,50,"Kubernetes, GCP, Java, Deep Learning, Statistics",Associate,0,Finance,2024-02-26,2024-03-21,1565,6.9,Autonomous Tech +AI00773,Machine Learning Researcher,181623,USD,181623,SE,FL,Norway,L,Norway,100,"Azure, Scala, Python, Git",Bachelor,7,Telecommunications,2024-02-14,2024-03-10,2148,9.1,Neural Networks Co +AI00774,Machine Learning Engineer,23848,USD,23848,EN,FL,China,S,Poland,0,"TensorFlow, Spark, NLP, Mathematics",Associate,1,Real Estate,2024-02-29,2024-04-17,1126,8.6,Machine Intelligence Group +AI00775,Head of AI,67555,USD,67555,SE,PT,China,L,China,100,"Mathematics, Scala, Java",PhD,5,Education,2024-11-30,2025-01-08,1445,8.8,Future Systems +AI00776,Autonomous Systems Engineer,156672,USD,156672,EX,FL,Sweden,L,Sweden,0,"Statistics, SQL, Python, AWS, Computer Vision",Associate,19,Real Estate,2025-03-23,2025-05-11,2253,7,AI Innovations +AI00777,Data Analyst,99310,USD,99310,EX,FT,China,S,Vietnam,50,"Scala, Java, Deep Learning",Associate,14,Transportation,2024-04-28,2024-05-28,1790,5.8,TechCorp Inc +AI00778,Data Scientist,106468,USD,106468,SE,FL,South Korea,S,Singapore,0,"Kubernetes, PyTorch, SQL, Computer Vision, Tableau",PhD,5,Energy,2025-02-07,2025-03-21,735,8.3,DataVision Ltd +AI00779,NLP Engineer,133549,JPY,14690390,SE,PT,Japan,L,Portugal,50,"Statistics, Docker, TensorFlow",Master,8,Government,2024-02-03,2024-03-05,762,7.5,Autonomous Tech +AI00780,AI Consultant,101850,USD,101850,EN,FL,Norway,L,Norway,50,"Mathematics, NLP, MLOps, Linux",PhD,1,Healthcare,2025-04-04,2025-04-24,1992,7.7,TechCorp Inc +AI00781,Data Analyst,135555,USD,135555,EX,FL,China,L,China,50,"Deep Learning, Scala, Python",Associate,18,Real Estate,2025-01-14,2025-02-16,1694,6.9,Advanced Robotics +AI00782,Data Scientist,194650,USD,194650,EX,CT,Norway,M,Norway,0,"GCP, Scala, PyTorch, SQL",Master,13,Automotive,2025-01-01,2025-01-16,1290,9.4,Cognitive Computing +AI00783,NLP Engineer,48184,USD,48184,SE,FT,India,S,India,50,"Kubernetes, Docker, Python, TensorFlow",PhD,8,Real Estate,2024-06-02,2024-07-06,526,7.4,Digital Transformation LLC +AI00784,NLP Engineer,102143,EUR,86822,MI,PT,Netherlands,S,Austria,100,"Docker, Git, Scala, Mathematics",Master,2,Technology,2024-10-02,2024-10-16,883,8.9,Cognitive Computing +AI00785,Data Engineer,130584,USD,130584,SE,FT,Finland,L,Hungary,0,"Kubernetes, Azure, Spark",PhD,6,Gaming,2024-05-29,2024-06-27,1303,8,Predictive Systems +AI00786,ML Ops Engineer,197290,USD,197290,SE,FL,Denmark,M,Nigeria,50,"Python, TensorFlow, Statistics, PyTorch, Deep Learning",Bachelor,5,Education,2024-08-30,2024-09-15,1376,8.8,TechCorp Inc +AI00787,AI Architect,57552,EUR,48919,EN,FL,Germany,M,Germany,50,"Hadoop, TensorFlow, Tableau",PhD,0,Retail,2024-04-21,2024-05-15,2185,5.4,Algorithmic Solutions +AI00788,AI Specialist,138325,USD,138325,SE,CT,Sweden,M,Sweden,0,"Azure, Spark, Data Visualization, R, Python",Master,7,Transportation,2024-10-25,2024-11-17,1112,5.6,Machine Intelligence Group +AI00789,AI Product Manager,62787,USD,62787,EN,FL,Norway,S,Singapore,0,"Hadoop, Scala, R, Python",Associate,1,Automotive,2024-09-11,2024-10-10,1204,5.1,Cloud AI Solutions +AI00790,AI Research Scientist,96898,EUR,82363,SE,FL,Austria,M,Austria,50,"Docker, Tableau, SQL, Deep Learning, MLOps",Bachelor,8,Healthcare,2024-09-15,2024-10-22,1719,6.3,Future Systems +AI00791,AI Software Engineer,101690,USD,101690,MI,CT,Norway,S,Norway,100,"Scala, Deep Learning, Git, TensorFlow",Bachelor,4,Telecommunications,2025-03-21,2025-05-01,2046,9.9,Predictive Systems +AI00792,Data Scientist,104342,USD,104342,MI,CT,United States,L,United States,50,"Azure, SQL, Python, AWS",Bachelor,2,Technology,2024-08-23,2024-09-21,2196,7.8,Future Systems +AI00793,Principal Data Scientist,182831,EUR,155406,EX,PT,Austria,S,Chile,100,"Kubernetes, Linux, Scala, Deep Learning, Azure",Master,18,Transportation,2024-12-22,2025-01-27,1334,5.8,Quantum Computing Inc +AI00794,AI Specialist,65362,EUR,55558,EN,PT,France,L,Japan,0,"TensorFlow, AWS, NLP, Data Visualization",Bachelor,1,Government,2024-09-12,2024-10-12,1819,5.2,Predictive Systems +AI00795,AI Software Engineer,116249,EUR,98812,SE,FL,France,M,France,50,"Scala, Java, MLOps, Azure",PhD,8,Finance,2024-05-02,2024-06-10,1595,8.6,Digital Transformation LLC +AI00796,Machine Learning Researcher,181065,USD,181065,EX,FL,Norway,S,Norway,0,"Java, R, Statistics, Linux, Mathematics",Master,19,Healthcare,2024-10-18,2024-11-03,2202,8,Machine Intelligence Group +AI00797,Data Engineer,110326,EUR,93777,SE,PT,France,S,France,0,"PyTorch, Hadoop, AWS, Python",Associate,8,Technology,2024-11-08,2024-12-14,739,9.3,Quantum Computing Inc +AI00798,AI Research Scientist,113275,EUR,96284,SE,FT,Netherlands,M,Netherlands,0,"Docker, Java, Tableau, Hadoop",Master,6,Consulting,2024-03-08,2024-04-17,1264,8,Quantum Computing Inc +AI00799,Autonomous Systems Engineer,86720,CAD,108400,SE,CT,Canada,S,Canada,0,"Spark, Kubernetes, SQL, Data Visualization",Bachelor,7,Consulting,2024-03-21,2024-05-18,821,6.7,Smart Analytics +AI00800,Deep Learning Engineer,88527,USD,88527,SE,CT,South Korea,M,South Korea,100,"Python, Docker, Linux, Spark, Scala",Master,8,Technology,2024-02-14,2024-04-27,1973,6.3,TechCorp Inc +AI00801,AI Software Engineer,75281,USD,75281,EN,FL,Finland,M,Finland,100,"Git, Python, Tableau, Spark",Associate,0,Technology,2024-07-12,2024-08-01,1666,8.4,Advanced Robotics +AI00802,Principal Data Scientist,63784,AUD,86108,EN,FL,Australia,L,Australia,100,"SQL, Deep Learning, Data Visualization, TensorFlow",Master,0,Healthcare,2025-02-14,2025-03-01,668,10,Quantum Computing Inc +AI00803,AI Product Manager,140500,SGD,182650,SE,CT,Singapore,L,Malaysia,0,"Kubernetes, Data Visualization, MLOps, Python, GCP",PhD,7,Energy,2024-12-15,2025-02-10,1733,8.6,Predictive Systems +AI00804,Deep Learning Engineer,30726,USD,30726,EN,FT,India,L,India,100,"Spark, Kubernetes, MLOps, Git",PhD,1,Telecommunications,2024-10-02,2024-10-18,782,7.9,Predictive Systems +AI00805,AI Specialist,242789,SGD,315626,EX,PT,Singapore,M,Singapore,50,"Data Visualization, Hadoop, MLOps, SQL",Associate,15,Manufacturing,2024-06-10,2024-07-03,592,8.7,DeepTech Ventures +AI00806,ML Ops Engineer,126827,USD,126827,EX,FT,South Korea,S,South Korea,0,"Python, Git, R, NLP, PyTorch",Master,17,Real Estate,2024-05-24,2024-06-19,2410,9.6,Digital Transformation LLC +AI00807,Robotics Engineer,77753,JPY,8552830,MI,CT,Japan,M,Japan,100,"Linux, Python, Java, Azure, Git",PhD,2,Automotive,2025-04-09,2025-06-19,845,9.4,Neural Networks Co +AI00808,Autonomous Systems Engineer,204502,USD,204502,EX,PT,United States,S,United States,100,"NLP, Linux, PyTorch",Master,13,Consulting,2024-11-23,2024-12-14,1899,9.7,Machine Intelligence Group +AI00809,Machine Learning Engineer,76869,EUR,65339,MI,PT,France,S,France,50,"SQL, Git, TensorFlow, Statistics",Bachelor,4,Healthcare,2025-03-11,2025-04-24,1199,7.6,AI Innovations +AI00810,Computer Vision Engineer,128192,USD,128192,SE,FT,Ireland,S,India,0,"R, SQL, PyTorch, Docker, Deep Learning",Bachelor,5,Energy,2024-11-01,2024-12-12,2010,5.4,Cognitive Computing +AI00811,Machine Learning Engineer,234782,CHF,211304,EX,PT,Switzerland,M,Switzerland,0,"Mathematics, SQL, MLOps, TensorFlow, Kubernetes",Associate,19,Education,2024-02-05,2024-03-25,1540,7.4,Quantum Computing Inc +AI00812,Robotics Engineer,243016,USD,243016,EX,CT,Norway,S,Norway,0,"SQL, Deep Learning, Data Visualization",PhD,14,Consulting,2024-04-20,2024-06-27,2207,5.9,Machine Intelligence Group +AI00813,ML Ops Engineer,232932,GBP,174699,EX,CT,United Kingdom,L,United Kingdom,50,"Statistics, Spark, Python, AWS, Azure",Bachelor,19,Education,2024-05-27,2024-07-02,2321,7.9,DeepTech Ventures +AI00814,AI Software Engineer,157713,EUR,134056,EX,FT,France,L,France,100,"Statistics, Azure, NLP, Data Visualization, Deep Learning",Associate,11,Real Estate,2024-03-29,2024-04-18,1275,7.3,Quantum Computing Inc +AI00815,Computer Vision Engineer,78731,GBP,59048,MI,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, PyTorch, SQL, Mathematics, Scala",Bachelor,4,Retail,2025-01-12,2025-01-26,893,9.7,DataVision Ltd +AI00816,Machine Learning Engineer,118802,CAD,148503,SE,PT,Canada,L,Canada,50,"GCP, Docker, Azure, Tableau, PyTorch",PhD,5,Telecommunications,2025-01-18,2025-02-08,2228,9.6,Digital Transformation LLC +AI00817,AI Software Engineer,86119,CHF,77507,EN,PT,Switzerland,M,Switzerland,50,"MLOps, Scala, Azure",Master,1,Retail,2025-03-14,2025-04-18,1655,7.2,Future Systems +AI00818,Head of AI,148519,GBP,111389,EX,CT,United Kingdom,M,United Kingdom,50,"MLOps, Java, Scala, R",PhD,19,Retail,2025-02-11,2025-02-26,1578,5.8,Neural Networks Co +AI00819,AI Research Scientist,48058,USD,48058,EN,PT,South Korea,S,South Korea,100,"Spark, Hadoop, TensorFlow, Data Visualization, Computer Vision",Associate,1,Manufacturing,2024-08-26,2024-11-06,1378,5.2,Future Systems +AI00820,AI Architect,68183,EUR,57956,EN,FT,France,M,France,0,"Mathematics, SQL, Spark, Kubernetes, PyTorch",PhD,0,Retail,2024-12-08,2025-02-11,1399,5.9,Algorithmic Solutions +AI00821,Principal Data Scientist,237151,GBP,177863,EX,FT,United Kingdom,S,United Kingdom,100,"Git, Computer Vision, Tableau, Azure",PhD,15,Energy,2025-04-02,2025-05-20,2094,9.5,Algorithmic Solutions +AI00822,Data Engineer,95252,USD,95252,MI,PT,Ireland,S,Ireland,50,"Scala, MLOps, SQL",Bachelor,4,Real Estate,2024-11-05,2024-12-17,1479,9.9,AI Innovations +AI00823,NLP Engineer,142166,JPY,15638260,SE,CT,Japan,L,Japan,50,"Python, TensorFlow, Computer Vision, AWS, Statistics",Master,5,Transportation,2024-11-02,2024-12-20,1946,6.1,DeepTech Ventures +AI00824,Machine Learning Engineer,107965,USD,107965,SE,CT,Sweden,S,Romania,100,"SQL, Kubernetes, MLOps, NLP, GCP",Bachelor,9,Healthcare,2024-08-16,2024-08-31,1211,7.3,Advanced Robotics +AI00825,ML Ops Engineer,239943,EUR,203952,EX,FT,Netherlands,L,Netherlands,50,"Azure, MLOps, R, Python, TensorFlow",Bachelor,12,Real Estate,2024-05-16,2024-07-11,602,9.1,Machine Intelligence Group +AI00826,Robotics Engineer,287023,USD,287023,EX,PT,Ireland,L,Ireland,100,"Computer Vision, Linux, GCP, Scala",Master,10,Education,2025-03-31,2025-04-29,543,7.4,Cloud AI Solutions +AI00827,AI Architect,108794,USD,108794,MI,FL,Norway,L,Ukraine,0,"Hadoop, Kubernetes, Docker, Statistics, SQL",Associate,4,Government,2024-09-27,2024-11-26,1050,5.9,Advanced Robotics +AI00828,AI Specialist,91776,USD,91776,EN,FT,United States,M,Germany,0,"Docker, Computer Vision, AWS, Python, TensorFlow",PhD,1,Technology,2024-03-19,2024-04-25,2314,6.1,Predictive Systems +AI00829,Robotics Engineer,61890,USD,61890,EN,PT,South Korea,L,Italy,0,"Java, R, SQL",Bachelor,1,Consulting,2024-12-20,2025-01-15,709,5.4,Advanced Robotics +AI00830,Data Analyst,345294,USD,345294,EX,FT,Norway,L,Norway,100,"Kubernetes, TensorFlow, GCP",PhD,11,Telecommunications,2025-02-03,2025-04-06,1012,6.6,DataVision Ltd +AI00831,AI Product Manager,78569,USD,78569,MI,CT,Israel,L,Israel,0,"Spark, PyTorch, MLOps, NLP, Kubernetes",Master,4,Healthcare,2024-11-20,2024-12-05,2033,7.4,DataVision Ltd +AI00832,Autonomous Systems Engineer,66673,EUR,56672,EN,PT,France,M,France,100,"Git, Scala, Python",Master,0,Telecommunications,2024-11-27,2024-12-14,1825,8.6,Future Systems +AI00833,Machine Learning Researcher,183500,CHF,165150,SE,CT,Switzerland,M,Switzerland,50,"TensorFlow, Python, Computer Vision, Statistics, Scala",PhD,8,Transportation,2025-01-24,2025-03-08,686,9.1,Digital Transformation LLC +AI00834,ML Ops Engineer,165234,SGD,214804,EX,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Python, NLP",Associate,10,Manufacturing,2024-05-07,2024-05-22,913,6,Future Systems +AI00835,Principal Data Scientist,119549,SGD,155414,MI,FT,Singapore,L,Singapore,100,"Kubernetes, NLP, MLOps",Master,2,Consulting,2024-11-05,2024-12-12,1344,5.7,Digital Transformation LLC +AI00836,NLP Engineer,325936,USD,325936,EX,PT,Norway,L,Norway,100,"Scala, Spark, Deep Learning",Bachelor,19,Government,2024-09-01,2024-11-04,1066,8.3,Cognitive Computing +AI00837,ML Ops Engineer,157221,SGD,204387,SE,FT,Singapore,L,Singapore,0,"PyTorch, Java, GCP, Python, Hadoop",Associate,7,Gaming,2025-02-24,2025-03-23,908,8.5,Future Systems +AI00838,Machine Learning Engineer,98221,USD,98221,SE,PT,South Korea,L,South Korea,0,"Python, Deep Learning, AWS, Statistics",Bachelor,6,Finance,2024-05-04,2024-06-10,1650,6.7,Algorithmic Solutions +AI00839,Autonomous Systems Engineer,155502,GBP,116627,EX,CT,United Kingdom,M,India,50,"Kubernetes, Java, Docker, Hadoop",Master,11,Healthcare,2025-03-18,2025-05-10,503,9.5,DeepTech Ventures +AI00840,Principal Data Scientist,276679,USD,276679,EX,FT,Denmark,L,Denmark,0,"PyTorch, GCP, MLOps, AWS, Mathematics",Master,11,Telecommunications,2024-07-11,2024-09-21,1457,8.7,Predictive Systems +AI00841,AI Product Manager,187955,EUR,159762,EX,CT,Germany,S,Turkey,0,"Docker, Git, Linux",Master,19,Manufacturing,2025-02-01,2025-04-04,2439,7.9,Smart Analytics +AI00842,Data Engineer,135585,USD,135585,MI,FT,Denmark,L,Denmark,100,"AWS, Python, GCP",Associate,4,Real Estate,2024-06-02,2024-08-11,2302,5.1,Cloud AI Solutions +AI00843,Machine Learning Researcher,138945,USD,138945,SE,PT,United States,L,Kenya,50,"Java, Azure, Data Visualization, NLP",Master,5,Transportation,2024-07-08,2024-08-01,1468,7.3,TechCorp Inc +AI00844,Autonomous Systems Engineer,89723,EUR,76265,MI,FL,Netherlands,S,Netherlands,50,"Python, PyTorch, Spark, TensorFlow",Associate,3,Education,2024-06-17,2024-08-12,914,5.3,Advanced Robotics +AI00845,Computer Vision Engineer,74250,USD,74250,EN,FL,United States,L,Colombia,100,"NLP, R, TensorFlow",Associate,0,Consulting,2024-09-22,2024-10-07,2179,5.3,Predictive Systems +AI00846,Machine Learning Researcher,209546,USD,209546,EX,FT,Norway,M,Norway,100,"NLP, SQL, PyTorch, Git, Spark",Associate,11,Telecommunications,2025-01-24,2025-02-23,2485,7.7,Smart Analytics +AI00847,AI Product Manager,137463,JPY,15120930,EX,FL,Japan,S,Japan,0,"AWS, Git, Python, NLP, Scala",Associate,13,Healthcare,2024-05-28,2024-06-11,1088,7.9,Autonomous Tech +AI00848,Head of AI,83657,USD,83657,EN,FT,Ireland,L,Ireland,0,"Python, MLOps, Data Visualization, Spark",Master,0,Government,2024-06-25,2024-08-14,1808,6.4,Predictive Systems +AI00849,Data Engineer,120560,USD,120560,MI,FT,United States,M,Vietnam,0,"Hadoop, MLOps, Spark, Kubernetes",Bachelor,3,Retail,2024-08-18,2024-09-15,1128,7.5,AI Innovations +AI00850,AI Architect,87119,USD,87119,SE,PT,Israel,S,Denmark,100,"Scala, Statistics, Java",Associate,7,Media,2025-04-05,2025-05-17,1585,8.6,AI Innovations +AI00851,Principal Data Scientist,71418,USD,71418,MI,FL,South Korea,L,South Korea,100,"AWS, Linux, R",Master,4,Government,2024-10-17,2024-12-22,1154,8.8,Predictive Systems +AI00852,AI Consultant,46727,USD,46727,EX,FT,India,S,India,50,"SQL, Docker, Python",Bachelor,19,Automotive,2024-08-31,2024-10-20,1896,6.9,Advanced Robotics +AI00853,Data Scientist,164321,USD,164321,EX,PT,Sweden,S,Netherlands,50,"Kubernetes, GCP, PyTorch",Master,16,Energy,2024-08-01,2024-09-10,2008,6.4,Predictive Systems +AI00854,AI Product Manager,80460,JPY,8850600,EN,FL,Japan,M,Indonesia,0,"Python, Scala, TensorFlow",Bachelor,1,Energy,2025-01-17,2025-03-02,2267,9.9,Quantum Computing Inc +AI00855,Robotics Engineer,99510,EUR,84584,SE,CT,France,S,France,50,"Deep Learning, SQL, PyTorch",Associate,8,Technology,2025-04-26,2025-06-26,2131,9.8,Neural Networks Co +AI00856,Head of AI,145409,CHF,130868,MI,PT,Switzerland,M,Switzerland,100,"Git, NLP, Tableau, Python",Associate,2,Energy,2024-06-03,2024-08-04,1347,8.8,Cognitive Computing +AI00857,Data Analyst,289465,USD,289465,EX,PT,United States,M,United States,50,"Docker, MLOps, Python, Statistics, SQL",Bachelor,13,Retail,2025-04-08,2025-05-20,1420,9.2,Digital Transformation LLC +AI00858,ML Ops Engineer,85216,JPY,9373760,EN,FT,Japan,M,Japan,0,"AWS, Data Visualization, Python",Bachelor,1,Telecommunications,2024-09-17,2024-10-23,797,8.8,Cognitive Computing +AI00859,AI Software Engineer,88921,CAD,111151,MI,CT,Canada,S,Canada,100,"SQL, Kubernetes, Azure, Hadoop",PhD,3,Technology,2024-09-01,2024-09-21,1630,8.8,Advanced Robotics +AI00860,NLP Engineer,65144,USD,65144,EN,FL,Sweden,L,Argentina,100,"Hadoop, MLOps, Docker, Deep Learning, Statistics",Associate,0,Retail,2024-09-16,2024-11-25,1121,5.5,Quantum Computing Inc +AI00861,Data Analyst,103403,USD,103403,MI,CT,Israel,M,Israel,50,"Tableau, SQL, Linux, NLP, Kubernetes",Bachelor,3,Technology,2024-01-14,2024-02-11,2139,6.6,Smart Analytics +AI00862,Deep Learning Engineer,121368,USD,121368,SE,FL,Israel,M,Israel,50,"Spark, Python, Data Visualization",PhD,8,Energy,2024-04-01,2024-05-29,1567,5.2,Predictive Systems +AI00863,Head of AI,168109,AUD,226947,SE,CT,Australia,L,Australia,50,"Data Visualization, GCP, SQL",Bachelor,7,Gaming,2025-01-25,2025-03-22,2457,9.6,Cognitive Computing +AI00864,Robotics Engineer,40616,USD,40616,MI,CT,China,S,Canada,0,"TensorFlow, Git, Python, Hadoop",Associate,2,Finance,2024-07-31,2024-08-27,2010,5.9,Neural Networks Co +AI00865,NLP Engineer,176886,CHF,159197,EX,CT,Switzerland,S,Switzerland,0,"PyTorch, Scala, Deep Learning, Computer Vision",Master,16,Real Estate,2024-02-18,2024-04-22,1045,9.8,DataVision Ltd +AI00866,Autonomous Systems Engineer,107548,EUR,91416,MI,CT,Germany,M,Germany,0,"Linux, Python, TensorFlow",Master,2,Consulting,2024-08-16,2024-10-17,1812,9.7,AI Innovations +AI00867,AI Software Engineer,313203,CHF,281883,EX,FL,Switzerland,S,Switzerland,50,"Kubernetes, Python, Mathematics, Java",Master,15,Finance,2025-04-02,2025-06-14,1078,6,Algorithmic Solutions +AI00868,AI Consultant,147571,EUR,125435,EX,FT,France,M,United States,0,"R, GCP, Git",Associate,12,Consulting,2024-12-14,2025-02-12,679,5,Advanced Robotics +AI00869,Deep Learning Engineer,239432,EUR,203517,EX,PT,France,M,France,100,"R, NLP, Java, Hadoop",Associate,19,Automotive,2024-06-03,2024-08-02,1371,8,Machine Intelligence Group +AI00870,Machine Learning Researcher,119559,USD,119559,MI,CT,United States,L,United States,0,"PyTorch, Linux, NLP, MLOps, Java",Bachelor,2,Real Estate,2025-03-31,2025-05-15,546,5.9,Quantum Computing Inc +AI00871,AI Consultant,72051,SGD,93666,EN,FT,Singapore,S,Singapore,100,"AWS, Kubernetes, Tableau, Azure, Java",Master,0,Education,2024-09-11,2024-10-07,2394,6,Future Systems +AI00872,Machine Learning Engineer,80766,AUD,109034,EN,FT,Australia,L,India,100,"Java, R, NLP, Azure",PhD,1,Media,2025-02-03,2025-02-18,845,7.2,Future Systems +AI00873,Computer Vision Engineer,75201,CHF,67681,EN,PT,Switzerland,M,Switzerland,100,"Data Visualization, SQL, Scala, Deep Learning, Hadoop",Associate,0,Telecommunications,2024-08-11,2024-10-21,505,6.5,Cloud AI Solutions +AI00874,Machine Learning Engineer,367330,CHF,330597,EX,PT,Switzerland,L,Belgium,100,"Kubernetes, SQL, Mathematics, Deep Learning, Computer Vision",Master,12,Finance,2025-01-25,2025-02-26,1732,6.1,Cloud AI Solutions +AI00875,AI Specialist,99824,CHF,89842,EN,FL,Switzerland,S,Switzerland,100,"Tableau, Linux, AWS, Python, Mathematics",Master,1,Manufacturing,2025-01-30,2025-03-15,1530,9.4,DataVision Ltd +AI00876,Computer Vision Engineer,183643,GBP,137732,EX,FL,United Kingdom,L,United Kingdom,50,"Git, Python, NLP",Bachelor,16,Transportation,2024-09-30,2024-10-22,1295,9.9,DataVision Ltd +AI00877,Research Scientist,86875,CAD,108594,MI,FL,Canada,L,Canada,0,"Kubernetes, NLP, SQL",Bachelor,2,Education,2025-01-27,2025-03-10,2499,8.1,DataVision Ltd +AI00878,AI Architect,92050,USD,92050,EN,PT,Denmark,S,Denmark,100,"Spark, Docker, Computer Vision, NLP, Data Visualization",PhD,0,Healthcare,2025-02-04,2025-03-26,1907,5,DataVision Ltd +AI00879,Machine Learning Engineer,188547,EUR,160265,EX,CT,Germany,S,Indonesia,100,"Hadoop, SQL, Computer Vision, PyTorch, Docker",Bachelor,10,Transportation,2024-07-01,2024-08-17,1395,7.2,Cloud AI Solutions +AI00880,Data Scientist,93400,USD,93400,MI,FT,Ireland,S,Ireland,0,"Scala, Azure, Data Visualization, PyTorch, Git",Bachelor,4,Government,2024-11-09,2025-01-08,1829,5.7,Machine Intelligence Group +AI00881,Data Scientist,121492,EUR,103268,SE,PT,Germany,M,Germany,50,"AWS, Tableau, Kubernetes, Python",Associate,5,Technology,2025-04-11,2025-06-15,799,6.4,Future Systems +AI00882,AI Software Engineer,214716,CAD,268395,EX,CT,Canada,M,Canada,100,"SQL, Java, Git, Scala, Spark",Bachelor,13,Transportation,2024-01-29,2024-04-02,1629,7.4,Smart Analytics +AI00883,Machine Learning Engineer,96552,USD,96552,MI,PT,Denmark,S,Chile,0,"Spark, Git, Data Visualization, Kubernetes, SQL",Bachelor,3,Transportation,2025-03-01,2025-04-25,1746,6.7,DataVision Ltd +AI00884,Research Scientist,82126,EUR,69807,MI,CT,France,M,France,50,"Tableau, Hadoop, Python, AWS",PhD,4,Energy,2024-06-20,2024-08-31,1435,6.3,AI Innovations +AI00885,ML Ops Engineer,101793,EUR,86524,MI,FT,France,L,France,50,"TensorFlow, Azure, Python, Deep Learning",PhD,3,Education,2024-07-14,2024-07-31,926,5.5,Future Systems +AI00886,AI Research Scientist,119593,CAD,149491,MI,PT,Canada,L,Canada,100,"Data Visualization, Python, Tableau",Master,3,Government,2024-02-17,2024-04-23,908,6.3,Autonomous Tech +AI00887,AI Software Engineer,83380,USD,83380,EX,FL,China,M,China,0,"R, Scala, AWS, Data Visualization",PhD,18,Education,2024-08-19,2024-09-06,848,9.6,Advanced Robotics +AI00888,NLP Engineer,104077,EUR,88465,MI,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, Docker, Azure",Associate,3,Transportation,2025-03-29,2025-05-19,821,6.8,Smart Analytics +AI00889,Research Scientist,107155,EUR,91082,SE,PT,France,M,France,100,"Scala, SQL, GCP, Git, Linux",Associate,5,Real Estate,2024-09-29,2024-11-03,2162,6.2,Autonomous Tech +AI00890,AI Architect,95613,USD,95613,EN,FL,Denmark,M,Denmark,50,"Hadoop, Docker, Scala",Associate,0,Consulting,2024-11-08,2024-12-06,1404,8.3,TechCorp Inc +AI00891,AI Research Scientist,79915,USD,79915,MI,CT,Israel,S,Israel,0,"PyTorch, Hadoop, TensorFlow",Master,2,Consulting,2024-01-08,2024-01-29,2279,9.7,Advanced Robotics +AI00892,ML Ops Engineer,152836,USD,152836,SE,FT,Israel,L,Israel,100,"Statistics, PyTorch, NLP, Git",Associate,9,Education,2024-01-25,2024-02-24,2225,5.8,Predictive Systems +AI00893,AI Research Scientist,201144,SGD,261487,EX,FT,Singapore,M,Singapore,50,"Linux, AWS, R, Deep Learning, Docker",Associate,10,Government,2024-11-09,2025-01-10,1814,7.9,TechCorp Inc +AI00894,Machine Learning Researcher,74068,USD,74068,MI,FT,Israel,S,Israel,100,"SQL, PyTorch, Linux",PhD,4,Healthcare,2024-11-11,2024-12-06,1384,5.9,Digital Transformation LLC +AI00895,Principal Data Scientist,94861,EUR,80632,MI,FT,Netherlands,S,Netherlands,50,"Git, Scala, Tableau, Spark",Master,2,Government,2024-06-01,2024-07-10,1711,5.7,Autonomous Tech +AI00896,Head of AI,89534,USD,89534,MI,FL,South Korea,M,Romania,100,"Azure, AWS, GCP, Git, Kubernetes",PhD,4,Consulting,2024-02-21,2024-04-30,1229,7.5,AI Innovations +AI00897,Research Scientist,121009,USD,121009,MI,PT,Denmark,L,Switzerland,50,"R, Scala, Computer Vision, Azure",Associate,2,Government,2024-10-17,2024-12-20,2092,7.5,Autonomous Tech +AI00898,AI Software Engineer,98503,USD,98503,MI,FT,Denmark,M,United Kingdom,100,"Kubernetes, Linux, Hadoop",Bachelor,3,Energy,2025-01-24,2025-03-07,2120,7.1,Algorithmic Solutions +AI00899,Autonomous Systems Engineer,92133,USD,92133,MI,FL,Finland,L,Finland,100,"R, Scala, GCP",Bachelor,2,Automotive,2024-08-24,2024-10-18,2014,6.8,Predictive Systems +AI00900,Research Scientist,108765,USD,108765,MI,PT,United States,M,United States,0,"Spark, TensorFlow, Java, Azure",Bachelor,4,Automotive,2024-06-24,2024-07-28,1043,8.9,Autonomous Tech +AI00901,Machine Learning Engineer,93440,CHF,84096,EN,CT,Switzerland,M,Switzerland,0,"Statistics, Git, Kubernetes, Python, Azure",Bachelor,0,Retail,2024-10-17,2024-11-20,659,6.1,Cloud AI Solutions +AI00902,AI Architect,88745,SGD,115369,MI,FT,Singapore,S,Singapore,100,"SQL, Deep Learning, GCP, MLOps, Spark",Associate,4,Finance,2025-03-02,2025-03-22,1741,9.5,Algorithmic Solutions +AI00903,Research Scientist,105976,USD,105976,SE,PT,Ireland,M,Ireland,100,"SQL, Hadoop, Kubernetes",Associate,7,Transportation,2024-03-16,2024-05-20,1015,7.6,Digital Transformation LLC +AI00904,NLP Engineer,59221,USD,59221,MI,PT,South Korea,S,South Korea,0,"Statistics, Spark, Tableau, Java",Associate,3,Media,2024-09-09,2024-10-19,1905,5.3,Quantum Computing Inc +AI00905,NLP Engineer,61996,USD,61996,EN,FT,Sweden,L,United States,100,"Scala, Kubernetes, Computer Vision, SQL",PhD,0,Gaming,2024-02-25,2024-03-23,2259,7.8,Quantum Computing Inc +AI00906,ML Ops Engineer,90426,EUR,76862,MI,FT,France,S,France,50,"Git, Data Visualization, Spark",Master,3,Real Estate,2025-04-02,2025-04-28,1535,6.2,Autonomous Tech +AI00907,AI Consultant,60924,EUR,51785,EN,PT,France,S,France,0,"Scala, Hadoop, Java",Associate,0,Healthcare,2024-08-09,2024-09-03,2378,7.5,Advanced Robotics +AI00908,Data Engineer,243192,CAD,303990,EX,CT,Canada,L,Canada,0,"Scala, Azure, Kubernetes, Java, Statistics",Bachelor,16,Automotive,2024-03-07,2024-05-19,1815,9,Machine Intelligence Group +AI00909,Deep Learning Engineer,166087,EUR,141174,EX,FT,France,L,France,0,"Mathematics, Git, Data Visualization, Scala",Associate,10,Finance,2024-01-20,2024-02-14,2264,9.3,Smart Analytics +AI00910,Research Scientist,85173,USD,85173,EN,CT,Finland,L,Finland,0,"Statistics, Java, NLP, Git",Bachelor,0,Real Estate,2024-07-18,2024-09-06,2477,5.6,Machine Intelligence Group +AI00911,AI Specialist,309247,CHF,278322,EX,CT,Switzerland,L,Switzerland,100,"Computer Vision, GCP, Statistics, Azure, TensorFlow",Associate,10,Telecommunications,2024-02-18,2024-03-26,749,5.1,Digital Transformation LLC +AI00912,Computer Vision Engineer,121556,EUR,103323,MI,FL,Germany,L,Germany,0,"Data Visualization, Scala, PyTorch",PhD,3,Gaming,2025-04-17,2025-05-04,1461,5.2,Neural Networks Co +AI00913,AI Consultant,89998,JPY,9899780,EN,CT,Japan,L,Japan,50,"Scala, TensorFlow, Linux",PhD,1,Technology,2024-06-11,2024-07-20,617,8,Cognitive Computing +AI00914,AI Architect,63415,EUR,53903,MI,FT,France,S,France,100,"Kubernetes, Scala, Hadoop, Java, NLP",Master,3,Energy,2025-02-19,2025-04-13,1601,5.4,Future Systems +AI00915,Data Scientist,132964,USD,132964,MI,PT,Denmark,M,Denmark,0,"Scala, Python, MLOps",Master,2,Energy,2024-04-01,2024-06-11,1070,6.9,Machine Intelligence Group +AI00916,ML Ops Engineer,65099,SGD,84629,EN,PT,Singapore,S,Singapore,50,"Linux, PyTorch, SQL",Associate,0,Transportation,2024-02-03,2024-02-21,2192,5.1,DataVision Ltd +AI00917,AI Product Manager,170410,USD,170410,EX,FT,South Korea,L,South Korea,100,"MLOps, PyTorch, Tableau, SQL",Associate,16,Healthcare,2024-01-25,2024-02-18,1497,9.6,DataVision Ltd +AI00918,Data Engineer,25440,USD,25440,EN,CT,India,M,India,0,"Kubernetes, Scala, AWS",Master,1,Gaming,2024-10-28,2024-11-12,987,6.4,Advanced Robotics +AI00919,Research Scientist,173489,JPY,19083790,SE,FT,Japan,L,France,50,"Git, SQL, Kubernetes, Mathematics, PyTorch",Bachelor,8,Energy,2025-01-12,2025-01-29,647,5,Cloud AI Solutions +AI00920,Computer Vision Engineer,216939,USD,216939,EX,FT,United States,L,United States,100,"GCP, Git, MLOps, Mathematics, Scala",Master,13,Real Estate,2024-02-18,2024-04-25,1487,5.8,Algorithmic Solutions +AI00921,Autonomous Systems Engineer,117695,USD,117695,SE,FL,United States,S,Austria,50,"Hadoop, Azure, Java, Linux, Deep Learning",Bachelor,9,Gaming,2024-04-30,2024-06-10,894,9.4,Neural Networks Co +AI00922,AI Specialist,78936,AUD,106564,MI,CT,Australia,M,Australia,100,"Python, Git, TensorFlow, Deep Learning",Associate,4,Telecommunications,2024-09-07,2024-11-13,1081,9,Cloud AI Solutions +AI00923,NLP Engineer,113661,USD,113661,EN,FT,Norway,L,Norway,50,"Python, PyTorch, Git, Linux",Associate,0,Manufacturing,2025-02-16,2025-04-25,1471,5.9,Quantum Computing Inc +AI00924,Computer Vision Engineer,226030,JPY,24863300,EX,FT,Japan,S,Japan,50,"Git, SQL, Spark",Bachelor,17,Energy,2025-01-04,2025-02-16,744,9.8,AI Innovations +AI00925,Machine Learning Researcher,162220,USD,162220,EX,CT,Finland,S,Russia,50,"Spark, Data Visualization, PyTorch",Master,17,Transportation,2024-01-27,2024-03-12,862,5.5,Future Systems +AI00926,Deep Learning Engineer,165689,USD,165689,EX,FT,Ireland,S,Ireland,0,"R, TensorFlow, GCP, Linux, Statistics",PhD,19,Automotive,2024-11-13,2024-11-29,567,9.5,Cognitive Computing +AI00927,Principal Data Scientist,319536,CHF,287582,EX,FT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Java, Tableau",PhD,16,Technology,2024-01-22,2024-02-17,1950,6,DeepTech Ventures +AI00928,Data Scientist,97294,USD,97294,SE,CT,Israel,M,Israel,50,"Azure, Java, Spark, Linux, R",PhD,7,Manufacturing,2024-07-17,2024-08-21,985,7.9,Quantum Computing Inc +AI00929,Machine Learning Researcher,94506,USD,94506,EN,FT,Denmark,L,Denmark,50,"Docker, Scala, Azure, Mathematics, MLOps",Associate,1,Consulting,2024-09-29,2024-11-06,2181,9.4,Quantum Computing Inc +AI00930,Data Engineer,122519,USD,122519,SE,PT,Israel,M,Israel,50,"Data Visualization, MLOps, Hadoop, Docker",Bachelor,8,Manufacturing,2024-07-19,2024-08-09,644,7.3,Machine Intelligence Group +AI00931,Autonomous Systems Engineer,61916,USD,61916,MI,FT,South Korea,S,South Korea,100,"Java, Statistics, GCP, Kubernetes, NLP",Associate,2,Energy,2024-10-16,2024-11-03,1639,5.1,Autonomous Tech +AI00932,Principal Data Scientist,78823,USD,78823,MI,FL,Israel,M,India,50,"Python, GCP, TensorFlow, Mathematics",Associate,4,Technology,2024-09-07,2024-09-26,756,5.2,Machine Intelligence Group +AI00933,Data Engineer,111124,USD,111124,EN,CT,Denmark,L,China,0,"Spark, GCP, Data Visualization",Master,0,Technology,2024-04-23,2024-07-01,1021,8.5,Neural Networks Co +AI00934,Robotics Engineer,91289,EUR,77596,EN,FL,Netherlands,L,Netherlands,0,"PyTorch, Spark, Azure, Kubernetes, Java",Master,0,Education,2024-02-06,2024-03-10,972,8.5,DataVision Ltd +AI00935,AI Specialist,195659,USD,195659,SE,PT,Norway,L,Norway,50,"Python, Hadoop, TensorFlow, Computer Vision",PhD,6,Media,2024-02-08,2024-03-18,1789,7,Future Systems +AI00936,Data Engineer,199412,EUR,169500,EX,PT,Germany,S,Norway,50,"Java, Scala, Docker",Bachelor,17,Government,2024-02-05,2024-03-08,1254,8.1,Smart Analytics +AI00937,Data Engineer,202421,USD,202421,EX,FL,Norway,L,Norway,100,"Kubernetes, Git, PyTorch",Master,19,Manufacturing,2024-11-22,2025-01-28,2135,6.4,Machine Intelligence Group +AI00938,Data Scientist,133682,GBP,100262,MI,FL,United Kingdom,L,United Kingdom,100,"Hadoop, Spark, MLOps, GCP, R",Associate,3,Manufacturing,2025-03-20,2025-05-05,2382,8,Autonomous Tech +AI00939,Data Analyst,205143,GBP,153857,EX,PT,United Kingdom,L,South Africa,0,"TensorFlow, Azure, NLP",Associate,11,Finance,2024-08-28,2024-10-29,2193,9.1,Future Systems +AI00940,Head of AI,27765,USD,27765,EN,CT,China,S,China,0,"MLOps, Deep Learning, Python, Tableau",Bachelor,1,Consulting,2025-01-15,2025-02-12,968,9.3,Cloud AI Solutions +AI00941,NLP Engineer,170181,USD,170181,EX,PT,Ireland,M,Ireland,100,"Deep Learning, Python, Azure, TensorFlow",Bachelor,11,Gaming,2024-12-26,2025-01-24,2089,8,DataVision Ltd +AI00942,ML Ops Engineer,103167,USD,103167,MI,CT,United States,M,United States,100,"AWS, Kubernetes, MLOps",Associate,2,Healthcare,2024-04-05,2024-04-21,1873,8,Predictive Systems +AI00943,ML Ops Engineer,194546,USD,194546,EX,PT,Sweden,L,Sweden,0,"TensorFlow, Docker, Python, Hadoop",Master,16,Retail,2025-01-07,2025-03-05,1532,7.2,Digital Transformation LLC +AI00944,Research Scientist,130072,USD,130072,EX,CT,Israel,S,Israel,100,"R, Data Visualization, Java",Master,13,Government,2024-10-14,2024-11-20,2006,5.4,Cloud AI Solutions +AI00945,AI Specialist,39197,USD,39197,EN,PT,China,L,Australia,0,"Kubernetes, Java, SQL, NLP",Associate,1,Energy,2024-05-17,2024-07-08,1770,6.7,Quantum Computing Inc +AI00946,Autonomous Systems Engineer,204421,EUR,173758,EX,FL,Austria,L,Austria,50,"PyTorch, Data Visualization, Azure",Master,14,Energy,2024-07-30,2024-09-05,2389,8.5,Neural Networks Co +AI00947,Head of AI,112925,CHF,101633,EN,FT,Switzerland,L,Switzerland,100,"SQL, GCP, Spark, Azure, Linux",Bachelor,0,Government,2024-11-07,2024-11-26,1221,5.7,DataVision Ltd +AI00948,Data Scientist,265788,SGD,345524,EX,FT,Singapore,M,Turkey,0,"MLOps, Data Visualization, Scala, Python, AWS",Associate,18,Technology,2025-01-26,2025-04-07,2270,5.4,Smart Analytics +AI00949,Machine Learning Researcher,98150,USD,98150,EN,FL,Denmark,L,Denmark,0,"Data Visualization, Java, Hadoop",PhD,1,Energy,2025-03-11,2025-04-27,1648,7.6,Autonomous Tech +AI00950,Data Engineer,126741,USD,126741,SE,FL,United States,S,Romania,50,"PyTorch, Data Visualization, Azure, Computer Vision",Master,9,Finance,2024-05-29,2024-07-20,1974,5.9,Predictive Systems +AI00951,ML Ops Engineer,75006,USD,75006,EN,FL,Israel,M,Austria,100,"MLOps, TensorFlow, Scala",Associate,1,Finance,2024-02-15,2024-03-01,1642,7.3,DeepTech Ventures +AI00952,AI Research Scientist,84346,EUR,71694,MI,FT,Austria,S,France,0,"Statistics, Spark, GCP",Associate,4,Manufacturing,2024-09-20,2024-10-27,2188,7.5,DataVision Ltd +AI00953,Autonomous Systems Engineer,48241,USD,48241,SE,PT,India,M,India,50,"SQL, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-03-16,2025-05-06,2398,9.9,Neural Networks Co +AI00954,Research Scientist,162681,EUR,138279,EX,CT,Germany,L,Germany,50,"Python, Scala, Data Visualization",Associate,18,Telecommunications,2025-02-21,2025-03-09,2201,9.8,Advanced Robotics +AI00955,Deep Learning Engineer,125204,JPY,13772440,SE,CT,Japan,S,Vietnam,100,"Data Visualization, Kubernetes, Scala, NLP",Master,7,Retail,2024-04-30,2024-05-20,2284,5.9,Cloud AI Solutions +AI00956,Machine Learning Engineer,140001,EUR,119001,SE,FT,Netherlands,M,Luxembourg,50,"Python, TensorFlow, GCP, Computer Vision, Java",Bachelor,8,Manufacturing,2024-12-14,2025-02-06,1825,6.5,Autonomous Tech +AI00957,AI Software Engineer,162125,AUD,218869,SE,FT,Australia,L,Austria,100,"Computer Vision, Docker, TensorFlow",Bachelor,8,Consulting,2024-12-10,2025-02-07,565,5.4,Predictive Systems +AI00958,Deep Learning Engineer,128132,SGD,166572,SE,FL,Singapore,S,Japan,100,"Python, NLP, TensorFlow",PhD,7,Technology,2024-08-10,2024-09-24,1112,6.2,Cognitive Computing +AI00959,NLP Engineer,225554,USD,225554,SE,FT,Denmark,L,Latvia,50,"PyTorch, R, Docker",Bachelor,8,Technology,2024-09-12,2024-11-17,1301,9.3,Cloud AI Solutions +AI00960,ML Ops Engineer,130639,EUR,111043,SE,FT,Germany,M,Germany,0,"Python, Hadoop, PyTorch, Git, TensorFlow",PhD,7,Healthcare,2024-09-12,2024-11-12,1996,6.9,TechCorp Inc +AI00961,Data Analyst,66422,USD,66422,EN,FT,United States,S,United States,0,"Python, Hadoop, Kubernetes",Associate,0,Retail,2024-05-13,2024-07-18,1765,5.4,Autonomous Tech +AI00962,AI Architect,54625,CAD,68281,EN,CT,Canada,S,Ireland,0,"Scala, SQL, GCP, Computer Vision, Mathematics",Bachelor,0,Technology,2024-05-01,2024-07-08,1946,5.7,Cloud AI Solutions +AI00963,ML Ops Engineer,135145,USD,135145,MI,PT,Norway,M,Norway,50,"SQL, Docker, PyTorch, GCP, Kubernetes",Bachelor,3,Automotive,2025-04-27,2025-05-15,998,7.5,Smart Analytics +AI00964,ML Ops Engineer,61177,CAD,76471,EN,FL,Canada,S,Canada,100,"Spark, R, AWS, GCP, MLOps",Bachelor,0,Consulting,2025-04-04,2025-05-30,1465,6.8,Cognitive Computing +AI00965,AI Product Manager,74961,USD,74961,EX,FT,China,L,China,100,"Kubernetes, Git, Java, Azure, Tableau",PhD,16,Consulting,2024-07-17,2024-09-05,954,6.8,Smart Analytics +AI00966,NLP Engineer,47280,USD,47280,MI,PT,China,M,China,100,"Computer Vision, TensorFlow, Statistics, Python",PhD,2,Finance,2025-03-30,2025-06-05,985,9.4,Algorithmic Solutions +AI00967,Research Scientist,141577,USD,141577,EX,PT,Finland,S,Finland,50,"AWS, SQL, Python",Associate,13,Transportation,2024-09-16,2024-10-16,1955,6.1,TechCorp Inc +AI00968,NLP Engineer,130504,CHF,117454,EN,FT,Switzerland,L,Philippines,100,"Spark, MLOps, Tableau, Git",Bachelor,0,Media,2025-02-11,2025-02-26,691,8.4,Neural Networks Co +AI00969,Research Scientist,107421,USD,107421,MI,CT,Norway,S,Norway,50,"Git, Docker, Tableau, PyTorch",Bachelor,2,Consulting,2024-08-02,2024-09-23,1782,8.9,DataVision Ltd +AI00970,Data Analyst,93042,USD,93042,MI,PT,United States,S,United States,50,"Statistics, Linux, Git, Hadoop, Mathematics",Master,2,Finance,2024-10-14,2024-11-02,803,5.2,DataVision Ltd +AI00971,AI Consultant,168047,USD,168047,EX,FL,Ireland,L,Ireland,0,"Data Visualization, Linux, Docker, Python, GCP",Master,11,Government,2024-06-25,2024-08-04,1693,9.7,Predictive Systems +AI00972,AI Specialist,27281,USD,27281,EN,PT,China,S,Latvia,100,"Java, SQL, Tableau, GCP",PhD,1,Telecommunications,2025-01-04,2025-03-01,1739,7.1,Advanced Robotics +AI00973,Research Scientist,99145,USD,99145,MI,FL,United States,M,United States,100,"Kubernetes, Mathematics, Data Visualization, MLOps, Hadoop",Master,4,Media,2025-01-20,2025-03-09,954,9.2,Advanced Robotics +AI00974,Deep Learning Engineer,121002,USD,121002,SE,PT,Finland,S,Finland,100,"AWS, NLP, Kubernetes",Master,8,Consulting,2024-03-07,2024-05-12,1557,8.6,Cognitive Computing +AI00975,Data Scientist,259814,USD,259814,EX,PT,Norway,M,Vietnam,50,"PyTorch, R, TensorFlow, AWS, Statistics",Associate,12,Automotive,2024-04-15,2024-05-07,1416,5,DeepTech Ventures +AI00976,Computer Vision Engineer,209072,EUR,177711,EX,CT,France,L,France,100,"TensorFlow, PyTorch, SQL, AWS",Bachelor,15,Transportation,2024-03-23,2024-05-16,1826,7,Predictive Systems +AI00977,AI Software Engineer,50802,USD,50802,SE,CT,China,M,Russia,50,"MLOps, Computer Vision, Data Visualization, Java",PhD,5,Energy,2024-10-13,2024-11-20,501,6.5,Cognitive Computing +AI00978,NLP Engineer,112292,JPY,12352120,MI,PT,Japan,M,Japan,100,"Docker, Hadoop, Kubernetes, AWS",Bachelor,2,Gaming,2024-09-04,2024-10-30,875,8.7,TechCorp Inc +AI00979,Machine Learning Engineer,255076,USD,255076,EX,PT,Ireland,L,Finland,0,"Azure, Docker, Scala",PhD,15,Finance,2024-12-15,2025-02-21,1651,6.2,Digital Transformation LLC +AI00980,Head of AI,75393,EUR,64084,MI,FL,Netherlands,S,Finland,50,"Scala, Hadoop, Linux, GCP",Master,2,Consulting,2024-12-15,2025-01-30,1146,5.1,Quantum Computing Inc +AI00981,Head of AI,96519,USD,96519,EN,FL,United States,L,United States,100,"TensorFlow, Tableau, Git, Scala",Master,1,Finance,2024-07-24,2024-09-08,984,9.6,Autonomous Tech +AI00982,Deep Learning Engineer,135767,USD,135767,SE,FL,Sweden,L,Ukraine,50,"Scala, Azure, Git, Python, R",Associate,7,Gaming,2024-09-05,2024-10-13,736,8.7,DataVision Ltd +AI00983,AI Research Scientist,169082,USD,169082,EX,FT,Finland,L,Finland,50,"GCP, Hadoop, Python, Tableau, Mathematics",Master,17,Finance,2024-02-10,2024-03-22,914,6.9,Quantum Computing Inc +AI00984,AI Software Engineer,91630,EUR,77886,MI,FL,Germany,L,United States,50,"SQL, Linux, Data Visualization, NLP",Bachelor,3,Finance,2024-12-31,2025-03-04,2243,5.6,Machine Intelligence Group +AI00985,Research Scientist,172863,USD,172863,EX,CT,United States,M,United States,100,"SQL, Scala, Kubernetes",Bachelor,13,Transportation,2024-10-24,2024-11-08,2023,8.9,DataVision Ltd +AI00986,Head of AI,103897,USD,103897,MI,FL,Finland,L,Finland,100,"Scala, Java, Git, Azure, R",Associate,3,Retail,2025-04-06,2025-05-02,1242,8.9,Future Systems +AI00987,Computer Vision Engineer,93834,CAD,117293,MI,PT,Canada,L,Canada,100,"TensorFlow, PyTorch, AWS",Associate,2,Gaming,2024-09-01,2024-10-21,1303,5.8,Smart Analytics +AI00988,Autonomous Systems Engineer,53634,GBP,40226,EN,CT,United Kingdom,S,United Kingdom,0,"SQL, Hadoop, Kubernetes",PhD,0,Telecommunications,2025-04-16,2025-06-15,1608,7.3,Machine Intelligence Group +AI00989,AI Research Scientist,127594,USD,127594,SE,FT,Finland,L,Finland,0,"Python, TensorFlow, Hadoop, PyTorch",Bachelor,8,Automotive,2024-12-19,2025-02-24,926,6.4,Future Systems +AI00990,AI Product Manager,292915,CHF,263624,EX,FT,Switzerland,L,Thailand,100,"Data Visualization, Python, R, Azure",Bachelor,16,Media,2025-01-14,2025-02-25,2345,8.2,Future Systems +AI00991,Data Scientist,174020,USD,174020,EX,FT,Israel,S,Israel,100,"TensorFlow, PyTorch, MLOps, Computer Vision",Bachelor,18,Media,2025-01-25,2025-04-08,2090,6.6,Cloud AI Solutions +AI00992,ML Ops Engineer,88526,EUR,75247,MI,CT,Germany,S,Egypt,100,"Python, Git, MLOps, NLP, Spark",Master,4,Real Estate,2025-03-05,2025-05-17,1279,7.6,Cognitive Computing +AI00993,AI Software Engineer,74475,AUD,100541,EN,PT,Australia,M,Australia,0,"TensorFlow, Data Visualization, R",Associate,1,Transportation,2024-09-09,2024-10-10,734,9.8,Neural Networks Co +AI00994,Deep Learning Engineer,96427,USD,96427,EX,CT,China,S,China,100,"Computer Vision, Hadoop, Statistics, Deep Learning",PhD,18,Automotive,2024-10-10,2024-11-10,1393,7.3,Cognitive Computing +AI00995,ML Ops Engineer,225810,SGD,293553,EX,FT,Singapore,S,India,100,"Data Visualization, Spark, Kubernetes",PhD,19,Gaming,2025-02-19,2025-04-15,1937,8.2,Cloud AI Solutions +AI00996,AI Research Scientist,168512,EUR,143235,EX,CT,Netherlands,S,Hungary,0,"Java, Linux, MLOps, Tableau",Bachelor,10,Consulting,2024-10-15,2024-11-29,929,6.5,Cognitive Computing +AI00997,Head of AI,168159,GBP,126119,EX,CT,United Kingdom,M,United Kingdom,50,"Azure, PyTorch, GCP, Deep Learning, Kubernetes",PhD,14,Finance,2024-05-26,2024-06-27,1479,5.4,Cognitive Computing +AI00998,Research Scientist,59148,CAD,73935,EN,CT,Canada,L,Canada,0,"AWS, R, PyTorch",PhD,1,Government,2024-11-07,2024-12-12,1951,7.1,Predictive Systems +AI00999,Data Analyst,65802,GBP,49352,EN,PT,United Kingdom,L,Ghana,100,"Azure, Hadoop, Git",PhD,0,Telecommunications,2024-03-20,2024-05-18,1364,6.8,DataVision Ltd +AI01000,AI Architect,110206,EUR,93675,MI,CT,France,L,France,100,"Git, R, Python, Azure, Tableau",PhD,4,Finance,2024-11-29,2025-01-07,903,6.5,Autonomous Tech +AI01001,Data Analyst,149976,EUR,127480,SE,FL,France,L,France,100,"GCP, Git, Data Visualization, PyTorch",Bachelor,9,Energy,2024-05-31,2024-08-07,1685,7.2,TechCorp Inc +AI01002,Principal Data Scientist,179731,AUD,242637,EX,CT,Australia,M,Australia,50,"Python, GCP, Kubernetes, Deep Learning",Bachelor,18,Education,2024-03-29,2024-05-12,2328,7.2,Algorithmic Solutions +AI01003,Research Scientist,148216,USD,148216,EX,FL,Israel,S,Israel,100,"Kubernetes, Python, Scala, Computer Vision",PhD,10,Telecommunications,2024-12-13,2025-02-14,1572,6.3,Machine Intelligence Group +AI01004,AI Research Scientist,69697,CAD,87121,MI,FL,Canada,S,Canada,0,"GCP, AWS, Hadoop, Statistics, Docker",PhD,4,Automotive,2025-01-05,2025-03-09,1809,6.1,Future Systems +AI01005,Autonomous Systems Engineer,193479,CHF,174131,SE,CT,Switzerland,S,Switzerland,50,"Computer Vision, Linux, Tableau, NLP",Associate,6,Manufacturing,2025-02-01,2025-04-12,1620,9,Predictive Systems +AI01006,Data Engineer,27327,USD,27327,EN,CT,India,M,India,100,"Hadoop, Python, SQL, Azure, Kubernetes",PhD,1,Gaming,2024-03-10,2024-04-08,858,8.8,AI Innovations +AI01007,Deep Learning Engineer,175817,USD,175817,SE,PT,Denmark,L,Denmark,50,"SQL, Python, GCP, Computer Vision",PhD,9,Automotive,2024-12-14,2025-02-05,2179,10,Future Systems +AI01008,AI Software Engineer,79605,EUR,67664,MI,FT,France,S,France,50,"Mathematics, SQL, Computer Vision",PhD,2,Technology,2024-05-03,2024-07-10,1656,9.9,Smart Analytics +AI01009,AI Specialist,136610,USD,136610,SE,FL,Denmark,M,Denmark,100,"NLP, Azure, Data Visualization, Kubernetes",Bachelor,6,Education,2024-10-29,2025-01-06,1763,9.8,TechCorp Inc +AI01010,Data Scientist,54165,EUR,46040,EN,CT,France,S,France,100,"PyTorch, Git, Mathematics, SQL",PhD,1,Healthcare,2024-12-17,2025-01-12,1474,7,DataVision Ltd +AI01011,AI Consultant,82548,USD,82548,EN,FL,Denmark,S,Malaysia,50,"R, Tableau, Kubernetes",Associate,1,Real Estate,2025-02-20,2025-03-18,1171,6.9,AI Innovations +AI01012,Research Scientist,149033,USD,149033,EX,FL,South Korea,M,South Korea,100,"SQL, R, Docker, Data Visualization",Bachelor,17,Technology,2024-06-15,2024-08-13,1619,9.1,Machine Intelligence Group +AI01013,Machine Learning Engineer,26672,USD,26672,MI,PT,India,M,India,50,"AWS, PyTorch, MLOps, Deep Learning",PhD,2,Real Estate,2024-11-21,2025-01-10,1601,9.1,Algorithmic Solutions +AI01014,AI Consultant,103610,USD,103610,MI,FT,Sweden,L,Sweden,50,"Mathematics, Python, TensorFlow, Scala",Associate,3,Government,2024-07-02,2024-08-27,859,6.4,Predictive Systems +AI01015,Principal Data Scientist,59901,GBP,44926,EN,CT,United Kingdom,M,Colombia,100,"R, Hadoop, Python, Computer Vision",Bachelor,1,Finance,2024-03-20,2024-05-27,2189,8.2,Cognitive Computing +AI01016,Machine Learning Engineer,84403,USD,84403,MI,FT,Finland,M,India,0,"Tableau, Spark, Python",PhD,4,Finance,2024-09-10,2024-11-05,2085,5.6,Neural Networks Co +AI01017,AI Product Manager,235236,EUR,199951,EX,FL,France,M,South Africa,50,"GCP, Python, Data Visualization, MLOps, TensorFlow",Associate,10,Healthcare,2024-09-01,2024-10-11,2164,7.5,Machine Intelligence Group +AI01018,AI Research Scientist,140841,USD,140841,SE,FL,United States,S,United States,100,"Python, TensorFlow, Kubernetes",PhD,9,Finance,2024-10-17,2024-11-29,1005,5.2,Future Systems +AI01019,Deep Learning Engineer,64188,EUR,54560,EN,PT,Austria,M,Austria,0,"Kubernetes, Scala, Mathematics, SQL",Bachelor,1,Media,2025-01-16,2025-02-01,2217,5.6,Digital Transformation LLC +AI01020,Principal Data Scientist,140677,CHF,126609,SE,FL,Switzerland,S,Switzerland,100,"Python, TensorFlow, GCP, PyTorch",PhD,6,Retail,2024-05-22,2024-06-14,1249,5.2,Machine Intelligence Group +AI01021,Research Scientist,275555,USD,275555,EX,FT,Ireland,L,Egypt,0,"R, Linux, Scala",Associate,15,Retail,2024-12-16,2025-01-14,801,6.9,TechCorp Inc +AI01022,AI Specialist,174133,CHF,156720,SE,FT,Switzerland,M,Switzerland,0,"R, Deep Learning, TensorFlow",Associate,8,Real Estate,2025-01-23,2025-02-18,1540,9.6,Smart Analytics +AI01023,Machine Learning Engineer,49918,USD,49918,EN,CT,South Korea,M,South Korea,0,"Git, Python, SQL",PhD,0,Manufacturing,2025-04-17,2025-05-07,1226,8.1,AI Innovations +AI01024,Computer Vision Engineer,211602,USD,211602,EX,FL,Norway,L,Turkey,50,"AWS, Hadoop, NLP, Computer Vision, Statistics",Master,16,Real Estate,2025-03-27,2025-04-30,1244,7.3,Neural Networks Co +AI01025,AI Software Engineer,192792,USD,192792,EX,FT,Israel,L,Ireland,50,"Scala, NLP, SQL, Linux, Docker",PhD,15,Technology,2024-06-12,2024-08-11,2314,6.2,Digital Transformation LLC +AI01026,AI Specialist,70846,EUR,60219,MI,CT,Austria,S,Turkey,100,"TensorFlow, Java, R",Associate,4,Gaming,2024-02-11,2024-04-07,1268,9.4,Digital Transformation LLC +AI01027,AI Architect,93783,USD,93783,EN,PT,United States,M,United States,100,"MLOps, Java, Azure, Mathematics, PyTorch",Bachelor,1,Finance,2024-05-19,2024-06-10,1828,10,Neural Networks Co +AI01028,AI Architect,41072,USD,41072,MI,FT,China,S,China,0,"R, Docker, MLOps",Associate,3,Telecommunications,2024-04-11,2024-05-24,2158,6.6,Advanced Robotics +AI01029,AI Architect,102805,CAD,128506,MI,PT,Canada,M,Switzerland,100,"Azure, TensorFlow, Data Visualization, NLP",Master,3,Education,2024-12-16,2025-02-02,1000,9.9,Autonomous Tech +AI01030,AI Product Manager,113537,USD,113537,MI,FT,Ireland,L,Ireland,0,"GCP, Scala, Hadoop",PhD,4,Media,2024-01-20,2024-03-21,1063,8.1,DeepTech Ventures +AI01031,Research Scientist,73590,USD,73590,EN,FL,Denmark,M,Denmark,100,"Python, Git, Tableau, R",Master,1,Retail,2024-11-01,2024-12-27,1490,9.2,Digital Transformation LLC +AI01032,Computer Vision Engineer,96582,USD,96582,EN,CT,Denmark,L,Denmark,100,"Java, Computer Vision, GCP",PhD,0,Real Estate,2024-08-27,2024-09-29,649,9.1,DataVision Ltd +AI01033,AI Research Scientist,62705,USD,62705,EN,PT,Israel,M,India,0,"Java, GCP, Linux, Spark, Python",Bachelor,0,Gaming,2024-10-19,2024-12-08,723,5.1,Smart Analytics +AI01034,AI Product Manager,77955,GBP,58466,EN,FT,United Kingdom,M,United Kingdom,50,"Data Visualization, Computer Vision, Scala",Master,0,Education,2024-06-07,2024-07-04,2444,7,Autonomous Tech +AI01035,Data Analyst,129874,AUD,175330,EX,FT,Australia,S,Australia,0,"Linux, Statistics, Computer Vision",PhD,15,Education,2024-11-16,2024-12-05,2443,7.5,Quantum Computing Inc +AI01036,AI Architect,106907,GBP,80180,MI,CT,United Kingdom,L,United Kingdom,100,"NLP, Java, SQL, Spark, Mathematics",Associate,4,Gaming,2024-12-08,2025-02-16,1589,7.3,Algorithmic Solutions +AI01037,AI Consultant,110152,USD,110152,MI,CT,United States,L,United States,0,"Tableau, Azure, R, NLP",Bachelor,4,Gaming,2024-02-24,2024-03-27,976,8.9,Cognitive Computing +AI01038,AI Research Scientist,49922,USD,49922,MI,FT,China,L,China,50,"Azure, Spark, Scala, SQL, Deep Learning",Bachelor,4,Government,2024-07-26,2024-09-14,1580,8.8,DataVision Ltd +AI01039,AI Software Engineer,84890,USD,84890,EN,CT,Ireland,L,Ireland,100,"GCP, Hadoop, Azure, Scala",PhD,0,Gaming,2024-05-28,2024-07-01,2159,9.2,Cloud AI Solutions +AI01040,Data Scientist,73564,EUR,62529,MI,PT,France,M,Singapore,50,"Scala, Tableau, Docker, SQL, Mathematics",Associate,4,Consulting,2024-04-05,2024-05-26,1702,7.5,Cognitive Computing +AI01041,Autonomous Systems Engineer,196201,USD,196201,SE,PT,United States,L,Philippines,0,"Git, Python, Java",Master,5,Consulting,2025-02-15,2025-04-07,1756,8.8,Cloud AI Solutions +AI01042,NLP Engineer,164425,USD,164425,SE,CT,Finland,L,Italy,0,"GCP, Docker, R, Git",Master,9,Education,2024-07-17,2024-09-02,1881,5.6,Autonomous Tech +AI01043,ML Ops Engineer,158518,JPY,17436980,SE,FT,Japan,L,United Kingdom,0,"GCP, NLP, Deep Learning, Docker, R",Bachelor,6,Healthcare,2025-02-06,2025-02-25,2218,7.2,Quantum Computing Inc +AI01044,Autonomous Systems Engineer,137246,USD,137246,MI,PT,Norway,M,Norway,100,"TensorFlow, Kubernetes, AWS, Linux, Docker",Bachelor,4,Consulting,2024-04-12,2024-05-14,609,8.4,Machine Intelligence Group +AI01045,NLP Engineer,222330,EUR,188981,EX,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Scala",Associate,15,Automotive,2025-04-08,2025-05-12,1335,9.6,Autonomous Tech +AI01046,ML Ops Engineer,73721,USD,73721,MI,FL,Israel,S,Sweden,100,"Java, Tableau, MLOps",Master,2,Real Estate,2025-03-06,2025-04-14,1797,5.2,Predictive Systems +AI01047,AI Software Engineer,125284,CHF,112756,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, SQL, Hadoop, Spark, Deep Learning",Associate,3,Healthcare,2024-02-01,2024-02-15,553,9.4,DeepTech Ventures +AI01048,AI Software Engineer,266424,USD,266424,EX,PT,Ireland,L,Ireland,50,"Azure, Scala, R, Tableau",PhD,17,Education,2024-04-19,2024-06-26,515,5.2,DataVision Ltd +AI01049,AI Consultant,158788,EUR,134970,EX,FL,France,S,France,50,"Linux, Mathematics, SQL",Associate,14,Automotive,2025-03-07,2025-04-12,559,7,Advanced Robotics +AI01050,Autonomous Systems Engineer,99628,SGD,129516,MI,FL,Singapore,S,Singapore,100,"PyTorch, AWS, Azure, Kubernetes, MLOps",Associate,3,Government,2024-07-22,2024-08-27,799,5.1,Smart Analytics +AI01051,AI Architect,52727,GBP,39545,EN,FT,United Kingdom,S,Austria,100,"Java, SQL, Linux",Bachelor,1,Energy,2025-03-17,2025-05-24,1166,9,Neural Networks Co +AI01052,AI Specialist,38473,USD,38473,MI,PT,India,L,India,100,"Tableau, Spark, Scala, NLP",Master,4,Manufacturing,2024-10-05,2024-11-03,2320,7.9,Smart Analytics +AI01053,Machine Learning Researcher,64133,USD,64133,EN,PT,United States,M,Sweden,0,"Azure, AWS, TensorFlow, Hadoop",Master,1,Real Estate,2024-09-24,2024-12-03,955,7.8,DataVision Ltd +AI01054,Data Analyst,47110,CAD,58888,EN,CT,Canada,S,Canada,50,"Java, Linux, Kubernetes, Azure",Bachelor,1,Media,2024-11-26,2025-01-06,844,8.4,Quantum Computing Inc +AI01055,Machine Learning Engineer,71783,EUR,61016,EN,CT,France,L,France,50,"Mathematics, SQL, Computer Vision",Associate,1,Media,2024-07-31,2024-10-07,524,8.8,Cognitive Computing +AI01056,AI Software Engineer,83829,USD,83829,EN,FL,Norway,S,India,50,"PyTorch, TensorFlow, Statistics, Hadoop, Python",Bachelor,0,Finance,2024-06-18,2024-08-29,1929,8.3,TechCorp Inc +AI01057,Robotics Engineer,91511,USD,91511,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, Mathematics, Spark",PhD,4,Technology,2024-11-17,2024-12-09,1221,5.7,Quantum Computing Inc +AI01058,ML Ops Engineer,198095,EUR,168381,EX,PT,France,S,France,50,"Git, R, Python, Scala",PhD,14,Education,2024-07-01,2024-08-27,1815,9.5,Machine Intelligence Group +AI01059,AI Product Manager,119407,USD,119407,SE,PT,Norway,S,Norway,0,"Git, Java, Tableau, Linux, Deep Learning",PhD,7,Manufacturing,2025-02-15,2025-03-24,2040,6.2,Algorithmic Solutions +AI01060,Data Engineer,87493,USD,87493,MI,FL,Denmark,S,Denmark,100,"MLOps, Hadoop, Linux, Scala",PhD,4,Energy,2024-12-04,2025-01-21,2032,6.5,Advanced Robotics +AI01061,Data Engineer,121335,USD,121335,SE,PT,Norway,S,Norway,50,"Python, Spark, Mathematics, SQL",Associate,7,Automotive,2024-12-06,2025-01-11,1573,7.9,DeepTech Ventures +AI01062,AI Architect,289174,SGD,375926,EX,FL,Singapore,L,Singapore,0,"Hadoop, SQL, Data Visualization, Deep Learning",Master,13,Retail,2025-02-04,2025-03-26,2451,8.5,Cognitive Computing +AI01063,Deep Learning Engineer,154280,USD,154280,SE,CT,Finland,L,Finland,0,"Data Visualization, Python, AWS",Bachelor,5,Education,2024-01-28,2024-03-21,547,9.6,Autonomous Tech +AI01064,Head of AI,62297,CAD,77871,EN,PT,Canada,S,Canada,100,"Mathematics, Hadoop, MLOps, Linux",Associate,0,Healthcare,2024-09-26,2024-11-02,2467,7.4,AI Innovations +AI01065,AI Software Engineer,114311,CAD,142889,MI,FL,Canada,L,Canada,50,"Mathematics, Computer Vision, Python",PhD,2,Telecommunications,2024-04-10,2024-04-27,1979,8.8,TechCorp Inc +AI01066,AI Research Scientist,163458,CAD,204323,SE,CT,Canada,L,Canada,50,"Azure, Python, Deep Learning, Spark",Master,7,Real Estate,2024-07-30,2024-10-05,1096,7.4,Cloud AI Solutions +AI01067,AI Software Engineer,107211,EUR,91129,MI,CT,France,L,Singapore,0,"Statistics, R, Computer Vision",Master,4,Government,2024-10-18,2024-11-13,678,8.4,Machine Intelligence Group +AI01068,Deep Learning Engineer,136382,USD,136382,MI,FL,Denmark,M,Spain,50,"AWS, Mathematics, NLP",PhD,2,Transportation,2024-10-03,2024-12-06,1219,6.1,AI Innovations +AI01069,Head of AI,249477,CHF,224529,EX,CT,Switzerland,S,Switzerland,50,"NLP, Hadoop, Python, Data Visualization, R",Associate,11,Government,2024-01-31,2024-03-01,1495,7.3,Predictive Systems +AI01070,Data Analyst,177617,EUR,150974,EX,PT,France,M,France,0,"AWS, TensorFlow, Data Visualization, Deep Learning",Master,11,Gaming,2024-12-13,2025-01-06,1493,8,Predictive Systems +AI01071,Computer Vision Engineer,66870,EUR,56840,EN,FL,Austria,M,Austria,0,"Azure, Deep Learning, Python, Git, Docker",Associate,1,Technology,2024-06-09,2024-07-08,2209,9.8,TechCorp Inc +AI01072,AI Software Engineer,79882,EUR,67900,MI,PT,Netherlands,M,Netherlands,0,"Spark, Hadoop, Git, Python, R",Associate,3,Education,2024-10-14,2024-11-16,1560,6.2,AI Innovations +AI01073,AI Research Scientist,114997,EUR,97747,MI,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Python",Bachelor,4,Telecommunications,2024-03-10,2024-03-25,1176,8.2,Predictive Systems +AI01074,Principal Data Scientist,67556,CHF,60800,EN,FT,Switzerland,S,Switzerland,100,"MLOps, Python, Hadoop, Kubernetes, Deep Learning",Master,1,Finance,2024-10-19,2024-12-07,885,6.6,Algorithmic Solutions +AI01075,Deep Learning Engineer,50726,USD,50726,SE,FT,India,M,Australia,0,"Java, AWS, R, Computer Vision, Git",Master,9,Telecommunications,2024-05-02,2024-05-18,556,8.3,Neural Networks Co +AI01076,Data Scientist,45956,EUR,39063,EN,FT,France,S,Italy,0,"Data Visualization, MLOps, AWS",PhD,1,Consulting,2024-11-12,2024-12-14,2065,6.6,Smart Analytics +AI01077,Data Engineer,29934,USD,29934,MI,FT,India,S,India,50,"SQL, Kubernetes, MLOps, Scala, Linux",Bachelor,2,Technology,2024-07-10,2024-08-01,2366,7,DataVision Ltd +AI01078,Deep Learning Engineer,89070,USD,89070,EX,PT,India,M,United Kingdom,0,"Python, Scala, Linux, GCP, Deep Learning",Associate,14,Technology,2025-02-23,2025-04-20,1673,8.1,Autonomous Tech +AI01079,AI Consultant,123195,EUR,104716,SE,FT,Germany,L,Chile,100,"GCP, SQL, Tableau, Spark, Mathematics",Bachelor,6,Finance,2024-12-16,2025-01-21,1581,8.6,Digital Transformation LLC +AI01080,Research Scientist,83392,USD,83392,MI,PT,South Korea,L,Singapore,100,"R, PyTorch, Tableau, Deep Learning, GCP",Associate,3,Automotive,2024-03-27,2024-06-05,1328,7.3,Digital Transformation LLC +AI01081,Principal Data Scientist,241040,USD,241040,EX,FT,Norway,S,Norway,100,"Azure, Linux, Data Visualization",PhD,18,Retail,2024-04-15,2024-06-08,2485,6.9,Cloud AI Solutions +AI01082,AI Consultant,226924,GBP,170193,EX,FL,United Kingdom,S,United Kingdom,100,"AWS, Docker, Kubernetes, Deep Learning, Tableau",Bachelor,17,Government,2024-08-30,2024-10-29,860,8.1,Neural Networks Co +AI01083,Data Analyst,28173,USD,28173,EN,FL,India,M,Singapore,100,"R, SQL, AWS",PhD,1,Gaming,2024-03-17,2024-04-23,2356,8.7,Predictive Systems +AI01084,Autonomous Systems Engineer,96863,EUR,82334,MI,PT,France,M,France,0,"Python, TensorFlow, Tableau",PhD,3,Government,2024-08-18,2024-10-19,1317,7.6,Future Systems +AI01085,ML Ops Engineer,126853,USD,126853,EX,FT,China,L,China,100,"AWS, Spark, NLP, Azure",PhD,13,Real Estate,2025-04-18,2025-05-12,2007,7.3,Algorithmic Solutions +AI01086,Principal Data Scientist,143421,USD,143421,SE,CT,United States,M,United States,100,"Azure, MLOps, Hadoop",Bachelor,6,Telecommunications,2024-11-07,2024-12-28,1193,9.5,DeepTech Ventures +AI01087,AI Consultant,20785,USD,20785,EN,PT,India,S,India,0,"Kubernetes, Spark, Azure, PyTorch",Master,1,Manufacturing,2024-12-24,2025-01-22,642,6.2,Cognitive Computing +AI01088,AI Research Scientist,67394,EUR,57285,EN,FT,Austria,M,Austria,100,"Tableau, Java, Python, Azure, R",PhD,0,Education,2024-11-07,2024-12-23,989,9.1,Algorithmic Solutions +AI01089,Data Engineer,93436,AUD,126139,MI,CT,Australia,L,Hungary,50,"Tableau, PyTorch, Scala, Azure",Master,3,Gaming,2024-01-21,2024-03-09,1503,6.1,Digital Transformation LLC +AI01090,ML Ops Engineer,95063,EUR,80804,MI,PT,France,M,France,100,"Kubernetes, Spark, Scala",Associate,2,Government,2024-09-08,2024-10-22,2378,9.6,Machine Intelligence Group +AI01091,Computer Vision Engineer,167478,USD,167478,EX,PT,United States,M,United States,100,"Statistics, Git, Docker",Bachelor,18,Healthcare,2024-03-16,2024-04-13,626,7.2,Machine Intelligence Group +AI01092,Autonomous Systems Engineer,139198,CHF,125278,SE,CT,Switzerland,S,Switzerland,100,"Java, Linux, Python, Hadoop, Azure",Master,5,Automotive,2024-02-27,2024-04-05,2301,9.1,Digital Transformation LLC +AI01093,Computer Vision Engineer,215699,USD,215699,EX,PT,Ireland,L,Ireland,0,"Computer Vision, Java, MLOps, AWS",Master,19,Automotive,2024-06-03,2024-06-30,2486,8.5,Advanced Robotics +AI01094,Research Scientist,138827,AUD,187416,EX,CT,Australia,S,Australia,100,"Docker, Data Visualization, Tableau, TensorFlow, AWS",Master,15,Manufacturing,2025-04-28,2025-05-28,1069,9.4,Machine Intelligence Group +AI01095,AI Consultant,79327,JPY,8725970,EN,PT,Japan,M,Japan,100,"AWS, TensorFlow, SQL, Computer Vision",Master,0,Real Estate,2025-02-26,2025-04-20,1008,7.3,Machine Intelligence Group +AI01096,AI Research Scientist,70002,USD,70002,EN,FT,Finland,L,Finland,50,"Mathematics, SQL, Data Visualization, MLOps",Master,1,Gaming,2024-12-31,2025-02-10,2355,9,Cognitive Computing +AI01097,AI Research Scientist,85342,EUR,72541,EN,FL,Netherlands,L,Netherlands,50,"Java, SQL, Spark",Associate,1,Energy,2024-11-25,2025-01-20,1783,6.7,TechCorp Inc +AI01098,AI Architect,116683,SGD,151688,SE,FT,Singapore,M,Singapore,100,"AWS, PyTorch, Python, Spark",Master,5,Automotive,2024-03-27,2024-05-12,2269,5.3,Cloud AI Solutions +AI01099,Head of AI,127338,EUR,108237,EX,CT,France,S,Estonia,50,"Scala, Spark, TensorFlow",Associate,19,Gaming,2024-03-09,2024-04-29,2085,5.1,Cloud AI Solutions +AI01100,Research Scientist,80026,USD,80026,SE,FT,South Korea,S,South Korea,100,"R, Java, Linux, GCP",Master,9,Healthcare,2024-04-24,2024-06-06,1833,6.7,Neural Networks Co +AI01101,Deep Learning Engineer,119475,CHF,107528,EN,PT,Switzerland,L,Switzerland,0,"Spark, Azure, Python",PhD,1,Gaming,2024-05-03,2024-07-14,2219,5.9,Predictive Systems +AI01102,ML Ops Engineer,254552,AUD,343645,EX,CT,Australia,L,Egypt,0,"Deep Learning, Python, Java, GCP, TensorFlow",Associate,12,Transportation,2024-04-23,2024-05-13,1757,5.6,Cognitive Computing +AI01103,Head of AI,118245,USD,118245,SE,PT,Ireland,M,Canada,0,"Mathematics, AWS, Data Visualization, Computer Vision",Master,6,Consulting,2024-08-16,2024-10-08,1898,9.3,Neural Networks Co +AI01104,AI Software Engineer,117254,EUR,99666,SE,FL,Austria,M,Austria,0,"SQL, Data Visualization, R, Spark, GCP",PhD,7,Government,2024-12-26,2025-02-18,2230,9.3,Autonomous Tech +AI01105,Data Scientist,256695,USD,256695,EX,FL,Ireland,L,Ireland,50,"MLOps, Scala, AWS",Bachelor,14,Automotive,2024-06-11,2024-07-26,617,9.1,Autonomous Tech +AI01106,Computer Vision Engineer,188203,USD,188203,EX,FL,Finland,M,Finland,0,"Hadoop, R, Python, Git",Bachelor,15,Real Estate,2024-08-12,2024-09-07,1201,9.4,Advanced Robotics +AI01107,Computer Vision Engineer,191049,USD,191049,EX,FL,United States,S,United States,0,"AWS, Linux, Azure",Bachelor,17,Education,2024-06-02,2024-07-06,887,7.7,AI Innovations +AI01108,AI Product Manager,75973,EUR,64577,EN,FT,Germany,M,Thailand,50,"SQL, NLP, Tableau",Master,1,Automotive,2024-08-16,2024-09-27,646,7.7,DataVision Ltd +AI01109,Machine Learning Researcher,205143,SGD,266686,EX,FT,Singapore,M,Singapore,100,"Scala, Docker, MLOps",PhD,14,Transportation,2024-08-04,2024-08-28,2458,9,Machine Intelligence Group +AI01110,AI Specialist,92600,USD,92600,SE,FT,Ireland,S,Ireland,0,"SQL, Java, Computer Vision",PhD,8,Healthcare,2024-03-03,2024-04-03,1281,6.1,Predictive Systems +AI01111,Research Scientist,307696,USD,307696,EX,CT,Denmark,L,Czech Republic,100,"Data Visualization, TensorFlow, Python, MLOps, Deep Learning",Bachelor,12,Government,2024-09-25,2024-10-17,526,7.3,Advanced Robotics +AI01112,Machine Learning Engineer,289667,USD,289667,EX,FL,United States,L,United States,0,"Mathematics, Scala, PyTorch",Master,15,Automotive,2024-10-26,2024-12-20,2369,6.6,Cognitive Computing +AI01113,AI Product Manager,104108,USD,104108,SE,FT,Sweden,S,Sweden,50,"Spark, Java, R, TensorFlow, SQL",PhD,9,Automotive,2025-01-02,2025-02-26,1083,6.1,Predictive Systems +AI01114,NLP Engineer,85459,USD,85459,EN,FT,Denmark,M,Denmark,50,"Statistics, Spark, PyTorch",Bachelor,1,Retail,2024-07-18,2024-08-13,2416,6.6,DataVision Ltd +AI01115,Computer Vision Engineer,48088,EUR,40875,EN,FT,France,M,France,0,"NLP, Scala, Java",Bachelor,0,Finance,2024-04-08,2024-05-19,1362,9.7,Smart Analytics +AI01116,AI Architect,103764,USD,103764,SE,PT,Sweden,S,Sweden,50,"SQL, Docker, AWS",Associate,9,Manufacturing,2024-11-15,2025-01-01,1227,9.4,Future Systems +AI01117,Deep Learning Engineer,135128,SGD,175666,SE,PT,Singapore,M,Singapore,100,"NLP, R, Azure, SQL, Java",Master,9,Government,2024-05-15,2024-07-11,693,6.1,Machine Intelligence Group +AI01118,NLP Engineer,78044,JPY,8584840,MI,PT,Japan,S,Japan,0,"TensorFlow, Azure, Python, Tableau",Bachelor,4,Gaming,2024-11-08,2024-12-12,1943,7.9,Autonomous Tech +AI01119,Research Scientist,77226,SGD,100394,MI,FT,Singapore,M,Singapore,0,"Scala, Spark, Computer Vision, Python, Tableau",PhD,3,Telecommunications,2024-07-16,2024-08-29,1506,6.6,Predictive Systems +AI01120,Machine Learning Engineer,149651,CAD,187064,EX,CT,Canada,M,Canada,100,"TensorFlow, Python, Kubernetes, MLOps, AWS",Associate,11,Gaming,2024-09-18,2024-11-15,943,7.9,DeepTech Ventures +AI01121,Machine Learning Engineer,183833,EUR,156258,EX,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, R",Associate,10,Healthcare,2025-03-24,2025-05-29,2012,9.6,Future Systems +AI01122,Computer Vision Engineer,104425,EUR,88761,MI,PT,Germany,L,China,0,"MLOps, Java, Python, Kubernetes, Computer Vision",Bachelor,4,Transportation,2024-07-30,2024-08-24,532,5.7,Quantum Computing Inc +AI01123,AI Consultant,163323,USD,163323,EX,CT,Sweden,S,Sweden,0,"NLP, Data Visualization, AWS, Python, TensorFlow",Bachelor,10,Gaming,2024-10-14,2024-11-11,1137,6.6,Autonomous Tech +AI01124,Data Engineer,136850,EUR,116323,EX,FT,Germany,S,Norway,0,"Tableau, Python, TensorFlow, Computer Vision, GCP",PhD,11,Healthcare,2024-08-14,2024-09-02,831,7.2,Cloud AI Solutions +AI01125,AI Consultant,133658,GBP,100244,SE,FL,United Kingdom,S,United Kingdom,100,"Kubernetes, SQL, GCP",PhD,8,Manufacturing,2024-05-17,2024-06-24,1514,6,Smart Analytics +AI01126,AI Specialist,168161,JPY,18497710,SE,FT,Japan,L,Japan,0,"Python, GCP, TensorFlow, Computer Vision, Hadoop",PhD,6,Government,2025-02-06,2025-03-12,2290,5.8,Cloud AI Solutions +AI01127,AI Research Scientist,87945,JPY,9673950,MI,FT,Japan,M,Japan,0,"Computer Vision, PyTorch, Data Visualization",Associate,2,Consulting,2025-04-30,2025-06-13,1525,6.3,Autonomous Tech +AI01128,Data Analyst,150603,USD,150603,SE,FL,Norway,M,Norway,50,"GCP, R, Computer Vision, Linux, SQL",Master,9,Healthcare,2024-05-14,2024-07-09,2451,9.6,Cloud AI Solutions +AI01129,Research Scientist,41667,USD,41667,MI,CT,China,M,China,100,"Data Visualization, Kubernetes, MLOps, TensorFlow",Master,3,Finance,2024-06-03,2024-08-12,1963,9,Cognitive Computing +AI01130,Machine Learning Researcher,270857,USD,270857,EX,FT,Denmark,L,Denmark,0,"Spark, PyTorch, Hadoop",Associate,14,Healthcare,2025-01-09,2025-02-17,1836,7.5,Machine Intelligence Group +AI01131,AI Product Manager,70021,JPY,7702310,EN,FL,Japan,M,South Korea,100,"SQL, Git, Python",Master,1,Automotive,2024-09-30,2024-11-08,2044,9,Machine Intelligence Group +AI01132,Deep Learning Engineer,180120,USD,180120,EX,FL,Finland,S,Finland,50,"PyTorch, R, Java, SQL",Bachelor,19,Gaming,2025-03-21,2025-04-27,2134,9.4,TechCorp Inc +AI01133,Data Analyst,109592,CAD,136990,SE,FT,Canada,S,Kenya,50,"GCP, Spark, AWS, Python, Mathematics",Master,8,Gaming,2024-04-30,2024-06-13,1754,8.9,TechCorp Inc +AI01134,NLP Engineer,248395,EUR,211136,EX,FL,Germany,M,Germany,100,"Kubernetes, Data Visualization, Java, Scala, MLOps",Master,11,Energy,2024-06-19,2024-08-31,2176,7.6,Digital Transformation LLC +AI01135,ML Ops Engineer,166428,EUR,141464,EX,FL,France,S,Luxembourg,50,"Linux, AWS, Deep Learning, Computer Vision",Bachelor,12,Real Estate,2024-10-28,2024-12-07,2272,9.4,DataVision Ltd +AI01136,AI Product Manager,64110,SGD,83343,EN,FL,Singapore,S,Ukraine,50,"Kubernetes, Statistics, Scala, Deep Learning",Master,1,Manufacturing,2024-02-23,2024-03-17,1013,7.7,Autonomous Tech +AI01137,NLP Engineer,89254,USD,89254,MI,CT,Israel,M,Israel,50,"Azure, PyTorch, Data Visualization, Computer Vision, Mathematics",Bachelor,2,Real Estate,2025-02-03,2025-03-03,736,5.6,Neural Networks Co +AI01138,ML Ops Engineer,89632,CAD,112040,SE,FT,Canada,S,Brazil,50,"PyTorch, Git, Python",Master,7,Technology,2024-09-11,2024-10-26,1963,8.9,Digital Transformation LLC +AI01139,Research Scientist,94147,JPY,10356170,MI,FL,Japan,S,Austria,100,"NLP, Python, GCP, Mathematics",Associate,4,Telecommunications,2024-07-04,2024-08-12,2179,9.7,DeepTech Ventures +AI01140,Data Scientist,95536,USD,95536,EX,PT,China,M,Poland,50,"PyTorch, TensorFlow, GCP, NLP",Bachelor,12,Consulting,2024-07-13,2024-08-13,2028,5.3,DataVision Ltd +AI01141,AI Specialist,128104,USD,128104,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, Git, Data Visualization",Master,6,Manufacturing,2024-03-16,2024-04-12,1759,6.7,DeepTech Ventures +AI01142,Data Analyst,224736,USD,224736,EX,FL,Denmark,S,South Africa,100,"Python, TensorFlow, SQL, Kubernetes, AWS",Associate,15,Manufacturing,2024-01-18,2024-02-12,617,6.5,Machine Intelligence Group +AI01143,Principal Data Scientist,132221,JPY,14544310,MI,FT,Japan,L,Japan,0,"Python, Git, GCP, NLP, Hadoop",PhD,4,Consulting,2024-09-26,2024-10-22,1834,9.4,Cloud AI Solutions +AI01144,AI Consultant,107463,EUR,91344,SE,FT,Austria,M,Ireland,0,"Data Visualization, PyTorch, Git, Computer Vision",PhD,7,Media,2025-03-17,2025-04-19,1360,6.3,DataVision Ltd +AI01145,Machine Learning Researcher,200093,CAD,250116,EX,FL,Canada,M,India,50,"Statistics, R, Tableau, Hadoop",Bachelor,18,Real Estate,2024-09-22,2024-11-06,1322,8.4,Advanced Robotics +AI01146,Machine Learning Engineer,168952,AUD,228085,SE,PT,Australia,L,Australia,100,"SQL, R, Hadoop, Docker",Master,7,Finance,2024-02-11,2024-02-25,1398,5.9,Digital Transformation LLC +AI01147,Deep Learning Engineer,223789,JPY,24616790,EX,FT,Japan,S,Japan,100,"Hadoop, SQL, Linux",Bachelor,10,Technology,2024-05-22,2024-06-16,1821,5.2,Machine Intelligence Group +AI01148,Data Engineer,121814,USD,121814,SE,CT,South Korea,L,South Korea,0,"Spark, Linux, Hadoop",PhD,7,Telecommunications,2024-04-11,2024-05-26,808,9.6,Predictive Systems +AI01149,NLP Engineer,188710,USD,188710,EX,PT,Finland,S,Finland,0,"SQL, Hadoop, Tableau",Associate,19,Transportation,2024-05-31,2024-07-28,2221,5.7,Smart Analytics +AI01150,AI Consultant,73645,AUD,99421,MI,PT,Australia,S,Australia,50,"Python, Spark, Data Visualization, NLP",Bachelor,3,Government,2024-03-23,2024-04-22,1750,9.6,Advanced Robotics +AI01151,ML Ops Engineer,167924,GBP,125943,EX,FL,United Kingdom,S,Ghana,0,"Hadoop, SQL, GCP, Scala, Computer Vision",Master,13,Education,2025-03-24,2025-05-11,2123,10,Future Systems +AI01152,NLP Engineer,104995,USD,104995,MI,FT,Sweden,L,Sweden,50,"Tableau, GCP, Mathematics",Bachelor,3,Media,2024-02-10,2024-02-29,2335,5.9,Algorithmic Solutions +AI01153,NLP Engineer,319365,CHF,287429,EX,FT,Switzerland,M,Switzerland,100,"Python, Linux, TensorFlow, AWS",Associate,15,Telecommunications,2024-08-01,2024-08-31,2420,7.4,Advanced Robotics +AI01154,Data Engineer,120902,USD,120902,SE,FL,South Korea,L,South Korea,0,"Linux, Python, MLOps, Spark, Mathematics",PhD,6,Healthcare,2024-12-15,2025-02-07,592,7.2,DataVision Ltd +AI01155,AI Research Scientist,93958,EUR,79864,MI,CT,Germany,M,Latvia,50,"SQL, Data Visualization, Scala",Master,3,Real Estate,2024-11-25,2025-02-04,2028,7.9,Advanced Robotics +AI01156,Machine Learning Researcher,204959,USD,204959,EX,CT,Denmark,L,Denmark,50,"TensorFlow, Python, GCP, R",Bachelor,10,Manufacturing,2025-03-27,2025-04-30,2354,6.1,Digital Transformation LLC +AI01157,Computer Vision Engineer,45750,USD,45750,MI,FL,China,M,Denmark,0,"Statistics, PyTorch, TensorFlow, Computer Vision, Deep Learning",PhD,2,Energy,2025-03-09,2025-03-24,972,7.4,TechCorp Inc +AI01158,Data Engineer,191169,EUR,162494,EX,CT,Germany,M,Egypt,100,"Scala, Java, Computer Vision, AWS",Associate,13,Gaming,2025-03-19,2025-04-03,2281,5.6,Algorithmic Solutions +AI01159,Robotics Engineer,187320,JPY,20605200,EX,PT,Japan,L,Spain,100,"Java, TensorFlow, Data Visualization",PhD,16,Education,2024-09-23,2024-11-10,701,8.8,Cloud AI Solutions +AI01160,AI Architect,45995,USD,45995,SE,FL,China,S,China,0,"Python, TensorFlow, Linux, Statistics",Bachelor,8,Telecommunications,2024-12-03,2024-12-22,1433,8.3,AI Innovations +AI01161,Principal Data Scientist,189388,EUR,160980,EX,FL,France,S,France,50,"TensorFlow, Python, PyTorch, AWS, R",Associate,10,Healthcare,2024-11-23,2025-01-20,2162,9.9,Digital Transformation LLC +AI01162,AI Research Scientist,77764,CHF,69988,EN,PT,Switzerland,M,Ghana,100,"Kubernetes, SQL, Data Visualization",Master,0,Finance,2024-11-28,2024-12-21,1143,8,Cognitive Computing +AI01163,Data Engineer,70260,EUR,59721,EN,FL,Germany,L,Germany,0,"Linux, Data Visualization, MLOps, Git",Master,1,Education,2024-12-05,2025-01-03,604,8,Cloud AI Solutions +AI01164,Autonomous Systems Engineer,59125,EUR,50256,EN,PT,Germany,S,Germany,50,"Scala, Python, Tableau, Computer Vision",PhD,1,Gaming,2024-10-22,2024-12-14,706,7.7,Smart Analytics +AI01165,Head of AI,85915,CHF,77324,EN,FL,Switzerland,S,Switzerland,0,"Python, Tableau, Java, AWS, Statistics",Associate,1,Telecommunications,2025-04-15,2025-05-29,1359,8.5,Cognitive Computing +AI01166,AI Software Engineer,161147,USD,161147,SE,FL,Israel,L,Israel,50,"Spark, Linux, Kubernetes, Hadoop, Python",Associate,9,Energy,2024-09-05,2024-11-03,1023,6.3,Cognitive Computing +AI01167,AI Consultant,145874,USD,145874,EX,PT,Israel,M,Israel,50,"GCP, Statistics, MLOps, Python, AWS",PhD,16,Education,2024-08-23,2024-11-01,1826,9.6,Smart Analytics +AI01168,Research Scientist,41928,USD,41928,MI,PT,India,L,India,50,"AWS, MLOps, NLP",Associate,3,Telecommunications,2024-07-06,2024-09-04,1539,7.1,Quantum Computing Inc +AI01169,NLP Engineer,244108,USD,244108,EX,CT,Denmark,S,Denmark,0,"Hadoop, Python, SQL",Associate,14,Transportation,2024-05-21,2024-06-29,974,8.9,AI Innovations +AI01170,NLP Engineer,74765,CHF,67289,EN,FT,Switzerland,M,Vietnam,50,"Tableau, Deep Learning, Kubernetes, AWS",Master,0,Retail,2025-04-20,2025-06-25,861,6.6,Quantum Computing Inc +AI01171,AI Software Engineer,111797,USD,111797,SE,CT,Finland,S,Finland,50,"Python, MLOps, Linux",Bachelor,8,Finance,2024-07-14,2024-09-06,778,7.1,Cognitive Computing +AI01172,AI Product Manager,129173,AUD,174384,SE,FL,Australia,M,Australia,100,"Scala, Spark, MLOps, Mathematics, Linux",PhD,8,Automotive,2024-08-12,2024-10-10,1154,9.1,Neural Networks Co +AI01173,Robotics Engineer,109849,USD,109849,SE,FL,Ireland,S,Ireland,0,"SQL, TensorFlow, MLOps",Master,5,Transportation,2024-11-08,2024-11-27,1872,9.3,Smart Analytics +AI01174,NLP Engineer,86314,CHF,77683,EN,FL,Switzerland,L,Switzerland,0,"Scala, Python, TensorFlow, Computer Vision",Bachelor,0,Retail,2025-01-30,2025-03-15,2197,9.2,Cognitive Computing +AI01175,AI Product Manager,134718,CHF,121246,MI,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Linux, R",Bachelor,4,Finance,2024-10-09,2024-11-11,2272,6.1,TechCorp Inc +AI01176,Machine Learning Researcher,146659,USD,146659,SE,CT,Sweden,M,Sweden,100,"TensorFlow, PyTorch, Kubernetes",Associate,6,Government,2025-01-24,2025-02-15,2107,8.3,DeepTech Ventures +AI01177,NLP Engineer,207301,GBP,155476,EX,FL,United Kingdom,M,United Kingdom,100,"Java, SQL, Spark, TensorFlow",Master,15,Real Estate,2024-01-06,2024-02-17,1385,6.5,DeepTech Ventures +AI01178,Data Scientist,86551,EUR,73568,MI,CT,Netherlands,S,Netherlands,100,"Scala, Statistics, SQL",PhD,2,Finance,2024-01-18,2024-02-14,752,8.8,Neural Networks Co +AI01179,AI Consultant,101086,SGD,131412,MI,FL,Singapore,L,Latvia,0,"Tableau, AWS, Hadoop, Kubernetes, SQL",Bachelor,2,Automotive,2024-11-02,2024-12-18,1462,10,Autonomous Tech +AI01180,Computer Vision Engineer,243742,USD,243742,EX,FL,Ireland,M,Ireland,100,"Linux, GCP, AWS",Master,16,Automotive,2024-10-18,2024-11-12,972,8.4,Future Systems +AI01181,AI Software Engineer,45910,EUR,39024,EN,FL,Austria,S,Austria,100,"Linux, Data Visualization, Git, Scala",Master,0,Automotive,2024-09-17,2024-10-25,1021,9.7,Machine Intelligence Group +AI01182,Principal Data Scientist,165181,EUR,140404,EX,CT,France,L,France,100,"TensorFlow, NLP, Hadoop, Kubernetes, Python",Bachelor,14,Finance,2024-01-07,2024-02-25,1029,6.7,Quantum Computing Inc +AI01183,Machine Learning Researcher,47299,AUD,63854,EN,PT,Australia,S,Australia,100,"SQL, Linux, Git, Tableau",Master,1,Telecommunications,2024-06-17,2024-07-23,2432,6.8,DeepTech Ventures +AI01184,AI Specialist,69234,CAD,86543,EN,FT,Canada,M,Ireland,100,"Computer Vision, Java, Data Visualization",PhD,0,Retail,2024-01-15,2024-02-13,1184,5,AI Innovations +AI01185,AI Product Manager,95021,SGD,123527,MI,FL,Singapore,L,Belgium,50,"MLOps, Tableau, Python, Docker",Bachelor,3,Telecommunications,2024-10-12,2024-10-26,2138,5.7,Future Systems +AI01186,Machine Learning Engineer,27279,USD,27279,EN,CT,India,L,India,0,"Statistics, Mathematics, Tableau",Associate,0,Real Estate,2024-02-27,2024-03-25,1258,6.5,TechCorp Inc +AI01187,Machine Learning Researcher,74665,SGD,97065,EN,FL,Singapore,S,Singapore,100,"R, Azure, PyTorch",PhD,0,Retail,2024-01-14,2024-03-05,1743,7.5,Advanced Robotics +AI01188,AI Consultant,105569,USD,105569,SE,CT,South Korea,M,France,0,"Python, Java, Data Visualization, Deep Learning",Associate,7,Manufacturing,2024-06-07,2024-07-06,765,6.9,Future Systems +AI01189,Principal Data Scientist,75073,USD,75073,EN,FL,Sweden,M,Sweden,0,"Python, R, Tableau, Data Visualization, AWS",Associate,1,Retail,2024-11-20,2025-01-28,1316,5.8,Future Systems +AI01190,AI Software Engineer,185794,USD,185794,EX,FT,Denmark,M,Singapore,100,"R, MLOps, Computer Vision, Git",PhD,18,Energy,2025-01-27,2025-02-13,691,7.1,DeepTech Ventures +AI01191,AI Specialist,222006,USD,222006,EX,FL,United States,S,New Zealand,100,"Hadoop, Spark, Mathematics",Bachelor,19,Energy,2025-02-19,2025-03-27,987,9.1,TechCorp Inc +AI01192,Robotics Engineer,95988,USD,95988,MI,PT,Ireland,M,Switzerland,0,"PyTorch, Linux, Scala, Mathematics, GCP",Master,2,Real Estate,2025-02-21,2025-03-18,1899,9.6,Autonomous Tech +AI01193,Autonomous Systems Engineer,75420,GBP,56565,EN,CT,United Kingdom,M,Israel,50,"Linux, Spark, TensorFlow, Python",Associate,1,Media,2024-07-03,2024-09-02,1590,5.9,Quantum Computing Inc +AI01194,AI Consultant,56066,CAD,70083,EN,FL,Canada,S,Japan,0,"Spark, Kubernetes, TensorFlow",PhD,0,Technology,2024-09-28,2024-10-28,1278,9.1,Neural Networks Co +AI01195,ML Ops Engineer,34199,USD,34199,MI,CT,India,S,India,100,"Java, Kubernetes, Azure, GCP",Associate,3,Energy,2025-02-11,2025-04-09,1150,6.6,DeepTech Ventures +AI01196,Robotics Engineer,123046,USD,123046,SE,PT,Israel,M,Israel,50,"Python, Docker, Data Visualization, MLOps, Deep Learning",Master,9,Media,2024-09-13,2024-10-08,1501,6.8,Predictive Systems +AI01197,Research Scientist,155715,EUR,132358,SE,CT,Austria,L,Brazil,100,"Java, Kubernetes, Docker",Associate,8,Manufacturing,2024-09-01,2024-10-31,1240,6.6,Cloud AI Solutions +AI01198,AI Architect,135052,CHF,121547,MI,CT,Switzerland,M,New Zealand,100,"GCP, Python, Git, Java, Computer Vision",PhD,4,Finance,2024-07-08,2024-09-15,1191,6.2,Smart Analytics +AI01199,AI Research Scientist,139723,GBP,104792,SE,PT,United Kingdom,L,Canada,100,"Kubernetes, Spark, MLOps",Associate,5,Finance,2024-06-27,2024-07-23,1731,9.7,Cloud AI Solutions +AI01200,AI Software Engineer,126789,USD,126789,SE,CT,Israel,S,Israel,50,"Hadoop, Git, Statistics",Bachelor,6,Healthcare,2024-07-31,2024-08-14,2157,5.9,DeepTech Ventures +AI01201,Data Analyst,51041,SGD,66353,EN,FT,Singapore,S,Singapore,100,"Statistics, AWS, Scala, PyTorch",PhD,1,Healthcare,2024-01-30,2024-02-19,1755,6.8,Cloud AI Solutions +AI01202,Machine Learning Engineer,66473,AUD,89739,EN,FT,Australia,M,Australia,100,"Docker, Kubernetes, Statistics, Spark",Master,0,Energy,2025-02-04,2025-02-20,2260,7.9,Future Systems +AI01203,AI Consultant,82798,JPY,9107780,EN,FT,Japan,L,Japan,50,"Azure, SQL, AWS",Master,0,Real Estate,2025-01-10,2025-03-06,1844,8.2,Quantum Computing Inc +AI01204,Machine Learning Researcher,208808,USD,208808,EX,CT,Ireland,M,Estonia,100,"Java, Python, PyTorch, SQL",Associate,16,Healthcare,2024-01-16,2024-02-29,2313,5.3,Autonomous Tech +AI01205,Principal Data Scientist,85454,USD,85454,EN,FT,Denmark,M,Denmark,100,"SQL, Scala, Kubernetes",PhD,0,Government,2024-12-20,2025-02-05,1407,7.8,Cloud AI Solutions +AI01206,Principal Data Scientist,312926,CHF,281633,EX,FT,Switzerland,S,Switzerland,100,"Kubernetes, Git, Mathematics, Hadoop, PyTorch",Bachelor,17,Media,2024-08-07,2024-10-14,1468,6.5,Predictive Systems +AI01207,Computer Vision Engineer,112468,USD,112468,EN,FT,Denmark,L,Italy,100,"R, Java, Linux",Master,0,Manufacturing,2024-11-13,2024-11-30,1081,9.1,Neural Networks Co +AI01208,Data Analyst,184835,USD,184835,EX,PT,Sweden,L,Sweden,100,"GCP, Python, TensorFlow, SQL",Bachelor,12,Consulting,2024-09-22,2024-10-31,570,6.7,Algorithmic Solutions +AI01209,Robotics Engineer,114775,EUR,97559,SE,PT,France,L,France,100,"Python, Git, TensorFlow, Data Visualization, Linux",Bachelor,7,Education,2024-06-20,2024-08-10,1743,9.4,Neural Networks Co +AI01210,Deep Learning Engineer,87755,CAD,109694,MI,PT,Canada,L,Portugal,100,"Deep Learning, Scala, Data Visualization, TensorFlow",Bachelor,3,Energy,2024-11-03,2024-12-15,1436,6.4,Predictive Systems +AI01211,AI Consultant,226988,SGD,295084,EX,CT,Singapore,S,Singapore,0,"Statistics, NLP, Linux",Master,12,Manufacturing,2024-05-03,2024-06-13,2480,5.1,Advanced Robotics +AI01212,Data Scientist,109751,CAD,137189,SE,PT,Canada,S,Denmark,100,"Azure, Kubernetes, Spark, Computer Vision",PhD,9,Energy,2024-09-01,2024-10-13,2171,7.1,Future Systems +AI01213,NLP Engineer,110714,USD,110714,EX,FL,China,M,China,100,"NLP, Scala, Kubernetes, Python",Master,15,Finance,2024-06-01,2024-08-13,835,7.9,TechCorp Inc +AI01214,AI Architect,243320,USD,243320,EX,CT,Israel,L,Israel,0,"NLP, Scala, Python, Computer Vision",PhD,16,Telecommunications,2024-09-17,2024-11-17,2026,5.8,DataVision Ltd +AI01215,Machine Learning Researcher,137660,USD,137660,SE,FT,Sweden,M,India,100,"Tableau, Kubernetes, SQL, Java",Associate,6,Technology,2024-07-19,2024-09-02,964,8.2,Future Systems +AI01216,Deep Learning Engineer,101137,USD,101137,MI,CT,Denmark,M,Belgium,50,"R, Azure, Deep Learning, SQL, Java",Master,2,Telecommunications,2025-01-02,2025-02-06,2016,10,DataVision Ltd +AI01217,Data Analyst,76750,EUR,65238,EN,FT,Netherlands,M,Netherlands,0,"Java, Git, Data Visualization",Bachelor,0,Gaming,2024-07-20,2024-09-01,723,6.9,Cognitive Computing +AI01218,Machine Learning Researcher,225610,USD,225610,EX,PT,Denmark,M,Denmark,50,"PyTorch, Deep Learning, TensorFlow",Associate,14,Telecommunications,2024-06-21,2024-08-10,810,7.1,Predictive Systems +AI01219,AI Consultant,250681,USD,250681,EX,FL,Denmark,S,Denmark,0,"TensorFlow, R, Spark, Python",PhD,15,Retail,2024-07-17,2024-09-22,818,6.3,Smart Analytics +AI01220,Deep Learning Engineer,68073,USD,68073,EN,PT,United States,M,United States,50,"MLOps, AWS, SQL, NLP, Statistics",Master,0,Technology,2024-03-11,2024-04-05,1104,5.4,TechCorp Inc +AI01221,Data Scientist,83363,EUR,70859,MI,FL,Germany,S,Germany,100,"Git, Linux, MLOps, Mathematics",Bachelor,2,Energy,2024-08-01,2024-09-15,2321,6.2,Cognitive Computing +AI01222,AI Architect,82241,USD,82241,EN,FL,United States,L,United States,0,"Spark, R, Deep Learning, Java, Git",Master,0,Education,2024-03-04,2024-05-09,515,9.9,Neural Networks Co +AI01223,AI Research Scientist,70446,USD,70446,EN,PT,South Korea,L,South Korea,0,"Python, Git, TensorFlow, GCP, PyTorch",Master,1,Energy,2024-11-08,2024-11-27,688,8.3,Digital Transformation LLC +AI01224,Machine Learning Researcher,91327,USD,91327,EN,PT,United States,M,United States,0,"Hadoop, Scala, Statistics, Git",Bachelor,0,Technology,2024-06-20,2024-07-15,703,5.6,Advanced Robotics +AI01225,Data Scientist,39389,USD,39389,MI,CT,India,L,India,0,"Data Visualization, SQL, Hadoop",Associate,4,Media,2024-10-03,2024-11-12,1197,9.6,Neural Networks Co +AI01226,Robotics Engineer,81525,EUR,69296,EN,CT,Netherlands,L,Netherlands,0,"AWS, Data Visualization, PyTorch",PhD,0,Finance,2025-04-03,2025-06-04,2353,5.8,DeepTech Ventures +AI01227,Data Analyst,64441,EUR,54775,EN,PT,Germany,S,Germany,50,"PyTorch, TensorFlow, Tableau, GCP",Associate,1,Retail,2024-10-15,2024-11-18,604,5.3,Cloud AI Solutions +AI01228,Data Scientist,154936,CAD,193670,SE,FL,Canada,L,Spain,0,"Data Visualization, Python, Scala, TensorFlow, Statistics",Master,7,Energy,2024-01-23,2024-03-19,1911,5.5,Autonomous Tech +AI01229,Machine Learning Engineer,252651,USD,252651,EX,CT,Finland,L,Finland,0,"Python, Java, MLOps, Computer Vision, Deep Learning",Associate,11,Media,2024-07-25,2024-09-09,1989,9.7,AI Innovations +AI01230,AI Research Scientist,85211,GBP,63908,MI,PT,United Kingdom,M,United Kingdom,0,"AWS, MLOps, Deep Learning, SQL",Bachelor,2,Energy,2024-08-28,2024-09-20,1984,6.7,Advanced Robotics +AI01231,Head of AI,75989,USD,75989,MI,CT,South Korea,S,South Korea,0,"PyTorch, TensorFlow, Docker, Hadoop",Associate,2,Telecommunications,2024-11-22,2025-01-08,1985,5.6,Algorithmic Solutions +AI01232,NLP Engineer,81874,USD,81874,MI,CT,Ireland,M,Ireland,50,"Azure, GCP, Statistics, PyTorch",Bachelor,2,Real Estate,2024-10-16,2024-12-09,1992,8.5,Autonomous Tech +AI01233,Robotics Engineer,159436,USD,159436,SE,CT,Israel,L,Australia,50,"TensorFlow, Data Visualization, Java, Azure",Associate,7,Telecommunications,2024-02-02,2024-03-12,1302,10,DeepTech Ventures +AI01234,AI Research Scientist,116597,USD,116597,SE,FT,Finland,M,Switzerland,50,"Deep Learning, Statistics, AWS",Associate,5,Media,2024-12-12,2025-01-11,762,8.9,Future Systems +AI01235,ML Ops Engineer,123943,JPY,13633730,SE,CT,Japan,M,Japan,50,"Python, TensorFlow, GCP, SQL, Git",PhD,9,Consulting,2024-08-04,2024-08-31,2347,8.3,DataVision Ltd +AI01236,Principal Data Scientist,142168,EUR,120843,SE,PT,France,M,France,50,"Mathematics, TensorFlow, Docker, NLP",Associate,9,Gaming,2024-05-21,2024-06-07,1546,7.3,TechCorp Inc +AI01237,Machine Learning Engineer,145212,USD,145212,MI,FT,United States,L,United Kingdom,50,"Linux, R, Deep Learning",Master,3,Finance,2024-01-14,2024-03-20,1063,7.7,Neural Networks Co +AI01238,Data Engineer,150880,JPY,16596800,SE,FT,Japan,L,Japan,100,"Mathematics, R, Data Visualization",Associate,6,Gaming,2024-12-11,2025-01-15,2362,6,Neural Networks Co +AI01239,ML Ops Engineer,78416,USD,78416,MI,FL,Israel,M,Israel,0,"Kubernetes, Python, Data Visualization, TensorFlow, AWS",PhD,4,Technology,2024-12-29,2025-03-11,521,8.6,Machine Intelligence Group +AI01240,Robotics Engineer,167446,EUR,142329,EX,CT,Netherlands,L,Netherlands,0,"Git, Azure, PyTorch, Deep Learning",Associate,13,Education,2025-04-28,2025-05-26,2462,5.7,DataVision Ltd +AI01241,AI Architect,136891,USD,136891,EX,FT,South Korea,S,South Korea,50,"Data Visualization, Java, Linux, AWS",Associate,13,Manufacturing,2024-11-09,2025-01-06,2072,6.3,Cloud AI Solutions +AI01242,AI Product Manager,56186,CAD,70233,EN,CT,Canada,L,Sweden,0,"Tableau, Deep Learning, Spark, TensorFlow, Hadoop",Bachelor,0,Retail,2024-02-09,2024-03-02,1179,7.5,Future Systems +AI01243,Data Scientist,89015,CAD,111269,MI,FL,Canada,L,India,100,"Kubernetes, Python, Azure",PhD,3,Transportation,2025-02-25,2025-03-24,1473,8.2,Cloud AI Solutions +AI01244,Principal Data Scientist,101256,GBP,75942,MI,CT,United Kingdom,L,Brazil,0,"PyTorch, Linux, Spark",PhD,4,Manufacturing,2024-10-28,2024-11-12,635,6.8,Digital Transformation LLC +AI01245,Machine Learning Engineer,223846,EUR,190269,EX,FL,Austria,M,Austria,50,"Hadoop, TensorFlow, Python",PhD,10,Finance,2024-11-02,2024-12-03,1775,8.2,Algorithmic Solutions +AI01246,Data Analyst,89705,CAD,112131,MI,PT,Canada,L,Canada,0,"Scala, Python, Kubernetes",Associate,4,Gaming,2024-11-23,2025-01-08,1486,8.3,DataVision Ltd +AI01247,Head of AI,173178,USD,173178,EX,FL,South Korea,L,South Korea,0,"Python, AWS, Statistics, Computer Vision, SQL",Associate,17,Real Estate,2025-03-10,2025-04-07,2301,6.6,TechCorp Inc +AI01248,Deep Learning Engineer,119123,USD,119123,SE,PT,Norway,S,Portugal,100,"Data Visualization, Python, TensorFlow",Associate,9,Automotive,2024-11-16,2025-01-05,2295,9.7,Autonomous Tech +AI01249,Robotics Engineer,205428,USD,205428,EX,FL,United States,L,United States,0,"R, Spark, Mathematics, TensorFlow, Deep Learning",Associate,10,Finance,2024-06-30,2024-08-22,1349,8.2,TechCorp Inc +AI01250,Deep Learning Engineer,107614,USD,107614,SE,FT,Israel,M,Switzerland,0,"Statistics, NLP, GCP, Python, PyTorch",Bachelor,5,Gaming,2024-04-02,2024-06-11,2346,7.6,Advanced Robotics +AI01251,AI Architect,96395,USD,96395,SE,FT,Israel,M,Israel,50,"Git, PyTorch, Statistics",PhD,5,Energy,2024-10-21,2024-11-27,824,5.4,Quantum Computing Inc +AI01252,Deep Learning Engineer,113420,USD,113420,EN,CT,Norway,L,Norway,50,"Spark, Hadoop, PyTorch, TensorFlow, NLP",Master,1,Technology,2024-07-10,2024-09-11,1658,7.3,DataVision Ltd +AI01253,Machine Learning Engineer,186496,USD,186496,EX,FL,Israel,L,Israel,100,"Azure, AWS, Computer Vision, Java",Bachelor,19,Finance,2024-04-02,2024-05-14,1245,9.2,Smart Analytics +AI01254,Research Scientist,212359,USD,212359,EX,FL,Finland,M,Finland,0,"PyTorch, NLP, Hadoop",Associate,13,Technology,2024-08-01,2024-08-31,508,8.3,TechCorp Inc +AI01255,Head of AI,48963,USD,48963,SE,CT,India,L,India,100,"Python, Computer Vision, TensorFlow",Associate,9,Telecommunications,2025-04-15,2025-05-27,1577,5.6,Quantum Computing Inc +AI01256,Principal Data Scientist,84644,EUR,71947,MI,FL,France,L,France,100,"NLP, Kubernetes, Python",Bachelor,4,Healthcare,2025-02-25,2025-04-03,1615,5.7,Quantum Computing Inc +AI01257,Robotics Engineer,129200,USD,129200,MI,CT,Denmark,L,Denmark,100,"Java, SQL, Kubernetes, Computer Vision",Associate,4,Manufacturing,2025-03-06,2025-05-16,1076,9.3,Neural Networks Co +AI01258,AI Research Scientist,131449,JPY,14459390,SE,FT,Japan,M,Japan,50,"SQL, Hadoop, NLP, Deep Learning, GCP",Associate,9,Retail,2025-02-25,2025-05-08,2118,7.4,Digital Transformation LLC +AI01259,Computer Vision Engineer,37726,USD,37726,EN,CT,China,L,United States,0,"Git, Python, PyTorch, GCP, AWS",PhD,1,Media,2024-03-18,2024-04-03,2339,9.5,Machine Intelligence Group +AI01260,Robotics Engineer,147408,USD,147408,SE,CT,United States,L,United States,0,"Scala, Python, AWS",Master,6,Media,2024-09-26,2024-11-18,652,6.5,DeepTech Ventures +AI01261,Autonomous Systems Engineer,68165,USD,68165,EN,PT,United States,S,Netherlands,0,"Azure, Linux, Computer Vision, R, Java",Bachelor,1,Finance,2024-07-30,2024-10-07,1978,8.5,Quantum Computing Inc +AI01262,Head of AI,153774,USD,153774,EX,FL,Finland,M,Finland,100,"Azure, Hadoop, AWS, Docker",Master,15,Automotive,2024-06-30,2024-08-18,1117,6.7,Quantum Computing Inc +AI01263,AI Consultant,139995,EUR,118996,EX,PT,Austria,S,Colombia,50,"Mathematics, Computer Vision, Linux, Scala, PyTorch",Associate,13,Government,2024-02-13,2024-04-18,546,9,Machine Intelligence Group +AI01264,Computer Vision Engineer,126306,CAD,157883,SE,CT,Canada,S,Vietnam,0,"Azure, R, TensorFlow, AWS, Deep Learning",Associate,6,Transportation,2024-04-20,2024-06-17,2177,8.8,Algorithmic Solutions +AI01265,Principal Data Scientist,142937,USD,142937,SE,FL,United States,S,United States,50,"Git, Python, R, MLOps, Statistics",Bachelor,5,Healthcare,2024-03-12,2024-05-15,1101,5.8,Cloud AI Solutions +AI01266,Data Analyst,157493,USD,157493,SE,FL,Norway,L,Norway,0,"PyTorch, Hadoop, TensorFlow",PhD,8,Media,2024-04-01,2024-04-30,1738,5.9,Algorithmic Solutions +AI01267,Research Scientist,81840,USD,81840,EN,FT,Denmark,S,Denmark,50,"Python, Docker, Deep Learning, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-07,558,8.5,Neural Networks Co +AI01268,AI Product Manager,120340,USD,120340,MI,CT,Norway,S,Norway,0,"Spark, TensorFlow, Python",Associate,2,Transportation,2024-12-18,2025-02-20,2435,9.3,Algorithmic Solutions +AI01269,Deep Learning Engineer,133498,GBP,100124,MI,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,3,Gaming,2024-04-02,2024-05-04,2347,9.6,Autonomous Tech +AI01270,Autonomous Systems Engineer,168321,EUR,143073,EX,PT,Netherlands,M,Netherlands,100,"Mathematics, R, NLP, Deep Learning",Master,18,Automotive,2025-02-13,2025-04-27,1845,7.9,Future Systems +AI01271,Machine Learning Engineer,128450,CAD,160563,SE,PT,Canada,M,Canada,50,"SQL, Hadoop, Git, AWS",Bachelor,7,Healthcare,2024-03-29,2024-05-23,552,6.2,DeepTech Ventures +AI01272,Robotics Engineer,71869,SGD,93430,EN,FT,Singapore,M,Luxembourg,100,"Tableau, Azure, Scala, Computer Vision",Associate,0,Energy,2024-10-23,2024-12-19,1601,7.9,Advanced Robotics +AI01273,AI Architect,86340,USD,86340,MI,FL,Sweden,M,Sweden,0,"AWS, Scala, Hadoop",Master,2,Consulting,2024-12-17,2025-02-05,1229,5,Smart Analytics +AI01274,AI Product Manager,73047,CAD,91309,EN,PT,Canada,M,Australia,100,"NLP, Computer Vision, Python, Hadoop, TensorFlow",Associate,1,Finance,2024-01-17,2024-02-04,1706,8.6,Predictive Systems +AI01275,Principal Data Scientist,125916,AUD,169987,MI,PT,Australia,L,Australia,50,"Tableau, Python, SQL",Master,3,Real Estate,2024-10-25,2024-12-04,1314,9.1,Autonomous Tech +AI01276,AI Software Engineer,107722,USD,107722,SE,PT,Finland,M,Finland,0,"GCP, R, Docker, SQL",PhD,6,Media,2024-08-04,2024-09-20,2439,5.2,DeepTech Ventures +AI01277,AI Architect,100220,USD,100220,MI,PT,Ireland,M,Ukraine,100,"Java, Azure, Spark, Mathematics",Associate,3,Real Estate,2025-04-12,2025-06-17,1841,9.7,DataVision Ltd +AI01278,Machine Learning Researcher,141420,USD,141420,EX,FL,Finland,S,Finland,50,"Linux, PyTorch, Hadoop",Associate,15,Telecommunications,2024-07-26,2024-10-07,877,9.3,Cognitive Computing +AI01279,ML Ops Engineer,43276,USD,43276,SE,FT,China,S,China,0,"AWS, Docker, Computer Vision, PyTorch, SQL",Bachelor,7,Finance,2025-01-26,2025-02-22,2494,6.5,Machine Intelligence Group +AI01280,ML Ops Engineer,101313,EUR,86116,SE,FT,Germany,S,Germany,50,"Statistics, Spark, Data Visualization",Associate,6,Government,2025-03-28,2025-05-08,937,9.9,DataVision Ltd +AI01281,Data Analyst,238881,EUR,203049,EX,FT,Austria,L,Austria,0,"PyTorch, NLP, Scala, Linux",PhD,13,Technology,2024-05-03,2024-07-09,897,7.5,Future Systems +AI01282,Data Scientist,144471,SGD,187812,SE,FL,Singapore,M,Singapore,100,"Java, Deep Learning, Azure",Associate,8,Real Estate,2024-04-01,2024-05-09,984,6,Neural Networks Co +AI01283,Head of AI,71781,EUR,61014,MI,CT,Austria,M,Estonia,100,"Docker, R, Linux, SQL",Bachelor,4,Education,2024-05-05,2024-06-15,2151,5.9,Quantum Computing Inc +AI01284,AI Architect,34334,USD,34334,MI,FT,India,M,Norway,50,"Hadoop, GCP, PyTorch, MLOps, TensorFlow",PhD,3,Government,2024-07-20,2024-08-07,1662,5.8,Neural Networks Co +AI01285,AI Research Scientist,59699,USD,59699,EN,PT,Sweden,L,Sweden,0,"Tableau, MLOps, Scala, Java, NLP",Master,1,Telecommunications,2024-03-09,2024-04-17,526,9.8,Autonomous Tech +AI01286,AI Specialist,74398,SGD,96717,EN,PT,Singapore,L,Denmark,50,"GCP, Kubernetes, Data Visualization, Deep Learning",PhD,1,Gaming,2024-07-05,2024-08-04,560,6.5,Smart Analytics +AI01287,Data Scientist,114132,USD,114132,MI,CT,Israel,L,Israel,100,"R, Spark, NLP, Hadoop",PhD,4,Real Estate,2024-04-02,2024-06-01,1575,7.8,Quantum Computing Inc +AI01288,AI Specialist,82988,USD,82988,EN,FL,Israel,L,United Kingdom,50,"NLP, TensorFlow, PyTorch, Deep Learning, AWS",PhD,1,Gaming,2024-11-05,2024-11-20,1031,5.3,Algorithmic Solutions +AI01289,Data Engineer,129184,USD,129184,MI,FT,Denmark,M,Denmark,100,"Scala, Java, Computer Vision, R, Tableau",Associate,4,Transportation,2024-06-19,2024-08-22,2210,8.1,Autonomous Tech +AI01290,Head of AI,122761,USD,122761,SE,PT,Sweden,S,Sweden,100,"Java, Scala, Mathematics",Master,7,Automotive,2024-07-17,2024-09-06,1608,9.1,TechCorp Inc +AI01291,Machine Learning Engineer,176080,USD,176080,EX,PT,South Korea,S,South Korea,50,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,10,Manufacturing,2024-08-08,2024-09-14,2453,7.3,Cognitive Computing +AI01292,AI Software Engineer,132322,USD,132322,MI,CT,Denmark,L,Denmark,0,"PyTorch, MLOps, Scala, Computer Vision",PhD,3,Healthcare,2024-09-08,2024-11-11,2323,6.5,Machine Intelligence Group +AI01293,Head of AI,220734,EUR,187624,EX,CT,Netherlands,S,Netherlands,50,"TensorFlow, Azure, Scala, Statistics",Associate,19,Media,2024-04-24,2024-05-20,1183,8.8,Advanced Robotics +AI01294,Deep Learning Engineer,210396,USD,210396,EX,PT,Ireland,S,Ireland,0,"Git, MLOps, Kubernetes, Java, Azure",PhD,10,Energy,2025-03-19,2025-04-05,1745,5.2,Future Systems +AI01295,Research Scientist,178095,USD,178095,SE,CT,Norway,L,New Zealand,100,"Python, Tableau, Azure, Statistics",Bachelor,9,Healthcare,2024-09-16,2024-10-12,1142,5.7,Machine Intelligence Group +AI01296,AI Consultant,130897,EUR,111262,EX,FL,France,S,France,50,"GCP, Linux, Data Visualization",Associate,11,Real Estate,2024-03-05,2024-03-30,1235,5.1,Advanced Robotics +AI01297,Computer Vision Engineer,278652,EUR,236854,EX,FL,Netherlands,L,Netherlands,100,"R, Kubernetes, NLP",PhD,14,Real Estate,2025-04-19,2025-05-29,1960,5.7,Cognitive Computing +AI01298,ML Ops Engineer,241681,USD,241681,EX,FL,Finland,L,Finland,0,"Kubernetes, Azure, AWS",Associate,10,Gaming,2024-10-25,2024-12-05,2150,6.3,TechCorp Inc +AI01299,Data Scientist,108165,USD,108165,MI,FL,Norway,S,Poland,50,"Data Visualization, Linux, MLOps, R, NLP",PhD,2,Media,2025-03-09,2025-05-16,962,7.7,Smart Analytics +AI01300,AI Research Scientist,37809,USD,37809,SE,CT,India,M,Estonia,0,"Hadoop, Data Visualization, NLP, Python, Docker",Bachelor,7,Government,2024-05-24,2024-06-13,1144,9.4,DeepTech Ventures +AI01301,Machine Learning Engineer,59161,USD,59161,SE,CT,China,L,China,100,"SQL, Tableau, Scala, Data Visualization",Bachelor,6,Consulting,2024-10-03,2024-11-01,848,9.8,Neural Networks Co +AI01302,Deep Learning Engineer,65717,AUD,88718,EN,FL,Australia,M,Australia,50,"Scala, Git, TensorFlow, Linux",PhD,1,Gaming,2024-08-25,2024-10-20,2168,8.9,Neural Networks Co +AI01303,Machine Learning Engineer,131415,USD,131415,EX,FL,South Korea,M,Czech Republic,0,"TensorFlow, Scala, Computer Vision",Master,14,Finance,2025-04-27,2025-06-20,686,9.2,DataVision Ltd +AI01304,NLP Engineer,165177,CHF,148659,SE,FL,Switzerland,S,Switzerland,0,"Azure, Kubernetes, NLP, AWS",PhD,6,Energy,2024-07-07,2024-09-09,2397,8.6,Algorithmic Solutions +AI01305,Machine Learning Researcher,134710,USD,134710,SE,PT,Finland,L,Finland,50,"Python, Hadoop, NLP",Associate,9,Automotive,2025-01-27,2025-03-22,898,5.9,Smart Analytics +AI01306,AI Specialist,132331,EUR,112481,SE,CT,France,L,France,100,"NLP, Scala, Kubernetes",Master,6,Automotive,2025-02-14,2025-03-17,1623,6,Quantum Computing Inc +AI01307,Machine Learning Researcher,25085,USD,25085,EN,CT,China,S,China,100,"TensorFlow, Scala, PyTorch, GCP, Git",Associate,1,Manufacturing,2024-07-31,2024-09-25,2291,5.2,DataVision Ltd +AI01308,AI Architect,81436,USD,81436,EN,FL,United States,M,United States,50,"Java, Docker, Tableau, Linux, Deep Learning",Associate,0,Technology,2024-11-25,2025-01-31,1081,8.4,Autonomous Tech +AI01309,Robotics Engineer,121581,JPY,13373910,SE,FT,Japan,M,Japan,100,"GCP, Kubernetes, AWS, Docker",Associate,8,Technology,2024-12-10,2025-01-31,1652,9.7,Quantum Computing Inc +AI01310,NLP Engineer,85043,USD,85043,MI,CT,South Korea,M,South Korea,100,"Kubernetes, PyTorch, Computer Vision, GCP, Git",Master,3,Telecommunications,2024-08-20,2024-10-26,1219,8,DeepTech Ventures +AI01311,Principal Data Scientist,77847,EUR,66170,EN,PT,Netherlands,L,Netherlands,50,"Mathematics, Linux, Scala, GCP, Kubernetes",Bachelor,0,Consulting,2024-07-31,2024-09-24,2283,7.1,Cloud AI Solutions +AI01312,Research Scientist,112294,EUR,95450,SE,FT,France,M,France,50,"Python, Java, Hadoop, Deep Learning",PhD,6,Government,2024-09-17,2024-11-16,2496,7.4,Smart Analytics +AI01313,Autonomous Systems Engineer,118482,USD,118482,SE,FT,Finland,M,Portugal,50,"Kubernetes, Docker, NLP, Python, Deep Learning",Master,7,Finance,2024-02-01,2024-02-20,1250,7.6,Neural Networks Co +AI01314,NLP Engineer,76423,USD,76423,EN,PT,United States,M,United States,0,"SQL, Data Visualization, Scala, GCP",Associate,1,Consulting,2024-05-27,2024-07-17,2180,8.7,Autonomous Tech +AI01315,Computer Vision Engineer,66969,EUR,56924,MI,CT,Austria,S,Israel,0,"Python, TensorFlow, Spark, Deep Learning",Associate,2,Government,2024-06-29,2024-08-20,2048,8.5,Predictive Systems +AI01316,AI Architect,88996,USD,88996,MI,FL,Ireland,L,Ireland,100,"SQL, Mathematics, Python",Bachelor,4,Finance,2024-01-12,2024-02-03,2325,8.4,Smart Analytics +AI01317,AI Architect,67741,GBP,50806,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Spark, Computer Vision, PyTorch, Linux",Master,0,Manufacturing,2024-07-24,2024-08-18,808,8.6,Smart Analytics +AI01318,AI Architect,104123,CHF,93711,EN,FL,Switzerland,M,Switzerland,0,"TensorFlow, Computer Vision, NLP",Master,0,Automotive,2024-09-16,2024-10-12,1848,5.4,TechCorp Inc +AI01319,AI Specialist,52117,SGD,67752,EN,FL,Singapore,S,Singapore,50,"Kubernetes, GCP, Linux",PhD,1,Government,2025-03-20,2025-05-17,1881,8.5,Cognitive Computing +AI01320,AI Specialist,107002,USD,107002,EN,CT,Denmark,L,South Korea,100,"GCP, R, Tableau, Statistics, Data Visualization",Bachelor,1,Retail,2024-03-12,2024-04-20,2188,9.9,Algorithmic Solutions +AI01321,Head of AI,171421,JPY,18856310,EX,FT,Japan,S,Japan,0,"Scala, Computer Vision, Tableau, Statistics",Bachelor,12,Education,2025-02-26,2025-04-27,867,7.3,Quantum Computing Inc +AI01322,Principal Data Scientist,102160,USD,102160,SE,FL,Finland,M,Norway,50,"Kubernetes, Scala, Tableau, MLOps",Associate,5,Transportation,2024-12-16,2025-02-04,1617,9.4,Advanced Robotics +AI01323,Robotics Engineer,78797,GBP,59098,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, TensorFlow, R",Associate,0,Automotive,2024-10-11,2024-12-01,708,9.2,DeepTech Ventures +AI01324,Machine Learning Researcher,143483,CAD,179354,SE,CT,Canada,M,Malaysia,0,"Linux, Deep Learning, PyTorch, Mathematics",PhD,8,Education,2025-03-18,2025-04-08,2064,6.2,Machine Intelligence Group +AI01325,Autonomous Systems Engineer,224567,USD,224567,SE,FL,Denmark,L,India,0,"Spark, Linux, Tableau, Data Visualization",Bachelor,7,Automotive,2025-02-03,2025-03-24,1751,7,Smart Analytics +AI01326,Autonomous Systems Engineer,141545,AUD,191086,SE,FL,Australia,L,Australia,0,"Computer Vision, Mathematics, Spark",Bachelor,8,Automotive,2024-10-16,2024-11-09,2451,7.8,Digital Transformation LLC +AI01327,Data Engineer,56427,USD,56427,EN,FT,Israel,M,Hungary,0,"Kubernetes, Tableau, SQL",Bachelor,1,Transportation,2025-01-26,2025-04-07,838,6.1,Future Systems +AI01328,Robotics Engineer,90510,USD,90510,MI,CT,Norway,S,China,100,"SQL, Spark, Mathematics",Bachelor,4,Retail,2024-03-05,2024-04-01,2031,7.2,Future Systems +AI01329,Research Scientist,158669,USD,158669,EX,PT,Israel,S,Israel,100,"SQL, Computer Vision, Docker, AWS, PyTorch",Associate,19,Manufacturing,2024-08-12,2024-08-28,1226,7.8,Digital Transformation LLC +AI01330,AI Software Engineer,74539,JPY,8199290,EN,FT,Japan,S,South Korea,50,"GCP, Java, SQL, R, AWS",PhD,1,Media,2024-12-11,2024-12-30,746,5.1,Neural Networks Co +AI01331,Computer Vision Engineer,124395,EUR,105736,SE,FL,Netherlands,S,Russia,0,"Spark, Git, SQL, Python, TensorFlow",Master,9,Energy,2025-04-15,2025-06-10,2301,9.2,DataVision Ltd +AI01332,AI Research Scientist,174114,USD,174114,EX,PT,United States,M,United States,0,"Data Visualization, MLOps, Tableau, Python, Kubernetes",Master,10,Real Estate,2024-05-15,2024-06-13,2132,7,Digital Transformation LLC +AI01333,Autonomous Systems Engineer,321202,CHF,289082,EX,CT,Switzerland,M,Switzerland,0,"Scala, Linux, Computer Vision",Master,19,Telecommunications,2024-01-14,2024-03-27,1102,9.8,Advanced Robotics +AI01334,NLP Engineer,73469,USD,73469,MI,FL,Sweden,S,Sweden,0,"Python, Hadoop, TensorFlow",Associate,3,Media,2024-02-02,2024-04-08,1664,8.2,DataVision Ltd +AI01335,ML Ops Engineer,142197,USD,142197,SE,PT,Sweden,L,Finland,50,"R, PyTorch, NLP, GCP",PhD,8,Media,2025-03-31,2025-05-14,1349,7.3,Digital Transformation LLC +AI01336,Machine Learning Researcher,157699,EUR,134044,EX,PT,France,S,France,50,"Python, GCP, Scala",Bachelor,19,Consulting,2024-11-05,2024-12-03,1625,7.9,Cognitive Computing +AI01337,Research Scientist,101213,USD,101213,SE,CT,Finland,S,Finland,100,"SQL, Scala, Statistics, Git",Associate,9,Real Estate,2025-04-06,2025-04-28,801,5.1,Predictive Systems +AI01338,AI Architect,84729,USD,84729,MI,CT,Sweden,S,New Zealand,100,"Scala, Spark, Hadoop, Python",Master,3,Automotive,2024-04-07,2024-05-31,1053,9.3,TechCorp Inc +AI01339,Robotics Engineer,87739,CHF,78965,EN,CT,Switzerland,M,Switzerland,0,"R, SQL, Java, Statistics, Linux",Master,0,Finance,2024-10-09,2024-10-28,2211,10,AI Innovations +AI01340,Autonomous Systems Engineer,30121,USD,30121,EN,FL,China,M,Spain,50,"R, Docker, PyTorch",PhD,0,Manufacturing,2024-04-08,2024-06-19,1586,8.1,Digital Transformation LLC +AI01341,Machine Learning Engineer,100916,JPY,11100760,MI,CT,Japan,S,Japan,50,"Scala, Python, MLOps",Bachelor,2,Real Estate,2024-03-17,2024-05-15,2096,5.6,DeepTech Ventures +AI01342,Computer Vision Engineer,55277,USD,55277,EN,FL,Israel,S,Israel,50,"Git, GCP, Kubernetes, Computer Vision, R",Bachelor,0,Finance,2024-08-28,2024-09-24,1348,6.9,DeepTech Ventures +AI01343,ML Ops Engineer,113420,USD,113420,MI,PT,Ireland,L,Romania,0,"Python, TensorFlow, Tableau, MLOps",Master,4,Manufacturing,2025-02-04,2025-03-31,858,7.3,Digital Transformation LLC +AI01344,Machine Learning Engineer,50194,USD,50194,EN,FL,Finland,M,Finland,0,"SQL, Java, Python, Scala, Deep Learning",Bachelor,1,Automotive,2025-02-08,2025-04-11,664,8.1,DataVision Ltd +AI01345,Head of AI,98859,USD,98859,EX,CT,India,L,India,50,"Azure, Python, Kubernetes, Statistics, Deep Learning",Associate,14,Consulting,2024-04-25,2024-06-20,1997,9.2,Predictive Systems +AI01346,Deep Learning Engineer,195373,CHF,175836,SE,FL,Switzerland,M,Switzerland,100,"PyTorch, Git, Tableau",Associate,7,Finance,2025-02-21,2025-03-21,555,7.2,Cloud AI Solutions +AI01347,AI Software Engineer,150038,AUD,202551,SE,CT,Australia,M,Australia,100,"SQL, TensorFlow, Mathematics, Python",Master,8,Automotive,2024-04-26,2024-05-21,2430,5.8,Autonomous Tech +AI01348,AI Software Engineer,46960,USD,46960,EN,PT,South Korea,S,Chile,100,"NLP, Azure, Data Visualization",PhD,1,Government,2024-05-21,2024-07-18,2271,9.1,Autonomous Tech +AI01349,Research Scientist,256508,EUR,218032,EX,FL,Germany,L,Germany,0,"R, Data Visualization, Docker, Scala, Deep Learning",Associate,14,Government,2024-07-04,2024-08-28,1511,7,DeepTech Ventures +AI01350,Principal Data Scientist,123766,GBP,92825,MI,CT,United Kingdom,L,United Kingdom,50,"Python, TensorFlow, R, Computer Vision, PyTorch",Bachelor,4,Retail,2024-06-14,2024-07-20,868,5.9,Neural Networks Co +AI01351,Data Analyst,138655,EUR,117857,SE,PT,Germany,L,Germany,50,"Deep Learning, NLP, Kubernetes, Hadoop",Master,9,Technology,2024-03-10,2024-04-09,1039,6.2,Digital Transformation LLC +AI01352,AI Software Engineer,112307,EUR,95461,MI,FT,Netherlands,M,Vietnam,0,"Python, Azure, Linux, TensorFlow, Java",Associate,3,Government,2024-05-04,2024-06-30,1320,9.4,Future Systems +AI01353,AI Product Manager,75008,USD,75008,EX,FT,India,L,New Zealand,50,"PyTorch, TensorFlow, Spark, Tableau, Scala",Bachelor,15,Retail,2024-09-23,2024-10-29,1493,8,Algorithmic Solutions +AI01354,Robotics Engineer,72038,USD,72038,MI,CT,South Korea,S,South Korea,50,"Python, Docker, AWS, GCP",PhD,3,Energy,2024-05-01,2024-06-26,2322,5.3,DeepTech Ventures +AI01355,AI Software Engineer,141038,USD,141038,SE,CT,Finland,M,Finland,100,"Statistics, MLOps, Python, Linux, Deep Learning",Bachelor,6,Transportation,2025-04-06,2025-04-25,1720,7.3,Algorithmic Solutions +AI01356,AI Research Scientist,113496,USD,113496,SE,CT,Israel,S,Israel,50,"R, Spark, TensorFlow",PhD,9,Real Estate,2024-10-29,2024-11-13,542,8.3,Neural Networks Co +AI01357,Computer Vision Engineer,100144,EUR,85122,SE,FL,France,S,France,0,"Tableau, PyTorch, TensorFlow",PhD,8,Healthcare,2024-09-18,2024-10-22,1494,5.8,Cloud AI Solutions +AI01358,AI Research Scientist,210470,SGD,273611,EX,PT,Singapore,M,Singapore,0,"PyTorch, Azure, Hadoop, Java",Bachelor,12,Real Estate,2024-07-05,2024-07-25,1609,8.3,Autonomous Tech +AI01359,Head of AI,66974,CAD,83718,MI,FT,Canada,S,Canada,100,"Python, Docker, TensorFlow, PyTorch",Master,3,Media,2024-07-03,2024-08-14,2141,7.4,Future Systems +AI01360,Autonomous Systems Engineer,137007,EUR,116456,SE,FT,Netherlands,L,Malaysia,100,"Scala, Computer Vision, SQL, PyTorch, Azure",Associate,8,Government,2025-03-10,2025-05-02,1033,6.7,Cognitive Computing +AI01361,Machine Learning Engineer,80135,USD,80135,MI,CT,Ireland,S,Ireland,50,"Data Visualization, GCP, AWS, SQL, NLP",PhD,4,Government,2024-07-23,2024-10-01,2267,8.8,Smart Analytics +AI01362,Research Scientist,158546,EUR,134764,SE,FT,Netherlands,M,Netherlands,50,"SQL, Hadoop, R, Computer Vision, Docker",Associate,9,Manufacturing,2024-02-03,2024-04-09,2352,9.9,Algorithmic Solutions +AI01363,Deep Learning Engineer,194317,USD,194317,EX,FT,Denmark,M,Denmark,100,"Git, GCP, Tableau, Kubernetes",Bachelor,19,Energy,2024-03-31,2024-06-02,1493,7.2,Digital Transformation LLC +AI01364,Head of AI,83493,EUR,70969,MI,CT,Netherlands,M,Netherlands,50,"Java, Spark, GCP",Master,2,Automotive,2024-05-26,2024-06-10,2305,6.9,Predictive Systems +AI01365,Data Analyst,104222,USD,104222,EN,FT,United States,L,Malaysia,100,"Spark, SQL, Azure, Git, Hadoop",PhD,1,Government,2024-12-06,2025-01-01,1541,5.3,AI Innovations +AI01366,Autonomous Systems Engineer,49854,USD,49854,MI,CT,China,L,China,100,"Python, Hadoop, Computer Vision, Spark, Kubernetes",Master,4,Automotive,2025-01-06,2025-01-28,2345,6.9,Cloud AI Solutions +AI01367,Autonomous Systems Engineer,158519,CAD,198149,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, Mathematics, Hadoop, AWS",Bachelor,14,Government,2025-03-07,2025-04-26,2403,9.8,TechCorp Inc +AI01368,Autonomous Systems Engineer,180734,USD,180734,SE,PT,United States,L,United States,50,"Java, Python, Linux",Master,6,Technology,2024-02-12,2024-04-09,2239,6.3,Machine Intelligence Group +AI01369,ML Ops Engineer,261993,USD,261993,EX,PT,Ireland,L,Russia,0,"SQL, GCP, Mathematics, NLP",Master,11,Telecommunications,2025-04-11,2025-05-10,2341,5.4,Cognitive Computing +AI01370,Robotics Engineer,98054,USD,98054,SE,FT,Finland,M,Finland,0,"PyTorch, SQL, Git, MLOps, AWS",Associate,9,Gaming,2024-01-08,2024-03-04,950,9.8,DataVision Ltd +AI01371,AI Product Manager,82903,USD,82903,MI,PT,South Korea,M,South Korea,50,"Mathematics, Docker, NLP",Bachelor,4,Gaming,2024-12-24,2025-03-05,2095,8.2,Algorithmic Solutions +AI01372,AI Software Engineer,121557,USD,121557,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Scala, Statistics, GCP",PhD,4,Education,2024-08-27,2024-10-09,1642,8.2,Cognitive Computing +AI01373,Data Analyst,172640,USD,172640,SE,FT,Norway,S,Norway,50,"Linux, Kubernetes, SQL",PhD,6,Manufacturing,2024-11-08,2024-12-31,1912,6.7,DataVision Ltd +AI01374,AI Product Manager,122704,EUR,104298,SE,FT,France,M,France,50,"Azure, Tableau, SQL, GCP, Git",PhD,9,Retail,2024-05-24,2024-07-10,1627,9.2,Future Systems +AI01375,Deep Learning Engineer,60832,JPY,6691520,EN,CT,Japan,S,Japan,0,"Tableau, Java, Python, Azure",Bachelor,1,Transportation,2024-06-07,2024-08-17,2416,5.8,AI Innovations +AI01376,AI Research Scientist,134265,USD,134265,EX,FL,South Korea,L,South Korea,0,"Kubernetes, GCP, Mathematics, AWS",Associate,19,Media,2024-09-27,2024-11-06,635,7.2,Cloud AI Solutions +AI01377,Machine Learning Engineer,65618,USD,65618,EN,FT,Denmark,S,Thailand,100,"R, Linux, Hadoop, Git, Computer Vision",Bachelor,1,Gaming,2025-03-15,2025-04-08,508,5.4,Neural Networks Co +AI01378,NLP Engineer,104745,GBP,78559,SE,FL,United Kingdom,S,Denmark,100,"Docker, Linux, Data Visualization, R",Bachelor,7,Government,2025-02-01,2025-03-13,1749,9.3,DataVision Ltd +AI01379,AI Software Engineer,53253,GBP,39940,EN,FL,United Kingdom,S,United Kingdom,50,"PyTorch, Spark, TensorFlow, Azure, Hadoop",Master,0,Technology,2025-04-11,2025-06-03,652,9,Cloud AI Solutions +AI01380,Computer Vision Engineer,166691,JPY,18336010,EX,PT,Japan,S,Japan,100,"Mathematics, Deep Learning, Scala, R, PyTorch",Master,14,Automotive,2024-05-17,2024-06-10,1849,7,DeepTech Ventures +AI01381,Computer Vision Engineer,146267,CAD,182834,EX,PT,Canada,M,Canada,0,"Scala, R, Docker",PhD,10,Gaming,2025-01-10,2025-02-13,2428,7,DeepTech Ventures +AI01382,AI Consultant,97969,USD,97969,SE,FT,Finland,M,Finland,0,"Spark, PyTorch, MLOps, Tableau",PhD,9,Energy,2024-06-09,2024-07-07,530,9.7,Advanced Robotics +AI01383,Principal Data Scientist,206614,CAD,258268,EX,PT,Canada,M,Ireland,100,"Hadoop, R, Kubernetes",Bachelor,14,Government,2024-02-11,2024-03-20,874,6.2,Machine Intelligence Group +AI01384,Data Analyst,78327,EUR,66578,MI,FT,Austria,M,Austria,0,"Data Visualization, NLP, Mathematics",PhD,3,Consulting,2024-06-29,2024-08-23,2076,5.7,AI Innovations +AI01385,Robotics Engineer,70510,EUR,59934,EN,PT,Austria,L,Turkey,0,"R, Python, TensorFlow, Tableau, Statistics",Bachelor,0,Gaming,2024-08-28,2024-09-29,912,7.1,DataVision Ltd +AI01386,Data Analyst,41791,USD,41791,SE,FT,India,M,India,100,"Linux, SQL, Mathematics, Hadoop",Bachelor,7,Media,2024-12-02,2025-01-11,2227,9.7,Algorithmic Solutions +AI01387,AI Consultant,115800,EUR,98430,MI,FL,Austria,L,Luxembourg,50,"Python, TensorFlow, Spark, PyTorch",Bachelor,3,Media,2025-02-02,2025-03-29,1284,7.9,Digital Transformation LLC +AI01388,Machine Learning Engineer,113860,USD,113860,SE,PT,Finland,L,Sweden,100,"SQL, PyTorch, Python, Docker",Associate,6,Healthcare,2024-05-02,2024-07-11,1096,8.5,AI Innovations +AI01389,Data Analyst,181595,USD,181595,SE,FT,United States,L,United States,100,"Docker, PyTorch, Data Visualization, Hadoop, Spark",Master,7,Automotive,2024-12-31,2025-03-10,1181,8.7,Digital Transformation LLC +AI01390,AI Product Manager,157567,EUR,133932,EX,FT,Austria,L,Israel,50,"Azure, Hadoop, Java, Deep Learning",Associate,18,Finance,2024-01-14,2024-02-22,2191,5.6,Quantum Computing Inc +AI01391,Autonomous Systems Engineer,124885,EUR,106152,MI,FL,Netherlands,L,Netherlands,0,"Linux, AWS, Spark, SQL, PyTorch",PhD,4,Automotive,2024-12-11,2025-01-11,1416,9.2,Smart Analytics +AI01392,NLP Engineer,123910,USD,123910,EX,FL,Ireland,S,Ireland,50,"PyTorch, Tableau, Computer Vision, Git",Bachelor,16,Transportation,2024-09-22,2024-11-24,1656,8,Neural Networks Co +AI01393,AI Specialist,137838,USD,137838,SE,FL,Sweden,L,Belgium,0,"Mathematics, MLOps, Tableau, Kubernetes, Python",PhD,8,Gaming,2024-07-12,2024-08-07,732,7.8,Cloud AI Solutions +AI01394,Data Engineer,313735,USD,313735,EX,FT,Denmark,M,Denmark,0,"NLP, Linux, Kubernetes",Associate,12,Healthcare,2024-12-16,2025-01-06,1940,6.7,Neural Networks Co +AI01395,Computer Vision Engineer,96380,USD,96380,EN,PT,Denmark,M,Ireland,50,"Kubernetes, Python, Statistics",Bachelor,0,Media,2024-10-12,2024-11-30,1399,9,Digital Transformation LLC +AI01396,Data Engineer,63171,EUR,53695,EN,CT,Netherlands,M,Netherlands,100,"Scala, Hadoop, AWS",Bachelor,0,Automotive,2024-12-24,2025-03-03,561,8.8,AI Innovations +AI01397,AI Specialist,123969,USD,123969,SE,FT,Sweden,S,Sweden,0,"SQL, PyTorch, GCP",Bachelor,9,Energy,2025-04-01,2025-04-22,1527,9.8,Quantum Computing Inc +AI01398,Data Analyst,54611,EUR,46419,EN,CT,France,M,France,0,"Python, Linux, TensorFlow, Computer Vision, PyTorch",PhD,0,Technology,2024-12-11,2024-12-26,865,9,Machine Intelligence Group +AI01399,Machine Learning Engineer,119705,USD,119705,MI,PT,Denmark,L,Switzerland,0,"MLOps, Python, R, AWS, Docker",Bachelor,3,Education,2024-03-23,2024-06-02,1556,7.2,Quantum Computing Inc +AI01400,Autonomous Systems Engineer,173697,CHF,156327,SE,FL,Switzerland,S,China,50,"Python, AWS, Scala",Associate,9,Media,2025-01-09,2025-03-23,927,8.2,Algorithmic Solutions +AI01401,Data Scientist,144553,AUD,195147,SE,CT,Australia,L,South Korea,0,"Data Visualization, R, Linux, MLOps",PhD,6,Telecommunications,2024-07-22,2024-09-21,1806,5.8,AI Innovations +AI01402,Research Scientist,76409,GBP,57307,MI,FL,United Kingdom,S,Brazil,50,"AWS, Hadoop, PyTorch",Master,2,Government,2024-10-29,2024-11-12,2125,8.3,DataVision Ltd +AI01403,NLP Engineer,105022,AUD,141780,SE,FT,Australia,M,Japan,0,"Mathematics, Python, Data Visualization, Deep Learning, GCP",PhD,8,Government,2024-01-11,2024-03-12,1947,8.4,Cognitive Computing +AI01404,Data Engineer,147919,AUD,199691,SE,PT,Australia,L,Australia,0,"TensorFlow, Linux, Azure, Mathematics",Bachelor,8,Manufacturing,2024-05-20,2024-07-28,1479,7.6,Neural Networks Co +AI01405,Data Engineer,105054,CHF,94549,EN,CT,Switzerland,L,Switzerland,100,"Azure, Java, Data Visualization",Master,0,Technology,2024-03-06,2024-04-21,740,5.3,Advanced Robotics +AI01406,AI Architect,168883,USD,168883,EX,PT,South Korea,S,South Korea,50,"PyTorch, Spark, R, TensorFlow",Bachelor,17,Government,2024-04-02,2024-04-28,1976,5.5,TechCorp Inc +AI01407,AI Architect,54905,USD,54905,EN,PT,Finland,S,Malaysia,50,"SQL, Python, Azure, Hadoop, Mathematics",PhD,0,Government,2025-02-24,2025-03-31,1770,6.6,Machine Intelligence Group +AI01408,Data Scientist,73214,USD,73214,EX,CT,China,M,China,50,"SQL, Statistics, PyTorch, AWS",Bachelor,19,Government,2024-01-14,2024-03-03,1326,8.6,Future Systems +AI01409,Computer Vision Engineer,75589,USD,75589,MI,PT,South Korea,S,South Korea,50,"Python, Statistics, Computer Vision, Linux",Bachelor,4,Automotive,2024-02-11,2024-04-16,2026,7.2,Digital Transformation LLC +AI01410,Robotics Engineer,104795,CHF,94316,EN,CT,Switzerland,M,Japan,50,"Deep Learning, TensorFlow, Python, Linux, Java",Master,1,Telecommunications,2025-04-06,2025-05-28,1865,6.6,Future Systems +AI01411,AI Architect,19456,USD,19456,EN,CT,India,S,India,0,"Java, GCP, AWS, Deep Learning, Spark",Associate,1,Automotive,2024-02-24,2024-03-11,1072,9.7,Autonomous Tech +AI01412,Data Engineer,212599,EUR,180709,EX,FT,Austria,S,Austria,50,"Python, Docker, SQL, Linux",Master,13,Automotive,2024-07-11,2024-07-27,1697,10,DeepTech Ventures +AI01413,AI Research Scientist,63226,JPY,6954860,EN,CT,Japan,M,Japan,0,"Hadoop, Python, TensorFlow, Deep Learning",Bachelor,1,Government,2024-10-04,2024-12-07,963,6.7,Cloud AI Solutions +AI01414,AI Architect,188891,USD,188891,SE,PT,United States,L,Portugal,0,"Python, SQL, Linux",Master,5,Automotive,2024-01-16,2024-03-01,2133,5.8,DeepTech Ventures +AI01415,Head of AI,45335,USD,45335,EN,FT,South Korea,S,South Korea,100,"NLP, SQL, Java, MLOps, Kubernetes",Bachelor,0,Manufacturing,2024-06-01,2024-06-17,1381,6.3,Predictive Systems +AI01416,NLP Engineer,114078,GBP,85559,MI,CT,United Kingdom,M,United Kingdom,50,"Java, TensorFlow, GCP",PhD,4,Technology,2024-05-01,2024-05-26,1203,6.5,Digital Transformation LLC +AI01417,AI Software Engineer,221905,USD,221905,EX,FL,Norway,L,Norway,0,"Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-11-19,2024-12-05,1585,5.9,Algorithmic Solutions +AI01418,Principal Data Scientist,34898,USD,34898,MI,FL,China,M,China,100,"Kubernetes, Linux, Git, SQL, R",PhD,4,Retail,2025-01-17,2025-02-14,1878,7.1,AI Innovations +AI01419,Autonomous Systems Engineer,288283,USD,288283,EX,FL,Ireland,L,Vietnam,50,"Tableau, Statistics, Spark, Kubernetes, Git",Master,17,Consulting,2024-01-31,2024-03-21,882,7.1,Cloud AI Solutions +AI01420,Robotics Engineer,75188,USD,75188,MI,FT,Ireland,M,Ukraine,50,"Python, Git, Azure",Associate,3,Government,2025-04-11,2025-05-26,1123,9,TechCorp Inc +AI01421,Principal Data Scientist,87149,USD,87149,EN,FL,Denmark,S,Italy,50,"Azure, Kubernetes, Docker, SQL, Data Visualization",Associate,1,Real Estate,2024-11-02,2024-11-18,1009,7.4,TechCorp Inc +AI01422,Robotics Engineer,91150,USD,91150,MI,CT,Norway,S,Norway,50,"Java, Python, Computer Vision",PhD,4,Retail,2024-06-05,2024-08-04,2308,7,Quantum Computing Inc +AI01423,Research Scientist,126040,AUD,170154,SE,FL,Australia,S,Australia,50,"Docker, SQL, Mathematics, Spark",Master,9,Manufacturing,2024-05-07,2024-06-21,2052,9.9,DeepTech Ventures +AI01424,AI Research Scientist,187737,USD,187737,EX,FT,Sweden,L,Sweden,0,"Java, R, Mathematics, Computer Vision",PhD,15,Government,2024-03-30,2024-04-25,1706,7,Machine Intelligence Group +AI01425,AI Product Manager,125535,USD,125535,MI,PT,United States,M,United States,0,"Hadoop, PyTorch, Scala, GCP",Bachelor,3,Retail,2024-06-17,2024-07-16,2147,7.7,TechCorp Inc +AI01426,AI Product Manager,373536,USD,373536,EX,FL,Norway,L,Norway,100,"NLP, Kubernetes, Spark",Master,10,Technology,2025-03-20,2025-05-22,730,9.4,DeepTech Ventures +AI01427,Deep Learning Engineer,100732,CHF,90659,EN,FT,Switzerland,M,Switzerland,100,"Tableau, Python, Hadoop, Kubernetes",PhD,1,Media,2024-06-16,2024-07-30,1200,10,Predictive Systems +AI01428,Data Engineer,212371,GBP,159278,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Kubernetes, Tableau, Hadoop, Scala",Bachelor,15,Consulting,2025-03-06,2025-03-20,615,9.5,Autonomous Tech +AI01429,AI Software Engineer,65466,EUR,55646,EN,PT,Germany,L,Germany,0,"Mathematics, PyTorch, Statistics",Master,1,Finance,2024-03-25,2024-05-04,1943,8.2,Quantum Computing Inc +AI01430,Computer Vision Engineer,109204,SGD,141965,MI,PT,Singapore,M,Nigeria,50,"Mathematics, Data Visualization, MLOps, Tableau",Associate,3,Retail,2024-09-15,2024-11-16,1841,5.3,AI Innovations +AI01431,Data Engineer,72736,JPY,8000960,MI,CT,Japan,S,Germany,50,"R, Python, Data Visualization, PyTorch",Associate,2,Telecommunications,2025-02-13,2025-03-21,1794,8.9,AI Innovations +AI01432,Autonomous Systems Engineer,20520,USD,20520,EN,FL,India,M,Israel,100,"R, Spark, Hadoop, Kubernetes, GCP",Associate,0,Gaming,2024-07-21,2024-08-07,2201,8.9,Cloud AI Solutions +AI01433,AI Architect,158930,USD,158930,EX,PT,Ireland,M,Ireland,100,"Spark, PyTorch, Mathematics",PhD,19,Transportation,2025-01-29,2025-03-23,965,7.9,DeepTech Ventures +AI01434,Principal Data Scientist,76074,CHF,68467,EN,FT,Switzerland,M,Switzerland,100,"Scala, Spark, MLOps",Master,0,Gaming,2024-06-14,2024-07-22,2169,6,Cognitive Computing +AI01435,Machine Learning Researcher,59343,EUR,50442,EN,FT,France,S,France,0,"NLP, Mathematics, Kubernetes, Computer Vision, Tableau",Bachelor,1,Government,2024-03-29,2024-05-11,690,8.2,Advanced Robotics +AI01436,Data Scientist,104447,USD,104447,MI,CT,United States,S,United States,100,"Deep Learning, Data Visualization, AWS, TensorFlow, Scala",Bachelor,2,Technology,2024-12-10,2025-02-15,1675,8.4,Neural Networks Co +AI01437,AI Software Engineer,43120,USD,43120,MI,PT,China,M,China,50,"AWS, Docker, NLP",Bachelor,4,Automotive,2024-03-04,2024-04-21,1871,8.9,DataVision Ltd +AI01438,Machine Learning Engineer,219852,EUR,186874,EX,FL,Austria,L,Austria,100,"Hadoop, Kubernetes, TensorFlow, GCP",Associate,14,Healthcare,2024-01-11,2024-03-11,1760,6.6,DataVision Ltd +AI01439,Data Engineer,40164,USD,40164,SE,CT,India,S,India,0,"Scala, Kubernetes, Git, Docker",Bachelor,7,Telecommunications,2024-11-21,2025-01-23,2230,5.9,Digital Transformation LLC +AI01440,Data Analyst,164110,SGD,213343,EX,FT,Singapore,S,Singapore,50,"SQL, Git, GCP",Associate,15,Gaming,2025-01-04,2025-02-01,1042,7.8,Future Systems +AI01441,Machine Learning Researcher,33846,USD,33846,MI,PT,China,S,China,100,"PyTorch, Hadoop, Statistics, AWS, Computer Vision",Bachelor,2,Transportation,2024-03-06,2024-03-22,804,6.8,Digital Transformation LLC +AI01442,Data Engineer,126266,USD,126266,MI,PT,Sweden,L,Sweden,100,"PyTorch, Spark, TensorFlow",Master,4,Energy,2024-06-28,2024-07-28,1765,6.6,Machine Intelligence Group +AI01443,Head of AI,98327,USD,98327,MI,PT,United States,L,United States,50,"R, Data Visualization, Mathematics",Associate,4,Education,2024-09-12,2024-10-04,1849,5.1,Neural Networks Co +AI01444,Data Scientist,77366,GBP,58025,MI,PT,United Kingdom,S,Japan,50,"Python, TensorFlow, NLP, Azure, AWS",PhD,3,Automotive,2024-06-19,2024-08-04,2357,5.6,Cognitive Computing +AI01445,ML Ops Engineer,76129,USD,76129,EN,FL,Denmark,S,Indonesia,50,"Hadoop, PyTorch, MLOps",Master,0,Education,2024-12-01,2024-12-15,788,7.8,Cloud AI Solutions +AI01446,AI Product Manager,134331,CHF,120898,MI,PT,Switzerland,L,Switzerland,100,"Java, Mathematics, TensorFlow",Associate,2,Energy,2024-01-11,2024-02-19,842,10,DeepTech Ventures +AI01447,Data Engineer,56083,EUR,47671,EN,FL,Austria,M,Austria,0,"Python, Statistics, SQL, R, Linux",Master,1,Transportation,2024-07-24,2024-08-16,1613,6.4,AI Innovations +AI01448,Robotics Engineer,147444,USD,147444,EX,CT,Finland,S,Finland,0,"Scala, Spark, Java",PhD,15,Technology,2025-04-18,2025-06-06,2271,5.6,Cloud AI Solutions +AI01449,AI Product Manager,92983,USD,92983,EN,CT,Norway,S,Ghana,50,"TensorFlow, Scala, GCP, Git",PhD,0,Education,2025-01-04,2025-01-26,1036,7.8,Neural Networks Co +AI01450,ML Ops Engineer,83859,EUR,71280,EN,FL,Austria,L,Austria,50,"Tableau, Hadoop, PyTorch",Bachelor,1,Real Estate,2025-01-18,2025-03-31,2435,8.2,Predictive Systems +AI01451,NLP Engineer,84786,EUR,72068,MI,FL,Germany,M,Ukraine,0,"Java, Linux, Statistics, Git",Master,2,Transportation,2025-02-04,2025-03-18,1912,9.2,Digital Transformation LLC +AI01452,Computer Vision Engineer,154829,EUR,131605,EX,CT,Germany,S,Kenya,100,"Tableau, AWS, Hadoop, Kubernetes, Git",Bachelor,11,Energy,2024-08-21,2024-10-30,2309,5.4,DataVision Ltd +AI01453,Machine Learning Engineer,216967,GBP,162725,EX,FT,United Kingdom,S,Chile,0,"R, Scala, NLP, Git, Docker",Bachelor,12,Education,2024-07-18,2024-09-29,1500,8.6,Future Systems +AI01454,Computer Vision Engineer,90170,USD,90170,MI,PT,Ireland,L,Ireland,100,"Git, TensorFlow, Deep Learning",Bachelor,3,Transportation,2024-04-12,2024-05-08,2067,5.6,TechCorp Inc +AI01455,AI Software Engineer,59279,SGD,77063,EN,PT,Singapore,M,Singapore,0,"Python, TensorFlow, PyTorch, Linux",Associate,1,Education,2025-02-22,2025-04-02,2481,9.2,Cloud AI Solutions +AI01456,AI Specialist,85165,USD,85165,EX,FL,China,L,China,100,"MLOps, Spark, Azure, TensorFlow",Bachelor,19,Automotive,2025-03-11,2025-04-29,1813,6.6,Digital Transformation LLC +AI01457,Machine Learning Researcher,58417,EUR,49654,EN,PT,Netherlands,S,United States,100,"Spark, Docker, GCP, Statistics, Python",PhD,1,Technology,2024-07-22,2024-09-17,1842,8.4,Smart Analytics +AI01458,Research Scientist,160456,EUR,136388,EX,CT,Netherlands,M,Netherlands,100,"Python, TensorFlow, MLOps, Spark, R",Master,11,Manufacturing,2024-04-08,2024-05-27,1814,5.4,Autonomous Tech +AI01459,Robotics Engineer,29590,USD,29590,EN,FT,China,S,South Korea,0,"Linux, Data Visualization, Java, Hadoop, NLP",Bachelor,1,Retail,2024-06-10,2024-08-07,1355,5.4,TechCorp Inc +AI01460,Deep Learning Engineer,242489,GBP,181867,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, Hadoop, Python, Mathematics, Docker",Bachelor,19,Telecommunications,2024-08-14,2024-09-04,985,5.8,Algorithmic Solutions +AI01461,ML Ops Engineer,136042,GBP,102032,SE,FT,United Kingdom,S,Austria,0,"Scala, Kubernetes, Linux, AWS",Bachelor,8,Gaming,2024-07-19,2024-09-08,2139,8.7,Future Systems +AI01462,AI Software Engineer,104200,CAD,130250,SE,FT,Canada,M,Canada,100,"Linux, Kubernetes, Scala",Master,9,Gaming,2025-03-26,2025-05-11,2429,6.3,Advanced Robotics +AI01463,Principal Data Scientist,137878,EUR,117196,SE,CT,Germany,L,Latvia,50,"R, SQL, Tableau, MLOps, Kubernetes",Master,7,Manufacturing,2025-03-10,2025-03-31,640,7.2,Cognitive Computing +AI01464,ML Ops Engineer,187710,USD,187710,SE,PT,Denmark,M,Denmark,50,"Git, NLP, SQL",Bachelor,8,Consulting,2025-02-15,2025-03-25,1597,7.4,Algorithmic Solutions +AI01465,AI Software Engineer,50439,USD,50439,SE,CT,India,M,India,100,"Spark, Python, TensorFlow, Statistics, Java",Master,7,Telecommunications,2024-01-08,2024-03-03,2331,7.7,Algorithmic Solutions +AI01466,AI Architect,29300,USD,29300,EN,FT,India,L,India,50,"Tableau, R, MLOps",PhD,1,Media,2024-11-03,2025-01-01,2378,8.5,Algorithmic Solutions +AI01467,Machine Learning Engineer,93689,USD,93689,EX,FT,China,S,China,0,"Python, TensorFlow, Mathematics, Kubernetes, Docker",Associate,18,Real Estate,2024-04-02,2024-05-26,2251,8.3,Smart Analytics +AI01468,Data Analyst,182500,USD,182500,EX,FL,United States,M,United States,0,"Mathematics, MLOps, Azure",Associate,16,Automotive,2024-11-22,2024-12-29,1397,9.6,Neural Networks Co +AI01469,Robotics Engineer,149041,AUD,201205,SE,FL,Australia,L,Australia,0,"PyTorch, TensorFlow, Scala, Git",PhD,8,Education,2025-03-10,2025-04-23,851,7.2,Digital Transformation LLC +AI01470,Computer Vision Engineer,43748,EUR,37186,EN,PT,France,S,Mexico,50,"Deep Learning, Java, SQL, Git, Docker",PhD,0,Education,2024-12-18,2025-01-30,692,9.5,AI Innovations +AI01471,Principal Data Scientist,54185,EUR,46057,EN,FT,Germany,S,India,0,"Computer Vision, PyTorch, Scala, GCP",Master,0,Telecommunications,2025-03-18,2025-05-29,755,6.8,TechCorp Inc +AI01472,NLP Engineer,69436,USD,69436,EX,PT,India,M,India,100,"Data Visualization, Kubernetes, Python",Associate,19,Automotive,2024-11-10,2024-12-04,748,8.4,Neural Networks Co +AI01473,Data Analyst,103188,USD,103188,EN,PT,United States,L,United States,0,"Git, Spark, Python, Java, GCP",PhD,1,Transportation,2024-03-24,2024-04-24,1596,5.6,Smart Analytics +AI01474,AI Research Scientist,116739,CHF,105065,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Java, Hadoop",Bachelor,0,Education,2025-01-21,2025-02-11,2191,6.3,Future Systems +AI01475,Deep Learning Engineer,73367,EUR,62362,EN,FL,Austria,M,Austria,0,"AWS, SQL, Tableau, PyTorch",Bachelor,1,Gaming,2024-11-30,2024-12-30,521,6.3,Predictive Systems +AI01476,Data Engineer,72979,JPY,8027690,EN,CT,Japan,S,Japan,50,"PyTorch, R, Docker, GCP, Azure",Associate,1,Retail,2025-02-21,2025-03-27,2262,6.5,Neural Networks Co +AI01477,Data Engineer,193939,USD,193939,EX,PT,Israel,M,Israel,100,"TensorFlow, Python, Hadoop, Tableau, Data Visualization",Bachelor,12,Technology,2025-01-28,2025-03-24,1382,8.6,DeepTech Ventures +AI01478,Research Scientist,151333,USD,151333,EX,FL,Ireland,M,Ireland,50,"Kubernetes, R, Statistics, GCP, Scala",Master,19,Gaming,2025-03-04,2025-05-04,503,5.8,Cognitive Computing +AI01479,Data Scientist,63229,USD,63229,SE,CT,China,S,China,100,"Scala, Java, Statistics, AWS, Kubernetes",Associate,6,Education,2024-12-17,2025-01-21,2342,9.8,Cognitive Computing +AI01480,Principal Data Scientist,188397,CHF,169557,SE,FT,Switzerland,S,Netherlands,50,"Git, PyTorch, AWS, Docker, GCP",Master,7,Healthcare,2024-09-02,2024-10-31,1198,9.6,AI Innovations +AI01481,Robotics Engineer,102987,USD,102987,MI,FT,Denmark,M,Denmark,0,"Python, GCP, MLOps, Azure, Hadoop",PhD,4,Retail,2024-07-28,2024-10-05,1017,6.5,DataVision Ltd +AI01482,AI Specialist,226210,USD,226210,SE,FT,Denmark,L,Denmark,50,"PyTorch, Scala, TensorFlow, AWS, Deep Learning",PhD,9,Manufacturing,2024-02-15,2024-03-29,2494,5.6,Future Systems +AI01483,AI Architect,18309,USD,18309,EN,FL,India,S,India,100,"PyTorch, Deep Learning, TensorFlow",Associate,0,Media,2024-10-14,2024-12-12,1247,7.6,DeepTech Ventures +AI01484,AI Software Engineer,210459,USD,210459,EX,CT,Israel,S,Israel,0,"Python, Computer Vision, NLP, Azure, Java",Master,17,Government,2025-02-19,2025-04-26,898,6.9,Advanced Robotics +AI01485,Robotics Engineer,70962,USD,70962,SE,CT,China,M,China,0,"Computer Vision, SQL, Linux",Associate,6,Consulting,2025-02-10,2025-03-22,1509,5.3,Machine Intelligence Group +AI01486,AI Research Scientist,71103,EUR,60438,MI,PT,Netherlands,S,New Zealand,0,"R, AWS, Kubernetes, Linux, Mathematics",Bachelor,3,Healthcare,2024-06-04,2024-08-16,1863,8.7,Predictive Systems +AI01487,Computer Vision Engineer,94344,USD,94344,EN,FT,Denmark,M,Argentina,50,"AWS, Tableau, SQL, PyTorch",Master,0,Education,2024-08-31,2024-09-27,1961,8.1,Predictive Systems +AI01488,Autonomous Systems Engineer,31310,USD,31310,EN,FT,China,M,China,100,"Tableau, Kubernetes, Scala",Bachelor,0,Healthcare,2025-03-16,2025-04-20,712,6.8,DataVision Ltd +AI01489,AI Product Manager,186865,USD,186865,EX,PT,Ireland,L,Ireland,100,"Data Visualization, Python, TensorFlow, AWS",PhD,17,Technology,2024-06-07,2024-08-14,1906,8,Cognitive Computing +AI01490,AI Product Manager,22689,USD,22689,EN,CT,India,S,India,50,"Deep Learning, SQL, MLOps, Data Visualization, Git",Bachelor,0,Finance,2024-08-20,2024-09-29,835,5.1,DataVision Ltd +AI01491,AI Product Manager,71875,USD,71875,EX,FT,China,M,China,50,"Hadoop, SQL, Data Visualization, TensorFlow",PhD,17,Healthcare,2024-01-30,2024-03-22,2427,8.7,DataVision Ltd +AI01492,AI Specialist,91093,USD,91093,EN,FT,Denmark,M,Denmark,50,"Tableau, SQL, Python",Master,1,Finance,2024-07-07,2024-07-22,1322,7.4,Cloud AI Solutions +AI01493,NLP Engineer,59983,USD,59983,MI,CT,South Korea,S,Colombia,50,"SQL, PyTorch, Tableau, Kubernetes",Master,3,Finance,2025-02-22,2025-04-04,1654,9.6,Smart Analytics +AI01494,AI Specialist,315917,CHF,284325,EX,FL,Switzerland,M,Switzerland,50,"Statistics, SQL, Tableau, Computer Vision, Docker",PhD,13,Media,2024-01-21,2024-03-01,870,7.4,Predictive Systems +AI01495,Robotics Engineer,49015,USD,49015,EN,FT,Ireland,S,Ireland,100,"Scala, Data Visualization, SQL, MLOps",Bachelor,1,Healthcare,2024-11-30,2025-01-28,920,5.1,Predictive Systems +AI01496,NLP Engineer,45174,USD,45174,EN,CT,South Korea,M,South Korea,50,"Python, Scala, SQL",Associate,0,Consulting,2024-07-27,2024-08-17,857,5.7,Quantum Computing Inc +AI01497,Head of AI,124375,USD,124375,MI,FL,Norway,L,Norway,0,"SQL, Computer Vision, Git, GCP, PyTorch",Master,3,Transportation,2024-10-22,2025-01-01,2017,6.1,TechCorp Inc +AI01498,Principal Data Scientist,24919,USD,24919,EN,CT,India,M,Indonesia,0,"TensorFlow, Tableau, GCP",Associate,0,Gaming,2024-07-25,2024-08-18,2434,7.3,Predictive Systems +AI01499,AI Architect,103196,EUR,87717,SE,FL,Austria,M,Austria,50,"SQL, Java, Kubernetes, Deep Learning",Master,9,Automotive,2025-04-08,2025-06-02,2102,8,DataVision Ltd +AI01500,Computer Vision Engineer,101200,USD,101200,EN,FL,Norway,M,Norway,100,"SQL, Computer Vision, PyTorch, Git, Tableau",Bachelor,1,Government,2024-11-04,2024-11-21,2344,6.9,Advanced Robotics +AI01501,Data Scientist,146547,USD,146547,SE,FT,Finland,L,Canada,100,"TensorFlow, NLP, Mathematics, Tableau, Kubernetes",Bachelor,9,Automotive,2024-10-30,2024-12-27,669,6.9,Machine Intelligence Group +AI01502,Autonomous Systems Engineer,72296,USD,72296,SE,CT,China,L,China,50,"Scala, AWS, NLP, Git, Python",Associate,8,Automotive,2025-03-21,2025-05-14,1029,9.8,Algorithmic Solutions +AI01503,ML Ops Engineer,63430,USD,63430,EN,FL,United States,S,Thailand,50,"GCP, Deep Learning, PyTorch, AWS",PhD,0,Automotive,2024-11-14,2025-01-08,2301,6.9,Machine Intelligence Group +AI01504,Computer Vision Engineer,266480,USD,266480,EX,FT,Israel,L,Israel,100,"SQL, Python, Tableau, Statistics",Bachelor,16,Consulting,2024-12-02,2025-01-20,1350,6.4,Predictive Systems +AI01505,Computer Vision Engineer,115622,EUR,98279,SE,CT,Austria,S,Austria,0,"Spark, Hadoop, Data Visualization, MLOps, Azure",Master,6,Transportation,2024-07-26,2024-08-18,589,7.9,DataVision Ltd +AI01506,NLP Engineer,59313,USD,59313,SE,FT,India,L,Philippines,0,"Data Visualization, GCP, Linux, Computer Vision",Master,7,Manufacturing,2024-12-26,2025-02-16,901,7.3,AI Innovations +AI01507,Research Scientist,106901,EUR,90866,MI,FL,Germany,L,Germany,50,"TensorFlow, Python, Statistics",PhD,3,Manufacturing,2025-04-14,2025-06-23,746,5.8,Smart Analytics +AI01508,NLP Engineer,179377,EUR,152470,EX,CT,Netherlands,S,Nigeria,0,"Data Visualization, GCP, Scala, R, AWS",Associate,11,Technology,2024-09-21,2024-10-23,1996,6.3,Algorithmic Solutions +AI01509,Data Engineer,98356,USD,98356,MI,CT,Sweden,M,Sweden,0,"NLP, PyTorch, Scala, Deep Learning",Associate,2,Technology,2024-12-12,2025-01-17,1771,6,Autonomous Tech +AI01510,Data Analyst,143818,SGD,186963,SE,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, TensorFlow, Statistics",Bachelor,8,Manufacturing,2024-05-16,2024-07-14,807,8,DeepTech Ventures +AI01511,AI Research Scientist,148765,CAD,185956,SE,PT,Canada,L,Canada,50,"Computer Vision, PyTorch, SQL",Associate,6,Gaming,2025-04-28,2025-07-10,1542,6.4,Quantum Computing Inc +AI01512,Research Scientist,88116,USD,88116,EN,FT,Norway,S,Singapore,0,"R, NLP, GCP",PhD,1,Telecommunications,2025-03-14,2025-03-29,2478,6.7,Predictive Systems +AI01513,Robotics Engineer,49914,USD,49914,EN,FL,South Korea,S,South Korea,50,"Hadoop, Python, Computer Vision",PhD,0,Telecommunications,2024-01-30,2024-04-11,1057,6.9,Quantum Computing Inc +AI01514,Autonomous Systems Engineer,39015,USD,39015,EN,PT,China,L,China,0,"R, Linux, SQL, PyTorch",PhD,0,Automotive,2024-10-27,2024-12-10,1371,6.3,Digital Transformation LLC +AI01515,AI Architect,88810,GBP,66608,MI,FL,United Kingdom,L,Russia,0,"Tableau, Scala, Spark",PhD,4,Finance,2024-07-25,2024-09-25,963,9.9,Predictive Systems +AI01516,Machine Learning Engineer,224663,USD,224663,EX,FL,United States,L,United States,50,"TensorFlow, Deep Learning, Computer Vision",Associate,19,Automotive,2024-11-28,2025-01-18,1986,9.9,DeepTech Ventures +AI01517,Data Scientist,63881,AUD,86239,EN,CT,Australia,L,Australia,0,"PyTorch, GCP, Computer Vision, AWS",Associate,0,Transportation,2024-10-24,2024-11-10,1505,9.4,Digital Transformation LLC +AI01518,Machine Learning Researcher,95307,USD,95307,SE,CT,South Korea,M,South Korea,0,"Hadoop, AWS, Scala, TensorFlow",Master,6,Energy,2024-09-22,2024-10-21,1156,8.5,DeepTech Ventures +AI01519,AI Software Engineer,102086,USD,102086,EN,PT,Norway,L,Norway,100,"Mathematics, Git, Java",PhD,0,Education,2024-01-16,2024-02-10,1340,8.2,Autonomous Tech +AI01520,Deep Learning Engineer,97103,AUD,131089,MI,PT,Australia,M,Australia,100,"Statistics, Tableau, Data Visualization",PhD,2,Technology,2024-12-31,2025-01-23,1745,8.3,Future Systems +AI01521,Data Scientist,174876,CHF,157388,SE,PT,Switzerland,M,Switzerland,100,"SQL, Spark, GCP, PyTorch, Azure",Bachelor,7,Retail,2024-05-23,2024-07-07,2247,7.3,Autonomous Tech +AI01522,Machine Learning Researcher,77585,EUR,65947,MI,FT,France,M,France,50,"GCP, Scala, Deep Learning",Associate,2,Gaming,2024-08-13,2024-10-15,2332,5.5,Machine Intelligence Group +AI01523,Robotics Engineer,83753,USD,83753,EN,PT,Denmark,M,Denmark,0,"Tableau, Spark, Python, MLOps",Master,0,Retail,2024-05-26,2024-07-02,1715,5.8,Algorithmic Solutions +AI01524,Deep Learning Engineer,191492,JPY,21064120,EX,FT,Japan,S,Japan,0,"Python, MLOps, Mathematics",Bachelor,11,Healthcare,2024-05-21,2024-07-26,1072,7.3,TechCorp Inc +AI01525,AI Consultant,71219,USD,71219,EN,FL,Israel,M,Israel,0,"PyTorch, SQL, TensorFlow, Scala, Python",PhD,0,Healthcare,2024-04-03,2024-05-25,1209,9.4,TechCorp Inc +AI01526,Computer Vision Engineer,143605,AUD,193867,SE,PT,Australia,L,Australia,50,"Git, TensorFlow, Computer Vision, MLOps, Deep Learning",Bachelor,9,Media,2024-03-27,2024-04-16,1914,6.8,Digital Transformation LLC +AI01527,Data Analyst,261388,USD,261388,EX,FL,Norway,L,Norway,100,"Tableau, Mathematics, Scala, Java, Computer Vision",Bachelor,11,Finance,2024-10-20,2024-12-27,688,10,DeepTech Ventures +AI01528,Data Engineer,115250,GBP,86438,MI,FT,United Kingdom,L,United Kingdom,0,"Java, Tableau, PyTorch, Statistics, Azure",Bachelor,3,Retail,2024-07-01,2024-08-03,1696,8.9,Algorithmic Solutions +AI01529,AI Research Scientist,214259,USD,214259,EX,FT,Ireland,M,Ireland,0,"Tableau, Linux, PyTorch, Docker, Deep Learning",Associate,16,Education,2024-10-07,2024-10-31,609,6.8,Algorithmic Solutions +AI01530,Machine Learning Researcher,50907,USD,50907,SE,FT,China,S,Poland,0,"Statistics, Scala, Deep Learning, NLP",Bachelor,6,Telecommunications,2024-04-23,2024-05-18,1329,6.2,DataVision Ltd +AI01531,NLP Engineer,157211,USD,157211,EX,CT,Israel,S,Israel,0,"Java, GCP, Computer Vision, Git, Hadoop",Master,11,Education,2024-11-10,2024-12-02,1072,8.1,Machine Intelligence Group +AI01532,ML Ops Engineer,110447,EUR,93880,MI,FT,Germany,M,Germany,50,"Java, Python, Git, SQL, Computer Vision",Bachelor,4,Gaming,2024-08-18,2024-10-19,666,6.9,Cognitive Computing +AI01533,ML Ops Engineer,108700,SGD,141310,MI,CT,Singapore,L,Singapore,0,"Git, NLP, Kubernetes, Statistics",Bachelor,4,Education,2024-09-23,2024-10-28,1849,8.3,Digital Transformation LLC +AI01534,Head of AI,67170,EUR,57095,EN,CT,France,L,Australia,100,"AWS, R, SQL, Mathematics",Master,1,Finance,2025-01-07,2025-03-07,832,6.6,Machine Intelligence Group +AI01535,Computer Vision Engineer,45079,USD,45079,SE,FL,China,S,China,0,"Data Visualization, Spark, Linux",Master,6,Energy,2024-09-15,2024-11-17,1064,6,Advanced Robotics +AI01536,AI Architect,97906,AUD,132173,MI,PT,Australia,S,Australia,100,"Linux, SQL, R, Computer Vision, Spark",Bachelor,3,Government,2024-04-28,2024-06-05,2486,5.6,TechCorp Inc +AI01537,Principal Data Scientist,88189,USD,88189,SE,PT,South Korea,S,South Korea,100,"Scala, Hadoop, Tableau, Git",Associate,8,Retail,2025-03-02,2025-04-20,1536,7.3,Machine Intelligence Group +AI01538,Robotics Engineer,103595,CAD,129494,MI,FT,Canada,M,Canada,0,"TensorFlow, Computer Vision, Python, MLOps",Associate,2,Consulting,2024-04-04,2024-05-20,657,6.9,Smart Analytics +AI01539,Data Analyst,113624,USD,113624,SE,CT,Finland,S,Sweden,50,"SQL, GCP, Linux, Tableau, Hadoop",Bachelor,8,Technology,2024-05-24,2024-06-23,2433,7.2,Smart Analytics +AI01540,Autonomous Systems Engineer,134364,SGD,174673,SE,CT,Singapore,M,Singapore,100,"Mathematics, NLP, Docker, Tableau, Git",Master,8,Healthcare,2024-12-22,2025-01-18,1559,7.7,Smart Analytics +AI01541,AI Product Manager,143237,AUD,193370,EX,FT,Australia,S,Australia,100,"Docker, Python, Kubernetes",PhD,12,Real Estate,2025-02-13,2025-03-31,723,6.6,Predictive Systems +AI01542,ML Ops Engineer,61187,CAD,76484,EN,FT,Canada,L,Canada,100,"TensorFlow, Computer Vision, SQL, Scala, Hadoop",Associate,0,Telecommunications,2024-08-21,2024-09-21,1196,7.9,Machine Intelligence Group +AI01543,Autonomous Systems Engineer,64608,USD,64608,EN,FT,South Korea,M,Colombia,50,"GCP, Python, Hadoop, TensorFlow",PhD,0,Government,2025-03-21,2025-05-16,2441,8.1,Smart Analytics +AI01544,Principal Data Scientist,311834,CHF,280651,EX,FT,Switzerland,L,Switzerland,0,"Kubernetes, Hadoop, Python, Data Visualization, Mathematics",Bachelor,14,Transportation,2024-02-29,2024-04-11,1088,7.6,DataVision Ltd +AI01545,Deep Learning Engineer,127894,USD,127894,MI,CT,Denmark,M,Denmark,50,"TensorFlow, Azure, GCP, Java",Master,4,Finance,2024-07-17,2024-09-04,538,8.3,Machine Intelligence Group +AI01546,Data Scientist,75336,GBP,56502,EN,FL,United Kingdom,S,United Kingdom,0,"NLP, Java, MLOps, Kubernetes",Bachelor,0,Telecommunications,2024-09-12,2024-10-21,2367,9.7,AI Innovations +AI01547,Research Scientist,66416,USD,66416,EN,FL,Ireland,S,Ireland,50,"R, SQL, Linux, Mathematics",Associate,1,Telecommunications,2024-04-05,2024-06-09,1592,8.4,AI Innovations +AI01548,AI Architect,49315,USD,49315,EN,FT,Israel,S,Israel,50,"GCP, Git, Data Visualization, Tableau, MLOps",Bachelor,0,Government,2024-11-05,2024-12-08,1778,6.7,Neural Networks Co +AI01549,AI Architect,130837,EUR,111211,SE,FT,Germany,S,Germany,100,"Python, TensorFlow, Deep Learning, Scala, Computer Vision",Master,9,Automotive,2024-02-03,2024-03-18,1032,7.6,DataVision Ltd +AI01550,Head of AI,93179,CAD,116474,SE,PT,Canada,S,Canada,0,"Kubernetes, NLP, MLOps, Spark, Hadoop",Associate,5,Gaming,2024-08-28,2024-10-20,2076,5.8,Future Systems +AI01551,Machine Learning Researcher,88696,EUR,75392,EN,PT,Netherlands,L,Netherlands,50,"Java, Mathematics, GCP",Bachelor,1,Consulting,2025-03-23,2025-04-11,896,5.3,Smart Analytics +AI01552,AI Specialist,125978,GBP,94484,SE,PT,United Kingdom,S,United Kingdom,100,"Azure, TensorFlow, Scala",Bachelor,8,Energy,2025-03-01,2025-05-12,1769,9.5,Predictive Systems +AI01553,Robotics Engineer,73015,EUR,62063,EN,CT,Netherlands,M,Netherlands,50,"Git, GCP, Tableau, MLOps",Bachelor,1,Gaming,2024-02-19,2024-04-26,647,5.7,Machine Intelligence Group +AI01554,Data Analyst,89921,EUR,76433,MI,CT,Austria,S,Austria,100,"R, NLP, Python",Bachelor,2,Finance,2024-12-07,2025-01-20,1779,5.3,Digital Transformation LLC +AI01555,AI Specialist,145615,USD,145615,SE,FL,Denmark,S,Denmark,50,"Deep Learning, MLOps, PyTorch, Git, Statistics",Master,8,Automotive,2024-08-16,2024-10-28,2383,5.3,Quantum Computing Inc +AI01556,Machine Learning Researcher,72798,EUR,61878,EN,PT,France,L,France,0,"Deep Learning, SQL, Tableau, Python",PhD,1,Finance,2024-02-26,2024-04-20,976,8.1,Algorithmic Solutions +AI01557,AI Architect,202771,EUR,172355,EX,FL,France,S,Estonia,0,"Linux, Spark, Computer Vision",Master,19,Gaming,2024-04-30,2024-06-04,1300,8.1,Machine Intelligence Group +AI01558,Computer Vision Engineer,101963,SGD,132552,MI,FL,Singapore,S,Singapore,50,"Data Visualization, Scala, Tableau, Java, Mathematics",PhD,2,Telecommunications,2025-01-27,2025-03-04,2401,8.7,Cloud AI Solutions +AI01559,Principal Data Scientist,131393,EUR,111684,SE,FL,Netherlands,L,Egypt,0,"Python, Data Visualization, TensorFlow",Associate,6,Gaming,2024-06-30,2024-09-04,1399,7.3,Predictive Systems +AI01560,Data Engineer,216001,USD,216001,SE,PT,Denmark,L,Philippines,100,"Java, GCP, Deep Learning, Docker, Spark",Associate,7,Education,2024-11-17,2024-12-05,2098,7.9,Machine Intelligence Group +AI01561,AI Research Scientist,165488,USD,165488,EX,FT,South Korea,S,Egypt,100,"Tableau, Computer Vision, Docker, Python",Associate,17,Finance,2024-01-01,2024-03-12,732,5,Smart Analytics +AI01562,AI Consultant,279330,SGD,363129,EX,FT,Singapore,L,Nigeria,100,"PyTorch, Mathematics, Docker, Statistics, R",Associate,11,Media,2024-08-26,2024-09-25,1724,5.4,Algorithmic Solutions +AI01563,Head of AI,120176,EUR,102150,SE,CT,Austria,M,Austria,0,"Computer Vision, AWS, Data Visualization, Linux, R",PhD,9,Retail,2024-04-16,2024-06-07,922,8.9,Advanced Robotics +AI01564,AI Architect,242800,EUR,206380,EX,FL,Netherlands,M,Netherlands,50,"Docker, Git, Data Visualization, MLOps",PhD,14,Finance,2024-07-09,2024-08-10,1726,8.7,Algorithmic Solutions +AI01565,Autonomous Systems Engineer,135978,AUD,183570,SE,FT,Australia,S,Romania,0,"Azure, GCP, Linux, Python",Associate,7,Gaming,2025-04-19,2025-05-08,1352,9.8,Machine Intelligence Group +AI01566,Computer Vision Engineer,233643,CHF,210279,SE,PT,Switzerland,L,Switzerland,100,"Linux, GCP, TensorFlow, Docker, Python",Master,6,Education,2024-03-30,2024-06-10,1082,9.4,Neural Networks Co +AI01567,AI Architect,63249,USD,63249,MI,FT,South Korea,M,South Korea,100,"Spark, Data Visualization, Kubernetes, Python, Docker",Associate,2,Education,2024-08-12,2024-09-15,839,6,TechCorp Inc +AI01568,Data Engineer,89516,USD,89516,EX,PT,India,L,India,0,"Java, R, MLOps, Spark",Master,11,Real Estate,2024-03-12,2024-05-08,1876,9.7,Algorithmic Solutions +AI01569,Principal Data Scientist,176954,EUR,150411,EX,FT,France,M,Australia,50,"SQL, Python, MLOps",Master,15,Transportation,2024-08-18,2024-09-20,1122,6,Cloud AI Solutions +AI01570,Head of AI,55961,USD,55961,MI,PT,China,L,China,50,"Spark, Kubernetes, MLOps, Azure, Data Visualization",Associate,3,Education,2024-10-01,2024-12-03,1474,8.7,Smart Analytics +AI01571,Head of AI,132864,GBP,99648,SE,FT,United Kingdom,M,United Kingdom,100,"Scala, Python, Tableau",Bachelor,6,Finance,2025-03-18,2025-04-08,616,5.8,DataVision Ltd +AI01572,Research Scientist,104418,AUD,140964,MI,CT,Australia,M,Austria,50,"R, Git, MLOps, Spark",Associate,4,Manufacturing,2025-02-20,2025-04-03,2135,5.3,Algorithmic Solutions +AI01573,Deep Learning Engineer,80490,AUD,108662,EN,FL,Australia,M,South Africa,0,"TensorFlow, Java, Git",Bachelor,0,Healthcare,2024-06-15,2024-07-11,1830,9.8,Cognitive Computing +AI01574,Head of AI,85744,USD,85744,MI,FT,Israel,L,Israel,50,"R, GCP, Mathematics",Bachelor,3,Automotive,2024-12-04,2025-01-09,1123,7.8,DeepTech Ventures +AI01575,Principal Data Scientist,101111,EUR,85944,SE,FL,Austria,S,Netherlands,100,"Docker, Mathematics, Tableau, Linux",Master,9,Education,2025-02-09,2025-02-24,1304,8.8,Future Systems +AI01576,Machine Learning Engineer,195573,CAD,244466,EX,FT,Canada,L,Canada,100,"Mathematics, GCP, Kubernetes",Master,18,Telecommunications,2024-03-07,2024-04-23,1002,6.4,DataVision Ltd +AI01577,Robotics Engineer,136148,AUD,183800,SE,FL,Australia,M,Indonesia,0,"Azure, Java, SQL, Python, Computer Vision",PhD,9,Retail,2024-06-14,2024-07-02,1581,8.4,Quantum Computing Inc +AI01578,AI Architect,108512,SGD,141066,MI,FT,Singapore,L,Denmark,50,"Computer Vision, Linux, Data Visualization, Java, Azure",Master,4,Government,2024-03-23,2024-04-10,2122,9.3,Machine Intelligence Group +AI01579,Data Engineer,216695,EUR,184191,EX,FL,Germany,S,Germany,0,"Java, Tableau, Python, Deep Learning",Master,16,Education,2024-08-11,2024-09-07,646,7,Digital Transformation LLC +AI01580,NLP Engineer,169781,CHF,152803,SE,CT,Switzerland,S,Switzerland,50,"Python, Hadoop, Linux",PhD,5,Telecommunications,2024-08-20,2024-10-18,2253,8.6,Cloud AI Solutions +AI01581,Robotics Engineer,306082,CHF,275474,EX,PT,Switzerland,L,Switzerland,0,"Spark, AWS, Statistics",PhD,19,Telecommunications,2025-03-12,2025-05-16,1909,8.5,AI Innovations +AI01582,AI Research Scientist,82438,CHF,74194,EN,CT,Switzerland,S,Switzerland,0,"PyTorch, Java, MLOps",Associate,0,Finance,2024-10-20,2024-12-26,1139,5.2,DataVision Ltd +AI01583,NLP Engineer,57552,USD,57552,EN,FT,Ireland,M,India,0,"R, SQL, Deep Learning, PyTorch, Git",Associate,0,Finance,2024-03-10,2024-05-05,2293,7.6,Predictive Systems +AI01584,Head of AI,54111,CAD,67639,EN,CT,Canada,M,Canada,50,"Statistics, Spark, TensorFlow, Scala, GCP",PhD,1,Technology,2025-03-11,2025-04-13,1725,9.3,TechCorp Inc +AI01585,AI Product Manager,139157,EUR,118283,SE,PT,Germany,M,Germany,0,"Java, Azure, Python, MLOps",Bachelor,7,Media,2025-03-06,2025-05-13,1081,9.7,Cognitive Computing +AI01586,Deep Learning Engineer,84808,EUR,72087,MI,FT,Austria,M,Austria,100,"Git, Linux, Hadoop, GCP, Python",PhD,4,Telecommunications,2024-04-25,2024-05-18,764,5.7,TechCorp Inc +AI01587,AI Software Engineer,141179,EUR,120002,SE,CT,Austria,M,Austria,100,"Java, Python, TensorFlow",Associate,7,Transportation,2024-04-07,2024-06-03,1342,6.3,Advanced Robotics +AI01588,Computer Vision Engineer,318090,USD,318090,EX,PT,United States,L,United States,0,"PyTorch, MLOps, Hadoop",Bachelor,14,Technology,2024-04-04,2024-04-23,1247,6,DeepTech Ventures +AI01589,Data Analyst,130980,EUR,111333,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, R, Linux",PhD,3,Healthcare,2024-07-04,2024-09-04,1109,10,DataVision Ltd +AI01590,Robotics Engineer,134292,USD,134292,EX,FT,Israel,S,Israel,0,"NLP, Git, Tableau, GCP",Bachelor,13,Government,2024-11-14,2025-01-17,696,8.4,Cognitive Computing +AI01591,AI Architect,137679,AUD,185867,EX,PT,Australia,M,Australia,50,"R, Linux, Python, Deep Learning",Associate,11,Gaming,2024-09-19,2024-10-31,1964,8.3,Autonomous Tech +AI01592,AI Product Manager,179453,EUR,152535,EX,FT,France,M,France,0,"SQL, Tableau, Azure, Kubernetes, Python",Bachelor,12,Technology,2024-02-27,2024-04-12,996,8.9,Digital Transformation LLC +AI01593,ML Ops Engineer,118618,USD,118618,SE,FL,Ireland,M,Ireland,50,"Python, Java, Git, Hadoop, Statistics",Associate,8,Healthcare,2025-03-29,2025-05-21,1265,7.8,Advanced Robotics +AI01594,Data Analyst,154250,USD,154250,SE,PT,Finland,L,Finland,0,"AWS, Mathematics, PyTorch, TensorFlow",Associate,7,Education,2024-11-15,2024-12-14,2495,9,DataVision Ltd +AI01595,Machine Learning Researcher,63563,USD,63563,MI,FT,South Korea,M,Romania,50,"Java, Data Visualization, SQL, MLOps, Python",PhD,4,Manufacturing,2025-03-13,2025-04-22,1537,5.7,Predictive Systems +AI01596,Head of AI,199854,GBP,149891,EX,FT,United Kingdom,S,United Kingdom,100,"NLP, Hadoop, Kubernetes, Docker",Master,18,Consulting,2024-10-21,2024-12-22,660,5.3,Smart Analytics +AI01597,ML Ops Engineer,123361,EUR,104857,SE,FL,Germany,L,Germany,0,"NLP, Spark, Hadoop, Python",Master,6,Media,2024-09-27,2024-10-14,1538,8.9,TechCorp Inc +AI01598,AI Consultant,103643,USD,103643,SE,CT,Finland,S,Portugal,0,"Linux, Azure, Python",Master,6,Manufacturing,2024-12-11,2025-02-19,858,8.8,Cognitive Computing +AI01599,Data Scientist,61632,USD,61632,MI,CT,South Korea,M,United Kingdom,0,"R, Git, Scala",Bachelor,4,Real Estate,2024-01-06,2024-02-16,607,6.5,DataVision Ltd +AI01600,Data Engineer,64782,USD,64782,EN,CT,South Korea,M,South Korea,50,"GCP, Azure, Data Visualization, Git",Master,0,Automotive,2025-02-04,2025-03-03,942,8.1,AI Innovations +AI01601,Machine Learning Engineer,160583,USD,160583,SE,FL,Norway,L,France,100,"Data Visualization, Spark, Kubernetes",Master,7,Healthcare,2024-01-24,2024-03-28,1801,8,Advanced Robotics +AI01602,NLP Engineer,259300,SGD,337090,EX,CT,Singapore,M,Singapore,100,"Spark, GCP, Azure, Python, Tableau",Master,16,Healthcare,2025-03-10,2025-05-12,1482,5.3,DeepTech Ventures +AI01603,AI Architect,99029,EUR,84175,MI,PT,Netherlands,M,Netherlands,100,"Hadoop, Azure, Python, TensorFlow, Git",Master,2,Healthcare,2024-08-18,2024-10-04,1003,9.3,Future Systems +AI01604,Principal Data Scientist,84037,USD,84037,EN,CT,Ireland,L,Ireland,100,"TensorFlow, PyTorch, SQL, Spark, Docker",Associate,1,Energy,2024-11-20,2024-12-31,1267,6.6,Smart Analytics +AI01605,Computer Vision Engineer,70093,USD,70093,MI,FT,South Korea,L,Egypt,0,"R, Azure, PyTorch",PhD,2,Consulting,2024-11-23,2025-01-06,945,9.4,Future Systems +AI01606,Head of AI,133209,EUR,113228,SE,FT,Germany,M,Malaysia,0,"Hadoop, Python, Linux, TensorFlow, Java",PhD,9,Healthcare,2025-02-14,2025-03-15,1859,6.7,Autonomous Tech +AI01607,Head of AI,116248,USD,116248,SE,FL,Sweden,M,Sweden,100,"Python, TensorFlow, PyTorch",Associate,9,Transportation,2024-08-10,2024-10-21,1971,5.7,AI Innovations +AI01608,Machine Learning Researcher,62383,CAD,77979,EN,PT,Canada,M,Canada,100,"Data Visualization, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Media,2024-06-18,2024-08-10,1148,9.2,Quantum Computing Inc +AI01609,AI Consultant,192600,CHF,173340,EX,CT,Switzerland,S,Switzerland,100,"Linux, MLOps, GCP, TensorFlow",Associate,12,Transportation,2024-06-09,2024-08-05,1620,8,Neural Networks Co +AI01610,Research Scientist,91590,CAD,114488,MI,PT,Canada,M,Canada,0,"Statistics, SQL, AWS, Mathematics, Azure",Associate,2,Telecommunications,2024-11-18,2025-01-06,770,7.2,Algorithmic Solutions +AI01611,AI Consultant,102798,USD,102798,SE,FL,South Korea,L,South Korea,50,"Spark, SQL, Statistics",Bachelor,7,Real Estate,2025-03-15,2025-04-07,1954,8.6,AI Innovations +AI01612,AI Architect,103697,EUR,88142,MI,FT,Germany,M,Germany,0,"SQL, Python, Hadoop, Computer Vision, GCP",Associate,2,Media,2024-05-18,2024-07-01,1173,9.2,Quantum Computing Inc +AI01613,Machine Learning Engineer,28499,USD,28499,MI,CT,India,S,Brazil,0,"Tableau, SQL, Scala, AWS, GCP",Master,2,Manufacturing,2024-01-26,2024-03-20,2350,8.9,DeepTech Ventures +AI01614,Research Scientist,69768,USD,69768,MI,PT,South Korea,L,Mexico,0,"Kubernetes, Docker, AWS, SQL, Python",Bachelor,3,Automotive,2024-10-03,2024-11-24,2257,7,Predictive Systems +AI01615,Research Scientist,71036,AUD,95899,MI,FT,Australia,S,Australia,100,"Azure, Scala, MLOps, Computer Vision, Data Visualization",PhD,4,Real Estate,2024-05-08,2024-06-04,1216,7.4,Advanced Robotics +AI01616,Data Scientist,121894,GBP,91421,SE,CT,United Kingdom,S,United Kingdom,50,"Linux, Python, Kubernetes, TensorFlow, Git",Master,7,Transportation,2024-04-12,2024-05-29,1233,5.3,Cognitive Computing +AI01617,AI Software Engineer,60930,EUR,51791,EN,FL,Austria,S,Austria,50,"Tableau, PyTorch, Scala, GCP",Master,0,Consulting,2024-05-14,2024-06-16,1096,9.8,TechCorp Inc +AI01618,Principal Data Scientist,124442,USD,124442,SE,CT,Finland,M,Finland,0,"Computer Vision, Docker, SQL, Mathematics, Hadoop",PhD,7,Consulting,2025-04-02,2025-06-08,970,8.2,Advanced Robotics +AI01619,Computer Vision Engineer,88420,USD,88420,MI,CT,Sweden,L,Sweden,50,"Git, Hadoop, Java",Bachelor,2,Manufacturing,2024-08-11,2024-09-04,2056,5.9,Future Systems +AI01620,AI Consultant,84817,USD,84817,EN,CT,Ireland,L,Ireland,100,"Python, GCP, SQL",Bachelor,0,Telecommunications,2024-12-12,2025-02-01,1659,5.3,Smart Analytics +AI01621,AI Consultant,155811,SGD,202554,SE,CT,Singapore,M,Singapore,0,"Tableau, Git, SQL, Statistics",Master,6,Education,2024-10-09,2024-12-10,1916,5.3,TechCorp Inc +AI01622,AI Product Manager,95395,USD,95395,MI,PT,Israel,M,Japan,0,"TensorFlow, Deep Learning, Python, Computer Vision, PyTorch",Master,3,Media,2024-11-14,2025-01-12,908,8.2,DataVision Ltd +AI01623,NLP Engineer,82987,EUR,70539,MI,FT,Germany,S,Germany,0,"Python, NLP, AWS, Computer Vision, R",Bachelor,2,Real Estate,2024-10-30,2024-11-24,2035,5.8,Cloud AI Solutions +AI01624,Data Scientist,161403,USD,161403,EX,FL,Finland,M,Finland,50,"SQL, Statistics, PyTorch, Deep Learning",PhD,15,Finance,2024-05-16,2024-07-15,1635,9.8,DataVision Ltd +AI01625,Robotics Engineer,151191,USD,151191,SE,FT,Denmark,S,Denmark,0,"NLP, Tableau, Scala, GCP",PhD,8,Energy,2025-04-01,2025-04-24,890,6.7,Digital Transformation LLC +AI01626,Machine Learning Researcher,92075,EUR,78264,SE,CT,France,S,France,100,"GCP, Java, R",Bachelor,6,Government,2024-11-02,2024-12-05,2261,7.7,Cloud AI Solutions +AI01627,Autonomous Systems Engineer,43996,USD,43996,MI,FL,China,S,China,100,"Python, Azure, TensorFlow, Hadoop",Master,2,Manufacturing,2024-02-22,2024-03-16,2422,7.2,DataVision Ltd +AI01628,AI Research Scientist,25803,USD,25803,EN,PT,India,M,India,50,"Kubernetes, MLOps, Azure, Linux, Computer Vision",Master,0,Technology,2024-12-30,2025-03-04,1599,7.1,DataVision Ltd +AI01629,Machine Learning Engineer,99682,USD,99682,EN,FL,United States,L,Ukraine,0,"SQL, Scala, Git",Associate,0,Technology,2025-03-12,2025-04-19,2193,5.3,AI Innovations +AI01630,Autonomous Systems Engineer,108655,USD,108655,EX,PT,China,L,China,0,"PyTorch, Mathematics, Spark, Java, Hadoop",Associate,17,Gaming,2024-05-11,2024-06-25,1410,7.9,Algorithmic Solutions +AI01631,Machine Learning Researcher,79605,AUD,107467,MI,PT,Australia,M,Australia,50,"GCP, Tableau, Data Visualization, MLOps, Python",Master,3,Real Estate,2024-05-29,2024-07-25,789,7,DeepTech Ventures +AI01632,AI Specialist,68143,EUR,57922,EN,PT,Netherlands,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2024-01-25,2024-02-23,1355,5.5,Future Systems +AI01633,ML Ops Engineer,177618,SGD,230903,EX,PT,Singapore,S,Singapore,0,"Hadoop, SQL, NLP",Bachelor,18,Energy,2024-02-08,2024-03-19,957,8.1,Neural Networks Co +AI01634,Robotics Engineer,220052,CAD,275065,EX,CT,Canada,L,Ghana,50,"Hadoop, Scala, Tableau",Master,17,Media,2025-01-02,2025-01-26,1422,9.1,DeepTech Ventures +AI01635,AI Software Engineer,83629,GBP,62722,MI,PT,United Kingdom,M,Denmark,100,"Python, Tableau, Deep Learning, Data Visualization, Hadoop",PhD,2,Gaming,2024-04-12,2024-05-24,2018,6.2,Autonomous Tech +AI01636,AI Software Engineer,162381,EUR,138024,SE,FT,Netherlands,L,Netherlands,0,"Scala, Python, GCP",Bachelor,6,Gaming,2024-09-19,2024-11-27,1315,5.4,DataVision Ltd +AI01637,Machine Learning Researcher,124109,USD,124109,SE,FT,Sweden,M,Sweden,0,"Python, Hadoop, Git, GCP",Bachelor,8,Transportation,2024-01-31,2024-03-22,1835,5.9,Predictive Systems +AI01638,AI Product Manager,59192,AUD,79909,EN,CT,Australia,M,Indonesia,0,"Linux, TensorFlow, PyTorch, Java, AWS",Associate,1,Media,2024-03-28,2024-04-15,1675,6.3,Smart Analytics +AI01639,AI Research Scientist,49329,USD,49329,SE,PT,India,M,India,0,"Hadoop, Tableau, Kubernetes, PyTorch, Computer Vision",Associate,7,Energy,2025-01-25,2025-03-17,1500,5.9,DataVision Ltd +AI01640,Autonomous Systems Engineer,76915,USD,76915,EX,FT,India,M,India,100,"Statistics, Python, TensorFlow, GCP",Associate,13,Government,2024-10-14,2024-12-13,1541,5.4,Quantum Computing Inc +AI01641,AI Product Manager,101027,USD,101027,EX,FT,China,M,China,100,"Java, Deep Learning, Python",Master,11,Media,2024-01-28,2024-03-06,882,8.8,Predictive Systems +AI01642,Machine Learning Engineer,238301,USD,238301,EX,FT,Norway,S,Norway,100,"Linux, SQL, PyTorch, AWS, Hadoop",PhD,13,Transportation,2024-10-08,2024-11-25,2043,5.7,Quantum Computing Inc +AI01643,Data Scientist,143521,USD,143521,SE,PT,Ireland,L,Luxembourg,50,"SQL, Docker, Azure, MLOps",Associate,5,Retail,2024-04-26,2024-05-23,2414,8.2,Neural Networks Co +AI01644,AI Research Scientist,139551,JPY,15350610,SE,FL,Japan,L,Luxembourg,100,"MLOps, TensorFlow, SQL, Linux",Bachelor,7,Education,2025-01-18,2025-03-10,1243,7,AI Innovations +AI01645,Autonomous Systems Engineer,85768,EUR,72903,EN,FL,Austria,L,Austria,50,"Hadoop, Statistics, NLP, Python",Master,1,Manufacturing,2025-04-09,2025-06-11,1439,9,Cloud AI Solutions +AI01646,Data Engineer,252548,USD,252548,EX,FL,United States,L,United States,50,"Kubernetes, Python, AWS, GCP",PhD,13,Consulting,2024-09-12,2024-10-12,2479,6.3,DeepTech Ventures +AI01647,AI Architect,116048,EUR,98641,MI,CT,Austria,L,Austria,0,"SQL, Azure, Computer Vision, Statistics",Bachelor,4,Government,2024-06-11,2024-07-18,526,9.6,Machine Intelligence Group +AI01648,Head of AI,29834,USD,29834,EN,PT,China,L,China,0,"SQL, Docker, NLP",Bachelor,0,Gaming,2024-05-01,2024-05-22,1564,9,DataVision Ltd +AI01649,Machine Learning Engineer,120609,CAD,150761,SE,FT,Canada,S,Canada,0,"Spark, PyTorch, Statistics",Bachelor,5,Energy,2024-06-11,2024-08-09,844,6.4,Algorithmic Solutions +AI01650,Robotics Engineer,79431,EUR,67516,MI,PT,Austria,L,Austria,0,"R, Hadoop, Azure, Java, Docker",Master,2,Real Estate,2024-04-04,2024-05-09,1677,5.6,Algorithmic Solutions +AI01651,Research Scientist,194187,CAD,242734,EX,CT,Canada,S,Canada,100,"Python, Computer Vision, Spark",Master,14,Telecommunications,2024-12-14,2024-12-29,2369,8.9,Machine Intelligence Group +AI01652,Principal Data Scientist,177785,USD,177785,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Python, Scala, Linux",Master,7,Energy,2024-05-16,2024-06-17,1684,9.6,AI Innovations +AI01653,Computer Vision Engineer,231560,USD,231560,EX,CT,Israel,L,Israel,100,"Spark, Git, SQL, TensorFlow, Azure",Associate,14,Media,2024-01-04,2024-02-03,881,7.6,Smart Analytics +AI01654,AI Software Engineer,114280,CHF,102852,MI,FT,Switzerland,M,Switzerland,0,"Statistics, Kubernetes, Tableau, Docker, Scala",PhD,4,Healthcare,2024-08-31,2024-10-05,695,6.9,Predictive Systems +AI01655,Deep Learning Engineer,75014,EUR,63762,EN,PT,Netherlands,S,Indonesia,100,"Python, Tableau, Azure",Bachelor,1,Finance,2024-11-23,2025-01-21,1349,7.1,TechCorp Inc +AI01656,Data Engineer,32244,USD,32244,EN,CT,India,L,India,100,"SQL, Docker, GCP, Computer Vision",Associate,0,Automotive,2024-05-23,2024-07-29,915,6.3,Cognitive Computing +AI01657,Data Engineer,130809,USD,130809,SE,CT,Sweden,L,Sweden,100,"Python, Git, Kubernetes, GCP",PhD,9,Real Estate,2025-04-30,2025-06-29,696,8.1,Advanced Robotics +AI01658,Data Scientist,194628,CAD,243285,EX,CT,Canada,M,Canada,0,"Git, SQL, Data Visualization, PyTorch, Azure",Associate,19,Real Estate,2024-03-03,2024-04-07,1807,8.9,Digital Transformation LLC +AI01659,Deep Learning Engineer,31750,USD,31750,EN,FL,China,M,Italy,100,"PyTorch, SQL, AWS",Bachelor,1,Energy,2024-11-23,2024-12-27,1036,5.4,Predictive Systems +AI01660,Autonomous Systems Engineer,72863,USD,72863,MI,CT,Israel,S,Netherlands,0,"Git, MLOps, Java, Mathematics",Bachelor,2,Healthcare,2024-04-12,2024-06-02,2466,5.9,Smart Analytics +AI01661,AI Architect,158698,EUR,134893,EX,CT,France,M,France,100,"SQL, Kubernetes, R",Bachelor,11,Manufacturing,2025-04-19,2025-06-10,1473,5.6,Neural Networks Co +AI01662,AI Consultant,70435,USD,70435,EN,CT,United States,L,Germany,0,"Computer Vision, Azure, MLOps, NLP, Git",PhD,0,Real Estate,2024-02-10,2024-04-19,1111,8.5,Smart Analytics +AI01663,Robotics Engineer,70871,USD,70871,MI,FT,Israel,M,Israel,100,"Computer Vision, Kubernetes, Git, PyTorch",Bachelor,2,Consulting,2024-10-18,2024-11-07,2450,7.5,Cloud AI Solutions +AI01664,AI Research Scientist,69256,USD,69256,EN,FT,Finland,L,Hungary,50,"Docker, Tableau, Kubernetes",Master,0,Retail,2025-01-01,2025-03-07,1772,8.3,Cloud AI Solutions +AI01665,Computer Vision Engineer,172569,EUR,146684,EX,CT,Germany,M,Germany,100,"Kubernetes, Spark, PyTorch, GCP",Bachelor,14,Consulting,2025-01-08,2025-02-02,2081,6,Predictive Systems +AI01666,Data Engineer,105421,USD,105421,MI,PT,Ireland,M,Netherlands,50,"R, SQL, Statistics, Java, Data Visualization",Master,4,Manufacturing,2024-10-18,2024-12-20,1129,5,Advanced Robotics +AI01667,Research Scientist,280936,USD,280936,EX,PT,Ireland,L,Ireland,0,"Spark, Python, TensorFlow, SQL, Linux",Bachelor,13,Finance,2024-01-27,2024-03-16,2149,7.9,AI Innovations +AI01668,AI Research Scientist,244804,USD,244804,EX,FT,Denmark,S,Denmark,100,"Azure, Computer Vision, TensorFlow, Python, GCP",PhD,12,Real Estate,2025-01-24,2025-03-17,2021,9.3,Advanced Robotics +AI01669,AI Architect,116583,USD,116583,MI,PT,United States,S,Colombia,100,"SQL, Computer Vision, Kubernetes, AWS, R",Bachelor,2,Transportation,2024-01-17,2024-01-31,2075,9.1,Digital Transformation LLC +AI01670,Computer Vision Engineer,44363,USD,44363,SE,CT,India,M,India,50,"Hadoop, Tableau, R, MLOps, AWS",PhD,9,Government,2024-10-25,2024-12-03,1663,6.6,Algorithmic Solutions +AI01671,Robotics Engineer,103234,GBP,77426,MI,FT,United Kingdom,S,Nigeria,50,"GCP, MLOps, Scala",Associate,4,Media,2024-06-25,2024-08-29,1363,8.2,Machine Intelligence Group +AI01672,AI Research Scientist,241862,USD,241862,EX,FL,Norway,M,France,0,"Scala, PyTorch, Docker, Mathematics, SQL",Master,17,Retail,2025-02-21,2025-04-22,1897,5.9,Machine Intelligence Group +AI01673,Data Scientist,61352,USD,61352,EX,PT,India,L,Argentina,100,"Python, SQL, MLOps",Master,19,Consulting,2025-01-31,2025-04-11,901,9.7,DataVision Ltd +AI01674,Principal Data Scientist,247449,USD,247449,EX,FT,Ireland,M,Ireland,50,"SQL, Mathematics, AWS, Linux, R",Bachelor,16,Manufacturing,2025-04-11,2025-05-19,1591,6.1,Smart Analytics +AI01675,NLP Engineer,91517,USD,91517,MI,CT,Denmark,S,Denmark,100,"Linux, PyTorch, Tableau",Bachelor,4,Energy,2025-01-05,2025-01-24,1982,6.5,Predictive Systems +AI01676,Deep Learning Engineer,231797,EUR,197027,EX,PT,Netherlands,L,Israel,100,"SQL, Java, Deep Learning, MLOps",Bachelor,13,Retail,2024-11-02,2024-11-18,1062,7.4,Cloud AI Solutions +AI01677,AI Software Engineer,29053,USD,29053,EN,FT,China,L,China,100,"Scala, GCP, NLP, PyTorch",Associate,1,Finance,2024-05-17,2024-06-15,503,5.3,Smart Analytics +AI01678,Data Scientist,38480,USD,38480,MI,FT,India,L,India,50,"Scala, Spark, PyTorch, AWS",Bachelor,2,Consulting,2025-03-25,2025-05-06,2254,5.6,Autonomous Tech +AI01679,Data Scientist,49357,USD,49357,EN,FT,Finland,S,Finland,0,"Java, Mathematics, Tableau, NLP, Deep Learning",Bachelor,1,Transportation,2024-07-02,2024-07-31,2422,5.9,DeepTech Ventures +AI01680,Data Analyst,100391,CAD,125489,SE,FT,Canada,M,Nigeria,50,"Hadoop, Linux, SQL",Bachelor,9,Government,2024-10-05,2024-12-02,1941,5.7,Algorithmic Solutions +AI01681,ML Ops Engineer,72840,CHF,65556,EN,FL,Switzerland,S,Switzerland,50,"Python, Git, Java, Docker",Associate,0,Gaming,2024-02-28,2024-03-19,2048,5,Autonomous Tech +AI01682,Data Scientist,265397,EUR,225587,EX,FL,Germany,L,Germany,100,"Scala, AWS, NLP, Statistics",Master,16,Retail,2024-07-24,2024-08-21,1192,5.9,Predictive Systems +AI01683,NLP Engineer,92492,AUD,124864,EN,FL,Australia,L,Australia,100,"Tableau, SQL, Git, Python",PhD,0,Consulting,2024-05-26,2024-07-24,1700,9.4,TechCorp Inc +AI01684,AI Specialist,110408,USD,110408,SE,CT,Sweden,S,Sweden,0,"Python, Linux, R, Computer Vision",Associate,7,Technology,2024-09-25,2024-12-01,2267,10,Quantum Computing Inc +AI01685,NLP Engineer,139699,EUR,118744,EX,FT,Germany,M,Ireland,50,"Azure, Deep Learning, Scala, Mathematics",Associate,19,Finance,2024-07-25,2024-08-31,582,9.1,Advanced Robotics +AI01686,ML Ops Engineer,80747,EUR,68635,MI,CT,Netherlands,S,Netherlands,50,"NLP, Data Visualization, Python, TensorFlow, Linux",Master,3,Telecommunications,2024-02-22,2024-03-09,1345,7.1,Cognitive Computing +AI01687,Data Scientist,86520,EUR,73542,MI,FL,Austria,S,Nigeria,100,"Python, Git, TensorFlow",Bachelor,4,Finance,2024-07-08,2024-09-05,1578,6.4,Machine Intelligence Group +AI01688,AI Specialist,55997,USD,55997,EX,CT,India,M,Israel,50,"NLP, Azure, Python",PhD,12,Manufacturing,2025-03-25,2025-05-28,1550,5.4,AI Innovations +AI01689,AI Software Engineer,107119,SGD,139255,MI,PT,Singapore,M,Singapore,100,"Kubernetes, MLOps, Java, TensorFlow",Bachelor,3,Transportation,2024-04-22,2024-06-21,2417,5.3,Advanced Robotics +AI01690,Research Scientist,117336,EUR,99736,SE,FT,Austria,S,Malaysia,0,"NLP, Scala, Python",Bachelor,9,Consulting,2024-08-23,2024-09-10,1052,6.3,DeepTech Ventures +AI01691,Head of AI,164003,EUR,139403,EX,PT,Austria,S,Vietnam,0,"NLP, Java, PyTorch, GCP",PhD,16,Education,2024-03-09,2024-03-25,645,6,TechCorp Inc +AI01692,Computer Vision Engineer,109093,USD,109093,MI,FL,Ireland,L,Ireland,50,"Statistics, Azure, Scala, GCP, NLP",Master,4,Manufacturing,2025-04-26,2025-06-12,2262,8.6,AI Innovations +AI01693,Machine Learning Researcher,60847,USD,60847,EN,FL,Ireland,M,Ireland,50,"Azure, Mathematics, Python",Associate,0,Manufacturing,2024-12-19,2025-02-26,1775,7.8,DeepTech Ventures +AI01694,AI Product Manager,64394,USD,64394,MI,FT,South Korea,S,South Africa,0,"Azure, Deep Learning, GCP, Spark, R",Bachelor,4,Gaming,2024-01-24,2024-02-20,1682,9.2,Digital Transformation LLC +AI01695,Principal Data Scientist,56336,USD,56336,EN,FT,Sweden,M,Sweden,100,"Python, MLOps, Git",Bachelor,1,Transportation,2024-12-15,2025-01-23,1402,9.9,Predictive Systems +AI01696,AI Consultant,151360,JPY,16649600,EX,PT,Japan,M,Japan,50,"Scala, Kubernetes, Computer Vision, NLP, Git",PhD,11,Transportation,2024-05-26,2024-07-29,2089,5.4,Digital Transformation LLC +AI01697,Head of AI,108867,EUR,92537,SE,FL,Netherlands,M,Netherlands,50,"Mathematics, Java, Spark",PhD,7,Automotive,2024-07-15,2024-09-15,1367,6.6,Cognitive Computing +AI01698,AI Consultant,163581,EUR,139044,SE,CT,Germany,L,Germany,50,"GCP, Computer Vision, Hadoop",PhD,8,Automotive,2024-10-15,2024-12-01,1213,8.5,Machine Intelligence Group +AI01699,AI Product Manager,111866,JPY,12305260,MI,FT,Japan,M,Japan,0,"Java, Kubernetes, SQL, Mathematics",Bachelor,2,Media,2024-11-04,2024-12-30,1683,9.3,Cloud AI Solutions +AI01700,NLP Engineer,56511,USD,56511,EN,CT,South Korea,L,Israel,50,"Kubernetes, Java, Deep Learning, Mathematics, Computer Vision",PhD,0,Media,2024-10-29,2024-11-30,2130,7.1,Future Systems +AI01701,NLP Engineer,40401,USD,40401,MI,CT,China,L,China,100,"TensorFlow, SQL, Mathematics, Linux",PhD,4,Healthcare,2024-05-11,2024-06-10,2122,9.1,TechCorp Inc +AI01702,Research Scientist,130250,CHF,117225,MI,FL,Switzerland,L,Hungary,0,"Data Visualization, GCP, Scala, Docker",PhD,2,Media,2024-03-30,2024-05-22,2139,5,Algorithmic Solutions +AI01703,Computer Vision Engineer,41173,USD,41173,MI,CT,China,S,Austria,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2025-04-29,2025-06-23,1174,6.2,Smart Analytics +AI01704,Data Engineer,69187,USD,69187,EN,FL,United States,S,United States,50,"Kubernetes, Spark, Java",Associate,0,Media,2024-01-31,2024-04-04,1954,9.2,Quantum Computing Inc +AI01705,NLP Engineer,80973,USD,80973,EX,FT,India,S,Australia,100,"Linux, Python, Tableau, Kubernetes, SQL",Associate,11,Energy,2024-04-07,2024-05-31,1601,7.7,Quantum Computing Inc +AI01706,AI Software Engineer,117099,USD,117099,SE,PT,Ireland,M,Ireland,50,"Spark, Java, Computer Vision, Tableau",Bachelor,7,Real Estate,2024-10-03,2024-10-20,672,6.3,DeepTech Ventures +AI01707,AI Architect,62738,USD,62738,EN,FL,Finland,S,Canada,0,"Git, SQL, GCP",Associate,1,Consulting,2024-02-06,2024-03-01,1244,9.7,Neural Networks Co +AI01708,AI Product Manager,120017,EUR,102014,MI,FT,Germany,L,Germany,100,"Java, Kubernetes, Deep Learning",Bachelor,4,Education,2025-02-03,2025-03-17,588,8.6,Digital Transformation LLC +AI01709,AI Architect,146456,USD,146456,MI,FL,United States,L,United States,0,"SQL, Spark, Linux",PhD,2,Real Estate,2024-08-20,2024-10-17,1112,5.3,Autonomous Tech +AI01710,Data Engineer,116585,AUD,157390,SE,FL,Australia,M,Australia,0,"Mathematics, Computer Vision, Linux, Kubernetes",Master,8,Energy,2024-02-26,2024-04-21,1405,8.2,DeepTech Ventures +AI01711,AI Architect,48908,EUR,41572,EN,FT,France,M,France,100,"Spark, TensorFlow, Python, NLP, Statistics",Master,1,Healthcare,2024-12-28,2025-03-06,739,7.1,Machine Intelligence Group +AI01712,Head of AI,140368,USD,140368,MI,FT,Norway,M,Norway,0,"Java, Linux, Statistics, GCP",Master,2,Manufacturing,2024-06-25,2024-08-09,1177,8.6,Future Systems +AI01713,Deep Learning Engineer,117338,JPY,12907180,MI,FL,Japan,L,Brazil,100,"PyTorch, SQL, Hadoop, Deep Learning, Kubernetes",Associate,3,Manufacturing,2024-12-07,2025-01-22,1586,6.8,Quantum Computing Inc +AI01714,Head of AI,25199,USD,25199,EN,PT,China,M,Germany,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Media,2024-04-18,2024-06-22,849,9.8,Machine Intelligence Group +AI01715,AI Architect,101321,EUR,86123,MI,FT,France,M,France,50,"Python, Statistics, Tableau",PhD,3,Gaming,2025-03-24,2025-04-20,2449,7.7,Predictive Systems +AI01716,Machine Learning Engineer,86336,USD,86336,MI,FT,Ireland,S,Ghana,0,"Deep Learning, SQL, Data Visualization, PyTorch",Master,4,Retail,2025-03-09,2025-05-21,1028,8.6,TechCorp Inc +AI01717,Machine Learning Researcher,104654,JPY,11511940,MI,FL,Japan,L,Japan,100,"Azure, Deep Learning, R",Master,2,Energy,2024-02-24,2024-04-20,739,8.1,Cognitive Computing +AI01718,AI Specialist,93107,USD,93107,MI,FT,Ireland,L,Mexico,0,"PyTorch, GCP, Tableau",Associate,3,Gaming,2024-03-18,2024-04-05,2334,9.5,Smart Analytics +AI01719,AI Consultant,113304,USD,113304,MI,CT,Norway,S,Norway,0,"SQL, Azure, PyTorch",Bachelor,3,Healthcare,2024-04-24,2024-05-19,517,6.1,Algorithmic Solutions +AI01720,Deep Learning Engineer,159382,USD,159382,EX,CT,Ireland,M,Ireland,100,"Java, Python, Computer Vision, R",Master,12,Transportation,2024-07-03,2024-07-18,617,8.7,Future Systems +AI01721,AI Specialist,112099,USD,112099,SE,FL,South Korea,M,South Korea,50,"Azure, Python, Computer Vision",Bachelor,9,Media,2024-07-03,2024-07-17,1317,8,Advanced Robotics +AI01722,Head of AI,106493,USD,106493,MI,PT,Norway,M,Norway,0,"Linux, Scala, PyTorch, MLOps, Tableau",Master,4,Real Estate,2025-03-27,2025-05-18,1839,7.1,AI Innovations +AI01723,AI Architect,76693,SGD,99701,EN,FT,Singapore,M,Singapore,100,"Mathematics, Statistics, PyTorch",PhD,1,Real Estate,2025-04-14,2025-05-02,740,8.4,Neural Networks Co +AI01724,NLP Engineer,145475,USD,145475,SE,CT,Finland,L,Latvia,100,"Spark, Java, Deep Learning, AWS",Associate,9,Energy,2025-02-11,2025-03-14,1076,8.5,DataVision Ltd +AI01725,Data Analyst,79166,GBP,59375,EN,FT,United Kingdom,L,United Kingdom,50,"Scala, Kubernetes, MLOps, Azure, AWS",PhD,0,Finance,2024-09-24,2024-10-08,1643,9.6,DeepTech Ventures +AI01726,AI Architect,187864,USD,187864,EX,FL,Sweden,M,Sweden,0,"Git, PyTorch, SQL, Scala",Associate,16,Gaming,2024-12-06,2025-01-07,921,6.1,Future Systems +AI01727,AI Consultant,50080,USD,50080,EN,CT,Israel,S,Israel,100,"Deep Learning, Python, Mathematics",Bachelor,1,Technology,2025-01-27,2025-04-06,2110,6.6,Autonomous Tech +AI01728,Autonomous Systems Engineer,103470,JPY,11381700,MI,CT,Japan,L,Japan,100,"Computer Vision, R, Kubernetes, Tableau",Master,2,Technology,2024-11-14,2024-12-09,1694,6.9,Predictive Systems +AI01729,Machine Learning Engineer,84323,USD,84323,MI,FT,Sweden,M,Sweden,50,"Kubernetes, Git, Statistics",Bachelor,3,Real Estate,2024-11-25,2025-01-08,1134,8,DeepTech Ventures +AI01730,Robotics Engineer,71020,CAD,88775,MI,PT,Canada,S,Czech Republic,100,"Java, Tableau, PyTorch, NLP, SQL",Bachelor,3,Manufacturing,2024-02-21,2024-04-23,1253,9.7,Future Systems +AI01731,NLP Engineer,74489,USD,74489,EX,FL,China,M,Austria,50,"Linux, Docker, SQL",PhD,11,Healthcare,2024-06-03,2024-07-24,1437,9.7,TechCorp Inc +AI01732,AI Product Manager,55564,AUD,75011,EN,FT,Australia,M,Australia,50,"SQL, PyTorch, Git, Azure, AWS",Bachelor,0,Transportation,2025-03-22,2025-06-02,2036,6.3,Predictive Systems +AI01733,AI Consultant,84737,USD,84737,EN,CT,United States,S,United States,0,"Spark, Data Visualization, Computer Vision",Bachelor,1,Telecommunications,2025-01-06,2025-02-02,1139,6.8,DeepTech Ventures +AI01734,AI Software Engineer,125029,EUR,106275,SE,FL,France,M,France,50,"SQL, Azure, Java, Spark, AWS",Master,5,Healthcare,2025-01-19,2025-03-23,1740,5.6,DataVision Ltd +AI01735,Robotics Engineer,93053,EUR,79095,MI,FL,France,S,France,0,"Spark, R, Data Visualization",PhD,3,Education,2025-01-06,2025-02-15,629,5.1,DeepTech Ventures +AI01736,AI Architect,116161,USD,116161,MI,FT,United States,S,United States,50,"SQL, PyTorch, GCP, Linux",PhD,2,Technology,2025-01-07,2025-02-22,1201,7.2,Predictive Systems +AI01737,AI Software Engineer,96819,USD,96819,MI,FT,United States,S,United States,0,"Spark, Python, Tableau, Kubernetes",PhD,3,Finance,2024-11-18,2025-01-12,1105,7.7,TechCorp Inc +AI01738,Computer Vision Engineer,21074,USD,21074,EN,CT,India,M,India,50,"Git, Azure, Data Visualization",Associate,0,Retail,2024-06-29,2024-07-30,1551,7.4,Algorithmic Solutions +AI01739,Data Scientist,131324,USD,131324,MI,PT,Denmark,M,Denmark,100,"Tableau, Deep Learning, GCP, Java",PhD,2,Transportation,2024-12-14,2025-02-16,2003,6,Digital Transformation LLC +AI01740,Principal Data Scientist,58660,USD,58660,EN,CT,Finland,M,Finland,50,"Hadoop, Spark, Tableau",PhD,1,Finance,2024-10-09,2024-11-22,1205,9.9,Digital Transformation LLC +AI01741,Machine Learning Engineer,132875,EUR,112944,MI,PT,Netherlands,L,Malaysia,50,"GCP, Python, Mathematics, Linux, SQL",PhD,4,Consulting,2024-08-28,2024-10-31,1392,6.1,Quantum Computing Inc +AI01742,Computer Vision Engineer,74316,USD,74316,MI,FT,South Korea,S,South Korea,50,"TensorFlow, GCP, Azure",Bachelor,3,Energy,2024-11-17,2025-01-04,1075,9.4,Advanced Robotics +AI01743,Data Engineer,65320,EUR,55522,EN,FT,France,S,France,100,"Java, Python, Git",Bachelor,1,Media,2024-04-01,2024-05-18,915,8.7,Digital Transformation LLC +AI01744,Autonomous Systems Engineer,128941,USD,128941,SE,CT,Finland,L,Finland,50,"TensorFlow, Spark, PyTorch",Master,7,Manufacturing,2025-01-26,2025-03-07,2349,7.6,Cognitive Computing +AI01745,Principal Data Scientist,42409,USD,42409,MI,CT,China,M,South Korea,100,"PyTorch, TensorFlow, NLP",Bachelor,2,Media,2024-04-16,2024-05-09,2188,9.6,Algorithmic Solutions +AI01746,NLP Engineer,76564,GBP,57423,EN,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, Azure, Scala",PhD,0,Government,2024-03-03,2024-04-13,1639,9.4,Neural Networks Co +AI01747,NLP Engineer,289808,EUR,246337,EX,FT,Netherlands,L,Luxembourg,100,"Statistics, TensorFlow, PyTorch, Data Visualization, Hadoop",PhD,17,Automotive,2025-03-17,2025-04-28,2224,6.3,Neural Networks Co +AI01748,Data Analyst,62042,CAD,77553,EN,FL,Canada,M,Kenya,50,"Python, Azure, Tableau",Bachelor,1,Government,2024-02-15,2024-03-21,1611,6.1,TechCorp Inc +AI01749,AI Product Manager,98976,EUR,84130,MI,FT,Netherlands,M,Netherlands,100,"Statistics, Python, Mathematics, Linux, Hadoop",PhD,4,Manufacturing,2024-11-08,2024-12-24,2377,6.9,Autonomous Tech +AI01750,AI Architect,122469,USD,122469,EX,FL,South Korea,M,South Korea,50,"Linux, Scala, Java, Deep Learning, Spark",Bachelor,19,Education,2024-09-05,2024-10-17,1048,7.1,Future Systems +AI01751,NLP Engineer,187847,USD,187847,EX,FT,Ireland,M,Ireland,50,"PyTorch, TensorFlow, SQL, R",PhD,16,Transportation,2024-01-27,2024-02-16,2318,10,DeepTech Ventures +AI01752,AI Consultant,157782,JPY,17356020,EX,FT,Japan,S,Japan,0,"Spark, NLP, GCP",Master,13,Transportation,2024-11-25,2025-01-06,670,9.1,Cognitive Computing +AI01753,Research Scientist,128659,USD,128659,MI,FL,Denmark,S,Mexico,50,"Python, Linux, Scala, TensorFlow",Bachelor,2,Gaming,2024-03-04,2024-05-03,1580,5.7,Algorithmic Solutions +AI01754,AI Architect,61499,USD,61499,EN,FL,Finland,M,Ukraine,100,"Scala, Data Visualization, SQL, Tableau, MLOps",PhD,0,Government,2024-08-12,2024-10-13,1241,6.6,Neural Networks Co +AI01755,Deep Learning Engineer,66190,USD,66190,EN,FL,Ireland,L,Ireland,50,"Computer Vision, Git, Tableau, Linux, Python",PhD,1,Telecommunications,2024-10-18,2024-11-22,642,9.5,Digital Transformation LLC +AI01756,Machine Learning Engineer,29153,USD,29153,EN,FL,China,M,China,0,"Hadoop, Linux, Deep Learning, Mathematics, Git",PhD,0,Media,2024-01-16,2024-02-14,1718,9.1,Predictive Systems +AI01757,Deep Learning Engineer,64431,JPY,7087410,EN,FT,Japan,S,Japan,0,"Java, Tableau, MLOps",Master,1,Gaming,2024-03-06,2024-04-13,1972,9.2,Machine Intelligence Group +AI01758,Data Analyst,330366,USD,330366,EX,FL,Denmark,L,Denmark,0,"NLP, SQL, Tableau, Docker",Bachelor,17,Gaming,2024-03-14,2024-04-20,736,7.9,DataVision Ltd +AI01759,Machine Learning Engineer,128575,USD,128575,MI,PT,United States,M,United States,0,"Linux, Kubernetes, Spark",Bachelor,3,Automotive,2025-04-26,2025-05-21,518,9.4,Cloud AI Solutions +AI01760,AI Software Engineer,150066,GBP,112550,SE,PT,United Kingdom,M,United Kingdom,100,"Java, NLP, AWS, R, SQL",Associate,9,Media,2024-04-28,2024-07-10,1608,9.3,Predictive Systems +AI01761,Data Engineer,147214,SGD,191378,SE,CT,Singapore,L,Singapore,0,"Azure, Tableau, Scala, NLP, SQL",Associate,6,Gaming,2024-06-12,2024-07-31,1222,7.4,Cognitive Computing +AI01762,Computer Vision Engineer,35538,USD,35538,EN,FT,China,M,New Zealand,100,"AWS, Git, PyTorch, Java",Bachelor,0,Consulting,2024-11-03,2024-11-17,1062,9.5,DeepTech Ventures +AI01763,ML Ops Engineer,131200,EUR,111520,SE,FL,Germany,S,Germany,100,"GCP, Scala, NLP, Computer Vision, AWS",PhD,7,Government,2024-10-23,2024-12-30,1286,6.9,DeepTech Ventures +AI01764,Computer Vision Engineer,65465,USD,65465,EN,FT,South Korea,M,Switzerland,100,"Java, Linux, Scala",Associate,1,Consulting,2024-08-08,2024-09-29,728,8.9,TechCorp Inc +AI01765,AI Software Engineer,239103,GBP,179327,EX,CT,United Kingdom,M,United Kingdom,50,"R, Python, TensorFlow, Computer Vision",Associate,12,Automotive,2024-07-04,2024-07-25,1486,9.7,AI Innovations +AI01766,Robotics Engineer,107447,EUR,91330,SE,FL,Germany,S,France,50,"Data Visualization, Spark, R",Master,8,Technology,2024-07-13,2024-07-31,633,8.4,AI Innovations +AI01767,Machine Learning Researcher,56221,USD,56221,MI,FT,South Korea,S,South Korea,100,"PyTorch, SQL, MLOps, Data Visualization, Statistics",Master,4,Real Estate,2024-10-18,2024-12-08,575,8.1,Predictive Systems +AI01768,Deep Learning Engineer,123027,AUD,166086,MI,CT,Australia,L,Australia,0,"Linux, Kubernetes, Tableau, Java",Associate,4,Technology,2024-07-27,2024-09-03,1040,5.2,Predictive Systems +AI01769,AI Research Scientist,117390,JPY,12912900,SE,FT,Japan,S,Japan,50,"Java, SQL, Scala, Kubernetes",PhD,5,Education,2024-10-23,2024-12-21,2199,7.3,Algorithmic Solutions +AI01770,Autonomous Systems Engineer,89124,EUR,75755,MI,PT,France,L,France,100,"Kubernetes, TensorFlow, AWS, Linux, Azure",Master,4,Finance,2025-04-15,2025-05-02,1308,9.1,DataVision Ltd +AI01771,AI Product Manager,251508,EUR,213782,EX,PT,France,L,France,0,"GCP, R, Tableau, Spark",Associate,15,Finance,2024-09-05,2024-11-07,2493,9,Future Systems +AI01772,AI Software Engineer,100520,USD,100520,EX,CT,China,L,China,100,"Azure, Python, SQL",Associate,15,Media,2024-07-27,2024-09-29,1705,6.9,DeepTech Ventures +AI01773,Data Scientist,348466,CHF,313619,EX,PT,Switzerland,M,Switzerland,100,"GCP, SQL, Tableau, Data Visualization",Bachelor,13,Energy,2024-02-28,2024-04-19,1875,7.4,TechCorp Inc +AI01774,Autonomous Systems Engineer,132749,USD,132749,SE,FL,Norway,S,Latvia,0,"Linux, Computer Vision, SQL",Bachelor,5,Government,2024-03-22,2024-05-26,2272,7.5,Digital Transformation LLC +AI01775,AI Specialist,63454,USD,63454,EN,FT,Sweden,M,Colombia,50,"Azure, NLP, Deep Learning",PhD,1,Government,2024-12-30,2025-01-26,1742,5.1,Advanced Robotics +AI01776,ML Ops Engineer,102787,EUR,87369,SE,CT,Germany,M,Egypt,100,"Data Visualization, SQL, Python, Computer Vision",Bachelor,5,Transportation,2024-08-21,2024-10-01,1436,7.7,AI Innovations +AI01777,NLP Engineer,19313,USD,19313,EN,FT,India,M,Australia,50,"Python, MLOps, Linux, Deep Learning, Computer Vision",Associate,1,Finance,2024-10-07,2024-10-30,1240,9.1,DeepTech Ventures +AI01778,Machine Learning Researcher,129410,USD,129410,SE,FL,Ireland,M,Ireland,100,"Hadoop, Spark, Python, Kubernetes",Master,5,Automotive,2025-04-23,2025-07-04,1559,6.1,DataVision Ltd +AI01779,NLP Engineer,172013,JPY,18921430,EX,FT,Japan,L,Japan,0,"TensorFlow, Tableau, Azure",Master,11,Manufacturing,2025-01-13,2025-02-08,597,8.1,Machine Intelligence Group +AI01780,Autonomous Systems Engineer,158074,USD,158074,EX,CT,South Korea,S,Estonia,50,"SQL, PyTorch, Deep Learning, Tableau",PhD,14,Government,2024-03-08,2024-04-08,2054,9.4,Smart Analytics +AI01781,Data Engineer,70476,SGD,91619,MI,FL,Singapore,S,Poland,50,"AWS, Deep Learning, Python, SQL",Associate,4,Telecommunications,2024-12-20,2025-01-07,2322,6.3,TechCorp Inc +AI01782,Principal Data Scientist,90948,USD,90948,MI,CT,Israel,L,Canada,100,"Linux, GCP, Tableau, Deep Learning",Master,3,Manufacturing,2024-10-25,2024-12-10,1802,5.7,Quantum Computing Inc +AI01783,Machine Learning Researcher,238184,EUR,202456,EX,CT,Netherlands,M,Romania,50,"Python, Java, GCP, TensorFlow",Bachelor,10,Technology,2024-07-08,2024-07-25,715,6,Machine Intelligence Group +AI01784,Computer Vision Engineer,142525,USD,142525,EX,CT,Finland,M,Finland,0,"PyTorch, Kubernetes, NLP, Java",Bachelor,14,Gaming,2024-03-08,2024-04-04,647,6.7,DeepTech Ventures +AI01785,Deep Learning Engineer,210001,EUR,178501,EX,FL,Netherlands,S,Romania,50,"Python, Spark, NLP, Mathematics, Deep Learning",Bachelor,12,Consulting,2024-01-20,2024-03-21,1318,6.8,Cloud AI Solutions +AI01786,Data Analyst,124024,USD,124024,MI,FL,Denmark,L,Indonesia,0,"Spark, Python, Hadoop",Master,4,Manufacturing,2024-07-27,2024-08-24,973,6,Advanced Robotics +AI01787,AI Product Manager,269130,USD,269130,EX,PT,Denmark,M,Denmark,0,"Spark, Tableau, GCP",Associate,17,Manufacturing,2025-04-28,2025-07-10,1322,6.4,Autonomous Tech +AI01788,AI Specialist,44705,USD,44705,SE,CT,India,M,China,100,"Hadoop, Statistics, Scala, Mathematics, Kubernetes",Bachelor,8,Energy,2024-06-02,2024-07-04,1945,9.4,Digital Transformation LLC +AI01789,Data Analyst,79352,EUR,67449,EN,PT,Netherlands,M,Netherlands,100,"MLOps, Java, Python",Bachelor,0,Finance,2025-03-19,2025-05-10,2050,9.5,Cloud AI Solutions +AI01790,AI Consultant,143377,JPY,15771470,SE,FL,Japan,M,Japan,50,"TensorFlow, Computer Vision, MLOps, Data Visualization, Python",PhD,7,Real Estate,2024-01-27,2024-02-19,786,5.3,Machine Intelligence Group +AI01791,Machine Learning Engineer,40231,USD,40231,MI,FL,China,M,Malaysia,100,"Tableau, TensorFlow, Scala, Python, Mathematics",Bachelor,4,Retail,2024-01-27,2024-02-12,967,7.5,Advanced Robotics +AI01792,Robotics Engineer,79846,GBP,59885,MI,PT,United Kingdom,M,Ukraine,50,"PyTorch, Kubernetes, Computer Vision, GCP, Linux",PhD,2,Energy,2024-05-28,2024-07-03,668,5.9,Advanced Robotics +AI01793,Research Scientist,138782,USD,138782,EX,FL,Ireland,S,Malaysia,0,"Azure, Spark, R, Statistics, SQL",PhD,12,Manufacturing,2025-01-29,2025-03-13,1957,9.3,DeepTech Ventures +AI01794,ML Ops Engineer,199769,EUR,169804,EX,CT,Austria,S,Portugal,0,"AWS, Python, PyTorch",Associate,18,Transportation,2024-06-13,2024-08-19,580,7.9,Machine Intelligence Group +AI01795,AI Research Scientist,305289,USD,305289,EX,FL,Denmark,L,France,100,"Docker, MLOps, Data Visualization",Associate,17,Technology,2025-04-11,2025-06-08,1208,9.1,Algorithmic Solutions +AI01796,AI Product Manager,230691,EUR,196087,EX,FT,Austria,M,Estonia,0,"Git, Python, Linux, Kubernetes, AWS",Master,17,Consulting,2025-02-22,2025-03-10,1625,8.6,Future Systems +AI01797,AI Product Manager,238615,JPY,26247650,EX,CT,Japan,L,Austria,0,"Kubernetes, Git, Java, GCP, SQL",Bachelor,19,Manufacturing,2024-07-04,2024-08-11,1578,8.1,Neural Networks Co +AI01798,Machine Learning Engineer,98044,USD,98044,SE,FT,Sweden,S,Sweden,100,"Scala, R, TensorFlow",Associate,7,Telecommunications,2024-02-06,2024-03-31,1120,5.1,Cloud AI Solutions +AI01799,AI Research Scientist,69231,AUD,93462,MI,PT,Australia,S,Australia,100,"Scala, Java, R, Deep Learning, SQL",Associate,3,Gaming,2024-08-19,2024-10-02,2261,9.7,Machine Intelligence Group +AI01800,NLP Engineer,233794,AUD,315622,EX,FT,Australia,L,Australia,50,"Azure, Spark, SQL, Mathematics",Master,19,Transportation,2024-01-14,2024-02-18,902,6.8,Neural Networks Co +AI01801,Computer Vision Engineer,145411,EUR,123599,SE,FT,Netherlands,S,Netherlands,50,"TensorFlow, SQL, Deep Learning, R",PhD,8,Manufacturing,2025-03-20,2025-05-19,1854,6.4,Advanced Robotics +AI01802,ML Ops Engineer,119952,USD,119952,SE,FT,United States,S,Russia,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,9,Finance,2024-10-14,2024-11-06,1828,8.2,Neural Networks Co +AI01803,AI Architect,152045,USD,152045,EX,PT,United States,S,United States,50,"Mathematics, Docker, Tableau",Associate,17,Retail,2024-10-22,2024-12-23,2178,7.6,Predictive Systems +AI01804,AI Software Engineer,60657,USD,60657,SE,FT,China,L,China,0,"Java, Data Visualization, Git, Statistics",Master,8,Government,2025-02-06,2025-03-10,2006,5.1,DeepTech Ventures +AI01805,AI Specialist,157794,USD,157794,EX,PT,South Korea,L,Argentina,50,"Java, Spark, MLOps, Statistics, Python",Associate,13,Media,2025-03-04,2025-04-16,2398,8.4,DataVision Ltd +AI01806,Data Engineer,37836,USD,37836,MI,FT,India,L,Sweden,50,"GCP, Mathematics, Hadoop",Bachelor,2,Finance,2025-04-23,2025-07-05,1374,7.8,Neural Networks Co +AI01807,AI Research Scientist,68797,USD,68797,MI,FL,Israel,S,United Kingdom,100,"TensorFlow, Docker, Git, R",Bachelor,2,Manufacturing,2024-04-02,2024-05-05,2438,5.1,Autonomous Tech +AI01808,Data Scientist,144648,EUR,122951,SE,FL,France,L,France,50,"GCP, Kubernetes, Docker, Spark, Azure",Associate,6,Government,2024-04-22,2024-05-29,1741,5.8,Cloud AI Solutions +AI01809,AI Architect,88724,USD,88724,EN,FT,Ireland,L,Ireland,0,"Scala, Python, Data Visualization",Bachelor,1,Telecommunications,2024-01-26,2024-03-12,2198,9.9,Digital Transformation LLC +AI01810,Data Engineer,186244,CHF,167620,SE,PT,Switzerland,S,Switzerland,50,"Python, Scala, Computer Vision, MLOps, Linux",Master,5,Media,2025-02-14,2025-04-13,2167,5,Neural Networks Co +AI01811,Deep Learning Engineer,88469,USD,88469,SE,FL,South Korea,S,Czech Republic,0,"Spark, R, Scala, Java",Master,6,Education,2025-02-26,2025-04-02,1641,5.2,Machine Intelligence Group +AI01812,Principal Data Scientist,310111,USD,310111,EX,CT,Norway,L,Norway,0,"Statistics, Computer Vision, NLP, Linux",Bachelor,19,Retail,2024-08-08,2024-10-02,1834,6.2,AI Innovations +AI01813,AI Consultant,98560,SGD,128128,SE,CT,Singapore,S,Switzerland,100,"Statistics, MLOps, Mathematics, GCP",PhD,5,Education,2024-11-25,2024-12-09,1838,9.6,AI Innovations +AI01814,AI Specialist,159392,USD,159392,SE,FT,Norway,M,Poland,0,"Java, R, PyTorch",Bachelor,6,Media,2024-10-13,2024-11-27,1842,8,Autonomous Tech +AI01815,Data Engineer,109927,USD,109927,MI,FT,Norway,S,Norway,0,"PyTorch, Kubernetes, TensorFlow, Git",Associate,2,Manufacturing,2025-03-20,2025-05-04,1979,5,Autonomous Tech +AI01816,AI Consultant,135881,EUR,115499,SE,PT,Germany,S,Germany,100,"PyTorch, SQL, NLP",Bachelor,9,Transportation,2025-03-17,2025-04-30,1232,8.4,TechCorp Inc +AI01817,Data Engineer,170048,USD,170048,EX,CT,United States,S,Israel,100,"Statistics, Linux, Tableau, R",PhD,16,Automotive,2024-02-20,2024-03-28,1561,9.8,Machine Intelligence Group +AI01818,Computer Vision Engineer,86374,USD,86374,EX,CT,India,M,India,50,"TensorFlow, Statistics, Scala, Python",PhD,12,Healthcare,2025-01-01,2025-02-09,1201,9.7,Advanced Robotics +AI01819,Computer Vision Engineer,79277,CAD,99096,MI,FT,Canada,S,Canada,100,"PyTorch, R, GCP, Java, Linux",Master,2,Real Estate,2024-05-10,2024-06-02,1121,9.6,AI Innovations +AI01820,Data Scientist,73902,USD,73902,MI,FT,Finland,S,Turkey,100,"Deep Learning, Scala, TensorFlow, MLOps",Master,2,Gaming,2024-02-03,2024-04-03,1351,9,Cognitive Computing +AI01821,Principal Data Scientist,61896,USD,61896,EN,FL,Ireland,M,Ghana,0,"Kubernetes, Azure, SQL, R, Docker",Associate,1,Automotive,2024-01-13,2024-02-12,1699,5.2,DeepTech Ventures +AI01822,AI Product Manager,57201,CAD,71501,EN,PT,Canada,L,Canada,100,"Linux, Tableau, MLOps, Azure",Bachelor,1,Healthcare,2024-12-08,2025-01-30,1408,6.3,AI Innovations +AI01823,Principal Data Scientist,72205,USD,72205,EN,CT,Sweden,M,Brazil,100,"Tableau, Docker, Spark, Kubernetes",Bachelor,0,Transportation,2024-03-31,2024-05-22,943,9.2,Quantum Computing Inc +AI01824,AI Specialist,45721,USD,45721,EN,FL,Israel,S,Singapore,0,"Azure, AWS, Docker",Master,1,Retail,2024-01-16,2024-02-09,2151,7.9,Quantum Computing Inc +AI01825,AI Research Scientist,76605,USD,76605,EN,CT,Denmark,M,Denmark,100,"Spark, Java, Deep Learning, Kubernetes, AWS",Master,1,Healthcare,2024-12-31,2025-03-06,1455,9.9,TechCorp Inc +AI01826,Data Engineer,90927,EUR,77288,MI,FL,Netherlands,L,Netherlands,0,"R, Git, Deep Learning",PhD,2,Automotive,2024-03-05,2024-04-25,777,6.5,Digital Transformation LLC +AI01827,ML Ops Engineer,129674,CAD,162093,SE,CT,Canada,L,Canada,50,"MLOps, Python, NLP, Linux, Hadoop",Master,5,Energy,2025-02-14,2025-04-20,1628,9.7,Smart Analytics +AI01828,Autonomous Systems Engineer,79647,USD,79647,EN,CT,Israel,L,Brazil,100,"Azure, Tableau, Spark",PhD,0,Automotive,2024-06-28,2024-09-03,1836,5.4,DeepTech Ventures +AI01829,Autonomous Systems Engineer,143268,USD,143268,SE,CT,United States,L,United States,100,"Scala, Docker, SQL, Git, MLOps",Bachelor,6,Finance,2024-04-22,2024-06-02,2000,7.5,Neural Networks Co +AI01830,Principal Data Scientist,55944,USD,55944,EN,CT,United States,S,United States,0,"Python, Scala, GCP",Master,1,Consulting,2024-04-21,2024-06-22,2218,8.8,Cloud AI Solutions +AI01831,Head of AI,147714,USD,147714,SE,PT,Denmark,M,Denmark,50,"R, Hadoop, Scala",PhD,7,Gaming,2024-03-05,2024-03-23,1834,5.2,Neural Networks Co +AI01832,AI Product Manager,62923,GBP,47192,EN,FL,United Kingdom,L,United Kingdom,100,"SQL, Statistics, MLOps",Master,0,Automotive,2024-05-17,2024-06-02,2457,5.2,Predictive Systems +AI01833,Deep Learning Engineer,195780,USD,195780,EX,FT,Denmark,S,Japan,100,"Java, PyTorch, Spark",PhD,13,Automotive,2024-04-24,2024-06-03,943,6.5,Machine Intelligence Group +AI01834,Data Analyst,127106,USD,127106,SE,CT,United States,S,Estonia,50,"Python, R, NLP, MLOps, Java",Bachelor,8,Automotive,2025-04-12,2025-06-06,935,5.4,Advanced Robotics +AI01835,Deep Learning Engineer,57038,USD,57038,EN,FT,South Korea,L,South Korea,100,"Data Visualization, R, Hadoop, PyTorch",Master,1,Media,2024-01-06,2024-02-01,2304,5.1,Predictive Systems +AI01836,AI Software Engineer,130998,USD,130998,SE,CT,South Korea,L,South Korea,100,"Data Visualization, PyTorch, Tableau, Git",Bachelor,8,Real Estate,2024-08-01,2024-09-15,1062,5.7,DeepTech Ventures +AI01837,Autonomous Systems Engineer,66589,EUR,56601,EN,FT,Austria,S,Austria,50,"Azure, NLP, GCP, PyTorch",Associate,1,Transportation,2024-11-03,2025-01-07,2290,5.9,AI Innovations +AI01838,Computer Vision Engineer,194996,EUR,165747,EX,CT,Netherlands,L,Malaysia,100,"Data Visualization, Docker, Git, PyTorch, Java",Associate,12,Gaming,2024-10-23,2024-12-10,1664,9.5,Cognitive Computing +AI01839,Data Engineer,152454,EUR,129586,SE,FT,Austria,L,Finland,0,"Statistics, Docker, Hadoop, R",Master,7,Real Estate,2024-08-03,2024-09-01,1068,8.1,DeepTech Ventures +AI01840,Data Analyst,72614,EUR,61722,EN,CT,Germany,S,Germany,50,"Tableau, GCP, MLOps, PyTorch, Git",Associate,0,Real Estate,2024-05-24,2024-07-09,1330,6.5,Predictive Systems +AI01841,Machine Learning Researcher,69406,EUR,58995,EN,CT,Netherlands,L,Netherlands,50,"Hadoop, PyTorch, Data Visualization, TensorFlow, Scala",Associate,1,Education,2024-08-26,2024-09-24,1163,6,Future Systems +AI01842,Machine Learning Engineer,109931,CHF,98938,MI,FL,Switzerland,S,Mexico,50,"TensorFlow, Git, Computer Vision",Master,4,Technology,2025-03-12,2025-05-04,1832,7.5,Future Systems +AI01843,AI Software Engineer,37793,USD,37793,EN,CT,China,M,China,50,"Python, TensorFlow, MLOps, Statistics, Scala",Bachelor,1,Retail,2024-02-05,2024-02-27,2034,8.8,DataVision Ltd +AI01844,Autonomous Systems Engineer,273120,USD,273120,EX,FL,Ireland,L,Ireland,100,"Mathematics, Linux, TensorFlow",Bachelor,15,Retail,2025-04-16,2025-06-27,910,8,Neural Networks Co +AI01845,ML Ops Engineer,105016,CHF,94514,MI,CT,Switzerland,M,Switzerland,100,"Scala, Mathematics, SQL",Master,3,Retail,2025-02-17,2025-04-13,1877,6.2,Cognitive Computing +AI01846,Machine Learning Engineer,231563,CAD,289454,EX,CT,Canada,M,Canada,0,"PyTorch, Hadoop, Kubernetes",Bachelor,10,Education,2024-05-05,2024-06-11,1289,7.7,Neural Networks Co +AI01847,NLP Engineer,120136,USD,120136,SE,CT,Finland,M,Finland,50,"Hadoop, Docker, SQL, TensorFlow, Tableau",Associate,5,Real Estate,2024-07-20,2024-09-19,1156,9.1,Quantum Computing Inc +AI01848,Robotics Engineer,25404,USD,25404,EN,FT,India,L,India,100,"Python, Azure, TensorFlow, GCP",Associate,0,Retail,2024-03-27,2024-04-13,650,8.1,Digital Transformation LLC +AI01849,Data Analyst,58557,JPY,6441270,EN,PT,Japan,M,Japan,100,"R, Docker, Computer Vision, Deep Learning, Hadoop",Associate,1,Government,2025-01-26,2025-02-21,1676,6.7,Predictive Systems +AI01850,AI Software Engineer,78957,EUR,67113,EN,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Java",Master,1,Telecommunications,2024-02-26,2024-04-12,540,8.2,Neural Networks Co +AI01851,NLP Engineer,22675,USD,22675,EN,FL,India,L,India,50,"GCP, R, Data Visualization",PhD,0,Transportation,2024-01-15,2024-03-27,2064,8.5,DataVision Ltd +AI01852,NLP Engineer,147152,USD,147152,SE,FT,Norway,S,Norway,0,"Scala, SQL, PyTorch, Computer Vision, Deep Learning",PhD,9,Finance,2024-10-11,2024-12-08,660,6.2,Cognitive Computing +AI01853,AI Architect,103466,EUR,87946,SE,FL,Austria,M,Austria,100,"Hadoop, Spark, PyTorch",Bachelor,9,Technology,2024-11-28,2024-12-31,1886,6.3,Machine Intelligence Group +AI01854,Machine Learning Researcher,78287,USD,78287,EN,FL,Ireland,M,Ireland,0,"Spark, AWS, Hadoop, Java",PhD,1,Real Estate,2025-02-21,2025-05-04,2397,9.4,Autonomous Tech +AI01855,AI Consultant,142221,EUR,120888,SE,CT,Germany,M,Germany,50,"Git, Kubernetes, Python, TensorFlow, Hadoop",Associate,9,Gaming,2024-07-21,2024-09-26,1266,9.3,Future Systems +AI01856,Machine Learning Engineer,82950,USD,82950,EN,FT,Norway,L,Germany,50,"Kubernetes, Data Visualization, SQL, Mathematics, GCP",Master,0,Gaming,2024-07-21,2024-08-24,800,6.1,Cognitive Computing +AI01857,AI Product Manager,124220,USD,124220,MI,CT,Ireland,L,Ireland,0,"Linux, Computer Vision, Tableau, Kubernetes",Associate,3,Government,2024-08-16,2024-10-11,2005,9.7,Cloud AI Solutions +AI01858,NLP Engineer,78087,CAD,97609,EN,FT,Canada,L,Belgium,50,"MLOps, R, Computer Vision",Bachelor,1,Technology,2024-02-09,2024-03-26,760,9.2,AI Innovations +AI01859,Machine Learning Researcher,50319,GBP,37739,EN,FT,United Kingdom,S,United Kingdom,50,"Deep Learning, MLOps, Java, Git",Bachelor,0,Government,2024-03-29,2024-05-17,2216,10,Smart Analytics +AI01860,Data Analyst,82880,EUR,70448,MI,PT,Netherlands,S,Turkey,0,"TensorFlow, Python, Spark, MLOps",Bachelor,3,Education,2024-05-31,2024-07-19,1846,7.1,Algorithmic Solutions +AI01861,AI Specialist,119491,USD,119491,MI,FT,Ireland,L,Ireland,50,"R, AWS, Spark, Linux, Computer Vision",Master,3,Automotive,2024-04-30,2024-06-27,1982,7.5,Future Systems +AI01862,AI Specialist,202791,USD,202791,SE,FT,United States,L,United States,0,"Kubernetes, Tableau, GCP",Bachelor,8,Technology,2025-02-27,2025-05-03,1627,5.7,DeepTech Ventures +AI01863,Autonomous Systems Engineer,203607,EUR,173066,EX,FL,France,M,Czech Republic,0,"Linux, Data Visualization, NLP",Bachelor,13,Automotive,2024-06-13,2024-08-25,615,8.8,AI Innovations +AI01864,ML Ops Engineer,76776,SGD,99809,EN,FT,Singapore,L,Singapore,0,"Computer Vision, R, Tableau, Linux",PhD,1,Gaming,2024-09-02,2024-10-02,2193,6.9,Neural Networks Co +AI01865,Data Analyst,66728,USD,66728,EN,FL,Sweden,S,Indonesia,100,"Scala, Kubernetes, Computer Vision, TensorFlow",PhD,1,Education,2024-08-17,2024-09-16,679,6.9,Autonomous Tech +AI01866,AI Software Engineer,135400,USD,135400,SE,FL,United States,S,Luxembourg,0,"Hadoop, Python, TensorFlow",Bachelor,5,Consulting,2024-11-09,2024-12-12,856,5.6,Cloud AI Solutions +AI01867,Research Scientist,123743,CAD,154679,SE,FT,Canada,S,Austria,50,"R, Java, Statistics, GCP, Git",Associate,7,Consulting,2024-07-21,2024-09-13,1360,5.3,Cloud AI Solutions +AI01868,Deep Learning Engineer,109631,USD,109631,MI,FL,Norway,S,Germany,50,"AWS, Computer Vision, Data Visualization, NLP",Master,3,Manufacturing,2025-04-05,2025-06-09,2205,6.4,Future Systems +AI01869,Principal Data Scientist,153283,USD,153283,SE,FL,Norway,L,Israel,100,"Python, NLP, Kubernetes, Mathematics",Associate,6,Automotive,2024-04-19,2024-06-02,2060,8.2,Algorithmic Solutions +AI01870,AI Consultant,96402,USD,96402,MI,CT,Norway,M,Norway,0,"Statistics, Scala, Tableau, Computer Vision",PhD,4,Healthcare,2024-07-15,2024-09-25,2089,9.6,Neural Networks Co +AI01871,Research Scientist,158028,USD,158028,SE,FT,Denmark,L,Denmark,100,"Hadoop, Python, TensorFlow",PhD,9,Retail,2024-02-25,2024-04-03,1515,7.3,Predictive Systems +AI01872,NLP Engineer,45538,USD,45538,SE,FL,India,S,India,50,"Git, TensorFlow, Java",Bachelor,8,Gaming,2024-02-06,2024-02-26,1204,9.4,TechCorp Inc +AI01873,AI Architect,115560,USD,115560,MI,FT,Finland,L,Finland,100,"Data Visualization, Linux, AWS, MLOps, Kubernetes",Master,3,Government,2024-03-24,2024-05-02,1753,9,TechCorp Inc +AI01874,AI Consultant,136534,EUR,116054,SE,PT,Germany,M,Germany,100,"Python, TensorFlow, Scala, Java",Master,6,Education,2024-12-19,2025-02-05,1155,7.6,TechCorp Inc +AI01875,AI Research Scientist,211480,USD,211480,EX,CT,Ireland,S,Philippines,50,"Git, TensorFlow, Data Visualization, Computer Vision, Kubernetes",Master,16,Education,2024-05-16,2024-07-17,847,6.5,Cognitive Computing +AI01876,Deep Learning Engineer,112194,USD,112194,SE,FL,Ireland,S,Ireland,50,"Git, Docker, Kubernetes, GCP, Tableau",Bachelor,7,Government,2024-01-27,2024-03-13,1418,8.8,Cloud AI Solutions +AI01877,Autonomous Systems Engineer,150077,USD,150077,EX,FT,Sweden,M,Italy,100,"R, GCP, Linux, Data Visualization, Azure",Bachelor,14,Manufacturing,2024-01-18,2024-03-02,1325,8.6,AI Innovations +AI01878,AI Consultant,125806,USD,125806,SE,CT,Sweden,S,Sweden,50,"Mathematics, Kubernetes, Computer Vision, R",Master,6,Technology,2024-01-01,2024-01-30,1313,5.8,Future Systems +AI01879,Head of AI,66045,USD,66045,EN,CT,Israel,S,Israel,0,"Java, Docker, Computer Vision, Linux, PyTorch",Bachelor,0,Energy,2024-02-17,2024-03-11,1759,9.8,Digital Transformation LLC +AI01880,AI Research Scientist,174743,USD,174743,SE,FT,Norway,S,Poland,0,"SQL, Python, AWS, Java",Bachelor,8,Automotive,2024-09-16,2024-10-31,2102,7.6,AI Innovations +AI01881,AI Product Manager,96725,EUR,82216,EN,CT,Netherlands,L,Romania,0,"Scala, Hadoop, Data Visualization, Azure",Bachelor,1,Consulting,2024-03-22,2024-04-24,2067,6.5,Smart Analytics +AI01882,Data Analyst,61494,USD,61494,EX,PT,India,S,India,50,"Scala, SQL, PyTorch, Statistics",Master,15,Gaming,2024-05-31,2024-06-28,700,9.2,Algorithmic Solutions +AI01883,Autonomous Systems Engineer,51504,CAD,64380,EN,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, Kubernetes",Bachelor,0,Finance,2024-02-16,2024-04-20,725,10,Future Systems +AI01884,Research Scientist,84676,USD,84676,EN,FL,Norway,L,Norway,50,"Hadoop, Git, Data Visualization, PyTorch",Bachelor,1,Automotive,2024-02-13,2024-03-08,2299,5.6,Neural Networks Co +AI01885,Data Engineer,116829,USD,116829,MI,FT,United States,S,United States,100,"GCP, MLOps, AWS",Bachelor,2,Manufacturing,2024-02-02,2024-02-23,2179,5.6,Algorithmic Solutions +AI01886,Machine Learning Researcher,253322,USD,253322,EX,FT,Norway,M,Norway,0,"PyTorch, SQL, MLOps, TensorFlow, Computer Vision",Associate,17,Consulting,2025-01-02,2025-01-29,928,6.3,AI Innovations +AI01887,Machine Learning Researcher,307829,CHF,277046,EX,CT,Switzerland,L,Switzerland,50,"Python, R, Computer Vision, Hadoop, NLP",Master,18,Healthcare,2024-07-09,2024-07-25,2073,9.3,Digital Transformation LLC +AI01888,Head of AI,74701,USD,74701,EN,PT,United States,L,United States,50,"SQL, Git, Java, Mathematics",Master,0,Telecommunications,2024-12-25,2025-02-10,2396,6.5,Cloud AI Solutions +AI01889,Machine Learning Researcher,77814,CAD,97268,MI,PT,Canada,S,Canada,100,"Python, MLOps, Git, Java",PhD,3,Technology,2024-03-23,2024-04-28,2111,5.3,Predictive Systems +AI01890,Head of AI,153857,USD,153857,SE,FL,Ireland,L,Ireland,50,"NLP, Linux, Scala",Master,5,Finance,2024-11-14,2024-12-18,2443,8.8,Autonomous Tech +AI01891,Head of AI,53752,EUR,45689,EN,FL,Netherlands,S,Netherlands,50,"R, Mathematics, SQL",PhD,0,Government,2024-02-26,2024-05-06,1201,5.2,Advanced Robotics +AI01892,Head of AI,67828,USD,67828,EN,PT,Denmark,S,Denmark,0,"PyTorch, Scala, TensorFlow",PhD,0,Government,2025-04-23,2025-07-01,2053,9,Cognitive Computing +AI01893,Machine Learning Engineer,98247,USD,98247,MI,PT,Ireland,S,Vietnam,50,"SQL, TensorFlow, Python, Computer Vision",Bachelor,2,Telecommunications,2025-03-30,2025-04-19,993,7,Digital Transformation LLC +AI01894,AI Product Manager,171970,USD,171970,SE,FL,United States,M,United States,100,"NLP, Linux, MLOps, TensorFlow, Python",PhD,5,Finance,2024-05-17,2024-07-16,698,9.9,Autonomous Tech +AI01895,Machine Learning Engineer,143515,JPY,15786650,SE,FL,Japan,S,Japan,50,"PyTorch, Linux, Tableau, Kubernetes, Spark",Bachelor,9,Consulting,2024-04-24,2024-07-02,2340,7.8,DeepTech Ventures +AI01896,Head of AI,39901,USD,39901,SE,CT,India,S,India,50,"Spark, AWS, Python, Deep Learning",Bachelor,6,Retail,2024-07-11,2024-09-12,685,6.5,Smart Analytics +AI01897,Autonomous Systems Engineer,117566,JPY,12932260,SE,FT,Japan,S,Ukraine,50,"Kubernetes, Python, NLP, Deep Learning, Mathematics",Master,8,Transportation,2025-03-31,2025-05-30,2123,5.2,Smart Analytics +AI01898,Head of AI,113872,CHF,102485,EN,FL,Switzerland,M,Switzerland,50,"SQL, AWS, Statistics, PyTorch",PhD,1,Retail,2024-12-17,2025-01-14,2123,8.5,AI Innovations +AI01899,Machine Learning Engineer,68525,USD,68525,EN,CT,Finland,L,Finland,100,"Mathematics, Kubernetes, R",Master,1,Telecommunications,2024-09-01,2024-09-30,1605,7.2,Advanced Robotics +AI01900,Data Analyst,143796,GBP,107847,SE,FT,United Kingdom,L,Belgium,50,"R, Scala, PyTorch, Git, Python",Master,7,Manufacturing,2024-08-19,2024-10-08,1811,5.6,Predictive Systems +AI01901,NLP Engineer,267822,GBP,200867,EX,CT,United Kingdom,M,Canada,100,"Tableau, Docker, AWS, NLP",Associate,16,Automotive,2024-08-19,2024-09-30,997,9.7,Digital Transformation LLC +AI01902,AI Research Scientist,92727,USD,92727,SE,FL,South Korea,M,Denmark,100,"MLOps, Data Visualization, Java",PhD,8,Retail,2024-01-05,2024-02-07,2179,8.6,Cloud AI Solutions +AI01903,AI Research Scientist,87977,EUR,74780,MI,FT,France,L,France,0,"Hadoop, Linux, Java",Master,3,Real Estate,2024-04-14,2024-05-07,1923,10,Future Systems +AI01904,Autonomous Systems Engineer,71922,EUR,61134,MI,PT,Germany,S,Germany,0,"AWS, Spark, Data Visualization, Git, Scala",PhD,3,Manufacturing,2025-03-07,2025-03-20,1861,9.3,Cognitive Computing +AI01905,Principal Data Scientist,31507,USD,31507,EN,FT,China,L,China,100,"Tableau, Linux, Python, Statistics, R",PhD,0,Gaming,2025-01-26,2025-04-02,1263,8.9,TechCorp Inc +AI01906,Principal Data Scientist,30492,USD,30492,EN,FL,China,M,China,100,"SQL, PyTorch, Tableau, Statistics",PhD,0,Healthcare,2024-10-04,2024-11-19,748,5.1,Advanced Robotics +AI01907,AI Research Scientist,116151,EUR,98728,MI,PT,Netherlands,M,Netherlands,50,"Azure, Linux, Computer Vision, Tableau",Master,3,Automotive,2025-04-16,2025-05-12,1794,9.6,Quantum Computing Inc +AI01908,Machine Learning Researcher,71966,CAD,89958,MI,FL,Canada,M,Canada,50,"Tableau, Python, TensorFlow, Computer Vision, Azure",Associate,2,Finance,2024-03-04,2024-05-05,779,6.1,Autonomous Tech +AI01909,Computer Vision Engineer,163401,GBP,122551,SE,FT,United Kingdom,L,United Kingdom,50,"Python, SQL, Linux",Master,6,Automotive,2024-09-18,2024-11-11,744,6.7,Quantum Computing Inc +AI01910,Robotics Engineer,61330,EUR,52131,EN,CT,France,M,Denmark,0,"Hadoop, Scala, Linux",PhD,1,Consulting,2024-08-09,2024-10-03,1120,9.6,TechCorp Inc +AI01911,Data Engineer,214921,USD,214921,EX,PT,Ireland,S,Ireland,0,"R, MLOps, SQL, Computer Vision, Docker",PhD,16,Media,2025-02-21,2025-04-17,793,8,Algorithmic Solutions +AI01912,AI Product Manager,76932,EUR,65392,EN,FL,Germany,M,Germany,100,"Tableau, TensorFlow, Docker, Spark, SQL",PhD,1,Government,2024-04-29,2024-06-29,614,6.6,Future Systems +AI01913,Research Scientist,169028,CAD,211285,EX,FT,Canada,S,Canada,0,"Java, Deep Learning, Computer Vision, Hadoop",Master,11,Gaming,2024-07-17,2024-09-24,1655,6.5,Smart Analytics +AI01914,Autonomous Systems Engineer,118035,AUD,159347,SE,PT,Australia,L,Australia,0,"Mathematics, Linux, Kubernetes, Python",Associate,9,Automotive,2024-04-18,2024-06-29,1343,8.9,DeepTech Ventures +AI01915,AI Product Manager,113938,USD,113938,MI,PT,Denmark,M,Denmark,100,"Data Visualization, GCP, TensorFlow",Associate,3,Finance,2024-12-02,2025-01-19,863,5.5,Smart Analytics +AI01916,Autonomous Systems Engineer,109615,CAD,137019,SE,FL,Canada,S,Canada,100,"Hadoop, Kubernetes, Scala, Statistics, GCP",PhD,7,Media,2025-03-26,2025-04-22,2420,9.6,Smart Analytics +AI01917,Data Analyst,27659,USD,27659,MI,PT,India,M,India,100,"NLP, Data Visualization, MLOps, Hadoop",Master,2,Healthcare,2024-10-03,2024-10-26,2282,6.1,Neural Networks Co +AI01918,AI Product Manager,67740,USD,67740,EN,PT,United States,S,Austria,100,"Python, Scala, Linux",PhD,0,Real Estate,2025-03-14,2025-05-16,1682,9.8,DeepTech Ventures +AI01919,Machine Learning Researcher,174654,USD,174654,SE,CT,Sweden,L,South Korea,50,"Scala, R, Hadoop, AWS, Python",Master,6,Energy,2024-02-21,2024-03-26,502,5.4,DeepTech Ventures +AI01920,Data Analyst,232730,CAD,290913,EX,FT,Canada,M,India,50,"Hadoop, Kubernetes, Data Visualization, Mathematics, Tableau",PhD,15,Technology,2024-03-11,2024-05-19,1522,5.4,Cognitive Computing +AI01921,Data Analyst,63711,EUR,54154,MI,PT,Austria,S,Austria,50,"Computer Vision, Data Visualization, Python, NLP, AWS",PhD,3,Energy,2025-02-02,2025-02-22,1411,7.5,DataVision Ltd +AI01922,Principal Data Scientist,116990,USD,116990,SE,CT,South Korea,M,South Korea,100,"Computer Vision, R, Scala, GCP, SQL",Associate,8,Media,2024-01-08,2024-03-05,731,6.6,Autonomous Tech +AI01923,AI Architect,105481,USD,105481,MI,CT,Israel,L,Israel,0,"PyTorch, SQL, Computer Vision, NLP, TensorFlow",Master,3,Manufacturing,2024-03-15,2024-04-23,2371,5.2,DeepTech Ventures +AI01924,Data Analyst,161259,EUR,137070,EX,CT,Netherlands,M,Netherlands,0,"Spark, SQL, MLOps",Associate,11,Education,2024-10-15,2024-12-05,1598,9.3,Advanced Robotics +AI01925,Research Scientist,121460,USD,121460,SE,FT,Ireland,L,Ireland,50,"Java, AWS, Mathematics",Bachelor,8,Healthcare,2024-08-28,2024-10-21,848,6.3,Digital Transformation LLC +AI01926,Data Engineer,70644,USD,70644,EN,FL,Sweden,M,Sweden,100,"Python, TensorFlow, Deep Learning",Master,1,Consulting,2025-03-14,2025-04-20,2323,7.4,Future Systems +AI01927,NLP Engineer,109579,GBP,82184,SE,CT,United Kingdom,M,United Kingdom,100,"Python, Docker, Mathematics, Linux, Hadoop",Bachelor,7,Real Estate,2024-10-12,2024-12-04,2482,8.3,Cognitive Computing +AI01928,Head of AI,90547,CAD,113184,MI,CT,Canada,S,United Kingdom,100,"Kubernetes, Docker, Tableau, Azure",PhD,4,Consulting,2024-10-26,2024-12-15,2228,6,Predictive Systems +AI01929,Machine Learning Researcher,218360,USD,218360,EX,PT,South Korea,L,South Korea,0,"GCP, PyTorch, Linux, Azure",Bachelor,18,Healthcare,2024-03-27,2024-04-11,960,6.4,Predictive Systems +AI01930,Robotics Engineer,140380,EUR,119323,SE,PT,Austria,M,Austria,100,"Kubernetes, Scala, R, Computer Vision",PhD,6,Media,2025-04-02,2025-05-10,2084,9.7,Neural Networks Co +AI01931,Computer Vision Engineer,119973,USD,119973,SE,FT,South Korea,L,South Korea,50,"Azure, Python, TensorFlow",Bachelor,7,Transportation,2024-02-18,2024-04-20,2141,6.7,TechCorp Inc +AI01932,NLP Engineer,102535,USD,102535,MI,CT,United States,S,United States,100,"Scala, Python, Linux, Tableau, Computer Vision",Bachelor,4,Energy,2024-01-04,2024-03-09,2029,7.7,DeepTech Ventures +AI01933,Machine Learning Researcher,106806,AUD,144188,MI,FT,Australia,L,Australia,50,"SQL, Java, Docker",Bachelor,2,Manufacturing,2025-03-02,2025-04-09,1517,8.7,Predictive Systems +AI01934,Deep Learning Engineer,54346,CAD,67933,EN,CT,Canada,S,Canada,100,"MLOps, TensorFlow, SQL, Scala",Associate,1,Media,2025-02-27,2025-03-22,1549,8.5,Future Systems +AI01935,AI Consultant,70194,USD,70194,SE,CT,China,L,China,0,"Linux, PyTorch, TensorFlow, AWS",PhD,6,Automotive,2024-07-08,2024-08-24,1557,6.3,Cloud AI Solutions +AI01936,Computer Vision Engineer,94729,EUR,80520,MI,FL,Netherlands,S,Argentina,100,"Data Visualization, Spark, Mathematics",PhD,3,Transportation,2025-03-21,2025-04-18,770,6.5,Neural Networks Co +AI01937,NLP Engineer,46286,USD,46286,EN,FT,Finland,S,Finland,100,"Python, Git, Kubernetes",Master,0,Transportation,2024-09-18,2024-11-20,2261,9.6,Algorithmic Solutions +AI01938,Machine Learning Engineer,166362,USD,166362,SE,CT,Norway,L,Denmark,50,"Data Visualization, PyTorch, Hadoop, Linux",Associate,9,Technology,2025-03-14,2025-04-03,884,6.9,Smart Analytics +AI01939,AI Software Engineer,185959,GBP,139469,EX,CT,United Kingdom,S,United Kingdom,100,"AWS, SQL, Data Visualization, Computer Vision",Master,12,Manufacturing,2024-04-21,2024-06-15,2359,6.1,Advanced Robotics +AI01940,AI Software Engineer,124415,USD,124415,SE,PT,South Korea,M,South Korea,50,"SQL, Spark, R",Associate,9,Media,2024-04-15,2024-05-30,2248,6.3,Advanced Robotics +AI01941,AI Architect,69802,USD,69802,EN,CT,Ireland,S,Netherlands,50,"Linux, Kubernetes, Python, TensorFlow, Data Visualization",Master,0,Transportation,2025-04-10,2025-05-24,1731,7.8,Machine Intelligence Group +AI01942,NLP Engineer,220589,USD,220589,EX,FL,United States,S,United States,50,"Scala, Spark, Linux, TensorFlow",Master,18,Telecommunications,2024-02-11,2024-03-30,1595,5.7,Autonomous Tech +AI01943,AI Specialist,80123,AUD,108166,MI,PT,Australia,S,Australia,0,"TensorFlow, Kubernetes, NLP, Linux",PhD,4,Manufacturing,2025-01-17,2025-02-27,1255,9.2,AI Innovations +AI01944,Data Scientist,116909,USD,116909,MI,FL,United States,S,Brazil,100,"MLOps, Linux, SQL, NLP",Bachelor,2,Telecommunications,2024-07-28,2024-10-08,2205,9.1,DataVision Ltd +AI01945,Machine Learning Engineer,43728,EUR,37169,EN,PT,Austria,S,Austria,0,"Java, Python, Azure, NLP",Bachelor,1,Government,2024-10-28,2025-01-06,2246,5.4,DataVision Ltd +AI01946,Autonomous Systems Engineer,64573,EUR,54887,EN,FT,Austria,L,Austria,50,"AWS, Java, NLP",PhD,0,Finance,2025-04-26,2025-06-30,2310,9,Future Systems +AI01947,NLP Engineer,117914,CHF,106123,MI,FL,Switzerland,S,Switzerland,100,"Hadoop, NLP, R",Bachelor,2,Transportation,2024-07-29,2024-10-10,1827,6.1,Autonomous Tech +AI01948,Autonomous Systems Engineer,152384,USD,152384,EX,CT,South Korea,L,Ukraine,100,"Kubernetes, R, Tableau",Bachelor,16,Real Estate,2025-01-19,2025-02-16,1687,6.3,Digital Transformation LLC +AI01949,AI Software Engineer,68312,EUR,58065,MI,FL,Austria,M,Austria,100,"Python, Deep Learning, Computer Vision, Spark, TensorFlow",PhD,3,Telecommunications,2025-03-31,2025-04-19,509,5.2,DataVision Ltd +AI01950,AI Specialist,85129,CAD,106411,MI,PT,Canada,M,Canada,100,"SQL, Kubernetes, Git, Statistics, Docker",Master,4,Real Estate,2024-01-01,2024-01-17,1017,8.8,Advanced Robotics +AI01951,AI Software Engineer,146496,CHF,131846,SE,CT,Switzerland,S,Switzerland,0,"R, Hadoop, Mathematics, Tableau",Bachelor,7,Consulting,2025-03-06,2025-04-12,1644,6.6,Autonomous Tech +AI01952,Research Scientist,120458,USD,120458,MI,FT,Norway,M,Norway,0,"SQL, PyTorch, AWS, Linux, Computer Vision",Master,4,Retail,2025-02-28,2025-03-31,650,5.8,AI Innovations +AI01953,AI Architect,306393,USD,306393,EX,PT,Denmark,M,United Kingdom,100,"Python, Scala, Computer Vision, Mathematics, TensorFlow",Master,12,Retail,2024-04-29,2024-05-27,2084,6.5,Quantum Computing Inc +AI01954,Data Analyst,119182,USD,119182,SE,FT,Ireland,M,Ireland,0,"Mathematics, Azure, Kubernetes, Git",Associate,6,Gaming,2024-08-02,2024-10-10,1648,5.6,Neural Networks Co +AI01955,AI Product Manager,190595,CHF,171536,EX,PT,Switzerland,S,Switzerland,100,"R, PyTorch, GCP, Tableau, Java",PhD,18,Automotive,2024-10-12,2024-11-06,668,5.2,Future Systems +AI01956,AI Product Manager,133627,AUD,180396,SE,PT,Australia,M,Indonesia,100,"Data Visualization, PyTorch, Spark, GCP",PhD,9,Transportation,2024-08-04,2024-10-13,1422,7.2,AI Innovations +AI01957,AI Specialist,102896,USD,102896,MI,FL,Norway,S,Israel,100,"TensorFlow, Azure, MLOps",Bachelor,2,Energy,2024-04-21,2024-05-05,1871,6.3,Machine Intelligence Group +AI01958,AI Consultant,53828,EUR,45754,EN,CT,France,S,France,100,"Hadoop, TensorFlow, Spark, Computer Vision, SQL",PhD,0,Technology,2024-03-17,2024-04-07,1829,6.3,DataVision Ltd +AI01959,Robotics Engineer,229532,EUR,195102,EX,FT,Netherlands,L,Austria,100,"PyTorch, Tableau, Linux, Python",Master,19,Finance,2025-01-02,2025-03-15,548,7.8,Cognitive Computing +AI01960,Machine Learning Researcher,50929,USD,50929,SE,FL,India,L,India,100,"Spark, Kubernetes, Azure, Deep Learning",Associate,7,Healthcare,2024-12-31,2025-01-30,1837,7.8,Machine Intelligence Group +AI01961,Autonomous Systems Engineer,119585,EUR,101647,SE,PT,Germany,S,Germany,50,"R, Kubernetes, Git",Master,5,Media,2025-02-27,2025-04-28,1402,6,Future Systems +AI01962,Deep Learning Engineer,94488,USD,94488,EN,FT,Denmark,M,New Zealand,0,"Linux, TensorFlow, SQL",Associate,0,Manufacturing,2025-03-24,2025-04-20,2344,7.6,Autonomous Tech +AI01963,Data Analyst,62316,EUR,52969,MI,PT,Austria,S,Austria,50,"Statistics, Python, Deep Learning, Git, TensorFlow",PhD,2,Manufacturing,2024-03-24,2024-04-07,602,6.4,Quantum Computing Inc +AI01964,ML Ops Engineer,108014,USD,108014,EN,PT,Denmark,L,Denmark,50,"MLOps, Spark, SQL, NLP",Bachelor,1,Real Estate,2024-05-07,2024-06-02,1694,8.3,Machine Intelligence Group +AI01965,Deep Learning Engineer,137340,EUR,116739,SE,CT,Netherlands,M,Netherlands,50,"Git, MLOps, Java",Associate,5,Automotive,2024-07-31,2024-09-16,776,9.1,DeepTech Ventures +AI01966,AI Consultant,51851,AUD,69999,EN,FL,Australia,M,Australia,50,"MLOps, Scala, Kubernetes, Python, TensorFlow",PhD,0,Education,2024-05-17,2024-07-20,2465,6.1,TechCorp Inc +AI01967,Machine Learning Engineer,158813,USD,158813,SE,PT,Norway,S,Norway,100,"Tableau, Git, Azure, Scala, GCP",Associate,7,Telecommunications,2024-05-17,2024-06-27,2495,6.8,TechCorp Inc +AI01968,NLP Engineer,272366,USD,272366,EX,CT,Norway,M,Norway,100,"Mathematics, TensorFlow, Tableau, Linux, R",Bachelor,11,Consulting,2025-02-25,2025-03-15,1869,5.8,Cloud AI Solutions +AI01969,AI Research Scientist,66656,USD,66656,EN,PT,Finland,S,France,0,"Kubernetes, PyTorch, Java, AWS, Deep Learning",Bachelor,0,Media,2025-02-16,2025-04-20,559,9.2,Neural Networks Co +AI01970,Computer Vision Engineer,97650,EUR,83003,MI,CT,Austria,M,Austria,100,"MLOps, Data Visualization, TensorFlow, Tableau, SQL",PhD,4,Healthcare,2024-08-31,2024-09-14,1105,5.2,Future Systems +AI01971,Data Scientist,198520,USD,198520,EX,FT,Sweden,L,Sweden,50,"Hadoop, PyTorch, Deep Learning, TensorFlow",Bachelor,15,Retail,2025-02-24,2025-03-24,1825,9.4,Machine Intelligence Group +AI01972,Computer Vision Engineer,113590,CHF,102231,MI,FL,Switzerland,M,France,0,"Git, Computer Vision, PyTorch",Bachelor,4,Gaming,2025-01-17,2025-03-20,2437,5.8,AI Innovations +AI01973,Data Scientist,153445,EUR,130428,EX,CT,France,S,France,0,"Python, Data Visualization, TensorFlow, Deep Learning",Master,10,Manufacturing,2025-03-25,2025-04-12,2026,7,Digital Transformation LLC +AI01974,Robotics Engineer,97324,SGD,126521,EN,FL,Singapore,L,Singapore,50,"Java, Tableau, Kubernetes",Bachelor,0,Manufacturing,2024-07-27,2024-09-23,1832,8.8,Algorithmic Solutions +AI01975,Research Scientist,44666,USD,44666,EN,PT,South Korea,S,South Korea,50,"Kubernetes, Python, AWS",Associate,0,Education,2024-11-06,2024-11-30,2233,6.3,Machine Intelligence Group +AI01976,Deep Learning Engineer,296548,USD,296548,EX,PT,United States,M,United States,100,"Tableau, Azure, Java",Bachelor,18,Technology,2024-06-15,2024-08-13,768,9.8,AI Innovations +AI01977,AI Architect,89790,EUR,76322,EN,CT,Netherlands,L,Netherlands,100,"SQL, Git, MLOps",PhD,0,Government,2024-06-11,2024-08-04,1109,9.6,Cognitive Computing +AI01978,ML Ops Engineer,146337,SGD,190238,SE,PT,Singapore,M,Portugal,0,"R, Data Visualization, Java, GCP, Python",Bachelor,9,Consulting,2024-07-09,2024-07-23,1346,5.6,Neural Networks Co +AI01979,Machine Learning Engineer,99555,CHF,89600,MI,PT,Switzerland,S,South Africa,100,"NLP, Docker, PyTorch",Master,4,Energy,2024-02-13,2024-03-05,1281,8.8,Future Systems +AI01980,NLP Engineer,153992,JPY,16939120,EX,FT,Japan,M,Japan,100,"Linux, GCP, MLOps, Data Visualization, Git",PhD,10,Media,2024-07-05,2024-07-27,1340,8.2,Algorithmic Solutions +AI01981,Deep Learning Engineer,103750,EUR,88188,MI,FT,Netherlands,S,Netherlands,100,"Python, Statistics, Mathematics, TensorFlow, Java",Bachelor,4,Government,2025-02-25,2025-04-05,1399,9.5,DataVision Ltd +AI01982,Principal Data Scientist,88704,USD,88704,MI,PT,Ireland,L,Ghana,0,"Linux, Hadoop, R, Mathematics, Kubernetes",Master,2,Real Estate,2024-01-31,2024-03-25,1929,5.3,Cloud AI Solutions +AI01983,Data Analyst,118310,JPY,13014100,MI,PT,Japan,L,Japan,100,"TensorFlow, Data Visualization, Statistics",Master,3,Telecommunications,2024-06-10,2024-08-06,1801,7.4,Smart Analytics +AI01984,Deep Learning Engineer,171397,EUR,145687,EX,FT,Germany,S,Germany,100,"Azure, Linux, Deep Learning",Master,17,Healthcare,2025-03-22,2025-05-23,1983,5.5,Future Systems +AI01985,AI Research Scientist,80403,CAD,100504,MI,CT,Canada,M,Canada,50,"Scala, Java, Deep Learning",Associate,3,Automotive,2025-02-09,2025-03-12,681,9.5,Algorithmic Solutions +AI01986,Robotics Engineer,118077,USD,118077,SE,FL,United States,S,Norway,50,"Statistics, Azure, TensorFlow",Master,6,Manufacturing,2024-05-24,2024-08-01,1654,5.7,TechCorp Inc +AI01987,Head of AI,103534,USD,103534,SE,FL,Sweden,M,Sweden,100,"SQL, Tableau, PyTorch",Associate,9,Technology,2024-12-04,2025-01-26,2035,7.6,Predictive Systems +AI01988,Computer Vision Engineer,101905,EUR,86619,MI,FT,Austria,M,Switzerland,100,"TensorFlow, Python, GCP",Associate,2,Consulting,2024-04-11,2024-05-22,1083,6.1,AI Innovations +AI01989,AI Research Scientist,182075,USD,182075,EX,CT,South Korea,L,Estonia,0,"Kubernetes, Mathematics, Tableau",PhD,18,Finance,2024-03-12,2024-04-19,979,7.8,DeepTech Ventures +AI01990,AI Research Scientist,230990,SGD,300287,EX,FL,Singapore,M,Singapore,0,"SQL, PyTorch, Computer Vision",Master,16,Government,2024-03-13,2024-04-04,574,8.7,Digital Transformation LLC +AI01991,Computer Vision Engineer,215816,EUR,183444,EX,PT,Germany,S,Germany,100,"Mathematics, PyTorch, NLP",PhD,19,Retail,2024-01-15,2024-02-23,2001,8.2,Cognitive Computing +AI01992,Research Scientist,83946,EUR,71354,EN,FL,Germany,L,Germany,50,"R, Spark, Statistics",PhD,1,Energy,2025-04-30,2025-05-30,726,5.2,DeepTech Ventures +AI01993,ML Ops Engineer,96785,USD,96785,MI,PT,Ireland,S,United Kingdom,0,"TensorFlow, R, SQL, Data Visualization, AWS",Bachelor,2,Telecommunications,2024-03-29,2024-05-27,712,5.5,TechCorp Inc +AI01994,Data Scientist,82495,EUR,70121,MI,PT,Netherlands,M,Malaysia,100,"Linux, Git, MLOps",PhD,3,Gaming,2025-03-10,2025-04-05,856,5.8,Neural Networks Co +AI01995,Machine Learning Engineer,131731,GBP,98798,MI,CT,United Kingdom,L,United Kingdom,0,"TensorFlow, AWS, Linux",PhD,3,Technology,2024-11-08,2024-12-31,814,8.2,Digital Transformation LLC +AI01996,Head of AI,56604,USD,56604,EN,CT,Israel,M,Israel,100,"Kubernetes, PyTorch, Statistics, NLP, TensorFlow",PhD,1,Retail,2024-11-17,2025-01-12,1845,7.4,Cognitive Computing +AI01997,Data Analyst,63776,USD,63776,EN,FL,Ireland,S,Ireland,100,"Spark, Mathematics, Java, Statistics, Python",Bachelor,1,Retail,2024-12-04,2025-01-15,2083,7.1,Digital Transformation LLC +AI01998,AI Architect,68800,CAD,86000,MI,CT,Canada,M,Canada,100,"PyTorch, R, Tableau, Deep Learning",Associate,4,Government,2024-08-15,2024-08-29,868,6.4,Smart Analytics +AI01999,AI Architect,45902,USD,45902,MI,CT,China,S,China,100,"SQL, Scala, Tableau, R",Associate,3,Transportation,2024-04-10,2024-06-17,2292,9,Autonomous Tech +AI02000,Data Scientist,87974,SGD,114366,MI,CT,Singapore,S,Singapore,100,"Mathematics, R, TensorFlow, Hadoop",PhD,4,Retail,2024-11-20,2025-01-31,1465,6.4,Quantum Computing Inc +AI02001,AI Architect,141156,USD,141156,SE,CT,Sweden,M,Sweden,100,"Azure, R, Deep Learning, Scala, Java",PhD,8,Manufacturing,2024-09-19,2024-10-03,928,6.4,Machine Intelligence Group +AI02002,Autonomous Systems Engineer,72809,CHF,65528,EN,CT,Switzerland,M,Switzerland,100,"Linux, Hadoop, Deep Learning, PyTorch, Computer Vision",PhD,1,Telecommunications,2024-05-09,2024-06-18,924,9,Advanced Robotics +AI02003,Autonomous Systems Engineer,74905,CHF,67415,EN,PT,Switzerland,M,South Korea,100,"Statistics, SQL, PyTorch, Deep Learning, Azure",Bachelor,1,Healthcare,2024-12-17,2025-02-06,1485,7.6,Neural Networks Co +AI02004,Deep Learning Engineer,83543,CAD,104429,MI,FL,Canada,L,Portugal,50,"Data Visualization, SQL, MLOps, PyTorch",PhD,4,Transportation,2024-09-28,2024-11-16,1281,5.5,AI Innovations +AI02005,ML Ops Engineer,74348,EUR,63196,EN,FL,France,L,France,0,"Kubernetes, Deep Learning, SQL, Python, NLP",PhD,0,Gaming,2024-02-12,2024-03-05,1746,8.1,DeepTech Ventures +AI02006,AI Product Manager,221177,USD,221177,EX,PT,Israel,M,Russia,50,"Python, Git, Data Visualization, Mathematics, GCP",Associate,10,Manufacturing,2024-08-12,2024-09-04,1529,9,DeepTech Ventures +AI02007,Machine Learning Engineer,188560,USD,188560,EX,FT,Israel,S,Israel,100,"Python, Kubernetes, NLP, Linux",PhD,14,Finance,2024-07-20,2024-08-06,1635,6.9,Cloud AI Solutions +AI02008,Principal Data Scientist,63698,JPY,7006780,EN,FL,Japan,M,Japan,0,"Computer Vision, Java, R",PhD,0,Media,2024-12-28,2025-03-02,1197,5.2,Neural Networks Co +AI02009,AI Architect,80238,USD,80238,EN,CT,Norway,L,Norway,50,"MLOps, Docker, GCP, Scala, PyTorch",Bachelor,0,Manufacturing,2024-12-29,2025-02-27,2410,5.4,Quantum Computing Inc +AI02010,Autonomous Systems Engineer,161051,EUR,136893,EX,PT,Austria,L,Austria,50,"Linux, Python, Scala",Bachelor,15,Education,2024-12-18,2025-01-22,1314,5.2,Smart Analytics +AI02011,NLP Engineer,130144,EUR,110622,SE,FT,Germany,S,Argentina,0,"GCP, PyTorch, TensorFlow, Python, Data Visualization",Bachelor,8,Finance,2024-02-04,2024-02-27,2268,5.5,Autonomous Tech +AI02012,AI Research Scientist,50319,USD,50319,EN,PT,Israel,S,Israel,0,"PyTorch, Java, Python, Mathematics, SQL",Bachelor,1,Media,2024-05-12,2024-05-30,782,7.7,DeepTech Ventures +AI02013,Machine Learning Researcher,256545,USD,256545,EX,CT,Sweden,L,Sweden,100,"PyTorch, SQL, Computer Vision, Spark, Azure",Bachelor,18,Healthcare,2025-02-02,2025-02-20,2493,6.9,Autonomous Tech +AI02014,AI Research Scientist,138961,USD,138961,SE,FT,South Korea,L,South Korea,0,"TensorFlow, Docker, SQL",Associate,6,Government,2024-04-11,2024-06-13,1018,8.6,TechCorp Inc +AI02015,Machine Learning Engineer,60037,EUR,51031,EN,CT,Germany,L,United Kingdom,0,"Mathematics, Scala, Data Visualization",Bachelor,0,Education,2024-07-25,2024-08-31,2188,6.3,AI Innovations +AI02016,AI Software Engineer,102110,USD,102110,MI,PT,Norway,M,Norway,0,"Git, Python, Java",Master,3,Retail,2024-11-17,2025-01-17,1311,8.1,AI Innovations +AI02017,Research Scientist,159317,EUR,135419,SE,FL,Germany,L,Germany,50,"Java, TensorFlow, PyTorch, Azure, GCP",PhD,9,Automotive,2025-02-25,2025-03-16,2179,5.8,Machine Intelligence Group +AI02018,Data Analyst,113026,EUR,96072,SE,PT,Netherlands,S,Netherlands,0,"R, GCP, Kubernetes, Spark, Linux",Bachelor,6,Technology,2024-12-19,2025-03-01,1999,9.2,Machine Intelligence Group +AI02019,Data Engineer,175703,USD,175703,SE,FL,Denmark,S,Denmark,50,"Deep Learning, Azure, Hadoop, SQL, Git",Bachelor,8,Telecommunications,2024-03-07,2024-04-19,1080,7,Autonomous Tech +AI02020,Deep Learning Engineer,79945,USD,79945,MI,CT,United States,S,Luxembourg,0,"Git, Statistics, Azure",Master,2,Retail,2024-02-21,2024-04-19,1292,7.3,Machine Intelligence Group +AI02021,Data Analyst,78895,AUD,106508,EN,FL,Australia,L,Australia,0,"MLOps, Kubernetes, TensorFlow, Python",PhD,1,Gaming,2024-03-03,2024-04-22,655,8.2,Neural Networks Co +AI02022,Head of AI,65331,USD,65331,EN,FT,Ireland,S,Ireland,50,"Azure, Kubernetes, AWS, MLOps, TensorFlow",PhD,0,Consulting,2024-06-29,2024-07-23,629,5.2,Advanced Robotics +AI02023,AI Software Engineer,88502,USD,88502,EN,PT,Denmark,L,Denmark,100,"Linux, Git, Deep Learning, SQL, Azure",PhD,0,Gaming,2024-03-06,2024-04-23,2419,8.8,Neural Networks Co +AI02024,AI Research Scientist,218753,SGD,284379,EX,FL,Singapore,M,Norway,0,"Git, Python, Mathematics",Bachelor,17,Media,2024-08-06,2024-09-06,1029,8.6,Cloud AI Solutions +AI02025,Machine Learning Researcher,286960,SGD,373048,EX,FL,Singapore,L,Singapore,50,"Scala, Mathematics, Data Visualization, Git, Python",PhD,13,Energy,2024-07-02,2024-07-19,1324,7.9,Future Systems +AI02026,Autonomous Systems Engineer,54703,USD,54703,EN,FL,Sweden,M,Sweden,0,"Hadoop, Git, Tableau, Scala",PhD,0,Gaming,2024-04-19,2024-06-07,2069,6.4,Advanced Robotics +AI02027,Machine Learning Engineer,119409,USD,119409,SE,PT,Finland,L,Belgium,0,"AWS, MLOps, Kubernetes, Azure, Spark",Bachelor,5,Technology,2024-07-27,2024-09-03,2467,6.3,Autonomous Tech +AI02028,AI Software Engineer,169745,CAD,212181,EX,CT,Canada,M,Canada,50,"Java, SQL, PyTorch",Master,16,Real Estate,2024-03-20,2024-05-06,2094,5.4,Digital Transformation LLC +AI02029,AI Product Manager,117185,EUR,99607,MI,FT,Austria,L,Brazil,50,"Java, Kubernetes, Scala, Computer Vision, Git",Associate,2,Gaming,2025-01-13,2025-02-04,1341,7.6,Quantum Computing Inc +AI02030,AI Specialist,67488,EUR,57365,EN,PT,Germany,L,Italy,0,"SQL, Azure, PyTorch, Docker, TensorFlow",Master,0,Education,2024-10-02,2024-11-21,1857,7.4,Algorithmic Solutions +AI02031,Data Analyst,237063,AUD,320035,EX,FT,Australia,L,Australia,0,"Azure, Java, NLP, Hadoop",Bachelor,12,Technology,2024-07-17,2024-09-09,2126,9.3,Future Systems +AI02032,Data Engineer,121918,EUR,103630,MI,FL,Germany,L,Germany,50,"Kubernetes, Statistics, Tableau",Associate,2,Gaming,2024-07-09,2024-08-08,1044,5.7,Autonomous Tech +AI02033,Deep Learning Engineer,147358,USD,147358,EX,CT,Ireland,S,Argentina,0,"AWS, Python, Kubernetes, TensorFlow, Docker",Master,19,Transportation,2025-02-22,2025-04-06,932,6.2,DeepTech Ventures +AI02034,Data Analyst,159954,SGD,207940,SE,CT,Singapore,M,Singapore,50,"R, Kubernetes, MLOps, AWS, PyTorch",Master,8,Energy,2024-10-10,2024-11-04,886,7.5,Future Systems +AI02035,Data Analyst,112591,USD,112591,SE,FL,South Korea,M,Thailand,0,"Azure, Scala, Data Visualization, Mathematics",Bachelor,5,Government,2024-04-21,2024-05-07,758,5.4,TechCorp Inc +AI02036,AI Consultant,51670,EUR,43920,EN,CT,France,M,France,50,"R, MLOps, TensorFlow, Hadoop",Bachelor,1,Energy,2024-03-25,2024-04-26,1983,9.2,Predictive Systems +AI02037,Data Analyst,54739,USD,54739,EN,CT,Finland,S,Finland,50,"Statistics, MLOps, Tableau, SQL, Linux",PhD,1,Consulting,2024-09-20,2024-11-06,2488,6.7,Future Systems +AI02038,Principal Data Scientist,93238,EUR,79252,SE,CT,France,S,France,0,"NLP, Docker, Python, AWS",Bachelor,5,Education,2024-07-13,2024-08-24,1683,6,DeepTech Ventures +AI02039,AI Research Scientist,84825,USD,84825,MI,FL,Ireland,L,Malaysia,100,"Kubernetes, Mathematics, Tableau, MLOps",Associate,2,Technology,2024-05-16,2024-07-20,1709,6.7,TechCorp Inc +AI02040,AI Software Engineer,78450,USD,78450,MI,FT,Sweden,S,Sweden,100,"Computer Vision, Python, Git, TensorFlow",Bachelor,4,Energy,2024-12-18,2025-01-01,505,5.5,AI Innovations +AI02041,Head of AI,66222,USD,66222,EN,FL,South Korea,L,South Korea,50,"SQL, Deep Learning, NLP, Python",PhD,1,Technology,2024-09-04,2024-10-10,692,9.7,Algorithmic Solutions +AI02042,ML Ops Engineer,87393,USD,87393,MI,FL,United States,S,China,100,"Docker, Kubernetes, Data Visualization, Mathematics, Hadoop",Associate,2,Automotive,2025-01-14,2025-02-13,703,9.5,Smart Analytics +AI02043,Data Scientist,293844,GBP,220383,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Git, Tableau",Master,13,Healthcare,2024-02-11,2024-03-20,905,5.1,Neural Networks Co +AI02044,NLP Engineer,89635,USD,89635,EX,CT,China,S,China,50,"NLP, Scala, SQL, Deep Learning, Azure",Master,17,Manufacturing,2024-02-02,2024-04-05,1941,6.3,Quantum Computing Inc +AI02045,Data Analyst,40827,USD,40827,SE,CT,India,M,Argentina,100,"Deep Learning, PyTorch, Scala, Computer Vision",Associate,8,Consulting,2024-01-21,2024-03-11,867,6.1,DataVision Ltd +AI02046,AI Architect,53958,USD,53958,MI,PT,China,L,New Zealand,50,"SQL, Docker, Tableau",Bachelor,2,Real Estate,2024-05-12,2024-07-15,2051,7.5,DeepTech Ventures +AI02047,Autonomous Systems Engineer,209986,EUR,178488,EX,PT,France,S,France,50,"Scala, Kubernetes, Data Visualization, SQL, R",Associate,15,Real Estate,2024-04-12,2024-05-11,1552,5.3,Smart Analytics +AI02048,Data Engineer,48509,USD,48509,EN,FL,Finland,S,Finland,0,"Git, Mathematics, Hadoop, AWS, Azure",Bachelor,1,Education,2025-03-30,2025-05-03,2109,9.7,TechCorp Inc +AI02049,Autonomous Systems Engineer,256412,USD,256412,EX,CT,Denmark,L,Germany,0,"Java, TensorFlow, Spark, AWS",PhD,18,Real Estate,2025-04-10,2025-05-21,2390,5.7,TechCorp Inc +AI02050,Research Scientist,54244,USD,54244,EN,FL,South Korea,M,South Korea,100,"Python, Java, Tableau, TensorFlow",Master,0,Manufacturing,2024-05-29,2024-06-30,896,5.3,Cloud AI Solutions +AI02051,AI Architect,58064,USD,58064,EN,FT,Sweden,S,Denmark,100,"Kubernetes, MLOps, Statistics",Bachelor,0,Real Estate,2025-03-11,2025-04-30,1851,6.3,Predictive Systems +AI02052,Data Analyst,89637,USD,89637,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, MLOps, Hadoop",Bachelor,8,Gaming,2025-01-01,2025-02-15,795,7.4,Quantum Computing Inc +AI02053,Autonomous Systems Engineer,74071,USD,74071,EN,FL,Denmark,S,Vietnam,100,"R, Computer Vision, PyTorch, GCP",Bachelor,1,Technology,2024-04-11,2024-04-30,1809,7.5,Algorithmic Solutions +AI02054,AI Consultant,89562,EUR,76128,MI,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, Python, SQL, TensorFlow",PhD,4,Retail,2024-10-02,2024-10-16,750,9.4,Neural Networks Co +AI02055,Research Scientist,199418,CHF,179476,SE,FT,Switzerland,L,Switzerland,0,"Python, R, GCP, Spark",PhD,9,Government,2024-03-01,2024-05-01,1597,9.1,Advanced Robotics +AI02056,Robotics Engineer,128887,EUR,109554,EX,PT,France,M,France,50,"Azure, AWS, Tableau",Bachelor,13,Consulting,2024-03-19,2024-04-26,963,8.3,AI Innovations +AI02057,Data Analyst,72518,EUR,61640,EN,PT,Germany,S,Germany,50,"Python, SQL, Tableau",Bachelor,1,Finance,2024-05-30,2024-07-16,506,6.3,DataVision Ltd +AI02058,Autonomous Systems Engineer,63237,EUR,53751,MI,CT,France,S,France,0,"NLP, Kubernetes, Scala, Git, Tableau",PhD,4,Automotive,2024-01-17,2024-02-19,737,6.6,DeepTech Ventures +AI02059,Deep Learning Engineer,135732,GBP,101799,SE,PT,United Kingdom,S,Switzerland,100,"Python, SQL, Java, Computer Vision",Bachelor,5,Government,2024-05-01,2024-07-03,1777,5.8,Cognitive Computing +AI02060,AI Software Engineer,99662,USD,99662,EX,CT,China,M,China,100,"Kubernetes, Azure, Python, Hadoop",Bachelor,12,Transportation,2024-02-04,2024-03-14,1974,5,TechCorp Inc +AI02061,AI Consultant,282892,USD,282892,EX,FL,Ireland,L,Israel,100,"Scala, Java, Kubernetes",Master,14,Real Estate,2024-01-23,2024-02-14,2335,9.5,TechCorp Inc +AI02062,Computer Vision Engineer,126107,USD,126107,MI,CT,Denmark,L,Denmark,100,"Azure, Scala, Kubernetes",PhD,4,Retail,2024-08-23,2024-10-30,1170,9.4,Quantum Computing Inc +AI02063,Research Scientist,157203,USD,157203,SE,FL,United States,M,United States,0,"Git, Python, Computer Vision, Mathematics, AWS",PhD,5,Technology,2024-10-21,2024-12-01,1718,6.6,TechCorp Inc +AI02064,AI Specialist,91180,USD,91180,EN,CT,Norway,M,Norway,0,"Java, GCP, AWS, Hadoop",Master,0,Consulting,2024-12-09,2025-01-23,1561,5.4,Digital Transformation LLC +AI02065,Data Scientist,102489,USD,102489,EX,CT,China,M,China,50,"Tableau, Git, Kubernetes, MLOps, Computer Vision",PhD,19,Retail,2024-08-04,2024-09-15,1000,5.7,Smart Analytics +AI02066,AI Architect,220299,USD,220299,EX,FT,Finland,L,Finland,100,"NLP, Scala, Data Visualization",Associate,18,Retail,2025-04-18,2025-06-27,994,9.8,Smart Analytics +AI02067,AI Specialist,83499,USD,83499,MI,FL,Israel,M,Israel,50,"Data Visualization, Linux, Python, TensorFlow, PyTorch",Master,4,Manufacturing,2025-01-03,2025-02-28,1120,8.5,Cloud AI Solutions +AI02068,AI Research Scientist,72075,EUR,61264,EN,FT,Germany,M,Germany,50,"MLOps, Azure, AWS, Deep Learning, R",Associate,1,Government,2024-08-02,2024-10-03,1635,6.1,Advanced Robotics +AI02069,Deep Learning Engineer,87037,EUR,73981,MI,CT,Netherlands,M,Netherlands,0,"Deep Learning, Docker, NLP, Hadoop",Master,2,Automotive,2024-10-06,2024-11-02,967,5.4,Smart Analytics +AI02070,AI Research Scientist,123099,USD,123099,MI,FT,Denmark,S,Denmark,0,"PyTorch, AWS, MLOps, Python",PhD,2,Consulting,2025-02-22,2025-05-04,1204,7.5,Autonomous Tech +AI02071,Machine Learning Engineer,104913,EUR,89176,SE,CT,Germany,S,China,0,"Kubernetes, Scala, NLP, Mathematics, TensorFlow",Associate,5,Technology,2024-08-13,2024-10-24,2478,7.5,Machine Intelligence Group +AI02072,Deep Learning Engineer,221690,EUR,188437,EX,CT,Austria,L,Mexico,50,"PyTorch, Python, Git, Spark, Azure",Bachelor,19,Telecommunications,2024-08-05,2024-08-29,1602,7.3,Digital Transformation LLC +AI02073,Data Scientist,113653,EUR,96605,SE,FL,Germany,S,Germany,0,"Data Visualization, Kubernetes, Mathematics",Master,8,Real Estate,2024-01-06,2024-03-09,2077,8.6,DataVision Ltd +AI02074,Computer Vision Engineer,250419,USD,250419,EX,PT,United States,L,United States,100,"Data Visualization, Python, Azure, Scala, GCP",Bachelor,18,Retail,2024-05-17,2024-06-08,2362,7.2,Algorithmic Solutions +AI02075,AI Consultant,108412,EUR,92150,SE,CT,France,S,France,100,"Java, Python, Data Visualization, Linux",Associate,8,Gaming,2024-09-14,2024-10-16,1441,8.1,Algorithmic Solutions +AI02076,AI Specialist,186753,EUR,158740,EX,FL,Netherlands,S,Netherlands,100,"Mathematics, SQL, PyTorch",Associate,16,Technology,2025-04-05,2025-06-01,2436,8.9,Advanced Robotics +AI02077,AI Product Manager,134362,GBP,100772,MI,FT,United Kingdom,L,Finland,100,"Tableau, Hadoop, R, Docker",Associate,3,Consulting,2024-04-04,2024-05-15,2222,7.5,Smart Analytics +AI02078,Data Scientist,157702,USD,157702,EX,CT,Sweden,S,Vietnam,0,"Python, TensorFlow, Data Visualization, PyTorch, Hadoop",PhD,19,Real Estate,2024-04-25,2024-07-07,2122,8,Algorithmic Solutions +AI02079,Data Scientist,69203,USD,69203,EN,FL,Israel,M,Israel,0,"Spark, Scala, Python, Kubernetes, Docker",Master,0,Manufacturing,2024-02-16,2024-04-03,1738,9.9,Advanced Robotics +AI02080,AI Product Manager,97206,GBP,72905,MI,FL,United Kingdom,M,New Zealand,0,"TensorFlow, Scala, Deep Learning, Statistics, AWS",PhD,2,Consulting,2024-03-04,2024-03-18,1813,9.6,Quantum Computing Inc +AI02081,Data Scientist,82737,USD,82737,SE,CT,China,L,Japan,50,"Python, R, TensorFlow",Bachelor,9,Government,2024-06-06,2024-08-17,2069,9.9,DeepTech Ventures +AI02082,Machine Learning Engineer,99693,USD,99693,SE,PT,Sweden,S,Sweden,0,"Docker, Scala, Git, AWS",PhD,7,Telecommunications,2024-08-29,2024-10-20,1189,8.3,Autonomous Tech +AI02083,Autonomous Systems Engineer,82795,USD,82795,EN,PT,Finland,L,Finland,0,"SQL, Git, PyTorch, Spark, GCP",Associate,1,Transportation,2024-08-22,2024-09-13,1102,9.8,AI Innovations +AI02084,AI Research Scientist,174298,USD,174298,EX,FL,Finland,M,United States,50,"TensorFlow, Kubernetes, Statistics, SQL, AWS",Bachelor,13,Technology,2024-09-06,2024-09-28,721,7,Advanced Robotics +AI02085,Machine Learning Researcher,270830,CHF,243747,EX,PT,Switzerland,M,Switzerland,100,"PyTorch, Kubernetes, Tableau, SQL, Spark",Bachelor,11,Consulting,2024-11-10,2024-12-22,1174,7.1,Predictive Systems +AI02086,Machine Learning Researcher,68593,USD,68593,MI,PT,Israel,M,Israel,50,"Docker, Tableau, GCP",Master,3,Transportation,2024-10-05,2024-12-07,1095,9.1,Cloud AI Solutions +AI02087,Machine Learning Engineer,67495,EUR,57371,EN,PT,Netherlands,S,Netherlands,50,"Python, Kubernetes, Computer Vision",Bachelor,1,Transportation,2025-01-18,2025-03-19,2058,6.2,Smart Analytics +AI02088,AI Product Manager,114616,GBP,85962,MI,FL,United Kingdom,M,United Kingdom,50,"Statistics, Kubernetes, GCP, NLP, TensorFlow",Master,3,Energy,2024-03-25,2024-04-15,869,5.6,Neural Networks Co +AI02089,Data Engineer,213578,USD,213578,EX,CT,Sweden,M,Japan,50,"PyTorch, Kubernetes, Hadoop, R",Associate,15,Energy,2025-04-14,2025-05-03,1459,8.6,Algorithmic Solutions +AI02090,AI Product Manager,212620,USD,212620,EX,CT,Denmark,L,Denmark,0,"GCP, PyTorch, Data Visualization, Computer Vision",Bachelor,16,Education,2024-09-10,2024-11-10,905,9.1,Cloud AI Solutions +AI02091,Computer Vision Engineer,56144,USD,56144,SE,CT,China,M,China,100,"SQL, Docker, PyTorch, Kubernetes",Master,6,Real Estate,2024-02-08,2024-03-04,2052,7.4,AI Innovations +AI02092,Research Scientist,81572,EUR,69336,MI,FL,Austria,L,Luxembourg,0,"Computer Vision, Linux, PyTorch, Scala",Master,2,Healthcare,2024-09-25,2024-10-31,2115,8,AI Innovations +AI02093,Head of AI,69805,EUR,59334,EN,FL,Germany,S,South Korea,100,"SQL, Linux, Java, TensorFlow",PhD,1,Government,2024-07-09,2024-07-27,1396,6.2,Autonomous Tech +AI02094,ML Ops Engineer,134815,EUR,114593,SE,CT,Netherlands,S,Vietnam,100,"Docker, Tableau, Git, Kubernetes",PhD,7,Transportation,2024-07-14,2024-08-13,1842,9.6,TechCorp Inc +AI02095,NLP Engineer,201072,EUR,170911,EX,PT,Germany,S,Norway,100,"Linux, PyTorch, Git, Mathematics, Statistics",Bachelor,12,Education,2025-02-09,2025-03-21,965,6.2,Autonomous Tech +AI02096,AI Research Scientist,295447,JPY,32499170,EX,FL,Japan,L,Japan,50,"Spark, Linux, Statistics, PyTorch",Master,13,Finance,2024-01-31,2024-03-26,2060,5.6,Neural Networks Co +AI02097,Deep Learning Engineer,76720,USD,76720,EX,FL,China,M,China,50,"SQL, Kubernetes, TensorFlow, Scala",Associate,14,Gaming,2025-02-25,2025-04-02,970,7.9,Neural Networks Co +AI02098,Machine Learning Engineer,125533,USD,125533,SE,FL,Denmark,S,Denmark,0,"Deep Learning, Java, Scala",PhD,8,Automotive,2024-10-11,2024-12-01,1268,9.5,Digital Transformation LLC +AI02099,Robotics Engineer,253018,CAD,316273,EX,FT,Canada,L,Nigeria,50,"R, PyTorch, SQL, Scala",Associate,17,Government,2024-12-31,2025-03-06,1852,7.6,Cognitive Computing +AI02100,AI Product Manager,133162,GBP,99872,SE,FT,United Kingdom,S,United Kingdom,50,"Python, NLP, SQL, Linux, Kubernetes",Bachelor,7,Gaming,2025-04-14,2025-05-17,779,7.6,Digital Transformation LLC +AI02101,AI Architect,91600,USD,91600,MI,FL,South Korea,L,South Korea,100,"Python, GCP, Scala, Docker, Computer Vision",PhD,4,Finance,2024-04-26,2024-05-30,621,7.1,DataVision Ltd +AI02102,AI Product Manager,157559,EUR,133925,EX,CT,Austria,L,Austria,0,"Azure, MLOps, Scala, Computer Vision",Bachelor,19,Telecommunications,2025-03-13,2025-05-23,873,7.5,DeepTech Ventures +AI02103,Data Scientist,171584,USD,171584,EX,CT,Finland,M,Finland,100,"PyTorch, Python, Statistics",PhD,13,Education,2024-08-28,2024-09-24,1690,6.8,Autonomous Tech +AI02104,ML Ops Engineer,156785,CAD,195981,EX,FT,Canada,M,Canada,50,"SQL, PyTorch, Linux, Tableau",Bachelor,16,Media,2024-03-31,2024-04-20,2139,6.3,DataVision Ltd +AI02105,Machine Learning Engineer,293023,USD,293023,EX,CT,Denmark,M,Australia,100,"Docker, Computer Vision, Python, NLP, Deep Learning",Master,12,Manufacturing,2024-08-10,2024-10-10,1377,8.6,Smart Analytics +AI02106,Principal Data Scientist,86508,JPY,9515880,EN,FT,Japan,L,Japan,0,"Computer Vision, TensorFlow, GCP",Master,0,Technology,2025-03-28,2025-06-09,1511,8.8,Cloud AI Solutions +AI02107,AI Software Engineer,81412,USD,81412,EX,FT,China,S,Philippines,0,"Tableau, Linux, MLOps, Spark, Mathematics",Master,18,Media,2024-06-10,2024-07-22,1689,8.6,Advanced Robotics +AI02108,NLP Engineer,186673,EUR,158672,EX,FT,Austria,S,Austria,50,"Docker, Linux, SQL",Associate,10,Healthcare,2024-07-12,2024-08-22,1860,10,Advanced Robotics +AI02109,Principal Data Scientist,112912,USD,112912,MI,PT,United States,L,United States,100,"SQL, Spark, Git",Bachelor,4,Education,2024-09-19,2024-10-15,631,8.3,Cloud AI Solutions +AI02110,Principal Data Scientist,51942,USD,51942,EN,PT,Sweden,M,Japan,0,"R, Linux, Git, GCP, Deep Learning",PhD,0,Energy,2024-01-24,2024-02-27,828,6,Quantum Computing Inc +AI02111,Research Scientist,127418,USD,127418,MI,FT,Norway,M,Norway,0,"Hadoop, Java, Data Visualization",Associate,3,Automotive,2025-03-05,2025-04-16,1167,6.1,Machine Intelligence Group +AI02112,Research Scientist,96844,USD,96844,EN,CT,Denmark,L,Denmark,50,"MLOps, Kubernetes, Python, TensorFlow, PyTorch",Bachelor,0,Finance,2025-01-23,2025-03-03,2403,7.9,Autonomous Tech +AI02113,Principal Data Scientist,205497,USD,205497,EX,PT,Norway,M,Belgium,100,"Spark, TensorFlow, Data Visualization",Master,13,Automotive,2024-03-12,2024-04-14,990,5.2,Future Systems +AI02114,Machine Learning Researcher,36123,USD,36123,MI,FT,China,S,China,50,"R, SQL, Git, PyTorch",Associate,3,Manufacturing,2025-01-10,2025-02-18,812,9.3,Quantum Computing Inc +AI02115,Data Engineer,26530,USD,26530,EN,PT,China,S,China,0,"Scala, MLOps, SQL",Master,0,Automotive,2025-03-26,2025-04-25,2428,7.5,DataVision Ltd +AI02116,Deep Learning Engineer,118399,CAD,147999,SE,FL,Canada,L,Canada,50,"PyTorch, Scala, R",Master,9,Technology,2024-09-27,2024-11-05,2031,6.9,Cloud AI Solutions +AI02117,Data Analyst,100255,GBP,75191,MI,FT,United Kingdom,M,India,100,"Git, SQL, TensorFlow",Bachelor,2,Consulting,2025-04-25,2025-05-14,1999,8.9,Smart Analytics +AI02118,Research Scientist,129800,SGD,168740,SE,FT,Singapore,L,Singapore,100,"SQL, Computer Vision, Tableau, Python",Associate,6,Consulting,2025-03-18,2025-05-11,1202,8.2,DataVision Ltd +AI02119,Data Engineer,165833,AUD,223875,SE,PT,Australia,L,Australia,100,"NLP, Hadoop, Tableau, TensorFlow, SQL",Associate,8,Consulting,2024-12-31,2025-03-13,604,8.2,DataVision Ltd +AI02120,Computer Vision Engineer,84617,EUR,71924,MI,FL,France,L,France,50,"Azure, Java, Statistics",Master,3,Healthcare,2024-06-24,2024-07-15,1313,8.4,DeepTech Ventures +AI02121,AI Product Manager,228358,USD,228358,EX,FL,Sweden,M,Sweden,50,"TensorFlow, SQL, Python, GCP",Master,19,Transportation,2024-10-01,2024-11-15,849,5.3,Predictive Systems +AI02122,Deep Learning Engineer,89402,CHF,80462,EN,FT,Switzerland,S,Ireland,100,"Java, Git, Kubernetes, Scala, Mathematics",Associate,0,Real Estate,2024-03-28,2024-05-18,1854,8.7,Digital Transformation LLC +AI02123,AI Software Engineer,251892,USD,251892,EX,FT,Finland,L,Finland,100,"Spark, Python, Computer Vision, Data Visualization",Master,14,Technology,2024-07-22,2024-08-20,1045,7.9,Algorithmic Solutions +AI02124,NLP Engineer,91223,USD,91223,MI,PT,Ireland,L,Ireland,100,"Python, R, Statistics, GCP",Associate,4,Energy,2024-06-14,2024-08-24,1730,5.3,Algorithmic Solutions +AI02125,Robotics Engineer,178163,EUR,151439,EX,FL,France,L,France,100,"Linux, Hadoop, NLP, Kubernetes",Bachelor,18,Media,2024-07-07,2024-08-30,610,7.8,Cognitive Computing +AI02126,Machine Learning Researcher,110328,USD,110328,MI,FL,Denmark,M,Denmark,50,"AWS, Data Visualization, Tableau, TensorFlow",Bachelor,2,Energy,2024-11-04,2025-01-02,2362,5.9,DeepTech Ventures +AI02127,Research Scientist,80058,USD,80058,EN,CT,Norway,L,Norway,0,"SQL, PyTorch, Statistics, NLP",Master,0,Consulting,2025-04-13,2025-05-08,2081,8.4,AI Innovations +AI02128,Machine Learning Researcher,81768,USD,81768,SE,CT,China,L,China,100,"Git, R, Computer Vision",Master,7,Consulting,2025-03-10,2025-04-23,1020,5.1,Digital Transformation LLC +AI02129,Computer Vision Engineer,273957,EUR,232863,EX,FT,Netherlands,L,Netherlands,100,"Kubernetes, Azure, Spark, GCP",PhD,13,Government,2024-07-10,2024-08-28,589,7,Advanced Robotics +AI02130,Principal Data Scientist,71171,JPY,7828810,MI,CT,Japan,S,Japan,100,"Python, Statistics, Scala, Git",Master,2,Gaming,2025-03-24,2025-04-30,2269,8.9,AI Innovations +AI02131,Research Scientist,262050,EUR,222743,EX,CT,Netherlands,M,China,50,"Python, R, Tableau, Mathematics, GCP",Bachelor,19,Real Estate,2024-05-09,2024-06-14,2049,6.9,Digital Transformation LLC +AI02132,Principal Data Scientist,74346,JPY,8178060,EN,FL,Japan,S,Japan,50,"Git, MLOps, Python, Scala, Computer Vision",Associate,0,Technology,2024-07-31,2024-08-26,1392,5.6,Cognitive Computing +AI02133,AI Architect,26055,USD,26055,EN,FT,India,M,United States,100,"Python, AWS, Data Visualization, NLP",Master,1,Manufacturing,2025-02-04,2025-04-14,2432,5.8,Smart Analytics +AI02134,Autonomous Systems Engineer,113953,USD,113953,MI,FT,Israel,L,Israel,50,"GCP, PyTorch, Tableau",Bachelor,2,Healthcare,2024-07-07,2024-09-05,1361,9.1,Cloud AI Solutions +AI02135,Data Engineer,176525,GBP,132394,SE,CT,United Kingdom,L,United Kingdom,0,"R, Scala, Data Visualization, Linux, PyTorch",Associate,7,Manufacturing,2024-03-15,2024-04-28,2353,9.3,Advanced Robotics +AI02136,Robotics Engineer,137979,CHF,124181,SE,CT,Switzerland,S,Netherlands,0,"Linux, Python, TensorFlow",Bachelor,6,Gaming,2024-10-26,2024-12-29,1773,9.3,Cloud AI Solutions +AI02137,Data Engineer,232117,GBP,174088,EX,PT,United Kingdom,M,United Kingdom,100,"Computer Vision, SQL, Java",Master,15,Government,2024-11-21,2024-12-16,945,6.7,Cognitive Computing +AI02138,Data Analyst,130819,USD,130819,EX,FT,Finland,M,Finland,100,"Java, R, Mathematics",PhD,15,Telecommunications,2024-09-08,2024-10-04,1792,8.5,Neural Networks Co +AI02139,Machine Learning Engineer,245291,GBP,183968,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Python, Docker, Linux, NLP",Master,17,Telecommunications,2024-11-21,2025-01-19,1549,9.1,Future Systems +AI02140,NLP Engineer,121783,EUR,103516,SE,CT,France,M,Colombia,0,"Mathematics, PyTorch, SQL, Linux",PhD,5,Energy,2024-03-19,2024-04-09,2367,9.4,Cloud AI Solutions +AI02141,Machine Learning Engineer,145307,SGD,188899,SE,PT,Singapore,S,Chile,0,"Scala, Hadoop, MLOps, NLP, Java",Bachelor,5,Gaming,2024-05-17,2024-07-17,1974,8.5,Future Systems +AI02142,Robotics Engineer,77107,USD,77107,EN,FL,Norway,M,Norway,50,"Tableau, Kubernetes, Data Visualization",Bachelor,0,Consulting,2024-08-12,2024-08-30,527,5.8,Digital Transformation LLC +AI02143,AI Architect,67501,CAD,84376,EN,CT,Canada,S,Canada,0,"NLP, Tableau, Scala, PyTorch, SQL",PhD,1,Technology,2024-12-23,2025-02-20,720,6.4,Algorithmic Solutions +AI02144,Robotics Engineer,67669,USD,67669,EX,CT,China,M,China,100,"Deep Learning, Docker, Tableau",Bachelor,14,Gaming,2024-04-28,2024-06-09,1412,9.3,Cognitive Computing +AI02145,Head of AI,100999,EUR,85849,MI,FL,France,L,France,0,"MLOps, PyTorch, Kubernetes, Azure",Associate,2,Energy,2024-02-09,2024-04-02,2384,6.4,Algorithmic Solutions +AI02146,AI Consultant,57275,USD,57275,SE,CT,China,L,China,0,"Python, R, Azure",Associate,7,Real Estate,2025-01-23,2025-04-01,1686,9.4,Quantum Computing Inc +AI02147,Data Analyst,116317,USD,116317,EX,FT,Finland,S,Finland,0,"Data Visualization, Hadoop, Spark, Azure",Master,19,Energy,2024-01-24,2024-03-13,2115,5.8,Algorithmic Solutions +AI02148,Autonomous Systems Engineer,72220,USD,72220,EN,FT,United States,S,Argentina,50,"Statistics, Kubernetes, Mathematics",Bachelor,1,Education,2024-04-01,2024-05-18,1403,9.8,Autonomous Tech +AI02149,Computer Vision Engineer,48520,USD,48520,MI,CT,China,L,China,0,"Data Visualization, Python, TensorFlow, GCP, PyTorch",Associate,4,Transportation,2024-08-17,2024-09-03,1182,8.9,Predictive Systems +AI02150,AI Architect,91794,SGD,119332,MI,FT,Singapore,S,Russia,100,"Docker, Python, TensorFlow",Associate,4,Government,2024-10-23,2024-11-18,1817,9.2,Machine Intelligence Group +AI02151,Head of AI,148235,EUR,126000,SE,FL,Netherlands,L,Ireland,100,"Data Visualization, TensorFlow, Docker, Git",Associate,7,Manufacturing,2024-08-20,2024-09-07,2094,6.2,Neural Networks Co +AI02152,AI Software Engineer,63004,EUR,53553,EN,FL,Germany,S,Germany,100,"Azure, PyTorch, Docker, Kubernetes",PhD,1,Healthcare,2025-03-17,2025-04-28,1850,8.4,Future Systems +AI02153,Principal Data Scientist,256279,USD,256279,EX,PT,Finland,L,Finland,0,"Kubernetes, Python, Java, Linux",Master,13,Healthcare,2024-11-17,2025-01-25,573,6.5,Cognitive Computing +AI02154,Machine Learning Engineer,100220,USD,100220,MI,PT,United States,M,United States,100,"Kubernetes, Git, Scala, Statistics, GCP",Bachelor,2,Automotive,2025-03-09,2025-04-19,1993,9.5,Advanced Robotics +AI02155,Deep Learning Engineer,97614,CAD,122018,SE,CT,Canada,S,Canada,50,"Azure, Scala, SQL, Git",Master,7,Healthcare,2024-06-05,2024-06-25,1140,9.9,Cognitive Computing +AI02156,Data Engineer,128100,USD,128100,SE,FL,Sweden,S,Switzerland,100,"Python, AWS, Git, MLOps",PhD,7,Consulting,2024-09-05,2024-09-24,1215,10,Cloud AI Solutions +AI02157,AI Specialist,78590,USD,78590,EN,FL,Denmark,M,Denmark,50,"Python, Data Visualization, TensorFlow",Bachelor,0,Transportation,2025-03-11,2025-04-11,1220,8.7,DataVision Ltd +AI02158,Research Scientist,56489,USD,56489,EN,CT,United States,S,India,0,"Hadoop, Scala, Tableau, GCP",Master,0,Consulting,2024-08-10,2024-09-05,501,8.1,Predictive Systems +AI02159,Head of AI,145462,GBP,109097,SE,PT,United Kingdom,S,United Kingdom,100,"Git, NLP, Azure",PhD,9,Energy,2025-03-15,2025-05-09,2279,5.1,Quantum Computing Inc +AI02160,Robotics Engineer,114141,USD,114141,SE,FT,South Korea,M,South Korea,100,"Git, Java, Deep Learning, Scala, Mathematics",Master,9,Transportation,2024-03-30,2024-04-17,1412,8.6,Digital Transformation LLC +AI02161,Data Scientist,122099,USD,122099,SE,PT,Israel,S,Israel,100,"Azure, GCP, Python, TensorFlow",Bachelor,9,Media,2024-04-29,2024-06-30,1064,5.2,Digital Transformation LLC +AI02162,Data Engineer,109552,SGD,142418,SE,PT,Singapore,M,Singapore,0,"Linux, SQL, Kubernetes, Azure, Python",Master,7,Telecommunications,2024-08-28,2024-10-17,897,5.1,DeepTech Ventures +AI02163,AI Product Manager,57229,EUR,48645,EN,FT,Germany,S,Germany,0,"Kubernetes, Spark, Computer Vision, PyTorch",Associate,1,Manufacturing,2024-08-22,2024-10-10,831,6.6,Quantum Computing Inc +AI02164,NLP Engineer,174350,EUR,148198,EX,FL,France,M,France,100,"Kubernetes, SQL, Docker, Spark, R",Master,12,Technology,2024-08-14,2024-08-29,2021,6.8,Cognitive Computing +AI02165,AI Consultant,131413,USD,131413,SE,FL,Finland,L,Finland,0,"Java, GCP, Kubernetes",Master,6,Media,2024-05-26,2024-07-15,2012,5.7,Algorithmic Solutions +AI02166,NLP Engineer,109502,CAD,136878,SE,FT,Canada,S,Canada,100,"Data Visualization, SQL, R, PyTorch",Associate,7,Education,2025-04-21,2025-06-27,1888,7.3,DataVision Ltd +AI02167,Autonomous Systems Engineer,29846,USD,29846,MI,FL,India,S,India,50,"Spark, Deep Learning, Computer Vision",Master,4,Finance,2024-08-31,2024-10-06,2061,7.4,Future Systems +AI02168,Computer Vision Engineer,155786,USD,155786,SE,FT,Denmark,M,Portugal,0,"R, Computer Vision, Linux, Deep Learning",Master,8,Transportation,2025-04-12,2025-05-06,2317,5.1,Algorithmic Solutions +AI02169,Data Scientist,84770,USD,84770,EX,FT,India,M,India,100,"AWS, Tableau, Git, Deep Learning",Bachelor,17,Finance,2024-11-25,2024-12-28,1787,7.4,Algorithmic Solutions +AI02170,Computer Vision Engineer,89112,USD,89112,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Java, Python",PhD,2,Technology,2024-07-22,2024-08-06,669,6.1,DeepTech Ventures +AI02171,AI Specialist,104744,USD,104744,EN,FT,Denmark,L,United States,0,"Docker, Python, Scala",Master,1,Technology,2025-01-27,2025-04-03,2167,8,Predictive Systems +AI02172,Data Analyst,199544,USD,199544,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Docker, Hadoop, GCP, Linux",Bachelor,11,Education,2025-03-11,2025-04-01,2130,9.5,Quantum Computing Inc +AI02173,Machine Learning Engineer,93564,EUR,79529,MI,CT,France,S,Hungary,100,"SQL, Azure, Tableau, Java, Statistics",Bachelor,3,Energy,2024-01-05,2024-02-03,1181,6,AI Innovations +AI02174,AI Specialist,109257,AUD,147497,MI,PT,Australia,M,Australia,100,"Linux, Git, Statistics, R",PhD,2,Energy,2024-09-15,2024-11-10,1854,8.5,Advanced Robotics +AI02175,AI Product Manager,233827,EUR,198753,EX,FT,Austria,L,Sweden,100,"Kubernetes, R, SQL, AWS",Associate,19,Retail,2024-04-17,2024-05-09,2089,8.7,Algorithmic Solutions +AI02176,AI Specialist,199622,USD,199622,SE,CT,United States,L,United States,0,"TensorFlow, Deep Learning, MLOps, Git, Kubernetes",PhD,8,Consulting,2024-11-04,2024-11-25,1993,10,Cognitive Computing +AI02177,Data Analyst,158846,USD,158846,EX,PT,Sweden,S,Ukraine,50,"Python, Git, Scala, NLP",Bachelor,10,Technology,2025-03-29,2025-04-20,1386,9.9,Neural Networks Co +AI02178,AI Software Engineer,43785,USD,43785,EN,PT,Israel,S,Israel,100,"Statistics, SQL, Spark, Tableau",Bachelor,0,Telecommunications,2024-05-23,2024-07-07,2022,8.6,Neural Networks Co +AI02179,AI Architect,101184,USD,101184,EX,PT,China,S,Estonia,100,"Data Visualization, Docker, Python, Kubernetes",Master,10,Healthcare,2025-03-16,2025-04-20,513,8.3,Machine Intelligence Group +AI02180,Principal Data Scientist,89965,USD,89965,EX,FT,India,L,India,0,"Python, SQL, Computer Vision, Docker, Java",Associate,16,Manufacturing,2025-02-21,2025-03-20,2467,7.2,AI Innovations +AI02181,Principal Data Scientist,73352,SGD,95358,EN,PT,Singapore,L,Brazil,50,"Docker, Data Visualization, Python, Mathematics, R",Bachelor,0,Finance,2025-02-14,2025-04-08,954,7,Digital Transformation LLC +AI02182,Head of AI,199823,USD,199823,EX,CT,Finland,L,India,0,"Azure, Computer Vision, TensorFlow",Bachelor,11,Transportation,2024-07-22,2024-08-20,2424,5.4,Neural Networks Co +AI02183,ML Ops Engineer,77392,GBP,58044,EN,FL,United Kingdom,M,Latvia,50,"Python, Azure, TensorFlow, Statistics, AWS",PhD,1,Technology,2024-02-26,2024-04-01,841,6.5,Algorithmic Solutions +AI02184,Machine Learning Researcher,75898,CAD,94873,EN,FT,Canada,M,Portugal,0,"Git, PyTorch, SQL, Python",PhD,0,Education,2024-02-03,2024-03-26,1178,8.2,AI Innovations +AI02185,Data Analyst,76715,USD,76715,EN,PT,Israel,L,Israel,50,"Tableau, Hadoop, Deep Learning",PhD,0,Energy,2025-03-24,2025-05-12,756,6.7,DataVision Ltd +AI02186,Machine Learning Engineer,99717,JPY,10968870,MI,PT,Japan,M,Japan,50,"GCP, Azure, Linux, Scala",Master,3,Media,2024-02-18,2024-04-11,1134,7.3,Neural Networks Co +AI02187,AI Research Scientist,181613,USD,181613,EX,FL,Israel,L,Israel,50,"Scala, Linux, Java",Bachelor,11,Consulting,2024-08-02,2024-09-21,514,7.4,Cloud AI Solutions +AI02188,Autonomous Systems Engineer,109710,EUR,93254,MI,PT,Netherlands,L,Australia,100,"SQL, Linux, PyTorch, NLP",Bachelor,2,Energy,2024-04-06,2024-04-27,2356,6.3,Digital Transformation LLC +AI02189,AI Product Manager,195849,JPY,21543390,EX,PT,Japan,L,Japan,0,"Scala, Statistics, NLP",PhD,11,Finance,2024-03-18,2024-05-17,1271,6.8,Future Systems +AI02190,Data Scientist,125807,USD,125807,SE,FT,Sweden,L,Indonesia,0,"Python, Data Visualization, Docker, NLP",PhD,8,Media,2024-05-05,2024-05-31,1151,5.8,Digital Transformation LLC +AI02191,Research Scientist,104357,CHF,93921,MI,PT,Switzerland,M,Switzerland,100,"Java, AWS, Mathematics, Hadoop",Master,3,Government,2025-01-23,2025-02-10,1996,9.6,Smart Analytics +AI02192,Data Scientist,176952,EUR,150409,EX,CT,Netherlands,S,Netherlands,50,"Java, MLOps, R, Linux, NLP",Master,12,Transportation,2025-02-24,2025-03-12,2382,9.7,Smart Analytics +AI02193,Head of AI,57405,EUR,48794,EN,FL,France,M,France,100,"PyTorch, Computer Vision, Git, Azure, Scala",Master,1,Technology,2024-08-31,2024-09-26,605,7,Quantum Computing Inc +AI02194,Data Analyst,130621,EUR,111028,EX,FL,France,S,France,0,"Linux, Hadoop, Python, Computer Vision, Git",PhD,16,Real Estate,2024-05-13,2024-07-22,1072,8.9,Smart Analytics +AI02195,Research Scientist,78485,CAD,98106,EN,PT,Canada,L,Canada,0,"Scala, SQL, Statistics, Hadoop",PhD,0,Retail,2024-07-27,2024-09-20,1057,8,AI Innovations +AI02196,AI Consultant,200595,CHF,180536,SE,CT,Switzerland,M,South Africa,50,"Hadoop, Python, Deep Learning, Azure",Master,5,Media,2024-05-20,2024-07-12,2146,9.2,DeepTech Ventures +AI02197,AI Architect,50119,EUR,42601,EN,FL,France,M,France,0,"Docker, Azure, Computer Vision",PhD,1,Energy,2025-01-03,2025-03-01,2042,5.7,Smart Analytics +AI02198,Computer Vision Engineer,78348,EUR,66596,EN,FL,Germany,L,Czech Republic,0,"Tableau, Java, Kubernetes",Master,1,Finance,2024-08-22,2024-09-09,867,7.6,TechCorp Inc +AI02199,AI Software Engineer,158752,USD,158752,MI,FL,Norway,L,China,0,"Python, GCP, TensorFlow, Computer Vision, PyTorch",PhD,2,Energy,2024-02-19,2024-04-02,751,8.1,Smart Analytics +AI02200,Data Scientist,35696,USD,35696,MI,CT,India,L,India,100,"Scala, TensorFlow, Python, Computer Vision, Kubernetes",PhD,3,Transportation,2024-12-22,2025-02-17,2146,9.8,DataVision Ltd +AI02201,AI Architect,81558,AUD,110103,MI,PT,Australia,S,Portugal,50,"Python, Kubernetes, Deep Learning, AWS, MLOps",Master,4,Media,2024-06-03,2024-07-17,1216,9.3,Cognitive Computing +AI02202,AI Architect,240445,JPY,26448950,EX,PT,Japan,L,Japan,0,"Data Visualization, NLP, Python",PhD,12,Finance,2024-10-11,2024-12-10,2060,5.2,Predictive Systems +AI02203,Research Scientist,60197,USD,60197,SE,FT,China,M,Indonesia,100,"PyTorch, NLP, Hadoop, Statistics, Kubernetes",Master,5,Energy,2024-04-26,2024-07-06,2308,5.2,Machine Intelligence Group +AI02204,Deep Learning Engineer,67887,USD,67887,EN,FT,Norway,M,Norway,0,"PyTorch, Java, Spark, Hadoop, GCP",Bachelor,1,Transportation,2024-11-20,2025-01-22,1444,7.6,Autonomous Tech +AI02205,AI Research Scientist,251281,CAD,314101,EX,FL,Canada,L,Canada,50,"Data Visualization, Python, Azure, Scala, Spark",PhD,11,Transportation,2024-09-16,2024-11-14,1947,8.9,AI Innovations +AI02206,Data Engineer,266985,CHF,240287,EX,CT,Switzerland,L,New Zealand,50,"Tableau, PyTorch, Statistics",PhD,19,Automotive,2025-04-11,2025-04-25,889,7.1,Machine Intelligence Group +AI02207,AI Consultant,129783,EUR,110316,MI,FL,Netherlands,L,Netherlands,0,"Spark, Git, Statistics, PyTorch",Associate,4,Education,2024-01-11,2024-03-22,1435,6.1,Neural Networks Co +AI02208,Data Analyst,79996,GBP,59997,EN,FL,United Kingdom,L,United Kingdom,100,"Azure, GCP, Data Visualization",PhD,1,Healthcare,2024-08-22,2024-10-25,2334,8.6,Autonomous Tech +AI02209,Data Engineer,86496,CAD,108120,MI,FT,Canada,S,Canada,100,"Scala, Java, Mathematics, AWS, TensorFlow",PhD,2,Government,2025-01-17,2025-02-19,777,8.7,Advanced Robotics +AI02210,ML Ops Engineer,114996,USD,114996,MI,FT,Israel,L,Israel,50,"Scala, NLP, Hadoop",Master,4,Technology,2024-10-05,2024-11-13,820,5.7,Predictive Systems +AI02211,AI Architect,124110,USD,124110,SE,FL,Israel,L,Israel,0,"GCP, R, Tableau, Data Visualization, Scala",Bachelor,8,Media,2025-01-09,2025-03-08,975,5.6,Autonomous Tech +AI02212,AI Software Engineer,99108,USD,99108,SE,FT,South Korea,S,South Korea,100,"TensorFlow, Azure, Java, PyTorch, Computer Vision",Bachelor,5,Finance,2024-11-07,2024-12-28,895,6.2,Future Systems +AI02213,AI Product Manager,141155,CHF,127040,MI,PT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Tableau",PhD,3,Real Estate,2024-01-09,2024-02-05,1858,6.8,Future Systems +AI02214,AI Product Manager,71602,USD,71602,EN,FT,Ireland,M,Ireland,100,"Git, Computer Vision, Python, TensorFlow, NLP",Associate,1,Manufacturing,2024-06-14,2024-07-14,1203,7.7,Algorithmic Solutions +AI02215,Machine Learning Researcher,99305,USD,99305,EN,FT,Norway,L,Norway,100,"Kubernetes, SQL, NLP, Statistics",Master,1,Finance,2024-03-17,2024-05-29,1286,7.3,Digital Transformation LLC +AI02216,Machine Learning Engineer,268561,EUR,228277,EX,FT,France,L,India,0,"Git, Python, TensorFlow, Linux",PhD,17,Gaming,2025-02-19,2025-03-12,2172,6.4,AI Innovations +AI02217,AI Software Engineer,101510,CHF,91359,EN,CT,Switzerland,L,Austria,100,"SQL, Hadoop, PyTorch, Deep Learning",PhD,0,Gaming,2024-02-10,2024-03-04,1555,7,Machine Intelligence Group +AI02218,Principal Data Scientist,270963,USD,270963,EX,CT,Denmark,L,Austria,0,"MLOps, Statistics, GCP, PyTorch, Scala",PhD,13,Transportation,2024-10-20,2024-12-23,2253,6.3,Autonomous Tech +AI02219,AI Specialist,79001,USD,79001,MI,CT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker",PhD,4,Retail,2024-10-15,2024-12-18,1577,8.2,Machine Intelligence Group +AI02220,Principal Data Scientist,51039,GBP,38279,EN,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, R, Computer Vision",Master,0,Energy,2024-07-10,2024-08-23,527,5.9,Digital Transformation LLC +AI02221,ML Ops Engineer,86750,EUR,73738,EN,PT,Netherlands,L,Austria,50,"Java, Linux, Azure, GCP",Master,1,Energy,2025-04-21,2025-06-24,2026,8.5,DeepTech Ventures +AI02222,Research Scientist,52962,CAD,66203,EN,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Data Visualization, Python, Spark",Associate,1,Telecommunications,2024-07-20,2024-09-30,1427,6.8,Smart Analytics +AI02223,AI Software Engineer,253468,USD,253468,EX,CT,Sweden,M,Sweden,100,"Scala, R, Data Visualization, NLP, Python",Bachelor,19,Gaming,2024-08-12,2024-10-03,2402,7.5,TechCorp Inc +AI02224,AI Specialist,122016,EUR,103714,SE,PT,Germany,L,Australia,50,"Kubernetes, Hadoop, Tableau, PyTorch",Bachelor,7,Education,2024-11-10,2024-11-24,2156,9.1,Smart Analytics +AI02225,Research Scientist,51691,AUD,69783,EN,FT,Australia,S,Malaysia,50,"PyTorch, Linux, Git, TensorFlow, Deep Learning",PhD,1,Manufacturing,2024-03-11,2024-04-11,2158,9.4,DeepTech Ventures +AI02226,Principal Data Scientist,119127,USD,119127,EX,FT,Israel,S,Israel,0,"SQL, Tableau, MLOps",PhD,13,Finance,2025-02-01,2025-04-03,2048,6.3,Autonomous Tech +AI02227,Computer Vision Engineer,190161,USD,190161,EX,FL,Israel,S,Israel,100,"Azure, AWS, Statistics, GCP, Tableau",Associate,15,Technology,2024-05-12,2024-06-23,741,7.6,Smart Analytics +AI02228,Computer Vision Engineer,241186,USD,241186,EX,FT,Denmark,S,Denmark,0,"SQL, TensorFlow, Mathematics",PhD,14,Telecommunications,2024-09-23,2024-11-03,2069,6.3,Advanced Robotics +AI02229,Research Scientist,103949,CAD,129936,SE,CT,Canada,M,Czech Republic,50,"Kubernetes, Java, Data Visualization, MLOps",Associate,8,Education,2024-09-05,2024-10-20,1017,7.6,Smart Analytics +AI02230,Deep Learning Engineer,199232,USD,199232,EX,FT,Sweden,M,Sweden,100,"PyTorch, Data Visualization, Deep Learning",Bachelor,14,Government,2024-06-01,2024-06-18,1509,7.4,Advanced Robotics +AI02231,AI Research Scientist,157050,USD,157050,EX,PT,Sweden,S,Finland,0,"Tableau, Hadoop, R, Linux",PhD,17,Retail,2024-08-19,2024-09-18,852,7.4,Predictive Systems +AI02232,Computer Vision Engineer,84353,USD,84353,MI,PT,Israel,S,Luxembourg,0,"Azure, AWS, Computer Vision",Bachelor,2,Media,2024-08-26,2024-10-07,1724,7.8,Machine Intelligence Group +AI02233,Robotics Engineer,192697,USD,192697,EX,CT,Denmark,S,Denmark,50,"Java, PyTorch, Mathematics, Data Visualization, SQL",Master,12,Healthcare,2025-02-14,2025-03-09,2434,8.7,DeepTech Ventures +AI02234,NLP Engineer,154367,CAD,192959,SE,FT,Canada,L,Mexico,100,"Git, SQL, GCP, Tableau",PhD,5,Transportation,2024-12-12,2025-01-18,1287,5.1,Neural Networks Co +AI02235,Principal Data Scientist,305641,CHF,275077,EX,PT,Switzerland,S,Switzerland,0,"R, NLP, MLOps, Scala, Docker",Master,19,Transportation,2024-12-26,2025-03-08,674,7.7,Neural Networks Co +AI02236,Computer Vision Engineer,337542,CHF,303788,EX,FL,Switzerland,L,Netherlands,50,"Python, NLP, Tableau",PhD,15,Real Estate,2024-10-26,2025-01-07,1813,6.9,Machine Intelligence Group +AI02237,AI Software Engineer,82530,USD,82530,MI,CT,Finland,M,Germany,100,"Java, GCP, Kubernetes, MLOps",Bachelor,2,Technology,2024-08-13,2024-08-27,1062,5.3,Future Systems +AI02238,AI Specialist,183461,USD,183461,EX,CT,South Korea,L,South Korea,100,"Hadoop, Deep Learning, Data Visualization, Java",PhD,10,Telecommunications,2024-07-15,2024-09-08,2037,7.7,Digital Transformation LLC +AI02239,ML Ops Engineer,112033,USD,112033,SE,CT,Israel,M,Israel,50,"GCP, SQL, Data Visualization, Linux, Scala",Bachelor,9,Transportation,2024-01-29,2024-02-19,775,9.4,Cognitive Computing +AI02240,Deep Learning Engineer,121109,EUR,102943,MI,FL,Germany,L,India,100,"PyTorch, Tableau, MLOps, Linux",PhD,3,Healthcare,2024-07-13,2024-09-06,1184,6.8,Digital Transformation LLC +AI02241,NLP Engineer,208944,EUR,177602,EX,FT,Austria,S,Austria,100,"Data Visualization, R, AWS, Azure",Bachelor,16,Technology,2024-09-27,2024-10-27,924,5.5,AI Innovations +AI02242,AI Product Manager,60646,CAD,75808,EN,PT,Canada,L,Canada,50,"TensorFlow, MLOps, Python, AWS",Master,1,Gaming,2024-01-17,2024-03-29,1189,6.8,Neural Networks Co +AI02243,AI Architect,83782,EUR,71215,MI,FT,Germany,M,Germany,100,"Kubernetes, Statistics, MLOps",Associate,2,Transportation,2024-07-14,2024-07-31,1645,7,Algorithmic Solutions +AI02244,Research Scientist,130792,USD,130792,EX,FL,Finland,S,United Kingdom,0,"Spark, Kubernetes, Data Visualization, Python, Linux",Associate,14,Gaming,2025-04-11,2025-04-26,697,8.4,AI Innovations +AI02245,Head of AI,98316,USD,98316,SE,FL,South Korea,M,South Korea,50,"Linux, Hadoop, SQL",Associate,9,Education,2025-02-16,2025-03-14,1669,7.8,Digital Transformation LLC +AI02246,AI Software Engineer,157782,EUR,134115,SE,PT,Netherlands,M,Netherlands,100,"Git, Python, SQL, Deep Learning, Spark",Bachelor,9,Retail,2025-01-01,2025-02-27,709,5.6,Smart Analytics +AI02247,Computer Vision Engineer,54428,USD,54428,EN,PT,South Korea,M,Netherlands,50,"TensorFlow, Mathematics, Tableau, Kubernetes, Linux",Master,0,Manufacturing,2024-10-26,2024-11-19,1158,5.2,DeepTech Ventures +AI02248,Autonomous Systems Engineer,90867,EUR,77237,MI,FT,Germany,L,Germany,50,"Azure, Git, Hadoop",PhD,2,Education,2025-04-16,2025-06-04,634,9.7,Advanced Robotics +AI02249,Machine Learning Researcher,67221,EUR,57138,EN,FT,Austria,S,Austria,50,"Scala, Hadoop, Computer Vision, GCP",Master,1,Technology,2024-05-05,2024-05-29,2072,7.1,Digital Transformation LLC +AI02250,Principal Data Scientist,154303,EUR,131158,EX,FL,France,M,France,100,"Linux, Git, Tableau",Master,17,Manufacturing,2024-05-23,2024-06-22,2153,7.8,Cloud AI Solutions +AI02251,Data Engineer,100244,CHF,90220,EN,FT,Switzerland,S,Russia,0,"Kubernetes, Java, Docker",Associate,1,Healthcare,2025-03-16,2025-05-11,1905,9.8,Machine Intelligence Group +AI02252,Principal Data Scientist,135424,USD,135424,SE,PT,Denmark,S,New Zealand,100,"Tableau, Azure, Git",PhD,5,Automotive,2024-07-08,2024-08-16,562,7,Quantum Computing Inc +AI02253,AI Research Scientist,61375,EUR,52169,EN,PT,France,S,France,100,"Computer Vision, Python, TensorFlow",Bachelor,0,Automotive,2024-12-20,2025-02-24,1802,9.5,Algorithmic Solutions +AI02254,AI Consultant,113261,USD,113261,MI,PT,Sweden,L,Sweden,0,"Tableau, Python, GCP, TensorFlow",PhD,4,Real Estate,2024-12-04,2025-01-12,1918,8.7,Autonomous Tech +AI02255,AI Product Manager,114736,EUR,97526,SE,PT,Austria,S,Mexico,0,"Python, Computer Vision, GCP, MLOps, Data Visualization",Master,9,Government,2024-04-21,2024-05-08,2032,5.1,Machine Intelligence Group +AI02256,NLP Engineer,48296,USD,48296,MI,PT,China,M,Chile,50,"SQL, Java, Python",Associate,2,Government,2024-08-27,2024-11-01,1041,6.4,Cognitive Computing +AI02257,AI Software Engineer,205168,USD,205168,EX,CT,Sweden,L,Sweden,100,"Spark, TensorFlow, NLP, Computer Vision",Associate,10,Real Estate,2024-10-27,2024-11-15,2325,7.7,Cognitive Computing +AI02258,Data Engineer,44379,USD,44379,SE,FL,China,S,China,0,"Python, Docker, Tableau, Kubernetes",Bachelor,7,Energy,2024-03-28,2024-05-16,2495,6.4,Neural Networks Co +AI02259,Head of AI,89555,AUD,120899,EN,FL,Australia,L,Austria,100,"Azure, Git, Computer Vision, SQL, Scala",Master,1,Telecommunications,2025-01-28,2025-02-28,608,8.8,Cloud AI Solutions +AI02260,Head of AI,186544,CAD,233180,EX,FL,Canada,L,South Africa,0,"AWS, Spark, PyTorch, Linux",Master,15,Automotive,2024-08-14,2024-09-08,990,9.5,Autonomous Tech +AI02261,Deep Learning Engineer,130260,USD,130260,MI,FL,Norway,M,Norway,50,"AWS, Deep Learning, Java, Linux",Associate,3,Finance,2024-04-28,2024-06-13,543,5.1,TechCorp Inc +AI02262,AI Specialist,61880,USD,61880,EX,FT,India,S,India,100,"Spark, Git, Scala",Bachelor,14,Media,2025-01-05,2025-03-18,2089,6.2,Smart Analytics +AI02263,Robotics Engineer,185105,EUR,157339,EX,FT,France,M,France,50,"TensorFlow, Data Visualization, Spark",PhD,11,Real Estate,2024-11-11,2024-12-16,944,6,Neural Networks Co +AI02264,AI Consultant,60068,EUR,51058,EN,CT,Netherlands,M,Netherlands,0,"Docker, Git, R, Linux, Scala",Bachelor,1,Technology,2024-03-07,2024-03-23,1856,5.8,Quantum Computing Inc +AI02265,AI Product Manager,152832,JPY,16811520,SE,FL,Japan,L,Japan,100,"Linux, PyTorch, TensorFlow",Master,9,Consulting,2025-02-01,2025-03-15,2241,7.9,TechCorp Inc +AI02266,AI Consultant,163684,AUD,220973,SE,CT,Australia,L,Belgium,0,"TensorFlow, Python, Spark, Java",Associate,5,Automotive,2024-05-01,2024-07-04,2186,9.7,Future Systems +AI02267,Machine Learning Engineer,51675,AUD,69761,EN,PT,Australia,M,Australia,50,"Git, Scala, Computer Vision, Java, Deep Learning",Bachelor,0,Healthcare,2025-01-08,2025-02-02,1966,5.3,Cloud AI Solutions +AI02268,Principal Data Scientist,270523,USD,270523,EX,PT,Norway,S,Thailand,100,"SQL, MLOps, PyTorch, TensorFlow, Tableau",Associate,12,Gaming,2024-06-16,2024-07-30,1569,9.7,TechCorp Inc +AI02269,Principal Data Scientist,138679,EUR,117877,SE,PT,France,M,Finland,100,"Statistics, Tableau, Linux",Master,8,Retail,2024-11-10,2024-12-30,681,6.2,Autonomous Tech +AI02270,Data Scientist,153448,GBP,115086,EX,PT,United Kingdom,S,United Kingdom,100,"PyTorch, TensorFlow, Hadoop, Kubernetes, R",Bachelor,16,Manufacturing,2024-11-26,2024-12-10,2074,9.7,Quantum Computing Inc +AI02271,Autonomous Systems Engineer,99198,CHF,89278,EN,FL,Switzerland,M,Malaysia,100,"PyTorch, NLP, Git, Azure, Mathematics",PhD,0,Education,2024-01-27,2024-03-20,916,6.3,DeepTech Ventures +AI02272,AI Architect,108736,EUR,92426,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, TensorFlow, Java, SQL, Azure",Associate,6,Automotive,2024-11-28,2024-12-21,1268,7.8,AI Innovations +AI02273,AI Product Manager,108349,EUR,92097,SE,PT,Netherlands,S,Netherlands,0,"Linux, MLOps, NLP",Bachelor,8,Education,2025-02-14,2025-04-25,944,5.1,Cloud AI Solutions +AI02274,AI Consultant,97976,USD,97976,SE,FL,Finland,M,Finland,100,"TensorFlow, Kubernetes, Deep Learning, Scala, Azure",Associate,9,Telecommunications,2024-01-05,2024-02-12,1332,5.6,TechCorp Inc +AI02275,Data Engineer,106852,USD,106852,MI,FT,Sweden,L,United States,50,"Kubernetes, SQL, GCP, Computer Vision",PhD,2,Automotive,2024-07-21,2024-09-01,2193,9.1,Algorithmic Solutions +AI02276,AI Research Scientist,157337,CHF,141603,SE,CT,Switzerland,S,Italy,100,"Scala, PyTorch, MLOps, SQL",Bachelor,5,Retail,2024-06-24,2024-07-30,1623,6.4,Digital Transformation LLC +AI02277,Data Engineer,119797,CHF,107817,EN,FT,Switzerland,L,Switzerland,50,"Python, Linux, Deep Learning",Associate,0,Telecommunications,2024-06-27,2024-07-27,624,6.4,Neural Networks Co +AI02278,Machine Learning Researcher,69161,USD,69161,EX,FL,India,M,India,100,"Deep Learning, TensorFlow, Kubernetes, Statistics",Master,15,Healthcare,2024-07-31,2024-09-18,997,5.6,Machine Intelligence Group +AI02279,Data Engineer,138491,AUD,186963,EX,FL,Australia,M,Australia,50,"Deep Learning, TensorFlow, Linux",Bachelor,18,Government,2024-12-19,2025-01-26,839,5.6,Autonomous Tech +AI02280,AI Product Manager,103654,GBP,77741,MI,FL,United Kingdom,M,United Kingdom,0,"GCP, Python, Docker",Associate,2,Real Estate,2025-04-05,2025-04-26,591,9.9,TechCorp Inc +AI02281,Deep Learning Engineer,61991,USD,61991,EN,CT,Ireland,S,Ireland,50,"Mathematics, Python, AWS, TensorFlow, Scala",Bachelor,0,Retail,2024-11-06,2025-01-11,2413,7.5,Autonomous Tech +AI02282,AI Research Scientist,81076,EUR,68915,EN,CT,Austria,L,Austria,100,"Python, Linux, MLOps, TensorFlow, Azure",Master,0,Consulting,2025-03-28,2025-06-09,927,7.4,Digital Transformation LLC +AI02283,Data Engineer,84481,USD,84481,MI,CT,Israel,S,Israel,100,"Mathematics, Data Visualization, TensorFlow",Master,4,Government,2024-06-24,2024-08-08,1198,8.5,Autonomous Tech +AI02284,Machine Learning Engineer,31910,USD,31910,MI,FL,China,S,Singapore,0,"TensorFlow, SQL, Mathematics, NLP",Bachelor,2,Technology,2024-04-05,2024-06-06,1846,7.7,Cognitive Computing +AI02285,Principal Data Scientist,103659,AUD,139940,MI,PT,Australia,L,Australia,50,"Docker, SQL, NLP, GCP, MLOps",Bachelor,2,Media,2024-03-02,2024-04-08,2362,9.8,Predictive Systems +AI02286,Machine Learning Researcher,241811,AUD,326445,EX,CT,Australia,L,Romania,0,"PyTorch, GCP, Python, Spark, MLOps",PhD,19,Government,2024-06-11,2024-08-06,2082,8.8,Smart Analytics +AI02287,Principal Data Scientist,85528,EUR,72699,MI,PT,Netherlands,M,Netherlands,50,"NLP, Mathematics, Java, R",Associate,3,Technology,2024-12-18,2025-01-21,927,8.4,Algorithmic Solutions +AI02288,Research Scientist,233646,SGD,303740,EX,CT,Singapore,M,Singapore,0,"Statistics, SQL, Computer Vision, Linux, Deep Learning",Bachelor,12,Real Estate,2024-06-23,2024-08-03,2210,5.6,Digital Transformation LLC +AI02289,AI Specialist,180558,USD,180558,EX,PT,Denmark,M,Denmark,100,"GCP, Computer Vision, Java",PhD,10,Finance,2025-04-24,2025-05-31,1812,6.5,DeepTech Ventures +AI02290,Data Scientist,94791,EUR,80572,MI,CT,Germany,L,Germany,100,"TensorFlow, Statistics, Kubernetes, PyTorch, R",Master,3,Government,2024-04-08,2024-05-05,1246,6.5,Machine Intelligence Group +AI02291,Robotics Engineer,189914,USD,189914,EX,FT,United States,M,United States,0,"TensorFlow, Hadoop, Linux, Scala",Bachelor,17,Energy,2025-04-27,2025-06-30,2134,7.6,TechCorp Inc +AI02292,Machine Learning Researcher,96777,GBP,72583,MI,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, PyTorch, Java",Associate,3,Education,2024-07-05,2024-07-19,2490,5.5,Quantum Computing Inc +AI02293,AI Architect,29644,USD,29644,MI,PT,India,L,Norway,100,"Hadoop, Python, SQL, Deep Learning, Azure",Associate,4,Gaming,2024-03-20,2024-04-26,825,8.1,Future Systems +AI02294,Autonomous Systems Engineer,191246,USD,191246,EX,CT,United States,L,Kenya,50,"TensorFlow, Python, AWS, R, PyTorch",Bachelor,16,Technology,2025-02-23,2025-05-06,2386,5.7,AI Innovations +AI02295,Data Analyst,74691,USD,74691,MI,CT,South Korea,L,South Korea,50,"MLOps, Tableau, AWS, Linux",Associate,4,Telecommunications,2024-01-09,2024-03-01,1718,7.9,Autonomous Tech +AI02296,NLP Engineer,94955,JPY,10445050,EN,PT,Japan,L,Japan,0,"Spark, R, MLOps, Kubernetes, Azure",Bachelor,1,Automotive,2024-12-19,2025-01-14,2392,9.9,Smart Analytics +AI02297,Robotics Engineer,174201,USD,174201,SE,PT,Norway,M,Norway,50,"Java, Docker, Tableau, Statistics, MLOps",Bachelor,9,Real Estate,2025-02-05,2025-03-14,1951,7.3,DataVision Ltd +AI02298,Machine Learning Researcher,110906,CHF,99815,MI,FL,Switzerland,M,Switzerland,100,"Linux, Spark, Hadoop",PhD,3,Energy,2024-10-05,2024-12-01,2406,9.8,Cloud AI Solutions +AI02299,Research Scientist,129560,SGD,168428,SE,CT,Singapore,S,Singapore,100,"Scala, Java, MLOps",Master,9,Government,2024-08-05,2024-10-02,2483,9.5,Quantum Computing Inc +AI02300,Deep Learning Engineer,56552,AUD,76345,EN,PT,Australia,M,Australia,0,"MLOps, Python, GCP, SQL, Linux",Master,1,Retail,2024-09-01,2024-10-01,1431,8,Machine Intelligence Group +AI02301,AI Product Manager,82665,USD,82665,SE,FT,China,L,Finland,100,"Kubernetes, R, Java, SQL, NLP",Master,6,Gaming,2024-01-26,2024-02-13,1960,7,DataVision Ltd +AI02302,AI Specialist,57257,USD,57257,EN,CT,Ireland,S,Ireland,50,"Deep Learning, MLOps, Hadoop, GCP",Bachelor,0,Healthcare,2024-04-12,2024-04-27,1328,9.7,Machine Intelligence Group +AI02303,Deep Learning Engineer,156738,USD,156738,SE,FT,United States,S,United States,50,"Spark, Scala, Mathematics",PhD,8,Transportation,2024-07-31,2024-08-22,1295,6.4,Cognitive Computing +AI02304,Data Analyst,105347,EUR,89545,SE,CT,Netherlands,S,Netherlands,0,"Linux, R, MLOps",Bachelor,6,Consulting,2024-01-27,2024-03-05,2296,9.4,Advanced Robotics +AI02305,AI Product Manager,223454,JPY,24579940,EX,FT,Japan,S,Japan,100,"Computer Vision, R, PyTorch, GCP",Associate,19,Retail,2025-02-25,2025-03-17,510,5.4,DeepTech Ventures +AI02306,Machine Learning Engineer,72740,USD,72740,MI,PT,Finland,M,Netherlands,0,"GCP, Linux, MLOps, Tableau",Bachelor,3,Media,2025-01-08,2025-02-14,2001,5.1,Autonomous Tech +AI02307,Research Scientist,107622,USD,107622,MI,PT,Ireland,L,Ireland,50,"Git, SQL, PyTorch",Associate,4,Telecommunications,2024-03-06,2024-04-05,602,5.9,TechCorp Inc +AI02308,Principal Data Scientist,150523,EUR,127945,EX,CT,France,S,France,100,"Java, NLP, AWS",Master,18,Education,2024-11-20,2024-12-30,1927,6.8,Neural Networks Co +AI02309,Data Scientist,134704,EUR,114498,SE,FT,Austria,L,Malaysia,0,"Statistics, SQL, GCP, NLP",PhD,5,Manufacturing,2024-08-02,2024-08-27,2230,9.1,AI Innovations +AI02310,Research Scientist,51843,USD,51843,EN,CT,Finland,S,Sweden,0,"Kubernetes, Hadoop, Java, Computer Vision, Tableau",Master,1,Technology,2024-08-25,2024-10-16,797,7.3,TechCorp Inc +AI02311,AI Research Scientist,81429,EUR,69215,MI,FL,Germany,M,Germany,50,"Linux, Git, GCP, AWS, Spark",Master,3,Healthcare,2025-02-14,2025-03-02,2079,5.8,AI Innovations +AI02312,Deep Learning Engineer,208862,CAD,261078,EX,FL,Canada,L,Canada,50,"MLOps, Tableau, Git, Python, Scala",Associate,13,Gaming,2024-06-20,2024-07-25,1901,5.6,Neural Networks Co +AI02313,Machine Learning Engineer,90374,USD,90374,SE,FT,Israel,S,Israel,50,"R, Tableau, Azure, SQL",Master,7,Media,2024-07-10,2024-09-17,1887,9.5,Algorithmic Solutions +AI02314,AI Consultant,61463,EUR,52244,MI,PT,France,S,France,100,"Scala, Azure, MLOps, Python",Associate,3,Finance,2024-11-24,2025-01-11,2182,6,Machine Intelligence Group +AI02315,Deep Learning Engineer,109194,USD,109194,SE,CT,Finland,M,Finland,50,"R, Computer Vision, GCP",Associate,7,Technology,2024-04-01,2024-06-05,1756,7.6,Quantum Computing Inc +AI02316,AI Software Engineer,170066,USD,170066,EX,CT,South Korea,S,Thailand,0,"Data Visualization, Python, PyTorch",Associate,18,Education,2024-05-31,2024-07-18,835,6.1,Quantum Computing Inc +AI02317,Machine Learning Engineer,130203,USD,130203,SE,FL,Sweden,M,Sweden,100,"SQL, Statistics, R, MLOps, Hadoop",Bachelor,5,Education,2024-04-27,2024-06-22,1041,8.1,Algorithmic Solutions +AI02318,Robotics Engineer,92631,USD,92631,MI,CT,United States,M,United States,50,"AWS, Java, Python, GCP, Tableau",Associate,2,Transportation,2024-12-12,2025-01-11,2185,7,Cloud AI Solutions +AI02319,Data Analyst,124406,EUR,105745,SE,CT,France,S,France,50,"Computer Vision, PyTorch, Linux, AWS, SQL",PhD,6,Transportation,2024-01-15,2024-02-21,1041,9.3,Quantum Computing Inc +AI02320,Machine Learning Researcher,81253,USD,81253,MI,FL,Israel,M,Israel,0,"Azure, Git, NLP, Deep Learning, TensorFlow",Bachelor,4,Retail,2024-11-18,2025-01-13,2045,7.4,DeepTech Ventures +AI02321,Data Analyst,94671,EUR,80470,MI,CT,Germany,M,Germany,0,"PyTorch, Kubernetes, Mathematics",Associate,4,Automotive,2024-07-01,2024-08-11,1911,8.4,Smart Analytics +AI02322,Data Scientist,104689,USD,104689,MI,FL,Ireland,M,Ireland,50,"Tableau, Python, TensorFlow, Hadoop",Bachelor,2,Gaming,2024-01-02,2024-03-05,1563,5.7,DeepTech Ventures +AI02323,Research Scientist,124477,EUR,105805,SE,PT,Netherlands,L,Netherlands,100,"Java, R, SQL, Git",Associate,7,Government,2024-02-22,2024-03-17,655,8.5,Future Systems +AI02324,Machine Learning Engineer,225013,EUR,191261,EX,PT,Netherlands,S,Argentina,0,"SQL, Python, Java",PhD,17,Transportation,2024-08-18,2024-09-09,1668,7,Future Systems +AI02325,AI Specialist,57156,USD,57156,EN,PT,Finland,M,Finland,100,"GCP, MLOps, PyTorch",PhD,0,Technology,2024-10-24,2024-12-09,1115,8.4,Machine Intelligence Group +AI02326,Robotics Engineer,75630,USD,75630,MI,PT,Israel,S,Israel,100,"NLP, Mathematics, MLOps, Docker",Associate,2,Finance,2024-11-30,2025-02-07,1371,5.3,Cognitive Computing +AI02327,Data Scientist,193038,USD,193038,EX,CT,Israel,M,Israel,50,"GCP, Linux, MLOps, Mathematics, AWS",PhD,12,Automotive,2024-08-30,2024-10-30,2331,8.4,Predictive Systems +AI02328,ML Ops Engineer,354091,USD,354091,EX,FT,Norway,L,Thailand,0,"Java, Scala, GCP, Mathematics, MLOps",Master,15,Gaming,2024-05-26,2024-06-24,2237,9.6,Autonomous Tech +AI02329,Computer Vision Engineer,116471,CAD,145589,MI,FL,Canada,L,Canada,50,"Statistics, Linux, Azure, Kubernetes, Computer Vision",Master,4,Real Estate,2025-03-04,2025-05-13,1445,6,Neural Networks Co +AI02330,Computer Vision Engineer,52386,EUR,44528,EN,PT,France,M,Thailand,100,"Python, Kubernetes, Data Visualization, TensorFlow",Master,1,Manufacturing,2025-04-27,2025-06-09,1561,8.3,Cloud AI Solutions +AI02331,AI Specialist,23595,USD,23595,EN,CT,China,S,China,100,"NLP, Python, TensorFlow",Associate,1,Retail,2024-08-13,2024-10-13,1556,7.7,Predictive Systems +AI02332,AI Research Scientist,123617,AUD,166883,EX,FL,Australia,S,Australia,0,"MLOps, Mathematics, Python, TensorFlow, Git",Associate,17,Transportation,2024-07-07,2024-09-07,838,5.6,Quantum Computing Inc +AI02333,Robotics Engineer,294173,USD,294173,EX,FT,United States,L,Switzerland,0,"SQL, GCP, Tableau, TensorFlow, Python",Master,16,Media,2025-01-25,2025-02-22,1739,5.6,DeepTech Ventures +AI02334,Data Engineer,158889,USD,158889,SE,FT,United States,L,Netherlands,100,"AWS, Hadoop, Deep Learning, Mathematics, SQL",Master,9,Technology,2024-01-20,2024-03-27,1615,6.4,Future Systems +AI02335,Research Scientist,92187,USD,92187,SE,PT,Israel,S,Spain,0,"Data Visualization, Computer Vision, GCP, Scala, NLP",PhD,8,Telecommunications,2024-08-25,2024-09-22,1474,5.5,Quantum Computing Inc +AI02336,ML Ops Engineer,266476,EUR,226505,EX,PT,France,L,France,0,"Azure, Hadoop, Data Visualization, Spark",Bachelor,18,Gaming,2024-02-22,2024-04-22,886,8.2,Autonomous Tech +AI02337,Data Scientist,64951,EUR,55208,EN,FL,Netherlands,S,Austria,0,"PyTorch, Kubernetes, Java, Azure, MLOps",Master,1,Media,2024-03-15,2024-04-23,1222,9.2,DeepTech Ventures +AI02338,AI Research Scientist,173215,EUR,147233,EX,CT,Netherlands,M,Netherlands,50,"Computer Vision, AWS, Python, TensorFlow, Data Visualization",PhD,19,Telecommunications,2024-02-15,2024-03-15,733,5.1,TechCorp Inc +AI02339,Machine Learning Researcher,114900,USD,114900,MI,PT,Denmark,M,Indonesia,0,"Python, Kubernetes, Git",Bachelor,3,Retail,2024-12-17,2025-02-27,1669,9.5,Future Systems +AI02340,AI Consultant,65123,USD,65123,MI,FT,Finland,S,Finland,0,"SQL, R, AWS, Python",PhD,3,Manufacturing,2025-02-10,2025-03-22,1882,9.2,Smart Analytics +AI02341,AI Consultant,176135,EUR,149715,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Deep Learning, SQL, NLP",Bachelor,17,Automotive,2024-02-18,2024-03-21,512,9.6,Neural Networks Co +AI02342,AI Specialist,128894,USD,128894,EX,FL,South Korea,M,South Korea,100,"Scala, AWS, MLOps, Data Visualization, Statistics",Bachelor,15,Telecommunications,2024-01-24,2024-03-25,2001,8.2,TechCorp Inc +AI02343,AI Specialist,140129,CAD,175161,EX,CT,Canada,M,Canada,0,"Java, Python, GCP",Bachelor,15,Finance,2024-03-19,2024-05-25,1796,6.1,AI Innovations +AI02344,Head of AI,211366,EUR,179661,EX,CT,Austria,S,Austria,100,"R, SQL, Kubernetes, Git, Tableau",Associate,17,Consulting,2025-03-30,2025-04-14,1025,6.6,Future Systems +AI02345,Data Scientist,89067,GBP,66800,MI,FT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Tableau, Git",Master,2,Government,2024-03-23,2024-06-03,1133,8,Predictive Systems +AI02346,Deep Learning Engineer,120608,AUD,162821,SE,FL,Australia,S,Spain,100,"Python, TensorFlow, Data Visualization",Master,9,Healthcare,2024-10-23,2024-11-26,2358,5.9,Advanced Robotics +AI02347,AI Research Scientist,173641,CAD,217051,EX,FL,Canada,S,Canada,0,"Python, Linux, Scala, TensorFlow, R",Bachelor,11,Healthcare,2025-01-20,2025-02-28,2102,5.6,DeepTech Ventures +AI02348,AI Research Scientist,93978,JPY,10337580,MI,PT,Japan,L,Austria,50,"Python, Git, Kubernetes, TensorFlow, Scala",PhD,2,Manufacturing,2025-02-06,2025-03-13,1541,5,Cognitive Computing +AI02349,Data Analyst,291451,CHF,262306,EX,PT,Switzerland,S,Switzerland,100,"Python, TensorFlow, PyTorch, SQL, Hadoop",Associate,18,Education,2024-10-05,2024-12-14,2356,5.5,Cognitive Computing +AI02350,Data Engineer,115058,USD,115058,MI,FL,Denmark,L,Denmark,100,"Scala, NLP, Python, Deep Learning",Master,4,Consulting,2024-03-26,2024-05-10,2092,7.1,Predictive Systems +AI02351,Head of AI,121394,USD,121394,MI,PT,Norway,M,Norway,100,"Linux, Kubernetes, MLOps, PyTorch",PhD,4,Gaming,2024-10-18,2024-12-23,1538,6.8,DeepTech Ventures +AI02352,AI Specialist,51431,USD,51431,MI,CT,China,L,China,50,"Deep Learning, Git, Mathematics, Data Visualization, R",Bachelor,4,Manufacturing,2024-05-31,2024-06-17,2302,7.1,Smart Analytics +AI02353,Robotics Engineer,90064,USD,90064,MI,FT,United States,M,United States,0,"Python, TensorFlow, Computer Vision, Kubernetes",Associate,3,Real Estate,2025-01-29,2025-03-28,1740,8.5,Future Systems +AI02354,Data Scientist,120867,JPY,13295370,SE,PT,Japan,S,Australia,50,"Java, R, Tableau",Associate,6,Retail,2024-03-31,2024-04-29,2008,5.7,Cloud AI Solutions +AI02355,Data Engineer,51975,EUR,44179,EN,FT,Netherlands,S,South Africa,100,"Git, Docker, MLOps",PhD,0,Retail,2024-03-21,2024-04-29,1266,5.5,Cognitive Computing +AI02356,AI Product Manager,125213,EUR,106431,SE,FL,Netherlands,S,Netherlands,50,"R, AWS, Azure",Associate,7,Manufacturing,2024-07-26,2024-09-20,1233,9.9,Machine Intelligence Group +AI02357,AI Specialist,73632,EUR,62587,EN,FL,Netherlands,L,Netherlands,100,"Git, Kubernetes, Spark",Master,0,Automotive,2024-09-23,2024-10-10,2163,7.7,DeepTech Ventures +AI02358,AI Consultant,147336,USD,147336,SE,CT,Israel,L,Israel,50,"Hadoop, Scala, PyTorch, TensorFlow, Python",Master,9,Healthcare,2024-03-12,2024-05-03,2452,8.1,Cloud AI Solutions +AI02359,Data Engineer,113940,JPY,12533400,SE,FL,Japan,S,France,0,"Java, AWS, Linux, GCP, Docker",Associate,7,Transportation,2024-01-28,2024-03-21,1981,6.4,TechCorp Inc +AI02360,Robotics Engineer,115793,EUR,98424,SE,PT,Netherlands,M,Austria,0,"GCP, Statistics, Hadoop",Associate,5,Retail,2025-04-16,2025-06-07,2490,6.9,Digital Transformation LLC +AI02361,Research Scientist,385250,CHF,346725,EX,CT,Switzerland,L,China,0,"Kubernetes, SQL, Docker, Java, Python",Associate,19,Retail,2024-12-31,2025-02-20,2183,6.5,Smart Analytics +AI02362,ML Ops Engineer,97449,EUR,82832,EN,FT,Netherlands,L,Belgium,50,"Linux, Tableau, Python, Deep Learning, TensorFlow",Associate,0,Manufacturing,2024-02-11,2024-03-10,665,5.2,Machine Intelligence Group +AI02363,Autonomous Systems Engineer,158205,EUR,134474,EX,CT,France,L,Mexico,100,"Scala, Linux, Docker, Statistics",Associate,12,Healthcare,2024-08-12,2024-08-27,656,8.8,Predictive Systems +AI02364,Machine Learning Researcher,227940,SGD,296322,EX,FL,Singapore,L,Finland,0,"GCP, Java, SQL",Associate,11,Consulting,2024-09-27,2024-11-13,1038,9.3,Smart Analytics +AI02365,AI Specialist,82774,USD,82774,MI,PT,Israel,L,Sweden,50,"TensorFlow, Java, Deep Learning, Spark",Associate,3,Technology,2024-02-27,2024-04-01,1190,7.9,TechCorp Inc +AI02366,Data Engineer,151102,CHF,135992,SE,CT,Switzerland,S,China,0,"SQL, TensorFlow, AWS, NLP",Associate,6,Real Estate,2024-12-19,2025-01-24,1992,8.7,Advanced Robotics +AI02367,Computer Vision Engineer,135010,USD,135010,MI,CT,Norway,M,Ireland,50,"Statistics, AWS, PyTorch, Data Visualization, Spark",PhD,4,Retail,2025-01-01,2025-02-03,589,6.2,Algorithmic Solutions +AI02368,Head of AI,99493,JPY,10944230,MI,FL,Japan,S,Japan,100,"Deep Learning, Tableau, SQL",PhD,2,Energy,2024-06-25,2024-07-22,2338,8.6,TechCorp Inc +AI02369,AI Product Manager,104842,GBP,78632,MI,CT,United Kingdom,L,Australia,50,"Azure, Scala, AWS, TensorFlow, Statistics",Master,2,Healthcare,2025-03-15,2025-05-26,1211,8.6,Cloud AI Solutions +AI02370,Head of AI,77587,USD,77587,EN,FT,Sweden,L,Estonia,100,"TensorFlow, Linux, R",Master,0,Manufacturing,2024-05-06,2024-06-05,2238,8,Smart Analytics +AI02371,ML Ops Engineer,94792,SGD,123230,MI,FL,Singapore,L,Singapore,50,"AWS, MLOps, Python, TensorFlow",Master,4,Transportation,2024-03-06,2024-05-11,695,6.8,Autonomous Tech +AI02372,AI Consultant,170382,EUR,144825,SE,PT,Netherlands,L,Netherlands,0,"Statistics, Scala, Java",PhD,6,Manufacturing,2024-12-09,2025-01-30,1927,7.3,Autonomous Tech +AI02373,AI Consultant,69714,USD,69714,EN,PT,Finland,M,Switzerland,100,"Scala, Linux, Python",Associate,0,Manufacturing,2024-04-15,2024-06-03,1972,5.9,Quantum Computing Inc +AI02374,AI Specialist,61848,USD,61848,EN,FT,Ireland,L,Ireland,100,"Hadoop, Data Visualization, Python, PyTorch, Deep Learning",PhD,0,Real Estate,2025-01-10,2025-03-05,651,8,Quantum Computing Inc +AI02375,Computer Vision Engineer,65280,EUR,55488,EN,CT,Netherlands,M,Netherlands,100,"Azure, PyTorch, Spark, SQL",PhD,0,Retail,2024-11-04,2024-12-08,1890,6.5,Neural Networks Co +AI02376,Deep Learning Engineer,67421,USD,67421,EN,PT,United States,S,Sweden,50,"Docker, Tableau, Kubernetes, SQL, GCP",PhD,0,Real Estate,2025-02-15,2025-04-10,2051,8.7,Advanced Robotics +AI02377,Data Engineer,276843,USD,276843,EX,FL,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, GCP",PhD,11,Retail,2024-08-10,2024-09-09,740,6.2,Cognitive Computing +AI02378,Computer Vision Engineer,86366,USD,86366,MI,CT,Norway,S,Norway,0,"Statistics, AWS, Kubernetes, Computer Vision, GCP",PhD,4,Education,2024-01-16,2024-03-28,1664,7.7,DataVision Ltd +AI02379,AI Specialist,113593,SGD,147671,SE,PT,Singapore,M,Singapore,100,"SQL, Data Visualization, Tableau, TensorFlow",PhD,9,Real Estate,2024-04-06,2024-06-16,1375,6,Neural Networks Co +AI02380,Autonomous Systems Engineer,248477,USD,248477,EX,CT,United States,L,Austria,100,"Git, TensorFlow, Linux, NLP, Docker",Associate,17,Telecommunications,2024-08-08,2024-08-28,2245,7.4,Machine Intelligence Group +AI02381,Head of AI,140516,USD,140516,SE,FL,Israel,M,Israel,0,"Python, Kubernetes, Tableau, AWS, Computer Vision",Bachelor,5,Real Estate,2024-02-06,2024-04-01,2138,5.8,Algorithmic Solutions +AI02382,ML Ops Engineer,101660,USD,101660,MI,CT,Israel,M,Israel,50,"Tableau, GCP, Hadoop",Master,4,Telecommunications,2025-01-08,2025-02-01,1455,5.1,AI Innovations +AI02383,NLP Engineer,59401,AUD,80191,EN,PT,Australia,S,Australia,0,"Statistics, Python, MLOps, Data Visualization",Associate,1,Real Estate,2025-02-22,2025-03-11,2022,6.2,DataVision Ltd +AI02384,Machine Learning Researcher,282872,CHF,254585,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, SQL, Mathematics",Master,16,Consulting,2024-10-20,2024-11-14,1004,7.7,TechCorp Inc +AI02385,AI Consultant,79004,USD,79004,EN,FL,Denmark,S,Denmark,50,"R, PyTorch, Mathematics",Bachelor,1,Government,2024-10-07,2024-11-22,1888,9,Digital Transformation LLC +AI02386,Autonomous Systems Engineer,90214,USD,90214,EX,CT,China,L,China,100,"Java, PyTorch, SQL, NLP",PhD,14,Healthcare,2024-11-23,2024-12-08,1536,6.3,Machine Intelligence Group +AI02387,NLP Engineer,177517,USD,177517,EX,PT,Denmark,S,Denmark,0,"PyTorch, Tableau, Java, GCP, R",PhD,10,Consulting,2024-05-02,2024-06-22,1170,9.2,TechCorp Inc +AI02388,Research Scientist,138067,USD,138067,SE,PT,Denmark,S,Denmark,100,"Linux, GCP, R, Mathematics",PhD,6,Automotive,2024-05-19,2024-07-17,1830,5.3,Predictive Systems +AI02389,AI Product Manager,175216,EUR,148934,SE,FL,Germany,L,Austria,100,"Linux, Statistics, Data Visualization",Bachelor,6,Retail,2024-10-24,2024-12-14,909,7.9,Quantum Computing Inc +AI02390,Machine Learning Engineer,67149,EUR,57077,EN,PT,France,M,France,0,"Data Visualization, Kubernetes, Spark",Master,0,Telecommunications,2024-12-10,2025-02-06,840,8.6,Advanced Robotics +AI02391,AI Consultant,65086,USD,65086,EN,CT,Sweden,L,Sweden,0,"Data Visualization, PyTorch, Kubernetes, Azure",Associate,1,Government,2024-11-10,2025-01-22,1761,8.1,Predictive Systems +AI02392,Principal Data Scientist,97236,USD,97236,MI,PT,Denmark,S,Ireland,0,"Spark, SQL, Computer Vision",PhD,3,Manufacturing,2024-10-15,2024-12-04,2272,6.9,Advanced Robotics +AI02393,Data Analyst,33499,USD,33499,MI,PT,India,L,India,50,"Data Visualization, R, Linux, GCP",Bachelor,2,Energy,2025-04-03,2025-05-15,1644,8.9,Quantum Computing Inc +AI02394,Data Analyst,83973,EUR,71377,MI,FL,France,S,France,0,"GCP, SQL, Git",PhD,2,Energy,2024-04-15,2024-06-18,2438,7.1,Neural Networks Co +AI02395,AI Software Engineer,77052,USD,77052,MI,CT,Ireland,S,Ireland,50,"GCP, Hadoop, TensorFlow, Deep Learning, AWS",Associate,2,Education,2024-10-08,2024-11-07,1146,9.3,Autonomous Tech +AI02396,NLP Engineer,121702,SGD,158213,SE,FT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Kubernetes, Data Visualization, Java",Bachelor,5,Transportation,2024-07-15,2024-08-09,1798,6.5,Advanced Robotics +AI02397,Data Scientist,226834,USD,226834,EX,CT,Norway,L,Norway,0,"PyTorch, SQL, NLP, R",Master,14,Finance,2024-11-19,2025-01-27,1368,8.2,DataVision Ltd +AI02398,AI Specialist,269663,GBP,202247,EX,FL,United Kingdom,L,Singapore,100,"Mathematics, Git, SQL, TensorFlow",Master,13,Government,2024-08-10,2024-09-15,1189,8.7,AI Innovations +AI02399,ML Ops Engineer,121309,USD,121309,SE,FT,Sweden,L,Sweden,100,"SQL, Deep Learning, Tableau",PhD,7,Real Estate,2024-09-11,2024-10-01,1599,7.5,AI Innovations +AI02400,Machine Learning Researcher,81603,USD,81603,MI,FT,South Korea,S,South Korea,100,"Python, Mathematics, Data Visualization, Scala, Azure",Bachelor,2,Consulting,2025-04-19,2025-06-11,927,9.5,Predictive Systems +AI02401,AI Architect,101849,USD,101849,MI,PT,Denmark,S,France,0,"Python, Azure, TensorFlow",PhD,2,Telecommunications,2024-07-16,2024-09-24,546,8.6,Algorithmic Solutions +AI02402,Deep Learning Engineer,184180,JPY,20259800,SE,PT,Japan,L,Ukraine,0,"Tableau, TensorFlow, GCP, Data Visualization",PhD,9,Automotive,2024-11-15,2024-12-28,2001,7.7,Algorithmic Solutions +AI02403,AI Architect,117248,USD,117248,EN,CT,Denmark,L,Denmark,100,"Docker, Kubernetes, Statistics, Tableau, Python",PhD,0,Education,2024-07-20,2024-08-07,624,7.9,Future Systems +AI02404,Machine Learning Researcher,95725,JPY,10529750,MI,CT,Japan,S,Japan,0,"AWS, Linux, Kubernetes, Data Visualization",Bachelor,4,Media,2025-03-27,2025-05-05,720,6.6,Smart Analytics +AI02405,Computer Vision Engineer,101075,EUR,85914,MI,CT,Germany,M,Germany,0,"TensorFlow, Statistics, Spark, Linux",Bachelor,2,Healthcare,2024-05-19,2024-06-18,2308,5.7,Autonomous Tech +AI02406,AI Architect,138619,CAD,173274,SE,PT,Canada,M,Canada,50,"Kubernetes, PyTorch, Linux, AWS",Bachelor,9,Telecommunications,2025-01-01,2025-01-15,690,7.3,Machine Intelligence Group +AI02407,Data Engineer,138645,AUD,187171,SE,CT,Australia,L,Australia,100,"Deep Learning, Mathematics, PyTorch",Bachelor,5,Finance,2024-10-28,2024-12-18,1590,9.7,TechCorp Inc +AI02408,AI Product Manager,55621,EUR,47278,EN,CT,Netherlands,M,Netherlands,50,"R, Python, Computer Vision, Deep Learning",Bachelor,1,Healthcare,2025-02-04,2025-04-04,684,7.8,Quantum Computing Inc +AI02409,Head of AI,135303,EUR,115008,SE,FL,Germany,L,Germany,100,"AWS, Git, SQL, Docker, Statistics",Bachelor,7,Retail,2024-09-14,2024-09-29,2317,7.9,Neural Networks Co +AI02410,Data Scientist,172436,USD,172436,SE,FT,United States,L,United States,50,"Tableau, Hadoop, Python",Associate,6,Real Estate,2025-03-07,2025-03-31,1364,5.4,Neural Networks Co +AI02411,Data Scientist,152590,AUD,205997,EX,PT,Australia,M,Australia,50,"GCP, Python, NLP, Computer Vision, Data Visualization",Bachelor,17,Finance,2024-08-12,2024-09-02,1932,9.5,DataVision Ltd +AI02412,AI Specialist,110412,USD,110412,SE,PT,Finland,L,Austria,50,"Docker, Spark, Hadoop, Git, SQL",Master,5,Healthcare,2024-03-01,2024-03-17,2307,8.4,Autonomous Tech +AI02413,Data Analyst,98339,GBP,73754,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, Python, Java, Linux",Bachelor,8,Retail,2024-05-09,2024-05-30,1819,7.5,Quantum Computing Inc +AI02414,Machine Learning Engineer,68002,USD,68002,EN,FT,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, Python",Bachelor,0,Consulting,2024-10-04,2024-11-29,1489,5.7,Cloud AI Solutions +AI02415,Data Engineer,187944,JPY,20673840,EX,CT,Japan,S,Germany,50,"Python, SQL, TensorFlow",Associate,10,Retail,2024-08-02,2024-08-29,1862,9.4,Cognitive Computing +AI02416,Autonomous Systems Engineer,50316,USD,50316,EN,CT,Sweden,S,France,100,"Linux, Docker, Data Visualization, PyTorch, Deep Learning",Bachelor,1,Education,2024-02-10,2024-04-07,1983,9.2,Neural Networks Co +AI02417,Data Analyst,104865,USD,104865,MI,FT,Denmark,M,Denmark,100,"NLP, Python, Java, Statistics",Master,2,Gaming,2024-09-02,2024-10-28,608,7.7,Cloud AI Solutions +AI02418,Deep Learning Engineer,79547,EUR,67615,MI,FL,France,S,France,50,"Statistics, Java, Data Visualization, Computer Vision, Linux",Bachelor,4,Government,2024-06-07,2024-08-17,2315,7.9,Future Systems +AI02419,Data Analyst,48817,USD,48817,EN,PT,Israel,S,Singapore,50,"Linux, R, Git, Kubernetes, Statistics",Bachelor,0,Energy,2024-01-02,2024-02-19,2161,8.2,Algorithmic Solutions +AI02420,Deep Learning Engineer,60358,EUR,51304,EN,FT,France,M,France,50,"Git, Scala, Tableau",PhD,1,Government,2025-01-24,2025-03-09,2400,8.9,DeepTech Ventures +AI02421,Data Scientist,36483,USD,36483,EN,CT,China,M,China,100,"AWS, Java, Tableau, Python",Bachelor,1,Real Estate,2024-12-19,2025-02-03,2044,7,Predictive Systems +AI02422,AI Specialist,34602,USD,34602,MI,CT,India,S,India,50,"Scala, TensorFlow, MLOps, Spark, Deep Learning",Bachelor,4,Consulting,2025-02-05,2025-02-21,2409,9.4,Advanced Robotics +AI02423,Data Scientist,183641,CHF,165277,SE,FL,Switzerland,S,Ukraine,50,"Mathematics, PyTorch, Spark, Scala, AWS",Master,8,Government,2025-01-11,2025-02-04,2248,9.1,AI Innovations +AI02424,Principal Data Scientist,137861,USD,137861,MI,CT,Denmark,M,Denmark,0,"Scala, Mathematics, Computer Vision, Deep Learning",Associate,4,Technology,2024-05-27,2024-07-17,988,8,Cloud AI Solutions +AI02425,Data Engineer,55797,EUR,47427,EN,PT,France,S,France,100,"GCP, Scala, Spark, Python",PhD,0,Manufacturing,2024-06-26,2024-08-06,2194,9.5,DeepTech Ventures +AI02426,Principal Data Scientist,60447,CAD,75559,EN,CT,Canada,L,Canada,50,"Scala, Tableau, Azure, Spark, SQL",Master,1,Retail,2024-03-05,2024-04-25,2068,7,DataVision Ltd +AI02427,Head of AI,188935,EUR,160595,EX,FT,Austria,L,Austria,0,"Java, AWS, R",PhD,14,Retail,2025-01-29,2025-03-12,1647,5,AI Innovations +AI02428,Data Engineer,74196,USD,74196,EX,FL,India,L,India,50,"TensorFlow, Python, Git, Hadoop",Associate,19,Education,2024-03-06,2024-04-22,910,8.1,Machine Intelligence Group +AI02429,AI Architect,171635,CHF,154472,SE,FL,Switzerland,S,Switzerland,100,"R, Tableau, Spark, SQL, Computer Vision",Bachelor,9,Gaming,2024-07-23,2024-09-07,2310,6.8,Neural Networks Co +AI02430,AI Architect,71217,EUR,60534,EN,CT,Netherlands,M,Netherlands,0,"Python, NLP, TensorFlow, AWS",Master,0,Government,2024-06-15,2024-07-02,2397,5.9,Quantum Computing Inc +AI02431,Data Scientist,55275,GBP,41456,EN,CT,United Kingdom,S,United Kingdom,0,"PyTorch, NLP, Java, Python, Docker",Bachelor,1,Technology,2025-04-02,2025-06-08,933,6.2,Autonomous Tech +AI02432,Machine Learning Engineer,63318,USD,63318,EN,CT,Ireland,S,Vietnam,50,"SQL, GCP, PyTorch, Kubernetes",Associate,1,Finance,2025-01-26,2025-02-25,937,9.7,Algorithmic Solutions +AI02433,AI Specialist,102417,USD,102417,MI,CT,South Korea,L,South Korea,50,"Linux, SQL, PyTorch",Master,2,Transportation,2024-08-15,2024-09-01,2253,8.2,AI Innovations +AI02434,Deep Learning Engineer,145507,USD,145507,SE,FT,Ireland,L,Ireland,0,"Deep Learning, Python, NLP, GCP, Git",Master,8,Real Estate,2024-07-08,2024-08-04,1577,8,Neural Networks Co +AI02435,Machine Learning Engineer,70110,EUR,59594,EN,FL,Germany,S,Finland,0,"Kubernetes, Python, Data Visualization",Master,1,Education,2025-01-01,2025-02-12,680,5.1,Autonomous Tech +AI02436,AI Research Scientist,171213,USD,171213,EX,CT,South Korea,M,South Korea,0,"Git, Docker, Deep Learning, Kubernetes, Statistics",PhD,10,Retail,2025-01-06,2025-02-28,731,5.8,Autonomous Tech +AI02437,Robotics Engineer,84500,USD,84500,MI,PT,Sweden,M,Turkey,0,"Spark, Python, TensorFlow, SQL",Associate,4,Consulting,2025-01-15,2025-03-22,1603,9.2,Cognitive Computing +AI02438,Machine Learning Researcher,156224,USD,156224,EX,FL,Israel,S,Israel,0,"Data Visualization, NLP, Java, R, Mathematics",Bachelor,15,Telecommunications,2024-07-07,2024-09-17,2135,9.7,Predictive Systems +AI02439,Research Scientist,92098,USD,92098,MI,FL,Sweden,S,Sweden,0,"TensorFlow, Mathematics, MLOps, Computer Vision",Associate,3,Retail,2025-04-23,2025-05-20,825,5.1,Future Systems +AI02440,Principal Data Scientist,167891,USD,167891,EX,FT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, Deep Learning",Master,15,Government,2024-03-16,2024-05-28,2352,7,Cognitive Computing +AI02441,Data Engineer,101538,SGD,131999,MI,CT,Singapore,S,France,0,"Kubernetes, Data Visualization, Python, Statistics, AWS",PhD,4,Telecommunications,2024-08-01,2024-10-07,2037,5.9,Machine Intelligence Group +AI02442,Computer Vision Engineer,156055,CAD,195069,SE,PT,Canada,L,Canada,100,"Python, SQL, TensorFlow, GCP",PhD,9,Consulting,2024-10-23,2024-12-21,865,9.5,DeepTech Ventures +AI02443,Principal Data Scientist,97531,EUR,82901,MI,PT,Germany,S,Malaysia,50,"Git, Scala, Python",PhD,4,Healthcare,2025-02-13,2025-03-29,1379,6.9,AI Innovations +AI02444,Deep Learning Engineer,66041,USD,66041,EN,CT,Sweden,S,Sweden,0,"GCP, Kubernetes, Docker",Associate,0,Telecommunications,2024-08-16,2024-10-25,746,7.9,AI Innovations +AI02445,Principal Data Scientist,78618,EUR,66825,EN,FL,Germany,M,Turkey,50,"Python, Azure, Scala, Hadoop",Master,1,Education,2025-04-25,2025-05-29,633,8.3,Advanced Robotics +AI02446,Data Scientist,63321,JPY,6965310,EN,CT,Japan,S,Japan,0,"Python, TensorFlow, PyTorch",Associate,1,Government,2024-05-03,2024-07-04,2329,8.4,Autonomous Tech +AI02447,Machine Learning Researcher,171661,AUD,231742,EX,CT,Australia,S,Australia,50,"PyTorch, Hadoop, Computer Vision",Bachelor,14,Government,2024-04-17,2024-06-06,2090,5.7,DeepTech Ventures +AI02448,Data Engineer,65836,CAD,82295,EN,CT,Canada,S,Luxembourg,100,"Scala, Statistics, PyTorch",Master,0,Energy,2025-03-21,2025-04-14,2090,5.3,Quantum Computing Inc +AI02449,Machine Learning Engineer,27320,USD,27320,EN,CT,India,L,India,0,"Python, Kubernetes, Tableau, PyTorch",Bachelor,0,Energy,2025-04-07,2025-06-15,1130,7.5,Cognitive Computing +AI02450,AI Specialist,135041,EUR,114785,SE,CT,Germany,S,Germany,100,"SQL, Kubernetes, Statistics, Hadoop",Associate,5,Energy,2024-07-20,2024-08-29,1002,5.8,Autonomous Tech +AI02451,AI Specialist,113501,USD,113501,SE,PT,United States,S,United States,0,"Spark, Docker, Python, Kubernetes",Master,5,Automotive,2024-01-29,2024-02-29,2412,9.8,Smart Analytics +AI02452,NLP Engineer,84009,USD,84009,EN,FT,Denmark,S,Denmark,50,"Kubernetes, R, Azure, AWS",Master,1,Retail,2024-12-07,2025-02-15,1122,6.1,TechCorp Inc +AI02453,Data Scientist,202038,CAD,252548,EX,FT,Canada,S,Canada,0,"Tableau, TensorFlow, Scala",Associate,17,Government,2024-10-08,2024-10-26,2244,7.4,Cloud AI Solutions +AI02454,AI Research Scientist,157447,USD,157447,SE,PT,Norway,M,Nigeria,0,"R, Python, Git, NLP, Java",Master,5,Healthcare,2024-02-18,2024-04-03,2450,8.4,Future Systems +AI02455,Research Scientist,69117,USD,69117,EX,FL,China,S,South Korea,50,"Scala, Docker, Kubernetes",PhD,16,Government,2025-04-12,2025-05-04,517,8.7,Neural Networks Co +AI02456,AI Consultant,85916,SGD,111691,MI,FT,Singapore,S,Ireland,50,"Scala, Python, Data Visualization, NLP",Associate,2,Gaming,2024-12-19,2025-02-21,2108,5.7,Predictive Systems +AI02457,NLP Engineer,208144,EUR,176922,EX,FL,France,S,France,100,"Hadoop, MLOps, Spark, Git",Master,16,Technology,2024-06-01,2024-07-03,922,9.3,Machine Intelligence Group +AI02458,Computer Vision Engineer,201845,CAD,252306,EX,FT,Canada,L,Canada,100,"Data Visualization, Kubernetes, Scala, AWS, TensorFlow",Associate,11,Energy,2024-11-29,2025-02-05,1453,6.8,Neural Networks Co +AI02459,AI Software Engineer,70992,AUD,95839,EN,FL,Australia,S,Austria,0,"R, Data Visualization, AWS, Scala",PhD,0,Media,2024-05-01,2024-05-20,1609,6.8,DeepTech Ventures +AI02460,Computer Vision Engineer,78762,EUR,66948,MI,FL,Netherlands,S,Malaysia,50,"AWS, Azure, Docker, Hadoop, TensorFlow",Associate,4,Gaming,2024-06-08,2024-06-26,1864,7.5,Advanced Robotics +AI02461,Autonomous Systems Engineer,124250,USD,124250,SE,CT,South Korea,M,United Kingdom,0,"Linux, PyTorch, Kubernetes",PhD,9,Finance,2025-04-16,2025-05-27,1031,7.5,Future Systems +AI02462,AI Architect,79482,USD,79482,EN,PT,Norway,M,South Korea,0,"Computer Vision, Spark, Linux, Deep Learning",Associate,0,Healthcare,2024-09-30,2024-10-14,1803,5.6,Neural Networks Co +AI02463,Machine Learning Engineer,139133,EUR,118263,SE,CT,France,M,France,0,"Hadoop, SQL, Computer Vision, PyTorch",Master,6,Energy,2024-09-11,2024-10-28,1604,7.3,Digital Transformation LLC +AI02464,Computer Vision Engineer,220326,USD,220326,EX,FT,Norway,L,Norway,100,"PyTorch, Linux, TensorFlow, Azure, Hadoop",Master,10,Retail,2025-03-12,2025-05-11,1484,5.1,Autonomous Tech +AI02465,Machine Learning Researcher,56936,USD,56936,SE,FT,China,L,China,0,"Spark, Python, Tableau",Associate,7,Automotive,2024-09-14,2024-11-24,2347,6.1,Machine Intelligence Group +AI02466,Data Scientist,186597,SGD,242576,EX,FL,Singapore,M,Singapore,100,"Git, PyTorch, TensorFlow, Hadoop",PhD,12,Manufacturing,2024-09-12,2024-10-28,796,8.1,Quantum Computing Inc +AI02467,Autonomous Systems Engineer,98276,EUR,83535,MI,CT,Netherlands,M,South Korea,100,"Computer Vision, Hadoop, SQL",Associate,4,Finance,2024-09-29,2024-12-04,1681,7.8,Quantum Computing Inc +AI02468,Machine Learning Researcher,265980,EUR,226083,EX,FT,Netherlands,M,Netherlands,0,"Azure, Kubernetes, Tableau, Computer Vision, Statistics",Master,18,Consulting,2025-01-20,2025-02-15,1629,7.3,Neural Networks Co +AI02469,Principal Data Scientist,28831,USD,28831,EN,CT,China,S,Kenya,0,"Computer Vision, SQL, PyTorch, Docker, TensorFlow",Master,1,Energy,2024-09-23,2024-11-10,1887,7,DeepTech Ventures +AI02470,Machine Learning Engineer,41710,USD,41710,SE,FT,India,S,Mexico,100,"Docker, Java, Hadoop",Master,5,Finance,2024-06-11,2024-07-17,1648,9.4,Advanced Robotics +AI02471,AI Software Engineer,183499,JPY,20184890,SE,FT,Japan,L,Japan,0,"NLP, Git, Python, Java",Associate,8,Technology,2024-05-07,2024-06-21,1918,6.6,Cognitive Computing +AI02472,NLP Engineer,106203,CAD,132754,SE,PT,Canada,S,Canada,50,"Scala, Hadoop, Tableau, SQL, Deep Learning",Associate,6,Telecommunications,2024-06-02,2024-06-25,869,8.1,DataVision Ltd +AI02473,AI Architect,165971,USD,165971,EX,FL,Denmark,S,Denmark,0,"Docker, Hadoop, GCP",Associate,16,Consulting,2024-02-24,2024-05-06,584,7.4,Neural Networks Co +AI02474,Deep Learning Engineer,124861,USD,124861,MI,PT,Denmark,L,Denmark,0,"Kubernetes, Deep Learning, Scala, Java",Associate,4,Retail,2025-01-28,2025-04-11,2295,6,Smart Analytics +AI02475,AI Research Scientist,90314,USD,90314,MI,CT,Ireland,S,Ireland,0,"MLOps, NLP, PyTorch, Kubernetes",Associate,2,Education,2024-01-01,2024-01-18,1471,5.2,Cognitive Computing +AI02476,Data Engineer,82549,USD,82549,EN,PT,Denmark,S,Denmark,100,"Tableau, Java, SQL, Computer Vision, Kubernetes",Associate,0,Manufacturing,2024-03-05,2024-04-14,2066,6.2,DataVision Ltd +AI02477,ML Ops Engineer,24960,USD,24960,EN,FT,India,M,Norway,100,"Kubernetes, Hadoop, Java, Mathematics, Deep Learning",Associate,0,Retail,2025-04-16,2025-05-19,1088,7.1,DeepTech Ventures +AI02478,Deep Learning Engineer,106178,AUD,143340,MI,PT,Australia,M,Australia,0,"PyTorch, GCP, Kubernetes, Statistics, Computer Vision",Associate,3,Government,2024-03-30,2024-06-10,1148,5.2,Cognitive Computing +AI02479,Principal Data Scientist,136353,CHF,122718,MI,FT,Switzerland,M,Switzerland,100,"NLP, Azure, Tableau",Bachelor,4,Technology,2024-04-25,2024-06-29,1915,6.1,Algorithmic Solutions +AI02480,Machine Learning Researcher,140620,USD,140620,MI,FT,Denmark,L,Denmark,50,"NLP, Spark, Scala",Master,4,Technology,2025-03-20,2025-04-15,825,5.1,Predictive Systems +AI02481,Machine Learning Researcher,261035,USD,261035,EX,FT,Finland,L,Finland,50,"Python, AWS, Statistics, TensorFlow, NLP",Master,10,Technology,2024-03-14,2024-04-08,1299,8,Algorithmic Solutions +AI02482,Robotics Engineer,119849,SGD,155804,MI,CT,Singapore,L,Singapore,0,"SQL, PyTorch, Computer Vision",Master,3,Government,2024-04-09,2024-05-27,1022,6.5,Smart Analytics +AI02483,AI Consultant,58782,EUR,49965,EN,CT,Germany,S,Germany,50,"Hadoop, Linux, SQL, Computer Vision",Associate,1,Telecommunications,2025-03-24,2025-04-26,1785,7.7,Machine Intelligence Group +AI02484,Autonomous Systems Engineer,77795,GBP,58346,EN,FL,United Kingdom,L,United Kingdom,100,"Tableau, Python, Mathematics, Scala",Master,0,Gaming,2024-12-02,2025-01-30,1815,6.5,AI Innovations +AI02485,Data Analyst,162430,EUR,138066,EX,FT,Austria,M,Austria,0,"SQL, Scala, AWS, MLOps, NLP",Bachelor,15,Retail,2025-02-04,2025-03-07,621,7.6,DeepTech Ventures +AI02486,Robotics Engineer,156099,JPY,17170890,SE,FT,Japan,M,Poland,0,"Deep Learning, PyTorch, R",Associate,7,Gaming,2025-01-07,2025-01-30,2171,6.5,Predictive Systems +AI02487,NLP Engineer,105660,USD,105660,SE,FL,South Korea,M,South Korea,0,"Spark, PyTorch, Tableau, Statistics, AWS",Bachelor,6,Government,2024-11-30,2024-12-28,1284,6.4,TechCorp Inc +AI02488,ML Ops Engineer,100617,USD,100617,MI,PT,Finland,M,Ireland,0,"Docker, Scala, Data Visualization, NLP",Associate,2,Manufacturing,2025-04-04,2025-05-20,871,6.8,Cognitive Computing +AI02489,Deep Learning Engineer,85747,JPY,9432170,EN,PT,Japan,L,Japan,0,"GCP, Linux, SQL",Associate,0,Government,2024-07-26,2024-08-21,1790,8.8,DataVision Ltd +AI02490,AI Product Manager,103946,SGD,135130,MI,CT,Singapore,M,Singapore,0,"SQL, AWS, Tableau, Java, R",Master,3,Finance,2025-01-14,2025-03-22,2223,9.5,Advanced Robotics +AI02491,Deep Learning Engineer,163429,USD,163429,SE,PT,United States,L,Colombia,100,"Statistics, GCP, TensorFlow, Tableau",PhD,6,Real Estate,2025-04-18,2025-06-25,829,9.2,TechCorp Inc +AI02492,NLP Engineer,134989,CHF,121490,SE,CT,Switzerland,S,Ghana,100,"Azure, Deep Learning, Docker",Bachelor,8,Transportation,2024-05-27,2024-07-16,1154,6.9,Digital Transformation LLC +AI02493,AI Architect,232913,USD,232913,EX,PT,Israel,L,Israel,0,"AWS, MLOps, Data Visualization",PhD,14,Consulting,2025-03-19,2025-04-16,955,5.3,Cloud AI Solutions +AI02494,Machine Learning Researcher,72913,CHF,65622,EN,PT,Switzerland,S,Switzerland,0,"Scala, Python, TensorFlow, Spark, Linux",Master,1,Automotive,2024-06-13,2024-08-24,913,5.9,Neural Networks Co +AI02495,NLP Engineer,62004,CAD,77505,EN,CT,Canada,S,Poland,50,"TensorFlow, Statistics, Hadoop",Master,0,Government,2025-03-09,2025-05-19,2303,7.7,TechCorp Inc +AI02496,Head of AI,54572,USD,54572,EN,FL,Israel,S,Finland,100,"NLP, Scala, PyTorch",Bachelor,0,Retail,2025-04-27,2025-07-03,2392,8,Advanced Robotics +AI02497,Data Scientist,304083,CHF,273675,EX,FL,Switzerland,S,Switzerland,100,"Kubernetes, AWS, Python, Git",Master,15,Transportation,2024-06-20,2024-08-18,1922,7,Autonomous Tech +AI02498,Head of AI,263203,AUD,355324,EX,FL,Australia,L,Australia,0,"Java, Kubernetes, Tableau",PhD,18,Automotive,2024-08-26,2024-09-25,1516,8.6,DeepTech Ventures +AI02499,Machine Learning Researcher,78835,EUR,67010,EN,CT,Germany,L,Brazil,0,"Computer Vision, AWS, Data Visualization, Hadoop, PyTorch",Associate,1,Retail,2024-09-28,2024-11-29,2474,9.1,DeepTech Ventures +AI02500,AI Specialist,91165,USD,91165,EX,PT,China,M,China,0,"AWS, Spark, Git",PhD,10,Education,2024-08-02,2024-08-28,700,9,Quantum Computing Inc +AI02501,Robotics Engineer,141371,USD,141371,SE,PT,Finland,M,Turkey,100,"Java, Git, Mathematics, GCP, Hadoop",Bachelor,7,Consulting,2024-10-25,2024-12-27,1708,5.6,Quantum Computing Inc +AI02502,AI Architect,176050,EUR,149643,EX,FL,Austria,S,Austria,0,"Python, MLOps, TensorFlow",Associate,14,Gaming,2024-04-03,2024-05-04,1629,6.5,Advanced Robotics +AI02503,Research Scientist,164808,USD,164808,SE,PT,Norway,S,Norway,50,"Docker, SQL, Kubernetes, Java",Master,6,Real Estate,2024-08-17,2024-09-11,705,6.4,Cognitive Computing +AI02504,Principal Data Scientist,73825,USD,73825,MI,FL,South Korea,S,South Korea,50,"Spark, SQL, Computer Vision",Associate,3,Manufacturing,2025-01-24,2025-02-18,1905,6.6,TechCorp Inc +AI02505,Data Scientist,56305,USD,56305,EN,FT,Finland,M,Finland,100,"Java, Statistics, Git, Hadoop",Bachelor,0,Consulting,2024-06-29,2024-07-22,904,7.7,Advanced Robotics +AI02506,Computer Vision Engineer,95982,SGD,124777,MI,FT,Singapore,S,Singapore,0,"Scala, Spark, Tableau, SQL",Master,4,Telecommunications,2024-04-20,2024-06-29,2187,7.5,Machine Intelligence Group +AI02507,Robotics Engineer,139813,EUR,118841,EX,FL,France,S,France,100,"Python, Linux, Kubernetes",Bachelor,12,Automotive,2024-08-06,2024-08-27,2393,6.7,Quantum Computing Inc +AI02508,AI Architect,103705,CAD,129631,MI,PT,Canada,L,Canada,0,"Docker, Java, PyTorch",Bachelor,2,Finance,2024-01-12,2024-03-12,1589,6.5,TechCorp Inc +AI02509,AI Product Manager,90682,EUR,77080,MI,FT,Austria,M,Austria,100,"Computer Vision, Tableau, GCP",Master,2,Transportation,2025-03-08,2025-04-06,2327,7.9,Algorithmic Solutions +AI02510,Autonomous Systems Engineer,71388,EUR,60680,EN,PT,Netherlands,S,Belgium,50,"Linux, Git, Kubernetes",Associate,1,Manufacturing,2024-09-19,2024-11-16,1567,7,TechCorp Inc +AI02511,Deep Learning Engineer,96336,USD,96336,MI,PT,Israel,M,Vietnam,100,"Java, Linux, Tableau, Scala",Master,2,Transportation,2024-10-28,2024-12-19,2444,9.1,Advanced Robotics +AI02512,Deep Learning Engineer,128679,USD,128679,EX,CT,Finland,M,Finland,0,"R, Python, Linux",Master,10,Transportation,2024-06-29,2024-08-04,1288,8.4,Neural Networks Co +AI02513,Robotics Engineer,109988,EUR,93490,MI,FL,France,L,France,50,"SQL, MLOps, Java, Azure",Master,3,Retail,2025-02-11,2025-04-11,2329,7.8,Autonomous Tech +AI02514,Robotics Engineer,146873,EUR,124842,SE,FT,Netherlands,L,Vietnam,50,"Kubernetes, SQL, AWS, GCP",PhD,9,Real Estate,2025-03-16,2025-04-24,1914,7.5,TechCorp Inc +AI02515,Machine Learning Engineer,165141,USD,165141,EX,PT,South Korea,M,South Korea,0,"Java, Python, Tableau, Linux, Deep Learning",Master,15,Consulting,2024-03-10,2024-04-14,1945,5.9,Autonomous Tech +AI02516,Machine Learning Engineer,77901,AUD,105166,EN,FT,Australia,M,Australia,100,"Python, AWS, Statistics",Associate,0,Energy,2024-10-18,2024-12-03,2251,7.8,Smart Analytics +AI02517,Research Scientist,94620,SGD,123006,EN,PT,Singapore,L,New Zealand,100,"Hadoop, Java, Spark",Associate,1,Automotive,2024-09-22,2024-12-04,1019,8.6,Cloud AI Solutions +AI02518,Principal Data Scientist,162374,GBP,121781,SE,CT,United Kingdom,L,United Kingdom,50,"Git, Azure, Computer Vision, Mathematics, PyTorch",Associate,9,Retail,2024-03-08,2024-04-16,1503,9.9,Smart Analytics +AI02519,Data Engineer,85536,USD,85536,EN,FL,Finland,L,Finland,100,"MLOps, GCP, SQL",PhD,1,Automotive,2025-01-19,2025-03-17,1202,5.8,Future Systems +AI02520,Research Scientist,132794,GBP,99596,SE,PT,United Kingdom,M,United States,100,"NLP, Git, Python, Mathematics",PhD,7,Telecommunications,2024-10-07,2024-12-05,1060,10,Quantum Computing Inc +AI02521,Head of AI,51202,CAD,64003,EN,CT,Canada,S,Canada,50,"Mathematics, Deep Learning, Kubernetes",PhD,0,Transportation,2024-06-09,2024-07-26,2084,9,Machine Intelligence Group +AI02522,Machine Learning Researcher,105407,USD,105407,MI,CT,Ireland,M,Ireland,0,"Git, Hadoop, Scala, Spark",Bachelor,3,Technology,2024-07-15,2024-08-01,515,6.2,Algorithmic Solutions +AI02523,NLP Engineer,94037,USD,94037,MI,CT,Finland,M,Finland,50,"GCP, Kubernetes, R",Associate,3,Automotive,2024-07-15,2024-08-04,2256,7.6,Advanced Robotics +AI02524,Data Engineer,206898,EUR,175863,EX,FT,Austria,S,Austria,100,"Mathematics, Linux, MLOps",Associate,13,Healthcare,2024-01-10,2024-03-14,527,9.1,Digital Transformation LLC +AI02525,Deep Learning Engineer,243562,CHF,219206,EX,PT,Switzerland,M,Switzerland,0,"Git, Java, Data Visualization",Master,19,Telecommunications,2024-02-01,2024-02-15,1421,5,Machine Intelligence Group +AI02526,Data Analyst,51859,USD,51859,EN,PT,Ireland,S,Luxembourg,100,"Git, PyTorch, Statistics, Docker, Python",Master,1,Technology,2025-03-09,2025-03-28,1458,8.8,Quantum Computing Inc +AI02527,ML Ops Engineer,86795,USD,86795,MI,PT,Sweden,S,Sweden,100,"Tableau, GCP, Linux, Computer Vision, Java",Bachelor,4,Retail,2024-08-02,2024-09-20,659,9.1,Digital Transformation LLC +AI02528,AI Research Scientist,81483,EUR,69261,MI,CT,Germany,M,Ireland,50,"Linux, AWS, Python",Bachelor,4,Gaming,2025-03-26,2025-04-13,1391,9.8,AI Innovations +AI02529,ML Ops Engineer,269686,CHF,242717,EX,PT,Switzerland,M,Portugal,50,"Python, NLP, SQL, Linux, Git",PhD,10,Healthcare,2024-09-29,2024-10-17,1421,9.8,AI Innovations +AI02530,AI Architect,55579,USD,55579,EN,PT,South Korea,S,South Korea,50,"MLOps, Python, Deep Learning",Master,0,Education,2024-10-13,2024-11-05,1101,8.8,Predictive Systems +AI02531,AI Software Engineer,60607,USD,60607,EN,FT,Ireland,L,Ireland,0,"Data Visualization, SQL, GCP, Python, Mathematics",PhD,0,Energy,2024-12-16,2025-02-18,2279,5.8,Machine Intelligence Group +AI02532,NLP Engineer,131631,EUR,111886,SE,PT,Germany,M,Germany,50,"AWS, Data Visualization, Azure",Associate,7,Manufacturing,2024-08-12,2024-09-12,697,8.4,DeepTech Ventures +AI02533,Machine Learning Engineer,54944,EUR,46702,EN,FT,Germany,S,Germany,100,"Statistics, SQL, Python",Bachelor,0,Energy,2025-01-21,2025-03-29,975,7,Cognitive Computing +AI02534,AI Software Engineer,191195,CHF,172076,SE,PT,Switzerland,M,Switzerland,100,"PyTorch, Python, Docker, Kubernetes, Hadoop",Master,5,Healthcare,2024-12-02,2024-12-24,2199,5.2,AI Innovations +AI02535,Data Engineer,120333,CAD,150416,EX,FT,Canada,S,Brazil,100,"Java, NLP, MLOps, TensorFlow",Master,13,Government,2024-01-20,2024-02-03,2326,7.2,Smart Analytics +AI02536,Deep Learning Engineer,65699,USD,65699,EX,FT,China,S,China,0,"Statistics, SQL, Docker",Associate,17,Telecommunications,2025-03-21,2025-04-12,2252,6.9,AI Innovations +AI02537,AI Architect,64976,USD,64976,EN,PT,Israel,M,Luxembourg,0,"Tableau, Azure, Linux, Data Visualization",Master,1,Transportation,2024-02-06,2024-03-12,979,8,Cognitive Computing +AI02538,Research Scientist,209582,USD,209582,EX,CT,Denmark,M,Denmark,0,"SQL, Linux, Computer Vision, AWS",Bachelor,10,Government,2025-02-15,2025-04-19,1382,6.4,Smart Analytics +AI02539,Data Scientist,145591,USD,145591,SE,PT,United States,S,Austria,0,"Tableau, Git, PyTorch",Bachelor,7,Healthcare,2024-08-24,2024-10-18,1653,9.9,TechCorp Inc +AI02540,AI Product Manager,291098,USD,291098,EX,FL,Denmark,M,Denmark,100,"AWS, Kubernetes, R, Python, Statistics",Associate,16,Technology,2024-07-26,2024-09-14,2086,8.7,Algorithmic Solutions +AI02541,Autonomous Systems Engineer,196197,USD,196197,EX,FT,Sweden,L,Sweden,50,"Python, SQL, Kubernetes",Associate,11,Telecommunications,2024-05-04,2024-05-18,2425,8.7,Quantum Computing Inc +AI02542,Principal Data Scientist,186336,USD,186336,EX,PT,South Korea,L,France,0,"R, Docker, Java",Bachelor,10,Healthcare,2024-06-20,2024-07-20,1557,5.9,DataVision Ltd +AI02543,Data Scientist,62080,USD,62080,SE,PT,India,L,India,100,"Spark, Statistics, Data Visualization, Azure, Computer Vision",Bachelor,8,Manufacturing,2024-03-05,2024-04-18,774,6.8,Smart Analytics +AI02544,AI Software Engineer,85101,USD,85101,EN,FT,Denmark,S,Ireland,0,"NLP, Deep Learning, Git, Azure, R",Associate,1,Healthcare,2025-04-27,2025-05-12,1077,7.4,Quantum Computing Inc +AI02545,Robotics Engineer,149817,AUD,202253,SE,FT,Australia,M,Australia,0,"PyTorch, Computer Vision, MLOps, Statistics, Mathematics",Bachelor,7,Media,2024-02-07,2024-03-02,964,7.3,Algorithmic Solutions +AI02546,AI Architect,73727,EUR,62668,EN,FL,Austria,L,Austria,50,"GCP, Java, NLP, Computer Vision, Statistics",Associate,0,Retail,2025-03-09,2025-04-04,2292,6.1,Algorithmic Solutions +AI02547,Machine Learning Researcher,95260,USD,95260,EX,FT,China,L,China,100,"Docker, Git, R, SQL",Master,14,Education,2024-09-22,2024-10-16,1846,9.7,AI Innovations +AI02548,AI Specialist,59469,USD,59469,EN,CT,United States,S,United States,0,"R, Mathematics, Data Visualization, Deep Learning",Master,1,Transportation,2024-09-05,2024-10-06,1302,5.1,Digital Transformation LLC +AI02549,Data Engineer,95741,USD,95741,MI,CT,Ireland,S,Ireland,50,"TensorFlow, Spark, R, AWS, Linux",Master,4,Technology,2024-11-08,2024-11-29,836,6.9,Predictive Systems +AI02550,Data Analyst,99330,CHF,89397,EN,FT,Switzerland,S,Vietnam,0,"Kubernetes, Scala, Deep Learning, GCP",Master,1,Telecommunications,2024-01-22,2024-02-21,636,6.5,AI Innovations +AI02551,Data Engineer,169622,USD,169622,EX,PT,United States,M,United States,100,"GCP, Mathematics, Java, PyTorch",Associate,10,Media,2025-04-10,2025-05-02,1878,5.7,Autonomous Tech +AI02552,NLP Engineer,34014,USD,34014,MI,CT,India,L,India,0,"AWS, R, Kubernetes",Master,2,Government,2024-10-16,2024-11-25,2084,5.6,Advanced Robotics +AI02553,Deep Learning Engineer,48009,EUR,40808,EN,CT,France,S,France,100,"Linux, Java, R, Tableau",Associate,1,Automotive,2024-06-20,2024-07-05,1365,8.1,Quantum Computing Inc +AI02554,Machine Learning Researcher,186879,USD,186879,EX,FL,Ireland,M,United States,0,"Tableau, R, Linux",PhD,13,Consulting,2024-10-22,2024-12-05,923,7.4,Machine Intelligence Group +AI02555,Machine Learning Engineer,43587,USD,43587,SE,CT,India,L,Kenya,100,"Mathematics, Tableau, Azure, Linux",Bachelor,6,Government,2024-07-03,2024-07-22,1803,7.8,Algorithmic Solutions +AI02556,AI Product Manager,296908,USD,296908,EX,FT,Denmark,M,Denmark,0,"Scala, PyTorch, AWS, SQL",Associate,17,Education,2024-01-14,2024-02-12,963,8.2,DeepTech Ventures +AI02557,Principal Data Scientist,185850,CHF,167265,SE,FL,Switzerland,L,Switzerland,0,"Linux, Kubernetes, PyTorch, Deep Learning, Docker",Associate,9,Manufacturing,2025-01-19,2025-02-27,1056,9.1,Advanced Robotics +AI02558,AI Specialist,171053,CAD,213816,EX,CT,Canada,M,Canada,50,"GCP, Kubernetes, Data Visualization, Scala",Associate,18,Finance,2024-04-10,2024-05-30,1822,6.7,Quantum Computing Inc +AI02559,ML Ops Engineer,149653,EUR,127205,EX,PT,France,L,France,0,"Computer Vision, Mathematics, Scala, Data Visualization, Python",PhD,13,Transportation,2024-11-02,2024-11-16,1909,5.8,TechCorp Inc +AI02560,AI Specialist,86772,USD,86772,MI,PT,United States,M,United States,0,"TensorFlow, Kubernetes, PyTorch, Azure",PhD,3,Government,2024-06-25,2024-07-14,934,6.9,AI Innovations +AI02561,Machine Learning Researcher,80745,EUR,68633,MI,FL,Austria,L,Austria,100,"Data Visualization, Python, Spark",Master,4,Healthcare,2024-08-07,2024-09-05,2274,7.6,Autonomous Tech +AI02562,Principal Data Scientist,88333,CAD,110416,MI,FT,Canada,L,Canada,100,"MLOps, GCP, Java, Hadoop",Master,3,Transportation,2024-10-31,2025-01-03,1219,7.5,Quantum Computing Inc +AI02563,Data Engineer,294564,CHF,265108,EX,FT,Switzerland,M,United States,0,"Git, Python, TensorFlow",Master,16,Healthcare,2024-02-28,2024-05-10,1523,9,DeepTech Ventures +AI02564,Autonomous Systems Engineer,151837,USD,151837,SE,FL,United States,S,Estonia,100,"SQL, Mathematics, Tableau, Git",Master,6,Automotive,2025-03-24,2025-04-23,1538,6.9,Algorithmic Solutions +AI02565,Deep Learning Engineer,258351,USD,258351,EX,FL,United States,M,United States,50,"Python, TensorFlow, Scala, Deep Learning",Associate,14,Transportation,2024-12-24,2025-02-14,2412,8.3,AI Innovations +AI02566,AI Specialist,93903,CAD,117379,SE,CT,Canada,S,Canada,50,"Java, MLOps, Statistics, Tableau, Linux",PhD,5,Education,2025-02-20,2025-04-17,968,5.6,Cloud AI Solutions +AI02567,AI Product Manager,129113,USD,129113,SE,CT,Israel,S,Israel,0,"Hadoop, Computer Vision, Kubernetes, R, Docker",Bachelor,9,Automotive,2024-09-30,2024-10-16,2205,8.5,Future Systems +AI02568,AI Software Engineer,86397,EUR,73437,EN,PT,Germany,L,Germany,0,"Computer Vision, Git, Kubernetes, PyTorch",Bachelor,1,Automotive,2024-07-19,2024-09-25,1310,6.3,Algorithmic Solutions +AI02569,Autonomous Systems Engineer,124460,USD,124460,SE,CT,Sweden,M,Brazil,100,"SQL, Scala, Python, AWS, Hadoop",Master,9,Healthcare,2024-06-08,2024-07-07,2132,9.4,AI Innovations +AI02570,Data Engineer,149448,EUR,127031,EX,FT,France,M,France,50,"MLOps, Mathematics, Data Visualization",Master,18,Retail,2024-03-30,2024-04-17,1536,9.8,DeepTech Ventures +AI02571,Data Engineer,58804,EUR,49983,EN,PT,Germany,M,Germany,0,"Statistics, Java, Spark",Associate,1,Healthcare,2024-04-24,2024-06-19,609,7,Cloud AI Solutions +AI02572,AI Consultant,79567,CHF,71610,EN,FL,Switzerland,S,United States,100,"TensorFlow, Deep Learning, Computer Vision",PhD,0,Retail,2024-07-18,2024-08-09,1174,7.3,DataVision Ltd +AI02573,AI Specialist,92586,EUR,78698,MI,PT,Austria,M,Austria,50,"Python, Deep Learning, Kubernetes, Computer Vision",Master,4,Energy,2024-10-19,2024-11-02,739,7.1,Neural Networks Co +AI02574,Data Engineer,88553,JPY,9740830,EN,PT,Japan,L,Italy,0,"PyTorch, Computer Vision, Deep Learning",Associate,0,Finance,2025-01-25,2025-03-24,903,7,DeepTech Ventures +AI02575,Deep Learning Engineer,180911,EUR,153774,EX,FT,Netherlands,M,Netherlands,50,"Kubernetes, Statistics, R, Python, Mathematics",Master,13,Retail,2024-09-29,2024-11-13,1874,6.6,TechCorp Inc +AI02576,Computer Vision Engineer,180125,USD,180125,SE,FL,United States,L,United States,100,"TensorFlow, SQL, Git, AWS",Associate,8,Automotive,2024-12-07,2024-12-21,2412,8.4,Machine Intelligence Group +AI02577,Computer Vision Engineer,52185,EUR,44357,EN,FT,France,S,France,50,"R, Spark, TensorFlow, Data Visualization, SQL",Master,1,Retail,2024-06-27,2024-08-22,2119,9.3,Smart Analytics +AI02578,Machine Learning Researcher,246154,EUR,209231,EX,CT,Austria,L,Austria,0,"Deep Learning, Computer Vision, TensorFlow, Scala",Associate,14,Finance,2025-01-05,2025-03-07,1880,9.6,Cognitive Computing +AI02579,AI Specialist,57512,EUR,48885,EN,FL,Netherlands,M,Australia,100,"Statistics, PyTorch, SQL, Scala, Data Visualization",Associate,0,Consulting,2024-03-23,2024-04-19,575,6.8,AI Innovations +AI02580,Head of AI,170182,CHF,153164,MI,FT,Switzerland,L,Switzerland,0,"TensorFlow, Java, GCP",Master,2,Retail,2024-02-07,2024-03-03,1519,6.4,Cloud AI Solutions +AI02581,Data Scientist,40011,USD,40011,MI,CT,China,M,China,100,"Linux, Tableau, Spark, Java",Associate,3,Finance,2024-07-25,2024-08-30,1950,9.5,DeepTech Ventures +AI02582,Machine Learning Engineer,112165,GBP,84124,SE,CT,United Kingdom,M,Japan,100,"GCP, Kubernetes, Java, SQL, Deep Learning",Associate,7,Finance,2024-07-22,2024-09-02,1763,5.6,Smart Analytics +AI02583,Head of AI,118931,USD,118931,SE,CT,Ireland,L,Ireland,100,"Python, GCP, Scala",PhD,8,Government,2024-09-21,2024-10-28,1210,9,Cognitive Computing +AI02584,AI Specialist,163364,USD,163364,SE,FL,Finland,L,Mexico,0,"PyTorch, Spark, TensorFlow",Bachelor,8,Government,2025-01-06,2025-02-18,1293,6.9,Cloud AI Solutions +AI02585,Data Scientist,131301,USD,131301,EX,FL,South Korea,S,South Korea,0,"Linux, Spark, Deep Learning, Kubernetes",PhD,18,Education,2024-04-10,2024-05-02,2382,7.5,Quantum Computing Inc +AI02586,AI Software Engineer,68441,USD,68441,MI,PT,Ireland,S,Ireland,50,"Kubernetes, Statistics, GCP, Tableau",Master,4,Real Estate,2024-10-02,2024-10-20,1488,8.3,DataVision Ltd +AI02587,Robotics Engineer,135907,USD,135907,MI,CT,United States,L,United States,0,"NLP, GCP, Tableau",PhD,2,Energy,2024-09-26,2024-11-28,597,6.5,Machine Intelligence Group +AI02588,AI Architect,99860,EUR,84881,SE,FT,France,M,France,100,"PyTorch, AWS, NLP, Java, Azure",Master,6,Telecommunications,2024-06-19,2024-08-27,654,8.9,Quantum Computing Inc +AI02589,NLP Engineer,91537,USD,91537,MI,FL,South Korea,L,Argentina,100,"PyTorch, Tableau, NLP, TensorFlow",PhD,3,Telecommunications,2025-03-21,2025-05-29,845,6.9,Future Systems +AI02590,AI Specialist,167565,USD,167565,SE,PT,United States,M,France,50,"Hadoop, Azure, Deep Learning",Master,5,Energy,2024-07-10,2024-08-21,916,6.8,Digital Transformation LLC +AI02591,Machine Learning Researcher,102636,SGD,133427,MI,PT,Singapore,L,Singapore,100,"SQL, MLOps, PyTorch, Data Visualization, TensorFlow",Associate,2,Energy,2024-10-20,2024-12-13,663,7.1,Future Systems +AI02592,AI Consultant,116030,EUR,98626,SE,CT,Germany,M,Germany,100,"TensorFlow, Linux, PyTorch, GCP, Azure",PhD,6,Media,2024-04-05,2024-05-13,1375,5.9,Machine Intelligence Group +AI02593,AI Architect,84644,CAD,105805,EN,PT,Canada,L,Canada,100,"Kubernetes, Python, Hadoop",Master,1,Government,2024-12-25,2025-02-16,2101,8.9,Predictive Systems +AI02594,Research Scientist,65082,AUD,87861,EN,CT,Australia,M,Nigeria,50,"Python, Deep Learning, Kubernetes, Linux",PhD,1,Energy,2024-07-17,2024-08-06,1907,8.2,DataVision Ltd +AI02595,AI Software Engineer,62534,AUD,84421,EN,PT,Australia,M,Australia,50,"Python, Git, TensorFlow",Master,0,Telecommunications,2024-11-26,2025-01-12,2305,6.5,DeepTech Ventures +AI02596,AI Specialist,241137,CHF,217023,SE,FT,Switzerland,L,Switzerland,50,"Spark, Kubernetes, Tableau, Python, Statistics",Master,5,Education,2024-12-05,2025-02-04,1926,7.6,Machine Intelligence Group +AI02597,AI Software Engineer,85906,USD,85906,EN,PT,Finland,L,Finland,50,"Statistics, Linux, Scala, Kubernetes",Associate,1,Media,2024-10-21,2024-11-27,1026,7.7,Cognitive Computing +AI02598,Data Scientist,99399,USD,99399,SE,FT,South Korea,S,Singapore,50,"R, Python, Mathematics",Master,9,Real Estate,2024-03-21,2024-04-10,1095,5,Machine Intelligence Group +AI02599,Machine Learning Engineer,69551,USD,69551,EN,FL,Denmark,S,Denmark,0,"Docker, Python, Hadoop, SQL",Associate,0,Transportation,2024-10-24,2024-11-21,1355,6.4,Quantum Computing Inc +AI02600,Autonomous Systems Engineer,98388,USD,98388,MI,FT,South Korea,L,South Korea,0,"Python, Computer Vision, TensorFlow",Bachelor,4,Energy,2024-07-23,2024-09-17,1870,5.8,Machine Intelligence Group +AI02601,NLP Engineer,59613,CAD,74516,EN,CT,Canada,M,Canada,100,"Computer Vision, R, Docker",PhD,1,Retail,2024-02-07,2024-03-06,1939,6.2,Advanced Robotics +AI02602,AI Software Engineer,84934,USD,84934,EN,FL,United States,S,United States,100,"Computer Vision, Deep Learning, Tableau, Linux",Master,0,Telecommunications,2024-08-16,2024-10-18,1161,6.7,Quantum Computing Inc +AI02603,Data Analyst,86399,USD,86399,EX,FT,India,L,India,50,"Docker, R, Linux",Associate,18,Technology,2024-07-23,2024-09-10,1885,7.5,AI Innovations +AI02604,Data Scientist,167659,AUD,226340,SE,FT,Australia,L,Australia,50,"Kubernetes, TensorFlow, Spark, SQL",PhD,8,Education,2024-12-30,2025-01-22,1211,6.1,Digital Transformation LLC +AI02605,Data Engineer,101084,AUD,136463,MI,CT,Australia,L,Australia,100,"Java, TensorFlow, AWS, Computer Vision",Bachelor,2,Manufacturing,2024-08-01,2024-09-11,724,8.4,Neural Networks Co +AI02606,AI Architect,32520,USD,32520,EN,CT,China,M,Romania,50,"GCP, Linux, Statistics",PhD,1,Technology,2025-02-02,2025-03-08,1144,6.9,Smart Analytics +AI02607,Data Scientist,109024,EUR,92670,SE,FT,Germany,S,Germany,100,"Azure, SQL, TensorFlow, Tableau, Deep Learning",Bachelor,6,Real Estate,2024-09-11,2024-11-10,931,7.8,Predictive Systems +AI02608,AI Consultant,130052,USD,130052,SE,CT,Norway,S,Portugal,100,"Python, PyTorch, Data Visualization, Kubernetes",Associate,8,Healthcare,2025-02-22,2025-03-09,1571,5.6,DeepTech Ventures +AI02609,Deep Learning Engineer,118889,EUR,101056,MI,PT,Austria,L,Austria,50,"Tableau, Deep Learning, Kubernetes",PhD,2,Energy,2024-04-11,2024-05-13,2266,9.5,Smart Analytics +AI02610,Robotics Engineer,120628,USD,120628,EX,FT,Finland,S,Egypt,100,"Hadoop, Linux, Azure, MLOps, Kubernetes",Associate,15,Automotive,2024-04-26,2024-06-12,1815,9.4,DataVision Ltd +AI02611,AI Specialist,74800,CAD,93500,EN,FT,Canada,L,Canada,0,"Azure, Hadoop, Kubernetes, TensorFlow, Statistics",PhD,0,Automotive,2024-07-20,2024-09-04,688,5.2,Quantum Computing Inc +AI02612,AI Software Engineer,64207,GBP,48155,EN,PT,United Kingdom,M,Portugal,0,"Docker, GCP, SQL, AWS",Associate,1,Technology,2024-10-24,2025-01-03,2149,8.1,AI Innovations +AI02613,Computer Vision Engineer,133828,CHF,120445,MI,FT,Switzerland,S,Indonesia,100,"Scala, Spark, Data Visualization, R, Git",Associate,2,Automotive,2025-01-26,2025-02-17,1345,8.3,Advanced Robotics +AI02614,AI Product Manager,79575,AUD,107426,EN,FL,Australia,L,Australia,0,"Linux, AWS, Scala, PyTorch, Docker",Bachelor,1,Energy,2024-01-10,2024-03-18,1969,7.7,Advanced Robotics +AI02615,Autonomous Systems Engineer,131921,AUD,178093,SE,CT,Australia,M,Australia,100,"PyTorch, AWS, Tableau",Bachelor,7,Healthcare,2024-04-25,2024-05-22,546,7.1,Predictive Systems +AI02616,Machine Learning Engineer,237422,USD,237422,EX,FL,Denmark,L,Vietnam,100,"Scala, TensorFlow, SQL, NLP",PhD,18,Retail,2024-08-31,2024-10-04,2210,7.3,Cloud AI Solutions +AI02617,Computer Vision Engineer,78318,EUR,66570,MI,FL,Germany,S,Germany,100,"Data Visualization, Python, Java",Bachelor,2,Manufacturing,2025-04-03,2025-06-10,1370,8.5,Cognitive Computing +AI02618,Autonomous Systems Engineer,108458,EUR,92189,MI,FL,Netherlands,L,Netherlands,100,"Docker, Java, Computer Vision",Bachelor,2,Manufacturing,2024-09-26,2024-11-10,524,7,Smart Analytics +AI02619,Data Analyst,263428,GBP,197571,EX,CT,United Kingdom,M,United Kingdom,100,"MLOps, GCP, Python, TensorFlow, Scala",PhD,18,Gaming,2024-04-28,2024-06-10,1293,5.8,Digital Transformation LLC +AI02620,AI Consultant,46582,USD,46582,MI,PT,China,S,China,100,"MLOps, Deep Learning, Python, NLP, Scala",Bachelor,3,Automotive,2024-03-12,2024-05-14,1625,6.3,DeepTech Ventures +AI02621,Robotics Engineer,169033,SGD,219743,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Data Visualization",PhD,17,Healthcare,2025-03-06,2025-03-24,1506,8.4,TechCorp Inc +AI02622,Machine Learning Researcher,59167,USD,59167,MI,FL,South Korea,S,South Korea,0,"Statistics, Git, Linux, GCP, Computer Vision",Bachelor,2,Telecommunications,2024-12-18,2025-02-14,965,7.3,AI Innovations +AI02623,Deep Learning Engineer,76863,SGD,99922,EN,PT,Singapore,S,Singapore,0,"AWS, Hadoop, NLP, Python, Scala",Master,0,Telecommunications,2024-11-17,2024-12-20,1525,6.4,Quantum Computing Inc +AI02624,Research Scientist,54769,USD,54769,EN,FL,South Korea,S,South Korea,0,"Python, Scala, Java",Bachelor,1,Consulting,2024-12-10,2025-02-10,1118,7.9,TechCorp Inc +AI02625,AI Product Manager,227468,USD,227468,EX,FT,United States,M,Colombia,50,"Linux, TensorFlow, Deep Learning",Master,14,Retail,2024-01-03,2024-03-10,1849,7.9,Algorithmic Solutions +AI02626,Deep Learning Engineer,27385,USD,27385,EN,FT,China,S,Malaysia,50,"TensorFlow, Python, R, Statistics, Spark",PhD,0,Consulting,2024-11-22,2025-01-28,1243,5.3,Quantum Computing Inc +AI02627,NLP Engineer,192062,USD,192062,EX,PT,Norway,M,Norway,100,"TensorFlow, SQL, Mathematics",PhD,10,Real Estate,2024-08-07,2024-09-27,1863,5.4,Cloud AI Solutions +AI02628,Data Analyst,84809,USD,84809,MI,FL,Israel,M,Israel,100,"TensorFlow, AWS, Python, Computer Vision, Scala",Associate,4,Automotive,2024-11-27,2024-12-31,519,8.3,Algorithmic Solutions +AI02629,Computer Vision Engineer,129372,USD,129372,SE,CT,Israel,M,Ukraine,50,"Deep Learning, MLOps, Azure, Java",Master,6,Transportation,2024-03-19,2024-04-04,2253,6.9,Neural Networks Co +AI02630,Principal Data Scientist,61768,CAD,77210,EN,FT,Canada,L,Canada,100,"Java, Git, Kubernetes, PyTorch, Data Visualization",Associate,1,Automotive,2024-02-26,2024-03-14,1170,7.5,Cloud AI Solutions +AI02631,AI Product Manager,33922,USD,33922,EN,CT,China,M,China,100,"Spark, Python, Git, Linux",Associate,0,Technology,2024-07-17,2024-08-15,590,7.1,Algorithmic Solutions +AI02632,Research Scientist,127911,USD,127911,SE,PT,Sweden,M,Sweden,100,"AWS, Python, TensorFlow, Statistics, Deep Learning",Bachelor,6,Real Estate,2024-08-14,2024-09-15,847,9.3,Future Systems +AI02633,AI Consultant,132207,EUR,112376,EX,CT,Austria,S,Austria,100,"Hadoop, Python, Statistics",Master,16,Automotive,2024-01-29,2024-03-16,1880,7.1,Cloud AI Solutions +AI02634,AI Specialist,60862,CAD,76078,EN,CT,Canada,S,United Kingdom,0,"SQL, Computer Vision, Tableau, PyTorch, Scala",PhD,1,Healthcare,2024-07-26,2024-09-06,1914,5.5,Autonomous Tech +AI02635,Machine Learning Researcher,30483,USD,30483,MI,FT,India,S,India,100,"Kubernetes, NLP, Linux",PhD,2,Finance,2024-12-21,2025-01-15,2424,9,TechCorp Inc +AI02636,AI Product Manager,99046,USD,99046,MI,FL,Denmark,S,Denmark,0,"MLOps, R, Kubernetes",Associate,4,Healthcare,2024-12-15,2025-01-30,990,8.9,Quantum Computing Inc +AI02637,AI Product Manager,126174,USD,126174,MI,CT,Denmark,S,New Zealand,0,"Data Visualization, Kubernetes, Scala, Python",Associate,3,Healthcare,2024-06-25,2024-08-27,877,6.1,Cognitive Computing +AI02638,Deep Learning Engineer,226713,USD,226713,EX,FT,Denmark,S,South Africa,50,"Python, TensorFlow, Docker, Mathematics",Bachelor,11,Education,2025-03-16,2025-05-04,760,8.7,Advanced Robotics +AI02639,Robotics Engineer,66662,SGD,86661,EN,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, Kubernetes, Spark, SQL",Bachelor,0,Consulting,2024-03-03,2024-03-28,2192,6.7,Autonomous Tech +AI02640,Machine Learning Engineer,156202,USD,156202,EX,CT,Ireland,S,China,0,"TensorFlow, Data Visualization, Python",Bachelor,14,Media,2024-05-14,2024-06-15,1849,6.6,Predictive Systems +AI02641,ML Ops Engineer,106445,USD,106445,SE,CT,South Korea,S,South Korea,50,"Docker, Deep Learning, Python, GCP, Mathematics",Master,9,Technology,2025-02-01,2025-03-31,2203,7.7,Advanced Robotics +AI02642,Research Scientist,57527,USD,57527,SE,CT,China,L,China,50,"R, SQL, Scala, Tableau, AWS",Associate,7,Telecommunications,2024-11-24,2024-12-18,1466,9.9,DataVision Ltd +AI02643,Data Analyst,71613,USD,71613,EN,CT,Ireland,L,Norway,0,"Azure, Python, GCP, TensorFlow, MLOps",Associate,1,Media,2024-05-12,2024-06-06,1682,8.8,Quantum Computing Inc +AI02644,Data Engineer,214057,USD,214057,SE,FT,Norway,L,Norway,0,"Scala, Deep Learning, Computer Vision, Data Visualization, Docker",PhD,9,Education,2024-12-11,2025-02-03,1422,7.3,DeepTech Ventures +AI02645,AI Research Scientist,113033,USD,113033,SE,PT,Finland,L,Finland,50,"MLOps, Spark, Azure",Bachelor,6,Media,2024-10-07,2024-10-21,1899,6.8,Advanced Robotics +AI02646,Computer Vision Engineer,83831,AUD,113172,MI,FT,Australia,L,Philippines,50,"Scala, Hadoop, Linux, SQL",Associate,4,Retail,2025-02-21,2025-03-25,904,5.3,Cloud AI Solutions +AI02647,Deep Learning Engineer,130289,USD,130289,SE,CT,United States,S,United States,0,"Kubernetes, Scala, Deep Learning",Associate,6,Government,2025-03-10,2025-04-15,2201,9.8,Algorithmic Solutions +AI02648,Data Engineer,128723,CAD,160904,SE,CT,Canada,S,Canada,100,"Scala, Tableau, Python",Master,7,Transportation,2024-09-11,2024-11-13,1131,5.8,DeepTech Ventures +AI02649,AI Consultant,197237,AUD,266270,EX,FL,Australia,S,Australia,0,"Hadoop, Python, Tableau, SQL",Associate,10,Telecommunications,2024-10-10,2024-12-10,2281,6.6,Future Systems +AI02650,Machine Learning Engineer,49680,USD,49680,MI,FL,China,L,China,100,"AWS, Spark, Tableau, NLP, Kubernetes",PhD,2,Finance,2024-02-26,2024-03-20,785,9.9,Future Systems +AI02651,Computer Vision Engineer,79494,USD,79494,MI,CT,United States,S,Indonesia,0,"Scala, Spark, Hadoop",Bachelor,3,Finance,2025-01-07,2025-02-24,1427,6.2,Algorithmic Solutions +AI02652,Data Engineer,120305,SGD,156397,MI,PT,Singapore,L,Singapore,0,"Computer Vision, SQL, Docker, Python, Hadoop",Bachelor,3,Education,2024-09-24,2024-10-18,1572,8.5,Algorithmic Solutions +AI02653,Research Scientist,109402,USD,109402,EX,FL,South Korea,S,South Korea,50,"Python, Scala, TensorFlow, Java, AWS",Bachelor,11,Telecommunications,2024-08-30,2024-10-25,2305,9,Machine Intelligence Group +AI02654,Computer Vision Engineer,131199,SGD,170559,MI,CT,Singapore,L,Russia,50,"R, Linux, Statistics, Spark",Bachelor,3,Consulting,2024-01-25,2024-03-19,593,7.2,TechCorp Inc +AI02655,Data Engineer,89303,USD,89303,MI,PT,Israel,L,Israel,0,"PyTorch, Mathematics, SQL, Scala, NLP",Associate,4,Energy,2024-03-25,2024-04-20,1319,8.3,TechCorp Inc +AI02656,AI Consultant,152868,AUD,206372,EX,FL,Australia,S,United States,0,"Hadoop, Java, Git, Statistics, Spark",PhD,13,Telecommunications,2025-02-13,2025-03-16,1303,6.8,Cloud AI Solutions +AI02657,Machine Learning Engineer,77521,USD,77521,MI,CT,South Korea,L,South Korea,50,"Spark, Hadoop, Tableau, MLOps, Linux",Associate,2,Finance,2025-01-25,2025-04-07,2414,8.6,DataVision Ltd +AI02658,ML Ops Engineer,140909,GBP,105682,SE,FT,United Kingdom,S,United Kingdom,100,"AWS, R, SQL",Master,9,Government,2024-01-14,2024-03-24,1248,9,Future Systems +AI02659,Data Engineer,156224,USD,156224,EX,CT,Finland,L,Finland,0,"Azure, Data Visualization, Statistics",PhD,18,Telecommunications,2024-09-21,2024-10-17,1780,9.1,DataVision Ltd +AI02660,AI Software Engineer,98611,SGD,128194,MI,FT,Singapore,M,Chile,100,"MLOps, Git, Kubernetes",Associate,3,Healthcare,2024-09-14,2024-10-16,1867,9.6,Algorithmic Solutions +AI02661,AI Research Scientist,129667,USD,129667,SE,CT,Ireland,M,South Korea,50,"Hadoop, Data Visualization, SQL, MLOps",Bachelor,7,Real Estate,2024-01-26,2024-02-17,2455,5.6,Cognitive Computing +AI02662,AI Research Scientist,143589,EUR,122051,SE,PT,Austria,M,Germany,50,"Scala, GCP, Computer Vision, Statistics, Tableau",PhD,5,Manufacturing,2024-03-04,2024-05-01,1222,6.3,Quantum Computing Inc +AI02663,Deep Learning Engineer,102918,USD,102918,EN,FT,United States,L,Luxembourg,100,"Python, TensorFlow, Deep Learning, R",Master,0,Finance,2025-04-08,2025-05-19,2329,7.7,DataVision Ltd +AI02664,NLP Engineer,233285,EUR,198292,EX,FT,Austria,L,Ukraine,100,"MLOps, R, Computer Vision",Master,10,Finance,2025-01-12,2025-02-20,1375,6.2,Neural Networks Co +AI02665,AI Research Scientist,161043,USD,161043,SE,FL,United States,M,United States,100,"PyTorch, Spark, Mathematics",Master,5,Energy,2024-07-18,2024-09-21,1559,9.8,Advanced Robotics +AI02666,AI Architect,184501,GBP,138376,EX,FL,United Kingdom,L,Russia,100,"Statistics, TensorFlow, Deep Learning",Associate,18,Consulting,2024-12-10,2025-01-13,1574,6.9,Digital Transformation LLC +AI02667,NLP Engineer,77968,USD,77968,EX,PT,India,S,India,50,"Deep Learning, Spark, MLOps, Hadoop, SQL",Bachelor,10,Retail,2024-03-06,2024-05-16,585,6.2,Digital Transformation LLC +AI02668,AI Architect,251626,USD,251626,EX,PT,United States,S,Argentina,50,"Mathematics, Data Visualization, MLOps, Docker",Bachelor,17,Media,2024-12-30,2025-02-08,2096,7.4,Neural Networks Co +AI02669,AI Product Manager,93801,USD,93801,MI,FL,Finland,L,Malaysia,100,"Python, Git, SQL, Docker",PhD,3,Retail,2024-01-24,2024-02-21,1501,8.3,AI Innovations +AI02670,Autonomous Systems Engineer,85270,USD,85270,EN,FL,United States,M,Indonesia,100,"Spark, Scala, AWS, Deep Learning",PhD,0,Government,2024-01-09,2024-01-24,1067,8.8,DataVision Ltd +AI02671,AI Product Manager,116844,USD,116844,EX,PT,South Korea,S,Malaysia,50,"Docker, Spark, Python, Java",Master,12,Transportation,2025-03-17,2025-04-17,2064,9.8,TechCorp Inc +AI02672,AI Consultant,115484,USD,115484,SE,FL,Finland,S,Finland,0,"Kubernetes, Spark, Git, Computer Vision, Java",Master,6,Gaming,2024-09-16,2024-10-28,1669,5.3,Digital Transformation LLC +AI02673,NLP Engineer,215938,USD,215938,EX,CT,Norway,M,Australia,100,"Linux, Kubernetes, Mathematics, SQL",Bachelor,15,Consulting,2024-01-06,2024-01-25,920,8.1,Smart Analytics +AI02674,Head of AI,112832,USD,112832,SE,FT,Ireland,S,Ireland,0,"R, SQL, Tableau, PyTorch, Java",Master,9,Consulting,2024-03-11,2024-05-17,1000,6.1,AI Innovations +AI02675,Principal Data Scientist,375327,CHF,337794,EX,CT,Switzerland,L,South Africa,0,"SQL, Python, Deep Learning, Kubernetes",Bachelor,12,Automotive,2025-02-23,2025-03-23,700,7.9,DeepTech Ventures +AI02676,AI Product Manager,167432,CHF,150689,SE,FL,Switzerland,M,United Kingdom,50,"Statistics, NLP, MLOps, Linux",Master,9,Healthcare,2024-11-02,2024-12-20,1081,7.9,Machine Intelligence Group +AI02677,Autonomous Systems Engineer,117408,CHF,105667,MI,PT,Switzerland,L,Switzerland,50,"Scala, MLOps, Hadoop, SQL",Master,2,Healthcare,2024-01-14,2024-03-16,2132,7.4,Neural Networks Co +AI02678,Research Scientist,76644,USD,76644,MI,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Data Visualization",Bachelor,3,Technology,2024-02-28,2024-04-09,2292,6,TechCorp Inc +AI02679,Autonomous Systems Engineer,80930,USD,80930,EN,FL,Finland,L,Finland,100,"Git, MLOps, Tableau",Associate,1,Consulting,2024-01-14,2024-03-14,1105,9.2,Predictive Systems +AI02680,ML Ops Engineer,96017,EUR,81614,MI,FL,Austria,M,Austria,0,"Python, Git, NLP, Mathematics, TensorFlow",Master,3,Energy,2024-09-23,2024-10-30,1268,9.5,Predictive Systems +AI02681,Deep Learning Engineer,85062,USD,85062,EN,PT,Denmark,L,Denmark,0,"Kubernetes, Statistics, Python, Java",PhD,0,Education,2024-05-05,2024-07-11,1703,6.8,Advanced Robotics +AI02682,Data Analyst,123126,EUR,104657,SE,FT,France,L,Luxembourg,50,"Linux, SQL, R",Bachelor,9,Manufacturing,2024-02-21,2024-03-25,2431,6.2,DataVision Ltd +AI02683,Robotics Engineer,131093,USD,131093,EX,FL,Finland,M,Finland,50,"PyTorch, Mathematics, Git, R",PhD,13,Real Estate,2024-06-10,2024-08-22,1037,9.8,Advanced Robotics +AI02684,Data Scientist,110151,JPY,12116610,MI,FL,Japan,M,Malaysia,0,"Git, AWS, Python, Kubernetes, Docker",Bachelor,2,Real Estate,2024-01-11,2024-02-05,1352,8.1,Algorithmic Solutions +AI02685,NLP Engineer,120418,CHF,108376,MI,FL,Switzerland,M,Switzerland,0,"GCP, Docker, Mathematics",Master,4,Technology,2025-04-25,2025-06-18,1356,8.8,Quantum Computing Inc +AI02686,Data Analyst,135377,USD,135377,EX,FL,South Korea,L,South Korea,100,"Spark, SQL, Linux, Azure, AWS",Master,10,Transportation,2024-09-16,2024-11-10,784,6.7,Autonomous Tech +AI02687,ML Ops Engineer,87833,USD,87833,MI,FT,Ireland,L,Ireland,50,"Git, Azure, MLOps, Python",PhD,3,Technology,2024-01-10,2024-02-21,2222,8,Advanced Robotics +AI02688,AI Architect,227660,EUR,193511,EX,FL,Germany,S,Germany,50,"Computer Vision, Python, Deep Learning",Bachelor,15,Government,2024-10-16,2024-11-03,1915,9.8,DataVision Ltd +AI02689,Deep Learning Engineer,133632,USD,133632,EX,FT,China,L,China,0,"NLP, Python, Mathematics, GCP",Associate,15,Telecommunications,2024-12-31,2025-01-18,850,8.8,AI Innovations +AI02690,AI Software Engineer,78480,USD,78480,EN,FT,Norway,M,Norway,50,"Spark, Git, Deep Learning, Docker",Associate,1,Healthcare,2024-07-22,2024-08-28,1560,7.4,DeepTech Ventures +AI02691,Head of AI,206088,EUR,175175,EX,FT,France,M,China,0,"Statistics, Tableau, SQL, Data Visualization, PyTorch",Associate,14,Healthcare,2024-03-27,2024-05-28,821,9.3,Future Systems +AI02692,Head of AI,153198,CAD,191498,SE,PT,Canada,L,Canada,100,"Linux, Mathematics, Deep Learning, PyTorch, Azure",Master,9,Transportation,2025-02-01,2025-02-21,1912,8.2,Machine Intelligence Group +AI02693,Head of AI,92186,EUR,78358,MI,FT,France,M,France,100,"Deep Learning, Python, Spark",PhD,2,Retail,2024-09-07,2024-09-28,612,7.8,Advanced Robotics +AI02694,Data Engineer,123240,USD,123240,SE,PT,Finland,M,Finland,0,"NLP, GCP, R",PhD,7,Media,2024-11-05,2024-11-25,2331,9.4,Quantum Computing Inc +AI02695,Data Analyst,77013,SGD,100117,MI,PT,Singapore,M,Singapore,50,"Hadoop, AWS, Linux",Bachelor,4,Retail,2024-06-29,2024-08-01,2245,5.3,Autonomous Tech +AI02696,AI Software Engineer,79315,AUD,107075,MI,PT,Australia,S,Australia,50,"Java, Scala, Hadoop",Master,3,Technology,2024-09-24,2024-10-26,928,7,Smart Analytics +AI02697,Autonomous Systems Engineer,82499,USD,82499,MI,PT,Israel,S,Israel,50,"Linux, Git, TensorFlow, PyTorch, R",Master,3,Energy,2024-12-23,2025-02-08,1156,8.6,DeepTech Ventures +AI02698,AI Research Scientist,89597,USD,89597,MI,CT,Ireland,M,Ireland,100,"PyTorch, Git, Tableau",Master,3,Gaming,2025-04-28,2025-06-27,638,9.4,Future Systems +AI02699,AI Consultant,79127,USD,79127,MI,CT,South Korea,L,South Africa,50,"Spark, Kubernetes, PyTorch, Mathematics, TensorFlow",Bachelor,4,Retail,2025-04-18,2025-06-01,660,9.8,Predictive Systems +AI02700,NLP Engineer,181523,EUR,154295,EX,FT,Germany,S,Germany,100,"Java, SQL, Mathematics",PhD,16,Automotive,2025-03-19,2025-04-25,1872,8.7,Smart Analytics +AI02701,Machine Learning Researcher,136263,USD,136263,EX,FT,Sweden,S,Italy,0,"MLOps, Docker, TensorFlow, Statistics",PhD,14,Technology,2024-06-22,2024-08-27,1042,8.8,DataVision Ltd +AI02702,Computer Vision Engineer,83502,JPY,9185220,MI,FL,Japan,M,Japan,0,"Data Visualization, Java, TensorFlow",Master,4,Education,2024-11-02,2024-11-24,1113,8,TechCorp Inc +AI02703,Autonomous Systems Engineer,80445,USD,80445,EN,FL,Israel,L,Vietnam,100,"Spark, Kubernetes, Linux, Deep Learning",Master,0,Automotive,2024-11-29,2025-01-13,1701,5.6,Algorithmic Solutions +AI02704,NLP Engineer,129262,EUR,109873,SE,CT,Germany,M,Germany,100,"Scala, Mathematics, Deep Learning",Bachelor,5,Education,2025-03-31,2025-06-03,1314,5.9,AI Innovations +AI02705,AI Research Scientist,318729,USD,318729,EX,CT,Denmark,L,Denmark,100,"SQL, PyTorch, MLOps, Scala",PhD,15,Transportation,2024-04-20,2024-06-26,1885,5.1,TechCorp Inc +AI02706,Head of AI,42907,USD,42907,SE,CT,India,S,India,50,"AWS, Spark, NLP",PhD,9,Energy,2025-01-08,2025-02-21,1752,6.7,Quantum Computing Inc +AI02707,AI Architect,35590,USD,35590,MI,CT,China,S,China,50,"Deep Learning, AWS, SQL, Kubernetes",PhD,2,Energy,2025-03-11,2025-04-17,2175,7.9,Machine Intelligence Group +AI02708,ML Ops Engineer,201427,USD,201427,EX,PT,Sweden,M,Sweden,0,"Python, SQL, MLOps, Azure",Bachelor,15,Media,2024-01-04,2024-02-17,1405,6.4,Smart Analytics +AI02709,Head of AI,206878,USD,206878,EX,PT,Israel,S,Portugal,100,"Java, R, Computer Vision, Git, GCP",PhD,11,Government,2024-05-17,2024-07-01,2015,7.1,Neural Networks Co +AI02710,Data Engineer,59555,AUD,80399,EN,FL,Australia,L,Sweden,0,"SQL, Deep Learning, Linux, Python, PyTorch",Master,0,Healthcare,2025-04-18,2025-06-12,631,8.4,Neural Networks Co +AI02711,Computer Vision Engineer,40698,USD,40698,MI,FL,China,L,Egypt,100,"R, PyTorch, Tableau, Scala",Associate,2,Healthcare,2025-04-19,2025-06-18,1730,6.9,Future Systems +AI02712,AI Consultant,60205,USD,60205,EN,FT,Ireland,S,Denmark,50,"AWS, Java, Data Visualization",Associate,1,Retail,2024-06-29,2024-07-18,2272,7,Cloud AI Solutions +AI02713,AI Research Scientist,153723,SGD,199840,EX,CT,Singapore,M,Singapore,0,"Deep Learning, Linux, Computer Vision",Associate,16,Transportation,2025-01-28,2025-04-02,743,5.1,DeepTech Ventures +AI02714,AI Architect,185811,USD,185811,EX,PT,Israel,S,Israel,50,"Hadoop, Kubernetes, Tableau, Spark",Associate,12,Government,2025-04-13,2025-05-26,513,6.5,Autonomous Tech +AI02715,AI Product Manager,49147,EUR,41775,EN,FL,Germany,S,Germany,0,"Data Visualization, Docker, Spark, TensorFlow, Statistics",PhD,1,Gaming,2024-02-05,2024-04-08,996,8.1,TechCorp Inc +AI02716,Computer Vision Engineer,102077,USD,102077,MI,PT,Norway,M,Norway,0,"Kubernetes, Java, Statistics, Mathematics",Bachelor,3,Education,2024-05-05,2024-05-26,2332,5.2,Cloud AI Solutions +AI02717,Robotics Engineer,62401,USD,62401,SE,CT,China,M,Kenya,100,"TensorFlow, Java, Azure, Tableau, R",PhD,6,Retail,2024-08-24,2024-09-25,889,5.4,Cloud AI Solutions +AI02718,AI Architect,107823,EUR,91650,SE,CT,Austria,M,Australia,50,"Statistics, PyTorch, Tableau, Scala",Associate,5,Media,2024-11-10,2024-12-26,1821,8.7,DeepTech Ventures +AI02719,AI Consultant,91347,EUR,77645,MI,CT,Austria,S,Austria,100,"AWS, Linux, Docker",PhD,3,Energy,2024-08-10,2024-10-11,539,6.3,DeepTech Ventures +AI02720,AI Specialist,51459,USD,51459,SE,PT,India,L,India,100,"R, Docker, Statistics, SQL",PhD,5,Transportation,2024-04-23,2024-05-30,1996,9,Smart Analytics +AI02721,AI Product Manager,81873,USD,81873,EN,FT,Denmark,M,Denmark,100,"Linux, Computer Vision, Data Visualization, Git",Associate,0,Healthcare,2024-08-19,2024-09-08,1229,9.3,Cloud AI Solutions +AI02722,ML Ops Engineer,83272,USD,83272,MI,CT,United States,S,United States,50,"Kubernetes, SQL, TensorFlow, NLP",Master,2,Real Estate,2024-05-23,2024-07-07,1214,5.3,Smart Analytics +AI02723,Machine Learning Researcher,116075,SGD,150898,SE,CT,Singapore,S,Singapore,50,"Python, Spark, Java, TensorFlow",Bachelor,7,Education,2024-08-23,2024-10-31,781,5.1,AI Innovations +AI02724,Head of AI,89742,USD,89742,SE,PT,Finland,S,Finland,0,"PyTorch, Statistics, Data Visualization, SQL",Bachelor,9,Telecommunications,2024-08-25,2024-09-19,1044,7.7,Smart Analytics +AI02725,Machine Learning Researcher,72250,USD,72250,EN,FL,Ireland,L,Nigeria,0,"MLOps, Git, PyTorch",Associate,1,Education,2024-10-28,2024-12-05,1070,8.1,Cloud AI Solutions +AI02726,AI Product Manager,89161,CHF,80245,EN,CT,Switzerland,M,Switzerland,100,"Kubernetes, Statistics, Tableau, Data Visualization",Master,1,Consulting,2025-03-04,2025-03-25,905,5.5,Digital Transformation LLC +AI02727,AI Software Engineer,248371,SGD,322882,EX,CT,Singapore,M,Singapore,100,"Spark, Python, Data Visualization, Kubernetes, Deep Learning",Master,19,Retail,2025-01-19,2025-03-05,628,9.1,Machine Intelligence Group +AI02728,Head of AI,237882,GBP,178412,EX,FL,United Kingdom,M,United Kingdom,0,"R, Linux, SQL, Mathematics, MLOps",PhD,12,Consulting,2024-11-11,2024-12-17,1603,7.7,Autonomous Tech +AI02729,AI Product Manager,234093,CHF,210684,SE,FT,Switzerland,L,Switzerland,0,"Data Visualization, TensorFlow, Statistics",Bachelor,8,Consulting,2025-03-21,2025-05-19,2420,5.4,Cloud AI Solutions +AI02730,Head of AI,69998,EUR,59498,EN,FT,France,M,France,50,"Azure, Kubernetes, Scala",Associate,1,Government,2024-07-17,2024-08-09,557,8.1,Algorithmic Solutions +AI02731,Principal Data Scientist,92320,EUR,78472,MI,FL,Netherlands,M,Norway,50,"R, SQL, Azure",Master,3,Government,2024-05-01,2024-06-25,2297,9.4,DeepTech Ventures +AI02732,Principal Data Scientist,61179,CAD,76474,EN,FT,Canada,S,Canada,100,"Hadoop, Kubernetes, MLOps, Docker",PhD,0,Media,2024-04-09,2024-05-11,1420,7.8,Autonomous Tech +AI02733,Deep Learning Engineer,61702,EUR,52447,MI,CT,France,S,France,50,"Java, Hadoop, Tableau, Kubernetes, AWS",Bachelor,3,Technology,2025-02-05,2025-02-20,1250,9,Autonomous Tech +AI02734,Autonomous Systems Engineer,85122,USD,85122,EN,FL,Norway,L,Norway,100,"PyTorch, TensorFlow, Azure, Git",Master,1,Energy,2024-03-29,2024-04-27,734,8,Quantum Computing Inc +AI02735,Data Analyst,78254,USD,78254,EN,PT,Denmark,M,Denmark,0,"TensorFlow, AWS, Hadoop",Bachelor,1,Technology,2025-01-25,2025-02-15,1718,8.4,Quantum Computing Inc +AI02736,AI Research Scientist,70895,USD,70895,EN,PT,Sweden,S,Sweden,50,"Scala, PyTorch, MLOps, SQL, Computer Vision",Associate,1,Government,2025-01-11,2025-03-18,1398,5.8,Future Systems +AI02737,Data Engineer,199927,USD,199927,SE,CT,Norway,L,Latvia,50,"SQL, Spark, PyTorch",Associate,6,Healthcare,2024-03-17,2024-04-02,1138,6.9,Cloud AI Solutions +AI02738,Deep Learning Engineer,170229,CAD,212786,EX,CT,Canada,M,United States,50,"Deep Learning, R, Hadoop, Kubernetes, SQL",Master,16,Retail,2024-03-29,2024-04-30,1109,8.8,Smart Analytics +AI02739,Data Engineer,154419,USD,154419,MI,FT,Norway,L,Norway,50,"Tableau, Computer Vision, Python, TensorFlow, Java",Master,4,Technology,2024-08-12,2024-10-08,1099,9.3,DataVision Ltd +AI02740,AI Product Manager,162643,EUR,138247,SE,CT,Netherlands,L,South Africa,100,"Python, TensorFlow, Tableau, PyTorch",PhD,9,Media,2024-03-24,2024-05-21,2247,7.3,Neural Networks Co +AI02741,Computer Vision Engineer,268185,JPY,29500350,EX,CT,Japan,L,Argentina,50,"Data Visualization, Spark, NLP",Bachelor,11,Automotive,2024-12-27,2025-01-16,942,8.7,TechCorp Inc +AI02742,Data Scientist,180863,GBP,135647,SE,PT,United Kingdom,L,United Kingdom,50,"Python, GCP, TensorFlow, NLP, PyTorch",Bachelor,5,Automotive,2024-01-21,2024-02-20,1397,7.6,Cognitive Computing +AI02743,Machine Learning Researcher,34377,USD,34377,EN,CT,China,L,China,0,"PyTorch, TensorFlow, Computer Vision, Mathematics",Bachelor,1,Real Estate,2024-03-01,2024-05-03,1626,5.8,Machine Intelligence Group +AI02744,Deep Learning Engineer,66309,USD,66309,EX,PT,China,M,China,100,"Spark, Tableau, Linux",Associate,12,Real Estate,2025-01-23,2025-04-05,2186,7.5,TechCorp Inc +AI02745,Computer Vision Engineer,151661,SGD,197159,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, NLP, Mathematics",Master,17,Automotive,2025-01-21,2025-03-24,2125,6,Algorithmic Solutions +AI02746,Principal Data Scientist,169405,JPY,18634550,EX,FL,Japan,M,Sweden,100,"R, Hadoop, Linux",Bachelor,10,Consulting,2024-02-12,2024-03-16,2077,9,DeepTech Ventures +AI02747,NLP Engineer,72571,JPY,7982810,EN,CT,Japan,S,Japan,50,"AWS, Hadoop, SQL, PyTorch",Associate,0,Consulting,2024-11-22,2025-01-29,1015,5,Machine Intelligence Group +AI02748,Data Scientist,240989,GBP,180742,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, TensorFlow, NLP, MLOps",PhD,15,Energy,2024-08-22,2024-10-13,2290,8.6,Future Systems +AI02749,Data Analyst,44658,USD,44658,EN,FL,Finland,S,Finland,0,"AWS, PyTorch, Tableau",Bachelor,1,Energy,2024-08-26,2024-10-14,1578,9.3,Smart Analytics +AI02750,Autonomous Systems Engineer,51559,EUR,43825,EN,CT,France,S,France,50,"Scala, Deep Learning, Computer Vision, PyTorch, SQL",PhD,1,Technology,2024-06-24,2024-07-27,2101,9.5,Cognitive Computing +AI02751,NLP Engineer,165686,CHF,149117,MI,CT,Switzerland,L,Switzerland,100,"Docker, Statistics, Python",Bachelor,2,Real Estate,2024-05-23,2024-06-23,1760,7.2,DeepTech Ventures +AI02752,Head of AI,105339,CHF,94805,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Git, Deep Learning, Data Visualization",Master,0,Healthcare,2024-08-02,2024-08-24,876,8,Algorithmic Solutions +AI02753,AI Software Engineer,209800,EUR,178330,EX,CT,Netherlands,M,Netherlands,0,"Kubernetes, Python, SQL",PhD,18,Consulting,2024-11-19,2024-12-05,2126,8.9,Predictive Systems +AI02754,AI Architect,118780,USD,118780,MI,FT,United States,M,United States,0,"SQL, Data Visualization, TensorFlow, MLOps",Associate,3,Consulting,2025-02-06,2025-03-13,933,6.8,Smart Analytics +AI02755,AI Consultant,125984,CAD,157480,SE,FL,Canada,S,Canada,100,"NLP, Java, Computer Vision",Bachelor,6,Finance,2024-10-30,2024-12-23,1473,9.1,Future Systems +AI02756,Research Scientist,121739,SGD,158261,SE,FT,Singapore,M,Singapore,0,"PyTorch, Java, Spark",PhD,6,Technology,2024-08-19,2024-10-25,1712,8.9,Cloud AI Solutions +AI02757,Deep Learning Engineer,141394,EUR,120185,SE,FT,Netherlands,M,Chile,50,"Hadoop, TensorFlow, Python",Bachelor,5,Telecommunications,2024-05-08,2024-06-01,1923,8.8,Cloud AI Solutions +AI02758,Machine Learning Researcher,74325,USD,74325,EN,FL,Norway,S,Norway,0,"Linux, MLOps, SQL, R",Master,0,Technology,2024-06-21,2024-08-02,2350,9.2,DataVision Ltd +AI02759,Head of AI,181015,SGD,235320,SE,PT,Singapore,L,Singapore,100,"Java, SQL, GCP",Master,7,Technology,2025-03-01,2025-03-26,968,6.6,Cognitive Computing +AI02760,NLP Engineer,54802,SGD,71243,EN,FT,Singapore,M,Singapore,0,"Scala, Python, Docker, Computer Vision",Bachelor,0,Healthcare,2025-03-24,2025-05-20,733,6.3,Smart Analytics +AI02761,Data Analyst,113391,JPY,12473010,MI,PT,Japan,M,Japan,100,"Scala, Data Visualization, Git, Spark",Master,3,Automotive,2024-04-11,2024-05-16,865,8.5,Future Systems +AI02762,NLP Engineer,171064,USD,171064,EX,CT,Ireland,L,Ireland,50,"AWS, PyTorch, Computer Vision, Hadoop, SQL",Bachelor,15,Consulting,2024-11-10,2024-12-27,1791,7.2,Cloud AI Solutions +AI02763,Head of AI,122125,USD,122125,MI,FT,Denmark,M,Denmark,100,"Scala, Tableau, Python, Linux",Bachelor,3,Media,2024-10-08,2024-12-18,1199,7.4,Cognitive Computing +AI02764,Machine Learning Engineer,133237,AUD,179870,SE,CT,Australia,S,Australia,50,"Python, Hadoop, Linux, Scala, Computer Vision",Associate,5,Retail,2024-04-22,2024-06-26,1707,8.4,Machine Intelligence Group +AI02765,Deep Learning Engineer,89475,JPY,9842250,EN,PT,Japan,L,Japan,100,"Python, TensorFlow, Git, Mathematics, Spark",PhD,1,Transportation,2025-01-01,2025-02-27,1924,5.1,DeepTech Ventures +AI02766,AI Product Manager,92805,USD,92805,MI,FL,United States,S,New Zealand,50,"Linux, Spark, Scala, MLOps",Associate,2,Government,2024-04-10,2024-06-21,1389,8,Digital Transformation LLC +AI02767,AI Product Manager,277302,AUD,374358,EX,PT,Australia,L,Australia,100,"Git, Statistics, TensorFlow, SQL, Kubernetes",Master,14,Finance,2024-03-27,2024-05-08,1139,5.7,Quantum Computing Inc +AI02768,AI Consultant,157131,USD,157131,SE,FT,Norway,L,Norway,50,"Spark, Tableau, Computer Vision, NLP",PhD,8,Automotive,2024-07-01,2024-08-31,1981,7.3,Cognitive Computing +AI02769,Machine Learning Engineer,124242,EUR,105606,SE,CT,France,S,Singapore,50,"Spark, Mathematics, MLOps",Master,6,Media,2024-04-29,2024-07-09,2466,9.1,Predictive Systems +AI02770,Robotics Engineer,165005,AUD,222757,EX,FL,Australia,L,Austria,0,"Mathematics, Computer Vision, Data Visualization, Statistics",PhD,18,Education,2024-08-08,2024-09-14,1077,7.9,Quantum Computing Inc +AI02771,Data Analyst,55240,EUR,46954,EN,CT,Austria,S,Austria,0,"Kubernetes, Deep Learning, Git",Bachelor,1,Finance,2024-06-24,2024-08-24,1766,9.7,Neural Networks Co +AI02772,Robotics Engineer,39042,USD,39042,SE,PT,India,M,Colombia,0,"Deep Learning, Linux, Java",Bachelor,6,Manufacturing,2025-02-28,2025-04-17,655,8.5,Autonomous Tech +AI02773,Machine Learning Researcher,64577,USD,64577,EX,FL,India,M,India,50,"NLP, SQL, Scala",Bachelor,15,Government,2024-03-01,2024-04-21,1560,6.6,Cognitive Computing +AI02774,Head of AI,50657,USD,50657,EN,CT,Israel,S,Israel,0,"Python, Java, Tableau, TensorFlow, Mathematics",PhD,0,Real Estate,2024-11-23,2024-12-14,1622,9.1,TechCorp Inc +AI02775,Machine Learning Engineer,108147,GBP,81110,SE,FL,United Kingdom,M,Switzerland,100,"MLOps, Kubernetes, R",Associate,6,Finance,2025-02-07,2025-02-25,690,5.1,Future Systems +AI02776,Robotics Engineer,186468,USD,186468,EX,FL,Norway,M,Norway,100,"TensorFlow, AWS, Data Visualization, Python",Master,17,Automotive,2024-09-06,2024-10-09,2476,5.1,Digital Transformation LLC +AI02777,Data Engineer,148941,EUR,126600,SE,PT,Germany,M,Germany,0,"Python, NLP, Docker, GCP",Bachelor,6,Media,2025-04-24,2025-05-18,2164,9.1,Digital Transformation LLC +AI02778,AI Software Engineer,61003,USD,61003,EN,FT,Norway,S,Norway,100,"Statistics, Computer Vision, Data Visualization",PhD,0,Manufacturing,2025-04-09,2025-05-26,847,7.2,Cloud AI Solutions +AI02779,ML Ops Engineer,130513,USD,130513,SE,PT,Ireland,L,Ireland,0,"Linux, Kubernetes, Scala, Java",Bachelor,9,Technology,2024-05-30,2024-06-22,1034,5.3,Future Systems +AI02780,AI Architect,218583,EUR,185796,EX,FT,France,L,France,100,"Hadoop, R, SQL, PyTorch, Git",PhD,18,Gaming,2024-05-06,2024-06-10,1862,9.4,Machine Intelligence Group +AI02781,AI Consultant,57623,USD,57623,EN,FT,Sweden,S,Sweden,50,"Tableau, AWS, Hadoop, Docker, Statistics",Bachelor,0,Media,2024-05-30,2024-06-20,973,9.8,Future Systems +AI02782,AI Product Manager,63893,USD,63893,EN,FL,South Korea,M,Australia,0,"Linux, Deep Learning, Java, SQL, AWS",PhD,1,Finance,2025-01-12,2025-01-27,984,9.8,Smart Analytics +AI02783,AI Consultant,198531,USD,198531,EX,FL,Norway,M,Norway,100,"AWS, Kubernetes, NLP, Statistics",Associate,12,Transportation,2025-04-14,2025-05-14,1650,9.5,Cognitive Computing +AI02784,Machine Learning Researcher,66355,SGD,86262,EN,FT,Singapore,S,Singapore,100,"Kubernetes, Tableau, Hadoop",PhD,1,Finance,2024-03-10,2024-03-28,762,8.1,Cognitive Computing +AI02785,Head of AI,71500,USD,71500,EN,FT,Finland,L,Finland,0,"R, Hadoop, Linux, SQL, Computer Vision",Master,1,Automotive,2025-01-26,2025-04-01,1426,6.3,AI Innovations +AI02786,AI Specialist,99853,USD,99853,MI,FT,Israel,L,Israel,0,"Computer Vision, Kubernetes, SQL, Docker",Master,2,Consulting,2025-01-07,2025-03-21,679,10,AI Innovations +AI02787,Autonomous Systems Engineer,160109,CHF,144098,SE,PT,Switzerland,M,Thailand,100,"MLOps, AWS, Spark, R",Master,5,Consulting,2024-02-18,2024-03-28,914,9,Digital Transformation LLC +AI02788,AI Specialist,126146,USD,126146,SE,CT,Sweden,M,United Kingdom,50,"PyTorch, TensorFlow, R, SQL, Spark",Master,9,Media,2025-03-06,2025-05-10,2264,8.7,Quantum Computing Inc +AI02789,AI Consultant,32128,USD,32128,EN,PT,China,L,China,50,"Python, Spark, MLOps, TensorFlow, Scala",Master,0,Media,2024-04-23,2024-07-02,1091,7.4,Future Systems +AI02790,AI Software Engineer,23707,USD,23707,EN,FL,India,M,Spain,0,"PyTorch, Hadoop, Deep Learning, Linux",Bachelor,1,Healthcare,2024-03-02,2024-04-27,1306,9.8,Predictive Systems +AI02791,Data Scientist,210918,CAD,263648,EX,FT,Canada,L,Japan,50,"Python, R, Docker, Linux",Master,10,Energy,2024-01-03,2024-01-31,881,7.5,Future Systems +AI02792,AI Architect,132476,EUR,112605,SE,CT,France,L,France,50,"PyTorch, Spark, Statistics, Python",PhD,6,Education,2024-10-16,2024-11-05,2332,7.4,Digital Transformation LLC +AI02793,Research Scientist,97049,EUR,82492,SE,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Git",PhD,5,Telecommunications,2025-01-10,2025-03-02,1819,8.1,Smart Analytics +AI02794,AI Software Engineer,52529,CAD,65661,EN,FT,Canada,M,Ireland,100,"MLOps, Spark, Tableau, Scala, Statistics",Master,0,Manufacturing,2024-03-06,2024-04-27,2052,5.1,Cognitive Computing +AI02795,Principal Data Scientist,204220,EUR,173587,EX,PT,Austria,S,Egypt,50,"Computer Vision, Deep Learning, Linux",Bachelor,12,Automotive,2024-03-24,2024-04-13,607,8.7,TechCorp Inc +AI02796,AI Software Engineer,132720,SGD,172536,SE,FL,Singapore,L,Singapore,50,"R, Hadoop, Tableau",Bachelor,8,Media,2024-08-04,2024-10-16,1384,6.8,Advanced Robotics +AI02797,Autonomous Systems Engineer,81244,USD,81244,MI,CT,Finland,L,Finland,50,"Docker, Hadoop, Statistics, Linux",Master,4,Manufacturing,2024-05-17,2024-06-27,1528,9.8,Machine Intelligence Group +AI02798,Machine Learning Researcher,161739,USD,161739,MI,FL,Norway,L,Norway,100,"NLP, Kubernetes, PyTorch, Docker, SQL",Master,3,Automotive,2024-04-06,2024-06-08,1521,6.4,DataVision Ltd +AI02799,ML Ops Engineer,71582,CAD,89478,MI,CT,Canada,S,Canada,0,"Kubernetes, Scala, AWS, TensorFlow",PhD,4,Manufacturing,2025-01-18,2025-02-05,865,9.2,DataVision Ltd +AI02800,Robotics Engineer,55770,USD,55770,SE,PT,China,S,China,0,"Docker, R, AWS, Python, Kubernetes",Bachelor,6,Manufacturing,2025-02-17,2025-03-12,1015,9.6,Smart Analytics +AI02801,AI Product Manager,176027,USD,176027,SE,CT,Norway,M,Norway,0,"R, SQL, Tableau",Bachelor,7,Government,2024-08-01,2024-10-05,1205,5.3,Machine Intelligence Group +AI02802,AI Product Manager,47687,USD,47687,SE,CT,India,L,Japan,0,"Data Visualization, TensorFlow, Statistics",Associate,9,Telecommunications,2024-07-20,2024-09-18,681,6.2,Advanced Robotics +AI02803,Autonomous Systems Engineer,60812,USD,60812,MI,PT,South Korea,M,South Korea,0,"R, Git, Deep Learning, GCP",Master,4,Finance,2024-07-02,2024-08-07,628,7.4,Predictive Systems +AI02804,Research Scientist,126567,JPY,13922370,MI,PT,Japan,L,Netherlands,50,"PyTorch, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-12-15,2024-12-29,2386,7.1,Cognitive Computing +AI02805,Research Scientist,97033,SGD,126143,MI,CT,Singapore,S,France,0,"Azure, GCP, Spark, Statistics, Computer Vision",Master,2,Real Estate,2025-02-08,2025-04-19,2196,9.6,Future Systems +AI02806,AI Specialist,70605,USD,70605,EN,FL,Norway,S,Norway,0,"Kubernetes, GCP, Spark, Tableau, Python",Bachelor,0,Consulting,2024-08-04,2024-09-14,1382,8.9,Autonomous Tech +AI02807,Deep Learning Engineer,121078,USD,121078,SE,FT,Israel,L,Israel,50,"Computer Vision, Azure, Data Visualization, Java",Bachelor,5,Retail,2024-06-11,2024-07-22,1033,5.9,DeepTech Ventures +AI02808,ML Ops Engineer,255771,USD,255771,EX,FT,Denmark,S,Denmark,0,"Azure, Kubernetes, Tableau, Python, Hadoop",Master,10,Transportation,2024-11-13,2025-01-14,1097,5.4,Machine Intelligence Group +AI02809,Data Engineer,111629,EUR,94885,SE,PT,France,L,France,50,"Tableau, Statistics, Spark",Master,9,Healthcare,2024-02-07,2024-03-13,1123,6.3,DeepTech Ventures +AI02810,Autonomous Systems Engineer,127275,USD,127275,MI,PT,Denmark,S,Denmark,100,"Java, AWS, SQL, NLP, Deep Learning",Associate,3,Automotive,2024-08-07,2024-09-19,2009,7,Smart Analytics +AI02811,Robotics Engineer,226295,USD,226295,EX,FL,Ireland,S,New Zealand,100,"Docker, Python, AWS",Associate,19,Consulting,2025-01-26,2025-02-12,615,7.6,Autonomous Tech +AI02812,AI Consultant,60249,USD,60249,EN,FL,Sweden,M,Sweden,50,"Scala, Mathematics, Tableau, Statistics, MLOps",Associate,0,Real Estate,2024-01-15,2024-03-05,2151,5.3,Quantum Computing Inc +AI02813,Principal Data Scientist,154394,USD,154394,SE,FL,United States,S,United States,0,"Kubernetes, Hadoop, Python, Azure",Master,5,Manufacturing,2024-04-19,2024-06-20,611,9.2,Digital Transformation LLC +AI02814,Deep Learning Engineer,77141,EUR,65570,MI,CT,Netherlands,S,Russia,0,"Kubernetes, Data Visualization, Mathematics",Associate,2,Automotive,2025-03-24,2025-04-09,1999,7.6,DataVision Ltd +AI02815,AI Product Manager,89813,EUR,76341,MI,PT,Austria,M,Austria,100,"GCP, Java, PyTorch",Associate,2,Technology,2024-06-20,2024-08-20,2490,8.9,Algorithmic Solutions +AI02816,Research Scientist,80989,USD,80989,MI,FT,Finland,S,Finland,0,"R, Statistics, Hadoop, Docker",PhD,4,Retail,2025-02-14,2025-04-25,540,8.4,DataVision Ltd +AI02817,Data Engineer,271778,CHF,244600,EX,PT,Switzerland,L,Switzerland,50,"AWS, Scala, Docker",Bachelor,12,Consulting,2024-03-23,2024-05-31,1285,5.1,Algorithmic Solutions +AI02818,AI Research Scientist,46378,USD,46378,SE,FL,India,S,India,100,"SQL, NLP, PyTorch",Associate,9,Finance,2025-01-26,2025-02-11,1773,9.2,Digital Transformation LLC +AI02819,Principal Data Scientist,101913,EUR,86626,MI,FL,Germany,L,Germany,50,"Spark, Java, MLOps, PyTorch",PhD,3,Telecommunications,2025-01-12,2025-03-23,2063,7.4,Quantum Computing Inc +AI02820,Data Analyst,29407,USD,29407,MI,PT,India,M,India,50,"SQL, TensorFlow, Tableau",PhD,4,Retail,2024-04-30,2024-06-23,2053,5.5,Predictive Systems +AI02821,AI Specialist,122457,USD,122457,EX,FL,South Korea,M,South Korea,0,"Scala, Deep Learning, R, Hadoop, Statistics",Master,12,Automotive,2024-03-13,2024-05-23,595,6.7,Machine Intelligence Group +AI02822,AI Research Scientist,121296,EUR,103102,SE,CT,France,M,Philippines,100,"Data Visualization, SQL, PyTorch",PhD,6,Technology,2024-02-12,2024-03-24,602,6.3,Neural Networks Co +AI02823,AI Specialist,154186,USD,154186,SE,CT,Norway,S,Norway,0,"Git, PyTorch, Tableau, MLOps",PhD,6,Gaming,2024-11-07,2024-12-15,1374,9.5,AI Innovations +AI02824,Robotics Engineer,215813,CAD,269766,EX,CT,Canada,S,Canada,0,"Python, Hadoop, SQL",Master,17,Government,2025-01-06,2025-02-04,664,6.1,TechCorp Inc +AI02825,Robotics Engineer,121313,SGD,157707,MI,FT,Singapore,L,Switzerland,50,"Git, NLP, PyTorch, Python",Associate,4,Gaming,2024-10-05,2024-11-20,1250,8,Predictive Systems +AI02826,Machine Learning Researcher,103697,JPY,11406670,MI,CT,Japan,S,Japan,0,"SQL, Scala, Hadoop, Azure",Bachelor,2,Energy,2024-01-30,2024-03-07,657,5.6,Algorithmic Solutions +AI02827,Research Scientist,148481,CHF,133633,MI,FT,Switzerland,M,Switzerland,0,"Python, MLOps, SQL, Java, Kubernetes",Bachelor,3,Manufacturing,2024-07-11,2024-09-16,1271,8.3,Future Systems +AI02828,AI Software Engineer,247799,USD,247799,EX,CT,Norway,S,Norway,50,"PyTorch, SQL, Linux, Hadoop",Associate,18,Media,2024-04-27,2024-06-30,717,7.8,Cognitive Computing +AI02829,Autonomous Systems Engineer,250860,USD,250860,EX,FL,United States,M,United States,50,"SQL, Tableau, Kubernetes, GCP",Associate,10,Transportation,2024-06-25,2024-07-11,891,7.8,Quantum Computing Inc +AI02830,Research Scientist,163167,AUD,220275,EX,CT,Australia,S,Australia,100,"Kubernetes, Java, GCP, SQL, AWS",Bachelor,19,Energy,2024-01-27,2024-04-03,1603,5.9,Autonomous Tech +AI02831,Principal Data Scientist,323671,USD,323671,EX,CT,United States,L,United States,50,"Computer Vision, Hadoop, Deep Learning",PhD,15,Telecommunications,2025-04-28,2025-06-15,1701,8.3,TechCorp Inc +AI02832,Robotics Engineer,70337,USD,70337,EN,FT,Norway,S,Norway,100,"Hadoop, NLP, SQL, Scala",Associate,1,Healthcare,2024-08-27,2024-10-10,888,9.2,Machine Intelligence Group +AI02833,Data Analyst,63357,EUR,53853,EN,FL,Germany,M,Egypt,100,"Mathematics, Data Visualization, Scala, SQL, Tableau",Bachelor,1,Government,2025-02-15,2025-03-29,2153,5.6,Digital Transformation LLC +AI02834,Head of AI,107154,USD,107154,SE,FL,Israel,S,Israel,0,"PyTorch, GCP, NLP, Java",Master,8,Healthcare,2024-06-22,2024-08-26,1412,6.5,TechCorp Inc +AI02835,AI Research Scientist,184525,USD,184525,SE,PT,Norway,M,Norway,0,"SQL, Python, AWS, TensorFlow",Master,5,Retail,2024-01-26,2024-02-09,2036,5.8,Algorithmic Solutions +AI02836,Robotics Engineer,94391,EUR,80232,MI,FL,Austria,L,Austria,100,"Spark, PyTorch, Python, MLOps",Master,3,Media,2025-01-05,2025-01-27,1704,5.7,Smart Analytics +AI02837,NLP Engineer,134275,USD,134275,SE,FL,South Korea,L,South Korea,0,"Spark, Azure, Computer Vision, Data Visualization, SQL",PhD,9,Automotive,2024-08-26,2024-11-05,1728,5.9,Autonomous Tech +AI02838,AI Consultant,211162,USD,211162,EX,FT,United States,M,United States,50,"Spark, Python, Tableau",PhD,19,Technology,2024-04-12,2024-05-17,2411,9.2,DataVision Ltd +AI02839,Computer Vision Engineer,70647,USD,70647,EN,PT,Ireland,L,Ireland,0,"Python, Statistics, Mathematics, Docker, TensorFlow",Bachelor,0,Education,2024-07-17,2024-09-10,1471,9.5,DataVision Ltd +AI02840,Principal Data Scientist,243402,USD,243402,EX,FT,Finland,L,Finland,0,"AWS, NLP, Docker, Linux",Bachelor,11,Consulting,2024-04-28,2024-05-12,2037,8.1,Digital Transformation LLC +AI02841,AI Product Manager,57000,USD,57000,EN,FL,South Korea,S,India,100,"Linux, SQL, Scala",Associate,0,Finance,2024-11-08,2025-01-03,1424,7.6,Smart Analytics +AI02842,Data Analyst,90610,USD,90610,MI,CT,Israel,S,Israel,50,"Kubernetes, Scala, Mathematics",PhD,4,Telecommunications,2025-02-14,2025-03-18,2329,9.1,Future Systems +AI02843,Research Scientist,240830,EUR,204706,EX,FL,Austria,L,Austria,50,"PyTorch, SQL, Java, Linux, Statistics",PhD,16,Manufacturing,2024-03-29,2024-04-13,563,9.3,Smart Analytics +AI02844,Robotics Engineer,205777,EUR,174910,EX,FL,Austria,L,Colombia,0,"GCP, Spark, TensorFlow, Git",Bachelor,11,Healthcare,2025-04-18,2025-05-27,1273,6.4,DataVision Ltd +AI02845,Machine Learning Researcher,52483,USD,52483,EN,FT,Finland,M,Finland,100,"Hadoop, Data Visualization, SQL",Bachelor,0,Manufacturing,2024-08-30,2024-09-21,1921,9.4,Neural Networks Co +AI02846,Principal Data Scientist,35085,USD,35085,MI,PT,India,M,India,50,"Python, TensorFlow, Mathematics, Hadoop",Associate,4,Media,2025-04-17,2025-05-05,525,9.2,Algorithmic Solutions +AI02847,Principal Data Scientist,170138,USD,170138,SE,PT,Ireland,L,Belgium,0,"Linux, Python, TensorFlow, AWS, Tableau",Master,7,Technology,2025-04-08,2025-05-22,1991,7.6,Advanced Robotics +AI02848,AI Software Engineer,86746,USD,86746,MI,FT,Ireland,M,Turkey,100,"Docker, SQL, Computer Vision",Associate,2,Consulting,2024-12-19,2025-02-26,2126,7.6,Predictive Systems +AI02849,Data Analyst,27601,USD,27601,MI,FT,India,S,India,50,"Python, TensorFlow, Mathematics, MLOps, SQL",Bachelor,4,Technology,2024-05-17,2024-07-06,2050,9.4,Future Systems +AI02850,Principal Data Scientist,114696,USD,114696,SE,FT,Sweden,S,Sweden,0,"Computer Vision, Java, Git, TensorFlow",Associate,7,Government,2025-02-28,2025-05-10,736,6,Neural Networks Co +AI02851,Data Analyst,123445,USD,123445,SE,FT,Finland,M,Canada,50,"Kubernetes, Python, AWS, SQL",Master,5,Telecommunications,2025-04-26,2025-06-15,1506,5.1,Quantum Computing Inc +AI02852,Head of AI,70615,USD,70615,EN,CT,South Korea,L,South Korea,50,"PyTorch, GCP, Linux, Spark",Associate,0,Automotive,2025-04-16,2025-06-19,1374,5.4,Neural Networks Co +AI02853,Data Scientist,190307,CAD,237884,EX,CT,Canada,L,Canada,100,"Statistics, Kubernetes, Azure",Master,17,Consulting,2024-03-30,2024-04-16,746,5.6,Cognitive Computing +AI02854,AI Software Engineer,319590,USD,319590,EX,FL,United States,L,United States,100,"PyTorch, MLOps, GCP",Master,19,Government,2024-01-01,2024-03-14,720,6.4,Cloud AI Solutions +AI02855,AI Research Scientist,207479,USD,207479,SE,PT,Norway,L,China,0,"NLP, Python, Computer Vision, Mathematics",Master,7,Technology,2024-06-03,2024-06-17,2025,6.2,Cloud AI Solutions +AI02856,AI Product Manager,131422,USD,131422,MI,FL,United States,L,Vietnam,50,"Java, Computer Vision, AWS",Associate,4,Gaming,2024-05-24,2024-07-17,1676,5.2,Digital Transformation LLC +AI02857,ML Ops Engineer,95848,EUR,81471,MI,PT,Germany,M,Thailand,0,"Linux, Spark, Deep Learning",Associate,4,Consulting,2024-09-08,2024-10-22,919,5.3,Predictive Systems +AI02858,Robotics Engineer,94145,JPY,10355950,MI,FL,Japan,L,Japan,50,"Python, R, Mathematics, Scala, NLP",PhD,4,Real Estate,2024-01-20,2024-03-09,721,7.5,AI Innovations +AI02859,AI Consultant,130395,CAD,162994,SE,CT,Canada,L,Canada,100,"GCP, Python, MLOps, Kubernetes",PhD,9,Real Estate,2024-12-01,2025-02-05,1098,6.4,Neural Networks Co +AI02860,Robotics Engineer,77116,EUR,65549,EN,CT,Germany,M,Germany,100,"Kubernetes, Computer Vision, Hadoop",Associate,0,Education,2024-03-23,2024-05-01,2136,5.7,Algorithmic Solutions +AI02861,Robotics Engineer,21922,USD,21922,EN,PT,India,L,Romania,50,"Spark, Java, GCP",Bachelor,0,Finance,2024-11-06,2025-01-12,624,5.3,TechCorp Inc +AI02862,AI Research Scientist,248823,USD,248823,EX,CT,United States,S,United States,100,"Python, Git, Mathematics, TensorFlow, Statistics",Bachelor,13,Education,2024-10-05,2024-12-01,990,6.8,Advanced Robotics +AI02863,Head of AI,36405,USD,36405,MI,PT,India,M,India,100,"Linux, Deep Learning, Python, NLP",Master,3,Automotive,2024-10-21,2024-11-13,2089,5.7,DataVision Ltd +AI02864,Principal Data Scientist,253609,EUR,215568,EX,CT,France,L,France,50,"Spark, Tableau, Linux, Python, R",PhD,15,Transportation,2024-10-23,2024-11-12,2390,6,Advanced Robotics +AI02865,NLP Engineer,203699,CHF,183329,SE,CT,Switzerland,M,China,0,"Python, Kubernetes, Computer Vision, TensorFlow, Statistics",PhD,5,Media,2025-02-04,2025-02-21,1665,7.3,Autonomous Tech +AI02866,Machine Learning Engineer,141871,CHF,127684,MI,FL,Switzerland,M,Estonia,100,"Scala, SQL, TensorFlow, Java",Bachelor,2,Finance,2024-01-19,2024-03-02,1034,7.5,Machine Intelligence Group +AI02867,AI Consultant,190310,AUD,256919,EX,PT,Australia,S,Australia,50,"Linux, PyTorch, R, Computer Vision, Python",PhD,10,Technology,2024-11-23,2024-12-18,793,9.6,Smart Analytics +AI02868,Data Scientist,68143,USD,68143,MI,CT,South Korea,S,China,50,"Mathematics, TensorFlow, Git, Python",PhD,2,Gaming,2024-12-29,2025-02-07,560,9.2,Autonomous Tech +AI02869,Robotics Engineer,74136,USD,74136,EN,FL,Ireland,L,Ireland,50,"Statistics, SQL, Azure",PhD,1,Automotive,2024-03-27,2024-06-01,886,9.6,DeepTech Ventures +AI02870,NLP Engineer,73619,EUR,62576,EN,CT,France,L,Estonia,0,"Kubernetes, R, MLOps",PhD,0,Telecommunications,2025-01-26,2025-04-04,1664,6.1,Digital Transformation LLC +AI02871,Research Scientist,77655,USD,77655,EN,PT,Denmark,M,Denmark,50,"Python, Spark, NLP, Java, SQL",Master,0,Media,2025-03-02,2025-05-04,859,9.1,Cloud AI Solutions +AI02872,NLP Engineer,123447,EUR,104930,SE,FL,Austria,S,Austria,50,"Python, TensorFlow, MLOps, Computer Vision",Associate,5,Retail,2024-11-21,2025-01-28,2155,9,Neural Networks Co +AI02873,AI Software Engineer,89174,USD,89174,MI,FL,United States,S,United States,50,"Linux, Statistics, SQL",PhD,4,Gaming,2024-04-10,2024-04-27,1358,7.6,Neural Networks Co +AI02874,Data Analyst,59752,USD,59752,SE,FT,India,L,India,100,"Deep Learning, SQL, Data Visualization, PyTorch, Hadoop",Associate,8,Retail,2024-07-17,2024-09-08,1777,6.7,Neural Networks Co +AI02875,AI Research Scientist,82657,USD,82657,EN,FT,United States,M,United States,100,"MLOps, Python, Linux, Deep Learning",Master,0,Consulting,2025-01-17,2025-03-14,1168,7.6,Digital Transformation LLC +AI02876,Data Analyst,60940,GBP,45705,EN,FL,United Kingdom,M,United Kingdom,50,"GCP, Statistics, Tableau, Data Visualization, NLP",Associate,1,Finance,2025-02-28,2025-04-30,1822,9.4,TechCorp Inc +AI02877,AI Specialist,147265,EUR,125175,EX,FT,Germany,M,Indonesia,50,"Kubernetes, Hadoop, PyTorch, Azure, Git",PhD,15,Real Estate,2024-04-11,2024-05-31,1634,7.4,Future Systems +AI02878,AI Research Scientist,87462,USD,87462,MI,PT,United States,M,Turkey,50,"Git, R, Mathematics, Linux",Associate,4,Telecommunications,2024-09-29,2024-11-18,808,5.4,DeepTech Ventures +AI02879,Principal Data Scientist,203296,CAD,254120,EX,FL,Canada,S,Canada,0,"Java, MLOps, R, Scala",Master,14,Telecommunications,2024-03-01,2024-04-12,1334,9.5,Machine Intelligence Group +AI02880,Machine Learning Researcher,102443,USD,102443,EN,FT,United States,L,Turkey,0,"NLP, TensorFlow, Data Visualization",PhD,0,Technology,2024-07-06,2024-08-13,2438,5.9,TechCorp Inc +AI02881,Autonomous Systems Engineer,165965,SGD,215755,EX,FL,Singapore,S,Singapore,50,"PyTorch, TensorFlow, Python, Statistics, Azure",Master,14,Healthcare,2024-03-31,2024-04-24,567,8.1,Algorithmic Solutions +AI02882,Computer Vision Engineer,142165,USD,142165,SE,FT,Israel,M,Thailand,0,"Python, Tableau, TensorFlow, Mathematics, PyTorch",Bachelor,6,Finance,2024-10-08,2024-12-12,544,8.6,DeepTech Ventures +AI02883,ML Ops Engineer,96944,SGD,126027,MI,FL,Singapore,S,Singapore,100,"Data Visualization, Linux, Scala, Azure",Associate,4,Consulting,2024-11-16,2025-01-19,2107,6,Quantum Computing Inc +AI02884,Data Analyst,101791,USD,101791,MI,FT,Norway,S,Norway,50,"R, Python, TensorFlow, Spark, Computer Vision",Bachelor,2,Technology,2024-04-23,2024-06-20,1704,7.1,Predictive Systems +AI02885,Data Engineer,24801,USD,24801,EN,FL,India,L,Estonia,100,"Scala, Spark, Python, Statistics",Bachelor,1,Manufacturing,2024-07-18,2024-08-18,2393,5.5,AI Innovations +AI02886,AI Specialist,76230,USD,76230,MI,CT,South Korea,M,South Korea,0,"GCP, PyTorch, Computer Vision",Master,3,Real Estate,2024-01-22,2024-03-16,1380,8.2,Future Systems +AI02887,AI Research Scientist,63817,CAD,79771,MI,FL,Canada,S,France,100,"PyTorch, Computer Vision, Mathematics",Bachelor,3,Consulting,2024-06-03,2024-08-12,1787,6.4,Algorithmic Solutions +AI02888,AI Specialist,65577,EUR,55740,MI,FL,Austria,S,Austria,0,"Scala, Mathematics, Linux, MLOps",Associate,3,Energy,2024-10-11,2024-11-04,1471,7.3,TechCorp Inc +AI02889,Autonomous Systems Engineer,114972,JPY,12646920,MI,FT,Japan,M,Japan,100,"Docker, Mathematics, Hadoop",PhD,3,Education,2024-01-25,2024-03-24,1490,7.5,Neural Networks Co +AI02890,AI Product Manager,87185,EUR,74107,SE,PT,Austria,S,Austria,100,"Spark, GCP, Git, Python",PhD,9,Consulting,2024-11-04,2024-12-27,2477,8.8,Autonomous Tech +AI02891,Deep Learning Engineer,212207,CHF,190986,SE,CT,Switzerland,M,Switzerland,100,"Tableau, Scala, Java, Spark, Linux",PhD,8,Gaming,2024-07-14,2024-08-24,519,6.9,Future Systems +AI02892,Machine Learning Engineer,90028,USD,90028,EN,PT,Denmark,L,Denmark,50,"R, SQL, PyTorch, Statistics, Kubernetes",Associate,1,Education,2024-12-24,2025-01-19,2044,7.2,DeepTech Ventures +AI02893,AI Product Manager,156876,JPY,17256360,SE,PT,Japan,L,Ireland,100,"Java, AWS, Computer Vision, Deep Learning",PhD,5,Gaming,2024-08-10,2024-08-28,1727,8.8,Neural Networks Co +AI02894,AI Consultant,116522,USD,116522,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Mathematics, Deep Learning",PhD,6,Manufacturing,2024-03-20,2024-05-09,2027,8.7,Neural Networks Co +AI02895,ML Ops Engineer,156992,CAD,196240,SE,FT,Canada,L,Denmark,0,"Data Visualization, Java, R",Associate,6,Technology,2025-01-28,2025-03-05,2468,9.3,Smart Analytics +AI02896,AI Architect,86246,USD,86246,EN,PT,Sweden,L,Denmark,0,"Java, Linux, Computer Vision, Python",PhD,0,Energy,2024-08-30,2024-09-15,1034,5,DeepTech Ventures +AI02897,Research Scientist,71217,EUR,60534,EN,CT,Austria,M,Israel,0,"GCP, Docker, Statistics, Kubernetes",PhD,1,Media,2024-12-13,2025-01-08,2027,7.4,Neural Networks Co +AI02898,AI Consultant,206746,EUR,175734,EX,CT,Netherlands,L,Netherlands,100,"AWS, Spark, Python",Associate,14,Government,2024-05-22,2024-06-24,1248,8.7,Algorithmic Solutions +AI02899,AI Consultant,169673,EUR,144222,EX,FL,Netherlands,S,Hungary,100,"Git, Scala, AWS",PhD,17,Technology,2024-02-11,2024-04-01,749,8.9,Algorithmic Solutions +AI02900,AI Product Manager,144440,GBP,108330,EX,FL,United Kingdom,S,United Kingdom,0,"NLP, Hadoop, Python",Associate,16,Gaming,2024-10-20,2024-11-19,1944,5.2,Cognitive Computing +AI02901,Machine Learning Engineer,153212,EUR,130230,EX,FT,France,L,France,100,"Deep Learning, Tableau, Python, TensorFlow, Data Visualization",PhD,16,Real Estate,2024-11-14,2025-01-01,1882,5.3,Future Systems +AI02902,Head of AI,204044,EUR,173437,EX,FL,France,S,France,0,"Python, Spark, Deep Learning",PhD,10,Education,2024-11-25,2025-01-31,788,9.1,Smart Analytics +AI02903,Autonomous Systems Engineer,151754,EUR,128991,SE,FT,Germany,L,Germany,100,"Scala, R, Tableau, SQL, GCP",Bachelor,7,Media,2025-04-30,2025-07-05,966,7.8,Quantum Computing Inc +AI02904,Computer Vision Engineer,31800,USD,31800,MI,FT,India,M,India,0,"Scala, Java, Statistics, Tableau",Associate,3,Gaming,2024-01-12,2024-02-28,977,8.8,Neural Networks Co +AI02905,Machine Learning Researcher,58310,JPY,6414100,EN,FL,Japan,M,Japan,0,"R, Docker, NLP, AWS, Hadoop",Bachelor,0,Retail,2024-09-22,2024-11-09,2121,9.9,TechCorp Inc +AI02906,Research Scientist,56624,USD,56624,EN,FL,South Korea,L,United Kingdom,100,"Hadoop, MLOps, Statistics, PyTorch",Bachelor,1,Government,2024-12-03,2024-12-27,2253,8.6,Cloud AI Solutions +AI02907,Machine Learning Researcher,150671,JPY,16573810,SE,FT,Japan,L,Denmark,50,"Mathematics, Scala, Git, Data Visualization, SQL",Bachelor,6,Gaming,2024-05-03,2024-07-07,2248,6.4,Quantum Computing Inc +AI02908,Deep Learning Engineer,202936,GBP,152202,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, SQL, Tableau, Computer Vision",Associate,15,Transportation,2025-03-01,2025-03-30,1479,8,AI Innovations +AI02909,Machine Learning Engineer,162469,AUD,219333,SE,FL,Australia,L,Australia,50,"Azure, Hadoop, Kubernetes, Python, TensorFlow",Master,9,Finance,2025-04-01,2025-05-26,2079,5.2,Future Systems +AI02910,Robotics Engineer,212416,USD,212416,EX,CT,Norway,L,Norway,50,"Linux, Azure, SQL, Statistics",PhD,15,Gaming,2024-05-19,2024-06-05,1563,6.3,Future Systems +AI02911,Robotics Engineer,109255,CHF,98330,MI,PT,Switzerland,S,Switzerland,50,"Deep Learning, Git, Statistics, PyTorch, Computer Vision",Master,3,Gaming,2024-11-15,2025-01-03,2497,5.6,Neural Networks Co +AI02912,Head of AI,88844,CAD,111055,MI,FT,Canada,S,Canada,0,"Azure, Spark, Tableau, GCP, AWS",PhD,3,Media,2024-01-26,2024-02-26,2105,6.8,DataVision Ltd +AI02913,Data Engineer,113440,USD,113440,SE,PT,South Korea,M,Luxembourg,50,"AWS, Tableau, Kubernetes, Docker",Bachelor,9,Automotive,2024-08-20,2024-09-14,2313,9.9,Autonomous Tech +AI02914,Data Engineer,98544,USD,98544,MI,PT,Sweden,L,Sweden,0,"Statistics, Azure, Git, AWS",Associate,2,Manufacturing,2024-09-21,2024-11-19,1775,6.1,AI Innovations +AI02915,Principal Data Scientist,216605,USD,216605,EX,FL,Israel,M,Israel,0,"Deep Learning, Python, Data Visualization, Hadoop, TensorFlow",Bachelor,17,Government,2024-01-05,2024-03-14,920,5.1,Digital Transformation LLC +AI02916,Data Analyst,43555,USD,43555,MI,FL,China,M,South Korea,50,"TensorFlow, GCP, Azure, Scala",Bachelor,4,Energy,2024-05-08,2024-07-02,1426,6.8,TechCorp Inc +AI02917,AI Product Manager,216702,USD,216702,EX,FL,Ireland,S,Ireland,50,"Git, Kubernetes, NLP, Hadoop",PhD,11,Education,2025-04-06,2025-06-17,1477,7.8,Smart Analytics +AI02918,NLP Engineer,172329,USD,172329,SE,CT,Norway,L,Norway,100,"Hadoop, Kubernetes, Scala, Java, PyTorch",PhD,7,Technology,2024-06-05,2024-07-23,2023,6.9,Autonomous Tech +AI02919,Data Scientist,162643,USD,162643,EX,CT,Ireland,M,Ireland,100,"R, GCP, SQL, Docker",Bachelor,17,Finance,2024-06-22,2024-07-13,809,5.2,Autonomous Tech +AI02920,Computer Vision Engineer,239531,CHF,215578,EX,FT,Switzerland,M,South Africa,0,"SQL, TensorFlow, Git",Associate,10,Media,2024-06-11,2024-08-16,2292,5.8,Autonomous Tech +AI02921,Deep Learning Engineer,169678,USD,169678,SE,PT,Norway,M,Norway,100,"TensorFlow, Python, Azure, Scala, NLP",Bachelor,8,Manufacturing,2024-06-15,2024-07-24,1276,6.1,Neural Networks Co +AI02922,Autonomous Systems Engineer,119875,USD,119875,MI,CT,Denmark,M,Denmark,50,"Computer Vision, SQL, PyTorch, R",Associate,4,Healthcare,2024-11-20,2025-01-05,2145,9.7,Cloud AI Solutions +AI02923,Machine Learning Researcher,136892,JPY,15058120,SE,FT,Japan,L,Japan,100,"TensorFlow, MLOps, R, AWS",Associate,8,Finance,2025-04-03,2025-05-03,953,5.8,Machine Intelligence Group +AI02924,Principal Data Scientist,213789,GBP,160342,EX,PT,United Kingdom,M,United Kingdom,100,"Data Visualization, Python, Tableau, Spark, Hadoop",Bachelor,15,Manufacturing,2024-10-26,2024-12-13,1726,6.5,Smart Analytics +AI02925,AI Product Manager,145769,GBP,109327,SE,PT,United Kingdom,S,United Kingdom,0,"Scala, Kubernetes, Statistics",Associate,7,Government,2025-01-07,2025-02-03,588,6.1,Algorithmic Solutions +AI02926,Principal Data Scientist,178902,USD,178902,EX,PT,Finland,S,Finland,0,"PyTorch, Python, Data Visualization",Associate,18,Media,2024-02-19,2024-04-24,1082,8.3,Cloud AI Solutions +AI02927,Machine Learning Researcher,57877,USD,57877,SE,PT,China,S,China,50,"MLOps, Linux, Docker, Deep Learning, Computer Vision",PhD,8,Gaming,2024-06-27,2024-07-28,2380,8.4,Algorithmic Solutions +AI02928,Autonomous Systems Engineer,74494,CAD,93118,MI,FT,Canada,S,Canada,100,"MLOps, AWS, Python",Bachelor,2,Retail,2024-11-05,2024-12-15,554,5.4,Algorithmic Solutions +AI02929,Data Analyst,23410,USD,23410,EN,CT,China,S,China,0,"Java, Kubernetes, NLP",PhD,0,Finance,2024-07-23,2024-09-07,1946,6.1,Advanced Robotics +AI02930,AI Specialist,144968,JPY,15946480,SE,PT,Japan,S,Japan,50,"Java, Computer Vision, Python, Data Visualization",Master,6,Consulting,2024-10-12,2024-12-24,1986,7.8,Neural Networks Co +AI02931,ML Ops Engineer,283252,CHF,254927,EX,FT,Switzerland,S,Switzerland,100,"TensorFlow, Azure, Deep Learning, Python, Linux",Master,18,Energy,2024-02-29,2024-04-18,2390,5.5,DeepTech Ventures +AI02932,Computer Vision Engineer,70074,GBP,52556,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, Statistics",Associate,0,Automotive,2025-03-03,2025-05-07,2141,9.7,DeepTech Ventures +AI02933,Autonomous Systems Engineer,111820,SGD,145366,SE,FL,Singapore,M,Mexico,100,"Kubernetes, Scala, PyTorch",Associate,5,Manufacturing,2024-11-01,2025-01-08,533,8.3,DeepTech Ventures +AI02934,ML Ops Engineer,190557,USD,190557,EX,CT,Israel,S,Israel,100,"Scala, Statistics, PyTorch, Docker",Master,12,Retail,2024-12-26,2025-01-13,798,6.9,Machine Intelligence Group +AI02935,Data Scientist,111831,USD,111831,SE,FL,Ireland,S,Ireland,50,"GCP, Tableau, Python",Associate,7,Manufacturing,2024-05-04,2024-06-24,533,8.3,Digital Transformation LLC +AI02936,Machine Learning Engineer,19152,USD,19152,EN,FT,India,M,India,100,"Java, Scala, Tableau, Data Visualization",Master,1,Gaming,2024-03-10,2024-05-01,1579,9.7,Smart Analytics +AI02937,Machine Learning Researcher,193150,USD,193150,EX,FL,Ireland,S,Ireland,100,"Python, TensorFlow, Tableau",PhD,12,Finance,2024-01-07,2024-02-22,911,7.8,Autonomous Tech +AI02938,Machine Learning Researcher,56802,USD,56802,EN,CT,South Korea,M,France,0,"Python, Scala, Statistics, Spark, Docker",Bachelor,1,Gaming,2024-11-17,2025-01-20,1044,8,TechCorp Inc +AI02939,Data Engineer,128940,EUR,109599,SE,CT,Germany,L,Germany,50,"SQL, PyTorch, Mathematics, Azure",Associate,5,Retail,2024-01-22,2024-03-12,2032,6.5,DataVision Ltd +AI02940,NLP Engineer,142396,USD,142396,SE,FL,Ireland,L,Philippines,100,"Tableau, Python, R, Docker",Master,6,Automotive,2024-05-14,2024-07-01,1925,8.3,Cloud AI Solutions +AI02941,Robotics Engineer,47879,USD,47879,SE,PT,China,S,China,100,"TensorFlow, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-09-18,1035,9.3,TechCorp Inc +AI02942,Data Analyst,129487,SGD,168333,SE,FL,Singapore,M,Singapore,0,"Linux, PyTorch, Data Visualization, Kubernetes",Associate,7,Telecommunications,2024-07-20,2024-09-01,803,6,Advanced Robotics +AI02943,Head of AI,272031,EUR,231226,EX,FL,France,L,France,0,"PyTorch, TensorFlow, Data Visualization",PhD,12,Healthcare,2024-05-15,2024-07-08,666,9.6,DataVision Ltd +AI02944,Data Analyst,125924,GBP,94443,SE,PT,United Kingdom,L,Australia,0,"Linux, Statistics, Git",Bachelor,6,Technology,2025-02-07,2025-03-09,780,6.9,Advanced Robotics +AI02945,Principal Data Scientist,24104,USD,24104,EN,FT,India,S,India,50,"Python, TensorFlow, Tableau, PyTorch",Associate,0,Media,2025-04-01,2025-05-31,860,5.2,Smart Analytics +AI02946,Principal Data Scientist,69920,EUR,59432,EN,FT,Germany,M,Germany,0,"SQL, Scala, Git, GCP",Bachelor,1,Telecommunications,2024-09-13,2024-10-25,2048,5.8,Neural Networks Co +AI02947,Data Scientist,99241,EUR,84355,SE,FT,Austria,S,Austria,50,"Kubernetes, Git, Mathematics",Bachelor,5,Manufacturing,2024-06-13,2024-08-06,803,9.8,Predictive Systems +AI02948,Principal Data Scientist,80687,CHF,72618,EN,CT,Switzerland,S,Switzerland,50,"AWS, NLP, Python, Mathematics, Scala",PhD,1,Automotive,2024-06-26,2024-07-26,1786,7.7,Algorithmic Solutions +AI02949,Deep Learning Engineer,45985,USD,45985,MI,FT,China,L,China,50,"Deep Learning, Python, Docker",PhD,2,Transportation,2024-04-28,2024-07-05,1598,8.6,TechCorp Inc +AI02950,NLP Engineer,71121,USD,71121,MI,PT,South Korea,M,Mexico,50,"Tableau, Deep Learning, TensorFlow, Python, Java",Associate,4,Technology,2024-08-20,2024-09-06,905,8.6,Algorithmic Solutions +AI02951,Principal Data Scientist,214331,USD,214331,EX,FL,Finland,L,Finland,50,"GCP, Python, TensorFlow, Docker, Statistics",Bachelor,10,Transportation,2024-03-02,2024-03-23,1877,8.9,Algorithmic Solutions +AI02952,NLP Engineer,179501,EUR,152576,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, Git, AWS, R, Java",Bachelor,9,Consulting,2024-04-13,2024-05-12,1341,8.5,DeepTech Ventures +AI02953,AI Specialist,213182,USD,213182,EX,FL,Denmark,L,United Kingdom,0,"Hadoop, R, GCP, Deep Learning",Bachelor,15,Real Estate,2024-10-26,2024-12-30,2424,9.3,Smart Analytics +AI02954,Data Analyst,257116,USD,257116,EX,CT,United States,M,Ghana,50,"NLP, R, SQL",PhD,16,Healthcare,2024-09-18,2024-10-19,2162,6.3,Autonomous Tech +AI02955,Principal Data Scientist,210838,EUR,179212,EX,FT,France,S,France,50,"SQL, Azure, Git",Associate,13,Government,2024-07-18,2024-09-26,723,8.1,DeepTech Ventures +AI02956,ML Ops Engineer,161032,USD,161032,SE,PT,Norway,S,Norway,0,"SQL, R, Java, AWS",Associate,5,Telecommunications,2024-01-14,2024-02-08,1827,7.6,Autonomous Tech +AI02957,Data Engineer,97860,EUR,83181,MI,FL,Austria,L,Chile,50,"PyTorch, Computer Vision, R",Bachelor,4,Healthcare,2024-09-19,2024-10-07,2445,6.1,Algorithmic Solutions +AI02958,Machine Learning Researcher,76742,GBP,57557,EN,FT,United Kingdom,S,United Kingdom,0,"GCP, Python, TensorFlow, NLP, Computer Vision",PhD,1,Energy,2024-10-26,2024-12-03,2112,5.1,Autonomous Tech +AI02959,AI Architect,124869,USD,124869,EX,CT,Sweden,S,Czech Republic,0,"Mathematics, Hadoop, GCP, Azure",Bachelor,19,Telecommunications,2024-04-11,2024-05-18,718,7.8,Smart Analytics +AI02960,Data Analyst,158246,USD,158246,SE,FT,Norway,L,South Korea,50,"Tableau, Spark, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-08-28,2024-09-28,939,9.5,TechCorp Inc +AI02961,Data Engineer,277909,USD,277909,EX,CT,Sweden,L,Sweden,0,"Python, Hadoop, Scala, TensorFlow",Master,16,Technology,2025-04-06,2025-06-06,1601,6.7,Neural Networks Co +AI02962,Principal Data Scientist,58343,EUR,49592,EN,FT,Germany,S,Germany,50,"SQL, Spark, Data Visualization",Bachelor,0,Education,2024-10-23,2024-12-01,535,6.5,Neural Networks Co +AI02963,AI Product Manager,98072,USD,98072,MI,PT,Sweden,L,Sweden,0,"TensorFlow, R, Statistics",Associate,4,Energy,2024-03-26,2024-05-19,710,7.8,Predictive Systems +AI02964,ML Ops Engineer,58209,USD,58209,SE,CT,India,L,India,50,"Kubernetes, Python, Spark",Bachelor,6,Government,2024-03-10,2024-05-15,621,7.8,Advanced Robotics +AI02965,Principal Data Scientist,101880,EUR,86598,SE,PT,Germany,S,Czech Republic,50,"Spark, Azure, Docker",PhD,7,Retail,2025-02-04,2025-04-03,1759,8.1,Cloud AI Solutions +AI02966,AI Architect,119812,USD,119812,MI,FL,United States,M,Italy,0,"Deep Learning, Git, Data Visualization, Statistics",Bachelor,4,Manufacturing,2024-02-02,2024-02-17,1503,7.7,TechCorp Inc +AI02967,Research Scientist,184524,USD,184524,EX,FL,Finland,S,Finland,100,"SQL, PyTorch, Deep Learning",Bachelor,12,Manufacturing,2024-10-15,2024-10-30,619,9.1,Smart Analytics +AI02968,AI Architect,212494,EUR,180620,EX,CT,Austria,M,Austria,50,"Spark, Mathematics, Java",Bachelor,19,Automotive,2024-01-03,2024-02-15,1929,6,Digital Transformation LLC +AI02969,NLP Engineer,83942,EUR,71351,MI,CT,Netherlands,S,Israel,0,"Linux, SQL, AWS",Bachelor,3,Finance,2025-04-05,2025-05-10,678,9.8,Machine Intelligence Group +AI02970,ML Ops Engineer,92507,GBP,69380,MI,PT,United Kingdom,L,Canada,100,"Git, Data Visualization, AWS, SQL",Master,3,Government,2025-04-01,2025-06-06,2111,7.5,Future Systems +AI02971,Machine Learning Researcher,71494,EUR,60770,MI,PT,France,M,South Africa,50,"R, Kubernetes, AWS, Python, Computer Vision",PhD,4,Education,2025-04-19,2025-05-31,738,8.3,Smart Analytics +AI02972,AI Product Manager,89952,AUD,121435,MI,FT,Australia,S,Australia,50,"Linux, Spark, Deep Learning",Master,2,Government,2024-07-18,2024-08-06,2280,8.2,Digital Transformation LLC +AI02973,AI Product Manager,74909,USD,74909,EX,CT,India,L,Argentina,100,"Statistics, Kubernetes, Git, GCP, Python",Master,17,Media,2024-02-28,2024-03-14,618,9.2,Algorithmic Solutions +AI02974,Data Scientist,121133,AUD,163530,SE,PT,Australia,M,Australia,100,"Python, Kubernetes, MLOps, Azure",Master,6,Manufacturing,2025-01-01,2025-03-13,1194,8.2,Autonomous Tech +AI02975,Head of AI,106190,SGD,138047,MI,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, Tableau",Bachelor,3,Finance,2024-03-05,2024-05-17,1987,7.2,AI Innovations +AI02976,AI Software Engineer,261845,EUR,222568,EX,FL,Netherlands,M,Netherlands,50,"Python, GCP, Hadoop",PhD,19,Automotive,2024-06-14,2024-08-05,1868,5.7,Quantum Computing Inc +AI02977,Robotics Engineer,104354,EUR,88701,MI,CT,Austria,L,Switzerland,100,"Java, Linux, TensorFlow, Hadoop",Associate,4,Transportation,2025-04-06,2025-04-23,611,9,TechCorp Inc +AI02978,AI Architect,86549,USD,86549,EN,FT,Sweden,L,Sweden,100,"Azure, PyTorch, Data Visualization, Kubernetes",Associate,1,Education,2025-01-27,2025-03-07,1075,6.2,DataVision Ltd +AI02979,ML Ops Engineer,170055,USD,170055,SE,FT,Sweden,L,Netherlands,100,"AWS, Linux, Scala, MLOps, Mathematics",Associate,6,Energy,2024-02-12,2024-03-31,2029,5.2,Machine Intelligence Group +AI02980,Computer Vision Engineer,92633,USD,92633,SE,FT,Israel,S,Israel,0,"Spark, Docker, Data Visualization, PyTorch",PhD,9,Real Estate,2024-05-08,2024-06-16,1790,7,DataVision Ltd +AI02981,Deep Learning Engineer,108025,EUR,91821,SE,FL,France,S,Vietnam,100,"Docker, Java, Linux, Statistics, Computer Vision",Bachelor,5,Manufacturing,2024-08-27,2024-10-11,856,8,Algorithmic Solutions +AI02982,NLP Engineer,231357,EUR,196653,EX,FT,France,L,France,100,"TensorFlow, Data Visualization, SQL, Scala",Master,10,Real Estate,2025-02-05,2025-03-18,771,7.4,Autonomous Tech +AI02983,AI Consultant,75714,AUD,102214,MI,PT,Australia,M,Australia,0,"Git, SQL, Computer Vision, Hadoop, Java",Associate,3,Real Estate,2025-04-25,2025-05-18,895,7.1,Neural Networks Co +AI02984,Machine Learning Researcher,48731,EUR,41421,EN,CT,Austria,S,Austria,100,"R, Hadoop, Docker, Computer Vision, Python",PhD,0,Real Estate,2024-10-05,2024-12-15,1480,9.2,Future Systems +AI02985,AI Architect,63620,EUR,54077,EN,FL,Austria,L,Austria,100,"Linux, Spark, NLP, Kubernetes",Master,1,Energy,2024-05-01,2024-06-14,1567,7.5,DataVision Ltd +AI02986,Deep Learning Engineer,146711,USD,146711,SE,FL,United States,S,United States,50,"R, NLP, Kubernetes",Bachelor,8,Retail,2024-04-09,2024-06-02,1302,6.2,Cloud AI Solutions +AI02987,Autonomous Systems Engineer,217093,USD,217093,EX,PT,Finland,M,Finland,0,"Scala, PyTorch, GCP",Associate,15,Government,2024-01-01,2024-03-13,1010,9.5,Predictive Systems +AI02988,Computer Vision Engineer,158838,EUR,135012,SE,FL,Netherlands,L,South Africa,100,"Hadoop, Python, R",Master,7,Media,2024-11-21,2025-01-20,814,6.7,Cloud AI Solutions +AI02989,Machine Learning Engineer,26471,USD,26471,MI,CT,India,S,India,50,"Tableau, Git, Python, Computer Vision",Master,3,Healthcare,2025-04-15,2025-05-24,2355,8.1,Machine Intelligence Group +AI02990,Principal Data Scientist,52315,EUR,44468,EN,FT,Germany,M,Germany,100,"AWS, Python, Tableau",Master,0,Technology,2024-01-02,2024-02-21,1188,9.6,Quantum Computing Inc +AI02991,Research Scientist,155395,USD,155395,SE,PT,Finland,L,Finland,100,"Git, NLP, Scala",Bachelor,7,Consulting,2024-07-05,2024-08-06,1078,6.3,Smart Analytics +AI02992,Deep Learning Engineer,103774,USD,103774,SE,CT,Sweden,M,Sweden,100,"Python, Java, TensorFlow",PhD,5,Manufacturing,2024-02-14,2024-03-18,738,8.7,Machine Intelligence Group +AI02993,AI Specialist,116286,USD,116286,SE,CT,Finland,M,Czech Republic,0,"AWS, Java, Statistics, Mathematics",Associate,7,Media,2025-04-27,2025-06-01,1491,6.7,Cognitive Computing +AI02994,ML Ops Engineer,75877,USD,75877,EN,CT,United States,S,United States,50,"NLP, Python, SQL, Git",Master,0,Healthcare,2025-01-11,2025-02-22,751,9.7,Future Systems +AI02995,Data Analyst,73643,AUD,99418,MI,FT,Australia,S,Indonesia,0,"Azure, Spark, MLOps",Bachelor,2,Consulting,2024-07-04,2024-07-27,1225,9.9,Advanced Robotics +AI02996,AI Specialist,252203,CHF,226983,EX,FL,Switzerland,L,Switzerland,50,"Hadoop, PyTorch, Java, Computer Vision, Mathematics",Bachelor,13,Automotive,2025-04-18,2025-06-12,1635,7.6,Predictive Systems +AI02997,AI Specialist,82912,USD,82912,MI,FT,Israel,M,Indonesia,0,"R, Tableau, Linux",Bachelor,4,Energy,2024-08-03,2024-08-25,2064,7.6,Advanced Robotics +AI02998,AI Specialist,152624,USD,152624,SE,FL,Ireland,L,Ireland,100,"R, Python, Git, GCP, Linux",Master,9,Retail,2024-11-28,2025-01-15,1068,5.4,Future Systems +AI02999,AI Architect,87630,USD,87630,MI,FT,South Korea,L,South Korea,100,"AWS, Linux, Deep Learning, R",Associate,2,Manufacturing,2024-05-01,2024-06-16,945,8.8,Cognitive Computing +AI03000,AI Research Scientist,234953,SGD,305439,EX,FL,Singapore,S,Singapore,50,"Linux, R, TensorFlow, Git, Tableau",PhD,12,Consulting,2024-04-14,2024-05-18,930,9,AI Innovations +AI03001,AI Research Scientist,121264,SGD,157643,SE,FL,Singapore,S,Singapore,0,"Spark, Kubernetes, GCP, TensorFlow",Master,7,Government,2024-01-14,2024-03-21,1534,9.8,Digital Transformation LLC +AI03002,Machine Learning Researcher,158964,USD,158964,MI,PT,Denmark,L,Denmark,0,"Scala, SQL, Java, Docker, PyTorch",Master,4,Education,2024-06-25,2024-07-10,638,7.6,Cloud AI Solutions +AI03003,Computer Vision Engineer,73586,JPY,8094460,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, Docker, Data Visualization",Bachelor,1,Retail,2024-11-26,2025-01-15,1557,7,DeepTech Ventures +AI03004,Machine Learning Engineer,230512,GBP,172884,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Kubernetes, Python",Master,13,Telecommunications,2024-05-26,2024-06-24,827,7,Advanced Robotics +AI03005,Autonomous Systems Engineer,125009,CAD,156261,SE,CT,Canada,S,Czech Republic,50,"Kubernetes, Computer Vision, SQL",PhD,7,Telecommunications,2025-01-28,2025-03-31,1710,5.3,Advanced Robotics +AI03006,AI Architect,262701,USD,262701,EX,PT,Sweden,L,Belgium,50,"Python, AWS, TensorFlow",Bachelor,19,Gaming,2024-12-02,2025-01-07,1868,9.6,Autonomous Tech +AI03007,ML Ops Engineer,266606,USD,266606,EX,CT,Denmark,S,Denmark,50,"Hadoop, Python, Tableau, Deep Learning",PhD,18,Automotive,2025-02-02,2025-03-30,1674,8.3,Smart Analytics +AI03008,NLP Engineer,140178,SGD,182231,SE,FT,Singapore,S,Singapore,100,"Tableau, Deep Learning, Hadoop, MLOps",Bachelor,5,Retail,2025-04-15,2025-06-20,2368,5.3,Future Systems +AI03009,NLP Engineer,187857,CAD,234821,EX,FL,Canada,L,Canada,0,"Deep Learning, Spark, Data Visualization, SQL, Kubernetes",Bachelor,18,Consulting,2024-07-21,2024-09-28,1818,5.9,Cognitive Computing +AI03010,Data Analyst,42710,USD,42710,MI,FT,China,M,Spain,100,"Java, R, Hadoop, Linux",PhD,2,Finance,2024-11-30,2025-01-16,691,9.8,Digital Transformation LLC +AI03011,Data Scientist,84841,EUR,72115,MI,PT,Netherlands,M,Netherlands,50,"Java, R, Tableau, SQL, Scala",Bachelor,4,Transportation,2024-03-02,2024-04-23,2405,7.6,Advanced Robotics +AI03012,AI Consultant,74980,EUR,63733,MI,CT,Austria,S,Austria,0,"SQL, PyTorch, R, Hadoop, Python",Bachelor,3,Telecommunications,2024-06-25,2024-08-19,1005,8.3,TechCorp Inc +AI03013,AI Consultant,84006,EUR,71405,MI,CT,France,M,Brazil,0,"Deep Learning, SQL, Mathematics",Master,3,Real Estate,2024-06-20,2024-08-04,1656,6.9,Digital Transformation LLC +AI03014,AI Consultant,174420,EUR,148257,EX,CT,France,S,Romania,100,"Kubernetes, Scala, Java, Spark",PhD,19,Education,2024-01-16,2024-03-23,1377,9.3,Future Systems +AI03015,Computer Vision Engineer,243382,USD,243382,EX,PT,Sweden,M,Sweden,50,"Linux, Kubernetes, Git, Docker, Python",Associate,19,Gaming,2024-04-22,2024-06-10,1260,8.7,Advanced Robotics +AI03016,AI Consultant,72001,EUR,61201,MI,PT,Austria,S,Austria,0,"Java, Hadoop, Scala, GCP",PhD,4,Government,2024-04-01,2024-05-16,698,9.4,Cloud AI Solutions +AI03017,AI Architect,349094,USD,349094,EX,PT,Denmark,L,Denmark,100,"PyTorch, Scala, NLP, Computer Vision",Bachelor,13,Healthcare,2024-03-04,2024-05-09,2490,8.9,Cloud AI Solutions +AI03018,Machine Learning Engineer,135760,USD,135760,SE,FT,Norway,S,Norway,50,"Azure, Linux, Docker, SQL",Bachelor,5,Consulting,2024-08-28,2024-09-30,1383,7.4,Quantum Computing Inc +AI03019,AI Research Scientist,127359,EUR,108255,SE,CT,France,L,France,50,"Computer Vision, Java, SQL",Master,9,Telecommunications,2024-06-19,2024-08-08,1050,5.7,Smart Analytics +AI03020,Data Engineer,97760,SGD,127088,SE,PT,Singapore,S,Ireland,0,"TensorFlow, GCP, Tableau, Computer Vision",PhD,6,Technology,2024-03-09,2024-04-17,2013,6.9,Machine Intelligence Group +AI03021,AI Software Engineer,217718,JPY,23948980,EX,FT,Japan,M,Japan,100,"MLOps, R, Computer Vision, Scala",Associate,13,Telecommunications,2024-08-08,2024-10-13,1785,9.8,Smart Analytics +AI03022,Deep Learning Engineer,129149,CAD,161436,SE,CT,Canada,S,Canada,100,"R, Kubernetes, Mathematics",Associate,5,Gaming,2025-04-18,2025-06-30,650,6.7,AI Innovations +AI03023,Data Analyst,66925,USD,66925,EN,PT,Ireland,S,Ireland,50,"SQL, Java, PyTorch, Git, Spark",Master,1,Technology,2024-05-26,2024-06-10,783,5.4,Digital Transformation LLC +AI03024,Data Engineer,87198,EUR,74118,MI,PT,Germany,S,Germany,50,"Git, R, Kubernetes, Spark",Bachelor,2,Gaming,2024-12-18,2025-01-25,1440,9.8,Autonomous Tech +AI03025,AI Software Engineer,94601,USD,94601,EN,PT,United States,L,United States,0,"AWS, Java, Deep Learning, Python, TensorFlow",PhD,0,Telecommunications,2025-01-20,2025-03-30,874,9.3,Neural Networks Co +AI03026,Principal Data Scientist,51043,USD,51043,EN,PT,South Korea,M,South Korea,100,"Data Visualization, AWS, TensorFlow, SQL, NLP",Associate,0,Gaming,2024-07-21,2024-08-30,1749,5.9,Smart Analytics +AI03027,Autonomous Systems Engineer,88860,EUR,75531,MI,CT,France,L,France,50,"Hadoop, Computer Vision, Mathematics, MLOps",Bachelor,3,Retail,2024-09-27,2024-12-08,1581,10,Machine Intelligence Group +AI03028,AI Specialist,91219,USD,91219,MI,FT,Sweden,S,Sweden,50,"GCP, Java, SQL, Deep Learning",PhD,4,Transportation,2025-04-16,2025-06-01,1553,5.8,Autonomous Tech +AI03029,AI Product Manager,23010,USD,23010,MI,FL,India,S,India,100,"Python, Computer Vision, Java",Master,4,Gaming,2024-08-24,2024-11-02,1484,7.7,Predictive Systems +AI03030,Autonomous Systems Engineer,84775,USD,84775,MI,PT,Finland,L,Finland,100,"PyTorch, SQL, Computer Vision",PhD,4,Consulting,2024-11-23,2024-12-08,1320,5.7,Neural Networks Co +AI03031,Machine Learning Researcher,182231,USD,182231,EX,FT,Norway,M,Norway,100,"Tableau, Computer Vision, NLP, Python, MLOps",PhD,11,Government,2024-02-16,2024-03-29,2292,8.2,Autonomous Tech +AI03032,Data Engineer,76682,USD,76682,EX,FT,India,M,India,0,"PyTorch, AWS, Data Visualization, Deep Learning",PhD,12,Finance,2025-04-25,2025-06-15,552,8.7,Neural Networks Co +AI03033,NLP Engineer,103728,EUR,88169,SE,CT,Austria,S,Austria,100,"R, Spark, TensorFlow",Master,8,Gaming,2024-05-01,2024-06-01,700,9.8,Digital Transformation LLC +AI03034,Machine Learning Engineer,108739,CHF,97865,EN,FT,Switzerland,L,Switzerland,0,"Scala, Linux, Computer Vision, Java",Associate,0,Telecommunications,2024-04-23,2024-06-11,829,6.3,Neural Networks Co +AI03035,AI Architect,127790,USD,127790,SE,PT,Israel,L,Israel,50,"GCP, R, Tableau",Master,8,Finance,2024-06-07,2024-07-18,880,6.2,Cloud AI Solutions +AI03036,Deep Learning Engineer,113774,USD,113774,MI,CT,United States,L,Belgium,50,"Data Visualization, R, Java, Tableau",Associate,3,Automotive,2024-04-28,2024-05-27,529,9.4,Algorithmic Solutions +AI03037,Research Scientist,119989,USD,119989,EN,FL,Denmark,L,Denmark,100,"Data Visualization, Linux, Tableau",Associate,1,Telecommunications,2024-07-15,2024-08-25,1170,6.1,Advanced Robotics +AI03038,Machine Learning Engineer,75024,USD,75024,MI,PT,Israel,S,Netherlands,100,"Tableau, Azure, AWS, SQL",Associate,4,Government,2025-04-13,2025-05-22,1521,9.3,Advanced Robotics +AI03039,Research Scientist,67687,USD,67687,EN,CT,Ireland,M,Indonesia,0,"R, Deep Learning, SQL, Data Visualization, Kubernetes",PhD,1,Media,2024-08-12,2024-10-08,508,5.4,AI Innovations +AI03040,Data Scientist,82087,USD,82087,MI,FL,United States,S,United States,100,"MLOps, Hadoop, Java, Spark, Tableau",PhD,4,Media,2024-10-11,2024-11-07,1535,6.8,AI Innovations +AI03041,Computer Vision Engineer,240800,USD,240800,EX,FL,Sweden,M,Sweden,50,"Kubernetes, Deep Learning, SQL, PyTorch",Bachelor,15,Consulting,2024-08-27,2024-09-11,2073,8,TechCorp Inc +AI03042,Principal Data Scientist,76214,EUR,64782,MI,PT,Germany,S,Germany,0,"Python, R, SQL, Kubernetes, Mathematics",PhD,3,Media,2025-02-26,2025-04-14,1646,6.7,Autonomous Tech +AI03043,AI Consultant,259438,CHF,233494,EX,PT,Switzerland,L,Switzerland,0,"Git, Scala, Hadoop, SQL",Bachelor,13,Energy,2024-01-19,2024-02-03,2304,5.3,Predictive Systems +AI03044,Data Engineer,245492,USD,245492,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Deep Learning, Mathematics, AWS",Master,17,Manufacturing,2024-07-24,2024-09-30,2187,8.1,Autonomous Tech +AI03045,ML Ops Engineer,102823,CAD,128529,MI,FL,Canada,M,Canada,100,"Linux, R, TensorFlow, Deep Learning, Data Visualization",Master,3,Manufacturing,2025-04-04,2025-04-24,1976,9.7,Digital Transformation LLC +AI03046,Deep Learning Engineer,283410,USD,283410,EX,FT,Ireland,L,Ireland,50,"Docker, Statistics, Deep Learning, R, SQL",Bachelor,18,Telecommunications,2024-01-27,2024-03-15,1313,7.1,Machine Intelligence Group +AI03047,Machine Learning Engineer,208241,USD,208241,EX,FT,Ireland,M,Kenya,50,"Kubernetes, Azure, Data Visualization",Bachelor,18,Automotive,2024-08-18,2024-10-22,2371,8.9,TechCorp Inc +AI03048,ML Ops Engineer,105274,GBP,78956,MI,PT,United Kingdom,S,Brazil,100,"Java, Git, R, Linux, SQL",PhD,3,Government,2025-01-08,2025-02-16,936,7.4,Neural Networks Co +AI03049,Principal Data Scientist,94841,USD,94841,MI,FL,Israel,L,Israel,0,"SQL, Java, Linux, NLP, Tableau",Bachelor,3,Media,2024-09-17,2024-11-12,651,6.1,Future Systems +AI03050,Autonomous Systems Engineer,114463,EUR,97294,MI,FT,Austria,L,Austria,50,"Python, Hadoop, SQL, Docker",Master,2,Consulting,2024-07-28,2024-09-23,2088,6.8,AI Innovations +AI03051,Data Engineer,158187,USD,158187,SE,PT,Denmark,S,Denmark,100,"SQL, R, Data Visualization, Docker",Bachelor,5,Telecommunications,2024-03-20,2024-05-21,835,6,Future Systems +AI03052,Principal Data Scientist,45177,USD,45177,EN,PT,South Korea,S,South Korea,50,"R, Linux, Python, Tableau, Mathematics",PhD,1,Education,2024-01-23,2024-02-06,1425,5.5,Smart Analytics +AI03053,Head of AI,147403,EUR,125293,SE,PT,Germany,L,Germany,50,"Kubernetes, Hadoop, NLP, Statistics, Python",Associate,8,Automotive,2024-04-26,2024-05-31,1232,8.4,Predictive Systems +AI03054,Deep Learning Engineer,103578,USD,103578,SE,FL,Ireland,S,Ireland,50,"TensorFlow, Linux, PyTorch, Tableau",PhD,5,Transportation,2024-10-16,2024-12-06,2330,8.9,Quantum Computing Inc +AI03055,Deep Learning Engineer,90139,AUD,121688,MI,FL,Australia,L,Australia,100,"R, Mathematics, Data Visualization, Linux, Kubernetes",Master,4,Telecommunications,2025-01-10,2025-02-08,1856,7.4,DataVision Ltd +AI03056,AI Product Manager,140051,EUR,119043,SE,FT,France,L,France,100,"Scala, Git, Statistics, Computer Vision, Python",Master,5,Automotive,2024-01-13,2024-03-02,1252,7.4,Quantum Computing Inc +AI03057,Head of AI,55899,USD,55899,EN,FT,Israel,M,Israel,50,"Tableau, Azure, Hadoop",Bachelor,0,Education,2024-06-01,2024-07-03,1765,8.2,Future Systems +AI03058,Machine Learning Engineer,228939,EUR,194598,EX,CT,Germany,M,Mexico,50,"NLP, AWS, Git, GCP, Mathematics",PhD,14,Transportation,2024-09-10,2024-10-20,2130,8.5,Neural Networks Co +AI03059,Computer Vision Engineer,169575,CHF,152618,SE,PT,Switzerland,S,Switzerland,50,"Tableau, Git, Computer Vision, Python, Statistics",Associate,8,Energy,2025-04-09,2025-06-16,1773,5.1,Autonomous Tech +AI03060,AI Specialist,92434,GBP,69326,EN,CT,United Kingdom,L,Vietnam,0,"Data Visualization, Spark, Computer Vision, SQL, PyTorch",Bachelor,0,Gaming,2024-10-27,2024-12-11,1856,7.4,TechCorp Inc +AI03061,NLP Engineer,45214,CAD,56518,EN,CT,Canada,S,Canada,100,"GCP, Computer Vision, Python, R, TensorFlow",PhD,1,Finance,2024-01-25,2024-03-23,2385,7.6,DeepTech Ventures +AI03062,Principal Data Scientist,125545,AUD,169486,MI,FT,Australia,L,Thailand,50,"Python, Git, TensorFlow, NLP",Associate,4,Technology,2024-09-14,2024-10-20,868,8.1,Future Systems +AI03063,AI Research Scientist,63222,USD,63222,EX,FT,India,M,India,100,"MLOps, TensorFlow, Tableau, Linux",PhD,15,Government,2024-03-21,2024-05-29,1313,5.4,Neural Networks Co +AI03064,Deep Learning Engineer,90458,USD,90458,MI,PT,Finland,L,Finland,0,"SQL, Python, NLP, Statistics",Master,2,Transportation,2024-10-26,2024-12-04,834,9.1,DataVision Ltd +AI03065,Data Analyst,53532,USD,53532,EN,PT,Sweden,S,Brazil,0,"Kubernetes, Statistics, Tableau, Mathematics, Java",Bachelor,1,Energy,2025-03-04,2025-04-17,1479,8.4,Algorithmic Solutions +AI03066,Computer Vision Engineer,111068,USD,111068,MI,FL,Norway,M,United States,100,"Data Visualization, Python, TensorFlow, Docker",Master,4,Telecommunications,2025-03-23,2025-04-24,618,8.8,Future Systems +AI03067,AI Research Scientist,51281,CAD,64101,EN,FT,Canada,M,Ireland,50,"SQL, Kubernetes, Scala, Mathematics",Master,0,Government,2025-01-25,2025-02-20,1572,6.7,Neural Networks Co +AI03068,Robotics Engineer,70333,USD,70333,EX,CT,India,S,India,100,"Tableau, Data Visualization, SQL, PyTorch",Bachelor,12,Finance,2024-05-13,2024-06-24,1694,7.8,Neural Networks Co +AI03069,Data Scientist,113289,USD,113289,MI,PT,Norway,M,Italy,50,"Python, Java, Hadoop, AWS, Kubernetes",Bachelor,4,Gaming,2024-09-17,2024-11-26,1355,7.9,Algorithmic Solutions +AI03070,Deep Learning Engineer,76340,USD,76340,EN,FT,Israel,L,Israel,100,"AWS, SQL, Python",Master,0,Retail,2024-07-29,2024-09-19,1293,8,Predictive Systems +AI03071,Deep Learning Engineer,83602,USD,83602,MI,CT,Finland,M,Finland,100,"Data Visualization, R, NLP, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-15,884,5.7,Quantum Computing Inc +AI03072,Machine Learning Researcher,140958,AUD,190293,EX,CT,Australia,M,Thailand,0,"Docker, Hadoop, Mathematics, Kubernetes",Master,15,Consulting,2024-05-31,2024-07-29,1825,7.2,DeepTech Ventures +AI03073,Machine Learning Engineer,224243,USD,224243,EX,FL,United States,L,United States,50,"Java, R, SQL, Data Visualization, Linux",PhD,17,Media,2024-06-25,2024-08-19,1126,7.2,Predictive Systems +AI03074,AI Product Manager,182443,USD,182443,EX,PT,Sweden,L,Sweden,50,"Computer Vision, Python, Tableau, Data Visualization",Bachelor,15,Technology,2024-10-26,2024-12-02,2303,6.3,Autonomous Tech +AI03075,Principal Data Scientist,116360,AUD,157086,SE,CT,Australia,S,Australia,0,"Mathematics, Kubernetes, Data Visualization, GCP, PyTorch",Master,9,Technology,2024-02-03,2024-03-03,1533,6.7,DeepTech Ventures +AI03076,Machine Learning Engineer,59186,SGD,76942,EN,CT,Singapore,S,Singapore,0,"Java, R, Computer Vision, Tableau, Statistics",Master,1,Government,2025-04-16,2025-06-27,1282,6.6,Digital Transformation LLC +AI03077,AI Product Manager,230221,CAD,287776,EX,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Python",Master,11,Manufacturing,2024-02-06,2024-04-07,883,7.7,Cognitive Computing +AI03078,AI Specialist,249223,EUR,211840,EX,FL,Germany,L,Chile,50,"Scala, TensorFlow, SQL, Kubernetes",Master,14,Retail,2025-04-13,2025-05-23,1427,6.4,Cognitive Computing +AI03079,Principal Data Scientist,170776,USD,170776,SE,CT,United States,M,United States,0,"Java, Data Visualization, R, Scala",Master,5,Gaming,2025-01-16,2025-02-03,1122,8.8,DeepTech Ventures +AI03080,Computer Vision Engineer,76117,EUR,64699,EN,FL,Germany,M,Estonia,0,"R, Git, Hadoop",Master,1,Consulting,2024-01-03,2024-02-07,1271,9.4,Algorithmic Solutions +AI03081,AI Research Scientist,65226,AUD,88055,EN,FT,Australia,L,Australia,0,"Kubernetes, PyTorch, Azure, SQL",PhD,0,Finance,2024-10-26,2024-11-28,684,5.5,Machine Intelligence Group +AI03082,Computer Vision Engineer,63087,EUR,53624,EN,PT,Austria,M,Austria,0,"Git, Azure, Statistics, GCP",Associate,1,Telecommunications,2024-12-19,2025-01-26,2458,8.8,Cloud AI Solutions +AI03083,Machine Learning Engineer,44772,USD,44772,MI,FL,China,M,China,50,"R, Java, Data Visualization",Master,4,Transportation,2024-01-01,2024-01-24,1106,9.3,Algorithmic Solutions +AI03084,Data Scientist,204283,AUD,275782,EX,FT,Australia,S,Brazil,100,"Python, Scala, Kubernetes, Docker",Associate,12,Retail,2024-04-21,2024-06-19,1045,8.5,Advanced Robotics +AI03085,Machine Learning Engineer,114299,USD,114299,SE,PT,Ireland,M,Portugal,100,"GCP, Java, MLOps",Bachelor,8,Transportation,2024-10-26,2024-11-22,1175,6.8,Future Systems +AI03086,AI Consultant,298889,USD,298889,EX,FT,Norway,L,Norway,50,"GCP, Statistics, Git, Hadoop",Associate,16,Consulting,2024-02-29,2024-04-06,1175,6.8,Cloud AI Solutions +AI03087,AI Specialist,71400,JPY,7854000,EN,FT,Japan,S,Japan,50,"Azure, Docker, MLOps",Bachelor,0,Manufacturing,2024-02-13,2024-03-13,2014,8.1,TechCorp Inc +AI03088,Research Scientist,69118,USD,69118,EN,FL,United States,S,United States,100,"Spark, TensorFlow, Git, Docker, Java",Associate,0,Telecommunications,2024-12-12,2025-02-16,739,6,DeepTech Ventures +AI03089,Robotics Engineer,47701,USD,47701,MI,PT,China,M,China,0,"Git, Linux, Mathematics, Kubernetes, Spark",Master,3,Education,2024-08-02,2024-08-17,2068,9.5,Advanced Robotics +AI03090,Data Scientist,162815,USD,162815,SE,FL,Norway,L,Norway,50,"Mathematics, Docker, Statistics",Bachelor,9,Gaming,2024-12-13,2025-01-30,1879,7.3,Predictive Systems +AI03091,Deep Learning Engineer,136275,CHF,122648,MI,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Spark",Associate,3,Automotive,2024-07-11,2024-09-07,506,7.9,Future Systems +AI03092,AI Specialist,77774,CAD,97218,MI,PT,Canada,S,Canada,0,"AWS, Deep Learning, Docker",PhD,2,Retail,2025-04-16,2025-06-09,675,6.2,Neural Networks Co +AI03093,Computer Vision Engineer,151655,JPY,16682050,EX,FT,Japan,S,Japan,0,"Scala, SQL, MLOps, Azure, Kubernetes",Bachelor,17,Energy,2025-02-04,2025-02-27,1886,9.8,DataVision Ltd +AI03094,AI Specialist,147631,USD,147631,SE,FT,Finland,L,Finland,50,"Scala, Deep Learning, Java, Azure, PyTorch",PhD,5,Automotive,2024-03-18,2024-04-10,834,7.5,Digital Transformation LLC +AI03095,Robotics Engineer,44181,USD,44181,EX,CT,India,S,India,100,"GCP, Kubernetes, PyTorch",PhD,15,Transportation,2024-03-28,2024-05-15,2429,8.4,Predictive Systems +AI03096,AI Specialist,92006,EUR,78205,MI,FL,Germany,M,Germany,100,"Spark, Linux, NLP, SQL, Python",PhD,2,Real Estate,2024-10-06,2024-11-10,1434,6,DeepTech Ventures +AI03097,Data Analyst,104944,EUR,89202,MI,CT,Germany,L,Germany,0,"Python, Deep Learning, Data Visualization, R",Master,3,Education,2024-03-10,2024-04-04,1885,6.2,Predictive Systems +AI03098,ML Ops Engineer,261580,USD,261580,EX,CT,United States,M,United States,50,"Linux, Docker, Data Visualization, GCP, SQL",Bachelor,10,Transportation,2024-11-29,2024-12-31,1601,5.1,Neural Networks Co +AI03099,AI Software Engineer,32682,USD,32682,MI,FT,India,L,India,0,"GCP, Kubernetes, Azure",Master,4,Real Estate,2024-06-08,2024-07-17,1624,8.3,Algorithmic Solutions +AI03100,Research Scientist,46243,USD,46243,EN,FT,Sweden,S,Sweden,0,"Hadoop, TensorFlow, Git",Bachelor,1,Real Estate,2025-02-09,2025-04-13,1897,8.6,Quantum Computing Inc +AI03101,AI Software Engineer,51801,CAD,64751,EN,CT,Canada,S,Canada,0,"R, SQL, Linux, Kubernetes, Hadoop",PhD,1,Government,2024-03-16,2024-04-13,1014,8.8,Smart Analytics +AI03102,AI Software Engineer,110654,SGD,143850,MI,PT,Singapore,M,Singapore,0,"Hadoop, Mathematics, Kubernetes, PyTorch",Associate,4,Technology,2024-07-31,2024-09-04,1544,7.4,Cognitive Computing +AI03103,Data Scientist,123362,USD,123362,SE,CT,Israel,S,Israel,0,"Linux, AWS, MLOps, Scala, Python",PhD,8,Energy,2024-03-23,2024-05-08,1021,6.9,Future Systems +AI03104,Principal Data Scientist,66961,USD,66961,MI,FT,South Korea,M,South Korea,100,"Hadoop, Computer Vision, Java, Linux, R",PhD,3,Retail,2024-11-23,2025-01-04,960,7.7,Machine Intelligence Group +AI03105,Autonomous Systems Engineer,96935,USD,96935,MI,FL,Denmark,S,South Korea,50,"AWS, Data Visualization, MLOps",PhD,2,Education,2024-04-02,2024-05-17,597,9.4,DeepTech Ventures +AI03106,NLP Engineer,165702,JPY,18227220,EX,PT,Japan,L,Japan,50,"SQL, R, Linux, PyTorch",Master,12,Retail,2024-08-13,2024-09-01,1511,5.4,Autonomous Tech +AI03107,Computer Vision Engineer,102570,CHF,92313,MI,PT,Switzerland,M,Switzerland,0,"R, SQL, Data Visualization, Computer Vision, Java",Master,4,Healthcare,2024-11-15,2024-12-27,2061,7,Cognitive Computing +AI03108,Principal Data Scientist,31054,USD,31054,MI,CT,India,S,India,50,"Azure, Scala, Java, Mathematics",PhD,4,Government,2025-04-06,2025-05-05,716,5.4,Cognitive Computing +AI03109,AI Software Engineer,26978,USD,26978,EN,CT,China,M,China,0,"Kubernetes, Linux, Mathematics, Hadoop, Scala",Bachelor,1,Healthcare,2024-12-22,2025-01-30,2254,5.5,Neural Networks Co +AI03110,Machine Learning Engineer,45155,USD,45155,SE,FT,China,S,China,50,"Computer Vision, Tableau, Azure, Kubernetes, Spark",Master,5,Gaming,2024-04-03,2024-05-07,582,9.2,Smart Analytics +AI03111,Deep Learning Engineer,84059,USD,84059,MI,FL,United States,S,United States,50,"Linux, Docker, TensorFlow",Bachelor,4,Manufacturing,2024-06-23,2024-07-09,1520,9.1,Future Systems +AI03112,AI Product Manager,66866,USD,66866,EX,FT,India,L,India,0,"Spark, TensorFlow, SQL",Master,13,Transportation,2024-08-09,2024-09-29,2158,9.9,Cloud AI Solutions +AI03113,AI Software Engineer,56427,USD,56427,EN,CT,Ireland,M,Belgium,0,"Docker, Mathematics, PyTorch, Scala",Associate,0,Media,2024-12-19,2025-02-05,568,8.4,Autonomous Tech +AI03114,Principal Data Scientist,91432,USD,91432,MI,FL,Israel,L,Chile,50,"Git, Hadoop, Computer Vision",PhD,3,Healthcare,2024-01-09,2024-03-19,958,7.4,AI Innovations +AI03115,ML Ops Engineer,117486,EUR,99863,SE,FL,France,L,France,50,"Python, R, Computer Vision, Data Visualization, Statistics",PhD,9,Automotive,2025-02-18,2025-04-13,1430,6.9,Digital Transformation LLC +AI03116,ML Ops Engineer,85568,USD,85568,MI,CT,Finland,M,Sweden,0,"Kubernetes, Spark, Tableau, Statistics",PhD,2,Finance,2025-04-11,2025-06-17,538,9.7,Cognitive Computing +AI03117,ML Ops Engineer,308132,EUR,261912,EX,FL,Netherlands,L,India,0,"Hadoop, MLOps, Spark, Linux, R",Associate,19,Retail,2025-04-04,2025-05-24,991,7.7,Future Systems +AI03118,Head of AI,262758,SGD,341585,EX,FL,Singapore,M,Singapore,100,"Python, Computer Vision, Scala",Master,19,Transportation,2024-08-31,2024-09-22,1556,7.2,Autonomous Tech +AI03119,Principal Data Scientist,61958,USD,61958,EX,FL,India,M,Canada,50,"Java, Python, Tableau, Kubernetes, Docker",Master,12,Gaming,2024-10-23,2024-12-27,1245,8.3,Digital Transformation LLC +AI03120,Data Engineer,116493,USD,116493,SE,FL,Ireland,M,Brazil,0,"Linux, AWS, SQL, Kubernetes",PhD,8,Transportation,2024-05-30,2024-07-13,2110,5.1,TechCorp Inc +AI03121,Machine Learning Engineer,174253,SGD,226529,EX,FT,Singapore,S,Singapore,100,"Hadoop, Azure, NLP",Bachelor,14,Education,2025-04-02,2025-04-16,783,5.7,Algorithmic Solutions +AI03122,Research Scientist,133772,USD,133772,SE,PT,United States,S,United States,50,"Kubernetes, PyTorch, GCP",Bachelor,7,Media,2024-04-19,2024-05-04,1741,7.8,Smart Analytics +AI03123,Machine Learning Engineer,183867,USD,183867,EX,FT,Israel,L,Israel,0,"Scala, Computer Vision, Tableau, AWS",PhD,15,Manufacturing,2024-10-05,2024-12-08,1829,6.4,Advanced Robotics +AI03124,Data Analyst,100550,JPY,11060500,MI,FL,Japan,L,Japan,100,"Tableau, Hadoop, Azure, PyTorch, TensorFlow",Associate,3,Transportation,2025-02-28,2025-04-15,842,6.9,Digital Transformation LLC +AI03125,Data Engineer,209570,EUR,178135,EX,FT,Austria,M,Austria,100,"SQL, Python, Java",Associate,10,Telecommunications,2025-01-04,2025-03-08,1946,6.3,Cognitive Computing +AI03126,Machine Learning Researcher,27770,USD,27770,EN,CT,India,L,India,50,"Deep Learning, PyTorch, MLOps, TensorFlow",PhD,0,Manufacturing,2025-01-31,2025-03-25,695,6.1,Machine Intelligence Group +AI03127,Head of AI,239820,SGD,311766,EX,PT,Singapore,M,Singapore,100,"Java, Python, NLP",Bachelor,13,Retail,2024-04-12,2024-06-01,1250,8.2,Future Systems +AI03128,Machine Learning Researcher,90202,USD,90202,EN,FL,Ireland,L,Ireland,50,"Kubernetes, MLOps, PyTorch",PhD,0,Consulting,2025-01-15,2025-03-16,1443,8.8,DataVision Ltd +AI03129,Computer Vision Engineer,47313,EUR,40216,EN,FL,Austria,S,Austria,0,"Python, NLP, TensorFlow",Master,0,Consulting,2025-03-22,2025-05-10,1996,7.4,Predictive Systems +AI03130,Data Analyst,57899,USD,57899,EN,CT,Israel,M,Israel,100,"R, Computer Vision, GCP",Bachelor,1,Healthcare,2024-02-18,2024-04-01,1649,7.8,Machine Intelligence Group +AI03131,ML Ops Engineer,181110,GBP,135833,SE,PT,United Kingdom,L,Mexico,0,"SQL, R, Scala",Bachelor,5,Consulting,2025-04-09,2025-04-29,692,7.4,Autonomous Tech +AI03132,Principal Data Scientist,81776,USD,81776,MI,PT,South Korea,L,South Korea,0,"SQL, Java, Docker, Tableau, Computer Vision",PhD,2,Finance,2024-09-28,2024-12-08,1310,8.1,Advanced Robotics +AI03133,ML Ops Engineer,144619,GBP,108464,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, AWS, Kubernetes",PhD,12,Retail,2025-03-02,2025-05-02,1415,5.4,Digital Transformation LLC +AI03134,AI Specialist,79986,EUR,67988,MI,FL,Germany,S,Germany,50,"Hadoop, Python, MLOps, NLP",Associate,2,Automotive,2024-01-10,2024-03-17,772,6.7,Predictive Systems +AI03135,AI Architect,70655,USD,70655,EN,FT,United States,M,United States,50,"Mathematics, Linux, SQL, AWS, Tableau",Master,1,Healthcare,2024-07-30,2024-09-01,2024,5.8,Future Systems +AI03136,AI Specialist,250855,USD,250855,EX,PT,United States,S,United States,0,"Spark, Git, Data Visualization, MLOps",Master,15,Energy,2024-04-05,2024-05-01,1802,6.1,Advanced Robotics +AI03137,Machine Learning Engineer,91522,GBP,68642,MI,CT,United Kingdom,M,United Kingdom,100,"Tableau, Azure, PyTorch, SQL, Deep Learning",Bachelor,2,Technology,2024-03-27,2024-05-07,1299,7.3,Digital Transformation LLC +AI03138,Principal Data Scientist,124095,CAD,155119,SE,FL,Canada,S,Ghana,50,"SQL, Scala, GCP",Master,9,Media,2024-05-31,2024-06-28,932,8.3,Cloud AI Solutions +AI03139,Computer Vision Engineer,84282,CAD,105353,MI,FT,Canada,M,Indonesia,50,"Scala, Linux, Kubernetes, Python",PhD,2,Energy,2024-07-22,2024-09-15,1571,6.4,Digital Transformation LLC +AI03140,Data Scientist,163240,USD,163240,SE,FL,United States,M,Russia,50,"Scala, SQL, Azure",Master,5,Government,2024-09-23,2024-11-10,896,8.1,Quantum Computing Inc +AI03141,Machine Learning Researcher,168185,USD,168185,SE,CT,Ireland,L,Ireland,50,"Computer Vision, Git, Python, TensorFlow",Bachelor,7,Consulting,2024-11-08,2024-12-06,2288,7.5,DataVision Ltd +AI03142,Robotics Engineer,116627,USD,116627,MI,CT,United States,S,United States,0,"TensorFlow, NLP, Azure, Linux, Mathematics",Master,3,Education,2024-03-07,2024-05-03,1812,9.9,Machine Intelligence Group +AI03143,AI Product Manager,101270,USD,101270,MI,FT,United States,S,United States,50,"Python, Azure, Tableau",Associate,2,Healthcare,2024-01-03,2024-02-12,602,7,Digital Transformation LLC +AI03144,ML Ops Engineer,65343,USD,65343,EN,CT,Sweden,M,Sweden,100,"GCP, SQL, Tableau",Bachelor,1,Media,2025-03-06,2025-05-15,818,9.8,Predictive Systems +AI03145,Computer Vision Engineer,137416,USD,137416,SE,FT,South Korea,L,Colombia,50,"SQL, Python, MLOps",PhD,9,Telecommunications,2024-07-28,2024-09-22,1997,8.8,Machine Intelligence Group +AI03146,Robotics Engineer,295909,EUR,251523,EX,FL,Netherlands,L,Netherlands,100,"Spark, TensorFlow, Tableau, AWS, Python",Bachelor,10,Healthcare,2024-08-09,2024-08-23,1672,9.7,AI Innovations +AI03147,Autonomous Systems Engineer,143218,USD,143218,SE,FL,Ireland,M,Finland,0,"SQL, Scala, Spark, Azure",PhD,8,Technology,2024-02-15,2024-03-01,1730,9.3,Neural Networks Co +AI03148,Head of AI,190216,EUR,161684,EX,FL,Netherlands,L,Netherlands,0,"Python, MLOps, Kubernetes",Associate,18,Manufacturing,2024-04-10,2024-04-27,2389,5.4,Smart Analytics +AI03149,Data Analyst,151114,JPY,16622540,EX,FT,Japan,S,Japan,50,"Spark, Statistics, Docker, Linux, Hadoop",Master,18,Gaming,2025-04-06,2025-05-03,1213,5.7,Algorithmic Solutions +AI03150,Robotics Engineer,77870,USD,77870,EN,CT,Norway,L,Norway,50,"TensorFlow, PyTorch, AWS, Deep Learning",PhD,0,Automotive,2025-01-12,2025-03-11,2177,5.8,Smart Analytics +AI03151,Robotics Engineer,49183,JPY,5410130,EN,FL,Japan,S,Japan,50,"Tableau, Statistics, Python, NLP, Computer Vision",Master,0,Consulting,2025-02-13,2025-02-27,2439,8.5,DeepTech Ventures +AI03152,Autonomous Systems Engineer,62143,USD,62143,EN,PT,Israel,M,Ukraine,100,"Python, GCP, Deep Learning",Associate,1,Education,2025-01-24,2025-02-24,2048,5.3,Quantum Computing Inc +AI03153,AI Software Engineer,121259,AUD,163700,SE,CT,Australia,M,Belgium,0,"Statistics, Git, Deep Learning, Data Visualization, GCP",PhD,5,Real Estate,2025-02-01,2025-03-03,2113,8.3,Advanced Robotics +AI03154,AI Software Engineer,128628,JPY,14149080,SE,PT,Japan,M,Japan,50,"Statistics, Python, Kubernetes, Git, TensorFlow",Bachelor,9,Telecommunications,2024-12-01,2024-12-21,2034,7.3,Cloud AI Solutions +AI03155,Research Scientist,115473,CAD,144341,SE,CT,Canada,M,Ukraine,50,"Python, Kubernetes, Azure, Spark, TensorFlow",Associate,8,Government,2025-01-21,2025-02-25,1666,9.7,Quantum Computing Inc +AI03156,Data Engineer,238600,USD,238600,EX,FT,Israel,M,Israel,0,"PyTorch, NLP, Python, GCP",Master,11,Media,2024-01-26,2024-03-31,1708,9.6,Advanced Robotics +AI03157,AI Product Manager,113103,CHF,101793,EN,PT,Switzerland,L,Switzerland,0,"SQL, Linux, NLP, Azure, PyTorch",Bachelor,1,Real Estate,2025-01-21,2025-03-19,1928,6.4,Advanced Robotics +AI03158,Deep Learning Engineer,47429,USD,47429,SE,PT,India,S,India,50,"R, Git, SQL, Docker",Associate,7,Government,2024-04-28,2024-06-19,1964,6.3,Algorithmic Solutions +AI03159,AI Research Scientist,274181,USD,274181,EX,PT,Israel,L,Philippines,0,"Scala, AWS, SQL, MLOps",Associate,17,Technology,2025-02-18,2025-03-10,780,9.2,Neural Networks Co +AI03160,Principal Data Scientist,139553,CAD,174441,SE,FT,Canada,M,Canada,50,"Kubernetes, Java, Spark",Bachelor,6,Consulting,2024-12-13,2025-02-03,2398,8.9,Digital Transformation LLC +AI03161,AI Product Manager,83557,USD,83557,MI,CT,Finland,S,Singapore,100,"NLP, Kubernetes, Hadoop, R",PhD,3,Consulting,2024-08-25,2024-10-14,2148,5.2,Autonomous Tech +AI03162,AI Consultant,211357,AUD,285332,EX,CT,Australia,S,Turkey,0,"Scala, Git, Spark, Python",Master,15,Transportation,2024-12-16,2025-02-09,2101,8.2,Digital Transformation LLC +AI03163,ML Ops Engineer,181722,CHF,163550,SE,PT,Switzerland,M,Switzerland,100,"Azure, R, GCP",PhD,8,Real Estate,2024-02-11,2024-04-04,1248,7.2,Machine Intelligence Group +AI03164,Computer Vision Engineer,137403,CAD,171754,SE,CT,Canada,M,Indonesia,0,"TensorFlow, Mathematics, Computer Vision, Python, GCP",Bachelor,8,Finance,2024-03-17,2024-04-07,2482,5.8,Quantum Computing Inc +AI03165,Principal Data Scientist,65926,SGD,85704,EN,CT,Singapore,S,Singapore,0,"Python, MLOps, GCP, Mathematics",Master,1,Transportation,2024-10-08,2024-12-03,666,7.8,DeepTech Ventures +AI03166,Head of AI,63867,USD,63867,EN,CT,Sweden,L,Italy,100,"MLOps, Tableau, GCP, PyTorch, TensorFlow",PhD,0,Real Estate,2025-04-01,2025-05-22,1004,9.7,Advanced Robotics +AI03167,Deep Learning Engineer,73754,EUR,62691,EN,CT,Germany,L,Germany,0,"Linux, R, Data Visualization",Associate,0,Real Estate,2024-07-26,2024-08-17,1181,7.4,Predictive Systems +AI03168,Data Analyst,100588,GBP,75441,MI,CT,United Kingdom,S,United Kingdom,0,"Git, AWS, SQL",Master,4,Government,2024-02-23,2024-03-08,722,9.7,AI Innovations +AI03169,Robotics Engineer,215335,USD,215335,EX,PT,Ireland,S,Ireland,100,"NLP, SQL, Tableau",Bachelor,19,Technology,2025-03-17,2025-04-07,1676,7.2,Quantum Computing Inc +AI03170,AI Architect,96892,GBP,72669,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Linux, PyTorch",PhD,1,Real Estate,2024-07-02,2024-09-03,680,7.3,Neural Networks Co +AI03171,Head of AI,203281,USD,203281,SE,CT,Norway,L,Norway,0,"SQL, Docker, Azure",PhD,9,Technology,2024-07-24,2024-09-30,875,8.7,Cloud AI Solutions +AI03172,Deep Learning Engineer,128930,CHF,116037,MI,PT,Switzerland,M,Switzerland,0,"SQL, PyTorch, GCP, Tableau, Deep Learning",Associate,3,Consulting,2024-12-20,2025-02-21,1288,5,Machine Intelligence Group +AI03173,AI Architect,59295,CAD,74119,EN,FL,Canada,S,Canada,50,"MLOps, Linux, SQL, Statistics",Bachelor,0,Consulting,2024-03-22,2024-04-20,1581,5.1,Algorithmic Solutions +AI03174,AI Architect,149462,CAD,186828,EX,CT,Canada,S,Canada,100,"Spark, Computer Vision, R, SQL",PhD,13,Real Estate,2024-05-28,2024-06-30,1196,7.9,Digital Transformation LLC +AI03175,Data Analyst,134389,USD,134389,EX,FL,South Korea,S,South Korea,50,"Python, Java, MLOps, GCP, Deep Learning",PhD,12,Manufacturing,2025-04-30,2025-05-26,2156,8,Quantum Computing Inc +AI03176,Deep Learning Engineer,77125,USD,77125,EN,FT,Sweden,L,Sweden,50,"Azure, SQL, Linux, Data Visualization, Git",Master,1,Telecommunications,2024-10-22,2024-12-11,2144,8.6,Machine Intelligence Group +AI03177,Autonomous Systems Engineer,177796,GBP,133347,EX,PT,United Kingdom,L,United Kingdom,0,"SQL, Tableau, GCP, AWS",Bachelor,12,Real Estate,2024-09-18,2024-10-03,1210,8.5,Algorithmic Solutions +AI03178,Robotics Engineer,146724,USD,146724,SE,CT,Denmark,M,Denmark,100,"Data Visualization, Python, MLOps, Kubernetes",Bachelor,5,Media,2024-09-01,2024-10-05,628,9.4,DeepTech Ventures +AI03179,Data Engineer,170330,USD,170330,SE,CT,Norway,M,Norway,100,"Git, Statistics, Spark, Python, MLOps",Master,6,Manufacturing,2024-05-06,2024-05-29,2072,7.8,Quantum Computing Inc +AI03180,Computer Vision Engineer,79412,USD,79412,MI,CT,South Korea,S,Finland,100,"NLP, Docker, SQL, Python",Master,3,Energy,2024-09-13,2024-10-22,1679,9.2,Future Systems +AI03181,AI Specialist,124306,EUR,105660,SE,FL,Netherlands,L,Netherlands,100,"Python, Azure, GCP, Mathematics, R",Associate,7,Finance,2024-11-02,2024-12-23,1981,6.4,TechCorp Inc +AI03182,Head of AI,119037,EUR,101181,SE,FT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, Tableau, Python, TensorFlow",Bachelor,7,Technology,2024-12-24,2025-01-16,1560,9.9,Algorithmic Solutions +AI03183,NLP Engineer,222977,EUR,189530,EX,FL,Germany,L,Germany,0,"NLP, Computer Vision, Data Visualization, Docker, SQL",PhD,13,Finance,2025-02-21,2025-03-24,869,9,Machine Intelligence Group +AI03184,Data Engineer,136646,CAD,170808,SE,PT,Canada,M,Canada,100,"Python, Docker, Hadoop, Deep Learning",PhD,9,Telecommunications,2024-05-03,2024-06-06,1317,8.4,Algorithmic Solutions +AI03185,AI Specialist,192004,JPY,21120440,EX,FT,Japan,L,France,0,"Kubernetes, AWS, PyTorch",Master,11,Real Estate,2024-05-25,2024-08-03,2244,6.5,Future Systems +AI03186,Research Scientist,270814,GBP,203111,EX,PT,United Kingdom,L,Sweden,0,"Spark, Deep Learning, Azure, Java, Tableau",Bachelor,17,Gaming,2024-05-18,2024-07-25,1890,6.6,Neural Networks Co +AI03187,AI Consultant,125599,USD,125599,SE,FL,Sweden,M,Sweden,0,"Computer Vision, Java, Data Visualization",Associate,8,Technology,2024-03-07,2024-04-17,723,7.7,TechCorp Inc +AI03188,Machine Learning Engineer,102825,USD,102825,MI,PT,Finland,L,United Kingdom,100,"Docker, Tableau, Hadoop, Computer Vision",Associate,3,Technology,2024-02-16,2024-04-02,1608,7.2,Cloud AI Solutions +AI03189,AI Research Scientist,233678,JPY,25704580,EX,FT,Japan,L,Malaysia,100,"MLOps, Azure, Tableau, NLP, PyTorch",Associate,15,Consulting,2024-08-04,2024-09-30,1310,6.8,Predictive Systems +AI03190,AI Consultant,92649,EUR,78752,MI,PT,Netherlands,M,Czech Republic,100,"Spark, Tableau, MLOps",Associate,4,Energy,2024-09-04,2024-09-23,644,9.9,Advanced Robotics +AI03191,AI Research Scientist,102702,EUR,87297,MI,CT,Germany,M,Germany,0,"GCP, Docker, Scala, Python",PhD,4,Automotive,2025-03-05,2025-04-18,765,7,Machine Intelligence Group +AI03192,Autonomous Systems Engineer,220138,SGD,286179,EX,PT,Singapore,S,Singapore,0,"Java, Linux, Scala, Kubernetes",Associate,10,Finance,2024-12-10,2025-01-28,1094,5.1,Machine Intelligence Group +AI03193,NLP Engineer,102269,SGD,132950,MI,PT,Singapore,L,Singapore,50,"SQL, Python, Deep Learning, Linux",Bachelor,3,Energy,2024-08-19,2024-10-31,1527,10,Cognitive Computing +AI03194,AI Software Engineer,164789,USD,164789,EX,FL,Denmark,S,Denmark,100,"Linux, Scala, Docker",Master,15,Retail,2024-02-22,2024-04-09,2219,9.6,DeepTech Ventures +AI03195,AI Software Engineer,37291,USD,37291,MI,FT,India,L,India,50,"PyTorch, TensorFlow, Docker, Hadoop, Linux",Associate,2,Consulting,2024-12-19,2025-01-27,2137,8.6,AI Innovations +AI03196,NLP Engineer,112266,USD,112266,MI,FT,United States,M,United States,50,"Azure, Kubernetes, AWS",Associate,3,Transportation,2025-03-18,2025-05-22,2235,5.7,Cloud AI Solutions +AI03197,NLP Engineer,67601,USD,67601,EN,FL,South Korea,L,Canada,0,"NLP, GCP, Scala",Associate,0,Finance,2024-01-26,2024-03-27,2022,5.7,Cognitive Computing +AI03198,AI Software Engineer,265839,CAD,332299,EX,CT,Canada,L,Canada,0,"Tableau, SQL, Hadoop, Computer Vision, PyTorch",Master,16,Technology,2024-07-12,2024-08-17,1079,9.9,Cloud AI Solutions +AI03199,Autonomous Systems Engineer,127393,CAD,159241,SE,FT,Canada,S,Canada,50,"SQL, Tableau, Docker, PyTorch",PhD,6,Finance,2025-03-02,2025-04-06,961,9.6,Digital Transformation LLC +AI03200,Machine Learning Engineer,79956,USD,79956,MI,FL,Israel,M,Israel,50,"SQL, Scala, Hadoop, Computer Vision, Python",Associate,3,Automotive,2024-05-05,2024-07-16,1366,7,AI Innovations +AI03201,AI Product Manager,64844,USD,64844,EN,PT,Finland,M,Finland,100,"MLOps, Linux, TensorFlow",Associate,0,Manufacturing,2025-03-11,2025-04-05,642,6.3,AI Innovations +AI03202,Data Analyst,255126,GBP,191345,EX,PT,United Kingdom,L,Netherlands,50,"Docker, MLOps, Data Visualization",Master,17,Technology,2024-02-26,2024-03-11,1055,5.4,Cognitive Computing +AI03203,Data Analyst,55235,USD,55235,EN,FL,Sweden,M,Sweden,100,"Scala, Kubernetes, NLP, Azure",Associate,0,Gaming,2025-01-19,2025-03-16,2002,6.9,Cognitive Computing +AI03204,AI Product Manager,179903,EUR,152918,SE,FT,Netherlands,L,Netherlands,0,"Linux, Scala, Java, Docker",Master,7,Media,2024-01-24,2024-03-30,759,6.3,Machine Intelligence Group +AI03205,Deep Learning Engineer,99326,USD,99326,MI,FT,Finland,L,Finland,100,"Tableau, R, Linux, Git, Java",PhD,2,Transportation,2024-11-09,2024-12-01,713,7.9,Algorithmic Solutions +AI03206,NLP Engineer,36397,USD,36397,MI,PT,China,S,China,100,"NLP, Tableau, Docker, MLOps, Data Visualization",Master,4,Gaming,2025-03-20,2025-05-18,863,9.6,Advanced Robotics +AI03207,Head of AI,55499,USD,55499,SE,FT,China,L,China,50,"Spark, R, Hadoop, Kubernetes",PhD,6,Consulting,2024-03-15,2024-04-29,2352,9.4,Future Systems +AI03208,Data Analyst,32595,USD,32595,MI,FT,India,M,Kenya,100,"Python, MLOps, Data Visualization, AWS",Master,3,Government,2024-09-08,2024-10-05,1738,6.4,Advanced Robotics +AI03209,AI Software Engineer,257447,USD,257447,EX,PT,United States,S,United States,0,"Python, PyTorch, TensorFlow, R",Master,19,Consulting,2024-04-07,2024-06-05,2080,6.7,Predictive Systems +AI03210,Research Scientist,92838,EUR,78912,MI,CT,Austria,M,Austria,0,"PyTorch, Azure, MLOps, GCP",Bachelor,2,Real Estate,2024-04-24,2024-05-10,957,7.2,Cloud AI Solutions +AI03211,ML Ops Engineer,90741,EUR,77130,MI,FT,Austria,S,Austria,0,"Tableau, NLP, GCP, Java",PhD,4,Retail,2024-05-05,2024-06-27,2471,7.1,Cloud AI Solutions +AI03212,Computer Vision Engineer,76319,USD,76319,SE,FL,South Korea,S,South Korea,0,"TensorFlow, Python, Docker, Java",Master,6,Media,2024-03-20,2024-05-24,839,6.4,Autonomous Tech +AI03213,AI Specialist,210418,EUR,178855,EX,FT,Austria,L,Austria,100,"Java, Azure, MLOps",Master,11,Government,2024-11-12,2024-12-14,1743,8.4,DataVision Ltd +AI03214,AI Software Engineer,196045,EUR,166638,EX,FL,Germany,M,Romania,0,"Docker, Python, Kubernetes",PhD,10,Education,2024-11-02,2024-11-23,512,5.2,Neural Networks Co +AI03215,Deep Learning Engineer,135969,CHF,122372,SE,FT,Switzerland,S,Belgium,100,"R, Kubernetes, Docker",PhD,8,Technology,2024-09-18,2024-10-09,1530,5.3,Future Systems +AI03216,Head of AI,48643,EUR,41347,EN,FT,Netherlands,S,Netherlands,100,"NLP, Scala, R, Tableau, Python",Bachelor,1,Retail,2024-03-11,2024-04-04,2102,7.5,DeepTech Ventures +AI03217,AI Architect,78066,USD,78066,EN,PT,Finland,L,Egypt,0,"Python, Data Visualization, Kubernetes",Bachelor,0,Real Estate,2025-03-24,2025-05-26,2098,7.9,TechCorp Inc +AI03218,Machine Learning Researcher,41677,USD,41677,EN,CT,South Korea,S,South Korea,100,"MLOps, R, Kubernetes, Deep Learning",Associate,0,Energy,2024-07-09,2024-09-15,1351,6.1,Autonomous Tech +AI03219,Deep Learning Engineer,93162,JPY,10247820,EN,FT,Japan,L,Japan,100,"Python, Deep Learning, Java",Master,0,Manufacturing,2024-09-06,2024-11-10,1406,9.7,Cognitive Computing +AI03220,Research Scientist,64788,EUR,55070,EN,PT,Germany,S,Hungary,50,"PyTorch, Statistics, Spark, SQL, GCP",Associate,0,Media,2024-11-18,2025-01-28,1017,6,Neural Networks Co +AI03221,AI Architect,154205,USD,154205,EX,CT,Ireland,S,Ireland,50,"Azure, AWS, GCP, Spark",Bachelor,19,Media,2024-10-15,2024-10-31,1369,7.8,Algorithmic Solutions +AI03222,Principal Data Scientist,143701,USD,143701,SE,CT,Israel,M,Israel,100,"Tableau, SQL, Scala, Azure",Associate,8,Media,2025-04-04,2025-06-14,557,6.2,DataVision Ltd +AI03223,Data Scientist,164876,CHF,148388,SE,PT,Switzerland,S,Switzerland,0,"Kubernetes, AWS, Scala, GCP",Bachelor,9,Government,2025-01-01,2025-01-16,1603,6.2,Neural Networks Co +AI03224,Autonomous Systems Engineer,35464,USD,35464,EN,FT,China,M,China,0,"Mathematics, Docker, Azure",PhD,1,Education,2024-02-03,2024-02-28,736,9.4,DeepTech Ventures +AI03225,AI Specialist,59626,USD,59626,EN,FL,Ireland,M,Ireland,0,"Linux, Java, Scala",Bachelor,1,Gaming,2025-03-15,2025-04-18,624,5.5,TechCorp Inc +AI03226,AI Specialist,307432,USD,307432,EX,FL,Norway,M,Norway,100,"Linux, Python, NLP",PhD,11,Manufacturing,2025-01-31,2025-03-30,2437,9.6,Digital Transformation LLC +AI03227,AI Architect,176090,USD,176090,SE,FL,Norway,S,Luxembourg,100,"Hadoop, AWS, Spark",Associate,6,Technology,2025-02-27,2025-04-07,2082,9.2,AI Innovations +AI03228,AI Architect,66682,USD,66682,EN,FL,United States,S,United States,0,"Scala, Java, NLP, R",Associate,0,Finance,2024-08-19,2024-09-24,1664,9.8,Digital Transformation LLC +AI03229,Data Analyst,39616,USD,39616,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Scala, Tableau, R, Python",PhD,0,Real Estate,2024-06-13,2024-07-30,550,8,DeepTech Ventures +AI03230,AI Product Manager,122403,CHF,110163,EN,PT,Switzerland,L,Singapore,100,"TensorFlow, Kubernetes, NLP",Associate,0,Finance,2024-01-23,2024-03-02,2351,8.2,Cognitive Computing +AI03231,Deep Learning Engineer,130431,USD,130431,SE,FT,Finland,M,Finland,100,"Linux, R, NLP",PhD,8,Government,2024-08-26,2024-11-07,1081,6.4,Smart Analytics +AI03232,AI Software Engineer,91342,EUR,77641,MI,PT,Germany,S,Germany,100,"Hadoop, SQL, Docker",Bachelor,4,Healthcare,2024-02-05,2024-04-15,524,6.7,TechCorp Inc +AI03233,AI Product Manager,34743,USD,34743,EN,FL,China,M,China,100,"R, Hadoop, PyTorch",Master,0,Real Estate,2024-03-08,2024-05-01,1698,7.9,Future Systems +AI03234,Computer Vision Engineer,75941,EUR,64550,MI,FT,France,S,France,100,"Statistics, R, Python, GCP",Master,3,Telecommunications,2024-06-30,2024-08-12,1131,6.5,Machine Intelligence Group +AI03235,AI Product Manager,53406,USD,53406,EN,CT,South Korea,M,South Korea,100,"NLP, Kubernetes, Python",Associate,0,Manufacturing,2025-03-01,2025-05-12,2231,9.6,Neural Networks Co +AI03236,Autonomous Systems Engineer,280999,CHF,252899,EX,FT,Switzerland,M,Switzerland,100,"Linux, Kubernetes, GCP, Python",Associate,18,Gaming,2024-06-11,2024-08-17,1120,9.3,Predictive Systems +AI03237,Computer Vision Engineer,211482,SGD,274927,EX,PT,Singapore,L,Singapore,50,"Scala, Statistics, Python",Bachelor,17,Education,2024-09-26,2024-11-06,1183,8,DeepTech Ventures +AI03238,AI Architect,188072,CHF,169265,EX,CT,Switzerland,S,Switzerland,100,"SQL, Kubernetes, Azure",Associate,11,Automotive,2025-02-15,2025-03-15,1142,5.9,Predictive Systems +AI03239,NLP Engineer,89391,EUR,75982,MI,FL,Germany,M,Germany,0,"SQL, Hadoop, Java",Bachelor,2,Consulting,2025-04-15,2025-04-29,2251,6.3,DeepTech Ventures +AI03240,Machine Learning Researcher,172617,CHF,155355,SE,FL,Switzerland,L,Switzerland,0,"Data Visualization, NLP, Azure",Associate,7,Real Estate,2024-11-08,2024-12-19,1254,6.3,Digital Transformation LLC +AI03241,Head of AI,247125,SGD,321263,EX,FT,Singapore,L,Singapore,100,"TensorFlow, Git, Java, Azure, NLP",PhD,18,Energy,2025-03-23,2025-04-11,616,6.1,Advanced Robotics +AI03242,AI Architect,58586,EUR,49798,EN,CT,Austria,L,Austria,0,"Python, AWS, Kubernetes, Scala, Statistics",PhD,0,Government,2025-02-10,2025-03-02,1313,8.6,Quantum Computing Inc +AI03243,AI Consultant,66857,USD,66857,EN,FT,United States,M,France,100,"GCP, Scala, Mathematics",Associate,0,Manufacturing,2024-04-16,2024-05-05,1143,8.9,DeepTech Ventures +AI03244,Machine Learning Engineer,61082,USD,61082,EN,FT,Ireland,S,Ireland,0,"MLOps, Data Visualization, PyTorch, Kubernetes, Python",PhD,1,Government,2024-10-19,2024-12-13,1334,6.9,DataVision Ltd +AI03245,Principal Data Scientist,109973,SGD,142965,MI,FL,Singapore,M,Singapore,100,"Kubernetes, MLOps, Spark, R, SQL",Associate,4,Real Estate,2024-03-04,2024-03-29,1826,9.1,Machine Intelligence Group +AI03246,Machine Learning Engineer,96154,GBP,72116,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, Data Visualization, Scala, Tableau",PhD,3,Telecommunications,2024-10-28,2024-12-15,1199,8.5,Smart Analytics +AI03247,Data Engineer,80737,EUR,68626,MI,CT,France,L,France,50,"Java, Python, Docker",PhD,3,Manufacturing,2024-08-25,2024-09-15,1683,7.5,Quantum Computing Inc +AI03248,Data Analyst,60211,USD,60211,EN,PT,Israel,S,Israel,50,"NLP, Deep Learning, PyTorch, Mathematics, Scala",PhD,0,Technology,2025-01-16,2025-03-09,1572,5.4,DataVision Ltd +AI03249,AI Research Scientist,77885,EUR,66202,MI,PT,Austria,M,Austria,50,"Docker, Azure, Kubernetes",Associate,2,Gaming,2024-09-16,2024-10-07,1002,8.5,Algorithmic Solutions +AI03250,Machine Learning Engineer,91640,CAD,114550,MI,PT,Canada,S,China,50,"PyTorch, TensorFlow, Java, MLOps, AWS",Bachelor,4,Education,2025-03-02,2025-04-13,2355,6.5,Digital Transformation LLC +AI03251,Principal Data Scientist,136201,CAD,170251,EX,FT,Canada,S,Canada,100,"Kubernetes, Java, MLOps",Associate,11,Healthcare,2024-09-24,2024-11-22,1786,9.9,Smart Analytics +AI03252,Machine Learning Researcher,100307,SGD,130399,SE,PT,Singapore,S,Singapore,100,"R, SQL, Statistics, PyTorch",Associate,8,Government,2024-04-16,2024-05-10,844,7.7,Cloud AI Solutions +AI03253,AI Specialist,71821,CAD,89776,EN,FT,Canada,L,Canada,0,"Azure, R, NLP, Hadoop, Git",Bachelor,0,Manufacturing,2024-08-27,2024-09-24,1281,7.9,Future Systems +AI03254,AI Software Engineer,92325,USD,92325,MI,CT,Finland,L,Finland,100,"TensorFlow, Python, Java, Linux",Bachelor,2,Telecommunications,2024-07-26,2024-08-28,1168,8.5,Digital Transformation LLC +AI03255,Machine Learning Researcher,128402,EUR,109142,SE,PT,Germany,S,Germany,0,"Spark, SQL, Azure, GCP, Deep Learning",PhD,5,Government,2025-01-18,2025-03-10,2118,6.3,Quantum Computing Inc +AI03256,Data Analyst,49741,USD,49741,EX,CT,India,M,India,0,"Docker, MLOps, Spark",Associate,12,Real Estate,2024-02-11,2024-04-19,1653,8.1,TechCorp Inc +AI03257,AI Software Engineer,189605,CHF,170645,SE,FT,Switzerland,S,Switzerland,0,"TensorFlow, Python, Tableau, Deep Learning",PhD,5,Real Estate,2025-02-06,2025-03-22,1625,6,Cognitive Computing +AI03258,Machine Learning Engineer,91412,SGD,118836,EN,FL,Singapore,L,United States,100,"Deep Learning, SQL, Hadoop",Associate,1,Education,2025-01-25,2025-03-19,966,7.7,Machine Intelligence Group +AI03259,Robotics Engineer,214536,USD,214536,SE,CT,Denmark,L,Poland,50,"SQL, Java, Statistics, Computer Vision, Deep Learning",PhD,8,Healthcare,2024-08-26,2024-10-23,1367,9.8,AI Innovations +AI03260,Machine Learning Researcher,93353,USD,93353,MI,PT,Norway,S,Norway,0,"Computer Vision, SQL, NLP, PyTorch, AWS",Associate,3,Education,2024-06-30,2024-07-30,2332,5.1,Autonomous Tech +AI03261,AI Architect,119157,USD,119157,SE,CT,Finland,L,Finland,100,"Kubernetes, PyTorch, GCP, Azure",Bachelor,7,Government,2024-01-07,2024-01-24,783,5.4,Advanced Robotics +AI03262,AI Specialist,262609,CHF,236348,EX,CT,Switzerland,L,Switzerland,50,"Hadoop, TensorFlow, PyTorch, Azure",Bachelor,16,Education,2024-05-11,2024-07-22,2100,5.6,Cloud AI Solutions +AI03263,AI Product Manager,69585,AUD,93940,EN,PT,Australia,S,Australia,100,"Computer Vision, Mathematics, Azure, R",PhD,0,Real Estate,2024-12-23,2025-01-20,1195,9.8,Machine Intelligence Group +AI03264,AI Product Manager,74761,AUD,100927,EN,PT,Australia,M,Australia,50,"MLOps, GCP, Docker, Python",Bachelor,0,Government,2024-12-07,2025-01-15,1022,6.9,AI Innovations +AI03265,ML Ops Engineer,162450,CHF,146205,SE,PT,Switzerland,M,Switzerland,0,"Spark, Git, Mathematics, Kubernetes, Python",Associate,7,Automotive,2024-07-06,2024-08-05,2224,6.5,Machine Intelligence Group +AI03266,Data Scientist,88851,USD,88851,EN,FL,Norway,S,Norway,100,"Data Visualization, Linux, Hadoop, Tableau",Bachelor,1,Retail,2025-03-30,2025-04-27,776,9.7,Quantum Computing Inc +AI03267,Autonomous Systems Engineer,91547,EUR,77815,EN,CT,Netherlands,L,Denmark,100,"PyTorch, Scala, Spark, SQL",Master,0,Finance,2025-02-22,2025-03-14,1399,6.3,DeepTech Ventures +AI03268,Principal Data Scientist,58081,EUR,49369,EN,FT,Germany,M,Germany,50,"TensorFlow, Kubernetes, Python, R",PhD,0,Technology,2024-12-27,2025-01-16,1995,8.1,Cloud AI Solutions +AI03269,Computer Vision Engineer,103246,EUR,87759,SE,PT,Austria,S,Austria,50,"Docker, Scala, GCP, AWS",Associate,5,Finance,2024-06-29,2024-08-28,1275,5,Quantum Computing Inc +AI03270,AI Research Scientist,32356,USD,32356,EN,CT,China,S,Estonia,100,"MLOps, R, Hadoop, SQL",PhD,0,Government,2025-01-11,2025-02-08,804,5.2,DeepTech Ventures +AI03271,AI Product Manager,48264,USD,48264,SE,FL,China,S,Hungary,0,"MLOps, PyTorch, Tableau, Data Visualization",Associate,7,Education,2024-08-02,2024-09-27,602,7.5,Neural Networks Co +AI03272,Research Scientist,66275,JPY,7290250,EN,PT,Japan,S,Japan,50,"Python, Tableau, SQL, MLOps",Master,1,Manufacturing,2024-10-01,2024-10-28,1057,7.8,Cloud AI Solutions +AI03273,Machine Learning Researcher,177406,JPY,19514660,EX,FT,Japan,L,Mexico,50,"Hadoop, Spark, Kubernetes",Master,14,Consulting,2024-09-12,2024-10-22,1985,8.4,Algorithmic Solutions +AI03274,Deep Learning Engineer,68779,USD,68779,EN,PT,United States,M,Poland,50,"Python, Git, NLP, Mathematics",PhD,0,Automotive,2024-05-24,2024-06-13,1842,9.1,Predictive Systems +AI03275,Robotics Engineer,93037,EUR,79081,MI,CT,France,M,France,0,"Git, Azure, Computer Vision, Python",PhD,2,Finance,2025-02-20,2025-03-23,1043,5.9,Cognitive Computing +AI03276,AI Product Manager,90694,CAD,113368,SE,CT,Canada,S,Canada,50,"R, Hadoop, Computer Vision, TensorFlow",Associate,8,Manufacturing,2024-12-30,2025-03-09,951,6.9,Quantum Computing Inc +AI03277,Autonomous Systems Engineer,197861,USD,197861,EX,FL,Israel,L,Malaysia,50,"Hadoop, MLOps, TensorFlow",Associate,17,Manufacturing,2025-03-25,2025-05-28,2052,7.2,DataVision Ltd +AI03278,AI Research Scientist,68932,USD,68932,MI,PT,South Korea,M,Chile,0,"Azure, Python, Linux",Master,2,Finance,2024-09-10,2024-10-02,2382,9.7,Quantum Computing Inc +AI03279,AI Software Engineer,83285,EUR,70792,MI,CT,France,M,France,100,"Data Visualization, SQL, R, NLP",Master,2,Media,2024-11-07,2024-12-02,886,9.7,Neural Networks Co +AI03280,NLP Engineer,161470,USD,161470,SE,CT,Israel,L,Israel,0,"Data Visualization, Kubernetes, Computer Vision",PhD,6,Retail,2025-01-18,2025-02-27,1896,9.2,Autonomous Tech +AI03281,NLP Engineer,101298,USD,101298,EN,FT,Norway,M,Norway,50,"NLP, GCP, Scala",Master,1,Technology,2024-12-27,2025-02-18,1133,9.3,Machine Intelligence Group +AI03282,AI Software Engineer,98441,USD,98441,MI,PT,United States,M,United States,0,"Mathematics, Java, Scala, Docker",PhD,2,Finance,2024-03-04,2024-05-15,1689,8.7,Digital Transformation LLC +AI03283,Principal Data Scientist,142540,USD,142540,SE,FT,South Korea,L,Czech Republic,0,"R, PyTorch, Linux, Mathematics",Master,6,Telecommunications,2024-07-19,2024-09-29,1555,8.7,Autonomous Tech +AI03284,Machine Learning Researcher,141976,USD,141976,SE,FT,Israel,M,Indonesia,50,"Git, Kubernetes, PyTorch",PhD,9,Telecommunications,2024-09-14,2024-10-29,2038,9.2,DeepTech Ventures +AI03285,Robotics Engineer,56123,USD,56123,EN,PT,Finland,M,Finland,50,"GCP, Python, AWS",Master,1,Manufacturing,2024-02-15,2024-04-28,503,5.1,Algorithmic Solutions +AI03286,NLP Engineer,93288,EUR,79295,MI,PT,Germany,L,Germany,0,"Statistics, Scala, Mathematics, Kubernetes",Bachelor,4,Gaming,2024-07-22,2024-08-28,2014,7.3,Machine Intelligence Group +AI03287,AI Consultant,111008,USD,111008,MI,FT,United States,S,United States,100,"Azure, R, Mathematics, NLP",Master,4,Consulting,2024-10-27,2024-12-20,2364,8.4,Smart Analytics +AI03288,NLP Engineer,188040,SGD,244452,EX,FT,Singapore,S,Singapore,0,"Scala, Git, SQL, Java, Mathematics",Associate,11,Transportation,2024-06-25,2024-08-12,2155,7.7,DataVision Ltd +AI03289,Computer Vision Engineer,37867,USD,37867,MI,PT,China,S,China,0,"Git, Statistics, Scala",PhD,4,Real Estate,2024-01-08,2024-02-04,2351,8.9,Predictive Systems +AI03290,AI Research Scientist,130573,USD,130573,EX,PT,Israel,S,India,100,"SQL, AWS, Python",Master,18,Finance,2024-02-02,2024-03-05,1006,5.4,Advanced Robotics +AI03291,AI Product Manager,84549,EUR,71867,EN,FL,Austria,L,Austria,50,"Linux, Mathematics, MLOps, Java, PyTorch",PhD,0,Transportation,2024-03-08,2024-04-22,1947,9.8,DataVision Ltd +AI03292,AI Specialist,115767,USD,115767,EN,PT,Denmark,L,Denmark,50,"PyTorch, Python, Linux, Mathematics",PhD,1,Gaming,2025-01-23,2025-03-25,2233,5.3,Autonomous Tech +AI03293,AI Consultant,229034,CHF,206131,SE,FL,Switzerland,L,Malaysia,50,"R, Statistics, Data Visualization, Deep Learning",PhD,5,Gaming,2024-02-08,2024-04-08,1422,9.4,DeepTech Ventures +AI03294,AI Research Scientist,128520,SGD,167076,SE,PT,Singapore,S,Singapore,0,"Scala, TensorFlow, Kubernetes, Docker, Mathematics",Master,6,Media,2024-12-27,2025-01-23,1971,6.5,AI Innovations +AI03295,Data Analyst,73935,EUR,62845,EN,FT,Netherlands,S,Netherlands,100,"Spark, PyTorch, Java, GCP",Associate,0,Government,2024-03-18,2024-04-10,806,8.6,Machine Intelligence Group +AI03296,AI Product Manager,113864,USD,113864,SE,FT,Ireland,S,Kenya,50,"R, Hadoop, SQL, Data Visualization",Master,6,Finance,2025-04-21,2025-06-25,859,5.3,Predictive Systems +AI03297,Computer Vision Engineer,98526,SGD,128084,SE,PT,Singapore,S,Singapore,50,"Azure, PyTorch, NLP",Associate,7,Manufacturing,2024-06-20,2024-08-21,974,8,Autonomous Tech +AI03298,Deep Learning Engineer,66726,USD,66726,EN,PT,Finland,M,Finland,100,"Docker, Computer Vision, Python, Spark",Bachelor,0,Real Estate,2024-06-17,2024-07-10,1308,7.8,Cloud AI Solutions +AI03299,Data Analyst,88638,AUD,119661,EN,CT,Australia,L,Sweden,100,"Mathematics, Deep Learning, Python, Java, TensorFlow",Master,1,Healthcare,2025-03-29,2025-06-03,835,7.6,DataVision Ltd +AI03300,Autonomous Systems Engineer,93012,USD,93012,MI,PT,United States,S,United States,50,"Kubernetes, Deep Learning, Git",PhD,3,Finance,2024-12-07,2024-12-21,1664,9.8,Cloud AI Solutions +AI03301,Computer Vision Engineer,78878,USD,78878,EN,FL,Denmark,L,Canada,50,"Scala, GCP, MLOps, Linux, Spark",Associate,0,Consulting,2025-01-17,2025-03-27,1459,9.1,Advanced Robotics +AI03302,NLP Engineer,82710,JPY,9098100,EN,FT,Japan,M,Japan,0,"Linux, Computer Vision, Tableau, NLP",Master,0,Gaming,2024-06-03,2024-07-20,1488,6.3,DeepTech Ventures +AI03303,Machine Learning Engineer,29961,USD,29961,EN,FT,China,S,Canada,100,"Data Visualization, Python, Kubernetes",Bachelor,1,Real Estate,2025-01-20,2025-02-15,1613,6.1,Future Systems +AI03304,NLP Engineer,273589,USD,273589,EX,FL,Denmark,M,Denmark,100,"R, Spark, GCP, Azure",PhD,11,Real Estate,2025-02-21,2025-04-11,763,7.4,Cognitive Computing +AI03305,AI Consultant,73518,JPY,8086980,EN,FL,Japan,M,Japan,0,"Data Visualization, NLP, AWS, Spark, Computer Vision",PhD,1,Real Estate,2024-11-14,2024-11-30,1298,7.4,AI Innovations +AI03306,Autonomous Systems Engineer,62379,JPY,6861690,EN,FT,Japan,L,Japan,50,"Deep Learning, Python, TensorFlow",Bachelor,1,Retail,2024-02-21,2024-03-26,1088,6,Autonomous Tech +AI03307,Data Analyst,73138,USD,73138,EX,CT,India,L,India,100,"PyTorch, GCP, MLOps, R, Deep Learning",Master,19,Real Estate,2024-01-14,2024-02-28,1574,9.4,Cloud AI Solutions +AI03308,Data Engineer,308012,EUR,261810,EX,FT,Netherlands,L,Israel,0,"Statistics, Spark, SQL, PyTorch, GCP",PhD,19,Automotive,2024-10-26,2024-11-29,852,8.5,Predictive Systems +AI03309,Robotics Engineer,72475,USD,72475,EN,FT,Israel,M,Israel,0,"Linux, TensorFlow, Python, Scala",Master,1,Retail,2024-11-04,2025-01-04,2425,8.7,Autonomous Tech +AI03310,Research Scientist,71202,USD,71202,EN,CT,Norway,S,Norway,0,"Hadoop, MLOps, Git, Linux, NLP",Master,0,Automotive,2025-02-02,2025-02-23,2495,7.8,Predictive Systems +AI03311,AI Research Scientist,178194,EUR,151465,EX,FT,Netherlands,M,Netherlands,100,"Deep Learning, Git, R",Associate,15,Retail,2024-07-18,2024-08-21,2376,7.5,DeepTech Ventures +AI03312,AI Consultant,26837,USD,26837,EN,CT,India,M,India,0,"PyTorch, SQL, Scala",Bachelor,0,Healthcare,2024-01-27,2024-03-06,1504,7.4,Advanced Robotics +AI03313,Principal Data Scientist,97019,USD,97019,MI,FL,Finland,M,Estonia,50,"NLP, Spark, Scala, Git",Bachelor,4,Retail,2025-02-11,2025-04-25,1089,6.5,DataVision Ltd +AI03314,Robotics Engineer,118655,EUR,100857,SE,FT,France,L,Czech Republic,0,"Computer Vision, Tableau, Scala",Bachelor,7,Consulting,2025-02-23,2025-03-27,822,7.4,Machine Intelligence Group +AI03315,AI Specialist,84059,JPY,9246490,MI,FT,Japan,S,Japan,100,"SQL, Docker, Mathematics, GCP",PhD,2,Healthcare,2025-04-04,2025-06-06,2331,5.4,Quantum Computing Inc +AI03316,AI Consultant,205243,CAD,256554,EX,FL,Canada,M,Poland,50,"Java, Tableau, Statistics, Mathematics",Master,11,Education,2025-03-12,2025-05-18,1170,8.7,Digital Transformation LLC +AI03317,AI Research Scientist,65453,USD,65453,MI,PT,Israel,S,Romania,50,"Python, PyTorch, GCP, Java, Deep Learning",PhD,4,Transportation,2024-02-06,2024-03-25,818,8.8,Neural Networks Co +AI03318,Computer Vision Engineer,103929,USD,103929,SE,CT,South Korea,M,South Korea,0,"Data Visualization, Python, Linux, Mathematics",Bachelor,9,Transportation,2024-01-12,2024-01-27,996,6.4,Smart Analytics +AI03319,Head of AI,83770,JPY,9214700,MI,PT,Japan,M,Russia,0,"Kubernetes, NLP, PyTorch",Master,3,Telecommunications,2025-01-31,2025-03-12,1521,6.7,AI Innovations +AI03320,AI Software Engineer,71511,EUR,60784,EN,FL,Germany,M,Germany,50,"Mathematics, R, Java, Git, Linux",Bachelor,1,Government,2024-01-24,2024-04-05,2237,5.2,Smart Analytics +AI03321,Robotics Engineer,86602,USD,86602,MI,FT,Sweden,S,Egypt,100,"PyTorch, TensorFlow, Data Visualization",Master,4,Government,2024-06-10,2024-08-21,1231,6.9,TechCorp Inc +AI03322,AI Consultant,57477,SGD,74720,EN,CT,Singapore,S,Singapore,50,"Python, Hadoop, MLOps, Deep Learning",Master,1,Finance,2024-05-20,2024-06-21,665,6.8,Neural Networks Co +AI03323,Machine Learning Engineer,104741,JPY,11521510,MI,FT,Japan,M,Japan,50,"Docker, Python, Computer Vision, Scala",PhD,4,Technology,2024-08-10,2024-09-12,595,6.6,DataVision Ltd +AI03324,Computer Vision Engineer,257714,USD,257714,EX,FT,Denmark,S,Denmark,100,"Python, Docker, Spark, Azure, Linux",Master,12,Finance,2024-07-22,2024-08-20,1875,5.9,Advanced Robotics +AI03325,Data Engineer,67170,JPY,7388700,EN,FL,Japan,S,Japan,100,"Kubernetes, Scala, NLP, Deep Learning",Bachelor,0,Retail,2024-10-22,2024-12-21,2375,6.8,Advanced Robotics +AI03326,Machine Learning Engineer,145681,EUR,123829,SE,PT,Austria,L,Austria,0,"TensorFlow, Computer Vision, Data Visualization",Associate,5,Consulting,2024-01-20,2024-03-29,808,7.1,DeepTech Ventures +AI03327,AI Specialist,118285,EUR,100542,MI,PT,Austria,L,Ireland,50,"Statistics, Scala, Data Visualization, Spark, Java",Bachelor,2,Government,2025-04-14,2025-05-07,1534,5.3,Cognitive Computing +AI03328,Principal Data Scientist,151221,USD,151221,SE,FL,United States,M,United States,0,"PyTorch, Scala, Hadoop, GCP",Master,6,Technology,2024-07-18,2024-08-17,638,8.6,Machine Intelligence Group +AI03329,Robotics Engineer,97110,CHF,87399,EN,FT,Switzerland,L,Switzerland,50,"Python, GCP, Mathematics",PhD,0,Healthcare,2024-04-25,2024-07-04,825,8.7,Cloud AI Solutions +AI03330,Research Scientist,142010,USD,142010,SE,CT,Israel,L,Israel,0,"Spark, Mathematics, Data Visualization, PyTorch, MLOps",Associate,9,Technology,2024-06-01,2024-07-18,590,5.7,Cloud AI Solutions +AI03331,AI Product Manager,221988,EUR,188690,EX,FT,Netherlands,S,Philippines,100,"Kubernetes, Data Visualization, Git, SQL",Associate,13,Technology,2025-02-15,2025-03-07,2002,9.2,DataVision Ltd +AI03332,AI Consultant,171046,USD,171046,EX,CT,United States,S,United States,100,"PyTorch, AWS, MLOps, Docker",PhD,13,Government,2024-10-09,2024-11-06,1843,6.9,Cloud AI Solutions +AI03333,Research Scientist,71257,USD,71257,EN,FT,South Korea,L,Kenya,50,"Data Visualization, AWS, Tableau, SQL",PhD,0,Technology,2025-02-17,2025-03-07,2459,8.3,TechCorp Inc +AI03334,ML Ops Engineer,109428,USD,109428,SE,PT,Ireland,S,Ireland,0,"Scala, SQL, NLP, Mathematics",Bachelor,5,Healthcare,2024-12-13,2024-12-29,2367,6.1,Smart Analytics +AI03335,Autonomous Systems Engineer,221626,AUD,299195,EX,CT,Australia,M,Romania,100,"Kubernetes, GCP, Data Visualization",Bachelor,13,Healthcare,2024-10-18,2024-11-24,1179,7.6,Machine Intelligence Group +AI03336,Deep Learning Engineer,189458,GBP,142094,EX,CT,United Kingdom,S,Portugal,0,"PyTorch, Spark, SQL, Hadoop, Mathematics",Master,10,Energy,2024-04-14,2024-05-09,1518,5.1,Smart Analytics +AI03337,Principal Data Scientist,200620,CHF,180558,EX,PT,Switzerland,M,Australia,50,"Computer Vision, AWS, Python, TensorFlow",PhD,17,Energy,2024-04-30,2024-07-01,1920,5.4,Machine Intelligence Group +AI03338,AI Specialist,205234,CAD,256543,EX,FT,Canada,S,Canada,50,"Hadoop, Azure, NLP",Bachelor,18,Energy,2024-12-23,2025-02-24,809,7.8,Neural Networks Co +AI03339,Research Scientist,247132,USD,247132,EX,PT,Israel,L,Israel,50,"Python, Kubernetes, SQL",PhD,10,Government,2024-04-21,2024-06-01,673,9.4,TechCorp Inc +AI03340,Deep Learning Engineer,97358,USD,97358,EN,CT,Norway,M,Canada,50,"PyTorch, AWS, Azure, Git, TensorFlow",Master,0,Telecommunications,2024-05-14,2024-07-06,1847,7.1,Quantum Computing Inc +AI03341,Head of AI,57152,SGD,74298,EN,FL,Singapore,M,Singapore,0,"Statistics, Git, Data Visualization",Master,0,Automotive,2024-01-15,2024-03-25,1629,9,Smart Analytics +AI03342,Data Engineer,103950,EUR,88358,SE,PT,France,M,France,100,"Spark, Hadoop, NLP",Master,8,Consulting,2024-06-12,2024-07-25,1220,7.7,Future Systems +AI03343,Principal Data Scientist,112737,AUD,152195,SE,FL,Australia,S,Australia,0,"NLP, Scala, Mathematics, Java, SQL",Bachelor,5,Transportation,2024-08-17,2024-10-12,820,9.9,Neural Networks Co +AI03344,AI Product Manager,81647,JPY,8981170,EN,PT,Japan,L,Denmark,50,"GCP, Tableau, SQL, Computer Vision, Azure",Master,1,Media,2025-03-15,2025-05-10,2037,9,Predictive Systems +AI03345,Autonomous Systems Engineer,80194,USD,80194,MI,PT,Finland,M,Finland,100,"Python, GCP, Statistics",Associate,3,Automotive,2024-06-29,2024-08-07,1331,6.4,Algorithmic Solutions +AI03346,Machine Learning Researcher,50217,USD,50217,SE,FT,India,L,India,0,"Scala, TensorFlow, Tableau",Master,7,Energy,2025-01-29,2025-03-25,677,8.8,Neural Networks Co +AI03347,AI Consultant,242187,SGD,314843,EX,FL,Singapore,S,Netherlands,100,"Statistics, Tableau, PyTorch, NLP",Bachelor,10,Healthcare,2025-03-11,2025-04-12,2106,5.2,Autonomous Tech +AI03348,Head of AI,140261,USD,140261,SE,FL,Norway,M,Norway,100,"Linux, TensorFlow, SQL, Deep Learning, Java",Bachelor,6,Manufacturing,2024-09-02,2024-10-27,640,8.4,Advanced Robotics +AI03349,Data Engineer,92105,USD,92105,MI,FT,Finland,S,Austria,50,"AWS, Hadoop, Spark, NLP, Git",PhD,4,Transportation,2024-12-18,2025-02-17,1207,9,Digital Transformation LLC +AI03350,Research Scientist,123667,USD,123667,SE,PT,Ireland,M,China,50,"PyTorch, Statistics, Azure",PhD,6,Energy,2024-05-21,2024-06-13,1651,9.9,Machine Intelligence Group +AI03351,Machine Learning Engineer,93495,USD,93495,MI,PT,United States,S,United States,0,"TensorFlow, Kubernetes, Hadoop, Azure, Scala",Bachelor,3,Telecommunications,2024-11-14,2025-01-18,1663,6.5,Digital Transformation LLC +AI03352,Research Scientist,164403,AUD,221944,EX,FT,Australia,L,Australia,0,"Python, Git, TensorFlow, Hadoop, Mathematics",Bachelor,14,Government,2025-01-26,2025-03-26,1244,6.3,AI Innovations +AI03353,Deep Learning Engineer,161726,GBP,121295,SE,PT,United Kingdom,M,Indonesia,50,"AWS, Python, Tableau, R",Bachelor,8,Manufacturing,2025-03-03,2025-03-26,1141,8.1,Advanced Robotics +AI03354,Data Engineer,65395,AUD,88283,EN,CT,Australia,S,Australia,100,"PyTorch, Statistics, SQL, AWS",Bachelor,0,Transportation,2025-02-12,2025-04-20,2277,5.7,DeepTech Ventures +AI03355,Research Scientist,163112,USD,163112,SE,PT,Finland,L,Finland,50,"Python, Linux, Java, R",PhD,8,Telecommunications,2024-06-08,2024-08-02,1351,5.6,Autonomous Tech +AI03356,NLP Engineer,120372,USD,120372,SE,PT,Sweden,S,Sweden,0,"Spark, MLOps, Deep Learning",Associate,7,Real Estate,2024-12-27,2025-03-07,1014,5.1,Smart Analytics +AI03357,AI Consultant,80130,USD,80130,EN,FT,Denmark,L,Denmark,100,"SQL, PyTorch, R",Associate,1,Gaming,2024-12-27,2025-02-28,2374,7.3,Advanced Robotics +AI03358,Deep Learning Engineer,69483,USD,69483,SE,CT,China,L,China,50,"Python, R, GCP, Docker",Master,6,Technology,2024-07-26,2024-08-19,733,6.5,Digital Transformation LLC +AI03359,AI Specialist,275292,USD,275292,EX,FL,Denmark,M,Denmark,50,"Git, PyTorch, MLOps, Spark, Kubernetes",Master,16,Government,2024-03-12,2024-03-28,572,9.9,Machine Intelligence Group +AI03360,Data Analyst,90173,EUR,76647,MI,CT,Germany,L,Germany,50,"Linux, Scala, Mathematics, AWS, SQL",Bachelor,4,Technology,2024-11-25,2025-01-29,1158,7.8,Quantum Computing Inc +AI03361,AI Consultant,115690,JPY,12725900,MI,CT,Japan,L,Latvia,100,"Spark, Scala, Tableau, SQL",Master,3,Automotive,2024-11-25,2025-02-05,2463,9.8,Neural Networks Co +AI03362,Machine Learning Engineer,52110,USD,52110,EN,CT,Sweden,M,Luxembourg,100,"Mathematics, Scala, Python, Kubernetes",Associate,0,Energy,2024-06-01,2024-08-07,838,5.6,Cloud AI Solutions +AI03363,Deep Learning Engineer,163804,USD,163804,SE,CT,Norway,M,Estonia,100,"R, Java, Azure, Mathematics, NLP",PhD,7,Energy,2024-04-24,2024-06-25,2440,8.9,AI Innovations +AI03364,Machine Learning Researcher,173688,EUR,147635,SE,PT,Netherlands,L,Netherlands,100,"R, Linux, Git",Associate,6,Media,2024-09-05,2024-10-08,2247,8.2,Autonomous Tech +AI03365,Machine Learning Researcher,244135,AUD,329582,EX,PT,Australia,M,Australia,100,"Linux, SQL, Git, Data Visualization",Master,17,Automotive,2024-12-24,2025-01-16,2027,7.7,Machine Intelligence Group +AI03366,Research Scientist,177041,USD,177041,EX,CT,Finland,S,Estonia,100,"Azure, R, Tableau, Hadoop",Associate,12,Transportation,2024-05-06,2024-05-30,959,7.9,Neural Networks Co +AI03367,Head of AI,113070,CHF,101763,MI,FL,Switzerland,M,Poland,0,"R, Kubernetes, Tableau",PhD,4,Technology,2024-09-10,2024-11-15,1787,8.8,DeepTech Ventures +AI03368,Machine Learning Engineer,34381,USD,34381,SE,CT,India,S,India,0,"Hadoop, Python, Statistics, Linux, AWS",PhD,6,Retail,2025-02-28,2025-03-20,2339,5.2,Machine Intelligence Group +AI03369,AI Architect,102804,USD,102804,EX,FL,China,M,China,100,"Computer Vision, Azure, MLOps, NLP",PhD,11,Government,2024-09-17,2024-11-15,1482,5.7,TechCorp Inc +AI03370,AI Architect,124994,EUR,106245,SE,CT,Netherlands,L,Ukraine,50,"Python, Spark, Tableau",Associate,9,Manufacturing,2024-03-11,2024-05-17,867,7.6,Neural Networks Co +AI03371,Autonomous Systems Engineer,48674,USD,48674,SE,FT,India,M,Ukraine,100,"Scala, NLP, TensorFlow, Java, Git",Associate,9,Technology,2025-02-14,2025-03-07,2390,8.8,DataVision Ltd +AI03372,Autonomous Systems Engineer,83060,GBP,62295,EN,FT,United Kingdom,M,United Kingdom,50,"Scala, Hadoop, Azure, Java",Associate,0,Manufacturing,2025-04-08,2025-04-26,920,5.2,Algorithmic Solutions +AI03373,Computer Vision Engineer,116877,SGD,151940,MI,PT,Singapore,L,Singapore,0,"Mathematics, Spark, PyTorch, Java, SQL",Master,2,Healthcare,2024-12-22,2025-02-21,1090,9.4,AI Innovations +AI03374,AI Consultant,49966,USD,49966,SE,CT,India,M,India,100,"AWS, Git, NLP, Spark",Associate,5,Consulting,2024-10-23,2024-12-03,2239,5.7,DataVision Ltd +AI03375,Machine Learning Engineer,109823,USD,109823,SE,CT,Ireland,S,France,0,"Azure, Linux, Data Visualization, Tableau",Associate,7,Real Estate,2024-09-09,2024-09-27,590,6.4,Digital Transformation LLC +AI03376,Computer Vision Engineer,89964,EUR,76469,MI,CT,Netherlands,M,Romania,100,"Java, GCP, Mathematics",Master,2,Energy,2024-03-26,2024-04-28,1914,7.8,Cloud AI Solutions +AI03377,NLP Engineer,99897,CHF,89907,EN,CT,Switzerland,S,Switzerland,0,"Tableau, SQL, Linux",Associate,1,Energy,2025-02-17,2025-04-16,501,5.5,TechCorp Inc +AI03378,AI Product Manager,112037,CHF,100833,EN,FT,Switzerland,M,Switzerland,0,"AWS, SQL, R, Computer Vision",Associate,1,Telecommunications,2024-02-13,2024-04-04,1799,5.3,DataVision Ltd +AI03379,Robotics Engineer,97555,USD,97555,MI,FL,Sweden,S,Ireland,0,"Deep Learning, AWS, Mathematics, Python",Bachelor,3,Education,2024-07-18,2024-08-05,1520,9.7,Autonomous Tech +AI03380,Deep Learning Engineer,51067,USD,51067,MI,FT,China,L,China,0,"AWS, Kubernetes, R",Bachelor,2,Real Estate,2024-09-29,2024-11-29,705,8.4,Quantum Computing Inc +AI03381,AI Software Engineer,74645,AUD,100771,EN,PT,Australia,M,Australia,50,"Kubernetes, Python, Data Visualization, Statistics, Deep Learning",Master,1,Government,2024-03-18,2024-05-12,652,8.5,Predictive Systems +AI03382,ML Ops Engineer,73008,JPY,8030880,MI,CT,Japan,S,Japan,50,"Java, Kubernetes, Azure",Master,3,Finance,2024-10-18,2024-12-14,1485,8.2,AI Innovations +AI03383,Autonomous Systems Engineer,31006,USD,31006,EN,FT,China,S,China,100,"Python, Data Visualization, Linux, MLOps",PhD,0,Government,2024-06-08,2024-07-24,1097,9.2,Machine Intelligence Group +AI03384,Data Scientist,101583,USD,101583,SE,PT,South Korea,S,Canada,0,"Python, Scala, Hadoop, AWS",Master,9,Government,2024-07-29,2024-09-02,1325,6.1,Smart Analytics +AI03385,Computer Vision Engineer,90261,USD,90261,MI,CT,Sweden,M,Romania,0,"Tableau, Kubernetes, Scala, AWS, Git",Associate,4,Retail,2024-07-08,2024-07-23,1414,6.5,Future Systems +AI03386,AI Product Manager,111512,GBP,83634,MI,FL,United Kingdom,M,Latvia,0,"Statistics, NLP, Linux, Kubernetes, Hadoop",Bachelor,2,Media,2024-05-26,2024-06-15,1256,6.6,Smart Analytics +AI03387,AI Software Engineer,135059,JPY,14856490,SE,PT,Japan,M,South Africa,0,"PyTorch, Computer Vision, Scala, Azure, Linux",PhD,8,Telecommunications,2024-06-01,2024-08-02,1857,8.1,DataVision Ltd +AI03388,AI Architect,188799,USD,188799,EX,CT,Denmark,S,Denmark,50,"Tableau, Docker, NLP, Kubernetes",Associate,13,Real Estate,2024-03-28,2024-04-14,953,9.3,Autonomous Tech +AI03389,Data Scientist,133225,USD,133225,SE,FL,Ireland,S,Ireland,50,"PyTorch, Spark, Docker",PhD,5,Telecommunications,2024-08-27,2024-09-18,573,7,Smart Analytics +AI03390,Autonomous Systems Engineer,60400,USD,60400,SE,FL,China,S,China,0,"Computer Vision, Git, Python",Bachelor,5,Healthcare,2024-12-11,2025-01-06,1043,5.6,DeepTech Ventures +AI03391,Data Scientist,114422,USD,114422,SE,FT,Ireland,M,Ireland,100,"Azure, Linux, Mathematics, Data Visualization",Bachelor,7,Real Estate,2024-06-22,2024-08-11,2321,5.9,Cognitive Computing +AI03392,Research Scientist,85322,USD,85322,EN,CT,Denmark,S,Denmark,100,"Kubernetes, Scala, Mathematics, Azure",Bachelor,1,Healthcare,2024-10-28,2024-12-19,2265,5.8,AI Innovations +AI03393,Head of AI,64462,EUR,54793,MI,FL,Austria,S,Colombia,0,"Scala, PyTorch, TensorFlow, NLP",Master,4,Gaming,2024-04-17,2024-05-24,640,7.8,DataVision Ltd +AI03394,Deep Learning Engineer,214640,CAD,268300,EX,CT,Canada,M,Canada,100,"PyTorch, Kubernetes, GCP, Statistics, AWS",Bachelor,13,Media,2025-01-01,2025-02-04,708,8.6,Algorithmic Solutions +AI03395,NLP Engineer,160700,USD,160700,EX,FT,Israel,M,Israel,100,"Spark, GCP, Scala",Bachelor,18,Consulting,2025-04-15,2025-05-22,1966,6.4,Digital Transformation LLC +AI03396,Machine Learning Researcher,114986,CAD,143733,SE,CT,Canada,S,Israel,0,"AWS, Kubernetes, Azure",PhD,9,Automotive,2024-05-31,2024-08-05,1103,9.5,Predictive Systems +AI03397,Robotics Engineer,160285,GBP,120214,SE,PT,United Kingdom,M,Ireland,50,"Kubernetes, Computer Vision, Python, Git, Mathematics",Master,9,Technology,2025-01-12,2025-03-09,1719,5.4,Digital Transformation LLC +AI03398,ML Ops Engineer,184764,AUD,249431,EX,FT,Australia,L,Argentina,100,"Kubernetes, Python, Scala, Git, TensorFlow",Master,17,Media,2024-07-16,2024-08-18,2153,5.3,Advanced Robotics +AI03399,Deep Learning Engineer,168868,CHF,151981,MI,FL,Switzerland,L,Switzerland,50,"Kubernetes, Deep Learning, Data Visualization",Bachelor,3,Technology,2025-04-12,2025-06-17,2054,7.7,Neural Networks Co +AI03400,AI Architect,59852,GBP,44889,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Tableau, Linux, Scala, Deep Learning",PhD,1,Manufacturing,2025-01-21,2025-04-02,1905,8.8,Quantum Computing Inc +AI03401,Computer Vision Engineer,127118,EUR,108050,SE,CT,Austria,S,France,100,"Spark, Statistics, AWS, GCP, Scala",PhD,6,Technology,2024-10-16,2024-11-04,610,6.6,Quantum Computing Inc +AI03402,Machine Learning Engineer,62015,USD,62015,EN,FL,Sweden,L,Sweden,50,"GCP, SQL, Deep Learning, Python",PhD,1,Consulting,2024-04-17,2024-05-12,1071,9.3,Future Systems +AI03403,AI Software Engineer,70434,EUR,59869,EN,FL,Austria,L,Austria,50,"Python, Spark, Git, Deep Learning, Tableau",Master,1,Telecommunications,2024-04-18,2024-05-13,2274,6.7,AI Innovations +AI03404,AI Software Engineer,102013,USD,102013,EX,PT,South Korea,S,South Korea,0,"Linux, AWS, R",Associate,17,Transportation,2025-04-06,2025-06-04,2244,7.6,AI Innovations +AI03405,AI Architect,178561,USD,178561,EX,CT,Finland,L,Philippines,50,"Data Visualization, Linux, Git, PyTorch",PhD,19,Education,2024-01-23,2024-03-13,651,8,DeepTech Ventures +AI03406,Head of AI,63698,USD,63698,EN,FL,South Korea,L,Kenya,100,"Linux, Python, TensorFlow, MLOps",Bachelor,0,Automotive,2024-02-15,2024-04-14,1653,6.8,Smart Analytics +AI03407,NLP Engineer,70117,USD,70117,EN,CT,Sweden,M,Ukraine,50,"SQL, Data Visualization, Scala, Computer Vision, Azure",Master,0,Real Estate,2024-10-05,2024-12-03,2200,6,Quantum Computing Inc +AI03408,AI Specialist,125886,USD,125886,SE,CT,Israel,L,Ukraine,0,"PyTorch, MLOps, TensorFlow, SQL, Computer Vision",Associate,5,Automotive,2024-10-15,2024-10-31,923,5.9,AI Innovations +AI03409,Head of AI,143263,EUR,121774,SE,CT,Germany,L,Germany,100,"Data Visualization, NLP, Java, PyTorch",PhD,9,Gaming,2024-06-28,2024-08-03,1811,8.7,Quantum Computing Inc +AI03410,Autonomous Systems Engineer,61495,USD,61495,MI,CT,South Korea,S,South Korea,100,"AWS, Hadoop, Mathematics",PhD,4,Finance,2024-12-27,2025-02-24,2423,8.6,Machine Intelligence Group +AI03411,Robotics Engineer,275523,USD,275523,EX,CT,Norway,S,Netherlands,0,"NLP, Scala, Hadoop, Data Visualization",PhD,17,Technology,2024-08-19,2024-09-16,891,8.9,AI Innovations +AI03412,Data Engineer,65593,EUR,55754,EN,CT,France,M,France,100,"Deep Learning, Data Visualization, PyTorch, Kubernetes, Tableau",Master,1,Telecommunications,2024-02-29,2024-04-26,1617,6.2,DataVision Ltd +AI03413,Robotics Engineer,63298,USD,63298,EN,FT,United States,S,United States,50,"Hadoop, Python, TensorFlow, PyTorch, Statistics",PhD,0,Manufacturing,2025-04-30,2025-06-25,1610,9.9,Predictive Systems +AI03414,AI Software Engineer,70299,EUR,59754,MI,PT,France,M,France,100,"SQL, PyTorch, TensorFlow",Bachelor,2,Energy,2025-01-19,2025-02-16,2016,8.4,Cloud AI Solutions +AI03415,Machine Learning Engineer,202655,SGD,263452,EX,FL,Singapore,M,Singapore,0,"Linux, Hadoop, Git",Bachelor,12,Energy,2024-02-17,2024-03-27,2364,8,Quantum Computing Inc +AI03416,AI Specialist,256495,USD,256495,EX,PT,Norway,L,Norway,0,"Python, TensorFlow, Hadoop, Java",Bachelor,13,Transportation,2024-03-08,2024-04-05,1154,8.7,Neural Networks Co +AI03417,AI Product Manager,84934,AUD,114661,EN,PT,Australia,L,Australia,100,"Spark, Linux, R",Master,0,Energy,2024-10-06,2024-11-06,1062,8.9,Smart Analytics +AI03418,Research Scientist,83381,EUR,70874,MI,FL,Germany,S,Germany,100,"Git, Python, TensorFlow, NLP",Bachelor,3,Real Estate,2024-04-20,2024-06-07,1342,9.7,Algorithmic Solutions +AI03419,Data Analyst,26293,USD,26293,EN,FT,India,M,India,50,"PyTorch, SQL, AWS",Bachelor,1,Technology,2025-03-19,2025-05-12,2348,6.2,DataVision Ltd +AI03420,Head of AI,114838,USD,114838,SE,CT,Sweden,S,Sweden,50,"NLP, Python, Computer Vision, R, Deep Learning",Associate,9,Automotive,2025-01-11,2025-02-14,1472,7.1,Smart Analytics +AI03421,AI Specialist,130423,AUD,176071,SE,PT,Australia,S,Australia,0,"Python, Git, TensorFlow",PhD,9,Automotive,2024-11-09,2024-12-22,1640,8.3,Smart Analytics +AI03422,Head of AI,73362,USD,73362,MI,CT,Israel,S,Romania,0,"Python, Data Visualization, TensorFlow",Associate,4,Energy,2024-04-11,2024-06-13,1395,9.4,Algorithmic Solutions +AI03423,Research Scientist,55846,USD,55846,MI,FL,China,L,Sweden,100,"Tableau, Python, Statistics",Master,2,Media,2024-08-15,2024-09-01,1702,7.3,TechCorp Inc +AI03424,AI Product Manager,216173,USD,216173,EX,FT,South Korea,L,Hungary,50,"Python, Git, TensorFlow, Linux",Associate,17,Automotive,2024-04-19,2024-06-07,2275,8.4,Autonomous Tech +AI03425,Data Engineer,184151,GBP,138113,EX,FT,United Kingdom,M,United Kingdom,0,"Python, Docker, Tableau, GCP",Associate,12,Energy,2024-05-11,2024-06-28,957,8.4,Smart Analytics +AI03426,AI Product Manager,109524,CAD,136905,MI,FL,Canada,L,Canada,0,"PyTorch, Hadoop, MLOps, Kubernetes, Linux",PhD,4,Telecommunications,2024-03-27,2024-05-01,1174,8,AI Innovations +AI03427,Research Scientist,83789,USD,83789,EN,FT,United States,M,Colombia,0,"Python, MLOps, SQL, NLP",PhD,0,Healthcare,2025-01-15,2025-02-13,2307,6.7,Digital Transformation LLC +AI03428,Computer Vision Engineer,163508,USD,163508,EX,PT,South Korea,S,South Korea,0,"Scala, R, Deep Learning, Azure",PhD,17,Energy,2025-02-22,2025-04-15,1992,7.7,Smart Analytics +AI03429,Principal Data Scientist,159674,CHF,143707,MI,CT,Switzerland,L,Switzerland,100,"Scala, SQL, Python, Tableau",Master,2,Retail,2024-05-08,2024-06-06,888,8.1,Autonomous Tech +AI03430,Machine Learning Engineer,72337,USD,72337,EN,FL,Norway,S,Finland,50,"Git, Spark, Docker, TensorFlow, Linux",Master,0,Technology,2024-08-23,2024-10-25,598,9.8,Smart Analytics +AI03431,AI Research Scientist,168105,EUR,142889,EX,CT,Germany,L,Germany,100,"Kubernetes, Scala, Python",PhD,10,Telecommunications,2024-01-12,2024-01-27,1693,8.2,Algorithmic Solutions +AI03432,Data Scientist,157793,USD,157793,SE,PT,United States,L,India,0,"Docker, SQL, Computer Vision, Java",Bachelor,7,Telecommunications,2024-01-20,2024-03-09,2041,8.3,Quantum Computing Inc +AI03433,Machine Learning Engineer,186928,USD,186928,SE,FL,Norway,L,Chile,100,"Computer Vision, Python, Kubernetes, AWS",Master,9,Retail,2024-11-01,2024-11-24,1184,5.4,AI Innovations +AI03434,AI Specialist,97344,USD,97344,MI,PT,Ireland,S,Philippines,0,"Docker, Python, Computer Vision",Bachelor,2,Finance,2024-12-02,2025-01-18,1143,6.9,Cognitive Computing +AI03435,AI Product Manager,47190,EUR,40112,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, GCP, AWS, Deep Learning",Associate,0,Finance,2024-12-16,2025-01-04,539,9.7,Neural Networks Co +AI03436,Data Scientist,64670,CAD,80838,EN,PT,Canada,M,Canada,50,"Git, Azure, SQL, Mathematics",PhD,1,Consulting,2024-10-04,2024-11-24,1319,6.8,Machine Intelligence Group +AI03437,AI Architect,126076,USD,126076,SE,CT,Finland,S,Finland,50,"Data Visualization, Python, Linux, Statistics, TensorFlow",PhD,8,Media,2024-05-14,2024-07-22,2017,9.8,Predictive Systems +AI03438,Principal Data Scientist,98433,AUD,132885,MI,CT,Australia,M,Australia,50,"Linux, PyTorch, AWS, Deep Learning, MLOps",Master,2,Media,2024-02-10,2024-04-15,2422,9,Machine Intelligence Group +AI03439,Robotics Engineer,31915,USD,31915,EN,CT,China,L,China,100,"Statistics, Spark, Kubernetes, R, SQL",Bachelor,0,Gaming,2024-08-31,2024-10-07,1804,9.6,Neural Networks Co +AI03440,Data Scientist,175657,USD,175657,SE,PT,Norway,S,Norway,100,"Data Visualization, Spark, MLOps",Bachelor,5,Government,2024-10-07,2024-11-29,1903,9.8,Digital Transformation LLC +AI03441,Deep Learning Engineer,200463,USD,200463,EX,FL,Israel,M,Israel,0,"Scala, Hadoop, Deep Learning, AWS",PhD,19,Media,2024-10-17,2024-12-16,885,5,Quantum Computing Inc +AI03442,Robotics Engineer,109629,USD,109629,SE,CT,South Korea,S,Poland,100,"MLOps, Kubernetes, GCP",Associate,6,Finance,2024-04-12,2024-05-19,811,6.7,DataVision Ltd +AI03443,NLP Engineer,80126,USD,80126,EN,FT,Finland,L,Australia,100,"AWS, Tableau, Linux, Data Visualization",Master,0,Automotive,2024-01-31,2024-02-14,1963,6.2,Future Systems +AI03444,Machine Learning Engineer,91862,GBP,68897,EN,FT,United Kingdom,L,Malaysia,100,"TensorFlow, NLP, Git",PhD,0,Healthcare,2024-07-10,2024-09-02,2134,6.2,DeepTech Ventures +AI03445,Data Scientist,102655,JPY,11292050,MI,CT,Japan,L,Canada,50,"Kubernetes, R, PyTorch, GCP, Java",Master,4,Retail,2025-01-12,2025-02-01,864,6.5,Cloud AI Solutions +AI03446,Data Scientist,147186,AUD,198701,SE,CT,Australia,M,Chile,50,"TensorFlow, Mathematics, Kubernetes, SQL, Statistics",PhD,5,Telecommunications,2025-04-26,2025-06-18,983,7.4,DataVision Ltd +AI03447,Research Scientist,184149,USD,184149,EX,FT,Ireland,S,Ireland,0,"GCP, SQL, Data Visualization, Mathematics",Bachelor,14,Automotive,2024-03-31,2024-04-26,645,6.8,Digital Transformation LLC +AI03448,Computer Vision Engineer,273048,USD,273048,EX,FL,Norway,M,Germany,50,"Python, Mathematics, Data Visualization, Computer Vision",Master,16,Energy,2024-12-15,2024-12-30,892,6.2,Cloud AI Solutions +AI03449,NLP Engineer,105192,GBP,78894,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, TensorFlow, Hadoop, Linux",Master,2,Media,2024-05-21,2024-06-27,845,5.2,DataVision Ltd +AI03450,Deep Learning Engineer,37406,USD,37406,MI,PT,India,M,India,0,"Git, Java, Linux, Python",Master,4,Education,2024-01-27,2024-03-01,1756,6.8,DataVision Ltd +AI03451,AI Specialist,27619,USD,27619,EN,FT,India,M,India,0,"Tableau, Python, R, Kubernetes",Bachelor,0,Government,2024-08-10,2024-10-11,570,8.8,Smart Analytics +AI03452,Machine Learning Researcher,94921,USD,94921,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Spark, Docker",PhD,8,Media,2024-04-04,2024-06-12,2257,5.4,Quantum Computing Inc +AI03453,Data Scientist,199186,USD,199186,EX,FT,Israel,M,Israel,0,"Docker, Kubernetes, Hadoop, Java",Master,13,Automotive,2024-05-26,2024-07-02,2222,9.8,Neural Networks Co +AI03454,ML Ops Engineer,118265,SGD,153745,SE,PT,Singapore,M,Belgium,50,"Kubernetes, R, PyTorch, Git",PhD,8,Energy,2024-08-31,2024-11-01,1950,7.6,Advanced Robotics +AI03455,Computer Vision Engineer,75240,SGD,97812,EN,CT,Singapore,L,Kenya,100,"Azure, Kubernetes, NLP, Computer Vision",Bachelor,1,Technology,2024-05-15,2024-06-30,826,9.8,AI Innovations +AI03456,Research Scientist,65569,USD,65569,EN,FL,Israel,M,Switzerland,50,"GCP, Java, MLOps",PhD,1,Gaming,2024-04-16,2024-06-20,2302,6.3,Predictive Systems +AI03457,Data Scientist,205247,USD,205247,EX,FL,Denmark,S,Denmark,0,"Docker, Kubernetes, Git, SQL",PhD,17,Real Estate,2024-01-16,2024-03-22,1888,7.3,Digital Transformation LLC +AI03458,Data Scientist,37999,USD,37999,MI,CT,India,L,India,100,"Statistics, GCP, MLOps",PhD,4,Government,2024-12-20,2025-01-20,1159,6.2,Quantum Computing Inc +AI03459,Data Engineer,136750,JPY,15042500,SE,CT,Japan,M,Japan,100,"Tableau, Linux, TensorFlow, MLOps",Associate,7,Consulting,2024-03-17,2024-04-10,939,6.6,Neural Networks Co +AI03460,AI Product Manager,55482,USD,55482,EN,FL,Finland,M,Finland,100,"Python, Data Visualization, TensorFlow, Deep Learning",Associate,1,Consulting,2025-02-28,2025-04-05,2469,7.1,DeepTech Ventures +AI03461,Principal Data Scientist,126580,AUD,170883,MI,CT,Australia,L,Australia,0,"Data Visualization, GCP, Computer Vision, Kubernetes",Bachelor,2,Consulting,2025-04-24,2025-06-07,1369,5.4,AI Innovations +AI03462,Deep Learning Engineer,45523,USD,45523,MI,PT,China,L,Switzerland,0,"Spark, GCP, Hadoop, SQL",PhD,2,Retail,2024-08-11,2024-10-17,733,7.2,Future Systems +AI03463,Computer Vision Engineer,69117,USD,69117,MI,PT,Finland,S,New Zealand,0,"Deep Learning, AWS, Docker",Master,4,Finance,2025-03-02,2025-03-30,1948,9.6,Algorithmic Solutions +AI03464,Robotics Engineer,147154,USD,147154,MI,PT,United States,L,United States,0,"MLOps, Scala, SQL, PyTorch, NLP",Master,3,Education,2025-03-07,2025-04-23,1786,8.8,Advanced Robotics +AI03465,Computer Vision Engineer,129411,EUR,109999,SE,CT,Germany,M,Germany,0,"Azure, SQL, NLP, Deep Learning",Associate,6,Retail,2024-04-02,2024-04-25,2001,7.2,Cloud AI Solutions +AI03466,NLP Engineer,103365,AUD,139543,SE,CT,Australia,S,Australia,0,"Hadoop, Statistics, GCP, MLOps, Spark",PhD,7,Education,2024-07-17,2024-09-21,1363,7.2,TechCorp Inc +AI03467,Machine Learning Researcher,155656,USD,155656,SE,FL,United States,L,United States,50,"Deep Learning, R, PyTorch, Docker, Linux",Master,8,Transportation,2025-02-23,2025-03-28,2452,7.1,Cloud AI Solutions +AI03468,Deep Learning Engineer,60372,EUR,51316,EN,PT,Netherlands,M,Netherlands,100,"SQL, GCP, Java",Bachelor,1,Gaming,2024-01-14,2024-02-19,1363,7.7,TechCorp Inc +AI03469,Machine Learning Engineer,90624,EUR,77030,SE,FT,Austria,S,Spain,50,"GCP, Hadoop, PyTorch",Associate,8,Retail,2025-02-24,2025-04-08,655,8.9,Autonomous Tech +AI03470,Principal Data Scientist,28839,USD,28839,EN,CT,China,S,Estonia,50,"Scala, Python, SQL",Master,1,Real Estate,2024-08-20,2024-10-18,1826,10,Cognitive Computing +AI03471,Data Analyst,95397,EUR,81087,MI,FT,Germany,S,Germany,50,"Deep Learning, R, Spark",Bachelor,3,Healthcare,2024-02-06,2024-02-21,705,5.3,DataVision Ltd +AI03472,ML Ops Engineer,265922,JPY,29251420,EX,CT,Japan,L,United States,0,"GCP, Tableau, AWS, SQL",Associate,16,Energy,2024-03-16,2024-05-01,1345,5.6,Predictive Systems +AI03473,NLP Engineer,123952,CHF,111557,MI,CT,Switzerland,M,Switzerland,50,"PyTorch, Java, Git, Computer Vision",Bachelor,2,Automotive,2024-05-14,2024-06-20,713,8.8,Cloud AI Solutions +AI03474,Data Scientist,243390,EUR,206882,EX,FT,Germany,M,Indonesia,100,"Linux, PyTorch, Tableau, Java, Git",Bachelor,12,Automotive,2024-12-01,2024-12-31,1715,9,Cognitive Computing +AI03475,Autonomous Systems Engineer,86886,JPY,9557460,MI,FT,Japan,M,Poland,100,"Kubernetes, Tableau, Azure, NLP, Python",Associate,2,Energy,2024-12-23,2025-02-26,1947,8.7,Machine Intelligence Group +AI03476,Machine Learning Researcher,86470,CHF,77823,EN,FT,Switzerland,S,Switzerland,0,"Python, Java, GCP, NLP",PhD,1,Education,2024-11-30,2024-12-14,1713,6.3,Cloud AI Solutions +AI03477,Principal Data Scientist,128696,EUR,109392,SE,PT,France,L,Malaysia,0,"Git, Linux, Data Visualization, PyTorch",Associate,6,Energy,2024-10-05,2024-11-14,1015,6.2,Autonomous Tech +AI03478,Data Analyst,108456,USD,108456,MI,CT,United States,L,United States,0,"TensorFlow, Deep Learning, Kubernetes, Python",Bachelor,2,Retail,2024-05-19,2024-07-04,1400,5.5,Machine Intelligence Group +AI03479,Data Engineer,114242,USD,114242,SE,FT,Ireland,M,Ireland,0,"Statistics, R, Scala",Master,9,Retail,2024-08-03,2024-09-22,2189,6.4,Smart Analytics +AI03480,Data Engineer,94224,USD,94224,MI,CT,Finland,L,Finland,0,"Spark, Scala, Computer Vision, Mathematics",PhD,2,Technology,2024-10-10,2024-12-14,540,9.2,TechCorp Inc +AI03481,Data Engineer,277483,SGD,360728,EX,FL,Singapore,L,Singapore,50,"MLOps, Spark, Data Visualization, Hadoop",Bachelor,19,Finance,2024-07-30,2024-09-09,770,9.7,Cognitive Computing +AI03482,Computer Vision Engineer,40704,USD,40704,MI,FT,China,M,China,50,"NLP, PyTorch, Tableau, Git, Docker",PhD,2,Media,2024-03-06,2024-05-10,795,6.8,TechCorp Inc +AI03483,Machine Learning Engineer,93238,EUR,79252,EN,CT,Netherlands,L,Portugal,100,"AWS, Statistics, Hadoop",PhD,1,Finance,2024-03-20,2024-05-24,2049,7.8,DeepTech Ventures +AI03484,Machine Learning Researcher,196588,CHF,176929,SE,FT,Switzerland,M,Estonia,0,"Data Visualization, Docker, R",Associate,9,Energy,2024-07-03,2024-09-04,1947,7.5,Autonomous Tech +AI03485,AI Software Engineer,90440,GBP,67830,MI,PT,United Kingdom,M,United Kingdom,50,"PyTorch, AWS, Computer Vision, NLP, GCP",Master,2,Energy,2025-03-19,2025-04-30,2326,6.6,Neural Networks Co +AI03486,AI Consultant,150604,USD,150604,MI,FT,Denmark,L,India,100,"Hadoop, Mathematics, GCP, Kubernetes, MLOps",Associate,2,Gaming,2024-09-03,2024-09-26,762,6.4,Advanced Robotics +AI03487,ML Ops Engineer,58876,USD,58876,SE,PT,India,L,India,0,"MLOps, GCP, SQL",Master,8,Government,2024-11-02,2025-01-02,730,6.3,AI Innovations +AI03488,AI Product Manager,28266,USD,28266,MI,CT,India,S,India,100,"NLP, Data Visualization, Tableau, Mathematics, MLOps",Master,2,Telecommunications,2025-01-26,2025-03-18,901,9.2,TechCorp Inc +AI03489,Research Scientist,83652,CAD,104565,MI,FL,Canada,M,Nigeria,100,"Azure, Tableau, Linux, AWS, Docker",Master,3,Energy,2025-02-01,2025-03-14,2027,6,AI Innovations +AI03490,AI Specialist,69368,USD,69368,EN,FT,Norway,S,Israel,50,"Spark, Python, Git, Azure",Associate,1,Manufacturing,2024-05-16,2024-06-08,1302,7.8,Autonomous Tech +AI03491,Head of AI,130656,USD,130656,SE,PT,Israel,L,Israel,50,"SQL, Mathematics, TensorFlow",PhD,9,Government,2025-02-21,2025-04-01,1038,5.4,Autonomous Tech +AI03492,AI Architect,168459,EUR,143190,SE,PT,Germany,L,Germany,0,"Spark, Hadoop, Scala, MLOps, R",Associate,6,Telecommunications,2024-04-07,2024-04-22,2246,7.9,Advanced Robotics +AI03493,Data Scientist,72394,AUD,97732,MI,CT,Australia,S,Ghana,100,"Deep Learning, GCP, SQL, Python",Master,4,Technology,2024-08-06,2024-08-28,882,6.4,Predictive Systems +AI03494,Principal Data Scientist,37641,USD,37641,MI,FL,India,M,India,0,"Python, Hadoop, SQL, Git, AWS",Master,2,Technology,2025-01-16,2025-03-08,897,5.7,Smart Analytics +AI03495,Deep Learning Engineer,109311,USD,109311,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Hadoop, Python, Linux",Bachelor,2,Government,2024-09-13,2024-11-21,2222,6.1,Algorithmic Solutions +AI03496,Machine Learning Engineer,237727,USD,237727,EX,FL,Denmark,M,Austria,50,"Python, NLP, Data Visualization",Bachelor,16,Telecommunications,2024-03-15,2024-05-25,728,7.3,Advanced Robotics +AI03497,AI Consultant,138467,USD,138467,EX,FT,Sweden,M,Sweden,0,"Python, Hadoop, SQL, Computer Vision",Associate,19,Technology,2024-07-21,2024-08-08,612,10,Digital Transformation LLC +AI03498,Head of AI,125705,EUR,106849,SE,FL,France,M,France,100,"PyTorch, Python, Scala",Bachelor,9,Energy,2024-11-06,2024-12-03,2098,8.1,AI Innovations +AI03499,ML Ops Engineer,107784,USD,107784,MI,PT,Norway,L,Norway,0,"SQL, Statistics, Data Visualization, Python, Mathematics",Bachelor,4,Technology,2024-07-07,2024-09-17,1589,5.9,TechCorp Inc +AI03500,Computer Vision Engineer,49527,USD,49527,SE,CT,India,M,India,0,"Python, Scala, AWS",Master,6,Media,2024-11-03,2025-01-11,1906,9.6,Advanced Robotics +AI03501,AI Software Engineer,73779,JPY,8115690,EN,PT,Japan,S,Poland,0,"Python, Azure, Statistics",Bachelor,1,Transportation,2024-07-05,2024-08-26,1183,10,Digital Transformation LLC +AI03502,AI Consultant,98422,USD,98422,MI,FL,United States,L,United States,50,"SQL, GCP, Statistics, Hadoop, Linux",PhD,3,Real Estate,2024-06-18,2024-07-16,2175,5.9,Algorithmic Solutions +AI03503,Principal Data Scientist,110310,SGD,143403,MI,PT,Singapore,L,Singapore,100,"PyTorch, Deep Learning, Spark",Associate,4,Retail,2025-02-28,2025-03-27,1821,6.7,Future Systems +AI03504,ML Ops Engineer,167443,EUR,142327,EX,FL,Austria,M,Austria,50,"R, Scala, NLP",Master,19,Transportation,2024-12-25,2025-01-21,2422,6.3,Cloud AI Solutions +AI03505,Machine Learning Engineer,135296,SGD,175885,SE,FT,Singapore,S,Singapore,0,"Spark, Kubernetes, Computer Vision",Associate,7,Media,2024-02-18,2024-03-07,2274,9.6,TechCorp Inc +AI03506,Data Scientist,101322,SGD,131719,MI,CT,Singapore,L,Singapore,100,"TensorFlow, Data Visualization, Git",Master,4,Technology,2024-10-30,2024-11-16,1477,9,AI Innovations +AI03507,AI Consultant,81204,AUD,109625,MI,FL,Australia,S,Australia,100,"Python, Hadoop, Linux, NLP, Statistics",PhD,2,Education,2024-01-07,2024-01-30,2214,5.5,DataVision Ltd +AI03508,Machine Learning Engineer,216778,USD,216778,EX,CT,United States,M,United States,100,"AWS, Azure, MLOps",Bachelor,12,Consulting,2024-06-22,2024-07-24,2366,6.3,DeepTech Ventures +AI03509,Computer Vision Engineer,176928,AUD,238853,EX,FL,Australia,M,Australia,100,"GCP, Git, Hadoop",PhD,14,Real Estate,2024-11-29,2025-01-15,1015,5.7,Neural Networks Co +AI03510,Research Scientist,76676,USD,76676,SE,PT,South Korea,S,Russia,0,"Java, SQL, MLOps, Mathematics, Hadoop",PhD,7,Retail,2024-05-27,2024-07-09,2390,9.1,Smart Analytics +AI03511,Data Analyst,167099,USD,167099,SE,PT,United States,L,United States,0,"R, Git, MLOps",PhD,7,Energy,2024-07-03,2024-07-30,720,8.7,Cognitive Computing +AI03512,ML Ops Engineer,89898,USD,89898,SE,CT,South Korea,M,South Korea,50,"SQL, Azure, Scala, MLOps, Python",Master,5,Transportation,2025-03-11,2025-03-30,1286,6,Quantum Computing Inc +AI03513,Robotics Engineer,123146,USD,123146,SE,PT,South Korea,M,South Korea,50,"Spark, Python, Linux, Statistics, Tableau",Master,9,Technology,2024-03-25,2024-05-03,1632,8,Predictive Systems +AI03514,ML Ops Engineer,244148,USD,244148,EX,FT,Denmark,L,Australia,50,"AWS, Python, TensorFlow, PyTorch, Scala",PhD,16,Transportation,2024-12-29,2025-01-14,1215,8.8,AI Innovations +AI03515,Machine Learning Researcher,212784,CHF,191506,EX,FT,Switzerland,S,Switzerland,50,"NLP, Linux, Python, R, TensorFlow",Bachelor,14,Manufacturing,2025-02-25,2025-04-06,689,9.1,Predictive Systems +AI03516,Principal Data Scientist,206443,AUD,278698,EX,PT,Australia,M,Australia,0,"Python, Kubernetes, GCP",Master,15,Gaming,2024-04-27,2024-06-19,2094,7.6,Future Systems +AI03517,ML Ops Engineer,55944,JPY,6153840,EN,FT,Japan,M,Japan,50,"MLOps, Java, R",Bachelor,0,Technology,2024-04-28,2024-05-26,1744,9.3,Machine Intelligence Group +AI03518,Autonomous Systems Engineer,71392,USD,71392,EN,FL,Sweden,S,Sweden,50,"Linux, Statistics, SQL, Git, Mathematics",Bachelor,1,Gaming,2024-05-05,2024-06-28,1567,8.5,Cloud AI Solutions +AI03519,Principal Data Scientist,126751,CAD,158439,SE,PT,Canada,M,Latvia,0,"Git, Java, R, GCP, SQL",Master,8,Technology,2025-01-24,2025-02-23,1506,7.2,Predictive Systems +AI03520,AI Specialist,99185,USD,99185,SE,CT,Finland,M,Finland,50,"GCP, Python, Linux, SQL",Bachelor,5,Retail,2024-01-20,2024-03-13,599,9.6,Cognitive Computing +AI03521,Machine Learning Engineer,218350,AUD,294773,EX,CT,Australia,S,Australia,0,"PyTorch, Tableau, TensorFlow",Master,16,Media,2024-10-28,2024-12-03,909,8.7,Algorithmic Solutions +AI03522,Principal Data Scientist,123624,SGD,160711,MI,PT,Singapore,L,Singapore,100,"PyTorch, Scala, Computer Vision, Spark",Associate,3,Automotive,2024-08-25,2024-09-25,1195,9.5,Cloud AI Solutions +AI03523,AI Research Scientist,150816,USD,150816,EX,PT,Ireland,S,Nigeria,50,"Python, AWS, Computer Vision, Docker, Data Visualization",PhD,18,Technology,2024-10-24,2024-12-09,1118,6.4,TechCorp Inc +AI03524,Computer Vision Engineer,248052,CAD,310065,EX,PT,Canada,L,Canada,0,"Docker, Scala, Data Visualization, Azure, Spark",Master,15,Real Estate,2024-08-08,2024-09-20,1640,6,Predictive Systems +AI03525,Research Scientist,174068,SGD,226288,SE,CT,Singapore,L,Singapore,100,"Mathematics, PyTorch, TensorFlow",Associate,9,Transportation,2024-12-06,2024-12-21,1050,8.7,Smart Analytics +AI03526,Data Analyst,202119,USD,202119,EX,CT,South Korea,L,South Korea,50,"NLP, Python, Spark, TensorFlow",Bachelor,13,Transportation,2024-07-08,2024-08-24,1755,6.6,Cloud AI Solutions +AI03527,AI Research Scientist,52293,USD,52293,EX,CT,India,M,India,50,"AWS, Docker, Statistics",Associate,10,Real Estate,2024-05-25,2024-07-01,2424,5.9,Quantum Computing Inc +AI03528,Machine Learning Researcher,127194,EUR,108115,EX,FL,France,S,France,100,"PyTorch, Docker, TensorFlow, Deep Learning",Associate,10,Real Estate,2024-01-05,2024-03-05,853,7.6,Neural Networks Co +AI03529,Machine Learning Researcher,133885,USD,133885,MI,FT,United States,L,United States,100,"Hadoop, Spark, Tableau",PhD,3,Automotive,2025-01-28,2025-02-23,1070,8.6,Digital Transformation LLC +AI03530,AI Software Engineer,134073,EUR,113962,SE,CT,France,M,France,0,"Hadoop, MLOps, Linux, Spark",Associate,9,Automotive,2024-07-17,2024-08-29,2452,8.7,Predictive Systems +AI03531,Data Analyst,128939,CAD,161174,SE,PT,Canada,L,Canada,100,"Data Visualization, Deep Learning, SQL, MLOps, Java",PhD,5,Telecommunications,2024-11-27,2025-01-24,824,5.1,DeepTech Ventures +AI03532,Data Scientist,65196,USD,65196,MI,PT,Ireland,S,Ireland,0,"GCP, Git, NLP, PyTorch, Statistics",PhD,4,Finance,2025-03-23,2025-04-15,1393,7.4,Cloud AI Solutions +AI03533,Deep Learning Engineer,122554,USD,122554,MI,FL,Ireland,L,Ireland,100,"Kubernetes, R, Python, AWS",Associate,2,Real Estate,2024-12-16,2025-02-05,1118,6.5,DeepTech Ventures +AI03534,NLP Engineer,72995,EUR,62046,EN,CT,Netherlands,S,Kenya,100,"Mathematics, R, Python, Docker, PyTorch",Master,1,Consulting,2024-07-24,2024-08-28,1205,8.6,DeepTech Ventures +AI03535,AI Architect,36919,USD,36919,SE,FT,India,M,India,100,"Hadoop, Scala, Python, Docker",PhD,9,Real Estate,2025-01-26,2025-03-26,842,8.7,Smart Analytics +AI03536,Computer Vision Engineer,111161,JPY,12227710,SE,CT,Japan,S,Japan,50,"Git, Linux, GCP, AWS, SQL",Bachelor,5,Technology,2024-03-01,2024-05-03,999,7.6,AI Innovations +AI03537,Principal Data Scientist,226559,USD,226559,EX,PT,South Korea,L,Argentina,50,"R, Python, Azure, SQL",PhD,11,Consulting,2024-01-27,2024-04-06,679,8,Future Systems +AI03538,AI Product Manager,194134,USD,194134,EX,FT,United States,M,United States,0,"Scala, Docker, Data Visualization, Kubernetes, PyTorch",Bachelor,11,Gaming,2024-08-19,2024-10-01,653,7.3,DataVision Ltd +AI03539,Machine Learning Engineer,48340,CAD,60425,EN,CT,Canada,S,Canada,100,"PyTorch, R, Data Visualization",Bachelor,0,Finance,2024-11-06,2024-12-21,2251,8.2,Future Systems +AI03540,ML Ops Engineer,93478,USD,93478,MI,FL,Sweden,S,Sweden,100,"AWS, SQL, Mathematics",PhD,4,Gaming,2024-01-25,2024-03-18,990,8.9,Cognitive Computing +AI03541,AI Specialist,135053,GBP,101290,SE,FT,United Kingdom,L,United Kingdom,0,"Azure, Deep Learning, TensorFlow",Bachelor,9,Education,2024-04-18,2024-06-23,974,5.4,DataVision Ltd +AI03542,AI Specialist,118702,AUD,160248,SE,CT,Australia,M,New Zealand,50,"AWS, MLOps, Hadoop, NLP, R",Master,5,Government,2025-01-21,2025-03-23,2213,8.3,Neural Networks Co +AI03543,Computer Vision Engineer,66189,USD,66189,EN,CT,Ireland,S,Ireland,0,"Scala, Kubernetes, Python",Associate,1,Education,2024-02-09,2024-03-03,1274,7.5,Quantum Computing Inc +AI03544,NLP Engineer,135922,USD,135922,SE,FL,Finland,M,Finland,100,"Hadoop, Statistics, Azure",Bachelor,8,Finance,2024-03-07,2024-04-24,2462,9.3,Autonomous Tech +AI03545,AI Research Scientist,220929,USD,220929,SE,FT,Denmark,L,Denmark,50,"Linux, Azure, Spark",Master,8,Energy,2024-01-17,2024-03-26,2021,5.8,Machine Intelligence Group +AI03546,NLP Engineer,82829,JPY,9111190,MI,FT,Japan,M,Japan,100,"Spark, Kubernetes, NLP, Hadoop",Associate,2,Technology,2025-04-05,2025-04-29,1930,7.3,Smart Analytics +AI03547,NLP Engineer,91897,AUD,124061,MI,PT,Australia,S,Australia,50,"MLOps, PyTorch, TensorFlow",PhD,3,Manufacturing,2024-09-30,2024-10-16,533,5.1,DataVision Ltd +AI03548,Research Scientist,120965,USD,120965,MI,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Kubernetes",Master,4,Media,2024-01-02,2024-02-08,2239,9.6,Advanced Robotics +AI03549,Machine Learning Engineer,310818,CHF,279736,EX,PT,Switzerland,S,Switzerland,100,"SQL, Python, MLOps, Java, Mathematics",Bachelor,18,Technology,2025-01-27,2025-03-30,1771,6.4,Smart Analytics +AI03550,Deep Learning Engineer,73677,EUR,62625,EN,FL,Austria,L,Austria,50,"SQL, Git, Linux, AWS",Bachelor,0,Technology,2024-07-30,2024-08-30,1254,6.4,Quantum Computing Inc +AI03551,Principal Data Scientist,71156,USD,71156,EN,CT,United States,L,India,0,"Azure, Mathematics, Kubernetes, Deep Learning, Data Visualization",Associate,0,Government,2024-02-17,2024-03-16,2491,7.6,Digital Transformation LLC +AI03552,AI Software Engineer,190140,EUR,161619,EX,PT,Germany,M,Germany,100,"MLOps, Data Visualization, Python, TensorFlow, Deep Learning",Master,17,Real Estate,2024-07-04,2024-07-26,1541,7.4,Future Systems +AI03553,ML Ops Engineer,133027,EUR,113073,SE,FT,Austria,L,Austria,50,"Spark, Linux, Java, PyTorch",Master,5,Telecommunications,2024-08-09,2024-08-27,901,6,Smart Analytics +AI03554,Research Scientist,232210,USD,232210,EX,PT,South Korea,L,Spain,50,"Scala, PyTorch, AWS, Spark, SQL",Master,15,Consulting,2024-08-07,2024-09-05,2085,5,Cognitive Computing +AI03555,Data Analyst,113916,GBP,85437,SE,FT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Hadoop, R, AWS",Associate,8,Energy,2024-05-12,2024-07-02,2364,6,AI Innovations +AI03556,Head of AI,228576,SGD,297149,EX,PT,Singapore,M,Singapore,0,"GCP, Java, SQL, Git",Associate,13,Education,2024-07-25,2024-09-03,1965,7.8,Smart Analytics +AI03557,Machine Learning Researcher,25011,USD,25011,EN,CT,China,M,Portugal,0,"SQL, Linux, Hadoop, Mathematics",PhD,1,Manufacturing,2024-09-01,2024-11-03,1692,9.1,Algorithmic Solutions +AI03558,AI Product Manager,139200,USD,139200,SE,PT,Sweden,M,Sweden,0,"Git, Azure, Tableau, MLOps",Master,5,Energy,2024-05-31,2024-07-16,1241,9.1,Machine Intelligence Group +AI03559,Computer Vision Engineer,292522,CHF,263270,EX,FL,Switzerland,S,Switzerland,0,"R, Java, Tableau, MLOps",Associate,15,Consulting,2024-01-01,2024-01-27,824,7,Machine Intelligence Group +AI03560,AI Specialist,159257,USD,159257,SE,FL,Denmark,L,Denmark,100,"R, TensorFlow, Data Visualization, Tableau, NLP",PhD,5,Healthcare,2024-10-03,2024-12-14,1309,9.8,Quantum Computing Inc +AI03561,AI Research Scientist,108189,USD,108189,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, Azure, GCP, Scala",Master,5,Media,2025-02-26,2025-03-30,1421,5.9,Neural Networks Co +AI03562,Robotics Engineer,112943,USD,112943,SE,CT,Sweden,M,Sweden,100,"SQL, Statistics, Tableau",Master,7,Media,2024-01-16,2024-02-02,1584,7.4,AI Innovations +AI03563,Data Engineer,101976,SGD,132569,MI,CT,Singapore,M,Singapore,50,"Python, Computer Vision, Git",Master,2,Technology,2024-08-24,2024-11-02,2384,6.8,Machine Intelligence Group +AI03564,Principal Data Scientist,90165,GBP,67624,EN,CT,United Kingdom,L,United Kingdom,100,"GCP, Hadoop, Statistics, Computer Vision",Bachelor,1,Technology,2024-05-21,2024-06-15,700,6.6,Cloud AI Solutions +AI03565,ML Ops Engineer,179183,JPY,19710130,EX,CT,Japan,S,Japan,100,"Scala, R, Kubernetes, Python, Docker",Master,18,Real Estate,2024-05-30,2024-06-27,1393,7.2,Digital Transformation LLC +AI03566,NLP Engineer,113638,EUR,96592,SE,PT,Netherlands,M,South Africa,50,"SQL, Python, TensorFlow, Statistics, PyTorch",Bachelor,5,Transportation,2025-04-18,2025-05-12,2288,5.5,Predictive Systems +AI03567,Data Analyst,50907,SGD,66179,EN,PT,Singapore,S,Singapore,0,"Hadoop, SQL, Statistics",Bachelor,0,Manufacturing,2025-03-29,2025-04-26,902,7.7,Smart Analytics +AI03568,AI Consultant,167654,EUR,142506,EX,PT,France,M,France,50,"Kubernetes, Mathematics, Linux, SQL",Bachelor,13,Consulting,2025-04-07,2025-05-27,2217,7.5,DeepTech Ventures +AI03569,Machine Learning Researcher,119056,CHF,107150,MI,FL,Switzerland,S,Switzerland,50,"Docker, Python, Tableau",Master,2,Gaming,2024-09-02,2024-11-02,2403,8.9,Autonomous Tech +AI03570,Autonomous Systems Engineer,95121,USD,95121,MI,PT,United States,M,Poland,0,"Python, TensorFlow, Azure, NLP",PhD,2,Retail,2025-01-26,2025-02-24,1927,7.1,Smart Analytics +AI03571,AI Architect,111821,JPY,12300310,MI,FL,Japan,L,Turkey,50,"Linux, AWS, MLOps, SQL",Master,4,Healthcare,2024-03-04,2024-04-30,1694,5.8,Cognitive Computing +AI03572,Principal Data Scientist,183873,GBP,137905,EX,FT,United Kingdom,M,United Kingdom,0,"PyTorch, Git, Computer Vision, Java, MLOps",Associate,18,Education,2024-07-04,2024-08-04,684,6.5,AI Innovations +AI03573,AI Architect,247623,CHF,222861,EX,FL,Switzerland,L,Switzerland,100,"Java, Statistics, R, SQL, MLOps",PhD,15,Retail,2024-12-12,2025-01-15,2363,9,Future Systems +AI03574,AI Product Manager,70419,USD,70419,SE,FL,China,M,China,0,"Hadoop, Scala, Tableau, PyTorch, Mathematics",PhD,5,Manufacturing,2024-02-15,2024-03-04,1299,5.4,Advanced Robotics +AI03575,AI Architect,80822,CAD,101028,MI,CT,Canada,M,Canada,50,"Kubernetes, Git, Python, Docker",Bachelor,2,Real Estate,2024-11-12,2024-12-22,2216,8.2,DataVision Ltd +AI03576,AI Research Scientist,116798,USD,116798,MI,FL,United States,L,United States,100,"Python, AWS, Tableau, Computer Vision",Associate,2,Media,2024-09-08,2024-11-09,1703,9,Advanced Robotics +AI03577,AI Consultant,32773,USD,32773,EN,PT,India,L,India,50,"Python, MLOps, R, Java",Master,1,Transportation,2024-11-20,2024-12-12,1687,5.4,Machine Intelligence Group +AI03578,AI Research Scientist,153325,AUD,206989,EX,PT,Australia,S,Australia,100,"Kubernetes, Deep Learning, Scala, Linux",Bachelor,18,Energy,2025-04-30,2025-07-11,951,9.7,DeepTech Ventures +AI03579,AI Consultant,139637,EUR,118691,SE,FL,Germany,L,Germany,0,"AWS, Hadoop, MLOps",Associate,9,Retail,2025-03-20,2025-04-09,2137,6.9,Neural Networks Co +AI03580,AI Product Manager,228479,CHF,205631,SE,FT,Switzerland,L,Switzerland,0,"Git, Linux, Spark, Python, GCP",Bachelor,6,Real Estate,2025-04-24,2025-05-30,630,7.4,DeepTech Ventures +AI03581,Data Analyst,213432,USD,213432,EX,FL,Denmark,S,Norway,0,"Kubernetes, NLP, Azure",PhD,14,Automotive,2024-11-14,2024-12-30,1371,9.8,TechCorp Inc +AI03582,Data Scientist,120417,USD,120417,SE,FL,Norway,S,Norway,50,"Python, TensorFlow, GCP, Statistics",Master,7,Real Estate,2024-09-01,2024-10-28,1954,8,Autonomous Tech +AI03583,Computer Vision Engineer,128062,USD,128062,MI,FL,Denmark,S,Denmark,50,"R, Spark, Statistics, Deep Learning",Master,3,Transportation,2024-07-19,2024-09-28,2040,8.6,Quantum Computing Inc +AI03584,AI Product Manager,152788,EUR,129870,SE,FT,France,L,France,100,"Statistics, Deep Learning, Java, Docker",Associate,8,Gaming,2024-08-17,2024-10-28,1390,7.1,Smart Analytics +AI03585,Data Engineer,151742,EUR,128981,EX,PT,France,L,France,0,"TensorFlow, Python, NLP",Bachelor,19,Gaming,2024-06-28,2024-07-21,816,8.9,DeepTech Ventures +AI03586,Robotics Engineer,127281,USD,127281,SE,FL,South Korea,L,South Korea,100,"Deep Learning, Kubernetes, Linux, Mathematics, Hadoop",PhD,8,Gaming,2024-12-15,2025-02-23,2078,7.3,Future Systems +AI03587,Autonomous Systems Engineer,95779,CAD,119724,MI,PT,Canada,M,Canada,50,"Python, Computer Vision, SQL",Associate,2,Real Estate,2025-01-07,2025-01-28,1351,6.2,Future Systems +AI03588,AI Software Engineer,127704,AUD,172400,SE,CT,Australia,L,Australia,0,"SQL, Python, Git, Statistics, MLOps",Associate,5,Automotive,2024-01-22,2024-02-17,2062,9.4,TechCorp Inc +AI03589,Computer Vision Engineer,119308,CAD,149135,SE,FL,Canada,S,Canada,50,"Computer Vision, Hadoop, Python, GCP",Bachelor,8,Education,2025-01-01,2025-01-15,564,8,Machine Intelligence Group +AI03590,ML Ops Engineer,62680,AUD,84618,EN,FT,Australia,M,Australia,50,"GCP, Java, SQL, R",Associate,1,Technology,2024-11-07,2024-12-18,2105,6.6,Advanced Robotics +AI03591,Data Scientist,272438,AUD,367791,EX,PT,Australia,L,Norway,50,"AWS, Scala, NLP, PyTorch",PhD,17,Consulting,2024-03-10,2024-04-13,1144,8.1,Cognitive Computing +AI03592,AI Software Engineer,174329,EUR,148180,SE,CT,Netherlands,L,Netherlands,100,"R, NLP, Java",Master,7,Energy,2024-04-30,2024-05-27,1675,7,Smart Analytics +AI03593,Computer Vision Engineer,46653,USD,46653,EN,CT,Israel,S,Israel,0,"Python, GCP, Statistics",Associate,0,Technology,2024-04-20,2024-06-27,2203,5.6,DeepTech Ventures +AI03594,Head of AI,173890,USD,173890,EX,FT,Israel,M,Israel,100,"MLOps, Python, TensorFlow, Data Visualization, GCP",Associate,17,Finance,2024-04-08,2024-05-19,1771,6.1,Cloud AI Solutions +AI03595,Deep Learning Engineer,338945,CHF,305051,EX,FT,Switzerland,M,Switzerland,50,"MLOps, Git, Statistics",Master,14,Government,2024-04-06,2024-06-02,817,9.6,Advanced Robotics +AI03596,AI Architect,140480,USD,140480,SE,PT,South Korea,L,South Korea,50,"Deep Learning, AWS, Tableau, Azure",Master,7,Retail,2024-06-19,2024-08-10,863,5.1,Cognitive Computing +AI03597,Data Engineer,92646,USD,92646,MI,FT,Israel,S,Israel,100,"Spark, R, Statistics",PhD,2,Education,2024-06-07,2024-08-18,832,6.9,Autonomous Tech +AI03598,Data Engineer,54404,USD,54404,EX,PT,India,M,India,0,"PyTorch, MLOps, TensorFlow",PhD,10,Media,2024-05-05,2024-07-17,875,8.9,Machine Intelligence Group +AI03599,AI Specialist,113043,GBP,84782,SE,CT,United Kingdom,M,United Kingdom,0,"Deep Learning, Computer Vision, Tableau, Spark",PhD,8,Consulting,2025-01-30,2025-04-05,1712,8.2,Digital Transformation LLC +AI03600,Data Analyst,159400,EUR,135490,EX,CT,France,S,Turkey,50,"Deep Learning, Mathematics, TensorFlow",Bachelor,14,Real Estate,2025-01-23,2025-02-21,1732,8.4,Machine Intelligence Group +AI03601,Deep Learning Engineer,31170,USD,31170,EN,FL,China,S,South Africa,0,"Kubernetes, TensorFlow, MLOps",PhD,0,Transportation,2024-11-01,2024-12-09,1498,8.8,Advanced Robotics +AI03602,Principal Data Scientist,108438,USD,108438,MI,FL,Sweden,M,Indonesia,0,"Docker, NLP, Python",Bachelor,2,Real Estate,2024-08-02,2024-08-19,1635,8.9,Smart Analytics +AI03603,AI Architect,111346,USD,111346,SE,FT,United States,S,Indonesia,50,"Scala, Python, TensorFlow, Kubernetes, Statistics",Bachelor,7,Retail,2024-11-11,2024-12-01,970,9,Predictive Systems +AI03604,Deep Learning Engineer,223449,USD,223449,EX,FT,Denmark,S,Denmark,0,"Linux, Computer Vision, Git",Associate,16,Real Estate,2024-03-13,2024-04-26,1483,5.9,AI Innovations +AI03605,Computer Vision Engineer,48324,USD,48324,EN,FT,Sweden,S,Poland,50,"Docker, Azure, Tableau, Kubernetes",Bachelor,0,Telecommunications,2024-10-10,2024-11-19,1822,9.4,AI Innovations +AI03606,Autonomous Systems Engineer,66696,AUD,90040,EN,FT,Australia,M,Australia,100,"Docker, Scala, Computer Vision, Git",Bachelor,1,Retail,2024-07-01,2024-07-29,1526,6.5,Smart Analytics +AI03607,AI Research Scientist,210386,USD,210386,EX,CT,Sweden,S,Sweden,50,"Java, Git, GCP",Bachelor,16,Consulting,2024-11-30,2025-02-01,883,8.6,DataVision Ltd +AI03608,Machine Learning Researcher,48698,USD,48698,MI,CT,China,M,China,0,"Python, Java, AWS, NLP",PhD,3,Finance,2024-11-22,2024-12-16,1110,8,Smart Analytics +AI03609,Machine Learning Researcher,60193,EUR,51164,EN,CT,Austria,M,Austria,50,"Python, TensorFlow, Azure, SQL, PyTorch",Bachelor,0,Government,2024-02-12,2024-03-01,526,5.1,Cognitive Computing +AI03610,AI Specialist,60740,USD,60740,EN,PT,United States,M,United States,100,"AWS, R, Deep Learning, Python, Scala",Bachelor,0,Consulting,2024-03-20,2024-05-12,1052,7.3,Future Systems +AI03611,AI Specialist,118920,USD,118920,MI,CT,Norway,S,Canada,0,"Deep Learning, SQL, Statistics, Mathematics, Java",Master,3,Education,2024-08-19,2024-09-15,1491,5.2,Future Systems +AI03612,Principal Data Scientist,87000,AUD,117450,EN,CT,Australia,L,Australia,100,"R, SQL, Tableau",Associate,1,Finance,2024-07-31,2024-09-05,1336,6.9,DataVision Ltd +AI03613,Deep Learning Engineer,204824,USD,204824,EX,CT,Israel,M,Israel,0,"Hadoop, Computer Vision, Python, MLOps, Kubernetes",Bachelor,12,Media,2024-09-20,2024-10-10,1610,8.8,Advanced Robotics +AI03614,Principal Data Scientist,87194,USD,87194,MI,PT,Norway,S,Norway,0,"Computer Vision, Python, Tableau",Associate,2,Technology,2024-07-18,2024-08-07,1333,9.5,Neural Networks Co +AI03615,Autonomous Systems Engineer,232255,USD,232255,EX,CT,Norway,L,Portugal,100,"Deep Learning, Azure, PyTorch",Associate,16,Automotive,2024-05-28,2024-06-28,2132,9,Digital Transformation LLC +AI03616,Data Engineer,101827,USD,101827,MI,FL,Sweden,L,Sweden,50,"Azure, Docker, Git, NLP",Master,4,Telecommunications,2024-10-05,2024-11-08,1136,7.7,Future Systems +AI03617,Head of AI,240245,GBP,180184,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, R, Data Visualization, Computer Vision",PhD,16,Retail,2024-05-06,2024-06-15,1309,8.9,DeepTech Ventures +AI03618,Data Scientist,167576,USD,167576,SE,CT,Sweden,L,Sweden,50,"Tableau, Hadoop, R, Python",Bachelor,9,Energy,2025-03-06,2025-04-25,1628,8.3,Neural Networks Co +AI03619,AI Research Scientist,215103,CAD,268879,EX,CT,Canada,M,Canada,0,"Python, Git, TensorFlow, Docker, Linux",Master,13,Finance,2024-05-31,2024-07-24,1236,8.7,Smart Analytics +AI03620,Machine Learning Engineer,48369,EUR,41114,EN,PT,Austria,S,Austria,0,"GCP, Kubernetes, SQL, Hadoop, Docker",PhD,1,Telecommunications,2024-06-05,2024-07-18,2049,6.2,Quantum Computing Inc +AI03621,Research Scientist,133879,SGD,174043,SE,FT,Singapore,S,Singapore,100,"Docker, Scala, GCP, Deep Learning",Bachelor,9,Automotive,2024-09-25,2024-11-22,1927,5.1,Machine Intelligence Group +AI03622,Machine Learning Researcher,28565,USD,28565,EN,FT,China,L,China,100,"Statistics, Linux, SQL, Scala",Master,0,Healthcare,2025-02-23,2025-03-27,1764,5.4,Cognitive Computing +AI03623,ML Ops Engineer,159550,USD,159550,MI,PT,Denmark,L,Belgium,50,"Tableau, Linux, Kubernetes",PhD,3,Consulting,2024-01-17,2024-03-19,844,9.1,DataVision Ltd +AI03624,ML Ops Engineer,78403,EUR,66643,MI,FL,Netherlands,M,Netherlands,0,"MLOps, GCP, Data Visualization, Git",PhD,2,Automotive,2025-04-11,2025-05-16,1044,6.9,Neural Networks Co +AI03625,Head of AI,87867,USD,87867,EN,CT,Sweden,L,Sweden,50,"Linux, Git, Statistics",Associate,0,Consulting,2025-04-26,2025-07-06,2334,9.2,Algorithmic Solutions +AI03626,Machine Learning Engineer,116358,USD,116358,SE,CT,Israel,L,Norway,50,"NLP, Kubernetes, Docker, Deep Learning, GCP",Bachelor,8,Telecommunications,2025-01-28,2025-03-21,2472,5.1,Future Systems +AI03627,ML Ops Engineer,198454,SGD,257990,EX,PT,Singapore,L,Singapore,50,"Hadoop, Statistics, Mathematics, Kubernetes, R",Bachelor,18,Gaming,2024-02-05,2024-03-06,1969,5.8,AI Innovations +AI03628,Data Analyst,118657,EUR,100858,SE,PT,Germany,M,Germany,100,"MLOps, SQL, Kubernetes, Mathematics",Associate,6,Gaming,2024-12-03,2025-01-19,1755,8.6,DataVision Ltd +AI03629,Research Scientist,86457,USD,86457,EN,CT,Israel,L,Israel,100,"Mathematics, Java, Git, Linux, Computer Vision",Bachelor,1,Media,2024-04-05,2024-05-18,750,8.2,Digital Transformation LLC +AI03630,AI Research Scientist,52898,EUR,44963,EN,PT,France,M,Poland,50,"Scala, Tableau, Computer Vision, Java, Git",PhD,1,Energy,2024-12-15,2025-01-14,1017,7,Machine Intelligence Group +AI03631,Deep Learning Engineer,25159,USD,25159,EN,PT,India,M,India,50,"Data Visualization, Spark, AWS",Master,0,Manufacturing,2024-04-02,2024-06-11,615,5.5,Predictive Systems +AI03632,AI Research Scientist,67708,USD,67708,MI,CT,Ireland,S,Ireland,50,"Python, Java, SQL, Linux",Bachelor,4,Transportation,2024-04-19,2024-05-17,1446,8.5,Smart Analytics +AI03633,Machine Learning Engineer,214023,USD,214023,EX,FL,Denmark,L,South Korea,0,"R, SQL, Tableau, AWS, Java",Bachelor,13,Energy,2025-03-28,2025-04-20,1796,5.7,AI Innovations +AI03634,AI Product Manager,110880,SGD,144144,SE,CT,Singapore,M,Singapore,0,"MLOps, R, Linux, Python",Master,7,Retail,2024-02-15,2024-03-15,843,8.1,Cognitive Computing +AI03635,Data Engineer,49214,USD,49214,EN,CT,South Korea,M,Sweden,50,"AWS, Linux, Kubernetes",PhD,1,Healthcare,2025-01-05,2025-01-21,1103,6.9,Quantum Computing Inc +AI03636,Robotics Engineer,65197,USD,65197,MI,PT,South Korea,S,South Korea,50,"PyTorch, Hadoop, TensorFlow, Java",Associate,4,Technology,2024-12-04,2025-01-15,903,6.8,Quantum Computing Inc +AI03637,AI Consultant,94494,AUD,127567,MI,PT,Australia,S,Spain,50,"Kubernetes, SQL, Tableau",PhD,2,Real Estate,2024-10-10,2024-12-16,1260,6.6,AI Innovations +AI03638,ML Ops Engineer,93560,CHF,84204,EN,FL,Switzerland,M,China,50,"Linux, AWS, Tableau, Spark, Git",Associate,1,Telecommunications,2024-08-20,2024-10-10,1422,7.3,Predictive Systems +AI03639,Deep Learning Engineer,65918,USD,65918,EN,CT,Ireland,S,Ireland,50,"Docker, Python, Mathematics, Kubernetes, Git",Master,1,Retail,2024-11-09,2025-01-18,1621,6,DataVision Ltd +AI03640,AI Product Manager,136380,EUR,115923,SE,FL,Austria,L,Austria,100,"Mathematics, Tableau, Scala",PhD,6,Consulting,2025-01-28,2025-04-04,1271,7.8,DataVision Ltd +AI03641,Computer Vision Engineer,58677,USD,58677,EN,FL,Finland,M,Finland,100,"R, PyTorch, Azure, SQL, Statistics",Master,1,Gaming,2024-06-04,2024-08-02,1115,9.4,Digital Transformation LLC +AI03642,AI Specialist,78838,USD,78838,MI,FT,Israel,M,Israel,0,"Deep Learning, GCP, Git, Python",Bachelor,2,Energy,2024-07-26,2024-09-13,792,8.9,Autonomous Tech +AI03643,AI Architect,269456,USD,269456,EX,CT,Norway,M,Norway,50,"Python, Scala, Azure, Deep Learning, Computer Vision",Bachelor,15,Telecommunications,2024-02-10,2024-04-03,1052,9.8,Cloud AI Solutions +AI03644,AI Research Scientist,134951,USD,134951,SE,FL,Sweden,L,Sweden,100,"Tableau, Deep Learning, GCP, Python, TensorFlow",Bachelor,9,Automotive,2024-01-28,2024-02-13,1296,8.8,Smart Analytics +AI03645,AI Specialist,71037,USD,71037,EN,PT,Ireland,S,Ireland,0,"Hadoop, R, Java",PhD,0,Healthcare,2025-01-27,2025-03-26,2034,8.9,Cognitive Computing +AI03646,Deep Learning Engineer,81347,CHF,73212,EN,FT,Switzerland,M,Finland,0,"Deep Learning, Kubernetes, Linux",PhD,1,Healthcare,2024-12-11,2025-01-15,2320,9,AI Innovations +AI03647,Deep Learning Engineer,42928,USD,42928,MI,PT,China,S,China,0,"Docker, Linux, TensorFlow",Bachelor,3,Government,2024-03-02,2024-05-08,1427,9.3,DeepTech Ventures +AI03648,AI Architect,133466,CAD,166833,SE,PT,Canada,L,Canada,0,"PyTorch, TensorFlow, Azure",Associate,7,Technology,2024-07-25,2024-09-16,1603,5.4,Cloud AI Solutions +AI03649,Robotics Engineer,199990,USD,199990,EX,FT,Norway,M,Norway,100,"Docker, Kubernetes, AWS, Java",Associate,10,Education,2024-11-13,2024-12-07,1983,5.9,Cloud AI Solutions +AI03650,Machine Learning Researcher,146195,USD,146195,EX,FT,Finland,S,Finland,50,"Spark, Statistics, Hadoop",Master,17,Healthcare,2024-10-04,2024-12-07,502,6.8,Digital Transformation LLC +AI03651,NLP Engineer,98140,EUR,83419,EN,FL,Netherlands,L,Netherlands,100,"Kubernetes, R, Tableau, Data Visualization, AWS",Master,1,Finance,2024-01-01,2024-02-06,1249,6,AI Innovations +AI03652,Data Analyst,37739,USD,37739,EN,PT,China,L,China,100,"Linux, Kubernetes, Data Visualization, MLOps",Associate,0,Retail,2024-02-24,2024-03-12,1183,9.1,Neural Networks Co +AI03653,Deep Learning Engineer,76141,USD,76141,MI,CT,Ireland,S,Ireland,50,"Docker, SQL, PyTorch",Associate,4,Manufacturing,2024-02-13,2024-03-10,1482,9.2,Algorithmic Solutions +AI03654,Robotics Engineer,168289,USD,168289,EX,PT,United States,S,United States,50,"Scala, NLP, Git, Kubernetes",Bachelor,15,Transportation,2024-03-11,2024-05-19,924,6,Smart Analytics +AI03655,ML Ops Engineer,35309,USD,35309,MI,CT,India,M,Belgium,0,"Linux, PyTorch, NLP",PhD,4,Government,2025-02-01,2025-03-24,1527,5.1,AI Innovations +AI03656,Head of AI,252143,EUR,214322,EX,CT,Netherlands,M,Netherlands,100,"Docker, Data Visualization, Hadoop, Statistics",Bachelor,13,Automotive,2025-03-08,2025-03-23,1165,5.5,Digital Transformation LLC +AI03657,Robotics Engineer,61954,USD,61954,EN,PT,Sweden,M,Sweden,100,"SQL, MLOps, PyTorch, Hadoop",Master,1,Education,2024-09-16,2024-11-28,1789,9.3,Quantum Computing Inc +AI03658,Deep Learning Engineer,128736,USD,128736,SE,FT,Sweden,S,Turkey,0,"Git, Hadoop, Mathematics, SQL, R",PhD,5,Finance,2024-09-20,2024-11-28,797,6.1,Machine Intelligence Group +AI03659,AI Product Manager,90524,EUR,76945,MI,CT,Germany,L,Philippines,50,"NLP, Java, Deep Learning, Git",Bachelor,3,Consulting,2024-08-02,2024-09-10,2227,5.1,Smart Analytics +AI03660,Machine Learning Researcher,164213,GBP,123160,EX,FT,United Kingdom,M,United Kingdom,0,"Git, Hadoop, MLOps",Associate,19,Retail,2024-07-30,2024-09-22,2447,7.1,Quantum Computing Inc +AI03661,Data Analyst,106152,SGD,137998,MI,FT,Singapore,L,Singapore,0,"R, Git, Linux",Associate,4,Transportation,2025-04-03,2025-06-14,1267,7.2,DeepTech Ventures +AI03662,Robotics Engineer,101811,EUR,86539,SE,CT,France,M,Brazil,50,"Kubernetes, Python, Tableau",Associate,9,Transportation,2024-03-31,2024-05-23,1113,8.1,Neural Networks Co +AI03663,Machine Learning Engineer,130689,JPY,14375790,SE,FT,Japan,M,Argentina,0,"R, Spark, Data Visualization, Statistics, Azure",Master,8,Manufacturing,2024-04-02,2024-05-23,594,9.8,Neural Networks Co +AI03664,NLP Engineer,134597,USD,134597,EX,FL,Finland,S,Finland,0,"GCP, Java, PyTorch",Associate,14,Gaming,2024-03-07,2024-04-01,1997,6.2,TechCorp Inc +AI03665,Data Scientist,127982,USD,127982,SE,PT,South Korea,L,South Korea,50,"Spark, Kubernetes, Git, Tableau, Python",Bachelor,9,Automotive,2024-04-01,2024-06-04,804,9.3,Cognitive Computing +AI03666,AI Software Engineer,76846,USD,76846,EN,PT,United States,L,Sweden,100,"NLP, Deep Learning, Spark, MLOps",Master,0,Manufacturing,2024-04-13,2024-05-17,590,5.2,Cognitive Computing +AI03667,AI Software Engineer,121507,USD,121507,SE,FL,United States,M,United States,100,"Tableau, Kubernetes, AWS, GCP",Associate,7,Telecommunications,2025-02-05,2025-04-09,1356,7.4,Machine Intelligence Group +AI03668,Principal Data Scientist,190021,USD,190021,EX,FL,Norway,S,Norway,100,"Deep Learning, Java, Spark, Git",Associate,15,Transportation,2024-03-23,2024-05-01,789,8.4,Digital Transformation LLC +AI03669,Robotics Engineer,146680,CAD,183350,SE,FT,Canada,L,Spain,50,"Scala, PyTorch, Computer Vision, Hadoop",Master,5,Energy,2024-04-06,2024-05-19,2431,9.9,Autonomous Tech +AI03670,Autonomous Systems Engineer,82088,GBP,61566,EN,CT,United Kingdom,M,United Kingdom,0,"AWS, Linux, MLOps",PhD,1,Manufacturing,2024-01-11,2024-02-08,1485,9.8,Algorithmic Solutions +AI03671,Computer Vision Engineer,142953,USD,142953,SE,CT,Ireland,L,Ireland,50,"Kubernetes, Java, MLOps, GCP, Mathematics",Bachelor,6,Technology,2024-01-16,2024-03-15,1720,8.7,Quantum Computing Inc +AI03672,AI Specialist,178787,USD,178787,EX,PT,Israel,S,Israel,0,"Docker, Data Visualization, NLP",PhD,15,Technology,2025-04-27,2025-06-07,1111,6.5,AI Innovations +AI03673,Data Engineer,216277,EUR,183835,EX,PT,Austria,M,Austria,100,"Git, Java, MLOps",Master,13,Telecommunications,2024-02-23,2024-03-30,1084,8.5,Cognitive Computing +AI03674,Data Scientist,94882,USD,94882,MI,FT,Finland,L,Finland,50,"Data Visualization, Java, Git, Python, SQL",PhD,3,Education,2025-01-15,2025-03-10,985,8.3,Smart Analytics +AI03675,Data Scientist,73031,GBP,54773,EN,PT,United Kingdom,L,United Kingdom,50,"Computer Vision, Tableau, Python, TensorFlow",Associate,1,Education,2024-11-10,2025-01-22,1425,8.3,Smart Analytics +AI03676,Data Engineer,126700,USD,126700,EX,PT,Sweden,S,Sweden,0,"Linux, Hadoop, Python, TensorFlow",Bachelor,17,Manufacturing,2024-05-18,2024-06-18,2292,7,Machine Intelligence Group +AI03677,Head of AI,95630,GBP,71723,MI,FT,United Kingdom,S,United Kingdom,100,"Scala, Mathematics, Java, Spark, AWS",Master,3,Finance,2024-10-28,2025-01-04,2231,7.4,Algorithmic Solutions +AI03678,Deep Learning Engineer,75175,USD,75175,EN,CT,United States,S,United States,100,"NLP, Linux, SQL",Bachelor,1,Transportation,2025-02-10,2025-03-24,807,5.4,DataVision Ltd +AI03679,Machine Learning Engineer,83872,USD,83872,MI,PT,Israel,L,Egypt,0,"Scala, R, Tableau, Mathematics, Linux",PhD,2,Healthcare,2024-07-17,2024-08-22,619,9.7,AI Innovations +AI03680,Data Scientist,156742,USD,156742,SE,FT,Israel,L,Israel,0,"Deep Learning, R, Java",Bachelor,8,Finance,2024-07-07,2024-08-06,857,9.1,Smart Analytics +AI03681,Principal Data Scientist,111290,USD,111290,SE,FT,Finland,M,Finland,50,"R, Kubernetes, Docker, GCP",PhD,6,Telecommunications,2025-01-30,2025-03-02,2301,6.7,Cloud AI Solutions +AI03682,Computer Vision Engineer,83694,GBP,62771,MI,CT,United Kingdom,M,United Kingdom,0,"Scala, SQL, Hadoop",Bachelor,3,Media,2025-03-28,2025-06-04,1440,7.2,AI Innovations +AI03683,Principal Data Scientist,63711,EUR,54154,EN,FT,France,M,France,50,"Scala, SQL, R",PhD,0,Telecommunications,2024-12-14,2025-01-20,1184,6,Algorithmic Solutions +AI03684,Machine Learning Engineer,108037,EUR,91831,MI,FL,Netherlands,M,Netherlands,100,"GCP, SQL, MLOps, Data Visualization",Associate,2,Real Estate,2024-03-29,2024-05-28,929,7.7,Cognitive Computing +AI03685,Machine Learning Engineer,151599,SGD,197079,SE,FL,Singapore,M,Philippines,0,"Hadoop, Scala, SQL, Kubernetes, AWS",Master,5,Healthcare,2025-04-05,2025-05-09,1044,7.1,Quantum Computing Inc +AI03686,AI Architect,113115,EUR,96148,MI,CT,Netherlands,L,Netherlands,50,"Docker, Spark, Hadoop, NLP",Bachelor,3,Energy,2024-04-18,2024-06-23,1096,6.1,Advanced Robotics +AI03687,Head of AI,213162,USD,213162,EX,FL,Israel,M,Israel,0,"Spark, Python, Tableau, Azure",PhD,18,Real Estate,2024-03-20,2024-05-22,744,9.6,Machine Intelligence Group +AI03688,Deep Learning Engineer,172013,AUD,232218,EX,CT,Australia,L,Italy,50,"R, TensorFlow, Linux, Spark, Mathematics",PhD,16,Manufacturing,2024-05-12,2024-06-04,1245,8.3,Cognitive Computing +AI03689,NLP Engineer,81655,USD,81655,EX,PT,China,L,China,0,"Python, Linux, Git, TensorFlow",Bachelor,12,Consulting,2024-12-10,2025-02-02,580,8.6,Advanced Robotics +AI03690,NLP Engineer,70576,EUR,59990,MI,FL,France,S,France,100,"Computer Vision, R, Azure",PhD,2,Energy,2024-07-11,2024-08-19,1274,9.2,Cognitive Computing +AI03691,Machine Learning Engineer,27457,USD,27457,MI,FL,India,M,India,0,"Kubernetes, Java, Azure",Bachelor,4,Education,2025-04-15,2025-06-27,1890,6,Quantum Computing Inc +AI03692,AI Product Manager,115606,SGD,150288,SE,CT,Singapore,M,France,100,"R, SQL, Scala, Mathematics",Associate,9,Retail,2024-11-21,2025-01-17,2279,8.3,Predictive Systems +AI03693,ML Ops Engineer,85378,EUR,72571,EN,PT,Austria,L,Austria,100,"Computer Vision, Git, Kubernetes",Associate,1,Government,2024-07-09,2024-09-08,500,6.6,DeepTech Ventures +AI03694,AI Specialist,305455,CHF,274910,EX,PT,Switzerland,M,Argentina,0,"Git, Azure, Statistics, R",Master,16,Healthcare,2024-03-29,2024-04-12,1280,5.2,DataVision Ltd +AI03695,Robotics Engineer,115424,USD,115424,MI,FT,Finland,L,Finland,0,"Python, Git, Deep Learning, Spark",Bachelor,4,Finance,2024-02-23,2024-03-23,2154,6.3,Autonomous Tech +AI03696,AI Consultant,73524,USD,73524,EN,FL,United States,S,Vietnam,0,"Python, PyTorch, NLP",Bachelor,0,Government,2024-03-05,2024-04-12,757,6.1,AI Innovations +AI03697,AI Research Scientist,164239,EUR,139603,EX,FT,Germany,M,Germany,50,"Python, Computer Vision, Azure, Java",Bachelor,17,Telecommunications,2024-01-09,2024-02-07,542,9.4,Smart Analytics +AI03698,Head of AI,187030,USD,187030,EX,FT,South Korea,S,South Korea,50,"Docker, Python, R, Kubernetes",PhD,17,Retail,2025-01-28,2025-03-06,2173,8.7,Cloud AI Solutions +AI03699,Principal Data Scientist,201791,AUD,272418,EX,CT,Australia,S,Australia,50,"PyTorch, AWS, Python, NLP",Bachelor,12,Automotive,2024-04-06,2024-04-30,1444,9.7,AI Innovations +AI03700,AI Product Manager,189693,USD,189693,EX,FT,Norway,M,Norway,0,"Computer Vision, PyTorch, Spark",Associate,13,Technology,2024-06-30,2024-09-03,2479,7.2,Autonomous Tech +AI03701,Data Engineer,65796,EUR,55927,EN,PT,Austria,L,Austria,0,"Spark, AWS, Linux, TensorFlow, Azure",Associate,1,Real Estate,2025-03-29,2025-06-09,765,9.1,Autonomous Tech +AI03702,Principal Data Scientist,50207,EUR,42676,EN,FT,France,S,France,50,"Docker, Scala, GCP, Mathematics",PhD,0,Gaming,2024-04-03,2024-05-17,2206,8.8,Future Systems +AI03703,Data Scientist,90924,EUR,77285,MI,CT,Germany,M,Germany,0,"Java, R, NLP, GCP, Linux",Bachelor,3,Technology,2024-05-01,2024-05-26,1171,5.2,Future Systems +AI03704,Autonomous Systems Engineer,66161,CAD,82701,MI,FT,Canada,S,Canada,100,"R, Hadoop, TensorFlow, Git, SQL",Associate,4,Education,2024-07-08,2024-08-31,1791,5,Smart Analytics +AI03705,Data Engineer,166384,AUD,224618,EX,CT,Australia,L,Netherlands,100,"NLP, R, Java, Azure",Bachelor,18,Technology,2024-03-24,2024-05-20,2322,9.5,Cognitive Computing +AI03706,Autonomous Systems Engineer,124008,USD,124008,SE,FL,United States,M,United States,50,"Computer Vision, Azure, PyTorch",Master,6,Technology,2024-11-25,2025-02-02,625,8.6,Smart Analytics +AI03707,AI Software Engineer,83812,USD,83812,MI,CT,Ireland,M,Ireland,0,"Kubernetes, SQL, Tableau",PhD,2,Gaming,2024-06-28,2024-09-09,1991,6,Machine Intelligence Group +AI03708,Computer Vision Engineer,142427,SGD,185155,SE,PT,Singapore,S,Singapore,100,"Git, Python, Tableau, Computer Vision",Bachelor,5,Automotive,2024-12-12,2024-12-27,1392,5.8,AI Innovations +AI03709,AI Consultant,186900,USD,186900,SE,PT,Denmark,M,Denmark,100,"PyTorch, Scala, MLOps, Linux",Bachelor,5,Retail,2024-08-17,2024-09-24,1593,7.9,DataVision Ltd +AI03710,AI Specialist,129050,CAD,161313,SE,CT,Canada,M,Canada,0,"SQL, Deep Learning, Kubernetes, Scala",PhD,9,Healthcare,2025-04-18,2025-05-04,835,9.8,Future Systems +AI03711,Machine Learning Engineer,274462,CHF,247016,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Hadoop, Tableau, MLOps",Bachelor,14,Energy,2025-03-17,2025-04-23,2406,6.4,Quantum Computing Inc +AI03712,AI Product Manager,62465,JPY,6871150,EN,CT,Japan,M,Japan,50,"Mathematics, PyTorch, Tableau, Computer Vision, Git",PhD,0,Telecommunications,2024-12-07,2025-01-03,955,7.6,Smart Analytics +AI03713,Principal Data Scientist,73182,USD,73182,MI,PT,Israel,M,Sweden,100,"Linux, TensorFlow, Scala, SQL, Spark",Associate,2,Retail,2025-03-25,2025-04-30,1570,7.7,Neural Networks Co +AI03714,Deep Learning Engineer,184437,GBP,138328,EX,FL,United Kingdom,S,United Kingdom,50,"Linux, Hadoop, Tableau",PhD,17,Consulting,2024-07-07,2024-08-16,1473,5.4,Predictive Systems +AI03715,Robotics Engineer,94373,GBP,70780,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, TensorFlow, Azure",Bachelor,2,Healthcare,2024-06-26,2024-08-01,1713,8.6,DataVision Ltd +AI03716,Autonomous Systems Engineer,222341,EUR,188990,EX,PT,Austria,M,Denmark,100,"Azure, Scala, Data Visualization",Bachelor,16,Media,2025-01-15,2025-03-23,1873,7.3,Machine Intelligence Group +AI03717,Deep Learning Engineer,54047,CAD,67559,EN,PT,Canada,M,Canada,0,"NLP, Deep Learning, Scala, AWS",Bachelor,0,Government,2024-10-26,2025-01-01,804,5.6,Cloud AI Solutions +AI03718,NLP Engineer,127771,USD,127771,SE,CT,Denmark,S,Denmark,50,"SQL, Azure, Linux",Associate,9,Education,2024-07-06,2024-07-21,677,9.1,DataVision Ltd +AI03719,AI Specialist,93985,EUR,79887,MI,CT,France,M,France,50,"Statistics, Kubernetes, MLOps, R",PhD,3,Gaming,2024-02-18,2024-04-07,548,7.2,DataVision Ltd +AI03720,ML Ops Engineer,66798,EUR,56778,MI,PT,Germany,S,Kenya,0,"NLP, SQL, PyTorch, Java, Computer Vision",Associate,4,Technology,2024-06-03,2024-07-24,1988,5.5,AI Innovations +AI03721,Machine Learning Engineer,155058,USD,155058,SE,FL,Sweden,L,Sweden,100,"Statistics, Kubernetes, GCP, AWS",PhD,7,Gaming,2025-03-15,2025-04-15,1894,5.5,Cloud AI Solutions +AI03722,ML Ops Engineer,280160,JPY,30817600,EX,PT,Japan,L,Japan,0,"Mathematics, Tableau, Linux, Data Visualization",PhD,15,Manufacturing,2024-10-02,2024-11-21,2398,5.6,TechCorp Inc +AI03723,Autonomous Systems Engineer,77244,EUR,65657,MI,FL,France,S,France,50,"Spark, Tableau, TensorFlow, Data Visualization",Associate,4,Manufacturing,2024-01-19,2024-03-23,769,8.2,Cloud AI Solutions +AI03724,Autonomous Systems Engineer,216834,USD,216834,EX,FL,Israel,M,Estonia,100,"Kubernetes, Mathematics, Python",PhD,11,Manufacturing,2025-04-20,2025-07-02,1824,6.6,DeepTech Ventures +AI03725,AI Product Manager,110485,USD,110485,MI,FT,United States,L,Norway,50,"Python, TensorFlow, Spark, PyTorch, NLP",Master,2,Transportation,2024-06-16,2024-07-24,2063,8.6,Neural Networks Co +AI03726,Computer Vision Engineer,43499,USD,43499,SE,FT,China,S,China,50,"SQL, Java, Kubernetes, TensorFlow, Tableau",Bachelor,7,Media,2025-03-24,2025-05-27,537,5.1,DeepTech Ventures +AI03727,Computer Vision Engineer,266981,GBP,200236,EX,PT,United Kingdom,L,United Kingdom,0,"Data Visualization, Java, Spark",Bachelor,13,Telecommunications,2024-10-06,2024-11-05,1978,9.5,Algorithmic Solutions +AI03728,Machine Learning Researcher,126042,USD,126042,SE,FT,Finland,M,Finland,50,"Git, Docker, MLOps, Mathematics, Kubernetes",Associate,8,Automotive,2024-08-28,2024-10-08,1314,7.2,Neural Networks Co +AI03729,AI Specialist,173706,CAD,217133,EX,FL,Canada,S,Canada,50,"Kubernetes, Python, Azure, R, Mathematics",Master,10,Media,2025-01-20,2025-02-22,2026,8.8,Cloud AI Solutions +AI03730,AI Architect,75161,AUD,101467,EN,FT,Australia,M,Portugal,0,"GCP, Python, NLP",Associate,0,Real Estate,2025-02-10,2025-04-22,2388,5.6,Cloud AI Solutions +AI03731,Autonomous Systems Engineer,115030,USD,115030,SE,FT,Israel,M,Israel,50,"Git, TensorFlow, Tableau, Docker",Associate,7,Media,2024-09-07,2024-10-15,623,7.8,Machine Intelligence Group +AI03732,AI Product Manager,151796,AUD,204925,SE,FT,Australia,M,Australia,0,"Python, Kubernetes, Tableau, Computer Vision",PhD,8,Real Estate,2025-03-24,2025-05-26,2435,6.3,Algorithmic Solutions +AI03733,AI Research Scientist,59337,USD,59337,SE,FL,China,M,China,100,"GCP, MLOps, Tableau, R, Hadoop",Master,8,Government,2024-12-23,2025-01-22,617,9.7,Advanced Robotics +AI03734,Robotics Engineer,84211,CHF,75790,EN,PT,Switzerland,L,Finland,100,"TensorFlow, Python, Git",Bachelor,0,Real Estate,2025-03-13,2025-05-18,2309,9.8,AI Innovations +AI03735,Data Analyst,121798,CAD,152248,SE,PT,Canada,S,Sweden,50,"Linux, Tableau, AWS",Associate,5,Media,2025-04-13,2025-06-06,2077,9.9,TechCorp Inc +AI03736,Principal Data Scientist,198790,USD,198790,EX,PT,Israel,M,Ireland,50,"Python, Data Visualization, TensorFlow, Deep Learning, AWS",Associate,11,Government,2024-08-12,2024-10-16,2155,7.2,Autonomous Tech +AI03737,Data Engineer,80590,USD,80590,EN,CT,Norway,L,Thailand,0,"SQL, Spark, MLOps, Statistics, Python",Bachelor,1,Gaming,2024-10-07,2024-11-03,865,8.8,Algorithmic Solutions +AI03738,Principal Data Scientist,158320,EUR,134572,EX,CT,Germany,M,Colombia,50,"SQL, Python, MLOps, Deep Learning",Associate,19,Automotive,2024-01-26,2024-03-16,2065,5.4,Machine Intelligence Group +AI03739,AI Software Engineer,28067,USD,28067,MI,CT,India,S,South Africa,0,"Python, Deep Learning, Scala, Azure, Git",Master,3,Real Estate,2024-12-31,2025-01-19,928,8.1,Quantum Computing Inc +AI03740,Machine Learning Researcher,221734,EUR,188474,EX,FL,France,M,France,100,"MLOps, Hadoop, Python",Bachelor,12,Media,2024-11-12,2024-12-30,1964,8.2,Digital Transformation LLC +AI03741,Research Scientist,66023,USD,66023,EN,CT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, R, Git, Data Visualization",Master,1,Energy,2024-06-22,2024-08-07,820,6,Smart Analytics +AI03742,Machine Learning Engineer,79053,EUR,67195,MI,PT,Austria,M,Austria,100,"Statistics, PyTorch, Azure, Linux, TensorFlow",Master,4,Finance,2024-01-26,2024-03-11,1071,7.5,Quantum Computing Inc +AI03743,AI Specialist,90414,USD,90414,SE,CT,South Korea,M,South Korea,100,"Statistics, TensorFlow, Hadoop",Master,9,Healthcare,2024-07-03,2024-07-28,2008,7.4,TechCorp Inc +AI03744,Head of AI,44966,EUR,38221,EN,CT,France,S,France,0,"PyTorch, TensorFlow, Kubernetes, Scala, Java",Bachelor,1,Healthcare,2024-06-16,2024-08-03,1948,7.6,Quantum Computing Inc +AI03745,Principal Data Scientist,135292,USD,135292,SE,FL,United States,M,Egypt,100,"Deep Learning, Kubernetes, AWS, Scala, NLP",Bachelor,6,Transportation,2024-06-25,2024-07-31,846,9.2,Cloud AI Solutions +AI03746,Principal Data Scientist,224798,EUR,191078,EX,PT,France,M,France,0,"Mathematics, Git, Docker",PhD,19,Media,2024-12-04,2024-12-26,802,6.9,Cloud AI Solutions +AI03747,Deep Learning Engineer,169956,AUD,229441,EX,FT,Australia,S,Australia,100,"Spark, Java, Docker, Computer Vision",Bachelor,10,Gaming,2025-01-26,2025-03-06,750,6.9,Predictive Systems +AI03748,Data Scientist,218143,SGD,283586,EX,FT,Singapore,L,Singapore,0,"Spark, Tableau, Python",Master,19,Energy,2024-05-10,2024-07-17,2434,5.6,AI Innovations +AI03749,AI Research Scientist,123186,EUR,104708,SE,PT,Germany,S,United States,0,"Git, Docker, SQL, Kubernetes",Bachelor,5,Consulting,2024-10-14,2024-11-07,1709,8,Digital Transformation LLC +AI03750,Robotics Engineer,69645,CAD,87056,MI,FT,Canada,S,Canada,100,"Git, Scala, Spark",PhD,2,Automotive,2024-09-09,2024-11-06,1857,8.9,Cloud AI Solutions +AI03751,Head of AI,157091,EUR,133527,EX,PT,Austria,L,Austria,0,"Statistics, Tableau, SQL, Hadoop",PhD,16,Telecommunications,2024-12-21,2025-01-24,888,9.3,TechCorp Inc +AI03752,AI Specialist,90830,EUR,77206,MI,CT,Germany,L,China,50,"Azure, PyTorch, NLP",Associate,4,Retail,2025-03-29,2025-05-26,1841,9.2,Advanced Robotics +AI03753,Deep Learning Engineer,249590,EUR,212152,EX,PT,Netherlands,M,Netherlands,0,"Hadoop, Docker, Data Visualization",PhD,17,Transportation,2025-03-10,2025-03-24,2428,6.1,DeepTech Ventures +AI03754,Computer Vision Engineer,123791,USD,123791,SE,PT,Israel,M,Israel,0,"Linux, AWS, MLOps, Azure, Kubernetes",Bachelor,7,Finance,2024-06-17,2024-08-20,1043,7,Machine Intelligence Group +AI03755,Head of AI,117223,USD,117223,SE,PT,Finland,S,Finland,100,"Docker, MLOps, Computer Vision, Statistics",Bachelor,5,Education,2024-10-17,2024-11-06,2009,9.4,Future Systems +AI03756,NLP Engineer,27366,USD,27366,MI,CT,India,S,India,100,"Data Visualization, Scala, R",PhD,3,Energy,2024-06-04,2024-08-09,2448,6.5,Smart Analytics +AI03757,Machine Learning Researcher,182032,EUR,154727,EX,CT,Austria,L,Austria,0,"MLOps, SQL, AWS, NLP, Spark",Master,13,Consulting,2024-07-27,2024-10-02,1455,8.9,Advanced Robotics +AI03758,Data Analyst,31017,USD,31017,MI,FT,India,L,India,0,"Java, SQL, Deep Learning, PyTorch, Azure",Master,2,Gaming,2024-09-14,2024-10-26,669,5.8,Machine Intelligence Group +AI03759,Head of AI,148948,USD,148948,EX,CT,Finland,S,Finland,100,"Spark, R, MLOps",PhD,16,Technology,2024-06-21,2024-08-14,2352,7.5,Predictive Systems +AI03760,Data Engineer,126217,CHF,113595,MI,CT,Switzerland,L,Switzerland,50,"TensorFlow, Kubernetes, NLP, Deep Learning, Statistics",Bachelor,3,Energy,2024-10-30,2024-12-14,1310,8.9,Neural Networks Co +AI03761,AI Research Scientist,85615,EUR,72773,MI,PT,France,M,France,100,"Deep Learning, NLP, MLOps, Statistics, Kubernetes",Master,3,Gaming,2024-10-17,2024-11-24,2387,9.4,Predictive Systems +AI03762,Deep Learning Engineer,224102,USD,224102,EX,CT,Sweden,M,Sweden,100,"Tableau, Computer Vision, R",Bachelor,17,Government,2024-04-24,2024-05-16,1525,10,Smart Analytics +AI03763,Autonomous Systems Engineer,67594,EUR,57455,EN,PT,Germany,M,Germany,0,"Git, Deep Learning, Python, Tableau",Associate,1,Retail,2024-11-03,2024-11-25,2297,9.8,Cloud AI Solutions +AI03764,Autonomous Systems Engineer,172931,EUR,146991,EX,CT,Germany,S,Germany,100,"Java, Scala, Statistics, Data Visualization",Bachelor,19,Real Estate,2024-08-15,2024-09-13,992,5.9,Future Systems +AI03765,AI Research Scientist,109233,SGD,142003,SE,FT,Singapore,S,Singapore,50,"Python, TensorFlow, R, SQL",PhD,9,Healthcare,2024-07-02,2024-09-12,1286,5.7,Quantum Computing Inc +AI03766,AI Architect,240499,SGD,312649,EX,FT,Singapore,L,Singapore,100,"Hadoop, PyTorch, SQL, R, MLOps",Associate,18,Media,2025-04-28,2025-05-27,2292,7.4,Advanced Robotics +AI03767,Autonomous Systems Engineer,92133,USD,92133,EN,PT,Denmark,M,Denmark,100,"Java, Git, Statistics, R",PhD,1,Education,2025-03-09,2025-05-08,1048,7.5,DeepTech Ventures +AI03768,Machine Learning Researcher,76049,USD,76049,EX,PT,India,M,India,50,"NLP, Python, Linux, Data Visualization",Bachelor,12,Telecommunications,2024-01-07,2024-02-06,1742,5.8,TechCorp Inc +AI03769,Machine Learning Researcher,272882,AUD,368391,EX,CT,Australia,L,Australia,50,"R, SQL, Spark",PhD,19,Transportation,2025-01-29,2025-03-22,656,6.3,Quantum Computing Inc +AI03770,AI Specialist,60278,USD,60278,MI,CT,South Korea,S,South Korea,100,"Spark, NLP, Linux, Kubernetes",Associate,2,Manufacturing,2024-08-11,2024-10-18,1855,9.2,Machine Intelligence Group +AI03771,AI Product Manager,232998,USD,232998,EX,FT,Norway,L,South Africa,50,"Git, SQL, Deep Learning, Scala",Associate,17,Government,2024-08-14,2024-10-18,1447,6.5,Quantum Computing Inc +AI03772,AI Software Engineer,125478,SGD,163121,SE,CT,Singapore,S,Singapore,100,"R, Linux, SQL, Statistics, Deep Learning",Master,9,Consulting,2025-03-23,2025-04-09,703,6.9,Smart Analytics +AI03773,AI Consultant,80666,EUR,68566,MI,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, SQL, R, GCP",Associate,3,Healthcare,2024-03-24,2024-05-11,1026,7.3,TechCorp Inc +AI03774,AI Software Engineer,130187,CHF,117168,MI,CT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Linux, SQL",Associate,4,Consulting,2024-11-19,2025-01-06,1055,5.3,Future Systems +AI03775,Data Analyst,112669,USD,112669,MI,FT,Finland,L,Japan,50,"SQL, Git, TensorFlow, NLP, AWS",Associate,4,Gaming,2025-01-02,2025-02-06,1107,8.8,Machine Intelligence Group +AI03776,AI Research Scientist,117310,CAD,146638,MI,FT,Canada,L,Canada,100,"Python, Azure, NLP",PhD,2,Technology,2024-11-27,2024-12-28,1372,7,Predictive Systems +AI03777,Autonomous Systems Engineer,104436,USD,104436,EN,FL,United States,L,United States,100,"Scala, PyTorch, SQL, AWS",Master,1,Consulting,2024-11-09,2024-12-07,2286,9.8,Cognitive Computing +AI03778,Robotics Engineer,151858,USD,151858,SE,FT,Denmark,L,Denmark,50,"GCP, Data Visualization, MLOps, SQL, Linux",Master,7,Education,2024-09-25,2024-10-12,2069,8,Cloud AI Solutions +AI03779,AI Software Engineer,300122,USD,300122,EX,FL,United States,L,United States,100,"Linux, Data Visualization, Kubernetes",Bachelor,11,Manufacturing,2025-04-12,2025-05-24,1771,8.4,Machine Intelligence Group +AI03780,Research Scientist,123704,USD,123704,MI,PT,United States,M,India,100,"Python, GCP, TensorFlow, Linux, PyTorch",PhD,4,Energy,2024-05-11,2024-05-27,1820,5.6,Quantum Computing Inc +AI03781,NLP Engineer,123407,CAD,154259,SE,PT,Canada,M,Canada,100,"Mathematics, Python, MLOps, SQL, Linux",Bachelor,7,Energy,2024-11-04,2024-11-23,2275,5.9,TechCorp Inc +AI03782,AI Research Scientist,113350,SGD,147355,SE,PT,Singapore,S,Singapore,100,"Scala, Mathematics, Data Visualization, Deep Learning, Java",Bachelor,8,Real Estate,2025-03-23,2025-05-19,1968,7.3,AI Innovations +AI03783,Principal Data Scientist,240944,JPY,26503840,EX,CT,Japan,M,Japan,50,"MLOps, Statistics, Linux",PhD,17,Education,2025-03-05,2025-03-23,1690,6.5,Smart Analytics +AI03784,Autonomous Systems Engineer,56468,USD,56468,MI,FT,China,L,China,100,"R, NLP, TensorFlow, Data Visualization",Master,2,Media,2024-09-06,2024-10-30,1620,9.1,Quantum Computing Inc +AI03785,AI Specialist,23467,USD,23467,EN,FL,India,S,India,0,"Azure, Linux, Computer Vision, AWS, Docker",Bachelor,1,Education,2025-03-22,2025-04-08,1780,8.7,Predictive Systems +AI03786,AI Product Manager,41589,USD,41589,SE,FT,India,S,India,100,"Java, GCP, Azure, PyTorch, Mathematics",PhD,5,Manufacturing,2024-05-18,2024-06-25,1576,7.1,TechCorp Inc +AI03787,Autonomous Systems Engineer,56436,USD,56436,SE,FL,India,L,South Korea,50,"Git, PyTorch, Azure, Data Visualization",PhD,6,Telecommunications,2024-03-05,2024-04-02,2128,8.9,Autonomous Tech +AI03788,Deep Learning Engineer,102052,USD,102052,EN,FT,Denmark,M,Denmark,50,"Scala, Computer Vision, GCP, Git",Master,0,Finance,2025-03-07,2025-03-26,2234,9.6,Cognitive Computing +AI03789,Data Engineer,140417,GBP,105313,SE,PT,United Kingdom,M,New Zealand,0,"SQL, MLOps, PyTorch",Bachelor,5,Energy,2024-10-03,2024-12-15,939,6.5,Predictive Systems +AI03790,Head of AI,62079,USD,62079,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Python, AWS",Master,0,Media,2024-01-29,2024-04-05,845,8.3,Advanced Robotics +AI03791,Robotics Engineer,181941,GBP,136456,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Hadoop, SQL",Bachelor,9,Transportation,2024-09-15,2024-11-16,1538,7.2,Cloud AI Solutions +AI03792,Deep Learning Engineer,48759,USD,48759,EN,CT,South Korea,S,South Korea,50,"Kubernetes, Deep Learning, Python",PhD,0,Gaming,2024-06-28,2024-07-21,891,6.7,Smart Analytics +AI03793,Data Engineer,94775,EUR,80559,SE,PT,France,S,France,50,"Statistics, AWS, Spark, Deep Learning",PhD,8,Retail,2024-07-01,2024-08-29,1544,6.4,AI Innovations +AI03794,AI Specialist,111479,JPY,12262690,SE,FL,Japan,S,Poland,100,"Git, Java, GCP, Deep Learning",Master,6,Technology,2024-06-18,2024-08-13,568,9.1,Algorithmic Solutions +AI03795,Data Analyst,196602,USD,196602,EX,CT,Finland,M,Philippines,50,"Statistics, PyTorch, Git, Mathematics",Master,15,Manufacturing,2024-05-29,2024-06-12,1304,5.3,Advanced Robotics +AI03796,Principal Data Scientist,264173,EUR,224547,EX,PT,France,L,France,100,"Mathematics, Python, TensorFlow, MLOps, NLP",PhD,15,Technology,2024-12-15,2025-02-17,2407,9.6,DeepTech Ventures +AI03797,Head of AI,69502,SGD,90353,EN,CT,Singapore,M,Singapore,0,"Hadoop, SQL, PyTorch, Scala, R",PhD,1,Education,2024-12-31,2025-01-23,1948,8.8,Smart Analytics +AI03798,ML Ops Engineer,130004,EUR,110503,SE,PT,Germany,S,Italy,50,"MLOps, SQL, Python",PhD,6,Retail,2024-01-06,2024-02-03,1868,9.7,AI Innovations +AI03799,AI Product Manager,225220,USD,225220,EX,CT,Finland,M,Finland,0,"GCP, Python, TensorFlow, Hadoop, Deep Learning",PhD,11,Real Estate,2024-11-18,2025-01-02,699,8.5,AI Innovations +AI03800,Robotics Engineer,96826,SGD,125874,MI,CT,Singapore,M,Singapore,0,"GCP, PyTorch, Azure, R",PhD,3,Finance,2024-04-13,2024-05-26,1526,5.2,Digital Transformation LLC +AI03801,Machine Learning Engineer,56293,EUR,47849,EN,FL,Germany,S,Estonia,50,"SQL, Data Visualization, R, Computer Vision, NLP",PhD,1,Technology,2024-05-16,2024-07-11,1637,5.2,DeepTech Ventures +AI03802,Principal Data Scientist,197669,USD,197669,EX,FT,Denmark,M,Denmark,50,"Kubernetes, PyTorch, SQL, Docker",Bachelor,17,Real Estate,2025-04-11,2025-05-24,909,7.5,TechCorp Inc +AI03803,Machine Learning Engineer,129726,SGD,168644,SE,FL,Singapore,M,Singapore,50,"Python, Scala, GCP, R",Master,8,Government,2024-08-30,2024-10-26,967,5.1,Autonomous Tech +AI03804,AI Product Manager,146815,USD,146815,EX,PT,Sweden,S,Indonesia,0,"Computer Vision, PyTorch, Scala",Master,12,Consulting,2025-03-02,2025-04-17,850,5.4,Machine Intelligence Group +AI03805,Data Scientist,108448,USD,108448,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, AWS, NLP, Computer Vision",Master,5,Real Estate,2024-04-18,2024-05-12,2123,9.9,DataVision Ltd +AI03806,NLP Engineer,56987,GBP,42740,EN,CT,United Kingdom,S,Romania,0,"Linux, Tableau, TensorFlow, Deep Learning, Git",Master,0,Manufacturing,2024-02-05,2024-02-29,579,5.1,DeepTech Ventures +AI03807,Research Scientist,109575,USD,109575,SE,CT,Finland,S,Finland,0,"Hadoop, SQL, Python, Tableau, Deep Learning",Bachelor,6,Automotive,2024-10-19,2024-12-13,2369,9.7,Machine Intelligence Group +AI03808,AI Research Scientist,61632,USD,61632,EN,CT,Israel,L,Israel,50,"GCP, R, Tableau, Data Visualization, PyTorch",Bachelor,1,Real Estate,2024-10-26,2024-12-29,1601,6.6,Cognitive Computing +AI03809,Research Scientist,86859,USD,86859,MI,CT,Sweden,M,Sweden,0,"NLP, R, AWS, Linux, Deep Learning",Master,4,Technology,2024-06-27,2024-08-25,1979,7.7,Predictive Systems +AI03810,Data Analyst,93901,EUR,79816,MI,PT,Austria,M,Austria,100,"Python, Scala, Git",Bachelor,2,Gaming,2024-04-22,2024-05-17,2379,5,DeepTech Ventures +AI03811,Machine Learning Researcher,78383,USD,78383,SE,CT,South Korea,S,Austria,0,"Azure, Python, MLOps, R",Bachelor,9,Government,2024-10-30,2024-12-25,2250,6.8,Algorithmic Solutions +AI03812,Data Scientist,105143,USD,105143,EX,CT,China,L,China,0,"Deep Learning, Tableau, TensorFlow, R",Bachelor,13,Manufacturing,2024-06-08,2024-07-22,1396,9.6,Cognitive Computing +AI03813,AI Product Manager,113830,EUR,96756,SE,PT,France,M,Ukraine,0,"SQL, Hadoop, TensorFlow, Data Visualization, Linux",Associate,5,Healthcare,2024-10-06,2024-11-15,2416,7.3,Cloud AI Solutions +AI03814,Research Scientist,104205,EUR,88574,MI,FT,Netherlands,M,Romania,0,"Python, Docker, Tableau",Bachelor,4,Education,2025-02-10,2025-04-12,1015,6.6,Autonomous Tech +AI03815,Data Scientist,76948,USD,76948,MI,FL,Finland,S,Finland,0,"Deep Learning, Python, GCP, TensorFlow, Linux",Associate,3,Healthcare,2024-07-30,2024-09-14,2006,9.8,DataVision Ltd +AI03816,Data Scientist,158361,CAD,197951,SE,FT,Canada,L,Austria,100,"Spark, Python, Tableau, TensorFlow, GCP",Master,6,Energy,2024-06-26,2024-08-25,950,7.2,Digital Transformation LLC +AI03817,ML Ops Engineer,246286,USD,246286,EX,PT,Sweden,M,Sweden,100,"Scala, Spark, PyTorch, GCP",Associate,15,Gaming,2024-05-17,2024-07-22,1743,9.9,Advanced Robotics +AI03818,AI Architect,29444,USD,29444,MI,PT,India,M,India,50,"Git, Python, MLOps, NLP",Associate,3,Technology,2025-01-21,2025-02-24,1338,5.3,Machine Intelligence Group +AI03819,Data Scientist,65572,USD,65572,EX,PT,India,L,India,100,"NLP, Kubernetes, Data Visualization",PhD,10,Manufacturing,2025-03-06,2025-05-12,1167,8.5,Autonomous Tech +AI03820,AI Research Scientist,89996,EUR,76497,MI,FL,Austria,M,Austria,0,"MLOps, GCP, Python, TensorFlow, Computer Vision",PhD,3,Energy,2024-06-03,2024-07-11,1872,8.5,Neural Networks Co +AI03821,Head of AI,251600,EUR,213860,EX,FL,Germany,M,Germany,50,"PyTorch, Kubernetes, NLP",Associate,16,Energy,2024-07-03,2024-07-22,634,8.1,Advanced Robotics +AI03822,Principal Data Scientist,97239,GBP,72929,EN,FL,United Kingdom,L,United Kingdom,0,"Hadoop, Scala, Spark, TensorFlow, Tableau",Bachelor,0,Transportation,2024-09-19,2024-11-14,1174,7.8,Cloud AI Solutions +AI03823,Research Scientist,117805,JPY,12958550,SE,FL,Japan,S,Japan,100,"Linux, Azure, Python, Computer Vision",Associate,8,Energy,2024-07-31,2024-09-28,1354,7.7,Autonomous Tech +AI03824,Deep Learning Engineer,124143,USD,124143,MI,CT,United States,M,Finland,100,"Scala, Python, Computer Vision",PhD,2,Automotive,2024-03-20,2024-04-26,1879,9.1,Quantum Computing Inc +AI03825,Robotics Engineer,119551,USD,119551,SE,PT,Sweden,S,Sweden,50,"AWS, Azure, Python, TensorFlow, MLOps",PhD,9,Media,2024-03-28,2024-04-22,1443,8.8,DataVision Ltd +AI03826,NLP Engineer,122489,USD,122489,MI,PT,Ireland,L,Mexico,50,"Linux, Git, Tableau",Master,2,Retail,2024-01-20,2024-02-24,2181,8.3,AI Innovations +AI03827,AI Product Manager,297922,USD,297922,EX,CT,Denmark,L,Denmark,0,"Linux, Java, Tableau, Spark",Master,19,Finance,2024-02-01,2024-02-17,868,9.1,Cloud AI Solutions +AI03828,Autonomous Systems Engineer,284790,CHF,256311,EX,FT,Switzerland,M,Switzerland,100,"Tableau, Computer Vision, Git, MLOps, GCP",Associate,12,Real Estate,2024-03-17,2024-05-02,1087,6,DeepTech Ventures +AI03829,Machine Learning Engineer,140500,SGD,182650,SE,FT,Singapore,S,Singapore,100,"Scala, GCP, Data Visualization, Deep Learning, Mathematics",PhD,8,Energy,2024-11-11,2024-12-25,2434,7.7,AI Innovations +AI03830,NLP Engineer,116663,CHF,104997,MI,PT,Switzerland,S,Finland,50,"Kubernetes, Java, Spark",Master,4,Technology,2025-04-06,2025-06-05,899,6.3,Algorithmic Solutions +AI03831,AI Product Manager,136106,USD,136106,SE,FT,Norway,S,Norway,0,"TensorFlow, Statistics, Linux",Bachelor,6,Energy,2024-01-17,2024-02-09,1312,8.2,AI Innovations +AI03832,AI Specialist,120352,AUD,162475,SE,FL,Australia,S,United Kingdom,0,"Python, TensorFlow, Data Visualization",Associate,8,Technology,2025-02-22,2025-04-20,1026,5.1,Algorithmic Solutions +AI03833,Principal Data Scientist,115824,USD,115824,EX,PT,Finland,S,Finland,100,"Azure, Mathematics, GCP",Associate,10,Energy,2024-10-24,2024-12-23,1678,9.8,Advanced Robotics +AI03834,Data Engineer,192495,USD,192495,EX,PT,Israel,S,Israel,100,"SQL, Data Visualization, Spark, PyTorch",Associate,16,Government,2025-02-21,2025-03-13,1136,9.2,Autonomous Tech +AI03835,AI Consultant,70175,USD,70175,EN,CT,Finland,L,Finland,50,"Python, TensorFlow, MLOps, Tableau",Associate,0,Gaming,2024-03-27,2024-05-07,1939,5.9,Digital Transformation LLC +AI03836,Deep Learning Engineer,36741,USD,36741,MI,FL,India,M,India,100,"Azure, AWS, Spark, Hadoop, GCP",PhD,3,Consulting,2024-01-13,2024-02-01,825,8.6,Quantum Computing Inc +AI03837,Research Scientist,60568,USD,60568,EN,CT,Finland,L,Finland,100,"TensorFlow, SQL, Spark, Mathematics",Master,1,Government,2024-03-06,2024-04-17,1308,5.3,DeepTech Ventures +AI03838,Autonomous Systems Engineer,56833,USD,56833,EN,CT,Israel,M,Israel,50,"Statistics, Mathematics, Deep Learning, Python, TensorFlow",Associate,1,Gaming,2025-02-06,2025-03-19,1659,9.3,Machine Intelligence Group +AI03839,AI Research Scientist,138563,SGD,180132,SE,FT,Singapore,S,Singapore,100,"Tableau, SQL, Computer Vision",Associate,5,Consulting,2024-02-17,2024-03-16,1786,6.1,Machine Intelligence Group +AI03840,Autonomous Systems Engineer,69031,EUR,58676,MI,FL,Germany,S,Germany,50,"NLP, TensorFlow, Scala, Mathematics, R",PhD,3,Telecommunications,2024-09-25,2024-11-09,1921,7.4,Future Systems +AI03841,Principal Data Scientist,49258,USD,49258,EN,CT,Sweden,S,Sweden,100,"R, Docker, Python, Scala, Kubernetes",Bachelor,1,Consulting,2025-01-30,2025-04-04,1364,8.6,Advanced Robotics +AI03842,Machine Learning Engineer,177507,USD,177507,EX,FT,Sweden,M,Sweden,50,"Deep Learning, SQL, PyTorch, Git",Master,16,Gaming,2025-03-13,2025-04-11,1788,7,Cloud AI Solutions +AI03843,Robotics Engineer,278819,USD,278819,EX,CT,Denmark,M,Netherlands,100,"Computer Vision, Hadoop, R",Bachelor,12,Finance,2024-01-23,2024-03-02,1360,6.4,Algorithmic Solutions +AI03844,Data Analyst,101827,JPY,11200970,MI,PT,Japan,M,Japan,50,"Azure, PyTorch, MLOps, Python",Bachelor,4,Gaming,2024-06-07,2024-07-20,1347,5.8,Advanced Robotics +AI03845,Data Engineer,84062,SGD,109281,EN,CT,Singapore,L,Singapore,0,"Kubernetes, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Real Estate,2024-04-26,2024-05-27,2252,8.9,Cognitive Computing +AI03846,Deep Learning Engineer,102646,CHF,92381,MI,PT,Switzerland,S,Spain,50,"Hadoop, Linux, SQL, Python, Java",Bachelor,4,Healthcare,2024-12-26,2025-01-15,2383,6.6,AI Innovations +AI03847,AI Architect,95477,USD,95477,MI,CT,Norway,M,Norway,0,"GCP, TensorFlow, MLOps",Master,4,Gaming,2024-05-23,2024-08-01,1534,8.4,DeepTech Ventures +AI03848,Autonomous Systems Engineer,46111,USD,46111,SE,FL,China,S,China,0,"Spark, Kubernetes, Linux, Mathematics",Master,6,Transportation,2025-01-07,2025-01-25,518,5.9,Machine Intelligence Group +AI03849,Machine Learning Researcher,97023,EUR,82470,MI,FL,Netherlands,M,South Korea,50,"Python, TensorFlow, Linux, PyTorch, Mathematics",PhD,3,Retail,2024-07-31,2024-09-17,2239,8.7,DataVision Ltd +AI03850,Robotics Engineer,220428,USD,220428,EX,CT,Finland,M,Russia,100,"PyTorch, NLP, Statistics, TensorFlow",PhD,18,Energy,2025-01-14,2025-02-15,2110,8.2,Future Systems +AI03851,Data Analyst,111944,USD,111944,MI,FT,United States,L,Japan,50,"GCP, Java, Python, Tableau",PhD,4,Energy,2024-01-19,2024-03-13,1258,6.3,Algorithmic Solutions +AI03852,AI Product Manager,186617,GBP,139963,EX,FL,United Kingdom,L,United Kingdom,100,"AWS, Mathematics, Python",Bachelor,18,Government,2024-01-14,2024-03-23,1910,6.5,Smart Analytics +AI03853,Data Analyst,161013,EUR,136861,EX,FL,Netherlands,M,Netherlands,100,"SQL, Spark, NLP",Bachelor,18,Real Estate,2024-07-04,2024-08-13,1215,7.1,Digital Transformation LLC +AI03854,Principal Data Scientist,30458,USD,30458,MI,FL,India,S,India,100,"Kubernetes, NLP, SQL",Master,2,Consulting,2024-07-30,2024-09-27,1135,8.8,Algorithmic Solutions +AI03855,Research Scientist,64590,USD,64590,EN,FL,Israel,S,Israel,100,"Kubernetes, MLOps, Computer Vision, Azure",PhD,0,Technology,2024-01-17,2024-03-23,2116,9.5,Quantum Computing Inc +AI03856,ML Ops Engineer,113088,USD,113088,SE,PT,South Korea,S,Russia,0,"PyTorch, Kubernetes, Scala, Java, AWS",PhD,6,Automotive,2024-06-19,2024-07-07,2410,8.2,Autonomous Tech +AI03857,Research Scientist,110516,EUR,93939,MI,CT,Netherlands,L,Netherlands,0,"Python, SQL, Java, GCP, Docker",Associate,3,Media,2025-04-16,2025-05-10,1068,7.3,Future Systems +AI03858,Data Analyst,33400,USD,33400,EN,PT,China,S,China,0,"Statistics, Docker, PyTorch, AWS, Python",Associate,1,Consulting,2024-08-30,2024-10-12,2143,9.2,DataVision Ltd +AI03859,Research Scientist,57862,CAD,72328,EN,FT,Canada,M,Canada,0,"GCP, Mathematics, Kubernetes, Statistics",Master,1,Gaming,2024-07-12,2024-09-14,1817,6.1,Digital Transformation LLC +AI03860,Machine Learning Engineer,111403,EUR,94693,SE,FL,Germany,M,South Africa,50,"NLP, GCP, AWS, SQL, Python",Associate,5,Retail,2024-09-26,2024-11-15,2297,8.5,Future Systems +AI03861,AI Consultant,51736,EUR,43976,EN,FT,Netherlands,S,Netherlands,50,"Data Visualization, Kubernetes, Docker, Statistics",Bachelor,0,Government,2024-07-08,2024-08-01,982,5.1,Digital Transformation LLC +AI03862,Data Engineer,23717,USD,23717,EN,FL,India,M,India,50,"Tableau, Azure, R",Bachelor,0,Gaming,2024-05-27,2024-06-26,2332,7.6,Advanced Robotics +AI03863,Principal Data Scientist,109386,USD,109386,MI,FL,Ireland,M,Ireland,0,"Computer Vision, PyTorch, Kubernetes",Master,2,Government,2025-03-28,2025-05-26,1823,6.5,Advanced Robotics +AI03864,Deep Learning Engineer,74878,CAD,93598,MI,PT,Canada,M,Canada,50,"Python, Java, GCP",Bachelor,4,Government,2024-03-24,2024-04-15,2256,7.7,Predictive Systems +AI03865,Autonomous Systems Engineer,65141,USD,65141,EX,FT,India,M,India,0,"Java, R, SQL",Associate,16,Gaming,2024-12-07,2025-01-28,1317,9.2,Cloud AI Solutions +AI03866,AI Architect,128867,CHF,115980,MI,PT,Switzerland,M,Switzerland,50,"Spark, TensorFlow, SQL, Python",Bachelor,4,Energy,2024-10-06,2024-12-06,2112,5.2,DeepTech Ventures +AI03867,Data Analyst,90726,CHF,81653,EN,CT,Switzerland,S,Hungary,100,"Computer Vision, Java, Docker",Associate,1,Telecommunications,2024-09-24,2024-11-07,601,7.2,DeepTech Ventures +AI03868,Deep Learning Engineer,194760,USD,194760,EX,FT,Israel,M,Israel,100,"Python, Tableau, Git, TensorFlow",Master,17,Technology,2024-04-17,2024-05-18,2424,5.2,TechCorp Inc +AI03869,Autonomous Systems Engineer,107056,USD,107056,SE,CT,Ireland,S,Switzerland,0,"TensorFlow, Hadoop, PyTorch, Azure, GCP",Bachelor,5,Healthcare,2024-11-13,2024-12-05,1395,7.6,Future Systems +AI03870,Principal Data Scientist,108594,CAD,135743,SE,FT,Canada,M,South Africa,50,"Hadoop, TensorFlow, Kubernetes",Bachelor,9,Automotive,2025-03-02,2025-03-21,1796,9.7,DataVision Ltd +AI03871,Data Engineer,79163,EUR,67289,MI,CT,Germany,S,Germany,50,"Mathematics, Linux, R, Docker",Master,2,Technology,2024-12-24,2025-02-26,948,8.6,Advanced Robotics +AI03872,Principal Data Scientist,32589,USD,32589,EN,FT,China,M,China,100,"Java, Spark, Tableau, Hadoop, R",PhD,0,Finance,2024-09-08,2024-09-28,2482,6.1,Machine Intelligence Group +AI03873,Machine Learning Researcher,151184,USD,151184,SE,PT,United States,L,United States,50,"Python, Statistics, Computer Vision, TensorFlow, Spark",Associate,9,Telecommunications,2024-06-19,2024-08-19,1282,8.1,Autonomous Tech +AI03874,AI Research Scientist,80519,USD,80519,SE,PT,South Korea,S,South Korea,100,"GCP, Python, Docker, Computer Vision",Bachelor,7,Finance,2024-10-27,2024-12-28,1784,8.5,Future Systems +AI03875,Autonomous Systems Engineer,67798,USD,67798,EN,FT,Finland,S,Finland,50,"NLP, Mathematics, Linux",Bachelor,1,Consulting,2024-02-04,2024-04-17,1593,9,Predictive Systems +AI03876,Data Engineer,142055,JPY,15626050,SE,PT,Japan,L,Japan,0,"Python, Deep Learning, MLOps, Scala, Linux",Master,5,Retail,2024-08-09,2024-09-24,2229,6,Smart Analytics +AI03877,Data Scientist,120576,GBP,90432,SE,PT,United Kingdom,M,United Kingdom,50,"AWS, TensorFlow, Scala, Tableau",Associate,5,Finance,2025-01-15,2025-02-08,2007,6.4,Cloud AI Solutions +AI03878,Principal Data Scientist,125509,USD,125509,MI,FT,Norway,M,Norway,0,"MLOps, Statistics, Kubernetes",PhD,3,Transportation,2024-12-23,2025-01-27,2272,8.5,Advanced Robotics +AI03879,Data Analyst,55931,USD,55931,EX,PT,India,M,Vietnam,50,"Linux, Docker, AWS, Python",Associate,13,Finance,2024-03-07,2024-04-22,2317,8,DataVision Ltd +AI03880,Machine Learning Researcher,231123,JPY,25423530,EX,FT,Japan,L,Japan,50,"NLP, R, SQL, Tableau",Bachelor,13,Consulting,2024-07-09,2024-08-06,1704,6.8,DeepTech Ventures +AI03881,AI Product Manager,228322,USD,228322,EX,FT,South Korea,L,South Korea,0,"Kubernetes, Statistics, MLOps, SQL",Bachelor,17,Education,2025-02-25,2025-04-21,1258,9,Machine Intelligence Group +AI03882,Research Scientist,143444,USD,143444,EX,PT,Finland,S,Russia,0,"TensorFlow, Scala, Linux, PyTorch",Bachelor,14,Finance,2024-04-21,2024-05-30,1040,8.8,Future Systems +AI03883,AI Product Manager,72811,AUD,98295,EN,FT,Australia,M,Australia,0,"PyTorch, SQL, Java, Statistics, Azure",Associate,0,Manufacturing,2024-04-23,2024-06-17,1188,9.5,Quantum Computing Inc +AI03884,Research Scientist,53482,USD,53482,SE,FL,China,S,China,0,"Python, Git, Hadoop, Scala",Bachelor,5,Automotive,2024-01-20,2024-03-15,1359,6.2,Quantum Computing Inc +AI03885,Computer Vision Engineer,69221,AUD,93448,EN,PT,Australia,S,Australia,0,"Python, MLOps, Docker",Bachelor,1,Media,2024-01-14,2024-02-20,2077,5.7,TechCorp Inc +AI03886,ML Ops Engineer,171506,USD,171506,SE,CT,Norway,L,Mexico,50,"Data Visualization, Kubernetes, GCP, Scala",Master,5,Transportation,2024-02-24,2024-03-14,2170,7.8,Smart Analytics +AI03887,Data Analyst,149279,EUR,126887,EX,FT,France,S,France,100,"Kubernetes, Hadoop, Computer Vision, Python, Statistics",PhD,18,Technology,2024-10-01,2024-11-09,1669,9.7,DataVision Ltd +AI03888,AI Architect,123862,EUR,105283,SE,FT,France,M,France,50,"TensorFlow, SQL, Deep Learning, MLOps, Spark",PhD,5,Transportation,2024-07-07,2024-09-04,1315,8.1,DataVision Ltd +AI03889,Data Scientist,261986,USD,261986,EX,PT,Israel,L,Israel,50,"Hadoop, Kubernetes, Java, R",PhD,12,Energy,2025-02-11,2025-03-07,2344,8.3,Machine Intelligence Group +AI03890,Principal Data Scientist,158894,AUD,214507,EX,PT,Australia,S,Austria,0,"Kubernetes, SQL, Linux, Java, PyTorch",PhD,15,Media,2024-04-21,2024-06-17,1938,5.8,Digital Transformation LLC +AI03891,Deep Learning Engineer,137974,EUR,117278,SE,CT,Austria,L,Hungary,50,"Docker, Scala, Hadoop, Git",PhD,6,Telecommunications,2024-08-29,2024-11-07,2039,6.1,Digital Transformation LLC +AI03892,Head of AI,90760,JPY,9983600,MI,CT,Japan,L,Japan,100,"Hadoop, Tableau, Docker",PhD,4,Education,2024-12-17,2025-02-13,1338,9.3,DeepTech Ventures +AI03893,Data Engineer,137606,SGD,178888,SE,CT,Singapore,L,Latvia,0,"GCP, Python, Mathematics, MLOps",Associate,6,Telecommunications,2024-08-24,2024-10-18,858,8.8,Future Systems +AI03894,Deep Learning Engineer,133207,EUR,113226,EX,FL,France,S,France,50,"SQL, Python, TensorFlow",Master,19,Government,2024-10-02,2024-11-27,629,8.3,Machine Intelligence Group +AI03895,AI Product Manager,100495,USD,100495,EX,FT,India,L,India,50,"PyTorch, MLOps, Java, NLP, Scala",PhD,10,Media,2025-03-12,2025-05-17,2399,6.6,Digital Transformation LLC +AI03896,AI Product Manager,91306,EUR,77610,MI,CT,Germany,S,Germany,0,"Tableau, Python, Hadoop, Mathematics",Master,2,Energy,2025-01-24,2025-02-15,2200,5.4,TechCorp Inc +AI03897,AI Specialist,331986,USD,331986,EX,PT,United States,L,Indonesia,0,"PyTorch, Mathematics, MLOps, SQL",Bachelor,11,Consulting,2024-11-18,2025-01-19,2486,5,Machine Intelligence Group +AI03898,AI Software Engineer,75194,EUR,63915,MI,CT,Germany,M,India,0,"Python, TensorFlow, Spark, Azure",PhD,4,Real Estate,2024-08-27,2024-10-07,610,8,Advanced Robotics +AI03899,AI Product Manager,89154,USD,89154,EN,PT,Denmark,M,Singapore,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Technology,2024-03-28,2024-05-28,1881,5.9,DataVision Ltd +AI03900,AI Consultant,64299,USD,64299,EN,PT,South Korea,M,South Korea,50,"Git, Data Visualization, TensorFlow",Bachelor,0,Transportation,2024-08-15,2024-09-18,683,7.8,TechCorp Inc +AI03901,AI Specialist,137294,EUR,116700,SE,FT,Germany,L,Germany,100,"GCP, TensorFlow, MLOps, Mathematics, SQL",Bachelor,8,Government,2024-06-10,2024-07-30,1946,6.4,TechCorp Inc +AI03902,Data Scientist,101275,USD,101275,MI,FL,Ireland,M,Ireland,0,"Git, Kubernetes, Computer Vision, Deep Learning",Associate,2,Technology,2025-01-30,2025-03-29,795,8.7,Cloud AI Solutions +AI03903,Autonomous Systems Engineer,139984,USD,139984,MI,PT,United States,L,United States,100,"Spark, SQL, Mathematics, Docker, Deep Learning",PhD,2,Retail,2024-02-09,2024-04-11,930,8.9,Future Systems +AI03904,Deep Learning Engineer,151316,EUR,128619,EX,FL,France,S,United States,100,"Hadoop, SQL, Deep Learning",Master,12,Consulting,2025-01-04,2025-02-25,2299,6.4,Advanced Robotics +AI03905,NLP Engineer,84471,USD,84471,EN,PT,Denmark,M,Ireland,100,"Python, Git, GCP, Spark",Master,1,Finance,2024-05-14,2024-06-24,796,5.6,AI Innovations +AI03906,Data Engineer,104379,GBP,78284,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Statistics, R, PyTorch",Bachelor,5,Transportation,2024-02-03,2024-03-11,2366,6.3,Machine Intelligence Group +AI03907,Principal Data Scientist,252832,USD,252832,EX,PT,Denmark,S,Denmark,50,"Scala, TensorFlow, Tableau",PhD,10,Energy,2024-10-14,2024-12-24,1983,8.7,Cognitive Computing +AI03908,Machine Learning Researcher,214285,EUR,182142,EX,FT,Germany,L,Chile,100,"Git, Azure, Data Visualization, R, Computer Vision",Master,17,Manufacturing,2024-05-17,2024-07-20,1999,9.6,DataVision Ltd +AI03909,Data Engineer,100489,USD,100489,EN,CT,Norway,L,Norway,100,"Kubernetes, MLOps, SQL, TensorFlow, R",Associate,0,Automotive,2024-10-22,2024-11-30,1403,7.7,AI Innovations +AI03910,Research Scientist,116902,AUD,157818,SE,FT,Australia,M,Australia,50,"GCP, Mathematics, Data Visualization",PhD,8,Real Estate,2024-07-04,2024-08-06,739,6,DataVision Ltd +AI03911,Data Scientist,98004,USD,98004,EN,PT,Norway,M,Israel,0,"Git, AWS, GCP, Deep Learning, Docker",Master,1,Telecommunications,2024-07-22,2024-09-24,2303,6.7,Machine Intelligence Group +AI03912,ML Ops Engineer,216802,USD,216802,EX,FL,United States,S,United States,50,"Python, TensorFlow, Tableau, PyTorch, Azure",PhD,15,Education,2025-03-11,2025-04-21,869,6,Smart Analytics +AI03913,Principal Data Scientist,97639,USD,97639,MI,FT,Sweden,M,United States,50,"Python, TensorFlow, Spark",Master,4,Energy,2024-12-15,2025-02-15,1662,8.8,Quantum Computing Inc +AI03914,AI Specialist,112321,USD,112321,MI,CT,Israel,L,Israel,0,"Mathematics, GCP, Computer Vision, TensorFlow, Spark",PhD,4,Gaming,2024-02-11,2024-03-21,2160,6,Predictive Systems +AI03915,Data Engineer,192260,AUD,259551,EX,FT,Australia,S,Finland,0,"Tableau, MLOps, GCP, Scala",Bachelor,18,Automotive,2024-10-04,2024-12-14,1151,9.4,Quantum Computing Inc +AI03916,Head of AI,109993,AUD,148491,MI,PT,Australia,L,Australia,50,"SQL, Linux, AWS",Associate,4,Telecommunications,2024-02-06,2024-04-12,1361,8.9,Autonomous Tech +AI03917,AI Product Manager,65943,USD,65943,MI,FL,Sweden,S,Sweden,50,"Python, Kubernetes, Java, Hadoop",Master,2,Finance,2024-08-26,2024-10-09,861,9.3,DeepTech Ventures +AI03918,AI Software Engineer,90867,SGD,118127,MI,PT,Singapore,M,Singapore,100,"SQL, Scala, GCP, Kubernetes, Tableau",Associate,3,Education,2024-11-22,2024-12-23,1269,9.5,DataVision Ltd +AI03919,ML Ops Engineer,84856,USD,84856,EX,FT,India,M,India,100,"AWS, Azure, Spark, Data Visualization, Deep Learning",Bachelor,13,Automotive,2025-03-16,2025-05-05,1793,9.5,Future Systems +AI03920,Data Analyst,171549,EUR,145817,EX,FT,France,M,South Africa,0,"Spark, Linux, Tableau, TensorFlow, Data Visualization",Bachelor,11,Manufacturing,2024-08-12,2024-09-15,1377,5.2,AI Innovations +AI03921,AI Research Scientist,191772,EUR,163006,EX,FL,Germany,M,Thailand,0,"Docker, Statistics, Scala, Kubernetes",Bachelor,19,Telecommunications,2024-07-22,2024-08-14,1912,8.4,Advanced Robotics +AI03922,Robotics Engineer,111326,USD,111326,SE,FT,Ireland,S,Ireland,100,"Computer Vision, SQL, Git, Deep Learning, GCP",Bachelor,6,Retail,2024-08-17,2024-09-16,565,7.3,Cognitive Computing +AI03923,Robotics Engineer,180543,JPY,19859730,EX,CT,Japan,M,Japan,50,"SQL, Deep Learning, Python, NLP",Associate,16,Transportation,2024-06-26,2024-07-13,1493,7.1,Predictive Systems +AI03924,AI Research Scientist,35560,USD,35560,EN,FT,China,M,China,50,"Kubernetes, Azure, Python, Deep Learning",Bachelor,1,Energy,2024-06-21,2024-08-09,983,5.7,Future Systems +AI03925,AI Software Engineer,80024,USD,80024,SE,PT,China,L,China,0,"Hadoop, Linux, Data Visualization",PhD,8,Manufacturing,2024-06-06,2024-06-23,1425,10,Machine Intelligence Group +AI03926,AI Architect,62790,USD,62790,EN,PT,Finland,M,Norway,100,"Python, TensorFlow, AWS, Docker",Master,1,Healthcare,2024-09-01,2024-11-12,1164,8.4,Advanced Robotics +AI03927,NLP Engineer,172119,USD,172119,SE,FT,Norway,M,Norway,0,"MLOps, Mathematics, Tableau, Docker, Azure",Associate,5,Finance,2024-03-05,2024-03-20,727,5.8,Quantum Computing Inc +AI03928,AI Software Engineer,144594,USD,144594,EX,FT,Finland,S,Finland,100,"PyTorch, Python, Azure",Associate,14,Finance,2025-04-30,2025-06-24,1107,6.8,Algorithmic Solutions +AI03929,Autonomous Systems Engineer,59241,EUR,50355,EN,FL,France,S,France,50,"Git, PyTorch, Hadoop, Azure, Deep Learning",Bachelor,0,Transportation,2024-01-30,2024-03-19,2005,9.1,Neural Networks Co +AI03930,Research Scientist,114166,EUR,97041,SE,CT,Netherlands,M,Netherlands,0,"SQL, GCP, NLP, Statistics",Bachelor,9,Media,2024-03-05,2024-04-15,2009,6.8,Cloud AI Solutions +AI03931,AI Product Manager,32706,USD,32706,EN,CT,China,S,Hungary,0,"Hadoop, R, SQL",PhD,1,Manufacturing,2024-03-07,2024-04-26,1525,8.4,Smart Analytics +AI03932,AI Research Scientist,120324,USD,120324,SE,FL,Sweden,M,Sweden,0,"PyTorch, TensorFlow, Tableau, SQL",PhD,8,Real Estate,2024-08-24,2024-10-08,1364,8.8,Algorithmic Solutions +AI03933,NLP Engineer,59232,CAD,74040,EN,PT,Canada,L,Austria,50,"Java, Computer Vision, Mathematics, Hadoop",Master,0,Manufacturing,2025-01-16,2025-03-22,1616,8.4,Neural Networks Co +AI03934,AI Architect,221142,CHF,199028,EX,PT,Switzerland,M,Switzerland,50,"PyTorch, Statistics, TensorFlow",Associate,18,Real Estate,2025-02-25,2025-03-29,1739,5.6,Neural Networks Co +AI03935,Research Scientist,48487,USD,48487,EN,CT,Israel,S,Israel,50,"Mathematics, AWS, Data Visualization, Azure, Git",Associate,1,Manufacturing,2025-03-07,2025-04-18,1412,7.8,DeepTech Ventures +AI03936,Machine Learning Researcher,145495,SGD,189144,SE,FT,Singapore,M,Singapore,0,"NLP, Hadoop, Linux",Bachelor,8,Healthcare,2024-10-25,2024-12-07,1094,5,Algorithmic Solutions +AI03937,Autonomous Systems Engineer,64092,SGD,83320,EN,FL,Singapore,L,Kenya,50,"Kubernetes, SQL, Spark, Python, Statistics",Associate,0,Consulting,2024-10-11,2024-12-15,779,7.3,Predictive Systems +AI03938,Data Analyst,135974,USD,135974,SE,CT,Denmark,S,Kenya,0,"Hadoop, Tableau, Python, Mathematics",Master,9,Education,2024-11-09,2024-12-31,2321,7.6,Quantum Computing Inc +AI03939,AI Product Manager,215605,USD,215605,EX,FL,Israel,M,Israel,0,"Java, R, SQL",Master,12,Technology,2024-12-16,2025-01-26,1940,5.6,Predictive Systems +AI03940,Principal Data Scientist,109621,USD,109621,MI,PT,United States,L,Singapore,0,"SQL, AWS, Git, MLOps, GCP",Bachelor,2,Energy,2024-12-20,2025-01-05,849,9.8,Future Systems +AI03941,AI Specialist,155788,USD,155788,SE,FT,United States,S,United States,0,"SQL, Data Visualization, Scala, Azure, Linux",Associate,6,Gaming,2024-06-07,2024-07-29,2489,7.7,Autonomous Tech +AI03942,Research Scientist,114493,USD,114493,SE,FT,Israel,L,Luxembourg,0,"Spark, NLP, Python, Deep Learning",Associate,9,Manufacturing,2024-06-22,2024-07-06,1482,6.2,Digital Transformation LLC +AI03943,AI Architect,127669,EUR,108519,SE,FT,Germany,S,Finland,100,"Mathematics, Kubernetes, Statistics, GCP, Tableau",Master,7,Government,2025-04-23,2025-07-03,1199,8.5,TechCorp Inc +AI03944,Machine Learning Engineer,184048,SGD,239262,EX,CT,Singapore,M,Singapore,0,"TensorFlow, R, Azure, GCP, Hadoop",Master,11,Technology,2024-01-24,2024-02-10,924,6.6,Algorithmic Solutions +AI03945,Machine Learning Engineer,62821,USD,62821,MI,FL,Finland,S,Finland,100,"Python, Linux, Scala, Kubernetes, TensorFlow",PhD,2,Transportation,2025-04-04,2025-05-30,1805,7.6,Autonomous Tech +AI03946,Data Analyst,116061,USD,116061,MI,FL,Norway,M,Norway,50,"Scala, Statistics, Python, Git",PhD,2,Gaming,2024-05-07,2024-07-11,1188,9.5,Predictive Systems +AI03947,Deep Learning Engineer,68069,JPY,7487590,EN,CT,Japan,M,Japan,100,"Docker, R, Deep Learning, Statistics, Mathematics",PhD,1,Consulting,2024-10-10,2024-10-31,2039,8.5,Future Systems +AI03948,ML Ops Engineer,55034,USD,55034,EN,FL,South Korea,S,Czech Republic,100,"R, GCP, Statistics, SQL, Tableau",Bachelor,1,Media,2024-09-27,2024-11-07,1092,8.6,Advanced Robotics +AI03949,AI Product Manager,197089,EUR,167526,EX,FT,Germany,M,Germany,100,"Hadoop, TensorFlow, Tableau, Data Visualization, Kubernetes",Bachelor,13,Government,2024-04-28,2024-06-26,1527,9,Quantum Computing Inc +AI03950,Data Analyst,63965,EUR,54370,EN,FL,Austria,S,Austria,100,"SQL, Spark, PyTorch, AWS, Java",Master,1,Consulting,2024-11-17,2024-12-02,1541,9.2,Cognitive Computing +AI03951,Research Scientist,88359,CHF,79523,EN,FT,Switzerland,S,Switzerland,100,"TensorFlow, Python, NLP",Associate,0,Real Estate,2024-11-04,2024-11-19,1376,6.4,Machine Intelligence Group +AI03952,ML Ops Engineer,58746,USD,58746,EN,CT,Ireland,S,Ireland,50,"SQL, Python, NLP, Scala, Git",Associate,1,Retail,2024-10-16,2024-11-21,748,9,Future Systems +AI03953,ML Ops Engineer,84148,USD,84148,EX,FT,China,M,China,50,"Tableau, PyTorch, Azure, Linux, NLP",Bachelor,17,Retail,2024-08-26,2024-11-05,1420,5.2,Neural Networks Co +AI03954,Machine Learning Engineer,106957,CHF,96261,EN,FL,Switzerland,M,Switzerland,50,"R, PyTorch, Computer Vision",Master,1,Healthcare,2024-11-27,2024-12-12,1030,6.4,Future Systems +AI03955,Autonomous Systems Engineer,83304,CAD,104130,MI,PT,Canada,S,Denmark,50,"GCP, Scala, Data Visualization, TensorFlow",PhD,3,Education,2024-03-30,2024-05-01,943,6.3,TechCorp Inc +AI03956,Principal Data Scientist,169228,USD,169228,EX,FL,United States,M,United States,100,"Python, Azure, Mathematics",Bachelor,10,Education,2024-04-02,2024-05-11,1923,9.7,TechCorp Inc +AI03957,Deep Learning Engineer,87246,CAD,109058,MI,CT,Canada,S,Nigeria,50,"Deep Learning, Python, Mathematics, MLOps",Master,3,Gaming,2024-05-01,2024-06-26,916,9.4,DataVision Ltd +AI03958,Research Scientist,71057,GBP,53293,EN,PT,United Kingdom,M,United Kingdom,100,"Python, PyTorch, Kubernetes, Azure, SQL",PhD,0,Retail,2024-03-04,2024-05-13,1746,7.6,AI Innovations +AI03959,Data Engineer,197354,CAD,246693,EX,CT,Canada,M,Mexico,50,"SQL, R, Tableau, Statistics, Scala",Associate,11,Energy,2024-01-30,2024-03-18,2412,8.8,DeepTech Ventures +AI03960,Research Scientist,128498,USD,128498,EX,FL,Israel,S,China,0,"Mathematics, SQL, Linux",Bachelor,15,Technology,2024-04-29,2024-06-08,1531,9,Advanced Robotics +AI03961,AI Architect,186865,USD,186865,SE,CT,Denmark,L,Denmark,0,"TensorFlow, Azure, NLP, Git, SQL",Master,8,Telecommunications,2024-11-07,2024-12-21,1088,5.3,Quantum Computing Inc +AI03962,AI Research Scientist,107253,USD,107253,MI,FT,United States,M,Russia,100,"Linux, Computer Vision, Python, Data Visualization, Git",PhD,2,Automotive,2024-01-25,2024-03-27,2074,9.8,TechCorp Inc +AI03963,NLP Engineer,63687,USD,63687,MI,FL,Israel,S,Israel,50,"Computer Vision, Kubernetes, SQL, Deep Learning",PhD,4,Education,2024-07-18,2024-09-05,1291,9.5,Neural Networks Co +AI03964,Principal Data Scientist,79216,USD,79216,MI,FT,Israel,S,Israel,100,"PyTorch, Linux, Data Visualization",Associate,2,Education,2024-06-12,2024-07-20,1511,6,Autonomous Tech +AI03965,Data Scientist,231383,USD,231383,EX,FT,Israel,L,Israel,0,"GCP, TensorFlow, Scala, Python, Data Visualization",Master,11,Technology,2024-02-21,2024-04-07,2362,8.9,Smart Analytics +AI03966,Data Engineer,43977,USD,43977,SE,PT,India,S,Sweden,100,"Scala, Data Visualization, Tableau, Java",Bachelor,9,Automotive,2025-04-22,2025-05-15,1455,8.7,DeepTech Ventures +AI03967,Principal Data Scientist,58328,USD,58328,SE,FT,China,M,China,50,"Data Visualization, Scala, Linux, Java",Bachelor,8,Telecommunications,2024-10-09,2024-12-13,860,6.6,DataVision Ltd +AI03968,Machine Learning Engineer,26547,USD,26547,EN,PT,India,L,Turkey,0,"Python, Azure, SQL, Computer Vision",Master,1,Finance,2025-04-01,2025-05-25,976,7.8,TechCorp Inc +AI03969,Autonomous Systems Engineer,55423,USD,55423,EN,CT,South Korea,S,Australia,0,"Docker, SQL, Java, PyTorch, Linux",Master,0,Real Estate,2024-12-12,2025-01-12,1325,7,Advanced Robotics +AI03970,Machine Learning Engineer,24833,USD,24833,MI,FT,India,S,Mexico,0,"R, SQL, Data Visualization",Master,3,Media,2024-12-20,2025-03-03,2055,9.3,Advanced Robotics +AI03971,Principal Data Scientist,110197,USD,110197,MI,FL,United States,M,United States,100,"R, PyTorch, Scala",PhD,3,Real Estate,2025-01-02,2025-03-01,1672,8.7,Machine Intelligence Group +AI03972,AI Architect,72964,USD,72964,EN,FL,Israel,M,Ukraine,100,"AWS, Spark, MLOps, Scala",Associate,0,Government,2024-03-07,2024-04-04,2318,9.2,AI Innovations +AI03973,Robotics Engineer,59921,USD,59921,EN,CT,Sweden,M,Spain,50,"Data Visualization, Python, TensorFlow, Docker, Statistics",Bachelor,1,Finance,2024-11-02,2025-01-11,1707,8.4,Smart Analytics +AI03974,AI Software Engineer,56383,EUR,47926,EN,CT,Austria,S,Argentina,100,"Azure, AWS, NLP, Spark",PhD,0,Telecommunications,2024-12-05,2025-02-15,1841,8.8,Digital Transformation LLC +AI03975,AI Specialist,71225,USD,71225,EX,FL,India,S,India,0,"Git, MLOps, Deep Learning, Python",Master,19,Government,2024-10-14,2024-11-01,987,6.9,Cloud AI Solutions +AI03976,AI Consultant,64188,USD,64188,EN,CT,Sweden,M,Sweden,50,"Statistics, Hadoop, R, TensorFlow",Bachelor,1,Consulting,2024-06-04,2024-06-26,1597,7.2,AI Innovations +AI03977,Machine Learning Researcher,111850,USD,111850,MI,FT,Norway,S,Norway,0,"MLOps, Python, TensorFlow",PhD,2,Real Estate,2024-02-25,2024-03-21,2475,6.4,Algorithmic Solutions +AI03978,Machine Learning Engineer,193873,EUR,164792,EX,FT,Netherlands,M,Netherlands,0,"Scala, Kubernetes, Deep Learning, Java",Master,12,Real Estate,2024-11-10,2025-01-11,2444,8.6,Machine Intelligence Group +AI03979,Head of AI,69980,USD,69980,EX,CT,China,M,China,50,"Mathematics, PyTorch, Statistics, Kubernetes, Hadoop",PhD,17,Technology,2024-01-03,2024-02-05,1838,8.5,Future Systems +AI03980,AI Specialist,17744,USD,17744,EN,FT,India,S,Kenya,0,"AWS, Git, NLP",Master,1,Media,2025-03-11,2025-04-09,1086,7.8,DeepTech Ventures +AI03981,Research Scientist,55353,EUR,47050,EN,PT,France,L,France,100,"PyTorch, TensorFlow, Java, SQL, Mathematics",Associate,0,Consulting,2024-10-17,2024-12-10,1210,8.2,Neural Networks Co +AI03982,AI Specialist,29786,USD,29786,EN,PT,China,M,Latvia,50,"Spark, Statistics, Data Visualization",Bachelor,0,Telecommunications,2024-11-17,2025-01-19,2453,7.3,Advanced Robotics +AI03983,Machine Learning Researcher,75425,EUR,64111,MI,FT,France,M,France,100,"Python, Kubernetes, Deep Learning, Hadoop, R",Master,4,Telecommunications,2025-01-06,2025-02-04,1488,9.1,DeepTech Ventures +AI03984,Data Engineer,154886,EUR,131653,EX,FT,Austria,S,Australia,0,"Git, SQL, Python",Master,13,Gaming,2024-03-04,2024-04-17,2028,9.6,Advanced Robotics +AI03985,Data Engineer,99073,CAD,123841,SE,FT,Canada,M,Canada,0,"Git, Kubernetes, SQL, PyTorch, Hadoop",PhD,9,Automotive,2025-03-07,2025-04-25,1381,6.4,Quantum Computing Inc +AI03986,Head of AI,73454,EUR,62436,EN,FT,France,M,France,0,"Azure, Java, Docker",Bachelor,0,Telecommunications,2024-02-04,2024-02-29,2135,8.8,DataVision Ltd +AI03987,AI Consultant,59838,USD,59838,SE,CT,China,S,China,100,"Kubernetes, PyTorch, Linux, Computer Vision, MLOps",Associate,9,Government,2024-10-19,2024-12-31,2206,7.2,TechCorp Inc +AI03988,AI Consultant,87537,USD,87537,MI,FT,Israel,M,South Korea,0,"Java, Scala, Deep Learning, Azure",Master,2,Energy,2025-02-28,2025-04-22,2433,8.3,Predictive Systems +AI03989,AI Architect,26899,USD,26899,EN,CT,India,M,Estonia,0,"Scala, NLP, Docker",Master,0,Healthcare,2024-05-09,2024-07-19,1252,5.6,DataVision Ltd +AI03990,AI Architect,89970,USD,89970,SE,PT,South Korea,S,Germany,0,"R, MLOps, AWS",Bachelor,7,Telecommunications,2024-11-08,2025-01-03,809,5.6,Cognitive Computing +AI03991,Deep Learning Engineer,135427,USD,135427,SE,FL,Finland,L,Finland,50,"Java, GCP, Scala",PhD,6,Government,2025-03-24,2025-05-14,1411,6.9,Machine Intelligence Group +AI03992,NLP Engineer,55414,EUR,47102,EN,PT,Austria,M,Latvia,0,"Hadoop, Python, Spark, TensorFlow",PhD,0,Transportation,2025-01-27,2025-02-21,977,8.9,DataVision Ltd +AI03993,AI Architect,214757,CHF,193281,SE,CT,Switzerland,M,Switzerland,100,"Tableau, TensorFlow, Kubernetes, Azure",PhD,8,Energy,2024-08-26,2024-09-11,2055,8.7,Cloud AI Solutions +AI03994,AI Specialist,165695,USD,165695,SE,FL,United States,M,United States,50,"MLOps, Kubernetes, Deep Learning, Git",Associate,5,Finance,2025-02-24,2025-04-26,1087,7.7,Algorithmic Solutions +AI03995,AI Research Scientist,88990,USD,88990,EN,CT,Denmark,M,Denmark,50,"Python, TensorFlow, AWS",Master,0,Government,2025-02-19,2025-03-07,697,5.4,Advanced Robotics +AI03996,Head of AI,74202,GBP,55652,EN,FT,United Kingdom,M,United Kingdom,0,"Python, Kubernetes, GCP, Spark",Associate,1,Consulting,2025-01-24,2025-03-26,1970,6.7,Cognitive Computing +AI03997,Computer Vision Engineer,127421,USD,127421,EX,FT,Finland,S,Netherlands,100,"SQL, Docker, Tableau, PyTorch",Master,11,Healthcare,2024-04-12,2024-04-29,920,9.1,DeepTech Ventures +AI03998,Computer Vision Engineer,278984,CHF,251086,EX,PT,Switzerland,L,Austria,0,"Python, TensorFlow, MLOps, GCP, Data Visualization",Master,14,Finance,2024-02-11,2024-03-09,595,6.2,Smart Analytics +AI03999,Autonomous Systems Engineer,158896,USD,158896,SE,FT,Norway,S,Norway,0,"Data Visualization, Tableau, Hadoop, MLOps",Master,9,Technology,2024-03-19,2024-05-23,541,5.4,TechCorp Inc +AI04000,Robotics Engineer,135260,USD,135260,MI,FT,United States,L,United States,0,"Scala, Python, Hadoop, TensorFlow",PhD,2,Consulting,2024-01-29,2024-02-19,1479,5.3,TechCorp Inc +AI04001,AI Architect,75021,EUR,63768,MI,FT,Austria,S,Colombia,50,"Java, R, Data Visualization, NLP",Bachelor,2,Government,2024-02-01,2024-03-04,1164,9.1,Machine Intelligence Group +AI04002,Head of AI,154992,EUR,131743,EX,FL,Austria,S,Austria,50,"Linux, Git, Spark",Associate,19,Automotive,2025-03-28,2025-04-22,1595,6.9,DataVision Ltd +AI04003,Robotics Engineer,190121,JPY,20913310,EX,FL,Japan,L,Japan,100,"Git, Linux, Deep Learning",PhD,11,Government,2024-04-16,2024-06-21,1539,7.5,Predictive Systems +AI04004,Machine Learning Engineer,385410,CHF,346869,EX,FL,Switzerland,L,Switzerland,0,"Data Visualization, Java, GCP",Bachelor,16,Real Estate,2024-12-18,2025-01-04,849,5.5,Cognitive Computing +AI04005,Computer Vision Engineer,100524,USD,100524,SE,FT,Israel,S,Chile,50,"TensorFlow, Hadoop, Kubernetes",Master,5,Real Estate,2025-03-09,2025-05-15,1296,7.4,DeepTech Ventures +AI04006,Machine Learning Researcher,277819,USD,277819,EX,PT,Denmark,M,Denmark,100,"Data Visualization, Python, SQL, Hadoop",Master,14,Gaming,2025-03-22,2025-05-02,1616,9.1,Autonomous Tech +AI04007,NLP Engineer,65703,AUD,88699,EN,FL,Australia,S,Australia,50,"Hadoop, TensorFlow, Python, NLP",Associate,1,Finance,2024-01-21,2024-03-02,532,8.9,Machine Intelligence Group +AI04008,Data Scientist,132522,EUR,112644,SE,FT,France,L,France,50,"Scala, PyTorch, Java, Deep Learning, Mathematics",PhD,6,Transportation,2024-04-13,2024-06-10,1844,7.3,TechCorp Inc +AI04009,Autonomous Systems Engineer,165364,EUR,140559,EX,FL,France,S,France,0,"Computer Vision, Tableau, Hadoop, R, Deep Learning",Master,11,Transportation,2025-04-07,2025-06-14,1602,5.7,Digital Transformation LLC +AI04010,Principal Data Scientist,106407,AUD,143649,SE,CT,Australia,S,Australia,0,"PyTorch, Hadoop, SQL, Azure",PhD,9,Technology,2024-08-07,2024-09-11,1007,5.1,Predictive Systems +AI04011,Autonomous Systems Engineer,72285,JPY,7951350,EN,CT,Japan,M,Turkey,50,"Python, Spark, Hadoop, Computer Vision, TensorFlow",Bachelor,0,Education,2024-02-16,2024-03-17,2400,6.7,Algorithmic Solutions +AI04012,Principal Data Scientist,105498,USD,105498,SE,FT,Finland,S,Finland,0,"Linux, R, Statistics, SQL, Java",Associate,8,Telecommunications,2024-03-20,2024-05-17,1901,9.7,DeepTech Ventures +AI04013,Autonomous Systems Engineer,93513,EUR,79486,MI,CT,Netherlands,S,Netherlands,50,"R, Python, Tableau, Git",Bachelor,3,Energy,2024-10-14,2024-11-17,915,7.7,Cognitive Computing +AI04014,Data Scientist,56370,USD,56370,EN,PT,Finland,M,Finland,0,"MLOps, Python, Docker",PhD,0,Real Estate,2024-02-08,2024-03-27,722,7.5,Future Systems +AI04015,Computer Vision Engineer,111901,EUR,95116,MI,FT,France,L,Indonesia,50,"Scala, Linux, Java, Git, Statistics",Associate,2,Healthcare,2025-03-14,2025-04-07,750,9.7,Cognitive Computing +AI04016,AI Product Manager,250059,USD,250059,EX,CT,Denmark,S,Denmark,0,"Python, TensorFlow, Hadoop, Mathematics, Computer Vision",Associate,18,Telecommunications,2024-09-18,2024-10-22,2174,6.3,Neural Networks Co +AI04017,Research Scientist,273161,USD,273161,EX,CT,Denmark,M,Switzerland,50,"PyTorch, Tableau, Deep Learning, Statistics",Bachelor,19,Consulting,2024-11-21,2024-12-06,612,5.3,Quantum Computing Inc +AI04018,Data Engineer,132189,EUR,112361,SE,FL,Germany,S,Estonia,100,"Linux, Data Visualization, Scala",Master,8,Education,2025-01-23,2025-03-28,1573,6.8,Autonomous Tech +AI04019,AI Architect,66589,EUR,56601,EN,PT,Germany,M,Germany,50,"Linux, Java, NLP",Associate,0,Real Estate,2024-04-14,2024-05-18,1587,9.5,Smart Analytics +AI04020,Data Analyst,60676,EUR,51575,EN,FL,France,M,Singapore,0,"Computer Vision, GCP, Python, Spark, TensorFlow",Bachelor,0,Education,2024-05-27,2024-06-23,1379,8.3,Quantum Computing Inc +AI04021,Principal Data Scientist,109570,CAD,136963,SE,CT,Canada,M,Romania,0,"GCP, Azure, Data Visualization, AWS",PhD,9,Government,2024-12-17,2025-01-15,2415,5.9,DeepTech Ventures +AI04022,Machine Learning Engineer,58052,USD,58052,EN,FT,Israel,S,France,50,"Git, Statistics, MLOps, Azure",Associate,1,Consulting,2024-08-18,2024-10-19,1438,7.2,DeepTech Ventures +AI04023,AI Research Scientist,98945,EUR,84103,MI,FL,Austria,M,Austria,0,"MLOps, PyTorch, Git, AWS",Associate,3,Manufacturing,2024-12-06,2025-01-26,1831,9.1,Algorithmic Solutions +AI04024,AI Product Manager,199637,USD,199637,EX,CT,Israel,L,Israel,100,"Java, Linux, Hadoop",Bachelor,12,Consulting,2024-02-08,2024-02-24,2356,9.9,TechCorp Inc +AI04025,AI Software Engineer,78109,USD,78109,MI,PT,Finland,S,Finland,50,"NLP, Git, Hadoop, Docker",Master,4,Consulting,2024-04-07,2024-05-19,1816,8.6,Predictive Systems +AI04026,AI Software Engineer,73974,USD,73974,MI,FL,Israel,M,Malaysia,0,"Python, GCP, Tableau",Associate,4,Automotive,2024-03-20,2024-04-14,1538,6,Cloud AI Solutions +AI04027,AI Software Engineer,134116,EUR,113999,SE,PT,France,M,France,100,"NLP, SQL, MLOps",Bachelor,7,Manufacturing,2024-05-25,2024-06-16,832,5.2,Digital Transformation LLC +AI04028,Deep Learning Engineer,135851,USD,135851,SE,CT,Finland,L,Ghana,100,"Docker, AWS, Tableau, GCP, TensorFlow",Associate,7,Consulting,2024-09-21,2024-10-14,543,8.9,Digital Transformation LLC +AI04029,Deep Learning Engineer,142460,USD,142460,SE,PT,Ireland,M,Thailand,100,"Tableau, Statistics, Linux, Mathematics, Deep Learning",Master,5,Education,2024-04-02,2024-04-20,697,6.5,AI Innovations +AI04030,Head of AI,69316,USD,69316,EN,PT,Denmark,S,Japan,50,"SQL, Spark, GCP",Associate,0,Government,2024-04-05,2024-04-24,862,8.1,DataVision Ltd +AI04031,Deep Learning Engineer,82158,EUR,69834,EN,FT,France,L,France,50,"AWS, MLOps, SQL, PyTorch, Git",Associate,1,Retail,2024-05-17,2024-06-22,1467,5.6,Machine Intelligence Group +AI04032,AI Product Manager,167922,USD,167922,SE,PT,Ireland,L,Ireland,100,"SQL, AWS, MLOps",Master,5,Healthcare,2024-12-03,2024-12-24,824,9.4,Quantum Computing Inc +AI04033,NLP Engineer,142118,EUR,120800,SE,FL,Austria,L,Austria,100,"Python, Git, SQL, AWS",Associate,8,Manufacturing,2024-07-06,2024-08-18,1172,5.8,Cognitive Computing +AI04034,Deep Learning Engineer,215397,USD,215397,EX,FT,Israel,S,Israel,50,"Data Visualization, Statistics, Hadoop, Deep Learning, Docker",Associate,15,Retail,2024-10-07,2024-12-07,2434,7.6,Quantum Computing Inc +AI04035,Research Scientist,294594,CHF,265135,EX,FT,Switzerland,L,China,0,"Data Visualization, AWS, SQL, PyTorch, Java",Associate,10,Manufacturing,2024-06-23,2024-07-07,1111,5.5,TechCorp Inc +AI04036,AI Specialist,63057,USD,63057,EN,CT,United States,M,United States,50,"NLP, Scala, Data Visualization",Associate,1,Energy,2024-07-30,2024-08-27,2384,10,Cloud AI Solutions +AI04037,ML Ops Engineer,217874,EUR,185193,EX,FL,Austria,M,Portugal,100,"Java, Hadoop, Computer Vision, R, Python",Master,19,Education,2024-08-26,2024-10-09,2330,9.6,Smart Analytics +AI04038,Autonomous Systems Engineer,32792,USD,32792,SE,PT,India,S,India,50,"GCP, Python, SQL, R",Associate,8,Gaming,2024-10-05,2024-12-16,2354,7.7,Advanced Robotics +AI04039,ML Ops Engineer,116266,JPY,12789260,SE,CT,Japan,M,Japan,100,"Kubernetes, Linux, Data Visualization, NLP, Docker",PhD,7,Education,2025-02-08,2025-03-07,1459,6,Future Systems +AI04040,AI Research Scientist,70410,EUR,59849,EN,FL,Austria,L,Austria,50,"PyTorch, Kubernetes, Docker, TensorFlow",PhD,1,Technology,2024-11-11,2024-12-14,1600,5.3,DeepTech Ventures +AI04041,Data Analyst,56897,CAD,71121,EN,FL,Canada,L,Canada,100,"Java, MLOps, R",PhD,1,Consulting,2024-09-04,2024-09-27,2164,8.6,Cognitive Computing +AI04042,Autonomous Systems Engineer,135997,CHF,122397,MI,PT,Switzerland,S,Ghana,100,"Linux, Python, Kubernetes, MLOps, Data Visualization",Associate,3,Technology,2024-05-14,2024-07-09,1556,7.9,Cloud AI Solutions +AI04043,Machine Learning Engineer,50494,USD,50494,EN,FT,Israel,S,Israel,100,"Git, Tableau, PyTorch, Kubernetes, Spark",Associate,1,Media,2024-09-07,2024-10-01,2213,6,DataVision Ltd +AI04044,AI Research Scientist,144481,GBP,108361,EX,PT,United Kingdom,S,United Kingdom,0,"Git, Linux, Data Visualization, Azure",Bachelor,13,Retail,2024-10-06,2024-12-06,1779,5.1,DeepTech Ventures +AI04045,Principal Data Scientist,102340,USD,102340,MI,FT,Ireland,M,Ireland,50,"GCP, Computer Vision, Linux, Tableau",PhD,3,Retail,2024-06-04,2024-06-24,807,5.4,TechCorp Inc +AI04046,AI Research Scientist,289309,USD,289309,EX,FL,Denmark,S,Denmark,50,"Python, Azure, Tableau, Mathematics",Associate,19,Finance,2025-03-07,2025-04-25,557,7.2,Machine Intelligence Group +AI04047,AI Specialist,86564,GBP,64923,EN,PT,United Kingdom,L,United Kingdom,0,"Linux, Azure, TensorFlow",Associate,0,Education,2024-05-22,2024-06-30,2341,6.6,Cognitive Computing +AI04048,Computer Vision Engineer,105245,GBP,78934,MI,CT,United Kingdom,L,United Kingdom,0,"Spark, R, Computer Vision, Deep Learning, Python",Master,3,Government,2025-03-07,2025-04-04,2141,7.9,AI Innovations +AI04049,Principal Data Scientist,135249,USD,135249,EX,FT,Sweden,S,Sweden,100,"Mathematics, Git, Spark, SQL, PyTorch",Master,14,Energy,2024-09-23,2024-10-20,1386,8.8,Predictive Systems +AI04050,AI Research Scientist,351014,CHF,315913,EX,FT,Switzerland,L,Egypt,50,"Statistics, MLOps, Python, TensorFlow",Master,10,Consulting,2024-10-25,2024-12-13,922,5.8,Quantum Computing Inc +AI04051,Data Scientist,170313,GBP,127735,SE,PT,United Kingdom,L,United Kingdom,0,"Azure, Scala, Statistics, SQL, Deep Learning",Master,5,Gaming,2024-07-27,2024-08-29,1363,5.6,Algorithmic Solutions +AI04052,Autonomous Systems Engineer,96839,USD,96839,MI,FL,Israel,L,Israel,0,"Scala, Data Visualization, Computer Vision",Associate,3,Automotive,2025-02-16,2025-03-31,2388,9.8,DeepTech Ventures +AI04053,Machine Learning Engineer,112039,USD,112039,EX,CT,South Korea,M,South Korea,0,"TensorFlow, GCP, Scala",Bachelor,16,Finance,2024-10-01,2024-12-06,1359,5.5,Future Systems +AI04054,Autonomous Systems Engineer,161578,GBP,121184,SE,FL,United Kingdom,L,United Kingdom,50,"Python, Linux, Kubernetes, Git, GCP",PhD,9,Energy,2024-03-23,2024-04-19,538,8.7,Quantum Computing Inc +AI04055,Deep Learning Engineer,162342,USD,162342,SE,CT,United States,L,United States,0,"Deep Learning, SQL, Scala",Associate,7,Manufacturing,2025-03-11,2025-05-06,1837,6.3,Autonomous Tech +AI04056,AI Software Engineer,81152,CAD,101440,MI,FL,Canada,M,Indonesia,50,"Mathematics, Hadoop, SQL, Python, Data Visualization",Master,3,Media,2024-01-16,2024-03-15,1532,5.1,DeepTech Ventures +AI04057,Robotics Engineer,146791,EUR,124772,SE,PT,Germany,L,Germany,50,"MLOps, Git, Kubernetes",Bachelor,6,Media,2024-11-07,2024-12-21,661,6.9,Predictive Systems +AI04058,AI Architect,231457,SGD,300894,EX,FL,Singapore,M,Singapore,0,"Computer Vision, TensorFlow, Linux, Tableau",Associate,13,Manufacturing,2024-01-28,2024-03-28,671,6.5,Cognitive Computing +AI04059,Data Scientist,114857,EUR,97628,SE,PT,Austria,S,Argentina,0,"Python, TensorFlow, Tableau, NLP",Associate,7,Manufacturing,2024-06-26,2024-07-27,1809,9.5,Future Systems +AI04060,Computer Vision Engineer,73750,USD,73750,EX,CT,China,L,China,50,"Spark, PyTorch, SQL, Computer Vision",Associate,15,Gaming,2024-07-29,2024-09-12,1258,9.7,TechCorp Inc +AI04061,Data Engineer,87162,SGD,113311,EN,FL,Singapore,L,Singapore,50,"Computer Vision, Spark, Python, Scala",Bachelor,0,Real Estate,2024-10-20,2024-11-29,979,9.8,Autonomous Tech +AI04062,Machine Learning Engineer,85264,USD,85264,EX,CT,China,M,China,50,"Linux, Java, Docker, SQL, Git",Master,17,Education,2025-01-09,2025-02-11,1762,8.9,Digital Transformation LLC +AI04063,Principal Data Scientist,72355,CAD,90444,EN,FL,Canada,M,Canada,0,"Git, MLOps, Kubernetes, Hadoop",Associate,0,Energy,2024-11-15,2025-01-27,1357,5.3,TechCorp Inc +AI04064,ML Ops Engineer,83615,AUD,112880,MI,CT,Australia,S,Australia,50,"Git, Hadoop, Mathematics",Associate,4,Retail,2024-01-09,2024-02-05,2152,9.3,DataVision Ltd +AI04065,Machine Learning Researcher,201139,USD,201139,SE,FT,United States,L,Denmark,0,"Python, Azure, TensorFlow, Hadoop",PhD,8,Energy,2025-03-07,2025-04-17,2236,8.2,Digital Transformation LLC +AI04066,Research Scientist,227744,USD,227744,EX,FT,Denmark,M,Denmark,50,"Docker, Mathematics, R, SQL, Computer Vision",Bachelor,11,Media,2025-02-23,2025-04-26,656,9.3,Predictive Systems +AI04067,Research Scientist,50231,CAD,62789,EN,PT,Canada,M,Canada,100,"Scala, Spark, SQL, Mathematics",Associate,1,Media,2024-07-17,2024-07-31,572,7.1,Machine Intelligence Group +AI04068,Data Analyst,149410,EUR,126999,EX,FT,Austria,M,Austria,50,"Kubernetes, PyTorch, MLOps",PhD,15,Automotive,2024-04-20,2024-06-19,941,9.2,AI Innovations +AI04069,Data Engineer,322650,CHF,290385,EX,FL,Switzerland,S,Switzerland,50,"NLP, Linux, Python",PhD,18,Consulting,2024-07-24,2024-08-24,1900,6.3,Autonomous Tech +AI04070,Head of AI,138075,CAD,172594,SE,FL,Canada,L,Canada,50,"GCP, Kubernetes, Data Visualization, SQL",Bachelor,8,Technology,2025-03-05,2025-04-21,2390,6.1,Cloud AI Solutions +AI04071,Data Engineer,70492,USD,70492,MI,FL,South Korea,L,South Korea,0,"NLP, R, Kubernetes, Linux, TensorFlow",Bachelor,4,Media,2024-09-10,2024-11-05,1832,8.5,DataVision Ltd +AI04072,AI Architect,50946,USD,50946,EN,FT,South Korea,S,South Korea,0,"Deep Learning, Java, Computer Vision, AWS, Kubernetes",Associate,0,Transportation,2024-05-11,2024-07-06,1102,7.1,Autonomous Tech +AI04073,AI Architect,74567,JPY,8202370,EN,FT,Japan,M,Sweden,0,"TensorFlow, Linux, Python, SQL, AWS",Associate,1,Manufacturing,2024-02-19,2024-03-15,514,5.3,Cognitive Computing +AI04074,Machine Learning Engineer,63683,AUD,85972,EN,CT,Australia,L,Australia,100,"Python, NLP, GCP, Mathematics, Git",Associate,0,Government,2024-12-08,2025-01-07,1692,5.7,TechCorp Inc +AI04075,AI Product Manager,93281,USD,93281,EN,FT,United States,L,Ukraine,100,"Hadoop, Python, Azure, Spark, Statistics",Bachelor,1,Technology,2024-08-20,2024-10-15,1066,6.7,Cloud AI Solutions +AI04076,Deep Learning Engineer,86606,CAD,108258,MI,PT,Canada,S,Ireland,0,"Docker, Scala, Linux",Bachelor,3,Media,2024-05-08,2024-06-29,573,6.2,Smart Analytics +AI04077,AI Software Engineer,114314,EUR,97167,SE,CT,France,M,France,100,"Azure, Git, Hadoop, Data Visualization, Mathematics",PhD,7,Media,2024-09-26,2024-11-11,743,5.1,AI Innovations +AI04078,Machine Learning Researcher,44105,USD,44105,SE,PT,India,L,India,0,"Java, Hadoop, MLOps",PhD,6,Retail,2024-07-10,2024-09-01,724,5.7,Future Systems +AI04079,AI Specialist,87807,EUR,74636,MI,FT,Austria,L,Austria,50,"PyTorch, Git, Java, Scala, TensorFlow",Bachelor,3,Automotive,2024-03-30,2024-04-19,2006,7.2,AI Innovations +AI04080,Principal Data Scientist,105998,AUD,143097,MI,FT,Australia,L,Australia,100,"Spark, Tableau, GCP, Linux, Hadoop",Bachelor,4,Energy,2024-09-05,2024-11-16,1627,7.3,Cloud AI Solutions +AI04081,Deep Learning Engineer,205845,CHF,185261,SE,CT,Switzerland,M,Portugal,0,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Associate,9,Telecommunications,2024-03-05,2024-04-06,2211,8.5,Machine Intelligence Group +AI04082,AI Architect,108031,SGD,140440,SE,CT,Singapore,S,Singapore,50,"Mathematics, Azure, PyTorch",Associate,6,Manufacturing,2024-09-20,2024-10-30,1358,9.2,DeepTech Ventures +AI04083,AI Consultant,43599,USD,43599,MI,PT,China,S,China,50,"MLOps, R, TensorFlow, SQL, GCP",Associate,4,Media,2024-02-23,2024-05-01,2059,6.4,Quantum Computing Inc +AI04084,Data Scientist,100782,GBP,75587,MI,FL,United Kingdom,S,United Kingdom,100,"Mathematics, R, SQL, Spark",Bachelor,3,Manufacturing,2025-02-21,2025-04-09,2245,9.9,Algorithmic Solutions +AI04085,Autonomous Systems Engineer,124064,SGD,161283,SE,PT,Singapore,S,Israel,50,"Java, Scala, NLP, Azure",PhD,8,Gaming,2024-12-25,2025-02-16,1257,7.4,DataVision Ltd +AI04086,Head of AI,32020,USD,32020,EN,FL,China,L,China,100,"SQL, Hadoop, PyTorch, Linux",Associate,1,Media,2024-01-09,2024-01-30,878,8.5,Algorithmic Solutions +AI04087,Machine Learning Engineer,88815,USD,88815,MI,FL,Finland,M,Finland,50,"Linux, Java, Git, Mathematics, NLP",Bachelor,3,Finance,2024-08-21,2024-10-25,2150,6.1,Digital Transformation LLC +AI04088,Data Analyst,102567,CHF,92310,MI,FT,Switzerland,M,Switzerland,50,"Hadoop, Python, PyTorch",Master,4,Consulting,2025-01-14,2025-03-03,1066,7.6,Predictive Systems +AI04089,Computer Vision Engineer,72234,USD,72234,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, SQL, Python, Kubernetes",Associate,1,Telecommunications,2024-03-08,2024-05-01,1659,9.1,Algorithmic Solutions +AI04090,NLP Engineer,284726,CHF,256253,EX,FL,Switzerland,M,Italy,0,"Python, PyTorch, TensorFlow",Master,15,Gaming,2025-02-28,2025-05-07,697,6.5,Algorithmic Solutions +AI04091,Principal Data Scientist,103801,EUR,88231,MI,CT,Netherlands,M,Russia,50,"NLP, AWS, Linux, Statistics, Computer Vision",Master,3,Telecommunications,2025-02-22,2025-03-08,1806,5.2,Neural Networks Co +AI04092,AI Specialist,211598,EUR,179858,EX,FT,Germany,L,Israel,50,"TensorFlow, Scala, Hadoop, Deep Learning, PyTorch",Master,10,Manufacturing,2024-11-18,2025-01-20,1067,6.5,Cloud AI Solutions +AI04093,Principal Data Scientist,65479,GBP,49109,EN,CT,United Kingdom,M,Portugal,50,"GCP, Kubernetes, SQL",Associate,1,Manufacturing,2024-08-06,2024-10-05,2120,8.9,DataVision Ltd +AI04094,ML Ops Engineer,55701,CAD,69626,EN,CT,Canada,S,Canada,50,"Azure, PyTorch, Git",Associate,1,Energy,2024-10-09,2024-12-21,1684,9,TechCorp Inc +AI04095,Machine Learning Researcher,265222,CHF,238700,EX,CT,Switzerland,S,Switzerland,0,"Git, Azure, Spark, Mathematics, AWS",Master,14,Gaming,2025-03-09,2025-03-27,1418,9.8,TechCorp Inc +AI04096,NLP Engineer,33734,USD,33734,MI,FT,China,S,China,50,"R, SQL, NLP, Azure",Associate,4,Gaming,2024-04-27,2024-06-29,964,7.2,Smart Analytics +AI04097,AI Software Engineer,69684,USD,69684,MI,FT,South Korea,S,Spain,50,"Git, R, Tableau, SQL",Bachelor,3,Energy,2025-02-01,2025-03-03,850,7.1,Future Systems +AI04098,AI Specialist,96701,AUD,130546,MI,FT,Australia,L,Australia,50,"PyTorch, Hadoop, Git",Master,4,Technology,2024-07-20,2024-09-30,1167,9.2,Predictive Systems +AI04099,Deep Learning Engineer,180946,USD,180946,EX,FL,Ireland,M,Ireland,50,"Scala, AWS, Git, Hadoop",Bachelor,19,Finance,2024-12-14,2025-01-31,1194,8.5,Advanced Robotics +AI04100,Data Analyst,166915,USD,166915,EX,FL,Finland,M,Finland,100,"Java, PyTorch, Kubernetes, Mathematics, Data Visualization",Associate,12,Technology,2025-02-04,2025-04-08,880,5.2,AI Innovations +AI04101,Autonomous Systems Engineer,121685,USD,121685,SE,FL,Sweden,M,Sweden,0,"Data Visualization, Deep Learning, Python, Statistics",Bachelor,9,Consulting,2024-03-13,2024-05-15,1830,5.2,TechCorp Inc +AI04102,Research Scientist,167790,USD,167790,SE,FL,Norway,L,Norway,100,"Linux, NLP, Python",Bachelor,6,Government,2025-02-27,2025-03-16,1947,9.7,DeepTech Ventures +AI04103,Robotics Engineer,80516,EUR,68439,EN,CT,Netherlands,M,Netherlands,0,"Scala, Git, SQL, Python",PhD,1,Media,2024-09-13,2024-10-21,1007,6,Cognitive Computing +AI04104,Data Scientist,100310,GBP,75233,MI,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Docker, GCP",Associate,2,Education,2024-01-18,2024-03-05,1460,7.7,Cognitive Computing +AI04105,Research Scientist,120643,USD,120643,SE,FT,Sweden,M,Sweden,0,"Docker, R, Deep Learning, Java, Computer Vision",Associate,6,Technology,2025-04-21,2025-06-23,817,7.2,Cognitive Computing +AI04106,AI Architect,68168,EUR,57943,MI,PT,Austria,S,Austria,100,"PyTorch, Linux, SQL, GCP, R",Bachelor,3,Telecommunications,2025-01-09,2025-02-22,2194,5.9,TechCorp Inc +AI04107,Data Engineer,103407,USD,103407,EX,FL,India,L,India,0,"Python, NLP, Statistics",Master,17,Government,2024-10-30,2024-12-23,2100,6.4,Cognitive Computing +AI04108,Principal Data Scientist,79353,JPY,8728830,EN,FT,Japan,M,Japan,0,"GCP, PyTorch, NLP",PhD,0,Telecommunications,2024-05-04,2024-06-19,1235,7,AI Innovations +AI04109,Principal Data Scientist,215826,GBP,161870,EX,FT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Azure, R, Statistics",Associate,14,Telecommunications,2024-04-03,2024-05-25,886,8.7,DeepTech Ventures +AI04110,Data Analyst,124330,EUR,105681,MI,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Deep Learning",Master,3,Retail,2024-12-12,2025-02-19,1635,5.3,Advanced Robotics +AI04111,Machine Learning Engineer,53595,EUR,45556,EN,FT,France,M,Luxembourg,100,"NLP, Git, Docker, Hadoop, Spark",Master,0,Consulting,2024-09-19,2024-11-06,1568,5.2,Advanced Robotics +AI04112,AI Research Scientist,141469,EUR,120249,EX,FL,Germany,S,Germany,0,"R, Python, Computer Vision",Master,14,Transportation,2024-06-08,2024-08-02,1693,6.5,Predictive Systems +AI04113,Computer Vision Engineer,115046,USD,115046,MI,FT,Sweden,L,Sweden,100,"Kubernetes, AWS, GCP, Scala",Master,4,Media,2025-03-14,2025-05-23,739,8,Predictive Systems +AI04114,Machine Learning Engineer,147907,CHF,133116,MI,PT,Switzerland,M,Egypt,0,"SQL, AWS, Scala, Tableau",Associate,4,Automotive,2025-03-11,2025-04-01,1372,8.8,Machine Intelligence Group +AI04115,AI Product Manager,50641,USD,50641,EX,FL,India,S,Hungary,50,"Data Visualization, GCP, R, Hadoop",PhD,19,Healthcare,2024-06-19,2024-08-25,1905,9.3,DataVision Ltd +AI04116,AI Product Manager,214441,EUR,182275,EX,FL,Netherlands,M,Philippines,0,"Linux, Scala, Python, NLP, Mathematics",PhD,10,Manufacturing,2024-02-19,2024-03-29,2265,6.3,Future Systems +AI04117,Computer Vision Engineer,114417,GBP,85813,MI,FL,United Kingdom,M,United Kingdom,50,"Python, R, Mathematics",PhD,2,Technology,2024-03-28,2024-05-14,2050,9.9,Digital Transformation LLC +AI04118,AI Consultant,112932,JPY,12422520,MI,FT,Japan,L,Japan,100,"Scala, Computer Vision, NLP, PyTorch, Spark",Bachelor,4,Healthcare,2025-03-03,2025-04-08,2449,9.3,Autonomous Tech +AI04119,ML Ops Engineer,72211,USD,72211,EN,CT,Israel,L,Israel,0,"Git, Scala, SQL, Mathematics",Bachelor,0,Retail,2024-04-16,2024-05-05,2062,9.8,Cognitive Computing +AI04120,Deep Learning Engineer,182222,AUD,246000,EX,CT,Australia,L,Spain,100,"Azure, Deep Learning, Java",Master,18,Energy,2024-10-01,2024-11-06,1155,7.2,AI Innovations +AI04121,Machine Learning Engineer,83596,EUR,71057,EN,FT,Germany,L,Germany,50,"Data Visualization, NLP, Kubernetes, Python",PhD,0,Government,2025-01-04,2025-03-18,1822,5.2,Future Systems +AI04122,NLP Engineer,109011,CHF,98110,EN,FT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Data Visualization, R",Associate,1,Consulting,2024-01-25,2024-03-12,2002,8.6,DataVision Ltd +AI04123,Deep Learning Engineer,74573,AUD,100674,EN,PT,Australia,L,Australia,0,"Git, Python, Mathematics, Tableau, Docker",PhD,0,Retail,2024-10-21,2024-12-26,926,8.1,Cognitive Computing +AI04124,Principal Data Scientist,117158,EUR,99584,MI,PT,Netherlands,L,Philippines,50,"Python, TensorFlow, Git, Computer Vision, Azure",Master,2,Consulting,2024-11-19,2024-12-17,1918,6.4,Future Systems +AI04125,Head of AI,84442,JPY,9288620,MI,FL,Japan,M,Sweden,50,"SQL, TensorFlow, Mathematics",PhD,2,Telecommunications,2024-12-30,2025-02-23,1372,6.8,Cloud AI Solutions +AI04126,Machine Learning Researcher,64765,USD,64765,EX,FL,India,L,Brazil,100,"PyTorch, Scala, Hadoop, Computer Vision",PhD,11,Media,2024-05-14,2024-06-24,1270,5.8,Algorithmic Solutions +AI04127,Data Scientist,161364,USD,161364,SE,FT,Norway,S,Norway,100,"AWS, MLOps, SQL, Azure",Bachelor,9,Real Estate,2024-02-27,2024-04-29,1176,6.5,Algorithmic Solutions +AI04128,Data Scientist,259567,AUD,350415,EX,PT,Australia,L,Australia,0,"GCP, Docker, Python, Azure, Data Visualization",Master,11,Government,2025-03-23,2025-05-11,789,10,Smart Analytics +AI04129,Machine Learning Engineer,58926,USD,58926,MI,FT,South Korea,S,Finland,0,"Statistics, PyTorch, Java, Scala, Azure",Bachelor,3,Education,2024-05-19,2024-07-04,1330,9.8,Smart Analytics +AI04130,Machine Learning Researcher,205317,USD,205317,SE,FL,United States,L,Argentina,100,"Scala, AWS, Tableau",Associate,7,Government,2024-10-25,2024-12-18,2425,7.3,Neural Networks Co +AI04131,Robotics Engineer,142793,CHF,128514,MI,PT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Mathematics, Statistics, GCP",Bachelor,4,Telecommunications,2024-06-19,2024-08-18,1439,7,Algorithmic Solutions +AI04132,AI Architect,48948,USD,48948,SE,FL,India,L,India,50,"Git, GCP, Python, AWS, NLP",Bachelor,5,Technology,2024-08-30,2024-09-19,2439,8.5,Neural Networks Co +AI04133,Machine Learning Engineer,101284,USD,101284,MI,FL,Ireland,M,Ireland,0,"Kubernetes, Docker, R, Azure",Bachelor,2,Finance,2024-05-07,2024-06-14,2361,7.2,Future Systems +AI04134,Autonomous Systems Engineer,94804,USD,94804,MI,CT,South Korea,L,Vietnam,100,"SQL, PyTorch, GCP",Associate,2,Finance,2025-04-20,2025-06-25,1817,8.7,Cognitive Computing +AI04135,AI Consultant,55274,SGD,71856,EN,FT,Singapore,S,Singapore,0,"Python, TensorFlow, Spark, Deep Learning",Associate,1,Real Estate,2024-12-13,2025-02-04,1539,8.1,DataVision Ltd +AI04136,Machine Learning Engineer,46056,EUR,39148,EN,CT,France,S,France,100,"Kubernetes, Scala, GCP",Associate,1,Government,2024-07-03,2024-09-12,2123,7.8,Smart Analytics +AI04137,AI Research Scientist,71471,SGD,92912,EN,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, NLP, Deep Learning, Scala",Master,0,Education,2024-07-31,2024-09-20,989,6.3,Quantum Computing Inc +AI04138,Data Analyst,173574,AUD,234325,EX,CT,Australia,S,Australia,0,"Linux, Hadoop, R",Master,12,Finance,2025-03-07,2025-04-30,832,5.8,AI Innovations +AI04139,AI Software Engineer,228777,CAD,285971,EX,PT,Canada,L,Canada,0,"Scala, Deep Learning, Data Visualization, Kubernetes, Statistics",PhD,18,Energy,2024-10-02,2024-10-24,2368,8.5,Algorithmic Solutions +AI04140,Data Engineer,218206,AUD,294578,EX,FL,Australia,M,Australia,0,"Linux, TensorFlow, Statistics, Python, Computer Vision",PhD,17,Technology,2025-04-27,2025-06-05,2119,5.6,Digital Transformation LLC +AI04141,Autonomous Systems Engineer,218548,EUR,185766,EX,CT,Netherlands,L,Netherlands,100,"Git, Hadoop, Linux",Master,11,Energy,2024-11-08,2025-01-09,1487,9.7,Digital Transformation LLC +AI04142,Data Scientist,137310,EUR,116714,SE,FT,France,M,France,100,"Scala, NLP, Java, Kubernetes, Linux",PhD,5,Government,2024-10-27,2024-12-13,1017,5.8,Advanced Robotics +AI04143,Research Scientist,112353,EUR,95500,MI,CT,Netherlands,L,Netherlands,0,"PyTorch, GCP, Mathematics, Deep Learning",Associate,2,Media,2024-11-18,2025-01-29,1367,9.6,Algorithmic Solutions +AI04144,Data Analyst,217691,EUR,185037,EX,FT,Germany,M,Germany,50,"R, SQL, NLP",PhD,10,Real Estate,2025-01-17,2025-03-04,1455,9.8,Machine Intelligence Group +AI04145,Data Engineer,82416,EUR,70054,MI,FL,France,L,France,100,"Git, Tableau, Hadoop, Java, Linux",PhD,2,Telecommunications,2024-07-25,2024-08-08,1499,9.1,Machine Intelligence Group +AI04146,Data Engineer,271408,USD,271408,EX,CT,Finland,L,Finland,50,"Kubernetes, R, SQL",Associate,19,Real Estate,2025-02-22,2025-05-04,2037,5.3,Neural Networks Co +AI04147,Robotics Engineer,50767,USD,50767,EN,FT,Israel,M,Israel,100,"Kubernetes, Git, Python",Master,0,Government,2024-08-13,2024-10-04,735,9.7,DeepTech Ventures +AI04148,Computer Vision Engineer,110614,EUR,94022,SE,FT,France,L,France,100,"SQL, Python, Kubernetes",Master,6,Real Estate,2024-12-11,2025-01-01,1473,5.7,Autonomous Tech +AI04149,Computer Vision Engineer,92141,EUR,78320,MI,CT,Netherlands,M,Spain,100,"Scala, Python, Statistics, Deep Learning",PhD,3,Technology,2024-04-18,2024-05-15,1681,6.9,DeepTech Ventures +AI04150,Machine Learning Engineer,48318,USD,48318,EN,FL,South Korea,M,South Korea,50,"Spark, Kubernetes, Statistics",PhD,1,Retail,2025-04-08,2025-04-22,871,5.6,Cloud AI Solutions +AI04151,Research Scientist,263753,EUR,224190,EX,FL,Austria,L,Austria,100,"Linux, Python, Git, Spark",Bachelor,11,Automotive,2024-04-23,2024-06-02,850,8.3,Algorithmic Solutions +AI04152,Machine Learning Researcher,273323,CHF,245991,EX,PT,Switzerland,M,Switzerland,50,"SQL, Statistics, Tableau",PhD,12,Automotive,2025-04-10,2025-05-26,991,8.7,Machine Intelligence Group +AI04153,Research Scientist,62268,USD,62268,MI,FT,Finland,S,Vietnam,0,"Docker, SQL, Spark, Linux",Associate,2,Transportation,2025-02-21,2025-04-13,1843,6.9,Cognitive Computing +AI04154,NLP Engineer,116686,USD,116686,MI,FT,Ireland,L,Ireland,50,"Azure, SQL, Data Visualization, Python, Kubernetes",Master,2,Finance,2025-04-16,2025-06-21,2006,9.9,Smart Analytics +AI04155,AI Research Scientist,129353,EUR,109950,SE,FL,Germany,M,Germany,0,"Python, Deep Learning, Java",PhD,9,Finance,2024-12-29,2025-03-08,2476,8.5,Smart Analytics +AI04156,Principal Data Scientist,267772,EUR,227606,EX,FT,Netherlands,L,Netherlands,0,"Python, R, MLOps, GCP, Kubernetes",Master,15,Real Estate,2024-12-28,2025-02-11,1950,7.8,Quantum Computing Inc +AI04157,AI Architect,59923,EUR,50935,EN,CT,Netherlands,M,Netherlands,100,"R, Java, Mathematics, MLOps, NLP",Associate,1,Consulting,2025-02-04,2025-04-06,1615,7.1,AI Innovations +AI04158,Data Analyst,75531,USD,75531,EX,CT,India,L,India,0,"Java, R, Spark, MLOps",PhD,11,Manufacturing,2024-11-09,2025-01-18,1354,9.1,Quantum Computing Inc +AI04159,AI Specialist,71196,USD,71196,EN,FL,Israel,L,Chile,0,"Data Visualization, Deep Learning, Docker",Master,1,Transportation,2024-01-27,2024-03-21,2117,9.2,Neural Networks Co +AI04160,AI Specialist,88243,USD,88243,MI,FL,Sweden,S,Germany,50,"SQL, Java, PyTorch",Master,2,Automotive,2024-10-03,2024-10-24,1074,9,Future Systems +AI04161,Robotics Engineer,105621,JPY,11618310,SE,PT,Japan,S,Japan,100,"Python, R, GCP, MLOps, TensorFlow",Associate,7,Gaming,2024-06-03,2024-07-28,889,5.6,AI Innovations +AI04162,AI Product Manager,98658,CAD,123323,SE,CT,Canada,S,Canada,0,"SQL, Scala, Python",Associate,5,Consulting,2024-02-09,2024-03-23,1266,6.2,Algorithmic Solutions +AI04163,Machine Learning Researcher,61301,USD,61301,EX,FL,India,L,India,100,"Python, TensorFlow, GCP",Associate,10,Education,2024-03-19,2024-05-10,1512,7.6,Cognitive Computing +AI04164,Head of AI,170872,USD,170872,EX,FT,Norway,S,Norway,0,"AWS, Hadoop, Data Visualization",PhD,16,Consulting,2024-06-10,2024-07-06,1985,10,Smart Analytics +AI04165,AI Software Engineer,56083,USD,56083,EN,FT,South Korea,L,Nigeria,0,"Kubernetes, Hadoop, Statistics",Bachelor,1,Education,2024-12-06,2025-02-02,1313,8.6,DeepTech Ventures +AI04166,AI Architect,71351,EUR,60648,EN,FL,Netherlands,S,Netherlands,0,"Python, TensorFlow, Computer Vision, PyTorch, SQL",PhD,1,Finance,2024-11-15,2025-01-20,1598,6.3,Cloud AI Solutions +AI04167,Deep Learning Engineer,131806,AUD,177938,SE,CT,Australia,L,Australia,0,"TensorFlow, Linux, Java",Bachelor,6,Retail,2024-08-13,2024-10-04,2368,6.9,Neural Networks Co +AI04168,Head of AI,85952,USD,85952,EN,CT,Norway,M,Norway,50,"NLP, Data Visualization, TensorFlow, Linux",PhD,1,Automotive,2024-01-07,2024-02-24,1437,7.8,Cloud AI Solutions +AI04169,Head of AI,177858,SGD,231215,SE,FT,Singapore,L,Singapore,0,"TensorFlow, Mathematics, Docker, Tableau, Deep Learning",Associate,8,Education,2024-10-02,2024-10-23,1797,9.6,DeepTech Ventures +AI04170,Head of AI,210574,USD,210574,SE,FL,Denmark,L,Chile,0,"Hadoop, Scala, Python, Computer Vision, Deep Learning",Associate,9,Government,2024-08-24,2024-10-31,874,6.1,TechCorp Inc +AI04171,Computer Vision Engineer,96894,USD,96894,MI,FT,South Korea,L,Vietnam,100,"Scala, Spark, Data Visualization",Master,4,Gaming,2024-11-18,2025-01-25,1945,5.2,AI Innovations +AI04172,AI Research Scientist,137829,AUD,186069,EX,FL,Australia,M,Australia,100,"GCP, Hadoop, PyTorch, Spark, R",Bachelor,16,Energy,2024-11-03,2024-12-28,1831,7.4,Neural Networks Co +AI04173,Data Analyst,99906,USD,99906,MI,CT,Israel,M,Israel,50,"Kubernetes, SQL, Python, Deep Learning",Bachelor,4,Education,2024-05-30,2024-07-27,517,8,DeepTech Ventures +AI04174,AI Consultant,78189,CAD,97736,EN,FT,Canada,L,Canada,50,"Docker, GCP, Java, Mathematics",Bachelor,1,Retail,2024-06-21,2024-07-29,2449,5.3,DeepTech Ventures +AI04175,Head of AI,221259,JPY,24338490,EX,CT,Japan,L,Austria,100,"Python, SQL, Scala, Tableau",PhD,12,Energy,2025-01-22,2025-02-15,1106,8.1,AI Innovations +AI04176,Data Engineer,69907,GBP,52430,EN,CT,United Kingdom,S,United Kingdom,100,"GCP, Git, SQL, NLP",Bachelor,1,Retail,2024-09-15,2024-11-01,531,7,Predictive Systems +AI04177,Computer Vision Engineer,114573,EUR,97387,MI,CT,Germany,L,Germany,0,"Scala, TensorFlow, SQL",Master,4,Manufacturing,2024-02-22,2024-03-24,1045,8.9,Algorithmic Solutions +AI04178,Autonomous Systems Engineer,91770,CAD,114713,SE,PT,Canada,S,Canada,100,"Python, Deep Learning, TensorFlow, Hadoop, GCP",Master,7,Finance,2025-02-08,2025-03-04,1669,9.5,Autonomous Tech +AI04179,AI Research Scientist,97661,EUR,83012,SE,FT,Germany,S,Germany,0,"Scala, Data Visualization, Git, AWS, Hadoop",PhD,5,Healthcare,2024-12-24,2025-02-02,1681,7.9,Cognitive Computing +AI04180,Machine Learning Researcher,93001,USD,93001,SE,FT,Israel,S,Israel,0,"R, Kubernetes, AWS",Master,8,Healthcare,2024-05-23,2024-08-01,2033,7.1,Cloud AI Solutions +AI04181,Machine Learning Researcher,138207,CAD,172759,EX,FL,Canada,S,Canada,50,"AWS, Java, Data Visualization",Bachelor,19,Healthcare,2024-01-30,2024-02-22,1932,5.6,Future Systems +AI04182,ML Ops Engineer,87070,EUR,74010,MI,FT,Austria,L,Ghana,0,"Data Visualization, Kubernetes, SQL, Deep Learning, GCP",Bachelor,4,Real Estate,2024-02-17,2024-03-08,1838,5.7,Future Systems +AI04183,Research Scientist,102685,USD,102685,SE,FT,South Korea,S,Indonesia,0,"NLP, Kubernetes, PyTorch, Azure, Tableau",Bachelor,9,Consulting,2024-10-03,2024-11-26,1996,9,DataVision Ltd +AI04184,AI Consultant,36735,USD,36735,MI,CT,India,M,India,0,"Python, AWS, Data Visualization, TensorFlow, Spark",Associate,2,Media,2025-02-12,2025-03-19,1482,7.2,Cognitive Computing +AI04185,Machine Learning Researcher,141810,EUR,120539,EX,PT,Germany,M,Germany,100,"Kubernetes, Azure, Statistics, R, Tableau",Associate,18,Telecommunications,2024-04-09,2024-06-16,1488,5.2,Algorithmic Solutions +AI04186,Head of AI,44764,USD,44764,EN,FT,South Korea,M,South Korea,50,"Spark, Kubernetes, NLP, Python, Linux",Associate,1,Energy,2025-02-08,2025-02-27,910,9.1,Future Systems +AI04187,Machine Learning Engineer,251178,EUR,213501,EX,FL,Austria,L,Austria,0,"GCP, Scala, SQL, Deep Learning",Associate,15,Government,2024-08-10,2024-09-30,674,5,Digital Transformation LLC +AI04188,Autonomous Systems Engineer,293534,USD,293534,EX,CT,Norway,M,Norway,50,"Java, PyTorch, AWS, R, Hadoop",Associate,19,Healthcare,2025-04-13,2025-05-31,1581,5.8,DataVision Ltd +AI04189,Data Scientist,47064,USD,47064,EN,PT,Ireland,S,Ireland,0,"Python, Linux, Computer Vision, Azure",Master,1,Technology,2024-04-16,2024-05-26,941,9.6,TechCorp Inc +AI04190,NLP Engineer,133682,SGD,173787,SE,PT,Singapore,M,Singapore,100,"Data Visualization, Kubernetes, R, AWS, NLP",Master,6,Technology,2024-12-05,2025-02-11,1401,8.7,TechCorp Inc +AI04191,Machine Learning Researcher,104881,GBP,78661,SE,CT,United Kingdom,S,United Kingdom,0,"R, Scala, Linux",PhD,5,Real Estate,2024-12-20,2025-01-26,2075,7.9,Future Systems +AI04192,Data Scientist,93613,USD,93613,EX,FT,India,L,India,100,"Azure, PyTorch, Hadoop",Bachelor,11,Technology,2025-01-05,2025-02-06,672,5.7,AI Innovations +AI04193,AI Architect,207719,USD,207719,EX,FT,Sweden,S,Sweden,50,"Tableau, AWS, PyTorch",Associate,17,Consulting,2024-10-02,2024-12-12,1642,5.8,Autonomous Tech +AI04194,Data Scientist,169583,JPY,18654130,EX,FT,Japan,S,Japan,100,"Python, Statistics, Azure, Tableau, Scala",Associate,15,Transportation,2024-12-09,2025-02-18,2352,7.7,Digital Transformation LLC +AI04195,Data Scientist,102146,CHF,91931,EN,FT,Switzerland,M,Japan,0,"Python, Deep Learning, R",PhD,1,Technology,2025-01-07,2025-02-20,2109,5.2,Machine Intelligence Group +AI04196,AI Product Manager,171881,AUD,232039,SE,FL,Australia,L,Australia,50,"PyTorch, AWS, Data Visualization, Git, Deep Learning",PhD,6,Consulting,2024-05-12,2024-07-24,1188,8.1,AI Innovations +AI04197,Data Scientist,24066,USD,24066,EN,FT,India,S,France,0,"TensorFlow, Computer Vision, Python",Master,0,Finance,2024-12-26,2025-01-09,838,7.7,Cloud AI Solutions +AI04198,AI Architect,149018,EUR,126665,EX,PT,France,L,France,0,"TensorFlow, Docker, Spark, NLP",Associate,18,Finance,2024-09-03,2024-09-22,2468,7.6,Future Systems +AI04199,Principal Data Scientist,119622,AUD,161490,SE,PT,Australia,S,Australia,100,"AWS, Scala, Kubernetes, Mathematics",Bachelor,5,Consulting,2024-01-01,2024-03-14,1210,6.5,Smart Analytics +AI04200,Machine Learning Researcher,135418,USD,135418,SE,FT,Sweden,M,Sweden,0,"Kubernetes, GCP, Docker",PhD,8,Gaming,2024-02-15,2024-04-09,2215,6.1,Algorithmic Solutions +AI04201,Robotics Engineer,80410,GBP,60308,MI,PT,United Kingdom,M,United Kingdom,100,"Scala, PyTorch, NLP",Bachelor,2,Retail,2024-05-12,2024-07-04,2221,8,Predictive Systems +AI04202,AI Architect,158403,JPY,17424330,SE,PT,Japan,M,Netherlands,0,"R, Kubernetes, Git",PhD,6,Real Estate,2024-03-15,2024-05-05,2333,8.8,Machine Intelligence Group +AI04203,Deep Learning Engineer,143401,EUR,121891,EX,CT,Austria,M,Austria,50,"Git, Computer Vision, Statistics, Kubernetes, Java",PhD,18,Telecommunications,2024-01-26,2024-04-04,2218,9.7,Advanced Robotics +AI04204,NLP Engineer,72505,USD,72505,MI,CT,Israel,S,Israel,0,"SQL, Linux, Scala",Bachelor,2,Gaming,2025-04-26,2025-06-01,2155,6.3,Digital Transformation LLC +AI04205,Principal Data Scientist,101052,EUR,85894,MI,CT,France,L,France,100,"Java, Python, Mathematics, GCP, Spark",Bachelor,3,Real Estate,2024-09-09,2024-11-13,2376,6,Algorithmic Solutions +AI04206,Robotics Engineer,90464,CAD,113080,MI,FT,Canada,S,Canada,50,"Scala, Kubernetes, Mathematics, Tableau, Hadoop",Master,3,Finance,2024-11-29,2025-01-16,1450,5.1,DeepTech Ventures +AI04207,Machine Learning Engineer,155870,USD,155870,EX,CT,Finland,M,Finland,100,"GCP, SQL, PyTorch, Data Visualization",Bachelor,18,Technology,2024-06-03,2024-08-08,2068,8.4,TechCorp Inc +AI04208,Autonomous Systems Engineer,86105,USD,86105,EX,FL,India,M,India,100,"TensorFlow, Linux, Azure, Kubernetes, Spark",Associate,16,Finance,2025-01-30,2025-03-07,2236,7.9,Algorithmic Solutions +AI04209,AI Software Engineer,60304,EUR,51258,EN,PT,Germany,M,Germany,100,"SQL, Scala, Azure",Master,1,Media,2024-09-27,2024-12-04,1530,8.9,Algorithmic Solutions +AI04210,NLP Engineer,158258,USD,158258,SE,CT,Denmark,S,Denmark,50,"NLP, MLOps, Python, Deep Learning",Master,8,Finance,2024-07-18,2024-08-18,1416,9.5,Future Systems +AI04211,Robotics Engineer,139108,USD,139108,SE,FT,Denmark,M,Hungary,50,"GCP, R, Spark, Data Visualization, Docker",PhD,7,Healthcare,2024-05-05,2024-05-19,2202,7.9,Advanced Robotics +AI04212,Robotics Engineer,127647,GBP,95735,SE,FL,United Kingdom,L,United Kingdom,50,"SQL, Kubernetes, TensorFlow, AWS, R",Master,8,Gaming,2024-06-22,2024-07-14,1248,8.1,Smart Analytics +AI04213,NLP Engineer,113026,CAD,141283,SE,FT,Canada,L,Canada,50,"NLP, Linux, Python, Deep Learning, Java",Associate,8,Gaming,2025-01-09,2025-02-21,1025,8.4,AI Innovations +AI04214,NLP Engineer,160446,USD,160446,EX,FT,United States,M,United States,50,"Mathematics, SQL, MLOps, PyTorch",Associate,16,Manufacturing,2024-04-26,2024-07-07,2148,5.5,AI Innovations +AI04215,Research Scientist,170414,USD,170414,SE,FT,Denmark,S,Denmark,50,"Kubernetes, Azure, Computer Vision",Associate,5,Gaming,2024-08-14,2024-09-16,2394,8.1,Predictive Systems +AI04216,Robotics Engineer,153701,USD,153701,EX,FT,Finland,L,France,100,"Spark, Kubernetes, Statistics",PhD,15,Telecommunications,2024-08-04,2024-09-08,641,6.6,Neural Networks Co +AI04217,AI Research Scientist,66536,SGD,86497,EN,FT,Singapore,M,Singapore,50,"Mathematics, SQL, Kubernetes",Bachelor,1,Government,2024-03-17,2024-04-17,952,9.9,Cloud AI Solutions +AI04218,Autonomous Systems Engineer,144573,USD,144573,EX,CT,South Korea,S,South Korea,100,"Linux, Statistics, GCP, Python, Computer Vision",PhD,18,Energy,2024-11-30,2025-02-10,1931,8,Quantum Computing Inc +AI04219,Autonomous Systems Engineer,39124,USD,39124,SE,FT,India,M,India,0,"Deep Learning, MLOps, Statistics, Spark",Master,5,Manufacturing,2024-10-12,2024-11-15,2309,5.7,Quantum Computing Inc +AI04220,Machine Learning Researcher,148877,EUR,126545,SE,FL,Netherlands,L,Netherlands,50,"Hadoop, Docker, NLP",Associate,5,Consulting,2024-06-28,2024-08-17,1349,9.8,Smart Analytics +AI04221,Research Scientist,62439,AUD,84293,EN,FT,Australia,S,Australia,100,"Java, Python, Kubernetes, GCP",Bachelor,1,Technology,2024-06-05,2024-06-29,1944,7.9,DeepTech Ventures +AI04222,Data Analyst,70705,USD,70705,MI,PT,South Korea,M,South Korea,0,"Data Visualization, Hadoop, Tableau, Mathematics, Linux",PhD,4,Healthcare,2025-01-21,2025-03-04,2030,5.6,DataVision Ltd +AI04223,AI Software Engineer,136064,USD,136064,EX,PT,Israel,M,Israel,100,"SQL, Python, Tableau",Master,13,Energy,2024-12-26,2025-01-14,2276,9.4,DataVision Ltd +AI04224,Machine Learning Researcher,114102,GBP,85577,SE,CT,United Kingdom,S,United Kingdom,50,"GCP, AWS, NLP",Bachelor,9,Manufacturing,2025-02-20,2025-03-15,515,9.1,Neural Networks Co +AI04225,ML Ops Engineer,48875,USD,48875,SE,CT,China,S,Germany,0,"Spark, PyTorch, Java, NLP",Associate,7,Education,2024-05-15,2024-06-07,843,10,Neural Networks Co +AI04226,ML Ops Engineer,66920,USD,66920,EN,CT,Denmark,M,Kenya,0,"Deep Learning, Linux, Computer Vision",Bachelor,1,Gaming,2025-02-18,2025-04-04,1486,7,AI Innovations +AI04227,Deep Learning Engineer,60046,USD,60046,EN,FT,United States,S,Australia,0,"Git, Scala, NLP, SQL, Azure",Bachelor,1,Transportation,2025-04-27,2025-06-06,992,7.9,Machine Intelligence Group +AI04228,Machine Learning Engineer,65824,EUR,55950,MI,FL,France,S,France,0,"Azure, GCP, Mathematics, Scala, TensorFlow",Associate,4,Government,2024-03-31,2024-05-26,639,9.4,Predictive Systems +AI04229,Computer Vision Engineer,92205,USD,92205,MI,FL,Finland,M,Finland,0,"Git, Spark, Deep Learning, AWS",Bachelor,4,Transportation,2024-06-18,2024-08-03,1381,5.8,DataVision Ltd +AI04230,Principal Data Scientist,69016,EUR,58664,MI,FL,Germany,S,Germany,50,"Spark, Linux, Kubernetes, Mathematics",Associate,2,Finance,2024-03-20,2024-04-26,954,6,Machine Intelligence Group +AI04231,AI Consultant,71384,USD,71384,EN,FL,Ireland,M,Ireland,100,"Python, Java, Deep Learning",PhD,0,Finance,2024-01-12,2024-02-27,1060,7.8,DataVision Ltd +AI04232,Data Scientist,63659,EUR,54110,EN,PT,Germany,S,United States,100,"GCP, SQL, Tableau, MLOps",Associate,0,Technology,2024-11-29,2025-01-18,1082,9.9,DeepTech Ventures +AI04233,AI Research Scientist,117611,GBP,88208,SE,FL,United Kingdom,M,Vietnam,0,"PyTorch, Tableau, Hadoop, TensorFlow, Statistics",Associate,7,Media,2025-01-05,2025-01-24,1849,6.6,Digital Transformation LLC +AI04234,Deep Learning Engineer,48074,USD,48074,EN,FL,Sweden,S,Sweden,0,"PyTorch, Python, Spark, Azure, SQL",Bachelor,0,Government,2024-12-26,2025-01-23,606,7.4,Future Systems +AI04235,Principal Data Scientist,122232,EUR,103897,SE,CT,Germany,S,Colombia,0,"R, Java, GCP, Python, Hadoop",Associate,8,Automotive,2025-02-27,2025-03-13,1471,5,Digital Transformation LLC +AI04236,Head of AI,197539,EUR,167908,EX,FL,France,L,Turkey,0,"Kubernetes, PyTorch, Docker, TensorFlow, Python",Master,13,Consulting,2025-01-01,2025-02-26,904,7,Cloud AI Solutions +AI04237,AI Specialist,255683,EUR,217331,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Tableau, Azure",Associate,18,Telecommunications,2024-03-15,2024-04-25,1130,9,Cognitive Computing +AI04238,Machine Learning Engineer,77121,USD,77121,EN,FL,Israel,L,Hungary,100,"SQL, Azure, PyTorch",Associate,1,Consulting,2024-10-06,2024-12-18,2312,6.9,Predictive Systems +AI04239,ML Ops Engineer,52575,USD,52575,MI,FL,China,L,South Africa,50,"Hadoop, Git, Python, Kubernetes",Bachelor,4,Finance,2025-01-23,2025-03-16,624,9.7,Machine Intelligence Group +AI04240,Autonomous Systems Engineer,86907,EUR,73871,SE,CT,Austria,S,Austria,100,"Spark, Data Visualization, AWS, R",Associate,6,Retail,2024-01-18,2024-03-11,733,7.3,Advanced Robotics +AI04241,Computer Vision Engineer,148771,EUR,126455,SE,CT,Germany,M,Germany,0,"Spark, Kubernetes, Deep Learning",Associate,6,Retail,2025-02-12,2025-02-26,2370,9.4,Autonomous Tech +AI04242,Deep Learning Engineer,124742,EUR,106031,SE,FL,Netherlands,L,Netherlands,0,"Python, Scala, Linux, Tableau, TensorFlow",Bachelor,7,Media,2024-11-13,2025-01-07,972,5.2,Cognitive Computing +AI04243,AI Specialist,80538,USD,80538,MI,PT,Sweden,M,Sweden,0,"Hadoop, Azure, Computer Vision, SQL, R",Bachelor,3,Manufacturing,2024-05-26,2024-07-25,1372,7.4,TechCorp Inc +AI04244,Deep Learning Engineer,261998,CHF,235798,EX,FT,Switzerland,S,Switzerland,0,"NLP, R, Computer Vision, Python, Azure",Bachelor,13,Energy,2024-01-21,2024-03-29,751,8.6,Future Systems +AI04245,Data Scientist,161380,JPY,17751800,EX,FT,Japan,M,Japan,0,"Python, Scala, Computer Vision, Hadoop",Master,13,Media,2024-05-14,2024-06-26,1306,6.2,Digital Transformation LLC +AI04246,Research Scientist,114449,USD,114449,SE,PT,Ireland,S,Thailand,0,"Scala, Git, SQL, NLP",PhD,8,Telecommunications,2024-04-22,2024-06-30,683,7.6,Autonomous Tech +AI04247,Robotics Engineer,65542,AUD,88482,EN,FT,Australia,M,Malaysia,0,"Java, Deep Learning, PyTorch, Data Visualization, Tableau",Associate,1,Education,2024-06-29,2024-09-01,1053,7,Predictive Systems +AI04248,Machine Learning Researcher,177905,JPY,19569550,EX,CT,Japan,M,Japan,100,"Kubernetes, SQL, Deep Learning",Bachelor,10,Transportation,2024-01-12,2024-03-07,1848,9.9,Cloud AI Solutions +AI04249,NLP Engineer,89958,SGD,116945,EN,FL,Singapore,L,Singapore,0,"Java, Docker, Deep Learning",Bachelor,1,Automotive,2025-01-04,2025-03-08,993,7.6,AI Innovations +AI04250,Data Scientist,50166,USD,50166,EN,CT,South Korea,S,South Korea,100,"Deep Learning, R, MLOps, Tableau, Scala",Associate,0,Automotive,2024-09-20,2024-11-21,1812,6.3,Cognitive Computing +AI04251,Research Scientist,153548,USD,153548,MI,FT,Denmark,L,Denmark,50,"Statistics, Spark, SQL",PhD,3,Manufacturing,2024-12-03,2025-01-01,977,6,Neural Networks Co +AI04252,AI Research Scientist,199709,CHF,179738,SE,CT,Switzerland,M,Switzerland,100,"GCP, R, NLP, Deep Learning",Associate,9,Consulting,2024-09-29,2024-11-07,992,5.7,Digital Transformation LLC +AI04253,Research Scientist,106748,USD,106748,SE,PT,South Korea,M,South Korea,50,"Scala, Kubernetes, SQL, NLP",Associate,5,Finance,2024-08-11,2024-10-05,501,5.7,Predictive Systems +AI04254,AI Consultant,164745,CHF,148271,SE,PT,Switzerland,S,Switzerland,100,"Computer Vision, NLP, Kubernetes, Scala, Java",Associate,6,Consulting,2024-04-08,2024-05-09,2246,7.6,Cloud AI Solutions +AI04255,Principal Data Scientist,74190,EUR,63062,MI,FL,Austria,S,Austria,0,"Java, PyTorch, Docker, Computer Vision, GCP",Associate,4,Energy,2024-06-10,2024-06-28,1983,9.9,Digital Transformation LLC +AI04256,AI Specialist,77889,EUR,66206,EN,FT,Netherlands,L,Netherlands,100,"Linux, Mathematics, MLOps",Associate,1,Transportation,2024-05-29,2024-07-24,517,6.5,Autonomous Tech +AI04257,Autonomous Systems Engineer,172285,EUR,146442,EX,PT,Austria,S,Austria,100,"Python, Java, Git, AWS, TensorFlow",Master,10,Automotive,2024-05-20,2024-07-15,1924,7.6,Machine Intelligence Group +AI04258,Robotics Engineer,192684,JPY,21195240,EX,FL,Japan,S,Japan,100,"Mathematics, TensorFlow, Deep Learning, Git, Spark",Associate,17,Manufacturing,2024-04-02,2024-05-25,509,5.2,Advanced Robotics +AI04259,Machine Learning Engineer,62085,USD,62085,SE,PT,China,L,China,50,"NLP, PyTorch, Kubernetes, Linux, SQL",Bachelor,6,Technology,2024-11-25,2025-01-24,2146,9.1,AI Innovations +AI04260,Autonomous Systems Engineer,70641,USD,70641,SE,FT,China,M,China,50,"Statistics, R, Python, Git",Master,9,Retail,2024-02-10,2024-03-13,960,9.9,Neural Networks Co +AI04261,Deep Learning Engineer,57845,AUD,78091,EN,CT,Australia,S,Australia,50,"Statistics, Python, PyTorch, R, Spark",Associate,1,Technology,2025-04-19,2025-05-15,1260,5.4,Quantum Computing Inc +AI04262,Deep Learning Engineer,70641,USD,70641,EX,PT,India,S,India,0,"Statistics, Tableau, R, Spark, GCP",Associate,18,Government,2024-10-30,2024-11-19,623,9.6,Autonomous Tech +AI04263,NLP Engineer,266056,SGD,345873,EX,FL,Singapore,L,Singapore,50,"SQL, PyTorch, NLP, Python",Associate,13,Transportation,2024-02-02,2024-03-01,1761,9.8,Digital Transformation LLC +AI04264,AI Software Engineer,39810,USD,39810,MI,PT,China,L,India,100,"PyTorch, Spark, Data Visualization, Kubernetes",Master,3,Telecommunications,2024-10-30,2024-12-17,1598,7.4,Algorithmic Solutions +AI04265,ML Ops Engineer,46834,USD,46834,MI,FT,China,L,China,0,"Git, GCP, AWS, Mathematics",Bachelor,3,Media,2024-06-30,2024-08-02,2086,7.2,AI Innovations +AI04266,Autonomous Systems Engineer,151336,GBP,113502,SE,FT,United Kingdom,L,United Kingdom,100,"Kubernetes, Python, Scala, GCP",Bachelor,7,Technology,2025-03-26,2025-04-16,930,7.3,Cloud AI Solutions +AI04267,AI Consultant,76149,EUR,64727,EN,PT,Austria,L,Austria,0,"Linux, Hadoop, Statistics, Scala, Mathematics",PhD,0,Technology,2025-04-08,2025-06-09,2299,9.7,Cognitive Computing +AI04268,AI Specialist,132231,USD,132231,EX,PT,Israel,S,Israel,100,"Tableau, Python, TensorFlow",Master,11,Automotive,2024-09-20,2024-11-24,526,6.7,Cognitive Computing +AI04269,AI Consultant,163387,USD,163387,SE,CT,Denmark,M,Denmark,50,"R, AWS, Git, Data Visualization",Bachelor,7,Transportation,2024-08-19,2024-10-30,635,5.8,DataVision Ltd +AI04270,Deep Learning Engineer,63017,SGD,81922,EN,CT,Singapore,M,Singapore,50,"Spark, Python, Java, Docker, Scala",Associate,1,Media,2024-12-10,2025-02-10,2238,5.3,Predictive Systems +AI04271,NLP Engineer,33704,USD,33704,MI,FT,India,S,Austria,0,"Java, Python, Mathematics, Git",PhD,4,Technology,2024-10-13,2024-12-18,1957,9.6,Smart Analytics +AI04272,NLP Engineer,199909,USD,199909,EX,CT,Finland,M,Finland,100,"Spark, Git, Linux, Statistics",Master,10,Technology,2024-08-31,2024-09-21,2126,7.7,Future Systems +AI04273,AI Specialist,109037,USD,109037,MI,PT,United States,M,United States,0,"Kubernetes, Python, PyTorch",PhD,2,Consulting,2024-04-29,2024-06-25,1905,6.3,Algorithmic Solutions +AI04274,Data Analyst,79918,EUR,67930,EN,FT,France,L,France,50,"Spark, Computer Vision, AWS, SQL",Associate,0,Gaming,2024-03-12,2024-04-05,2142,6.6,DataVision Ltd +AI04275,Data Analyst,140756,EUR,119643,EX,CT,Austria,S,Romania,50,"MLOps, Python, Tableau",PhD,12,Education,2025-03-06,2025-03-28,1437,5.1,Autonomous Tech +AI04276,Research Scientist,193092,CAD,241365,EX,CT,Canada,S,France,0,"Scala, Git, Data Visualization, Mathematics, Tableau",Associate,14,Automotive,2024-10-29,2024-11-12,2415,9.2,Quantum Computing Inc +AI04277,Head of AI,152328,USD,152328,MI,FT,Norway,L,Norway,50,"Java, Python, AWS",Associate,4,Healthcare,2024-10-09,2024-12-07,1932,6.3,Advanced Robotics +AI04278,NLP Engineer,115808,USD,115808,MI,FL,Norway,L,Norway,100,"Python, TensorFlow, Mathematics, Scala",Bachelor,3,Telecommunications,2024-03-27,2024-04-29,1892,7.4,Cognitive Computing +AI04279,Head of AI,123117,EUR,104649,SE,CT,Austria,S,Austria,50,"Git, AWS, Docker",Bachelor,6,Automotive,2025-01-14,2025-03-02,951,6.4,DataVision Ltd +AI04280,AI Architect,48031,USD,48031,EN,CT,Israel,S,New Zealand,100,"PyTorch, Mathematics, MLOps, SQL, Deep Learning",PhD,1,Automotive,2024-05-15,2024-06-08,1171,6.9,DeepTech Ventures +AI04281,Research Scientist,267720,USD,267720,EX,FL,United States,S,United States,100,"Tableau, Scala, Hadoop, SQL, Kubernetes",Master,16,Technology,2024-07-19,2024-08-30,2497,9.6,Neural Networks Co +AI04282,Head of AI,130274,JPY,14330140,SE,FT,Japan,L,Luxembourg,50,"SQL, Docker, PyTorch, Git",Master,5,Government,2025-04-21,2025-06-04,2222,5.6,Neural Networks Co +AI04283,Deep Learning Engineer,217100,USD,217100,SE,CT,Norway,L,Hungary,0,"Java, Computer Vision, SQL, NLP, Linux",Master,9,Retail,2025-03-08,2025-04-15,593,5.2,Autonomous Tech +AI04284,AI Software Engineer,69518,USD,69518,EN,FT,Denmark,S,Denmark,100,"NLP, SQL, Linux, Scala",Bachelor,1,Education,2024-03-09,2024-03-25,1880,7.4,Cognitive Computing +AI04285,AI Specialist,149647,CAD,187059,EX,FL,Canada,S,Canada,0,"Spark, SQL, Python, Computer Vision",Associate,14,Finance,2025-03-12,2025-05-15,2155,9.2,Digital Transformation LLC +AI04286,NLP Engineer,56185,SGD,73041,EN,PT,Singapore,S,New Zealand,50,"Kubernetes, Data Visualization, Python, TensorFlow, GCP",Bachelor,1,Transportation,2025-04-11,2025-06-10,1919,5.2,Future Systems +AI04287,Head of AI,47695,USD,47695,EN,FT,Sweden,S,Sweden,50,"Spark, Kubernetes, NLP, TensorFlow, Deep Learning",PhD,0,Gaming,2024-01-14,2024-02-24,1378,7.9,DeepTech Ventures +AI04288,AI Specialist,100301,EUR,85256,SE,PT,Germany,S,Germany,50,"Hadoop, Kubernetes, Scala, Computer Vision",PhD,7,Retail,2024-07-17,2024-08-31,1403,9.4,Quantum Computing Inc +AI04289,Machine Learning Engineer,66736,USD,66736,MI,FL,South Korea,M,South Korea,100,"Linux, Kubernetes, Data Visualization, Hadoop, Computer Vision",PhD,4,Gaming,2024-08-25,2024-09-20,754,5.8,Future Systems +AI04290,Principal Data Scientist,71795,JPY,7897450,EN,FL,Japan,L,Egypt,50,"SQL, PyTorch, TensorFlow, Azure",PhD,1,Government,2024-03-21,2024-04-26,2175,5.4,Cognitive Computing +AI04291,ML Ops Engineer,40743,USD,40743,MI,FT,China,M,China,50,"SQL, PyTorch, Data Visualization, Scala",PhD,4,Consulting,2024-05-01,2024-06-09,1212,5.2,Quantum Computing Inc +AI04292,Deep Learning Engineer,50361,EUR,42807,EN,FT,France,M,Belgium,100,"Linux, SQL, Hadoop, Python, Computer Vision",Bachelor,1,Media,2024-09-02,2024-09-25,607,7.3,Algorithmic Solutions +AI04293,Computer Vision Engineer,25504,USD,25504,EN,CT,India,S,India,100,"Python, Deep Learning, NLP, Mathematics, Spark",Master,0,Manufacturing,2024-12-01,2025-01-31,1174,6.5,Algorithmic Solutions +AI04294,Robotics Engineer,100549,USD,100549,SE,FT,South Korea,S,Spain,50,"Kubernetes, Statistics, Spark",Master,5,Healthcare,2024-07-23,2024-09-25,1869,8.2,Autonomous Tech +AI04295,Machine Learning Engineer,96451,EUR,81983,SE,PT,Austria,S,Austria,50,"Deep Learning, Git, Python",Master,7,Transportation,2024-12-23,2025-02-16,1078,7.9,Quantum Computing Inc +AI04296,NLP Engineer,94478,USD,94478,SE,FL,Sweden,S,Sweden,0,"Data Visualization, Computer Vision, Kubernetes",Bachelor,9,Media,2024-04-18,2024-06-14,677,8.3,Autonomous Tech +AI04297,Data Analyst,69250,EUR,58863,EN,CT,Netherlands,S,Ukraine,100,"Linux, PyTorch, R, Java, Git",Master,1,Automotive,2025-01-17,2025-03-05,1851,5.7,DataVision Ltd +AI04298,Data Analyst,99816,USD,99816,MI,CT,Ireland,L,Estonia,100,"Docker, Python, MLOps, Linux, TensorFlow",PhD,2,Retail,2024-02-29,2024-04-10,1889,9.9,Advanced Robotics +AI04299,Data Scientist,151190,USD,151190,SE,FL,Sweden,M,Sweden,100,"Kubernetes, Hadoop, Scala",Bachelor,7,Automotive,2024-04-24,2024-05-23,1258,9.2,Algorithmic Solutions +AI04300,Principal Data Scientist,234904,JPY,25839440,EX,PT,Japan,S,Japan,50,"Kubernetes, Data Visualization, Spark, Docker",PhD,15,Manufacturing,2024-08-03,2024-09-25,1974,9.6,Autonomous Tech +AI04301,AI Architect,100583,CHF,90525,EN,CT,Switzerland,L,China,100,"Computer Vision, AWS, Scala",Bachelor,1,Government,2024-05-11,2024-07-03,1471,8,DeepTech Ventures +AI04302,Head of AI,193990,USD,193990,EX,PT,United States,L,Israel,0,"Python, Kubernetes, Tableau",Associate,15,Consulting,2024-12-25,2025-03-03,2132,8.8,Digital Transformation LLC +AI04303,AI Product Manager,138206,EUR,117475,SE,FL,France,L,United Kingdom,100,"Statistics, PyTorch, Computer Vision, Mathematics, TensorFlow",Associate,7,Education,2025-03-24,2025-05-05,2261,8.5,Neural Networks Co +AI04304,Data Analyst,130833,AUD,176625,SE,PT,Australia,M,Austria,50,"Git, Scala, TensorFlow, AWS, R",Associate,6,Telecommunications,2024-12-06,2025-02-08,1325,6.7,DataVision Ltd +AI04305,Data Scientist,178524,USD,178524,SE,PT,Denmark,M,Sweden,50,"Python, Azure, Tableau, Hadoop",PhD,9,Healthcare,2024-01-31,2024-03-14,1457,7,Quantum Computing Inc +AI04306,NLP Engineer,58009,USD,58009,EN,FT,South Korea,S,South Korea,0,"Data Visualization, Git, Hadoop, SQL",PhD,0,Finance,2024-04-12,2024-05-18,650,9.2,Predictive Systems +AI04307,Autonomous Systems Engineer,51134,USD,51134,MI,CT,China,L,China,100,"TensorFlow, Statistics, Deep Learning",Bachelor,2,Education,2024-09-22,2024-11-21,2371,9,Future Systems +AI04308,Data Engineer,121528,EUR,103299,SE,FT,Germany,M,Germany,100,"TensorFlow, Kubernetes, Computer Vision, Tableau, Data Visualization",Associate,7,Energy,2025-04-03,2025-06-07,1250,5.6,Advanced Robotics +AI04309,NLP Engineer,161005,USD,161005,SE,CT,Israel,L,Israel,50,"Spark, PyTorch, Tableau",Bachelor,8,Transportation,2024-09-14,2024-10-22,2281,8.4,DeepTech Ventures +AI04310,Head of AI,172723,GBP,129542,EX,FL,United Kingdom,M,Ireland,50,"SQL, Git, PyTorch, Linux, Data Visualization",Bachelor,11,Media,2024-03-12,2024-05-19,2264,8.2,Advanced Robotics +AI04311,AI Consultant,124515,EUR,105838,EX,CT,Austria,S,Latvia,100,"Docker, Linux, Data Visualization, SQL",PhD,13,Transportation,2025-02-24,2025-05-06,2164,6.2,Cloud AI Solutions +AI04312,AI Research Scientist,80001,CAD,100001,EN,CT,Canada,L,Canada,0,"Docker, Kubernetes, Spark",Bachelor,1,Manufacturing,2024-01-19,2024-02-02,827,6,Neural Networks Co +AI04313,ML Ops Engineer,106148,EUR,90226,SE,CT,Netherlands,S,Ghana,0,"SQL, TensorFlow, Hadoop",Master,8,Education,2024-12-05,2025-02-10,1912,5.4,Cognitive Computing +AI04314,Computer Vision Engineer,88162,EUR,74938,MI,FL,France,M,France,50,"Data Visualization, Scala, GCP, Python, PyTorch",Master,2,Real Estate,2025-04-16,2025-05-29,1187,5.3,DeepTech Ventures +AI04315,Principal Data Scientist,80965,USD,80965,MI,CT,Israel,S,Argentina,0,"Tableau, Linux, Azure",Master,3,Gaming,2025-03-16,2025-04-03,1786,6,Predictive Systems +AI04316,AI Software Engineer,102591,USD,102591,MI,FL,Sweden,L,Sweden,50,"Docker, SQL, Hadoop, PyTorch",Bachelor,3,Real Estate,2024-06-14,2024-07-17,1331,6.2,Autonomous Tech +AI04317,Data Analyst,83458,CAD,104323,EN,FL,Canada,L,Romania,0,"Mathematics, Kubernetes, MLOps, Hadoop",Bachelor,0,Consulting,2024-06-14,2024-08-21,1749,6.3,Quantum Computing Inc +AI04318,Machine Learning Engineer,131559,EUR,111825,SE,CT,Germany,S,Austria,0,"Hadoop, Linux, Docker",PhD,5,Transportation,2024-01-12,2024-02-25,1897,8.8,Predictive Systems +AI04319,Robotics Engineer,103944,USD,103944,MI,FT,Finland,M,Finland,100,"Linux, MLOps, Computer Vision",PhD,2,Government,2024-10-04,2024-12-14,661,5.1,Smart Analytics +AI04320,AI Specialist,92612,USD,92612,EX,FL,China,S,China,0,"Java, Kubernetes, Python, Git",Bachelor,18,Consulting,2024-12-05,2025-02-02,2154,8.7,Autonomous Tech +AI04321,AI Product Manager,91367,USD,91367,SE,PT,South Korea,M,Luxembourg,100,"Azure, TensorFlow, Tableau, Hadoop",Master,5,Healthcare,2024-03-16,2024-05-04,1310,9.8,TechCorp Inc +AI04322,Deep Learning Engineer,102393,CHF,92154,EN,FL,Switzerland,L,Romania,100,"Azure, Deep Learning, Linux, Tableau, SQL",PhD,1,Consulting,2025-04-29,2025-06-12,1531,7.9,Digital Transformation LLC +AI04323,Computer Vision Engineer,126897,EUR,107862,EX,PT,Austria,S,Austria,50,"Python, SQL, Linux",Bachelor,17,Transportation,2024-07-30,2024-08-21,2068,9.9,Future Systems +AI04324,Deep Learning Engineer,49677,USD,49677,EN,FL,Israel,S,Canada,50,"Tableau, Docker, Kubernetes, Scala, Deep Learning",Bachelor,0,Manufacturing,2024-07-04,2024-08-30,2192,9.4,DataVision Ltd +AI04325,Data Scientist,220260,USD,220260,EX,FT,Sweden,S,Sweden,100,"Data Visualization, TensorFlow, Java, Docker",Master,19,Real Estate,2024-06-24,2024-08-24,1627,5.8,Autonomous Tech +AI04326,NLP Engineer,124924,USD,124924,SE,FL,South Korea,M,Singapore,50,"Linux, SQL, PyTorch",Master,6,Consulting,2024-11-13,2024-12-11,2445,8.4,Machine Intelligence Group +AI04327,Autonomous Systems Engineer,221162,USD,221162,SE,FT,Denmark,L,Denmark,100,"PyTorch, Scala, TensorFlow",PhD,8,Government,2024-07-18,2024-09-24,2325,9.6,Predictive Systems +AI04328,Deep Learning Engineer,68143,EUR,57922,EN,FT,France,S,Colombia,100,"Scala, TensorFlow, Azure, Mathematics",PhD,0,Energy,2024-06-07,2024-06-28,504,7.4,DataVision Ltd +AI04329,Machine Learning Engineer,139571,USD,139571,MI,FL,Denmark,L,Germany,0,"Kubernetes, Spark, PyTorch, Docker, AWS",Associate,2,Healthcare,2024-03-23,2024-05-26,2296,8.7,Advanced Robotics +AI04330,Data Analyst,75216,EUR,63934,MI,CT,Austria,M,Austria,50,"Scala, SQL, PyTorch",Associate,4,Education,2024-05-30,2024-08-04,2468,5.5,TechCorp Inc +AI04331,Data Scientist,185001,USD,185001,EX,CT,Denmark,S,Denmark,100,"Mathematics, Python, NLP",Bachelor,16,Gaming,2025-01-16,2025-03-25,1924,8,Smart Analytics +AI04332,AI Software Engineer,92328,JPY,10156080,MI,CT,Japan,L,Japan,50,"Python, GCP, Docker, Data Visualization, Linux",Master,2,Gaming,2024-01-28,2024-04-10,914,8.2,Predictive Systems +AI04333,AI Product Manager,100927,USD,100927,MI,FT,Denmark,S,Canada,50,"Docker, Tableau, Python, Linux, Mathematics",Bachelor,4,Energy,2025-03-20,2025-04-04,787,8.1,AI Innovations +AI04334,Deep Learning Engineer,99845,SGD,129799,MI,CT,Singapore,L,Singapore,0,"Python, Computer Vision, Scala, Docker",PhD,4,Automotive,2024-08-31,2024-10-08,812,8.4,Neural Networks Co +AI04335,Autonomous Systems Engineer,77405,EUR,65794,EN,CT,Germany,L,Austria,0,"Data Visualization, R, Java, Spark, Linux",Bachelor,0,Consulting,2024-05-01,2024-06-13,649,6,Algorithmic Solutions +AI04336,Deep Learning Engineer,60738,GBP,45554,EN,PT,United Kingdom,S,United Kingdom,50,"Python, Docker, AWS, TensorFlow",Master,0,Automotive,2024-03-22,2024-04-26,555,5.7,Digital Transformation LLC +AI04337,AI Software Engineer,105471,JPY,11601810,MI,FL,Japan,L,Japan,0,"Git, Deep Learning, Statistics",Master,4,Energy,2024-06-18,2024-08-02,1116,6.6,Machine Intelligence Group +AI04338,Deep Learning Engineer,159419,USD,159419,EX,FL,Israel,S,Ghana,0,"Deep Learning, SQL, Tableau, Linux",Master,18,Healthcare,2024-01-03,2024-01-28,925,9.1,AI Innovations +AI04339,ML Ops Engineer,90738,SGD,117959,MI,PT,Singapore,M,Singapore,0,"Spark, GCP, Tableau",Bachelor,3,Energy,2024-12-14,2025-01-14,2148,9,Future Systems +AI04340,Machine Learning Engineer,90479,USD,90479,MI,FT,Finland,S,Austria,50,"Java, Python, GCP, Mathematics, TensorFlow",Bachelor,3,Media,2025-02-13,2025-04-22,2020,8.3,Advanced Robotics +AI04341,NLP Engineer,155058,USD,155058,SE,FL,Ireland,L,Ireland,100,"Data Visualization, Python, SQL",Associate,9,Manufacturing,2024-11-21,2024-12-28,1821,8.5,Machine Intelligence Group +AI04342,AI Research Scientist,85529,USD,85529,MI,CT,Israel,S,Israel,50,"Deep Learning, Mathematics, GCP, Kubernetes, Git",Master,2,Consulting,2024-01-12,2024-02-28,1458,7.7,Quantum Computing Inc +AI04343,AI Research Scientist,86082,SGD,111907,MI,FL,Singapore,S,Singapore,100,"Hadoop, Deep Learning, Computer Vision, PyTorch, R",Master,4,Transportation,2025-01-27,2025-03-26,1346,5.7,DataVision Ltd +AI04344,Autonomous Systems Engineer,96560,USD,96560,EN,FT,Norway,L,Norway,50,"R, Spark, SQL, Deep Learning, Python",PhD,1,Automotive,2024-09-22,2024-11-24,1139,8.2,Machine Intelligence Group +AI04345,Research Scientist,83531,EUR,71001,EN,PT,Austria,L,Ghana,100,"TensorFlow, Kubernetes, Mathematics, NLP",Bachelor,0,Gaming,2024-12-04,2025-01-15,1024,5.5,Predictive Systems +AI04346,AI Research Scientist,113892,EUR,96808,SE,FL,Germany,S,Singapore,100,"Data Visualization, Scala, Deep Learning, Docker",Bachelor,8,Automotive,2025-02-16,2025-03-05,863,8,DeepTech Ventures +AI04347,Data Engineer,261519,JPY,28767090,EX,CT,Japan,M,Japan,50,"R, PyTorch, Scala",PhD,18,Media,2024-07-10,2024-08-28,1671,5.4,Neural Networks Co +AI04348,AI Consultant,112036,USD,112036,MI,CT,Israel,L,Israel,50,"Python, MLOps, TensorFlow",PhD,4,Transportation,2025-02-11,2025-04-25,2093,6.4,Autonomous Tech +AI04349,Data Analyst,91847,USD,91847,EN,PT,Sweden,L,Sweden,100,"Deep Learning, Java, Tableau, PyTorch, Git",Associate,0,Government,2024-02-17,2024-03-15,1937,9.1,Cognitive Computing +AI04350,NLP Engineer,58336,USD,58336,EN,FL,Sweden,S,Sweden,0,"TensorFlow, Java, R",Associate,1,Consulting,2025-02-27,2025-05-03,1310,5.9,Digital Transformation LLC +AI04351,AI Research Scientist,66684,USD,66684,EN,CT,Ireland,M,Ireland,0,"SQL, Python, AWS, TensorFlow",Associate,1,Technology,2025-03-07,2025-04-19,533,7.4,Cloud AI Solutions +AI04352,Research Scientist,91813,USD,91813,MI,PT,Ireland,M,Ireland,0,"R, Mathematics, Tableau, NLP, Data Visualization",Bachelor,3,Gaming,2024-12-26,2025-02-18,1649,7.9,TechCorp Inc +AI04353,AI Consultant,138037,USD,138037,SE,CT,United States,M,United States,0,"Azure, TensorFlow, GCP",Master,7,Transportation,2024-03-25,2024-04-27,1243,7.5,Autonomous Tech +AI04354,Data Analyst,118721,USD,118721,EN,CT,Denmark,L,New Zealand,50,"Hadoop, Tableau, Azure, MLOps, PyTorch",Associate,1,Real Estate,2025-03-21,2025-04-15,2159,7.7,Digital Transformation LLC +AI04355,NLP Engineer,70536,USD,70536,EN,FL,Israel,L,Ghana,50,"Azure, Scala, Docker",Master,1,Technology,2024-04-20,2024-06-05,2136,8.6,Future Systems +AI04356,Research Scientist,96320,EUR,81872,MI,PT,France,L,France,0,"Kubernetes, TensorFlow, NLP",Associate,4,Gaming,2024-12-26,2025-02-28,1277,5.5,TechCorp Inc +AI04357,Head of AI,134322,EUR,114174,SE,FT,Austria,L,Austria,100,"GCP, Deep Learning, Git, Python",Bachelor,8,Consulting,2024-02-03,2024-04-13,848,6.9,Autonomous Tech +AI04358,Robotics Engineer,61853,USD,61853,EN,FL,United States,M,United States,100,"Spark, R, Data Visualization",Master,0,Finance,2024-04-10,2024-05-17,1366,7.6,TechCorp Inc +AI04359,Robotics Engineer,118786,EUR,100968,SE,CT,Austria,S,Austria,0,"Scala, SQL, Computer Vision",Bachelor,5,Consulting,2024-07-22,2024-08-19,818,8.3,Cognitive Computing +AI04360,Autonomous Systems Engineer,63582,USD,63582,EN,FL,Ireland,S,Ireland,50,"Spark, AWS, GCP",PhD,1,Media,2024-01-11,2024-03-21,2243,9.4,Cognitive Computing +AI04361,Machine Learning Engineer,120025,AUD,162034,SE,FT,Australia,L,Norway,50,"PyTorch, Kubernetes, Spark, Java, Mathematics",Bachelor,8,Transportation,2025-03-13,2025-04-02,2126,7.5,Quantum Computing Inc +AI04362,Data Analyst,69623,EUR,59180,MI,CT,France,S,France,0,"Python, SQL, Java, R, AWS",PhD,2,Real Estate,2024-12-02,2025-01-02,1244,9.6,Machine Intelligence Group +AI04363,AI Architect,84572,USD,84572,EN,CT,Denmark,M,Denmark,50,"NLP, Computer Vision, Data Visualization, Deep Learning",Master,0,Finance,2024-07-03,2024-08-31,1897,8,Machine Intelligence Group +AI04364,Machine Learning Engineer,75649,USD,75649,SE,CT,China,L,China,100,"TensorFlow, Linux, Spark, Python, Azure",PhD,8,Transportation,2024-07-23,2024-09-19,1102,5.3,Smart Analytics +AI04365,AI Software Engineer,101898,USD,101898,EN,FL,Norway,M,Netherlands,50,"Python, Scala, Docker, Mathematics, AWS",Bachelor,1,Automotive,2024-03-26,2024-04-18,2051,5.1,Smart Analytics +AI04366,AI Product Manager,146918,EUR,124880,SE,FT,Netherlands,M,Kenya,50,"R, MLOps, PyTorch, NLP",Master,6,Energy,2024-02-18,2024-03-08,770,10,Advanced Robotics +AI04367,Principal Data Scientist,48437,USD,48437,SE,PT,India,S,Norway,100,"Hadoop, Linux, Azure, Computer Vision",PhD,6,Government,2024-12-31,2025-01-23,1949,8.8,DeepTech Ventures +AI04368,AI Software Engineer,156021,USD,156021,EX,CT,Israel,L,Ireland,100,"Scala, Python, SQL",Associate,15,Energy,2024-10-16,2024-12-16,2144,9,DataVision Ltd +AI04369,Research Scientist,142101,USD,142101,SE,PT,Sweden,L,Sweden,100,"Kubernetes, Java, Data Visualization",Master,7,Energy,2024-01-16,2024-03-26,623,6.7,Advanced Robotics +AI04370,AI Research Scientist,85556,EUR,72723,MI,PT,Germany,L,Germany,0,"TensorFlow, Tableau, Python, GCP",Associate,4,Telecommunications,2024-11-06,2025-01-04,1206,8.4,Quantum Computing Inc +AI04371,AI Research Scientist,36647,USD,36647,MI,PT,China,S,Turkey,0,"Java, AWS, GCP, Computer Vision",PhD,2,Retail,2025-03-11,2025-04-20,2008,7.2,Digital Transformation LLC +AI04372,Data Scientist,82294,EUR,69950,MI,CT,Austria,L,Denmark,50,"Spark, Mathematics, Deep Learning, Computer Vision",Master,2,Finance,2024-02-01,2024-03-25,1644,7.3,Predictive Systems +AI04373,AI Specialist,91519,AUD,123551,MI,FL,Australia,L,Australia,100,"Data Visualization, GCP, AWS, Docker",Bachelor,2,Real Estate,2025-04-13,2025-06-10,2219,6.2,Digital Transformation LLC +AI04374,Data Analyst,67529,USD,67529,SE,CT,China,L,Kenya,0,"Spark, Linux, Data Visualization, Scala",Master,7,Consulting,2025-01-24,2025-02-13,1676,6,AI Innovations +AI04375,Data Engineer,194639,USD,194639,EX,FT,Ireland,L,Ireland,0,"Tableau, NLP, SQL",Bachelor,13,Manufacturing,2024-05-04,2024-07-13,1333,5.7,Algorithmic Solutions +AI04376,AI Product Manager,194962,USD,194962,EX,FL,South Korea,M,South Korea,0,"Tableau, Azure, PyTorch, AWS",PhD,17,Real Estate,2024-12-12,2025-02-01,513,6.2,TechCorp Inc +AI04377,Machine Learning Engineer,68003,CAD,85004,MI,FL,Canada,M,Canada,0,"PyTorch, Linux, TensorFlow, Spark",PhD,3,Gaming,2024-08-11,2024-08-26,534,6.1,Digital Transformation LLC +AI04378,Data Engineer,160113,USD,160113,SE,FL,United States,L,United States,100,"Python, Scala, Azure, AWS",Master,7,Automotive,2024-10-07,2024-11-30,1941,6.5,DeepTech Ventures +AI04379,Head of AI,51041,USD,51041,EN,FT,Ireland,S,Ireland,50,"Hadoop, Linux, Mathematics",Associate,0,Government,2025-01-06,2025-01-24,1849,7.6,Autonomous Tech +AI04380,Robotics Engineer,123576,USD,123576,MI,CT,Denmark,S,Denmark,0,"Java, R, Tableau, AWS",Bachelor,3,Healthcare,2024-04-11,2024-05-21,1068,8.6,Advanced Robotics +AI04381,Machine Learning Researcher,76765,EUR,65250,MI,FT,Netherlands,M,Australia,100,"R, SQL, Tableau, Docker, Deep Learning",Associate,2,Finance,2024-10-25,2024-12-25,1685,6.4,TechCorp Inc +AI04382,Data Scientist,212410,USD,212410,EX,CT,Israel,L,Israel,100,"Hadoop, Azure, Statistics",Bachelor,17,Retail,2024-09-28,2024-11-01,1414,9.4,Cognitive Computing +AI04383,Computer Vision Engineer,64240,USD,64240,SE,PT,China,M,China,50,"Hadoop, Scala, PyTorch",Bachelor,8,Retail,2024-09-01,2024-10-28,2324,6.4,Neural Networks Co +AI04384,Autonomous Systems Engineer,132240,USD,132240,EX,CT,Finland,M,Spain,0,"Tableau, Python, Spark, Statistics",PhD,16,Real Estate,2024-08-22,2024-10-19,1289,8.4,Quantum Computing Inc +AI04385,Machine Learning Engineer,90724,CAD,113405,MI,PT,Canada,S,Belgium,0,"Python, GCP, TensorFlow, Spark, AWS",Master,3,Telecommunications,2024-06-29,2024-08-26,1928,7.8,Cloud AI Solutions +AI04386,Machine Learning Researcher,210905,USD,210905,EX,FT,Norway,L,Norway,100,"PyTorch, TensorFlow, Tableau, Data Visualization, Python",Master,12,Real Estate,2024-03-24,2024-05-11,1507,8.1,Cloud AI Solutions +AI04387,AI Product Manager,113235,AUD,152867,SE,PT,Australia,S,Argentina,0,"Python, TensorFlow, Azure",Master,7,Gaming,2024-03-03,2024-04-25,617,8,Algorithmic Solutions +AI04388,AI Software Engineer,167568,EUR,142433,EX,PT,France,S,United States,50,"Mathematics, PyTorch, SQL, Git, Docker",PhD,19,Government,2025-04-20,2025-05-13,1087,6.4,Quantum Computing Inc +AI04389,Data Engineer,60687,USD,60687,EN,FL,Finland,M,Finland,0,"AWS, NLP, Statistics, Python, Deep Learning",PhD,1,Consulting,2024-07-28,2024-09-29,1930,5.3,Advanced Robotics +AI04390,Computer Vision Engineer,140330,USD,140330,EX,PT,Finland,S,Belgium,50,"Python, Scala, Hadoop, Computer Vision, TensorFlow",PhD,16,Technology,2024-08-13,2024-10-12,1619,7.5,DeepTech Ventures +AI04391,Machine Learning Researcher,87316,EUR,74219,MI,FL,Netherlands,S,Netherlands,50,"Data Visualization, Azure, Git",Bachelor,2,Automotive,2024-04-25,2024-06-13,558,7,Cloud AI Solutions +AI04392,AI Software Engineer,103223,USD,103223,EN,CT,United States,L,United States,50,"Linux, Docker, NLP, Computer Vision, Kubernetes",Bachelor,0,Real Estate,2024-12-01,2025-02-02,1214,5,Advanced Robotics +AI04393,Head of AI,259484,GBP,194613,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, Hadoop, TensorFlow, GCP",PhD,19,Energy,2025-01-04,2025-03-16,1671,5.7,Predictive Systems +AI04394,Machine Learning Researcher,83379,USD,83379,EN,FL,United States,S,United States,100,"Tableau, Scala, SQL",PhD,1,Energy,2024-04-16,2024-05-07,831,6.5,Predictive Systems +AI04395,ML Ops Engineer,108902,GBP,81677,MI,FT,United Kingdom,M,United Kingdom,0,"Linux, MLOps, Data Visualization",Bachelor,3,Technology,2024-04-27,2024-06-13,1500,9.9,Future Systems +AI04396,Data Engineer,56324,USD,56324,EN,FT,Finland,L,Finland,0,"R, SQL, MLOps, Linux",PhD,1,Gaming,2024-02-29,2024-03-16,1319,9.6,Cognitive Computing +AI04397,Principal Data Scientist,117902,EUR,100217,MI,FL,Netherlands,L,Netherlands,100,"Deep Learning, Python, NLP",Bachelor,4,Technology,2024-09-06,2024-10-22,2283,5.6,Algorithmic Solutions +AI04398,AI Software Engineer,113637,EUR,96591,MI,FT,Netherlands,L,Netherlands,50,"Scala, SQL, Statistics",Master,3,Retail,2025-02-15,2025-03-31,1625,7.6,Neural Networks Co +AI04399,AI Specialist,100672,EUR,85571,MI,PT,Germany,M,Israel,100,"R, SQL, TensorFlow",Associate,3,Retail,2024-12-11,2025-02-16,1012,8.1,Cognitive Computing +AI04400,Robotics Engineer,59217,JPY,6513870,EN,FL,Japan,S,Nigeria,100,"SQL, R, Data Visualization",Bachelor,0,Technology,2024-05-26,2024-07-02,1332,6.2,Cloud AI Solutions +AI04401,AI Specialist,180746,USD,180746,EX,FL,Ireland,L,Ireland,0,"Scala, Azure, NLP",Bachelor,18,Finance,2024-02-29,2024-04-12,778,9,Cognitive Computing +AI04402,NLP Engineer,76000,AUD,102600,EN,FT,Australia,M,Russia,50,"Azure, Hadoop, Tableau",Bachelor,1,Retail,2025-02-21,2025-03-30,1457,9,Digital Transformation LLC +AI04403,AI Consultant,158289,CAD,197861,EX,CT,Canada,S,Canada,50,"Azure, Python, AWS, TensorFlow",Associate,19,Finance,2024-03-29,2024-05-07,904,6.7,Autonomous Tech +AI04404,AI Software Engineer,210409,USD,210409,EX,CT,South Korea,L,Denmark,100,"Git, Statistics, Azure, SQL, Computer Vision",Bachelor,12,Telecommunications,2024-05-24,2024-06-13,1401,9.6,AI Innovations +AI04405,Data Analyst,72009,USD,72009,MI,CT,Ireland,S,Ireland,0,"Kubernetes, Tableau, TensorFlow, MLOps, Python",PhD,2,Healthcare,2025-01-15,2025-02-17,1726,7,AI Innovations +AI04406,Computer Vision Engineer,216981,SGD,282075,EX,FT,Singapore,L,Estonia,0,"SQL, MLOps, Git, Docker",Master,12,Government,2025-02-02,2025-02-20,884,5.1,Cognitive Computing +AI04407,AI Architect,125378,USD,125378,MI,FL,Denmark,M,Denmark,100,"Spark, Computer Vision, NLP, R",Bachelor,4,Consulting,2024-07-28,2024-08-17,1609,8.1,Advanced Robotics +AI04408,Machine Learning Researcher,80879,USD,80879,MI,CT,United States,S,United States,50,"AWS, Tableau, Linux",PhD,3,Automotive,2024-10-17,2024-12-25,1607,8.5,Cloud AI Solutions +AI04409,Data Scientist,304522,SGD,395879,EX,FT,Singapore,L,Vietnam,0,"TensorFlow, Python, Tableau, Docker",Master,10,Consulting,2025-03-09,2025-05-03,2161,9.3,Autonomous Tech +AI04410,Autonomous Systems Engineer,106646,USD,106646,MI,FT,Sweden,M,Sweden,50,"Java, Kubernetes, Tableau, SQL",PhD,3,Automotive,2025-02-15,2025-03-23,2468,7,Neural Networks Co +AI04411,AI Architect,91413,SGD,118837,MI,PT,Singapore,M,Spain,100,"Mathematics, Computer Vision, NLP, TensorFlow",PhD,4,Technology,2024-11-24,2025-01-13,881,9,Neural Networks Co +AI04412,Deep Learning Engineer,224651,USD,224651,EX,FL,Denmark,L,Denmark,100,"Git, Kubernetes, Python",Bachelor,19,Technology,2024-12-11,2025-02-14,1208,9.4,DataVision Ltd +AI04413,AI Architect,130860,USD,130860,EX,PT,South Korea,L,South Korea,50,"TensorFlow, Docker, MLOps, Kubernetes, Data Visualization",PhD,13,Education,2025-03-19,2025-04-27,1934,7.1,Smart Analytics +AI04414,Machine Learning Researcher,46877,USD,46877,EN,CT,Israel,S,Israel,100,"NLP, TensorFlow, Mathematics, MLOps",PhD,0,Consulting,2024-05-28,2024-06-13,2354,7,Digital Transformation LLC +AI04415,Deep Learning Engineer,179047,EUR,152190,EX,PT,France,M,France,0,"NLP, Docker, Mathematics, Computer Vision, PyTorch",Master,18,Media,2024-10-13,2024-10-27,2472,9.9,Machine Intelligence Group +AI04416,Data Engineer,104146,EUR,88524,SE,FL,Austria,M,Turkey,0,"Docker, Python, Mathematics",PhD,8,Technology,2024-03-15,2024-05-04,1388,5,Machine Intelligence Group +AI04417,AI Consultant,31567,USD,31567,MI,FL,India,S,India,0,"Kubernetes, Git, GCP, Linux",Bachelor,2,Manufacturing,2025-01-23,2025-03-27,1204,6.6,DataVision Ltd +AI04418,Principal Data Scientist,97690,USD,97690,SE,FL,South Korea,S,Kenya,100,"Linux, Computer Vision, Deep Learning, Kubernetes",PhD,7,Transportation,2024-08-22,2024-09-17,2486,6.6,Autonomous Tech +AI04419,Head of AI,62371,AUD,84201,EN,FT,Australia,M,Australia,50,"Azure, NLP, SQL",PhD,0,Technology,2024-09-13,2024-10-11,1120,7.4,DeepTech Ventures +AI04420,AI Product Manager,262516,CHF,236264,EX,FL,Switzerland,L,Switzerland,50,"Scala, Spark, Docker, Kubernetes",Bachelor,19,Media,2024-09-02,2024-10-15,614,9.1,Cognitive Computing +AI04421,AI Specialist,75844,CAD,94805,MI,FL,Canada,S,India,100,"TensorFlow, Kubernetes, Tableau",Associate,2,Energy,2024-05-27,2024-07-01,2116,9.7,Future Systems +AI04422,Data Scientist,131997,JPY,14519670,SE,FL,Japan,L,Thailand,0,"Kubernetes, PyTorch, Computer Vision",Master,5,Government,2024-07-10,2024-08-23,1204,6.1,Smart Analytics +AI04423,Principal Data Scientist,103953,EUR,88360,MI,FT,Netherlands,M,Netherlands,0,"SQL, NLP, PyTorch, Computer Vision, Hadoop",Master,3,Transportation,2024-12-25,2025-01-28,1919,5.8,TechCorp Inc +AI04424,AI Specialist,177676,USD,177676,SE,PT,Denmark,L,Denmark,0,"Azure, Java, Python, Linux, Statistics",Bachelor,8,Finance,2024-11-21,2024-12-30,2199,9.3,Algorithmic Solutions +AI04425,AI Product Manager,122946,AUD,165977,SE,PT,Australia,S,Australia,0,"Spark, Kubernetes, Git, Java, GCP",PhD,9,Education,2024-12-26,2025-02-23,835,7.1,TechCorp Inc +AI04426,Head of AI,202266,USD,202266,EX,CT,Israel,S,Israel,50,"GCP, Computer Vision, SQL, Azure",Associate,12,Healthcare,2024-08-02,2024-09-17,1550,5.9,AI Innovations +AI04427,Machine Learning Engineer,42862,USD,42862,SE,FL,India,S,Russia,100,"Git, Java, Kubernetes, R, Mathematics",Bachelor,5,Gaming,2024-11-08,2025-01-17,1330,6.6,DeepTech Ventures +AI04428,Data Scientist,221324,USD,221324,SE,FT,Norway,L,Spain,100,"Spark, R, Tableau, Python, Linux",Bachelor,7,Retail,2025-04-01,2025-04-29,1133,7.6,Predictive Systems +AI04429,Machine Learning Researcher,129064,SGD,167783,MI,CT,Singapore,L,Hungary,100,"Python, Hadoop, Statistics",Bachelor,4,Manufacturing,2024-07-07,2024-09-17,2002,5.8,TechCorp Inc +AI04430,Computer Vision Engineer,116116,CAD,145145,SE,FT,Canada,L,Singapore,100,"AWS, SQL, Deep Learning, Kubernetes",PhD,8,Manufacturing,2024-06-25,2024-07-12,849,8.3,Algorithmic Solutions +AI04431,Data Scientist,204614,AUD,276229,EX,CT,Australia,L,Australia,0,"Linux, MLOps, NLP, PyTorch",Associate,19,Telecommunications,2025-04-07,2025-04-23,1784,9.7,Neural Networks Co +AI04432,Data Engineer,44008,USD,44008,EX,FT,India,S,India,100,"TensorFlow, Python, Java, Scala, Azure",PhD,15,Transportation,2024-03-12,2024-04-08,1391,5.9,Smart Analytics +AI04433,AI Research Scientist,59937,USD,59937,SE,PT,China,M,Indonesia,100,"PyTorch, TensorFlow, Git",Bachelor,9,Technology,2024-08-21,2024-11-02,798,9.2,Predictive Systems +AI04434,AI Product Manager,86443,USD,86443,MI,PT,Israel,S,Belgium,50,"SQL, Java, MLOps",Master,4,Technology,2024-10-15,2024-11-10,1882,5.9,Digital Transformation LLC +AI04435,AI Specialist,104949,SGD,136434,SE,FL,Singapore,S,Singapore,50,"Java, Linux, Spark",Bachelor,6,Manufacturing,2024-06-07,2024-08-15,855,9.8,Digital Transformation LLC +AI04436,Principal Data Scientist,186813,USD,186813,EX,CT,Ireland,S,France,100,"NLP, Linux, Java",Bachelor,17,Healthcare,2024-01-03,2024-03-12,958,8.6,Algorithmic Solutions +AI04437,AI Specialist,211822,JPY,23300420,EX,FL,Japan,L,Indonesia,50,"Computer Vision, Hadoop, Python, SQL",Bachelor,13,Transportation,2024-03-23,2024-05-05,2204,9.4,Cognitive Computing +AI04438,AI Consultant,153646,SGD,199740,EX,FL,Singapore,M,Romania,100,"Mathematics, PyTorch, MLOps",Master,18,Real Estate,2024-01-07,2024-03-14,607,7.6,DeepTech Ventures +AI04439,Data Analyst,117982,USD,117982,SE,PT,Israel,M,Israel,0,"Python, Linux, R, TensorFlow",PhD,5,Gaming,2024-02-18,2024-04-23,752,9.9,Quantum Computing Inc +AI04440,Data Engineer,133740,SGD,173862,SE,FL,Singapore,S,Mexico,0,"Java, SQL, Mathematics, Deep Learning",Associate,9,Government,2025-01-10,2025-01-24,2271,7.8,Algorithmic Solutions +AI04441,Machine Learning Researcher,84175,USD,84175,EN,FL,Denmark,S,Chile,0,"Azure, Mathematics, MLOps, Scala, Git",Bachelor,1,Healthcare,2024-02-17,2024-04-07,2409,6.9,Smart Analytics +AI04442,Computer Vision Engineer,87366,GBP,65525,MI,CT,United Kingdom,S,Vietnam,0,"Azure, Python, Data Visualization, Mathematics, Computer Vision",Bachelor,2,Consulting,2024-11-26,2024-12-11,1180,10,Digital Transformation LLC +AI04443,Autonomous Systems Engineer,110287,USD,110287,MI,CT,Sweden,L,Vietnam,50,"GCP, Spark, Azure, PyTorch",Bachelor,4,Retail,2025-02-14,2025-03-21,674,7.8,Quantum Computing Inc +AI04444,Data Scientist,104258,USD,104258,SE,CT,South Korea,L,South Korea,0,"Statistics, Kubernetes, R, Java",Associate,8,Automotive,2024-10-26,2024-12-01,2028,9.2,Machine Intelligence Group +AI04445,AI Software Engineer,114211,USD,114211,EN,FT,Denmark,L,Ireland,100,"Python, Kubernetes, Docker",PhD,0,Healthcare,2025-01-07,2025-03-10,1349,9,DeepTech Ventures +AI04446,Head of AI,194011,EUR,164909,EX,PT,France,L,France,100,"PyTorch, Python, NLP, Hadoop",Master,18,Healthcare,2025-04-08,2025-06-06,814,8.4,Algorithmic Solutions +AI04447,Principal Data Scientist,293192,USD,293192,EX,FL,Sweden,L,Sweden,50,"Azure, AWS, Linux, Scala, R",Associate,13,Technology,2024-12-07,2025-01-29,2000,8.4,Future Systems +AI04448,Robotics Engineer,53874,EUR,45793,EN,FL,France,S,France,100,"GCP, R, Statistics",PhD,1,Manufacturing,2024-03-15,2024-04-01,503,6.9,TechCorp Inc +AI04449,Robotics Engineer,88454,USD,88454,SE,CT,Finland,S,Finland,0,"Docker, Hadoop, GCP, Java, Scala",PhD,7,Media,2025-04-25,2025-06-28,2354,5.2,Predictive Systems +AI04450,Robotics Engineer,161911,SGD,210484,EX,CT,Singapore,S,Singapore,50,"SQL, Scala, Linux, Azure",Associate,11,Healthcare,2024-11-04,2025-01-11,1397,8.7,DeepTech Ventures +AI04451,AI Consultant,64565,USD,64565,MI,FT,South Korea,S,South Korea,100,"Hadoop, Git, Tableau, NLP, Azure",PhD,4,Gaming,2024-09-13,2024-10-18,2397,8.1,DeepTech Ventures +AI04452,Data Scientist,47708,USD,47708,EN,CT,Israel,S,Philippines,100,"Python, TensorFlow, Azure, Linux",Bachelor,1,Technology,2024-06-13,2024-07-03,1203,9.5,DeepTech Ventures +AI04453,AI Product Manager,140313,SGD,182407,SE,FL,Singapore,M,Singapore,50,"Mathematics, Scala, Deep Learning",Master,6,Energy,2024-08-15,2024-09-27,1946,6.2,Neural Networks Co +AI04454,AI Software Engineer,94235,JPY,10365850,EN,FL,Japan,L,Spain,100,"R, Tableau, Python, Azure, TensorFlow",Associate,1,Consulting,2024-05-05,2024-07-07,2010,9.2,Machine Intelligence Group +AI04455,Data Engineer,57467,USD,57467,MI,CT,South Korea,S,South Korea,0,"Computer Vision, Spark, Docker, Hadoop, Python",PhD,3,Government,2024-07-21,2024-08-18,1968,8,Neural Networks Co +AI04456,AI Research Scientist,129225,SGD,167993,SE,PT,Singapore,M,Finland,0,"Hadoop, Python, PyTorch, Git",Associate,9,Healthcare,2025-03-22,2025-05-16,1335,5.9,DeepTech Ventures +AI04457,Data Scientist,157816,USD,157816,EX,PT,Ireland,M,Ireland,100,"Scala, GCP, AWS",Bachelor,12,Manufacturing,2025-04-22,2025-06-12,733,10,Neural Networks Co +AI04458,Data Engineer,77796,EUR,66127,MI,FL,Austria,S,Austria,50,"Python, TensorFlow, Tableau",Bachelor,2,Automotive,2024-01-09,2024-01-26,832,5.4,Predictive Systems +AI04459,Deep Learning Engineer,202840,EUR,172414,EX,FT,Netherlands,S,Netherlands,0,"Git, Spark, Computer Vision, Tableau, Java",Associate,17,Manufacturing,2025-02-22,2025-03-18,1954,8.6,Smart Analytics +AI04460,Data Scientist,77051,AUD,104019,EN,FL,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch",Master,0,Media,2024-09-30,2024-11-08,2129,5.6,Advanced Robotics +AI04461,AI Specialist,105395,AUD,142283,MI,FT,Australia,L,Australia,50,"Linux, Git, Kubernetes, NLP, Python",Master,2,Transportation,2024-06-25,2024-08-27,1203,7.1,TechCorp Inc +AI04462,AI Research Scientist,83359,EUR,70855,EN,FL,Netherlands,M,Netherlands,100,"Kubernetes, Java, Data Visualization",Bachelor,0,Real Estate,2025-01-21,2025-02-19,1507,5.4,Machine Intelligence Group +AI04463,Machine Learning Engineer,98213,CHF,88392,EN,CT,Switzerland,L,Switzerland,0,"Java, SQL, Kubernetes, PyTorch",Associate,1,Media,2024-12-23,2025-01-23,1844,8.8,Cognitive Computing +AI04464,AI Software Engineer,39868,USD,39868,MI,FL,China,S,China,100,"R, Docker, TensorFlow, Git",Master,2,Automotive,2024-09-25,2024-11-20,526,5.1,Future Systems +AI04465,Computer Vision Engineer,246512,USD,246512,EX,CT,Norway,M,Norway,0,"Data Visualization, Git, Linux",Bachelor,19,Manufacturing,2025-01-24,2025-03-24,2255,10,Quantum Computing Inc +AI04466,AI Software Engineer,77063,USD,77063,EX,CT,India,M,India,50,"MLOps, Git, Kubernetes",Associate,18,Media,2025-03-31,2025-05-21,680,9.8,Advanced Robotics +AI04467,Principal Data Scientist,60066,EUR,51056,EN,PT,Germany,L,Germany,50,"Deep Learning, Scala, Data Visualization",Associate,0,Media,2024-11-03,2024-11-25,1884,9.6,Quantum Computing Inc +AI04468,NLP Engineer,93900,USD,93900,MI,CT,Ireland,L,Ireland,50,"Linux, AWS, NLP, Git",Bachelor,3,Retail,2024-11-04,2024-12-02,918,5.8,DeepTech Ventures +AI04469,Machine Learning Engineer,132017,EUR,112214,SE,PT,Germany,L,China,50,"GCP, Statistics, SQL, TensorFlow",PhD,7,Technology,2025-03-15,2025-05-08,1645,9.5,Cognitive Computing +AI04470,Head of AI,94447,USD,94447,MI,CT,Norway,S,Norway,0,"Kubernetes, SQL, TensorFlow, PyTorch",Master,4,Education,2024-11-14,2025-01-04,1613,7.8,Cognitive Computing +AI04471,AI Software Engineer,65304,USD,65304,EX,FL,India,M,India,50,"MLOps, Python, TensorFlow, Docker",Associate,12,Finance,2024-07-19,2024-08-04,574,5.8,Cognitive Computing +AI04472,AI Software Engineer,172150,EUR,146328,SE,FL,Netherlands,L,Netherlands,100,"Spark, PyTorch, Data Visualization, Computer Vision",Associate,9,Transportation,2024-11-26,2024-12-10,2024,5.7,Digital Transformation LLC +AI04473,NLP Engineer,88827,USD,88827,MI,FT,Ireland,M,Ireland,50,"Computer Vision, R, Azure, Deep Learning, MLOps",Bachelor,4,Retail,2024-07-13,2024-09-06,2422,7.2,Future Systems +AI04474,Data Engineer,144886,AUD,195596,SE,FT,Australia,L,Australia,0,"Git, GCP, Linux, Computer Vision",Master,8,Manufacturing,2024-07-09,2024-09-11,1834,8.3,Future Systems +AI04475,Research Scientist,133043,USD,133043,EX,FL,Israel,S,France,0,"Python, Deep Learning, Java",PhD,16,Transportation,2024-04-05,2024-06-06,2319,8.8,Advanced Robotics +AI04476,AI Software Engineer,127811,EUR,108639,SE,FL,Netherlands,L,Ireland,50,"Scala, Azure, Docker, AWS, Mathematics",Associate,7,Automotive,2024-11-27,2024-12-24,1278,9.6,Quantum Computing Inc +AI04477,Computer Vision Engineer,103521,CAD,129401,SE,CT,Canada,S,Canada,50,"R, Java, Tableau, Docker",Associate,7,Real Estate,2024-01-04,2024-02-16,2044,5.6,Predictive Systems +AI04478,Research Scientist,54480,SGD,70824,EN,FL,Singapore,M,Singapore,50,"Spark, TensorFlow, MLOps, Python",Master,1,Education,2025-01-30,2025-02-17,1495,9.3,Autonomous Tech +AI04479,Principal Data Scientist,74709,EUR,63503,MI,FL,France,M,France,50,"Scala, Git, MLOps, Statistics",Bachelor,4,Technology,2024-09-11,2024-10-15,1967,5.8,Machine Intelligence Group +AI04480,Computer Vision Engineer,59379,USD,59379,EN,FL,Israel,S,Czech Republic,100,"Java, Computer Vision, MLOps",PhD,1,Government,2025-01-18,2025-02-14,2335,8,Advanced Robotics +AI04481,AI Product Manager,61440,USD,61440,SE,FT,China,M,Japan,0,"Scala, Mathematics, Java",PhD,5,Telecommunications,2024-08-17,2024-10-11,1501,8,Neural Networks Co +AI04482,Autonomous Systems Engineer,134360,GBP,100770,EX,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Python, NLP, TensorFlow, Java",Master,17,Gaming,2024-04-11,2024-05-05,2337,7,Autonomous Tech +AI04483,AI Product Manager,225183,JPY,24770130,EX,FL,Japan,S,Japan,50,"Data Visualization, MLOps, TensorFlow",PhD,13,Energy,2024-10-12,2024-12-17,729,8.6,Algorithmic Solutions +AI04484,Principal Data Scientist,262051,CAD,327564,EX,FT,Canada,L,Colombia,100,"R, Tableau, Statistics, Hadoop, SQL",Bachelor,18,Government,2025-01-30,2025-02-20,678,5.4,Digital Transformation LLC +AI04485,ML Ops Engineer,51148,USD,51148,MI,FL,China,L,Norway,50,"Docker, MLOps, Hadoop, R, Azure",Bachelor,3,Energy,2024-11-06,2024-12-17,1629,9.4,Smart Analytics +AI04486,Deep Learning Engineer,50384,USD,50384,SE,CT,India,L,Finland,100,"Azure, NLP, Spark, Tableau",Bachelor,9,Technology,2024-11-21,2024-12-31,1978,7.9,Algorithmic Solutions +AI04487,Autonomous Systems Engineer,45747,CAD,57184,EN,PT,Canada,S,Philippines,0,"Azure, Docker, Deep Learning, Data Visualization, Python",Master,1,Manufacturing,2024-09-27,2024-12-03,2476,8.3,AI Innovations +AI04488,AI Architect,27660,USD,27660,EN,CT,China,M,China,50,"PyTorch, Git, Hadoop",Master,0,Healthcare,2024-09-12,2024-10-31,2159,7.4,Future Systems +AI04489,Machine Learning Researcher,66412,USD,66412,EN,CT,Finland,L,Finland,0,"Python, Linux, Spark, NLP",Associate,1,Gaming,2024-10-27,2024-11-26,1366,7.1,Autonomous Tech +AI04490,Computer Vision Engineer,286005,USD,286005,EX,CT,Ireland,L,Ireland,100,"R, Python, TensorFlow, PyTorch",Associate,15,Telecommunications,2024-03-06,2024-05-04,1637,9.4,Digital Transformation LLC +AI04491,Data Scientist,162115,EUR,137798,EX,PT,Austria,S,South Africa,50,"Hadoop, PyTorch, Git, R",Master,15,Automotive,2024-09-21,2024-10-27,780,6.4,AI Innovations +AI04492,Autonomous Systems Engineer,179992,JPY,19799120,EX,FL,Japan,M,Japan,50,"Scala, Azure, Deep Learning, Data Visualization",Master,10,Media,2025-01-23,2025-02-12,2176,8.4,Future Systems +AI04493,Data Analyst,52604,USD,52604,EN,FL,Sweden,S,Finland,50,"NLP, Scala, Data Visualization, Kubernetes",Bachelor,1,Energy,2025-01-15,2025-02-20,2181,9.8,DataVision Ltd +AI04494,AI Consultant,135693,USD,135693,MI,FL,Norway,L,Switzerland,0,"Kubernetes, PyTorch, GCP, Scala",Bachelor,2,Healthcare,2024-05-16,2024-05-30,1410,7.8,Autonomous Tech +AI04495,Data Scientist,132806,USD,132806,SE,CT,Norway,M,Norway,100,"Java, PyTorch, Data Visualization, Deep Learning, GCP",PhD,5,Government,2024-08-09,2024-09-10,745,10,TechCorp Inc +AI04496,AI Consultant,119154,CHF,107239,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Tableau, PyTorch",PhD,3,Technology,2024-04-25,2024-07-05,1701,5.6,TechCorp Inc +AI04497,NLP Engineer,116153,CHF,104538,EN,FT,Switzerland,L,Switzerland,0,"PyTorch, SQL, Docker, Deep Learning",PhD,1,Telecommunications,2024-05-22,2024-07-08,2130,5.5,DataVision Ltd +AI04498,AI Product Manager,122285,USD,122285,SE,FL,Norway,S,South Africa,50,"Computer Vision, R, Java, Azure",PhD,7,Consulting,2024-08-05,2024-10-07,1831,8.3,Digital Transformation LLC +AI04499,AI Research Scientist,87146,USD,87146,SE,FL,South Korea,M,South Korea,0,"R, Linux, MLOps, Mathematics, Git",Bachelor,7,Retail,2025-01-06,2025-03-05,2199,5.7,AI Innovations +AI04500,Head of AI,101820,AUD,137457,MI,CT,Australia,M,Ukraine,50,"AWS, Statistics, Data Visualization",Associate,4,Technology,2025-03-18,2025-04-17,1073,6.2,AI Innovations +AI04501,AI Research Scientist,76032,EUR,64627,MI,FL,France,M,Netherlands,100,"PyTorch, GCP, TensorFlow, NLP, Python",Bachelor,3,Consulting,2024-09-08,2024-10-08,1911,8.6,Digital Transformation LLC +AI04502,AI Software Engineer,138064,JPY,15187040,SE,FL,Japan,L,Japan,100,"GCP, PyTorch, Spark",Bachelor,5,Government,2024-02-22,2024-03-17,1028,8.1,Smart Analytics +AI04503,Research Scientist,131574,AUD,177625,SE,FL,Australia,L,Philippines,0,"Python, Spark, Azure, Linux",Bachelor,6,Finance,2024-09-30,2024-11-24,1280,6.4,Digital Transformation LLC +AI04504,Head of AI,366922,CHF,330230,EX,FL,Switzerland,L,Malaysia,0,"TensorFlow, Computer Vision, Hadoop, Python, MLOps",Bachelor,14,Real Estate,2024-01-21,2024-02-06,2396,9.3,Quantum Computing Inc +AI04505,AI Consultant,113179,USD,113179,EN,FT,Denmark,L,Denmark,0,"Git, Docker, Hadoop",Bachelor,1,Automotive,2024-06-26,2024-07-25,1016,8.2,DeepTech Ventures +AI04506,Robotics Engineer,249140,AUD,336339,EX,FL,Australia,L,Australia,100,"Scala, Statistics, NLP",PhD,18,Transportation,2024-07-22,2024-08-22,1206,6.1,Algorithmic Solutions +AI04507,Principal Data Scientist,171609,EUR,145868,EX,FT,Netherlands,M,Germany,50,"Spark, SQL, Java, MLOps, Linux",Bachelor,10,Education,2024-04-27,2024-06-17,2287,7.4,Smart Analytics +AI04508,Machine Learning Engineer,105792,EUR,89923,SE,FL,France,S,Portugal,50,"Spark, NLP, Git, Computer Vision",Master,6,Telecommunications,2024-05-31,2024-07-25,2141,5.3,Cognitive Computing +AI04509,Machine Learning Researcher,173700,USD,173700,EX,FT,South Korea,M,Luxembourg,100,"MLOps, Python, Data Visualization, Mathematics, Linux",Bachelor,19,Finance,2024-01-18,2024-03-02,529,6.5,Predictive Systems +AI04510,Data Analyst,97074,EUR,82513,MI,PT,Netherlands,L,Netherlands,100,"Data Visualization, Linux, Python, MLOps, SQL",Associate,4,Automotive,2025-01-16,2025-02-09,1335,8.4,Smart Analytics +AI04511,Machine Learning Researcher,22207,USD,22207,EN,CT,India,M,India,100,"Deep Learning, Git, Mathematics",Master,1,Energy,2024-03-19,2024-05-08,602,9.6,TechCorp Inc +AI04512,Machine Learning Researcher,166711,USD,166711,SE,PT,Ireland,L,Ireland,100,"Spark, PyTorch, NLP, TensorFlow",Bachelor,8,Consulting,2024-12-01,2024-12-17,886,7.1,Advanced Robotics +AI04513,Machine Learning Researcher,91344,EUR,77642,MI,PT,Germany,S,Austria,100,"Spark, Python, Data Visualization",PhD,4,Telecommunications,2024-01-27,2024-03-30,1213,9.8,TechCorp Inc +AI04514,Data Scientist,171048,USD,171048,SE,FT,Denmark,L,Denmark,0,"PyTorch, SQL, Spark, TensorFlow, Data Visualization",PhD,7,Gaming,2024-12-19,2025-01-04,1329,7.1,Algorithmic Solutions +AI04515,AI Software Engineer,129514,USD,129514,EX,PT,Israel,M,Israel,0,"Python, AWS, GCP, R",Bachelor,14,Real Estate,2025-02-14,2025-04-06,2310,6.5,Future Systems +AI04516,AI Research Scientist,70909,USD,70909,MI,FL,Ireland,S,Ireland,100,"AWS, MLOps, PyTorch, TensorFlow",Master,4,Telecommunications,2024-11-09,2024-12-08,926,6.6,AI Innovations +AI04517,Deep Learning Engineer,55311,EUR,47014,EN,FT,France,M,France,0,"Java, MLOps, TensorFlow, Statistics",Master,1,Healthcare,2024-07-29,2024-09-25,1413,5.2,Smart Analytics +AI04518,Deep Learning Engineer,61598,USD,61598,EX,FT,India,M,India,50,"Linux, Deep Learning, NLP",Bachelor,18,Gaming,2024-04-06,2024-06-04,2247,7,Machine Intelligence Group +AI04519,AI Product Manager,129700,USD,129700,MI,CT,Norway,L,South Korea,0,"Tableau, SQL, Docker",Master,2,Consulting,2025-02-13,2025-03-25,1327,8.3,Autonomous Tech +AI04520,AI Specialist,135809,EUR,115438,SE,FT,Netherlands,S,Netherlands,0,"Scala, R, SQL, Data Visualization, Git",Associate,6,Consulting,2025-03-28,2025-04-22,695,7.3,Autonomous Tech +AI04521,Deep Learning Engineer,238500,EUR,202725,EX,FL,Netherlands,S,South Korea,0,"Linux, Computer Vision, Kubernetes",Associate,18,Transportation,2024-04-01,2024-05-27,1845,6,AI Innovations +AI04522,Head of AI,50048,SGD,65062,EN,FT,Singapore,S,Czech Republic,50,"PyTorch, TensorFlow, Docker",Associate,0,Energy,2024-05-14,2024-06-03,680,7.1,Algorithmic Solutions +AI04523,Autonomous Systems Engineer,164914,USD,164914,SE,PT,United States,L,United States,50,"Hadoop, TensorFlow, Linux, MLOps, GCP",Master,8,Consulting,2024-03-04,2024-04-22,917,7.1,Cloud AI Solutions +AI04524,AI Consultant,181134,CAD,226418,EX,CT,Canada,M,Canada,0,"Git, PyTorch, GCP, AWS, Mathematics",Master,19,Healthcare,2024-01-15,2024-02-05,2366,5.9,Machine Intelligence Group +AI04525,AI Specialist,81453,EUR,69235,EN,FL,Netherlands,L,Netherlands,50,"TensorFlow, Java, Deep Learning, Tableau",Associate,1,Education,2025-02-09,2025-03-27,2323,9.2,DataVision Ltd +AI04526,Machine Learning Researcher,52632,USD,52632,EN,FL,Israel,S,Israel,50,"SQL, Spark, Tableau, Scala",PhD,0,Retail,2024-03-15,2024-04-16,585,8.8,Neural Networks Co +AI04527,Data Analyst,77848,USD,77848,EN,FL,Denmark,L,Denmark,50,"SQL, GCP, PyTorch, Java",PhD,0,Government,2025-02-04,2025-03-16,1735,6.9,DataVision Ltd +AI04528,Autonomous Systems Engineer,117315,USD,117315,SE,PT,Sweden,M,Singapore,0,"Computer Vision, Java, MLOps, Kubernetes, Docker",PhD,5,Retail,2024-08-23,2024-10-07,1852,9,DeepTech Ventures +AI04529,AI Architect,166998,USD,166998,SE,CT,Denmark,S,Israel,100,"MLOps, Linux, Data Visualization, Computer Vision",Associate,7,Manufacturing,2025-02-18,2025-04-09,1054,7.3,Neural Networks Co +AI04530,Head of AI,174172,GBP,130629,SE,CT,United Kingdom,L,United Kingdom,50,"TensorFlow, Python, Linux, Hadoop, Statistics",Associate,8,Healthcare,2024-11-09,2024-12-24,574,5.7,Machine Intelligence Group +AI04531,ML Ops Engineer,93049,CAD,116311,MI,CT,Canada,M,Canada,100,"PyTorch, Data Visualization, SQL, Kubernetes",Bachelor,2,Consulting,2025-04-27,2025-05-12,812,7.4,DeepTech Ventures +AI04532,Robotics Engineer,139395,USD,139395,SE,FL,Sweden,L,Sweden,100,"Docker, SQL, Scala, MLOps, Kubernetes",Master,6,Retail,2024-01-08,2024-02-04,1681,6.5,Algorithmic Solutions +AI04533,AI Software Engineer,207936,USD,207936,SE,FT,Norway,L,Norway,100,"Hadoop, Python, AWS, Linux",Bachelor,6,Technology,2024-11-16,2024-12-12,2030,5,Cognitive Computing +AI04534,Machine Learning Engineer,188512,EUR,160235,EX,CT,Austria,M,Austria,50,"Docker, Git, SQL, Spark, Linux",Master,18,Healthcare,2024-04-03,2024-06-09,1323,9.7,Smart Analytics +AI04535,AI Specialist,176564,GBP,132423,EX,FT,United Kingdom,M,Egypt,0,"Azure, Kubernetes, Linux, SQL",PhD,11,Finance,2024-01-11,2024-02-21,631,7.3,Predictive Systems +AI04536,Research Scientist,156332,GBP,117249,SE,CT,United Kingdom,L,Denmark,100,"Kubernetes, Mathematics, Hadoop, MLOps",Bachelor,7,Manufacturing,2025-02-19,2025-04-25,1511,10,Cognitive Computing +AI04537,Data Scientist,113860,USD,113860,MI,FL,United States,M,United States,50,"Tableau, Kubernetes, Java, MLOps",Bachelor,4,Finance,2024-09-16,2024-11-20,1497,9,DeepTech Ventures +AI04538,Data Scientist,95951,USD,95951,MI,FL,Finland,L,Finland,0,"SQL, Mathematics, Kubernetes, Python",Master,2,Media,2024-10-14,2024-12-07,2141,8.2,AI Innovations +AI04539,Data Engineer,177286,CHF,159557,SE,CT,Switzerland,S,Switzerland,50,"Scala, GCP, SQL, MLOps",Associate,7,Manufacturing,2024-04-28,2024-06-22,2473,9.8,Predictive Systems +AI04540,AI Software Engineer,53681,CAD,67101,EN,CT,Canada,M,Canada,50,"Tableau, Azure, Java, Data Visualization",Associate,0,Energy,2024-05-04,2024-05-26,2123,8.3,AI Innovations +AI04541,AI Research Scientist,130939,AUD,176768,SE,FL,Australia,M,Ireland,100,"Data Visualization, GCP, SQL, NLP, Linux",Bachelor,5,Automotive,2024-07-18,2024-09-10,562,6.6,Autonomous Tech +AI04542,Principal Data Scientist,39395,USD,39395,SE,PT,India,M,India,0,"Spark, Data Visualization, Linux, Deep Learning",PhD,7,Transportation,2024-10-05,2024-10-28,1164,8.6,Algorithmic Solutions +AI04543,AI Architect,123582,USD,123582,MI,FL,Norway,M,Norway,0,"Scala, Java, Spark, Mathematics",PhD,3,Manufacturing,2025-03-21,2025-04-10,630,9.6,Predictive Systems +AI04544,AI Research Scientist,136808,EUR,116287,EX,CT,Netherlands,S,Netherlands,0,"Git, TensorFlow, Scala, GCP, Python",PhD,17,Manufacturing,2024-02-20,2024-03-10,2222,8.2,Advanced Robotics +AI04545,Computer Vision Engineer,38736,USD,38736,SE,FT,India,S,India,100,"Python, Java, TensorFlow, Computer Vision, AWS",Bachelor,5,Retail,2025-03-25,2025-04-29,544,9,TechCorp Inc +AI04546,Data Engineer,111692,USD,111692,SE,CT,Ireland,M,Ireland,0,"Python, Scala, Statistics, NLP, Git",Associate,8,Manufacturing,2025-01-27,2025-03-22,2475,5.5,AI Innovations +AI04547,Robotics Engineer,320350,CHF,288315,EX,FT,Switzerland,M,Switzerland,100,"MLOps, PyTorch, Python, Spark",Bachelor,16,Energy,2024-07-25,2024-09-30,2313,6.9,Digital Transformation LLC +AI04548,Data Scientist,148284,EUR,126041,EX,FL,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,14,Consulting,2024-01-26,2024-03-04,1188,5.7,TechCorp Inc +AI04549,AI Research Scientist,164350,USD,164350,EX,FL,Israel,S,Israel,50,"Java, Docker, Azure, Computer Vision, AWS",Master,19,Consulting,2025-04-20,2025-06-23,2272,9.9,Quantum Computing Inc +AI04550,AI Specialist,300752,CHF,270677,EX,FT,Switzerland,L,Switzerland,100,"Mathematics, Hadoop, Data Visualization, R",Associate,14,Retail,2024-08-16,2024-08-30,1923,9.1,Smart Analytics +AI04551,Research Scientist,71687,USD,71687,SE,CT,China,L,Singapore,0,"Docker, AWS, Computer Vision, Java",Associate,7,Education,2024-02-24,2024-04-25,1076,8,Cloud AI Solutions +AI04552,Robotics Engineer,78911,CAD,98639,MI,FL,Canada,S,Canada,100,"Data Visualization, Python, GCP",PhD,4,Government,2024-10-21,2024-11-17,1168,9.7,Machine Intelligence Group +AI04553,Machine Learning Researcher,85224,USD,85224,MI,CT,Israel,L,Israel,50,"NLP, Hadoop, GCP",Bachelor,4,Consulting,2024-12-18,2025-02-27,1115,7,Cloud AI Solutions +AI04554,AI Research Scientist,30653,USD,30653,MI,PT,India,S,India,100,"Java, TensorFlow, R, GCP",Bachelor,2,Media,2025-03-06,2025-04-14,2316,9.7,Neural Networks Co +AI04555,AI Consultant,125667,USD,125667,MI,FT,Sweden,L,Ireland,100,"Java, Computer Vision, MLOps, Tableau",Bachelor,3,Healthcare,2024-08-06,2024-09-08,1356,7.9,Quantum Computing Inc +AI04556,Data Scientist,59008,USD,59008,EN,FT,Finland,M,Argentina,100,"MLOps, Python, Java, AWS, TensorFlow",Bachelor,1,Education,2024-01-03,2024-03-02,816,8.3,Machine Intelligence Group +AI04557,Head of AI,87615,USD,87615,MI,FL,Norway,S,Norway,100,"Linux, Computer Vision, Statistics, Deep Learning",Bachelor,3,Education,2024-03-18,2024-04-27,2060,6.4,Algorithmic Solutions +AI04558,AI Specialist,64656,USD,64656,SE,FL,China,M,China,0,"NLP, SQL, Spark, TensorFlow, MLOps",PhD,7,Government,2024-11-29,2024-12-24,1692,5.7,TechCorp Inc +AI04559,NLP Engineer,236797,JPY,26047670,EX,CT,Japan,S,Turkey,50,"Scala, Java, Python, Kubernetes",Master,17,Automotive,2024-03-20,2024-05-11,1015,8.6,Autonomous Tech +AI04560,AI Research Scientist,69325,EUR,58926,EN,FT,Germany,L,United Kingdom,0,"SQL, MLOps, Spark, Computer Vision",Associate,0,Finance,2024-06-12,2024-08-02,1048,9.9,TechCorp Inc +AI04561,Research Scientist,100014,USD,100014,SE,FL,South Korea,S,South Korea,50,"Scala, Java, Deep Learning, NLP",Associate,7,Finance,2024-02-23,2024-03-14,1690,9.1,AI Innovations +AI04562,ML Ops Engineer,145257,EUR,123468,SE,FT,France,L,France,50,"SQL, MLOps, Python, NLP",Bachelor,5,Transportation,2025-04-21,2025-06-14,1793,7.5,Cloud AI Solutions +AI04563,Robotics Engineer,129098,SGD,167827,SE,CT,Singapore,M,Singapore,100,"AWS, TensorFlow, Python, Tableau, Statistics",Master,9,Real Estate,2024-04-25,2024-05-22,513,6.6,Autonomous Tech +AI04564,AI Research Scientist,58400,USD,58400,EX,FL,India,M,Australia,0,"R, Mathematics, Computer Vision",Master,15,Real Estate,2024-12-04,2025-01-23,1072,6.4,Machine Intelligence Group +AI04565,Data Engineer,146073,USD,146073,EX,CT,Israel,S,Israel,100,"Docker, Kubernetes, GCP",Bachelor,19,Manufacturing,2024-09-01,2024-09-23,2328,5.9,DataVision Ltd +AI04566,ML Ops Engineer,110488,EUR,93915,SE,FL,Germany,M,Germany,100,"MLOps, NLP, SQL",PhD,9,Manufacturing,2025-02-23,2025-05-05,2166,7.7,Cloud AI Solutions +AI04567,Data Analyst,71058,USD,71058,EN,FL,Norway,M,United States,100,"Computer Vision, SQL, NLP",Master,0,Consulting,2024-04-04,2024-06-14,1040,6.3,Cloud AI Solutions +AI04568,Machine Learning Engineer,231110,SGD,300443,EX,FT,Singapore,L,Singapore,100,"Hadoop, Scala, GCP, PyTorch",Associate,17,Energy,2024-12-14,2025-01-17,2122,8.3,TechCorp Inc +AI04569,Data Engineer,138306,EUR,117560,SE,CT,Germany,L,Germany,100,"Java, Kubernetes, AWS",Master,8,Finance,2025-04-27,2025-05-30,1642,9.6,Algorithmic Solutions +AI04570,Principal Data Scientist,187455,CHF,168710,EX,PT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Azure, Deep Learning, Tableau",PhD,12,Energy,2024-04-18,2024-06-05,2092,8.1,Autonomous Tech +AI04571,Autonomous Systems Engineer,94272,CHF,84845,EN,FT,Switzerland,L,Switzerland,100,"Statistics, SQL, Hadoop, Scala, Data Visualization",PhD,1,Government,2024-03-02,2024-04-04,1216,7.8,DeepTech Ventures +AI04572,ML Ops Engineer,136910,EUR,116374,EX,FT,Germany,S,Philippines,100,"Java, AWS, Computer Vision",Bachelor,17,Consulting,2024-10-15,2024-11-27,1487,5.6,Cloud AI Solutions +AI04573,AI Product Manager,155455,CAD,194319,EX,PT,Canada,L,Luxembourg,0,"Java, GCP, Kubernetes, AWS, NLP",Bachelor,16,Transportation,2024-06-01,2024-06-15,625,5.7,Predictive Systems +AI04574,Machine Learning Engineer,218908,JPY,24079880,EX,FT,Japan,S,Japan,100,"Tableau, AWS, MLOps",Associate,14,Finance,2025-01-11,2025-02-25,1370,6.6,Neural Networks Co +AI04575,AI Specialist,58456,EUR,49688,EN,FL,Austria,S,Austria,0,"Scala, Computer Vision, Statistics",Associate,1,Media,2024-12-27,2025-01-16,1460,6.5,Quantum Computing Inc +AI04576,ML Ops Engineer,79370,GBP,59528,EN,CT,United Kingdom,M,Chile,50,"PyTorch, TensorFlow, R",PhD,1,Technology,2025-01-12,2025-03-13,2208,5.9,DeepTech Ventures +AI04577,Head of AI,56598,USD,56598,SE,FT,China,L,China,50,"MLOps, Git, Java, TensorFlow",PhD,8,Retail,2024-02-18,2024-03-28,1009,8.7,DeepTech Ventures +AI04578,Machine Learning Researcher,164862,USD,164862,EX,FL,United States,M,United States,50,"NLP, Linux, Kubernetes, SQL, MLOps",Master,11,Manufacturing,2024-07-28,2024-09-18,1904,6.9,Algorithmic Solutions +AI04579,AI Consultant,78776,USD,78776,MI,PT,South Korea,L,Chile,100,"Data Visualization, MLOps, AWS",Associate,3,Technology,2025-01-11,2025-02-25,2434,7.7,Predictive Systems +AI04580,Principal Data Scientist,107481,GBP,80611,MI,FT,United Kingdom,M,Canada,50,"Linux, R, Python",Master,4,Manufacturing,2024-06-19,2024-08-24,2101,6.1,Cloud AI Solutions +AI04581,AI Specialist,165800,GBP,124350,EX,FL,United Kingdom,M,United Kingdom,50,"Git, Linux, Deep Learning, MLOps, AWS",Associate,11,Energy,2024-09-08,2024-09-26,883,8.3,AI Innovations +AI04582,Data Scientist,114567,EUR,97382,MI,FL,Netherlands,L,Netherlands,100,"Java, Linux, Python, Hadoop, MLOps",Bachelor,4,Technology,2024-10-23,2024-12-23,931,9.8,Digital Transformation LLC +AI04583,Research Scientist,45528,EUR,38699,EN,FL,France,S,France,100,"Python, Azure, Data Visualization, Deep Learning",Bachelor,1,Telecommunications,2024-12-24,2025-02-18,1363,8.7,Neural Networks Co +AI04584,Computer Vision Engineer,156683,GBP,117512,SE,FT,United Kingdom,M,Nigeria,100,"Computer Vision, AWS, Kubernetes, MLOps, Deep Learning",Bachelor,7,Finance,2024-01-22,2024-03-28,1328,8.6,Digital Transformation LLC +AI04585,Machine Learning Engineer,38720,USD,38720,SE,FL,India,S,India,50,"Kubernetes, Linux, Computer Vision, TensorFlow, NLP",PhD,8,Consulting,2024-04-12,2024-04-30,785,8.3,Cognitive Computing +AI04586,ML Ops Engineer,114629,AUD,154749,SE,FL,Australia,M,Australia,0,"R, Azure, SQL",Master,7,Technology,2025-04-19,2025-05-10,1688,5.4,Neural Networks Co +AI04587,Computer Vision Engineer,57392,CAD,71740,EN,FT,Canada,L,Canada,0,"Tableau, SQL, Kubernetes, Hadoop",Associate,1,Gaming,2024-11-30,2025-01-07,1624,6.3,Advanced Robotics +AI04588,Data Scientist,341117,USD,341117,EX,FL,Norway,L,Norway,50,"Linux, Docker, Kubernetes",Bachelor,18,Telecommunications,2024-01-06,2024-01-24,790,8.5,DataVision Ltd +AI04589,ML Ops Engineer,86046,GBP,64535,MI,CT,United Kingdom,S,United Kingdom,0,"Git, R, Spark, Deep Learning, Data Visualization",Bachelor,3,Transportation,2025-01-12,2025-02-21,1892,9.8,Algorithmic Solutions +AI04590,Computer Vision Engineer,149937,USD,149937,EX,PT,South Korea,S,South Korea,50,"Hadoop, Git, SQL",Master,18,Gaming,2024-07-31,2024-10-10,2454,5.1,Machine Intelligence Group +AI04591,Principal Data Scientist,80029,SGD,104038,EN,CT,Singapore,M,Ghana,0,"TensorFlow, MLOps, Data Visualization, Java",Associate,0,Technology,2025-02-26,2025-05-05,2367,9.5,Quantum Computing Inc +AI04592,Machine Learning Engineer,165691,GBP,124268,SE,PT,United Kingdom,L,Ukraine,0,"Scala, Tableau, SQL",Bachelor,9,Healthcare,2024-05-01,2024-06-09,1945,6,Advanced Robotics +AI04593,Autonomous Systems Engineer,141765,EUR,120500,SE,FL,Netherlands,M,Netherlands,0,"Python, PyTorch, Tableau",PhD,7,Telecommunications,2024-06-05,2024-07-31,1988,8.6,Algorithmic Solutions +AI04594,AI Research Scientist,47675,USD,47675,EN,PT,Ireland,S,Ireland,100,"Git, AWS, R, Mathematics, Kubernetes",Master,0,Energy,2024-02-08,2024-03-06,1872,8,Smart Analytics +AI04595,Data Analyst,114484,USD,114484,EX,CT,China,L,China,0,"Spark, PyTorch, Tableau",Bachelor,13,Consulting,2024-12-14,2025-02-08,2154,6.9,Neural Networks Co +AI04596,Machine Learning Engineer,88276,EUR,75035,MI,FT,Austria,S,Norway,100,"TensorFlow, SQL, R, Tableau",Master,4,Healthcare,2024-05-29,2024-06-26,2038,8.3,Cognitive Computing +AI04597,Autonomous Systems Engineer,174969,USD,174969,SE,FT,Sweden,L,Sweden,50,"Java, Azure, R",Associate,8,Telecommunications,2024-11-02,2024-11-18,2445,9.2,Digital Transformation LLC +AI04598,NLP Engineer,193261,USD,193261,EX,FT,South Korea,L,South Korea,50,"Data Visualization, Spark, R, Mathematics, Linux",Associate,10,Education,2024-12-23,2025-03-06,1301,8.7,DataVision Ltd +AI04599,Deep Learning Engineer,58905,USD,58905,EX,CT,India,S,Hungary,100,"SQL, NLP, PyTorch",PhD,12,Automotive,2024-03-26,2024-06-01,1885,5.1,DeepTech Ventures +AI04600,AI Software Engineer,155003,CAD,193754,SE,CT,Canada,L,South Korea,50,"Azure, AWS, Docker",Master,5,Education,2025-04-11,2025-06-16,1609,5.7,Autonomous Tech +AI04601,AI Research Scientist,137955,USD,137955,MI,PT,United States,L,Turkey,50,"TensorFlow, Python, PyTorch, Linux, NLP",PhD,2,Healthcare,2025-04-23,2025-05-24,1334,9.6,AI Innovations +AI04602,NLP Engineer,127644,USD,127644,SE,CT,Finland,M,Finland,100,"MLOps, SQL, Computer Vision",Master,6,Consulting,2024-08-08,2024-10-19,1112,7.2,Future Systems +AI04603,Data Scientist,131769,EUR,112004,SE,FT,France,M,Romania,0,"Python, AWS, MLOps, GCP, SQL",Associate,7,Education,2024-07-11,2024-09-04,1615,9.2,AI Innovations +AI04604,AI Consultant,69280,CAD,86600,MI,FL,Canada,S,Canada,100,"GCP, Azure, Spark",Associate,4,Education,2024-05-26,2024-08-04,2319,8.4,Cloud AI Solutions +AI04605,Computer Vision Engineer,298482,USD,298482,EX,FT,United States,M,United States,0,"Mathematics, Deep Learning, MLOps, PyTorch, AWS",PhD,10,Real Estate,2024-08-11,2024-09-03,2282,9.1,Cognitive Computing +AI04606,Principal Data Scientist,91961,USD,91961,SE,FT,Ireland,S,Ireland,0,"Scala, GCP, Spark, SQL, Mathematics",Master,5,Education,2024-09-08,2024-10-30,781,9,Quantum Computing Inc +AI04607,Research Scientist,108071,EUR,91860,MI,FL,France,L,France,0,"Docker, AWS, GCP, Computer Vision, Azure",Master,4,Education,2024-07-26,2024-09-28,843,8.8,DeepTech Ventures +AI04608,Principal Data Scientist,89067,USD,89067,MI,CT,Denmark,S,India,0,"Python, TensorFlow, AWS, Computer Vision, SQL",PhD,2,Telecommunications,2025-01-06,2025-03-05,1228,8.5,Neural Networks Co +AI04609,Data Engineer,80773,USD,80773,MI,FT,South Korea,S,South Korea,50,"Python, Kubernetes, NLP, Tableau",Master,2,Real Estate,2024-11-01,2024-11-16,1040,5,AI Innovations +AI04610,Machine Learning Researcher,246330,CHF,221697,EX,PT,Switzerland,M,Switzerland,100,"Scala, PyTorch, AWS",Master,17,Government,2025-01-11,2025-03-04,2363,6,Autonomous Tech +AI04611,AI Software Engineer,158632,USD,158632,EX,FL,Sweden,L,Australia,50,"AWS, Kubernetes, TensorFlow, Statistics, SQL",PhD,16,Automotive,2025-03-16,2025-04-19,969,9.8,Quantum Computing Inc +AI04612,Computer Vision Engineer,55191,GBP,41393,EN,FT,United Kingdom,M,United Kingdom,100,"Hadoop, Java, Computer Vision, Spark",Associate,0,Manufacturing,2025-04-03,2025-06-05,2166,6,Autonomous Tech +AI04613,Data Analyst,290447,USD,290447,EX,PT,Norway,L,Norway,100,"R, Mathematics, Scala, PyTorch",Bachelor,17,Energy,2025-03-16,2025-05-13,2278,6.3,Smart Analytics +AI04614,ML Ops Engineer,162470,EUR,138100,EX,PT,Germany,M,Germany,100,"NLP, Docker, GCP",PhD,16,Manufacturing,2024-03-01,2024-05-08,2135,8.3,DeepTech Ventures +AI04615,Data Engineer,237565,USD,237565,EX,CT,Sweden,L,Spain,0,"Spark, Docker, Scala, Computer Vision, Tableau",PhD,13,Energy,2024-09-17,2024-10-29,1692,7.5,Digital Transformation LLC +AI04616,NLP Engineer,74020,USD,74020,MI,FT,Finland,M,Indonesia,100,"SQL, Spark, NLP, Data Visualization, Computer Vision",Master,2,Automotive,2024-03-06,2024-05-13,553,8.5,TechCorp Inc +AI04617,Principal Data Scientist,184394,USD,184394,EX,CT,Sweden,M,Sweden,0,"Spark, Kubernetes, MLOps, NLP, PyTorch",Bachelor,16,Healthcare,2024-04-03,2024-06-08,659,7.3,Autonomous Tech +AI04618,Data Scientist,195735,USD,195735,EX,FT,Norway,M,Norway,0,"Kubernetes, SQL, NLP",Master,14,Real Estate,2024-02-01,2024-03-07,2095,5.8,Cognitive Computing +AI04619,Machine Learning Engineer,321668,USD,321668,EX,FT,Norway,M,Norway,50,"TensorFlow, Git, Python, R",Associate,17,Finance,2024-05-14,2024-06-13,1411,5.6,Quantum Computing Inc +AI04620,Data Analyst,132287,USD,132287,EX,FL,South Korea,L,South Korea,100,"R, Java, NLP",Associate,16,Energy,2025-03-08,2025-04-02,520,7.3,Neural Networks Co +AI04621,AI Architect,70147,CHF,63132,EN,PT,Switzerland,S,China,0,"TensorFlow, NLP, Linux",Master,1,Transportation,2024-05-17,2024-06-18,887,9.1,Autonomous Tech +AI04622,Head of AI,58977,USD,58977,SE,FL,China,L,China,50,"Docker, GCP, Tableau, Computer Vision, Statistics",PhD,7,Consulting,2025-03-15,2025-05-01,1835,6.9,DeepTech Ventures +AI04623,Head of AI,115529,GBP,86647,MI,FT,United Kingdom,M,United Kingdom,50,"Java, Data Visualization, AWS",Master,2,Automotive,2024-05-03,2024-05-30,1604,5.3,Predictive Systems +AI04624,AI Specialist,123402,USD,123402,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Mathematics",Bachelor,5,Gaming,2024-02-15,2024-03-13,697,8.5,DataVision Ltd +AI04625,Robotics Engineer,81236,USD,81236,MI,PT,Sweden,S,Italy,0,"Scala, Deep Learning, Tableau, R, Python",Bachelor,3,Automotive,2024-10-06,2024-11-13,1216,8.6,Predictive Systems +AI04626,Deep Learning Engineer,23762,USD,23762,EN,FT,China,S,China,50,"Computer Vision, Kubernetes, SQL",Associate,1,Automotive,2024-05-10,2024-06-11,1602,8.5,Quantum Computing Inc +AI04627,Head of AI,80966,USD,80966,EN,CT,Norway,M,Norway,0,"Git, Kubernetes, Hadoop",Associate,1,Education,2024-03-20,2024-05-14,2283,6.1,Quantum Computing Inc +AI04628,AI Product Manager,184463,USD,184463,EX,FT,Denmark,M,United Kingdom,0,"Spark, Statistics, Linux, Java, Deep Learning",Master,10,Finance,2024-07-10,2024-08-22,944,9.5,Future Systems +AI04629,Machine Learning Engineer,80922,CHF,72830,EN,FL,Switzerland,S,Switzerland,100,"R, Azure, MLOps, Tableau, AWS",Bachelor,0,Automotive,2024-10-08,2024-11-21,1763,6.1,TechCorp Inc +AI04630,Data Engineer,225786,SGD,293522,EX,FL,Singapore,L,Netherlands,50,"Python, Spark, Deep Learning, Statistics",Bachelor,12,Transportation,2024-11-20,2024-12-20,2261,5.7,Advanced Robotics +AI04631,AI Specialist,174292,USD,174292,EX,FT,Sweden,S,Colombia,50,"Kubernetes, R, Data Visualization",PhD,10,Energy,2024-07-05,2024-08-16,1578,5.5,Future Systems +AI04632,AI Architect,141209,USD,141209,SE,FL,Finland,M,Finland,50,"Java, PyTorch, Tableau",Associate,9,Government,2025-03-15,2025-03-31,1379,5.6,TechCorp Inc +AI04633,AI Architect,33494,USD,33494,EN,FT,China,M,Chile,0,"R, MLOps, SQL, NLP",PhD,1,Gaming,2025-04-18,2025-05-05,2021,8.1,Algorithmic Solutions +AI04634,Head of AI,102081,GBP,76561,MI,FL,United Kingdom,L,Romania,100,"TensorFlow, Git, Spark, Data Visualization",Master,4,Manufacturing,2024-08-05,2024-09-27,1236,5.9,Cloud AI Solutions +AI04635,Computer Vision Engineer,142338,EUR,120987,SE,PT,Netherlands,M,Netherlands,100,"Scala, Kubernetes, Azure, Python",Master,6,Real Estate,2024-04-29,2024-07-02,1165,5.7,Neural Networks Co +AI04636,Robotics Engineer,111416,USD,111416,MI,FL,United States,S,United States,50,"Linux, Java, MLOps, Azure",Bachelor,3,Telecommunications,2024-11-08,2024-12-21,1032,6.8,AI Innovations +AI04637,Data Analyst,171510,USD,171510,EX,CT,Sweden,S,Austria,0,"SQL, Git, PyTorch, TensorFlow, Tableau",Master,14,Gaming,2024-05-10,2024-07-02,845,6.8,Predictive Systems +AI04638,Robotics Engineer,32757,USD,32757,EN,CT,China,S,Philippines,0,"Spark, Linux, PyTorch, Mathematics, Python",PhD,0,Energy,2024-04-27,2024-06-13,1275,9.6,TechCorp Inc +AI04639,Data Analyst,78323,GBP,58742,MI,CT,United Kingdom,S,United States,0,"TensorFlow, GCP, Mathematics, Java, Linux",Bachelor,3,Real Estate,2025-04-17,2025-05-09,942,8.2,DataVision Ltd +AI04640,Robotics Engineer,68649,GBP,51487,EN,FL,United Kingdom,S,Austria,0,"Hadoop, Git, Spark, PyTorch, Linux",PhD,1,Finance,2024-11-02,2024-12-07,1578,9.7,AI Innovations +AI04641,Deep Learning Engineer,82078,AUD,110805,MI,FL,Australia,M,Australia,50,"PyTorch, Java, Scala, Computer Vision, R",Bachelor,2,Energy,2025-03-30,2025-05-07,1484,6.2,Future Systems +AI04642,AI Software Engineer,65931,USD,65931,EN,CT,Denmark,S,Denmark,0,"Kubernetes, PyTorch, Mathematics, Linux, Git",Master,1,Media,2024-06-24,2024-08-13,691,6.8,DataVision Ltd +AI04643,Research Scientist,207846,USD,207846,EX,PT,South Korea,L,South Korea,50,"Linux, MLOps, SQL, Scala",Bachelor,15,Gaming,2024-06-12,2024-07-11,1452,6.7,Autonomous Tech +AI04644,Principal Data Scientist,107642,GBP,80732,MI,PT,United Kingdom,M,United Kingdom,0,"PyTorch, TensorFlow, Python, R, Data Visualization",Bachelor,4,Healthcare,2024-06-30,2024-07-31,2023,5.9,Cloud AI Solutions +AI04645,Head of AI,51450,EUR,43733,EN,PT,Germany,M,Germany,100,"Kubernetes, SQL, Tableau, MLOps, Deep Learning",PhD,0,Finance,2024-08-13,2024-08-31,1211,8.3,DeepTech Ventures +AI04646,Data Scientist,79522,CAD,99403,EN,CT,Canada,L,Germany,100,"Hadoop, Data Visualization, GCP",PhD,0,Gaming,2024-09-24,2024-11-29,802,8.6,Cloud AI Solutions +AI04647,Machine Learning Engineer,100881,USD,100881,MI,FT,Sweden,L,Sweden,100,"R, Azure, Kubernetes, Hadoop",Bachelor,4,Real Estate,2024-03-22,2024-04-21,631,5.3,Advanced Robotics +AI04648,Research Scientist,89648,USD,89648,MI,PT,Ireland,L,Japan,50,"Data Visualization, NLP, Scala, Python",Bachelor,2,Healthcare,2025-03-22,2025-04-18,785,9.6,Neural Networks Co +AI04649,Principal Data Scientist,227077,JPY,24978470,EX,FT,Japan,S,Japan,50,"NLP, PyTorch, GCP, Azure, AWS",Associate,16,Healthcare,2024-06-07,2024-08-15,1178,6.9,Autonomous Tech +AI04650,Data Scientist,141613,EUR,120371,SE,CT,France,L,Mexico,50,"Git, SQL, AWS",Associate,5,Technology,2024-06-13,2024-07-05,1876,9.5,Advanced Robotics +AI04651,AI Specialist,197086,USD,197086,SE,PT,Denmark,L,Denmark,50,"AWS, Linux, PyTorch, Spark",Associate,8,Retail,2024-05-20,2024-06-18,2105,7.5,Smart Analytics +AI04652,Research Scientist,34933,USD,34933,MI,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, Linux, Java",PhD,2,Media,2025-03-20,2025-04-07,683,9.8,AI Innovations +AI04653,AI Consultant,57403,AUD,77494,EN,PT,Australia,M,Australia,0,"Computer Vision, Java, Git, Hadoop",Associate,0,Automotive,2024-09-11,2024-10-22,584,8,TechCorp Inc +AI04654,Robotics Engineer,217171,GBP,162878,EX,FL,United Kingdom,S,United Kingdom,0,"R, Java, Data Visualization, Git, TensorFlow",Master,16,Healthcare,2024-04-24,2024-07-01,836,6.2,AI Innovations +AI04655,Computer Vision Engineer,85086,USD,85086,EX,FL,China,L,China,50,"Tableau, GCP, Python, Azure",Associate,19,Finance,2024-05-03,2024-07-02,1158,9.4,Quantum Computing Inc +AI04656,AI Product Manager,77309,GBP,57982,EN,CT,United Kingdom,L,Netherlands,50,"Python, R, Computer Vision, NLP, Java",Associate,1,Healthcare,2024-07-30,2024-09-21,936,9.9,Advanced Robotics +AI04657,AI Software Engineer,152616,EUR,129724,SE,FT,Netherlands,M,Malaysia,0,"Git, Scala, Deep Learning, Linux, R",Bachelor,5,Education,2024-05-30,2024-07-22,801,9.5,Cloud AI Solutions +AI04658,AI Architect,80354,CAD,100443,MI,FT,Canada,M,Canada,100,"SQL, AWS, MLOps, Linux, Python",Bachelor,3,Government,2025-02-12,2025-03-25,2160,5.3,AI Innovations +AI04659,Principal Data Scientist,130383,USD,130383,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, TensorFlow, Mathematics, Python",PhD,9,Automotive,2024-04-16,2024-06-10,1167,5.6,TechCorp Inc +AI04660,AI Consultant,191150,AUD,258053,EX,PT,Australia,M,India,0,"Kubernetes, Linux, Tableau",Associate,11,Healthcare,2024-12-12,2025-02-09,2246,5,TechCorp Inc +AI04661,AI Specialist,77392,EUR,65783,MI,CT,Germany,S,Germany,50,"TensorFlow, Python, Azure, GCP",Master,4,Telecommunications,2024-05-07,2024-06-23,786,8.2,TechCorp Inc +AI04662,Data Scientist,72963,USD,72963,EN,CT,Israel,L,Israel,50,"Scala, TensorFlow, Deep Learning",Bachelor,0,Energy,2024-09-22,2024-10-31,1307,9.4,Smart Analytics +AI04663,AI Consultant,77791,AUD,105018,EN,FT,Australia,M,Australia,50,"Computer Vision, Git, Azure, Kubernetes, Statistics",Master,0,Real Estate,2024-04-06,2024-04-30,1900,7.2,DataVision Ltd +AI04664,Robotics Engineer,150499,EUR,127924,EX,CT,Austria,L,Russia,100,"Scala, Kubernetes, PyTorch, TensorFlow",Associate,17,Technology,2024-08-04,2024-10-07,1341,9.2,TechCorp Inc +AI04665,Principal Data Scientist,79579,USD,79579,MI,FT,Sweden,M,Sweden,0,"Linux, Python, GCP",PhD,4,Media,2025-01-16,2025-03-01,1594,6.1,DeepTech Ventures +AI04666,AI Software Engineer,251411,EUR,213699,EX,CT,Germany,L,Germany,100,"Python, Kubernetes, TensorFlow, GCP, Scala",Master,11,Retail,2024-02-07,2024-04-13,581,8.3,Autonomous Tech +AI04667,AI Specialist,54870,USD,54870,MI,FT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker, Linux",Master,3,Transportation,2024-05-24,2024-07-18,1639,8.5,Machine Intelligence Group +AI04668,ML Ops Engineer,104878,EUR,89146,SE,FL,France,S,France,0,"PyTorch, Mathematics, Linux, Git, Deep Learning",Master,9,Healthcare,2025-04-15,2025-05-31,597,9.6,Cognitive Computing +AI04669,Data Scientist,76528,USD,76528,MI,FL,South Korea,L,Sweden,50,"TensorFlow, PyTorch, Docker, NLP, Computer Vision",Master,2,Automotive,2024-05-09,2024-06-14,1549,5.7,Cognitive Computing +AI04670,Autonomous Systems Engineer,372494,CHF,335245,EX,FL,Switzerland,L,Switzerland,50,"Kubernetes, Scala, Java, Git, MLOps",Associate,18,Media,2024-01-15,2024-02-24,1253,8.8,Predictive Systems +AI04671,Machine Learning Engineer,135702,USD,135702,SE,PT,Finland,M,Belgium,100,"Scala, Git, Computer Vision",Bachelor,5,Telecommunications,2024-07-23,2024-08-21,563,8.4,Predictive Systems +AI04672,AI Software Engineer,75693,USD,75693,EN,FT,Denmark,S,Denmark,100,"PyTorch, Kubernetes, Azure",Associate,1,Automotive,2025-04-19,2025-06-09,690,9.8,Machine Intelligence Group +AI04673,Data Scientist,104982,USD,104982,EN,FL,Norway,L,Norway,50,"Java, Tableau, Mathematics, Scala",Bachelor,1,Transportation,2025-03-16,2025-04-20,1806,5.6,Advanced Robotics +AI04674,Research Scientist,244711,EUR,208004,EX,FT,Austria,L,Austria,50,"SQL, NLP, MLOps",Master,12,Government,2024-08-29,2024-10-07,2403,8.7,Future Systems +AI04675,Machine Learning Researcher,45500,USD,45500,EN,CT,South Korea,S,South Korea,50,"TensorFlow, Python, AWS",Master,1,Transportation,2024-01-09,2024-02-24,670,6.9,Autonomous Tech +AI04676,Machine Learning Engineer,117161,USD,117161,EX,FL,Israel,S,Russia,100,"R, Hadoop, Python",Bachelor,14,Automotive,2024-08-06,2024-08-26,1132,5.6,TechCorp Inc +AI04677,ML Ops Engineer,69868,CAD,87335,EN,CT,Canada,M,Turkey,100,"TensorFlow, SQL, Azure, AWS",Master,0,Manufacturing,2024-10-06,2024-11-05,1205,7.8,TechCorp Inc +AI04678,Data Engineer,64406,EUR,54745,EN,CT,Austria,M,Austria,50,"Deep Learning, Kubernetes, R",Bachelor,1,Healthcare,2024-09-07,2024-10-23,1125,9.2,Autonomous Tech +AI04679,AI Consultant,237645,EUR,201998,EX,FL,Netherlands,M,Netherlands,100,"Python, TensorFlow, Deep Learning, NLP",Associate,19,Technology,2025-03-22,2025-04-29,1161,5.5,Autonomous Tech +AI04680,AI Product Manager,49582,USD,49582,EN,FL,Finland,S,Finland,100,"GCP, Java, Python",Master,0,Manufacturing,2024-11-10,2024-11-25,1340,7.8,AI Innovations +AI04681,Data Scientist,83059,USD,83059,MI,PT,Ireland,S,Russia,100,"PyTorch, Data Visualization, Scala, GCP, Mathematics",Associate,3,Transportation,2024-01-02,2024-03-08,837,8.6,Cloud AI Solutions +AI04682,AI Specialist,136959,USD,136959,SE,FT,Ireland,L,Ireland,100,"Mathematics, Git, Statistics",Associate,6,Transportation,2024-02-22,2024-04-03,2084,7.6,Predictive Systems +AI04683,Autonomous Systems Engineer,107694,USD,107694,MI,FT,Denmark,S,Italy,0,"SQL, Mathematics, Tableau, Azure, MLOps",PhD,3,Retail,2024-12-24,2025-01-15,1759,8.1,TechCorp Inc +AI04684,AI Architect,179863,SGD,233822,EX,FT,Singapore,S,Singapore,0,"Data Visualization, Python, TensorFlow, Computer Vision",PhD,13,Telecommunications,2024-08-17,2024-10-29,1456,8.9,Future Systems +AI04685,Principal Data Scientist,138581,USD,138581,SE,CT,Sweden,L,Sweden,0,"Java, R, Linux, Git, MLOps",Master,5,Technology,2024-06-18,2024-08-29,602,9.3,Autonomous Tech +AI04686,Robotics Engineer,167250,GBP,125438,SE,FT,United Kingdom,L,Denmark,100,"Linux, Kubernetes, Computer Vision, Deep Learning, Data Visualization",Master,8,Finance,2024-02-26,2024-04-02,1324,6.9,TechCorp Inc +AI04687,ML Ops Engineer,73285,CAD,91606,MI,FL,Canada,S,Canada,0,"Statistics, AWS, SQL, MLOps",Bachelor,4,Telecommunications,2025-02-19,2025-04-19,1577,7.6,Digital Transformation LLC +AI04688,Machine Learning Researcher,90517,USD,90517,MI,PT,Finland,M,Sweden,50,"NLP, AWS, Scala",Master,3,Retail,2024-05-09,2024-07-02,1600,5.8,Future Systems +AI04689,AI Specialist,137917,USD,137917,EX,FT,Ireland,S,Spain,100,"TensorFlow, SQL, Linux, Python",PhD,17,Automotive,2025-01-01,2025-02-04,1945,6,Cloud AI Solutions +AI04690,AI Architect,113385,EUR,96377,MI,FL,Netherlands,M,Netherlands,100,"Data Visualization, SQL, Git",Bachelor,2,Real Estate,2024-08-12,2024-10-10,1861,7.3,Cognitive Computing +AI04691,Research Scientist,91903,USD,91903,MI,FL,South Korea,L,South Korea,0,"GCP, Git, Tableau",Master,4,Manufacturing,2024-10-24,2024-12-09,1403,5.4,Future Systems +AI04692,Autonomous Systems Engineer,62142,USD,62142,EN,FL,Denmark,S,Denmark,100,"SQL, R, Computer Vision, Statistics",Associate,1,Finance,2024-12-25,2025-02-19,897,8.4,Advanced Robotics +AI04693,Head of AI,162597,EUR,138207,EX,CT,Austria,M,Austria,0,"Computer Vision, MLOps, Python",Associate,13,Technology,2024-02-14,2024-04-04,2369,5,Cognitive Computing +AI04694,AI Product Manager,277090,CHF,249381,EX,PT,Switzerland,S,Switzerland,100,"PyTorch, Deep Learning, Azure",Associate,18,Gaming,2024-07-14,2024-08-10,1405,7.3,DeepTech Ventures +AI04695,AI Architect,111361,EUR,94657,SE,PT,Germany,S,Nigeria,100,"Linux, Scala, Statistics, Python, Computer Vision",Bachelor,7,Media,2024-12-28,2025-02-22,566,5.9,Digital Transformation LLC +AI04696,Data Engineer,124750,USD,124750,SE,CT,Sweden,S,Sweden,50,"Hadoop, Python, NLP",Master,9,Government,2024-03-08,2024-04-13,1770,9.3,Smart Analytics +AI04697,AI Architect,59624,USD,59624,MI,FL,South Korea,M,Netherlands,100,"SQL, Data Visualization, Java, Docker, Linux",PhD,3,Transportation,2024-05-13,2024-06-07,776,5.7,Neural Networks Co +AI04698,AI Consultant,176619,USD,176619,SE,FT,Norway,M,Norway,0,"Git, AWS, Kubernetes, Hadoop",PhD,6,Consulting,2024-08-25,2024-10-17,1981,7.1,Predictive Systems +AI04699,Head of AI,60007,USD,60007,EX,CT,China,S,China,0,"Python, Data Visualization, TensorFlow, Java, Mathematics",Master,17,Education,2025-03-16,2025-04-08,1337,8,Cloud AI Solutions +AI04700,Head of AI,76104,EUR,64688,EN,FL,Germany,M,Germany,0,"Spark, NLP, Deep Learning, Hadoop, Kubernetes",Bachelor,0,Government,2024-01-21,2024-02-26,1394,6.7,Algorithmic Solutions +AI04701,NLP Engineer,116281,USD,116281,SE,CT,Ireland,S,Ireland,100,"Data Visualization, Kubernetes, NLP, Python, Deep Learning",PhD,8,Energy,2024-10-26,2024-12-12,1894,7,Advanced Robotics +AI04702,Autonomous Systems Engineer,67934,USD,67934,EN,FL,Ireland,S,Ireland,0,"SQL, Kubernetes, Python",Associate,1,Transportation,2024-08-05,2024-09-09,946,7.4,Digital Transformation LLC +AI04703,Data Analyst,62548,EUR,53166,EN,FL,Netherlands,M,Singapore,100,"Data Visualization, PyTorch, AWS, Python, Hadoop",PhD,1,Government,2024-11-12,2025-01-21,1149,8.5,Cognitive Computing +AI04704,Machine Learning Researcher,32890,USD,32890,EN,CT,China,L,China,100,"Hadoop, Mathematics, Kubernetes",Bachelor,0,Energy,2025-02-15,2025-03-24,802,9,AI Innovations +AI04705,Computer Vision Engineer,82416,USD,82416,MI,PT,Sweden,S,Sweden,0,"Tableau, GCP, Docker, Kubernetes, Statistics",Master,2,Finance,2024-11-05,2025-01-05,1089,6.6,Predictive Systems +AI04706,Machine Learning Engineer,143048,CAD,178810,SE,PT,Canada,M,Nigeria,50,"R, SQL, AWS, GCP, Data Visualization",Associate,8,Manufacturing,2024-09-19,2024-10-29,571,9.8,Quantum Computing Inc +AI04707,Deep Learning Engineer,76432,USD,76432,EX,CT,India,M,India,100,"MLOps, Kubernetes, SQL, R",Bachelor,11,Technology,2024-11-14,2025-01-14,1773,5,Advanced Robotics +AI04708,ML Ops Engineer,91651,EUR,77903,MI,FT,Germany,L,Belgium,50,"Hadoop, Spark, Data Visualization, Statistics",Bachelor,2,Energy,2024-03-13,2024-04-21,2373,5.1,Autonomous Tech +AI04709,Data Engineer,119672,CHF,107705,EN,PT,Switzerland,L,Switzerland,50,"Mathematics, R, NLP",Associate,0,Energy,2025-02-25,2025-04-11,2305,6.2,Quantum Computing Inc +AI04710,AI Consultant,91372,USD,91372,SE,FL,Finland,S,Finland,0,"Python, GCP, Linux, TensorFlow, R",Master,9,Automotive,2024-04-06,2024-05-29,2201,9.8,Smart Analytics +AI04711,AI Specialist,136154,CHF,122539,MI,FT,Switzerland,M,Switzerland,0,"PyTorch, Docker, Kubernetes, SQL",Associate,2,Technology,2024-09-03,2024-11-05,2425,6.2,Autonomous Tech +AI04712,Robotics Engineer,48395,USD,48395,EX,CT,India,S,United Kingdom,50,"Deep Learning, Azure, Spark, Python",Associate,13,Education,2024-11-21,2024-12-20,2192,5.2,Algorithmic Solutions +AI04713,Machine Learning Engineer,105774,USD,105774,EN,FL,United States,L,United States,0,"PyTorch, MLOps, Docker",Associate,1,Automotive,2024-10-31,2025-01-05,2274,7.1,Digital Transformation LLC +AI04714,Data Analyst,160016,USD,160016,SE,FT,Denmark,S,Denmark,50,"Kubernetes, TensorFlow, Docker, Statistics, Computer Vision",Associate,8,Government,2024-01-31,2024-02-17,1543,8.7,Future Systems +AI04715,Autonomous Systems Engineer,206793,CHF,186114,SE,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Kubernetes",Bachelor,9,Retail,2024-09-04,2024-10-09,1451,7.9,Predictive Systems +AI04716,AI Architect,86168,USD,86168,EX,CT,India,L,India,100,"Mathematics, GCP, Data Visualization, Spark, Java",Bachelor,11,Technology,2024-12-08,2025-02-08,2468,7.7,Cloud AI Solutions +AI04717,AI Consultant,123853,USD,123853,SE,PT,Sweden,L,Sweden,100,"Computer Vision, Python, TensorFlow, Spark, Deep Learning",PhD,7,Retail,2024-04-27,2024-06-29,2048,8,Autonomous Tech +AI04718,AI Specialist,78399,SGD,101919,EN,PT,Singapore,L,Singapore,0,"SQL, GCP, MLOps, Deep Learning",Bachelor,0,Real Estate,2025-03-20,2025-05-19,962,9.3,Predictive Systems +AI04719,Machine Learning Engineer,138128,SGD,179566,SE,FL,Singapore,M,Ukraine,50,"Kubernetes, Deep Learning, TensorFlow",Master,6,Automotive,2025-02-15,2025-03-13,1918,8.5,Algorithmic Solutions +AI04720,Data Engineer,90321,CAD,112901,MI,FL,Canada,S,Canada,50,"Python, Linux, GCP, Hadoop",Master,2,Consulting,2024-06-05,2024-06-26,2352,9.8,Machine Intelligence Group +AI04721,NLP Engineer,90443,CAD,113054,MI,FT,Canada,L,Canada,0,"Git, Hadoop, Azure, Tableau, Java",Associate,2,Retail,2025-04-08,2025-06-15,1599,8.2,Smart Analytics +AI04722,ML Ops Engineer,121587,EUR,103349,SE,PT,Austria,M,Austria,50,"Docker, Python, MLOps, Git",Master,8,Government,2025-02-22,2025-04-16,1807,7.7,Autonomous Tech +AI04723,Principal Data Scientist,226775,CHF,204098,SE,PT,Switzerland,L,Switzerland,0,"Scala, Deep Learning, Statistics",Associate,8,Telecommunications,2024-11-30,2025-01-26,819,5.3,Future Systems +AI04724,AI Research Scientist,97958,USD,97958,SE,PT,Ireland,S,Ireland,50,"Kubernetes, Python, Data Visualization, MLOps",PhD,5,Gaming,2024-12-02,2025-02-11,1617,9.8,Predictive Systems +AI04725,Deep Learning Engineer,59895,SGD,77864,EN,CT,Singapore,S,Singapore,50,"Python, TensorFlow, Computer Vision, Azure",PhD,1,Real Estate,2024-08-03,2024-08-23,1154,6.8,Neural Networks Co +AI04726,Deep Learning Engineer,96051,USD,96051,MI,CT,Norway,S,Norway,50,"GCP, Hadoop, Deep Learning, Computer Vision",Bachelor,3,Telecommunications,2024-04-15,2024-05-15,1776,6.5,TechCorp Inc +AI04727,Data Analyst,194676,USD,194676,EX,FT,United States,S,Russia,100,"GCP, SQL, Statistics, Java",PhD,13,Transportation,2025-04-26,2025-06-26,1204,9.7,Machine Intelligence Group +AI04728,Principal Data Scientist,83606,SGD,108688,EN,CT,Singapore,M,Singapore,100,"Python, Kubernetes, Hadoop",Associate,0,Gaming,2025-02-24,2025-03-29,2429,5.2,Machine Intelligence Group +AI04729,AI Product Manager,35409,USD,35409,EN,FT,China,L,China,0,"Spark, Kubernetes, Deep Learning",Master,0,Technology,2024-06-13,2024-07-04,2134,5.4,Future Systems +AI04730,AI Product Manager,75374,USD,75374,MI,FL,Ireland,S,Kenya,50,"R, NLP, AWS, Java",Bachelor,2,Manufacturing,2025-02-09,2025-04-03,701,7.6,Cognitive Computing +AI04731,Principal Data Scientist,79994,USD,79994,EX,FT,China,L,China,0,"Hadoop, Python, NLP",Master,17,Real Estate,2024-05-02,2024-07-07,597,8,Autonomous Tech +AI04732,Deep Learning Engineer,78389,EUR,66631,MI,CT,France,S,France,50,"R, Java, Deep Learning, Statistics, Docker",Master,4,Energy,2025-04-30,2025-06-14,2477,5.9,DeepTech Ventures +AI04733,Head of AI,295681,USD,295681,EX,FT,Denmark,L,Denmark,100,"Tableau, Linux, Git",Master,10,Healthcare,2024-05-26,2024-06-27,524,9.4,Digital Transformation LLC +AI04734,AI Software Engineer,126906,EUR,107870,SE,PT,Germany,L,South Korea,100,"Spark, SQL, Azure",PhD,5,Real Estate,2025-04-29,2025-06-05,1181,9.6,Advanced Robotics +AI04735,AI Architect,158136,EUR,134416,EX,CT,Germany,M,Germany,50,"Kubernetes, Python, Linux, Docker",PhD,19,Manufacturing,2024-11-21,2024-12-17,1866,10,Advanced Robotics +AI04736,Computer Vision Engineer,147980,USD,147980,SE,FL,Norway,S,Norway,50,"Python, NLP, Azure",Master,9,Government,2024-07-06,2024-08-17,1488,6.4,Predictive Systems +AI04737,Head of AI,90573,USD,90573,MI,CT,Norway,S,Norway,0,"SQL, Kubernetes, Tableau",Associate,2,Gaming,2024-06-18,2024-08-07,883,5.2,Cloud AI Solutions +AI04738,Machine Learning Researcher,287295,USD,287295,EX,FL,Norway,L,Switzerland,100,"Azure, Data Visualization, Python, TensorFlow, AWS",PhD,10,Healthcare,2024-07-23,2024-08-08,1834,6,Cognitive Computing +AI04739,Deep Learning Engineer,206996,EUR,175947,EX,PT,Netherlands,L,Netherlands,50,"Mathematics, Data Visualization, Java, Docker",PhD,18,Real Estate,2024-08-09,2024-09-06,865,8.7,DataVision Ltd +AI04740,Autonomous Systems Engineer,122080,SGD,158704,SE,PT,Singapore,M,Romania,100,"Tableau, Mathematics, GCP",Bachelor,5,Transportation,2024-11-12,2024-11-28,1587,9.6,Digital Transformation LLC +AI04741,Computer Vision Engineer,70756,USD,70756,EN,FT,United States,S,United States,50,"NLP, TensorFlow, Azure",Associate,0,Finance,2024-01-04,2024-02-05,1760,7.6,Neural Networks Co +AI04742,AI Architect,97152,CHF,87437,EN,FT,Switzerland,L,Switzerland,0,"Python, Data Visualization, TensorFlow",Bachelor,0,Automotive,2024-07-27,2024-09-02,1520,6.2,Quantum Computing Inc +AI04743,Machine Learning Engineer,166402,EUR,141442,SE,CT,Netherlands,L,Netherlands,100,"Linux, R, Scala, Azure, SQL",Bachelor,6,Media,2024-08-30,2024-10-23,1184,8.5,AI Innovations +AI04744,AI Research Scientist,67835,JPY,7461850,EN,FT,Japan,L,Japan,0,"Spark, Docker, Python",Associate,1,Automotive,2024-12-22,2025-01-08,620,9.2,Digital Transformation LLC +AI04745,Data Scientist,149496,EUR,127072,EX,PT,Austria,M,Austria,100,"Computer Vision, AWS, Python, TensorFlow",PhD,13,Consulting,2024-09-02,2024-10-14,1813,10,Future Systems +AI04746,AI Software Engineer,261114,USD,261114,EX,FT,Finland,L,Finland,100,"Computer Vision, Python, Docker, Deep Learning, Linux",Bachelor,10,Government,2025-01-27,2025-03-29,573,5.6,AI Innovations +AI04747,Machine Learning Researcher,39992,USD,39992,EN,CT,China,L,China,0,"GCP, Computer Vision, Data Visualization, Python",PhD,1,Manufacturing,2025-02-24,2025-05-05,2160,6.3,Predictive Systems +AI04748,NLP Engineer,127090,JPY,13979900,SE,FT,Japan,M,Japan,100,"Tableau, Hadoop, Computer Vision, Azure, Deep Learning",Master,6,Automotive,2024-05-05,2024-05-20,1570,8.1,Cognitive Computing +AI04749,Data Analyst,25060,USD,25060,EN,FT,India,M,India,100,"Hadoop, Spark, SQL, NLP, Docker",PhD,1,Gaming,2024-04-14,2024-06-13,1845,9.4,Neural Networks Co +AI04750,NLP Engineer,121674,JPY,13384140,SE,CT,Japan,M,Indonesia,50,"Python, Tableau, Hadoop",Master,5,Real Estate,2024-02-03,2024-03-22,1668,8.7,Quantum Computing Inc +AI04751,AI Product Manager,60372,JPY,6640920,EN,FT,Japan,M,Japan,100,"GCP, Git, NLP, Python, SQL",Associate,0,Retail,2025-04-15,2025-05-23,1562,8.1,AI Innovations +AI04752,Data Engineer,277451,USD,277451,EX,FT,Norway,S,China,100,"Docker, SQL, PyTorch",Bachelor,11,Retail,2024-03-25,2024-06-03,2111,7.8,Future Systems +AI04753,Research Scientist,112653,JPY,12391830,MI,FL,Japan,L,Japan,100,"Python, SQL, Java, Spark",Bachelor,2,Energy,2024-12-25,2025-02-06,2007,8.1,Future Systems +AI04754,AI Consultant,65378,EUR,55571,EN,PT,Austria,S,Austria,100,"PyTorch, Git, MLOps, TensorFlow",Bachelor,0,Healthcare,2025-03-15,2025-05-12,990,7.1,Future Systems +AI04755,Data Engineer,70603,USD,70603,EN,FL,Ireland,M,Chile,50,"NLP, Deep Learning, Git, Kubernetes",PhD,1,Media,2025-01-03,2025-02-12,1881,7.6,Smart Analytics +AI04756,Head of AI,190525,USD,190525,EX,FT,Denmark,S,Estonia,0,"Python, Deep Learning, MLOps, Azure",Bachelor,15,Gaming,2025-02-21,2025-03-16,2332,7.2,Smart Analytics +AI04757,Research Scientist,61699,EUR,52444,EN,FT,Netherlands,M,Netherlands,50,"R, Tableau, Kubernetes",Bachelor,1,Automotive,2024-09-03,2024-10-30,594,8.8,Machine Intelligence Group +AI04758,AI Research Scientist,273689,GBP,205267,EX,FT,United Kingdom,L,Czech Republic,100,"Azure, Linux, Hadoop, Java, Python",PhD,10,Manufacturing,2025-02-02,2025-04-14,2382,6.3,DeepTech Ventures +AI04759,Machine Learning Researcher,99938,USD,99938,MI,CT,United States,M,United States,0,"Azure, Kubernetes, Deep Learning",PhD,3,Retail,2024-09-13,2024-11-02,2160,6.9,Future Systems +AI04760,Robotics Engineer,109758,USD,109758,MI,FT,Ireland,M,Ireland,0,"SQL, NLP, Tableau, Computer Vision, PyTorch",Bachelor,4,Retail,2024-08-14,2024-10-01,1696,5.1,Advanced Robotics +AI04761,AI Consultant,107303,USD,107303,MI,CT,Israel,L,Singapore,50,"TensorFlow, SQL, NLP, Git",PhD,3,Energy,2025-02-28,2025-04-29,1075,8.2,Algorithmic Solutions +AI04762,Data Analyst,89290,USD,89290,EN,FT,Ireland,L,Ireland,50,"Scala, Kubernetes, Tableau",PhD,0,Finance,2024-02-15,2024-04-01,2246,7,Autonomous Tech +AI04763,Data Scientist,172273,USD,172273,EX,PT,Israel,S,Israel,0,"Java, Tableau, Docker",Associate,10,Government,2025-01-26,2025-03-28,1270,9.4,Machine Intelligence Group +AI04764,AI Product Manager,98723,AUD,133276,MI,FL,Australia,L,Australia,50,"Data Visualization, GCP, Scala, MLOps",Master,4,Real Estate,2024-05-08,2024-05-22,824,5.3,Cloud AI Solutions +AI04765,Autonomous Systems Engineer,64219,USD,64219,EN,FT,Ireland,S,Ireland,0,"Linux, Spark, Tableau",PhD,1,Government,2024-01-12,2024-02-18,885,9.1,Predictive Systems +AI04766,Principal Data Scientist,163057,JPY,17936270,SE,FT,Japan,L,Japan,100,"Spark, SQL, Docker, Linux",Master,7,Government,2025-04-20,2025-05-09,1937,8.5,Quantum Computing Inc +AI04767,Machine Learning Engineer,175853,EUR,149475,EX,CT,Netherlands,L,Philippines,100,"PyTorch, AWS, SQL, Python",Master,16,Automotive,2024-02-11,2024-04-12,505,7.7,Cognitive Computing +AI04768,Computer Vision Engineer,24322,USD,24322,EN,PT,India,S,Canada,0,"Azure, MLOps, Python",Associate,1,Finance,2024-07-12,2024-08-28,631,10,Predictive Systems +AI04769,Autonomous Systems Engineer,296894,GBP,222671,EX,CT,United Kingdom,L,United Kingdom,0,"MLOps, SQL, Python, Tableau, Git",Associate,12,Education,2024-12-12,2025-01-04,1608,7.2,TechCorp Inc +AI04770,Deep Learning Engineer,102705,AUD,138652,MI,PT,Australia,M,Australia,0,"SQL, Azure, R",Bachelor,4,Government,2025-01-18,2025-03-27,2238,6.7,Advanced Robotics +AI04771,AI Software Engineer,80745,SGD,104969,MI,CT,Singapore,S,Singapore,50,"Kubernetes, Python, TensorFlow, Statistics",Associate,4,Technology,2024-01-28,2024-03-23,1996,6,Digital Transformation LLC +AI04772,AI Specialist,135774,USD,135774,EX,FT,Ireland,S,Ireland,50,"Computer Vision, Kubernetes, Git",PhD,14,Government,2024-02-27,2024-03-15,927,6.8,Predictive Systems +AI04773,AI Architect,66185,GBP,49639,EN,CT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow, PyTorch",PhD,0,Manufacturing,2024-04-03,2024-06-11,2185,7.8,Autonomous Tech +AI04774,Computer Vision Engineer,142177,USD,142177,MI,FL,Denmark,M,Denmark,0,"Kubernetes, TensorFlow, Docker",PhD,2,Telecommunications,2024-10-16,2024-12-09,2400,8.8,DeepTech Ventures +AI04775,Head of AI,85696,USD,85696,MI,CT,Israel,S,Denmark,100,"Data Visualization, Docker, PyTorch, MLOps, AWS",Master,3,Healthcare,2024-09-16,2024-10-25,1250,8.2,Predictive Systems +AI04776,Data Analyst,148270,GBP,111203,SE,FL,United Kingdom,M,United Kingdom,100,"TensorFlow, Hadoop, MLOps, Statistics",Associate,6,Media,2024-03-16,2024-04-12,583,9.5,Cognitive Computing +AI04777,NLP Engineer,133788,USD,133788,SE,FL,Denmark,S,Ukraine,100,"Linux, Azure, Docker, Computer Vision",PhD,8,Gaming,2025-04-15,2025-05-24,2156,6,Machine Intelligence Group +AI04778,AI Specialist,162677,GBP,122008,EX,FL,United Kingdom,S,United Kingdom,50,"R, Python, Linux",Master,17,Healthcare,2025-03-23,2025-04-20,2094,7.5,Advanced Robotics +AI04779,Autonomous Systems Engineer,152781,USD,152781,SE,CT,Finland,L,Egypt,0,"SQL, PyTorch, NLP, Computer Vision, Deep Learning",Master,9,Technology,2024-07-31,2024-08-21,1388,7.3,Neural Networks Co +AI04780,Research Scientist,91758,EUR,77994,EN,CT,Germany,L,Germany,0,"Scala, PyTorch, Spark",Bachelor,1,Telecommunications,2024-06-09,2024-07-29,2194,9.1,Autonomous Tech +AI04781,AI Architect,151164,CHF,136048,MI,FL,Switzerland,M,Switzerland,100,"Python, Linux, Computer Vision, Tableau",Associate,2,Finance,2024-09-17,2024-11-04,1670,7.9,DeepTech Ventures +AI04782,AI Product Manager,71129,GBP,53347,EN,CT,United Kingdom,S,Spain,50,"SQL, R, Kubernetes",Associate,1,Education,2025-04-22,2025-06-19,1826,7.3,Autonomous Tech +AI04783,Data Scientist,133851,GBP,100388,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, AWS, Hadoop",Master,8,Gaming,2024-07-27,2024-08-14,1570,9.4,Neural Networks Co +AI04784,Principal Data Scientist,60769,USD,60769,MI,FT,South Korea,S,Spain,0,"Data Visualization, Deep Learning, TensorFlow, SQL, Git",Associate,2,Retail,2024-10-03,2024-12-13,2176,7.5,DataVision Ltd +AI04785,AI Research Scientist,184176,EUR,156550,EX,CT,Netherlands,L,Netherlands,100,"Git, NLP, Tableau, SQL, Linux",Associate,15,Manufacturing,2024-06-04,2024-07-16,1994,5.6,TechCorp Inc +AI04786,NLP Engineer,225359,USD,225359,EX,FL,Israel,M,Indonesia,100,"R, Git, AWS",Associate,18,Healthcare,2024-10-25,2024-11-28,1608,6.1,AI Innovations +AI04787,Autonomous Systems Engineer,257030,USD,257030,EX,PT,United States,S,Romania,50,"Git, Linux, Python",PhD,18,Manufacturing,2025-01-20,2025-03-15,1880,6.3,Algorithmic Solutions +AI04788,Data Scientist,106616,SGD,138601,SE,FT,Singapore,S,Sweden,0,"Python, Mathematics, Java, Computer Vision",Associate,8,Retail,2024-02-22,2024-04-22,1948,6.5,DeepTech Ventures +AI04789,Machine Learning Engineer,28056,USD,28056,EN,CT,China,S,China,0,"NLP, Kubernetes, Java",Bachelor,0,Gaming,2024-03-29,2024-05-13,2016,7.1,DataVision Ltd +AI04790,AI Consultant,149551,EUR,127118,SE,CT,France,L,France,0,"Spark, R, SQL, Hadoop",Associate,9,Gaming,2025-01-09,2025-03-17,1387,8.7,Digital Transformation LLC +AI04791,Machine Learning Engineer,72604,AUD,98015,EN,PT,Australia,S,Australia,50,"Tableau, Mathematics, MLOps, Python, TensorFlow",Associate,1,Technology,2024-06-12,2024-07-08,1177,5.6,AI Innovations +AI04792,Principal Data Scientist,57678,USD,57678,EN,FT,Finland,L,Finland,0,"Spark, Java, Statistics, Linux",Bachelor,1,Consulting,2024-12-09,2025-02-20,1801,6.7,Machine Intelligence Group +AI04793,Robotics Engineer,56249,USD,56249,EN,FL,Israel,S,Israel,50,"Python, Tableau, TensorFlow, Data Visualization, Mathematics",Bachelor,1,Transportation,2024-03-01,2024-04-21,537,7.6,Machine Intelligence Group +AI04794,ML Ops Engineer,100701,USD,100701,EX,FL,China,L,France,0,"SQL, Git, Spark, Linux",Associate,13,Media,2024-12-18,2025-01-04,2279,9.3,DataVision Ltd +AI04795,Machine Learning Engineer,86400,USD,86400,EN,CT,United States,M,Kenya,100,"Scala, Deep Learning, Java",Master,0,Retail,2024-01-29,2024-02-21,1913,7.1,AI Innovations +AI04796,AI Specialist,161695,JPY,17786450,SE,CT,Japan,L,Japan,0,"NLP, Docker, Tableau, R",Bachelor,6,Finance,2024-10-12,2024-11-10,2341,7.2,Cognitive Computing +AI04797,AI Consultant,101102,JPY,11121220,MI,PT,Japan,L,Japan,100,"Linux, Data Visualization, PyTorch, Statistics",Master,3,Telecommunications,2024-03-14,2024-04-01,1091,8.8,DeepTech Ventures +AI04798,AI Architect,72270,USD,72270,EN,FL,Ireland,M,Ireland,0,"Deep Learning, R, PyTorch",Associate,1,Energy,2025-03-26,2025-04-25,913,7.9,TechCorp Inc +AI04799,Machine Learning Engineer,53789,USD,53789,EN,PT,South Korea,M,South Korea,0,"SQL, Spark, Tableau",Bachelor,0,Energy,2024-11-19,2025-01-20,1724,5.2,Future Systems +AI04800,Computer Vision Engineer,104468,USD,104468,MI,FL,South Korea,L,South Korea,100,"Java, SQL, Hadoop",Master,2,Retail,2024-09-08,2024-10-25,1169,7.9,Future Systems +AI04801,ML Ops Engineer,225913,USD,225913,EX,FT,Ireland,S,Ireland,100,"Azure, SQL, TensorFlow, Python",Associate,17,Energy,2025-01-30,2025-02-24,2216,6.7,Neural Networks Co +AI04802,AI Specialist,178459,USD,178459,SE,FL,Norway,L,France,100,"SQL, AWS, Computer Vision, GCP, Data Visualization",Master,8,Gaming,2024-05-21,2024-06-07,879,7.1,Quantum Computing Inc +AI04803,Principal Data Scientist,168120,USD,168120,EX,FT,United States,S,United States,0,"Computer Vision, Docker, AWS, Python",PhD,19,Education,2024-11-12,2024-12-16,996,6.9,Quantum Computing Inc +AI04804,AI Specialist,66095,USD,66095,EN,PT,United States,S,Egypt,100,"GCP, Git, Hadoop, Tableau, PyTorch",PhD,0,Manufacturing,2024-08-31,2024-10-07,2130,7.6,Predictive Systems +AI04805,AI Architect,288067,USD,288067,EX,PT,United States,L,United States,0,"SQL, MLOps, PyTorch, Azure",Associate,18,Telecommunications,2024-04-01,2024-05-22,1686,7.8,Autonomous Tech +AI04806,Deep Learning Engineer,18634,USD,18634,EN,FL,India,S,Ireland,50,"Java, Docker, GCP",Master,1,Transportation,2024-09-13,2024-11-20,1978,9.2,Advanced Robotics +AI04807,Research Scientist,66098,USD,66098,EX,FT,China,M,China,0,"Python, Azure, MLOps, TensorFlow, Docker",Master,18,Manufacturing,2025-01-09,2025-02-26,639,7.5,Machine Intelligence Group +AI04808,Computer Vision Engineer,43744,EUR,37182,EN,FL,Austria,S,Austria,0,"Azure, Linux, PyTorch",Bachelor,1,Government,2024-08-27,2024-11-05,1325,7.1,Future Systems +AI04809,Computer Vision Engineer,57278,EUR,48686,EN,PT,Netherlands,M,Netherlands,50,"Deep Learning, Hadoop, GCP",Bachelor,0,Transportation,2024-03-30,2024-05-29,1116,6.2,Cloud AI Solutions +AI04810,AI Product Manager,59918,GBP,44939,EN,FT,United Kingdom,S,United Kingdom,50,"Python, Spark, Git, Deep Learning",Associate,0,Real Estate,2024-07-10,2024-09-04,1899,5.1,Advanced Robotics +AI04811,Data Scientist,68180,EUR,57953,EN,FT,Austria,M,Austria,0,"Python, Azure, Scala",Master,1,Manufacturing,2025-04-16,2025-06-15,563,9.4,Neural Networks Co +AI04812,AI Software Engineer,97864,GBP,73398,SE,PT,United Kingdom,S,United Kingdom,100,"Linux, Spark, GCP",Associate,6,Finance,2024-09-25,2024-10-25,2473,5.3,Advanced Robotics +AI04813,Research Scientist,113546,USD,113546,MI,FT,Ireland,L,Ireland,100,"Azure, Kubernetes, Statistics",Master,3,Healthcare,2024-04-27,2024-05-22,2269,5.8,AI Innovations +AI04814,Deep Learning Engineer,237348,JPY,26108280,EX,PT,Japan,S,Japan,50,"MLOps, Java, Spark, Azure",Master,10,Manufacturing,2025-03-13,2025-03-30,803,9.1,TechCorp Inc +AI04815,AI Architect,251015,SGD,326320,EX,FL,Singapore,M,Singapore,0,"PyTorch, Statistics, Azure, SQL",Associate,11,Government,2024-02-03,2024-04-15,1783,6,Cognitive Computing +AI04816,Machine Learning Engineer,78579,CAD,98224,MI,CT,Canada,M,Canada,100,"MLOps, Hadoop, Statistics, PyTorch, Mathematics",Bachelor,4,Government,2024-02-09,2024-03-09,1867,5.4,Future Systems +AI04817,Principal Data Scientist,85161,USD,85161,MI,CT,Ireland,M,Ireland,0,"PyTorch, TensorFlow, Statistics",Master,4,Telecommunications,2025-02-24,2025-03-29,1322,8.9,Future Systems +AI04818,Machine Learning Researcher,190172,EUR,161646,EX,FL,Netherlands,M,Netherlands,0,"Java, Computer Vision, Spark, GCP, Kubernetes",Bachelor,19,Technology,2024-05-02,2024-07-13,1469,9,Cognitive Computing +AI04819,AI Specialist,100405,JPY,11044550,MI,PT,Japan,L,Japan,50,"Python, Git, Tableau",PhD,3,Energy,2024-09-02,2024-11-14,1833,7.2,DataVision Ltd +AI04820,AI Research Scientist,42239,USD,42239,MI,FT,China,L,China,100,"Git, PyTorch, Azure",Bachelor,2,Energy,2024-03-19,2024-05-07,1606,6.7,DataVision Ltd +AI04821,Research Scientist,287260,USD,287260,EX,CT,Ireland,L,Malaysia,50,"Docker, PyTorch, Computer Vision",Master,14,Manufacturing,2024-06-26,2024-07-18,1892,7.2,Future Systems +AI04822,Data Analyst,198733,AUD,268290,EX,FL,Australia,M,Australia,100,"PyTorch, Computer Vision, AWS, Scala, Kubernetes",Associate,11,Media,2024-04-01,2024-04-22,1667,6.9,Future Systems +AI04823,Robotics Engineer,258415,EUR,219653,EX,CT,France,L,France,0,"MLOps, Scala, Spark",Master,17,Gaming,2024-01-21,2024-02-10,1407,5.7,Neural Networks Co +AI04824,AI Specialist,82073,USD,82073,MI,PT,Finland,M,Finland,100,"Python, TensorFlow, MLOps",Bachelor,3,Finance,2024-07-20,2024-08-25,1654,7.1,Cognitive Computing +AI04825,Deep Learning Engineer,111443,USD,111443,SE,FT,Israel,S,Japan,100,"GCP, SQL, Kubernetes, AWS",PhD,8,Consulting,2024-07-26,2024-09-14,500,8.3,Autonomous Tech +AI04826,AI Architect,200094,JPY,22010340,EX,CT,Japan,L,Japan,0,"Java, PyTorch, Azure, SQL",Bachelor,14,Education,2025-04-11,2025-05-19,1610,8.3,Cloud AI Solutions +AI04827,AI Product Manager,248923,EUR,211585,EX,PT,Germany,M,Nigeria,100,"Linux, Deep Learning, Mathematics, Docker",Master,19,Government,2024-07-25,2024-08-18,555,8.8,Cognitive Computing +AI04828,Computer Vision Engineer,72550,GBP,54413,EN,PT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Computer Vision, Git",Bachelor,1,Media,2024-12-22,2025-01-18,702,9.9,Machine Intelligence Group +AI04829,Deep Learning Engineer,206051,EUR,175143,EX,FL,Austria,L,Austria,100,"GCP, Hadoop, Deep Learning",Associate,13,Retail,2024-11-09,2024-12-22,1120,8.1,Advanced Robotics +AI04830,AI Software Engineer,141826,USD,141826,SE,CT,Sweden,M,Sweden,100,"Java, Scala, Mathematics",Bachelor,7,Finance,2024-12-18,2025-02-07,1838,7.2,DataVision Ltd +AI04831,ML Ops Engineer,196522,EUR,167044,EX,FT,France,S,France,100,"Python, Docker, Statistics",Master,18,Finance,2025-01-18,2025-02-25,708,7.9,Neural Networks Co +AI04832,Machine Learning Researcher,104082,SGD,135307,MI,PT,Singapore,M,Portugal,0,"AWS, R, Azure, Python, Git",PhD,2,Automotive,2024-11-26,2024-12-30,765,6.5,TechCorp Inc +AI04833,ML Ops Engineer,256314,USD,256314,EX,FL,United States,S,United States,0,"Mathematics, R, Deep Learning",Bachelor,11,Consulting,2024-05-23,2024-07-23,2116,9.7,Predictive Systems +AI04834,Computer Vision Engineer,62614,USD,62614,EX,PT,India,M,India,100,"TensorFlow, Git, Java, Computer Vision, Scala",Associate,15,Manufacturing,2024-05-14,2024-07-21,1318,7.9,Cloud AI Solutions +AI04835,AI Product Manager,104089,JPY,11449790,MI,PT,Japan,S,Japan,100,"Git, Docker, Data Visualization, Kubernetes, Scala",Associate,3,Government,2024-06-24,2024-08-16,1828,6.6,DeepTech Ventures +AI04836,ML Ops Engineer,52607,USD,52607,SE,FL,China,S,Vietnam,0,"Python, Statistics, Deep Learning, Scala",PhD,7,Telecommunications,2024-08-29,2024-09-18,2113,7.1,TechCorp Inc +AI04837,ML Ops Engineer,131333,USD,131333,SE,FT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Computer Vision",Master,6,Energy,2025-01-09,2025-02-25,1082,7.7,Predictive Systems +AI04838,Data Engineer,369918,CHF,332926,EX,CT,Switzerland,L,Switzerland,0,"Scala, Java, Deep Learning",Associate,18,Finance,2025-03-23,2025-06-03,2322,6,Machine Intelligence Group +AI04839,Computer Vision Engineer,288629,USD,288629,EX,PT,Sweden,L,Sweden,50,"PyTorch, MLOps, GCP",Associate,19,Telecommunications,2024-04-02,2024-05-27,1934,5.5,TechCorp Inc +AI04840,AI Consultant,186990,EUR,158942,EX,CT,Germany,S,Germany,100,"SQL, Data Visualization, Linux, Scala",PhD,16,Automotive,2025-04-02,2025-05-12,1952,9.8,DataVision Ltd +AI04841,AI Specialist,122223,USD,122223,SE,FT,Sweden,S,Sweden,100,"Data Visualization, Linux, PyTorch",PhD,7,Transportation,2025-03-26,2025-05-22,2384,6.8,DataVision Ltd +AI04842,Computer Vision Engineer,116177,USD,116177,SE,PT,Ireland,S,Ireland,100,"Git, Mathematics, Computer Vision, Java, Deep Learning",PhD,8,Consulting,2024-05-28,2024-06-22,939,9.8,Quantum Computing Inc +AI04843,Research Scientist,155331,USD,155331,EX,FT,Israel,M,Israel,0,"Statistics, Computer Vision, NLP, SQL, Data Visualization",Bachelor,15,Consulting,2024-04-17,2024-05-19,1147,5.7,Autonomous Tech +AI04844,Computer Vision Engineer,157720,EUR,134062,EX,PT,Austria,L,United States,50,"Python, GCP, Tableau, TensorFlow",Bachelor,11,Real Estate,2024-10-24,2024-12-27,1805,6.7,Predictive Systems +AI04845,AI Consultant,80697,CHF,72627,EN,PT,Switzerland,M,Switzerland,100,"PyTorch, Azure, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-10-08,2024-12-02,2026,6.8,Machine Intelligence Group +AI04846,Data Analyst,95727,EUR,81368,EN,FT,Netherlands,L,Netherlands,50,"PyTorch, Spark, Computer Vision",PhD,0,Government,2024-01-15,2024-03-03,1960,6.1,DeepTech Ventures +AI04847,NLP Engineer,303364,USD,303364,EX,FL,Norway,L,Norway,50,"Java, R, Spark, Docker, Deep Learning",Bachelor,18,Manufacturing,2024-10-10,2024-11-12,930,5.4,Machine Intelligence Group +AI04848,Robotics Engineer,130193,JPY,14321230,SE,FL,Japan,M,Japan,0,"Spark, Python, R, AWS, Statistics",Bachelor,5,Government,2025-04-16,2025-06-03,1110,8.1,DeepTech Ventures +AI04849,Data Scientist,87100,CAD,108875,MI,PT,Canada,S,Canada,0,"R, GCP, Azure, Linux, Kubernetes",Associate,3,Automotive,2024-05-14,2024-06-03,2350,5.4,Quantum Computing Inc +AI04850,Principal Data Scientist,253609,SGD,329692,EX,CT,Singapore,M,Singapore,100,"Tableau, Deep Learning, Hadoop",PhD,13,Telecommunications,2024-01-09,2024-02-12,723,5.2,TechCorp Inc +AI04851,Deep Learning Engineer,111947,CAD,139934,MI,PT,Canada,L,Canada,0,"Spark, NLP, Python, Kubernetes, Mathematics",PhD,2,Transportation,2024-10-08,2024-12-08,1637,7.6,Advanced Robotics +AI04852,ML Ops Engineer,149929,SGD,194908,SE,FL,Singapore,L,Singapore,50,"Deep Learning, AWS, Mathematics, GCP, Python",Master,8,Media,2025-04-11,2025-05-06,2130,5.6,AI Innovations +AI04853,AI Product Manager,101866,SGD,132426,MI,FT,Singapore,L,Singapore,0,"SQL, NLP, R",PhD,3,Gaming,2024-04-24,2024-05-19,1461,8.5,Algorithmic Solutions +AI04854,Research Scientist,77165,AUD,104173,MI,PT,Australia,S,Australia,100,"Tableau, Git, Docker, PyTorch, Linux",Master,4,Media,2024-12-02,2025-01-21,1863,7.6,Machine Intelligence Group +AI04855,Computer Vision Engineer,121396,EUR,103187,SE,FL,Germany,M,Canada,50,"Data Visualization, PyTorch, TensorFlow, Statistics, Java",Master,7,Gaming,2024-07-01,2024-07-26,1567,8.8,Advanced Robotics +AI04856,Machine Learning Researcher,136213,USD,136213,SE,FT,Ireland,L,Ireland,50,"Deep Learning, TensorFlow, R, MLOps, Git",Associate,5,Retail,2024-06-23,2024-08-25,2377,8.5,Future Systems +AI04857,AI Architect,145362,USD,145362,SE,CT,Sweden,L,Sweden,50,"R, PyTorch, GCP",Associate,5,Manufacturing,2025-03-11,2025-04-21,939,5.6,Autonomous Tech +AI04858,Head of AI,53624,CAD,67030,EN,FL,Canada,S,Canada,100,"Spark, R, Computer Vision, Data Visualization",PhD,0,Energy,2024-06-02,2024-07-21,2033,6.9,Algorithmic Solutions +AI04859,NLP Engineer,85771,EUR,72905,MI,FT,Austria,L,Austria,0,"Kubernetes, Python, AWS, GCP, Linux",Associate,4,Retail,2024-01-09,2024-03-09,1532,5.3,Quantum Computing Inc +AI04860,Data Analyst,181719,EUR,154461,EX,FT,Germany,L,Germany,0,"Spark, NLP, Data Visualization, Statistics, R",PhD,16,Education,2024-01-20,2024-04-02,820,9,Smart Analytics +AI04861,AI Research Scientist,69580,EUR,59143,MI,PT,Austria,S,Austria,0,"Java, Docker, GCP, Computer Vision, Git",Master,2,Consulting,2025-03-31,2025-06-05,1398,9.3,AI Innovations +AI04862,Data Engineer,132740,EUR,112829,SE,FL,Austria,L,Austria,50,"Kubernetes, AWS, GCP, SQL",Bachelor,7,Gaming,2025-01-29,2025-04-09,1832,6.4,Quantum Computing Inc +AI04863,Principal Data Scientist,130258,CAD,162823,SE,CT,Canada,M,Canada,50,"Data Visualization, Python, TensorFlow",Master,7,Telecommunications,2025-04-28,2025-07-01,1257,6.4,Autonomous Tech +AI04864,Computer Vision Engineer,116709,USD,116709,SE,PT,Israel,S,Russia,50,"SQL, Python, R, AWS, Tableau",PhD,9,Manufacturing,2024-06-23,2024-08-31,1408,6.5,Predictive Systems +AI04865,Research Scientist,80310,EUR,68264,MI,CT,Netherlands,M,Netherlands,0,"SQL, Docker, AWS",Associate,3,Automotive,2024-07-07,2024-09-04,1673,7.5,TechCorp Inc +AI04866,Robotics Engineer,185837,EUR,157961,EX,FL,Austria,M,Austria,100,"Scala, Kubernetes, NLP",Associate,13,Media,2024-05-23,2024-07-09,2427,9.4,Machine Intelligence Group +AI04867,Data Engineer,73290,EUR,62297,EN,CT,Netherlands,M,Netherlands,0,"Java, Mathematics, R",Master,0,Media,2024-12-31,2025-02-03,2265,8.4,Advanced Robotics +AI04868,AI Research Scientist,115082,GBP,86312,MI,PT,United Kingdom,M,United Kingdom,100,"R, MLOps, Git, Linux",Bachelor,2,Finance,2024-12-17,2025-02-06,2229,5.5,Digital Transformation LLC +AI04869,Machine Learning Researcher,239030,AUD,322691,EX,PT,Australia,L,Australia,50,"SQL, TensorFlow, PyTorch, Computer Vision, Mathematics",Associate,11,Automotive,2025-04-09,2025-05-09,1765,6.8,Cloud AI Solutions +AI04870,AI Software Engineer,78991,EUR,67142,MI,CT,Austria,L,Austria,50,"Kubernetes, Java, SQL, Statistics",Bachelor,4,Telecommunications,2025-04-15,2025-05-24,1694,5.1,Predictive Systems +AI04871,Head of AI,174805,USD,174805,EX,PT,Sweden,S,Sweden,100,"Spark, Azure, Scala, Deep Learning",Master,19,Media,2025-01-06,2025-02-01,2055,6.3,DataVision Ltd +AI04872,Machine Learning Researcher,181104,CHF,162994,SE,CT,Switzerland,S,Switzerland,50,"Python, Docker, NLP, AWS, Computer Vision",PhD,9,Consulting,2024-08-23,2024-10-25,2359,7.1,Future Systems +AI04873,AI Architect,115681,USD,115681,SE,PT,Finland,L,Ghana,0,"GCP, Scala, Python",Master,9,Consulting,2024-02-18,2024-04-11,1305,6.7,DeepTech Ventures +AI04874,Robotics Engineer,43208,USD,43208,EN,PT,China,L,China,100,"Scala, Python, Kubernetes, Hadoop",PhD,1,Education,2024-10-29,2025-01-08,2363,5.3,Advanced Robotics +AI04875,AI Specialist,94668,USD,94668,MI,PT,Sweden,S,Sweden,100,"Spark, SQL, Python",Bachelor,4,Manufacturing,2024-12-25,2025-03-06,2189,5.5,Advanced Robotics +AI04876,Principal Data Scientist,88758,EUR,75444,EN,FL,Germany,L,Germany,0,"AWS, Computer Vision, Spark, Java",Master,1,Technology,2024-06-08,2024-07-04,1959,9,Future Systems +AI04877,Data Scientist,107851,EUR,91673,SE,FT,Austria,S,Austria,0,"Statistics, PyTorch, Mathematics",Associate,9,Consulting,2025-02-13,2025-03-24,952,8.1,Predictive Systems +AI04878,Research Scientist,77521,USD,77521,EN,PT,Denmark,L,Japan,0,"Hadoop, Git, Mathematics, Computer Vision",Bachelor,0,Manufacturing,2024-08-27,2024-10-18,1875,6.6,Predictive Systems +AI04879,NLP Engineer,48915,USD,48915,EN,FL,Finland,M,Finland,50,"Kubernetes, Docker, Statistics, Azure, SQL",PhD,0,Transportation,2025-01-15,2025-03-21,2032,8.8,TechCorp Inc +AI04880,AI Specialist,144329,USD,144329,EX,FL,Ireland,S,Ireland,50,"Azure, SQL, TensorFlow, R, Statistics",Master,12,Media,2024-05-03,2024-06-11,1802,9,Algorithmic Solutions +AI04881,Deep Learning Engineer,74868,AUD,101072,MI,CT,Australia,S,Australia,50,"Python, TensorFlow, Java, PyTorch",PhD,4,Retail,2025-04-04,2025-06-11,1782,5.1,Smart Analytics +AI04882,AI Consultant,173810,AUD,234644,SE,PT,Australia,L,Australia,50,"TensorFlow, SQL, Linux, Git",Bachelor,7,Government,2024-03-27,2024-05-04,703,9.5,Advanced Robotics +AI04883,Computer Vision Engineer,119626,USD,119626,SE,CT,Israel,S,Ukraine,50,"Kubernetes, Statistics, Scala",Master,5,Finance,2025-04-29,2025-07-07,1482,7.8,Algorithmic Solutions +AI04884,Head of AI,55331,USD,55331,EN,CT,Finland,S,Finland,50,"Git, Spark, Python",Associate,0,Technology,2024-12-23,2025-03-01,853,6.3,Digital Transformation LLC +AI04885,Research Scientist,126364,EUR,107409,MI,FL,Germany,L,Germany,0,"Statistics, Python, Computer Vision",Master,2,Finance,2024-06-22,2024-08-08,1656,5.6,DeepTech Ventures +AI04886,Autonomous Systems Engineer,193012,USD,193012,EX,PT,Sweden,M,Sweden,50,"Spark, Docker, MLOps, GCP, Kubernetes",PhD,12,Energy,2024-07-03,2024-08-30,1282,8.1,DataVision Ltd +AI04887,Machine Learning Engineer,50277,USD,50277,SE,CT,China,M,China,50,"GCP, Tableau, SQL, Git",PhD,7,Media,2024-07-23,2024-09-01,1771,9.9,AI Innovations +AI04888,Computer Vision Engineer,52691,USD,52691,EN,CT,Sweden,S,Italy,0,"PyTorch, Computer Vision, Tableau, TensorFlow",Bachelor,0,Education,2024-10-17,2024-11-05,1506,6.4,Machine Intelligence Group +AI04889,Head of AI,88745,EUR,75433,MI,CT,Austria,M,Austria,50,"AWS, Spark, Hadoop, Azure, Scala",Master,3,Energy,2025-03-19,2025-05-26,1029,8.9,Predictive Systems +AI04890,AI Research Scientist,69741,EUR,59280,EN,FL,France,M,France,0,"PyTorch, TensorFlow, Kubernetes, NLP, GCP",Bachelor,1,Technology,2024-05-15,2024-07-18,1172,6.8,Autonomous Tech +AI04891,Research Scientist,103812,SGD,134956,SE,PT,Singapore,S,Singapore,50,"GCP, Kubernetes, Docker, Mathematics",Bachelor,7,Energy,2024-06-25,2024-08-14,1953,9.6,Predictive Systems +AI04892,AI Product Manager,110207,USD,110207,EN,PT,Denmark,L,Denmark,0,"PyTorch, Hadoop, Data Visualization, AWS, SQL",PhD,1,Finance,2025-03-17,2025-04-11,1555,6.1,Autonomous Tech +AI04893,Data Engineer,90086,USD,90086,EN,CT,United States,L,United States,50,"Python, Data Visualization, Mathematics, TensorFlow",Master,1,Manufacturing,2024-01-30,2024-03-10,1449,5.4,Digital Transformation LLC +AI04894,Computer Vision Engineer,69149,USD,69149,MI,FT,Finland,M,Kenya,100,"Spark, Python, TensorFlow, GCP",Master,4,Telecommunications,2024-04-12,2024-06-21,1681,7.5,Predictive Systems +AI04895,Robotics Engineer,62098,USD,62098,EX,FL,India,M,India,0,"Deep Learning, MLOps, TensorFlow",Associate,16,Energy,2025-04-13,2025-04-28,2374,8.2,Autonomous Tech +AI04896,AI Research Scientist,58340,EUR,49589,EN,PT,Germany,S,Germany,50,"SQL, MLOps, Tableau, AWS, Azure",PhD,0,Automotive,2024-03-20,2024-05-01,1877,5,Advanced Robotics +AI04897,Machine Learning Researcher,27753,USD,27753,EN,FL,China,M,Chile,0,"SQL, Data Visualization, Python, Kubernetes",PhD,1,Telecommunications,2024-07-30,2024-10-05,853,8.1,DataVision Ltd +AI04898,Data Engineer,94238,EUR,80102,MI,FL,France,L,France,100,"Mathematics, Linux, Azure, Python, TensorFlow",Bachelor,2,Transportation,2024-07-19,2024-08-13,1185,6.9,Algorithmic Solutions +AI04899,AI Research Scientist,90515,USD,90515,SE,CT,South Korea,M,South Korea,0,"Python, TensorFlow, Data Visualization",PhD,6,Media,2024-03-04,2024-05-14,1338,9.1,Autonomous Tech +AI04900,Research Scientist,252088,USD,252088,EX,FL,Ireland,M,Ireland,100,"Mathematics, NLP, Scala, PyTorch, Docker",Master,12,Government,2024-03-11,2024-04-30,1589,7.5,DataVision Ltd +AI04901,Computer Vision Engineer,123498,AUD,166722,EX,FT,Australia,S,Australia,50,"Linux, PyTorch, TensorFlow, Data Visualization, SQL",PhD,19,Media,2025-01-02,2025-01-20,2319,7.5,Smart Analytics +AI04902,Machine Learning Engineer,97399,GBP,73049,SE,PT,United Kingdom,S,United Kingdom,0,"Kubernetes, SQL, R",Bachelor,8,Manufacturing,2024-12-24,2025-01-30,1269,7.4,Cognitive Computing +AI04903,AI Product Manager,122301,SGD,158991,MI,FL,Singapore,L,Singapore,100,"Scala, Python, TensorFlow, AWS",PhD,4,Education,2024-04-04,2024-05-22,2205,7.2,Future Systems +AI04904,Computer Vision Engineer,102239,SGD,132911,MI,PT,Singapore,S,Belgium,50,"Mathematics, Docker, AWS",Associate,4,Manufacturing,2024-07-20,2024-09-28,1780,9,AI Innovations +AI04905,Computer Vision Engineer,194401,JPY,21384110,EX,FL,Japan,S,Nigeria,0,"Java, Python, GCP, AWS",PhD,19,Real Estate,2024-10-12,2024-11-20,2140,5.9,AI Innovations +AI04906,Machine Learning Researcher,88107,USD,88107,EN,PT,Denmark,L,France,50,"Hadoop, Scala, Spark",PhD,0,Technology,2024-07-27,2024-09-15,889,6.7,Autonomous Tech +AI04907,AI Software Engineer,147607,USD,147607,SE,FL,Finland,L,Finland,0,"Python, NLP, GCP, Computer Vision",PhD,7,Automotive,2024-05-24,2024-06-26,2274,8.1,Advanced Robotics +AI04908,AI Product Manager,62399,USD,62399,EN,FT,South Korea,L,South Korea,100,"Python, Data Visualization, R",Master,1,Technology,2025-03-08,2025-05-04,1926,9.4,Machine Intelligence Group +AI04909,AI Consultant,178097,CHF,160287,EX,FL,Switzerland,S,Latvia,50,"Git, PyTorch, Hadoop",PhD,16,Education,2024-03-02,2024-03-22,1043,6.6,Digital Transformation LLC +AI04910,Autonomous Systems Engineer,121196,EUR,103017,SE,FL,Netherlands,S,Netherlands,100,"Docker, Linux, Computer Vision",Master,9,Automotive,2025-03-02,2025-04-27,639,6.4,Quantum Computing Inc +AI04911,ML Ops Engineer,196124,USD,196124,EX,CT,Ireland,L,Ireland,0,"PyTorch, R, AWS",Bachelor,11,Retail,2024-11-14,2024-12-18,1350,5.4,TechCorp Inc +AI04912,Deep Learning Engineer,133436,EUR,113421,EX,FL,Germany,S,United States,100,"Computer Vision, Python, Linux",Bachelor,12,Finance,2024-04-23,2024-06-06,708,5.6,Quantum Computing Inc +AI04913,Research Scientist,63143,JPY,6945730,EN,CT,Japan,S,Japan,0,"Git, Hadoop, Data Visualization, GCP",Bachelor,0,Consulting,2024-01-23,2024-02-09,844,9.7,Future Systems +AI04914,Data Engineer,101308,USD,101308,SE,CT,Finland,M,Finland,100,"SQL, NLP, Statistics, Hadoop",Master,9,Transportation,2024-01-28,2024-03-09,1781,9.5,TechCorp Inc +AI04915,Head of AI,129700,USD,129700,EX,PT,Israel,M,Israel,100,"Mathematics, PyTorch, Computer Vision, Azure, NLP",Bachelor,10,Education,2024-12-07,2025-02-11,819,7.3,Future Systems +AI04916,Data Scientist,82759,GBP,62069,MI,FT,United Kingdom,M,Italy,100,"Azure, Kubernetes, Docker",Associate,3,Technology,2024-09-08,2024-10-17,2024,9,AI Innovations +AI04917,Principal Data Scientist,58384,USD,58384,EN,CT,Sweden,S,Sweden,0,"R, MLOps, Hadoop, Computer Vision",PhD,0,Manufacturing,2024-11-21,2025-01-20,1210,9.6,Predictive Systems +AI04918,NLP Engineer,57840,USD,57840,SE,PT,China,M,China,50,"Kubernetes, PyTorch, Statistics, Docker, Azure",Master,7,Telecommunications,2024-08-17,2024-10-13,1991,5,Machine Intelligence Group +AI04919,AI Architect,67529,USD,67529,EN,FL,Ireland,M,Ireland,0,"Linux, GCP, Mathematics, Deep Learning",PhD,0,Energy,2024-09-27,2024-11-19,1391,5.9,Advanced Robotics +AI04920,Autonomous Systems Engineer,103319,EUR,87821,MI,CT,Netherlands,M,Spain,50,"Kubernetes, Tableau, Java, Computer Vision",Associate,2,Gaming,2024-05-04,2024-06-07,744,6.7,Machine Intelligence Group +AI04921,Data Analyst,264281,USD,264281,EX,FL,Israel,L,Israel,100,"Hadoop, Docker, PyTorch, Spark, Tableau",Associate,16,Healthcare,2024-02-19,2024-03-24,2369,8.6,Quantum Computing Inc +AI04922,Robotics Engineer,90375,USD,90375,EN,FT,Norway,S,Hungary,100,"Statistics, TensorFlow, R, MLOps",PhD,1,Energy,2025-03-11,2025-05-09,2386,9.1,Algorithmic Solutions +AI04923,Machine Learning Researcher,168030,CAD,210038,EX,FT,Canada,L,Canada,100,"GCP, Spark, Deep Learning, TensorFlow, Hadoop",PhD,18,Education,2024-08-02,2024-08-17,1548,9.9,Cognitive Computing +AI04924,AI Architect,144693,USD,144693,SE,CT,United States,S,United States,100,"AWS, Azure, PyTorch",PhD,7,Transportation,2025-01-19,2025-02-28,1380,8.6,Algorithmic Solutions +AI04925,NLP Engineer,169169,EUR,143794,EX,FT,Netherlands,S,Netherlands,100,"Scala, AWS, R",Bachelor,17,Government,2024-10-29,2024-12-16,1867,7.8,Cognitive Computing +AI04926,AI Research Scientist,97205,EUR,82624,MI,PT,Austria,L,Austria,100,"MLOps, Hadoop, Java",Bachelor,2,Automotive,2024-12-04,2025-01-05,1638,8.1,DeepTech Ventures +AI04927,AI Consultant,116462,USD,116462,SE,FL,United States,S,United States,100,"Hadoop, Docker, NLP, Kubernetes, Computer Vision",Master,5,Manufacturing,2024-12-17,2025-02-18,936,9.5,Advanced Robotics +AI04928,AI Research Scientist,161251,USD,161251,EX,CT,United States,S,United States,0,"Tableau, Statistics, TensorFlow, Data Visualization, AWS",Associate,13,Transportation,2024-11-04,2025-01-12,2473,10,Cognitive Computing +AI04929,AI Software Engineer,127524,USD,127524,SE,FL,Sweden,M,Sweden,50,"Deep Learning, SQL, MLOps",Bachelor,8,Gaming,2024-11-25,2025-01-10,845,5.6,TechCorp Inc +AI04930,Autonomous Systems Engineer,40391,USD,40391,MI,CT,India,L,Czech Republic,100,"AWS, PyTorch, Linux, Mathematics, Data Visualization",Master,4,Energy,2024-02-05,2024-04-02,1473,9.8,Neural Networks Co +AI04931,Data Engineer,125657,USD,125657,SE,FT,Finland,S,Hungary,50,"Python, Azure, SQL",PhD,9,Automotive,2024-03-11,2024-03-30,1378,9,Neural Networks Co +AI04932,Computer Vision Engineer,220521,GBP,165391,EX,FL,United Kingdom,S,Poland,100,"AWS, Python, TensorFlow, Statistics",PhD,15,Finance,2024-03-01,2024-04-05,1224,7.4,Autonomous Tech +AI04933,AI Software Engineer,75300,GBP,56475,EN,FL,United Kingdom,S,United Kingdom,50,"GCP, R, Mathematics, Hadoop",Bachelor,0,Real Estate,2025-02-13,2025-04-27,1543,7.5,Machine Intelligence Group +AI04934,Data Analyst,89549,USD,89549,MI,PT,Ireland,L,Vietnam,100,"PyTorch, TensorFlow, Mathematics, Docker",Master,3,Consulting,2025-02-01,2025-04-03,1192,6.1,Cognitive Computing +AI04935,AI Research Scientist,230750,GBP,173063,EX,FL,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Git",Master,18,Retail,2024-07-26,2024-08-25,828,5.6,TechCorp Inc +AI04936,Computer Vision Engineer,43742,USD,43742,MI,CT,China,M,China,100,"Kubernetes, GCP, Scala",PhD,4,Finance,2024-02-28,2024-04-03,568,8.1,Advanced Robotics +AI04937,Machine Learning Engineer,73505,USD,73505,EN,FT,Ireland,L,Israel,100,"Kubernetes, GCP, SQL, Azure",Master,1,Energy,2025-02-15,2025-04-19,1617,8.5,AI Innovations +AI04938,ML Ops Engineer,93032,USD,93032,MI,CT,Israel,S,Ireland,100,"SQL, R, Tableau",Bachelor,2,Real Estate,2024-09-23,2024-11-05,697,8.4,Smart Analytics +AI04939,Machine Learning Researcher,310945,CHF,279851,EX,FL,Switzerland,S,Poland,0,"Kubernetes, Scala, Azure",Bachelor,18,Retail,2024-09-03,2024-10-20,1636,7.5,Smart Analytics +AI04940,Principal Data Scientist,91705,USD,91705,MI,FL,Israel,S,Israel,0,"Computer Vision, Kubernetes, GCP, R",PhD,2,Gaming,2024-05-31,2024-08-09,1029,9.7,Cloud AI Solutions +AI04941,AI Consultant,84567,USD,84567,EN,FL,Norway,L,Norway,50,"R, SQL, Azure, Deep Learning, Linux",Associate,0,Education,2024-04-16,2024-06-03,1320,9.6,Digital Transformation LLC +AI04942,AI Architect,77592,EUR,65953,EN,FT,Austria,L,Vietnam,100,"Docker, Hadoop, Tableau",Master,1,Automotive,2024-07-22,2024-09-16,1129,8.7,DeepTech Ventures +AI04943,Head of AI,106660,USD,106660,SE,FL,Sweden,M,Chile,100,"MLOps, Statistics, AWS, NLP, Computer Vision",Associate,9,Retail,2024-06-15,2024-07-05,1054,9.8,AI Innovations +AI04944,Data Engineer,46462,USD,46462,MI,PT,China,L,China,100,"Kubernetes, Git, Statistics",Bachelor,3,Consulting,2024-12-02,2025-01-04,2365,6.6,Neural Networks Co +AI04945,Autonomous Systems Engineer,131368,GBP,98526,SE,PT,United Kingdom,M,Luxembourg,50,"Git, Azure, GCP, Python, AWS",Bachelor,9,Manufacturing,2024-08-10,2024-10-13,503,5,Cognitive Computing +AI04946,Data Scientist,78787,USD,78787,MI,PT,South Korea,S,South Korea,50,"Kubernetes, PyTorch, MLOps, SQL",Master,3,Retail,2024-11-25,2025-01-12,1588,6.4,Cloud AI Solutions +AI04947,ML Ops Engineer,57111,USD,57111,EN,PT,Sweden,M,Sweden,100,"Java, Azure, PyTorch, Scala",Master,1,Automotive,2025-02-24,2025-04-26,931,9,Quantum Computing Inc +AI04948,Deep Learning Engineer,70529,USD,70529,EN,FL,United States,L,United States,100,"Computer Vision, R, SQL",Master,0,Retail,2024-09-17,2024-11-05,1367,8.8,Cognitive Computing +AI04949,Principal Data Scientist,166422,USD,166422,SE,FT,Ireland,L,United States,100,"Spark, Tableau, R, SQL",PhD,6,Transportation,2024-07-20,2024-09-25,1832,5.5,Future Systems +AI04950,Deep Learning Engineer,132627,JPY,14588970,SE,CT,Japan,S,Japan,100,"R, Kubernetes, Python",Bachelor,9,Finance,2025-03-22,2025-05-06,2345,9.9,Advanced Robotics +AI04951,AI Product Manager,79266,USD,79266,EN,PT,Ireland,M,Ireland,0,"Statistics, Kubernetes, Computer Vision, Python, Git",PhD,0,Automotive,2025-04-29,2025-05-15,1442,6.4,AI Innovations +AI04952,Data Analyst,159779,EUR,135812,EX,CT,Germany,L,Portugal,50,"Azure, Python, Docker, Hadoop, Linux",PhD,12,Government,2024-10-14,2024-11-18,975,7.5,Digital Transformation LLC +AI04953,Principal Data Scientist,139290,USD,139290,SE,CT,United States,S,United States,0,"Tableau, SQL, Scala, Computer Vision, Java",Master,8,Education,2024-10-16,2024-11-17,1978,7.6,AI Innovations +AI04954,Robotics Engineer,231125,CHF,208013,EX,CT,Switzerland,S,Romania,100,"SQL, NLP, Tableau",Master,16,Healthcare,2024-05-05,2024-05-26,1244,9.1,Predictive Systems +AI04955,AI Architect,122595,GBP,91946,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Kubernetes, Scala, Deep Learning",Master,3,Energy,2024-09-02,2024-11-04,2102,8,Algorithmic Solutions +AI04956,Data Analyst,68427,USD,68427,EN,CT,Ireland,S,Ireland,0,"AWS, Linux, SQL",Bachelor,1,Retail,2024-07-20,2024-09-11,1893,6.4,Cognitive Computing +AI04957,Head of AI,202722,USD,202722,EX,FL,Finland,L,Finland,100,"AWS, Git, Python, Deep Learning, Spark",Bachelor,16,Healthcare,2024-06-27,2024-08-21,1923,6.2,Neural Networks Co +AI04958,Data Scientist,108147,EUR,91925,SE,FT,Austria,M,Latvia,50,"Data Visualization, PyTorch, MLOps",PhD,7,Finance,2024-09-26,2024-11-15,626,8.1,Machine Intelligence Group +AI04959,ML Ops Engineer,115437,AUD,155840,SE,FT,Australia,S,Australia,100,"TensorFlow, Hadoop, Mathematics, SQL",Master,6,Automotive,2024-12-13,2025-02-08,1204,9.8,Predictive Systems +AI04960,Head of AI,77217,GBP,57913,MI,PT,United Kingdom,S,United Kingdom,50,"Hadoop, Java, SQL, AWS",Bachelor,4,Finance,2024-10-16,2024-11-02,1484,9.7,DeepTech Ventures +AI04961,AI Software Engineer,57529,USD,57529,EN,CT,Israel,L,Kenya,100,"MLOps, TensorFlow, Kubernetes, Data Visualization",PhD,1,Manufacturing,2024-03-15,2024-03-29,928,8.4,Smart Analytics +AI04962,Principal Data Scientist,113427,EUR,96413,MI,PT,France,L,France,100,"SQL, Data Visualization, TensorFlow, Scala, R",Bachelor,4,Transportation,2024-01-13,2024-03-10,794,6.3,TechCorp Inc +AI04963,Autonomous Systems Engineer,71693,USD,71693,EN,PT,Denmark,M,Denmark,50,"Python, Deep Learning, Mathematics, PyTorch, AWS",PhD,0,Gaming,2024-06-08,2024-07-27,2047,7.3,Digital Transformation LLC +AI04964,ML Ops Engineer,151134,EUR,128464,SE,CT,Germany,M,Germany,0,"PyTorch, Git, TensorFlow",PhD,9,Healthcare,2024-12-05,2025-01-31,1045,9.7,DataVision Ltd +AI04965,AI Product Manager,135496,EUR,115172,EX,CT,France,M,France,0,"GCP, Data Visualization, Scala, Git",PhD,18,Consulting,2024-01-23,2024-02-15,938,7.3,Future Systems +AI04966,NLP Engineer,93530,USD,93530,EX,CT,India,L,India,100,"R, Tableau, Data Visualization, Python, PyTorch",Associate,10,Finance,2024-07-13,2024-08-22,1866,8.2,TechCorp Inc +AI04967,AI Research Scientist,194766,JPY,21424260,EX,PT,Japan,L,Japan,50,"Kubernetes, Spark, PyTorch, TensorFlow",PhD,17,Government,2024-02-20,2024-04-03,1832,7,Smart Analytics +AI04968,Data Engineer,214036,JPY,23543960,EX,PT,Japan,M,Netherlands,0,"Deep Learning, SQL, Spark",Associate,15,Healthcare,2025-02-27,2025-04-29,2309,5.8,Neural Networks Co +AI04969,AI Consultant,33244,USD,33244,EN,CT,China,M,China,50,"Deep Learning, Scala, Tableau, Computer Vision",Associate,0,Gaming,2024-08-03,2024-09-29,1665,7.8,Algorithmic Solutions +AI04970,AI Specialist,133388,USD,133388,SE,FL,Denmark,M,Denmark,100,"Computer Vision, Hadoop, Tableau, TensorFlow, Python",Bachelor,6,Telecommunications,2024-02-10,2024-03-09,623,8.1,Algorithmic Solutions +AI04971,Research Scientist,44185,USD,44185,EN,FT,Israel,S,New Zealand,0,"AWS, Scala, Mathematics, TensorFlow, Hadoop",Master,1,Technology,2024-10-07,2024-12-01,781,5.7,Future Systems +AI04972,AI Architect,89882,EUR,76400,SE,CT,Austria,S,Malaysia,50,"AWS, Azure, GCP, Statistics",Master,8,Healthcare,2024-05-14,2024-07-11,1075,8,Smart Analytics +AI04973,Data Engineer,167159,GBP,125369,EX,PT,United Kingdom,L,United Kingdom,100,"Computer Vision, Git, AWS",Associate,10,Telecommunications,2024-12-05,2025-01-08,1609,7.3,Advanced Robotics +AI04974,Autonomous Systems Engineer,110919,USD,110919,SE,FT,South Korea,M,Australia,50,"Scala, Mathematics, Deep Learning, Computer Vision",Associate,9,Technology,2024-08-09,2024-09-17,1747,6.7,Future Systems +AI04975,AI Consultant,153715,USD,153715,SE,FT,Israel,L,Turkey,0,"MLOps, Linux, Kubernetes",Associate,7,Energy,2024-12-09,2025-01-07,2330,6.8,Quantum Computing Inc +AI04976,AI Consultant,132249,USD,132249,SE,CT,Sweden,M,Ireland,50,"Kubernetes, Git, Spark",Associate,6,Retail,2024-06-21,2024-08-01,690,5.4,Smart Analytics +AI04977,NLP Engineer,231132,USD,231132,EX,FT,Denmark,S,Denmark,0,"Python, Git, Docker, Hadoop, Statistics",Bachelor,14,Media,2024-10-18,2024-12-24,1890,6.3,Neural Networks Co +AI04978,AI Consultant,85300,EUR,72505,EN,CT,France,L,France,50,"Java, Data Visualization, PyTorch, AWS",Associate,0,Energy,2024-04-24,2024-05-21,1221,6.4,Machine Intelligence Group +AI04979,AI Product Manager,128111,USD,128111,EX,CT,Sweden,S,Mexico,100,"Java, R, Computer Vision, Statistics, Kubernetes",Associate,15,Education,2025-03-22,2025-05-06,1631,7.6,Future Systems +AI04980,AI Architect,61852,SGD,80408,EN,FT,Singapore,S,Canada,50,"MLOps, SQL, Git, PyTorch",Bachelor,1,Energy,2024-09-11,2024-09-27,2061,5.6,DataVision Ltd +AI04981,Data Scientist,59300,USD,59300,EN,FL,Israel,S,Sweden,0,"PyTorch, Spark, Tableau, MLOps, SQL",Associate,0,Energy,2024-01-08,2024-03-18,1348,9.3,Machine Intelligence Group +AI04982,Machine Learning Researcher,126739,SGD,164761,SE,PT,Singapore,S,Singapore,50,"Git, TensorFlow, SQL",Associate,5,Media,2024-11-29,2025-01-31,554,8.3,Machine Intelligence Group +AI04983,Computer Vision Engineer,80800,USD,80800,EN,CT,Denmark,M,Denmark,50,"Python, Kubernetes, NLP, Statistics",Associate,0,Gaming,2024-03-25,2024-04-28,594,6,Quantum Computing Inc +AI04984,NLP Engineer,85451,AUD,115359,MI,FT,Australia,S,Luxembourg,50,"Kubernetes, Linux, Python",Bachelor,3,Government,2024-06-02,2024-08-05,2249,7.8,DeepTech Ventures +AI04985,AI Product Manager,82153,USD,82153,EN,CT,United States,M,Estonia,50,"Hadoop, TensorFlow, AWS",Associate,0,Telecommunications,2024-03-14,2024-05-17,927,6,DataVision Ltd +AI04986,Machine Learning Researcher,79663,USD,79663,MI,FL,Ireland,S,Ireland,100,"Java, R, MLOps, SQL, Statistics",Associate,2,Energy,2024-08-06,2024-08-21,1985,7.7,Future Systems +AI04987,Robotics Engineer,141209,EUR,120028,SE,PT,Austria,L,Austria,0,"Hadoop, Linux, PyTorch, Java, Mathematics",Master,8,Energy,2025-04-24,2025-05-10,2143,7.8,TechCorp Inc +AI04988,Machine Learning Researcher,47558,USD,47558,EX,FT,India,S,India,0,"NLP, Tableau, Spark, TensorFlow, Statistics",Bachelor,12,Healthcare,2024-02-03,2024-04-05,1793,9,Predictive Systems +AI04989,Machine Learning Researcher,134887,USD,134887,MI,FT,Denmark,L,Denmark,100,"Data Visualization, Scala, Java, R, Computer Vision",PhD,2,Government,2025-03-13,2025-04-23,2069,9.1,Machine Intelligence Group +AI04990,AI Research Scientist,216990,USD,216990,EX,PT,Finland,M,Finland,50,"Hadoop, SQL, Computer Vision, Scala",Master,19,Technology,2024-04-13,2024-05-19,2371,5.6,TechCorp Inc +AI04991,Machine Learning Engineer,270223,EUR,229690,EX,CT,France,L,France,50,"Linux, Python, Deep Learning, Hadoop",Associate,15,Consulting,2024-02-25,2024-05-08,820,8.2,Digital Transformation LLC +AI04992,AI Product Manager,123617,USD,123617,SE,PT,Sweden,S,Indonesia,50,"Python, Hadoop, TensorFlow, PyTorch",Bachelor,8,Technology,2024-11-14,2024-12-13,1367,9,Advanced Robotics +AI04993,Deep Learning Engineer,179200,CHF,161280,SE,CT,Switzerland,M,Switzerland,50,"Python, Linux, Git, R, TensorFlow",Master,6,Media,2024-10-31,2025-01-02,654,9.1,Quantum Computing Inc +AI04994,Robotics Engineer,123515,USD,123515,SE,FL,Finland,M,Finland,0,"Spark, Kubernetes, Scala, Mathematics, Linux",Master,5,Retail,2025-03-29,2025-05-08,736,9.6,Cloud AI Solutions +AI04995,AI Research Scientist,101862,AUD,137514,MI,PT,Australia,L,Ukraine,100,"Git, Python, Computer Vision, TensorFlow, PyTorch",Associate,3,Transportation,2024-04-13,2024-05-22,1831,5.3,Predictive Systems +AI04996,AI Consultant,183450,USD,183450,EX,PT,United States,S,United States,50,"GCP, Computer Vision, SQL",Bachelor,17,Government,2024-06-17,2024-07-12,902,6.3,Neural Networks Co +AI04997,Machine Learning Engineer,81041,SGD,105353,EN,PT,Singapore,L,Singapore,0,"MLOps, PyTorch, Python, TensorFlow",Associate,1,Finance,2024-06-29,2024-08-16,1494,9.3,Autonomous Tech +AI04998,AI Software Engineer,80467,USD,80467,EX,PT,India,S,India,0,"Mathematics, Linux, Git, PyTorch",Master,14,Manufacturing,2024-11-22,2024-12-25,2205,6.8,Predictive Systems +AI04999,AI Software Engineer,88669,AUD,119703,MI,CT,Australia,L,Australia,100,"Python, Hadoop, MLOps",Master,3,Real Estate,2024-05-30,2024-08-10,1427,5.5,DataVision Ltd +AI05000,Machine Learning Researcher,113313,USD,113313,MI,FT,Sweden,L,Sweden,100,"Scala, SQL, PyTorch, R",PhD,3,Education,2024-09-27,2024-11-25,1895,9.5,Digital Transformation LLC +AI05001,Research Scientist,306192,USD,306192,EX,FT,Denmark,L,Denmark,0,"PyTorch, Azure, Tableau, Scala",PhD,11,Automotive,2025-02-25,2025-03-20,2405,5.5,Smart Analytics +AI05002,Head of AI,190624,USD,190624,EX,CT,Denmark,S,Denmark,50,"Kubernetes, Tableau, Python, Hadoop",Bachelor,15,Automotive,2024-10-22,2024-12-06,1947,7.2,Cloud AI Solutions +AI05003,NLP Engineer,68152,SGD,88598,EN,FT,Singapore,L,Egypt,0,"R, Azure, Kubernetes, Linux",PhD,0,Telecommunications,2024-03-20,2024-05-06,1227,9.1,Algorithmic Solutions +AI05004,Principal Data Scientist,91590,USD,91590,EN,CT,United States,L,Kenya,0,"PyTorch, SQL, Kubernetes, Java, AWS",Associate,1,Media,2024-06-27,2024-07-19,578,6.6,Autonomous Tech +AI05005,AI Research Scientist,50730,EUR,43121,EN,FT,Netherlands,S,Netherlands,0,"R, Java, Data Visualization, NLP",PhD,1,Real Estate,2024-04-28,2024-05-15,1020,5.7,TechCorp Inc +AI05006,Robotics Engineer,57915,GBP,43436,EN,FL,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, AWS, Mathematics, Git",Associate,0,Finance,2025-03-02,2025-04-20,2451,8.9,Future Systems +AI05007,AI Architect,74536,AUD,100624,MI,FL,Australia,S,Turkey,0,"Kubernetes, Docker, Data Visualization",PhD,2,Retail,2025-02-19,2025-04-26,1612,9.3,Predictive Systems +AI05008,Data Engineer,179315,USD,179315,SE,FL,Denmark,L,Denmark,0,"Python, TensorFlow, Linux, PyTorch",PhD,8,Education,2024-09-14,2024-10-29,925,5.3,Digital Transformation LLC +AI05009,ML Ops Engineer,19776,USD,19776,EN,FT,India,M,Japan,50,"Docker, Scala, GCP, MLOps",Bachelor,0,Consulting,2024-07-30,2024-09-17,604,8.3,DataVision Ltd +AI05010,Data Analyst,73489,EUR,62466,EN,CT,Netherlands,S,Ireland,0,"Computer Vision, Tableau, Linux, Git, Deep Learning",Master,0,Education,2024-11-23,2025-01-04,1966,9.7,DeepTech Ventures +AI05011,AI Product Manager,67007,JPY,7370770,EN,CT,Japan,S,Japan,100,"SQL, TensorFlow, Data Visualization, NLP, Linux",Bachelor,1,Finance,2024-10-18,2024-12-25,1765,8.2,Advanced Robotics +AI05012,Machine Learning Engineer,26216,USD,26216,EN,PT,China,M,China,50,"Hadoop, Data Visualization, Python, Statistics, Mathematics",Associate,1,Gaming,2024-08-16,2024-10-25,2458,6.5,Cognitive Computing +AI05013,ML Ops Engineer,80593,CAD,100741,MI,CT,Canada,L,Canada,100,"Hadoop, SQL, Java",Associate,3,Government,2024-06-09,2024-07-02,714,5.3,Machine Intelligence Group +AI05014,Principal Data Scientist,251940,AUD,340119,EX,FL,Australia,L,Australia,50,"NLP, R, Statistics, SQL, Data Visualization",Master,12,Manufacturing,2025-01-01,2025-01-21,2150,7.3,Advanced Robotics +AI05015,Data Scientist,271778,USD,271778,EX,FT,Ireland,L,Ukraine,0,"AWS, Linux, Python, TensorFlow, Computer Vision",Bachelor,17,Automotive,2024-05-06,2024-06-18,1477,8.3,Algorithmic Solutions +AI05016,AI Research Scientist,136680,EUR,116178,SE,FT,Austria,M,Austria,100,"Linux, Scala, Mathematics, Hadoop, Java",Associate,7,Energy,2024-06-27,2024-07-24,1821,6.7,Digital Transformation LLC +AI05017,AI Architect,90736,USD,90736,MI,CT,South Korea,M,Colombia,50,"Data Visualization, Git, R",Bachelor,3,Finance,2025-02-04,2025-03-18,1998,7.6,Future Systems +AI05018,Machine Learning Engineer,176612,USD,176612,EX,FT,Norway,M,Norway,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,12,Real Estate,2025-01-06,2025-01-23,1705,9.6,Digital Transformation LLC +AI05019,NLP Engineer,86142,USD,86142,SE,PT,South Korea,M,Czech Republic,100,"Computer Vision, NLP, Tableau, Data Visualization, MLOps",Master,6,Technology,2024-05-29,2024-07-19,2196,5.1,Advanced Robotics +AI05020,AI Research Scientist,71454,SGD,92890,MI,PT,Singapore,S,Singapore,100,"Scala, Linux, Data Visualization",Bachelor,4,Gaming,2024-02-21,2024-03-23,1063,6.1,Advanced Robotics +AI05021,AI Software Engineer,70698,USD,70698,EN,FT,Norway,S,Norway,100,"TensorFlow, Data Visualization, SQL, Hadoop, R",PhD,0,Real Estate,2024-08-07,2024-10-12,515,9.9,Algorithmic Solutions +AI05022,Computer Vision Engineer,70125,EUR,59606,EN,CT,Germany,M,United States,0,"TensorFlow, Tableau, GCP, Spark, Linux",Associate,0,Manufacturing,2025-04-14,2025-06-25,525,7.9,Machine Intelligence Group +AI05023,AI Specialist,164581,AUD,222184,EX,CT,Australia,S,Australia,100,"Tableau, Linux, PyTorch, TensorFlow, Computer Vision",Bachelor,11,Automotive,2025-02-04,2025-03-02,1128,9.7,TechCorp Inc +AI05024,NLP Engineer,125674,GBP,94256,SE,FL,United Kingdom,L,United Kingdom,100,"Computer Vision, MLOps, Git",Bachelor,6,Media,2024-08-16,2024-10-22,1388,8.8,Quantum Computing Inc +AI05025,Robotics Engineer,108470,CHF,97623,EN,FL,Switzerland,L,Switzerland,100,"Spark, Tableau, Docker, Deep Learning, NLP",Master,1,Telecommunications,2024-04-30,2024-07-10,1708,6.5,Quantum Computing Inc +AI05026,AI Architect,68849,USD,68849,EN,PT,United States,S,United States,0,"PyTorch, AWS, Computer Vision",Associate,0,Healthcare,2024-04-12,2024-06-09,1204,10,TechCorp Inc +AI05027,Autonomous Systems Engineer,101825,JPY,11200750,SE,CT,Japan,S,Japan,50,"MLOps, Java, Data Visualization, Linux, Scala",Bachelor,8,Real Estate,2025-02-27,2025-04-05,960,9.7,Future Systems +AI05028,Deep Learning Engineer,351728,USD,351728,EX,CT,Norway,L,Norway,0,"Tableau, Spark, Python, SQL",Bachelor,17,Real Estate,2024-09-22,2024-10-13,1508,5.3,Quantum Computing Inc +AI05029,Machine Learning Researcher,97819,USD,97819,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Git, GCP, Linux",Bachelor,9,Retail,2024-08-28,2024-09-14,1494,7.2,AI Innovations +AI05030,Data Scientist,163331,USD,163331,SE,FL,United States,M,United States,50,"TensorFlow, Git, Data Visualization, Kubernetes",Master,6,Healthcare,2025-04-29,2025-05-21,1419,9.5,Advanced Robotics +AI05031,Head of AI,93720,USD,93720,MI,CT,United States,M,United States,100,"Linux, Spark, SQL, PyTorch",PhD,4,Government,2024-12-19,2025-01-19,1659,9.1,Machine Intelligence Group +AI05032,NLP Engineer,108820,EUR,92497,MI,PT,Netherlands,M,Netherlands,50,"Kubernetes, Computer Vision, R, GCP, Hadoop",Master,2,Gaming,2024-12-14,2025-02-09,2389,9.4,AI Innovations +AI05033,AI Consultant,23491,USD,23491,EN,FL,India,S,India,0,"R, PyTorch, TensorFlow, Statistics",Bachelor,0,Healthcare,2024-02-07,2024-03-31,1921,7,TechCorp Inc +AI05034,Robotics Engineer,38464,USD,38464,SE,CT,India,M,Israel,100,"Python, TensorFlow, Statistics, PyTorch, Mathematics",PhD,6,Real Estate,2024-09-16,2024-10-17,1319,6.5,TechCorp Inc +AI05035,Data Analyst,121725,USD,121725,SE,PT,South Korea,M,South Korea,0,"Linux, TensorFlow, MLOps, Git, NLP",Bachelor,5,Government,2024-11-20,2024-12-23,1624,7.8,TechCorp Inc +AI05036,Computer Vision Engineer,121877,CHF,109689,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Deep Learning, Data Visualization",Bachelor,3,Finance,2024-03-21,2024-06-01,1183,6.6,Future Systems +AI05037,Machine Learning Researcher,96000,USD,96000,EN,CT,Norway,M,Norway,50,"Scala, Deep Learning, Computer Vision, GCP, Git",Bachelor,0,Retail,2024-01-27,2024-02-24,1635,8,Advanced Robotics +AI05038,Robotics Engineer,46573,USD,46573,SE,FT,China,S,China,100,"AWS, Linux, PyTorch, GCP",PhD,9,Government,2024-03-22,2024-05-09,830,9.9,Predictive Systems +AI05039,AI Architect,203167,EUR,172692,EX,CT,Austria,M,Austria,50,"SQL, PyTorch, Java, Hadoop",Associate,17,Education,2024-09-14,2024-10-09,865,9.6,DeepTech Ventures +AI05040,Data Scientist,177459,CHF,159713,SE,CT,Switzerland,S,Switzerland,50,"Spark, R, Hadoop, Linux, Mathematics",Bachelor,6,Telecommunications,2024-09-15,2024-10-29,740,9.4,Future Systems +AI05041,Machine Learning Engineer,41556,USD,41556,MI,FT,China,S,China,50,"Python, TensorFlow, Azure, Kubernetes",Associate,3,Gaming,2024-01-04,2024-03-05,1652,6.1,Quantum Computing Inc +AI05042,Data Scientist,152796,USD,152796,EX,PT,Sweden,M,Sweden,100,"Linux, Hadoop, Python",Master,10,Automotive,2025-02-17,2025-04-09,2123,8.4,Cognitive Computing +AI05043,Robotics Engineer,70161,JPY,7717710,EN,PT,Japan,L,Japan,0,"Spark, PyTorch, GCP, Scala, Statistics",PhD,0,Manufacturing,2024-01-18,2024-02-05,1333,6.3,DataVision Ltd +AI05044,ML Ops Engineer,66092,CAD,82615,EN,PT,Canada,S,Sweden,100,"SQL, Scala, NLP",PhD,1,Transportation,2024-03-07,2024-03-31,2308,5.6,Future Systems +AI05045,Data Engineer,271475,SGD,352918,EX,FL,Singapore,L,Singapore,0,"Git, Docker, Hadoop",Associate,10,Media,2024-08-25,2024-10-08,1142,7.1,DataVision Ltd +AI05046,AI Architect,71751,JPY,7892610,EN,CT,Japan,L,Japan,0,"Java, MLOps, Git, Computer Vision, Kubernetes",Associate,1,Real Estate,2024-08-08,2024-09-24,1649,8.1,DeepTech Ventures +AI05047,Research Scientist,91975,USD,91975,EX,PT,China,S,China,0,"Azure, Docker, Mathematics, Statistics, GCP",Bachelor,10,Technology,2024-03-28,2024-05-08,735,8.1,Autonomous Tech +AI05048,Machine Learning Researcher,139317,EUR,118419,SE,FL,France,M,France,100,"Python, Kubernetes, Data Visualization",Bachelor,9,Consulting,2024-09-02,2024-10-04,2142,7.9,Future Systems +AI05049,Machine Learning Researcher,56279,EUR,47837,EN,CT,Netherlands,S,Indonesia,0,"Docker, Python, Data Visualization, Deep Learning",Bachelor,1,Technology,2024-05-07,2024-07-06,2433,7.6,Cloud AI Solutions +AI05050,Head of AI,212031,AUD,286242,EX,PT,Australia,M,Australia,100,"AWS, Statistics, Git, SQL",Associate,15,Gaming,2025-03-10,2025-04-16,1142,7.9,Autonomous Tech +AI05051,AI Research Scientist,261631,AUD,353202,EX,FT,Australia,L,New Zealand,50,"Computer Vision, NLP, GCP",Associate,10,Technology,2024-07-31,2024-08-18,982,6.6,Cognitive Computing +AI05052,Machine Learning Researcher,41755,USD,41755,MI,FL,China,M,China,100,"NLP, SQL, TensorFlow, Linux, Computer Vision",Associate,4,Gaming,2024-10-21,2024-11-30,1171,7.6,Advanced Robotics +AI05053,Computer Vision Engineer,78608,EUR,66817,EN,PT,Netherlands,M,Malaysia,50,"Data Visualization, Scala, Java, Computer Vision, Tableau",PhD,0,Energy,2025-01-20,2025-03-10,642,9.9,Digital Transformation LLC +AI05054,Head of AI,37889,USD,37889,SE,FT,India,M,India,100,"Scala, Deep Learning, MLOps, Python",Associate,8,Retail,2024-02-19,2024-04-03,856,8.9,DataVision Ltd +AI05055,Data Scientist,97397,USD,97397,EN,CT,United States,L,Brazil,50,"Git, Deep Learning, TensorFlow",PhD,1,Finance,2025-04-02,2025-05-05,1562,9.5,Cognitive Computing +AI05056,Data Analyst,265023,USD,265023,EX,CT,Denmark,S,Spain,50,"Git, Docker, Statistics",Master,16,Manufacturing,2024-12-15,2025-01-12,1294,7.7,DataVision Ltd +AI05057,Machine Learning Researcher,143323,AUD,193486,SE,FL,Australia,M,Australia,0,"Tableau, Java, Git",Bachelor,5,Energy,2024-10-31,2025-01-06,729,7,Machine Intelligence Group +AI05058,Head of AI,97000,EUR,82450,SE,CT,France,M,France,0,"Java, SQL, Python, Docker",Associate,5,Technology,2024-01-10,2024-02-03,2147,6.5,Neural Networks Co +AI05059,AI Software Engineer,46374,USD,46374,EN,CT,Ireland,S,United States,100,"PyTorch, Kubernetes, Docker",Bachelor,1,Telecommunications,2024-07-03,2024-09-10,2065,8.9,Smart Analytics +AI05060,AI Architect,229381,EUR,194974,EX,CT,France,M,France,50,"Python, TensorFlow, Scala",PhD,19,Technology,2024-10-01,2024-10-23,1365,9,Digital Transformation LLC +AI05061,Computer Vision Engineer,158873,JPY,17476030,SE,FL,Japan,M,Japan,50,"GCP, Java, Azure",Bachelor,6,Education,2024-06-07,2024-07-04,2166,9.1,Future Systems +AI05062,Machine Learning Engineer,69868,USD,69868,EN,PT,Norway,M,India,50,"Kubernetes, AWS, GCP",Associate,0,Education,2024-02-23,2024-03-26,1959,7.7,DeepTech Ventures +AI05063,AI Specialist,101000,CHF,90900,EN,PT,Switzerland,S,Switzerland,0,"PyTorch, TensorFlow, Python, Git",Bachelor,0,Consulting,2024-12-31,2025-02-13,2181,5.7,Digital Transformation LLC +AI05064,Data Engineer,81849,SGD,106404,EN,CT,Singapore,M,Singapore,100,"NLP, PyTorch, Statistics, Hadoop",PhD,1,Automotive,2024-07-21,2024-09-24,1881,7.7,Smart Analytics +AI05065,AI Architect,134380,GBP,100785,SE,CT,United Kingdom,L,United Kingdom,100,"Git, Azure, Statistics, NLP",PhD,5,Telecommunications,2025-03-04,2025-04-12,2293,5.6,TechCorp Inc +AI05066,Data Scientist,167829,CHF,151046,SE,PT,Switzerland,M,Switzerland,50,"Hadoop, PyTorch, Git, Data Visualization, Docker",Master,7,Government,2024-06-17,2024-08-09,1514,6.7,AI Innovations +AI05067,Machine Learning Engineer,24678,USD,24678,EN,PT,China,S,China,0,"Python, SQL, PyTorch",Master,0,Healthcare,2024-03-22,2024-04-05,1955,9,Predictive Systems +AI05068,Autonomous Systems Engineer,54248,SGD,70522,EN,CT,Singapore,S,Singapore,50,"Scala, Docker, MLOps, AWS, SQL",Bachelor,0,Technology,2024-10-14,2024-12-06,1096,5.5,DeepTech Ventures +AI05069,Head of AI,99288,EUR,84395,SE,CT,Austria,S,Austria,100,"Kubernetes, Spark, AWS",PhD,6,Healthcare,2024-04-04,2024-05-22,2422,7.6,Machine Intelligence Group +AI05070,AI Product Manager,189688,USD,189688,EX,FL,United States,S,United States,100,"Scala, TensorFlow, Mathematics, NLP, Linux",Master,11,Consulting,2024-06-01,2024-06-27,1807,9.8,Smart Analytics +AI05071,Machine Learning Engineer,89528,JPY,9848080,MI,CT,Japan,M,Russia,50,"SQL, Python, Tableau, Java, Docker",Bachelor,3,Government,2024-05-19,2024-06-26,1088,5.4,Advanced Robotics +AI05072,AI Consultant,88720,USD,88720,MI,FT,United States,S,United States,0,"Statistics, Python, TensorFlow, PyTorch, Hadoop",PhD,3,Finance,2025-04-27,2025-07-03,2198,5.6,Algorithmic Solutions +AI05073,NLP Engineer,72059,USD,72059,EN,FT,Sweden,S,Sweden,50,"Git, Scala, Tableau, Computer Vision",Associate,0,Technology,2024-04-26,2024-05-15,2043,8,Predictive Systems +AI05074,Machine Learning Researcher,50803,EUR,43183,EN,PT,France,S,France,0,"TensorFlow, Git, Statistics, SQL",Master,0,Finance,2024-02-18,2024-04-15,1539,9.3,Cloud AI Solutions +AI05075,AI Consultant,24223,USD,24223,EN,FL,India,S,India,100,"Statistics, Hadoop, MLOps, Azure",Associate,1,Gaming,2025-04-03,2025-04-29,2463,8,Cognitive Computing +AI05076,Deep Learning Engineer,121910,USD,121910,MI,FL,Denmark,M,Denmark,100,"Data Visualization, PyTorch, Spark, TensorFlow, SQL",PhD,2,Retail,2025-03-05,2025-05-11,1058,5.9,Machine Intelligence Group +AI05077,Autonomous Systems Engineer,27869,USD,27869,MI,FT,India,M,India,100,"NLP, Docker, Python, Azure",Bachelor,2,Retail,2024-12-03,2025-01-15,1498,9.5,Advanced Robotics +AI05078,Data Scientist,79781,USD,79781,SE,FL,China,L,China,100,"PyTorch, NLP, Data Visualization",PhD,7,Government,2024-05-27,2024-07-28,1915,7.4,Smart Analytics +AI05079,Computer Vision Engineer,94380,CAD,117975,MI,PT,Canada,L,Canada,100,"Git, Hadoop, Python",Master,3,Government,2024-11-23,2025-01-23,943,6.6,Neural Networks Co +AI05080,Deep Learning Engineer,57159,GBP,42869,EN,FL,United Kingdom,S,Netherlands,50,"R, Azure, Tableau, NLP, Linux",Master,1,Healthcare,2024-01-08,2024-02-25,766,6.6,Cloud AI Solutions +AI05081,AI Software Engineer,70183,USD,70183,EX,FT,China,S,China,100,"Statistics, NLP, TensorFlow, Git",Associate,18,Technology,2025-02-20,2025-04-14,1019,7.4,Predictive Systems +AI05082,AI Research Scientist,63741,USD,63741,EN,PT,Finland,L,Finland,0,"Java, Python, Hadoop",Bachelor,1,Healthcare,2024-01-27,2024-02-10,2032,6.1,AI Innovations +AI05083,AI Product Manager,125484,AUD,169403,SE,FT,Australia,L,Australia,100,"PyTorch, TensorFlow, NLP, Git, Spark",Master,6,Gaming,2024-11-29,2024-12-26,1576,8.1,TechCorp Inc +AI05084,Head of AI,165739,JPY,18231290,SE,FT,Japan,L,Japan,50,"R, Python, NLP, TensorFlow",Bachelor,5,Energy,2024-12-09,2025-02-16,2291,9.6,Digital Transformation LLC +AI05085,ML Ops Engineer,70983,EUR,60336,EN,PT,Austria,M,Austria,100,"Deep Learning, Python, MLOps, Java, TensorFlow",Associate,0,Finance,2024-04-05,2024-04-26,1418,5.4,Predictive Systems +AI05086,AI Specialist,110016,GBP,82512,MI,PT,United Kingdom,L,United Kingdom,0,"Python, Hadoop, TensorFlow",PhD,4,Real Estate,2025-04-30,2025-05-28,2127,8.4,Algorithmic Solutions +AI05087,Data Engineer,123436,CHF,111092,EN,PT,Switzerland,L,Switzerland,100,"Kubernetes, Java, Statistics, NLP, Docker",PhD,0,Technology,2025-02-26,2025-04-15,1329,9.2,Smart Analytics +AI05088,Deep Learning Engineer,81729,USD,81729,MI,CT,Ireland,M,Thailand,100,"Java, Azure, NLP, SQL, AWS",Associate,3,Technology,2024-03-06,2024-04-25,552,6.2,Machine Intelligence Group +AI05089,Principal Data Scientist,24353,USD,24353,EN,FT,China,S,China,100,"R, SQL, NLP",Bachelor,1,Finance,2024-02-16,2024-04-27,1050,8.8,DeepTech Ventures +AI05090,AI Consultant,48696,USD,48696,EN,CT,South Korea,L,Mexico,50,"Hadoop, Tableau, Spark, MLOps",PhD,1,Consulting,2025-02-26,2025-03-24,1665,7.6,Cloud AI Solutions +AI05091,AI Software Engineer,114364,CHF,102928,EN,PT,Switzerland,L,South Africa,100,"MLOps, PyTorch, NLP, Mathematics",PhD,0,Telecommunications,2024-01-11,2024-03-15,1731,8.4,Advanced Robotics +AI05092,AI Architect,93835,USD,93835,EN,CT,United States,M,Argentina,50,"Docker, MLOps, Git",Bachelor,1,Real Estate,2025-02-05,2025-03-06,1431,6.9,Autonomous Tech +AI05093,AI Architect,170109,USD,170109,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Computer Vision, Tableau, Python, Azure",Associate,8,Consulting,2025-03-14,2025-05-21,1430,8.9,Predictive Systems +AI05094,Principal Data Scientist,89443,JPY,9838730,EN,FT,Japan,L,Romania,0,"Git, AWS, R",PhD,0,Automotive,2025-02-09,2025-02-27,2366,7,Future Systems +AI05095,AI Specialist,252682,CHF,227414,EX,CT,Switzerland,L,Switzerland,50,"Git, SQL, GCP",Bachelor,12,Education,2025-03-28,2025-05-30,969,8.2,Machine Intelligence Group +AI05096,Machine Learning Engineer,133737,JPY,14711070,SE,CT,Japan,M,Japan,0,"Azure, GCP, Spark, MLOps, AWS",PhD,9,Retail,2024-12-23,2025-02-22,1774,6.6,Cognitive Computing +AI05097,NLP Engineer,73390,USD,73390,EN,CT,Israel,L,Brazil,0,"SQL, TensorFlow, Tableau, AWS",PhD,1,Consulting,2024-01-10,2024-03-08,2396,6.3,Algorithmic Solutions +AI05098,Deep Learning Engineer,215737,EUR,183376,EX,FT,Germany,M,Ghana,100,"Computer Vision, PyTorch, Python, AWS",Associate,13,Telecommunications,2024-07-14,2024-08-14,670,6.4,Machine Intelligence Group +AI05099,Data Analyst,154884,CHF,139396,MI,FL,Switzerland,L,Switzerland,100,"Scala, Java, AWS, PyTorch",PhD,3,Technology,2024-05-18,2024-06-26,1197,7.6,Autonomous Tech +AI05100,AI Specialist,63606,EUR,54065,MI,FT,France,S,India,0,"Scala, Spark, Git, Computer Vision",Associate,2,Media,2024-08-18,2024-09-29,1449,5.6,Machine Intelligence Group +AI05101,AI Software Engineer,26739,USD,26739,MI,FL,India,S,India,50,"Python, SQL, Linux",PhD,2,Automotive,2024-09-10,2024-10-28,2446,5.6,Smart Analytics +AI05102,AI Research Scientist,38550,USD,38550,SE,PT,India,S,Argentina,50,"Kubernetes, TensorFlow, Git",Master,7,Energy,2024-07-13,2024-09-09,503,9.6,Advanced Robotics +AI05103,Machine Learning Engineer,74739,USD,74739,MI,FT,South Korea,M,South Korea,0,"AWS, Computer Vision, R",PhD,3,Retail,2024-06-21,2024-08-02,1362,7.5,Digital Transformation LLC +AI05104,AI Architect,160816,CHF,144734,MI,FT,Switzerland,L,Switzerland,50,"Scala, Java, AWS, Computer Vision",PhD,3,Technology,2024-01-11,2024-02-23,1597,8.3,DeepTech Ventures +AI05105,Research Scientist,73482,USD,73482,EN,PT,United States,S,Colombia,100,"Computer Vision, Tableau, TensorFlow, GCP",PhD,0,Government,2024-05-17,2024-06-29,1698,8.2,Smart Analytics +AI05106,Deep Learning Engineer,53504,USD,53504,EN,PT,Finland,S,Finland,100,"Data Visualization, Azure, Tableau, Docker, PyTorch",PhD,1,Manufacturing,2025-03-01,2025-04-05,1171,6.5,Cognitive Computing +AI05107,AI Architect,58640,EUR,49844,EN,FL,Germany,S,Malaysia,50,"Mathematics, Linux, PyTorch",Associate,1,Manufacturing,2025-03-03,2025-04-21,2294,9.3,Advanced Robotics +AI05108,Principal Data Scientist,110169,EUR,93644,SE,CT,France,S,Switzerland,100,"Java, SQL, Mathematics, MLOps, Deep Learning",Bachelor,5,Energy,2024-04-23,2024-06-28,2276,6.2,Cloud AI Solutions +AI05109,Data Engineer,61539,EUR,52308,EN,FT,Netherlands,S,Netherlands,50,"PyTorch, Docker, Tableau, Mathematics, Azure",Master,0,Gaming,2024-12-15,2025-02-10,972,5.9,Advanced Robotics +AI05110,AI Product Manager,33132,USD,33132,EN,FT,China,M,China,0,"Deep Learning, TensorFlow, Linux, MLOps, Python",Master,0,Finance,2024-02-07,2024-04-04,1289,6,Smart Analytics +AI05111,NLP Engineer,50597,USD,50597,EN,FT,Ireland,S,Ireland,100,"Tableau, GCP, Git, MLOps, Java",Master,0,Healthcare,2025-02-25,2025-04-05,1056,8,Smart Analytics +AI05112,AI Product Manager,138723,SGD,180340,SE,CT,Singapore,S,Norway,0,"Spark, PyTorch, Mathematics",Associate,7,Technology,2025-04-16,2025-05-18,1946,5.5,Predictive Systems +AI05113,ML Ops Engineer,96580,USD,96580,EX,PT,China,L,China,50,"Computer Vision, GCP, Hadoop",Associate,17,Real Estate,2025-03-14,2025-05-13,608,5.5,DataVision Ltd +AI05114,Principal Data Scientist,75245,GBP,56434,EN,FL,United Kingdom,M,United Kingdom,100,"Deep Learning, Python, Linux, Kubernetes",Master,0,Finance,2025-02-21,2025-04-07,579,6.3,Cognitive Computing +AI05115,AI Research Scientist,100596,USD,100596,EN,FL,Denmark,L,Switzerland,100,"PyTorch, Java, MLOps",Bachelor,0,Real Estate,2025-02-17,2025-03-26,1945,7.3,DeepTech Ventures +AI05116,Principal Data Scientist,82608,USD,82608,EN,FT,Sweden,L,Sweden,50,"Data Visualization, Docker, Mathematics",Master,0,Healthcare,2024-01-14,2024-02-28,2416,7.5,DataVision Ltd +AI05117,Principal Data Scientist,86868,EUR,73838,MI,PT,Austria,M,Estonia,50,"Python, Deep Learning, Kubernetes, Statistics, Hadoop",PhD,3,Transportation,2024-06-12,2024-07-13,1798,8.4,Smart Analytics +AI05118,Data Engineer,92090,USD,92090,EN,FT,Denmark,M,Denmark,0,"Data Visualization, AWS, Azure",Associate,0,Gaming,2025-02-20,2025-04-19,2090,6.2,DataVision Ltd +AI05119,AI Research Scientist,125783,USD,125783,MI,PT,Denmark,M,Denmark,50,"Spark, TensorFlow, Deep Learning, Tableau",Master,2,Retail,2024-02-14,2024-04-27,2313,8.6,TechCorp Inc +AI05120,Machine Learning Researcher,168390,SGD,218907,EX,FT,Singapore,S,Singapore,50,"TensorFlow, NLP, Git, GCP, Spark",Master,18,Telecommunications,2024-06-25,2024-07-11,635,5.4,Future Systems +AI05121,AI Product Manager,193710,CHF,174339,SE,FT,Switzerland,L,Turkey,0,"Python, Kubernetes, Data Visualization",Bachelor,8,Finance,2024-09-20,2024-10-14,696,5.2,Neural Networks Co +AI05122,Robotics Engineer,86414,USD,86414,MI,CT,Ireland,S,Thailand,50,"Python, Linux, Data Visualization, Deep Learning",PhD,4,Energy,2024-09-09,2024-10-10,644,6.2,AI Innovations +AI05123,AI Software Engineer,136589,CAD,170736,SE,FT,Canada,M,Canada,100,"Java, Scala, MLOps, Statistics",Bachelor,8,Energy,2024-02-18,2024-04-17,2280,6.5,Neural Networks Co +AI05124,Research Scientist,116556,AUD,157351,MI,PT,Australia,L,Australia,0,"Hadoop, AWS, Java, Computer Vision",Bachelor,4,Government,2024-12-10,2025-01-17,1582,8.8,Advanced Robotics +AI05125,AI Research Scientist,147616,EUR,125474,SE,FT,France,L,France,50,"Git, Azure, MLOps, Python",Master,9,Telecommunications,2025-01-16,2025-03-05,1224,6.1,AI Innovations +AI05126,ML Ops Engineer,167103,JPY,18381330,EX,CT,Japan,L,Colombia,100,"PyTorch, Git, NLP",Master,19,Manufacturing,2024-01-10,2024-02-24,918,6.5,Digital Transformation LLC +AI05127,Research Scientist,187756,USD,187756,EX,PT,Norway,M,Norway,0,"Scala, SQL, MLOps, Kubernetes",PhD,13,Government,2025-03-21,2025-04-30,635,9.7,Neural Networks Co +AI05128,ML Ops Engineer,25560,USD,25560,EN,FL,India,S,India,0,"Git, Java, Hadoop, AWS",Bachelor,0,Finance,2024-12-17,2025-02-09,1801,9.3,Predictive Systems +AI05129,Data Analyst,64206,USD,64206,MI,CT,South Korea,S,South Korea,100,"SQL, R, Scala",Bachelor,3,Media,2024-10-15,2024-12-14,1941,9.9,Digital Transformation LLC +AI05130,AI Architect,118221,EUR,100488,MI,PT,Germany,L,Germany,100,"Statistics, GCP, Mathematics, R, NLP",Master,4,Consulting,2024-12-08,2025-01-22,2017,5.7,Digital Transformation LLC +AI05131,Data Analyst,104839,JPY,11532290,MI,CT,Japan,M,Japan,100,"Java, Linux, Data Visualization, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-25,1810,5.9,Autonomous Tech +AI05132,AI Architect,86714,USD,86714,MI,CT,South Korea,L,South Korea,0,"GCP, Linux, Hadoop, TensorFlow, Data Visualization",Master,2,Education,2024-10-25,2024-11-20,1338,6.7,Cloud AI Solutions +AI05133,AI Research Scientist,110353,USD,110353,MI,CT,Norway,S,Norway,50,"PyTorch, AWS, SQL, R, MLOps",Bachelor,4,Retail,2025-04-25,2025-06-10,877,9.9,Predictive Systems +AI05134,Machine Learning Researcher,61142,USD,61142,EN,PT,Finland,M,Germany,50,"Mathematics, Linux, R, Java",Bachelor,1,Consulting,2024-10-04,2024-10-29,933,7.5,DataVision Ltd +AI05135,ML Ops Engineer,155690,USD,155690,SE,CT,Norway,L,Ukraine,0,"R, Git, Data Visualization, Python, Spark",Bachelor,6,Education,2025-01-20,2025-02-16,619,6.5,AI Innovations +AI05136,Research Scientist,117303,USD,117303,EX,FL,China,L,China,0,"Python, Git, Azure, Deep Learning, TensorFlow",Master,17,Energy,2024-06-16,2024-08-14,1415,6.9,Quantum Computing Inc +AI05137,Data Scientist,55265,CAD,69081,EN,CT,Canada,M,Canada,100,"Java, Kubernetes, NLP, Spark",Master,1,Automotive,2024-12-12,2024-12-27,1241,9.6,Algorithmic Solutions +AI05138,Data Analyst,76310,USD,76310,EX,CT,India,L,India,100,"Git, Python, MLOps",Master,19,Telecommunications,2024-11-17,2024-12-27,786,8.4,Cloud AI Solutions +AI05139,Autonomous Systems Engineer,93083,SGD,121008,EN,FT,Singapore,L,Egypt,50,"Azure, AWS, Deep Learning, Git",Master,1,Technology,2024-08-06,2024-09-28,2421,6.5,Machine Intelligence Group +AI05140,Research Scientist,133350,USD,133350,SE,CT,Norway,S,Norway,100,"Computer Vision, Docker, PyTorch",PhD,7,Transportation,2025-02-25,2025-03-26,1457,8.7,Machine Intelligence Group +AI05141,Computer Vision Engineer,86337,USD,86337,MI,CT,Finland,S,United Kingdom,0,"Hadoop, SQL, Data Visualization, PyTorch",Master,2,Telecommunications,2025-01-18,2025-02-18,1291,8.2,DataVision Ltd +AI05142,Data Scientist,86313,USD,86313,MI,CT,Ireland,M,Ireland,100,"Data Visualization, R, GCP, Python, Computer Vision",PhD,2,Retail,2024-05-12,2024-06-19,2120,7.6,Neural Networks Co +AI05143,ML Ops Engineer,57198,USD,57198,SE,CT,China,M,China,0,"Mathematics, Scala, Kubernetes",PhD,7,Education,2024-05-14,2024-06-21,2017,5.4,DataVision Ltd +AI05144,AI Software Engineer,60582,JPY,6664020,EN,FT,Japan,S,Japan,0,"NLP, Deep Learning, Azure, Python",PhD,1,Education,2024-07-16,2024-08-21,1597,9.4,Advanced Robotics +AI05145,Head of AI,55380,EUR,47073,EN,CT,Austria,M,Austria,0,"Git, GCP, AWS, Mathematics",Bachelor,0,Gaming,2025-03-10,2025-03-26,1708,6.8,DeepTech Ventures +AI05146,AI Research Scientist,48341,USD,48341,SE,FL,India,M,India,0,"Kubernetes, GCP, MLOps, Docker",Associate,7,Technology,2024-06-11,2024-07-23,1819,7.5,AI Innovations +AI05147,AI Product Manager,251565,USD,251565,EX,FT,Norway,L,Norway,50,"GCP, Python, Statistics",Master,17,Healthcare,2024-05-10,2024-06-28,1282,8,Advanced Robotics +AI05148,Machine Learning Researcher,236217,CHF,212595,EX,PT,Switzerland,S,Switzerland,50,"Tableau, Kubernetes, AWS, Mathematics, Scala",Bachelor,13,Education,2025-04-16,2025-06-03,1026,9.3,Digital Transformation LLC +AI05149,Autonomous Systems Engineer,91231,USD,91231,SE,CT,South Korea,M,Colombia,100,"Spark, Scala, MLOps",Master,6,Healthcare,2024-02-04,2024-03-04,1711,7,Neural Networks Co +AI05150,Machine Learning Researcher,61130,USD,61130,EN,FL,Israel,S,Nigeria,0,"SQL, MLOps, Computer Vision, Python, GCP",Bachelor,0,Manufacturing,2024-11-24,2025-01-10,1637,9,AI Innovations +AI05151,Computer Vision Engineer,62398,CAD,77998,EN,CT,Canada,L,Canada,50,"Data Visualization, Linux, Spark",Master,1,Healthcare,2024-06-03,2024-07-05,1982,9.2,AI Innovations +AI05152,Research Scientist,176242,EUR,149806,EX,FL,France,M,South Africa,50,"Python, Hadoop, GCP",Bachelor,14,Education,2025-02-04,2025-04-05,1846,8.2,Neural Networks Co +AI05153,Data Analyst,153418,EUR,130405,EX,FL,France,M,France,100,"MLOps, R, Scala",Bachelor,13,Government,2025-03-26,2025-04-15,844,7.6,DeepTech Ventures +AI05154,Data Scientist,81657,CAD,102071,MI,CT,Canada,S,New Zealand,50,"Scala, Git, Python",Master,2,Energy,2024-08-31,2024-10-12,2064,6.7,Algorithmic Solutions +AI05155,Data Analyst,69844,USD,69844,EN,PT,Israel,L,Israel,100,"Java, SQL, PyTorch, Computer Vision, Hadoop",Bachelor,0,Technology,2025-04-16,2025-05-16,910,7.3,TechCorp Inc +AI05156,AI Consultant,91682,EUR,77930,MI,FT,Netherlands,M,Netherlands,50,"NLP, Linux, Azure, Deep Learning",Associate,4,Gaming,2024-10-02,2024-11-27,1604,5.1,Smart Analytics +AI05157,Computer Vision Engineer,69595,AUD,93953,MI,FT,Australia,S,Russia,50,"PyTorch, TensorFlow, Tableau, AWS, Hadoop",Bachelor,3,Transportation,2024-03-19,2024-04-14,774,8.7,Predictive Systems +AI05158,AI Software Engineer,101742,USD,101742,EN,CT,Norway,L,Spain,100,"Linux, SQL, Tableau, Java",Bachelor,0,Retail,2024-10-03,2024-11-20,1067,9.2,Algorithmic Solutions +AI05159,Head of AI,97961,USD,97961,MI,PT,Israel,L,Israel,0,"AWS, Azure, Git, Mathematics",PhD,4,Education,2024-02-14,2024-04-01,1688,8.1,Future Systems +AI05160,AI Consultant,106022,JPY,11662420,MI,FT,Japan,M,Romania,100,"R, SQL, Data Visualization",Master,3,Energy,2024-08-11,2024-09-29,1832,6.4,AI Innovations +AI05161,ML Ops Engineer,46651,USD,46651,MI,PT,China,M,China,50,"Java, Tableau, PyTorch, Computer Vision",Bachelor,2,Telecommunications,2025-03-15,2025-04-17,807,7.3,Algorithmic Solutions +AI05162,Robotics Engineer,124553,CAD,155691,SE,PT,Canada,L,Canada,0,"Mathematics, Linux, Python, Deep Learning, Kubernetes",PhD,9,Manufacturing,2024-06-03,2024-07-31,922,9.8,DeepTech Ventures +AI05163,ML Ops Engineer,104780,EUR,89063,SE,PT,Austria,S,Austria,100,"Git, Python, Spark",Bachelor,8,Education,2024-07-02,2024-09-06,926,6.4,Autonomous Tech +AI05164,AI Specialist,114730,AUD,154886,SE,CT,Australia,S,Brazil,100,"SQL, R, PyTorch",Master,5,Retail,2024-05-13,2024-06-27,787,6.3,Machine Intelligence Group +AI05165,Research Scientist,162856,EUR,138428,SE,CT,France,L,France,0,"Git, Spark, Kubernetes, Statistics, Azure",Bachelor,5,Telecommunications,2024-10-14,2024-11-15,635,9.7,TechCorp Inc +AI05166,Robotics Engineer,125641,USD,125641,SE,FL,Sweden,S,Vietnam,100,"PyTorch, Computer Vision, AWS, SQL, MLOps",Associate,5,Education,2024-11-09,2025-01-20,1422,8,Cognitive Computing +AI05167,Machine Learning Engineer,89881,CHF,80893,EN,CT,Switzerland,L,Australia,0,"Data Visualization, TensorFlow, Azure",Bachelor,1,Telecommunications,2024-12-14,2025-01-22,993,5.3,TechCorp Inc +AI05168,AI Consultant,289064,USD,289064,EX,FL,United States,L,United States,50,"R, SQL, Tableau, MLOps, Docker",Master,17,Education,2024-04-04,2024-05-13,581,6.2,Machine Intelligence Group +AI05169,AI Specialist,226888,USD,226888,EX,FT,Sweden,S,Denmark,0,"Java, SQL, Data Visualization, PyTorch, Computer Vision",Master,13,Technology,2024-09-15,2024-10-27,2487,8.4,Cloud AI Solutions +AI05170,Principal Data Scientist,153723,EUR,130665,EX,CT,Netherlands,M,Netherlands,50,"Statistics, Spark, Python",Associate,13,Retail,2024-12-28,2025-03-05,1731,8.8,DeepTech Ventures +AI05171,AI Research Scientist,220723,SGD,286940,EX,FT,Singapore,S,Canada,50,"Mathematics, Python, Tableau",Associate,13,Media,2024-02-29,2024-04-19,1833,8,Future Systems +AI05172,Data Analyst,93378,EUR,79371,MI,FT,France,L,South Africa,100,"Spark, GCP, Scala, Computer Vision, Deep Learning",Master,3,Gaming,2024-08-06,2024-08-21,1938,6,TechCorp Inc +AI05173,ML Ops Engineer,162034,GBP,121526,SE,FT,United Kingdom,L,United Kingdom,50,"SQL, TensorFlow, Data Visualization",PhD,5,Media,2024-07-28,2024-08-30,1441,10,Cloud AI Solutions +AI05174,Head of AI,117365,USD,117365,SE,PT,Ireland,S,Ireland,100,"Statistics, Data Visualization, Git",Bachelor,5,Retail,2024-07-25,2024-09-04,1472,7.2,Autonomous Tech +AI05175,Machine Learning Engineer,128624,USD,128624,MI,PT,Denmark,M,Denmark,50,"GCP, Java, Azure, Linux",Master,2,Consulting,2025-04-15,2025-05-24,527,8.9,Quantum Computing Inc +AI05176,Head of AI,112504,EUR,95628,SE,PT,France,M,Austria,50,"Deep Learning, Docker, Computer Vision, Azure, Kubernetes",Bachelor,9,Education,2024-02-16,2024-03-28,1791,5.2,Digital Transformation LLC +AI05177,Data Analyst,91750,USD,91750,MI,CT,Norway,S,Norway,0,"Mathematics, TensorFlow, Computer Vision",Master,4,Transportation,2025-02-08,2025-03-09,1374,10,Neural Networks Co +AI05178,Machine Learning Engineer,216192,USD,216192,EX,FT,South Korea,L,South Korea,100,"Hadoop, Spark, NLP, Computer Vision",Bachelor,15,Gaming,2024-03-03,2024-04-12,508,6.2,Advanced Robotics +AI05179,Principal Data Scientist,102086,USD,102086,SE,FT,Israel,S,Israel,50,"Scala, Java, Azure, Data Visualization, TensorFlow",Associate,5,Finance,2024-04-21,2024-06-10,1342,6.2,Machine Intelligence Group +AI05180,Machine Learning Engineer,150372,USD,150372,SE,PT,Israel,L,Israel,0,"Scala, R, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-08-12,2306,7,Algorithmic Solutions +AI05181,Data Analyst,132314,USD,132314,MI,FT,Norway,L,Turkey,100,"PyTorch, Scala, GCP, Mathematics",Bachelor,4,Automotive,2024-09-21,2024-10-14,1172,9.6,Cloud AI Solutions +AI05182,Data Analyst,103230,USD,103230,MI,PT,Sweden,M,Sweden,100,"Java, Scala, Kubernetes, NLP",Bachelor,2,Telecommunications,2024-03-27,2024-05-22,1418,9.9,Algorithmic Solutions +AI05183,AI Architect,120695,CAD,150869,SE,FL,Canada,L,Hungary,50,"GCP, NLP, Azure",Associate,8,Government,2024-08-16,2024-09-30,1328,5.8,Advanced Robotics +AI05184,Machine Learning Engineer,182121,USD,182121,EX,FT,Ireland,M,Austria,100,"Data Visualization, PyTorch, TensorFlow",Associate,19,Energy,2025-04-22,2025-05-07,2017,8.9,Neural Networks Co +AI05185,AI Architect,73616,CHF,66254,EN,PT,Switzerland,S,Argentina,100,"PyTorch, TensorFlow, Docker, Hadoop, Mathematics",PhD,0,Automotive,2024-03-06,2024-04-03,1044,9,Future Systems +AI05186,NLP Engineer,80112,USD,80112,EN,FT,Sweden,M,Denmark,50,"SQL, Python, Scala",Master,0,Telecommunications,2024-01-01,2024-02-06,2050,9.3,Algorithmic Solutions +AI05187,Data Scientist,95409,GBP,71557,MI,FL,United Kingdom,S,United Kingdom,100,"SQL, GCP, Computer Vision",Master,2,Automotive,2024-09-26,2024-11-25,1359,7.1,Predictive Systems +AI05188,NLP Engineer,120427,USD,120427,SE,FT,Israel,L,Israel,100,"Kubernetes, Spark, Java, TensorFlow, Statistics",Bachelor,5,Government,2024-08-12,2024-09-08,2168,9.9,Future Systems +AI05189,AI Research Scientist,38463,USD,38463,SE,CT,India,M,India,0,"Docker, Tableau, Java",Master,6,Gaming,2024-03-06,2024-05-09,2482,9.3,Algorithmic Solutions +AI05190,AI Software Engineer,38200,USD,38200,MI,FT,India,L,India,100,"PyTorch, Tableau, GCP",Bachelor,2,Media,2024-10-24,2024-12-03,1106,5.2,Smart Analytics +AI05191,Head of AI,74370,USD,74370,EN,CT,Ireland,M,Ireland,100,"Python, AWS, MLOps",Bachelor,0,Education,2025-01-10,2025-02-27,2007,9.1,Quantum Computing Inc +AI05192,AI Software Engineer,96885,EUR,82352,MI,FL,Germany,M,Germany,0,"R, Deep Learning, SQL, Statistics",Associate,3,Media,2024-01-17,2024-02-26,2017,5.8,Quantum Computing Inc +AI05193,AI Specialist,23564,USD,23564,EN,FL,India,M,Australia,0,"Linux, Python, Tableau, Hadoop",PhD,1,Healthcare,2025-04-19,2025-05-17,514,6.8,Neural Networks Co +AI05194,Machine Learning Engineer,135679,EUR,115327,SE,FL,Austria,M,Austria,50,"Python, Java, Computer Vision",Master,9,Media,2025-04-27,2025-06-17,1647,9.2,DeepTech Ventures +AI05195,ML Ops Engineer,85715,USD,85715,MI,CT,Finland,L,Ghana,100,"MLOps, Deep Learning, R",Master,2,Energy,2025-02-24,2025-05-03,2049,7.3,Digital Transformation LLC +AI05196,Machine Learning Researcher,127789,CAD,159736,SE,CT,Canada,S,Canada,100,"SQL, Python, NLP, Scala",PhD,6,Healthcare,2024-10-10,2024-12-14,1217,7.2,Algorithmic Solutions +AI05197,Data Engineer,186154,CHF,167539,SE,FT,Switzerland,S,Switzerland,100,"Statistics, Kubernetes, Linux",Bachelor,9,Energy,2025-01-08,2025-02-23,1306,7.4,Smart Analytics +AI05198,Research Scientist,202606,USD,202606,EX,CT,United States,L,United States,50,"Mathematics, TensorFlow, Linux, Docker, R",Master,17,Education,2024-10-15,2024-11-25,898,5.2,Machine Intelligence Group +AI05199,Data Engineer,80486,USD,80486,EX,FL,China,L,China,0,"Python, AWS, GCP, Java",Bachelor,13,Automotive,2024-08-24,2024-10-26,2297,8.4,Cloud AI Solutions +AI05200,Principal Data Scientist,23519,USD,23519,EN,FT,India,S,India,0,"Computer Vision, MLOps, Statistics",Bachelor,0,Real Estate,2024-04-23,2024-06-08,1217,7.9,DeepTech Ventures +AI05201,Head of AI,54022,CAD,67528,EN,CT,Canada,S,Colombia,50,"Spark, Tableau, Deep Learning, Python",Associate,0,Finance,2024-08-25,2024-10-09,1620,5.2,Future Systems +AI05202,Deep Learning Engineer,94661,USD,94661,MI,CT,South Korea,L,South Korea,0,"Spark, Python, Java, Linux",Bachelor,3,Transportation,2024-09-26,2024-10-30,1281,8.3,TechCorp Inc +AI05203,AI Architect,92817,JPY,10209870,EN,FL,Japan,L,Finland,50,"Scala, Git, GCP, Hadoop",Associate,0,Education,2024-01-19,2024-03-08,2205,8.7,Algorithmic Solutions +AI05204,AI Product Manager,183387,SGD,238403,EX,FL,Singapore,S,Singapore,50,"NLP, Tableau, Spark",Associate,14,Transportation,2024-04-28,2024-05-30,1925,5.2,Future Systems +AI05205,Research Scientist,39823,USD,39823,MI,FT,China,S,China,0,"R, Python, Kubernetes, GCP",Bachelor,3,Energy,2024-02-22,2024-04-06,1780,6.6,Quantum Computing Inc +AI05206,Principal Data Scientist,204455,USD,204455,EX,CT,Denmark,S,Denmark,50,"Java, Python, Data Visualization, Kubernetes",Associate,16,Gaming,2025-03-04,2025-03-29,1148,5.5,Autonomous Tech +AI05207,ML Ops Engineer,61232,USD,61232,SE,PT,China,L,Australia,100,"Spark, Azure, Computer Vision",Master,8,Education,2024-09-20,2024-11-17,544,7.3,Autonomous Tech +AI05208,Research Scientist,112367,EUR,95512,SE,FT,France,M,France,100,"Hadoop, Python, Linux, NLP",Bachelor,6,Manufacturing,2024-07-02,2024-08-26,547,6.7,Cognitive Computing +AI05209,Data Analyst,73735,EUR,62675,EN,FL,Germany,L,Germany,0,"Python, PyTorch, Java, Computer Vision",Master,1,Education,2024-06-08,2024-08-04,971,8.9,Autonomous Tech +AI05210,Robotics Engineer,294725,USD,294725,EX,FL,United States,M,United States,0,"Spark, PyTorch, NLP",PhD,11,Healthcare,2024-04-20,2024-05-16,1054,7.2,Autonomous Tech +AI05211,Data Analyst,242630,USD,242630,EX,CT,Denmark,M,Denmark,0,"Kubernetes, Python, Statistics, TensorFlow, Data Visualization",Bachelor,15,Consulting,2024-12-01,2024-12-26,2423,9,Quantum Computing Inc +AI05212,Data Engineer,86849,USD,86849,SE,FT,South Korea,S,South Korea,100,"Scala, Hadoop, Kubernetes, SQL",Associate,6,Education,2024-07-05,2024-08-24,1936,6.7,Cloud AI Solutions +AI05213,AI Specialist,48264,USD,48264,SE,FL,India,M,India,0,"Python, Deep Learning, TensorFlow, Docker",Bachelor,7,Media,2024-11-20,2025-01-24,1965,7.5,AI Innovations +AI05214,ML Ops Engineer,66226,JPY,7284860,EN,PT,Japan,S,Finland,0,"Python, Kubernetes, TensorFlow",Associate,1,Retail,2024-08-17,2024-10-28,584,8.5,Neural Networks Co +AI05215,AI Software Engineer,59484,USD,59484,EX,CT,India,S,France,0,"Linux, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-01-28,2024-02-26,528,6.2,TechCorp Inc +AI05216,AI Software Engineer,75033,GBP,56275,MI,FL,United Kingdom,S,United Kingdom,50,"Git, TensorFlow, Deep Learning",PhD,4,Manufacturing,2025-01-18,2025-02-05,1597,7.4,Cognitive Computing +AI05217,Principal Data Scientist,53070,USD,53070,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Java, GCP, Git",Master,1,Retail,2024-04-02,2024-06-14,2279,5.2,Algorithmic Solutions +AI05218,Autonomous Systems Engineer,80312,USD,80312,MI,PT,Ireland,S,Ireland,0,"Statistics, TensorFlow, Deep Learning, Kubernetes, Mathematics",Master,3,Automotive,2024-03-28,2024-05-26,1395,6.1,DataVision Ltd +AI05219,AI Research Scientist,61589,USD,61589,EN,PT,Finland,S,Finland,100,"Linux, Python, Docker, Deep Learning, MLOps",PhD,0,Education,2025-01-28,2025-04-09,682,7.7,DataVision Ltd +AI05220,Machine Learning Researcher,64464,USD,64464,EN,PT,South Korea,L,South Korea,50,"Kubernetes, Scala, Data Visualization",PhD,1,Retail,2024-02-29,2024-04-22,1904,8.9,Algorithmic Solutions +AI05221,Data Engineer,155127,CHF,139614,MI,PT,Switzerland,M,Switzerland,100,"AWS, Python, MLOps, TensorFlow, PyTorch",PhD,3,Transportation,2024-02-07,2024-03-24,644,6.3,DeepTech Ventures +AI05222,Research Scientist,218691,EUR,185887,EX,CT,Germany,S,Germany,100,"Linux, Statistics, Hadoop, Spark, MLOps",PhD,12,Technology,2024-01-23,2024-03-05,795,6,Future Systems +AI05223,Robotics Engineer,204587,CHF,184128,SE,PT,Switzerland,L,Switzerland,0,"Python, Computer Vision, TensorFlow, Linux",PhD,9,Telecommunications,2024-09-30,2024-10-20,1680,6.9,AI Innovations +AI05224,Robotics Engineer,113415,EUR,96403,SE,PT,Austria,S,Austria,0,"Kubernetes, Scala, Tableau, Mathematics, AWS",PhD,9,Telecommunications,2024-01-18,2024-02-22,2041,8.4,Smart Analytics +AI05225,AI Consultant,111108,USD,111108,SE,FT,South Korea,S,South Korea,0,"Linux, GCP, Mathematics, Computer Vision, MLOps",Associate,5,Automotive,2025-03-08,2025-04-14,2348,8.4,Advanced Robotics +AI05226,AI Product Manager,162371,GBP,121778,EX,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Azure, PyTorch",Associate,13,Consulting,2024-09-01,2024-11-13,2361,9.6,Smart Analytics +AI05227,Data Engineer,78542,USD,78542,EN,PT,Sweden,M,Sweden,100,"R, MLOps, SQL",Master,0,Technology,2024-07-25,2024-08-26,1736,9.6,Autonomous Tech +AI05228,Data Analyst,111272,CHF,100145,MI,CT,Switzerland,M,Italy,0,"R, Spark, Statistics, GCP",Master,2,Finance,2024-07-01,2024-08-04,584,6.6,Machine Intelligence Group +AI05229,Machine Learning Researcher,141413,USD,141413,SE,PT,United States,M,Nigeria,50,"PyTorch, NLP, Scala, GCP, Azure",Associate,9,Government,2025-01-01,2025-03-02,2468,8.9,Autonomous Tech +AI05230,Robotics Engineer,153448,USD,153448,MI,CT,Norway,L,Norway,0,"Scala, Java, MLOps",Associate,4,Telecommunications,2024-02-02,2024-02-24,1035,5.9,Predictive Systems +AI05231,AI Consultant,126522,EUR,107544,SE,CT,Austria,L,Austria,0,"Python, AWS, Data Visualization, Docker, Computer Vision",Bachelor,9,Government,2024-06-13,2024-08-08,1749,9.2,Autonomous Tech +AI05232,Data Analyst,75216,USD,75216,MI,PT,Finland,S,India,0,"Kubernetes, SQL, Scala, GCP, TensorFlow",Bachelor,2,Government,2025-03-04,2025-04-29,979,7,TechCorp Inc +AI05233,Data Analyst,157426,JPY,17316860,EX,FT,Japan,M,Ghana,0,"Deep Learning, Azure, Spark",Bachelor,19,Education,2024-05-10,2024-05-30,1193,5,TechCorp Inc +AI05234,Research Scientist,78696,USD,78696,EN,PT,United States,S,Sweden,0,"Azure, R, Git",Bachelor,1,Government,2024-10-04,2024-12-15,898,6.6,Digital Transformation LLC +AI05235,Robotics Engineer,113402,USD,113402,EX,CT,China,M,China,0,"SQL, Python, Git",Associate,18,Gaming,2025-03-27,2025-05-27,2353,6.1,Machine Intelligence Group +AI05236,Machine Learning Researcher,86790,CHF,78111,EN,CT,Switzerland,M,Switzerland,100,"Python, NLP, TensorFlow",Master,1,Real Estate,2024-11-12,2025-01-18,1071,9.3,DeepTech Ventures +AI05237,Machine Learning Researcher,85140,USD,85140,EN,PT,United States,S,Spain,100,"Git, Spark, Java, SQL, GCP",PhD,0,Education,2025-03-29,2025-05-18,2413,9.7,DataVision Ltd +AI05238,Robotics Engineer,80679,EUR,68577,EN,FT,Austria,L,Austria,100,"R, Git, Tableau",Bachelor,1,Telecommunications,2024-06-23,2024-08-14,1374,8.3,Cloud AI Solutions +AI05239,AI Specialist,207222,USD,207222,EX,CT,Ireland,S,Ireland,100,"Spark, GCP, Data Visualization, Kubernetes, Python",PhD,19,Finance,2024-09-07,2024-10-19,1846,5.3,Autonomous Tech +AI05240,Principal Data Scientist,121677,SGD,158180,MI,PT,Singapore,L,Singapore,50,"Python, R, SQL, Linux",Bachelor,3,Education,2024-03-18,2024-05-23,1099,8.9,Cloud AI Solutions +AI05241,AI Research Scientist,190049,USD,190049,EX,PT,Sweden,M,Sweden,100,"Statistics, Mathematics, Tableau",Master,18,Finance,2025-01-29,2025-03-21,1642,8.9,AI Innovations +AI05242,Data Engineer,77584,USD,77584,EN,PT,Norway,S,Malaysia,100,"Python, AWS, MLOps",Master,0,Government,2024-02-08,2024-04-04,2356,6.9,Future Systems +AI05243,AI Software Engineer,120788,USD,120788,EX,FT,Finland,S,Finland,50,"AWS, TensorFlow, Linux",Master,16,Consulting,2024-02-28,2024-05-05,1853,9.4,Autonomous Tech +AI05244,Deep Learning Engineer,46291,USD,46291,SE,CT,India,S,India,0,"Linux, Deep Learning, R",Bachelor,8,Telecommunications,2025-01-17,2025-03-07,1918,9.6,Quantum Computing Inc +AI05245,Computer Vision Engineer,74298,USD,74298,EN,PT,Israel,L,Israel,100,"Python, Computer Vision, TensorFlow, Linux, Statistics",Associate,0,Energy,2024-05-31,2024-07-12,2312,9.2,Cloud AI Solutions +AI05246,Machine Learning Researcher,166410,USD,166410,SE,FL,Denmark,S,Denmark,100,"Computer Vision, GCP, Scala, Statistics",Associate,7,Finance,2025-01-07,2025-03-06,1366,5.5,DeepTech Ventures +AI05247,Data Analyst,30796,USD,30796,EN,FL,China,S,China,0,"PyTorch, Hadoop, TensorFlow, Docker",PhD,0,Manufacturing,2024-09-30,2024-11-23,1747,5.9,Advanced Robotics +AI05248,Machine Learning Researcher,60780,USD,60780,EN,FT,Sweden,S,Sweden,0,"Azure, Tableau, Mathematics, Data Visualization, Python",PhD,1,Real Estate,2024-01-30,2024-03-11,546,7,AI Innovations +AI05249,Data Engineer,59678,USD,59678,EN,CT,South Korea,L,South Korea,0,"Azure, Kubernetes, Spark, Scala",Master,1,Retail,2024-02-03,2024-03-05,644,7.9,Neural Networks Co +AI05250,Principal Data Scientist,253960,USD,253960,EX,PT,Sweden,L,Sweden,100,"Linux, Git, R, SQL",Master,17,Healthcare,2024-10-24,2024-11-30,1172,6.9,DeepTech Ventures +AI05251,AI Specialist,87660,USD,87660,EN,CT,Sweden,L,Sweden,0,"Hadoop, TensorFlow, PyTorch, GCP, Linux",PhD,1,Energy,2024-07-05,2024-08-07,2016,5.3,DeepTech Ventures +AI05252,AI Architect,210655,USD,210655,EX,CT,Sweden,S,Sweden,50,"SQL, Spark, Tableau, AWS, Git",PhD,13,Automotive,2024-11-17,2025-01-18,1041,7.2,Neural Networks Co +AI05253,Principal Data Scientist,144360,USD,144360,SE,FL,Sweden,M,Sweden,50,"Kubernetes, Docker, Java",Master,9,Manufacturing,2024-04-18,2024-05-03,562,6.9,TechCorp Inc +AI05254,Computer Vision Engineer,57145,USD,57145,EN,FL,Israel,M,Austria,50,"Linux, R, SQL, PyTorch, Java",Associate,0,Retail,2024-02-29,2024-03-31,516,8,Cognitive Computing +AI05255,Computer Vision Engineer,196565,USD,196565,EX,FL,Denmark,S,Denmark,0,"Deep Learning, PyTorch, Linux",Associate,18,Government,2024-07-19,2024-09-08,1595,8.9,Cloud AI Solutions +AI05256,Computer Vision Engineer,78696,CHF,70826,EN,FL,Switzerland,S,Kenya,50,"Spark, Azure, Java, TensorFlow, Kubernetes",Bachelor,0,Real Estate,2024-04-13,2024-06-14,842,8.2,Quantum Computing Inc +AI05257,Autonomous Systems Engineer,69517,USD,69517,SE,PT,China,M,Thailand,50,"AWS, R, Tableau, Deep Learning",Bachelor,8,Healthcare,2025-03-26,2025-05-01,1621,9.5,Cognitive Computing +AI05258,Autonomous Systems Engineer,80960,USD,80960,MI,PT,Israel,S,Israel,50,"Kubernetes, Docker, Tableau, Java, NLP",Master,3,Healthcare,2024-12-31,2025-02-18,1893,9.3,Digital Transformation LLC +AI05259,Data Engineer,111422,EUR,94709,MI,CT,Germany,L,Germany,100,"Kubernetes, Docker, Java, R",PhD,2,Manufacturing,2024-06-15,2024-08-19,1824,5.3,DeepTech Ventures +AI05260,Robotics Engineer,112063,USD,112063,SE,CT,Israel,L,Israel,0,"Git, R, Computer Vision",Bachelor,9,Energy,2025-04-19,2025-06-13,1840,8.6,Machine Intelligence Group +AI05261,AI Architect,206889,USD,206889,EX,PT,United States,S,United States,100,"Scala, GCP, NLP, Python, Kubernetes",Bachelor,10,Telecommunications,2024-06-11,2024-08-11,979,6.2,Neural Networks Co +AI05262,Autonomous Systems Engineer,58383,EUR,49626,EN,CT,Austria,L,Austria,100,"Python, TensorFlow, Tableau, Data Visualization",Bachelor,0,Manufacturing,2024-05-11,2024-07-23,879,9.4,Machine Intelligence Group +AI05263,AI Consultant,176960,USD,176960,SE,CT,Denmark,S,Denmark,0,"Scala, Hadoop, SQL, Kubernetes, Azure",Master,7,Manufacturing,2024-06-14,2024-07-12,1584,5.3,Digital Transformation LLC +AI05264,Research Scientist,68995,EUR,58646,MI,FL,Austria,M,Netherlands,100,"R, Linux, Scala, SQL",Associate,4,Consulting,2025-04-24,2025-07-04,2408,9.5,AI Innovations +AI05265,ML Ops Engineer,130169,CAD,162711,SE,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Deep Learning",PhD,9,Transportation,2024-06-02,2024-08-02,747,8,DataVision Ltd +AI05266,Data Engineer,51950,USD,51950,SE,CT,China,S,China,0,"Java, Git, Kubernetes, Python",Bachelor,9,Government,2024-12-18,2025-02-26,1106,7.8,DataVision Ltd +AI05267,AI Software Engineer,95065,USD,95065,MI,FL,Norway,S,Norway,100,"Linux, Kubernetes, Scala, GCP, Statistics",Bachelor,2,Automotive,2024-02-12,2024-03-04,967,9.6,Quantum Computing Inc +AI05268,AI Product Manager,78158,USD,78158,EN,PT,Ireland,M,Ireland,50,"R, SQL, Scala, PyTorch",Associate,1,Education,2024-06-11,2024-07-27,571,8.1,Advanced Robotics +AI05269,AI Architect,156925,EUR,133386,EX,PT,Germany,L,Switzerland,0,"Git, Hadoop, SQL, Linux, Azure",Associate,14,Retail,2024-10-13,2024-12-17,1184,6.8,Machine Intelligence Group +AI05270,Machine Learning Engineer,57461,USD,57461,SE,PT,China,S,China,100,"Data Visualization, SQL, Tableau, Java, GCP",Bachelor,6,Real Estate,2024-05-15,2024-06-29,1779,5.4,Quantum Computing Inc +AI05271,AI Architect,178905,CHF,161015,MI,CT,Switzerland,L,Switzerland,100,"Java, Azure, SQL",Master,4,Telecommunications,2024-06-24,2024-08-11,1733,5.8,Cloud AI Solutions +AI05272,Deep Learning Engineer,72036,EUR,61231,MI,PT,France,M,France,50,"R, Scala, Java, Docker, Kubernetes",PhD,4,Government,2024-03-17,2024-04-28,2121,5.1,Cognitive Computing +AI05273,AI Software Engineer,28532,USD,28532,EN,CT,China,S,China,50,"Spark, Data Visualization, SQL",PhD,1,Energy,2025-01-14,2025-02-04,551,6.3,Smart Analytics +AI05274,Research Scientist,102165,USD,102165,MI,FL,Ireland,M,Australia,50,"SQL, Docker, Data Visualization, GCP",PhD,2,Consulting,2024-04-26,2024-07-03,907,6.1,Future Systems +AI05275,AI Specialist,54248,USD,54248,EN,FT,Sweden,M,Sweden,100,"SQL, Scala, Docker, Kubernetes, Computer Vision",PhD,0,Finance,2025-04-27,2025-06-05,1496,7.7,Cognitive Computing +AI05276,AI Architect,133384,USD,133384,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Scala, TensorFlow, Linux, Deep Learning",Associate,8,Automotive,2025-02-16,2025-03-08,1747,5.8,Digital Transformation LLC +AI05277,Head of AI,166944,JPY,18363840,SE,CT,Japan,L,Japan,0,"SQL, Git, Mathematics",PhD,9,Transportation,2024-12-14,2025-02-25,594,5.2,TechCorp Inc +AI05278,Data Engineer,72269,USD,72269,EN,PT,South Korea,L,Mexico,50,"GCP, Spark, Linux, Computer Vision",Bachelor,1,Technology,2024-05-14,2024-07-03,1113,6,Cloud AI Solutions +AI05279,AI Specialist,39537,USD,39537,SE,FT,India,M,Nigeria,50,"Git, AWS, MLOps, Data Visualization",Associate,5,Manufacturing,2024-07-12,2024-08-07,1801,9.6,Autonomous Tech +AI05280,AI Specialist,206054,USD,206054,EX,FT,Ireland,S,Nigeria,50,"Azure, Hadoop, TensorFlow",Bachelor,12,Manufacturing,2024-03-03,2024-03-19,1141,8.2,Cognitive Computing +AI05281,Autonomous Systems Engineer,94121,CAD,117651,SE,FL,Canada,S,Belgium,50,"Deep Learning, Docker, Scala, Tableau, TensorFlow",Associate,7,Transportation,2025-02-10,2025-02-24,2387,7.9,Advanced Robotics +AI05282,Deep Learning Engineer,110533,AUD,149220,SE,PT,Australia,M,Italy,0,"Linux, TensorFlow, Python",Master,7,Government,2025-01-13,2025-03-20,1907,7.1,Machine Intelligence Group +AI05283,Data Scientist,106010,CHF,95409,MI,CT,Switzerland,M,Switzerland,100,"PyTorch, Statistics, SQL, Deep Learning",PhD,3,Automotive,2024-11-22,2024-12-22,1805,8.2,Autonomous Tech +AI05284,AI Software Engineer,213187,EUR,181209,EX,CT,France,L,France,100,"Linux, Spark, MLOps",PhD,18,Real Estate,2025-01-29,2025-04-02,1803,7.3,Cognitive Computing +AI05285,Research Scientist,103681,USD,103681,EX,PT,China,L,China,100,"PyTorch, Hadoop, Scala, GCP",Associate,17,Gaming,2024-08-03,2024-09-04,2335,7.7,Cognitive Computing +AI05286,Deep Learning Engineer,350954,CHF,315859,EX,FT,Switzerland,L,Switzerland,50,"R, Statistics, PyTorch",PhD,18,Education,2024-09-03,2024-09-25,1159,5.3,Neural Networks Co +AI05287,Robotics Engineer,166456,USD,166456,SE,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Data Visualization, SQL, Statistics",Master,6,Government,2025-04-20,2025-05-26,747,8.1,TechCorp Inc +AI05288,Machine Learning Researcher,127694,USD,127694,SE,FT,Israel,M,Israel,100,"Java, Deep Learning, Statistics",Associate,5,Education,2024-07-27,2024-09-01,1919,9.3,TechCorp Inc +AI05289,AI Architect,44798,USD,44798,SE,CT,India,M,Norway,50,"PyTorch, Azure, Tableau, Spark",Bachelor,5,Technology,2025-01-25,2025-04-08,1375,9.5,Quantum Computing Inc +AI05290,Machine Learning Engineer,97713,USD,97713,MI,FL,Sweden,L,Germany,100,"R, Python, Deep Learning, Computer Vision, Mathematics",Bachelor,2,Gaming,2024-04-15,2024-06-18,2136,8.7,Future Systems +AI05291,AI Research Scientist,104377,EUR,88720,MI,CT,Netherlands,S,Vietnam,50,"Python, Data Visualization, TensorFlow",Master,3,Media,2024-10-28,2024-12-08,1813,6.8,Cloud AI Solutions +AI05292,AI Architect,50775,CAD,63469,EN,FL,Canada,S,Canada,50,"Mathematics, PyTorch, GCP",Master,1,Transportation,2025-04-03,2025-05-06,1795,6.7,Quantum Computing Inc +AI05293,NLP Engineer,212513,USD,212513,EX,FL,South Korea,L,India,50,"Python, AWS, Tableau",Associate,10,Technology,2024-06-28,2024-08-27,2002,7.1,DataVision Ltd +AI05294,Robotics Engineer,33907,USD,33907,MI,PT,India,S,Colombia,100,"MLOps, R, Docker",Bachelor,2,Education,2024-10-13,2024-12-02,1146,8.3,Future Systems +AI05295,AI Specialist,130049,AUD,175566,SE,FT,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch, AWS",Master,6,Consulting,2024-05-28,2024-07-26,1484,8,TechCorp Inc +AI05296,Research Scientist,214956,USD,214956,EX,FT,Norway,S,Thailand,50,"AWS, PyTorch, GCP, Statistics",Master,13,Energy,2025-01-05,2025-01-26,1776,9.6,Smart Analytics +AI05297,Data Scientist,131854,USD,131854,SE,CT,United States,M,United States,100,"Data Visualization, MLOps, Tableau, PyTorch",Associate,9,Manufacturing,2025-01-27,2025-04-02,533,9.5,DataVision Ltd +AI05298,Computer Vision Engineer,71723,JPY,7889530,EN,FT,Japan,L,Japan,100,"Computer Vision, NLP, Spark, GCP",Master,0,Technology,2024-09-02,2024-09-19,666,5.5,Digital Transformation LLC +AI05299,Principal Data Scientist,96917,USD,96917,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Git, Hadoop, PyTorch",Master,8,Transportation,2024-12-18,2025-01-28,1627,5.8,DataVision Ltd +AI05300,AI Product Manager,74302,USD,74302,MI,PT,South Korea,L,South Korea,100,"R, Python, Git",PhD,3,Finance,2025-04-24,2025-05-25,752,8.7,Machine Intelligence Group +AI05301,Computer Vision Engineer,284665,USD,284665,EX,CT,Denmark,M,France,50,"Data Visualization, Java, Scala, MLOps",Bachelor,14,Automotive,2024-06-22,2024-07-09,2464,7.9,Neural Networks Co +AI05302,AI Architect,83787,EUR,71219,MI,PT,France,S,France,0,"SQL, R, AWS, Deep Learning, Hadoop",PhD,3,Healthcare,2024-10-12,2024-11-17,2212,8,Future Systems +AI05303,Machine Learning Engineer,85475,GBP,64106,MI,CT,United Kingdom,M,Mexico,100,"Tableau, GCP, NLP, Spark, Java",PhD,2,Healthcare,2024-05-12,2024-07-13,536,8.5,DataVision Ltd +AI05304,Principal Data Scientist,173819,EUR,147746,EX,PT,Austria,S,Austria,100,"Kubernetes, Statistics, PyTorch, GCP, Linux",Master,14,Education,2024-12-08,2025-02-19,2412,9,Quantum Computing Inc +AI05305,Data Scientist,94067,EUR,79957,MI,PT,Germany,M,Germany,50,"NLP, R, Tableau, Docker, AWS",PhD,4,Healthcare,2025-02-13,2025-03-10,1782,6.6,Cognitive Computing +AI05306,AI Consultant,301786,JPY,33196460,EX,FL,Japan,L,Japan,0,"Deep Learning, Git, Scala, Python",PhD,11,Retail,2025-04-03,2025-04-18,902,9.6,Neural Networks Co +AI05307,AI Research Scientist,86235,EUR,73300,EN,CT,Netherlands,L,Netherlands,100,"SQL, Kubernetes, PyTorch",Associate,1,Retail,2024-02-15,2024-03-04,1324,8.2,DeepTech Ventures +AI05308,Head of AI,165965,USD,165965,EX,FT,Israel,S,Israel,0,"TensorFlow, Azure, Linux",Associate,12,Government,2024-03-01,2024-04-19,1525,5.6,Smart Analytics +AI05309,Machine Learning Engineer,85823,USD,85823,EN,CT,Denmark,M,Denmark,100,"PyTorch, Azure, Data Visualization",Associate,1,Education,2024-07-30,2024-10-08,1458,6.7,Smart Analytics +AI05310,AI Software Engineer,85037,USD,85037,EX,FL,China,L,China,0,"Mathematics, Hadoop, Data Visualization",Bachelor,16,Retail,2024-12-03,2025-01-16,1818,7.9,AI Innovations +AI05311,AI Research Scientist,61149,USD,61149,MI,PT,South Korea,M,Germany,0,"SQL, Kubernetes, PyTorch",Bachelor,2,Media,2024-03-25,2024-06-05,1921,9.4,Advanced Robotics +AI05312,AI Specialist,92493,CAD,115616,MI,CT,Canada,L,Canada,50,"Linux, PyTorch, Git",PhD,3,Consulting,2024-08-13,2024-09-12,1208,7.6,AI Innovations +AI05313,Principal Data Scientist,114033,JPY,12543630,MI,FT,Japan,L,Japan,100,"Tableau, R, MLOps",PhD,4,Automotive,2025-01-24,2025-03-31,1016,7.8,Predictive Systems +AI05314,NLP Engineer,53893,EUR,45809,EN,CT,Germany,S,United Kingdom,0,"Python, Spark, Hadoop",Bachelor,1,Gaming,2024-02-20,2024-03-07,2172,7.6,Machine Intelligence Group +AI05315,ML Ops Engineer,84318,USD,84318,EN,PT,Finland,L,Romania,100,"TensorFlow, Computer Vision, Tableau",PhD,1,Automotive,2024-11-02,2024-12-09,785,7.4,TechCorp Inc +AI05316,Deep Learning Engineer,102359,CAD,127949,SE,CT,Canada,S,Canada,50,"GCP, R, Git, Kubernetes",Bachelor,9,Education,2025-04-24,2025-05-27,1201,7.1,Quantum Computing Inc +AI05317,Data Analyst,37425,USD,37425,EN,CT,China,M,China,100,"SQL, R, Tableau, Azure, PyTorch",Master,1,Manufacturing,2024-04-03,2024-06-08,1464,9.5,Advanced Robotics +AI05318,AI Specialist,78231,USD,78231,EN,CT,Denmark,M,Thailand,100,"Deep Learning, GCP, Python, Data Visualization, Docker",Bachelor,0,Manufacturing,2024-06-01,2024-07-06,2337,5.8,Algorithmic Solutions +AI05319,Machine Learning Engineer,62558,EUR,53174,EN,CT,Netherlands,M,Norway,50,"R, SQL, AWS, MLOps, Docker",Master,1,Transportation,2025-03-30,2025-04-20,2055,7.8,Future Systems +AI05320,Deep Learning Engineer,123579,CAD,154474,SE,FL,Canada,L,Canada,0,"Hadoop, Tableau, GCP, Deep Learning",PhD,5,Technology,2024-10-24,2024-12-15,785,9.3,TechCorp Inc +AI05321,Deep Learning Engineer,83741,CAD,104676,MI,FL,Canada,M,Canada,100,"NLP, Docker, Git",Master,3,Automotive,2025-03-04,2025-05-06,2180,5.3,Quantum Computing Inc +AI05322,Principal Data Scientist,103613,USD,103613,SE,PT,Sweden,S,Spain,50,"Linux, TensorFlow, Hadoop, Computer Vision, Tableau",PhD,7,Automotive,2024-01-10,2024-02-11,1225,10,Algorithmic Solutions +AI05323,Deep Learning Engineer,122345,USD,122345,SE,FT,Israel,S,Israel,0,"SQL, Python, TensorFlow, Git, PyTorch",Associate,9,Manufacturing,2024-02-20,2024-04-15,563,8.7,Autonomous Tech +AI05324,AI Software Engineer,125817,CHF,113235,EN,FT,Switzerland,L,Singapore,0,"Tableau, Scala, Python",Associate,0,Finance,2024-06-25,2024-07-12,2037,6.9,Neural Networks Co +AI05325,AI Research Scientist,83848,USD,83848,MI,CT,Sweden,S,Nigeria,50,"Python, Git, TensorFlow, Deep Learning",Bachelor,2,Media,2024-04-21,2024-07-01,1561,8.1,Predictive Systems +AI05326,Data Analyst,126646,EUR,107649,SE,FT,Netherlands,L,Netherlands,100,"Hadoop, Spark, Linux",Associate,5,Manufacturing,2024-03-20,2024-04-09,2308,7.6,DataVision Ltd +AI05327,AI Product Manager,216544,USD,216544,EX,FT,United States,M,United States,100,"Kubernetes, SQL, Azure, Linux, PyTorch",Associate,14,Transportation,2024-07-25,2024-09-23,1367,5.1,Cloud AI Solutions +AI05328,AI Research Scientist,254248,EUR,216111,EX,FL,Austria,L,Austria,50,"R, Docker, Data Visualization, MLOps, Spark",PhD,13,Automotive,2024-11-17,2025-01-29,2380,8,Machine Intelligence Group +AI05329,Deep Learning Engineer,238603,GBP,178952,EX,FT,United Kingdom,L,United Kingdom,0,"R, Hadoop, SQL, Azure, Tableau",Bachelor,16,Energy,2024-05-10,2024-05-25,1566,8.9,Cloud AI Solutions +AI05330,NLP Engineer,71862,USD,71862,EN,FT,Sweden,M,Austria,50,"SQL, PyTorch, MLOps, NLP, GCP",PhD,1,Automotive,2024-12-15,2025-01-10,2276,9.3,Autonomous Tech +AI05331,Autonomous Systems Engineer,43525,USD,43525,SE,CT,China,S,Philippines,50,"Python, SQL, R, Git, TensorFlow",Master,6,Gaming,2024-09-23,2024-10-19,2248,7.1,Smart Analytics +AI05332,Computer Vision Engineer,133643,EUR,113597,SE,FL,Austria,L,Austria,0,"Python, MLOps, Kubernetes",Associate,5,Healthcare,2025-02-05,2025-03-08,1300,7,Digital Transformation LLC +AI05333,Machine Learning Researcher,209974,SGD,272966,EX,PT,Singapore,S,Singapore,0,"Python, GCP, Scala, SQL",Master,18,Consulting,2024-10-27,2024-11-24,2148,10,Quantum Computing Inc +AI05334,AI Consultant,188802,CAD,236003,EX,FT,Canada,L,Austria,50,"Kubernetes, NLP, PyTorch, Git",Bachelor,14,Automotive,2024-02-27,2024-04-15,1309,8.3,Machine Intelligence Group +AI05335,ML Ops Engineer,109423,USD,109423,MI,FT,Norway,S,Czech Republic,0,"Java, Linux, Computer Vision",Associate,4,Telecommunications,2025-01-05,2025-01-19,1573,5.2,Digital Transformation LLC +AI05336,Data Scientist,193402,SGD,251423,EX,CT,Singapore,L,Singapore,0,"Hadoop, Python, Kubernetes",Bachelor,13,Healthcare,2024-08-27,2024-09-23,1658,8.9,TechCorp Inc +AI05337,Deep Learning Engineer,68104,EUR,57888,EN,FL,France,L,France,100,"Scala, Docker, Mathematics, Spark",PhD,0,Real Estate,2025-01-01,2025-02-23,2350,5.2,Future Systems +AI05338,AI Consultant,115997,USD,115997,MI,FT,United States,M,United States,0,"Linux, Scala, Mathematics, GCP, Deep Learning",Bachelor,4,Gaming,2024-06-27,2024-07-13,2145,8.7,DataVision Ltd +AI05339,AI Specialist,87942,USD,87942,MI,FT,South Korea,M,New Zealand,50,"R, MLOps, SQL, AWS, Scala",PhD,4,Education,2024-03-10,2024-03-27,1259,6.9,Autonomous Tech +AI05340,Machine Learning Engineer,303218,USD,303218,EX,CT,Denmark,L,Denmark,50,"R, Git, Scala",PhD,18,Government,2024-12-15,2025-02-02,1087,9.7,DataVision Ltd +AI05341,Research Scientist,63427,USD,63427,MI,CT,South Korea,S,South Korea,100,"Spark, Hadoop, R",Bachelor,2,Finance,2024-04-14,2024-05-25,952,7.2,Machine Intelligence Group +AI05342,Principal Data Scientist,148375,GBP,111281,SE,FT,United Kingdom,L,United Kingdom,0,"Mathematics, Python, Linux, Hadoop, TensorFlow",Bachelor,6,Education,2025-02-24,2025-04-29,609,7.3,Machine Intelligence Group +AI05343,Machine Learning Researcher,91410,CAD,114263,MI,FL,Canada,M,Canada,0,"GCP, Python, Spark",PhD,2,Transportation,2024-02-11,2024-04-24,1107,5.9,AI Innovations +AI05344,Data Engineer,217295,USD,217295,EX,FL,United States,L,United States,50,"TensorFlow, Java, Scala",Associate,14,Education,2024-01-27,2024-02-23,1243,9.1,Future Systems +AI05345,AI Consultant,65815,AUD,88850,EN,PT,Australia,L,Kenya,50,"Scala, AWS, Git, Computer Vision, Azure",Bachelor,0,Consulting,2025-04-07,2025-05-17,2254,5.6,TechCorp Inc +AI05346,Research Scientist,185973,SGD,241765,EX,CT,Singapore,S,Singapore,0,"NLP, Deep Learning, Git",Associate,13,Real Estate,2025-04-29,2025-06-08,940,5.5,DeepTech Ventures +AI05347,Principal Data Scientist,113175,USD,113175,SE,PT,Finland,S,Finland,100,"TensorFlow, Deep Learning, PyTorch, MLOps, Hadoop",Master,7,Government,2024-08-28,2024-10-29,722,8.4,DeepTech Ventures +AI05348,Deep Learning Engineer,198579,USD,198579,EX,FT,Denmark,S,Denmark,50,"Data Visualization, Docker, Spark, Python, Java",Master,14,Healthcare,2025-03-29,2025-06-08,1705,8.2,Smart Analytics +AI05349,Machine Learning Researcher,25817,USD,25817,EN,CT,India,M,India,0,"MLOps, Scala, Linux, Azure",Bachelor,0,Media,2025-04-08,2025-04-23,1618,7.7,DeepTech Ventures +AI05350,Head of AI,81249,USD,81249,MI,CT,Sweden,M,Ukraine,50,"Computer Vision, R, GCP",Associate,3,Manufacturing,2024-04-08,2024-06-07,1936,9.5,Autonomous Tech +AI05351,Data Analyst,107111,AUD,144600,SE,CT,Australia,S,Australia,100,"Python, Docker, Linux, Statistics, GCP",Associate,7,Finance,2024-06-22,2024-09-01,671,5,Digital Transformation LLC +AI05352,AI Software Engineer,158552,USD,158552,SE,CT,Norway,M,United Kingdom,0,"Git, Python, GCP",Bachelor,7,Technology,2024-11-25,2025-01-14,2214,7.6,TechCorp Inc +AI05353,Autonomous Systems Engineer,209929,USD,209929,EX,CT,United States,M,United States,0,"Azure, Python, Spark, GCP",PhD,14,Transportation,2024-11-24,2025-02-01,1931,5.2,DeepTech Ventures +AI05354,AI Research Scientist,288133,GBP,216100,EX,CT,United Kingdom,L,United Kingdom,0,"Scala, Data Visualization, AWS, Computer Vision",Master,13,Real Estate,2025-02-02,2025-03-05,1068,8.8,Advanced Robotics +AI05355,Head of AI,243777,JPY,26815470,EX,FT,Japan,M,Japan,50,"Mathematics, R, NLP, Linux, SQL",Bachelor,13,Gaming,2025-01-29,2025-02-24,2295,7.8,Digital Transformation LLC +AI05356,Data Engineer,54043,AUD,72958,EN,FT,Australia,M,Germany,50,"Kubernetes, Deep Learning, Git, Hadoop",Associate,0,Manufacturing,2024-02-20,2024-03-05,855,9.4,Cognitive Computing +AI05357,Data Analyst,82069,USD,82069,MI,FL,Ireland,M,Ireland,100,"MLOps, PyTorch, TensorFlow",Associate,3,Retail,2025-01-27,2025-02-28,1505,9.7,Advanced Robotics +AI05358,ML Ops Engineer,65179,USD,65179,MI,CT,Ireland,S,Ireland,50,"SQL, Hadoop, Tableau",PhD,3,Telecommunications,2024-03-09,2024-04-08,2284,5.1,Future Systems +AI05359,AI Specialist,162962,USD,162962,SE,PT,Sweden,L,Poland,0,"Spark, Scala, PyTorch, NLP, GCP",Bachelor,8,Healthcare,2025-02-14,2025-04-26,1367,5.9,Smart Analytics +AI05360,AI Specialist,91928,USD,91928,EX,FT,China,L,China,50,"PyTorch, Scala, Tableau, Linux, NLP",Master,10,Government,2025-04-12,2025-05-07,1517,6.3,DeepTech Ventures +AI05361,AI Architect,134846,USD,134846,SE,PT,United States,M,United States,100,"PyTorch, Git, MLOps, SQL, Java",Master,6,Retail,2024-08-29,2024-09-13,1153,9.9,DataVision Ltd +AI05362,Data Analyst,22186,USD,22186,EN,PT,India,L,Spain,0,"Computer Vision, TensorFlow, NLP, SQL, Mathematics",Bachelor,1,Retail,2024-04-13,2024-06-15,512,8,Quantum Computing Inc +AI05363,Research Scientist,61335,USD,61335,SE,PT,China,L,China,0,"Java, PyTorch, Statistics",Associate,9,Retail,2024-03-05,2024-03-26,733,8.9,TechCorp Inc +AI05364,AI Specialist,246778,EUR,209761,EX,FT,Germany,L,New Zealand,100,"Kubernetes, PyTorch, NLP, TensorFlow",Master,15,Gaming,2025-01-20,2025-03-28,506,5.1,Quantum Computing Inc +AI05365,AI Architect,104343,GBP,78257,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Data Visualization, Java, GCP",Master,3,Retail,2024-05-21,2024-08-01,812,7.3,Autonomous Tech +AI05366,AI Architect,130307,USD,130307,MI,PT,Denmark,L,Denmark,50,"Linux, AWS, Java",PhD,2,Telecommunications,2024-08-05,2024-10-08,1924,6.6,DeepTech Ventures +AI05367,Computer Vision Engineer,83046,USD,83046,EN,FL,Norway,S,Norway,50,"SQL, Linux, Git, PyTorch, Deep Learning",Master,0,Retail,2025-03-05,2025-05-15,2443,6.4,Digital Transformation LLC +AI05368,AI Specialist,157446,USD,157446,MI,PT,Norway,L,Norway,100,"MLOps, Python, Tableau, Kubernetes, Data Visualization",Master,3,Healthcare,2024-08-29,2024-10-25,1804,5.7,Cognitive Computing +AI05369,Machine Learning Researcher,297092,JPY,32680120,EX,FL,Japan,L,Japan,0,"Spark, GCP, Python, Mathematics",Associate,16,Finance,2024-08-07,2024-10-07,989,8.6,Future Systems +AI05370,AI Product Manager,68384,USD,68384,MI,CT,Finland,S,Finland,100,"Python, Linux, MLOps, Kubernetes, TensorFlow",Master,2,Transportation,2025-01-17,2025-03-14,1050,6.4,DataVision Ltd +AI05371,ML Ops Engineer,92089,USD,92089,EX,FL,India,L,India,50,"Docker, Hadoop, SQL, Azure, Java",PhD,17,Automotive,2024-08-13,2024-09-04,764,6,Neural Networks Co +AI05372,Deep Learning Engineer,136227,EUR,115793,SE,FT,Netherlands,L,Netherlands,0,"Statistics, Scala, Deep Learning",PhD,6,Healthcare,2024-01-01,2024-02-29,1685,9.2,Neural Networks Co +AI05373,AI Product Manager,129513,USD,129513,SE,PT,Ireland,M,Australia,100,"Python, Docker, Mathematics",PhD,7,Government,2024-10-18,2024-11-29,1009,7.8,Cloud AI Solutions +AI05374,AI Specialist,135626,USD,135626,SE,PT,Israel,M,Vietnam,50,"Scala, Hadoop, Computer Vision, Deep Learning",PhD,7,Manufacturing,2025-03-27,2025-06-08,1852,8,Advanced Robotics +AI05375,AI Specialist,43215,USD,43215,SE,FL,China,S,Hungary,50,"PyTorch, Python, Linux",Master,9,Energy,2024-08-16,2024-10-05,714,8.1,Smart Analytics +AI05376,AI Research Scientist,70887,EUR,60254,MI,FT,Germany,S,Germany,50,"Python, Java, AWS, Scala, SQL",Associate,4,Retail,2025-02-15,2025-04-17,610,5.4,Smart Analytics +AI05377,ML Ops Engineer,288695,CHF,259826,EX,PT,Switzerland,L,Switzerland,0,"Spark, Linux, Statistics, Mathematics",Master,16,Transportation,2024-03-12,2024-05-19,1570,6,TechCorp Inc +AI05378,Data Engineer,85081,CHF,76573,EN,FT,Switzerland,S,Nigeria,50,"Java, PyTorch, AWS",PhD,1,Energy,2025-03-16,2025-05-10,1736,5.3,Advanced Robotics +AI05379,NLP Engineer,111446,USD,111446,MI,CT,Israel,L,Israel,100,"Spark, MLOps, Scala, AWS",Master,4,Energy,2024-06-17,2024-07-13,513,7.5,Predictive Systems +AI05380,Data Analyst,66898,USD,66898,MI,CT,Israel,S,Israel,50,"Git, Spark, R, PyTorch",Master,3,Gaming,2024-12-01,2025-01-02,1269,6.9,Predictive Systems +AI05381,AI Product Manager,37660,USD,37660,EN,FL,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-07-28,2024-09-17,835,8.5,Neural Networks Co +AI05382,Autonomous Systems Engineer,79062,EUR,67203,EN,PT,Netherlands,L,Finland,50,"NLP, SQL, TensorFlow, Scala, PyTorch",Master,0,Healthcare,2024-07-06,2024-08-07,2128,9.7,Predictive Systems +AI05383,Deep Learning Engineer,125125,SGD,162663,MI,PT,Singapore,L,Singapore,0,"Java, Git, Tableau, Scala",PhD,4,Healthcare,2024-03-03,2024-04-17,1935,6,Advanced Robotics +AI05384,Research Scientist,137554,JPY,15130940,SE,FT,Japan,M,Japan,0,"Data Visualization, Kubernetes, Computer Vision",Bachelor,8,Transportation,2024-09-23,2024-11-04,812,6.2,DeepTech Ventures +AI05385,AI Specialist,95923,EUR,81535,MI,FT,France,M,France,0,"NLP, Git, Mathematics",Associate,2,Transportation,2024-11-03,2024-11-21,667,9.2,DeepTech Ventures +AI05386,Autonomous Systems Engineer,126145,GBP,94609,SE,PT,United Kingdom,L,United Kingdom,50,"Git, Mathematics, NLP",PhD,7,Media,2024-01-15,2024-02-29,1112,6.3,Machine Intelligence Group +AI05387,Principal Data Scientist,98692,USD,98692,SE,PT,Ireland,S,Ireland,0,"Deep Learning, Scala, Computer Vision",Bachelor,5,Gaming,2025-02-02,2025-04-09,1354,6.7,Algorithmic Solutions +AI05388,Head of AI,200999,EUR,170849,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Computer Vision, PyTorch, Git",Master,16,Consulting,2025-03-29,2025-04-29,1230,6.6,Future Systems +AI05389,Head of AI,54737,GBP,41053,EN,CT,United Kingdom,M,South Africa,50,"Python, Kubernetes, Scala",Associate,1,Telecommunications,2024-12-10,2025-01-01,2060,9.6,Quantum Computing Inc +AI05390,Machine Learning Engineer,202067,SGD,262687,EX,FT,Singapore,M,Brazil,100,"R, Scala, Python",Associate,18,Technology,2024-09-02,2024-09-17,2350,7.9,Neural Networks Co +AI05391,AI Research Scientist,247645,CAD,309556,EX,PT,Canada,L,Canada,100,"R, Mathematics, Python, Statistics",Associate,12,Gaming,2024-06-08,2024-07-02,935,8,Future Systems +AI05392,Data Engineer,136820,GBP,102615,SE,PT,United Kingdom,L,United Kingdom,100,"TensorFlow, Tableau, Computer Vision, Scala",Master,9,Real Estate,2025-03-27,2025-05-27,1477,6.5,Machine Intelligence Group +AI05393,Robotics Engineer,118345,USD,118345,EX,PT,Israel,S,Israel,0,"MLOps, Data Visualization, Linux, Docker, GCP",Associate,15,Media,2024-02-13,2024-04-18,1177,9.5,Neural Networks Co +AI05394,Computer Vision Engineer,86939,JPY,9563290,EN,CT,Japan,L,Japan,100,"Kubernetes, R, Hadoop, SQL, Deep Learning",PhD,1,Automotive,2024-08-14,2024-09-28,1232,7.2,Digital Transformation LLC +AI05395,Research Scientist,85462,JPY,9400820,EN,PT,Japan,M,Japan,100,"Kubernetes, Docker, NLP, Statistics, GCP",Associate,0,Government,2025-02-25,2025-04-11,1813,6.4,Algorithmic Solutions +AI05396,AI Research Scientist,75148,CHF,67633,EN,FL,Switzerland,M,Colombia,0,"NLP, Java, Kubernetes, Git",Master,1,Gaming,2025-01-14,2025-02-08,1792,10,Machine Intelligence Group +AI05397,Principal Data Scientist,253163,USD,253163,EX,FL,Denmark,L,Denmark,50,"TensorFlow, Git, Data Visualization",PhD,19,Real Estate,2024-06-06,2024-08-16,1330,5.2,TechCorp Inc +AI05398,AI Architect,30114,USD,30114,EN,FL,China,L,Finland,100,"Statistics, PyTorch, Java, Azure, TensorFlow",Master,1,Telecommunications,2024-11-16,2025-01-19,2090,8,Smart Analytics +AI05399,Computer Vision Engineer,176415,USD,176415,EX,CT,Finland,M,Finland,0,"GCP, NLP, Deep Learning, Spark",PhD,12,Telecommunications,2025-02-20,2025-04-21,1544,8.9,TechCorp Inc +AI05400,AI Specialist,73489,EUR,62466,MI,FT,Germany,M,Germany,50,"SQL, Java, Spark, TensorFlow, R",Associate,4,Automotive,2024-06-02,2024-07-03,2185,8.2,TechCorp Inc +AI05401,ML Ops Engineer,115294,USD,115294,SE,FT,Finland,M,Canada,100,"Azure, MLOps, Scala",Master,7,Real Estate,2024-03-21,2024-04-21,1538,7.8,Neural Networks Co +AI05402,Data Engineer,74479,SGD,96823,EN,FL,Singapore,L,Singapore,100,"SQL, Python, Statistics, Git",Associate,0,Gaming,2024-11-10,2024-12-01,1859,7.7,Smart Analytics +AI05403,AI Software Engineer,97495,USD,97495,SE,FT,Sweden,S,Sweden,0,"Spark, Git, Scala, Computer Vision",Associate,8,Government,2024-09-29,2024-11-25,899,6.9,DeepTech Ventures +AI05404,Principal Data Scientist,63891,USD,63891,EN,FL,Norway,S,Norway,100,"MLOps, SQL, Scala, GCP, Python",Associate,0,Manufacturing,2024-05-15,2024-06-09,1557,6.1,Smart Analytics +AI05405,Data Analyst,49339,CAD,61674,EN,PT,Canada,S,Canada,50,"Kubernetes, MLOps, Git, NLP, Scala",Master,1,Transportation,2024-05-21,2024-06-05,1652,6.6,Advanced Robotics +AI05406,Autonomous Systems Engineer,114592,USD,114592,EX,FL,China,L,Estonia,0,"Scala, NLP, Kubernetes",Master,12,Media,2024-04-14,2024-06-26,967,5.2,DataVision Ltd +AI05407,Data Scientist,44734,USD,44734,SE,FT,India,M,India,50,"NLP, MLOps, Scala, Python, Java",Master,6,Media,2024-11-01,2024-12-12,2496,7.7,Predictive Systems +AI05408,AI Architect,191311,USD,191311,EX,FL,Israel,S,Israel,50,"SQL, Kubernetes, GCP",Master,14,Consulting,2025-03-28,2025-04-21,873,8.3,Predictive Systems +AI05409,Data Engineer,198417,USD,198417,EX,FT,Finland,L,Switzerland,0,"Statistics, Kubernetes, Spark, R",Bachelor,16,Consulting,2024-05-20,2024-07-21,2466,9,Quantum Computing Inc +AI05410,AI Specialist,104925,JPY,11541750,SE,PT,Japan,S,Nigeria,0,"Git, MLOps, Scala, Python",Master,6,Media,2024-04-10,2024-05-05,2391,7.8,Neural Networks Co +AI05411,Research Scientist,221209,EUR,188028,EX,FT,Austria,L,Austria,0,"PyTorch, Data Visualization, MLOps",Bachelor,12,Technology,2024-02-28,2024-04-13,1267,8.2,TechCorp Inc +AI05412,NLP Engineer,85694,EUR,72840,MI,FT,Austria,S,Austria,0,"PyTorch, TensorFlow, MLOps, Hadoop, Python",PhD,3,Technology,2025-02-15,2025-04-14,1832,8.5,Neural Networks Co +AI05413,Research Scientist,148534,USD,148534,SE,FT,United States,S,United States,0,"R, Scala, SQL, Azure",PhD,9,Energy,2024-11-06,2025-01-16,1625,5.3,Neural Networks Co +AI05414,Machine Learning Engineer,79799,USD,79799,MI,FT,Israel,L,Israel,0,"Mathematics, AWS, NLP, PyTorch",Master,2,Manufacturing,2024-02-27,2024-04-09,1588,5.1,DataVision Ltd +AI05415,Robotics Engineer,42345,USD,42345,MI,PT,China,S,China,100,"Python, TensorFlow, Deep Learning, Tableau, Azure",Associate,4,Media,2024-06-02,2024-07-11,1265,9.9,Quantum Computing Inc +AI05416,Deep Learning Engineer,120846,CHF,108761,MI,CT,Switzerland,L,Egypt,50,"PyTorch, Java, TensorFlow, Docker",Master,3,Telecommunications,2024-06-09,2024-08-03,1725,6,Algorithmic Solutions +AI05417,AI Specialist,23612,USD,23612,EN,FL,India,S,Thailand,50,"SQL, Kubernetes, Tableau, Git",Associate,1,Gaming,2024-08-18,2024-09-06,2269,8,Autonomous Tech +AI05418,Deep Learning Engineer,166613,GBP,124960,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, Tableau, PyTorch, Data Visualization",Master,12,Technology,2024-06-03,2024-06-28,1513,9.9,Machine Intelligence Group +AI05419,Principal Data Scientist,56615,AUD,76430,EN,CT,Australia,M,Australia,100,"Spark, Statistics, Computer Vision, Python, MLOps",PhD,0,Telecommunications,2025-04-20,2025-06-26,1809,5.8,Algorithmic Solutions +AI05420,AI Specialist,78519,AUD,106001,MI,FT,Australia,M,Australia,100,"TensorFlow, Kubernetes, Computer Vision, Docker",PhD,4,Consulting,2024-04-30,2024-06-08,1672,6,DeepTech Ventures +AI05421,Data Engineer,176102,CAD,220128,EX,FT,Canada,S,Canada,50,"Kubernetes, Docker, AWS",PhD,11,Media,2025-01-11,2025-03-05,2408,9.4,Cognitive Computing +AI05422,AI Product Manager,39202,USD,39202,MI,CT,China,L,China,100,"NLP, Docker, Azure, Hadoop",Bachelor,3,Gaming,2024-09-17,2024-10-20,2380,9.3,Machine Intelligence Group +AI05423,Machine Learning Engineer,52424,USD,52424,EN,CT,Finland,S,Finland,100,"R, Kubernetes, Java, SQL, Docker",Associate,1,Energy,2025-03-03,2025-04-26,1801,6.4,Smart Analytics +AI05424,AI Research Scientist,74687,SGD,97093,EN,PT,Singapore,S,United States,0,"AWS, Tableau, Docker, Computer Vision",PhD,1,Consulting,2025-03-08,2025-04-02,2295,8,Algorithmic Solutions +AI05425,Computer Vision Engineer,231540,CAD,289425,EX,PT,Canada,L,Canada,100,"Java, Kubernetes, Hadoop, Mathematics, Scala",Associate,12,Education,2025-03-21,2025-04-29,2222,7.1,Neural Networks Co +AI05426,Data Analyst,156641,USD,156641,SE,FT,Norway,S,China,50,"Statistics, TensorFlow, Python, GCP",PhD,6,Transportation,2024-12-20,2025-01-20,717,9.2,TechCorp Inc +AI05427,Data Engineer,119985,CAD,149981,SE,FT,Canada,M,Canada,100,"Git, Deep Learning, Hadoop, NLP, Kubernetes",Associate,9,Transportation,2024-09-07,2024-10-07,1933,9.6,Advanced Robotics +AI05428,Autonomous Systems Engineer,131450,AUD,177458,EX,FT,Australia,S,Australia,100,"Hadoop, Linux, Computer Vision, Deep Learning, Kubernetes",PhD,11,Telecommunications,2024-05-02,2024-06-20,962,8.7,Digital Transformation LLC +AI05429,Machine Learning Engineer,179649,CAD,224561,EX,CT,Canada,M,Canada,50,"Linux, Kubernetes, Data Visualization, AWS",PhD,16,Manufacturing,2024-02-14,2024-03-31,1284,6.3,DeepTech Ventures +AI05430,Deep Learning Engineer,113259,EUR,96270,SE,PT,Austria,L,Switzerland,50,"Java, TensorFlow, Azure, Computer Vision",Bachelor,9,Automotive,2024-07-16,2024-09-04,514,8,Predictive Systems +AI05431,Head of AI,90625,CAD,113281,MI,CT,Canada,M,Canada,50,"SQL, Hadoop, R, Java, Python",Bachelor,4,Consulting,2024-04-19,2024-07-01,2289,7.7,Digital Transformation LLC +AI05432,Computer Vision Engineer,115445,USD,115445,MI,FL,Ireland,L,Ireland,100,"AWS, Hadoop, Data Visualization",Bachelor,2,Gaming,2024-09-10,2024-10-03,1925,5.1,Predictive Systems +AI05433,Deep Learning Engineer,82908,EUR,70472,MI,FL,Austria,S,Austria,0,"Python, Spark, SQL, Hadoop, Mathematics",Associate,4,Transportation,2025-02-06,2025-03-17,2093,8.2,Machine Intelligence Group +AI05434,Machine Learning Engineer,104007,CHF,93606,EN,CT,Switzerland,L,India,0,"Python, Scala, Data Visualization, Hadoop, Linux",PhD,0,Finance,2024-09-04,2024-10-11,1160,5.5,Smart Analytics +AI05435,Research Scientist,90940,AUD,122769,MI,PT,Australia,M,Australia,50,"Hadoop, Python, GCP",Bachelor,3,Media,2024-01-04,2024-03-13,2095,5.1,Digital Transformation LLC +AI05436,AI Product Manager,28492,USD,28492,EN,FT,China,L,China,50,"Python, SQL, Statistics",Associate,1,Healthcare,2024-08-08,2024-09-20,2004,7.6,Future Systems +AI05437,ML Ops Engineer,84521,CHF,76069,EN,FL,Switzerland,S,Switzerland,100,"Git, AWS, Kubernetes, MLOps, Tableau",PhD,0,Media,2025-04-01,2025-06-07,740,7.9,Smart Analytics +AI05438,AI Software Engineer,125527,USD,125527,SE,PT,Finland,L,Argentina,0,"PyTorch, Kubernetes, Docker",Associate,6,Gaming,2024-01-20,2024-03-14,1985,8.9,Cognitive Computing +AI05439,Machine Learning Researcher,98155,SGD,127602,MI,FL,Singapore,S,Singapore,0,"Spark, NLP, Python, TensorFlow, Data Visualization",Associate,2,Finance,2025-03-10,2025-04-13,1473,6.1,Smart Analytics +AI05440,Computer Vision Engineer,54723,SGD,71140,EN,FT,Singapore,M,Singapore,0,"SQL, Git, Hadoop, PyTorch, AWS",Master,0,Real Estate,2024-08-14,2024-10-17,1181,6.8,Machine Intelligence Group +AI05441,AI Research Scientist,132179,GBP,99134,SE,FT,United Kingdom,L,United Kingdom,50,"Python, Linux, Deep Learning, Scala",Associate,9,Manufacturing,2025-02-05,2025-03-02,954,7.6,Smart Analytics +AI05442,Data Engineer,99414,JPY,10935540,MI,CT,Japan,S,South Africa,100,"SQL, Kubernetes, Linux, Hadoop",Associate,2,Real Estate,2025-03-25,2025-05-29,1582,6.3,Predictive Systems +AI05443,Computer Vision Engineer,162201,USD,162201,SE,PT,Israel,L,Ireland,50,"NLP, Azure, Hadoop, Python",PhD,6,Finance,2024-02-02,2024-03-30,1047,9.2,Digital Transformation LLC +AI05444,Data Engineer,61351,USD,61351,EN,PT,Israel,L,Israel,50,"AWS, GCP, MLOps, PyTorch, SQL",Master,0,Gaming,2024-09-01,2024-09-15,2430,8.2,Advanced Robotics +AI05445,Machine Learning Engineer,23989,USD,23989,EN,FL,India,S,India,100,"SQL, R, PyTorch, NLP, Computer Vision",Bachelor,1,Automotive,2024-10-13,2024-11-17,1139,9.5,DataVision Ltd +AI05446,Robotics Engineer,65446,USD,65446,MI,CT,Finland,S,Finland,50,"Python, Git, Mathematics",PhD,3,Education,2024-03-30,2024-04-19,879,6,Predictive Systems +AI05447,ML Ops Engineer,160753,USD,160753,MI,FL,Denmark,L,Denmark,100,"Tableau, Docker, Hadoop, MLOps, GCP",Bachelor,2,Telecommunications,2024-07-31,2024-09-15,1572,7.3,Cloud AI Solutions +AI05448,ML Ops Engineer,159740,AUD,215649,SE,CT,Australia,L,Australia,100,"GCP, Spark, PyTorch",Bachelor,5,Telecommunications,2024-05-29,2024-07-11,1719,5.4,Future Systems +AI05449,Research Scientist,86339,EUR,73388,EN,PT,Austria,L,Austria,100,"Data Visualization, Python, Git, TensorFlow",PhD,1,Manufacturing,2024-01-24,2024-04-03,2369,7.3,Machine Intelligence Group +AI05450,Principal Data Scientist,223810,USD,223810,EX,PT,Israel,M,New Zealand,100,"Statistics, Data Visualization, Python",Bachelor,13,Gaming,2024-08-06,2024-10-18,1937,10,Algorithmic Solutions +AI05451,Robotics Engineer,156078,EUR,132666,EX,FT,Austria,M,Austria,0,"Java, Hadoop, R, AWS",Bachelor,13,Finance,2024-08-23,2024-10-31,1683,9.4,Algorithmic Solutions +AI05452,Principal Data Scientist,95770,CHF,86193,EN,PT,Switzerland,M,Switzerland,100,"Kubernetes, Hadoop, Data Visualization",Bachelor,0,Government,2024-05-12,2024-07-06,1591,9.7,Predictive Systems +AI05453,Deep Learning Engineer,94666,JPY,10413260,EN,FT,Japan,L,Japan,50,"Mathematics, Spark, Python, TensorFlow, PyTorch",Bachelor,1,Consulting,2025-03-27,2025-05-14,2335,7.4,Digital Transformation LLC +AI05454,AI Software Engineer,74801,SGD,97241,EN,FL,Singapore,L,Philippines,50,"Git, GCP, Docker, Mathematics",Associate,0,Manufacturing,2025-02-20,2025-04-28,1151,6.9,Digital Transformation LLC +AI05455,Research Scientist,106506,EUR,90530,SE,FT,Austria,S,Austria,0,"Linux, R, Git",PhD,8,Transportation,2024-05-18,2024-07-12,734,9.2,Neural Networks Co +AI05456,Computer Vision Engineer,150029,SGD,195038,SE,FL,Singapore,L,Singapore,100,"GCP, Kubernetes, Java",Associate,7,Manufacturing,2025-01-24,2025-03-15,1856,7.4,Autonomous Tech +AI05457,NLP Engineer,200851,USD,200851,SE,FT,United States,L,Switzerland,50,"GCP, AWS, PyTorch",Bachelor,5,Transportation,2024-12-15,2025-01-10,2386,7,DeepTech Ventures +AI05458,Machine Learning Researcher,99863,GBP,74897,MI,PT,United Kingdom,S,United Kingdom,0,"AWS, Git, Spark",PhD,2,Transportation,2024-11-26,2024-12-29,2303,7.6,Digital Transformation LLC +AI05459,Head of AI,39799,USD,39799,SE,PT,India,S,Kenya,50,"Computer Vision, SQL, Kubernetes, GCP",Associate,5,Manufacturing,2024-07-26,2024-09-30,1362,7,AI Innovations +AI05460,Data Engineer,96455,USD,96455,MI,PT,Denmark,S,Italy,50,"Statistics, Kubernetes, Linux, SQL, Data Visualization",PhD,4,Education,2024-07-24,2024-09-05,1910,6.3,Algorithmic Solutions +AI05461,Data Analyst,158698,USD,158698,EX,PT,South Korea,S,South Korea,50,"Scala, R, MLOps, Spark",Associate,19,Telecommunications,2024-03-25,2024-04-10,1132,6.3,Future Systems +AI05462,Machine Learning Researcher,180104,EUR,153088,EX,FT,Germany,M,Germany,0,"R, GCP, Git, Statistics",PhD,11,Government,2025-01-04,2025-02-09,2103,6.5,Autonomous Tech +AI05463,ML Ops Engineer,60136,EUR,51116,EN,PT,Netherlands,M,Netherlands,50,"SQL, Linux, AWS",PhD,0,Healthcare,2024-05-23,2024-08-01,691,9.7,Advanced Robotics +AI05464,AI Product Manager,183029,USD,183029,EX,FL,Israel,S,Israel,100,"Scala, TensorFlow, Tableau, MLOps, Kubernetes",Bachelor,19,Manufacturing,2024-01-05,2024-01-23,1507,6.7,Machine Intelligence Group +AI05465,AI Product Manager,114370,EUR,97215,MI,FL,Netherlands,M,Romania,50,"Linux, Kubernetes, Statistics, Python",Master,4,Retail,2025-02-19,2025-03-14,1343,8.5,AI Innovations +AI05466,Head of AI,54599,USD,54599,MI,CT,China,L,Netherlands,100,"Statistics, Docker, Python",Bachelor,2,Gaming,2024-04-23,2024-07-02,1436,6.1,Cloud AI Solutions +AI05467,AI Consultant,149215,EUR,126833,EX,CT,Germany,S,Germany,100,"TensorFlow, Deep Learning, Computer Vision, Tableau, SQL",PhD,12,Technology,2024-09-30,2024-11-10,1897,7,AI Innovations +AI05468,Data Analyst,36117,USD,36117,MI,FT,China,S,China,0,"Python, Azure, SQL, R, Mathematics",PhD,2,Consulting,2024-06-03,2024-07-28,1999,5.4,Cognitive Computing +AI05469,NLP Engineer,58126,EUR,49407,EN,PT,Austria,L,Philippines,100,"Python, SQL, Tableau, AWS, Kubernetes",Master,0,Finance,2025-03-17,2025-05-04,1896,5.7,Advanced Robotics +AI05470,AI Specialist,72607,AUD,98019,MI,CT,Australia,M,Australia,0,"Python, TensorFlow, AWS",Master,2,Real Estate,2025-02-11,2025-03-01,1088,7.4,TechCorp Inc +AI05471,Data Analyst,71757,CAD,89696,MI,FL,Canada,S,Kenya,0,"Statistics, PyTorch, Computer Vision, R, Git",Master,2,Media,2024-03-01,2024-04-26,2146,6.5,Future Systems +AI05472,Deep Learning Engineer,105689,EUR,89836,SE,FL,Germany,M,Germany,50,"R, Kubernetes, Mathematics, NLP",Master,9,Real Estate,2024-11-28,2025-01-13,758,5.1,Quantum Computing Inc +AI05473,Head of AI,42540,USD,42540,MI,FL,India,L,Egypt,100,"Python, Data Visualization, R, Spark, Java",PhD,2,Healthcare,2024-03-08,2024-04-06,1622,5.5,Digital Transformation LLC +AI05474,AI Architect,123577,EUR,105040,EX,FT,Austria,S,Portugal,0,"Python, R, NLP",PhD,12,Government,2024-10-17,2024-12-03,1020,6.6,Machine Intelligence Group +AI05475,AI Architect,236155,CAD,295194,EX,FT,Canada,L,Canada,0,"Scala, Spark, SQL",Master,16,Retail,2024-08-16,2024-09-26,1079,5,TechCorp Inc +AI05476,Machine Learning Engineer,70398,EUR,59838,EN,CT,Austria,L,Romania,100,"PyTorch, Spark, SQL, Mathematics",Master,1,Healthcare,2024-09-24,2024-11-20,1778,8,Machine Intelligence Group +AI05477,Data Scientist,146441,USD,146441,EX,FT,Israel,S,Israel,100,"AWS, Scala, Data Visualization, Java",Master,18,Technology,2024-11-13,2024-11-30,551,8.3,Machine Intelligence Group +AI05478,AI Specialist,47127,USD,47127,SE,CT,India,M,India,0,"Statistics, Azure, Git",PhD,6,Finance,2025-01-31,2025-03-17,1325,8,Algorithmic Solutions +AI05479,AI Product Manager,142445,EUR,121078,EX,FT,Austria,M,Austria,0,"Java, Tableau, Docker, Statistics",Master,10,Telecommunications,2024-05-10,2024-06-08,1295,7.5,Advanced Robotics +AI05480,AI Consultant,67586,USD,67586,SE,FL,China,M,China,0,"Mathematics, MLOps, Python, PyTorch, Tableau",PhD,9,Automotive,2025-04-26,2025-06-04,1573,5.5,Smart Analytics +AI05481,Research Scientist,176023,USD,176023,SE,FL,Denmark,S,Denmark,0,"Azure, SQL, Python, Kubernetes, Deep Learning",PhD,6,Real Estate,2024-07-26,2024-09-18,749,6.7,Advanced Robotics +AI05482,Machine Learning Engineer,21634,USD,21634,EN,FT,China,S,China,100,"Azure, SQL, R, Mathematics",Associate,1,Consulting,2024-09-26,2024-12-04,1237,9.1,Digital Transformation LLC +AI05483,ML Ops Engineer,105516,USD,105516,SE,FT,South Korea,S,Malaysia,50,"Azure, SQL, GCP",Associate,9,Technology,2024-07-31,2024-08-27,2063,7.3,Digital Transformation LLC +AI05484,Research Scientist,144381,USD,144381,EX,PT,Ireland,M,Ireland,0,"R, SQL, Docker",PhD,17,Telecommunications,2024-03-27,2024-04-28,1007,9,Advanced Robotics +AI05485,Deep Learning Engineer,76971,USD,76971,MI,FT,Israel,S,Belgium,0,"Python, Scala, Deep Learning",Associate,3,Automotive,2024-07-08,2024-07-26,1221,6.3,DeepTech Ventures +AI05486,AI Research Scientist,69347,USD,69347,SE,FL,China,L,Austria,50,"Data Visualization, Computer Vision, TensorFlow",Associate,6,Retail,2024-09-16,2024-10-29,2123,5.3,Smart Analytics +AI05487,ML Ops Engineer,63587,JPY,6994570,EN,CT,Japan,S,Japan,50,"Computer Vision, PyTorch, Kubernetes, Java, Spark",Master,1,Finance,2025-01-01,2025-03-12,1372,9.2,Advanced Robotics +AI05488,AI Consultant,159882,EUR,135900,SE,CT,Germany,L,Finland,50,"PyTorch, Tableau, R, Data Visualization",Bachelor,9,Media,2024-11-26,2025-01-30,895,6,Predictive Systems +AI05489,Head of AI,63760,USD,63760,EN,FT,Ireland,M,Ireland,100,"Kubernetes, Python, Tableau",Master,0,Telecommunications,2024-12-18,2025-02-06,1750,9.6,Algorithmic Solutions +AI05490,AI Software Engineer,91323,JPY,10045530,MI,CT,Japan,S,Japan,0,"Linux, AWS, Python",Bachelor,3,Healthcare,2025-01-02,2025-03-10,2170,5.1,DataVision Ltd +AI05491,Principal Data Scientist,95852,SGD,124608,MI,CT,Singapore,S,Singapore,100,"TensorFlow, Azure, Git",Associate,2,Media,2024-04-18,2024-06-02,2250,9.5,Autonomous Tech +AI05492,AI Research Scientist,142643,USD,142643,EX,FT,Ireland,M,Germany,50,"Data Visualization, Statistics, Linux",PhD,19,Telecommunications,2024-09-19,2024-11-09,1075,8.6,Advanced Robotics +AI05493,AI Research Scientist,183011,USD,183011,EX,PT,Finland,S,Luxembourg,100,"SQL, MLOps, TensorFlow, AWS",Bachelor,18,Education,2025-01-01,2025-02-23,1368,5.2,Quantum Computing Inc +AI05494,AI Product Manager,60370,USD,60370,EN,PT,United States,S,United States,50,"NLP, R, Linux, SQL",PhD,0,Technology,2024-01-24,2024-03-07,1727,9.5,Future Systems +AI05495,AI Software Engineer,296283,JPY,32591130,EX,CT,Japan,L,Egypt,50,"Git, SQL, Computer Vision, Mathematics",PhD,13,Media,2024-07-26,2024-08-22,947,7.8,Neural Networks Co +AI05496,NLP Engineer,89935,JPY,9892850,EN,CT,Japan,L,Switzerland,100,"MLOps, Python, Computer Vision, Spark",Master,0,Government,2024-10-12,2024-11-04,2250,8.7,Future Systems +AI05497,Data Analyst,94666,CHF,85199,EN,CT,Switzerland,L,Switzerland,50,"Scala, Tableau, AWS, Computer Vision, TensorFlow",PhD,0,Media,2024-04-28,2024-05-24,1878,6.1,Neural Networks Co +AI05498,Machine Learning Engineer,86209,USD,86209,EN,CT,United States,M,United States,0,"Hadoop, Linux, SQL, NLP, Kubernetes",Bachelor,0,Real Estate,2025-01-12,2025-03-01,1116,8,Digital Transformation LLC +AI05499,Machine Learning Engineer,81814,GBP,61361,EN,FT,United Kingdom,M,United Kingdom,0,"Linux, Azure, Scala",Associate,1,Real Estate,2024-11-22,2024-12-06,1079,8.5,Predictive Systems +AI05500,Data Engineer,122880,EUR,104448,SE,FT,Austria,S,Japan,50,"Scala, Python, Data Visualization, Deep Learning, TensorFlow",PhD,5,Transportation,2024-03-02,2024-05-08,907,5.3,Smart Analytics +AI05501,Data Analyst,161377,CHF,145239,SE,PT,Switzerland,M,Switzerland,0,"Linux, Spark, TensorFlow, Python, Tableau",Associate,5,Government,2025-02-20,2025-03-31,900,9.9,Quantum Computing Inc +AI05502,AI Consultant,64242,JPY,7066620,EN,FL,Japan,S,Japan,0,"Computer Vision, Kubernetes, SQL",Bachelor,1,Real Estate,2024-09-25,2024-11-14,526,6,DeepTech Ventures +AI05503,Robotics Engineer,142995,EUR,121546,SE,CT,Netherlands,M,Ukraine,50,"Computer Vision, Statistics, Kubernetes",Bachelor,5,Government,2024-08-26,2024-10-05,1795,7.9,Autonomous Tech +AI05504,Autonomous Systems Engineer,108977,CAD,136221,SE,PT,Canada,S,Chile,50,"Azure, Computer Vision, NLP, SQL, Mathematics",PhD,7,Education,2025-04-17,2025-06-25,1497,5.4,Predictive Systems +AI05505,Deep Learning Engineer,32809,USD,32809,EN,PT,China,M,China,50,"Statistics, Python, Tableau, Docker, AWS",Bachelor,1,Transportation,2025-01-22,2025-03-08,1052,5.1,Machine Intelligence Group +AI05506,Computer Vision Engineer,236299,GBP,177224,EX,PT,United Kingdom,L,United Kingdom,0,"PyTorch, SQL, Data Visualization, Hadoop",Bachelor,13,Automotive,2024-05-20,2024-07-28,1337,9.6,Future Systems +AI05507,Machine Learning Engineer,133957,USD,133957,MI,CT,Norway,M,Norway,100,"Tableau, Kubernetes, Python, Deep Learning, Azure",Bachelor,3,Transportation,2024-04-29,2024-05-29,1599,8.3,AI Innovations +AI05508,Data Scientist,62909,GBP,47182,EN,PT,United Kingdom,L,United Kingdom,0,"Computer Vision, GCP, MLOps, Statistics, Deep Learning",Bachelor,0,Technology,2025-01-19,2025-03-07,928,8.7,Machine Intelligence Group +AI05509,Machine Learning Engineer,147022,SGD,191129,EX,CT,Singapore,S,Singapore,100,"SQL, PyTorch, NLP, Docker",PhD,15,Manufacturing,2024-12-03,2025-01-02,679,8.9,Neural Networks Co +AI05510,Machine Learning Engineer,144913,EUR,123176,SE,FL,France,L,France,50,"Data Visualization, Git, Spark, Computer Vision",Associate,8,Technology,2025-04-19,2025-06-05,578,8.9,Cognitive Computing +AI05511,AI Specialist,45877,USD,45877,SE,FT,India,M,India,0,"Python, Docker, GCP",PhD,7,Automotive,2024-08-28,2024-09-29,1780,9.7,Algorithmic Solutions +AI05512,Principal Data Scientist,33228,USD,33228,EN,FT,China,S,China,100,"Kubernetes, SQL, Git, Statistics",Associate,1,Media,2024-06-09,2024-07-03,642,6.8,Cloud AI Solutions +AI05513,Machine Learning Researcher,87357,USD,87357,MI,FL,South Korea,M,South Korea,0,"MLOps, Hadoop, NLP, Mathematics",Bachelor,2,Retail,2024-07-25,2024-09-09,1707,7.2,TechCorp Inc +AI05514,AI Product Manager,57116,USD,57116,EN,FT,Finland,M,Finland,100,"NLP, Java, Spark, Kubernetes",PhD,0,Real Estate,2024-06-16,2024-08-23,2471,8.4,Smart Analytics +AI05515,Machine Learning Engineer,67628,GBP,50721,EN,CT,United Kingdom,L,Philippines,0,"Kubernetes, Java, R, Deep Learning",PhD,1,Transportation,2024-04-22,2024-06-05,1168,6.2,Smart Analytics +AI05516,AI Specialist,51699,JPY,5686890,EN,PT,Japan,S,Japan,0,"Tableau, R, PyTorch",Master,0,Transportation,2024-12-30,2025-03-06,1456,6.5,Cloud AI Solutions +AI05517,AI Research Scientist,158696,USD,158696,EX,PT,Sweden,S,Singapore,0,"Git, TensorFlow, Computer Vision, Linux, Python",PhD,16,Automotive,2024-08-16,2024-09-28,1409,6.4,Predictive Systems +AI05518,AI Specialist,181010,EUR,153859,EX,CT,Austria,L,Austria,50,"Azure, Tableau, Python",Bachelor,18,Retail,2025-01-13,2025-01-31,1209,9.6,DeepTech Ventures +AI05519,ML Ops Engineer,143355,USD,143355,SE,FL,Ireland,M,United States,100,"Python, Kubernetes, NLP",Bachelor,8,Manufacturing,2025-03-02,2025-04-09,973,8.8,AI Innovations +AI05520,Data Scientist,94621,USD,94621,MI,CT,Israel,M,South Africa,100,"Data Visualization, Git, Linux, AWS",Master,2,Consulting,2024-09-25,2024-11-17,1804,6.1,Machine Intelligence Group +AI05521,Data Engineer,50440,USD,50440,SE,FT,China,M,China,100,"SQL, PyTorch, Mathematics, Git",Associate,6,Real Estate,2024-10-24,2024-11-17,1306,6.9,DeepTech Ventures +AI05522,Autonomous Systems Engineer,39850,USD,39850,MI,CT,China,L,China,50,"SQL, Computer Vision, Statistics",Master,4,Energy,2024-07-16,2024-08-30,1706,6.3,Neural Networks Co +AI05523,Data Analyst,129312,USD,129312,SE,CT,Finland,M,Finland,100,"Docker, MLOps, Python, Java, Tableau",PhD,9,Real Estate,2024-12-07,2025-02-11,2388,6.2,DeepTech Ventures +AI05524,ML Ops Engineer,262770,EUR,223355,EX,FT,France,L,Philippines,100,"Git, MLOps, Tableau, Scala, Kubernetes",Bachelor,11,Real Estate,2025-01-22,2025-03-31,942,9.9,Cognitive Computing +AI05525,Principal Data Scientist,95183,JPY,10470130,MI,FT,Japan,S,Japan,100,"Tableau, Python, AWS, TensorFlow, Deep Learning",Associate,3,Consulting,2024-07-23,2024-09-01,1428,9.6,Smart Analytics +AI05526,Data Analyst,40242,USD,40242,MI,PT,India,L,India,0,"PyTorch, Azure, Tableau, Kubernetes, TensorFlow",PhD,2,Telecommunications,2024-07-02,2024-07-24,1322,6.8,Autonomous Tech +AI05527,Machine Learning Researcher,164259,JPY,18068490,EX,FT,Japan,S,Colombia,100,"Docker, Kubernetes, NLP, PyTorch, TensorFlow",Associate,19,Gaming,2024-11-05,2024-11-27,2246,8.8,Advanced Robotics +AI05528,Machine Learning Engineer,102309,USD,102309,SE,FT,Finland,M,Finland,100,"Data Visualization, NLP, Python, Hadoop",Master,8,Education,2024-03-04,2024-05-11,939,7.1,Predictive Systems +AI05529,Head of AI,53973,USD,53973,EN,FL,Ireland,S,Thailand,0,"Python, TensorFlow, MLOps",PhD,0,Technology,2025-02-03,2025-03-05,611,7.2,Cognitive Computing +AI05530,AI Product Manager,54973,USD,54973,SE,FT,India,L,India,0,"Scala, Data Visualization, Azure, PyTorch",PhD,7,Automotive,2024-11-12,2024-12-08,1043,9.6,Digital Transformation LLC +AI05531,NLP Engineer,187522,USD,187522,EX,CT,Finland,S,Finland,0,"Scala, Linux, Spark, PyTorch, MLOps",Bachelor,10,Media,2024-11-27,2024-12-31,1802,7.4,Future Systems +AI05532,NLP Engineer,57683,EUR,49031,EN,CT,Austria,S,Austria,0,"R, GCP, Mathematics, Deep Learning",Bachelor,0,Finance,2024-04-04,2024-04-30,1641,5.4,Cloud AI Solutions +AI05533,AI Architect,78473,USD,78473,MI,FL,South Korea,L,South Korea,50,"Kubernetes, Deep Learning, R, Tableau",Bachelor,3,Automotive,2024-07-31,2024-10-03,1798,5.2,DataVision Ltd +AI05534,Computer Vision Engineer,55008,SGD,71510,EN,CT,Singapore,S,Portugal,100,"Mathematics, Azure, Computer Vision",Bachelor,1,Technology,2024-12-16,2025-02-20,1194,9.6,TechCorp Inc +AI05535,Computer Vision Engineer,76394,USD,76394,EN,FL,Norway,S,Norway,100,"Python, Computer Vision, SQL, Docker",PhD,0,Government,2024-01-16,2024-03-04,2400,8.2,Smart Analytics +AI05536,AI Research Scientist,102251,USD,102251,SE,CT,Finland,M,France,100,"MLOps, NLP, R, Data Visualization",Associate,6,Government,2025-01-07,2025-02-08,1801,6.7,Quantum Computing Inc +AI05537,Head of AI,225096,USD,225096,EX,FT,Ireland,L,Ireland,50,"PyTorch, AWS, TensorFlow, Mathematics, Scala",Master,15,Education,2024-05-01,2024-07-01,726,5.7,DeepTech Ventures +AI05538,Principal Data Scientist,204843,CHF,184359,SE,PT,Switzerland,L,Brazil,100,"PyTorch, Scala, Java",PhD,6,Finance,2025-01-06,2025-02-14,1120,7.8,TechCorp Inc +AI05539,Principal Data Scientist,138580,USD,138580,SE,CT,Norway,M,Norway,50,"R, SQL, PyTorch",Master,6,Education,2024-08-09,2024-10-11,944,6.5,DeepTech Ventures +AI05540,Head of AI,85499,EUR,72674,EN,FL,Netherlands,L,Netherlands,50,"PyTorch, TensorFlow, Hadoop",Associate,1,Finance,2024-03-02,2024-03-27,767,5.8,Algorithmic Solutions +AI05541,Machine Learning Researcher,83346,SGD,108350,EN,CT,Singapore,M,Singapore,100,"NLP, Kubernetes, TensorFlow, Docker",Master,0,Finance,2024-04-10,2024-05-23,723,9.1,DeepTech Ventures +AI05542,NLP Engineer,115766,USD,115766,MI,PT,Norway,S,Norway,50,"Tableau, SQL, Azure, PyTorch",PhD,2,Consulting,2024-08-11,2024-10-17,1493,7.2,DataVision Ltd +AI05543,Data Analyst,205113,USD,205113,SE,CT,Denmark,L,Denmark,50,"Java, Spark, NLP",PhD,7,Gaming,2025-03-18,2025-04-17,1640,7.7,AI Innovations +AI05544,AI Software Engineer,160912,USD,160912,SE,FT,Sweden,L,Sweden,100,"Git, GCP, Hadoop, Azure, Statistics",PhD,6,Finance,2024-02-27,2024-04-22,856,6,Predictive Systems +AI05545,AI Research Scientist,142229,USD,142229,SE,PT,Finland,L,Finland,50,"Statistics, Tableau, Computer Vision, Java, Python",Bachelor,6,Real Estate,2024-02-07,2024-03-19,1243,6,Predictive Systems +AI05546,Deep Learning Engineer,79913,USD,79913,MI,FT,Finland,S,Finland,0,"SQL, AWS, Scala",Bachelor,2,Gaming,2024-04-21,2024-05-21,1381,5.6,Digital Transformation LLC +AI05547,Data Scientist,105268,USD,105268,MI,CT,Denmark,M,Denmark,100,"Kubernetes, GCP, Mathematics, Computer Vision, Hadoop",Master,3,Telecommunications,2024-10-25,2024-12-11,1041,6.4,Neural Networks Co +AI05548,Research Scientist,222239,SGD,288911,EX,CT,Singapore,S,Singapore,100,"Spark, Python, R, Computer Vision",Master,11,Technology,2025-02-22,2025-03-08,1199,9.6,AI Innovations +AI05549,Computer Vision Engineer,95349,USD,95349,MI,PT,Sweden,S,Sweden,100,"R, Statistics, Hadoop",Master,3,Telecommunications,2024-05-08,2024-06-18,913,7.2,AI Innovations +AI05550,Machine Learning Engineer,276306,USD,276306,EX,CT,United States,L,United States,0,"TensorFlow, R, Azure",Associate,13,Government,2024-07-21,2024-09-08,880,7.6,DataVision Ltd +AI05551,Head of AI,86349,USD,86349,MI,FL,Finland,S,Finland,100,"Git, Java, Computer Vision, Mathematics, Spark",Master,2,Transportation,2024-06-24,2024-08-13,744,6.4,Autonomous Tech +AI05552,AI Product Manager,200534,USD,200534,EX,FT,United States,S,Luxembourg,50,"Linux, Kubernetes, Python, Mathematics",Bachelor,15,Manufacturing,2024-07-22,2024-09-01,1411,7.1,Autonomous Tech +AI05553,ML Ops Engineer,130848,GBP,98136,SE,PT,United Kingdom,M,United Kingdom,50,"Tableau, Spark, Python, Computer Vision",Associate,7,Transportation,2024-11-18,2025-01-19,506,8.6,Neural Networks Co +AI05554,ML Ops Engineer,137574,USD,137574,SE,FL,Denmark,M,Denmark,100,"Python, MLOps, Scala",Master,9,Gaming,2024-02-05,2024-03-25,2456,6,AI Innovations +AI05555,AI Research Scientist,64547,EUR,54865,MI,PT,France,S,France,100,"Data Visualization, SQL, Statistics",Bachelor,4,Real Estate,2024-10-06,2024-11-08,1689,5.6,Cloud AI Solutions +AI05556,AI Specialist,220582,CHF,198524,SE,FL,Switzerland,L,Switzerland,50,"Data Visualization, Python, Hadoop, MLOps, TensorFlow",Master,9,Education,2025-04-29,2025-05-30,1189,7.7,Autonomous Tech +AI05557,Machine Learning Engineer,68236,EUR,58001,EN,CT,France,M,France,100,"Docker, Deep Learning, Java",Associate,1,Manufacturing,2024-03-04,2024-04-25,2050,8.7,DeepTech Ventures +AI05558,Machine Learning Engineer,102411,CHF,92170,MI,FT,Switzerland,S,Switzerland,0,"Python, SQL, Linux, Azure",Bachelor,3,Real Estate,2024-03-20,2024-04-10,2337,8.1,Neural Networks Co +AI05559,Data Analyst,98866,JPY,10875260,MI,FL,Japan,S,Japan,50,"Python, Mathematics, Scala",Master,3,Real Estate,2025-04-23,2025-05-20,1232,8.7,DeepTech Ventures +AI05560,AI Research Scientist,71678,USD,71678,EN,CT,Norway,S,Norway,50,"Java, Kubernetes, TensorFlow, GCP, Spark",Bachelor,0,Education,2025-02-21,2025-03-23,2418,8.2,DeepTech Ventures +AI05561,Principal Data Scientist,38368,USD,38368,MI,PT,India,L,Ghana,50,"PyTorch, Java, Docker, Kubernetes, GCP",Master,4,Finance,2024-02-16,2024-04-22,1578,9.7,DataVision Ltd +AI05562,Autonomous Systems Engineer,53056,EUR,45098,EN,PT,Germany,M,Germany,100,"Python, MLOps, NLP, TensorFlow",Associate,0,Automotive,2024-12-27,2025-02-05,1918,6.2,Predictive Systems +AI05563,Research Scientist,77960,USD,77960,MI,FT,Finland,S,India,50,"NLP, Kubernetes, Git",PhD,3,Media,2024-08-25,2024-09-30,2354,5.9,DataVision Ltd +AI05564,Computer Vision Engineer,137750,USD,137750,EX,FL,Israel,S,Israel,50,"Hadoop, TensorFlow, Data Visualization, MLOps",Bachelor,15,Transportation,2024-12-13,2025-01-07,686,9.3,AI Innovations +AI05565,Deep Learning Engineer,70399,USD,70399,EN,PT,Finland,L,Singapore,0,"Spark, SQL, Kubernetes",Master,0,Media,2024-06-06,2024-07-02,885,5.8,TechCorp Inc +AI05566,Data Scientist,81497,USD,81497,EX,CT,China,L,China,50,"Azure, Java, Computer Vision, Kubernetes, R",Bachelor,16,Gaming,2024-06-17,2024-08-04,897,8.5,Future Systems +AI05567,Autonomous Systems Engineer,97979,USD,97979,SE,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, Statistics",Master,5,Education,2024-03-11,2024-05-04,1745,5.1,Cloud AI Solutions +AI05568,Machine Learning Engineer,74733,CHF,67260,EN,FT,Switzerland,M,Switzerland,0,"Linux, GCP, PyTorch",Bachelor,0,Retail,2025-04-07,2025-06-01,2308,9.4,Neural Networks Co +AI05569,AI Consultant,34474,USD,34474,MI,FL,India,S,India,100,"Scala, NLP, Java, R, Kubernetes",Associate,3,Education,2025-01-15,2025-02-05,2489,7.9,Quantum Computing Inc +AI05570,Machine Learning Researcher,138565,EUR,117780,EX,CT,France,S,Vietnam,0,"NLP, Docker, Java",Bachelor,11,Media,2024-05-07,2024-06-08,2445,7.8,Digital Transformation LLC +AI05571,Head of AI,91979,USD,91979,MI,FL,Finland,M,Finland,100,"SQL, Computer Vision, Git, Python, Azure",Master,4,Automotive,2024-01-31,2024-03-17,1365,6.3,Predictive Systems +AI05572,AI Product Manager,156226,CHF,140603,MI,FL,Switzerland,L,Philippines,50,"SQL, R, Python",PhD,3,Energy,2024-07-14,2024-09-15,563,7.9,DataVision Ltd +AI05573,Robotics Engineer,220616,SGD,286801,EX,FL,Singapore,S,United States,0,"Linux, NLP, Kubernetes, Scala, SQL",Master,18,Consulting,2024-04-03,2024-05-22,793,6.6,Neural Networks Co +AI05574,Data Engineer,125635,CHF,113072,MI,FL,Switzerland,S,Switzerland,100,"NLP, Python, Scala, GCP",Master,2,Technology,2024-04-24,2024-06-25,569,8.4,TechCorp Inc +AI05575,Data Scientist,141071,EUR,119910,SE,FL,France,L,Austria,0,"Spark, Azure, SQL",PhD,5,Education,2024-07-09,2024-08-16,1177,9.1,Advanced Robotics +AI05576,NLP Engineer,77457,USD,77457,EN,CT,Ireland,M,France,0,"Azure, Mathematics, Python",Bachelor,1,Real Estate,2025-02-26,2025-03-26,1430,6.1,Machine Intelligence Group +AI05577,Computer Vision Engineer,81274,EUR,69083,MI,FL,Austria,L,Austria,100,"Docker, AWS, GCP, PyTorch, Scala",Associate,4,Energy,2024-03-25,2024-04-22,1457,6.7,Neural Networks Co +AI05578,Robotics Engineer,123555,USD,123555,SE,FT,Ireland,S,Ireland,50,"TensorFlow, Git, NLP",Bachelor,7,Finance,2024-06-28,2024-08-29,2138,6.9,DeepTech Ventures +AI05579,AI Product Manager,107981,USD,107981,SE,PT,Finland,M,Finland,100,"Data Visualization, Python, GCP, MLOps, Deep Learning",Master,9,Finance,2024-09-21,2024-10-28,910,5.2,AI Innovations +AI05580,Research Scientist,91339,USD,91339,EN,PT,Sweden,L,Luxembourg,50,"Hadoop, Kubernetes, Computer Vision, TensorFlow, GCP",Bachelor,0,Finance,2025-01-25,2025-04-04,1507,7.5,DataVision Ltd +AI05581,Principal Data Scientist,137460,CHF,123714,MI,CT,Switzerland,L,Switzerland,50,"Python, Hadoop, Git, TensorFlow, PyTorch",Master,3,Healthcare,2025-04-19,2025-05-25,1966,7.9,Neural Networks Co +AI05582,Data Scientist,104465,USD,104465,MI,PT,Norway,M,Netherlands,0,"Statistics, Git, SQL",Bachelor,2,Finance,2024-10-03,2024-11-12,820,7.7,Autonomous Tech +AI05583,Robotics Engineer,77385,USD,77385,MI,FL,Sweden,S,Spain,100,"Git, GCP, MLOps, Deep Learning, Kubernetes",Associate,3,Transportation,2024-02-29,2024-04-20,1137,7.6,Advanced Robotics +AI05584,Machine Learning Engineer,26283,USD,26283,EN,FT,China,S,Colombia,50,"Python, TensorFlow, Kubernetes, PyTorch",PhD,0,Energy,2025-03-31,2025-05-10,714,8.6,Predictive Systems +AI05585,Data Scientist,132539,USD,132539,SE,PT,Denmark,M,Denmark,100,"Data Visualization, Kubernetes, Docker",Master,6,Media,2024-11-04,2024-12-05,2172,10,DeepTech Ventures +AI05586,AI Product Manager,59940,EUR,50949,EN,CT,Netherlands,M,Spain,100,"Python, R, Computer Vision, Git, Azure",Bachelor,0,Finance,2025-01-19,2025-03-25,953,6.9,AI Innovations +AI05587,NLP Engineer,308476,USD,308476,EX,FL,Denmark,M,Ukraine,100,"Data Visualization, TensorFlow, Python",Bachelor,13,Education,2024-05-14,2024-06-09,807,6.4,Future Systems +AI05588,Machine Learning Engineer,117756,GBP,88317,SE,FT,United Kingdom,M,United Kingdom,0,"Tableau, Python, Azure, Statistics, Scala",Master,7,Real Estate,2024-12-06,2025-01-28,1370,7.8,TechCorp Inc +AI05589,Robotics Engineer,95582,USD,95582,EN,PT,Norway,M,Norway,50,"TensorFlow, Statistics, Deep Learning",Master,0,Education,2025-01-13,2025-03-11,1148,5,DeepTech Ventures +AI05590,Deep Learning Engineer,152384,USD,152384,MI,CT,Norway,L,Norway,0,"AWS, PyTorch, Linux, GCP, Computer Vision",Associate,4,Energy,2024-08-23,2024-09-30,2279,7.3,Machine Intelligence Group +AI05591,Data Engineer,149481,USD,149481,SE,CT,Denmark,S,Indonesia,0,"MLOps, Tableau, Hadoop, SQL, R",Master,7,Automotive,2024-05-31,2024-08-10,1674,5.9,DataVision Ltd +AI05592,Robotics Engineer,133014,CHF,119713,MI,FT,Switzerland,M,Switzerland,0,"Hadoop, Scala, Data Visualization, PyTorch",Bachelor,4,Media,2024-04-24,2024-05-20,1451,6.1,Autonomous Tech +AI05593,Computer Vision Engineer,80242,SGD,104315,MI,FT,Singapore,M,Singapore,100,"SQL, Linux, Python, AWS",Master,3,Real Estate,2024-04-12,2024-06-01,956,7,Future Systems +AI05594,AI Product Manager,71080,USD,71080,EN,FL,United States,M,United States,100,"AWS, Kubernetes, TensorFlow",Bachelor,1,Energy,2024-03-04,2024-04-18,895,8.4,Neural Networks Co +AI05595,Robotics Engineer,158297,USD,158297,EX,FT,Sweden,M,Sweden,100,"MLOps, R, Python",PhD,16,Finance,2024-04-14,2024-06-08,1393,6.1,DataVision Ltd +AI05596,Computer Vision Engineer,64920,AUD,87642,EN,FL,Australia,M,Australia,50,"Deep Learning, Linux, Spark, GCP",Bachelor,1,Retail,2024-02-24,2024-04-02,1085,8.3,DeepTech Ventures +AI05597,AI Research Scientist,82287,USD,82287,SE,FT,South Korea,S,South Korea,0,"Kubernetes, TensorFlow, Deep Learning",Master,5,Energy,2024-08-23,2024-09-20,1089,9.3,DataVision Ltd +AI05598,Data Analyst,108508,USD,108508,MI,FT,Finland,L,Finland,50,"Python, GCP, NLP, Spark",PhD,2,Energy,2025-04-04,2025-06-09,929,9.3,DeepTech Ventures +AI05599,Data Analyst,86007,AUD,116109,MI,PT,Australia,M,Australia,50,"Spark, Docker, Data Visualization",Associate,3,Media,2024-07-25,2024-09-17,992,9.4,DeepTech Ventures +AI05600,Principal Data Scientist,157752,USD,157752,SE,CT,Denmark,M,Denmark,50,"R, Scala, PyTorch, Mathematics",Master,9,Real Estate,2024-08-09,2024-10-10,1080,5.6,Algorithmic Solutions +AI05601,Autonomous Systems Engineer,91594,USD,91594,MI,FL,Finland,M,Hungary,0,"Git, Hadoop, MLOps",Bachelor,3,Finance,2024-05-10,2024-06-11,1794,6.4,Predictive Systems +AI05602,Autonomous Systems Engineer,74217,USD,74217,MI,FL,Finland,M,India,50,"GCP, Tableau, Hadoop",PhD,2,Manufacturing,2024-02-22,2024-04-09,683,5.6,TechCorp Inc +AI05603,AI Research Scientist,284154,GBP,213116,EX,CT,United Kingdom,L,United Kingdom,50,"Linux, Java, Data Visualization",Bachelor,15,Consulting,2024-11-29,2025-01-28,725,6.4,AI Innovations +AI05604,AI Software Engineer,163958,USD,163958,EX,FT,South Korea,L,South Korea,50,"Scala, PyTorch, Data Visualization, MLOps",PhD,13,Manufacturing,2024-11-03,2024-11-23,596,8,TechCorp Inc +AI05605,ML Ops Engineer,62034,CAD,77543,EN,PT,Canada,S,Canada,0,"Linux, SQL, Docker, PyTorch, Deep Learning",Associate,1,Real Estate,2025-01-27,2025-02-18,1422,9.4,Advanced Robotics +AI05606,AI Software Engineer,166512,CAD,208140,EX,FT,Canada,S,Ireland,0,"Python, Java, Computer Vision",Master,10,Consulting,2024-02-19,2024-04-24,624,8.8,Future Systems +AI05607,AI Product Manager,209138,USD,209138,EX,PT,Ireland,L,Ireland,100,"Python, Spark, MLOps",Associate,10,Telecommunications,2024-12-17,2025-02-05,790,8.5,DataVision Ltd +AI05608,AI Product Manager,149550,USD,149550,SE,PT,United States,S,United States,100,"Computer Vision, PyTorch, Spark",PhD,7,Technology,2024-08-13,2024-09-02,2025,6.8,Machine Intelligence Group +AI05609,ML Ops Engineer,162213,EUR,137881,EX,FT,Germany,M,Germany,50,"R, Kubernetes, Docker, Tableau, TensorFlow",Bachelor,14,Government,2024-06-14,2024-08-01,979,6,Smart Analytics +AI05610,Robotics Engineer,179531,USD,179531,EX,CT,Norway,M,Latvia,50,"Kubernetes, Deep Learning, Computer Vision, Java",Bachelor,14,Manufacturing,2024-06-09,2024-08-15,1650,7.2,Algorithmic Solutions +AI05611,Data Analyst,206536,USD,206536,EX,FL,South Korea,M,South Korea,50,"Linux, Python, Git, TensorFlow",PhD,12,Healthcare,2024-01-21,2024-02-10,1380,5.6,DataVision Ltd +AI05612,AI Specialist,33744,USD,33744,SE,FT,India,S,India,100,"TensorFlow, Deep Learning, Computer Vision",Associate,7,Manufacturing,2024-12-16,2025-02-26,1221,5.4,Algorithmic Solutions +AI05613,AI Consultant,60562,USD,60562,EN,PT,Israel,L,France,0,"SQL, Statistics, PyTorch, Deep Learning, R",PhD,1,Healthcare,2025-01-07,2025-02-07,1322,7.6,Advanced Robotics +AI05614,AI Software Engineer,55911,AUD,75480,EN,FL,Australia,M,Australia,0,"Spark, Kubernetes, Linux, Hadoop",PhD,0,Manufacturing,2024-02-28,2024-03-26,1136,5.1,Neural Networks Co +AI05615,Autonomous Systems Engineer,95326,USD,95326,MI,FL,South Korea,L,South Korea,50,"R, Kubernetes, MLOps",Associate,4,Retail,2024-11-29,2025-01-29,953,7,AI Innovations +AI05616,Machine Learning Engineer,185388,JPY,20392680,EX,CT,Japan,L,Japan,0,"TensorFlow, Python, MLOps, Spark",PhD,17,Manufacturing,2024-07-28,2024-09-26,2466,9.2,Predictive Systems +AI05617,Research Scientist,150527,EUR,127948,SE,CT,Netherlands,M,Switzerland,100,"Linux, AWS, Tableau, Docker, Mathematics",PhD,7,Healthcare,2024-12-20,2025-02-10,545,5.5,Quantum Computing Inc +AI05618,ML Ops Engineer,119633,USD,119633,EX,FL,China,M,China,100,"Java, PyTorch, Hadoop, Git",Master,11,Finance,2024-07-22,2024-08-20,2109,7,TechCorp Inc +AI05619,Data Scientist,227078,USD,227078,SE,FL,Norway,L,Norway,50,"Git, Spark, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-06-21,2024-07-11,1035,8,Cloud AI Solutions +AI05620,AI Product Manager,195528,USD,195528,SE,FL,Denmark,M,Argentina,0,"PyTorch, Python, NLP, Azure, Spark",Associate,7,Media,2024-09-27,2024-10-22,532,8,TechCorp Inc +AI05621,Data Scientist,123024,CAD,153780,SE,FL,Canada,M,Canada,100,"Hadoop, Spark, Python, Git",Master,7,Finance,2024-12-21,2025-02-20,1417,5,Smart Analytics +AI05622,Research Scientist,151053,USD,151053,MI,FT,Denmark,L,Philippines,50,"AWS, Kubernetes, SQL",PhD,2,Technology,2024-06-13,2024-07-09,628,8.1,DataVision Ltd +AI05623,AI Architect,116626,JPY,12828860,SE,PT,Japan,S,Japan,50,"Scala, Kubernetes, NLP, Statistics, R",PhD,7,Telecommunications,2024-11-06,2024-12-30,791,7.1,Advanced Robotics +AI05624,ML Ops Engineer,97656,EUR,83008,MI,FL,Austria,M,Austria,100,"Kubernetes, Java, R",PhD,4,Retail,2025-02-20,2025-03-13,2400,8,Digital Transformation LLC +AI05625,Research Scientist,94494,EUR,80320,EN,PT,Netherlands,L,Netherlands,100,"Scala, Spark, Java, Computer Vision, Git",PhD,1,Consulting,2025-04-24,2025-05-13,1566,9.9,DeepTech Ventures +AI05626,ML Ops Engineer,43321,USD,43321,SE,PT,India,L,India,100,"TensorFlow, Azure, Git",Master,9,Telecommunications,2024-09-06,2024-10-04,1763,8.8,DataVision Ltd +AI05627,AI Software Engineer,58243,EUR,49507,EN,FL,Germany,S,Malaysia,100,"Kubernetes, GCP, Computer Vision, MLOps",PhD,0,Energy,2024-11-02,2024-12-16,535,8.6,TechCorp Inc +AI05628,Machine Learning Engineer,106076,USD,106076,SE,FT,Israel,M,Malaysia,0,"GCP, Azure, SQL, Docker",Associate,6,Government,2024-08-06,2024-10-14,830,7.9,DeepTech Ventures +AI05629,Head of AI,124280,USD,124280,SE,CT,Israel,M,Malaysia,100,"Git, Python, Kubernetes, MLOps",Associate,7,Automotive,2024-08-01,2024-08-16,1666,9.3,Machine Intelligence Group +AI05630,Robotics Engineer,237713,GBP,178285,EX,FT,United Kingdom,M,Denmark,50,"Java, TensorFlow, Tableau, NLP, Mathematics",Bachelor,18,Education,2025-02-05,2025-03-04,861,7.6,Autonomous Tech +AI05631,AI Product Manager,133896,USD,133896,SE,FL,Sweden,S,Sweden,50,"Spark, SQL, TensorFlow, Computer Vision, Python",PhD,5,Technology,2024-11-20,2024-12-16,2374,5.1,Algorithmic Solutions +AI05632,AI Software Engineer,116023,JPY,12762530,SE,PT,Japan,M,Japan,0,"Tableau, Hadoop, Python, TensorFlow, Deep Learning",Associate,7,Finance,2024-11-09,2025-01-15,2298,5.3,Cognitive Computing +AI05633,Computer Vision Engineer,96751,USD,96751,MI,CT,United States,S,Indonesia,50,"Data Visualization, Python, Java",Bachelor,4,Energy,2025-02-07,2025-03-04,1001,9,Digital Transformation LLC +AI05634,Computer Vision Engineer,134644,EUR,114447,SE,PT,Austria,L,Brazil,50,"Kubernetes, Data Visualization, Tableau, MLOps, Deep Learning",PhD,8,Media,2025-04-25,2025-06-22,1118,6.3,Advanced Robotics +AI05635,Principal Data Scientist,102778,JPY,11305580,MI,FT,Japan,M,Kenya,50,"Spark, SQL, TensorFlow, Azure",Bachelor,2,Healthcare,2025-01-07,2025-01-27,1080,6.1,AI Innovations +AI05636,AI Product Manager,103788,USD,103788,EN,FT,Norway,M,Norway,100,"Kubernetes, TensorFlow, Azure, Tableau",PhD,1,Transportation,2024-07-09,2024-09-17,2278,9.7,Quantum Computing Inc +AI05637,Machine Learning Researcher,43133,USD,43133,EN,CT,China,L,China,100,"AWS, Hadoop, Deep Learning, PyTorch",Associate,1,Gaming,2025-03-02,2025-05-04,1800,9.8,Quantum Computing Inc +AI05638,Research Scientist,186168,EUR,158243,EX,PT,Germany,S,Germany,100,"SQL, Python, MLOps",Master,10,Healthcare,2024-07-01,2024-08-26,655,7,Algorithmic Solutions +AI05639,AI Specialist,269018,GBP,201764,EX,FT,United Kingdom,M,United Kingdom,0,"Hadoop, Deep Learning, Azure, Python, NLP",Associate,18,Real Estate,2024-08-08,2024-09-02,2032,9,DataVision Ltd +AI05640,AI Software Engineer,168038,USD,168038,SE,FL,Denmark,L,Denmark,100,"Azure, Deep Learning, Python",PhD,6,Media,2024-08-24,2024-11-03,797,9.9,Smart Analytics +AI05641,Machine Learning Engineer,63639,USD,63639,EN,FL,South Korea,M,South Korea,100,"Python, Hadoop, Linux, Computer Vision",Associate,0,Manufacturing,2024-08-08,2024-09-23,816,9.5,Algorithmic Solutions +AI05642,AI Specialist,204416,USD,204416,EX,PT,Israel,L,Canada,50,"AWS, Java, TensorFlow, Azure, SQL",Bachelor,16,Consulting,2024-02-02,2024-03-17,1641,6.1,DataVision Ltd +AI05643,AI Research Scientist,28315,USD,28315,MI,CT,India,S,India,0,"AWS, Scala, R, Git",Bachelor,3,Transportation,2024-10-31,2024-12-09,2250,6.6,Algorithmic Solutions +AI05644,Autonomous Systems Engineer,69096,USD,69096,EN,FL,United States,L,United States,100,"Git, Mathematics, TensorFlow, Linux",Bachelor,0,Consulting,2024-07-01,2024-07-28,804,5.5,Smart Analytics +AI05645,Data Analyst,72148,USD,72148,MI,FL,South Korea,L,South Korea,100,"Kubernetes, Git, MLOps, R, Computer Vision",Associate,2,Education,2025-04-12,2025-05-02,1906,7.6,Cloud AI Solutions +AI05646,Research Scientist,155411,USD,155411,SE,PT,Norway,M,Norway,100,"TensorFlow, Scala, MLOps",Bachelor,9,Gaming,2025-04-17,2025-06-23,835,5.2,TechCorp Inc +AI05647,Autonomous Systems Engineer,119240,USD,119240,MI,FL,Ireland,L,Indonesia,0,"Computer Vision, Data Visualization, Hadoop, Kubernetes, Deep Learning",Master,4,Technology,2024-01-16,2024-02-11,674,6,Smart Analytics +AI05648,Autonomous Systems Engineer,57600,USD,57600,EX,CT,India,S,Vietnam,100,"Hadoop, PyTorch, Spark",Master,10,Real Estate,2025-01-18,2025-02-19,1769,9.1,DeepTech Ventures +AI05649,Computer Vision Engineer,53542,USD,53542,EN,CT,Ireland,S,Ireland,50,"Scala, Azure, Python",PhD,0,Consulting,2025-03-24,2025-04-19,2480,8.8,Smart Analytics +AI05650,AI Consultant,151442,USD,151442,EX,PT,Finland,L,Chile,0,"Python, Spark, Computer Vision",PhD,15,Technology,2024-12-17,2025-02-25,2014,9.9,Cognitive Computing +AI05651,Data Analyst,113037,USD,113037,SE,CT,South Korea,S,Vietnam,100,"Kubernetes, PyTorch, GCP",Associate,5,Telecommunications,2024-01-26,2024-03-05,1389,7,Smart Analytics +AI05652,AI Consultant,63321,AUD,85483,EN,PT,Australia,M,Australia,50,"Data Visualization, Computer Vision, Docker, R",PhD,0,Energy,2024-03-27,2024-05-19,2054,6.5,Cloud AI Solutions +AI05653,Head of AI,216696,EUR,184192,EX,PT,Netherlands,L,Argentina,100,"R, SQL, Deep Learning, Spark, Linux",Associate,10,Energy,2024-04-11,2024-05-08,2464,5.3,Autonomous Tech +AI05654,AI Consultant,68832,CAD,86040,MI,CT,Canada,S,Canada,0,"Tableau, Linux, TensorFlow, Data Visualization, Hadoop",Bachelor,3,Telecommunications,2024-01-13,2024-01-29,2000,8.1,Predictive Systems +AI05655,AI Product Manager,125853,JPY,13843830,SE,CT,Japan,L,Japan,50,"Scala, R, Docker, Computer Vision",Bachelor,7,Finance,2024-06-17,2024-08-17,645,5.4,Future Systems +AI05656,AI Architect,90307,USD,90307,MI,FL,South Korea,L,South Korea,100,"Git, SQL, GCP, Azure",PhD,2,Telecommunications,2024-03-06,2024-05-15,1785,8.2,Digital Transformation LLC +AI05657,AI Software Engineer,208536,USD,208536,EX,CT,Norway,L,Norway,0,"Computer Vision, MLOps, Git",Bachelor,11,Consulting,2024-11-30,2025-01-27,1876,9.1,Predictive Systems +AI05658,Data Engineer,79479,USD,79479,SE,PT,China,L,Finland,50,"MLOps, PyTorch, Kubernetes",Master,9,Education,2024-02-12,2024-03-25,861,6,Algorithmic Solutions +AI05659,AI Product Manager,145587,JPY,16014570,SE,FL,Japan,S,Japan,50,"SQL, PyTorch, TensorFlow, Hadoop, Tableau",Bachelor,7,Retail,2025-03-07,2025-03-22,1397,9.9,Autonomous Tech +AI05660,Robotics Engineer,237771,USD,237771,EX,PT,South Korea,L,South Korea,50,"Linux, Python, MLOps",Bachelor,15,Education,2025-02-06,2025-04-20,1107,5.9,Quantum Computing Inc +AI05661,AI Specialist,131882,CHF,118694,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Scala, R",Associate,4,Technology,2024-04-21,2024-05-13,1742,7.2,Predictive Systems +AI05662,Principal Data Scientist,194531,USD,194531,SE,PT,Denmark,L,South Korea,100,"PyTorch, Hadoop, Tableau, Azure, TensorFlow",Associate,5,Finance,2024-07-09,2024-08-12,2058,8.9,Smart Analytics +AI05663,Robotics Engineer,170274,CHF,153247,MI,FL,Switzerland,L,Switzerland,0,"SQL, Kubernetes, Scala, Data Visualization, PyTorch",PhD,3,Consulting,2024-04-28,2024-05-22,1146,9.7,DataVision Ltd +AI05664,AI Architect,238256,GBP,178692,EX,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Java, Tableau, Deep Learning",Master,18,Healthcare,2024-01-28,2024-03-03,1005,7.2,Machine Intelligence Group +AI05665,NLP Engineer,98574,USD,98574,MI,FL,United States,S,United States,50,"GCP, Statistics, Hadoop",PhD,4,Finance,2025-03-30,2025-05-12,916,9.1,Machine Intelligence Group +AI05666,Head of AI,84725,EUR,72016,MI,PT,Germany,L,Germany,50,"Java, Scala, Hadoop, Linux, AWS",Master,3,Energy,2024-06-14,2024-07-27,1296,6.4,Quantum Computing Inc +AI05667,AI Consultant,237420,USD,237420,EX,FL,United States,L,United States,50,"PyTorch, NLP, MLOps, Mathematics, Kubernetes",Associate,17,Energy,2025-04-20,2025-06-04,2368,7.6,DataVision Ltd +AI05668,Research Scientist,94852,SGD,123308,MI,CT,Singapore,M,Singapore,0,"TensorFlow, Scala, Kubernetes, NLP, Python",PhD,3,Media,2024-12-25,2025-01-12,1503,9.1,TechCorp Inc +AI05669,NLP Engineer,53187,EUR,45209,EN,PT,Austria,M,Austria,0,"Python, Docker, NLP",Bachelor,1,Government,2024-10-02,2024-11-02,2170,8.4,Cognitive Computing +AI05670,Head of AI,85325,USD,85325,EN,FT,Norway,L,Norway,100,"MLOps, GCP, Kubernetes, Hadoop, SQL",Bachelor,0,Transportation,2024-10-16,2024-11-24,2270,9.4,Autonomous Tech +AI05671,Data Analyst,84861,EUR,72132,MI,PT,France,M,France,100,"Scala, Hadoop, Computer Vision, Data Visualization",Associate,3,Technology,2025-02-26,2025-04-29,1644,8.7,Autonomous Tech +AI05672,Machine Learning Engineer,110677,EUR,94075,MI,CT,Netherlands,M,Netherlands,0,"PyTorch, Docker, Tableau",Master,4,Consulting,2024-06-30,2024-08-16,500,7.2,Digital Transformation LLC +AI05673,Machine Learning Engineer,55583,EUR,47246,EN,FL,France,S,France,0,"Statistics, PyTorch, R",PhD,0,Healthcare,2024-04-19,2024-05-14,602,8.8,Cloud AI Solutions +AI05674,Deep Learning Engineer,103137,SGD,134078,MI,CT,Singapore,S,United Kingdom,100,"R, GCP, SQL",PhD,3,Gaming,2025-03-18,2025-04-20,546,7.8,AI Innovations +AI05675,Autonomous Systems Engineer,94118,SGD,122353,MI,FT,Singapore,M,Singapore,100,"GCP, Docker, PyTorch, SQL",Bachelor,4,Real Estate,2024-05-23,2024-06-13,1065,6.1,Future Systems +AI05676,AI Product Manager,263320,USD,263320,EX,FL,Ireland,L,Ireland,100,"Data Visualization, Azure, Git, Python, Spark",Bachelor,12,Telecommunications,2025-03-11,2025-05-21,1510,8.9,Predictive Systems +AI05677,Principal Data Scientist,81751,USD,81751,EX,FT,China,S,Indonesia,50,"Statistics, Data Visualization, SQL, Python, Tableau",PhD,19,Real Estate,2024-01-16,2024-03-20,2349,9.8,DeepTech Ventures +AI05678,AI Product Manager,69515,USD,69515,EN,PT,Israel,M,Japan,100,"Python, SQL, Tableau, R, AWS",Master,1,Government,2024-05-14,2024-06-03,1662,6,TechCorp Inc +AI05679,AI Consultant,102539,USD,102539,SE,PT,Ireland,M,New Zealand,50,"Linux, TensorFlow, PyTorch, Data Visualization",Associate,7,Technology,2024-06-29,2024-08-26,1816,9.1,Neural Networks Co +AI05680,AI Consultant,83366,EUR,70861,MI,PT,Germany,M,Germany,50,"Python, Computer Vision, AWS",Associate,3,Telecommunications,2024-11-28,2025-01-28,1453,5.1,Digital Transformation LLC +AI05681,Data Analyst,103994,JPY,11439340,MI,CT,Japan,S,Japan,50,"Linux, Scala, R",Bachelor,3,Energy,2025-04-03,2025-05-27,1046,7.6,TechCorp Inc +AI05682,AI Specialist,63790,USD,63790,EN,PT,Ireland,M,Ireland,0,"SQL, Spark, Computer Vision",Associate,1,Technology,2024-05-14,2024-07-11,1573,8,Algorithmic Solutions +AI05683,Computer Vision Engineer,223100,EUR,189635,EX,PT,Netherlands,S,Thailand,100,"AWS, Data Visualization, Tableau, Hadoop, Statistics",Associate,12,Finance,2024-09-23,2024-11-18,698,6.7,Predictive Systems +AI05684,Robotics Engineer,60827,USD,60827,EN,FT,Sweden,S,Sweden,100,"Scala, Spark, Kubernetes, Docker, NLP",Associate,0,Manufacturing,2024-03-04,2024-03-21,1247,7.5,AI Innovations +AI05685,AI Architect,77717,USD,77717,MI,FT,United States,S,Mexico,0,"Hadoop, Scala, TensorFlow",Master,3,Transportation,2024-03-08,2024-05-13,1519,9.4,Machine Intelligence Group +AI05686,Machine Learning Engineer,97963,USD,97963,MI,CT,South Korea,L,Kenya,100,"Git, TensorFlow, Tableau, Data Visualization",Associate,3,Energy,2024-12-13,2025-01-05,2218,5.8,Cognitive Computing +AI05687,Data Engineer,214315,USD,214315,EX,PT,United States,M,United States,0,"PyTorch, Azure, Kubernetes, Deep Learning, TensorFlow",Associate,18,Media,2024-11-08,2024-12-25,1940,6.2,Quantum Computing Inc +AI05688,Autonomous Systems Engineer,71291,USD,71291,EN,FL,Denmark,M,Denmark,100,"Docker, Scala, AWS, Python",Master,0,Consulting,2024-07-27,2024-08-31,1540,9.6,Quantum Computing Inc +AI05689,Data Scientist,87518,USD,87518,EN,CT,United States,L,Vietnam,0,"AWS, PyTorch, Scala, Hadoop",Bachelor,1,Healthcare,2024-12-13,2025-01-04,906,5.9,AI Innovations +AI05690,Machine Learning Researcher,149558,USD,149558,SE,FL,United States,S,United States,0,"Azure, SQL, TensorFlow, Kubernetes",Bachelor,5,Media,2024-07-27,2024-09-12,2478,7.1,AI Innovations +AI05691,AI Consultant,107945,AUD,145726,MI,FT,Australia,M,Australia,0,"Hadoop, Computer Vision, Kubernetes, Tableau, Azure",PhD,2,Manufacturing,2024-04-25,2024-07-02,2267,5.8,Autonomous Tech +AI05692,Machine Learning Engineer,63957,USD,63957,EX,FT,China,S,Australia,50,"Linux, Tableau, TensorFlow, Computer Vision",PhD,12,Education,2024-02-01,2024-03-24,2482,9.6,Autonomous Tech +AI05693,AI Architect,93563,EUR,79529,MI,CT,Germany,S,Germany,0,"Data Visualization, Python, SQL, Kubernetes",Associate,3,Media,2024-06-24,2024-08-24,953,9,Cloud AI Solutions +AI05694,AI Research Scientist,161134,EUR,136964,SE,FT,France,L,France,100,"R, Data Visualization, Python, Docker",PhD,6,Real Estate,2024-08-04,2024-09-01,2303,5.8,Machine Intelligence Group +AI05695,Principal Data Scientist,212931,CAD,266164,EX,FT,Canada,S,New Zealand,0,"SQL, Linux, Python",Master,12,Technology,2024-04-13,2024-05-18,1452,6.8,TechCorp Inc +AI05696,AI Product Manager,119167,USD,119167,MI,CT,Denmark,M,Denmark,100,"Linux, Azure, MLOps, Kubernetes",Master,2,Automotive,2024-04-27,2024-06-12,1621,9.3,DataVision Ltd +AI05697,Head of AI,102382,USD,102382,EN,FT,Denmark,M,Denmark,100,"Tableau, Spark, NLP, PyTorch, Computer Vision",PhD,1,Government,2025-02-21,2025-05-02,1096,5.2,Predictive Systems +AI05698,AI Specialist,69931,USD,69931,MI,PT,Finland,S,Finland,100,"Kubernetes, GCP, Computer Vision, AWS",PhD,4,Transportation,2025-03-25,2025-05-23,1511,5.2,Predictive Systems +AI05699,Autonomous Systems Engineer,61743,SGD,80266,EN,CT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Tableau",PhD,1,Technology,2024-11-28,2025-01-03,1091,10,Predictive Systems +AI05700,AI Product Manager,70132,AUD,94678,MI,FT,Australia,S,Australia,50,"Scala, Data Visualization, Docker, R",Associate,4,Transportation,2024-01-12,2024-02-23,2242,5.7,Digital Transformation LLC +AI05701,Robotics Engineer,96886,JPY,10657460,MI,FT,Japan,S,Japan,0,"Git, Hadoop, SQL, Python, Kubernetes",Master,3,Consulting,2024-03-13,2024-05-22,1366,8.7,Future Systems +AI05702,AI Research Scientist,200782,EUR,170665,EX,PT,Netherlands,M,Switzerland,50,"Linux, Java, Kubernetes, TensorFlow",PhD,15,Consulting,2025-03-07,2025-05-13,840,5.2,Digital Transformation LLC +AI05703,Data Analyst,23579,USD,23579,EN,FL,India,L,India,50,"Java, PyTorch, Statistics, Deep Learning",Associate,0,Transportation,2025-02-04,2025-03-03,1565,9.2,Cloud AI Solutions +AI05704,NLP Engineer,55614,AUD,75079,EN,PT,Australia,M,Australia,0,"Java, Hadoop, NLP, Linux",Bachelor,1,Consulting,2024-12-16,2025-02-18,2492,8,Algorithmic Solutions +AI05705,AI Product Manager,150781,EUR,128164,SE,FL,Germany,M,Nigeria,100,"Spark, Tableau, Hadoop, Computer Vision",Master,5,Retail,2024-07-22,2024-09-02,1421,5.3,Cognitive Computing +AI05706,AI Specialist,131468,EUR,111748,SE,CT,Austria,L,Luxembourg,0,"Kubernetes, PyTorch, MLOps, GCP, R",Master,8,Technology,2024-12-27,2025-01-31,2220,8.5,Advanced Robotics +AI05707,Deep Learning Engineer,72393,EUR,61534,EN,FT,France,M,France,0,"PyTorch, Kubernetes, SQL, Scala",Bachelor,1,Energy,2024-02-10,2024-03-22,2211,9.4,Cloud AI Solutions +AI05708,NLP Engineer,139017,USD,139017,SE,PT,Sweden,L,Sweden,100,"MLOps, Computer Vision, R, PyTorch",Associate,5,Manufacturing,2025-02-27,2025-05-02,1808,9.8,Autonomous Tech +AI05709,Principal Data Scientist,112229,USD,112229,MI,FL,Denmark,S,Denmark,50,"Scala, GCP, SQL, Hadoop, Data Visualization",Bachelor,4,Technology,2024-03-03,2024-05-13,702,8.6,Digital Transformation LLC +AI05710,ML Ops Engineer,88643,USD,88643,MI,FL,South Korea,M,South Korea,100,"MLOps, Data Visualization, Azure, AWS",Associate,4,Manufacturing,2024-12-20,2025-01-16,2308,7.5,Cognitive Computing +AI05711,Head of AI,119522,USD,119522,MI,CT,Denmark,S,United States,0,"Deep Learning, Docker, Git, Mathematics",Associate,4,Finance,2025-01-09,2025-03-08,1799,5.9,Predictive Systems +AI05712,NLP Engineer,146464,EUR,124494,SE,CT,Netherlands,M,Denmark,100,"MLOps, AWS, SQL",PhD,6,Real Estate,2024-05-24,2024-07-21,2415,9.5,Cloud AI Solutions +AI05713,Data Scientist,98192,CAD,122740,SE,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP, R, Computer Vision",PhD,6,Telecommunications,2024-07-25,2024-08-11,1143,9.1,Cloud AI Solutions +AI05714,Machine Learning Engineer,80479,USD,80479,EN,FT,Norway,L,Norway,100,"Kubernetes, NLP, Spark, Deep Learning",Associate,1,Healthcare,2025-04-26,2025-07-02,1630,8.7,Future Systems +AI05715,Data Engineer,152265,EUR,129425,EX,FT,Netherlands,S,Netherlands,50,"MLOps, Python, Computer Vision, Linux, TensorFlow",Master,12,Media,2025-04-16,2025-05-25,1049,9.7,AI Innovations +AI05716,AI Software Engineer,77835,USD,77835,EN,FT,Norway,S,Norway,0,"Azure, Python, GCP, TensorFlow",PhD,1,Technology,2024-01-10,2024-03-11,1316,5.8,Quantum Computing Inc +AI05717,AI Architect,63922,JPY,7031420,EN,FT,Japan,L,Japan,50,"NLP, Python, TensorFlow, Linux",Master,1,Energy,2025-04-21,2025-05-12,1569,8.7,AI Innovations +AI05718,NLP Engineer,257100,JPY,28281000,EX,FL,Japan,L,Finland,0,"TensorFlow, Tableau, Docker, NLP",Associate,15,Automotive,2025-02-04,2025-04-12,876,9.3,DeepTech Ventures +AI05719,Deep Learning Engineer,88350,USD,88350,MI,FT,Finland,L,China,50,"Python, Linux, Statistics, Computer Vision",Associate,4,Transportation,2024-07-04,2024-08-20,986,7.7,Neural Networks Co +AI05720,AI Specialist,99465,USD,99465,MI,FL,Denmark,S,France,50,"GCP, Data Visualization, Spark, R",Bachelor,4,Government,2025-03-31,2025-05-09,1730,5.3,Algorithmic Solutions +AI05721,NLP Engineer,179088,USD,179088,EX,CT,Norway,S,Romania,50,"Python, SQL, Deep Learning, Git, Docker",Bachelor,14,Media,2024-07-11,2024-07-26,1923,8.1,Predictive Systems +AI05722,Data Engineer,159540,USD,159540,SE,FT,Denmark,L,Denmark,100,"Mathematics, Git, NLP",Associate,6,Energy,2024-10-06,2024-11-16,1350,9,AI Innovations +AI05723,Deep Learning Engineer,37477,USD,37477,MI,FT,India,M,India,50,"Spark, Scala, Linux, Deep Learning, SQL",PhD,2,Automotive,2024-05-24,2024-07-26,2369,9.3,Predictive Systems +AI05724,Research Scientist,133739,SGD,173861,MI,PT,Singapore,L,Russia,0,"Computer Vision, AWS, Kubernetes",Associate,4,Education,2025-02-08,2025-02-28,865,7.1,Advanced Robotics +AI05725,AI Research Scientist,373674,CHF,336307,EX,FT,Switzerland,L,Switzerland,50,"R, Python, Statistics, Scala, Deep Learning",Associate,16,Automotive,2024-04-19,2024-05-21,626,9.6,Cloud AI Solutions +AI05726,Head of AI,57593,USD,57593,MI,PT,South Korea,S,China,100,"Docker, Linux, AWS, Scala",Associate,3,Retail,2024-11-01,2024-12-15,1985,8.3,TechCorp Inc +AI05727,Machine Learning Researcher,62998,USD,62998,SE,FT,China,S,China,0,"Statistics, Scala, NLP, MLOps, Azure",Bachelor,7,Real Estate,2024-12-01,2025-02-01,1256,7.4,Machine Intelligence Group +AI05728,Research Scientist,99028,SGD,128736,SE,CT,Singapore,S,Singapore,100,"Docker, Spark, AWS",PhD,5,Retail,2024-12-26,2025-01-29,1673,9.8,Advanced Robotics +AI05729,Data Analyst,283076,USD,283076,EX,CT,Norway,S,Norway,50,"NLP, Deep Learning, Spark, MLOps",Master,15,Finance,2024-01-19,2024-02-05,1350,7.5,Cloud AI Solutions +AI05730,Data Scientist,77013,USD,77013,MI,FL,South Korea,L,South Korea,0,"Statistics, Mathematics, Java",Master,2,Retail,2024-10-12,2024-11-16,916,7.2,TechCorp Inc +AI05731,Computer Vision Engineer,88457,USD,88457,MI,FT,South Korea,L,South Korea,100,"Python, Kubernetes, Spark, GCP",Master,4,Healthcare,2024-09-01,2024-09-19,2182,5.6,Cognitive Computing +AI05732,Machine Learning Researcher,99330,USD,99330,MI,CT,South Korea,L,South Korea,0,"Computer Vision, GCP, Kubernetes, SQL",Bachelor,4,Government,2024-10-21,2024-11-27,2415,9.3,AI Innovations +AI05733,Data Scientist,65665,USD,65665,EN,CT,Israel,S,Israel,0,"Python, Azure, Statistics",PhD,1,Government,2024-10-29,2024-12-23,1506,7.6,Autonomous Tech +AI05734,AI Architect,92187,USD,92187,MI,FT,Israel,M,Israel,0,"Hadoop, NLP, MLOps",PhD,3,Manufacturing,2024-02-20,2024-04-23,1555,5.9,Smart Analytics +AI05735,ML Ops Engineer,72655,USD,72655,MI,FT,Israel,M,Israel,100,"GCP, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2024-11-02,2024-12-22,1742,6.7,DeepTech Ventures +AI05736,ML Ops Engineer,117047,CAD,146309,SE,FL,Canada,M,Canada,100,"Linux, SQL, Computer Vision, Kubernetes, PyTorch",Bachelor,6,Healthcare,2024-07-03,2024-09-06,2314,9,TechCorp Inc +AI05737,Data Analyst,66295,USD,66295,EN,FT,Israel,L,Israel,50,"GCP, Linux, Spark",Master,1,Media,2025-02-12,2025-04-10,1387,5.2,Neural Networks Co +AI05738,AI Specialist,159977,USD,159977,SE,CT,United States,L,United States,100,"SQL, Docker, Mathematics, Computer Vision, AWS",Associate,9,Finance,2025-04-13,2025-06-13,1434,9,Cognitive Computing +AI05739,ML Ops Engineer,213245,EUR,181258,EX,CT,Netherlands,S,Netherlands,100,"SQL, Hadoop, Tableau",Bachelor,17,Finance,2025-03-21,2025-04-22,1998,9,DeepTech Ventures +AI05740,Head of AI,119945,EUR,101953,EX,CT,Austria,S,United States,50,"Java, SQL, Git, Docker",PhD,10,Transportation,2024-02-13,2024-03-11,1193,6.3,Algorithmic Solutions +AI05741,Robotics Engineer,216153,USD,216153,EX,PT,Finland,L,Nigeria,100,"TensorFlow, Python, Data Visualization, Statistics",Master,10,Retail,2024-07-03,2024-07-22,2438,8.4,Smart Analytics +AI05742,Data Analyst,40020,USD,40020,MI,FT,India,L,India,50,"Python, SQL, Computer Vision, Git, Linux",Master,4,Healthcare,2025-03-14,2025-05-26,666,5.6,Neural Networks Co +AI05743,AI Architect,92086,CAD,115108,MI,CT,Canada,L,Switzerland,0,"NLP, Kubernetes, Python, Git",PhD,2,Consulting,2024-04-28,2024-06-23,1486,8.5,Predictive Systems +AI05744,AI Product Manager,200654,GBP,150491,EX,FT,United Kingdom,M,Luxembourg,100,"Git, Java, Scala",Master,19,Consulting,2024-12-13,2025-02-04,1872,9.7,TechCorp Inc +AI05745,Computer Vision Engineer,68829,USD,68829,EN,CT,United States,S,United States,100,"Scala, Hadoop, TensorFlow",PhD,1,Gaming,2024-10-27,2024-12-04,1492,9.3,Cognitive Computing +AI05746,Head of AI,197686,USD,197686,EX,CT,Norway,M,Norway,50,"Kubernetes, Docker, Data Visualization, Git, Hadoop",PhD,17,Energy,2024-03-03,2024-04-24,2251,5.2,Advanced Robotics +AI05747,AI Product Manager,165557,USD,165557,EX,PT,Finland,M,Finland,0,"TensorFlow, Spark, Tableau, Computer Vision, MLOps",Associate,12,Retail,2025-03-19,2025-05-30,1803,5.4,Smart Analytics +AI05748,AI Architect,66906,USD,66906,EN,CT,Ireland,S,Argentina,100,"Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-12-13,2025-02-19,1384,8.8,TechCorp Inc +AI05749,AI Software Engineer,59768,USD,59768,EX,FT,China,S,China,100,"SQL, Linux, Git, Mathematics",PhD,16,Consulting,2024-07-11,2024-08-27,793,8.3,Cognitive Computing +AI05750,AI Architect,139169,GBP,104377,SE,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, GCP, Computer Vision, Azure, Kubernetes",Associate,7,Transportation,2024-08-22,2024-09-10,1739,10,Future Systems +AI05751,NLP Engineer,177662,JPY,19542820,EX,FL,Japan,L,Japan,50,"MLOps, Statistics, PyTorch, Spark, Java",PhD,14,Transportation,2025-02-13,2025-03-14,1326,8.3,Machine Intelligence Group +AI05752,ML Ops Engineer,81894,JPY,9008340,MI,FL,Japan,S,Turkey,0,"Python, TensorFlow, Docker, Mathematics",PhD,2,Manufacturing,2024-12-30,2025-01-24,808,9.2,AI Innovations +AI05753,Computer Vision Engineer,213516,USD,213516,EX,PT,Israel,L,Japan,50,"AWS, Docker, Mathematics, Python",Associate,10,Automotive,2024-12-03,2025-02-11,907,7.4,Algorithmic Solutions +AI05754,Deep Learning Engineer,231165,EUR,196490,EX,FL,Austria,M,Sweden,0,"Python, SQL, Azure",Master,17,Energy,2025-02-03,2025-03-01,1994,9.8,Machine Intelligence Group +AI05755,AI Specialist,110726,AUD,149480,SE,PT,Australia,S,Estonia,50,"Deep Learning, Java, NLP",PhD,8,Transportation,2024-04-27,2024-05-14,2129,5.1,Neural Networks Co +AI05756,Research Scientist,83571,USD,83571,EX,PT,China,L,China,50,"MLOps, PyTorch, Git, Scala, Linux",Master,18,Finance,2024-02-25,2024-04-13,2311,8,Predictive Systems +AI05757,NLP Engineer,232736,USD,232736,EX,FT,Denmark,M,Denmark,0,"Hadoop, Deep Learning, NLP, Python, TensorFlow",Master,17,Healthcare,2024-10-06,2024-12-08,577,6.9,Neural Networks Co +AI05758,Robotics Engineer,127623,AUD,172291,SE,CT,Australia,S,Australia,50,"Data Visualization, Kubernetes, Java, Deep Learning, Docker",Bachelor,7,Transportation,2024-09-21,2024-11-05,2226,6.7,TechCorp Inc +AI05759,Computer Vision Engineer,120233,USD,120233,MI,CT,United States,M,United States,100,"Python, R, Tableau, AWS, Hadoop",Bachelor,4,Consulting,2025-01-25,2025-03-04,2398,8.8,Neural Networks Co +AI05760,NLP Engineer,138054,CAD,172568,EX,FL,Canada,M,Canada,0,"Spark, TensorFlow, PyTorch, NLP, Docker",Master,11,Manufacturing,2024-11-10,2024-12-08,2103,10,Machine Intelligence Group +AI05761,AI Specialist,217066,USD,217066,EX,FL,United States,M,Ukraine,100,"GCP, Scala, Data Visualization",PhD,14,Gaming,2025-01-09,2025-02-23,1157,8.5,Algorithmic Solutions +AI05762,Data Analyst,210737,USD,210737,EX,CT,Israel,S,Sweden,50,"Statistics, Mathematics, PyTorch, AWS, Computer Vision",PhD,10,Government,2024-01-22,2024-04-03,2498,8,Machine Intelligence Group +AI05763,Research Scientist,69613,SGD,90497,EN,PT,Singapore,L,Singapore,50,"Python, GCP, Azure",Master,1,Automotive,2024-03-22,2024-05-16,1729,8.4,Algorithmic Solutions +AI05764,AI Product Manager,93437,USD,93437,MI,FL,Finland,M,Finland,50,"Kubernetes, Python, Mathematics, Docker",PhD,3,Healthcare,2025-01-03,2025-02-24,1095,9.6,Future Systems +AI05765,AI Architect,111139,CHF,100025,MI,FT,Switzerland,M,Czech Republic,100,"Kubernetes, Azure, Data Visualization, Python",Bachelor,2,Retail,2024-01-28,2024-03-14,690,7.8,TechCorp Inc +AI05766,AI Architect,91789,EUR,78021,SE,CT,France,S,Belgium,50,"NLP, SQL, Python, TensorFlow",PhD,6,Manufacturing,2024-07-01,2024-07-21,2003,7.1,TechCorp Inc +AI05767,Deep Learning Engineer,103244,AUD,139379,SE,CT,Australia,M,Australia,50,"Python, TensorFlow, Spark, GCP",Bachelor,5,Finance,2024-07-21,2024-08-08,601,6.1,Future Systems +AI05768,Data Analyst,134116,USD,134116,SE,CT,South Korea,L,South Korea,50,"GCP, Git, Java",Associate,9,Retail,2024-07-27,2024-09-22,2148,9.4,Autonomous Tech +AI05769,Machine Learning Engineer,97581,USD,97581,EX,FT,China,M,China,50,"Spark, AWS, Deep Learning",Associate,10,Retail,2024-06-18,2024-07-12,1179,8.8,Neural Networks Co +AI05770,Autonomous Systems Engineer,62705,USD,62705,SE,FT,China,M,China,100,"Java, PyTorch, AWS, Spark",Associate,8,Media,2024-05-11,2024-06-07,1072,6.8,Autonomous Tech +AI05771,Principal Data Scientist,101330,EUR,86131,MI,CT,Netherlands,M,Netherlands,100,"Kubernetes, AWS, Spark, Computer Vision",Bachelor,2,Retail,2024-12-07,2025-02-01,2469,8.4,Algorithmic Solutions +AI05772,Deep Learning Engineer,96335,USD,96335,MI,FT,Norway,M,Norway,0,"Linux, AWS, Git, Scala",Associate,4,Gaming,2024-06-16,2024-08-18,1862,6.3,Digital Transformation LLC +AI05773,Research Scientist,139068,USD,139068,MI,CT,Norway,L,Norway,50,"PyTorch, Spark, TensorFlow, Deep Learning",Master,4,Telecommunications,2024-10-10,2024-10-25,1147,9.1,Algorithmic Solutions +AI05774,AI Architect,70157,USD,70157,EN,FL,United States,S,Vietnam,100,"Spark, Python, Docker, Tableau",PhD,0,Media,2024-08-31,2024-11-12,623,9.2,Algorithmic Solutions +AI05775,AI Specialist,74222,EUR,63089,MI,CT,Germany,M,Ireland,50,"Data Visualization, Tableau, Computer Vision",Associate,3,Consulting,2024-03-27,2024-04-20,1609,8.5,Quantum Computing Inc +AI05776,Autonomous Systems Engineer,53889,USD,53889,SE,CT,India,M,India,50,"NLP, Python, PyTorch, AWS",PhD,9,Manufacturing,2024-12-13,2025-02-06,1295,7.1,TechCorp Inc +AI05777,AI Consultant,59745,AUD,80656,EN,PT,Australia,S,Australia,0,"AWS, Data Visualization, Linux",PhD,1,Real Estate,2025-01-21,2025-03-04,2003,6.5,Smart Analytics +AI05778,Machine Learning Engineer,93809,USD,93809,MI,CT,Denmark,M,Denmark,0,"SQL, PyTorch, GCP, R, Linux",Bachelor,4,Government,2024-09-07,2024-10-10,500,8.2,Predictive Systems +AI05779,Research Scientist,56388,EUR,47930,EN,FL,Austria,L,South Korea,100,"Data Visualization, Computer Vision, GCP, TensorFlow, Tableau",Associate,1,Real Estate,2024-05-20,2024-07-16,733,8.8,Smart Analytics +AI05780,Machine Learning Researcher,73376,USD,73376,EX,FT,China,S,China,0,"Computer Vision, Git, Hadoop, NLP, Linux",PhD,16,Energy,2024-06-18,2024-07-02,1032,5.5,Digital Transformation LLC +AI05781,NLP Engineer,246014,USD,246014,EX,PT,Finland,L,Finland,0,"AWS, Kubernetes, Git, Java",Bachelor,11,Education,2024-03-09,2024-04-11,1900,8.7,DataVision Ltd +AI05782,Data Engineer,75181,CAD,93976,MI,FT,Canada,M,Canada,100,"Spark, NLP, Python, TensorFlow",Master,4,Finance,2024-12-06,2025-02-06,936,9.9,Cloud AI Solutions +AI05783,Research Scientist,175703,USD,175703,EX,PT,Israel,M,Thailand,0,"Git, Spark, Data Visualization, SQL",Bachelor,16,Retail,2024-07-18,2024-09-04,1971,8.4,TechCorp Inc +AI05784,Deep Learning Engineer,120364,CAD,150455,SE,FT,Canada,M,Portugal,100,"NLP, TensorFlow, Scala",PhD,7,Technology,2024-08-23,2024-10-24,635,5.7,DeepTech Ventures +AI05785,Computer Vision Engineer,76445,USD,76445,MI,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Hadoop, NLP, Statistics",Bachelor,2,Government,2024-06-30,2024-08-24,787,9.2,Digital Transformation LLC +AI05786,AI Software Engineer,93159,CHF,83843,EN,PT,Switzerland,M,Switzerland,50,"Scala, Azure, GCP, SQL, Mathematics",PhD,0,Government,2024-10-20,2024-12-20,1154,8.3,Advanced Robotics +AI05787,Machine Learning Researcher,157430,EUR,133816,SE,FT,Germany,L,Italy,0,"SQL, Spark, TensorFlow, Linux",PhD,5,Real Estate,2024-07-15,2024-09-09,1632,9.9,Predictive Systems +AI05788,NLP Engineer,97775,EUR,83109,MI,FL,Germany,L,Germany,100,"Spark, Statistics, Git",Associate,2,Education,2025-01-05,2025-03-17,1419,8.2,Quantum Computing Inc +AI05789,NLP Engineer,59315,USD,59315,EN,FT,Sweden,S,Thailand,50,"R, Linux, Tableau, Kubernetes, AWS",Bachelor,0,Education,2024-05-24,2024-08-01,2125,9.9,Neural Networks Co +AI05790,AI Product Manager,135321,EUR,115023,SE,FT,France,L,France,50,"Hadoop, Python, Mathematics, Data Visualization",Bachelor,8,Transportation,2024-04-17,2024-06-01,1089,8.6,Smart Analytics +AI05791,AI Software Engineer,54243,SGD,70516,EN,PT,Singapore,S,Czech Republic,100,"TensorFlow, Tableau, Mathematics",Bachelor,0,Telecommunications,2024-01-17,2024-02-11,1715,9,Algorithmic Solutions +AI05792,AI Architect,66510,SGD,86463,EN,PT,Singapore,L,Singapore,0,"NLP, Linux, Statistics",Bachelor,0,Government,2025-02-10,2025-04-16,890,8.8,Autonomous Tech +AI05793,Data Engineer,290571,USD,290571,EX,CT,Norway,M,Norway,50,"R, TensorFlow, Git",Bachelor,11,Healthcare,2024-07-26,2024-08-12,1050,5.6,Cognitive Computing +AI05794,Machine Learning Researcher,174210,USD,174210,SE,CT,United States,L,United States,50,"Java, GCP, Hadoop, Deep Learning",Associate,6,Telecommunications,2024-11-09,2024-12-17,718,5.2,DataVision Ltd +AI05795,Autonomous Systems Engineer,187877,USD,187877,SE,FL,United States,L,Latvia,100,"Git, Data Visualization, SQL",PhD,8,Technology,2024-06-23,2024-07-29,1005,7.8,Cognitive Computing +AI05796,AI Product Manager,238675,EUR,202874,EX,CT,Netherlands,M,Netherlands,100,"Git, Data Visualization, Spark, R, Computer Vision",PhD,12,Energy,2025-01-09,2025-02-26,1576,7.2,Algorithmic Solutions +AI05797,Machine Learning Researcher,115479,EUR,98157,SE,CT,France,L,France,100,"Deep Learning, Azure, PyTorch, Kubernetes",Associate,8,Government,2025-01-01,2025-01-19,883,8.1,Algorithmic Solutions +AI05798,AI Consultant,89054,USD,89054,MI,CT,United States,S,United States,0,"Git, SQL, PyTorch",Associate,3,Healthcare,2024-10-22,2024-11-23,1689,9.2,AI Innovations +AI05799,Deep Learning Engineer,161406,USD,161406,SE,CT,Israel,L,Israel,0,"AWS, Computer Vision, MLOps, Python, Mathematics",Master,5,Finance,2024-03-30,2024-06-04,911,6.6,Advanced Robotics +AI05800,AI Research Scientist,64215,GBP,48161,EN,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, Mathematics, GCP, Scala, NLP",Bachelor,0,Automotive,2024-03-30,2024-05-26,1193,5.7,Future Systems +AI05801,Autonomous Systems Engineer,64511,USD,64511,MI,FL,South Korea,M,Vietnam,100,"Python, TensorFlow, Spark, PyTorch",Associate,4,Real Estate,2024-02-19,2024-04-30,1416,8.6,Digital Transformation LLC +AI05802,Autonomous Systems Engineer,126060,USD,126060,EX,CT,China,L,China,50,"Scala, Docker, GCP, Git",Associate,18,Real Estate,2024-06-27,2024-09-04,2144,6.8,Algorithmic Solutions +AI05803,Autonomous Systems Engineer,54920,USD,54920,EN,CT,South Korea,S,Norway,0,"Data Visualization, Python, Docker, Java",PhD,1,Real Estate,2024-03-28,2024-04-22,510,9,DeepTech Ventures +AI05804,AI Research Scientist,266720,GBP,200040,EX,CT,United Kingdom,M,Hungary,0,"Kubernetes, SQL, Docker, Tableau",Bachelor,16,Telecommunications,2024-04-08,2024-05-19,1513,7.1,DeepTech Ventures +AI05805,Principal Data Scientist,54944,AUD,74174,EN,FL,Australia,M,Australia,50,"Azure, Spark, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-02-10,2024-03-08,708,6.3,DeepTech Ventures +AI05806,AI Product Manager,152987,USD,152987,SE,FL,Norway,S,Norway,100,"NLP, MLOps, Data Visualization",Associate,6,Government,2024-03-09,2024-04-10,1687,8.5,Quantum Computing Inc +AI05807,AI Consultant,158814,CHF,142933,SE,CT,Switzerland,M,Switzerland,50,"Azure, Kubernetes, Linux, Docker, Mathematics",Bachelor,8,Retail,2024-12-27,2025-03-10,1650,9.7,Advanced Robotics +AI05808,AI Software Engineer,92910,USD,92910,EX,CT,China,S,India,100,"MLOps, Hadoop, Spark, Deep Learning, Python",Bachelor,15,Consulting,2024-03-19,2024-04-26,1516,8.9,Machine Intelligence Group +AI05809,Autonomous Systems Engineer,209901,USD,209901,EX,CT,Denmark,L,Denmark,50,"Scala, Java, Azure, Deep Learning",Associate,13,Manufacturing,2024-01-05,2024-02-27,761,6.8,Smart Analytics +AI05810,Computer Vision Engineer,82999,AUD,112049,EN,FL,Australia,L,Australia,0,"Scala, Statistics, Data Visualization",Master,0,Telecommunications,2024-05-28,2024-06-23,2391,9.1,TechCorp Inc +AI05811,Computer Vision Engineer,28848,USD,28848,EN,CT,China,L,Ukraine,50,"Docker, Scala, Linux, Java",Bachelor,1,Energy,2024-03-13,2024-05-21,2267,6.6,Autonomous Tech +AI05812,Computer Vision Engineer,65556,AUD,88501,EN,PT,Australia,M,Latvia,100,"Kubernetes, Java, NLP, AWS",Master,1,Gaming,2024-03-11,2024-04-18,1984,7.5,DataVision Ltd +AI05813,Autonomous Systems Engineer,130176,USD,130176,SE,PT,United States,M,United States,0,"TensorFlow, Spark, Git, Java, AWS",Associate,6,Government,2025-01-31,2025-03-08,789,6.5,Predictive Systems +AI05814,Principal Data Scientist,101126,USD,101126,SE,FT,Finland,M,Philippines,0,"Kubernetes, Docker, SQL, PyTorch",Associate,9,Automotive,2025-01-29,2025-04-11,2420,8.2,Future Systems +AI05815,NLP Engineer,116327,USD,116327,SE,CT,United States,S,United States,100,"SQL, MLOps, Java, AWS, TensorFlow",Bachelor,7,Telecommunications,2024-03-03,2024-03-31,1709,7.6,Cloud AI Solutions +AI05816,AI Consultant,70463,EUR,59894,MI,PT,Austria,M,Japan,100,"Scala, Hadoop, Git, Azure, MLOps",Bachelor,3,Healthcare,2024-07-27,2024-08-23,1950,8.2,Autonomous Tech +AI05817,Machine Learning Engineer,66266,CAD,82833,EN,CT,Canada,M,Canada,0,"Tableau, Python, Kubernetes, Mathematics",Bachelor,1,Telecommunications,2024-12-16,2025-01-09,986,8.2,Quantum Computing Inc +AI05818,Head of AI,61462,EUR,52243,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Python, Spark",Associate,1,Manufacturing,2024-08-25,2024-10-14,1730,8.2,Digital Transformation LLC +AI05819,ML Ops Engineer,169366,USD,169366,EX,PT,Sweden,S,Brazil,50,"GCP, Spark, Tableau",Associate,18,Automotive,2024-12-15,2025-02-01,1988,9.5,Quantum Computing Inc +AI05820,Computer Vision Engineer,128994,JPY,14189340,SE,FL,Japan,L,Japan,100,"PyTorch, Mathematics, Azure",Associate,9,Technology,2024-09-19,2024-10-30,1049,7.5,Algorithmic Solutions +AI05821,Machine Learning Engineer,93837,USD,93837,EN,FT,Norway,M,Norway,50,"Scala, AWS, MLOps",PhD,0,Transportation,2025-02-16,2025-04-11,1859,8.1,Advanced Robotics +AI05822,Robotics Engineer,199989,AUD,269985,EX,FL,Australia,M,Australia,50,"Tableau, Azure, NLP, Linux, Python",Master,11,Technology,2024-10-20,2024-12-26,1214,9.7,Digital Transformation LLC +AI05823,Research Scientist,120387,EUR,102329,SE,FL,France,M,France,0,"Linux, SQL, NLP, PyTorch, Hadoop",Associate,8,Finance,2025-01-17,2025-03-22,2031,6.2,Algorithmic Solutions +AI05824,AI Consultant,73237,EUR,62251,EN,CT,Netherlands,M,Netherlands,100,"MLOps, Hadoop, Scala, Computer Vision, TensorFlow",PhD,1,Energy,2024-03-06,2024-04-10,898,7.5,Predictive Systems +AI05825,Robotics Engineer,201799,EUR,171529,EX,CT,Germany,M,Germany,0,"AWS, PyTorch, Mathematics, TensorFlow",Bachelor,19,Gaming,2024-07-28,2024-08-14,1838,9.7,AI Innovations +AI05826,Deep Learning Engineer,134094,USD,134094,EX,FL,South Korea,S,South Korea,100,"Spark, Tableau, SQL, PyTorch, Computer Vision",Bachelor,15,Education,2024-01-08,2024-02-16,1396,5.3,Algorithmic Solutions +AI05827,Machine Learning Engineer,93152,CHF,83837,MI,CT,Switzerland,S,Norway,0,"TensorFlow, AWS, Spark, Statistics",Associate,4,Finance,2024-08-30,2024-09-15,1329,7.2,Cognitive Computing +AI05828,AI Consultant,50681,CAD,63351,EN,FL,Canada,S,Canada,50,"MLOps, Deep Learning, Linux, Hadoop",PhD,0,Education,2024-03-18,2024-04-17,640,6.9,Smart Analytics +AI05829,Autonomous Systems Engineer,153066,EUR,130106,SE,CT,Netherlands,L,Netherlands,0,"Docker, Computer Vision, Azure, Tableau",Associate,7,Education,2025-02-06,2025-04-06,2226,7.4,Smart Analytics +AI05830,Data Scientist,113891,USD,113891,MI,FT,Norway,L,Germany,0,"Docker, Statistics, Git, Spark",Master,4,Healthcare,2024-01-30,2024-03-15,1612,9.8,Digital Transformation LLC +AI05831,Machine Learning Engineer,182667,CAD,228334,EX,FL,Canada,S,Canada,50,"Data Visualization, Scala, Python, Tableau",PhD,19,Education,2024-02-06,2024-03-27,693,8.4,DeepTech Ventures +AI05832,Deep Learning Engineer,85673,USD,85673,SE,CT,South Korea,M,Finland,0,"SQL, Linux, Python",Master,9,Energy,2024-10-15,2024-11-22,2316,8.3,Smart Analytics +AI05833,ML Ops Engineer,141382,USD,141382,MI,PT,Norway,M,South Korea,50,"TensorFlow, Azure, Kubernetes, Deep Learning, MLOps",Bachelor,4,Healthcare,2025-01-15,2025-02-23,1098,6.7,DeepTech Ventures +AI05834,Research Scientist,104303,CAD,130379,SE,FL,Canada,S,Canada,100,"Kubernetes, Git, Hadoop, TensorFlow",Associate,5,Gaming,2024-08-13,2024-09-14,2000,7,Algorithmic Solutions +AI05835,AI Consultant,105290,EUR,89497,SE,CT,Netherlands,S,Netherlands,0,"Java, PyTorch, Azure, GCP",PhD,6,Technology,2024-09-09,2024-10-16,2185,8.7,TechCorp Inc +AI05836,ML Ops Engineer,110705,EUR,94099,MI,FT,Netherlands,L,United Kingdom,50,"Docker, Data Visualization, PyTorch",Master,2,Automotive,2024-05-18,2024-07-20,1968,9.5,Digital Transformation LLC +AI05837,Autonomous Systems Engineer,98458,USD,98458,SE,FT,South Korea,S,South Korea,0,"Spark, R, Java, Mathematics, Azure",Associate,5,Real Estate,2024-08-21,2024-10-15,2455,6,AI Innovations +AI05838,Computer Vision Engineer,80189,CHF,72170,EN,CT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Azure, Hadoop",Associate,0,Automotive,2024-08-28,2024-10-11,2452,6.4,Advanced Robotics +AI05839,AI Consultant,152024,EUR,129220,EX,FT,France,L,Thailand,0,"Deep Learning, MLOps, Linux, Kubernetes",Bachelor,12,Finance,2024-01-17,2024-03-13,2051,6.3,Algorithmic Solutions +AI05840,Computer Vision Engineer,144136,USD,144136,EX,PT,Sweden,S,Egypt,0,"Git, Kubernetes, AWS",Master,15,Media,2024-10-17,2024-11-25,756,9.7,DataVision Ltd +AI05841,Head of AI,68248,USD,68248,EN,FT,Ireland,M,Ireland,100,"PyTorch, Scala, Computer Vision, AWS, Deep Learning",Bachelor,0,Technology,2025-02-24,2025-04-09,1649,6.8,Algorithmic Solutions +AI05842,Autonomous Systems Engineer,162400,CAD,203000,EX,CT,Canada,M,Canada,0,"R, Kubernetes, Linux, Tableau, Hadoop",PhD,18,Education,2024-06-05,2024-07-24,1538,7.5,Cloud AI Solutions +AI05843,Computer Vision Engineer,271814,EUR,231042,EX,CT,Austria,L,Austria,0,"MLOps, SQL, Linux",Bachelor,12,Energy,2024-11-30,2025-01-31,1677,5.9,Neural Networks Co +AI05844,Autonomous Systems Engineer,145196,USD,145196,SE,PT,Israel,L,Israel,50,"R, SQL, Java",Bachelor,7,Telecommunications,2024-04-26,2024-06-04,1164,6.3,Predictive Systems +AI05845,Machine Learning Researcher,204480,EUR,173808,EX,FT,Netherlands,S,Ghana,100,"Docker, Kubernetes, Spark",Master,16,Gaming,2024-08-08,2024-09-10,858,9.8,Digital Transformation LLC +AI05846,Head of AI,60712,EUR,51605,EN,CT,France,M,France,50,"MLOps, Python, Docker",Master,1,Government,2024-04-29,2024-06-30,579,6.3,Predictive Systems +AI05847,AI Research Scientist,142958,CAD,178698,SE,CT,Canada,L,Latvia,50,"Java, SQL, Data Visualization, Docker",Master,8,Education,2024-08-30,2024-10-14,649,5.9,Predictive Systems +AI05848,Deep Learning Engineer,73847,USD,73847,MI,FL,Ireland,S,Ireland,50,"Git, Deep Learning, Data Visualization, Computer Vision",Master,3,Energy,2024-01-17,2024-02-07,834,5.7,AI Innovations +AI05849,Deep Learning Engineer,44043,USD,44043,MI,PT,India,L,India,50,"Git, Azure, Spark, Kubernetes",Bachelor,3,Transportation,2024-06-19,2024-07-04,1303,5.9,Neural Networks Co +AI05850,AI Product Manager,230859,CHF,207773,SE,CT,Switzerland,L,Switzerland,50,"Azure, TensorFlow, Data Visualization, NLP",PhD,5,Retail,2025-04-23,2025-06-02,2335,7.8,Algorithmic Solutions +AI05851,Principal Data Scientist,31387,USD,31387,MI,FT,India,M,India,0,"Mathematics, Tableau, MLOps, SQL, Linux",Master,3,Government,2025-03-02,2025-03-28,1711,5.1,Quantum Computing Inc +AI05852,AI Consultant,69067,CAD,86334,EN,PT,Canada,M,Israel,100,"Python, TensorFlow, PyTorch, AWS",Master,0,Gaming,2024-05-02,2024-07-02,1204,8.2,Predictive Systems +AI05853,Principal Data Scientist,131432,USD,131432,SE,FT,Sweden,S,Canada,100,"Linux, PyTorch, Deep Learning, Python",Master,9,Gaming,2024-10-19,2024-12-12,2263,6.5,Autonomous Tech +AI05854,AI Consultant,83942,USD,83942,MI,CT,Ireland,M,Ireland,0,"Python, Docker, Linux, Kubernetes, Git",Master,4,Automotive,2024-11-29,2025-01-05,1333,9.9,Advanced Robotics +AI05855,AI Specialist,261743,JPY,28791730,EX,CT,Japan,M,Japan,0,"NLP, Scala, Linux",Bachelor,14,Transportation,2024-08-17,2024-09-14,1461,6.8,Machine Intelligence Group +AI05856,Autonomous Systems Engineer,81198,USD,81198,EN,FL,Finland,L,Finland,100,"Hadoop, SQL, Data Visualization, Tableau",PhD,0,Media,2024-08-27,2024-09-15,1880,10,Smart Analytics +AI05857,AI Consultant,99681,JPY,10964910,MI,PT,Japan,M,Japan,100,"Linux, PyTorch, SQL, Java",PhD,2,Consulting,2024-10-01,2024-11-26,2486,5.6,Future Systems +AI05858,Principal Data Scientist,116363,EUR,98909,MI,CT,Netherlands,L,Netherlands,100,"Java, Python, Computer Vision",Bachelor,4,Automotive,2025-02-26,2025-04-21,1595,6.8,Machine Intelligence Group +AI05859,AI Architect,167056,USD,167056,SE,CT,Denmark,S,Denmark,100,"Java, SQL, Data Visualization, Git, Deep Learning",Master,5,Consulting,2024-03-25,2024-04-11,2492,9.8,Machine Intelligence Group +AI05860,AI Architect,44476,EUR,37805,EN,FT,Austria,S,Austria,50,"Java, Kubernetes, Scala, Python",Bachelor,1,Government,2025-01-16,2025-03-04,1671,8.9,Quantum Computing Inc +AI05861,Data Scientist,85390,AUD,115277,EN,PT,Australia,L,Australia,0,"SQL, Azure, Mathematics, AWS",Master,0,Consulting,2024-04-28,2024-05-24,1172,5,Quantum Computing Inc +AI05862,NLP Engineer,151511,CHF,136360,SE,PT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Tableau, Docker",Bachelor,5,Manufacturing,2024-04-23,2024-06-24,2354,9.9,Advanced Robotics +AI05863,AI Product Manager,112471,JPY,12371810,MI,FT,Japan,L,Nigeria,100,"NLP, Azure, AWS",Associate,4,Healthcare,2025-03-30,2025-04-14,809,5.1,DataVision Ltd +AI05864,ML Ops Engineer,172627,CHF,155364,SE,CT,Switzerland,M,Switzerland,0,"NLP, Tableau, Mathematics",Associate,8,Telecommunications,2024-12-10,2024-12-27,1336,6,DeepTech Ventures +AI05865,NLP Engineer,233363,USD,233363,EX,FT,Finland,L,Finland,0,"SQL, Computer Vision, TensorFlow",Master,10,Retail,2024-04-08,2024-05-18,2008,6.6,Cognitive Computing +AI05866,Machine Learning Researcher,116985,EUR,99437,SE,PT,Austria,S,United Kingdom,100,"Mathematics, Git, Docker, SQL",Bachelor,5,Finance,2025-01-11,2025-02-19,2373,7.7,Algorithmic Solutions +AI05867,Computer Vision Engineer,184253,GBP,138190,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Java, Linux",Bachelor,6,Finance,2024-05-01,2024-07-05,2168,7.1,Cloud AI Solutions +AI05868,AI Specialist,118246,USD,118246,MI,FL,Norway,S,Sweden,50,"Linux, SQL, Mathematics",PhD,4,Education,2024-07-12,2024-08-04,1005,7.9,Machine Intelligence Group +AI05869,AI Software Engineer,173631,CHF,156268,SE,FT,Switzerland,L,Austria,100,"MLOps, Git, Azure, NLP, Statistics",Bachelor,5,Real Estate,2025-01-31,2025-03-19,1567,9.5,Digital Transformation LLC +AI05870,Computer Vision Engineer,105596,USD,105596,MI,PT,Finland,L,Finland,0,"Azure, Scala, Java, Kubernetes",Associate,2,Automotive,2024-12-26,2025-01-13,2408,9.6,Autonomous Tech +AI05871,AI Product Manager,239497,USD,239497,EX,CT,Finland,L,Finland,0,"R, Tableau, Kubernetes",PhD,18,Media,2024-04-12,2024-05-03,1848,7.6,Predictive Systems +AI05872,Research Scientist,60880,USD,60880,EN,FT,South Korea,M,Mexico,50,"SQL, Deep Learning, Hadoop, GCP, PyTorch",Master,0,Gaming,2024-02-14,2024-04-08,1842,6.6,Smart Analytics +AI05873,Machine Learning Researcher,192915,CHF,173624,EX,FT,Switzerland,S,Switzerland,50,"MLOps, Azure, Spark, Python, PyTorch",Associate,14,Government,2024-08-06,2024-09-05,1358,9.1,DataVision Ltd +AI05874,NLP Engineer,62398,USD,62398,MI,FT,Israel,S,Israel,0,"AWS, Linux, Deep Learning, R",Bachelor,2,Gaming,2025-03-18,2025-04-08,1025,9.2,Predictive Systems +AI05875,Machine Learning Researcher,87874,USD,87874,MI,CT,Sweden,S,Sweden,0,"Hadoop, NLP, SQL, Kubernetes",Bachelor,2,Healthcare,2024-02-13,2024-03-15,2305,7.8,Future Systems +AI05876,Computer Vision Engineer,76770,GBP,57578,EN,FL,United Kingdom,L,United Kingdom,0,"Python, Azure, SQL",PhD,0,Healthcare,2024-03-21,2024-05-20,669,9.3,Cognitive Computing +AI05877,AI Software Engineer,134200,EUR,114070,SE,CT,France,M,France,0,"Python, TensorFlow, Tableau, SQL",PhD,5,Real Estate,2024-04-15,2024-05-19,1184,8.2,Cloud AI Solutions +AI05878,Machine Learning Engineer,120552,EUR,102469,SE,CT,Netherlands,S,Netherlands,100,"R, Java, AWS, Computer Vision, GCP",Associate,7,Consulting,2024-05-11,2024-06-03,2434,6.5,Smart Analytics +AI05879,AI Specialist,52784,USD,52784,EN,FL,Sweden,S,Sweden,100,"NLP, Kubernetes, SQL, TensorFlow, Tableau",Associate,1,Gaming,2024-07-31,2024-09-23,1275,7.3,Neural Networks Co +AI05880,AI Product Manager,70428,USD,70428,EN,PT,Israel,L,Israel,0,"Hadoop, R, Deep Learning, NLP, GCP",PhD,1,Government,2024-04-25,2024-05-14,1514,8.1,Advanced Robotics +AI05881,Autonomous Systems Engineer,80363,JPY,8839930,MI,CT,Japan,M,France,100,"AWS, Spark, SQL",Associate,3,Transportation,2024-04-04,2024-05-15,1293,5.9,DeepTech Ventures +AI05882,Machine Learning Engineer,168502,CAD,210628,EX,CT,Canada,L,South Africa,0,"Hadoop, Kubernetes, Java, Mathematics",Master,16,Education,2024-08-17,2024-09-23,1036,9.5,Autonomous Tech +AI05883,NLP Engineer,95415,USD,95415,MI,FT,United States,S,United States,50,"Docker, Scala, Git, Tableau, GCP",Associate,2,Technology,2024-08-06,2024-09-26,1802,9.8,TechCorp Inc +AI05884,Principal Data Scientist,57820,GBP,43365,EN,FL,United Kingdom,S,United Kingdom,100,"GCP, SQL, PyTorch",Bachelor,1,Energy,2024-01-18,2024-02-03,1681,9.2,Autonomous Tech +AI05885,AI Consultant,274165,JPY,30158150,EX,FT,Japan,L,Ukraine,100,"Docker, Python, Spark, Git",Master,16,Automotive,2025-01-30,2025-03-16,2388,7.6,Future Systems +AI05886,ML Ops Engineer,242363,USD,242363,EX,FL,Israel,L,Israel,50,"PyTorch, SQL, Linux, Docker, Azure",Bachelor,16,Manufacturing,2024-10-03,2024-10-24,934,8.1,Future Systems +AI05887,AI Consultant,182784,SGD,237619,EX,CT,Singapore,L,Latvia,0,"MLOps, Kubernetes, NLP, Git, Hadoop",Bachelor,18,Media,2024-01-03,2024-02-27,972,5.2,Advanced Robotics +AI05888,AI Architect,76429,SGD,99358,MI,CT,Singapore,S,Singapore,100,"Computer Vision, Hadoop, Tableau, Spark, Data Visualization",Associate,3,Education,2024-05-11,2024-07-12,1395,8.9,Quantum Computing Inc +AI05889,AI Product Manager,66004,USD,66004,SE,FL,China,L,China,50,"Statistics, Python, Data Visualization, MLOps, TensorFlow",Bachelor,7,Media,2024-01-21,2024-02-19,503,6.2,Machine Intelligence Group +AI05890,Principal Data Scientist,151148,GBP,113361,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Docker, Data Visualization, Computer Vision, Azure",Bachelor,7,Manufacturing,2024-10-21,2024-12-30,1588,9.1,Predictive Systems +AI05891,Data Engineer,168460,USD,168460,EX,FT,South Korea,S,Argentina,100,"Docker, Hadoop, Git, PyTorch, Deep Learning",Bachelor,14,Real Estate,2025-01-01,2025-03-05,1317,8.4,Smart Analytics +AI05892,AI Architect,124855,USD,124855,EX,FT,Israel,S,Israel,0,"Git, Python, AWS",Master,16,Education,2024-07-16,2024-09-21,879,6,Machine Intelligence Group +AI05893,Autonomous Systems Engineer,154883,CHF,139395,MI,FT,Switzerland,M,Switzerland,50,"Python, Spark, Kubernetes",PhD,4,Media,2024-10-25,2025-01-05,1623,6.2,Digital Transformation LLC +AI05894,Robotics Engineer,241392,EUR,205183,EX,PT,Austria,L,Austria,50,"Git, GCP, Linux",Associate,18,Gaming,2025-01-11,2025-01-26,2393,7.9,Advanced Robotics +AI05895,AI Specialist,147818,EUR,125645,EX,CT,France,S,Czech Republic,50,"R, Tableau, Kubernetes, SQL, Deep Learning",Bachelor,16,Transportation,2024-05-11,2024-06-26,921,5.9,Quantum Computing Inc +AI05896,Computer Vision Engineer,89182,USD,89182,EN,CT,Ireland,L,Ireland,50,"PyTorch, Hadoop, Python, Deep Learning, MLOps",PhD,0,Media,2025-02-07,2025-03-25,575,6.5,Cognitive Computing +AI05897,Robotics Engineer,48483,USD,48483,EN,FT,South Korea,S,South Korea,50,"Python, Data Visualization, Spark",PhD,1,Automotive,2025-03-07,2025-04-02,1954,6.1,Advanced Robotics +AI05898,Machine Learning Engineer,39290,USD,39290,MI,CT,China,M,Argentina,100,"Scala, Hadoop, NLP",Master,4,Finance,2025-02-08,2025-03-07,2097,9.5,DataVision Ltd +AI05899,Data Analyst,60878,EUR,51746,EN,FT,Austria,L,Austria,50,"Git, Java, TensorFlow, Statistics",Bachelor,1,Energy,2024-09-18,2024-11-01,639,7.1,Autonomous Tech +AI05900,Computer Vision Engineer,232706,JPY,25597660,EX,PT,Japan,S,Japan,50,"Python, TensorFlow, Kubernetes, Azure, Data Visualization",PhD,14,Real Estate,2024-06-23,2024-08-05,1494,6.7,Quantum Computing Inc +AI05901,AI Research Scientist,52076,EUR,44265,EN,PT,Austria,M,Ireland,50,"Statistics, TensorFlow, SQL, MLOps",Bachelor,0,Technology,2024-09-19,2024-10-07,971,8.7,Future Systems +AI05902,Data Engineer,198461,CAD,248076,EX,PT,Canada,M,Canada,50,"Java, Kubernetes, PyTorch, Statistics",Associate,11,Finance,2024-04-16,2024-06-13,580,5.6,Predictive Systems +AI05903,Computer Vision Engineer,37606,USD,37606,EN,PT,China,L,China,100,"AWS, Git, SQL",PhD,0,Telecommunications,2024-04-03,2024-05-26,1982,7.8,Digital Transformation LLC +AI05904,AI Consultant,238598,EUR,202808,EX,FT,France,L,France,100,"Linux, Git, Spark",Master,13,Retail,2025-04-15,2025-05-12,567,9,TechCorp Inc +AI05905,AI Research Scientist,117613,EUR,99971,MI,FL,France,L,France,100,"Azure, Kubernetes, Tableau, Computer Vision, Deep Learning",Master,4,Energy,2024-11-25,2024-12-25,1812,8.4,Quantum Computing Inc +AI05906,AI Product Manager,296254,USD,296254,EX,FT,Norway,S,Norway,0,"Python, TensorFlow, PyTorch, Computer Vision",Bachelor,14,Consulting,2024-09-17,2024-11-04,2170,6.2,Quantum Computing Inc +AI05907,AI Product Manager,118508,EUR,100732,SE,FL,Netherlands,S,Netherlands,50,"Kubernetes, Linux, NLP",Associate,7,Government,2025-03-21,2025-05-21,1770,9.9,Digital Transformation LLC +AI05908,Research Scientist,90559,EUR,76975,MI,FT,Germany,M,Germany,50,"Spark, TensorFlow, Git, Mathematics",Bachelor,3,Telecommunications,2024-11-13,2024-12-23,1180,6.2,Machine Intelligence Group +AI05909,NLP Engineer,194311,JPY,21374210,EX,CT,Japan,M,Japan,0,"MLOps, GCP, AWS, Azure, Git",Associate,11,Retail,2025-02-19,2025-05-01,953,7.7,Advanced Robotics +AI05910,Robotics Engineer,96127,USD,96127,MI,FL,Ireland,S,Ireland,0,"Linux, SQL, Data Visualization, PyTorch",Master,3,Media,2025-01-02,2025-02-18,1209,7.8,Advanced Robotics +AI05911,Research Scientist,237774,AUD,320995,EX,FT,Australia,L,Australia,100,"R, Linux, Mathematics, Java",Bachelor,19,Finance,2025-01-23,2025-02-14,2373,7.3,TechCorp Inc +AI05912,AI Product Manager,114455,JPY,12590050,SE,PT,Japan,S,Russia,50,"GCP, Data Visualization, Scala, PyTorch",Associate,5,Gaming,2024-04-14,2024-06-19,1943,9,Quantum Computing Inc +AI05913,AI Specialist,70786,CHF,63707,EN,CT,Switzerland,S,Switzerland,0,"R, Java, Azure, Computer Vision",PhD,0,Finance,2025-03-20,2025-04-19,699,5.4,Autonomous Tech +AI05914,AI Software Engineer,38502,USD,38502,MI,FL,China,M,China,50,"GCP, PyTorch, Data Visualization, TensorFlow",Associate,3,Manufacturing,2024-07-19,2024-09-11,776,9.1,Neural Networks Co +AI05915,AI Architect,75059,USD,75059,MI,CT,South Korea,S,South Korea,50,"Git, SQL, MLOps, Mathematics",PhD,3,Education,2024-10-14,2024-12-16,988,5.1,Quantum Computing Inc +AI05916,AI Research Scientist,22820,USD,22820,EN,FL,India,M,India,100,"MLOps, PyTorch, Tableau, AWS, Scala",Associate,1,Consulting,2024-01-17,2024-03-15,2336,7.6,Autonomous Tech +AI05917,NLP Engineer,88433,USD,88433,MI,FL,Israel,S,Israel,0,"Computer Vision, Docker, Mathematics, AWS",PhD,4,Gaming,2024-11-30,2025-01-15,1395,5.4,TechCorp Inc +AI05918,AI Product Manager,202400,AUD,273240,EX,PT,Australia,S,Australia,50,"Python, Azure, Deep Learning",Master,14,Telecommunications,2024-12-06,2025-01-03,636,6,TechCorp Inc +AI05919,ML Ops Engineer,158886,EUR,135053,EX,FT,France,S,Chile,50,"Spark, Linux, NLP",Bachelor,15,Gaming,2024-11-08,2025-01-16,1540,9,Autonomous Tech +AI05920,AI Specialist,101963,EUR,86669,MI,CT,Netherlands,L,Netherlands,50,"Data Visualization, SQL, Python, Spark, Deep Learning",Master,2,Education,2025-04-20,2025-05-16,1011,5.9,Advanced Robotics +AI05921,AI Consultant,86650,USD,86650,MI,FT,Finland,M,Finland,50,"Kubernetes, Git, Azure, NLP, Scala",PhD,4,Manufacturing,2024-08-22,2024-10-31,1975,8.3,Smart Analytics +AI05922,AI Software Engineer,263809,AUD,356142,EX,FT,Australia,L,Ghana,50,"Scala, Python, Computer Vision",Master,13,Gaming,2025-04-28,2025-06-15,512,7.1,Algorithmic Solutions +AI05923,AI Architect,92448,USD,92448,MI,CT,United States,M,United States,0,"GCP, R, PyTorch, SQL",Bachelor,4,Gaming,2024-04-06,2024-04-21,501,6.8,Machine Intelligence Group +AI05924,Machine Learning Engineer,209496,JPY,23044560,EX,FL,Japan,S,Japan,100,"TensorFlow, Spark, Computer Vision, Linux",Master,18,Government,2025-02-07,2025-02-25,1382,7.2,Autonomous Tech +AI05925,Robotics Engineer,72371,AUD,97701,MI,CT,Australia,M,Australia,0,"TensorFlow, Docker, Computer Vision, Linux",Master,4,Telecommunications,2024-12-03,2025-01-12,899,6.9,Future Systems +AI05926,AI Consultant,21755,USD,21755,EN,FL,India,S,India,0,"Azure, TensorFlow, Tableau, Mathematics, PyTorch",Associate,0,Finance,2024-11-27,2025-01-21,1420,8.1,Autonomous Tech +AI05927,Data Engineer,92976,USD,92976,MI,PT,Sweden,M,Sweden,0,"Tableau, Mathematics, Scala, Computer Vision",PhD,3,Automotive,2025-03-01,2025-04-16,900,8.9,Algorithmic Solutions +AI05928,Machine Learning Engineer,148362,AUD,200289,SE,CT,Australia,L,Belgium,100,"Python, Deep Learning, Spark, Mathematics",Bachelor,6,Retail,2024-12-27,2025-01-25,841,6.3,DataVision Ltd +AI05929,Data Analyst,50796,AUD,68575,EN,FL,Australia,S,Australia,100,"SQL, Kubernetes, MLOps",PhD,0,Transportation,2025-04-28,2025-06-12,1502,7,Digital Transformation LLC +AI05930,Autonomous Systems Engineer,123224,AUD,166352,SE,CT,Australia,L,Australia,100,"Python, Kubernetes, Data Visualization, Java",PhD,5,Finance,2024-12-08,2025-01-05,2333,8.8,Predictive Systems +AI05931,Principal Data Scientist,230556,JPY,25361160,EX,FT,Japan,M,Japan,100,"Git, SQL, Scala, MLOps",PhD,18,Telecommunications,2025-02-08,2025-03-25,2163,7.1,Autonomous Tech +AI05932,AI Research Scientist,148164,USD,148164,SE,CT,Denmark,M,Denmark,100,"Java, Hadoop, Mathematics",Associate,6,Retail,2025-02-26,2025-03-31,606,8,Advanced Robotics +AI05933,AI Research Scientist,80479,USD,80479,MI,FL,Finland,S,Poland,0,"Linux, Docker, NLP, Kubernetes, Tableau",Master,4,Energy,2024-05-31,2024-07-12,2043,6.1,Machine Intelligence Group +AI05934,Machine Learning Engineer,109612,USD,109612,SE,PT,Sweden,M,Argentina,50,"Python, Data Visualization, Git, Spark, GCP",Bachelor,6,Transportation,2024-06-27,2024-08-13,1783,10,Neural Networks Co +AI05935,Research Scientist,194931,JPY,21442410,EX,FT,Japan,M,Japan,0,"Azure, Python, Computer Vision",Master,10,Media,2024-07-07,2024-09-13,799,5.7,Quantum Computing Inc +AI05936,Head of AI,111273,SGD,144655,SE,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Docker, Data Visualization",Associate,5,Healthcare,2024-10-12,2024-11-19,893,6.7,Cloud AI Solutions +AI05937,Computer Vision Engineer,52668,EUR,44768,EN,FT,Austria,S,Australia,100,"TensorFlow, Kubernetes, GCP",Associate,0,Education,2025-02-17,2025-03-17,2461,7.1,Algorithmic Solutions +AI05938,AI Specialist,190969,EUR,162324,EX,FL,Netherlands,S,Canada,0,"Docker, Java, Mathematics, PyTorch, TensorFlow",Master,14,Media,2024-02-13,2024-03-31,1311,6.6,Advanced Robotics +AI05939,Research Scientist,211110,CHF,189999,EX,FT,Switzerland,S,Switzerland,100,"SQL, Git, Tableau, Statistics",Associate,14,Energy,2025-03-04,2025-05-09,1747,8.1,Cloud AI Solutions +AI05940,Data Scientist,99999,CHF,89999,EN,FL,Switzerland,S,Switzerland,50,"PyTorch, Linux, Hadoop",Associate,0,Real Estate,2025-04-11,2025-05-13,788,9.6,Neural Networks Co +AI05941,AI Software Engineer,108942,USD,108942,MI,CT,Norway,L,Norway,50,"Linux, Kubernetes, Python, TensorFlow",Bachelor,4,Government,2024-12-09,2025-01-16,926,7.4,Neural Networks Co +AI05942,ML Ops Engineer,131962,AUD,178149,SE,CT,Australia,S,Australia,50,"Java, TensorFlow, Docker, GCP",Associate,9,Gaming,2024-03-14,2024-04-20,550,7.8,Predictive Systems +AI05943,Computer Vision Engineer,76651,EUR,65153,MI,FL,Austria,S,Austria,100,"AWS, Tableau, Kubernetes",Associate,2,Consulting,2024-10-07,2024-11-28,2276,9.3,DataVision Ltd +AI05944,Deep Learning Engineer,98325,USD,98325,EN,PT,Norway,L,Sweden,0,"MLOps, GCP, Python, Mathematics, TensorFlow",Master,1,Media,2024-02-23,2024-03-10,534,5.5,Quantum Computing Inc +AI05945,Robotics Engineer,62079,USD,62079,SE,FL,China,M,China,100,"Scala, Git, Kubernetes, SQL",Master,8,Healthcare,2024-03-28,2024-04-23,1221,8.8,Advanced Robotics +AI05946,ML Ops Engineer,95740,USD,95740,EN,CT,Denmark,L,Denmark,0,"NLP, Spark, SQL, Python",Bachelor,1,Gaming,2025-01-20,2025-03-21,1209,6.5,Future Systems +AI05947,AI Product Manager,105725,USD,105725,SE,CT,Finland,S,Norway,100,"Spark, Git, Linux",PhD,6,Telecommunications,2025-02-16,2025-03-11,615,10,Advanced Robotics +AI05948,Robotics Engineer,187160,CHF,168444,SE,PT,Switzerland,M,Sweden,0,"Python, Git, TensorFlow",PhD,9,Gaming,2024-03-19,2024-04-02,2451,8.5,Autonomous Tech +AI05949,Principal Data Scientist,222856,USD,222856,EX,CT,Ireland,M,Ireland,0,"Python, Data Visualization, TensorFlow, Scala",Bachelor,14,Government,2025-04-01,2025-05-13,1792,8.4,AI Innovations +AI05950,Head of AI,73259,USD,73259,MI,FT,South Korea,S,South Korea,0,"Git, Java, Python",Master,2,Finance,2024-04-16,2024-06-28,1797,5.5,DataVision Ltd +AI05951,Data Engineer,117240,USD,117240,SE,PT,Ireland,S,Ireland,50,"GCP, R, Deep Learning, Tableau",Associate,7,Technology,2024-09-19,2024-11-13,2169,6,Algorithmic Solutions +AI05952,AI Product Manager,124299,USD,124299,SE,FT,Finland,M,Finland,50,"TensorFlow, Python, Mathematics, Statistics, AWS",PhD,8,Finance,2024-04-16,2024-05-04,2498,7,Autonomous Tech +AI05953,Robotics Engineer,67930,EUR,57741,EN,PT,Netherlands,S,Netherlands,50,"SQL, AWS, Data Visualization, R",Master,0,Media,2024-11-19,2024-12-12,663,6.2,Machine Intelligence Group +AI05954,NLP Engineer,85388,EUR,72580,EN,FT,Germany,L,Germany,100,"Java, Azure, Hadoop, Spark",Bachelor,1,Finance,2024-03-16,2024-04-17,610,7.8,Advanced Robotics +AI05955,Machine Learning Researcher,42537,USD,42537,EN,CT,South Korea,S,South Korea,50,"GCP, Kubernetes, Python, Azure, Statistics",Bachelor,1,Manufacturing,2025-02-22,2025-04-25,2004,6.3,Neural Networks Co +AI05956,AI Software Engineer,109665,CAD,137081,SE,FT,Canada,M,Canada,100,"Java, Kubernetes, Mathematics",PhD,9,Real Estate,2024-10-03,2024-12-02,2250,7.3,Neural Networks Co +AI05957,Data Scientist,78478,USD,78478,EN,FT,Norway,M,China,50,"Mathematics, Kubernetes, Docker, Azure, Scala",Associate,1,Automotive,2024-06-28,2024-08-16,1775,6,DataVision Ltd +AI05958,Principal Data Scientist,127696,USD,127696,SE,FT,Finland,L,Finland,0,"Azure, Mathematics, Linux, MLOps, Tableau",Master,5,Gaming,2024-08-14,2024-09-26,610,9.3,Neural Networks Co +AI05959,AI Product Manager,75623,USD,75623,MI,PT,South Korea,S,South Korea,0,"Scala, Kubernetes, Git",PhD,3,Transportation,2024-03-03,2024-04-22,2215,9.3,Cognitive Computing +AI05960,Deep Learning Engineer,221113,AUD,298503,EX,FT,Australia,L,Australia,0,"AWS, Spark, MLOps, Python",Master,19,Gaming,2024-11-03,2024-12-24,1616,5.9,TechCorp Inc +AI05961,Deep Learning Engineer,171238,CAD,214048,EX,CT,Canada,L,Canada,50,"PyTorch, Spark, Tableau, MLOps",Bachelor,14,Automotive,2025-02-05,2025-04-08,1948,9.9,Digital Transformation LLC +AI05962,Robotics Engineer,201912,USD,201912,EX,FT,Israel,L,Israel,100,"GCP, R, PyTorch, Spark, Mathematics",PhD,18,Energy,2025-03-11,2025-04-03,1298,5.7,DataVision Ltd +AI05963,AI Research Scientist,205861,USD,205861,EX,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Kubernetes, Azure, Tableau",Bachelor,15,Media,2025-04-16,2025-06-02,1682,7,Cloud AI Solutions +AI05964,Deep Learning Engineer,302543,USD,302543,EX,PT,Norway,L,Norway,0,"Python, Azure, TensorFlow",PhD,12,Automotive,2024-04-26,2024-05-31,582,8.1,Machine Intelligence Group +AI05965,ML Ops Engineer,115521,EUR,98193,MI,PT,Austria,L,Austria,0,"Azure, Git, Scala, Java",PhD,4,Telecommunications,2024-05-11,2024-07-13,2101,9.5,Cognitive Computing +AI05966,Data Engineer,50057,USD,50057,SE,PT,China,M,China,100,"PyTorch, Tableau, TensorFlow, Azure",Bachelor,9,Retail,2024-03-05,2024-05-12,722,9.3,Cloud AI Solutions +AI05967,Computer Vision Engineer,139280,EUR,118388,SE,CT,Austria,M,Austria,0,"GCP, PyTorch, Data Visualization, Statistics, R",Associate,9,Real Estate,2024-07-06,2024-08-12,2434,6.5,Neural Networks Co +AI05968,AI Research Scientist,80202,USD,80202,EN,CT,Denmark,S,Denmark,0,"Spark, SQL, R, Deep Learning",PhD,1,Government,2024-01-15,2024-03-19,1892,8.2,TechCorp Inc +AI05969,Computer Vision Engineer,115152,USD,115152,SE,PT,Ireland,S,Ireland,100,"Spark, Git, NLP",Associate,7,Media,2024-01-15,2024-02-29,1179,7.3,AI Innovations +AI05970,Deep Learning Engineer,104936,SGD,136417,MI,FL,Singapore,M,Singapore,50,"Java, AWS, PyTorch",Associate,3,Automotive,2024-11-07,2025-01-05,1188,6.7,Future Systems +AI05971,Robotics Engineer,292055,USD,292055,EX,PT,Norway,L,Norway,100,"Kubernetes, Git, Computer Vision, Deep Learning, Mathematics",Master,10,Media,2025-01-20,2025-02-08,1589,9.8,Algorithmic Solutions +AI05972,ML Ops Engineer,129611,USD,129611,SE,PT,Sweden,S,Sweden,100,"AWS, Hadoop, NLP",Bachelor,8,Real Estate,2024-03-02,2024-04-23,1529,8.9,Autonomous Tech +AI05973,Computer Vision Engineer,56599,USD,56599,SE,CT,China,L,China,100,"Python, MLOps, Data Visualization, Deep Learning, R",Bachelor,9,Education,2024-11-23,2024-12-13,2269,7.7,Predictive Systems +AI05974,AI Software Engineer,66137,CAD,82671,MI,FL,Canada,S,Italy,0,"Kubernetes, AWS, Azure",PhD,3,Real Estate,2024-02-23,2024-04-28,508,5.8,DeepTech Ventures +AI05975,AI Specialist,83658,CAD,104573,MI,FT,Canada,L,Canada,0,"R, SQL, PyTorch, NLP",PhD,2,Gaming,2025-04-21,2025-05-23,1619,6.4,Autonomous Tech +AI05976,Autonomous Systems Engineer,197361,USD,197361,SE,FL,Denmark,L,Denmark,100,"Statistics, PyTorch, Kubernetes",PhD,7,Finance,2024-02-04,2024-03-26,1427,8.2,TechCorp Inc +AI05977,AI Architect,283431,EUR,240916,EX,PT,Germany,L,Germany,100,"Computer Vision, Kubernetes, R",Associate,19,Technology,2024-01-03,2024-02-29,2104,5,Machine Intelligence Group +AI05978,Head of AI,83530,JPY,9188300,EN,FT,Japan,L,Japan,0,"Spark, Java, Hadoop, Scala",Bachelor,1,Finance,2024-01-02,2024-02-01,629,8,Predictive Systems +AI05979,NLP Engineer,197715,EUR,168058,EX,FL,France,M,France,0,"Python, Linux, Hadoop",Associate,10,Energy,2025-03-05,2025-04-22,2465,8.4,DeepTech Ventures +AI05980,NLP Engineer,88355,EUR,75102,MI,FL,Netherlands,S,Portugal,100,"Data Visualization, Azure, R, MLOps",Master,3,Real Estate,2024-11-27,2024-12-26,2128,7.7,Autonomous Tech +AI05981,Data Analyst,30619,USD,30619,EN,PT,India,L,India,50,"AWS, Linux, Spark, Java",Master,1,Finance,2024-03-27,2024-05-02,1811,9.9,Cloud AI Solutions +AI05982,NLP Engineer,206289,EUR,175346,EX,FL,Austria,S,Netherlands,0,"Scala, MLOps, NLP",Associate,14,Education,2024-09-03,2024-10-03,1611,8.5,Autonomous Tech +AI05983,Head of AI,27137,USD,27137,EN,CT,China,M,Russia,100,"NLP, Git, Hadoop, Computer Vision, Scala",Master,0,Energy,2025-01-14,2025-03-11,1238,5.4,Advanced Robotics +AI05984,Data Engineer,107037,CAD,133796,SE,FL,Canada,M,Canada,0,"GCP, Scala, NLP, Spark",Bachelor,5,Retail,2025-04-30,2025-06-04,2340,6.8,Neural Networks Co +AI05985,NLP Engineer,134388,USD,134388,SE,FL,South Korea,L,Kenya,50,"GCP, Docker, Python",Associate,6,Manufacturing,2024-06-26,2024-08-27,1415,6.3,Cognitive Computing +AI05986,Data Analyst,154970,EUR,131725,SE,PT,Netherlands,M,Netherlands,0,"Tableau, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-02-17,2024-03-25,1795,5.9,Cloud AI Solutions +AI05987,Autonomous Systems Engineer,127560,USD,127560,MI,CT,United States,L,United States,0,"GCP, AWS, Hadoop",Bachelor,4,Healthcare,2024-02-01,2024-02-26,727,6.2,Digital Transformation LLC +AI05988,Head of AI,71171,AUD,96081,EN,FT,Australia,S,Belgium,100,"Git, SQL, Azure, Spark, Scala",PhD,0,Finance,2024-08-20,2024-09-17,608,8.1,Neural Networks Co +AI05989,ML Ops Engineer,249331,USD,249331,EX,FL,United States,M,United States,0,"Scala, Kubernetes, Mathematics, Python",Bachelor,12,Telecommunications,2024-02-20,2024-04-13,1618,8.7,DataVision Ltd +AI05990,Research Scientist,130515,SGD,169670,SE,PT,Singapore,S,Singapore,0,"NLP, Deep Learning, Statistics",Associate,6,Manufacturing,2025-04-01,2025-05-16,2354,7,TechCorp Inc +AI05991,ML Ops Engineer,57678,EUR,49026,EN,FT,Austria,M,Austria,0,"Statistics, TensorFlow, Data Visualization, Mathematics, Computer Vision",Bachelor,1,Government,2024-05-25,2024-07-05,1904,7.2,Cloud AI Solutions +AI05992,AI Product Manager,269938,USD,269938,EX,FL,Denmark,S,Denmark,50,"Python, Kubernetes, MLOps",Master,16,Transportation,2024-02-08,2024-02-28,789,9.6,Algorithmic Solutions +AI05993,Computer Vision Engineer,63932,USD,63932,SE,FL,China,S,China,0,"GCP, MLOps, Hadoop, NLP",Associate,5,Government,2024-09-13,2024-11-14,753,9.6,Smart Analytics +AI05994,Principal Data Scientist,151633,USD,151633,EX,PT,Sweden,S,Philippines,0,"Python, R, Git",PhD,14,Telecommunications,2024-03-24,2024-04-26,1334,6.4,Advanced Robotics +AI05995,AI Research Scientist,149659,EUR,127210,EX,FT,Austria,L,Poland,100,"TensorFlow, Hadoop, Data Visualization, Docker",Master,14,Energy,2024-10-02,2024-12-03,809,9.1,Cloud AI Solutions +AI05996,AI Architect,63919,USD,63919,EX,FL,China,S,Luxembourg,50,"SQL, MLOps, Kubernetes, Azure",PhD,17,Consulting,2025-04-01,2025-05-30,860,5.8,Algorithmic Solutions +AI05997,Head of AI,189843,USD,189843,EX,PT,Denmark,S,Sweden,100,"TensorFlow, Kubernetes, GCP, Statistics, PyTorch",Associate,11,Retail,2024-01-31,2024-03-21,2054,8.8,AI Innovations +AI05998,NLP Engineer,72310,EUR,61464,MI,PT,Germany,M,Philippines,0,"MLOps, SQL, PyTorch, AWS, Linux",Associate,4,Media,2024-04-24,2024-06-16,1435,8.2,Digital Transformation LLC +AI05999,Computer Vision Engineer,90085,GBP,67564,MI,CT,United Kingdom,M,United Kingdom,50,"Linux, Git, R, Python",Associate,3,Government,2024-03-06,2024-04-23,2417,5.2,Cognitive Computing +AI06000,Head of AI,84107,USD,84107,MI,CT,Israel,M,Israel,0,"R, SQL, Computer Vision",Master,3,Retail,2024-05-21,2024-06-30,1588,5.3,Neural Networks Co +AI06001,AI Architect,99493,USD,99493,MI,CT,United States,M,United States,0,"Python, Git, R",PhD,3,Manufacturing,2025-04-12,2025-06-02,1258,6.7,Algorithmic Solutions +AI06002,Computer Vision Engineer,76756,EUR,65243,MI,PT,Netherlands,S,Netherlands,0,"Deep Learning, Python, Linux, SQL",Bachelor,4,Media,2025-01-17,2025-03-16,1000,5.4,Autonomous Tech +AI06003,Robotics Engineer,74296,GBP,55722,EN,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Spark, R, Data Visualization, Git",Master,1,Automotive,2025-03-09,2025-05-16,2465,6.7,Cloud AI Solutions +AI06004,Machine Learning Engineer,139465,JPY,15341150,SE,FT,Japan,L,Japan,100,"Azure, Docker, Java, Computer Vision, AWS",PhD,5,Healthcare,2025-04-02,2025-05-28,1680,5.3,Neural Networks Co +AI06005,Deep Learning Engineer,124464,AUD,168026,MI,CT,Australia,L,Russia,100,"Python, Hadoop, Data Visualization, Scala, Kubernetes",Bachelor,3,Retail,2024-10-20,2024-12-14,2113,8.2,Advanced Robotics +AI06006,NLP Engineer,169364,SGD,220173,SE,FL,Singapore,L,Estonia,0,"PyTorch, SQL, Tableau, TensorFlow, R",Master,7,Consulting,2024-11-08,2025-01-13,2464,6,TechCorp Inc +AI06007,ML Ops Engineer,104092,EUR,88478,MI,FL,France,L,France,50,"NLP, Docker, TensorFlow, Python, Azure",PhD,2,Retail,2025-01-20,2025-03-18,1428,8.3,Algorithmic Solutions +AI06008,AI Architect,236270,SGD,307151,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization",Associate,14,Healthcare,2024-01-02,2024-03-13,1176,6.9,DeepTech Ventures +AI06009,Machine Learning Researcher,127297,EUR,108202,SE,FT,Germany,L,Germany,50,"TensorFlow, Statistics, Computer Vision",Bachelor,8,Healthcare,2024-10-26,2024-12-21,1450,8.5,TechCorp Inc +AI06010,AI Architect,59837,USD,59837,SE,CT,China,S,China,50,"R, Tableau, Python, TensorFlow",PhD,8,Healthcare,2024-12-01,2025-01-26,1409,7.7,Neural Networks Co +AI06011,Head of AI,101553,EUR,86320,MI,PT,Austria,M,Austria,50,"Kubernetes, Linux, Deep Learning, Mathematics, Tableau",PhD,2,Telecommunications,2024-04-20,2024-05-26,1360,8.4,Quantum Computing Inc +AI06012,Data Analyst,308290,USD,308290,EX,PT,United States,L,Singapore,50,"Scala, Linux, SQL, PyTorch",Master,17,Consulting,2025-02-20,2025-03-26,2200,8.4,Smart Analytics +AI06013,Deep Learning Engineer,151359,USD,151359,SE,PT,Sweden,L,Sweden,50,"R, Scala, Statistics, Kubernetes, SQL",Bachelor,5,Retail,2024-10-15,2024-12-18,1006,8.4,Neural Networks Co +AI06014,AI Research Scientist,130025,EUR,110521,SE,FT,Germany,L,Germany,0,"PyTorch, SQL, R, Hadoop, Git",Master,7,Media,2024-02-24,2024-03-09,841,6.9,Future Systems +AI06015,ML Ops Engineer,257725,USD,257725,EX,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Azure",Associate,14,Retail,2024-12-07,2025-01-22,666,5.9,Smart Analytics +AI06016,Data Scientist,71138,USD,71138,EN,FT,Norway,M,Norway,50,"SQL, Python, Data Visualization, Mathematics, Linux",Bachelor,0,Automotive,2024-03-07,2024-04-13,2470,7.2,AI Innovations +AI06017,AI Product Manager,148695,USD,148695,SE,CT,Denmark,S,Denmark,50,"MLOps, AWS, R",Associate,8,Energy,2024-03-12,2024-05-20,705,7.3,Quantum Computing Inc +AI06018,Research Scientist,141557,USD,141557,SE,FL,United States,S,United States,50,"Tableau, MLOps, R, SQL",Associate,8,Automotive,2024-04-22,2024-05-09,1135,6.6,Digital Transformation LLC +AI06019,Data Analyst,38669,USD,38669,SE,CT,India,S,United Kingdom,0,"Tableau, Java, Deep Learning, Python, Mathematics",Bachelor,6,Manufacturing,2024-04-23,2024-05-16,2029,5.5,DeepTech Ventures +AI06020,ML Ops Engineer,68663,USD,68663,MI,PT,Israel,M,Czech Republic,0,"PyTorch, Kubernetes, Git, TensorFlow",Master,4,Finance,2025-04-16,2025-05-28,676,6.5,Digital Transformation LLC +AI06021,AI Specialist,44333,USD,44333,MI,FL,India,L,Canada,50,"Scala, Linux, Python",Master,3,Consulting,2025-02-06,2025-02-27,566,9.2,Cloud AI Solutions +AI06022,AI Architect,142509,USD,142509,SE,CT,Denmark,S,Denmark,100,"Computer Vision, TensorFlow, Mathematics, NLP",Associate,5,Telecommunications,2024-08-23,2024-10-30,1296,6.9,Cloud AI Solutions +AI06023,Robotics Engineer,55014,USD,55014,MI,CT,China,L,Ireland,0,"R, Python, Tableau",PhD,2,Healthcare,2024-08-13,2024-10-02,2362,9.8,Autonomous Tech +AI06024,AI Consultant,195813,JPY,21539430,EX,FL,Japan,M,Turkey,100,"GCP, Python, AWS, SQL, TensorFlow",Associate,14,Automotive,2024-01-05,2024-01-29,2233,8.2,AI Innovations +AI06025,Data Scientist,43954,USD,43954,SE,FL,China,S,Romania,100,"Java, Linux, Mathematics, Data Visualization",PhD,6,Energy,2024-03-29,2024-06-03,1318,7.5,Machine Intelligence Group +AI06026,Autonomous Systems Engineer,99890,CAD,124863,MI,FL,Canada,L,Canada,50,"Git, SQL, Computer Vision",PhD,3,Media,2024-10-13,2024-11-23,1008,6.3,Algorithmic Solutions +AI06027,AI Specialist,178380,JPY,19621800,SE,CT,Japan,L,Japan,0,"Git, MLOps, TensorFlow, Python, Tableau",Bachelor,8,Media,2025-03-26,2025-04-22,1368,6.1,Neural Networks Co +AI06028,Principal Data Scientist,121764,USD,121764,SE,FT,Finland,S,South Africa,100,"GCP, Hadoop, Python, TensorFlow, Kubernetes",Master,8,Media,2024-12-17,2025-01-05,2150,5.6,AI Innovations +AI06029,AI Research Scientist,148778,JPY,16365580,EX,FT,Japan,M,Japan,100,"Linux, Java, Data Visualization, Tableau, Kubernetes",Associate,15,Media,2024-03-28,2024-05-07,966,5.3,Digital Transformation LLC +AI06030,ML Ops Engineer,139963,CHF,125967,SE,PT,Switzerland,S,Portugal,100,"Hadoop, NLP, Java, Computer Vision",Master,9,Real Estate,2024-08-31,2024-10-15,1961,7.4,AI Innovations +AI06031,Deep Learning Engineer,75640,GBP,56730,EN,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, Hadoop, Spark",PhD,1,Finance,2024-09-10,2024-11-13,2183,8,Cloud AI Solutions +AI06032,AI Research Scientist,78384,USD,78384,MI,FL,Ireland,M,Ireland,50,"GCP, Spark, Data Visualization",Associate,3,Transportation,2024-04-30,2024-06-01,712,6.2,DataVision Ltd +AI06033,AI Research Scientist,50999,USD,50999,MI,FL,China,L,China,100,"Python, NLP, Kubernetes",PhD,3,Manufacturing,2024-07-26,2024-08-22,1225,5.9,DeepTech Ventures +AI06034,AI Research Scientist,61119,EUR,51951,EN,FL,Germany,L,South Africa,50,"GCP, Scala, TensorFlow, Python, Mathematics",PhD,0,Media,2025-03-20,2025-04-11,1428,8.5,Neural Networks Co +AI06035,AI Architect,99511,SGD,129364,MI,FT,Singapore,L,Latvia,100,"R, Java, Tableau, Python, Linux",Bachelor,4,Finance,2024-04-19,2024-06-06,2368,6.8,Neural Networks Co +AI06036,Deep Learning Engineer,208119,EUR,176901,EX,PT,Germany,S,Germany,0,"PyTorch, Spark, Scala, Java",Associate,12,Technology,2024-05-13,2024-06-24,2228,7,Predictive Systems +AI06037,NLP Engineer,64737,USD,64737,EN,FL,South Korea,L,Egypt,0,"SQL, NLP, MLOps, GCP, Tableau",Associate,1,Real Estate,2024-09-08,2024-09-24,1189,6.3,Machine Intelligence Group +AI06038,Deep Learning Engineer,85166,USD,85166,EX,PT,China,L,China,0,"Java, PyTorch, Mathematics, AWS",PhD,12,Real Estate,2024-03-16,2024-05-04,1675,6.2,Quantum Computing Inc +AI06039,AI Specialist,132470,EUR,112600,MI,FT,Netherlands,L,Belgium,100,"Deep Learning, Kubernetes, GCP, Statistics, Computer Vision",Bachelor,2,Consulting,2024-10-15,2024-12-27,1763,7,Advanced Robotics +AI06040,AI Product Manager,27118,USD,27118,EN,FL,China,S,China,0,"Data Visualization, Python, TensorFlow, Spark",PhD,1,Consulting,2024-06-20,2024-08-19,2259,8.4,Neural Networks Co +AI06041,Head of AI,189995,EUR,161496,EX,FL,Germany,S,Denmark,100,"Scala, GCP, Java, Linux",PhD,13,Finance,2025-02-25,2025-03-13,2204,9,Machine Intelligence Group +AI06042,NLP Engineer,182291,CAD,227864,EX,FL,Canada,M,Turkey,50,"GCP, Java, SQL, NLP, Docker",PhD,15,Media,2025-04-25,2025-06-06,1075,6.7,DataVision Ltd +AI06043,AI Specialist,58125,AUD,78469,EN,FL,Australia,M,Argentina,100,"Python, Mathematics, TensorFlow, Azure, Linux",Associate,0,Technology,2024-07-24,2024-08-29,751,7.1,DataVision Ltd +AI06044,Deep Learning Engineer,304701,CHF,274231,EX,PT,Switzerland,M,Switzerland,100,"Git, Linux, Tableau",Associate,15,Energy,2024-08-08,2024-10-14,990,7.1,Digital Transformation LLC +AI06045,Machine Learning Engineer,28807,USD,28807,EN,PT,India,L,India,50,"R, Python, Docker",Master,0,Retail,2024-04-06,2024-06-09,2227,8.6,Algorithmic Solutions +AI06046,AI Research Scientist,119295,CHF,107366,MI,FT,Switzerland,S,Switzerland,100,"Mathematics, TensorFlow, NLP, Scala",Master,4,Government,2024-12-20,2025-01-05,1352,6.2,Neural Networks Co +AI06047,Data Engineer,75061,EUR,63802,MI,CT,Germany,S,Germany,100,"Python, Statistics, Linux, Spark, Deep Learning",Master,4,Gaming,2025-03-25,2025-05-31,2222,7.7,DeepTech Ventures +AI06048,Principal Data Scientist,134979,EUR,114732,SE,FL,Austria,M,Netherlands,50,"Mathematics, PyTorch, Tableau, Linux",Master,7,Government,2024-06-11,2024-08-07,1909,8.4,DeepTech Ventures +AI06049,Computer Vision Engineer,138134,GBP,103601,SE,FL,United Kingdom,S,United Kingdom,50,"SQL, Kubernetes, Python",Master,6,Real Estate,2024-02-01,2024-02-28,507,5.4,Smart Analytics +AI06050,Head of AI,71317,USD,71317,EN,PT,Ireland,M,Ireland,100,"Deep Learning, Data Visualization, Linux",Associate,1,Education,2025-04-20,2025-06-20,2132,9.6,AI Innovations +AI06051,Robotics Engineer,238482,JPY,26233020,EX,FL,Japan,S,Japan,100,"Data Visualization, Git, Kubernetes, NLP, Python",Master,17,Manufacturing,2024-02-06,2024-03-01,1858,8.4,Future Systems +AI06052,Computer Vision Engineer,217112,EUR,184545,EX,PT,France,L,France,100,"Mathematics, Python, Azure, Linux",Bachelor,17,Retail,2025-01-11,2025-02-09,2235,7.7,Predictive Systems +AI06053,AI Architect,91189,AUD,123105,MI,FT,Australia,S,Australia,50,"MLOps, Kubernetes, R, SQL",Master,4,Government,2025-03-19,2025-05-24,1179,6,Digital Transformation LLC +AI06054,AI Software Engineer,31432,USD,31432,MI,PT,India,M,India,0,"Python, Statistics, TensorFlow, Kubernetes, Azure",PhD,2,Finance,2025-03-14,2025-04-09,1250,7.7,Future Systems +AI06055,AI Software Engineer,203827,EUR,173253,EX,FL,Austria,L,Austria,100,"PyTorch, Python, TensorFlow, Statistics, Data Visualization",Associate,19,Finance,2024-07-13,2024-09-09,2138,7.5,Predictive Systems +AI06056,Data Engineer,78958,EUR,67114,MI,CT,France,M,Ukraine,50,"Mathematics, Azure, Tableau, NLP",Master,3,Education,2024-07-08,2024-08-17,2012,8.5,TechCorp Inc +AI06057,Robotics Engineer,100020,AUD,135027,SE,FT,Australia,S,Australia,50,"Kubernetes, NLP, R, Computer Vision",PhD,9,Finance,2024-08-15,2024-09-09,1515,8.7,Advanced Robotics +AI06058,AI Consultant,168504,USD,168504,EX,FT,Israel,L,Israel,100,"R, SQL, Hadoop, Docker",Bachelor,17,Government,2024-10-15,2024-11-07,1388,9.3,Machine Intelligence Group +AI06059,Deep Learning Engineer,59253,USD,59253,EN,CT,Finland,S,New Zealand,100,"Kubernetes, Computer Vision, TensorFlow",Bachelor,1,Finance,2024-04-02,2024-06-11,2238,6.6,DataVision Ltd +AI06060,Computer Vision Engineer,74984,USD,74984,EX,FT,China,S,Turkey,50,"Hadoop, Data Visualization, Git",PhD,15,Education,2024-07-14,2024-09-23,1980,8.3,Cloud AI Solutions +AI06061,Robotics Engineer,236625,USD,236625,EX,CT,Finland,M,Portugal,100,"Hadoop, Deep Learning, TensorFlow, SQL",Master,15,Energy,2024-09-07,2024-11-09,1087,6.7,Neural Networks Co +AI06062,AI Product Manager,111066,USD,111066,SE,FT,United States,S,United States,0,"SQL, Scala, MLOps",Master,6,Automotive,2025-03-28,2025-05-29,2442,7.6,Cloud AI Solutions +AI06063,AI Research Scientist,123116,USD,123116,MI,PT,Denmark,M,Denmark,100,"Git, Java, NLP",Master,4,Healthcare,2024-02-03,2024-02-26,694,5.7,Advanced Robotics +AI06064,AI Software Engineer,72971,EUR,62025,EN,CT,Netherlands,S,Finland,50,"Git, AWS, Data Visualization, Java",Bachelor,1,Gaming,2024-11-10,2024-11-28,1884,9,AI Innovations +AI06065,Head of AI,73070,CAD,91338,EN,FL,Canada,L,Canada,100,"Linux, Azure, Python",Bachelor,0,Retail,2024-03-06,2024-05-18,1253,6.3,Advanced Robotics +AI06066,Data Engineer,73301,USD,73301,EN,CT,Israel,M,Ukraine,50,"R, Git, Tableau",PhD,0,Manufacturing,2024-12-07,2025-01-16,1946,9.1,AI Innovations +AI06067,Research Scientist,46090,USD,46090,MI,FT,China,L,China,50,"TensorFlow, Kubernetes, Mathematics, PyTorch, AWS",PhD,3,Media,2024-09-03,2024-10-13,2485,8.4,Digital Transformation LLC +AI06068,Principal Data Scientist,268531,USD,268531,EX,FT,Sweden,L,Sweden,50,"SQL, GCP, Statistics",PhD,11,Media,2025-02-13,2025-04-20,1051,5.8,Autonomous Tech +AI06069,Robotics Engineer,116014,CHF,104413,MI,PT,Switzerland,M,Switzerland,100,"Docker, Hadoop, NLP, Kubernetes, Scala",PhD,3,Manufacturing,2024-08-14,2024-10-07,1865,6.8,Cloud AI Solutions +AI06070,Data Analyst,112161,USD,112161,MI,FT,Sweden,L,Sweden,0,"R, Spark, SQL, GCP",Bachelor,2,Gaming,2024-04-03,2024-05-16,2499,9.1,Predictive Systems +AI06071,AI Specialist,62287,USD,62287,EX,FT,India,L,Luxembourg,100,"Tableau, Computer Vision, GCP, Data Visualization",Associate,17,Automotive,2024-07-12,2024-08-10,2286,6.4,Quantum Computing Inc +AI06072,NLP Engineer,71300,USD,71300,EN,FL,Israel,M,Israel,50,"GCP, Spark, PyTorch",Bachelor,0,Consulting,2024-10-19,2024-11-26,2200,6.2,Future Systems +AI06073,Machine Learning Engineer,65583,USD,65583,MI,PT,Finland,S,Russia,0,"R, Kubernetes, Mathematics",Associate,2,Media,2025-02-21,2025-04-14,733,8.9,Future Systems +AI06074,Autonomous Systems Engineer,175971,EUR,149575,EX,PT,Austria,S,Austria,100,"Kubernetes, Computer Vision, GCP, SQL",Bachelor,11,Retail,2025-03-21,2025-05-23,1930,9.4,DeepTech Ventures +AI06075,Robotics Engineer,29541,USD,29541,MI,PT,India,M,India,0,"Python, Docker, Linux",Master,3,Gaming,2025-04-02,2025-04-20,1449,6.3,Advanced Robotics +AI06076,Computer Vision Engineer,76318,USD,76318,MI,PT,South Korea,M,Norway,0,"PyTorch, Java, TensorFlow",Master,2,Technology,2025-02-08,2025-03-07,1449,7.9,DeepTech Ventures +AI06077,AI Consultant,257587,USD,257587,EX,PT,Denmark,S,Denmark,50,"Hadoop, Linux, Deep Learning, Scala, R",Bachelor,11,Healthcare,2024-02-05,2024-03-09,1770,5.1,Smart Analytics +AI06078,Autonomous Systems Engineer,188465,EUR,160195,EX,CT,Austria,S,Austria,50,"Hadoop, Python, NLP",PhD,12,Healthcare,2024-02-06,2024-03-19,1220,8.7,Cloud AI Solutions +AI06079,Robotics Engineer,106976,USD,106976,MI,CT,Ireland,L,Ireland,50,"Java, Kubernetes, GCP, Deep Learning, MLOps",PhD,4,Consulting,2024-11-30,2025-01-12,1164,8.7,AI Innovations +AI06080,Autonomous Systems Engineer,142983,EUR,121536,EX,CT,Germany,M,Germany,50,"TensorFlow, Mathematics, GCP, Python",Master,13,Technology,2024-06-20,2024-08-16,1906,6.4,Predictive Systems +AI06081,AI Research Scientist,61577,USD,61577,EN,CT,Sweden,S,Israel,100,"Python, Tableau, Kubernetes, Scala",PhD,0,Finance,2025-04-13,2025-05-05,2097,5.8,Autonomous Tech +AI06082,Machine Learning Engineer,89159,AUD,120365,MI,FL,Australia,S,Australia,0,"Git, AWS, Data Visualization, Hadoop, Tableau",PhD,2,Government,2024-02-25,2024-04-05,2019,7.9,Algorithmic Solutions +AI06083,AI Research Scientist,98446,USD,98446,EN,FT,Denmark,M,Denmark,100,"Kubernetes, Linux, Scala, Mathematics, MLOps",Associate,0,Technology,2024-07-13,2024-09-22,2393,6.7,DataVision Ltd +AI06084,Machine Learning Engineer,50109,GBP,37582,EN,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, Kubernetes, NLP",Bachelor,1,Healthcare,2025-01-04,2025-02-18,2307,5.3,Cognitive Computing +AI06085,Machine Learning Researcher,78378,USD,78378,MI,FL,South Korea,S,South Korea,0,"Git, Deep Learning, Kubernetes, SQL",Master,4,Media,2024-06-25,2024-09-06,1328,9.3,DataVision Ltd +AI06086,Deep Learning Engineer,72771,CAD,90964,MI,CT,Canada,S,Canada,50,"PyTorch, TensorFlow, Data Visualization",Associate,4,Automotive,2025-03-24,2025-06-04,2063,6.6,Future Systems +AI06087,Data Engineer,269658,USD,269658,EX,CT,Finland,L,Finland,0,"SQL, Hadoop, R, GCP",Bachelor,18,Consulting,2024-09-14,2024-10-25,2037,5.7,Cognitive Computing +AI06088,ML Ops Engineer,94499,CAD,118124,SE,PT,Canada,S,United Kingdom,50,"Data Visualization, MLOps, Git",PhD,6,Media,2024-06-26,2024-08-21,2299,8.2,TechCorp Inc +AI06089,Autonomous Systems Engineer,98191,EUR,83462,MI,FT,France,M,France,0,"Scala, PyTorch, SQL",Master,2,Gaming,2024-10-23,2024-11-10,1994,6.3,Smart Analytics +AI06090,AI Software Engineer,52424,EUR,44560,EN,FL,France,M,Vietnam,50,"Kubernetes, Docker, Tableau, PyTorch, Java",Bachelor,1,Gaming,2024-02-28,2024-05-08,1715,8.9,DeepTech Ventures +AI06091,AI Consultant,58246,EUR,49509,EN,PT,Germany,M,Belgium,0,"Hadoop, Spark, NLP",Master,1,Transportation,2024-09-06,2024-11-12,859,8.7,Quantum Computing Inc +AI06092,Head of AI,267949,AUD,361731,EX,CT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, Python",Bachelor,10,Telecommunications,2024-03-12,2024-04-30,707,9.7,Machine Intelligence Group +AI06093,Machine Learning Engineer,70389,USD,70389,EN,FT,Sweden,S,Thailand,100,"Hadoop, Computer Vision, NLP, Azure, Spark",Master,0,Media,2025-02-27,2025-04-12,861,6.6,Cloud AI Solutions +AI06094,Computer Vision Engineer,189799,USD,189799,EX,FL,Denmark,M,Denmark,100,"Hadoop, Python, TensorFlow, MLOps",Bachelor,17,Energy,2024-08-16,2024-10-16,1028,8.6,Machine Intelligence Group +AI06095,Deep Learning Engineer,71097,USD,71097,EN,CT,South Korea,L,South Korea,0,"SQL, TensorFlow, GCP",Master,0,Media,2025-04-02,2025-06-13,1765,8.6,Cognitive Computing +AI06096,ML Ops Engineer,129008,GBP,96756,MI,CT,United Kingdom,L,United Kingdom,0,"SQL, Hadoop, MLOps, Git",Master,4,Government,2025-04-15,2025-05-30,1561,10,Algorithmic Solutions +AI06097,Robotics Engineer,75236,EUR,63951,MI,FL,Netherlands,S,Netherlands,0,"MLOps, Spark, Docker",Associate,3,Consulting,2024-08-04,2024-08-30,664,9.2,Machine Intelligence Group +AI06098,Autonomous Systems Engineer,169125,USD,169125,EX,CT,Denmark,S,Denmark,0,"Data Visualization, Spark, PyTorch, Hadoop, Python",Bachelor,11,Education,2025-02-13,2025-04-10,2098,8.5,Neural Networks Co +AI06099,AI Software Engineer,109880,USD,109880,SE,CT,Israel,M,Israel,100,"SQL, Hadoop, NLP, Deep Learning",Bachelor,9,Gaming,2024-10-11,2024-11-07,804,9.5,Smart Analytics +AI06100,NLP Engineer,122068,USD,122068,MI,PT,United States,L,United States,100,"Kubernetes, Tableau, SQL",PhD,3,Consulting,2024-04-07,2024-04-26,1213,7.9,Cognitive Computing +AI06101,AI Specialist,62513,USD,62513,SE,FL,China,S,Romania,0,"Python, Scala, R, Hadoop, SQL",Associate,8,Consulting,2025-02-28,2025-04-09,1022,8.5,Neural Networks Co +AI06102,AI Software Engineer,67497,USD,67497,EN,CT,Denmark,M,Denmark,100,"Scala, Spark, R",Master,1,Energy,2024-07-05,2024-09-03,1542,8,Digital Transformation LLC +AI06103,Robotics Engineer,68328,USD,68328,SE,FL,China,M,China,50,"R, Java, Tableau",Associate,9,Telecommunications,2024-02-06,2024-03-13,630,6.4,DeepTech Ventures +AI06104,Research Scientist,73887,CAD,92359,EN,PT,Canada,M,Canada,0,"NLP, SQL, R, PyTorch",Bachelor,0,Healthcare,2024-03-30,2024-06-03,2057,6.9,DataVision Ltd +AI06105,Deep Learning Engineer,85387,EUR,72579,MI,PT,France,M,France,50,"Azure, Python, Spark",Master,4,Technology,2024-02-27,2024-03-27,541,7.3,Digital Transformation LLC +AI06106,Data Engineer,81892,JPY,9008120,MI,FT,Japan,S,Japan,0,"NLP, Kubernetes, Data Visualization",PhD,3,Consulting,2024-06-30,2024-07-28,1150,7.3,DeepTech Ventures +AI06107,Autonomous Systems Engineer,125416,SGD,163041,SE,FL,Singapore,S,South Korea,0,"SQL, Python, Azure, Deep Learning",PhD,9,Energy,2024-10-23,2024-12-05,1037,5.6,Algorithmic Solutions +AI06108,Research Scientist,362104,USD,362104,EX,FL,Norway,L,Norway,0,"TensorFlow, Docker, PyTorch",Bachelor,14,Finance,2024-05-23,2024-07-24,2245,8.5,Algorithmic Solutions +AI06109,Machine Learning Engineer,109467,EUR,93047,SE,FT,France,S,France,0,"TensorFlow, Docker, Python",Bachelor,5,Government,2025-01-07,2025-03-12,1615,8.2,Neural Networks Co +AI06110,AI Software Engineer,74992,USD,74992,MI,FT,Israel,S,Denmark,100,"R, SQL, MLOps, AWS",Bachelor,2,Education,2024-10-09,2024-12-15,1285,7.3,Machine Intelligence Group +AI06111,AI Research Scientist,83813,USD,83813,EX,CT,China,S,China,50,"Python, Mathematics, TensorFlow, Data Visualization, Computer Vision",Bachelor,15,Education,2024-01-23,2024-03-07,1797,6.7,Quantum Computing Inc +AI06112,Data Scientist,98188,CHF,88369,EN,FT,Switzerland,S,Switzerland,100,"Spark, PyTorch, TensorFlow, Hadoop",Master,0,Gaming,2024-05-16,2024-06-11,1249,8.7,Advanced Robotics +AI06113,AI Architect,120407,USD,120407,EX,FT,Finland,S,Italy,0,"Deep Learning, R, MLOps, Computer Vision, Azure",PhD,17,Education,2024-11-17,2024-12-31,763,8.5,Algorithmic Solutions +AI06114,Deep Learning Engineer,187126,EUR,159057,EX,PT,France,M,France,0,"Linux, Docker, Computer Vision",Bachelor,18,Energy,2024-04-24,2024-06-23,2499,8.6,AI Innovations +AI06115,Autonomous Systems Engineer,55832,USD,55832,SE,FT,China,M,China,100,"Spark, Statistics, MLOps",PhD,9,Media,2025-03-27,2025-05-29,1242,5.5,Cognitive Computing +AI06116,Data Scientist,99693,USD,99693,MI,FL,Norway,S,Denmark,100,"TensorFlow, PyTorch, MLOps, GCP",Bachelor,2,Automotive,2024-03-06,2024-04-27,580,6.6,Smart Analytics +AI06117,Principal Data Scientist,111940,AUD,151119,SE,PT,Australia,M,South Korea,100,"Python, R, GCP, TensorFlow, Linux",Bachelor,8,Energy,2024-05-05,2024-06-15,601,9.9,Neural Networks Co +AI06118,AI Consultant,350058,USD,350058,EX,CT,Norway,L,Malaysia,50,"SQL, TensorFlow, Data Visualization, Hadoop",PhD,19,Healthcare,2024-02-19,2024-04-02,2435,8.6,Predictive Systems +AI06119,AI Product Manager,118196,EUR,100467,SE,PT,Germany,S,Germany,0,"Computer Vision, Tableau, SQL, Deep Learning, Linux",Bachelor,7,Technology,2024-07-15,2024-09-25,960,7.6,Advanced Robotics +AI06120,Data Analyst,149669,USD,149669,EX,FT,South Korea,L,South Korea,0,"AWS, GCP, Git, Computer Vision, Hadoop",Associate,18,Government,2025-01-14,2025-02-27,1730,7.8,Future Systems +AI06121,AI Architect,207625,CHF,186863,EX,PT,Switzerland,S,Switzerland,0,"GCP, Statistics, NLP, Computer Vision, Spark",Master,10,Transportation,2025-03-30,2025-05-02,2116,8.4,DeepTech Ventures +AI06122,AI Specialist,179611,CHF,161650,SE,PT,Switzerland,M,Switzerland,100,"Scala, TensorFlow, GCP",Associate,5,Media,2025-03-08,2025-04-07,1131,8.8,TechCorp Inc +AI06123,Deep Learning Engineer,72594,USD,72594,MI,FT,Israel,S,Israel,100,"PyTorch, Computer Vision, Tableau, AWS, SQL",Bachelor,4,Education,2024-04-01,2024-05-30,1372,7.6,TechCorp Inc +AI06124,Data Engineer,74990,USD,74990,MI,FL,Ireland,S,Ireland,100,"Spark, Statistics, Data Visualization, Linux",Associate,4,Transportation,2025-01-06,2025-03-19,1208,8.6,Digital Transformation LLC +AI06125,Principal Data Scientist,128233,USD,128233,SE,PT,United States,S,New Zealand,100,"AWS, MLOps, Mathematics",Bachelor,9,Automotive,2024-12-17,2025-01-26,505,9.1,DataVision Ltd +AI06126,AI Specialist,211020,USD,211020,EX,FT,Denmark,S,Denmark,100,"Git, Python, Deep Learning, Computer Vision",Bachelor,19,Technology,2024-08-17,2024-10-08,717,8.6,Quantum Computing Inc +AI06127,Data Engineer,81260,USD,81260,MI,FL,Sweden,S,Sweden,100,"Hadoop, Azure, Mathematics, TensorFlow, MLOps",Master,4,Gaming,2025-02-15,2025-03-05,733,9.9,DataVision Ltd +AI06128,Data Analyst,119633,EUR,101688,SE,PT,France,M,Thailand,50,"SQL, Kubernetes, Linux",Bachelor,7,Government,2024-01-18,2024-03-20,1998,7.5,Cognitive Computing +AI06129,Machine Learning Engineer,73814,USD,73814,MI,PT,Finland,M,Finland,100,"Python, Spark, TensorFlow, Data Visualization, AWS",PhD,4,Technology,2024-02-19,2024-04-20,1409,8.1,DataVision Ltd +AI06130,AI Specialist,288274,EUR,245033,EX,FT,Germany,L,Indonesia,0,"GCP, SQL, AWS",Associate,13,Automotive,2024-09-29,2024-11-30,1683,9.7,Cloud AI Solutions +AI06131,AI Architect,194644,USD,194644,EX,PT,United States,M,United States,100,"Python, Spark, R, Data Visualization, Scala",Master,19,Energy,2024-04-27,2024-06-20,585,9.8,Neural Networks Co +AI06132,AI Software Engineer,116370,JPY,12800700,MI,FL,Japan,M,Japan,100,"AWS, Scala, GCP",Master,4,Gaming,2025-04-07,2025-05-27,1512,9.3,AI Innovations +AI06133,Robotics Engineer,58648,USD,58648,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Mathematics, Spark",PhD,0,Retail,2024-09-14,2024-10-31,2333,7.3,Smart Analytics +AI06134,Head of AI,94136,EUR,80016,MI,FT,France,L,France,0,"SQL, PyTorch, Docker, Statistics",Associate,2,Technology,2024-08-17,2024-10-02,1740,5.9,Neural Networks Co +AI06135,ML Ops Engineer,60881,JPY,6696910,EN,FT,Japan,S,Japan,50,"SQL, AWS, Tableau, R, NLP",Associate,1,Retail,2024-05-13,2024-07-08,2420,9.3,Advanced Robotics +AI06136,NLP Engineer,134266,USD,134266,SE,CT,United States,S,United States,0,"Tableau, GCP, TensorFlow, Docker",PhD,6,Media,2024-04-22,2024-05-09,2340,9.2,Advanced Robotics +AI06137,Head of AI,61969,USD,61969,SE,PT,China,S,China,50,"Kubernetes, SQL, Deep Learning, Statistics, MLOps",Master,7,Energy,2024-08-05,2024-09-14,903,7,Algorithmic Solutions +AI06138,Machine Learning Engineer,122843,CAD,153554,SE,FT,Canada,S,Canada,0,"R, Java, Data Visualization, Python, AWS",Bachelor,9,Healthcare,2025-01-07,2025-02-14,1013,5.8,Quantum Computing Inc +AI06139,AI Specialist,127779,USD,127779,SE,CT,Finland,L,Finland,50,"Docker, Data Visualization, Python",Bachelor,8,Consulting,2025-03-06,2025-04-27,2111,5.8,Machine Intelligence Group +AI06140,AI Architect,27705,USD,27705,MI,FT,India,M,Spain,50,"Linux, Tableau, NLP, Azure",Master,2,Retail,2024-02-21,2024-04-12,1650,6.3,Digital Transformation LLC +AI06141,AI Architect,31007,USD,31007,MI,PT,India,S,India,50,"Python, Docker, Deep Learning, Java, NLP",Bachelor,3,Finance,2025-04-23,2025-05-30,1414,9.3,Cognitive Computing +AI06142,Head of AI,159103,USD,159103,SE,CT,Denmark,L,China,0,"GCP, Hadoop, SQL",PhD,9,Manufacturing,2024-08-25,2024-09-13,1683,6.3,Quantum Computing Inc +AI06143,AI Specialist,81172,USD,81172,MI,FT,Ireland,M,Ireland,50,"Python, Docker, Deep Learning, Azure, GCP",Associate,3,Consulting,2024-05-24,2024-07-10,710,8,TechCorp Inc +AI06144,Deep Learning Engineer,38128,USD,38128,EN,PT,China,L,Canada,100,"Docker, TensorFlow, Hadoop",Associate,0,Media,2024-04-09,2024-06-19,1299,6,AI Innovations +AI06145,Data Engineer,128255,EUR,109017,SE,FT,Germany,S,India,100,"Statistics, Kubernetes, R, GCP",Associate,6,Gaming,2024-03-16,2024-04-27,1216,7.4,TechCorp Inc +AI06146,ML Ops Engineer,101526,USD,101526,SE,FT,Finland,S,Finland,0,"Hadoop, PyTorch, Java, Statistics",Master,7,Media,2024-09-28,2024-10-20,1406,5.7,Algorithmic Solutions +AI06147,Robotics Engineer,46864,AUD,63266,EN,FL,Australia,S,Australia,100,"Azure, Kubernetes, Python, Deep Learning",PhD,1,Telecommunications,2024-11-04,2024-12-30,540,6.2,Smart Analytics +AI06148,Autonomous Systems Engineer,115707,CHF,104136,MI,CT,Switzerland,M,South Africa,50,"NLP, Python, SQL, TensorFlow",Master,3,Media,2024-04-07,2024-05-14,1458,6.7,DeepTech Ventures +AI06149,Data Engineer,94886,USD,94886,MI,FT,Sweden,L,Norway,100,"Statistics, Git, Spark",Bachelor,2,Automotive,2024-01-16,2024-01-31,1256,6.2,Neural Networks Co +AI06150,AI Research Scientist,66330,USD,66330,EN,FL,Ireland,M,Norway,50,"Python, AWS, Azure",Master,1,Real Estate,2024-01-16,2024-02-23,1111,8,Quantum Computing Inc +AI06151,Machine Learning Researcher,66467,EUR,56497,MI,PT,Austria,S,Austria,50,"Linux, SQL, Computer Vision, PyTorch",Bachelor,2,Education,2024-12-27,2025-02-15,1854,5.5,Neural Networks Co +AI06152,Data Scientist,112672,SGD,146474,MI,FT,Singapore,L,Singapore,100,"NLP, Python, Linux, GCP, Git",Associate,2,Education,2024-10-07,2024-11-28,1006,9.8,Digital Transformation LLC +AI06153,Deep Learning Engineer,92337,EUR,78486,MI,FT,Netherlands,M,Netherlands,50,"Mathematics, GCP, Computer Vision, Python",Bachelor,2,Gaming,2024-04-02,2024-05-15,1553,7.1,Smart Analytics +AI06154,ML Ops Engineer,77521,EUR,65893,EN,FL,Germany,L,Japan,100,"Deep Learning, Mathematics, Data Visualization, SQL, Azure",Associate,0,Telecommunications,2024-01-03,2024-03-15,573,7.7,Digital Transformation LLC +AI06155,AI Research Scientist,323583,CHF,291225,EX,FL,Switzerland,L,Kenya,0,"Azure, Java, AWS, Mathematics",Master,13,Manufacturing,2024-05-20,2024-07-29,1566,8.7,Cloud AI Solutions +AI06156,ML Ops Engineer,123796,GBP,92847,MI,FL,United Kingdom,L,Ukraine,0,"Python, Java, Azure",PhD,4,Media,2024-11-05,2024-12-27,2211,6.3,Advanced Robotics +AI06157,Data Engineer,191974,USD,191974,EX,FT,United States,L,United States,100,"Scala, Python, Git, AWS, Spark",Associate,15,Transportation,2024-06-12,2024-08-14,2068,8.2,Neural Networks Co +AI06158,Machine Learning Engineer,92459,USD,92459,MI,CT,Sweden,L,Sweden,0,"Deep Learning, Data Visualization, Statistics, Computer Vision, Azure",Bachelor,3,Energy,2024-03-03,2024-05-12,1148,5.1,Cognitive Computing +AI06159,Deep Learning Engineer,99147,EUR,84275,MI,FT,Germany,S,Germany,50,"Scala, TensorFlow, Spark",Associate,2,Gaming,2025-03-04,2025-04-08,1132,7.1,Machine Intelligence Group +AI06160,Principal Data Scientist,86412,CHF,77771,EN,CT,Switzerland,L,Turkey,0,"AWS, Azure, Git, Data Visualization, SQL",Master,0,Real Estate,2025-03-13,2025-04-06,2437,5.2,Algorithmic Solutions +AI06161,Machine Learning Engineer,208435,USD,208435,EX,FL,Finland,S,Czech Republic,100,"GCP, Scala, SQL",Master,19,Energy,2025-01-03,2025-02-18,2064,5.1,Algorithmic Solutions +AI06162,Head of AI,126593,CHF,113934,MI,FT,Switzerland,M,Switzerland,0,"Spark, Git, Linux",PhD,3,Education,2024-12-21,2025-01-12,1142,7,Neural Networks Co +AI06163,ML Ops Engineer,141683,USD,141683,SE,FL,Denmark,S,Denmark,100,"MLOps, NLP, Python, SQL, R",Associate,7,Finance,2024-02-21,2024-04-15,961,8.5,AI Innovations +AI06164,Data Engineer,72525,USD,72525,EN,PT,Norway,M,Austria,50,"Scala, Statistics, Git, SQL, Linux",PhD,1,Media,2024-04-11,2024-06-07,2328,5.4,Autonomous Tech +AI06165,Head of AI,210148,EUR,178626,EX,FL,Netherlands,S,Netherlands,50,"Git, Linux, Deep Learning, Data Visualization",Associate,16,Technology,2024-11-30,2025-01-04,1851,7.5,Algorithmic Solutions +AI06166,Data Engineer,100933,USD,100933,EX,CT,India,L,India,50,"Hadoop, MLOps, Docker, Git, Spark",Master,18,Government,2024-04-04,2024-05-21,1702,8,AI Innovations +AI06167,AI Product Manager,133499,USD,133499,SE,FT,Denmark,M,Denmark,100,"Spark, PyTorch, Linux",PhD,6,Manufacturing,2024-11-27,2024-12-29,1819,9.2,Algorithmic Solutions +AI06168,Computer Vision Engineer,143384,USD,143384,EX,PT,South Korea,S,South Korea,0,"MLOps, GCP, Docker, Statistics",PhD,19,Technology,2024-01-15,2024-02-23,1599,9.1,Cognitive Computing +AI06169,Head of AI,83098,USD,83098,EN,FL,Denmark,S,Denmark,50,"Linux, SQL, Spark",Associate,0,Telecommunications,2024-02-21,2024-03-12,1501,6.1,DeepTech Ventures +AI06170,ML Ops Engineer,58485,USD,58485,EN,CT,South Korea,S,South Korea,50,"NLP, Azure, Python",Master,1,Government,2024-09-02,2024-10-17,2191,7.2,Advanced Robotics +AI06171,AI Architect,43970,USD,43970,MI,PT,China,M,Luxembourg,0,"Computer Vision, MLOps, NLP, Statistics, PyTorch",PhD,4,Consulting,2025-01-29,2025-03-02,780,7.5,AI Innovations +AI06172,Head of AI,410273,CHF,369246,EX,FT,Switzerland,L,Switzerland,50,"Python, TensorFlow, Deep Learning",PhD,19,Education,2024-03-01,2024-03-28,1739,7,Machine Intelligence Group +AI06173,Principal Data Scientist,76227,SGD,99095,EN,CT,Singapore,L,Canada,50,"Python, Azure, TensorFlow, Java, Docker",Bachelor,0,Real Estate,2024-07-11,2024-09-12,1081,6.2,Predictive Systems +AI06174,Deep Learning Engineer,121236,CAD,151545,SE,FL,Canada,M,Canada,0,"TensorFlow, Linux, Python, MLOps",Bachelor,7,Energy,2024-02-10,2024-04-19,526,6.8,Cognitive Computing +AI06175,Computer Vision Engineer,82912,AUD,111931,EN,CT,Australia,L,Australia,50,"Python, Kubernetes, Tableau, TensorFlow, Deep Learning",Master,1,Consulting,2025-04-15,2025-05-28,1620,8.3,DeepTech Ventures +AI06176,Autonomous Systems Engineer,227232,AUD,306763,EX,FL,Australia,L,Australia,100,"Python, MLOps, SQL, Spark",Associate,14,Finance,2024-07-22,2024-09-21,1893,6,Cloud AI Solutions +AI06177,AI Specialist,46804,USD,46804,SE,FL,India,S,Italy,0,"Hadoop, Docker, Linux",Master,7,Real Estate,2024-06-02,2024-07-20,2125,6.9,Digital Transformation LLC +AI06178,Machine Learning Engineer,269514,USD,269514,EX,PT,Denmark,L,Denmark,50,"Java, Kubernetes, Data Visualization, Docker, GCP",PhD,16,Automotive,2024-07-21,2024-09-01,1570,9.7,Cloud AI Solutions +AI06179,NLP Engineer,37274,USD,37274,SE,CT,India,S,India,100,"GCP, R, Git, NLP",PhD,7,Technology,2024-01-29,2024-03-06,1576,8,TechCorp Inc +AI06180,Deep Learning Engineer,27007,USD,27007,EN,CT,China,M,China,50,"SQL, PyTorch, Git, Deep Learning, Azure",PhD,1,Finance,2024-12-06,2024-12-25,587,7.2,TechCorp Inc +AI06181,Research Scientist,80678,USD,80678,EX,PT,India,S,India,100,"R, Tableau, SQL",PhD,14,Gaming,2024-02-04,2024-04-11,1900,8.5,AI Innovations +AI06182,Data Engineer,270264,CHF,243238,EX,CT,Switzerland,M,Switzerland,0,"NLP, MLOps, Statistics, Scala",PhD,14,Retail,2024-10-28,2024-12-04,578,9.9,TechCorp Inc +AI06183,AI Product Manager,63878,EUR,54296,MI,FL,France,S,France,50,"Azure, Deep Learning, MLOps, TensorFlow, Kubernetes",PhD,3,Retail,2025-04-21,2025-05-16,2333,6,DataVision Ltd +AI06184,Research Scientist,280852,CHF,252767,EX,CT,Switzerland,L,Switzerland,0,"Git, Scala, Tableau, Linux, Statistics",Master,15,Transportation,2025-02-28,2025-05-04,562,9.8,Digital Transformation LLC +AI06185,Head of AI,103833,USD,103833,MI,FL,Ireland,M,Ireland,0,"PyTorch, Linux, Spark, Tableau, Deep Learning",Associate,3,Manufacturing,2024-05-18,2024-07-06,1743,7.9,Neural Networks Co +AI06186,AI Product Manager,200183,AUD,270247,EX,PT,Australia,S,Australia,50,"AWS, Python, Scala, Spark, Deep Learning",PhD,10,Retail,2024-06-06,2024-07-03,1737,6.9,Algorithmic Solutions +AI06187,Machine Learning Researcher,76963,USD,76963,EX,PT,India,M,India,100,"Kubernetes, Hadoop, Docker, Deep Learning, Statistics",PhD,15,Gaming,2025-04-01,2025-05-23,2228,6.1,TechCorp Inc +AI06188,NLP Engineer,119389,USD,119389,SE,PT,Sweden,M,Sweden,100,"Kubernetes, AWS, Python",Master,7,Healthcare,2024-04-06,2024-06-04,1618,6.8,AI Innovations +AI06189,Machine Learning Researcher,187897,EUR,159712,EX,FL,France,M,France,50,"Hadoop, GCP, Scala, Python, TensorFlow",Associate,18,Manufacturing,2024-04-02,2024-06-07,2109,5.5,TechCorp Inc +AI06190,AI Architect,82319,AUD,111131,MI,FL,Australia,M,Denmark,0,"Spark, Java, PyTorch, Docker, AWS",PhD,4,Manufacturing,2025-04-10,2025-06-01,2081,9.6,Predictive Systems +AI06191,Computer Vision Engineer,145319,USD,145319,SE,FT,Norway,M,Norway,100,"Java, MLOps, Linux, Python, GCP",Bachelor,7,Technology,2024-05-05,2024-05-27,549,7.3,Quantum Computing Inc +AI06192,Deep Learning Engineer,159987,EUR,135989,EX,FT,Germany,M,Germany,100,"Spark, Kubernetes, Deep Learning",PhD,15,Media,2024-11-22,2025-01-06,1827,8.1,DataVision Ltd +AI06193,AI Specialist,68999,USD,68999,EN,FT,United States,S,Russia,50,"Scala, Git, Data Visualization",Bachelor,0,Energy,2024-12-01,2025-02-10,2474,7.9,Predictive Systems +AI06194,Data Engineer,96411,JPY,10605210,MI,FT,Japan,M,Japan,100,"Statistics, Java, Git",Master,2,Education,2024-03-13,2024-05-24,1125,7.2,Advanced Robotics +AI06195,Robotics Engineer,262229,USD,262229,EX,PT,Sweden,L,Sweden,50,"Git, Kubernetes, Scala",PhD,17,Healthcare,2024-09-25,2024-12-05,1786,6,Advanced Robotics +AI06196,Data Analyst,77309,USD,77309,MI,CT,Israel,M,Israel,100,"SQL, Java, Python, Data Visualization",Associate,2,Automotive,2024-11-10,2025-01-19,823,6.1,Cloud AI Solutions +AI06197,Robotics Engineer,327821,USD,327821,EX,PT,Denmark,L,Denmark,0,"Azure, Python, MLOps, Scala",PhD,13,Gaming,2024-01-08,2024-02-17,2292,6.7,Future Systems +AI06198,NLP Engineer,97172,GBP,72879,EN,PT,United Kingdom,L,United Kingdom,100,"Statistics, Linux, Mathematics, Tableau, Kubernetes",PhD,0,Retail,2024-02-14,2024-04-02,819,7.2,DeepTech Ventures +AI06199,Autonomous Systems Engineer,58968,EUR,50123,EN,PT,Germany,L,Germany,50,"PyTorch, Java, TensorFlow, R, GCP",Associate,0,Telecommunications,2024-07-09,2024-08-09,2302,6.4,DataVision Ltd +AI06200,Machine Learning Researcher,209608,AUD,282971,EX,FL,Australia,M,Australia,0,"NLP, Python, Hadoop, Kubernetes",Master,18,Automotive,2025-03-04,2025-04-28,1596,5.5,Digital Transformation LLC +AI06201,Head of AI,47165,EUR,40090,EN,PT,Austria,S,Austria,0,"Python, TensorFlow, SQL",Bachelor,0,Finance,2025-02-12,2025-03-30,1483,6.5,Smart Analytics +AI06202,Data Engineer,95552,USD,95552,EN,FT,United States,L,United States,0,"Python, Computer Vision, Scala, TensorFlow, Git",Master,1,Media,2024-09-30,2024-11-30,1965,5.8,Cloud AI Solutions +AI06203,NLP Engineer,140834,EUR,119709,SE,PT,France,M,France,0,"NLP, TensorFlow, Java, Data Visualization, Mathematics",PhD,5,Finance,2024-01-21,2024-03-01,727,9.9,TechCorp Inc +AI06204,NLP Engineer,50964,USD,50964,EN,CT,Finland,M,Israel,100,"Docker, Azure, NLP, Linux",Associate,0,Consulting,2024-03-14,2024-03-31,1190,7.1,Cognitive Computing +AI06205,Machine Learning Researcher,141955,USD,141955,EX,FT,Israel,M,Israel,0,"TensorFlow, Spark, Hadoop, Python",PhD,12,Government,2024-11-10,2025-01-11,1814,6.9,DataVision Ltd +AI06206,Research Scientist,79587,USD,79587,MI,FT,Israel,M,Israel,50,"PyTorch, SQL, NLP",Associate,4,Transportation,2024-03-31,2024-06-03,1811,8.9,DataVision Ltd +AI06207,Data Engineer,114995,USD,114995,EX,PT,China,L,China,100,"Kubernetes, Data Visualization, SQL, Python",Bachelor,17,Consulting,2025-02-15,2025-04-23,566,6.2,DataVision Ltd +AI06208,ML Ops Engineer,65857,USD,65857,EN,PT,Israel,S,Malaysia,0,"Deep Learning, TensorFlow, Computer Vision",PhD,0,Media,2025-04-20,2025-06-08,1998,9.3,Predictive Systems +AI06209,AI Consultant,58926,USD,58926,EN,FT,Ireland,M,Portugal,100,"Scala, NLP, GCP, Hadoop",Associate,1,Manufacturing,2025-04-14,2025-05-12,597,9.8,Autonomous Tech +AI06210,AI Software Engineer,275093,USD,275093,EX,FL,Denmark,S,Denmark,100,"Git, Hadoop, Mathematics",Master,16,Government,2024-04-02,2024-06-11,2078,8.7,Neural Networks Co +AI06211,Machine Learning Engineer,220073,EUR,187062,EX,FL,Netherlands,L,Netherlands,50,"Python, Java, SQL, PyTorch",Bachelor,18,Energy,2024-11-23,2025-01-02,1489,5.1,Cloud AI Solutions +AI06212,Robotics Engineer,58905,GBP,44179,EN,FT,United Kingdom,S,New Zealand,50,"Python, Linux, Azure, AWS, Java",Associate,1,Finance,2024-06-06,2024-07-31,1625,7.1,Predictive Systems +AI06213,Principal Data Scientist,264666,USD,264666,EX,CT,Norway,M,Norway,100,"Git, NLP, SQL, PyTorch",PhD,11,Healthcare,2025-01-14,2025-02-27,1025,6.9,DeepTech Ventures +AI06214,Data Analyst,149181,EUR,126804,EX,PT,Austria,M,Austria,50,"SQL, Spark, Data Visualization, TensorFlow, GCP",Master,17,Healthcare,2024-07-24,2024-08-29,985,9.9,Future Systems +AI06215,ML Ops Engineer,92326,USD,92326,EN,FL,Sweden,L,Sweden,0,"Scala, Java, NLP",Associate,1,Gaming,2024-01-27,2024-04-04,2411,5.3,Autonomous Tech +AI06216,Autonomous Systems Engineer,103737,USD,103737,MI,FT,United States,S,United States,0,"Kubernetes, Docker, Deep Learning",Bachelor,4,Automotive,2024-10-21,2024-11-11,1472,8.1,TechCorp Inc +AI06217,AI Consultant,105787,EUR,89919,SE,PT,France,M,France,100,"Computer Vision, GCP, Deep Learning, PyTorch",Bachelor,9,Healthcare,2024-10-27,2025-01-03,1053,5.4,Digital Transformation LLC +AI06218,Data Engineer,121968,USD,121968,MI,FL,Denmark,M,Denmark,50,"SQL, TensorFlow, Linux",Associate,4,Retail,2025-03-22,2025-06-03,2484,7.9,Cloud AI Solutions +AI06219,Computer Vision Engineer,308831,CHF,277948,EX,FL,Switzerland,S,Switzerland,50,"GCP, Deep Learning, Python, Kubernetes, TensorFlow",PhD,17,Government,2025-01-03,2025-02-25,1901,8.6,Neural Networks Co +AI06220,AI Product Manager,52330,USD,52330,EN,PT,Sweden,M,Sweden,0,"GCP, Tableau, NLP",Associate,1,Gaming,2024-06-29,2024-08-27,623,9.9,Cloud AI Solutions +AI06221,NLP Engineer,105139,EUR,89368,MI,PT,Germany,M,Germany,0,"AWS, Java, Mathematics",Bachelor,2,Automotive,2024-01-09,2024-03-14,806,5.2,Predictive Systems +AI06222,AI Consultant,57833,USD,57833,MI,FT,China,L,Nigeria,100,"Java, Statistics, Tableau",PhD,3,Healthcare,2024-02-26,2024-03-23,1963,6.2,Quantum Computing Inc +AI06223,ML Ops Engineer,136814,CHF,123133,MI,FT,Switzerland,M,Switzerland,50,"GCP, Linux, Statistics, Mathematics",PhD,3,Manufacturing,2024-04-02,2024-05-02,1076,9.1,AI Innovations +AI06224,AI Architect,158438,USD,158438,EX,FL,South Korea,M,Malaysia,100,"Hadoop, MLOps, Java, Python, TensorFlow",Master,15,Retail,2025-03-16,2025-05-18,2329,5.3,AI Innovations +AI06225,NLP Engineer,45309,USD,45309,EN,PT,South Korea,M,South Korea,50,"PyTorch, Git, Kubernetes, Statistics, Deep Learning",Master,0,Finance,2024-03-18,2024-04-08,1552,6.5,Cloud AI Solutions +AI06226,AI Software Engineer,45432,USD,45432,EN,CT,Israel,S,Israel,100,"TensorFlow, Spark, Linux, Deep Learning, Java",Master,1,Manufacturing,2024-06-27,2024-08-22,555,6.4,DeepTech Ventures +AI06227,AI Product Manager,109543,CHF,98589,EN,FL,Switzerland,L,Estonia,100,"Docker, Git, Kubernetes, TensorFlow",PhD,0,Healthcare,2024-05-29,2024-07-02,1108,7.6,Cognitive Computing +AI06228,Head of AI,174342,USD,174342,EX,FT,Israel,M,Mexico,100,"Statistics, SQL, Data Visualization",Bachelor,13,Manufacturing,2024-05-14,2024-07-16,1145,6.4,Autonomous Tech +AI06229,Head of AI,52826,EUR,44902,EN,PT,Germany,M,Italy,0,"Linux, Computer Vision, SQL, Spark, PyTorch",Associate,1,Finance,2024-04-12,2024-05-09,1680,8.7,Predictive Systems +AI06230,AI Research Scientist,43403,USD,43403,MI,FT,China,S,China,0,"Git, NLP, Docker, TensorFlow, AWS",Bachelor,3,Technology,2024-01-20,2024-03-04,2127,5.5,Cognitive Computing +AI06231,AI Specialist,58657,AUD,79187,EN,FT,Australia,L,Australia,50,"Kubernetes, Scala, Linux, Spark",Associate,1,Finance,2024-03-10,2024-05-05,2476,6.8,Quantum Computing Inc +AI06232,ML Ops Engineer,334601,CHF,301141,EX,CT,Switzerland,L,Indonesia,0,"PyTorch, Azure, MLOps",Master,14,Gaming,2024-08-01,2024-09-21,1260,7.9,Predictive Systems +AI06233,Computer Vision Engineer,91169,AUD,123078,MI,FL,Australia,M,Australia,50,"SQL, PyTorch, R, Java",Master,2,Gaming,2024-06-07,2024-06-24,1508,6.8,DeepTech Ventures +AI06234,Machine Learning Engineer,89246,EUR,75859,MI,CT,France,S,France,0,"Spark, Hadoop, Git, SQL",Associate,3,Energy,2024-07-11,2024-09-11,817,7.5,Algorithmic Solutions +AI06235,AI Consultant,70820,AUD,95607,EN,CT,Australia,L,Australia,100,"Tableau, Linux, R, Azure, Scala",Master,1,Transportation,2024-08-24,2024-10-30,2272,9.1,Cognitive Computing +AI06236,Data Engineer,127145,SGD,165289,SE,CT,Singapore,L,Singapore,50,"NLP, Python, SQL, Docker, GCP",PhD,7,Retail,2025-04-29,2025-06-14,1599,6.3,Future Systems +AI06237,Computer Vision Engineer,74447,GBP,55835,EN,CT,United Kingdom,S,United Kingdom,100,"Linux, Data Visualization, TensorFlow",Bachelor,1,Technology,2024-01-21,2024-02-12,1024,9.2,DataVision Ltd +AI06238,AI Product Manager,85168,GBP,63876,MI,FT,United Kingdom,M,Austria,100,"Python, MLOps, Java, Computer Vision, Git",PhD,3,Energy,2024-08-04,2024-09-28,2129,6.1,Digital Transformation LLC +AI06239,AI Consultant,333929,CHF,300536,EX,CT,Switzerland,L,Switzerland,100,"SQL, PyTorch, MLOps, Computer Vision, AWS",PhD,14,Transportation,2024-03-31,2024-06-03,1031,9.5,Smart Analytics +AI06240,Deep Learning Engineer,119472,EUR,101551,SE,FT,Austria,M,Denmark,100,"Python, Spark, TensorFlow",Master,7,Retail,2024-03-17,2024-05-16,914,8.2,Neural Networks Co +AI06241,Machine Learning Engineer,185566,USD,185566,EX,CT,United States,M,Ireland,100,"Kubernetes, Statistics, R, Docker, Computer Vision",Associate,13,Real Estate,2024-01-09,2024-03-18,669,5.1,AI Innovations +AI06242,Deep Learning Engineer,98638,AUD,133161,SE,CT,Australia,S,Philippines,50,"Mathematics, Python, GCP, Azure",Associate,7,Healthcare,2024-10-07,2024-11-12,1188,5.6,Neural Networks Co +AI06243,Machine Learning Engineer,96950,EUR,82408,MI,PT,Netherlands,L,Netherlands,50,"Python, MLOps, Data Visualization",Master,2,Automotive,2024-06-22,2024-07-29,2329,7.2,Machine Intelligence Group +AI06244,AI Product Manager,55210,GBP,41408,EN,FT,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, Mathematics, Java",Associate,0,Healthcare,2024-04-23,2024-07-01,2059,6.1,Autonomous Tech +AI06245,Robotics Engineer,231279,USD,231279,EX,FL,South Korea,L,South Korea,0,"Git, TensorFlow, Python",Bachelor,19,Consulting,2024-10-07,2024-12-06,2187,8.7,Digital Transformation LLC +AI06246,ML Ops Engineer,125808,USD,125808,MI,FT,Denmark,L,Denmark,100,"NLP, Scala, Python",PhD,4,Education,2024-03-25,2024-05-16,532,6.3,Advanced Robotics +AI06247,Head of AI,201000,SGD,261300,EX,CT,Singapore,M,Singapore,100,"NLP, Java, Docker, Deep Learning",Bachelor,10,Education,2024-06-12,2024-08-13,598,5.9,Predictive Systems +AI06248,Machine Learning Researcher,235015,SGD,305520,EX,CT,Singapore,S,Singapore,0,"MLOps, Java, R, Kubernetes, Data Visualization",PhD,10,Finance,2024-10-18,2024-12-06,1281,8.8,Machine Intelligence Group +AI06249,Research Scientist,104461,AUD,141022,SE,PT,Australia,S,Australia,100,"PyTorch, SQL, AWS, Python, Deep Learning",Bachelor,7,Real Estate,2024-10-25,2024-12-24,949,6.9,TechCorp Inc +AI06250,AI Consultant,120951,USD,120951,MI,FT,Sweden,L,Sweden,100,"Deep Learning, Docker, R, Linux, MLOps",Associate,4,Education,2024-05-03,2024-06-20,1048,5.2,DeepTech Ventures +AI06251,Deep Learning Engineer,94126,USD,94126,MI,CT,Ireland,S,Ireland,100,"Statistics, Spark, Java, Deep Learning",Bachelor,4,Automotive,2024-09-30,2024-11-19,1008,5.6,Digital Transformation LLC +AI06252,Machine Learning Researcher,188011,USD,188011,EX,FL,Finland,S,Finland,100,"Git, Mathematics, Scala, PyTorch",Bachelor,16,Retail,2025-01-12,2025-03-08,2175,6.1,Digital Transformation LLC +AI06253,NLP Engineer,143061,USD,143061,SE,PT,Norway,M,China,0,"Statistics, Python, Tableau, Linux",PhD,9,Technology,2024-12-22,2025-02-05,1284,7.8,AI Innovations +AI06254,NLP Engineer,206350,EUR,175398,EX,CT,France,S,France,0,"Kubernetes, GCP, Hadoop, Statistics",Master,16,Gaming,2025-04-13,2025-05-21,919,6.7,Smart Analytics +AI06255,Data Analyst,60881,AUD,82189,EN,CT,Australia,S,Australia,0,"Scala, Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-03-26,2024-05-02,672,10,Smart Analytics +AI06256,Data Analyst,103178,EUR,87701,MI,FT,Austria,L,Austria,0,"Azure, Hadoop, AWS, Statistics",Bachelor,3,Finance,2025-04-08,2025-05-28,687,6.4,DataVision Ltd +AI06257,AI Software Engineer,81446,SGD,105880,MI,FL,Singapore,S,Singapore,100,"Docker, Hadoop, Data Visualization, Java, R",Bachelor,2,Healthcare,2025-01-28,2025-03-28,801,5.3,TechCorp Inc +AI06258,ML Ops Engineer,304317,GBP,228238,EX,FT,United Kingdom,L,Denmark,100,"GCP, Linux, Git",PhD,13,Transportation,2024-06-11,2024-07-10,1876,9.3,Cognitive Computing +AI06259,NLP Engineer,37648,USD,37648,SE,FL,India,S,India,50,"Spark, Scala, Git, Python, Azure",Bachelor,5,Technology,2024-09-29,2024-12-02,1398,5.8,Quantum Computing Inc +AI06260,AI Architect,88718,GBP,66539,EN,CT,United Kingdom,L,United Kingdom,50,"Linux, Scala, Computer Vision",Associate,1,Consulting,2024-02-03,2024-02-17,946,9.1,Smart Analytics +AI06261,AI Consultant,36001,USD,36001,MI,FL,China,M,Ukraine,100,"Git, Mathematics, Spark",PhD,4,Finance,2024-01-26,2024-03-22,986,5.3,Advanced Robotics +AI06262,ML Ops Engineer,78519,CAD,98149,MI,CT,Canada,L,Canada,0,"Linux, Deep Learning, Python, TensorFlow",Associate,2,Transportation,2024-09-30,2024-10-20,870,7.7,AI Innovations +AI06263,AI Product Manager,109953,CHF,98958,MI,FT,Switzerland,M,Switzerland,0,"Java, Docker, Kubernetes, Scala",Master,4,Consulting,2025-01-22,2025-03-11,852,6.5,Algorithmic Solutions +AI06264,Head of AI,105406,AUD,142298,SE,CT,Australia,S,Australia,100,"Docker, MLOps, NLP, Java, R",Master,7,Telecommunications,2024-01-19,2024-03-27,2213,7.6,Quantum Computing Inc +AI06265,AI Specialist,70408,USD,70408,EN,FT,Israel,L,South Korea,0,"Mathematics, AWS, Data Visualization, Docker",Bachelor,0,Gaming,2024-06-27,2024-07-12,562,8.7,AI Innovations +AI06266,AI Architect,220323,USD,220323,EX,PT,Sweden,S,Sweden,0,"PyTorch, Linux, Tableau, Computer Vision",Associate,13,Transportation,2025-04-26,2025-06-01,1088,8.3,Neural Networks Co +AI06267,AI Architect,163354,EUR,138851,EX,PT,France,M,France,0,"Azure, AWS, GCP",Associate,10,Telecommunications,2024-12-15,2024-12-29,814,8.2,AI Innovations +AI06268,Autonomous Systems Engineer,89007,SGD,115709,MI,CT,Singapore,L,Singapore,100,"SQL, Spark, Scala, Azure",Master,4,Finance,2024-01-04,2024-01-28,837,8.8,Quantum Computing Inc +AI06269,Computer Vision Engineer,89914,AUD,121384,EN,FT,Australia,L,Australia,50,"AWS, Scala, GCP",Associate,1,Technology,2024-12-16,2025-02-17,1937,5.5,Machine Intelligence Group +AI06270,NLP Engineer,117917,USD,117917,SE,FL,Israel,M,Israel,0,"Python, NLP, Git",Master,8,Consulting,2024-07-22,2024-09-06,701,9.3,Cognitive Computing +AI06271,AI Specialist,86279,AUD,116477,MI,FT,Australia,S,Australia,0,"AWS, Docker, Git, Data Visualization",Bachelor,3,Gaming,2025-01-25,2025-03-07,828,6.5,AI Innovations +AI06272,Computer Vision Engineer,232296,USD,232296,EX,CT,Denmark,S,Denmark,0,"Statistics, Kubernetes, Linux, NLP",Associate,15,Manufacturing,2024-05-31,2024-07-09,2320,5.7,AI Innovations +AI06273,Principal Data Scientist,84539,USD,84539,MI,PT,Israel,S,Israel,0,"R, Scala, Data Visualization, Java, Statistics",Associate,3,Consulting,2024-05-14,2024-07-11,1864,5.8,TechCorp Inc +AI06274,Autonomous Systems Engineer,191852,CHF,172667,SE,FT,Switzerland,S,Switzerland,50,"Spark, PyTorch, Mathematics, Data Visualization, MLOps",Associate,7,Government,2024-10-11,2024-11-16,1459,9.6,Cognitive Computing +AI06275,Head of AI,271790,USD,271790,EX,CT,Denmark,S,Denmark,50,"NLP, Scala, Git",Master,16,Finance,2024-12-15,2025-02-25,609,6.1,Cloud AI Solutions +AI06276,Head of AI,69511,USD,69511,EN,CT,Ireland,M,Ireland,50,"Python, Docker, Computer Vision, Statistics, GCP",PhD,1,Finance,2024-03-02,2024-03-24,2017,6.3,AI Innovations +AI06277,AI Research Scientist,92982,USD,92982,EN,PT,Denmark,M,Denmark,0,"Linux, PyTorch, Hadoop",PhD,1,Manufacturing,2025-03-18,2025-04-02,2141,7.1,Digital Transformation LLC +AI06278,Machine Learning Researcher,123526,EUR,104997,EX,FL,Germany,S,Germany,0,"Docker, Linux, Data Visualization, Statistics",PhD,10,Automotive,2024-03-03,2024-05-01,856,5.5,Smart Analytics +AI06279,AI Consultant,184103,SGD,239334,SE,PT,Singapore,L,Singapore,100,"Kubernetes, Spark, Tableau, Hadoop, Docker",Master,5,Gaming,2024-08-14,2024-09-25,2427,7.2,Cloud AI Solutions +AI06280,AI Research Scientist,58966,USD,58966,MI,FL,China,L,Estonia,50,"Spark, AWS, Azure, Mathematics",Associate,2,Technology,2024-02-12,2024-04-14,2263,8.1,Cognitive Computing +AI06281,Robotics Engineer,118203,USD,118203,SE,PT,Ireland,M,Ireland,50,"Docker, Kubernetes, Data Visualization, GCP, Deep Learning",PhD,6,Finance,2024-02-16,2024-03-31,1541,9.4,TechCorp Inc +AI06282,Machine Learning Researcher,307747,USD,307747,EX,PT,Norway,L,Norway,0,"PyTorch, Spark, Data Visualization, AWS",PhD,11,Transportation,2024-12-23,2025-02-04,1840,7.3,Advanced Robotics +AI06283,Computer Vision Engineer,180858,JPY,19894380,EX,PT,Japan,L,Japan,100,"TensorFlow, Java, NLP, Docker, Computer Vision",Associate,14,Healthcare,2024-08-31,2024-09-26,1599,6,Machine Intelligence Group +AI06284,NLP Engineer,93668,SGD,121768,EN,FL,Singapore,L,Singapore,0,"Docker, PyTorch, Statistics",PhD,0,Media,2025-03-21,2025-04-22,1615,5.8,AI Innovations +AI06285,Computer Vision Engineer,74686,USD,74686,MI,FL,Ireland,S,Ireland,50,"Python, PyTorch, GCP, Deep Learning",Master,4,Government,2024-01-20,2024-03-19,2252,8.7,Digital Transformation LLC +AI06286,ML Ops Engineer,116392,USD,116392,SE,FL,South Korea,M,South Korea,50,"Hadoop, Scala, Python, R, Statistics",PhD,6,Media,2025-01-25,2025-03-28,1578,7.9,DataVision Ltd +AI06287,AI Architect,76585,GBP,57439,EN,CT,United Kingdom,M,Russia,100,"Tableau, Deep Learning, Git, SQL",Bachelor,1,Retail,2025-03-05,2025-04-16,911,9.1,Neural Networks Co +AI06288,Computer Vision Engineer,178074,CAD,222593,EX,FL,Canada,S,Canada,0,"Linux, SQL, Hadoop, PyTorch, Kubernetes",Master,19,Gaming,2025-01-29,2025-02-12,1184,6.6,Smart Analytics +AI06289,AI Consultant,28737,USD,28737,EN,PT,China,M,China,100,"GCP, R, Data Visualization",PhD,1,Media,2025-04-03,2025-06-14,1804,5.1,AI Innovations +AI06290,AI Research Scientist,175508,USD,175508,EX,CT,Ireland,S,Norway,100,"Kubernetes, AWS, Deep Learning, MLOps, SQL",PhD,19,Finance,2025-03-02,2025-04-29,2085,6,DataVision Ltd +AI06291,AI Product Manager,52615,USD,52615,EN,FL,South Korea,M,South Korea,50,"Data Visualization, MLOps, SQL",Associate,1,Finance,2024-07-10,2024-08-02,1516,7.9,DataVision Ltd +AI06292,ML Ops Engineer,177787,USD,177787,SE,PT,Norway,M,Norway,100,"Python, MLOps, Scala, R",Master,7,Finance,2025-01-07,2025-03-17,1543,7.3,Smart Analytics +AI06293,Robotics Engineer,67831,EUR,57656,EN,FL,France,S,France,100,"Python, Git, Hadoop, Spark",Master,0,Real Estate,2024-01-05,2024-02-03,673,5.5,Autonomous Tech +AI06294,Data Engineer,79450,USD,79450,EN,PT,Sweden,L,Finland,100,"Mathematics, Java, Python",Master,1,Retail,2024-03-19,2024-05-21,873,8.6,Digital Transformation LLC +AI06295,AI Research Scientist,61213,USD,61213,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Tableau, Linux, Statistics",Bachelor,0,Consulting,2024-11-16,2025-01-14,842,8.2,Neural Networks Co +AI06296,ML Ops Engineer,142856,USD,142856,SE,FL,United States,M,United States,50,"Git, SQL, Data Visualization, Linux, AWS",Associate,6,Government,2024-09-16,2024-11-24,1332,6.9,Predictive Systems +AI06297,AI Architect,49252,CAD,61565,EN,FT,Canada,S,Canada,50,"Java, R, GCP, SQL, Docker",Master,0,Finance,2024-12-20,2025-01-24,2021,8.7,Neural Networks Co +AI06298,ML Ops Engineer,102093,USD,102093,EX,PT,China,S,Netherlands,0,"Kubernetes, Python, R, Java",Associate,13,Consulting,2024-02-24,2024-04-07,902,7.4,AI Innovations +AI06299,Data Scientist,152000,USD,152000,SE,PT,United States,S,United States,100,"Azure, Mathematics, Python, TensorFlow",PhD,8,Retail,2025-01-10,2025-02-20,839,7.6,AI Innovations +AI06300,AI Research Scientist,145423,AUD,196321,SE,FT,Australia,L,Australia,100,"Mathematics, Git, Python, TensorFlow",PhD,7,Manufacturing,2024-06-24,2024-08-22,1828,8.8,DeepTech Ventures +AI06301,AI Architect,65475,USD,65475,SE,FT,China,M,China,0,"Linux, Computer Vision, R, Statistics",PhD,7,Technology,2024-12-30,2025-03-04,2327,9.9,Neural Networks Co +AI06302,ML Ops Engineer,240444,GBP,180333,EX,CT,United Kingdom,M,United Kingdom,0,"Git, SQL, R, NLP",PhD,19,Education,2024-09-12,2024-11-02,2186,6,AI Innovations +AI06303,Autonomous Systems Engineer,82512,EUR,70135,EN,FT,Germany,L,Germany,50,"Azure, AWS, MLOps",Master,1,Consulting,2025-03-08,2025-04-01,609,9.9,DeepTech Ventures +AI06304,AI Software Engineer,130547,JPY,14360170,MI,CT,Japan,L,Japan,100,"PyTorch, GCP, Kubernetes, AWS",PhD,2,Media,2025-02-03,2025-03-02,1276,6.2,TechCorp Inc +AI06305,Data Engineer,88285,EUR,75042,EN,FL,Germany,L,Germany,50,"Azure, R, Deep Learning, Linux",PhD,0,Education,2024-12-07,2025-02-14,2151,5,Cloud AI Solutions +AI06306,AI Software Engineer,127722,USD,127722,EX,PT,South Korea,S,South Korea,50,"SQL, Kubernetes, MLOps, Computer Vision, NLP",Associate,16,Transportation,2024-07-02,2024-08-04,2126,5.6,Quantum Computing Inc +AI06307,AI Consultant,267077,USD,267077,EX,PT,Norway,M,Norway,50,"Python, Kubernetes, Azure",Bachelor,18,Telecommunications,2025-04-01,2025-05-14,766,8.4,DeepTech Ventures +AI06308,ML Ops Engineer,178106,EUR,151390,EX,CT,Germany,L,Germany,0,"Spark, Git, Tableau, Python",Associate,19,Energy,2025-03-29,2025-04-23,814,5.2,Autonomous Tech +AI06309,Principal Data Scientist,160177,USD,160177,SE,CT,Denmark,L,Israel,100,"AWS, Git, Python, Tableau, GCP",Master,7,Manufacturing,2024-08-28,2024-09-28,1921,6,Future Systems +AI06310,Data Engineer,123876,USD,123876,SE,FT,Israel,S,Israel,0,"SQL, Linux, MLOps, TensorFlow",PhD,9,Transportation,2024-03-30,2024-05-28,1307,8.5,Advanced Robotics +AI06311,Machine Learning Researcher,51598,USD,51598,EN,PT,Finland,M,Finland,0,"Data Visualization, Git, Python, Kubernetes",Associate,0,Telecommunications,2024-05-14,2024-07-13,2313,9.1,Cloud AI Solutions +AI06312,Deep Learning Engineer,127577,USD,127577,SE,FL,Israel,S,Israel,50,"Tableau, AWS, Azure, Python",Associate,6,Technology,2024-08-29,2024-09-20,2494,9.5,Digital Transformation LLC +AI06313,Machine Learning Researcher,64037,GBP,48028,EN,CT,United Kingdom,M,United Kingdom,100,"Spark, Python, Data Visualization",Associate,1,Gaming,2024-03-21,2024-05-16,1649,5.9,DeepTech Ventures +AI06314,AI Consultant,27121,USD,27121,EN,CT,India,L,India,50,"Tableau, Kubernetes, Azure, Scala",Bachelor,1,Retail,2024-09-21,2024-10-17,2379,7.9,AI Innovations +AI06315,AI Software Engineer,177989,USD,177989,SE,CT,United States,L,United States,100,"Python, Scala, TensorFlow, Linux, GCP",Master,6,Healthcare,2024-10-12,2024-11-07,522,7.8,Smart Analytics +AI06316,AI Software Engineer,84799,USD,84799,EN,FL,United States,S,United States,100,"NLP, R, Scala, Linux",Bachelor,0,Technology,2024-12-12,2025-02-14,809,6.8,Cognitive Computing +AI06317,ML Ops Engineer,130027,USD,130027,SE,PT,Israel,L,Israel,50,"R, TensorFlow, Tableau, Computer Vision",PhD,8,Real Estate,2024-04-18,2024-05-02,627,6.5,Future Systems +AI06318,Data Engineer,116389,CAD,145486,SE,PT,Canada,S,Canada,0,"Deep Learning, Java, Scala",Master,5,Automotive,2024-01-25,2024-03-27,583,9.2,Machine Intelligence Group +AI06319,AI Product Manager,16795,USD,16795,EN,FL,India,S,India,100,"R, Hadoop, SQL",Bachelor,0,Real Estate,2025-04-27,2025-06-12,1009,5.1,Algorithmic Solutions +AI06320,Research Scientist,79356,JPY,8729160,MI,FL,Japan,S,Japan,50,"Statistics, Git, MLOps",Associate,4,Real Estate,2024-05-07,2024-06-02,1580,7.1,Algorithmic Solutions +AI06321,AI Research Scientist,71342,SGD,92745,EN,PT,Singapore,L,Belgium,50,"Git, Kubernetes, GCP, Mathematics, Azure",Bachelor,0,Automotive,2024-05-19,2024-07-15,1611,9.4,Digital Transformation LLC +AI06322,Data Engineer,66947,GBP,50210,EN,FT,United Kingdom,M,United Kingdom,0,"R, Mathematics, Kubernetes, Deep Learning, NLP",Bachelor,0,Consulting,2024-02-24,2024-04-03,1935,8.7,Autonomous Tech +AI06323,Machine Learning Engineer,66042,USD,66042,EN,FT,Israel,S,Israel,0,"SQL, GCP, Linux, Tableau",Bachelor,1,Healthcare,2025-04-06,2025-05-09,521,9.6,DataVision Ltd +AI06324,AI Software Engineer,232173,CHF,208956,EX,FT,Switzerland,S,Switzerland,0,"Git, PyTorch, Mathematics, Hadoop, Azure",Bachelor,18,Technology,2024-03-31,2024-05-08,2066,8.1,TechCorp Inc +AI06325,Data Scientist,108812,GBP,81609,SE,FT,United Kingdom,S,Turkey,100,"SQL, R, Data Visualization, Azure",Associate,5,Technology,2025-01-05,2025-01-26,654,6.5,Digital Transformation LLC +AI06326,Research Scientist,96625,USD,96625,MI,PT,Ireland,S,Norway,0,"R, Computer Vision, Data Visualization",Master,2,Consulting,2024-06-30,2024-07-28,777,7.6,Quantum Computing Inc +AI06327,Data Scientist,256663,SGD,333662,EX,FL,Singapore,M,Singapore,0,"Python, Linux, TensorFlow, Mathematics",Master,14,Automotive,2024-07-19,2024-09-03,1871,9.5,Autonomous Tech +AI06328,Machine Learning Researcher,92568,USD,92568,MI,CT,Ireland,S,Ireland,0,"Azure, Python, MLOps, Kubernetes",Master,3,Manufacturing,2024-03-30,2024-05-28,2342,9.9,Advanced Robotics +AI06329,Computer Vision Engineer,85546,EUR,72714,MI,CT,France,M,Netherlands,50,"Spark, Python, SQL",Associate,3,Real Estate,2025-04-10,2025-05-17,1014,9.9,Future Systems +AI06330,Data Engineer,185667,USD,185667,EX,PT,Ireland,L,Ireland,0,"SQL, Deep Learning, Hadoop, TensorFlow, Mathematics",Master,15,Transportation,2025-03-07,2025-03-21,1512,9.8,Future Systems +AI06331,AI Research Scientist,94718,USD,94718,SE,CT,Israel,S,Israel,0,"PyTorch, NLP, GCP",Associate,9,Government,2024-03-05,2024-03-22,860,6.4,Algorithmic Solutions +AI06332,Research Scientist,153864,AUD,207716,SE,CT,Australia,L,Australia,100,"Linux, PyTorch, Spark, NLP",Bachelor,5,Energy,2024-03-17,2024-04-29,986,5.1,TechCorp Inc +AI06333,Computer Vision Engineer,49125,SGD,63863,EN,FL,Singapore,S,Singapore,100,"MLOps, Python, TensorFlow",Master,1,Energy,2025-02-20,2025-04-04,1236,8,TechCorp Inc +AI06334,AI Software Engineer,79549,SGD,103414,EN,PT,Singapore,M,Singapore,100,"Python, R, Kubernetes, Computer Vision",Master,1,Transportation,2024-08-03,2024-08-19,1979,8,Cognitive Computing +AI06335,AI Research Scientist,95354,USD,95354,MI,FL,Sweden,S,Sweden,0,"Scala, Kubernetes, Spark, Hadoop",Associate,3,Manufacturing,2024-06-18,2024-07-13,2489,9.8,DeepTech Ventures +AI06336,AI Architect,91154,CHF,82039,EN,FL,Switzerland,L,Switzerland,100,"AWS, Azure, Python, Java",Master,1,Finance,2024-05-19,2024-06-17,1997,7.1,Autonomous Tech +AI06337,AI Specialist,76991,GBP,57743,EN,PT,United Kingdom,M,United Kingdom,50,"Java, Scala, Azure, Hadoop, Computer Vision",PhD,1,Technology,2024-02-21,2024-03-13,2053,9,Machine Intelligence Group +AI06338,AI Software Engineer,64003,USD,64003,EN,FL,Israel,M,Israel,100,"R, Git, Statistics, MLOps",Bachelor,1,Energy,2024-12-19,2025-01-22,1438,9.1,Neural Networks Co +AI06339,AI Product Manager,107493,EUR,91369,MI,FT,Netherlands,M,Netherlands,100,"Scala, Spark, Deep Learning",Master,2,Gaming,2024-04-10,2024-05-24,1960,9.6,Machine Intelligence Group +AI06340,Machine Learning Researcher,54975,JPY,6047250,EN,CT,Japan,S,Japan,0,"Hadoop, Git, Python",PhD,1,Real Estate,2025-04-13,2025-05-24,702,7.9,Future Systems +AI06341,AI Research Scientist,157422,USD,157422,SE,PT,Norway,L,Norway,50,"Spark, Statistics, PyTorch, Kubernetes",Master,8,Telecommunications,2024-10-16,2024-12-09,616,5.9,Digital Transformation LLC +AI06342,Computer Vision Engineer,289891,USD,289891,EX,FL,Norway,L,Finland,100,"Kubernetes, TensorFlow, PyTorch",Associate,11,Finance,2024-08-01,2024-09-09,1979,9.5,Machine Intelligence Group +AI06343,AI Research Scientist,111548,CHF,100393,EN,PT,Switzerland,M,Australia,100,"NLP, R, Hadoop, Java",PhD,0,Gaming,2024-08-07,2024-09-14,1085,8.2,AI Innovations +AI06344,Computer Vision Engineer,89985,EUR,76487,MI,PT,Austria,L,Austria,50,"Computer Vision, Spark, MLOps",Bachelor,4,Real Estate,2024-04-19,2024-06-13,2089,8.6,TechCorp Inc +AI06345,Data Engineer,67846,USD,67846,EN,FL,Finland,S,Finland,100,"Hadoop, MLOps, Computer Vision, SQL, Java",Bachelor,1,Healthcare,2024-04-21,2024-06-19,2207,5.6,Algorithmic Solutions +AI06346,Autonomous Systems Engineer,54041,EUR,45935,EN,PT,Austria,S,Austria,0,"TensorFlow, Scala, Kubernetes, Tableau",PhD,1,Transportation,2024-11-28,2024-12-24,919,7,Neural Networks Co +AI06347,Autonomous Systems Engineer,72359,USD,72359,SE,PT,China,L,China,0,"PyTorch, Computer Vision, Java, AWS",PhD,7,Government,2025-03-13,2025-05-07,1032,6.8,Cognitive Computing +AI06348,NLP Engineer,123879,USD,123879,SE,PT,Finland,S,Austria,0,"AWS, Hadoop, Mathematics",Associate,8,Media,2025-04-30,2025-07-02,828,7.2,Predictive Systems +AI06349,AI Product Manager,166701,USD,166701,SE,FL,Ireland,L,Ghana,100,"NLP, Git, Hadoop, PyTorch",Associate,8,Transportation,2024-12-11,2024-12-30,2134,5.5,Quantum Computing Inc +AI06350,AI Product Manager,129156,CAD,161445,SE,PT,Canada,S,Nigeria,50,"PyTorch, SQL, TensorFlow, Kubernetes",Bachelor,8,Education,2024-02-11,2024-03-16,1419,8.9,Cloud AI Solutions +AI06351,NLP Engineer,120933,USD,120933,MI,FL,Denmark,M,Denmark,50,"Mathematics, Computer Vision, GCP, PyTorch, SQL",Bachelor,4,Media,2025-03-23,2025-05-09,1949,5.5,Advanced Robotics +AI06352,Computer Vision Engineer,81946,USD,81946,EN,PT,Finland,L,Indonesia,100,"Deep Learning, Data Visualization, PyTorch, MLOps, Computer Vision",PhD,0,Media,2024-06-12,2024-08-18,814,8.1,AI Innovations +AI06353,Machine Learning Engineer,70100,USD,70100,EN,FT,Sweden,L,Sweden,100,"R, Linux, Mathematics, TensorFlow",Master,1,Telecommunications,2024-08-28,2024-10-07,1311,6.1,Digital Transformation LLC +AI06354,Machine Learning Engineer,159640,CHF,143676,MI,CT,Switzerland,L,Mexico,50,"Hadoop, Python, Azure, Linux, Java",Associate,3,Government,2024-04-01,2024-05-10,915,8.4,Algorithmic Solutions +AI06355,AI Architect,137323,USD,137323,SE,CT,United States,S,United States,100,"Tableau, Deep Learning, Git",Bachelor,5,Media,2025-01-16,2025-03-10,2296,5.5,DataVision Ltd +AI06356,AI Specialist,173170,USD,173170,SE,FL,Norway,S,Germany,100,"Git, Linux, Python, Tableau",Master,6,Consulting,2024-02-12,2024-04-20,501,8.8,DataVision Ltd +AI06357,Data Engineer,72402,SGD,94123,EN,CT,Singapore,M,Argentina,0,"MLOps, Mathematics, Statistics, Scala",Bachelor,0,Telecommunications,2024-12-27,2025-03-08,1616,6.4,DataVision Ltd +AI06358,AI Software Engineer,138464,CAD,173080,SE,FL,Canada,L,Canada,100,"Azure, R, Statistics, Spark, TensorFlow",PhD,8,Automotive,2025-04-02,2025-05-28,2151,8.2,Machine Intelligence Group +AI06359,Research Scientist,132681,USD,132681,SE,FL,Israel,M,Japan,100,"Git, Java, AWS",Associate,6,Gaming,2024-05-25,2024-06-19,1871,9.8,Cognitive Computing +AI06360,Data Engineer,255255,USD,255255,EX,FL,Denmark,M,Nigeria,100,"Azure, GCP, Statistics, SQL, Deep Learning",Bachelor,16,Media,2025-03-12,2025-05-03,1099,6.1,Autonomous Tech +AI06361,Data Scientist,65881,EUR,55999,EN,FT,Netherlands,L,Netherlands,100,"Python, GCP, Data Visualization",PhD,1,Media,2025-01-08,2025-03-05,704,5.1,Advanced Robotics +AI06362,Data Analyst,100927,USD,100927,SE,FT,Israel,M,Israel,100,"Python, Data Visualization, Mathematics, SQL, Java",Bachelor,6,Telecommunications,2024-08-03,2024-08-21,1875,7.6,TechCorp Inc +AI06363,ML Ops Engineer,158295,USD,158295,EX,FL,Ireland,M,Finland,0,"Tableau, Docker, SQL",Associate,18,Telecommunications,2024-04-27,2024-05-18,1494,9.9,DataVision Ltd +AI06364,NLP Engineer,62963,GBP,47222,EN,FL,United Kingdom,M,United Kingdom,50,"Scala, Java, R, SQL",Master,0,Telecommunications,2024-02-06,2024-04-14,535,6.2,Neural Networks Co +AI06365,Machine Learning Researcher,100228,USD,100228,MI,FT,Israel,L,Israel,100,"Java, Mathematics, TensorFlow, Python",Bachelor,2,Consulting,2024-12-24,2025-01-12,1774,5.4,Quantum Computing Inc +AI06366,Computer Vision Engineer,74437,EUR,63271,EN,PT,France,M,Spain,0,"Kubernetes, Python, Spark, Linux, SQL",Bachelor,1,Energy,2024-07-30,2024-09-13,1328,6.8,Cognitive Computing +AI06367,Computer Vision Engineer,82236,USD,82236,EX,CT,China,M,China,50,"MLOps, SQL, Statistics, Scala",Associate,16,Healthcare,2024-08-21,2024-10-10,2143,5.8,Algorithmic Solutions +AI06368,Data Analyst,161597,EUR,137357,EX,FT,Germany,L,Portugal,100,"PyTorch, Mathematics, Hadoop, NLP",Master,10,Technology,2024-09-02,2024-10-16,1862,5.3,Smart Analytics +AI06369,Research Scientist,158726,USD,158726,EX,FT,United States,S,United States,0,"Kubernetes, R, Computer Vision, Deep Learning, Statistics",Associate,19,Energy,2024-06-24,2024-08-20,1436,7.4,Autonomous Tech +AI06370,Robotics Engineer,42660,USD,42660,SE,FT,India,M,India,0,"NLP, SQL, Git, PyTorch",Master,6,Consulting,2024-08-21,2024-09-14,1864,5.6,Cognitive Computing +AI06371,Head of AI,201912,CHF,181721,EX,FL,Switzerland,S,Switzerland,100,"Python, R, Data Visualization, Computer Vision",PhD,14,Healthcare,2024-10-19,2024-11-23,755,7.7,Predictive Systems +AI06372,AI Research Scientist,16975,USD,16975,EN,FL,India,S,India,50,"Deep Learning, SQL, MLOps, R, Docker",Bachelor,1,Telecommunications,2024-04-07,2024-05-27,1613,8.3,Quantum Computing Inc +AI06373,Data Analyst,65768,USD,65768,EN,FT,United States,M,Czech Republic,0,"Java, Hadoop, Kubernetes, Computer Vision, Statistics",Bachelor,1,Education,2024-06-05,2024-07-05,589,5.9,AI Innovations +AI06374,Machine Learning Engineer,31201,USD,31201,MI,FL,India,M,India,0,"Linux, GCP, Data Visualization",Bachelor,4,Retail,2024-01-18,2024-02-12,1186,6.2,Advanced Robotics +AI06375,AI Research Scientist,99393,EUR,84484,MI,FL,France,L,China,50,"Mathematics, Docker, Python, TensorFlow, Tableau",Master,2,Consulting,2024-08-13,2024-09-20,523,8.9,DeepTech Ventures +AI06376,Data Analyst,184065,EUR,156455,EX,FT,Germany,L,Germany,50,"Kubernetes, PyTorch, Tableau, Mathematics",PhD,12,Gaming,2025-04-03,2025-05-13,703,6.7,TechCorp Inc +AI06377,AI Specialist,173893,USD,173893,SE,CT,Norway,M,Norway,0,"AWS, Mathematics, Python",Master,6,Gaming,2024-05-27,2024-08-03,1454,5.5,Cloud AI Solutions +AI06378,NLP Engineer,112570,USD,112570,SE,FL,South Korea,S,Romania,50,"Spark, Git, MLOps, Scala",PhD,6,Technology,2025-01-29,2025-02-20,1131,8.1,TechCorp Inc +AI06379,AI Product Manager,86672,USD,86672,MI,CT,Finland,M,Finland,50,"Git, R, Docker, AWS",Bachelor,2,Automotive,2024-08-28,2024-10-27,849,7.3,Future Systems +AI06380,Data Scientist,225977,USD,225977,SE,FL,Norway,L,Argentina,50,"Linux, Data Visualization, Spark",PhD,9,Consulting,2024-11-21,2024-12-05,1561,5.2,Digital Transformation LLC +AI06381,AI Consultant,65278,AUD,88125,MI,CT,Australia,S,Austria,100,"AWS, Data Visualization, Tableau",Master,4,Real Estate,2024-02-20,2024-03-09,1960,5.2,Predictive Systems +AI06382,Robotics Engineer,103808,EUR,88237,SE,CT,Austria,S,Norway,100,"Data Visualization, MLOps, Tableau, PyTorch",PhD,7,Education,2024-06-21,2024-07-08,2354,8.6,TechCorp Inc +AI06383,Data Analyst,202963,CAD,253704,EX,FL,Canada,M,Canada,50,"Deep Learning, Scala, Python, Mathematics",Bachelor,11,Technology,2024-03-02,2024-04-12,568,5.6,Neural Networks Co +AI06384,ML Ops Engineer,85463,USD,85463,EX,FT,China,S,China,100,"Scala, Kubernetes, Deep Learning, NLP",Associate,15,Healthcare,2024-08-22,2024-10-15,1703,7.8,TechCorp Inc +AI06385,AI Consultant,104466,USD,104466,EN,FT,Norway,L,Norway,100,"Kubernetes, PyTorch, Hadoop, Computer Vision",PhD,1,Healthcare,2025-01-22,2025-03-04,1730,6.4,Algorithmic Solutions +AI06386,Machine Learning Engineer,63202,USD,63202,MI,FL,South Korea,M,Poland,50,"Python, SQL, Statistics, Spark",Bachelor,3,Telecommunications,2025-03-08,2025-04-10,2044,6.1,Neural Networks Co +AI06387,Head of AI,120132,USD,120132,SE,PT,Norway,S,Norway,0,"Java, SQL, Python, R, Linux",Bachelor,5,Education,2024-03-25,2024-05-09,1500,5,Autonomous Tech +AI06388,Robotics Engineer,83672,CHF,75305,EN,CT,Switzerland,S,India,100,"NLP, Data Visualization, Tableau",Bachelor,1,Automotive,2024-12-11,2024-12-25,2484,6,DeepTech Ventures +AI06389,Data Analyst,74974,USD,74974,EN,FT,Norway,S,Norway,0,"SQL, Computer Vision, R, Hadoop",PhD,1,Healthcare,2024-03-20,2024-05-27,899,8,DeepTech Ventures +AI06390,Research Scientist,70564,USD,70564,EN,CT,Sweden,S,Sweden,50,"SQL, Data Visualization, GCP, MLOps",Master,0,Government,2024-02-26,2024-05-08,2322,8.4,Neural Networks Co +AI06391,AI Consultant,181975,SGD,236568,SE,FL,Singapore,L,South Korea,0,"Azure, Java, Hadoop, PyTorch",Master,6,Transportation,2024-04-30,2024-06-30,2186,5.1,Digital Transformation LLC +AI06392,Data Scientist,125178,CHF,112660,EN,CT,Switzerland,L,Switzerland,100,"Docker, Azure, SQL, Computer Vision",Bachelor,1,Government,2025-03-10,2025-05-04,1828,8,Smart Analytics +AI06393,AI Software Engineer,118802,USD,118802,EX,FT,South Korea,M,Estonia,0,"GCP, Docker, Computer Vision",PhD,10,Education,2024-08-29,2024-10-17,2036,8.6,Cognitive Computing +AI06394,Autonomous Systems Engineer,96565,USD,96565,SE,FL,Ireland,S,Ireland,50,"Mathematics, Python, TensorFlow, Spark, Hadoop",Master,9,Healthcare,2025-03-24,2025-05-18,1179,6.5,Cognitive Computing +AI06395,NLP Engineer,31256,USD,31256,EN,FL,China,S,Singapore,0,"AWS, Docker, Linux, Kubernetes",PhD,1,Energy,2025-04-18,2025-06-06,1804,5.5,Future Systems +AI06396,Data Engineer,75314,USD,75314,EN,FL,Finland,M,Finland,50,"Tableau, PyTorch, Statistics, NLP",PhD,1,Media,2024-10-29,2024-11-12,1581,7.3,Smart Analytics +AI06397,Research Scientist,51533,USD,51533,EN,FT,Sweden,M,Nigeria,0,"Computer Vision, AWS, GCP, Kubernetes",Associate,1,Finance,2024-12-29,2025-01-13,2031,10,Cloud AI Solutions +AI06398,Data Engineer,121829,USD,121829,MI,CT,Ireland,L,Ireland,0,"Python, Docker, Mathematics, Kubernetes",Associate,2,Automotive,2024-07-10,2024-08-01,2140,6.7,Future Systems +AI06399,AI Research Scientist,138335,EUR,117585,EX,PT,Germany,M,Germany,100,"Kubernetes, Spark, Statistics",Associate,19,Transportation,2025-04-21,2025-05-13,808,6.3,Quantum Computing Inc +AI06400,Data Engineer,143264,EUR,121774,SE,CT,Netherlands,M,Netherlands,50,"Hadoop, GCP, NLP",Bachelor,9,Healthcare,2024-02-05,2024-03-21,1023,9.2,Autonomous Tech +AI06401,Principal Data Scientist,121815,EUR,103543,SE,CT,Germany,L,Germany,50,"Scala, Python, Spark, MLOps",Associate,7,Manufacturing,2024-10-11,2024-12-13,1914,9.1,Digital Transformation LLC +AI06402,AI Consultant,49981,USD,49981,EN,PT,Finland,S,Thailand,0,"Python, AWS, SQL, NLP",PhD,1,Energy,2024-12-12,2025-02-17,1018,9.2,DataVision Ltd +AI06403,AI Specialist,150416,EUR,127854,EX,FL,Germany,M,Germany,100,"AWS, Python, TensorFlow, PyTorch, GCP",PhD,13,Telecommunications,2024-05-02,2024-07-03,2420,5.3,Quantum Computing Inc +AI06404,AI Software Engineer,121297,CHF,109167,EN,PT,Switzerland,L,Switzerland,0,"Scala, Docker, Mathematics, AWS, Java",PhD,0,Consulting,2024-06-06,2024-06-27,2283,6.8,AI Innovations +AI06405,Deep Learning Engineer,213889,AUD,288750,EX,FL,Australia,S,Australia,50,"Git, Mathematics, PyTorch, Java",Associate,11,Technology,2024-04-30,2024-06-15,2273,7.6,Algorithmic Solutions +AI06406,Deep Learning Engineer,130442,USD,130442,MI,CT,United States,L,United States,50,"Statistics, Git, PyTorch",PhD,2,Gaming,2024-03-19,2024-05-10,1768,5.4,Algorithmic Solutions +AI06407,Computer Vision Engineer,206439,CAD,258049,EX,FT,Canada,S,Canada,0,"Linux, Deep Learning, NLP",Master,10,Government,2024-01-18,2024-02-03,1229,8.2,AI Innovations +AI06408,Data Analyst,34594,USD,34594,EN,PT,China,L,China,100,"NLP, AWS, Azure, Python",Associate,0,Automotive,2025-04-20,2025-06-24,624,7,AI Innovations +AI06409,Deep Learning Engineer,162384,USD,162384,SE,PT,Israel,L,Kenya,100,"GCP, SQL, Linux",PhD,6,Automotive,2024-12-10,2025-02-19,2298,7.3,Advanced Robotics +AI06410,Data Analyst,102488,CAD,128110,SE,FT,Canada,M,Canada,50,"Statistics, MLOps, TensorFlow, Data Visualization, Spark",Associate,5,Consulting,2024-10-13,2024-11-13,680,8.7,TechCorp Inc +AI06411,ML Ops Engineer,156199,USD,156199,EX,FL,Finland,S,Finland,50,"R, Data Visualization, Docker",PhD,17,Automotive,2024-12-11,2025-02-11,2456,7.6,AI Innovations +AI06412,AI Software Engineer,150000,USD,150000,EX,FT,South Korea,L,South Korea,100,"Kubernetes, Azure, Spark",Associate,16,Government,2025-04-01,2025-04-23,939,9.9,Autonomous Tech +AI06413,Data Scientist,111963,CAD,139954,SE,FT,Canada,L,Canada,100,"Statistics, Scala, Linux",Master,5,Finance,2024-09-15,2024-10-08,638,6.8,Cloud AI Solutions +AI06414,Data Engineer,67558,USD,67558,MI,FL,Sweden,S,Sweden,50,"NLP, Python, Mathematics, AWS, Scala",Bachelor,3,Education,2024-02-01,2024-02-27,2198,5.2,Future Systems +AI06415,Data Scientist,75401,EUR,64091,MI,FL,France,M,France,100,"SQL, Linux, Kubernetes, Java, PyTorch",Bachelor,3,Automotive,2024-01-06,2024-01-25,2376,5.6,AI Innovations +AI06416,AI Research Scientist,77098,CHF,69388,EN,FL,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, GCP, Statistics",Master,1,Healthcare,2024-02-10,2024-04-19,1408,5.9,Future Systems +AI06417,Data Engineer,129667,GBP,97250,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Git, NLP, AWS",Associate,4,Telecommunications,2024-04-08,2024-05-17,1925,9.2,AI Innovations +AI06418,Robotics Engineer,62417,EUR,53054,EN,FL,Netherlands,M,Netherlands,100,"Python, R, Docker",PhD,0,Government,2024-07-22,2024-08-11,1830,6.3,Machine Intelligence Group +AI06419,AI Consultant,161660,JPY,17782600,SE,PT,Japan,M,Romania,0,"Computer Vision, Python, GCP",PhD,6,Real Estate,2024-05-04,2024-05-18,1197,6.1,Advanced Robotics +AI06420,Computer Vision Engineer,85425,AUD,115324,MI,PT,Australia,S,Australia,0,"Spark, Git, Python, Computer Vision, NLP",Associate,4,Consulting,2024-08-12,2024-10-07,1642,8.8,DeepTech Ventures +AI06421,AI Product Manager,269941,CHF,242947,EX,PT,Switzerland,S,Switzerland,0,"SQL, GCP, NLP, Spark",PhD,17,Finance,2024-01-06,2024-03-12,2138,7.5,Advanced Robotics +AI06422,Data Analyst,349432,USD,349432,EX,FT,Denmark,L,Denmark,0,"SQL, Linux, GCP, Hadoop, R",Associate,17,Energy,2024-10-17,2024-12-13,1557,9.9,Quantum Computing Inc +AI06423,Autonomous Systems Engineer,52126,USD,52126,SE,CT,China,S,Brazil,100,"Hadoop, Git, Java",Master,9,Government,2024-09-18,2024-11-02,1709,8,Predictive Systems +AI06424,AI Product Manager,166822,EUR,141799,EX,PT,Germany,M,Germany,0,"Hadoop, Data Visualization, Scala",PhD,11,Consulting,2025-01-23,2025-02-17,2222,5.9,Digital Transformation LLC +AI06425,Robotics Engineer,136925,AUD,184849,EX,CT,Australia,S,Australia,100,"MLOps, AWS, Python, Scala",Associate,17,Healthcare,2024-09-08,2024-09-30,2197,7.5,Advanced Robotics +AI06426,Deep Learning Engineer,98877,CAD,123596,MI,FT,Canada,L,Canada,100,"TensorFlow, Azure, Linux, Git",Master,2,Energy,2024-01-06,2024-03-18,871,5.4,Digital Transformation LLC +AI06427,Deep Learning Engineer,168236,EUR,143001,EX,FT,France,M,France,100,"AWS, Kubernetes, PyTorch",Bachelor,18,Telecommunications,2024-04-08,2024-05-15,1463,7.3,Advanced Robotics +AI06428,Machine Learning Engineer,102521,CAD,128151,MI,PT,Canada,L,Canada,100,"Kubernetes, R, SQL, Python",Bachelor,3,Gaming,2024-04-24,2024-06-19,697,6.9,Machine Intelligence Group +AI06429,Robotics Engineer,106928,USD,106928,MI,PT,Norway,M,Vietnam,0,"TensorFlow, Statistics, Spark",Associate,4,Real Estate,2024-11-10,2025-01-18,829,7.9,DeepTech Ventures +AI06430,Data Scientist,76026,GBP,57020,EN,FL,United Kingdom,S,United Kingdom,100,"Python, Docker, AWS, TensorFlow",PhD,0,Healthcare,2024-02-06,2024-03-14,2063,8.2,Algorithmic Solutions +AI06431,AI Specialist,88213,USD,88213,EN,FT,Sweden,L,Sweden,100,"Linux, TensorFlow, Computer Vision, Python, Hadoop",PhD,1,Energy,2024-05-03,2024-05-19,1771,8.7,Quantum Computing Inc +AI06432,AI Architect,82027,USD,82027,EN,FL,Sweden,L,Romania,0,"Mathematics, Hadoop, Scala",Associate,0,Media,2025-01-10,2025-01-25,2035,6.7,Advanced Robotics +AI06433,Robotics Engineer,109435,USD,109435,EN,FT,Denmark,L,Denmark,100,"Mathematics, GCP, Linux, MLOps, Python",PhD,1,Real Estate,2024-01-10,2024-03-01,545,8.5,Cognitive Computing +AI06434,Autonomous Systems Engineer,123502,AUD,166728,MI,FL,Australia,L,Sweden,100,"Python, Kubernetes, Deep Learning, Computer Vision, Hadoop",Associate,2,Education,2024-07-29,2024-08-27,1793,8,DataVision Ltd +AI06435,Autonomous Systems Engineer,80462,USD,80462,EN,PT,United States,S,Brazil,100,"Kubernetes, AWS, Hadoop",Associate,1,Consulting,2024-12-24,2025-01-24,1904,7.9,Machine Intelligence Group +AI06436,Machine Learning Engineer,109229,USD,109229,MI,PT,Ireland,M,Ireland,50,"Statistics, TensorFlow, Azure, GCP",PhD,4,Telecommunications,2024-04-09,2024-05-02,2303,9.2,Advanced Robotics +AI06437,AI Consultant,159957,EUR,135963,SE,FL,Netherlands,L,Netherlands,50,"GCP, TensorFlow, SQL, Computer Vision, Hadoop",Associate,9,Consulting,2024-07-17,2024-09-06,1452,5.2,Cloud AI Solutions +AI06438,Head of AI,65788,USD,65788,MI,CT,Sweden,S,Portugal,0,"Git, Tableau, Python",PhD,2,Retail,2024-10-17,2024-12-20,1066,9,Predictive Systems +AI06439,AI Software Engineer,100348,USD,100348,MI,FT,Ireland,L,Ireland,100,"Hadoop, Python, Git, AWS, Docker",Bachelor,2,Retail,2024-07-02,2024-09-07,2267,8,Digital Transformation LLC +AI06440,Computer Vision Engineer,47408,USD,47408,SE,FT,China,S,China,50,"NLP, Tableau, Python",Master,6,Gaming,2024-06-14,2024-08-26,2076,6.8,Machine Intelligence Group +AI06441,ML Ops Engineer,104139,USD,104139,SE,FT,Finland,M,Romania,100,"Python, TensorFlow, Statistics, Git",Associate,7,Energy,2024-10-29,2024-12-22,2233,9.6,Autonomous Tech +AI06442,AI Product Manager,88730,JPY,9760300,EN,FL,Japan,L,Japan,0,"R, Spark, MLOps, TensorFlow",PhD,1,Media,2024-05-23,2024-06-30,888,7.2,DataVision Ltd +AI06443,AI Product Manager,352205,USD,352205,EX,FT,Denmark,L,Denmark,100,"Computer Vision, Python, Tableau, NLP",Bachelor,16,Media,2024-10-27,2024-11-28,1380,6.6,Neural Networks Co +AI06444,AI Research Scientist,98921,EUR,84083,MI,FT,Austria,L,Austria,0,"Kubernetes, TensorFlow, Computer Vision, Git, NLP",PhD,2,Finance,2024-11-25,2025-01-28,2210,6.2,DeepTech Ventures +AI06445,Robotics Engineer,183596,EUR,156057,EX,CT,Netherlands,S,Netherlands,100,"Hadoop, Scala, Mathematics",Bachelor,19,Energy,2024-01-01,2024-03-11,1209,8.8,DataVision Ltd +AI06446,AI Architect,80147,USD,80147,MI,CT,Sweden,M,Denmark,50,"Python, Spark, GCP, Deep Learning, MLOps",PhD,2,Automotive,2024-03-28,2024-04-27,2364,6.9,Cloud AI Solutions +AI06447,Head of AI,38802,USD,38802,EN,FL,South Korea,S,South Korea,50,"Data Visualization, Git, Spark",Master,0,Manufacturing,2024-12-28,2025-02-14,1953,9.4,Quantum Computing Inc +AI06448,Robotics Engineer,42256,USD,42256,EN,FT,South Korea,M,South Korea,50,"PyTorch, GCP, SQL, Data Visualization",Bachelor,1,Automotive,2024-04-04,2024-05-22,2290,7.2,DataVision Ltd +AI06449,Machine Learning Researcher,295649,JPY,32521390,EX,FL,Japan,L,Japan,100,"Git, Mathematics, R, Python, Azure",Associate,10,Technology,2024-11-14,2025-01-12,2439,7.2,Cloud AI Solutions +AI06450,Head of AI,139693,GBP,104770,SE,PT,United Kingdom,S,United Kingdom,0,"GCP, Git, Tableau, MLOps",Master,5,Media,2025-03-24,2025-04-22,1262,5,AI Innovations +AI06451,Deep Learning Engineer,252118,USD,252118,EX,FT,Norway,S,Norway,50,"Hadoop, Computer Vision, Python",Associate,12,Automotive,2024-12-02,2025-02-03,1914,5.3,DataVision Ltd +AI06452,Research Scientist,96310,USD,96310,MI,FL,South Korea,L,South Korea,100,"Python, NLP, TensorFlow",Master,3,Real Estate,2024-09-30,2024-10-15,880,7.3,Advanced Robotics +AI06453,Machine Learning Researcher,97905,USD,97905,EX,FL,China,M,United States,50,"Python, Git, Statistics, Computer Vision, Linux",Bachelor,11,Consulting,2024-08-08,2024-09-15,1148,8.1,Smart Analytics +AI06454,AI Product Manager,74082,GBP,55562,EN,PT,United Kingdom,L,United Kingdom,50,"Python, Spark, Tableau, Mathematics, Linux",Master,0,Automotive,2024-08-27,2024-10-01,1197,9.4,Cloud AI Solutions +AI06455,ML Ops Engineer,189768,CHF,170791,SE,FL,Switzerland,S,Switzerland,100,"AWS, Linux, MLOps",Associate,5,Consulting,2024-01-19,2024-03-23,1493,9.4,AI Innovations +AI06456,AI Software Engineer,66570,USD,66570,EN,CT,Sweden,S,Philippines,50,"Computer Vision, GCP, Tableau",Master,1,Telecommunications,2024-07-07,2024-09-08,1957,5.9,Digital Transformation LLC +AI06457,Machine Learning Researcher,326160,CHF,293544,EX,FL,Switzerland,M,Indonesia,100,"Python, Java, Azure",Associate,16,Gaming,2025-01-04,2025-03-02,902,5.9,Cognitive Computing +AI06458,AI Research Scientist,78922,JPY,8681420,EN,FT,Japan,M,Japan,50,"Deep Learning, Computer Vision, PyTorch",Associate,0,Retail,2024-10-15,2024-12-27,1123,5.8,Quantum Computing Inc +AI06459,Data Analyst,49976,USD,49976,MI,PT,China,M,China,100,"Python, GCP, Tableau, SQL",Bachelor,2,Government,2024-12-24,2025-02-03,2010,8.6,Quantum Computing Inc +AI06460,Machine Learning Researcher,64771,USD,64771,EX,CT,China,M,China,50,"Tableau, Python, AWS, Spark, TensorFlow",PhD,10,Government,2025-04-03,2025-05-02,2118,9.9,Neural Networks Co +AI06461,Data Scientist,77752,EUR,66089,EN,CT,Netherlands,M,Netherlands,0,"R, GCP, Tableau, Python, AWS",Master,1,Transportation,2024-01-15,2024-03-05,818,8.1,TechCorp Inc +AI06462,AI Consultant,101180,AUD,136593,SE,CT,Australia,S,India,100,"Java, Data Visualization, PyTorch, Kubernetes, TensorFlow",Associate,5,Telecommunications,2024-04-24,2024-05-13,1032,8.6,Future Systems +AI06463,Computer Vision Engineer,207576,EUR,176440,EX,FL,France,L,France,50,"Statistics, NLP, Scala, Data Visualization",Associate,10,Manufacturing,2025-04-30,2025-05-21,716,8.2,Advanced Robotics +AI06464,AI Software Engineer,30028,USD,30028,MI,FL,India,L,India,50,"Tableau, Kubernetes, GCP, R, Deep Learning",Bachelor,4,Media,2024-01-15,2024-03-04,1402,9.2,Smart Analytics +AI06465,Robotics Engineer,243505,CAD,304381,EX,FT,Canada,L,Canada,50,"Spark, Scala, SQL, Java",Bachelor,12,Finance,2024-07-29,2024-09-12,2274,5.4,TechCorp Inc +AI06466,Robotics Engineer,51214,USD,51214,EN,FT,Finland,S,Finland,0,"Azure, GCP, Java",Master,1,Retail,2024-06-22,2024-07-06,802,7.3,Quantum Computing Inc +AI06467,Data Scientist,76863,CHF,69177,EN,CT,Switzerland,M,Switzerland,0,"Scala, Git, Statistics",Associate,0,Energy,2024-02-05,2024-03-24,1557,7.6,Predictive Systems +AI06468,Machine Learning Engineer,179636,USD,179636,SE,FL,United States,L,United States,0,"Mathematics, Linux, Hadoop, Deep Learning",Master,8,Consulting,2024-12-16,2025-01-29,2432,6.7,Predictive Systems +AI06469,Robotics Engineer,30950,USD,30950,MI,PT,India,L,France,50,"R, SQL, Statistics",PhD,3,Consulting,2024-02-08,2024-03-15,1262,9.1,AI Innovations +AI06470,Principal Data Scientist,148429,USD,148429,SE,CT,Finland,L,South Africa,100,"PyTorch, Computer Vision, TensorFlow, SQL, Java",Associate,5,Manufacturing,2024-08-16,2024-09-13,717,8.9,TechCorp Inc +AI06471,AI Specialist,49035,EUR,41680,EN,FL,Austria,S,Netherlands,100,"Azure, Linux, MLOps",Master,1,Government,2024-11-20,2024-12-28,1457,8.6,Machine Intelligence Group +AI06472,AI Specialist,75189,SGD,97746,EN,CT,Singapore,M,Norway,0,"Mathematics, Azure, TensorFlow, Computer Vision, Hadoop",Master,0,Transportation,2024-12-02,2025-01-04,598,5.7,DeepTech Ventures +AI06473,Robotics Engineer,71967,GBP,53975,EN,PT,United Kingdom,L,United Kingdom,0,"Scala, Tableau, Hadoop, MLOps, NLP",Associate,0,Gaming,2024-05-18,2024-07-10,1985,8.9,Advanced Robotics +AI06474,NLP Engineer,190712,CAD,238390,EX,CT,Canada,S,Canada,50,"PyTorch, R, Kubernetes, Azure",Master,12,Media,2024-12-21,2025-01-10,1967,9.3,DataVision Ltd +AI06475,NLP Engineer,297771,GBP,223328,EX,FL,United Kingdom,L,United Kingdom,50,"AWS, Linux, PyTorch, Azure",PhD,14,Gaming,2025-02-24,2025-03-21,1502,5.7,Future Systems +AI06476,AI Specialist,156829,USD,156829,EX,FT,South Korea,S,South Korea,0,"SQL, Scala, Deep Learning, GCP",Associate,13,Consulting,2025-04-19,2025-05-17,762,7.6,AI Innovations +AI06477,ML Ops Engineer,143894,EUR,122310,EX,CT,France,M,Indonesia,0,"Python, TensorFlow, Computer Vision, Spark",PhD,18,Automotive,2025-04-21,2025-05-12,1614,7.7,Predictive Systems +AI06478,AI Software Engineer,150682,CHF,135614,MI,CT,Switzerland,M,Switzerland,100,"Java, PyTorch, Azure",Master,3,Education,2024-01-15,2024-02-13,1957,6.2,Algorithmic Solutions +AI06479,AI Product Manager,72926,USD,72926,EN,CT,United States,M,United States,0,"Python, Kubernetes, TensorFlow, Mathematics, Docker",PhD,1,Consulting,2024-08-26,2024-09-23,2383,9.7,Future Systems +AI06480,AI Specialist,50034,USD,50034,MI,FL,China,M,China,50,"Computer Vision, Azure, Kubernetes, Scala, MLOps",Associate,3,Healthcare,2025-04-14,2025-05-24,1718,9.8,DataVision Ltd +AI06481,Machine Learning Engineer,227301,USD,227301,EX,FL,Sweden,M,Sweden,0,"Linux, Tableau, R, Docker, Statistics",Bachelor,12,Manufacturing,2024-03-16,2024-05-07,1933,9.2,Future Systems +AI06482,Data Engineer,177520,GBP,133140,SE,FL,United Kingdom,L,Portugal,0,"Scala, Mathematics, Spark, Kubernetes",Associate,7,Retail,2024-12-03,2025-01-10,1975,8.3,Machine Intelligence Group +AI06483,AI Product Manager,290219,CHF,261197,EX,FT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Linux, TensorFlow",Associate,19,Finance,2024-07-22,2024-09-22,513,5.8,DataVision Ltd +AI06484,AI Research Scientist,178653,EUR,151855,EX,CT,Austria,L,Germany,0,"GCP, Kubernetes, Python",Master,18,Healthcare,2025-01-20,2025-02-14,1825,7.3,Autonomous Tech +AI06485,AI Product Manager,122006,EUR,103705,SE,CT,Germany,M,Germany,0,"Git, NLP, Linux, Scala, Data Visualization",Associate,8,Finance,2025-02-07,2025-04-09,1514,9.6,Neural Networks Co +AI06486,Robotics Engineer,168307,GBP,126230,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, SQL",Master,12,Finance,2024-12-01,2024-12-30,1505,9.9,DeepTech Ventures +AI06487,Principal Data Scientist,124629,USD,124629,EX,FT,South Korea,M,South Korea,50,"Git, Python, Azure",PhD,19,Real Estate,2024-12-02,2025-02-12,1102,8.1,Algorithmic Solutions +AI06488,Data Engineer,137796,EUR,117127,EX,CT,Austria,S,Austria,0,"Statistics, TensorFlow, Kubernetes, Linux",PhD,13,Government,2024-08-04,2024-08-28,1582,6.4,DeepTech Ventures +AI06489,AI Specialist,81533,EUR,69303,EN,CT,France,L,France,0,"Data Visualization, Docker, Tableau",Bachelor,1,Telecommunications,2025-04-08,2025-05-21,1781,5.6,Future Systems +AI06490,Principal Data Scientist,86860,USD,86860,EX,CT,China,S,Estonia,50,"SQL, Git, Kubernetes, Deep Learning",Master,18,Consulting,2024-09-02,2024-10-17,1805,7.6,AI Innovations +AI06491,Data Engineer,81781,EUR,69514,EN,FL,Netherlands,L,Netherlands,100,"PyTorch, Computer Vision, Deep Learning, TensorFlow, Azure",PhD,1,Telecommunications,2025-01-15,2025-03-04,2388,5.5,Predictive Systems +AI06492,AI Product Manager,140704,USD,140704,SE,FL,Finland,M,Finland,0,"PyTorch, SQL, Deep Learning, Tableau, NLP",Bachelor,8,Retail,2024-02-05,2024-03-24,1057,5.1,Cognitive Computing +AI06493,AI Specialist,61576,EUR,52340,EN,FL,Germany,S,Germany,50,"Spark, Linux, Git, R, Deep Learning",PhD,0,Consulting,2024-04-02,2024-04-25,698,9.1,Cloud AI Solutions +AI06494,AI Research Scientist,29955,USD,29955,EN,CT,China,M,Netherlands,50,"Hadoop, SQL, Azure, Kubernetes, Tableau",Associate,0,Transportation,2025-02-28,2025-03-26,1800,8.1,DataVision Ltd +AI06495,Computer Vision Engineer,107488,EUR,91365,SE,PT,Netherlands,S,Turkey,0,"Mathematics, Docker, Kubernetes, SQL, TensorFlow",Associate,6,Transportation,2024-03-27,2024-04-20,503,9.8,Autonomous Tech +AI06496,AI Specialist,18247,USD,18247,EN,PT,India,S,India,0,"Scala, Python, Computer Vision, Deep Learning, TensorFlow",Master,1,Gaming,2024-10-09,2024-10-30,1178,7.9,Algorithmic Solutions +AI06497,Machine Learning Engineer,141464,USD,141464,MI,FT,Norway,M,Norway,100,"Git, Java, AWS",PhD,2,Real Estate,2024-02-03,2024-03-11,1296,6.7,AI Innovations +AI06498,AI Product Manager,41759,USD,41759,SE,FL,India,S,India,100,"Mathematics, Scala, MLOps, Statistics, Linux",Master,6,Gaming,2024-01-26,2024-03-05,1858,7.6,Cloud AI Solutions +AI06499,Data Analyst,55004,JPY,6050440,EN,PT,Japan,M,Japan,100,"Git, Kubernetes, NLP",Associate,1,Gaming,2024-02-14,2024-03-20,2454,7,DeepTech Ventures +AI06500,AI Consultant,43128,USD,43128,MI,CT,China,M,China,100,"TensorFlow, Java, Azure, Mathematics, AWS",PhD,4,Transportation,2024-01-22,2024-02-20,871,7.8,Machine Intelligence Group +AI06501,AI Consultant,82614,EUR,70222,EN,CT,Germany,L,Vietnam,100,"Azure, Kubernetes, SQL",Bachelor,1,Real Estate,2024-03-17,2024-05-26,2454,7.5,Smart Analytics +AI06502,AI Research Scientist,306002,EUR,260102,EX,PT,Netherlands,L,Netherlands,100,"Linux, Hadoop, Azure, Deep Learning",Associate,17,Automotive,2024-12-17,2025-02-08,1412,9.2,Cloud AI Solutions +AI06503,Deep Learning Engineer,129451,USD,129451,SE,PT,Ireland,S,Austria,50,"Python, Linux, Deep Learning, Git, Computer Vision",Bachelor,8,Automotive,2024-10-15,2024-11-05,1411,10,Cognitive Computing +AI06504,AI Architect,192815,CHF,173534,EX,FL,Switzerland,M,Switzerland,50,"Git, SQL, TensorFlow",Master,11,Retail,2024-01-02,2024-01-29,2257,8.8,Autonomous Tech +AI06505,Research Scientist,133972,USD,133972,EX,FT,Israel,M,Singapore,0,"AWS, Kubernetes, Mathematics",Bachelor,12,Healthcare,2024-05-14,2024-06-12,1654,6.5,Digital Transformation LLC +AI06506,Data Scientist,77616,USD,77616,MI,FL,South Korea,S,South Korea,50,"AWS, TensorFlow, Scala, Tableau, Deep Learning",Master,4,Technology,2025-04-07,2025-06-12,665,5.5,Machine Intelligence Group +AI06507,Principal Data Scientist,47133,USD,47133,EN,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Spark, NLP, Java",Associate,1,Energy,2025-03-14,2025-04-03,533,5.1,Cognitive Computing +AI06508,Research Scientist,70801,USD,70801,MI,CT,South Korea,S,South Korea,100,"Tableau, Python, Java",Associate,3,Retail,2024-07-18,2024-08-10,1335,6.1,DeepTech Ventures +AI06509,AI Specialist,120997,USD,120997,SE,FL,Finland,M,Finland,50,"AWS, Deep Learning, SQL, Scala",Associate,9,Automotive,2024-05-03,2024-07-06,2203,6.7,Digital Transformation LLC +AI06510,AI Product Manager,263003,EUR,223553,EX,FL,Austria,L,Austria,100,"Scala, R, Hadoop, Deep Learning",Bachelor,15,Real Estate,2024-02-01,2024-03-18,851,6.6,Neural Networks Co +AI06511,AI Consultant,48759,GBP,36569,EN,PT,United Kingdom,S,Australia,50,"Azure, Java, Linux",PhD,0,Transportation,2024-08-30,2024-10-04,1794,7.8,Cognitive Computing +AI06512,Machine Learning Engineer,195629,GBP,146722,EX,CT,United Kingdom,S,United Kingdom,100,"R, GCP, Git",Associate,17,Energy,2024-12-30,2025-02-21,1765,8,Algorithmic Solutions +AI06513,AI Research Scientist,161173,USD,161173,SE,PT,Norway,L,Norway,0,"Computer Vision, AWS, Linux, Spark",Bachelor,9,Gaming,2024-10-01,2024-11-09,968,9.3,Digital Transformation LLC +AI06514,AI Consultant,94896,USD,94896,SE,CT,South Korea,S,South Korea,100,"Python, MLOps, Azure, Tableau",Associate,7,Finance,2024-02-05,2024-03-06,1668,5.9,Cognitive Computing +AI06515,AI Architect,47417,USD,47417,EN,FL,Israel,S,Israel,0,"Spark, Docker, Computer Vision",Bachelor,1,Retail,2025-02-14,2025-03-27,1934,6.2,AI Innovations +AI06516,Deep Learning Engineer,90359,AUD,121985,MI,FL,Australia,S,Australia,50,"Kubernetes, MLOps, Hadoop",Master,3,Government,2024-12-24,2025-02-05,1562,8.3,Advanced Robotics +AI06517,AI Research Scientist,123662,GBP,92747,MI,FL,United Kingdom,L,China,50,"Linux, Data Visualization, Hadoop",Master,2,Energy,2024-07-02,2024-07-21,2185,9,Predictive Systems +AI06518,Machine Learning Researcher,146667,AUD,198000,SE,PT,Australia,M,Australia,50,"R, PyTorch, Linux, Mathematics",Bachelor,5,Retail,2024-03-28,2024-04-18,2204,6.1,Digital Transformation LLC +AI06519,Data Scientist,66452,EUR,56484,EN,FT,Germany,S,Germany,50,"Java, Kubernetes, Tableau, NLP",Associate,0,Government,2024-12-04,2025-01-09,1711,8,Algorithmic Solutions +AI06520,Principal Data Scientist,50813,GBP,38110,EN,CT,United Kingdom,S,United Kingdom,0,"Python, Mathematics, Data Visualization, Spark, TensorFlow",Associate,1,Healthcare,2024-12-11,2025-01-30,880,6.1,DeepTech Ventures +AI06521,AI Research Scientist,226711,USD,226711,EX,PT,Sweden,L,Sweden,50,"SQL, Tableau, Python",Master,17,Consulting,2025-03-27,2025-04-14,1098,6.8,DeepTech Ventures +AI06522,AI Specialist,145967,EUR,124072,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Python, Hadoop, Docker",PhD,15,Education,2025-02-04,2025-02-24,913,5.1,Predictive Systems +AI06523,Machine Learning Engineer,214976,USD,214976,EX,CT,Sweden,S,Sweden,0,"Python, Kubernetes, PyTorch",Master,11,Manufacturing,2024-04-16,2024-06-01,2129,7,Cognitive Computing +AI06524,AI Specialist,60294,USD,60294,MI,CT,South Korea,S,South Korea,100,"R, SQL, Tableau",Associate,4,Transportation,2024-03-26,2024-05-28,1820,7.8,Algorithmic Solutions +AI06525,NLP Engineer,100722,USD,100722,MI,CT,Norway,S,Thailand,100,"Python, Azure, Computer Vision, Docker",Master,3,Real Estate,2024-08-20,2024-10-17,1877,6.2,Digital Transformation LLC +AI06526,Machine Learning Engineer,100577,EUR,85490,MI,FL,Netherlands,S,Netherlands,50,"SQL, Scala, Computer Vision, Data Visualization, PyTorch",Bachelor,3,Automotive,2024-04-12,2024-06-05,717,7.7,Future Systems +AI06527,Autonomous Systems Engineer,117696,USD,117696,MI,FL,United States,M,United States,0,"Linux, MLOps, Java, SQL, PyTorch",Associate,3,Energy,2024-12-30,2025-02-11,1640,5.8,Machine Intelligence Group +AI06528,Head of AI,184939,USD,184939,EX,PT,Finland,L,Finland,50,"R, SQL, PyTorch, TensorFlow, Tableau",Master,19,Gaming,2024-03-07,2024-04-18,1259,7.7,Autonomous Tech +AI06529,AI Software Engineer,279576,USD,279576,EX,PT,Norway,S,Netherlands,50,"SQL, PyTorch, Java, Data Visualization, AWS",Bachelor,13,Automotive,2024-03-12,2024-05-03,2005,6,Smart Analytics +AI06530,Data Analyst,223224,USD,223224,SE,PT,Norway,L,Norway,0,"Spark, Mathematics, R, TensorFlow, GCP",Bachelor,6,Government,2024-07-04,2024-09-09,2433,8.4,Cloud AI Solutions +AI06531,Robotics Engineer,154533,USD,154533,EX,FL,South Korea,M,South Korea,100,"Hadoop, AWS, Computer Vision, Azure",Bachelor,18,Gaming,2024-11-26,2025-01-27,2073,5,AI Innovations +AI06532,AI Architect,175373,SGD,227985,EX,FL,Singapore,M,Singapore,0,"SQL, Deep Learning, Kubernetes",Master,11,Healthcare,2024-11-29,2024-12-17,1476,7,Quantum Computing Inc +AI06533,Data Analyst,71134,USD,71134,SE,CT,China,M,China,0,"Linux, Deep Learning, Data Visualization",Bachelor,7,Real Estate,2024-06-29,2024-08-17,727,7.5,Predictive Systems +AI06534,AI Product Manager,61514,EUR,52287,EN,FL,Netherlands,S,Netherlands,100,"TensorFlow, Kubernetes, Data Visualization, Spark, SQL",PhD,0,Telecommunications,2024-10-15,2024-11-22,1193,7.5,Predictive Systems +AI06535,AI Architect,95381,USD,95381,MI,PT,Sweden,S,Sweden,50,"SQL, Scala, Data Visualization",Associate,4,Finance,2025-02-24,2025-03-14,1983,9,Neural Networks Co +AI06536,Machine Learning Researcher,190339,USD,190339,EX,PT,Norway,S,Norway,50,"Tableau, R, AWS",Bachelor,15,Transportation,2024-05-24,2024-07-12,2438,9,Smart Analytics +AI06537,AI Research Scientist,228266,GBP,171200,EX,FL,United Kingdom,M,Austria,0,"Tableau, Scala, Java, Azure",Master,15,Education,2024-04-01,2024-05-03,2081,7.6,Smart Analytics +AI06538,AI Specialist,201526,USD,201526,SE,PT,United States,L,Thailand,50,"Kubernetes, Spark, SQL, Statistics, Mathematics",Associate,5,Healthcare,2024-10-19,2024-11-21,2490,7.2,AI Innovations +AI06539,Data Engineer,165854,USD,165854,EX,FL,Denmark,S,Denmark,0,"Linux, Azure, Mathematics",PhD,18,Real Estate,2024-10-13,2024-11-22,2073,8,Advanced Robotics +AI06540,Head of AI,50399,USD,50399,MI,FT,China,M,Chile,50,"Linux, GCP, Data Visualization",Master,4,Energy,2024-03-30,2024-05-21,2432,7.6,TechCorp Inc +AI06541,Research Scientist,146895,USD,146895,SE,FL,Ireland,M,Ireland,0,"Git, PyTorch, SQL, AWS, Mathematics",PhD,5,Transportation,2024-03-03,2024-04-25,1660,6.8,Cognitive Computing +AI06542,Machine Learning Engineer,141242,USD,141242,EX,FL,Ireland,M,Ireland,0,"Hadoop, Java, PyTorch, TensorFlow",Associate,19,Finance,2025-03-30,2025-04-17,1744,7.6,Smart Analytics +AI06543,AI Research Scientist,227276,GBP,170457,EX,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, Computer Vision, Statistics, Python, R",Master,19,Media,2025-01-02,2025-01-30,640,8.4,Algorithmic Solutions +AI06544,AI Software Engineer,91381,EUR,77674,MI,PT,Netherlands,S,Netherlands,50,"SQL, Computer Vision, Java, R",Master,3,Gaming,2025-03-31,2025-06-04,1247,7.4,AI Innovations +AI06545,Data Analyst,127378,USD,127378,SE,PT,Israel,M,Israel,100,"Statistics, Kubernetes, Data Visualization, Git, PyTorch",Associate,6,Retail,2024-09-28,2024-10-24,2487,8.6,Machine Intelligence Group +AI06546,Principal Data Scientist,67976,USD,67976,EN,FL,Israel,S,Hungary,0,"Python, TensorFlow, Kubernetes",PhD,1,Automotive,2024-07-09,2024-08-06,1680,6.5,Future Systems +AI06547,AI Specialist,213311,CHF,191980,SE,FT,Switzerland,M,Switzerland,100,"Linux, Azure, Kubernetes",Associate,9,Manufacturing,2025-04-15,2025-05-12,2384,8.4,DeepTech Ventures +AI06548,Machine Learning Engineer,68136,EUR,57916,EN,CT,France,S,Nigeria,100,"Kubernetes, Git, Azure, NLP, Deep Learning",Master,0,Gaming,2024-04-01,2024-06-08,976,6.7,Autonomous Tech +AI06549,Robotics Engineer,137648,USD,137648,MI,CT,Norway,L,Norway,100,"SQL, Python, GCP, NLP, Mathematics",Master,2,Finance,2025-03-22,2025-05-07,1030,6.4,Neural Networks Co +AI06550,AI Software Engineer,176624,USD,176624,EX,FT,Sweden,S,Sweden,0,"SQL, Azure, Tableau",Master,18,Transportation,2024-02-02,2024-03-19,1038,7.1,TechCorp Inc +AI06551,Robotics Engineer,117861,USD,117861,EX,FL,Finland,S,Finland,0,"Python, Scala, Java",Bachelor,19,Energy,2024-12-17,2025-01-21,823,7.2,DeepTech Ventures +AI06552,Computer Vision Engineer,95983,USD,95983,MI,FL,Israel,L,Israel,100,"PyTorch, Docker, Tableau, MLOps, Linux",Associate,3,Media,2025-04-07,2025-04-27,678,5.9,Neural Networks Co +AI06553,Head of AI,127320,EUR,108222,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Deep Learning, Computer Vision, Python, R",PhD,8,Healthcare,2024-06-22,2024-08-24,980,6.6,Neural Networks Co +AI06554,Data Analyst,156695,EUR,133191,EX,FT,Austria,M,Japan,100,"Azure, Python, Scala",Associate,17,Telecommunications,2024-09-05,2024-10-05,1229,6.2,DeepTech Ventures +AI06555,ML Ops Engineer,70934,USD,70934,EN,PT,United States,S,United States,50,"AWS, Git, TensorFlow, SQL, Mathematics",Bachelor,0,Media,2024-09-14,2024-10-07,2413,8.2,Future Systems +AI06556,Research Scientist,160766,USD,160766,EX,FL,Israel,L,Israel,50,"Python, TensorFlow, Spark, Linux",PhD,19,Transportation,2024-08-07,2024-09-27,2169,9.9,AI Innovations +AI06557,Autonomous Systems Engineer,112463,USD,112463,SE,PT,Finland,M,Finland,0,"GCP, PyTorch, MLOps",Bachelor,8,Finance,2024-03-30,2024-05-13,1069,7.4,Predictive Systems +AI06558,NLP Engineer,143144,USD,143144,SE,PT,Sweden,M,Sweden,100,"Spark, Git, Tableau",Master,6,Finance,2025-01-13,2025-02-18,892,9.5,DataVision Ltd +AI06559,Principal Data Scientist,38842,USD,38842,MI,FL,China,M,China,50,"MLOps, Python, TensorFlow, PyTorch",Associate,3,Technology,2024-07-21,2024-08-21,2083,9,Algorithmic Solutions +AI06560,Machine Learning Engineer,64116,GBP,48087,EN,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Computer Vision, Kubernetes, Docker",Master,0,Media,2024-07-09,2024-08-12,2386,5.8,Cognitive Computing +AI06561,AI Software Engineer,88010,USD,88010,MI,CT,South Korea,L,South Korea,0,"Python, TensorFlow, Hadoop",Associate,2,Consulting,2024-07-12,2024-07-27,2443,7,Smart Analytics +AI06562,Head of AI,95648,USD,95648,MI,FT,Norway,S,Norway,0,"Scala, Hadoop, Docker, Computer Vision, GCP",Master,4,Healthcare,2024-11-04,2025-01-14,2231,5.3,AI Innovations +AI06563,Deep Learning Engineer,97522,SGD,126779,EN,FT,Singapore,L,Singapore,50,"Git, Python, Statistics, TensorFlow, Mathematics",Master,1,Media,2024-10-06,2024-10-31,1772,6.6,DeepTech Ventures +AI06564,Data Analyst,31058,USD,31058,EN,CT,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-06-07,2024-07-18,605,9.6,Advanced Robotics +AI06565,Research Scientist,278889,CHF,251000,EX,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, Kubernetes, Statistics, Docker",Associate,10,Transportation,2025-01-28,2025-03-16,724,5.2,DeepTech Ventures +AI06566,Data Scientist,83674,SGD,108776,EN,CT,Singapore,L,Singapore,100,"Kubernetes, Scala, Data Visualization, MLOps, GCP",Bachelor,0,Government,2024-11-02,2024-11-20,1581,6.9,Cloud AI Solutions +AI06567,AI Specialist,59348,JPY,6528280,EN,CT,Japan,M,Japan,0,"Hadoop, Java, Linux",Bachelor,0,Telecommunications,2024-12-27,2025-02-05,2315,7.8,Digital Transformation LLC +AI06568,Robotics Engineer,178661,CHF,160795,EX,FL,Switzerland,S,Netherlands,100,"AWS, Linux, NLP",Associate,18,Telecommunications,2024-07-11,2024-09-19,1704,7.8,Predictive Systems +AI06569,AI Specialist,150401,AUD,203041,EX,PT,Australia,M,Italy,0,"Mathematics, PyTorch, MLOps, AWS, TensorFlow",Master,13,Transportation,2024-05-10,2024-07-11,1135,6.6,Advanced Robotics +AI06570,AI Research Scientist,62718,EUR,53310,EN,FL,Austria,L,Austria,50,"MLOps, Scala, TensorFlow, SQL",Associate,1,Consulting,2025-04-12,2025-06-10,896,7,Cognitive Computing +AI06571,Deep Learning Engineer,68205,EUR,57974,EN,PT,Austria,L,Singapore,0,"Docker, GCP, SQL, Git, Statistics",Master,1,Telecommunications,2024-05-26,2024-08-01,2360,7.1,DeepTech Ventures +AI06572,Data Analyst,58067,USD,58067,EN,CT,Israel,L,Israel,50,"MLOps, R, Docker, Python, AWS",PhD,1,Retail,2024-03-26,2024-04-28,833,5.3,Cloud AI Solutions +AI06573,AI Product Manager,94059,SGD,122277,MI,CT,Singapore,S,Singapore,50,"Python, GCP, Statistics, Computer Vision, Kubernetes",Associate,4,Telecommunications,2024-06-27,2024-08-25,1033,9.2,AI Innovations +AI06574,Machine Learning Researcher,124056,USD,124056,SE,FL,Denmark,S,Denmark,100,"Python, Kubernetes, TensorFlow, Scala, Git",Master,5,Technology,2024-09-22,2024-10-06,1381,9.8,Cognitive Computing +AI06575,Principal Data Scientist,103972,USD,103972,EN,FT,Denmark,L,Denmark,100,"Kubernetes, Data Visualization, Hadoop",Associate,1,Healthcare,2024-01-03,2024-03-01,2122,8.4,Predictive Systems +AI06576,AI Research Scientist,120733,SGD,156953,SE,FL,Singapore,M,Singapore,50,"Hadoop, Git, Statistics",Bachelor,8,Automotive,2025-04-20,2025-05-10,2362,6,Advanced Robotics +AI06577,Autonomous Systems Engineer,49939,JPY,5493290,EN,PT,Japan,S,Poland,50,"Java, SQL, Tableau",Master,0,Gaming,2024-08-13,2024-10-22,1862,6.5,Predictive Systems +AI06578,Machine Learning Engineer,131946,USD,131946,EX,PT,Finland,M,Nigeria,0,"AWS, Python, GCP, Scala, Computer Vision",Master,17,Technology,2024-01-30,2024-03-10,1122,8.4,Cloud AI Solutions +AI06579,Principal Data Scientist,74473,CHF,67026,EN,CT,Switzerland,S,Russia,0,"GCP, Computer Vision, SQL, Deep Learning",PhD,1,Gaming,2024-06-19,2024-08-18,1120,6,Digital Transformation LLC +AI06580,ML Ops Engineer,42235,USD,42235,EN,FT,South Korea,M,South Korea,0,"TensorFlow, Tableau, SQL, NLP",Associate,0,Government,2024-02-10,2024-02-29,623,7.1,DeepTech Ventures +AI06581,AI Software Engineer,100391,USD,100391,EX,PT,China,S,China,100,"Python, R, Data Visualization",Master,16,Retail,2024-12-02,2025-02-05,2094,5.7,Autonomous Tech +AI06582,Data Analyst,224884,USD,224884,EX,CT,Ireland,L,Chile,50,"Linux, Python, TensorFlow",Master,17,Manufacturing,2025-03-29,2025-04-12,2203,7.8,Advanced Robotics +AI06583,AI Specialist,138421,USD,138421,SE,PT,Finland,L,Switzerland,0,"Deep Learning, Hadoop, PyTorch",Bachelor,8,Manufacturing,2024-05-10,2024-05-29,1120,8.3,Future Systems +AI06584,Data Analyst,73596,EUR,62557,MI,PT,Germany,S,Germany,50,"Scala, Kubernetes, Tableau, MLOps, GCP",Bachelor,3,Energy,2024-02-07,2024-03-02,783,6.4,Autonomous Tech +AI06585,AI Product Manager,118358,USD,118358,MI,CT,Ireland,L,Ireland,50,"Scala, Python, TensorFlow, AWS",Associate,4,Finance,2025-04-27,2025-06-29,1805,9.6,Autonomous Tech +AI06586,Autonomous Systems Engineer,60553,USD,60553,SE,CT,China,L,France,50,"Python, Data Visualization, Scala",PhD,5,Energy,2024-10-05,2024-12-01,688,6.9,Predictive Systems +AI06587,Principal Data Scientist,151705,EUR,128949,SE,FL,Netherlands,L,Kenya,0,"Deep Learning, Tableau, MLOps",Bachelor,9,Telecommunications,2024-06-10,2024-08-21,1911,9.3,Digital Transformation LLC +AI06588,AI Specialist,119879,EUR,101897,MI,FT,Germany,L,Germany,50,"Python, Java, Azure, Scala, R",Master,4,Manufacturing,2024-06-15,2024-07-29,1659,7.1,Autonomous Tech +AI06589,Head of AI,79545,EUR,67613,MI,FL,France,L,France,100,"Spark, Python, Computer Vision, Data Visualization, Docker",PhD,3,Consulting,2025-03-25,2025-05-06,2147,9.2,Quantum Computing Inc +AI06590,Data Analyst,59043,USD,59043,EN,FT,Finland,L,Ukraine,50,"Scala, Kubernetes, SQL, Linux",PhD,1,Real Estate,2024-06-01,2024-06-24,2127,7,AI Innovations +AI06591,ML Ops Engineer,103365,GBP,77524,MI,PT,United Kingdom,M,United Kingdom,50,"MLOps, Hadoop, Statistics",Master,3,Manufacturing,2024-05-12,2024-07-12,2256,9,Smart Analytics +AI06592,AI Software Engineer,94572,EUR,80386,MI,CT,Netherlands,M,Netherlands,0,"Java, SQL, Git, Hadoop",Master,3,Telecommunications,2025-03-24,2025-04-07,2391,6.5,DataVision Ltd +AI06593,AI Software Engineer,95620,CHF,86058,MI,CT,Switzerland,S,South Africa,100,"R, Tableau, Python, TensorFlow",Master,3,Energy,2024-09-08,2024-10-11,814,6.6,Quantum Computing Inc +AI06594,AI Consultant,333608,USD,333608,EX,FL,United States,L,United States,50,"Kubernetes, Java, NLP, R",Associate,13,Retail,2024-02-23,2024-03-17,677,6.6,Predictive Systems +AI06595,Data Analyst,125818,USD,125818,SE,FT,Norway,S,Norway,50,"SQL, TensorFlow, AWS, Python, Linux",Master,6,Telecommunications,2025-04-04,2025-05-14,2303,7.8,Quantum Computing Inc +AI06596,Robotics Engineer,79536,USD,79536,MI,CT,United States,S,United States,50,"Scala, Kubernetes, Deep Learning, Mathematics, Data Visualization",PhD,4,Telecommunications,2025-03-14,2025-05-18,2441,7.3,Predictive Systems +AI06597,Machine Learning Researcher,112134,USD,112134,MI,CT,Denmark,M,Denmark,0,"Scala, SQL, Mathematics, Java, Python",Associate,3,Consulting,2024-12-30,2025-02-18,1804,7.7,Cloud AI Solutions +AI06598,Robotics Engineer,286727,USD,286727,EX,FL,Ireland,L,Ireland,100,"Java, NLP, Data Visualization",PhD,11,Technology,2024-12-01,2025-01-07,2222,5.2,TechCorp Inc +AI06599,AI Product Manager,86549,EUR,73567,EN,PT,Netherlands,L,Netherlands,100,"Linux, Git, Data Visualization, Python, Computer Vision",PhD,0,Retail,2024-03-27,2024-05-18,1317,8.5,Neural Networks Co +AI06600,Computer Vision Engineer,137974,USD,137974,MI,PT,Norway,M,Norway,0,"Python, R, GCP, AWS, Kubernetes",PhD,2,Manufacturing,2024-10-15,2024-10-29,1016,5.2,Digital Transformation LLC +AI06601,Principal Data Scientist,48191,USD,48191,EN,FT,Israel,S,Israel,50,"R, Scala, TensorFlow, Git",Bachelor,0,Government,2024-03-19,2024-05-06,1811,6.9,DeepTech Ventures +AI06602,Robotics Engineer,137089,EUR,116526,EX,CT,Germany,S,Germany,50,"Java, PyTorch, Hadoop",Master,10,Manufacturing,2025-02-05,2025-04-07,523,9.5,Predictive Systems +AI06603,ML Ops Engineer,146050,JPY,16065500,EX,CT,Japan,S,Japan,50,"SQL, Hadoop, Statistics, PyTorch",Master,16,Gaming,2025-02-10,2025-04-20,1060,8.9,Future Systems +AI06604,Machine Learning Researcher,83076,EUR,70615,EN,CT,Austria,L,Ukraine,0,"Hadoop, Python, GCP",Associate,0,Government,2024-05-17,2024-06-23,1739,9.8,Neural Networks Co +AI06605,Data Scientist,184817,SGD,240262,EX,CT,Singapore,S,Singapore,0,"Python, Scala, Hadoop",Associate,11,Energy,2024-08-24,2024-10-13,1726,7.4,DataVision Ltd +AI06606,Head of AI,76584,EUR,65096,MI,CT,Austria,M,Poland,50,"Kubernetes, Statistics, AWS",Associate,4,Manufacturing,2025-02-04,2025-04-02,1410,5.8,Autonomous Tech +AI06607,NLP Engineer,79065,USD,79065,EN,PT,Sweden,L,Sweden,100,"Python, Scala, Linux",Associate,0,Finance,2024-07-23,2024-09-30,2099,9.3,Future Systems +AI06608,Data Scientist,118313,EUR,100566,MI,PT,France,L,France,100,"Mathematics, SQL, Python",Bachelor,3,Healthcare,2024-11-06,2024-12-21,554,5,DataVision Ltd +AI06609,Data Scientist,177046,USD,177046,EX,FT,Israel,M,Israel,100,"Git, Tableau, Linux, Python",Bachelor,17,Energy,2024-10-10,2024-11-12,2366,5.8,Future Systems +AI06610,Machine Learning Researcher,38680,USD,38680,MI,FL,China,S,China,100,"MLOps, PyTorch, GCP",Associate,2,Real Estate,2024-10-12,2024-12-05,2445,5.7,Machine Intelligence Group +AI06611,AI Architect,161186,EUR,137008,SE,FL,Netherlands,M,Sweden,100,"Python, TensorFlow, NLP, Deep Learning, Statistics",Associate,7,Healthcare,2024-09-22,2024-11-01,1454,8.9,Predictive Systems +AI06612,Data Scientist,121651,EUR,103403,SE,FL,Netherlands,M,Netherlands,100,"Hadoop, GCP, Tableau, Docker, PyTorch",Bachelor,9,Transportation,2024-07-09,2024-07-29,1405,6.6,Autonomous Tech +AI06613,Autonomous Systems Engineer,134960,JPY,14845600,SE,PT,Japan,S,Japan,50,"Java, Tableau, Azure",PhD,6,Energy,2024-06-22,2024-07-27,657,6.7,Advanced Robotics +AI06614,AI Research Scientist,52748,USD,52748,EN,CT,Israel,M,Israel,0,"SQL, Kubernetes, Python, AWS",Master,1,Manufacturing,2025-03-02,2025-05-08,1280,9.5,Cognitive Computing +AI06615,AI Software Engineer,77009,CAD,96261,MI,PT,Canada,M,Canada,100,"Deep Learning, Kubernetes, Mathematics",Bachelor,2,Media,2024-03-01,2024-04-06,2072,9,Smart Analytics +AI06616,Data Analyst,101929,SGD,132508,SE,FT,Singapore,S,Luxembourg,50,"MLOps, Java, Data Visualization",Master,5,Manufacturing,2024-02-22,2024-03-22,1996,9.2,Smart Analytics +AI06617,AI Software Engineer,118002,EUR,100302,SE,PT,France,L,Czech Republic,0,"Kubernetes, GCP, Azure, Java, R",Master,6,Real Estate,2024-09-19,2024-11-13,1549,9.7,Advanced Robotics +AI06618,Machine Learning Engineer,138903,SGD,180574,EX,PT,Singapore,S,Singapore,100,"Tableau, Java, Deep Learning",Associate,11,Energy,2024-03-13,2024-04-22,2245,9.3,DataVision Ltd +AI06619,AI Architect,279851,JPY,30783610,EX,PT,Japan,L,Japan,50,"Spark, SQL, Linux",Associate,10,Automotive,2024-02-01,2024-03-05,2260,8.4,AI Innovations +AI06620,Principal Data Scientist,168724,EUR,143415,EX,PT,Austria,L,Austria,0,"TensorFlow, Tableau, R, Java, Linux",PhD,18,Real Estate,2024-09-15,2024-11-07,942,7,DeepTech Ventures +AI06621,AI Software Engineer,305904,SGD,397675,EX,PT,Singapore,L,Australia,100,"Scala, Data Visualization, R",Master,10,Gaming,2024-01-15,2024-03-27,1819,8.8,Neural Networks Co +AI06622,Robotics Engineer,27196,USD,27196,EN,FT,China,M,China,100,"Linux, NLP, Tableau, Spark",Associate,1,Telecommunications,2025-04-22,2025-05-08,503,8.7,AI Innovations +AI06623,Machine Learning Engineer,108913,USD,108913,SE,CT,South Korea,M,Portugal,100,"GCP, Scala, Statistics, Python",Bachelor,5,Real Estate,2024-03-24,2024-04-24,1058,6.2,Autonomous Tech +AI06624,Computer Vision Engineer,133154,CAD,166443,EX,PT,Canada,M,Estonia,50,"Hadoop, Scala, PyTorch",Associate,10,Media,2024-12-19,2025-01-20,968,5.7,Autonomous Tech +AI06625,AI Research Scientist,253346,SGD,329350,EX,PT,Singapore,L,Estonia,50,"Spark, PyTorch, Kubernetes, Hadoop",Master,17,Gaming,2025-02-10,2025-04-16,1851,10,Cognitive Computing +AI06626,Autonomous Systems Engineer,257998,JPY,28379780,EX,CT,Japan,M,Nigeria,100,"MLOps, Mathematics, AWS, NLP, Linux",PhD,18,Manufacturing,2024-12-22,2025-02-23,1851,6.8,Predictive Systems +AI06627,AI Research Scientist,118724,USD,118724,SE,FL,South Korea,M,South Korea,0,"Hadoop, Docker, Mathematics, Computer Vision, Scala",Bachelor,6,Finance,2025-03-10,2025-03-25,1941,8,Cognitive Computing +AI06628,Data Scientist,88590,GBP,66443,EN,PT,United Kingdom,L,United Kingdom,100,"Data Visualization, Docker, Linux",PhD,0,Transportation,2024-08-13,2024-10-16,881,8.5,AI Innovations +AI06629,Data Scientist,45950,EUR,39058,EN,FT,Germany,S,Germany,100,"Linux, Java, Python, TensorFlow",Master,0,Manufacturing,2024-08-28,2024-11-04,1012,9.8,Autonomous Tech +AI06630,AI Consultant,202145,SGD,262789,EX,CT,Singapore,M,Singapore,50,"Spark, Python, Tableau, Git, TensorFlow",Associate,18,Retail,2025-03-04,2025-04-04,1103,9.7,Machine Intelligence Group +AI06631,ML Ops Engineer,354485,CHF,319037,EX,FL,Switzerland,M,Finland,50,"MLOps, Docker, AWS, SQL",Associate,12,Finance,2024-04-11,2024-05-15,1424,5.4,Quantum Computing Inc +AI06632,AI Architect,145381,EUR,123574,SE,FT,Netherlands,M,Netherlands,100,"TensorFlow, Python, Computer Vision, PyTorch, Git",Bachelor,6,Technology,2024-07-30,2024-09-08,2076,6.1,DeepTech Ventures +AI06633,AI Research Scientist,80273,USD,80273,SE,CT,China,L,China,50,"Azure, NLP, Scala",Associate,7,Energy,2024-09-12,2024-10-21,1925,8.7,Algorithmic Solutions +AI06634,Computer Vision Engineer,93627,CAD,117034,MI,CT,Canada,L,Netherlands,50,"Linux, Docker, Data Visualization",PhD,2,Retail,2024-03-21,2024-05-31,2091,8.7,DeepTech Ventures +AI06635,Machine Learning Researcher,101958,EUR,86664,MI,PT,Germany,L,Germany,50,"SQL, Docker, Java, NLP",Associate,4,Real Estate,2024-02-22,2024-03-17,1416,7.1,Smart Analytics +AI06636,Machine Learning Engineer,310491,EUR,263917,EX,PT,Netherlands,L,Netherlands,50,"SQL, Hadoop, PyTorch",Associate,14,Education,2024-05-13,2024-06-25,2239,7.4,Cloud AI Solutions +AI06637,Machine Learning Researcher,92455,GBP,69341,EN,PT,United Kingdom,L,Colombia,50,"Scala, Linux, Statistics, Java, Docker",Associate,1,Manufacturing,2025-04-09,2025-04-26,1369,7.4,Future Systems +AI06638,Data Engineer,106939,USD,106939,EX,PT,China,M,China,50,"Hadoop, Computer Vision, PyTorch, Data Visualization, R",Master,11,Manufacturing,2024-09-14,2024-11-18,1333,9.9,Digital Transformation LLC +AI06639,AI Product Manager,194351,EUR,165198,EX,FT,Austria,M,Austria,100,"GCP, Azure, SQL, TensorFlow, Statistics",Bachelor,16,Automotive,2025-01-03,2025-03-07,1968,7.8,Future Systems +AI06640,Machine Learning Engineer,110209,USD,110209,EX,PT,China,L,China,100,"R, Scala, Python",Associate,15,Education,2025-03-25,2025-06-01,951,9.1,Future Systems +AI06641,Data Engineer,274986,USD,274986,EX,FT,Finland,L,Finland,50,"Scala, Deep Learning, MLOps",Associate,10,Media,2024-01-31,2024-02-23,1539,6.5,Digital Transformation LLC +AI06642,Deep Learning Engineer,292272,AUD,394567,EX,CT,Australia,L,Luxembourg,0,"Computer Vision, GCP, Azure",Associate,17,Technology,2025-02-23,2025-04-11,1628,7.1,Machine Intelligence Group +AI06643,AI Specialist,70159,USD,70159,EN,PT,Finland,M,Finland,0,"Kubernetes, Spark, Python",PhD,1,Education,2024-03-27,2024-05-05,1064,8.9,Advanced Robotics +AI06644,NLP Engineer,57113,USD,57113,EN,PT,Ireland,M,Hungary,0,"Java, Tableau, Scala",Associate,0,Finance,2024-12-15,2025-02-08,1510,8.6,Cognitive Computing +AI06645,Machine Learning Engineer,67207,USD,67207,EN,CT,Israel,L,Israel,0,"Azure, Data Visualization, Git, Java, R",Associate,1,Automotive,2024-03-02,2024-04-27,1753,5.3,Neural Networks Co +AI06646,AI Product Manager,62513,USD,62513,EN,FT,Israel,M,Israel,50,"Java, MLOps, Azure",PhD,0,Education,2025-04-28,2025-05-15,935,7.3,Predictive Systems +AI06647,AI Software Engineer,120652,USD,120652,MI,PT,Norway,L,Ireland,50,"Kubernetes, Azure, Deep Learning, PyTorch, R",Associate,3,Media,2024-09-07,2024-11-15,2101,8.4,Machine Intelligence Group +AI06648,AI Research Scientist,28595,USD,28595,EN,CT,India,L,India,50,"SQL, Data Visualization, Kubernetes, Spark",Master,1,Gaming,2024-02-20,2024-03-21,588,8.7,Algorithmic Solutions +AI06649,Autonomous Systems Engineer,32487,USD,32487,MI,FT,India,L,India,50,"Spark, Azure, Statistics, Docker",Associate,2,Gaming,2024-07-11,2024-08-26,2166,6.5,TechCorp Inc +AI06650,ML Ops Engineer,124352,SGD,161658,MI,FT,Singapore,L,South Africa,100,"Python, Git, Tableau, TensorFlow, Deep Learning",Associate,2,Education,2024-03-11,2024-04-11,1805,6.1,Autonomous Tech +AI06651,Research Scientist,106533,USD,106533,MI,FT,Ireland,M,Czech Republic,0,"Hadoop, SQL, AWS, MLOps",Associate,2,Telecommunications,2024-01-20,2024-03-12,870,8.6,Advanced Robotics +AI06652,Robotics Engineer,207708,EUR,176552,EX,PT,Austria,L,Austria,50,"Tableau, GCP, AWS, MLOps, Data Visualization",Bachelor,15,Healthcare,2024-04-09,2024-05-01,2248,6.6,Autonomous Tech +AI06653,Machine Learning Engineer,66074,EUR,56163,EN,FL,Netherlands,L,Netherlands,100,"Docker, Git, Statistics, Python",PhD,0,Retail,2024-01-16,2024-01-30,2044,7.4,Quantum Computing Inc +AI06654,Head of AI,73696,USD,73696,EN,FT,Ireland,M,Ireland,0,"Java, GCP, Azure",PhD,0,Retail,2025-01-20,2025-02-25,1925,6.8,Advanced Robotics +AI06655,AI Product Manager,88897,GBP,66673,EN,PT,United Kingdom,L,United Kingdom,100,"Linux, Statistics, GCP, PyTorch",Master,1,Gaming,2025-03-06,2025-03-25,1828,7.3,Machine Intelligence Group +AI06656,AI Specialist,155437,USD,155437,EX,FL,Finland,M,Turkey,50,"Python, Azure, Git, GCP",Associate,15,Manufacturing,2024-05-22,2024-06-16,1408,8.5,Smart Analytics +AI06657,AI Software Engineer,64451,USD,64451,MI,PT,Finland,S,Finland,100,"Azure, PyTorch, Mathematics, GCP, TensorFlow",Bachelor,3,Real Estate,2024-09-05,2024-10-05,843,7.6,Autonomous Tech +AI06658,AI Specialist,105020,USD,105020,SE,PT,South Korea,M,South Korea,100,"Tableau, NLP, Scala",Bachelor,7,Finance,2024-04-28,2024-07-01,2434,5.1,Advanced Robotics +AI06659,AI Architect,116832,USD,116832,SE,FL,Finland,S,Finland,100,"Statistics, GCP, Azure, Hadoop, Mathematics",Master,9,Healthcare,2024-11-21,2024-12-27,885,8.7,Machine Intelligence Group +AI06660,AI Research Scientist,59624,USD,59624,SE,PT,India,L,Chile,0,"PyTorch, Docker, AWS, Tableau",Associate,9,Real Estate,2024-12-26,2025-02-08,597,5.3,DataVision Ltd +AI06661,Machine Learning Researcher,200837,EUR,170711,EX,CT,Germany,S,Vietnam,0,"Kubernetes, Azure, Computer Vision",Master,19,Telecommunications,2024-04-17,2024-05-17,629,9.9,TechCorp Inc +AI06662,Data Analyst,353742,USD,353742,EX,CT,Denmark,L,Denmark,100,"Data Visualization, Azure, Tableau",Associate,16,Consulting,2024-04-07,2024-05-22,1671,7.4,AI Innovations +AI06663,Machine Learning Researcher,118225,GBP,88669,SE,PT,United Kingdom,M,Singapore,0,"Git, Spark, AWS",Master,9,Transportation,2025-03-26,2025-05-25,2351,8.5,AI Innovations +AI06664,ML Ops Engineer,47080,USD,47080,MI,FL,China,M,China,100,"Spark, SQL, R, Docker",Bachelor,4,Media,2024-02-20,2024-03-09,2184,6.6,TechCorp Inc +AI06665,AI Specialist,51135,USD,51135,SE,CT,India,L,Czech Republic,0,"Data Visualization, Scala, PyTorch, Git",Associate,7,Retail,2024-12-23,2025-01-12,1475,8.4,Predictive Systems +AI06666,AI Research Scientist,155505,USD,155505,SE,CT,Israel,L,Israel,50,"R, Hadoop, SQL",PhD,6,Real Estate,2025-03-16,2025-04-30,2108,6.8,Future Systems +AI06667,Robotics Engineer,69674,JPY,7664140,MI,CT,Japan,S,Japan,100,"MLOps, AWS, Java",Bachelor,2,Consulting,2024-09-15,2024-10-05,2064,7,AI Innovations +AI06668,Computer Vision Engineer,124927,JPY,13741970,SE,CT,Japan,L,Brazil,0,"Python, Linux, Computer Vision",PhD,5,Manufacturing,2024-04-02,2024-04-17,1126,7.8,DataVision Ltd +AI06669,AI Architect,112130,USD,112130,MI,PT,United States,L,United States,50,"Statistics, AWS, Azure, MLOps, Java",Bachelor,3,Gaming,2024-06-01,2024-08-01,2120,9,Cognitive Computing +AI06670,AI Software Engineer,104109,USD,104109,EX,CT,China,L,China,100,"Kubernetes, Spark, Data Visualization, Docker",PhD,13,Technology,2025-01-28,2025-03-18,759,6.5,Algorithmic Solutions +AI06671,AI Architect,47100,EUR,40035,EN,FT,Austria,S,New Zealand,0,"Kubernetes, Deep Learning, Computer Vision",Master,0,Media,2025-04-01,2025-04-25,2189,8.6,DataVision Ltd +AI06672,Research Scientist,176096,USD,176096,EX,CT,Sweden,L,Sweden,0,"Python, TensorFlow, PyTorch, NLP, Spark",Bachelor,10,Education,2024-08-13,2024-10-08,2428,9.4,DeepTech Ventures +AI06673,Robotics Engineer,52718,EUR,44810,EN,CT,France,S,France,0,"R, Kubernetes, Spark, SQL",Associate,1,Manufacturing,2025-02-23,2025-03-28,1176,6.6,Cloud AI Solutions +AI06674,Deep Learning Engineer,103610,USD,103610,EN,FT,Norway,L,Norway,100,"Kubernetes, Scala, NLP, PyTorch",Associate,1,Consulting,2025-02-19,2025-03-11,1742,9.3,Autonomous Tech +AI06675,Robotics Engineer,121009,USD,121009,MI,FT,Denmark,L,Denmark,0,"MLOps, Spark, Computer Vision, Linux, AWS",Master,2,Telecommunications,2025-02-04,2025-04-18,2066,8.3,Machine Intelligence Group +AI06676,Research Scientist,41556,USD,41556,MI,FT,India,L,India,50,"Python, PyTorch, Git, Java, Mathematics",Bachelor,4,Manufacturing,2025-01-28,2025-03-30,1688,8.6,Future Systems +AI06677,AI Consultant,185304,GBP,138978,EX,FT,United Kingdom,L,Czech Republic,0,"SQL, Hadoop, MLOps",PhD,16,Automotive,2024-10-23,2024-12-27,1002,6.6,Autonomous Tech +AI06678,Data Engineer,53652,USD,53652,EN,CT,Israel,S,Israel,0,"Azure, TensorFlow, SQL, Java",Bachelor,0,Finance,2024-01-10,2024-03-06,1224,5.8,Machine Intelligence Group +AI06679,ML Ops Engineer,92383,USD,92383,EN,FT,Denmark,L,Denmark,0,"AWS, PyTorch, GCP, Statistics",Master,1,Automotive,2024-06-10,2024-07-11,1190,5.7,Future Systems +AI06680,Robotics Engineer,63352,EUR,53849,EN,FT,Austria,S,Brazil,0,"Tableau, Data Visualization, Docker",Bachelor,1,Real Estate,2024-12-21,2025-02-08,1985,9.5,Quantum Computing Inc +AI06681,Data Analyst,177446,EUR,150829,EX,PT,Netherlands,L,China,50,"SQL, Tableau, Mathematics, MLOps, R",Associate,14,Education,2024-08-22,2024-10-24,1232,5.4,Predictive Systems +AI06682,NLP Engineer,141780,USD,141780,SE,PT,Finland,M,Finland,50,"Python, TensorFlow, Hadoop, Computer Vision",Associate,8,Automotive,2024-09-11,2024-11-06,1148,5.2,DeepTech Ventures +AI06683,Data Scientist,106379,USD,106379,EX,CT,South Korea,S,South Korea,0,"Hadoop, Docker, NLP, MLOps",Master,19,Technology,2024-01-12,2024-03-23,1018,6,Advanced Robotics +AI06684,AI Architect,126231,EUR,107296,MI,PT,Netherlands,L,Netherlands,0,"Git, Deep Learning, Docker",Bachelor,2,Consulting,2024-06-18,2024-07-25,2285,7.4,Cloud AI Solutions +AI06685,NLP Engineer,98327,CHF,88494,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Linux, Mathematics, Data Visualization, Hadoop",Associate,0,Consulting,2024-07-13,2024-08-13,641,5.1,Machine Intelligence Group +AI06686,Robotics Engineer,48433,EUR,41168,EN,PT,France,S,France,0,"PyTorch, Mathematics, Spark, Data Visualization, Kubernetes",PhD,0,Education,2025-03-11,2025-04-01,995,5.1,Algorithmic Solutions +AI06687,NLP Engineer,98587,USD,98587,MI,FT,Sweden,M,Latvia,0,"PyTorch, Kubernetes, Java, TensorFlow, Mathematics",Associate,2,Telecommunications,2024-04-29,2024-07-10,1796,6.9,Quantum Computing Inc +AI06688,AI Consultant,126335,SGD,164236,MI,FL,Singapore,L,Estonia,100,"Kubernetes, GCP, MLOps",Master,4,Gaming,2024-05-02,2024-06-15,1252,5.6,Machine Intelligence Group +AI06689,Principal Data Scientist,155034,USD,155034,SE,FT,Sweden,L,Belgium,100,"AWS, Git, SQL, Scala",Associate,6,Automotive,2025-02-09,2025-03-07,1045,5.5,Autonomous Tech +AI06690,Machine Learning Researcher,68806,USD,68806,EN,FT,Denmark,S,Denmark,50,"Linux, Git, MLOps, R, NLP",PhD,0,Education,2024-01-10,2024-02-24,1873,8.9,Advanced Robotics +AI06691,Robotics Engineer,161126,EUR,136957,EX,FT,Germany,L,Australia,0,"R, AWS, SQL, Git",PhD,16,Manufacturing,2025-02-12,2025-04-01,1563,9.9,Cognitive Computing +AI06692,Principal Data Scientist,61977,USD,61977,EN,PT,South Korea,M,Netherlands,0,"Scala, Tableau, R, MLOps, Java",Master,1,Gaming,2025-02-03,2025-04-12,535,8.1,Cloud AI Solutions +AI06693,Robotics Engineer,92188,AUD,124454,SE,FT,Australia,S,Australia,100,"NLP, Docker, Scala, Azure",PhD,9,Real Estate,2025-04-28,2025-05-24,2170,5.3,Machine Intelligence Group +AI06694,Data Analyst,34860,USD,34860,SE,FT,India,S,Italy,100,"NLP, PyTorch, Kubernetes",Associate,7,Government,2025-03-11,2025-05-02,2487,7.3,Machine Intelligence Group +AI06695,Data Scientist,65877,USD,65877,EN,FT,Finland,M,Finland,0,"Computer Vision, Statistics, Linux, Git, Data Visualization",Bachelor,0,Government,2024-03-28,2024-05-23,1899,7.2,Future Systems +AI06696,Data Analyst,126854,AUD,171253,SE,CT,Australia,S,Australia,100,"TensorFlow, PyTorch, Statistics",Master,9,Retail,2024-09-02,2024-10-15,1528,6.9,Algorithmic Solutions +AI06697,Machine Learning Researcher,242745,USD,242745,EX,FT,Israel,L,Israel,0,"GCP, Python, NLP, SQL",Master,18,Media,2024-03-20,2024-04-14,1897,5.4,Autonomous Tech +AI06698,Research Scientist,91867,USD,91867,EX,CT,China,L,Ireland,0,"Kubernetes, Git, Linux, Computer Vision, Azure",Master,17,Media,2024-03-21,2024-05-10,1486,8.7,Quantum Computing Inc +AI06699,Computer Vision Engineer,134543,USD,134543,EX,PT,Israel,S,Israel,50,"SQL, Hadoop, Tableau, Deep Learning",Master,14,Education,2024-05-14,2024-07-20,2330,8.2,Smart Analytics +AI06700,AI Product Manager,193446,USD,193446,EX,PT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Mathematics",Master,13,Government,2024-04-09,2024-06-06,1027,6.2,AI Innovations +AI06701,Machine Learning Engineer,60381,USD,60381,SE,CT,China,S,China,100,"SQL, Docker, Statistics, Tableau",Master,5,Technology,2024-06-10,2024-07-10,2340,9,DataVision Ltd +AI06702,Data Engineer,163915,AUD,221285,SE,CT,Australia,L,Australia,50,"Scala, Azure, Tableau, Python",PhD,8,Real Estate,2024-09-18,2024-11-20,1260,9.1,Advanced Robotics +AI06703,AI Research Scientist,68470,EUR,58200,MI,FT,France,S,France,100,"Kubernetes, Git, Mathematics, PyTorch",PhD,4,Media,2024-03-20,2024-05-22,2278,7,Neural Networks Co +AI06704,AI Product Manager,161796,USD,161796,EX,FL,Norway,S,Switzerland,0,"Docker, PyTorch, Git, Deep Learning",Bachelor,13,Energy,2024-10-01,2024-11-28,529,5.1,Quantum Computing Inc +AI06705,Data Engineer,179771,USD,179771,EX,FL,Sweden,S,South Korea,0,"SQL, Hadoop, PyTorch",Master,12,Healthcare,2024-04-03,2024-05-12,508,7.4,Autonomous Tech +AI06706,AI Software Engineer,93524,USD,93524,EN,FT,Norway,M,Norway,100,"Computer Vision, Docker, Git, Spark",Bachelor,0,Retail,2024-03-09,2024-04-23,1533,7.2,DeepTech Ventures +AI06707,AI Architect,165207,USD,165207,SE,FL,Denmark,S,Germany,100,"Java, Kubernetes, Tableau, Scala, Computer Vision",Master,5,Automotive,2025-03-10,2025-04-07,946,6.8,TechCorp Inc +AI06708,Data Analyst,63790,GBP,47843,EN,PT,United Kingdom,M,United Kingdom,50,"Java, SQL, GCP, Docker",Associate,1,Government,2025-02-06,2025-03-28,644,8.1,Autonomous Tech +AI06709,Autonomous Systems Engineer,166660,USD,166660,EX,CT,Finland,S,Finland,50,"MLOps, Deep Learning, Linux",PhD,11,Government,2025-01-14,2025-02-21,715,9.7,Digital Transformation LLC +AI06710,AI Product Manager,65921,USD,65921,MI,PT,Finland,S,Finland,0,"AWS, Python, Deep Learning, Computer Vision, TensorFlow",Master,4,Retail,2025-01-22,2025-03-19,905,6.7,DataVision Ltd +AI06711,AI Product Manager,126851,EUR,107823,SE,FL,Austria,L,Austria,100,"Mathematics, Computer Vision, PyTorch",PhD,7,Consulting,2024-10-12,2024-11-06,2223,9.8,Neural Networks Co +AI06712,Machine Learning Researcher,90333,USD,90333,SE,FT,Israel,S,Nigeria,100,"SQL, Spark, Deep Learning, Computer Vision",Master,9,Real Estate,2024-10-07,2024-11-05,2265,8.1,Digital Transformation LLC +AI06713,AI Consultant,70882,CAD,88603,EN,FL,Canada,M,Canada,0,"Computer Vision, Scala, SQL, Azure",PhD,1,Media,2024-12-04,2025-02-09,598,7.2,DataVision Ltd +AI06714,AI Specialist,196013,EUR,166611,EX,FL,Austria,M,Austria,100,"PyTorch, Python, Computer Vision",Associate,13,Government,2024-06-22,2024-08-09,1413,8.6,TechCorp Inc +AI06715,AI Software Engineer,81980,EUR,69683,EN,FL,Austria,L,Chile,50,"Kubernetes, Data Visualization, Scala, MLOps, Docker",PhD,1,Media,2024-11-27,2024-12-14,1918,8.3,Cognitive Computing +AI06716,Data Engineer,58677,EUR,49875,EN,PT,Germany,S,Germany,100,"Hadoop, SQL, TensorFlow, Python, Tableau",Associate,1,Telecommunications,2024-07-11,2024-09-09,2173,9.9,AI Innovations +AI06717,Head of AI,73309,EUR,62313,EN,CT,France,M,France,100,"Docker, Computer Vision, MLOps, Python",Associate,0,Telecommunications,2024-02-18,2024-04-13,1884,6.2,Algorithmic Solutions +AI06718,Deep Learning Engineer,201876,CHF,181688,SE,FT,Switzerland,M,Switzerland,0,"SQL, Hadoop, Python, Computer Vision, Statistics",PhD,7,Media,2025-02-08,2025-04-19,2072,9.8,Algorithmic Solutions +AI06719,Computer Vision Engineer,65018,USD,65018,EN,CT,Ireland,S,Ireland,100,"Python, Java, Spark, Linux, Hadoop",Associate,0,Consulting,2024-10-22,2024-11-15,2365,9,DeepTech Ventures +AI06720,Robotics Engineer,161696,GBP,121272,SE,FT,United Kingdom,L,United Kingdom,50,"Hadoop, SQL, Linux, Java, AWS",Master,6,Manufacturing,2024-05-14,2024-06-09,1123,5.1,Cognitive Computing +AI06721,Head of AI,59865,USD,59865,SE,CT,China,S,China,0,"SQL, Python, Docker, TensorFlow, Statistics",Bachelor,7,Healthcare,2024-11-20,2025-01-26,1696,7,Advanced Robotics +AI06722,Principal Data Scientist,73349,GBP,55012,MI,PT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow",Master,3,Retail,2024-10-20,2024-12-16,1212,9.7,Predictive Systems +AI06723,AI Consultant,62324,CAD,77905,EN,FL,Canada,S,Canada,100,"Mathematics, SQL, Azure, PyTorch, Scala",PhD,1,Energy,2024-01-27,2024-02-20,1034,7.5,Autonomous Tech +AI06724,AI Software Engineer,125505,USD,125505,MI,FL,Denmark,M,Denmark,50,"PyTorch, Scala, AWS",Bachelor,2,Government,2024-09-21,2024-11-10,1131,7.5,Quantum Computing Inc +AI06725,Data Scientist,124940,USD,124940,MI,CT,Ireland,L,Ireland,100,"Computer Vision, Kubernetes, NLP, Hadoop, Mathematics",Associate,4,Technology,2025-04-06,2025-05-29,1172,8.8,Autonomous Tech +AI06726,Machine Learning Engineer,62978,EUR,53531,EN,CT,Germany,S,Germany,100,"Statistics, Linux, Computer Vision, Deep Learning",PhD,1,Energy,2024-10-20,2024-12-18,889,8.9,Autonomous Tech +AI06727,Head of AI,146869,CAD,183586,EX,FL,Canada,S,Indonesia,50,"Tableau, Scala, Kubernetes, Data Visualization",Master,18,Healthcare,2024-05-12,2024-07-14,595,6.9,Quantum Computing Inc +AI06728,Robotics Engineer,216474,AUD,292240,EX,FT,Australia,M,India,100,"AWS, Kubernetes, Hadoop, Tableau",Bachelor,10,Media,2024-08-23,2024-09-11,1460,7.9,Cognitive Computing +AI06729,Machine Learning Researcher,91542,GBP,68657,MI,FL,United Kingdom,S,Ukraine,50,"TensorFlow, Statistics, Mathematics",PhD,3,Consulting,2024-08-17,2024-09-05,2001,6.9,Quantum Computing Inc +AI06730,Research Scientist,104890,CAD,131113,MI,FL,Canada,L,Canada,0,"Scala, Kubernetes, MLOps, Computer Vision, Git",Associate,4,Automotive,2024-04-29,2024-07-08,1658,5.3,DataVision Ltd +AI06731,AI Product Manager,74588,EUR,63400,MI,FL,France,S,France,100,"Scala, Linux, Git, TensorFlow, Deep Learning",Bachelor,4,Finance,2024-09-16,2024-11-04,1680,5.4,Future Systems +AI06732,Data Scientist,142343,EUR,120992,EX,PT,Germany,S,Germany,50,"Hadoop, Spark, MLOps",PhD,19,Media,2024-08-21,2024-09-18,1251,9.5,Digital Transformation LLC +AI06733,Deep Learning Engineer,161000,GBP,120750,EX,CT,United Kingdom,S,United Kingdom,50,"Git, Statistics, SQL, Deep Learning",Bachelor,13,Government,2024-09-08,2024-10-13,1604,8,DeepTech Ventures +AI06734,Autonomous Systems Engineer,214330,AUD,289346,EX,FT,Australia,S,Spain,50,"Python, TensorFlow, SQL",Bachelor,16,Education,2024-04-04,2024-05-09,2467,6.7,Cloud AI Solutions +AI06735,Deep Learning Engineer,103678,EUR,88126,SE,CT,France,M,Denmark,100,"Python, Git, TensorFlow, SQL, MLOps",Bachelor,9,Energy,2024-06-25,2024-09-02,514,5.5,Predictive Systems +AI06736,Principal Data Scientist,54303,USD,54303,EN,FL,South Korea,M,Israel,100,"PyTorch, Data Visualization, Tableau, Deep Learning, Scala",PhD,0,Retail,2024-01-24,2024-03-27,1109,6.8,Advanced Robotics +AI06737,NLP Engineer,56474,USD,56474,EN,CT,Sweden,M,Sweden,50,"PyTorch, Kubernetes, Hadoop, Mathematics, SQL",Associate,0,Technology,2024-05-23,2024-08-02,1477,6,Neural Networks Co +AI06738,NLP Engineer,300349,GBP,225262,EX,PT,United Kingdom,L,United Kingdom,0,"Java, Data Visualization, Hadoop, Python",Bachelor,18,Media,2024-05-22,2024-07-11,827,7.5,Cloud AI Solutions +AI06739,AI Consultant,44528,EUR,37849,EN,FT,France,S,France,100,"R, MLOps, Data Visualization, Kubernetes",Master,1,Finance,2024-04-01,2024-05-07,1942,5.5,DeepTech Ventures +AI06740,Machine Learning Researcher,118343,USD,118343,SE,FT,Israel,M,Israel,100,"Mathematics, MLOps, Data Visualization",PhD,6,Healthcare,2024-07-30,2024-09-03,1236,8.3,Advanced Robotics +AI06741,AI Architect,125950,USD,125950,MI,FT,Denmark,L,Poland,50,"SQL, AWS, NLP",Bachelor,4,Technology,2025-01-30,2025-03-01,1563,6,Neural Networks Co +AI06742,AI Research Scientist,61502,USD,61502,EN,CT,Israel,M,Austria,50,"R, Python, Java, GCP",Master,1,Media,2025-01-01,2025-01-28,2019,9.1,Quantum Computing Inc +AI06743,Head of AI,44859,EUR,38130,EN,CT,France,S,France,0,"Azure, Tableau, GCP",PhD,1,Healthcare,2024-11-21,2024-12-31,1364,5.3,Advanced Robotics +AI06744,Autonomous Systems Engineer,119175,JPY,13109250,MI,CT,Japan,L,Japan,100,"Kubernetes, Python, MLOps",Bachelor,4,Automotive,2025-04-21,2025-06-27,1528,6.9,Algorithmic Solutions +AI06745,Research Scientist,90723,USD,90723,MI,PT,United States,M,United States,0,"Hadoop, Mathematics, Tableau",Master,3,Government,2024-07-23,2024-10-01,1136,5.5,Quantum Computing Inc +AI06746,Robotics Engineer,239693,EUR,203739,EX,CT,France,L,China,100,"AWS, Scala, Statistics, Spark",PhD,11,Healthcare,2025-02-06,2025-03-01,2160,5.9,DeepTech Ventures +AI06747,Autonomous Systems Engineer,89947,CHF,80952,EN,FT,Switzerland,L,Australia,0,"AWS, Python, MLOps",Bachelor,0,Energy,2024-03-01,2024-05-02,1832,5.7,DataVision Ltd +AI06748,AI Architect,78388,USD,78388,MI,CT,Finland,S,Finland,50,"MLOps, Tableau, Python",Associate,3,Consulting,2024-08-23,2024-10-11,1416,9,TechCorp Inc +AI06749,Deep Learning Engineer,205050,USD,205050,SE,FL,United States,L,United States,100,"Kubernetes, Deep Learning, PyTorch, TensorFlow, SQL",Bachelor,7,Retail,2024-02-28,2024-04-22,2190,5.3,Autonomous Tech +AI06750,Data Scientist,91998,EUR,78198,MI,FL,Netherlands,M,Netherlands,0,"Data Visualization, Python, GCP",PhD,4,Education,2024-03-25,2024-05-20,1349,5.6,Cloud AI Solutions +AI06751,Data Engineer,226755,USD,226755,EX,PT,Finland,L,Finland,0,"Git, PyTorch, SQL, TensorFlow",Master,13,Gaming,2024-12-27,2025-02-28,564,6.4,Algorithmic Solutions +AI06752,NLP Engineer,123422,USD,123422,MI,FT,Denmark,S,Denmark,100,"Python, AWS, TensorFlow, Data Visualization, GCP",Associate,4,Telecommunications,2024-11-16,2024-12-12,2296,6.2,Cloud AI Solutions +AI06753,Data Engineer,206557,USD,206557,SE,FT,Norway,L,Norway,0,"PyTorch, Kubernetes, AWS, Azure, Computer Vision",PhD,9,Automotive,2025-02-18,2025-03-25,2426,6.9,TechCorp Inc +AI06754,Computer Vision Engineer,97955,USD,97955,EN,PT,Denmark,L,Kenya,100,"SQL, Linux, Azure, Spark, Deep Learning",Associate,1,Consulting,2024-07-05,2024-09-01,2218,9.7,Neural Networks Co +AI06755,Robotics Engineer,113968,AUD,153857,SE,CT,Australia,M,Australia,0,"Docker, Java, Python, Azure",Bachelor,9,Telecommunications,2024-06-12,2024-07-17,1975,5.5,Predictive Systems +AI06756,Autonomous Systems Engineer,73215,CAD,91519,EN,PT,Canada,M,Canada,0,"Scala, Python, Tableau",Master,0,Education,2024-06-28,2024-09-06,1660,7.5,Machine Intelligence Group +AI06757,Data Analyst,79628,CAD,99535,EN,FT,Canada,L,Japan,50,"Python, Docker, Computer Vision, Mathematics, Statistics",Bachelor,0,Technology,2024-06-02,2024-06-26,913,9.9,DataVision Ltd +AI06758,Data Engineer,177463,USD,177463,SE,CT,Norway,L,Norway,50,"Kubernetes, Mathematics, NLP, TensorFlow, Computer Vision",PhD,7,Technology,2025-02-24,2025-04-13,849,5.5,Future Systems +AI06759,AI Architect,126055,SGD,163872,SE,PT,Singapore,L,Luxembourg,50,"PyTorch, Scala, Tableau",PhD,5,Education,2024-11-03,2024-12-26,1623,6.6,AI Innovations +AI06760,AI Consultant,41096,USD,41096,SE,PT,India,M,Japan,0,"Scala, Java, Docker, Deep Learning",Associate,7,Real Estate,2024-05-14,2024-07-13,629,8.5,Machine Intelligence Group +AI06761,Principal Data Scientist,141579,AUD,191132,EX,FL,Australia,S,Australia,100,"R, Kubernetes, NLP, SQL",Master,10,Energy,2024-07-28,2024-10-09,608,7.9,Advanced Robotics +AI06762,Principal Data Scientist,117805,CAD,147256,EX,PT,Canada,S,Israel,50,"Python, Scala, MLOps, Linux",Associate,17,Media,2024-04-12,2024-06-08,1141,8.5,Advanced Robotics +AI06763,ML Ops Engineer,76368,USD,76368,SE,FT,China,L,Portugal,50,"Computer Vision, Java, Kubernetes, MLOps, Deep Learning",Bachelor,6,Healthcare,2024-07-06,2024-09-11,2307,9.9,TechCorp Inc +AI06764,NLP Engineer,66318,USD,66318,EN,FL,South Korea,M,Finland,0,"Hadoop, SQL, Computer Vision",Associate,1,Technology,2024-09-28,2024-12-07,548,5.5,Neural Networks Co +AI06765,AI Research Scientist,170692,USD,170692,EX,CT,Ireland,S,Ireland,0,"GCP, AWS, Deep Learning, PyTorch",PhD,15,Transportation,2024-05-15,2024-07-16,706,6.8,Machine Intelligence Group +AI06766,Computer Vision Engineer,289060,SGD,375778,EX,FL,Singapore,L,Singapore,0,"SQL, Git, Computer Vision, Statistics",Master,15,Real Estate,2024-04-28,2024-06-17,2412,8.6,DataVision Ltd +AI06767,Data Analyst,120746,USD,120746,SE,CT,Sweden,S,Sweden,0,"PyTorch, Python, Deep Learning, GCP, NLP",Associate,9,Technology,2024-12-21,2025-01-06,2167,5.5,Machine Intelligence Group +AI06768,Principal Data Scientist,97475,JPY,10722250,MI,FT,Japan,S,Japan,0,"Java, Kubernetes, SQL, Python",Bachelor,4,Finance,2025-01-02,2025-03-11,627,6.8,DataVision Ltd +AI06769,Computer Vision Engineer,228776,USD,228776,EX,FL,Israel,M,Israel,100,"TensorFlow, Python, Scala, Java",Bachelor,18,Manufacturing,2024-04-15,2024-06-22,1406,5.1,Digital Transformation LLC +AI06770,AI Specialist,224210,CAD,280263,EX,FL,Canada,M,Canada,100,"Statistics, Spark, Python, PyTorch",PhD,10,Manufacturing,2024-07-13,2024-09-02,1369,8.2,Quantum Computing Inc +AI06771,Head of AI,71016,USD,71016,EN,CT,Finland,L,Finland,50,"Git, Linux, Tableau",Master,0,Energy,2024-08-26,2024-10-26,2128,5.4,DataVision Ltd +AI06772,AI Product Manager,157055,USD,157055,MI,FT,Norway,L,Latvia,50,"PyTorch, Kubernetes, Statistics",Master,4,Energy,2024-02-13,2024-03-07,679,6.4,Digital Transformation LLC +AI06773,AI Specialist,78910,USD,78910,MI,FL,Israel,S,Latvia,0,"Azure, Deep Learning, Computer Vision",Associate,4,Telecommunications,2025-02-26,2025-04-19,913,5.8,DataVision Ltd +AI06774,AI Product Manager,133220,USD,133220,EX,FT,Finland,S,Estonia,50,"Hadoop, Docker, NLP, Git, PyTorch",PhD,10,Government,2024-02-16,2024-03-28,960,5.1,Quantum Computing Inc +AI06775,Machine Learning Engineer,102537,EUR,87156,MI,FL,France,M,France,100,"Spark, Java, Mathematics",Bachelor,3,Gaming,2025-02-27,2025-04-25,2295,7.7,Cognitive Computing +AI06776,Autonomous Systems Engineer,95026,USD,95026,EN,FT,United States,L,Latvia,50,"Git, Python, Azure",Master,0,Real Estate,2024-06-02,2024-07-14,968,8.4,Neural Networks Co +AI06777,AI Research Scientist,163095,USD,163095,EX,FT,Finland,L,Finland,50,"Git, AWS, MLOps, Statistics",Bachelor,17,Retail,2024-02-15,2024-03-01,1932,8,Algorithmic Solutions +AI06778,Data Scientist,86115,JPY,9472650,MI,FT,Japan,S,Japan,50,"R, Spark, Linux, Data Visualization",Associate,2,Education,2024-10-15,2024-11-03,2194,6.4,Cloud AI Solutions +AI06779,Robotics Engineer,81518,EUR,69290,MI,PT,France,S,France,50,"Computer Vision, Docker, Azure",PhD,2,Finance,2024-03-26,2024-04-23,724,5.6,Autonomous Tech +AI06780,Head of AI,112582,EUR,95695,SE,PT,Austria,S,Austria,100,"Spark, AWS, Docker",PhD,5,Media,2025-01-11,2025-03-09,569,5.7,Digital Transformation LLC +AI06781,Data Engineer,179222,USD,179222,SE,PT,Norway,L,Argentina,100,"Spark, Statistics, PyTorch, SQL, TensorFlow",PhD,8,Retail,2024-03-07,2024-05-02,619,7.4,Algorithmic Solutions +AI06782,AI Research Scientist,267085,CHF,240377,EX,FL,Switzerland,L,Argentina,0,"AWS, PyTorch, Statistics",PhD,14,Transportation,2024-11-18,2025-01-06,591,6.7,DeepTech Ventures +AI06783,AI Specialist,72647,USD,72647,EN,FL,South Korea,L,Estonia,50,"Azure, Spark, Scala, Linux",Bachelor,0,Manufacturing,2024-07-03,2024-07-21,2440,8,Algorithmic Solutions +AI06784,Principal Data Scientist,157364,SGD,204573,EX,CT,Singapore,M,Singapore,0,"Azure, MLOps, Data Visualization, Hadoop",Bachelor,18,Finance,2024-01-23,2024-03-16,2250,9.9,Future Systems +AI06785,Research Scientist,147887,GBP,110915,SE,PT,United Kingdom,L,Chile,100,"Linux, Spark, NLP, Python",Bachelor,7,Education,2024-09-22,2024-11-26,1467,9.6,Advanced Robotics +AI06786,AI Specialist,93908,JPY,10329880,MI,PT,Japan,L,Japan,0,"Hadoop, Deep Learning, Java, Kubernetes",Bachelor,4,Technology,2025-03-28,2025-05-27,1495,6.4,DataVision Ltd +AI06787,Data Scientist,221005,USD,221005,SE,FL,Norway,L,New Zealand,0,"SQL, NLP, Statistics, Deep Learning, R",Associate,9,Energy,2024-07-11,2024-08-06,1072,6.3,Neural Networks Co +AI06788,AI Consultant,188472,USD,188472,SE,FL,Denmark,M,Denmark,0,"Git, AWS, Mathematics, NLP",PhD,8,Finance,2024-04-16,2024-06-13,769,8,DataVision Ltd +AI06789,AI Research Scientist,134644,USD,134644,SE,FL,South Korea,L,South Korea,100,"Scala, TensorFlow, Kubernetes, Statistics, R",PhD,9,Real Estate,2024-10-22,2024-12-15,1688,7.9,DataVision Ltd +AI06790,ML Ops Engineer,158617,AUD,214133,EX,CT,Australia,L,Australia,50,"Python, AWS, TensorFlow",Bachelor,11,Healthcare,2024-06-16,2024-08-11,2165,8.6,Quantum Computing Inc +AI06791,ML Ops Engineer,80635,USD,80635,MI,FT,Israel,L,Canada,50,"Spark, Azure, Data Visualization, Computer Vision",PhD,3,Consulting,2024-12-26,2025-01-23,2490,9.8,Predictive Systems +AI06792,Machine Learning Researcher,186187,SGD,242043,EX,PT,Singapore,M,Singapore,50,"Computer Vision, Git, Python, Deep Learning",Associate,18,Technology,2025-02-26,2025-04-05,1822,5.2,Machine Intelligence Group +AI06793,Computer Vision Engineer,101105,EUR,85939,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP",Bachelor,4,Real Estate,2024-01-19,2024-03-25,888,9.7,Machine Intelligence Group +AI06794,Data Scientist,178163,USD,178163,EX,FT,Ireland,L,Ireland,0,"GCP, TensorFlow, Linux",PhD,15,Manufacturing,2024-06-04,2024-08-07,979,8.8,Cloud AI Solutions +AI06795,ML Ops Engineer,63735,EUR,54175,EN,PT,France,L,France,0,"SQL, PyTorch, Data Visualization",Master,0,Healthcare,2024-05-04,2024-06-12,2161,9.4,Autonomous Tech +AI06796,AI Consultant,148327,CHF,133494,MI,FL,Switzerland,M,Canada,0,"Azure, Scala, Linux",Master,3,Energy,2024-03-23,2024-04-07,1743,8.7,Algorithmic Solutions +AI06797,Computer Vision Engineer,70092,USD,70092,MI,PT,Finland,S,Chile,100,"Java, SQL, Tableau",Bachelor,2,Technology,2025-01-23,2025-03-03,899,5.8,Cognitive Computing +AI06798,AI Research Scientist,168805,USD,168805,SE,PT,Sweden,L,Sweden,50,"AWS, SQL, Data Visualization, Computer Vision",Bachelor,5,Energy,2024-05-07,2024-06-08,1562,10,Algorithmic Solutions +AI06799,AI Product Manager,167702,CAD,209628,EX,PT,Canada,S,Germany,50,"Python, MLOps, TensorFlow, NLP",Associate,16,Gaming,2024-06-26,2024-08-11,1409,9.6,TechCorp Inc +AI06800,Robotics Engineer,77196,EUR,65617,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Spark, Computer Vision, SQL, GCP",Master,3,Energy,2025-01-17,2025-02-05,566,9.7,Quantum Computing Inc +AI06801,AI Product Manager,60668,EUR,51568,EN,FL,Austria,M,Austria,0,"Python, Java, NLP, Azure",Bachelor,0,Telecommunications,2024-07-03,2024-07-22,934,8.5,Autonomous Tech +AI06802,Machine Learning Researcher,238168,AUD,321527,EX,FL,Australia,L,Australia,0,"SQL, Git, Deep Learning",Master,14,Energy,2024-04-05,2024-05-07,1426,7.2,Cognitive Computing +AI06803,Principal Data Scientist,80987,SGD,105283,MI,PT,Singapore,S,Singapore,0,"SQL, Git, NLP, Deep Learning",Bachelor,4,Manufacturing,2024-12-08,2025-02-11,1153,8.3,Autonomous Tech +AI06804,Autonomous Systems Engineer,58908,USD,58908,EN,FL,United States,S,Hungary,100,"PyTorch, TensorFlow, R",Bachelor,1,Gaming,2024-02-06,2024-04-08,1768,5.7,Algorithmic Solutions +AI06805,Machine Learning Engineer,56978,GBP,42734,EN,PT,United Kingdom,S,United Kingdom,0,"NLP, Spark, Python, Hadoop",PhD,1,Manufacturing,2025-01-16,2025-02-20,1809,6.3,Algorithmic Solutions +AI06806,Autonomous Systems Engineer,149583,USD,149583,EX,PT,Israel,M,Israel,50,"TensorFlow, Azure, PyTorch",Master,12,Manufacturing,2024-08-16,2024-10-27,1499,9.5,Digital Transformation LLC +AI06807,Robotics Engineer,275970,USD,275970,EX,CT,Ireland,L,Ireland,50,"Tableau, Scala, R",Bachelor,16,Real Estate,2025-02-18,2025-04-26,2306,5.3,Autonomous Tech +AI06808,Head of AI,154006,EUR,130905,EX,CT,Germany,M,Germany,100,"TensorFlow, Hadoop, AWS, SQL",PhD,12,Energy,2024-07-26,2024-08-17,1303,7.7,Advanced Robotics +AI06809,Principal Data Scientist,131751,JPY,14492610,MI,FT,Japan,L,Japan,0,"Kubernetes, Python, R",Master,4,Automotive,2024-11-12,2024-12-29,2127,6.3,Future Systems +AI06810,Robotics Engineer,163158,JPY,17947380,SE,FL,Japan,L,Mexico,50,"Mathematics, Tableau, Kubernetes",Master,7,Transportation,2024-01-27,2024-03-08,885,6.8,Digital Transformation LLC +AI06811,Principal Data Scientist,52986,USD,52986,EN,PT,Sweden,M,Thailand,0,"SQL, Hadoop, MLOps",Associate,1,Real Estate,2024-09-08,2024-10-02,1605,5.5,Digital Transformation LLC +AI06812,NLP Engineer,326359,CHF,293723,EX,PT,Switzerland,L,Switzerland,0,"Linux, Python, Data Visualization, Computer Vision, Scala",Bachelor,11,Government,2024-05-27,2024-07-26,904,6.1,Cognitive Computing +AI06813,NLP Engineer,78523,USD,78523,EN,FT,Israel,L,United States,100,"Deep Learning, PyTorch, SQL",Associate,1,Technology,2024-10-13,2024-11-24,1039,5.8,AI Innovations +AI06814,NLP Engineer,104203,SGD,135464,MI,FL,Singapore,M,Singapore,100,"Statistics, Python, NLP, Spark, Data Visualization",Bachelor,4,Government,2024-03-19,2024-05-01,937,8,AI Innovations +AI06815,Data Engineer,39561,USD,39561,SE,PT,India,S,India,100,"TensorFlow, Git, Data Visualization",PhD,9,Automotive,2024-08-04,2024-09-18,1448,7.4,Predictive Systems +AI06816,AI Research Scientist,80731,EUR,68621,EN,PT,Austria,L,Austria,100,"Kubernetes, GCP, Java",Bachelor,0,Education,2024-02-07,2024-04-19,2243,9.4,Advanced Robotics +AI06817,Research Scientist,138085,EUR,117372,EX,FT,Austria,M,Austria,100,"SQL, NLP, Kubernetes, R",Associate,14,Transportation,2024-08-10,2024-09-30,875,5.5,Advanced Robotics +AI06818,ML Ops Engineer,77251,GBP,57938,EN,PT,United Kingdom,M,United Kingdom,50,"Data Visualization, Tableau, Python, TensorFlow, Linux",Master,0,Finance,2024-05-02,2024-06-08,1189,7.5,Future Systems +AI06819,Data Engineer,82330,JPY,9056300,EN,CT,Japan,L,Brazil,0,"Azure, PyTorch, Tableau, Data Visualization, Scala",PhD,0,Media,2024-11-10,2025-01-06,988,7.9,Neural Networks Co +AI06820,Data Engineer,78143,EUR,66422,EN,FT,Netherlands,L,India,0,"PyTorch, Hadoop, Tableau, MLOps",PhD,0,Consulting,2024-01-05,2024-03-12,1227,7.5,Algorithmic Solutions +AI06821,Computer Vision Engineer,143711,USD,143711,SE,PT,Israel,M,Israel,100,"Computer Vision, GCP, Statistics, Python, Mathematics",Bachelor,8,Finance,2025-03-22,2025-05-08,1997,7.8,Neural Networks Co +AI06822,Autonomous Systems Engineer,33586,USD,33586,EN,FL,China,S,China,0,"PyTorch, Computer Vision, Linux, Deep Learning, NLP",Bachelor,0,Retail,2024-05-27,2024-07-23,942,7.2,Algorithmic Solutions +AI06823,Research Scientist,22293,USD,22293,EN,FL,India,L,India,50,"SQL, MLOps, PyTorch",PhD,1,Gaming,2024-07-14,2024-09-22,753,8.4,DeepTech Ventures +AI06824,ML Ops Engineer,98076,JPY,10788360,MI,CT,Japan,L,Japan,0,"Docker, Kubernetes, Data Visualization, TensorFlow, Azure",Master,4,Media,2025-04-22,2025-06-27,1933,7.9,Cloud AI Solutions +AI06825,Machine Learning Engineer,98006,EUR,83305,SE,FL,Netherlands,S,Netherlands,100,"SQL, Spark, PyTorch, R, TensorFlow",Bachelor,5,Consulting,2024-03-24,2024-04-14,1977,8.6,Autonomous Tech +AI06826,Data Scientist,66357,USD,66357,EN,FL,South Korea,M,New Zealand,100,"Java, SQL, Tableau",Associate,1,Gaming,2024-08-31,2024-09-16,2478,8.7,DeepTech Ventures +AI06827,AI Architect,193061,CHF,173755,SE,PT,Switzerland,L,Romania,50,"Computer Vision, Statistics, MLOps, NLP, Kubernetes",Master,5,Finance,2024-08-18,2024-10-16,1911,5.8,Autonomous Tech +AI06828,AI Software Engineer,220816,USD,220816,EX,CT,Sweden,M,Sweden,100,"AWS, Hadoop, Deep Learning",PhD,16,Transportation,2024-10-03,2024-11-03,610,5.9,Predictive Systems +AI06829,AI Software Engineer,130692,USD,130692,SE,FL,Sweden,L,Sweden,0,"Python, Linux, Tableau, Java, NLP",Master,9,Finance,2024-12-28,2025-03-08,1297,9.7,Algorithmic Solutions +AI06830,Machine Learning Researcher,207792,CHF,187013,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, SQL, Java",Associate,9,Gaming,2024-06-17,2024-08-10,1818,6.8,Advanced Robotics +AI06831,Data Scientist,65685,USD,65685,EN,PT,United States,S,United States,100,"Azure, SQL, NLP, Python",Master,1,Consulting,2024-01-01,2024-03-10,1366,9.2,Neural Networks Co +AI06832,AI Architect,125757,EUR,106893,SE,CT,Germany,L,Germany,0,"PyTorch, Computer Vision, GCP, Linux",Associate,6,Real Estate,2025-03-02,2025-04-24,1445,6.4,Quantum Computing Inc +AI06833,Head of AI,85426,EUR,72612,EN,CT,Netherlands,L,Netherlands,50,"Java, Python, Tableau",PhD,0,Real Estate,2024-03-22,2024-04-16,551,8.8,Autonomous Tech +AI06834,AI Specialist,25694,USD,25694,EN,FT,India,L,India,100,"AWS, Hadoop, NLP, Java",Bachelor,1,Technology,2025-02-10,2025-03-30,2280,8.3,Algorithmic Solutions +AI06835,Deep Learning Engineer,175415,CHF,157874,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, SQL, Azure",PhD,8,Telecommunications,2025-02-18,2025-03-09,1460,8.6,Neural Networks Co +AI06836,AI Product Manager,123361,USD,123361,SE,PT,Sweden,S,Estonia,50,"Spark, Python, Computer Vision, Kubernetes",Master,5,Consulting,2024-10-15,2024-10-30,1859,6.3,Quantum Computing Inc +AI06837,Robotics Engineer,158738,JPY,17461180,EX,FT,Japan,S,Japan,50,"Docker, Deep Learning, Scala, Spark",PhD,14,Media,2024-04-04,2024-05-13,1906,6,Digital Transformation LLC +AI06838,AI Research Scientist,83310,EUR,70814,EN,PT,Netherlands,L,Netherlands,50,"Linux, Statistics, TensorFlow",Master,0,Gaming,2025-02-04,2025-03-26,1650,10,DeepTech Ventures +AI06839,AI Architect,90940,EUR,77299,MI,FT,Germany,L,Germany,0,"Hadoop, Python, Deep Learning",PhD,3,Finance,2024-06-06,2024-07-03,2371,7,Neural Networks Co +AI06840,Principal Data Scientist,78709,USD,78709,EN,FL,Finland,L,Finland,50,"Tableau, Python, Scala",Master,1,Automotive,2024-10-08,2024-10-28,505,8,Predictive Systems +AI06841,Principal Data Scientist,23429,USD,23429,MI,CT,India,S,India,50,"Python, Azure, Deep Learning, Java, Scala",Bachelor,3,Media,2025-01-26,2025-03-18,2362,9,Autonomous Tech +AI06842,Data Scientist,56096,USD,56096,SE,PT,China,L,France,50,"Deep Learning, Python, Data Visualization, Statistics, Linux",Bachelor,5,Media,2024-05-20,2024-06-07,1141,6.5,Algorithmic Solutions +AI06843,Machine Learning Researcher,79608,USD,79608,MI,FL,South Korea,S,South Korea,100,"GCP, Linux, NLP, Data Visualization, Mathematics",Associate,2,Finance,2024-04-11,2024-05-28,1325,8,Neural Networks Co +AI06844,ML Ops Engineer,62288,USD,62288,EN,FL,Finland,M,Finland,100,"Spark, Scala, GCP",Bachelor,1,Government,2025-01-05,2025-01-29,1712,7.1,Quantum Computing Inc +AI06845,NLP Engineer,231007,AUD,311859,EX,FL,Australia,L,Australia,0,"TensorFlow, Linux, PyTorch, Spark, SQL",Bachelor,15,Automotive,2024-03-26,2024-05-04,1826,8.5,Digital Transformation LLC +AI06846,Principal Data Scientist,100308,USD,100308,EN,FT,United States,L,Australia,100,"Computer Vision, Scala, MLOps, NLP",Master,0,Energy,2024-03-18,2024-04-05,2263,9.2,TechCorp Inc +AI06847,AI Consultant,106652,EUR,90654,MI,PT,Austria,L,Austria,100,"Python, Hadoop, Linux, TensorFlow",PhD,4,Transportation,2025-01-24,2025-03-04,897,9.5,Cognitive Computing +AI06848,Research Scientist,75358,USD,75358,MI,FL,South Korea,M,South Korea,100,"Data Visualization, Python, TensorFlow, Git, Computer Vision",PhD,4,Retail,2024-07-22,2024-09-30,2175,7.9,Autonomous Tech +AI06849,ML Ops Engineer,20791,USD,20791,EN,FL,India,S,India,0,"Computer Vision, MLOps, Data Visualization",Bachelor,0,Automotive,2025-02-22,2025-04-20,946,6.2,Autonomous Tech +AI06850,Principal Data Scientist,97537,EUR,82906,SE,FL,Germany,S,Germany,100,"Deep Learning, Computer Vision, Azure",Associate,6,Gaming,2024-11-09,2025-01-11,704,5.2,Cloud AI Solutions +AI06851,Autonomous Systems Engineer,137228,AUD,185258,SE,CT,Australia,S,Australia,0,"Computer Vision, Azure, AWS",Master,7,Healthcare,2024-03-29,2024-05-14,2399,8.3,DeepTech Ventures +AI06852,AI Consultant,130679,AUD,176417,EX,FL,Australia,S,France,100,"Hadoop, Data Visualization, Python",PhD,19,Telecommunications,2024-05-03,2024-07-06,2270,7.7,Cloud AI Solutions +AI06853,Research Scientist,212506,EUR,180630,EX,CT,Germany,M,Indonesia,50,"Scala, SQL, Linux, AWS",Bachelor,11,Media,2024-05-10,2024-07-13,2220,5.3,Quantum Computing Inc +AI06854,AI Research Scientist,107510,CHF,96759,EN,PT,Switzerland,M,Romania,0,"Kubernetes, MLOps, Docker, AWS",PhD,0,Energy,2024-12-06,2024-12-20,1845,9.5,Algorithmic Solutions +AI06855,Autonomous Systems Engineer,75716,EUR,64359,EN,FL,France,L,Indonesia,100,"SQL, Hadoop, PyTorch",Associate,0,Government,2024-04-30,2024-06-08,2217,5,Autonomous Tech +AI06856,AI Software Engineer,86830,EUR,73806,SE,CT,France,S,France,100,"Statistics, AWS, R, GCP, Azure",Master,6,Automotive,2024-07-14,2024-08-18,1611,5.3,Cognitive Computing +AI06857,Research Scientist,148673,USD,148673,SE,FL,Norway,S,Hungary,100,"Data Visualization, Spark, Python",Bachelor,6,Automotive,2024-07-03,2024-07-19,1209,7.6,Cognitive Computing +AI06858,Data Analyst,128336,USD,128336,EX,FT,Israel,M,Israel,0,"Python, TensorFlow, Mathematics",Associate,18,Gaming,2024-01-08,2024-02-08,1804,5.6,Smart Analytics +AI06859,Data Scientist,281503,USD,281503,EX,CT,United States,M,United States,0,"Deep Learning, GCP, Statistics, Kubernetes, PyTorch",PhD,11,Gaming,2024-11-17,2024-12-02,1099,6.8,Future Systems +AI06860,Robotics Engineer,59139,EUR,50268,EN,CT,Austria,S,Austria,50,"R, MLOps, Azure, NLP, Linux",Associate,1,Finance,2024-10-10,2024-11-25,685,7.9,Algorithmic Solutions +AI06861,Data Engineer,76076,AUD,102703,EN,PT,Australia,L,Australia,0,"TensorFlow, Docker, Kubernetes",Master,1,Energy,2025-01-16,2025-02-11,544,8.6,DataVision Ltd +AI06862,Deep Learning Engineer,116557,USD,116557,SE,FT,South Korea,M,South Korea,50,"Git, SQL, PyTorch",Master,7,Energy,2024-11-26,2025-01-18,1024,9.1,DataVision Ltd +AI06863,Research Scientist,153326,USD,153326,SE,CT,Israel,L,Israel,0,"Data Visualization, Deep Learning, MLOps, Python",Associate,9,Automotive,2024-04-30,2024-06-25,1225,5.5,Cognitive Computing +AI06864,Principal Data Scientist,145710,CHF,131139,SE,FT,Switzerland,S,Finland,100,"Hadoop, GCP, Linux, Kubernetes",Bachelor,7,Consulting,2024-11-06,2024-11-30,1025,6.8,Cloud AI Solutions +AI06865,AI Software Engineer,208806,EUR,177485,EX,FT,Netherlands,L,Poland,100,"Tableau, Scala, Python",Associate,15,Education,2024-09-03,2024-10-09,833,8.3,Digital Transformation LLC +AI06866,Robotics Engineer,59495,USD,59495,EN,FL,Norway,S,Norway,100,"Statistics, GCP, Computer Vision",PhD,1,Consulting,2024-06-27,2024-08-16,2122,8.7,Smart Analytics +AI06867,Research Scientist,161310,AUD,217769,EX,PT,Australia,M,Australia,50,"Deep Learning, Computer Vision, Data Visualization",PhD,12,Technology,2024-12-09,2025-01-05,2010,8.5,Quantum Computing Inc +AI06868,Research Scientist,63732,EUR,54172,EN,FT,Austria,M,China,100,"Spark, Python, Docker, TensorFlow",PhD,1,Manufacturing,2025-03-19,2025-04-08,2143,8.2,DataVision Ltd +AI06869,Data Analyst,144081,USD,144081,SE,PT,Sweden,M,Sweden,0,"Docker, TensorFlow, GCP",Master,6,Telecommunications,2024-10-15,2024-11-12,1553,8.2,Cloud AI Solutions +AI06870,Computer Vision Engineer,81528,USD,81528,MI,FT,South Korea,L,South Korea,50,"Python, Java, Mathematics, Linux",PhD,4,Telecommunications,2024-03-26,2024-04-28,605,6.9,DataVision Ltd +AI06871,Machine Learning Researcher,23844,USD,23844,EN,FL,India,L,India,0,"GCP, AWS, Data Visualization, Statistics, Spark",Bachelor,1,Automotive,2024-08-23,2024-09-25,2315,6.8,Machine Intelligence Group +AI06872,Deep Learning Engineer,46652,USD,46652,MI,CT,China,M,China,100,"Spark, Scala, Git, NLP, Hadoop",PhD,2,Government,2024-06-21,2024-08-28,632,6.8,Quantum Computing Inc +AI06873,Robotics Engineer,63871,USD,63871,MI,CT,Finland,S,Finland,100,"PyTorch, Statistics, Kubernetes",Master,3,Finance,2025-03-13,2025-05-09,2415,7.8,AI Innovations +AI06874,Head of AI,86503,USD,86503,MI,PT,Ireland,M,Ireland,0,"Python, TensorFlow, Computer Vision",Master,2,Transportation,2025-01-16,2025-02-07,1848,6,Machine Intelligence Group +AI06875,Data Engineer,68882,AUD,92991,EN,CT,Australia,M,Australia,100,"Hadoop, Deep Learning, Spark, PyTorch, Statistics",Associate,0,Transportation,2024-08-30,2024-10-11,2401,5.3,Future Systems +AI06876,ML Ops Engineer,120496,EUR,102422,SE,FT,Germany,S,Germany,0,"Data Visualization, Mathematics, R",Master,6,Automotive,2024-12-31,2025-01-26,2097,7,Machine Intelligence Group +AI06877,Data Scientist,67737,EUR,57576,EN,FL,Germany,S,Denmark,50,"Linux, Data Visualization, Docker",Bachelor,0,Consulting,2024-01-31,2024-03-30,1686,7.3,Cloud AI Solutions +AI06878,Head of AI,58637,EUR,49841,EN,FL,Netherlands,S,Thailand,50,"Statistics, Computer Vision, NLP, Git, Kubernetes",Master,1,Technology,2024-06-29,2024-09-04,540,10,Neural Networks Co +AI06879,AI Specialist,130820,EUR,111197,SE,FL,Austria,M,Sweden,0,"Computer Vision, SQL, Statistics, Git",Associate,7,Healthcare,2024-06-24,2024-08-22,913,9.1,Digital Transformation LLC +AI06880,Deep Learning Engineer,101122,USD,101122,MI,CT,Sweden,M,Sweden,0,"Git, Kubernetes, SQL",PhD,3,Automotive,2024-11-20,2025-01-11,1832,7,DeepTech Ventures +AI06881,AI Architect,130892,USD,130892,SE,PT,Finland,L,Finland,0,"Git, R, TensorFlow, Python, PyTorch",PhD,6,Real Estate,2024-07-07,2024-08-29,2367,5.1,Smart Analytics +AI06882,AI Product Manager,26937,USD,26937,EN,CT,India,L,Portugal,0,"R, AWS, Python, Mathematics",Associate,1,Government,2025-04-30,2025-05-25,1341,9.1,Smart Analytics +AI06883,AI Research Scientist,90590,GBP,67943,MI,FT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Azure, Hadoop",Master,3,Real Estate,2024-05-27,2024-08-03,1264,6.8,Quantum Computing Inc +AI06884,AI Consultant,121858,USD,121858,SE,FT,Sweden,S,Sweden,50,"Kubernetes, PyTorch, Statistics, R, Java",Associate,7,Manufacturing,2024-02-09,2024-02-23,1435,6.9,Cognitive Computing +AI06885,Research Scientist,102740,EUR,87329,SE,CT,Netherlands,S,Netherlands,100,"PyTorch, SQL, Linux, Statistics",Bachelor,8,Automotive,2024-05-29,2024-07-23,1550,8.3,DataVision Ltd +AI06886,Data Scientist,250788,USD,250788,EX,FL,Denmark,S,United States,0,"Spark, Tableau, Python, Scala, GCP",Bachelor,11,Consulting,2024-03-25,2024-05-26,626,6.3,DeepTech Ventures +AI06887,Research Scientist,45176,USD,45176,SE,FL,India,S,United Kingdom,0,"Python, Spark, NLP, Data Visualization",PhD,6,Gaming,2024-01-06,2024-01-25,1783,8.5,DeepTech Ventures +AI06888,AI Specialist,107442,USD,107442,SE,FT,South Korea,M,South Korea,0,"Mathematics, Kubernetes, Python, Docker, Data Visualization",Associate,7,Telecommunications,2024-04-22,2024-06-28,1030,5.7,Advanced Robotics +AI06889,Computer Vision Engineer,193572,EUR,164536,EX,FT,Austria,M,Singapore,0,"PyTorch, SQL, GCP",Associate,11,Healthcare,2024-12-13,2025-01-02,1285,6,Future Systems +AI06890,AI Consultant,93956,USD,93956,EX,PT,India,L,India,0,"Azure, PyTorch, TensorFlow, Docker, Git",Master,16,Automotive,2024-03-18,2024-04-07,1868,9.9,DataVision Ltd +AI06891,Autonomous Systems Engineer,77210,EUR,65629,EN,FT,Netherlands,M,Netherlands,0,"Data Visualization, Java, Linux",Associate,1,Technology,2024-08-21,2024-10-04,1539,6.8,Algorithmic Solutions +AI06892,AI Consultant,59058,USD,59058,EX,CT,India,L,Malaysia,50,"NLP, Kubernetes, PyTorch, Git, Tableau",Bachelor,12,Gaming,2024-06-20,2024-08-30,1756,9.9,DeepTech Ventures +AI06893,Machine Learning Researcher,285291,CHF,256762,EX,FT,Switzerland,M,Switzerland,50,"PyTorch, Linux, TensorFlow, Mathematics",Bachelor,12,Technology,2024-03-17,2024-04-25,2134,8.6,Digital Transformation LLC +AI06894,Data Analyst,92251,USD,92251,MI,FT,Sweden,S,Sweden,100,"Python, Tableau, Java, Statistics",PhD,3,Government,2024-09-25,2024-11-26,1721,5.4,Autonomous Tech +AI06895,Machine Learning Engineer,138851,CAD,173564,SE,PT,Canada,L,Canada,50,"Python, Azure, Statistics, Linux",Master,7,Manufacturing,2024-08-14,2024-10-03,2484,5.7,Cloud AI Solutions +AI06896,Deep Learning Engineer,208953,EUR,177610,EX,FT,Netherlands,S,Netherlands,0,"Git, Docker, Scala",PhD,12,Government,2024-02-16,2024-03-28,2051,9.4,Quantum Computing Inc +AI06897,NLP Engineer,187224,CHF,168502,SE,FT,Switzerland,M,Switzerland,100,"Git, Scala, Java",Bachelor,8,Healthcare,2025-02-15,2025-04-14,1158,9.9,Machine Intelligence Group +AI06898,Principal Data Scientist,266395,USD,266395,EX,PT,Sweden,L,Sweden,0,"SQL, Spark, PyTorch, Linux",Bachelor,12,Automotive,2024-03-05,2024-04-05,936,8.4,Smart Analytics +AI06899,AI Specialist,88761,USD,88761,MI,FT,Sweden,S,Brazil,0,"AWS, Linux, Deep Learning, Mathematics",Master,2,Media,2024-01-06,2024-01-28,2134,7.1,Predictive Systems +AI06900,Machine Learning Engineer,81928,USD,81928,EX,CT,China,M,China,50,"Git, Tableau, SQL, Mathematics, Kubernetes",Bachelor,10,Government,2024-08-05,2024-08-25,1453,9.6,Neural Networks Co +AI06901,Machine Learning Researcher,127931,SGD,166310,SE,CT,Singapore,L,Singapore,50,"MLOps, Python, Kubernetes",Master,7,Finance,2024-07-23,2024-10-02,1159,6.3,Predictive Systems +AI06902,Data Analyst,107379,CHF,96641,EN,FT,Switzerland,L,Switzerland,0,"R, Git, Tableau, Azure",Associate,0,Real Estate,2024-09-29,2024-11-23,890,8.2,Smart Analytics +AI06903,Principal Data Scientist,82295,USD,82295,SE,PT,China,L,China,0,"Java, Kubernetes, PyTorch, MLOps",Associate,9,Manufacturing,2024-11-29,2025-02-10,1560,8.6,Neural Networks Co +AI06904,AI Product Manager,91254,EUR,77566,MI,FL,Netherlands,M,Netherlands,100,"Python, Azure, Tableau, SQL",PhD,3,Consulting,2024-02-28,2024-04-28,1098,6.6,Smart Analytics +AI06905,Data Engineer,139532,USD,139532,MI,CT,Denmark,L,Italy,100,"Tableau, TensorFlow, Kubernetes",Associate,2,Telecommunications,2025-04-23,2025-05-19,1554,7.5,Predictive Systems +AI06906,Data Scientist,105160,JPY,11567600,MI,FT,Japan,L,Japan,50,"Scala, AWS, Data Visualization, NLP",Master,2,Energy,2024-03-16,2024-05-11,2229,5.2,Cognitive Computing +AI06907,Research Scientist,123788,JPY,13616680,MI,FT,Japan,L,Japan,100,"Python, SQL, Linux, Deep Learning, Mathematics",Master,3,Real Estate,2025-01-17,2025-02-01,651,8.2,TechCorp Inc +AI06908,Research Scientist,108313,EUR,92066,MI,FL,Netherlands,L,Netherlands,0,"PyTorch, SQL, Kubernetes, R",Bachelor,2,Manufacturing,2025-01-21,2025-02-27,2052,5.7,Predictive Systems +AI06909,Robotics Engineer,105151,USD,105151,SE,CT,Ireland,M,Ireland,50,"Git, TensorFlow, Tableau, SQL, Deep Learning",Bachelor,9,Government,2024-09-09,2024-10-11,1671,6.4,Neural Networks Co +AI06910,Principal Data Scientist,55680,USD,55680,EX,PT,India,M,India,50,"Computer Vision, Hadoop, Azure",Master,12,Manufacturing,2024-08-30,2024-09-17,1329,7.2,DataVision Ltd +AI06911,AI Consultant,141286,JPY,15541460,SE,FL,Japan,S,Japan,100,"Kubernetes, Git, Hadoop",Bachelor,6,Education,2024-06-10,2024-08-07,1364,9.3,TechCorp Inc +AI06912,Machine Learning Engineer,87004,CAD,108755,SE,PT,Canada,S,Norway,0,"Linux, Data Visualization, TensorFlow",Master,8,Retail,2024-09-02,2024-11-02,581,7.4,Advanced Robotics +AI06913,Data Analyst,101540,USD,101540,MI,FL,Sweden,M,India,0,"Linux, Python, R, Java",Master,3,Gaming,2024-12-25,2025-02-06,1662,5.5,Autonomous Tech +AI06914,Research Scientist,176009,USD,176009,SE,PT,Norway,L,Norway,50,"Azure, Java, Scala, Kubernetes",Associate,6,Education,2024-06-02,2024-07-24,2272,6.3,Autonomous Tech +AI06915,Deep Learning Engineer,85561,GBP,64171,EN,PT,United Kingdom,L,Switzerland,50,"R, Kubernetes, Data Visualization",Bachelor,0,Healthcare,2024-12-18,2025-01-04,826,9.2,Smart Analytics +AI06916,Deep Learning Engineer,102426,USD,102426,MI,CT,Ireland,L,Ireland,50,"Computer Vision, Tableau, Linux",Master,3,Automotive,2024-10-13,2024-12-08,1346,8.4,AI Innovations +AI06917,Data Analyst,103962,USD,103962,EN,FT,Norway,L,Norway,0,"SQL, Java, Git, Deep Learning",Associate,1,Retail,2024-05-17,2024-06-20,1235,9.3,Cognitive Computing +AI06918,Head of AI,81801,USD,81801,MI,CT,Israel,M,Israel,50,"MLOps, Kubernetes, SQL, PyTorch",PhD,4,Real Estate,2024-11-03,2025-01-06,1081,6.7,AI Innovations +AI06919,Deep Learning Engineer,141646,USD,141646,SE,FL,Ireland,L,Ireland,0,"Java, SQL, MLOps, Azure",Associate,5,Automotive,2024-08-21,2024-10-11,1664,5.9,Digital Transformation LLC +AI06920,Machine Learning Engineer,197459,USD,197459,EX,CT,Israel,L,Israel,50,"Java, PyTorch, Tableau, Deep Learning",Master,12,Healthcare,2025-03-03,2025-03-23,1470,6.1,Quantum Computing Inc +AI06921,Deep Learning Engineer,86119,EUR,73201,MI,CT,Austria,L,Italy,0,"Azure, Python, Computer Vision, NLP, Tableau",PhD,2,Healthcare,2024-12-06,2024-12-31,665,9.6,Smart Analytics +AI06922,Autonomous Systems Engineer,54196,EUR,46067,EN,CT,Germany,S,Germany,50,"Kubernetes, Statistics, NLP, Azure",Master,1,Real Estate,2025-01-10,2025-02-27,1458,6.9,DataVision Ltd +AI06923,Machine Learning Engineer,83714,USD,83714,EN,FL,Denmark,M,France,100,"Hadoop, TensorFlow, Kubernetes, PyTorch, Git",PhD,1,Finance,2024-09-01,2024-09-25,1593,7,Future Systems +AI06924,Deep Learning Engineer,156483,GBP,117362,SE,CT,United Kingdom,M,United Kingdom,50,"Spark, Hadoop, Linux",Master,7,Technology,2024-10-10,2024-10-30,1052,7.2,TechCorp Inc +AI06925,AI Architect,147145,USD,147145,SE,FT,Norway,S,Norway,0,"Deep Learning, Python, Git, TensorFlow, AWS",PhD,8,Transportation,2024-12-30,2025-02-28,2183,5.1,Smart Analytics +AI06926,NLP Engineer,278709,EUR,236903,EX,FL,Netherlands,L,Brazil,50,"PyTorch, SQL, AWS, R, Java",Associate,18,Transportation,2025-01-24,2025-03-26,2323,6.1,Cloud AI Solutions +AI06927,Computer Vision Engineer,163345,EUR,138843,EX,PT,Austria,S,Austria,100,"Hadoop, Git, Python",Bachelor,14,Automotive,2024-07-23,2024-08-24,2230,9.2,Cloud AI Solutions +AI06928,AI Product Manager,97503,AUD,131629,SE,CT,Australia,S,Australia,50,"Deep Learning, Docker, Java, AWS",Bachelor,6,Manufacturing,2025-01-01,2025-01-20,2440,5.6,Quantum Computing Inc +AI06929,Machine Learning Researcher,173549,CHF,156194,SE,FL,Switzerland,L,Germany,50,"Kubernetes, Scala, Spark",Bachelor,9,Consulting,2025-01-20,2025-03-03,2076,8.6,Advanced Robotics +AI06930,AI Product Manager,229619,GBP,172214,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Hadoop, Java",Associate,18,Government,2025-01-19,2025-02-07,1585,9.7,DeepTech Ventures +AI06931,Computer Vision Engineer,197390,USD,197390,SE,PT,Denmark,M,Denmark,0,"GCP, MLOps, Git, Computer Vision, Java",Master,5,Government,2024-10-20,2024-12-21,1655,9.9,Digital Transformation LLC +AI06932,Computer Vision Engineer,53391,EUR,45382,EN,FL,Austria,S,Romania,50,"Kubernetes, Linux, Tableau, SQL, Statistics",Bachelor,0,Government,2024-11-17,2024-12-18,2141,6.9,Smart Analytics +AI06933,AI Software Engineer,70421,EUR,59858,MI,FL,France,S,Colombia,0,"SQL, Scala, NLP",Associate,3,Energy,2024-12-25,2025-02-04,2200,7.2,Digital Transformation LLC +AI06934,Machine Learning Engineer,82065,USD,82065,EN,PT,Sweden,L,Romania,0,"Docker, Java, Tableau, Hadoop, NLP",Bachelor,1,Automotive,2025-02-21,2025-04-23,1455,9.8,DataVision Ltd +AI06935,NLP Engineer,114605,USD,114605,SE,FL,Israel,L,Israel,0,"GCP, MLOps, R",Master,6,Gaming,2024-06-27,2024-08-24,1238,5.2,DeepTech Ventures +AI06936,AI Architect,209622,CAD,262028,EX,PT,Canada,M,Ireland,0,"Tableau, PyTorch, Kubernetes",Master,17,Manufacturing,2024-06-09,2024-07-10,1344,6.2,Neural Networks Co +AI06937,Computer Vision Engineer,159369,USD,159369,MI,PT,Denmark,L,Denmark,0,"TensorFlow, SQL, R",Bachelor,2,Education,2024-03-18,2024-05-10,1590,7.7,Cognitive Computing +AI06938,Head of AI,287596,USD,287596,EX,FT,Sweden,L,Sweden,0,"Hadoop, Linux, Docker, Data Visualization",Associate,11,Energy,2024-01-01,2024-02-18,714,9.1,Digital Transformation LLC +AI06939,AI Product Manager,145099,EUR,123334,SE,PT,Germany,L,Germany,100,"TensorFlow, Scala, Linux",Associate,5,Government,2024-04-29,2024-06-28,1557,6.3,Predictive Systems +AI06940,ML Ops Engineer,265723,EUR,225865,EX,PT,Germany,L,Germany,0,"Kubernetes, Mathematics, Data Visualization",Master,16,Real Estate,2025-04-30,2025-06-25,645,5.8,Advanced Robotics +AI06941,Data Scientist,146927,EUR,124888,SE,PT,Germany,L,Germany,0,"TensorFlow, Hadoop, Linux, AWS, Computer Vision",Bachelor,5,Healthcare,2024-01-14,2024-03-16,927,7.7,Advanced Robotics +AI06942,AI Research Scientist,55638,USD,55638,MI,CT,China,L,China,50,"Scala, GCP, Data Visualization, Computer Vision",Associate,2,Transportation,2025-01-09,2025-03-18,2069,7.5,Smart Analytics +AI06943,Head of AI,147236,USD,147236,SE,FT,Norway,M,Norway,100,"TensorFlow, Linux, Java",Bachelor,8,Automotive,2024-11-03,2024-12-23,1031,8.6,Advanced Robotics +AI06944,AI Research Scientist,195009,EUR,165758,EX,FL,France,S,New Zealand,100,"Java, Data Visualization, Python",PhD,18,Energy,2025-02-25,2025-05-07,2121,5.3,Advanced Robotics +AI06945,AI Consultant,75991,EUR,64592,EN,FL,France,L,France,50,"Git, SQL, Java",Bachelor,1,Transportation,2024-02-08,2024-03-13,550,8.8,Predictive Systems +AI06946,Research Scientist,188727,USD,188727,EX,CT,Ireland,M,Ireland,0,"Scala, R, PyTorch",Bachelor,12,Telecommunications,2025-01-23,2025-03-28,1066,8.6,Autonomous Tech +AI06947,Machine Learning Researcher,122620,USD,122620,MI,FT,Denmark,L,Denmark,0,"Kubernetes, Spark, Python, Tableau, Linux",Master,3,Consulting,2024-03-03,2024-05-10,1623,8.8,Predictive Systems +AI06948,Computer Vision Engineer,169343,USD,169343,SE,CT,Ireland,L,Hungary,0,"Mathematics, Git, Java",Bachelor,8,Gaming,2024-01-10,2024-03-05,630,7.5,Future Systems +AI06949,AI Architect,76731,CAD,95914,EN,FT,Canada,L,Canada,100,"Azure, Kubernetes, Git",Associate,0,Real Estate,2024-03-12,2024-04-19,1818,8.1,Machine Intelligence Group +AI06950,Machine Learning Researcher,257911,USD,257911,EX,FL,Ireland,L,Mexico,100,"Python, Kubernetes, AWS, Azure, GCP",Bachelor,10,Real Estate,2024-02-02,2024-02-19,1181,9.7,Smart Analytics +AI06951,Head of AI,163774,AUD,221095,EX,FT,Australia,S,Australia,50,"Computer Vision, R, Tableau",Associate,18,Transportation,2024-07-14,2024-08-29,1817,7.5,Cognitive Computing +AI06952,Computer Vision Engineer,31330,USD,31330,EN,FL,China,M,China,0,"R, Spark, Statistics",Master,1,Education,2024-09-25,2024-10-18,2401,10,TechCorp Inc +AI06953,Data Scientist,145202,USD,145202,SE,FT,Israel,L,Poland,0,"Spark, AWS, Deep Learning",Bachelor,6,Gaming,2025-04-21,2025-06-20,728,5,Autonomous Tech +AI06954,Robotics Engineer,89064,SGD,115783,EN,PT,Singapore,L,Singapore,100,"SQL, Python, Computer Vision, Deep Learning",Bachelor,0,Retail,2025-04-13,2025-05-21,1888,7.8,Algorithmic Solutions +AI06955,Data Analyst,132621,USD,132621,SE,PT,Finland,L,Finland,50,"Scala, Docker, Spark, Statistics",Master,7,Education,2025-02-03,2025-03-11,1598,7.3,Quantum Computing Inc +AI06956,NLP Engineer,84808,USD,84808,EN,CT,Sweden,L,Sweden,100,"SQL, NLP, Spark, Hadoop",Bachelor,0,Government,2024-01-04,2024-01-24,2408,8.7,Machine Intelligence Group +AI06957,AI Consultant,59952,USD,59952,EN,FT,Norway,S,Norway,100,"Kubernetes, NLP, Data Visualization",Associate,1,Media,2025-01-31,2025-04-13,1048,5.1,DataVision Ltd +AI06958,Deep Learning Engineer,100845,USD,100845,MI,FT,Finland,M,Germany,0,"TensorFlow, Mathematics, Java, Linux",Master,2,Media,2024-11-25,2024-12-31,1984,9.4,TechCorp Inc +AI06959,Machine Learning Engineer,98597,EUR,83807,MI,CT,Netherlands,M,Japan,100,"GCP, Scala, R",Bachelor,3,Retail,2024-12-24,2025-01-13,1549,8.5,Future Systems +AI06960,Data Engineer,142965,EUR,121520,SE,FT,Germany,M,Nigeria,0,"Kubernetes, Linux, Azure, GCP, Git",PhD,5,Automotive,2024-06-24,2024-08-13,2341,6.4,TechCorp Inc +AI06961,Machine Learning Researcher,84811,GBP,63608,EN,PT,United Kingdom,L,United Kingdom,100,"Tableau, MLOps, NLP, Linux",PhD,1,Retail,2024-08-10,2024-09-11,1114,6.6,Neural Networks Co +AI06962,AI Software Engineer,150732,USD,150732,SE,CT,Denmark,M,Italy,100,"MLOps, Git, GCP, R, Python",Associate,5,Automotive,2025-01-23,2025-02-20,1915,6.6,Cloud AI Solutions +AI06963,AI Research Scientist,146631,AUD,197952,SE,FT,Australia,M,Australia,50,"Scala, Data Visualization, Linux, SQL",Master,8,Gaming,2024-01-23,2024-03-01,1304,5.2,Digital Transformation LLC +AI06964,AI Consultant,87006,CAD,108758,EN,FT,Canada,L,Canada,100,"Docker, Statistics, Computer Vision, Linux, Deep Learning",PhD,1,Education,2024-11-20,2025-01-03,1023,7.8,Cognitive Computing +AI06965,ML Ops Engineer,93917,AUD,126788,SE,CT,Australia,S,France,100,"Git, Python, NLP",Master,5,Manufacturing,2024-06-17,2024-07-07,1248,9.7,Smart Analytics +AI06966,Data Analyst,168686,EUR,143383,EX,FL,Netherlands,S,Netherlands,50,"Statistics, Python, Git, Linux, SQL",Bachelor,12,Real Estate,2025-01-09,2025-02-01,2404,7.4,AI Innovations +AI06967,Research Scientist,128330,GBP,96248,SE,PT,United Kingdom,S,South Africa,50,"Azure, Mathematics, Kubernetes, Deep Learning",Associate,6,Gaming,2025-02-28,2025-05-05,1920,6.8,TechCorp Inc +AI06968,Data Engineer,111839,SGD,145391,SE,PT,Singapore,S,Singapore,50,"Scala, MLOps, Docker, Hadoop, Statistics",PhD,9,Retail,2024-03-02,2024-03-21,2328,7.3,Predictive Systems +AI06969,AI Software Engineer,187884,USD,187884,EX,PT,South Korea,L,Malaysia,50,"TensorFlow, SQL, Mathematics",Master,18,Consulting,2025-01-31,2025-03-09,675,9,AI Innovations +AI06970,AI Specialist,50117,USD,50117,MI,FT,China,M,China,0,"Python, AWS, Kubernetes, MLOps",Bachelor,4,Consulting,2024-05-19,2024-07-15,1362,6.3,Advanced Robotics +AI06971,Data Scientist,355672,CHF,320105,EX,CT,Switzerland,L,Philippines,0,"Tableau, SQL, Kubernetes, PyTorch",Master,16,Automotive,2025-04-25,2025-05-27,776,8.2,Machine Intelligence Group +AI06972,Deep Learning Engineer,114352,AUD,154375,MI,PT,Australia,L,Australia,0,"PyTorch, Scala, Azure, AWS, TensorFlow",Master,4,Gaming,2025-01-23,2025-03-12,2361,9.8,Quantum Computing Inc +AI06973,Data Engineer,167395,USD,167395,EX,CT,United States,M,United States,0,"Spark, Git, Computer Vision, Data Visualization",Bachelor,17,Retail,2024-02-18,2024-04-03,683,8.9,Cloud AI Solutions +AI06974,Autonomous Systems Engineer,172621,JPY,18988310,SE,PT,Japan,L,Japan,100,"Python, SQL, R",Associate,6,Energy,2025-04-30,2025-06-08,813,9.7,Algorithmic Solutions +AI06975,AI Architect,64356,USD,64356,MI,CT,Finland,S,Finland,100,"Deep Learning, MLOps, PyTorch, Tableau",Master,2,Finance,2024-11-09,2025-01-14,1866,6.1,Machine Intelligence Group +AI06976,Data Scientist,54970,USD,54970,EX,PT,India,M,Belgium,50,"SQL, TensorFlow, Linux, Tableau, Java",PhD,13,Transportation,2024-09-02,2024-10-04,821,7.6,Autonomous Tech +AI06977,Deep Learning Engineer,101375,CHF,91238,EN,CT,Switzerland,L,Switzerland,100,"R, PyTorch, Mathematics, Hadoop, Azure",Associate,1,Government,2025-02-09,2025-02-28,1818,7.6,Algorithmic Solutions +AI06978,Computer Vision Engineer,162080,USD,162080,EX,CT,Finland,S,Finland,50,"TensorFlow, Docker, Mathematics, Linux, AWS",PhD,11,Telecommunications,2025-01-01,2025-03-02,688,9.3,DataVision Ltd +AI06979,AI Product Manager,81146,USD,81146,SE,FT,South Korea,S,South Korea,100,"Tableau, Git, Docker, PyTorch, Data Visualization",Associate,5,Manufacturing,2024-05-31,2024-06-29,540,8.6,Quantum Computing Inc +AI06980,Autonomous Systems Engineer,144815,USD,144815,SE,PT,United States,S,United States,50,"R, NLP, Java",PhD,8,Transportation,2025-02-02,2025-02-23,1685,7.9,Future Systems +AI06981,ML Ops Engineer,145112,USD,145112,SE,FT,Ireland,M,Ireland,100,"Kubernetes, Git, Deep Learning, PyTorch, Docker",PhD,9,Transportation,2024-12-23,2025-02-09,1411,5.7,Digital Transformation LLC +AI06982,Principal Data Scientist,66759,USD,66759,EX,FL,China,S,China,100,"TensorFlow, Git, Azure, Spark",PhD,12,Finance,2024-11-29,2025-01-31,1327,9.9,Advanced Robotics +AI06983,Machine Learning Engineer,163174,EUR,138698,EX,PT,Germany,S,United Kingdom,100,"Linux, PyTorch, Git, Mathematics, Deep Learning",PhD,11,Energy,2024-05-04,2024-05-22,2045,5.1,AI Innovations +AI06984,Deep Learning Engineer,112919,CHF,101627,EN,CT,Switzerland,L,Switzerland,100,"R, SQL, Azure",Master,1,Transportation,2025-03-31,2025-06-10,625,6.7,Predictive Systems +AI06985,Principal Data Scientist,113118,SGD,147053,MI,PT,Singapore,M,Japan,50,"Git, Data Visualization, Scala, Azure, Kubernetes",Associate,4,Manufacturing,2024-02-20,2024-03-27,1777,8.6,Machine Intelligence Group +AI06986,Robotics Engineer,64270,USD,64270,EN,FL,Sweden,L,Sweden,0,"NLP, Git, Java",Associate,0,Healthcare,2024-07-19,2024-08-27,598,9.2,AI Innovations +AI06987,Deep Learning Engineer,167528,USD,167528,SE,CT,Denmark,M,Denmark,50,"Scala, Azure, Mathematics, PyTorch, Statistics",Master,5,Retail,2024-09-21,2024-10-11,1659,5.8,Smart Analytics +AI06988,ML Ops Engineer,82676,CAD,103345,MI,FL,Canada,S,Sweden,100,"Data Visualization, Spark, R, SQL",Master,4,Technology,2024-02-23,2024-03-21,1707,6.4,Cloud AI Solutions +AI06989,Computer Vision Engineer,148614,EUR,126322,SE,CT,Austria,L,Austria,50,"PyTorch, Kubernetes, Git",Associate,9,Gaming,2024-04-05,2024-05-24,1048,7.8,Autonomous Tech +AI06990,Machine Learning Engineer,75332,USD,75332,MI,CT,Finland,M,Australia,100,"TensorFlow, SQL, R, Deep Learning, NLP",Associate,3,Energy,2024-12-09,2025-01-18,2177,5.7,Quantum Computing Inc +AI06991,Head of AI,170124,CHF,153112,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, MLOps, Kubernetes, PyTorch, NLP",PhD,4,Consulting,2025-01-16,2025-03-25,2424,6.5,DataVision Ltd +AI06992,Principal Data Scientist,103653,USD,103653,MI,FT,Israel,M,Israel,0,"R, Git, Statistics",PhD,2,Automotive,2024-08-22,2024-09-26,1801,6.7,Future Systems +AI06993,AI Architect,30142,USD,30142,MI,FL,India,L,India,0,"TensorFlow, Git, SQL, Hadoop",Associate,4,Telecommunications,2025-01-27,2025-03-03,1476,7.8,Digital Transformation LLC +AI06994,Machine Learning Researcher,54940,USD,54940,EN,CT,South Korea,M,Brazil,100,"Git, R, Computer Vision, Java",Master,1,Government,2024-09-06,2024-09-30,2122,9.9,Machine Intelligence Group +AI06995,Principal Data Scientist,84125,USD,84125,MI,FL,United States,S,United States,0,"Hadoop, Linux, Data Visualization, Tableau",Master,3,Media,2024-05-24,2024-06-23,1222,7.4,Cloud AI Solutions +AI06996,NLP Engineer,221441,EUR,188225,EX,FT,France,L,Nigeria,100,"Git, SQL, Spark, Tableau, Kubernetes",Bachelor,19,Media,2024-11-02,2025-01-11,1718,5.9,Future Systems +AI06997,AI Software Engineer,64993,EUR,55244,EN,FT,Netherlands,S,Hungary,0,"Git, Java, Kubernetes",Bachelor,0,Media,2024-01-23,2024-03-24,2180,5.8,Future Systems +AI06998,Research Scientist,114387,CAD,142984,MI,FL,Canada,L,Canada,100,"Java, Scala, Tableau, NLP",Associate,2,Retail,2024-09-04,2024-10-21,2379,5.8,Quantum Computing Inc +AI06999,Data Analyst,87162,SGD,113311,EN,PT,Singapore,L,Luxembourg,50,"GCP, PyTorch, Python",Master,1,Gaming,2024-08-04,2024-09-10,2232,8.4,Autonomous Tech +AI07000,Head of AI,117970,USD,117970,MI,FL,United States,L,Philippines,100,"Mathematics, Java, Python",Bachelor,2,Finance,2024-03-27,2024-04-27,2075,5.6,AI Innovations +AI07001,AI Research Scientist,111336,USD,111336,SE,CT,Ireland,S,Ireland,0,"Tableau, TensorFlow, Scala, Git, Azure",PhD,7,Telecommunications,2024-03-14,2024-05-02,1486,5.5,Algorithmic Solutions +AI07002,Machine Learning Researcher,86134,GBP,64601,MI,FL,United Kingdom,S,United Kingdom,0,"TensorFlow, AWS, Azure",Associate,4,Energy,2024-10-31,2024-11-26,2104,6.7,Neural Networks Co +AI07003,Data Engineer,159132,USD,159132,EX,CT,Finland,M,Finland,50,"R, MLOps, SQL",PhD,18,Manufacturing,2024-08-31,2024-10-04,1832,9,DataVision Ltd +AI07004,Autonomous Systems Engineer,88313,USD,88313,EN,CT,United States,M,United States,0,"PyTorch, TensorFlow, Azure, AWS",Associate,1,Telecommunications,2024-12-10,2025-02-12,2142,7.1,DeepTech Ventures +AI07005,AI Product Manager,147619,USD,147619,EX,FL,United States,S,United States,0,"Java, SQL, Hadoop, Git, GCP",Associate,17,Education,2024-06-29,2024-07-15,1756,5.6,Quantum Computing Inc +AI07006,Machine Learning Engineer,41968,USD,41968,MI,CT,India,L,India,50,"Data Visualization, Kubernetes, Azure",PhD,4,Media,2025-03-13,2025-05-10,2229,9.9,Neural Networks Co +AI07007,Data Scientist,68997,USD,68997,EN,CT,South Korea,L,New Zealand,50,"TensorFlow, Python, Tableau, GCP",Bachelor,1,Manufacturing,2024-08-04,2024-10-07,2237,6.6,Advanced Robotics +AI07008,Data Scientist,81660,USD,81660,EN,FL,Israel,L,Israel,50,"Git, Deep Learning, SQL, Linux, Kubernetes",Master,0,Government,2024-03-15,2024-03-30,2337,5.7,Future Systems +AI07009,Autonomous Systems Engineer,151107,GBP,113330,SE,CT,United Kingdom,M,United Kingdom,100,"Deep Learning, AWS, MLOps",Master,7,Government,2024-07-07,2024-09-18,1900,5.9,Algorithmic Solutions +AI07010,Deep Learning Engineer,54435,USD,54435,EN,FT,Sweden,M,Egypt,50,"MLOps, SQL, PyTorch, GCP",PhD,0,Healthcare,2025-01-25,2025-03-20,1222,8.2,Cloud AI Solutions +AI07011,NLP Engineer,295862,EUR,251483,EX,FT,Netherlands,L,Netherlands,0,"Hadoop, GCP, Tableau, Docker, Scala",PhD,16,Technology,2024-04-07,2024-05-18,1139,8,TechCorp Inc +AI07012,AI Product Manager,110402,EUR,93842,SE,FL,France,M,France,100,"R, SQL, Mathematics",Master,9,Energy,2024-06-24,2024-07-29,2427,7.1,Algorithmic Solutions +AI07013,Data Scientist,97747,CAD,122184,MI,PT,Canada,M,Finland,0,"TensorFlow, Mathematics, Python",PhD,4,Manufacturing,2024-07-21,2024-09-12,1776,9.7,Cognitive Computing +AI07014,AI Consultant,57591,EUR,48952,EN,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Spark, Deep Learning, Statistics",Associate,1,Retail,2024-10-31,2025-01-06,1101,9.9,Machine Intelligence Group +AI07015,Autonomous Systems Engineer,202829,USD,202829,EX,FT,Finland,S,Finland,100,"Kubernetes, Python, Linux, GCP",Associate,11,Finance,2024-02-07,2024-03-12,840,6.5,Machine Intelligence Group +AI07016,Autonomous Systems Engineer,49667,CAD,62084,EN,FT,Canada,M,Canada,0,"Data Visualization, Git, R, AWS",Bachelor,0,Education,2024-10-04,2024-11-11,1038,6.7,DataVision Ltd +AI07017,Principal Data Scientist,107663,CHF,96897,EN,PT,Switzerland,L,Switzerland,50,"PyTorch, SQL, NLP",Bachelor,0,Retail,2025-02-26,2025-04-14,1016,6.2,Neural Networks Co +AI07018,Data Engineer,114200,USD,114200,SE,CT,Israel,S,Singapore,100,"Hadoop, Computer Vision, Java, R, Statistics",Associate,6,Retail,2024-05-17,2024-06-11,2297,6.9,Cloud AI Solutions +AI07019,NLP Engineer,195219,GBP,146414,EX,CT,United Kingdom,L,United Kingdom,50,"PyTorch, Hadoop, R, Linux",Associate,11,Consulting,2024-08-13,2024-08-29,1251,9.3,Quantum Computing Inc +AI07020,Principal Data Scientist,174084,JPY,19149240,EX,CT,Japan,M,Japan,100,"Git, NLP, Tableau, Hadoop",Master,10,Transportation,2024-07-07,2024-08-04,877,5.5,Predictive Systems +AI07021,Computer Vision Engineer,86465,EUR,73495,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Hadoop, Scala",PhD,1,Energy,2025-01-19,2025-03-16,1607,9.6,Smart Analytics +AI07022,Head of AI,112857,USD,112857,MI,FL,United States,M,United States,50,"Kubernetes, TensorFlow, NLP, MLOps, Git",Master,3,Telecommunications,2024-08-15,2024-10-06,1126,8.7,TechCorp Inc +AI07023,Robotics Engineer,122484,EUR,104111,MI,CT,Netherlands,L,Indonesia,50,"Git, Mathematics, Python, Data Visualization",Associate,2,Transportation,2024-08-19,2024-10-27,814,5.7,Machine Intelligence Group +AI07024,NLP Engineer,165700,USD,165700,SE,CT,United States,M,United States,0,"Git, Tableau, R, SQL, Scala",Associate,7,Gaming,2024-12-28,2025-02-21,656,7.1,Predictive Systems +AI07025,Principal Data Scientist,168066,USD,168066,SE,PT,Denmark,S,Denmark,50,"Spark, MLOps, Python, Tableau",Master,6,Technology,2024-10-29,2024-12-28,1679,7.2,Autonomous Tech +AI07026,AI Software Engineer,76293,SGD,99181,EN,PT,Singapore,S,Singapore,0,"MLOps, Azure, Docker, AWS, NLP",Associate,1,Manufacturing,2024-03-07,2024-03-28,567,7.6,TechCorp Inc +AI07027,Principal Data Scientist,52755,AUD,71219,EN,FL,Australia,S,Nigeria,50,"PyTorch, Docker, Mathematics",Master,1,Telecommunications,2024-11-14,2025-01-10,2140,7.9,DataVision Ltd +AI07028,NLP Engineer,194324,SGD,252621,EX,CT,Singapore,S,Singapore,100,"Java, Python, Statistics",Master,12,Finance,2024-12-08,2025-01-19,1413,5.9,Machine Intelligence Group +AI07029,Deep Learning Engineer,118307,CAD,147884,SE,FT,Canada,M,Canada,100,"TensorFlow, Java, Git",Bachelor,9,Manufacturing,2024-04-03,2024-06-09,977,7.9,Cognitive Computing +AI07030,ML Ops Engineer,96881,AUD,130789,MI,PT,Australia,M,Egypt,0,"Mathematics, Kubernetes, R",Master,4,Consulting,2025-04-08,2025-06-05,628,8.5,Smart Analytics +AI07031,Autonomous Systems Engineer,57804,USD,57804,SE,FT,China,M,China,50,"Git, Python, Statistics, Azure",Bachelor,5,Government,2024-03-12,2024-04-09,1288,6.5,Cloud AI Solutions +AI07032,Autonomous Systems Engineer,51971,USD,51971,EN,PT,Ireland,S,Ireland,100,"Azure, Kubernetes, SQL, PyTorch",Master,0,Government,2025-04-28,2025-06-03,1884,5.3,Predictive Systems +AI07033,Machine Learning Researcher,175177,SGD,227730,SE,PT,Singapore,L,Singapore,50,"MLOps, Mathematics, SQL, Computer Vision, Kubernetes",Bachelor,8,Media,2024-04-08,2024-05-22,1954,7.7,Quantum Computing Inc +AI07034,Deep Learning Engineer,119721,USD,119721,SE,CT,Norway,S,Russia,0,"TensorFlow, Python, Azure, Kubernetes",Master,7,Media,2024-04-28,2024-06-30,812,8.4,Autonomous Tech +AI07035,AI Product Manager,227954,USD,227954,EX,FT,Israel,L,Israel,0,"Java, R, GCP",Associate,17,Education,2024-04-20,2024-06-22,859,8.5,Machine Intelligence Group +AI07036,Autonomous Systems Engineer,78211,USD,78211,EN,PT,United States,L,United States,0,"TensorFlow, MLOps, Hadoop",PhD,1,Transportation,2025-02-01,2025-03-05,1038,8.4,Cloud AI Solutions +AI07037,AI Research Scientist,175370,EUR,149065,SE,FL,Netherlands,L,Netherlands,0,"Statistics, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-03-13,2024-05-23,1321,8.8,Digital Transformation LLC +AI07038,AI Product Manager,74020,CAD,92525,MI,PT,Canada,S,Canada,50,"PyTorch, Spark, SQL",Bachelor,2,Media,2024-06-29,2024-08-27,932,5.7,Autonomous Tech +AI07039,AI Consultant,66966,GBP,50225,EN,CT,United Kingdom,L,France,0,"SQL, Deep Learning, PyTorch, Java",PhD,0,Education,2024-05-20,2024-07-14,1481,7.2,Advanced Robotics +AI07040,NLP Engineer,73557,EUR,62523,EN,FT,Germany,M,Germany,50,"R, Data Visualization, Linux",Associate,0,Automotive,2024-04-08,2024-05-06,2105,7.3,Future Systems +AI07041,AI Architect,73095,SGD,95024,EN,PT,Singapore,M,Egypt,50,"MLOps, Git, R",Bachelor,1,Healthcare,2024-11-22,2025-01-17,2409,8.5,Advanced Robotics +AI07042,Research Scientist,57811,USD,57811,EN,FL,South Korea,M,South Korea,100,"Python, Linux, Data Visualization, Tableau, R",Master,1,Healthcare,2025-01-01,2025-02-07,1723,7.7,AI Innovations +AI07043,Machine Learning Researcher,235424,EUR,200110,EX,FL,Netherlands,M,Netherlands,100,"Java, Python, Tableau",Master,19,Education,2025-01-26,2025-03-26,1778,9.9,Algorithmic Solutions +AI07044,Robotics Engineer,140023,AUD,189031,SE,FT,Australia,L,Australia,50,"Java, Git, Mathematics",PhD,5,Consulting,2025-04-11,2025-05-25,1371,5.5,AI Innovations +AI07045,Data Engineer,142826,USD,142826,SE,CT,Norway,M,Norway,50,"Deep Learning, Python, TensorFlow, Computer Vision",PhD,9,Energy,2024-02-15,2024-03-20,1317,7.4,Machine Intelligence Group +AI07046,Autonomous Systems Engineer,89624,USD,89624,MI,FL,South Korea,M,Netherlands,0,"Scala, Python, Azure, NLP",Bachelor,3,Transportation,2025-01-13,2025-03-19,1805,5.6,TechCorp Inc +AI07047,Computer Vision Engineer,80501,USD,80501,EN,PT,Denmark,M,Portugal,50,"Deep Learning, Data Visualization, R",Bachelor,0,Finance,2025-03-01,2025-05-01,1126,5.3,Machine Intelligence Group +AI07048,Data Engineer,95043,USD,95043,EN,FT,United States,L,United States,100,"SQL, AWS, Deep Learning, Linux",Associate,0,Finance,2024-04-25,2024-06-03,1627,6.6,Future Systems +AI07049,Deep Learning Engineer,134255,SGD,174532,MI,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning",PhD,2,Automotive,2024-06-30,2024-09-07,913,6.3,Predictive Systems +AI07050,Machine Learning Researcher,108386,CHF,97547,EN,FT,Switzerland,M,Switzerland,100,"Statistics, Tableau, Java, SQL, Python",PhD,0,Transportation,2024-10-25,2024-11-18,1501,5.8,Cloud AI Solutions +AI07051,Robotics Engineer,205581,USD,205581,EX,FL,Israel,M,Israel,50,"Spark, SQL, Python, Statistics",PhD,13,Transportation,2024-12-31,2025-02-20,2163,5.2,Cloud AI Solutions +AI07052,Deep Learning Engineer,115712,EUR,98355,MI,PT,France,L,France,100,"AWS, TensorFlow, Mathematics, SQL",PhD,2,Energy,2024-09-15,2024-10-19,1798,8.3,Predictive Systems +AI07053,AI Software Engineer,41871,USD,41871,MI,FT,China,S,China,0,"Scala, Python, Java, Hadoop",Bachelor,4,Real Estate,2025-03-21,2025-04-04,2356,6.7,DataVision Ltd +AI07054,ML Ops Engineer,89638,CAD,112048,SE,FL,Canada,S,Canada,0,"R, Java, GCP, Spark, Mathematics",Associate,5,Technology,2024-12-15,2025-02-16,2116,8.6,Algorithmic Solutions +AI07055,Machine Learning Engineer,62796,USD,62796,EN,FT,South Korea,L,South Korea,100,"SQL, Tableau, PyTorch",Associate,0,Transportation,2024-01-31,2024-02-28,539,6.6,Algorithmic Solutions +AI07056,AI Product Manager,174278,JPY,19170580,EX,PT,Japan,L,Japan,0,"Python, MLOps, TensorFlow, Git",PhD,13,Media,2024-08-08,2024-10-16,1840,8.2,Neural Networks Co +AI07057,AI Product Manager,236382,JPY,26002020,EX,PT,Japan,M,Argentina,50,"Scala, Tableau, Python, Computer Vision, Deep Learning",PhD,15,Technology,2024-04-06,2024-04-24,821,8.4,Future Systems +AI07058,Computer Vision Engineer,119050,USD,119050,EX,FL,Finland,S,Finland,50,"Spark, Statistics, Computer Vision, Git",Bachelor,15,Technology,2024-09-24,2024-11-06,850,7.1,TechCorp Inc +AI07059,Autonomous Systems Engineer,139306,SGD,181098,SE,PT,Singapore,L,Singapore,50,"Spark, SQL, PyTorch",Bachelor,8,Real Estate,2025-01-10,2025-03-21,723,8,DeepTech Ventures +AI07060,AI Research Scientist,146203,USD,146203,SE,CT,Denmark,M,Denmark,0,"Linux, GCP, Python, Data Visualization, Mathematics",Master,6,Energy,2024-05-06,2024-07-05,1191,8.2,Predictive Systems +AI07061,Research Scientist,91867,EUR,78087,MI,PT,Austria,M,Ireland,100,"Scala, MLOps, Docker",Associate,3,Retail,2024-08-26,2024-10-10,623,7.2,Cloud AI Solutions +AI07062,NLP Engineer,139325,USD,139325,SE,PT,Norway,M,Norway,100,"NLP, PyTorch, TensorFlow",Master,5,Automotive,2024-08-29,2024-11-03,1668,9.3,Predictive Systems +AI07063,Robotics Engineer,368470,USD,368470,EX,PT,Norway,L,Australia,0,"Docker, Deep Learning, SQL",Associate,11,Technology,2024-08-31,2024-10-09,1117,8.5,Digital Transformation LLC +AI07064,AI Research Scientist,79264,USD,79264,MI,FL,South Korea,M,Germany,50,"Java, Python, Kubernetes, Mathematics",Master,2,Technology,2025-04-16,2025-06-02,1050,6,Future Systems +AI07065,Robotics Engineer,213820,USD,213820,EX,CT,Finland,L,Sweden,0,"Kubernetes, Linux, Mathematics, Java",Associate,17,Consulting,2024-06-11,2024-07-05,1605,8.6,Future Systems +AI07066,AI Consultant,91365,AUD,123343,MI,CT,Australia,S,Ireland,100,"Git, Scala, GCP, Computer Vision",Bachelor,2,Consulting,2024-10-05,2024-11-11,634,7.6,Predictive Systems +AI07067,Machine Learning Researcher,135173,EUR,114897,SE,PT,Germany,L,Germany,100,"PyTorch, Linux, Java",Associate,6,Finance,2025-01-21,2025-03-27,1073,6,Smart Analytics +AI07068,Deep Learning Engineer,68488,AUD,92459,EN,FT,Australia,S,Australia,50,"R, Docker, Scala, Statistics, MLOps",Bachelor,0,Government,2024-07-16,2024-09-04,1631,6.4,Cloud AI Solutions +AI07069,AI Software Engineer,117333,EUR,99733,SE,CT,Austria,S,Austria,100,"Scala, TensorFlow, Python, PyTorch",Associate,9,Transportation,2024-09-15,2024-10-05,1294,5.1,Digital Transformation LLC +AI07070,Deep Learning Engineer,99292,USD,99292,MI,PT,Finland,L,Finland,0,"Kubernetes, Scala, Statistics",Associate,3,Healthcare,2024-07-13,2024-09-08,939,8.4,Cloud AI Solutions +AI07071,NLP Engineer,215599,USD,215599,SE,CT,Denmark,L,Denmark,100,"MLOps, Git, PyTorch, Java, Scala",Associate,8,Transportation,2024-09-25,2024-11-01,1492,7,TechCorp Inc +AI07072,ML Ops Engineer,159635,USD,159635,EX,FL,South Korea,M,South Korea,0,"Kubernetes, PyTorch, Docker",PhD,10,Real Estate,2024-05-27,2024-07-16,1395,9,Autonomous Tech +AI07073,AI Product Manager,108321,AUD,146233,MI,FL,Australia,L,Brazil,0,"Computer Vision, Hadoop, Git, Kubernetes",Master,2,Real Estate,2024-05-07,2024-06-10,1705,5.7,Smart Analytics +AI07074,Computer Vision Engineer,76476,CAD,95595,MI,FT,Canada,M,Canada,100,"SQL, Python, Docker, AWS",Associate,2,Consulting,2025-01-28,2025-03-03,543,8.9,AI Innovations +AI07075,Head of AI,83952,AUD,113335,MI,PT,Australia,M,Australia,50,"Kubernetes, Azure, AWS, Deep Learning, Java",Associate,2,Real Estate,2025-03-03,2025-04-06,2076,6.5,Advanced Robotics +AI07076,AI Research Scientist,235700,USD,235700,EX,FT,Israel,L,Ghana,0,"Kubernetes, Python, NLP",Associate,12,Energy,2024-04-21,2024-06-12,1601,8.1,Predictive Systems +AI07077,AI Specialist,131627,USD,131627,SE,FT,United States,M,United States,100,"Hadoop, Kubernetes, Statistics",PhD,6,Real Estate,2024-07-22,2024-08-30,758,7.7,Smart Analytics +AI07078,AI Architect,178535,EUR,151755,EX,CT,Austria,M,Japan,0,"MLOps, Git, Java, Kubernetes, Computer Vision",PhD,12,Automotive,2024-11-13,2025-01-13,1594,5.8,Advanced Robotics +AI07079,AI Architect,209551,USD,209551,EX,PT,Denmark,S,Denmark,0,"Hadoop, Python, Statistics, Linux, Data Visualization",Master,11,Real Estate,2024-03-14,2024-05-04,772,9.6,Machine Intelligence Group +AI07080,AI Software Engineer,84533,EUR,71853,MI,CT,Austria,L,Austria,100,"Python, GCP, TensorFlow",Associate,4,Healthcare,2024-09-07,2024-10-12,860,6.1,Neural Networks Co +AI07081,AI Architect,25457,USD,25457,EN,FL,China,M,Chile,0,"NLP, Linux, SQL",Bachelor,0,Finance,2024-11-01,2024-12-12,1856,5.6,DataVision Ltd +AI07082,Data Analyst,91380,USD,91380,EN,PT,Denmark,M,Denmark,0,"Scala, Tableau, Java, SQL",Associate,0,Media,2024-10-13,2024-11-04,925,7.6,Predictive Systems +AI07083,NLP Engineer,60940,GBP,45705,EN,FT,United Kingdom,S,United Kingdom,50,"Scala, GCP, Tableau, Mathematics",Bachelor,1,Real Estate,2024-11-10,2025-01-20,867,7.8,Smart Analytics +AI07084,Machine Learning Researcher,86902,USD,86902,MI,FL,United States,M,India,50,"R, GCP, Azure, SQL",Associate,3,Consulting,2024-05-04,2024-05-31,538,5.8,Smart Analytics +AI07085,AI Product Manager,119818,USD,119818,MI,PT,United States,M,China,50,"NLP, Data Visualization, Java",Master,3,Energy,2024-11-25,2024-12-30,1964,6.1,Quantum Computing Inc +AI07086,Autonomous Systems Engineer,35047,USD,35047,MI,FT,India,L,India,50,"Python, SQL, TensorFlow, NLP, Deep Learning",Bachelor,3,Real Estate,2024-05-15,2024-06-24,1946,7.6,DataVision Ltd +AI07087,Machine Learning Researcher,175805,GBP,131854,EX,CT,United Kingdom,M,United Kingdom,100,"Statistics, Hadoop, NLP",Bachelor,10,Healthcare,2024-07-02,2024-08-24,1033,7.7,DeepTech Ventures +AI07088,AI Research Scientist,45668,EUR,38818,EN,PT,France,S,France,100,"Azure, MLOps, Scala",Associate,1,Real Estate,2024-05-28,2024-06-20,1406,6.6,Predictive Systems +AI07089,Research Scientist,149817,CAD,187271,EX,PT,Canada,S,Canada,50,"R, Hadoop, MLOps, Java",Bachelor,18,Finance,2024-05-02,2024-06-25,957,6.3,Machine Intelligence Group +AI07090,ML Ops Engineer,82947,GBP,62210,EN,FT,United Kingdom,M,Hungary,50,"Python, Java, Data Visualization, Statistics, Tableau",PhD,0,Education,2024-08-15,2024-09-15,2320,8.3,Algorithmic Solutions +AI07091,AI Research Scientist,85406,CHF,76865,EN,CT,Switzerland,S,Latvia,50,"SQL, AWS, NLP, Scala",Bachelor,1,Healthcare,2024-10-15,2024-11-06,1504,5.9,TechCorp Inc +AI07092,Autonomous Systems Engineer,87146,USD,87146,MI,FL,Ireland,M,Ireland,0,"MLOps, Scala, R, Azure, Computer Vision",PhD,3,Healthcare,2024-06-08,2024-08-16,2101,6.4,Predictive Systems +AI07093,NLP Engineer,69088,AUD,93269,EN,PT,Australia,S,Australia,0,"SQL, Mathematics, Spark, Kubernetes, Git",Associate,0,Gaming,2024-04-07,2024-05-01,1029,7.1,Neural Networks Co +AI07094,AI Consultant,37599,USD,37599,MI,FL,China,S,Romania,100,"Python, TensorFlow, Git, AWS",PhD,3,Government,2024-06-10,2024-08-03,1308,7.8,Cognitive Computing +AI07095,Computer Vision Engineer,87778,USD,87778,EX,FL,China,S,China,0,"NLP, Data Visualization, Tableau, Linux, PyTorch",Bachelor,12,Government,2024-07-03,2024-09-07,578,7.8,Smart Analytics +AI07096,AI Research Scientist,141646,USD,141646,SE,FL,Israel,L,Israel,0,"Azure, Java, R, Data Visualization, Computer Vision",Master,8,Telecommunications,2024-10-11,2024-11-10,784,8,DeepTech Ventures +AI07097,Head of AI,64214,USD,64214,EN,FL,Finland,S,Poland,0,"Docker, Azure, Deep Learning",Bachelor,1,Consulting,2025-02-10,2025-04-06,2117,5.9,DataVision Ltd +AI07098,Data Engineer,167315,GBP,125486,EX,PT,United Kingdom,M,United Kingdom,50,"Git, Data Visualization, Kubernetes, Mathematics, PyTorch",Master,17,Finance,2024-08-14,2024-10-19,1552,5.7,Digital Transformation LLC +AI07099,AI Consultant,48070,USD,48070,SE,PT,India,L,Poland,50,"SQL, AWS, Data Visualization, Docker, PyTorch",PhD,5,Consulting,2024-10-13,2024-10-27,1908,5.6,Quantum Computing Inc +AI07100,Autonomous Systems Engineer,274846,USD,274846,EX,PT,Norway,M,Norway,0,"Scala, Kubernetes, Data Visualization",Master,11,Media,2024-12-05,2025-01-30,855,9.1,Predictive Systems +AI07101,Deep Learning Engineer,116699,SGD,151709,MI,FT,Singapore,M,Brazil,100,"Kubernetes, Python, Spark, Data Visualization, Deep Learning",Bachelor,2,Automotive,2024-02-10,2024-04-14,1991,8.2,Cloud AI Solutions +AI07102,AI Architect,192135,GBP,144101,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Linux, Docker, Spark",Master,15,Government,2024-04-27,2024-05-20,1558,8.3,Neural Networks Co +AI07103,Computer Vision Engineer,129329,EUR,109930,SE,PT,Netherlands,L,Ireland,100,"SQL, Scala, Computer Vision",Bachelor,5,Healthcare,2024-09-21,2024-10-17,1464,7,Cognitive Computing +AI07104,AI Architect,119619,USD,119619,SE,FL,Norway,S,New Zealand,100,"Docker, Kubernetes, Tableau, Mathematics",PhD,9,Automotive,2024-01-30,2024-03-17,1182,5.4,Smart Analytics +AI07105,Machine Learning Researcher,164906,CHF,148415,SE,FL,Switzerland,M,Switzerland,50,"R, SQL, TensorFlow, Tableau, NLP",PhD,7,Retail,2025-04-22,2025-06-10,1394,8.5,Cloud AI Solutions +AI07106,Data Analyst,93246,EUR,79259,SE,PT,Germany,S,Australia,50,"Python, MLOps, Deep Learning, Computer Vision, GCP",Bachelor,7,Education,2024-12-17,2025-01-07,2269,9.7,Digital Transformation LLC +AI07107,Data Engineer,84575,USD,84575,EX,FL,India,L,Argentina,50,"Python, Computer Vision, Java",Associate,13,Transportation,2025-03-25,2025-05-15,1161,5.1,Advanced Robotics +AI07108,AI Specialist,120060,CAD,150075,SE,FL,Canada,M,Canada,0,"Data Visualization, Hadoop, Python, Git",Bachelor,9,Real Estate,2025-04-25,2025-07-07,907,6,Cognitive Computing +AI07109,Deep Learning Engineer,122916,USD,122916,SE,FT,Israel,S,South Korea,100,"Data Visualization, GCP, Linux, PyTorch, Git",Bachelor,5,Manufacturing,2025-02-16,2025-04-20,1429,6.1,Digital Transformation LLC +AI07110,Autonomous Systems Engineer,86361,SGD,112269,MI,CT,Singapore,M,Romania,0,"Python, GCP, Scala, R",Associate,4,Finance,2024-11-16,2024-12-14,741,8.5,Digital Transformation LLC +AI07111,Robotics Engineer,114870,CAD,143588,SE,CT,Canada,S,Canada,100,"PyTorch, Azure, AWS",Associate,8,Education,2025-04-11,2025-05-31,671,9.5,Cognitive Computing +AI07112,Autonomous Systems Engineer,174174,JPY,19159140,EX,FL,Japan,L,Vietnam,100,"Azure, Python, TensorFlow",Bachelor,15,Healthcare,2025-02-06,2025-03-21,1297,6.4,Future Systems +AI07113,Robotics Engineer,174611,USD,174611,EX,CT,Finland,M,Czech Republic,0,"Azure, Git, PyTorch",PhD,18,Technology,2025-04-13,2025-05-02,2132,9.4,Cloud AI Solutions +AI07114,AI Product Manager,79305,USD,79305,MI,FT,Ireland,S,China,100,"R, MLOps, Scala, Mathematics",Associate,4,Government,2024-08-13,2024-09-02,2145,8.8,Neural Networks Co +AI07115,AI Product Manager,104456,USD,104456,SE,FT,South Korea,M,South Korea,50,"Python, Deep Learning, MLOps, TensorFlow",PhD,5,Government,2024-04-09,2024-05-26,1561,9.2,Predictive Systems +AI07116,AI Product Manager,134807,USD,134807,SE,FT,Israel,M,Romania,100,"SQL, AWS, PyTorch",Bachelor,6,Transportation,2025-03-14,2025-04-18,1452,9.1,TechCorp Inc +AI07117,AI Architect,149312,USD,149312,MI,FT,Denmark,L,Denmark,100,"Deep Learning, PyTorch, Mathematics",Master,2,Education,2024-06-26,2024-07-13,549,9.2,DataVision Ltd +AI07118,Research Scientist,138822,USD,138822,MI,CT,Denmark,L,Denmark,100,"Scala, Docker, Azure, Python",Master,4,Telecommunications,2024-04-08,2024-06-11,1428,6.6,Smart Analytics +AI07119,AI Research Scientist,87558,AUD,118203,EN,CT,Australia,L,Australia,0,"NLP, Kubernetes, AWS",PhD,1,Transportation,2024-06-11,2024-08-23,1979,7.5,Neural Networks Co +AI07120,AI Software Engineer,48577,EUR,41290,EN,PT,France,S,Russia,50,"TensorFlow, Scala, Deep Learning, Git",Associate,0,Gaming,2024-09-26,2024-10-11,617,7.6,AI Innovations +AI07121,Machine Learning Engineer,247655,EUR,210507,EX,PT,Germany,M,Germany,50,"Azure, Git, Python",PhD,14,Automotive,2024-07-28,2024-08-16,1618,6.5,Quantum Computing Inc +AI07122,Robotics Engineer,108278,GBP,81209,MI,PT,United Kingdom,M,United Kingdom,50,"Scala, R, SQL, AWS, Tableau",Master,2,Manufacturing,2024-05-03,2024-06-19,799,9.8,TechCorp Inc +AI07123,NLP Engineer,78812,EUR,66990,EN,FL,Germany,L,Germany,0,"R, AWS, Linux",Associate,0,Finance,2025-03-22,2025-05-11,1619,6.9,AI Innovations +AI07124,AI Specialist,116018,USD,116018,MI,PT,Sweden,L,Sweden,0,"PyTorch, Scala, Computer Vision, Mathematics",Bachelor,3,Automotive,2024-04-25,2024-06-25,2267,6.5,Algorithmic Solutions +AI07125,AI Research Scientist,27858,USD,27858,EN,FL,India,M,India,0,"SQL, R, PyTorch",Master,1,Gaming,2024-11-22,2025-01-20,1457,7.7,Cloud AI Solutions +AI07126,AI Consultant,60002,JPY,6600220,EN,CT,Japan,S,Japan,50,"Scala, PyTorch, Statistics, Spark",PhD,0,Government,2025-03-31,2025-05-08,660,6,DeepTech Ventures +AI07127,AI Specialist,167636,CHF,150872,SE,CT,Switzerland,L,Switzerland,0,"Python, Linux, Hadoop, Statistics, Mathematics",Associate,5,Real Estate,2024-02-19,2024-04-15,2370,7.1,Cloud AI Solutions +AI07128,AI Research Scientist,89617,USD,89617,MI,PT,Norway,S,Norway,0,"SQL, GCP, Python, Java, Git",Master,4,Media,2024-10-28,2024-12-24,2284,6.2,Cognitive Computing +AI07129,AI Consultant,133164,EUR,113189,SE,PT,France,L,Germany,100,"Computer Vision, Python, MLOps",Associate,7,Government,2025-03-09,2025-03-25,1886,9.1,Machine Intelligence Group +AI07130,ML Ops Engineer,91502,USD,91502,MI,PT,Finland,M,Finland,0,"Scala, Hadoop, AWS, Spark",Associate,2,Education,2024-04-01,2024-06-05,2387,5.4,Digital Transformation LLC +AI07131,AI Specialist,127869,USD,127869,SE,CT,South Korea,L,South Korea,0,"AWS, Python, Scala, Data Visualization",PhD,7,Manufacturing,2025-02-18,2025-04-04,773,9.6,Predictive Systems +AI07132,AI Architect,127426,CHF,114683,EN,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, NLP",Bachelor,0,Finance,2024-07-27,2024-10-02,1623,6.4,Neural Networks Co +AI07133,Data Analyst,210284,SGD,273369,EX,CT,Singapore,L,Singapore,50,"Java, TensorFlow, Statistics",Master,15,Gaming,2024-06-15,2024-08-07,2166,8.8,Machine Intelligence Group +AI07134,Machine Learning Engineer,78163,USD,78163,EN,PT,Ireland,M,Ireland,50,"SQL, Python, TensorFlow, PyTorch",Bachelor,1,Manufacturing,2024-07-27,2024-08-17,510,9.5,Predictive Systems +AI07135,AI Software Engineer,134757,USD,134757,MI,PT,Norway,L,China,50,"Scala, Mathematics, Git",Associate,4,Manufacturing,2024-08-27,2024-10-09,1181,8.6,TechCorp Inc +AI07136,Autonomous Systems Engineer,71562,CAD,89453,MI,PT,Canada,S,Canada,0,"Hadoop, R, Linux, Computer Vision",Bachelor,4,Gaming,2024-08-25,2024-09-20,2480,6.7,DeepTech Ventures +AI07137,Machine Learning Engineer,47242,CAD,59053,EN,FL,Canada,S,Canada,100,"AWS, Docker, GCP",Master,1,Automotive,2024-06-05,2024-07-01,1580,5.9,DataVision Ltd +AI07138,Head of AI,57033,USD,57033,EX,FT,India,M,Mexico,0,"Scala, PyTorch, Statistics",Bachelor,16,Transportation,2025-02-19,2025-04-04,1212,7,Quantum Computing Inc +AI07139,Data Analyst,119717,USD,119717,SE,PT,Sweden,S,Sweden,100,"GCP, TensorFlow, Python, Kubernetes",PhD,5,Healthcare,2024-03-04,2024-04-11,1807,7.8,Digital Transformation LLC +AI07140,Data Analyst,127727,USD,127727,SE,FL,Sweden,S,Sweden,0,"AWS, PyTorch, Java",Associate,9,Transportation,2024-03-12,2024-05-05,1142,5.6,DeepTech Ventures +AI07141,Machine Learning Engineer,78754,USD,78754,EN,CT,Finland,L,Finland,50,"NLP, SQL, Mathematics, MLOps, PyTorch",Bachelor,1,Energy,2024-10-05,2024-11-27,1435,9.9,Advanced Robotics +AI07142,Autonomous Systems Engineer,76900,USD,76900,MI,FL,Finland,M,Finland,50,"Kubernetes, PyTorch, Git, Linux",Bachelor,3,Government,2024-01-01,2024-01-16,1848,9.7,Algorithmic Solutions +AI07143,NLP Engineer,140463,USD,140463,SE,FT,Ireland,L,Ireland,50,"Data Visualization, TensorFlow, SQL, Git, Scala",PhD,8,Government,2024-04-01,2024-05-10,2156,6.9,Cognitive Computing +AI07144,AI Software Engineer,107972,AUD,145762,SE,FL,Australia,S,Romania,0,"TensorFlow, SQL, Mathematics, Linux",Associate,5,Retail,2025-02-04,2025-02-26,1598,9.4,Machine Intelligence Group +AI07145,Deep Learning Engineer,210162,USD,210162,EX,PT,United States,L,United States,100,"Java, Computer Vision, Python, Hadoop, Scala",Associate,12,Manufacturing,2025-03-06,2025-05-12,2178,9.7,Quantum Computing Inc +AI07146,Data Analyst,199015,CAD,248769,EX,PT,Canada,S,Egypt,50,"Git, TensorFlow, Mathematics, Spark",Master,13,Retail,2024-12-08,2025-02-05,722,7.8,DeepTech Ventures +AI07147,Data Analyst,214251,USD,214251,EX,PT,Ireland,M,Argentina,0,"Python, MLOps, GCP, Statistics, Linux",Master,14,Automotive,2024-04-13,2024-05-26,838,6.6,DataVision Ltd +AI07148,AI Research Scientist,200251,USD,200251,EX,FT,Sweden,M,Sweden,50,"MLOps, Hadoop, NLP, Data Visualization, R",Master,17,Government,2025-02-01,2025-04-09,693,10,Predictive Systems +AI07149,Machine Learning Engineer,56919,AUD,76841,EN,CT,Australia,S,Australia,0,"R, SQL, Git, Mathematics, Kubernetes",Bachelor,1,Technology,2024-06-07,2024-07-31,605,8.9,Quantum Computing Inc +AI07150,ML Ops Engineer,52483,USD,52483,EN,FT,Sweden,M,Sweden,0,"Spark, Mathematics, Data Visualization",Associate,1,Retail,2025-03-01,2025-03-18,2260,8.9,DataVision Ltd +AI07151,Computer Vision Engineer,124533,USD,124533,SE,CT,United States,S,South Africa,0,"Python, TensorFlow, Hadoop, Java",PhD,9,Telecommunications,2024-01-03,2024-01-19,1465,5.4,Future Systems +AI07152,NLP Engineer,122990,AUD,166037,MI,FT,Australia,L,Australia,100,"MLOps, Scala, Statistics",Associate,2,Finance,2025-02-01,2025-03-26,1567,9.2,Predictive Systems +AI07153,Head of AI,149199,USD,149199,EX,PT,Sweden,M,Chile,0,"PyTorch, Scala, Statistics",Bachelor,12,Energy,2024-10-24,2024-11-07,1675,6.6,Neural Networks Co +AI07154,NLP Engineer,82914,EUR,70477,MI,CT,Germany,S,Latvia,100,"Tableau, PyTorch, Kubernetes, GCP, AWS",Bachelor,3,Government,2024-02-19,2024-04-08,1754,5.9,Advanced Robotics +AI07155,Data Scientist,73131,EUR,62161,EN,PT,Austria,M,New Zealand,100,"Azure, Deep Learning, Git, Hadoop",Bachelor,1,Automotive,2024-03-26,2024-04-14,1533,5.3,Algorithmic Solutions +AI07156,AI Software Engineer,84202,JPY,9262220,EN,PT,Japan,M,Japan,50,"Spark, Docker, GCP, AWS, Hadoop",Bachelor,0,Real Estate,2024-11-15,2024-12-02,1057,8.8,Predictive Systems +AI07157,Autonomous Systems Engineer,196071,GBP,147053,EX,PT,United Kingdom,S,Kenya,0,"Linux, SQL, Deep Learning, Python, R",Associate,17,Transportation,2024-06-19,2024-08-27,741,8.2,Algorithmic Solutions +AI07158,AI Software Engineer,56307,USD,56307,EN,PT,Israel,M,Israel,100,"Python, Docker, Hadoop, Git",Bachelor,0,Real Estate,2025-01-27,2025-03-14,1013,6.1,Algorithmic Solutions +AI07159,Robotics Engineer,118127,USD,118127,EX,PT,China,L,China,0,"Python, Docker, MLOps",PhD,10,Energy,2024-12-20,2025-01-15,788,6.3,Cloud AI Solutions +AI07160,Deep Learning Engineer,286081,AUD,386209,EX,CT,Australia,L,Australia,0,"Statistics, Spark, TensorFlow, Linux, Docker",PhD,10,Automotive,2025-01-01,2025-02-22,1102,7.4,DataVision Ltd +AI07161,Data Analyst,38151,USD,38151,MI,FT,China,S,China,0,"PyTorch, TensorFlow, Statistics, Mathematics",Associate,4,Media,2024-10-09,2024-11-24,633,5.2,Cloud AI Solutions +AI07162,AI Product Manager,51436,JPY,5657960,EN,PT,Japan,S,Japan,0,"SQL, GCP, Kubernetes, Docker, Mathematics",Master,1,Manufacturing,2025-02-04,2025-02-20,1703,5.6,Future Systems +AI07163,Head of AI,179375,CHF,161438,MI,PT,Switzerland,L,New Zealand,0,"Python, Computer Vision, Linux, Azure, Deep Learning",Bachelor,3,Real Estate,2024-10-28,2024-12-07,501,9.2,Neural Networks Co +AI07164,AI Research Scientist,224945,USD,224945,EX,FL,Israel,M,Israel,100,"Docker, SQL, PyTorch, Java",PhD,16,Education,2024-08-28,2024-10-23,2317,9.1,Machine Intelligence Group +AI07165,AI Architect,199077,USD,199077,EX,FT,Sweden,S,India,100,"Computer Vision, Tableau, Data Visualization",Associate,14,Retail,2024-11-14,2024-12-25,2448,6.7,Cognitive Computing +AI07166,Data Engineer,154017,USD,154017,SE,PT,United States,L,United States,50,"Python, SQL, Spark, MLOps, TensorFlow",Associate,9,Transportation,2024-08-07,2024-09-11,1991,6.4,AI Innovations +AI07167,Data Engineer,187633,JPY,20639630,EX,CT,Japan,S,Japan,100,"Tableau, Scala, NLP, TensorFlow",Bachelor,17,Consulting,2024-09-28,2024-10-12,1306,8.4,Cloud AI Solutions +AI07168,Research Scientist,113467,USD,113467,MI,FL,Norway,M,Norway,50,"Azure, AWS, NLP, Deep Learning, GCP",Associate,4,Manufacturing,2024-02-16,2024-03-31,1916,8.6,Future Systems +AI07169,AI Product Manager,97170,USD,97170,MI,FL,Sweden,M,Sweden,100,"Kubernetes, GCP, SQL",PhD,4,Consulting,2024-07-01,2024-08-18,1337,6,Autonomous Tech +AI07170,AI Specialist,117600,USD,117600,MI,FT,Norway,S,Norway,50,"Java, Azure, Kubernetes",PhD,2,Technology,2024-09-11,2024-11-01,536,5.1,Neural Networks Co +AI07171,ML Ops Engineer,175430,CAD,219288,EX,CT,Canada,S,Canada,100,"Hadoop, R, SQL",Master,13,Finance,2025-03-17,2025-05-12,2082,9.2,Advanced Robotics +AI07172,Research Scientist,92546,EUR,78664,MI,FL,Netherlands,L,Netherlands,0,"R, Java, SQL",PhD,4,Transportation,2025-03-03,2025-03-17,1865,5.2,Cloud AI Solutions +AI07173,NLP Engineer,78042,USD,78042,MI,FL,United States,S,United States,100,"Python, GCP, TensorFlow, AWS, Deep Learning",Associate,2,Automotive,2024-03-21,2024-04-07,1251,6.2,DataVision Ltd +AI07174,Head of AI,60141,USD,60141,SE,FT,China,S,China,0,"Azure, AWS, Deep Learning, Computer Vision, GCP",PhD,5,Education,2025-01-03,2025-02-16,834,9.5,DeepTech Ventures +AI07175,Computer Vision Engineer,74219,EUR,63086,MI,FT,France,M,France,100,"Spark, NLP, Scala, PyTorch",Master,4,Gaming,2024-11-06,2025-01-03,577,5.7,Future Systems +AI07176,Data Scientist,117670,USD,117670,SE,PT,Finland,M,Finland,0,"Azure, TensorFlow, SQL, Tableau, Deep Learning",Associate,9,Manufacturing,2024-03-07,2024-03-25,585,9.5,Predictive Systems +AI07177,AI Product Manager,43045,USD,43045,EN,PT,South Korea,S,South Korea,100,"Mathematics, Data Visualization, Git, Linux",Associate,0,Healthcare,2024-05-22,2024-06-18,1964,5.9,Future Systems +AI07178,Computer Vision Engineer,204977,USD,204977,EX,FT,Israel,L,Israel,0,"NLP, Docker, Tableau, TensorFlow",Master,13,Retail,2024-01-23,2024-04-01,1912,8.8,Autonomous Tech +AI07179,Data Scientist,99117,USD,99117,MI,PT,Sweden,S,Sweden,50,"Azure, TensorFlow, AWS, Linux",Associate,3,Technology,2024-08-07,2024-08-30,1543,7.4,Autonomous Tech +AI07180,AI Product Manager,71043,USD,71043,EN,FT,Ireland,L,Ireland,50,"Data Visualization, Python, Spark, MLOps",Associate,1,Healthcare,2024-04-28,2024-07-01,2161,9.5,Algorithmic Solutions +AI07181,Machine Learning Engineer,245455,SGD,319092,EX,FL,Singapore,M,Singapore,0,"Git, Azure, Scala",PhD,19,Government,2025-04-25,2025-05-26,1625,7.6,Future Systems +AI07182,NLP Engineer,100152,USD,100152,MI,FL,South Korea,L,South Korea,50,"Java, Spark, Kubernetes",Bachelor,2,Government,2025-03-14,2025-04-16,529,6.5,Advanced Robotics +AI07183,Machine Learning Researcher,184471,EUR,156800,SE,PT,Netherlands,L,Singapore,100,"Python, MLOps, Statistics, Mathematics, Kubernetes",Associate,5,Gaming,2025-02-09,2025-04-13,1628,6.2,Future Systems +AI07184,Research Scientist,192741,EUR,163830,EX,FL,Austria,L,India,100,"Scala, Tableau, SQL, AWS",PhD,14,Real Estate,2024-12-25,2025-01-21,893,6.8,Neural Networks Co +AI07185,Autonomous Systems Engineer,130456,USD,130456,SE,FT,Norway,S,Norway,0,"Mathematics, Spark, NLP, Linux, Git",PhD,7,Healthcare,2025-03-21,2025-04-26,1191,8,Neural Networks Co +AI07186,ML Ops Engineer,131122,USD,131122,MI,CT,Denmark,M,Denmark,50,"Scala, Docker, Kubernetes",Associate,3,Gaming,2024-06-15,2024-08-08,2321,6.7,TechCorp Inc +AI07187,AI Research Scientist,92768,USD,92768,MI,FT,Ireland,S,Ireland,0,"Mathematics, R, SQL",Master,4,Finance,2024-08-20,2024-10-19,774,9.9,DeepTech Ventures +AI07188,AI Architect,117822,USD,117822,SE,FL,Israel,M,Israel,0,"Python, Spark, NLP, SQL, AWS",Associate,7,Telecommunications,2024-07-06,2024-09-11,690,9.3,Future Systems +AI07189,Data Scientist,220795,EUR,187676,EX,CT,Austria,L,Austria,100,"Kubernetes, Python, Tableau",Master,15,Transportation,2024-07-06,2024-08-04,1166,8.1,Digital Transformation LLC +AI07190,AI Specialist,71908,CAD,89885,MI,CT,Canada,M,Canada,0,"Python, TensorFlow, MLOps, Linux, Hadoop",Bachelor,4,Telecommunications,2024-06-19,2024-07-25,1717,9,DeepTech Ventures +AI07191,AI Consultant,217854,USD,217854,EX,FL,Denmark,L,Denmark,0,"Statistics, AWS, Hadoop, Docker, GCP",PhD,19,Media,2024-05-24,2024-07-28,2421,9.4,Machine Intelligence Group +AI07192,Head of AI,50633,JPY,5569630,EN,CT,Japan,S,Japan,0,"R, PyTorch, GCP",Master,0,Manufacturing,2024-05-15,2024-07-20,1102,7,Digital Transformation LLC +AI07193,Data Scientist,67836,CAD,84795,EN,CT,Canada,S,Indonesia,100,"Azure, Python, NLP, Docker",Bachelor,0,Telecommunications,2025-02-13,2025-04-05,2052,7.7,Autonomous Tech +AI07194,Deep Learning Engineer,120724,AUD,162977,MI,PT,Australia,L,Australia,50,"Scala, Java, Kubernetes, Mathematics",PhD,2,Government,2024-11-22,2025-01-30,1133,6.4,Quantum Computing Inc +AI07195,Head of AI,117611,USD,117611,MI,FL,Denmark,S,Denmark,50,"SQL, Mathematics, R, PyTorch",Bachelor,4,Consulting,2024-11-01,2025-01-04,2446,9.4,Autonomous Tech +AI07196,Autonomous Systems Engineer,143600,USD,143600,EX,CT,Ireland,S,Ireland,50,"MLOps, Python, Statistics",Master,12,Automotive,2024-11-11,2025-01-08,907,7.1,Advanced Robotics +AI07197,Deep Learning Engineer,54479,SGD,70823,EN,FL,Singapore,M,Singapore,50,"MLOps, Linux, Azure",Bachelor,0,Manufacturing,2024-06-15,2024-07-18,1974,6.7,Future Systems +AI07198,AI Research Scientist,234608,JPY,25806880,EX,FL,Japan,S,Japan,50,"Spark, Python, Docker, GCP",Associate,17,Telecommunications,2024-10-08,2024-12-16,558,8,Cognitive Computing +AI07199,Computer Vision Engineer,58879,EUR,50047,EN,FL,Germany,L,Germany,100,"TensorFlow, Spark, PyTorch, Git",Master,0,Government,2025-01-03,2025-02-24,1177,7.5,Cloud AI Solutions +AI07200,Principal Data Scientist,94161,USD,94161,MI,FT,Denmark,S,Denmark,50,"Java, SQL, Tableau, Azure, Spark",Associate,3,Energy,2024-06-30,2024-09-02,1398,5.2,Autonomous Tech +AI07201,Head of AI,83285,USD,83285,MI,FL,Ireland,S,Ireland,50,"R, Java, Spark, TensorFlow, Kubernetes",Master,3,Retail,2025-03-07,2025-04-21,2452,8.8,Neural Networks Co +AI07202,AI Software Engineer,203713,AUD,275013,EX,FL,Australia,M,Australia,50,"Mathematics, Kubernetes, MLOps",PhD,14,Transportation,2024-11-21,2025-01-04,594,7.1,Autonomous Tech +AI07203,Data Scientist,31793,USD,31793,MI,PT,China,S,China,100,"MLOps, Docker, Linux, Tableau, Data Visualization",Master,2,Government,2024-05-21,2024-06-24,718,5.4,DataVision Ltd +AI07204,Principal Data Scientist,48887,USD,48887,SE,PT,India,L,India,50,"PyTorch, Tableau, Hadoop, AWS",PhD,9,Technology,2025-04-24,2025-06-04,1126,8.2,Digital Transformation LLC +AI07205,Principal Data Scientist,106359,AUD,143585,MI,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, SQL, GCP",Master,4,Technology,2025-03-20,2025-05-19,905,5.7,TechCorp Inc +AI07206,Deep Learning Engineer,115364,USD,115364,SE,CT,Israel,M,Australia,50,"Python, Java, Deep Learning, TensorFlow",Master,8,Manufacturing,2024-03-05,2024-05-01,844,6.7,Quantum Computing Inc +AI07207,Research Scientist,135236,EUR,114951,SE,CT,Germany,S,Germany,0,"MLOps, Spark, Python, Git",Bachelor,5,Education,2024-08-20,2024-10-31,2100,7.1,Advanced Robotics +AI07208,Data Analyst,196882,EUR,167350,EX,FL,Netherlands,L,Netherlands,100,"Computer Vision, Hadoop, Statistics, TensorFlow",Master,11,Real Estate,2024-05-06,2024-06-26,2375,8.3,DeepTech Ventures +AI07209,AI Specialist,52592,GBP,39444,EN,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Scala, SQL, NLP",PhD,0,Transportation,2024-12-26,2025-02-02,1544,8.8,Future Systems +AI07210,Machine Learning Researcher,130809,JPY,14388990,SE,CT,Japan,L,Japan,0,"PyTorch, SQL, Git, Hadoop, Mathematics",Associate,7,Healthcare,2024-02-15,2024-03-25,897,6.4,AI Innovations +AI07211,Data Engineer,83254,EUR,70766,EN,FL,Germany,L,Germany,50,"PyTorch, NLP, Deep Learning, Python, MLOps",Master,1,Technology,2024-01-01,2024-02-27,798,9.4,Predictive Systems +AI07212,Deep Learning Engineer,116639,USD,116639,MI,PT,Denmark,S,Denmark,50,"Tableau, Java, MLOps, Hadoop, Azure",Associate,3,Retail,2024-06-28,2024-07-14,892,6,Cloud AI Solutions +AI07213,Data Engineer,188382,CHF,169544,SE,FL,Switzerland,M,Portugal,0,"MLOps, PyTorch, Mathematics, TensorFlow",Bachelor,6,Consulting,2024-06-02,2024-07-11,2297,6.8,Cognitive Computing +AI07214,AI Software Engineer,126123,SGD,163960,SE,PT,Singapore,L,Romania,100,"Scala, Tableau, Python, Data Visualization",Master,7,Healthcare,2025-04-22,2025-06-26,686,8.1,Quantum Computing Inc +AI07215,AI Product Manager,108451,USD,108451,SE,FT,South Korea,M,South Korea,0,"NLP, Docker, SQL, Git",PhD,6,Technology,2024-06-15,2024-08-19,2311,6.2,Future Systems +AI07216,Computer Vision Engineer,241452,EUR,205234,EX,FL,Netherlands,L,Netherlands,0,"Python, Tableau, Deep Learning",Master,11,Finance,2024-09-23,2024-10-15,1584,6.5,Advanced Robotics +AI07217,Robotics Engineer,95945,EUR,81553,MI,CT,Netherlands,S,Netherlands,0,"SQL, Linux, Tableau",Master,2,Consulting,2024-01-02,2024-02-23,1803,10,Machine Intelligence Group +AI07218,Data Scientist,92299,AUD,124604,MI,PT,Australia,L,Portugal,50,"Deep Learning, Scala, SQL, Git",Associate,3,Finance,2024-07-08,2024-08-16,1353,7.7,Neural Networks Co +AI07219,Data Engineer,92328,USD,92328,MI,FT,Israel,M,Ukraine,0,"Java, Python, Hadoop, Spark",Associate,4,Automotive,2024-01-02,2024-02-02,1233,5,AI Innovations +AI07220,AI Consultant,63650,USD,63650,EN,FT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, Mathematics",Associate,1,Government,2024-05-17,2024-06-07,2110,7.3,Quantum Computing Inc +AI07221,AI Consultant,240627,EUR,204533,EX,FT,Netherlands,M,Netherlands,0,"Data Visualization, Spark, Scala, Deep Learning",PhD,18,Retail,2024-06-26,2024-07-19,1850,5.1,AI Innovations +AI07222,AI Specialist,113824,USD,113824,MI,PT,Norway,L,Norway,100,"AWS, Docker, Azure, Computer Vision",PhD,4,Consulting,2024-11-18,2025-01-06,2039,8.2,Algorithmic Solutions +AI07223,Data Analyst,102248,CHF,92023,MI,CT,Switzerland,S,Spain,0,"AWS, Mathematics, Hadoop",PhD,2,Real Estate,2024-03-09,2024-03-30,1863,9.9,Smart Analytics +AI07224,Machine Learning Researcher,72700,USD,72700,MI,PT,South Korea,S,South Korea,100,"Python, Hadoop, Linux, Scala, Java",PhD,4,Consulting,2024-11-18,2024-12-04,1842,5.6,Advanced Robotics +AI07225,AI Product Manager,101760,USD,101760,MI,FL,Ireland,L,Ireland,50,"Scala, Git, Statistics, Computer Vision, Kubernetes",Associate,3,Retail,2024-02-19,2024-03-13,2062,6.9,Digital Transformation LLC +AI07226,Machine Learning Researcher,75850,USD,75850,MI,PT,Israel,S,Israel,0,"Deep Learning, Java, Git, Mathematics, R",Bachelor,4,Retail,2024-05-03,2024-06-26,969,8.4,Cloud AI Solutions +AI07227,Robotics Engineer,54596,EUR,46407,EN,FL,Austria,M,Austria,100,"NLP, Python, Deep Learning",Bachelor,1,Technology,2025-01-12,2025-03-13,1823,9.4,Algorithmic Solutions +AI07228,AI Research Scientist,133583,AUD,180337,EX,PT,Australia,S,Australia,100,"Hadoop, SQL, Spark",Bachelor,11,Retail,2024-10-04,2024-10-18,1642,6.8,Digital Transformation LLC +AI07229,Autonomous Systems Engineer,75968,CAD,94960,MI,FL,Canada,M,Canada,100,"Mathematics, Docker, Python, Hadoop",Master,4,Manufacturing,2024-07-11,2024-08-17,1020,8,Quantum Computing Inc +AI07230,AI Product Manager,142238,AUD,192021,SE,FT,Australia,L,Australia,50,"GCP, R, Mathematics",PhD,7,Government,2024-07-03,2024-08-16,978,6.3,AI Innovations +AI07231,Machine Learning Engineer,211317,USD,211317,EX,FL,Israel,L,Israel,0,"MLOps, Mathematics, SQL, AWS",Master,13,Consulting,2025-01-18,2025-03-18,990,6.7,Autonomous Tech +AI07232,Data Engineer,260422,EUR,221359,EX,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Data Visualization, Spark",PhD,15,Education,2024-06-17,2024-08-13,2056,9.5,Machine Intelligence Group +AI07233,Autonomous Systems Engineer,203781,CAD,254726,EX,FL,Canada,S,Canada,0,"Linux, Java, Data Visualization, MLOps, Hadoop",PhD,11,Healthcare,2024-11-19,2024-12-19,1698,10,Neural Networks Co +AI07234,Machine Learning Engineer,53311,USD,53311,SE,PT,India,M,India,0,"Spark, SQL, Kubernetes, Python, Computer Vision",Associate,8,Transportation,2025-04-19,2025-06-15,727,5.4,Cloud AI Solutions +AI07235,AI Product Manager,111471,JPY,12261810,SE,FL,Japan,S,Japan,100,"SQL, Java, R, Scala",Bachelor,6,Healthcare,2024-05-15,2024-07-21,597,7.5,Predictive Systems +AI07236,Robotics Engineer,195168,EUR,165893,EX,PT,Germany,S,Spain,50,"Python, Docker, AWS",Master,11,Government,2024-12-29,2025-02-03,1452,8.2,Advanced Robotics +AI07237,AI Product Manager,48863,USD,48863,EN,FL,Finland,S,Finland,50,"Python, SQL, Hadoop",Bachelor,0,Transportation,2025-03-31,2025-05-22,870,7.7,Advanced Robotics +AI07238,AI Consultant,272513,CHF,245262,EX,CT,Switzerland,L,Switzerland,50,"PyTorch, AWS, NLP, SQL",Master,16,Real Estate,2024-10-19,2024-12-16,2456,9.1,AI Innovations +AI07239,ML Ops Engineer,180571,USD,180571,EX,CT,Sweden,L,Turkey,0,"GCP, TensorFlow, NLP, SQL, Tableau",Bachelor,19,Gaming,2025-03-18,2025-05-26,642,7.3,Algorithmic Solutions +AI07240,Data Scientist,177014,USD,177014,SE,FT,Denmark,L,Denmark,50,"Data Visualization, R, Deep Learning",Master,7,Automotive,2024-12-17,2024-12-31,2171,6.1,Predictive Systems +AI07241,Research Scientist,105629,USD,105629,EN,FL,United States,L,Finland,50,"SQL, NLP, Git, PyTorch",Bachelor,0,Real Estate,2024-10-28,2024-11-19,1188,8.6,Cognitive Computing +AI07242,NLP Engineer,201624,USD,201624,EX,FL,Ireland,S,Latvia,50,"Scala, Spark, Kubernetes, TensorFlow, Statistics",Bachelor,11,Technology,2024-10-09,2024-12-13,1376,7.5,Predictive Systems +AI07243,NLP Engineer,131783,EUR,112016,SE,CT,France,L,South Africa,100,"Java, GCP, Tableau, Scala",Associate,5,Gaming,2025-04-30,2025-07-04,548,8.6,DeepTech Ventures +AI07244,NLP Engineer,75289,USD,75289,EN,FL,Sweden,L,Sweden,100,"Linux, PyTorch, R, Python, Mathematics",Bachelor,0,Energy,2024-03-02,2024-04-28,1011,8.3,Quantum Computing Inc +AI07245,Data Scientist,336868,USD,336868,EX,PT,Norway,L,Norway,100,"Spark, NLP, Tableau, Docker",Master,14,Media,2024-06-21,2024-08-03,902,8.1,Digital Transformation LLC +AI07246,AI Research Scientist,163534,EUR,139004,SE,FL,Germany,L,Germany,0,"GCP, Hadoop, Docker, Deep Learning, SQL",Master,7,Consulting,2024-07-13,2024-08-06,1179,6.7,Machine Intelligence Group +AI07247,Data Engineer,116592,USD,116592,SE,FT,Finland,S,China,100,"Git, Spark, NLP, Kubernetes",PhD,9,Healthcare,2025-03-10,2025-04-17,2130,8.6,Cloud AI Solutions +AI07248,AI Consultant,124845,JPY,13732950,SE,FL,Japan,L,New Zealand,0,"Kubernetes, Data Visualization, Python, AWS, MLOps",Bachelor,9,Technology,2024-10-16,2024-12-10,1028,7.3,Machine Intelligence Group +AI07249,Robotics Engineer,130238,USD,130238,EX,PT,Sweden,S,Sweden,100,"SQL, Kubernetes, PyTorch, Git",Master,10,Consulting,2024-07-01,2024-07-16,1080,8.9,Digital Transformation LLC +AI07250,Data Engineer,190431,CAD,238039,EX,PT,Canada,M,Canada,50,"Spark, Scala, SQL",Master,19,Healthcare,2024-10-22,2024-11-19,2125,7.1,Quantum Computing Inc +AI07251,Research Scientist,21657,USD,21657,EN,CT,India,L,India,50,"TensorFlow, Java, PyTorch, GCP",Bachelor,0,Real Estate,2024-01-08,2024-02-04,790,5.1,DataVision Ltd +AI07252,Data Engineer,120635,USD,120635,MI,PT,Ireland,L,Ireland,100,"Linux, R, SQL, Deep Learning",PhD,4,Media,2025-02-26,2025-03-18,1761,7,Machine Intelligence Group +AI07253,AI Research Scientist,86185,USD,86185,MI,FL,Israel,L,Israel,50,"Statistics, Computer Vision, Data Visualization, Scala, MLOps",Bachelor,4,Government,2024-09-06,2024-11-18,552,5.6,Neural Networks Co +AI07254,AI Software Engineer,165333,CAD,206666,SE,FL,Canada,L,Australia,0,"Linux, Spark, TensorFlow",Associate,9,Energy,2024-09-01,2024-10-26,2165,6.6,Autonomous Tech +AI07255,Head of AI,160948,USD,160948,EX,FL,Finland,L,Finland,50,"Deep Learning, Kubernetes, Java, Hadoop",Master,15,Finance,2024-12-08,2025-01-19,726,6.3,DeepTech Ventures +AI07256,Deep Learning Engineer,74480,CHF,67032,EN,CT,Switzerland,M,Switzerland,50,"Java, Linux, TensorFlow, AWS, NLP",PhD,1,Energy,2024-04-23,2024-06-30,1898,7.9,Predictive Systems +AI07257,Data Scientist,64243,CAD,80304,EN,PT,Canada,L,Canada,0,"Computer Vision, Python, TensorFlow",Bachelor,0,Finance,2024-10-26,2024-12-21,1629,5.5,DeepTech Ventures +AI07258,Data Engineer,86729,USD,86729,MI,CT,Sweden,S,Switzerland,100,"Computer Vision, Mathematics, Kubernetes, Tableau",Bachelor,4,Manufacturing,2024-08-16,2024-10-01,1998,7.1,Algorithmic Solutions +AI07259,AI Specialist,72797,JPY,8007670,EN,PT,Japan,M,Japan,50,"SQL, GCP, Tableau, TensorFlow, Data Visualization",Master,1,Consulting,2024-09-28,2024-11-02,1471,8,DeepTech Ventures +AI07260,Research Scientist,124502,SGD,161853,SE,PT,Singapore,S,Singapore,100,"Deep Learning, Scala, Computer Vision, SQL, PyTorch",Associate,6,Education,2024-01-02,2024-01-28,619,9.5,Advanced Robotics +AI07261,AI Software Engineer,271059,AUD,365930,EX,CT,Australia,L,Philippines,100,"Git, Azure, Python, TensorFlow",Bachelor,12,Finance,2025-01-19,2025-02-15,1510,5.3,Cognitive Computing +AI07262,AI Product Manager,108790,EUR,92472,MI,CT,Netherlands,M,United States,0,"Kubernetes, Python, Tableau",PhD,3,Media,2024-05-04,2024-05-23,1626,9.1,Predictive Systems +AI07263,AI Product Manager,259708,AUD,350606,EX,PT,Australia,L,Australia,0,"Spark, Kubernetes, Statistics",PhD,17,Healthcare,2025-02-20,2025-03-17,2391,6.6,AI Innovations +AI07264,ML Ops Engineer,83606,USD,83606,EN,CT,United States,S,Germany,100,"TensorFlow, Tableau, Python, Computer Vision",Master,1,Consulting,2025-03-22,2025-05-14,1408,9.1,Cloud AI Solutions +AI07265,Robotics Engineer,160120,AUD,216162,SE,FT,Australia,L,Australia,50,"R, GCP, Deep Learning",Master,5,Manufacturing,2024-06-07,2024-07-16,1221,8.2,Cloud AI Solutions +AI07266,Robotics Engineer,97279,USD,97279,MI,PT,Israel,M,Israel,0,"Kubernetes, Python, Deep Learning, Data Visualization, Java",Master,2,Gaming,2024-05-10,2024-06-19,1144,6.4,Quantum Computing Inc +AI07267,AI Research Scientist,120260,USD,120260,SE,PT,Sweden,S,Sweden,50,"Computer Vision, MLOps, Deep Learning, Spark, PyTorch",Associate,9,Consulting,2024-03-07,2024-04-21,1969,5.4,DataVision Ltd +AI07268,Research Scientist,70585,AUD,95290,EN,FT,Australia,L,Estonia,50,"Mathematics, Hadoop, GCP, PyTorch",Associate,1,Retail,2024-08-18,2024-10-20,1909,6,TechCorp Inc +AI07269,Machine Learning Engineer,88166,AUD,119024,MI,CT,Australia,S,Australia,100,"Python, TensorFlow, Linux",Associate,2,Finance,2024-03-22,2024-05-21,1056,6.5,Smart Analytics +AI07270,Machine Learning Researcher,112078,USD,112078,MI,PT,United States,S,Japan,50,"Hadoop, GCP, Kubernetes, Tableau",Master,3,Technology,2025-03-16,2025-04-25,2346,5.1,Cognitive Computing +AI07271,AI Product Manager,33267,USD,33267,MI,CT,China,S,China,50,"Spark, AWS, Deep Learning",Master,2,Media,2024-06-08,2024-07-27,773,6.7,AI Innovations +AI07272,Machine Learning Researcher,118202,USD,118202,MI,PT,Norway,M,Norway,100,"Docker, Deep Learning, PyTorch",Bachelor,4,Media,2024-02-23,2024-04-29,1741,7,Future Systems +AI07273,Machine Learning Researcher,83199,USD,83199,MI,FT,Ireland,S,Ireland,0,"Kubernetes, Docker, Python, Computer Vision",PhD,4,Automotive,2025-03-20,2025-04-17,1720,7.2,Digital Transformation LLC +AI07274,Deep Learning Engineer,64159,CAD,80199,EN,PT,Canada,M,Canada,0,"Python, Kubernetes, AWS",Bachelor,1,Education,2024-03-28,2024-05-04,1069,5.8,Autonomous Tech +AI07275,ML Ops Engineer,67930,USD,67930,MI,FL,South Korea,S,South Korea,100,"Statistics, TensorFlow, R, Deep Learning, Tableau",Master,4,Real Estate,2024-06-18,2024-08-19,618,7.1,Future Systems +AI07276,Principal Data Scientist,118438,GBP,88829,SE,FT,United Kingdom,M,United Kingdom,50,"Spark, Kubernetes, Mathematics, Tableau",Master,9,Automotive,2024-02-10,2024-04-03,1557,6.5,Cognitive Computing +AI07277,AI Product Manager,49451,USD,49451,SE,PT,India,L,India,0,"SQL, Python, PyTorch",Master,5,Media,2024-04-25,2024-05-28,1974,7,Machine Intelligence Group +AI07278,Head of AI,199445,USD,199445,SE,PT,Norway,L,Norway,0,"NLP, Azure, Spark, Scala, Tableau",PhD,5,Healthcare,2024-12-29,2025-01-14,2056,7,Smart Analytics +AI07279,AI Software Engineer,151206,USD,151206,EX,CT,Sweden,S,Sweden,100,"NLP, R, Kubernetes, Mathematics",Master,14,Energy,2024-12-23,2025-02-15,1491,8.2,Predictive Systems +AI07280,AI Product Manager,129233,JPY,14215630,SE,PT,Japan,S,Japan,50,"SQL, Tableau, Spark",Master,6,Telecommunications,2024-11-17,2024-12-30,1828,6,Cloud AI Solutions +AI07281,Data Engineer,126854,EUR,107826,MI,PT,Germany,L,Denmark,50,"Linux, Kubernetes, Docker, Hadoop",Bachelor,4,Retail,2024-01-23,2024-04-02,1955,6.9,Predictive Systems +AI07282,NLP Engineer,85718,CAD,107148,MI,PT,Canada,M,Canada,50,"GCP, Linux, Spark, PyTorch, R",Bachelor,3,Automotive,2025-01-23,2025-03-28,2152,5.8,Neural Networks Co +AI07283,ML Ops Engineer,79085,USD,79085,MI,FT,South Korea,L,Vietnam,100,"Data Visualization, Mathematics, Python, Git",PhD,4,Consulting,2025-02-11,2025-04-01,2363,5.5,Future Systems +AI07284,Robotics Engineer,95382,USD,95382,MI,FL,Sweden,M,Sweden,100,"Git, TensorFlow, Tableau, Docker, PyTorch",Bachelor,2,Education,2025-03-17,2025-04-21,1788,8.1,TechCorp Inc +AI07285,AI Consultant,114244,GBP,85683,MI,CT,United Kingdom,L,United Kingdom,100,"SQL, Scala, Deep Learning, Tableau",Bachelor,3,Manufacturing,2024-10-28,2024-12-12,1445,6.4,DeepTech Ventures +AI07286,Principal Data Scientist,86971,SGD,113062,EN,FT,Singapore,L,Singapore,0,"Docker, Git, MLOps",Associate,1,Gaming,2024-08-10,2024-09-24,2324,5,AI Innovations +AI07287,AI Product Manager,113959,SGD,148147,SE,PT,Singapore,M,Czech Republic,50,"Python, Mathematics, SQL",Bachelor,7,Consulting,2024-08-13,2024-10-08,1989,8.8,Algorithmic Solutions +AI07288,ML Ops Engineer,138785,USD,138785,SE,FL,South Korea,L,South Korea,0,"Deep Learning, Computer Vision, PyTorch, Java, MLOps",Master,9,Retail,2024-10-20,2024-12-07,1829,7.1,TechCorp Inc +AI07289,Robotics Engineer,122279,GBP,91709,MI,FT,United Kingdom,L,Ukraine,100,"Hadoop, AWS, MLOps, Scala",Associate,4,Retail,2024-06-13,2024-08-01,1295,8.6,DataVision Ltd +AI07290,NLP Engineer,46233,EUR,39298,EN,PT,Austria,S,Austria,100,"Computer Vision, AWS, Git, Tableau",Bachelor,0,Education,2024-07-16,2024-08-11,1131,7.3,Smart Analytics +AI07291,Machine Learning Researcher,298282,USD,298282,EX,FT,Denmark,L,Denmark,50,"Kubernetes, SQL, GCP, PyTorch, Mathematics",Associate,17,Telecommunications,2024-01-30,2024-03-27,1484,5.5,Machine Intelligence Group +AI07292,AI Architect,20587,USD,20587,EN,FL,India,M,Estonia,0,"Kubernetes, R, Computer Vision, Deep Learning",Associate,1,Energy,2024-12-05,2024-12-22,773,8.9,Algorithmic Solutions +AI07293,Data Scientist,85412,USD,85412,MI,PT,Ireland,L,Indonesia,100,"Deep Learning, Statistics, NLP, Kubernetes",Master,2,Government,2025-03-28,2025-06-06,2482,9.8,TechCorp Inc +AI07294,Deep Learning Engineer,164904,EUR,140168,SE,CT,Netherlands,L,Netherlands,100,"SQL, PyTorch, AWS, Scala, Java",Bachelor,9,Healthcare,2024-06-17,2024-08-03,2150,7.8,DataVision Ltd +AI07295,Principal Data Scientist,153719,EUR,130661,EX,FT,Austria,M,Austria,50,"SQL, AWS, Deep Learning, NLP, PyTorch",Associate,10,Healthcare,2024-10-21,2024-12-01,757,9,Predictive Systems +AI07296,Data Analyst,128775,EUR,109459,MI,CT,Netherlands,L,China,0,"Hadoop, PyTorch, Data Visualization, NLP",Master,3,Education,2025-01-07,2025-03-08,2131,7.3,Advanced Robotics +AI07297,AI Architect,74122,EUR,63004,MI,FT,Netherlands,S,Netherlands,50,"Azure, Kubernetes, GCP",Bachelor,3,Technology,2024-01-30,2024-02-28,1960,5.7,Cloud AI Solutions +AI07298,NLP Engineer,153979,USD,153979,EX,CT,Sweden,M,Sweden,50,"Python, Docker, MLOps",PhD,14,Automotive,2025-04-30,2025-07-04,698,9.7,AI Innovations +AI07299,Data Scientist,130397,CHF,117357,SE,CT,Switzerland,S,Switzerland,50,"Statistics, Hadoop, Azure, Java",PhD,9,Manufacturing,2025-02-27,2025-03-25,897,5.8,TechCorp Inc +AI07300,Autonomous Systems Engineer,79354,GBP,59516,EN,FT,United Kingdom,M,Ireland,0,"TensorFlow, Statistics, Docker",PhD,1,Media,2025-02-22,2025-03-12,1379,7.5,Quantum Computing Inc +AI07301,Data Scientist,120736,USD,120736,MI,FL,Ireland,L,Israel,0,"Azure, Linux, NLP",Associate,3,Energy,2024-11-08,2025-01-02,2417,6,Autonomous Tech +AI07302,Research Scientist,92591,USD,92591,SE,FT,Finland,S,Portugal,0,"Deep Learning, Python, GCP",Bachelor,6,Real Estate,2024-06-13,2024-07-23,1341,6.6,Smart Analytics +AI07303,Robotics Engineer,167422,USD,167422,SE,FL,Denmark,S,Denmark,100,"Python, Mathematics, Tableau, Deep Learning, SQL",Master,7,Gaming,2024-11-11,2024-12-18,1682,5.5,Cloud AI Solutions +AI07304,Research Scientist,43875,USD,43875,SE,CT,China,S,China,0,"Statistics, Kubernetes, SQL",Master,6,Healthcare,2024-11-25,2025-01-11,2385,9.1,Algorithmic Solutions +AI07305,Data Engineer,154370,EUR,131215,SE,PT,Austria,L,Austria,0,"Python, Spark, Statistics, Deep Learning, Java",Master,7,Education,2024-10-31,2024-12-07,1667,6,Future Systems +AI07306,Computer Vision Engineer,89756,CAD,112195,MI,PT,Canada,S,Canada,0,"Data Visualization, SQL, Azure, Kubernetes, Mathematics",PhD,2,Energy,2024-08-10,2024-09-19,2415,7.2,Advanced Robotics +AI07307,AI Specialist,58025,EUR,49321,EN,CT,Germany,S,Luxembourg,100,"R, SQL, NLP, Hadoop",Bachelor,1,Government,2024-10-08,2024-12-10,1563,7.1,DataVision Ltd +AI07308,Computer Vision Engineer,52365,EUR,44510,EN,PT,Netherlands,S,Netherlands,0,"Tableau, Linux, SQL, PyTorch",PhD,1,Manufacturing,2025-04-17,2025-05-03,1878,6.7,Machine Intelligence Group +AI07309,Research Scientist,252611,EUR,214719,EX,FL,Netherlands,L,Netherlands,100,"AWS, Data Visualization, MLOps, Spark",Associate,18,Media,2024-05-22,2024-06-28,787,9.3,DeepTech Ventures +AI07310,AI Consultant,292045,JPY,32124950,EX,FT,Japan,L,Japan,50,"Python, Scala, Hadoop, Linux, GCP",Bachelor,15,Telecommunications,2024-12-17,2025-02-16,1701,5.5,Autonomous Tech +AI07311,Research Scientist,180417,SGD,234542,EX,FL,Singapore,S,Singapore,100,"TensorFlow, Java, Tableau",Master,15,Transportation,2025-04-08,2025-04-23,1308,8.1,DataVision Ltd +AI07312,Deep Learning Engineer,65703,USD,65703,EN,FT,Ireland,S,United States,100,"Hadoop, Computer Vision, SQL, R, PyTorch",PhD,1,Gaming,2024-08-24,2024-09-07,1472,9.4,DataVision Ltd +AI07313,ML Ops Engineer,33627,USD,33627,MI,FT,India,L,India,0,"Hadoop, AWS, Kubernetes, NLP, Azure",Master,3,Automotive,2024-12-06,2025-01-03,1675,9.2,Neural Networks Co +AI07314,NLP Engineer,117069,CHF,105362,MI,PT,Switzerland,M,Nigeria,50,"PyTorch, GCP, Deep Learning, Docker, Tableau",Master,3,Automotive,2024-02-03,2024-03-01,1738,8.6,Predictive Systems +AI07315,Deep Learning Engineer,109443,EUR,93027,SE,CT,France,S,France,50,"Kubernetes, Python, Scala",PhD,8,Healthcare,2025-01-11,2025-03-04,2280,8.7,Digital Transformation LLC +AI07316,AI Software Engineer,114421,EUR,97258,MI,FL,Austria,L,Luxembourg,0,"Python, Tableau, Linux, Hadoop",Master,3,Manufacturing,2024-05-10,2024-07-14,1941,5.7,Neural Networks Co +AI07317,Head of AI,297806,USD,297806,EX,FT,United States,M,China,0,"Data Visualization, PyTorch, Tableau, GCP",Bachelor,15,Media,2024-11-07,2024-12-13,1644,9.3,DataVision Ltd +AI07318,Autonomous Systems Engineer,96103,JPY,10571330,MI,FL,Japan,M,Japan,0,"Java, Scala, Hadoop",Master,2,Technology,2024-08-30,2024-10-13,993,6.2,Advanced Robotics +AI07319,AI Consultant,104183,EUR,88556,MI,PT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, Scala",PhD,4,Automotive,2024-05-30,2024-07-27,1802,8.3,Quantum Computing Inc +AI07320,Research Scientist,203843,CHF,183459,SE,FT,Switzerland,L,Switzerland,100,"Docker, GCP, Hadoop, Computer Vision",Master,6,Transportation,2025-03-31,2025-05-17,1710,8.4,TechCorp Inc +AI07321,AI Specialist,159445,CHF,143501,SE,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Java, GCP",Master,9,Consulting,2025-04-17,2025-06-21,823,7.8,DeepTech Ventures +AI07322,Computer Vision Engineer,98252,USD,98252,SE,CT,Finland,S,Finland,50,"Azure, Tableau, AWS, Linux",Bachelor,7,Gaming,2024-12-14,2025-01-24,1131,6.2,Advanced Robotics +AI07323,Data Engineer,140598,USD,140598,SE,FL,Sweden,L,Switzerland,50,"Python, PyTorch, Docker",PhD,5,Energy,2024-02-08,2024-04-07,1530,6.6,Quantum Computing Inc +AI07324,Data Engineer,122530,USD,122530,SE,FT,Ireland,S,Ireland,0,"SQL, Tableau, Deep Learning",Master,5,Consulting,2025-03-06,2025-03-30,1123,8.1,Advanced Robotics +AI07325,AI Specialist,79216,USD,79216,EN,FT,United States,S,United States,100,"Kubernetes, Java, MLOps",Associate,0,Government,2024-11-24,2025-01-16,1296,5.6,Autonomous Tech +AI07326,AI Software Engineer,208065,USD,208065,EX,FT,South Korea,M,South Korea,100,"Azure, TensorFlow, R, Tableau",Master,14,Real Estate,2025-02-06,2025-04-03,1320,7.5,Digital Transformation LLC +AI07327,Data Engineer,212005,EUR,180204,EX,PT,Germany,M,Germany,0,"GCP, R, Python",PhD,10,Retail,2024-06-10,2024-07-16,1605,5.2,TechCorp Inc +AI07328,Computer Vision Engineer,142069,EUR,120759,SE,PT,Netherlands,L,Netherlands,0,"Data Visualization, Kubernetes, Scala, Python, Mathematics",Bachelor,7,Consulting,2024-11-23,2024-12-18,2476,5.3,Algorithmic Solutions +AI07329,NLP Engineer,189432,USD,189432,EX,PT,Israel,S,Nigeria,50,"GCP, R, SQL, TensorFlow, Java",Master,17,Manufacturing,2024-06-21,2024-08-15,1030,6.3,AI Innovations +AI07330,AI Architect,148090,USD,148090,EX,PT,United States,S,United States,100,"Mathematics, MLOps, Data Visualization, TensorFlow",Associate,13,Media,2025-01-26,2025-04-03,1491,8.1,Cognitive Computing +AI07331,Autonomous Systems Engineer,90214,AUD,121789,MI,FL,Australia,M,Singapore,100,"R, AWS, MLOps, Git",Bachelor,2,Government,2025-02-01,2025-03-13,1301,5.2,Algorithmic Solutions +AI07332,Autonomous Systems Engineer,179077,CAD,223846,EX,FT,Canada,M,Austria,100,"SQL, Data Visualization, MLOps, Mathematics, Java",Bachelor,11,Telecommunications,2024-01-21,2024-02-18,1876,5.3,DeepTech Ventures +AI07333,NLP Engineer,49419,AUD,66716,EN,PT,Australia,S,Australia,50,"AWS, Linux, Kubernetes, Git",Associate,1,Transportation,2025-03-31,2025-05-20,1252,7.8,Algorithmic Solutions +AI07334,Robotics Engineer,121147,USD,121147,SE,FL,Sweden,S,Sweden,50,"SQL, TensorFlow, Java, Scala",Associate,8,Retail,2025-02-22,2025-03-28,1565,9.6,Algorithmic Solutions +AI07335,AI Architect,246001,USD,246001,EX,FL,Ireland,M,Ireland,100,"Mathematics, GCP, SQL",Associate,17,Technology,2025-01-31,2025-03-07,955,6.3,Neural Networks Co +AI07336,Principal Data Scientist,52336,USD,52336,EN,PT,Israel,M,Israel,0,"Data Visualization, Statistics, NLP, Python, Computer Vision",Master,1,Government,2024-12-20,2025-02-01,1645,8.1,Machine Intelligence Group +AI07337,ML Ops Engineer,43262,EUR,36773,EN,PT,France,S,France,100,"Java, Git, Kubernetes, Python",Master,0,Transportation,2024-11-14,2025-01-11,639,5,Cloud AI Solutions +AI07338,Research Scientist,107059,EUR,91000,MI,PT,France,L,France,50,"Python, Java, NLP, AWS",Bachelor,4,Real Estate,2024-05-04,2024-05-18,654,5.4,Machine Intelligence Group +AI07339,Autonomous Systems Engineer,77881,EUR,66199,MI,CT,France,S,Sweden,0,"GCP, Java, Python, Deep Learning",Bachelor,3,Consulting,2024-08-15,2024-09-21,1815,5.6,Cognitive Computing +AI07340,Head of AI,77351,CAD,96689,MI,PT,Canada,M,Italy,0,"PyTorch, TensorFlow, MLOps",Associate,2,Finance,2024-03-15,2024-04-25,1356,9.2,Cloud AI Solutions +AI07341,Principal Data Scientist,148317,USD,148317,EX,FT,United States,S,China,0,"MLOps, Tableau, Python, Docker, Linux",Bachelor,10,Government,2024-01-12,2024-02-04,1930,9.4,Neural Networks Co +AI07342,AI Research Scientist,185184,CHF,166666,SE,FL,Switzerland,M,Switzerland,0,"MLOps, Mathematics, Python, TensorFlow",PhD,9,Healthcare,2024-11-01,2024-12-22,1638,6.6,Quantum Computing Inc +AI07343,AI Consultant,215064,EUR,182804,EX,CT,Austria,L,Austria,50,"PyTorch, SQL, Spark, Computer Vision, Mathematics",PhD,11,Telecommunications,2024-07-12,2024-07-26,581,8.7,Algorithmic Solutions +AI07344,Deep Learning Engineer,38054,USD,38054,EN,FL,South Korea,S,South Korea,100,"Computer Vision, Kubernetes, Mathematics",Associate,0,Government,2024-12-07,2024-12-23,1966,7.2,Predictive Systems +AI07345,Data Engineer,297668,SGD,386968,EX,FT,Singapore,L,Ireland,50,"Kubernetes, SQL, Docker",Master,16,Healthcare,2025-04-16,2025-05-04,1714,7.5,Digital Transformation LLC +AI07346,Machine Learning Engineer,72953,SGD,94839,EN,FT,Singapore,S,Russia,0,"Deep Learning, Data Visualization, Hadoop",Bachelor,1,Consulting,2024-08-17,2024-10-20,706,8.1,AI Innovations +AI07347,ML Ops Engineer,145761,EUR,123897,SE,FT,Netherlands,L,Netherlands,50,"Linux, Hadoop, Mathematics",PhD,8,Healthcare,2024-03-16,2024-04-01,756,5.4,DeepTech Ventures +AI07348,Computer Vision Engineer,203224,USD,203224,SE,PT,Norway,L,Norway,0,"AWS, Azure, Hadoop, Spark",Associate,6,Energy,2024-07-26,2024-08-27,1287,7.6,DataVision Ltd +AI07349,Computer Vision Engineer,242702,EUR,206297,EX,CT,Netherlands,L,Netherlands,0,"SQL, AWS, Computer Vision, Kubernetes, Spark",Associate,14,Finance,2024-05-31,2024-08-10,882,8.1,Smart Analytics +AI07350,Machine Learning Engineer,46733,CAD,58416,EN,FT,Canada,S,Canada,0,"GCP, Linux, Hadoop",Master,0,Automotive,2024-09-16,2024-11-07,698,9.2,Digital Transformation LLC +AI07351,Machine Learning Researcher,85044,USD,85044,MI,CT,Norway,S,Norway,0,"Computer Vision, Linux, SQL, TensorFlow",Master,2,Transportation,2024-09-14,2024-09-28,933,5.4,Machine Intelligence Group +AI07352,AI Specialist,90679,EUR,77077,MI,PT,France,L,Sweden,0,"PyTorch, Deep Learning, Azure, Computer Vision",Associate,4,Technology,2024-09-25,2024-11-05,2118,6.7,Quantum Computing Inc +AI07353,ML Ops Engineer,81449,EUR,69232,MI,CT,Netherlands,M,Netherlands,0,"Linux, Java, Computer Vision",Associate,2,Transportation,2024-09-17,2024-11-27,1721,8.7,Autonomous Tech +AI07354,ML Ops Engineer,79173,EUR,67297,EN,CT,France,L,France,50,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Energy,2025-01-10,2025-03-19,1994,7.1,Quantum Computing Inc +AI07355,Machine Learning Researcher,266789,USD,266789,EX,FL,Denmark,M,Denmark,100,"Kubernetes, Linux, Tableau, TensorFlow",PhD,16,Government,2024-08-28,2024-10-23,693,9.9,Machine Intelligence Group +AI07356,Machine Learning Researcher,170028,CHF,153025,SE,FL,Switzerland,S,Switzerland,50,"Azure, Deep Learning, Tableau, R",Associate,8,Gaming,2024-10-10,2024-12-10,1166,7.2,Predictive Systems +AI07357,AI Software Engineer,26042,USD,26042,EN,PT,India,L,Vietnam,50,"Kubernetes, Git, Mathematics, Python",PhD,0,Transportation,2025-01-01,2025-02-25,2059,5.7,Cognitive Computing +AI07358,NLP Engineer,192917,EUR,163979,EX,PT,France,M,France,50,"Kubernetes, Linux, GCP, Java, R",Bachelor,15,Consulting,2025-04-16,2025-05-10,1803,9.1,DataVision Ltd +AI07359,Head of AI,106638,USD,106638,MI,CT,Finland,L,Czech Republic,100,"Kubernetes, MLOps, Deep Learning, Python",Bachelor,2,Finance,2024-07-26,2024-08-09,1911,9.4,DataVision Ltd +AI07360,Machine Learning Researcher,76474,USD,76474,EX,FL,India,M,India,50,"Git, Statistics, Computer Vision, Deep Learning, R",Bachelor,10,Energy,2024-01-14,2024-02-27,585,7.9,Quantum Computing Inc +AI07361,AI Architect,177950,USD,177950,SE,FT,United States,M,United States,50,"TensorFlow, R, AWS, Mathematics, Computer Vision",PhD,5,Media,2024-11-04,2024-12-09,2298,6.1,Advanced Robotics +AI07362,Machine Learning Researcher,104483,CHF,94035,MI,FL,Switzerland,S,Switzerland,50,"MLOps, Kubernetes, Tableau, Hadoop, Mathematics",Associate,2,Healthcare,2024-10-19,2024-12-13,2315,6.7,Smart Analytics +AI07363,ML Ops Engineer,64384,JPY,7082240,EN,FL,Japan,L,Turkey,0,"Python, TensorFlow, MLOps, GCP",Associate,1,Education,2024-12-06,2024-12-20,1208,6.2,Cognitive Computing +AI07364,AI Consultant,50482,SGD,65627,EN,PT,Singapore,S,Singapore,100,"PyTorch, Hadoop, Deep Learning",Associate,1,Real Estate,2024-09-22,2024-11-01,2204,7.6,Algorithmic Solutions +AI07365,Data Scientist,151120,EUR,128452,SE,FL,Germany,L,Germany,50,"Linux, R, SQL, Spark, TensorFlow",Bachelor,5,Healthcare,2024-08-11,2024-09-26,1422,8.1,Autonomous Tech +AI07366,AI Research Scientist,145148,USD,145148,MI,FL,Norway,L,Norway,50,"TensorFlow, Spark, Computer Vision, Linux",Associate,3,Media,2025-03-06,2025-04-15,2298,8,Algorithmic Solutions +AI07367,Machine Learning Researcher,46232,CAD,57790,EN,PT,Canada,S,Canada,100,"Data Visualization, Azure, PyTorch",Master,0,Telecommunications,2024-07-28,2024-09-01,1275,8.8,Quantum Computing Inc +AI07368,Data Engineer,192522,CAD,240653,EX,FT,Canada,L,Canada,100,"Kubernetes, GCP, AWS, Git, NLP",Master,10,Finance,2024-10-19,2024-12-31,2175,8.2,Algorithmic Solutions +AI07369,Machine Learning Researcher,227433,USD,227433,EX,FT,Sweden,L,Sweden,0,"Python, R, SQL",Associate,18,Government,2024-10-07,2024-11-11,543,7.2,DeepTech Ventures +AI07370,Data Analyst,104134,USD,104134,SE,PT,Finland,M,Finland,0,"AWS, Git, Java, Azure, Python",Associate,5,Energy,2024-11-17,2024-12-20,1295,7.5,Cloud AI Solutions +AI07371,Computer Vision Engineer,193260,USD,193260,SE,PT,Norway,L,Norway,0,"Computer Vision, Data Visualization, Python",Master,7,Finance,2024-06-01,2024-08-04,1662,8.4,Digital Transformation LLC +AI07372,AI Research Scientist,215088,EUR,182825,EX,CT,Germany,M,Germany,50,"Scala, NLP, R, GCP, Python",Associate,15,Gaming,2024-01-20,2024-03-26,1288,6.2,Machine Intelligence Group +AI07373,Autonomous Systems Engineer,74692,USD,74692,MI,FT,Sweden,M,Sweden,0,"SQL, Linux, Statistics",Associate,4,Technology,2024-05-28,2024-08-05,1682,7.3,DataVision Ltd +AI07374,Deep Learning Engineer,89378,EUR,75971,MI,FT,France,S,France,50,"Linux, GCP, Computer Vision",Bachelor,2,Technology,2024-10-01,2024-12-05,2365,5,Advanced Robotics +AI07375,AI Consultant,222964,USD,222964,EX,FL,Finland,L,Colombia,0,"R, Spark, Linux, Java",Bachelor,17,Finance,2024-10-15,2024-12-04,1826,6.1,Machine Intelligence Group +AI07376,Robotics Engineer,219494,USD,219494,EX,CT,Ireland,L,Hungary,50,"AWS, Azure, SQL, Statistics, Git",Associate,17,Transportation,2024-07-05,2024-08-21,996,5.5,Neural Networks Co +AI07377,AI Research Scientist,132643,EUR,112747,SE,CT,Netherlands,M,Netherlands,50,"TensorFlow, NLP, Linux, GCP, Data Visualization",Associate,9,Telecommunications,2024-07-08,2024-09-03,920,8.3,AI Innovations +AI07378,Data Engineer,54621,USD,54621,EX,PT,India,M,Brazil,0,"Hadoop, Python, R, SQL",Associate,18,Real Estate,2024-07-08,2024-08-09,1912,5.8,DataVision Ltd +AI07379,Deep Learning Engineer,149274,GBP,111956,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, Java, PyTorch, Spark, Docker",PhD,5,Energy,2024-11-02,2025-01-09,834,5.2,Cloud AI Solutions +AI07380,AI Software Engineer,79871,SGD,103832,EN,FL,Singapore,L,Singapore,50,"MLOps, SQL, Azure, Mathematics",PhD,0,Retail,2025-04-30,2025-05-18,2489,5.3,Algorithmic Solutions +AI07381,Data Engineer,240902,USD,240902,EX,PT,Sweden,M,Philippines,100,"GCP, Data Visualization, Python",PhD,12,Automotive,2025-01-05,2025-01-23,1762,7.9,DeepTech Ventures +AI07382,Principal Data Scientist,88819,CAD,111024,MI,FL,Canada,M,Canada,100,"Kubernetes, PyTorch, Git",PhD,3,Gaming,2025-01-26,2025-03-13,1594,8.5,Smart Analytics +AI07383,AI Software Engineer,245168,JPY,26968480,EX,FT,Japan,L,Norway,100,"SQL, AWS, Linux, Spark",PhD,11,Telecommunications,2024-10-04,2024-11-17,1753,7,Machine Intelligence Group +AI07384,Research Scientist,226851,USD,226851,EX,FL,Finland,L,Finland,50,"Azure, Linux, Data Visualization, Git, Kubernetes",Associate,17,Consulting,2025-01-17,2025-03-15,1652,9.6,DataVision Ltd +AI07385,AI Architect,65693,USD,65693,MI,PT,South Korea,M,Russia,50,"Linux, Hadoop, Computer Vision",Bachelor,2,Energy,2024-02-22,2024-03-10,910,8.2,Cloud AI Solutions +AI07386,Computer Vision Engineer,173491,EUR,147467,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, Mathematics, Statistics",PhD,9,Gaming,2025-04-01,2025-06-09,515,8.3,AI Innovations +AI07387,Head of AI,78460,CAD,98075,MI,PT,Canada,M,Argentina,50,"Scala, Hadoop, Deep Learning",Bachelor,3,Automotive,2025-01-16,2025-03-30,2303,5.9,Cloud AI Solutions +AI07388,AI Specialist,87156,USD,87156,MI,FT,Sweden,M,Czech Republic,0,"Computer Vision, Scala, Python, TensorFlow",PhD,2,Transportation,2024-03-27,2024-05-18,2028,8.5,AI Innovations +AI07389,Data Engineer,251231,CHF,226108,EX,PT,Switzerland,S,Switzerland,100,"Docker, Linux, Python, Data Visualization, TensorFlow",PhD,17,Media,2024-03-28,2024-05-17,1025,8.3,AI Innovations +AI07390,Data Engineer,75609,USD,75609,EN,FT,Denmark,M,Denmark,50,"Docker, Spark, R, Hadoop",PhD,1,Gaming,2025-04-20,2025-06-25,1240,9.5,Predictive Systems +AI07391,Data Scientist,85774,USD,85774,MI,CT,Sweden,M,Latvia,50,"MLOps, Linux, Mathematics",Bachelor,4,Telecommunications,2024-05-04,2024-07-03,1310,6.9,Smart Analytics +AI07392,Robotics Engineer,270769,USD,270769,EX,PT,Israel,L,Israel,100,"Kubernetes, R, MLOps",PhD,14,Gaming,2025-01-07,2025-03-21,1665,9.4,DataVision Ltd +AI07393,Data Scientist,56999,USD,56999,EN,CT,United States,S,United States,50,"Spark, Data Visualization, AWS, Kubernetes, Hadoop",Associate,1,Transportation,2024-07-25,2024-08-28,1690,5.6,Smart Analytics +AI07394,ML Ops Engineer,95205,EUR,80924,SE,PT,Germany,S,Germany,0,"Python, Scala, MLOps, Statistics",Associate,5,Real Estate,2024-01-19,2024-02-09,923,7.5,Future Systems +AI07395,Data Analyst,116878,USD,116878,SE,FL,South Korea,L,South Korea,100,"Python, TensorFlow, Data Visualization, Computer Vision, Azure",PhD,8,Telecommunications,2024-07-27,2024-10-03,1058,8.2,DataVision Ltd +AI07396,Autonomous Systems Engineer,92083,CAD,115104,MI,FT,Canada,S,Canada,0,"Kubernetes, Linux, R",Bachelor,3,Finance,2024-05-25,2024-07-02,1467,7,Digital Transformation LLC +AI07397,Head of AI,89908,USD,89908,EN,FT,Denmark,L,Denmark,50,"Git, Azure, SQL, Kubernetes",Bachelor,1,Media,2024-01-26,2024-03-01,989,9.4,AI Innovations +AI07398,AI Architect,82155,EUR,69832,MI,CT,France,M,France,50,"Linux, Git, Computer Vision, PyTorch",Associate,2,Real Estate,2024-05-16,2024-06-21,2168,5.9,Future Systems +AI07399,Research Scientist,250839,USD,250839,EX,FT,Finland,L,Finland,100,"SQL, Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,15,Real Estate,2024-02-08,2024-03-25,1727,6.1,Future Systems +AI07400,Autonomous Systems Engineer,141610,USD,141610,SE,FT,United States,L,United States,100,"Python, TensorFlow, Data Visualization, MLOps",PhD,7,Manufacturing,2025-02-07,2025-03-15,2115,8.5,Predictive Systems +AI07401,ML Ops Engineer,134017,USD,134017,SE,FT,Denmark,S,Denmark,0,"Linux, SQL, Statistics, R",PhD,9,Government,2025-02-14,2025-03-31,1735,5.1,Advanced Robotics +AI07402,AI Specialist,287847,EUR,244670,EX,FL,Netherlands,L,Netherlands,100,"SQL, TensorFlow, PyTorch",Master,19,Manufacturing,2024-09-22,2024-10-20,1149,5.7,DataVision Ltd +AI07403,AI Research Scientist,72341,USD,72341,EX,FT,India,M,Turkey,100,"GCP, Computer Vision, Spark, Java, R",Bachelor,15,Telecommunications,2024-08-11,2024-09-10,2228,8,AI Innovations +AI07404,ML Ops Engineer,196644,EUR,167147,EX,CT,France,S,Turkey,0,"GCP, Computer Vision, Data Visualization, Scala",Bachelor,16,Finance,2024-07-11,2024-08-16,2103,5.2,DataVision Ltd +AI07405,AI Consultant,80695,GBP,60521,MI,FT,United Kingdom,M,United Kingdom,100,"NLP, Computer Vision, PyTorch, TensorFlow",Bachelor,4,Manufacturing,2025-02-13,2025-03-05,1974,5.5,Autonomous Tech +AI07406,Robotics Engineer,112650,USD,112650,EN,FL,Denmark,L,Denmark,50,"Kubernetes, Hadoop, Mathematics, Git",Associate,0,Transportation,2024-03-12,2024-04-20,1124,7,Algorithmic Solutions +AI07407,AI Product Manager,138862,USD,138862,MI,FT,United States,L,United States,50,"Hadoop, Mathematics, MLOps",Associate,3,Transportation,2024-07-18,2024-08-03,1894,6.7,Quantum Computing Inc +AI07408,Machine Learning Engineer,92680,CHF,83412,EN,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, MLOps, SQL, Deep Learning",Bachelor,1,Real Estate,2024-05-10,2024-07-01,974,8.1,Cognitive Computing +AI07409,AI Software Engineer,106542,USD,106542,EN,CT,United States,L,United States,0,"Scala, PyTorch, Data Visualization, Tableau",Bachelor,0,Healthcare,2024-05-16,2024-06-19,1892,5.1,Advanced Robotics +AI07410,Machine Learning Engineer,57987,EUR,49289,EN,CT,Germany,S,United States,0,"Docker, Mathematics, TensorFlow",PhD,0,Manufacturing,2025-04-15,2025-05-07,2129,8.9,DeepTech Ventures +AI07411,Machine Learning Engineer,224659,USD,224659,EX,PT,Finland,L,Vietnam,50,"SQL, PyTorch, Kubernetes",Associate,15,Education,2024-08-30,2024-09-14,585,6.2,Quantum Computing Inc +AI07412,AI Consultant,223546,CHF,201191,EX,FT,Switzerland,M,South Korea,100,"TensorFlow, Azure, AWS, GCP, MLOps",PhD,12,Retail,2024-07-08,2024-08-07,1511,9,Digital Transformation LLC +AI07413,AI Research Scientist,151758,CHF,136582,MI,CT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Azure, Computer Vision, NLP",Master,3,Education,2024-04-09,2024-05-05,946,9.4,Quantum Computing Inc +AI07414,AI Specialist,46742,USD,46742,EN,CT,Sweden,S,Italy,50,"NLP, Deep Learning, SQL, Tableau, Hadoop",Master,1,Retail,2024-04-24,2024-07-06,1123,6.7,Algorithmic Solutions +AI07415,AI Software Engineer,159242,USD,159242,EX,PT,Finland,S,Finland,100,"Kubernetes, Deep Learning, Data Visualization, GCP",Associate,10,Real Estate,2024-12-31,2025-02-08,1926,6.1,Future Systems +AI07416,Data Analyst,87254,USD,87254,EN,FT,Norway,S,Brazil,0,"Hadoop, Scala, Data Visualization, SQL",Associate,1,Retail,2024-08-12,2024-10-08,992,6.8,Cloud AI Solutions +AI07417,AI Research Scientist,62366,USD,62366,EN,CT,Finland,M,Singapore,50,"Spark, SQL, Hadoop, AWS",PhD,1,Gaming,2024-02-21,2024-04-02,1969,5.4,Cognitive Computing +AI07418,Data Scientist,194278,USD,194278,SE,FL,Norway,L,Israel,50,"Java, Statistics, Deep Learning, Tableau",Master,7,Media,2024-10-24,2024-12-09,809,8.9,Autonomous Tech +AI07419,AI Product Manager,107060,SGD,139178,SE,CT,Singapore,S,Singapore,100,"Statistics, R, Spark, Deep Learning, Linux",PhD,9,Retail,2025-01-31,2025-04-09,884,9.5,Machine Intelligence Group +AI07420,AI Product Manager,125649,USD,125649,SE,FL,Ireland,L,Ireland,50,"Linux, Spark, Data Visualization, NLP",PhD,5,Automotive,2025-03-29,2025-06-06,1974,10,Machine Intelligence Group +AI07421,AI Architect,151908,USD,151908,EX,PT,Sweden,M,Sweden,100,"Tableau, Computer Vision, PyTorch, SQL, Python",Bachelor,10,Gaming,2024-02-24,2024-05-01,1600,9.1,Machine Intelligence Group +AI07422,ML Ops Engineer,207008,CHF,186307,SE,CT,Switzerland,M,Switzerland,0,"Hadoop, MLOps, Deep Learning, GCP",PhD,7,Retail,2024-05-05,2024-06-01,1235,9,Smart Analytics +AI07423,Data Scientist,93359,CHF,84023,EN,CT,Switzerland,S,Switzerland,100,"Linux, Kubernetes, SQL, Java, Deep Learning",Bachelor,1,Telecommunications,2025-01-02,2025-02-02,1179,9.9,TechCorp Inc +AI07424,AI Research Scientist,102494,AUD,138367,MI,FL,Australia,L,Australia,0,"SQL, R, Mathematics, Linux",Master,4,Automotive,2024-07-18,2024-08-23,1974,5.4,Cloud AI Solutions +AI07425,NLP Engineer,82281,EUR,69939,MI,FL,France,M,France,50,"SQL, Spark, Hadoop",PhD,4,Technology,2024-08-16,2024-09-18,828,6,Algorithmic Solutions +AI07426,Deep Learning Engineer,148607,USD,148607,SE,FT,Finland,L,Finland,0,"Git, Spark, NLP, Computer Vision",Bachelor,9,Finance,2024-10-18,2024-11-04,1627,8.7,AI Innovations +AI07427,Autonomous Systems Engineer,97107,USD,97107,MI,FL,Finland,M,Finland,50,"PyTorch, NLP, Kubernetes, Azure",PhD,4,Finance,2025-01-23,2025-03-19,596,7.2,Neural Networks Co +AI07428,Data Engineer,156750,USD,156750,SE,CT,Norway,S,Norway,50,"Java, Tableau, Scala",PhD,6,Gaming,2024-06-24,2024-07-20,617,6.3,Future Systems +AI07429,Data Scientist,43046,USD,43046,MI,CT,China,M,Mexico,100,"Hadoop, Kubernetes, NLP",Master,4,Telecommunications,2024-07-28,2024-09-04,532,7.9,Advanced Robotics +AI07430,Autonomous Systems Engineer,259249,CAD,324061,EX,FL,Canada,L,Canada,50,"Data Visualization, Linux, SQL, R",Master,13,Real Estate,2024-11-16,2025-01-19,1880,8.9,Neural Networks Co +AI07431,Research Scientist,76203,USD,76203,MI,FT,Sweden,S,Sweden,0,"TensorFlow, R, Git, AWS, Computer Vision",PhD,2,Government,2024-01-09,2024-03-20,2304,9,Predictive Systems +AI07432,Data Engineer,145647,USD,145647,SE,PT,Denmark,M,Philippines,100,"Data Visualization, TensorFlow, Kubernetes, NLP, Deep Learning",PhD,8,Transportation,2024-07-05,2024-09-09,1327,8.5,Algorithmic Solutions +AI07433,AI Specialist,61066,EUR,51906,EN,CT,Netherlands,S,Portugal,0,"Scala, Computer Vision, Python, Docker, TensorFlow",Master,1,Technology,2024-03-15,2024-05-11,2259,6.9,Digital Transformation LLC +AI07434,AI Specialist,186576,USD,186576,SE,CT,Norway,M,Norway,100,"Git, Azure, Data Visualization, PyTorch",PhD,6,Automotive,2025-04-15,2025-06-04,1906,8.8,TechCorp Inc +AI07435,Machine Learning Researcher,132277,USD,132277,SE,CT,Ireland,L,Ireland,0,"Docker, GCP, Linux",Bachelor,9,Telecommunications,2024-04-04,2024-05-05,820,8.4,Machine Intelligence Group +AI07436,NLP Engineer,170334,USD,170334,SE,FL,United States,M,Poland,50,"Spark, R, Git",Bachelor,7,Retail,2025-02-01,2025-03-04,807,6,Cognitive Computing +AI07437,AI Research Scientist,124463,USD,124463,SE,CT,South Korea,M,South Korea,100,"TensorFlow, SQL, NLP, MLOps, Deep Learning",PhD,8,Finance,2024-04-24,2024-05-19,2246,6.2,Cognitive Computing +AI07438,AI Specialist,82706,USD,82706,MI,CT,Sweden,S,Sweden,50,"MLOps, Deep Learning, TensorFlow, NLP",PhD,4,Healthcare,2024-11-15,2025-01-18,756,9,Cognitive Computing +AI07439,AI Architect,250961,CHF,225865,EX,FL,Switzerland,M,Switzerland,100,"Spark, MLOps, Kubernetes, Linux",Bachelor,13,Real Estate,2024-04-07,2024-05-06,1666,9.8,Neural Networks Co +AI07440,AI Consultant,77065,EUR,65505,EN,CT,Germany,L,Denmark,50,"TensorFlow, SQL, AWS",PhD,0,Automotive,2025-04-28,2025-06-26,2078,5.5,Autonomous Tech +AI07441,AI Consultant,60980,AUD,82323,EN,FL,Australia,M,Norway,100,"Python, NLP, TensorFlow, Deep Learning",PhD,1,Energy,2024-10-27,2024-11-30,1528,7.9,Algorithmic Solutions +AI07442,Principal Data Scientist,122642,JPY,13490620,SE,FT,Japan,M,Canada,0,"MLOps, Java, Data Visualization, Hadoop, Python",Associate,6,Automotive,2024-09-04,2024-11-04,1486,8.7,Smart Analytics +AI07443,Machine Learning Researcher,126416,USD,126416,MI,FT,Norway,S,Norway,0,"Spark, Mathematics, Python",Master,2,Retail,2024-06-03,2024-07-07,1354,7.2,DataVision Ltd +AI07444,Data Analyst,43069,USD,43069,EN,FT,China,L,China,50,"Java, Python, Git, Spark, TensorFlow",Bachelor,1,Real Estate,2024-05-15,2024-07-09,2034,8.9,Autonomous Tech +AI07445,AI Product Manager,191754,SGD,249280,EX,FL,Singapore,L,Singapore,0,"Spark, MLOps, Docker, NLP, TensorFlow",Master,19,Manufacturing,2024-01-26,2024-03-13,1056,6.3,Future Systems +AI07446,Principal Data Scientist,89978,SGD,116971,MI,PT,Singapore,S,Singapore,100,"PyTorch, TensorFlow, Data Visualization, Computer Vision",PhD,4,Gaming,2025-03-19,2025-05-31,2223,6.2,Predictive Systems +AI07447,Deep Learning Engineer,69497,SGD,90346,EN,CT,Singapore,M,Singapore,0,"Tableau, Python, TensorFlow, NLP, Computer Vision",Associate,1,Education,2024-11-02,2024-12-27,2304,7,Digital Transformation LLC +AI07448,NLP Engineer,68144,CAD,85180,EN,CT,Canada,L,Poland,100,"Kubernetes, Scala, GCP, Docker, Hadoop",PhD,0,Gaming,2024-09-03,2024-11-09,1002,5.6,Predictive Systems +AI07449,Machine Learning Researcher,245939,JPY,27053290,EX,FL,Japan,L,Japan,50,"SQL, Data Visualization, Python",PhD,15,Retail,2025-04-07,2025-06-19,1029,6.1,Cloud AI Solutions +AI07450,Computer Vision Engineer,143618,EUR,122075,EX,CT,France,M,France,100,"Docker, GCP, NLP, Azure, Kubernetes",Master,12,Energy,2024-01-11,2024-03-02,1998,6.3,Cloud AI Solutions +AI07451,AI Software Engineer,118901,EUR,101066,MI,FL,Netherlands,L,Netherlands,100,"Linux, Java, Statistics",Bachelor,4,Transportation,2024-02-11,2024-03-09,2248,5.5,Algorithmic Solutions +AI07452,AI Research Scientist,31907,USD,31907,MI,PT,India,S,India,0,"MLOps, Spark, Linux, Data Visualization, NLP",PhD,4,Real Estate,2025-03-26,2025-05-25,2009,8.9,Quantum Computing Inc +AI07453,AI Specialist,165521,USD,165521,EX,PT,Sweden,M,Sweden,0,"Computer Vision, R, Linux",Master,16,Healthcare,2024-02-17,2024-03-09,993,9.5,Neural Networks Co +AI07454,Principal Data Scientist,143655,USD,143655,SE,FL,Finland,L,Finland,100,"MLOps, Spark, Java, NLP, SQL",Associate,7,Media,2024-01-01,2024-02-16,1009,5.6,DeepTech Ventures +AI07455,Data Engineer,18305,USD,18305,EN,CT,India,M,India,0,"SQL, AWS, Spark",Bachelor,1,Finance,2024-01-02,2024-01-18,1652,5.8,Autonomous Tech +AI07456,Principal Data Scientist,103388,CHF,93049,EN,PT,Switzerland,L,Israel,0,"SQL, Mathematics, Spark, TensorFlow",Associate,0,Education,2025-04-26,2025-07-06,1717,5.4,Digital Transformation LLC +AI07457,Autonomous Systems Engineer,216271,USD,216271,EX,FL,Israel,M,Israel,100,"Python, Linux, Java, TensorFlow",Master,14,Energy,2024-10-25,2024-12-10,666,6.3,Future Systems +AI07458,Autonomous Systems Engineer,54685,JPY,6015350,EN,PT,Japan,M,Japan,50,"Python, Linux, Hadoop, Data Visualization",Master,0,Media,2024-08-28,2024-11-03,1196,6.3,Neural Networks Co +AI07459,ML Ops Engineer,101910,USD,101910,SE,FT,South Korea,M,Canada,50,"Tableau, GCP, Azure",Master,6,Real Estate,2025-04-15,2025-06-11,1897,7.4,Algorithmic Solutions +AI07460,Deep Learning Engineer,232335,JPY,25556850,EX,FL,Japan,M,Japan,100,"Scala, Spark, Java, SQL",Master,19,Technology,2024-10-18,2024-12-11,606,9.1,Machine Intelligence Group +AI07461,Machine Learning Engineer,196676,GBP,147507,EX,PT,United Kingdom,S,United Kingdom,50,"Linux, Azure, TensorFlow, Tableau, PyTorch",Associate,18,Technology,2024-02-11,2024-02-29,1568,8.1,AI Innovations +AI07462,Machine Learning Engineer,97001,USD,97001,MI,PT,United States,M,Singapore,100,"PyTorch, Java, Mathematics, Deep Learning",Associate,2,Healthcare,2024-07-30,2024-08-17,1730,8.6,DeepTech Ventures +AI07463,AI Software Engineer,141916,EUR,120629,SE,FL,Germany,L,Germany,100,"Python, TensorFlow, Azure",Master,9,Manufacturing,2024-10-20,2024-11-28,2447,6.7,Advanced Robotics +AI07464,Machine Learning Engineer,58453,USD,58453,EN,FT,United States,S,Malaysia,0,"Linux, Azure, Statistics",PhD,1,Gaming,2024-01-25,2024-02-08,524,9.4,TechCorp Inc +AI07465,AI Architect,65377,EUR,55570,EN,FT,Germany,M,Germany,0,"SQL, Statistics, AWS, Docker",Master,0,Technology,2024-04-17,2024-06-19,1603,5.8,DeepTech Ventures +AI07466,Machine Learning Engineer,84606,SGD,109988,MI,FL,Singapore,S,Singapore,100,"GCP, NLP, Python, Data Visualization, Spark",Master,3,Government,2024-10-21,2024-11-08,2113,9.1,TechCorp Inc +AI07467,ML Ops Engineer,61087,EUR,51924,EN,FT,France,M,France,0,"NLP, R, MLOps",Master,0,Automotive,2025-04-26,2025-06-18,2334,6.1,Quantum Computing Inc +AI07468,NLP Engineer,66540,AUD,89829,EN,FL,Australia,M,China,0,"Spark, Docker, PyTorch, Computer Vision",PhD,0,Healthcare,2024-06-28,2024-08-14,2020,7.2,DeepTech Ventures +AI07469,Machine Learning Researcher,148528,USD,148528,SE,FT,Israel,L,Israel,0,"MLOps, Java, AWS, Deep Learning",Master,9,Telecommunications,2025-01-23,2025-03-09,874,7.4,Smart Analytics +AI07470,Deep Learning Engineer,126440,USD,126440,EX,FT,South Korea,S,South Korea,100,"R, Computer Vision, Scala, Java",Associate,18,Transportation,2024-09-04,2024-09-23,764,5.9,DataVision Ltd +AI07471,Research Scientist,117780,CHF,106002,EN,FT,Switzerland,L,Switzerland,0,"Computer Vision, Data Visualization, Linux, MLOps",Bachelor,1,Finance,2025-04-28,2025-05-21,2477,6.3,DataVision Ltd +AI07472,AI Research Scientist,129661,USD,129661,EX,FT,Finland,M,Ukraine,50,"NLP, MLOps, Python, Spark, Mathematics",Master,10,Real Estate,2024-03-02,2024-04-02,914,6.2,Smart Analytics +AI07473,Robotics Engineer,46753,EUR,39740,EN,PT,Austria,S,Austria,0,"SQL, Hadoop, Statistics, Spark",Associate,0,Manufacturing,2024-05-25,2024-07-06,1228,6.7,TechCorp Inc +AI07474,Computer Vision Engineer,43491,USD,43491,EX,FL,India,S,Vietnam,0,"Azure, TensorFlow, Scala",Bachelor,12,Healthcare,2024-10-16,2024-12-15,1489,7.5,Autonomous Tech +AI07475,AI Architect,120298,SGD,156387,MI,PT,Singapore,L,Singapore,0,"Kubernetes, Git, Spark, Linux, SQL",PhD,3,Gaming,2024-02-25,2024-04-24,890,5.4,DataVision Ltd +AI07476,ML Ops Engineer,260872,USD,260872,EX,FT,Norway,S,Norway,0,"Java, Data Visualization, MLOps",Associate,13,Education,2025-03-23,2025-04-20,1870,5.4,AI Innovations +AI07477,Robotics Engineer,71601,AUD,96661,EN,FT,Australia,S,Australia,50,"Linux, Hadoop, AWS, Python, Deep Learning",Master,0,Education,2025-04-25,2025-06-10,1267,5.9,Algorithmic Solutions +AI07478,Machine Learning Engineer,49525,USD,49525,EX,FL,India,M,Portugal,50,"Docker, Git, GCP, Scala",PhD,15,Manufacturing,2024-04-28,2024-05-20,1446,8.2,AI Innovations +AI07479,AI Research Scientist,82352,USD,82352,EN,FL,Ireland,L,Ireland,50,"GCP, Python, Computer Vision",PhD,1,Healthcare,2024-04-25,2024-05-30,1036,9.6,Neural Networks Co +AI07480,Machine Learning Researcher,238897,USD,238897,EX,CT,Norway,M,Norway,0,"Git, Linux, Statistics",Bachelor,12,Transportation,2024-05-05,2024-06-11,638,7.1,Neural Networks Co +AI07481,AI Research Scientist,64610,USD,64610,EN,CT,Israel,L,Israel,100,"Spark, Kubernetes, Linux, GCP, AWS",PhD,1,Retail,2024-06-04,2024-07-04,552,6.9,Future Systems +AI07482,Principal Data Scientist,121207,USD,121207,EX,FL,Finland,S,Finland,50,"GCP, Git, Statistics",Associate,12,Healthcare,2024-08-10,2024-09-07,1835,8.7,AI Innovations +AI07483,AI Specialist,118359,JPY,13019490,SE,FL,Japan,M,Japan,50,"MLOps, Linux, Java, TensorFlow, Python",Associate,7,Media,2024-11-13,2024-12-24,1107,6.4,Algorithmic Solutions +AI07484,NLP Engineer,176333,CHF,158700,SE,FL,Switzerland,L,Switzerland,0,"Scala, Kubernetes, Deep Learning",Bachelor,8,Education,2024-11-03,2024-11-30,1123,5.5,Cognitive Computing +AI07485,AI Consultant,137799,USD,137799,SE,CT,Ireland,M,Ireland,50,"Spark, Python, Hadoop",Associate,8,Real Estate,2024-06-20,2024-08-31,1243,7.2,Quantum Computing Inc +AI07486,AI Architect,147983,USD,147983,EX,CT,Sweden,S,Russia,50,"SQL, TensorFlow, Tableau, AWS, Mathematics",Master,16,Energy,2025-02-06,2025-04-01,1503,8.1,Quantum Computing Inc +AI07487,AI Research Scientist,44458,USD,44458,EN,FT,Finland,S,Finland,0,"Azure, Scala, Tableau",Bachelor,0,Telecommunications,2024-03-26,2024-06-06,2344,5.6,Algorithmic Solutions +AI07488,ML Ops Engineer,182046,EUR,154739,EX,CT,Netherlands,M,Netherlands,0,"Python, Java, Linux, Statistics, Deep Learning",Bachelor,17,Retail,2024-02-02,2024-04-12,2221,6,DeepTech Ventures +AI07489,Robotics Engineer,89818,SGD,116763,EN,FL,Singapore,L,Singapore,100,"Java, PyTorch, GCP, Tableau",Master,0,Gaming,2024-03-29,2024-05-26,636,5.7,Machine Intelligence Group +AI07490,NLP Engineer,154108,GBP,115581,SE,CT,United Kingdom,M,New Zealand,0,"PyTorch, Kubernetes, Computer Vision",PhD,8,Manufacturing,2025-02-15,2025-04-01,1863,9.1,Machine Intelligence Group +AI07491,Autonomous Systems Engineer,77976,USD,77976,EN,FT,Ireland,M,Ireland,0,"SQL, GCP, Java, Hadoop, Data Visualization",Associate,1,Retail,2024-06-14,2024-07-24,2169,6.7,AI Innovations +AI07492,Computer Vision Engineer,158800,AUD,214380,SE,FT,Australia,L,Australia,100,"Kubernetes, Python, NLP, R",Associate,5,Technology,2024-08-04,2024-09-29,895,5.4,Digital Transformation LLC +AI07493,AI Software Engineer,269552,CHF,242597,EX,FL,Switzerland,L,Switzerland,50,"NLP, Kubernetes, Spark",Associate,16,Retail,2024-09-26,2024-11-21,1202,8.9,Cloud AI Solutions +AI07494,ML Ops Engineer,40777,USD,40777,SE,FT,India,M,India,50,"AWS, MLOps, Java, Scala",Associate,6,Telecommunications,2024-04-21,2024-05-20,1471,9.3,Future Systems +AI07495,Data Scientist,40524,USD,40524,EN,FL,China,L,China,0,"TensorFlow, Azure, MLOps, Linux",Master,1,Government,2024-01-20,2024-03-08,1447,7.8,DeepTech Ventures +AI07496,AI Product Manager,104604,USD,104604,SE,PT,Finland,S,Mexico,100,"NLP, Docker, Data Visualization, Python",Master,8,Retail,2024-03-17,2024-05-24,1519,7.1,Neural Networks Co +AI07497,Research Scientist,108828,GBP,81621,SE,FL,United Kingdom,S,Indonesia,50,"Python, Kubernetes, MLOps, Linux, Mathematics",Bachelor,7,Real Estate,2024-11-22,2024-12-14,2377,5.6,Digital Transformation LLC +AI07498,AI Product Manager,332899,USD,332899,EX,FL,Denmark,L,Denmark,0,"GCP, SQL, PyTorch",PhD,10,Telecommunications,2024-09-23,2024-10-12,786,8.8,Digital Transformation LLC +AI07499,AI Product Manager,282331,USD,282331,EX,FL,United States,M,United States,0,"Statistics, Tableau, Python, Computer Vision, TensorFlow",PhD,17,Media,2024-09-01,2024-10-17,2115,9.5,Predictive Systems +AI07500,Robotics Engineer,50649,USD,50649,MI,FT,China,L,China,0,"Computer Vision, Git, Hadoop",PhD,3,Government,2024-05-04,2024-07-05,754,7.3,Cognitive Computing +AI07501,AI Product Manager,74786,JPY,8226460,EN,FL,Japan,S,Ukraine,100,"AWS, Statistics, R, Hadoop, TensorFlow",Associate,1,Real Estate,2024-01-11,2024-01-30,1792,8,Cognitive Computing +AI07502,Machine Learning Engineer,246647,USD,246647,EX,CT,Denmark,L,Colombia,50,"Git, Linux, Python, Deep Learning, MLOps",Bachelor,11,Telecommunications,2024-05-12,2024-06-24,1926,8.9,Neural Networks Co +AI07503,Machine Learning Engineer,219909,USD,219909,EX,CT,Norway,S,Norway,0,"SQL, Java, Scala, Spark",Bachelor,17,Media,2024-09-06,2024-10-21,798,7.7,Quantum Computing Inc +AI07504,AI Research Scientist,137360,SGD,178568,EX,PT,Singapore,S,Norway,100,"MLOps, Azure, Scala, AWS",Master,13,Media,2025-03-29,2025-05-29,1811,9.3,DeepTech Ventures +AI07505,Data Analyst,80377,USD,80377,EN,CT,Sweden,M,United States,50,"PyTorch, Hadoop, TensorFlow, Computer Vision",Master,1,Healthcare,2024-05-15,2024-06-13,1584,6,Neural Networks Co +AI07506,AI Software Engineer,150710,JPY,16578100,SE,PT,Japan,L,Japan,100,"Mathematics, Spark, Docker, Statistics",PhD,6,Automotive,2024-06-13,2024-08-14,2040,5.4,Cognitive Computing +AI07507,Head of AI,165703,USD,165703,EX,CT,Israel,L,Ireland,50,"Kubernetes, GCP, Computer Vision",Master,16,Transportation,2025-03-29,2025-05-05,1006,6,AI Innovations +AI07508,AI Product Manager,89181,USD,89181,EN,FL,Denmark,S,Singapore,0,"Python, Azure, Mathematics",PhD,0,Energy,2025-02-18,2025-03-20,875,7.7,Smart Analytics +AI07509,Robotics Engineer,179770,CHF,161793,SE,FL,Switzerland,S,Switzerland,0,"NLP, GCP, Docker, Git, Azure",Associate,6,Manufacturing,2024-09-15,2024-10-17,2220,8.3,DataVision Ltd +AI07510,Machine Learning Researcher,148095,USD,148095,SE,FL,Sweden,M,Sweden,0,"Spark, Scala, Deep Learning, Hadoop",Associate,8,Media,2024-06-17,2024-08-16,784,9.3,Predictive Systems +AI07511,AI Software Engineer,86619,USD,86619,MI,PT,United States,S,Sweden,0,"Spark, GCP, Java, R",Bachelor,4,Government,2024-01-19,2024-03-27,1171,7.7,DeepTech Ventures +AI07512,Data Engineer,94298,USD,94298,SE,FL,South Korea,S,South Korea,100,"Scala, Computer Vision, Docker, Java",Associate,6,Energy,2024-11-06,2024-12-28,1362,6.9,Predictive Systems +AI07513,Computer Vision Engineer,196323,USD,196323,SE,CT,Norway,M,Norway,0,"PyTorch, SQL, Spark, TensorFlow",Master,8,Automotive,2024-12-13,2025-01-04,1981,6.6,Predictive Systems +AI07514,Robotics Engineer,21114,USD,21114,EN,CT,India,L,India,100,"Computer Vision, SQL, Tableau",PhD,0,Energy,2025-03-21,2025-04-15,2127,5.5,Autonomous Tech +AI07515,NLP Engineer,149569,EUR,127134,SE,FL,Austria,L,Austria,100,"Kubernetes, Git, SQL",Bachelor,5,Retail,2024-04-30,2024-06-24,2372,8.1,Future Systems +AI07516,Machine Learning Engineer,103038,USD,103038,MI,FL,Sweden,M,Sweden,0,"Computer Vision, Python, Java, Tableau",PhD,2,Energy,2025-03-14,2025-05-03,1504,7.8,Smart Analytics +AI07517,Head of AI,118703,USD,118703,SE,PT,Israel,M,Israel,50,"GCP, PyTorch, Docker",Associate,5,Gaming,2024-10-09,2024-12-04,536,5.4,Smart Analytics +AI07518,AI Consultant,65083,USD,65083,EN,FL,South Korea,L,Vietnam,50,"Linux, Deep Learning, Data Visualization, TensorFlow, Kubernetes",Bachelor,1,Media,2024-05-31,2024-07-21,2356,7.8,Autonomous Tech +AI07519,Data Analyst,143495,USD,143495,SE,PT,Norway,M,Norway,100,"PyTorch, AWS, Scala, Java",PhD,8,Gaming,2024-12-31,2025-01-18,811,7.4,Autonomous Tech +AI07520,Autonomous Systems Engineer,158654,USD,158654,SE,FL,Norway,L,Norway,50,"AWS, Git, Python, GCP, Scala",Bachelor,7,Gaming,2024-10-28,2024-12-21,1527,6.8,Advanced Robotics +AI07521,Head of AI,76071,EUR,64660,MI,FL,Netherlands,S,Netherlands,100,"Kubernetes, Git, Scala, Computer Vision, Python",PhD,2,Education,2024-07-08,2024-08-14,688,8.4,TechCorp Inc +AI07522,Data Analyst,70355,USD,70355,MI,FL,Finland,M,Finland,50,"Java, Spark, Hadoop, Mathematics",Associate,2,Technology,2024-07-25,2024-08-24,2367,5.2,DeepTech Ventures +AI07523,Data Analyst,100575,CAD,125719,MI,CT,Canada,M,Canada,100,"Spark, Tableau, Azure, NLP, Mathematics",PhD,2,Manufacturing,2025-01-04,2025-01-24,1421,6.6,Advanced Robotics +AI07524,Machine Learning Researcher,137502,GBP,103127,SE,FL,United Kingdom,M,United Kingdom,50,"PyTorch, SQL, NLP",PhD,9,Manufacturing,2024-07-24,2024-09-02,1538,5.6,Quantum Computing Inc +AI07525,Data Analyst,76419,AUD,103166,EN,FT,Australia,M,Australia,0,"Python, Deep Learning, Linux, Mathematics, Kubernetes",PhD,0,Education,2024-10-13,2024-12-25,925,9.2,Algorithmic Solutions +AI07526,AI Research Scientist,76902,USD,76902,MI,PT,Finland,M,Finland,50,"TensorFlow, Kubernetes, Spark, Azure, Git",PhD,4,Education,2024-09-20,2024-10-23,2336,8.8,AI Innovations +AI07527,AI Product Manager,89926,USD,89926,EN,CT,Denmark,S,China,50,"Azure, Git, NLP, GCP, Scala",PhD,1,Retail,2024-06-11,2024-07-23,1513,7.4,Future Systems +AI07528,Research Scientist,213625,EUR,181581,EX,FT,Netherlands,S,Philippines,50,"Docker, Java, Data Visualization, TensorFlow, MLOps",Master,14,Manufacturing,2024-09-14,2024-11-13,2394,9.8,Cognitive Computing +AI07529,AI Architect,160222,EUR,136189,EX,FL,Austria,L,Austria,50,"GCP, Linux, Azure, Git",PhD,14,Transportation,2024-01-07,2024-03-03,885,8.1,Smart Analytics +AI07530,Machine Learning Engineer,35947,USD,35947,MI,FL,India,M,Spain,50,"SQL, GCP, Deep Learning",PhD,4,Finance,2024-11-28,2024-12-18,2230,5,Predictive Systems +AI07531,Research Scientist,53653,SGD,69749,EN,CT,Singapore,S,Brazil,0,"Git, Data Visualization, R, Java, GCP",Associate,1,Government,2024-10-16,2024-12-23,2404,6.5,Machine Intelligence Group +AI07532,NLP Engineer,108963,EUR,92619,SE,CT,Netherlands,M,Portugal,0,"Python, TensorFlow, NLP",Associate,7,Telecommunications,2025-01-20,2025-03-09,1210,8.2,Autonomous Tech +AI07533,AI Software Engineer,77378,USD,77378,MI,CT,South Korea,S,Estonia,0,"Spark, Computer Vision, Scala, SQL",PhD,4,Energy,2024-06-16,2024-08-12,1392,5.7,Advanced Robotics +AI07534,Machine Learning Engineer,84375,EUR,71719,MI,CT,Germany,S,Germany,0,"NLP, Data Visualization, Python, Tableau",PhD,4,Healthcare,2025-03-30,2025-05-07,2486,7.8,Advanced Robotics +AI07535,AI Architect,212229,CAD,265286,EX,CT,Canada,L,Canada,0,"NLP, Mathematics, Git, TensorFlow",Bachelor,18,Media,2024-09-30,2024-11-27,1563,8.4,TechCorp Inc +AI07536,Machine Learning Researcher,122917,USD,122917,EX,FT,Israel,S,Israel,0,"Docker, MLOps, TensorFlow, Data Visualization, Linux",PhD,14,Technology,2024-05-31,2024-07-02,1245,8,Advanced Robotics +AI07537,AI Product Manager,75040,EUR,63784,EN,CT,France,L,France,50,"Azure, Python, Linux, Java",Bachelor,0,Technology,2024-01-03,2024-01-24,843,6.2,Autonomous Tech +AI07538,Data Scientist,302015,USD,302015,EX,CT,Denmark,M,Turkey,50,"Computer Vision, GCP, Git, SQL, Hadoop",Master,11,Transportation,2024-08-11,2024-09-09,1447,5.2,TechCorp Inc +AI07539,Data Scientist,100206,EUR,85175,MI,CT,Germany,M,Germany,0,"NLP, Kubernetes, Mathematics",Bachelor,3,Finance,2024-03-24,2024-05-28,1544,6.6,TechCorp Inc +AI07540,Machine Learning Researcher,74112,CAD,92640,EN,FL,Canada,M,Turkey,100,"SQL, PyTorch, AWS, TensorFlow",Master,0,Retail,2024-06-06,2024-07-31,1498,5.6,Digital Transformation LLC +AI07541,Data Engineer,52847,USD,52847,SE,FL,India,L,India,0,"Statistics, Azure, Computer Vision, Deep Learning, SQL",Associate,9,Consulting,2024-04-22,2024-05-15,614,8.4,Future Systems +AI07542,AI Research Scientist,121952,EUR,103659,SE,CT,Austria,M,Austria,0,"Java, Scala, Spark",PhD,9,Retail,2024-02-03,2024-04-08,808,10,Smart Analytics +AI07543,AI Specialist,22932,USD,22932,EN,FT,India,M,India,0,"SQL, Kubernetes, Tableau",Bachelor,1,Technology,2024-06-08,2024-08-12,1556,7.3,Cloud AI Solutions +AI07544,Robotics Engineer,185551,USD,185551,EX,FL,Ireland,L,Sweden,50,"Azure, SQL, Data Visualization, Linux",Bachelor,12,Real Estate,2024-03-13,2024-05-13,608,6.6,Quantum Computing Inc +AI07545,NLP Engineer,144980,USD,144980,EX,FL,South Korea,M,Poland,50,"Python, Linux, AWS, Deep Learning",PhD,12,Manufacturing,2025-04-20,2025-05-24,1125,8.2,Smart Analytics +AI07546,NLP Engineer,137887,USD,137887,MI,CT,United States,L,United States,100,"NLP, Linux, Tableau",Master,4,Government,2024-04-09,2024-05-12,642,10,AI Innovations +AI07547,Principal Data Scientist,26422,USD,26422,EN,FT,China,S,Latvia,100,"Hadoop, Spark, Java, Scala",Master,0,Technology,2025-01-14,2025-01-30,1300,8.4,Future Systems +AI07548,ML Ops Engineer,92812,USD,92812,EN,FL,United States,M,United States,100,"NLP, Computer Vision, Linux",Master,0,Media,2024-12-18,2025-02-20,1521,7.3,TechCorp Inc +AI07549,AI Software Engineer,60930,USD,60930,MI,FT,South Korea,S,South Korea,0,"SQL, TensorFlow, Statistics, Git",Bachelor,3,Healthcare,2024-11-25,2025-01-23,1040,7.5,Autonomous Tech +AI07550,ML Ops Engineer,218956,USD,218956,EX,PT,Finland,M,Finland,50,"SQL, Java, Azure",PhD,18,Education,2024-01-21,2024-03-13,1594,8.8,Digital Transformation LLC +AI07551,Data Scientist,75273,USD,75273,MI,CT,Israel,M,Israel,50,"MLOps, Tableau, Spark",PhD,4,Transportation,2024-09-16,2024-10-18,801,6,Algorithmic Solutions +AI07552,Autonomous Systems Engineer,49221,USD,49221,MI,CT,China,M,China,0,"PyTorch, Hadoop, Python, SQL",Associate,2,Energy,2024-08-28,2024-10-03,1967,5.6,AI Innovations +AI07553,Robotics Engineer,199243,EUR,169357,EX,FT,Germany,L,Indonesia,0,"Docker, TensorFlow, Tableau, SQL",Bachelor,13,Energy,2024-12-31,2025-01-16,1820,9.5,Advanced Robotics +AI07554,NLP Engineer,98108,USD,98108,SE,CT,Ireland,S,Ireland,0,"Tableau, Deep Learning, Git, Python, Scala",PhD,8,Healthcare,2024-10-19,2024-12-17,710,7.6,AI Innovations +AI07555,Principal Data Scientist,251392,EUR,213683,EX,FT,France,L,France,0,"Kubernetes, PyTorch, GCP",PhD,13,Gaming,2025-04-02,2025-06-01,1365,6.9,Smart Analytics +AI07556,Head of AI,102675,SGD,133478,SE,CT,Singapore,S,South Africa,50,"Spark, Hadoop, SQL, Tableau",Associate,8,Automotive,2024-05-30,2024-06-14,2253,8.5,Machine Intelligence Group +AI07557,NLP Engineer,289291,JPY,31822010,EX,PT,Japan,L,Japan,50,"Scala, Kubernetes, R, MLOps",Master,16,Government,2024-12-13,2025-01-18,537,5.7,Quantum Computing Inc +AI07558,AI Consultant,58763,SGD,76392,EN,FT,Singapore,S,Singapore,100,"Scala, PyTorch, AWS",Master,1,Manufacturing,2024-11-21,2024-12-30,1146,8.1,Algorithmic Solutions +AI07559,Machine Learning Engineer,119668,USD,119668,SE,PT,Israel,M,Italy,0,"NLP, Kubernetes, Scala, GCP",Bachelor,8,Finance,2024-09-26,2024-11-12,986,6.9,Machine Intelligence Group +AI07560,Data Scientist,50856,AUD,68656,EN,FT,Australia,S,New Zealand,0,"Azure, NLP, Kubernetes, Scala",Associate,1,Government,2024-11-11,2024-12-02,1490,7.7,Digital Transformation LLC +AI07561,ML Ops Engineer,98859,USD,98859,MI,FT,Norway,S,Norway,50,"Computer Vision, Java, Scala",Master,3,Media,2025-04-26,2025-07-08,932,7,Predictive Systems +AI07562,Principal Data Scientist,276933,USD,276933,EX,FT,Denmark,M,Denmark,50,"Deep Learning, R, MLOps",PhD,14,Manufacturing,2024-09-28,2024-12-03,2353,9.2,Neural Networks Co +AI07563,AI Research Scientist,154287,USD,154287,SE,FT,Norway,S,Norway,0,"Linux, Statistics, NLP",PhD,7,Gaming,2024-02-06,2024-04-09,1675,5.1,Smart Analytics +AI07564,AI Product Manager,185605,EUR,157764,EX,FL,Germany,M,India,0,"SQL, Scala, Kubernetes, MLOps, Spark",Master,11,Healthcare,2024-10-13,2024-11-02,2420,7.4,Autonomous Tech +AI07565,Computer Vision Engineer,147217,AUD,198743,EX,PT,Australia,M,Australia,50,"PyTorch, Scala, Mathematics",Bachelor,13,Real Estate,2024-12-03,2025-01-23,1945,6.1,Cognitive Computing +AI07566,Machine Learning Engineer,84531,USD,84531,MI,PT,Norway,S,Norway,0,"Linux, Python, Scala, Computer Vision",Master,2,Telecommunications,2024-02-13,2024-03-23,967,8.9,Autonomous Tech +AI07567,AI Specialist,188423,GBP,141317,EX,CT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Git, NLP",Bachelor,13,Manufacturing,2024-10-22,2024-11-23,2357,6.3,Advanced Robotics +AI07568,Machine Learning Engineer,93853,USD,93853,EN,PT,United States,L,Norway,50,"Docker, Kubernetes, AWS, Tableau",Associate,1,Real Estate,2025-01-22,2025-03-03,1530,9.7,Smart Analytics +AI07569,AI Software Engineer,173348,USD,173348,EX,FL,South Korea,L,South Korea,100,"NLP, Linux, SQL",Master,13,Gaming,2025-02-23,2025-04-19,786,6.3,TechCorp Inc +AI07570,Computer Vision Engineer,81621,EUR,69378,MI,CT,France,S,Ghana,100,"Java, NLP, R, Docker, Tableau",PhD,4,Technology,2024-08-04,2024-09-11,2069,7.6,DeepTech Ventures +AI07571,Machine Learning Researcher,171427,USD,171427,EX,FL,Finland,S,Chile,0,"Python, Spark, Docker, Computer Vision",Master,12,Retail,2024-08-07,2024-09-19,1068,9.8,Machine Intelligence Group +AI07572,AI Architect,124261,USD,124261,MI,CT,United States,M,United States,100,"Computer Vision, Java, PyTorch, Git, Linux",PhD,4,Technology,2025-03-02,2025-05-12,1411,8.5,TechCorp Inc +AI07573,Autonomous Systems Engineer,78038,GBP,58529,MI,CT,United Kingdom,M,United Kingdom,100,"Mathematics, Hadoop, R",Master,3,Technology,2024-01-16,2024-02-19,1335,9.3,AI Innovations +AI07574,NLP Engineer,84616,JPY,9307760,MI,FL,Japan,S,Japan,50,"Statistics, R, Computer Vision",PhD,2,Automotive,2025-03-09,2025-03-26,757,6.8,AI Innovations +AI07575,Deep Learning Engineer,56130,USD,56130,EN,CT,Ireland,S,Ireland,50,"NLP, Deep Learning, R, SQL, MLOps",PhD,1,Transportation,2025-04-04,2025-06-12,984,7.1,Algorithmic Solutions +AI07576,Principal Data Scientist,180941,EUR,153800,EX,FL,Austria,L,Vietnam,50,"Deep Learning, NLP, Python",Master,15,Education,2024-12-22,2025-01-15,1773,5.9,Smart Analytics +AI07577,Robotics Engineer,36195,USD,36195,MI,PT,India,M,Spain,0,"Kubernetes, Linux, Git, Python",PhD,2,Technology,2024-02-04,2024-02-22,1586,9.2,Quantum Computing Inc +AI07578,Machine Learning Researcher,74934,USD,74934,EN,FT,Denmark,M,Denmark,100,"GCP, PyTorch, Tableau, Deep Learning",Associate,1,Finance,2024-01-30,2024-02-16,2411,6.4,Neural Networks Co +AI07579,Data Analyst,92668,EUR,78768,MI,FL,France,S,France,0,"Python, Hadoop, Data Visualization, Git, Docker",Bachelor,3,Gaming,2024-05-03,2024-06-03,2476,7.3,Digital Transformation LLC +AI07580,ML Ops Engineer,106319,AUD,143531,MI,PT,Australia,M,Australia,0,"SQL, NLP, MLOps, Hadoop",Associate,4,Media,2025-02-19,2025-04-25,655,5.5,Cognitive Computing +AI07581,AI Product Manager,119428,USD,119428,SE,FT,Finland,L,Finland,50,"Java, GCP, Hadoop, Data Visualization, R",Bachelor,5,Technology,2024-01-10,2024-01-24,2417,9.7,Neural Networks Co +AI07582,Research Scientist,148430,JPY,16327300,EX,CT,Japan,S,Japan,100,"Git, Spark, TensorFlow, SQL, Deep Learning",PhD,18,Automotive,2024-04-18,2024-06-23,907,8.3,Neural Networks Co +AI07583,AI Software Engineer,97277,EUR,82685,SE,FT,France,S,India,0,"Mathematics, Kubernetes, Tableau, NLP",Master,5,Technology,2024-07-22,2024-08-26,2242,5.7,Cloud AI Solutions +AI07584,Head of AI,22873,USD,22873,EN,PT,India,S,India,0,"Python, Computer Vision, Git, TensorFlow",Associate,0,Telecommunications,2025-01-15,2025-02-08,1699,8,Digital Transformation LLC +AI07585,Principal Data Scientist,78064,EUR,66354,MI,PT,Germany,M,Germany,100,"Hadoop, Git, Statistics",Master,4,Technology,2025-01-25,2025-02-08,974,8.5,AI Innovations +AI07586,AI Research Scientist,29207,USD,29207,EN,FL,China,S,China,50,"SQL, Kubernetes, MLOps",Associate,1,Energy,2024-02-19,2024-04-11,893,8.4,DeepTech Ventures +AI07587,ML Ops Engineer,171296,EUR,145602,SE,CT,Netherlands,L,Kenya,0,"Hadoop, Spark, Docker, Azure, Scala",Master,7,Automotive,2024-10-22,2024-11-10,1712,6.6,Machine Intelligence Group +AI07588,Data Engineer,60437,USD,60437,EN,CT,Israel,L,Israel,100,"Java, TensorFlow, Docker, Computer Vision",Associate,1,Transportation,2024-03-28,2024-04-18,975,8.4,Algorithmic Solutions +AI07589,AI Specialist,106204,SGD,138065,SE,PT,Singapore,S,Singapore,100,"Python, Kubernetes, AWS",Bachelor,5,Retail,2024-07-01,2024-09-01,1199,7.2,Advanced Robotics +AI07590,NLP Engineer,30321,USD,30321,MI,FT,India,M,India,100,"Data Visualization, Java, Docker, Python",Bachelor,4,Consulting,2024-08-27,2024-09-13,1329,9.5,Cloud AI Solutions +AI07591,Head of AI,189953,EUR,161460,EX,CT,Austria,L,Austria,0,"Spark, SQL, Data Visualization, Deep Learning",Associate,10,Real Estate,2025-01-01,2025-02-04,1500,8.9,Smart Analytics +AI07592,Machine Learning Researcher,54381,EUR,46224,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, Statistics, Azure, Scala",Bachelor,0,Automotive,2024-06-23,2024-08-30,942,5.9,Cognitive Computing +AI07593,Machine Learning Researcher,88330,JPY,9716300,EN,FT,Japan,L,Japan,0,"MLOps, Hadoop, SQL, Git, AWS",Associate,0,Healthcare,2025-03-10,2025-04-29,1145,8.1,Cognitive Computing +AI07594,AI Product Manager,154426,USD,154426,SE,FT,Sweden,L,Thailand,100,"Computer Vision, Tableau, MLOps, SQL",Bachelor,7,Education,2024-02-16,2024-03-09,1855,7.6,Digital Transformation LLC +AI07595,AI Software Engineer,119526,EUR,101597,SE,PT,Netherlands,S,Netherlands,50,"Java, Kubernetes, Spark, Mathematics",Master,6,Media,2025-03-21,2025-04-19,2244,8,Cognitive Computing +AI07596,AI Architect,137197,USD,137197,SE,FT,Denmark,M,Vietnam,0,"Java, Docker, PyTorch, AWS, Hadoop",Associate,6,Healthcare,2024-12-25,2025-02-19,1065,6.7,Smart Analytics +AI07597,Head of AI,117462,USD,117462,SE,CT,Israel,M,Colombia,50,"Data Visualization, PyTorch, NLP, Docker",Associate,8,Transportation,2024-09-27,2024-10-24,2441,6.3,DeepTech Ventures +AI07598,Data Analyst,163257,EUR,138768,SE,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Statistics, Scala",Master,7,Healthcare,2024-11-18,2024-12-09,840,7.3,Neural Networks Co +AI07599,Data Analyst,185659,USD,185659,EX,PT,Israel,L,Israel,50,"Data Visualization, Docker, Computer Vision, NLP",PhD,10,Education,2024-08-29,2024-11-03,1965,7.2,DeepTech Ventures +AI07600,AI Architect,266642,CAD,333303,EX,CT,Canada,L,Germany,0,"PyTorch, GCP, Azure, Mathematics, Statistics",Bachelor,16,Energy,2025-04-16,2025-05-08,1518,5.8,Smart Analytics +AI07601,ML Ops Engineer,73310,USD,73310,EN,FT,Norway,S,Brazil,0,"SQL, Statistics, MLOps, R",Associate,1,Retail,2024-04-26,2024-05-31,530,10,Machine Intelligence Group +AI07602,AI Software Engineer,175822,CHF,158240,MI,FT,Switzerland,L,Portugal,100,"Computer Vision, GCP, Linux, AWS, Tableau",PhD,3,Healthcare,2024-06-05,2024-07-13,1150,5,Neural Networks Co +AI07603,Machine Learning Researcher,82893,USD,82893,EN,FT,Israel,L,Romania,50,"Azure, MLOps, Kubernetes, Docker",PhD,0,Real Estate,2025-02-24,2025-04-14,1318,9.8,Advanced Robotics +AI07604,Computer Vision Engineer,121156,USD,121156,SE,PT,Finland,M,United States,100,"Mathematics, GCP, MLOps, Docker",Associate,7,Technology,2025-04-15,2025-05-01,1153,5.6,Machine Intelligence Group +AI07605,Machine Learning Engineer,85501,USD,85501,MI,CT,Ireland,S,Ireland,100,"Scala, NLP, Java, R",PhD,2,Energy,2024-05-01,2024-06-17,1409,9.7,Cloud AI Solutions +AI07606,Deep Learning Engineer,200592,USD,200592,EX,FL,Sweden,L,Sweden,100,"Scala, PyTorch, Tableau, Mathematics, Kubernetes",PhD,19,Automotive,2024-12-02,2024-12-17,714,6.3,DeepTech Ventures +AI07607,Data Analyst,157367,USD,157367,EX,FL,United States,S,Hungary,50,"MLOps, PyTorch, Kubernetes",PhD,18,Finance,2025-01-09,2025-02-05,1308,8.7,Digital Transformation LLC +AI07608,AI Architect,96408,USD,96408,MI,FL,Norway,S,Norway,50,"R, TensorFlow, SQL, Azure, Spark",Bachelor,4,Automotive,2024-03-23,2024-04-25,574,9,Cloud AI Solutions +AI07609,AI Research Scientist,41086,USD,41086,MI,CT,China,M,China,100,"TensorFlow, Docker, GCP",Bachelor,4,Telecommunications,2025-01-18,2025-03-03,1587,8.9,Quantum Computing Inc +AI07610,AI Architect,87699,EUR,74544,MI,CT,France,L,France,100,"R, PyTorch, Docker, TensorFlow, SQL",Bachelor,2,Government,2024-10-18,2024-11-29,2105,8.6,Predictive Systems +AI07611,AI Architect,173811,CHF,156430,SE,PT,Switzerland,S,Switzerland,0,"Python, PyTorch, Linux",Associate,7,Retail,2025-04-24,2025-05-21,1883,6.7,Cognitive Computing +AI07612,AI Product Manager,126276,EUR,107335,SE,FL,France,S,France,0,"Statistics, GCP, R, Git",Master,5,Government,2024-12-13,2025-01-13,1695,5.4,Quantum Computing Inc +AI07613,Computer Vision Engineer,242933,EUR,206493,EX,FL,Netherlands,M,Finland,100,"Spark, TensorFlow, Linux",PhD,11,Consulting,2024-12-16,2025-01-23,2045,6.3,AI Innovations +AI07614,Robotics Engineer,62515,USD,62515,EN,FL,United States,S,United States,50,"PyTorch, SQL, TensorFlow",Master,1,Media,2025-03-29,2025-04-14,871,7.3,Cognitive Computing +AI07615,AI Software Engineer,96579,USD,96579,SE,FT,Israel,M,Israel,100,"Scala, TensorFlow, Deep Learning",PhD,9,Telecommunications,2024-09-15,2024-11-10,1055,8.3,DataVision Ltd +AI07616,Machine Learning Researcher,66417,USD,66417,EN,FT,Norway,M,Norway,0,"R, NLP, Azure, Git, SQL",Master,0,Consulting,2024-11-07,2024-12-12,795,6.6,TechCorp Inc +AI07617,AI Product Manager,66775,USD,66775,EN,PT,Ireland,M,Mexico,100,"Computer Vision, Git, MLOps, NLP, TensorFlow",Master,0,Education,2024-02-29,2024-04-29,550,9.8,Predictive Systems +AI07618,Autonomous Systems Engineer,112618,SGD,146403,MI,PT,Singapore,L,Singapore,100,"AWS, PyTorch, Docker, TensorFlow, Scala",Associate,4,Finance,2025-02-04,2025-03-31,1936,6.3,Digital Transformation LLC +AI07619,AI Consultant,172134,USD,172134,SE,FT,Norway,M,Brazil,0,"Hadoop, Computer Vision, Python, Docker, GCP",Master,9,Finance,2024-08-12,2024-08-28,2319,6.3,Algorithmic Solutions +AI07620,Research Scientist,89513,EUR,76086,SE,FL,France,S,France,0,"Scala, Git, Python, Azure",Associate,6,Telecommunications,2024-08-08,2024-09-27,2056,6.2,Machine Intelligence Group +AI07621,Head of AI,124617,USD,124617,SE,FL,Denmark,S,Denmark,100,"Azure, NLP, Spark, Hadoop",Associate,9,Gaming,2025-03-19,2025-04-03,1175,7.2,Machine Intelligence Group +AI07622,NLP Engineer,211681,USD,211681,EX,FL,Sweden,S,Colombia,100,"Spark, Tableau, Kubernetes",Bachelor,13,Real Estate,2024-06-25,2024-07-23,2078,6.8,Digital Transformation LLC +AI07623,AI Architect,70756,USD,70756,EN,CT,Sweden,L,Czech Republic,100,"Python, NLP, AWS",PhD,1,Media,2025-03-21,2025-04-29,2181,8.7,Algorithmic Solutions +AI07624,AI Consultant,124712,EUR,106005,SE,PT,Germany,S,Germany,100,"Kubernetes, Tableau, Mathematics, MLOps, Git",Associate,8,Real Estate,2024-01-23,2024-03-07,2333,8,Digital Transformation LLC +AI07625,Research Scientist,81724,USD,81724,EN,FT,Ireland,L,Ireland,0,"Python, Azure, Mathematics, GCP, Statistics",Bachelor,0,Real Estate,2024-10-25,2024-11-21,2292,9.4,TechCorp Inc +AI07626,Data Scientist,98773,USD,98773,MI,FT,Ireland,L,Ireland,50,"TensorFlow, NLP, Git, Hadoop",Bachelor,4,Transportation,2024-04-20,2024-06-29,640,6.3,Future Systems +AI07627,NLP Engineer,123212,SGD,160176,SE,PT,Singapore,S,Singapore,0,"Azure, PyTorch, GCP",PhD,5,Transportation,2024-01-23,2024-03-03,1509,5.9,Future Systems +AI07628,AI Consultant,158235,EUR,134500,EX,CT,France,M,France,100,"Scala, Git, Data Visualization, AWS",PhD,11,Healthcare,2025-04-04,2025-05-28,2070,6.1,Machine Intelligence Group +AI07629,Robotics Engineer,243378,USD,243378,EX,FL,Finland,L,Japan,50,"Linux, Deep Learning, Python, SQL",Master,17,Manufacturing,2024-01-23,2024-03-15,1771,8.9,Smart Analytics +AI07630,Data Engineer,72159,SGD,93807,EN,CT,Singapore,L,Sweden,100,"GCP, Docker, MLOps",Associate,1,Education,2025-04-26,2025-06-29,1183,9,Machine Intelligence Group +AI07631,Computer Vision Engineer,117447,CAD,146809,SE,FT,Canada,M,Canada,50,"Git, Python, TensorFlow",Bachelor,7,Gaming,2025-02-25,2025-04-03,907,6.4,Predictive Systems +AI07632,Data Engineer,93398,EUR,79388,EN,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Data Visualization, Spark",PhD,0,Telecommunications,2024-09-21,2024-10-15,595,6.4,DeepTech Ventures +AI07633,Head of AI,130830,USD,130830,SE,FL,Sweden,L,Latvia,0,"Kubernetes, Python, Hadoop",Associate,5,Technology,2024-04-19,2024-05-25,1607,8.3,Quantum Computing Inc +AI07634,Data Engineer,226889,USD,226889,EX,PT,United States,S,Sweden,50,"GCP, Kubernetes, Data Visualization, Deep Learning, Hadoop",Bachelor,12,Retail,2025-02-02,2025-03-11,792,9,Cognitive Computing +AI07635,Data Engineer,81702,JPY,8987220,EN,FT,Japan,M,Japan,50,"SQL, GCP, Statistics",Associate,0,Consulting,2024-06-12,2024-07-20,504,5.3,Quantum Computing Inc +AI07636,AI Product Manager,111373,EUR,94667,SE,FL,Germany,S,Germany,0,"Mathematics, Python, Tableau, TensorFlow, PyTorch",Bachelor,6,Consulting,2025-01-05,2025-02-08,2037,6.3,Neural Networks Co +AI07637,Robotics Engineer,57310,USD,57310,MI,FL,South Korea,S,Switzerland,50,"Docker, NLP, Python, Kubernetes, Mathematics",Master,4,Telecommunications,2024-05-03,2024-06-27,1556,7.6,Smart Analytics +AI07638,Principal Data Scientist,43322,USD,43322,MI,FL,China,S,China,50,"Spark, Python, TensorFlow, Linux",PhD,3,Real Estate,2024-11-02,2024-12-10,1131,7.2,Predictive Systems +AI07639,Computer Vision Engineer,95292,CHF,85763,EN,PT,Switzerland,L,Switzerland,100,"Git, Hadoop, SQL, Computer Vision",Master,0,Education,2024-02-12,2024-03-25,1940,5.2,DataVision Ltd +AI07640,NLP Engineer,174223,GBP,130667,EX,FT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, Azure",Master,10,Telecommunications,2024-05-26,2024-06-19,981,7.2,DeepTech Ventures +AI07641,Machine Learning Engineer,84562,AUD,114159,MI,FT,Australia,M,Australia,100,"Linux, GCP, TensorFlow, Kubernetes, Statistics",Master,3,Technology,2024-11-09,2024-12-11,1796,5.3,DataVision Ltd +AI07642,Data Analyst,166804,AUD,225185,SE,FL,Australia,L,Philippines,100,"Tableau, Python, TensorFlow, Mathematics",Associate,7,Retail,2024-05-09,2024-07-10,745,5.4,Algorithmic Solutions +AI07643,AI Consultant,32768,USD,32768,EN,PT,China,L,China,50,"Python, SQL, Docker, Mathematics",Bachelor,1,Real Estate,2025-04-30,2025-05-24,1770,7.9,Cognitive Computing +AI07644,Head of AI,217646,EUR,184999,EX,PT,Netherlands,S,Brazil,50,"Spark, TensorFlow, Scala, Hadoop, MLOps",PhD,10,Healthcare,2024-12-10,2025-01-15,2225,8.5,TechCorp Inc +AI07645,Computer Vision Engineer,144258,EUR,122619,SE,FL,Netherlands,S,Netherlands,50,"PyTorch, R, Hadoop",Bachelor,5,Media,2025-01-25,2025-02-18,2300,9.7,DeepTech Ventures +AI07646,AI Architect,104597,USD,104597,SE,FL,South Korea,M,South Korea,100,"GCP, SQL, PyTorch, R",Bachelor,8,Transportation,2024-06-27,2024-07-28,1106,8.2,Neural Networks Co +AI07647,AI Specialist,95849,USD,95849,MI,FL,South Korea,L,South Korea,50,"Tableau, Kubernetes, PyTorch",Bachelor,4,Automotive,2024-11-06,2024-11-22,1076,6,DeepTech Ventures +AI07648,Computer Vision Engineer,265185,EUR,225407,EX,FT,Netherlands,L,Netherlands,50,"Python, PyTorch, Java, Computer Vision",Master,18,Energy,2024-12-14,2025-01-29,674,6.9,Predictive Systems +AI07649,AI Specialist,63417,EUR,53904,EN,CT,Austria,L,South Africa,50,"Linux, Scala, Kubernetes, GCP, Mathematics",PhD,1,Media,2024-10-09,2024-11-20,1572,9.6,Algorithmic Solutions +AI07650,Robotics Engineer,162111,USD,162111,SE,PT,Ireland,L,Thailand,50,"Docker, Statistics, GCP, Mathematics, PyTorch",PhD,8,Real Estate,2024-08-04,2024-10-06,1021,7,AI Innovations +AI07651,AI Architect,51830,USD,51830,EN,CT,South Korea,M,South Korea,0,"GCP, Scala, Tableau, PyTorch, Statistics",Bachelor,1,Energy,2024-08-04,2024-09-22,2067,9.2,Cloud AI Solutions +AI07652,AI Architect,80660,USD,80660,EN,CT,Denmark,L,Denmark,0,"Docker, AWS, MLOps",Bachelor,0,Energy,2024-11-03,2024-12-22,1825,5.3,Cognitive Computing +AI07653,Research Scientist,183478,USD,183478,SE,FT,Denmark,M,New Zealand,0,"Python, TensorFlow, Computer Vision, MLOps",PhD,8,Automotive,2024-02-24,2024-03-11,2350,9.6,Machine Intelligence Group +AI07654,Data Scientist,93839,EUR,79763,EN,FT,Netherlands,L,Netherlands,0,"TensorFlow, Spark, Computer Vision",Associate,1,Manufacturing,2024-01-22,2024-02-08,1415,5.5,Smart Analytics +AI07655,Machine Learning Engineer,63882,JPY,7027020,EN,FT,Japan,L,Japan,0,"Git, AWS, Python, Tableau, Linux",Associate,1,Technology,2024-02-27,2024-04-24,2251,6.2,DeepTech Ventures +AI07656,Data Analyst,126076,GBP,94557,SE,FT,United Kingdom,L,Ghana,50,"Data Visualization, SQL, Azure",Master,6,Finance,2024-02-11,2024-04-05,2026,9.8,DeepTech Ventures +AI07657,Principal Data Scientist,91813,JPY,10099430,MI,FL,Japan,S,Australia,100,"Scala, Data Visualization, Kubernetes, SQL, AWS",Master,3,Education,2024-07-23,2024-08-08,1170,7.6,DataVision Ltd +AI07658,AI Architect,44127,USD,44127,EN,PT,Finland,S,Finland,100,"SQL, Java, Data Visualization",Master,1,Media,2024-05-09,2024-06-05,2336,5,Predictive Systems +AI07659,AI Research Scientist,70724,CAD,88405,EN,FT,Canada,M,Canada,50,"Data Visualization, MLOps, SQL",Associate,0,Automotive,2024-01-20,2024-02-05,541,8,Advanced Robotics +AI07660,Data Analyst,306380,GBP,229785,EX,FT,United Kingdom,L,United Kingdom,50,"PyTorch, TensorFlow, Mathematics, Azure, R",Bachelor,16,Finance,2024-06-16,2024-07-03,1441,9.6,Digital Transformation LLC +AI07661,Data Scientist,59061,EUR,50202,EN,PT,Germany,S,Germany,100,"Scala, SQL, Data Visualization, TensorFlow, Git",Associate,0,Gaming,2024-08-28,2024-10-12,2199,5.2,Future Systems +AI07662,Data Scientist,127372,USD,127372,SE,PT,Denmark,S,Hungary,100,"GCP, AWS, Python, Linux",PhD,6,Telecommunications,2025-04-02,2025-06-10,1330,5.6,DataVision Ltd +AI07663,AI Software Engineer,324728,CHF,292255,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, Python, TensorFlow, Linux",PhD,13,Retail,2024-08-03,2024-09-23,1682,5.2,Smart Analytics +AI07664,AI Consultant,132294,USD,132294,SE,FT,Denmark,S,Denmark,100,"Data Visualization, Python, GCP",Master,7,Manufacturing,2024-01-22,2024-03-09,1383,7.8,AI Innovations +AI07665,Data Engineer,110217,EUR,93684,SE,FL,Germany,S,Germany,50,"R, Tableau, Azure, Python, Hadoop",Associate,7,Finance,2024-08-09,2024-08-29,2475,7.2,Smart Analytics +AI07666,Deep Learning Engineer,108463,USD,108463,MI,FL,Denmark,M,Brazil,50,"Statistics, SQL, Linux, NLP, Hadoop",PhD,4,Consulting,2024-04-24,2024-07-05,1652,8.4,AI Innovations +AI07667,AI Consultant,60083,USD,60083,MI,FL,South Korea,M,Italy,100,"AWS, Scala, Docker, NLP, Linux",PhD,2,Transportation,2025-02-19,2025-03-18,1564,8.2,Machine Intelligence Group +AI07668,NLP Engineer,74921,USD,74921,EX,CT,India,L,India,0,"TensorFlow, NLP, R, Python",PhD,11,Government,2024-02-28,2024-03-26,1818,6.1,Digital Transformation LLC +AI07669,AI Consultant,229930,CHF,206937,EX,FT,Switzerland,S,Kenya,0,"Java, GCP, Statistics, Python, TensorFlow",Associate,13,Retail,2024-05-12,2024-06-24,1945,9.9,Advanced Robotics +AI07670,Research Scientist,134348,CAD,167935,SE,FL,Canada,M,Canada,50,"NLP, Kubernetes, MLOps, Java",Bachelor,9,Transportation,2024-11-21,2025-01-17,2441,6.7,Neural Networks Co +AI07671,AI Research Scientist,84844,GBP,63633,MI,FT,United Kingdom,S,United Kingdom,50,"Scala, Hadoop, Data Visualization, Git, Python",Bachelor,2,Media,2024-12-14,2025-01-13,1273,8.1,Smart Analytics +AI07672,Computer Vision Engineer,75519,CAD,94399,MI,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP",PhD,2,Energy,2024-08-15,2024-09-15,2158,8.4,Machine Intelligence Group +AI07673,AI Specialist,83770,USD,83770,MI,FT,Finland,M,Switzerland,100,"Kubernetes, Scala, Statistics, PyTorch, NLP",PhD,4,Education,2024-12-21,2025-01-11,1827,6,Future Systems +AI07674,Computer Vision Engineer,99649,USD,99649,EN,PT,United States,L,Romania,100,"GCP, R, Data Visualization, SQL, Linux",Associate,1,Energy,2025-04-25,2025-05-14,1620,7.7,DeepTech Ventures +AI07675,Data Engineer,288454,USD,288454,EX,FT,Denmark,M,Denmark,100,"AWS, MLOps, GCP, Scala",Master,18,Consulting,2024-06-27,2024-08-26,1751,5.5,Cognitive Computing +AI07676,Research Scientist,185909,EUR,158023,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, TensorFlow, GCP, Statistics, Java",Associate,15,Telecommunications,2024-11-06,2024-12-19,1477,5.7,Digital Transformation LLC +AI07677,Robotics Engineer,82676,USD,82676,EN,FL,United States,M,United States,100,"AWS, Git, Data Visualization",Associate,0,Automotive,2024-03-03,2024-03-28,2443,6,Cognitive Computing +AI07678,Deep Learning Engineer,180023,USD,180023,EX,FT,South Korea,S,China,0,"Scala, GCP, Deep Learning, Data Visualization, Hadoop",Associate,11,Real Estate,2024-06-08,2024-07-05,2224,10,Quantum Computing Inc +AI07679,AI Consultant,85630,USD,85630,EN,PT,Ireland,L,Ireland,0,"Java, Kubernetes, Scala, Deep Learning, Computer Vision",Bachelor,0,Media,2025-04-02,2025-06-01,1688,9.3,Cognitive Computing +AI07680,AI Research Scientist,91309,EUR,77613,MI,FT,France,L,France,0,"Java, NLP, Linux, TensorFlow",Associate,4,Education,2024-08-20,2024-10-08,1703,7.9,Digital Transformation LLC +AI07681,AI Consultant,73734,EUR,62674,EN,FL,Austria,M,Austria,0,"Python, MLOps, PyTorch, R",PhD,1,Gaming,2024-04-15,2024-05-12,577,7.4,Predictive Systems +AI07682,Research Scientist,180469,USD,180469,EX,FT,Sweden,S,Sweden,50,"SQL, Python, MLOps, AWS",PhD,17,Government,2025-02-24,2025-05-08,2313,5.1,Smart Analytics +AI07683,Machine Learning Researcher,55451,EUR,47133,EN,CT,Austria,L,Austria,50,"Spark, Kubernetes, Statistics, Computer Vision, PyTorch",Master,1,Finance,2025-01-05,2025-02-21,1493,9.2,DeepTech Ventures +AI07684,Deep Learning Engineer,113073,USD,113073,EN,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Data Visualization, Python, R",PhD,0,Automotive,2024-11-28,2025-01-28,2139,9.3,Neural Networks Co +AI07685,Computer Vision Engineer,68363,EUR,58109,EN,FT,France,M,France,50,"Hadoop, Linux, Mathematics, Python",Master,0,Government,2024-08-12,2024-08-29,1755,9.5,Advanced Robotics +AI07686,Robotics Engineer,62860,USD,62860,EX,CT,China,S,China,50,"Hadoop, SQL, NLP",Associate,16,Real Estate,2024-06-30,2024-07-19,540,5.1,Predictive Systems +AI07687,NLP Engineer,176108,USD,176108,EX,PT,Ireland,S,Israel,50,"Python, Hadoop, Kubernetes, Scala, Git",Bachelor,11,Telecommunications,2024-05-30,2024-07-11,1478,5.2,TechCorp Inc +AI07688,AI Software Engineer,86453,EUR,73485,MI,FT,France,L,France,0,"Azure, GCP, Spark, Scala, Hadoop",Master,2,Real Estate,2024-07-20,2024-09-24,1547,8.2,Advanced Robotics +AI07689,Head of AI,170116,EUR,144599,EX,FL,Netherlands,L,Czech Republic,0,"Kubernetes, Java, Git, AWS, Computer Vision",PhD,17,Government,2025-02-23,2025-04-03,1237,5.5,Smart Analytics +AI07690,Principal Data Scientist,79589,EUR,67651,EN,CT,Netherlands,L,Sweden,50,"Python, TensorFlow, SQL, Linux",PhD,1,Government,2025-02-01,2025-02-20,1924,7.6,Cloud AI Solutions +AI07691,AI Architect,190789,USD,190789,EX,PT,Finland,S,Finland,50,"PyTorch, Tableau, SQL, Git",Bachelor,10,Education,2024-04-21,2024-06-12,659,9.9,Smart Analytics +AI07692,Data Engineer,79062,USD,79062,EN,PT,United States,M,United States,0,"Data Visualization, Docker, Mathematics",Bachelor,0,Telecommunications,2024-05-15,2024-07-10,1269,8.7,Algorithmic Solutions +AI07693,Deep Learning Engineer,212322,GBP,159242,EX,FL,United Kingdom,M,United Kingdom,0,"Python, Linux, SQL",Bachelor,14,Retail,2024-11-16,2025-01-19,651,8.2,TechCorp Inc +AI07694,Machine Learning Engineer,126710,CAD,158388,SE,FT,Canada,M,Turkey,0,"Git, Kubernetes, GCP, Spark, NLP",Bachelor,6,Healthcare,2024-03-20,2024-05-14,804,8.2,Autonomous Tech +AI07695,Deep Learning Engineer,135567,SGD,176237,SE,FT,Singapore,S,Singapore,100,"Python, Hadoop, SQL, Data Visualization, NLP",Associate,5,Transportation,2024-08-28,2024-09-22,1554,5.1,AI Innovations +AI07696,Autonomous Systems Engineer,77684,GBP,58263,MI,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, AWS, Azure, R",Associate,2,Finance,2024-02-19,2024-03-31,1848,6.3,Quantum Computing Inc +AI07697,Head of AI,87101,CHF,78391,EN,FT,Switzerland,S,Switzerland,50,"TensorFlow, AWS, Mathematics, NLP",PhD,1,Automotive,2024-04-24,2024-05-21,1700,6.2,Quantum Computing Inc +AI07698,Head of AI,65182,USD,65182,EN,FL,Ireland,L,Ireland,100,"NLP, Statistics, SQL, Data Visualization",Master,0,Manufacturing,2024-05-12,2024-06-23,1768,7.2,Predictive Systems +AI07699,Research Scientist,155741,JPY,17131510,SE,CT,Japan,L,Sweden,50,"SQL, Tableau, NLP, Data Visualization, Azure",Master,8,Automotive,2024-06-02,2024-06-19,590,9.5,Advanced Robotics +AI07700,Computer Vision Engineer,35630,USD,35630,MI,PT,India,M,Russia,100,"Scala, R, Deep Learning, Computer Vision, GCP",PhD,2,Gaming,2024-04-07,2024-05-14,501,7.2,Cognitive Computing +AI07701,Machine Learning Engineer,92685,EUR,78782,EN,PT,Netherlands,L,Philippines,50,"Hadoop, Statistics, Scala, TensorFlow, NLP",Master,0,Automotive,2025-03-28,2025-05-08,1696,9.5,Digital Transformation LLC +AI07702,Machine Learning Engineer,63966,EUR,54371,EN,FT,France,S,France,50,"Spark, Python, Statistics",Associate,0,Government,2024-03-03,2024-03-19,562,6.7,TechCorp Inc +AI07703,Data Scientist,193308,AUD,260966,EX,FL,Australia,L,Italy,50,"Azure, Hadoop, SQL, Python",Associate,19,Media,2024-10-08,2024-11-08,2482,8.6,Quantum Computing Inc +AI07704,AI Architect,68810,JPY,7569100,EN,PT,Japan,M,Japan,50,"Linux, Statistics, Python",Bachelor,0,Technology,2024-01-09,2024-02-05,1000,5.1,DataVision Ltd +AI07705,Head of AI,133424,CHF,120082,MI,PT,Switzerland,S,Switzerland,50,"R, Deep Learning, SQL",Associate,2,Finance,2025-03-19,2025-05-25,2253,8.2,Cloud AI Solutions +AI07706,Head of AI,99725,CHF,89753,MI,PT,Switzerland,S,Switzerland,0,"Python, Statistics, Java, TensorFlow",Associate,3,Telecommunications,2024-03-25,2024-05-07,1474,9,Cognitive Computing +AI07707,Principal Data Scientist,92186,USD,92186,MI,CT,Finland,M,Finland,100,"Mathematics, Python, MLOps, Kubernetes, Linux",Associate,3,Consulting,2025-02-12,2025-02-27,1793,6.8,Advanced Robotics +AI07708,AI Consultant,67420,EUR,57307,MI,CT,France,S,France,0,"Scala, AWS, Tableau",Master,4,Telecommunications,2025-04-17,2025-06-03,1056,7.9,Future Systems +AI07709,ML Ops Engineer,63821,CAD,79776,EN,CT,Canada,L,South Korea,50,"TensorFlow, Tableau, Statistics, Java, Linux",PhD,0,Finance,2025-03-14,2025-04-14,1786,7.2,TechCorp Inc +AI07710,ML Ops Engineer,79858,JPY,8784380,MI,PT,Japan,M,Finland,100,"Tableau, Statistics, Hadoop, Scala, Python",Bachelor,2,Media,2024-08-07,2024-08-22,1849,9.5,AI Innovations +AI07711,Autonomous Systems Engineer,92037,GBP,69028,MI,CT,United Kingdom,S,United Kingdom,50,"Python, MLOps, GCP, TensorFlow, Tableau",PhD,3,Telecommunications,2024-05-26,2024-07-15,1867,7.2,Future Systems +AI07712,Deep Learning Engineer,145429,JPY,15997190,SE,CT,Japan,L,Japan,0,"NLP, PyTorch, SQL, R, Kubernetes",Bachelor,6,Healthcare,2024-04-17,2024-05-27,1406,7.6,DeepTech Ventures +AI07713,ML Ops Engineer,49642,USD,49642,EN,FT,South Korea,M,South Korea,50,"Git, Data Visualization, Scala, Python",Bachelor,1,Healthcare,2024-07-27,2024-09-05,1285,5.5,Quantum Computing Inc +AI07714,NLP Engineer,123567,SGD,160637,SE,FT,Singapore,M,Singapore,0,"Git, Java, Tableau",Associate,9,Transportation,2025-01-07,2025-02-19,2046,8.7,Autonomous Tech +AI07715,AI Architect,110776,CHF,99698,EN,FL,Switzerland,M,Switzerland,50,"SQL, Java, Hadoop, Azure, Python",Associate,1,Transportation,2024-10-17,2024-11-13,1304,8.6,Neural Networks Co +AI07716,Principal Data Scientist,173372,AUD,234052,EX,PT,Australia,M,Australia,50,"Deep Learning, Python, Spark, Hadoop, Mathematics",Bachelor,16,Transportation,2024-11-01,2024-12-28,519,9.9,DataVision Ltd +AI07717,Autonomous Systems Engineer,66211,EUR,56279,EN,CT,Germany,L,Germany,100,"Git, Hadoop, Spark, TensorFlow, Java",PhD,1,Gaming,2024-11-22,2024-12-28,2210,9.7,Cognitive Computing +AI07718,Data Scientist,152011,SGD,197614,SE,FT,Singapore,L,Japan,0,"Docker, Linux, Computer Vision, SQL, PyTorch",PhD,5,Transportation,2024-05-29,2024-06-30,501,5.5,Algorithmic Solutions +AI07719,ML Ops Engineer,227332,SGD,295532,EX,FL,Singapore,S,Singapore,50,"Python, Hadoop, SQL, Azure",Bachelor,19,Education,2025-01-15,2025-03-15,1975,8.9,TechCorp Inc +AI07720,Robotics Engineer,124845,CAD,156056,EX,FT,Canada,S,Romania,100,"SQL, NLP, Azure, Statistics, Python",Associate,15,Retail,2024-03-05,2024-05-14,1059,6.6,Machine Intelligence Group +AI07721,NLP Engineer,88027,SGD,114435,MI,FT,Singapore,M,Singapore,0,"PyTorch, Computer Vision, MLOps, Docker",PhD,3,Real Estate,2024-07-28,2024-09-23,652,8.2,Autonomous Tech +AI07722,Head of AI,160105,USD,160105,SE,PT,Ireland,L,Ireland,50,"Python, Kubernetes, Linux",Master,6,Real Estate,2024-01-31,2024-03-13,1280,9,Machine Intelligence Group +AI07723,AI Research Scientist,45928,USD,45928,SE,FT,India,M,India,0,"Linux, Git, Tableau, Data Visualization",Bachelor,7,Media,2024-10-08,2024-12-05,2291,7.7,Smart Analytics +AI07724,Head of AI,71793,USD,71793,EN,CT,Denmark,M,Denmark,100,"Linux, PyTorch, Computer Vision, Git",Bachelor,1,Automotive,2024-12-08,2024-12-23,1035,6.7,Algorithmic Solutions +AI07725,AI Research Scientist,250916,USD,250916,EX,FT,Norway,L,Norway,0,"Deep Learning, Linux, MLOps, NLP, Tableau",PhD,12,Manufacturing,2024-10-26,2024-11-21,1614,6.4,Future Systems +AI07726,Data Scientist,174103,USD,174103,SE,FL,Denmark,L,Denmark,0,"Git, Linux, NLP, Spark",Associate,6,Manufacturing,2024-04-07,2024-06-14,2322,5.4,Advanced Robotics +AI07727,Principal Data Scientist,109543,GBP,82157,MI,PT,United Kingdom,L,United Kingdom,50,"Azure, Python, GCP, Deep Learning, TensorFlow",Associate,2,Healthcare,2024-10-22,2024-12-07,2284,5.4,TechCorp Inc +AI07728,Robotics Engineer,87605,USD,87605,EN,PT,Ireland,L,Ireland,0,"Azure, Python, Kubernetes, Tableau, TensorFlow",PhD,0,Manufacturing,2024-11-23,2024-12-12,1772,5,Predictive Systems +AI07729,AI Software Engineer,146983,EUR,124936,SE,CT,Germany,M,Germany,0,"Spark, AWS, Git, MLOps",Master,9,Real Estate,2024-04-24,2024-05-16,2162,6.3,Cognitive Computing +AI07730,Deep Learning Engineer,102384,USD,102384,SE,CT,Sweden,M,Brazil,50,"R, Deep Learning, Data Visualization, Hadoop, AWS",Master,8,Technology,2024-06-17,2024-08-22,846,6.4,Predictive Systems +AI07731,AI Research Scientist,261474,JPY,28762140,EX,CT,Japan,L,Japan,50,"Computer Vision, GCP, NLP, Kubernetes, Java",Associate,18,Transportation,2024-04-29,2024-05-21,1030,8.1,Advanced Robotics +AI07732,Data Analyst,74595,CAD,93244,EN,FL,Canada,L,Canada,0,"SQL, Computer Vision, PyTorch, Statistics, Kubernetes",Associate,0,Government,2024-02-17,2024-04-28,736,9,DeepTech Ventures +AI07733,Head of AI,96835,USD,96835,EX,CT,China,L,United Kingdom,0,"Kubernetes, Hadoop, Computer Vision",PhD,18,Government,2024-05-01,2024-06-28,1151,6,Quantum Computing Inc +AI07734,Machine Learning Researcher,136419,USD,136419,MI,PT,Denmark,L,Denmark,0,"Python, Hadoop, Deep Learning, TensorFlow",Master,2,Manufacturing,2024-05-11,2024-06-22,1928,6.7,Digital Transformation LLC +AI07735,Autonomous Systems Engineer,62698,USD,62698,SE,FL,China,L,China,100,"Hadoop, Python, Tableau",Associate,9,Energy,2024-01-01,2024-02-07,512,7,Machine Intelligence Group +AI07736,AI Architect,82570,GBP,61928,MI,PT,United Kingdom,M,Turkey,50,"Scala, Git, Tableau, Computer Vision",Bachelor,4,Retail,2024-04-22,2024-05-06,1986,5.6,Predictive Systems +AI07737,Autonomous Systems Engineer,63993,EUR,54394,EN,FT,France,S,Chile,50,"Scala, SQL, Git, Linux",PhD,1,Energy,2024-04-22,2024-07-02,2119,5.6,Quantum Computing Inc +AI07738,Deep Learning Engineer,117183,USD,117183,MI,FT,Israel,L,Israel,0,"TensorFlow, AWS, PyTorch",Master,4,Technology,2024-03-29,2024-05-15,615,8.3,Smart Analytics +AI07739,NLP Engineer,228120,SGD,296556,EX,CT,Singapore,S,Estonia,50,"Kubernetes, Data Visualization, GCP, Scala, Computer Vision",PhD,18,Media,2024-05-29,2024-07-11,982,6.3,Predictive Systems +AI07740,Autonomous Systems Engineer,168150,USD,168150,EX,FL,Ireland,S,Ireland,100,"SQL, Docker, NLP, Mathematics, Computer Vision",Bachelor,10,Telecommunications,2024-07-10,2024-08-22,2461,7.6,DataVision Ltd +AI07741,Data Engineer,251868,EUR,214088,EX,PT,Netherlands,L,Netherlands,0,"Java, Spark, TensorFlow",PhD,10,Energy,2025-02-27,2025-05-01,2060,6,Future Systems +AI07742,AI Consultant,134610,EUR,114419,SE,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, PyTorch, Linux",Associate,9,Healthcare,2024-01-03,2024-02-22,2155,9.1,DeepTech Ventures +AI07743,Data Scientist,39473,USD,39473,MI,PT,China,M,Poland,0,"Hadoop, Linux, R, Git, SQL",PhD,2,Government,2024-03-09,2024-04-07,1821,7.2,DataVision Ltd +AI07744,Data Engineer,59378,EUR,50471,EN,FT,Germany,S,Germany,50,"Python, AWS, Java",Bachelor,1,Telecommunications,2025-04-22,2025-06-15,1884,5.9,Cognitive Computing +AI07745,AI Research Scientist,126770,EUR,107755,SE,CT,Austria,L,Austria,0,"Docker, Kubernetes, Azure, MLOps",Master,6,Retail,2024-04-12,2024-06-15,1519,5.6,Cloud AI Solutions +AI07746,AI Research Scientist,78592,CAD,98240,MI,CT,Canada,S,Canada,100,"R, TensorFlow, Deep Learning, Git, Docker",Bachelor,2,Retail,2024-11-13,2024-12-29,1997,8,Quantum Computing Inc +AI07747,Deep Learning Engineer,29559,USD,29559,MI,CT,India,L,India,0,"Hadoop, Deep Learning, Java, Tableau",Associate,2,Healthcare,2024-10-04,2024-11-04,754,7,Cloud AI Solutions +AI07748,AI Software Engineer,223895,USD,223895,EX,CT,Sweden,L,Brazil,100,"SQL, AWS, Deep Learning, Statistics, Data Visualization",Master,12,Gaming,2025-01-02,2025-02-11,793,9.4,AI Innovations +AI07749,Principal Data Scientist,170881,AUD,230689,SE,PT,Australia,L,Japan,0,"PyTorch, MLOps, TensorFlow",Bachelor,8,Technology,2024-09-07,2024-10-26,1484,8.9,AI Innovations +AI07750,AI Architect,77100,SGD,100230,MI,FL,Singapore,M,Vietnam,0,"SQL, Git, Data Visualization, PyTorch",Associate,4,Telecommunications,2024-11-01,2024-12-03,1851,8.6,Smart Analytics +AI07751,AI Research Scientist,61337,EUR,52136,EN,PT,France,L,France,0,"Linux, Statistics, Computer Vision",Bachelor,1,Energy,2025-04-29,2025-06-14,1576,9.8,Machine Intelligence Group +AI07752,Data Engineer,90203,AUD,121774,MI,FT,Australia,M,Australia,0,"Linux, Python, Data Visualization, MLOps",Bachelor,2,Manufacturing,2024-07-18,2024-09-13,1980,9.1,Smart Analytics +AI07753,AI Software Engineer,95206,USD,95206,EX,CT,India,L,India,0,"GCP, Scala, Java, Azure",Master,19,Finance,2024-12-17,2025-02-12,1590,8.3,Smart Analytics +AI07754,Machine Learning Engineer,143694,CHF,129325,SE,CT,Switzerland,S,Switzerland,100,"PyTorch, Java, SQL, MLOps, Deep Learning",Associate,7,Transportation,2024-07-13,2024-09-02,1769,5.7,Neural Networks Co +AI07755,AI Software Engineer,205240,CAD,256550,EX,FT,Canada,S,Canada,0,"TensorFlow, Kubernetes, Statistics, R, MLOps",PhD,19,Technology,2024-10-05,2024-11-02,2041,7.4,Future Systems +AI07756,Principal Data Scientist,130858,CAD,163573,SE,FL,Canada,L,Canada,100,"Computer Vision, SQL, PyTorch",Bachelor,5,Consulting,2024-01-14,2024-03-11,835,9.6,DataVision Ltd +AI07757,AI Specialist,109839,USD,109839,MI,PT,Norway,M,Norway,0,"Tableau, AWS, Python",PhD,2,Energy,2025-01-19,2025-03-22,2213,5.6,Digital Transformation LLC +AI07758,AI Architect,234658,EUR,199459,EX,CT,Germany,L,Germany,0,"Computer Vision, GCP, TensorFlow, Deep Learning, Java",Associate,14,Gaming,2025-03-18,2025-05-21,1240,7.2,Cloud AI Solutions +AI07759,Computer Vision Engineer,212824,USD,212824,EX,FL,Israel,S,United States,50,"AWS, GCP, Data Visualization, Computer Vision",Associate,18,Technology,2024-08-27,2024-10-08,1963,9.2,Smart Analytics +AI07760,Computer Vision Engineer,89614,EUR,76172,MI,FT,France,S,France,100,"TensorFlow, Linux, MLOps, R",Master,4,Gaming,2024-09-11,2024-09-26,1242,7.8,DeepTech Ventures +AI07761,AI Research Scientist,230152,EUR,195629,EX,PT,Germany,L,Germany,50,"Python, AWS, Computer Vision, TensorFlow, Mathematics",Bachelor,16,Real Estate,2025-04-05,2025-05-20,2279,5.6,Algorithmic Solutions +AI07762,Machine Learning Engineer,138749,USD,138749,EX,FT,Finland,M,Philippines,0,"Data Visualization, MLOps, Java, R, NLP",Bachelor,17,Retail,2024-06-28,2024-08-19,997,5.1,TechCorp Inc +AI07763,Data Scientist,151433,USD,151433,SE,FL,Denmark,M,Denmark,0,"Linux, Git, AWS, Tableau, SQL",PhD,6,Manufacturing,2024-05-09,2024-07-12,698,7.8,Cognitive Computing +AI07764,Head of AI,113027,USD,113027,MI,FL,United States,M,United States,50,"Scala, Spark, Computer Vision",Master,2,Government,2024-11-12,2025-01-13,522,5.4,Smart Analytics +AI07765,AI Architect,75238,USD,75238,EN,PT,United States,M,Sweden,0,"MLOps, Data Visualization, Statistics, PyTorch",PhD,0,Government,2024-12-04,2024-12-19,2206,6.3,DeepTech Ventures +AI07766,Data Scientist,181300,SGD,235690,EX,CT,Singapore,M,Singapore,0,"Python, GCP, Computer Vision",Bachelor,12,Consulting,2024-04-23,2024-05-28,1081,6.4,DeepTech Ventures +AI07767,Data Analyst,180520,USD,180520,EX,FL,Israel,S,Israel,0,"NLP, Spark, Git",Bachelor,16,Real Estate,2025-03-25,2025-04-14,2169,9.4,Digital Transformation LLC +AI07768,AI Research Scientist,60195,GBP,45146,EN,CT,United Kingdom,S,United Kingdom,100,"R, Python, Tableau, Scala",Bachelor,1,Government,2025-03-01,2025-05-12,2478,7.9,TechCorp Inc +AI07769,Deep Learning Engineer,85237,SGD,110808,EN,FL,Singapore,L,Ghana,50,"Python, Kubernetes, Docker, TensorFlow, SQL",PhD,1,Retail,2024-03-03,2024-05-06,2404,9.4,Advanced Robotics +AI07770,Computer Vision Engineer,120221,USD,120221,SE,FL,Norway,S,New Zealand,100,"Scala, PyTorch, Hadoop, Git, GCP",PhD,8,Government,2024-10-03,2024-12-12,651,7,Cognitive Computing +AI07771,Data Engineer,196214,USD,196214,EX,FT,Finland,M,Finland,50,"Linux, Java, GCP, TensorFlow, NLP",Master,14,Automotive,2024-02-01,2024-03-09,1141,9.8,Advanced Robotics +AI07772,AI Consultant,132988,CAD,166235,SE,FT,Canada,M,Canada,0,"Python, Hadoop, MLOps, TensorFlow, Mathematics",Bachelor,6,Media,2024-06-08,2024-08-09,2131,7.3,Digital Transformation LLC +AI07773,Data Analyst,77664,USD,77664,EN,PT,Ireland,M,Ireland,0,"NLP, Docker, Tableau",PhD,0,Energy,2025-03-06,2025-04-14,2381,6.8,Future Systems +AI07774,Robotics Engineer,148890,CAD,186113,SE,FT,Canada,L,Canada,50,"Scala, Linux, MLOps, Spark, Git",Master,9,Automotive,2025-01-27,2025-03-22,1437,8.6,Machine Intelligence Group +AI07775,Head of AI,95335,USD,95335,MI,PT,Israel,L,China,100,"Python, Hadoop, MLOps",Bachelor,2,Finance,2025-04-12,2025-04-30,2096,9.5,Machine Intelligence Group +AI07776,AI Software Engineer,60390,USD,60390,SE,FT,China,M,China,100,"SQL, GCP, PyTorch, Java",Master,5,Healthcare,2024-02-02,2024-03-19,1377,5.8,TechCorp Inc +AI07777,AI Specialist,113740,CHF,102366,EN,FT,Switzerland,L,Switzerland,50,"Kubernetes, TensorFlow, Python, Linux, Computer Vision",Associate,1,Manufacturing,2024-03-30,2024-05-12,646,7.9,DeepTech Ventures +AI07778,Research Scientist,107116,EUR,91049,SE,PT,France,S,Russia,0,"NLP, PyTorch, AWS, Linux, Computer Vision",Bachelor,5,Automotive,2024-05-31,2024-06-18,1158,9.5,Future Systems +AI07779,Data Scientist,116275,USD,116275,EX,PT,China,L,China,50,"Scala, Java, Spark, Docker",Master,17,Media,2024-03-16,2024-04-07,1611,9,DeepTech Ventures +AI07780,AI Product Manager,75695,EUR,64341,MI,FT,Austria,S,South Korea,50,"Linux, Hadoop, SQL, Spark, Java",Master,4,Education,2024-11-06,2025-01-05,984,5.6,Predictive Systems +AI07781,ML Ops Engineer,123821,EUR,105248,SE,FT,Austria,M,Austria,50,"Kubernetes, Spark, MLOps, NLP",Bachelor,8,Technology,2024-03-08,2024-05-09,2226,8.8,AI Innovations +AI07782,Data Engineer,220673,USD,220673,EX,CT,Ireland,L,Switzerland,50,"Docker, Hadoop, PyTorch, Git",PhD,19,Telecommunications,2024-11-27,2025-02-03,2497,5.6,Smart Analytics +AI07783,ML Ops Engineer,69580,EUR,59143,MI,CT,Netherlands,S,Netherlands,0,"NLP, Git, Kubernetes, Tableau",Master,3,Media,2024-01-10,2024-02-25,752,6.3,Digital Transformation LLC +AI07784,NLP Engineer,64614,USD,64614,EN,CT,Finland,S,Finland,0,"Git, R, Spark, Data Visualization",Master,1,Telecommunications,2024-11-29,2025-01-05,1789,6.1,Cognitive Computing +AI07785,Data Engineer,100944,EUR,85802,SE,CT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch",Master,8,Healthcare,2024-04-10,2024-06-15,1527,6.9,Advanced Robotics +AI07786,Machine Learning Engineer,35266,USD,35266,MI,PT,India,M,India,0,"AWS, SQL, Hadoop, Docker, Computer Vision",PhD,4,Automotive,2024-11-16,2024-11-30,761,7.4,Advanced Robotics +AI07787,AI Software Engineer,79263,AUD,107005,EN,FL,Australia,M,Vietnam,50,"Git, Hadoop, PyTorch",Master,1,Gaming,2024-06-11,2024-07-04,1102,7.8,Smart Analytics +AI07788,Data Scientist,94630,USD,94630,MI,CT,Sweden,S,Sweden,0,"Data Visualization, Azure, Kubernetes, GCP, SQL",PhD,4,Government,2025-02-15,2025-04-03,680,7.7,Neural Networks Co +AI07789,AI Research Scientist,290745,EUR,247133,EX,FT,Netherlands,L,Netherlands,0,"Docker, Linux, AWS",Bachelor,16,Energy,2024-11-05,2024-11-27,2383,7.5,Cloud AI Solutions +AI07790,Computer Vision Engineer,177261,USD,177261,SE,FL,Denmark,M,Vietnam,0,"Azure, PyTorch, SQL, Docker, R",Associate,9,Energy,2024-08-05,2024-10-13,1377,10,Future Systems +AI07791,AI Consultant,79754,SGD,103680,MI,FT,Singapore,S,Singapore,0,"Spark, Computer Vision, Linux, AWS, Statistics",Master,3,Telecommunications,2024-02-15,2024-03-21,970,5.9,AI Innovations +AI07792,AI Specialist,179275,USD,179275,EX,FL,Finland,L,United States,50,"R, AWS, Deep Learning",Master,17,Media,2024-12-11,2025-02-05,2187,5.7,Smart Analytics +AI07793,AI Consultant,120982,CHF,108884,MI,FT,Switzerland,L,Switzerland,0,"Statistics, MLOps, TensorFlow, Java",Master,4,Transportation,2024-01-14,2024-03-19,1448,8,Machine Intelligence Group +AI07794,Data Scientist,56033,USD,56033,EN,FL,Israel,L,Israel,100,"Deep Learning, TensorFlow, Data Visualization, PyTorch",Associate,1,Education,2025-01-20,2025-03-11,1633,8.3,Smart Analytics +AI07795,AI Product Manager,43195,USD,43195,SE,CT,India,L,India,0,"R, Java, Python, Statistics, TensorFlow",Bachelor,6,Technology,2024-06-11,2024-08-05,1479,9.9,Predictive Systems +AI07796,AI Software Engineer,95245,USD,95245,EN,FL,United States,L,Ukraine,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,0,Technology,2024-01-18,2024-03-21,1994,6.3,TechCorp Inc +AI07797,Deep Learning Engineer,68796,USD,68796,MI,PT,South Korea,L,South Korea,0,"Hadoop, Python, Tableau, MLOps, Computer Vision",PhD,4,Education,2024-09-23,2024-10-28,1211,5.1,Future Systems +AI07798,AI Architect,236279,CHF,212651,SE,PT,Switzerland,L,Israel,50,"Kubernetes, SQL, Linux, PyTorch",Master,9,Education,2025-03-05,2025-05-07,1087,6.4,TechCorp Inc +AI07799,Deep Learning Engineer,67944,AUD,91724,EN,CT,Australia,M,Australia,50,"Deep Learning, Kubernetes, Spark, Git",Associate,0,Retail,2025-04-04,2025-05-10,2112,5.6,Predictive Systems +AI07800,Computer Vision Engineer,89810,USD,89810,MI,CT,Denmark,S,Malaysia,100,"Deep Learning, TensorFlow, SQL, Hadoop",Bachelor,4,Media,2024-10-02,2024-11-17,1632,8.6,Machine Intelligence Group +AI07801,Computer Vision Engineer,153315,CAD,191644,EX,FL,Canada,L,Portugal,0,"Java, R, SQL, Deep Learning, Docker",Associate,13,Consulting,2024-11-22,2024-12-17,1764,7.7,TechCorp Inc +AI07802,Machine Learning Researcher,205401,USD,205401,EX,FT,Denmark,M,Denmark,100,"R, TensorFlow, Mathematics",PhD,10,Healthcare,2024-03-18,2024-05-24,1464,8.4,Smart Analytics +AI07803,Robotics Engineer,57780,CAD,72225,EN,PT,Canada,S,Canada,100,"Java, NLP, Mathematics",PhD,1,Retail,2024-10-31,2025-01-10,2381,9.8,TechCorp Inc +AI07804,AI Research Scientist,110762,USD,110762,MI,CT,Norway,L,Sweden,100,"R, Data Visualization, Git, Docker",PhD,2,Real Estate,2024-11-03,2024-12-19,777,6.8,Cognitive Computing +AI07805,Deep Learning Engineer,157791,EUR,134122,SE,FL,France,L,France,50,"Git, Java, GCP, SQL, AWS",PhD,9,Gaming,2024-10-16,2024-11-01,1818,7.8,Cognitive Computing +AI07806,AI Software Engineer,146629,USD,146629,SE,PT,Denmark,S,Denmark,50,"Git, TensorFlow, Deep Learning",Associate,8,Manufacturing,2025-04-25,2025-06-02,1219,8.6,Autonomous Tech +AI07807,AI Consultant,67825,USD,67825,MI,FT,Sweden,S,Poland,100,"Java, Scala, R, SQL, Kubernetes",PhD,3,Education,2025-03-26,2025-06-03,1845,7.4,Autonomous Tech +AI07808,Autonomous Systems Engineer,53522,USD,53522,SE,FL,China,S,China,0,"PyTorch, GCP, Mathematics",Associate,9,Gaming,2025-04-19,2025-05-20,1898,8.6,Future Systems +AI07809,Robotics Engineer,96556,CAD,120695,MI,FT,Canada,L,Portugal,100,"PyTorch, Statistics, Deep Learning",Associate,4,Gaming,2024-10-10,2024-11-19,1150,9.1,DataVision Ltd +AI07810,AI Consultant,161008,USD,161008,SE,CT,Israel,L,Israel,0,"Docker, Deep Learning, Python, Git, Kubernetes",Master,9,Education,2025-03-25,2025-05-08,1648,5.7,Cognitive Computing +AI07811,Head of AI,71917,JPY,7910870,EN,PT,Japan,M,Hungary,100,"Tableau, PyTorch, GCP",Master,1,Media,2024-11-04,2024-12-29,2269,9.6,Neural Networks Co +AI07812,AI Research Scientist,143195,CAD,178994,EX,FL,Canada,S,Canada,50,"Java, Linux, Scala, NLP, Tableau",PhD,13,Healthcare,2025-04-12,2025-06-07,510,5.3,Neural Networks Co +AI07813,Robotics Engineer,135878,SGD,176641,SE,FT,Singapore,S,Singapore,0,"Azure, Kubernetes, Tableau",Bachelor,9,Technology,2024-12-28,2025-02-13,772,8.2,AI Innovations +AI07814,AI Consultant,58123,USD,58123,EN,PT,Finland,L,Finland,50,"Linux, AWS, GCP",Master,1,Manufacturing,2025-01-22,2025-02-10,1596,7.8,Digital Transformation LLC +AI07815,Principal Data Scientist,85459,USD,85459,EX,FT,India,M,Estonia,0,"Scala, Spark, AWS, Statistics",Master,16,Technology,2024-09-10,2024-11-20,1167,7.5,Advanced Robotics +AI07816,AI Consultant,188011,EUR,159809,EX,FL,Germany,S,Germany,0,"SQL, Kubernetes, Tableau",Bachelor,10,Transportation,2024-05-26,2024-07-10,2353,5.7,TechCorp Inc +AI07817,NLP Engineer,76608,USD,76608,EN,CT,United States,M,United States,100,"Hadoop, Spark, Python, GCP, SQL",Associate,1,Transportation,2024-11-19,2025-01-29,617,6.1,AI Innovations +AI07818,Computer Vision Engineer,87288,GBP,65466,MI,PT,United Kingdom,M,Egypt,50,"Statistics, Kubernetes, Tableau, Linux",Master,4,Energy,2024-08-22,2024-09-09,1983,8.5,Cloud AI Solutions +AI07819,AI Specialist,114472,JPY,12591920,SE,CT,Japan,S,France,50,"Mathematics, Hadoop, Spark, Tableau, GCP",Bachelor,5,Education,2024-10-03,2024-11-30,1545,8.3,DeepTech Ventures +AI07820,AI Research Scientist,115293,GBP,86470,MI,CT,United Kingdom,M,Romania,0,"PyTorch, Kubernetes, Deep Learning, Git",Associate,4,Finance,2024-01-17,2024-03-21,1165,6.1,AI Innovations +AI07821,Deep Learning Engineer,85770,USD,85770,SE,PT,South Korea,S,South Korea,50,"GCP, Computer Vision, Hadoop, Azure",PhD,7,Government,2024-08-30,2024-10-31,2128,9.5,Digital Transformation LLC +AI07822,Computer Vision Engineer,153843,EUR,130767,EX,FT,France,M,France,50,"Python, Tableau, SQL, PyTorch, Hadoop",Bachelor,16,Education,2025-02-23,2025-03-23,1151,9.8,DeepTech Ventures +AI07823,NLP Engineer,119824,CHF,107842,MI,FL,Switzerland,M,Switzerland,50,"Linux, Computer Vision, R, Python",PhD,3,Technology,2025-04-25,2025-05-13,2109,8.8,Neural Networks Co +AI07824,Data Engineer,88480,EUR,75208,MI,FL,Germany,M,Finland,100,"PyTorch, Kubernetes, MLOps, Scala, Java",Master,4,Energy,2024-02-16,2024-04-08,1029,9.3,DeepTech Ventures +AI07825,AI Research Scientist,86607,USD,86607,SE,PT,Finland,S,Finland,100,"GCP, AWS, MLOps",PhD,7,Consulting,2024-04-24,2024-05-12,2162,8.8,Digital Transformation LLC +AI07826,AI Research Scientist,185098,EUR,157333,EX,FL,Netherlands,M,Netherlands,50,"Docker, Azure, Git, Deep Learning",Bachelor,18,Gaming,2024-04-11,2024-05-28,902,5.8,AI Innovations +AI07827,AI Specialist,42629,USD,42629,EN,FT,South Korea,S,Sweden,0,"Spark, Hadoop, Tableau",Bachelor,0,Energy,2024-07-06,2024-07-21,1250,5.1,Cloud AI Solutions +AI07828,AI Architect,73796,EUR,62727,EN,FL,France,L,France,100,"Deep Learning, SQL, PyTorch",Bachelor,0,Government,2024-06-09,2024-07-23,2437,5.8,Cognitive Computing +AI07829,AI Consultant,145709,USD,145709,EX,FT,United States,S,Mexico,100,"Python, Azure, Tableau, Statistics",Bachelor,18,Energy,2024-09-11,2024-09-26,1740,7.9,TechCorp Inc +AI07830,Principal Data Scientist,153383,CHF,138045,MI,FT,Switzerland,M,Switzerland,100,"Kubernetes, SQL, Tableau",Associate,4,Consulting,2024-02-21,2024-03-08,686,7.6,Quantum Computing Inc +AI07831,Data Analyst,138997,USD,138997,SE,CT,Israel,L,Israel,50,"Python, Git, Computer Vision, Java, GCP",Bachelor,5,Telecommunications,2024-11-15,2024-12-13,1685,6.3,Algorithmic Solutions +AI07832,ML Ops Engineer,52674,USD,52674,EN,CT,Israel,S,Italy,50,"Git, Tableau, Computer Vision, SQL",Master,0,Gaming,2024-01-12,2024-02-08,1383,7.3,Cloud AI Solutions +AI07833,NLP Engineer,46073,USD,46073,EN,PT,Sweden,S,France,0,"Python, MLOps, R",Bachelor,0,Manufacturing,2024-04-23,2024-06-29,1299,5.1,Advanced Robotics +AI07834,AI Architect,143115,EUR,121648,SE,FT,Austria,M,Austria,50,"Python, Data Visualization, TensorFlow, Statistics",Associate,9,Retail,2024-06-26,2024-08-20,1232,9.1,Smart Analytics +AI07835,Machine Learning Engineer,133093,EUR,113129,EX,CT,Austria,S,Austria,100,"Tableau, Docker, Hadoop, Scala, R",PhD,11,Media,2024-07-25,2024-09-09,1717,5.9,Neural Networks Co +AI07836,Autonomous Systems Engineer,99958,USD,99958,MI,CT,Sweden,M,Romania,50,"Data Visualization, Java, NLP",Associate,2,Retail,2024-10-20,2024-11-14,655,5.9,Autonomous Tech +AI07837,AI Consultant,100906,JPY,11099660,MI,PT,Japan,M,Nigeria,0,"Mathematics, R, Deep Learning",Associate,3,Finance,2024-11-23,2025-01-08,1322,9.6,DeepTech Ventures +AI07838,Principal Data Scientist,73621,USD,73621,EN,PT,Ireland,L,Ireland,0,"Java, Scala, Python",Master,0,Finance,2024-12-14,2025-01-19,1999,7.3,DeepTech Ventures +AI07839,ML Ops Engineer,131785,AUD,177910,SE,CT,Australia,M,Mexico,0,"PyTorch, Linux, Computer Vision, Azure",Master,5,Real Estate,2025-02-03,2025-02-17,785,5.8,Predictive Systems +AI07840,NLP Engineer,302166,USD,302166,EX,FT,United States,L,United States,100,"Python, Linux, Hadoop, MLOps, Azure",PhD,15,Consulting,2024-05-16,2024-07-06,1539,8.4,Cognitive Computing +AI07841,AI Specialist,230443,USD,230443,EX,CT,United States,L,United States,50,"Git, R, AWS, SQL",Associate,11,Gaming,2024-05-24,2024-06-14,589,7.7,Digital Transformation LLC +AI07842,Machine Learning Engineer,52678,USD,52678,EN,PT,Sweden,S,Romania,0,"Kubernetes, SQL, Computer Vision, MLOps, Deep Learning",Master,0,Technology,2025-02-09,2025-04-21,2097,8.8,DataVision Ltd +AI07843,Data Scientist,219188,CHF,197269,EX,PT,Switzerland,M,Switzerland,0,"Kubernetes, Docker, Linux, Azure, Scala",Associate,19,Government,2024-07-05,2024-08-08,1009,8.2,Smart Analytics +AI07844,AI Specialist,63772,USD,63772,SE,PT,China,M,China,0,"PyTorch, Java, GCP, Mathematics",PhD,8,Retail,2024-10-24,2024-12-14,1928,8.2,Advanced Robotics +AI07845,NLP Engineer,63461,EUR,53942,MI,FT,Austria,S,Austria,50,"Computer Vision, Git, Python",Bachelor,2,Telecommunications,2025-01-12,2025-03-25,1638,7.5,Future Systems +AI07846,AI Consultant,125077,USD,125077,MI,PT,Norway,L,Norway,100,"Data Visualization, TensorFlow, Java, Deep Learning",PhD,4,Automotive,2024-02-15,2024-04-06,1340,7.5,Cloud AI Solutions +AI07847,Computer Vision Engineer,157223,EUR,133640,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Scala",Master,7,Manufacturing,2024-03-24,2024-04-12,1193,6.3,AI Innovations +AI07848,Data Scientist,216895,EUR,184361,EX,CT,Netherlands,L,India,100,"Tableau, Scala, AWS",Bachelor,19,Automotive,2024-02-08,2024-02-27,1605,9,Advanced Robotics +AI07849,AI Architect,133507,USD,133507,SE,FT,Sweden,S,Vietnam,50,"TensorFlow, Git, AWS, GCP, Deep Learning",Master,5,Finance,2024-02-28,2024-04-29,1863,6.8,Advanced Robotics +AI07850,Data Engineer,207722,USD,207722,EX,FL,South Korea,L,South Korea,100,"Statistics, Git, Spark, R",Bachelor,17,Media,2024-08-08,2024-09-20,1585,8.9,DataVision Ltd +AI07851,Machine Learning Engineer,91743,EUR,77982,MI,CT,Netherlands,L,Netherlands,50,"Hadoop, Tableau, Scala",Associate,2,Retail,2024-07-16,2024-09-19,1685,7,AI Innovations +AI07852,ML Ops Engineer,87600,USD,87600,MI,FT,Denmark,S,Denmark,100,"GCP, Docker, Python, Spark, NLP",PhD,2,Education,2025-02-18,2025-03-07,881,6.5,Cloud AI Solutions +AI07853,AI Product Manager,78893,USD,78893,MI,PT,South Korea,M,Israel,50,"Docker, PyTorch, Kubernetes, MLOps",PhD,4,Healthcare,2024-09-19,2024-10-29,1284,9.5,Machine Intelligence Group +AI07854,Research Scientist,139691,USD,139691,EX,PT,Israel,S,Israel,100,"Linux, Python, Data Visualization",Master,15,Media,2024-10-24,2024-11-13,800,6.9,Quantum Computing Inc +AI07855,Principal Data Scientist,71086,USD,71086,MI,FL,Finland,S,Finland,0,"Hadoop, Azure, NLP, PyTorch, TensorFlow",Associate,2,Telecommunications,2025-04-12,2025-06-07,2412,6.7,TechCorp Inc +AI07856,AI Consultant,38307,USD,38307,SE,FL,India,M,India,50,"Hadoop, PyTorch, Computer Vision, SQL",Master,7,Education,2024-08-13,2024-10-13,1489,5.8,AI Innovations +AI07857,Principal Data Scientist,236250,USD,236250,EX,FT,Norway,L,Norway,50,"SQL, Mathematics, Java",PhD,15,Automotive,2024-02-24,2024-03-27,1164,7.3,Algorithmic Solutions +AI07858,NLP Engineer,94410,CHF,84969,MI,CT,Switzerland,S,Switzerland,50,"Hadoop, Linux, Computer Vision, Spark, PyTorch",PhD,4,Automotive,2024-03-26,2024-05-03,1633,9.5,Cloud AI Solutions +AI07859,ML Ops Engineer,239612,EUR,203670,EX,PT,Austria,L,Israel,100,"Docker, Scala, Java, Deep Learning, R",Associate,10,Healthcare,2024-05-07,2024-05-29,1636,5.3,Algorithmic Solutions +AI07860,Data Analyst,49846,USD,49846,EN,FT,South Korea,L,South Korea,50,"TensorFlow, SQL, Mathematics",Bachelor,1,Manufacturing,2024-09-12,2024-11-07,602,9.6,Cloud AI Solutions +AI07861,Data Scientist,90589,SGD,117766,MI,CT,Singapore,M,Singapore,50,"Computer Vision, Linux, MLOps, Scala, Kubernetes",Master,3,Real Estate,2024-10-29,2024-11-30,2105,8.8,Cloud AI Solutions +AI07862,Machine Learning Researcher,75857,USD,75857,EN,FT,Denmark,S,Denmark,100,"R, Spark, GCP",Associate,0,Transportation,2025-04-05,2025-06-04,1331,7.5,Future Systems +AI07863,Machine Learning Engineer,229106,USD,229106,EX,PT,United States,S,United States,0,"Python, MLOps, Data Visualization, Deep Learning",Associate,10,Transportation,2024-06-03,2024-06-28,703,8.9,DeepTech Ventures +AI07864,Robotics Engineer,226048,EUR,192141,EX,FT,Germany,M,Germany,100,"Java, PyTorch, TensorFlow, SQL",PhD,15,Media,2025-01-28,2025-02-17,1648,8.8,Cloud AI Solutions +AI07865,Robotics Engineer,74551,EUR,63368,MI,PT,Austria,S,Austria,0,"R, Statistics, Mathematics, Data Visualization",Associate,3,Finance,2024-06-09,2024-08-20,1298,5.1,Autonomous Tech +AI07866,Deep Learning Engineer,209614,EUR,178172,EX,CT,Netherlands,S,Netherlands,100,"Scala, NLP, Kubernetes",Associate,18,Automotive,2024-03-08,2024-04-28,1958,7.1,Algorithmic Solutions +AI07867,Research Scientist,62202,USD,62202,EN,PT,Ireland,S,Hungary,100,"Statistics, Spark, Scala, Linux",Master,1,Technology,2024-09-13,2024-10-19,2499,8.3,Digital Transformation LLC +AI07868,Data Engineer,76226,SGD,99094,EN,CT,Singapore,L,Singapore,100,"Spark, SQL, Python, Scala, Deep Learning",Master,1,Government,2024-10-30,2024-12-11,1269,5.5,DataVision Ltd +AI07869,Principal Data Scientist,186638,CHF,167974,SE,FL,Switzerland,M,Switzerland,100,"Spark, Linux, Python",PhD,9,Consulting,2024-03-01,2024-05-07,1062,8.2,Smart Analytics +AI07870,AI Research Scientist,275375,USD,275375,EX,FT,Ireland,L,Ireland,50,"Mathematics, Azure, Scala",Associate,15,Healthcare,2024-07-29,2024-09-19,1842,6,Autonomous Tech +AI07871,Autonomous Systems Engineer,59693,JPY,6566230,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, SQL, Deep Learning",Associate,1,Finance,2024-11-15,2025-01-22,765,5.1,Cloud AI Solutions +AI07872,Research Scientist,72671,USD,72671,EN,FT,Sweden,L,Sweden,100,"Kubernetes, Scala, Linux, Docker, NLP",Bachelor,1,Retail,2024-10-18,2024-11-25,827,8.9,Cognitive Computing +AI07873,AI Architect,103897,AUD,140261,MI,PT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, SQL, Deep Learning",Master,3,Telecommunications,2024-12-29,2025-03-02,547,9.2,TechCorp Inc +AI07874,Head of AI,101567,AUD,137115,SE,FL,Australia,S,Australia,0,"Linux, Hadoop, MLOps",Master,6,Real Estate,2024-09-11,2024-10-07,1857,9.1,Predictive Systems +AI07875,Head of AI,74940,USD,74940,EN,PT,Sweden,L,Sweden,50,"GCP, Computer Vision, Python",PhD,1,Real Estate,2024-01-16,2024-03-22,2286,6.1,Algorithmic Solutions +AI07876,Machine Learning Researcher,204444,GBP,153333,EX,PT,United Kingdom,M,United Kingdom,50,"MLOps, Azure, TensorFlow, Python",Bachelor,13,Finance,2024-11-19,2024-12-19,1862,7,Autonomous Tech +AI07877,Deep Learning Engineer,264606,CAD,330758,EX,CT,Canada,L,Canada,100,"GCP, SQL, Azure, R",PhD,11,Government,2024-02-07,2024-04-10,2308,6.4,Digital Transformation LLC +AI07878,AI Product Manager,170883,EUR,145251,EX,CT,Germany,S,Germany,50,"Python, Git, Tableau, TensorFlow, Statistics",Master,17,Media,2024-03-23,2024-05-24,1102,7.6,Smart Analytics +AI07879,Data Analyst,152247,USD,152247,MI,FT,Denmark,L,Denmark,100,"SQL, Scala, Statistics",PhD,2,Transportation,2024-05-15,2024-06-06,529,8.5,Machine Intelligence Group +AI07880,AI Specialist,75029,AUD,101289,MI,FT,Australia,M,Australia,100,"Hadoop, MLOps, Tableau, GCP",Bachelor,4,Manufacturing,2024-09-09,2024-10-06,2288,8.7,DeepTech Ventures +AI07881,Machine Learning Engineer,44910,USD,44910,SE,FL,India,M,India,50,"Azure, R, Statistics, NLP",Master,8,Transportation,2024-06-09,2024-07-10,1285,6.9,TechCorp Inc +AI07882,Autonomous Systems Engineer,57794,GBP,43346,EN,FT,United Kingdom,M,United Kingdom,0,"NLP, AWS, R, Python, TensorFlow",Master,0,Finance,2024-03-01,2024-05-11,1515,10,Future Systems +AI07883,AI Research Scientist,155551,USD,155551,SE,FT,Denmark,S,Netherlands,50,"GCP, Linux, MLOps",Master,9,Finance,2024-12-08,2025-01-14,2040,8.3,TechCorp Inc +AI07884,Computer Vision Engineer,185612,USD,185612,EX,FL,Ireland,L,Ireland,50,"Scala, PyTorch, NLP",Master,13,Manufacturing,2025-04-27,2025-06-28,1410,9.3,Cognitive Computing +AI07885,Deep Learning Engineer,69810,JPY,7679100,EN,FL,Japan,M,Japan,50,"Docker, Scala, Python, Statistics, Hadoop",Master,0,Retail,2024-04-20,2024-06-12,874,5.9,Future Systems +AI07886,Machine Learning Engineer,108934,EUR,92594,MI,PT,Netherlands,L,Philippines,0,"Hadoop, Linux, NLP",PhD,3,Real Estate,2024-10-04,2024-10-31,2217,8.1,TechCorp Inc +AI07887,Robotics Engineer,116867,USD,116867,MI,FL,United States,M,United States,100,"Python, Deep Learning, Hadoop, Docker",Bachelor,4,Technology,2024-05-29,2024-07-30,1731,9.8,TechCorp Inc +AI07888,Principal Data Scientist,107417,EUR,91304,MI,FL,Austria,L,Czech Republic,100,"Spark, Computer Vision, Azure, SQL, Scala",Bachelor,2,Manufacturing,2024-12-12,2025-01-29,581,8.2,Quantum Computing Inc +AI07889,Autonomous Systems Engineer,60938,EUR,51797,EN,FT,Austria,S,Austria,50,"Tableau, Python, TensorFlow",Bachelor,1,Telecommunications,2024-04-06,2024-04-24,1259,6.8,AI Innovations +AI07890,Computer Vision Engineer,228287,GBP,171215,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Azure, Scala, SQL, Git",Master,14,Education,2024-04-17,2024-05-28,1740,9.3,DataVision Ltd +AI07891,AI Consultant,149332,USD,149332,SE,PT,Norway,M,Norway,50,"Deep Learning, R, Kubernetes",PhD,7,Energy,2024-07-02,2024-07-31,1673,8.9,Smart Analytics +AI07892,Autonomous Systems Engineer,101212,CAD,126515,SE,PT,Canada,M,Canada,100,"NLP, Scala, Python, PyTorch",Master,6,Media,2024-03-02,2024-03-21,1825,9.5,Algorithmic Solutions +AI07893,AI Architect,136111,USD,136111,MI,PT,Denmark,L,Denmark,0,"Scala, AWS, Hadoop, Python, Git",Associate,2,Automotive,2025-03-24,2025-05-11,1343,5.9,Future Systems +AI07894,Autonomous Systems Engineer,106323,GBP,79742,MI,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, Scala",Bachelor,3,Technology,2024-12-23,2025-02-28,2392,8.7,DeepTech Ventures +AI07895,Computer Vision Engineer,156650,AUD,211478,EX,FT,Australia,M,Netherlands,50,"Data Visualization, Azure, SQL, Hadoop, Java",Master,12,Transportation,2024-08-19,2024-10-15,763,5.7,Algorithmic Solutions +AI07896,Data Scientist,137174,EUR,116598,SE,PT,France,M,Philippines,0,"Java, Python, Data Visualization, AWS",Bachelor,5,Consulting,2025-04-16,2025-05-09,1132,7.2,Cognitive Computing +AI07897,AI Product Manager,106794,USD,106794,MI,CT,Finland,L,South Korea,100,"MLOps, AWS, Tableau, SQL, Python",Associate,2,Retail,2025-04-06,2025-05-12,1189,6.1,Quantum Computing Inc +AI07898,Autonomous Systems Engineer,229594,CAD,286993,EX,PT,Canada,M,Canada,0,"Python, Linux, MLOps",PhD,15,Energy,2024-11-24,2024-12-23,1826,7.1,Quantum Computing Inc +AI07899,Autonomous Systems Engineer,72245,EUR,61408,EN,PT,Netherlands,M,Netherlands,50,"SQL, PyTorch, AWS, Linux",PhD,0,Finance,2024-10-30,2024-12-09,2296,7.6,Autonomous Tech +AI07900,AI Architect,154453,USD,154453,SE,PT,Ireland,L,Ireland,0,"Data Visualization, Linux, R, Python, Azure",Associate,6,Retail,2024-12-25,2025-03-07,1418,8.6,Algorithmic Solutions +AI07901,AI Specialist,64086,EUR,54473,EN,CT,Germany,S,Romania,50,"Java, R, SQL, Git, Deep Learning",Bachelor,1,Technology,2024-07-23,2024-08-17,2472,5.1,Autonomous Tech +AI07902,ML Ops Engineer,101108,EUR,85942,MI,PT,France,L,France,100,"Statistics, Linux, Mathematics",Bachelor,3,Energy,2025-04-03,2025-06-05,2003,6.3,Machine Intelligence Group +AI07903,Head of AI,88469,USD,88469,EN,FL,Denmark,L,Denmark,100,"Python, Linux, MLOps",PhD,1,Gaming,2024-12-01,2025-02-07,626,6,Digital Transformation LLC +AI07904,Data Engineer,111556,USD,111556,EX,CT,China,M,China,50,"SQL, GCP, Kubernetes",Master,15,Telecommunications,2024-11-05,2024-12-19,1737,5.5,Quantum Computing Inc +AI07905,AI Research Scientist,95017,EUR,80764,MI,FT,Netherlands,S,Thailand,100,"Azure, SQL, Computer Vision, R",Bachelor,2,Transportation,2025-03-23,2025-04-09,1717,7.8,Cognitive Computing +AI07906,Data Analyst,98367,AUD,132795,SE,PT,Australia,S,Mexico,50,"Docker, Statistics, Python, NLP, Tableau",PhD,7,Gaming,2024-02-04,2024-04-07,1534,8.7,Smart Analytics +AI07907,AI Product Manager,92735,EUR,78825,EN,PT,Germany,L,Chile,0,"Tableau, SQL, TensorFlow",PhD,0,Finance,2025-04-28,2025-05-30,1976,5.2,TechCorp Inc +AI07908,Principal Data Scientist,135039,USD,135039,SE,FL,Ireland,M,Ireland,0,"Python, Azure, Data Visualization, SQL",Master,7,Media,2024-04-06,2024-05-24,1236,8.6,Machine Intelligence Group +AI07909,Machine Learning Engineer,205457,EUR,174638,EX,FT,Netherlands,M,Netherlands,50,"Git, Kubernetes, Hadoop",Bachelor,10,Technology,2025-03-30,2025-04-17,1285,9.3,Future Systems +AI07910,Deep Learning Engineer,86892,JPY,9558120,MI,FL,Japan,S,Japan,50,"MLOps, Python, Linux, TensorFlow, GCP",PhD,2,Technology,2024-06-24,2024-07-20,1287,5.6,Neural Networks Co +AI07911,AI Product Manager,100067,EUR,85057,MI,FL,Netherlands,L,Netherlands,100,"AWS, Deep Learning, Computer Vision",PhD,4,Healthcare,2024-12-18,2025-02-04,1780,5.7,Advanced Robotics +AI07912,Autonomous Systems Engineer,86435,USD,86435,EN,CT,Sweden,L,Sweden,50,"Kubernetes, NLP, Tableau, Python, Computer Vision",PhD,1,Education,2024-12-18,2025-01-04,2053,6.1,Machine Intelligence Group +AI07913,AI Product Manager,69261,SGD,90039,MI,FL,Singapore,S,Singapore,100,"Python, SQL, Docker",Associate,2,Automotive,2024-05-26,2024-07-27,1673,7,Cloud AI Solutions +AI07914,Computer Vision Engineer,187635,CHF,168872,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, AWS, MLOps, R, GCP",PhD,5,Consulting,2024-06-23,2024-08-21,2261,8.7,Neural Networks Co +AI07915,Data Engineer,150751,CHF,135676,MI,FT,Switzerland,M,Switzerland,50,"Statistics, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2025-02-21,2025-04-12,1563,7.4,Machine Intelligence Group +AI07916,AI Product Manager,117003,AUD,157954,SE,FL,Australia,M,Australia,100,"TensorFlow, AWS, MLOps, Azure, Linux",PhD,8,Manufacturing,2025-02-25,2025-05-09,533,8.4,DataVision Ltd +AI07917,Machine Learning Engineer,81733,EUR,69473,EN,FL,France,L,Belgium,50,"Azure, TensorFlow, Tableau, Python",Associate,0,Real Estate,2024-04-03,2024-05-06,1383,8.5,AI Innovations +AI07918,AI Architect,187345,USD,187345,EX,CT,Ireland,S,Ireland,0,"R, Data Visualization, SQL, Docker",Master,11,Gaming,2024-03-22,2024-05-05,1543,8.3,Cognitive Computing +AI07919,Robotics Engineer,143200,USD,143200,MI,PT,Denmark,L,Denmark,100,"Spark, Computer Vision, Data Visualization, GCP, AWS",PhD,3,Transportation,2025-02-15,2025-03-26,1646,7.2,Smart Analytics +AI07920,AI Product Manager,68868,EUR,58538,EN,FL,Germany,S,Finland,0,"NLP, TensorFlow, Azure",PhD,1,Education,2024-09-02,2024-10-25,571,6.7,Predictive Systems +AI07921,Autonomous Systems Engineer,79844,USD,79844,MI,CT,Sweden,M,Mexico,0,"Kubernetes, AWS, NLP",Master,2,Telecommunications,2024-01-20,2024-02-28,1962,5.4,Smart Analytics +AI07922,Research Scientist,158799,USD,158799,SE,FT,Denmark,L,Denmark,0,"Scala, R, Git",PhD,9,Education,2024-12-30,2025-02-02,1832,6.6,Quantum Computing Inc +AI07923,AI Architect,125614,EUR,106772,SE,FT,Netherlands,L,Argentina,100,"PyTorch, Python, GCP",Bachelor,5,Automotive,2024-05-23,2024-07-05,2140,5.6,Predictive Systems +AI07924,AI Software Engineer,104482,USD,104482,MI,FT,United States,L,United States,0,"Java, SQL, Statistics",PhD,3,Gaming,2024-11-22,2024-12-09,1939,5.3,Neural Networks Co +AI07925,Deep Learning Engineer,196895,EUR,167361,EX,FT,Austria,M,Austria,50,"Scala, Spark, PyTorch",Bachelor,16,Gaming,2024-07-30,2024-10-08,751,6.9,AI Innovations +AI07926,Computer Vision Engineer,133125,EUR,113156,SE,PT,Germany,M,Germany,50,"MLOps, R, Statistics",Master,8,Consulting,2025-03-17,2025-04-28,1400,6.3,DeepTech Ventures +AI07927,AI Specialist,182420,USD,182420,EX,CT,South Korea,L,South Korea,50,"PyTorch, Data Visualization, Spark",Master,17,Energy,2024-07-03,2024-07-26,1745,8.9,Predictive Systems +AI07928,AI Architect,151509,CHF,136358,SE,CT,Switzerland,M,Switzerland,100,"TensorFlow, Python, Kubernetes, AWS",Master,8,Transportation,2024-01-07,2024-02-26,1536,5.8,Advanced Robotics +AI07929,Head of AI,69352,USD,69352,MI,CT,Finland,M,Finland,0,"Data Visualization, TensorFlow, Azure",PhD,3,Manufacturing,2024-12-25,2025-02-02,1882,6.8,Advanced Robotics +AI07930,NLP Engineer,45522,USD,45522,SE,PT,India,S,India,0,"Computer Vision, Hadoop, Git, MLOps",PhD,9,Automotive,2024-04-08,2024-05-06,1194,6.9,Future Systems +AI07931,Data Engineer,43570,USD,43570,SE,PT,India,S,India,100,"MLOps, Hadoop, Spark, NLP, Mathematics",Associate,9,Energy,2024-08-05,2024-09-23,1359,8.8,AI Innovations +AI07932,AI Software Engineer,98915,USD,98915,MI,CT,Israel,M,Israel,0,"Docker, Git, TensorFlow, GCP",Associate,3,Real Estate,2025-03-02,2025-04-18,2083,7.5,Machine Intelligence Group +AI07933,Research Scientist,132893,USD,132893,MI,FT,Norway,M,Thailand,50,"Computer Vision, SQL, Tableau",Bachelor,2,Real Estate,2024-10-23,2024-11-16,1749,6.9,TechCorp Inc +AI07934,ML Ops Engineer,97204,CHF,87484,EN,PT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Docker",Bachelor,1,Finance,2025-03-31,2025-04-29,816,9.8,Predictive Systems +AI07935,Machine Learning Engineer,127523,USD,127523,MI,FL,United States,M,United States,0,"Hadoop, Mathematics, Docker, Data Visualization, Kubernetes",Bachelor,2,Education,2024-04-13,2024-04-27,634,5.7,Quantum Computing Inc +AI07936,AI Product Manager,89735,USD,89735,EN,CT,Norway,L,Norway,50,"Java, Python, Git",Associate,0,Government,2025-03-10,2025-04-14,757,6.2,TechCorp Inc +AI07937,Research Scientist,97385,USD,97385,MI,PT,Norway,S,Norway,0,"Docker, PyTorch, NLP, Python",PhD,4,Education,2024-12-16,2025-02-13,1489,5.8,Autonomous Tech +AI07938,Machine Learning Researcher,52180,USD,52180,EN,CT,Sweden,S,Egypt,100,"PyTorch, Java, Statistics",Associate,0,Finance,2024-12-05,2025-01-07,2313,7.8,DataVision Ltd +AI07939,Robotics Engineer,233176,USD,233176,EX,FT,Denmark,L,Denmark,0,"Hadoop, Python, Azure, TensorFlow",Bachelor,18,Media,2024-07-09,2024-08-04,2378,6.6,Digital Transformation LLC +AI07940,NLP Engineer,151930,AUD,205106,EX,FT,Australia,M,Australia,100,"NLP, Java, PyTorch, TensorFlow",PhD,17,Energy,2024-05-05,2024-07-01,543,9.3,DeepTech Ventures +AI07941,Data Analyst,166632,SGD,216622,EX,PT,Singapore,M,Singapore,100,"Linux, MLOps, Python",Bachelor,15,Media,2025-02-14,2025-03-25,1476,5.7,Cloud AI Solutions +AI07942,Data Analyst,100715,USD,100715,MI,CT,United States,M,United States,0,"SQL, Statistics, Git, Data Visualization, Java",Associate,2,Consulting,2024-06-25,2024-08-27,1320,6,DeepTech Ventures +AI07943,Computer Vision Engineer,74580,JPY,8203800,EN,CT,Japan,S,Japan,0,"Git, Computer Vision, Tableau",Associate,0,Telecommunications,2024-03-02,2024-04-17,616,5.5,DataVision Ltd +AI07944,AI Architect,120355,SGD,156462,SE,FT,Singapore,M,Philippines,50,"Scala, Python, MLOps, SQL",Master,5,Gaming,2024-03-11,2024-03-25,1771,5.8,Neural Networks Co +AI07945,AI Specialist,129835,USD,129835,EX,CT,Ireland,S,Ireland,100,"Deep Learning, Spark, Tableau, Python",Bachelor,11,Media,2025-01-24,2025-03-28,1977,7.4,Cognitive Computing +AI07946,AI Product Manager,143095,EUR,121631,SE,FT,Netherlands,L,Russia,0,"MLOps, Kubernetes, Tableau",Bachelor,5,Media,2024-08-04,2024-10-13,1147,8.4,Predictive Systems +AI07947,AI Consultant,162582,CHF,146324,SE,CT,Switzerland,M,Malaysia,100,"Data Visualization, Docker, Computer Vision, Git",PhD,9,Healthcare,2025-04-30,2025-05-18,558,6.1,Neural Networks Co +AI07948,Deep Learning Engineer,66995,USD,66995,EX,CT,India,M,India,100,"Python, MLOps, TensorFlow",Bachelor,13,Finance,2025-04-30,2025-05-22,1661,6,Cognitive Computing +AI07949,AI Specialist,99477,JPY,10942470,MI,PT,Japan,L,Japan,100,"Hadoop, R, Scala, Azure",Bachelor,2,Government,2024-10-18,2024-12-14,594,8.8,Algorithmic Solutions +AI07950,AI Architect,159574,USD,159574,SE,FT,Denmark,L,Ghana,50,"Python, Data Visualization, Git, PyTorch",Master,9,Finance,2025-04-07,2025-04-29,998,5.3,Predictive Systems +AI07951,AI Product Manager,23228,USD,23228,EN,PT,India,S,India,0,"MLOps, Hadoop, R, TensorFlow, Tableau",Associate,1,Technology,2024-03-01,2024-04-02,1213,7.5,DataVision Ltd +AI07952,AI Architect,173217,USD,173217,SE,CT,United States,M,United States,50,"Statistics, Linux, Docker, Deep Learning",Bachelor,5,Real Estate,2024-02-10,2024-03-18,1019,6.8,DataVision Ltd +AI07953,AI Research Scientist,80075,USD,80075,MI,PT,Finland,L,Finland,100,"SQL, AWS, TensorFlow, Mathematics, Linux",Bachelor,4,Healthcare,2024-05-31,2024-07-03,2425,8.4,Cognitive Computing +AI07954,Data Scientist,55361,JPY,6089710,EN,PT,Japan,S,Japan,100,"SQL, PyTorch, Hadoop, Kubernetes",Bachelor,1,Telecommunications,2024-07-09,2024-09-04,2030,5.8,Quantum Computing Inc +AI07955,Research Scientist,93720,USD,93720,MI,FL,Israel,M,Israel,50,"PyTorch, TensorFlow, MLOps",Master,4,Manufacturing,2024-10-22,2024-11-12,1971,5.9,Future Systems +AI07956,Data Engineer,103590,USD,103590,MI,FT,Finland,M,Ghana,0,"Python, AWS, Azure, Linux",Bachelor,3,Transportation,2024-10-28,2024-11-26,1170,6,Digital Transformation LLC +AI07957,Head of AI,166505,JPY,18315550,EX,PT,Japan,L,Japan,100,"Git, Docker, Python, GCP, Linux",PhD,17,Real Estate,2024-12-13,2025-01-02,858,5.3,Future Systems +AI07958,Deep Learning Engineer,150946,CHF,135851,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, Azure, Deep Learning",Associate,2,Transportation,2024-06-14,2024-08-26,1490,9.1,Cognitive Computing +AI07959,ML Ops Engineer,218604,AUD,295115,EX,PT,Australia,L,Ghana,50,"Tableau, Azure, AWS, Kubernetes, Java",PhD,17,Education,2024-04-17,2024-05-09,1976,5.3,Cognitive Computing +AI07960,Data Analyst,201864,USD,201864,EX,CT,Sweden,S,Sweden,100,"Computer Vision, Java, R",Associate,16,Transportation,2024-09-06,2024-10-26,523,6,Algorithmic Solutions +AI07961,AI Research Scientist,77414,AUD,104509,MI,PT,Australia,M,Argentina,100,"Scala, Java, Tableau",Bachelor,3,Energy,2024-01-13,2024-02-13,1416,5.2,TechCorp Inc +AI07962,Machine Learning Researcher,128494,EUR,109220,EX,FL,Austria,S,Austria,0,"Kubernetes, PyTorch, R",PhD,12,Transportation,2024-05-25,2024-08-04,730,5.5,Cognitive Computing +AI07963,AI Research Scientist,120539,USD,120539,EX,CT,China,L,China,0,"Python, GCP, Docker",Bachelor,10,Real Estate,2025-03-27,2025-06-06,572,8.7,Advanced Robotics +AI07964,AI Software Engineer,60570,USD,60570,EN,PT,Finland,L,Finland,0,"MLOps, Spark, TensorFlow, Kubernetes, SQL",Associate,1,Healthcare,2024-03-25,2024-04-16,1857,5.9,TechCorp Inc +AI07965,Research Scientist,88260,USD,88260,EN,PT,Denmark,S,Philippines,100,"Git, Statistics, Linux, Azure",Bachelor,0,Real Estate,2024-12-09,2025-01-01,1245,8.8,Smart Analytics +AI07966,Deep Learning Engineer,78518,USD,78518,MI,FT,Israel,S,Israel,50,"Hadoop, Kubernetes, Python, Deep Learning, Mathematics",Master,2,Real Estate,2024-09-12,2024-09-27,2279,8.7,TechCorp Inc +AI07967,Machine Learning Engineer,97759,EUR,83095,MI,FT,Netherlands,S,Netherlands,50,"PyTorch, GCP, Statistics, Docker",Master,2,Manufacturing,2025-03-11,2025-05-18,1358,6.1,TechCorp Inc +AI07968,Data Analyst,92686,EUR,78783,MI,FT,Germany,M,Israel,50,"Computer Vision, MLOps, TensorFlow, Python, PyTorch",PhD,2,Gaming,2025-02-10,2025-03-25,1588,9.7,Neural Networks Co +AI07969,Deep Learning Engineer,109730,CHF,98757,EN,CT,Switzerland,M,Switzerland,0,"Python, Spark, Tableau",Master,1,Manufacturing,2024-07-15,2024-09-05,1812,6.5,Neural Networks Co +AI07970,Computer Vision Engineer,61314,USD,61314,EX,FT,India,L,India,100,"Kubernetes, TensorFlow, MLOps",Bachelor,18,Telecommunications,2024-04-01,2024-05-20,953,5.8,Future Systems +AI07971,AI Research Scientist,34450,USD,34450,MI,CT,China,M,Switzerland,0,"Python, TensorFlow, Scala, Kubernetes, Java",Master,3,Retail,2024-07-06,2024-09-15,1840,8,Predictive Systems +AI07972,Deep Learning Engineer,104797,USD,104797,SE,CT,Ireland,S,Ireland,50,"Python, Data Visualization, Spark, SQL, Java",PhD,5,Retail,2025-01-28,2025-02-24,1987,8.8,Cognitive Computing +AI07973,NLP Engineer,143973,AUD,194364,SE,PT,Australia,L,Australia,100,"PyTorch, SQL, Hadoop",Bachelor,7,Education,2024-02-18,2024-04-18,683,9.4,Digital Transformation LLC +AI07974,Data Engineer,60516,USD,60516,EN,FL,Sweden,M,Sweden,50,"Java, PyTorch, Scala, Statistics",Master,0,Automotive,2024-09-13,2024-10-18,818,5.6,Machine Intelligence Group +AI07975,Autonomous Systems Engineer,110800,CHF,99720,MI,PT,Switzerland,M,Switzerland,50,"Python, Computer Vision, Kubernetes, R, TensorFlow",PhD,3,Healthcare,2024-05-13,2024-07-21,1718,5.9,TechCorp Inc +AI07976,Data Scientist,83576,USD,83576,SE,FT,South Korea,S,Norway,0,"Deep Learning, NLP, Data Visualization, Scala, Mathematics",Bachelor,5,Real Estate,2025-02-27,2025-05-03,1461,5.4,Advanced Robotics +AI07977,AI Consultant,150796,USD,150796,SE,CT,Finland,L,Finland,100,"Hadoop, NLP, Linux, Scala, Python",PhD,9,Media,2024-12-03,2024-12-23,766,5.7,Autonomous Tech +AI07978,Head of AI,67072,USD,67072,EN,PT,Israel,L,Israel,0,"Deep Learning, AWS, NLP, Docker, GCP",Associate,1,Telecommunications,2024-03-26,2024-05-01,1888,10,Cloud AI Solutions +AI07979,Robotics Engineer,51985,USD,51985,EN,FT,Sweden,S,Sweden,100,"AWS, R, MLOps, Azure",Master,0,Technology,2024-03-25,2024-05-18,2215,6.4,AI Innovations +AI07980,AI Product Manager,110993,USD,110993,SE,CT,Finland,M,Finland,100,"Linux, Tableau, SQL, Spark, Scala",PhD,5,Education,2024-04-12,2024-04-29,2320,5.5,Cloud AI Solutions +AI07981,Head of AI,94069,USD,94069,EN,FT,Norway,M,Norway,100,"R, TensorFlow, Java, Git, Python",Associate,1,Telecommunications,2024-09-14,2024-10-16,1036,7.7,DeepTech Ventures +AI07982,AI Architect,146889,CHF,132200,MI,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, Mathematics",PhD,4,Telecommunications,2025-03-04,2025-04-15,726,5.8,Advanced Robotics +AI07983,Principal Data Scientist,155346,USD,155346,SE,FL,United States,S,United States,0,"Computer Vision, Java, Git, Docker",Bachelor,9,Telecommunications,2025-01-01,2025-02-27,1994,9.9,TechCorp Inc +AI07984,Data Scientist,124124,EUR,105505,SE,CT,France,S,France,50,"TensorFlow, PyTorch, Tableau, Computer Vision",PhD,6,Gaming,2024-05-28,2024-08-07,1082,9.7,Cloud AI Solutions +AI07985,Deep Learning Engineer,137231,CAD,171539,EX,FT,Canada,S,Canada,100,"Docker, AWS, PyTorch, SQL",Associate,15,Consulting,2024-01-22,2024-03-22,1011,7.7,Advanced Robotics +AI07986,AI Architect,45728,CAD,57160,EN,CT,Canada,S,Canada,0,"MLOps, Docker, SQL",Master,1,Gaming,2024-04-21,2024-07-03,2066,5.7,Advanced Robotics +AI07987,Machine Learning Researcher,61291,EUR,52097,EN,FL,France,L,France,100,"SQL, MLOps, AWS, Hadoop",Bachelor,0,Education,2024-06-27,2024-08-09,1539,8.3,Neural Networks Co +AI07988,AI Architect,64443,EUR,54777,EN,FL,France,M,France,100,"Git, Kubernetes, Computer Vision",PhD,0,Media,2025-02-01,2025-04-11,2228,6.7,Future Systems +AI07989,Deep Learning Engineer,66409,USD,66409,EN,FL,United States,M,Colombia,50,"MLOps, Azure, Python, Kubernetes, Data Visualization",Bachelor,1,Healthcare,2024-11-05,2025-01-09,1753,8.3,Advanced Robotics +AI07990,NLP Engineer,76025,USD,76025,EX,CT,China,S,China,0,"Deep Learning, PyTorch, Linux",Associate,10,Retail,2024-05-14,2024-06-05,1627,5,Cloud AI Solutions +AI07991,Machine Learning Researcher,211009,USD,211009,EX,FL,Ireland,L,Ireland,100,"SQL, Computer Vision, Tableau",Master,10,Manufacturing,2025-04-11,2025-05-31,1249,5.6,Algorithmic Solutions +AI07992,AI Product Manager,154995,EUR,131746,SE,FL,Germany,L,Poland,50,"Scala, NLP, Mathematics, Docker, Java",PhD,6,Government,2025-03-26,2025-05-17,1985,7.3,Cloud AI Solutions +AI07993,AI Consultant,44675,USD,44675,SE,FL,India,L,Singapore,0,"Docker, Scala, MLOps, Linux, SQL",PhD,7,Finance,2024-11-11,2025-01-21,782,8.5,AI Innovations +AI07994,Research Scientist,87124,SGD,113261,EN,PT,Singapore,L,Singapore,0,"Scala, Java, TensorFlow, GCP, Deep Learning",Bachelor,1,Healthcare,2024-03-10,2024-04-25,1861,5.7,Cognitive Computing +AI07995,Robotics Engineer,122808,USD,122808,MI,PT,Sweden,L,Sweden,0,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,4,Consulting,2024-03-23,2024-05-16,1697,9,Predictive Systems +AI07996,Data Engineer,133625,JPY,14698750,SE,PT,Japan,L,Ireland,50,"Azure, Python, Mathematics",Associate,8,Government,2024-11-17,2024-12-03,1052,9.2,AI Innovations +AI07997,Autonomous Systems Engineer,71366,USD,71366,EN,CT,Israel,M,Israel,0,"TensorFlow, NLP, Kubernetes, Data Visualization, AWS",Bachelor,0,Energy,2024-10-28,2024-11-22,2129,7.3,Neural Networks Co +AI07998,AI Consultant,123920,USD,123920,SE,CT,Sweden,S,Brazil,50,"Docker, AWS, Hadoop, Java, Azure",Bachelor,5,Automotive,2025-01-23,2025-03-18,972,8.5,Autonomous Tech +AI07999,AI Product Manager,134233,JPY,14765630,MI,CT,Japan,L,Japan,50,"GCP, SQL, Tableau, Kubernetes",PhD,4,Finance,2024-09-13,2024-11-05,1135,6.4,Machine Intelligence Group +AI08000,Machine Learning Researcher,109561,USD,109561,MI,FT,Sweden,L,Netherlands,0,"Python, Java, NLP, Linux",Bachelor,4,Finance,2024-04-09,2024-06-13,1402,8.9,AI Innovations +AI08001,Data Scientist,71713,SGD,93227,EN,PT,Singapore,L,Thailand,50,"GCP, Statistics, Tableau, Scala",Associate,0,Government,2024-05-02,2024-07-10,2238,5.7,Quantum Computing Inc +AI08002,Robotics Engineer,58752,CAD,73440,EN,PT,Canada,M,Canada,100,"SQL, TensorFlow, Git, AWS",Master,0,Automotive,2024-12-13,2025-01-06,878,8,Digital Transformation LLC +AI08003,Autonomous Systems Engineer,118460,USD,118460,MI,FL,Norway,M,Norway,50,"NLP, Mathematics, Deep Learning, Python",Bachelor,4,Retail,2024-06-25,2024-07-30,1000,8.5,DataVision Ltd +AI08004,Machine Learning Researcher,82449,EUR,70082,EN,FL,Netherlands,M,Norway,0,"NLP, Spark, TensorFlow",Bachelor,0,Telecommunications,2024-05-25,2024-06-19,1871,8,Advanced Robotics +AI08005,Machine Learning Engineer,80025,SGD,104033,MI,FT,Singapore,S,Singapore,100,"Hadoop, Tableau, Spark, GCP",PhD,4,Real Estate,2024-04-18,2024-06-12,1556,8.2,Quantum Computing Inc +AI08006,Robotics Engineer,221861,USD,221861,EX,FL,Ireland,S,Ireland,100,"Kubernetes, GCP, Linux, SQL, Data Visualization",Bachelor,10,Manufacturing,2024-11-13,2025-01-24,818,7.2,TechCorp Inc +AI08007,AI Consultant,284268,USD,284268,EX,FT,Ireland,L,Ireland,50,"Data Visualization, AWS, PyTorch, Spark, Hadoop",Master,18,Technology,2024-05-23,2024-06-07,2236,5.1,Autonomous Tech +AI08008,Deep Learning Engineer,171547,SGD,223011,EX,PT,Singapore,S,Singapore,50,"Linux, Java, Tableau, GCP, Kubernetes",PhD,12,Retail,2025-04-09,2025-04-25,1173,9.2,Cloud AI Solutions +AI08009,AI Software Engineer,323208,CHF,290887,EX,FL,Switzerland,L,Switzerland,100,"Tableau, Deep Learning, Data Visualization, SQL, Linux",Master,14,Energy,2024-05-24,2024-07-04,1871,5.7,Cognitive Computing +AI08010,AI Product Manager,113656,USD,113656,MI,FT,United States,M,Ireland,50,"Statistics, SQL, MLOps",Master,2,Government,2024-10-04,2024-11-20,1427,7,Digital Transformation LLC +AI08011,Principal Data Scientist,77152,USD,77152,MI,FL,Ireland,M,Ireland,50,"AWS, TensorFlow, GCP, Deep Learning, SQL",PhD,4,Technology,2025-02-01,2025-04-01,2268,8.4,Algorithmic Solutions +AI08012,NLP Engineer,222207,SGD,288869,EX,FT,Singapore,L,Singapore,100,"Statistics, Tableau, Scala",Associate,13,Telecommunications,2025-01-18,2025-02-28,1899,6.6,Smart Analytics +AI08013,AI Consultant,196407,USD,196407,EX,PT,Denmark,S,Denmark,100,"Java, SQL, Deep Learning, Computer Vision, Spark",Bachelor,17,Government,2024-11-01,2025-01-03,2236,7.5,Autonomous Tech +AI08014,Research Scientist,27068,USD,27068,MI,PT,India,M,India,100,"Spark, Statistics, PyTorch",Bachelor,4,Retail,2024-08-27,2024-11-08,2145,9.7,Neural Networks Co +AI08015,AI Research Scientist,99789,USD,99789,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Statistics, GCP",PhD,7,Automotive,2025-03-14,2025-05-09,564,6.7,Predictive Systems +AI08016,Research Scientist,157360,CHF,141624,SE,CT,Switzerland,S,Czech Republic,50,"Java, Scala, MLOps, NLP",Bachelor,7,Education,2024-12-28,2025-02-03,2474,5,Algorithmic Solutions +AI08017,Data Engineer,73368,CHF,66031,EN,CT,Switzerland,S,Switzerland,0,"Spark, Linux, Python",Bachelor,1,Healthcare,2024-08-03,2024-09-29,764,6.3,Smart Analytics +AI08018,AI Specialist,130971,CHF,117874,EN,FL,Switzerland,L,Switzerland,0,"TensorFlow, Python, Mathematics",Master,1,Transportation,2024-07-09,2024-09-09,2002,8.4,DataVision Ltd +AI08019,Autonomous Systems Engineer,42371,USD,42371,MI,FT,China,S,China,100,"SQL, Scala, Git",Associate,3,Consulting,2024-02-08,2024-03-16,2063,6.8,Machine Intelligence Group +AI08020,AI Architect,96446,USD,96446,EN,PT,United States,L,Denmark,50,"PyTorch, Linux, Statistics",Master,1,Energy,2024-02-11,2024-03-22,1721,8.2,DeepTech Ventures +AI08021,Data Scientist,253346,USD,253346,EX,FT,United States,M,United States,50,"NLP, Linux, Azure",PhD,15,Manufacturing,2024-11-12,2025-01-14,1765,5.8,Smart Analytics +AI08022,AI Specialist,210688,JPY,23175680,EX,FT,Japan,M,Japan,50,"MLOps, Hadoop, Python",Associate,14,Transportation,2024-01-04,2024-02-16,1448,5.1,Algorithmic Solutions +AI08023,Data Analyst,20088,USD,20088,EN,CT,India,S,India,50,"R, Azure, TensorFlow, Tableau, Git",Master,1,Healthcare,2024-11-06,2024-12-07,1065,6.7,AI Innovations +AI08024,AI Research Scientist,115869,EUR,98489,MI,FT,France,L,France,100,"Kubernetes, Azure, TensorFlow, Java, Scala",Bachelor,4,Gaming,2024-12-01,2025-01-14,890,5.5,Neural Networks Co +AI08025,Computer Vision Engineer,27041,USD,27041,MI,FL,India,M,Argentina,0,"Git, GCP, Scala, Deep Learning, TensorFlow",Associate,2,Manufacturing,2024-05-08,2024-07-11,631,8.4,Future Systems +AI08026,AI Research Scientist,133722,USD,133722,SE,FL,Ireland,S,Ireland,50,"Mathematics, Statistics, Java",Master,8,Government,2025-04-11,2025-05-30,2432,6.4,Advanced Robotics +AI08027,Autonomous Systems Engineer,75208,USD,75208,EN,PT,United States,S,Ukraine,0,"PyTorch, Azure, Java, Spark",PhD,0,Finance,2024-07-15,2024-08-15,980,5.1,Future Systems +AI08028,Machine Learning Researcher,109705,EUR,93249,MI,FT,Germany,M,Russia,0,"Python, Linux, NLP",PhD,4,Real Estate,2024-12-18,2025-01-13,2235,7.4,AI Innovations +AI08029,AI Consultant,55926,USD,55926,EN,FT,South Korea,M,Poland,50,"Python, SQL, MLOps",Master,1,Consulting,2024-05-08,2024-06-17,538,7,Advanced Robotics +AI08030,Data Analyst,154681,USD,154681,SE,PT,Denmark,L,Denmark,50,"Git, Hadoop, Tableau, Data Visualization",Associate,7,Government,2025-02-09,2025-04-17,975,9.4,Digital Transformation LLC +AI08031,NLP Engineer,72975,USD,72975,EX,PT,India,M,India,0,"GCP, Tableau, Scala",PhD,14,Technology,2024-04-10,2024-05-03,556,9.2,Machine Intelligence Group +AI08032,Deep Learning Engineer,122344,USD,122344,SE,CT,Sweden,M,Brazil,50,"Spark, AWS, Git, PyTorch",Bachelor,8,Real Estate,2024-05-16,2024-07-25,1732,7,DeepTech Ventures +AI08033,Machine Learning Researcher,78706,EUR,66900,MI,FT,Germany,M,Germany,0,"Data Visualization, AWS, Python, Spark, TensorFlow",PhD,2,Retail,2024-05-22,2024-07-24,737,9.5,Machine Intelligence Group +AI08034,Data Analyst,87488,EUR,74365,SE,FT,Austria,S,Austria,50,"Kubernetes, PyTorch, TensorFlow, Statistics",Bachelor,8,Automotive,2024-11-30,2024-12-30,2075,6.2,DeepTech Ventures +AI08035,Data Scientist,109945,GBP,82459,SE,PT,United Kingdom,S,Australia,50,"AWS, Data Visualization, Scala, Tableau, MLOps",Associate,5,Telecommunications,2025-02-20,2025-03-10,1706,6.6,Algorithmic Solutions +AI08036,Autonomous Systems Engineer,128555,USD,128555,SE,FT,United States,S,Ireland,0,"SQL, Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,9,Automotive,2024-09-23,2024-11-10,2140,6.4,DataVision Ltd +AI08037,Data Engineer,83558,USD,83558,EX,FL,China,M,Portugal,0,"Java, GCP, Tableau, Deep Learning",Associate,13,Healthcare,2024-11-22,2025-01-12,1439,8.8,Advanced Robotics +AI08038,Autonomous Systems Engineer,59257,USD,59257,SE,CT,China,L,China,50,"R, Mathematics, Tableau",Bachelor,8,Education,2024-02-09,2024-04-11,1925,9.6,DeepTech Ventures +AI08039,Research Scientist,211226,USD,211226,EX,CT,Sweden,L,Sweden,50,"Hadoop, Scala, GCP, Docker, R",PhD,10,Real Estate,2024-10-18,2024-12-08,1516,8.5,Cloud AI Solutions +AI08040,Data Engineer,58429,EUR,49665,EN,FT,Austria,S,Austria,50,"Linux, Python, Computer Vision, AWS",Master,0,Healthcare,2024-05-11,2024-07-10,1024,8.5,AI Innovations +AI08041,AI Specialist,30008,USD,30008,EN,CT,India,L,India,100,"Linux, PyTorch, Git, Computer Vision",Master,1,Real Estate,2024-10-29,2024-11-23,799,6.5,Machine Intelligence Group +AI08042,Principal Data Scientist,63440,USD,63440,EX,PT,India,M,India,0,"Hadoop, Java, SQL, Computer Vision",PhD,18,Energy,2024-10-19,2024-12-06,1042,9.3,DataVision Ltd +AI08043,AI Architect,75902,USD,75902,EN,PT,United States,S,United States,50,"AWS, Data Visualization, Tableau, Scala",Associate,0,Real Estate,2024-02-05,2024-03-03,1077,8.2,Algorithmic Solutions +AI08044,AI Consultant,212552,GBP,159414,EX,FL,United Kingdom,S,Austria,100,"SQL, Spark, MLOps",Associate,11,Finance,2025-03-20,2025-05-02,516,7.9,Neural Networks Co +AI08045,AI Product Manager,105830,EUR,89956,MI,FL,France,L,France,100,"Hadoop, GCP, Scala, Tableau",Bachelor,3,Healthcare,2024-08-16,2024-10-12,878,9.8,Autonomous Tech +AI08046,Head of AI,82250,USD,82250,MI,PT,Sweden,M,Sweden,0,"Azure, MLOps, Statistics, R, GCP",Associate,2,Consulting,2024-07-15,2024-08-29,1795,7.2,DataVision Ltd +AI08047,AI Product Manager,106488,EUR,90515,SE,PT,Germany,M,Germany,0,"PyTorch, Kubernetes, Computer Vision, TensorFlow, Spark",Bachelor,9,Telecommunications,2024-12-20,2025-01-31,960,7.2,Quantum Computing Inc +AI08048,Head of AI,147509,USD,147509,SE,CT,Sweden,L,Sweden,0,"Python, Mathematics, Linux, TensorFlow, Deep Learning",Master,6,Healthcare,2024-12-18,2025-01-25,1965,6,Cognitive Computing +AI08049,AI Specialist,107129,EUR,91060,MI,CT,Netherlands,L,Netherlands,0,"R, PyTorch, GCP, Computer Vision, Git",Bachelor,2,Automotive,2024-04-19,2024-05-30,1355,9.2,Machine Intelligence Group +AI08050,AI Research Scientist,263994,CHF,237595,EX,FT,Switzerland,S,Switzerland,100,"Azure, Python, MLOps, Kubernetes, Hadoop",Bachelor,19,Consulting,2024-12-11,2025-01-16,1088,6.4,Quantum Computing Inc +AI08051,NLP Engineer,115888,SGD,150654,MI,FT,Singapore,L,Australia,50,"Kubernetes, Docker, Spark, Linux, Computer Vision",Associate,2,Energy,2024-05-03,2024-06-29,2345,5.2,Autonomous Tech +AI08052,Research Scientist,183653,SGD,238749,EX,PT,Singapore,M,Singapore,100,"Statistics, Computer Vision, Python",Master,14,Government,2024-10-22,2024-12-06,2176,8.6,DeepTech Ventures +AI08053,Autonomous Systems Engineer,136651,SGD,177646,EX,FT,Singapore,S,Singapore,50,"Statistics, Python, AWS, PyTorch",Master,18,Real Estate,2024-12-20,2025-01-29,1776,8.5,Autonomous Tech +AI08054,AI Product Manager,138663,USD,138663,EX,CT,Finland,M,New Zealand,100,"Git, Python, Mathematics, Linux",Associate,13,Gaming,2024-06-16,2024-08-04,2319,6.5,Future Systems +AI08055,AI Software Engineer,156452,GBP,117339,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, Tableau, Statistics",Bachelor,10,Gaming,2024-03-26,2024-05-10,1929,7.2,Neural Networks Co +AI08056,Computer Vision Engineer,91988,USD,91988,MI,CT,United States,M,United States,50,"Git, Scala, Data Visualization",PhD,4,Healthcare,2024-07-23,2024-10-02,1514,8.5,TechCorp Inc +AI08057,AI Product Manager,170809,GBP,128107,EX,CT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, AWS, Computer Vision",Master,11,Telecommunications,2024-08-23,2024-09-06,1384,9.9,Digital Transformation LLC +AI08058,NLP Engineer,102306,EUR,86960,MI,PT,Netherlands,L,Indonesia,100,"SQL, NLP, Python",Master,4,Automotive,2024-10-19,2024-12-24,1838,8.7,Machine Intelligence Group +AI08059,Computer Vision Engineer,66585,EUR,56597,EN,CT,France,S,France,0,"NLP, PyTorch, MLOps, Kubernetes, TensorFlow",Associate,0,Education,2024-02-03,2024-02-27,1482,7.9,Predictive Systems +AI08060,Machine Learning Researcher,207692,CHF,186923,SE,CT,Switzerland,M,Switzerland,100,"Python, Spark, TensorFlow, Tableau, PyTorch",PhD,5,Transportation,2024-03-28,2024-06-02,1924,9.6,Quantum Computing Inc +AI08061,Data Analyst,129361,USD,129361,SE,CT,Sweden,M,Sweden,100,"PyTorch, Spark, Hadoop",Master,8,Finance,2024-06-01,2024-07-16,1043,10,Algorithmic Solutions +AI08062,Head of AI,97125,USD,97125,EN,CT,Denmark,L,Denmark,100,"Scala, Tableau, Kubernetes",PhD,0,Energy,2024-01-18,2024-03-28,760,9.3,Algorithmic Solutions +AI08063,Principal Data Scientist,97060,USD,97060,MI,PT,Finland,M,Finland,0,"R, AWS, Statistics, Linux, Deep Learning",PhD,3,Transportation,2024-12-16,2025-01-03,1883,9.8,Future Systems +AI08064,AI Software Engineer,69840,USD,69840,SE,FT,China,L,Spain,50,"Java, AWS, Computer Vision, Docker, Deep Learning",Master,9,Energy,2024-03-12,2024-04-04,2372,7.1,Machine Intelligence Group +AI08065,ML Ops Engineer,86753,EUR,73740,MI,PT,France,L,France,0,"Java, Hadoop, Linux",Associate,3,Real Estate,2024-11-28,2024-12-30,1934,6.7,Quantum Computing Inc +AI08066,Research Scientist,120164,USD,120164,EN,PT,Norway,L,Norway,50,"Computer Vision, Scala, SQL",Associate,1,Telecommunications,2024-02-21,2024-04-14,2276,8.7,Digital Transformation LLC +AI08067,Deep Learning Engineer,63400,USD,63400,EN,PT,Finland,M,Finland,100,"GCP, Tableau, PyTorch",Master,0,Telecommunications,2025-02-17,2025-04-30,1004,8.3,Neural Networks Co +AI08068,Deep Learning Engineer,195225,AUD,263554,EX,FL,Australia,L,Hungary,50,"Git, Python, Azure",Master,17,Automotive,2024-03-06,2024-04-24,1304,7.9,Neural Networks Co +AI08069,AI Specialist,121448,USD,121448,SE,PT,South Korea,L,Luxembourg,50,"Hadoop, Linux, Git, Scala, Java",Master,9,Finance,2024-09-22,2024-10-19,1260,5.3,Autonomous Tech +AI08070,Autonomous Systems Engineer,127574,CHF,114817,MI,CT,Switzerland,S,Canada,0,"TensorFlow, Azure, Spark, Kubernetes",Master,4,Finance,2024-09-18,2024-10-23,733,9.1,Quantum Computing Inc +AI08071,NLP Engineer,28917,USD,28917,EN,FL,China,L,China,50,"SQL, PyTorch, Java, Docker, Linux",PhD,1,Finance,2024-11-08,2024-11-29,2062,8.5,Advanced Robotics +AI08072,NLP Engineer,175601,USD,175601,SE,CT,Denmark,S,Denmark,100,"Python, Scala, AWS, Spark",Master,5,Technology,2024-05-27,2024-06-16,1276,8.5,Quantum Computing Inc +AI08073,Principal Data Scientist,110916,JPY,12200760,SE,CT,Japan,S,United States,100,"Python, Linux, SQL, R, Statistics",Master,9,Retail,2024-03-07,2024-03-30,2208,9.7,Algorithmic Solutions +AI08074,Research Scientist,93983,CAD,117479,MI,PT,Canada,L,Canada,0,"Data Visualization, Kubernetes, Mathematics",Bachelor,4,Healthcare,2024-03-17,2024-03-31,2013,5.2,DeepTech Ventures +AI08075,NLP Engineer,323422,USD,323422,EX,PT,Norway,M,Norway,0,"Docker, R, Data Visualization, Deep Learning, Git",Associate,10,Education,2024-09-25,2024-11-06,1045,7.1,Smart Analytics +AI08076,Robotics Engineer,179355,USD,179355,SE,CT,United States,L,United States,50,"NLP, Python, Data Visualization, Azure, Java",PhD,5,Finance,2024-02-20,2024-04-12,2445,9.2,Advanced Robotics +AI08077,AI Product Manager,85532,USD,85532,EN,FT,Denmark,S,Denmark,50,"Docker, Kubernetes, AWS",Master,0,Telecommunications,2024-11-03,2024-12-30,837,5.9,Machine Intelligence Group +AI08078,Autonomous Systems Engineer,44071,USD,44071,MI,FT,India,L,India,0,"Java, PyTorch, NLP, R, TensorFlow",Associate,3,Government,2025-01-18,2025-03-02,974,8.9,Autonomous Tech +AI08079,Robotics Engineer,130737,USD,130737,SE,FL,Ireland,M,Ireland,50,"Linux, PyTorch, Java, Tableau, TensorFlow",Master,9,Automotive,2024-10-18,2024-11-29,1011,6.9,Cognitive Computing +AI08080,Deep Learning Engineer,147663,CHF,132897,MI,CT,Switzerland,L,Switzerland,50,"SQL, Computer Vision, Scala, GCP",Master,4,Energy,2025-02-18,2025-03-29,2092,7.6,AI Innovations +AI08081,Machine Learning Engineer,269175,USD,269175,EX,FL,Denmark,M,Argentina,100,"AWS, Hadoop, Java, Statistics, Deep Learning",Master,18,Real Estate,2024-02-26,2024-04-05,2398,6.5,AI Innovations +AI08082,Computer Vision Engineer,152150,EUR,129328,SE,FT,France,L,France,50,"Linux, Python, Data Visualization, Java",PhD,5,Consulting,2024-04-07,2024-05-17,1392,9.8,Autonomous Tech +AI08083,AI Consultant,18965,USD,18965,EN,FL,India,S,India,50,"Python, GCP, Deep Learning",Master,0,Automotive,2025-03-07,2025-03-28,2011,7.6,Cloud AI Solutions +AI08084,NLP Engineer,293774,USD,293774,EX,FT,Norway,S,Norway,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,14,Media,2024-06-15,2024-07-21,2330,9.2,Cognitive Computing +AI08085,Head of AI,116082,USD,116082,SE,CT,South Korea,M,United Kingdom,50,"Tableau, Deep Learning, SQL",PhD,9,Consulting,2025-03-02,2025-04-03,1469,6.8,Machine Intelligence Group +AI08086,AI Consultant,55542,USD,55542,EN,FT,South Korea,S,Argentina,100,"Kubernetes, Tableau, MLOps",Master,1,Real Estate,2024-02-20,2024-04-13,1159,8,Quantum Computing Inc +AI08087,AI Consultant,136996,USD,136996,SE,CT,Norway,M,Norway,100,"Linux, SQL, Deep Learning, PyTorch, Hadoop",Bachelor,6,Retail,2024-02-21,2024-03-08,2025,9.8,Cloud AI Solutions +AI08088,ML Ops Engineer,79319,EUR,67421,MI,PT,France,L,France,0,"MLOps, SQL, TensorFlow, Hadoop",Bachelor,3,Media,2024-02-05,2024-03-31,1325,9.7,DataVision Ltd +AI08089,Computer Vision Engineer,105493,CAD,131866,SE,CT,Canada,S,Canada,0,"PyTorch, Linux, Python, Statistics, GCP",Master,9,Education,2025-01-02,2025-01-23,902,9.8,Cloud AI Solutions +AI08090,AI Research Scientist,58931,USD,58931,EN,CT,Israel,S,Israel,50,"Computer Vision, R, SQL",Associate,0,Transportation,2024-09-03,2024-09-21,1976,8.9,DataVision Ltd +AI08091,AI Specialist,269865,USD,269865,EX,CT,Ireland,L,Ireland,100,"Linux, Azure, Deep Learning",Bachelor,18,Technology,2025-03-30,2025-06-07,729,5.7,Autonomous Tech +AI08092,Head of AI,94339,USD,94339,MI,CT,Norway,S,Norway,50,"Kubernetes, TensorFlow, Azure, Tableau, MLOps",Associate,3,Government,2024-04-14,2024-05-02,1970,5.9,Autonomous Tech +AI08093,AI Product Manager,295017,JPY,32451870,EX,CT,Japan,L,Estonia,50,"Kubernetes, Java, Git, SQL",Master,14,Media,2024-09-22,2024-11-04,1295,6.3,Digital Transformation LLC +AI08094,Machine Learning Engineer,101293,SGD,131681,MI,CT,Singapore,S,Singapore,100,"NLP, SQL, Azure, Scala",PhD,2,Healthcare,2025-01-20,2025-03-07,2199,7.9,Machine Intelligence Group +AI08095,AI Specialist,32078,USD,32078,EN,FT,India,L,India,100,"Computer Vision, Tableau, GCP",Associate,0,Consulting,2025-04-16,2025-06-14,2105,5.5,Autonomous Tech +AI08096,Head of AI,99238,GBP,74429,MI,FT,United Kingdom,M,United Kingdom,0,"NLP, R, Kubernetes",Associate,3,Healthcare,2024-09-01,2024-09-23,956,8.2,DeepTech Ventures +AI08097,Data Analyst,87032,USD,87032,MI,FL,Finland,S,Finland,100,"Python, Kubernetes, Tableau",Bachelor,4,Consulting,2024-04-22,2024-05-17,1298,8.2,DeepTech Ventures +AI08098,Data Scientist,156773,USD,156773,SE,FT,Israel,L,Israel,100,"Statistics, Kubernetes, NLP, Linux",Master,5,Technology,2024-02-16,2024-04-03,2324,9.8,Smart Analytics +AI08099,AI Research Scientist,61019,AUD,82376,EN,FT,Australia,L,Australia,100,"Statistics, Git, NLP, Python",Bachelor,0,Real Estate,2024-11-10,2024-11-24,1197,8.6,DeepTech Ventures +AI08100,AI Research Scientist,70543,EUR,59962,EN,PT,Germany,M,Malaysia,0,"TensorFlow, Linux, Tableau, Hadoop, Kubernetes",Bachelor,1,Automotive,2025-03-20,2025-05-19,1099,8,Cloud AI Solutions +AI08101,Deep Learning Engineer,65930,AUD,89006,EN,CT,Australia,S,Australia,50,"GCP, NLP, Hadoop",Master,0,Gaming,2025-02-13,2025-03-07,1258,9.7,Digital Transformation LLC +AI08102,Data Scientist,61443,EUR,52227,EN,CT,France,M,France,0,"SQL, Hadoop, MLOps",Master,1,Healthcare,2024-08-06,2024-10-08,793,7,Algorithmic Solutions +AI08103,Deep Learning Engineer,389007,CHF,350106,EX,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, Hadoop, Deep Learning, Spark",PhD,17,Gaming,2025-01-06,2025-02-22,1261,9.2,Smart Analytics +AI08104,Data Engineer,76813,EUR,65291,MI,PT,Germany,S,Germany,50,"Kubernetes, Spark, NLP, Statistics",Associate,2,Energy,2024-04-22,2024-06-14,1138,8.4,Future Systems +AI08105,ML Ops Engineer,98906,EUR,84070,MI,CT,Austria,L,Austria,0,"Computer Vision, Python, NLP, Spark, TensorFlow",Associate,4,Manufacturing,2025-01-23,2025-03-19,1508,7,DeepTech Ventures +AI08106,Data Scientist,74348,GBP,55761,MI,FL,United Kingdom,S,Singapore,100,"MLOps, Kubernetes, Deep Learning",PhD,3,Government,2025-01-30,2025-04-01,860,6,TechCorp Inc +AI08107,Data Analyst,91122,CHF,82010,EN,FL,Switzerland,M,Switzerland,100,"Mathematics, Deep Learning, Computer Vision, PyTorch, Kubernetes",PhD,0,Government,2024-02-12,2024-04-11,1786,8.6,Advanced Robotics +AI08108,Data Scientist,185096,EUR,157332,EX,FT,France,S,France,100,"Git, Azure, Linux",Bachelor,14,Consulting,2024-01-16,2024-03-06,2314,9.5,Quantum Computing Inc +AI08109,NLP Engineer,94648,EUR,80451,MI,FT,France,M,France,50,"GCP, R, Kubernetes",PhD,3,Automotive,2024-04-14,2024-05-28,2479,7.7,Digital Transformation LLC +AI08110,AI Architect,81723,EUR,69465,MI,PT,France,S,France,0,"Java, R, Spark, SQL, MLOps",Master,3,Gaming,2024-03-14,2024-03-28,724,6.2,Autonomous Tech +AI08111,Autonomous Systems Engineer,249442,GBP,187082,EX,FT,United Kingdom,M,United Kingdom,50,"Deep Learning, R, Tableau, GCP",Bachelor,11,Finance,2025-01-28,2025-03-16,1202,9.4,Digital Transformation LLC +AI08112,Robotics Engineer,111472,CAD,139340,SE,PT,Canada,M,Ghana,100,"Scala, Git, Computer Vision, NLP, AWS",PhD,8,Healthcare,2025-01-04,2025-01-26,2448,6.5,Machine Intelligence Group +AI08113,Data Analyst,107982,USD,107982,MI,PT,Norway,S,Norway,100,"Java, R, Azure, Hadoop, Git",Master,2,Finance,2025-04-03,2025-06-02,2009,8.4,Cognitive Computing +AI08114,NLP Engineer,106322,USD,106322,SE,FT,South Korea,L,South Korea,50,"Kubernetes, TensorFlow, Azure",PhD,5,Technology,2024-03-16,2024-04-16,2356,8.8,Cognitive Computing +AI08115,Data Scientist,97096,USD,97096,MI,PT,South Korea,L,Luxembourg,0,"Linux, NLP, Tableau, Scala",Master,2,Automotive,2025-03-13,2025-05-11,2414,6.3,Advanced Robotics +AI08116,Machine Learning Engineer,71329,USD,71329,SE,FL,China,L,China,0,"GCP, PyTorch, TensorFlow, Kubernetes, AWS",Bachelor,7,Education,2024-10-14,2024-10-31,2022,6.6,DataVision Ltd +AI08117,Machine Learning Researcher,204502,USD,204502,EX,FT,Israel,L,Canada,0,"Computer Vision, Deep Learning, SQL, Linux, Python",Associate,17,Automotive,2024-05-22,2024-06-12,636,7.7,Quantum Computing Inc +AI08118,AI Software Engineer,78540,AUD,106029,EN,PT,Australia,L,Canada,0,"Linux, Deep Learning, Spark, Hadoop",PhD,1,Real Estate,2024-06-27,2024-07-17,1984,8.4,Machine Intelligence Group +AI08119,AI Specialist,102696,USD,102696,MI,FL,Norway,M,Norway,50,"GCP, Statistics, Linux, PyTorch",Bachelor,3,Technology,2024-10-01,2024-11-24,2251,8.7,Digital Transformation LLC +AI08120,Machine Learning Engineer,140672,USD,140672,SE,FL,Ireland,M,Ireland,0,"SQL, Kubernetes, Data Visualization",Master,6,Energy,2025-04-16,2025-05-15,1303,5.4,Smart Analytics +AI08121,AI Consultant,306231,JPY,33685410,EX,FT,Japan,L,Japan,50,"SQL, Linux, Spark, Azure, Hadoop",PhD,11,Transportation,2024-11-09,2025-01-13,2186,7.7,DeepTech Ventures +AI08122,Research Scientist,79751,USD,79751,MI,FT,Israel,L,Israel,0,"Linux, PyTorch, R, NLP",Associate,3,Consulting,2025-01-12,2025-02-10,1412,6.5,Future Systems +AI08123,Data Analyst,59536,AUD,80374,EN,PT,Australia,S,Australia,0,"Python, SQL, AWS",Master,1,Real Estate,2024-03-14,2024-04-17,905,7.5,DeepTech Ventures +AI08124,Data Analyst,217273,USD,217273,EX,CT,Sweden,M,Sweden,100,"GCP, Deep Learning, PyTorch",Bachelor,14,Retail,2024-09-05,2024-10-15,1637,8.5,DataVision Ltd +AI08125,AI Software Engineer,61375,USD,61375,EN,CT,Finland,M,Finland,0,"MLOps, Data Visualization, Python",Associate,1,Technology,2024-04-07,2024-05-06,1196,5.2,Cognitive Computing +AI08126,AI Research Scientist,84104,CHF,75694,EN,PT,Switzerland,S,Switzerland,100,"MLOps, Mathematics, Linux",Associate,0,Energy,2024-12-07,2025-01-11,1663,9.1,Predictive Systems +AI08127,Machine Learning Researcher,119885,JPY,13187350,SE,FT,Japan,M,Japan,50,"Hadoop, Statistics, Git",Master,8,Consulting,2024-04-15,2024-05-15,1847,5.7,Advanced Robotics +AI08128,Head of AI,49872,USD,49872,EN,CT,Finland,M,Germany,100,"GCP, Deep Learning, MLOps, Linux, SQL",Bachelor,1,Telecommunications,2024-03-06,2024-03-30,2282,8.6,AI Innovations +AI08129,AI Product Manager,83785,USD,83785,EX,PT,India,L,Hungary,100,"Scala, R, Statistics",Bachelor,16,Real Estate,2024-12-11,2025-01-24,970,5.9,Cloud AI Solutions +AI08130,Principal Data Scientist,47263,AUD,63805,EN,PT,Australia,S,Australia,100,"AWS, Kubernetes, PyTorch",Associate,1,Education,2025-02-23,2025-05-05,2397,9.9,DataVision Ltd +AI08131,Machine Learning Researcher,82949,CAD,103686,EN,FT,Canada,L,Canada,50,"Mathematics, Git, NLP, Python",PhD,1,Media,2025-04-14,2025-06-10,1455,5.5,Smart Analytics +AI08132,AI Architect,85674,USD,85674,MI,FL,Sweden,M,China,0,"SQL, Python, GCP, Azure",Associate,4,Automotive,2025-04-19,2025-06-25,2146,5.6,Predictive Systems +AI08133,Research Scientist,66353,USD,66353,MI,FL,South Korea,S,South Korea,100,"Python, Hadoop, Deep Learning, SQL",PhD,4,Transportation,2024-08-10,2024-10-12,507,5.8,AI Innovations +AI08134,AI Product Manager,169078,USD,169078,EX,FT,Sweden,S,Sweden,100,"GCP, Statistics, Tableau",Bachelor,18,Automotive,2025-03-05,2025-04-16,814,6.9,Cognitive Computing +AI08135,Autonomous Systems Engineer,181932,EUR,154642,EX,CT,Germany,M,Germany,100,"Docker, Spark, Scala",Master,17,Education,2024-01-02,2024-01-28,1918,7.7,Cognitive Computing +AI08136,Autonomous Systems Engineer,93368,EUR,79363,SE,CT,Germany,S,Germany,50,"R, Scala, Data Visualization",Master,6,Healthcare,2024-08-02,2024-09-01,705,5.2,Neural Networks Co +AI08137,AI Specialist,112677,USD,112677,SE,CT,Israel,S,Israel,50,"Data Visualization, Linux, SQL, R",Bachelor,9,Automotive,2025-02-26,2025-04-06,1251,6.3,Digital Transformation LLC +AI08138,Computer Vision Engineer,145606,EUR,123765,EX,CT,Germany,M,Germany,50,"Java, SQL, Hadoop, Kubernetes",PhD,12,Real Estate,2024-09-20,2024-11-09,1136,6.7,Quantum Computing Inc +AI08139,AI Specialist,60885,USD,60885,EN,FL,Ireland,S,Argentina,50,"Python, SQL, Linux",PhD,0,Manufacturing,2025-03-07,2025-05-08,640,7.1,Digital Transformation LLC +AI08140,Robotics Engineer,53376,AUD,72058,EN,FL,Australia,M,China,100,"Deep Learning, GCP, Kubernetes",Bachelor,0,Technology,2024-08-24,2024-09-26,1725,7,Algorithmic Solutions +AI08141,AI Consultant,75818,EUR,64445,EN,CT,Netherlands,L,Netherlands,0,"Python, Spark, Scala, AWS, R",Master,0,Gaming,2024-10-28,2025-01-08,544,8.3,Quantum Computing Inc +AI08142,Principal Data Scientist,99061,EUR,84202,MI,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, Tableau",Associate,3,Gaming,2025-02-19,2025-04-17,1973,7,Quantum Computing Inc +AI08143,Data Analyst,107756,EUR,91593,MI,FT,Germany,L,Germany,50,"Azure, SQL, Java",Associate,4,Healthcare,2024-10-30,2024-12-10,661,8.1,Cognitive Computing +AI08144,Computer Vision Engineer,75125,USD,75125,SE,FL,China,L,China,0,"Tableau, Azure, Kubernetes, Mathematics",PhD,9,Automotive,2024-01-07,2024-02-08,1592,7.2,Smart Analytics +AI08145,Machine Learning Researcher,96840,CHF,87156,EN,CT,Switzerland,S,Switzerland,50,"Python, TensorFlow, PyTorch, Tableau, Mathematics",Bachelor,0,Finance,2024-12-25,2025-02-03,578,9.1,DataVision Ltd +AI08146,NLP Engineer,78676,USD,78676,EN,CT,Sweden,M,Sweden,100,"Mathematics, Hadoop, Python, Spark",PhD,0,Gaming,2024-07-03,2024-08-25,1565,9.9,Autonomous Tech +AI08147,Computer Vision Engineer,206627,CHF,185964,EX,FL,Switzerland,S,South Korea,100,"TensorFlow, Deep Learning, Tableau, Kubernetes, SQL",Bachelor,10,Transportation,2025-04-14,2025-05-26,767,7.4,Predictive Systems +AI08148,Principal Data Scientist,74509,USD,74509,SE,CT,China,L,Vietnam,100,"TensorFlow, Docker, Kubernetes, GCP, Data Visualization",Bachelor,9,Education,2024-07-17,2024-08-22,2330,7.3,Autonomous Tech +AI08149,Data Engineer,147081,EUR,125019,SE,FL,Germany,L,Malaysia,50,"R, SQL, Statistics",PhD,5,Government,2024-11-05,2024-12-17,1029,7.6,Autonomous Tech +AI08150,AI Consultant,148813,CAD,186016,EX,PT,Canada,M,Canada,0,"Tableau, GCP, Scala, NLP",Bachelor,15,Government,2024-08-22,2024-10-21,2385,8.7,Algorithmic Solutions +AI08151,Deep Learning Engineer,194557,AUD,262652,EX,CT,Australia,M,Australia,100,"Mathematics, Hadoop, Data Visualization, AWS",Master,18,Energy,2024-11-09,2025-01-16,1321,6.4,Quantum Computing Inc +AI08152,Data Analyst,220707,EUR,187601,EX,PT,Germany,S,Germany,100,"Mathematics, SQL, AWS, Kubernetes, Linux",PhD,18,Manufacturing,2024-01-08,2024-02-19,1499,6.4,Cognitive Computing +AI08153,AI Architect,83907,EUR,71321,EN,FT,Austria,L,Brazil,0,"R, Deep Learning, Tableau, PyTorch, Mathematics",PhD,0,Automotive,2024-09-29,2024-10-30,1079,8.8,DataVision Ltd +AI08154,NLP Engineer,203429,CHF,183086,SE,CT,Switzerland,M,China,100,"Kubernetes, AWS, GCP",PhD,5,Technology,2024-06-26,2024-07-22,1030,7.1,Advanced Robotics +AI08155,Head of AI,121903,USD,121903,SE,CT,South Korea,M,South Korea,0,"Python, Hadoop, Mathematics, Tableau, Computer Vision",Master,8,Media,2025-02-28,2025-03-18,667,6.9,Advanced Robotics +AI08156,Computer Vision Engineer,97513,CAD,121891,MI,PT,Canada,L,Canada,50,"Docker, Python, Statistics",Master,3,Real Estate,2024-05-11,2024-07-03,2187,7.1,Machine Intelligence Group +AI08157,AI Consultant,229343,CHF,206409,SE,FL,Switzerland,L,Switzerland,100,"PyTorch, Scala, MLOps, Computer Vision",PhD,6,Automotive,2024-06-20,2024-08-17,548,9.6,Autonomous Tech +AI08158,Data Scientist,135831,SGD,176580,SE,CT,Singapore,S,New Zealand,50,"AWS, Docker, Data Visualization, Deep Learning",Master,8,Manufacturing,2024-10-14,2024-11-18,1245,7.3,Algorithmic Solutions +AI08159,AI Specialist,229897,CHF,206907,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Computer Vision, Hadoop",PhD,9,Gaming,2024-07-14,2024-09-23,1540,5.1,Digital Transformation LLC +AI08160,Data Scientist,75572,AUD,102022,MI,FL,Australia,S,Australia,100,"Tableau, Python, Hadoop",Master,4,Healthcare,2024-09-10,2024-10-03,1850,9.3,Neural Networks Co +AI08161,AI Product Manager,160993,JPY,17709230,EX,FL,Japan,S,Japan,0,"Python, Kubernetes, Git, Linux",PhD,15,Real Estate,2024-05-11,2024-06-24,1652,6.6,Algorithmic Solutions +AI08162,Data Engineer,81776,SGD,106309,MI,CT,Singapore,S,Singapore,50,"R, PyTorch, Spark, Statistics",PhD,3,Consulting,2024-02-11,2024-04-17,820,5.6,Machine Intelligence Group +AI08163,Head of AI,81570,USD,81570,EN,PT,Finland,L,Finland,50,"Linux, Data Visualization, Hadoop, Azure, Tableau",Bachelor,0,Energy,2024-05-11,2024-06-12,507,7.4,Smart Analytics +AI08164,Autonomous Systems Engineer,93162,EUR,79188,MI,CT,Germany,S,Germany,100,"Data Visualization, Git, Python, Scala, Computer Vision",Master,4,Energy,2024-02-23,2024-04-27,535,7.2,Predictive Systems +AI08165,Machine Learning Researcher,227631,AUD,307302,EX,FT,Australia,S,Argentina,100,"SQL, GCP, Git",PhD,19,Gaming,2024-07-21,2024-09-26,640,6.2,AI Innovations +AI08166,AI Architect,131380,USD,131380,SE,FL,Sweden,L,Poland,100,"SQL, Deep Learning, Scala, Computer Vision, PyTorch",Bachelor,5,Telecommunications,2025-02-25,2025-05-01,2251,6.9,Algorithmic Solutions +AI08167,Data Analyst,33242,USD,33242,EN,FT,China,L,Estonia,0,"Kubernetes, SQL, Tableau",Associate,0,Healthcare,2024-08-07,2024-08-24,552,8.7,Cloud AI Solutions +AI08168,Data Scientist,336599,USD,336599,EX,FT,Denmark,L,Denmark,50,"PyTorch, Linux, Statistics, GCP, Python",Bachelor,14,Retail,2024-11-14,2025-01-14,1602,7,Smart Analytics +AI08169,AI Software Engineer,132545,SGD,172309,MI,FT,Singapore,L,United Kingdom,0,"AWS, Kubernetes, NLP, Azure",Bachelor,4,Consulting,2025-02-03,2025-02-21,2499,5.5,Smart Analytics +AI08170,AI Specialist,300635,USD,300635,EX,CT,United States,L,United States,100,"PyTorch, Python, Computer Vision, Scala",Associate,10,Energy,2024-06-18,2024-07-24,1527,7.8,Quantum Computing Inc +AI08171,AI Specialist,94953,USD,94953,MI,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Scala, Linux, TensorFlow",Bachelor,2,Healthcare,2024-01-04,2024-02-03,999,7.1,Machine Intelligence Group +AI08172,AI Architect,178775,AUD,241346,EX,FT,Australia,S,Denmark,0,"Java, Tableau, R, Statistics, GCP",Associate,11,Retail,2024-08-21,2024-10-13,1289,5,Machine Intelligence Group +AI08173,Data Analyst,74369,CAD,92961,MI,FT,Canada,S,Canada,100,"Statistics, Data Visualization, GCP, Hadoop",Associate,3,Real Estate,2024-11-10,2024-11-27,1659,7.9,Digital Transformation LLC +AI08174,Computer Vision Engineer,75798,USD,75798,EN,FL,Norway,M,Norway,0,"Statistics, R, Mathematics",Associate,1,Media,2024-04-28,2024-05-25,1617,6.8,DeepTech Ventures +AI08175,Autonomous Systems Engineer,186114,EUR,158197,EX,FL,Austria,L,Austria,100,"NLP, SQL, Data Visualization, Azure",Associate,19,Consulting,2024-12-15,2025-02-19,762,9.2,Cognitive Computing +AI08176,AI Product Manager,95648,USD,95648,MI,CT,Ireland,M,Austria,50,"Linux, Python, Java, Spark",Bachelor,4,Energy,2024-10-04,2024-11-29,1137,6.4,Digital Transformation LLC +AI08177,AI Research Scientist,359202,CHF,323282,EX,CT,Switzerland,M,Switzerland,0,"Python, MLOps, Computer Vision",Associate,13,Finance,2025-01-26,2025-03-29,1430,7.7,DataVision Ltd +AI08178,Head of AI,76073,GBP,57055,MI,FL,United Kingdom,S,United Kingdom,50,"Python, Git, TensorFlow, MLOps",Master,2,Technology,2024-09-17,2024-11-11,1703,7.3,Advanced Robotics +AI08179,NLP Engineer,49705,USD,49705,EN,FT,Finland,M,Indonesia,50,"Spark, Tableau, Azure, GCP",Bachelor,0,Telecommunications,2024-07-25,2024-08-30,1697,5.1,DataVision Ltd +AI08180,AI Consultant,98961,EUR,84117,MI,FL,Netherlands,S,Ireland,100,"R, PyTorch, Docker, Linux",Master,4,Technology,2025-01-16,2025-02-18,1231,6.1,Cloud AI Solutions +AI08181,Data Scientist,73832,USD,73832,EN,FL,United States,M,United States,0,"NLP, Spark, Deep Learning, MLOps",PhD,0,Healthcare,2025-04-28,2025-06-20,1551,5.2,Cloud AI Solutions +AI08182,NLP Engineer,209012,USD,209012,EX,FL,Sweden,M,Sweden,0,"Python, Kubernetes, Spark",Bachelor,16,Government,2024-10-04,2024-11-26,2115,7.8,DataVision Ltd +AI08183,AI Research Scientist,114933,JPY,12642630,MI,CT,Japan,M,Russia,0,"Kubernetes, Git, SQL",Associate,3,Automotive,2024-03-18,2024-05-29,608,6.3,Digital Transformation LLC +AI08184,Data Analyst,127420,CHF,114678,MI,FL,Switzerland,M,Switzerland,0,"Docker, Python, TensorFlow",PhD,3,Consulting,2024-04-30,2024-05-27,987,9.7,Smart Analytics +AI08185,Machine Learning Engineer,144510,EUR,122834,SE,PT,France,L,France,50,"Computer Vision, Hadoop, Mathematics",Master,5,Retail,2025-02-05,2025-02-24,2346,8.4,Digital Transformation LLC +AI08186,Autonomous Systems Engineer,99445,AUD,134251,SE,FT,Australia,S,Australia,50,"MLOps, Tableau, SQL, Data Visualization, R",PhD,9,Consulting,2024-08-30,2024-09-21,1691,8.9,Autonomous Tech +AI08187,AI Research Scientist,101862,EUR,86583,MI,FT,Netherlands,L,Netherlands,50,"Deep Learning, PyTorch, TensorFlow, GCP",Bachelor,4,Automotive,2024-09-04,2024-10-04,2009,7.1,Future Systems +AI08188,Computer Vision Engineer,54758,USD,54758,EN,CT,Israel,S,Ghana,0,"TensorFlow, SQL, MLOps, GCP",Bachelor,0,Transportation,2024-12-08,2025-02-18,1157,8.2,Neural Networks Co +AI08189,Robotics Engineer,93957,EUR,79863,MI,PT,Netherlands,S,Mexico,50,"GCP, SQL, Azure",PhD,4,Energy,2024-11-03,2025-01-03,569,6.7,Quantum Computing Inc +AI08190,Machine Learning Researcher,184257,EUR,156618,EX,PT,Austria,L,Austria,0,"SQL, Docker, Data Visualization",Associate,17,Telecommunications,2025-02-08,2025-04-17,1806,6.3,Cognitive Computing +AI08191,Head of AI,65196,EUR,55417,MI,PT,France,S,France,50,"SQL, TensorFlow, Data Visualization, Linux",PhD,2,Government,2024-09-16,2024-10-20,909,8.6,Future Systems +AI08192,Data Analyst,121164,USD,121164,EX,FL,South Korea,S,South Korea,50,"GCP, Git, Deep Learning, Docker",Bachelor,12,Education,2024-05-09,2024-06-11,1313,5.9,Machine Intelligence Group +AI08193,Machine Learning Engineer,93873,AUD,126729,SE,PT,Australia,S,Australia,50,"Mathematics, Data Visualization, Tableau, Linux, Hadoop",Bachelor,7,Retail,2024-06-04,2024-06-27,1816,9.2,Digital Transformation LLC +AI08194,Computer Vision Engineer,148307,USD,148307,MI,FL,Denmark,L,Denmark,50,"Java, Computer Vision, Python, Tableau, Data Visualization",PhD,3,Healthcare,2024-10-08,2024-11-09,2328,6.2,AI Innovations +AI08195,AI Specialist,145377,GBP,109033,EX,PT,United Kingdom,S,United Kingdom,100,"Git, Deep Learning, Data Visualization",PhD,10,Technology,2024-03-08,2024-05-14,1526,9.6,DataVision Ltd +AI08196,Autonomous Systems Engineer,42525,USD,42525,EN,PT,South Korea,M,Estonia,50,"SQL, Deep Learning, Java, Python",Associate,1,Finance,2024-10-26,2024-11-25,862,9.3,Cognitive Computing +AI08197,AI Software Engineer,282434,USD,282434,EX,CT,Denmark,S,Denmark,100,"Azure, Java, MLOps, SQL, R",PhD,18,Telecommunications,2024-06-07,2024-06-26,1490,8.2,DeepTech Ventures +AI08198,AI Research Scientist,209133,USD,209133,EX,FT,Norway,L,Germany,50,"Scala, Git, Computer Vision, Spark",Associate,15,Energy,2024-01-01,2024-01-26,2279,8.1,Cognitive Computing +AI08199,Principal Data Scientist,250333,GBP,187750,EX,FT,United Kingdom,L,United Kingdom,0,"Linux, Statistics, PyTorch, Mathematics, Tableau",Bachelor,18,Healthcare,2024-01-23,2024-03-22,1827,8,Predictive Systems +AI08200,Research Scientist,174979,USD,174979,EX,FL,Norway,S,Indonesia,100,"Deep Learning, AWS, Computer Vision, Scala",Bachelor,18,Technology,2024-03-16,2024-03-30,2275,7.5,Smart Analytics +AI08201,Data Scientist,101837,USD,101837,SE,CT,Sweden,S,Sweden,100,"Azure, Scala, PyTorch",Bachelor,6,Government,2024-10-03,2024-10-20,600,6.6,Quantum Computing Inc +AI08202,Machine Learning Researcher,109223,USD,109223,SE,FT,Finland,M,Estonia,100,"TensorFlow, Azure, Mathematics, Kubernetes, AWS",Bachelor,5,Gaming,2024-07-28,2024-08-16,1615,8.2,Algorithmic Solutions +AI08203,Machine Learning Researcher,160180,USD,160180,SE,CT,Norway,S,Norway,50,"Linux, Scala, Mathematics, Kubernetes, Tableau",PhD,8,Real Estate,2024-11-06,2025-01-07,1020,6.1,Autonomous Tech +AI08204,Principal Data Scientist,52809,USD,52809,EN,PT,South Korea,L,South Korea,0,"Tableau, PyTorch, Git",Bachelor,1,Retail,2024-05-04,2024-05-30,1410,6.8,Autonomous Tech +AI08205,Computer Vision Engineer,218360,USD,218360,EX,FT,Norway,M,Norway,0,"Kubernetes, R, AWS, Mathematics, Statistics",Bachelor,12,Healthcare,2025-04-06,2025-04-26,2264,9.8,Digital Transformation LLC +AI08206,AI Consultant,99844,EUR,84867,MI,FT,Austria,L,India,0,"Hadoop, TensorFlow, Java, GCP, Docker",Bachelor,2,Retail,2024-07-28,2024-10-05,1801,8.3,Algorithmic Solutions +AI08207,AI Research Scientist,191537,SGD,248998,EX,FL,Singapore,L,Ireland,0,"Data Visualization, Hadoop, Computer Vision",Associate,12,Finance,2024-03-25,2024-04-29,928,6.4,Algorithmic Solutions +AI08208,Machine Learning Researcher,225775,USD,225775,EX,CT,Israel,M,Israel,0,"Python, Java, Hadoop, GCP, NLP",Bachelor,14,Finance,2024-05-13,2024-06-02,1054,5.5,AI Innovations +AI08209,Data Scientist,83618,USD,83618,EN,FL,Finland,L,Finland,0,"TensorFlow, Python, Hadoop, Tableau",Master,0,Automotive,2024-11-14,2025-01-21,1114,8.9,Neural Networks Co +AI08210,ML Ops Engineer,167785,EUR,142617,EX,FT,Germany,S,Germany,100,"Git, Deep Learning, Azure",Master,14,Manufacturing,2024-09-30,2024-10-29,1951,8.1,Machine Intelligence Group +AI08211,AI Research Scientist,25456,USD,25456,EN,CT,India,S,India,0,"AWS, Mathematics, Python",Bachelor,0,Government,2024-10-05,2024-10-19,1184,6.8,Neural Networks Co +AI08212,Data Analyst,109322,USD,109322,SE,CT,South Korea,L,South Korea,50,"Python, SQL, TensorFlow, AWS, Java",PhD,6,Gaming,2024-03-05,2024-05-03,2326,9.2,TechCorp Inc +AI08213,AI Architect,100260,USD,100260,SE,FL,Finland,M,Belgium,50,"PyTorch, Hadoop, Docker, Computer Vision",PhD,9,Manufacturing,2024-09-07,2024-10-14,1995,10,Smart Analytics +AI08214,Data Analyst,111999,USD,111999,SE,PT,Israel,M,Israel,50,"PyTorch, Python, Java, NLP, Hadoop",PhD,5,Automotive,2025-03-02,2025-05-09,833,5,AI Innovations +AI08215,Robotics Engineer,70798,JPY,7787780,EN,FT,Japan,M,Japan,100,"Tableau, TensorFlow, Python",PhD,1,Finance,2024-12-17,2025-01-04,1022,6.7,DataVision Ltd +AI08216,Robotics Engineer,75569,AUD,102018,MI,PT,Australia,S,Australia,50,"AWS, PyTorch, SQL",Bachelor,4,Gaming,2025-03-15,2025-05-06,1557,6.9,Neural Networks Co +AI08217,Autonomous Systems Engineer,173910,USD,173910,EX,PT,Israel,L,Israel,0,"TensorFlow, Deep Learning, Azure",Master,10,Healthcare,2025-01-18,2025-03-06,1685,5.6,Smart Analytics +AI08218,AI Software Engineer,234620,USD,234620,EX,PT,United States,M,United States,50,"Data Visualization, Git, GCP",Master,11,Consulting,2024-03-19,2024-05-30,2246,5.6,TechCorp Inc +AI08219,Data Scientist,54313,EUR,46166,EN,FL,Netherlands,S,Netherlands,50,"Azure, R, Scala, SQL, Git",Associate,1,Transportation,2024-04-04,2024-05-14,626,5.5,Predictive Systems +AI08220,Machine Learning Engineer,223033,GBP,167275,EX,FL,United Kingdom,S,Mexico,50,"Java, Computer Vision, SQL",Bachelor,14,Telecommunications,2024-05-05,2024-06-16,531,9.2,Autonomous Tech +AI08221,ML Ops Engineer,235007,USD,235007,EX,FT,South Korea,L,South Korea,0,"SQL, Kubernetes, NLP",Master,16,Healthcare,2024-10-22,2024-12-18,2222,9.2,TechCorp Inc +AI08222,AI Specialist,68349,EUR,58097,EN,PT,Netherlands,S,Netherlands,100,"Docker, NLP, Data Visualization, Linux",Master,0,Finance,2025-04-19,2025-06-14,2333,8.6,Future Systems +AI08223,AI Consultant,88924,USD,88924,MI,CT,Israel,L,Israel,100,"SQL, PyTorch, Deep Learning, Azure, AWS",Master,4,Real Estate,2024-03-23,2024-05-25,1368,5.8,Predictive Systems +AI08224,AI Specialist,107723,USD,107723,SE,FT,South Korea,L,South Korea,50,"R, Python, Statistics, Spark, GCP",Associate,5,Energy,2025-04-13,2025-06-23,664,8.2,Machine Intelligence Group +AI08225,AI Architect,100120,USD,100120,MI,FL,Denmark,S,Denmark,100,"Python, Git, Spark",Associate,4,Technology,2024-02-17,2024-04-07,2445,5.5,Neural Networks Co +AI08226,AI Specialist,52959,USD,52959,EN,CT,Israel,S,Israel,50,"Python, Tableau, Git",Master,1,Retail,2024-12-09,2025-01-28,645,5.7,DataVision Ltd +AI08227,ML Ops Engineer,88552,EUR,75269,EN,CT,Germany,L,Portugal,50,"MLOps, Tableau, SQL",PhD,0,Consulting,2025-03-02,2025-04-08,1539,5.8,AI Innovations +AI08228,AI Research Scientist,152649,CHF,137384,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, Kubernetes, MLOps",Bachelor,6,Transportation,2025-04-20,2025-06-07,963,5.9,Cloud AI Solutions +AI08229,Computer Vision Engineer,89988,USD,89988,EX,FL,China,L,China,100,"TensorFlow, Spark, Data Visualization, SQL, Docker",Bachelor,19,Healthcare,2024-12-31,2025-01-23,686,6.8,Algorithmic Solutions +AI08230,Principal Data Scientist,91107,USD,91107,MI,PT,United States,S,Japan,0,"R, Data Visualization, Linux",PhD,4,Retail,2025-04-05,2025-04-23,2056,8.4,Digital Transformation LLC +AI08231,AI Software Engineer,144476,USD,144476,MI,FT,United States,L,Mexico,100,"Python, SQL, Tableau, Git, Java",Master,2,Manufacturing,2024-11-04,2024-12-02,1950,6.9,Advanced Robotics +AI08232,Data Engineer,161347,CHF,145212,SE,PT,Switzerland,M,Switzerland,0,"Data Visualization, Spark, PyTorch, Git, Statistics",Bachelor,6,Telecommunications,2024-11-24,2025-01-11,1879,9.9,DataVision Ltd +AI08233,Principal Data Scientist,140235,AUD,189317,EX,FT,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau",Master,11,Energy,2024-05-27,2024-06-13,2013,9.6,Algorithmic Solutions +AI08234,Data Analyst,148219,USD,148219,EX,CT,Sweden,S,Sweden,100,"Java, Azure, Tableau, Python",Associate,16,Manufacturing,2024-10-26,2024-12-31,1949,8.6,Smart Analytics +AI08235,AI Architect,105601,SGD,137281,SE,FT,Singapore,S,France,100,"Git, Python, Hadoop",Master,7,Media,2024-01-23,2024-03-30,2256,5.8,AI Innovations +AI08236,AI Architect,64809,JPY,7128990,EN,CT,Japan,L,Portugal,0,"Docker, R, NLP",Bachelor,1,Technology,2025-01-14,2025-02-15,1701,7.2,Algorithmic Solutions +AI08237,Machine Learning Researcher,78106,EUR,66390,EN,FT,Austria,L,Germany,50,"Spark, PyTorch, R, Computer Vision",Master,1,Consulting,2025-04-25,2025-06-26,2113,9.1,Advanced Robotics +AI08238,Data Analyst,60250,SGD,78325,EN,FL,Singapore,M,Singapore,100,"SQL, Scala, Kubernetes, Deep Learning",PhD,1,Retail,2025-04-01,2025-05-30,1424,7.3,Cloud AI Solutions +AI08239,Machine Learning Researcher,54773,GBP,41080,EN,CT,United Kingdom,S,United Kingdom,100,"SQL, TensorFlow, Computer Vision, Statistics",Bachelor,0,Automotive,2024-02-22,2024-04-25,2397,7.9,TechCorp Inc +AI08240,Machine Learning Researcher,111174,USD,111174,EN,FL,Denmark,L,Japan,50,"Data Visualization, Hadoop, Python, R",Master,0,Automotive,2024-08-12,2024-09-08,1329,5.9,Cognitive Computing +AI08241,AI Software Engineer,67798,CAD,84748,EN,PT,Canada,L,Malaysia,100,"PyTorch, Python, Docker, Mathematics, SQL",Master,1,Finance,2024-03-10,2024-04-20,631,7.1,Autonomous Tech +AI08242,AI Specialist,124429,USD,124429,SE,FT,Sweden,M,Sweden,50,"Python, Data Visualization, SQL, Computer Vision, Hadoop",Associate,5,Finance,2024-11-02,2024-12-03,1318,8.1,DeepTech Ventures +AI08243,Deep Learning Engineer,61446,EUR,52229,EN,PT,Austria,S,Austria,50,"Statistics, Git, MLOps, GCP",PhD,0,Real Estate,2024-09-06,2024-09-24,1899,6.2,AI Innovations +AI08244,Research Scientist,166025,EUR,141121,EX,CT,Germany,S,Germany,0,"Hadoop, Kubernetes, Git, PyTorch, Linux",PhD,14,Finance,2024-08-11,2024-10-17,782,7.7,Cognitive Computing +AI08245,Deep Learning Engineer,200365,AUD,270493,EX,CT,Australia,M,Australia,100,"Java, SQL, Data Visualization",Bachelor,10,Energy,2024-02-02,2024-03-17,1775,5.6,Cognitive Computing +AI08246,AI Consultant,68661,USD,68661,EN,CT,Denmark,M,Denmark,0,"Python, Git, TensorFlow, Computer Vision",Master,0,Education,2025-03-26,2025-04-10,1038,6.4,Cognitive Computing +AI08247,Research Scientist,128591,USD,128591,MI,CT,United States,L,United States,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,2,Government,2024-06-15,2024-08-08,1680,6.5,Predictive Systems +AI08248,Machine Learning Researcher,90540,USD,90540,MI,FT,Norway,S,Chile,100,"Data Visualization, R, Python, TensorFlow",Associate,2,Education,2024-11-11,2024-12-27,2176,9.9,Quantum Computing Inc +AI08249,AI Software Engineer,98359,USD,98359,MI,FL,United States,M,Spain,100,"Git, AWS, Hadoop, R",Associate,2,Real Estate,2024-10-13,2024-12-22,628,7.9,Cognitive Computing +AI08250,Deep Learning Engineer,60172,USD,60172,EN,FT,Finland,M,Finland,50,"Python, Azure, Tableau",Associate,1,Automotive,2024-01-17,2024-02-14,2166,9.6,Cloud AI Solutions +AI08251,Data Engineer,59702,USD,59702,MI,CT,South Korea,S,South Korea,0,"Statistics, Data Visualization, AWS, Mathematics, Python",Bachelor,4,Real Estate,2024-06-30,2024-08-30,2287,8,AI Innovations +AI08252,Research Scientist,231158,USD,231158,EX,CT,United States,M,Belgium,0,"GCP, Java, Hadoop, Scala",Associate,11,Government,2024-09-01,2024-11-09,1335,5.6,Cognitive Computing +AI08253,Principal Data Scientist,56253,EUR,47815,EN,PT,France,S,Sweden,0,"Tableau, Git, PyTorch, TensorFlow",Associate,1,Real Estate,2024-08-26,2024-09-26,1976,6.2,Autonomous Tech +AI08254,AI Product Manager,66100,USD,66100,EN,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Tableau, Hadoop",Master,1,Government,2024-09-23,2024-11-15,1415,9.7,AI Innovations +AI08255,AI Software Engineer,43269,USD,43269,MI,FT,China,M,China,100,"SQL, MLOps, PyTorch, Statistics, Python",Associate,3,Finance,2024-09-20,2024-10-05,2402,8.5,DeepTech Ventures +AI08256,AI Software Engineer,87445,SGD,113679,EN,PT,Singapore,L,Singapore,0,"Scala, Python, TensorFlow, AWS, Mathematics",Associate,0,Consulting,2025-01-13,2025-03-16,2260,6.9,Cloud AI Solutions +AI08257,Deep Learning Engineer,125861,EUR,106982,SE,FL,Netherlands,L,Netherlands,0,"AWS, Java, Python",Bachelor,9,Technology,2025-02-15,2025-03-06,574,7,Machine Intelligence Group +AI08258,AI Specialist,218971,GBP,164228,EX,PT,United Kingdom,S,Ukraine,0,"PyTorch, Hadoop, Kubernetes, Azure",Master,14,Telecommunications,2024-08-27,2024-11-07,2328,5.7,AI Innovations +AI08259,AI Software Engineer,192168,USD,192168,EX,FL,Ireland,L,Ireland,100,"SQL, Azure, Kubernetes, GCP, NLP",Master,13,Finance,2024-08-18,2024-10-01,1469,7.6,Quantum Computing Inc +AI08260,AI Product Manager,159792,EUR,135823,EX,FL,Austria,M,Austria,100,"R, NLP, Data Visualization, Kubernetes",PhD,19,Healthcare,2024-07-01,2024-07-24,576,8.3,AI Innovations +AI08261,Autonomous Systems Engineer,228879,EUR,194547,EX,FT,Germany,L,Australia,100,"Tableau, Java, Python",Master,13,Real Estate,2024-12-20,2025-01-12,1732,7.4,Machine Intelligence Group +AI08262,AI Product Manager,213850,GBP,160388,EX,FT,United Kingdom,S,United Kingdom,50,"Python, Docker, Hadoop, Statistics",Associate,13,Real Estate,2024-12-05,2025-01-07,1984,6.2,Digital Transformation LLC +AI08263,Machine Learning Engineer,161935,USD,161935,EX,CT,Sweden,S,Spain,50,"AWS, Azure, Deep Learning, Python",Bachelor,14,Finance,2025-01-12,2025-02-12,2282,6.1,AI Innovations +AI08264,NLP Engineer,46071,USD,46071,EN,FT,Finland,S,Finland,50,"Python, Kubernetes, R",Associate,1,Finance,2024-09-11,2024-11-23,1573,8.8,AI Innovations +AI08265,Head of AI,138140,SGD,179582,SE,PT,Singapore,M,Singapore,0,"Python, Statistics, Mathematics",Associate,9,Technology,2024-02-11,2024-03-10,1215,5.5,Advanced Robotics +AI08266,NLP Engineer,40218,USD,40218,MI,FT,India,L,India,0,"Deep Learning, Mathematics, Data Visualization",Master,2,Education,2024-01-01,2024-01-23,1620,7.2,Future Systems +AI08267,Robotics Engineer,69695,CAD,87119,EN,CT,Canada,L,Canada,0,"Hadoop, Java, Scala, Azure",Associate,1,Media,2024-06-03,2024-06-22,1729,6.4,Autonomous Tech +AI08268,Machine Learning Researcher,87123,EUR,74055,MI,PT,Germany,L,Germany,100,"Scala, Data Visualization, Statistics",Associate,4,Energy,2025-03-20,2025-05-13,1316,6.3,Cloud AI Solutions +AI08269,Data Engineer,88198,USD,88198,MI,PT,Israel,S,Israel,100,"Spark, PyTorch, Tableau",PhD,3,Energy,2025-01-22,2025-03-21,715,7.3,Smart Analytics +AI08270,AI Product Manager,64179,USD,64179,EN,PT,Sweden,S,Sweden,100,"Java, Git, AWS, Linux, Computer Vision",Associate,0,Consulting,2024-07-13,2024-08-11,1398,9.8,DataVision Ltd +AI08271,ML Ops Engineer,85336,USD,85336,MI,CT,Ireland,M,Ireland,100,"Kubernetes, TensorFlow, Tableau, MLOps, Data Visualization",Master,4,Manufacturing,2024-11-05,2024-12-23,754,6.4,TechCorp Inc +AI08272,Head of AI,83626,AUD,112895,MI,FL,Australia,L,Hungary,0,"Linux, Kubernetes, Scala, Java",PhD,2,Government,2025-03-28,2025-04-18,1439,8.6,Future Systems +AI08273,AI Product Manager,103151,USD,103151,MI,PT,United States,L,United States,50,"Data Visualization, Scala, Tableau",PhD,4,Gaming,2024-11-10,2024-12-04,1252,6.1,Quantum Computing Inc +AI08274,Principal Data Scientist,71248,USD,71248,MI,CT,South Korea,L,South Korea,0,"Data Visualization, Tableau, SQL, NLP, Python",PhD,3,Real Estate,2025-03-01,2025-04-26,1534,10,Advanced Robotics +AI08275,Data Scientist,85197,USD,85197,EN,FL,Ireland,L,Ireland,0,"Docker, Git, Data Visualization",PhD,1,Energy,2024-07-26,2024-09-25,590,6.8,TechCorp Inc +AI08276,AI Consultant,48680,USD,48680,EN,FL,South Korea,S,South Korea,0,"Hadoop, Computer Vision, AWS, PyTorch",Associate,0,Retail,2024-10-05,2024-12-07,1515,9.8,Quantum Computing Inc +AI08277,Head of AI,104442,USD,104442,EN,FL,Norway,M,Norway,50,"Hadoop, R, SQL, MLOps, NLP",PhD,0,Manufacturing,2025-03-21,2025-04-10,1557,8.3,Algorithmic Solutions +AI08278,AI Software Engineer,108808,EUR,92487,SE,FT,Germany,M,Germany,50,"Data Visualization, PyTorch, Scala, AWS",Bachelor,7,Energy,2024-11-29,2025-01-17,851,5.9,DeepTech Ventures +AI08279,Head of AI,222268,EUR,188928,EX,CT,France,L,France,0,"Azure, Kubernetes, Statistics",Associate,12,Automotive,2024-11-20,2024-12-13,1598,8.2,TechCorp Inc +AI08280,AI Research Scientist,69400,USD,69400,MI,CT,Finland,M,Turkey,0,"Deep Learning, Data Visualization, Tableau, Spark, Computer Vision",PhD,2,Real Estate,2024-04-27,2024-06-19,909,6.3,Smart Analytics +AI08281,ML Ops Engineer,146017,JPY,16061870,EX,CT,Japan,S,Colombia,0,"Linux, Deep Learning, SQL",PhD,17,Gaming,2024-02-07,2024-03-10,551,8.4,Advanced Robotics +AI08282,AI Architect,128715,SGD,167330,SE,CT,Singapore,M,Singapore,50,"Python, Deep Learning, Java, SQL",Bachelor,7,Technology,2024-11-05,2024-11-22,1880,6,Smart Analytics +AI08283,Principal Data Scientist,291772,CHF,262595,EX,PT,Switzerland,M,Switzerland,50,"Kubernetes, Docker, SQL, Tableau",Associate,15,Telecommunications,2024-01-02,2024-02-19,1924,6.9,Future Systems +AI08284,Robotics Engineer,88229,USD,88229,SE,FT,South Korea,M,Germany,50,"Docker, Azure, Mathematics, Java",Associate,5,Telecommunications,2024-03-12,2024-04-26,2075,5.3,Cognitive Computing +AI08285,Head of AI,125238,AUD,169071,SE,PT,Australia,S,Japan,0,"Deep Learning, AWS, R, Python",Master,5,Gaming,2024-01-16,2024-02-18,2338,6,Digital Transformation LLC +AI08286,Autonomous Systems Engineer,59375,USD,59375,EN,FL,Finland,S,Finland,0,"R, Tableau, Scala",Bachelor,0,Technology,2024-11-20,2024-12-16,2109,9.5,Advanced Robotics +AI08287,Computer Vision Engineer,200898,USD,200898,EX,FL,Sweden,L,Sweden,100,"MLOps, Git, SQL",Bachelor,16,Automotive,2024-10-11,2024-10-26,2127,9.4,Advanced Robotics +AI08288,AI Architect,70777,USD,70777,EX,CT,India,L,India,0,"Linux, Hadoop, Kubernetes",Associate,18,Retail,2024-10-07,2024-11-10,1846,8.8,DataVision Ltd +AI08289,Head of AI,174280,GBP,130710,EX,PT,United Kingdom,M,Singapore,0,"Git, GCP, MLOps, Python, Azure",PhD,11,Real Estate,2024-10-06,2024-12-05,1269,8.2,DataVision Ltd +AI08290,Autonomous Systems Engineer,83034,CAD,103793,MI,FL,Canada,M,Canada,50,"Azure, PyTorch, Scala, Git, TensorFlow",Bachelor,3,Real Estate,2025-01-07,2025-02-17,2323,7.6,Autonomous Tech +AI08291,Machine Learning Engineer,80523,USD,80523,MI,FT,South Korea,L,South Korea,100,"Statistics, PyTorch, NLP, Azure",Master,3,Real Estate,2025-04-06,2025-05-22,2395,6.7,Quantum Computing Inc +AI08292,Machine Learning Engineer,85363,USD,85363,EN,CT,Sweden,L,Turkey,50,"Python, SQL, Linux, GCP, Hadoop",Bachelor,0,Media,2024-03-19,2024-04-07,601,9.8,Machine Intelligence Group +AI08293,NLP Engineer,84635,USD,84635,EN,CT,Denmark,M,Denmark,0,"Tableau, SQL, Scala",PhD,1,Retail,2024-04-02,2024-04-19,1101,8.4,Machine Intelligence Group +AI08294,AI Research Scientist,92637,EUR,78741,SE,PT,Germany,S,Germany,0,"GCP, Mathematics, Git, SQL",Associate,7,Real Estate,2024-10-31,2024-12-12,716,7.4,AI Innovations +AI08295,AI Research Scientist,135123,SGD,175660,SE,FT,Singapore,S,Singapore,0,"MLOps, Spark, Deep Learning, AWS, R",Associate,7,Telecommunications,2024-08-25,2024-09-10,596,9.9,Future Systems +AI08296,Principal Data Scientist,73693,USD,73693,EX,CT,China,S,China,50,"R, Deep Learning, Statistics, Python, TensorFlow",Associate,13,Healthcare,2024-01-01,2024-02-25,1055,9.1,Cloud AI Solutions +AI08297,AI Specialist,62151,USD,62151,SE,FL,China,M,China,100,"TensorFlow, Python, Java",Bachelor,6,Government,2024-03-16,2024-04-17,1507,7.1,AI Innovations +AI08298,Data Engineer,107829,CHF,97046,MI,FL,Switzerland,S,Switzerland,0,"Spark, TensorFlow, Python, Git",Bachelor,3,Government,2024-07-27,2024-09-17,815,5.8,Cloud AI Solutions +AI08299,Robotics Engineer,149913,GBP,112435,SE,FT,United Kingdom,M,Mexico,100,"Kubernetes, SQL, Statistics, MLOps, Azure",Associate,8,Manufacturing,2024-12-15,2025-01-22,1153,5.7,Neural Networks Co +AI08300,Head of AI,147367,USD,147367,SE,PT,United States,M,Denmark,50,"Data Visualization, Scala, AWS, Computer Vision, SQL",Bachelor,9,Automotive,2025-04-13,2025-06-11,2235,5.2,Cloud AI Solutions +AI08301,Research Scientist,143496,USD,143496,EX,FT,Finland,M,Finland,50,"Linux, Kubernetes, Docker, Tableau",PhD,15,Consulting,2024-01-29,2024-02-23,962,7.3,Machine Intelligence Group +AI08302,AI Architect,265331,USD,265331,EX,FT,Norway,L,Netherlands,50,"Deep Learning, Hadoop, R, SQL, NLP",Master,10,Healthcare,2024-05-25,2024-06-21,605,6.3,Quantum Computing Inc +AI08303,AI Product Manager,72261,EUR,61422,EN,PT,Germany,S,Germany,0,"Data Visualization, Python, Hadoop, Linux, Java",Associate,1,Manufacturing,2024-06-18,2024-08-14,2384,5.7,DataVision Ltd +AI08304,AI Specialist,255237,CHF,229713,EX,CT,Switzerland,S,Mexico,50,"Azure, TensorFlow, Tableau, Data Visualization, GCP",Bachelor,12,Gaming,2024-02-16,2024-03-30,969,7.7,TechCorp Inc +AI08305,AI Specialist,61670,USD,61670,EN,PT,Ireland,M,Ireland,0,"Kubernetes, Python, Spark, Data Visualization",Associate,1,Retail,2024-10-05,2024-12-07,567,8,Smart Analytics +AI08306,AI Product Manager,92113,USD,92113,MI,PT,Ireland,M,Ireland,50,"Azure, Python, Data Visualization, Java, GCP",Master,3,Automotive,2024-05-05,2024-07-02,2339,6.7,Neural Networks Co +AI08307,Head of AI,291884,EUR,248101,EX,PT,Germany,L,Philippines,100,"Data Visualization, Mathematics, SQL",Bachelor,17,Consulting,2025-01-13,2025-02-14,859,7.4,Advanced Robotics +AI08308,Autonomous Systems Engineer,180243,JPY,19826730,EX,PT,Japan,L,Japan,0,"AWS, Hadoop, Java",Bachelor,18,Retail,2025-01-20,2025-03-27,2024,9.9,DeepTech Ventures +AI08309,AI Product Manager,57135,USD,57135,EX,CT,India,M,India,0,"PyTorch, Git, Data Visualization, Scala, Hadoop",Bachelor,10,Automotive,2025-02-07,2025-03-09,1222,8.6,Autonomous Tech +AI08310,Deep Learning Engineer,109488,SGD,142334,SE,FT,Singapore,S,Chile,100,"Linux, SQL, NLP",Bachelor,7,Healthcare,2024-05-13,2024-06-30,1770,5.8,Algorithmic Solutions +AI08311,Head of AI,124520,USD,124520,MI,FT,Denmark,S,Mexico,0,"Git, AWS, Kubernetes",Associate,4,Media,2024-03-09,2024-05-12,922,6.9,DataVision Ltd +AI08312,Deep Learning Engineer,127767,USD,127767,MI,CT,United States,M,United States,50,"Spark, GCP, PyTorch, Mathematics",Associate,4,Transportation,2024-05-01,2024-07-08,1260,7.7,Autonomous Tech +AI08313,Robotics Engineer,80406,USD,80406,MI,FT,Sweden,M,Sweden,0,"MLOps, Azure, Deep Learning",PhD,3,Media,2024-11-01,2024-11-26,1697,6.8,Predictive Systems +AI08314,AI Consultant,82023,CAD,102529,MI,CT,Canada,L,Canada,50,"Linux, Python, TensorFlow, PyTorch",Associate,4,Media,2024-04-14,2024-06-25,1382,9.6,TechCorp Inc +AI08315,Research Scientist,128543,SGD,167106,SE,CT,Singapore,M,Singapore,50,"Python, Spark, PyTorch, Kubernetes",Master,8,Energy,2024-08-05,2024-09-25,514,8,Advanced Robotics +AI08316,Deep Learning Engineer,75558,USD,75558,MI,PT,Sweden,M,Sweden,100,"Spark, Python, SQL, GCP",Associate,2,Transportation,2024-12-21,2025-01-27,1422,6.4,Quantum Computing Inc +AI08317,NLP Engineer,72192,GBP,54144,EN,PT,United Kingdom,M,Poland,50,"Kubernetes, Java, Hadoop",Master,0,Manufacturing,2024-09-08,2024-09-26,501,7.4,Cognitive Computing +AI08318,Data Scientist,68382,EUR,58125,EN,PT,Germany,S,Germany,0,"Deep Learning, Git, Java, SQL",PhD,1,Automotive,2024-03-23,2024-04-26,2001,8.9,Digital Transformation LLC +AI08319,Machine Learning Engineer,37162,USD,37162,SE,FT,India,S,China,100,"Scala, Mathematics, Deep Learning",Master,5,Retail,2024-12-14,2025-02-04,1613,7.5,Algorithmic Solutions +AI08320,Data Engineer,90745,EUR,77133,MI,CT,Netherlands,S,Netherlands,50,"Tableau, SQL, Scala, PyTorch, Python",Master,2,Automotive,2024-08-28,2024-11-03,2203,9.5,AI Innovations +AI08321,Data Engineer,68389,USD,68389,EN,CT,Finland,M,Finland,50,"Hadoop, Python, TensorFlow",Bachelor,1,Automotive,2024-05-27,2024-07-04,1625,8.4,Machine Intelligence Group +AI08322,Deep Learning Engineer,52150,USD,52150,EX,CT,India,S,Japan,50,"PyTorch, MLOps, SQL",Master,16,Telecommunications,2024-02-15,2024-03-10,839,8.4,AI Innovations +AI08323,Machine Learning Engineer,70856,USD,70856,MI,CT,Israel,M,Israel,0,"Kubernetes, Git, Spark, Scala",Bachelor,2,Manufacturing,2024-03-08,2024-05-13,1675,6.1,Cognitive Computing +AI08324,AI Product Manager,70901,USD,70901,EN,FT,Sweden,L,Sweden,0,"AWS, Python, Git, Deep Learning, TensorFlow",Bachelor,0,Education,2024-03-22,2024-04-23,1246,8,Cloud AI Solutions +AI08325,Machine Learning Engineer,18392,USD,18392,EN,CT,India,S,Colombia,100,"Spark, Git, R, Java",PhD,0,Manufacturing,2024-02-18,2024-03-09,1206,9.7,Machine Intelligence Group +AI08326,Machine Learning Engineer,72083,GBP,54062,MI,CT,United Kingdom,S,United Kingdom,100,"Scala, Git, Kubernetes, SQL, AWS",Master,4,Energy,2024-02-27,2024-04-26,1006,9.8,Advanced Robotics +AI08327,Data Engineer,80363,EUR,68309,EN,FL,Netherlands,M,United States,0,"Computer Vision, Spark, Deep Learning, SQL",Bachelor,1,Education,2025-04-30,2025-06-13,2448,8.5,Future Systems +AI08328,Deep Learning Engineer,81508,USD,81508,EX,PT,India,L,India,50,"Hadoop, NLP, Deep Learning, Tableau, Kubernetes",Master,10,Healthcare,2024-07-16,2024-09-17,1183,9.4,Cognitive Computing +AI08329,Computer Vision Engineer,58680,CAD,73350,EN,FT,Canada,M,Ghana,100,"Docker, Scala, SQL, Kubernetes",Bachelor,1,Real Estate,2025-03-24,2025-05-02,1626,5.9,DeepTech Ventures +AI08330,Deep Learning Engineer,127110,EUR,108044,SE,PT,Netherlands,L,Switzerland,100,"NLP, SQL, Linux, Git, GCP",PhD,6,Education,2024-10-21,2024-12-27,1388,9.8,DataVision Ltd +AI08331,Deep Learning Engineer,35777,USD,35777,EN,PT,China,L,China,0,"Hadoop, Java, Data Visualization, NLP",Master,1,Consulting,2024-02-04,2024-03-12,2081,6,Digital Transformation LLC +AI08332,AI Architect,137961,EUR,117267,SE,FL,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Kubernetes",Master,7,Finance,2025-02-23,2025-04-23,1015,8.2,Quantum Computing Inc +AI08333,Data Analyst,93307,CHF,83976,EN,FL,Switzerland,L,Switzerland,50,"SQL, PyTorch, TensorFlow, Linux",Master,0,Manufacturing,2024-03-30,2024-05-22,1208,6.4,Machine Intelligence Group +AI08334,Autonomous Systems Engineer,90828,AUD,122618,EN,FL,Australia,L,Australia,100,"Git, MLOps, Data Visualization",Bachelor,0,Education,2024-02-15,2024-03-30,1635,7.5,Cognitive Computing +AI08335,Data Engineer,42637,USD,42637,SE,PT,India,M,India,0,"SQL, PyTorch, Linux, Scala",PhD,8,Retail,2024-07-27,2024-10-03,1949,7.8,DataVision Ltd +AI08336,Machine Learning Engineer,183463,USD,183463,EX,CT,Denmark,S,Denmark,50,"Python, Computer Vision, Tableau, TensorFlow, Git",Associate,19,Automotive,2024-04-18,2024-05-24,674,5.9,Future Systems +AI08337,Machine Learning Engineer,110858,AUD,149658,MI,CT,Australia,L,Ireland,100,"PyTorch, Java, Tableau, Docker, Statistics",Associate,2,Manufacturing,2025-04-03,2025-05-15,1345,8.7,Cloud AI Solutions +AI08338,AI Consultant,187012,USD,187012,EX,CT,Finland,S,Finland,0,"Git, Azure, Computer Vision, Kubernetes",Master,13,Government,2024-03-21,2024-04-07,640,8.1,Algorithmic Solutions +AI08339,AI Software Engineer,267395,USD,267395,EX,PT,United States,L,United States,0,"Python, TensorFlow, Computer Vision, Statistics",Associate,17,Retail,2024-04-05,2024-05-03,2448,5.1,TechCorp Inc +AI08340,AI Software Engineer,49037,JPY,5394070,EN,PT,Japan,S,Sweden,50,"Computer Vision, Azure, Statistics, SQL, Spark",Bachelor,0,Government,2024-07-25,2024-08-29,2046,8.4,Machine Intelligence Group +AI08341,Deep Learning Engineer,231031,USD,231031,EX,FL,Ireland,L,Ireland,100,"NLP, AWS, SQL, Computer Vision",PhD,16,Automotive,2025-02-18,2025-04-10,1911,8.1,Future Systems +AI08342,AI Specialist,265453,USD,265453,EX,CT,Ireland,L,Ireland,50,"MLOps, AWS, Kubernetes, Scala, Hadoop",Master,14,Automotive,2024-12-24,2025-01-14,1989,7.9,Machine Intelligence Group +AI08343,AI Consultant,82540,USD,82540,MI,CT,Israel,S,Israel,100,"Git, AWS, Python, Computer Vision, Statistics",Bachelor,2,Gaming,2025-02-05,2025-04-01,2265,7.7,Cloud AI Solutions +AI08344,AI Specialist,126029,USD,126029,SE,FL,Israel,S,Israel,50,"Spark, Docker, Computer Vision, Statistics, Python",Master,6,Automotive,2025-02-23,2025-04-07,1666,8.1,Predictive Systems +AI08345,AI Architect,224510,JPY,24696100,EX,PT,Japan,S,Japan,50,"PyTorch, Docker, Git",Bachelor,14,Technology,2025-02-07,2025-04-17,2078,8.4,AI Innovations +AI08346,Research Scientist,76405,USD,76405,EN,FT,Denmark,L,Denmark,0,"Data Visualization, AWS, Spark, Mathematics",Bachelor,1,Gaming,2024-04-13,2024-05-03,1596,7.1,Algorithmic Solutions +AI08347,Machine Learning Researcher,57273,USD,57273,EN,FL,Israel,L,Israel,0,"Kubernetes, SQL, Mathematics",Bachelor,1,Transportation,2025-01-20,2025-03-23,984,7.8,Neural Networks Co +AI08348,Robotics Engineer,78816,USD,78816,MI,FL,South Korea,L,South Korea,50,"Linux, Computer Vision, R, Statistics",Associate,2,Gaming,2024-01-23,2024-02-19,1491,7,DataVision Ltd +AI08349,AI Specialist,129597,USD,129597,EX,FL,Ireland,S,Thailand,50,"Kubernetes, SQL, Statistics, Computer Vision, Java",Master,19,Real Estate,2024-09-25,2024-11-11,1470,7.5,DeepTech Ventures +AI08350,Robotics Engineer,78527,USD,78527,EX,PT,India,L,India,50,"SQL, Tableau, Linux",PhD,16,Energy,2025-01-12,2025-02-13,1545,6.5,Neural Networks Co +AI08351,AI Consultant,147701,GBP,110776,SE,FT,United Kingdom,L,Finland,50,"Computer Vision, Spark, Statistics, Python",Associate,7,Finance,2024-08-08,2024-09-20,623,8,Autonomous Tech +AI08352,Machine Learning Researcher,124500,USD,124500,SE,PT,Israel,L,Israel,100,"Git, Data Visualization, NLP",Associate,6,Consulting,2024-09-22,2024-11-26,2444,7.1,DataVision Ltd +AI08353,Data Engineer,30093,USD,30093,MI,FT,India,L,India,100,"Python, Computer Vision, Statistics",PhD,2,Real Estate,2024-07-08,2024-07-23,1079,5.6,DeepTech Ventures +AI08354,Computer Vision Engineer,95154,USD,95154,MI,CT,Sweden,M,Sweden,100,"Git, NLP, GCP",Bachelor,4,Gaming,2024-03-22,2024-04-23,755,5.8,Future Systems +AI08355,Machine Learning Researcher,125964,USD,125964,EX,FT,Ireland,S,Brazil,0,"SQL, AWS, Mathematics, NLP",Bachelor,14,Media,2025-01-25,2025-02-18,2241,6.7,Cloud AI Solutions +AI08356,Data Engineer,234668,EUR,199468,EX,FL,France,M,China,50,"Linux, NLP, Kubernetes, AWS, Python",PhD,15,Finance,2024-07-17,2024-08-18,1680,9,TechCorp Inc +AI08357,Head of AI,72375,EUR,61519,MI,FL,France,S,Philippines,0,"GCP, Mathematics, SQL, Scala, Deep Learning",Master,4,Consulting,2024-04-07,2024-04-30,759,6.9,DataVision Ltd +AI08358,Data Engineer,199511,USD,199511,EX,CT,Finland,L,Finland,50,"Statistics, NLP, SQL, Kubernetes",Master,15,Consulting,2024-12-19,2025-01-15,523,7.5,AI Innovations +AI08359,AI Specialist,82707,USD,82707,MI,FL,Ireland,S,Ireland,100,"Spark, NLP, Python",Bachelor,4,Manufacturing,2024-07-03,2024-08-19,538,8.9,Predictive Systems +AI08360,AI Architect,49846,USD,49846,EN,CT,Ireland,S,Ireland,50,"Mathematics, Spark, Deep Learning, NLP",Bachelor,0,Transportation,2025-04-03,2025-05-02,1323,5.9,Future Systems +AI08361,AI Research Scientist,231076,SGD,300399,EX,CT,Singapore,S,Singapore,50,"Python, Spark, Statistics, Data Visualization",Bachelor,14,Technology,2024-08-15,2024-09-28,1757,6.8,Neural Networks Co +AI08362,Research Scientist,150796,USD,150796,SE,CT,Denmark,M,Denmark,50,"Python, Mathematics, Kubernetes, Hadoop",Bachelor,7,Telecommunications,2024-05-28,2024-07-20,2287,6.2,Quantum Computing Inc +AI08363,Machine Learning Researcher,116702,USD,116702,SE,CT,Ireland,S,Ireland,50,"NLP, TensorFlow, Java, Linux, R",Bachelor,8,Technology,2025-03-01,2025-03-19,1076,8.3,Advanced Robotics +AI08364,Computer Vision Engineer,127076,CHF,114368,EN,PT,Switzerland,L,Switzerland,0,"NLP, Java, Mathematics, Python",Associate,0,Technology,2024-10-18,2024-12-09,1891,7.8,Quantum Computing Inc +AI08365,Machine Learning Researcher,138133,JPY,15194630,SE,CT,Japan,S,Philippines,100,"MLOps, Python, Data Visualization",PhD,9,Finance,2024-06-12,2024-08-15,1650,8,Cognitive Computing +AI08366,Data Scientist,72519,USD,72519,EN,FT,Finland,M,Switzerland,50,"Java, PyTorch, Spark",Bachelor,1,Manufacturing,2024-11-10,2025-01-22,1763,7.2,Predictive Systems +AI08367,AI Software Engineer,202605,USD,202605,EX,FL,Israel,L,Israel,100,"R, Deep Learning, TensorFlow",Master,19,Energy,2025-04-07,2025-05-04,950,9.1,Neural Networks Co +AI08368,ML Ops Engineer,147327,USD,147327,EX,PT,Finland,L,Vietnam,50,"Scala, GCP, Hadoop, SQL",Associate,12,Transportation,2025-01-07,2025-03-02,1715,5.9,DataVision Ltd +AI08369,AI Specialist,35455,USD,35455,MI,CT,India,M,India,100,"Kubernetes, Deep Learning, Data Visualization, Spark",Associate,4,Media,2025-03-05,2025-05-09,810,8.6,Machine Intelligence Group +AI08370,ML Ops Engineer,85603,USD,85603,MI,FL,Ireland,M,Ireland,100,"Data Visualization, Scala, Spark, Computer Vision",Bachelor,4,Gaming,2025-03-22,2025-05-19,1079,7,Cloud AI Solutions +AI08371,Data Scientist,174323,USD,174323,EX,FL,Israel,M,Spain,100,"Deep Learning, Kubernetes, NLP, Spark",PhD,11,Technology,2025-01-05,2025-01-22,2480,8.9,Autonomous Tech +AI08372,Head of AI,138386,CHF,124547,SE,FL,Switzerland,S,Switzerland,100,"Tableau, Azure, Hadoop, R, NLP",Master,5,Retail,2025-01-21,2025-03-15,2000,8.5,Future Systems +AI08373,AI Specialist,86425,USD,86425,MI,PT,Finland,S,Australia,100,"Python, Statistics, Git",Bachelor,4,Manufacturing,2024-10-24,2024-12-04,1636,9.1,Future Systems +AI08374,AI Architect,79209,EUR,67328,MI,FT,France,M,France,50,"Java, MLOps, TensorFlow",PhD,2,Gaming,2024-05-03,2024-05-22,2438,9.2,Future Systems +AI08375,Robotics Engineer,93206,GBP,69905,MI,PT,United Kingdom,L,United Kingdom,0,"Linux, Mathematics, Deep Learning",Bachelor,2,Consulting,2025-03-19,2025-04-09,692,6.2,Cloud AI Solutions +AI08376,Head of AI,183144,EUR,155672,EX,PT,Germany,S,Germany,50,"Data Visualization, GCP, Spark, TensorFlow",Associate,11,Gaming,2024-04-03,2024-05-12,1696,5.9,Smart Analytics +AI08377,Computer Vision Engineer,115035,USD,115035,MI,FL,United States,L,Poland,50,"Computer Vision, Linux, Mathematics, Git, Kubernetes",PhD,3,Telecommunications,2024-10-05,2024-12-14,1758,8.1,Advanced Robotics +AI08378,Robotics Engineer,52046,USD,52046,EN,PT,Ireland,M,Ireland,0,"Python, Java, Git, Linux, GCP",Master,0,Consulting,2024-04-21,2024-06-18,2451,7.5,Advanced Robotics +AI08379,Data Engineer,27042,USD,27042,MI,FT,India,M,India,0,"Scala, NLP, Java, Hadoop",Associate,3,Retail,2024-08-29,2024-10-21,1230,9.1,Quantum Computing Inc +AI08380,Principal Data Scientist,69140,EUR,58769,MI,FL,Germany,S,Philippines,100,"Java, Computer Vision, R",Associate,4,Education,2024-11-05,2024-11-23,2300,9.2,AI Innovations +AI08381,Principal Data Scientist,54144,USD,54144,SE,FL,China,M,South Korea,50,"Hadoop, Java, AWS, R, MLOps",Bachelor,5,Education,2024-04-07,2024-05-15,1069,8,Digital Transformation LLC +AI08382,Autonomous Systems Engineer,102140,GBP,76605,MI,PT,United Kingdom,M,United Kingdom,50,"Azure, Linux, Deep Learning",PhD,3,Real Estate,2024-09-02,2024-10-26,920,6.4,Smart Analytics +AI08383,Machine Learning Researcher,159981,EUR,135984,SE,PT,Germany,L,Germany,100,"Python, Computer Vision, Deep Learning",Associate,9,Retail,2024-01-16,2024-02-17,1058,7.1,DeepTech Ventures +AI08384,Research Scientist,52315,USD,52315,EN,FT,South Korea,M,South Korea,50,"Hadoop, SQL, Linux, Data Visualization, GCP",PhD,1,Media,2024-05-07,2024-06-17,944,6.2,Quantum Computing Inc +AI08385,AI Research Scientist,174231,AUD,235212,SE,PT,Australia,L,Australia,50,"NLP, Scala, Java, Linux",Associate,7,Manufacturing,2025-02-17,2025-03-14,2270,9.9,Cognitive Computing +AI08386,AI Specialist,97169,GBP,72877,MI,CT,United Kingdom,L,United Kingdom,0,"MLOps, AWS, Java, SQL, Git",Master,3,Government,2024-09-24,2024-10-09,2310,6.1,Predictive Systems +AI08387,Autonomous Systems Engineer,143744,CAD,179680,SE,PT,Canada,M,Poland,0,"Linux, Statistics, Deep Learning, MLOps",Bachelor,9,Energy,2024-12-17,2025-02-03,1811,5.8,Smart Analytics +AI08388,Data Scientist,112243,USD,112243,MI,CT,United States,S,Hungary,100,"Data Visualization, Scala, SQL, AWS",Master,2,Finance,2024-05-28,2024-07-18,978,7.8,Cognitive Computing +AI08389,ML Ops Engineer,127387,USD,127387,MI,FL,Denmark,M,China,0,"Deep Learning, PyTorch, MLOps",Bachelor,3,Technology,2025-04-02,2025-06-08,2393,7.7,Autonomous Tech +AI08390,Machine Learning Researcher,131304,EUR,111608,SE,PT,Austria,M,Austria,0,"SQL, PyTorch, GCP, Hadoop",PhD,6,Consulting,2024-12-16,2025-01-24,1299,8.4,Cognitive Computing +AI08391,Machine Learning Engineer,71777,AUD,96899,EN,FL,Australia,L,Ireland,50,"Java, R, Python, Azure, Mathematics",Master,0,Media,2025-01-03,2025-02-16,1167,8.2,Cognitive Computing +AI08392,Machine Learning Researcher,116676,SGD,151679,SE,PT,Singapore,S,Singapore,100,"Kubernetes, Hadoop, Java",Bachelor,7,Finance,2024-03-06,2024-04-09,764,7.6,AI Innovations +AI08393,AI Consultant,126226,GBP,94670,SE,FL,United Kingdom,S,Mexico,50,"Spark, Java, PyTorch, GCP",Master,6,Technology,2024-10-02,2024-12-11,901,9.1,Advanced Robotics +AI08394,ML Ops Engineer,82894,AUD,111907,MI,CT,Australia,S,Australia,100,"R, GCP, Computer Vision, Spark, SQL",Master,4,Government,2025-02-04,2025-02-18,624,7.8,TechCorp Inc +AI08395,Machine Learning Researcher,38746,USD,38746,EN,FT,China,L,South Korea,0,"Hadoop, Statistics, SQL, Tableau",Bachelor,0,Energy,2025-01-27,2025-02-26,1600,8.4,Quantum Computing Inc +AI08396,AI Consultant,92661,USD,92661,MI,FT,Norway,S,Japan,100,"SQL, Python, Git, Kubernetes",Master,2,Government,2024-04-26,2024-06-25,511,9.4,TechCorp Inc +AI08397,AI Research Scientist,62143,USD,62143,MI,PT,South Korea,M,Czech Republic,100,"Python, TensorFlow, NLP",Associate,4,Media,2025-01-31,2025-02-23,854,5.1,Autonomous Tech +AI08398,AI Software Engineer,176385,GBP,132289,EX,PT,United Kingdom,S,United Kingdom,100,"SQL, Scala, Azure, Computer Vision, GCP",Bachelor,14,Real Estate,2025-02-06,2025-02-21,2442,5.3,Machine Intelligence Group +AI08399,AI Software Engineer,81358,EUR,69154,MI,FL,France,M,France,0,"SQL, Docker, Data Visualization, Hadoop, Deep Learning",Associate,3,Media,2024-04-06,2024-04-28,836,5.3,DeepTech Ventures +AI08400,Robotics Engineer,78489,USD,78489,MI,FL,Israel,M,Israel,0,"Docker, AWS, NLP",PhD,2,Telecommunications,2025-04-02,2025-05-04,712,9,Advanced Robotics +AI08401,Autonomous Systems Engineer,157109,EUR,133543,SE,CT,Germany,L,Portugal,100,"Java, MLOps, R, NLP",PhD,5,Automotive,2025-01-12,2025-01-26,1530,8,Smart Analytics +AI08402,AI Software Engineer,154305,AUD,208312,EX,FL,Australia,S,Ghana,0,"TensorFlow, R, Statistics",Master,17,Telecommunications,2025-01-15,2025-02-19,2485,8,TechCorp Inc +AI08403,Machine Learning Engineer,61309,AUD,82767,EN,PT,Australia,S,India,50,"SQL, Python, Deep Learning, AWS, Statistics",Associate,0,Real Estate,2025-02-06,2025-03-11,820,6.9,DataVision Ltd +AI08404,Data Scientist,189613,AUD,255978,EX,FT,Australia,M,Australia,50,"Java, R, Hadoop",Associate,13,Media,2024-10-29,2024-11-22,1473,9.1,Cloud AI Solutions +AI08405,AI Product Manager,214403,USD,214403,EX,PT,United States,S,United States,0,"Docker, Linux, Azure, Statistics, Tableau",Associate,18,Retail,2025-03-18,2025-04-05,1843,6.3,TechCorp Inc +AI08406,AI Consultant,133222,EUR,113239,SE,PT,Austria,M,Argentina,0,"Scala, PyTorch, GCP, Spark, Computer Vision",Master,7,Transportation,2024-07-03,2024-08-09,1185,8.9,DataVision Ltd +AI08407,Data Engineer,62909,USD,62909,EN,PT,Israel,L,Israel,100,"Tableau, Java, Scala, Data Visualization, TensorFlow",PhD,1,Government,2024-08-19,2024-10-13,2330,5.2,DeepTech Ventures +AI08408,AI Product Manager,19343,USD,19343,EN,FT,India,S,India,50,"GCP, Git, PyTorch",Associate,1,Transportation,2025-01-05,2025-02-08,2174,9.3,Quantum Computing Inc +AI08409,Robotics Engineer,222547,USD,222547,EX,PT,Ireland,S,Ireland,0,"Linux, PyTorch, Data Visualization",Bachelor,14,Manufacturing,2024-02-19,2024-03-09,1579,5.6,Smart Analytics +AI08410,AI Consultant,234130,JPY,25754300,EX,FT,Japan,S,Japan,100,"Linux, Azure, MLOps, Git",Bachelor,11,Real Estate,2025-02-08,2025-02-23,1013,5.8,Cognitive Computing +AI08411,Deep Learning Engineer,215309,USD,215309,EX,CT,Finland,S,Finland,100,"Computer Vision, MLOps, GCP",Master,13,Media,2024-06-30,2024-09-09,1203,7.3,Cognitive Computing +AI08412,AI Product Manager,72372,USD,72372,MI,CT,Israel,S,Chile,50,"Scala, SQL, Spark, GCP",PhD,4,Technology,2024-04-13,2024-05-14,764,8.2,Smart Analytics +AI08413,Deep Learning Engineer,167429,AUD,226029,EX,CT,Australia,L,Austria,100,"SQL, AWS, Scala, GCP, Azure",Bachelor,11,Transportation,2024-04-17,2024-05-05,1020,6.5,Algorithmic Solutions +AI08414,AI Consultant,171432,USD,171432,EX,PT,Israel,L,Israel,50,"Spark, PyTorch, Java, TensorFlow",Bachelor,16,Energy,2024-06-06,2024-07-18,1921,6.1,Predictive Systems +AI08415,AI Research Scientist,162301,USD,162301,SE,FL,Sweden,L,United Kingdom,50,"SQL, Hadoop, Azure",Master,6,Telecommunications,2025-02-03,2025-04-02,1728,6.4,Cognitive Computing +AI08416,Computer Vision Engineer,106745,USD,106745,MI,CT,Sweden,M,Luxembourg,50,"Python, GCP, Azure, SQL, TensorFlow",Bachelor,3,Healthcare,2024-06-27,2024-07-23,2005,9.2,Advanced Robotics +AI08417,AI Specialist,169009,EUR,143658,EX,FL,Netherlands,L,Netherlands,0,"Computer Vision, PyTorch, Tableau",PhD,18,Government,2024-03-24,2024-05-26,1702,6.2,Algorithmic Solutions +AI08418,AI Architect,233941,SGD,304123,EX,PT,Singapore,M,Italy,50,"MLOps, SQL, AWS, NLP, Data Visualization",Bachelor,15,Energy,2024-06-13,2024-07-22,1480,6.3,Machine Intelligence Group +AI08419,AI Software Engineer,179620,EUR,152677,EX,PT,Austria,L,Sweden,50,"Python, Kubernetes, Statistics, AWS",Master,13,Technology,2024-01-28,2024-03-11,1610,9.6,Quantum Computing Inc +AI08420,ML Ops Engineer,128589,JPY,14144790,SE,PT,Japan,S,Japan,50,"PyTorch, TensorFlow, Docker",PhD,6,Gaming,2024-10-13,2024-11-08,2114,9,AI Innovations +AI08421,Deep Learning Engineer,76779,EUR,65262,EN,PT,Netherlands,L,Netherlands,0,"Mathematics, PyTorch, Scala",Associate,1,Retail,2024-12-16,2025-01-12,2438,7,Neural Networks Co +AI08422,AI Specialist,114807,EUR,97586,SE,FL,France,S,Norway,100,"Azure, Java, Git",Master,6,Automotive,2024-06-06,2024-07-31,1526,6.6,DataVision Ltd +AI08423,Autonomous Systems Engineer,126904,AUD,171320,SE,PT,Australia,S,Australia,50,"Scala, Kubernetes, R, GCP, Hadoop",Master,8,Consulting,2024-12-05,2025-01-11,2035,6.8,Neural Networks Co +AI08424,ML Ops Engineer,23823,USD,23823,EN,CT,India,L,India,50,"GCP, Python, TensorFlow, Deep Learning",PhD,0,Media,2024-08-10,2024-09-06,1222,6.2,Cloud AI Solutions +AI08425,Robotics Engineer,91085,USD,91085,MI,FL,United States,S,United States,50,"Computer Vision, Statistics, NLP, Kubernetes",Master,4,Consulting,2025-03-09,2025-05-09,1623,9.9,Cloud AI Solutions +AI08426,AI Software Engineer,123889,EUR,105306,SE,CT,Netherlands,M,Netherlands,0,"Python, Hadoop, R, Linux",Associate,6,Retail,2024-02-10,2024-04-04,1683,8.9,Quantum Computing Inc +AI08427,Machine Learning Engineer,116702,USD,116702,SE,CT,South Korea,M,South Korea,50,"Hadoop, Tableau, AWS, PyTorch",Master,9,Technology,2024-07-14,2024-09-04,1427,6,Predictive Systems +AI08428,Research Scientist,114453,USD,114453,MI,PT,Sweden,L,Argentina,0,"Spark, SQL, Azure, MLOps",PhD,2,Government,2024-06-06,2024-08-04,2473,5.2,TechCorp Inc +AI08429,Data Analyst,127753,GBP,95815,MI,FT,United Kingdom,L,United Kingdom,50,"TensorFlow, Docker, Tableau, Java",Master,4,Technology,2025-01-13,2025-03-14,665,5.1,Smart Analytics +AI08430,AI Research Scientist,279320,SGD,363116,EX,FT,Singapore,L,Turkey,50,"Computer Vision, MLOps, Statistics",Associate,14,Telecommunications,2024-02-28,2024-04-01,1660,8.8,DeepTech Ventures +AI08431,Computer Vision Engineer,193375,EUR,164369,EX,FT,Germany,M,Czech Republic,50,"Tableau, Python, NLP, Spark, Computer Vision",Master,10,Education,2024-06-21,2024-07-06,2499,9.3,Machine Intelligence Group +AI08432,AI Consultant,199737,CHF,179763,SE,FT,Switzerland,M,Switzerland,0,"Java, Scala, MLOps",Master,8,Telecommunications,2025-01-28,2025-02-27,2100,7.8,Cloud AI Solutions +AI08433,AI Software Engineer,53228,USD,53228,EN,CT,Finland,S,Finland,0,"TensorFlow, SQL, Data Visualization, Mathematics",Master,0,Energy,2024-03-06,2024-05-13,1656,9.8,Smart Analytics +AI08434,Autonomous Systems Engineer,124669,EUR,105969,SE,CT,Austria,L,Austria,100,"Deep Learning, Python, Linux",Master,6,Real Estate,2025-02-09,2025-03-21,1166,8.1,Algorithmic Solutions +AI08435,AI Research Scientist,139094,USD,139094,SE,CT,Norway,S,Singapore,50,"SQL, Docker, PyTorch, Hadoop, Scala",Bachelor,5,Education,2024-10-30,2024-11-20,842,9.6,Algorithmic Solutions +AI08436,AI Research Scientist,103028,CHF,92725,EN,FL,Switzerland,L,Portugal,100,"Computer Vision, Tableau, Scala, Deep Learning, Azure",Associate,1,Retail,2024-10-21,2024-11-06,1091,8,Advanced Robotics +AI08437,Data Analyst,140713,USD,140713,SE,PT,Ireland,L,Sweden,50,"Data Visualization, Python, TensorFlow",Associate,5,Automotive,2024-12-10,2025-01-27,2280,9,Cognitive Computing +AI08438,AI Software Engineer,93762,USD,93762,EN,CT,Norway,M,Norway,100,"GCP, Python, Deep Learning, TensorFlow",PhD,1,Education,2025-01-05,2025-03-09,1924,9.2,AI Innovations +AI08439,Machine Learning Engineer,60042,USD,60042,EN,CT,United States,M,United States,50,"Scala, Azure, Tableau",Associate,0,Automotive,2024-06-20,2024-08-16,905,5.2,Neural Networks Co +AI08440,Deep Learning Engineer,125462,USD,125462,SE,FL,Israel,M,Norway,0,"Mathematics, SQL, Data Visualization, Linux",Master,8,Manufacturing,2024-09-18,2024-10-20,1182,9.1,Future Systems +AI08441,Autonomous Systems Engineer,79766,EUR,67801,MI,PT,Germany,M,Germany,0,"Spark, Hadoop, Tableau",Associate,4,Automotive,2025-02-13,2025-03-29,769,7.3,Algorithmic Solutions +AI08442,AI Architect,63995,USD,63995,SE,CT,China,S,China,50,"Java, SQL, Kubernetes, AWS",Associate,9,Energy,2024-05-05,2024-07-09,1467,8,Cognitive Computing +AI08443,Deep Learning Engineer,67575,EUR,57439,EN,CT,France,S,France,0,"R, Scala, GCP, Linux",Bachelor,0,Real Estate,2024-12-28,2025-02-15,2065,9.8,DeepTech Ventures +AI08444,Machine Learning Engineer,180825,GBP,135619,SE,FT,United Kingdom,L,Russia,0,"SQL, Scala, NLP, Statistics, PyTorch",Master,5,Healthcare,2024-02-07,2024-03-17,2210,7.4,Neural Networks Co +AI08445,Autonomous Systems Engineer,46588,USD,46588,SE,CT,China,S,China,0,"Hadoop, Mathematics, NLP, AWS",Bachelor,7,Government,2024-12-04,2025-01-10,1897,8.6,Machine Intelligence Group +AI08446,AI Specialist,70840,USD,70840,EN,FT,Sweden,S,Sweden,0,"SQL, Data Visualization, Linux",Master,0,Telecommunications,2024-06-08,2024-07-21,2485,9,Predictive Systems +AI08447,AI Research Scientist,40656,USD,40656,MI,PT,China,M,China,50,"Python, Mathematics, GCP, AWS",PhD,3,Retail,2025-01-17,2025-03-15,1534,5.3,Advanced Robotics +AI08448,Research Scientist,50149,EUR,42627,EN,PT,Austria,S,Austria,50,"Data Visualization, AWS, SQL, Statistics",Associate,0,Finance,2024-10-15,2024-12-12,1516,6.1,TechCorp Inc +AI08449,Research Scientist,128622,AUD,173640,SE,FL,Australia,M,Australia,100,"Deep Learning, Scala, PyTorch, Mathematics, GCP",Associate,9,Education,2024-12-05,2025-01-22,1434,7.4,Cloud AI Solutions +AI08450,Machine Learning Engineer,100866,GBP,75650,MI,FL,United Kingdom,S,United Kingdom,0,"Java, Scala, Linux, Deep Learning",Bachelor,4,Telecommunications,2024-03-18,2024-04-26,1156,5.5,Quantum Computing Inc +AI08451,AI Architect,98292,GBP,73719,MI,FT,United Kingdom,L,United Kingdom,0,"Scala, Hadoop, Statistics, TensorFlow",Associate,2,Automotive,2024-07-18,2024-09-04,2349,8.4,Quantum Computing Inc +AI08452,Machine Learning Engineer,77362,AUD,104439,MI,FT,Australia,M,Australia,50,"SQL, Linux, Java, PyTorch",Bachelor,4,Gaming,2025-03-18,2025-04-24,834,7.9,DataVision Ltd +AI08453,Data Analyst,78850,AUD,106448,MI,FT,Australia,M,Australia,100,"Tableau, GCP, TensorFlow, PyTorch, Azure",Associate,2,Government,2025-03-06,2025-05-18,1560,5.7,Predictive Systems +AI08454,Computer Vision Engineer,87737,GBP,65803,EN,FT,United Kingdom,L,United Kingdom,0,"R, AWS, NLP, MLOps, Spark",PhD,1,Education,2025-02-09,2025-04-16,552,8.6,Predictive Systems +AI08455,AI Architect,91614,USD,91614,MI,FL,Ireland,L,Ireland,0,"Python, NLP, Kubernetes, Computer Vision",Associate,4,Technology,2024-12-21,2025-02-12,1349,5.5,AI Innovations +AI08456,Computer Vision Engineer,186919,USD,186919,EX,CT,Norway,S,Norway,0,"Java, Linux, SQL, Deep Learning",Bachelor,14,Healthcare,2024-05-16,2024-07-05,1629,9.9,Quantum Computing Inc +AI08457,Data Scientist,70265,CAD,87831,EN,PT,Canada,M,Estonia,50,"Kubernetes, SQL, Tableau, TensorFlow, Mathematics",Bachelor,0,Transportation,2024-07-23,2024-08-07,1608,7.5,AI Innovations +AI08458,Autonomous Systems Engineer,45732,USD,45732,EN,FT,Finland,S,Finland,100,"Kubernetes, SQL, Data Visualization",PhD,1,Energy,2025-02-23,2025-04-05,1157,7.4,DataVision Ltd +AI08459,Machine Learning Researcher,36182,USD,36182,SE,FT,India,M,India,100,"NLP, Data Visualization, PyTorch, MLOps, TensorFlow",Master,6,Automotive,2024-12-03,2025-01-24,2302,7.7,Future Systems +AI08460,AI Software Engineer,64887,EUR,55154,MI,PT,Austria,S,Austria,50,"Linux, Tableau, PyTorch",Associate,4,Consulting,2024-02-26,2024-04-09,1763,7.4,Predictive Systems +AI08461,AI Product Manager,309181,USD,309181,EX,FT,Denmark,L,Estonia,50,"GCP, Python, Spark",Master,15,Government,2025-01-01,2025-02-10,1074,7.6,Smart Analytics +AI08462,Data Analyst,93055,USD,93055,MI,FT,United States,M,United States,100,"Statistics, Kubernetes, Java, GCP, Scala",Master,3,Retail,2024-04-04,2024-05-23,1929,7.2,Cloud AI Solutions +AI08463,Data Analyst,186453,CHF,167808,SE,FL,Switzerland,M,Sweden,100,"Scala, Hadoop, Java, Mathematics, Statistics",Associate,6,Energy,2025-04-06,2025-04-26,567,6.9,DataVision Ltd +AI08464,Computer Vision Engineer,83203,USD,83203,EN,FT,United States,M,United States,100,"SQL, PyTorch, Data Visualization",Associate,0,Gaming,2024-01-27,2024-02-14,1842,6.9,DataVision Ltd +AI08465,Machine Learning Researcher,188584,EUR,160296,EX,FT,Germany,M,Germany,50,"SQL, Kubernetes, Spark, Hadoop",Bachelor,17,Technology,2025-02-16,2025-03-29,1547,9.3,Algorithmic Solutions +AI08466,Data Analyst,121863,USD,121863,MI,FL,Norway,S,Norway,100,"AWS, Linux, Scala",Associate,4,Real Estate,2024-05-16,2024-06-06,2163,9.1,AI Innovations +AI08467,Computer Vision Engineer,53043,CAD,66304,EN,CT,Canada,M,Canada,0,"SQL, Tableau, Java, Kubernetes",PhD,0,Consulting,2024-10-18,2024-11-11,1508,9.8,Predictive Systems +AI08468,Deep Learning Engineer,105766,USD,105766,MI,FL,Norway,S,Norway,50,"TensorFlow, SQL, Scala, Azure",Master,2,Retail,2024-04-03,2024-04-28,1624,9.9,Quantum Computing Inc +AI08469,AI Specialist,127422,EUR,108309,SE,FT,Austria,S,Austria,0,"Statistics, Hadoop, Computer Vision",PhD,6,Healthcare,2024-08-11,2024-10-13,1126,7.4,Future Systems +AI08470,NLP Engineer,274301,CHF,246871,EX,PT,Switzerland,M,Switzerland,0,"Computer Vision, Mathematics, NLP",Bachelor,13,Technology,2024-08-25,2024-09-15,987,5.4,Quantum Computing Inc +AI08471,Machine Learning Engineer,107589,USD,107589,SE,FL,Sweden,S,Sweden,0,"Linux, Docker, Data Visualization, Git",Master,7,Real Estate,2024-07-31,2024-09-23,568,7.7,Quantum Computing Inc +AI08472,ML Ops Engineer,68293,EUR,58049,EN,PT,France,M,France,0,"Git, Scala, Deep Learning, R, Azure",PhD,1,Education,2024-05-15,2024-06-24,2321,7.3,Future Systems +AI08473,Computer Vision Engineer,257050,JPY,28275500,EX,FT,Japan,M,Japan,100,"Deep Learning, Java, Mathematics, Hadoop, PyTorch",Associate,17,Finance,2025-04-27,2025-05-23,2319,9.9,Predictive Systems +AI08474,Deep Learning Engineer,154708,USD,154708,EX,FL,Sweden,M,Hungary,50,"PyTorch, GCP, SQL",Master,13,Healthcare,2024-09-03,2024-09-25,2285,6.8,AI Innovations +AI08475,Machine Learning Researcher,80788,USD,80788,MI,FL,Sweden,S,Sweden,0,"Python, Deep Learning, Docker",PhD,3,Transportation,2024-07-25,2024-09-02,1268,6.9,Digital Transformation LLC +AI08476,Head of AI,117314,USD,117314,SE,FT,Finland,L,Finland,0,"Data Visualization, Python, SQL, Git",Associate,7,Technology,2024-07-05,2024-08-01,1317,5.2,Advanced Robotics +AI08477,Machine Learning Researcher,117690,AUD,158882,SE,CT,Australia,M,Australia,0,"PyTorch, Python, Git",PhD,8,Consulting,2025-04-13,2025-05-08,989,5.6,TechCorp Inc +AI08478,AI Architect,214411,USD,214411,EX,PT,United States,L,United States,50,"NLP, Java, Git, Kubernetes",PhD,11,Finance,2024-11-04,2024-12-13,2395,8.6,Cloud AI Solutions +AI08479,Machine Learning Researcher,155700,USD,155700,SE,PT,United States,S,United States,0,"Python, Statistics, Docker",Bachelor,7,Healthcare,2024-10-15,2024-12-27,1971,9.8,DeepTech Ventures +AI08480,Autonomous Systems Engineer,111686,EUR,94933,SE,CT,Netherlands,M,Colombia,50,"Docker, MLOps, AWS, Deep Learning",Master,7,Finance,2024-08-05,2024-10-04,1018,9.4,Algorithmic Solutions +AI08481,AI Research Scientist,65656,AUD,88636,MI,PT,Australia,S,Malaysia,50,"Computer Vision, SQL, PyTorch, Mathematics, AWS",Master,4,Finance,2024-04-29,2024-07-11,2396,5.1,DataVision Ltd +AI08482,Principal Data Scientist,85926,USD,85926,EX,CT,India,M,India,0,"Data Visualization, R, Java, MLOps",PhD,10,Automotive,2025-02-28,2025-05-12,906,7.2,AI Innovations +AI08483,AI Research Scientist,130166,GBP,97625,EX,FL,United Kingdom,S,United Kingdom,0,"Mathematics, Deep Learning, Hadoop, Docker, Java",Master,11,Education,2024-01-29,2024-03-26,1014,5.4,Machine Intelligence Group +AI08484,Autonomous Systems Engineer,132900,USD,132900,MI,FT,Denmark,L,Denmark,100,"Git, SQL, Python, NLP, Deep Learning",Bachelor,4,Finance,2024-11-06,2024-12-13,660,7.8,DeepTech Ventures +AI08485,Deep Learning Engineer,156100,EUR,132685,SE,PT,Netherlands,L,Netherlands,50,"Python, Java, MLOps",Associate,7,Technology,2024-02-12,2024-03-28,2028,5.2,DataVision Ltd +AI08486,Data Engineer,133627,USD,133627,SE,FT,Norway,M,Norway,100,"Azure, SQL, Kubernetes, Computer Vision, Statistics",Bachelor,9,Education,2024-09-26,2024-11-10,1712,6.4,Cognitive Computing +AI08487,AI Architect,88478,EUR,75206,SE,FT,France,S,France,100,"Hadoop, Linux, AWS, PyTorch, MLOps",Associate,5,Transportation,2024-04-07,2024-06-15,1496,7.5,Smart Analytics +AI08488,Machine Learning Engineer,212608,EUR,180717,EX,PT,Austria,M,Austria,50,"Azure, Computer Vision, Git, AWS, Docker",PhD,12,Telecommunications,2024-07-06,2024-08-09,519,6.5,Quantum Computing Inc +AI08489,AI Architect,58073,USD,58073,EN,FT,Israel,S,Israel,50,"Java, TensorFlow, Mathematics",Master,0,Media,2024-12-23,2025-02-28,903,9.7,DeepTech Ventures +AI08490,AI Consultant,91448,USD,91448,EN,PT,Ireland,L,Czech Republic,50,"PyTorch, MLOps, Spark",PhD,1,Automotive,2025-01-17,2025-02-16,1090,5.6,Digital Transformation LLC +AI08491,Head of AI,95900,USD,95900,MI,PT,Sweden,L,Sweden,0,"TensorFlow, Tableau, R",PhD,4,Transportation,2024-08-14,2024-09-11,647,7.6,Future Systems +AI08492,Principal Data Scientist,179096,AUD,241780,EX,FT,Australia,M,Australia,100,"Spark, SQL, PyTorch, Deep Learning",Associate,18,Transportation,2025-01-25,2025-04-08,1108,6.7,DeepTech Ventures +AI08493,AI Product Manager,59907,USD,59907,EN,FT,Israel,M,Israel,50,"Mathematics, AWS, MLOps, Java",PhD,0,Government,2024-06-23,2024-07-31,1306,9.4,DeepTech Ventures +AI08494,Research Scientist,67233,AUD,90765,EN,FT,Australia,L,Australia,0,"Python, Java, Mathematics, Spark",PhD,1,Automotive,2024-03-15,2024-05-25,943,5.8,Cognitive Computing +AI08495,Data Engineer,203674,CHF,183307,SE,FL,Switzerland,M,Switzerland,50,"Scala, Spark, Azure, Tableau, Kubernetes",Bachelor,9,Real Estate,2024-11-29,2025-01-07,2130,6,Neural Networks Co +AI08496,AI Software Engineer,113013,EUR,96061,SE,FL,Austria,M,Colombia,50,"Python, AWS, Data Visualization, NLP",Bachelor,7,Retail,2025-03-26,2025-05-24,1018,9.9,TechCorp Inc +AI08497,AI Architect,239650,AUD,323528,EX,PT,Australia,M,Australia,50,"Scala, Computer Vision, SQL, Data Visualization",Bachelor,17,Transportation,2024-03-16,2024-05-19,1926,9.1,Neural Networks Co +AI08498,Computer Vision Engineer,237855,CAD,297319,EX,CT,Canada,L,Japan,50,"NLP, Hadoop, MLOps, Scala",PhD,14,Healthcare,2025-01-09,2025-03-17,2032,8.2,DataVision Ltd +AI08499,Machine Learning Researcher,90048,EUR,76541,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Docker, TensorFlow, Scala, AWS",Bachelor,3,Transportation,2025-03-14,2025-05-14,1034,8.4,AI Innovations +AI08500,Robotics Engineer,103593,USD,103593,SE,PT,South Korea,S,South Korea,0,"Spark, Scala, Kubernetes, Hadoop, Java",Master,5,Retail,2024-08-31,2024-09-30,1593,10,Neural Networks Co +AI08501,AI Software Engineer,118005,SGD,153407,SE,PT,Singapore,S,Singapore,0,"Azure, Scala, Deep Learning",Master,9,Media,2024-11-18,2025-01-09,1227,7.1,Predictive Systems +AI08502,Machine Learning Engineer,102645,CHF,92381,EN,FT,Switzerland,M,Switzerland,0,"Hadoop, Kubernetes, Python, Linux",Associate,1,Transportation,2024-09-27,2024-11-30,1269,6,Predictive Systems +AI08503,Research Scientist,213544,AUD,288284,EX,FL,Australia,S,Australia,0,"PyTorch, SQL, MLOps, Spark",Master,16,Telecommunications,2024-05-22,2024-06-21,2216,8.2,Autonomous Tech +AI08504,Autonomous Systems Engineer,99231,EUR,84346,MI,FT,Germany,S,Germany,100,"Azure, SQL, Mathematics, Docker, AWS",Bachelor,2,Finance,2025-03-08,2025-05-04,1765,6.3,Neural Networks Co +AI08505,AI Specialist,189940,CAD,237425,EX,FL,Canada,M,Canada,50,"Azure, Hadoop, SQL, PyTorch",Bachelor,15,Energy,2024-09-09,2024-10-28,949,6.5,Quantum Computing Inc +AI08506,Head of AI,97410,USD,97410,EN,FT,Denmark,M,Denmark,0,"Python, TensorFlow, Linux, PyTorch, Deep Learning",Associate,0,Telecommunications,2025-01-18,2025-02-13,678,8.7,TechCorp Inc +AI08507,AI Specialist,115419,GBP,86564,SE,PT,United Kingdom,M,United Kingdom,0,"Python, Docker, Mathematics",PhD,9,Government,2024-11-06,2024-12-15,2448,9.3,Autonomous Tech +AI08508,Deep Learning Engineer,55421,USD,55421,EN,PT,South Korea,M,South Korea,100,"Python, R, Mathematics, TensorFlow",Bachelor,1,Education,2024-07-09,2024-08-01,2257,8.5,DeepTech Ventures +AI08509,Principal Data Scientist,174114,EUR,147997,SE,FL,Germany,L,Germany,100,"GCP, Python, MLOps",Associate,9,Education,2024-09-02,2024-10-05,1057,7.6,Cloud AI Solutions +AI08510,Data Analyst,223978,USD,223978,EX,PT,Sweden,M,Sweden,0,"R, TensorFlow, Scala, Linux, Mathematics",Master,14,Government,2024-09-15,2024-10-23,1841,7.9,Cloud AI Solutions +AI08511,Principal Data Scientist,239199,GBP,179399,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, Python, Data Visualization",PhD,16,Government,2024-09-24,2024-10-28,2389,6.4,Predictive Systems +AI08512,AI Research Scientist,82844,CHF,74560,EN,FT,Switzerland,M,United Kingdom,0,"Data Visualization, Azure, GCP, Java",PhD,1,Media,2024-06-12,2024-08-18,2214,7.1,Neural Networks Co +AI08513,AI Specialist,122977,USD,122977,SE,PT,Finland,L,Finland,50,"Python, Azure, Spark",Associate,9,Government,2025-02-09,2025-04-12,2372,7.1,Algorithmic Solutions +AI08514,Deep Learning Engineer,113326,USD,113326,MI,PT,Denmark,M,Denmark,50,"Kubernetes, Scala, Git, Azure, AWS",Associate,4,Government,2024-04-16,2024-06-18,850,5,Autonomous Tech +AI08515,Research Scientist,90965,CAD,113706,MI,CT,Canada,S,Turkey,0,"Linux, Kubernetes, Python, TensorFlow, Scala",Associate,3,Education,2025-04-19,2025-05-13,1326,6,Cloud AI Solutions +AI08516,Data Engineer,134158,USD,134158,SE,FL,Finland,L,Finland,50,"Java, SQL, Kubernetes, Hadoop",Associate,5,Media,2024-02-28,2024-04-26,670,5.9,Advanced Robotics +AI08517,Data Engineer,62279,CAD,77849,EN,PT,Canada,M,Canada,50,"Statistics, Python, Computer Vision, Spark, Kubernetes",Master,0,Retail,2024-07-16,2024-08-03,2107,6.4,Neural Networks Co +AI08518,Principal Data Scientist,201716,USD,201716,SE,CT,United States,L,Germany,100,"Spark, NLP, GCP, Tableau",Associate,6,Healthcare,2024-08-06,2024-08-29,572,9.8,AI Innovations +AI08519,AI Software Engineer,165043,USD,165043,EX,PT,Finland,L,Finland,50,"NLP, SQL, Java, GCP",Master,13,Automotive,2024-02-15,2024-03-06,1770,9.4,Predictive Systems +AI08520,NLP Engineer,95834,USD,95834,MI,FT,Denmark,M,Denmark,100,"Python, TensorFlow, Statistics, Azure, GCP",PhD,4,Healthcare,2025-01-03,2025-03-06,1278,7.7,Neural Networks Co +AI08521,AI Architect,131818,USD,131818,SE,FT,South Korea,L,Brazil,0,"Kubernetes, Python, Azure, TensorFlow",Master,5,Energy,2025-03-01,2025-04-03,1547,7,Digital Transformation LLC +AI08522,Robotics Engineer,86510,USD,86510,MI,FT,Denmark,S,South Africa,0,"Deep Learning, Azure, Python",Bachelor,2,Retail,2024-07-23,2024-08-19,2077,6.9,TechCorp Inc +AI08523,AI Software Engineer,83243,USD,83243,EN,PT,Israel,L,United Kingdom,50,"Python, Computer Vision, Linux, TensorFlow, Kubernetes",PhD,1,Gaming,2025-02-25,2025-03-11,1789,5.2,Future Systems +AI08524,AI Software Engineer,76490,CHF,68841,EN,PT,Switzerland,M,United Kingdom,50,"Scala, GCP, Python, Statistics, MLOps",Master,0,Education,2024-01-20,2024-02-08,1601,7.4,Advanced Robotics +AI08525,Head of AI,239503,EUR,203578,EX,CT,Germany,M,Germany,0,"Kubernetes, Hadoop, GCP, TensorFlow, Python",PhD,12,Finance,2025-03-04,2025-03-20,717,9.5,Machine Intelligence Group +AI08526,AI Specialist,159699,AUD,215594,SE,CT,Australia,L,Australia,50,"Scala, Tableau, Azure, Docker",PhD,5,Technology,2024-07-14,2024-08-31,1429,8.8,DeepTech Ventures +AI08527,Machine Learning Engineer,127190,SGD,165347,MI,CT,Singapore,L,Portugal,100,"Linux, NLP, Docker, Hadoop, Computer Vision",Master,2,Technology,2024-06-21,2024-08-27,1630,8.3,Digital Transformation LLC +AI08528,Autonomous Systems Engineer,61030,SGD,79339,EN,FT,Singapore,M,Singapore,50,"Statistics, TensorFlow, Scala, Python",Master,1,Automotive,2024-03-02,2024-04-16,2268,8.9,Future Systems +AI08529,Computer Vision Engineer,30719,USD,30719,MI,FT,India,S,Switzerland,0,"Python, Linux, MLOps, Statistics, Git",Master,2,Healthcare,2024-06-08,2024-06-22,1519,5.4,Neural Networks Co +AI08530,Robotics Engineer,322323,USD,322323,EX,FL,Denmark,M,Denmark,100,"PyTorch, Mathematics, Deep Learning",Bachelor,15,Government,2025-04-11,2025-06-10,1717,7.2,Predictive Systems +AI08531,Data Engineer,239858,CHF,215872,SE,FL,Switzerland,L,Switzerland,0,"TensorFlow, Docker, Linux",PhD,9,Media,2024-01-16,2024-02-12,850,6.6,Smart Analytics +AI08532,AI Specialist,90256,USD,90256,EN,FL,Ireland,L,Norway,100,"TensorFlow, GCP, Statistics, Python",PhD,1,Manufacturing,2025-01-23,2025-02-16,2232,6.8,Quantum Computing Inc +AI08533,Data Scientist,96346,GBP,72260,EN,FT,United Kingdom,L,United Kingdom,50,"MLOps, Spark, GCP",PhD,1,Transportation,2024-11-20,2025-01-15,1593,6.8,Future Systems +AI08534,AI Architect,227082,GBP,170312,EX,FT,United Kingdom,S,United Kingdom,0,"Git, Hadoop, Tableau, AWS",Associate,18,Media,2024-03-18,2024-05-08,1054,8.4,Quantum Computing Inc +AI08535,AI Consultant,174649,USD,174649,EX,FL,Sweden,S,Sweden,100,"PyTorch, GCP, Deep Learning",PhD,19,Telecommunications,2025-01-07,2025-02-01,2161,9.6,Autonomous Tech +AI08536,Principal Data Scientist,244243,EUR,207607,EX,PT,Austria,L,Austria,50,"Mathematics, SQL, Docker, TensorFlow",Master,14,Manufacturing,2025-04-17,2025-05-29,881,5.9,DataVision Ltd +AI08537,AI Software Engineer,140294,GBP,105221,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Scala, MLOps",Master,6,Automotive,2025-01-23,2025-03-30,2467,6.9,AI Innovations +AI08538,AI Consultant,125410,CAD,156763,SE,CT,Canada,L,Ghana,100,"Scala, Hadoop, AWS",Master,5,Real Estate,2024-11-23,2025-01-04,2245,8.1,Cognitive Computing +AI08539,AI Specialist,102002,CAD,127503,MI,CT,Canada,M,Netherlands,0,"Linux, Mathematics, MLOps",Associate,2,Transportation,2024-02-22,2024-04-04,1720,9.7,Autonomous Tech +AI08540,Machine Learning Researcher,70722,AUD,95475,EN,CT,Australia,M,Belgium,100,"Mathematics, Linux, AWS, Docker, SQL",Master,1,Manufacturing,2025-04-25,2025-05-17,1856,8.8,Machine Intelligence Group +AI08541,AI Product Manager,92261,GBP,69196,MI,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, NLP",PhD,3,Government,2024-01-10,2024-01-29,2021,6.4,Quantum Computing Inc +AI08542,AI Architect,84465,CHF,76019,EN,PT,Switzerland,L,Switzerland,100,"Data Visualization, Spark, Deep Learning",Associate,0,Consulting,2025-01-02,2025-02-15,2374,5,Future Systems +AI08543,Machine Learning Engineer,73370,EUR,62365,EN,PT,Germany,M,Germany,50,"Linux, Docker, Kubernetes",PhD,0,Technology,2024-04-21,2024-06-05,2319,6.5,Algorithmic Solutions +AI08544,Data Scientist,125995,EUR,107096,EX,PT,France,S,United Kingdom,0,"SQL, Spark, PyTorch, Hadoop",PhD,12,Transportation,2024-03-21,2024-04-30,1217,9.4,DataVision Ltd +AI08545,Machine Learning Researcher,109740,SGD,142662,MI,CT,Singapore,L,Singapore,100,"Java, Deep Learning, TensorFlow, Statistics",Bachelor,4,Education,2024-02-25,2024-03-14,1024,9.7,Predictive Systems +AI08546,Principal Data Scientist,126186,USD,126186,MI,FL,Norway,S,Norway,50,"Git, Linux, Python, Kubernetes",PhD,3,Energy,2024-04-12,2024-06-04,2446,7.8,DeepTech Ventures +AI08547,AI Product Manager,114618,EUR,97425,SE,FL,Austria,S,Austria,50,"Git, AWS, Azure, Statistics, Scala",Master,8,Manufacturing,2024-11-01,2025-01-09,543,9.3,Advanced Robotics +AI08548,AI Consultant,194158,EUR,165034,EX,PT,France,L,France,100,"Linux, Azure, TensorFlow, Git",PhD,15,Media,2024-09-14,2024-10-18,971,9.5,Future Systems +AI08549,Machine Learning Engineer,68896,USD,68896,EN,CT,Ireland,L,Ireland,0,"TensorFlow, PyTorch, AWS, Statistics",Associate,1,Energy,2024-12-28,2025-01-19,903,6.7,TechCorp Inc +AI08550,AI Product Manager,179602,JPY,19756220,SE,PT,Japan,L,Japan,50,"Docker, Python, NLP, MLOps",Bachelor,8,Gaming,2024-10-22,2024-11-24,2386,7.6,Predictive Systems +AI08551,Machine Learning Engineer,197099,EUR,167534,EX,CT,Netherlands,S,Netherlands,0,"SQL, Spark, Python, R",PhD,17,Finance,2024-10-01,2024-12-09,874,6.6,Autonomous Tech +AI08552,AI Architect,63579,USD,63579,MI,FT,Israel,S,Israel,50,"Hadoop, Linux, GCP, Tableau, Mathematics",Master,3,Gaming,2024-03-16,2024-05-07,2455,7.2,Algorithmic Solutions +AI08553,Machine Learning Researcher,141152,USD,141152,EX,CT,South Korea,S,South Korea,0,"Spark, Linux, Python, Azure",Master,16,Government,2024-10-01,2024-12-12,1492,5.1,Machine Intelligence Group +AI08554,NLP Engineer,96134,SGD,124974,MI,PT,Singapore,M,Singapore,0,"TensorFlow, Mathematics, Data Visualization",Associate,4,Transportation,2024-09-23,2024-11-17,1025,9.4,AI Innovations +AI08555,Research Scientist,127024,GBP,95268,SE,FT,United Kingdom,L,United Kingdom,100,"R, SQL, MLOps, Statistics, Hadoop",Master,9,Energy,2024-05-14,2024-06-30,1870,6.8,Cognitive Computing +AI08556,Machine Learning Researcher,145838,USD,145838,SE,FL,Denmark,M,Denmark,50,"Docker, NLP, Kubernetes, Statistics, Mathematics",Associate,7,Consulting,2024-02-26,2024-03-29,1533,5.2,DataVision Ltd +AI08557,Robotics Engineer,130985,EUR,111337,SE,FL,Germany,M,Germany,50,"Data Visualization, Linux, Python, TensorFlow, AWS",Master,5,Telecommunications,2024-12-29,2025-02-05,2324,6.5,Cloud AI Solutions +AI08558,Robotics Engineer,154058,EUR,130949,SE,PT,France,L,France,0,"Python, TensorFlow, MLOps, Hadoop",PhD,5,Finance,2024-02-08,2024-03-19,2052,5.5,Smart Analytics +AI08559,Machine Learning Researcher,97591,USD,97591,MI,PT,Norway,S,Russia,0,"R, Git, Kubernetes, Computer Vision",Master,2,Government,2025-02-26,2025-04-24,1877,6.9,AI Innovations +AI08560,Machine Learning Engineer,271305,SGD,352697,EX,FL,Singapore,L,New Zealand,100,"Git, PyTorch, AWS, Data Visualization",Associate,19,Transportation,2024-10-04,2024-10-22,638,9.3,Algorithmic Solutions +AI08561,ML Ops Engineer,98409,EUR,83648,MI,CT,Netherlands,L,Netherlands,100,"TensorFlow, MLOps, Scala",PhD,3,Consulting,2024-01-05,2024-02-14,1500,7.7,Machine Intelligence Group +AI08562,AI Research Scientist,148798,JPY,16367780,SE,CT,Japan,L,Japan,100,"Scala, PyTorch, AWS, TensorFlow",Associate,6,Government,2024-11-21,2024-12-31,747,8.3,Cognitive Computing +AI08563,AI Product Manager,279602,GBP,209702,EX,FL,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, Statistics, Docker, Scala",Associate,16,Education,2025-01-23,2025-02-18,1232,7.6,AI Innovations +AI08564,NLP Engineer,95686,SGD,124392,MI,CT,Singapore,S,Luxembourg,50,"Tableau, TensorFlow, Java, Kubernetes",Bachelor,3,Healthcare,2024-11-18,2024-12-10,582,9.9,Future Systems +AI08565,AI Consultant,64322,USD,64322,EN,FT,Israel,M,Israel,0,"NLP, GCP, Docker",PhD,1,Telecommunications,2025-02-16,2025-04-22,2144,5.5,Smart Analytics +AI08566,NLP Engineer,136594,USD,136594,MI,PT,Denmark,M,Nigeria,0,"Java, Computer Vision, Python, AWS, TensorFlow",PhD,2,Energy,2024-05-03,2024-05-29,1479,6.7,AI Innovations +AI08567,Robotics Engineer,82693,EUR,70289,EN,FL,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure",PhD,0,Energy,2025-04-13,2025-05-14,1302,8.8,DataVision Ltd +AI08568,AI Specialist,153976,USD,153976,EX,CT,United States,S,Argentina,50,"Scala, R, Tableau, TensorFlow, Docker",PhD,19,Retail,2024-09-18,2024-10-19,591,6.5,Autonomous Tech +AI08569,Data Scientist,139600,USD,139600,SE,FL,Norway,M,Japan,0,"GCP, Kubernetes, SQL, Computer Vision",Master,6,Media,2024-12-20,2025-02-13,1575,5.5,Cognitive Computing +AI08570,Robotics Engineer,249090,GBP,186818,EX,FT,United Kingdom,L,Poland,50,"Java, Python, Deep Learning",PhD,17,Energy,2024-04-24,2024-06-13,1346,5.6,Cloud AI Solutions +AI08571,Data Analyst,40276,USD,40276,SE,FT,India,S,India,100,"Computer Vision, Linux, GCP, Statistics",Associate,9,Consulting,2024-11-09,2025-01-19,1140,7.5,Digital Transformation LLC +AI08572,Robotics Engineer,72904,USD,72904,MI,FL,Finland,S,Finland,100,"Python, Java, Docker",Master,4,Healthcare,2024-04-10,2024-05-07,920,5,Quantum Computing Inc +AI08573,Research Scientist,64042,SGD,83255,EN,CT,Singapore,S,Singapore,100,"Linux, SQL, Git, MLOps, Hadoop",Bachelor,1,Consulting,2024-10-11,2024-11-12,1592,8.3,DataVision Ltd +AI08574,Machine Learning Researcher,305717,JPY,33628870,EX,PT,Japan,L,Luxembourg,50,"Kubernetes, Git, GCP, NLP, SQL",PhD,15,Technology,2024-08-03,2024-09-04,1529,9.7,DeepTech Ventures +AI08575,Research Scientist,85542,USD,85542,EN,FL,Norway,S,Norway,100,"TensorFlow, Tableau, Python",Bachelor,0,Gaming,2024-07-12,2024-08-11,620,8.6,Digital Transformation LLC +AI08576,Computer Vision Engineer,62229,USD,62229,MI,FL,South Korea,M,Ukraine,100,"Scala, R, NLP, Linux, Deep Learning",Associate,2,Manufacturing,2025-01-20,2025-03-03,2251,6.6,Predictive Systems +AI08577,Data Scientist,183034,CAD,228793,EX,FT,Canada,S,Canada,100,"Azure, SQL, Scala, Data Visualization, Git",Master,15,Technology,2024-04-02,2024-05-25,1927,7.5,AI Innovations +AI08578,Robotics Engineer,77261,CAD,96576,EN,FT,Canada,L,Canada,100,"Hadoop, PyTorch, Java",PhD,0,Technology,2025-02-21,2025-03-10,1539,7.2,Quantum Computing Inc +AI08579,AI Software Engineer,101020,USD,101020,MI,CT,Ireland,L,Thailand,0,"R, Tableau, Azure",Associate,2,Healthcare,2024-09-04,2024-11-16,661,6.9,Predictive Systems +AI08580,AI Consultant,76948,USD,76948,MI,PT,Finland,S,Hungary,100,"Hadoop, Git, PyTorch, AWS, Linux",Bachelor,4,Consulting,2024-02-28,2024-04-01,1102,7.8,Cognitive Computing +AI08581,AI Specialist,81536,USD,81536,EX,FT,China,M,China,0,"Kubernetes, Python, Azure, Spark",Bachelor,13,Gaming,2024-11-02,2024-12-12,2087,5.4,AI Innovations +AI08582,Principal Data Scientist,95198,USD,95198,SE,FL,Finland,S,Finland,0,"Git, R, Tableau",Bachelor,9,Consulting,2024-03-09,2024-04-10,1619,6.4,Predictive Systems +AI08583,AI Consultant,164093,GBP,123070,SE,PT,United Kingdom,L,Ghana,50,"TensorFlow, AWS, Tableau, Kubernetes, NLP",Master,9,Media,2024-04-02,2024-05-23,2074,9.8,DataVision Ltd +AI08584,Research Scientist,140767,USD,140767,SE,CT,United States,L,Hungary,0,"Tableau, Python, TensorFlow, PyTorch",Bachelor,8,Automotive,2024-08-11,2024-10-16,1142,9.1,Algorithmic Solutions +AI08585,Machine Learning Researcher,102336,USD,102336,EX,FL,China,L,China,50,"PyTorch, Hadoop, Git",Master,19,Consulting,2025-04-27,2025-05-11,662,5.8,Advanced Robotics +AI08586,Research Scientist,58994,EUR,50145,EN,FT,Austria,L,Austria,50,"Spark, Linux, Git, Azure",Master,0,Automotive,2025-02-16,2025-03-15,1940,7,DeepTech Ventures +AI08587,NLP Engineer,51117,AUD,69008,EN,FL,Australia,M,Australia,50,"Python, Java, MLOps",Master,0,Real Estate,2024-09-07,2024-11-02,2071,7,Machine Intelligence Group +AI08588,Data Scientist,82013,USD,82013,EN,FT,United States,L,United States,100,"SQL, Statistics, PyTorch, R",PhD,1,Real Estate,2024-06-09,2024-07-24,1950,8.5,AI Innovations +AI08589,AI Product Manager,204881,USD,204881,EX,PT,Finland,S,Finland,50,"Python, Spark, NLP",Master,10,Manufacturing,2024-01-20,2024-02-05,936,8.9,Future Systems +AI08590,AI Software Engineer,78751,USD,78751,EX,CT,India,M,India,100,"NLP, GCP, Spark, Kubernetes",Bachelor,13,Retail,2024-12-20,2025-01-12,1019,6.5,AI Innovations +AI08591,Head of AI,130461,GBP,97846,MI,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Kubernetes, SQL, GCP",PhD,3,Education,2024-08-14,2024-09-10,1707,9,Digital Transformation LLC +AI08592,AI Product Manager,83311,JPY,9164210,MI,PT,Japan,S,Japan,0,"Docker, Spark, Data Visualization, Git, Python",PhD,4,Consulting,2024-01-16,2024-02-17,1419,5.3,AI Innovations +AI08593,AI Research Scientist,57136,GBP,42852,EN,PT,United Kingdom,M,Sweden,100,"AWS, R, SQL, Deep Learning",Associate,0,Retail,2024-02-06,2024-02-25,2040,8.5,TechCorp Inc +AI08594,Head of AI,109478,USD,109478,MI,CT,Sweden,L,Sweden,0,"GCP, Azure, Tableau, Computer Vision, Git",Bachelor,2,Energy,2024-05-12,2024-07-03,1628,9.1,Autonomous Tech +AI08595,NLP Engineer,86990,USD,86990,MI,PT,Israel,L,Romania,0,"TensorFlow, GCP, NLP, Spark, Scala",Associate,3,Consulting,2024-11-05,2024-12-05,2421,6.1,Predictive Systems +AI08596,Machine Learning Engineer,241562,USD,241562,EX,CT,Ireland,M,Ireland,50,"R, Python, Mathematics, NLP",PhD,11,Government,2025-03-21,2025-05-28,1893,5.8,DataVision Ltd +AI08597,Principal Data Scientist,21704,USD,21704,EN,PT,India,M,India,50,"GCP, Deep Learning, Tableau",Associate,1,Telecommunications,2024-10-18,2024-12-25,1489,7.5,Autonomous Tech +AI08598,ML Ops Engineer,88065,EUR,74855,MI,FT,Netherlands,S,Netherlands,50,"Kubernetes, PyTorch, Azure, GCP, MLOps",Bachelor,3,Retail,2025-04-19,2025-05-13,779,5.9,Predictive Systems +AI08599,Research Scientist,52913,USD,52913,MI,PT,China,L,Ghana,0,"Data Visualization, Spark, Kubernetes, Java, Statistics",Associate,2,Education,2024-05-22,2024-06-05,1036,7.7,DataVision Ltd +AI08600,Robotics Engineer,60550,EUR,51468,EN,CT,Netherlands,M,Poland,0,"SQL, Statistics, Spark, Git",Bachelor,1,Energy,2025-03-23,2025-05-17,1973,6.4,Neural Networks Co +AI08601,Computer Vision Engineer,57164,USD,57164,EN,FT,Israel,L,Israel,50,"Azure, Java, Git, Computer Vision, Python",Master,1,Government,2024-05-08,2024-06-05,1916,9.1,DeepTech Ventures +AI08602,Principal Data Scientist,196044,USD,196044,EX,FL,Finland,L,Finland,100,"Java, Python, R, Docker, AWS",Master,19,Automotive,2025-01-13,2025-03-06,1055,6.4,Future Systems +AI08603,Deep Learning Engineer,205349,CAD,256686,EX,CT,Canada,M,Canada,50,"Kubernetes, NLP, Statistics, Deep Learning",Bachelor,10,Finance,2025-02-13,2025-04-19,1523,7.2,Smart Analytics +AI08604,Machine Learning Engineer,141845,CHF,127661,MI,FL,Switzerland,L,Switzerland,50,"AWS, Statistics, Tableau",PhD,2,Real Estate,2024-07-30,2024-09-23,2215,5.3,Quantum Computing Inc +AI08605,AI Specialist,111688,USD,111688,MI,PT,United States,L,Vietnam,50,"Git, Kubernetes, Statistics, Tableau",Bachelor,4,Media,2024-06-12,2024-08-17,1284,6.3,DeepTech Ventures +AI08606,Head of AI,68031,JPY,7483410,EN,FL,Japan,M,Japan,0,"AWS, Linux, Python, TensorFlow, Java",Bachelor,1,Consulting,2024-11-06,2025-01-07,2344,10,Machine Intelligence Group +AI08607,AI Product Manager,107527,CHF,96774,EN,FT,Switzerland,L,Switzerland,100,"Hadoop, MLOps, TensorFlow",PhD,1,Retail,2024-03-14,2024-05-09,2383,6.7,Advanced Robotics +AI08608,AI Consultant,181374,EUR,154168,EX,FL,Germany,M,Germany,50,"Hadoop, GCP, PyTorch, SQL, Linux",Master,13,Energy,2025-03-02,2025-04-14,865,7.3,Algorithmic Solutions +AI08609,Data Engineer,118961,EUR,101117,SE,PT,Germany,S,Portugal,0,"Kubernetes, AWS, R",PhD,8,Retail,2024-09-04,2024-11-16,1248,9.6,Algorithmic Solutions +AI08610,ML Ops Engineer,52835,USD,52835,MI,FT,China,L,China,50,"Spark, Kubernetes, Deep Learning",Bachelor,4,Education,2025-04-14,2025-05-09,1169,8.6,Smart Analytics +AI08611,Machine Learning Engineer,70673,USD,70673,SE,FT,China,M,China,50,"Java, Kubernetes, Tableau",Master,7,Telecommunications,2024-04-28,2024-05-17,1371,9.1,Quantum Computing Inc +AI08612,ML Ops Engineer,94570,AUD,127670,SE,CT,Australia,S,Australia,0,"Python, TensorFlow, Docker, R, Computer Vision",PhD,8,Transportation,2024-09-09,2024-10-10,1297,5.5,Digital Transformation LLC +AI08613,AI Research Scientist,64693,USD,64693,EN,FT,Israel,L,Israel,0,"AWS, MLOps, GCP, Mathematics",Bachelor,0,Consulting,2024-05-17,2024-07-21,2215,6.2,Quantum Computing Inc +AI08614,Head of AI,191853,USD,191853,SE,PT,Denmark,M,Denmark,0,"Scala, Git, Kubernetes, PyTorch, Python",PhD,8,Media,2025-01-30,2025-03-22,900,7.4,Autonomous Tech +AI08615,Data Analyst,114269,SGD,148550,SE,FT,Singapore,M,Singapore,0,"AWS, Statistics, NLP, Tableau",Bachelor,9,Energy,2024-12-16,2025-01-29,2116,9,Machine Intelligence Group +AI08616,Machine Learning Researcher,269818,JPY,29679980,EX,PT,Japan,M,Japan,50,"Computer Vision, PyTorch, Python, Azure, AWS",Bachelor,15,Real Estate,2024-02-05,2024-03-07,935,9.8,TechCorp Inc +AI08617,AI Software Engineer,120069,USD,120069,SE,CT,Norway,S,Norway,50,"AWS, R, Statistics, PyTorch",PhD,5,Manufacturing,2024-07-10,2024-08-18,1887,7.3,Cognitive Computing +AI08618,Data Analyst,86504,USD,86504,MI,FT,South Korea,M,South Korea,0,"Python, Hadoop, Git, TensorFlow",Bachelor,3,Media,2025-01-13,2025-03-02,2433,6.4,Future Systems +AI08619,Machine Learning Researcher,120570,USD,120570,EX,CT,China,L,China,50,"Python, SQL, AWS, Computer Vision",Bachelor,17,Telecommunications,2024-02-11,2024-03-10,1747,5.2,DeepTech Ventures +AI08620,Data Scientist,184942,USD,184942,EX,CT,Ireland,L,Latvia,50,"Computer Vision, Docker, R",Master,17,Automotive,2024-07-09,2024-08-24,600,9.6,AI Innovations +AI08621,Data Scientist,89220,EUR,75837,EN,PT,Germany,L,Germany,50,"Linux, Git, Computer Vision, Hadoop, Java",PhD,0,Real Estate,2024-03-08,2024-04-13,1551,5.3,Future Systems +AI08622,AI Product Manager,134492,JPY,14794120,SE,FL,Japan,M,Japan,100,"R, Statistics, NLP, Spark",Associate,8,Transportation,2024-10-31,2024-12-23,2443,8.6,DeepTech Ventures +AI08623,Machine Learning Researcher,137903,EUR,117218,EX,FL,France,S,France,50,"Java, Hadoop, NLP",Associate,16,Manufacturing,2024-11-10,2024-12-10,796,7.2,Smart Analytics +AI08624,Deep Learning Engineer,139031,GBP,104273,EX,FT,United Kingdom,S,Norway,0,"Linux, Azure, Mathematics, SQL, Hadoop",PhD,16,Energy,2024-12-15,2025-01-03,1916,5.9,Autonomous Tech +AI08625,AI Software Engineer,202153,USD,202153,EX,FT,South Korea,L,South Korea,50,"Scala, Computer Vision, Linux, Python, Kubernetes",Associate,17,Consulting,2025-03-05,2025-04-09,1250,6.2,DeepTech Ventures +AI08626,AI Architect,71668,USD,71668,MI,PT,Israel,S,South Africa,100,"Kubernetes, Git, R, PyTorch",Associate,3,Retail,2025-01-19,2025-04-02,1593,6,Cloud AI Solutions +AI08627,AI Product Manager,89404,USD,89404,EN,CT,Denmark,L,Denmark,0,"PyTorch, Tableau, TensorFlow",Bachelor,0,Finance,2024-11-04,2024-12-09,1637,8,DeepTech Ventures +AI08628,Head of AI,145615,USD,145615,SE,FT,Sweden,M,Sweden,0,"Linux, MLOps, Data Visualization, Python, NLP",Associate,8,Consulting,2024-10-10,2024-11-09,2127,9.5,Cloud AI Solutions +AI08629,Data Analyst,207813,USD,207813,EX,FL,Finland,L,Finland,0,"R, Linux, Deep Learning",Associate,13,Transportation,2024-12-30,2025-02-17,1223,5.3,Cloud AI Solutions +AI08630,AI Architect,142528,EUR,121149,SE,FT,Netherlands,M,Netherlands,50,"Git, Scala, Statistics, MLOps, SQL",Master,8,Technology,2025-03-21,2025-05-22,1866,6.3,Autonomous Tech +AI08631,AI Specialist,68097,USD,68097,MI,FT,Finland,M,Finland,50,"Kubernetes, Python, GCP",Bachelor,3,Manufacturing,2025-03-11,2025-04-08,1548,7.5,Machine Intelligence Group +AI08632,Data Engineer,224311,SGD,291604,EX,CT,Singapore,S,Singapore,50,"Java, Linux, Mathematics, Azure, Scala",Associate,17,Transportation,2025-01-16,2025-01-30,659,8.8,AI Innovations +AI08633,Autonomous Systems Engineer,114501,CAD,143126,SE,FT,Canada,L,Canada,50,"Tableau, PyTorch, Git, Python, Linux",Bachelor,7,Consulting,2024-10-26,2024-11-11,880,6.1,Autonomous Tech +AI08634,NLP Engineer,65825,USD,65825,SE,FL,China,L,China,0,"AWS, Java, Azure",Bachelor,5,Finance,2024-10-04,2024-10-24,1602,9.2,Autonomous Tech +AI08635,AI Specialist,196121,CAD,245151,EX,PT,Canada,S,Canada,0,"Spark, Kubernetes, GCP, Tableau",Associate,18,Education,2025-04-30,2025-06-18,954,7.6,AI Innovations +AI08636,Principal Data Scientist,94824,USD,94824,EN,PT,United States,M,United States,100,"Hadoop, Linux, Kubernetes",Associate,1,Manufacturing,2024-01-02,2024-03-03,922,5,Machine Intelligence Group +AI08637,AI Software Engineer,48808,USD,48808,SE,PT,China,M,China,100,"Linux, Docker, R, Mathematics",Master,8,Government,2024-04-09,2024-06-16,2216,8.1,Autonomous Tech +AI08638,Robotics Engineer,119252,EUR,101364,SE,CT,Netherlands,M,Finland,0,"PyTorch, TensorFlow, Mathematics, Java, Spark",Master,5,Finance,2024-11-28,2025-02-05,1993,7.6,Machine Intelligence Group +AI08639,AI Architect,77771,CHF,69994,EN,FL,Switzerland,M,Switzerland,50,"Scala, Tableau, Deep Learning",Master,0,Education,2024-02-11,2024-03-05,1677,8.1,Future Systems +AI08640,ML Ops Engineer,106474,USD,106474,SE,CT,Ireland,S,Ireland,0,"PyTorch, SQL, AWS, Docker",Master,6,Consulting,2024-09-22,2024-10-06,1764,6.9,Algorithmic Solutions +AI08641,Computer Vision Engineer,233835,AUD,315677,EX,CT,Australia,M,Australia,100,"R, GCP, Mathematics",Associate,17,Government,2024-12-30,2025-02-18,2214,8.9,Future Systems +AI08642,Data Analyst,95754,SGD,124480,MI,CT,Singapore,M,Singapore,100,"Tableau, TensorFlow, NLP, SQL",Bachelor,2,Telecommunications,2024-07-21,2024-09-24,1939,8.9,AI Innovations +AI08643,Data Engineer,111708,CAD,139635,SE,CT,Canada,S,Russia,0,"Python, TensorFlow, Kubernetes, Hadoop, Docker",Bachelor,5,Government,2024-09-08,2024-11-12,2019,5.3,Quantum Computing Inc +AI08644,Principal Data Scientist,263271,JPY,28959810,EX,CT,Japan,M,Kenya,100,"Kubernetes, TensorFlow, Mathematics, AWS, PyTorch",Bachelor,14,Healthcare,2024-01-07,2024-03-11,1071,9.6,Quantum Computing Inc +AI08645,Robotics Engineer,201498,USD,201498,SE,PT,Norway,L,Norway,100,"Spark, Java, Docker, GCP, Statistics",Master,6,Telecommunications,2024-03-04,2024-04-17,1970,8.9,Cognitive Computing +AI08646,Machine Learning Researcher,98345,USD,98345,EN,PT,Norway,M,Norway,100,"R, Linux, Java",Bachelor,0,Automotive,2024-11-01,2024-11-27,1920,5.9,TechCorp Inc +AI08647,Data Engineer,47321,USD,47321,MI,PT,China,M,China,50,"GCP, Java, Tableau, Statistics",Associate,4,Manufacturing,2024-03-11,2024-04-06,1151,8.8,DataVision Ltd +AI08648,Data Analyst,76662,USD,76662,MI,FT,South Korea,S,Romania,100,"Statistics, Python, NLP",Associate,3,Retail,2025-04-06,2025-05-16,1934,9.5,Quantum Computing Inc +AI08649,Data Scientist,135115,USD,135115,SE,CT,Israel,L,Egypt,100,"Docker, Spark, R, MLOps, Azure",Associate,6,Manufacturing,2024-06-24,2024-08-29,1019,5.6,Cloud AI Solutions +AI08650,Computer Vision Engineer,95343,EUR,81042,MI,PT,France,M,France,100,"SQL, GCP, Docker, Computer Vision, Hadoop",Master,4,Technology,2024-07-08,2024-08-12,2321,7.6,TechCorp Inc +AI08651,Principal Data Scientist,19877,USD,19877,EN,FL,India,S,India,0,"R, Python, Computer Vision",PhD,1,Government,2024-10-25,2024-12-23,1853,6.7,Machine Intelligence Group +AI08652,AI Consultant,120340,SGD,156442,SE,FL,Singapore,M,Singapore,50,"Linux, Java, Python, Kubernetes, Deep Learning",Bachelor,8,Automotive,2024-07-20,2024-08-24,2341,9.6,Autonomous Tech +AI08653,Data Analyst,105495,SGD,137144,SE,CT,Singapore,S,Singapore,0,"Java, GCP, AWS",PhD,8,Transportation,2024-03-04,2024-05-16,715,7.8,Machine Intelligence Group +AI08654,Data Scientist,23760,USD,23760,EN,FL,China,S,China,50,"TensorFlow, Linux, Computer Vision",Associate,0,Telecommunications,2024-09-05,2024-10-10,2121,8.5,Neural Networks Co +AI08655,Research Scientist,81420,JPY,8956200,EN,FT,Japan,M,Japan,50,"PyTorch, Tableau, Scala",Bachelor,1,Technology,2024-08-07,2024-10-08,2240,6.8,Autonomous Tech +AI08656,Machine Learning Researcher,117907,SGD,153279,SE,PT,Singapore,M,Singapore,100,"Python, Git, R, TensorFlow, Statistics",Associate,6,Government,2024-02-08,2024-04-14,2148,7.7,Future Systems +AI08657,Machine Learning Engineer,96703,JPY,10637330,MI,FT,Japan,S,Japan,100,"Azure, Java, GCP, TensorFlow, MLOps",Associate,2,Healthcare,2025-04-06,2025-06-15,1390,8.5,Cloud AI Solutions +AI08658,Data Analyst,64544,AUD,87134,EN,CT,Australia,S,Australia,100,"SQL, Java, Mathematics, PyTorch",Bachelor,1,Transportation,2025-03-27,2025-04-17,1219,5.6,TechCorp Inc +AI08659,Principal Data Scientist,113782,JPY,12516020,SE,FL,Japan,M,Japan,100,"Scala, Azure, PyTorch, SQL",Bachelor,5,Media,2024-04-05,2024-05-10,1092,9.9,Predictive Systems +AI08660,Machine Learning Researcher,128270,USD,128270,MI,FT,United States,L,United States,100,"R, Git, Python, NLP, TensorFlow",Master,2,Telecommunications,2025-02-20,2025-03-25,2100,5.6,Machine Intelligence Group +AI08661,Head of AI,65592,USD,65592,MI,FL,Sweden,S,Sweden,100,"Python, Git, Scala",Master,3,Media,2024-03-04,2024-04-14,2111,9.3,Advanced Robotics +AI08662,AI Software Engineer,54617,CAD,68271,EN,FT,Canada,M,Canada,100,"MLOps, Java, Python",Bachelor,0,Manufacturing,2024-02-12,2024-04-24,993,8.7,Predictive Systems +AI08663,AI Consultant,82192,USD,82192,MI,FT,South Korea,M,Italy,50,"Kubernetes, Scala, Spark",Associate,2,Automotive,2024-03-05,2024-04-18,994,6.1,Advanced Robotics +AI08664,Principal Data Scientist,81981,EUR,69684,MI,FT,France,L,France,50,"Python, NLP, TensorFlow, Git, Java",Master,4,Media,2024-07-08,2024-09-08,1850,6.7,Neural Networks Co +AI08665,AI Research Scientist,76034,EUR,64629,MI,PT,Austria,S,Austria,0,"R, Computer Vision, Python, Kubernetes, MLOps",Bachelor,3,Manufacturing,2024-06-06,2024-07-30,1652,8,Future Systems +AI08666,AI Architect,24952,USD,24952,EN,CT,India,M,India,50,"Linux, PyTorch, Python, Hadoop",Bachelor,0,Manufacturing,2025-01-16,2025-03-24,2290,9.1,Cloud AI Solutions +AI08667,Data Engineer,44314,USD,44314,MI,CT,China,S,Switzerland,0,"PyTorch, GCP, SQL, Data Visualization, Tableau",PhD,2,Telecommunications,2024-09-05,2024-11-17,1117,7.4,Predictive Systems +AI08668,AI Product Manager,160046,CAD,200058,EX,CT,Canada,L,Canada,0,"Tableau, R, Git, Data Visualization, Computer Vision",Associate,10,Technology,2025-02-26,2025-04-08,1302,6.3,DataVision Ltd +AI08669,Data Scientist,224937,EUR,191196,EX,FL,Netherlands,M,China,0,"SQL, PyTorch, Mathematics",Master,13,Real Estate,2025-04-27,2025-06-14,2360,7.6,Predictive Systems +AI08670,Deep Learning Engineer,69057,SGD,89774,MI,PT,Singapore,S,Singapore,50,"R, AWS, Azure, Deep Learning",Associate,3,Technology,2024-01-25,2024-02-10,991,6.4,Cognitive Computing +AI08671,AI Consultant,65525,EUR,55696,EN,FL,Germany,M,Germany,100,"Hadoop, SQL, Computer Vision",PhD,0,Technology,2024-12-31,2025-01-27,1022,5.6,AI Innovations +AI08672,Data Engineer,231770,CHF,208593,EX,FT,Switzerland,M,Switzerland,0,"Kubernetes, Spark, GCP",PhD,10,Telecommunications,2024-03-09,2024-03-24,946,6.2,Quantum Computing Inc +AI08673,Autonomous Systems Engineer,189743,GBP,142307,EX,CT,United Kingdom,S,United Kingdom,0,"Python, Linux, TensorFlow, Data Visualization",Bachelor,11,Education,2024-11-11,2025-01-04,1985,7.6,DeepTech Ventures +AI08674,AI Consultant,84046,CAD,105058,MI,CT,Canada,L,Brazil,50,"NLP, GCP, Python, Tableau",Associate,2,Finance,2024-11-03,2025-01-11,1018,5.7,DeepTech Ventures +AI08675,Robotics Engineer,58018,USD,58018,SE,FL,China,M,China,100,"Computer Vision, Hadoop, Python",Associate,7,Media,2024-02-15,2024-03-11,2304,8,Neural Networks Co +AI08676,Head of AI,82096,USD,82096,EX,FT,China,L,Finland,50,"Git, Linux, Hadoop, GCP, Kubernetes",Associate,10,Finance,2025-02-10,2025-03-14,2277,5.1,Advanced Robotics +AI08677,AI Research Scientist,228962,EUR,194618,EX,FL,France,L,France,50,"Hadoop, SQL, Python",PhD,14,Energy,2024-10-15,2024-12-24,601,9.5,Quantum Computing Inc +AI08678,Head of AI,59789,EUR,50821,EN,CT,Netherlands,S,Netherlands,100,"R, Hadoop, Kubernetes, GCP",PhD,0,Finance,2024-10-26,2024-12-13,1908,7.9,Autonomous Tech +AI08679,AI Product Manager,65661,JPY,7222710,EN,CT,Japan,S,Japan,0,"Spark, Linux, PyTorch",Bachelor,0,Education,2024-09-27,2024-11-06,1374,6.3,Advanced Robotics +AI08680,Head of AI,192079,USD,192079,EX,FT,South Korea,L,South Korea,0,"Spark, Java, TensorFlow, Statistics, AWS",PhD,11,Telecommunications,2025-01-02,2025-03-05,2192,5.7,Predictive Systems +AI08681,Computer Vision Engineer,98259,EUR,83520,MI,FL,Germany,S,Germany,100,"Java, Spark, Mathematics, R",Associate,3,Telecommunications,2025-01-14,2025-03-21,639,8.4,Algorithmic Solutions +AI08682,Data Analyst,152980,SGD,198874,EX,FL,Singapore,M,Singapore,100,"R, Tableau, SQL",Associate,18,Transportation,2024-04-16,2024-05-07,1446,7,Autonomous Tech +AI08683,AI Product Manager,52672,EUR,44771,EN,FL,Austria,S,Austria,0,"R, Statistics, Data Visualization",Bachelor,0,Manufacturing,2024-07-12,2024-08-21,2084,9.1,Algorithmic Solutions +AI08684,ML Ops Engineer,22389,USD,22389,EN,FL,India,S,Luxembourg,0,"Mathematics, Tableau, GCP",Bachelor,1,Manufacturing,2024-10-17,2024-11-01,2404,9.6,Quantum Computing Inc +AI08685,ML Ops Engineer,62477,AUD,84344,EN,CT,Australia,M,Australia,0,"Hadoop, Git, Python",Master,1,Manufacturing,2024-02-07,2024-02-25,797,8.8,DataVision Ltd +AI08686,Principal Data Scientist,76545,USD,76545,MI,CT,Ireland,M,Ireland,100,"PyTorch, NLP, Java, Mathematics",Bachelor,3,Healthcare,2024-12-09,2025-02-01,1782,6.9,Cognitive Computing +AI08687,AI Software Engineer,86947,USD,86947,SE,FL,South Korea,M,Canada,100,"Kubernetes, TensorFlow, Python",PhD,6,Energy,2024-08-24,2024-10-19,976,6.5,Cloud AI Solutions +AI08688,Deep Learning Engineer,83441,GBP,62581,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, Python, TensorFlow, Git, PyTorch",Master,4,Media,2024-01-16,2024-03-19,555,7.4,Algorithmic Solutions +AI08689,AI Architect,300340,GBP,225255,EX,FT,United Kingdom,L,United Kingdom,100,"Git, Kubernetes, R, NLP, Deep Learning",Master,11,Real Estate,2025-03-16,2025-04-09,2004,6.7,Predictive Systems +AI08690,AI Research Scientist,149207,USD,149207,SE,CT,United States,S,United States,100,"Statistics, Azure, Computer Vision",Bachelor,6,Consulting,2024-01-12,2024-03-04,656,5.1,AI Innovations +AI08691,Principal Data Scientist,160666,EUR,136566,SE,PT,Netherlands,L,Nigeria,0,"GCP, Scala, Data Visualization, Spark, Mathematics",Master,9,Energy,2025-01-08,2025-01-30,2146,5.6,Algorithmic Solutions +AI08692,Machine Learning Researcher,150614,EUR,128022,SE,FL,Germany,L,Japan,0,"Python, Git, Spark",Master,7,Consulting,2024-07-28,2024-10-03,1729,8,DataVision Ltd +AI08693,AI Consultant,55468,EUR,47148,EN,CT,Germany,S,Germany,50,"Hadoop, Data Visualization, Git",Master,1,Technology,2024-05-18,2024-07-03,1912,9.4,Algorithmic Solutions +AI08694,Autonomous Systems Engineer,106627,USD,106627,MI,FL,Norway,M,Singapore,50,"Linux, Data Visualization, Python, Deep Learning",Associate,4,Automotive,2025-02-17,2025-04-03,2132,8.7,Future Systems +AI08695,Computer Vision Engineer,151032,SGD,196342,SE,CT,Singapore,M,Singapore,0,"Scala, Computer Vision, Linux, Spark",PhD,6,Automotive,2025-02-17,2025-04-16,2187,9.4,Algorithmic Solutions +AI08696,AI Architect,62996,USD,62996,EN,PT,South Korea,M,Mexico,100,"Scala, Data Visualization, Python, Statistics",PhD,0,Manufacturing,2024-12-15,2025-01-11,710,5.4,Quantum Computing Inc +AI08697,ML Ops Engineer,124463,AUD,168025,SE,PT,Australia,S,Ireland,100,"Spark, AWS, R, Computer Vision, PyTorch",PhD,6,Energy,2024-02-21,2024-04-05,2212,5.3,Predictive Systems +AI08698,Data Engineer,84011,EUR,71409,MI,FT,Germany,L,China,50,"SQL, Python, NLP, Statistics, Deep Learning",Bachelor,2,Healthcare,2024-10-16,2024-11-29,2444,8.4,Digital Transformation LLC +AI08699,Machine Learning Engineer,108909,USD,108909,SE,FL,South Korea,M,South Korea,0,"AWS, SQL, MLOps",PhD,6,Technology,2025-04-07,2025-06-06,2373,9.7,Machine Intelligence Group +AI08700,Autonomous Systems Engineer,117099,AUD,158084,SE,PT,Australia,M,Australia,50,"Azure, Tableau, SQL, Git",Bachelor,7,Telecommunications,2024-06-29,2024-07-16,1572,8.5,AI Innovations +AI08701,AI Architect,243649,CHF,219284,SE,CT,Switzerland,L,Switzerland,50,"R, NLP, Python, Azure",Bachelor,6,Telecommunications,2024-11-25,2024-12-22,734,7,Future Systems +AI08702,AI Consultant,85139,USD,85139,MI,CT,Sweden,S,Sweden,0,"Python, SQL, Computer Vision, Statistics",Bachelor,4,Manufacturing,2024-11-10,2024-12-25,746,9.7,Future Systems +AI08703,AI Architect,149890,CHF,134901,SE,PT,Switzerland,S,South Africa,50,"NLP, GCP, Spark, Linux",Associate,9,Retail,2024-10-04,2024-10-19,933,6.5,DeepTech Ventures +AI08704,Head of AI,72866,USD,72866,MI,FL,South Korea,M,South Korea,50,"Python, TensorFlow, NLP, Deep Learning, MLOps",Master,3,Finance,2024-07-12,2024-07-28,2089,9.4,Digital Transformation LLC +AI08705,AI Specialist,26722,USD,26722,EN,CT,India,L,India,50,"Azure, SQL, Java, PyTorch",Bachelor,1,Education,2024-07-12,2024-08-09,1064,6.8,TechCorp Inc +AI08706,AI Specialist,169001,USD,169001,SE,FT,Norway,L,Czech Republic,100,"Python, R, Computer Vision, Hadoop",Master,8,Finance,2024-09-14,2024-10-06,2184,5.4,Advanced Robotics +AI08707,Principal Data Scientist,71514,USD,71514,MI,PT,South Korea,S,South Korea,50,"Scala, Kubernetes, Azure, Deep Learning, SQL",Bachelor,3,Government,2025-01-30,2025-03-01,708,9.3,Algorithmic Solutions +AI08708,Machine Learning Researcher,128232,EUR,108997,SE,FT,Netherlands,M,Japan,50,"Spark, Data Visualization, TensorFlow, Mathematics, Azure",Master,6,Energy,2024-06-07,2024-07-01,883,6.9,Future Systems +AI08709,AI Software Engineer,58091,USD,58091,EN,FL,Israel,M,Austria,0,"Python, Mathematics, NLP, TensorFlow, Spark",Bachelor,1,Consulting,2025-04-07,2025-06-11,674,7.4,DataVision Ltd +AI08710,Deep Learning Engineer,63424,JPY,6976640,EN,CT,Japan,S,Japan,100,"Kubernetes, R, Hadoop, Azure",Associate,0,Real Estate,2024-08-27,2024-10-23,1625,8.8,Smart Analytics +AI08711,Computer Vision Engineer,65363,USD,65363,SE,FL,China,M,South Africa,0,"Hadoop, Tableau, GCP, Java",Associate,5,Telecommunications,2024-02-21,2024-03-19,2347,6.6,Smart Analytics +AI08712,Robotics Engineer,54587,USD,54587,EX,FL,India,M,India,0,"Python, TensorFlow, Docker, Mathematics, Java",Bachelor,18,Automotive,2024-10-04,2024-12-03,1159,6.4,Quantum Computing Inc +AI08713,Data Scientist,248642,CHF,223778,EX,FT,Switzerland,M,Switzerland,0,"AWS, MLOps, Docker",Master,11,Technology,2024-07-27,2024-09-02,1616,8.6,Algorithmic Solutions +AI08714,AI Software Engineer,64401,USD,64401,EX,FL,China,S,China,50,"Deep Learning, Kubernetes, Tableau, Python",PhD,17,Finance,2025-03-28,2025-04-12,1565,7.8,DeepTech Ventures +AI08715,AI Product Manager,92513,USD,92513,SE,PT,Finland,S,Belgium,50,"Kubernetes, TensorFlow, SQL, Deep Learning, Hadoop",Associate,5,Transportation,2024-10-14,2024-11-26,1362,9.3,Advanced Robotics +AI08716,Robotics Engineer,238453,USD,238453,EX,FT,United States,M,United States,0,"Java, Python, TensorFlow",Associate,11,Media,2025-03-27,2025-05-16,1106,7.8,Machine Intelligence Group +AI08717,Data Engineer,99160,AUD,133866,MI,PT,Australia,M,Australia,50,"Java, Scala, Python",PhD,3,Media,2024-11-29,2025-01-25,2447,7.6,Advanced Robotics +AI08718,Data Scientist,248599,USD,248599,EX,PT,Finland,L,Finland,0,"SQL, PyTorch, Tableau, Docker",Bachelor,13,Finance,2024-05-12,2024-06-26,2240,6.5,TechCorp Inc +AI08719,NLP Engineer,236767,USD,236767,EX,CT,Ireland,M,Ireland,100,"GCP, NLP, AWS, SQL, Kubernetes",Associate,13,Transportation,2024-10-12,2024-12-03,1905,5,AI Innovations +AI08720,Deep Learning Engineer,110782,GBP,83087,MI,FL,United Kingdom,L,United Kingdom,0,"GCP, Data Visualization, Linux, Computer Vision, Kubernetes",Associate,2,Gaming,2024-11-09,2024-12-16,609,8.5,Cloud AI Solutions +AI08721,AI Research Scientist,302161,GBP,226621,EX,CT,United Kingdom,L,United Kingdom,100,"Mathematics, Java, Data Visualization, R",PhD,18,Energy,2025-04-05,2025-05-01,2008,9.9,DataVision Ltd +AI08722,AI Architect,146187,SGD,190043,EX,FL,Singapore,S,Thailand,0,"Kubernetes, GCP, MLOps, Statistics, Git",Associate,12,Technology,2025-01-10,2025-03-23,1238,9.7,Advanced Robotics +AI08723,AI Specialist,94634,EUR,80439,MI,CT,France,L,France,0,"R, Scala, Computer Vision, Mathematics, Python",Master,3,Media,2024-08-26,2024-10-05,712,6.2,Neural Networks Co +AI08724,AI Consultant,115988,USD,115988,SE,FL,Finland,M,Finland,50,"Hadoop, SQL, R, NLP, Scala",Associate,8,Retail,2025-01-16,2025-03-25,1191,5.4,Future Systems +AI08725,Autonomous Systems Engineer,192776,EUR,163860,EX,PT,Austria,L,Chile,100,"Computer Vision, Kubernetes, Mathematics",PhD,12,Retail,2025-04-22,2025-06-07,1757,7.2,DataVision Ltd +AI08726,ML Ops Engineer,33869,USD,33869,EN,PT,China,L,China,0,"Computer Vision, Git, Python, Spark",Master,1,Consulting,2024-02-10,2024-03-09,2019,7.9,Cognitive Computing +AI08727,AI Research Scientist,77360,JPY,8509600,EN,PT,Japan,M,Kenya,100,"SQL, Mathematics, MLOps, Statistics, Azure",PhD,0,Media,2025-01-18,2025-02-24,1156,8.5,TechCorp Inc +AI08728,Data Engineer,236119,JPY,25973090,EX,CT,Japan,L,Japan,50,"AWS, Python, TensorFlow, NLP",PhD,13,Consulting,2024-11-22,2024-12-14,602,5.4,Cloud AI Solutions +AI08729,Machine Learning Researcher,99743,USD,99743,EX,FT,China,M,China,100,"Hadoop, Python, Deep Learning, Linux, Mathematics",Master,17,Healthcare,2024-07-03,2024-07-26,1081,5.7,Quantum Computing Inc +AI08730,Data Scientist,92399,USD,92399,EN,FT,Denmark,S,Germany,0,"Spark, Python, MLOps",PhD,1,Education,2025-04-24,2025-06-25,1223,5.8,TechCorp Inc +AI08731,Computer Vision Engineer,110170,USD,110170,MI,CT,Sweden,M,India,100,"Linux, Docker, R, Git, AWS",PhD,4,Gaming,2025-01-06,2025-02-21,2429,7.4,DataVision Ltd +AI08732,Machine Learning Researcher,198925,USD,198925,EX,CT,Ireland,S,Nigeria,0,"Scala, R, SQL",Master,13,Gaming,2024-03-05,2024-05-09,1898,5.9,Algorithmic Solutions +AI08733,Data Engineer,170795,EUR,145176,EX,PT,Austria,M,Austria,50,"Java, SQL, GCP",PhD,17,Gaming,2025-04-29,2025-05-14,2240,8.1,Quantum Computing Inc +AI08734,Machine Learning Researcher,152232,EUR,129397,EX,FL,Netherlands,M,Netherlands,100,"Java, Hadoop, Tableau, Statistics, Spark",Master,19,Telecommunications,2024-12-19,2025-02-23,1989,7.5,AI Innovations +AI08735,AI Architect,308244,USD,308244,EX,FL,Norway,M,Portugal,0,"Spark, Java, PyTorch, Azure, Linux",Associate,10,Energy,2025-04-07,2025-05-19,1331,6.8,DeepTech Ventures +AI08736,AI Product Manager,58771,USD,58771,SE,CT,India,L,India,50,"Deep Learning, Hadoop, Computer Vision",PhD,7,Government,2024-02-05,2024-03-08,1849,6.6,Algorithmic Solutions +AI08737,Machine Learning Engineer,69542,EUR,59111,EN,CT,Netherlands,M,New Zealand,50,"Azure, Java, AWS, Python",Associate,1,Government,2024-06-04,2024-06-27,680,7.1,Advanced Robotics +AI08738,Principal Data Scientist,99141,USD,99141,MI,FL,Ireland,L,Hungary,50,"AWS, Linux, R, NLP, Docker",Bachelor,2,Government,2024-04-22,2024-05-07,1798,7.7,Autonomous Tech +AI08739,Machine Learning Engineer,115731,AUD,156237,MI,CT,Australia,L,Australia,0,"Git, Kubernetes, R, Spark, Deep Learning",PhD,4,Automotive,2025-02-24,2025-03-17,1199,8.8,AI Innovations +AI08740,AI Architect,73001,SGD,94901,EN,FL,Singapore,L,Singapore,50,"PyTorch, Scala, Docker",PhD,0,Technology,2024-06-13,2024-07-21,1492,9.9,Predictive Systems +AI08741,ML Ops Engineer,354384,USD,354384,EX,CT,Denmark,L,Portugal,100,"Deep Learning, Azure, Data Visualization",Associate,17,Media,2024-08-28,2024-09-28,1776,7.6,Machine Intelligence Group +AI08742,AI Software Engineer,89933,JPY,9892630,MI,PT,Japan,M,Japan,100,"Python, Docker, Azure, AWS",PhD,3,Telecommunications,2024-04-09,2024-04-25,1282,8.2,DeepTech Ventures +AI08743,AI Specialist,165985,JPY,18258350,EX,FL,Japan,L,Japan,0,"Git, Scala, Computer Vision, PyTorch",Associate,11,Real Estate,2024-07-31,2024-09-05,2297,8.6,Machine Intelligence Group +AI08744,Machine Learning Engineer,84231,EUR,71596,MI,PT,France,M,Philippines,100,"Scala, Kubernetes, R, Mathematics",Bachelor,4,Automotive,2024-11-24,2025-01-01,663,7.3,Cloud AI Solutions +AI08745,AI Research Scientist,123845,USD,123845,SE,CT,United States,S,New Zealand,50,"AWS, Deep Learning, Git, Docker, Azure",Bachelor,6,Transportation,2024-01-13,2024-02-15,686,6.2,Algorithmic Solutions +AI08746,Data Scientist,272008,USD,272008,EX,FL,Norway,S,Romania,100,"Python, Kubernetes, Tableau, Deep Learning, Docker",Bachelor,19,Retail,2024-09-07,2024-10-12,1953,9.3,Smart Analytics +AI08747,ML Ops Engineer,338395,USD,338395,EX,PT,United States,L,United States,50,"Linux, Python, Spark, Scala, Deep Learning",PhD,15,Technology,2025-03-16,2025-04-19,2070,6.4,Cognitive Computing +AI08748,AI Consultant,104347,EUR,88695,MI,FL,Germany,M,Netherlands,100,"Spark, Mathematics, Deep Learning, Computer Vision, AWS",Associate,4,Manufacturing,2024-02-18,2024-04-02,821,9.4,Machine Intelligence Group +AI08749,ML Ops Engineer,129907,JPY,14289770,SE,PT,Japan,S,Japan,100,"Data Visualization, Java, Tableau, TensorFlow, GCP",PhD,8,Real Estate,2024-12-04,2025-01-17,2013,5.7,Machine Intelligence Group +AI08750,Robotics Engineer,75071,EUR,63810,EN,CT,Austria,L,Austria,50,"Tableau, Mathematics, Python, TensorFlow, Deep Learning",PhD,1,Finance,2024-03-17,2024-05-28,2359,7.6,TechCorp Inc +AI08751,Data Scientist,89718,USD,89718,EN,FL,Ireland,L,Ireland,0,"SQL, Python, PyTorch",PhD,1,Healthcare,2024-12-28,2025-01-13,883,6.6,Predictive Systems +AI08752,Head of AI,123663,JPY,13602930,SE,CT,Japan,S,Japan,50,"Kubernetes, AWS, Statistics, Computer Vision",Associate,6,Education,2024-03-31,2024-05-07,522,6.3,DataVision Ltd +AI08753,AI Architect,232491,EUR,197617,EX,CT,France,M,France,50,"GCP, AWS, Hadoop, Tableau, Statistics",Bachelor,18,Healthcare,2024-03-27,2024-05-09,1496,9.3,Machine Intelligence Group +AI08754,Machine Learning Researcher,54167,USD,54167,SE,PT,India,L,Norway,0,"Git, Linux, Spark, Mathematics",Master,7,Education,2024-01-31,2024-03-30,2248,8.6,DataVision Ltd +AI08755,AI Product Manager,89079,CAD,111349,MI,CT,Canada,L,Canada,100,"MLOps, SQL, Python",Associate,2,Manufacturing,2024-08-25,2024-09-15,2460,6.6,Smart Analytics +AI08756,Data Scientist,194970,GBP,146228,EX,PT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, R, NLP, Deep Learning",Master,19,Government,2024-10-02,2024-10-16,961,8.8,Smart Analytics +AI08757,ML Ops Engineer,228547,USD,228547,EX,FL,Sweden,S,Sweden,0,"Tableau, Spark, GCP",PhD,13,Government,2025-01-10,2025-02-18,1740,7.2,Digital Transformation LLC +AI08758,Robotics Engineer,52055,USD,52055,SE,FL,India,L,India,50,"Linux, Hadoop, SQL",Bachelor,7,Automotive,2024-03-14,2024-04-05,2193,8.6,Advanced Robotics +AI08759,Head of AI,57328,USD,57328,EX,CT,India,M,India,50,"Python, R, Deep Learning, NLP, AWS",Associate,12,Education,2025-03-02,2025-03-31,1122,8.4,TechCorp Inc +AI08760,Autonomous Systems Engineer,52301,USD,52301,EN,PT,Sweden,S,Sweden,0,"Hadoop, Python, Kubernetes, Computer Vision, TensorFlow",Master,1,Telecommunications,2025-04-04,2025-04-23,1291,7.4,Cloud AI Solutions +AI08761,Robotics Engineer,23552,USD,23552,EN,PT,India,L,India,50,"Azure, Java, NLP, R, Deep Learning",PhD,0,Manufacturing,2025-03-20,2025-04-14,953,9.5,Quantum Computing Inc +AI08762,AI Product Manager,135585,EUR,115247,SE,FT,Netherlands,S,Netherlands,50,"Java, SQL, PyTorch, Deep Learning, Docker",Bachelor,8,Government,2024-10-09,2024-11-29,2293,6.8,Advanced Robotics +AI08763,AI Software Engineer,281620,USD,281620,EX,FT,Ireland,L,Ireland,50,"Git, Kubernetes, Scala, Spark, Computer Vision",Bachelor,13,Gaming,2024-06-15,2024-08-10,770,8.7,Digital Transformation LLC +AI08764,NLP Engineer,158612,SGD,206196,SE,CT,Singapore,M,Singapore,0,"Spark, Data Visualization, Java, MLOps, Linux",Master,5,Retail,2024-07-17,2024-09-15,836,6.9,Advanced Robotics +AI08765,AI Specialist,104480,USD,104480,MI,CT,Ireland,L,Ireland,100,"TensorFlow, Python, Tableau, SQL",PhD,4,Energy,2024-01-29,2024-04-03,734,8.8,Machine Intelligence Group +AI08766,Machine Learning Engineer,50599,EUR,43009,EN,FT,Germany,S,Romania,50,"Python, Hadoop, Data Visualization, Scala",Master,1,Government,2024-09-22,2024-11-07,857,5.1,Future Systems +AI08767,AI Consultant,74316,EUR,63169,MI,FT,Netherlands,S,Netherlands,100,"Linux, Tableau, SQL, Kubernetes",Master,3,Technology,2024-11-05,2024-12-04,763,5.8,Predictive Systems +AI08768,Robotics Engineer,91016,CAD,113770,MI,CT,Canada,L,Switzerland,50,"Hadoop, Spark, Deep Learning, Python",Associate,3,Transportation,2025-04-14,2025-05-10,1257,6.5,Cloud AI Solutions +AI08769,AI Product Manager,83508,USD,83508,MI,FT,Finland,L,Finland,50,"Linux, Git, PyTorch, Hadoop",Bachelor,3,Technology,2024-12-11,2025-01-29,725,7.6,Machine Intelligence Group +AI08770,AI Research Scientist,54579,USD,54579,EN,PT,Israel,S,Luxembourg,100,"Tableau, GCP, Git",Associate,0,Government,2025-04-01,2025-05-12,1489,6.9,Machine Intelligence Group +AI08771,NLP Engineer,147819,EUR,125646,EX,PT,Netherlands,S,Netherlands,50,"Data Visualization, PyTorch, Hadoop",Master,13,Automotive,2025-03-22,2025-04-10,1636,10,Future Systems +AI08772,Autonomous Systems Engineer,85094,USD,85094,MI,FT,Sweden,S,Finland,100,"Scala, Azure, Spark",Master,3,Consulting,2024-10-17,2024-12-04,801,7.3,Digital Transformation LLC +AI08773,AI Product Manager,18730,USD,18730,EN,CT,India,S,India,100,"Data Visualization, R, SQL",Associate,0,Real Estate,2024-08-01,2024-08-18,1893,6,Smart Analytics +AI08774,Deep Learning Engineer,89305,EUR,75909,MI,FT,Netherlands,S,South Korea,100,"AWS, Python, MLOps, TensorFlow, Hadoop",Master,3,Manufacturing,2024-04-16,2024-06-22,659,6.6,Smart Analytics +AI08775,Data Engineer,67597,USD,67597,MI,FT,South Korea,S,South Korea,100,"Deep Learning, Kubernetes, GCP",PhD,2,Telecommunications,2024-11-08,2025-01-03,1645,6.6,Future Systems +AI08776,NLP Engineer,67427,SGD,87655,EN,PT,Singapore,M,Singapore,0,"Linux, Mathematics, Hadoop",Master,0,Automotive,2024-04-20,2024-06-22,563,7.4,Autonomous Tech +AI08777,Machine Learning Engineer,80525,CAD,100656,MI,CT,Canada,S,Canada,0,"Mathematics, Kubernetes, SQL",PhD,3,Technology,2024-04-12,2024-06-24,533,8.2,Cloud AI Solutions +AI08778,Machine Learning Researcher,73119,USD,73119,EN,CT,Israel,M,Australia,100,"R, Kubernetes, Docker",Associate,0,Technology,2024-08-30,2024-11-11,2228,9.9,Smart Analytics +AI08779,Data Engineer,76899,USD,76899,EN,FT,Norway,L,Norway,50,"MLOps, NLP, Docker, Git",PhD,1,Finance,2024-03-06,2024-05-18,728,9.6,Machine Intelligence Group +AI08780,AI Specialist,71826,EUR,61052,EN,CT,Austria,M,Brazil,100,"Docker, Git, Hadoop, SQL, Computer Vision",Master,0,Transportation,2024-11-24,2024-12-20,1285,5.3,Quantum Computing Inc +AI08781,Autonomous Systems Engineer,101327,USD,101327,EN,PT,Norway,M,Norway,50,"Java, GCP, Python",Associate,1,Telecommunications,2024-11-18,2024-12-23,1879,6,Algorithmic Solutions +AI08782,Robotics Engineer,69083,USD,69083,MI,CT,Israel,M,Israel,100,"Python, Kubernetes, Docker",Master,2,Technology,2024-07-22,2024-08-08,1075,5.2,Algorithmic Solutions +AI08783,ML Ops Engineer,90930,EUR,77291,MI,PT,Austria,M,Austria,0,"Scala, TensorFlow, MLOps, Python",Master,2,Media,2024-09-10,2024-09-27,2010,7.2,DeepTech Ventures +AI08784,Autonomous Systems Engineer,124784,USD,124784,SE,PT,South Korea,M,Mexico,100,"Linux, Azure, Python",Bachelor,8,Media,2024-08-10,2024-10-12,632,5.8,DataVision Ltd +AI08785,Deep Learning Engineer,112554,USD,112554,MI,FT,Norway,M,Norway,50,"Python, Computer Vision, TensorFlow, Java, Hadoop",Master,4,Technology,2024-03-26,2024-04-17,644,7.1,Neural Networks Co +AI08786,AI Consultant,138859,EUR,118030,SE,FT,France,M,France,0,"NLP, Git, Azure, R, Python",Master,6,Retail,2024-03-25,2024-05-02,2136,7.2,Future Systems +AI08787,Data Scientist,155807,EUR,132436,EX,CT,France,L,Singapore,100,"AWS, R, Python, Git, Scala",PhD,18,Consulting,2024-11-14,2024-12-10,1084,6.8,Digital Transformation LLC +AI08788,Computer Vision Engineer,70709,EUR,60103,EN,CT,Germany,S,Canada,50,"TensorFlow, SQL, AWS",Master,1,Automotive,2024-05-10,2024-07-16,1987,8.1,Advanced Robotics +AI08789,NLP Engineer,20948,USD,20948,EN,FL,India,S,India,50,"Scala, Spark, Docker",Associate,1,Technology,2025-03-14,2025-05-08,505,9.5,Smart Analytics +AI08790,Head of AI,128719,EUR,109411,SE,PT,Netherlands,M,Turkey,100,"R, GCP, Python, Java, Mathematics",PhD,7,Energy,2024-06-13,2024-08-06,1872,9.6,Neural Networks Co +AI08791,AI Product Manager,73053,USD,73053,EN,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Azure",PhD,1,Telecommunications,2024-07-18,2024-08-03,1480,6.1,DataVision Ltd +AI08792,Research Scientist,127282,USD,127282,MI,PT,Denmark,S,Denmark,50,"Tableau, Spark, Python, Linux",PhD,4,Telecommunications,2024-07-24,2024-09-01,2464,8.9,DeepTech Ventures +AI08793,AI Product Manager,195816,SGD,254561,EX,FT,Singapore,S,Singapore,0,"Git, R, Deep Learning, Mathematics, Java",Master,13,Telecommunications,2024-01-03,2024-02-25,1036,6.2,Autonomous Tech +AI08794,NLP Engineer,169752,USD,169752,EX,CT,United States,M,United States,0,"MLOps, Java, Statistics, Data Visualization",Associate,14,Healthcare,2025-04-23,2025-06-24,956,5.7,Predictive Systems +AI08795,AI Consultant,105502,USD,105502,EX,FT,China,L,China,0,"SQL, Linux, Tableau, Computer Vision",Master,10,Transportation,2025-01-09,2025-02-24,1935,5.5,TechCorp Inc +AI08796,Data Engineer,112014,USD,112014,SE,PT,Ireland,S,Ireland,100,"TensorFlow, Scala, Python, Docker, R",Associate,6,Finance,2025-01-19,2025-03-09,1596,9.5,Machine Intelligence Group +AI08797,Machine Learning Engineer,247688,JPY,27245680,EX,FT,Japan,L,Japan,50,"PyTorch, SQL, Kubernetes, R",Master,18,Real Estate,2025-02-20,2025-05-03,1479,8.2,Autonomous Tech +AI08798,ML Ops Engineer,74961,EUR,63717,EN,PT,France,M,France,0,"TensorFlow, Data Visualization, Linux",PhD,1,Gaming,2024-10-24,2024-12-19,1666,6.3,Neural Networks Co +AI08799,ML Ops Engineer,115927,USD,115927,SE,PT,South Korea,L,Latvia,50,"Kubernetes, Data Visualization, PyTorch, GCP",PhD,8,Real Estate,2024-09-19,2024-10-10,2021,9.5,AI Innovations +AI08800,AI Consultant,60784,EUR,51666,EN,FT,France,S,France,50,"Tableau, NLP, Computer Vision, R",Master,0,Transportation,2025-04-01,2025-05-24,2418,5.9,Advanced Robotics +AI08801,Research Scientist,88808,EUR,75487,MI,FL,Germany,S,Germany,50,"GCP, PyTorch, Computer Vision",Master,2,Telecommunications,2025-04-04,2025-05-14,865,9.4,DeepTech Ventures +AI08802,AI Research Scientist,147363,EUR,125259,SE,CT,Austria,L,Austria,100,"Python, GCP, Computer Vision, TensorFlow, Azure",Associate,6,Manufacturing,2024-10-25,2025-01-02,651,8.3,Digital Transformation LLC +AI08803,AI Specialist,49188,USD,49188,EX,FT,India,S,India,100,"R, Azure, Linux, Computer Vision, Java",Associate,17,Healthcare,2024-07-25,2024-08-18,1743,9.3,Cloud AI Solutions +AI08804,Principal Data Scientist,159673,AUD,215559,EX,PT,Australia,M,Australia,0,"Hadoop, Linux, Java",PhD,18,Transportation,2025-03-01,2025-04-14,594,7.9,Future Systems +AI08805,AI Specialist,113403,EUR,96393,SE,CT,Germany,M,Germany,50,"Spark, Java, Tableau, Python, Statistics",Bachelor,7,Energy,2024-12-18,2025-03-01,2388,7.3,Smart Analytics +AI08806,Deep Learning Engineer,101965,USD,101965,MI,PT,Denmark,M,Denmark,0,"Scala, Python, Spark, Data Visualization",Bachelor,2,Media,2025-02-21,2025-03-26,1964,9.9,Advanced Robotics +AI08807,Head of AI,75727,USD,75727,MI,FL,Ireland,M,Ireland,50,"Data Visualization, Python, Deep Learning",Bachelor,4,Real Estate,2024-04-11,2024-06-07,2012,7.1,Machine Intelligence Group +AI08808,Principal Data Scientist,64011,EUR,54409,MI,CT,France,S,France,0,"R, Scala, NLP",PhD,2,Retail,2024-12-19,2025-01-03,528,5.5,AI Innovations +AI08809,Machine Learning Engineer,108796,JPY,11967560,MI,FL,Japan,L,Brazil,50,"R, Deep Learning, GCP, Computer Vision, Scala",Bachelor,4,Automotive,2024-06-13,2024-08-07,877,7.6,TechCorp Inc +AI08810,Robotics Engineer,235070,JPY,25857700,EX,CT,Japan,L,Japan,100,"Data Visualization, Scala, Linux, Python, Hadoop",Bachelor,11,Technology,2025-04-17,2025-05-07,1540,5.5,AI Innovations +AI08811,Data Engineer,180679,USD,180679,EX,FT,South Korea,M,Netherlands,100,"SQL, Linux, Java, Git",PhD,15,Healthcare,2024-03-17,2024-05-29,2493,8.8,Advanced Robotics +AI08812,Robotics Engineer,151818,EUR,129045,EX,FL,Germany,S,Thailand,0,"SQL, Java, R",PhD,19,Technology,2024-12-21,2025-01-19,887,7.9,Digital Transformation LLC +AI08813,Autonomous Systems Engineer,106856,USD,106856,MI,CT,Israel,L,Portugal,0,"Statistics, R, Tableau",PhD,4,Consulting,2024-02-27,2024-04-09,1290,6.3,Cloud AI Solutions +AI08814,Robotics Engineer,108490,JPY,11933900,MI,PT,Japan,M,Mexico,100,"Azure, Python, Deep Learning",PhD,2,Education,2024-04-06,2024-04-22,1077,6,Smart Analytics +AI08815,ML Ops Engineer,71874,EUR,61093,MI,CT,France,M,France,0,"Kubernetes, Python, SQL, MLOps, Statistics",PhD,3,Real Estate,2024-09-18,2024-11-30,1725,5.5,Quantum Computing Inc +AI08816,AI Consultant,202910,EUR,172474,EX,FL,France,S,Hungary,50,"PyTorch, Tableau, TensorFlow, Computer Vision",Bachelor,19,Real Estate,2025-01-26,2025-03-15,1807,8.3,DataVision Ltd +AI08817,AI Product Manager,118893,EUR,101059,SE,FL,Austria,L,Australia,50,"Deep Learning, Linux, GCP, Mathematics",Master,9,Retail,2024-03-16,2024-04-03,718,5.9,Digital Transformation LLC +AI08818,Data Analyst,90747,USD,90747,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Java, Git",Associate,4,Technology,2024-12-17,2025-02-23,1975,7.1,Digital Transformation LLC +AI08819,AI Software Engineer,55913,USD,55913,EN,FT,Ireland,M,Estonia,50,"Tableau, Spark, PyTorch, SQL, Data Visualization",Master,0,Consulting,2024-01-27,2024-02-27,936,5.8,Future Systems +AI08820,Data Scientist,321130,CHF,289017,EX,PT,Switzerland,S,Finland,100,"AWS, Docker, MLOps, SQL, Kubernetes",Bachelor,16,Telecommunications,2024-01-31,2024-04-03,572,9.1,Cognitive Computing +AI08821,Data Scientist,48284,USD,48284,EN,CT,Finland,S,Finland,50,"Python, Git, Linux, AWS",Master,0,Education,2024-04-26,2024-06-29,1758,7,DataVision Ltd +AI08822,Machine Learning Engineer,93069,USD,93069,EN,PT,Denmark,L,Denmark,0,"Data Visualization, Mathematics, Python, NLP",Bachelor,1,Education,2025-03-20,2025-05-22,1265,9.3,DataVision Ltd +AI08823,AI Architect,154216,USD,154216,SE,CT,Norway,L,Norway,0,"Scala, Git, Mathematics, Spark",Bachelor,5,Finance,2024-09-08,2024-11-01,652,8.7,TechCorp Inc +AI08824,Autonomous Systems Engineer,212745,AUD,287206,EX,PT,Australia,M,Australia,50,"NLP, Data Visualization, Docker, Python, Spark",PhD,10,Automotive,2025-03-11,2025-04-22,1584,9,Cloud AI Solutions +AI08825,ML Ops Engineer,148725,AUD,200779,EX,FT,Australia,M,Australia,50,"Computer Vision, Docker, TensorFlow",PhD,16,Automotive,2025-04-25,2025-05-30,1977,5.7,Predictive Systems +AI08826,Deep Learning Engineer,214868,AUD,290072,EX,CT,Australia,S,South Africa,100,"SQL, Computer Vision, Java, Mathematics, AWS",Master,17,Consulting,2024-12-07,2025-01-17,613,6.9,Neural Networks Co +AI08827,AI Consultant,48192,USD,48192,EN,CT,Sweden,S,Luxembourg,100,"SQL, TensorFlow, Git",Associate,0,Manufacturing,2024-02-11,2024-03-09,1626,7.6,Digital Transformation LLC +AI08828,Autonomous Systems Engineer,53715,USD,53715,EN,FT,Israel,S,Israel,50,"Python, TensorFlow, Linux, AWS, R",Associate,1,Education,2024-07-18,2024-08-02,1454,6.6,AI Innovations +AI08829,Data Engineer,79419,EUR,67506,MI,FL,Netherlands,S,Chile,100,"Python, Java, Computer Vision, AWS",PhD,3,Retail,2024-03-22,2024-05-07,2420,9.3,Quantum Computing Inc +AI08830,ML Ops Engineer,189251,EUR,160863,EX,FL,Austria,M,Austria,100,"Kubernetes, Computer Vision, Python, GCP, Statistics",Bachelor,12,Energy,2024-07-28,2024-08-22,1299,8.1,Cognitive Computing +AI08831,AI Product Manager,82862,USD,82862,MI,FT,United States,S,United States,50,"Tableau, Spark, Python",PhD,2,Technology,2024-03-14,2024-04-21,1366,9.2,TechCorp Inc +AI08832,Research Scientist,312798,CHF,281518,EX,CT,Switzerland,S,Portugal,100,"PyTorch, Mathematics, Deep Learning, TensorFlow",Associate,12,Retail,2024-06-06,2024-06-27,1963,5.8,Cloud AI Solutions +AI08833,ML Ops Engineer,104615,CHF,94154,EN,FL,Switzerland,L,United States,0,"Linux, Spark, Git, SQL, Hadoop",Master,0,Media,2024-06-22,2024-07-29,2231,9.5,Smart Analytics +AI08834,Deep Learning Engineer,42852,USD,42852,MI,FL,China,L,China,50,"R, Java, Azure, Deep Learning, AWS",Bachelor,2,Automotive,2024-05-03,2024-07-04,934,6.3,Smart Analytics +AI08835,Principal Data Scientist,83129,CAD,103911,MI,FT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Linux",Bachelor,3,Real Estate,2024-04-15,2024-05-03,810,5.5,Digital Transformation LLC +AI08836,Robotics Engineer,64763,SGD,84192,EN,PT,Singapore,S,Singapore,50,"R, SQL, Deep Learning",PhD,0,Government,2024-04-30,2024-07-10,1126,9.1,Neural Networks Co +AI08837,Data Scientist,140525,SGD,182683,SE,PT,Singapore,L,China,0,"Docker, Spark, Python, AWS",Associate,6,Automotive,2024-05-15,2024-07-25,816,8.2,TechCorp Inc +AI08838,AI Software Engineer,164731,AUD,222387,SE,FT,Australia,L,Australia,0,"Linux, PyTorch, Data Visualization, SQL",Bachelor,8,Automotive,2024-11-18,2024-12-17,1758,6.2,DataVision Ltd +AI08839,Machine Learning Researcher,58860,USD,58860,MI,CT,China,L,China,100,"Python, R, TensorFlow",PhD,4,Transportation,2024-10-13,2024-12-15,1321,9.7,Cloud AI Solutions +AI08840,AI Specialist,117441,USD,117441,MI,CT,Norway,M,Norway,100,"Mathematics, Kubernetes, NLP, Computer Vision, Linux",Master,4,Automotive,2025-03-10,2025-05-04,1794,8.9,DataVision Ltd +AI08841,Computer Vision Engineer,72350,EUR,61498,EN,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, PyTorch, Tableau",Bachelor,1,Energy,2024-06-22,2024-07-12,504,6.1,TechCorp Inc +AI08842,Deep Learning Engineer,92337,AUD,124655,SE,PT,Australia,S,South Africa,100,"AWS, Spark, Computer Vision, Docker, Mathematics",Bachelor,7,Healthcare,2024-07-16,2024-08-26,1201,5.5,Advanced Robotics +AI08843,Autonomous Systems Engineer,53864,EUR,45784,EN,CT,Austria,M,Mexico,0,"Deep Learning, Hadoop, Linux",PhD,0,Transportation,2024-10-12,2024-12-11,2012,7.7,Machine Intelligence Group +AI08844,AI Architect,33665,USD,33665,MI,CT,India,L,India,0,"Mathematics, Kubernetes, Docker, Scala",Associate,4,Finance,2024-03-13,2024-04-13,1806,9.4,Advanced Robotics +AI08845,Machine Learning Researcher,182110,EUR,154794,EX,PT,France,M,France,50,"Python, Git, Tableau, NLP",Associate,13,Energy,2025-03-18,2025-04-08,1774,9.6,Future Systems +AI08846,Head of AI,115234,SGD,149804,MI,FL,Singapore,L,Singapore,0,"Kubernetes, Computer Vision, Azure",Master,4,Energy,2024-01-16,2024-02-03,2189,8.7,Neural Networks Co +AI08847,Data Analyst,163943,SGD,213126,EX,FL,Singapore,M,Singapore,100,"MLOps, Linux, NLP",PhD,12,Energy,2024-04-04,2024-06-05,843,8,DeepTech Ventures +AI08848,Autonomous Systems Engineer,153511,JPY,16886210,SE,PT,Japan,M,Argentina,50,"Spark, Git, Python, TensorFlow",PhD,9,Education,2024-12-30,2025-02-12,1650,6.8,DataVision Ltd +AI08849,NLP Engineer,110442,SGD,143575,MI,FT,Singapore,L,Singapore,100,"Spark, Python, TensorFlow, R",Master,4,Healthcare,2025-03-17,2025-05-20,894,5.7,TechCorp Inc +AI08850,Research Scientist,136904,USD,136904,EX,FL,Israel,M,Israel,0,"Spark, Linux, Kubernetes",Master,14,Technology,2024-10-31,2024-12-17,2225,9.7,Future Systems +AI08851,ML Ops Engineer,83201,USD,83201,EN,FT,Finland,L,Thailand,50,"Hadoop, NLP, Python",Master,1,Real Estate,2025-02-21,2025-03-27,543,7.2,Predictive Systems +AI08852,Robotics Engineer,134018,CAD,167523,SE,PT,Canada,L,Thailand,50,"Python, Java, Data Visualization",Associate,6,Media,2024-01-08,2024-03-14,889,6.6,Predictive Systems +AI08853,Principal Data Scientist,88509,EUR,75233,MI,PT,France,M,France,100,"PyTorch, R, Computer Vision, Scala",Associate,2,Healthcare,2024-01-14,2024-03-05,2308,8.5,Digital Transformation LLC +AI08854,Research Scientist,126724,USD,126724,MI,PT,Denmark,L,Denmark,100,"Git, Python, TensorFlow, PyTorch",PhD,2,Technology,2024-05-19,2024-06-12,1390,7.3,Future Systems +AI08855,Principal Data Scientist,281410,EUR,239199,EX,FL,Netherlands,L,Egypt,0,"Statistics, Mathematics, NLP, Docker, Computer Vision",Master,15,Government,2024-04-19,2024-05-12,1403,5.5,Digital Transformation LLC +AI08856,Head of AI,162401,CAD,203001,EX,PT,Canada,M,Ghana,0,"PyTorch, Mathematics, MLOps, TensorFlow, NLP",Associate,17,Healthcare,2025-04-20,2025-06-18,1233,7.2,Autonomous Tech +AI08857,Machine Learning Engineer,180046,CHF,162041,SE,FT,Switzerland,M,Ghana,0,"Statistics, R, Java",Associate,8,Consulting,2024-07-23,2024-09-21,740,6.3,Neural Networks Co +AI08858,Data Scientist,73927,USD,73927,MI,CT,Sweden,S,Mexico,0,"Hadoop, MLOps, Linux, Spark, Git",Associate,2,Healthcare,2024-07-31,2024-09-05,2041,5.5,TechCorp Inc +AI08859,Data Engineer,109990,EUR,93492,MI,FL,Germany,M,United States,50,"Python, Java, Hadoop, Statistics, Computer Vision",Master,3,Real Estate,2024-06-28,2024-08-22,2199,5.8,Machine Intelligence Group +AI08860,Data Scientist,126474,USD,126474,SE,CT,Israel,L,Russia,100,"Tableau, Java, Kubernetes",Master,6,Consulting,2025-02-20,2025-04-07,1834,5.9,AI Innovations +AI08861,AI Research Scientist,160685,EUR,136582,EX,PT,Netherlands,M,Netherlands,0,"R, GCP, Git, Spark",PhD,13,Media,2024-05-28,2024-06-13,2083,6,Machine Intelligence Group +AI08862,Deep Learning Engineer,317312,CHF,285581,EX,CT,Switzerland,S,United Kingdom,50,"Git, R, GCP, Kubernetes, Java",Bachelor,16,Technology,2024-09-15,2024-11-12,1711,7.7,Advanced Robotics +AI08863,AI Consultant,85129,USD,85129,EN,PT,Denmark,L,Denmark,0,"NLP, PyTorch, TensorFlow",Bachelor,0,Energy,2024-09-29,2024-12-06,1340,8.8,Quantum Computing Inc +AI08864,AI Consultant,162063,USD,162063,EX,FL,Finland,L,Poland,50,"Deep Learning, Docker, AWS, SQL",Bachelor,16,Gaming,2024-05-05,2024-06-11,1974,8.3,Machine Intelligence Group +AI08865,Computer Vision Engineer,50185,USD,50185,EN,CT,Finland,M,India,50,"AWS, R, Deep Learning",Master,1,Education,2024-06-16,2024-07-02,1048,7.8,AI Innovations +AI08866,Autonomous Systems Engineer,212146,EUR,180324,EX,FT,Austria,L,Austria,50,"Java, TensorFlow, Mathematics, Tableau",Master,12,Technology,2025-03-07,2025-04-18,1448,5.2,DataVision Ltd +AI08867,AI Specialist,205751,JPY,22632610,EX,PT,Japan,M,Norway,50,"TensorFlow, Azure, Scala",Associate,19,Education,2024-04-13,2024-05-12,1542,7.7,DataVision Ltd +AI08868,AI Software Engineer,144178,USD,144178,SE,CT,Sweden,L,Indonesia,50,"PyTorch, GCP, Spark",Associate,5,Energy,2024-01-24,2024-02-18,2406,5.2,Quantum Computing Inc +AI08869,Machine Learning Researcher,154217,CHF,138795,SE,CT,Switzerland,M,Switzerland,0,"Scala, Computer Vision, Kubernetes, Deep Learning, Docker",Master,5,Gaming,2024-10-30,2024-12-09,2011,8.5,Cognitive Computing +AI08870,Data Analyst,118300,USD,118300,SE,FL,Israel,L,Israel,0,"Statistics, MLOps, Spark, Computer Vision, TensorFlow",Associate,6,Retail,2024-03-22,2024-04-14,1823,6.4,Cognitive Computing +AI08871,Data Analyst,164623,USD,164623,SE,CT,Norway,L,Norway,0,"Python, SQL, Computer Vision, Mathematics, TensorFlow",Master,5,Education,2024-12-11,2025-01-19,2283,7.2,Advanced Robotics +AI08872,Data Engineer,209872,USD,209872,EX,PT,Denmark,M,Denmark,0,"Kubernetes, Azure, Tableau, R, NLP",PhD,12,Energy,2025-04-03,2025-05-14,1604,9.2,Quantum Computing Inc +AI08873,Deep Learning Engineer,140537,EUR,119456,SE,CT,France,L,France,100,"Linux, MLOps, TensorFlow, PyTorch, Mathematics",Master,6,Finance,2024-06-08,2024-07-29,1729,5.8,Neural Networks Co +AI08874,Principal Data Scientist,72674,USD,72674,MI,FT,Israel,S,Vietnam,0,"Linux, Java, SQL, Kubernetes, PyTorch",PhD,2,Consulting,2025-04-10,2025-06-22,1258,7.7,TechCorp Inc +AI08875,AI Product Manager,96117,EUR,81699,MI,FT,France,L,Australia,100,"Linux, Java, Scala",Master,2,Education,2025-04-21,2025-06-20,1684,7.7,AI Innovations +AI08876,Data Scientist,132251,EUR,112413,SE,FL,Netherlands,L,Canada,0,"SQL, Kubernetes, Azure, Computer Vision",Master,7,Gaming,2024-08-03,2024-08-22,1336,9.3,Advanced Robotics +AI08877,Robotics Engineer,180163,SGD,234212,SE,PT,Singapore,L,Singapore,100,"Kubernetes, SQL, Linux",Associate,9,Technology,2024-09-26,2024-10-14,2472,6,Machine Intelligence Group +AI08878,AI Software Engineer,64220,GBP,48165,EN,FL,United Kingdom,S,United Kingdom,0,"Data Visualization, Azure, NLP",Associate,0,Media,2024-10-13,2024-11-25,947,8.6,Digital Transformation LLC +AI08879,Computer Vision Engineer,70080,AUD,94608,EN,CT,Australia,L,Australia,0,"Scala, PyTorch, TensorFlow, Tableau, Deep Learning",PhD,1,Real Estate,2025-01-18,2025-03-27,2308,8.5,Algorithmic Solutions +AI08880,Head of AI,72201,USD,72201,MI,PT,Finland,M,Israel,50,"NLP, Deep Learning, MLOps, PyTorch",PhD,3,Manufacturing,2025-03-31,2025-04-16,1516,9.5,Advanced Robotics +AI08881,AI Research Scientist,150170,CAD,187713,EX,FL,Canada,S,Canada,50,"Computer Vision, Java, TensorFlow",PhD,11,Government,2025-02-27,2025-03-29,2288,9,Digital Transformation LLC +AI08882,NLP Engineer,68586,USD,68586,EN,FL,Sweden,M,Estonia,50,"Deep Learning, Spark, GCP",Bachelor,1,Telecommunications,2024-03-21,2024-04-21,2215,9.5,Future Systems +AI08883,AI Specialist,58484,EUR,49711,EN,PT,France,L,France,0,"Docker, Python, Spark, Hadoop",Master,1,Automotive,2024-01-31,2024-04-01,1875,5.3,AI Innovations +AI08884,Data Analyst,53494,USD,53494,EN,FL,South Korea,S,South Korea,0,"MLOps, Docker, Linux, Computer Vision",Master,0,Telecommunications,2024-09-20,2024-11-04,1820,9.5,Smart Analytics +AI08885,AI Software Engineer,175512,USD,175512,SE,FL,Norway,L,Norway,0,"Linux, Computer Vision, PyTorch, Azure, TensorFlow",Associate,7,Automotive,2025-02-11,2025-03-26,2244,9.9,Cloud AI Solutions +AI08886,AI Product Manager,124719,USD,124719,MI,PT,Norway,M,Argentina,100,"Python, Kubernetes, PyTorch",Associate,2,Automotive,2025-01-27,2025-02-27,2326,6.6,Autonomous Tech +AI08887,Machine Learning Researcher,65569,USD,65569,EN,CT,Israel,S,Israel,0,"AWS, Tableau, Mathematics",Bachelor,0,Gaming,2025-02-14,2025-03-04,2433,6.3,AI Innovations +AI08888,AI Software Engineer,184461,USD,184461,EX,CT,Denmark,M,Israel,0,"Python, R, Data Visualization",Associate,13,Education,2024-06-25,2024-08-11,2438,5.9,Neural Networks Co +AI08889,AI Software Engineer,176661,CHF,158995,SE,FL,Switzerland,L,Finland,0,"PyTorch, Mathematics, AWS, Azure, Deep Learning",Associate,8,Media,2024-04-15,2024-05-08,1040,6.3,Algorithmic Solutions +AI08890,Research Scientist,113468,GBP,85101,MI,FT,United Kingdom,L,United Kingdom,50,"Python, Computer Vision, Statistics, Tableau",Associate,3,Transportation,2024-11-24,2025-01-22,1859,7.7,Cognitive Computing +AI08891,Robotics Engineer,94278,EUR,80136,MI,FL,France,M,Belgium,50,"Git, Kubernetes, Computer Vision, Python",PhD,3,Automotive,2024-07-25,2024-08-31,2395,8.6,Quantum Computing Inc +AI08892,AI Research Scientist,124121,EUR,105503,MI,FT,Netherlands,L,Netherlands,0,"Git, PyTorch, TensorFlow",PhD,3,Manufacturing,2025-01-15,2025-02-07,1523,5.8,Smart Analytics +AI08893,ML Ops Engineer,118336,EUR,100586,SE,FL,Netherlands,S,Netherlands,0,"Computer Vision, Git, Docker, Azure, TensorFlow",Bachelor,7,Manufacturing,2024-07-04,2024-08-11,1467,6.5,Algorithmic Solutions +AI08894,AI Consultant,63446,JPY,6979060,EN,CT,Japan,M,Japan,100,"PyTorch, Docker, GCP",Associate,1,Education,2024-08-14,2024-09-07,2327,8.5,Smart Analytics +AI08895,Data Analyst,88302,GBP,66227,MI,CT,United Kingdom,M,United Kingdom,100,"SQL, Git, Docker, Deep Learning",Master,4,Energy,2025-04-18,2025-05-12,1494,7.8,Smart Analytics +AI08896,Data Engineer,69937,CAD,87421,EN,CT,Canada,L,South Korea,0,"Tableau, Git, Java, NLP, Mathematics",PhD,1,Healthcare,2024-07-08,2024-09-03,1246,6.4,Cloud AI Solutions +AI08897,Data Scientist,76500,USD,76500,MI,PT,South Korea,S,South Korea,50,"Python, Kubernetes, Azure",Associate,3,Manufacturing,2025-03-21,2025-05-09,1141,5.4,TechCorp Inc +AI08898,Data Analyst,133991,USD,133991,MI,PT,Denmark,L,Spain,100,"Deep Learning, SQL, TensorFlow, Computer Vision",PhD,2,Automotive,2025-02-27,2025-04-30,1018,7.6,DeepTech Ventures +AI08899,Research Scientist,37472,USD,37472,EN,CT,China,M,China,0,"SQL, Mathematics, Docker, Python, Linux",Master,1,Media,2024-07-30,2024-08-23,597,7.8,Neural Networks Co +AI08900,NLP Engineer,55334,GBP,41501,EN,PT,United Kingdom,S,United Kingdom,50,"SQL, Docker, Hadoop, GCP, Azure",Master,0,Retail,2024-11-01,2024-12-28,1928,8.9,Digital Transformation LLC +AI08901,Data Engineer,118965,CHF,107069,MI,FT,Switzerland,M,Switzerland,0,"SQL, Scala, PyTorch, TensorFlow",Master,4,Finance,2024-11-08,2024-12-10,1082,5.3,TechCorp Inc +AI08902,ML Ops Engineer,59325,EUR,50426,EN,PT,France,M,France,0,"Data Visualization, Git, Computer Vision",Bachelor,0,Retail,2024-03-24,2024-04-26,2308,8.2,DataVision Ltd +AI08903,AI Research Scientist,79037,EUR,67181,MI,FT,Austria,M,United Kingdom,0,"Tableau, R, Deep Learning, Computer Vision, Azure",PhD,3,Healthcare,2025-03-29,2025-05-20,566,8.8,Digital Transformation LLC +AI08904,Computer Vision Engineer,149385,EUR,126977,EX,FT,Austria,L,Belgium,50,"Python, TensorFlow, Git, Spark",Bachelor,15,Real Estate,2024-06-18,2024-07-05,586,6.5,Neural Networks Co +AI08905,AI Product Manager,76318,EUR,64870,MI,CT,Austria,M,Austria,100,"Python, Computer Vision, Linux",PhD,2,Government,2024-03-15,2024-05-03,1441,6.9,DeepTech Ventures +AI08906,Research Scientist,189385,AUD,255670,EX,FT,Australia,M,Australia,50,"Hadoop, GCP, Tableau, Java, Azure",Master,18,Transportation,2024-04-17,2024-05-05,1029,6.1,Cognitive Computing +AI08907,Autonomous Systems Engineer,130219,EUR,110686,SE,CT,Germany,M,Germany,100,"Python, SQL, Java",PhD,9,Government,2024-09-01,2024-11-04,1562,5.4,Smart Analytics +AI08908,NLP Engineer,150596,JPY,16565560,EX,CT,Japan,S,Japan,0,"TensorFlow, Hadoop, SQL, Scala, Python",Associate,16,Education,2024-03-14,2024-05-07,1265,8.4,Digital Transformation LLC +AI08909,Head of AI,144363,USD,144363,EX,PT,Sweden,S,Kenya,0,"Mathematics, Deep Learning, R, SQL, Linux",Master,14,Media,2024-05-19,2024-06-29,1823,7.6,Digital Transformation LLC +AI08910,AI Software Engineer,21072,USD,21072,EN,FT,India,L,India,100,"Kubernetes, GCP, NLP, MLOps",Bachelor,1,Technology,2024-12-15,2025-01-26,905,6.9,Future Systems +AI08911,ML Ops Engineer,186827,USD,186827,EX,FT,Israel,S,Israel,0,"Java, TensorFlow, NLP, Mathematics, PyTorch",Associate,14,Retail,2024-05-12,2024-06-03,1583,6.1,Machine Intelligence Group +AI08912,Principal Data Scientist,143167,USD,143167,SE,PT,South Korea,L,South Korea,100,"PyTorch, Python, NLP",Associate,9,Education,2025-01-19,2025-02-13,1955,8.8,Quantum Computing Inc +AI08913,ML Ops Engineer,128988,USD,128988,SE,CT,Israel,M,Estonia,100,"PyTorch, Data Visualization, Linux, MLOps",PhD,6,Government,2024-09-08,2024-11-01,960,6.1,Quantum Computing Inc +AI08914,Deep Learning Engineer,276188,EUR,234760,EX,FL,Germany,L,Germany,50,"GCP, Git, Data Visualization",Associate,13,Finance,2024-08-23,2024-10-28,1647,8.1,Digital Transformation LLC +AI08915,Autonomous Systems Engineer,41148,USD,41148,MI,PT,India,L,Portugal,100,"SQL, Hadoop, PyTorch, Docker, Git",Master,2,Consulting,2024-10-21,2024-12-28,2149,9.3,TechCorp Inc +AI08916,AI Consultant,79365,USD,79365,EX,FT,India,M,Czech Republic,0,"Data Visualization, Git, R",Master,10,Media,2025-03-02,2025-05-09,2308,5.8,TechCorp Inc +AI08917,Data Scientist,60786,USD,60786,EX,FL,India,M,India,100,"TensorFlow, PyTorch, Linux, Statistics",PhD,17,Manufacturing,2024-06-09,2024-07-14,1544,9.1,Cloud AI Solutions +AI08918,ML Ops Engineer,85296,USD,85296,MI,CT,Finland,S,India,100,"Deep Learning, Data Visualization, Python, Hadoop",PhD,3,Finance,2024-11-10,2024-12-17,2034,7.6,Future Systems +AI08919,Computer Vision Engineer,111246,SGD,144620,MI,FT,Singapore,L,Singapore,50,"Docker, Java, Data Visualization, Azure",Master,2,Consulting,2024-12-09,2025-01-03,1316,9.1,Cognitive Computing +AI08920,Robotics Engineer,89925,USD,89925,MI,PT,Ireland,L,Ireland,100,"Tableau, MLOps, Kubernetes, Hadoop, Computer Vision",PhD,2,Gaming,2024-12-27,2025-01-10,2334,6.3,AI Innovations +AI08921,Computer Vision Engineer,90696,USD,90696,MI,PT,United States,M,Israel,100,"Deep Learning, Statistics, Git, Kubernetes, NLP",Associate,2,Media,2024-08-23,2024-09-27,2447,6.3,Smart Analytics +AI08922,Robotics Engineer,131512,AUD,177541,SE,PT,Australia,S,Australia,0,"PyTorch, Scala, Spark, Deep Learning, Azure",Associate,8,Technology,2024-07-25,2024-09-13,1710,9.6,Cloud AI Solutions +AI08923,AI Product Manager,198409,AUD,267852,EX,CT,Australia,S,Australia,50,"PyTorch, GCP, MLOps, Spark",PhD,15,Healthcare,2025-04-26,2025-06-15,710,9.5,Autonomous Tech +AI08924,Data Analyst,157473,USD,157473,SE,FT,Sweden,L,Sweden,0,"Deep Learning, Tableau, R, NLP",Master,6,Finance,2024-10-24,2024-12-04,1694,7.5,Algorithmic Solutions +AI08925,NLP Engineer,126003,EUR,107103,SE,FL,France,M,France,0,"Java, Statistics, Spark, Computer Vision, TensorFlow",Bachelor,7,Energy,2024-08-04,2024-09-21,703,5.6,DeepTech Ventures +AI08926,AI Research Scientist,119850,USD,119850,SE,FT,South Korea,M,South Korea,0,"MLOps, Linux, Scala",Associate,5,Education,2024-03-29,2024-05-03,2346,9.8,DataVision Ltd +AI08927,AI Specialist,95591,CHF,86032,EN,FL,Switzerland,M,Ireland,100,"TensorFlow, PyTorch, Docker",Bachelor,1,Healthcare,2024-05-18,2024-06-03,618,8.3,TechCorp Inc +AI08928,Data Scientist,73865,GBP,55399,EN,PT,United Kingdom,M,United Kingdom,100,"Java, R, Kubernetes, Git",PhD,0,Transportation,2024-06-13,2024-07-26,2249,5.5,DeepTech Ventures +AI08929,Principal Data Scientist,71155,GBP,53366,EN,CT,United Kingdom,S,United Kingdom,0,"Java, PyTorch, NLP",PhD,0,Education,2025-01-05,2025-01-21,2184,8.6,DeepTech Ventures +AI08930,Robotics Engineer,69945,SGD,90929,MI,FL,Singapore,S,Singapore,50,"Scala, Kubernetes, Docker, Java",Associate,2,Real Estate,2024-08-15,2024-10-07,1353,9.3,Cognitive Computing +AI08931,Computer Vision Engineer,24897,USD,24897,EN,CT,China,M,China,100,"GCP, Azure, AWS",Master,0,Manufacturing,2025-04-01,2025-05-01,1147,5.1,DataVision Ltd +AI08932,Research Scientist,67162,AUD,90669,EN,FL,Australia,L,Australia,100,"Scala, Statistics, Java",Associate,0,Government,2024-08-29,2024-10-24,1973,9.2,Cloud AI Solutions +AI08933,Principal Data Scientist,57928,GBP,43446,EN,PT,United Kingdom,S,United Kingdom,50,"Java, Git, Python",PhD,1,Manufacturing,2024-02-27,2024-04-21,526,7.1,Machine Intelligence Group +AI08934,Autonomous Systems Engineer,153211,CHF,137890,MI,PT,Switzerland,M,Switzerland,50,"TensorFlow, Linux, Mathematics, Kubernetes",Bachelor,4,Transportation,2024-04-30,2024-06-21,891,8.8,Future Systems +AI08935,AI Software Engineer,111274,USD,111274,MI,CT,Denmark,S,Denmark,100,"AWS, Hadoop, Scala",Associate,2,Automotive,2024-09-20,2024-11-19,2435,8.2,Smart Analytics +AI08936,AI Specialist,119212,USD,119212,SE,CT,Israel,M,Kenya,50,"Kubernetes, Azure, Scala, SQL",Associate,5,Telecommunications,2025-03-24,2025-05-03,952,5.4,Neural Networks Co +AI08937,AI Software Engineer,167862,USD,167862,EX,FL,Israel,S,Israel,50,"Mathematics, Spark, NLP, R, Python",Bachelor,15,Automotive,2024-05-17,2024-06-03,622,9.8,Neural Networks Co +AI08938,AI Research Scientist,73151,EUR,62178,MI,PT,Germany,M,Finland,100,"Deep Learning, SQL, PyTorch, AWS",Master,4,Retail,2024-10-06,2024-10-26,1228,9.5,Cloud AI Solutions +AI08939,Research Scientist,159226,CHF,143303,MI,FT,Switzerland,L,China,0,"Linux, MLOps, Data Visualization",Master,4,Gaming,2024-05-26,2024-07-29,794,8.2,Future Systems +AI08940,AI Software Engineer,62380,USD,62380,EN,PT,Ireland,M,Romania,0,"Scala, Kubernetes, SQL, MLOps, Spark",PhD,1,Healthcare,2025-03-02,2025-03-28,1960,6.9,AI Innovations +AI08941,AI Product Manager,113996,JPY,12539560,SE,FL,Japan,M,Japan,50,"AWS, Linux, Java, Hadoop",Master,9,Consulting,2025-01-10,2025-03-06,2463,8.9,DeepTech Ventures +AI08942,NLP Engineer,51094,USD,51094,EN,CT,Ireland,M,Ireland,0,"NLP, MLOps, Statistics",Bachelor,1,Gaming,2025-04-21,2025-05-29,2239,9,TechCorp Inc +AI08943,AI Specialist,69394,USD,69394,EN,FT,Israel,L,Israel,100,"Kubernetes, Python, MLOps, Azure",PhD,1,Automotive,2025-01-08,2025-02-09,571,5.3,Future Systems +AI08944,AI Specialist,105999,CHF,95399,EN,PT,Switzerland,L,Ghana,50,"R, GCP, Hadoop, Kubernetes",Master,0,Consulting,2024-12-04,2025-02-09,1844,8,DeepTech Ventures +AI08945,ML Ops Engineer,99978,EUR,84981,SE,CT,Austria,M,Italy,0,"Kubernetes, NLP, Git, Mathematics, Hadoop",Associate,8,Energy,2025-04-29,2025-05-26,2222,8.3,DeepTech Ventures +AI08946,Data Scientist,52184,USD,52184,EN,FL,South Korea,L,South Korea,50,"SQL, Hadoop, GCP",Bachelor,0,Retail,2024-05-22,2024-06-15,1923,8.4,Digital Transformation LLC +AI08947,Data Scientist,76210,EUR,64779,MI,FL,Germany,M,Germany,50,"Java, Kubernetes, Data Visualization, NLP",PhD,2,Transportation,2024-02-02,2024-03-29,977,5.7,Predictive Systems +AI08948,AI Product Manager,67505,USD,67505,MI,FT,Israel,S,Israel,0,"PyTorch, TensorFlow, Data Visualization, Kubernetes, AWS",Bachelor,4,Consulting,2024-11-02,2024-12-17,1324,9.8,Digital Transformation LLC +AI08949,Robotics Engineer,70420,USD,70420,MI,PT,Israel,S,India,100,"Python, Scala, MLOps, AWS, NLP",PhD,4,Manufacturing,2025-01-22,2025-03-06,1191,8,Machine Intelligence Group +AI08950,AI Consultant,23683,USD,23683,EN,CT,India,L,India,50,"R, Kubernetes, Git",Master,0,Education,2024-08-04,2024-10-12,1085,8.9,Quantum Computing Inc +AI08951,Computer Vision Engineer,120220,USD,120220,MI,PT,United States,M,United States,0,"Python, Scala, Computer Vision, SQL",PhD,3,Telecommunications,2024-09-26,2024-12-01,785,5.1,Advanced Robotics +AI08952,AI Software Engineer,185311,USD,185311,EX,PT,Finland,M,Finland,50,"Hadoop, GCP, NLP, AWS, Tableau",PhD,15,Gaming,2024-09-07,2024-10-11,1773,8.5,Smart Analytics +AI08953,Robotics Engineer,140225,EUR,119191,SE,CT,Netherlands,S,Netherlands,0,"SQL, Kubernetes, Mathematics, Linux, Deep Learning",Associate,6,Real Estate,2024-04-23,2024-06-01,755,8,TechCorp Inc +AI08954,AI Specialist,126983,USD,126983,SE,FL,Israel,L,Israel,0,"Kubernetes, SQL, PyTorch, Git",PhD,9,Telecommunications,2024-12-09,2025-02-12,2196,5.3,AI Innovations +AI08955,Head of AI,198792,USD,198792,EX,FL,Finland,L,Thailand,50,"Git, PyTorch, R",Associate,11,Manufacturing,2024-05-09,2024-07-02,1864,8.1,Autonomous Tech +AI08956,AI Consultant,84341,EUR,71690,MI,FL,Austria,L,Austria,50,"Spark, Hadoop, Azure, Tableau",Bachelor,3,Finance,2024-09-29,2024-12-05,1673,6.8,Advanced Robotics +AI08957,Principal Data Scientist,59341,EUR,50440,EN,FT,Netherlands,M,Netherlands,50,"MLOps, Java, R",Associate,1,Healthcare,2024-04-22,2024-06-02,2363,7.2,Digital Transformation LLC +AI08958,Machine Learning Engineer,26028,USD,26028,MI,FT,India,M,India,0,"R, MLOps, SQL",Bachelor,3,Finance,2024-01-06,2024-02-17,991,6.9,TechCorp Inc +AI08959,AI Architect,146559,JPY,16121490,SE,PT,Japan,L,Denmark,100,"Azure, Hadoop, Python",Bachelor,9,Real Estate,2025-04-18,2025-05-11,550,9.9,Future Systems +AI08960,NLP Engineer,258425,USD,258425,EX,FT,Denmark,M,Mexico,100,"SQL, Deep Learning, AWS, Kubernetes, Mathematics",Master,12,Education,2024-07-28,2024-08-17,964,8.4,Neural Networks Co +AI08961,AI Research Scientist,158120,EUR,134402,SE,FT,Netherlands,L,South Korea,50,"Data Visualization, PyTorch, Kubernetes, Statistics",PhD,7,Real Estate,2024-09-22,2024-11-04,953,7.7,Algorithmic Solutions +AI08962,AI Specialist,77719,USD,77719,EN,CT,United States,M,United States,0,"Azure, Spark, Tableau, NLP",Master,0,Media,2024-07-29,2024-08-27,2030,6.2,Cognitive Computing +AI08963,AI Specialist,28039,USD,28039,EN,PT,China,S,China,0,"AWS, Tableau, Computer Vision, Hadoop, NLP",Master,0,Automotive,2024-08-24,2024-10-09,636,8.7,TechCorp Inc +AI08964,Robotics Engineer,96472,SGD,125414,MI,FT,Singapore,M,Ireland,50,"Python, SQL, GCP",Master,2,Government,2024-06-12,2024-07-20,724,8,Cloud AI Solutions +AI08965,Principal Data Scientist,89844,USD,89844,SE,PT,South Korea,M,Singapore,0,"Computer Vision, Hadoop, AWS, Scala, Spark",Bachelor,5,Finance,2024-02-05,2024-04-16,1977,7.1,Quantum Computing Inc +AI08966,AI Research Scientist,79472,SGD,103314,EN,PT,Singapore,L,Nigeria,0,"Scala, Kubernetes, MLOps, NLP, Mathematics",Bachelor,0,Gaming,2025-02-12,2025-02-28,1571,7,Predictive Systems +AI08967,AI Product Manager,92695,USD,92695,MI,PT,South Korea,L,South Korea,100,"Python, Docker, GCP, TensorFlow",Master,3,Government,2025-04-29,2025-06-19,802,5.6,Quantum Computing Inc +AI08968,NLP Engineer,105477,JPY,11602470,MI,PT,Japan,M,South Africa,0,"Spark, Deep Learning, Mathematics",PhD,2,Finance,2025-03-28,2025-04-16,1334,5.1,Algorithmic Solutions +AI08969,AI Consultant,59744,USD,59744,EN,FT,Finland,S,Finland,100,"Mathematics, Data Visualization, PyTorch, MLOps",Master,0,Consulting,2025-01-11,2025-03-23,1224,6.8,Neural Networks Co +AI08970,NLP Engineer,75054,JPY,8255940,EN,PT,Japan,M,Israel,0,"Data Visualization, Git, R, Scala",Master,0,Technology,2024-01-07,2024-01-26,1701,6.7,Smart Analytics +AI08971,AI Product Manager,75503,USD,75503,MI,FT,South Korea,M,South Korea,100,"Scala, Java, Data Visualization, Git",Associate,4,Education,2024-10-01,2024-10-25,1856,5.5,Cognitive Computing +AI08972,AI Specialist,86929,USD,86929,MI,FT,Israel,L,Israel,100,"R, Deep Learning, Spark",PhD,4,Technology,2024-03-16,2024-04-11,918,8.8,Predictive Systems +AI08973,Data Scientist,80667,EUR,68567,MI,FL,France,L,France,0,"TensorFlow, AWS, Statistics, Mathematics, Spark",Bachelor,4,Real Estate,2024-09-17,2024-10-20,1916,5.3,Predictive Systems +AI08974,Robotics Engineer,142450,USD,142450,EX,FT,South Korea,S,South Korea,50,"R, Scala, Python",Master,11,Education,2025-01-19,2025-03-27,2181,9,DataVision Ltd +AI08975,AI Software Engineer,145577,USD,145577,EX,FL,Ireland,S,Ireland,50,"Scala, Tableau, Spark, Statistics",Bachelor,11,Telecommunications,2024-07-19,2024-08-19,1784,7.6,Machine Intelligence Group +AI08976,Principal Data Scientist,138782,CHF,124904,MI,FT,Switzerland,L,Switzerland,100,"PyTorch, Git, GCP",Associate,2,Government,2024-04-10,2024-06-14,1512,5.7,Digital Transformation LLC +AI08977,Data Scientist,148776,AUD,200848,SE,FL,Australia,M,Australia,100,"R, Tableau, Python, Statistics",PhD,8,Gaming,2025-01-15,2025-03-21,1573,9.5,DeepTech Ventures +AI08978,Data Engineer,150654,USD,150654,MI,PT,Norway,L,Thailand,100,"AWS, Computer Vision, Data Visualization, R",Bachelor,4,Consulting,2024-02-29,2024-03-27,760,7.4,Advanced Robotics +AI08979,AI Consultant,262984,USD,262984,EX,CT,Ireland,L,Ireland,0,"Linux, Java, Spark, Scala, Computer Vision",Bachelor,11,Transportation,2024-12-06,2025-01-22,2032,5.7,Neural Networks Co +AI08980,AI Specialist,82698,GBP,62024,MI,CT,United Kingdom,S,United Kingdom,50,"Docker, Data Visualization, Spark",Master,2,Consulting,2025-03-22,2025-05-04,1128,5.7,Neural Networks Co +AI08981,Robotics Engineer,78355,GBP,58766,MI,FT,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, Statistics, Computer Vision",Master,3,Automotive,2024-02-22,2024-04-23,1032,7,Machine Intelligence Group +AI08982,AI Product Manager,83880,EUR,71298,MI,FL,France,L,France,100,"Hadoop, PyTorch, Tableau, TensorFlow, NLP",PhD,2,Technology,2024-08-08,2024-09-19,1316,9.3,Cloud AI Solutions +AI08983,Data Analyst,67262,GBP,50447,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Scala, R",Master,0,Automotive,2024-06-07,2024-07-05,1330,7.3,Predictive Systems +AI08984,Computer Vision Engineer,65253,USD,65253,SE,FT,China,M,China,0,"NLP, TensorFlow, Spark",Bachelor,5,Consulting,2025-03-22,2025-05-21,882,7.4,AI Innovations +AI08985,ML Ops Engineer,100727,USD,100727,SE,PT,Israel,S,Israel,0,"Tableau, TensorFlow, GCP, Statistics",Master,5,Automotive,2024-01-23,2024-02-23,2081,6,Cloud AI Solutions +AI08986,Principal Data Scientist,201256,CAD,251570,EX,CT,Canada,S,Italy,0,"Azure, Python, Computer Vision",Master,17,Media,2025-03-15,2025-05-14,999,6.2,DataVision Ltd +AI08987,Deep Learning Engineer,98333,CHF,88500,EN,CT,Switzerland,S,Poland,100,"GCP, R, SQL, Statistics, Data Visualization",Bachelor,1,Healthcare,2024-10-04,2024-10-27,1743,6.8,Cognitive Computing +AI08988,AI Product Manager,238048,GBP,178536,EX,CT,United Kingdom,S,Switzerland,100,"Scala, R, Computer Vision, Kubernetes",PhD,19,Automotive,2024-11-09,2024-12-01,696,8,Algorithmic Solutions +AI08989,Computer Vision Engineer,111723,USD,111723,SE,PT,South Korea,S,Ukraine,0,"R, Statistics, Computer Vision, GCP",PhD,6,Transportation,2024-06-15,2024-08-23,909,9.7,Autonomous Tech +AI08990,ML Ops Engineer,62271,EUR,52930,EN,FL,Germany,S,Germany,50,"Linux, R, Git, Hadoop, Docker",Associate,0,Manufacturing,2024-08-25,2024-11-02,1742,7.1,TechCorp Inc +AI08991,Machine Learning Researcher,186844,CAD,233555,EX,FL,Canada,L,Canada,100,"Kubernetes, Statistics, Mathematics, Linux, Java",Associate,18,Retail,2024-08-26,2024-10-11,1541,9.1,Machine Intelligence Group +AI08992,AI Software Engineer,151803,USD,151803,SE,FL,United States,S,United States,0,"Computer Vision, Data Visualization, R, NLP, Deep Learning",Master,9,Manufacturing,2024-07-07,2024-07-25,2344,8,Neural Networks Co +AI08993,AI Product Manager,86780,USD,86780,MI,FL,Norway,S,Estonia,50,"Kubernetes, NLP, SQL",Associate,3,Telecommunications,2024-05-26,2024-06-22,2178,9,Quantum Computing Inc +AI08994,Deep Learning Engineer,92335,USD,92335,EN,FT,Ireland,L,Ireland,100,"AWS, Kubernetes, SQL, Scala",Bachelor,0,Retail,2024-09-08,2024-10-31,1318,8,Algorithmic Solutions +AI08995,Data Analyst,79908,USD,79908,MI,CT,South Korea,L,South Korea,100,"Hadoop, GCP, Computer Vision, Mathematics",Master,4,Technology,2024-06-21,2024-07-17,597,5.5,Autonomous Tech +AI08996,AI Consultant,139660,USD,139660,MI,CT,Denmark,L,Denmark,100,"Deep Learning, Python, MLOps",Master,4,Government,2025-02-01,2025-04-13,2451,6.1,Cognitive Computing +AI08997,Head of AI,55908,CAD,69885,EN,FL,Canada,S,Canada,50,"Linux, SQL, MLOps, Mathematics, Spark",PhD,0,Technology,2025-01-31,2025-03-22,1148,6.3,Cognitive Computing +AI08998,Data Engineer,88659,EUR,75360,MI,CT,Austria,L,Austria,100,"AWS, R, NLP, Data Visualization, Tableau",Bachelor,4,Telecommunications,2024-03-05,2024-04-16,2403,7.5,Neural Networks Co +AI08999,Machine Learning Engineer,205613,USD,205613,SE,PT,Norway,L,Australia,100,"Deep Learning, TensorFlow, R",Bachelor,8,Real Estate,2024-10-01,2024-11-06,1407,5.6,Digital Transformation LLC +AI09000,AI Software Engineer,90371,EUR,76815,EN,FT,Germany,L,Germany,100,"Kubernetes, Java, Mathematics, Scala, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-12-06,1818,7.1,DeepTech Ventures +AI09001,Data Analyst,88134,USD,88134,EN,FT,Sweden,L,Sweden,100,"Hadoop, Git, Computer Vision",Associate,0,Automotive,2025-02-11,2025-03-15,587,7.3,Autonomous Tech +AI09002,Computer Vision Engineer,42049,USD,42049,EN,FT,South Korea,M,South Korea,50,"TensorFlow, Statistics, SQL, Git",Associate,1,Government,2024-08-30,2024-11-05,2280,9.8,Cognitive Computing +AI09003,AI Consultant,53035,USD,53035,SE,PT,India,M,India,50,"SQL, Computer Vision, Tableau",PhD,8,Media,2024-03-28,2024-06-01,2121,9.3,Advanced Robotics +AI09004,Autonomous Systems Engineer,24765,USD,24765,EN,FL,India,S,India,100,"Docker, Python, Mathematics, Kubernetes",PhD,1,Energy,2024-12-11,2024-12-28,1299,10,Quantum Computing Inc +AI09005,Data Analyst,162474,USD,162474,SE,FT,Denmark,S,Colombia,100,"Computer Vision, R, Scala",Master,5,Transportation,2024-04-30,2024-06-30,1769,6.3,Predictive Systems +AI09006,Computer Vision Engineer,156947,USD,156947,EX,FT,Finland,M,Finland,100,"Mathematics, AWS, Deep Learning, Computer Vision",PhD,15,Transportation,2024-07-29,2024-10-05,820,7.6,Neural Networks Co +AI09007,Deep Learning Engineer,174776,USD,174776,EX,CT,Ireland,M,Ireland,50,"Computer Vision, GCP, Scala, Linux, PyTorch",Master,13,Real Estate,2024-08-16,2024-09-27,652,6.6,Future Systems +AI09008,AI Architect,70304,USD,70304,MI,FT,South Korea,L,South Korea,0,"Java, AWS, Tableau",Associate,3,Technology,2024-09-26,2024-11-04,610,9.5,Quantum Computing Inc +AI09009,ML Ops Engineer,172841,USD,172841,EX,PT,Israel,S,Israel,100,"Spark, PyTorch, Git",Master,16,Government,2024-06-24,2024-08-07,2356,8.7,Autonomous Tech +AI09010,AI Software Engineer,130736,EUR,111126,SE,FL,Austria,L,Austria,100,"Spark, R, Hadoop, Statistics, SQL",Master,6,Education,2024-04-28,2024-06-21,1538,9.1,Machine Intelligence Group +AI09011,AI Research Scientist,250854,EUR,213226,EX,PT,Austria,L,Austria,0,"Deep Learning, Kubernetes, Python, Git",PhD,17,Manufacturing,2025-03-10,2025-04-15,2094,6.8,TechCorp Inc +AI09012,AI Consultant,143001,SGD,185901,SE,PT,Singapore,L,Singapore,100,"MLOps, Java, Python, Computer Vision, Docker",Master,7,Healthcare,2024-02-08,2024-03-15,935,6.8,Future Systems +AI09013,AI Product Manager,248777,USD,248777,EX,FL,Sweden,M,Sweden,100,"Tableau, PyTorch, Docker, GCP, TensorFlow",Associate,11,Finance,2024-03-09,2024-04-05,1927,9.3,Future Systems +AI09014,AI Software Engineer,287219,SGD,373385,EX,FL,Singapore,L,Netherlands,50,"AWS, Scala, Mathematics, GCP, Docker",Bachelor,11,Transportation,2024-03-18,2024-05-26,1759,5.1,Autonomous Tech +AI09015,NLP Engineer,116645,USD,116645,MI,CT,Norway,S,Norway,100,"NLP, SQL, Tableau, AWS",Associate,2,Telecommunications,2024-09-28,2024-11-28,1035,10,Future Systems +AI09016,AI Product Manager,52061,USD,52061,EN,FL,South Korea,L,South Korea,100,"Computer Vision, SQL, Kubernetes, Git",PhD,0,Gaming,2024-05-10,2024-07-21,1489,7.8,Cloud AI Solutions +AI09017,AI Architect,104358,EUR,88704,SE,PT,France,S,Philippines,100,"Linux, R, Spark",Associate,5,Media,2024-12-07,2025-02-14,2437,6.8,DeepTech Ventures +AI09018,Machine Learning Engineer,64123,USD,64123,SE,PT,China,S,United States,50,"Computer Vision, Spark, Tableau",Master,7,Real Estate,2024-06-28,2024-08-14,715,7.3,Advanced Robotics +AI09019,AI Specialist,149941,USD,149941,SE,FT,Sweden,L,Ukraine,100,"Hadoop, SQL, TensorFlow, Spark",PhD,6,Gaming,2024-11-13,2024-12-14,1278,5.6,TechCorp Inc +AI09020,Deep Learning Engineer,56400,CAD,70500,EN,FL,Canada,M,Canada,50,"Tableau, NLP, PyTorch, Kubernetes",PhD,0,Technology,2024-01-08,2024-03-12,1632,8.3,DataVision Ltd +AI09021,AI Research Scientist,95750,USD,95750,SE,CT,Ireland,S,Thailand,0,"Docker, Python, Kubernetes, MLOps, Mathematics",Bachelor,6,Real Estate,2024-12-21,2025-01-08,2016,9.2,Predictive Systems +AI09022,AI Research Scientist,64039,EUR,54433,EN,FL,Germany,M,Germany,100,"SQL, Deep Learning, Git, PyTorch",PhD,0,Government,2025-03-24,2025-05-01,778,7.7,Cognitive Computing +AI09023,Data Engineer,56110,EUR,47694,EN,FL,Germany,M,Ireland,50,"Azure, Tableau, TensorFlow, Data Visualization, Deep Learning",PhD,1,Telecommunications,2024-12-23,2025-02-01,1111,7,Future Systems +AI09024,AI Specialist,124462,USD,124462,MI,PT,Denmark,S,Denmark,50,"NLP, AWS, Computer Vision, Python",Associate,4,Energy,2025-03-29,2025-05-26,1940,7.4,Neural Networks Co +AI09025,AI Consultant,190189,EUR,161661,EX,PT,Austria,M,Brazil,50,"Scala, Hadoop, Java, Linux",Master,11,Government,2024-02-21,2024-03-29,1380,9.4,Neural Networks Co +AI09026,AI Research Scientist,110339,USD,110339,SE,FL,United States,S,United States,100,"Kubernetes, PyTorch, TensorFlow, Python",Associate,9,Retail,2024-08-29,2024-10-12,1207,6.2,Quantum Computing Inc +AI09027,Data Engineer,198685,USD,198685,EX,CT,Israel,M,Israel,0,"MLOps, TensorFlow, Kubernetes",PhD,18,Retail,2024-09-11,2024-10-07,2290,8.6,Algorithmic Solutions +AI09028,Robotics Engineer,118424,USD,118424,MI,CT,United States,M,Egypt,100,"Statistics, NLP, Deep Learning",Master,4,Healthcare,2024-04-11,2024-05-28,1308,9.3,TechCorp Inc +AI09029,Research Scientist,77664,CHF,69898,EN,PT,Switzerland,M,Canada,50,"Azure, Spark, Python, MLOps, Computer Vision",Associate,0,Consulting,2024-09-09,2024-11-21,2200,5.3,Future Systems +AI09030,Research Scientist,60040,USD,60040,EN,FL,Israel,M,Israel,0,"Docker, Python, Azure, Hadoop, Deep Learning",Master,1,Education,2024-12-03,2025-01-08,1776,6.9,Machine Intelligence Group +AI09031,NLP Engineer,79791,USD,79791,EN,FL,Denmark,L,Denmark,100,"TensorFlow, Java, Scala, Statistics",Associate,0,Retail,2024-11-20,2024-12-10,1808,9.2,DeepTech Ventures +AI09032,AI Product Manager,124008,USD,124008,MI,FT,Denmark,L,Denmark,50,"GCP, Java, TensorFlow, Deep Learning, Computer Vision",Associate,2,Gaming,2024-02-13,2024-04-16,741,7.2,Cognitive Computing +AI09033,AI Consultant,35031,USD,35031,MI,FT,India,S,India,50,"Java, Mathematics, Deep Learning, Data Visualization, TensorFlow",Associate,4,Energy,2024-12-23,2025-02-18,699,7.6,AI Innovations +AI09034,Head of AI,67240,USD,67240,EN,FL,Norway,S,Norway,0,"AWS, Scala, Data Visualization",Bachelor,0,Education,2024-06-23,2024-08-27,1817,9.8,Quantum Computing Inc +AI09035,AI Specialist,94732,USD,94732,SE,PT,South Korea,M,South Korea,100,"Statistics, R, Deep Learning",PhD,8,Energy,2024-05-05,2024-05-21,1209,9.9,Advanced Robotics +AI09036,Autonomous Systems Engineer,129130,CHF,116217,MI,FT,Switzerland,L,Belgium,0,"Kubernetes, Java, AWS, Azure",Associate,3,Energy,2025-03-16,2025-05-07,1250,5.6,DataVision Ltd +AI09037,Data Analyst,228742,EUR,194431,EX,CT,Austria,L,Chile,50,"PyTorch, SQL, Java",PhD,19,Transportation,2025-04-19,2025-05-31,1839,5.5,DataVision Ltd +AI09038,Machine Learning Engineer,96859,SGD,125917,MI,FL,Singapore,M,Singapore,100,"Kubernetes, SQL, Deep Learning, Hadoop, PyTorch",Master,4,Education,2024-08-17,2024-10-14,2037,9,Machine Intelligence Group +AI09039,AI Software Engineer,86548,JPY,9520280,EN,FL,Japan,L,Japan,0,"TensorFlow, Spark, NLP, PyTorch, Data Visualization",Associate,1,Education,2024-04-29,2024-05-30,2115,5.4,DataVision Ltd +AI09040,Deep Learning Engineer,145427,EUR,123613,SE,CT,France,L,France,0,"Git, Spark, Computer Vision",Associate,9,Telecommunications,2024-01-10,2024-01-30,1730,7.9,AI Innovations +AI09041,Head of AI,144726,USD,144726,SE,FL,South Korea,L,South Korea,0,"Computer Vision, AWS, Docker, PyTorch, Hadoop",Associate,7,Healthcare,2024-04-17,2024-06-28,2490,6.8,Neural Networks Co +AI09042,Data Scientist,118275,USD,118275,MI,FL,Finland,L,France,100,"R, Linux, Computer Vision",Master,2,Real Estate,2024-09-11,2024-11-04,556,7.7,Algorithmic Solutions +AI09043,Head of AI,90563,CHF,81507,EN,FL,Switzerland,L,Switzerland,100,"Git, Linux, AWS, Statistics, Hadoop",Bachelor,0,Healthcare,2024-09-14,2024-11-16,1631,7.9,Quantum Computing Inc +AI09044,Head of AI,107754,USD,107754,SE,PT,South Korea,S,South Korea,100,"Python, Scala, Linux",Master,9,Energy,2024-08-20,2024-09-20,1052,8.4,Cognitive Computing +AI09045,AI Research Scientist,63613,USD,63613,EN,FT,Sweden,S,Sweden,50,"Linux, PyTorch, TensorFlow",Bachelor,1,Finance,2024-04-23,2024-06-13,2070,5.3,Neural Networks Co +AI09046,Research Scientist,185435,USD,185435,EX,CT,Ireland,M,Canada,0,"Spark, Docker, Python",Bachelor,15,Technology,2024-09-11,2024-10-08,1991,8.2,Advanced Robotics +AI09047,Autonomous Systems Engineer,46410,USD,46410,SE,PT,India,M,India,0,"Scala, Spark, Git, Azure",Associate,9,Energy,2024-08-19,2024-09-09,1622,6.3,Smart Analytics +AI09048,ML Ops Engineer,143416,USD,143416,EX,PT,Sweden,S,Sweden,100,"MLOps, R, Computer Vision",PhD,18,Real Estate,2024-11-09,2024-12-08,2151,5.3,Digital Transformation LLC +AI09049,AI Consultant,76825,USD,76825,EN,CT,Norway,S,Norway,100,"Computer Vision, R, SQL, Linux, Docker",Associate,0,Real Estate,2024-04-05,2024-06-02,1986,5.8,Digital Transformation LLC +AI09050,NLP Engineer,198466,CHF,178619,SE,FL,Switzerland,M,Switzerland,0,"SQL, Tableau, Computer Vision, MLOps",Bachelor,7,Government,2024-04-26,2024-07-05,716,9.7,Future Systems +AI09051,Data Analyst,130066,CHF,117059,MI,CT,Switzerland,S,Switzerland,50,"Mathematics, Hadoop, Python",Master,2,Education,2024-06-02,2024-07-05,916,7.7,Advanced Robotics +AI09052,AI Specialist,112733,EUR,95823,MI,FL,Germany,L,Germany,50,"AWS, Git, PyTorch",PhD,4,Government,2024-03-13,2024-05-14,2111,6.3,Quantum Computing Inc +AI09053,Data Scientist,46914,USD,46914,EN,PT,Finland,S,United States,100,"Python, Linux, Spark, Deep Learning",Master,1,Finance,2024-02-26,2024-03-27,2063,5.8,Smart Analytics +AI09054,AI Specialist,275297,USD,275297,EX,FL,Israel,L,Vietnam,50,"Tableau, Python, Kubernetes, Computer Vision",Associate,19,Transportation,2025-01-22,2025-04-03,2364,7.2,Cloud AI Solutions +AI09055,AI Product Manager,161001,GBP,120751,EX,PT,United Kingdom,S,United Kingdom,50,"Deep Learning, Azure, Kubernetes, Java, SQL",Bachelor,10,Technology,2024-03-16,2024-04-11,1985,9.6,Algorithmic Solutions +AI09056,Data Analyst,73717,SGD,95832,EN,PT,Singapore,M,Ukraine,0,"Python, Hadoop, Data Visualization",Master,0,Government,2025-03-05,2025-03-22,2321,8.3,Cognitive Computing +AI09057,Data Engineer,173430,AUD,234131,EX,FL,Australia,S,Indonesia,100,"Azure, Spark, Computer Vision",Associate,16,Media,2024-11-01,2024-12-24,1601,6.3,TechCorp Inc +AI09058,Data Analyst,289418,USD,289418,EX,FT,Sweden,L,Sweden,50,"Hadoop, Spark, TensorFlow, Linux",Associate,10,Healthcare,2024-07-13,2024-08-25,1193,5.4,AI Innovations +AI09059,Autonomous Systems Engineer,25689,USD,25689,MI,FL,India,M,India,0,"Scala, GCP, Tableau, Kubernetes, Java",Associate,4,Automotive,2024-05-19,2024-06-18,1208,9.6,TechCorp Inc +AI09060,Data Engineer,60503,USD,60503,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, Computer Vision, R, SQL",PhD,1,Transportation,2024-02-25,2024-03-17,2322,9.1,DataVision Ltd +AI09061,AI Architect,278853,USD,278853,EX,PT,Sweden,L,Sweden,50,"Python, Tableau, SQL",Associate,16,Manufacturing,2025-03-05,2025-05-04,1316,9.2,Machine Intelligence Group +AI09062,NLP Engineer,84797,EUR,72077,MI,CT,France,L,France,50,"TensorFlow, Python, Hadoop, Kubernetes",Bachelor,4,Real Estate,2025-04-08,2025-05-29,1787,5.1,TechCorp Inc +AI09063,Data Engineer,112505,EUR,95629,SE,FT,France,S,France,50,"Data Visualization, Scala, AWS, TensorFlow, Kubernetes",Associate,5,Healthcare,2024-05-19,2024-06-28,2296,6.5,DeepTech Ventures +AI09064,Autonomous Systems Engineer,322176,USD,322176,EX,FL,United States,L,United States,100,"Python, Hadoop, SQL",PhD,19,Finance,2024-09-04,2024-09-23,2234,9.4,Smart Analytics +AI09065,Machine Learning Engineer,153151,USD,153151,SE,PT,Sweden,L,Sweden,100,"SQL, Spark, MLOps, Data Visualization",Associate,9,Manufacturing,2024-08-26,2024-10-02,2125,7.7,Advanced Robotics +AI09066,AI Software Engineer,89864,USD,89864,EN,CT,Norway,L,Hungary,100,"Python, Docker, Tableau, AWS",PhD,0,Technology,2025-04-02,2025-04-19,2399,9.8,Digital Transformation LLC +AI09067,Data Scientist,103238,SGD,134209,MI,PT,Singapore,M,Japan,100,"Azure, Statistics, Hadoop, R",Master,3,Consulting,2025-01-26,2025-04-06,924,5.3,Autonomous Tech +AI09068,AI Specialist,62237,USD,62237,MI,FT,South Korea,S,Hungary,100,"Statistics, Tableau, SQL, Spark, Data Visualization",Master,4,Energy,2025-03-10,2025-04-13,1059,9.5,Autonomous Tech +AI09069,ML Ops Engineer,250692,EUR,213088,EX,FL,Netherlands,M,Netherlands,50,"Linux, GCP, Python, Mathematics, Azure",PhD,11,Healthcare,2024-12-11,2024-12-28,1030,8,Machine Intelligence Group +AI09070,ML Ops Engineer,75599,USD,75599,MI,PT,Ireland,M,South Africa,0,"Java, Kubernetes, Mathematics, SQL",Master,2,Consulting,2024-05-01,2024-07-12,1978,8.9,Advanced Robotics +AI09071,AI Product Manager,170126,CHF,153113,SE,FT,Switzerland,M,Switzerland,0,"Data Visualization, Statistics, NLP, MLOps",Associate,9,Healthcare,2024-03-14,2024-05-15,1405,5.6,Digital Transformation LLC +AI09072,Machine Learning Engineer,112438,EUR,95572,MI,CT,France,L,France,100,"Python, Statistics, AWS, Kubernetes, NLP",Master,4,Government,2024-04-26,2024-06-06,1829,9.3,DataVision Ltd +AI09073,AI Specialist,202327,USD,202327,EX,PT,Israel,M,Israel,0,"PyTorch, Linux, R",Associate,17,Retail,2024-05-20,2024-06-24,520,7.9,Quantum Computing Inc +AI09074,Head of AI,49609,EUR,42168,EN,CT,France,S,France,100,"Python, Java, NLP",Associate,1,Retail,2024-01-11,2024-03-08,1480,6.9,Machine Intelligence Group +AI09075,Data Analyst,101267,USD,101267,EX,FL,South Korea,S,Indonesia,100,"GCP, Azure, NLP, SQL, R",Bachelor,12,Retail,2024-05-01,2024-06-13,1534,8.8,DataVision Ltd +AI09076,Data Engineer,175412,EUR,149100,EX,FT,Germany,S,Germany,100,"Statistics, MLOps, Java",Associate,17,Manufacturing,2025-03-25,2025-05-04,2138,7.7,Cloud AI Solutions +AI09077,Robotics Engineer,132763,SGD,172592,SE,CT,Singapore,S,Singapore,50,"Hadoop, Tableau, R, Deep Learning",Associate,6,Manufacturing,2024-03-19,2024-05-10,1912,7.5,DeepTech Ventures +AI09078,Head of AI,146012,EUR,124110,EX,CT,Austria,S,United States,50,"Tableau, Linux, Java, R",Master,19,Retail,2025-02-15,2025-04-14,955,9.4,TechCorp Inc +AI09079,AI Architect,128830,USD,128830,SE,PT,Finland,S,Finland,0,"Python, TensorFlow, GCP, Java",Bachelor,9,Consulting,2024-01-15,2024-03-10,2249,6.9,AI Innovations +AI09080,Data Analyst,73935,EUR,62845,MI,PT,Germany,S,Germany,50,"PyTorch, Scala, MLOps",Master,2,Technology,2024-09-13,2024-11-07,1797,8.9,Cognitive Computing +AI09081,Machine Learning Researcher,20704,USD,20704,EN,FL,India,S,India,100,"Hadoop, Linux, GCP, Statistics",Master,0,Education,2024-02-22,2024-03-18,1935,5.9,Digital Transformation LLC +AI09082,AI Software Engineer,106038,USD,106038,EN,PT,United States,L,United States,50,"Spark, R, Deep Learning",Bachelor,1,Telecommunications,2024-03-24,2024-04-15,1621,5.5,Smart Analytics +AI09083,Machine Learning Researcher,256638,USD,256638,EX,FT,United States,L,United States,0,"Docker, Scala, Statistics, Data Visualization",Associate,18,Transportation,2024-04-13,2024-05-09,1801,9.7,DeepTech Ventures +AI09084,ML Ops Engineer,160139,CHF,144125,MI,FL,Switzerland,L,Japan,0,"Azure, Scala, NLP, Deep Learning, Git",Master,4,Automotive,2024-07-12,2024-09-06,1577,7.8,Smart Analytics +AI09085,Data Engineer,125643,USD,125643,MI,CT,United States,L,United States,100,"Linux, Mathematics, Deep Learning, Python, Statistics",Master,2,Media,2024-12-12,2025-02-05,2246,9.7,Machine Intelligence Group +AI09086,Research Scientist,33763,USD,33763,EN,FT,China,M,South Africa,50,"Java, Tableau, AWS, Scala, Linux",Associate,1,Automotive,2024-08-19,2024-09-26,1405,7.1,TechCorp Inc +AI09087,Computer Vision Engineer,51407,USD,51407,EN,PT,Sweden,M,Sweden,100,"Linux, Mathematics, SQL, MLOps",Associate,0,Gaming,2024-07-22,2024-09-28,1140,8.2,Autonomous Tech +AI09088,Data Scientist,93819,USD,93819,SE,FL,Finland,S,Finland,50,"Kubernetes, Java, MLOps, Scala, GCP",Bachelor,9,Manufacturing,2024-06-01,2024-06-18,1272,8.9,DataVision Ltd +AI09089,Data Engineer,108668,USD,108668,MI,PT,United States,S,United States,100,"Kubernetes, TensorFlow, GCP",Associate,3,Energy,2024-06-12,2024-08-13,2463,9,Predictive Systems +AI09090,AI Consultant,128578,AUD,173580,EX,PT,Australia,S,Australia,0,"Kubernetes, SQL, NLP",PhD,19,Technology,2024-11-24,2024-12-16,853,9.9,Predictive Systems +AI09091,AI Specialist,34167,USD,34167,MI,FL,China,M,China,50,"Linux, Scala, Spark, Git",PhD,2,Automotive,2024-09-11,2024-11-02,1155,6.7,Smart Analytics +AI09092,Deep Learning Engineer,82557,JPY,9081270,MI,FL,Japan,S,Colombia,50,"MLOps, NLP, R",Master,3,Manufacturing,2024-01-02,2024-02-29,1336,5.5,Cloud AI Solutions +AI09093,Machine Learning Engineer,73184,EUR,62206,EN,FL,Austria,M,Austria,100,"Python, SQL, GCP",Master,0,Automotive,2024-10-20,2024-12-10,2376,7.1,Predictive Systems +AI09094,Research Scientist,185487,EUR,157664,EX,PT,France,L,France,50,"Python, Deep Learning, Data Visualization, Java",PhD,10,Gaming,2024-07-21,2024-08-18,2304,8.6,TechCorp Inc +AI09095,Computer Vision Engineer,184041,JPY,20244510,EX,PT,Japan,M,Sweden,0,"TensorFlow, Java, Linux",PhD,13,Energy,2024-10-28,2024-12-13,1131,6.9,Machine Intelligence Group +AI09096,Data Analyst,63990,USD,63990,EN,PT,South Korea,L,Czech Republic,0,"Linux, Mathematics, Tableau, MLOps",PhD,0,Real Estate,2024-07-18,2024-09-08,1360,8.4,Autonomous Tech +AI09097,Deep Learning Engineer,77439,USD,77439,EN,FT,Denmark,L,Denmark,100,"Tableau, Git, Linux",PhD,1,Technology,2024-08-13,2024-09-08,526,10,Predictive Systems +AI09098,Machine Learning Researcher,54169,CAD,67711,EN,PT,Canada,S,Switzerland,100,"Spark, Azure, SQL, Hadoop, Statistics",PhD,0,Gaming,2024-08-28,2024-10-20,1818,7.1,Predictive Systems +AI09099,Deep Learning Engineer,97993,EUR,83294,SE,PT,Germany,S,Germany,0,"Kubernetes, Python, TensorFlow, Statistics",Master,6,Government,2024-09-24,2024-11-25,1849,6.6,Cognitive Computing +AI09100,Data Scientist,79820,JPY,8780200,EN,PT,Japan,L,Japan,100,"Azure, Git, R, Java, Scala",Master,1,Technology,2024-10-12,2024-12-04,1735,6.9,DataVision Ltd +AI09101,Principal Data Scientist,104484,USD,104484,EN,FT,United States,L,United States,0,"PyTorch, TensorFlow, R, Scala",Master,1,Automotive,2024-03-14,2024-03-29,1370,5.8,Smart Analytics +AI09102,Machine Learning Researcher,103925,USD,103925,MI,FL,Sweden,M,United Kingdom,0,"R, PyTorch, Mathematics",Master,3,Telecommunications,2024-06-17,2024-08-25,1236,8.4,TechCorp Inc +AI09103,AI Architect,99884,EUR,84901,SE,FL,Germany,S,Germany,0,"Spark, Azure, NLP, Mathematics, SQL",Associate,9,Manufacturing,2025-03-13,2025-05-11,2448,7.6,TechCorp Inc +AI09104,Machine Learning Researcher,153139,JPY,16845290,SE,FL,Japan,L,Japan,0,"Linux, Python, Deep Learning, Statistics, Computer Vision",Associate,5,Technology,2025-04-25,2025-06-21,2037,7.4,Future Systems +AI09105,ML Ops Engineer,61944,EUR,52652,EN,FL,France,L,France,50,"Deep Learning, Hadoop, PyTorch, NLP",Master,0,Retail,2024-09-28,2024-10-18,2126,6.7,TechCorp Inc +AI09106,Data Engineer,65282,EUR,55490,EN,PT,Austria,M,Austria,50,"Docker, Tableau, NLP",Master,1,Automotive,2024-05-21,2024-08-02,837,8.6,Quantum Computing Inc +AI09107,NLP Engineer,96292,EUR,81848,SE,CT,Germany,S,Germany,100,"NLP, Deep Learning, Scala",Bachelor,9,Consulting,2024-05-18,2024-07-17,1311,6.3,Algorithmic Solutions +AI09108,ML Ops Engineer,157918,CHF,142126,MI,CT,Switzerland,L,Switzerland,100,"Docker, Git, Mathematics",PhD,4,Technology,2024-07-16,2024-08-28,1630,5.3,Cloud AI Solutions +AI09109,Robotics Engineer,68722,AUD,92775,EN,FT,Australia,M,Australia,100,"Python, Spark, Java",Master,0,Education,2024-04-17,2024-05-18,2294,7,Neural Networks Co +AI09110,Computer Vision Engineer,34572,USD,34572,MI,FT,India,S,Austria,50,"Statistics, Python, TensorFlow",PhD,4,Manufacturing,2025-04-13,2025-05-02,1135,5.9,Predictive Systems +AI09111,AI Research Scientist,46646,USD,46646,MI,CT,China,L,China,50,"Deep Learning, MLOps, GCP, NLP",PhD,4,Telecommunications,2025-04-10,2025-05-23,1392,5.4,TechCorp Inc +AI09112,AI Architect,235688,EUR,200335,EX,PT,France,M,Argentina,0,"AWS, Git, Data Visualization, Statistics",Master,15,Transportation,2025-03-24,2025-05-18,2377,6.6,Autonomous Tech +AI09113,NLP Engineer,273202,USD,273202,EX,FT,Israel,L,Russia,100,"Scala, R, Azure, SQL",PhD,17,Transportation,2024-04-04,2024-05-13,717,5.6,DataVision Ltd +AI09114,Principal Data Scientist,191484,CAD,239355,EX,FT,Canada,S,Canada,0,"NLP, Spark, Scala, TensorFlow, Deep Learning",Associate,11,Manufacturing,2025-03-03,2025-04-29,674,9.1,AI Innovations +AI09115,AI Research Scientist,59597,USD,59597,EX,CT,India,M,Israel,0,"MLOps, Scala, TensorFlow",Bachelor,12,Manufacturing,2024-04-19,2024-06-24,1996,7,Smart Analytics +AI09116,Autonomous Systems Engineer,152712,USD,152712,EX,FL,Ireland,S,Ireland,50,"Deep Learning, Python, Data Visualization, Git, R",Master,12,Transportation,2024-05-13,2024-07-23,2066,7.7,DataVision Ltd +AI09117,Machine Learning Engineer,260073,EUR,221062,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, TensorFlow, Computer Vision, Data Visualization",Associate,14,Government,2024-04-27,2024-06-16,2072,9.8,Digital Transformation LLC +AI09118,Principal Data Scientist,21379,USD,21379,EN,PT,India,M,India,50,"Computer Vision, GCP, Hadoop, Python, Data Visualization",PhD,1,Healthcare,2024-06-02,2024-07-05,785,5.4,Machine Intelligence Group +AI09119,Machine Learning Researcher,39561,USD,39561,MI,FT,China,L,China,100,"Computer Vision, TensorFlow, Hadoop",Bachelor,4,Retail,2024-09-21,2024-11-03,930,8.7,Smart Analytics +AI09120,AI Software Engineer,126547,EUR,107565,MI,CT,Germany,L,Germany,50,"Linux, Docker, PyTorch",Bachelor,4,Telecommunications,2025-04-24,2025-07-06,1681,7,Algorithmic Solutions +AI09121,Autonomous Systems Engineer,187489,USD,187489,EX,PT,South Korea,S,South Korea,50,"Java, Kubernetes, Tableau",PhD,17,Energy,2024-08-20,2024-10-06,2373,10,TechCorp Inc +AI09122,NLP Engineer,131267,USD,131267,SE,FL,United States,M,United States,0,"SQL, R, Linux, GCP",Bachelor,8,Finance,2024-01-24,2024-03-11,1746,9,Autonomous Tech +AI09123,AI Architect,77519,USD,77519,EN,FL,Finland,L,Finland,0,"Azure, Kubernetes, Scala",Associate,0,Finance,2025-03-21,2025-05-12,1803,6.2,DeepTech Ventures +AI09124,ML Ops Engineer,108940,AUD,147069,MI,PT,Australia,L,Kenya,100,"Hadoop, Java, Tableau",Bachelor,2,Government,2024-02-24,2024-04-24,2250,8.3,DataVision Ltd +AI09125,Machine Learning Researcher,151325,GBP,113494,EX,FL,United Kingdom,M,Ukraine,0,"Hadoop, PyTorch, Deep Learning",PhD,12,Real Estate,2025-01-05,2025-02-23,2290,8.5,TechCorp Inc +AI09126,Head of AI,164274,USD,164274,EX,FL,Ireland,L,Finland,50,"Python, TensorFlow, PyTorch, Deep Learning",Master,13,Automotive,2024-11-15,2024-12-17,930,6.2,Future Systems +AI09127,Principal Data Scientist,96078,AUD,129705,MI,CT,Australia,S,Australia,0,"Scala, AWS, Azure, R",Master,2,Telecommunications,2024-02-19,2024-03-15,2296,6.6,TechCorp Inc +AI09128,Principal Data Scientist,234097,EUR,198982,EX,FT,Netherlands,S,Luxembourg,100,"Hadoop, Scala, Deep Learning, R, AWS",PhD,17,Manufacturing,2024-09-16,2024-11-26,1852,5.8,Advanced Robotics +AI09129,Research Scientist,285597,USD,285597,EX,CT,Norway,M,Mexico,50,"Kubernetes, Deep Learning, TensorFlow, Scala",Associate,17,Energy,2024-04-09,2024-06-11,1210,7.6,Future Systems +AI09130,Autonomous Systems Engineer,273922,USD,273922,EX,FT,Norway,L,Norway,100,"Python, Docker, Hadoop, Deep Learning, Mathematics",Associate,16,Energy,2024-04-13,2024-05-11,1232,5.6,Quantum Computing Inc +AI09131,AI Software Engineer,61758,EUR,52494,MI,PT,Austria,S,Austria,50,"MLOps, Deep Learning, PyTorch, GCP",PhD,4,Energy,2025-03-06,2025-05-03,2361,7.4,Predictive Systems +AI09132,Autonomous Systems Engineer,216376,EUR,183920,EX,PT,Austria,L,Austria,100,"SQL, Azure, Kubernetes, Docker",Master,15,Transportation,2024-05-28,2024-07-21,2425,6.2,Autonomous Tech +AI09133,Data Engineer,137572,USD,137572,SE,PT,Denmark,S,Kenya,50,"Data Visualization, Azure, Python",Bachelor,7,Education,2025-04-29,2025-07-11,1115,8.3,Neural Networks Co +AI09134,Machine Learning Researcher,206544,JPY,22719840,EX,CT,Japan,S,Japan,50,"MLOps, SQL, TensorFlow, Data Visualization, Statistics",Master,16,Gaming,2024-06-13,2024-07-10,2087,6.2,DataVision Ltd +AI09135,ML Ops Engineer,141517,USD,141517,SE,FT,South Korea,L,Colombia,0,"Kubernetes, Python, AWS",Associate,6,Gaming,2024-04-07,2024-06-11,822,6.1,DeepTech Ventures +AI09136,Research Scientist,87198,EUR,74118,MI,PT,Austria,L,Austria,50,"Kubernetes, Spark, SQL, NLP",Master,4,Automotive,2025-04-11,2025-05-31,1541,9.8,Predictive Systems +AI09137,Machine Learning Researcher,87108,EUR,74042,EN,PT,Netherlands,L,Netherlands,0,"PyTorch, Java, Scala, Docker, TensorFlow",Bachelor,0,Gaming,2024-09-06,2024-11-16,2018,7.6,TechCorp Inc +AI09138,Robotics Engineer,214335,EUR,182185,EX,CT,Austria,S,Denmark,0,"Hadoop, AWS, SQL",Associate,15,Education,2024-10-30,2024-12-27,1232,9.5,Machine Intelligence Group +AI09139,AI Specialist,153507,CAD,191884,EX,FT,Canada,S,Canada,100,"SQL, Docker, Data Visualization, MLOps",PhD,15,Consulting,2024-09-04,2024-11-09,2064,8.6,Cloud AI Solutions +AI09140,Data Analyst,73451,EUR,62433,MI,PT,Austria,S,Austria,0,"Git, Python, Data Visualization, Azure, Tableau",PhD,2,Energy,2024-11-23,2024-12-26,2401,7.7,DeepTech Ventures +AI09141,Robotics Engineer,141812,SGD,184356,SE,PT,Singapore,M,Singapore,0,"Mathematics, Spark, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-02-17,2364,8.8,Future Systems +AI09142,AI Software Engineer,185928,USD,185928,EX,PT,South Korea,M,China,50,"Spark, Scala, Statistics, Hadoop",Master,11,Consulting,2024-05-08,2024-07-17,1047,8.2,Algorithmic Solutions +AI09143,Machine Learning Engineer,114515,USD,114515,SE,PT,Israel,S,Israel,50,"Tableau, NLP, GCP, Computer Vision",Bachelor,7,Education,2024-02-02,2024-03-01,961,7.9,AI Innovations +AI09144,Data Analyst,175467,EUR,149147,EX,CT,Germany,S,Germany,0,"Git, Statistics, Tableau, TensorFlow",Master,15,Retail,2025-02-10,2025-03-05,2273,6.5,DeepTech Ventures +AI09145,Head of AI,88766,EUR,75451,MI,CT,Netherlands,L,Netherlands,0,"R, AWS, Data Visualization",Associate,2,Transportation,2024-10-14,2024-11-16,850,9,Digital Transformation LLC +AI09146,Computer Vision Engineer,111355,JPY,12249050,MI,FL,Japan,M,Poland,0,"Python, PyTorch, Deep Learning, GCP",PhD,4,Telecommunications,2025-01-16,2025-02-20,2186,7.2,Future Systems +AI09147,Machine Learning Engineer,128271,CAD,160339,SE,FT,Canada,S,Canada,100,"Data Visualization, NLP, Tableau",Bachelor,5,Government,2024-11-15,2024-12-07,837,7.7,Advanced Robotics +AI09148,Machine Learning Engineer,123580,EUR,105043,SE,FT,France,M,France,0,"NLP, Spark, Deep Learning",Master,9,Education,2025-03-13,2025-05-21,1067,8.3,AI Innovations +AI09149,ML Ops Engineer,77084,AUD,104063,EN,CT,Australia,L,Australia,0,"Data Visualization, NLP, TensorFlow, Azure",Bachelor,1,Consulting,2024-07-02,2024-07-20,1859,7.6,DataVision Ltd +AI09150,AI Specialist,46762,USD,46762,EN,PT,Ireland,S,Ireland,100,"PyTorch, SQL, Deep Learning, Scala, Tableau",Associate,1,Government,2025-03-26,2025-05-25,1596,9.3,Machine Intelligence Group +AI09151,AI Consultant,218952,USD,218952,EX,PT,Ireland,M,Ireland,50,"MLOps, AWS, SQL, Mathematics, Azure",Bachelor,13,Government,2025-01-30,2025-03-21,628,7.9,Advanced Robotics +AI09152,AI Product Manager,61455,SGD,79892,EN,FT,Singapore,S,Australia,50,"Hadoop, Tableau, Spark, Linux, Computer Vision",Bachelor,1,Finance,2024-04-19,2024-06-14,1344,5.6,Predictive Systems +AI09153,Machine Learning Engineer,66187,USD,66187,EX,PT,China,M,China,100,"Azure, Git, Tableau, SQL",Bachelor,17,Finance,2024-11-22,2024-12-11,1180,6.7,Cloud AI Solutions +AI09154,NLP Engineer,130172,SGD,169224,SE,FT,Singapore,S,Japan,50,"GCP, Java, MLOps, Computer Vision",PhD,8,Automotive,2025-03-01,2025-05-09,1102,9.1,TechCorp Inc +AI09155,Machine Learning Engineer,77763,JPY,8553930,EN,FT,Japan,L,Japan,100,"SQL, PyTorch, Mathematics, Docker",Associate,1,Real Estate,2025-03-15,2025-05-08,648,5.8,Autonomous Tech +AI09156,Research Scientist,100848,USD,100848,MI,CT,Norway,M,Norway,100,"Docker, Git, AWS",PhD,2,Energy,2024-08-19,2024-09-28,752,6.5,Smart Analytics +AI09157,Machine Learning Engineer,144916,JPY,15940760,EX,FT,Japan,S,Japan,50,"PyTorch, Scala, Python",PhD,18,Retail,2025-02-06,2025-03-23,1976,5.7,Quantum Computing Inc +AI09158,Autonomous Systems Engineer,241167,SGD,313517,EX,PT,Singapore,S,Israel,100,"Spark, Statistics, Computer Vision, Git",Associate,17,Technology,2024-06-11,2024-07-22,2278,8.5,Algorithmic Solutions +AI09159,Head of AI,122631,GBP,91973,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, SQL, Deep Learning, MLOps",Associate,3,Healthcare,2025-03-21,2025-05-10,1649,7.5,AI Innovations +AI09160,ML Ops Engineer,52113,USD,52113,SE,FL,India,M,India,50,"Computer Vision, GCP, Tableau, NLP",Master,9,Telecommunications,2024-05-01,2024-05-19,1707,5.2,Digital Transformation LLC +AI09161,AI Specialist,131239,AUD,177173,SE,PT,Australia,S,Latvia,0,"Spark, Hadoop, TensorFlow, MLOps",Associate,8,Consulting,2024-12-07,2025-02-16,1374,6.6,Autonomous Tech +AI09162,AI Architect,39306,USD,39306,SE,CT,India,S,India,100,"Linux, MLOps, Tableau, AWS, Git",PhD,7,Automotive,2025-04-23,2025-05-24,703,6.6,Smart Analytics +AI09163,Machine Learning Engineer,55092,EUR,46828,EN,FT,Austria,M,Austria,100,"Python, GCP, Mathematics, MLOps",Bachelor,0,Automotive,2024-07-24,2024-09-15,1765,7.5,Quantum Computing Inc +AI09164,Research Scientist,155977,AUD,210569,SE,CT,Australia,L,Australia,50,"Azure, Mathematics, Data Visualization",PhD,7,Real Estate,2024-12-22,2025-02-15,564,9.6,AI Innovations +AI09165,AI Architect,92563,USD,92563,EN,FL,United States,M,United States,100,"Python, Kubernetes, Computer Vision, NLP",Associate,0,Education,2024-09-29,2024-10-17,2497,9.7,Cloud AI Solutions +AI09166,Data Scientist,56883,USD,56883,EN,FL,Finland,M,Finland,50,"Tableau, Hadoop, Python",PhD,1,Energy,2024-08-25,2024-10-24,2304,5.1,Advanced Robotics +AI09167,AI Research Scientist,63119,USD,63119,EN,FT,Norway,S,Norway,0,"Docker, MLOps, Scala, Computer Vision, Azure",Associate,1,Finance,2024-04-17,2024-05-28,1624,9.1,Algorithmic Solutions +AI09168,Robotics Engineer,124054,USD,124054,SE,CT,Finland,S,Argentina,0,"Python, GCP, Computer Vision",Bachelor,7,Energy,2024-09-10,2024-10-17,1475,8.2,DataVision Ltd +AI09169,Head of AI,70626,AUD,95345,EN,CT,Australia,S,Australia,100,"GCP, TensorFlow, MLOps, Python",Master,0,Government,2025-03-21,2025-04-13,2467,9.3,DataVision Ltd +AI09170,AI Consultant,95105,EUR,80839,MI,PT,Germany,M,China,50,"Spark, SQL, MLOps, Hadoop, Statistics",Master,3,Gaming,2024-02-26,2024-03-18,1527,5.9,Smart Analytics +AI09171,AI Architect,142966,GBP,107225,SE,FL,United Kingdom,M,Canada,0,"Computer Vision, SQL, Deep Learning, Git, Hadoop",Bachelor,6,Energy,2024-02-27,2024-04-18,1558,8.4,Machine Intelligence Group +AI09172,Autonomous Systems Engineer,30269,USD,30269,EN,FL,India,L,Israel,50,"NLP, Kubernetes, TensorFlow, MLOps, Git",Master,1,Retail,2024-12-02,2024-12-23,1413,6.7,Future Systems +AI09173,Computer Vision Engineer,172669,USD,172669,SE,FL,Norway,M,Norway,0,"Docker, PyTorch, Java, Python, Scala",Bachelor,8,Real Estate,2024-07-22,2024-08-16,1753,9.4,Future Systems +AI09174,Robotics Engineer,129725,USD,129725,EX,PT,Ireland,S,Ireland,50,"Scala, Azure, Tableau, NLP",Master,14,Media,2024-06-24,2024-09-02,1349,8.5,Digital Transformation LLC +AI09175,Computer Vision Engineer,63167,SGD,82117,EN,CT,Singapore,S,Singapore,100,"NLP, GCP, Deep Learning, Python, Hadoop",Master,0,Retail,2024-09-27,2024-12-09,686,8.7,Neural Networks Co +AI09176,AI Specialist,258786,USD,258786,EX,FL,Norway,S,Norway,50,"Linux, Kubernetes, PyTorch",Master,10,Technology,2024-04-22,2024-05-08,1899,5.4,Cognitive Computing +AI09177,AI Research Scientist,44253,USD,44253,MI,CT,China,S,Finland,50,"Hadoop, Python, Azure, Kubernetes, Scala",Bachelor,2,Energy,2025-01-02,2025-02-15,1158,8.5,Quantum Computing Inc +AI09178,AI Consultant,130321,GBP,97741,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, MLOps, SQL",Master,7,Technology,2024-04-29,2024-05-18,2064,8.7,Advanced Robotics +AI09179,Research Scientist,163239,EUR,138753,EX,FT,France,M,France,0,"Linux, Git, Data Visualization, Deep Learning",Master,13,Healthcare,2024-09-06,2024-11-17,766,9,Smart Analytics +AI09180,Research Scientist,88353,CAD,110441,MI,FL,Canada,S,Philippines,100,"R, Linux, SQL, Git, AWS",Bachelor,4,Manufacturing,2024-05-06,2024-05-31,1684,7.6,Algorithmic Solutions +AI09181,Machine Learning Engineer,99421,CAD,124276,MI,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Tableau",Master,4,Retail,2024-04-20,2024-05-16,1672,6.4,Machine Intelligence Group +AI09182,Deep Learning Engineer,92458,EUR,78589,SE,FL,Germany,S,Germany,0,"Scala, PyTorch, Hadoop",PhD,7,Transportation,2024-05-10,2024-07-15,1982,9.8,Cloud AI Solutions +AI09183,Autonomous Systems Engineer,176930,JPY,19462300,SE,FL,Japan,L,Japan,50,"Kubernetes, Deep Learning, MLOps, Azure",Master,7,Healthcare,2024-03-24,2024-04-25,1765,6.9,DeepTech Ventures +AI09184,Machine Learning Engineer,87956,USD,87956,MI,CT,Israel,S,Israel,50,"Spark, Python, Data Visualization",Master,4,Telecommunications,2024-01-16,2024-02-22,1350,9.5,Algorithmic Solutions +AI09185,Data Scientist,178060,USD,178060,SE,FT,Norway,L,Norway,100,"Spark, Git, NLP, Statistics",Master,7,Energy,2025-01-28,2025-04-11,2470,7.7,Algorithmic Solutions +AI09186,Robotics Engineer,274887,USD,274887,EX,FT,Finland,L,Finland,50,"Python, TensorFlow, Git, Linux, Azure",Bachelor,18,Media,2025-03-19,2025-05-06,524,5.2,Quantum Computing Inc +AI09187,AI Software Engineer,111752,USD,111752,MI,PT,Ireland,L,Ireland,100,"Docker, Spark, NLP, Kubernetes, Computer Vision",Bachelor,4,Gaming,2024-01-05,2024-01-20,1344,8.3,Cloud AI Solutions +AI09188,AI Specialist,58945,CAD,73681,EN,FL,Canada,L,South Africa,100,"R, SQL, Linux",Master,0,Education,2024-12-30,2025-02-24,1925,8.9,Machine Intelligence Group +AI09189,AI Specialist,192129,USD,192129,SE,FL,Denmark,L,Denmark,50,"Linux, Python, Tableau",Master,6,Education,2024-03-30,2024-06-03,1867,9.3,TechCorp Inc +AI09190,Data Analyst,111169,AUD,150078,SE,PT,Australia,M,Canada,50,"PyTorch, Linux, MLOps",Master,8,Education,2024-10-10,2024-10-26,726,6.8,DataVision Ltd +AI09191,Machine Learning Researcher,92985,GBP,69739,MI,PT,United Kingdom,L,United Kingdom,50,"AWS, TensorFlow, SQL, Azure",Master,3,Gaming,2024-07-23,2024-08-21,1875,6.4,Machine Intelligence Group +AI09192,AI Consultant,96505,CHF,86855,EN,PT,Switzerland,S,Switzerland,50,"SQL, TensorFlow, NLP, AWS, Tableau",Bachelor,0,Manufacturing,2024-02-29,2024-04-30,2394,7,Cognitive Computing +AI09193,AI Software Engineer,158342,USD,158342,EX,FT,South Korea,L,South Korea,0,"GCP, TensorFlow, NLP, Statistics, Computer Vision",Master,12,Consulting,2025-03-12,2025-04-27,1649,6.4,Cognitive Computing +AI09194,AI Specialist,93578,JPY,10293580,EN,CT,Japan,L,Japan,0,"Java, TensorFlow, Azure, Tableau, Kubernetes",Associate,1,Gaming,2024-10-26,2024-11-30,2036,9.3,Smart Analytics +AI09195,Data Engineer,214274,USD,214274,EX,CT,United States,M,Czech Republic,100,"Java, Data Visualization, PyTorch",Master,13,Technology,2024-11-12,2024-12-31,743,8,Digital Transformation LLC +AI09196,AI Consultant,178303,CAD,222879,EX,CT,Canada,M,Canada,50,"Mathematics, Computer Vision, Spark, Hadoop, SQL",Associate,17,Government,2025-03-03,2025-04-19,1070,8.9,Advanced Robotics +AI09197,Head of AI,36007,USD,36007,SE,FT,India,M,India,50,"AWS, Tableau, TensorFlow, Git",Associate,7,Finance,2024-02-07,2024-03-03,730,6,Advanced Robotics +AI09198,Deep Learning Engineer,171051,EUR,145393,EX,PT,Austria,S,Canada,50,"Python, AWS, TensorFlow",Bachelor,13,Consulting,2024-05-21,2024-07-03,1012,8.5,Algorithmic Solutions +AI09199,Head of AI,198950,EUR,169108,EX,FT,Austria,S,Austria,50,"Spark, SQL, Statistics",Associate,14,Government,2025-03-12,2025-04-20,2381,9.2,DeepTech Ventures +AI09200,Robotics Engineer,124387,EUR,105729,SE,FT,France,M,France,100,"PyTorch, TensorFlow, Deep Learning, Scala, Java",Associate,8,Gaming,2024-10-15,2024-12-06,911,5,Neural Networks Co +AI09201,Computer Vision Engineer,106704,USD,106704,MI,FL,Ireland,L,Ireland,100,"R, Git, Azure, Scala, Python",PhD,3,Telecommunications,2024-01-15,2024-02-03,1956,5.7,DeepTech Ventures +AI09202,Research Scientist,149562,USD,149562,EX,FL,Finland,L,Finland,0,"Scala, Tableau, Python, SQL, Kubernetes",Associate,16,Education,2024-10-12,2024-12-08,1386,7.2,Cloud AI Solutions +AI09203,AI Software Engineer,112666,USD,112666,SE,FL,Finland,L,Japan,50,"Azure, Java, Computer Vision",PhD,8,Telecommunications,2024-04-27,2024-06-01,1069,7.2,Cloud AI Solutions +AI09204,Data Analyst,102655,USD,102655,MI,CT,Norway,S,Norway,100,"PyTorch, Computer Vision, Git",Master,2,Telecommunications,2024-12-02,2025-02-12,721,5.4,TechCorp Inc +AI09205,Research Scientist,60391,CAD,75489,EN,FT,Canada,M,Canada,50,"SQL, Spark, PyTorch",PhD,1,Manufacturing,2024-01-31,2024-04-13,1304,6.9,DeepTech Ventures +AI09206,Data Analyst,93418,USD,93418,SE,PT,South Korea,S,Estonia,0,"Git, SQL, Hadoop, Mathematics, Scala",Associate,9,Education,2024-04-04,2024-06-10,2248,9.4,Cloud AI Solutions +AI09207,AI Architect,64099,EUR,54484,MI,PT,France,S,Japan,100,"Scala, Spark, Java, Computer Vision, Docker",Associate,4,Education,2024-11-15,2024-12-08,2247,5.1,Cognitive Computing +AI09208,Head of AI,170894,JPY,18798340,SE,FL,Japan,L,Japan,0,"Data Visualization, PyTorch, SQL",Bachelor,8,Real Estate,2024-03-13,2024-05-15,2021,6.9,Algorithmic Solutions +AI09209,Autonomous Systems Engineer,26067,USD,26067,EN,CT,India,M,Russia,100,"Hadoop, Python, TensorFlow, Git",Bachelor,0,Consulting,2024-01-23,2024-03-07,892,7.1,Advanced Robotics +AI09210,AI Specialist,87803,EUR,74633,EN,PT,Germany,L,Germany,100,"TensorFlow, Python, GCP",Master,1,Media,2024-11-08,2024-12-04,822,8.7,Algorithmic Solutions +AI09211,AI Consultant,73822,CAD,92278,EN,FL,Canada,M,Netherlands,0,"Tableau, TensorFlow, Scala, Statistics",Master,1,Technology,2024-10-03,2024-10-20,1230,5.2,Predictive Systems +AI09212,Machine Learning Engineer,92932,CHF,83639,EN,FT,Switzerland,M,Switzerland,100,"AWS, NLP, SQL",Bachelor,0,Education,2024-07-23,2024-09-05,608,6.4,Neural Networks Co +AI09213,AI Consultant,68084,EUR,57871,EN,PT,Netherlands,L,France,100,"Linux, Tableau, Spark, AWS, Azure",PhD,0,Technology,2025-02-23,2025-04-28,1068,8.9,Cloud AI Solutions +AI09214,AI Specialist,207439,SGD,269671,EX,FL,Singapore,M,Singapore,100,"Java, Spark, NLP",Associate,18,Media,2024-03-19,2024-04-21,1904,5.8,Machine Intelligence Group +AI09215,Data Analyst,96026,USD,96026,EX,FL,China,S,China,100,"SQL, PyTorch, Data Visualization, MLOps",Bachelor,10,Telecommunications,2025-04-16,2025-05-31,868,9.4,Digital Transformation LLC +AI09216,Research Scientist,59680,EUR,50728,EN,FT,France,M,France,0,"Hadoop, MLOps, TensorFlow, Mathematics",Associate,1,Retail,2025-03-12,2025-05-20,2217,6.3,DataVision Ltd +AI09217,AI Specialist,56599,USD,56599,EN,CT,Israel,M,Israel,50,"Azure, AWS, Docker",Master,1,Retail,2025-03-09,2025-04-18,2056,7.5,Future Systems +AI09218,Principal Data Scientist,76244,USD,76244,EN,PT,United States,M,Nigeria,50,"PyTorch, Statistics, TensorFlow",Bachelor,1,Government,2024-09-24,2024-11-27,2133,5.8,Cloud AI Solutions +AI09219,Research Scientist,79160,EUR,67286,MI,FT,France,S,France,100,"Kubernetes, PyTorch, MLOps, SQL",Associate,4,Consulting,2024-11-09,2024-12-14,1801,9.4,Quantum Computing Inc +AI09220,Data Scientist,60957,USD,60957,EN,CT,Ireland,L,Ireland,50,"Git, Python, GCP",PhD,0,Gaming,2025-03-31,2025-05-04,1384,8.1,Future Systems +AI09221,Autonomous Systems Engineer,155548,USD,155548,SE,FL,Israel,L,India,100,"MLOps, Python, TensorFlow, PyTorch, Data Visualization",Master,5,Consulting,2024-08-12,2024-09-22,1725,6.7,Algorithmic Solutions +AI09222,AI Product Manager,123088,JPY,13539680,MI,PT,Japan,L,Japan,0,"Statistics, Scala, Python, GCP, R",Master,2,Manufacturing,2024-05-23,2024-06-09,1989,9,Algorithmic Solutions +AI09223,Research Scientist,121682,USD,121682,MI,FL,Norway,L,Vietnam,100,"Hadoop, Tableau, Spark, Mathematics, Scala",Associate,4,Finance,2024-12-25,2025-02-05,1174,5.7,Cognitive Computing +AI09224,AI Consultant,169915,EUR,144428,EX,PT,Germany,L,Germany,0,"GCP, Hadoop, Git, Computer Vision, R",Associate,14,Media,2025-01-19,2025-02-24,852,5.2,Autonomous Tech +AI09225,AI Specialist,119381,CAD,149226,MI,PT,Canada,L,Canada,100,"Java, MLOps, AWS",PhD,4,Manufacturing,2024-09-22,2024-11-04,2129,8.6,Digital Transformation LLC +AI09226,Deep Learning Engineer,133384,GBP,100038,SE,PT,United Kingdom,M,United Kingdom,0,"SQL, TensorFlow, AWS",Associate,6,Government,2024-04-07,2024-05-07,575,9.1,Machine Intelligence Group +AI09227,AI Architect,122154,USD,122154,SE,FT,United States,S,Colombia,100,"Python, Spark, Mathematics",Master,8,Technology,2024-07-25,2024-09-20,2343,6.7,DeepTech Ventures +AI09228,AI Specialist,66659,EUR,56660,EN,FL,Netherlands,S,Netherlands,100,"Kubernetes, PyTorch, TensorFlow, Spark, Computer Vision",PhD,1,Finance,2024-03-02,2024-04-15,2386,6.7,Cloud AI Solutions +AI09229,Data Analyst,92410,EUR,78549,MI,PT,Germany,L,Germany,100,"Hadoop, SQL, AWS",Bachelor,2,Technology,2024-03-28,2024-05-25,2078,8.7,Algorithmic Solutions +AI09230,Principal Data Scientist,81950,USD,81950,SE,FT,South Korea,S,South Korea,50,"Azure, SQL, Python, TensorFlow",Associate,9,Real Estate,2025-01-27,2025-03-31,1513,6.6,Predictive Systems +AI09231,AI Research Scientist,192330,EUR,163481,EX,CT,Netherlands,L,Netherlands,100,"GCP, Spark, Data Visualization, SQL",Bachelor,19,Government,2025-04-30,2025-05-28,1050,6.7,Cloud AI Solutions +AI09232,AI Specialist,194139,CHF,174725,SE,CT,Switzerland,M,Romania,50,"Deep Learning, Java, MLOps, Kubernetes, AWS",Associate,7,Retail,2024-06-18,2024-07-23,2017,9.3,Cognitive Computing +AI09233,Machine Learning Researcher,287100,USD,287100,EX,PT,Denmark,S,Denmark,0,"R, Python, Spark",Master,14,Technology,2025-03-18,2025-04-23,505,7,DataVision Ltd +AI09234,AI Consultant,192660,USD,192660,EX,FT,Finland,S,Finland,50,"GCP, PyTorch, TensorFlow, SQL",Associate,18,Healthcare,2024-06-29,2024-08-24,1758,7,AI Innovations +AI09235,AI Specialist,79472,USD,79472,MI,CT,Israel,M,Kenya,0,"Python, Spark, Kubernetes, PyTorch, Tableau",Master,3,Technology,2024-07-21,2024-09-07,1228,5.5,Advanced Robotics +AI09236,Autonomous Systems Engineer,118867,USD,118867,MI,FL,Norway,L,Norway,0,"MLOps, TensorFlow, Python",PhD,2,Telecommunications,2024-10-11,2024-12-13,2362,9.9,Algorithmic Solutions +AI09237,Research Scientist,123406,USD,123406,SE,PT,South Korea,L,Colombia,100,"SQL, PyTorch, AWS, Kubernetes",Associate,7,Automotive,2024-12-14,2025-02-20,1950,9.1,AI Innovations +AI09238,NLP Engineer,122245,USD,122245,SE,PT,Denmark,S,Denmark,100,"Git, Data Visualization, AWS",Master,5,Gaming,2024-10-30,2024-11-15,1775,9.5,Machine Intelligence Group +AI09239,ML Ops Engineer,191922,EUR,163134,EX,PT,France,S,France,0,"MLOps, Java, Docker, Scala",Associate,14,Gaming,2024-12-15,2025-01-12,2390,6,Cognitive Computing +AI09240,Data Engineer,68565,SGD,89135,EN,PT,Singapore,L,Singapore,50,"Kubernetes, Statistics, Data Visualization, Azure, Computer Vision",Master,0,Retail,2024-03-05,2024-04-21,2290,6.2,Quantum Computing Inc +AI09241,ML Ops Engineer,102495,JPY,11274450,MI,PT,Japan,S,Estonia,0,"Linux, Scala, Java, Azure",PhD,3,Manufacturing,2024-12-06,2025-01-21,1059,9.7,Predictive Systems +AI09242,Research Scientist,69321,SGD,90117,EN,CT,Singapore,L,Singapore,50,"AWS, Scala, Statistics, R",Master,0,Telecommunications,2024-08-31,2024-11-01,1292,8,Autonomous Tech +AI09243,Autonomous Systems Engineer,100703,AUD,135949,MI,FT,Australia,L,Australia,100,"Kubernetes, Tableau, Docker",PhD,4,Education,2024-07-05,2024-09-04,2102,7.8,Cognitive Computing +AI09244,AI Product Manager,87600,AUD,118260,EN,FT,Australia,L,Norway,0,"R, Mathematics, PyTorch, Deep Learning",Associate,1,Gaming,2024-01-06,2024-02-17,2084,7.9,Cloud AI Solutions +AI09245,AI Product Manager,104439,USD,104439,EN,FT,Denmark,M,Denmark,100,"Data Visualization, Linux, Computer Vision, Kubernetes, Mathematics",PhD,1,Real Estate,2024-03-19,2024-04-02,765,5.1,Smart Analytics +AI09246,Machine Learning Engineer,114869,CHF,103382,MI,CT,Switzerland,M,Switzerland,50,"GCP, Python, SQL, Kubernetes, Docker",Bachelor,4,Healthcare,2024-02-02,2024-04-04,1465,6.6,Machine Intelligence Group +AI09247,AI Consultant,77038,USD,77038,MI,CT,South Korea,S,South Korea,50,"Deep Learning, Kubernetes, Tableau, NLP",Master,4,Consulting,2024-03-17,2024-05-05,590,9.9,Autonomous Tech +AI09248,Machine Learning Engineer,115588,USD,115588,SE,FL,Sweden,S,New Zealand,50,"Docker, Mathematics, Tableau, GCP",Associate,7,Gaming,2025-02-23,2025-03-10,1018,7.5,DataVision Ltd +AI09249,Computer Vision Engineer,124933,CAD,156166,SE,FL,Canada,S,Canada,0,"GCP, Python, Data Visualization, Computer Vision, Deep Learning",Associate,8,Gaming,2024-07-16,2024-09-02,2228,6.4,Smart Analytics +AI09250,Robotics Engineer,105467,EUR,89647,MI,FT,Germany,L,Germany,0,"TensorFlow, Computer Vision, PyTorch, Deep Learning, Statistics",Associate,2,Healthcare,2024-11-03,2024-12-29,743,9.4,TechCorp Inc +AI09251,Research Scientist,108242,USD,108242,MI,FT,Ireland,L,Germany,100,"Computer Vision, GCP, Git, Tableau",Master,2,Manufacturing,2024-09-10,2024-09-26,682,9.8,Advanced Robotics +AI09252,AI Architect,92353,AUD,124677,SE,CT,Australia,S,Australia,100,"Mathematics, Azure, Tableau, TensorFlow, Java",Bachelor,6,Consulting,2024-02-04,2024-04-17,1028,9.1,Cloud AI Solutions +AI09253,Head of AI,137894,USD,137894,SE,PT,South Korea,L,Argentina,100,"Mathematics, Docker, GCP, Spark",Bachelor,5,Healthcare,2025-01-25,2025-02-22,1638,8.3,Autonomous Tech +AI09254,AI Specialist,80356,SGD,104463,EN,FL,Singapore,L,India,0,"Python, GCP, Kubernetes, Scala, Linux",Associate,0,Telecommunications,2024-04-19,2024-06-05,512,5.1,Smart Analytics +AI09255,Data Analyst,97471,USD,97471,MI,PT,Ireland,L,New Zealand,0,"Linux, AWS, Hadoop",Bachelor,3,Manufacturing,2024-01-25,2024-03-27,610,9.8,Future Systems +AI09256,Data Scientist,157922,USD,157922,EX,CT,Finland,M,Singapore,50,"R, Python, Statistics, Docker, Deep Learning",Associate,13,Consulting,2024-10-26,2024-12-05,2233,5.2,Cognitive Computing +AI09257,NLP Engineer,86054,CAD,107568,MI,FL,Canada,L,India,0,"Kubernetes, Python, Azure, TensorFlow, PyTorch",Bachelor,3,Real Estate,2024-07-08,2024-08-17,680,5.3,Cognitive Computing +AI09258,Data Scientist,133023,JPY,14632530,SE,FL,Japan,L,Colombia,50,"Azure, Docker, Deep Learning, SQL, MLOps",PhD,8,Real Estate,2025-03-03,2025-04-23,936,7.5,Algorithmic Solutions +AI09259,NLP Engineer,96262,GBP,72197,EN,CT,United Kingdom,L,United Kingdom,0,"Scala, Kubernetes, Git, GCP, Hadoop",PhD,0,Consulting,2024-12-03,2025-01-25,1844,6.4,Digital Transformation LLC +AI09260,Machine Learning Engineer,33333,USD,33333,MI,PT,India,L,India,50,"Hadoop, Scala, Java",Master,4,Technology,2024-05-26,2024-07-21,1580,8.4,DataVision Ltd +AI09261,Deep Learning Engineer,87092,USD,87092,MI,CT,Ireland,L,Ireland,50,"Hadoop, Git, R, GCP",Bachelor,4,Consulting,2025-02-27,2025-03-31,1789,9,Digital Transformation LLC +AI09262,Research Scientist,146551,USD,146551,EX,FL,Ireland,M,Ireland,0,"AWS, Hadoop, R",Master,16,Energy,2024-10-11,2024-12-16,2266,7,Digital Transformation LLC +AI09263,Robotics Engineer,66231,CAD,82789,EN,PT,Canada,L,Canada,0,"Deep Learning, Spark, TensorFlow",Master,1,Energy,2025-02-03,2025-04-13,1660,5.5,Autonomous Tech +AI09264,Robotics Engineer,145114,AUD,195904,SE,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, NLP",Associate,5,Telecommunications,2024-12-01,2025-02-09,1103,9.5,Autonomous Tech +AI09265,Autonomous Systems Engineer,146269,USD,146269,SE,PT,Sweden,M,Malaysia,0,"NLP, Hadoop, MLOps",Master,7,Finance,2024-12-01,2025-02-05,683,5.6,Quantum Computing Inc +AI09266,Research Scientist,125674,CAD,157093,SE,CT,Canada,L,Ukraine,50,"MLOps, TensorFlow, Mathematics, AWS",Bachelor,9,Government,2025-03-24,2025-05-16,871,8.6,Neural Networks Co +AI09267,Machine Learning Engineer,127447,JPY,14019170,SE,PT,Japan,S,Japan,100,"Java, Kubernetes, SQL",Associate,8,Transportation,2024-02-26,2024-03-27,1801,7.2,Advanced Robotics +AI09268,NLP Engineer,61294,EUR,52100,EN,CT,France,M,France,0,"SQL, Hadoop, Scala, Data Visualization",Bachelor,0,Energy,2024-09-29,2024-10-28,1878,7.2,Cloud AI Solutions +AI09269,ML Ops Engineer,135156,USD,135156,SE,FL,Sweden,S,Sweden,50,"AWS, Linux, SQL",PhD,6,Education,2024-11-09,2024-12-20,1976,8.2,DeepTech Ventures +AI09270,Autonomous Systems Engineer,67394,EUR,57285,EN,FL,Austria,L,Portugal,50,"GCP, PyTorch, SQL",PhD,1,Consulting,2024-06-24,2024-07-31,1455,5.6,DeepTech Ventures +AI09271,Data Scientist,90125,EUR,76606,MI,FL,Germany,M,Germany,0,"Deep Learning, Computer Vision, Linux, SQL",PhD,3,Manufacturing,2024-02-27,2024-03-27,2164,6.7,Machine Intelligence Group +AI09272,Data Engineer,136268,USD,136268,SE,CT,Ireland,L,Ireland,50,"Kubernetes, PyTorch, SQL",PhD,5,Healthcare,2024-04-09,2024-05-26,521,8.3,DataVision Ltd +AI09273,Data Scientist,69814,USD,69814,MI,FL,Finland,M,Portugal,100,"Kubernetes, Linux, Azure, Scala, PyTorch",PhD,2,Healthcare,2024-08-16,2024-10-14,2026,7,TechCorp Inc +AI09274,Robotics Engineer,295783,USD,295783,EX,FT,Denmark,S,Germany,50,"Spark, NLP, Java, PyTorch",Associate,12,Energy,2024-06-03,2024-07-17,2053,10,Cloud AI Solutions +AI09275,Head of AI,85810,JPY,9439100,MI,FL,Japan,M,Japan,100,"Data Visualization, Azure, Python, Kubernetes, Linux",Associate,4,Automotive,2024-10-27,2024-11-23,2108,7.2,Cognitive Computing +AI09276,AI Research Scientist,197095,USD,197095,EX,FL,Finland,S,Finland,0,"R, Statistics, Java",PhD,10,Technology,2025-03-19,2025-04-05,1049,6.7,Advanced Robotics +AI09277,Head of AI,122788,USD,122788,SE,CT,Ireland,S,China,100,"Python, Scala, GCP, TensorFlow",PhD,7,Retail,2024-04-19,2024-06-19,2250,9.2,Algorithmic Solutions +AI09278,Research Scientist,124194,USD,124194,SE,PT,Sweden,S,Sweden,0,"Scala, Git, Docker, Data Visualization, NLP",Master,8,Gaming,2024-01-05,2024-02-24,1663,7.6,DataVision Ltd +AI09279,AI Consultant,58846,USD,58846,MI,CT,South Korea,S,New Zealand,100,"PyTorch, Kubernetes, Linux",PhD,3,Technology,2024-09-02,2024-10-29,1711,5.3,DataVision Ltd +AI09280,Data Engineer,106557,CHF,95901,MI,PT,Switzerland,M,Switzerland,100,"GCP, TensorFlow, Java",Bachelor,3,Telecommunications,2024-11-22,2024-12-10,2401,7.1,Autonomous Tech +AI09281,Research Scientist,128421,EUR,109158,SE,FL,France,S,Germany,0,"PyTorch, Linux, Tableau",Bachelor,9,Gaming,2025-02-26,2025-04-03,2027,7.1,Predictive Systems +AI09282,AI Product Manager,117576,EUR,99940,SE,FL,France,L,Philippines,0,"Python, Deep Learning, Tableau, Kubernetes, GCP",Associate,8,Energy,2024-09-30,2024-11-13,636,9.7,Future Systems +AI09283,AI Specialist,57593,USD,57593,EN,CT,Israel,L,Ukraine,100,"Python, Kubernetes, AWS",Bachelor,0,Real Estate,2024-09-14,2024-09-30,912,6.9,Algorithmic Solutions +AI09284,AI Software Engineer,212215,USD,212215,EX,FL,United States,S,United States,50,"Azure, Git, Hadoop, Spark",Bachelor,16,Finance,2024-10-06,2024-10-21,2111,8.6,TechCorp Inc +AI09285,AI Consultant,135399,CHF,121859,MI,CT,Switzerland,L,Switzerland,100,"Spark, TensorFlow, NLP, Kubernetes",PhD,3,Consulting,2024-04-04,2024-05-28,1618,9.2,Future Systems +AI09286,Machine Learning Researcher,166176,USD,166176,EX,FL,South Korea,L,South Korea,0,"Git, Python, Azure",Associate,15,Gaming,2024-08-08,2024-10-06,1302,7.1,DeepTech Ventures +AI09287,Machine Learning Engineer,144034,GBP,108026,SE,CT,United Kingdom,S,United Kingdom,0,"Git, Docker, R, Statistics",Associate,9,Finance,2024-06-15,2024-07-19,1279,9.7,Neural Networks Co +AI09288,Head of AI,61774,USD,61774,SE,FL,India,L,India,100,"R, Hadoop, Tableau, Java",Master,6,Real Estate,2024-12-05,2025-02-15,2230,7.1,Autonomous Tech +AI09289,Deep Learning Engineer,103881,EUR,88299,SE,FT,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,5,Consulting,2024-07-07,2024-07-27,893,5.4,TechCorp Inc +AI09290,Data Analyst,59689,EUR,50736,EN,CT,France,L,France,100,"Git, R, MLOps, Python",Associate,0,Retail,2024-11-04,2024-11-26,1476,6.6,DeepTech Ventures +AI09291,AI Architect,191160,SGD,248508,EX,FL,Singapore,S,Singapore,50,"R, TensorFlow, Spark, Git",PhD,12,Retail,2024-07-27,2024-09-14,928,6.8,Digital Transformation LLC +AI09292,Data Engineer,89134,USD,89134,MI,CT,United States,S,Netherlands,50,"PyTorch, NLP, Kubernetes, Deep Learning, GCP",Bachelor,3,Technology,2024-10-06,2024-12-08,2234,5.7,Future Systems +AI09293,AI Software Engineer,142040,CAD,177550,EX,CT,Canada,M,Canada,50,"Mathematics, R, Data Visualization, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-04-18,2024-05-31,1401,6.1,Digital Transformation LLC +AI09294,Computer Vision Engineer,67255,USD,67255,MI,PT,Sweden,S,Sweden,100,"Hadoop, Docker, Java, Tableau",PhD,2,Media,2025-04-24,2025-06-12,1670,6.1,Digital Transformation LLC +AI09295,Deep Learning Engineer,186135,USD,186135,EX,FT,Israel,M,Singapore,50,"Hadoop, R, Python, TensorFlow, PyTorch",Master,14,Retail,2024-03-17,2024-04-16,1967,9.8,DeepTech Ventures +AI09296,Machine Learning Engineer,53611,USD,53611,EN,FT,Finland,M,United States,0,"Scala, Python, Deep Learning, Spark, Git",Bachelor,0,Automotive,2024-07-22,2024-08-24,1846,6,Predictive Systems +AI09297,Deep Learning Engineer,94103,USD,94103,MI,FL,Sweden,M,Sweden,100,"Scala, SQL, MLOps, Data Visualization",PhD,3,Gaming,2025-04-20,2025-05-23,1959,8.2,AI Innovations +AI09298,AI Specialist,87733,SGD,114053,EN,FT,Singapore,L,Singapore,100,"Spark, Linux, SQL",Associate,0,Finance,2024-01-02,2024-02-29,632,5.9,Algorithmic Solutions +AI09299,Data Engineer,128376,USD,128376,MI,PT,Denmark,M,Denmark,100,"Python, SQL, PyTorch",Master,2,Healthcare,2024-01-22,2024-03-01,985,8.7,Machine Intelligence Group +AI09300,Head of AI,85553,EUR,72720,MI,FL,Germany,L,Germany,0,"Spark, TensorFlow, Tableau",Master,2,Media,2025-04-23,2025-05-27,934,6.8,DeepTech Ventures +AI09301,Robotics Engineer,165398,EUR,140588,EX,PT,Germany,S,Germany,0,"GCP, Kubernetes, SQL, Deep Learning",Master,10,Real Estate,2025-04-05,2025-05-31,2215,9.7,Autonomous Tech +AI09302,AI Product Manager,111102,GBP,83327,SE,FT,United Kingdom,S,United Kingdom,50,"GCP, Scala, Linux",Bachelor,9,Finance,2024-12-25,2025-01-18,2257,5.5,Cloud AI Solutions +AI09303,Machine Learning Researcher,259032,EUR,220177,EX,FT,Netherlands,L,Netherlands,50,"Python, SQL, R",Associate,18,Government,2025-04-20,2025-07-01,2247,9.6,TechCorp Inc +AI09304,Machine Learning Researcher,64774,EUR,55058,MI,FL,Austria,S,Austria,0,"PyTorch, Hadoop, Computer Vision",PhD,3,Education,2025-02-25,2025-05-06,1421,7.3,Neural Networks Co +AI09305,Data Engineer,221161,EUR,187987,EX,FT,Germany,M,Australia,50,"Computer Vision, TensorFlow, Kubernetes",Bachelor,19,Healthcare,2024-12-24,2025-01-19,725,6.8,Cognitive Computing +AI09306,Deep Learning Engineer,240461,AUD,324622,EX,FT,Australia,L,Australia,50,"Git, SQL, Statistics, Linux",Bachelor,18,Healthcare,2025-03-13,2025-05-14,1914,9,Smart Analytics +AI09307,Data Scientist,95043,SGD,123556,MI,FL,Singapore,S,Singapore,50,"Python, TensorFlow, Tableau",PhD,2,Manufacturing,2024-08-02,2024-10-14,2189,9.3,Advanced Robotics +AI09308,AI Consultant,39308,USD,39308,EN,PT,South Korea,S,Poland,0,"Kubernetes, Git, Deep Learning, TensorFlow, Spark",Associate,1,Transportation,2024-05-06,2024-06-20,1885,7.6,Predictive Systems +AI09309,Machine Learning Engineer,118281,USD,118281,SE,FT,South Korea,L,South Korea,100,"Docker, R, Statistics, Hadoop, GCP",Associate,9,Real Estate,2024-06-06,2024-08-05,2323,7.8,DataVision Ltd +AI09310,Data Analyst,107506,EUR,91380,MI,FT,Netherlands,M,Ireland,100,"Docker, Python, Data Visualization",PhD,3,Education,2024-07-29,2024-09-08,2123,5.7,Smart Analytics +AI09311,AI Architect,161533,USD,161533,EX,FL,Ireland,L,Ireland,100,"Data Visualization, TensorFlow, Git, Deep Learning",Bachelor,14,Energy,2024-08-20,2024-09-29,2120,8,Smart Analytics +AI09312,Machine Learning Researcher,106952,EUR,90909,MI,FL,Germany,M,Germany,0,"Tableau, TensorFlow, Git, Kubernetes, Docker",Bachelor,4,Technology,2025-04-07,2025-05-12,1647,5,TechCorp Inc +AI09313,Machine Learning Researcher,117619,JPY,12938090,MI,PT,Japan,L,Japan,100,"NLP, Python, GCP, Deep Learning, MLOps",Associate,3,Manufacturing,2024-04-17,2024-06-20,1171,7.2,Predictive Systems +AI09314,AI Research Scientist,164714,USD,164714,SE,FT,United States,L,United States,50,"Tableau, Java, Kubernetes",Bachelor,7,Real Estate,2024-07-06,2024-08-17,511,8.5,Machine Intelligence Group +AI09315,AI Software Engineer,55967,USD,55967,EN,FT,South Korea,M,South Korea,50,"Python, NLP, Mathematics",Associate,1,Media,2025-04-21,2025-05-15,2102,5.3,Autonomous Tech +AI09316,Research Scientist,48225,EUR,40991,EN,FT,Germany,S,Germany,100,"Azure, AWS, GCP, Git",PhD,1,Transportation,2024-04-11,2024-05-03,1919,5.3,Machine Intelligence Group +AI09317,Machine Learning Researcher,99314,USD,99314,MI,CT,United States,S,United States,50,"Statistics, Git, Kubernetes",Master,2,Automotive,2024-08-26,2024-10-06,1365,7,Quantum Computing Inc +AI09318,Research Scientist,61925,CAD,77406,MI,FT,Canada,S,Canada,50,"Git, Azure, Tableau, MLOps",Master,4,Finance,2024-08-06,2024-09-29,2038,9.6,Future Systems +AI09319,AI Research Scientist,64161,SGD,83409,EN,CT,Singapore,M,Singapore,100,"GCP, Hadoop, Docker, Computer Vision",Bachelor,0,Government,2024-09-17,2024-10-15,1222,7.1,Machine Intelligence Group +AI09320,Machine Learning Engineer,59904,USD,59904,SE,CT,China,L,China,100,"Kubernetes, Scala, Tableau",Bachelor,8,Manufacturing,2024-12-26,2025-02-28,942,9.9,Digital Transformation LLC +AI09321,AI Architect,84843,EUR,72117,MI,CT,Austria,L,Austria,50,"PyTorch, Git, Scala",Master,2,Media,2024-02-17,2024-03-11,1296,7.5,Autonomous Tech +AI09322,NLP Engineer,116882,EUR,99350,MI,FL,Netherlands,M,Ukraine,100,"Java, Kubernetes, Azure, Computer Vision",Associate,2,Transportation,2024-03-22,2024-05-14,893,7.7,Autonomous Tech +AI09323,Robotics Engineer,41992,USD,41992,MI,FT,India,L,India,0,"PyTorch, Deep Learning, Mathematics, Spark",Bachelor,4,Finance,2024-11-26,2025-01-09,556,6.6,Algorithmic Solutions +AI09324,Data Scientist,83559,USD,83559,MI,FT,Ireland,L,Singapore,100,"TensorFlow, SQL, Mathematics, Tableau, AWS",Bachelor,3,Government,2025-01-06,2025-02-19,1509,8.9,Advanced Robotics +AI09325,Machine Learning Engineer,165796,USD,165796,EX,FL,Ireland,L,Ireland,100,"Kubernetes, Docker, R, Tableau",Master,15,Government,2025-04-02,2025-04-28,1526,6.8,Quantum Computing Inc +AI09326,Data Scientist,27209,USD,27209,MI,PT,India,S,India,50,"Python, Computer Vision, Data Visualization, TensorFlow, Docker",PhD,2,Transportation,2024-06-06,2024-07-31,627,6.7,Neural Networks Co +AI09327,AI Specialist,238785,EUR,202967,EX,FT,France,L,Ghana,50,"Azure, Python, TensorFlow, MLOps, Computer Vision",PhD,19,Automotive,2024-05-14,2024-06-21,1303,9.7,Predictive Systems +AI09328,AI Specialist,36971,USD,36971,SE,PT,India,S,Argentina,0,"AWS, Tableau, Spark, Mathematics, Computer Vision",PhD,5,Education,2024-03-14,2024-04-06,1849,5.7,Cloud AI Solutions +AI09329,Deep Learning Engineer,281022,USD,281022,EX,FT,Norway,S,Netherlands,100,"Python, Data Visualization, Spark",PhD,12,Retail,2025-04-18,2025-06-15,1583,7,Predictive Systems +AI09330,AI Architect,69740,JPY,7671400,EN,CT,Japan,S,Japan,0,"NLP, GCP, Mathematics, Kubernetes",PhD,1,Education,2024-02-13,2024-04-14,1821,9.8,Algorithmic Solutions +AI09331,AI Architect,117773,USD,117773,MI,FT,United States,M,United States,100,"Hadoop, PyTorch, GCP, AWS",PhD,4,Real Estate,2025-02-28,2025-03-25,1720,6.3,Machine Intelligence Group +AI09332,Research Scientist,149573,USD,149573,EX,FT,Israel,S,Israel,0,"Python, GCP, Hadoop",Master,17,Government,2024-08-06,2024-10-03,1603,8,DeepTech Ventures +AI09333,Machine Learning Researcher,115785,GBP,86839,MI,CT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, Kubernetes, Scala, Hadoop",PhD,4,Automotive,2024-09-18,2024-10-09,1354,5,Predictive Systems +AI09334,Head of AI,155051,JPY,17055610,EX,FT,Japan,S,Estonia,0,"Hadoop, GCP, Linux",Bachelor,14,Technology,2025-04-04,2025-06-02,2362,8,Autonomous Tech +AI09335,AI Software Engineer,69683,SGD,90588,EN,CT,Singapore,M,Singapore,50,"NLP, SQL, Kubernetes",Bachelor,0,Gaming,2024-05-20,2024-06-10,860,5.3,Autonomous Tech +AI09336,Machine Learning Engineer,63898,USD,63898,EN,CT,Ireland,S,Ireland,100,"Mathematics, MLOps, GCP",Associate,0,Technology,2024-07-13,2024-08-04,1335,6.3,Digital Transformation LLC +AI09337,NLP Engineer,91901,USD,91901,MI,FL,Sweden,M,Sweden,0,"PyTorch, Mathematics, Kubernetes",PhD,4,Finance,2024-06-28,2024-09-07,641,7.8,Autonomous Tech +AI09338,AI Consultant,59695,EUR,50741,EN,FT,France,S,Ghana,100,"R, GCP, PyTorch, AWS",Master,1,Automotive,2024-10-04,2024-10-29,1315,7,Future Systems +AI09339,Data Engineer,65038,GBP,48779,EN,PT,United Kingdom,S,United Kingdom,50,"Docker, Python, Computer Vision, R",Master,0,Real Estate,2024-06-03,2024-08-10,1902,8.5,AI Innovations +AI09340,AI Consultant,86847,USD,86847,MI,FT,Finland,M,Finland,100,"Scala, MLOps, Java",Bachelor,2,Real Estate,2025-03-20,2025-05-08,2066,9,Advanced Robotics +AI09341,Deep Learning Engineer,34236,USD,34236,MI,FT,China,M,China,0,"TensorFlow, R, Linux",Associate,4,Telecommunications,2024-04-18,2024-06-01,2369,5.6,AI Innovations +AI09342,AI Consultant,160503,EUR,136428,SE,FL,France,L,Australia,50,"AWS, Python, Data Visualization",Bachelor,8,Government,2024-12-05,2025-01-07,1991,7,Algorithmic Solutions +AI09343,Machine Learning Engineer,120317,USD,120317,SE,FT,Israel,M,Israel,50,"SQL, Docker, TensorFlow, Linux, Tableau",Bachelor,6,Education,2025-01-05,2025-02-20,1725,9.6,Neural Networks Co +AI09344,Principal Data Scientist,79295,EUR,67401,EN,PT,France,L,France,100,"GCP, SQL, Scala, Python",Master,0,Real Estate,2024-04-13,2024-06-15,2373,6.9,Quantum Computing Inc +AI09345,Principal Data Scientist,57136,EUR,48566,EN,PT,Austria,M,United States,50,"Linux, Scala, TensorFlow",Master,0,Real Estate,2024-02-23,2024-04-03,1669,6.7,Autonomous Tech +AI09346,Research Scientist,109133,USD,109133,SE,PT,Israel,M,Israel,0,"Java, R, Statistics, SQL",PhD,8,Telecommunications,2025-03-17,2025-05-02,2042,8.7,Smart Analytics +AI09347,Machine Learning Engineer,226278,CHF,203650,EX,FT,Switzerland,M,Switzerland,50,"Mathematics, Scala, Azure",PhD,15,Media,2025-01-20,2025-03-29,1514,9.2,Autonomous Tech +AI09348,ML Ops Engineer,67762,USD,67762,EN,FT,Finland,S,Finland,100,"Kubernetes, Data Visualization, MLOps, Python",Associate,0,Gaming,2024-11-21,2024-12-10,1779,8.1,DeepTech Ventures +AI09349,Research Scientist,158626,USD,158626,SE,FT,Norway,S,Norway,0,"Python, Scala, Java, TensorFlow",PhD,9,Government,2024-06-23,2024-07-12,1918,5.6,Smart Analytics +AI09350,Research Scientist,35902,USD,35902,MI,FT,India,M,Philippines,0,"Linux, Spark, Data Visualization, Java, Mathematics",Bachelor,2,Finance,2024-05-30,2024-08-04,2143,6.3,Future Systems +AI09351,AI Specialist,199630,EUR,169686,EX,FL,France,S,France,100,"Linux, Hadoop, Data Visualization, MLOps",Associate,19,Retail,2024-03-14,2024-04-28,2431,6.4,Cognitive Computing +AI09352,ML Ops Engineer,34288,USD,34288,MI,PT,India,L,Austria,0,"Python, AWS, SQL, Data Visualization",Associate,3,Telecommunications,2024-12-29,2025-02-20,688,8.8,Autonomous Tech +AI09353,AI Consultant,64165,USD,64165,EN,PT,Finland,L,Finland,100,"Kubernetes, Deep Learning, Data Visualization, Python",Master,0,Healthcare,2024-02-23,2024-04-20,2185,5.9,Quantum Computing Inc +AI09354,AI Architect,68161,CAD,85201,EN,CT,Canada,L,Canada,100,"Scala, Azure, Statistics, Linux, PyTorch",PhD,1,Transportation,2024-08-25,2024-10-29,1318,5.2,Machine Intelligence Group +AI09355,Deep Learning Engineer,190540,AUD,257229,EX,PT,Australia,S,Australia,100,"SQL, Azure, Scala, Tableau, Spark",Associate,17,Automotive,2025-01-23,2025-02-11,1879,5.1,Digital Transformation LLC +AI09356,AI Consultant,145966,USD,145966,EX,FT,South Korea,S,South Korea,50,"PyTorch, TensorFlow, Python",Bachelor,13,Media,2024-10-09,2024-12-02,2054,8.6,Autonomous Tech +AI09357,AI Research Scientist,64339,USD,64339,MI,PT,South Korea,S,Belgium,0,"Java, R, Python, AWS",Associate,2,Consulting,2024-07-13,2024-08-18,632,6.7,Advanced Robotics +AI09358,Computer Vision Engineer,72089,GBP,54067,EN,FT,United Kingdom,L,Ireland,50,"Deep Learning, Scala, Statistics, Computer Vision, Docker",PhD,0,Finance,2025-02-18,2025-04-30,2314,6.2,TechCorp Inc +AI09359,Data Scientist,121917,USD,121917,MI,PT,Sweden,L,China,100,"PyTorch, Hadoop, Java, Kubernetes, MLOps",PhD,4,Finance,2024-01-15,2024-02-28,794,9.3,Advanced Robotics +AI09360,Computer Vision Engineer,62465,EUR,53095,EN,CT,Netherlands,M,Japan,0,"Python, AWS, Mathematics, SQL, Java",Associate,1,Energy,2024-01-29,2024-03-21,595,8.6,Autonomous Tech +AI09361,AI Consultant,120168,JPY,13218480,SE,PT,Japan,S,Japan,50,"Statistics, Computer Vision, Kubernetes, TensorFlow",Associate,9,Healthcare,2025-02-18,2025-04-10,781,9.7,Predictive Systems +AI09362,Data Scientist,74225,EUR,63091,MI,FL,France,S,France,100,"R, Git, Scala, Kubernetes",PhD,4,Manufacturing,2024-12-20,2025-02-05,524,7,DeepTech Ventures +AI09363,Head of AI,86630,USD,86630,SE,CT,Israel,S,Czech Republic,100,"Statistics, R, Kubernetes, Computer Vision, SQL",Bachelor,8,Education,2024-09-16,2024-11-19,2024,5.3,AI Innovations +AI09364,Data Analyst,45119,USD,45119,MI,FT,China,S,New Zealand,100,"Kubernetes, Python, Statistics, GCP",Master,4,Gaming,2024-09-15,2024-11-23,2360,5.9,DataVision Ltd +AI09365,Data Analyst,70424,USD,70424,SE,FL,China,M,China,100,"AWS, Docker, GCP, Python",Master,6,Manufacturing,2024-08-11,2024-09-30,1551,5.1,DeepTech Ventures +AI09366,Data Scientist,124107,EUR,105491,SE,PT,France,S,France,0,"Spark, Java, NLP, Computer Vision",Bachelor,7,Finance,2024-02-14,2024-03-08,1939,6.9,Machine Intelligence Group +AI09367,Machine Learning Researcher,104599,CHF,94139,MI,FL,Switzerland,S,Israel,0,"Hadoop, Scala, Deep Learning, NLP, TensorFlow",Master,2,Government,2024-07-05,2024-08-23,1948,9,TechCorp Inc +AI09368,AI Product Manager,130443,SGD,169576,SE,PT,Singapore,M,Singapore,50,"Deep Learning, MLOps, Git, SQL, Kubernetes",Bachelor,7,Finance,2024-09-18,2024-10-02,947,8.5,Cognitive Computing +AI09369,Machine Learning Engineer,51380,USD,51380,SE,PT,China,M,Turkey,100,"Linux, Spark, Kubernetes",Bachelor,7,Manufacturing,2024-04-27,2024-06-30,1994,7.2,Algorithmic Solutions +AI09370,ML Ops Engineer,55972,EUR,47576,EN,PT,France,S,Egypt,100,"Linux, Python, Deep Learning, AWS",Associate,0,Telecommunications,2024-01-13,2024-03-01,1786,6.9,Machine Intelligence Group +AI09371,AI Specialist,140112,EUR,119095,EX,PT,Austria,M,Kenya,100,"Linux, R, Data Visualization",PhD,10,Real Estate,2024-07-03,2024-08-18,991,6.3,DeepTech Ventures +AI09372,Research Scientist,77842,EUR,66166,EN,FL,Netherlands,M,Netherlands,100,"Statistics, Hadoop, Python",Master,1,Healthcare,2024-05-09,2024-07-14,1380,5,Cloud AI Solutions +AI09373,Data Analyst,143720,USD,143720,EX,FL,South Korea,M,Ukraine,50,"Scala, AWS, Azure, Computer Vision, Statistics",Associate,16,Technology,2024-06-09,2024-07-23,566,6.9,Cognitive Computing +AI09374,Machine Learning Engineer,93910,USD,93910,MI,CT,South Korea,L,Netherlands,100,"GCP, NLP, Data Visualization, Python, Linux",Master,2,Consulting,2024-12-31,2025-02-27,748,9.8,Autonomous Tech +AI09375,NLP Engineer,92622,JPY,10188420,MI,CT,Japan,M,Estonia,50,"Statistics, Kubernetes, R, Scala",Associate,2,Healthcare,2024-05-09,2024-06-26,508,8.6,Cognitive Computing +AI09376,Data Analyst,207950,USD,207950,EX,FL,Ireland,S,Portugal,0,"Hadoop, GCP, Statistics, Deep Learning",Bachelor,16,Gaming,2024-05-17,2024-06-21,823,5.1,Cognitive Computing +AI09377,AI Research Scientist,52390,CAD,65488,EN,FT,Canada,S,Ireland,50,"Deep Learning, Python, Docker",Master,0,Finance,2024-06-29,2024-08-19,818,8.7,Smart Analytics +AI09378,NLP Engineer,72765,EUR,61850,MI,FT,Germany,S,Germany,50,"AWS, Kubernetes, GCP, NLP",PhD,4,Telecommunications,2024-06-13,2024-08-25,604,9.9,Quantum Computing Inc +AI09379,Robotics Engineer,95125,EUR,80856,SE,PT,France,S,Turkey,0,"Python, Java, Kubernetes, TensorFlow, Docker",Master,7,Media,2024-09-06,2024-11-12,1188,6.3,DataVision Ltd +AI09380,Data Analyst,86783,USD,86783,EX,CT,China,S,China,50,"Kubernetes, Java, MLOps",Associate,10,Real Estate,2025-01-16,2025-02-23,1979,5.6,Predictive Systems +AI09381,Principal Data Scientist,195942,SGD,254725,EX,CT,Singapore,S,Singapore,50,"PyTorch, Python, Linux, Mathematics",Bachelor,18,Automotive,2024-02-24,2024-05-05,2119,9.8,Algorithmic Solutions +AI09382,AI Architect,88045,USD,88045,SE,PT,Finland,S,Finland,0,"AWS, Kubernetes, Java, GCP, Azure",Master,8,Media,2024-05-24,2024-06-10,1613,6.5,DataVision Ltd +AI09383,ML Ops Engineer,34080,USD,34080,EN,PT,China,S,China,100,"Python, Tableau, Statistics, Deep Learning",Associate,0,Telecommunications,2024-08-15,2024-08-30,858,6.4,Algorithmic Solutions +AI09384,Machine Learning Researcher,159791,AUD,215718,SE,CT,Australia,L,Australia,0,"TensorFlow, Mathematics, Data Visualization, Linux",Associate,9,Media,2024-11-05,2025-01-12,1415,5.4,Smart Analytics +AI09385,Computer Vision Engineer,82207,EUR,69876,MI,CT,Germany,M,Germany,100,"Kubernetes, Java, Docker, R, Statistics",Master,2,Telecommunications,2024-08-18,2024-10-28,2049,6.4,DataVision Ltd +AI09386,Computer Vision Engineer,121634,USD,121634,SE,CT,South Korea,M,Argentina,50,"R, SQL, Data Visualization",Master,6,Healthcare,2025-02-04,2025-03-25,1979,8.6,Smart Analytics +AI09387,AI Research Scientist,29142,USD,29142,EN,CT,India,L,India,0,"Linux, Hadoop, Data Visualization, Spark",Bachelor,1,Technology,2024-10-18,2024-11-13,2226,5.3,Advanced Robotics +AI09388,AI Software Engineer,62502,JPY,6875220,EN,PT,Japan,L,Japan,100,"Kubernetes, Python, Spark, Docker, Git",Bachelor,0,Gaming,2025-01-22,2025-03-06,1769,6.4,DeepTech Ventures +AI09389,NLP Engineer,106016,USD,106016,EX,PT,South Korea,S,South Korea,100,"Mathematics, Python, Statistics, Git, TensorFlow",Master,18,Energy,2025-03-19,2025-05-26,658,9,Algorithmic Solutions +AI09390,Machine Learning Engineer,223388,USD,223388,EX,FT,United States,S,United States,0,"Python, Spark, TensorFlow, GCP, PyTorch",Bachelor,13,Retail,2024-04-13,2024-05-02,776,7.7,Autonomous Tech +AI09391,AI Product Manager,260456,JPY,28650160,EX,CT,Japan,L,Poland,50,"Hadoop, Deep Learning, Tableau",Bachelor,13,Manufacturing,2024-04-11,2024-05-12,1344,6.3,Advanced Robotics +AI09392,Deep Learning Engineer,122043,AUD,164758,SE,FL,Australia,S,Malaysia,100,"SQL, R, Python, Statistics",PhD,9,Government,2025-04-14,2025-05-26,528,8.4,Autonomous Tech +AI09393,AI Software Engineer,79246,EUR,67359,MI,CT,Germany,S,Germany,50,"Kubernetes, Deep Learning, Java, Azure, R",Associate,4,Media,2025-01-18,2025-03-04,1975,8.8,AI Innovations +AI09394,AI Specialist,200872,GBP,150654,EX,PT,United Kingdom,L,Sweden,100,"Computer Vision, Statistics, Docker",Associate,14,Technology,2024-06-26,2024-09-05,2354,5.4,TechCorp Inc +AI09395,Head of AI,103261,AUD,139402,SE,FL,Australia,M,Australia,0,"Docker, SQL, Azure, AWS",Bachelor,5,Gaming,2025-03-11,2025-04-08,1989,10,Cloud AI Solutions +AI09396,AI Software Engineer,56852,USD,56852,EN,FT,Sweden,S,Sweden,50,"Git, Computer Vision, Data Visualization",Associate,1,Consulting,2024-02-26,2024-04-12,1249,8,Digital Transformation LLC +AI09397,Data Engineer,87803,AUD,118534,MI,CT,Australia,L,Australia,100,"PyTorch, GCP, Java, Docker, Tableau",Associate,4,Automotive,2024-10-23,2024-12-02,1156,7.5,TechCorp Inc +AI09398,ML Ops Engineer,63510,USD,63510,EN,FL,Israel,L,Israel,50,"SQL, Azure, TensorFlow, Computer Vision, R",Associate,1,Consulting,2025-04-14,2025-04-28,1830,7.1,DataVision Ltd +AI09399,Deep Learning Engineer,92068,USD,92068,EN,PT,United States,M,United States,50,"MLOps, Kubernetes, Python",Associate,1,Telecommunications,2024-10-03,2024-11-21,2475,6.3,Algorithmic Solutions +AI09400,NLP Engineer,75818,GBP,56864,MI,FL,United Kingdom,S,United States,100,"PyTorch, Java, AWS, GCP, TensorFlow",Associate,4,Technology,2025-01-17,2025-03-13,2063,6.9,Autonomous Tech +AI09401,Deep Learning Engineer,120141,USD,120141,SE,PT,Ireland,S,Malaysia,0,"Java, GCP, Python, Linux, MLOps",PhD,6,Media,2024-04-14,2024-06-16,2469,7.6,Quantum Computing Inc +AI09402,Principal Data Scientist,77151,USD,77151,MI,PT,Sweden,S,Sweden,50,"Linux, Statistics, Java",PhD,2,Automotive,2025-03-17,2025-05-05,1385,5.3,AI Innovations +AI09403,Principal Data Scientist,69108,USD,69108,MI,CT,South Korea,S,Turkey,0,"Python, GCP, TensorFlow, Data Visualization",Master,4,Consulting,2024-04-28,2024-05-23,2108,6.2,Quantum Computing Inc +AI09404,Machine Learning Researcher,209966,EUR,178471,EX,PT,France,L,Finland,100,"Linux, Azure, Kubernetes, Docker, Git",PhD,19,Real Estate,2024-06-30,2024-08-14,937,9,Algorithmic Solutions +AI09405,Robotics Engineer,75780,USD,75780,EN,PT,Ireland,M,Ireland,0,"MLOps, PyTorch, Mathematics, Kubernetes",Associate,1,Retail,2024-03-28,2024-05-03,1240,9.9,Future Systems +AI09406,AI Product Manager,59033,AUD,79695,EN,PT,Australia,L,Egypt,50,"Python, NLP, Tableau, TensorFlow",Master,0,Gaming,2025-02-01,2025-03-29,1668,8.1,Future Systems +AI09407,Data Engineer,173659,USD,173659,EX,CT,Ireland,M,Ireland,100,"Hadoop, Statistics, TensorFlow, Spark",PhD,15,Technology,2024-11-21,2025-01-29,1737,7.4,DataVision Ltd +AI09408,AI Architect,218617,USD,218617,EX,FT,Ireland,S,Ireland,50,"MLOps, Git, AWS, Docker",Bachelor,18,Consulting,2025-04-13,2025-06-08,878,6.9,AI Innovations +AI09409,AI Consultant,51900,USD,51900,SE,PT,India,M,South Africa,100,"Git, Python, MLOps",Bachelor,6,Gaming,2024-04-11,2024-06-06,1782,8.4,Digital Transformation LLC +AI09410,Autonomous Systems Engineer,83722,EUR,71164,MI,FT,Germany,S,Germany,100,"Git, Linux, Data Visualization",PhD,4,Real Estate,2025-04-14,2025-06-16,1176,9.3,TechCorp Inc +AI09411,ML Ops Engineer,64831,CAD,81039,EN,FL,Canada,S,Kenya,50,"NLP, Python, SQL, Linux, GCP",Master,1,Transportation,2024-05-16,2024-07-20,1981,5.5,Algorithmic Solutions +AI09412,AI Research Scientist,80478,JPY,8852580,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, GCP, Java, PyTorch",Master,1,Telecommunications,2024-06-15,2024-08-12,1157,9.6,AI Innovations +AI09413,Machine Learning Engineer,152682,CHF,137414,MI,FL,Switzerland,M,Switzerland,100,"Linux, Docker, R",Bachelor,2,Education,2025-01-22,2025-02-08,2221,7.8,Neural Networks Co +AI09414,Research Scientist,73388,USD,73388,EN,FT,Israel,M,Israel,0,"Hadoop, GCP, Data Visualization, Java, MLOps",Bachelor,0,Education,2025-01-22,2025-03-13,998,7.2,Advanced Robotics +AI09415,Head of AI,191472,AUD,258487,EX,FL,Australia,S,Belgium,0,"Azure, Java, TensorFlow, Linux, Git",Master,18,Automotive,2024-12-07,2025-02-06,654,9.3,Cognitive Computing +AI09416,AI Architect,111011,USD,111011,SE,FT,South Korea,M,South Korea,0,"Data Visualization, Linux, Python, Statistics, Mathematics",Master,5,Energy,2025-03-16,2025-05-28,2347,6.7,Digital Transformation LLC +AI09417,Machine Learning Researcher,61781,JPY,6795910,EN,FT,Japan,M,Singapore,100,"Linux, GCP, MLOps",Bachelor,0,Retail,2025-04-08,2025-05-21,548,8.5,DataVision Ltd +AI09418,NLP Engineer,194729,EUR,165520,EX,FT,France,M,France,50,"Mathematics, Java, Data Visualization",Master,13,Consulting,2024-08-04,2024-09-18,510,8.4,Quantum Computing Inc +AI09419,AI Product Manager,100526,EUR,85447,MI,CT,Netherlands,S,Netherlands,100,"Scala, Docker, Data Visualization",Master,3,Media,2024-06-04,2024-07-03,1421,7.6,DataVision Ltd +AI09420,Data Analyst,92755,USD,92755,MI,CT,Israel,L,Israel,0,"SQL, PyTorch, Azure, Git, R",Master,4,Finance,2024-08-15,2024-10-19,2437,9.7,Cloud AI Solutions +AI09421,Robotics Engineer,97289,GBP,72967,SE,PT,United Kingdom,S,United Kingdom,50,"NLP, AWS, Java",Bachelor,8,Automotive,2024-09-12,2024-09-30,1299,5.1,Autonomous Tech +AI09422,Machine Learning Engineer,153741,USD,153741,EX,FL,South Korea,L,South Korea,100,"Java, Deep Learning, Data Visualization",Bachelor,10,Retail,2024-09-19,2024-10-23,1707,6.7,DeepTech Ventures +AI09423,Head of AI,157987,SGD,205383,EX,CT,Singapore,M,Singapore,50,"Azure, Docker, Tableau",Bachelor,18,Healthcare,2024-02-18,2024-03-14,2161,9.1,Advanced Robotics +AI09424,AI Architect,120516,CHF,108464,MI,PT,Switzerland,M,Norway,50,"Linux, SQL, Computer Vision, Kubernetes",Master,3,Telecommunications,2024-08-26,2024-09-20,657,5.5,DataVision Ltd +AI09425,AI Specialist,203853,EUR,173275,EX,PT,Netherlands,L,Netherlands,50,"Spark, Scala, GCP",PhD,18,Real Estate,2024-03-20,2024-04-27,1169,7.2,Future Systems +AI09426,Data Scientist,142413,USD,142413,SE,CT,Finland,M,Finland,100,"TensorFlow, Python, Scala, Azure, MLOps",Associate,7,Retail,2024-12-04,2025-01-10,1806,8.3,Neural Networks Co +AI09427,Head of AI,173201,CHF,155881,SE,FL,Switzerland,S,Switzerland,100,"Computer Vision, Hadoop, Python",PhD,6,Finance,2024-07-02,2024-07-28,1290,8.9,Machine Intelligence Group +AI09428,Autonomous Systems Engineer,204387,CAD,255484,EX,FL,Canada,S,Thailand,50,"Computer Vision, TensorFlow, NLP, Python, Data Visualization",Associate,13,Government,2025-01-08,2025-02-03,1275,5.7,Algorithmic Solutions +AI09429,AI Specialist,24626,USD,24626,EN,PT,India,S,India,50,"Azure, Spark, SQL, Docker, Hadoop",Bachelor,0,Energy,2024-10-25,2024-12-14,2213,6.7,Cognitive Computing +AI09430,Data Engineer,30632,USD,30632,MI,FL,China,S,United States,100,"Docker, Python, GCP, TensorFlow, AWS",Bachelor,3,Technology,2025-02-03,2025-03-09,2442,7.1,Cognitive Computing +AI09431,Data Scientist,51880,CAD,64850,EN,FT,Canada,S,Canada,0,"R, PyTorch, Hadoop",PhD,1,Government,2024-11-23,2025-01-16,1334,8.9,Quantum Computing Inc +AI09432,Autonomous Systems Engineer,105546,USD,105546,SE,CT,Ireland,M,Ireland,0,"Data Visualization, Mathematics, Java, Computer Vision, Scala",Bachelor,5,Manufacturing,2024-07-06,2024-08-07,1958,9.4,TechCorp Inc +AI09433,AI Product Manager,156352,EUR,132899,EX,FT,France,S,France,100,"R, Scala, Computer Vision",Associate,18,Consulting,2024-09-17,2024-10-20,1481,7.5,TechCorp Inc +AI09434,Autonomous Systems Engineer,82869,USD,82869,MI,PT,Sweden,S,Sweden,0,"Hadoop, MLOps, Git",Master,4,Gaming,2024-04-10,2024-06-07,2048,5.3,AI Innovations +AI09435,Robotics Engineer,249284,EUR,211891,EX,PT,Germany,L,Finland,50,"Data Visualization, Hadoop, Statistics",Master,10,Education,2025-02-17,2025-04-19,1549,6.4,DeepTech Ventures +AI09436,AI Consultant,143332,EUR,121832,EX,FT,France,S,South Africa,50,"TensorFlow, Computer Vision, MLOps, Tableau, Kubernetes",Master,12,Telecommunications,2024-03-27,2024-05-14,1786,5.1,Cognitive Computing +AI09437,Data Analyst,102445,USD,102445,MI,CT,Denmark,S,Denmark,50,"SQL, Scala, AWS",Master,3,Consulting,2024-12-01,2025-02-06,1144,8.9,Predictive Systems +AI09438,Computer Vision Engineer,95141,CAD,118926,SE,PT,Canada,S,Netherlands,0,"SQL, PyTorch, R, Mathematics",Bachelor,5,Gaming,2024-07-05,2024-08-10,1531,9.4,Autonomous Tech +AI09439,Computer Vision Engineer,85527,EUR,72698,MI,FL,France,S,France,0,"Linux, R, Statistics, Kubernetes",Bachelor,2,Healthcare,2024-02-19,2024-04-28,543,9.9,DataVision Ltd +AI09440,Autonomous Systems Engineer,84275,EUR,71634,MI,CT,Austria,L,Austria,100,"Git, Linux, Python",Master,4,Healthcare,2024-11-01,2024-11-23,1865,6.5,Digital Transformation LLC +AI09441,Data Analyst,171765,USD,171765,EX,FL,Finland,S,Finland,100,"Tableau, NLP, Hadoop, Python",Master,10,Manufacturing,2024-07-29,2024-08-21,2398,6.2,Cognitive Computing +AI09442,Robotics Engineer,47657,USD,47657,MI,FT,China,L,China,0,"Computer Vision, Kubernetes, Java",Bachelor,4,Transportation,2025-04-26,2025-07-06,1427,6.5,Cloud AI Solutions +AI09443,Robotics Engineer,54748,USD,54748,EN,PT,Israel,S,Israel,50,"PyTorch, AWS, Data Visualization, GCP",Master,0,Education,2024-05-28,2024-07-31,2405,7.4,Future Systems +AI09444,Data Scientist,47134,AUD,63631,EN,FL,Australia,S,United Kingdom,50,"NLP, Statistics, Kubernetes, Python, GCP",PhD,0,Healthcare,2024-06-28,2024-08-26,613,6.1,DataVision Ltd +AI09445,ML Ops Engineer,84635,AUD,114257,MI,CT,Australia,L,Australia,100,"Kubernetes, SQL, Java, Git",PhD,3,Technology,2024-03-25,2024-05-30,1487,5.6,Future Systems +AI09446,ML Ops Engineer,84203,EUR,71573,MI,FL,France,L,France,100,"PyTorch, Mathematics, Scala",PhD,3,Real Estate,2025-02-26,2025-04-17,2353,6.5,Predictive Systems +AI09447,AI Product Manager,105870,EUR,89990,MI,PT,Netherlands,L,Netherlands,100,"Python, Linux, TensorFlow, Hadoop, PyTorch",Bachelor,4,Automotive,2024-07-29,2024-10-04,1615,5.4,DataVision Ltd +AI09448,AI Architect,66252,USD,66252,EX,CT,China,M,Russia,0,"Statistics, PyTorch, Tableau",Master,16,Healthcare,2024-11-30,2024-12-26,897,9.8,Neural Networks Co +AI09449,Data Engineer,91263,USD,91263,MI,FT,Finland,M,Finland,0,"GCP, PyTorch, Deep Learning, Mathematics, Computer Vision",Master,4,Finance,2024-10-01,2024-11-09,1366,7.7,Digital Transformation LLC +AI09450,Machine Learning Researcher,69243,USD,69243,EN,FT,Israel,M,Israel,50,"Azure, Python, SQL, Tableau, TensorFlow",Master,0,Manufacturing,2024-10-10,2024-12-16,689,6.2,TechCorp Inc +AI09451,Principal Data Scientist,137522,USD,137522,SE,PT,Ireland,M,France,100,"AWS, Tableau, Python",Bachelor,7,Government,2024-07-07,2024-07-28,709,6.8,Digital Transformation LLC +AI09452,NLP Engineer,266422,GBP,199817,EX,FT,United Kingdom,L,United Kingdom,50,"R, AWS, Data Visualization",PhD,11,Gaming,2024-03-29,2024-05-03,817,7.1,DeepTech Ventures +AI09453,Machine Learning Researcher,199823,EUR,169850,EX,PT,France,S,France,50,"Java, MLOps, GCP, AWS, PyTorch",Associate,12,Media,2024-02-25,2024-03-31,2329,6.6,Machine Intelligence Group +AI09454,NLP Engineer,69686,USD,69686,EN,CT,Ireland,M,Ireland,100,"Data Visualization, SQL, NLP, Kubernetes, Python",Associate,0,Real Estate,2025-01-25,2025-02-15,1109,7,Autonomous Tech +AI09455,Principal Data Scientist,173317,USD,173317,EX,FT,Denmark,S,Denmark,50,"TensorFlow, Scala, Statistics",PhD,18,Technology,2024-12-17,2025-02-23,1801,8.7,Future Systems +AI09456,Robotics Engineer,181014,EUR,153862,EX,FT,Austria,S,Austria,0,"Kubernetes, GCP, Python, Mathematics",PhD,18,Retail,2024-11-16,2025-01-05,1255,6,Predictive Systems +AI09457,AI Research Scientist,262405,USD,262405,EX,PT,Finland,L,Finland,0,"Deep Learning, Python, Azure, SQL",Master,19,Finance,2024-03-31,2024-05-27,2116,8.8,Machine Intelligence Group +AI09458,Data Engineer,109773,JPY,12075030,MI,FT,Japan,M,Vietnam,50,"Python, Tableau, Computer Vision",Bachelor,2,Gaming,2025-01-06,2025-02-25,2433,5.7,TechCorp Inc +AI09459,Data Scientist,81338,CAD,101673,EN,FL,Canada,L,Canada,0,"MLOps, Data Visualization, AWS, Python, TensorFlow",Bachelor,1,Healthcare,2025-01-23,2025-03-30,550,7.2,DataVision Ltd +AI09460,AI Research Scientist,147302,SGD,191493,SE,PT,Singapore,M,Singapore,0,"SQL, AWS, Kubernetes, Hadoop",Associate,5,Education,2024-05-27,2024-07-17,1214,7.5,Advanced Robotics +AI09461,Data Scientist,89314,CAD,111643,MI,PT,Canada,L,Romania,0,"Python, TensorFlow, Data Visualization, Git, Statistics",PhD,3,Technology,2024-01-25,2024-03-12,590,9.3,DataVision Ltd +AI09462,Head of AI,131205,USD,131205,SE,CT,Ireland,L,Ireland,0,"R, Python, TensorFlow, Java",Associate,8,Finance,2024-10-17,2024-12-12,1799,7.1,Cognitive Computing +AI09463,ML Ops Engineer,236960,EUR,201416,EX,FT,Netherlands,S,Netherlands,50,"Data Visualization, R, Linux, Tableau",Associate,12,Media,2024-05-12,2024-07-10,1716,9.1,Neural Networks Co +AI09464,Research Scientist,70521,EUR,59943,EN,FL,Netherlands,M,Nigeria,50,"Git, Python, TensorFlow",Bachelor,1,Telecommunications,2024-09-23,2024-11-21,2406,9.2,Advanced Robotics +AI09465,NLP Engineer,22718,USD,22718,EN,CT,India,M,India,100,"Computer Vision, SQL, Python",PhD,1,Consulting,2025-04-28,2025-06-01,2464,6.6,AI Innovations +AI09466,Autonomous Systems Engineer,302715,USD,302715,EX,PT,Norway,L,New Zealand,0,"Tableau, Python, NLP, Git, MLOps",PhD,12,Technology,2025-01-28,2025-02-21,655,8.2,Future Systems +AI09467,Data Engineer,148771,USD,148771,SE,FL,Finland,L,Finland,100,"PyTorch, GCP, TensorFlow, AWS, Deep Learning",Master,8,Education,2024-12-09,2025-01-28,1688,9.1,Autonomous Tech +AI09468,Principal Data Scientist,168216,USD,168216,SE,CT,United States,M,United States,50,"GCP, Linux, Docker, Hadoop",Bachelor,6,Telecommunications,2024-12-07,2024-12-27,1732,8.8,DataVision Ltd +AI09469,AI Architect,83184,USD,83184,MI,FL,Sweden,L,Sweden,0,"MLOps, Data Visualization, Hadoop, Java, TensorFlow",Master,4,Real Estate,2024-06-03,2024-08-08,1248,8.2,Cloud AI Solutions +AI09470,Machine Learning Researcher,98439,USD,98439,SE,CT,South Korea,L,South Korea,100,"Python, Git, Computer Vision, NLP, R",Associate,8,Manufacturing,2024-07-25,2024-09-29,1463,7.7,TechCorp Inc +AI09471,ML Ops Engineer,164239,USD,164239,MI,PT,Denmark,L,Denmark,0,"Spark, Computer Vision, Kubernetes, Python, Linux",Bachelor,4,Gaming,2024-06-04,2024-07-26,802,8.3,Digital Transformation LLC +AI09472,AI Product Manager,96933,USD,96933,EN,PT,Norway,L,Nigeria,50,"Data Visualization, AWS, Hadoop, Computer Vision",Bachelor,1,Government,2025-04-21,2025-05-19,1741,8.3,Advanced Robotics +AI09473,Data Analyst,108451,USD,108451,EN,CT,Denmark,L,Denmark,0,"Python, Tableau, Azure",Bachelor,0,Retail,2024-03-30,2024-06-03,620,9,TechCorp Inc +AI09474,Robotics Engineer,63644,AUD,85919,EN,PT,Australia,S,Australia,100,"Docker, Azure, GCP, Python",Master,0,Manufacturing,2024-12-29,2025-02-06,886,6.7,DeepTech Ventures +AI09475,AI Specialist,199800,USD,199800,SE,PT,Norway,L,Norway,100,"GCP, Git, Java",PhD,8,Technology,2024-04-09,2024-05-30,716,6.2,AI Innovations +AI09476,Robotics Engineer,158584,USD,158584,SE,FL,Denmark,L,Denmark,100,"PyTorch, GCP, Scala, Linux, Deep Learning",Associate,8,Real Estate,2024-10-11,2024-11-13,1060,8.8,Future Systems +AI09477,Head of AI,200639,USD,200639,EX,FT,Israel,M,Israel,50,"Docker, Tableau, Python, GCP, Azure",Bachelor,17,Energy,2024-02-10,2024-04-03,2424,6.2,Quantum Computing Inc +AI09478,Research Scientist,76094,USD,76094,EX,FT,China,M,China,50,"GCP, R, NLP, Deep Learning",PhD,19,Automotive,2025-03-28,2025-06-06,612,9.8,Cloud AI Solutions +AI09479,AI Research Scientist,24147,USD,24147,MI,FT,India,S,India,50,"GCP, Computer Vision, Kubernetes, Linux, Data Visualization",Bachelor,3,Retail,2024-10-31,2024-12-02,950,9.5,Machine Intelligence Group +AI09480,AI Research Scientist,50123,EUR,42605,EN,PT,France,M,France,50,"Python, Spark, NLP, R",PhD,1,Manufacturing,2024-01-06,2024-03-10,540,5.5,Smart Analytics +AI09481,Robotics Engineer,110573,USD,110573,SE,CT,South Korea,L,South Korea,0,"NLP, GCP, Hadoop",Associate,7,Retail,2024-07-27,2024-09-07,798,5.2,DeepTech Ventures +AI09482,NLP Engineer,108897,USD,108897,MI,CT,Sweden,M,Norway,0,"Kubernetes, Python, TensorFlow, Docker, PyTorch",PhD,4,Automotive,2024-03-10,2024-05-06,715,8.6,Advanced Robotics +AI09483,Principal Data Scientist,330519,USD,330519,EX,PT,Norway,L,Norway,50,"Statistics, Azure, PyTorch, MLOps, SQL",Master,11,Consulting,2025-02-04,2025-03-03,544,5.8,Cloud AI Solutions +AI09484,Deep Learning Engineer,64196,JPY,7061560,EN,FL,Japan,S,Egypt,0,"Statistics, SQL, Data Visualization",Associate,0,Media,2025-03-23,2025-05-14,911,8,Machine Intelligence Group +AI09485,Data Analyst,112869,USD,112869,EX,FT,China,M,Latvia,50,"Scala, Python, NLP",PhD,19,Media,2025-04-28,2025-06-13,588,5.9,Quantum Computing Inc +AI09486,AI Software Engineer,64664,EUR,54964,EN,FL,Germany,M,Germany,100,"SQL, Hadoop, Kubernetes, PyTorch, AWS",Bachelor,0,Automotive,2024-11-30,2025-01-27,1161,7.8,Algorithmic Solutions +AI09487,AI Consultant,175674,JPY,19324140,SE,PT,Japan,L,Japan,0,"Hadoop, Java, PyTorch",Associate,7,Manufacturing,2024-01-31,2024-03-23,723,6.4,AI Innovations +AI09488,Data Analyst,95581,SGD,124255,MI,CT,Singapore,L,Hungary,0,"Git, Azure, Statistics, TensorFlow, Kubernetes",Associate,2,Manufacturing,2024-08-06,2024-09-03,1006,9.8,Advanced Robotics +AI09489,AI Software Engineer,158682,EUR,134880,SE,CT,Austria,L,Romania,50,"Data Visualization, Spark, Hadoop, MLOps, Scala",Associate,7,Telecommunications,2025-04-09,2025-05-22,2434,6.5,Advanced Robotics +AI09490,NLP Engineer,145879,SGD,189643,SE,PT,Singapore,M,Singapore,0,"Statistics, GCP, Azure",Associate,9,Energy,2024-06-29,2024-07-16,1866,6.5,Predictive Systems +AI09491,AI Specialist,196139,USD,196139,EX,CT,Israel,S,Denmark,50,"R, Mathematics, PyTorch, Kubernetes, Azure",PhD,11,Consulting,2024-11-13,2024-12-27,1979,9.4,AI Innovations +AI09492,Deep Learning Engineer,334470,USD,334470,EX,FL,Denmark,L,Denmark,100,"Git, Computer Vision, Deep Learning, Python, TensorFlow",PhD,13,Media,2025-01-26,2025-02-10,1594,7.8,Machine Intelligence Group +AI09493,Computer Vision Engineer,87626,USD,87626,MI,FT,Ireland,S,Ireland,100,"Java, Data Visualization, Hadoop, R",PhD,3,Technology,2024-12-15,2025-02-15,2127,6.5,Algorithmic Solutions +AI09494,Research Scientist,98110,USD,98110,EX,PT,China,S,China,0,"Azure, Python, Deep Learning",Associate,18,Healthcare,2024-06-23,2024-07-27,774,9.5,Predictive Systems +AI09495,AI Research Scientist,125951,CAD,157439,SE,PT,Canada,S,Brazil,100,"Linux, PyTorch, Kubernetes, Tableau, Git",Bachelor,9,Education,2024-05-31,2024-07-27,2495,7.2,DeepTech Ventures +AI09496,Data Analyst,86390,USD,86390,SE,FL,South Korea,M,Philippines,0,"Kubernetes, Mathematics, Scala, Docker",Bachelor,6,Healthcare,2024-06-06,2024-08-03,1154,7.5,Smart Analytics +AI09497,Data Engineer,28282,USD,28282,EN,FT,India,M,India,0,"R, Statistics, SQL, Azure",Associate,0,Technology,2025-04-05,2025-05-29,1646,5.6,Smart Analytics +AI09498,Data Scientist,145712,CHF,131141,MI,CT,Switzerland,M,South Africa,50,"Scala, Docker, NLP",Bachelor,2,Media,2024-11-01,2024-12-13,1336,6.5,Cognitive Computing +AI09499,Machine Learning Engineer,90645,EUR,77048,MI,CT,Germany,L,Germany,50,"Docker, SQL, GCP, TensorFlow",PhD,4,Healthcare,2025-02-08,2025-03-28,2137,8.3,Autonomous Tech +AI09500,Head of AI,82283,SGD,106968,EN,CT,Singapore,M,Singapore,0,"Spark, Hadoop, AWS, Data Visualization, Java",Associate,1,Gaming,2024-11-27,2024-12-20,1536,7.8,Algorithmic Solutions +AI09501,AI Architect,71045,USD,71045,EX,CT,India,M,India,100,"SQL, TensorFlow, MLOps, Docker, Python",Master,19,Manufacturing,2024-01-20,2024-03-20,717,5.9,Smart Analytics +AI09502,Data Scientist,62430,USD,62430,SE,CT,China,L,China,0,"Scala, Statistics, Python",Master,6,Technology,2024-10-23,2025-01-02,1617,9.3,Algorithmic Solutions +AI09503,Principal Data Scientist,106555,USD,106555,SE,FL,Finland,S,Finland,0,"R, Python, Hadoop",PhD,9,Finance,2024-04-07,2024-04-26,2418,7.8,DeepTech Ventures +AI09504,AI Software Engineer,71729,USD,71729,EN,PT,Finland,L,Finland,100,"SQL, Python, Azure",Master,0,Real Estate,2024-10-03,2024-11-30,1129,7.5,Autonomous Tech +AI09505,AI Architect,50504,EUR,42928,EN,FT,France,S,France,100,"TensorFlow, Statistics, MLOps, Tableau, Linux",Master,0,Telecommunications,2024-01-16,2024-03-05,808,9.4,Neural Networks Co +AI09506,Data Scientist,113850,AUD,153698,SE,CT,Australia,M,Australia,50,"SQL, Hadoop, Data Visualization",Master,9,Manufacturing,2024-11-18,2025-01-26,2066,9.5,TechCorp Inc +AI09507,NLP Engineer,315569,USD,315569,EX,PT,United States,L,United States,50,"Tableau, Scala, R, Statistics, TensorFlow",Associate,14,Technology,2024-04-22,2024-05-08,644,8,Future Systems +AI09508,Machine Learning Engineer,235397,GBP,176548,EX,FT,United Kingdom,L,Israel,0,"Java, SQL, Mathematics, Kubernetes",Master,15,Telecommunications,2025-02-05,2025-04-14,503,8.8,Cloud AI Solutions +AI09509,Machine Learning Engineer,126375,USD,126375,MI,FT,Denmark,L,Argentina,50,"Java, Kubernetes, TensorFlow, NLP",Master,4,Telecommunications,2024-03-02,2024-04-10,1297,9.7,DeepTech Ventures +AI09510,Research Scientist,64708,SGD,84120,EN,CT,Singapore,M,Switzerland,0,"Python, TensorFlow, Mathematics",Master,0,Education,2024-12-29,2025-03-06,2203,8.8,TechCorp Inc +AI09511,Research Scientist,128518,GBP,96389,SE,PT,United Kingdom,M,United Kingdom,100,"Hadoop, Data Visualization, Kubernetes, MLOps, AWS",Bachelor,7,Manufacturing,2024-10-15,2024-11-20,2401,7.7,Neural Networks Co +AI09512,Machine Learning Researcher,103052,USD,103052,SE,FL,South Korea,M,Vietnam,0,"Computer Vision, Spark, Tableau, Python",Associate,9,Telecommunications,2024-10-19,2024-12-15,1990,5.6,Future Systems +AI09513,Data Engineer,98700,EUR,83895,SE,FL,Netherlands,S,Finland,0,"Python, TensorFlow, Azure, Kubernetes",Master,8,Transportation,2024-01-29,2024-03-26,663,8.9,TechCorp Inc +AI09514,Principal Data Scientist,36797,USD,36797,MI,CT,India,L,Philippines,100,"AWS, Python, Kubernetes, Mathematics, Deep Learning",Bachelor,4,Energy,2024-11-23,2025-01-13,1780,8.4,Algorithmic Solutions +AI09515,Head of AI,171574,USD,171574,EX,PT,South Korea,S,South Korea,50,"NLP, Python, Spark, Linux, Java",Master,10,Finance,2024-04-17,2024-06-01,1404,8.9,DataVision Ltd +AI09516,Autonomous Systems Engineer,156283,JPY,17191130,SE,FT,Japan,M,Japan,50,"Data Visualization, R, PyTorch",Master,8,Real Estate,2024-11-29,2025-01-15,939,7.9,TechCorp Inc +AI09517,Robotics Engineer,66972,JPY,7366920,EN,FT,Japan,L,Argentina,50,"Scala, Git, Python, Mathematics, Azure",Associate,0,Consulting,2025-03-20,2025-04-27,769,8.7,Smart Analytics +AI09518,Computer Vision Engineer,122877,CHF,110589,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, MLOps, SQL, Java, PyTorch",PhD,2,Real Estate,2024-08-12,2024-10-19,1550,5.4,Neural Networks Co +AI09519,Data Analyst,245072,USD,245072,EX,FL,United States,L,United States,100,"Mathematics, R, Scala, Hadoop",Master,15,Technology,2024-12-27,2025-02-16,1935,7.8,Quantum Computing Inc +AI09520,Data Engineer,43038,USD,43038,MI,FT,China,S,China,100,"Spark, SQL, MLOps",PhD,2,Telecommunications,2024-04-08,2024-05-23,1670,8.3,Future Systems +AI09521,Autonomous Systems Engineer,111598,EUR,94858,MI,CT,France,L,France,0,"Computer Vision, Linux, SQL",Associate,4,Consulting,2025-02-18,2025-04-11,2363,8.2,Predictive Systems +AI09522,NLP Engineer,251849,JPY,27703390,EX,PT,Japan,L,Japan,0,"Scala, Docker, GCP",PhD,15,Transportation,2024-04-06,2024-05-17,2248,6.3,Digital Transformation LLC +AI09523,Data Analyst,110989,USD,110989,MI,CT,Norway,M,Hungary,0,"Mathematics, Azure, SQL",PhD,3,Government,2024-06-23,2024-08-23,1859,7.8,Autonomous Tech +AI09524,Data Engineer,127024,USD,127024,SE,CT,United States,S,Chile,0,"Java, MLOps, Spark",PhD,8,Gaming,2024-06-21,2024-08-02,1861,7.6,Quantum Computing Inc +AI09525,Research Scientist,332546,USD,332546,EX,FL,Denmark,L,Denmark,100,"MLOps, Azure, Tableau, Python, TensorFlow",Bachelor,14,Energy,2024-01-11,2024-03-04,1609,8.8,Future Systems +AI09526,Head of AI,133295,AUD,179948,SE,CT,Australia,M,Australia,0,"Python, AWS, NLP",Master,5,Consulting,2024-03-09,2024-05-05,2345,7.6,AI Innovations +AI09527,AI Research Scientist,86259,CAD,107824,MI,PT,Canada,L,Canada,50,"Tableau, Computer Vision, PyTorch",Associate,3,Education,2024-04-23,2024-06-08,1409,6.3,Predictive Systems +AI09528,Research Scientist,110503,USD,110503,MI,FL,Norway,M,Norway,0,"AWS, SQL, Tableau",Associate,3,Real Estate,2025-03-27,2025-04-11,1252,9,Algorithmic Solutions +AI09529,AI Architect,108797,EUR,92477,MI,CT,Netherlands,M,Netherlands,50,"AWS, Docker, Mathematics",Bachelor,4,Transportation,2024-08-13,2024-10-08,1802,8.4,Autonomous Tech +AI09530,Data Analyst,184018,USD,184018,EX,PT,South Korea,L,South Korea,0,"Statistics, Data Visualization, Azure, Linux",Master,17,Real Estate,2024-04-13,2024-05-21,1346,6.3,Digital Transformation LLC +AI09531,AI Software Engineer,147794,SGD,192132,SE,PT,Singapore,M,Singapore,100,"Python, TensorFlow, Kubernetes, Hadoop",Associate,6,Government,2024-08-27,2024-09-29,815,9.6,Future Systems +AI09532,Autonomous Systems Engineer,71774,JPY,7895140,MI,FL,Japan,S,Japan,50,"SQL, Git, Tableau",PhD,3,Manufacturing,2024-01-28,2024-03-05,1074,5.2,Cognitive Computing +AI09533,Data Scientist,219834,EUR,186859,EX,PT,Austria,M,Austria,0,"Linux, Statistics, MLOps",Master,18,Retail,2025-04-22,2025-05-12,1865,6.1,AI Innovations +AI09534,ML Ops Engineer,186565,USD,186565,EX,FL,South Korea,M,South Korea,100,"MLOps, Statistics, Python",PhD,17,Manufacturing,2024-07-10,2024-09-19,538,5.1,Digital Transformation LLC +AI09535,Data Analyst,27602,USD,27602,EN,FT,China,M,China,0,"R, Scala, SQL, PyTorch",Bachelor,1,Real Estate,2024-08-26,2024-09-10,885,6.1,Cognitive Computing +AI09536,Robotics Engineer,57129,USD,57129,EN,PT,Israel,S,Israel,50,"Spark, Python, SQL, Azure",PhD,1,Manufacturing,2025-03-20,2025-05-21,1666,8.3,Predictive Systems +AI09537,AI Consultant,22217,USD,22217,EN,FT,India,S,India,100,"SQL, GCP, Statistics, Mathematics, PyTorch",Master,0,Real Estate,2024-12-05,2025-01-06,1760,9.9,AI Innovations +AI09538,Head of AI,67864,USD,67864,EX,PT,China,S,Turkey,0,"Hadoop, Deep Learning, Docker, Mathematics, Scala",Associate,19,Retail,2024-04-21,2024-06-06,501,7.2,Autonomous Tech +AI09539,AI Research Scientist,84278,EUR,71636,EN,FT,Germany,L,Germany,50,"Git, Data Visualization, Scala, Azure, Statistics",PhD,0,Media,2024-08-12,2024-10-18,1838,9.5,Advanced Robotics +AI09540,Machine Learning Researcher,116369,USD,116369,SE,FL,South Korea,M,South Korea,0,"Docker, Linux, Spark, Mathematics, NLP",Associate,5,Technology,2024-11-02,2024-12-15,2197,7.7,Machine Intelligence Group +AI09541,AI Specialist,110779,USD,110779,SE,FT,Israel,M,Israel,0,"PyTorch, NLP, Java, R, Computer Vision",Associate,7,Government,2025-02-15,2025-04-23,1776,6.2,Neural Networks Co +AI09542,Data Scientist,285402,USD,285402,EX,FL,Denmark,S,Denmark,50,"TensorFlow, R, Docker, Mathematics, Data Visualization",Bachelor,11,Real Estate,2024-12-30,2025-01-13,1349,6,Quantum Computing Inc +AI09543,NLP Engineer,169619,USD,169619,SE,FT,Norway,M,Norway,100,"GCP, Linux, Docker, Python",PhD,9,Consulting,2024-03-19,2024-05-03,1063,9.2,Quantum Computing Inc +AI09544,Data Scientist,119460,USD,119460,EX,CT,South Korea,S,South Korea,50,"Scala, Kubernetes, Hadoop, Git, Computer Vision",Master,16,Government,2025-02-05,2025-03-06,1333,8.1,Quantum Computing Inc +AI09545,Data Engineer,141162,USD,141162,MI,CT,Denmark,M,Kenya,0,"MLOps, Python, TensorFlow, Kubernetes",PhD,2,Technology,2024-04-21,2024-06-06,947,8.8,Future Systems +AI09546,AI Specialist,125984,USD,125984,SE,PT,Israel,S,Israel,0,"Scala, Tableau, Mathematics, Azure",Associate,9,Gaming,2025-03-20,2025-05-22,1335,8,Future Systems +AI09547,Robotics Engineer,121116,EUR,102949,SE,FL,France,L,France,50,"GCP, Scala, MLOps",Bachelor,8,Media,2025-02-02,2025-03-16,2159,8.7,Cognitive Computing +AI09548,Robotics Engineer,116096,SGD,150925,MI,CT,Singapore,L,Malaysia,100,"Tableau, Python, Linux, Hadoop, TensorFlow",Associate,3,Energy,2024-03-28,2024-05-08,1044,5,Autonomous Tech +AI09549,AI Architect,120313,USD,120313,SE,PT,Ireland,M,Ireland,50,"Python, Docker, Data Visualization",PhD,6,Consulting,2024-06-23,2024-07-22,1587,8.8,TechCorp Inc +AI09550,AI Software Engineer,136464,USD,136464,SE,FT,Ireland,L,Ireland,100,"Tableau, Linux, TensorFlow",Master,9,Transportation,2024-10-11,2024-12-03,1255,9.4,Digital Transformation LLC +AI09551,AI Research Scientist,95934,USD,95934,MI,FT,Israel,M,Israel,50,"Python, Data Visualization, Java, Azure",Bachelor,2,Government,2024-12-20,2025-01-10,2205,9.7,Autonomous Tech +AI09552,AI Software Engineer,85570,CHF,77013,EN,FT,Switzerland,S,Switzerland,50,"Kubernetes, Computer Vision, Scala, Python",Master,0,Finance,2024-06-16,2024-07-11,2114,6.6,Autonomous Tech +AI09553,AI Research Scientist,61645,AUD,83221,EN,CT,Australia,L,Singapore,50,"Kubernetes, Python, Scala, Computer Vision, TensorFlow",Bachelor,1,Gaming,2024-11-06,2024-11-22,2038,5.6,Algorithmic Solutions +AI09554,NLP Engineer,83872,EUR,71291,MI,FL,Austria,S,Austria,100,"GCP, Scala, Deep Learning, SQL, Computer Vision",Associate,4,Consulting,2024-12-21,2025-01-07,1490,8.8,Quantum Computing Inc +AI09555,Computer Vision Engineer,102899,EUR,87464,MI,FL,Austria,L,Austria,50,"Spark, Scala, Deep Learning, Data Visualization, TensorFlow",PhD,3,Real Estate,2024-11-08,2024-11-30,2454,5.4,Algorithmic Solutions +AI09556,Data Engineer,71513,SGD,92967,EN,FL,Singapore,S,United Kingdom,100,"Scala, Linux, Computer Vision, Kubernetes, Git",Master,0,Manufacturing,2024-10-29,2024-12-10,1345,8.4,Predictive Systems +AI09557,Machine Learning Engineer,115012,USD,115012,SE,FT,South Korea,M,China,0,"Java, R, Kubernetes, Docker",Associate,9,Technology,2024-09-26,2024-11-16,984,5.2,Neural Networks Co +AI09558,Machine Learning Engineer,47215,CAD,59019,EN,PT,Canada,S,Canada,100,"Kubernetes, TensorFlow, Docker",Bachelor,0,Technology,2024-06-11,2024-08-20,1165,6.6,AI Innovations +AI09559,AI Specialist,118372,EUR,100616,SE,FL,France,L,Belgium,100,"Linux, Spark, AWS, Deep Learning",PhD,8,Energy,2025-04-08,2025-05-18,1304,5,Cloud AI Solutions +AI09560,Computer Vision Engineer,147836,AUD,199579,SE,CT,Australia,L,Australia,50,"Git, Kubernetes, SQL, GCP, Azure",Bachelor,8,Manufacturing,2024-04-16,2024-05-11,1611,5.6,DataVision Ltd +AI09561,Data Analyst,224535,EUR,190855,EX,FT,Germany,M,Germany,0,"Statistics, SQL, Azure, Python",Associate,15,Education,2025-02-06,2025-03-10,1882,6.8,Predictive Systems +AI09562,AI Software Engineer,138016,USD,138016,SE,CT,Denmark,M,Denmark,50,"Python, Scala, NLP, Git",Associate,8,Government,2024-08-27,2024-10-11,2108,9.4,Future Systems +AI09563,AI Consultant,93538,USD,93538,EN,PT,Norway,S,Norway,0,"Kubernetes, PyTorch, Statistics",PhD,0,Manufacturing,2024-10-26,2024-12-02,2026,9.3,TechCorp Inc +AI09564,Computer Vision Engineer,120674,USD,120674,SE,PT,United States,S,United States,50,"NLP, Docker, Git",PhD,9,Transportation,2024-10-26,2024-12-23,634,6.2,Autonomous Tech +AI09565,AI Architect,299206,CHF,269285,EX,CT,Switzerland,S,Chile,50,"PyTorch, Linux, MLOps, TensorFlow",PhD,11,Telecommunications,2025-04-22,2025-06-13,1150,8.1,Future Systems +AI09566,AI Specialist,128478,AUD,173445,SE,CT,Australia,L,Australia,50,"Python, TensorFlow, Azure",Master,6,Government,2024-04-17,2024-05-17,1949,7.9,Digital Transformation LLC +AI09567,Machine Learning Researcher,60265,AUD,81358,EN,PT,Australia,M,Australia,50,"Computer Vision, Java, MLOps",Master,1,Gaming,2024-03-16,2024-05-17,773,6.6,Autonomous Tech +AI09568,Computer Vision Engineer,279290,USD,279290,EX,PT,Denmark,S,Hungary,50,"Git, R, Scala, Docker, MLOps",Master,16,Government,2024-06-24,2024-07-23,1099,7.6,DataVision Ltd +AI09569,Computer Vision Engineer,110511,CAD,138139,SE,FT,Canada,L,Estonia,0,"Python, TensorFlow, Linux",Associate,9,Telecommunications,2025-01-08,2025-01-30,2403,9.4,Smart Analytics +AI09570,Data Analyst,108968,USD,108968,SE,CT,South Korea,S,South Korea,100,"PyTorch, Spark, Git, Kubernetes",Associate,8,Technology,2025-04-02,2025-04-22,1818,6.1,Machine Intelligence Group +AI09571,Data Engineer,81290,GBP,60968,MI,FT,United Kingdom,S,Switzerland,0,"Kubernetes, R, PyTorch",Bachelor,3,Consulting,2025-02-27,2025-04-14,1907,6.4,Predictive Systems +AI09572,Robotics Engineer,191881,CHF,172693,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, MLOps, Python, Spark",Bachelor,5,Transportation,2024-12-16,2025-01-19,1266,5.1,Predictive Systems +AI09573,Robotics Engineer,106589,CHF,95930,MI,FT,Switzerland,M,Switzerland,100,"Mathematics, AWS, Computer Vision, TensorFlow",Master,2,Manufacturing,2024-09-28,2024-10-21,1384,6.9,Cognitive Computing +AI09574,Machine Learning Engineer,97626,USD,97626,MI,PT,Ireland,L,Austria,100,"Scala, PyTorch, MLOps",Bachelor,3,Telecommunications,2024-10-04,2024-11-26,2239,8.1,Autonomous Tech +AI09575,AI Architect,141618,USD,141618,MI,FT,Denmark,L,Italy,0,"Data Visualization, Scala, Docker, Python, TensorFlow",Master,2,Government,2024-02-18,2024-04-10,1654,5.2,Digital Transformation LLC +AI09576,Autonomous Systems Engineer,95458,EUR,81139,MI,FL,Netherlands,L,Argentina,0,"Linux, SQL, Java",Bachelor,4,Education,2025-03-25,2025-04-22,2104,6.8,AI Innovations +AI09577,Robotics Engineer,105315,CHF,94784,MI,FL,Switzerland,S,Vietnam,100,"Azure, Python, Linux",PhD,3,Technology,2025-03-22,2025-04-23,507,6.3,DataVision Ltd +AI09578,AI Specialist,71116,EUR,60449,MI,PT,Austria,S,Austria,50,"Mathematics, TensorFlow, Python, Computer Vision, Azure",Master,3,Finance,2025-01-11,2025-03-22,2210,6.9,DeepTech Ventures +AI09579,Autonomous Systems Engineer,82679,EUR,70277,EN,FT,Netherlands,L,China,0,"Scala, NLP, GCP",Associate,0,Automotive,2024-03-14,2024-04-12,1625,8.7,Algorithmic Solutions +AI09580,Machine Learning Engineer,177922,EUR,151234,EX,FT,Germany,S,Germany,0,"Data Visualization, Git, TensorFlow",Associate,12,Healthcare,2024-12-05,2025-01-23,1334,9.3,DeepTech Ventures +AI09581,Data Scientist,31465,USD,31465,EN,FT,India,L,India,0,"Scala, Linux, SQL, PyTorch",Master,1,Transportation,2024-05-23,2024-06-11,1808,6.1,DeepTech Ventures +AI09582,AI Specialist,114364,USD,114364,EN,FL,Denmark,L,Denmark,0,"AWS, NLP, Tableau, Docker",Bachelor,1,Finance,2024-08-24,2024-10-02,582,7.7,DeepTech Ventures +AI09583,Data Scientist,206549,USD,206549,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, MLOps",Associate,15,Gaming,2024-05-04,2024-06-07,2093,8,Neural Networks Co +AI09584,Computer Vision Engineer,112749,EUR,95837,SE,FL,Germany,M,Turkey,100,"Hadoop, Git, Computer Vision, R, Java",PhD,6,Education,2024-09-09,2024-11-10,2317,7.4,DataVision Ltd +AI09585,Machine Learning Researcher,97146,EUR,82574,MI,CT,France,M,France,50,"PyTorch, AWS, Hadoop, Azure, Deep Learning",PhD,2,Real Estate,2025-01-13,2025-01-27,1832,7.3,DeepTech Ventures +AI09586,Research Scientist,35698,USD,35698,SE,FL,India,S,India,0,"Linux, GCP, PyTorch, NLP, Scala",Associate,5,Media,2024-02-02,2024-04-10,2048,5.7,Future Systems +AI09587,AI Research Scientist,64209,USD,64209,EN,CT,Israel,M,Israel,100,"Tableau, GCP, Java",Master,1,Telecommunications,2024-07-22,2024-09-02,1711,6.1,Advanced Robotics +AI09588,Robotics Engineer,108749,USD,108749,EN,FT,United States,L,United States,100,"Mathematics, Python, TensorFlow, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-11-09,1228,7.8,DeepTech Ventures +AI09589,AI Research Scientist,78664,USD,78664,MI,CT,Sweden,M,Australia,50,"TensorFlow, Python, GCP, Deep Learning, NLP",Associate,4,Finance,2024-11-26,2024-12-31,1225,9.1,Predictive Systems +AI09590,Autonomous Systems Engineer,72106,SGD,93738,MI,CT,Singapore,S,Singapore,0,"Data Visualization, Python, AWS, GCP, TensorFlow",Associate,4,Government,2024-01-04,2024-03-10,2323,9.6,TechCorp Inc +AI09591,Deep Learning Engineer,41945,USD,41945,MI,FL,China,S,China,0,"TensorFlow, Deep Learning, Data Visualization, Hadoop",PhD,2,Technology,2024-11-01,2025-01-07,2002,5.6,DataVision Ltd +AI09592,AI Consultant,135711,USD,135711,SE,FL,Sweden,S,Sweden,100,"Docker, Tableau, GCP, PyTorch, Statistics",Master,8,Government,2024-11-23,2024-12-07,2244,7.9,Advanced Robotics +AI09593,NLP Engineer,311228,USD,311228,EX,FL,United States,L,United States,50,"Python, Computer Vision, Linux, Spark, TensorFlow",Bachelor,17,Gaming,2024-05-19,2024-06-25,1679,5.7,Neural Networks Co +AI09594,Deep Learning Engineer,80311,USD,80311,EN,FL,Denmark,S,Denmark,50,"TensorFlow, Kubernetes, Git",Master,1,Telecommunications,2024-07-30,2024-09-14,663,6.3,Advanced Robotics +AI09595,Computer Vision Engineer,140434,USD,140434,EX,CT,Finland,M,Finland,100,"Azure, Python, Docker",Associate,17,Real Estate,2024-04-03,2024-05-17,1737,8.8,Autonomous Tech +AI09596,AI Architect,242982,USD,242982,EX,FT,Norway,S,Norway,100,"Spark, NLP, Python, TensorFlow",Associate,10,Retail,2024-03-31,2024-06-11,2335,6.4,Digital Transformation LLC +AI09597,Deep Learning Engineer,71755,USD,71755,EN,PT,Finland,L,Finland,100,"Tableau, PyTorch, Deep Learning, Git, TensorFlow",PhD,1,Retail,2024-08-04,2024-10-03,2271,8.7,DeepTech Ventures +AI09598,AI Software Engineer,31328,USD,31328,MI,CT,India,L,India,100,"Git, Scala, Computer Vision",Master,2,Telecommunications,2024-09-25,2024-11-07,1426,6,TechCorp Inc +AI09599,Data Engineer,108210,USD,108210,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Deep Learning, Spark",Bachelor,9,Energy,2024-04-26,2024-06-04,925,8.1,AI Innovations +AI09600,NLP Engineer,127242,GBP,95432,SE,PT,United Kingdom,M,United Kingdom,100,"SQL, Kubernetes, Scala, AWS",Associate,9,Healthcare,2025-01-21,2025-04-03,1609,9.1,Algorithmic Solutions +AI09601,AI Software Engineer,122440,USD,122440,SE,CT,Finland,L,Finland,100,"Kubernetes, Spark, Hadoop, Git",Bachelor,7,Finance,2024-05-25,2024-06-20,1905,9.4,Smart Analytics +AI09602,Data Analyst,163000,USD,163000,EX,FT,Ireland,M,Belgium,100,"Scala, Linux, MLOps",Associate,17,Gaming,2025-01-09,2025-02-02,502,7.4,DataVision Ltd +AI09603,Machine Learning Researcher,238582,JPY,26244020,EX,FL,Japan,M,Japan,0,"Azure, Scala, Hadoop, Git",Master,12,Finance,2025-01-08,2025-02-10,773,7.3,AI Innovations +AI09604,ML Ops Engineer,56341,USD,56341,EN,PT,South Korea,M,South Korea,0,"SQL, Tableau, PyTorch",Bachelor,1,Media,2024-10-31,2024-12-01,815,7.9,TechCorp Inc +AI09605,ML Ops Engineer,82286,GBP,61715,EN,FL,United Kingdom,L,United Kingdom,50,"Java, Computer Vision, SQL, Deep Learning, PyTorch",Associate,1,Telecommunications,2025-02-24,2025-04-02,1160,7.2,TechCorp Inc +AI09606,ML Ops Engineer,206792,USD,206792,EX,FL,Norway,M,Norway,0,"Scala, GCP, PyTorch",Associate,10,Manufacturing,2024-08-27,2024-10-21,550,7.3,Smart Analytics +AI09607,Data Engineer,111725,EUR,94966,MI,PT,France,L,Russia,100,"Mathematics, MLOps, Data Visualization, Kubernetes",PhD,4,Real Estate,2024-07-24,2024-08-15,1981,5.9,Cloud AI Solutions +AI09608,Principal Data Scientist,256576,USD,256576,EX,FL,Finland,L,Ukraine,0,"Git, R, Computer Vision",Master,14,Finance,2024-04-28,2024-05-29,2329,8.6,Machine Intelligence Group +AI09609,NLP Engineer,157172,EUR,133596,EX,CT,France,S,France,100,"TensorFlow, Docker, Git",PhD,10,Manufacturing,2024-12-17,2025-02-24,703,7.4,AI Innovations +AI09610,Data Analyst,38565,USD,38565,MI,CT,India,L,India,50,"AWS, Computer Vision, SQL",Associate,3,Transportation,2024-09-16,2024-11-19,551,10,Cloud AI Solutions +AI09611,Principal Data Scientist,93643,CHF,84279,EN,FT,Switzerland,S,Egypt,0,"Python, Git, Computer Vision, Deep Learning, Linux",Associate,1,Healthcare,2024-11-15,2025-01-01,651,8.2,Cognitive Computing +AI09612,AI Product Manager,349386,CHF,314447,EX,PT,Switzerland,L,Switzerland,100,"Git, Tableau, TensorFlow",Associate,11,Retail,2024-10-02,2024-12-13,2214,9.4,Cloud AI Solutions +AI09613,ML Ops Engineer,135479,EUR,115157,EX,FT,Austria,S,Austria,50,"SQL, TensorFlow, Tableau, Hadoop, Spark",Bachelor,19,Telecommunications,2025-02-12,2025-04-19,2223,6.1,TechCorp Inc +AI09614,AI Architect,18474,USD,18474,EN,FL,India,S,Netherlands,50,"Git, Deep Learning, Scala, Java, Tableau",Master,1,Technology,2024-03-21,2024-05-07,1106,6.3,Quantum Computing Inc +AI09615,Deep Learning Engineer,84485,USD,84485,SE,FT,South Korea,M,South Korea,50,"TensorFlow, Python, Spark, SQL, AWS",Master,9,Telecommunications,2024-06-08,2024-06-25,1760,8.1,TechCorp Inc +AI09616,Data Engineer,108371,USD,108371,EN,PT,Denmark,L,Denmark,0,"AWS, Tableau, Hadoop",Bachelor,1,Energy,2024-07-29,2024-10-04,710,9.1,Algorithmic Solutions +AI09617,Data Analyst,115972,EUR,98576,SE,FL,Austria,L,Austria,0,"Deep Learning, GCP, Data Visualization, MLOps, NLP",Master,7,Government,2024-09-09,2024-10-17,1584,9.2,Quantum Computing Inc +AI09618,Computer Vision Engineer,107070,USD,107070,MI,CT,Norway,M,Norway,100,"Python, Docker, Azure, Spark",Bachelor,3,Retail,2024-02-09,2024-03-11,642,9.4,DataVision Ltd +AI09619,AI Consultant,63084,USD,63084,EN,FT,Sweden,L,Sweden,50,"Hadoop, Azure, Data Visualization, NLP",Master,0,Automotive,2024-06-20,2024-07-22,1427,5,Digital Transformation LLC +AI09620,Head of AI,152429,USD,152429,MI,CT,Denmark,L,Denmark,0,"TensorFlow, Mathematics, Azure, SQL",Associate,3,Retail,2024-09-18,2024-11-01,2456,9.6,Quantum Computing Inc +AI09621,Computer Vision Engineer,61740,USD,61740,SE,FT,India,L,Estonia,0,"Azure, Java, Deep Learning",PhD,6,Education,2024-05-26,2024-07-17,1435,7.1,Neural Networks Co +AI09622,Autonomous Systems Engineer,135651,USD,135651,SE,CT,Sweden,S,Sweden,50,"Mathematics, Python, TensorFlow, Tableau",Bachelor,5,Retail,2025-04-29,2025-06-07,626,7,Autonomous Tech +AI09623,Computer Vision Engineer,91734,USD,91734,MI,FT,Israel,L,Israel,50,"Scala, SQL, PyTorch, Spark",Associate,3,Transportation,2024-03-07,2024-04-03,2414,7.9,Digital Transformation LLC +AI09624,ML Ops Engineer,178754,USD,178754,SE,PT,United States,L,United States,0,"Python, Kubernetes, Spark, TensorFlow",Associate,7,Gaming,2024-03-28,2024-04-15,2228,9.3,DataVision Ltd +AI09625,Data Analyst,141292,USD,141292,SE,FL,Denmark,S,Denmark,50,"AWS, SQL, Data Visualization, Statistics, Git",Master,5,Energy,2024-12-03,2025-01-22,1969,7.3,Cloud AI Solutions +AI09626,Data Scientist,63976,CAD,79970,EN,FT,Canada,S,Egypt,0,"Spark, PyTorch, Statistics, Data Visualization, R",Associate,1,Technology,2024-08-20,2024-09-20,1847,6.2,Machine Intelligence Group +AI09627,Principal Data Scientist,172992,USD,172992,SE,FT,United States,L,United States,100,"TensorFlow, Python, Deep Learning",Bachelor,6,Healthcare,2024-01-05,2024-02-22,802,7,DeepTech Ventures +AI09628,Data Engineer,274237,USD,274237,EX,PT,Ireland,L,Ireland,50,"Docker, AWS, PyTorch, GCP",Master,12,Gaming,2024-08-27,2024-10-15,1234,8.1,AI Innovations +AI09629,Deep Learning Engineer,191469,USD,191469,EX,FT,Israel,M,Israel,50,"Python, Azure, Data Visualization, TensorFlow",PhD,13,Retail,2025-01-29,2025-02-12,543,6.7,Predictive Systems +AI09630,Research Scientist,203503,EUR,172978,EX,FT,Netherlands,L,Netherlands,50,"Python, AWS, Computer Vision, Linux, TensorFlow",Bachelor,19,Consulting,2025-02-27,2025-05-04,552,7.5,Digital Transformation LLC +AI09631,NLP Engineer,101614,EUR,86372,SE,PT,Austria,S,Austria,100,"Hadoop, Java, NLP, Deep Learning",PhD,6,Retail,2025-04-24,2025-06-07,1662,7.3,TechCorp Inc +AI09632,Machine Learning Engineer,72890,SGD,94757,EN,PT,Singapore,M,Chile,100,"TensorFlow, Kubernetes, Git",Master,0,Retail,2024-02-06,2024-04-12,2204,9.7,Smart Analytics +AI09633,Deep Learning Engineer,241369,USD,241369,EX,CT,Israel,L,Israel,50,"Computer Vision, Git, Mathematics",Master,11,Technology,2024-05-25,2024-08-03,1757,9.2,Algorithmic Solutions +AI09634,Data Analyst,80985,JPY,8908350,EN,PT,Japan,M,Japan,50,"Python, PyTorch, Spark, Mathematics, AWS",PhD,0,Technology,2024-03-16,2024-04-12,749,6.3,Machine Intelligence Group +AI09635,Computer Vision Engineer,48693,USD,48693,SE,FL,China,S,China,0,"Git, Python, NLP, Data Visualization",PhD,6,Healthcare,2024-02-09,2024-04-17,2083,8.9,Predictive Systems +AI09636,AI Software Engineer,120364,USD,120364,SE,FT,Ireland,M,Ireland,100,"Python, Tableau, MLOps, Azure, Computer Vision",PhD,6,Telecommunications,2024-08-20,2024-09-28,632,6.3,Cognitive Computing +AI09637,Data Analyst,119327,EUR,101428,SE,FL,France,M,Nigeria,100,"Mathematics, AWS, Tableau",Master,9,Education,2025-02-17,2025-04-26,1137,7.8,Autonomous Tech +AI09638,ML Ops Engineer,52959,USD,52959,EN,FL,Finland,S,Finland,0,"Java, MLOps, Python, Linux",Associate,1,Telecommunications,2024-11-07,2024-11-23,2153,9.6,DataVision Ltd +AI09639,Principal Data Scientist,44848,USD,44848,EN,PT,South Korea,S,South Korea,0,"Python, TensorFlow, Deep Learning, Linux, Computer Vision",Bachelor,1,Real Estate,2025-03-10,2025-05-20,615,8.8,Future Systems +AI09640,AI Software Engineer,279410,JPY,30735100,EX,CT,Japan,L,Japan,0,"R, Tableau, SQL, Computer Vision, Linux",Master,19,Healthcare,2024-09-30,2024-11-15,898,9.2,Neural Networks Co +AI09641,AI Product Manager,276943,USD,276943,EX,FL,Norway,S,Norway,0,"PyTorch, GCP, Statistics, Tableau",PhD,18,Automotive,2024-12-21,2025-02-03,1529,8.8,Future Systems +AI09642,Autonomous Systems Engineer,190274,USD,190274,SE,FT,Denmark,M,Denmark,0,"AWS, SQL, Kubernetes",Associate,9,Telecommunications,2024-01-12,2024-01-27,1114,9.4,AI Innovations +AI09643,Data Scientist,98262,JPY,10808820,EN,FL,Japan,L,France,0,"Python, SQL, Hadoop, Statistics",PhD,1,Manufacturing,2024-04-03,2024-04-28,1441,5.3,Future Systems +AI09644,AI Research Scientist,70103,USD,70103,EN,PT,South Korea,L,South Korea,100,"Mathematics, Computer Vision, Spark",Bachelor,1,Automotive,2024-02-20,2024-03-20,2351,5.5,Digital Transformation LLC +AI09645,Deep Learning Engineer,244222,USD,244222,EX,CT,Sweden,M,Israel,100,"PyTorch, TensorFlow, Deep Learning, Data Visualization, SQL",PhD,14,Energy,2024-03-18,2024-05-15,909,6.5,DataVision Ltd +AI09646,AI Software Engineer,98207,USD,98207,MI,FL,Sweden,S,Sweden,50,"R, Hadoop, Tableau, SQL, GCP",Associate,4,Real Estate,2024-09-26,2024-11-20,2490,8.4,Predictive Systems +AI09647,Machine Learning Engineer,74097,USD,74097,MI,CT,Finland,S,Brazil,50,"Hadoop, Python, MLOps",Master,4,Healthcare,2024-04-21,2024-05-11,2339,9.1,Quantum Computing Inc +AI09648,AI Specialist,57153,JPY,6286830,EN,CT,Japan,M,Japan,100,"TensorFlow, Scala, Docker, Hadoop",Master,1,Telecommunications,2024-09-12,2024-10-21,2307,8.8,DeepTech Ventures +AI09649,Research Scientist,99157,EUR,84283,MI,CT,France,M,Switzerland,0,"SQL, Hadoop, PyTorch",Master,3,Education,2024-04-23,2024-06-29,1974,9.2,Cloud AI Solutions +AI09650,AI Product Manager,104851,USD,104851,SE,CT,Israel,S,Israel,50,"Git, R, Python, Deep Learning, Java",Master,8,Automotive,2024-02-15,2024-04-26,2450,5.3,Quantum Computing Inc +AI09651,AI Specialist,70704,USD,70704,EN,CT,United States,M,United States,50,"Data Visualization, MLOps, Scala, Statistics, R",Master,1,Real Estate,2024-10-06,2024-12-11,513,5.8,Autonomous Tech +AI09652,AI Research Scientist,86595,AUD,116903,MI,FT,Australia,M,Australia,100,"Spark, TensorFlow, NLP",Master,4,Transportation,2025-01-04,2025-03-02,1800,5.7,Cognitive Computing +AI09653,Autonomous Systems Engineer,139992,USD,139992,SE,PT,Ireland,M,Egypt,0,"Mathematics, Python, Kubernetes",Master,5,Telecommunications,2024-04-30,2024-06-11,1651,8.9,Machine Intelligence Group +AI09654,AI Consultant,69365,EUR,58960,MI,CT,Germany,S,Germany,100,"Scala, Deep Learning, MLOps, Hadoop",PhD,2,Government,2024-01-25,2024-03-31,2284,7.6,Future Systems +AI09655,Data Engineer,98050,USD,98050,MI,FT,Finland,L,Finland,0,"Kubernetes, R, MLOps, Deep Learning, Scala",PhD,2,Telecommunications,2024-06-10,2024-07-19,1741,7,Smart Analytics +AI09656,AI Architect,20880,USD,20880,EN,CT,India,M,India,50,"Spark, Git, Kubernetes, Python",Bachelor,1,Finance,2024-05-11,2024-07-15,603,6.6,Cloud AI Solutions +AI09657,AI Research Scientist,80608,SGD,104790,EN,CT,Singapore,L,Singapore,0,"Scala, R, Hadoop, Deep Learning",PhD,0,Government,2025-04-04,2025-06-08,1483,5.4,Algorithmic Solutions +AI09658,Research Scientist,121634,CHF,109471,EN,PT,Switzerland,L,Czech Republic,50,"Python, Hadoop, AWS",Associate,1,Gaming,2024-03-08,2024-05-19,2259,8.4,Advanced Robotics +AI09659,Principal Data Scientist,200363,EUR,170309,EX,CT,Austria,L,Austria,100,"Tableau, Statistics, TensorFlow, Python",Bachelor,19,Technology,2025-01-07,2025-01-26,2480,7.7,Smart Analytics +AI09660,Machine Learning Researcher,65086,USD,65086,EN,FL,United States,S,United States,0,"Python, Linux, Tableau",PhD,1,Technology,2024-10-04,2024-11-23,2294,6.6,Predictive Systems +AI09661,Machine Learning Engineer,76722,USD,76722,EN,FT,Norway,S,Argentina,50,"Computer Vision, Spark, R, Hadoop, Docker",PhD,0,Government,2024-02-28,2024-05-05,1503,9.2,DataVision Ltd +AI09662,Data Engineer,136698,EUR,116193,SE,FL,Germany,M,Australia,0,"Statistics, Scala, SQL, Hadoop",Master,5,Healthcare,2024-07-28,2024-09-29,1467,8.3,TechCorp Inc +AI09663,Head of AI,89233,AUD,120465,MI,FT,Australia,S,Australia,100,"Azure, Statistics, Python, Data Visualization",Bachelor,3,Automotive,2025-01-11,2025-02-05,1410,9.4,Algorithmic Solutions +AI09664,AI Specialist,51178,AUD,69090,EN,FL,Australia,S,Egypt,50,"PyTorch, GCP, TensorFlow",Associate,1,Manufacturing,2024-01-25,2024-02-19,1458,9.7,Advanced Robotics +AI09665,AI Software Engineer,66263,EUR,56324,EN,FL,Germany,M,Argentina,0,"R, Tableau, Java",Associate,0,Transportation,2024-07-23,2024-09-13,558,9.3,Machine Intelligence Group +AI09666,Data Engineer,173476,USD,173476,EX,FL,Finland,S,Finland,100,"Linux, Kubernetes, Deep Learning, SQL, Git",Master,17,Government,2025-04-07,2025-04-30,2135,6.3,Machine Intelligence Group +AI09667,AI Software Engineer,161253,SGD,209629,EX,PT,Singapore,S,Singapore,100,"NLP, SQL, Statistics, Tableau",PhD,15,Real Estate,2024-03-21,2024-05-18,2353,9,AI Innovations +AI09668,AI Consultant,261254,EUR,222066,EX,PT,Germany,L,Germany,100,"Hadoop, Python, Kubernetes, Statistics, TensorFlow",Associate,12,Education,2025-04-26,2025-07-02,739,5.5,Advanced Robotics +AI09669,ML Ops Engineer,199726,USD,199726,EX,FT,Finland,M,Canada,0,"R, GCP, Deep Learning",Master,14,Technology,2024-09-05,2024-11-06,654,6.1,Smart Analytics +AI09670,Computer Vision Engineer,155809,AUD,210342,SE,PT,Australia,L,Australia,50,"PyTorch, Git, GCP",Master,8,Automotive,2024-04-25,2024-06-11,1358,5.6,Future Systems +AI09671,AI Specialist,27270,USD,27270,EN,FT,China,M,Vietnam,100,"Scala, Git, Azure",Associate,1,Transportation,2025-01-07,2025-02-06,2070,9.8,Smart Analytics +AI09672,NLP Engineer,123021,JPY,13532310,SE,CT,Japan,S,Japan,0,"Python, Scala, NLP, Docker, Kubernetes",Master,5,Finance,2024-10-29,2024-11-24,825,7.1,Neural Networks Co +AI09673,Robotics Engineer,218828,USD,218828,EX,FL,Ireland,S,Ireland,100,"PyTorch, TensorFlow, Azure, Kubernetes, Git",PhD,13,Telecommunications,2025-02-27,2025-05-08,1379,9.3,DeepTech Ventures +AI09674,Data Scientist,96009,USD,96009,EN,PT,Denmark,M,Denmark,100,"Spark, Statistics, SQL, Git",PhD,1,Real Estate,2024-04-02,2024-06-01,1154,7.4,Cloud AI Solutions +AI09675,AI Research Scientist,105293,USD,105293,EX,FT,China,L,China,100,"Tableau, Computer Vision, PyTorch, Linux, Mathematics",Associate,11,Automotive,2024-04-09,2024-06-02,1914,8,AI Innovations +AI09676,Machine Learning Researcher,140098,SGD,182127,SE,CT,Singapore,S,Singapore,50,"PyTorch, Java, GCP",Associate,6,Finance,2025-01-29,2025-03-07,951,6.5,Future Systems +AI09677,AI Product Manager,109453,CHF,98508,EN,FL,Switzerland,L,Switzerland,50,"Python, Scala, TensorFlow, Statistics, Computer Vision",Bachelor,1,Real Estate,2024-09-14,2024-10-27,2333,9.4,Cognitive Computing +AI09678,Data Engineer,135675,USD,135675,SE,FT,Ireland,S,Ghana,0,"Scala, GCP, Python",Associate,5,Real Estate,2025-03-27,2025-04-28,513,5.8,Cognitive Computing +AI09679,Data Analyst,55854,USD,55854,EN,FL,South Korea,S,South Korea,50,"Scala, TensorFlow, NLP",Bachelor,1,Government,2025-01-10,2025-03-03,2440,8.4,Quantum Computing Inc +AI09680,Data Analyst,95094,EUR,80830,SE,FT,Austria,S,Brazil,50,"Kubernetes, Python, Azure",Associate,5,Real Estate,2024-06-14,2024-08-02,2045,10,Smart Analytics +AI09681,Autonomous Systems Engineer,218586,USD,218586,EX,CT,Finland,L,Finland,0,"Linux, Hadoop, GCP, Tableau, Computer Vision",Bachelor,12,Media,2024-11-24,2025-01-25,1646,5.6,Quantum Computing Inc +AI09682,AI Specialist,49538,USD,49538,EN,CT,Finland,S,Finland,0,"Linux, Computer Vision, Docker, SQL",Master,1,Finance,2024-08-01,2024-09-10,1675,8.2,Cognitive Computing +AI09683,AI Software Engineer,133909,EUR,113823,EX,FT,France,S,Spain,50,"Data Visualization, GCP, MLOps, NLP",Associate,15,Manufacturing,2024-03-26,2024-04-24,1593,7.6,Cognitive Computing +AI09684,Principal Data Scientist,48444,EUR,41177,EN,CT,France,M,Hungary,100,"Azure, Scala, Python",Bachelor,1,Transportation,2024-02-02,2024-04-02,561,5.1,TechCorp Inc +AI09685,AI Research Scientist,256902,EUR,218367,EX,CT,Netherlands,M,Netherlands,100,"PyTorch, Tableau, Hadoop",Master,17,Gaming,2024-10-12,2024-11-27,1394,8.3,Autonomous Tech +AI09686,AI Architect,57022,USD,57022,SE,CT,China,M,China,0,"MLOps, Python, Docker",Master,9,Education,2024-05-16,2024-06-16,1314,9.5,Cognitive Computing +AI09687,AI Specialist,26272,USD,26272,EN,FL,India,M,Argentina,100,"Kubernetes, Tableau, Scala",Bachelor,1,Energy,2025-03-18,2025-04-08,1146,7.7,Advanced Robotics +AI09688,Deep Learning Engineer,191403,GBP,143552,EX,FL,United Kingdom,S,Philippines,50,"Tableau, Data Visualization, Computer Vision",PhD,13,Technology,2024-02-27,2024-05-05,2261,6.8,Cognitive Computing +AI09689,Machine Learning Researcher,102609,USD,102609,MI,CT,Ireland,M,Ireland,0,"Python, Linux, TensorFlow, Hadoop, Azure",PhD,3,Government,2024-04-25,2024-06-18,1130,9.7,Future Systems +AI09690,Machine Learning Engineer,86953,USD,86953,MI,PT,South Korea,M,Brazil,100,"R, SQL, TensorFlow, GCP, Computer Vision",Master,2,Energy,2024-01-07,2024-01-25,1942,9.5,DeepTech Ventures +AI09691,AI Architect,220260,EUR,187221,EX,FL,France,M,France,0,"Docker, Azure, Computer Vision, AWS, GCP",Bachelor,19,Automotive,2024-10-27,2025-01-01,2461,9.6,Autonomous Tech +AI09692,Robotics Engineer,129728,SGD,168646,SE,PT,Singapore,S,Singapore,100,"SQL, NLP, Hadoop",Bachelor,7,Gaming,2024-12-01,2025-01-12,2243,9.7,Cloud AI Solutions +AI09693,Principal Data Scientist,140854,USD,140854,SE,FL,Ireland,L,Ireland,0,"Python, Spark, Data Visualization",Bachelor,5,Transportation,2024-07-03,2024-09-14,1262,6.5,Cognitive Computing +AI09694,Data Analyst,247679,JPY,27244690,EX,FL,Japan,L,Japan,100,"PyTorch, NLP, Computer Vision, Java",Associate,19,Healthcare,2024-04-26,2024-06-02,1484,5.7,Predictive Systems +AI09695,Machine Learning Researcher,159898,JPY,17588780,SE,FL,Japan,M,Japan,50,"Spark, PyTorch, Tableau",PhD,9,Education,2024-11-30,2025-01-18,1577,7.7,Future Systems +AI09696,Data Engineer,119549,EUR,101617,SE,FT,Austria,M,Austria,0,"GCP, Docker, Tableau, Git",Bachelor,7,Telecommunications,2024-06-11,2024-08-11,1379,7.3,Cognitive Computing +AI09697,Data Scientist,141626,USD,141626,SE,PT,Finland,L,Finland,100,"MLOps, Docker, Kubernetes, R",PhD,9,Retail,2024-08-31,2024-10-31,688,8.3,Advanced Robotics +AI09698,Machine Learning Engineer,83010,EUR,70559,EN,CT,Germany,L,Malaysia,100,"Hadoop, SQL, Java",Bachelor,0,Retail,2024-12-21,2025-02-03,2456,9.9,Smart Analytics +AI09699,Machine Learning Engineer,102708,JPY,11297880,MI,CT,Japan,L,Japan,100,"TensorFlow, Linux, Tableau, SQL",Associate,2,Gaming,2024-03-24,2024-04-11,1512,7.6,Digital Transformation LLC +AI09700,NLP Engineer,108628,JPY,11949080,MI,FT,Japan,L,Japan,0,"NLP, Hadoop, GCP",Bachelor,3,Energy,2024-01-18,2024-02-26,667,9.1,Algorithmic Solutions +AI09701,Data Analyst,74902,JPY,8239220,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, NLP, GCP, Scala",Associate,0,Manufacturing,2024-07-01,2024-09-12,2409,8,Quantum Computing Inc +AI09702,Data Engineer,87428,CHF,78685,EN,FT,Switzerland,S,Switzerland,0,"Python, AWS, Deep Learning",Bachelor,0,Transportation,2024-03-27,2024-05-09,1937,6,Machine Intelligence Group +AI09703,Robotics Engineer,76047,AUD,102663,MI,PT,Australia,M,Australia,0,"R, AWS, MLOps, Scala, Deep Learning",PhD,3,Energy,2024-08-21,2024-09-08,1513,6.2,TechCorp Inc +AI09704,Deep Learning Engineer,260148,USD,260148,EX,FT,United States,S,Turkey,50,"Git, Scala, Data Visualization",Bachelor,18,Telecommunications,2025-01-10,2025-02-12,2240,8,Digital Transformation LLC +AI09705,Robotics Engineer,74496,USD,74496,MI,CT,Sweden,S,Sweden,0,"Java, Spark, TensorFlow",PhD,2,Energy,2025-04-23,2025-06-29,1834,6.9,Predictive Systems +AI09706,NLP Engineer,79118,EUR,67250,MI,PT,Germany,S,United States,0,"Azure, Tableau, Git",PhD,3,Manufacturing,2024-04-06,2024-05-11,1883,8.8,Advanced Robotics +AI09707,ML Ops Engineer,115756,EUR,98393,SE,FL,Germany,S,Germany,50,"Git, SQL, Kubernetes, Deep Learning, Hadoop",Bachelor,5,Transportation,2025-04-19,2025-05-27,1471,7.4,AI Innovations +AI09708,AI Software Engineer,86602,EUR,73612,SE,PT,France,S,Brazil,0,"SQL, Data Visualization, Scala, Azure",Associate,6,Education,2025-02-22,2025-03-18,1378,9.6,Machine Intelligence Group +AI09709,Principal Data Scientist,125719,AUD,169721,SE,CT,Australia,M,Australia,100,"Scala, Kubernetes, Docker",Master,6,Consulting,2024-03-02,2024-04-01,1265,7.2,Cloud AI Solutions +AI09710,NLP Engineer,18481,USD,18481,EN,CT,India,S,India,50,"Python, TensorFlow, Scala, PyTorch",Associate,0,Automotive,2024-05-11,2024-05-31,2012,6.4,Predictive Systems +AI09711,ML Ops Engineer,88351,USD,88351,SE,CT,Finland,S,Ghana,100,"SQL, Statistics, GCP, Hadoop, Deep Learning",Associate,6,Manufacturing,2024-07-10,2024-07-30,2256,5.5,Quantum Computing Inc +AI09712,AI Consultant,40280,USD,40280,MI,PT,India,L,India,50,"Statistics, PyTorch, Hadoop, Scala, AWS",Master,3,Automotive,2024-08-23,2024-09-27,1701,5.9,AI Innovations +AI09713,Deep Learning Engineer,87759,USD,87759,MI,FL,Ireland,L,Russia,100,"Hadoop, R, Tableau, GCP, Kubernetes",Bachelor,3,Finance,2024-05-29,2024-07-25,1034,6.2,Algorithmic Solutions +AI09714,AI Consultant,140279,USD,140279,SE,FT,Israel,L,Israel,100,"Data Visualization, SQL, Docker, TensorFlow",Bachelor,7,Media,2024-03-27,2024-05-16,725,9.6,Cognitive Computing +AI09715,Data Engineer,113020,EUR,96067,SE,CT,Austria,L,Austria,0,"Data Visualization, Kubernetes, Deep Learning",Associate,5,Consulting,2024-12-27,2025-01-23,753,9.3,Machine Intelligence Group +AI09716,Machine Learning Engineer,213625,USD,213625,EX,FT,Norway,M,Norway,100,"AWS, SQL, Git, Kubernetes",Master,15,Finance,2024-01-08,2024-03-09,562,7.3,Machine Intelligence Group +AI09717,Autonomous Systems Engineer,127115,EUR,108048,SE,FT,Austria,L,Brazil,100,"Spark, MLOps, Python, Tableau",PhD,5,Finance,2024-12-02,2025-02-07,1020,9,Advanced Robotics +AI09718,AI Software Engineer,53464,SGD,69503,EN,PT,Singapore,S,Colombia,0,"Hadoop, Statistics, Mathematics, Docker, AWS",Associate,1,Automotive,2025-04-18,2025-05-21,1121,5.5,Machine Intelligence Group +AI09719,Research Scientist,105947,USD,105947,EN,FT,Denmark,L,Denmark,50,"Kubernetes, Scala, Git",Bachelor,1,Consulting,2024-07-06,2024-08-05,1834,7.7,Cloud AI Solutions +AI09720,AI Research Scientist,389066,CHF,350159,EX,FT,Switzerland,L,Switzerland,0,"Hadoop, SQL, Docker",PhD,10,Finance,2024-08-13,2024-10-19,1479,6.6,Autonomous Tech +AI09721,AI Architect,162534,EUR,138154,EX,FT,Netherlands,S,Chile,100,"Scala, Tableau, Data Visualization, Deep Learning",Bachelor,13,Manufacturing,2024-01-07,2024-02-12,2180,6.9,Neural Networks Co +AI09722,Deep Learning Engineer,67954,EUR,57761,EN,CT,Austria,M,Austria,100,"Mathematics, TensorFlow, MLOps, NLP",Master,1,Transportation,2024-02-23,2024-04-27,2132,9.3,Predictive Systems +AI09723,Machine Learning Researcher,236172,AUD,318832,EX,PT,Australia,M,Australia,0,"SQL, Python, Deep Learning, NLP, Spark",Associate,16,Technology,2025-03-10,2025-04-22,1099,6.6,Cloud AI Solutions +AI09724,AI Architect,235127,EUR,199858,EX,CT,France,L,France,100,"Scala, R, Data Visualization, Azure",Associate,11,Finance,2024-02-14,2024-04-16,1353,7.4,Digital Transformation LLC +AI09725,Robotics Engineer,122654,EUR,104256,MI,FT,Netherlands,L,Netherlands,0,"Azure, Git, GCP, TensorFlow",Master,3,Transportation,2024-03-01,2024-04-29,1111,7.1,Advanced Robotics +AI09726,AI Research Scientist,205223,AUD,277051,EX,FT,Australia,S,Egypt,50,"Deep Learning, Kubernetes, Computer Vision, Hadoop, Data Visualization",Master,15,Transportation,2024-08-03,2024-10-12,2209,5.5,Advanced Robotics +AI09727,Robotics Engineer,148358,SGD,192865,SE,PT,Singapore,M,Egypt,100,"Scala, Statistics, AWS, TensorFlow",Bachelor,6,Healthcare,2024-05-10,2024-06-18,1848,6.6,Quantum Computing Inc +AI09728,Data Scientist,220353,USD,220353,EX,FL,Norway,L,Norway,100,"Python, Azure, Docker",Master,10,Finance,2025-02-25,2025-03-20,648,6.8,Algorithmic Solutions +AI09729,Deep Learning Engineer,189506,EUR,161080,EX,CT,Netherlands,L,Netherlands,50,"Python, MLOps, TensorFlow, AWS, Deep Learning",Associate,17,Healthcare,2024-10-04,2024-10-30,1498,7,Smart Analytics +AI09730,AI Software Engineer,69812,JPY,7679320,EN,FT,Japan,M,Brazil,50,"R, Java, Docker",Master,0,Gaming,2024-06-25,2024-09-04,1792,8.4,Machine Intelligence Group +AI09731,Data Scientist,61754,USD,61754,SE,PT,India,L,India,100,"R, PyTorch, Tableau, Computer Vision",Bachelor,5,Energy,2024-10-30,2025-01-09,993,9.9,Digital Transformation LLC +AI09732,Data Engineer,87674,USD,87674,MI,PT,Finland,S,Finland,0,"Tableau, TensorFlow, Linux, AWS, Computer Vision",Bachelor,3,Automotive,2024-01-27,2024-03-08,1229,8.2,Cloud AI Solutions +AI09733,AI Research Scientist,100642,USD,100642,MI,CT,Norway,S,Vietnam,100,"Scala, SQL, MLOps",PhD,4,Media,2024-08-01,2024-09-25,1487,7.8,Smart Analytics +AI09734,ML Ops Engineer,179394,AUD,242182,EX,FT,Australia,S,Australia,50,"Python, TensorFlow, Statistics",Associate,19,Real Estate,2024-03-19,2024-04-21,1973,7.1,Cognitive Computing +AI09735,AI Consultant,177616,USD,177616,SE,FL,United States,L,United States,50,"Scala, R, Data Visualization",Master,6,Transportation,2024-06-14,2024-08-07,1656,7.7,Cognitive Computing +AI09736,Deep Learning Engineer,31495,USD,31495,EN,CT,China,L,China,100,"NLP, Python, Statistics, SQL",PhD,1,Government,2024-06-21,2024-08-15,1654,6,Predictive Systems +AI09737,AI Consultant,44106,USD,44106,SE,PT,China,S,Nigeria,100,"Computer Vision, PyTorch, Git",Bachelor,9,Government,2024-10-06,2024-10-31,2386,7.4,Neural Networks Co +AI09738,Computer Vision Engineer,60523,EUR,51445,EN,CT,Netherlands,S,Netherlands,100,"SQL, PyTorch, Spark, TensorFlow, Tableau",PhD,0,Manufacturing,2025-02-15,2025-03-29,2025,7.3,Neural Networks Co +AI09739,Deep Learning Engineer,149499,SGD,194349,SE,FT,Singapore,M,Estonia,100,"MLOps, NLP, Tableau, TensorFlow, Java",Bachelor,5,Gaming,2024-09-21,2024-11-16,730,9,Machine Intelligence Group +AI09740,AI Architect,99163,USD,99163,SE,CT,South Korea,L,South Korea,50,"TensorFlow, SQL, Statistics",Bachelor,8,Energy,2024-12-22,2025-02-22,1266,9.5,Predictive Systems +AI09741,Computer Vision Engineer,295991,USD,295991,EX,CT,United States,L,Luxembourg,100,"Spark, TensorFlow, R",PhD,19,Education,2024-05-01,2024-07-04,1775,6.2,Cognitive Computing +AI09742,AI Architect,136129,USD,136129,MI,FL,Norway,L,Norway,100,"PyTorch, Hadoop, Statistics, Git, Deep Learning",PhD,2,Finance,2024-11-04,2024-11-19,1746,5.3,Smart Analytics +AI09743,Deep Learning Engineer,113701,EUR,96646,SE,FT,Austria,S,Austria,100,"R, Linux, Java",Master,5,Automotive,2024-04-06,2024-05-14,1949,7.4,Future Systems +AI09744,AI Architect,81106,CHF,72995,EN,PT,Switzerland,S,Switzerland,0,"Python, Spark, Statistics, Linux",PhD,1,Gaming,2025-02-11,2025-02-25,629,5.7,Advanced Robotics +AI09745,Data Analyst,69980,USD,69980,EX,FL,India,M,India,0,"PyTorch, TensorFlow, Docker, SQL, Statistics",Associate,14,Retail,2025-03-18,2025-04-23,1445,7.7,Digital Transformation LLC +AI09746,ML Ops Engineer,326836,USD,326836,EX,FT,Norway,M,Norway,0,"TensorFlow, SQL, Data Visualization",Bachelor,12,Finance,2024-09-14,2024-11-19,840,6.8,Algorithmic Solutions +AI09747,Data Engineer,99357,EUR,84453,SE,FL,Austria,M,Austria,50,"Python, Java, Azure, AWS",Bachelor,7,Automotive,2024-10-08,2024-11-16,560,6.6,DataVision Ltd +AI09748,Machine Learning Researcher,147291,USD,147291,EX,PT,Israel,L,Israel,50,"PyTorch, Spark, R, Git, Tableau",PhD,16,Manufacturing,2024-11-06,2024-11-27,1962,9.5,Digital Transformation LLC +AI09749,AI Research Scientist,241227,USD,241227,EX,FT,Norway,S,Norway,100,"Python, Spark, Tableau, TensorFlow, Deep Learning",Master,12,Media,2025-04-01,2025-05-12,667,7.5,TechCorp Inc +AI09750,Research Scientist,75529,USD,75529,EN,FL,Finland,L,Argentina,50,"Java, PyTorch, NLP, SQL, Scala",Bachelor,0,Manufacturing,2024-07-30,2024-08-24,1470,9.2,Future Systems +AI09751,Machine Learning Engineer,68543,USD,68543,EN,CT,Norway,S,Norway,100,"MLOps, Deep Learning, Data Visualization",Master,1,Telecommunications,2024-03-08,2024-04-16,2407,8.8,Cognitive Computing +AI09752,Principal Data Scientist,69686,USD,69686,EN,CT,United States,S,Czech Republic,100,"PyTorch, SQL, Data Visualization, Deep Learning",Bachelor,0,Telecommunications,2024-03-26,2024-05-18,1978,6.3,Advanced Robotics +AI09753,AI Architect,240290,EUR,204247,EX,CT,Netherlands,M,Netherlands,0,"Scala, Python, Azure",PhD,18,Retail,2024-04-14,2024-06-26,1249,8.2,Neural Networks Co +AI09754,Robotics Engineer,152827,CHF,137544,MI,CT,Switzerland,M,Poland,100,"Kubernetes, Docker, Mathematics",PhD,4,Automotive,2025-04-09,2025-05-17,2154,9.7,DeepTech Ventures +AI09755,AI Software Engineer,124396,EUR,105737,EX,CT,Germany,S,Germany,0,"PyTorch, Deep Learning, Hadoop, Computer Vision, Linux",PhD,15,Retail,2024-08-18,2024-10-09,708,6.3,Smart Analytics +AI09756,Machine Learning Engineer,246978,EUR,209931,EX,FL,Netherlands,M,Netherlands,100,"Azure, Java, PyTorch, Deep Learning, AWS",Bachelor,13,Transportation,2024-04-17,2024-05-26,605,8.1,TechCorp Inc +AI09757,Research Scientist,102797,JPY,11307670,MI,CT,Japan,M,Japan,0,"PyTorch, TensorFlow, Kubernetes",Associate,3,Manufacturing,2024-02-10,2024-04-23,522,7,Machine Intelligence Group +AI09758,Head of AI,67987,SGD,88383,EN,FL,Singapore,S,Singapore,0,"Python, Hadoop, SQL, Git, AWS",Bachelor,1,Consulting,2024-02-27,2024-05-01,761,7.4,Advanced Robotics +AI09759,Data Analyst,283056,USD,283056,EX,FL,Norway,L,Colombia,100,"Hadoop, Tableau, Python, Kubernetes, Mathematics",Master,15,Gaming,2024-10-17,2024-12-10,1021,7.7,Cloud AI Solutions +AI09760,Principal Data Scientist,362848,USD,362848,EX,CT,Norway,L,Norway,100,"GCP, Statistics, MLOps",Associate,13,Media,2025-01-08,2025-02-20,697,5.8,Predictive Systems +AI09761,Data Engineer,63275,SGD,82258,EN,PT,Singapore,M,Singapore,0,"Linux, Kubernetes, Hadoop, Docker, R",Associate,1,Media,2025-01-26,2025-02-13,1719,9.9,Cognitive Computing +AI09762,Data Scientist,61622,GBP,46217,EN,CT,United Kingdom,S,United Kingdom,50,"R, NLP, SQL",PhD,1,Telecommunications,2024-01-28,2024-03-25,1936,9.8,Predictive Systems +AI09763,Principal Data Scientist,82457,CHF,74211,EN,FL,Switzerland,M,Norway,0,"Python, Git, Computer Vision, TensorFlow",PhD,1,Automotive,2024-01-12,2024-02-13,1591,9,Neural Networks Co +AI09764,Head of AI,71625,EUR,60881,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch, Data Visualization, Azure",Associate,4,Gaming,2024-10-08,2024-12-10,1383,8.7,Advanced Robotics +AI09765,NLP Engineer,119422,EUR,101509,MI,FL,Germany,L,Ukraine,50,"PyTorch, TensorFlow, AWS",PhD,3,Media,2024-09-06,2024-10-02,2426,9.7,Quantum Computing Inc +AI09766,Deep Learning Engineer,54944,EUR,46702,EN,CT,Austria,S,Austria,50,"Python, SQL, Mathematics, Java",Associate,1,Finance,2024-10-17,2024-11-24,722,5,Quantum Computing Inc +AI09767,Robotics Engineer,52068,EUR,44258,EN,CT,France,M,France,100,"Python, SQL, Mathematics",Bachelor,1,Technology,2024-11-23,2025-01-20,908,6.3,Neural Networks Co +AI09768,Data Analyst,34503,USD,34503,EN,PT,China,L,Norway,50,"Statistics, Python, TensorFlow, PyTorch",Associate,0,Education,2025-04-01,2025-05-19,2330,7.6,TechCorp Inc +AI09769,Deep Learning Engineer,95396,USD,95396,SE,CT,Sweden,S,Sweden,100,"TensorFlow, SQL, Docker, Statistics",Bachelor,5,Telecommunications,2024-05-06,2024-06-09,1419,5.9,DeepTech Ventures +AI09770,AI Specialist,143291,EUR,121797,EX,CT,France,S,France,50,"PyTorch, R, TensorFlow, Computer Vision, GCP",PhD,14,Education,2025-02-27,2025-04-06,751,9.6,Cognitive Computing +AI09771,NLP Engineer,66180,USD,66180,EN,PT,Sweden,M,South Korea,50,"PyTorch, Git, Tableau",Bachelor,1,Government,2024-03-25,2024-05-15,1216,6.1,Digital Transformation LLC +AI09772,AI Product Manager,142280,USD,142280,SE,CT,Finland,M,Finland,0,"Python, Scala, Computer Vision, Tableau",Bachelor,9,Education,2024-11-23,2024-12-14,947,9.6,Cognitive Computing +AI09773,Principal Data Scientist,72824,USD,72824,MI,FT,South Korea,S,South Korea,50,"Computer Vision, GCP, Linux",Bachelor,3,Automotive,2024-09-14,2024-10-31,1124,6.5,Quantum Computing Inc +AI09774,AI Software Engineer,91337,JPY,10047070,MI,FT,Japan,M,Japan,0,"PyTorch, Docker, SQL, Deep Learning",PhD,3,Government,2024-07-15,2024-09-01,653,6.4,Quantum Computing Inc +AI09775,Machine Learning Researcher,59812,USD,59812,EN,FT,Israel,S,Hungary,0,"Python, Kubernetes, TensorFlow",PhD,1,Transportation,2024-10-02,2024-12-10,2279,9.5,Machine Intelligence Group +AI09776,Machine Learning Engineer,94416,CAD,118020,MI,PT,Canada,M,Canada,100,"Linux, Spark, Scala, Python",Associate,4,Retail,2024-01-31,2024-04-05,1742,5.1,TechCorp Inc +AI09777,Principal Data Scientist,162702,CHF,146432,MI,FL,Switzerland,L,China,100,"Computer Vision, Java, MLOps, Spark",Bachelor,4,Transportation,2024-08-24,2024-09-15,1799,5.4,Future Systems +AI09778,ML Ops Engineer,208539,CAD,260674,EX,FL,Canada,L,Canada,0,"SQL, Python, Git",PhD,16,Consulting,2024-07-13,2024-08-02,1191,5.7,Neural Networks Co +AI09779,Data Engineer,293805,USD,293805,EX,PT,Norway,L,Norway,100,"Java, Linux, Kubernetes, Deep Learning, Git",Master,13,Retail,2025-03-18,2025-05-24,1990,7.4,Digital Transformation LLC +AI09780,Robotics Engineer,109663,USD,109663,MI,FT,Norway,L,Norway,100,"NLP, Hadoop, Spark, PyTorch",Bachelor,4,Consulting,2024-04-05,2024-06-15,1177,6.5,Smart Analytics +AI09781,AI Product Manager,62003,USD,62003,EX,PT,India,M,Belgium,50,"Kubernetes, Data Visualization, Linux, Python, Scala",PhD,10,Government,2025-04-28,2025-07-07,1364,8.1,TechCorp Inc +AI09782,Deep Learning Engineer,110601,USD,110601,MI,PT,Denmark,S,Denmark,100,"MLOps, Docker, Kubernetes, Tableau, PyTorch",Master,4,Transportation,2024-07-21,2024-08-27,1275,6.7,AI Innovations +AI09783,Machine Learning Engineer,97802,USD,97802,SE,FL,Finland,S,Finland,100,"PyTorch, SQL, GCP, Docker",Master,7,Technology,2025-01-05,2025-03-01,1277,8.1,Future Systems +AI09784,AI Research Scientist,31409,USD,31409,EN,FL,China,S,China,100,"Scala, MLOps, SQL, Hadoop",Bachelor,0,Manufacturing,2024-02-28,2024-04-05,987,7,DataVision Ltd +AI09785,Data Analyst,217049,USD,217049,EX,CT,Ireland,S,Ireland,100,"Scala, Spark, Computer Vision, AWS",Bachelor,15,Energy,2025-01-02,2025-02-14,527,5.7,Future Systems +AI09786,AI Consultant,113873,USD,113873,SE,FL,Finland,L,Finland,0,"Statistics, MLOps, Python, Hadoop",Bachelor,5,Gaming,2024-02-15,2024-04-22,929,6.8,AI Innovations +AI09787,Data Scientist,154501,CHF,139051,MI,CT,Switzerland,M,France,50,"Python, TensorFlow, Linux, PyTorch, Scala",Associate,4,Technology,2024-07-05,2024-08-07,2288,8.3,Cloud AI Solutions +AI09788,Data Analyst,65431,CAD,81789,EN,PT,Canada,S,Belgium,100,"AWS, NLP, Git",Bachelor,1,Finance,2024-11-24,2024-12-11,2365,7.8,Cognitive Computing +AI09789,AI Consultant,182995,CAD,228744,EX,FL,Canada,S,Canada,0,"PyTorch, Hadoop, Mathematics, NLP",Bachelor,14,Transportation,2024-07-11,2024-09-11,1806,8.5,DataVision Ltd +AI09790,Data Engineer,69850,JPY,7683500,EN,FL,Japan,S,Japan,100,"SQL, NLP, Docker",PhD,1,Transportation,2025-01-26,2025-03-23,736,6.1,Neural Networks Co +AI09791,Data Engineer,204758,EUR,174044,EX,FL,Germany,S,Romania,100,"Scala, Kubernetes, Deep Learning",Associate,14,Gaming,2024-01-24,2024-02-07,2040,7.5,DataVision Ltd +AI09792,Robotics Engineer,118924,USD,118924,SE,CT,South Korea,M,South Korea,50,"Kubernetes, Git, TensorFlow",Master,9,Manufacturing,2025-02-14,2025-04-06,2190,8,Algorithmic Solutions +AI09793,AI Specialist,140720,GBP,105540,SE,CT,United Kingdom,M,Austria,50,"Spark, Hadoop, Linux, Scala",Bachelor,7,Technology,2024-10-21,2024-11-09,899,8.4,Cognitive Computing +AI09794,AI Consultant,83079,EUR,70617,MI,FT,Germany,S,Germany,100,"R, SQL, Statistics",Associate,4,Manufacturing,2025-04-08,2025-05-28,2250,9.7,DataVision Ltd +AI09795,Head of AI,160182,SGD,208237,SE,CT,Singapore,L,Canada,50,"Git, NLP, AWS",Bachelor,7,Consulting,2024-10-21,2024-11-07,2076,8.2,Predictive Systems +AI09796,AI Consultant,64536,USD,64536,EN,FL,Ireland,M,Ireland,0,"SQL, Hadoop, Mathematics",Bachelor,0,Healthcare,2024-01-22,2024-03-28,2158,9.8,Neural Networks Co +AI09797,Machine Learning Engineer,250363,AUD,337990,EX,FT,Australia,L,Australia,50,"MLOps, SQL, TensorFlow, R",Master,18,Consulting,2024-02-12,2024-04-03,1816,9.1,Quantum Computing Inc +AI09798,Data Engineer,45433,USD,45433,SE,PT,India,L,India,100,"Computer Vision, Spark, Statistics",Bachelor,7,Education,2024-08-28,2024-10-05,1982,7.3,Advanced Robotics +AI09799,Data Analyst,63135,CAD,78919,EN,FT,Canada,L,Sweden,0,"SQL, MLOps, Scala, TensorFlow",Associate,1,Manufacturing,2025-04-28,2025-07-10,2401,5.4,Neural Networks Co +AI09800,Data Scientist,72576,USD,72576,EX,FL,China,S,Italy,50,"Git, AWS, Scala, Data Visualization",Associate,10,Real Estate,2024-03-25,2024-05-12,678,8.2,DeepTech Ventures +AI09801,Research Scientist,137937,USD,137937,EX,CT,South Korea,M,South Korea,100,"Python, Statistics, Spark",Master,18,Energy,2024-07-11,2024-08-15,1878,8.4,Algorithmic Solutions +AI09802,Autonomous Systems Engineer,137663,EUR,117014,SE,CT,France,L,France,50,"Java, Spark, Mathematics, PyTorch",Bachelor,6,Consulting,2025-02-11,2025-03-12,1432,7,Machine Intelligence Group +AI09803,AI Consultant,201971,USD,201971,EX,FL,Sweden,L,Sweden,50,"Python, Data Visualization, Linux, GCP",Associate,19,Energy,2024-03-02,2024-04-18,1265,7.5,Digital Transformation LLC +AI09804,Data Scientist,49095,USD,49095,MI,CT,China,M,Egypt,0,"Tableau, Java, Azure, NLP, Python",PhD,4,Media,2024-10-20,2024-11-24,1490,6.8,Cognitive Computing +AI09805,Research Scientist,210286,USD,210286,EX,FT,United States,L,Czech Republic,0,"Spark, Linux, Scala",PhD,17,Transportation,2024-11-16,2024-12-02,2014,8.8,TechCorp Inc +AI09806,AI Specialist,196218,USD,196218,SE,PT,Denmark,M,Ghana,50,"Hadoop, Docker, Deep Learning, GCP, SQL",Associate,8,Energy,2024-08-22,2024-10-07,2279,8.6,Future Systems +AI09807,Machine Learning Engineer,18616,USD,18616,EN,FT,India,S,India,50,"Git, Tableau, Kubernetes, Data Visualization",Associate,0,Media,2024-07-20,2024-09-07,894,5.4,Machine Intelligence Group +AI09808,Autonomous Systems Engineer,118826,USD,118826,MI,FT,Finland,L,Finland,0,"Kubernetes, Docker, R",Associate,4,Education,2024-05-17,2024-06-12,1146,8.2,DataVision Ltd +AI09809,Computer Vision Engineer,277649,USD,277649,EX,FT,United States,L,Japan,100,"Statistics, SQL, Deep Learning",Associate,15,Media,2024-10-15,2024-12-11,2120,9.6,Advanced Robotics +AI09810,AI Research Scientist,67075,EUR,57014,MI,PT,France,S,France,50,"Linux, Scala, Computer Vision, PyTorch",Associate,2,Manufacturing,2024-08-24,2024-09-26,669,6.5,Autonomous Tech +AI09811,Machine Learning Engineer,62913,JPY,6920430,EN,FT,Japan,L,Japan,100,"SQL, Java, Mathematics",Bachelor,0,Media,2025-03-09,2025-03-25,1843,5.3,TechCorp Inc +AI09812,AI Software Engineer,95618,CHF,86056,MI,CT,Switzerland,S,India,50,"Computer Vision, Statistics, Kubernetes, Java",PhD,4,Education,2024-03-27,2024-06-01,1596,5.5,Future Systems +AI09813,Head of AI,219644,USD,219644,SE,PT,Norway,L,United States,100,"Git, Deep Learning, Python, Computer Vision",Bachelor,9,Education,2025-02-01,2025-03-18,1841,8.8,Quantum Computing Inc +AI09814,AI Research Scientist,183702,CHF,165332,SE,FT,Switzerland,L,Switzerland,50,"Computer Vision, Tableau, Git, MLOps, NLP",PhD,8,Telecommunications,2024-08-06,2024-08-28,1473,9.6,DeepTech Ventures +AI09815,Computer Vision Engineer,68877,AUD,92984,EN,PT,Australia,S,Australia,100,"SQL, PyTorch, Git, AWS, TensorFlow",Bachelor,1,Telecommunications,2025-03-03,2025-04-29,2430,5.8,Machine Intelligence Group +AI09816,AI Specialist,130605,EUR,111014,EX,CT,Austria,M,Austria,100,"Spark, R, Kubernetes",PhD,13,Consulting,2024-04-21,2024-05-18,1198,5.8,Advanced Robotics +AI09817,Machine Learning Researcher,204630,AUD,276251,EX,FT,Australia,S,Australia,50,"Azure, PyTorch, Linux",Associate,17,Consulting,2024-03-23,2024-05-13,1441,6.7,TechCorp Inc +AI09818,Machine Learning Researcher,52908,USD,52908,SE,PT,China,S,Ghana,0,"Python, Azure, Deep Learning, NLP",PhD,9,Manufacturing,2024-11-07,2024-12-03,1769,5.9,Predictive Systems +AI09819,AI Consultant,94508,CHF,85057,EN,FT,Switzerland,L,Russia,50,"Computer Vision, MLOps, Tableau",PhD,0,Retail,2024-04-23,2024-06-11,970,8.7,Machine Intelligence Group +AI09820,AI Consultant,129697,GBP,97273,SE,PT,United Kingdom,L,Denmark,50,"Hadoop, PyTorch, AWS, Linux, NLP",Associate,6,Consulting,2025-03-07,2025-03-30,895,8.6,Future Systems +AI09821,Computer Vision Engineer,114261,EUR,97122,SE,FT,France,S,France,0,"Computer Vision, Python, Mathematics",Bachelor,8,Retail,2024-10-15,2024-12-24,1576,7.1,Cloud AI Solutions +AI09822,Principal Data Scientist,66838,AUD,90231,EN,CT,Australia,L,Ukraine,50,"Azure, Linux, MLOps, Scala",Master,1,Transportation,2024-04-06,2024-06-15,2404,8,DeepTech Ventures +AI09823,Data Engineer,74558,CHF,67102,EN,CT,Switzerland,S,Switzerland,0,"Mathematics, GCP, Docker, AWS",Bachelor,0,Healthcare,2024-06-05,2024-08-15,1416,8.9,Autonomous Tech +AI09824,Autonomous Systems Engineer,77135,JPY,8484850,EN,FT,Japan,L,Japan,100,"Kubernetes, Statistics, PyTorch",Associate,1,Healthcare,2024-11-19,2025-01-27,805,6.4,Cognitive Computing +AI09825,AI Architect,186851,USD,186851,EX,FL,Norway,M,Norway,50,"Mathematics, R, Spark, Computer Vision",Bachelor,12,Media,2025-03-31,2025-05-03,804,9.9,Machine Intelligence Group +AI09826,AI Product Manager,77859,USD,77859,EN,FT,Sweden,M,Sweden,100,"Spark, Java, Statistics, Mathematics",Master,1,Government,2024-02-14,2024-03-12,1780,9.3,Cognitive Computing +AI09827,Deep Learning Engineer,90139,USD,90139,EN,FT,Denmark,M,Turkey,0,"TensorFlow, SQL, Python, NLP, AWS",Associate,0,Healthcare,2024-09-11,2024-10-03,852,8.2,Cognitive Computing +AI09828,AI Specialist,149714,USD,149714,MI,CT,Denmark,L,Denmark,0,"Python, SQL, NLP, Hadoop",Bachelor,2,Government,2025-04-05,2025-06-09,1519,8.6,Cloud AI Solutions +AI09829,Autonomous Systems Engineer,176198,EUR,149768,EX,CT,Austria,M,Latvia,50,"Deep Learning, Spark, Java, Computer Vision",Master,19,Government,2024-03-12,2024-05-07,1526,8.8,DeepTech Ventures +AI09830,AI Consultant,228336,CHF,205502,EX,FT,Switzerland,M,South Africa,0,"Java, Spark, Azure, Linux",Bachelor,19,Real Estate,2024-08-31,2024-09-16,805,5.5,Digital Transformation LLC +AI09831,Computer Vision Engineer,17942,USD,17942,EN,FL,India,S,South Korea,50,"Data Visualization, PyTorch, TensorFlow, SQL",PhD,1,Technology,2024-08-22,2024-10-28,1023,8.8,DataVision Ltd +AI09832,Autonomous Systems Engineer,140214,USD,140214,SE,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch, Azure",Bachelor,5,Real Estate,2024-09-22,2024-11-15,609,9.5,DeepTech Ventures +AI09833,AI Specialist,234802,USD,234802,EX,CT,Ireland,M,Ireland,0,"Spark, Kubernetes, Tableau, R, Linux",Master,12,Healthcare,2024-05-15,2024-07-25,906,8.3,Cognitive Computing +AI09834,AI Architect,54715,SGD,71130,EN,FL,Singapore,M,Singapore,50,"Data Visualization, Scala, NLP, Python, Mathematics",Master,1,Government,2025-01-29,2025-04-03,2046,6,Algorithmic Solutions +AI09835,AI Architect,288436,USD,288436,EX,FL,Norway,L,Singapore,100,"Java, Computer Vision, PyTorch, TensorFlow",Master,17,Healthcare,2025-01-21,2025-04-01,1751,8.3,Future Systems +AI09836,Robotics Engineer,77512,EUR,65885,MI,PT,Germany,S,Brazil,0,"Scala, R, Kubernetes",Master,3,Finance,2024-01-25,2024-02-29,704,5.5,DataVision Ltd +AI09837,Research Scientist,230817,GBP,173113,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, Hadoop, Spark",Bachelor,16,Healthcare,2025-01-14,2025-03-08,1547,8.9,Smart Analytics +AI09838,Data Analyst,126549,EUR,107567,SE,PT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, MLOps, AWS, Azure",Associate,7,Media,2025-03-07,2025-05-03,634,6.9,Digital Transformation LLC +AI09839,AI Specialist,55058,JPY,6056380,EN,CT,Japan,S,Japan,100,"Python, Mathematics, TensorFlow",Bachelor,0,Consulting,2024-06-15,2024-08-19,1925,6.1,Future Systems +AI09840,Data Engineer,123391,USD,123391,EX,PT,Israel,S,Mexico,50,"Java, Kubernetes, Tableau",Associate,11,Healthcare,2024-06-07,2024-06-23,2028,8.8,Autonomous Tech +AI09841,NLP Engineer,322051,USD,322051,EX,PT,Norway,L,Norway,100,"Git, R, Python, Computer Vision",Associate,11,Healthcare,2024-12-14,2025-01-08,2432,9.6,Quantum Computing Inc +AI09842,Research Scientist,37366,USD,37366,EN,FL,China,L,United Kingdom,0,"Git, SQL, NLP, PyTorch, Computer Vision",Master,0,Consulting,2024-01-24,2024-03-07,979,7.4,Autonomous Tech +AI09843,NLP Engineer,243682,EUR,207130,EX,FT,Netherlands,M,Netherlands,0,"Git, Python, TensorFlow",PhD,11,Manufacturing,2024-05-07,2024-06-26,1216,7.7,Predictive Systems +AI09844,Robotics Engineer,159124,CHF,143212,MI,FT,Switzerland,L,Switzerland,50,"Linux, GCP, Data Visualization",PhD,3,Media,2024-06-20,2024-07-07,2172,8,Algorithmic Solutions +AI09845,Computer Vision Engineer,49586,SGD,64462,EN,FT,Singapore,S,South Africa,0,"AWS, Git, PyTorch, Deep Learning",Associate,1,Finance,2024-02-20,2024-04-16,2441,9.9,Advanced Robotics +AI09846,Research Scientist,307401,USD,307401,EX,FL,United States,L,United States,50,"AWS, MLOps, Azure",PhD,10,Energy,2024-06-07,2024-07-08,1586,7.7,Neural Networks Co +AI09847,Robotics Engineer,173982,USD,173982,EX,CT,South Korea,S,South Korea,100,"Scala, Computer Vision, Python, Git, NLP",Associate,13,Manufacturing,2025-02-12,2025-03-20,725,7.4,Smart Analytics +AI09848,AI Product Manager,143207,USD,143207,SE,CT,Israel,M,Germany,0,"Python, NLP, TensorFlow",PhD,7,Telecommunications,2024-11-05,2024-11-25,1967,8.9,Algorithmic Solutions +AI09849,AI Research Scientist,144621,SGD,188007,EX,CT,Singapore,S,Singapore,0,"Linux, GCP, Scala",Associate,12,Healthcare,2024-05-31,2024-07-01,1397,6.9,Autonomous Tech +AI09850,AI Consultant,80428,EUR,68364,EN,FT,Germany,M,India,0,"SQL, Tableau, Scala, Git",PhD,0,Manufacturing,2024-11-19,2025-01-19,1987,8.8,Autonomous Tech +AI09851,ML Ops Engineer,306456,SGD,398393,EX,FL,Singapore,L,France,0,"Tableau, AWS, TensorFlow, Python, SQL",PhD,17,Manufacturing,2024-02-27,2024-03-27,2234,9.5,TechCorp Inc +AI09852,Data Scientist,123489,USD,123489,MI,PT,Denmark,M,Sweden,0,"Hadoop, Python, Data Visualization, Kubernetes",Associate,3,Gaming,2025-03-05,2025-04-21,761,8.1,Predictive Systems +AI09853,Machine Learning Researcher,131962,USD,131962,EX,CT,China,L,China,100,"Hadoop, SQL, Data Visualization",Bachelor,18,Retail,2024-01-03,2024-03-12,1973,8.6,Predictive Systems +AI09854,Principal Data Scientist,115511,CAD,144389,SE,FT,Canada,L,Canada,0,"Linux, Kubernetes, GCP, NLP",PhD,6,Technology,2024-06-30,2024-08-27,2363,6.6,Cloud AI Solutions +AI09855,Data Analyst,144101,EUR,122486,SE,PT,Netherlands,M,Netherlands,100,"R, Git, SQL, Java, Data Visualization",Master,9,Healthcare,2024-09-29,2024-10-14,961,5.2,Future Systems +AI09856,Data Engineer,187329,GBP,140497,EX,FT,United Kingdom,L,Russia,0,"Python, Java, Tableau, TensorFlow",Master,10,Energy,2024-12-03,2025-02-09,2026,9.2,Algorithmic Solutions +AI09857,Autonomous Systems Engineer,113840,CAD,142300,SE,CT,Canada,S,Canada,50,"Linux, Python, Tableau, Data Visualization",PhD,7,Technology,2024-11-20,2025-01-01,926,9.2,Digital Transformation LLC +AI09858,Principal Data Scientist,246771,USD,246771,EX,CT,Norway,M,Ghana,100,"R, Deep Learning, Azure, Linux, Kubernetes",Bachelor,19,Government,2024-04-29,2024-07-07,1293,7.2,Advanced Robotics +AI09859,AI Software Engineer,126469,SGD,164410,MI,PT,Singapore,L,Singapore,0,"Azure, R, Java, Python, SQL",Associate,4,Education,2024-01-22,2024-04-04,1395,8.6,Machine Intelligence Group +AI09860,Data Scientist,23821,USD,23821,MI,FL,India,S,India,100,"Git, Java, R",Bachelor,4,Gaming,2024-04-07,2024-06-03,1821,9.8,Cloud AI Solutions +AI09861,Research Scientist,165461,EUR,140642,SE,FT,Netherlands,L,Netherlands,100,"Mathematics, Data Visualization, Linux",Associate,8,Media,2024-11-25,2024-12-14,2016,9.1,Machine Intelligence Group +AI09862,AI Consultant,24465,USD,24465,EN,CT,India,L,India,50,"SQL, Scala, Deep Learning",Bachelor,1,Media,2024-12-15,2025-01-16,1653,7,DeepTech Ventures +AI09863,Machine Learning Researcher,83518,EUR,70990,MI,FT,Germany,M,Germany,100,"Python, NLP, Git, Kubernetes",Associate,4,Healthcare,2024-06-10,2024-07-29,1380,5.1,Neural Networks Co +AI09864,AI Software Engineer,172981,USD,172981,EX,PT,Sweden,S,Luxembourg,50,"Git, Linux, Computer Vision",Associate,16,Retail,2024-02-11,2024-04-13,673,7,Smart Analytics +AI09865,AI Specialist,68862,EUR,58533,MI,CT,Austria,M,Austria,0,"Linux, SQL, Tableau",Master,4,Technology,2024-09-03,2024-11-08,1318,6,Cognitive Computing +AI09866,Computer Vision Engineer,126859,USD,126859,SE,PT,Israel,S,Israel,50,"AWS, Git, Java",Master,7,Consulting,2024-09-13,2024-10-13,626,8.2,Smart Analytics +AI09867,Robotics Engineer,71219,CHF,64097,EN,FT,Switzerland,S,Switzerland,100,"SQL, Scala, Data Visualization, Linux, TensorFlow",PhD,0,Transportation,2024-09-07,2024-10-11,1446,7.2,Quantum Computing Inc +AI09868,AI Consultant,125998,EUR,107098,SE,CT,Austria,L,Austria,50,"SQL, Git, R, PyTorch, Computer Vision",Master,6,Media,2024-10-09,2024-11-27,2170,9.9,Cognitive Computing +AI09869,Head of AI,178944,USD,178944,SE,CT,Denmark,M,Denmark,50,"Kubernetes, Hadoop, MLOps",Bachelor,7,Real Estate,2024-02-29,2024-04-12,1915,7.6,Algorithmic Solutions +AI09870,Deep Learning Engineer,147376,USD,147376,EX,PT,Ireland,M,Ireland,0,"Java, Computer Vision, NLP, PyTorch, Statistics",Bachelor,17,Manufacturing,2024-05-03,2024-06-08,947,9,Predictive Systems +AI09871,Data Analyst,76399,USD,76399,MI,FL,Israel,S,Ukraine,50,"R, Azure, SQL, Computer Vision",Master,2,Manufacturing,2024-04-20,2024-05-31,1191,9.2,Machine Intelligence Group +AI09872,AI Research Scientist,136519,EUR,116041,EX,PT,Germany,M,Austria,100,"Scala, Java, Python, Mathematics, AWS",PhD,19,Manufacturing,2024-08-11,2024-10-16,1833,5.1,DataVision Ltd +AI09873,Deep Learning Engineer,116176,EUR,98750,MI,FL,Austria,L,Austria,50,"Spark, Azure, R, AWS",Master,4,Media,2025-04-06,2025-05-30,2202,5.3,Neural Networks Co +AI09874,AI Research Scientist,114218,AUD,154194,MI,CT,Australia,L,Australia,50,"Hadoop, Kubernetes, SQL",Bachelor,4,Gaming,2025-04-27,2025-05-22,1916,7.5,Digital Transformation LLC +AI09875,Data Analyst,79786,USD,79786,EN,PT,Israel,L,Israel,50,"Spark, Data Visualization, MLOps, Kubernetes, Scala",Bachelor,1,Transportation,2024-03-04,2024-04-12,1711,8.5,TechCorp Inc +AI09876,NLP Engineer,102654,USD,102654,MI,FL,United States,S,United States,50,"PyTorch, MLOps, Deep Learning",Bachelor,3,Telecommunications,2024-10-29,2024-12-28,1731,6.8,Cloud AI Solutions +AI09877,AI Consultant,110047,JPY,12105170,MI,FT,Japan,L,Japan,0,"Scala, Azure, Deep Learning, Linux",PhD,3,Education,2024-08-23,2024-10-11,2493,7.8,TechCorp Inc +AI09878,Robotics Engineer,43437,USD,43437,SE,FT,China,S,China,50,"Java, R, Azure, Data Visualization",PhD,9,Consulting,2024-01-24,2024-02-23,1497,8.3,Digital Transformation LLC +AI09879,AI Architect,197171,CHF,177454,SE,FT,Switzerland,M,Switzerland,100,"AWS, R, Tableau, Mathematics",Bachelor,6,Media,2024-02-18,2024-03-16,1025,5.1,DeepTech Ventures +AI09880,AI Software Engineer,174106,USD,174106,EX,FT,Ireland,L,Ireland,100,"Kubernetes, NLP, TensorFlow, GCP, AWS",PhD,12,Technology,2024-07-15,2024-08-17,1972,9.7,Smart Analytics +AI09881,NLP Engineer,88358,USD,88358,MI,CT,Finland,M,Finland,50,"Docker, MLOps, Python, Mathematics, R",PhD,4,Healthcare,2024-09-27,2024-10-14,2123,7.1,Algorithmic Solutions +AI09882,Head of AI,93787,USD,93787,SE,PT,South Korea,M,India,50,"Computer Vision, PyTorch, Data Visualization",Master,5,Manufacturing,2025-03-02,2025-04-09,1784,6.5,DataVision Ltd +AI09883,Research Scientist,116502,USD,116502,MI,FT,United States,L,United States,100,"NLP, Azure, Data Visualization",PhD,3,Education,2024-02-09,2024-03-30,2387,9.2,Algorithmic Solutions +AI09884,AI Consultant,35301,USD,35301,MI,FT,China,S,Italy,0,"GCP, Deep Learning, Tableau, AWS",PhD,2,Finance,2024-10-18,2024-11-18,820,6.5,DeepTech Ventures +AI09885,Computer Vision Engineer,130851,USD,130851,SE,PT,Denmark,S,Ukraine,0,"TensorFlow, Hadoop, Linux, Kubernetes",Bachelor,5,Retail,2025-03-18,2025-04-05,649,8.2,Digital Transformation LLC +AI09886,AI Research Scientist,122176,USD,122176,SE,FL,Sweden,M,Sweden,100,"Python, Git, Scala, TensorFlow",PhD,9,Government,2024-09-15,2024-10-31,2241,9.2,Future Systems +AI09887,AI Specialist,175333,SGD,227933,SE,FL,Singapore,L,Singapore,50,"Spark, Python, TensorFlow, Tableau",Associate,6,Education,2024-11-19,2025-01-16,826,9,TechCorp Inc +AI09888,Data Scientist,113930,USD,113930,SE,CT,Israel,M,Israel,0,"MLOps, Linux, AWS, Deep Learning, PyTorch",PhD,9,Transportation,2024-03-02,2024-04-27,1764,8.6,Autonomous Tech +AI09889,Data Engineer,122929,USD,122929,MI,FL,Ireland,L,Ireland,100,"PyTorch, R, Java, Python, Spark",Bachelor,2,Automotive,2024-07-09,2024-09-15,1307,8.3,Algorithmic Solutions +AI09890,Research Scientist,188908,EUR,160572,EX,FL,Netherlands,M,Netherlands,100,"Docker, Tableau, Python",PhD,16,Retail,2024-01-20,2024-02-11,1747,7.4,TechCorp Inc +AI09891,AI Architect,66033,USD,66033,EN,PT,South Korea,L,South Korea,50,"Deep Learning, SQL, Mathematics, AWS",PhD,1,Media,2024-06-27,2024-07-20,1478,9.1,Machine Intelligence Group +AI09892,Deep Learning Engineer,148648,AUD,200675,SE,PT,Australia,M,Australia,0,"R, SQL, TensorFlow, Azure, Tableau",Associate,6,Government,2024-08-31,2024-09-28,754,8.7,Smart Analytics +AI09893,Research Scientist,142225,EUR,120891,SE,PT,Germany,M,Germany,50,"Kubernetes, Git, NLP, Mathematics, GCP",Bachelor,9,Transportation,2025-03-03,2025-04-09,1697,9.9,Smart Analytics +AI09894,AI Product Manager,163931,USD,163931,EX,FL,Finland,M,Finland,50,"SQL, Kubernetes, Python, Spark, R",Master,13,Real Estate,2024-11-08,2025-01-08,1318,8.9,DataVision Ltd +AI09895,Autonomous Systems Engineer,71392,EUR,60683,EN,FT,Austria,M,Austria,50,"GCP, Java, Kubernetes, Spark",PhD,1,Finance,2024-02-23,2024-04-28,1661,5.7,Neural Networks Co +AI09896,Machine Learning Researcher,111415,JPY,12255650,SE,FL,Japan,S,Sweden,100,"Deep Learning, Kubernetes, R, TensorFlow, Java",Bachelor,6,Retail,2024-04-04,2024-05-16,742,8,Algorithmic Solutions +AI09897,NLP Engineer,67040,CAD,83800,EN,FL,Canada,M,Canada,0,"MLOps, Linux, Docker, Kubernetes",Master,1,Media,2024-10-25,2025-01-05,1056,8.1,Smart Analytics +AI09898,Research Scientist,336020,USD,336020,EX,CT,Denmark,L,Denmark,0,"Java, Git, PyTorch, AWS, Kubernetes",Master,16,Media,2024-01-25,2024-03-09,1964,6.8,DataVision Ltd +AI09899,AI Consultant,194195,USD,194195,SE,FL,Norway,L,Israel,50,"Scala, Python, NLP",Master,6,Retail,2025-02-12,2025-03-31,2305,7.2,DataVision Ltd +AI09900,AI Software Engineer,110004,EUR,93503,MI,FT,Germany,L,Germany,0,"AWS, Computer Vision, Kubernetes, Java, Spark",Bachelor,2,Consulting,2024-08-08,2024-09-03,1401,5.7,Cognitive Computing +AI09901,NLP Engineer,65717,USD,65717,EN,PT,Finland,S,Finland,0,"Data Visualization, Deep Learning, Spark, AWS",Master,1,Telecommunications,2024-10-08,2024-11-06,2155,8.5,Predictive Systems +AI09902,Data Engineer,80715,GBP,60536,EN,CT,United Kingdom,L,United Kingdom,100,"Azure, NLP, SQL, GCP, Docker",Bachelor,1,Healthcare,2025-01-04,2025-02-25,806,7.6,DataVision Ltd +AI09903,Data Scientist,225112,USD,225112,EX,PT,Ireland,M,Canada,100,"Git, Python, AWS, GCP",Master,19,Retail,2025-03-19,2025-05-21,2392,6,Neural Networks Co +AI09904,Data Engineer,206433,EUR,175468,EX,FL,France,L,Nigeria,50,"Mathematics, Linux, Tableau, Azure",Bachelor,16,Transportation,2025-02-13,2025-02-28,2389,8.6,Algorithmic Solutions +AI09905,Research Scientist,163201,USD,163201,SE,CT,Denmark,S,Denmark,0,"Statistics, NLP, SQL, PyTorch",PhD,8,Automotive,2025-03-20,2025-05-25,1445,9.2,Future Systems +AI09906,Robotics Engineer,210688,EUR,179085,EX,CT,Austria,S,Austria,50,"Java, SQL, Linux, AWS",Bachelor,17,Healthcare,2024-11-03,2024-12-21,1482,6,Algorithmic Solutions +AI09907,AI Specialist,135482,USD,135482,SE,CT,Denmark,S,Denmark,0,"Java, Kubernetes, Hadoop",Master,5,Healthcare,2024-09-03,2024-09-17,1042,5.9,Cloud AI Solutions +AI09908,ML Ops Engineer,80264,SGD,104343,EN,FT,Singapore,M,Netherlands,0,"Azure, GCP, SQL, TensorFlow, Data Visualization",PhD,0,Transportation,2025-01-23,2025-04-03,690,9.9,Smart Analytics +AI09909,AI Consultant,121140,USD,121140,SE,PT,Finland,M,Finland,50,"Mathematics, MLOps, Azure, Linux, SQL",Master,8,Technology,2024-06-30,2024-07-16,689,5.9,Machine Intelligence Group +AI09910,Data Scientist,210071,EUR,178560,EX,PT,Germany,M,Germany,0,"Spark, Statistics, PyTorch, Azure, Mathematics",Bachelor,13,Healthcare,2024-06-21,2024-08-24,1513,5.3,Future Systems +AI09911,Autonomous Systems Engineer,252427,EUR,214563,EX,CT,France,L,Thailand,50,"Python, Linux, TensorFlow",Bachelor,10,Manufacturing,2024-09-26,2024-11-01,2275,7.6,Neural Networks Co +AI09912,AI Architect,211690,USD,211690,EX,PT,Israel,M,Israel,100,"Tableau, Computer Vision, Python, AWS",Associate,11,Real Estate,2024-11-26,2025-01-19,1954,9.6,Advanced Robotics +AI09913,Principal Data Scientist,89052,USD,89052,MI,PT,Ireland,M,Japan,50,"NLP, PyTorch, TensorFlow",Master,2,Media,2025-02-10,2025-04-23,1301,6.4,Machine Intelligence Group +AI09914,Autonomous Systems Engineer,105815,USD,105815,MI,FT,Norway,M,Indonesia,50,"Linux, PyTorch, Kubernetes",Associate,2,Government,2025-02-17,2025-04-07,1594,6.6,DeepTech Ventures +AI09915,AI Research Scientist,107540,USD,107540,SE,FT,Israel,S,Israel,50,"NLP, Hadoop, Kubernetes",Bachelor,7,Manufacturing,2025-02-23,2025-04-09,2336,9.3,DeepTech Ventures +AI09916,ML Ops Engineer,95240,USD,95240,EN,FL,Denmark,M,Denmark,0,"SQL, Data Visualization, PyTorch, Linux",PhD,0,Gaming,2024-06-09,2024-07-06,2323,7.3,DeepTech Ventures +AI09917,Research Scientist,191684,USD,191684,EX,FL,Sweden,S,Sweden,100,"Java, Computer Vision, Git",Master,11,Transportation,2024-02-06,2024-03-04,1230,8.8,Advanced Robotics +AI09918,Principal Data Scientist,59242,USD,59242,EN,FT,South Korea,M,South Korea,50,"Spark, Hadoop, Mathematics, TensorFlow",Associate,1,Consulting,2024-04-08,2024-06-12,1353,6.7,Predictive Systems +AI09919,Machine Learning Researcher,83529,USD,83529,MI,FT,Finland,S,Finland,0,"TensorFlow, Docker, MLOps, Git, GCP",PhD,2,Government,2025-01-20,2025-03-02,1757,6.5,Advanced Robotics +AI09920,Machine Learning Engineer,139067,USD,139067,SE,FT,Finland,M,Finland,50,"Hadoop, Git, Kubernetes, AWS, Python",PhD,9,Technology,2024-03-08,2024-04-13,1871,8.2,Cloud AI Solutions +AI09921,AI Architect,49440,SGD,64272,EN,FT,Singapore,S,Turkey,50,"Data Visualization, NLP, Java, SQL, TensorFlow",Associate,0,Media,2025-04-10,2025-04-26,2447,7.1,Future Systems +AI09922,AI Software Engineer,18220,USD,18220,EN,FT,India,M,India,50,"SQL, TensorFlow, Python, R, Data Visualization",Master,0,Education,2024-04-06,2024-06-15,1271,5.5,Algorithmic Solutions +AI09923,NLP Engineer,65418,USD,65418,EN,FT,Israel,M,Israel,50,"Git, Mathematics, Linux",Bachelor,0,Finance,2024-11-02,2025-01-04,1374,5.7,Cloud AI Solutions +AI09924,Data Analyst,157206,USD,157206,EX,FT,Sweden,M,Sweden,0,"Python, NLP, Mathematics, Spark",Master,14,Automotive,2024-07-16,2024-07-31,2023,9.7,DeepTech Ventures +AI09925,AI Consultant,125227,CHF,112704,EN,PT,Switzerland,L,Switzerland,0,"Docker, Python, Computer Vision, SQL, Linux",Master,1,Manufacturing,2024-02-27,2024-04-03,536,8.5,AI Innovations +AI09926,Data Scientist,99081,USD,99081,SE,FT,Israel,M,Israel,100,"Java, Computer Vision, Kubernetes, Spark",PhD,8,Retail,2024-03-02,2024-04-20,1832,8.1,Neural Networks Co +AI09927,AI Architect,137965,USD,137965,SE,CT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, SQL, Docker, Linux",PhD,7,Retail,2024-09-26,2024-10-26,938,6.3,Cloud AI Solutions +AI09928,AI Product Manager,79335,USD,79335,EN,FT,Sweden,L,Indonesia,100,"MLOps, SQL, Azure, PyTorch",Bachelor,0,Energy,2024-03-04,2024-05-13,2184,7.5,Neural Networks Co +AI09929,Computer Vision Engineer,88458,USD,88458,EX,PT,China,S,China,50,"AWS, R, Tableau, Hadoop",Bachelor,16,Real Estate,2024-12-17,2025-02-24,1991,6.2,Neural Networks Co +AI09930,NLP Engineer,122917,USD,122917,SE,PT,Sweden,S,Sweden,100,"Python, R, GCP, MLOps, Deep Learning",Master,6,Manufacturing,2025-01-18,2025-03-15,763,8.6,Advanced Robotics +AI09931,Autonomous Systems Engineer,51646,JPY,5681060,EN,FT,Japan,S,Poland,0,"Spark, GCP, Docker, R, Kubernetes",Master,1,Transportation,2024-08-09,2024-09-20,1648,6.9,Smart Analytics +AI09932,AI Product Manager,105874,USD,105874,SE,FT,South Korea,S,South Korea,50,"Tableau, Linux, GCP, TensorFlow, Spark",Master,7,Transportation,2024-08-16,2024-09-28,1716,5.8,Machine Intelligence Group +AI09933,AI Specialist,52597,USD,52597,SE,PT,China,S,China,100,"AWS, R, Deep Learning, Computer Vision",Master,8,Telecommunications,2024-12-18,2025-02-25,1975,7.7,Algorithmic Solutions +AI09934,Data Scientist,90978,GBP,68234,MI,PT,United Kingdom,S,United Kingdom,100,"Scala, MLOps, TensorFlow",PhD,4,Healthcare,2024-01-09,2024-01-25,1444,6.4,Algorithmic Solutions +AI09935,Data Analyst,170390,USD,170390,EX,CT,Finland,M,Singapore,0,"Tableau, Azure, SQL, Statistics, AWS",Bachelor,18,Technology,2024-07-20,2024-08-26,650,6.9,Cloud AI Solutions +AI09936,Research Scientist,104491,EUR,88817,MI,CT,Germany,M,Germany,0,"Deep Learning, Linux, Computer Vision, GCP, Docker",PhD,2,Consulting,2024-01-17,2024-02-10,832,8,DeepTech Ventures +AI09937,AI Product Manager,89899,USD,89899,EX,FT,China,M,China,50,"R, AWS, Azure, Deep Learning, Python",Master,12,Real Estate,2025-02-28,2025-04-20,1332,5.4,Neural Networks Co +AI09938,Data Scientist,81953,EUR,69660,EN,PT,Germany,L,Germany,50,"Hadoop, Python, GCP, Deep Learning",Bachelor,0,Manufacturing,2024-12-21,2025-01-18,967,7.3,Neural Networks Co +AI09939,AI Product Manager,63919,GBP,47939,EN,FL,United Kingdom,S,United Kingdom,50,"Docker, SQL, AWS, Mathematics",PhD,0,Finance,2024-05-29,2024-07-25,2267,7,Cognitive Computing +AI09940,AI Software Engineer,251077,USD,251077,EX,PT,Sweden,L,Sweden,50,"Python, GCP, Mathematics, AWS",Bachelor,16,Retail,2024-04-16,2024-05-30,1188,7.2,Future Systems +AI09941,Research Scientist,154431,EUR,131266,EX,CT,Netherlands,M,Israel,0,"Scala, Tableau, Hadoop, Linux",Associate,11,Transportation,2024-09-10,2024-10-31,690,7.3,Machine Intelligence Group +AI09942,Data Scientist,84206,CAD,105258,MI,PT,Canada,S,Canada,0,"Hadoop, Java, SQL, Computer Vision, Azure",Bachelor,3,Real Estate,2024-12-02,2024-12-22,2097,6.3,AI Innovations +AI09943,AI Research Scientist,94103,USD,94103,EX,CT,India,L,Hungary,0,"Hadoop, SQL, Kubernetes",Master,10,Consulting,2024-04-30,2024-06-14,1596,8.2,Quantum Computing Inc +AI09944,Robotics Engineer,172742,EUR,146831,EX,FL,Netherlands,M,Netherlands,100,"Data Visualization, GCP, PyTorch, AWS",Associate,14,Media,2024-05-01,2024-06-22,1002,5.4,DeepTech Ventures +AI09945,AI Consultant,202350,AUD,273173,EX,FL,Australia,S,Australia,0,"Hadoop, Kubernetes, GCP",PhD,18,Media,2024-08-30,2024-10-09,2174,8.1,Predictive Systems +AI09946,AI Product Manager,220924,JPY,24301640,EX,PT,Japan,M,Japan,50,"TensorFlow, Deep Learning, Data Visualization",Associate,18,Government,2025-02-24,2025-04-14,717,6.1,Machine Intelligence Group +AI09947,Machine Learning Engineer,202063,EUR,171754,EX,FL,Germany,L,Germany,100,"Python, TensorFlow, SQL, Linux, Hadoop",Associate,16,Consulting,2024-05-29,2024-08-09,2230,8.7,Digital Transformation LLC +AI09948,NLP Engineer,156925,SGD,204003,SE,PT,Singapore,L,New Zealand,50,"Azure, Spark, Hadoop, Linux, SQL",Bachelor,8,Energy,2025-04-13,2025-05-26,679,8.6,DeepTech Ventures +AI09949,Machine Learning Researcher,127958,USD,127958,SE,FT,United States,S,United States,0,"AWS, SQL, Azure",PhD,6,Consulting,2024-11-25,2025-01-14,2152,9.7,Autonomous Tech +AI09950,AI Architect,88010,USD,88010,MI,PT,Finland,M,Finland,50,"SQL, Data Visualization, Spark, MLOps, Statistics",Bachelor,4,Education,2024-03-04,2024-05-05,2274,9.1,Predictive Systems +AI09951,Data Engineer,73299,USD,73299,EX,CT,India,S,India,0,"Python, Spark, SQL, Deep Learning, Linux",Associate,11,Media,2024-04-15,2024-06-03,668,7.4,Machine Intelligence Group +AI09952,Data Analyst,38886,USD,38886,MI,FT,India,L,India,0,"R, Python, Git, Statistics, Azure",Associate,3,Media,2025-01-14,2025-03-03,2418,5.1,Advanced Robotics +AI09953,Research Scientist,87404,EUR,74293,EN,CT,Netherlands,L,Norway,100,"TensorFlow, GCP, Python, Linux",Bachelor,0,Manufacturing,2024-12-19,2025-02-02,1258,8.5,Future Systems +AI09954,AI Product Manager,50608,EUR,43017,EN,FL,Netherlands,S,Denmark,100,"Spark, MLOps, Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-01-19,2024-03-04,2364,5.5,Advanced Robotics +AI09955,Data Analyst,87958,USD,87958,MI,FL,Sweden,S,Sweden,0,"Java, AWS, Mathematics, Deep Learning",Bachelor,4,Transportation,2024-07-12,2024-09-13,1500,7.9,Cloud AI Solutions +AI09956,NLP Engineer,65492,USD,65492,MI,CT,South Korea,M,Russia,100,"Deep Learning, Python, TensorFlow",Bachelor,2,Gaming,2024-07-06,2024-09-01,1987,9.6,Advanced Robotics +AI09957,Research Scientist,260160,USD,260160,EX,FL,Norway,M,Norway,0,"Linux, Computer Vision, R",Master,17,Finance,2024-03-14,2024-04-12,1484,9.1,AI Innovations +AI09958,Research Scientist,70254,GBP,52691,EN,CT,United Kingdom,M,United Kingdom,0,"Statistics, Tableau, GCP",Master,0,Healthcare,2024-08-06,2024-08-24,1063,7.7,Cognitive Computing +AI09959,NLP Engineer,159037,AUD,214700,EX,FT,Australia,L,Australia,50,"Kubernetes, Docker, Spark",PhD,19,Finance,2025-02-18,2025-03-16,858,6.7,Future Systems +AI09960,Data Scientist,117550,EUR,99918,SE,CT,France,S,France,100,"Computer Vision, Data Visualization, Kubernetes, Scala, Tableau",Master,9,Media,2024-04-08,2024-06-13,1552,7.1,Cognitive Computing +AI09961,Machine Learning Researcher,138817,USD,138817,MI,PT,United States,L,Estonia,50,"R, Deep Learning, TensorFlow, Docker",Master,2,Finance,2025-01-09,2025-03-13,1358,9.7,Neural Networks Co +AI09962,Machine Learning Researcher,233912,AUD,315781,EX,CT,Australia,L,Australia,50,"Hadoop, Linux, Docker",PhD,16,Real Estate,2024-09-26,2024-11-26,1830,8.5,AI Innovations +AI09963,AI Architect,83523,JPY,9187530,EN,FT,Japan,M,Japan,50,"AWS, Docker, Java, R",Associate,1,Transportation,2024-05-26,2024-07-09,1334,8.7,Digital Transformation LLC +AI09964,AI Consultant,49711,USD,49711,SE,CT,India,M,India,0,"PyTorch, Computer Vision, Linux",Bachelor,8,Education,2025-01-13,2025-02-22,1029,7.5,Advanced Robotics +AI09965,AI Product Manager,116921,CAD,146151,SE,FL,Canada,L,Canada,100,"Java, MLOps, SQL",Bachelor,6,Manufacturing,2024-05-09,2024-07-19,2433,8.1,Machine Intelligence Group +AI09966,Data Analyst,213255,CHF,191930,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Linux, Computer Vision, Python, Spark",Associate,8,Healthcare,2024-03-12,2024-04-16,749,7.6,DeepTech Ventures +AI09967,Principal Data Scientist,102306,USD,102306,MI,FL,United States,S,Denmark,0,"Python, NLP, Statistics, Spark, Mathematics",PhD,2,Manufacturing,2024-05-02,2024-05-23,2478,6,Digital Transformation LLC +AI09968,ML Ops Engineer,86619,CAD,108274,MI,CT,Canada,L,Canada,100,"Python, Java, Spark, Computer Vision, TensorFlow",Master,2,Retail,2024-02-08,2024-03-06,1030,7.9,AI Innovations +AI09969,ML Ops Engineer,66607,EUR,56616,EN,FL,Germany,M,Czech Republic,100,"PyTorch, Tableau, Python, Docker, AWS",Bachelor,1,Media,2024-02-14,2024-03-11,2276,9.9,Digital Transformation LLC +AI09970,Head of AI,103856,USD,103856,MI,CT,Ireland,M,Ireland,50,"Computer Vision, Azure, Python, Linux",PhD,3,Retail,2024-10-25,2024-12-04,928,6.4,Digital Transformation LLC +AI09971,AI Consultant,128302,GBP,96227,MI,FT,United Kingdom,L,United Kingdom,100,"Spark, GCP, Deep Learning, Python",Bachelor,2,Transportation,2024-06-22,2024-08-20,648,9.9,Quantum Computing Inc +AI09972,ML Ops Engineer,99518,EUR,84590,MI,PT,Germany,L,Germany,0,"Statistics, MLOps, AWS",Associate,4,Transportation,2024-06-04,2024-06-18,2181,5.9,Cognitive Computing +AI09973,Research Scientist,225083,USD,225083,EX,CT,United States,M,Malaysia,0,"Scala, TensorFlow, Tableau, R",PhD,19,Real Estate,2025-01-09,2025-01-30,1316,7,Quantum Computing Inc +AI09974,Data Scientist,76078,EUR,64666,MI,FL,Austria,S,Austria,100,"R, Java, Linux",Associate,2,Manufacturing,2024-11-29,2024-12-23,871,6,Future Systems +AI09975,Data Analyst,208198,USD,208198,EX,FL,United States,L,China,100,"GCP, R, Spark, SQL",PhD,17,Energy,2024-11-26,2024-12-10,2426,6.8,Machine Intelligence Group +AI09976,Machine Learning Researcher,115497,SGD,150146,SE,FL,Singapore,S,France,50,"Python, Git, Computer Vision, Tableau",Associate,6,Manufacturing,2024-03-23,2024-05-27,1337,7,Advanced Robotics +AI09977,Data Analyst,30191,USD,30191,EN,FL,China,S,South Africa,50,"Python, Computer Vision, Docker, Kubernetes, Git",Master,0,Automotive,2024-06-28,2024-08-09,1509,6.8,Cloud AI Solutions +AI09978,Robotics Engineer,122452,USD,122452,MI,CT,Norway,S,Norway,0,"Spark, PyTorch, Kubernetes, Deep Learning, Tableau",Master,2,Telecommunications,2024-09-10,2024-11-17,1088,7,AI Innovations +AI09979,Robotics Engineer,80064,JPY,8807040,EN,CT,Japan,M,New Zealand,100,"Scala, SQL, Kubernetes, Tableau",Associate,1,Media,2024-12-28,2025-01-16,2318,7.6,Smart Analytics +AI09980,AI Architect,156844,USD,156844,SE,FL,United States,S,United States,50,"Docker, Spark, NLP, SQL, R",Master,8,Telecommunications,2024-01-05,2024-02-18,1084,5.8,Digital Transformation LLC +AI09981,AI Consultant,204204,CHF,183784,SE,CT,Switzerland,L,Switzerland,50,"Spark, AWS, Python",Master,8,Technology,2025-02-24,2025-05-02,1083,6.1,Cloud AI Solutions +AI09982,Principal Data Scientist,33152,USD,33152,MI,PT,India,L,India,100,"Deep Learning, Azure, Scala",Associate,3,Real Estate,2025-02-27,2025-03-31,1465,9.2,TechCorp Inc +AI09983,Data Engineer,65768,USD,65768,SE,FL,China,M,France,100,"R, Statistics, Scala, AWS, Azure",PhD,9,Gaming,2024-12-04,2024-12-25,2408,6.3,Machine Intelligence Group +AI09984,Data Scientist,73194,USD,73194,MI,PT,Sweden,M,Sweden,100,"Docker, Data Visualization, Linux",Associate,3,Retail,2024-08-23,2024-09-08,1618,8.2,AI Innovations +AI09985,AI Architect,55370,SGD,71981,EN,FL,Singapore,S,Singapore,50,"Mathematics, AWS, Hadoop",Associate,0,Retail,2024-11-08,2024-12-07,2104,8.3,Advanced Robotics +AI09986,Deep Learning Engineer,210307,GBP,157730,EX,FT,United Kingdom,M,United Kingdom,0,"GCP, Linux, Computer Vision, Java, Deep Learning",PhD,18,Retail,2024-04-30,2024-06-16,1090,5.3,Digital Transformation LLC +AI09987,AI Research Scientist,84436,USD,84436,EN,FT,United States,M,United States,100,"Java, NLP, GCP, Kubernetes",Master,1,Consulting,2024-04-24,2024-05-12,1654,7.3,Cognitive Computing +AI09988,ML Ops Engineer,54161,AUD,73117,EN,FT,Australia,S,Australia,0,"Azure, Scala, Java",PhD,1,Healthcare,2024-10-22,2024-11-13,1338,8.3,Neural Networks Co +AI09989,AI Software Engineer,205169,USD,205169,EX,CT,United States,M,United States,100,"Python, Tableau, NLP, Computer Vision",Master,12,Transportation,2024-09-27,2024-11-13,2197,5.7,DeepTech Ventures +AI09990,Data Engineer,38591,USD,38591,MI,PT,China,M,Colombia,50,"Python, Statistics, MLOps, TensorFlow, Computer Vision",Master,4,Transportation,2025-01-01,2025-02-12,1506,9.6,Neural Networks Co +AI09991,Research Scientist,68630,EUR,58336,EN,FT,France,L,United Kingdom,50,"R, Python, NLP, Data Visualization",PhD,0,Finance,2025-04-30,2025-06-24,2243,6.6,DeepTech Ventures +AI09992,Autonomous Systems Engineer,43605,USD,43605,SE,CT,China,S,China,0,"PyTorch, Deep Learning, TensorFlow",Bachelor,9,Consulting,2025-03-28,2025-05-18,969,7,Advanced Robotics +AI09993,ML Ops Engineer,161575,USD,161575,EX,CT,Finland,M,Finland,0,"Docker, Scala, Hadoop, TensorFlow, NLP",Master,16,Consulting,2024-11-16,2024-12-06,2224,9.9,Cognitive Computing +AI09994,Autonomous Systems Engineer,45084,USD,45084,MI,FL,China,M,China,50,"Linux, SQL, GCP",Bachelor,3,Telecommunications,2024-05-10,2024-05-29,1998,8.6,Neural Networks Co +AI09995,AI Product Manager,88847,USD,88847,SE,CT,South Korea,S,South Korea,100,"Hadoop, Scala, Tableau",Associate,5,Media,2024-07-09,2024-09-19,1406,5.1,Smart Analytics +AI09996,Data Analyst,273652,USD,273652,EX,PT,Norway,L,Norway,50,"Docker, Statistics, Linux, Python",Master,12,Real Estate,2024-04-28,2024-06-03,1723,8.9,Cognitive Computing +AI09997,AI Specialist,77815,JPY,8559650,EN,CT,Japan,M,Japan,50,"Python, SQL, Data Visualization, MLOps",Bachelor,1,Technology,2024-10-14,2024-12-14,1183,8.1,Cognitive Computing +AI09998,Head of AI,71265,USD,71265,MI,CT,Sweden,S,Ireland,100,"PyTorch, GCP, Kubernetes",Associate,2,Transportation,2024-08-02,2024-09-08,937,7.6,Algorithmic Solutions +AI09999,ML Ops Engineer,206399,USD,206399,EX,CT,United States,L,United States,0,"PyTorch, R, Tableau",Master,18,Automotive,2024-12-04,2024-12-27,1313,9,Neural Networks Co +AI10000,AI Consultant,199903,JPY,21989330,EX,FL,Japan,L,France,0,"Git, Python, Docker",PhD,16,Education,2025-04-27,2025-05-11,2171,7.3,Advanced Robotics +AI10001,AI Specialist,167578,USD,167578,SE,FT,Denmark,S,Denmark,100,"Linux, Python, Hadoop",PhD,6,Healthcare,2024-08-07,2024-09-16,996,9.6,Autonomous Tech +AI10002,AI Architect,154721,CHF,139249,SE,CT,Switzerland,M,Sweden,0,"Python, TensorFlow, MLOps, Azure",Bachelor,6,Government,2024-09-15,2024-10-05,1917,8.6,Future Systems +AI10003,AI Consultant,122754,EUR,104341,SE,FT,Netherlands,S,Czech Republic,100,"Spark, MLOps, TensorFlow, NLP, Mathematics",Master,7,Transportation,2025-01-20,2025-03-05,1738,5.5,Autonomous Tech +AI10004,Data Analyst,68729,USD,68729,EN,FL,Israel,M,Israel,0,"Computer Vision, Statistics, SQL, Python",Master,0,Automotive,2025-03-07,2025-04-07,1313,5.1,Cognitive Computing +AI10005,AI Software Engineer,85966,SGD,111756,EN,FT,Singapore,L,Singapore,100,"Hadoop, Docker, Data Visualization, Python",Associate,0,Education,2025-04-01,2025-04-22,1119,9.4,DataVision Ltd +AI10006,Data Analyst,131244,JPY,14436840,SE,FL,Japan,L,Japan,50,"Git, Scala, Java, Computer Vision",Master,8,Media,2024-03-24,2024-04-26,960,8.3,Autonomous Tech +AI10007,Computer Vision Engineer,122218,USD,122218,SE,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Hadoop, MLOps",Associate,7,Automotive,2024-05-12,2024-07-18,2497,8.8,Quantum Computing Inc +AI10008,Research Scientist,79816,USD,79816,EN,PT,Norway,S,Canada,0,"Python, GCP, AWS",Bachelor,1,Manufacturing,2024-04-19,2024-06-25,546,6.3,Cognitive Computing +AI10009,Machine Learning Engineer,76709,EUR,65203,MI,PT,Netherlands,S,Netherlands,0,"TensorFlow, Azure, Kubernetes, Python, MLOps",Bachelor,2,Media,2024-04-28,2024-06-14,531,8.4,DeepTech Ventures +AI10010,Data Analyst,53982,USD,53982,EN,FT,Ireland,S,South Africa,0,"SQL, Scala, Tableau",Bachelor,0,Government,2024-06-29,2024-09-01,1371,8.3,Future Systems +AI10011,ML Ops Engineer,192615,EUR,163723,EX,FL,France,M,France,0,"Kubernetes, Tableau, Python",PhD,11,Energy,2025-01-29,2025-03-17,505,9.4,DataVision Ltd +AI10012,AI Architect,145605,JPY,16016550,SE,PT,Japan,L,Japan,100,"R, GCP, Java",Bachelor,8,Technology,2025-03-10,2025-04-10,2336,7.4,Neural Networks Co +AI10013,Autonomous Systems Engineer,97274,USD,97274,MI,PT,Denmark,S,Denmark,50,"PyTorch, Azure, Git",Bachelor,2,Technology,2024-10-18,2024-11-27,1260,9,TechCorp Inc +AI10014,AI Specialist,244858,USD,244858,EX,FL,Norway,S,Norway,100,"PyTorch, R, SQL, Statistics",Associate,15,Media,2024-03-14,2024-05-20,1932,7.1,Autonomous Tech +AI10015,Data Engineer,104413,EUR,88751,MI,PT,Netherlands,L,Netherlands,0,"GCP, MLOps, Scala, Kubernetes",Associate,4,Healthcare,2025-03-26,2025-05-18,1269,6.8,AI Innovations +AI10016,AI Specialist,213972,USD,213972,SE,CT,Norway,L,Norway,100,"AWS, Docker, Data Visualization, Deep Learning",Bachelor,6,Education,2024-05-04,2024-07-09,2063,5.1,Advanced Robotics +AI10017,Machine Learning Engineer,163739,USD,163739,EX,CT,Finland,S,Finland,0,"AWS, Kubernetes, Statistics, R",Associate,18,Real Estate,2024-12-11,2025-01-28,1031,8.2,Quantum Computing Inc +AI10018,Head of AI,54758,USD,54758,EN,CT,South Korea,S,Chile,0,"Tableau, Linux, AWS, TensorFlow, Deep Learning",Master,0,Technology,2024-12-13,2025-02-18,1502,6.9,DataVision Ltd +AI10019,Principal Data Scientist,90479,EUR,76907,MI,PT,France,M,Ireland,100,"Docker, R, MLOps, Kubernetes",Associate,4,Telecommunications,2024-03-19,2024-05-02,1148,9.7,Future Systems +AI10020,Deep Learning Engineer,159487,USD,159487,SE,PT,Norway,L,Singapore,100,"Docker, MLOps, Tableau, Python, Kubernetes",PhD,7,Real Estate,2024-09-25,2024-11-25,2469,6.3,Future Systems +AI10021,Computer Vision Engineer,64591,EUR,54902,EN,FT,Netherlands,L,Netherlands,0,"Scala, AWS, SQL, Python",Bachelor,1,Finance,2024-03-15,2024-04-23,2168,6.5,Neural Networks Co +AI10022,AI Product Manager,186453,GBP,139840,EX,CT,United Kingdom,M,Philippines,100,"TensorFlow, Hadoop, AWS, Java, Deep Learning",Bachelor,19,Technology,2024-09-17,2024-11-04,1428,5.1,DataVision Ltd +AI10023,Principal Data Scientist,367782,USD,367782,EX,FT,Denmark,L,Switzerland,0,"Data Visualization, Python, Git",Bachelor,16,Finance,2024-08-20,2024-10-12,1285,8.6,Future Systems +AI10024,Data Scientist,122924,AUD,165947,MI,FL,Australia,L,Spain,0,"Java, Linux, TensorFlow, SQL, MLOps",Master,4,Healthcare,2024-09-05,2024-09-19,797,7.6,Neural Networks Co +AI10025,Autonomous Systems Engineer,243749,AUD,329061,EX,PT,Australia,L,Australia,100,"GCP, Data Visualization, Linux, Computer Vision, SQL",PhD,19,Retail,2025-02-08,2025-03-22,2447,6.4,AI Innovations +AI10026,Computer Vision Engineer,78463,JPY,8630930,MI,CT,Japan,S,Japan,50,"Scala, Data Visualization, Git",Associate,3,Manufacturing,2024-04-17,2024-06-10,2462,9.4,TechCorp Inc +AI10027,Machine Learning Engineer,177410,USD,177410,SE,FT,Norway,M,Norway,0,"Linux, Python, PyTorch, Scala, AWS",Master,6,Consulting,2024-06-25,2024-08-15,1228,9.4,Machine Intelligence Group +AI10028,Robotics Engineer,85282,USD,85282,MI,FL,Israel,M,Israel,0,"Scala, Linux, TensorFlow, GCP, Statistics",PhD,2,Manufacturing,2024-07-04,2024-07-20,607,5.8,Digital Transformation LLC +AI10029,AI Consultant,54574,USD,54574,EN,CT,United States,S,United States,100,"Scala, Docker, Computer Vision, SQL",Master,1,Technology,2024-07-18,2024-08-21,1471,9.1,Algorithmic Solutions +AI10030,AI Architect,99684,JPY,10965240,MI,FL,Japan,M,Malaysia,100,"R, SQL, Kubernetes",Master,4,Transportation,2024-12-14,2025-02-25,1017,7,AI Innovations +AI10031,Autonomous Systems Engineer,107913,EUR,91726,SE,FT,France,S,France,100,"Spark, TensorFlow, Kubernetes",PhD,9,Government,2024-04-05,2024-06-09,769,9.3,Quantum Computing Inc +AI10032,Deep Learning Engineer,110437,SGD,143568,MI,FL,Singapore,L,Singapore,100,"Docker, MLOps, GCP, Python",Associate,2,Technology,2024-03-16,2024-05-18,1027,5.6,Cognitive Computing +AI10033,Data Scientist,32139,USD,32139,MI,FL,China,S,China,0,"Git, Python, Mathematics",Bachelor,2,Real Estate,2024-06-18,2024-07-31,1820,7.2,TechCorp Inc +AI10034,Research Scientist,78757,USD,78757,MI,FL,Ireland,M,Thailand,0,"Python, Tableau, NLP, MLOps",PhD,3,Government,2024-06-24,2024-08-26,1381,9.5,Algorithmic Solutions +AI10035,AI Architect,264042,AUD,356457,EX,FT,Australia,L,Australia,0,"Kubernetes, Statistics, MLOps, R",Associate,12,Telecommunications,2024-02-29,2024-05-01,2038,9.1,Autonomous Tech +AI10036,Data Engineer,208291,USD,208291,EX,PT,Ireland,L,Ireland,50,"Linux, AWS, Python, TensorFlow, Deep Learning",Master,11,Retail,2024-03-06,2024-05-15,1662,7.2,Cloud AI Solutions +AI10037,AI Architect,100038,USD,100038,MI,CT,Denmark,M,Egypt,100,"Kubernetes, Computer Vision, Git, NLP, Deep Learning",PhD,4,Retail,2024-01-23,2024-02-06,2234,6.8,DataVision Ltd +AI10038,NLP Engineer,77060,USD,77060,EN,PT,Norway,L,Israel,0,"Kubernetes, PyTorch, Mathematics",Associate,0,Government,2024-12-25,2025-01-08,1416,6.7,DeepTech Ventures +AI10039,Autonomous Systems Engineer,222150,USD,222150,EX,PT,Denmark,L,Switzerland,50,"Statistics, R, Python, Mathematics, Data Visualization",PhD,16,Gaming,2024-07-07,2024-09-10,1253,6.1,DataVision Ltd +AI10040,Robotics Engineer,163117,USD,163117,EX,CT,Israel,S,France,100,"SQL, Mathematics, Java",Bachelor,15,Education,2025-02-09,2025-04-20,584,6.3,Future Systems +AI10041,Research Scientist,221296,JPY,24342560,EX,PT,Japan,S,Austria,50,"AWS, Scala, GCP",PhD,10,Government,2024-02-06,2024-02-25,616,7.2,Advanced Robotics +AI10042,NLP Engineer,75240,USD,75240,MI,PT,Sweden,M,Sweden,50,"MLOps, NLP, TensorFlow",Bachelor,3,Technology,2024-01-03,2024-01-27,2150,9.7,Algorithmic Solutions +AI10043,AI Specialist,190468,GBP,142851,EX,PT,United Kingdom,S,United Kingdom,100,"R, Azure, Tableau, SQL",Associate,10,Gaming,2024-04-07,2024-05-11,2175,6,AI Innovations +AI10044,Machine Learning Engineer,229205,USD,229205,EX,FL,Norway,L,Norway,0,"Mathematics, PyTorch, Docker",Master,19,Government,2024-07-30,2024-08-27,702,5.6,Machine Intelligence Group +AI10045,AI Product Manager,158082,JPY,17389020,EX,FL,Japan,S,Japan,100,"Linux, Data Visualization, Spark",Bachelor,17,Retail,2024-04-13,2024-06-02,1116,6.2,Neural Networks Co +AI10046,Autonomous Systems Engineer,158388,EUR,134630,SE,PT,Austria,L,Austria,50,"MLOps, Azure, Tableau, Data Visualization",PhD,7,Transportation,2024-09-03,2024-11-15,1409,9.8,DataVision Ltd +AI10047,Deep Learning Engineer,270701,USD,270701,EX,CT,Norway,M,Norway,0,"GCP, Kubernetes, Python",Bachelor,10,Technology,2024-04-22,2024-06-02,673,9.5,AI Innovations +AI10048,AI Specialist,106640,EUR,90644,MI,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Statistics, Docker",PhD,4,Education,2024-12-18,2025-02-15,1432,8.5,TechCorp Inc +AI10049,AI Research Scientist,69424,EUR,59010,MI,FT,France,M,France,50,"GCP, AWS, Docker, Computer Vision, Python",Associate,2,Government,2024-05-11,2024-07-08,848,7,Cloud AI Solutions +AI10050,AI Research Scientist,93528,USD,93528,EN,FT,United States,L,United States,50,"Kubernetes, Docker, Statistics, Scala, Mathematics",Master,0,Transportation,2025-03-09,2025-05-15,1627,6,Autonomous Tech +AI10051,AI Software Engineer,114025,SGD,148233,MI,CT,Singapore,L,Singapore,50,"Scala, Python, Git, GCP, Computer Vision",Bachelor,3,Energy,2025-01-12,2025-02-16,2470,8.2,Cognitive Computing +AI10052,Machine Learning Engineer,91997,EUR,78197,MI,FL,France,S,France,100,"Python, Spark, Git, TensorFlow, Java",Associate,4,Transportation,2025-01-24,2025-02-13,505,8.6,DataVision Ltd +AI10053,Deep Learning Engineer,120244,SGD,156317,SE,PT,Singapore,S,Argentina,0,"Mathematics, Python, Hadoop, Tableau",Master,7,Gaming,2024-04-17,2024-05-07,721,7.3,DataVision Ltd +AI10054,Data Analyst,132194,USD,132194,EX,CT,China,L,China,50,"SQL, PyTorch, MLOps, TensorFlow",PhD,18,Telecommunications,2024-04-22,2024-06-24,1300,5.8,DataVision Ltd +AI10055,AI Specialist,108571,USD,108571,EX,CT,China,M,Kenya,100,"SQL, Linux, TensorFlow, Deep Learning",Bachelor,11,Media,2024-04-30,2024-05-17,1016,7.8,Predictive Systems +AI10056,Autonomous Systems Engineer,75698,USD,75698,EN,FL,Israel,M,Israel,100,"SQL, AWS, Hadoop, Python",Master,1,Technology,2025-03-25,2025-05-09,1791,8.2,AI Innovations +AI10057,Principal Data Scientist,39365,USD,39365,MI,CT,China,L,China,100,"Statistics, Git, GCP, Azure",Associate,3,Transportation,2024-01-19,2024-03-24,2176,8.1,Advanced Robotics +AI10058,Robotics Engineer,183526,EUR,155997,EX,PT,Germany,L,Germany,0,"NLP, Git, Java",Bachelor,10,Automotive,2024-10-10,2024-11-28,974,7.4,DataVision Ltd +AI10059,AI Consultant,143337,EUR,121836,EX,PT,Germany,M,Poland,100,"Data Visualization, SQL, PyTorch",Master,14,Technology,2024-06-16,2024-07-05,1608,5.2,DeepTech Ventures +AI10060,AI Software Engineer,63211,GBP,47408,EN,FL,United Kingdom,M,United Kingdom,50,"NLP, Git, MLOps",Associate,1,Gaming,2024-07-29,2024-09-17,2029,6.6,TechCorp Inc +AI10061,AI Architect,60718,GBP,45539,EN,FL,United Kingdom,S,United Kingdom,0,"GCP, Tableau, Scala, Java, AWS",Associate,0,Consulting,2024-03-05,2024-04-25,1108,9.2,DeepTech Ventures +AI10062,Robotics Engineer,93597,USD,93597,MI,FL,Finland,L,Poland,100,"Python, Scala, Tableau, MLOps, Azure",Bachelor,2,Government,2024-02-26,2024-03-16,1084,9.8,Quantum Computing Inc +AI10063,Deep Learning Engineer,92670,USD,92670,SE,FL,Israel,S,Israel,0,"Spark, Statistics, Linux, Mathematics",Master,9,Energy,2024-02-20,2024-04-18,674,5.5,Digital Transformation LLC +AI10064,Principal Data Scientist,52329,AUD,70644,EN,FL,Australia,M,Australia,100,"Linux, TensorFlow, Azure",Bachelor,1,Gaming,2025-02-07,2025-03-14,648,9.2,Autonomous Tech +AI10065,Autonomous Systems Engineer,110402,CHF,99362,MI,FT,Switzerland,M,Switzerland,100,"SQL, PyTorch, Azure",Bachelor,4,Finance,2024-02-11,2024-03-08,1722,5.9,Digital Transformation LLC +AI10066,Head of AI,79269,EUR,67379,EN,CT,France,L,France,100,"Python, TensorFlow, AWS",PhD,0,Transportation,2024-08-18,2024-10-10,1318,9.9,Cloud AI Solutions +AI10067,Deep Learning Engineer,147090,AUD,198572,SE,CT,Australia,L,Australia,0,"Statistics, GCP, NLP, MLOps",Bachelor,8,Media,2024-08-23,2024-10-13,1890,7.2,Digital Transformation LLC +AI10068,Research Scientist,95456,CAD,119320,SE,CT,Canada,S,Canada,0,"Scala, R, Hadoop, GCP",PhD,7,Technology,2024-01-06,2024-01-26,2009,9.3,Digital Transformation LLC +AI10069,AI Software Engineer,86713,GBP,65035,MI,CT,United Kingdom,S,United Kingdom,0,"R, Data Visualization, PyTorch, Java, Statistics",Associate,2,Real Estate,2024-06-09,2024-07-18,795,9.6,Cloud AI Solutions +AI10070,Robotics Engineer,267784,EUR,227616,EX,PT,Germany,L,Germany,0,"SQL, Java, Statistics, Computer Vision, GCP",PhD,17,Real Estate,2024-01-04,2024-02-25,2268,9,AI Innovations +AI10071,Autonomous Systems Engineer,107929,EUR,91740,MI,FL,Germany,M,Israel,0,"SQL, R, Data Visualization",PhD,4,Healthcare,2025-01-30,2025-03-16,608,9.1,Algorithmic Solutions +AI10072,Data Engineer,187961,USD,187961,SE,FT,Denmark,M,Denmark,50,"Mathematics, Java, Scala",PhD,5,Healthcare,2024-10-26,2024-11-17,887,8.6,Future Systems +AI10073,Research Scientist,79425,USD,79425,EN,CT,United States,S,Portugal,0,"Spark, R, Scala",Bachelor,0,Retail,2024-04-16,2024-05-04,2159,6.3,Machine Intelligence Group +AI10074,Autonomous Systems Engineer,69795,EUR,59326,MI,FL,France,M,France,50,"Java, Mathematics, Kubernetes, TensorFlow",Master,4,Finance,2025-02-19,2025-03-21,1831,9.8,Algorithmic Solutions +AI10075,NLP Engineer,91415,SGD,118840,MI,FT,Singapore,S,Singapore,0,"Computer Vision, Linux, Statistics",Associate,3,Media,2024-06-17,2024-08-24,607,6,Algorithmic Solutions +AI10076,AI Software Engineer,69308,EUR,58912,EN,PT,France,L,France,100,"R, PyTorch, Statistics, Git",Bachelor,0,Healthcare,2024-09-21,2024-11-28,1355,9.4,TechCorp Inc +AI10077,AI Software Engineer,262289,GBP,196717,EX,FT,United Kingdom,L,United Kingdom,100,"Computer Vision, Deep Learning, Data Visualization",Bachelor,12,Government,2025-03-26,2025-05-15,1644,9,Future Systems +AI10078,Research Scientist,117333,USD,117333,MI,PT,Ireland,L,Ireland,50,"Hadoop, Tableau, Java, Deep Learning",PhD,3,Education,2024-03-06,2024-05-10,1796,8,Digital Transformation LLC +AI10079,AI Architect,109771,USD,109771,MI,FT,United States,M,United States,100,"Linux, R, Kubernetes, Deep Learning",Associate,2,Finance,2024-01-09,2024-03-21,2490,5,Algorithmic Solutions +AI10080,NLP Engineer,150367,USD,150367,MI,FT,Norway,L,Romania,50,"SQL, TensorFlow, Computer Vision, AWS, Tableau",Associate,3,Technology,2024-05-15,2024-06-27,1894,5.2,AI Innovations +AI10081,Deep Learning Engineer,88240,EUR,75004,MI,PT,France,M,United Kingdom,100,"Data Visualization, TensorFlow, Docker, GCP, Deep Learning",Bachelor,2,Government,2025-03-26,2025-05-09,2369,9.8,Autonomous Tech +AI10082,NLP Engineer,158509,JPY,17435990,EX,FL,Japan,M,Japan,0,"PyTorch, Git, Scala, GCP",Master,19,Healthcare,2024-08-08,2024-09-13,2335,7.4,Digital Transformation LLC +AI10083,Computer Vision Engineer,95690,CHF,86121,EN,PT,Switzerland,M,Switzerland,100,"NLP, Spark, Python, Mathematics",Associate,0,Healthcare,2024-11-22,2025-01-23,2223,9.4,Digital Transformation LLC +AI10084,Research Scientist,65431,GBP,49073,EN,FL,United Kingdom,S,United Kingdom,100,"Docker, Tableau, Linux, Kubernetes",Associate,0,Transportation,2025-04-16,2025-05-05,1112,8,Cloud AI Solutions +AI10085,Research Scientist,41112,USD,41112,MI,FT,India,L,India,100,"Hadoop, Kubernetes, Python",PhD,4,Media,2024-05-12,2024-06-04,2195,8.7,Cognitive Computing +AI10086,AI Software Engineer,59137,EUR,50266,EN,FT,Netherlands,M,Netherlands,100,"Hadoop, Java, Azure",PhD,0,Transportation,2024-06-10,2024-08-02,514,9.7,Smart Analytics +AI10087,Autonomous Systems Engineer,78995,EUR,67146,MI,FT,Germany,S,Colombia,50,"Scala, Java, AWS",Bachelor,4,Real Estate,2024-06-15,2024-08-07,1977,5.2,DataVision Ltd +AI10088,Computer Vision Engineer,48283,USD,48283,SE,FL,China,S,Austria,0,"AWS, Deep Learning, Spark, SQL, Scala",Master,7,Technology,2024-05-10,2024-06-15,1845,5.8,Algorithmic Solutions +AI10089,Autonomous Systems Engineer,151012,USD,151012,SE,CT,Denmark,S,Australia,50,"Java, Kubernetes, Linux",Master,6,Healthcare,2025-01-29,2025-04-04,621,9.2,Neural Networks Co +AI10090,Deep Learning Engineer,225202,USD,225202,EX,FL,Norway,S,New Zealand,0,"R, Docker, Deep Learning",Associate,10,Technology,2024-01-15,2024-03-12,2018,7,Predictive Systems +AI10091,Computer Vision Engineer,172242,USD,172242,EX,FT,Denmark,S,Denmark,50,"MLOps, NLP, Spark",Associate,18,Telecommunications,2024-08-15,2024-10-24,500,6.8,Algorithmic Solutions +AI10092,AI Consultant,99624,JPY,10958640,MI,PT,Japan,S,Colombia,100,"R, GCP, Computer Vision, Data Visualization, Hadoop",PhD,3,Technology,2025-03-12,2025-04-17,2365,7.9,Neural Networks Co +AI10093,AI Software Engineer,116417,EUR,98954,SE,CT,Netherlands,M,Netherlands,100,"Kubernetes, GCP, AWS, Tableau",Associate,7,Automotive,2024-12-20,2025-02-26,1379,6.9,DeepTech Ventures +AI10094,Deep Learning Engineer,181783,EUR,154516,EX,PT,France,S,Romania,100,"Python, Mathematics, Hadoop, Java",PhD,19,Education,2024-05-01,2024-06-29,557,5.8,DataVision Ltd +AI10095,AI Research Scientist,150971,AUD,203811,SE,CT,Australia,L,Australia,50,"SQL, Hadoop, Mathematics, Git, Docker",Associate,7,Real Estate,2025-01-16,2025-02-04,2333,7.3,Autonomous Tech +AI10096,ML Ops Engineer,94318,USD,94318,MI,PT,Norway,S,Mexico,50,"Scala, GCP, Java, Git",Bachelor,2,Automotive,2024-03-02,2024-05-07,1541,7.2,Algorithmic Solutions +AI10097,AI Research Scientist,95368,GBP,71526,MI,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, AWS, Docker",Bachelor,2,Finance,2025-04-19,2025-05-17,2341,7,TechCorp Inc +AI10098,AI Product Manager,190518,AUD,257199,EX,FT,Australia,M,Australia,100,"Hadoop, Spark, PyTorch",Associate,15,Energy,2024-01-19,2024-02-10,880,9.8,Machine Intelligence Group +AI10099,Computer Vision Engineer,55407,USD,55407,SE,CT,China,L,China,100,"Statistics, NLP, Scala",Master,5,Government,2024-03-02,2024-03-19,2404,7.2,Neural Networks Co +AI10100,ML Ops Engineer,21909,USD,21909,EN,FL,India,S,India,100,"Spark, Kubernetes, Tableau, Linux, Scala",Master,1,Healthcare,2024-07-27,2024-09-24,2258,6.6,Quantum Computing Inc +AI10101,AI Product Manager,92434,EUR,78569,MI,FL,France,M,South Africa,50,"Spark, SQL, Kubernetes, Deep Learning, Mathematics",PhD,3,Retail,2024-02-18,2024-04-04,562,9.3,Advanced Robotics +AI10102,Data Engineer,161210,USD,161210,SE,PT,Denmark,S,Denmark,100,"SQL, GCP, Statistics, Docker",Associate,6,Manufacturing,2024-02-09,2024-03-15,1008,5.9,Future Systems +AI10103,Head of AI,67818,USD,67818,SE,PT,China,L,Belgium,100,"Git, PyTorch, Tableau, R",Bachelor,5,Education,2024-12-28,2025-03-04,972,6.6,Machine Intelligence Group +AI10104,Computer Vision Engineer,93012,EUR,79060,MI,CT,Netherlands,M,Netherlands,0,"MLOps, Scala, Statistics",PhD,3,Finance,2024-03-20,2024-05-18,1313,5.2,Quantum Computing Inc +AI10105,Data Scientist,44243,USD,44243,MI,FL,China,L,China,100,"Python, Spark, MLOps",Associate,4,Education,2025-04-03,2025-06-01,1470,7.3,Algorithmic Solutions +AI10106,Deep Learning Engineer,73792,CAD,92240,EN,CT,Canada,L,South Korea,50,"MLOps, TensorFlow, Scala, Hadoop",PhD,0,Healthcare,2024-07-27,2024-09-16,1612,7.8,TechCorp Inc +AI10107,Deep Learning Engineer,82816,USD,82816,EX,FL,China,L,China,0,"Java, AWS, Azure, Python",Master,17,Energy,2024-04-16,2024-06-26,1824,5.1,DeepTech Ventures +AI10108,Robotics Engineer,153795,EUR,130726,SE,FT,Netherlands,L,Austria,50,"MLOps, TensorFlow, Docker",PhD,5,Technology,2025-04-25,2025-05-26,1033,5.1,TechCorp Inc +AI10109,Machine Learning Researcher,86614,USD,86614,MI,FT,Finland,L,Finland,0,"Python, TensorFlow, AWS",PhD,3,Education,2025-01-09,2025-02-10,827,8.6,Cloud AI Solutions +AI10110,Autonomous Systems Engineer,75523,EUR,64195,EN,FT,France,L,Russia,100,"R, SQL, Docker, MLOps, PyTorch",Master,1,Transportation,2024-06-18,2024-08-12,1776,6.4,Advanced Robotics +AI10111,Principal Data Scientist,105311,USD,105311,SE,PT,Israel,M,Israel,0,"Java, PyTorch, Statistics",PhD,5,Media,2024-07-16,2024-08-13,1714,8.6,Autonomous Tech +AI10112,Machine Learning Engineer,49131,JPY,5404410,EN,CT,Japan,S,Belgium,50,"Hadoop, GCP, Scala, TensorFlow",Master,1,Healthcare,2024-07-30,2024-09-22,1387,6.7,Machine Intelligence Group +AI10113,Head of AI,26483,USD,26483,EN,FL,China,S,China,50,"Java, Computer Vision, Data Visualization, GCP, PyTorch",PhD,1,Consulting,2024-08-06,2024-10-05,1235,8.1,TechCorp Inc +AI10114,Data Engineer,107269,USD,107269,SE,FT,Israel,S,Australia,100,"PyTorch, Spark, SQL, Linux",Associate,9,Energy,2024-10-02,2024-11-22,1007,6,Future Systems +AI10115,AI Product Manager,78026,USD,78026,EN,FL,Denmark,S,Denmark,100,"Git, Python, Linux, Azure",Bachelor,1,Retail,2024-05-22,2024-07-07,2242,6.5,TechCorp Inc +AI10116,ML Ops Engineer,98849,USD,98849,MI,PT,United States,L,Poland,100,"PyTorch, SQL, Data Visualization, Computer Vision",Associate,4,Consulting,2024-11-04,2024-12-28,540,5.1,DataVision Ltd +AI10117,Machine Learning Engineer,246511,USD,246511,EX,PT,Denmark,S,Russia,50,"Hadoop, Python, Tableau",Master,16,Real Estate,2024-02-18,2024-03-26,812,8.6,Algorithmic Solutions +AI10118,Head of AI,108146,CHF,97331,EN,FL,Switzerland,M,Switzerland,0,"Python, AWS, TensorFlow",PhD,0,Telecommunications,2024-03-07,2024-04-06,794,8.1,Algorithmic Solutions +AI10119,Machine Learning Researcher,66740,JPY,7341400,EN,CT,Japan,M,Canada,50,"Tableau, Linux, Kubernetes, PyTorch, Mathematics",Associate,1,Government,2024-04-25,2024-07-03,1062,5,Machine Intelligence Group +AI10120,Machine Learning Engineer,253573,USD,253573,EX,FT,Norway,L,Norway,50,"PyTorch, Python, Java, Tableau, R",Bachelor,17,Government,2024-05-05,2024-06-14,1950,9.2,Cloud AI Solutions +AI10121,Data Engineer,79168,AUD,106877,MI,FL,Australia,S,Australia,100,"Mathematics, Python, R, Git, TensorFlow",PhD,2,Telecommunications,2024-08-05,2024-09-19,993,6.4,Autonomous Tech +AI10122,Data Analyst,139622,EUR,118679,SE,PT,Netherlands,L,Netherlands,50,"Deep Learning, Mathematics, Hadoop, PyTorch",Master,9,Consulting,2025-04-03,2025-06-01,2392,6.5,Cognitive Computing +AI10123,Machine Learning Engineer,43943,USD,43943,SE,FT,India,S,India,50,"SQL, Scala, Python",PhD,9,Telecommunications,2024-04-13,2024-05-31,1723,7.5,TechCorp Inc +AI10124,AI Research Scientist,162422,GBP,121817,EX,FT,United Kingdom,S,United Kingdom,0,"Git, SQL, NLP, Azure, Linux",Master,17,Education,2024-05-16,2024-07-05,1442,5.3,Advanced Robotics +AI10125,ML Ops Engineer,43406,USD,43406,EN,CT,South Korea,S,Mexico,50,"Kubernetes, Java, R, SQL",Bachelor,0,Consulting,2024-09-10,2024-10-02,2472,9.5,Cloud AI Solutions +AI10126,Data Analyst,95920,JPY,10551200,MI,FT,Japan,L,Japan,100,"Python, TensorFlow, Mathematics",Master,2,Transportation,2024-12-02,2025-01-08,2081,9.2,Neural Networks Co +AI10127,AI Consultant,197698,EUR,168043,EX,FT,Germany,S,Germany,100,"GCP, Azure, Python, PyTorch, Java",Master,13,Finance,2024-10-22,2024-12-02,718,5.8,Future Systems +AI10128,AI Specialist,173515,AUD,234245,EX,FT,Australia,L,Nigeria,0,"Python, Scala, AWS, TensorFlow, Linux",Bachelor,16,Finance,2024-02-11,2024-03-27,1432,5.6,AI Innovations +AI10129,AI Specialist,192426,AUD,259775,EX,FL,Australia,L,Philippines,50,"Statistics, Hadoop, SQL",PhD,11,Gaming,2024-04-02,2024-05-30,1928,8.3,Cognitive Computing +AI10130,Research Scientist,212764,USD,212764,SE,CT,Denmark,L,Denmark,50,"Linux, Kubernetes, Data Visualization",Bachelor,8,Technology,2024-09-05,2024-10-01,2235,8.8,Machine Intelligence Group +AI10131,Autonomous Systems Engineer,50136,USD,50136,EN,PT,Finland,M,Finland,0,"AWS, Git, SQL, Azure, Linux",Master,0,Education,2024-10-12,2024-11-30,1646,5.1,Algorithmic Solutions +AI10132,AI Consultant,199327,EUR,169428,EX,FL,Austria,S,Latvia,50,"Python, SQL, Mathematics, Deep Learning",Bachelor,14,Real Estate,2024-04-05,2024-05-26,1617,5.3,AI Innovations +AI10133,AI Architect,104098,CHF,93688,EN,FL,Switzerland,L,Indonesia,100,"Git, Java, Python, TensorFlow, Mathematics",Associate,0,Manufacturing,2024-03-05,2024-04-23,1488,7.5,Quantum Computing Inc +AI10134,Research Scientist,89534,USD,89534,MI,FT,Finland,S,Finland,0,"Kubernetes, Docker, R, Hadoop, PyTorch",PhD,2,Finance,2024-07-07,2024-09-10,2258,8.5,Cloud AI Solutions +AI10135,NLP Engineer,72126,CAD,90158,EN,CT,Canada,L,Canada,0,"Spark, Git, Computer Vision, PyTorch, Kubernetes",PhD,0,Education,2024-09-06,2024-11-11,679,9.5,DataVision Ltd +AI10136,Autonomous Systems Engineer,120139,USD,120139,SE,FL,Sweden,S,Netherlands,100,"Mathematics, Python, Linux, SQL",Master,6,Healthcare,2024-03-05,2024-03-22,1834,8.2,Smart Analytics +AI10137,NLP Engineer,209827,CHF,188844,EX,CT,Switzerland,M,Switzerland,0,"Python, Tableau, Data Visualization, NLP",Master,17,Government,2024-01-31,2024-03-24,1007,5.5,Machine Intelligence Group +AI10138,NLP Engineer,63620,JPY,6998200,EN,FL,Japan,M,Japan,50,"Computer Vision, R, MLOps, SQL, PyTorch",Master,0,Healthcare,2025-04-13,2025-06-21,696,8.1,Autonomous Tech +AI10139,Robotics Engineer,43464,USD,43464,EN,CT,China,L,China,0,"PyTorch, AWS, Hadoop, NLP, Spark",PhD,0,Retail,2025-02-06,2025-04-15,1875,8.6,DeepTech Ventures +AI10140,Machine Learning Researcher,81847,USD,81847,SE,PT,China,L,Czech Republic,0,"MLOps, Data Visualization, AWS, Scala",PhD,9,Technology,2024-05-22,2024-08-01,799,8.2,Neural Networks Co +AI10141,ML Ops Engineer,125011,GBP,93758,SE,CT,United Kingdom,S,Germany,50,"Linux, Azure, Git, Computer Vision, TensorFlow",Master,9,Gaming,2024-09-08,2024-09-25,977,7,Algorithmic Solutions +AI10142,Deep Learning Engineer,253282,CAD,316603,EX,FT,Canada,L,Kenya,0,"Python, Git, TensorFlow, Azure, PyTorch",Associate,18,Finance,2024-10-09,2024-12-10,1585,6.8,DataVision Ltd +AI10143,Data Analyst,163715,USD,163715,EX,FL,Finland,S,Finland,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Media,2025-01-19,2025-02-05,1900,8.5,Advanced Robotics +AI10144,Head of AI,71407,EUR,60696,EN,FL,Germany,S,Indonesia,50,"SQL, Tableau, PyTorch",Master,0,Energy,2024-12-08,2025-02-12,1897,6.3,Quantum Computing Inc +AI10145,Deep Learning Engineer,66634,USD,66634,EN,PT,Ireland,L,Ireland,100,"AWS, Deep Learning, SQL, Azure, PyTorch",Associate,0,Media,2024-02-24,2024-03-23,1775,9.5,Digital Transformation LLC +AI10146,Autonomous Systems Engineer,160350,EUR,136298,EX,PT,Germany,M,Germany,50,"Spark, Kubernetes, MLOps, Python, Computer Vision",Associate,10,Energy,2025-04-20,2025-05-08,681,7.6,AI Innovations +AI10147,Deep Learning Engineer,119141,EUR,101270,SE,FT,Netherlands,M,Chile,50,"Hadoop, Azure, Git, Computer Vision, Scala",PhD,7,Finance,2024-04-04,2024-05-30,923,7.7,AI Innovations +AI10148,Machine Learning Engineer,92580,USD,92580,MI,FL,Israel,L,Israel,100,"GCP, Kubernetes, Computer Vision",Associate,4,Education,2024-07-19,2024-09-18,2309,9.4,Autonomous Tech +AI10149,Data Engineer,145627,AUD,196596,SE,PT,Australia,L,Australia,50,"Scala, Deep Learning, Computer Vision",PhD,5,Government,2024-08-16,2024-10-08,530,5.3,Algorithmic Solutions +AI10150,AI Specialist,213045,EUR,181088,EX,PT,Germany,M,Thailand,50,"Docker, MLOps, Kubernetes",Bachelor,12,Manufacturing,2025-03-18,2025-05-01,1675,7.7,Cognitive Computing +AI10151,Computer Vision Engineer,297403,SGD,386624,EX,FT,Singapore,L,Singapore,50,"Computer Vision, Python, Azure, Data Visualization",Bachelor,14,Finance,2024-05-18,2024-06-13,964,5.2,TechCorp Inc +AI10152,Data Analyst,69197,EUR,58817,MI,FT,France,S,France,0,"TensorFlow, MLOps, Java",Master,3,Gaming,2024-11-24,2024-12-30,2362,7.6,Smart Analytics +AI10153,Data Analyst,132689,USD,132689,SE,FT,Israel,L,Israel,100,"Computer Vision, Spark, Python, Mathematics, MLOps",Bachelor,7,Gaming,2024-04-14,2024-05-01,1072,6,Neural Networks Co +AI10154,Computer Vision Engineer,83336,GBP,62502,MI,FL,United Kingdom,S,Italy,50,"PyTorch, MLOps, SQL, Spark",PhD,2,Real Estate,2024-12-17,2025-01-23,2268,5.4,Predictive Systems +AI10155,AI Consultant,172090,JPY,18929900,SE,FT,Japan,L,Japan,0,"NLP, SQL, TensorFlow, Spark",Associate,5,Media,2024-10-30,2024-11-30,1316,8.8,DeepTech Ventures +AI10156,AI Product Manager,24926,USD,24926,EN,PT,China,M,China,0,"Mathematics, NLP, Data Visualization, Deep Learning, Hadoop",Associate,0,Healthcare,2025-04-13,2025-06-19,853,9.2,Advanced Robotics +AI10157,Data Analyst,211550,EUR,179818,EX,FL,Austria,L,Austria,100,"AWS, Kubernetes, NLP",Bachelor,17,Gaming,2025-01-31,2025-04-07,1102,5.6,Digital Transformation LLC +AI10158,NLP Engineer,104635,USD,104635,SE,PT,Finland,S,Finland,100,"Deep Learning, Scala, Tableau",Master,6,Real Estate,2024-10-17,2024-12-18,623,6.9,Digital Transformation LLC +AI10159,Data Scientist,67458,USD,67458,EN,FT,Finland,S,Finland,50,"Python, Azure, Tableau, Java",Master,1,Government,2024-03-05,2024-04-03,2364,5.5,Predictive Systems +AI10160,Research Scientist,137160,USD,137160,SE,CT,Sweden,L,Sweden,100,"Docker, Tableau, GCP, R",Associate,8,Retail,2024-01-04,2024-03-13,839,7.5,Cloud AI Solutions +AI10161,Head of AI,68285,USD,68285,EN,PT,Norway,S,Norway,50,"Java, Azure, AWS, Statistics, Computer Vision",Bachelor,0,Automotive,2025-03-24,2025-04-15,1170,9.8,Quantum Computing Inc +AI10162,Machine Learning Researcher,74005,CHF,66605,EN,FT,Switzerland,S,Philippines,100,"Hadoop, R, NLP",Associate,0,Manufacturing,2024-03-18,2024-04-09,1639,6.8,Cognitive Computing +AI10163,AI Architect,127491,JPY,14024010,SE,PT,Japan,M,Czech Republic,0,"SQL, Docker, Data Visualization, Mathematics",Associate,5,Real Estate,2024-08-26,2024-09-24,990,7.8,DeepTech Ventures +AI10164,Principal Data Scientist,64002,USD,64002,EX,FL,China,S,China,0,"Python, GCP, Data Visualization, MLOps",Master,14,Real Estate,2024-04-29,2024-05-31,1479,9.6,Advanced Robotics +AI10165,Data Analyst,87641,USD,87641,MI,FT,South Korea,L,South Korea,100,"SQL, NLP, Statistics, GCP, Java",PhD,4,Media,2024-03-28,2024-06-03,2285,8.9,DataVision Ltd +AI10166,Autonomous Systems Engineer,54064,JPY,5947040,EN,PT,Japan,S,Poland,0,"PyTorch, Docker, R, Deep Learning, Java",Master,0,Retail,2025-01-02,2025-03-06,1094,6.7,Machine Intelligence Group +AI10167,Research Scientist,92164,USD,92164,MI,CT,Denmark,S,Denmark,100,"Azure, NLP, Python, Statistics, Scala",PhD,4,Real Estate,2024-03-28,2024-06-01,2147,9.1,Autonomous Tech +AI10168,AI Product Manager,303272,USD,303272,EX,FT,Norway,L,Norway,0,"SQL, Spark, Tableau, PyTorch, Hadoop",PhD,11,Real Estate,2025-04-02,2025-04-20,1007,8.3,Cognitive Computing +AI10169,Data Analyst,125114,USD,125114,EX,FT,Sweden,S,Sweden,50,"Kubernetes, Git, Deep Learning, Computer Vision, Scala",Bachelor,12,Technology,2024-08-12,2024-09-08,2065,9.5,AI Innovations +AI10170,Deep Learning Engineer,54317,USD,54317,EN,CT,Ireland,M,Egypt,50,"Deep Learning, Spark, TensorFlow, PyTorch, Azure",Bachelor,1,Education,2025-03-20,2025-05-11,1082,6.1,DataVision Ltd +AI10171,Principal Data Scientist,75401,GBP,56551,MI,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, Data Visualization, Java",Bachelor,4,Healthcare,2024-08-02,2024-09-25,1106,8.8,DeepTech Ventures +AI10172,ML Ops Engineer,125780,USD,125780,SE,FL,Ireland,L,Ireland,0,"TensorFlow, Python, Computer Vision, SQL, Scala",Master,5,Real Estate,2024-08-25,2024-09-09,1249,8.9,Quantum Computing Inc +AI10173,Machine Learning Researcher,92433,USD,92433,EN,PT,Denmark,M,Denmark,0,"Python, TensorFlow, Azure, Computer Vision",Associate,0,Finance,2025-03-31,2025-05-24,2132,5.2,Cloud AI Solutions +AI10174,AI Specialist,64856,GBP,48642,EN,CT,United Kingdom,L,Ukraine,50,"Java, R, Tableau",PhD,1,Gaming,2024-07-14,2024-08-09,1592,6.5,TechCorp Inc +AI10175,Autonomous Systems Engineer,403493,CHF,363144,EX,FL,Switzerland,L,Switzerland,100,"Git, SQL, Spark, PyTorch",PhD,14,Gaming,2025-03-15,2025-05-05,1045,5.5,Cognitive Computing +AI10176,NLP Engineer,68862,USD,68862,EX,CT,India,L,India,100,"PyTorch, SQL, Tableau",PhD,17,Manufacturing,2024-10-20,2024-11-11,988,5.2,Machine Intelligence Group +AI10177,AI Consultant,210010,GBP,157508,EX,CT,United Kingdom,S,United Kingdom,0,"Spark, GCP, Linux",Bachelor,18,Media,2025-04-16,2025-06-14,1217,7.5,Neural Networks Co +AI10178,Machine Learning Researcher,123778,AUD,167100,SE,FT,Australia,L,Turkey,0,"Linux, Python, Tableau, Mathematics",Bachelor,5,Healthcare,2024-03-26,2024-06-04,1700,10,Cognitive Computing +AI10179,Machine Learning Researcher,70793,SGD,92031,MI,FT,Singapore,S,Singapore,100,"R, SQL, Azure",Associate,2,Gaming,2025-02-04,2025-03-15,739,8,DataVision Ltd +AI10180,Autonomous Systems Engineer,135779,EUR,115412,EX,PT,Germany,S,Indonesia,50,"Deep Learning, Git, Spark, GCP, Azure",Master,18,Telecommunications,2024-05-03,2024-07-09,1937,5.3,AI Innovations +AI10181,AI Specialist,70351,USD,70351,MI,CT,Finland,S,Finland,100,"SQL, NLP, TensorFlow",Master,4,Healthcare,2024-03-07,2024-03-25,1223,7.8,AI Innovations +AI10182,AI Architect,168478,CHF,151630,MI,FL,Switzerland,L,Switzerland,50,"Git, Kubernetes, PyTorch, R, SQL",Master,2,Education,2024-06-03,2024-08-06,1027,8,DeepTech Ventures +AI10183,Robotics Engineer,132893,USD,132893,EX,FT,Israel,S,Israel,0,"Computer Vision, Python, TensorFlow, Mathematics, Linux",Bachelor,17,Real Estate,2024-11-17,2024-12-02,2289,9.3,Future Systems +AI10184,Data Engineer,277707,GBP,208280,EX,FT,United Kingdom,L,United Kingdom,50,"Git, R, Statistics, Data Visualization",Associate,13,Retail,2024-12-21,2025-01-09,1010,7.9,DataVision Ltd +AI10185,NLP Engineer,131380,USD,131380,MI,FT,United States,L,United States,100,"PyTorch, TensorFlow, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-02-17,2024-04-04,604,10,TechCorp Inc +AI10186,AI Specialist,104109,USD,104109,SE,FT,South Korea,S,Brazil,100,"Deep Learning, AWS, Kubernetes, SQL, PyTorch",Associate,7,Real Estate,2024-04-29,2024-07-08,1705,6.8,Cloud AI Solutions +AI10187,Autonomous Systems Engineer,144897,EUR,123162,SE,PT,Netherlands,L,Netherlands,100,"Spark, Computer Vision, Hadoop",Associate,7,Manufacturing,2024-10-07,2024-11-07,1202,5.7,DataVision Ltd +AI10188,Machine Learning Engineer,234506,SGD,304858,EX,FL,Singapore,S,Singapore,100,"Python, Kubernetes, Spark, Mathematics",Associate,12,Education,2024-12-28,2025-03-08,1410,6.5,Future Systems +AI10189,NLP Engineer,138684,USD,138684,MI,PT,Denmark,M,Denmark,50,"Python, Tableau, Azure, PyTorch",Master,4,Manufacturing,2024-07-25,2024-08-28,1314,7.5,Cloud AI Solutions +AI10190,Machine Learning Engineer,91626,USD,91626,MI,FL,Ireland,S,Ireland,0,"Data Visualization, Deep Learning, MLOps, Spark",Associate,3,Government,2024-06-30,2024-08-10,1506,6.3,Smart Analytics +AI10191,AI Consultant,227796,USD,227796,EX,FT,United States,S,Germany,100,"R, Hadoop, Docker",Master,11,Finance,2024-10-07,2024-10-22,728,6.8,Quantum Computing Inc +AI10192,Machine Learning Engineer,237622,EUR,201979,EX,FT,Germany,M,Germany,100,"TensorFlow, Python, Scala",Associate,11,Technology,2024-06-30,2024-07-27,788,9.8,Digital Transformation LLC +AI10193,Autonomous Systems Engineer,59553,JPY,6550830,EN,CT,Japan,M,Japan,100,"SQL, GCP, PyTorch, Java",Associate,1,Government,2024-11-02,2024-11-25,2408,5.6,Machine Intelligence Group +AI10194,Data Engineer,75248,EUR,63961,MI,FT,Austria,S,Austria,50,"Spark, TensorFlow, Linux",Bachelor,4,Finance,2024-02-08,2024-04-17,1561,6.8,Cloud AI Solutions +AI10195,AI Product Manager,44563,USD,44563,SE,FT,India,M,Hungary,0,"Java, Linux, Python, Spark",Master,5,Automotive,2024-12-17,2025-02-25,1663,7.9,Quantum Computing Inc +AI10196,AI Consultant,186290,CHF,167661,SE,CT,Switzerland,M,Switzerland,0,"Tableau, Kubernetes, Git",Master,8,Real Estate,2025-04-30,2025-05-31,1747,5.6,DataVision Ltd +AI10197,AI Consultant,130662,EUR,111063,EX,CT,France,S,France,100,"Python, Azure, Tableau, Linux",Master,13,Technology,2024-09-06,2024-10-29,2453,6.7,DeepTech Ventures +AI10198,Principal Data Scientist,202772,USD,202772,EX,CT,Ireland,S,Ireland,100,"Computer Vision, Docker, Statistics",Associate,11,Telecommunications,2025-02-06,2025-04-08,514,5.3,Digital Transformation LLC +AI10199,AI Product Manager,190276,USD,190276,EX,CT,Sweden,L,Sweden,50,"Kubernetes, Docker, Python",Master,18,Gaming,2025-04-02,2025-04-25,1339,5.8,Smart Analytics +AI10200,AI Architect,99498,EUR,84573,SE,CT,Netherlands,S,Switzerland,100,"Mathematics, Tableau, R, Java",Associate,6,Automotive,2024-04-03,2024-04-23,1999,9.7,Cognitive Computing +AI10201,AI Product Manager,190361,AUD,256987,EX,FT,Australia,M,Australia,0,"GCP, Deep Learning, Python, Linux",Master,15,Gaming,2024-12-24,2025-02-04,1361,7.6,Autonomous Tech +AI10202,Head of AI,62384,USD,62384,EN,FT,United States,M,United States,0,"Git, Azure, Deep Learning",Master,1,Energy,2024-09-14,2024-11-17,541,8,Smart Analytics +AI10203,AI Research Scientist,139626,USD,139626,SE,FT,Norway,M,Norway,100,"Scala, Python, NLP, Docker, AWS",Associate,8,Media,2024-12-04,2025-01-11,1764,8.7,AI Innovations +AI10204,AI Software Engineer,76788,USD,76788,EX,FL,India,S,India,50,"NLP, Kubernetes, GCP, Python, Java",Master,17,Manufacturing,2024-08-19,2024-09-07,2043,6.8,TechCorp Inc +AI10205,Robotics Engineer,177449,USD,177449,SE,CT,Norway,L,Norway,0,"Docker, Statistics, Python, Tableau",Bachelor,8,Healthcare,2024-06-08,2024-07-10,2020,8.5,AI Innovations +AI10206,Data Analyst,61915,USD,61915,EN,FL,Finland,L,Finland,0,"Mathematics, R, NLP",PhD,0,Energy,2025-02-24,2025-04-05,2439,7.3,Machine Intelligence Group +AI10207,Research Scientist,59769,SGD,77700,EN,CT,Singapore,S,Singapore,0,"R, AWS, Linux",Bachelor,0,Transportation,2024-09-05,2024-09-26,796,8.3,Cognitive Computing +AI10208,Autonomous Systems Engineer,102469,CHF,92222,MI,CT,Switzerland,M,Germany,0,"PyTorch, Kubernetes, Docker, SQL",PhD,2,Transportation,2024-10-17,2024-11-14,1833,6.8,TechCorp Inc +AI10209,Autonomous Systems Engineer,144818,USD,144818,MI,CT,Denmark,L,Denmark,0,"R, Hadoop, Scala, PyTorch",PhD,2,Technology,2024-09-03,2024-10-10,812,6.3,Digital Transformation LLC +AI10210,Principal Data Scientist,151885,CAD,189856,SE,PT,Canada,L,Canada,50,"Docker, Tableau, Data Visualization",Associate,7,Media,2025-03-27,2025-05-17,1140,9.6,Smart Analytics +AI10211,AI Consultant,76782,USD,76782,EN,PT,United States,L,United States,0,"GCP, Mathematics, AWS",PhD,1,Education,2024-04-03,2024-04-25,1697,5.3,Algorithmic Solutions +AI10212,Head of AI,76167,USD,76167,MI,CT,Sweden,M,Sweden,0,"Spark, Scala, SQL",Bachelor,3,Government,2024-08-09,2024-10-19,1139,7.8,Quantum Computing Inc +AI10213,Research Scientist,109222,SGD,141989,MI,PT,Singapore,M,Singapore,0,"Python, TensorFlow, Java",PhD,3,Automotive,2024-09-26,2024-11-13,1852,8.3,Algorithmic Solutions +AI10214,Robotics Engineer,112535,CAD,140669,SE,FT,Canada,L,Vietnam,50,"Kubernetes, GCP, Data Visualization, SQL",PhD,7,Transportation,2025-03-16,2025-05-24,1174,8.7,Quantum Computing Inc +AI10215,Principal Data Scientist,283415,USD,283415,EX,FT,Sweden,L,Japan,50,"Computer Vision, Statistics, Docker",PhD,19,Automotive,2024-10-10,2024-12-22,1359,5.2,Algorithmic Solutions +AI10216,Data Scientist,75965,EUR,64570,MI,FT,Germany,M,Germany,50,"AWS, Linux, Hadoop, R, MLOps",PhD,4,Government,2024-10-16,2024-11-12,2301,8.4,Machine Intelligence Group +AI10217,NLP Engineer,91675,EUR,77924,MI,FL,Austria,M,Austria,0,"TensorFlow, AWS, Statistics",Bachelor,4,Consulting,2024-12-24,2025-02-16,515,8.9,Quantum Computing Inc +AI10218,Data Scientist,142668,CAD,178335,EX,PT,Canada,S,Canada,0,"Python, Java, Git, Spark, Azure",Associate,15,Consulting,2024-11-03,2024-11-27,2152,6.1,AI Innovations +AI10219,AI Specialist,65229,CAD,81536,EN,FL,Canada,S,Russia,100,"Python, Kubernetes, TensorFlow, Hadoop",Associate,1,Media,2024-01-02,2024-02-16,1513,7.5,Machine Intelligence Group +AI10220,Machine Learning Engineer,80835,CAD,101044,MI,FL,Canada,S,Singapore,100,"Data Visualization, Scala, Kubernetes, Deep Learning, GCP",PhD,2,Healthcare,2024-11-28,2025-01-01,1934,5.8,Autonomous Tech +AI10221,Deep Learning Engineer,250293,SGD,325381,EX,FL,Singapore,M,Singapore,100,"Kubernetes, Java, SQL, PyTorch, Azure",Associate,13,Finance,2024-03-10,2024-04-25,2222,7.5,Algorithmic Solutions +AI10222,AI Architect,162995,CHF,146696,MI,FT,Switzerland,L,Switzerland,0,"Git, Java, Spark, Python, GCP",Master,2,Retail,2025-01-07,2025-02-23,2411,9.5,DataVision Ltd +AI10223,AI Consultant,247822,USD,247822,EX,FL,Norway,M,Norway,100,"Git, Tableau, Deep Learning, Docker",Bachelor,19,Gaming,2024-02-26,2024-04-14,573,8.5,Cloud AI Solutions +AI10224,Machine Learning Engineer,168577,AUD,227579,SE,FL,Australia,L,Indonesia,100,"Hadoop, Kubernetes, Scala, Azure",Bachelor,6,Transportation,2024-06-01,2024-06-22,1731,6.2,Cognitive Computing +AI10225,Deep Learning Engineer,86183,USD,86183,EN,PT,Ireland,L,Ireland,100,"Data Visualization, Linux, PyTorch, TensorFlow",Associate,1,Government,2024-03-24,2024-04-13,929,6.4,Machine Intelligence Group +AI10226,AI Product Manager,95435,USD,95435,EN,FT,Norway,M,Ukraine,50,"SQL, Tableau, AWS, Java, R",PhD,0,Government,2024-09-16,2024-10-25,882,9.1,Advanced Robotics +AI10227,Robotics Engineer,86159,JPY,9477490,MI,FL,Japan,S,Japan,50,"GCP, NLP, PyTorch, Python",Bachelor,4,Education,2024-03-31,2024-05-05,1672,5.1,Advanced Robotics +AI10228,Deep Learning Engineer,30009,USD,30009,EN,CT,China,L,China,100,"Java, Linux, NLP, Git, Spark",Bachelor,0,Retail,2025-01-06,2025-02-09,1576,9.5,Advanced Robotics +AI10229,Robotics Engineer,65632,USD,65632,EN,PT,Finland,S,Finland,100,"Git, Python, SQL, GCP",Bachelor,1,Government,2025-03-24,2025-06-04,911,5.5,Cloud AI Solutions +AI10230,Data Engineer,161846,USD,161846,SE,PT,Israel,L,Israel,50,"GCP, Spark, Linux",PhD,6,Healthcare,2024-11-20,2024-12-15,2142,6.7,Quantum Computing Inc +AI10231,AI Research Scientist,67413,EUR,57301,EN,CT,Netherlands,S,Netherlands,0,"Azure, SQL, Data Visualization",PhD,1,Automotive,2024-06-26,2024-08-10,624,5.2,Digital Transformation LLC +AI10232,AI Architect,95990,USD,95990,SE,FL,Finland,S,Finland,0,"Tableau, TensorFlow, Kubernetes, SQL, GCP",PhD,9,Consulting,2024-02-15,2024-04-20,1850,9.3,TechCorp Inc +AI10233,Research Scientist,80350,CAD,100438,MI,CT,Canada,S,Canada,100,"NLP, SQL, PyTorch, Deep Learning, MLOps",Associate,4,Gaming,2024-10-15,2024-12-27,2154,6.5,Advanced Robotics +AI10234,Robotics Engineer,135564,USD,135564,EX,PT,China,L,China,50,"PyTorch, Kubernetes, TensorFlow, Linux",Master,16,Healthcare,2024-12-06,2025-02-01,586,8.8,Smart Analytics +AI10235,AI Software Engineer,218274,JPY,24010140,EX,PT,Japan,L,Japan,0,"GCP, Spark, Data Visualization",Bachelor,12,Healthcare,2024-12-04,2025-01-27,1162,5.3,Cognitive Computing +AI10236,NLP Engineer,79956,USD,79956,MI,FT,Israel,L,Israel,50,"SQL, Statistics, AWS, Docker",Associate,3,Manufacturing,2024-05-16,2024-07-06,2101,5.8,DeepTech Ventures +AI10237,AI Product Manager,210360,USD,210360,EX,PT,Ireland,L,Hungary,50,"Python, Computer Vision, Mathematics",Master,11,Government,2024-10-08,2024-12-06,1305,7.1,DeepTech Ventures +AI10238,AI Software Engineer,203510,USD,203510,EX,PT,Finland,M,France,50,"Python, Hadoop, Linux",Associate,14,Finance,2024-06-29,2024-08-26,1073,7.3,TechCorp Inc +AI10239,Principal Data Scientist,54946,USD,54946,MI,FL,China,L,Norway,0,"Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,2,Energy,2024-04-27,2024-06-21,761,6.2,TechCorp Inc +AI10240,Deep Learning Engineer,301525,USD,301525,EX,FT,Norway,M,Norway,0,"Tableau, Kubernetes, Linux, AWS",PhD,15,Media,2024-10-16,2024-12-26,1359,9,TechCorp Inc +AI10241,Data Engineer,54730,AUD,73886,EN,CT,Australia,M,Australia,50,"Scala, Kubernetes, Deep Learning, GCP, SQL",Bachelor,0,Automotive,2024-09-07,2024-10-31,641,6.1,TechCorp Inc +AI10242,Data Engineer,70076,USD,70076,MI,CT,South Korea,M,South Korea,0,"Git, Hadoop, GCP",Bachelor,3,Transportation,2024-03-25,2024-05-26,1249,7,Predictive Systems +AI10243,Robotics Engineer,140236,USD,140236,EX,FL,South Korea,M,South Korea,0,"Spark, R, Java, Data Visualization, Tableau",Associate,14,Energy,2025-04-14,2025-06-15,1958,9.3,Machine Intelligence Group +AI10244,AI Consultant,76319,CHF,68687,EN,CT,Switzerland,S,South Africa,0,"Spark, Git, SQL",Associate,1,Gaming,2024-02-18,2024-03-10,1721,7.5,Quantum Computing Inc +AI10245,Principal Data Scientist,117897,USD,117897,EN,PT,Denmark,L,Philippines,0,"Spark, Tableau, Java",Bachelor,1,Retail,2024-12-02,2025-01-09,1874,6,AI Innovations +AI10246,Principal Data Scientist,67144,USD,67144,EX,FT,India,M,India,0,"Git, Python, NLP, Deep Learning, R",Associate,18,Finance,2024-02-13,2024-02-27,849,5.1,Predictive Systems +AI10247,Computer Vision Engineer,77616,EUR,65974,EN,CT,France,L,France,50,"AWS, Computer Vision, Data Visualization, MLOps, Statistics",Bachelor,0,Government,2024-04-04,2024-06-02,1095,6.9,Machine Intelligence Group +AI10248,Research Scientist,141826,USD,141826,MI,CT,Norway,L,Norway,0,"Python, Kubernetes, SQL, Linux, Hadoop",Associate,3,Real Estate,2024-11-12,2025-01-11,2171,5.3,DeepTech Ventures +AI10249,Data Engineer,73463,JPY,8080930,EN,FT,Japan,S,Japan,100,"Python, Git, NLP, GCP, Hadoop",Bachelor,1,Manufacturing,2024-07-11,2024-08-05,1343,6.1,Machine Intelligence Group +AI10250,AI Research Scientist,109715,USD,109715,MI,CT,Denmark,M,Denmark,0,"Docker, SQL, PyTorch, Spark",Bachelor,4,Finance,2024-02-05,2024-03-04,2237,7,DeepTech Ventures +AI10251,Robotics Engineer,69994,EUR,59495,MI,FT,Austria,M,Austria,0,"Statistics, Azure, Python",Bachelor,2,Manufacturing,2025-04-15,2025-05-07,1393,5.8,Predictive Systems +AI10252,NLP Engineer,117074,CHF,105367,MI,CT,Switzerland,S,Colombia,100,"GCP, Azure, NLP, TensorFlow",Master,4,Manufacturing,2025-02-13,2025-03-17,1001,6.5,DataVision Ltd +AI10253,Computer Vision Engineer,105296,GBP,78972,MI,FL,United Kingdom,S,United Kingdom,100,"Scala, Computer Vision, GCP, NLP, Git",Associate,3,Gaming,2024-05-09,2024-07-20,1754,8.6,DeepTech Ventures +AI10254,Head of AI,165753,CHF,149178,SE,FL,Switzerland,S,Netherlands,50,"Deep Learning, Hadoop, Java",Associate,9,Real Estate,2024-07-11,2024-08-17,1737,9.4,Cloud AI Solutions +AI10255,Deep Learning Engineer,136546,SGD,177510,SE,CT,Singapore,L,Japan,50,"SQL, R, NLP",Associate,5,Finance,2024-10-14,2024-11-05,1371,6.2,Cloud AI Solutions +AI10256,ML Ops Engineer,61219,USD,61219,EN,CT,Israel,M,Indonesia,0,"Kubernetes, MLOps, Scala",Master,0,Consulting,2025-01-01,2025-03-09,1568,8.3,DeepTech Ventures +AI10257,Head of AI,86631,EUR,73636,MI,FT,Austria,M,Austria,0,"Docker, SQL, Mathematics",PhD,2,Manufacturing,2024-01-20,2024-03-17,1632,7,Autonomous Tech +AI10258,AI Consultant,226414,USD,226414,EX,PT,Ireland,M,Ireland,100,"NLP, Azure, Deep Learning",Associate,13,Education,2024-07-26,2024-09-18,666,9.4,Neural Networks Co +AI10259,AI Research Scientist,113616,EUR,96574,SE,FT,Netherlands,S,Netherlands,50,"Scala, Hadoop, Computer Vision, Deep Learning",Master,7,Retail,2025-04-09,2025-06-14,1885,6,Smart Analytics +AI10260,Principal Data Scientist,191958,USD,191958,SE,FL,Norway,L,Norway,0,"Mathematics, Computer Vision, Kubernetes",Bachelor,6,Healthcare,2025-04-12,2025-05-03,1954,8.1,AI Innovations +AI10261,AI Research Scientist,50163,CAD,62704,EN,CT,Canada,S,Brazil,50,"Git, PyTorch, TensorFlow",PhD,1,Telecommunications,2025-03-03,2025-03-27,2229,8.6,TechCorp Inc +AI10262,Robotics Engineer,337422,USD,337422,EX,FL,United States,L,Sweden,100,"Linux, NLP, TensorFlow, Docker, Mathematics",PhD,12,Government,2024-04-21,2024-05-20,1783,9.7,Cognitive Computing +AI10263,AI Architect,67566,USD,67566,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Data Visualization, Git",Associate,1,Telecommunications,2024-10-21,2025-01-01,1563,6.5,Cloud AI Solutions +AI10264,AI Specialist,59923,EUR,50935,EN,FL,Netherlands,M,Australia,100,"Docker, Python, Deep Learning, SQL, Statistics",Bachelor,0,Education,2025-03-06,2025-04-26,2410,5.9,DataVision Ltd +AI10265,Data Engineer,238139,EUR,202418,EX,CT,France,M,France,50,"Deep Learning, Hadoop, Python, Docker, Git",Associate,12,Education,2024-01-19,2024-02-27,786,9.9,Advanced Robotics +AI10266,Research Scientist,231140,USD,231140,EX,PT,Israel,L,Israel,100,"SQL, PyTorch, R, Spark",Bachelor,16,Transportation,2024-02-02,2024-04-12,1351,6.2,Neural Networks Co +AI10267,Principal Data Scientist,124660,JPY,13712600,SE,PT,Japan,M,Japan,0,"Scala, Azure, Linux",Bachelor,7,Retail,2024-02-22,2024-05-02,1365,6.9,Cloud AI Solutions +AI10268,AI Product Manager,147934,USD,147934,SE,FL,Sweden,L,Finland,50,"R, SQL, PyTorch, Hadoop, Mathematics",Associate,5,Retail,2024-05-04,2024-07-15,2042,8.7,Digital Transformation LLC +AI10269,NLP Engineer,154109,USD,154109,SE,PT,Sweden,L,Argentina,0,"Python, Kubernetes, MLOps, NLP, TensorFlow",Bachelor,5,Technology,2024-06-14,2024-08-06,652,9.6,Machine Intelligence Group +AI10270,Head of AI,182664,SGD,237463,SE,PT,Singapore,L,Singapore,100,"SQL, PyTorch, NLP, TensorFlow, Statistics",Associate,8,Education,2024-08-08,2024-10-05,1732,5.8,AI Innovations +AI10271,AI Research Scientist,106779,GBP,80084,MI,PT,United Kingdom,L,Thailand,0,"Mathematics, SQL, Git",Associate,2,Retail,2024-03-22,2024-05-25,2379,7.7,TechCorp Inc +AI10272,Principal Data Scientist,76695,SGD,99704,EN,PT,Singapore,S,Indonesia,0,"Data Visualization, TensorFlow, MLOps",Bachelor,0,Manufacturing,2024-08-27,2024-10-30,1852,6.8,Machine Intelligence Group +AI10273,Deep Learning Engineer,33529,USD,33529,EN,CT,China,M,China,50,"Kubernetes, Deep Learning, GCP",PhD,1,Consulting,2024-10-11,2024-11-07,1608,7.6,Advanced Robotics +AI10274,Machine Learning Researcher,92400,EUR,78540,EN,CT,Germany,L,Germany,100,"Linux, Mathematics, Hadoop, Spark, Java",Associate,0,Government,2024-05-15,2024-07-12,1559,8.9,Cognitive Computing +AI10275,Autonomous Systems Engineer,222418,USD,222418,EX,FT,United States,M,United States,100,"Azure, Kubernetes, Deep Learning",Bachelor,17,Media,2025-03-01,2025-04-25,1951,9.3,Quantum Computing Inc +AI10276,AI Product Manager,86393,EUR,73434,EN,CT,Netherlands,L,Ukraine,50,"TensorFlow, Azure, Computer Vision",Associate,1,Automotive,2025-01-02,2025-02-15,1735,5.6,Quantum Computing Inc +AI10277,AI Software Engineer,122637,USD,122637,SE,PT,Norway,S,Norway,100,"NLP, Scala, R, Azure",PhD,8,Automotive,2024-04-15,2024-05-14,1246,9,Algorithmic Solutions +AI10278,ML Ops Engineer,190440,AUD,257094,EX,PT,Australia,L,Brazil,100,"Azure, TensorFlow, Data Visualization",Associate,16,Manufacturing,2024-12-26,2025-03-01,1381,6.6,Neural Networks Co +AI10279,Machine Learning Researcher,72783,CHF,65505,EN,FL,Switzerland,S,Switzerland,50,"AWS, SQL, Hadoop",Bachelor,1,Telecommunications,2024-06-17,2024-07-14,2348,9.5,Predictive Systems +AI10280,AI Software Engineer,191481,EUR,162759,EX,FL,Germany,S,Germany,0,"Docker, Python, Data Visualization",Master,10,Healthcare,2024-05-31,2024-07-08,1695,5.6,Predictive Systems +AI10281,AI Software Engineer,119141,USD,119141,MI,FL,Denmark,S,Denmark,50,"Scala, Python, Deep Learning, Azure, Linux",Bachelor,2,Manufacturing,2024-04-25,2024-06-14,1185,8.7,Neural Networks Co +AI10282,Autonomous Systems Engineer,61294,SGD,79682,EN,FT,Singapore,M,Czech Republic,0,"Docker, Spark, R, Linux",Bachelor,1,Energy,2024-04-16,2024-06-17,1547,8.3,Predictive Systems +AI10283,Machine Learning Researcher,112748,EUR,95836,SE,FT,Austria,L,South Africa,50,"Scala, Python, MLOps",PhD,9,Consulting,2024-01-05,2024-02-24,1639,6.8,Smart Analytics +AI10284,AI Specialist,69817,CAD,87271,MI,FL,Canada,M,Philippines,0,"Git, Statistics, Mathematics, Spark, Azure",Bachelor,2,Technology,2024-04-15,2024-06-11,1463,9.8,Quantum Computing Inc +AI10285,Data Engineer,162528,CAD,203160,EX,PT,Canada,S,Canada,0,"Git, Hadoop, TensorFlow, Scala",Bachelor,16,Energy,2024-09-24,2024-11-22,1815,9.5,Autonomous Tech +AI10286,Principal Data Scientist,80432,USD,80432,EN,PT,Denmark,L,Denmark,0,"Kubernetes, AWS, Java",PhD,1,Telecommunications,2024-11-13,2024-12-01,2443,6.2,DeepTech Ventures +AI10287,Robotics Engineer,263161,CHF,236845,EX,CT,Switzerland,L,Switzerland,0,"Kubernetes, Python, Computer Vision, TensorFlow",Bachelor,15,Government,2025-01-04,2025-02-06,1699,6.4,Predictive Systems +AI10288,AI Research Scientist,70408,CAD,88010,EN,CT,Canada,L,Canada,100,"PyTorch, Computer Vision, Statistics",PhD,0,Gaming,2024-03-29,2024-05-25,643,9.9,AI Innovations +AI10289,Machine Learning Researcher,84533,EUR,71853,MI,FL,France,S,Latvia,100,"Scala, Linux, Kubernetes",Associate,3,Automotive,2024-04-10,2024-04-28,2027,6.5,Quantum Computing Inc +AI10290,Machine Learning Researcher,94145,USD,94145,MI,CT,South Korea,L,South Korea,0,"Java, GCP, R",PhD,4,Energy,2024-04-20,2024-05-26,1087,7.6,Autonomous Tech +AI10291,Research Scientist,52193,USD,52193,EN,PT,Finland,M,Finland,100,"Azure, Spark, Git",Bachelor,0,Telecommunications,2024-12-31,2025-03-12,2340,8.1,Predictive Systems +AI10292,AI Consultant,153253,USD,153253,EX,CT,Ireland,M,Ireland,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,10,Media,2024-01-18,2024-03-30,1495,9.8,Smart Analytics +AI10293,Machine Learning Engineer,87192,USD,87192,MI,CT,Israel,L,Australia,100,"Computer Vision, R, Tableau, Data Visualization",Bachelor,4,Retail,2024-08-20,2024-10-04,1220,9.7,DeepTech Ventures +AI10294,AI Specialist,214211,CHF,192790,EX,PT,Switzerland,S,Turkey,100,"Java, AWS, Statistics, Hadoop",PhD,19,Gaming,2024-01-10,2024-02-05,746,5.5,Algorithmic Solutions +AI10295,AI Product Manager,203264,JPY,22359040,EX,CT,Japan,M,Poland,50,"SQL, Hadoop, Git, Linux",Bachelor,16,Finance,2025-01-19,2025-03-14,1961,5.2,Predictive Systems +AI10296,Autonomous Systems Engineer,172259,JPY,18948490,EX,PT,Japan,M,Russia,100,"Deep Learning, MLOps, Python, Tableau, Scala",Associate,16,Gaming,2024-02-03,2024-03-02,1017,7.4,Algorithmic Solutions +AI10297,Research Scientist,109363,SGD,142172,SE,CT,Singapore,S,Singapore,100,"Deep Learning, Java, Python",Associate,6,Energy,2024-11-02,2024-12-08,1270,7.9,Predictive Systems +AI10298,AI Software Engineer,50885,USD,50885,EX,FL,India,S,India,100,"AWS, Python, Git, Statistics, TensorFlow",Bachelor,17,Government,2025-04-08,2025-05-19,1119,9.6,Algorithmic Solutions +AI10299,ML Ops Engineer,108450,USD,108450,MI,FL,Norway,L,Norway,100,"Linux, PyTorch, TensorFlow, Docker, Mathematics",Associate,2,Media,2025-04-24,2025-07-04,1495,7,Digital Transformation LLC +AI10300,AI Specialist,57880,USD,57880,MI,FL,China,L,China,100,"Python, Spark, Tableau, Scala, Mathematics",Master,3,Transportation,2024-05-27,2024-07-02,2363,9.2,Neural Networks Co +AI10301,AI Software Engineer,113212,USD,113212,SE,FT,South Korea,S,South Korea,100,"GCP, Spark, NLP, TensorFlow, MLOps",PhD,7,Consulting,2024-01-04,2024-02-11,1158,8.9,Advanced Robotics +AI10302,AI Architect,161719,USD,161719,SE,PT,Norway,L,Norway,0,"R, Git, Kubernetes",Associate,8,Finance,2024-05-18,2024-07-18,653,7.1,Digital Transformation LLC +AI10303,Data Engineer,71629,USD,71629,EN,PT,South Korea,L,China,0,"Tableau, GCP, Linux",Bachelor,1,Telecommunications,2024-09-26,2024-11-24,1646,5.5,Smart Analytics +AI10304,Deep Learning Engineer,257527,USD,257527,EX,FL,Ireland,L,Ireland,50,"Linux, Deep Learning, MLOps, PyTorch",Master,10,Technology,2024-03-26,2024-05-21,1258,9.4,Cognitive Computing +AI10305,Computer Vision Engineer,174720,USD,174720,EX,FT,United States,M,Ireland,0,"Kubernetes, Spark, Computer Vision, TensorFlow, Scala",Associate,15,Finance,2024-03-19,2024-04-13,722,6.4,AI Innovations +AI10306,AI Software Engineer,163238,USD,163238,SE,FL,Ireland,L,Ireland,50,"Python, AWS, Scala",Master,7,Healthcare,2024-12-14,2025-01-11,1790,9.2,Algorithmic Solutions +AI10307,AI Consultant,212985,EUR,181037,EX,PT,Netherlands,M,Netherlands,50,"Spark, Deep Learning, Data Visualization",PhD,10,Energy,2024-07-06,2024-07-23,1464,8.8,Predictive Systems +AI10308,AI Specialist,115588,AUD,156044,SE,PT,Australia,S,Australia,0,"PyTorch, Mathematics, NLP, Kubernetes",PhD,8,Education,2025-03-03,2025-03-25,581,7.5,DeepTech Ventures +AI10309,AI Architect,76351,USD,76351,EN,FL,Ireland,L,Ireland,50,"SQL, Python, Tableau, Scala, Statistics",PhD,1,Gaming,2024-06-13,2024-08-05,1297,7.4,Machine Intelligence Group +AI10310,Robotics Engineer,127693,CAD,159616,EX,FL,Canada,S,Canada,100,"Python, TensorFlow, Mathematics, Azure, PyTorch",Associate,16,Gaming,2025-03-14,2025-03-31,1790,7.1,TechCorp Inc +AI10311,Autonomous Systems Engineer,199789,USD,199789,EX,CT,Sweden,L,Chile,50,"Linux, Java, R",Master,10,Government,2024-12-17,2025-01-16,2344,7.5,Neural Networks Co +AI10312,AI Specialist,60987,USD,60987,EN,PT,Ireland,M,Mexico,100,"Deep Learning, Data Visualization, Scala, AWS, Linux",PhD,1,Consulting,2024-07-17,2024-08-05,2185,9.7,Autonomous Tech +AI10313,AI Product Manager,86536,USD,86536,MI,CT,Finland,M,Finland,0,"Scala, R, AWS",Associate,4,Telecommunications,2024-01-06,2024-01-27,1328,9.6,Predictive Systems +AI10314,Data Analyst,96169,EUR,81744,MI,CT,Austria,L,Austria,100,"Scala, Hadoop, Docker, Deep Learning",Bachelor,3,Government,2024-03-16,2024-05-04,1754,8.9,DataVision Ltd +AI10315,Autonomous Systems Engineer,192529,CAD,240661,EX,FT,Canada,M,Canada,50,"AWS, Kubernetes, R, Computer Vision, Statistics",PhD,16,Automotive,2024-01-15,2024-02-16,1373,6.7,DeepTech Ventures +AI10316,Data Analyst,100410,USD,100410,EX,CT,India,L,India,50,"MLOps, Data Visualization, Mathematics, Azure, Java",PhD,19,Manufacturing,2024-11-18,2025-01-04,1798,9.5,Quantum Computing Inc +AI10317,Machine Learning Researcher,52644,USD,52644,EN,PT,Sweden,M,Sweden,0,"SQL, Git, R, Deep Learning",Associate,1,Transportation,2024-04-04,2024-06-08,1491,6.1,Digital Transformation LLC +AI10318,AI Consultant,141234,USD,141234,SE,FT,United States,S,United States,0,"SQL, Kubernetes, GCP",Bachelor,5,Government,2024-11-18,2024-12-08,1135,5.6,Advanced Robotics +AI10319,AI Research Scientist,110559,USD,110559,MI,FL,Denmark,M,Spain,0,"Hadoop, Docker, MLOps, Linux, Data Visualization",Associate,4,Consulting,2024-11-07,2025-01-17,1542,9,DataVision Ltd +AI10320,AI Consultant,217485,USD,217485,EX,PT,Ireland,L,Luxembourg,0,"Scala, Statistics, Python, Mathematics",PhD,11,Government,2024-03-12,2024-04-19,1730,5.2,Predictive Systems +AI10321,Research Scientist,71252,USD,71252,EN,CT,Norway,M,Norway,0,"R, TensorFlow, PyTorch, Spark",Master,0,Retail,2024-12-09,2025-01-19,2090,6.6,DeepTech Ventures +AI10322,Data Scientist,53971,EUR,45875,EN,FL,France,S,France,0,"TensorFlow, Python, Git, Computer Vision, AWS",Master,0,Technology,2025-01-01,2025-02-12,523,7.5,Algorithmic Solutions +AI10323,Machine Learning Engineer,220263,AUD,297355,EX,CT,Australia,L,Australia,0,"NLP, Data Visualization, TensorFlow, Hadoop",Associate,11,Media,2025-03-10,2025-03-27,1532,5.9,Cloud AI Solutions +AI10324,ML Ops Engineer,277182,USD,277182,EX,FL,Norway,M,Norway,50,"Azure, Linux, NLP, GCP",Bachelor,15,Technology,2024-11-16,2025-01-10,652,7.6,Advanced Robotics +AI10325,Computer Vision Engineer,66175,USD,66175,EN,FT,Finland,M,Turkey,0,"Kubernetes, Statistics, Docker, Spark",Bachelor,1,Gaming,2024-07-09,2024-09-19,1983,5.4,DeepTech Ventures +AI10326,Principal Data Scientist,87331,USD,87331,EN,FT,Norway,L,Norway,100,"Hadoop, SQL, MLOps, Statistics, PyTorch",PhD,0,Retail,2024-07-06,2024-08-26,1817,7.5,Neural Networks Co +AI10327,ML Ops Engineer,139322,USD,139322,MI,CT,Norway,M,Norway,100,"Git, MLOps, Java, GCP",Master,4,Manufacturing,2024-10-17,2024-11-29,1376,9.3,Cloud AI Solutions +AI10328,Autonomous Systems Engineer,111301,EUR,94606,SE,FT,Germany,M,Germany,0,"TensorFlow, R, GCP",Master,5,Transportation,2024-08-09,2024-10-07,1598,6.4,TechCorp Inc +AI10329,AI Architect,132825,GBP,99619,EX,FT,United Kingdom,S,United Kingdom,0,"Statistics, R, AWS, PyTorch, TensorFlow",PhD,17,Gaming,2024-12-16,2025-02-20,708,5.1,AI Innovations +AI10330,AI Consultant,169505,AUD,228832,EX,CT,Australia,M,Australia,0,"SQL, Hadoop, PyTorch, Scala, Kubernetes",PhD,14,Media,2024-02-25,2024-04-17,790,8.8,Machine Intelligence Group +AI10331,Machine Learning Researcher,88530,AUD,119516,MI,CT,Australia,L,Australia,0,"SQL, Scala, Docker, Azure, Mathematics",Master,4,Transportation,2024-04-05,2024-05-26,1421,9.5,Cognitive Computing +AI10332,Machine Learning Researcher,127006,EUR,107955,SE,FT,Austria,S,Austria,50,"GCP, Data Visualization, PyTorch, Computer Vision, Deep Learning",Bachelor,6,Energy,2025-01-02,2025-03-03,2400,6.2,Digital Transformation LLC +AI10333,Computer Vision Engineer,244361,AUD,329887,EX,FT,Australia,M,Australia,100,"Java, Deep Learning, Hadoop",Associate,10,Automotive,2025-03-25,2025-06-03,1476,6.4,Cloud AI Solutions +AI10334,Computer Vision Engineer,74201,CAD,92751,EN,PT,Canada,L,Canada,0,"PyTorch, Python, GCP, TensorFlow, Hadoop",Associate,1,Gaming,2024-11-23,2025-01-20,661,6.4,Machine Intelligence Group +AI10335,Robotics Engineer,166881,USD,166881,SE,PT,Norway,S,United Kingdom,0,"Java, PyTorch, Tableau, TensorFlow, Deep Learning",PhD,8,Healthcare,2024-11-09,2024-11-27,2036,5.9,TechCorp Inc +AI10336,Research Scientist,28173,USD,28173,EN,CT,India,L,India,50,"Python, NLP, Hadoop, Computer Vision",Bachelor,1,Real Estate,2024-08-03,2024-09-17,1891,5.5,Autonomous Tech +AI10337,AI Software Engineer,73010,USD,73010,EN,CT,United States,L,United States,100,"Docker, Tableau, Data Visualization, Azure",PhD,1,Government,2025-02-04,2025-04-15,2119,8,Future Systems +AI10338,Computer Vision Engineer,102446,EUR,87079,MI,CT,Austria,L,Argentina,100,"NLP, MLOps, SQL",Master,3,Telecommunications,2024-10-06,2024-11-16,1801,9.8,Predictive Systems +AI10339,Principal Data Scientist,89214,USD,89214,SE,CT,Finland,S,Finland,0,"Statistics, Azure, Python, SQL",Master,8,Education,2024-12-08,2025-01-30,1097,5.2,Autonomous Tech +AI10340,NLP Engineer,203849,USD,203849,EX,FT,South Korea,L,South Korea,0,"Scala, PyTorch, Git, Linux",Master,12,Finance,2024-07-13,2024-09-04,645,6.1,Future Systems +AI10341,AI Consultant,231925,EUR,197136,EX,CT,Austria,L,Austria,100,"TensorFlow, R, Linux, Hadoop",Associate,16,Transportation,2025-04-01,2025-06-12,2122,9.3,TechCorp Inc +AI10342,Principal Data Scientist,135857,CAD,169821,SE,PT,Canada,L,Czech Republic,50,"Mathematics, Spark, Data Visualization",Bachelor,7,Automotive,2025-04-02,2025-05-23,1584,6.5,Cloud AI Solutions +AI10343,AI Research Scientist,135341,SGD,175943,SE,FL,Singapore,L,Singapore,0,"GCP, Linux, Deep Learning",Bachelor,7,Finance,2024-03-20,2024-04-07,1590,7.7,Quantum Computing Inc +AI10344,AI Architect,131968,EUR,112173,SE,CT,France,L,France,0,"Python, Computer Vision, R, Deep Learning",Master,9,Technology,2025-04-03,2025-05-27,1288,9.7,Predictive Systems +AI10345,AI Software Engineer,123858,GBP,92894,SE,FL,United Kingdom,S,Ukraine,0,"Linux, GCP, R, AWS",Bachelor,5,Media,2025-03-02,2025-04-10,2322,5.5,Cognitive Computing +AI10346,NLP Engineer,348262,CHF,313436,EX,CT,Switzerland,M,Ireland,100,"AWS, Python, Kubernetes",Associate,16,Retail,2024-06-26,2024-08-22,720,6.2,Algorithmic Solutions +AI10347,AI Product Manager,139444,USD,139444,SE,CT,Sweden,L,Sweden,50,"Python, Docker, Data Visualization, MLOps, Statistics",Associate,8,Manufacturing,2024-07-20,2024-09-20,1968,5.5,DataVision Ltd +AI10348,Machine Learning Engineer,149870,USD,149870,SE,FL,Denmark,S,Denmark,50,"SQL, Data Visualization, Tableau, Spark, Java",Master,9,Healthcare,2024-01-26,2024-03-10,763,9.5,Machine Intelligence Group +AI10349,Computer Vision Engineer,71964,USD,71964,EN,PT,Sweden,S,Sweden,50,"NLP, MLOps, Python, Scala, Docker",Master,1,Finance,2024-05-07,2024-07-08,1882,9.7,Advanced Robotics +AI10350,Robotics Engineer,27319,USD,27319,EN,FL,India,L,India,0,"Linux, Scala, Python, PyTorch",Associate,0,Automotive,2024-11-16,2025-01-10,1675,7,Algorithmic Solutions +AI10351,Deep Learning Engineer,150456,GBP,112842,EX,FT,United Kingdom,M,United Kingdom,0,"Kubernetes, R, Statistics, Tableau, MLOps",Associate,12,Telecommunications,2025-03-27,2025-04-16,1274,9,AI Innovations +AI10352,AI Specialist,305568,USD,305568,EX,FL,Norway,L,Norway,50,"SQL, PyTorch, Java, Computer Vision, Deep Learning",PhD,12,Transportation,2024-10-01,2024-11-28,1211,9.1,Digital Transformation LLC +AI10353,Data Scientist,181656,EUR,154408,EX,PT,Austria,S,Austria,100,"SQL, Spark, PyTorch",Bachelor,11,Healthcare,2024-01-25,2024-04-04,2218,5,Smart Analytics +AI10354,AI Specialist,83544,CAD,104430,MI,FT,Canada,L,Canada,0,"TensorFlow, Linux, Git, Kubernetes, Mathematics",PhD,4,Energy,2024-05-10,2024-05-27,1605,5.3,Machine Intelligence Group +AI10355,Data Scientist,85383,SGD,110998,EN,CT,Singapore,L,Singapore,0,"MLOps, Statistics, AWS",Master,1,Telecommunications,2024-05-01,2024-07-06,920,8,Cognitive Computing +AI10356,Data Analyst,118808,USD,118808,MI,FL,Israel,L,Portugal,50,"MLOps, TensorFlow, Scala",Master,3,Transportation,2024-05-31,2024-08-06,837,7.5,Smart Analytics +AI10357,Research Scientist,110158,GBP,82619,MI,CT,United Kingdom,M,Belgium,100,"Java, Computer Vision, Data Visualization, MLOps",PhD,3,Finance,2025-03-28,2025-05-05,1881,9.2,AI Innovations +AI10358,Principal Data Scientist,68395,AUD,92333,EN,FT,Australia,M,Australia,50,"AWS, Python, Docker, Deep Learning, Hadoop",Associate,0,Automotive,2024-10-18,2024-11-04,985,9.6,Digital Transformation LLC +AI10359,AI Consultant,83740,EUR,71179,MI,FL,Austria,L,Austria,0,"Hadoop, Linux, Python, Deep Learning",Associate,2,Transportation,2025-03-21,2025-05-24,655,5.2,Cloud AI Solutions +AI10360,Data Scientist,52109,USD,52109,EX,PT,India,S,India,0,"Python, Kubernetes, Tableau, TensorFlow",Bachelor,15,Education,2025-02-03,2025-04-09,1995,6.1,DeepTech Ventures +AI10361,Machine Learning Researcher,103993,AUD,140391,SE,FT,Australia,S,Sweden,100,"Tableau, Java, Python, SQL, AWS",PhD,9,Education,2024-06-14,2024-07-17,1523,9.9,Predictive Systems +AI10362,Machine Learning Researcher,183121,GBP,137341,EX,FT,United Kingdom,L,United Kingdom,50,"Linux, Kubernetes, R, AWS",Bachelor,11,Telecommunications,2024-03-05,2024-03-28,1413,8.2,Advanced Robotics +AI10363,Data Scientist,76735,USD,76735,SE,PT,South Korea,S,New Zealand,0,"NLP, Kubernetes, AWS, SQL",PhD,8,Energy,2024-08-25,2024-09-23,1994,9.6,Future Systems +AI10364,NLP Engineer,206350,GBP,154763,EX,PT,United Kingdom,L,United Kingdom,100,"Tableau, SQL, Spark, Computer Vision",PhD,18,Telecommunications,2024-06-23,2024-08-09,2468,7.2,TechCorp Inc +AI10365,Autonomous Systems Engineer,105977,GBP,79483,MI,PT,United Kingdom,M,United Kingdom,50,"NLP, Java, TensorFlow",PhD,4,Media,2024-05-20,2024-07-02,2109,5.6,Cloud AI Solutions +AI10366,NLP Engineer,216215,JPY,23783650,EX,CT,Japan,L,Japan,100,"NLP, Hadoop, Kubernetes",Bachelor,19,Retail,2024-06-28,2024-07-30,1784,8,Predictive Systems +AI10367,NLP Engineer,75477,EUR,64155,MI,CT,Germany,M,Germany,0,"NLP, Scala, Spark, PyTorch, Linux",Associate,2,Media,2024-03-21,2024-05-21,1501,6.6,Smart Analytics +AI10368,Principal Data Scientist,48875,USD,48875,SE,FT,China,M,China,100,"Linux, Java, Computer Vision, Kubernetes, Mathematics",Associate,5,Healthcare,2024-12-11,2024-12-27,1022,9.1,Neural Networks Co +AI10369,Principal Data Scientist,104599,CHF,94139,EN,PT,Switzerland,M,Switzerland,50,"Python, Git, Linux, TensorFlow, R",Bachelor,1,Consulting,2025-04-10,2025-04-25,991,9.1,Future Systems +AI10370,Machine Learning Engineer,48610,GBP,36458,EN,PT,United Kingdom,S,United Kingdom,100,"MLOps, SQL, Azure, TensorFlow, GCP",Master,0,Education,2024-09-30,2024-11-05,527,8.4,DataVision Ltd +AI10371,Autonomous Systems Engineer,63371,USD,63371,EN,FT,Ireland,M,Ireland,0,"Docker, Tableau, Data Visualization, Python, Statistics",Associate,1,Finance,2024-12-26,2025-01-24,2265,6.7,AI Innovations +AI10372,Head of AI,62938,EUR,53497,EN,FL,Germany,S,Germany,0,"Java, Hadoop, R",PhD,0,Media,2025-01-17,2025-02-08,1240,6.9,Neural Networks Co +AI10373,AI Specialist,90753,EUR,77140,MI,CT,France,M,New Zealand,100,"Linux, Hadoop, Tableau",Master,4,Manufacturing,2024-12-15,2025-01-24,2436,6.4,Future Systems +AI10374,AI Specialist,82651,USD,82651,MI,FL,South Korea,M,South Korea,100,"Python, TensorFlow, Computer Vision, AWS, Java",Master,3,Education,2024-08-29,2024-10-04,794,5.4,DataVision Ltd +AI10375,Principal Data Scientist,76895,EUR,65361,MI,FT,Netherlands,S,Netherlands,0,"Azure, NLP, Python, Computer Vision, Docker",PhD,2,Finance,2024-02-29,2024-05-08,2416,7.8,AI Innovations +AI10376,NLP Engineer,180262,CAD,225328,EX,CT,Canada,L,Canada,100,"MLOps, Spark, Data Visualization, R",Bachelor,13,Government,2025-02-08,2025-04-19,2351,9.9,TechCorp Inc +AI10377,Head of AI,113460,USD,113460,SE,CT,Finland,S,Kenya,100,"Hadoop, Linux, PyTorch",Bachelor,7,Gaming,2024-06-03,2024-08-03,1972,5.3,DataVision Ltd +AI10378,NLP Engineer,153403,USD,153403,SE,PT,Sweden,L,Sweden,50,"GCP, Azure, Mathematics",Bachelor,7,Healthcare,2024-07-23,2024-09-05,2006,5.7,Autonomous Tech +AI10379,Data Engineer,84780,CAD,105975,MI,PT,Canada,S,Canada,100,"Kubernetes, Docker, Tableau, Azure, Git",PhD,4,Education,2024-08-25,2024-10-21,1131,5.2,AI Innovations +AI10380,AI Consultant,157851,JPY,17363610,EX,CT,Japan,M,Belgium,100,"Scala, TensorFlow, Kubernetes, SQL, PyTorch",Bachelor,12,Telecommunications,2024-12-25,2025-01-19,1496,6,DeepTech Ventures +AI10381,ML Ops Engineer,161328,JPY,17746080,EX,PT,Japan,S,Japan,50,"R, Scala, Mathematics, Deep Learning",Associate,12,Automotive,2024-01-01,2024-03-12,1229,7.1,Machine Intelligence Group +AI10382,AI Research Scientist,180015,CAD,225019,EX,FL,Canada,S,Canada,0,"Deep Learning, Statistics, Scala, Azure",Associate,15,Government,2024-06-11,2024-07-21,856,10,Cloud AI Solutions +AI10383,Machine Learning Researcher,169051,USD,169051,SE,PT,United States,L,United States,50,"R, Java, Deep Learning",PhD,6,Retail,2024-11-02,2025-01-01,2205,7.5,Cloud AI Solutions +AI10384,Robotics Engineer,47369,USD,47369,SE,PT,India,L,India,50,"Linux, Docker, AWS, R",Bachelor,7,Energy,2024-09-12,2024-09-30,2206,9.3,Future Systems +AI10385,Computer Vision Engineer,59893,EUR,50909,EN,FT,Austria,L,Luxembourg,50,"Docker, TensorFlow, NLP, GCP",Bachelor,1,Gaming,2025-01-17,2025-03-08,630,7.8,Cognitive Computing +AI10386,AI Research Scientist,77568,JPY,8532480,EN,FT,Japan,M,Japan,0,"Linux, Python, Deep Learning, TensorFlow, Git",PhD,0,Energy,2024-03-12,2024-05-03,2286,7.8,Advanced Robotics +AI10387,Robotics Engineer,65205,USD,65205,SE,PT,China,M,Kenya,100,"PyTorch, TensorFlow, Deep Learning",PhD,9,Finance,2024-03-10,2024-04-06,766,9.5,DataVision Ltd +AI10388,Robotics Engineer,123050,CHF,110745,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Hadoop, MLOps, SQL",Master,0,Transportation,2024-02-18,2024-03-24,961,9.9,Algorithmic Solutions +AI10389,AI Specialist,59751,USD,59751,EN,FL,Finland,M,Finland,50,"Kubernetes, Linux, GCP, Spark",PhD,0,Gaming,2024-01-08,2024-01-27,2237,7.2,TechCorp Inc +AI10390,AI Product Manager,158205,USD,158205,EX,PT,South Korea,S,South Korea,100,"Kubernetes, Spark, Python, Git, AWS",Master,12,Finance,2024-05-12,2024-06-04,1898,5.2,Future Systems +AI10391,Data Scientist,104978,USD,104978,MI,CT,Ireland,M,Netherlands,50,"AWS, Tableau, Java, Azure, Python",Associate,4,Technology,2024-02-14,2024-03-25,1561,5.3,Predictive Systems +AI10392,AI Product Manager,51383,JPY,5652130,EN,FL,Japan,S,Japan,50,"SQL, Kubernetes, Deep Learning, NLP",PhD,1,Gaming,2024-07-26,2024-08-17,1313,5.5,Quantum Computing Inc +AI10393,Head of AI,133639,CHF,120275,MI,FT,Switzerland,L,Switzerland,0,"Linux, AWS, Deep Learning",PhD,2,Education,2025-01-28,2025-03-05,1763,6.2,Predictive Systems +AI10394,NLP Engineer,70113,JPY,7712430,EN,FL,Japan,M,Japan,0,"Deep Learning, GCP, Scala",PhD,0,Gaming,2024-02-20,2024-04-30,2186,6.7,Quantum Computing Inc +AI10395,AI Product Manager,104072,EUR,88461,MI,FL,Germany,M,Germany,50,"Deep Learning, Python, TensorFlow, Mathematics, PyTorch",Bachelor,4,Retail,2024-05-30,2024-08-08,1966,9.8,TechCorp Inc +AI10396,AI Specialist,71642,AUD,96717,EN,PT,Australia,S,Australia,0,"SQL, Scala, Computer Vision, PyTorch, TensorFlow",Bachelor,0,Gaming,2024-10-08,2024-10-30,1976,6.4,DeepTech Ventures +AI10397,Deep Learning Engineer,140288,USD,140288,SE,FT,Sweden,L,Sweden,50,"Python, Mathematics, TensorFlow",Bachelor,8,Government,2024-06-28,2024-09-07,1002,7,Machine Intelligence Group +AI10398,Data Scientist,134675,EUR,114474,SE,CT,Netherlands,S,Argentina,100,"Python, Git, Statistics",Bachelor,8,Technology,2024-03-11,2024-03-27,1466,7.1,Neural Networks Co +AI10399,AI Consultant,22938,USD,22938,EN,FT,India,M,India,100,"GCP, Tableau, Azure, Mathematics, Spark",Associate,0,Education,2024-05-07,2024-06-09,1943,8.4,Cloud AI Solutions +AI10400,Deep Learning Engineer,141684,EUR,120431,SE,FT,France,L,France,0,"AWS, R, PyTorch, Docker, Tableau",Master,7,Retail,2024-05-11,2024-07-20,2266,5.2,AI Innovations +AI10401,Principal Data Scientist,83033,USD,83033,SE,FL,South Korea,S,South Korea,100,"NLP, Python, TensorFlow, Hadoop, Spark",Bachelor,8,Education,2024-10-28,2024-12-03,2458,6.5,Future Systems +AI10402,Data Engineer,222353,EUR,189000,EX,FT,Netherlands,M,Netherlands,50,"R, Tableau, NLP, MLOps, Docker",Bachelor,18,Telecommunications,2025-01-26,2025-04-09,2350,8.2,TechCorp Inc +AI10403,AI Specialist,89362,EUR,75958,MI,PT,Netherlands,L,Netherlands,0,"TensorFlow, PyTorch, Deep Learning",Master,4,Retail,2024-01-19,2024-03-03,906,9.7,AI Innovations +AI10404,AI Specialist,199765,USD,199765,EX,FL,South Korea,M,South Korea,100,"Python, Git, Docker, GCP, Tableau",Master,19,Real Estate,2024-09-30,2024-11-01,2156,8.1,Future Systems +AI10405,Head of AI,102081,AUD,137809,SE,PT,Australia,M,Australia,50,"Mathematics, Scala, R, Kubernetes",Master,9,Retail,2024-07-07,2024-08-26,2167,8.5,Cloud AI Solutions +AI10406,AI Research Scientist,221776,USD,221776,EX,FL,Norway,S,Norway,0,"SQL, Python, NLP",Bachelor,10,Finance,2024-03-30,2024-05-01,801,5.5,Cloud AI Solutions +AI10407,Deep Learning Engineer,95606,USD,95606,EX,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, GCP, Statistics",Associate,14,Retail,2025-04-12,2025-05-04,609,8.6,Advanced Robotics +AI10408,Data Scientist,102808,EUR,87387,MI,PT,Austria,M,Austria,100,"SQL, Linux, NLP, Scala",PhD,4,Real Estate,2024-07-06,2024-08-14,1703,5.2,Digital Transformation LLC +AI10409,ML Ops Engineer,104905,USD,104905,MI,CT,Norway,S,Norway,50,"Spark, AWS, Statistics",Master,4,Healthcare,2024-08-18,2024-10-02,1678,7.7,DataVision Ltd +AI10410,Computer Vision Engineer,133598,CHF,120238,MI,FT,Switzerland,S,Switzerland,0,"Spark, Kubernetes, Data Visualization",Bachelor,3,Energy,2024-10-11,2024-12-05,2492,6.9,Machine Intelligence Group +AI10411,Autonomous Systems Engineer,282463,JPY,31070930,EX,CT,Japan,L,Japan,0,"MLOps, Java, Python",Associate,19,Education,2024-12-22,2025-01-08,1949,9.9,Cloud AI Solutions +AI10412,Data Engineer,146803,EUR,124783,EX,PT,Germany,M,Germany,100,"SQL, Git, Computer Vision, AWS",Master,13,Finance,2025-02-09,2025-04-21,2291,6.2,Predictive Systems +AI10413,AI Product Manager,226731,USD,226731,EX,FT,Ireland,L,Ireland,0,"Linux, Computer Vision, R, Python",Associate,17,Consulting,2024-05-01,2024-06-25,2395,10,Predictive Systems +AI10414,Data Scientist,85796,EUR,72927,MI,FT,France,L,France,0,"Python, TensorFlow, Mathematics",Associate,3,Transportation,2024-06-16,2024-08-01,2131,9.4,Machine Intelligence Group +AI10415,Head of AI,67219,AUD,90746,EN,FT,Australia,L,Australia,50,"MLOps, Deep Learning, TensorFlow, Python, Computer Vision",PhD,0,Telecommunications,2025-03-29,2025-05-16,2183,5.8,Digital Transformation LLC +AI10416,Deep Learning Engineer,19495,USD,19495,EN,CT,India,M,India,50,"Azure, Python, Linux",Associate,1,Manufacturing,2024-11-20,2025-01-18,1129,6.5,Predictive Systems +AI10417,Machine Learning Engineer,143665,USD,143665,SE,CT,Sweden,M,Sweden,0,"Git, Deep Learning, MLOps, PyTorch",Bachelor,8,Manufacturing,2024-08-21,2024-09-04,951,6.9,DeepTech Ventures +AI10418,Computer Vision Engineer,54072,AUD,72997,EN,PT,Australia,S,Germany,100,"SQL, Tableau, PyTorch, AWS, MLOps",Master,0,Media,2024-09-01,2024-11-02,1394,7.4,DataVision Ltd +AI10419,Data Scientist,93668,EUR,79618,SE,FT,Austria,S,Austria,100,"Mathematics, Git, MLOps, Kubernetes",Bachelor,6,Finance,2024-04-26,2024-05-11,2402,5,Predictive Systems +AI10420,ML Ops Engineer,238158,USD,238158,EX,PT,Norway,L,Norway,50,"Git, SQL, Python, GCP",Master,19,Real Estate,2024-06-15,2024-07-29,1932,8.7,Quantum Computing Inc +AI10421,Computer Vision Engineer,71023,GBP,53267,EN,CT,United Kingdom,S,South Africa,100,"Hadoop, Git, R, Java",Master,1,Real Estate,2024-06-14,2024-07-12,1434,9.5,Digital Transformation LLC +AI10422,AI Specialist,86841,EUR,73815,MI,CT,Germany,L,Australia,100,"PyTorch, TensorFlow, MLOps",PhD,2,Media,2024-01-19,2024-03-24,806,9.9,Cognitive Computing +AI10423,ML Ops Engineer,154195,CAD,192744,EX,PT,Canada,S,Belgium,50,"NLP, PyTorch, R, Java",Master,15,Consulting,2024-10-09,2024-10-31,695,5.8,Future Systems +AI10424,Robotics Engineer,92933,SGD,120813,MI,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Scala",PhD,3,Education,2024-06-03,2024-07-30,1876,7.2,DataVision Ltd +AI10425,Deep Learning Engineer,122175,SGD,158828,SE,PT,Singapore,S,Nigeria,50,"NLP, Scala, Statistics, Deep Learning",Master,8,Technology,2024-05-18,2024-07-22,2133,5.2,Smart Analytics +AI10426,AI Software Engineer,123306,EUR,104810,EX,CT,France,S,France,100,"Python, TensorFlow, GCP",PhD,15,Education,2024-11-15,2025-01-06,1729,6.4,AI Innovations +AI10427,AI Research Scientist,103528,EUR,87999,MI,PT,Austria,L,Austria,100,"GCP, AWS, MLOps",Bachelor,4,Government,2024-08-05,2024-09-24,926,5.8,DataVision Ltd +AI10428,AI Specialist,98123,EUR,83405,SE,FT,Netherlands,S,Netherlands,0,"PyTorch, NLP, Docker, AWS",Associate,6,Telecommunications,2024-08-22,2024-10-12,1172,6.8,Predictive Systems +AI10429,AI Research Scientist,75392,USD,75392,EN,FL,South Korea,L,South Korea,0,"Python, Java, Azure, Kubernetes, Git",Bachelor,1,Finance,2024-02-08,2024-03-21,1380,8.2,Future Systems +AI10430,AI Architect,47588,CAD,59485,EN,FL,Canada,S,Canada,50,"Kubernetes, Git, Tableau",PhD,0,Real Estate,2024-08-23,2024-10-20,2296,6.1,Future Systems +AI10431,Data Engineer,64925,JPY,7141750,EN,CT,Japan,S,Estonia,50,"Scala, Mathematics, SQL, Azure, Data Visualization",Bachelor,1,Manufacturing,2024-10-13,2024-12-11,1706,8.8,DeepTech Ventures +AI10432,AI Consultant,59060,USD,59060,MI,CT,China,L,China,0,"Computer Vision, Java, PyTorch",Master,3,Government,2024-03-23,2024-05-12,2496,6.8,Quantum Computing Inc +AI10433,Machine Learning Researcher,206097,USD,206097,SE,CT,Denmark,L,Denmark,100,"Python, Data Visualization, Spark",Master,8,Energy,2024-10-08,2024-11-26,2416,8.5,AI Innovations +AI10434,Data Engineer,61098,USD,61098,EN,FL,South Korea,M,Indonesia,0,"Statistics, PyTorch, MLOps",Master,1,Telecommunications,2024-05-20,2024-06-27,1175,8,Quantum Computing Inc +AI10435,Data Scientist,63567,USD,63567,EN,CT,Ireland,M,Ireland,0,"AWS, R, Data Visualization",Bachelor,0,Gaming,2024-07-12,2024-07-31,2154,9.2,Quantum Computing Inc +AI10436,Machine Learning Engineer,247728,CHF,222955,SE,FL,Switzerland,L,Indonesia,0,"Hadoop, Kubernetes, NLP",Associate,9,Telecommunications,2024-08-22,2024-09-21,1912,5.7,TechCorp Inc +AI10437,Research Scientist,125206,GBP,93905,SE,CT,United Kingdom,M,Indonesia,50,"Deep Learning, Tableau, Kubernetes, Git",Master,7,Media,2024-09-26,2024-10-16,1042,8.2,Digital Transformation LLC +AI10438,Robotics Engineer,72094,EUR,61280,EN,PT,France,M,France,100,"Linux, Java, Mathematics, Computer Vision, PyTorch",Associate,1,Healthcare,2025-03-31,2025-05-23,2433,5.9,TechCorp Inc +AI10439,AI Research Scientist,85942,CAD,107428,EN,PT,Canada,L,Canada,100,"Linux, Kubernetes, Hadoop, Statistics",Associate,0,Consulting,2024-05-09,2024-06-25,2072,7.1,TechCorp Inc +AI10440,ML Ops Engineer,191299,USD,191299,EX,CT,Ireland,M,Spain,100,"Azure, SQL, PyTorch",Bachelor,17,Telecommunications,2024-05-14,2024-06-24,1221,5.6,Autonomous Tech +AI10441,Computer Vision Engineer,145582,USD,145582,SE,CT,Israel,L,Israel,50,"Deep Learning, Kubernetes, R",Associate,5,Technology,2024-08-24,2024-10-21,1743,7.9,AI Innovations +AI10442,AI Architect,91181,AUD,123094,MI,PT,Australia,S,Australia,100,"Git, Docker, SQL, Kubernetes",Master,4,Media,2024-12-18,2025-02-24,1535,5.8,Smart Analytics +AI10443,NLP Engineer,100215,USD,100215,EX,CT,China,S,Indonesia,0,"Docker, R, Java",Bachelor,11,Manufacturing,2024-03-11,2024-05-09,2088,9.3,Quantum Computing Inc +AI10444,AI Consultant,47259,USD,47259,EX,FT,India,S,India,100,"TensorFlow, Spark, NLP",PhD,14,Energy,2024-11-15,2024-12-28,1642,6.1,Quantum Computing Inc +AI10445,AI Architect,244995,USD,244995,EX,CT,Norway,M,Norway,0,"TensorFlow, Docker, R",PhD,14,Education,2024-09-19,2024-11-18,1936,9.3,TechCorp Inc +AI10446,Data Analyst,131732,AUD,177838,SE,CT,Australia,L,Australia,50,"TensorFlow, Java, Deep Learning, Linux",Associate,7,Government,2024-06-16,2024-08-09,943,6.1,Quantum Computing Inc +AI10447,Autonomous Systems Engineer,142453,SGD,185189,SE,CT,Singapore,M,Singapore,100,"Mathematics, Docker, Python, Scala, Computer Vision",Master,8,Transportation,2024-12-23,2025-02-02,846,6.6,DataVision Ltd +AI10448,Data Scientist,114905,EUR,97669,MI,FL,France,L,France,100,"Python, GCP, Spark",Bachelor,4,Real Estate,2024-03-30,2024-05-07,972,5.5,Smart Analytics +AI10449,Machine Learning Engineer,94309,USD,94309,MI,CT,Sweden,L,Sweden,0,"Python, Git, TensorFlow, Docker, PyTorch",Associate,2,Retail,2024-09-24,2024-12-03,1036,7.7,DeepTech Ventures +AI10450,AI Consultant,269435,CHF,242492,EX,PT,Switzerland,M,Switzerland,100,"MLOps, Java, Azure",Bachelor,18,Manufacturing,2025-02-26,2025-04-08,1393,9.2,Advanced Robotics +AI10451,Machine Learning Engineer,64365,EUR,54710,EN,FL,Germany,S,Germany,0,"Spark, GCP, Mathematics",Associate,1,Gaming,2024-04-26,2024-07-01,1828,10,TechCorp Inc +AI10452,AI Specialist,105348,USD,105348,EN,PT,Norway,L,Norway,100,"NLP, Python, Kubernetes, AWS",Master,0,Technology,2024-12-18,2025-01-13,1099,9.1,Cloud AI Solutions +AI10453,Machine Learning Engineer,157110,GBP,117833,SE,FL,United Kingdom,L,United Kingdom,50,"Scala, Deep Learning, MLOps, Data Visualization",Bachelor,6,Technology,2024-03-26,2024-05-22,1108,9.9,Autonomous Tech +AI10454,Computer Vision Engineer,312583,USD,312583,EX,FL,Denmark,L,United States,0,"SQL, Deep Learning, NLP",Master,19,Manufacturing,2024-08-16,2024-09-16,536,8.6,Digital Transformation LLC +AI10455,Autonomous Systems Engineer,74526,USD,74526,EX,FT,China,M,Canada,0,"TensorFlow, R, Data Visualization",Master,12,Education,2024-07-22,2024-09-24,1101,10,Cognitive Computing +AI10456,Robotics Engineer,172413,JPY,18965430,SE,FL,Japan,L,Japan,100,"Python, Docker, TensorFlow, SQL, AWS",Associate,5,Media,2025-03-02,2025-03-30,1199,5.3,TechCorp Inc +AI10457,Machine Learning Researcher,163535,EUR,139005,SE,PT,Austria,L,Austria,50,"Statistics, Spark, Tableau",Master,8,Government,2024-08-19,2024-10-10,1823,9,TechCorp Inc +AI10458,Data Analyst,132082,USD,132082,EX,FL,South Korea,M,South Korea,50,"SQL, NLP, Azure, Scala, Python",Master,17,Media,2024-06-13,2024-08-15,1298,9.2,Digital Transformation LLC +AI10459,Research Scientist,261749,USD,261749,EX,CT,Norway,S,Finland,100,"Computer Vision, Statistics, PyTorch, Java",PhD,12,Government,2024-02-19,2024-03-06,1489,8.4,Cognitive Computing +AI10460,Head of AI,68534,USD,68534,SE,FL,China,M,China,50,"Deep Learning, GCP, Computer Vision",Master,8,Media,2024-03-08,2024-03-26,1951,6.7,Machine Intelligence Group +AI10461,AI Consultant,95396,EUR,81087,MI,CT,Germany,M,Germany,100,"Linux, SQL, Kubernetes, GCP",Bachelor,4,Retail,2024-06-11,2024-07-03,1007,7.8,Predictive Systems +AI10462,Data Scientist,74131,AUD,100077,EN,CT,Australia,M,Australia,50,"Spark, Hadoop, Tableau, Mathematics",Master,1,Transportation,2024-01-15,2024-03-05,951,8.9,Neural Networks Co +AI10463,Computer Vision Engineer,115232,USD,115232,MI,CT,Denmark,M,Denmark,50,"Tableau, NLP, Scala, Deep Learning, PyTorch",Master,3,Technology,2024-12-25,2025-02-25,667,6.9,Digital Transformation LLC +AI10464,Machine Learning Engineer,58227,SGD,75695,EN,FL,Singapore,S,Singapore,100,"Kubernetes, Deep Learning, NLP, TensorFlow",Bachelor,1,Healthcare,2024-01-03,2024-01-19,2113,9.1,Machine Intelligence Group +AI10465,Data Analyst,188430,CHF,169587,SE,FT,Switzerland,L,Switzerland,100,"Python, Scala, Hadoop, Docker, TensorFlow",Associate,6,Technology,2025-03-01,2025-03-25,955,6.4,Quantum Computing Inc +AI10466,Head of AI,72415,SGD,94140,EN,PT,Singapore,M,Singapore,0,"Git, Scala, Linux, SQL",Associate,0,Retail,2024-05-12,2024-06-18,2310,7.2,DeepTech Ventures +AI10467,AI Consultant,49041,GBP,36781,EN,FT,United Kingdom,S,United Kingdom,100,"Docker, Spark, Deep Learning, TensorFlow, PyTorch",Master,1,Manufacturing,2024-10-28,2024-11-18,660,8.4,Neural Networks Co +AI10468,Research Scientist,78075,USD,78075,MI,FL,Finland,M,Finland,0,"Statistics, Hadoop, Tableau, Kubernetes",Master,3,Automotive,2025-03-27,2025-05-28,657,9,Neural Networks Co +AI10469,Autonomous Systems Engineer,96725,USD,96725,EN,PT,Denmark,L,Denmark,100,"Git, PyTorch, Scala, Azure",Associate,1,Technology,2025-01-26,2025-02-20,1553,5.6,Cloud AI Solutions +AI10470,AI Architect,116451,CAD,145564,MI,FL,Canada,L,Canada,0,"Kubernetes, Azure, SQL, Java, Spark",Bachelor,3,Automotive,2024-06-17,2024-08-24,883,9.6,Autonomous Tech +AI10471,AI Research Scientist,96459,SGD,125397,EN,FT,Singapore,L,Austria,100,"Data Visualization, Azure, Mathematics, PyTorch",PhD,0,Manufacturing,2024-03-26,2024-06-04,1160,7.4,DataVision Ltd +AI10472,AI Research Scientist,254343,CHF,228909,EX,FT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Hadoop, Statistics",Associate,18,Real Estate,2024-02-28,2024-04-15,1326,8.1,Autonomous Tech +AI10473,Autonomous Systems Engineer,131234,EUR,111549,SE,FL,Germany,S,Germany,100,"Java, Spark, Statistics, Mathematics",PhD,6,Manufacturing,2024-08-13,2024-09-24,701,9.5,Future Systems +AI10474,Autonomous Systems Engineer,53585,USD,53585,EN,CT,South Korea,S,South Korea,100,"Tableau, NLP, MLOps, Data Visualization",PhD,0,Media,2025-01-01,2025-03-09,1610,6.6,Future Systems +AI10475,AI Consultant,156371,USD,156371,SE,PT,Denmark,M,Denmark,0,"NLP, Hadoop, GCP, Azure, Java",Bachelor,8,Telecommunications,2025-01-21,2025-02-24,686,6.6,DataVision Ltd +AI10476,NLP Engineer,166022,GBP,124517,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, Docker",PhD,19,Consulting,2024-10-31,2024-12-31,2259,9.8,Predictive Systems +AI10477,AI Software Engineer,87583,SGD,113858,MI,FL,Singapore,M,Belgium,100,"Data Visualization, Docker, Kubernetes, Scala",Bachelor,2,Manufacturing,2024-08-12,2024-09-07,1779,9.8,Predictive Systems +AI10478,Robotics Engineer,131350,USD,131350,SE,FL,Ireland,M,Ireland,100,"NLP, Java, Kubernetes",Bachelor,7,Education,2024-10-07,2024-11-16,1324,5.1,Algorithmic Solutions +AI10479,Robotics Engineer,25847,USD,25847,EN,FL,China,M,China,100,"R, TensorFlow, Docker, Data Visualization",Master,1,Manufacturing,2024-05-13,2024-07-19,567,7.3,Smart Analytics +AI10480,Data Scientist,70279,USD,70279,EN,CT,Sweden,M,Sweden,0,"Docker, Kubernetes, AWS, Tableau, Git",Master,0,Transportation,2025-04-16,2025-05-18,2431,5.9,Quantum Computing Inc +AI10481,Principal Data Scientist,83967,USD,83967,MI,FL,Sweden,L,Sweden,50,"Data Visualization, Git, Scala",Associate,4,Consulting,2024-06-26,2024-07-30,533,5.8,Advanced Robotics +AI10482,Data Analyst,117772,USD,117772,SE,FT,Israel,S,Israel,50,"AWS, GCP, Statistics, Java",PhD,5,Government,2025-04-30,2025-07-02,1085,7,Predictive Systems +AI10483,Data Engineer,77901,USD,77901,MI,PT,Finland,S,Finland,100,"Scala, Spark, AWS, PyTorch, Linux",PhD,4,Government,2024-02-16,2024-04-19,2164,9.6,Digital Transformation LLC +AI10484,Robotics Engineer,251299,USD,251299,EX,FT,Israel,L,Israel,100,"Kubernetes, Scala, GCP",PhD,17,Retail,2024-02-17,2024-03-10,2304,9.5,Quantum Computing Inc +AI10485,ML Ops Engineer,56632,CAD,70790,EN,FL,Canada,S,Canada,0,"Computer Vision, AWS, NLP",Master,1,Media,2025-04-10,2025-06-08,1669,8.2,Cloud AI Solutions +AI10486,Data Scientist,89248,EUR,75861,SE,FT,Austria,S,Austria,0,"PyTorch, MLOps, Python, R",Master,6,Technology,2025-04-03,2025-06-01,819,6.8,Machine Intelligence Group +AI10487,ML Ops Engineer,159129,CHF,143216,SE,FL,Switzerland,S,Switzerland,0,"TensorFlow, SQL, R",Associate,8,Government,2024-09-09,2024-10-10,2320,5.5,Cognitive Computing +AI10488,Deep Learning Engineer,121563,USD,121563,SE,CT,Finland,S,Norway,100,"Python, GCP, Git, TensorFlow, Statistics",Associate,9,Government,2024-11-11,2024-12-16,1300,5.6,Future Systems +AI10489,Computer Vision Engineer,60861,EUR,51732,EN,CT,Austria,L,Austria,0,"Azure, PyTorch, Mathematics, Python",Bachelor,0,Telecommunications,2024-03-13,2024-05-24,1422,8.3,DeepTech Ventures +AI10490,Research Scientist,118967,CHF,107070,MI,CT,Switzerland,L,Canada,50,"Java, MLOps, Python, R",PhD,4,Technology,2024-08-31,2024-10-28,1605,9.3,DataVision Ltd +AI10491,AI Research Scientist,233392,EUR,198383,EX,FT,Germany,L,Germany,100,"Statistics, Java, PyTorch, Deep Learning",Bachelor,16,Government,2024-02-29,2024-05-07,2030,7.7,AI Innovations +AI10492,Data Analyst,132254,EUR,112416,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, Computer Vision, Tableau",Master,9,Education,2024-06-18,2024-07-04,2009,7.7,DataVision Ltd +AI10493,Data Analyst,64661,USD,64661,EN,FL,Finland,L,Finland,100,"Statistics, TensorFlow, Hadoop, GCP, Deep Learning",PhD,1,Finance,2024-09-08,2024-10-18,621,8.1,Smart Analytics +AI10494,Head of AI,113314,USD,113314,MI,CT,United States,M,Australia,50,"Python, SQL, Linux, GCP, Scala",Master,4,Media,2024-06-26,2024-08-09,936,9.4,AI Innovations +AI10495,Autonomous Systems Engineer,114505,SGD,148857,SE,CT,Singapore,S,Singapore,100,"Java, R, GCP, Mathematics, Hadoop",Associate,8,Media,2024-03-25,2024-04-16,1103,9.3,Smart Analytics +AI10496,AI Software Engineer,176423,EUR,149960,EX,CT,Austria,L,Ghana,100,"PyTorch, Hadoop, Linux, Azure, Scala",PhD,17,Government,2024-11-18,2024-12-08,2133,6.2,Smart Analytics +AI10497,Deep Learning Engineer,47416,EUR,40304,EN,PT,Austria,S,Austria,0,"Linux, AWS, Computer Vision",Associate,0,Telecommunications,2024-10-10,2024-12-09,1205,5.9,DeepTech Ventures +AI10498,Data Scientist,273664,GBP,205248,EX,FL,United Kingdom,L,United Kingdom,100,"Azure, Python, GCP",Bachelor,18,Technology,2024-08-21,2024-10-14,1518,6.8,Predictive Systems +AI10499,AI Product Manager,158106,SGD,205538,SE,PT,Singapore,L,Singapore,100,"Python, Kubernetes, Computer Vision, Hadoop",Bachelor,9,Telecommunications,2024-06-16,2024-07-05,576,8.1,Autonomous Tech +AI10500,Deep Learning Engineer,134252,EUR,114114,SE,CT,Austria,M,Austria,50,"Azure, Scala, AWS",Associate,7,Education,2025-04-01,2025-04-28,821,9.3,Smart Analytics +AI10501,Research Scientist,39883,USD,39883,EN,CT,South Korea,S,Australia,100,"Tableau, PyTorch, AWS, Statistics, Git",Bachelor,0,Real Estate,2024-09-18,2024-11-19,2465,6.2,Quantum Computing Inc +AI10502,AI Architect,86586,USD,86586,MI,FL,Ireland,S,Ireland,100,"SQL, Scala, Statistics, Kubernetes, GCP",Bachelor,4,Transportation,2024-11-26,2024-12-16,1516,8.2,Cognitive Computing +AI10503,NLP Engineer,158006,JPY,17380660,SE,PT,Japan,L,Switzerland,50,"Kubernetes, Spark, R, Deep Learning",Bachelor,9,Finance,2024-09-02,2024-11-12,2181,9.5,Quantum Computing Inc +AI10504,Research Scientist,160380,USD,160380,EX,FL,Israel,L,Israel,50,"Python, Azure, NLP, TensorFlow, AWS",Master,18,Government,2024-10-19,2024-11-29,2304,5.4,Advanced Robotics +AI10505,NLP Engineer,178755,USD,178755,SE,CT,Norway,L,Norway,100,"Hadoop, Spark, Computer Vision",PhD,6,Energy,2025-01-29,2025-02-20,1020,6.4,Predictive Systems +AI10506,Principal Data Scientist,99536,USD,99536,MI,CT,United States,M,United States,100,"Linux, PyTorch, SQL, Statistics, MLOps",Bachelor,2,Manufacturing,2025-04-07,2025-06-13,1184,6.2,Predictive Systems +AI10507,AI Research Scientist,124279,AUD,167777,MI,FT,Australia,L,Australia,50,"Java, PyTorch, R, Tableau",Bachelor,2,Retail,2025-04-27,2025-06-06,862,5.8,DeepTech Ventures +AI10508,Machine Learning Engineer,64888,EUR,55155,EN,FL,Germany,L,Germany,50,"Spark, Linux, PyTorch, Java",Associate,1,Technology,2025-02-11,2025-03-06,1392,5.1,Cloud AI Solutions +AI10509,AI Product Manager,102390,EUR,87032,SE,FL,Germany,S,Germany,0,"GCP, Deep Learning, R, TensorFlow",PhD,9,Gaming,2024-06-27,2024-08-12,1601,5.7,Future Systems +AI10510,Research Scientist,43363,USD,43363,MI,PT,China,L,China,100,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Master,3,Government,2024-05-10,2024-07-19,1250,9.1,Algorithmic Solutions +AI10511,Machine Learning Engineer,82118,AUD,110859,EN,CT,Australia,L,Australia,50,"Deep Learning, Mathematics, Data Visualization",PhD,0,Transportation,2024-05-22,2024-07-11,2347,9,Machine Intelligence Group +AI10512,Deep Learning Engineer,138768,USD,138768,SE,FL,Ireland,L,Ireland,50,"Hadoop, Kubernetes, Data Visualization, NLP, Spark",Associate,7,Media,2024-08-09,2024-09-26,2439,6.6,Neural Networks Co +AI10513,Computer Vision Engineer,48876,AUD,65983,EN,FL,Australia,S,Australia,50,"NLP, GCP, Tableau, Azure, Docker",Master,1,Gaming,2024-06-01,2024-07-29,1711,7.9,DataVision Ltd +AI10514,Machine Learning Researcher,72281,USD,72281,EN,FT,Ireland,S,Ireland,0,"SQL, Hadoop, Data Visualization",Bachelor,0,Consulting,2024-09-22,2024-10-09,1577,8.4,Neural Networks Co +AI10515,AI Research Scientist,136114,AUD,183754,SE,PT,Australia,S,Australia,100,"Python, Scala, Java, Deep Learning",Bachelor,8,Consulting,2024-01-04,2024-02-22,901,5.5,Predictive Systems +AI10516,Data Analyst,47355,USD,47355,SE,FL,India,S,Israel,100,"Tableau, Spark, AWS, Scala, SQL",Bachelor,6,Gaming,2024-11-09,2024-11-24,1396,6.4,Autonomous Tech +AI10517,AI Architect,116538,USD,116538,MI,FT,Israel,L,Israel,0,"Statistics, Spark, Mathematics",Bachelor,2,Finance,2024-09-06,2024-10-24,1791,9.1,Machine Intelligence Group +AI10518,Data Engineer,101215,USD,101215,MI,CT,Ireland,M,Ireland,0,"Git, Python, NLP, Statistics, Kubernetes",PhD,4,Energy,2024-06-25,2024-08-08,1775,9.3,Smart Analytics +AI10519,Computer Vision Engineer,120939,CHF,108845,MI,CT,Switzerland,L,Switzerland,0,"Git, Java, SQL, Azure",Associate,3,Media,2024-12-16,2025-02-17,1891,8,Smart Analytics +AI10520,AI Consultant,53345,JPY,5867950,EN,PT,Japan,S,Netherlands,50,"Python, TensorFlow, Kubernetes, Linux, MLOps",Master,1,Telecommunications,2024-05-28,2024-07-13,605,7.9,Quantum Computing Inc +AI10521,Machine Learning Researcher,49297,USD,49297,EN,FT,Israel,M,Israel,0,"Kubernetes, PyTorch, GCP",Master,0,Manufacturing,2024-06-15,2024-07-19,2343,8.2,Predictive Systems +AI10522,Data Engineer,85313,SGD,110907,EN,FL,Singapore,M,Singapore,100,"SQL, PyTorch, NLP, Hadoop, MLOps",PhD,1,Gaming,2024-02-03,2024-02-17,960,6.9,Future Systems +AI10523,Computer Vision Engineer,165378,CAD,206723,EX,FT,Canada,S,Canada,50,"Java, Git, Tableau, GCP",Bachelor,18,Real Estate,2024-01-26,2024-03-25,1637,9.5,Algorithmic Solutions +AI10524,AI Product Manager,78358,USD,78358,EN,PT,Israel,L,Israel,0,"Java, SQL, Computer Vision, R",Bachelor,0,Government,2024-01-24,2024-03-07,723,6.1,DeepTech Ventures +AI10525,NLP Engineer,23160,USD,23160,EN,FL,India,S,India,100,"Docker, Git, Statistics, R",Bachelor,1,Manufacturing,2024-05-09,2024-06-14,936,9.7,Quantum Computing Inc +AI10526,Research Scientist,85575,USD,85575,MI,PT,Israel,M,Israel,0,"Python, Kubernetes, Linux, NLP, PyTorch",Bachelor,2,Education,2025-03-28,2025-06-04,2322,7.1,TechCorp Inc +AI10527,AI Specialist,188461,JPY,20730710,EX,FL,Japan,S,Japan,50,"Scala, Spark, Tableau, MLOps",Master,18,Consulting,2025-01-19,2025-03-26,988,5.7,Digital Transformation LLC +AI10528,Autonomous Systems Engineer,16621,USD,16621,EN,CT,India,S,India,0,"Kubernetes, Python, AWS",Master,0,Manufacturing,2025-02-24,2025-04-29,1724,7.9,Advanced Robotics +AI10529,Machine Learning Researcher,154393,CAD,192991,SE,FL,Canada,L,Canada,100,"Kubernetes, Python, TensorFlow, Java",Master,7,Retail,2024-10-23,2024-11-26,2475,6.9,Quantum Computing Inc +AI10530,Machine Learning Researcher,115524,USD,115524,SE,FT,Finland,S,Finland,50,"R, SQL, Data Visualization, Linux, Deep Learning",Associate,6,Education,2024-01-27,2024-03-29,1229,6.9,Advanced Robotics +AI10531,AI Software Engineer,20633,USD,20633,EN,PT,India,S,India,100,"SQL, GCP, Azure",PhD,1,Real Estate,2024-03-02,2024-04-17,1824,6.9,Cognitive Computing +AI10532,Robotics Engineer,190066,GBP,142550,EX,FL,United Kingdom,S,Romania,50,"PyTorch, Docker, AWS, Deep Learning",Associate,11,Government,2024-08-17,2024-10-08,1342,9.3,Quantum Computing Inc +AI10533,Head of AI,296126,JPY,32573860,EX,FT,Japan,L,Japan,0,"PyTorch, Statistics, TensorFlow, NLP, Deep Learning",Associate,18,Gaming,2024-07-21,2024-09-18,775,9.6,Predictive Systems +AI10534,Autonomous Systems Engineer,187800,USD,187800,SE,FL,Norway,L,Norway,100,"Tableau, Git, Deep Learning, Python, SQL",PhD,7,Real Estate,2024-12-30,2025-03-13,1720,9.5,Autonomous Tech +AI10535,Data Scientist,206562,USD,206562,EX,CT,Ireland,S,Ireland,100,"GCP, Java, NLP, Data Visualization",Associate,17,Gaming,2024-06-10,2024-07-15,1196,7.1,Algorithmic Solutions +AI10536,AI Specialist,188230,JPY,20705300,EX,FL,Japan,S,Japan,0,"Python, Computer Vision, Tableau, Linux",PhD,11,Manufacturing,2024-08-20,2024-10-17,1097,7.5,TechCorp Inc +AI10537,Machine Learning Engineer,151183,USD,151183,SE,FT,Norway,S,Norway,50,"Hadoop, SQL, TensorFlow, NLP",PhD,5,Retail,2024-12-27,2025-01-31,1674,6,DeepTech Ventures +AI10538,Principal Data Scientist,84340,JPY,9277400,EN,PT,Japan,L,Japan,0,"MLOps, Git, Java, Kubernetes",Bachelor,1,Transportation,2024-06-05,2024-08-03,1477,7.1,Machine Intelligence Group +AI10539,Head of AI,130206,SGD,169268,SE,CT,Singapore,S,Singapore,100,"R, Scala, SQL, Data Visualization",Bachelor,7,Media,2024-10-05,2024-11-13,566,6,TechCorp Inc +AI10540,Machine Learning Researcher,59063,AUD,79735,EN,CT,Australia,M,Australia,0,"Azure, Python, GCP, Scala",Bachelor,0,Gaming,2024-06-07,2024-07-23,696,8.6,Cloud AI Solutions +AI10541,Data Engineer,105416,CHF,94874,EN,CT,Switzerland,M,Switzerland,50,"R, Python, Data Visualization, TensorFlow, Git",PhD,1,Consulting,2024-01-28,2024-03-11,2392,6.7,DeepTech Ventures +AI10542,Head of AI,116299,USD,116299,EX,PT,China,M,China,100,"Hadoop, Linux, SQL",Bachelor,17,Transportation,2025-01-03,2025-03-15,615,5.2,AI Innovations +AI10543,Data Analyst,123542,USD,123542,SE,FT,Sweden,M,Sweden,50,"Git, Python, AWS",Bachelor,8,Healthcare,2024-03-27,2024-05-07,2113,5.1,Cloud AI Solutions +AI10544,Computer Vision Engineer,268891,CHF,242002,EX,FL,Switzerland,L,Switzerland,50,"Statistics, R, Tableau",Master,19,Consulting,2024-10-05,2024-12-05,1722,5.8,Digital Transformation LLC +AI10545,Robotics Engineer,184006,USD,184006,EX,PT,South Korea,M,France,0,"Spark, Deep Learning, Computer Vision, Python",Bachelor,11,Telecommunications,2024-10-01,2024-11-25,1949,9.3,Future Systems +AI10546,Head of AI,253222,JPY,27854420,EX,CT,Japan,L,Japan,0,"PyTorch, Data Visualization, TensorFlow, GCP, Python",Master,17,Energy,2024-05-03,2024-06-01,1021,8.7,TechCorp Inc +AI10547,AI Software Engineer,117179,USD,117179,EN,PT,Norway,L,Thailand,100,"Data Visualization, Linux, Python",Master,1,Real Estate,2024-05-10,2024-07-06,2212,6.9,Digital Transformation LLC +AI10548,Machine Learning Engineer,267272,GBP,200454,EX,FT,United Kingdom,L,Portugal,0,"Git, Data Visualization, Java, NLP",PhD,10,Real Estate,2024-02-01,2024-03-15,503,8.8,DataVision Ltd +AI10549,Deep Learning Engineer,58015,EUR,49313,EN,FL,France,M,France,50,"Linux, NLP, Mathematics",PhD,0,Retail,2025-03-13,2025-05-25,2176,9,Smart Analytics +AI10550,Computer Vision Engineer,134945,EUR,114703,SE,FL,France,M,Philippines,100,"MLOps, Python, Hadoop, TensorFlow, Git",Master,5,Government,2024-05-20,2024-07-23,935,7.1,Machine Intelligence Group +AI10551,Data Analyst,171640,GBP,128730,SE,CT,United Kingdom,L,United Kingdom,100,"TensorFlow, Linux, Hadoop",PhD,7,Government,2024-03-26,2024-04-22,2475,9.2,Advanced Robotics +AI10552,NLP Engineer,188053,USD,188053,EX,PT,Sweden,S,Sweden,50,"Scala, Deep Learning, Java, PyTorch",Associate,18,Retail,2024-02-24,2024-03-21,2223,6.9,Machine Intelligence Group +AI10553,Research Scientist,174050,EUR,147943,SE,PT,Netherlands,L,Netherlands,100,"Linux, Statistics, Spark",Bachelor,5,Gaming,2024-07-08,2024-09-19,712,8.2,Digital Transformation LLC +AI10554,Machine Learning Researcher,162350,USD,162350,EX,CT,South Korea,S,South Korea,100,"SQL, AWS, MLOps, Azure",Master,15,Consulting,2024-06-01,2024-08-11,1094,7.6,Digital Transformation LLC +AI10555,NLP Engineer,48857,USD,48857,EN,FL,Sweden,S,Singapore,0,"Scala, Java, Computer Vision, Python, TensorFlow",Bachelor,1,Technology,2025-01-17,2025-03-10,2343,9.3,Neural Networks Co +AI10556,Autonomous Systems Engineer,81741,SGD,106263,EN,FT,Singapore,M,Singapore,100,"Mathematics, Git, NLP, SQL",Associate,0,Healthcare,2025-01-16,2025-03-25,2261,6.9,Cognitive Computing +AI10557,Data Scientist,93881,EUR,79799,MI,FT,Austria,M,Austria,100,"Scala, MLOps, Java, TensorFlow",Bachelor,3,Healthcare,2024-07-16,2024-08-24,1606,7.5,Machine Intelligence Group +AI10558,AI Research Scientist,52800,USD,52800,EN,FL,Finland,S,Finland,0,"MLOps, Docker, Data Visualization, R",PhD,0,Finance,2024-08-14,2024-10-18,551,6.8,Predictive Systems +AI10559,AI Consultant,164719,CHF,148247,MI,FL,Switzerland,L,Switzerland,100,"Hadoop, Data Visualization, Scala, Docker",Associate,4,Consulting,2024-06-24,2024-08-24,1239,5.3,Autonomous Tech +AI10560,Research Scientist,89861,GBP,67396,MI,CT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Python, Tableau",Master,2,Education,2024-07-03,2024-07-19,1058,6.4,AI Innovations +AI10561,Autonomous Systems Engineer,182265,USD,182265,EX,FL,Israel,S,Israel,100,"Kubernetes, TensorFlow, Mathematics, AWS",Bachelor,19,Manufacturing,2024-10-28,2025-01-04,1922,7.1,Quantum Computing Inc +AI10562,Head of AI,119526,USD,119526,SE,PT,Israel,M,Austria,100,"Spark, Mathematics, Python",Bachelor,6,Technology,2025-03-05,2025-04-23,1562,7,Cognitive Computing +AI10563,Deep Learning Engineer,167797,USD,167797,EX,FL,Sweden,S,United Kingdom,100,"Computer Vision, NLP, Statistics",Master,19,Healthcare,2024-12-19,2025-02-14,1184,7.9,Algorithmic Solutions +AI10564,Machine Learning Researcher,338875,USD,338875,EX,FT,United States,L,United States,100,"Statistics, PyTorch, Deep Learning, TensorFlow",Master,16,Automotive,2024-07-24,2024-08-10,2085,7.1,Smart Analytics +AI10565,NLP Engineer,191360,EUR,162656,EX,FT,Austria,S,Austria,50,"Mathematics, Hadoop, Git, Computer Vision, Data Visualization",Bachelor,16,Telecommunications,2025-04-06,2025-06-01,2448,6.5,Future Systems +AI10566,Machine Learning Researcher,134565,USD,134565,SE,FL,United States,S,United States,0,"Statistics, Linux, Python, Git, Tableau",PhD,6,Real Estate,2024-09-04,2024-10-21,653,9.5,TechCorp Inc +AI10567,AI Consultant,75173,JPY,8269030,EN,FL,Japan,S,Belgium,100,"Python, TensorFlow, Mathematics, Git",Associate,0,Real Estate,2024-11-01,2024-12-04,2083,5.4,Cloud AI Solutions +AI10568,Machine Learning Engineer,123862,EUR,105283,SE,FL,France,S,France,0,"NLP, Tableau, Computer Vision",PhD,7,Finance,2024-02-29,2024-03-18,1232,5.4,Algorithmic Solutions +AI10569,Research Scientist,118839,AUD,160433,MI,FL,Australia,L,Australia,50,"PyTorch, TensorFlow, GCP, Spark",Master,4,Automotive,2024-04-22,2024-05-25,963,8,TechCorp Inc +AI10570,Robotics Engineer,72716,EUR,61809,EN,FL,Germany,L,Germany,100,"GCP, Python, Data Visualization, TensorFlow, Computer Vision",Bachelor,0,Transportation,2024-07-03,2024-07-27,501,7.8,Smart Analytics +AI10571,Data Scientist,126408,USD,126408,MI,FT,United States,L,Nigeria,0,"R, Python, NLP, Hadoop, Deep Learning",Master,4,Retail,2024-08-10,2024-10-13,1126,5.1,Neural Networks Co +AI10572,AI Research Scientist,116295,EUR,98851,MI,CT,Netherlands,M,Netherlands,100,"SQL, Deep Learning, PyTorch, Git, GCP",Bachelor,4,Telecommunications,2024-06-04,2024-07-25,991,7.3,Digital Transformation LLC +AI10573,AI Architect,104716,EUR,89009,MI,CT,Germany,L,New Zealand,50,"Kubernetes, Docker, Git",Master,3,Media,2025-02-07,2025-04-15,688,7.5,Advanced Robotics +AI10574,AI Product Manager,130494,JPY,14354340,MI,FT,Japan,L,Japan,0,"Kubernetes, TensorFlow, Python",Bachelor,4,Technology,2025-01-27,2025-04-06,1863,7.8,Quantum Computing Inc +AI10575,ML Ops Engineer,150085,AUD,202615,SE,CT,Australia,L,Australia,100,"AWS, Azure, Python, Java, MLOps",Master,5,Automotive,2024-05-03,2024-07-07,523,8.6,DataVision Ltd +AI10576,Deep Learning Engineer,45879,USD,45879,SE,PT,India,S,Latvia,50,"R, GCP, PyTorch, Computer Vision, Statistics",Bachelor,6,Government,2024-01-29,2024-02-25,2273,7.7,Cloud AI Solutions +AI10577,Data Scientist,108528,USD,108528,MI,CT,Denmark,L,Latvia,50,"Git, Kubernetes, Java",PhD,3,Consulting,2024-10-30,2025-01-04,1012,10,DeepTech Ventures +AI10578,Autonomous Systems Engineer,191897,EUR,163112,EX,FL,Austria,L,China,100,"R, SQL, Deep Learning",PhD,19,Automotive,2025-02-18,2025-04-19,1240,5.1,Algorithmic Solutions +AI10579,AI Software Engineer,93358,USD,93358,MI,PT,Norway,S,Norway,50,"Statistics, Kubernetes, NLP, GCP",Associate,4,Technology,2024-04-08,2024-05-16,909,6.4,Predictive Systems +AI10580,Data Engineer,31111,USD,31111,MI,CT,India,M,Argentina,100,"Spark, Kubernetes, Mathematics",PhD,3,Gaming,2024-09-21,2024-11-08,2004,5.8,Predictive Systems +AI10581,NLP Engineer,275338,AUD,371706,EX,CT,Australia,L,Australia,50,"Docker, Data Visualization, Java, Spark",PhD,19,Media,2024-06-14,2024-08-08,784,8.5,AI Innovations +AI10582,AI Consultant,147650,USD,147650,SE,FL,Ireland,L,Ireland,100,"GCP, Kubernetes, PyTorch, Scala, Deep Learning",Master,8,Automotive,2024-09-15,2024-10-03,1084,5.9,Predictive Systems +AI10583,Data Scientist,204393,GBP,153295,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, GCP, Data Visualization",Bachelor,18,Gaming,2025-01-17,2025-02-02,1818,5.9,Cognitive Computing +AI10584,Data Engineer,63051,USD,63051,EN,CT,South Korea,M,South Korea,0,"Git, Java, NLP",Master,1,Energy,2024-10-26,2024-11-24,509,6.6,Smart Analytics +AI10585,Computer Vision Engineer,68170,JPY,7498700,EN,FT,Japan,M,Singapore,0,"Kubernetes, TensorFlow, GCP",Associate,1,Telecommunications,2025-01-08,2025-03-12,2423,6.7,Future Systems +AI10586,Principal Data Scientist,63760,GBP,47820,EN,PT,United Kingdom,L,United Kingdom,0,"Python, Kubernetes, TensorFlow, Scala",Associate,0,Technology,2024-02-04,2024-03-05,1911,6.2,Future Systems +AI10587,Machine Learning Engineer,93851,USD,93851,MI,FL,United States,S,Switzerland,0,"TensorFlow, Scala, GCP, SQL",Master,3,Gaming,2025-04-23,2025-06-22,2028,8.4,Smart Analytics +AI10588,Data Scientist,125553,USD,125553,SE,PT,United States,S,United States,50,"Java, GCP, Azure",Master,6,Education,2024-10-31,2024-11-29,1036,8.1,AI Innovations +AI10589,Computer Vision Engineer,56723,CAD,70904,EN,FT,Canada,L,Canada,100,"Tableau, Python, Kubernetes, Scala",Associate,1,Gaming,2024-11-08,2024-11-25,1997,6.6,Digital Transformation LLC +AI10590,AI Product Manager,78007,USD,78007,EN,CT,United States,S,United States,50,"Azure, Spark, MLOps, Tableau",Bachelor,1,Finance,2024-03-01,2024-03-17,2122,9.3,Advanced Robotics +AI10591,Data Scientist,230768,USD,230768,EX,CT,Finland,L,Spain,50,"MLOps, Scala, TensorFlow, Mathematics",PhD,17,Media,2024-06-26,2024-07-29,1798,8.4,Cognitive Computing +AI10592,Data Scientist,61453,USD,61453,EN,CT,Israel,S,Israel,100,"Java, Python, Git",Bachelor,0,Energy,2024-07-09,2024-08-07,671,9.4,Predictive Systems +AI10593,Robotics Engineer,86143,CAD,107679,MI,PT,Canada,S,Canada,50,"Hadoop, NLP, Scala",Master,2,Manufacturing,2025-01-03,2025-03-05,1242,6.6,TechCorp Inc +AI10594,Head of AI,60433,CAD,75541,EN,FT,Canada,L,Brazil,50,"Java, Kubernetes, MLOps, Computer Vision",Associate,0,Education,2024-08-29,2024-09-21,613,5.9,Quantum Computing Inc +AI10595,AI Architect,71504,EUR,60778,MI,FL,Austria,M,Austria,50,"PyTorch, Git, Kubernetes, Deep Learning, Scala",Bachelor,2,Finance,2024-11-17,2025-01-23,1193,5.3,Autonomous Tech +AI10596,Deep Learning Engineer,141331,CAD,176664,SE,FT,Canada,M,Canada,0,"SQL, Python, GCP, Java, TensorFlow",PhD,9,Consulting,2024-08-25,2024-11-06,2124,5.7,Machine Intelligence Group +AI10597,Data Scientist,182504,JPY,20075440,SE,PT,Japan,L,Finland,100,"Spark, Tableau, Deep Learning, SQL",Associate,5,Finance,2024-09-24,2024-11-09,2236,8.1,Advanced Robotics +AI10598,Data Analyst,32356,USD,32356,MI,FT,China,S,China,50,"NLP, SQL, Scala",PhD,2,Retail,2024-06-06,2024-06-24,1316,8,Neural Networks Co +AI10599,AI Specialist,212698,AUD,287142,EX,FL,Australia,S,Australia,50,"Scala, Git, SQL",Associate,16,Gaming,2024-06-28,2024-08-26,1759,5.3,Future Systems +AI10600,AI Software Engineer,159697,EUR,135742,EX,PT,France,M,France,0,"Linux, Python, R",Bachelor,11,Media,2024-06-17,2024-08-23,2236,9.1,Predictive Systems +AI10601,Principal Data Scientist,104312,USD,104312,EN,CT,United States,L,Australia,0,"Docker, Linux, PyTorch, Data Visualization",Associate,1,Education,2024-09-07,2024-10-06,1298,7.9,Smart Analytics +AI10602,Machine Learning Researcher,80606,USD,80606,EN,FL,Sweden,M,Sweden,50,"Scala, Git, Data Visualization, Mathematics, SQL",PhD,1,Energy,2024-08-06,2024-09-03,721,6.8,Digital Transformation LLC +AI10603,AI Specialist,123309,EUR,104813,SE,FT,Germany,M,United Kingdom,0,"Java, Docker, GCP",Master,7,Media,2024-11-26,2025-01-27,1603,9.3,Future Systems +AI10604,AI Architect,278484,AUD,375953,EX,FL,Australia,L,Norway,0,"Linux, Scala, Git, Python, TensorFlow",Bachelor,14,Education,2025-04-29,2025-05-24,605,8.6,DataVision Ltd +AI10605,NLP Engineer,88219,USD,88219,MI,FT,Ireland,L,Ireland,50,"Python, Linux, Kubernetes",PhD,2,Education,2025-03-04,2025-04-25,963,9.6,Cloud AI Solutions +AI10606,ML Ops Engineer,85752,CHF,77177,EN,FL,Switzerland,S,Canada,100,"Python, TensorFlow, Git, PyTorch, NLP",Master,1,Retail,2024-04-26,2024-06-06,1245,7.8,AI Innovations +AI10607,ML Ops Engineer,152528,USD,152528,SE,FT,Sweden,M,Argentina,100,"NLP, Azure, Java",Associate,5,Healthcare,2024-11-28,2024-12-19,1606,9.8,Advanced Robotics +AI10608,Principal Data Scientist,79883,EUR,67901,MI,PT,Austria,S,Austria,0,"Python, MLOps, TensorFlow, Computer Vision, Statistics",PhD,3,Real Estate,2024-01-25,2024-03-31,635,6.9,Future Systems +AI10609,Data Analyst,71938,USD,71938,MI,PT,Israel,M,United Kingdom,100,"Azure, Spark, Scala, Mathematics, Python",Bachelor,4,Media,2025-02-15,2025-03-31,1038,5.6,Smart Analytics +AI10610,AI Architect,187859,USD,187859,EX,PT,South Korea,M,South Korea,100,"Hadoop, R, PyTorch, SQL",PhD,13,Government,2025-03-13,2025-04-30,991,8.2,TechCorp Inc +AI10611,Research Scientist,80473,USD,80473,SE,FL,South Korea,S,South Korea,100,"NLP, AWS, Java, Computer Vision, Python",Bachelor,6,Consulting,2024-04-15,2024-05-04,2365,7.2,DataVision Ltd +AI10612,Machine Learning Engineer,150968,EUR,128323,SE,FL,Germany,L,Turkey,100,"Python, Scala, TensorFlow, Deep Learning, Java",Master,8,Gaming,2024-03-14,2024-05-18,953,6,Cognitive Computing +AI10613,AI Software Engineer,117941,USD,117941,MI,CT,Finland,L,Denmark,100,"R, Spark, Data Visualization, Deep Learning, Azure",PhD,4,Energy,2024-04-10,2024-06-03,786,9.1,Autonomous Tech +AI10614,AI Software Engineer,67317,USD,67317,EN,CT,Denmark,S,Russia,50,"Docker, Spark, R, GCP",Bachelor,0,Healthcare,2024-01-02,2024-03-04,2454,7.2,AI Innovations +AI10615,Data Engineer,120964,EUR,102819,SE,PT,Netherlands,M,Luxembourg,0,"R, Java, SQL",PhD,8,Healthcare,2024-01-24,2024-02-29,1395,8.5,TechCorp Inc +AI10616,Head of AI,147747,CHF,132972,MI,CT,Switzerland,L,Switzerland,50,"Scala, Spark, Data Visualization",Master,4,Transportation,2024-03-04,2024-03-26,1292,5.9,Algorithmic Solutions +AI10617,Computer Vision Engineer,144492,AUD,195064,SE,PT,Australia,L,Australia,50,"Java, Spark, TensorFlow, Hadoop, Scala",Associate,9,Manufacturing,2025-04-06,2025-06-12,2186,5.3,Algorithmic Solutions +AI10618,Machine Learning Engineer,245526,USD,245526,EX,FT,United States,S,Israel,100,"Python, Git, Kubernetes",Bachelor,12,Manufacturing,2025-02-28,2025-03-19,1919,5.4,Autonomous Tech +AI10619,Machine Learning Researcher,118930,GBP,89198,SE,FL,United Kingdom,S,United Kingdom,100,"GCP, NLP, Hadoop, Python, Scala",Master,8,Technology,2024-02-06,2024-03-12,2485,6.4,Autonomous Tech +AI10620,Data Scientist,173914,USD,173914,SE,PT,United States,L,United States,100,"Scala, Java, NLP, PyTorch, SQL",Bachelor,9,Telecommunications,2024-01-06,2024-02-15,1015,8.9,AI Innovations +AI10621,AI Architect,46392,EUR,39433,EN,FT,Germany,S,Latvia,100,"NLP, Azure, Linux, Kubernetes, Data Visualization",PhD,1,Finance,2024-06-08,2024-06-27,2495,7.9,DeepTech Ventures +AI10622,AI Product Manager,97856,USD,97856,SE,FT,Ireland,S,Ireland,50,"Python, Scala, Spark, GCP, Linux",Bachelor,8,Gaming,2024-06-17,2024-07-05,938,9.4,DeepTech Ventures +AI10623,Machine Learning Engineer,118261,EUR,100522,SE,FT,Germany,S,Germany,0,"MLOps, Git, Kubernetes, NLP",Master,6,Energy,2024-04-25,2024-05-24,1937,8.4,AI Innovations +AI10624,Deep Learning Engineer,85135,EUR,72365,MI,PT,France,M,France,50,"Scala, Spark, Git",Bachelor,3,Technology,2024-07-10,2024-08-30,967,7.4,Cognitive Computing +AI10625,Machine Learning Researcher,178627,AUD,241146,EX,FL,Australia,L,Austria,0,"Python, Deep Learning, Tableau",Bachelor,12,Transportation,2025-02-27,2025-04-23,1070,7.9,Quantum Computing Inc +AI10626,AI Specialist,95464,USD,95464,MI,FL,Sweden,S,Germany,100,"Scala, Java, AWS",Bachelor,3,Finance,2024-12-19,2025-02-11,629,9.5,Predictive Systems +AI10627,Deep Learning Engineer,91229,AUD,123159,EN,PT,Australia,L,Australia,0,"Azure, SQL, Tableau",Associate,0,Energy,2024-08-15,2024-09-26,1126,9.2,Cloud AI Solutions +AI10628,Research Scientist,192344,USD,192344,EX,FL,Sweden,S,Sweden,100,"TensorFlow, GCP, SQL, Docker, Git",Master,14,Automotive,2024-02-19,2024-03-10,2148,9.4,Predictive Systems +AI10629,Data Analyst,47789,USD,47789,EN,CT,Israel,S,Israel,100,"SQL, Linux, PyTorch, Git",Associate,0,Finance,2025-01-05,2025-01-26,1422,6,Predictive Systems +AI10630,Machine Learning Engineer,129729,EUR,110270,SE,FT,Germany,M,Germany,50,"Docker, Linux, Spark, Python",Associate,8,Technology,2024-02-05,2024-03-31,1715,7.5,TechCorp Inc +AI10631,AI Software Engineer,72974,USD,72974,MI,FT,South Korea,S,Canada,50,"Linux, Spark, Python, NLP, TensorFlow",PhD,2,Transportation,2024-03-07,2024-04-28,2093,9.4,Advanced Robotics +AI10632,Computer Vision Engineer,140615,EUR,119523,SE,FT,France,L,France,50,"PyTorch, Computer Vision, R, Scala, AWS",Bachelor,8,Manufacturing,2025-01-30,2025-02-27,876,5.4,Autonomous Tech +AI10633,Data Engineer,111490,SGD,144937,MI,FL,Singapore,M,Singapore,0,"Python, NLP, TensorFlow",PhD,4,Retail,2024-08-30,2024-10-18,1663,6.3,Predictive Systems +AI10634,Deep Learning Engineer,61103,GBP,45827,EN,FL,United Kingdom,S,United Kingdom,50,"Spark, Docker, Python, Deep Learning",PhD,1,Media,2025-01-23,2025-02-23,1769,5.6,Algorithmic Solutions +AI10635,AI Product Manager,116733,USD,116733,EX,CT,Israel,S,Israel,100,"Azure, Scala, MLOps, Python",Master,18,Media,2025-04-25,2025-05-14,1365,6.7,Machine Intelligence Group +AI10636,AI Specialist,283444,USD,283444,EX,PT,Ireland,L,Latvia,0,"SQL, Scala, R, Docker, Deep Learning",Associate,12,Government,2025-04-11,2025-05-02,2143,7.8,AI Innovations +AI10637,AI Architect,107069,EUR,91009,MI,FT,Netherlands,M,South Korea,100,"Python, TensorFlow, GCP",Master,2,Energy,2025-03-05,2025-04-09,1179,8.7,TechCorp Inc +AI10638,AI Consultant,73972,USD,73972,EN,PT,Israel,M,Israel,100,"Docker, MLOps, Mathematics, Linux",Master,0,Media,2024-06-10,2024-07-28,1551,9.9,DataVision Ltd +AI10639,AI Product Manager,52290,JPY,5751900,EN,PT,Japan,S,Japan,0,"NLP, Azure, Mathematics",Bachelor,1,Energy,2024-07-09,2024-09-10,1815,5.8,Advanced Robotics +AI10640,AI Product Manager,204367,CAD,255459,EX,CT,Canada,M,Canada,100,"AWS, Java, Azure, TensorFlow, Linux",Bachelor,15,Healthcare,2024-10-25,2024-11-23,1798,5.2,Smart Analytics +AI10641,Autonomous Systems Engineer,91739,JPY,10091290,MI,CT,Japan,M,Japan,50,"Statistics, R, Python, MLOps, GCP",Bachelor,3,Gaming,2025-01-25,2025-03-08,902,5.1,Autonomous Tech +AI10642,AI Specialist,52164,SGD,67813,EN,PT,Singapore,S,Singapore,100,"R, GCP, Computer Vision",Master,1,Retail,2024-10-23,2024-11-22,2141,5.9,Cognitive Computing +AI10643,Data Analyst,135990,EUR,115592,SE,FL,France,L,France,0,"Tableau, Java, SQL, Azure",Associate,7,Government,2024-10-23,2024-12-17,1398,8.2,Cloud AI Solutions +AI10644,Autonomous Systems Engineer,180546,GBP,135410,SE,CT,United Kingdom,L,United Kingdom,0,"Hadoop, SQL, Spark, Kubernetes",Bachelor,9,Gaming,2025-02-18,2025-03-06,1432,8.4,TechCorp Inc +AI10645,Data Analyst,173391,EUR,147382,EX,PT,France,S,Luxembourg,100,"Java, Python, Mathematics, GCP, Linux",Associate,16,Government,2024-08-24,2024-11-02,2082,8.5,Digital Transformation LLC +AI10646,AI Consultant,131162,JPY,14427820,SE,CT,Japan,S,India,100,"GCP, Azure, Spark, Data Visualization",PhD,5,Technology,2024-05-01,2024-07-03,2200,5.5,DeepTech Ventures +AI10647,Autonomous Systems Engineer,83876,USD,83876,EN,CT,Israel,L,Israel,100,"Python, GCP, Deep Learning, TensorFlow, Data Visualization",Master,1,Consulting,2024-12-27,2025-02-21,524,9.9,DeepTech Ventures +AI10648,AI Product Manager,120528,USD,120528,SE,CT,Denmark,S,Ghana,0,"Java, Python, Linux",Bachelor,5,Consulting,2024-09-05,2024-10-28,675,8.1,Advanced Robotics +AI10649,Head of AI,20105,USD,20105,EN,PT,India,S,India,100,"Java, PyTorch, MLOps, Data Visualization, Linux",Associate,1,Energy,2025-01-08,2025-01-28,926,9.6,Autonomous Tech +AI10650,Computer Vision Engineer,99524,EUR,84595,MI,PT,Austria,M,Austria,0,"GCP, SQL, Tableau, PyTorch",Master,2,Government,2025-01-24,2025-02-08,2434,9.2,Algorithmic Solutions +AI10651,Research Scientist,97168,EUR,82593,EN,FT,Netherlands,L,Australia,0,"Python, TensorFlow, Docker, Statistics, SQL",Bachelor,1,Manufacturing,2025-02-22,2025-04-26,1604,9.4,Advanced Robotics +AI10652,Machine Learning Researcher,79501,AUD,107326,MI,PT,Australia,S,Austria,0,"R, Hadoop, AWS, Docker",Master,3,Energy,2024-05-09,2024-05-23,1453,8.1,DeepTech Ventures +AI10653,NLP Engineer,80406,GBP,60305,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Python",Associate,0,Technology,2025-02-15,2025-04-28,1482,6,DataVision Ltd +AI10654,Principal Data Scientist,179168,SGD,232918,SE,FL,Singapore,L,Singapore,50,"SQL, PyTorch, Java, GCP",Master,5,Manufacturing,2024-07-30,2024-09-23,2303,5.6,Smart Analytics +AI10655,Machine Learning Researcher,117302,USD,117302,SE,FT,United States,S,United States,50,"Docker, Deep Learning, Kubernetes, R, SQL",Bachelor,7,Finance,2025-04-07,2025-06-05,1833,8.9,Predictive Systems +AI10656,Machine Learning Researcher,24496,USD,24496,EN,CT,China,S,Netherlands,0,"Java, Computer Vision, Kubernetes",Associate,1,Telecommunications,2024-04-07,2024-06-16,1991,9.8,Advanced Robotics +AI10657,AI Consultant,136071,GBP,102053,EX,CT,United Kingdom,S,United Kingdom,100,"Python, SQL, GCP, Hadoop, Spark",Associate,16,Real Estate,2025-03-27,2025-04-18,965,7.4,Cognitive Computing +AI10658,Robotics Engineer,238120,USD,238120,EX,PT,Sweden,L,Sweden,50,"Java, Docker, Mathematics, Git, Data Visualization",Master,16,Education,2024-02-25,2024-03-13,1211,8,DeepTech Ventures +AI10659,ML Ops Engineer,156352,JPY,17198720,SE,CT,Japan,M,Belgium,100,"Java, Kubernetes, GCP, Mathematics, TensorFlow",Associate,7,Finance,2024-12-10,2025-01-30,1328,7.7,Cognitive Computing +AI10660,Computer Vision Engineer,36448,USD,36448,EN,FL,China,L,China,0,"TensorFlow, Git, Python, GCP, SQL",Master,0,Healthcare,2024-02-06,2024-04-06,501,7.3,Smart Analytics +AI10661,ML Ops Engineer,225966,USD,225966,EX,FL,South Korea,L,South Korea,50,"R, Git, Tableau",Associate,14,Media,2024-09-11,2024-11-14,661,7,Quantum Computing Inc +AI10662,AI Specialist,30284,USD,30284,MI,CT,India,M,India,0,"Hadoop, Spark, MLOps, Git, Linux",PhD,3,Healthcare,2024-09-21,2024-11-24,2167,8.6,Autonomous Tech +AI10663,Research Scientist,202712,USD,202712,EX,FL,Denmark,S,Chile,100,"GCP, Kubernetes, AWS, R, Spark",Bachelor,12,Automotive,2024-08-20,2024-10-13,1609,5.7,TechCorp Inc +AI10664,AI Research Scientist,166959,USD,166959,EX,FT,Finland,M,Canada,50,"PyTorch, AWS, Azure",Associate,10,Finance,2024-12-21,2025-02-20,850,5.5,Quantum Computing Inc +AI10665,AI Consultant,122284,EUR,103941,SE,PT,France,S,South Africa,100,"MLOps, Python, TensorFlow",PhD,6,Telecommunications,2024-09-30,2024-11-21,1211,8.9,Algorithmic Solutions +AI10666,Head of AI,116235,USD,116235,SE,CT,Ireland,S,Brazil,100,"R, Java, Tableau, MLOps",Master,8,Healthcare,2024-10-27,2024-11-16,973,8.6,Advanced Robotics +AI10667,Head of AI,202957,USD,202957,EX,PT,Sweden,M,Sweden,0,"Git, Docker, Deep Learning, TensorFlow",PhD,19,Energy,2024-08-13,2024-09-02,2052,5.2,Algorithmic Solutions +AI10668,AI Consultant,79718,JPY,8768980,MI,FT,Japan,S,Portugal,100,"Tableau, Spark, Hadoop",Master,3,Real Estate,2024-11-22,2025-01-06,1868,5.3,Cognitive Computing +AI10669,Robotics Engineer,125746,GBP,94310,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, PyTorch, Mathematics",Master,9,Real Estate,2024-02-26,2024-03-16,919,7,Neural Networks Co +AI10670,AI Specialist,154306,GBP,115730,SE,FT,United Kingdom,M,United Kingdom,0,"Docker, MLOps, PyTorch, Spark",Bachelor,9,Transportation,2024-08-31,2024-09-17,987,9.6,Cloud AI Solutions +AI10671,AI Consultant,86374,EUR,73418,MI,CT,Netherlands,M,Norway,100,"MLOps, Git, GCP",Bachelor,4,Finance,2024-10-01,2024-11-08,558,6.8,DataVision Ltd +AI10672,ML Ops Engineer,113235,USD,113235,SE,FT,Finland,M,Switzerland,0,"GCP, Mathematics, Computer Vision",Master,8,Manufacturing,2024-03-08,2024-05-01,1365,7.5,Digital Transformation LLC +AI10673,Data Analyst,266149,USD,266149,EX,FT,Denmark,S,Denmark,100,"Data Visualization, Spark, NLP, Hadoop, Deep Learning",Master,16,Telecommunications,2024-02-10,2024-03-25,595,6.4,Algorithmic Solutions +AI10674,Head of AI,77319,JPY,8505090,MI,FL,Japan,S,Japan,0,"Git, MLOps, TensorFlow, Kubernetes",PhD,3,Transportation,2024-06-20,2024-07-17,1217,7.9,Algorithmic Solutions +AI10675,Data Engineer,74543,USD,74543,MI,FT,South Korea,M,South Korea,0,"Java, Python, Tableau, Azure, Hadoop",Bachelor,4,Finance,2024-11-18,2025-01-30,1362,9.3,TechCorp Inc +AI10676,AI Specialist,51768,SGD,67298,EN,FL,Singapore,S,Singapore,100,"Docker, AWS, Kubernetes, Tableau",PhD,0,Energy,2025-04-30,2025-06-05,1526,9.2,AI Innovations +AI10677,Autonomous Systems Engineer,213531,USD,213531,EX,PT,Norway,S,Norway,50,"AWS, Data Visualization, Docker, GCP, Python",Master,18,Consulting,2024-05-30,2024-07-20,885,8.5,AI Innovations +AI10678,AI Research Scientist,195386,GBP,146540,EX,FT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, SQL, Linux",Bachelor,14,Telecommunications,2025-01-05,2025-03-05,2185,5.4,Machine Intelligence Group +AI10679,Data Engineer,91835,USD,91835,EX,CT,China,L,China,50,"Linux, Mathematics, NLP, Python",PhD,19,Gaming,2024-10-21,2024-12-01,985,6.2,Cloud AI Solutions +AI10680,AI Research Scientist,95351,EUR,81048,SE,PT,Germany,S,Germany,50,"Spark, SQL, Deep Learning, NLP",Associate,9,Healthcare,2024-08-05,2024-10-13,2260,5,DataVision Ltd +AI10681,Robotics Engineer,89630,USD,89630,MI,CT,Finland,L,Finland,0,"Deep Learning, SQL, Computer Vision",PhD,2,Government,2024-07-21,2024-08-27,1413,9.3,Future Systems +AI10682,Computer Vision Engineer,70678,EUR,60076,MI,PT,Germany,S,Germany,0,"TensorFlow, AWS, Linux, MLOps, Azure",Associate,3,Automotive,2024-04-30,2024-06-18,2104,8,DataVision Ltd +AI10683,Computer Vision Engineer,134959,JPY,14845490,SE,CT,Japan,M,Kenya,100,"GCP, Java, Linux",Bachelor,9,Finance,2024-10-29,2025-01-07,1173,6,Advanced Robotics +AI10684,Head of AI,38645,USD,38645,SE,FL,India,S,India,100,"TensorFlow, Docker, SQL, MLOps",PhD,7,Transportation,2025-01-25,2025-03-26,2358,6.5,DataVision Ltd +AI10685,Machine Learning Engineer,156721,JPY,17239310,EX,FT,Japan,M,Japan,50,"NLP, Git, Deep Learning, Python",PhD,18,Education,2024-03-30,2024-06-10,1357,7.7,Machine Intelligence Group +AI10686,Computer Vision Engineer,60173,USD,60173,EN,PT,Sweden,S,Sweden,50,"TensorFlow, Scala, Java, Statistics",Master,1,Government,2024-06-25,2024-07-26,2352,8.5,AI Innovations +AI10687,Machine Learning Researcher,61314,USD,61314,MI,FT,South Korea,S,South Korea,50,"Python, Docker, Tableau",PhD,2,Manufacturing,2024-02-18,2024-04-27,1801,9.7,Cloud AI Solutions +AI10688,Autonomous Systems Engineer,151060,USD,151060,EX,CT,Israel,S,Israel,100,"Azure, Docker, Python",Master,13,Technology,2025-03-28,2025-05-27,2382,9,Quantum Computing Inc +AI10689,Robotics Engineer,78798,SGD,102437,MI,FL,Singapore,M,Singapore,50,"Data Visualization, PyTorch, Git, Docker",Associate,2,Government,2024-10-22,2024-12-02,2429,7.9,Predictive Systems +AI10690,Principal Data Scientist,28501,USD,28501,MI,FL,India,M,India,100,"Data Visualization, TensorFlow, Python, Scala",Bachelor,3,Gaming,2024-09-26,2024-10-16,2203,7.1,Advanced Robotics +AI10691,Data Scientist,147112,USD,147112,SE,FL,Denmark,M,Denmark,0,"SQL, GCP, Java, Statistics",Associate,7,Retail,2024-02-24,2024-03-23,2407,5.9,Future Systems +AI10692,Machine Learning Engineer,57860,EUR,49181,EN,FT,Austria,L,Finland,50,"Data Visualization, Tableau, Spark, Python, Hadoop",Master,0,Transportation,2024-03-13,2024-04-01,2104,5.7,Neural Networks Co +AI10693,Autonomous Systems Engineer,124336,JPY,13676960,SE,CT,Japan,L,Norway,100,"Docker, GCP, MLOps",Bachelor,6,Transportation,2024-04-02,2024-05-23,1518,6.2,AI Innovations +AI10694,Machine Learning Researcher,52712,EUR,44805,EN,FT,France,M,France,50,"Scala, Hadoop, Statistics, Azure, PyTorch",PhD,0,Energy,2024-08-21,2024-11-01,1117,5.2,TechCorp Inc +AI10695,NLP Engineer,151816,CHF,136634,SE,FL,Switzerland,S,Switzerland,100,"R, Scala, Statistics",PhD,8,Automotive,2024-12-18,2025-02-09,680,7.8,Autonomous Tech +AI10696,Data Engineer,136528,USD,136528,EX,PT,China,L,China,0,"Kubernetes, Java, MLOps",Associate,14,Transportation,2024-05-12,2024-06-17,2317,7.3,Advanced Robotics +AI10697,AI Software Engineer,117912,EUR,100225,SE,PT,France,L,France,50,"SQL, Docker, NLP, Statistics",Bachelor,6,Finance,2025-02-02,2025-04-04,2357,8.2,Machine Intelligence Group +AI10698,AI Consultant,152584,EUR,129696,EX,FT,Austria,S,Austria,0,"PyTorch, Docker, Data Visualization, AWS",PhD,16,Technology,2024-09-16,2024-10-23,1903,6.7,Neural Networks Co +AI10699,AI Software Engineer,148386,USD,148386,MI,FL,United States,L,Kenya,50,"AWS, Python, Statistics",PhD,4,Government,2025-03-01,2025-05-06,832,9.3,Neural Networks Co +AI10700,NLP Engineer,170113,USD,170113,SE,FT,United States,M,United States,100,"Data Visualization, Azure, Java, NLP, Hadoop",PhD,5,Automotive,2024-04-09,2024-05-30,2437,9.4,Algorithmic Solutions +AI10701,Data Engineer,76774,EUR,65258,MI,FL,Germany,M,Hungary,0,"Kubernetes, Statistics, Azure, Deep Learning, SQL",Associate,4,Healthcare,2025-03-29,2025-04-20,876,8.2,DeepTech Ventures +AI10702,AI Software Engineer,104215,USD,104215,EN,FT,Norway,L,Norway,50,"PyTorch, TensorFlow, Tableau, Java, Mathematics",Master,1,Government,2024-05-17,2024-06-26,869,9,Cognitive Computing +AI10703,NLP Engineer,214317,USD,214317,EX,FL,Denmark,S,Russia,50,"Statistics, Scala, Kubernetes, GCP",Bachelor,19,Transportation,2025-04-04,2025-06-10,1517,6.9,DeepTech Ventures +AI10704,Data Scientist,134618,EUR,114425,SE,PT,Austria,M,Austria,0,"Mathematics, GCP, PyTorch, TensorFlow",Master,5,Energy,2025-03-25,2025-05-15,1450,9.9,AI Innovations +AI10705,AI Software Engineer,73195,USD,73195,EN,CT,Ireland,L,Vietnam,100,"GCP, Scala, Mathematics",Associate,1,Finance,2024-08-03,2024-10-09,1283,8,Digital Transformation LLC +AI10706,Computer Vision Engineer,116013,USD,116013,SE,PT,Sweden,S,Austria,0,"Spark, PyTorch, NLP, Java",Bachelor,6,Gaming,2024-02-09,2024-03-20,2305,9.4,TechCorp Inc +AI10707,AI Specialist,129732,JPY,14270520,SE,PT,Japan,L,Japan,50,"Computer Vision, Deep Learning, Linux",Master,8,Real Estate,2024-06-01,2024-06-15,2326,6,Cloud AI Solutions +AI10708,AI Specialist,250954,GBP,188216,EX,FT,United Kingdom,L,United Kingdom,100,"Scala, MLOps, Linux, Kubernetes",Master,19,Media,2025-04-23,2025-05-11,1862,5.9,Autonomous Tech +AI10709,Data Scientist,64591,CAD,80739,EN,CT,Canada,L,Canada,100,"Azure, Scala, R",Bachelor,1,Retail,2024-01-21,2024-02-15,2126,9,Autonomous Tech +AI10710,Data Engineer,117699,USD,117699,SE,FT,Ireland,M,Ireland,100,"Docker, Python, SQL",Associate,7,Retail,2024-08-08,2024-10-07,1819,9.9,Future Systems +AI10711,NLP Engineer,111868,USD,111868,EX,FT,China,L,China,50,"Linux, Git, R, Docker",Master,13,Gaming,2024-06-05,2024-07-18,1727,5.4,Autonomous Tech +AI10712,Research Scientist,143592,USD,143592,SE,PT,United States,S,United States,50,"Computer Vision, Hadoop, Tableau",PhD,5,Finance,2024-01-10,2024-03-23,2454,7.9,Autonomous Tech +AI10713,AI Specialist,112805,EUR,95884,MI,FL,Austria,L,Austria,100,"Python, Hadoop, AWS, Statistics",PhD,4,Education,2024-01-04,2024-01-30,2148,8.7,TechCorp Inc +AI10714,AI Architect,161399,USD,161399,EX,FT,Israel,L,Israel,0,"Java, NLP, SQL",PhD,10,Manufacturing,2024-09-19,2024-11-24,1789,7.8,Autonomous Tech +AI10715,AI Architect,243356,USD,243356,EX,FL,Norway,S,Norway,0,"NLP, Scala, R",Master,14,Transportation,2024-05-12,2024-06-12,1489,5.6,Cognitive Computing +AI10716,Principal Data Scientist,91224,USD,91224,MI,CT,Israel,L,Canada,50,"PyTorch, GCP, AWS",Bachelor,2,Manufacturing,2024-07-30,2024-10-10,1336,8.1,Neural Networks Co +AI10717,Data Engineer,42308,USD,42308,MI,FL,China,M,China,50,"Java, SQL, Docker",PhD,2,Gaming,2024-11-19,2025-01-08,764,7.9,AI Innovations +AI10718,AI Research Scientist,44344,USD,44344,MI,PT,China,L,China,100,"Scala, Mathematics, Deep Learning, Data Visualization, PyTorch",Associate,2,Transportation,2025-01-27,2025-03-06,1050,7.7,Quantum Computing Inc +AI10719,AI Consultant,176796,EUR,150277,EX,FT,France,M,France,50,"Python, Docker, Deep Learning, TensorFlow, NLP",Associate,12,Manufacturing,2024-02-26,2024-04-14,1400,9.1,Neural Networks Co +AI10720,Data Analyst,128958,JPY,14185380,SE,CT,Japan,L,Ireland,100,"Python, Git, Docker, Mathematics, Tableau",PhD,5,Retail,2024-06-05,2024-07-24,1906,5.9,Predictive Systems +AI10721,AI Research Scientist,38734,USD,38734,SE,CT,India,S,India,50,"Azure, MLOps, Statistics, Docker",PhD,9,Retail,2024-09-11,2024-09-25,698,9.4,AI Innovations +AI10722,Robotics Engineer,139670,GBP,104753,SE,CT,United Kingdom,M,Canada,0,"Python, Scala, MLOps, AWS",PhD,6,Media,2024-06-22,2024-07-07,1717,6.3,Algorithmic Solutions +AI10723,Principal Data Scientist,151422,EUR,128709,EX,CT,Germany,S,Germany,0,"PyTorch, TensorFlow, R, Linux, Mathematics",PhD,14,Automotive,2025-02-08,2025-03-20,590,7.3,Digital Transformation LLC +AI10724,Computer Vision Engineer,59521,EUR,50593,EN,CT,Netherlands,S,Netherlands,50,"Scala, R, NLP, MLOps",Bachelor,0,Real Estate,2024-09-08,2024-09-26,1095,7.3,DeepTech Ventures +AI10725,ML Ops Engineer,71064,USD,71064,MI,FT,South Korea,M,South Korea,50,"Java, Python, R, Mathematics, PyTorch",PhD,2,Consulting,2024-06-22,2024-08-18,1716,8.6,Future Systems +AI10726,Data Scientist,226728,EUR,192719,EX,CT,France,L,France,100,"Java, MLOps, TensorFlow, Computer Vision",Associate,16,Transportation,2024-06-02,2024-06-18,971,7.2,Cognitive Computing +AI10727,Machine Learning Researcher,112137,CAD,140171,MI,FL,Canada,L,Canada,50,"TensorFlow, Linux, Computer Vision, Git, Java",Associate,4,Retail,2025-04-21,2025-05-21,2367,7.8,AI Innovations +AI10728,Machine Learning Engineer,127819,CAD,159774,SE,CT,Canada,L,Germany,100,"Python, SQL, Scala, Computer Vision",PhD,5,Healthcare,2025-04-05,2025-05-31,2077,9.2,DataVision Ltd +AI10729,Data Analyst,96910,JPY,10660100,MI,FL,Japan,M,Japan,0,"SQL, AWS, GCP",Associate,2,Consulting,2024-02-23,2024-04-02,1569,7.9,Machine Intelligence Group +AI10730,Autonomous Systems Engineer,80604,USD,80604,EX,CT,India,L,Singapore,50,"Python, Mathematics, Tableau",Associate,11,Media,2024-04-19,2024-06-17,897,5.4,DataVision Ltd +AI10731,Head of AI,104712,USD,104712,SE,CT,Ireland,S,Argentina,0,"Kubernetes, Python, AWS, Deep Learning",PhD,9,Real Estate,2024-12-10,2024-12-31,643,6.7,Neural Networks Co +AI10732,Data Engineer,76848,CAD,96060,MI,FT,Canada,M,Canada,0,"Kubernetes, Tableau, Hadoop",Bachelor,4,Energy,2024-09-23,2024-11-14,1993,7.5,Cognitive Computing +AI10733,Deep Learning Engineer,155320,AUD,209682,EX,CT,Australia,M,Australia,0,"SQL, Scala, Computer Vision, Tableau, Linux",Master,14,Government,2025-01-05,2025-02-21,1624,6.7,DataVision Ltd +AI10734,AI Consultant,197617,GBP,148213,EX,PT,United Kingdom,S,United Kingdom,50,"AWS, PyTorch, Deep Learning",Associate,18,Finance,2024-11-11,2024-12-24,1858,7.2,Future Systems +AI10735,AI Research Scientist,49891,EUR,42407,EN,FT,Netherlands,S,Netherlands,0,"NLP, R, Computer Vision, Azure",Associate,0,Media,2024-03-30,2024-05-03,1695,9.3,DataVision Ltd +AI10736,Principal Data Scientist,117730,EUR,100071,SE,FL,Germany,L,Germany,0,"AWS, MLOps, Mathematics, Tableau",Master,5,Automotive,2024-12-21,2025-02-13,1009,5.6,Cognitive Computing +AI10737,AI Architect,115851,USD,115851,SE,PT,South Korea,M,South Korea,100,"Git, Python, Kubernetes, Statistics, Data Visualization",Associate,8,Media,2024-10-08,2024-11-09,990,7,Cloud AI Solutions +AI10738,Machine Learning Engineer,73670,CAD,92088,EN,CT,Canada,M,Egypt,100,"Linux, PyTorch, SQL, Java, Statistics",Associate,0,Government,2024-09-01,2024-10-17,1315,7.8,Predictive Systems +AI10739,AI Software Engineer,214568,CHF,193111,SE,FL,Switzerland,M,Switzerland,50,"AWS, Linux, Computer Vision",Master,7,Retail,2024-08-10,2024-09-15,937,6.8,Algorithmic Solutions +AI10740,AI Architect,258181,USD,258181,EX,CT,United States,L,Mexico,0,"MLOps, Spark, Data Visualization, GCP, Computer Vision",PhD,19,Retail,2024-05-24,2024-07-22,1825,7.1,AI Innovations +AI10741,Deep Learning Engineer,39478,USD,39478,EN,FL,South Korea,S,South Korea,50,"Git, Deep Learning, Spark, Java",Master,0,Automotive,2024-07-01,2024-08-10,922,7.9,DataVision Ltd +AI10742,Robotics Engineer,54274,USD,54274,MI,FT,China,L,China,0,"R, Java, AWS",Master,4,Manufacturing,2024-06-25,2024-07-15,723,7.2,Machine Intelligence Group +AI10743,Data Analyst,48788,USD,48788,SE,FT,China,S,China,0,"SQL, Deep Learning, Java, Computer Vision",Master,5,Healthcare,2025-01-09,2025-01-31,1444,7.1,Algorithmic Solutions +AI10744,NLP Engineer,232286,CHF,209057,SE,PT,Switzerland,L,Switzerland,50,"AWS, Python, GCP",Associate,8,Healthcare,2024-08-26,2024-09-19,637,9.9,Neural Networks Co +AI10745,AI Specialist,251960,USD,251960,EX,FT,United States,S,United States,100,"SQL, Scala, Python, MLOps, R",Master,13,Gaming,2024-04-11,2024-06-03,2323,6.1,Digital Transformation LLC +AI10746,Data Engineer,100923,CHF,90831,MI,FL,Switzerland,S,Malaysia,100,"Kubernetes, Scala, Azure, TensorFlow, SQL",Master,4,Healthcare,2024-07-01,2024-09-09,2073,5.9,Cognitive Computing +AI10747,Robotics Engineer,101479,AUD,136997,MI,CT,Australia,M,Australia,100,"Spark, Git, Computer Vision, AWS",PhD,4,Government,2025-04-16,2025-06-08,867,5.2,Quantum Computing Inc +AI10748,AI Software Engineer,238738,USD,238738,EX,FT,Israel,L,Israel,50,"Python, TensorFlow, Tableau",Associate,18,Retail,2024-09-22,2024-11-14,851,6.6,TechCorp Inc +AI10749,ML Ops Engineer,63999,EUR,54399,EN,CT,Netherlands,L,Kenya,100,"SQL, Python, Kubernetes, Data Visualization",Associate,0,Media,2024-11-25,2025-01-13,2084,7.3,Algorithmic Solutions +AI10750,Deep Learning Engineer,89374,USD,89374,MI,PT,Ireland,M,Ireland,0,"SQL, Spark, Scala, Python, Data Visualization",Master,4,Gaming,2025-04-20,2025-05-06,2047,9.6,AI Innovations +AI10751,NLP Engineer,71485,USD,71485,MI,FL,Sweden,S,France,50,"R, Scala, Data Visualization",Bachelor,4,Gaming,2024-08-21,2024-09-14,979,7.1,AI Innovations +AI10752,AI Software Engineer,173599,CAD,216999,EX,FL,Canada,M,Canada,50,"Deep Learning, SQL, PyTorch",PhD,13,Media,2025-04-16,2025-06-19,876,8.2,Cognitive Computing +AI10753,AI Product Manager,44067,USD,44067,EX,FT,India,S,India,50,"Statistics, NLP, Hadoop, Linux, Deep Learning",Bachelor,11,Consulting,2024-08-13,2024-09-30,778,9.1,Cloud AI Solutions +AI10754,AI Software Engineer,103357,EUR,87853,MI,FT,Netherlands,L,Netherlands,100,"AWS, Linux, Mathematics",PhD,3,Education,2024-08-11,2024-08-31,600,8.9,DataVision Ltd +AI10755,Data Scientist,95805,EUR,81434,MI,FL,Netherlands,M,Netherlands,50,"Linux, Hadoop, Deep Learning",PhD,2,Energy,2025-04-17,2025-06-13,2304,5,Machine Intelligence Group +AI10756,Data Scientist,286492,USD,286492,EX,FT,Norway,M,Norway,0,"R, NLP, Python, Docker",Bachelor,10,Energy,2024-06-02,2024-06-22,746,8.7,Machine Intelligence Group +AI10757,Head of AI,64481,EUR,54809,EN,FL,France,S,Italy,50,"Spark, Linux, Deep Learning, MLOps, PyTorch",Master,0,Energy,2024-03-15,2024-05-16,2443,8.7,Cloud AI Solutions +AI10758,Autonomous Systems Engineer,206801,USD,206801,EX,CT,Israel,M,Israel,100,"NLP, AWS, Scala, Azure, Python",Bachelor,18,Gaming,2024-04-28,2024-06-10,747,8.5,Autonomous Tech +AI10759,AI Specialist,161515,JPY,17766650,SE,FT,Japan,M,Canada,100,"Data Visualization, R, Scala, MLOps",Bachelor,5,Media,2024-03-20,2024-05-15,1508,9.6,Cognitive Computing +AI10760,Machine Learning Engineer,129002,USD,129002,EX,FL,Israel,S,Israel,100,"Statistics, R, Git",PhD,13,Retail,2024-09-03,2024-09-20,1993,7.1,AI Innovations +AI10761,Computer Vision Engineer,77898,CAD,97373,MI,FL,Canada,M,Canada,100,"Azure, Spark, Scala, Java, Git",Associate,2,Automotive,2024-06-21,2024-07-22,984,7.4,Quantum Computing Inc +AI10762,Data Engineer,117229,EUR,99645,SE,FL,Netherlands,S,Norway,100,"Spark, Mathematics, Linux",Master,9,Automotive,2025-04-13,2025-05-18,1881,8.1,Autonomous Tech +AI10763,Machine Learning Researcher,81371,EUR,69165,MI,FL,Netherlands,S,Netherlands,0,"SQL, R, Java, Kubernetes, Git",Associate,3,Manufacturing,2024-01-28,2024-03-02,1429,8.7,Algorithmic Solutions +AI10764,Data Engineer,72322,USD,72322,EN,PT,South Korea,L,South Korea,0,"MLOps, Azure, Python",Bachelor,1,Automotive,2024-09-06,2024-11-18,2024,7.9,Cloud AI Solutions +AI10765,ML Ops Engineer,94388,USD,94388,EX,FT,India,L,India,0,"Azure, SQL, Spark, Statistics, R",Master,12,Media,2024-06-24,2024-08-24,1661,7.3,Advanced Robotics +AI10766,ML Ops Engineer,202122,USD,202122,EX,CT,Denmark,M,Australia,50,"GCP, R, Git, TensorFlow",PhD,16,Energy,2024-09-23,2024-12-01,1479,9.8,Smart Analytics +AI10767,AI Software Engineer,86254,CAD,107818,MI,FL,Canada,L,Canada,50,"TensorFlow, NLP, Linux",PhD,4,Government,2025-04-06,2025-06-05,2494,9.7,Quantum Computing Inc +AI10768,Machine Learning Researcher,83507,SGD,108559,MI,CT,Singapore,S,Singapore,100,"Tableau, Computer Vision, GCP",Bachelor,2,Education,2024-08-19,2024-10-16,2354,6.4,Quantum Computing Inc +AI10769,Research Scientist,173027,EUR,147073,SE,CT,Germany,L,Brazil,100,"Tableau, Git, Hadoop, Spark, PyTorch",PhD,8,Education,2024-12-05,2024-12-21,690,5.5,Advanced Robotics +AI10770,Data Engineer,116393,EUR,98934,SE,FT,Germany,M,Germany,100,"MLOps, Scala, Azure, GCP, Kubernetes",Associate,8,Finance,2024-08-03,2024-09-12,2354,6.9,Cloud AI Solutions +AI10771,AI Software Engineer,99131,CHF,89218,MI,PT,Switzerland,S,Switzerland,100,"Kubernetes, Docker, Tableau, Hadoop, Java",Associate,3,Government,2024-05-07,2024-06-19,2068,6.1,Digital Transformation LLC +AI10772,Autonomous Systems Engineer,50959,USD,50959,EN,PT,Israel,M,Israel,100,"Hadoop, Kubernetes, SQL, Java, R",Bachelor,0,Consulting,2024-04-29,2024-06-16,2134,8.9,AI Innovations +AI10773,Data Analyst,107661,USD,107661,MI,CT,Denmark,S,Denmark,100,"Docker, Hadoop, Kubernetes, Python",Master,2,Finance,2025-01-03,2025-03-15,922,7.6,Cognitive Computing +AI10774,AI Specialist,174458,EUR,148289,EX,CT,Netherlands,M,Netherlands,100,"Python, Git, Kubernetes, Tableau",Bachelor,15,Media,2024-10-04,2024-11-05,1151,9,DataVision Ltd +AI10775,AI Specialist,126182,SGD,164037,SE,FT,Singapore,L,Singapore,0,"Linux, Python, Java, Git",PhD,7,Gaming,2024-03-23,2024-06-04,2236,9.7,Machine Intelligence Group +AI10776,Computer Vision Engineer,293038,CHF,263734,EX,CT,Switzerland,L,Switzerland,100,"Python, TensorFlow, R, Java, Computer Vision",PhD,13,Education,2024-05-12,2024-07-04,872,7.7,Future Systems +AI10777,AI Consultant,171137,EUR,145466,EX,CT,Austria,L,Austria,0,"Statistics, Linux, Scala",PhD,19,Gaming,2024-09-18,2024-10-26,1784,8.5,Smart Analytics +AI10778,AI Architect,106675,CHF,96008,MI,FT,Switzerland,S,Switzerland,0,"MLOps, Git, Deep Learning, Mathematics",PhD,3,Energy,2025-01-19,2025-03-01,1725,8.7,Quantum Computing Inc +AI10779,ML Ops Engineer,266812,USD,266812,EX,CT,Denmark,S,Denmark,100,"Python, NLP, Mathematics, TensorFlow",Bachelor,11,Retail,2024-09-23,2024-12-03,675,5.9,AI Innovations +AI10780,Data Scientist,85605,USD,85605,MI,FT,Finland,M,Estonia,100,"Kubernetes, Python, Computer Vision",Associate,3,Healthcare,2024-04-30,2024-06-10,2427,7.2,Smart Analytics +AI10781,NLP Engineer,201964,USD,201964,EX,CT,Israel,L,Czech Republic,0,"Scala, Python, Kubernetes, Computer Vision, SQL",Bachelor,13,Government,2024-01-29,2024-02-22,1295,7,Smart Analytics +AI10782,AI Specialist,137083,USD,137083,SE,FT,Israel,L,Israel,50,"AWS, Hadoop, Python, Scala, Spark",Bachelor,8,Gaming,2025-04-28,2025-05-18,1859,9,Neural Networks Co +AI10783,Data Analyst,75000,EUR,63750,EN,FL,Netherlands,S,Mexico,100,"R, Hadoop, Deep Learning, Java",Master,0,Finance,2024-02-24,2024-03-16,1353,7.8,AI Innovations +AI10784,Principal Data Scientist,200686,USD,200686,EX,CT,Sweden,L,Sweden,0,"Tableau, Python, NLP, TensorFlow, Scala",Associate,16,Telecommunications,2024-11-02,2024-12-31,1499,9.9,Predictive Systems +AI10785,Principal Data Scientist,129291,JPY,14222010,SE,FL,Japan,L,Japan,50,"R, Computer Vision, Azure, GCP",Associate,8,Transportation,2024-10-01,2024-10-19,1209,6.7,DeepTech Ventures +AI10786,Data Engineer,86101,EUR,73186,MI,PT,France,S,France,50,"SQL, Scala, Hadoop",PhD,4,Gaming,2024-02-20,2024-04-17,1586,5.3,Digital Transformation LLC +AI10787,AI Architect,61948,USD,61948,EN,PT,Sweden,L,Sweden,100,"SQL, PyTorch, Java, Azure",Associate,0,Education,2025-03-18,2025-05-18,1004,9.5,DeepTech Ventures +AI10788,Machine Learning Researcher,53377,USD,53377,MI,PT,China,L,China,0,"Python, Java, TensorFlow",Associate,2,Consulting,2025-01-16,2025-03-02,633,6.6,Digital Transformation LLC +AI10789,Robotics Engineer,125096,CHF,112586,MI,PT,Switzerland,S,Brazil,50,"Kubernetes, Git, Data Visualization, Python, Linux",Bachelor,3,Education,2025-01-05,2025-02-12,567,5.3,Future Systems +AI10790,AI Specialist,303813,CHF,273432,EX,FT,Switzerland,S,Switzerland,100,"SQL, Tableau, NLP, PyTorch, Mathematics",Associate,14,Government,2024-09-14,2024-09-28,1178,8.9,Quantum Computing Inc +AI10791,Machine Learning Researcher,52898,USD,52898,EN,CT,South Korea,M,South Korea,0,"Tableau, Kubernetes, Computer Vision",Bachelor,0,Healthcare,2024-11-19,2024-12-27,1927,6.2,DeepTech Ventures +AI10792,Data Scientist,91033,JPY,10013630,MI,PT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization",PhD,3,Energy,2024-07-25,2024-09-30,1290,6.4,Quantum Computing Inc +AI10793,AI Architect,87585,USD,87585,EN,FL,United States,L,United States,100,"Hadoop, NLP, Linux, GCP, SQL",Bachelor,0,Energy,2025-02-01,2025-04-12,2491,6.7,AI Innovations +AI10794,AI Architect,136182,GBP,102137,SE,FT,United Kingdom,S,United Kingdom,100,"Computer Vision, NLP, Tableau, GCP",Bachelor,9,Automotive,2024-10-18,2024-11-20,1243,5.5,Quantum Computing Inc +AI10795,Data Engineer,132993,EUR,113044,SE,FT,Germany,M,Nigeria,100,"Python, TensorFlow, PyTorch, Spark, Kubernetes",Bachelor,7,Retail,2024-10-21,2024-11-06,2207,5.7,Digital Transformation LLC +AI10796,Autonomous Systems Engineer,165196,EUR,140417,EX,FT,Austria,S,Austria,100,"Python, TensorFlow, Kubernetes, Spark, AWS",Master,13,Education,2024-01-18,2024-02-19,551,9.2,Neural Networks Co +AI10797,AI Research Scientist,171750,GBP,128813,SE,CT,United Kingdom,L,United Kingdom,0,"Spark, NLP, Kubernetes, Data Visualization, Computer Vision",Master,5,Real Estate,2024-02-01,2024-04-04,1748,6.4,Smart Analytics +AI10798,AI Research Scientist,117335,EUR,99735,SE,FT,France,M,France,100,"Linux, GCP, Spark, MLOps",Associate,7,Real Estate,2024-05-23,2024-06-19,1923,8,Neural Networks Co +AI10799,Data Scientist,137278,GBP,102959,SE,PT,United Kingdom,S,United Kingdom,0,"R, SQL, Java, Kubernetes",Bachelor,9,Gaming,2025-01-19,2025-03-29,1473,6.4,Quantum Computing Inc +AI10800,Machine Learning Engineer,147147,USD,147147,EX,CT,Sweden,M,Sweden,100,"TensorFlow, Hadoop, Tableau, Docker, GCP",Master,14,Consulting,2024-08-29,2024-10-19,1580,7.2,Machine Intelligence Group +AI10801,Data Engineer,71205,EUR,60524,MI,FT,Austria,M,China,100,"NLP, SQL, PyTorch",Master,3,Retail,2024-07-10,2024-09-12,1566,8,Smart Analytics +AI10802,Machine Learning Researcher,134161,CAD,167701,SE,PT,Canada,M,Canada,0,"Linux, Hadoop, Kubernetes, Python",Master,6,Automotive,2024-12-15,2025-01-31,2485,5.4,Algorithmic Solutions +AI10803,Autonomous Systems Engineer,82237,USD,82237,MI,PT,Sweden,S,Australia,50,"Python, TensorFlow, Statistics",PhD,4,Retail,2024-10-19,2024-11-27,1074,5.8,Predictive Systems +AI10804,Autonomous Systems Engineer,38622,USD,38622,MI,FT,India,M,India,100,"Git, Linux, AWS, TensorFlow",Associate,3,Technology,2024-05-02,2024-05-22,2055,6.7,Cloud AI Solutions +AI10805,Robotics Engineer,55769,USD,55769,EN,FL,Sweden,M,India,100,"Scala, NLP, Computer Vision",Master,1,Retail,2024-12-22,2025-02-05,2420,7.4,TechCorp Inc +AI10806,ML Ops Engineer,67249,CHF,60524,EN,FL,Switzerland,S,Switzerland,100,"Scala, Java, Deep Learning",Associate,0,Automotive,2024-02-29,2024-04-04,523,7.5,Cloud AI Solutions +AI10807,AI Specialist,42394,USD,42394,MI,CT,China,M,China,0,"MLOps, Kubernetes, Git",Associate,3,Consulting,2024-08-17,2024-09-15,2406,7.8,AI Innovations +AI10808,AI Product Manager,22136,USD,22136,EN,FL,China,S,China,100,"SQL, Mathematics, Tableau, MLOps",Bachelor,1,Consulting,2024-11-10,2025-01-08,1809,8.3,Machine Intelligence Group +AI10809,Computer Vision Engineer,134580,SGD,174954,SE,CT,Singapore,S,Turkey,0,"MLOps, Computer Vision, Python, TensorFlow, Git",Associate,7,Retail,2024-12-27,2025-03-06,1655,6.9,Machine Intelligence Group +AI10810,AI Architect,65961,CAD,82451,EN,CT,Canada,M,Canada,0,"GCP, Spark, Scala, Kubernetes",PhD,1,Education,2024-12-29,2025-03-01,1771,6.4,Neural Networks Co +AI10811,AI Product Manager,117629,USD,117629,MI,CT,Norway,M,Norway,0,"Python, Deep Learning, Computer Vision, R",Associate,4,Transportation,2024-02-08,2024-02-22,795,8.7,Future Systems +AI10812,Machine Learning Researcher,87716,EUR,74559,MI,FT,Germany,S,Finland,50,"Linux, Mathematics, GCP",PhD,3,Energy,2025-01-27,2025-03-06,986,9.1,DeepTech Ventures +AI10813,AI Research Scientist,18861,USD,18861,EN,CT,India,M,India,50,"R, Linux, SQL",Bachelor,0,Manufacturing,2025-04-07,2025-06-04,1425,7.6,Autonomous Tech +AI10814,Robotics Engineer,122512,USD,122512,MI,FT,Norway,M,Norway,0,"PyTorch, R, Linux, Hadoop",Bachelor,2,Consulting,2024-10-09,2024-10-26,2292,6.8,Autonomous Tech +AI10815,Deep Learning Engineer,180159,CAD,225199,EX,FT,Canada,L,Canada,50,"Statistics, Azure, Python, Tableau, Scala",PhD,16,Manufacturing,2024-12-09,2025-01-12,2370,5.4,Neural Networks Co +AI10816,AI Architect,168620,EUR,143327,EX,CT,Austria,L,Austria,100,"Git, PyTorch, NLP, GCP",PhD,15,Real Estate,2025-03-21,2025-05-17,658,6.1,Cloud AI Solutions +AI10817,NLP Engineer,72274,USD,72274,SE,FT,China,L,China,0,"Mathematics, Computer Vision, Statistics, SQL, Spark",PhD,5,Telecommunications,2025-04-12,2025-05-03,1316,6.9,Future Systems +AI10818,Autonomous Systems Engineer,67126,USD,67126,EN,CT,Israel,L,Israel,100,"Mathematics, Kubernetes, Azure, Java",Associate,1,Manufacturing,2024-10-13,2024-12-03,2387,6.5,Advanced Robotics +AI10819,NLP Engineer,94449,EUR,80282,MI,PT,France,L,France,50,"Azure, Scala, Linux",PhD,4,Gaming,2024-06-15,2024-08-26,2175,7.3,Autonomous Tech +AI10820,Machine Learning Engineer,112859,EUR,95930,SE,PT,France,L,France,50,"NLP, SQL, PyTorch, Data Visualization",Master,5,Energy,2024-06-22,2024-08-28,2162,8.8,Advanced Robotics +AI10821,Data Engineer,144547,SGD,187911,SE,FT,Singapore,M,Switzerland,0,"NLP, SQL, PyTorch, AWS",PhD,6,Manufacturing,2024-07-15,2024-09-15,1374,7.1,Digital Transformation LLC +AI10822,Machine Learning Researcher,80627,EUR,68533,MI,FL,Austria,M,Austria,100,"Scala, Python, Docker, Kubernetes, TensorFlow",PhD,3,Education,2024-07-23,2024-08-25,2061,6.9,DataVision Ltd +AI10823,Deep Learning Engineer,151439,EUR,128723,EX,FT,Austria,L,Austria,50,"TensorFlow, Azure, Java, Docker, Git",PhD,11,Education,2024-09-13,2024-11-11,782,9.8,Machine Intelligence Group +AI10824,ML Ops Engineer,43069,USD,43069,MI,FT,China,M,China,50,"PyTorch, Spark, SQL, GCP, AWS",Bachelor,4,Technology,2024-01-03,2024-02-16,2356,6.4,Cognitive Computing +AI10825,AI Specialist,137861,USD,137861,EX,CT,Finland,M,China,0,"NLP, Scala, SQL, PyTorch",PhD,14,Government,2024-11-04,2025-01-13,703,9,Quantum Computing Inc +AI10826,AI Product Manager,192829,USD,192829,EX,CT,Denmark,S,Denmark,0,"Java, Mathematics, Git",Bachelor,10,Real Estate,2024-08-11,2024-09-17,971,7.4,AI Innovations +AI10827,AI Specialist,108163,EUR,91939,SE,FT,Austria,M,Austria,0,"Computer Vision, Linux, PyTorch, SQL, TensorFlow",Associate,7,Gaming,2024-09-16,2024-10-10,1127,7.5,Cognitive Computing +AI10828,ML Ops Engineer,65216,EUR,55434,MI,PT,Austria,S,Colombia,50,"SQL, Linux, Azure, NLP, Git",Master,3,Education,2024-01-08,2024-02-14,2280,9.4,Future Systems +AI10829,Machine Learning Researcher,80149,CAD,100186,MI,PT,Canada,M,Canada,0,"Python, Data Visualization, Docker, Hadoop",PhD,4,Retail,2025-03-26,2025-06-05,1233,5.3,TechCorp Inc +AI10830,ML Ops Engineer,205835,SGD,267586,EX,FT,Singapore,S,Singapore,50,"TensorFlow, Git, Hadoop",Master,12,Technology,2025-04-23,2025-06-15,2294,9.8,Autonomous Tech +AI10831,Head of AI,105584,USD,105584,EN,FT,Norway,L,Norway,100,"Git, Computer Vision, Python",Bachelor,0,Finance,2024-10-21,2024-12-10,2375,8.7,Neural Networks Co +AI10832,Data Scientist,134679,USD,134679,SE,FT,South Korea,L,South Korea,100,"Spark, Data Visualization, Deep Learning, NLP, Scala",PhD,7,Transportation,2025-04-12,2025-05-02,1266,6.8,Future Systems +AI10833,Data Analyst,63653,GBP,47740,EN,FT,United Kingdom,M,China,50,"Scala, Deep Learning, NLP, PyTorch",PhD,0,Government,2024-10-06,2024-11-21,1421,7.2,Digital Transformation LLC +AI10834,AI Architect,116733,EUR,99223,MI,FT,Germany,L,Germany,100,"Hadoop, SQL, Python",Associate,3,Real Estate,2025-04-13,2025-06-15,1457,5.1,Digital Transformation LLC +AI10835,Computer Vision Engineer,171496,USD,171496,EX,FL,Norway,S,Norway,50,"Mathematics, TensorFlow, Statistics, Linux, GCP",Master,18,Finance,2024-04-22,2024-06-09,897,9.1,Quantum Computing Inc +AI10836,Machine Learning Engineer,179259,SGD,233037,EX,FT,Singapore,L,Singapore,0,"PyTorch, Java, R, Statistics, Linux",Associate,16,Technology,2024-03-23,2024-05-04,1256,7.5,Cognitive Computing +AI10837,Data Scientist,222335,USD,222335,SE,FL,Denmark,L,Denmark,0,"PyTorch, AWS, NLP, Linux",Bachelor,8,Telecommunications,2024-11-25,2024-12-14,2295,6.2,Predictive Systems +AI10838,Head of AI,182726,USD,182726,EX,CT,Norway,M,Norway,0,"TensorFlow, Hadoop, PyTorch, Data Visualization, Spark",Bachelor,17,Telecommunications,2024-06-04,2024-07-28,2321,9.9,DeepTech Ventures +AI10839,Data Scientist,59545,USD,59545,SE,CT,China,L,China,100,"R, NLP, Kubernetes, Python, Docker",PhD,5,Education,2024-12-10,2025-01-26,1221,8.6,Algorithmic Solutions +AI10840,Autonomous Systems Engineer,159516,USD,159516,MI,CT,Norway,L,Philippines,0,"Hadoop, Kubernetes, Docker",Associate,3,Gaming,2024-03-30,2024-05-29,1823,7,Machine Intelligence Group +AI10841,Robotics Engineer,61743,USD,61743,EN,CT,Ireland,S,Ireland,0,"NLP, Azure, Spark, Deep Learning, GCP",PhD,1,Education,2024-10-04,2024-12-10,1963,6.5,Quantum Computing Inc +AI10842,Head of AI,68105,USD,68105,MI,FT,Finland,M,Ireland,50,"Python, Docker, Azure",Master,2,Retail,2025-01-08,2025-03-17,1930,6.6,Digital Transformation LLC +AI10843,Data Scientist,199352,EUR,169449,EX,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure, PyTorch",Associate,11,Real Estate,2024-06-17,2024-07-25,621,5.7,Algorithmic Solutions +AI10844,AI Specialist,177487,USD,177487,EX,CT,Denmark,M,Denmark,0,"Scala, Kubernetes, R",Bachelor,10,Manufacturing,2025-04-03,2025-06-14,878,8.6,Digital Transformation LLC +AI10845,Robotics Engineer,62199,EUR,52869,EN,CT,Germany,S,Russia,50,"Data Visualization, Python, Deep Learning, Computer Vision",Bachelor,0,Retail,2025-02-26,2025-05-02,1586,5.9,DataVision Ltd +AI10846,Head of AI,89631,USD,89631,EN,FL,Ireland,L,Ireland,0,"Git, R, Tableau, PyTorch",Associate,1,Education,2025-02-13,2025-04-16,1377,6.1,DataVision Ltd +AI10847,Data Engineer,73376,CAD,91720,MI,PT,Canada,S,Canada,100,"R, PyTorch, NLP",Associate,4,Media,2024-03-22,2024-05-16,1147,5.2,DeepTech Ventures +AI10848,Research Scientist,94533,USD,94533,MI,FT,Denmark,S,Denmark,50,"Linux, Scala, TensorFlow, Data Visualization, Python",Master,2,Finance,2024-01-12,2024-02-16,1115,8.8,Predictive Systems +AI10849,AI Software Engineer,193687,EUR,164634,EX,PT,Austria,M,Austria,100,"AWS, Scala, R, Tableau",Master,18,Retail,2024-04-19,2024-06-20,901,9.5,Smart Analytics +AI10850,Robotics Engineer,53931,USD,53931,SE,FL,India,L,Kenya,0,"MLOps, Python, Data Visualization, Azure",Associate,9,Retail,2024-12-30,2025-01-21,2014,8.9,TechCorp Inc +AI10851,Machine Learning Engineer,116512,USD,116512,EX,PT,China,M,China,100,"TensorFlow, SQL, MLOps, Deep Learning",PhD,19,Healthcare,2025-03-17,2025-04-24,1614,7.3,Predictive Systems +AI10852,ML Ops Engineer,99823,USD,99823,MI,PT,Denmark,S,Denmark,0,"Git, MLOps, SQL",Associate,2,Telecommunications,2024-03-29,2024-05-25,593,6.8,Future Systems +AI10853,AI Research Scientist,87180,CAD,108975,EN,FL,Canada,L,Canada,100,"GCP, Tableau, Data Visualization, PyTorch",Master,0,Real Estate,2024-04-18,2024-05-08,1341,8.3,Smart Analytics +AI10854,Data Analyst,47973,USD,47973,MI,FL,China,M,China,50,"Hadoop, PyTorch, GCP, Computer Vision",PhD,2,Telecommunications,2024-06-11,2024-08-06,776,8,Quantum Computing Inc +AI10855,Head of AI,313259,USD,313259,EX,FT,Denmark,M,Romania,100,"Python, R, Spark, Linux",Associate,10,Finance,2024-09-23,2024-11-28,2488,6.8,Predictive Systems +AI10856,AI Specialist,199489,USD,199489,SE,FT,Denmark,L,Denmark,50,"SQL, MLOps, Python, Data Visualization, Azure",Associate,8,Government,2024-02-16,2024-03-21,2398,5.9,DeepTech Ventures +AI10857,Autonomous Systems Engineer,32228,USD,32228,EN,CT,China,S,China,50,"Statistics, GCP, SQL, Python, Azure",PhD,1,Gaming,2024-02-17,2024-03-18,1063,6.4,Cloud AI Solutions +AI10858,Principal Data Scientist,113385,USD,113385,MI,PT,Denmark,M,Egypt,50,"GCP, Kubernetes, Tableau",Associate,2,Technology,2024-09-21,2024-11-22,1831,9.4,DataVision Ltd +AI10859,AI Specialist,252641,USD,252641,EX,FT,Ireland,L,Ireland,100,"Tableau, Scala, NLP, Python, Java",Master,17,Transportation,2024-08-30,2024-10-14,2301,7.9,TechCorp Inc +AI10860,Data Engineer,90555,USD,90555,MI,FT,Denmark,S,Denmark,50,"PyTorch, TensorFlow, Linux",Bachelor,4,Finance,2024-03-05,2024-04-18,1969,8.3,Algorithmic Solutions +AI10861,Research Scientist,77655,USD,77655,EN,FT,Norway,M,Norway,50,"Deep Learning, Linux, GCP, Python",Master,1,Manufacturing,2024-03-17,2024-04-15,2224,8.3,Neural Networks Co +AI10862,Data Engineer,141801,USD,141801,MI,FL,Norway,L,Thailand,0,"Spark, Git, Data Visualization, Azure",Bachelor,2,Consulting,2024-06-09,2024-08-15,937,5.9,Future Systems +AI10863,NLP Engineer,163767,USD,163767,SE,FT,Denmark,S,Denmark,100,"SQL, Hadoop, AWS",Bachelor,9,Healthcare,2024-06-13,2024-07-29,1267,6.5,TechCorp Inc +AI10864,Principal Data Scientist,59859,USD,59859,EN,FL,South Korea,L,South Korea,0,"Docker, SQL, Deep Learning, NLP",Associate,1,Healthcare,2025-02-19,2025-03-18,2208,6.4,Quantum Computing Inc +AI10865,Principal Data Scientist,90290,USD,90290,MI,PT,Israel,L,Israel,0,"Python, NLP, Kubernetes, Docker",PhD,3,Media,2024-07-02,2024-09-08,886,6.5,Cognitive Computing +AI10866,Research Scientist,114206,EUR,97075,SE,FT,France,L,France,100,"Python, Docker, Computer Vision, SQL, Kubernetes",PhD,6,Gaming,2025-01-07,2025-03-20,1772,9.1,Smart Analytics +AI10867,Head of AI,99967,USD,99967,SE,PT,Sweden,S,Sweden,50,"R, Java, AWS",Associate,6,Media,2024-12-31,2025-03-06,516,8.1,Neural Networks Co +AI10868,ML Ops Engineer,208430,USD,208430,EX,CT,Sweden,M,Sweden,100,"Azure, Data Visualization, Tableau, Git",PhD,16,Manufacturing,2025-02-18,2025-03-09,883,8.8,Neural Networks Co +AI10869,ML Ops Engineer,88936,GBP,66702,MI,CT,United Kingdom,S,United Kingdom,0,"NLP, Deep Learning, Spark, Git",Master,2,Manufacturing,2024-01-21,2024-04-02,882,7.3,Predictive Systems +AI10870,AI Specialist,172753,USD,172753,SE,CT,Norway,S,Norway,100,"Python, R, GCP, Scala, TensorFlow",Bachelor,6,Gaming,2024-06-04,2024-06-30,892,7.1,Autonomous Tech +AI10871,Robotics Engineer,172661,USD,172661,EX,CT,Finland,L,Finland,50,"SQL, Kubernetes, MLOps, Deep Learning",PhD,10,Telecommunications,2025-02-17,2025-03-03,795,9.9,TechCorp Inc +AI10872,Robotics Engineer,61484,EUR,52261,EN,FL,France,L,France,50,"Docker, SQL, AWS",Bachelor,1,Healthcare,2024-02-23,2024-04-08,2272,6.2,TechCorp Inc +AI10873,Robotics Engineer,71875,EUR,61094,EN,FT,Germany,S,Ukraine,0,"Mathematics, Tableau, Hadoop, Java",PhD,0,Telecommunications,2024-05-18,2024-06-13,1647,6.7,Cloud AI Solutions +AI10874,Data Engineer,79797,USD,79797,MI,FL,Sweden,S,Sweden,50,"Kubernetes, Python, TensorFlow, AWS, NLP",Bachelor,3,Telecommunications,2025-03-21,2025-05-08,527,9.2,Advanced Robotics +AI10875,AI Consultant,91965,USD,91965,EX,FT,India,L,India,50,"Computer Vision, Docker, Python, GCP, Linux",Bachelor,15,Manufacturing,2024-10-03,2024-11-10,1418,7.3,Smart Analytics +AI10876,Robotics Engineer,128584,EUR,109296,SE,FL,Austria,S,Austria,100,"Git, Data Visualization, SQL, Computer Vision",Master,5,Energy,2024-04-07,2024-06-11,2097,6.6,Machine Intelligence Group +AI10877,AI Product Manager,92990,USD,92990,EN,CT,United States,M,United States,100,"Kubernetes, R, GCP, Statistics",Master,0,Telecommunications,2024-12-07,2025-02-18,2231,9.9,DeepTech Ventures +AI10878,AI Architect,85862,USD,85862,EN,FT,Norway,M,Norway,0,"Hadoop, Docker, AWS, Data Visualization",PhD,1,Manufacturing,2024-05-19,2024-07-01,1306,8.6,Cloud AI Solutions +AI10879,AI Product Manager,96557,CAD,120696,MI,CT,Canada,M,Portugal,100,"Git, NLP, Tableau, Data Visualization",Bachelor,3,Telecommunications,2024-01-13,2024-03-13,1805,6.4,Digital Transformation LLC +AI10880,AI Research Scientist,136056,USD,136056,SE,CT,Sweden,S,Austria,50,"AWS, Computer Vision, Mathematics, R",Associate,8,Retail,2024-04-08,2024-05-16,884,9.7,Digital Transformation LLC +AI10881,Principal Data Scientist,191877,EUR,163095,EX,FT,Austria,L,Austria,0,"Spark, GCP, Deep Learning, Scala",Bachelor,15,Transportation,2024-07-08,2024-07-29,2481,7.8,DeepTech Ventures +AI10882,Deep Learning Engineer,58995,USD,58995,EN,CT,Sweden,L,Portugal,0,"Linux, Spark, R",Associate,1,Telecommunications,2025-03-01,2025-03-26,1543,9.8,Smart Analytics +AI10883,Robotics Engineer,171771,USD,171771,SE,FL,Denmark,L,Denmark,50,"AWS, Computer Vision, SQL, Spark",Master,7,Finance,2024-09-14,2024-10-08,1457,9.4,Cognitive Computing +AI10884,AI Software Engineer,124350,USD,124350,SE,PT,United States,M,Netherlands,100,"SQL, Deep Learning, NLP",Master,7,Media,2024-04-04,2024-05-14,1461,9,Autonomous Tech +AI10885,Autonomous Systems Engineer,264027,USD,264027,EX,FT,United States,S,Indonesia,50,"Scala, R, Data Visualization, Python, TensorFlow",Associate,13,Transportation,2024-08-31,2024-09-20,1916,6.7,Future Systems +AI10886,Machine Learning Engineer,254261,EUR,216122,EX,PT,Austria,L,Belgium,50,"Git, TensorFlow, Mathematics",Associate,18,Manufacturing,2024-03-12,2024-05-19,965,5.7,Algorithmic Solutions +AI10887,Head of AI,95509,GBP,71632,MI,FL,United Kingdom,L,United Kingdom,0,"Hadoop, GCP, Data Visualization, Statistics, MLOps",Master,4,Real Estate,2024-11-03,2024-11-24,1264,7.5,DataVision Ltd +AI10888,ML Ops Engineer,144757,CAD,180946,SE,FT,Canada,L,Canada,100,"Hadoop, TensorFlow, NLP",PhD,9,Government,2024-07-08,2024-08-09,1528,5.7,Quantum Computing Inc +AI10889,AI Specialist,80856,USD,80856,EN,FL,Norway,S,Norway,50,"NLP, Scala, Java",Bachelor,0,Energy,2024-11-29,2025-01-14,2142,8.8,DeepTech Ventures +AI10890,Data Engineer,170023,SGD,221030,EX,CT,Singapore,S,Singapore,50,"Mathematics, NLP, Git, Computer Vision, Deep Learning",Bachelor,14,Technology,2024-03-18,2024-05-29,1846,9.5,DataVision Ltd +AI10891,Data Scientist,67573,USD,67573,MI,PT,Israel,S,Kenya,100,"Python, SQL, Java, MLOps",Master,2,Transportation,2024-01-08,2024-03-12,1770,8.9,Cognitive Computing +AI10892,Deep Learning Engineer,43295,USD,43295,MI,FL,India,L,India,0,"Kubernetes, Azure, SQL, Computer Vision",Master,4,Finance,2024-07-25,2024-09-01,1342,7.4,DataVision Ltd +AI10893,Principal Data Scientist,138506,CAD,173133,SE,CT,Canada,L,Canada,0,"Java, Git, Tableau, Kubernetes, R",Bachelor,5,Consulting,2024-08-01,2024-09-17,971,9.6,Cognitive Computing +AI10894,AI Specialist,83927,SGD,109105,EN,FL,Singapore,L,Mexico,0,"Tableau, Kubernetes, Linux",PhD,0,Manufacturing,2024-08-25,2024-11-01,2240,9.8,Cloud AI Solutions +AI10895,AI Product Manager,77484,GBP,58113,EN,FT,United Kingdom,M,United Kingdom,50,"Spark, GCP, Scala, Docker, Hadoop",Bachelor,1,Retail,2025-04-29,2025-05-22,1818,8.7,DeepTech Ventures +AI10896,Deep Learning Engineer,149388,USD,149388,SE,FL,Ireland,M,Ireland,100,"Tableau, Azure, PyTorch, NLP, SQL",PhD,6,Government,2024-06-07,2024-07-30,855,9.9,Autonomous Tech +AI10897,AI Specialist,220434,EUR,187369,EX,PT,Netherlands,S,Netherlands,50,"Kubernetes, Git, Data Visualization, Python",PhD,14,Retail,2024-04-25,2024-05-14,1114,8.6,DataVision Ltd +AI10898,Head of AI,79212,GBP,59409,EN,FL,United Kingdom,M,Romania,100,"AWS, Data Visualization, Git",Associate,1,Finance,2025-03-13,2025-05-04,1636,5.9,Algorithmic Solutions +AI10899,Machine Learning Researcher,169031,EUR,143676,SE,FL,Germany,L,Germany,50,"Linux, Python, NLP, Java",Bachelor,7,Automotive,2024-10-07,2024-11-23,2421,9.2,Advanced Robotics +AI10900,AI Product Manager,165582,USD,165582,SE,CT,Norway,L,Norway,50,"Scala, Data Visualization, Python",PhD,8,Education,2024-02-12,2024-03-04,1890,6.5,Digital Transformation LLC +AI10901,NLP Engineer,323522,CHF,291170,EX,FL,Switzerland,L,Switzerland,100,"Docker, MLOps, Kubernetes, GCP",Bachelor,18,Energy,2025-04-27,2025-05-15,1564,10,Cognitive Computing +AI10902,ML Ops Engineer,89783,USD,89783,EN,FL,United States,L,United States,100,"Azure, MLOps, Statistics",Master,1,Gaming,2024-07-29,2024-10-08,1060,6.7,Advanced Robotics +AI10903,Head of AI,172737,USD,172737,EX,PT,Denmark,S,Denmark,50,"AWS, Linux, Mathematics, Data Visualization, NLP",Master,13,Telecommunications,2025-01-29,2025-03-10,1381,8.9,Algorithmic Solutions +AI10904,Data Scientist,118389,USD,118389,SE,FT,Ireland,M,Ireland,50,"GCP, Linux, SQL, Kubernetes",Associate,5,Consulting,2025-03-18,2025-05-12,1971,6.7,Algorithmic Solutions +AI10905,AI Research Scientist,77597,GBP,58198,EN,FL,United Kingdom,M,United Kingdom,100,"Java, Deep Learning, R, Docker",Associate,0,Gaming,2024-08-11,2024-09-03,2061,9.5,Advanced Robotics +AI10906,Data Scientist,139624,SGD,181511,SE,PT,Singapore,S,Singapore,50,"Python, TensorFlow, Statistics",Associate,7,Media,2024-10-02,2024-11-07,1774,9.6,Smart Analytics +AI10907,Data Scientist,118666,SGD,154266,SE,PT,Singapore,M,Singapore,100,"Linux, Scala, Data Visualization, Kubernetes",Master,5,Media,2025-01-14,2025-01-28,964,5.3,Autonomous Tech +AI10908,Data Scientist,74287,EUR,63144,EN,CT,Netherlands,S,Russia,100,"SQL, Kubernetes, Data Visualization, Deep Learning",PhD,1,Education,2024-04-04,2024-05-24,1947,7.1,DataVision Ltd +AI10909,AI Product Manager,208649,GBP,156487,EX,CT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Java",Associate,13,Finance,2024-12-13,2025-01-16,1064,8.1,Machine Intelligence Group +AI10910,Data Analyst,123996,EUR,105397,SE,FL,France,L,United Kingdom,0,"Kubernetes, Scala, Spark, PyTorch, Java",Bachelor,8,Healthcare,2024-04-07,2024-05-19,1805,8,Quantum Computing Inc +AI10911,Data Analyst,229871,EUR,195390,EX,PT,Germany,L,Germany,50,"PyTorch, Deep Learning, Computer Vision",PhD,15,Healthcare,2025-03-02,2025-04-05,2477,9.5,Cloud AI Solutions +AI10912,Machine Learning Engineer,92771,SGD,120602,MI,FL,Singapore,S,Singapore,50,"Docker, SQL, Azure, TensorFlow",Associate,2,Automotive,2024-08-02,2024-10-14,910,7.1,Autonomous Tech +AI10913,Data Scientist,31230,USD,31230,EN,FL,China,M,Vietnam,100,"Azure, Python, Data Visualization, R, Statistics",Bachelor,1,Consulting,2025-03-26,2025-05-15,1660,8.5,TechCorp Inc +AI10914,AI Specialist,120411,USD,120411,SE,CT,Israel,S,Turkey,50,"Python, AWS, Linux, Git",Associate,7,Energy,2025-02-02,2025-03-25,2299,6.3,Autonomous Tech +AI10915,Computer Vision Engineer,219663,EUR,186714,EX,FT,Germany,S,Germany,100,"Python, R, TensorFlow, Docker",Bachelor,16,Automotive,2024-01-05,2024-02-25,1906,7.1,DeepTech Ventures +AI10916,Research Scientist,62748,EUR,53336,MI,FT,Austria,S,Austria,50,"Tableau, Mathematics, Python, SQL, AWS",Master,3,Real Estate,2024-07-16,2024-08-12,1479,5.8,TechCorp Inc +AI10917,AI Software Engineer,60299,GBP,45224,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Data Visualization, PyTorch",Master,1,Education,2024-12-06,2025-02-05,1779,7.8,Smart Analytics +AI10918,Head of AI,266091,EUR,226177,EX,PT,Netherlands,M,Netherlands,50,"NLP, Kubernetes, Scala, Statistics, TensorFlow",Associate,13,Media,2025-04-02,2025-04-27,990,5.7,Algorithmic Solutions +AI10919,AI Specialist,252940,AUD,341469,EX,FT,Australia,L,Austria,0,"SQL, GCP, Python, Hadoop",PhD,16,Healthcare,2025-03-07,2025-04-07,2229,8.7,Algorithmic Solutions +AI10920,Principal Data Scientist,100217,JPY,11023870,MI,FT,Japan,L,New Zealand,50,"Scala, SQL, Git, Deep Learning",Associate,3,Gaming,2025-04-25,2025-06-30,1851,6.8,Neural Networks Co +AI10921,Deep Learning Engineer,197325,USD,197325,EX,FL,United States,S,United States,100,"Scala, Java, R",PhD,14,Manufacturing,2024-03-26,2024-06-06,1769,5,Cognitive Computing +AI10922,Head of AI,23752,USD,23752,EN,FT,India,M,India,0,"SQL, Linux, MLOps, GCP",Master,0,Technology,2024-10-22,2024-12-11,1459,6.8,Machine Intelligence Group +AI10923,Machine Learning Researcher,61586,GBP,46190,EN,FL,United Kingdom,S,United Kingdom,50,"Kubernetes, Tableau, Python, Docker, Java",Associate,0,Telecommunications,2024-10-21,2024-11-22,970,9.3,TechCorp Inc +AI10924,AI Software Engineer,32487,USD,32487,MI,FL,India,S,Latvia,100,"SQL, Git, R",Associate,2,Energy,2024-07-23,2024-09-21,2404,7,DataVision Ltd +AI10925,Deep Learning Engineer,71388,USD,71388,EN,FT,Ireland,S,Ireland,100,"SQL, Scala, Statistics, NLP",Associate,1,Transportation,2024-03-15,2024-04-02,2180,8,DataVision Ltd +AI10926,NLP Engineer,218351,CHF,196516,SE,FL,Switzerland,L,Switzerland,50,"SQL, Hadoop, Deep Learning",Bachelor,8,Government,2024-08-26,2024-09-23,1062,9.4,DataVision Ltd +AI10927,AI Specialist,166329,GBP,124747,EX,PT,United Kingdom,L,United Kingdom,100,"Statistics, Git, PyTorch",Master,14,Retail,2024-05-06,2024-06-02,1104,9.6,AI Innovations +AI10928,AI Software Engineer,75044,GBP,56283,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Java, MLOps, Scala",Master,0,Gaming,2024-12-01,2024-12-15,933,8.6,Cloud AI Solutions +AI10929,AI Consultant,206933,SGD,269013,EX,CT,Singapore,L,Switzerland,0,"Docker, Python, GCP",Bachelor,19,Real Estate,2025-03-11,2025-04-07,1194,7.7,Smart Analytics +AI10930,Machine Learning Engineer,195026,EUR,165772,EX,CT,Germany,M,Germany,100,"SQL, Spark, AWS",Master,10,Media,2025-03-18,2025-05-15,1217,7.7,Machine Intelligence Group +AI10931,Head of AI,104858,USD,104858,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, AWS, PyTorch",PhD,8,Transportation,2024-07-30,2024-09-27,1048,7.3,Future Systems +AI10932,Autonomous Systems Engineer,118890,USD,118890,SE,CT,Israel,S,Israel,0,"Scala, MLOps, Tableau, Kubernetes, Mathematics",Bachelor,6,Retail,2024-08-31,2024-10-02,1165,8.9,Quantum Computing Inc +AI10933,Deep Learning Engineer,87321,EUR,74223,MI,CT,Germany,L,Germany,50,"Git, Computer Vision, Java",PhD,3,Healthcare,2024-01-11,2024-03-01,2443,10,Smart Analytics +AI10934,AI Product Manager,104724,USD,104724,SE,CT,Ireland,S,Ireland,100,"Linux, Data Visualization, Tableau, MLOps, Kubernetes",PhD,9,Gaming,2024-06-02,2024-06-24,1259,8.3,Cloud AI Solutions +AI10935,AI Research Scientist,65970,EUR,56075,MI,FL,Austria,S,Austria,50,"PyTorch, Python, Linux, Scala",PhD,3,Energy,2024-07-01,2024-09-10,2200,5.2,AI Innovations +AI10936,AI Specialist,102652,USD,102652,SE,CT,South Korea,M,South Korea,100,"Data Visualization, Mathematics, GCP",Bachelor,5,Consulting,2024-04-02,2024-04-17,927,6.8,Quantum Computing Inc +AI10937,Data Scientist,120871,EUR,102740,SE,PT,Netherlands,M,Netherlands,100,"Linux, Hadoop, AWS, Data Visualization, GCP",Associate,6,Healthcare,2024-07-24,2024-10-01,1764,7.3,DataVision Ltd +AI10938,NLP Engineer,91506,JPY,10065660,EN,FT,Japan,L,Japan,100,"SQL, Linux, Mathematics",PhD,1,Energy,2025-03-16,2025-04-29,1817,7,Future Systems +AI10939,Data Scientist,156607,CAD,195759,EX,PT,Canada,L,Canada,0,"Spark, Python, Docker",PhD,12,Energy,2024-04-24,2024-06-02,1016,6.4,Autonomous Tech +AI10940,Computer Vision Engineer,114380,USD,114380,MI,FT,Israel,L,Israel,100,"R, GCP, PyTorch",Associate,4,Retail,2025-01-01,2025-02-01,646,7.1,Smart Analytics +AI10941,NLP Engineer,47258,EUR,40169,EN,FT,Austria,S,Austria,0,"Python, Scala, Computer Vision",Associate,1,Gaming,2024-10-28,2024-12-15,1295,6.9,Smart Analytics +AI10942,Computer Vision Engineer,63033,SGD,81943,EN,PT,Singapore,S,Singapore,100,"Python, GCP, Computer Vision, Azure",Associate,1,Retail,2024-11-23,2025-01-01,961,9.4,Machine Intelligence Group +AI10943,Data Analyst,51890,USD,51890,EX,CT,India,S,India,50,"Scala, Computer Vision, Kubernetes, GCP",Master,18,Finance,2025-01-31,2025-04-02,1200,9.1,Advanced Robotics +AI10944,NLP Engineer,114029,EUR,96925,MI,FL,France,L,Philippines,100,"GCP, Java, NLP",PhD,4,Technology,2025-02-07,2025-04-13,2083,5.4,Autonomous Tech +AI10945,Data Engineer,97612,USD,97612,MI,PT,Ireland,L,Ireland,100,"PyTorch, Kubernetes, GCP, NLP",PhD,4,Retail,2024-12-29,2025-01-20,912,6.7,TechCorp Inc +AI10946,Research Scientist,99042,EUR,84186,MI,PT,France,M,France,100,"Docker, Hadoop, Computer Vision",Bachelor,4,Government,2024-01-17,2024-03-19,1864,6,Predictive Systems +AI10947,Deep Learning Engineer,143114,EUR,121647,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Kubernetes",Master,8,Government,2024-08-07,2024-09-02,592,9.3,TechCorp Inc +AI10948,AI Consultant,246283,USD,246283,EX,CT,Norway,S,Norway,0,"R, PyTorch, Mathematics, TensorFlow",Bachelor,13,Healthcare,2025-01-06,2025-02-26,1469,7.7,Algorithmic Solutions +AI10949,NLP Engineer,83037,JPY,9134070,MI,PT,Japan,M,Germany,50,"Python, Data Visualization, TensorFlow, Hadoop",Associate,3,Government,2024-05-28,2024-07-26,1776,8.6,Digital Transformation LLC +AI10950,NLP Engineer,64015,USD,64015,EN,PT,Sweden,L,Sweden,0,"Python, Kubernetes, Docker",Bachelor,1,Technology,2024-10-01,2024-10-20,1023,7.3,AI Innovations +AI10951,Data Scientist,121642,USD,121642,EX,CT,Finland,S,Finland,0,"Kubernetes, NLP, Python, Mathematics",Associate,17,Education,2024-03-26,2024-05-23,549,10,Autonomous Tech +AI10952,AI Software Engineer,76327,GBP,57245,EN,PT,United Kingdom,S,Indonesia,50,"Tableau, GCP, Git, Azure, Kubernetes",Associate,0,Energy,2024-05-17,2024-07-19,1246,8.7,DeepTech Ventures +AI10953,Robotics Engineer,165749,EUR,140887,EX,CT,Austria,S,Austria,0,"Hadoop, Python, TensorFlow",Bachelor,16,Technology,2024-01-19,2024-02-07,1686,6.2,Cloud AI Solutions +AI10954,Data Analyst,137659,USD,137659,SE,FL,Sweden,L,Sweden,100,"Statistics, Docker, TensorFlow",PhD,7,Energy,2025-04-18,2025-06-08,1577,7.6,Machine Intelligence Group +AI10955,AI Specialist,105624,GBP,79218,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, R, Azure, Linux",Master,4,Healthcare,2024-08-18,2024-10-30,641,8.8,TechCorp Inc +AI10956,Autonomous Systems Engineer,146967,USD,146967,MI,CT,Norway,L,Norway,100,"Spark, GCP, Hadoop",Bachelor,4,Technology,2024-04-11,2024-05-09,2256,8.4,Smart Analytics +AI10957,Machine Learning Engineer,76091,USD,76091,EN,PT,Ireland,L,Ireland,100,"Docker, Computer Vision, Git, R, GCP",Bachelor,1,Government,2024-02-08,2024-04-05,1762,5.2,Machine Intelligence Group +AI10958,Machine Learning Researcher,79160,USD,79160,EN,FT,Denmark,M,Luxembourg,50,"Kubernetes, Python, TensorFlow",Bachelor,0,Transportation,2024-01-18,2024-03-14,2020,7.1,Cloud AI Solutions +AI10959,Robotics Engineer,176142,CHF,158528,MI,FT,Switzerland,L,Luxembourg,0,"AWS, R, Data Visualization",PhD,3,Education,2024-03-24,2024-04-10,1000,6.3,Cloud AI Solutions +AI10960,Computer Vision Engineer,85509,EUR,72683,MI,PT,Germany,S,Germany,100,"Data Visualization, MLOps, Kubernetes, SQL, Python",Associate,3,Education,2024-11-01,2025-01-06,610,9.4,Cloud AI Solutions +AI10961,Data Analyst,66853,USD,66853,MI,FL,Finland,S,Finland,100,"R, Mathematics, Linux",PhD,4,Finance,2024-08-02,2024-08-21,1589,5.9,Machine Intelligence Group +AI10962,Research Scientist,26651,USD,26651,MI,FL,India,S,India,100,"Java, SQL, Azure, Git, GCP",Bachelor,4,Transportation,2024-01-18,2024-02-23,1808,8.2,Digital Transformation LLC +AI10963,Machine Learning Engineer,60811,USD,60811,EN,FT,United States,M,United States,0,"MLOps, Tableau, Scala, Hadoop, AWS",Bachelor,0,Gaming,2024-02-14,2024-03-30,997,8.2,Future Systems +AI10964,Data Engineer,65850,USD,65850,EN,CT,South Korea,M,South Korea,0,"Hadoop, GCP, Tableau",Associate,0,Retail,2024-12-05,2025-02-09,580,5.1,Future Systems +AI10965,Deep Learning Engineer,159852,EUR,135874,EX,FL,France,M,France,100,"Kubernetes, Hadoop, Python, AWS",Bachelor,12,Technology,2024-02-26,2024-04-15,694,9,Cloud AI Solutions +AI10966,AI Software Engineer,117072,CHF,105365,MI,CT,Switzerland,M,Luxembourg,100,"Data Visualization, TensorFlow, Python",Master,4,Education,2024-02-01,2024-04-06,1043,9,TechCorp Inc +AI10967,Head of AI,73513,USD,73513,EX,FT,India,S,India,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Consulting,2024-12-31,2025-03-03,2106,5.9,AI Innovations +AI10968,AI Specialist,158422,EUR,134659,EX,PT,Germany,M,Germany,50,"Python, Mathematics, TensorFlow",PhD,19,Consulting,2024-06-19,2024-08-12,732,7.7,Quantum Computing Inc +AI10969,AI Consultant,52063,USD,52063,EN,PT,South Korea,M,South Korea,0,"Computer Vision, MLOps, Mathematics, Docker",PhD,1,Finance,2025-04-04,2025-05-02,2052,5.9,TechCorp Inc +AI10970,AI Architect,87999,USD,87999,EN,PT,Norway,L,Norway,50,"Azure, Python, Computer Vision",PhD,0,Consulting,2025-01-25,2025-03-04,2011,9.3,Cognitive Computing +AI10971,Robotics Engineer,65735,AUD,88742,EN,FL,Australia,S,Vietnam,100,"Scala, Git, Statistics",Associate,1,Real Estate,2025-02-02,2025-03-04,776,9.9,AI Innovations +AI10972,Machine Learning Researcher,79748,USD,79748,EX,FT,India,M,India,100,"NLP, Python, Mathematics, GCP",Master,17,Education,2025-02-02,2025-03-10,998,9.9,DeepTech Ventures +AI10973,Machine Learning Engineer,153047,CHF,137742,MI,FT,Switzerland,L,New Zealand,0,"SQL, Python, R",Master,3,Retail,2024-07-25,2024-09-26,1468,5.9,Future Systems +AI10974,Data Analyst,82660,GBP,61995,EN,PT,United Kingdom,L,United Kingdom,100,"Java, R, Mathematics",Bachelor,1,Retail,2024-09-09,2024-10-07,599,9.5,Smart Analytics +AI10975,Computer Vision Engineer,245036,USD,245036,EX,CT,United States,S,United States,100,"Git, Linux, Kubernetes, Deep Learning, NLP",Bachelor,17,Technology,2024-05-15,2024-07-22,804,9.9,Smart Analytics +AI10976,AI Research Scientist,223802,AUD,302133,EX,PT,Australia,S,Australia,100,"AWS, Kubernetes, Computer Vision",Bachelor,11,Energy,2024-11-04,2025-01-10,964,7.1,Cloud AI Solutions +AI10977,Machine Learning Researcher,83891,AUD,113253,MI,FL,Australia,M,Australia,50,"Git, MLOps, Scala, GCP, Spark",Master,3,Real Estate,2025-02-23,2025-04-21,852,6.8,Advanced Robotics +AI10978,Machine Learning Researcher,98442,GBP,73832,SE,PT,United Kingdom,S,United Kingdom,50,"SQL, Git, TensorFlow, Python",PhD,5,Education,2024-03-31,2024-04-21,1604,9.9,Advanced Robotics +AI10979,NLP Engineer,128077,JPY,14088470,SE,FL,Japan,M,Japan,100,"TensorFlow, Python, MLOps, Git",Associate,6,Energy,2024-03-06,2024-04-22,1539,5.5,TechCorp Inc +AI10980,Data Scientist,186264,USD,186264,EX,FT,Sweden,M,Sweden,0,"SQL, Computer Vision, Scala",Bachelor,15,Finance,2024-07-16,2024-09-10,612,7.4,Advanced Robotics +AI10981,AI Research Scientist,110728,USD,110728,MI,CT,Norway,M,Norway,0,"TensorFlow, Python, Kubernetes, R",PhD,3,Technology,2025-03-23,2025-04-11,1637,8.5,Algorithmic Solutions +AI10982,Robotics Engineer,215988,USD,215988,EX,PT,Denmark,M,Denmark,0,"PyTorch, Deep Learning, NLP, Git",Associate,15,Manufacturing,2024-06-09,2024-06-23,508,9.8,Cognitive Computing +AI10983,Autonomous Systems Engineer,125459,USD,125459,SE,CT,Israel,S,Indonesia,50,"Python, Scala, Kubernetes, Deep Learning, AWS",PhD,6,Automotive,2024-03-23,2024-05-26,1423,7.2,AI Innovations +AI10984,ML Ops Engineer,247115,USD,247115,EX,FL,United States,L,United States,0,"TensorFlow, R, Deep Learning, GCP, Git",Associate,19,Consulting,2024-12-03,2025-01-24,1894,5.5,Digital Transformation LLC +AI10985,Machine Learning Engineer,311593,USD,311593,EX,FL,Norway,L,Norway,0,"Linux, Python, TensorFlow",Master,16,Finance,2025-01-23,2025-03-08,1712,7.9,Future Systems +AI10986,Data Analyst,129554,USD,129554,EX,FT,China,L,China,0,"Data Visualization, Kubernetes, Java",Associate,18,Consulting,2025-03-23,2025-05-28,705,9.2,Cloud AI Solutions +AI10987,Deep Learning Engineer,284164,USD,284164,EX,PT,Norway,L,Norway,100,"R, Statistics, SQL, Python, Linux",Master,14,Telecommunications,2024-02-03,2024-02-28,2259,6.5,Cognitive Computing +AI10988,Deep Learning Engineer,144657,EUR,122958,SE,FT,Netherlands,L,Netherlands,0,"SQL, Statistics, Linux",Master,5,Government,2025-02-23,2025-04-30,586,5.7,Predictive Systems +AI10989,Computer Vision Engineer,178156,CAD,222695,EX,FT,Canada,M,Canada,0,"Kubernetes, SQL, Azure, Hadoop",PhD,19,Automotive,2025-02-03,2025-03-22,1702,7.2,Neural Networks Co +AI10990,Data Scientist,86173,CAD,107716,MI,FL,Canada,M,Canada,100,"MLOps, Git, PyTorch, Mathematics",Associate,2,Healthcare,2024-08-09,2024-10-03,1035,8.4,Cloud AI Solutions +AI10991,Data Scientist,106280,SGD,138164,MI,PT,Singapore,L,Czech Republic,100,"Java, SQL, Kubernetes, AWS",Associate,2,Energy,2024-11-26,2025-01-07,779,5.8,TechCorp Inc +AI10992,Data Scientist,80053,AUD,108072,MI,FL,Australia,M,Australia,50,"Deep Learning, Linux, MLOps, SQL, Kubernetes",Master,4,Healthcare,2025-03-05,2025-03-20,1525,9.8,TechCorp Inc +AI10993,AI Architect,91642,CAD,114553,MI,CT,Canada,M,Canada,50,"Git, Docker, Spark, R, Mathematics",Master,2,Real Estate,2024-11-17,2024-12-09,1599,5.7,AI Innovations +AI10994,Data Analyst,72487,EUR,61614,EN,FL,Germany,S,Netherlands,0,"PyTorch, Tableau, Mathematics, MLOps",PhD,1,Education,2025-02-01,2025-02-19,2284,6,Future Systems +AI10995,Data Analyst,40355,USD,40355,EN,FT,China,L,Denmark,0,"Python, TensorFlow, PyTorch, AWS",PhD,0,Gaming,2024-12-21,2025-01-26,1733,5.1,Cognitive Computing +AI10996,AI Architect,185648,USD,185648,EX,FL,Denmark,M,Denmark,50,"Tableau, TensorFlow, Git, Statistics",PhD,18,Education,2024-11-08,2025-01-11,711,7.2,Quantum Computing Inc +AI10997,NLP Engineer,177709,USD,177709,EX,PT,Ireland,M,Ireland,100,"AWS, MLOps, Deep Learning",Master,13,Real Estate,2024-04-13,2024-06-02,1165,6.5,Predictive Systems +AI10998,Computer Vision Engineer,60113,EUR,51096,EN,CT,Netherlands,S,Netherlands,100,"AWS, Data Visualization, Linux, TensorFlow",Associate,0,Consulting,2024-12-01,2025-01-06,1214,6.7,AI Innovations +AI10999,Data Engineer,170719,USD,170719,EX,FL,Norway,S,Norway,100,"Hadoop, Python, TensorFlow",PhD,13,Consulting,2025-01-31,2025-04-04,2355,6.2,AI Innovations +AI11000,Principal Data Scientist,94395,USD,94395,MI,CT,South Korea,L,South Korea,0,"R, SQL, Kubernetes",PhD,4,Telecommunications,2024-11-11,2024-12-13,1904,6.7,Digital Transformation LLC +AI11001,Robotics Engineer,170094,EUR,144580,EX,FL,Netherlands,L,Netherlands,50,"Kubernetes, Git, PyTorch, SQL, Deep Learning",Associate,12,Automotive,2025-02-25,2025-04-07,1931,9,Predictive Systems +AI11002,Robotics Engineer,44187,USD,44187,MI,FT,China,S,China,100,"TensorFlow, Docker, Scala",Associate,4,Manufacturing,2025-04-07,2025-05-06,1790,5.4,Predictive Systems +AI11003,NLP Engineer,199463,USD,199463,EX,FT,Ireland,S,Chile,0,"Tableau, TensorFlow, Linux, Python",Bachelor,16,Manufacturing,2024-10-06,2024-11-13,833,6.1,TechCorp Inc +AI11004,Machine Learning Researcher,103266,CAD,129083,SE,PT,Canada,M,Canada,100,"Python, Kubernetes, Docker",Master,9,Education,2024-10-12,2024-12-17,1567,8.5,Quantum Computing Inc +AI11005,Head of AI,74247,EUR,63110,MI,PT,Austria,M,Poland,100,"SQL, Deep Learning, Python, Hadoop",PhD,2,Finance,2025-03-10,2025-04-26,1921,7.6,DeepTech Ventures +AI11006,Robotics Engineer,267617,GBP,200713,EX,FL,United Kingdom,M,Egypt,100,"Python, TensorFlow, PyTorch, Tableau, Docker",Associate,12,Technology,2024-02-04,2024-04-16,1058,8.6,Future Systems +AI11007,AI Product Manager,170750,EUR,145138,SE,PT,Netherlands,L,Hungary,0,"Python, Data Visualization, MLOps, Hadoop, AWS",Associate,5,Finance,2024-07-14,2024-08-11,1811,7.5,Predictive Systems +AI11008,AI Architect,151644,EUR,128897,EX,FT,Germany,S,Germany,0,"TensorFlow, Tableau, GCP, PyTorch, Statistics",Associate,10,Automotive,2025-02-22,2025-04-29,1657,6.4,DeepTech Ventures +AI11009,Head of AI,19668,USD,19668,EN,CT,India,M,India,50,"MLOps, Scala, GCP, AWS, Kubernetes",Bachelor,0,Real Estate,2024-08-28,2024-09-13,1898,7.2,Advanced Robotics +AI11010,AI Specialist,133233,USD,133233,SE,FT,Sweden,M,Sweden,50,"SQL, PyTorch, Linux, Deep Learning",Master,8,Manufacturing,2024-08-20,2024-10-19,1836,6.2,Advanced Robotics +AI11011,AI Consultant,62844,USD,62844,EN,PT,Ireland,S,Ireland,50,"Git, PyTorch, TensorFlow, Docker",Bachelor,1,Media,2024-03-26,2024-05-17,987,8.8,Machine Intelligence Group +AI11012,Data Scientist,144621,USD,144621,SE,FL,Norway,S,Norway,50,"Spark, Kubernetes, Computer Vision, AWS",Associate,6,Transportation,2024-10-31,2024-11-29,2429,5.4,Digital Transformation LLC +AI11013,AI Product Manager,121548,USD,121548,SE,FT,United States,M,United States,50,"Hadoop, Deep Learning, Kubernetes, Spark, Python",Master,6,Real Estate,2024-11-28,2025-01-20,959,6.8,Algorithmic Solutions +AI11014,ML Ops Engineer,355399,CHF,319859,EX,FT,Switzerland,M,Switzerland,0,"GCP, Git, Computer Vision",Bachelor,14,Technology,2024-07-25,2024-08-29,1808,8.8,Digital Transformation LLC +AI11015,AI Research Scientist,261652,USD,261652,EX,PT,Norway,S,Norway,0,"SQL, AWS, GCP",Bachelor,10,Transportation,2024-12-24,2025-02-12,536,6,Quantum Computing Inc +AI11016,Principal Data Scientist,135239,USD,135239,SE,FL,United States,M,United States,0,"Python, Data Visualization, Hadoop, Scala",Bachelor,9,Automotive,2024-10-13,2024-11-21,941,5.3,AI Innovations +AI11017,AI Research Scientist,136136,USD,136136,SE,FL,United States,M,United States,0,"GCP, Data Visualization, PyTorch, R, Spark",Master,7,Real Estate,2024-02-17,2024-03-04,2020,9.3,Predictive Systems +AI11018,Computer Vision Engineer,162399,USD,162399,EX,FT,Ireland,S,Ireland,100,"R, GCP, MLOps, Python",Associate,16,Media,2025-04-10,2025-05-26,1549,5.8,DataVision Ltd +AI11019,Data Scientist,250763,GBP,188072,EX,FL,United Kingdom,L,Czech Republic,100,"Data Visualization, TensorFlow, NLP, Statistics",Associate,12,Transportation,2024-09-21,2024-10-27,1830,7.4,Cognitive Computing +AI11020,Deep Learning Engineer,63767,EUR,54202,EN,PT,Germany,S,Germany,50,"Hadoop, Data Visualization, GCP",Master,1,Consulting,2025-04-17,2025-05-08,1518,9.1,Cloud AI Solutions +AI11021,Research Scientist,74764,EUR,63549,MI,FL,Austria,M,Austria,50,"Python, TensorFlow, NLP",Master,2,Telecommunications,2024-12-05,2025-02-06,2011,5.2,Quantum Computing Inc +AI11022,Research Scientist,46031,USD,46031,EN,FT,Israel,S,Hungary,50,"Kubernetes, Java, Scala",PhD,1,Transportation,2024-10-28,2024-12-28,648,8.6,Cognitive Computing +AI11023,AI Consultant,52060,EUR,44251,EN,FL,Austria,M,Austria,50,"R, Hadoop, SQL",PhD,0,Automotive,2024-12-10,2025-01-19,1945,5.2,DataVision Ltd +AI11024,Autonomous Systems Engineer,138305,EUR,117559,SE,CT,France,M,France,50,"Java, Hadoop, NLP, Computer Vision",PhD,8,Consulting,2025-01-09,2025-02-16,1084,5.7,AI Innovations +AI11025,AI Product Manager,82393,USD,82393,MI,PT,United States,S,United States,100,"Docker, PyTorch, R, Azure",Bachelor,2,Government,2025-04-07,2025-05-14,2069,8.7,Quantum Computing Inc +AI11026,AI Product Manager,174517,USD,174517,EX,CT,Sweden,L,Sweden,100,"TensorFlow, Docker, R",PhD,16,Telecommunications,2024-10-06,2024-11-22,1820,9.2,TechCorp Inc +AI11027,Robotics Engineer,133855,USD,133855,MI,PT,Norway,L,Norway,0,"SQL, MLOps, Data Visualization",Bachelor,4,Automotive,2024-12-12,2024-12-30,1909,8.8,Future Systems +AI11028,Data Analyst,114683,EUR,97481,SE,FL,Austria,L,Ukraine,50,"Git, Hadoop, Java",PhD,7,Consulting,2025-03-06,2025-04-15,1203,8.5,Cloud AI Solutions +AI11029,Data Analyst,144927,CHF,130434,MI,FL,Switzerland,M,Ghana,50,"R, SQL, Java, Hadoop, Git",Master,3,Government,2025-02-18,2025-04-26,1093,5.9,Smart Analytics +AI11030,AI Software Engineer,125273,AUD,169119,SE,CT,Australia,S,Australia,100,"AWS, Python, GCP, Spark, TensorFlow",PhD,7,Finance,2024-04-14,2024-05-01,2128,9.5,Predictive Systems +AI11031,AI Consultant,147687,EUR,125534,SE,PT,Netherlands,L,Ireland,0,"Hadoop, Spark, PyTorch, Scala",Associate,5,Education,2024-10-21,2024-11-04,2008,7.1,Future Systems +AI11032,Data Scientist,50116,USD,50116,EN,CT,Finland,M,Vietnam,0,"Java, Kubernetes, Data Visualization, GCP, NLP",Bachelor,1,Education,2024-12-25,2025-01-26,1419,7.3,Algorithmic Solutions +AI11033,Data Analyst,104932,EUR,89192,MI,PT,Netherlands,S,Netherlands,100,"Linux, Scala, MLOps",Associate,2,Consulting,2024-12-16,2025-01-17,2408,7.1,Predictive Systems +AI11034,Machine Learning Engineer,109091,CAD,136364,SE,FL,Canada,M,Canada,0,"PyTorch, R, GCP, Tableau",PhD,8,Government,2024-08-31,2024-09-19,1227,7.5,Advanced Robotics +AI11035,Machine Learning Engineer,108563,GBP,81422,MI,CT,United Kingdom,L,Japan,50,"Python, PyTorch, Scala, SQL",Associate,4,Finance,2024-08-20,2024-10-19,663,6.6,Digital Transformation LLC +AI11036,AI Research Scientist,69383,SGD,90198,EN,FT,Singapore,M,Singapore,100,"Kubernetes, Statistics, GCP",Associate,0,Media,2024-04-15,2024-05-30,643,5.7,AI Innovations +AI11037,Principal Data Scientist,83302,JPY,9163220,MI,FL,Japan,S,Japan,0,"Java, MLOps, Tableau",Master,2,Automotive,2024-03-01,2024-04-30,1368,5.8,Algorithmic Solutions +AI11038,NLP Engineer,253256,EUR,215268,EX,FL,Netherlands,M,Netherlands,50,"Scala, Docker, Computer Vision, Python, Mathematics",Associate,14,Education,2024-12-01,2025-01-10,2350,9.3,DeepTech Ventures +AI11039,Autonomous Systems Engineer,247403,USD,247403,EX,PT,United States,M,United States,50,"Tableau, Docker, Python, Git",Bachelor,19,Education,2024-10-06,2024-12-04,2319,6.1,Smart Analytics +AI11040,Computer Vision Engineer,75025,USD,75025,MI,FL,Ireland,S,Canada,0,"PyTorch, R, Spark, MLOps, Git",Associate,2,Transportation,2024-10-06,2024-11-29,1591,8,TechCorp Inc +AI11041,AI Consultant,60929,USD,60929,EN,FT,Israel,M,Israel,0,"Hadoop, Git, Data Visualization",PhD,1,Retail,2025-03-20,2025-04-13,1691,9.7,Algorithmic Solutions +AI11042,AI Consultant,55166,GBP,41375,EN,FT,United Kingdom,M,United Kingdom,50,"Kubernetes, Statistics, Deep Learning, Tableau, MLOps",PhD,0,Media,2024-01-16,2024-03-22,1296,6,Cognitive Computing +AI11043,Data Engineer,70004,USD,70004,EN,PT,Sweden,M,Sweden,0,"R, Git, Java, Linux",Associate,0,Healthcare,2024-05-30,2024-08-02,2277,8.2,Future Systems +AI11044,AI Specialist,275697,USD,275697,EX,CT,Norway,L,Norway,0,"AWS, PyTorch, SQL, TensorFlow",Master,19,Government,2025-02-28,2025-05-04,951,8.6,Smart Analytics +AI11045,Principal Data Scientist,52725,EUR,44816,EN,PT,Germany,M,Ukraine,100,"Python, Computer Vision, Azure",Bachelor,0,Media,2024-08-11,2024-09-10,1030,5.1,Quantum Computing Inc +AI11046,Computer Vision Engineer,268365,USD,268365,EX,FL,Norway,M,United States,0,"Python, Azure, Data Visualization",Associate,11,Gaming,2025-03-04,2025-04-12,1695,9.3,DataVision Ltd +AI11047,Principal Data Scientist,76596,JPY,8425560,MI,PT,Japan,M,China,50,"Java, Linux, Python",Associate,2,Retail,2024-11-08,2024-12-05,623,7.5,Smart Analytics +AI11048,Computer Vision Engineer,285551,AUD,385494,EX,FL,Australia,L,Australia,50,"Python, NLP, Mathematics, PyTorch, Spark",Bachelor,12,Automotive,2024-02-28,2024-03-21,570,5.4,TechCorp Inc +AI11049,Robotics Engineer,118954,CAD,148693,SE,PT,Canada,L,Canada,100,"Python, PyTorch, Statistics",PhD,5,Government,2025-04-25,2025-05-15,2402,8.9,Cloud AI Solutions +AI11050,ML Ops Engineer,153938,CAD,192423,EX,CT,Canada,S,Canada,0,"PyTorch, Kubernetes, Scala, R, Data Visualization",Associate,16,Real Estate,2024-11-11,2024-12-29,1553,8.6,Advanced Robotics +AI11051,Deep Learning Engineer,131972,GBP,98979,MI,PT,United Kingdom,L,United Kingdom,100,"NLP, GCP, Python, Linux, Azure",Master,2,Manufacturing,2024-11-18,2024-12-21,2189,5.1,Advanced Robotics +AI11052,AI Product Manager,123154,USD,123154,EX,PT,Israel,S,Israel,50,"Data Visualization, Linux, Java",Bachelor,18,Energy,2024-07-29,2024-09-27,1275,7.4,Future Systems +AI11053,ML Ops Engineer,84249,JPY,9267390,MI,FL,Japan,M,Italy,50,"Java, NLP, Azure",Associate,4,Education,2024-04-25,2024-06-22,857,6.5,Smart Analytics +AI11054,Principal Data Scientist,93431,USD,93431,MI,PT,Sweden,S,Vietnam,50,"GCP, Tableau, Computer Vision, Linux",Associate,2,Finance,2025-02-04,2025-02-18,939,5,DataVision Ltd +AI11055,Computer Vision Engineer,135625,EUR,115281,EX,FL,France,M,France,0,"MLOps, Scala, NLP, PyTorch",Master,17,Gaming,2024-07-04,2024-08-28,1870,9.5,TechCorp Inc +AI11056,AI Product Manager,218295,EUR,185551,EX,PT,Austria,L,Austria,50,"SQL, Kubernetes, Docker, Tableau",Master,14,Gaming,2024-06-29,2024-08-03,1091,9.3,Predictive Systems +AI11057,ML Ops Engineer,99582,USD,99582,EN,FL,Denmark,L,Netherlands,100,"Linux, Data Visualization, PyTorch",Associate,1,Consulting,2025-03-29,2025-04-25,1168,9.6,Autonomous Tech +AI11058,Robotics Engineer,262079,GBP,196559,EX,FL,United Kingdom,L,United Kingdom,100,"Python, Java, Spark",Master,15,Technology,2024-02-06,2024-03-22,811,9.7,Smart Analytics +AI11059,AI Research Scientist,124785,USD,124785,SE,FT,Israel,M,Israel,50,"GCP, Scala, NLP, Kubernetes",Bachelor,7,Government,2024-12-19,2025-01-07,820,5.3,Cognitive Computing +AI11060,Autonomous Systems Engineer,78762,USD,78762,MI,FT,South Korea,S,South Korea,100,"TensorFlow, Python, Docker",Associate,3,Transportation,2024-01-05,2024-01-28,1893,8.9,Autonomous Tech +AI11061,Computer Vision Engineer,116968,JPY,12866480,MI,PT,Japan,M,Japan,50,"Java, R, Mathematics, Data Visualization, NLP",Bachelor,4,Manufacturing,2024-09-14,2024-10-25,2019,6.7,Machine Intelligence Group +AI11062,Machine Learning Researcher,82720,EUR,70312,MI,FT,Netherlands,M,Netherlands,0,"Data Visualization, Kubernetes, Azure",PhD,2,Telecommunications,2024-12-30,2025-03-08,812,9.1,DeepTech Ventures +AI11063,Data Analyst,105375,USD,105375,MI,FL,United States,M,United States,50,"TensorFlow, GCP, Azure, Hadoop",Master,3,Retail,2024-06-04,2024-07-24,1249,6.6,Algorithmic Solutions +AI11064,Computer Vision Engineer,123190,EUR,104712,EX,PT,Austria,S,Austria,50,"Data Visualization, AWS, Linux, Computer Vision, Statistics",Master,10,Real Estate,2024-07-11,2024-08-26,1042,9.7,DataVision Ltd +AI11065,ML Ops Engineer,277393,EUR,235784,EX,FL,Germany,L,Germany,0,"Kubernetes, Computer Vision, Git, Mathematics",Bachelor,17,Finance,2024-09-07,2024-11-01,996,5.5,DataVision Ltd +AI11066,Robotics Engineer,106542,EUR,90561,SE,FL,Germany,S,Germany,100,"Tableau, Java, Computer Vision",Bachelor,6,Media,2024-07-24,2024-09-12,547,8.7,DataVision Ltd +AI11067,NLP Engineer,94499,EUR,80324,MI,FL,France,L,Kenya,50,"Git, Java, MLOps, Computer Vision",Bachelor,2,Gaming,2024-02-12,2024-04-15,821,7.8,Quantum Computing Inc +AI11068,Autonomous Systems Engineer,189283,CHF,170355,SE,PT,Switzerland,M,Latvia,0,"Scala, GCP, Deep Learning",Master,8,Education,2024-06-16,2024-07-24,1321,9.7,Cloud AI Solutions +AI11069,Computer Vision Engineer,157133,EUR,133563,SE,FL,Germany,L,Germany,100,"Python, Git, Kubernetes, Deep Learning, R",Master,9,Finance,2024-08-07,2024-09-30,913,6.6,Algorithmic Solutions +AI11070,Robotics Engineer,258931,USD,258931,EX,FT,Denmark,S,Argentina,100,"Python, AWS, Docker",Associate,15,Government,2024-06-22,2024-07-31,1270,5.5,AI Innovations +AI11071,AI Specialist,94485,CAD,118106,MI,CT,Canada,M,Canada,50,"Java, Hadoop, SQL, Mathematics, GCP",Bachelor,3,Technology,2025-02-28,2025-03-23,1538,8.3,DataVision Ltd +AI11072,AI Architect,53437,USD,53437,EN,PT,Sweden,S,Sweden,50,"SQL, Hadoop, Linux",Bachelor,1,Government,2024-01-07,2024-02-08,980,9.9,Predictive Systems +AI11073,Computer Vision Engineer,81989,EUR,69691,MI,FT,France,S,Russia,100,"TensorFlow, Tableau, Mathematics, Java",Associate,2,Automotive,2024-03-08,2024-04-05,1163,7.1,Quantum Computing Inc +AI11074,AI Software Engineer,53872,GBP,40404,EN,PT,United Kingdom,S,Vietnam,100,"Python, SQL, Hadoop",PhD,1,Real Estate,2024-08-01,2024-09-27,1286,5.1,Predictive Systems +AI11075,AI Product Manager,112299,USD,112299,MI,PT,Finland,L,Finland,100,"Python, TensorFlow, Docker, PyTorch, Scala",Bachelor,4,Manufacturing,2024-05-06,2024-06-02,2011,8.1,AI Innovations +AI11076,Head of AI,148344,EUR,126092,EX,PT,Austria,M,Nigeria,50,"Git, Kubernetes, GCP, Tableau, MLOps",Associate,17,Education,2024-09-28,2024-11-09,1791,6.3,Future Systems +AI11077,AI Consultant,149732,AUD,202138,EX,PT,Australia,M,Australia,50,"Python, Git, NLP, Scala",PhD,19,Retail,2024-03-31,2024-04-28,1510,9.2,Cloud AI Solutions +AI11078,Research Scientist,86366,USD,86366,MI,FL,United States,S,United States,0,"Git, Scala, MLOps, R",PhD,4,Manufacturing,2025-04-23,2025-05-07,2253,7.7,Digital Transformation LLC +AI11079,AI Specialist,126508,USD,126508,MI,FL,Norway,S,Malaysia,0,"GCP, AWS, Data Visualization, Python, TensorFlow",Bachelor,3,Finance,2024-01-17,2024-03-07,1652,9.3,AI Innovations +AI11080,Data Scientist,88565,USD,88565,MI,FT,Israel,M,Malaysia,0,"MLOps, Mathematics, TensorFlow, GCP, AWS",Master,3,Media,2024-01-27,2024-02-19,1483,9.6,Future Systems +AI11081,AI Software Engineer,67656,USD,67656,EN,FT,Ireland,L,Czech Republic,0,"Python, Azure, Kubernetes",Associate,0,Retail,2024-06-20,2024-08-08,2044,6.3,Neural Networks Co +AI11082,AI Architect,112374,EUR,95518,MI,FT,Netherlands,L,Netherlands,50,"Scala, R, Spark",Associate,4,Retail,2025-01-11,2025-02-20,1000,6.6,DeepTech Ventures +AI11083,AI Research Scientist,117883,JPY,12967130,MI,PT,Japan,L,Japan,0,"Data Visualization, Hadoop, Linux",Master,3,Transportation,2024-01-15,2024-01-29,727,9.2,Autonomous Tech +AI11084,AI Software Engineer,121000,USD,121000,SE,FL,United States,M,China,100,"Java, Deep Learning, MLOps, Git",Bachelor,5,Media,2025-04-16,2025-05-28,2140,6.8,DeepTech Ventures +AI11085,Data Engineer,207170,CAD,258963,EX,FL,Canada,L,Canada,0,"TensorFlow, Statistics, Spark, SQL",Master,17,Healthcare,2024-10-28,2024-12-06,766,9.4,Smart Analytics +AI11086,AI Architect,116459,USD,116459,SE,FT,South Korea,L,South Korea,50,"Tableau, Azure, Java, NLP, R",Associate,5,Education,2025-04-25,2025-05-31,502,9.5,Predictive Systems +AI11087,Autonomous Systems Engineer,122703,CHF,110433,MI,FL,Switzerland,L,Switzerland,0,"Linux, Azure, Mathematics",PhD,2,Government,2024-12-26,2025-03-03,2270,8.4,Future Systems +AI11088,Computer Vision Engineer,97199,USD,97199,EN,CT,Norway,L,Norway,50,"Deep Learning, TensorFlow, Scala, Computer Vision, Linux",Bachelor,0,Gaming,2024-06-12,2024-07-22,2472,9,Future Systems +AI11089,Principal Data Scientist,290472,GBP,217854,EX,FT,United Kingdom,L,Italy,100,"Tableau, AWS, TensorFlow",Master,16,Media,2024-09-15,2024-10-23,1094,7.3,TechCorp Inc +AI11090,AI Specialist,81583,EUR,69346,EN,FL,France,L,France,100,"Spark, MLOps, Linux",Bachelor,1,Manufacturing,2024-04-08,2024-06-20,1025,9.5,Neural Networks Co +AI11091,Robotics Engineer,96594,USD,96594,MI,FT,Finland,L,Finland,50,"Linux, GCP, Tableau",Master,4,Media,2024-11-23,2025-01-26,1434,5.8,Algorithmic Solutions +AI11092,AI Consultant,64211,USD,64211,SE,FT,China,S,China,100,"R, Kubernetes, Tableau, Computer Vision, Azure",Master,7,Transportation,2024-01-19,2024-03-19,629,7,Future Systems +AI11093,Data Analyst,155715,EUR,132358,EX,CT,France,L,France,100,"Statistics, Mathematics, Data Visualization, Hadoop, Python",Master,18,Government,2024-04-25,2024-07-07,749,9.6,TechCorp Inc +AI11094,NLP Engineer,114469,USD,114469,MI,FT,Ireland,L,Switzerland,50,"Docker, Kubernetes, GCP",Associate,4,Media,2024-06-23,2024-07-09,556,8.2,Smart Analytics +AI11095,Autonomous Systems Engineer,90803,USD,90803,MI,FT,Ireland,S,India,100,"R, GCP, Computer Vision, Statistics",Bachelor,2,Gaming,2024-10-05,2024-10-29,983,7.6,Machine Intelligence Group +AI11096,Autonomous Systems Engineer,52790,USD,52790,EN,PT,Finland,S,Finland,0,"Kubernetes, R, Computer Vision, Java, Git",Associate,1,Gaming,2024-02-20,2024-04-06,637,9.2,Quantum Computing Inc +AI11097,AI Product Manager,123158,EUR,104684,SE,FL,Germany,S,Germany,50,"Linux, Tableau, Docker, Deep Learning",Bachelor,9,Gaming,2024-09-26,2024-11-06,1797,9.5,Predictive Systems +AI11098,NLP Engineer,136173,USD,136173,EX,FL,Ireland,M,Ireland,0,"Mathematics, Git, Scala",Bachelor,15,Finance,2024-03-06,2024-03-22,1892,9.9,AI Innovations +AI11099,AI Product Manager,33349,USD,33349,EN,FT,China,S,China,50,"AWS, Hadoop, MLOps, TensorFlow",PhD,1,Education,2025-02-15,2025-04-19,1995,9.9,Advanced Robotics +AI11100,Robotics Engineer,109691,USD,109691,EX,FL,China,L,China,100,"Git, PyTorch, SQL",PhD,12,Retail,2024-12-10,2025-01-27,542,8.7,Advanced Robotics +AI11101,AI Software Engineer,154172,USD,154172,SE,PT,Sweden,L,Sweden,50,"Scala, Deep Learning, Data Visualization, Tableau, Docker",Master,7,Real Estate,2024-12-03,2025-02-02,870,8.2,Quantum Computing Inc +AI11102,NLP Engineer,62316,AUD,84127,EN,FT,Australia,S,United States,100,"Python, AWS, Deep Learning, Kubernetes, Statistics",Associate,1,Finance,2024-09-14,2024-10-28,1518,7.6,Digital Transformation LLC +AI11103,Data Scientist,100179,USD,100179,SE,FT,Sweden,S,Finland,100,"Computer Vision, Mathematics, Linux, AWS",PhD,7,Transportation,2024-12-15,2025-01-25,722,9.9,Cognitive Computing +AI11104,Research Scientist,165296,SGD,214885,EX,FT,Singapore,S,Singapore,0,"NLP, SQL, Java, PyTorch",PhD,10,Consulting,2024-10-06,2024-11-08,1218,8.4,Predictive Systems +AI11105,Research Scientist,199699,AUD,269594,EX,FL,Australia,S,Australia,100,"Data Visualization, Python, Kubernetes, Deep Learning, Tableau",Associate,11,Technology,2024-11-10,2024-11-28,1954,8.6,Digital Transformation LLC +AI11106,Autonomous Systems Engineer,199230,USD,199230,SE,FL,Norway,L,Norway,0,"Azure, TensorFlow, Scala, Python, Java",Associate,8,Media,2025-04-19,2025-05-28,1359,8.2,Quantum Computing Inc +AI11107,Data Analyst,60772,AUD,82042,EN,PT,Australia,L,Australia,50,"Deep Learning, Linux, Data Visualization",Associate,0,Real Estate,2024-04-25,2024-06-22,2427,5.6,Machine Intelligence Group +AI11108,Head of AI,35534,USD,35534,MI,CT,China,S,China,50,"Python, TensorFlow, NLP, Scala",Bachelor,3,Finance,2024-01-16,2024-03-12,1054,7.2,Neural Networks Co +AI11109,Principal Data Scientist,127355,EUR,108252,SE,CT,France,S,Colombia,50,"GCP, Java, Scala, Data Visualization, Computer Vision",Associate,7,Healthcare,2025-02-09,2025-04-11,1012,7.9,Smart Analytics +AI11110,AI Research Scientist,150163,USD,150163,SE,PT,Sweden,M,Sweden,100,"Docker, Azure, Data Visualization, Spark, Kubernetes",Bachelor,8,Media,2025-03-16,2025-04-23,1933,6.9,Cognitive Computing +AI11111,Deep Learning Engineer,34278,USD,34278,SE,CT,India,S,India,0,"Data Visualization, Kubernetes, Scala, Statistics",Associate,8,Real Estate,2024-05-23,2024-06-29,550,8.4,Autonomous Tech +AI11112,Robotics Engineer,50385,JPY,5542350,EN,PT,Japan,S,Japan,0,"GCP, Kubernetes, Java, Spark",Bachelor,1,Energy,2024-01-17,2024-02-08,851,8.2,AI Innovations +AI11113,AI Software Engineer,127626,USD,127626,MI,FL,Norway,S,Nigeria,0,"Python, TensorFlow, Data Visualization",Bachelor,2,Technology,2024-09-05,2024-10-01,782,5.9,Predictive Systems +AI11114,Robotics Engineer,87121,USD,87121,EN,FL,Ireland,L,Ireland,0,"Python, Java, AWS, MLOps, Statistics",Master,0,Transportation,2024-07-14,2024-09-22,1394,6.5,AI Innovations +AI11115,Computer Vision Engineer,242532,EUR,206152,EX,FL,Austria,L,Czech Republic,50,"TensorFlow, GCP, Statistics, AWS",PhD,19,Transportation,2024-02-22,2024-04-09,2387,6.6,DataVision Ltd +AI11116,Autonomous Systems Engineer,42882,USD,42882,EN,PT,South Korea,S,Chile,50,"Data Visualization, Docker, Computer Vision, Hadoop",Master,0,Energy,2024-01-31,2024-03-28,2147,8.2,TechCorp Inc +AI11117,AI Software Engineer,63065,USD,63065,MI,CT,South Korea,S,Portugal,50,"SQL, Scala, Mathematics, R",PhD,2,Energy,2024-12-28,2025-02-24,1177,7.8,Smart Analytics +AI11118,Autonomous Systems Engineer,54039,USD,54039,SE,FL,China,S,China,100,"Spark, TensorFlow, Data Visualization",Associate,8,Healthcare,2025-02-05,2025-04-18,1353,5.6,Cognitive Computing +AI11119,Robotics Engineer,184798,JPY,20327780,EX,PT,Japan,L,South Africa,0,"Mathematics, Statistics, Python",Associate,18,Telecommunications,2025-02-07,2025-02-27,1660,9.1,TechCorp Inc +AI11120,Research Scientist,238260,USD,238260,EX,PT,Sweden,L,Sweden,100,"Python, TensorFlow, R, Computer Vision",Associate,12,Media,2025-04-16,2025-06-01,1703,5.3,Quantum Computing Inc +AI11121,Autonomous Systems Engineer,261853,USD,261853,EX,FL,Denmark,S,Denmark,100,"Docker, Linux, PyTorch",PhD,19,Finance,2024-01-28,2024-03-08,1113,8.7,Predictive Systems +AI11122,Data Engineer,239826,SGD,311774,EX,PT,Singapore,S,Singapore,0,"PyTorch, Linux, TensorFlow, SQL",Associate,16,Technology,2025-02-04,2025-02-18,2109,7.7,Predictive Systems +AI11123,Research Scientist,201246,EUR,171059,EX,CT,Germany,M,Germany,50,"Docker, Azure, Data Visualization",Associate,10,Transportation,2025-04-15,2025-05-27,2412,9.3,Machine Intelligence Group +AI11124,Data Engineer,109684,USD,109684,SE,CT,Finland,M,Finland,100,"Hadoop, R, Linux, Java, SQL",Associate,8,Manufacturing,2024-07-18,2024-09-07,876,5.8,Smart Analytics +AI11125,Data Analyst,83819,EUR,71246,MI,FT,Germany,L,Czech Republic,50,"R, Java, MLOps, Kubernetes",Master,2,Gaming,2024-02-25,2024-04-24,988,9.9,Cloud AI Solutions +AI11126,AI Software Engineer,61837,GBP,46378,EN,FT,United Kingdom,S,United Kingdom,50,"Python, GCP, Tableau, R",Bachelor,0,Telecommunications,2024-07-12,2024-09-14,2451,8,TechCorp Inc +AI11127,AI Architect,75517,GBP,56638,EN,FT,United Kingdom,S,Finland,50,"Data Visualization, TensorFlow, MLOps, Python",Bachelor,1,Retail,2024-11-24,2025-01-21,1177,7.3,AI Innovations +AI11128,NLP Engineer,131115,USD,131115,SE,CT,United States,S,United States,0,"TensorFlow, Python, PyTorch",Master,7,Energy,2024-11-27,2025-02-01,673,9.3,DataVision Ltd +AI11129,Data Engineer,169966,EUR,144471,EX,FL,France,S,Poland,50,"Hadoop, PyTorch, Statistics, Mathematics, Deep Learning",Bachelor,15,Consulting,2024-01-20,2024-02-27,529,6.3,DeepTech Ventures +AI11130,Head of AI,79201,USD,79201,EX,FT,India,S,India,50,"Docker, Python, Data Visualization, Scala",Master,10,Finance,2025-02-08,2025-03-08,2200,10,Predictive Systems +AI11131,AI Consultant,71991,EUR,61192,EN,FL,France,L,Israel,50,"Mathematics, GCP, Deep Learning",Bachelor,0,Transportation,2024-03-03,2024-04-05,2377,9.1,Cloud AI Solutions +AI11132,Data Engineer,211340,GBP,158505,EX,CT,United Kingdom,S,Nigeria,50,"NLP, Java, Kubernetes, Git",PhD,11,Automotive,2025-02-17,2025-04-27,921,9.3,TechCorp Inc +AI11133,Machine Learning Engineer,121942,USD,121942,SE,PT,Israel,S,Israel,100,"Kubernetes, GCP, SQL, Git",Associate,5,Healthcare,2024-06-08,2024-07-29,859,8.9,DataVision Ltd +AI11134,Principal Data Scientist,133708,CAD,167135,SE,FL,Canada,M,Canada,50,"Tableau, PyTorch, NLP",Associate,5,Education,2025-03-01,2025-04-24,1145,9.5,Advanced Robotics +AI11135,Data Scientist,128594,GBP,96446,MI,FT,United Kingdom,L,United Kingdom,0,"Statistics, R, PyTorch, TensorFlow",Associate,2,Automotive,2024-11-03,2024-11-19,895,9.7,Digital Transformation LLC +AI11136,Machine Learning Researcher,90783,EUR,77166,MI,PT,France,L,France,100,"R, Scala, NLP",Associate,4,Retail,2024-09-19,2024-11-13,1985,9.1,Neural Networks Co +AI11137,AI Product Manager,241386,GBP,181040,EX,CT,United Kingdom,S,United Kingdom,50,"Scala, Java, R",PhD,13,Technology,2024-03-19,2024-05-02,1706,6.4,Advanced Robotics +AI11138,Data Scientist,50199,USD,50199,EN,FL,South Korea,M,South Korea,50,"Azure, Hadoop, SQL",Master,0,Automotive,2025-03-05,2025-05-12,1284,9.4,TechCorp Inc +AI11139,Head of AI,69589,AUD,93945,EN,FL,Australia,S,Australia,0,"R, SQL, Data Visualization, Git",Bachelor,1,Transportation,2024-02-04,2024-04-10,2397,7.6,Autonomous Tech +AI11140,Data Analyst,249049,USD,249049,EX,FT,United States,L,United States,50,"Azure, Python, Tableau",Bachelor,19,Finance,2024-10-02,2024-11-20,708,5,Neural Networks Co +AI11141,Data Engineer,74973,USD,74973,EN,FT,United States,M,United States,0,"SQL, Kubernetes, AWS",PhD,1,Technology,2025-02-05,2025-03-23,2354,5.3,DeepTech Ventures +AI11142,AI Specialist,86870,USD,86870,MI,FL,Denmark,S,Australia,100,"NLP, SQL, R",PhD,4,Finance,2024-06-22,2024-08-11,1019,7.6,Cloud AI Solutions +AI11143,Robotics Engineer,132380,USD,132380,SE,FL,Israel,M,Israel,0,"Data Visualization, MLOps, SQL, R",Master,5,Energy,2024-08-18,2024-09-03,883,8.3,DeepTech Ventures +AI11144,AI Specialist,134074,EUR,113963,SE,FT,Germany,M,Germany,100,"Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,7,Manufacturing,2024-05-13,2024-06-13,1001,9.2,TechCorp Inc +AI11145,Autonomous Systems Engineer,29783,USD,29783,MI,PT,India,M,Australia,50,"Java, TensorFlow, AWS, Linux",Bachelor,2,Government,2024-11-25,2024-12-21,567,8.8,Neural Networks Co +AI11146,Autonomous Systems Engineer,129656,JPY,14262160,SE,FT,Japan,M,Japan,50,"Python, Kubernetes, Mathematics, MLOps",Associate,8,Media,2024-02-25,2024-05-03,1544,9.7,Smart Analytics +AI11147,AI Research Scientist,101315,USD,101315,SE,CT,Sweden,S,Sweden,50,"R, PyTorch, Azure, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-03-22,1720,8.1,Cognitive Computing +AI11148,Head of AI,154178,USD,154178,EX,FT,Israel,M,Austria,50,"Hadoop, Java, Mathematics",Bachelor,18,Government,2025-01-13,2025-03-16,2287,6.1,Cloud AI Solutions +AI11149,Data Scientist,71943,EUR,61152,EN,PT,Austria,L,Austria,50,"Docker, SQL, Python, AWS",Bachelor,0,Automotive,2024-03-13,2024-05-12,2360,5.5,Predictive Systems +AI11150,AI Research Scientist,187201,USD,187201,EX,FL,South Korea,M,Netherlands,50,"GCP, NLP, AWS",PhD,17,Gaming,2025-03-02,2025-05-12,1532,8.8,Machine Intelligence Group +AI11151,AI Software Engineer,69671,AUD,94056,MI,CT,Australia,S,Australia,100,"Python, Tableau, TensorFlow",Master,3,Healthcare,2024-08-18,2024-10-12,2262,6.6,Algorithmic Solutions +AI11152,Deep Learning Engineer,119940,AUD,161919,SE,CT,Australia,M,Australia,50,"SQL, PyTorch, TensorFlow, Deep Learning, Statistics",PhD,7,Gaming,2024-01-03,2024-03-14,1693,6.3,Future Systems +AI11153,Principal Data Scientist,102411,CHF,92170,MI,FL,Switzerland,S,Mexico,100,"Java, Hadoop, SQL, Computer Vision, Mathematics",Master,3,Healthcare,2024-08-23,2024-09-13,762,9.4,Neural Networks Co +AI11154,ML Ops Engineer,94579,CAD,118224,MI,FL,Canada,L,Canada,50,"PyTorch, GCP, Scala, Hadoop",Associate,4,Real Estate,2024-10-21,2024-12-09,813,8.3,Advanced Robotics +AI11155,Head of AI,93077,GBP,69808,EN,CT,United Kingdom,L,United Kingdom,100,"R, Deep Learning, Python, Statistics, Computer Vision",Associate,1,Finance,2024-06-19,2024-07-08,1504,5.2,Digital Transformation LLC +AI11156,AI Architect,215780,USD,215780,EX,FL,Denmark,L,Denmark,0,"Linux, Computer Vision, GCP, Azure",Master,15,Energy,2024-07-20,2024-09-13,2054,7.2,DataVision Ltd +AI11157,Machine Learning Researcher,123240,EUR,104754,SE,PT,Austria,M,Austria,0,"Kubernetes, Deep Learning, Docker, Statistics, Java",Bachelor,5,Education,2024-09-13,2024-10-09,1895,6.2,Predictive Systems +AI11158,Head of AI,172179,USD,172179,SE,PT,Denmark,M,Egypt,50,"GCP, R, MLOps, TensorFlow",Bachelor,6,Consulting,2024-08-30,2024-10-12,987,8.1,Digital Transformation LLC +AI11159,AI Software Engineer,211756,USD,211756,EX,PT,Sweden,L,Sweden,0,"Data Visualization, NLP, GCP",Master,10,Manufacturing,2024-07-04,2024-07-30,1708,7.2,Neural Networks Co +AI11160,Machine Learning Researcher,68820,USD,68820,MI,FL,South Korea,S,South Korea,50,"NLP, GCP, R, Data Visualization, Computer Vision",Master,4,Automotive,2025-01-03,2025-03-10,1419,9.4,Algorithmic Solutions +AI11161,Machine Learning Researcher,40630,USD,40630,EN,CT,South Korea,S,South Korea,0,"Git, Kubernetes, Hadoop, Java",PhD,1,Gaming,2025-02-28,2025-03-28,692,9.2,TechCorp Inc +AI11162,AI Product Manager,79533,EUR,67603,MI,FL,Austria,S,Israel,0,"NLP, SQL, PyTorch, Tableau, Docker",Associate,4,Manufacturing,2025-03-18,2025-05-02,1282,6.9,AI Innovations +AI11163,Data Engineer,85375,CHF,76838,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Scala, Linux, Docker, MLOps",PhD,0,Transportation,2024-09-14,2024-11-21,2017,7.8,DataVision Ltd +AI11164,Machine Learning Researcher,34517,USD,34517,MI,CT,China,S,China,50,"PyTorch, TensorFlow, MLOps, Java, R",Associate,3,Transportation,2024-02-18,2024-04-19,2242,9.2,AI Innovations +AI11165,Robotics Engineer,169364,USD,169364,EX,PT,Sweden,M,Sweden,0,"Data Visualization, PyTorch, TensorFlow, Statistics, Azure",Master,14,Real Estate,2025-01-06,2025-03-01,1951,9.6,Cognitive Computing +AI11166,AI Architect,118975,CAD,148719,SE,CT,Canada,L,Canada,50,"Python, Mathematics, Git, Computer Vision",PhD,6,Telecommunications,2024-11-26,2025-01-13,1063,7,Machine Intelligence Group +AI11167,AI Specialist,53965,USD,53965,SE,FL,India,L,India,100,"SQL, Java, PyTorch",Bachelor,5,Consulting,2024-01-13,2024-02-21,581,7.6,Neural Networks Co +AI11168,Principal Data Scientist,163916,USD,163916,EX,CT,Sweden,L,Sweden,0,"Data Visualization, Java, Tableau",Associate,19,Education,2024-03-01,2024-03-30,1789,8.4,Machine Intelligence Group +AI11169,Deep Learning Engineer,82346,USD,82346,MI,FT,Israel,M,New Zealand,0,"Azure, GCP, Deep Learning, Scala",Bachelor,2,Transportation,2024-03-31,2024-05-30,522,8.2,TechCorp Inc +AI11170,AI Specialist,124224,JPY,13664640,SE,FT,Japan,S,Japan,50,"Computer Vision, Python, Azure",Associate,8,Manufacturing,2024-01-18,2024-03-08,965,7.5,DataVision Ltd +AI11171,AI Consultant,141596,USD,141596,SE,CT,Finland,M,Denmark,100,"MLOps, Linux, Kubernetes, Python, Statistics",Bachelor,8,Healthcare,2025-04-29,2025-07-09,1133,8.3,Algorithmic Solutions +AI11172,AI Research Scientist,36117,USD,36117,MI,PT,India,L,Colombia,50,"Mathematics, Git, Python",Bachelor,2,Manufacturing,2024-04-04,2024-05-22,684,5.2,Smart Analytics +AI11173,Data Engineer,72859,USD,72859,MI,FT,Ireland,S,Thailand,100,"Deep Learning, TensorFlow, Git, SQL, Java",Bachelor,4,Real Estate,2024-06-19,2024-08-27,1261,7.3,Autonomous Tech +AI11174,AI Software Engineer,145568,GBP,109176,SE,FT,United Kingdom,S,Estonia,50,"AWS, Python, Tableau, Git",Associate,9,Finance,2024-05-03,2024-05-28,595,6.6,Predictive Systems +AI11175,NLP Engineer,81162,GBP,60872,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, Statistics, NLP, R",Master,4,Transportation,2024-01-29,2024-03-10,1900,7,Quantum Computing Inc +AI11176,NLP Engineer,222942,EUR,189501,EX,PT,Netherlands,M,Netherlands,100,"Docker, Scala, Computer Vision, Linux",Associate,13,Manufacturing,2024-09-15,2024-10-15,1315,8.7,Digital Transformation LLC +AI11177,Computer Vision Engineer,241236,AUD,325669,EX,FL,Australia,M,India,50,"Statistics, Python, R, Linux, SQL",Bachelor,11,Transportation,2024-09-22,2024-11-29,1590,9.6,Autonomous Tech +AI11178,Data Analyst,79043,CAD,98804,EN,FL,Canada,L,Canada,0,"R, Linux, Python, Java",Associate,1,Healthcare,2025-04-10,2025-05-19,556,6.3,Neural Networks Co +AI11179,AI Specialist,118334,USD,118334,MI,PT,United States,M,Chile,50,"GCP, MLOps, Scala, Python",Bachelor,4,Gaming,2024-12-23,2025-01-25,616,9.6,Autonomous Tech +AI11180,Head of AI,90117,USD,90117,SE,PT,Israel,S,Israel,0,"Linux, NLP, PyTorch, Git",PhD,7,Government,2024-08-16,2024-09-24,971,9.9,Neural Networks Co +AI11181,AI Software Engineer,174435,USD,174435,SE,PT,Denmark,L,Denmark,0,"Computer Vision, Kubernetes, Tableau, Linux, Mathematics",PhD,7,Retail,2025-03-17,2025-05-07,2391,6.2,Machine Intelligence Group +AI11182,Machine Learning Researcher,118598,USD,118598,SE,PT,Sweden,L,Sweden,100,"Azure, Python, Mathematics, Kubernetes, AWS",PhD,6,Manufacturing,2024-05-11,2024-07-23,2052,9,Quantum Computing Inc +AI11183,Robotics Engineer,37061,USD,37061,MI,PT,China,S,Argentina,0,"SQL, Docker, Kubernetes, MLOps",PhD,4,Transportation,2025-01-28,2025-02-19,2380,6,Algorithmic Solutions +AI11184,AI Product Manager,229849,EUR,195372,EX,FT,Netherlands,S,Netherlands,100,"Kubernetes, SQL, Computer Vision, Mathematics",Master,17,Technology,2024-10-03,2024-11-08,1912,6.5,Cloud AI Solutions +AI11185,AI Research Scientist,178162,CHF,160346,MI,PT,Switzerland,L,Switzerland,50,"Python, Kubernetes, TensorFlow",Bachelor,4,Education,2024-12-15,2025-01-26,1263,7.9,Advanced Robotics +AI11186,Data Engineer,175805,GBP,131854,EX,CT,United Kingdom,L,Canada,100,"Spark, AWS, Azure, GCP",Bachelor,10,Healthcare,2025-04-22,2025-06-03,984,7.2,DeepTech Ventures +AI11187,Autonomous Systems Engineer,105402,USD,105402,MI,FT,Sweden,L,New Zealand,50,"Computer Vision, Data Visualization, Java",Bachelor,3,Finance,2024-05-11,2024-07-02,2493,9.7,DeepTech Ventures +AI11188,AI Software Engineer,33884,USD,33884,MI,PT,India,M,Luxembourg,50,"PyTorch, GCP, TensorFlow, Scala, Kubernetes",PhD,2,Retail,2024-09-03,2024-11-12,1283,9.6,Machine Intelligence Group +AI11189,Computer Vision Engineer,60249,USD,60249,EN,FL,Ireland,M,Ireland,50,"Data Visualization, Azure, Tableau, TensorFlow, Statistics",Master,0,Education,2024-01-02,2024-02-24,1904,6.3,Digital Transformation LLC +AI11190,NLP Engineer,81942,USD,81942,MI,FT,Finland,M,Finland,100,"Data Visualization, Hadoop, Scala, Tableau",PhD,2,Finance,2025-01-25,2025-03-18,1325,8.5,Smart Analytics +AI11191,ML Ops Engineer,76583,AUD,103387,EN,FT,Australia,M,Belgium,0,"Docker, Spark, TensorFlow, AWS, Computer Vision",Master,1,Government,2024-06-22,2024-08-06,2483,8.6,Algorithmic Solutions +AI11192,AI Specialist,61080,USD,61080,SE,PT,India,L,India,50,"Java, MLOps, Data Visualization, Spark, Statistics",PhD,5,Consulting,2024-03-22,2024-05-14,2326,9.5,Cloud AI Solutions +AI11193,Data Engineer,129718,GBP,97289,SE,CT,United Kingdom,S,United Kingdom,0,"Python, TensorFlow, Docker",Associate,9,Consulting,2024-04-30,2024-07-07,1768,5.2,Cloud AI Solutions +AI11194,AI Specialist,89873,GBP,67405,MI,CT,United Kingdom,S,United Kingdom,100,"Azure, Linux, Tableau, Docker",Master,3,Consulting,2025-03-05,2025-04-11,692,5.9,Neural Networks Co +AI11195,Data Scientist,203419,USD,203419,EX,PT,Finland,S,Finland,100,"Python, Kubernetes, TensorFlow, MLOps, Tableau",Master,10,Manufacturing,2025-04-27,2025-05-27,1819,9.1,Machine Intelligence Group +AI11196,Machine Learning Engineer,154964,CHF,139468,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, Git, Computer Vision, TensorFlow",Bachelor,7,Manufacturing,2024-12-01,2025-01-13,1378,9.5,Autonomous Tech +AI11197,ML Ops Engineer,127404,USD,127404,EX,CT,Israel,S,Austria,100,"TensorFlow, Git, Python, Java",Bachelor,16,Transportation,2024-07-24,2024-09-08,2469,5.1,AI Innovations +AI11198,Head of AI,112946,EUR,96004,MI,PT,Austria,L,Austria,100,"Kubernetes, Linux, Scala, Java, Mathematics",Master,2,Real Estate,2024-10-23,2024-11-15,1555,5.3,AI Innovations +AI11199,Head of AI,166982,CHF,150284,SE,FL,Switzerland,L,Switzerland,0,"GCP, Kubernetes, Mathematics, AWS, Statistics",Master,5,Consulting,2024-04-18,2024-06-19,1128,7,Future Systems +AI11200,AI Architect,79897,USD,79897,EN,FT,Ireland,L,Ireland,0,"Java, Python, R, Kubernetes",Associate,1,Technology,2024-04-11,2024-04-29,1307,6,Algorithmic Solutions +AI11201,Machine Learning Researcher,199034,CHF,179131,EX,CT,Switzerland,S,Switzerland,0,"Linux, Deep Learning, Computer Vision, GCP, Git",PhD,13,Energy,2024-05-27,2024-06-14,2002,7.9,Advanced Robotics +AI11202,Robotics Engineer,121505,USD,121505,MI,CT,United States,L,Mexico,0,"Deep Learning, PyTorch, Kubernetes, Docker, TensorFlow",Bachelor,3,Transportation,2024-12-20,2025-02-22,505,9.6,Neural Networks Co +AI11203,AI Specialist,98949,EUR,84107,SE,FT,Austria,S,Austria,0,"SQL, Git, Docker, TensorFlow, NLP",Bachelor,9,Media,2024-03-12,2024-05-14,2235,7.3,Predictive Systems +AI11204,Autonomous Systems Engineer,175782,USD,175782,EX,PT,Sweden,S,Sweden,50,"Hadoop, GCP, NLP",Master,10,Automotive,2025-03-12,2025-05-08,909,7.6,Cloud AI Solutions +AI11205,Data Engineer,204328,EUR,173679,EX,CT,Netherlands,L,Russia,50,"Linux, R, Azure, Deep Learning",Associate,13,Automotive,2024-08-26,2024-10-17,747,7.8,Quantum Computing Inc +AI11206,Machine Learning Researcher,47111,USD,47111,EN,PT,Ireland,S,Ireland,50,"Python, Git, Hadoop, GCP, Deep Learning",Master,0,Transportation,2024-04-08,2024-05-01,2498,7.9,Smart Analytics +AI11207,Data Analyst,97477,GBP,73108,MI,PT,United Kingdom,S,United Kingdom,100,"Python, Docker, TensorFlow, Statistics, Java",Associate,3,Real Estate,2024-08-05,2024-09-09,1609,5.2,DeepTech Ventures +AI11208,ML Ops Engineer,45439,USD,45439,SE,CT,India,S,India,0,"Mathematics, SQL, Deep Learning, PyTorch",Associate,5,Manufacturing,2024-11-16,2024-12-24,1674,9.8,Quantum Computing Inc +AI11209,ML Ops Engineer,268419,GBP,201314,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, Spark, Python",Master,11,Technology,2024-07-12,2024-08-31,2445,5.6,DeepTech Ventures +AI11210,Head of AI,42030,USD,42030,MI,FT,India,L,Germany,50,"Git, Statistics, Data Visualization, Python, Deep Learning",Bachelor,2,Real Estate,2025-04-11,2025-06-18,1712,6.3,Quantum Computing Inc +AI11211,Research Scientist,134524,USD,134524,SE,FT,Finland,M,Finland,100,"PyTorch, MLOps, Deep Learning",Master,9,Real Estate,2024-03-21,2024-05-13,2193,9,Future Systems +AI11212,AI Research Scientist,178034,USD,178034,EX,FT,Israel,M,Chile,0,"PyTorch, Deep Learning, MLOps, Hadoop, Linux",Bachelor,19,Healthcare,2024-01-17,2024-03-28,2436,9.8,DeepTech Ventures +AI11213,AI Product Manager,79119,USD,79119,MI,PT,Sweden,S,Sweden,100,"Spark, Git, Statistics, Deep Learning, PyTorch",Associate,4,Manufacturing,2024-03-20,2024-05-11,1637,7.7,TechCorp Inc +AI11214,AI Product Manager,168770,USD,168770,EX,PT,Ireland,L,India,50,"PyTorch, TensorFlow, Docker, Mathematics",Associate,15,Transportation,2024-11-09,2024-12-28,1740,6.8,Cognitive Computing +AI11215,Machine Learning Researcher,65252,AUD,88090,EN,FT,Australia,M,Australia,100,"Computer Vision, Mathematics, NLP, Git, MLOps",Bachelor,1,Education,2025-01-15,2025-02-26,1035,6.7,DataVision Ltd +AI11216,Autonomous Systems Engineer,163792,GBP,122844,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, SQL, TensorFlow, Azure, Statistics",Associate,14,Retail,2024-07-25,2024-08-25,664,8.4,Cognitive Computing +AI11217,Machine Learning Engineer,196273,USD,196273,SE,FT,Norway,M,Thailand,0,"Mathematics, PyTorch, Scala, Azure",Master,5,Consulting,2024-09-30,2024-10-16,1052,7,Advanced Robotics +AI11218,Machine Learning Researcher,50242,EUR,42706,EN,CT,France,M,Australia,50,"Python, Java, NLP",Associate,0,Government,2025-03-31,2025-04-29,690,7.3,DeepTech Ventures +AI11219,Machine Learning Engineer,262801,USD,262801,EX,FL,Sweden,L,Sweden,50,"Data Visualization, SQL, Hadoop, MLOps",Associate,19,Transportation,2024-05-07,2024-06-14,1769,6.1,Advanced Robotics +AI11220,Data Analyst,61263,EUR,52074,EN,FL,Germany,L,Singapore,0,"Spark, Hadoop, Statistics, Linux, Python",PhD,0,Real Estate,2024-09-20,2024-10-22,892,9.5,Autonomous Tech +AI11221,ML Ops Engineer,146528,CHF,131875,MI,PT,Switzerland,M,Switzerland,50,"Azure, Python, TensorFlow, Docker",Associate,3,Consulting,2025-02-07,2025-03-22,2279,9.9,Predictive Systems +AI11222,AI Product Manager,163758,USD,163758,SE,FT,Norway,S,Norway,50,"Kubernetes, MLOps, Scala, AWS",Master,9,Media,2024-11-19,2024-12-18,1651,7.6,Algorithmic Solutions +AI11223,AI Research Scientist,166269,JPY,18289590,EX,CT,Japan,L,Japan,0,"Git, Python, Hadoop",Associate,16,Manufacturing,2024-04-18,2024-06-11,2443,8.9,Machine Intelligence Group +AI11224,Autonomous Systems Engineer,233000,EUR,198050,EX,CT,France,M,France,50,"Mathematics, Docker, Kubernetes",PhD,10,Healthcare,2025-01-02,2025-01-17,778,8,DeepTech Ventures +AI11225,AI Research Scientist,91649,USD,91649,MI,PT,United States,S,Ireland,50,"Java, Statistics, Data Visualization, Git, SQL",Associate,4,Media,2024-02-06,2024-03-14,1886,9.4,TechCorp Inc +AI11226,Machine Learning Researcher,152617,CHF,137355,SE,CT,Switzerland,M,Denmark,50,"Java, Mathematics, Kubernetes, Python, Scala",Bachelor,5,Transportation,2024-03-01,2024-04-18,2489,9,Autonomous Tech +AI11227,Deep Learning Engineer,111739,USD,111739,SE,FT,Finland,S,Finland,0,"TensorFlow, Tableau, Spark, GCP, SQL",Bachelor,5,Healthcare,2024-04-14,2024-05-19,2451,7.4,Algorithmic Solutions +AI11228,NLP Engineer,66659,EUR,56660,EN,PT,France,M,Mexico,50,"Tableau, Python, Scala",Bachelor,0,Automotive,2024-01-07,2024-01-22,1040,7.9,Cognitive Computing +AI11229,Machine Learning Engineer,186273,AUD,251469,EX,CT,Australia,L,Australia,50,"Data Visualization, Docker, Tableau, Java",Bachelor,14,Consulting,2024-05-25,2024-07-13,1691,5.6,Algorithmic Solutions +AI11230,AI Specialist,165955,USD,165955,EX,CT,Finland,L,India,100,"TensorFlow, Data Visualization, Tableau, Statistics, AWS",Bachelor,15,Education,2024-10-23,2024-11-29,603,8.8,AI Innovations +AI11231,Data Scientist,206355,EUR,175402,EX,CT,Germany,M,Germany,50,"Linux, Computer Vision, PyTorch, TensorFlow",PhD,14,Government,2024-09-09,2024-10-19,1908,5.4,Digital Transformation LLC +AI11232,Data Analyst,28132,USD,28132,EN,CT,India,M,Argentina,100,"Computer Vision, PyTorch, Spark",Bachelor,1,Energy,2025-01-05,2025-03-18,1774,7.4,Cloud AI Solutions +AI11233,Research Scientist,105432,USD,105432,EX,CT,China,M,China,0,"Spark, Kubernetes, Java, Statistics, TensorFlow",Bachelor,17,Energy,2024-07-19,2024-08-24,2474,7.7,Digital Transformation LLC +AI11234,Machine Learning Engineer,84482,USD,84482,EN,CT,United States,S,Malaysia,100,"Docker, Scala, NLP, AWS",Associate,1,Media,2024-06-27,2024-07-17,2399,5.2,Advanced Robotics +AI11235,Data Analyst,207967,USD,207967,EX,PT,Finland,S,Estonia,0,"Statistics, Mathematics, PyTorch",Master,11,Telecommunications,2024-02-17,2024-04-04,586,7.5,Machine Intelligence Group +AI11236,AI Product Manager,105835,USD,105835,MI,FT,Ireland,M,Ireland,0,"Azure, GCP, Git, AWS",PhD,4,Energy,2024-05-14,2024-07-20,1077,5.6,Predictive Systems +AI11237,Data Scientist,90084,USD,90084,MI,CT,Ireland,L,Japan,50,"R, SQL, Python, Spark, Deep Learning",Associate,3,Transportation,2025-03-24,2025-05-04,1376,5.1,Machine Intelligence Group +AI11238,AI Architect,70560,AUD,95256,EN,FT,Australia,M,Australia,50,"Python, TensorFlow, Java, Spark",Bachelor,0,Finance,2024-01-11,2024-03-09,1687,7.2,Neural Networks Co +AI11239,Data Scientist,119651,EUR,101703,SE,FL,France,S,France,0,"Linux, Python, Statistics, Kubernetes",Master,5,Media,2024-12-29,2025-03-11,1854,7.6,Digital Transformation LLC +AI11240,Deep Learning Engineer,81359,EUR,69155,EN,PT,Netherlands,L,Estonia,100,"Linux, Python, Spark, Computer Vision, Statistics",Bachelor,1,Consulting,2025-03-24,2025-05-11,607,8,Neural Networks Co +AI11241,Head of AI,94506,USD,94506,MI,CT,Ireland,M,Spain,0,"PyTorch, Deep Learning, MLOps",Master,3,Manufacturing,2024-02-08,2024-02-24,854,8.2,Digital Transformation LLC +AI11242,AI Consultant,57555,CAD,71944,EN,FT,Canada,S,Canada,0,"Git, Java, SQL",Bachelor,1,Gaming,2025-01-14,2025-03-01,993,8.6,TechCorp Inc +AI11243,AI Architect,58309,USD,58309,MI,FL,China,L,China,50,"Java, Linux, Tableau, Mathematics",Bachelor,4,Healthcare,2024-07-20,2024-09-03,671,7.1,Cognitive Computing +AI11244,Data Analyst,104581,USD,104581,MI,FT,United States,L,United States,100,"Python, Tableau, AWS",Associate,3,Retail,2024-02-07,2024-03-08,1281,9.1,Smart Analytics +AI11245,AI Architect,51087,USD,51087,SE,FT,China,M,China,50,"Data Visualization, Git, Kubernetes, Spark, R",PhD,8,Government,2024-01-22,2024-02-24,1657,7.2,Autonomous Tech +AI11246,Robotics Engineer,163866,CHF,147479,MI,FT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Deep Learning, AWS, Linux",PhD,3,Media,2024-04-01,2024-05-04,1667,5.9,DataVision Ltd +AI11247,Data Analyst,48310,USD,48310,EN,CT,Finland,M,Finland,50,"Data Visualization, Kubernetes, Scala",Associate,1,Transportation,2025-04-24,2025-05-29,1452,8.1,Digital Transformation LLC +AI11248,Machine Learning Engineer,189402,USD,189402,SE,FT,Denmark,L,Denmark,100,"Hadoop, GCP, Tableau, Computer Vision",Associate,8,Automotive,2025-03-05,2025-03-30,1720,6.8,Smart Analytics +AI11249,Robotics Engineer,30514,USD,30514,MI,FT,India,L,Czech Republic,0,"Python, Git, TensorFlow, Deep Learning, PyTorch",Bachelor,4,Media,2025-03-30,2025-04-13,1193,5.6,Predictive Systems +AI11250,AI Consultant,69642,GBP,52232,EN,PT,United Kingdom,L,Kenya,50,"Spark, Python, Computer Vision, Data Visualization, TensorFlow",Bachelor,0,Telecommunications,2024-09-17,2024-11-25,1878,10,Future Systems +AI11251,Head of AI,117224,JPY,12894640,SE,FT,Japan,S,South Africa,100,"AWS, R, PyTorch, Java, SQL",Bachelor,5,Media,2024-05-22,2024-06-16,2113,7.6,Digital Transformation LLC +AI11252,Computer Vision Engineer,100484,CAD,125605,MI,FL,Canada,L,Canada,50,"Java, Hadoop, PyTorch, AWS, TensorFlow",PhD,3,Consulting,2024-02-20,2024-04-02,2263,6.1,DeepTech Ventures +AI11253,AI Software Engineer,124618,CHF,112156,EN,PT,Switzerland,L,Switzerland,50,"Git, Python, R, Statistics",PhD,0,Transportation,2024-09-14,2024-10-05,1843,9.9,Future Systems +AI11254,AI Product Manager,191724,USD,191724,EX,FL,Ireland,S,Ireland,50,"Python, Hadoop, Spark, Docker",PhD,18,Education,2024-03-26,2024-06-01,2039,9.3,Machine Intelligence Group +AI11255,ML Ops Engineer,97569,USD,97569,EN,CT,Denmark,M,Denmark,100,"NLP, Statistics, SQL, PyTorch, Linux",Master,0,Education,2024-02-12,2024-03-25,2263,9.5,TechCorp Inc +AI11256,Computer Vision Engineer,118684,USD,118684,SE,CT,Finland,L,Finland,100,"Scala, Python, Statistics, Linux",PhD,9,Manufacturing,2024-08-29,2024-10-17,1785,6,DeepTech Ventures +AI11257,Deep Learning Engineer,80305,CHF,72275,EN,FL,Switzerland,S,Switzerland,50,"Git, GCP, SQL, Spark, Docker",PhD,1,Healthcare,2024-10-22,2024-12-02,1862,6.3,Machine Intelligence Group +AI11258,Principal Data Scientist,214921,USD,214921,EX,CT,Sweden,S,India,100,"Kubernetes, AWS, GCP, Git, Spark",PhD,17,Retail,2024-02-01,2024-03-15,1894,6,Predictive Systems +AI11259,AI Architect,178983,CHF,161085,SE,PT,Switzerland,L,Germany,100,"Java, TensorFlow, Hadoop",Associate,9,Transportation,2024-11-26,2024-12-30,1204,9.5,Algorithmic Solutions +AI11260,AI Product Manager,78327,USD,78327,MI,PT,Finland,L,Finland,50,"Spark, AWS, SQL, Tableau",Associate,4,Finance,2025-02-14,2025-03-28,2387,6.1,Predictive Systems +AI11261,Robotics Engineer,85793,USD,85793,EN,FL,Denmark,S,Denmark,0,"AWS, Java, GCP, PyTorch",Associate,0,Telecommunications,2024-07-25,2024-09-09,866,7.7,Predictive Systems +AI11262,AI Specialist,80644,EUR,68547,EN,FT,Netherlands,L,Netherlands,50,"Git, GCP, Java, Python, Computer Vision",Master,1,Energy,2025-04-08,2025-05-24,2017,6,DataVision Ltd +AI11263,AI Specialist,123929,SGD,161108,MI,CT,Singapore,L,Singapore,50,"PyTorch, TensorFlow, Mathematics, Deep Learning, Git",Bachelor,2,Automotive,2024-05-08,2024-06-25,1499,8.7,Algorithmic Solutions +AI11264,AI Research Scientist,108923,USD,108923,MI,FT,Finland,L,New Zealand,0,"Linux, Docker, Deep Learning, PyTorch",Master,4,Media,2024-09-28,2024-11-21,2273,9.3,AI Innovations +AI11265,Machine Learning Engineer,140940,USD,140940,SE,FL,South Korea,L,South Korea,50,"R, PyTorch, Computer Vision",Bachelor,9,Media,2024-10-03,2024-11-11,1587,8.4,Cognitive Computing +AI11266,NLP Engineer,315420,CHF,283878,EX,PT,Switzerland,L,Switzerland,100,"MLOps, SQL, PyTorch, Linux",PhD,13,Education,2024-10-14,2024-12-14,1791,9.4,TechCorp Inc +AI11267,Head of AI,71258,CAD,89073,EN,FL,Canada,M,Thailand,50,"GCP, Spark, Azure, PyTorch",Master,1,Technology,2024-05-29,2024-07-22,2017,5.9,Digital Transformation LLC +AI11268,Data Engineer,105428,JPY,11597080,MI,PT,Japan,L,Japan,0,"SQL, Python, Java, Tableau, TensorFlow",Associate,4,Technology,2025-03-29,2025-04-29,1302,5.6,Future Systems +AI11269,Data Scientist,167067,EUR,142007,EX,PT,France,L,Hungary,50,"Linux, PyTorch, Git, AWS, Java",Associate,12,Retail,2025-03-24,2025-04-15,1311,9.3,DeepTech Ventures +AI11270,Computer Vision Engineer,75062,USD,75062,EN,FT,Denmark,S,Denmark,50,"AWS, TensorFlow, Computer Vision, NLP",PhD,0,Gaming,2024-04-26,2024-06-17,2110,7,Cognitive Computing +AI11271,Computer Vision Engineer,54168,USD,54168,EX,FL,India,M,India,100,"Scala, PyTorch, Computer Vision, TensorFlow",PhD,10,Education,2024-04-09,2024-05-17,1658,7.9,Cognitive Computing +AI11272,Data Analyst,61930,SGD,80509,EN,PT,Singapore,M,Singapore,0,"Git, Computer Vision, SQL, Python, MLOps",Master,0,Consulting,2024-11-25,2025-01-08,1655,7.3,AI Innovations +AI11273,AI Product Manager,148519,EUR,126241,EX,PT,Austria,M,Austria,100,"Computer Vision, Data Visualization, Python",Master,11,Gaming,2025-04-27,2025-05-21,669,7.5,Smart Analytics +AI11274,Deep Learning Engineer,199528,USD,199528,EX,PT,Norway,S,Norway,100,"Python, Git, Computer Vision, TensorFlow",PhD,12,Finance,2024-02-08,2024-03-17,544,6.2,Quantum Computing Inc +AI11275,AI Architect,53596,USD,53596,EX,FL,India,S,India,50,"Azure, MLOps, Statistics, PyTorch, Computer Vision",Associate,11,Gaming,2024-11-09,2024-12-30,2407,9.4,Autonomous Tech +AI11276,Head of AI,97034,USD,97034,EN,CT,Denmark,M,Denmark,50,"PyTorch, Kubernetes, Deep Learning, Linux, Azure",Master,0,Media,2024-05-24,2024-07-01,1585,5.5,Cognitive Computing +AI11277,ML Ops Engineer,102547,AUD,138438,SE,FT,Australia,S,Australia,100,"Deep Learning, Python, Hadoop",Bachelor,5,Telecommunications,2024-05-07,2024-07-10,1872,7.2,Smart Analytics +AI11278,Machine Learning Engineer,63599,SGD,82679,EN,FT,Singapore,M,Singapore,50,"NLP, SQL, MLOps",Bachelor,1,Manufacturing,2024-10-17,2024-12-12,1319,6.6,Cloud AI Solutions +AI11279,Computer Vision Engineer,93730,EUR,79671,MI,FL,Austria,L,Austria,100,"Scala, Python, Mathematics, Kubernetes, Spark",Bachelor,4,Automotive,2024-11-08,2024-12-08,1254,6.8,DataVision Ltd +AI11280,AI Architect,205424,USD,205424,SE,FL,United States,L,Austria,100,"Data Visualization, Hadoop, Scala, PyTorch, Spark",Associate,7,Gaming,2024-04-03,2024-05-20,2330,8.7,Cognitive Computing +AI11281,Computer Vision Engineer,88065,USD,88065,EN,FL,Denmark,S,Denmark,100,"Linux, R, PyTorch, TensorFlow, Spark",Bachelor,1,Gaming,2025-03-23,2025-04-28,2085,5.6,Cloud AI Solutions +AI11282,ML Ops Engineer,115890,USD,115890,SE,FL,Israel,M,Israel,50,"PyTorch, GCP, Git",Master,9,Transportation,2024-11-04,2024-12-13,1762,7.5,AI Innovations +AI11283,Data Analyst,233264,SGD,303243,EX,CT,Singapore,S,Singapore,100,"Kubernetes, Scala, Tableau, Deep Learning",Associate,11,Telecommunications,2024-06-15,2024-08-03,814,6.1,Digital Transformation LLC +AI11284,AI Consultant,85232,EUR,72447,MI,FT,France,M,France,100,"Linux, Scala, Statistics, Python",PhD,3,Energy,2024-10-01,2024-11-26,2152,9.3,Predictive Systems +AI11285,AI Product Manager,125339,CHF,112805,MI,CT,Switzerland,M,Switzerland,0,"Python, Mathematics, Docker",PhD,2,Retail,2025-02-19,2025-05-02,1397,9.6,DataVision Ltd +AI11286,Research Scientist,185360,USD,185360,EX,CT,Ireland,L,Ireland,50,"NLP, Kubernetes, Docker, Python",Master,16,Retail,2024-01-23,2024-02-18,1618,7.8,Neural Networks Co +AI11287,Head of AI,106629,EUR,90635,MI,CT,France,L,France,0,"Data Visualization, Python, Azure, Scala",Bachelor,3,Retail,2025-02-06,2025-04-10,1496,8.7,Cloud AI Solutions +AI11288,Computer Vision Engineer,97894,USD,97894,EX,PT,India,L,India,0,"Scala, Java, Linux, R, SQL",PhD,13,Gaming,2025-01-01,2025-01-26,1062,9.3,Digital Transformation LLC +AI11289,Research Scientist,79189,USD,79189,EX,PT,India,M,Canada,50,"Java, Kubernetes, Scala",Master,12,Consulting,2024-05-06,2024-07-03,2204,9,Advanced Robotics +AI11290,AI Consultant,89489,JPY,9843790,MI,CT,Japan,L,Japan,50,"Docker, SQL, PyTorch",PhD,3,Retail,2024-11-24,2025-01-17,1809,6.4,AI Innovations +AI11291,Head of AI,119280,USD,119280,MI,CT,Israel,L,Netherlands,0,"Docker, Spark, Kubernetes, Scala, Mathematics",PhD,2,Manufacturing,2024-02-28,2024-05-05,716,7.1,DeepTech Ventures +AI11292,Robotics Engineer,219065,EUR,186205,EX,FT,Germany,S,Germany,0,"Python, Spark, Tableau",Associate,16,Manufacturing,2024-02-21,2024-03-13,800,7.6,TechCorp Inc +AI11293,Head of AI,218346,SGD,283850,EX,PT,Singapore,S,Singapore,50,"TensorFlow, Linux, GCP, Computer Vision, Deep Learning",Master,15,Finance,2024-05-22,2024-07-24,1652,9.7,Algorithmic Solutions +AI11294,AI Specialist,154420,SGD,200746,SE,CT,Singapore,M,Singapore,100,"Python, Git, Spark, Scala, Azure",Associate,7,Technology,2024-04-21,2024-06-29,645,8.8,Neural Networks Co +AI11295,AI Specialist,126566,USD,126566,SE,PT,Denmark,S,Norway,50,"Python, Data Visualization, Statistics",Bachelor,6,Consulting,2025-01-05,2025-01-28,1877,6.3,Cognitive Computing +AI11296,NLP Engineer,67525,AUD,91159,EN,FT,Australia,S,Australia,100,"Python, TensorFlow, Linux, AWS",Master,0,Gaming,2024-02-07,2024-04-03,1711,9.2,Digital Transformation LLC +AI11297,Research Scientist,130551,SGD,169716,SE,PT,Singapore,M,Singapore,0,"SQL, Kubernetes, Python, MLOps, Scala",Master,8,Telecommunications,2025-02-03,2025-03-04,890,7.7,Machine Intelligence Group +AI11298,Robotics Engineer,67815,USD,67815,EN,FL,Sweden,L,Sweden,0,"GCP, Scala, Kubernetes, Deep Learning",Master,1,Real Estate,2024-06-15,2024-07-30,2103,9.3,TechCorp Inc +AI11299,Data Scientist,26237,USD,26237,MI,CT,India,S,India,50,"MLOps, Git, SQL, Azure, Statistics",PhD,3,Transportation,2024-09-28,2024-11-27,850,5.9,Machine Intelligence Group +AI11300,Data Scientist,285608,SGD,371290,EX,PT,Singapore,L,Singapore,0,"PyTorch, Statistics, Computer Vision, GCP, Mathematics",PhD,10,Media,2025-01-09,2025-02-21,953,5.4,Autonomous Tech +AI11301,Machine Learning Engineer,73386,USD,73386,EN,FT,South Korea,L,South Korea,0,"Scala, Python, TensorFlow, Git, Hadoop",Associate,0,Manufacturing,2024-05-15,2024-07-03,1736,9.8,Autonomous Tech +AI11302,AI Specialist,24994,USD,24994,EN,CT,China,S,China,0,"Java, Kubernetes, GCP, Docker",Bachelor,0,Media,2024-04-08,2024-05-15,1010,7.6,Advanced Robotics +AI11303,Machine Learning Researcher,84205,AUD,113677,MI,FL,Australia,M,Australia,100,"Hadoop, MLOps, PyTorch, Scala, Kubernetes",Master,3,Energy,2024-06-17,2024-07-02,2481,9,Smart Analytics +AI11304,Deep Learning Engineer,167419,USD,167419,EX,FL,Israel,S,Australia,100,"AWS, Mathematics, Scala",Bachelor,11,Consulting,2024-08-10,2024-09-19,2109,6.1,Neural Networks Co +AI11305,Data Engineer,83819,EUR,71246,EN,CT,Austria,L,Austria,50,"Spark, Deep Learning, TensorFlow, Python, Git",Bachelor,1,Telecommunications,2025-04-05,2025-06-08,2018,7.8,Autonomous Tech +AI11306,Data Scientist,71467,USD,71467,EX,CT,China,M,China,100,"Python, Kubernetes, Tableau, Computer Vision",Master,11,Telecommunications,2024-09-05,2024-09-23,1673,5.8,Predictive Systems +AI11307,AI Specialist,150771,EUR,128155,SE,PT,Netherlands,L,Finland,0,"PyTorch, Kubernetes, Mathematics, Git",Master,5,Media,2025-02-08,2025-02-24,835,7.9,Cloud AI Solutions +AI11308,Autonomous Systems Engineer,187205,USD,187205,EX,FT,Finland,S,Finland,0,"Python, Scala, Git",Bachelor,15,Manufacturing,2024-05-09,2024-05-31,1333,9.2,Quantum Computing Inc +AI11309,AI Architect,25891,USD,25891,EN,FT,China,M,China,50,"SQL, Scala, Deep Learning",PhD,1,Automotive,2024-10-04,2024-12-05,2089,5.4,Cloud AI Solutions +AI11310,Machine Learning Researcher,62044,USD,62044,SE,CT,China,M,France,0,"Deep Learning, Statistics, SQL",Bachelor,5,Automotive,2025-02-13,2025-03-18,2477,6.4,DeepTech Ventures +AI11311,Data Scientist,155807,USD,155807,SE,CT,Israel,L,Israel,100,"Computer Vision, MLOps, Linux, TensorFlow",PhD,6,Real Estate,2024-07-22,2024-09-07,1354,9.4,Advanced Robotics +AI11312,Autonomous Systems Engineer,75916,EUR,64529,EN,FL,Netherlands,S,Netherlands,50,"TensorFlow, Mathematics, Java, MLOps, SQL",Associate,1,Gaming,2024-01-30,2024-03-29,708,7.8,Machine Intelligence Group +AI11313,Autonomous Systems Engineer,93324,SGD,121321,EN,FL,Singapore,L,Singapore,50,"Azure, GCP, Computer Vision, Deep Learning",PhD,1,Manufacturing,2024-04-18,2024-05-19,1592,9.6,Digital Transformation LLC +AI11314,Research Scientist,176161,EUR,149737,EX,FL,France,M,France,50,"Scala, Computer Vision, Azure",Bachelor,11,Real Estate,2024-12-10,2025-02-04,1294,9.5,Autonomous Tech +AI11315,ML Ops Engineer,135633,CAD,169541,SE,CT,Canada,L,Canada,100,"Python, GCP, TensorFlow",PhD,9,Manufacturing,2025-04-11,2025-05-30,2051,8,Future Systems +AI11316,Computer Vision Engineer,96084,USD,96084,MI,FT,Ireland,S,Thailand,50,"Kubernetes, Java, R, Deep Learning",Master,4,Real Estate,2024-06-19,2024-07-20,2346,9.6,AI Innovations +AI11317,AI Product Manager,229922,CHF,206930,EX,FT,Switzerland,M,Switzerland,50,"Python, TensorFlow, Scala, Kubernetes",Associate,15,Transportation,2025-01-14,2025-02-24,1777,7.5,Neural Networks Co +AI11318,AI Research Scientist,92771,USD,92771,EN,CT,Denmark,L,Denmark,50,"Git, Kubernetes, Python",Bachelor,1,Transportation,2024-09-10,2024-10-17,1267,9.4,Predictive Systems +AI11319,Machine Learning Engineer,137444,JPY,15118840,SE,FL,Japan,L,Japan,100,"Docker, Linux, Tableau, NLP, Mathematics",Associate,6,Energy,2024-01-14,2024-03-05,2117,5.1,Neural Networks Co +AI11320,Research Scientist,72988,CAD,91235,EN,FL,Canada,L,Canada,100,"Git, Python, Java, AWS, Scala",Associate,0,Automotive,2024-05-16,2024-06-12,1189,7.7,Smart Analytics +AI11321,Autonomous Systems Engineer,129227,USD,129227,SE,PT,Denmark,S,Denmark,0,"Python, TensorFlow, Git, Deep Learning",Bachelor,8,Automotive,2024-09-05,2024-10-31,1294,6.7,Future Systems +AI11322,ML Ops Engineer,84467,USD,84467,EN,FT,Ireland,L,Ireland,0,"SQL, Docker, Computer Vision",Master,0,Transportation,2025-01-15,2025-03-20,1191,9.7,Predictive Systems +AI11323,Data Analyst,98088,GBP,73566,MI,FL,United Kingdom,L,United Kingdom,0,"PyTorch, Mathematics, Git, Kubernetes, Python",Master,3,Government,2024-05-09,2024-07-11,988,7.3,Cloud AI Solutions +AI11324,Research Scientist,119116,USD,119116,SE,PT,Sweden,S,Sweden,100,"Docker, Linux, Mathematics, Deep Learning",PhD,9,Consulting,2024-03-26,2024-04-21,1723,6.2,Predictive Systems +AI11325,Autonomous Systems Engineer,181037,USD,181037,EX,FL,Ireland,M,Ireland,100,"Linux, Spark, NLP",PhD,18,Energy,2024-09-11,2024-11-23,1753,5.3,Digital Transformation LLC +AI11326,AI Consultant,79650,JPY,8761500,EN,FT,Japan,M,Thailand,50,"Tableau, GCP, PyTorch, MLOps, TensorFlow",PhD,1,Telecommunications,2025-04-06,2025-06-07,1950,9.7,Cognitive Computing +AI11327,Robotics Engineer,81235,CHF,73112,EN,FL,Switzerland,M,Switzerland,50,"R, Spark, Python, Azure",Bachelor,0,Government,2024-04-01,2024-06-08,1105,7.9,Neural Networks Co +AI11328,AI Architect,71268,EUR,60578,EN,CT,Netherlands,M,Netherlands,50,"Tableau, MLOps, Kubernetes, Scala, Mathematics",PhD,1,Telecommunications,2025-03-14,2025-04-10,630,5.3,Autonomous Tech +AI11329,AI Product Manager,227826,CAD,284783,EX,PT,Canada,M,Canada,50,"R, Scala, PyTorch, Python, Linux",Master,13,Technology,2024-08-30,2024-10-07,1875,6.1,Future Systems +AI11330,Robotics Engineer,96577,USD,96577,MI,PT,Ireland,L,Romania,50,"Deep Learning, Spark, Computer Vision, Scala",PhD,3,Energy,2025-04-18,2025-06-01,1204,7.4,Cognitive Computing +AI11331,Data Analyst,32109,USD,32109,EN,CT,China,L,China,0,"Git, NLP, Data Visualization, Mathematics, Linux",Associate,1,Transportation,2024-02-12,2024-03-10,2181,7.1,Smart Analytics +AI11332,AI Architect,125192,USD,125192,EX,PT,China,L,China,0,"MLOps, Deep Learning, R, SQL",Master,14,Manufacturing,2025-03-17,2025-04-21,1763,9.2,Quantum Computing Inc +AI11333,Machine Learning Researcher,70652,JPY,7771720,EN,FL,Japan,L,Japan,100,"Computer Vision, SQL, Linux, Tableau, Git",Bachelor,1,Transportation,2024-12-25,2025-01-15,2207,6,Quantum Computing Inc +AI11334,NLP Engineer,114477,USD,114477,SE,FT,South Korea,L,South Korea,100,"MLOps, Data Visualization, Azure, Docker",Master,7,Gaming,2024-07-12,2024-09-13,2184,7.6,TechCorp Inc +AI11335,Robotics Engineer,46341,USD,46341,EN,CT,South Korea,S,South Korea,100,"Kubernetes, Tableau, NLP, Spark, Linux",Associate,1,Technology,2024-04-05,2024-05-09,2226,7.3,Cognitive Computing +AI11336,Research Scientist,68397,USD,68397,MI,PT,Israel,M,Israel,50,"Tableau, Scala, GCP",Master,4,Automotive,2024-05-05,2024-06-27,1629,7.2,AI Innovations +AI11337,Machine Learning Researcher,87051,USD,87051,MI,FL,Finland,S,Finland,100,"Linux, Java, Data Visualization, Computer Vision",PhD,4,Government,2025-03-20,2025-04-11,1691,9.9,AI Innovations +AI11338,AI Architect,79887,USD,79887,EN,FT,United States,L,United States,0,"Computer Vision, SQL, R",Bachelor,0,Automotive,2025-02-24,2025-04-28,1084,8.7,Smart Analytics +AI11339,Deep Learning Engineer,134547,EUR,114365,EX,FT,France,S,Turkey,50,"Computer Vision, Python, Tableau, TensorFlow, Statistics",Associate,19,Consulting,2024-05-13,2024-07-07,2369,9.9,Algorithmic Solutions +AI11340,Deep Learning Engineer,108427,EUR,92163,MI,FL,Austria,L,Austria,0,"Tableau, GCP, Linux",Associate,2,Real Estate,2024-01-16,2024-02-05,2062,8.8,Smart Analytics +AI11341,Research Scientist,45769,EUR,38904,EN,FL,Austria,S,Canada,50,"Data Visualization, Hadoop, Mathematics, Kubernetes",Bachelor,1,Technology,2024-07-09,2024-08-09,2381,5.1,Digital Transformation LLC +AI11342,Research Scientist,65686,EUR,55833,EN,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, Git, Scala, MLOps",PhD,1,Telecommunications,2024-10-01,2024-12-09,1542,7.1,Future Systems +AI11343,AI Research Scientist,134629,USD,134629,EX,PT,Israel,M,Israel,0,"R, GCP, Docker, Kubernetes",Bachelor,16,Consulting,2025-04-07,2025-05-25,1542,8.7,Quantum Computing Inc +AI11344,Machine Learning Engineer,105266,USD,105266,EN,FT,Norway,L,Romania,100,"Python, TensorFlow, Kubernetes, PyTorch",Bachelor,0,Government,2024-10-01,2024-11-13,1447,8.2,AI Innovations +AI11345,ML Ops Engineer,111826,CAD,139783,SE,CT,Canada,L,New Zealand,0,"Linux, Python, AWS, SQL",Associate,9,Automotive,2025-02-26,2025-04-29,949,8.1,Advanced Robotics +AI11346,Robotics Engineer,97870,USD,97870,SE,FL,Sweden,S,Norway,0,"Spark, Deep Learning, R",Associate,8,Energy,2024-01-26,2024-03-14,582,9.6,Future Systems +AI11347,NLP Engineer,56233,USD,56233,SE,CT,China,S,China,50,"Tableau, SQL, PyTorch, MLOps, Docker",PhD,9,Manufacturing,2024-05-14,2024-07-03,710,6,TechCorp Inc +AI11348,Data Scientist,136380,AUD,184113,SE,CT,Australia,M,Australia,100,"Hadoop, Docker, Scala",Bachelor,5,Real Estate,2025-02-05,2025-03-17,711,8.6,Cloud AI Solutions +AI11349,Machine Learning Engineer,129432,USD,129432,SE,PT,Sweden,M,Sweden,0,"Linux, Azure, NLP, Statistics, AWS",Associate,7,Gaming,2025-04-13,2025-05-13,2032,8.1,AI Innovations +AI11350,Deep Learning Engineer,274081,USD,274081,EX,FT,Denmark,S,Luxembourg,0,"SQL, Spark, Statistics, Git, Python",Associate,17,Real Estate,2024-12-26,2025-02-23,1154,8.8,DataVision Ltd +AI11351,Data Engineer,70458,USD,70458,MI,PT,Finland,S,Finland,50,"Scala, SQL, Python, Spark, GCP",Bachelor,3,Telecommunications,2024-12-28,2025-01-25,1865,7.4,DataVision Ltd +AI11352,Deep Learning Engineer,54782,CAD,68478,EN,FT,Canada,S,Canada,50,"Hadoop, Data Visualization, AWS, TensorFlow",PhD,0,Government,2024-07-12,2024-08-29,2043,9.8,Advanced Robotics +AI11353,AI Research Scientist,64330,EUR,54681,EN,FT,Austria,M,Austria,100,"Deep Learning, Tableau, Python, Azure",Bachelor,0,Media,2024-03-05,2024-03-25,1355,7.6,Digital Transformation LLC +AI11354,Head of AI,253257,USD,253257,EX,PT,United States,L,United States,100,"GCP, Python, AWS",PhD,12,Transportation,2025-03-31,2025-05-04,950,7.9,Future Systems +AI11355,AI Research Scientist,72157,JPY,7937270,EN,CT,Japan,S,Japan,50,"Azure, Linux, R, Tableau",Associate,1,Gaming,2025-03-29,2025-04-21,1647,6.3,Digital Transformation LLC +AI11356,AI Specialist,79437,EUR,67521,EN,PT,Netherlands,M,Netherlands,100,"Tableau, Hadoop, Java",Master,0,Finance,2025-03-12,2025-03-29,566,6.8,Cognitive Computing +AI11357,AI Research Scientist,89807,USD,89807,EN,PT,Norway,S,Norway,100,"Docker, Spark, MLOps, Scala",Bachelor,0,Consulting,2024-02-28,2024-04-21,987,7.5,TechCorp Inc +AI11358,Data Engineer,223811,USD,223811,EX,FL,Norway,L,Norway,100,"Deep Learning, TensorFlow, NLP, Hadoop",Associate,13,Government,2025-02-10,2025-03-06,1630,6.3,Cloud AI Solutions +AI11359,Principal Data Scientist,43079,USD,43079,SE,CT,India,M,India,100,"MLOps, GCP, Java, PyTorch, Azure",Bachelor,7,Energy,2024-08-23,2024-10-24,781,9.2,Autonomous Tech +AI11360,Data Engineer,171228,SGD,222596,SE,FL,Singapore,L,Singapore,0,"Data Visualization, Hadoop, Python",Bachelor,7,Automotive,2024-12-23,2025-01-25,1585,7.1,DataVision Ltd +AI11361,AI Software Engineer,320305,USD,320305,EX,FT,United States,L,United States,50,"Scala, Hadoop, Tableau, MLOps, Spark",Associate,11,Healthcare,2025-03-05,2025-04-07,2126,9.8,Advanced Robotics +AI11362,AI Specialist,265506,CAD,331883,EX,FT,Canada,L,Canada,100,"AWS, Data Visualization, GCP, Linux",Bachelor,16,Retail,2025-03-18,2025-05-28,1455,7.6,Machine Intelligence Group +AI11363,AI Product Manager,191096,CHF,171986,SE,CT,Switzerland,S,Switzerland,100,"AWS, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-04-21,2025-06-06,1793,9.5,Machine Intelligence Group +AI11364,Computer Vision Engineer,46630,USD,46630,MI,PT,China,L,China,100,"Computer Vision, Mathematics, TensorFlow, Python",PhD,4,Healthcare,2024-01-19,2024-03-24,531,5.1,Cloud AI Solutions +AI11365,AI Specialist,97986,USD,97986,SE,FL,Ireland,S,Russia,100,"Python, GCP, TensorFlow, Java",PhD,5,Healthcare,2025-02-26,2025-03-27,686,8,AI Innovations +AI11366,ML Ops Engineer,136685,USD,136685,SE,PT,South Korea,L,South Korea,0,"PyTorch, AWS, Linux",Bachelor,5,Technology,2024-10-14,2024-11-27,784,6.5,Cloud AI Solutions +AI11367,ML Ops Engineer,90657,CAD,113321,MI,PT,Canada,M,Canada,0,"PyTorch, SQL, Mathematics",Bachelor,2,Automotive,2024-10-09,2024-12-10,991,9.8,AI Innovations +AI11368,Research Scientist,170307,USD,170307,SE,FT,United States,L,United States,100,"Azure, Git, AWS",PhD,9,Technology,2025-01-02,2025-03-08,2456,9,Advanced Robotics +AI11369,Deep Learning Engineer,137251,USD,137251,MI,CT,Denmark,L,Denmark,0,"Java, SQL, PyTorch, AWS",Bachelor,2,Telecommunications,2025-02-12,2025-03-07,2401,9.2,Future Systems +AI11370,Data Scientist,175338,USD,175338,EX,PT,Finland,L,Finland,100,"TensorFlow, R, Mathematics, GCP, Deep Learning",Associate,10,Government,2025-02-19,2025-03-09,602,9.1,Digital Transformation LLC +AI11371,Deep Learning Engineer,81903,JPY,9009330,EN,PT,Japan,L,Japan,100,"Scala, Java, GCP",PhD,1,Energy,2024-11-10,2024-11-27,2492,8.8,Predictive Systems +AI11372,Data Engineer,119281,SGD,155065,SE,FT,Singapore,S,Singapore,0,"SQL, Python, Tableau, Deep Learning, AWS",Bachelor,7,Transportation,2024-05-06,2024-07-01,579,6.1,Machine Intelligence Group +AI11373,Machine Learning Researcher,59467,USD,59467,EN,FT,South Korea,L,South Korea,100,"SQL, Git, PyTorch, Kubernetes, Java",PhD,1,Finance,2024-12-08,2025-01-06,1293,9.8,Neural Networks Co +AI11374,Head of AI,136127,EUR,115708,SE,FT,Germany,M,Germany,100,"Git, Computer Vision, Spark",Associate,8,Healthcare,2024-04-18,2024-06-18,1980,7.5,Algorithmic Solutions +AI11375,Deep Learning Engineer,150034,USD,150034,EX,FT,Israel,S,Israel,100,"AWS, Git, Python, TensorFlow, R",Master,19,Government,2025-02-12,2025-04-21,1236,8.8,Autonomous Tech +AI11376,Research Scientist,293963,EUR,249869,EX,FT,Netherlands,L,Netherlands,50,"Scala, NLP, AWS, Azure, Git",Bachelor,12,Manufacturing,2024-06-26,2024-07-24,1473,8,Cognitive Computing +AI11377,NLP Engineer,93910,USD,93910,EN,PT,Norway,M,South Korea,50,"R, Deep Learning, Git, Python, Docker",PhD,1,Energy,2024-11-19,2025-01-20,782,7.6,Predictive Systems +AI11378,AI Specialist,106154,CAD,132693,SE,FL,Canada,S,Canada,100,"Mathematics, Python, Statistics",PhD,9,Retail,2024-09-22,2024-11-24,869,7.9,AI Innovations +AI11379,Principal Data Scientist,83026,EUR,70572,EN,CT,Germany,L,Germany,100,"Java, R, Hadoop, Scala",Associate,1,Education,2025-02-15,2025-04-11,924,6.6,AI Innovations +AI11380,AI Consultant,62488,USD,62488,EX,FL,India,S,India,0,"Git, NLP, Kubernetes, AWS, Computer Vision",Master,10,Healthcare,2024-05-21,2024-07-22,1404,6.3,Cognitive Computing +AI11381,Data Engineer,82469,JPY,9071590,EN,FL,Japan,L,Japan,100,"PyTorch, TensorFlow, Mathematics, Deep Learning, Data Visualization",Associate,0,Telecommunications,2024-07-21,2024-09-18,1642,5.3,DeepTech Ventures +AI11382,AI Research Scientist,37153,USD,37153,MI,FL,India,M,India,100,"Java, R, GCP, MLOps, Docker",PhD,4,Energy,2024-02-14,2024-04-04,2213,8.1,Cloud AI Solutions +AI11383,Head of AI,100902,USD,100902,SE,PT,South Korea,L,South Korea,50,"Python, Java, Linux, TensorFlow",PhD,8,Education,2024-05-27,2024-07-13,1402,9.1,Predictive Systems +AI11384,Data Engineer,61167,SGD,79517,EN,FT,Singapore,S,Singapore,0,"Python, Java, SQL, Linux, NLP",Associate,1,Real Estate,2024-07-25,2024-09-17,1081,8,Advanced Robotics +AI11385,NLP Engineer,72149,USD,72149,EX,PT,India,L,Ukraine,100,"Python, GCP, Tableau",PhD,16,Education,2024-09-13,2024-11-18,917,8.4,Future Systems +AI11386,Machine Learning Engineer,145674,USD,145674,SE,FL,Finland,L,Finland,0,"Python, Docker, Hadoop",PhD,9,Finance,2025-03-06,2025-04-14,1983,9.4,Neural Networks Co +AI11387,NLP Engineer,121414,CAD,151768,SE,FL,Canada,M,Canada,50,"Linux, Hadoop, Tableau, SQL, Python",Bachelor,7,Education,2024-08-23,2024-10-12,890,6.6,Digital Transformation LLC +AI11388,ML Ops Engineer,78140,EUR,66419,EN,PT,France,L,France,100,"SQL, Git, Scala, Hadoop, NLP",Associate,1,Automotive,2024-12-14,2025-02-06,826,8.9,Digital Transformation LLC +AI11389,Head of AI,141442,USD,141442,SE,FL,United States,M,United States,50,"Kubernetes, AWS, Data Visualization",PhD,9,Real Estate,2025-03-26,2025-05-28,1718,8.5,Smart Analytics +AI11390,Machine Learning Researcher,96067,USD,96067,MI,CT,Israel,L,Israel,50,"Tableau, Spark, Hadoop",PhD,2,Healthcare,2025-04-20,2025-06-26,1870,7.7,Cloud AI Solutions +AI11391,Data Scientist,388535,CHF,349682,EX,CT,Switzerland,L,Egypt,50,"MLOps, Azure, Data Visualization, Scala, SQL",Master,16,Transportation,2024-06-20,2024-07-06,929,9.4,Predictive Systems +AI11392,Deep Learning Engineer,132494,CAD,165618,SE,FL,Canada,L,Canada,100,"Python, Kubernetes, Azure",PhD,6,Transportation,2024-01-25,2024-03-10,1687,8.1,Smart Analytics +AI11393,Machine Learning Engineer,66690,EUR,56687,MI,FT,Austria,S,New Zealand,50,"Docker, Statistics, Deep Learning, Azure, Scala",Bachelor,3,Automotive,2024-02-09,2024-03-23,868,9.6,DataVision Ltd +AI11394,Data Scientist,122287,GBP,91715,MI,PT,United Kingdom,L,United Kingdom,100,"AWS, Python, Spark",Bachelor,2,Retail,2024-09-12,2024-10-29,1159,6,Quantum Computing Inc +AI11395,Machine Learning Engineer,81923,USD,81923,EN,CT,Ireland,L,Ireland,0,"Python, TensorFlow, Git, Docker",Master,0,Real Estate,2025-03-05,2025-05-10,2422,7.5,Future Systems +AI11396,ML Ops Engineer,317576,USD,317576,EX,FL,Denmark,L,United States,100,"NLP, Tableau, SQL",Associate,16,Media,2024-10-17,2024-11-26,1252,8.1,TechCorp Inc +AI11397,AI Architect,111218,EUR,94535,SE,FT,Austria,S,Austria,0,"Mathematics, R, Computer Vision",Bachelor,6,Technology,2025-03-05,2025-03-20,2285,9,AI Innovations +AI11398,Data Engineer,137824,AUD,186062,EX,PT,Australia,S,Australia,0,"Java, SQL, Deep Learning, Azure, Computer Vision",Associate,13,Consulting,2025-02-14,2025-03-07,1942,6.7,Digital Transformation LLC +AI11399,Computer Vision Engineer,124975,EUR,106229,MI,PT,Netherlands,L,Netherlands,0,"Python, Linux, Scala, Data Visualization",Master,3,Automotive,2025-01-04,2025-02-02,1299,6,Digital Transformation LLC +AI11400,AI Product Manager,202807,SGD,263649,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Tableau",Bachelor,10,Finance,2024-05-11,2024-07-05,1842,7.1,Cognitive Computing +AI11401,AI Product Manager,225578,CHF,203020,EX,CT,Switzerland,S,Switzerland,50,"Docker, Azure, Python",Master,12,Technology,2025-01-06,2025-02-02,2234,5.7,Quantum Computing Inc +AI11402,Data Analyst,67004,EUR,56953,EN,CT,Austria,M,South Africa,0,"R, SQL, GCP, Computer Vision",Associate,1,Retail,2024-05-07,2024-06-07,1313,5.1,Smart Analytics +AI11403,NLP Engineer,91436,USD,91436,MI,PT,Finland,M,Ireland,0,"Data Visualization, Spark, SQL",PhD,4,Telecommunications,2024-12-14,2025-02-10,889,7.2,Machine Intelligence Group +AI11404,Data Engineer,190150,USD,190150,SE,CT,Denmark,M,Denmark,100,"Git, SQL, Tableau",Bachelor,5,Telecommunications,2024-10-10,2024-12-19,1116,6,AI Innovations +AI11405,Research Scientist,190516,AUD,257197,EX,CT,Australia,L,Australia,50,"AWS, SQL, Kubernetes, Python",Master,17,Healthcare,2024-01-22,2024-03-25,1876,8.5,Predictive Systems +AI11406,Machine Learning Engineer,113403,EUR,96393,MI,CT,Netherlands,L,Netherlands,100,"GCP, Computer Vision, Mathematics, SQL, Scala",Bachelor,3,Real Estate,2024-05-05,2024-07-10,2473,9.6,Smart Analytics +AI11407,AI Product Manager,206127,USD,206127,EX,FL,United States,M,Sweden,0,"Java, R, Computer Vision, Git",Master,16,Energy,2025-02-09,2025-03-15,1636,5.7,Predictive Systems +AI11408,Machine Learning Engineer,164366,USD,164366,SE,CT,Sweden,L,Sweden,100,"Scala, Data Visualization, Spark",Bachelor,8,Telecommunications,2024-09-16,2024-11-23,2292,5.6,TechCorp Inc +AI11409,Machine Learning Engineer,135548,CAD,169435,EX,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, GCP, Data Visualization",PhD,14,Automotive,2024-08-21,2024-10-29,731,8.5,Neural Networks Co +AI11410,Robotics Engineer,81926,EUR,69637,EN,CT,Netherlands,L,Singapore,0,"Data Visualization, Scala, AWS, Linux",Associate,1,Retail,2024-08-05,2024-10-07,1080,8.9,DeepTech Ventures +AI11411,NLP Engineer,61432,CAD,76790,MI,FT,Canada,S,Canada,0,"Python, NLP, Linux",Bachelor,4,Retail,2025-01-25,2025-03-22,1959,5.6,Quantum Computing Inc +AI11412,Data Engineer,82350,SGD,107055,EN,CT,Singapore,M,Austria,50,"Hadoop, Deep Learning, Kubernetes, Spark, NLP",PhD,1,Gaming,2024-03-29,2024-04-20,1918,8.6,Machine Intelligence Group +AI11413,Robotics Engineer,91758,USD,91758,EN,PT,Norway,L,Norway,0,"GCP, Docker, R",PhD,1,Media,2025-01-23,2025-02-24,1382,8.3,DataVision Ltd +AI11414,Head of AI,26320,USD,26320,MI,PT,India,M,India,100,"Scala, Python, Mathematics, SQL",Associate,4,Automotive,2024-11-16,2024-12-11,678,8.9,Digital Transformation LLC +AI11415,AI Research Scientist,181477,GBP,136108,SE,CT,United Kingdom,L,United Kingdom,100,"NLP, Python, Linux, Deep Learning, Scala",PhD,5,Finance,2024-07-14,2024-09-10,1750,9.9,DeepTech Ventures +AI11416,AI Product Manager,119031,CAD,148789,SE,FT,Canada,S,Canada,100,"R, PyTorch, Python, MLOps",Bachelor,7,Technology,2024-04-08,2024-05-15,1777,9,Advanced Robotics +AI11417,AI Consultant,199896,JPY,21988560,EX,CT,Japan,S,Japan,100,"Tableau, Computer Vision, Statistics",Associate,10,Healthcare,2024-06-16,2024-08-02,1371,8,Advanced Robotics +AI11418,Machine Learning Researcher,143700,CAD,179625,EX,FL,Canada,M,Norway,100,"Docker, MLOps, GCP, R",PhD,11,Technology,2025-04-17,2025-05-28,2111,5.4,Advanced Robotics +AI11419,Machine Learning Engineer,257865,GBP,193399,EX,CT,United Kingdom,M,United Kingdom,50,"AWS, Spark, TensorFlow, Docker",Bachelor,18,Retail,2025-03-28,2025-06-01,2455,6.7,DeepTech Ventures +AI11420,Data Engineer,88557,SGD,115124,MI,FL,Singapore,S,New Zealand,0,"Kubernetes, Git, Data Visualization",PhD,3,Finance,2024-09-11,2024-10-26,520,6.5,TechCorp Inc +AI11421,Computer Vision Engineer,170140,CAD,212675,EX,FT,Canada,S,Canada,0,"Tableau, PyTorch, Kubernetes, R, Linux",PhD,11,Healthcare,2024-09-27,2024-11-25,1734,5.4,DeepTech Ventures +AI11422,Data Engineer,78293,CAD,97866,MI,FL,Canada,L,Canada,100,"Python, SQL, Statistics, Docker, Java",Associate,2,Healthcare,2024-05-04,2024-06-06,2239,5.1,Machine Intelligence Group +AI11423,AI Product Manager,95607,USD,95607,EN,CT,Norway,M,Norway,0,"GCP, Git, Java, Azure",Bachelor,0,Consulting,2024-07-28,2024-08-16,1686,8.9,Smart Analytics +AI11424,Data Analyst,75288,USD,75288,EN,FT,United States,L,Ghana,50,"Git, Hadoop, Tableau, Linux",Master,1,Healthcare,2024-05-05,2024-06-29,1636,7.1,Advanced Robotics +AI11425,Data Engineer,99770,CHF,89793,MI,FT,Switzerland,S,Switzerland,100,"Tableau, Docker, Deep Learning, Python, Hadoop",Master,2,Retail,2024-08-13,2024-09-16,2414,6.4,Predictive Systems +AI11426,AI Product Manager,107307,EUR,91211,SE,PT,Germany,S,Germany,0,"Tableau, Hadoop, NLP, GCP",Associate,5,Government,2024-03-01,2024-04-25,1825,8.6,DataVision Ltd +AI11427,NLP Engineer,80388,CAD,100485,MI,PT,Canada,S,Australia,0,"Java, SQL, AWS",Master,4,Automotive,2024-03-17,2024-05-17,2261,5.8,AI Innovations +AI11428,AI Consultant,43320,USD,43320,MI,FL,India,L,India,0,"Java, SQL, Scala, Statistics, AWS",Associate,3,Gaming,2024-02-01,2024-04-05,1139,6.7,Digital Transformation LLC +AI11429,AI Product Manager,49686,USD,49686,EX,FL,India,S,India,0,"Spark, Mathematics, Linux, Python",Associate,14,Media,2024-07-22,2024-09-30,1729,5.2,Smart Analytics +AI11430,AI Consultant,41656,USD,41656,MI,FT,China,S,Romania,100,"Python, Java, MLOps, Git",Bachelor,4,Gaming,2024-02-09,2024-03-01,1449,9.6,DataVision Ltd +AI11431,Data Engineer,149191,USD,149191,EX,FT,South Korea,S,South Korea,50,"SQL, Mathematics, MLOps",Bachelor,13,Real Estate,2025-02-25,2025-04-05,2473,6.1,DataVision Ltd +AI11432,Data Analyst,70858,USD,70858,MI,FL,South Korea,S,Canada,100,"Python, PyTorch, Statistics, Data Visualization",Bachelor,4,Government,2024-02-23,2024-05-02,1997,7,TechCorp Inc +AI11433,AI Software Engineer,112994,EUR,96045,SE,FT,France,S,France,100,"TensorFlow, NLP, SQL, Hadoop, Spark",Bachelor,8,Technology,2024-06-16,2024-08-08,1673,5.6,Neural Networks Co +AI11434,NLP Engineer,81456,USD,81456,MI,FL,South Korea,L,South Korea,100,"Tableau, TensorFlow, PyTorch",Bachelor,2,Finance,2024-11-08,2024-11-22,515,5.2,TechCorp Inc +AI11435,Head of AI,54011,EUR,45909,EN,CT,Austria,M,Austria,0,"Deep Learning, PyTorch, Statistics, Computer Vision, R",Master,1,Consulting,2024-10-20,2024-11-08,1295,7.9,Algorithmic Solutions +AI11436,AI Specialist,85091,USD,85091,EN,PT,Denmark,M,Denmark,100,"Mathematics, Spark, Kubernetes",Associate,1,Energy,2024-02-15,2024-04-03,780,6.5,TechCorp Inc +AI11437,AI Software Engineer,115899,USD,115899,EN,PT,Norway,L,Norway,50,"PyTorch, Mathematics, Tableau, Spark",PhD,0,Media,2025-01-11,2025-03-10,2231,6,AI Innovations +AI11438,Research Scientist,89371,JPY,9830810,MI,FL,Japan,M,Japan,0,"GCP, Azure, Tableau, MLOps",PhD,2,Manufacturing,2025-02-13,2025-03-21,1803,8.4,Future Systems +AI11439,Principal Data Scientist,125683,EUR,106831,SE,FT,Netherlands,M,Netherlands,50,"SQL, Java, Python, Azure, R",PhD,9,Education,2025-02-08,2025-03-27,1423,8.8,AI Innovations +AI11440,AI Research Scientist,349284,CHF,314356,EX,PT,Switzerland,L,Switzerland,100,"Python, TensorFlow, Docker, Deep Learning",Bachelor,13,Retail,2025-04-05,2025-04-25,1937,5.4,Cognitive Computing +AI11441,Data Scientist,140809,EUR,119688,EX,PT,Netherlands,S,Denmark,0,"Python, TensorFlow, MLOps, Scala, Java",Associate,18,Government,2024-03-19,2024-05-05,1264,6.7,Algorithmic Solutions +AI11442,Machine Learning Engineer,69956,USD,69956,MI,CT,Finland,S,Finland,100,"R, PyTorch, NLP, Scala",Master,4,Media,2024-03-14,2024-05-13,841,9.4,Digital Transformation LLC +AI11443,Autonomous Systems Engineer,71681,EUR,60929,EN,FL,France,M,Belgium,0,"Deep Learning, Computer Vision, Tableau, Python, Azure",PhD,0,Transportation,2025-04-18,2025-05-09,1084,7.6,AI Innovations +AI11444,NLP Engineer,215291,CAD,269114,EX,FL,Canada,L,Canada,50,"R, SQL, Computer Vision, GCP, Kubernetes",Associate,15,Technology,2024-08-14,2024-09-27,2204,9.3,DataVision Ltd +AI11445,Computer Vision Engineer,22321,USD,22321,EN,FL,India,S,India,0,"Deep Learning, Java, Statistics, Hadoop, Scala",PhD,1,Gaming,2024-09-09,2024-11-01,1646,9.2,TechCorp Inc +AI11446,Machine Learning Researcher,107424,USD,107424,MI,FT,United States,S,United States,100,"Git, Docker, Python, Azure, Computer Vision",PhD,2,Finance,2025-01-17,2025-02-01,759,7.8,Digital Transformation LLC +AI11447,AI Product Manager,97858,AUD,132108,MI,FT,Australia,S,Sweden,100,"Git, Kubernetes, MLOps, Tableau, GCP",PhD,2,Telecommunications,2024-11-12,2024-12-27,948,5.5,DeepTech Ventures +AI11448,Head of AI,131805,USD,131805,SE,PT,Finland,L,Finland,100,"Kubernetes, MLOps, Azure, Deep Learning, Scala",Master,9,Manufacturing,2024-11-12,2024-12-13,1137,7.9,Cloud AI Solutions +AI11449,AI Product Manager,168977,EUR,143630,SE,FL,Germany,L,Norway,0,"Data Visualization, MLOps, PyTorch, Deep Learning",PhD,5,Media,2024-08-24,2024-10-29,1876,6.1,DeepTech Ventures +AI11450,Computer Vision Engineer,112692,USD,112692,SE,CT,Israel,M,Israel,100,"Scala, Kubernetes, Azure",Associate,5,Energy,2024-06-25,2024-08-20,2010,7.9,DataVision Ltd +AI11451,NLP Engineer,24819,USD,24819,EN,FL,India,S,India,100,"Spark, Deep Learning, Tableau",Bachelor,0,Retail,2024-10-01,2024-11-24,916,6.4,Cognitive Computing +AI11452,Autonomous Systems Engineer,50429,USD,50429,MI,CT,China,M,China,0,"AWS, Azure, R, Computer Vision",PhD,4,Transportation,2024-05-08,2024-07-17,2418,7.6,Algorithmic Solutions +AI11453,AI Product Manager,92616,CAD,115770,MI,PT,Canada,L,Canada,100,"TensorFlow, Mathematics, Tableau",PhD,4,Energy,2024-08-22,2024-09-17,1475,6.8,Predictive Systems +AI11454,AI Architect,149371,USD,149371,MI,PT,United States,L,Spain,100,"PyTorch, Azure, Kubernetes, TensorFlow",Bachelor,3,Healthcare,2025-01-02,2025-02-23,2177,6.7,Autonomous Tech +AI11455,Machine Learning Engineer,235873,CHF,212286,EX,PT,Switzerland,S,Brazil,100,"Java, Git, Docker, MLOps",Master,10,Consulting,2024-06-26,2024-09-03,1795,8.8,Smart Analytics +AI11456,AI Consultant,46440,USD,46440,EN,FT,South Korea,S,South Korea,0,"Kubernetes, Spark, NLP, Git, Python",Associate,0,Transportation,2024-05-04,2024-05-27,536,5.3,Neural Networks Co +AI11457,Computer Vision Engineer,227078,EUR,193016,EX,PT,Netherlands,M,Romania,0,"R, Spark, Scala, Python",PhD,14,Media,2024-12-27,2025-01-28,937,7.2,Autonomous Tech +AI11458,Robotics Engineer,63953,EUR,54360,EN,FL,Netherlands,M,Netherlands,100,"AWS, Python, Tableau, TensorFlow",Associate,0,Manufacturing,2024-11-13,2024-12-05,662,5.3,Cloud AI Solutions +AI11459,AI Software Engineer,77328,EUR,65729,MI,FL,Germany,S,Germany,0,"Spark, Scala, PyTorch, Linux",Bachelor,2,Technology,2024-05-01,2024-05-22,2423,7.8,Neural Networks Co +AI11460,AI Product Manager,64672,USD,64672,EN,CT,Sweden,L,Latvia,50,"TensorFlow, R, Spark, Python, Azure",PhD,0,Real Estate,2024-11-21,2024-12-14,1484,7.3,Digital Transformation LLC +AI11461,AI Product Manager,103343,GBP,77507,MI,CT,United Kingdom,S,Switzerland,100,"TensorFlow, Data Visualization, Linux, Mathematics, Kubernetes",PhD,3,Finance,2024-03-05,2024-05-08,1183,8.8,Quantum Computing Inc +AI11462,NLP Engineer,99987,EUR,84989,MI,CT,Netherlands,S,Netherlands,50,"Spark, Linux, Data Visualization, Python",Master,3,Education,2025-01-12,2025-01-26,2303,6.5,Machine Intelligence Group +AI11463,NLP Engineer,37144,USD,37144,MI,PT,China,M,China,0,"Mathematics, Scala, SQL, Python",Master,3,Media,2024-04-01,2024-05-23,2408,5.5,Predictive Systems +AI11464,Head of AI,239050,JPY,26295500,EX,FL,Japan,M,Japan,50,"Azure, SQL, Hadoop",Master,17,Government,2024-11-03,2024-12-21,1181,6.4,DataVision Ltd +AI11465,Research Scientist,63804,USD,63804,EN,FL,Ireland,M,Ireland,50,"MLOps, Mathematics, Statistics, AWS",Bachelor,1,Finance,2024-10-02,2024-10-22,1980,8,Predictive Systems +AI11466,AI Research Scientist,121719,USD,121719,MI,PT,Sweden,L,Germany,50,"Statistics, Hadoop, Deep Learning, R",Master,2,Automotive,2024-11-23,2024-12-15,1865,5.7,DataVision Ltd +AI11467,Robotics Engineer,318346,USD,318346,EX,FL,Norway,M,Norway,50,"Python, TensorFlow, Java",Associate,10,Telecommunications,2024-04-10,2024-06-17,1715,9.3,AI Innovations +AI11468,NLP Engineer,113713,JPY,12508430,SE,PT,Japan,M,Philippines,0,"Java, SQL, Python, TensorFlow, PyTorch",Associate,9,Technology,2024-07-22,2024-09-19,2127,9.1,TechCorp Inc +AI11469,Research Scientist,129110,CAD,161388,SE,FL,Canada,M,Canada,100,"Scala, AWS, Computer Vision, Statistics, Mathematics",Associate,6,Real Estate,2024-04-24,2024-06-15,1850,8.8,Quantum Computing Inc +AI11470,Research Scientist,76550,USD,76550,EN,FT,United States,S,France,0,"SQL, Statistics, R",Associate,1,Telecommunications,2024-03-21,2024-05-01,972,7.6,Neural Networks Co +AI11471,AI Software Engineer,160981,JPY,17707910,EX,CT,Japan,S,Japan,100,"Kubernetes, Computer Vision, NLP",Associate,19,Retail,2024-09-04,2024-10-19,2152,9.3,Cloud AI Solutions +AI11472,AI Software Engineer,249798,CHF,224818,EX,FL,Switzerland,L,Switzerland,100,"Azure, Deep Learning, Spark, Linux, NLP",PhD,13,Real Estate,2024-08-29,2024-10-23,854,7.2,Cloud AI Solutions +AI11473,AI Specialist,110277,USD,110277,MI,CT,Ireland,L,Ireland,0,"Python, Java, Tableau, Spark",PhD,4,Telecommunications,2024-09-11,2024-10-19,1386,5.6,Quantum Computing Inc +AI11474,AI Architect,314219,USD,314219,EX,CT,Denmark,M,Denmark,100,"Python, Azure, Scala",Bachelor,19,Transportation,2025-02-02,2025-03-29,1389,7.3,Quantum Computing Inc +AI11475,Data Analyst,335263,CHF,301737,EX,FL,Switzerland,L,Switzerland,100,"Statistics, SQL, GCP",Master,14,Consulting,2024-09-25,2024-11-23,1870,7.4,Quantum Computing Inc +AI11476,Machine Learning Engineer,124417,CHF,111975,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, SQL, MLOps, Linux",PhD,2,Gaming,2024-04-26,2024-05-25,2021,8.9,DataVision Ltd +AI11477,AI Research Scientist,124130,USD,124130,SE,FL,Finland,M,Finland,0,"Scala, Hadoop, R, Linux, NLP",Associate,8,Education,2024-06-03,2024-07-07,1239,6.5,Machine Intelligence Group +AI11478,Machine Learning Researcher,80925,USD,80925,EN,FL,United States,S,Netherlands,50,"Python, Kubernetes, Data Visualization, Azure",Master,0,Finance,2024-10-06,2024-11-03,1923,8.3,Quantum Computing Inc +AI11479,Head of AI,79342,USD,79342,MI,CT,Ireland,M,Colombia,100,"Linux, Java, Scala",Master,3,Healthcare,2024-03-18,2024-05-25,1291,9.5,Digital Transformation LLC +AI11480,Autonomous Systems Engineer,97152,USD,97152,EN,CT,United States,L,United States,0,"PyTorch, Scala, Tableau",Bachelor,0,Technology,2025-02-08,2025-04-13,2187,7,Machine Intelligence Group +AI11481,Machine Learning Engineer,142004,EUR,120703,SE,FT,France,L,France,0,"SQL, Computer Vision, AWS",Associate,6,Automotive,2024-02-25,2024-05-05,731,8.5,Future Systems +AI11482,Computer Vision Engineer,147965,USD,147965,SE,PT,United States,M,United States,50,"Azure, Java, GCP",PhD,7,Consulting,2024-03-21,2024-05-08,2334,7.9,Predictive Systems +AI11483,Deep Learning Engineer,192037,USD,192037,EX,CT,Ireland,L,Ireland,50,"Java, Docker, NLP",Bachelor,10,Real Estate,2024-01-11,2024-02-08,1028,5.9,DeepTech Ventures +AI11484,Data Scientist,127383,EUR,108276,SE,FL,France,M,South Korea,0,"Kubernetes, Hadoop, Linux, GCP",PhD,9,Finance,2024-10-29,2024-12-30,1853,8.4,DeepTech Ventures +AI11485,Principal Data Scientist,85256,EUR,72468,MI,CT,Netherlands,S,Netherlands,50,"Scala, Mathematics, Python, Spark, GCP",PhD,3,Healthcare,2024-05-31,2024-08-06,899,5.5,Cloud AI Solutions +AI11486,Data Analyst,191885,USD,191885,SE,CT,Norway,L,Norway,50,"PyTorch, Python, Data Visualization",Bachelor,7,Consulting,2024-04-19,2024-06-15,2006,8.6,DataVision Ltd +AI11487,Data Engineer,106706,USD,106706,SE,FL,Israel,S,Israel,100,"Docker, Git, NLP, MLOps",Bachelor,6,Gaming,2025-03-24,2025-05-22,1323,7.6,Advanced Robotics +AI11488,AI Product Manager,144625,USD,144625,SE,FT,Ireland,L,Ireland,50,"Scala, Python, SQL, Mathematics",Bachelor,6,Government,2025-02-07,2025-04-08,2418,6.6,Machine Intelligence Group +AI11489,NLP Engineer,89096,GBP,66822,MI,CT,United Kingdom,L,United Kingdom,0,"R, SQL, Tableau, Statistics, Azure",PhD,4,Government,2025-02-17,2025-04-27,944,8.8,Predictive Systems +AI11490,AI Product Manager,113094,USD,113094,MI,FL,Denmark,M,Denmark,50,"Java, R, Statistics",Master,3,Real Estate,2024-03-15,2024-05-22,1878,7.7,DeepTech Ventures +AI11491,Machine Learning Researcher,44438,USD,44438,EN,FL,South Korea,S,South Korea,50,"Hadoop, Tableau, GCP, MLOps",PhD,0,Government,2024-03-11,2024-03-25,2149,8.8,Advanced Robotics +AI11492,AI Research Scientist,74828,EUR,63604,EN,CT,Netherlands,S,Netherlands,0,"Computer Vision, Python, Kubernetes, SQL",Master,1,Manufacturing,2024-09-12,2024-10-21,1386,6.3,Quantum Computing Inc +AI11493,Principal Data Scientist,79856,AUD,107806,MI,PT,Australia,M,Australia,0,"Hadoop, Scala, Git, Deep Learning, Java",PhD,2,Retail,2024-05-22,2024-07-24,1575,6.9,Quantum Computing Inc +AI11494,AI Specialist,155247,USD,155247,EX,FT,Ireland,M,Ireland,100,"Python, Mathematics, Git, Hadoop, Computer Vision",Master,17,Consulting,2025-02-04,2025-02-18,1759,9.4,Algorithmic Solutions +AI11495,AI Research Scientist,86084,EUR,73171,EN,PT,France,L,Poland,100,"Java, GCP, Data Visualization, Kubernetes, Python",Bachelor,1,Healthcare,2025-02-05,2025-04-03,1866,5.1,AI Innovations +AI11496,AI Specialist,121255,USD,121255,MI,PT,Norway,L,Norway,0,"SQL, Scala, AWS, GCP",PhD,4,Telecommunications,2024-03-28,2024-06-03,2180,8.1,TechCorp Inc +AI11497,AI Consultant,120964,USD,120964,SE,CT,Denmark,S,Nigeria,50,"Spark, SQL, Deep Learning",Associate,9,Healthcare,2024-05-10,2024-07-02,511,9.3,TechCorp Inc +AI11498,Autonomous Systems Engineer,170957,GBP,128218,SE,FL,United Kingdom,L,United Kingdom,100,"Azure, Hadoop, Python",Associate,6,Retail,2024-11-16,2024-12-12,1965,8.5,DataVision Ltd +AI11499,Machine Learning Engineer,80134,JPY,8814740,MI,FL,Japan,M,Ireland,0,"Java, AWS, TensorFlow, Spark, Tableau",Associate,2,Manufacturing,2024-04-11,2024-06-07,936,6.7,Smart Analytics +AI11500,AI Consultant,139486,JPY,15343460,EX,FT,Japan,S,Canada,50,"NLP, Python, Data Visualization",Associate,13,Finance,2024-09-07,2024-11-17,1203,6.6,Neural Networks Co +AI11501,Deep Learning Engineer,65381,SGD,84995,EN,FT,Singapore,L,Singapore,50,"Linux, R, Docker, Python",Bachelor,0,Education,2024-11-21,2025-01-17,1622,6.9,TechCorp Inc +AI11502,Data Engineer,171324,USD,171324,EX,CT,Norway,S,Norway,0,"Statistics, SQL, Scala, Kubernetes, Data Visualization",Bachelor,15,Education,2024-07-02,2024-08-11,1183,7.5,Advanced Robotics +AI11503,AI Specialist,87775,USD,87775,SE,FL,South Korea,M,South Korea,100,"MLOps, SQL, Python, Scala, Git",Master,6,Media,2024-07-07,2024-08-04,2349,6.3,Cognitive Computing +AI11504,Deep Learning Engineer,172632,EUR,146737,EX,FL,Austria,S,Austria,0,"Tableau, Kubernetes, AWS",Master,11,Manufacturing,2024-11-10,2024-12-30,2272,5.6,Neural Networks Co +AI11505,Data Analyst,88588,USD,88588,MI,PT,Denmark,S,Denmark,50,"Hadoop, Docker, Mathematics",Bachelor,4,Real Estate,2024-10-02,2024-10-18,572,6.8,DeepTech Ventures +AI11506,Data Scientist,168771,EUR,143455,EX,FT,Netherlands,M,Netherlands,0,"TensorFlow, NLP, Python, GCP",Associate,15,Retail,2025-03-16,2025-05-06,1787,5.7,DeepTech Ventures +AI11507,AI Product Manager,90000,USD,90000,MI,FT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, Data Visualization, SQL",Associate,4,Real Estate,2024-04-12,2024-04-29,1336,5.1,Quantum Computing Inc +AI11508,NLP Engineer,38919,USD,38919,MI,PT,China,M,Belgium,0,"R, Hadoop, NLP",Bachelor,3,Finance,2025-03-02,2025-03-24,1440,7.8,Predictive Systems +AI11509,Deep Learning Engineer,63396,EUR,53887,EN,CT,France,M,France,50,"Hadoop, GCP, AWS, Scala, Azure",Bachelor,0,Government,2024-07-03,2024-08-24,1182,5.9,DataVision Ltd +AI11510,AI Software Engineer,127703,USD,127703,EX,FL,South Korea,S,Indonesia,50,"Hadoop, Scala, TensorFlow, GCP",PhD,14,Retail,2024-11-18,2025-01-03,1976,6.3,Algorithmic Solutions +AI11511,Research Scientist,136930,USD,136930,MI,FT,Norway,M,Norway,50,"Azure, SQL, Computer Vision, Spark, Statistics",PhD,2,Manufacturing,2024-02-05,2024-03-06,2481,9.8,Cognitive Computing +AI11512,Machine Learning Researcher,62653,EUR,53255,EN,FL,Austria,S,Austria,0,"SQL, Scala, GCP",Bachelor,0,Media,2024-02-07,2024-04-07,1111,5.1,Smart Analytics +AI11513,AI Consultant,238158,USD,238158,EX,FL,Sweden,L,Sweden,0,"Mathematics, Data Visualization, GCP, Python, Git",PhD,19,Telecommunications,2025-02-03,2025-02-26,2232,7.3,Advanced Robotics +AI11514,AI Specialist,67273,AUD,90819,MI,FL,Australia,S,Australia,100,"AWS, Computer Vision, Linux, NLP",Bachelor,2,Telecommunications,2024-12-05,2024-12-25,1782,8.6,Cloud AI Solutions +AI11515,AI Software Engineer,296408,USD,296408,EX,FL,Denmark,L,Denmark,50,"Azure, Git, Statistics",PhD,12,Real Estate,2024-01-07,2024-02-03,1976,8.8,DeepTech Ventures +AI11516,Deep Learning Engineer,82078,EUR,69766,MI,FT,Netherlands,S,Netherlands,100,"AWS, Statistics, Tableau",Associate,3,Media,2025-03-27,2025-05-19,2475,9.3,Algorithmic Solutions +AI11517,Data Analyst,62170,EUR,52845,MI,CT,France,S,Australia,0,"AWS, Git, Python, GCP",PhD,2,Telecommunications,2025-04-17,2025-05-30,2294,6.8,AI Innovations +AI11518,Principal Data Scientist,156317,GBP,117238,SE,FL,United Kingdom,L,Thailand,100,"SQL, Scala, Kubernetes, Git",Bachelor,8,Government,2025-02-15,2025-03-20,2149,5.3,Algorithmic Solutions +AI11519,Principal Data Scientist,222260,CHF,200034,EX,FL,Switzerland,S,Switzerland,0,"SQL, PyTorch, Linux",Bachelor,11,Transportation,2024-08-15,2024-09-29,1557,8.8,Machine Intelligence Group +AI11520,Deep Learning Engineer,37876,USD,37876,SE,FL,India,S,India,0,"Data Visualization, Scala, R",Associate,5,Manufacturing,2024-09-05,2024-11-03,1333,8.7,Smart Analytics +AI11521,AI Consultant,78486,USD,78486,MI,PT,Sweden,M,Sweden,50,"Java, PyTorch, Linux",Associate,4,Energy,2024-10-03,2024-12-07,2117,9.1,DataVision Ltd +AI11522,Deep Learning Engineer,192938,EUR,163997,EX,CT,Netherlands,S,Kenya,100,"AWS, Scala, Deep Learning",Master,14,Transportation,2024-10-18,2024-12-29,1316,9.7,Predictive Systems +AI11523,Principal Data Scientist,43359,USD,43359,SE,PT,India,L,India,50,"Statistics, MLOps, Mathematics, Data Visualization",PhD,8,Healthcare,2025-01-27,2025-02-27,2445,8.8,Cognitive Computing +AI11524,Principal Data Scientist,118994,EUR,101145,SE,PT,Germany,M,Germany,100,"Spark, GCP, TensorFlow",Associate,9,Technology,2024-08-25,2024-10-07,1049,5.6,Neural Networks Co +AI11525,NLP Engineer,97478,CHF,87730,MI,FL,Switzerland,S,Switzerland,0,"Hadoop, SQL, Scala, Data Visualization, AWS",PhD,4,Telecommunications,2025-03-30,2025-05-01,1307,9.6,Digital Transformation LLC +AI11526,Head of AI,88392,EUR,75133,MI,FT,France,S,France,50,"Data Visualization, R, GCP, SQL",PhD,2,Energy,2024-11-28,2024-12-26,1526,5.8,Smart Analytics +AI11527,Machine Learning Researcher,134966,USD,134966,SE,FL,Sweden,S,Austria,50,"Kubernetes, Hadoop, PyTorch, Data Visualization, Computer Vision",Associate,6,Energy,2024-05-24,2024-06-14,1182,6,Cognitive Computing +AI11528,AI Specialist,106203,AUD,143374,MI,FL,Australia,M,Australia,0,"Azure, Computer Vision, SQL, Kubernetes, Statistics",Master,3,Telecommunications,2024-02-03,2024-02-24,1658,9.8,Predictive Systems +AI11529,AI Software Engineer,202928,USD,202928,EX,CT,Ireland,S,Ireland,0,"R, PyTorch, Git, Java",Bachelor,18,Gaming,2024-06-26,2024-07-24,2250,6.3,TechCorp Inc +AI11530,NLP Engineer,127991,USD,127991,MI,FT,Norway,S,Norway,100,"Mathematics, Data Visualization, R, Computer Vision",Bachelor,3,Real Estate,2024-11-18,2025-01-25,1062,8,AI Innovations +AI11531,AI Architect,92358,EUR,78504,SE,FL,Austria,S,Finland,50,"GCP, Kubernetes, AWS, Computer Vision",Associate,8,Manufacturing,2024-10-03,2024-12-02,2090,9,DataVision Ltd +AI11532,Data Engineer,272629,USD,272629,EX,FL,Norway,S,Russia,50,"MLOps, Docker, Java, Mathematics, PyTorch",Master,19,Retail,2025-02-17,2025-03-27,1463,8.6,Future Systems +AI11533,AI Architect,221472,JPY,24361920,EX,PT,Japan,S,Japan,50,"Tableau, Java, Docker, Scala",PhD,10,Media,2024-09-28,2024-10-19,1044,8.7,Neural Networks Co +AI11534,Autonomous Systems Engineer,73577,CAD,91971,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, MLOps, Java, PyTorch",PhD,1,Automotive,2024-03-30,2024-05-03,1561,7.1,DeepTech Ventures +AI11535,ML Ops Engineer,58063,EUR,49354,EN,CT,Germany,M,Germany,0,"Data Visualization, Scala, Linux, NLP",Master,0,Consulting,2024-09-04,2024-11-05,2249,9.1,DeepTech Ventures +AI11536,Computer Vision Engineer,219400,AUD,296190,EX,FL,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau, Azure, GCP",PhD,17,Transportation,2024-04-27,2024-07-03,1931,5.6,DeepTech Ventures +AI11537,Machine Learning Engineer,103961,GBP,77971,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Docker, Hadoop, Mathematics",Associate,2,Real Estate,2024-10-26,2024-12-20,1011,9.3,Algorithmic Solutions +AI11538,Data Scientist,82413,USD,82413,EX,PT,India,M,India,0,"Python, Spark, TensorFlow, GCP, PyTorch",Master,13,Finance,2024-03-18,2024-05-21,1591,8.7,Machine Intelligence Group +AI11539,Computer Vision Engineer,172900,CHF,155610,SE,FL,Switzerland,L,Switzerland,50,"SQL, Deep Learning, Tableau, TensorFlow, Statistics",Master,6,Media,2024-05-28,2024-06-15,2243,7.4,Quantum Computing Inc +AI11540,Research Scientist,189271,EUR,160880,EX,CT,Netherlands,M,Netherlands,0,"TensorFlow, GCP, Mathematics, Docker",Bachelor,10,Transportation,2024-10-02,2024-11-15,1545,5.3,Advanced Robotics +AI11541,AI Product Manager,111442,EUR,94726,MI,CT,France,L,France,100,"Python, Statistics, NLP",Bachelor,3,Government,2024-05-07,2024-07-01,1973,7.6,Predictive Systems +AI11542,NLP Engineer,67863,GBP,50897,EN,PT,United Kingdom,S,United Kingdom,100,"GCP, Deep Learning, NLP",Bachelor,0,Automotive,2024-07-06,2024-08-11,751,8.8,Cognitive Computing +AI11543,NLP Engineer,37216,USD,37216,MI,FT,India,M,India,100,"Scala, Spark, Tableau, Mathematics, Python",Associate,2,Consulting,2025-01-12,2025-02-18,1396,8.8,Autonomous Tech +AI11544,ML Ops Engineer,146138,USD,146138,SE,FT,Ireland,M,Ireland,0,"Deep Learning, Scala, Tableau, SQL, Computer Vision",Master,9,Media,2024-10-06,2024-11-11,1436,8.5,Cognitive Computing +AI11545,Data Scientist,45328,CAD,56660,EN,PT,Canada,S,Hungary,50,"Deep Learning, R, MLOps, SQL, Spark",Bachelor,0,Automotive,2024-10-18,2024-11-19,2424,8.9,TechCorp Inc +AI11546,Data Scientist,100310,USD,100310,MI,PT,Israel,L,Estonia,50,"Linux, Kubernetes, Scala, Python",PhD,4,Consulting,2024-04-22,2024-05-30,1423,7.2,Quantum Computing Inc +AI11547,Principal Data Scientist,147245,EUR,125158,SE,CT,France,L,France,50,"MLOps, Linux, Data Visualization, Spark",Associate,6,Media,2024-10-23,2024-11-18,729,6.4,Autonomous Tech +AI11548,Autonomous Systems Engineer,88089,EUR,74876,MI,FT,Germany,S,Germany,0,"Git, Azure, Python, Hadoop",PhD,3,Automotive,2024-01-17,2024-02-18,2100,7.4,Digital Transformation LLC +AI11549,Principal Data Scientist,72575,USD,72575,EN,CT,South Korea,L,South Korea,50,"TensorFlow, AWS, Deep Learning, Python, MLOps",Bachelor,0,Media,2024-11-06,2025-01-17,753,9.5,DeepTech Ventures +AI11550,AI Research Scientist,85617,USD,85617,MI,FL,Finland,S,Finland,50,"SQL, GCP, PyTorch, AWS",Bachelor,4,Healthcare,2025-04-26,2025-07-02,911,5.5,Cloud AI Solutions +AI11551,AI Consultant,89607,CAD,112009,MI,PT,Canada,S,Canada,50,"Computer Vision, AWS, SQL",Associate,2,Government,2024-10-17,2024-12-10,851,5.1,AI Innovations +AI11552,Robotics Engineer,51322,EUR,43624,EN,FL,Austria,S,Austria,50,"Git, Hadoop, SQL, NLP",PhD,1,Transportation,2025-01-05,2025-02-16,1864,7.7,Cognitive Computing +AI11553,Computer Vision Engineer,93109,EUR,79143,SE,PT,France,S,France,0,"Docker, Hadoop, Tableau, Statistics, GCP",Bachelor,9,Real Estate,2024-05-09,2024-06-23,1392,5.4,DeepTech Ventures +AI11554,Robotics Engineer,39952,USD,39952,MI,PT,China,S,China,100,"Statistics, R, Docker, Deep Learning",Master,4,Manufacturing,2024-12-22,2025-01-12,2188,7.8,TechCorp Inc +AI11555,Head of AI,53528,USD,53528,SE,CT,China,M,China,100,"TensorFlow, Python, Data Visualization",Bachelor,6,Media,2024-08-30,2024-10-28,1322,5.8,Predictive Systems +AI11556,Data Engineer,87394,EUR,74285,MI,FL,Netherlands,M,Netherlands,0,"Mathematics, GCP, Scala, NLP",Master,3,Healthcare,2024-03-12,2024-05-19,2338,9.7,Smart Analytics +AI11557,Deep Learning Engineer,172148,EUR,146326,EX,PT,Netherlands,S,Netherlands,50,"SQL, Python, Git",Bachelor,19,Manufacturing,2024-07-31,2024-08-24,712,5.6,TechCorp Inc +AI11558,AI Research Scientist,63353,EUR,53850,EN,FT,France,S,France,50,"Linux, PyTorch, R, MLOps, Statistics",Associate,1,Finance,2025-04-04,2025-04-23,1231,7.1,TechCorp Inc +AI11559,Machine Learning Researcher,65724,USD,65724,EN,FL,South Korea,L,South Korea,50,"Git, MLOps, GCP",Bachelor,0,Transportation,2024-02-04,2024-03-14,1883,7.4,Machine Intelligence Group +AI11560,ML Ops Engineer,114291,EUR,97147,SE,PT,Austria,S,Austria,100,"SQL, Kubernetes, Tableau, Linux",Associate,8,Education,2024-09-27,2024-11-09,666,8.2,DataVision Ltd +AI11561,Machine Learning Engineer,85594,USD,85594,EN,PT,Ireland,L,Ireland,50,"Git, Data Visualization, Hadoop, NLP, Deep Learning",Bachelor,0,Automotive,2024-04-04,2024-05-15,2034,7.9,DataVision Ltd +AI11562,AI Specialist,123737,JPY,13611070,SE,PT,Japan,M,Japan,50,"Python, AWS, Computer Vision, TensorFlow",Bachelor,5,Education,2024-09-01,2024-09-25,2237,5,Predictive Systems +AI11563,Deep Learning Engineer,240031,EUR,204026,EX,PT,Germany,M,Germany,0,"Java, Mathematics, TensorFlow",Master,11,Technology,2024-09-07,2024-10-18,683,8.7,Autonomous Tech +AI11564,Research Scientist,31490,USD,31490,MI,PT,India,M,Sweden,100,"Linux, SQL, Computer Vision, Data Visualization",Master,2,Telecommunications,2025-01-14,2025-02-12,1008,7.5,TechCorp Inc +AI11565,AI Specialist,60618,EUR,51525,EN,CT,Germany,L,South Korea,0,"R, Tableau, Deep Learning, Kubernetes",Master,0,Retail,2024-10-29,2024-12-02,1489,7.3,Predictive Systems +AI11566,AI Architect,78418,USD,78418,EN,CT,Israel,L,Israel,100,"Python, NLP, MLOps",Associate,0,Manufacturing,2024-09-05,2024-09-30,846,9.3,AI Innovations +AI11567,Data Scientist,269385,JPY,29632350,EX,CT,Japan,M,Japan,50,"NLP, Kubernetes, Spark, Mathematics, Python",Associate,13,Automotive,2025-01-31,2025-04-09,1439,8,Autonomous Tech +AI11568,Autonomous Systems Engineer,97601,USD,97601,MI,PT,United States,S,Ireland,100,"PyTorch, Azure, Linux, GCP",Bachelor,2,Finance,2024-09-08,2024-10-29,1430,6.3,AI Innovations +AI11569,AI Software Engineer,195834,USD,195834,EX,FL,Finland,S,Argentina,50,"TensorFlow, GCP, SQL",Associate,15,Consulting,2024-09-22,2024-11-15,987,9.9,Cognitive Computing +AI11570,AI Consultant,136182,USD,136182,EX,CT,South Korea,M,South Korea,100,"Scala, Deep Learning, Azure, Statistics, Data Visualization",Master,18,Transportation,2025-02-06,2025-03-05,1479,6.8,Smart Analytics +AI11571,AI Software Engineer,210024,CAD,262530,EX,FT,Canada,S,Switzerland,50,"Scala, Python, Hadoop, Git",Bachelor,11,Healthcare,2025-02-21,2025-03-22,1133,9.1,DeepTech Ventures +AI11572,Principal Data Scientist,54381,USD,54381,EN,FT,Israel,S,Israel,0,"Spark, PyTorch, Azure, R, Scala",Associate,1,Manufacturing,2024-12-06,2024-12-22,1312,5.1,DataVision Ltd +AI11573,AI Product Manager,190082,USD,190082,SE,CT,Denmark,M,Denmark,0,"Docker, GCP, Java, PyTorch, Deep Learning",Bachelor,9,Manufacturing,2024-08-23,2024-10-19,945,6.2,Cloud AI Solutions +AI11574,AI Software Engineer,84428,JPY,9287080,MI,FT,Japan,S,Japan,50,"Hadoop, TensorFlow, GCP",Associate,2,Media,2024-03-14,2024-04-14,1969,6.7,Cognitive Computing +AI11575,Robotics Engineer,111780,SGD,145314,SE,CT,Singapore,S,Singapore,0,"Python, GCP, AWS, Mathematics, TensorFlow",PhD,5,Transportation,2025-03-13,2025-03-30,746,5.1,Machine Intelligence Group +AI11576,Principal Data Scientist,103260,USD,103260,EN,FT,Norway,M,Norway,0,"R, Python, Spark, Java, GCP",Bachelor,0,Education,2024-12-21,2025-02-17,714,8.4,Digital Transformation LLC +AI11577,AI Specialist,129654,USD,129654,MI,CT,Denmark,L,France,50,"Docker, SQL, Data Visualization",Master,2,Gaming,2024-04-03,2024-06-07,815,6.6,Neural Networks Co +AI11578,AI Product Manager,37250,USD,37250,EN,PT,China,M,Indonesia,50,"Python, Scala, TensorFlow, Tableau",Associate,0,Telecommunications,2024-06-22,2024-09-03,1594,5.3,Advanced Robotics +AI11579,Data Scientist,287770,USD,287770,EX,PT,Ireland,L,Ireland,50,"Hadoop, PyTorch, Kubernetes",Master,13,Energy,2025-01-10,2025-03-14,761,5.5,Digital Transformation LLC +AI11580,Data Scientist,65359,JPY,7189490,EN,PT,Japan,M,Colombia,100,"Data Visualization, Git, Scala, Computer Vision",PhD,0,Gaming,2025-03-25,2025-04-14,1483,8.7,Smart Analytics +AI11581,NLP Engineer,122773,USD,122773,SE,FT,Ireland,M,Ireland,100,"SQL, Tableau, Spark",Associate,8,Government,2024-03-14,2024-04-05,1698,9.2,DataVision Ltd +AI11582,Data Engineer,60408,USD,60408,EN,PT,Finland,L,Finland,100,"Git, PyTorch, GCP, Spark, Tableau",Bachelor,1,Manufacturing,2024-08-13,2024-10-01,1351,6.5,TechCorp Inc +AI11583,AI Software Engineer,150096,USD,150096,SE,FT,Sweden,L,Sweden,50,"Python, TensorFlow, Spark",Associate,6,Telecommunications,2024-02-05,2024-04-08,1653,7.2,Future Systems +AI11584,Data Scientist,205206,EUR,174425,EX,FL,France,L,France,100,"SQL, Kubernetes, PyTorch",Bachelor,17,Gaming,2024-05-19,2024-06-11,1708,5.6,TechCorp Inc +AI11585,Data Scientist,26000,USD,26000,MI,FT,India,M,India,100,"PyTorch, Azure, NLP",PhD,4,Consulting,2024-10-17,2024-12-02,1250,9.1,Advanced Robotics +AI11586,Data Engineer,65860,USD,65860,EN,CT,South Korea,L,South Korea,100,"Mathematics, Scala, Python, Git, Computer Vision",Associate,0,Manufacturing,2024-09-19,2024-11-09,1493,7.8,Future Systems +AI11587,Computer Vision Engineer,94548,GBP,70911,MI,FT,United Kingdom,L,United Kingdom,50,"Hadoop, Tableau, Computer Vision",PhD,2,Telecommunications,2024-09-22,2024-11-27,848,9.5,Cognitive Computing +AI11588,Robotics Engineer,139420,USD,139420,SE,CT,Finland,L,Kenya,0,"GCP, Computer Vision, NLP",PhD,6,Automotive,2024-02-08,2024-03-11,1488,7.9,Neural Networks Co +AI11589,AI Consultant,96731,USD,96731,EN,FL,United States,L,United States,50,"Java, R, SQL, Docker",Associate,0,Real Estate,2024-07-19,2024-08-13,2423,5.2,Algorithmic Solutions +AI11590,Data Engineer,166302,EUR,141357,SE,FT,Netherlands,L,Switzerland,50,"Hadoop, Computer Vision, Python, Java, Kubernetes",Bachelor,6,Real Estate,2024-09-08,2024-09-25,622,6.3,Autonomous Tech +AI11591,AI Research Scientist,169852,USD,169852,EX,PT,South Korea,M,South Korea,100,"SQL, Git, Docker, PyTorch",Bachelor,19,Automotive,2024-05-04,2024-06-04,2138,5.4,Future Systems +AI11592,Autonomous Systems Engineer,50112,USD,50112,EN,PT,Ireland,S,Ireland,50,"Data Visualization, Computer Vision, SQL, Hadoop",PhD,0,Energy,2024-10-13,2024-12-03,1750,9.7,Autonomous Tech +AI11593,Data Engineer,25790,USD,25790,EN,FT,India,L,Romania,50,"TensorFlow, SQL, Hadoop, Tableau",Master,0,Media,2024-07-29,2024-08-27,1971,8,Cognitive Computing +AI11594,Robotics Engineer,111118,SGD,144453,SE,PT,Singapore,M,Singapore,50,"AWS, Docker, NLP, Kubernetes, Azure",Associate,7,Telecommunications,2025-03-23,2025-05-02,960,8.7,Cloud AI Solutions +AI11595,Data Engineer,63655,GBP,47741,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, Python, R, TensorFlow",PhD,0,Consulting,2024-03-16,2024-04-29,2498,6.2,Algorithmic Solutions +AI11596,AI Product Manager,180875,USD,180875,EX,CT,Ireland,L,Sweden,0,"Scala, Kubernetes, Python",Master,11,Finance,2024-11-07,2024-12-25,649,8.2,Algorithmic Solutions +AI11597,AI Software Engineer,59927,EUR,50938,EN,CT,France,S,Czech Republic,50,"Mathematics, Computer Vision, Data Visualization",Bachelor,0,Real Estate,2024-03-06,2024-05-12,794,9.5,Machine Intelligence Group +AI11598,AI Research Scientist,254962,EUR,216718,EX,FT,France,L,France,0,"SQL, NLP, Docker",Bachelor,15,Finance,2024-11-30,2025-01-07,1476,9.7,Autonomous Tech +AI11599,Machine Learning Researcher,173503,CHF,156153,SE,CT,Switzerland,S,Kenya,50,"Mathematics, Computer Vision, AWS",Associate,5,Retail,2024-06-02,2024-07-05,2001,7.4,Neural Networks Co +AI11600,Data Engineer,33680,USD,33680,EN,FL,China,M,China,100,"Statistics, AWS, PyTorch, Kubernetes, TensorFlow",Associate,0,Gaming,2024-10-14,2024-11-16,555,6.4,TechCorp Inc +AI11601,Machine Learning Researcher,115942,USD,115942,MI,FL,United States,L,United States,0,"Scala, AWS, Data Visualization, Computer Vision",Bachelor,3,Finance,2024-07-20,2024-09-09,1811,7.7,AI Innovations +AI11602,AI Architect,77384,AUD,104468,EN,FL,Australia,L,Australia,0,"R, Tableau, Linux, GCP",PhD,1,Real Estate,2025-02-28,2025-04-10,593,5.3,DeepTech Ventures +AI11603,Data Analyst,331419,CHF,298277,EX,FT,Switzerland,M,Switzerland,0,"Git, NLP, R",Associate,18,Manufacturing,2024-05-05,2024-06-17,2175,5.8,DeepTech Ventures +AI11604,Data Scientist,131344,USD,131344,SE,CT,Sweden,L,Australia,100,"Statistics, MLOps, Hadoop, Kubernetes, Docker",PhD,6,Government,2025-01-23,2025-03-23,2206,6.1,Advanced Robotics +AI11605,Autonomous Systems Engineer,81352,USD,81352,EX,PT,India,M,Kenya,50,"Python, TensorFlow, Deep Learning, Hadoop, Linux",Master,11,Telecommunications,2024-01-27,2024-03-15,1582,6.7,Quantum Computing Inc +AI11606,NLP Engineer,75140,EUR,63869,EN,FT,Netherlands,S,Netherlands,100,"Java, Spark, Kubernetes",Associate,0,Real Estate,2025-04-26,2025-05-23,2246,9.4,Cloud AI Solutions +AI11607,AI Specialist,57023,USD,57023,EN,FL,Ireland,M,United Kingdom,100,"NLP, Statistics, AWS, Kubernetes",Bachelor,0,Education,2024-03-23,2024-04-25,1207,8,Future Systems +AI11608,Principal Data Scientist,76910,JPY,8460100,EN,FL,Japan,S,Japan,50,"Python, Azure, Tableau, SQL, Deep Learning",Associate,1,Transportation,2025-02-24,2025-04-05,1100,5.5,Machine Intelligence Group +AI11609,Data Engineer,86816,USD,86816,EN,FT,Norway,S,Norway,50,"Hadoop, Python, MLOps, Docker, Tableau",Bachelor,1,Automotive,2024-12-28,2025-02-16,1200,7.4,Predictive Systems +AI11610,Head of AI,177419,EUR,150806,EX,FL,Austria,L,Austria,50,"PyTorch, Hadoop, Kubernetes, TensorFlow, Java",Master,14,Telecommunications,2024-11-19,2025-01-27,1430,7.7,DataVision Ltd +AI11611,Principal Data Scientist,143077,USD,143077,EX,FT,Israel,M,Italy,50,"R, Spark, AWS, Scala, NLP",Master,12,Real Estate,2024-12-05,2025-02-02,2272,5.8,Cognitive Computing +AI11612,Robotics Engineer,55124,SGD,71661,EN,FT,Singapore,S,United Kingdom,50,"Statistics, Scala, Hadoop, Spark",Associate,1,Government,2024-03-23,2024-05-01,792,7,Digital Transformation LLC +AI11613,Data Analyst,202411,USD,202411,EX,FL,Sweden,S,Sweden,100,"SQL, R, Tableau, PyTorch, Java",PhD,16,Healthcare,2024-09-05,2024-10-26,2074,6.4,AI Innovations +AI11614,Deep Learning Engineer,84402,EUR,71742,MI,PT,Austria,S,Belgium,50,"AWS, Git, TensorFlow, R",PhD,2,Healthcare,2024-04-20,2024-05-29,1385,10,Autonomous Tech +AI11615,Machine Learning Engineer,194046,GBP,145535,EX,PT,United Kingdom,L,United Kingdom,100,"Linux, Azure, Statistics, PyTorch",PhD,12,Manufacturing,2024-12-10,2024-12-26,2089,9.9,Smart Analytics +AI11616,Research Scientist,59744,AUD,80654,EN,PT,Australia,S,Australia,100,"MLOps, Computer Vision, Deep Learning, R",Associate,0,Healthcare,2024-04-18,2024-05-12,1076,7.2,Future Systems +AI11617,ML Ops Engineer,102625,USD,102625,SE,FL,Israel,M,Israel,50,"Azure, SQL, GCP",Master,5,Government,2024-01-27,2024-03-18,751,7.9,Neural Networks Co +AI11618,Computer Vision Engineer,56790,EUR,48272,EN,FT,France,S,South Korea,100,"Git, GCP, Java",Master,1,Manufacturing,2024-01-28,2024-04-05,1966,5.2,Autonomous Tech +AI11619,AI Specialist,56948,USD,56948,EN,PT,Ireland,M,Ireland,50,"SQL, Mathematics, TensorFlow, AWS",Master,0,Transportation,2024-01-25,2024-04-04,1345,6.9,Quantum Computing Inc +AI11620,AI Product Manager,124698,USD,124698,MI,FT,United States,M,Chile,50,"Java, R, Scala, Linux",PhD,3,Gaming,2024-10-11,2024-11-24,600,5.1,AI Innovations +AI11621,Principal Data Scientist,158637,USD,158637,SE,PT,Norway,L,Indonesia,50,"Data Visualization, Docker, Azure, R, PyTorch",Associate,6,Real Estate,2024-02-22,2024-04-23,1254,7.8,Quantum Computing Inc +AI11622,AI Product Manager,104750,USD,104750,MI,CT,Israel,L,Switzerland,100,"PyTorch, Spark, Tableau, Computer Vision, Azure",Associate,4,Technology,2024-12-11,2025-01-23,2141,6.4,Autonomous Tech +AI11623,AI Software Engineer,149617,JPY,16457870,EX,CT,Japan,S,Japan,50,"Kubernetes, Scala, Java",PhD,13,Consulting,2024-03-03,2024-03-20,523,6.7,DataVision Ltd +AI11624,Data Analyst,54122,SGD,70359,EN,CT,Singapore,M,Singapore,100,"Spark, PyTorch, Statistics, Docker, Mathematics",Bachelor,1,Real Estate,2024-04-30,2024-07-11,851,7.3,Smart Analytics +AI11625,Deep Learning Engineer,103462,JPY,11380820,MI,PT,Japan,S,Germany,100,"SQL, Kubernetes, Computer Vision, Java",Bachelor,3,Gaming,2024-05-07,2024-05-24,1539,5.1,Future Systems +AI11626,Data Analyst,200620,USD,200620,EX,PT,Denmark,S,Denmark,100,"TensorFlow, NLP, GCP, AWS, PyTorch",PhD,10,Energy,2024-09-26,2024-11-05,1152,9.5,Digital Transformation LLC +AI11627,Deep Learning Engineer,63203,GBP,47402,EN,FT,United Kingdom,S,Israel,0,"NLP, Python, AWS",Bachelor,1,Technology,2024-09-21,2024-10-21,1794,5.4,Advanced Robotics +AI11628,Machine Learning Researcher,92506,EUR,78630,EN,FL,Netherlands,L,Netherlands,50,"Scala, Python, Mathematics",Bachelor,0,Manufacturing,2024-09-26,2024-10-10,565,6.2,Predictive Systems +AI11629,AI Research Scientist,78404,USD,78404,MI,FT,South Korea,S,South Korea,50,"Mathematics, TensorFlow, Tableau, MLOps, Kubernetes",PhD,4,Real Estate,2025-01-19,2025-02-25,2407,9.3,Future Systems +AI11630,AI Product Manager,155868,EUR,132488,SE,FT,Netherlands,L,Netherlands,0,"Hadoop, TensorFlow, NLP",Master,6,Technology,2024-12-05,2025-01-17,2008,5.3,Predictive Systems +AI11631,AI Research Scientist,156517,USD,156517,SE,FL,United States,M,United States,50,"SQL, Linux, Data Visualization",PhD,8,Healthcare,2024-10-11,2024-12-17,1487,6.4,Algorithmic Solutions +AI11632,Data Analyst,212507,USD,212507,EX,FT,United States,S,Estonia,100,"AWS, Scala, Java, Statistics",Associate,12,Finance,2025-03-30,2025-05-04,1171,9.9,Advanced Robotics +AI11633,Machine Learning Researcher,171831,JPY,18901410,SE,CT,Japan,L,Japan,0,"TensorFlow, Hadoop, NLP",Bachelor,5,Technology,2024-03-30,2024-05-12,1514,6.1,AI Innovations +AI11634,Computer Vision Engineer,208009,USD,208009,EX,FT,United States,S,Chile,50,"Spark, PyTorch, SQL",Bachelor,14,Transportation,2024-07-28,2024-10-06,2490,5.8,Quantum Computing Inc +AI11635,Data Scientist,193197,EUR,164217,EX,FL,Germany,L,Germany,50,"Tableau, Python, Spark, Mathematics",Associate,19,Telecommunications,2024-05-18,2024-06-24,1462,5.7,Smart Analytics +AI11636,AI Architect,105371,USD,105371,MI,FT,Norway,S,Colombia,100,"R, MLOps, Spark, PyTorch, GCP",Bachelor,4,Finance,2024-10-16,2024-11-21,797,9.7,Algorithmic Solutions +AI11637,Deep Learning Engineer,166349,CAD,207936,EX,CT,Canada,L,Canada,0,"Spark, NLP, Scala",Bachelor,14,Telecommunications,2024-04-13,2024-06-17,1478,7.6,Autonomous Tech +AI11638,Research Scientist,141464,USD,141464,SE,FT,Denmark,M,Denmark,100,"MLOps, Git, Scala, GCP",Bachelor,6,Manufacturing,2024-12-27,2025-02-09,1520,7.4,Cognitive Computing +AI11639,AI Consultant,28009,USD,28009,EN,CT,China,M,China,100,"Linux, SQL, MLOps",Master,1,Telecommunications,2024-03-04,2024-03-26,2322,5.1,Digital Transformation LLC +AI11640,Head of AI,173041,USD,173041,EX,FL,Finland,S,Finland,100,"NLP, Kubernetes, Deep Learning, Git",Master,10,Government,2024-01-14,2024-02-17,730,8,Autonomous Tech +AI11641,Robotics Engineer,239925,USD,239925,EX,CT,Finland,L,Finland,100,"Python, Linux, Data Visualization, Scala, Mathematics",PhD,10,Manufacturing,2024-08-23,2024-10-29,2431,7.9,TechCorp Inc +AI11642,Deep Learning Engineer,36984,USD,36984,EN,FT,China,L,China,0,"Hadoop, Java, R, Data Visualization, Kubernetes",Associate,0,Government,2024-06-13,2024-07-21,1370,8.3,Predictive Systems +AI11643,AI Consultant,251261,USD,251261,EX,PT,Denmark,L,Poland,100,"Azure, Git, Linux",Bachelor,18,Real Estate,2024-12-13,2025-02-11,593,7.8,Neural Networks Co +AI11644,AI Consultant,139815,USD,139815,EX,PT,South Korea,L,Turkey,0,"NLP, SQL, Java, Deep Learning",Bachelor,13,Gaming,2024-09-26,2024-11-25,969,8.3,DataVision Ltd +AI11645,Deep Learning Engineer,51437,EUR,43721,EN,PT,France,M,France,50,"MLOps, AWS, Python, Hadoop, Statistics",Master,0,Media,2025-01-11,2025-03-08,830,8.6,Quantum Computing Inc +AI11646,AI Software Engineer,89863,USD,89863,SE,CT,South Korea,S,South Korea,50,"Git, Hadoop, Python, Linux, Kubernetes",Master,6,Healthcare,2024-02-06,2024-03-30,1952,8.7,Cloud AI Solutions +AI11647,Machine Learning Researcher,65048,USD,65048,EN,PT,Denmark,S,Denmark,50,"Computer Vision, Scala, R, Mathematics, Azure",PhD,0,Healthcare,2024-12-12,2025-01-30,1762,7,AI Innovations +AI11648,Machine Learning Researcher,136806,USD,136806,SE,PT,Sweden,L,Sweden,100,"TensorFlow, R, NLP",Associate,6,Media,2024-04-21,2024-05-06,952,9,Future Systems +AI11649,Deep Learning Engineer,104749,SGD,136174,SE,FT,Singapore,S,Singapore,0,"GCP, TensorFlow, Deep Learning, Python, Git",Associate,7,Retail,2024-02-29,2024-03-17,1742,6.4,Machine Intelligence Group +AI11650,Robotics Engineer,96999,USD,96999,MI,PT,South Korea,L,South Korea,0,"Python, Deep Learning, NLP",Associate,4,Finance,2024-06-25,2024-08-18,1657,5.2,Advanced Robotics +AI11651,Principal Data Scientist,243815,USD,243815,EX,FL,Norway,S,Ukraine,100,"Scala, Java, AWS, R, NLP",Master,18,Healthcare,2024-08-06,2024-09-04,1774,9.8,Neural Networks Co +AI11652,AI Product Manager,76637,GBP,57478,MI,FL,United Kingdom,S,Australia,100,"R, PyTorch, Mathematics, Kubernetes",PhD,4,Education,2025-03-08,2025-05-18,2173,7.5,Digital Transformation LLC +AI11653,ML Ops Engineer,85502,USD,85502,EN,PT,Denmark,L,Denmark,100,"PyTorch, Data Visualization, Spark, Scala, Deep Learning",Bachelor,1,Education,2025-04-12,2025-06-06,2375,6.9,Advanced Robotics +AI11654,Research Scientist,120897,JPY,13298670,SE,CT,Japan,M,Japan,50,"Python, Java, Mathematics",Master,6,Consulting,2024-11-25,2024-12-11,2364,8.5,Machine Intelligence Group +AI11655,Robotics Engineer,91013,USD,91013,EN,FL,Denmark,M,Denmark,0,"Python, Docker, Linux, Git, Scala",Bachelor,0,Media,2024-01-15,2024-01-29,2453,9.9,Predictive Systems +AI11656,Data Engineer,85335,EUR,72535,MI,FL,Austria,S,Austria,50,"Git, PyTorch, MLOps, Computer Vision",PhD,3,Energy,2024-09-09,2024-11-16,1556,5.4,Cognitive Computing +AI11657,AI Consultant,163644,USD,163644,SE,FL,Ireland,L,Ireland,0,"Git, GCP, Deep Learning, Python",Master,7,Finance,2024-10-14,2024-12-16,2454,7.4,Digital Transformation LLC +AI11658,Autonomous Systems Engineer,95444,USD,95444,EN,FT,Norway,M,Luxembourg,0,"Hadoop, PyTorch, TensorFlow",PhD,0,Media,2025-03-31,2025-05-28,1706,8.3,Neural Networks Co +AI11659,Computer Vision Engineer,246523,EUR,209545,EX,PT,Netherlands,M,Netherlands,0,"Scala, PyTorch, Statistics, SQL, Spark",Associate,11,Healthcare,2024-09-23,2024-11-08,1759,6.4,DataVision Ltd +AI11660,Research Scientist,65060,USD,65060,EN,CT,Finland,S,Finland,50,"Data Visualization, Hadoop, Azure",Master,1,Healthcare,2025-01-24,2025-02-24,2176,5.5,Cloud AI Solutions +AI11661,Principal Data Scientist,78657,GBP,58993,EN,PT,United Kingdom,M,United Kingdom,50,"Docker, Tableau, R",Bachelor,1,Gaming,2025-02-25,2025-04-10,545,6.9,Predictive Systems +AI11662,AI Specialist,138491,JPY,15234010,EX,PT,Japan,S,Denmark,0,"Hadoop, Azure, Python",Master,17,Telecommunications,2024-11-01,2024-12-04,749,8.7,Autonomous Tech +AI11663,AI Research Scientist,78736,SGD,102357,EN,PT,Singapore,L,Singapore,0,"Computer Vision, Data Visualization, Scala",PhD,1,Transportation,2024-09-20,2024-11-22,1390,8.7,Autonomous Tech +AI11664,Research Scientist,72680,EUR,61778,EN,PT,France,L,France,0,"Tableau, Git, Computer Vision, TensorFlow",Master,1,Automotive,2024-08-22,2024-10-16,1594,5.2,Cloud AI Solutions +AI11665,Data Scientist,46963,CAD,58704,EN,FL,Canada,S,Canada,100,"NLP, Python, Azure, TensorFlow, PyTorch",PhD,0,Finance,2024-05-26,2024-07-23,2231,6.8,Algorithmic Solutions +AI11666,AI Software Engineer,196455,AUD,265214,EX,PT,Australia,M,Egypt,0,"TensorFlow, Mathematics, Kubernetes",Master,16,Healthcare,2024-04-15,2024-06-10,714,7.7,Smart Analytics +AI11667,Data Scientist,150699,GBP,113024,SE,FT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Scala",PhD,7,Consulting,2024-05-07,2024-07-14,1491,8.2,Neural Networks Co +AI11668,Robotics Engineer,225713,EUR,191856,EX,PT,Netherlands,M,Netherlands,100,"Tableau, Kubernetes, Mathematics",Master,18,Real Estate,2024-02-23,2024-03-09,764,7.6,Predictive Systems +AI11669,Robotics Engineer,89546,USD,89546,EX,PT,India,M,Indonesia,100,"Java, NLP, Hadoop, SQL, Mathematics",Associate,10,Energy,2024-06-28,2024-08-30,2223,7.3,Autonomous Tech +AI11670,Data Scientist,38039,USD,38039,SE,PT,India,M,India,100,"Deep Learning, Git, Kubernetes, GCP",PhD,6,Media,2024-06-30,2024-07-23,1391,6.2,Machine Intelligence Group +AI11671,Data Analyst,157935,CHF,142142,SE,PT,Switzerland,M,Switzerland,50,"Docker, Statistics, NLP, Scala, Python",PhD,6,Consulting,2024-05-13,2024-07-05,2149,8.2,Cognitive Computing +AI11672,Data Analyst,87759,SGD,114087,MI,PT,Singapore,S,Singapore,100,"Git, AWS, Docker, SQL",Bachelor,3,Telecommunications,2024-01-09,2024-03-10,1228,6.9,Advanced Robotics +AI11673,AI Architect,155389,GBP,116542,SE,FL,United Kingdom,L,United Kingdom,0,"Tableau, Hadoop, PyTorch, NLP, Mathematics",Master,7,Manufacturing,2024-05-22,2024-07-04,1487,9.3,Predictive Systems +AI11674,Machine Learning Engineer,73343,EUR,62342,EN,CT,France,M,France,50,"Java, Deep Learning, NLP, SQL, Python",PhD,1,Automotive,2024-08-11,2024-10-04,2451,8.6,Autonomous Tech +AI11675,NLP Engineer,24357,USD,24357,EN,FT,India,L,India,50,"Deep Learning, Hadoop, Kubernetes, Java",Master,1,Automotive,2024-06-03,2024-06-18,950,7.8,Future Systems +AI11676,Autonomous Systems Engineer,69149,USD,69149,EN,FL,Israel,M,Israel,50,"Data Visualization, Java, SQL",PhD,1,Retail,2024-07-30,2024-09-10,2197,8.5,DeepTech Ventures +AI11677,AI Specialist,65314,EUR,55517,EN,PT,France,S,France,50,"Linux, R, PyTorch, GCP, Git",Associate,1,Media,2024-06-20,2024-07-27,1963,5.8,AI Innovations +AI11678,Deep Learning Engineer,133224,USD,133224,SE,PT,Sweden,L,Sweden,50,"TensorFlow, Git, Python, Deep Learning",Master,7,Gaming,2024-07-18,2024-08-18,2306,6.3,Cloud AI Solutions +AI11679,Head of AI,38105,USD,38105,EN,CT,South Korea,S,Italy,0,"AWS, Python, Statistics, TensorFlow",Associate,1,Real Estate,2025-03-17,2025-04-03,563,7.8,Cloud AI Solutions +AI11680,Deep Learning Engineer,63981,USD,63981,EN,FL,Israel,L,Israel,0,"SQL, NLP, Tableau, Computer Vision",PhD,1,Retail,2024-01-09,2024-02-14,1632,8.7,Cognitive Computing +AI11681,AI Software Engineer,231463,GBP,173597,EX,PT,United Kingdom,L,United Kingdom,50,"Data Visualization, Scala, R",Master,12,Education,2024-04-17,2024-06-04,1661,7.4,DataVision Ltd +AI11682,Data Engineer,303234,USD,303234,EX,FL,United States,L,United States,0,"Python, MLOps, Java, TensorFlow, Git",Bachelor,10,Finance,2024-03-14,2024-04-19,2490,6.8,Cognitive Computing +AI11683,Data Analyst,57839,USD,57839,EN,FT,Ireland,S,Ireland,100,"Git, Python, Java, Computer Vision, Scala",PhD,1,Manufacturing,2024-07-04,2024-09-15,746,5.9,DeepTech Ventures +AI11684,Head of AI,105737,USD,105737,MI,FL,Norway,M,Norway,100,"Computer Vision, Kubernetes, TensorFlow, Hadoop, Statistics",Associate,4,Education,2024-11-10,2024-12-31,746,7.9,TechCorp Inc +AI11685,NLP Engineer,83703,GBP,62777,EN,CT,United Kingdom,M,United Kingdom,0,"NLP, Deep Learning, Spark",PhD,1,Technology,2025-01-14,2025-03-14,1926,7,Quantum Computing Inc +AI11686,Research Scientist,374078,USD,374078,EX,FL,Denmark,L,Denmark,100,"Docker, Kubernetes, Deep Learning",PhD,18,Media,2024-04-04,2024-04-27,617,8.4,Predictive Systems +AI11687,AI Consultant,73845,USD,73845,MI,PT,Sweden,S,Sweden,50,"Mathematics, R, AWS",Associate,3,Transportation,2025-03-13,2025-05-22,1960,8.4,Predictive Systems +AI11688,Autonomous Systems Engineer,199570,USD,199570,EX,PT,South Korea,M,South Korea,0,"MLOps, Java, AWS",Master,18,Real Estate,2024-10-29,2024-11-24,1566,5.8,Predictive Systems +AI11689,ML Ops Engineer,59456,USD,59456,EN,FL,Ireland,S,Ireland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Retail,2024-06-23,2024-09-01,765,5.6,Cloud AI Solutions +AI11690,Principal Data Scientist,46874,USD,46874,MI,CT,China,M,China,50,"PyTorch, GCP, Computer Vision, NLP, AWS",Associate,2,Education,2024-06-09,2024-08-11,730,9.2,Quantum Computing Inc +AI11691,Machine Learning Researcher,264204,USD,264204,EX,PT,United States,M,United States,100,"Kubernetes, Hadoop, NLP",Master,12,Education,2025-04-19,2025-05-21,1029,5.7,Advanced Robotics +AI11692,Autonomous Systems Engineer,92702,USD,92702,MI,CT,Denmark,S,Denmark,100,"Linux, MLOps, Deep Learning, Hadoop",Bachelor,4,Energy,2024-04-13,2024-05-31,803,6,Digital Transformation LLC +AI11693,Machine Learning Engineer,127152,USD,127152,SE,FT,Ireland,M,Ireland,100,"Kubernetes, PyTorch, Git, Hadoop",Master,9,Media,2024-03-11,2024-04-17,821,8.2,Future Systems +AI11694,AI Product Manager,97952,USD,97952,EX,FL,India,L,India,0,"Linux, Data Visualization, Git, Deep Learning",Master,15,Finance,2024-07-17,2024-09-18,957,5.7,Algorithmic Solutions +AI11695,Deep Learning Engineer,119734,EUR,101774,SE,CT,Austria,L,Australia,100,"Scala, Python, NLP, Azure",Master,6,Gaming,2025-02-21,2025-05-03,2012,5.1,Neural Networks Co +AI11696,Head of AI,52313,USD,52313,SE,FL,India,L,India,100,"GCP, NLP, Git, Azure, MLOps",PhD,8,Education,2025-04-03,2025-05-24,2225,6,Algorithmic Solutions +AI11697,Principal Data Scientist,150527,USD,150527,SE,PT,Norway,S,Norway,100,"Tableau, Python, TensorFlow, Spark, Scala",PhD,6,Energy,2025-04-10,2025-05-09,1649,6.3,TechCorp Inc +AI11698,Research Scientist,102071,EUR,86760,SE,CT,Austria,M,Austria,100,"Data Visualization, PyTorch, Tableau, Spark",Bachelor,8,Transportation,2024-09-29,2024-10-24,750,6.4,Digital Transformation LLC +AI11699,AI Specialist,120049,JPY,13205390,SE,FL,Japan,M,Australia,100,"Python, GCP, TensorFlow, Docker, Mathematics",Master,8,Healthcare,2024-09-12,2024-10-31,2407,6.7,Advanced Robotics +AI11700,Data Scientist,57666,USD,57666,EN,FT,United States,S,Germany,0,"Python, TensorFlow, MLOps",Master,1,Telecommunications,2025-02-12,2025-03-09,664,6.4,AI Innovations +AI11701,Research Scientist,48186,USD,48186,EN,FT,South Korea,M,Egypt,0,"Data Visualization, Tableau, Linux, MLOps",Associate,1,Technology,2024-01-18,2024-02-28,1545,7.3,Advanced Robotics +AI11702,Research Scientist,105485,EUR,89662,SE,PT,Germany,S,Germany,0,"Statistics, Azure, Python",PhD,7,Manufacturing,2024-10-31,2025-01-10,2359,8.1,Cloud AI Solutions +AI11703,NLP Engineer,131219,SGD,170585,SE,PT,Singapore,S,Singapore,50,"Azure, NLP, Scala",Bachelor,7,Media,2025-03-22,2025-04-18,1790,9.4,Advanced Robotics +AI11704,Robotics Engineer,51061,AUD,68932,EN,CT,Australia,M,Switzerland,50,"Java, Linux, PyTorch, Azure, Spark",Bachelor,1,Retail,2025-03-07,2025-05-16,900,8.2,Digital Transformation LLC +AI11705,AI Research Scientist,118577,USD,118577,MI,PT,Israel,L,Singapore,0,"Hadoop, Spark, TensorFlow, Mathematics, NLP",Master,3,Telecommunications,2024-11-17,2024-12-08,915,9.3,TechCorp Inc +AI11706,Robotics Engineer,123562,JPY,13591820,MI,PT,Japan,L,Canada,0,"NLP, Computer Vision, Linux",Bachelor,4,Healthcare,2024-01-08,2024-02-17,2221,8.1,Advanced Robotics +AI11707,AI Research Scientist,51487,GBP,38615,EN,FT,United Kingdom,S,United Kingdom,50,"Tableau, Docker, MLOps, R, Kubernetes",Associate,0,Education,2024-05-08,2024-05-29,1828,6.3,Advanced Robotics +AI11708,AI Research Scientist,48045,EUR,40838,EN,CT,Austria,M,South Africa,0,"NLP, Git, PyTorch",PhD,1,Healthcare,2025-01-04,2025-01-22,2067,6.2,Quantum Computing Inc +AI11709,Principal Data Scientist,107844,USD,107844,SE,FT,Sweden,M,India,0,"Hadoop, Linux, Data Visualization",PhD,5,Telecommunications,2024-02-19,2024-03-09,2493,6.6,TechCorp Inc +AI11710,Machine Learning Engineer,39178,USD,39178,EN,FT,South Korea,S,India,50,"R, SQL, MLOps, Statistics, GCP",Bachelor,1,Consulting,2024-02-25,2024-04-07,2194,8.4,Machine Intelligence Group +AI11711,AI Architect,222589,SGD,289366,EX,FL,Singapore,S,Singapore,100,"Scala, R, MLOps, AWS, Tableau",Associate,19,Technology,2025-04-01,2025-04-19,1448,7.8,AI Innovations +AI11712,AI Software Engineer,103634,EUR,88089,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, Data Visualization, Tableau, TensorFlow, Docker",PhD,2,Education,2024-03-26,2024-04-13,1772,6.2,Smart Analytics +AI11713,AI Consultant,144301,SGD,187591,SE,FT,Singapore,M,Singapore,0,"Spark, R, TensorFlow, Computer Vision",Bachelor,6,Healthcare,2024-12-17,2025-02-21,2482,8.9,Predictive Systems +AI11714,AI Specialist,99374,EUR,84468,SE,PT,Austria,M,Austria,0,"Git, Scala, Java",Associate,7,Transportation,2024-04-05,2024-04-22,2414,6.5,Quantum Computing Inc +AI11715,AI Software Engineer,182255,USD,182255,EX,FL,Sweden,M,Sweden,0,"Data Visualization, Spark, Python, TensorFlow",Associate,18,Manufacturing,2024-10-22,2024-11-13,846,8,TechCorp Inc +AI11716,Data Engineer,64006,USD,64006,MI,CT,Finland,S,Finland,100,"Java, Kubernetes, Data Visualization, Scala, AWS",PhD,2,Retail,2025-04-12,2025-06-07,1653,6.9,Autonomous Tech +AI11717,Autonomous Systems Engineer,240322,CHF,216290,SE,FL,Switzerland,L,Switzerland,100,"Docker, Mathematics, PyTorch",Bachelor,7,Government,2024-06-28,2024-08-10,2379,7.5,AI Innovations +AI11718,Computer Vision Engineer,90893,USD,90893,MI,PT,Ireland,M,Ireland,50,"MLOps, Python, Azure, Statistics",Bachelor,4,Automotive,2025-04-26,2025-07-07,1506,5.3,Cognitive Computing +AI11719,AI Research Scientist,126730,GBP,95048,SE,PT,United Kingdom,M,United Kingdom,50,"Java, Python, R, TensorFlow, Kubernetes",Associate,6,Automotive,2024-01-27,2024-03-25,760,8.2,TechCorp Inc +AI11720,Deep Learning Engineer,90617,USD,90617,MI,FT,Ireland,S,Ireland,50,"Deep Learning, Git, Java",PhD,4,Media,2024-12-31,2025-02-16,2047,8.8,DataVision Ltd +AI11721,Head of AI,67532,CAD,84415,EN,FT,Canada,M,Luxembourg,100,"Computer Vision, Git, R, Kubernetes",Associate,0,Education,2024-05-11,2024-07-04,1673,5.8,Cloud AI Solutions +AI11722,AI Product Manager,81482,USD,81482,EN,CT,United States,M,United States,50,"AWS, Scala, Kubernetes, NLP",Associate,0,Finance,2024-12-16,2025-02-01,1186,7.6,Advanced Robotics +AI11723,Data Engineer,100637,JPY,11070070,MI,CT,Japan,M,Japan,0,"Java, Scala, Tableau",Master,2,Manufacturing,2024-06-07,2024-08-09,2037,8.2,Smart Analytics +AI11724,Autonomous Systems Engineer,182186,USD,182186,SE,CT,United States,L,United States,50,"Linux, AWS, NLP, TensorFlow",Master,7,Media,2024-06-11,2024-07-20,1317,6.9,Autonomous Tech +AI11725,Research Scientist,124119,USD,124119,MI,CT,Denmark,S,Belgium,0,"Java, Data Visualization, Scala, TensorFlow",Master,2,Government,2024-12-04,2025-01-23,1255,9.6,Advanced Robotics +AI11726,Robotics Engineer,75711,EUR,64354,EN,FL,France,M,South Korea,0,"R, Scala, GCP",PhD,0,Government,2024-04-26,2024-05-29,1596,7.8,DataVision Ltd +AI11727,AI Specialist,105178,USD,105178,EX,CT,China,L,Indonesia,50,"AWS, Azure, Tableau, SQL",Master,17,Consulting,2024-02-21,2024-05-02,1551,8.1,Advanced Robotics +AI11728,Data Engineer,245876,USD,245876,EX,FL,United States,M,United States,0,"Hadoop, Data Visualization, SQL, AWS",Associate,13,Government,2024-02-17,2024-04-20,1530,5.7,Cognitive Computing +AI11729,Principal Data Scientist,60817,USD,60817,SE,PT,China,M,New Zealand,0,"Kubernetes, PyTorch, Java, Spark, Computer Vision",Bachelor,6,Energy,2025-04-04,2025-06-08,2238,5.3,AI Innovations +AI11730,Autonomous Systems Engineer,159519,AUD,215351,EX,CT,Australia,S,Australia,100,"Linux, Java, Spark",Bachelor,13,Finance,2025-04-30,2025-07-09,686,8.6,TechCorp Inc +AI11731,AI Software Engineer,62606,USD,62606,EN,FL,Norway,S,Norway,100,"Tableau, TensorFlow, Git, Python",PhD,1,Real Estate,2024-09-27,2024-10-24,2295,7.1,TechCorp Inc +AI11732,ML Ops Engineer,87179,USD,87179,MI,FL,Sweden,S,Denmark,50,"Python, GCP, PyTorch, MLOps, AWS",Associate,4,Education,2024-07-30,2024-09-02,2230,5.6,Neural Networks Co +AI11733,Autonomous Systems Engineer,248988,GBP,186741,EX,PT,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, AWS, SQL",PhD,18,Healthcare,2024-01-30,2024-02-15,2260,8.5,DeepTech Ventures +AI11734,Research Scientist,85390,EUR,72582,EN,CT,Austria,L,Austria,50,"Linux, Hadoop, Docker, Python, Kubernetes",Master,0,Manufacturing,2025-03-19,2025-04-19,1718,7.1,Machine Intelligence Group +AI11735,Machine Learning Researcher,85050,USD,85050,EN,FT,Norway,L,Ukraine,0,"TensorFlow, Java, AWS",PhD,0,Healthcare,2024-03-08,2024-05-10,1927,5.7,Machine Intelligence Group +AI11736,Machine Learning Researcher,162248,USD,162248,SE,FL,Denmark,M,China,50,"Python, NLP, TensorFlow",Master,7,Media,2024-11-27,2025-01-11,1029,5.6,Autonomous Tech +AI11737,Machine Learning Engineer,89020,USD,89020,MI,FT,Ireland,M,Ireland,50,"Kubernetes, Data Visualization, Computer Vision, MLOps, NLP",Master,3,Energy,2024-12-05,2024-12-24,1355,7.9,Cloud AI Solutions +AI11738,Head of AI,197899,EUR,168214,EX,FL,Netherlands,L,Netherlands,0,"MLOps, Hadoop, AWS, Scala, TensorFlow",Bachelor,17,Consulting,2024-08-06,2024-10-06,1178,7.4,DataVision Ltd +AI11739,AI Software Engineer,300946,USD,300946,EX,CT,Denmark,L,Denmark,50,"MLOps, Azure, SQL, Kubernetes",Master,11,Gaming,2024-01-05,2024-03-13,949,6.2,Cloud AI Solutions +AI11740,ML Ops Engineer,128716,AUD,173767,SE,FT,Australia,L,Chile,100,"Azure, Scala, SQL, Spark",Associate,6,Technology,2025-01-16,2025-02-04,704,7.8,Autonomous Tech +AI11741,Machine Learning Researcher,69635,USD,69635,MI,FL,Ireland,S,Austria,50,"Mathematics, TensorFlow, Hadoop",Master,4,Energy,2024-04-17,2024-06-02,2256,10,DataVision Ltd +AI11742,Robotics Engineer,75013,USD,75013,EN,FL,Sweden,M,Latvia,0,"Kubernetes, Docker, Hadoop, MLOps",Bachelor,1,Government,2024-01-20,2024-03-25,2410,6.2,Cognitive Computing +AI11743,Head of AI,55579,USD,55579,EX,CT,India,L,India,100,"Spark, Git, R, Computer Vision",PhD,15,Finance,2024-10-15,2024-11-28,2417,8.1,Autonomous Tech +AI11744,Data Engineer,296991,EUR,252442,EX,PT,Netherlands,L,Netherlands,0,"Computer Vision, Python, TensorFlow, Mathematics, GCP",PhD,14,Retail,2024-01-02,2024-02-13,2415,8.6,Algorithmic Solutions +AI11745,Autonomous Systems Engineer,112545,JPY,12379950,MI,PT,Japan,M,Japan,0,"Python, NLP, SQL",PhD,3,Retail,2025-01-21,2025-03-06,1781,7.6,Quantum Computing Inc +AI11746,Computer Vision Engineer,69324,USD,69324,EX,PT,China,M,Colombia,0,"NLP, SQL, Java, R, Tableau",PhD,14,Education,2024-10-24,2024-12-23,519,7.5,DeepTech Ventures +AI11747,AI Research Scientist,98287,USD,98287,SE,FT,South Korea,S,South Korea,100,"R, Hadoop, Java, GCP, NLP",Bachelor,8,Retail,2024-12-05,2024-12-27,2317,7.2,DataVision Ltd +AI11748,AI Research Scientist,115628,SGD,150316,MI,CT,Singapore,L,Singapore,100,"Computer Vision, Python, GCP",Bachelor,2,Energy,2025-04-23,2025-07-03,2069,6.6,TechCorp Inc +AI11749,AI Research Scientist,61446,USD,61446,EN,PT,Finland,L,Finland,50,"Docker, Linux, Tableau",Master,0,Education,2025-02-08,2025-02-26,1567,8.6,Neural Networks Co +AI11750,AI Consultant,120919,USD,120919,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, AWS",Associate,3,Healthcare,2025-03-20,2025-04-13,1792,8.8,Cloud AI Solutions +AI11751,Research Scientist,145685,SGD,189391,SE,FL,Singapore,L,Chile,50,"AWS, Hadoop, NLP",Bachelor,5,Education,2024-11-30,2025-01-18,1182,7.2,DataVision Ltd +AI11752,Autonomous Systems Engineer,67265,USD,67265,EN,FL,South Korea,L,South Africa,100,"SQL, Kubernetes, Mathematics, PyTorch",Master,0,Transportation,2024-03-06,2024-04-05,927,9.6,DeepTech Ventures +AI11753,Principal Data Scientist,93562,CAD,116953,MI,CT,Canada,S,Canada,100,"Tableau, Linux, Kubernetes, GCP, Spark",Bachelor,4,Government,2024-02-26,2024-04-26,1548,5.6,DataVision Ltd +AI11754,AI Software Engineer,128363,EUR,109109,SE,CT,Germany,L,Germany,0,"Azure, Linux, Python, SQL",PhD,9,Media,2024-09-28,2024-12-10,591,5.6,Cognitive Computing +AI11755,Data Scientist,142169,EUR,120844,SE,FL,Netherlands,M,Netherlands,50,"Tableau, NLP, Scala, Java",Master,9,Transportation,2024-10-01,2024-12-03,1840,8.7,Autonomous Tech +AI11756,Data Analyst,82106,EUR,69790,MI,FL,Germany,M,Germany,0,"Java, Git, Computer Vision, Statistics, Data Visualization",PhD,4,Consulting,2024-02-01,2024-04-04,1738,5.8,Cognitive Computing +AI11757,AI Software Engineer,349865,CHF,314879,EX,FL,Switzerland,M,Switzerland,50,"Mathematics, Hadoop, Data Visualization",Associate,17,Automotive,2024-03-27,2024-06-06,661,9.9,Algorithmic Solutions +AI11758,Data Engineer,105787,USD,105787,SE,FL,South Korea,M,South Korea,100,"R, SQL, PyTorch, Mathematics",PhD,5,Telecommunications,2024-12-23,2025-01-18,2347,9.8,Smart Analytics +AI11759,Data Scientist,123402,USD,123402,MI,CT,Sweden,L,Ukraine,100,"NLP, AWS, PyTorch",Master,3,Gaming,2024-11-27,2024-12-22,592,7.6,Autonomous Tech +AI11760,Machine Learning Researcher,239675,USD,239675,EX,FT,Israel,M,Malaysia,100,"Tableau, MLOps, SQL, Mathematics, Git",Associate,12,Transportation,2024-01-13,2024-02-09,1523,8.8,Advanced Robotics +AI11761,Principal Data Scientist,241965,AUD,326653,EX,FT,Australia,L,Australia,100,"Hadoop, Data Visualization, Tableau, Deep Learning, Python",Bachelor,19,Telecommunications,2024-11-07,2024-11-24,853,8.5,Smart Analytics +AI11762,Machine Learning Engineer,76847,USD,76847,MI,FT,Sweden,M,Sweden,50,"MLOps, Computer Vision, SQL, Mathematics",Bachelor,4,Transportation,2024-07-17,2024-09-23,1659,7.9,Cloud AI Solutions +AI11763,Computer Vision Engineer,200851,USD,200851,SE,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Python, Azure",PhD,7,Gaming,2024-11-29,2025-01-11,2272,7.8,Cognitive Computing +AI11764,Research Scientist,130522,USD,130522,MI,FL,Denmark,L,Denmark,50,"Linux, Data Visualization, Hadoop, Git",Associate,3,Automotive,2024-11-22,2025-02-03,1442,5.3,DataVision Ltd +AI11765,AI Research Scientist,68149,USD,68149,EN,PT,South Korea,L,Thailand,50,"GCP, Linux, Spark, Computer Vision, Mathematics",Master,0,Manufacturing,2024-05-29,2024-07-05,673,6.1,Future Systems +AI11766,Principal Data Scientist,61452,EUR,52234,EN,FL,Netherlands,M,Singapore,0,"Python, AWS, Data Visualization, PyTorch, Kubernetes",Associate,0,Education,2025-01-15,2025-03-07,1472,9.6,Neural Networks Co +AI11767,Head of AI,86593,SGD,112571,MI,FL,Singapore,S,Singapore,100,"Mathematics, Computer Vision, Tableau, MLOps, Hadoop",Master,2,Transportation,2024-06-17,2024-08-04,766,9.4,Smart Analytics +AI11768,AI Consultant,62600,USD,62600,EN,FL,Norway,S,Norway,0,"AWS, R, MLOps, SQL",Master,1,Education,2025-03-29,2025-04-29,851,8,TechCorp Inc +AI11769,Machine Learning Researcher,77533,USD,77533,EN,FT,Denmark,M,Denmark,0,"Statistics, SQL, Python",Master,0,Telecommunications,2025-04-18,2025-05-20,2403,6.5,Autonomous Tech +AI11770,Deep Learning Engineer,212689,EUR,180786,EX,PT,Austria,L,Norway,50,"SQL, Git, Hadoop, Docker, GCP",Master,13,Telecommunications,2024-05-17,2024-06-20,2432,9.3,Advanced Robotics +AI11771,Data Scientist,118889,USD,118889,MI,FL,Israel,L,Netherlands,50,"Hadoop, SQL, Scala",PhD,2,Media,2024-08-18,2024-10-17,669,5.3,Advanced Robotics +AI11772,AI Software Engineer,145546,GBP,109160,SE,FT,United Kingdom,M,United Kingdom,100,"Statistics, Python, NLP, Deep Learning, R",Master,7,Telecommunications,2024-09-06,2024-11-05,1299,7.1,Quantum Computing Inc +AI11773,Deep Learning Engineer,91754,EUR,77991,MI,FL,Netherlands,S,Netherlands,100,"Hadoop, TensorFlow, PyTorch",Associate,3,Transportation,2024-07-27,2024-08-18,745,6.8,Autonomous Tech +AI11774,Research Scientist,144229,GBP,108172,EX,FL,United Kingdom,M,Germany,100,"Kubernetes, GCP, SQL",PhD,18,Real Estate,2024-02-16,2024-03-10,1543,8,Neural Networks Co +AI11775,Robotics Engineer,109199,EUR,92819,SE,PT,Austria,S,Austria,0,"Kubernetes, Statistics, Scala, PyTorch",Master,7,Automotive,2025-02-03,2025-03-08,2168,8.3,Quantum Computing Inc +AI11776,Head of AI,56909,USD,56909,EN,CT,Finland,M,Finland,100,"SQL, Scala, PyTorch, GCP, Java",PhD,1,Real Estate,2024-04-16,2024-05-27,1343,7,Algorithmic Solutions +AI11777,AI Consultant,117496,USD,117496,EX,PT,China,M,China,100,"Deep Learning, Docker, Data Visualization, Tableau, R",Associate,19,Transportation,2024-01-09,2024-02-01,1773,6.1,Predictive Systems +AI11778,Machine Learning Researcher,115487,USD,115487,MI,FL,Denmark,L,Denmark,100,"Kubernetes, PyTorch, Azure, Spark",Associate,4,Telecommunications,2024-01-02,2024-03-15,980,7.2,Cognitive Computing +AI11779,Computer Vision Engineer,115188,EUR,97910,MI,FT,Netherlands,M,India,0,"Data Visualization, NLP, SQL",PhD,4,Telecommunications,2024-08-07,2024-09-06,609,6.4,Cognitive Computing +AI11780,ML Ops Engineer,192782,USD,192782,EX,FL,Ireland,M,Ireland,50,"MLOps, Statistics, Mathematics, Scala, Data Visualization",Associate,16,Media,2025-03-21,2025-04-24,648,9.1,DeepTech Ventures +AI11781,Principal Data Scientist,158600,EUR,134810,EX,CT,Netherlands,S,Netherlands,100,"Python, Linux, Deep Learning",PhD,14,Automotive,2024-09-23,2024-11-18,582,5.5,Smart Analytics +AI11782,Robotics Engineer,64447,GBP,48335,EN,CT,United Kingdom,M,United Kingdom,100,"Computer Vision, Git, Tableau",Master,0,Finance,2024-07-25,2024-09-05,1713,6.5,Future Systems +AI11783,Research Scientist,189773,CHF,170796,SE,FL,Switzerland,M,Ukraine,100,"Computer Vision, Python, TensorFlow",Associate,8,Transportation,2024-05-28,2024-07-24,1824,6.1,Predictive Systems +AI11784,ML Ops Engineer,136525,CAD,170656,SE,CT,Canada,L,Canada,100,"Docker, Azure, Mathematics",Bachelor,9,Healthcare,2024-09-22,2024-11-21,1768,5.3,Algorithmic Solutions +AI11785,Head of AI,108746,USD,108746,EX,FT,South Korea,S,South Korea,50,"Azure, R, Scala, Tableau, Statistics",Master,16,Technology,2025-03-14,2025-05-24,2133,6.3,TechCorp Inc +AI11786,Robotics Engineer,79890,USD,79890,EX,PT,China,S,United States,50,"Computer Vision, Hadoop, GCP, Statistics",PhD,15,Automotive,2024-11-29,2024-12-20,1445,5.3,Predictive Systems +AI11787,AI Architect,128508,USD,128508,EX,FT,Finland,S,Nigeria,50,"Kubernetes, Docker, Spark",Master,16,Technology,2024-11-28,2025-01-05,1335,10,Algorithmic Solutions +AI11788,Computer Vision Engineer,149717,EUR,127259,SE,FT,Netherlands,M,Netherlands,0,"Mathematics, GCP, SQL",Master,6,Consulting,2024-05-22,2024-07-12,893,5.5,Cognitive Computing +AI11789,ML Ops Engineer,74780,CHF,67302,EN,CT,Switzerland,M,Italy,100,"Computer Vision, Mathematics, Tableau, Data Visualization",Master,0,Automotive,2025-03-26,2025-04-11,846,8.7,Autonomous Tech +AI11790,Data Analyst,86855,EUR,73827,EN,FT,France,L,France,50,"PyTorch, Deep Learning, NLP, R, AWS",Associate,1,Gaming,2024-03-06,2024-04-30,577,9.1,Cloud AI Solutions +AI11791,AI Research Scientist,153299,AUD,206954,SE,CT,Australia,L,Egypt,0,"TensorFlow, Python, Deep Learning",Master,9,Energy,2024-04-26,2024-05-11,1120,5.6,DeepTech Ventures +AI11792,Head of AI,53256,USD,53256,EN,PT,Ireland,S,Ireland,100,"GCP, R, Data Visualization, Hadoop, Kubernetes",Associate,1,Gaming,2024-03-29,2024-04-27,1989,7.5,Digital Transformation LLC +AI11793,ML Ops Engineer,104761,USD,104761,EN,CT,Norway,L,Norway,0,"Computer Vision, Git, GCP, Data Visualization",Associate,1,Automotive,2024-09-08,2024-11-13,1927,5.5,DeepTech Ventures +AI11794,AI Product Manager,257772,JPY,28354920,EX,CT,Japan,L,United States,0,"Java, R, Linux, SQL, NLP",Bachelor,11,Education,2024-02-19,2024-04-22,1495,7.6,Smart Analytics +AI11795,Data Analyst,113051,USD,113051,SE,FL,Israel,M,Thailand,50,"Mathematics, Deep Learning, Data Visualization",Master,5,Telecommunications,2024-01-04,2024-03-06,728,5.4,AI Innovations +AI11796,AI Architect,184356,JPY,20279160,SE,PT,Japan,L,Japan,100,"AWS, Tableau, Python",Bachelor,9,Consulting,2024-04-03,2024-04-24,1525,6.7,DeepTech Ventures +AI11797,AI Research Scientist,48522,CAD,60653,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, Tableau",Bachelor,1,Education,2024-05-25,2024-07-20,1523,6.9,Machine Intelligence Group +AI11798,Data Engineer,57358,SGD,74565,EN,CT,Singapore,M,Singapore,100,"Kubernetes, Docker, MLOps, Scala, Mathematics",Associate,0,Education,2025-04-18,2025-05-03,1292,8.7,Future Systems +AI11799,AI Architect,92877,CAD,116096,SE,FT,Canada,S,Canada,0,"Statistics, AWS, Deep Learning",Associate,8,Manufacturing,2024-01-06,2024-03-13,2113,9.1,Cloud AI Solutions +AI11800,Data Engineer,64999,USD,64999,MI,FT,Israel,S,Israel,0,"GCP, Mathematics, Data Visualization, Python",Associate,3,Transportation,2024-03-22,2024-04-16,2159,9.7,Neural Networks Co +AI11801,Deep Learning Engineer,216255,EUR,183817,EX,PT,Germany,L,Germany,50,"SQL, AWS, Tableau",Bachelor,14,Technology,2024-05-01,2024-07-07,742,8.8,DataVision Ltd +AI11802,AI Software Engineer,139600,CAD,174500,SE,FT,Canada,L,Canada,50,"PyTorch, Kubernetes, Computer Vision, Python, Tableau",PhD,9,Gaming,2024-05-08,2024-07-01,1981,9.8,Machine Intelligence Group +AI11803,AI Specialist,214259,USD,214259,SE,FT,Norway,L,Norway,50,"Python, Docker, Azure, Mathematics, Java",PhD,9,Automotive,2025-04-27,2025-05-11,2008,5.9,Predictive Systems +AI11804,Machine Learning Engineer,90613,USD,90613,EX,FL,India,L,India,0,"SQL, Git, Deep Learning, AWS",PhD,12,Education,2024-07-17,2024-09-06,1898,5.4,Future Systems +AI11805,AI Software Engineer,237611,AUD,320775,EX,PT,Australia,M,Australia,0,"Java, Computer Vision, Python, Mathematics",Associate,18,Automotive,2024-09-15,2024-11-23,2125,7.3,Quantum Computing Inc +AI11806,AI Specialist,85520,USD,85520,MI,CT,Israel,L,Israel,50,"Linux, SQL, Python, Scala",Master,2,Technology,2025-02-25,2025-03-11,1858,8.4,Digital Transformation LLC +AI11807,Computer Vision Engineer,120980,CAD,151225,EX,CT,Canada,S,Ukraine,0,"Computer Vision, Azure, Spark",Bachelor,10,Healthcare,2024-04-19,2024-05-31,940,7,Cognitive Computing +AI11808,Autonomous Systems Engineer,91834,EUR,78059,MI,PT,Austria,S,Portugal,50,"PyTorch, Scala, Data Visualization",Master,4,Government,2024-02-27,2024-04-21,516,7.9,DeepTech Ventures +AI11809,Computer Vision Engineer,197241,USD,197241,EX,FT,United States,M,Nigeria,0,"Deep Learning, TensorFlow, Hadoop, GCP",Bachelor,19,Education,2024-11-07,2024-12-28,652,7.3,Predictive Systems +AI11810,Machine Learning Researcher,26172,USD,26172,MI,FL,India,S,India,100,"Linux, NLP, Scala, Statistics",PhD,2,Consulting,2025-02-09,2025-03-14,603,5,Smart Analytics +AI11811,ML Ops Engineer,95730,USD,95730,SE,FT,Israel,S,Israel,0,"Tableau, Kubernetes, TensorFlow, Data Visualization, NLP",Master,5,Consulting,2024-02-26,2024-04-07,1257,6.2,Quantum Computing Inc +AI11812,Machine Learning Engineer,269491,USD,269491,EX,FT,United States,S,United States,50,"Tableau, R, Azure",Associate,15,Consulting,2024-11-04,2024-11-29,2469,8.9,Digital Transformation LLC +AI11813,Research Scientist,103816,CHF,93434,EN,FL,Switzerland,M,Switzerland,0,"GCP, R, Mathematics",Master,1,Government,2025-01-21,2025-02-25,1061,9.4,DataVision Ltd +AI11814,Data Analyst,120743,USD,120743,SE,PT,South Korea,M,Nigeria,100,"PyTorch, Java, Data Visualization",Bachelor,8,Education,2024-08-20,2024-10-07,2458,8.4,TechCorp Inc +AI11815,Data Scientist,23025,USD,23025,MI,FT,India,S,Denmark,100,"Linux, Hadoop, Python, Computer Vision",Associate,4,Consulting,2024-04-04,2024-05-15,1444,5.5,Machine Intelligence Group +AI11816,Autonomous Systems Engineer,44505,USD,44505,SE,FT,India,L,Romania,50,"Hadoop, Data Visualization, Git",Associate,6,Telecommunications,2024-10-04,2024-11-23,2406,8.7,Cognitive Computing +AI11817,Head of AI,105183,JPY,11570130,MI,PT,Japan,L,South Korea,100,"GCP, Spark, Deep Learning",PhD,3,Gaming,2024-09-03,2024-09-30,633,5.8,Autonomous Tech +AI11818,Machine Learning Engineer,137294,USD,137294,EX,PT,Israel,S,Mexico,0,"R, Scala, Docker, GCP",Master,12,Finance,2024-02-03,2024-03-05,1274,8.3,DeepTech Ventures +AI11819,ML Ops Engineer,101696,GBP,76272,SE,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Azure, PyTorch, Statistics, Mathematics",Associate,6,Telecommunications,2024-04-08,2024-06-15,766,7.1,Autonomous Tech +AI11820,Data Analyst,64069,EUR,54459,MI,PT,Austria,S,Austria,50,"Docker, NLP, Mathematics, Data Visualization",Bachelor,3,Energy,2024-02-28,2024-03-14,748,5.4,TechCorp Inc +AI11821,AI Product Manager,111264,USD,111264,SE,PT,South Korea,M,South Korea,100,"Data Visualization, Linux, SQL, R, Deep Learning",PhD,6,Media,2024-09-16,2024-10-28,2399,8.8,Smart Analytics +AI11822,Principal Data Scientist,109807,USD,109807,MI,PT,Denmark,M,Denmark,50,"Python, Spark, Deep Learning",Associate,4,Telecommunications,2024-10-04,2024-11-24,1800,7.9,Cloud AI Solutions +AI11823,AI Research Scientist,92835,EUR,78910,MI,CT,Netherlands,M,Netherlands,100,"Spark, Computer Vision, PyTorch, Tableau",Associate,3,Retail,2025-02-04,2025-03-07,2441,6.1,Neural Networks Co +AI11824,AI Product Manager,203369,EUR,172864,EX,CT,France,M,France,0,"PyTorch, Docker, Deep Learning",Bachelor,13,Retail,2024-09-09,2024-10-29,1041,7.4,Future Systems +AI11825,Head of AI,177370,USD,177370,EX,CT,Israel,S,Israel,100,"Git, AWS, Python, TensorFlow",Master,17,Telecommunications,2024-10-29,2024-12-16,1070,9.3,Quantum Computing Inc +AI11826,AI Software Engineer,244805,CHF,220325,EX,PT,Switzerland,L,Switzerland,100,"Docker, Python, Data Visualization, TensorFlow",PhD,18,Retail,2024-05-25,2024-07-11,1889,8.5,Algorithmic Solutions +AI11827,AI Product Manager,35462,USD,35462,MI,FT,India,L,India,100,"Tableau, AWS, Mathematics, Linux",Bachelor,3,Healthcare,2024-11-22,2024-12-07,1136,9.7,Future Systems +AI11828,Data Scientist,68404,CAD,85505,EN,FL,Canada,L,Romania,100,"Azure, Scala, SQL, PyTorch, Spark",Associate,0,Real Estate,2024-07-18,2024-09-20,2166,6.5,Cognitive Computing +AI11829,Autonomous Systems Engineer,128996,AUD,174145,SE,FT,Australia,L,Ukraine,100,"GCP, Spark, MLOps, NLP, SQL",Bachelor,7,Healthcare,2024-10-08,2024-12-04,1539,5,Machine Intelligence Group +AI11830,Data Analyst,72807,EUR,61886,EN,FT,Austria,M,Austria,100,"Git, R, Scala, Deep Learning, SQL",PhD,0,Energy,2024-03-02,2024-04-10,2177,7.5,Autonomous Tech +AI11831,Deep Learning Engineer,107118,USD,107118,MI,CT,Denmark,M,Denmark,100,"PyTorch, Data Visualization, GCP, TensorFlow, Linux",Bachelor,4,Automotive,2025-04-11,2025-05-01,2040,8.1,Cognitive Computing +AI11832,Principal Data Scientist,27731,USD,27731,MI,FT,India,M,India,0,"Python, Linux, TensorFlow",Master,4,Consulting,2024-09-04,2024-10-14,976,8.5,Autonomous Tech +AI11833,AI Research Scientist,74228,USD,74228,EN,PT,Norway,M,Norway,100,"Mathematics, Kubernetes, R, Spark, Scala",PhD,0,Automotive,2025-03-29,2025-05-21,2187,9.4,Digital Transformation LLC +AI11834,AI Consultant,77712,USD,77712,EN,FL,Sweden,M,Sweden,0,"Hadoop, PyTorch, Git, Computer Vision",Associate,1,Manufacturing,2024-02-25,2024-05-01,826,6.1,AI Innovations +AI11835,AI Specialist,94668,USD,94668,EX,PT,China,S,China,50,"SQL, NLP, Kubernetes, PyTorch, GCP",PhD,19,Consulting,2024-03-18,2024-04-22,1984,5.4,Cloud AI Solutions +AI11836,AI Architect,212705,USD,212705,EX,FT,South Korea,L,Luxembourg,100,"R, GCP, Tableau",Master,16,Manufacturing,2024-01-15,2024-03-28,2206,6.1,Quantum Computing Inc +AI11837,AI Research Scientist,200761,CHF,180685,EX,PT,Switzerland,S,Switzerland,50,"Kubernetes, SQL, PyTorch, R",Master,11,Real Estate,2024-05-02,2024-06-07,1090,7.1,DeepTech Ventures +AI11838,Machine Learning Engineer,85039,AUD,114803,MI,CT,Australia,M,Australia,100,"Statistics, Tableau, MLOps, Java",Bachelor,2,Manufacturing,2024-08-10,2024-09-22,1756,9.5,Predictive Systems +AI11839,AI Product Manager,62080,USD,62080,EX,CT,India,L,India,50,"Scala, Git, Tableau, Kubernetes, Azure",Bachelor,12,Real Estate,2024-10-03,2024-10-30,987,5.1,Cognitive Computing +AI11840,AI Architect,196292,USD,196292,EX,CT,Sweden,M,Argentina,100,"R, SQL, Deep Learning",Associate,18,Education,2024-03-22,2024-04-29,1280,9.4,Quantum Computing Inc +AI11841,AI Specialist,158220,USD,158220,EX,CT,Sweden,M,Sweden,0,"SQL, TensorFlow, Deep Learning",PhD,19,Gaming,2024-03-13,2024-04-13,1358,7.8,Cognitive Computing +AI11842,AI Architect,29068,USD,29068,MI,FT,India,M,Indonesia,100,"Computer Vision, Hadoop, Linux",Master,4,Gaming,2024-09-14,2024-10-28,913,7.7,DataVision Ltd +AI11843,Data Scientist,61344,GBP,46008,EN,CT,United Kingdom,M,France,0,"TensorFlow, Java, Mathematics, GCP",PhD,1,Transportation,2024-06-15,2024-08-16,1521,7.4,Smart Analytics +AI11844,AI Architect,192580,CHF,173322,SE,FL,Switzerland,M,Switzerland,50,"TensorFlow, NLP, Linux",PhD,5,Technology,2024-01-20,2024-02-12,1743,9.7,Predictive Systems +AI11845,Data Engineer,69295,SGD,90084,EN,PT,Singapore,L,Singapore,100,"SQL, GCP, Computer Vision",Master,0,Retail,2024-09-16,2024-11-18,2296,8.5,TechCorp Inc +AI11846,Computer Vision Engineer,132554,EUR,112671,SE,CT,France,M,France,50,"Kubernetes, Scala, Computer Vision, Java, Docker",Associate,7,Real Estate,2024-05-10,2024-07-04,826,8.8,Quantum Computing Inc +AI11847,AI Consultant,172103,EUR,146288,EX,FL,France,S,Czech Republic,0,"R, SQL, Statistics, Azure, Computer Vision",Master,14,Manufacturing,2024-02-10,2024-03-01,1648,7.4,DeepTech Ventures +AI11848,AI Specialist,113947,GBP,85460,SE,FT,United Kingdom,M,United Kingdom,50,"Git, Deep Learning, R",Bachelor,8,Energy,2025-04-13,2025-05-21,1447,9.4,Cognitive Computing +AI11849,AI Consultant,38972,USD,38972,MI,CT,China,M,China,50,"Tableau, Hadoop, Deep Learning, Spark, GCP",Associate,2,Retail,2024-07-28,2024-08-19,2480,9.4,Future Systems +AI11850,Robotics Engineer,129198,EUR,109818,SE,PT,Austria,L,Canada,100,"SQL, Git, NLP, Python, Kubernetes",Associate,9,Healthcare,2024-11-20,2025-01-20,2336,7.3,DataVision Ltd +AI11851,Machine Learning Researcher,85968,USD,85968,EN,FL,Sweden,L,Sweden,0,"R, Azure, NLP, SQL, Data Visualization",Bachelor,1,Government,2024-03-21,2024-04-10,2330,5.2,Cognitive Computing +AI11852,AI Specialist,89602,USD,89602,EN,PT,Denmark,M,Portugal,50,"Computer Vision, Java, Python, Scala",PhD,1,Finance,2024-11-17,2025-01-06,2474,5.5,Digital Transformation LLC +AI11853,AI Software Engineer,75324,USD,75324,EN,PT,United States,S,United States,50,"GCP, Scala, Data Visualization, Spark",PhD,1,Real Estate,2025-02-06,2025-02-26,830,9.3,AI Innovations +AI11854,AI Consultant,89924,USD,89924,MI,CT,Finland,S,Finland,0,"Azure, Docker, Deep Learning",Master,3,Media,2024-11-17,2025-01-10,844,9.8,Digital Transformation LLC +AI11855,Machine Learning Engineer,65329,USD,65329,EN,PT,South Korea,M,Switzerland,100,"R, Hadoop, Spark, Mathematics, Computer Vision",Bachelor,0,Healthcare,2024-04-30,2024-05-28,547,5.2,DataVision Ltd +AI11856,AI Software Engineer,93470,AUD,126185,MI,CT,Australia,M,Australia,0,"MLOps, R, Tableau",Master,4,Media,2024-11-29,2024-12-22,1805,8.1,Digital Transformation LLC +AI11857,Research Scientist,95936,JPY,10552960,EN,PT,Japan,L,Japan,100,"Git, Python, MLOps",Master,0,Finance,2024-08-17,2024-10-26,1297,8.2,Predictive Systems +AI11858,Machine Learning Researcher,112418,SGD,146143,MI,PT,Singapore,M,Singapore,0,"Linux, R, Hadoop, Statistics, MLOps",Associate,4,Consulting,2024-08-31,2024-09-30,1676,9.9,AI Innovations +AI11859,AI Architect,210662,USD,210662,EX,CT,Sweden,S,Sweden,0,"SQL, Hadoop, TensorFlow, Spark",Bachelor,16,Gaming,2024-09-10,2024-10-07,1986,7.4,DataVision Ltd +AI11860,Machine Learning Engineer,55827,USD,55827,EN,FT,South Korea,M,South Korea,0,"SQL, Docker, MLOps, Azure",Associate,1,Real Estate,2024-07-09,2024-08-20,2250,5.2,Neural Networks Co +AI11861,Deep Learning Engineer,174827,USD,174827,SE,PT,Denmark,M,Denmark,50,"Computer Vision, SQL, Kubernetes, Mathematics",Bachelor,5,Healthcare,2024-07-18,2024-09-25,1268,5.9,Machine Intelligence Group +AI11862,Head of AI,222968,USD,222968,EX,FT,South Korea,L,Nigeria,100,"PyTorch, Hadoop, TensorFlow",PhD,17,Energy,2024-10-30,2024-12-18,1644,6,Autonomous Tech +AI11863,Data Analyst,250630,USD,250630,EX,FL,Denmark,L,Estonia,50,"Python, Docker, MLOps, Azure",Bachelor,15,Telecommunications,2024-07-29,2024-09-02,606,6.1,Cloud AI Solutions +AI11864,AI Product Manager,188795,CHF,169916,SE,FT,Switzerland,M,Switzerland,0,"R, Docker, Tableau, Azure, PyTorch",Associate,5,Technology,2025-01-24,2025-02-22,1357,7.6,AI Innovations +AI11865,Data Scientist,116184,EUR,98756,SE,FT,France,S,Italy,50,"Linux, Java, Scala, Kubernetes, MLOps",PhD,5,Automotive,2025-02-15,2025-03-26,2428,5.5,Digital Transformation LLC +AI11866,Deep Learning Engineer,85463,USD,85463,EN,FL,Israel,L,Switzerland,100,"Deep Learning, MLOps, Statistics, NLP",Associate,1,Government,2024-04-16,2024-05-04,2237,6.5,Smart Analytics +AI11867,Robotics Engineer,62097,EUR,52782,EN,PT,Netherlands,S,Netherlands,0,"Hadoop, Kubernetes, Python",Associate,1,Energy,2024-11-30,2025-02-04,1363,9.3,Cognitive Computing +AI11868,Data Scientist,77625,USD,77625,EN,FL,Israel,L,Israel,50,"AWS, Kubernetes, PyTorch, Docker",Bachelor,1,Technology,2025-01-14,2025-03-07,1422,5.7,Digital Transformation LLC +AI11869,Data Engineer,89334,JPY,9826740,MI,CT,Japan,M,Canada,100,"Linux, GCP, Statistics, AWS, Hadoop",Bachelor,2,Manufacturing,2024-09-21,2024-10-19,733,9.5,Neural Networks Co +AI11870,Deep Learning Engineer,115065,EUR,97805,SE,CT,Austria,M,Austria,0,"SQL, Git, Tableau, Linux",Master,7,Consulting,2024-02-05,2024-03-02,1057,6.6,Quantum Computing Inc +AI11871,NLP Engineer,29565,USD,29565,MI,CT,India,M,India,100,"Python, Linux, Tableau, TensorFlow",PhD,2,Manufacturing,2025-03-21,2025-05-10,2038,8.4,Neural Networks Co +AI11872,Autonomous Systems Engineer,151856,USD,151856,SE,FL,Denmark,M,Denmark,0,"PyTorch, Docker, Tableau, Spark, GCP",PhD,6,Real Estate,2024-01-03,2024-03-04,795,6.1,Algorithmic Solutions +AI11873,Principal Data Scientist,59832,USD,59832,EN,FL,Israel,L,Australia,100,"Git, TensorFlow, SQL, NLP",Associate,1,Government,2024-03-07,2024-04-25,2026,9.5,Cloud AI Solutions +AI11874,Data Scientist,100061,USD,100061,SE,FT,Finland,S,Finland,0,"Docker, Python, TensorFlow, Tableau, Kubernetes",Bachelor,7,Gaming,2024-09-16,2024-11-15,2469,8.8,Autonomous Tech +AI11875,Computer Vision Engineer,55729,EUR,47370,EN,FL,France,S,France,50,"Docker, R, GCP, SQL",PhD,0,Education,2024-02-06,2024-02-29,1845,7.7,Quantum Computing Inc +AI11876,Machine Learning Researcher,47262,EUR,40173,EN,FT,France,S,France,50,"Python, TensorFlow, MLOps, Deep Learning, Java",Master,1,Education,2025-03-20,2025-05-04,1036,9,AI Innovations +AI11877,AI Product Manager,126583,USD,126583,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Linux, Java",Master,19,Automotive,2025-04-04,2025-06-11,1998,8.7,Autonomous Tech +AI11878,NLP Engineer,46601,EUR,39611,EN,PT,France,S,France,50,"Scala, Statistics, Linux, TensorFlow, MLOps",Master,0,Consulting,2024-05-26,2024-06-17,1646,7.1,AI Innovations +AI11879,AI Research Scientist,53772,GBP,40329,EN,PT,United Kingdom,S,United Kingdom,100,"Tableau, Git, Computer Vision",PhD,1,Technology,2025-03-20,2025-05-25,1581,5.1,Smart Analytics +AI11880,Data Scientist,203974,USD,203974,EX,FL,Ireland,L,Ireland,100,"Git, Python, Scala",Bachelor,17,Consulting,2024-09-04,2024-10-29,2278,7.8,AI Innovations +AI11881,AI Product Manager,23558,USD,23558,EN,FT,China,S,China,100,"Linux, Scala, Mathematics, Computer Vision",PhD,0,Gaming,2025-01-23,2025-04-01,1696,9.1,Smart Analytics +AI11882,Head of AI,195265,USD,195265,EX,FT,Finland,M,Finland,0,"Kubernetes, PyTorch, Scala, Git, AWS",Bachelor,12,Media,2025-03-21,2025-04-29,2425,9.6,Quantum Computing Inc +AI11883,AI Consultant,125170,USD,125170,MI,PT,United States,L,United States,0,"Tableau, Hadoop, PyTorch",Master,2,Energy,2025-03-05,2025-04-29,574,5.3,Autonomous Tech +AI11884,Machine Learning Researcher,154524,USD,154524,MI,PT,Norway,L,Norway,0,"Python, Scala, GCP, Computer Vision, AWS",Master,4,Gaming,2024-12-19,2025-02-23,1061,6.8,Future Systems +AI11885,Principal Data Scientist,78129,EUR,66410,MI,FT,Germany,M,Switzerland,100,"Mathematics, TensorFlow, Kubernetes",Master,4,Education,2024-12-15,2025-02-02,1911,6.1,AI Innovations +AI11886,AI Specialist,82474,USD,82474,EN,FL,Denmark,L,Denmark,100,"AWS, Linux, Tableau",Master,0,Government,2024-10-31,2024-11-29,1015,6.7,Digital Transformation LLC +AI11887,Data Analyst,60195,USD,60195,EN,CT,Ireland,S,Ireland,50,"Hadoop, NLP, Scala, Azure, Spark",Associate,0,Manufacturing,2025-03-11,2025-04-08,535,7.4,TechCorp Inc +AI11888,Computer Vision Engineer,85391,JPY,9393010,EN,FL,Japan,M,Japan,50,"Scala, Python, Mathematics, GCP",Master,0,Consulting,2025-02-05,2025-02-24,2183,8.4,DeepTech Ventures +AI11889,AI Product Manager,138187,GBP,103640,SE,PT,United Kingdom,M,United Kingdom,0,"NLP, PyTorch, SQL",Associate,7,Government,2025-04-01,2025-05-16,1041,7.6,Future Systems +AI11890,AI Research Scientist,90522,USD,90522,MI,CT,United States,S,Brazil,50,"SQL, Docker, PyTorch",PhD,4,Consulting,2025-02-18,2025-04-13,1067,8.7,TechCorp Inc +AI11891,Data Scientist,118016,EUR,100314,SE,FL,France,S,France,100,"Deep Learning, Spark, Python, Computer Vision, Linux",Bachelor,5,Media,2024-05-20,2024-06-20,2461,7.7,Quantum Computing Inc +AI11892,Principal Data Scientist,45677,USD,45677,MI,FT,China,L,China,50,"TensorFlow, Statistics, Git, MLOps",Master,2,Real Estate,2024-04-06,2024-05-06,1862,7.3,DataVision Ltd +AI11893,AI Specialist,80735,USD,80735,MI,PT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, SQL, MLOps",Associate,3,Energy,2024-10-09,2024-11-16,2497,6.8,Smart Analytics +AI11894,Data Engineer,174749,EUR,148537,SE,FT,Netherlands,L,Nigeria,50,"Kubernetes, SQL, Python",Master,6,Media,2024-01-28,2024-03-02,2235,5.5,DataVision Ltd +AI11895,Autonomous Systems Engineer,153986,USD,153986,EX,FL,South Korea,S,South Korea,50,"GCP, Python, Data Visualization",Master,19,Government,2024-07-05,2024-09-07,1093,6.4,Digital Transformation LLC +AI11896,AI Consultant,239879,GBP,179909,EX,PT,United Kingdom,S,United Kingdom,100,"Java, TensorFlow, Docker, SQL, AWS",Associate,10,Gaming,2025-01-25,2025-02-15,814,7.5,Algorithmic Solutions +AI11897,AI Product Manager,113202,JPY,12452220,MI,PT,Japan,L,Japan,0,"NLP, Spark, Python, TensorFlow, Git",Bachelor,3,Government,2024-05-24,2024-06-15,618,5.6,Quantum Computing Inc +AI11898,Deep Learning Engineer,176289,USD,176289,EX,FT,Sweden,M,Sweden,0,"Data Visualization, GCP, Linux",Associate,19,Real Estate,2024-08-14,2024-10-16,1171,7.7,Quantum Computing Inc +AI11899,AI Specialist,74877,CAD,93596,EN,FL,Canada,M,Romania,100,"Hadoop, Data Visualization, AWS, Java",Master,0,Transportation,2024-04-05,2024-05-19,1958,5.7,Autonomous Tech +AI11900,Deep Learning Engineer,121054,USD,121054,SE,PT,Israel,M,South Africa,50,"GCP, AWS, Mathematics, Tableau",Bachelor,9,Manufacturing,2024-11-17,2025-01-18,2146,7.1,Predictive Systems +AI11901,Head of AI,121862,CAD,152328,SE,FL,Canada,M,Chile,0,"Git, GCP, Spark, R, AWS",Bachelor,8,Finance,2025-04-11,2025-05-05,2480,8.7,Neural Networks Co +AI11902,AI Product Manager,68676,USD,68676,MI,PT,South Korea,L,South Korea,50,"Tableau, Kubernetes, Python",PhD,3,Manufacturing,2024-04-05,2024-05-28,951,7.4,Cognitive Computing +AI11903,AI Specialist,140355,CAD,175444,SE,CT,Canada,L,Canada,100,"Spark, SQL, Computer Vision",Bachelor,7,Automotive,2024-06-20,2024-07-21,738,5.6,Neural Networks Co +AI11904,Data Scientist,107343,EUR,91242,SE,CT,Austria,S,United States,100,"Linux, R, SQL, Spark, GCP",Master,6,Retail,2025-01-17,2025-02-24,1393,5.6,Advanced Robotics +AI11905,Data Analyst,124289,USD,124289,SE,PT,Ireland,M,Ireland,100,"Statistics, Tableau, SQL, Data Visualization, Python",Master,6,Telecommunications,2024-01-19,2024-03-30,1647,7.1,Cloud AI Solutions +AI11906,Deep Learning Engineer,111588,USD,111588,MI,FL,Ireland,L,Ireland,50,"Mathematics, TensorFlow, Tableau, Computer Vision",Associate,2,Consulting,2024-04-17,2024-06-23,2381,5.5,Advanced Robotics +AI11907,NLP Engineer,140602,AUD,189813,SE,PT,Australia,M,Australia,50,"SQL, Azure, AWS",Master,7,Technology,2024-05-08,2024-07-12,583,6.9,Autonomous Tech +AI11908,Deep Learning Engineer,220576,USD,220576,SE,PT,Norway,L,Norway,0,"Deep Learning, Data Visualization, Java, GCP",Master,6,Real Estate,2024-09-12,2024-10-13,1736,5.6,Neural Networks Co +AI11909,Data Scientist,63791,USD,63791,EX,FT,India,L,India,50,"Java, Spark, GCP, Tableau, Computer Vision",PhD,16,Retail,2025-01-06,2025-02-17,1610,9.6,Predictive Systems +AI11910,Robotics Engineer,115544,EUR,98212,SE,FT,Austria,S,Italy,100,"PyTorch, TensorFlow, Computer Vision, GCP, Spark",PhD,5,Gaming,2024-11-21,2024-12-28,2140,6.8,Digital Transformation LLC +AI11911,Computer Vision Engineer,141470,USD,141470,SE,FL,Finland,L,Canada,50,"Java, Python, Kubernetes",Bachelor,7,Transportation,2024-04-17,2024-05-11,1095,5.5,Machine Intelligence Group +AI11912,Robotics Engineer,119546,USD,119546,SE,FL,Sweden,M,Switzerland,100,"Kubernetes, AWS, Computer Vision",Associate,8,Energy,2024-09-13,2024-11-23,1690,7.2,TechCorp Inc +AI11913,Robotics Engineer,70709,SGD,91922,EN,PT,Singapore,L,Singapore,0,"Spark, Linux, Scala, Docker",PhD,0,Technology,2024-05-01,2024-06-11,984,8.9,Cognitive Computing +AI11914,Autonomous Systems Engineer,139969,AUD,188958,SE,FT,Australia,M,Australia,100,"Python, Spark, TensorFlow, MLOps, AWS",Bachelor,7,Gaming,2025-03-01,2025-03-18,1633,6,Machine Intelligence Group +AI11915,Computer Vision Engineer,249239,USD,249239,EX,CT,United States,M,United States,100,"Data Visualization, AWS, TensorFlow",Bachelor,19,Healthcare,2024-11-12,2024-12-16,1154,6.6,DataVision Ltd +AI11916,Data Scientist,72005,EUR,61204,EN,FL,France,M,France,0,"PyTorch, Scala, Data Visualization, Statistics, AWS",Master,1,Real Estate,2024-05-07,2024-05-25,1077,7.7,Digital Transformation LLC +AI11917,Head of AI,82315,USD,82315,MI,FL,Finland,M,Finland,0,"Java, Computer Vision, Tableau, Python",PhD,2,Media,2025-01-19,2025-03-24,653,5.4,DataVision Ltd +AI11918,AI Product Manager,172045,USD,172045,SE,PT,Sweden,L,Sweden,100,"GCP, Linux, Deep Learning, Scala, MLOps",Associate,6,Consulting,2024-12-20,2025-02-20,1852,8.2,Quantum Computing Inc +AI11919,Data Engineer,227310,EUR,193214,EX,CT,Germany,M,Germany,100,"Data Visualization, Python, R",PhD,19,Technology,2025-02-23,2025-04-07,560,9,AI Innovations +AI11920,Head of AI,84752,GBP,63564,MI,FL,United Kingdom,M,United Kingdom,50,"Azure, Tableau, Linux",Bachelor,3,Energy,2024-04-16,2024-06-06,789,5.7,Autonomous Tech +AI11921,Principal Data Scientist,141732,USD,141732,SE,FL,Finland,L,Brazil,50,"MLOps, Scala, TensorFlow, Deep Learning, GCP",PhD,7,Transportation,2024-12-08,2025-01-04,734,9.6,Autonomous Tech +AI11922,AI Architect,169211,USD,169211,SE,PT,Denmark,S,Argentina,100,"Java, Python, MLOps, TensorFlow, Kubernetes",Bachelor,8,Transportation,2025-03-07,2025-04-21,1516,9.5,Machine Intelligence Group +AI11923,Research Scientist,247914,GBP,185936,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, Python, GCP, R, Hadoop",Master,17,Automotive,2024-02-19,2024-03-13,849,7.8,TechCorp Inc +AI11924,Deep Learning Engineer,66536,CAD,83170,EN,FT,Canada,S,Malaysia,0,"PyTorch, Azure, MLOps",PhD,1,Energy,2024-05-29,2024-06-13,1642,5.4,DeepTech Ventures +AI11925,Robotics Engineer,133785,CHF,120407,MI,FL,Switzerland,M,Switzerland,50,"Spark, MLOps, GCP, Docker, Java",PhD,4,Finance,2025-02-01,2025-04-14,1364,5.8,Digital Transformation LLC +AI11926,Data Analyst,65022,GBP,48767,EN,CT,United Kingdom,L,United Kingdom,100,"Spark, GCP, SQL, NLP",Master,1,Real Estate,2025-04-21,2025-05-22,1446,6.4,Cognitive Computing +AI11927,NLP Engineer,247285,USD,247285,EX,FL,Norway,M,Norway,50,"NLP, SQL, Azure",Master,11,Government,2025-01-11,2025-03-04,767,9.8,Neural Networks Co +AI11928,NLP Engineer,51541,USD,51541,EN,FL,Finland,M,Finland,0,"Java, Kubernetes, Data Visualization, Docker",PhD,0,Manufacturing,2024-01-27,2024-02-26,1836,8.4,Digital Transformation LLC +AI11929,AI Consultant,186164,GBP,139623,SE,PT,United Kingdom,L,New Zealand,0,"Linux, Scala, Mathematics, R, Azure",Master,6,Telecommunications,2024-09-01,2024-11-09,2042,7.3,Quantum Computing Inc +AI11930,NLP Engineer,80116,USD,80116,MI,CT,Ireland,S,Ireland,0,"Python, Hadoop, GCP, TensorFlow",PhD,4,Media,2025-01-02,2025-01-21,1716,5.6,Neural Networks Co +AI11931,AI Consultant,62190,EUR,52862,EN,CT,Austria,M,Netherlands,100,"Hadoop, Git, NLP, TensorFlow",PhD,0,Gaming,2024-04-08,2024-04-25,1587,5.8,Cognitive Computing +AI11932,Principal Data Scientist,99982,USD,99982,MI,PT,Sweden,M,Italy,50,"Git, Azure, Kubernetes",Bachelor,3,Finance,2024-03-18,2024-05-28,2079,6.7,Smart Analytics +AI11933,AI Architect,126992,CAD,158740,SE,PT,Canada,L,Austria,100,"Git, Scala, Data Visualization, Python",PhD,5,Consulting,2024-11-05,2024-12-12,1638,6.9,Quantum Computing Inc +AI11934,NLP Engineer,283236,USD,283236,EX,FL,Denmark,M,Denmark,0,"Mathematics, Linux, Git",PhD,12,Real Estate,2024-10-07,2024-11-14,1479,8.2,AI Innovations +AI11935,Machine Learning Engineer,211425,CHF,190283,SE,PT,Switzerland,L,Singapore,100,"Linux, Data Visualization, Hadoop",PhD,8,Manufacturing,2024-07-10,2024-09-08,2048,7.7,Cloud AI Solutions +AI11936,Data Scientist,44730,CAD,55913,EN,PT,Canada,S,Israel,0,"Linux, GCP, R, Hadoop, SQL",Associate,0,Retail,2024-10-24,2024-12-23,1274,8.7,Digital Transformation LLC +AI11937,Data Analyst,34838,USD,34838,MI,PT,China,S,China,50,"Scala, AWS, Docker",Associate,4,Finance,2024-02-18,2024-03-21,2184,6.9,Smart Analytics +AI11938,AI Software Engineer,225196,USD,225196,EX,FL,United States,S,United States,0,"Java, R, Hadoop, Kubernetes, PyTorch",PhD,12,Transportation,2024-03-07,2024-04-13,1541,7.1,Neural Networks Co +AI11939,Head of AI,122390,USD,122390,MI,FT,United States,M,United States,0,"PyTorch, TensorFlow, Computer Vision, Docker, Mathematics",Associate,2,Media,2024-09-02,2024-10-09,1198,6.3,TechCorp Inc +AI11940,Deep Learning Engineer,134314,USD,134314,SE,FL,Finland,M,Finland,100,"AWS, SQL, PyTorch",Master,9,Government,2024-05-03,2024-05-19,2257,9.4,Machine Intelligence Group +AI11941,Autonomous Systems Engineer,63509,USD,63509,EN,PT,Israel,M,Israel,100,"Hadoop, Deep Learning, Scala, Python",Master,1,Transportation,2024-08-10,2024-09-13,1368,6.5,Algorithmic Solutions +AI11942,AI Software Engineer,179124,JPY,19703640,SE,CT,Japan,L,Japan,50,"Spark, SQL, R, Scala",Bachelor,6,Gaming,2024-10-09,2024-12-13,2235,7.7,DataVision Ltd +AI11943,AI Architect,128394,GBP,96296,MI,PT,United Kingdom,L,Poland,100,"SQL, Tableau, Mathematics, Data Visualization",PhD,3,Manufacturing,2024-12-16,2025-02-07,1582,6.4,TechCorp Inc +AI11944,Deep Learning Engineer,126623,CHF,113961,MI,FL,Switzerland,L,Brazil,0,"SQL, Scala, MLOps, R, Git",PhD,3,Energy,2024-05-23,2024-07-18,2276,6.4,Algorithmic Solutions +AI11945,AI Architect,113817,EUR,96744,SE,PT,Germany,M,Germany,50,"TensorFlow, Docker, Kubernetes",Master,8,Finance,2024-02-03,2024-02-24,1339,8,Quantum Computing Inc +AI11946,AI Architect,139320,USD,139320,EX,CT,South Korea,L,South Korea,100,"MLOps, Scala, Linux, Deep Learning, Computer Vision",Master,16,Technology,2025-04-05,2025-06-13,2440,7.6,Advanced Robotics +AI11947,AI Product Manager,123195,EUR,104716,SE,FL,Germany,S,Germany,100,"Python, MLOps, Tableau, TensorFlow, GCP",Master,6,Transportation,2024-01-02,2024-03-03,1983,8.6,Quantum Computing Inc +AI11948,AI Architect,59966,CAD,74958,EN,PT,Canada,M,Ireland,0,"Computer Vision, NLP, GCP, Linux, Azure",PhD,0,Finance,2024-01-24,2024-02-14,1953,5.8,Digital Transformation LLC +AI11949,AI Research Scientist,32241,USD,32241,EN,CT,India,L,India,100,"Kubernetes, Data Visualization, Azure",Bachelor,1,Energy,2024-12-07,2025-02-02,1441,6.2,Cognitive Computing +AI11950,Autonomous Systems Engineer,125879,CAD,157349,EX,FT,Canada,S,Canada,0,"Git, GCP, MLOps",Bachelor,13,Retail,2024-04-20,2024-05-25,1270,8.7,Quantum Computing Inc +AI11951,Head of AI,63170,USD,63170,MI,FL,Israel,S,Israel,0,"SQL, PyTorch, Azure, MLOps, Git",Bachelor,2,Media,2025-03-23,2025-04-21,1528,5.1,Digital Transformation LLC +AI11952,NLP Engineer,155126,JPY,17063860,EX,CT,Japan,M,New Zealand,50,"Python, TensorFlow, NLP",Associate,16,Real Estate,2024-09-30,2024-12-04,2446,10,Neural Networks Co +AI11953,AI Architect,86565,CAD,108206,MI,CT,Canada,M,Canada,100,"SQL, Python, Spark, Scala",Bachelor,2,Manufacturing,2024-03-29,2024-05-19,1589,6.7,Quantum Computing Inc +AI11954,Principal Data Scientist,103951,EUR,88358,MI,CT,Germany,L,Germany,100,"TensorFlow, Data Visualization, Python, Mathematics, Kubernetes",PhD,4,Retail,2024-04-23,2024-05-07,955,9.4,Algorithmic Solutions +AI11955,Data Engineer,121572,USD,121572,SE,FL,Ireland,L,Ireland,100,"Linux, TensorFlow, Docker",Associate,8,Real Estate,2024-07-01,2024-08-10,1827,8.3,TechCorp Inc +AI11956,Deep Learning Engineer,80289,USD,80289,EN,CT,Denmark,M,Denmark,50,"R, Azure, AWS",Associate,0,Transportation,2024-11-04,2025-01-06,1019,9.5,Smart Analytics +AI11957,Head of AI,142312,USD,142312,SE,FL,United States,L,United States,100,"NLP, Hadoop, Scala, Tableau",Bachelor,9,Media,2024-08-18,2024-10-13,1326,7.4,Future Systems +AI11958,ML Ops Engineer,45228,USD,45228,MI,PT,China,L,China,100,"Deep Learning, Kubernetes, Spark, NLP",Associate,3,Government,2025-01-01,2025-03-10,994,5.3,Algorithmic Solutions +AI11959,AI Architect,105421,SGD,137047,MI,FL,Singapore,M,Singapore,50,"NLP, TensorFlow, Tableau",Associate,3,Transportation,2025-03-20,2025-04-19,1425,7,Cognitive Computing +AI11960,Autonomous Systems Engineer,253979,CHF,228581,EX,FL,Switzerland,M,Thailand,100,"Hadoop, Scala, PyTorch, AWS, Data Visualization",Associate,11,Government,2025-04-18,2025-05-21,1367,7.3,Neural Networks Co +AI11961,Autonomous Systems Engineer,80682,EUR,68580,MI,PT,Netherlands,S,Chile,50,"NLP, Git, Spark, AWS, Hadoop",Bachelor,4,Education,2025-04-09,2025-05-09,1274,6.8,Machine Intelligence Group +AI11962,Machine Learning Engineer,58564,USD,58564,SE,PT,China,L,China,0,"Java, GCP, Deep Learning",Master,5,Energy,2024-08-17,2024-09-08,1669,7.7,Future Systems +AI11963,ML Ops Engineer,165885,EUR,141002,EX,FL,France,M,France,0,"Python, Deep Learning, Data Visualization",PhD,19,Media,2024-08-07,2024-09-19,783,10,Digital Transformation LLC +AI11964,Data Engineer,190838,USD,190838,SE,PT,Denmark,M,Austria,100,"Deep Learning, AWS, Statistics",Bachelor,6,Telecommunications,2024-02-14,2024-04-06,2414,9.6,Predictive Systems +AI11965,AI Specialist,55369,USD,55369,EX,FL,India,M,India,0,"Docker, GCP, Data Visualization, Mathematics, Tableau",Associate,17,Automotive,2024-01-09,2024-02-27,1164,10,AI Innovations +AI11966,Data Scientist,71105,EUR,60439,EN,FL,Netherlands,L,Netherlands,0,"Spark, PyTorch, Mathematics",Master,0,Telecommunications,2024-03-25,2024-05-30,1018,7.5,Quantum Computing Inc +AI11967,Deep Learning Engineer,75264,USD,75264,EN,FL,Sweden,M,Sweden,0,"GCP, Tableau, Python, Data Visualization, TensorFlow",Associate,0,Retail,2024-07-03,2024-07-22,1393,6.1,Smart Analytics +AI11968,Autonomous Systems Engineer,164799,USD,164799,SE,FT,Norway,M,Norway,100,"Hadoop, Kubernetes, Python, R, SQL",Master,9,Gaming,2024-05-10,2024-06-23,518,6.2,Neural Networks Co +AI11969,Machine Learning Engineer,76924,EUR,65385,MI,FT,Austria,M,Portugal,50,"Spark, Azure, Kubernetes",PhD,3,Telecommunications,2024-11-09,2024-12-18,913,6.5,Cognitive Computing +AI11970,Principal Data Scientist,43350,USD,43350,MI,PT,India,L,Ireland,50,"Git, Azure, Hadoop",Associate,3,Healthcare,2025-04-15,2025-06-19,1003,9.3,Predictive Systems +AI11971,AI Product Manager,61506,EUR,52280,EN,FL,Austria,S,Austria,0,"Kubernetes, Hadoop, PyTorch, Git, Data Visualization",Associate,0,Education,2025-03-18,2025-05-22,1927,6.3,Cognitive Computing +AI11972,AI Architect,102342,AUD,138162,MI,PT,Australia,M,Australia,100,"Python, SQL, Hadoop",PhD,4,Consulting,2024-04-13,2024-05-08,1056,9.6,Digital Transformation LLC +AI11973,AI Product Manager,167315,CHF,150584,SE,CT,Switzerland,L,Switzerland,50,"Scala, Computer Vision, SQL, GCP, MLOps",PhD,8,Transportation,2024-12-07,2025-01-08,1876,6.2,Quantum Computing Inc +AI11974,AI Consultant,128451,EUR,109183,EX,PT,France,M,France,0,"Spark, Python, Statistics, Java, TensorFlow",Master,19,Real Estate,2024-08-06,2024-09-04,2292,9.4,Autonomous Tech +AI11975,Robotics Engineer,71957,GBP,53968,EN,FT,United Kingdom,S,United Kingdom,0,"Scala, GCP, Computer Vision, Docker",Master,0,Healthcare,2024-04-15,2024-05-17,529,6.3,DataVision Ltd +AI11976,ML Ops Engineer,117836,AUD,159079,SE,PT,Australia,L,Argentina,50,"Python, PyTorch, Git, Computer Vision, Statistics",PhD,6,Education,2024-06-29,2024-07-16,2090,5.9,Algorithmic Solutions +AI11977,Data Engineer,121319,SGD,157715,MI,PT,Singapore,L,New Zealand,50,"GCP, Git, Mathematics, Computer Vision, TensorFlow",Bachelor,4,Real Estate,2024-05-16,2024-07-28,1785,8.7,TechCorp Inc +AI11978,Machine Learning Researcher,118151,EUR,100428,EX,FL,France,S,France,100,"TensorFlow, SQL, MLOps",Associate,13,Retail,2025-04-12,2025-06-22,1142,6.1,Cognitive Computing +AI11979,AI Software Engineer,82974,GBP,62231,MI,FL,United Kingdom,S,United Kingdom,0,"Linux, AWS, Deep Learning, Scala",Bachelor,3,Telecommunications,2024-01-09,2024-02-03,662,7.9,Future Systems +AI11980,Data Analyst,91372,USD,91372,EN,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-10-03,2024-10-26,2231,9.5,Predictive Systems +AI11981,AI Product Manager,33654,USD,33654,EN,FL,China,M,China,0,"Spark, SQL, Linux, Hadoop",Associate,0,Healthcare,2025-03-07,2025-05-19,1924,5.9,Neural Networks Co +AI11982,Head of AI,156264,EUR,132824,SE,FL,France,L,South Africa,50,"Kubernetes, SQL, PyTorch, Data Visualization, Computer Vision",PhD,8,Education,2024-11-24,2025-01-21,1009,7.4,Cognitive Computing +AI11983,Data Analyst,84928,CAD,106160,MI,FL,Canada,M,Canada,50,"PyTorch, Spark, Data Visualization, SQL, Docker",Master,4,Technology,2024-11-12,2024-12-15,574,9.6,DataVision Ltd +AI11984,Research Scientist,129254,CAD,161568,SE,PT,Canada,M,Canada,0,"Python, Azure, Statistics, Java, Computer Vision",Master,9,Consulting,2024-12-28,2025-02-11,2081,9.1,Autonomous Tech +AI11985,AI Consultant,206297,USD,206297,EX,CT,Finland,M,Finland,50,"AWS, Spark, Mathematics, Hadoop, GCP",Master,10,Real Estate,2024-06-25,2024-08-25,2117,6.1,Algorithmic Solutions +AI11986,Data Analyst,105092,EUR,89328,MI,CT,Austria,L,Austria,0,"Linux, TensorFlow, Scala, Azure",Master,3,Government,2024-04-25,2024-05-27,2118,6.5,DataVision Ltd +AI11987,Deep Learning Engineer,216314,USD,216314,EX,PT,Denmark,L,Denmark,0,"TensorFlow, Scala, GCP, R, Tableau",PhD,19,Media,2025-03-05,2025-04-18,2302,8.6,Quantum Computing Inc +AI11988,AI Software Engineer,114139,EUR,97018,SE,FT,France,S,France,0,"Java, NLP, Git, Statistics",Master,6,Gaming,2024-11-06,2025-01-18,2402,8.2,DataVision Ltd +AI11989,Autonomous Systems Engineer,253207,GBP,189905,EX,FT,United Kingdom,L,United Kingdom,0,"R, Mathematics, SQL, Java",Bachelor,12,Manufacturing,2024-11-08,2024-12-27,534,9.6,Cloud AI Solutions +AI11990,Data Engineer,117195,CHF,105476,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Docker, NLP, PyTorch",PhD,4,Technology,2024-03-28,2024-04-27,998,5.9,Quantum Computing Inc +AI11991,AI Research Scientist,75215,USD,75215,EN,FT,United States,S,United States,100,"TensorFlow, GCP, Java, Scala, Python",Master,1,Energy,2025-03-13,2025-03-30,2257,8.4,AI Innovations +AI11992,Data Scientist,91308,USD,91308,MI,CT,Ireland,S,Ireland,100,"Azure, Linux, Scala",PhD,2,Telecommunications,2024-05-29,2024-07-03,1125,9.7,Cloud AI Solutions +AI11993,NLP Engineer,101994,USD,101994,MI,FT,United States,L,United States,50,"Python, R, PyTorch, Deep Learning",Master,3,Healthcare,2025-03-09,2025-04-03,1316,7.3,Digital Transformation LLC +AI11994,AI Consultant,63814,SGD,82958,EN,FT,Singapore,M,Singapore,0,"Java, AWS, PyTorch",PhD,1,Gaming,2024-12-23,2025-02-07,1775,5.5,Predictive Systems +AI11995,AI Software Engineer,82096,CHF,73886,EN,FL,Switzerland,M,Switzerland,50,"SQL, Tableau, TensorFlow, Docker",PhD,1,Manufacturing,2024-01-26,2024-03-03,2046,7.2,Future Systems +AI11996,Data Analyst,139446,USD,139446,SE,FL,United States,L,United States,0,"Python, Data Visualization, Kubernetes",Associate,8,Consulting,2025-04-27,2025-05-31,1178,5.2,Cognitive Computing +AI11997,AI Consultant,50489,CAD,63111,EN,PT,Canada,S,Canada,0,"Mathematics, SQL, AWS, Deep Learning",Master,1,Healthcare,2024-07-07,2024-08-30,1144,8.2,Autonomous Tech +AI11998,AI Architect,202463,EUR,172094,EX,CT,France,L,France,50,"R, Statistics, Tableau",Associate,18,Retail,2024-05-07,2024-06-08,2361,5.1,TechCorp Inc +AI11999,AI Consultant,257007,USD,257007,EX,FL,Israel,L,Israel,0,"SQL, Git, Spark",Associate,16,Healthcare,2025-03-29,2025-06-02,2113,8.4,Future Systems +AI12000,Data Analyst,165859,JPY,18244490,SE,FL,Japan,L,Japan,50,"Kubernetes, Mathematics, MLOps",PhD,5,Education,2024-11-04,2025-01-12,1168,5.2,Quantum Computing Inc +AI12001,NLP Engineer,269890,USD,269890,EX,FL,Norway,S,Norway,0,"PyTorch, Python, Git, Kubernetes",Associate,19,Technology,2024-03-09,2024-03-25,1218,5.8,Algorithmic Solutions +AI12002,AI Product Manager,249468,EUR,212048,EX,FL,Netherlands,M,Netherlands,100,"Azure, Tableau, Statistics",PhD,16,Telecommunications,2024-06-14,2024-07-15,534,5,Cognitive Computing +AI12003,Robotics Engineer,146512,SGD,190466,SE,FT,Singapore,M,Singapore,100,"Python, Deep Learning, Computer Vision, Scala",Master,7,Manufacturing,2024-12-29,2025-01-27,728,5.8,Smart Analytics +AI12004,Robotics Engineer,74373,EUR,63217,MI,CT,Austria,S,Austria,0,"NLP, Docker, PyTorch, Azure, Mathematics",Master,4,Gaming,2024-11-09,2025-01-16,1187,8.1,Cognitive Computing +AI12005,AI Consultant,191280,USD,191280,EX,CT,Israel,M,Ukraine,100,"SQL, R, MLOps, Docker",Associate,18,Gaming,2024-03-28,2024-05-16,789,5.7,Algorithmic Solutions +AI12006,Machine Learning Engineer,122748,EUR,104336,SE,CT,Germany,M,Germany,100,"Java, R, NLP, Computer Vision, Azure",Bachelor,8,Healthcare,2024-11-22,2025-02-03,1419,5.3,Autonomous Tech +AI12007,Deep Learning Engineer,40909,USD,40909,SE,PT,India,M,India,50,"NLP, Hadoop, MLOps",Associate,7,Government,2024-08-07,2024-09-08,2498,9.3,TechCorp Inc +AI12008,Principal Data Scientist,51031,USD,51031,EX,CT,India,M,India,0,"Kubernetes, Docker, Azure",PhD,12,Telecommunications,2025-01-21,2025-02-12,1890,10,Advanced Robotics +AI12009,Deep Learning Engineer,111269,CHF,100142,MI,PT,Switzerland,M,Switzerland,0,"Java, TensorFlow, Linux",Associate,4,Automotive,2024-09-13,2024-10-07,1949,6.5,Machine Intelligence Group +AI12010,AI Architect,68234,EUR,57999,EN,FT,Austria,L,Switzerland,100,"Scala, Python, Docker, SQL, Statistics",Associate,1,Transportation,2024-12-05,2025-02-01,2202,5.9,Cognitive Computing +AI12011,Deep Learning Engineer,138852,USD,138852,MI,FT,Denmark,L,Romania,50,"Deep Learning, Python, Scala, GCP, SQL",Bachelor,2,Retail,2024-03-29,2024-05-12,2392,8.3,TechCorp Inc +AI12012,AI Research Scientist,112322,USD,112322,SE,PT,Israel,M,Israel,0,"Java, Git, Mathematics, Statistics",Bachelor,8,Government,2024-03-31,2024-04-21,1766,5.1,Autonomous Tech +AI12013,AI Consultant,172547,AUD,232938,EX,PT,Australia,L,Australia,0,"Python, PyTorch, Mathematics, Java, Tableau",Bachelor,19,Energy,2025-01-13,2025-02-03,1606,5.6,TechCorp Inc +AI12014,Machine Learning Engineer,210775,CHF,189698,SE,CT,Switzerland,M,Switzerland,50,"Docker, R, Computer Vision, Hadoop, MLOps",Associate,7,Education,2025-02-25,2025-03-24,891,6.1,Cognitive Computing +AI12015,ML Ops Engineer,42437,USD,42437,SE,CT,India,M,India,0,"Hadoop, R, Statistics, Git, Docker",Master,5,Education,2025-02-20,2025-03-15,1846,7.9,Predictive Systems +AI12016,Research Scientist,75457,USD,75457,MI,FT,South Korea,M,South Korea,0,"Docker, Tableau, Computer Vision, Java, Hadoop",Master,2,Technology,2024-01-16,2024-03-09,510,5.1,Cognitive Computing +AI12017,AI Architect,81055,AUD,109424,MI,FT,Australia,S,Israel,0,"Data Visualization, TensorFlow, Tableau",Associate,3,Manufacturing,2025-03-19,2025-04-30,1842,8.3,Autonomous Tech +AI12018,Data Analyst,158028,GBP,118521,EX,CT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Mathematics, Hadoop, MLOps",Associate,13,Telecommunications,2024-11-20,2025-01-02,2151,6.6,Quantum Computing Inc +AI12019,Computer Vision Engineer,85667,EUR,72817,MI,FT,Austria,L,Austria,100,"Scala, Mathematics, MLOps, Java",Associate,3,Automotive,2025-03-06,2025-04-14,1455,7.1,Neural Networks Co +AI12020,AI Consultant,92565,USD,92565,MI,FL,South Korea,L,South Korea,100,"Mathematics, AWS, MLOps, R, Java",Bachelor,2,Media,2024-02-15,2024-04-03,2106,7.6,Cloud AI Solutions +AI12021,Data Scientist,218585,USD,218585,EX,FL,United States,S,United States,0,"Azure, SQL, Linux",Master,19,Technology,2025-02-21,2025-04-29,1692,7.1,Smart Analytics +AI12022,Machine Learning Engineer,135669,CHF,122102,MI,FT,Switzerland,S,Switzerland,100,"Kubernetes, SQL, Computer Vision, PyTorch",Bachelor,4,Transportation,2024-06-19,2024-07-10,1965,5.8,Autonomous Tech +AI12023,Machine Learning Engineer,161267,SGD,209647,SE,FT,Singapore,M,Canada,50,"Scala, Python, Docker, Kubernetes, Tableau",Associate,5,Consulting,2024-08-07,2024-09-11,1851,5.4,Digital Transformation LLC +AI12024,Machine Learning Researcher,161659,EUR,137410,EX,PT,Austria,L,Austria,100,"Python, AWS, Azure, Deep Learning, R",Associate,12,Finance,2024-01-06,2024-02-24,730,5.1,Digital Transformation LLC +AI12025,ML Ops Engineer,84538,GBP,63404,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Java, Tableau, Statistics",Bachelor,0,Media,2024-02-18,2024-03-04,1481,8.2,Cloud AI Solutions +AI12026,AI Consultant,123396,EUR,104887,SE,CT,Germany,S,Poland,100,"Git, SQL, Kubernetes",Master,7,Finance,2025-03-17,2025-05-03,1628,9.6,Cognitive Computing +AI12027,NLP Engineer,94740,USD,94740,SE,FT,Sweden,S,Sweden,50,"SQL, NLP, Azure, Mathematics, Python",Bachelor,7,Automotive,2024-09-21,2024-11-21,1527,9.1,DataVision Ltd +AI12028,Machine Learning Engineer,237856,USD,237856,EX,PT,Denmark,M,Denmark,100,"Scala, NLP, Java, Data Visualization",Master,11,Technology,2024-10-29,2024-12-31,1067,9.5,Digital Transformation LLC +AI12029,Computer Vision Engineer,144410,USD,144410,EX,PT,South Korea,L,South Korea,100,"Data Visualization, Python, Tableau, Docker, Deep Learning",PhD,11,Technology,2024-08-16,2024-10-08,1659,7.5,TechCorp Inc +AI12030,Autonomous Systems Engineer,62979,EUR,53532,EN,FL,Netherlands,S,Latvia,50,"R, Deep Learning, Tableau",Bachelor,0,Gaming,2024-12-04,2024-12-27,1609,6.9,Smart Analytics +AI12031,AI Consultant,134825,CHF,121343,MI,FL,Switzerland,L,Argentina,50,"PyTorch, Computer Vision, TensorFlow",Master,4,Gaming,2024-01-15,2024-03-22,853,7.2,Machine Intelligence Group +AI12032,Deep Learning Engineer,115226,USD,115226,MI,PT,Ireland,L,Ireland,50,"Docker, Tableau, Statistics, GCP, Deep Learning",Master,4,Media,2024-02-19,2024-03-12,1816,5.4,Smart Analytics +AI12033,AI Consultant,128090,JPY,14089900,MI,FL,Japan,L,Japan,100,"Statistics, Spark, PyTorch, Data Visualization",Master,3,Education,2024-10-11,2024-12-12,2013,5.1,TechCorp Inc +AI12034,Machine Learning Engineer,148729,USD,148729,EX,FT,Sweden,S,Sweden,100,"Data Visualization, Git, PyTorch, Hadoop",Master,11,Media,2024-02-10,2024-03-19,1419,5.6,Smart Analytics +AI12035,AI Research Scientist,42922,USD,42922,MI,FL,China,L,China,100,"Computer Vision, Tableau, GCP, Spark, PyTorch",Bachelor,3,Telecommunications,2024-01-25,2024-03-15,582,6,Algorithmic Solutions +AI12036,Robotics Engineer,97362,USD,97362,EN,CT,Norway,L,Norway,100,"Computer Vision, Data Visualization, MLOps, Tableau, NLP",Associate,0,Healthcare,2024-09-09,2024-09-29,1851,9.7,DeepTech Ventures +AI12037,Machine Learning Researcher,59118,USD,59118,SE,CT,China,M,China,0,"Hadoop, Linux, SQL",Bachelor,7,Consulting,2024-07-02,2024-08-19,871,7.8,Advanced Robotics +AI12038,Computer Vision Engineer,73489,CAD,91861,EN,PT,Canada,M,Israel,50,"AWS, Azure, SQL, PyTorch, NLP",PhD,0,Gaming,2024-01-07,2024-02-24,2056,5.3,Smart Analytics +AI12039,Deep Learning Engineer,111684,CAD,139605,SE,PT,Canada,L,Brazil,50,"Linux, Hadoop, Data Visualization, Kubernetes",PhD,7,Automotive,2024-04-02,2024-05-09,957,7.3,Cloud AI Solutions +AI12040,AI Research Scientist,64479,EUR,54807,EN,FT,France,S,Switzerland,100,"PyTorch, NLP, Deep Learning",PhD,0,Energy,2025-02-25,2025-04-11,1960,5.1,Predictive Systems +AI12041,AI Specialist,175295,USD,175295,SE,CT,United States,M,United States,0,"Hadoop, Tableau, Linux, Scala, Python",Master,8,Technology,2024-09-16,2024-11-24,2420,5.5,Neural Networks Co +AI12042,Deep Learning Engineer,29310,USD,29310,EN,FL,China,L,China,100,"Java, R, NLP, GCP, Tableau",Associate,0,Real Estate,2024-08-06,2024-10-11,1524,7.3,DataVision Ltd +AI12043,Data Engineer,109138,EUR,92767,MI,FL,Germany,M,Canada,50,"Data Visualization, TensorFlow, PyTorch",Bachelor,3,Technology,2024-07-28,2024-09-08,1065,6.9,Future Systems +AI12044,AI Software Engineer,74590,USD,74590,EX,FT,India,L,India,0,"GCP, Java, Linux",Master,11,Manufacturing,2024-10-05,2024-12-16,1788,8.5,Neural Networks Co +AI12045,AI Consultant,137100,USD,137100,MI,CT,United States,L,Egypt,100,"Tableau, Java, Mathematics, SQL, R",Associate,3,Media,2024-05-21,2024-07-26,1922,7.8,Advanced Robotics +AI12046,AI Research Scientist,169631,USD,169631,EX,FL,Ireland,L,Ireland,50,"SQL, Git, Mathematics, AWS",Master,15,Manufacturing,2024-05-25,2024-07-31,2372,5.4,Digital Transformation LLC +AI12047,Machine Learning Engineer,182100,USD,182100,SE,PT,Norway,L,Norway,0,"TensorFlow, SQL, Java, Computer Vision, Git",Master,6,Retail,2025-03-10,2025-04-11,1534,6.7,Neural Networks Co +AI12048,Robotics Engineer,30598,USD,30598,EN,FT,India,L,India,50,"Data Visualization, Kubernetes, Scala",Associate,0,Consulting,2025-04-20,2025-05-24,707,5.7,Smart Analytics +AI12049,AI Research Scientist,59506,EUR,50580,EN,CT,France,S,France,50,"Computer Vision, NLP, Git, Kubernetes",Bachelor,0,Healthcare,2025-02-24,2025-05-06,2354,5.9,Machine Intelligence Group +AI12050,AI Consultant,176984,CAD,221230,EX,FT,Canada,S,Belgium,50,"Computer Vision, Java, Spark, Statistics, Deep Learning",Bachelor,19,Transportation,2025-04-06,2025-05-11,753,5.1,Machine Intelligence Group +AI12051,Head of AI,76635,USD,76635,MI,FL,Finland,M,Argentina,0,"PyTorch, Python, MLOps",PhD,3,Transportation,2024-10-21,2024-11-09,2223,5.7,Cognitive Computing +AI12052,ML Ops Engineer,142757,USD,142757,SE,CT,Israel,M,Israel,0,"Tableau, NLP, Mathematics",PhD,6,Gaming,2024-10-27,2024-11-28,2278,9.3,Cloud AI Solutions +AI12053,Machine Learning Engineer,157767,AUD,212985,SE,FL,Australia,L,Australia,100,"NLP, Linux, Mathematics",Associate,5,Transportation,2025-01-19,2025-03-14,1357,10,Smart Analytics +AI12054,Data Scientist,155133,JPY,17064630,SE,FL,Japan,M,Japan,50,"MLOps, AWS, R",Associate,8,Education,2024-04-22,2024-05-14,679,8.7,Machine Intelligence Group +AI12055,AI Consultant,103814,USD,103814,MI,FL,Finland,M,Indonesia,50,"Mathematics, AWS, Linux",Associate,3,Finance,2024-02-21,2024-05-04,619,7.6,Smart Analytics +AI12056,NLP Engineer,126742,CHF,114068,MI,PT,Switzerland,M,Switzerland,0,"AWS, Kubernetes, Tableau",Associate,3,Real Estate,2024-09-05,2024-10-20,1227,7.1,Advanced Robotics +AI12057,Machine Learning Engineer,149642,SGD,194535,EX,PT,Singapore,S,Singapore,0,"Python, NLP, SQL, AWS, TensorFlow",Associate,14,Telecommunications,2024-04-11,2024-06-04,599,5.6,Quantum Computing Inc +AI12058,Machine Learning Engineer,119639,GBP,89729,SE,PT,United Kingdom,S,United Kingdom,50,"Tableau, Python, Data Visualization",Bachelor,9,Retail,2025-01-06,2025-02-27,1845,5.5,Quantum Computing Inc +AI12059,AI Architect,94779,CAD,118474,SE,FT,Canada,S,Canada,100,"Scala, Java, Docker, Kubernetes, Data Visualization",Master,7,Media,2024-05-15,2024-07-19,2195,7.1,Advanced Robotics +AI12060,Data Scientist,289132,USD,289132,EX,FT,Norway,S,Norway,100,"TensorFlow, R, NLP",Associate,12,Automotive,2025-01-12,2025-02-15,1149,7.1,Cloud AI Solutions +AI12061,NLP Engineer,81914,EUR,69627,EN,CT,Germany,L,Germany,0,"Linux, Git, SQL",Master,1,Government,2024-08-06,2024-10-05,2272,6.8,DataVision Ltd +AI12062,Autonomous Systems Engineer,143423,EUR,121910,SE,FT,Austria,L,Austria,100,"Python, Java, Deep Learning",Associate,5,Healthcare,2024-03-01,2024-04-12,2001,7.8,Predictive Systems +AI12063,Autonomous Systems Engineer,67712,EUR,57555,EN,CT,Austria,S,Austria,0,"Scala, Linux, Python, AWS, Docker",Bachelor,0,Government,2025-01-18,2025-03-03,2191,5.6,Autonomous Tech +AI12064,Robotics Engineer,119637,GBP,89728,SE,FT,United Kingdom,S,Spain,50,"Python, AWS, Data Visualization",PhD,9,Education,2024-04-23,2024-06-03,787,5.7,Digital Transformation LLC +AI12065,Computer Vision Engineer,95673,EUR,81322,MI,FL,Netherlands,L,South Korea,0,"Tableau, TensorFlow, Python, Linux",PhD,3,Finance,2024-08-30,2024-10-22,1692,6.9,Predictive Systems +AI12066,ML Ops Engineer,206540,EUR,175559,EX,FT,Germany,M,Germany,50,"R, Mathematics, TensorFlow",PhD,11,Media,2025-02-23,2025-04-21,1614,9.8,TechCorp Inc +AI12067,ML Ops Engineer,251443,USD,251443,EX,FT,United States,S,United States,0,"Python, Scala, Docker, Deep Learning, NLP",Associate,10,Automotive,2024-03-08,2024-04-10,620,7.3,DataVision Ltd +AI12068,Data Engineer,116790,CAD,145988,SE,CT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Computer Vision, R",Associate,7,Education,2025-01-18,2025-03-12,1376,5.8,Algorithmic Solutions +AI12069,Computer Vision Engineer,113165,EUR,96190,SE,FT,Germany,S,Portugal,0,"Docker, Python, NLP, Computer Vision",Master,6,Consulting,2024-09-18,2024-11-17,1378,5.3,Digital Transformation LLC +AI12070,AI Research Scientist,117256,CHF,105530,MI,PT,Switzerland,S,Switzerland,100,"AWS, Scala, Computer Vision",PhD,3,Healthcare,2024-06-12,2024-07-14,1082,8.6,Algorithmic Solutions +AI12071,AI Specialist,300778,USD,300778,EX,PT,Norway,M,Norway,0,"Java, Python, GCP, Spark, TensorFlow",Bachelor,12,Technology,2025-02-04,2025-04-13,867,7.6,Predictive Systems +AI12072,Robotics Engineer,141137,SGD,183478,SE,CT,Singapore,L,Singapore,100,"Git, Linux, GCP, Spark",Associate,6,Finance,2024-02-12,2024-03-12,975,6.3,Advanced Robotics +AI12073,Robotics Engineer,46660,USD,46660,MI,CT,China,S,China,0,"AWS, Kubernetes, Docker",Bachelor,4,Consulting,2024-06-19,2024-08-01,2391,8.2,Autonomous Tech +AI12074,Principal Data Scientist,167557,USD,167557,EX,PT,Israel,L,Israel,0,"Azure, SQL, Data Visualization, Deep Learning",Associate,10,Consulting,2024-06-19,2024-08-16,820,5,Digital Transformation LLC +AI12075,Data Engineer,152794,USD,152794,SE,PT,United States,L,United States,100,"Scala, GCP, Docker",Associate,9,Automotive,2024-05-24,2024-06-07,1160,7.9,Neural Networks Co +AI12076,AI Consultant,96217,USD,96217,EX,FL,China,L,Romania,100,"R, SQL, Linux, Docker",Master,18,Healthcare,2024-12-25,2025-02-03,1390,8.2,Digital Transformation LLC +AI12077,AI Architect,93192,CHF,83873,EN,CT,Switzerland,L,Switzerland,50,"Azure, Python, MLOps, Scala, R",Master,0,Education,2024-03-12,2024-04-16,2202,6.2,Autonomous Tech +AI12078,Robotics Engineer,104902,USD,104902,MI,FL,Ireland,L,Ireland,0,"Azure, NLP, Spark, AWS",Master,4,Real Estate,2024-01-09,2024-03-22,1676,9.4,Future Systems +AI12079,AI Software Engineer,77869,USD,77869,MI,PT,South Korea,S,South Korea,100,"GCP, Kubernetes, Tableau, Mathematics, SQL",Associate,4,Finance,2024-05-23,2024-06-22,2322,9.6,DataVision Ltd +AI12080,AI Software Engineer,61860,USD,61860,SE,FT,China,M,China,100,"Kubernetes, Python, Computer Vision, TensorFlow, Linux",Master,6,Transportation,2024-10-05,2024-11-14,2429,6.5,Predictive Systems +AI12081,ML Ops Engineer,149417,USD,149417,SE,FT,Ireland,L,Ireland,0,"Docker, Azure, Linux, GCP, Java",PhD,9,Government,2024-11-12,2024-12-01,1510,7.5,Smart Analytics +AI12082,Head of AI,46702,USD,46702,MI,PT,China,M,China,100,"Kubernetes, R, SQL",Bachelor,2,Media,2024-11-09,2024-12-11,850,9.8,Quantum Computing Inc +AI12083,Data Scientist,65493,USD,65493,EN,PT,Ireland,L,Ireland,50,"Data Visualization, Linux, Mathematics, Python, Computer Vision",Associate,0,Finance,2024-09-02,2024-10-04,1196,9.4,DeepTech Ventures +AI12084,Head of AI,84582,JPY,9304020,MI,FL,Japan,M,Japan,100,"Scala, Spark, TensorFlow, AWS",Associate,4,Government,2024-07-14,2024-08-05,922,9.1,Smart Analytics +AI12085,AI Software Engineer,168343,JPY,18517730,SE,FT,Japan,L,Japan,0,"Git, Scala, Statistics, Mathematics",Associate,7,Education,2024-02-01,2024-04-04,1613,5.8,DataVision Ltd +AI12086,Machine Learning Researcher,122314,USD,122314,EX,FT,South Korea,S,Portugal,50,"R, Java, AWS, Deep Learning",PhD,10,Manufacturing,2025-04-18,2025-06-13,1322,7.9,DeepTech Ventures +AI12087,Autonomous Systems Engineer,177998,USD,177998,SE,CT,United States,L,United States,50,"Deep Learning, Mathematics, NLP",PhD,9,Energy,2024-12-30,2025-03-07,1399,5.9,Digital Transformation LLC +AI12088,Data Analyst,53354,USD,53354,EN,PT,South Korea,S,South Korea,100,"TensorFlow, Python, MLOps",Associate,0,Real Estate,2024-05-15,2024-07-05,1721,7.6,Digital Transformation LLC +AI12089,Head of AI,160257,USD,160257,MI,CT,Norway,L,Italy,100,"PyTorch, AWS, Mathematics, Docker",Master,4,Retail,2024-02-05,2024-03-04,2077,6.3,Future Systems +AI12090,Robotics Engineer,47255,USD,47255,EN,CT,South Korea,S,Poland,100,"R, Docker, Statistics, GCP, Git",Bachelor,1,Media,2024-12-07,2025-02-05,1532,7.3,Advanced Robotics +AI12091,AI Research Scientist,244976,SGD,318469,EX,CT,Singapore,M,Singapore,100,"Java, AWS, MLOps, Computer Vision",Associate,15,Gaming,2024-01-12,2024-02-17,730,6.1,TechCorp Inc +AI12092,Principal Data Scientist,18580,USD,18580,EN,FL,India,S,India,50,"Spark, NLP, Statistics, Linux, Python",Master,0,Real Estate,2025-02-24,2025-03-10,1215,9.6,Digital Transformation LLC +AI12093,Robotics Engineer,92541,GBP,69406,EN,FT,United Kingdom,L,Spain,50,"NLP, GCP, MLOps",Bachelor,1,Finance,2024-09-11,2024-10-10,1775,7.6,Predictive Systems +AI12094,AI Software Engineer,136851,USD,136851,SE,FT,United States,S,United States,100,"R, GCP, Scala",Bachelor,5,Finance,2024-07-29,2024-09-06,1209,5.3,Machine Intelligence Group +AI12095,AI Specialist,74577,GBP,55933,EN,FL,United Kingdom,L,Russia,0,"Git, Spark, Computer Vision, Hadoop, AWS",PhD,1,Education,2025-02-16,2025-03-16,1122,8,Machine Intelligence Group +AI12096,Data Engineer,130249,SGD,169324,MI,PT,Singapore,L,Hungary,0,"Mathematics, Statistics, Tableau, Spark",PhD,3,Consulting,2024-12-27,2025-02-11,1095,9.4,Autonomous Tech +AI12097,Machine Learning Researcher,279715,USD,279715,EX,FL,Denmark,S,Singapore,50,"Docker, SQL, Hadoop, AWS",Master,10,Telecommunications,2024-01-12,2024-01-28,2016,9.8,Digital Transformation LLC +AI12098,Data Analyst,25917,USD,25917,MI,CT,India,S,India,0,"SQL, GCP, MLOps",Associate,2,Retail,2024-05-29,2024-06-28,2476,5.5,Cognitive Computing +AI12099,Deep Learning Engineer,192954,EUR,164011,EX,CT,Netherlands,S,Netherlands,50,"AWS, Kubernetes, Scala",Bachelor,10,Retail,2024-06-16,2024-07-23,1690,6.4,DeepTech Ventures +AI12100,Machine Learning Engineer,151696,USD,151696,EX,FT,United States,S,United States,0,"Python, Computer Vision, Git",Master,19,Education,2024-05-28,2024-06-27,1075,5.5,AI Innovations +AI12101,Computer Vision Engineer,181487,USD,181487,EX,CT,United States,M,United States,100,"Python, TensorFlow, Tableau",PhD,15,Manufacturing,2024-09-05,2024-10-20,729,9.3,Neural Networks Co +AI12102,Machine Learning Engineer,290032,CHF,261029,EX,FL,Switzerland,S,Switzerland,100,"AWS, Spark, R, Statistics, Mathematics",Master,18,Gaming,2024-12-07,2025-01-10,1549,5.5,Algorithmic Solutions +AI12103,Principal Data Scientist,88078,USD,88078,MI,PT,Israel,L,Israel,100,"Kubernetes, TensorFlow, SQL, Spark",Bachelor,2,Automotive,2024-03-31,2024-04-24,1515,8.7,Machine Intelligence Group +AI12104,Robotics Engineer,120897,USD,120897,MI,FT,Ireland,L,Ireland,100,"SQL, Java, PyTorch",PhD,3,Gaming,2024-05-11,2024-06-25,830,5.6,Neural Networks Co +AI12105,Head of AI,99552,GBP,74664,MI,CT,United Kingdom,L,United Kingdom,100,"Azure, TensorFlow, GCP, Kubernetes, Computer Vision",PhD,3,Manufacturing,2024-06-16,2024-07-10,1141,7.8,Predictive Systems +AI12106,AI Architect,229166,EUR,194791,EX,FT,Germany,S,Canada,50,"Scala, Linux, PyTorch",Master,15,Healthcare,2025-02-12,2025-03-20,1754,5.9,DataVision Ltd +AI12107,Data Engineer,65688,EUR,55835,EN,CT,Netherlands,S,Netherlands,0,"SQL, PyTorch, Azure, Computer Vision",Bachelor,0,Healthcare,2024-10-29,2024-12-09,586,9.5,Digital Transformation LLC +AI12108,Data Analyst,94258,GBP,70694,MI,FT,United Kingdom,S,Vietnam,100,"Java, Deep Learning, R",Bachelor,4,Manufacturing,2024-05-15,2024-06-18,2486,7.2,Autonomous Tech +AI12109,Machine Learning Researcher,61046,EUR,51889,EN,CT,France,S,South Korea,50,"Spark, Tableau, R, AWS",Associate,0,Real Estate,2024-08-25,2024-10-20,2285,8.2,Future Systems +AI12110,AI Research Scientist,200891,AUD,271203,EX,FT,Australia,S,Estonia,50,"Spark, TensorFlow, PyTorch, Computer Vision, Docker",PhD,12,Gaming,2024-12-01,2025-01-01,2100,7.9,Algorithmic Solutions +AI12111,AI Software Engineer,135505,JPY,14905550,SE,FL,Japan,L,Japan,0,"AWS, MLOps, Tableau, Statistics, Computer Vision",Bachelor,7,Education,2025-03-20,2025-05-29,664,8.6,Predictive Systems +AI12112,Computer Vision Engineer,98227,USD,98227,MI,CT,Norway,S,Switzerland,0,"Python, Git, Tableau, Computer Vision",Associate,3,Retail,2024-07-31,2024-10-10,1973,7.5,TechCorp Inc +AI12113,Principal Data Scientist,156496,USD,156496,EX,PT,South Korea,M,South Korea,0,"AWS, R, Python, Statistics",PhD,15,Retail,2024-05-28,2024-08-01,1858,7.7,Future Systems +AI12114,Machine Learning Researcher,102263,AUD,138055,MI,FL,Australia,M,Australia,0,"AWS, Tableau, Hadoop, TensorFlow, Azure",Associate,4,Retail,2024-06-28,2024-07-23,1553,6.3,Algorithmic Solutions +AI12115,Data Scientist,82355,GBP,61766,MI,FL,United Kingdom,S,United Kingdom,50,"Scala, Kubernetes, MLOps, SQL",Associate,4,Government,2024-11-04,2024-12-31,1044,7.3,Algorithmic Solutions +AI12116,AI Software Engineer,102312,USD,102312,EX,CT,China,M,China,100,"AWS, Scala, PyTorch",Master,14,Government,2025-03-24,2025-05-07,1376,9.9,DataVision Ltd +AI12117,Machine Learning Engineer,213639,USD,213639,EX,FL,Sweden,S,Hungary,50,"R, SQL, Docker, Computer Vision",Associate,14,Transportation,2024-12-04,2025-01-07,2256,7.8,Algorithmic Solutions +AI12118,Autonomous Systems Engineer,79347,USD,79347,EN,FT,Denmark,M,Denmark,0,"Python, Mathematics, Spark",Master,1,Healthcare,2024-11-12,2024-12-03,2385,9.2,Cloud AI Solutions +AI12119,Machine Learning Engineer,378082,USD,378082,EX,PT,Denmark,L,Denmark,100,"Scala, Statistics, R, Linux",PhD,14,Transportation,2024-12-21,2025-01-17,1551,8.5,DataVision Ltd +AI12120,AI Specialist,90690,USD,90690,MI,FL,Israel,M,Netherlands,0,"R, SQL, Python, TensorFlow",Bachelor,3,Telecommunications,2024-01-27,2024-03-19,2135,8.9,Advanced Robotics +AI12121,AI Software Engineer,183050,USD,183050,EX,CT,Israel,L,Philippines,50,"Deep Learning, NLP, PyTorch, GCP",Master,19,Retail,2024-09-11,2024-11-03,562,7.9,Autonomous Tech +AI12122,AI Research Scientist,106292,EUR,90348,MI,FT,France,L,France,0,"GCP, Python, PyTorch, Tableau",Associate,2,Gaming,2025-02-13,2025-03-12,2000,7.8,DataVision Ltd +AI12123,Data Engineer,281331,CHF,253198,EX,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Mathematics",Associate,19,Automotive,2025-04-15,2025-05-08,1116,5.1,Advanced Robotics +AI12124,Deep Learning Engineer,269789,JPY,29676790,EX,PT,Japan,M,Brazil,50,"SQL, Python, Kubernetes, Computer Vision, Data Visualization",PhD,18,Transportation,2025-01-03,2025-02-14,1006,9.3,DataVision Ltd +AI12125,Principal Data Scientist,55691,EUR,47337,EN,PT,Germany,M,Germany,0,"Azure, Tableau, Spark, Git",Bachelor,1,Energy,2024-06-14,2024-07-04,1510,5.8,Predictive Systems +AI12126,AI Research Scientist,162401,EUR,138041,EX,FL,Netherlands,M,Netherlands,50,"Deep Learning, Linux, SQL, MLOps",PhD,19,Education,2024-04-29,2024-06-03,2255,5.9,Cognitive Computing +AI12127,Robotics Engineer,185193,CHF,166674,SE,FT,Switzerland,S,Switzerland,50,"Data Visualization, Spark, SQL, Java, Deep Learning",Associate,8,Government,2024-04-05,2024-05-31,1191,5.6,Quantum Computing Inc +AI12128,AI Product Manager,288184,EUR,244956,EX,FT,Germany,L,Germany,100,"Docker, MLOps, R, Hadoop",Bachelor,13,Manufacturing,2024-11-25,2024-12-20,1153,5.8,Algorithmic Solutions +AI12129,Machine Learning Researcher,124643,CAD,155804,SE,CT,Canada,L,Ghana,0,"MLOps, Scala, Java",PhD,9,Automotive,2025-04-30,2025-05-21,1770,9.9,Neural Networks Co +AI12130,AI Software Engineer,43362,USD,43362,EN,FT,Israel,S,Israel,0,"GCP, PyTorch, Kubernetes, AWS, Docker",Master,0,Consulting,2025-02-13,2025-04-10,597,5,DataVision Ltd +AI12131,ML Ops Engineer,79374,USD,79374,SE,PT,South Korea,S,South Korea,50,"GCP, Mathematics, TensorFlow, Python",Bachelor,5,Telecommunications,2024-12-21,2025-01-14,1133,8.1,Neural Networks Co +AI12132,AI Consultant,316394,CHF,284755,EX,FT,Switzerland,S,Switzerland,50,"Azure, SQL, Git",Bachelor,10,Finance,2024-07-24,2024-10-04,891,5.4,Advanced Robotics +AI12133,Autonomous Systems Engineer,96744,EUR,82232,SE,PT,Germany,S,Germany,50,"AWS, Docker, GCP, Tableau, PyTorch",Master,8,Real Estate,2024-11-05,2024-12-12,1905,9,Cloud AI Solutions +AI12134,Head of AI,95183,SGD,123738,EN,FT,Singapore,L,Singapore,0,"PyTorch, Kubernetes, GCP",PhD,1,Finance,2024-11-17,2025-01-08,1001,8,Algorithmic Solutions +AI12135,Machine Learning Researcher,121586,USD,121586,SE,PT,United States,M,United States,100,"Scala, PyTorch, Mathematics, MLOps, Git",Bachelor,9,Consulting,2024-06-23,2024-07-25,1663,9.6,DeepTech Ventures +AI12136,Machine Learning Researcher,64380,SGD,83694,EN,FL,Singapore,M,Singapore,50,"Spark, Data Visualization, Java, TensorFlow",Bachelor,1,Healthcare,2024-11-11,2024-12-27,579,5.6,Predictive Systems +AI12137,Computer Vision Engineer,142065,GBP,106549,SE,PT,United Kingdom,S,United Kingdom,0,"R, Computer Vision, Data Visualization, NLP",PhD,9,Transportation,2024-09-14,2024-11-07,1555,5.9,Quantum Computing Inc +AI12138,Autonomous Systems Engineer,30742,USD,30742,EN,FT,China,S,China,0,"Azure, TensorFlow, GCP, Deep Learning",Bachelor,0,Media,2025-04-19,2025-05-17,1319,7.5,Smart Analytics +AI12139,Head of AI,207496,CHF,186746,SE,FL,Switzerland,L,Switzerland,50,"Git, Scala, Docker, Tableau",Master,5,Consulting,2024-03-27,2024-04-18,1801,6.2,Advanced Robotics +AI12140,AI Research Scientist,89982,USD,89982,MI,CT,Israel,S,Brazil,0,"Deep Learning, Kubernetes, Scala",Associate,4,Transportation,2025-03-29,2025-06-04,2083,5.7,Machine Intelligence Group +AI12141,Deep Learning Engineer,116355,USD,116355,SE,FT,Ireland,S,Luxembourg,50,"Python, TensorFlow, MLOps, Deep Learning",Bachelor,9,Gaming,2024-07-26,2024-08-23,2384,8.5,Advanced Robotics +AI12142,AI Architect,87703,USD,87703,MI,FT,Israel,L,Israel,0,"Docker, Tableau, R",Master,4,Manufacturing,2025-02-15,2025-03-14,1525,5.7,Cognitive Computing +AI12143,Data Scientist,75219,CHF,67697,EN,FT,Switzerland,M,Switzerland,100,"Git, R, Tableau, NLP",Associate,0,Government,2024-07-03,2024-07-20,1775,9.1,Future Systems +AI12144,Deep Learning Engineer,71478,EUR,60756,EN,FT,France,L,France,0,"Docker, PyTorch, Spark",PhD,0,Education,2024-09-11,2024-11-12,622,7.3,Digital Transformation LLC +AI12145,AI Research Scientist,132922,GBP,99692,SE,FL,United Kingdom,L,United Kingdom,0,"Linux, Spark, MLOps, Mathematics, Python",Bachelor,9,Automotive,2025-03-13,2025-05-04,721,9.8,Machine Intelligence Group +AI12146,Robotics Engineer,155903,CAD,194879,SE,PT,Canada,L,Canada,100,"Scala, MLOps, Data Visualization",Bachelor,5,Finance,2025-01-05,2025-02-28,1869,5.4,DeepTech Ventures +AI12147,AI Research Scientist,176781,USD,176781,EX,FL,South Korea,S,Singapore,0,"PyTorch, Statistics, Java, GCP",Bachelor,16,Manufacturing,2024-04-05,2024-05-08,2499,8.8,Cloud AI Solutions +AI12148,ML Ops Engineer,125692,AUD,169684,SE,FT,Australia,S,Australia,50,"SQL, Python, Git, Deep Learning",Associate,8,Consulting,2024-11-23,2025-01-19,2471,9.8,Cognitive Computing +AI12149,AI Product Manager,118577,USD,118577,EX,PT,South Korea,M,South Korea,50,"SQL, AWS, Java, Azure, R",PhD,10,Media,2024-10-24,2024-11-14,1747,9.7,AI Innovations +AI12150,AI Product Manager,56555,USD,56555,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Java, Data Visualization",Associate,1,Real Estate,2024-12-30,2025-01-13,2499,7.3,DeepTech Ventures +AI12151,Research Scientist,60065,USD,60065,EN,FT,Finland,L,Finland,0,"Mathematics, PyTorch, Spark",PhD,0,Manufacturing,2024-12-26,2025-02-14,859,9.9,Future Systems +AI12152,Research Scientist,139198,USD,139198,SE,CT,Sweden,L,France,0,"Spark, Hadoop, GCP, Java, Mathematics",Associate,6,Gaming,2024-07-26,2024-09-19,879,8.4,Algorithmic Solutions +AI12153,Machine Learning Researcher,143607,USD,143607,SE,FT,Ireland,M,Ireland,0,"Azure, Hadoop, Python, GCP",Associate,6,Retail,2025-03-20,2025-04-04,1532,10,Digital Transformation LLC +AI12154,Data Analyst,176811,USD,176811,EX,CT,South Korea,L,South Korea,50,"Kubernetes, Scala, Git, Java, GCP",Associate,16,Consulting,2024-11-04,2025-01-09,1133,10,Advanced Robotics +AI12155,Principal Data Scientist,166590,EUR,141602,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Docker, Azure, Scala, Python",Bachelor,5,Media,2024-07-20,2024-09-09,2307,7,Quantum Computing Inc +AI12156,Computer Vision Engineer,34463,USD,34463,MI,FL,India,M,India,100,"PyTorch, Python, Kubernetes, AWS",PhD,2,Technology,2024-07-20,2024-08-26,2225,6.4,Neural Networks Co +AI12157,AI Software Engineer,195880,USD,195880,EX,FL,Finland,S,Finland,0,"Hadoop, Python, TensorFlow, GCP, R",PhD,18,Retail,2024-01-17,2024-03-05,1179,5.6,Neural Networks Co +AI12158,Research Scientist,41697,USD,41697,MI,PT,China,M,China,50,"Azure, Python, TensorFlow",PhD,3,Manufacturing,2024-12-11,2025-02-07,1376,5.2,AI Innovations +AI12159,Research Scientist,61900,USD,61900,EN,CT,Norway,S,Norway,50,"TensorFlow, Scala, Deep Learning",Master,1,Healthcare,2024-11-20,2024-12-30,665,6.2,DataVision Ltd +AI12160,AI Consultant,32827,USD,32827,MI,FL,China,S,China,100,"Python, Kubernetes, SQL, Linux, Docker",Associate,2,Manufacturing,2024-11-03,2024-12-09,2369,7,DataVision Ltd +AI12161,Research Scientist,71766,CAD,89708,EN,FL,Canada,L,Canada,50,"Spark, Java, Mathematics, PyTorch, Computer Vision",Bachelor,1,Technology,2024-06-17,2024-07-07,1130,8.3,DeepTech Ventures +AI12162,ML Ops Engineer,221363,EUR,188159,EX,CT,Austria,M,Austria,0,"PyTorch, TensorFlow, Spark, Hadoop, Azure",Associate,16,Telecommunications,2024-04-08,2024-05-14,2389,5.5,Machine Intelligence Group +AI12163,Autonomous Systems Engineer,125926,AUD,170000,MI,FT,Australia,L,Australia,50,"Spark, Python, Mathematics, TensorFlow, Data Visualization",PhD,2,Gaming,2025-03-11,2025-04-16,1021,8.7,Autonomous Tech +AI12164,Deep Learning Engineer,121421,USD,121421,MI,FL,Denmark,M,Denmark,0,"Docker, AWS, Azure, Tableau, Spark",PhD,3,Telecommunications,2024-06-25,2024-07-18,824,9.4,Quantum Computing Inc +AI12165,Machine Learning Engineer,252757,AUD,341222,EX,FL,Australia,L,Australia,50,"Deep Learning, Scala, PyTorch, GCP, Azure",Associate,15,Automotive,2024-08-13,2024-09-04,2321,6.6,Autonomous Tech +AI12166,Data Scientist,132931,USD,132931,SE,PT,United States,S,United States,50,"Azure, Deep Learning, SQL",Associate,7,Finance,2024-09-07,2024-11-12,792,9.2,Autonomous Tech +AI12167,NLP Engineer,76358,GBP,57269,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, SQL, Computer Vision",Bachelor,1,Telecommunications,2024-12-28,2025-02-05,2476,7.7,Advanced Robotics +AI12168,Research Scientist,243166,AUD,328274,EX,CT,Australia,M,Estonia,0,"PyTorch, Mathematics, NLP, Computer Vision, TensorFlow",Bachelor,17,Automotive,2024-08-22,2024-11-01,2356,6.4,Smart Analytics +AI12169,Principal Data Scientist,101437,USD,101437,EN,CT,Norway,L,Israel,100,"SQL, Docker, Scala",Bachelor,0,Automotive,2024-07-28,2024-09-09,2330,9,Machine Intelligence Group +AI12170,Deep Learning Engineer,99518,USD,99518,MI,CT,United States,L,Luxembourg,100,"Python, TensorFlow, Git, Tableau",PhD,3,Retail,2024-06-25,2024-07-30,600,5.5,Advanced Robotics +AI12171,Deep Learning Engineer,240736,USD,240736,EX,PT,South Korea,L,Vietnam,100,"Scala, Kubernetes, Computer Vision",PhD,17,Telecommunications,2024-02-15,2024-04-24,1757,9.6,Future Systems +AI12172,Data Scientist,296026,SGD,384834,EX,FT,Singapore,L,India,100,"AWS, Scala, Data Visualization, MLOps",Master,12,Transportation,2025-02-05,2025-02-26,1392,5.6,Neural Networks Co +AI12173,Data Engineer,229184,JPY,25210240,EX,FT,Japan,L,Japan,0,"Java, SQL, GCP, NLP",Associate,17,Real Estate,2025-04-24,2025-06-01,1733,9.9,Smart Analytics +AI12174,ML Ops Engineer,151494,USD,151494,SE,FL,Ireland,M,Brazil,0,"Git, Python, MLOps, Java",Associate,7,Automotive,2024-12-04,2025-01-06,1744,6.3,Cloud AI Solutions +AI12175,NLP Engineer,237805,USD,237805,EX,CT,Sweden,L,Sweden,100,"PyTorch, Scala, Git, Mathematics",Master,10,Government,2024-08-03,2024-10-13,1883,5.1,Digital Transformation LLC +AI12176,Autonomous Systems Engineer,71970,AUD,97160,EN,FT,Australia,S,Australia,100,"R, Hadoop, NLP, SQL, Java",Master,0,Consulting,2025-03-22,2025-05-05,1066,6.9,Future Systems +AI12177,AI Architect,142468,SGD,185208,SE,CT,Singapore,S,Singapore,100,"PyTorch, Hadoop, AWS, R, Statistics",PhD,9,Automotive,2024-09-18,2024-10-09,2447,7.8,Predictive Systems +AI12178,NLP Engineer,88665,GBP,66499,MI,FT,United Kingdom,L,Kenya,100,"TensorFlow, Computer Vision, Scala, Tableau, Linux",Bachelor,4,Education,2024-04-12,2024-04-28,2448,7.7,Quantum Computing Inc +AI12179,AI Research Scientist,30066,USD,30066,EN,FL,China,L,China,50,"Azure, Python, Kubernetes, Deep Learning",Associate,1,Finance,2024-04-18,2024-05-10,2492,8.4,Predictive Systems +AI12180,AI Product Manager,90082,EUR,76570,MI,FL,France,S,France,0,"Linux, Docker, Statistics",Bachelor,4,Finance,2025-01-19,2025-02-12,1737,5.8,TechCorp Inc +AI12181,Research Scientist,101851,SGD,132406,MI,CT,Singapore,S,Singapore,0,"Kubernetes, SQL, PyTorch, MLOps",Bachelor,2,Automotive,2024-10-19,2024-12-14,1603,5.2,DeepTech Ventures +AI12182,ML Ops Engineer,246833,USD,246833,EX,FL,United States,S,United States,0,"Spark, AWS, MLOps",Associate,11,Government,2024-01-14,2024-01-28,1238,7.5,DataVision Ltd +AI12183,AI Software Engineer,89470,CHF,80523,EN,PT,Switzerland,S,Switzerland,0,"AWS, Python, GCP, Hadoop",PhD,1,Retail,2024-03-07,2024-05-02,2108,9.5,AI Innovations +AI12184,Deep Learning Engineer,71297,CAD,89121,EN,FT,Canada,M,Luxembourg,0,"SQL, Data Visualization, R",Bachelor,1,Finance,2024-06-28,2024-07-17,1898,9.1,Future Systems +AI12185,Data Scientist,86039,GBP,64529,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Scala, NLP, Computer Vision, Deep Learning",Master,2,Education,2024-05-30,2024-07-07,1586,9.9,Future Systems +AI12186,Data Scientist,34424,USD,34424,MI,CT,India,L,India,50,"GCP, Linux, Statistics",PhD,3,Technology,2024-08-22,2024-10-29,521,9.1,Predictive Systems +AI12187,Machine Learning Researcher,29840,USD,29840,MI,FT,India,M,India,0,"Python, Scala, Tableau, GCP",Master,4,Education,2025-03-20,2025-05-26,1867,8.5,Advanced Robotics +AI12188,Machine Learning Researcher,82805,AUD,111787,MI,PT,Australia,M,Ukraine,100,"TensorFlow, AWS, MLOps",Master,4,Government,2024-07-09,2024-08-15,1520,9.1,Neural Networks Co +AI12189,AI Specialist,90863,USD,90863,MI,CT,Ireland,M,Ireland,100,"Scala, R, Data Visualization",Bachelor,3,Telecommunications,2025-02-05,2025-02-19,928,7.1,Cloud AI Solutions +AI12190,AI Software Engineer,75880,USD,75880,EN,FL,Finland,L,Finland,100,"NLP, TensorFlow, AWS, Tableau, Java",PhD,1,Government,2025-01-11,2025-02-01,2354,8.3,DeepTech Ventures +AI12191,AI Specialist,90998,USD,90998,MI,CT,Norway,S,Norway,100,"Linux, Python, Kubernetes, Spark, Hadoop",PhD,2,Real Estate,2024-10-01,2024-10-15,1560,8.3,AI Innovations +AI12192,AI Product Manager,83633,EUR,71088,MI,CT,Netherlands,S,Netherlands,0,"PyTorch, GCP, Mathematics, Linux",Associate,2,Real Estate,2024-05-25,2024-07-09,2074,5.8,Algorithmic Solutions +AI12193,Deep Learning Engineer,64326,USD,64326,EN,FL,Israel,M,Israel,100,"Computer Vision, Linux, GCP",PhD,0,Finance,2024-07-02,2024-08-21,2230,8.7,Smart Analytics +AI12194,Computer Vision Engineer,111239,CHF,100115,MI,CT,Switzerland,S,Switzerland,50,"PyTorch, SQL, Computer Vision, Java",Bachelor,4,Real Estate,2024-07-08,2024-08-11,2220,7.8,Cognitive Computing +AI12195,AI Product Manager,193976,USD,193976,EX,FL,Norway,M,Belgium,100,"Mathematics, Python, SQL, GCP",PhD,17,Healthcare,2024-12-01,2025-02-03,636,5.3,Smart Analytics +AI12196,AI Architect,252737,USD,252737,EX,CT,Sweden,L,Sweden,0,"Java, Scala, MLOps, Python, Computer Vision",Master,11,Media,2024-08-30,2024-10-12,729,6.4,Quantum Computing Inc +AI12197,AI Specialist,83997,EUR,71397,MI,FL,France,M,France,0,"Kubernetes, Spark, PyTorch",Master,3,Real Estate,2025-02-25,2025-03-30,1849,7.4,Autonomous Tech +AI12198,AI Research Scientist,243739,EUR,207178,EX,PT,Germany,M,Germany,0,"Tableau, Mathematics, MLOps, Hadoop, Python",PhD,16,Technology,2024-07-27,2024-09-28,1990,9.4,Smart Analytics +AI12199,AI Consultant,169734,USD,169734,EX,FL,South Korea,M,South Korea,0,"Scala, Mathematics, Docker, Kubernetes",PhD,17,Energy,2024-12-07,2025-02-15,829,6.6,Algorithmic Solutions +AI12200,Machine Learning Researcher,59827,EUR,50853,EN,FL,Netherlands,S,China,0,"Git, Java, PyTorch, MLOps",Master,0,Finance,2024-04-20,2024-07-02,1072,5.9,Cloud AI Solutions +AI12201,Machine Learning Engineer,107719,SGD,140035,MI,PT,Singapore,L,Singapore,100,"AWS, Deep Learning, Hadoop, Linux",Master,4,Media,2024-04-16,2024-06-15,1335,8.5,AI Innovations +AI12202,AI Software Engineer,75575,JPY,8313250,EN,FT,Japan,M,Japan,50,"Computer Vision, Tableau, Deep Learning, MLOps",PhD,0,Media,2024-12-18,2025-02-17,1152,9.3,Autonomous Tech +AI12203,Autonomous Systems Engineer,281411,GBP,211058,EX,PT,United Kingdom,L,Russia,0,"Git, Spark, TensorFlow, Docker",Bachelor,13,Technology,2024-06-06,2024-07-22,1091,8.9,Cognitive Computing +AI12204,Deep Learning Engineer,88523,USD,88523,MI,FT,Ireland,L,Ireland,50,"Java, Python, Mathematics, Azure, Deep Learning",Bachelor,3,Automotive,2025-04-08,2025-06-13,1762,6.7,Digital Transformation LLC +AI12205,Deep Learning Engineer,61599,USD,61599,EN,PT,South Korea,L,South Korea,0,"Java, Spark, Tableau, Mathematics",Master,1,Government,2024-03-21,2024-05-06,794,7.6,Neural Networks Co +AI12206,Robotics Engineer,74511,SGD,96864,EN,CT,Singapore,L,Singapore,50,"NLP, Statistics, Python",Bachelor,1,Telecommunications,2024-09-22,2024-10-29,2068,6.3,DeepTech Ventures +AI12207,AI Research Scientist,23318,USD,23318,MI,FL,India,S,Thailand,50,"Scala, GCP, Python",Master,3,Government,2025-01-04,2025-02-14,1584,6.2,Quantum Computing Inc +AI12208,Computer Vision Engineer,136734,USD,136734,SE,CT,Finland,L,Finland,100,"Java, Scala, GCP, Kubernetes",Master,7,Telecommunications,2024-06-16,2024-07-24,1494,8,Predictive Systems +AI12209,Deep Learning Engineer,21533,USD,21533,EN,FL,India,L,India,100,"TensorFlow, Python, Data Visualization, Azure",Master,0,Transportation,2024-06-20,2024-07-27,759,9.6,Predictive Systems +AI12210,AI Consultant,69344,EUR,58942,EN,PT,France,M,France,50,"Kubernetes, AWS, Deep Learning",PhD,1,Automotive,2024-11-21,2024-12-21,760,6.5,Quantum Computing Inc +AI12211,Data Engineer,77016,USD,77016,EN,CT,Denmark,M,Thailand,50,"R, GCP, Kubernetes",PhD,0,Consulting,2024-12-05,2024-12-21,1323,7.8,Advanced Robotics +AI12212,AI Product Manager,79033,AUD,106695,MI,FT,Australia,M,Australia,50,"NLP, GCP, Spark",PhD,3,Manufacturing,2024-12-07,2025-01-30,1300,7.2,Future Systems +AI12213,AI Research Scientist,98816,CHF,88934,EN,FT,Switzerland,M,Switzerland,100,"Spark, Statistics, TensorFlow, Tableau",Master,1,Telecommunications,2024-06-05,2024-08-08,1929,7.3,Digital Transformation LLC +AI12214,Robotics Engineer,149985,USD,149985,SE,PT,Israel,L,Hungary,0,"TensorFlow, SQL, GCP, NLP, AWS",Master,6,Government,2024-08-14,2024-09-22,658,5.7,DataVision Ltd +AI12215,Data Scientist,129162,EUR,109788,SE,CT,Netherlands,S,Netherlands,0,"Mathematics, Git, R, SQL",Master,8,Retail,2024-03-24,2024-06-04,1376,8.6,Quantum Computing Inc +AI12216,Robotics Engineer,162024,CAD,202530,EX,CT,Canada,M,Canada,0,"Spark, SQL, Mathematics, PyTorch",Bachelor,14,Healthcare,2024-09-24,2024-11-28,2158,7.9,Algorithmic Solutions +AI12217,AI Consultant,72727,USD,72727,MI,PT,South Korea,S,South Korea,50,"MLOps, GCP, Scala, Computer Vision",Associate,4,Healthcare,2024-11-19,2025-01-02,914,5.4,Machine Intelligence Group +AI12218,Machine Learning Researcher,74894,USD,74894,EN,FL,Ireland,L,Ireland,100,"Kubernetes, MLOps, Linux, PyTorch, Git",PhD,0,Transportation,2025-02-13,2025-04-20,619,6.5,Advanced Robotics +AI12219,AI Specialist,106226,CAD,132783,SE,CT,Canada,M,Canada,100,"Scala, PyTorch, Docker",Associate,5,Energy,2024-12-02,2025-01-14,1075,9.4,Future Systems +AI12220,Computer Vision Engineer,103330,USD,103330,SE,FT,South Korea,L,South Korea,0,"NLP, AWS, Python",Associate,7,Finance,2024-01-07,2024-02-22,1951,6.2,Smart Analytics +AI12221,AI Software Engineer,228843,GBP,171632,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, Python, Computer Vision",Bachelor,18,Manufacturing,2024-10-31,2024-12-16,2231,7.7,Neural Networks Co +AI12222,Deep Learning Engineer,129776,USD,129776,MI,FT,Denmark,M,Vietnam,50,"Hadoop, Linux, SQL",Associate,3,Healthcare,2025-01-30,2025-03-07,1368,8.4,Quantum Computing Inc +AI12223,Research Scientist,146735,USD,146735,SE,FL,Norway,S,United States,50,"Computer Vision, TensorFlow, GCP",Associate,6,Automotive,2024-05-05,2024-05-20,623,8,DeepTech Ventures +AI12224,AI Research Scientist,128592,USD,128592,MI,CT,Denmark,S,Poland,50,"Hadoop, Deep Learning, Spark, AWS",Associate,4,Automotive,2024-06-11,2024-06-26,1115,6.1,TechCorp Inc +AI12225,AI Architect,166057,USD,166057,SE,PT,United States,L,United States,50,"R, MLOps, PyTorch, TensorFlow, Azure",PhD,9,Real Estate,2025-02-05,2025-03-11,2164,6.4,TechCorp Inc +AI12226,Principal Data Scientist,183692,CHF,165323,EX,FT,Switzerland,S,Switzerland,0,"R, Statistics, Git, Mathematics, GCP",Associate,10,Energy,2024-10-19,2024-11-15,2045,7,Machine Intelligence Group +AI12227,AI Software Engineer,43783,USD,43783,EN,FT,South Korea,M,South Korea,50,"SQL, Kubernetes, AWS, R",PhD,0,Education,2024-03-23,2024-04-12,2327,6.8,Quantum Computing Inc +AI12228,Data Scientist,131756,SGD,171283,SE,CT,Singapore,S,Singapore,100,"Mathematics, Deep Learning, Python, Java",Associate,7,Media,2024-01-01,2024-01-27,967,5.1,DeepTech Ventures +AI12229,AI Product Manager,93277,EUR,79285,MI,CT,Germany,S,Nigeria,100,"SQL, Azure, Computer Vision, Scala",PhD,4,Automotive,2024-03-16,2024-03-31,764,5.9,Machine Intelligence Group +AI12230,NLP Engineer,75614,SGD,98298,MI,FT,Singapore,S,Singapore,50,"Kubernetes, R, GCP, MLOps, Docker",Master,2,Government,2024-12-02,2025-01-19,2241,9.1,Cognitive Computing +AI12231,AI Consultant,247382,USD,247382,EX,FT,Ireland,M,Ireland,50,"TensorFlow, Docker, Deep Learning, Python",Master,15,Consulting,2024-10-29,2024-12-25,2013,6,Cloud AI Solutions +AI12232,AI Architect,106997,SGD,139096,MI,CT,Singapore,M,Singapore,50,"MLOps, Data Visualization, R",PhD,2,Healthcare,2024-11-27,2025-01-31,2177,8.8,Cognitive Computing +AI12233,Data Scientist,138109,GBP,103582,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Hadoop, Docker",Bachelor,6,Manufacturing,2024-02-24,2024-04-07,1495,6.9,Machine Intelligence Group +AI12234,Computer Vision Engineer,138794,USD,138794,EX,FT,Ireland,M,Ireland,100,"Statistics, Computer Vision, PyTorch, Azure, Deep Learning",Master,16,Media,2024-02-04,2024-04-09,2355,7.7,DataVision Ltd +AI12235,Autonomous Systems Engineer,168757,USD,168757,EX,CT,South Korea,L,Mexico,0,"TensorFlow, Hadoop, Linux, Docker",Master,11,Media,2024-06-03,2024-07-19,2255,9.6,Digital Transformation LLC +AI12236,AI Consultant,124514,USD,124514,MI,FT,Sweden,L,Spain,0,"Linux, R, Spark, Python, GCP",Associate,4,Government,2024-08-28,2024-10-03,587,9.7,Advanced Robotics +AI12237,Head of AI,59609,GBP,44707,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Computer Vision",Master,0,Retail,2024-05-19,2024-06-03,1917,7.4,Autonomous Tech +AI12238,Computer Vision Engineer,96741,JPY,10641510,MI,PT,Japan,S,Japan,0,"Computer Vision, Azure, Git, TensorFlow, Mathematics",Associate,4,Energy,2024-02-11,2024-04-18,2132,6.9,Quantum Computing Inc +AI12239,Data Analyst,263387,EUR,223879,EX,FL,Netherlands,L,Czech Republic,0,"Statistics, PyTorch, Java, MLOps, Deep Learning",PhD,16,Education,2024-08-08,2024-10-12,2083,6.1,TechCorp Inc +AI12240,Computer Vision Engineer,98959,GBP,74219,MI,PT,United Kingdom,S,United Kingdom,50,"Computer Vision, Hadoop, R, Scala",Bachelor,2,Healthcare,2025-02-15,2025-03-20,1818,7.3,Future Systems +AI12241,Data Scientist,120653,USD,120653,MI,FL,United States,L,United States,100,"Mathematics, Python, Tableau, Data Visualization",Associate,3,Government,2025-04-28,2025-05-19,2337,7.3,DeepTech Ventures +AI12242,AI Architect,157279,AUD,212327,EX,PT,Australia,S,India,100,"Scala, Python, Computer Vision",PhD,18,Real Estate,2024-08-03,2024-09-05,2318,7.4,Cloud AI Solutions +AI12243,AI Specialist,252708,EUR,214802,EX,PT,France,L,France,100,"GCP, Azure, Scala, Data Visualization",Master,18,Government,2024-07-16,2024-09-12,1823,5.1,Advanced Robotics +AI12244,Computer Vision Engineer,98348,USD,98348,EN,FT,Denmark,M,Denmark,0,"NLP, MLOps, Git",PhD,1,Retail,2024-11-22,2024-12-13,1969,7,Smart Analytics +AI12245,AI Architect,195438,USD,195438,EX,FT,Denmark,M,Denmark,50,"Scala, Kubernetes, NLP, Statistics, Python",Associate,11,Gaming,2024-11-18,2024-12-13,1555,9.1,TechCorp Inc +AI12246,Deep Learning Engineer,118243,USD,118243,SE,FT,Israel,M,Luxembourg,50,"Git, MLOps, R, Data Visualization",Master,8,Automotive,2024-09-19,2024-10-11,1355,8.2,Digital Transformation LLC +AI12247,Principal Data Scientist,70867,SGD,92127,MI,CT,Singapore,S,Estonia,100,"R, SQL, Deep Learning",Associate,4,Real Estate,2024-11-03,2024-12-09,715,5.6,Advanced Robotics +AI12248,Data Scientist,108015,USD,108015,SE,PT,South Korea,L,Spain,50,"Hadoop, Python, GCP",PhD,7,Manufacturing,2024-02-22,2024-03-07,2082,5.4,AI Innovations +AI12249,Computer Vision Engineer,68609,USD,68609,MI,FT,South Korea,S,South Korea,50,"Kubernetes, Linux, Docker",Master,3,Transportation,2024-02-01,2024-03-29,652,7.1,Smart Analytics +AI12250,Research Scientist,138450,USD,138450,SE,FL,Norway,M,France,100,"Azure, Java, MLOps, Computer Vision",Bachelor,7,Healthcare,2024-06-18,2024-08-17,1731,5.6,Neural Networks Co +AI12251,Autonomous Systems Engineer,129185,USD,129185,SE,PT,Israel,L,Israel,0,"GCP, Python, Git, Java",PhD,8,Telecommunications,2024-05-18,2024-07-11,2162,8.2,Cognitive Computing +AI12252,Data Engineer,62912,EUR,53475,EN,PT,Austria,L,Austria,50,"SQL, Docker, Linux",PhD,0,Transportation,2024-08-06,2024-09-25,926,6.4,Machine Intelligence Group +AI12253,Machine Learning Engineer,185718,USD,185718,EX,PT,Israel,L,Israel,50,"Python, Mathematics, MLOps, TensorFlow, Deep Learning",Bachelor,11,Manufacturing,2024-02-08,2024-04-04,2195,5.2,DataVision Ltd +AI12254,Machine Learning Engineer,159827,USD,159827,EX,FL,Israel,M,Israel,100,"Python, GCP, Linux, Statistics, Hadoop",Master,19,Finance,2024-12-09,2024-12-28,963,5.4,Autonomous Tech +AI12255,Computer Vision Engineer,93928,SGD,122106,MI,FT,Singapore,M,China,0,"Computer Vision, Python, TensorFlow, Docker, Statistics",Master,3,Media,2024-11-11,2024-11-30,870,6.1,Digital Transformation LLC +AI12256,Research Scientist,75790,GBP,56843,EN,FL,United Kingdom,S,Japan,0,"Java, Scala, GCP, Spark",Bachelor,1,Energy,2024-01-24,2024-03-03,1431,6.5,Neural Networks Co +AI12257,AI Consultant,34200,USD,34200,EN,FT,China,L,China,0,"NLP, Mathematics, Tableau, R, MLOps",Associate,0,Media,2024-04-13,2024-06-24,912,8.4,AI Innovations +AI12258,AI Software Engineer,90286,USD,90286,EN,FT,Denmark,M,Denmark,50,"Deep Learning, Spark, Azure, Tableau, AWS",Master,0,Telecommunications,2024-08-27,2024-10-29,1571,5.3,Digital Transformation LLC +AI12259,Robotics Engineer,146547,CAD,183184,EX,FL,Canada,S,Canada,100,"Kubernetes, Spark, Deep Learning, Statistics, PyTorch",PhD,17,Automotive,2025-03-30,2025-06-01,1978,8.4,TechCorp Inc +AI12260,Computer Vision Engineer,31797,USD,31797,MI,FT,India,M,Belgium,50,"Linux, Kubernetes, Statistics, Deep Learning, R",Associate,3,Gaming,2024-07-10,2024-09-18,923,8.9,Predictive Systems +AI12261,Machine Learning Engineer,54017,CAD,67521,EN,FT,Canada,M,Canada,50,"Git, Python, Spark, Scala",Associate,0,Transportation,2024-09-12,2024-10-08,513,9.2,Quantum Computing Inc +AI12262,Head of AI,272906,EUR,231970,EX,FT,Netherlands,L,India,50,"Python, Spark, Java, Data Visualization",Associate,16,Automotive,2025-03-10,2025-04-11,1833,7.6,Smart Analytics +AI12263,Machine Learning Engineer,43901,CAD,54876,EN,FT,Canada,S,Romania,100,"Deep Learning, AWS, Docker",Master,1,Energy,2024-01-11,2024-03-13,1700,6.7,Advanced Robotics +AI12264,Data Engineer,127644,AUD,172319,SE,FT,Australia,L,India,50,"Mathematics, Python, Computer Vision",Master,8,Finance,2024-07-14,2024-08-25,1260,5.1,Cognitive Computing +AI12265,AI Product Manager,128688,USD,128688,MI,PT,Denmark,L,Ireland,0,"R, Azure, Statistics",Master,4,Automotive,2024-06-28,2024-08-30,2202,9.9,Cognitive Computing +AI12266,AI Product Manager,94657,USD,94657,SE,FT,South Korea,S,South Korea,100,"SQL, TensorFlow, Deep Learning, Hadoop",PhD,8,Government,2025-04-09,2025-05-28,1489,8.8,TechCorp Inc +AI12267,AI Architect,109965,USD,109965,EN,PT,Denmark,L,Mexico,50,"Java, PyTorch, Docker, TensorFlow",Master,1,Gaming,2024-03-07,2024-04-29,752,7,Future Systems +AI12268,Head of AI,206612,USD,206612,EX,CT,Denmark,S,Denmark,0,"Java, R, SQL",Associate,17,Finance,2024-11-19,2025-01-18,1979,9.5,Autonomous Tech +AI12269,Data Engineer,181402,USD,181402,EX,FL,Sweden,S,China,100,"Statistics, SQL, Linux, Spark, Computer Vision",Associate,10,Transportation,2024-09-09,2024-11-09,1526,5,DataVision Ltd +AI12270,Machine Learning Engineer,193935,CHF,174542,SE,FT,Switzerland,L,Switzerland,100,"Git, Docker, Python",Associate,8,Finance,2024-12-22,2025-02-01,671,8.6,Advanced Robotics +AI12271,AI Architect,59622,USD,59622,SE,FT,China,L,China,100,"PyTorch, GCP, Scala",Master,8,Retail,2024-08-19,2024-09-10,616,6.9,DeepTech Ventures +AI12272,Data Engineer,82962,EUR,70518,MI,FL,Netherlands,S,Luxembourg,50,"Hadoop, AWS, NLP",Associate,4,Telecommunications,2024-03-05,2024-05-03,2217,6.5,AI Innovations +AI12273,AI Research Scientist,179005,USD,179005,EX,PT,Sweden,S,New Zealand,50,"Python, TensorFlow, Deep Learning, AWS, Statistics",Master,13,Consulting,2024-02-09,2024-03-09,1916,9.8,Cloud AI Solutions +AI12274,NLP Engineer,45061,USD,45061,EN,FL,South Korea,M,South Korea,50,"Java, SQL, GCP, Deep Learning",PhD,1,Gaming,2024-02-07,2024-02-24,2265,7.7,Future Systems +AI12275,Robotics Engineer,183033,USD,183033,EX,PT,Israel,L,Israel,100,"Git, GCP, MLOps, Computer Vision",PhD,18,Healthcare,2024-10-31,2025-01-03,1456,6.2,DataVision Ltd +AI12276,AI Architect,85926,USD,85926,EN,FL,United States,L,United States,50,"Linux, R, Mathematics, SQL",PhD,0,Technology,2024-02-14,2024-03-31,724,7.7,Cognitive Computing +AI12277,AI Specialist,90585,EUR,76997,SE,FL,Austria,S,United Kingdom,0,"Python, Azure, TensorFlow, Statistics",Bachelor,8,Finance,2024-12-16,2025-01-28,694,7.3,Cognitive Computing +AI12278,ML Ops Engineer,175783,CHF,158205,SE,CT,Switzerland,L,Austria,100,"Docker, Tableau, NLP, Linux, AWS",Associate,7,Gaming,2025-02-12,2025-03-25,1058,8.5,Machine Intelligence Group +AI12279,AI Consultant,136939,USD,136939,SE,FT,Denmark,M,Denmark,0,"Java, GCP, Python, R, Computer Vision",Master,5,Education,2024-12-16,2025-02-04,2284,6.8,Autonomous Tech +AI12280,Computer Vision Engineer,91436,USD,91436,MI,FL,Israel,M,Denmark,50,"Kubernetes, Spark, Tableau",Bachelor,3,Telecommunications,2024-12-28,2025-03-06,596,7.2,TechCorp Inc +AI12281,Computer Vision Engineer,149033,CHF,134130,MI,FT,Switzerland,M,Switzerland,0,"Git, TensorFlow, Data Visualization, Computer Vision, Docker",PhD,4,Media,2024-02-01,2024-04-01,1269,9.8,Advanced Robotics +AI12282,Machine Learning Engineer,66306,USD,66306,EN,CT,Denmark,M,Denmark,100,"SQL, TensorFlow, NLP, Linux",Master,0,Consulting,2024-02-25,2024-05-01,939,5.2,DataVision Ltd +AI12283,AI Software Engineer,59399,USD,59399,SE,CT,China,M,China,100,"Python, TensorFlow, Deep Learning, Git",PhD,5,Healthcare,2024-06-27,2024-08-24,2474,6.1,TechCorp Inc +AI12284,Data Analyst,99702,USD,99702,SE,CT,Sweden,S,Sweden,100,"Python, TensorFlow, Data Visualization",Bachelor,7,Transportation,2025-04-01,2025-05-15,874,9.5,TechCorp Inc +AI12285,AI Architect,100196,USD,100196,SE,CT,South Korea,S,South Korea,50,"Docker, Scala, Python",Master,6,Healthcare,2024-04-04,2024-05-03,600,9.7,Machine Intelligence Group +AI12286,AI Architect,247639,CAD,309549,EX,CT,Canada,L,Spain,100,"R, GCP, Python, Mathematics",Master,10,Media,2024-11-25,2024-12-11,1628,9.1,Digital Transformation LLC +AI12287,Autonomous Systems Engineer,98862,USD,98862,MI,FT,Norway,S,Chile,50,"Python, Computer Vision, GCP, Java, MLOps",Master,4,Manufacturing,2024-05-22,2024-07-16,1346,9.2,Cloud AI Solutions +AI12288,AI Software Engineer,100088,EUR,85075,MI,FL,Netherlands,S,Colombia,100,"Java, Azure, GCP, R",Associate,4,Gaming,2025-01-31,2025-03-12,677,9,Digital Transformation LLC +AI12289,ML Ops Engineer,67854,USD,67854,MI,FL,Israel,S,Israel,50,"Data Visualization, Computer Vision, PyTorch, Spark, GCP",Bachelor,2,Finance,2024-03-28,2024-06-07,1834,7.5,AI Innovations +AI12290,Research Scientist,133071,USD,133071,SE,CT,Finland,M,Finland,0,"Python, Linux, MLOps, Statistics",PhD,8,Healthcare,2024-03-17,2024-05-18,859,8.6,AI Innovations +AI12291,AI Research Scientist,94334,SGD,122634,MI,FL,Singapore,L,Singapore,0,"NLP, Docker, Mathematics, Hadoop",Bachelor,3,Healthcare,2024-12-19,2025-01-24,871,6,Digital Transformation LLC +AI12292,AI Research Scientist,79114,USD,79114,EX,PT,China,L,China,50,"NLP, SQL, Python, Kubernetes",Bachelor,14,Real Estate,2024-08-07,2024-09-27,1681,9.1,Machine Intelligence Group +AI12293,Autonomous Systems Engineer,140641,USD,140641,SE,FL,Sweden,M,Sweden,50,"Python, Kubernetes, GCP, Statistics, Tableau",Master,7,Telecommunications,2024-05-01,2024-05-21,2152,9.2,DeepTech Ventures +AI12294,Computer Vision Engineer,108378,CHF,97540,MI,FT,Switzerland,S,Switzerland,0,"R, Azure, MLOps, Spark, Python",Master,2,Gaming,2024-05-13,2024-06-08,2394,8.6,Autonomous Tech +AI12295,Deep Learning Engineer,66720,USD,66720,EN,FL,Denmark,M,Thailand,0,"Python, TensorFlow, MLOps",Bachelor,0,Technology,2024-04-28,2024-06-22,2040,6.9,Algorithmic Solutions +AI12296,AI Architect,103843,EUR,88267,MI,PT,Germany,L,Germany,100,"Linux, R, Azure, Python",PhD,3,Healthcare,2025-04-03,2025-05-26,789,8.4,Predictive Systems +AI12297,Principal Data Scientist,180949,USD,180949,SE,FL,Norway,M,Norway,0,"SQL, Java, Spark",Associate,7,Real Estate,2024-04-29,2024-06-17,740,8.6,TechCorp Inc +AI12298,Robotics Engineer,320986,USD,320986,EX,CT,United States,L,United States,100,"NLP, Azure, Scala",Bachelor,11,Media,2025-02-28,2025-03-15,1339,8.7,Neural Networks Co +AI12299,AI Product Manager,164065,SGD,213285,SE,PT,Singapore,L,Singapore,100,"Statistics, GCP, Linux, Hadoop",Bachelor,9,Technology,2024-09-19,2024-11-02,1815,8.8,TechCorp Inc +AI12300,Data Analyst,84134,USD,84134,MI,FT,Sweden,S,Sweden,0,"Python, Java, Tableau",PhD,3,Healthcare,2024-01-29,2024-02-19,2364,8.2,Algorithmic Solutions +AI12301,AI Product Manager,59000,USD,59000,EN,FT,Ireland,L,Ireland,0,"Spark, Mathematics, R",Master,0,Energy,2024-11-17,2025-01-16,975,6.3,AI Innovations +AI12302,Data Analyst,184365,USD,184365,EX,FL,Sweden,M,Sweden,50,"SQL, Python, Linux, Docker, Java",Bachelor,17,Automotive,2024-03-21,2024-04-05,2378,5.9,Cognitive Computing +AI12303,AI Architect,74246,CAD,92808,MI,PT,Canada,S,Thailand,100,"PyTorch, SQL, Docker, Computer Vision, R",Master,2,Automotive,2024-08-11,2024-10-22,819,5.2,Cloud AI Solutions +AI12304,Machine Learning Researcher,116928,USD,116928,SE,PT,Ireland,S,Ireland,0,"Docker, MLOps, Scala, Python, AWS",PhD,7,Finance,2024-03-31,2024-04-22,1068,5.2,AI Innovations +AI12305,Principal Data Scientist,64457,USD,64457,SE,FT,China,L,China,50,"Statistics, Scala, Kubernetes",PhD,7,Finance,2024-03-27,2024-05-17,915,9.4,Autonomous Tech +AI12306,AI Architect,34017,USD,34017,EN,CT,China,S,China,50,"Git, Docker, Azure, Tableau, Python",Associate,1,Government,2025-03-01,2025-04-15,1811,8.1,Cognitive Computing +AI12307,Principal Data Scientist,86245,USD,86245,EN,FL,Ireland,L,Ireland,0,"Deep Learning, R, SQL, PyTorch",Master,1,Technology,2024-05-14,2024-06-24,1477,6.9,Predictive Systems +AI12308,Data Analyst,304034,USD,304034,EX,CT,Denmark,M,Denmark,50,"MLOps, Linux, Hadoop, PyTorch",Master,11,Retail,2024-01-06,2024-01-23,683,9,Machine Intelligence Group +AI12309,Machine Learning Researcher,207016,USD,207016,EX,FT,Finland,S,Finland,100,"Hadoop, R, PyTorch, Java, Docker",Associate,11,Media,2024-12-11,2025-01-06,593,5.3,AI Innovations +AI12310,AI Research Scientist,192387,GBP,144290,EX,FL,United Kingdom,M,Singapore,50,"Java, Python, R",PhD,17,Consulting,2024-09-18,2024-11-22,2353,8.6,Future Systems +AI12311,Data Analyst,23733,USD,23733,MI,FT,India,S,Switzerland,100,"Git, Python, MLOps, Tableau",Master,3,Gaming,2024-08-25,2024-09-15,628,8.6,Advanced Robotics +AI12312,AI Architect,154274,USD,154274,SE,PT,Denmark,L,United States,0,"Deep Learning, Mathematics, Scala, AWS",PhD,9,Retail,2024-02-13,2024-03-27,1673,6,DeepTech Ventures +AI12313,NLP Engineer,43529,USD,43529,MI,CT,China,S,Colombia,50,"Scala, Kubernetes, R, Computer Vision",Master,4,Education,2025-01-04,2025-02-27,855,8.4,Future Systems +AI12314,AI Product Manager,214849,EUR,182622,EX,FL,Austria,M,Austria,50,"Git, Hadoop, Mathematics, PyTorch, Statistics",Bachelor,11,Government,2024-10-25,2024-11-09,2133,8.4,Algorithmic Solutions +AI12315,AI Research Scientist,49530,USD,49530,MI,PT,China,M,China,50,"Kubernetes, GCP, Python",PhD,3,Transportation,2024-12-16,2025-02-12,1247,5.3,Algorithmic Solutions +AI12316,AI Product Manager,90866,USD,90866,EN,FL,Denmark,S,Denmark,0,"Tableau, TensorFlow, Linux, Java",PhD,1,Education,2024-09-04,2024-11-03,2019,9.6,Neural Networks Co +AI12317,Principal Data Scientist,38519,USD,38519,EN,CT,South Korea,S,South Korea,0,"Tableau, AWS, SQL, Computer Vision",PhD,1,Healthcare,2024-07-04,2024-09-02,1845,5.3,DeepTech Ventures +AI12318,Principal Data Scientist,190560,SGD,247728,EX,PT,Singapore,L,Singapore,50,"Kubernetes, Spark, TensorFlow, Data Visualization, Mathematics",PhD,14,Automotive,2024-01-07,2024-03-06,1253,8.5,Future Systems +AI12319,Data Scientist,111397,USD,111397,SE,FL,Sweden,M,Sweden,0,"NLP, Java, Git, SQL",Bachelor,9,Healthcare,2024-04-21,2024-05-27,2032,9.6,DeepTech Ventures +AI12320,Head of AI,100635,USD,100635,MI,CT,Finland,M,Finland,0,"Linux, Java, SQL, Mathematics",PhD,2,Automotive,2025-04-28,2025-05-20,2219,9,Quantum Computing Inc +AI12321,Robotics Engineer,108577,USD,108577,SE,FT,Finland,M,Finland,100,"Statistics, GCP, Docker, Git, Computer Vision",Associate,7,Healthcare,2024-07-23,2024-09-11,641,5,TechCorp Inc +AI12322,AI Product Manager,34193,USD,34193,MI,PT,India,L,India,0,"Scala, GCP, Linux, SQL, Hadoop",Bachelor,3,Healthcare,2024-06-08,2024-07-20,679,6.1,Quantum Computing Inc +AI12323,AI Software Engineer,110241,EUR,93705,SE,PT,Austria,M,Indonesia,50,"GCP, Computer Vision, TensorFlow, Tableau",Bachelor,6,Real Estate,2024-06-06,2024-07-21,1072,8.8,DeepTech Ventures +AI12324,Data Scientist,184497,USD,184497,EX,PT,Denmark,S,Denmark,50,"Tableau, Azure, Java, Kubernetes, MLOps",Master,16,Real Estate,2024-07-24,2024-09-07,1516,5.3,DeepTech Ventures +AI12325,AI Architect,84774,USD,84774,EN,FL,Finland,L,Finland,50,"Hadoop, PyTorch, Git, Azure, TensorFlow",Bachelor,0,Manufacturing,2024-09-12,2024-11-17,1470,6.4,Cloud AI Solutions +AI12326,Robotics Engineer,235792,USD,235792,EX,CT,United States,L,Philippines,0,"MLOps, Java, Docker",Bachelor,14,Finance,2024-10-20,2024-11-03,1360,6,Advanced Robotics +AI12327,Autonomous Systems Engineer,54131,USD,54131,EX,FL,India,M,India,0,"Computer Vision, GCP, Scala, Git",Master,15,Government,2024-07-09,2024-07-25,1390,7,Cognitive Computing +AI12328,Research Scientist,154810,CAD,193513,EX,FT,Canada,L,Canada,100,"Computer Vision, Kubernetes, NLP, R, Scala",Bachelor,15,Media,2024-09-03,2024-10-30,1652,6,DataVision Ltd +AI12329,AI Software Engineer,86911,EUR,73874,EN,PT,Netherlands,L,Netherlands,0,"Python, Spark, GCP, AWS, Azure",PhD,0,Telecommunications,2024-03-02,2024-05-11,2154,5.1,Digital Transformation LLC +AI12330,Machine Learning Engineer,83432,JPY,9177520,MI,CT,Japan,S,Austria,0,"Kubernetes, Git, MLOps, GCP",PhD,3,Media,2024-11-03,2024-12-08,1132,8.1,AI Innovations +AI12331,Data Analyst,104994,USD,104994,EX,CT,China,M,China,100,"Deep Learning, PyTorch, Data Visualization, TensorFlow, MLOps",PhD,11,Healthcare,2025-02-05,2025-03-22,1601,9.4,Cloud AI Solutions +AI12332,Principal Data Scientist,114869,EUR,97639,SE,PT,France,L,France,50,"Scala, Git, PyTorch",PhD,6,Consulting,2024-06-12,2024-07-28,1537,6.3,Predictive Systems +AI12333,AI Consultant,108366,USD,108366,SE,FT,South Korea,M,South Korea,100,"Azure, AWS, Data Visualization, Git, Computer Vision",Associate,7,Transportation,2024-04-07,2024-06-17,1379,8.2,Future Systems +AI12334,Machine Learning Engineer,112203,USD,112203,MI,FL,Ireland,L,Ireland,50,"SQL, R, Python, AWS",PhD,2,Media,2024-12-04,2025-01-07,1218,8.6,Smart Analytics +AI12335,Data Analyst,152809,EUR,129888,EX,FL,France,S,France,100,"Spark, Python, Tableau, Statistics",Master,19,Retail,2024-05-07,2024-06-07,1099,6.6,Autonomous Tech +AI12336,AI Consultant,55945,USD,55945,MI,CT,China,L,Finland,0,"Azure, Scala, Python, Statistics, Mathematics",Bachelor,4,Gaming,2024-01-01,2024-01-23,2346,6.7,Machine Intelligence Group +AI12337,Research Scientist,139128,USD,139128,SE,PT,Finland,L,Finland,100,"Hadoop, Scala, Computer Vision, TensorFlow, Docker",PhD,8,Media,2024-09-19,2024-10-07,761,6.9,Quantum Computing Inc +AI12338,NLP Engineer,74433,USD,74433,MI,PT,Ireland,S,Ireland,50,"R, GCP, Hadoop",Master,2,Real Estate,2024-05-15,2024-07-04,888,6.7,Predictive Systems +AI12339,Deep Learning Engineer,62585,USD,62585,EN,PT,Finland,L,Russia,100,"GCP, SQL, NLP, Statistics",PhD,1,Real Estate,2024-03-14,2024-04-09,1943,8.9,Cognitive Computing +AI12340,Deep Learning Engineer,64130,JPY,7054300,EN,PT,Japan,S,Japan,50,"Hadoop, Tableau, AWS, Java, Data Visualization",PhD,1,Telecommunications,2025-01-16,2025-01-31,2403,8.8,DataVision Ltd +AI12341,Head of AI,24000,USD,24000,EN,FL,India,M,India,50,"Spark, Hadoop, Statistics, Python",PhD,1,Retail,2024-06-20,2024-08-19,1168,9.5,Advanced Robotics +AI12342,ML Ops Engineer,63740,EUR,54179,EN,FL,France,L,Belgium,100,"Computer Vision, MLOps, Deep Learning, Python",Associate,0,Telecommunications,2024-12-15,2025-01-26,2452,5,Cognitive Computing +AI12343,AI Architect,75688,EUR,64335,EN,FT,Netherlands,M,Netherlands,100,"TensorFlow, Spark, Tableau, Data Visualization, Scala",PhD,0,Retail,2024-12-01,2025-02-10,1406,6.3,Smart Analytics +AI12344,Autonomous Systems Engineer,91038,USD,91038,EN,CT,Sweden,L,Sweden,0,"Python, Java, AWS, Mathematics",Associate,1,Consulting,2024-02-05,2024-03-18,908,5.5,Predictive Systems +AI12345,Autonomous Systems Engineer,171871,USD,171871,EX,FT,Israel,M,Malaysia,50,"PyTorch, R, Mathematics, MLOps",Associate,10,Real Estate,2024-06-03,2024-07-14,2018,8.2,Predictive Systems +AI12346,ML Ops Engineer,92855,USD,92855,EN,FL,Norway,S,Ukraine,0,"Python, Data Visualization, TensorFlow, Spark, Hadoop",Associate,1,Education,2024-08-01,2024-09-11,1286,9.5,Future Systems +AI12347,AI Specialist,138709,USD,138709,MI,PT,Norway,M,Norway,100,"Scala, MLOps, TensorFlow, Hadoop",Master,2,Government,2025-04-27,2025-06-27,1095,7.7,Predictive Systems +AI12348,AI Product Manager,89902,USD,89902,EX,CT,India,L,India,50,"Java, Statistics, Tableau, NLP, PyTorch",Bachelor,12,Telecommunications,2024-03-08,2024-04-04,791,9.8,TechCorp Inc +AI12349,Machine Learning Engineer,172633,USD,172633,SE,CT,United States,M,Poland,50,"Python, R, Git, GCP, Deep Learning",Associate,8,Retail,2024-10-08,2024-12-08,645,6.9,TechCorp Inc +AI12350,Robotics Engineer,113910,USD,113910,SE,FT,Israel,M,Israel,0,"Azure, Scala, Data Visualization, Java, Spark",Bachelor,5,Retail,2024-08-20,2024-10-17,1576,5.7,Neural Networks Co +AI12351,Robotics Engineer,145181,USD,145181,SE,FT,United States,S,United Kingdom,50,"Spark, Tableau, MLOps, R, Computer Vision",Associate,8,Gaming,2024-06-23,2024-07-19,1128,5.5,Smart Analytics +AI12352,Data Scientist,126932,CAD,158665,SE,FL,Canada,S,Canada,0,"Computer Vision, Scala, Azure, SQL, Hadoop",PhD,7,Education,2024-11-02,2025-01-14,1822,6.6,Algorithmic Solutions +AI12353,Data Engineer,237969,EUR,202274,EX,FT,Austria,L,Austria,100,"Computer Vision, Azure, Hadoop, Git",Bachelor,13,Manufacturing,2024-03-22,2024-04-19,1312,9.3,Cloud AI Solutions +AI12354,ML Ops Engineer,70164,USD,70164,EX,CT,China,S,China,50,"Kubernetes, Scala, GCP",PhD,12,Energy,2024-02-05,2024-02-25,1714,6.4,Algorithmic Solutions +AI12355,Principal Data Scientist,91580,USD,91580,MI,PT,Sweden,L,Sweden,50,"Java, TensorFlow, NLP, R, Linux",Associate,2,Retail,2025-04-17,2025-05-30,1576,8.7,Algorithmic Solutions +AI12356,Data Scientist,210798,SGD,274037,EX,CT,Singapore,L,Czech Republic,50,"Azure, Python, TensorFlow",Bachelor,16,Automotive,2025-04-27,2025-06-03,1488,5.4,Advanced Robotics +AI12357,Data Scientist,172275,SGD,223958,EX,FL,Singapore,S,Norway,100,"PyTorch, MLOps, Scala, Mathematics, Computer Vision",Associate,11,Telecommunications,2024-01-22,2024-03-26,1642,5.1,DeepTech Ventures +AI12358,Data Scientist,181539,GBP,136154,SE,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, AWS",Bachelor,5,Gaming,2024-03-29,2024-04-30,849,9.6,AI Innovations +AI12359,Principal Data Scientist,83912,JPY,9230320,EN,FT,Japan,L,Japan,100,"Docker, Data Visualization, Computer Vision",Master,0,Automotive,2024-09-05,2024-10-07,1372,5.8,Predictive Systems +AI12360,AI Product Manager,126540,USD,126540,MI,PT,Sweden,L,Sweden,0,"Deep Learning, Kubernetes, Python, Git",Bachelor,3,Government,2024-11-17,2024-12-20,747,8.2,Future Systems +AI12361,Machine Learning Researcher,136341,USD,136341,MI,FL,Denmark,L,South Africa,100,"SQL, NLP, MLOps",Master,2,Finance,2024-08-19,2024-10-08,2113,7.4,Machine Intelligence Group +AI12362,Principal Data Scientist,134759,EUR,114545,SE,FT,Germany,S,Germany,50,"NLP, Spark, Azure, Python",Bachelor,6,Energy,2024-08-24,2024-10-23,901,5.4,Digital Transformation LLC +AI12363,AI Research Scientist,71946,EUR,61154,MI,FT,Netherlands,S,Turkey,100,"Spark, Hadoop, TensorFlow, MLOps",Master,3,Healthcare,2024-08-14,2024-10-03,1113,7.5,Quantum Computing Inc +AI12364,NLP Engineer,93601,EUR,79561,MI,PT,France,L,France,50,"Python, GCP, Kubernetes, TensorFlow, Git",Master,2,Telecommunications,2025-01-18,2025-02-19,986,5.6,Predictive Systems +AI12365,Autonomous Systems Engineer,96130,CAD,120163,SE,FL,Canada,M,Canada,50,"Scala, AWS, Tableau, TensorFlow, Spark",Bachelor,7,Transportation,2024-08-16,2024-09-13,547,5.1,Neural Networks Co +AI12366,AI Consultant,62895,CAD,78619,EN,FT,Canada,L,Canada,0,"Hadoop, SQL, TensorFlow, Python",Associate,0,Telecommunications,2025-04-07,2025-05-17,903,7.6,Predictive Systems +AI12367,ML Ops Engineer,71053,USD,71053,EN,FT,Finland,M,Finland,50,"Scala, Java, GCP, Spark",Bachelor,1,Finance,2024-04-25,2024-05-17,626,5.2,Algorithmic Solutions +AI12368,Data Scientist,235335,USD,235335,EX,CT,Ireland,M,Ireland,100,"Scala, R, NLP",PhD,10,Finance,2024-12-12,2025-01-02,826,7.7,Neural Networks Co +AI12369,Data Analyst,189502,EUR,161077,EX,CT,Austria,S,Australia,50,"Hadoop, PyTorch, SQL, GCP",Bachelor,15,Finance,2025-02-24,2025-04-25,2412,8.9,Algorithmic Solutions +AI12370,Deep Learning Engineer,60818,USD,60818,SE,FT,China,M,China,50,"Scala, Data Visualization, SQL, TensorFlow",PhD,7,Education,2024-11-13,2024-12-05,1109,6.7,Quantum Computing Inc +AI12371,Data Analyst,139977,EUR,118980,SE,CT,Netherlands,L,Norway,50,"Java, GCP, Azure, Tableau, AWS",PhD,5,Energy,2024-02-25,2024-03-24,1555,6,DeepTech Ventures +AI12372,Autonomous Systems Engineer,305019,GBP,228764,EX,FT,United Kingdom,L,United Kingdom,0,"Kubernetes, Spark, Python, Java",PhD,19,Gaming,2024-08-06,2024-08-24,907,6.5,Autonomous Tech +AI12373,AI Architect,74292,EUR,63148,MI,FT,Austria,M,Philippines,0,"Python, Mathematics, PyTorch, SQL, Deep Learning",Associate,3,Finance,2025-02-24,2025-04-25,2408,8.3,Cloud AI Solutions +AI12374,ML Ops Engineer,65497,USD,65497,EN,FL,Finland,L,Finland,0,"Linux, Deep Learning, Python, Mathematics, Git",PhD,1,Media,2024-11-18,2025-01-05,1132,9.1,Advanced Robotics +AI12375,Principal Data Scientist,17450,USD,17450,EN,FT,India,S,India,50,"MLOps, Azure, Git",Bachelor,0,Real Estate,2024-12-03,2025-02-13,517,6.4,Neural Networks Co +AI12376,Machine Learning Engineer,56393,CAD,70491,EN,FL,Canada,S,Canada,100,"R, Tableau, Docker",Bachelor,0,Real Estate,2024-08-28,2024-10-25,2498,6.7,Algorithmic Solutions +AI12377,Machine Learning Researcher,28903,USD,28903,EN,FT,India,L,India,0,"Python, Deep Learning, Computer Vision",Associate,0,Finance,2025-03-14,2025-05-09,2425,5.8,Cognitive Computing +AI12378,Machine Learning Researcher,204225,JPY,22464750,EX,FL,Japan,M,Japan,100,"NLP, SQL, PyTorch",Bachelor,14,Manufacturing,2025-02-25,2025-03-16,735,9.2,Neural Networks Co +AI12379,Head of AI,182487,EUR,155114,EX,CT,Austria,M,Italy,100,"Python, PyTorch, Linux, Java, GCP",Associate,13,Consulting,2024-03-12,2024-04-02,891,6.2,AI Innovations +AI12380,Robotics Engineer,122104,USD,122104,SE,PT,United States,M,South Africa,50,"R, Data Visualization, Linux",PhD,8,Transportation,2024-05-09,2024-05-30,933,5.6,Neural Networks Co +AI12381,Data Engineer,107231,USD,107231,SE,CT,Sweden,S,Sweden,100,"Git, Kubernetes, PyTorch",Bachelor,9,Telecommunications,2024-06-15,2024-08-14,643,9.2,Quantum Computing Inc +AI12382,Deep Learning Engineer,37458,USD,37458,MI,PT,India,M,Czech Republic,50,"Tableau, Hadoop, Java, Azure",Bachelor,4,Consulting,2024-12-02,2024-12-22,1953,5.2,AI Innovations +AI12383,AI Architect,145761,USD,145761,EX,CT,Israel,S,Israel,100,"Java, Statistics, Python, Tableau",Master,13,Media,2024-06-05,2024-07-08,2475,9.1,Predictive Systems +AI12384,Data Engineer,200170,CHF,180153,EX,FL,Switzerland,S,Switzerland,0,"Git, PyTorch, Tableau, Data Visualization, Docker",Master,13,Manufacturing,2025-04-24,2025-06-27,780,5.6,Future Systems +AI12385,ML Ops Engineer,82455,CAD,103069,MI,PT,Canada,S,Canada,50,"Deep Learning, Git, MLOps",Bachelor,4,Retail,2024-01-29,2024-04-09,1588,6,AI Innovations +AI12386,Principal Data Scientist,77760,AUD,104976,EN,PT,Australia,M,Australia,50,"Hadoop, Mathematics, TensorFlow, R",PhD,1,Government,2024-05-01,2024-06-01,1392,8.5,Algorithmic Solutions +AI12387,AI Architect,142182,USD,142182,SE,FT,Finland,M,Finland,100,"Statistics, Kubernetes, Python, Computer Vision, TensorFlow",Associate,5,Government,2024-04-24,2024-05-10,853,9.9,Cloud AI Solutions +AI12388,Robotics Engineer,132350,USD,132350,SE,CT,Ireland,L,Ireland,100,"Data Visualization, Scala, Python, Azure",Associate,9,Real Estate,2025-01-28,2025-02-21,2147,8.2,Advanced Robotics +AI12389,Data Engineer,141077,USD,141077,SE,FL,South Korea,L,South Korea,100,"Docker, Linux, Spark, Deep Learning",Master,7,Government,2025-01-14,2025-02-13,1331,7.2,DeepTech Ventures +AI12390,Research Scientist,237360,CHF,213624,EX,FT,Switzerland,M,Switzerland,100,"MLOps, Statistics, Hadoop",Bachelor,13,Real Estate,2024-12-24,2025-01-21,1615,8.4,Future Systems +AI12391,Data Engineer,138254,JPY,15207940,EX,CT,Japan,S,Japan,50,"Spark, Kubernetes, Data Visualization, SQL",PhD,15,Healthcare,2024-11-01,2025-01-07,1803,9.5,TechCorp Inc +AI12392,AI Consultant,181342,EUR,154141,EX,FL,Netherlands,S,Netherlands,50,"Mathematics, PyTorch, Data Visualization, Scala, Spark",PhD,16,Technology,2025-03-11,2025-05-20,2346,6.8,Autonomous Tech +AI12393,Deep Learning Engineer,154049,JPY,16945390,SE,PT,Japan,M,Japan,100,"Git, Hadoop, Tableau",PhD,8,Healthcare,2024-04-27,2024-05-25,830,6.3,Advanced Robotics +AI12394,Machine Learning Researcher,57960,EUR,49266,EN,FT,Netherlands,S,Netherlands,0,"Python, Azure, Scala, Linux",Master,1,Education,2024-06-01,2024-07-07,1746,5.7,Machine Intelligence Group +AI12395,Principal Data Scientist,281214,USD,281214,EX,CT,Sweden,L,Russia,50,"Data Visualization, Tableau, Python",Bachelor,11,Manufacturing,2024-12-13,2025-01-05,775,8,Autonomous Tech +AI12396,ML Ops Engineer,78328,EUR,66579,EN,CT,Austria,L,Italy,100,"Linux, Scala, Azure, Statistics, Kubernetes",Associate,0,Transportation,2024-03-20,2024-04-12,662,6,Cloud AI Solutions +AI12397,Deep Learning Engineer,253374,CAD,316718,EX,FT,Canada,L,Canada,50,"SQL, Spark, Hadoop",Bachelor,16,Energy,2024-09-16,2024-10-24,1534,8.8,Algorithmic Solutions +AI12398,Autonomous Systems Engineer,168477,USD,168477,SE,CT,Norway,M,Norway,0,"Spark, Linux, PyTorch, SQL",Master,8,Gaming,2024-07-30,2024-08-24,1899,9.6,Autonomous Tech +AI12399,Machine Learning Engineer,87035,USD,87035,MI,FT,United States,S,United States,0,"Data Visualization, Computer Vision, Java, Spark, Statistics",PhD,3,Healthcare,2025-04-22,2025-06-14,2493,8.2,Future Systems +AI12400,AI Specialist,152751,SGD,198576,EX,FL,Singapore,S,Australia,50,"Azure, Scala, Python, TensorFlow, Spark",Associate,16,Energy,2024-02-06,2024-02-21,1240,8,DeepTech Ventures +AI12401,Data Engineer,92050,USD,92050,MI,FT,Sweden,S,Sweden,0,"Docker, MLOps, Python, R, Statistics",Bachelor,4,Automotive,2025-01-28,2025-02-16,1432,6.2,Autonomous Tech +AI12402,Data Scientist,55016,EUR,46764,EN,FT,France,M,Indonesia,0,"Statistics, Python, PyTorch",Associate,1,Retail,2024-06-07,2024-06-21,1512,9.1,Autonomous Tech +AI12403,Computer Vision Engineer,135145,GBP,101359,SE,PT,United Kingdom,M,United Kingdom,100,"AWS, Linux, TensorFlow",Associate,9,Consulting,2024-05-16,2024-06-04,711,10,DeepTech Ventures +AI12404,Head of AI,118429,GBP,88822,SE,CT,United Kingdom,S,Egypt,100,"Spark, Mathematics, Linux, Deep Learning, TensorFlow",Master,7,Consulting,2025-01-19,2025-03-13,995,8.6,Autonomous Tech +AI12405,NLP Engineer,57898,GBP,43424,EN,FL,United Kingdom,M,United Kingdom,50,"Java, Spark, Tableau, MLOps",Master,0,Energy,2024-02-16,2024-03-25,717,7.3,Quantum Computing Inc +AI12406,AI Architect,51180,EUR,43503,EN,CT,Austria,S,Italy,0,"Python, NLP, Data Visualization",Associate,0,Media,2024-11-22,2024-12-06,698,5.5,Quantum Computing Inc +AI12407,Data Scientist,103458,USD,103458,EX,PT,India,L,India,0,"AWS, Docker, Spark, Java, Tableau",Master,19,Media,2024-06-16,2024-08-12,2212,5.5,Future Systems +AI12408,Data Scientist,102748,USD,102748,EX,CT,China,L,China,0,"AWS, Azure, PyTorch, Scala",Bachelor,10,Finance,2025-02-08,2025-04-08,1986,8.1,Smart Analytics +AI12409,Data Analyst,151467,USD,151467,SE,PT,Ireland,M,Ireland,0,"Statistics, TensorFlow, NLP, Mathematics, Java",Bachelor,8,Real Estate,2024-03-12,2024-04-02,1772,9.7,Cognitive Computing +AI12410,Data Scientist,74836,USD,74836,MI,PT,South Korea,M,Singapore,100,"Statistics, NLP, GCP",Associate,2,Telecommunications,2024-08-19,2024-09-23,571,8.7,Neural Networks Co +AI12411,Machine Learning Engineer,169620,EUR,144177,EX,CT,Netherlands,S,Hungary,100,"Java, Git, Hadoop, Docker",PhD,14,Education,2024-10-07,2024-12-17,2161,6,Cognitive Computing +AI12412,AI Software Engineer,113721,CHF,102349,EN,CT,Switzerland,L,Russia,100,"Java, Python, Statistics, Azure",PhD,1,Automotive,2025-03-08,2025-04-10,2083,8.3,Cognitive Computing +AI12413,Head of AI,127743,CHF,114969,MI,FT,Switzerland,S,Austria,0,"SQL, Mathematics, NLP, Spark, Python",PhD,4,Consulting,2024-11-21,2024-12-07,527,8.6,Quantum Computing Inc +AI12414,Principal Data Scientist,305463,USD,305463,EX,FL,Norway,M,Belgium,50,"Scala, Linux, Computer Vision, Tableau, Java",PhD,13,Media,2024-11-13,2024-12-16,1809,5.9,DataVision Ltd +AI12415,AI Specialist,75828,USD,75828,SE,FT,South Korea,S,Indonesia,100,"Scala, GCP, Spark, Java, Mathematics",PhD,6,Education,2024-03-12,2024-04-26,909,8.5,DeepTech Ventures +AI12416,Data Scientist,116542,GBP,87407,SE,FT,United Kingdom,S,United Kingdom,0,"Docker, Linux, AWS, GCP",Master,7,Technology,2024-05-31,2024-07-31,749,5.4,Machine Intelligence Group +AI12417,Deep Learning Engineer,53985,USD,53985,EN,CT,Finland,M,Finland,0,"Java, Tableau, SQL, GCP",Master,0,Retail,2024-05-19,2024-07-09,1864,5.6,Machine Intelligence Group +AI12418,Computer Vision Engineer,60582,EUR,51495,EN,FT,Netherlands,S,Netherlands,100,"Python, Kubernetes, PyTorch, MLOps",Associate,1,Media,2024-04-10,2024-05-02,2394,6.1,Cognitive Computing +AI12419,Machine Learning Engineer,135425,USD,135425,SE,FL,Norway,S,Norway,100,"PyTorch, Linux, Java, R, Git",Associate,6,Energy,2024-07-24,2024-10-04,1969,5.9,Neural Networks Co +AI12420,AI Specialist,62590,JPY,6884900,EN,CT,Japan,L,Japan,100,"Kubernetes, Java, Hadoop",Bachelor,0,Technology,2024-01-07,2024-02-26,2155,9.5,Smart Analytics +AI12421,AI Architect,231935,GBP,173951,EX,PT,United Kingdom,S,United Kingdom,0,"Scala, Spark, R",Bachelor,11,Retail,2024-03-18,2024-05-29,1567,8.6,Neural Networks Co +AI12422,Machine Learning Researcher,71430,USD,71430,EN,FL,Norway,S,Singapore,0,"Python, Statistics, Data Visualization, AWS",Associate,0,Education,2024-03-30,2024-06-01,1777,6.7,Advanced Robotics +AI12423,Computer Vision Engineer,220600,EUR,187510,EX,FT,France,L,France,0,"Java, TensorFlow, Statistics, Computer Vision",PhD,10,Healthcare,2024-10-19,2024-12-04,1423,9.7,Predictive Systems +AI12424,Head of AI,82694,USD,82694,EN,FT,Norway,S,Norway,50,"Python, Mathematics, Azure",Bachelor,1,Gaming,2024-04-06,2024-05-10,1192,9.6,DeepTech Ventures +AI12425,Robotics Engineer,123932,USD,123932,MI,PT,Sweden,L,Belgium,100,"Python, PyTorch, GCP",Master,3,Education,2024-10-30,2024-12-07,1401,6.8,Smart Analytics +AI12426,AI Consultant,137592,EUR,116953,SE,FT,Germany,M,Germany,100,"Kubernetes, AWS, Data Visualization",Associate,7,Automotive,2025-01-18,2025-03-07,1087,9.8,Predictive Systems +AI12427,Machine Learning Engineer,57950,USD,57950,EN,FL,South Korea,S,South Korea,100,"Tableau, Scala, Python, Deep Learning",PhD,1,Energy,2025-03-05,2025-04-08,2003,8.6,Neural Networks Co +AI12428,AI Architect,126435,USD,126435,SE,FT,Israel,S,Israel,0,"PyTorch, SQL, Linux",Bachelor,5,Real Estate,2024-12-21,2025-02-08,2132,5.6,Algorithmic Solutions +AI12429,Machine Learning Researcher,128267,JPY,14109370,SE,CT,Japan,M,Japan,50,"PyTorch, GCP, TensorFlow, Azure, Python",Bachelor,8,Transportation,2025-04-10,2025-05-17,2324,5.4,Autonomous Tech +AI12430,AI Research Scientist,309048,SGD,401762,EX,PT,Singapore,L,Singapore,50,"MLOps, Data Visualization, Java, Linux, R",PhD,12,Finance,2025-04-07,2025-05-31,1545,8.1,Neural Networks Co +AI12431,Data Analyst,134105,JPY,14751550,SE,FL,Japan,L,Japan,0,"Python, MLOps, Spark, NLP, Kubernetes",Bachelor,6,Education,2024-03-17,2024-05-23,2363,10,DeepTech Ventures +AI12432,AI Software Engineer,84521,USD,84521,MI,FT,Israel,S,Israel,0,"GCP, AWS, NLP, Python, Spark",PhD,4,Retail,2024-02-20,2024-04-29,1050,8.6,Smart Analytics +AI12433,Research Scientist,61395,SGD,79814,EN,CT,Singapore,M,Singapore,50,"Statistics, Tableau, NLP",Master,1,Real Estate,2024-04-29,2024-07-05,1577,9.7,Machine Intelligence Group +AI12434,NLP Engineer,152906,USD,152906,SE,CT,Norway,S,Norway,50,"R, GCP, Computer Vision, Linux",Master,6,Technology,2025-04-27,2025-06-19,2345,6.9,TechCorp Inc +AI12435,AI Research Scientist,150492,USD,150492,EX,FT,Israel,S,Switzerland,50,"Linux, TensorFlow, SQL, Deep Learning",Bachelor,18,Transportation,2024-10-24,2024-11-26,2445,5.1,DataVision Ltd +AI12436,Head of AI,261388,SGD,339804,EX,FT,Singapore,M,Singapore,0,"Java, Python, NLP, Docker",Master,10,Healthcare,2025-02-23,2025-04-23,1326,8.3,AI Innovations +AI12437,AI Software Engineer,181176,USD,181176,EX,CT,Finland,S,South Africa,50,"Computer Vision, Linux, Hadoop, Kubernetes, Scala",Bachelor,11,Real Estate,2024-11-22,2025-01-08,1295,6.7,Cognitive Computing +AI12438,Robotics Engineer,185060,EUR,157301,EX,FT,Germany,M,Germany,100,"R, Spark, SQL, Mathematics, Java",Bachelor,12,Media,2024-07-13,2024-08-14,1670,7.3,Neural Networks Co +AI12439,Data Scientist,128763,SGD,167392,SE,PT,Singapore,L,Singapore,100,"Python, Statistics, PyTorch, Spark",Associate,5,Education,2024-11-10,2024-12-24,1042,9,Cloud AI Solutions +AI12440,AI Software Engineer,125753,USD,125753,MI,FL,Denmark,M,Malaysia,50,"Scala, R, Kubernetes, Git, Python",Master,3,Education,2024-11-24,2024-12-11,2160,6.6,Neural Networks Co +AI12441,Data Scientist,121075,USD,121075,SE,FT,Israel,S,Israel,0,"PyTorch, Scala, Deep Learning, MLOps",PhD,6,Consulting,2024-12-24,2025-01-29,1737,5.8,Autonomous Tech +AI12442,ML Ops Engineer,27334,USD,27334,EN,CT,India,M,India,0,"Kubernetes, PyTorch, Statistics, Computer Vision, TensorFlow",PhD,1,Education,2025-04-01,2025-06-09,1734,8.9,Quantum Computing Inc +AI12443,Computer Vision Engineer,234245,CHF,210821,SE,FT,Switzerland,L,Egypt,50,"PyTorch, SQL, Git, Statistics, GCP",Associate,5,Media,2024-02-08,2024-04-13,2405,9.8,DataVision Ltd +AI12444,AI Software Engineer,79787,USD,79787,EN,FT,Norway,S,Norway,50,"TensorFlow, Tableau, AWS, MLOps",Associate,0,Government,2025-04-27,2025-06-17,695,6.3,Algorithmic Solutions +AI12445,Head of AI,46395,USD,46395,EN,FT,Sweden,S,Sweden,100,"PyTorch, Java, Git, Azure",Bachelor,0,Manufacturing,2024-10-19,2024-12-23,1792,5.6,Cognitive Computing +AI12446,AI Consultant,82377,EUR,70020,EN,CT,Austria,L,Poland,50,"TensorFlow, Python, Tableau",Bachelor,0,Healthcare,2024-02-20,2024-05-02,1384,7.5,Smart Analytics +AI12447,Machine Learning Engineer,63540,CAD,79425,EN,CT,Canada,M,Canada,0,"SQL, NLP, Kubernetes, Git",Associate,0,Energy,2024-12-19,2025-01-08,1756,6.7,Advanced Robotics +AI12448,NLP Engineer,90047,USD,90047,EX,PT,China,M,China,100,"SQL, Deep Learning, Spark, R, Tableau",Bachelor,18,Telecommunications,2025-04-22,2025-06-01,1548,9.9,Predictive Systems +AI12449,Head of AI,108278,USD,108278,SE,PT,Sweden,M,Sweden,50,"PyTorch, Git, Mathematics, Scala",Bachelor,5,Manufacturing,2024-05-13,2024-05-31,1662,8.1,Cognitive Computing +AI12450,Machine Learning Engineer,255205,JPY,28072550,EX,CT,Japan,L,Japan,100,"R, Mathematics, Linux",Bachelor,17,Technology,2024-09-12,2024-10-16,1755,5.2,Algorithmic Solutions +AI12451,Machine Learning Engineer,63780,USD,63780,SE,PT,China,M,China,100,"PyTorch, Computer Vision, Tableau",Associate,8,Energy,2024-08-13,2024-10-04,1419,6.3,Predictive Systems +AI12452,Machine Learning Researcher,57335,GBP,43001,EN,FT,United Kingdom,S,Belgium,50,"Git, Mathematics, MLOps, Deep Learning, R",PhD,0,Retail,2024-01-31,2024-03-11,814,10,Neural Networks Co +AI12453,AI Consultant,68846,USD,68846,EN,PT,Finland,M,Finland,50,"Scala, Tableau, Deep Learning",PhD,1,Gaming,2025-02-18,2025-03-12,2445,7.5,DataVision Ltd +AI12454,Autonomous Systems Engineer,127642,EUR,108496,SE,CT,Netherlands,L,India,50,"MLOps, TensorFlow, AWS, Hadoop",Master,6,Technology,2025-04-24,2025-07-04,1015,7.5,Machine Intelligence Group +AI12455,Data Engineer,119425,USD,119425,SE,PT,Ireland,M,Nigeria,0,"Hadoop, Python, MLOps",Associate,9,Education,2025-04-15,2025-05-14,1732,5.9,Advanced Robotics +AI12456,Data Scientist,29224,USD,29224,EN,PT,China,S,China,0,"Data Visualization, Scala, Kubernetes, SQL, R",Associate,0,Finance,2024-12-08,2024-12-28,2189,9.1,Predictive Systems +AI12457,Computer Vision Engineer,198486,EUR,168713,EX,PT,Austria,M,Austria,100,"TensorFlow, Azure, NLP, Computer Vision",Associate,13,Telecommunications,2024-07-25,2024-09-25,1275,8.2,Advanced Robotics +AI12458,Machine Learning Engineer,203533,CHF,183180,EX,FT,Switzerland,S,Switzerland,0,"GCP, SQL, PyTorch, Kubernetes, Statistics",Bachelor,14,Technology,2025-04-24,2025-05-20,696,6.6,TechCorp Inc +AI12459,AI Product Manager,194939,EUR,165698,EX,FL,France,L,France,50,"Linux, Mathematics, NLP, PyTorch",Bachelor,10,Telecommunications,2024-03-26,2024-05-07,1719,6.7,Algorithmic Solutions +AI12460,Data Analyst,61708,EUR,52452,EN,PT,Germany,S,Germany,50,"Hadoop, Python, Git",Bachelor,1,Manufacturing,2024-05-22,2024-06-14,629,7.5,DataVision Ltd +AI12461,AI Research Scientist,100793,USD,100793,MI,FL,Ireland,L,Ireland,50,"Linux, Hadoop, R, Computer Vision, Statistics",Master,4,Gaming,2024-05-29,2024-08-09,2070,9,Advanced Robotics +AI12462,AI Architect,75694,GBP,56771,EN,PT,United Kingdom,M,Austria,0,"Statistics, PyTorch, Docker, Azure, SQL",Associate,0,Manufacturing,2025-01-06,2025-02-11,2171,8.3,Cognitive Computing +AI12463,Data Scientist,115446,EUR,98129,MI,FL,Netherlands,L,Netherlands,50,"Docker, Python, Deep Learning, Spark",Associate,2,Transportation,2024-07-21,2024-08-23,2121,7.9,Smart Analytics +AI12464,Research Scientist,49167,EUR,41792,EN,FT,Austria,S,Austria,100,"R, Mathematics, Hadoop",Associate,0,Automotive,2024-07-10,2024-08-10,614,8.4,DataVision Ltd +AI12465,AI Product Manager,70180,USD,70180,EN,FL,Sweden,S,Sweden,0,"Docker, R, Deep Learning, SQL",Master,1,Government,2024-03-23,2024-05-12,580,7.5,DeepTech Ventures +AI12466,Data Analyst,19503,USD,19503,EN,CT,India,S,India,0,"PyTorch, Azure, R, SQL",Bachelor,0,Education,2025-03-12,2025-03-26,2448,5.9,Digital Transformation LLC +AI12467,Data Engineer,92958,USD,92958,SE,FT,South Korea,M,South Korea,0,"Azure, SQL, Kubernetes, Spark, Linux",Associate,7,Government,2024-03-19,2024-04-03,1193,6.8,AI Innovations +AI12468,ML Ops Engineer,46075,USD,46075,EX,CT,India,S,India,50,"Scala, NLP, Git",Bachelor,17,Media,2024-10-06,2024-11-30,1655,10,Algorithmic Solutions +AI12469,Data Engineer,31356,USD,31356,MI,FT,China,S,China,0,"Mathematics, Python, Tableau, Computer Vision, SQL",Bachelor,4,Real Estate,2025-03-05,2025-04-06,857,7.5,AI Innovations +AI12470,Data Engineer,169277,EUR,143885,EX,FL,Austria,M,Vietnam,0,"SQL, Git, PyTorch, NLP",Master,12,Media,2024-08-17,2024-10-27,664,7.8,Smart Analytics +AI12471,Machine Learning Engineer,34533,USD,34533,MI,CT,China,M,China,100,"AWS, Tableau, TensorFlow, Spark",PhD,3,Government,2024-04-18,2024-05-15,1855,8.2,DataVision Ltd +AI12472,Deep Learning Engineer,72285,JPY,7951350,EN,FL,Japan,S,Japan,50,"Linux, MLOps, Git, Java",PhD,0,Healthcare,2024-09-24,2024-10-28,1564,7.9,Machine Intelligence Group +AI12473,Machine Learning Researcher,212718,USD,212718,EX,CT,Finland,S,Finland,50,"SQL, Python, Hadoop, Mathematics, Computer Vision",PhD,17,Education,2025-04-05,2025-06-06,2270,8.6,Machine Intelligence Group +AI12474,Machine Learning Engineer,202624,EUR,172230,EX,CT,France,S,France,50,"PyTorch, Hadoop, TensorFlow, SQL",PhD,16,Finance,2024-12-30,2025-01-13,1686,7.2,Machine Intelligence Group +AI12475,ML Ops Engineer,71740,USD,71740,MI,CT,South Korea,L,South Korea,50,"SQL, AWS, Computer Vision, Spark, Linux",Associate,3,Automotive,2025-04-06,2025-05-13,756,9.9,Cloud AI Solutions +AI12476,Autonomous Systems Engineer,232339,CHF,209105,EX,CT,Switzerland,L,Switzerland,0,"AWS, Python, Kubernetes",Master,18,Retail,2024-12-07,2025-01-25,1266,7.2,AI Innovations +AI12477,Machine Learning Engineer,147817,USD,147817,EX,CT,Israel,S,India,0,"Scala, R, SQL",Bachelor,15,Telecommunications,2024-12-13,2025-01-18,1399,6.3,Future Systems +AI12478,Data Engineer,73011,EUR,62059,MI,PT,Germany,S,Germany,50,"SQL, Scala, Tableau",Associate,3,Education,2024-11-22,2024-12-16,1245,7.3,Cognitive Computing +AI12479,ML Ops Engineer,69151,USD,69151,EN,CT,Israel,M,Israel,100,"PyTorch, Python, Statistics",PhD,0,Technology,2024-06-09,2024-08-07,1621,6.5,Digital Transformation LLC +AI12480,Machine Learning Engineer,200050,CHF,180045,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Data Visualization, Statistics, Git",Associate,5,Transportation,2024-05-24,2024-07-16,982,5.5,Autonomous Tech +AI12481,Data Engineer,68571,AUD,92571,MI,FL,Australia,S,Romania,0,"MLOps, Azure, Tableau",Bachelor,3,Consulting,2025-04-10,2025-05-15,578,9.6,DataVision Ltd +AI12482,AI Specialist,27494,USD,27494,EN,FL,China,S,Brazil,50,"Python, Azure, Git, R, Computer Vision",PhD,0,Finance,2024-10-05,2024-11-07,1180,9.1,Cloud AI Solutions +AI12483,AI Research Scientist,54178,USD,54178,SE,CT,China,M,United States,100,"Linux, Scala, PyTorch",PhD,5,Healthcare,2025-04-02,2025-05-31,1625,7.5,Advanced Robotics +AI12484,Robotics Engineer,147943,USD,147943,SE,CT,Denmark,M,Denmark,0,"GCP, Python, Mathematics, Linux",Bachelor,9,Finance,2025-03-19,2025-04-15,1829,6.6,Cloud AI Solutions +AI12485,Research Scientist,246165,CHF,221549,SE,FT,Switzerland,L,Switzerland,50,"Deep Learning, Data Visualization, Docker",Associate,8,Transportation,2024-08-13,2024-09-19,1412,6.4,DataVision Ltd +AI12486,Autonomous Systems Engineer,31203,USD,31203,MI,FT,India,M,India,50,"Data Visualization, SQL, Scala, Tableau, Git",Bachelor,2,Energy,2024-02-27,2024-04-03,1073,5.4,Digital Transformation LLC +AI12487,Head of AI,109051,USD,109051,SE,PT,South Korea,S,South Korea,100,"Scala, AWS, Python",Master,7,Technology,2024-11-09,2024-12-11,1828,7.7,DataVision Ltd +AI12488,AI Consultant,76767,EUR,65252,EN,FL,Netherlands,M,Romania,100,"Tableau, Scala, Docker",Associate,0,Transportation,2024-08-22,2024-10-22,1011,5.9,TechCorp Inc +AI12489,Computer Vision Engineer,64846,GBP,48635,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Scala, TensorFlow",Master,0,Gaming,2024-10-08,2024-12-06,621,6.9,TechCorp Inc +AI12490,Data Engineer,126205,AUD,170377,SE,FT,Australia,L,Australia,100,"Spark, Linux, GCP",Associate,7,Real Estate,2024-01-19,2024-03-08,2036,6.5,Future Systems +AI12491,Data Engineer,162483,USD,162483,MI,PT,Norway,L,Norway,100,"Java, Statistics, R, Docker, Scala",Master,3,Consulting,2024-12-17,2025-02-02,1825,8.3,DeepTech Ventures +AI12492,Machine Learning Engineer,77554,USD,77554,MI,CT,Israel,S,Israel,50,"Azure, AWS, TensorFlow, Linux, Mathematics",Master,3,Education,2024-10-26,2024-11-30,807,5.5,Algorithmic Solutions +AI12493,AI Product Manager,216415,JPY,23805650,EX,FT,Japan,L,Japan,0,"Scala, Python, Hadoop, Git",Master,14,Transportation,2024-01-20,2024-02-15,1804,7.5,Future Systems +AI12494,AI Architect,130182,EUR,110655,SE,FL,Germany,S,Germany,50,"SQL, TensorFlow, GCP",Bachelor,9,Education,2025-03-27,2025-05-17,662,5.9,Machine Intelligence Group +AI12495,Data Scientist,187797,SGD,244136,EX,FL,Singapore,S,Singapore,100,"R, MLOps, Kubernetes, Statistics, Deep Learning",PhD,18,Healthcare,2024-06-30,2024-09-03,799,5.2,Advanced Robotics +AI12496,AI Software Engineer,123365,USD,123365,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Mathematics, TensorFlow, AWS",Associate,4,Manufacturing,2025-01-20,2025-03-24,1723,5.6,Quantum Computing Inc +AI12497,Data Analyst,69926,EUR,59437,EN,FT,Austria,L,Austria,50,"GCP, MLOps, Statistics",Master,1,Real Estate,2024-04-23,2024-06-20,2381,7.5,Cognitive Computing +AI12498,AI Architect,80574,GBP,60431,EN,FT,United Kingdom,M,Poland,50,"Python, Deep Learning, Kubernetes",Associate,0,Finance,2024-07-31,2024-08-23,2300,6.7,Neural Networks Co +AI12499,Computer Vision Engineer,80148,USD,80148,EN,CT,United States,S,United States,50,"Kubernetes, TensorFlow, Computer Vision, Hadoop, Linux",PhD,1,Transportation,2024-10-28,2024-12-23,1220,6.7,DataVision Ltd +AI12500,Machine Learning Engineer,270850,EUR,230223,EX,CT,Germany,L,Indonesia,100,"Statistics, Python, Data Visualization, Scala",Associate,11,Gaming,2025-02-04,2025-03-09,1919,9.5,Neural Networks Co +AI12501,Deep Learning Engineer,160933,CHF,144840,SE,CT,Switzerland,M,Switzerland,100,"Docker, R, Mathematics, Spark, Azure",PhD,7,Energy,2024-03-19,2024-04-19,2404,8,DataVision Ltd +AI12502,Machine Learning Researcher,165119,USD,165119,EX,FT,Ireland,M,Ireland,0,"Data Visualization, Hadoop, Python, Linux",Bachelor,16,Energy,2024-02-05,2024-02-27,709,5.5,Cognitive Computing +AI12503,Deep Learning Engineer,145099,EUR,123334,SE,PT,Germany,L,Germany,50,"GCP, Linux, Tableau, Spark, Data Visualization",Master,7,Media,2025-03-11,2025-05-07,717,6.9,Smart Analytics +AI12504,NLP Engineer,51742,JPY,5691620,EN,FL,Japan,S,Japan,100,"Kubernetes, Python, Data Visualization, Git",PhD,1,Education,2024-02-28,2024-03-19,1536,8.3,Autonomous Tech +AI12505,AI Software Engineer,109327,USD,109327,SE,CT,Sweden,M,Sweden,50,"Docker, MLOps, AWS",PhD,9,Consulting,2024-07-03,2024-07-24,1297,9,DataVision Ltd +AI12506,AI Specialist,151570,CHF,136413,MI,PT,Switzerland,M,Switzerland,100,"Tableau, Kubernetes, TensorFlow, Spark",Master,2,Government,2024-05-27,2024-07-18,2059,7.2,Advanced Robotics +AI12507,Deep Learning Engineer,214037,USD,214037,EX,PT,Sweden,S,Sweden,0,"Mathematics, Computer Vision, Linux",Master,19,Government,2024-03-18,2024-04-11,1865,9.1,Advanced Robotics +AI12508,AI Product Manager,238972,USD,238972,EX,CT,Finland,L,Finland,0,"GCP, Hadoop, Tableau, Deep Learning",Master,18,Healthcare,2024-01-10,2024-02-29,1350,9.8,Predictive Systems +AI12509,Data Analyst,120788,EUR,102670,SE,PT,Germany,L,Germany,50,"Spark, Linux, Deep Learning, Git, TensorFlow",Associate,7,Retail,2024-07-24,2024-09-15,606,8.3,Cognitive Computing +AI12510,AI Product Manager,161084,USD,161084,SE,FT,United States,L,Spain,0,"Linux, Tableau, Data Visualization, Hadoop",Bachelor,7,Telecommunications,2024-01-23,2024-03-16,1681,8,Future Systems +AI12511,AI Specialist,224471,CAD,280589,EX,PT,Canada,M,Canada,100,"SQL, NLP, Azure",Master,17,Government,2024-12-04,2025-02-02,2031,5.4,Neural Networks Co +AI12512,Robotics Engineer,162992,AUD,220039,SE,CT,Australia,L,South Korea,100,"R, NLP, Linux, SQL",Bachelor,8,Government,2024-08-22,2024-09-27,746,6.8,Future Systems +AI12513,Data Analyst,30696,USD,30696,EN,CT,China,S,Portugal,0,"GCP, NLP, Linux, R",Master,0,Media,2024-10-08,2024-11-14,1377,9.1,Algorithmic Solutions +AI12514,Research Scientist,98339,EUR,83588,SE,CT,Austria,M,Austria,0,"PyTorch, R, TensorFlow",Associate,5,Retail,2025-03-28,2025-06-07,1314,5.7,Neural Networks Co +AI12515,Research Scientist,129262,EUR,109873,SE,CT,Austria,M,Austria,0,"Python, Azure, Docker, R, Git",PhD,7,Energy,2024-01-08,2024-02-05,2298,8.5,Autonomous Tech +AI12516,Machine Learning Engineer,112931,CAD,141164,SE,PT,Canada,L,Canada,0,"Python, Tableau, Docker",Associate,8,Consulting,2024-12-14,2025-01-25,2110,6.5,Cognitive Computing +AI12517,AI Product Manager,109950,USD,109950,MI,FT,Ireland,L,Estonia,0,"Azure, AWS, Linux, Docker",Associate,3,Media,2024-07-25,2024-09-12,1158,8.2,Autonomous Tech +AI12518,Computer Vision Engineer,84503,EUR,71828,EN,FT,Germany,L,Germany,0,"R, Linux, NLP",PhD,1,Gaming,2024-04-19,2024-06-20,1765,5.6,Smart Analytics +AI12519,Principal Data Scientist,89243,USD,89243,MI,FL,Sweden,M,South Africa,100,"Azure, Data Visualization, Kubernetes, Docker",PhD,3,Retail,2024-11-09,2024-12-14,592,8,Predictive Systems +AI12520,Data Analyst,194683,CHF,175215,SE,FL,Switzerland,M,Switzerland,100,"Hadoop, SQL, Linux, Scala",PhD,8,Real Estate,2024-03-03,2024-05-11,2107,7.7,Autonomous Tech +AI12521,Data Scientist,34111,USD,34111,MI,PT,China,S,China,50,"Statistics, AWS, R",Master,2,Telecommunications,2024-08-10,2024-09-03,870,6.5,AI Innovations +AI12522,NLP Engineer,104286,SGD,135572,MI,PT,Singapore,L,Singapore,100,"MLOps, Docker, Java, Spark",PhD,4,Finance,2024-04-19,2024-06-07,2023,8.2,Cognitive Computing +AI12523,Research Scientist,87236,EUR,74151,MI,FL,Germany,M,Germany,100,"Java, Hadoop, Python, Spark, TensorFlow",Associate,3,Technology,2024-02-23,2024-04-13,1927,9.6,DataVision Ltd +AI12524,Head of AI,61002,EUR,51852,EN,PT,Germany,L,Germany,50,"Computer Vision, Kubernetes, Hadoop",Master,1,Media,2024-07-14,2024-07-31,2002,5.9,Advanced Robotics +AI12525,Autonomous Systems Engineer,131108,GBP,98331,MI,FL,United Kingdom,L,United Kingdom,100,"AWS, MLOps, Tableau",PhD,3,Government,2024-02-18,2024-04-21,1902,5.8,TechCorp Inc +AI12526,NLP Engineer,109470,GBP,82103,MI,PT,United Kingdom,L,Egypt,100,"Python, TensorFlow, Statistics",Master,3,Media,2025-03-03,2025-05-01,1242,6.5,Autonomous Tech +AI12527,AI Consultant,63355,GBP,47516,EN,FT,United Kingdom,S,United Kingdom,50,"PyTorch, Linux, Python, Scala",Bachelor,0,Healthcare,2024-07-12,2024-09-09,1354,9.1,DataVision Ltd +AI12528,Data Engineer,199949,EUR,169957,EX,PT,Austria,M,Austria,50,"Git, Spark, GCP",Master,17,Retail,2024-08-30,2024-11-10,1410,8.9,TechCorp Inc +AI12529,Principal Data Scientist,59401,CAD,74251,EN,FL,Canada,S,Portugal,50,"Git, SQL, Scala",PhD,0,Energy,2024-04-27,2024-05-16,2043,9.9,Algorithmic Solutions +AI12530,Head of AI,100922,USD,100922,MI,PT,South Korea,L,South Korea,100,"Python, Git, SQL, Java, Computer Vision",PhD,3,Real Estate,2024-12-21,2025-02-20,2101,8,Machine Intelligence Group +AI12531,Data Analyst,64014,USD,64014,EN,FT,Israel,M,Israel,50,"SQL, PyTorch, Computer Vision, Git",Master,1,Finance,2024-08-01,2024-08-16,2168,8.9,Predictive Systems +AI12532,AI Consultant,164409,AUD,221952,SE,CT,Australia,L,Canada,0,"Kubernetes, PyTorch, Mathematics, SQL, Tableau",Master,6,Gaming,2024-08-30,2024-11-01,2111,7.2,Digital Transformation LLC +AI12533,NLP Engineer,214487,EUR,182314,EX,FL,France,M,France,100,"Kubernetes, SQL, PyTorch",Master,11,Government,2024-09-29,2024-11-04,1748,8.5,Cloud AI Solutions +AI12534,Autonomous Systems Engineer,133642,USD,133642,MI,PT,Norway,L,Norway,100,"Scala, Statistics, Spark",Master,4,Manufacturing,2024-05-25,2024-07-13,850,7.5,Predictive Systems +AI12535,AI Software Engineer,93357,USD,93357,EN,CT,United States,L,United States,0,"Computer Vision, NLP, Tableau, Python",PhD,1,Healthcare,2024-06-28,2024-08-07,1914,7.6,TechCorp Inc +AI12536,Robotics Engineer,68512,USD,68512,SE,FL,China,M,China,0,"Linux, MLOps, AWS, Statistics",PhD,9,Technology,2024-12-11,2025-01-29,1339,8,Algorithmic Solutions +AI12537,AI Specialist,134492,USD,134492,MI,PT,Denmark,M,Denmark,50,"MLOps, GCP, Java, Hadoop",Master,4,Retail,2024-02-21,2024-03-23,2035,5.2,AI Innovations +AI12538,Autonomous Systems Engineer,131311,JPY,14444210,SE,CT,Japan,M,Vietnam,0,"Scala, R, Azure, Git, Kubernetes",Associate,5,Manufacturing,2024-08-10,2024-09-23,1940,8.9,DeepTech Ventures +AI12539,Principal Data Scientist,255914,GBP,191936,EX,PT,United Kingdom,M,South Korea,0,"Git, Kubernetes, NLP",PhD,15,Gaming,2025-01-29,2025-03-25,1748,7.6,Machine Intelligence Group +AI12540,ML Ops Engineer,49654,USD,49654,EN,FT,Ireland,S,Ireland,100,"Scala, Linux, SQL, Statistics",PhD,0,Real Estate,2024-04-14,2024-06-16,2019,7.4,Predictive Systems +AI12541,AI Architect,47136,USD,47136,EN,CT,Israel,S,Israel,0,"PyTorch, SQL, Docker, AWS, Linux",PhD,1,Technology,2024-05-06,2024-06-21,721,9,Quantum Computing Inc +AI12542,AI Research Scientist,42011,USD,42011,MI,FT,India,L,India,50,"Computer Vision, Java, Python, Azure, Git",Master,3,Real Estate,2024-01-15,2024-02-12,1652,8.1,DataVision Ltd +AI12543,AI Consultant,119147,USD,119147,MI,FL,Finland,L,Russia,100,"Java, PyTorch, MLOps, Hadoop, NLP",Associate,4,Consulting,2024-04-21,2024-05-23,1670,7.3,DeepTech Ventures +AI12544,ML Ops Engineer,98976,USD,98976,MI,CT,United States,S,Mexico,50,"Computer Vision, TensorFlow, Python, Git, R",Bachelor,2,Consulting,2024-10-22,2024-12-31,613,6.7,Smart Analytics +AI12545,Autonomous Systems Engineer,50267,EUR,42727,EN,FT,Germany,S,Philippines,100,"Spark, TensorFlow, Kubernetes, Java, Mathematics",Master,1,Real Estate,2025-04-25,2025-05-25,1081,8.6,Machine Intelligence Group +AI12546,Robotics Engineer,26722,USD,26722,EN,FT,China,S,China,0,"Git, SQL, R, GCP",Bachelor,0,Consulting,2024-10-13,2024-11-11,2251,6.1,Digital Transformation LLC +AI12547,ML Ops Engineer,131283,GBP,98462,SE,CT,United Kingdom,M,Thailand,50,"Tableau, TensorFlow, Docker, GCP, Scala",Bachelor,6,Telecommunications,2024-04-07,2024-05-30,2032,8.5,Cognitive Computing +AI12548,AI Product Manager,117952,SGD,153338,SE,FL,Singapore,M,France,50,"MLOps, SQL, Python, Computer Vision",PhD,5,Technology,2024-04-25,2024-06-10,2174,5.7,AI Innovations +AI12549,Deep Learning Engineer,25607,USD,25607,MI,PT,India,M,Ukraine,100,"PyTorch, Linux, Tableau, GCP",Bachelor,2,Media,2024-12-30,2025-01-17,518,6.9,Digital Transformation LLC +AI12550,Deep Learning Engineer,233172,USD,233172,EX,PT,United States,M,Netherlands,50,"SQL, Tableau, Deep Learning, Java",PhD,18,Telecommunications,2024-04-30,2024-06-19,802,6,TechCorp Inc +AI12551,Data Analyst,74780,AUD,100953,EN,PT,Australia,L,Australia,100,"AWS, GCP, Kubernetes",Bachelor,1,Consulting,2025-03-04,2025-03-24,1215,8.9,Quantum Computing Inc +AI12552,AI Research Scientist,166556,CHF,149900,SE,FT,Switzerland,L,Australia,0,"NLP, R, Scala",Bachelor,7,Finance,2024-09-15,2024-10-14,911,7.1,Advanced Robotics +AI12553,AI Research Scientist,332451,USD,332451,EX,CT,United States,L,United States,50,"Spark, Hadoop, PyTorch",Associate,17,Technology,2024-12-15,2025-01-03,1752,8.2,Advanced Robotics +AI12554,Research Scientist,226551,CHF,203896,SE,FL,Switzerland,L,Switzerland,0,"R, Python, Tableau, Deep Learning",Bachelor,9,Retail,2024-02-08,2024-03-21,1144,9,Advanced Robotics +AI12555,AI Consultant,182206,USD,182206,EX,PT,Sweden,M,Sweden,50,"SQL, Java, Tableau, Statistics, PyTorch",Master,18,Media,2024-09-21,2024-11-02,1591,7.5,Machine Intelligence Group +AI12556,AI Consultant,155691,EUR,132337,SE,CT,Austria,L,Brazil,100,"Hadoop, TensorFlow, GCP, Spark",PhD,6,Telecommunications,2025-01-12,2025-02-16,568,7.4,Smart Analytics +AI12557,Machine Learning Researcher,69981,USD,69981,EN,PT,Sweden,S,Sweden,50,"Python, Deep Learning, TensorFlow, Scala",Master,0,Technology,2024-03-27,2024-06-04,809,5.3,Cognitive Computing +AI12558,Computer Vision Engineer,115602,USD,115602,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Git, Tableau, Statistics, Scala",Associate,2,Consulting,2024-07-31,2024-09-20,2388,7.9,Autonomous Tech +AI12559,Data Analyst,65661,GBP,49246,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, NLP, Kubernetes",Associate,1,Automotive,2024-03-10,2024-04-01,2178,6.6,Future Systems +AI12560,ML Ops Engineer,54988,EUR,46740,EN,FL,France,M,France,100,"Hadoop, SQL, Deep Learning",Bachelor,1,Energy,2024-06-20,2024-08-16,904,5.6,Machine Intelligence Group +AI12561,Deep Learning Engineer,255127,GBP,191345,EX,FT,United Kingdom,L,United Kingdom,0,"Git, PyTorch, Java",Associate,13,Healthcare,2024-01-15,2024-03-25,2312,7.5,Quantum Computing Inc +AI12562,NLP Engineer,60129,USD,60129,EN,CT,Finland,L,Finland,50,"AWS, PyTorch, TensorFlow",Associate,0,Real Estate,2024-01-12,2024-03-12,1811,6.7,Smart Analytics +AI12563,NLP Engineer,151050,USD,151050,EX,FT,Finland,M,Romania,100,"Git, PyTorch, Statistics, R",Bachelor,13,Technology,2024-07-08,2024-09-04,1605,7.8,Smart Analytics +AI12564,NLP Engineer,102467,EUR,87097,MI,FL,France,L,France,0,"PyTorch, Hadoop, Deep Learning, Statistics",PhD,3,Healthcare,2024-05-19,2024-07-26,2339,8.1,Future Systems +AI12565,AI Software Engineer,91655,USD,91655,MI,FL,Sweden,M,Sweden,50,"R, Linux, Spark, Scala, Python",Associate,3,Gaming,2024-09-13,2024-11-11,598,9.4,Digital Transformation LLC +AI12566,Machine Learning Engineer,114161,EUR,97037,MI,FT,France,L,France,50,"Java, Python, Spark",Master,2,Government,2024-11-30,2025-01-30,521,9.2,DeepTech Ventures +AI12567,Data Analyst,73257,EUR,62268,MI,CT,Austria,M,Austria,100,"AWS, PyTorch, Spark, Statistics",Bachelor,2,Education,2024-05-28,2024-07-25,1845,9.4,AI Innovations +AI12568,Computer Vision Engineer,108618,USD,108618,MI,FL,Israel,L,Israel,0,"Java, Docker, GCP, R",PhD,3,Finance,2024-01-18,2024-02-22,581,7.5,Predictive Systems +AI12569,AI Specialist,62843,USD,62843,EN,FL,Denmark,S,Denmark,50,"AWS, Azure, Mathematics, Docker, Kubernetes",Bachelor,1,Education,2024-02-23,2024-04-25,2065,6.3,Quantum Computing Inc +AI12570,Research Scientist,178712,EUR,151905,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, NLP, Docker, Spark",Bachelor,8,Finance,2025-02-22,2025-03-23,1151,8.8,Cloud AI Solutions +AI12571,Machine Learning Researcher,66399,USD,66399,EN,FT,Sweden,M,Sweden,0,"Deep Learning, Python, SQL, GCP, Hadoop",Bachelor,0,Consulting,2024-05-05,2024-06-23,1774,6.6,Algorithmic Solutions +AI12572,Deep Learning Engineer,26206,USD,26206,MI,PT,India,S,Australia,50,"PyTorch, Scala, Git, Data Visualization, Spark",Master,4,Gaming,2024-05-02,2024-06-25,2135,9.7,Smart Analytics +AI12573,Autonomous Systems Engineer,132926,CAD,166158,SE,CT,Canada,M,Canada,100,"R, Deep Learning, Hadoop",Bachelor,9,Healthcare,2024-12-05,2025-01-30,779,6.3,Advanced Robotics +AI12574,Machine Learning Researcher,212788,USD,212788,SE,FT,Norway,L,Spain,100,"Python, Statistics, TensorFlow, Tableau",PhD,9,Consulting,2025-02-24,2025-04-01,743,5.6,Algorithmic Solutions +AI12575,AI Specialist,38991,USD,38991,EN,FL,South Korea,S,South Korea,100,"Docker, Python, TensorFlow",Master,1,Telecommunications,2024-07-02,2024-08-15,955,9.8,Machine Intelligence Group +AI12576,AI Product Manager,50232,USD,50232,EN,PT,Israel,S,Israel,100,"Statistics, R, Data Visualization, Tableau, Deep Learning",PhD,1,Manufacturing,2025-01-07,2025-02-06,2141,7.2,Algorithmic Solutions +AI12577,AI Software Engineer,134499,USD,134499,EX,PT,Finland,M,Finland,50,"SQL, NLP, Spark, Python",PhD,13,Real Estate,2024-11-15,2024-12-05,1800,7.2,DataVision Ltd +AI12578,Research Scientist,148779,USD,148779,EX,PT,South Korea,L,South Korea,100,"R, Azure, Tableau, Docker",Associate,17,Telecommunications,2025-04-24,2025-05-20,2101,9.9,Future Systems +AI12579,Principal Data Scientist,70847,USD,70847,EN,FL,Norway,S,Norway,100,"R, Data Visualization, GCP",Associate,1,Energy,2024-10-23,2024-11-13,1102,9.5,Autonomous Tech +AI12580,AI Software Engineer,62204,USD,62204,EN,FT,Ireland,L,New Zealand,0,"AWS, NLP, Kubernetes, R",Associate,0,Manufacturing,2024-10-06,2024-12-09,1579,5.9,Algorithmic Solutions +AI12581,AI Software Engineer,129841,SGD,168793,EX,FT,Singapore,S,Singapore,100,"R, SQL, NLP, Azure, Python",Master,17,Finance,2024-01-01,2024-03-14,591,9.3,DataVision Ltd +AI12582,Data Analyst,155034,EUR,131779,SE,FT,Netherlands,M,Mexico,50,"TensorFlow, Python, MLOps, PyTorch, Tableau",Master,9,Healthcare,2024-11-14,2024-12-31,2353,9.2,Cognitive Computing +AI12583,AI Software Engineer,187509,JPY,20625990,EX,FL,Japan,S,Israel,100,"R, MLOps, Java, Statistics, TensorFlow",Master,15,Automotive,2024-05-13,2024-05-31,2287,9.4,Algorithmic Solutions +AI12584,AI Consultant,177222,EUR,150639,EX,FL,France,M,Colombia,50,"AWS, Git, NLP, Linux",Bachelor,10,Automotive,2025-02-25,2025-04-07,1455,7.7,DataVision Ltd +AI12585,ML Ops Engineer,333553,USD,333553,EX,FL,Norway,L,Norway,100,"TensorFlow, Python, MLOps, Java, R",PhD,17,Healthcare,2025-04-16,2025-06-27,638,9,Predictive Systems +AI12586,AI Product Manager,51703,EUR,43948,EN,PT,Germany,S,Luxembourg,100,"Linux, Docker, Git, R",Associate,1,Retail,2025-02-26,2025-04-15,914,6.4,Future Systems +AI12587,Data Analyst,161634,USD,161634,SE,FL,Israel,L,Israel,50,"Python, Azure, Mathematics",Bachelor,7,Retail,2025-02-22,2025-03-31,2194,7,AI Innovations +AI12588,AI Product Manager,166572,JPY,18322920,SE,FL,Japan,L,Japan,100,"Docker, Java, R, SQL, AWS",PhD,8,Retail,2024-09-17,2024-10-27,2063,9.2,Predictive Systems +AI12589,NLP Engineer,208798,USD,208798,EX,CT,Sweden,L,Indonesia,50,"Kubernetes, Data Visualization, TensorFlow",Master,19,Automotive,2024-12-02,2025-01-28,1995,5.2,AI Innovations +AI12590,Data Analyst,86613,USD,86613,MI,FL,Finland,L,Finland,100,"Git, GCP, Computer Vision, AWS, Hadoop",PhD,2,Manufacturing,2024-11-16,2024-12-04,1178,6.7,Neural Networks Co +AI12591,Machine Learning Engineer,117597,CHF,105837,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, Docker, Java",Bachelor,4,Automotive,2024-03-30,2024-04-20,2021,5.2,Machine Intelligence Group +AI12592,Data Analyst,22513,USD,22513,EN,CT,India,L,India,0,"Deep Learning, GCP, Mathematics, R",Associate,0,Telecommunications,2024-05-05,2024-06-20,1160,7.9,Future Systems +AI12593,Machine Learning Engineer,105654,SGD,137350,MI,CT,Singapore,L,Singapore,0,"Mathematics, Git, Scala, Linux",Bachelor,4,Education,2025-01-15,2025-02-03,938,9.7,Quantum Computing Inc +AI12594,AI Consultant,224641,SGD,292033,EX,FT,Singapore,L,Israel,100,"Linux, Java, Mathematics, Hadoop, SQL",Associate,12,Education,2024-09-20,2024-10-09,1957,6.6,Autonomous Tech +AI12595,Computer Vision Engineer,92817,USD,92817,MI,CT,Denmark,S,Denmark,100,"PyTorch, Linux, TensorFlow, R, Mathematics",Associate,4,Finance,2024-06-05,2024-06-23,1419,8.8,Neural Networks Co +AI12596,Deep Learning Engineer,87012,EUR,73960,EN,PT,Austria,L,Austria,100,"Linux, PyTorch, Computer Vision",Bachelor,1,Retail,2025-01-26,2025-02-20,2106,9.6,Autonomous Tech +AI12597,AI Product Manager,176978,USD,176978,EX,PT,Finland,S,New Zealand,100,"Hadoop, Docker, Linux",PhD,19,Automotive,2024-07-11,2024-08-06,776,8.9,Digital Transformation LLC +AI12598,AI Software Engineer,31871,USD,31871,MI,CT,India,L,India,0,"Statistics, Mathematics, TensorFlow",Associate,4,Transportation,2024-04-08,2024-06-08,905,7.7,Future Systems +AI12599,Data Engineer,111513,USD,111513,MI,FL,United States,S,Finland,0,"Kubernetes, Azure, Deep Learning, Data Visualization, SQL",Associate,3,Healthcare,2024-06-09,2024-06-23,901,7.5,AI Innovations +AI12600,Data Scientist,124502,EUR,105827,SE,CT,Austria,M,Austria,100,"Linux, Tableau, Python, Computer Vision, TensorFlow",Master,7,Retail,2024-03-07,2024-03-30,1777,6,DeepTech Ventures +AI12601,AI Architect,143750,EUR,122188,SE,CT,France,M,Brazil,50,"Java, AWS, Git",PhD,9,Finance,2024-06-10,2024-07-15,1569,9.6,Predictive Systems +AI12602,Deep Learning Engineer,107546,EUR,91414,SE,PT,Germany,M,Czech Republic,0,"Tableau, Python, PyTorch",Master,9,Finance,2025-02-20,2025-04-09,641,8.7,Quantum Computing Inc +AI12603,Research Scientist,208493,EUR,177219,EX,FL,Germany,L,Germany,100,"R, SQL, PyTorch",PhD,19,Manufacturing,2024-10-07,2024-11-03,615,6.4,AI Innovations +AI12604,Computer Vision Engineer,290203,USD,290203,EX,CT,Norway,M,Norway,100,"GCP, Python, SQL",Bachelor,18,Real Estate,2024-10-06,2024-11-20,1734,5.3,Autonomous Tech +AI12605,AI Product Manager,79948,USD,79948,MI,CT,Ireland,S,Israel,100,"Scala, Kubernetes, Computer Vision, Tableau, Docker",Bachelor,4,Healthcare,2025-02-15,2025-03-30,1869,9,AI Innovations +AI12606,AI Research Scientist,139049,CHF,125144,MI,FL,Switzerland,M,Canada,50,"Scala, Java, TensorFlow, Tableau",Master,3,Healthcare,2024-02-23,2024-04-12,1656,6.1,DeepTech Ventures +AI12607,NLP Engineer,123828,USD,123828,MI,FL,United States,L,Belgium,100,"Spark, Azure, MLOps, R, GCP",Bachelor,4,Automotive,2025-04-13,2025-05-20,1675,5.3,Quantum Computing Inc +AI12608,Research Scientist,125635,USD,125635,MI,PT,Norway,L,Norway,100,"PyTorch, Tableau, SQL, NLP",Master,4,Government,2024-07-30,2024-08-27,681,7.2,Neural Networks Co +AI12609,Data Scientist,102852,USD,102852,MI,PT,United States,S,United States,100,"Scala, Linux, Python, AWS",Associate,2,Automotive,2024-06-14,2024-07-13,1842,9.2,Smart Analytics +AI12610,Autonomous Systems Engineer,126788,EUR,107770,SE,CT,France,S,France,100,"Tableau, Computer Vision, Kubernetes, R",Bachelor,9,Government,2024-03-12,2024-04-21,1769,9,Smart Analytics +AI12611,Research Scientist,140019,GBP,105014,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, TensorFlow, Hadoop",PhD,15,Consulting,2024-04-05,2024-06-17,1104,7.8,Cloud AI Solutions +AI12612,ML Ops Engineer,225786,JPY,24836460,EX,FL,Japan,M,Japan,100,"Git, Kubernetes, Computer Vision, Python, Deep Learning",Master,13,Gaming,2024-09-03,2024-11-04,859,9.1,Algorithmic Solutions +AI12613,Principal Data Scientist,126761,EUR,107747,SE,FL,Austria,S,Austria,0,"Java, Kubernetes, Python, Computer Vision, TensorFlow",Associate,9,Energy,2024-08-23,2024-09-20,1014,8.6,DeepTech Ventures +AI12614,AI Specialist,97895,USD,97895,SE,FT,Israel,S,Israel,0,"Python, Scala, Docker, Azure, Deep Learning",Master,6,Transportation,2024-05-06,2024-06-24,1202,5.6,Neural Networks Co +AI12615,AI Architect,234625,EUR,199431,EX,PT,Netherlands,L,Norway,50,"Git, Python, NLP, TensorFlow, AWS",Bachelor,15,Healthcare,2024-09-17,2024-11-25,1955,6.4,Quantum Computing Inc +AI12616,Data Engineer,118185,GBP,88639,SE,PT,United Kingdom,M,Germany,100,"Computer Vision, Git, Hadoop, Java",Associate,8,Gaming,2025-01-17,2025-02-13,1198,9.1,Advanced Robotics +AI12617,Deep Learning Engineer,66948,USD,66948,EN,FL,Denmark,S,Denmark,100,"Deep Learning, Scala, Data Visualization",Master,0,Healthcare,2024-09-27,2024-11-26,1683,5.1,Digital Transformation LLC +AI12618,Autonomous Systems Engineer,64481,EUR,54809,EN,FL,France,S,Mexico,100,"Python, Hadoop, GCP",PhD,1,Consulting,2024-05-02,2024-05-22,1179,6.6,Future Systems +AI12619,Research Scientist,153732,CHF,138359,MI,FT,Switzerland,L,Switzerland,0,"MLOps, Spark, Scala, Java, Azure",PhD,3,Consulting,2025-03-10,2025-05-03,789,6.4,Algorithmic Solutions +AI12620,Computer Vision Engineer,130492,USD,130492,SE,FT,Ireland,S,Egypt,50,"Python, Data Visualization, Kubernetes",Associate,8,Education,2024-02-16,2024-03-26,1900,7.4,Neural Networks Co +AI12621,NLP Engineer,116529,USD,116529,MI,FT,Sweden,L,Sweden,50,"SQL, MLOps, Computer Vision, Data Visualization",Bachelor,2,Gaming,2024-12-12,2025-01-19,926,6.1,Algorithmic Solutions +AI12622,Autonomous Systems Engineer,125193,AUD,169011,SE,FT,Australia,L,Australia,100,"AWS, Java, Docker",Bachelor,6,Government,2025-03-21,2025-05-16,1239,7.8,Smart Analytics +AI12623,ML Ops Engineer,153136,EUR,130166,SE,PT,Netherlands,L,Netherlands,0,"Python, Kubernetes, Mathematics, Data Visualization, AWS",Associate,9,Media,2024-08-28,2024-11-01,1464,7.7,Advanced Robotics +AI12624,Data Analyst,174479,USD,174479,EX,FT,United States,S,United States,50,"Python, Hadoop, Linux, Tableau, Computer Vision",Bachelor,12,Government,2024-01-24,2024-03-18,2121,7.5,Machine Intelligence Group +AI12625,Machine Learning Researcher,137316,AUD,185377,SE,PT,Australia,M,Austria,50,"Deep Learning, Spark, AWS, Azure",Bachelor,8,Gaming,2024-05-04,2024-06-13,2081,9.3,DeepTech Ventures +AI12626,Deep Learning Engineer,160330,USD,160330,SE,FL,Norway,S,Norway,100,"R, Statistics, Scala, AWS, Computer Vision",Bachelor,7,Government,2024-04-05,2024-05-14,1371,5.6,TechCorp Inc +AI12627,AI Architect,41342,USD,41342,MI,FL,China,L,Denmark,100,"Python, Git, Scala, GCP, Kubernetes",Bachelor,3,Education,2025-03-18,2025-05-15,1068,6.3,DataVision Ltd +AI12628,Autonomous Systems Engineer,31869,USD,31869,EN,CT,China,S,China,100,"SQL, Linux, PyTorch, GCP, R",Associate,1,Education,2024-11-11,2025-01-20,2218,5.2,Cloud AI Solutions +AI12629,Autonomous Systems Engineer,190329,USD,190329,SE,FL,United States,L,Ghana,0,"R, Python, Docker, SQL",PhD,5,Media,2024-05-18,2024-06-04,615,8,DataVision Ltd +AI12630,Research Scientist,80831,USD,80831,EN,FT,Finland,L,Finland,50,"Git, R, MLOps",Bachelor,1,Gaming,2024-07-01,2024-07-20,1907,7.2,Cloud AI Solutions +AI12631,AI Product Manager,102054,USD,102054,SE,FT,Sweden,S,Sweden,100,"Docker, Linux, MLOps, SQL, Deep Learning",Bachelor,7,Media,2025-03-22,2025-04-19,1223,9.2,Future Systems +AI12632,Computer Vision Engineer,198047,USD,198047,EX,PT,South Korea,M,South Korea,100,"Kubernetes, Tableau, Python",Bachelor,12,Healthcare,2024-05-27,2024-07-15,1391,6.6,Predictive Systems +AI12633,NLP Engineer,70324,USD,70324,EN,CT,United States,M,United States,0,"Linux, Docker, PyTorch, Spark",Master,0,Education,2024-03-24,2024-06-02,578,9.9,Future Systems +AI12634,AI Consultant,61593,USD,61593,EN,FL,Ireland,M,Ireland,0,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-07-15,2024-08-30,2459,7.4,Smart Analytics +AI12635,NLP Engineer,225178,EUR,191401,EX,FL,Austria,M,Austria,100,"Python, Data Visualization, Tableau, Java",Master,17,Healthcare,2024-07-10,2024-08-13,1008,7.2,Algorithmic Solutions +AI12636,Machine Learning Engineer,119102,CAD,148878,SE,FL,Canada,M,Canada,50,"Statistics, Linux, Python, Java, Scala",PhD,9,Telecommunications,2025-03-13,2025-05-11,687,8.1,Smart Analytics +AI12637,AI Architect,188552,USD,188552,EX,CT,Finland,S,Finland,0,"Docker, Computer Vision, Python",Associate,10,Automotive,2025-04-16,2025-05-28,1801,7.3,Algorithmic Solutions +AI12638,Head of AI,226063,CHF,203457,SE,CT,Switzerland,L,Romania,0,"Scala, Hadoop, Deep Learning",Master,5,Technology,2025-02-23,2025-04-07,1020,5.1,DataVision Ltd +AI12639,AI Product Manager,62015,USD,62015,MI,CT,Israel,S,Israel,50,"Python, Scala, PyTorch, Statistics",PhD,3,Technology,2024-11-08,2024-12-28,1879,9.2,Cognitive Computing +AI12640,Computer Vision Engineer,93014,CAD,116268,MI,FT,Canada,M,Canada,0,"MLOps, SQL, PyTorch, Mathematics",PhD,3,Energy,2024-10-12,2024-11-05,1673,8.5,Cloud AI Solutions +AI12641,Machine Learning Researcher,128718,SGD,167333,SE,PT,Singapore,M,Singapore,50,"Mathematics, Hadoop, AWS, Statistics",Associate,7,Manufacturing,2024-12-15,2025-02-03,669,9.6,Autonomous Tech +AI12642,Data Engineer,66805,EUR,56784,EN,CT,Austria,M,Italy,0,"Spark, Git, Deep Learning, Statistics",Associate,1,Real Estate,2024-01-23,2024-02-23,554,5.2,Autonomous Tech +AI12643,ML Ops Engineer,90978,USD,90978,EN,FT,Norway,S,Norway,50,"Python, AWS, Data Visualization, Spark, MLOps",Bachelor,1,Finance,2024-06-14,2024-08-04,2462,8.6,Advanced Robotics +AI12644,Data Scientist,139567,USD,139567,SE,PT,Ireland,L,Ireland,0,"PyTorch, Azure, Docker, GCP",Associate,5,Healthcare,2024-11-17,2024-12-05,1020,9.1,Neural Networks Co +AI12645,Machine Learning Engineer,133001,USD,133001,MI,FL,Denmark,M,Denmark,100,"Git, Linux, Python",Master,3,Healthcare,2024-04-02,2024-06-01,731,7.5,Advanced Robotics +AI12646,AI Product Manager,117366,EUR,99761,SE,FT,Netherlands,S,Netherlands,100,"Statistics, TensorFlow, AWS",Bachelor,5,Retail,2025-02-07,2025-03-23,1523,8.1,Quantum Computing Inc +AI12647,Machine Learning Engineer,56948,USD,56948,EN,PT,South Korea,S,South Korea,100,"Statistics, SQL, Scala, PyTorch, Git",Associate,1,Retail,2025-04-04,2025-05-18,2302,7.3,Digital Transformation LLC +AI12648,AI Product Manager,271210,SGD,352573,EX,PT,Singapore,L,Switzerland,100,"Computer Vision, Scala, SQL, PyTorch, R",Master,11,Media,2024-06-23,2024-07-15,583,9.2,Cloud AI Solutions +AI12649,NLP Engineer,108474,EUR,92203,MI,CT,France,L,Australia,0,"Git, SQL, Tableau, Deep Learning",Master,3,Government,2024-10-09,2024-11-12,966,7.2,TechCorp Inc +AI12650,Data Engineer,74225,USD,74225,MI,PT,Ireland,M,Ireland,0,"PyTorch, Statistics, Docker, Kubernetes",Associate,2,Education,2024-08-21,2024-10-13,1353,8.7,DataVision Ltd +AI12651,AI Research Scientist,97911,CAD,122389,SE,PT,Canada,S,Canada,0,"SQL, R, Tableau, Kubernetes",Master,9,Education,2024-02-28,2024-03-31,2122,9.1,Cognitive Computing +AI12652,Deep Learning Engineer,87471,USD,87471,MI,PT,Finland,L,Finland,50,"Git, Azure, Statistics",Master,3,Technology,2024-06-05,2024-06-19,831,5.3,Digital Transformation LLC +AI12653,AI Consultant,66358,USD,66358,MI,FL,South Korea,M,Poland,0,"Kubernetes, Deep Learning, Python, Data Visualization, Mathematics",Master,3,Transportation,2024-05-18,2024-07-25,1793,8.5,Predictive Systems +AI12654,AI Research Scientist,67502,USD,67502,EN,CT,Ireland,L,Ireland,50,"Statistics, Docker, Python, Hadoop, Git",Associate,0,Healthcare,2024-01-09,2024-01-30,2491,7,Cognitive Computing +AI12655,AI Architect,84581,USD,84581,MI,FL,Ireland,M,Ireland,50,"Linux, Java, R",PhD,2,Energy,2024-10-10,2024-12-21,1998,10,Machine Intelligence Group +AI12656,Autonomous Systems Engineer,94615,USD,94615,EN,FT,United States,M,United States,0,"PyTorch, Scala, Linux",Associate,0,Consulting,2024-09-20,2024-11-27,2355,5.3,Algorithmic Solutions +AI12657,Computer Vision Engineer,126277,EUR,107335,SE,FL,Netherlands,S,Philippines,100,"Python, TensorFlow, Tableau, Azure, Statistics",Master,9,Manufacturing,2025-03-28,2025-05-13,1919,6.5,Smart Analytics +AI12658,Autonomous Systems Engineer,108046,EUR,91839,MI,FT,Netherlands,M,Netherlands,100,"Deep Learning, AWS, Hadoop",Master,4,Consulting,2024-10-22,2024-12-19,2301,9.5,Predictive Systems +AI12659,Machine Learning Researcher,214302,EUR,182157,EX,FT,Netherlands,S,Netherlands,50,"Spark, Docker, Data Visualization, NLP",Associate,16,Retail,2025-04-23,2025-05-19,1213,8.9,Predictive Systems +AI12660,Head of AI,60614,USD,60614,EN,FL,Finland,S,Portugal,100,"Linux, Docker, MLOps",PhD,0,Education,2024-02-24,2024-04-28,2024,7,Advanced Robotics +AI12661,Robotics Engineer,126247,SGD,164121,SE,FT,Singapore,S,Singapore,100,"PyTorch, Python, Docker",Master,8,Finance,2024-10-11,2024-11-08,1708,6.3,Smart Analytics +AI12662,Research Scientist,153207,USD,153207,SE,CT,Denmark,S,Denmark,0,"Python, Java, Git",Bachelor,9,Transportation,2024-11-07,2025-01-02,1270,5.6,DataVision Ltd +AI12663,NLP Engineer,91093,EUR,77429,MI,CT,Austria,M,Austria,0,"Deep Learning, Mathematics, Java, Spark, NLP",PhD,4,Technology,2024-06-13,2024-08-02,1465,7.1,Advanced Robotics +AI12664,Data Analyst,177639,USD,177639,EX,FL,Denmark,S,Denmark,100,"Deep Learning, Linux, Kubernetes",PhD,13,Real Estate,2024-11-11,2024-12-28,1835,7.9,Neural Networks Co +AI12665,AI Architect,72729,EUR,61820,EN,PT,Netherlands,M,Netherlands,50,"Docker, Kubernetes, Scala, Git, Mathematics",Bachelor,1,Real Estate,2024-08-17,2024-09-07,1687,5.5,Predictive Systems +AI12666,ML Ops Engineer,231764,EUR,196999,EX,PT,Netherlands,S,South Korea,50,"Kubernetes, Spark, Scala, Data Visualization",Master,14,Manufacturing,2024-07-28,2024-08-25,1535,7.3,Cloud AI Solutions +AI12667,Robotics Engineer,91852,USD,91852,MI,FT,Israel,M,South Korea,50,"Deep Learning, TensorFlow, Azure",Bachelor,2,Energy,2024-02-09,2024-02-27,876,6.7,Smart Analytics +AI12668,Data Scientist,108220,USD,108220,EN,CT,Denmark,L,Ukraine,50,"Tableau, Computer Vision, AWS, Git",PhD,1,Finance,2024-12-09,2025-02-12,2251,8.5,Smart Analytics +AI12669,NLP Engineer,44513,USD,44513,EN,FL,Israel,S,Israel,100,"Scala, Azure, Statistics",Master,0,Education,2024-01-27,2024-02-16,1799,6.1,Quantum Computing Inc +AI12670,Autonomous Systems Engineer,115978,USD,115978,MI,PT,Finland,L,Germany,50,"Azure, Spark, Mathematics, Java",PhD,4,Government,2024-08-19,2024-10-25,2133,8,DeepTech Ventures +AI12671,AI Architect,60623,USD,60623,EN,FT,Ireland,L,Ireland,0,"Git, Python, TensorFlow, GCP, Linux",Associate,0,Manufacturing,2024-05-10,2024-06-12,1778,8.5,AI Innovations +AI12672,Machine Learning Researcher,193676,USD,193676,SE,FT,Denmark,M,Denmark,100,"Docker, Mathematics, Python",Associate,6,Technology,2024-03-05,2024-05-13,1107,6.2,Cloud AI Solutions +AI12673,Computer Vision Engineer,101827,USD,101827,MI,CT,Norway,S,Norway,100,"Kubernetes, Git, Deep Learning, Python",Bachelor,2,Real Estate,2025-03-06,2025-05-05,1206,9.4,Autonomous Tech +AI12674,AI Consultant,90586,SGD,117762,EN,FT,Singapore,L,Hungary,0,"Statistics, AWS, Python",PhD,0,Real Estate,2024-01-22,2024-03-16,1090,5.1,Cognitive Computing +AI12675,AI Specialist,194601,CAD,243251,EX,PT,Canada,M,Canada,50,"SQL, Kubernetes, GCP",PhD,11,Transportation,2024-09-21,2024-10-16,1795,5.7,Future Systems +AI12676,Data Engineer,382222,CHF,344000,EX,FL,Switzerland,L,Thailand,50,"R, PyTorch, Java, GCP, Deep Learning",Associate,15,Government,2024-05-24,2024-08-04,674,9.9,Algorithmic Solutions +AI12677,AI Specialist,111690,CAD,139613,SE,CT,Canada,L,Canada,100,"Git, Python, Spark",Master,5,Transportation,2024-04-04,2024-05-23,1034,6.3,Future Systems +AI12678,Machine Learning Researcher,74807,EUR,63586,MI,CT,France,S,France,100,"Scala, Python, Mathematics, GCP, Linux",Bachelor,3,Automotive,2024-09-19,2024-11-05,2286,8.2,Predictive Systems +AI12679,Machine Learning Researcher,68533,AUD,92520,EN,FT,Australia,S,Colombia,100,"GCP, R, Linux, Mathematics, Java",PhD,0,Gaming,2024-08-14,2024-10-10,1038,7.9,Quantum Computing Inc +AI12680,Robotics Engineer,130226,EUR,110692,SE,CT,Netherlands,L,Netherlands,100,"PyTorch, Docker, TensorFlow, Java, AWS",Bachelor,5,Healthcare,2024-05-24,2024-06-22,513,5.1,Future Systems +AI12681,AI Specialist,112790,GBP,84593,MI,PT,United Kingdom,L,United Kingdom,50,"TensorFlow, Java, Tableau, Computer Vision, R",Associate,4,Manufacturing,2025-02-28,2025-04-25,1695,6,Cloud AI Solutions +AI12682,Data Scientist,189996,CAD,237495,EX,PT,Canada,L,France,100,"Python, Azure, Scala, Statistics, PyTorch",Associate,11,Retail,2024-12-15,2025-01-28,1151,9.4,DataVision Ltd +AI12683,AI Research Scientist,114387,USD,114387,MI,CT,Norway,M,Norway,50,"Tableau, Spark, Linux, Python",PhD,4,Media,2024-06-10,2024-07-15,640,6.5,Autonomous Tech +AI12684,Machine Learning Engineer,185728,CHF,167155,SE,FL,Switzerland,S,Switzerland,50,"Spark, Java, Scala, AWS",PhD,7,Technology,2024-01-25,2024-02-08,2147,8.7,AI Innovations +AI12685,Computer Vision Engineer,142898,EUR,121463,EX,PT,France,M,France,50,"SQL, Hadoop, Scala",PhD,16,Real Estate,2024-07-13,2024-08-14,1190,9.6,TechCorp Inc +AI12686,Autonomous Systems Engineer,84890,USD,84890,EN,FT,Finland,L,Finland,100,"Kubernetes, Python, Git",Associate,1,Retail,2024-08-01,2024-09-07,772,8.7,AI Innovations +AI12687,Machine Learning Researcher,95220,JPY,10474200,EN,CT,Japan,L,Luxembourg,0,"Scala, Spark, NLP, Tableau",Associate,1,Technology,2025-03-11,2025-04-23,536,9.8,Neural Networks Co +AI12688,Machine Learning Engineer,73529,USD,73529,EN,FT,Norway,M,Russia,0,"Linux, Data Visualization, Spark, SQL",Bachelor,0,Consulting,2024-12-10,2025-01-27,979,9,Advanced Robotics +AI12689,AI Specialist,96565,EUR,82080,MI,FT,Netherlands,S,Netherlands,100,"Python, SQL, PyTorch, Deep Learning",Bachelor,4,Technology,2025-04-05,2025-05-14,713,9.1,Quantum Computing Inc +AI12690,AI Research Scientist,81266,USD,81266,EN,PT,Israel,L,Israel,100,"GCP, Kubernetes, Java, Python, SQL",Master,1,Consulting,2024-01-20,2024-03-02,2055,7.2,Cloud AI Solutions +AI12691,Deep Learning Engineer,120489,CAD,150611,SE,FL,Canada,L,Canada,100,"GCP, Linux, R, SQL",Master,8,Retail,2024-07-17,2024-09-15,1009,9.3,TechCorp Inc +AI12692,ML Ops Engineer,160293,SGD,208381,SE,CT,Singapore,L,Chile,100,"Docker, Deep Learning, NLP, PyTorch, Scala",Associate,7,Transportation,2024-04-29,2024-07-11,2163,6.5,DataVision Ltd +AI12693,Research Scientist,259694,CAD,324618,EX,FL,Canada,L,Canada,100,"R, Deep Learning, Mathematics, Statistics",Bachelor,16,Healthcare,2025-02-20,2025-04-04,2352,6.2,TechCorp Inc +AI12694,NLP Engineer,134216,AUD,181192,SE,PT,Australia,M,Ghana,50,"Linux, Spark, MLOps, PyTorch",Associate,7,Government,2025-01-05,2025-03-15,1073,5.1,DeepTech Ventures +AI12695,Machine Learning Engineer,70756,USD,70756,MI,FL,South Korea,M,South Korea,50,"Linux, Scala, Mathematics",PhD,3,Healthcare,2024-06-09,2024-08-01,1480,8.6,DataVision Ltd +AI12696,AI Software Engineer,74648,USD,74648,MI,CT,Israel,M,Israel,50,"Scala, Tableau, R, SQL",Associate,2,Healthcare,2024-08-05,2024-09-18,581,5.5,TechCorp Inc +AI12697,Deep Learning Engineer,62208,EUR,52877,EN,FT,France,M,Singapore,100,"Java, Scala, MLOps, NLP, TensorFlow",Bachelor,0,Technology,2024-02-06,2024-04-03,1324,9.7,Cognitive Computing +AI12698,AI Research Scientist,127798,USD,127798,SE,PT,Ireland,M,Ireland,0,"Kubernetes, Scala, MLOps",Associate,6,Government,2024-12-16,2025-02-18,2486,9.1,Machine Intelligence Group +AI12699,Research Scientist,44314,USD,44314,MI,FT,China,L,China,0,"Statistics, R, Git, Computer Vision",Bachelor,3,Transportation,2024-03-22,2024-04-18,2342,5.3,Autonomous Tech +AI12700,Machine Learning Researcher,112441,USD,112441,SE,FT,Sweden,S,Sweden,100,"Scala, Azure, NLP, Deep Learning",Master,5,Finance,2025-01-16,2025-02-24,1319,9.8,Cloud AI Solutions +AI12701,AI Architect,67815,EUR,57643,EN,PT,Netherlands,S,United States,0,"Statistics, Docker, R, GCP",Associate,0,Technology,2024-01-16,2024-02-19,1170,9.4,Advanced Robotics +AI12702,AI Software Engineer,116101,USD,116101,MI,FT,Norway,L,Norway,50,"MLOps, Python, Data Visualization, NLP, TensorFlow",Master,4,Manufacturing,2024-07-11,2024-08-14,527,6.6,DeepTech Ventures +AI12703,AI Software Engineer,142224,EUR,120890,EX,PT,Germany,M,Germany,50,"Data Visualization, MLOps, R, Spark",Associate,15,Transportation,2024-08-17,2024-09-12,1792,5.2,Cloud AI Solutions +AI12704,Data Engineer,122247,USD,122247,SE,PT,United States,M,United States,50,"SQL, PyTorch, MLOps, Java, TensorFlow",Master,5,Healthcare,2024-02-18,2024-04-16,507,6.7,Algorithmic Solutions +AI12705,Data Analyst,68996,USD,68996,SE,PT,China,L,China,100,"SQL, Linux, GCP",Bachelor,5,Energy,2024-06-10,2024-07-22,1239,5.9,Cloud AI Solutions +AI12706,AI Research Scientist,58278,GBP,43709,EN,CT,United Kingdom,S,Norway,100,"TensorFlow, Kubernetes, Linux, Tableau",Associate,1,Retail,2024-08-16,2024-09-16,1495,8.6,Digital Transformation LLC +AI12707,AI Product Manager,161500,AUD,218025,SE,CT,Australia,L,Colombia,100,"Kubernetes, R, SQL",Associate,8,Technology,2024-11-14,2025-01-07,1847,8.2,TechCorp Inc +AI12708,Data Analyst,97036,USD,97036,EN,PT,Denmark,L,United Kingdom,0,"Python, NLP, Docker",PhD,0,Transportation,2024-12-20,2025-02-20,1466,6.7,Smart Analytics +AI12709,AI Product Manager,97890,USD,97890,MI,PT,Finland,L,Finland,100,"Statistics, Mathematics, Deep Learning, Linux",PhD,2,Media,2024-09-14,2024-10-07,1422,9.9,DataVision Ltd +AI12710,AI Product Manager,192865,EUR,163935,EX,CT,France,L,France,0,"SQL, Statistics, Mathematics, NLP",Associate,11,Manufacturing,2024-07-12,2024-09-07,1150,9.7,DeepTech Ventures +AI12711,Computer Vision Engineer,19662,USD,19662,EN,FL,India,M,India,0,"Linux, AWS, SQL, Data Visualization",Master,1,Manufacturing,2024-01-08,2024-02-15,2190,8.7,Algorithmic Solutions +AI12712,Research Scientist,95674,USD,95674,SE,CT,Sweden,S,Czech Republic,0,"NLP, Git, Kubernetes, Azure, AWS",PhD,7,Finance,2024-08-24,2024-09-16,855,8.1,Autonomous Tech +AI12713,Head of AI,83952,EUR,71359,EN,CT,Netherlands,L,Netherlands,50,"Statistics, R, Azure, GCP",Bachelor,1,Healthcare,2025-01-22,2025-03-12,798,8.3,Neural Networks Co +AI12714,Autonomous Systems Engineer,70247,USD,70247,EN,PT,Ireland,S,Ireland,0,"Spark, Tableau, Azure",Associate,1,Gaming,2025-02-10,2025-04-16,2099,7.3,Cloud AI Solutions +AI12715,Computer Vision Engineer,194385,GBP,145789,EX,FL,United Kingdom,S,Poland,50,"Python, Tableau, AWS, Azure",Bachelor,14,Transportation,2025-04-07,2025-05-11,1896,8.8,Autonomous Tech +AI12716,Machine Learning Researcher,50464,USD,50464,MI,FT,China,M,China,100,"NLP, Python, Kubernetes, Docker",Associate,2,Telecommunications,2024-11-11,2024-12-17,792,5.9,Neural Networks Co +AI12717,AI Architect,71270,EUR,60580,EN,FL,Netherlands,S,Netherlands,0,"GCP, Linux, MLOps",Bachelor,0,Energy,2024-03-05,2024-03-28,2402,6.4,Autonomous Tech +AI12718,AI Specialist,243177,AUD,328289,EX,FT,Australia,M,Australia,50,"Mathematics, Python, SQL",Bachelor,12,Automotive,2024-11-04,2024-11-26,1744,9.4,Cloud AI Solutions +AI12719,Data Scientist,239543,EUR,203612,EX,FL,Austria,M,India,0,"MLOps, SQL, Deep Learning, Kubernetes",Bachelor,15,Manufacturing,2025-01-08,2025-03-18,2258,6.6,Cognitive Computing +AI12720,Machine Learning Engineer,53499,USD,53499,EN,PT,South Korea,S,South Korea,0,"Data Visualization, AWS, Mathematics, Tableau, Deep Learning",Master,1,Energy,2025-04-03,2025-05-08,1026,5.8,Advanced Robotics +AI12721,Computer Vision Engineer,150607,USD,150607,EX,FT,Israel,M,Israel,50,"R, SQL, PyTorch",Associate,18,Government,2024-01-27,2024-04-08,2485,5.7,Cognitive Computing +AI12722,AI Specialist,79623,USD,79623,EN,FL,United States,L,Australia,0,"Computer Vision, Tableau, Kubernetes, Linux",Master,1,Transportation,2024-06-12,2024-08-09,1144,7.7,Autonomous Tech +AI12723,AI Architect,81308,USD,81308,EN,PT,United States,L,United States,50,"R, Python, Tableau",Associate,0,Media,2025-02-23,2025-03-09,749,6.6,Cloud AI Solutions +AI12724,Head of AI,123946,AUD,167327,SE,FT,Australia,S,Australia,100,"Tableau, Data Visualization, Mathematics",PhD,9,Government,2024-01-19,2024-03-29,2481,8.6,Digital Transformation LLC +AI12725,ML Ops Engineer,42381,USD,42381,SE,CT,India,S,Romania,0,"Python, NLP, Azure, TensorFlow",Associate,9,Retail,2025-01-24,2025-03-22,1466,5.4,Autonomous Tech +AI12726,Data Analyst,35803,USD,35803,MI,CT,China,S,China,0,"Git, TensorFlow, Python, AWS, Kubernetes",Associate,4,Education,2024-06-04,2024-07-16,2091,6.4,Algorithmic Solutions +AI12727,Data Analyst,126100,EUR,107185,SE,FT,Netherlands,L,Netherlands,50,"PyTorch, Tableau, Hadoop, Kubernetes",Bachelor,7,Government,2024-04-10,2024-05-24,2184,7.4,Digital Transformation LLC +AI12728,NLP Engineer,138184,USD,138184,SE,FT,Norway,M,Norway,100,"PyTorch, Hadoop, MLOps, Azure",Master,9,Gaming,2025-03-30,2025-04-25,516,5.2,Algorithmic Solutions +AI12729,AI Architect,38303,USD,38303,MI,FT,India,M,India,50,"Python, TensorFlow, Docker, Mathematics, Hadoop",Master,3,Telecommunications,2024-07-21,2024-08-27,1857,7.1,Neural Networks Co +AI12730,Autonomous Systems Engineer,41682,USD,41682,MI,PT,India,L,India,0,"Python, SQL, Mathematics",Bachelor,4,Manufacturing,2024-08-04,2024-10-16,2045,6.4,Algorithmic Solutions +AI12731,AI Specialist,255802,USD,255802,EX,PT,Israel,L,Romania,100,"Hadoop, Git, GCP, Computer Vision",Associate,12,Telecommunications,2024-04-20,2024-05-05,1123,9.5,Cloud AI Solutions +AI12732,Machine Learning Researcher,80108,CAD,100135,MI,PT,Canada,L,Canada,0,"Kubernetes, Docker, R, Linux, Statistics",Master,3,Telecommunications,2025-03-07,2025-04-06,1393,6.1,Quantum Computing Inc +AI12733,Autonomous Systems Engineer,60460,CAD,75575,EN,PT,Canada,M,Canada,100,"Java, Kubernetes, Data Visualization",PhD,1,Energy,2024-09-25,2024-12-03,1853,10,DataVision Ltd +AI12734,Principal Data Scientist,110481,USD,110481,SE,PT,Sweden,S,Sweden,100,"Kubernetes, Hadoop, Data Visualization, Scala, Java",Bachelor,6,Technology,2024-01-30,2024-03-10,1762,9.4,Digital Transformation LLC +AI12735,AI Research Scientist,181707,EUR,154451,EX,PT,Germany,L,Germany,50,"MLOps, Linux, Hadoop",Bachelor,17,Automotive,2024-07-29,2024-08-19,500,9.7,Autonomous Tech +AI12736,AI Architect,171315,CAD,214144,EX,CT,Canada,S,Colombia,100,"SQL, Java, PyTorch",Bachelor,18,Consulting,2025-01-14,2025-02-22,2115,6,AI Innovations +AI12737,Machine Learning Researcher,186907,EUR,158871,EX,PT,France,S,France,0,"NLP, Hadoop, SQL, Statistics, R",Master,12,Real Estate,2025-04-10,2025-05-12,952,9.4,Cloud AI Solutions +AI12738,Computer Vision Engineer,197246,GBP,147935,EX,FL,United Kingdom,S,United Kingdom,50,"SQL, TensorFlow, Linux, Java",PhD,12,Technology,2024-12-10,2024-12-31,2123,6.2,Future Systems +AI12739,AI Research Scientist,62903,AUD,84919,EN,FL,Australia,M,Australia,0,"Python, Tableau, Scala",Bachelor,0,Media,2024-10-09,2024-12-06,834,6.6,Autonomous Tech +AI12740,Robotics Engineer,168184,CAD,210230,EX,PT,Canada,L,Canada,0,"Hadoop, Mathematics, Spark, Computer Vision, Python",Bachelor,10,Finance,2024-04-05,2024-05-31,2000,5.3,Smart Analytics +AI12741,AI Software Engineer,147859,CAD,184824,EX,FL,Canada,M,Germany,100,"SQL, Tableau, Statistics, Linux, Mathematics",Master,10,Gaming,2024-11-02,2025-01-09,858,8.9,Neural Networks Co +AI12742,Machine Learning Researcher,87226,EUR,74142,MI,FT,Netherlands,S,Romania,50,"Azure, R, SQL, AWS",PhD,2,Education,2024-08-09,2024-09-21,1357,5.7,Predictive Systems +AI12743,Machine Learning Engineer,138319,EUR,117571,SE,FL,France,L,France,0,"Computer Vision, Python, TensorFlow",PhD,9,Manufacturing,2024-11-03,2025-01-06,824,9.1,Future Systems +AI12744,Autonomous Systems Engineer,103507,GBP,77630,MI,CT,United Kingdom,M,Luxembourg,0,"Azure, Data Visualization, Python",PhD,4,Media,2024-04-16,2024-05-29,2078,8,Advanced Robotics +AI12745,Data Engineer,223904,EUR,190318,EX,FT,France,M,France,100,"Azure, PyTorch, Hadoop, Kubernetes, Spark",Associate,11,Transportation,2024-04-12,2024-05-29,581,6.1,Neural Networks Co +AI12746,ML Ops Engineer,142980,USD,142980,EX,FL,Finland,M,Austria,100,"R, SQL, Scala, AWS",Bachelor,15,Telecommunications,2024-10-10,2024-11-15,1600,7.9,DataVision Ltd +AI12747,Head of AI,64103,EUR,54488,EN,FL,Austria,M,Austria,100,"Scala, NLP, Java, GCP, Azure",Master,1,Technology,2025-01-14,2025-02-12,1817,6,Algorithmic Solutions +AI12748,Autonomous Systems Engineer,91062,EUR,77403,MI,PT,Austria,S,Austria,100,"Statistics, PyTorch, Spark, Git, Data Visualization",Master,4,Healthcare,2024-02-14,2024-04-27,1057,9.1,DataVision Ltd +AI12749,Robotics Engineer,78579,EUR,66792,EN,CT,Netherlands,L,Germany,100,"Python, Azure, Scala, Tableau",Bachelor,1,Telecommunications,2024-04-29,2024-05-16,1050,5,Advanced Robotics +AI12750,Deep Learning Engineer,115061,EUR,97802,MI,FL,France,L,France,50,"Linux, Java, R, Mathematics, Kubernetes",Bachelor,4,Manufacturing,2024-02-20,2024-03-05,1225,8.8,Cognitive Computing +AI12751,AI Software Engineer,61569,SGD,80040,EN,PT,Singapore,S,Colombia,0,"Azure, NLP, GCP, Java, Mathematics",PhD,0,Retail,2025-03-05,2025-05-06,1412,5.4,Machine Intelligence Group +AI12752,Principal Data Scientist,106803,SGD,138844,SE,CT,Singapore,S,Singapore,100,"Mathematics, Spark, Java, PyTorch",Associate,7,Finance,2024-09-24,2024-10-27,2223,7.5,Neural Networks Co +AI12753,Data Scientist,88775,USD,88775,MI,FT,Ireland,M,Ireland,50,"Python, Scala, NLP, Kubernetes, TensorFlow",Bachelor,4,Manufacturing,2024-07-23,2024-08-08,677,9.9,Cognitive Computing +AI12754,Principal Data Scientist,143329,CAD,179161,EX,FT,Canada,M,Indonesia,100,"Kubernetes, SQL, PyTorch",Associate,16,Consulting,2024-12-06,2025-01-24,1069,8,Machine Intelligence Group +AI12755,Machine Learning Researcher,83311,CHF,74980,EN,CT,Switzerland,S,China,50,"Git, Mathematics, SQL, PyTorch, Azure",Bachelor,0,Consulting,2025-02-01,2025-02-22,1003,8.6,Algorithmic Solutions +AI12756,Machine Learning Engineer,200496,GBP,150372,EX,FT,United Kingdom,S,United Kingdom,50,"R, Java, Computer Vision, Kubernetes",Associate,18,Finance,2024-04-07,2024-05-03,2129,5.8,Future Systems +AI12757,Principal Data Scientist,60235,SGD,78306,EN,CT,Singapore,S,Singapore,100,"Spark, SQL, R, Scala",Master,1,Media,2024-10-15,2024-12-08,963,6.9,Future Systems +AI12758,Head of AI,74675,USD,74675,EN,FT,Sweden,L,Netherlands,50,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-10-02,2024-11-06,1444,5.8,Cloud AI Solutions +AI12759,AI Consultant,61377,EUR,52170,EN,FT,Austria,S,Austria,100,"SQL, NLP, Spark, MLOps",Associate,1,Transportation,2024-08-06,2024-10-02,1373,6.2,AI Innovations +AI12760,AI Specialist,23390,USD,23390,MI,PT,India,S,India,100,"Linux, R, SQL, Data Visualization, NLP",Associate,2,Telecommunications,2025-02-05,2025-03-01,882,7,TechCorp Inc +AI12761,Machine Learning Researcher,91528,EUR,77799,EN,CT,Netherlands,L,Netherlands,100,"Spark, Python, R, Linux",Master,1,Real Estate,2024-08-22,2024-09-25,2097,7.1,DataVision Ltd +AI12762,Robotics Engineer,146429,USD,146429,SE,PT,Denmark,S,Portugal,50,"Docker, AWS, Tableau, Computer Vision, Kubernetes",Associate,6,Retail,2025-02-08,2025-03-12,1796,5.6,DeepTech Ventures +AI12763,Machine Learning Engineer,44242,USD,44242,SE,FT,India,L,New Zealand,50,"Python, Hadoop, AWS, Statistics",Associate,6,Telecommunications,2025-01-07,2025-01-25,1911,6.5,Quantum Computing Inc +AI12764,Principal Data Scientist,141895,USD,141895,MI,PT,United States,L,United States,50,"Statistics, MLOps, Python",PhD,4,Finance,2025-04-15,2025-06-22,1539,6.5,DataVision Ltd +AI12765,Head of AI,172701,EUR,146796,EX,FT,France,L,Estonia,100,"TensorFlow, Git, Computer Vision, Tableau",Bachelor,16,Media,2024-11-21,2024-12-13,1649,6.9,Machine Intelligence Group +AI12766,AI Research Scientist,122947,JPY,13524170,SE,CT,Japan,S,Switzerland,50,"GCP, Git, Statistics",Master,6,Education,2024-11-02,2024-12-17,1589,8.2,Future Systems +AI12767,Data Analyst,76332,EUR,64882,EN,PT,Netherlands,M,Japan,50,"Java, Docker, PyTorch, Computer Vision, Azure",PhD,1,Energy,2024-09-19,2024-11-09,572,5.1,Predictive Systems +AI12768,ML Ops Engineer,165380,EUR,140573,EX,PT,Austria,S,China,100,"Kubernetes, NLP, GCP, Computer Vision",Associate,17,Education,2024-11-17,2024-12-18,551,5.7,Smart Analytics +AI12769,Head of AI,142751,EUR,121338,EX,FT,Austria,M,Austria,0,"Data Visualization, PyTorch, Tableau, Kubernetes",Bachelor,15,Technology,2024-06-24,2024-08-10,848,9.7,Algorithmic Solutions +AI12770,AI Architect,62156,USD,62156,EX,FL,India,M,India,100,"Java, R, NLP, Computer Vision, Kubernetes",Bachelor,14,Gaming,2024-10-21,2024-12-30,539,5.8,Smart Analytics +AI12771,AI Product Manager,152270,USD,152270,SE,FT,United States,M,United States,50,"Linux, AWS, Data Visualization",Associate,5,Media,2025-03-15,2025-04-17,1162,7.3,Autonomous Tech +AI12772,AI Software Engineer,86405,EUR,73444,MI,CT,Netherlands,M,Denmark,0,"NLP, Mathematics, SQL",Master,2,Automotive,2024-06-04,2024-06-27,1890,10,Cloud AI Solutions +AI12773,Machine Learning Engineer,82630,JPY,9089300,MI,FL,Japan,M,Japan,50,"Python, GCP, Data Visualization",PhD,3,Government,2024-10-04,2024-11-27,1829,7.5,Autonomous Tech +AI12774,AI Specialist,57873,USD,57873,EX,CT,China,S,Malaysia,100,"AWS, Azure, Mathematics",Associate,13,Telecommunications,2024-06-07,2024-07-12,1519,6.3,Digital Transformation LLC +AI12775,Robotics Engineer,28348,USD,28348,EN,FL,India,M,India,0,"Statistics, Spark, Python, Computer Vision, Git",PhD,0,Technology,2024-09-22,2024-11-17,723,8.3,Cognitive Computing +AI12776,Computer Vision Engineer,87180,SGD,113334,MI,FT,Singapore,M,Czech Republic,100,"Linux, Data Visualization, GCP, TensorFlow",PhD,2,Consulting,2024-07-15,2024-09-09,1059,9.7,Cloud AI Solutions +AI12777,Head of AI,91044,GBP,68283,EN,PT,United Kingdom,L,United Kingdom,0,"R, PyTorch, Spark, Git, SQL",Master,0,Retail,2025-03-04,2025-04-03,596,5.4,Digital Transformation LLC +AI12778,NLP Engineer,76331,USD,76331,MI,FT,South Korea,L,South Korea,100,"GCP, Kubernetes, Mathematics, Python",PhD,4,Retail,2025-02-17,2025-03-29,1303,5.6,Digital Transformation LLC +AI12779,Robotics Engineer,118613,EUR,100821,SE,CT,France,L,France,0,"Linux, AWS, Deep Learning",Bachelor,8,Telecommunications,2025-01-19,2025-03-09,615,5.2,DataVision Ltd +AI12780,Machine Learning Researcher,92441,GBP,69331,EN,FL,United Kingdom,L,United Kingdom,50,"R, Computer Vision, Linux, Hadoop, SQL",Associate,0,Retail,2024-01-28,2024-03-27,1260,8.2,Advanced Robotics +AI12781,Data Analyst,268946,CHF,242051,EX,CT,Switzerland,M,Switzerland,50,"Data Visualization, Linux, R, Tableau, NLP",Associate,11,Gaming,2024-05-10,2024-07-03,1285,6.6,Quantum Computing Inc +AI12782,Robotics Engineer,32200,USD,32200,EN,FT,China,S,Estonia,100,"SQL, Git, Azure",Bachelor,1,Finance,2024-10-15,2024-12-11,1756,8.6,AI Innovations +AI12783,Robotics Engineer,138675,GBP,104006,SE,FL,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes",PhD,8,Energy,2024-12-09,2025-02-01,1248,8.5,TechCorp Inc +AI12784,Robotics Engineer,68778,EUR,58461,EN,PT,Germany,L,Germany,100,"TensorFlow, Scala, PyTorch, MLOps",PhD,0,Automotive,2025-02-04,2025-03-16,693,6.4,Future Systems +AI12785,Machine Learning Engineer,209006,CHF,188105,SE,CT,Switzerland,M,Switzerland,100,"PyTorch, Python, NLP, Azure",Associate,9,Transportation,2024-06-10,2024-07-04,2219,8.9,Smart Analytics +AI12786,Machine Learning Engineer,131992,CAD,164990,EX,PT,Canada,M,Canada,0,"Python, NLP, Linux, MLOps, AWS",Associate,15,Gaming,2024-09-22,2024-11-16,1295,6.1,Cognitive Computing +AI12787,Data Engineer,94712,USD,94712,MI,FL,Sweden,L,Sweden,50,"Mathematics, PyTorch, Tableau",PhD,2,Technology,2024-03-28,2024-06-07,1216,8.4,Advanced Robotics +AI12788,NLP Engineer,134256,USD,134256,SE,FL,Sweden,S,Sweden,100,"Kubernetes, TensorFlow, GCP",PhD,5,Media,2025-04-24,2025-06-26,1279,7.7,AI Innovations +AI12789,Deep Learning Engineer,103820,USD,103820,MI,PT,Israel,M,Israel,50,"Python, Tableau, Statistics, TensorFlow, Spark",Bachelor,2,Real Estate,2025-03-01,2025-04-10,1980,6.8,Smart Analytics +AI12790,Research Scientist,90645,USD,90645,MI,PT,United States,M,Portugal,0,"PyTorch, Statistics, Kubernetes, NLP",Master,3,Media,2024-05-09,2024-07-02,585,8.9,Smart Analytics +AI12791,ML Ops Engineer,119424,USD,119424,MI,PT,Finland,L,Canada,100,"SQL, Deep Learning, AWS, PyTorch, Spark",PhD,2,Retail,2024-11-11,2024-12-03,2449,5.3,DeepTech Ventures +AI12792,AI Specialist,100887,USD,100887,MI,FL,Ireland,M,Ireland,100,"Git, GCP, Scala, Linux, PyTorch",Master,3,Manufacturing,2024-07-28,2024-09-22,2297,6.9,Quantum Computing Inc +AI12793,NLP Engineer,99370,USD,99370,EX,FT,China,S,China,0,"Python, Java, AWS",PhD,19,Education,2024-04-06,2024-05-03,1851,7.8,Advanced Robotics +AI12794,Deep Learning Engineer,136900,AUD,184815,EX,FT,Australia,M,Australia,100,"MLOps, Kubernetes, Scala",PhD,19,Finance,2024-11-07,2025-01-14,2396,7.5,Cognitive Computing +AI12795,Autonomous Systems Engineer,46438,USD,46438,EN,PT,South Korea,M,South Korea,0,"Kubernetes, SQL, Hadoop, GCP, Computer Vision",Bachelor,1,Manufacturing,2024-02-01,2024-03-09,2305,5.7,Predictive Systems +AI12796,Machine Learning Engineer,49841,USD,49841,MI,FL,China,M,China,0,"Scala, Git, Spark, SQL, Data Visualization",Associate,2,Gaming,2024-07-09,2024-08-19,2197,8.9,DataVision Ltd +AI12797,AI Research Scientist,87830,USD,87830,EX,FL,China,M,China,0,"Spark, Statistics, Python, Docker, Scala",Associate,12,Education,2024-04-02,2024-06-02,2416,9.3,Neural Networks Co +AI12798,Autonomous Systems Engineer,78608,EUR,66817,MI,CT,Austria,M,Austria,0,"R, Scala, TensorFlow, Java",PhD,3,Education,2024-02-26,2024-03-20,2454,5.2,TechCorp Inc +AI12799,Principal Data Scientist,76299,USD,76299,EN,FL,South Korea,L,Estonia,100,"Scala, Java, GCP",Master,0,Media,2024-07-24,2024-09-17,1410,6.9,TechCorp Inc +AI12800,Machine Learning Engineer,70823,USD,70823,MI,FT,Sweden,S,Sweden,100,"SQL, Hadoop, Git",Master,2,Transportation,2024-04-28,2024-06-09,1116,9,Neural Networks Co +AI12801,Head of AI,161626,USD,161626,SE,PT,Norway,L,Norway,50,"PyTorch, SQL, TensorFlow, Python, Deep Learning",Bachelor,7,Finance,2024-11-10,2024-12-06,2400,5.1,Quantum Computing Inc +AI12802,AI Specialist,94357,GBP,70768,MI,PT,United Kingdom,L,United Kingdom,0,"Scala, Spark, Mathematics, Git",PhD,3,Energy,2024-01-11,2024-03-21,1784,8.3,Future Systems +AI12803,AI Architect,154775,USD,154775,EX,CT,Sweden,M,Sweden,50,"Python, Hadoop, Mathematics",Master,15,Telecommunications,2024-04-16,2024-05-30,2227,8.8,Predictive Systems +AI12804,AI Software Engineer,81393,EUR,69184,MI,PT,France,M,France,100,"Deep Learning, SQL, Azure",Associate,4,Consulting,2025-02-09,2025-03-25,1445,6.4,DeepTech Ventures +AI12805,AI Software Engineer,64623,USD,64623,EN,PT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",Master,1,Energy,2024-06-21,2024-08-28,1928,5.5,DeepTech Ventures +AI12806,Autonomous Systems Engineer,53147,USD,53147,EN,CT,Finland,S,Egypt,100,"AWS, Python, Statistics, Tableau, Hadoop",PhD,1,Technology,2024-08-03,2024-10-07,1518,6.8,DeepTech Ventures +AI12807,Data Scientist,95590,USD,95590,SE,PT,Israel,S,Israel,100,"MLOps, AWS, GCP, NLP, Azure",Bachelor,5,Telecommunications,2024-07-03,2024-08-05,1154,6,Machine Intelligence Group +AI12808,Robotics Engineer,72897,USD,72897,EN,CT,Norway,S,Norway,0,"Spark, MLOps, Kubernetes, Linux, TensorFlow",Associate,1,Telecommunications,2024-06-07,2024-07-16,2207,6.8,Neural Networks Co +AI12809,AI Consultant,150728,USD,150728,EX,PT,United States,S,India,100,"Docker, Java, Statistics, SQL, Hadoop",Associate,14,Government,2024-08-13,2024-09-23,2349,8.2,Cognitive Computing +AI12810,ML Ops Engineer,117055,USD,117055,MI,CT,Norway,M,Norway,100,"Git, Docker, Python, Tableau, Azure",PhD,4,Manufacturing,2024-10-09,2024-12-19,794,5.6,Algorithmic Solutions +AI12811,Machine Learning Researcher,87825,EUR,74651,MI,FL,Austria,M,Austria,50,"SQL, Hadoop, TensorFlow, AWS",Bachelor,2,Media,2024-01-07,2024-02-23,2030,9.6,Algorithmic Solutions +AI12812,Data Analyst,199854,AUD,269803,EX,PT,Australia,S,United States,100,"Tableau, Hadoop, SQL, Data Visualization",Bachelor,13,Media,2024-08-28,2024-10-20,1378,6.7,Quantum Computing Inc +AI12813,Deep Learning Engineer,159183,EUR,135306,SE,FL,Netherlands,L,Netherlands,0,"Docker, Python, Tableau",Master,6,Transportation,2024-11-30,2025-01-19,1835,8,Digital Transformation LLC +AI12814,AI Specialist,64547,GBP,48410,EN,PT,United Kingdom,S,United Kingdom,100,"TensorFlow, SQL, Deep Learning, Docker, NLP",Master,0,Energy,2024-08-12,2024-10-21,666,5.8,Autonomous Tech +AI12815,Data Analyst,95432,CHF,85889,EN,FL,Switzerland,S,Switzerland,100,"Linux, SQL, Azure, Hadoop",Associate,0,Education,2024-08-22,2024-10-27,2451,7.1,Cloud AI Solutions +AI12816,AI Research Scientist,38213,USD,38213,MI,FT,India,M,India,50,"Hadoop, Python, Java",Master,2,Finance,2024-10-09,2024-11-24,2359,5.3,Cloud AI Solutions +AI12817,Computer Vision Engineer,122719,USD,122719,SE,PT,Finland,L,Finland,0,"Python, Data Visualization, Kubernetes, Docker, Linux",Bachelor,7,Gaming,2024-09-18,2024-11-22,1724,7.1,DeepTech Ventures +AI12818,Computer Vision Engineer,126604,CHF,113944,MI,PT,Switzerland,L,Switzerland,0,"AWS, Spark, Statistics, SQL, R",Associate,2,Consulting,2024-10-26,2024-11-29,605,8.4,Neural Networks Co +AI12819,Autonomous Systems Engineer,27641,USD,27641,MI,FT,India,S,India,50,"Git, TensorFlow, AWS",PhD,3,Education,2024-05-21,2024-07-16,1784,7.8,Predictive Systems +AI12820,Data Analyst,106504,USD,106504,EN,CT,Denmark,L,Denmark,0,"TensorFlow, Git, Statistics, Tableau, MLOps",Master,1,Finance,2025-04-29,2025-07-02,2091,8.6,TechCorp Inc +AI12821,AI Product Manager,211310,EUR,179614,EX,PT,Netherlands,M,Netherlands,50,"Git, NLP, AWS, Hadoop",Associate,13,Energy,2024-11-07,2024-11-24,1971,6.2,DeepTech Ventures +AI12822,Autonomous Systems Engineer,55929,USD,55929,MI,CT,China,L,China,0,"Java, Linux, Python, GCP",Associate,3,Telecommunications,2024-03-26,2024-05-25,2125,8.5,Cognitive Computing +AI12823,Principal Data Scientist,189125,GBP,141844,EX,FT,United Kingdom,L,Singapore,0,"AWS, PyTorch, Java, TensorFlow, Statistics",Master,16,Education,2024-06-21,2024-07-30,2004,5.9,TechCorp Inc +AI12824,AI Product Manager,232230,JPY,25545300,EX,FT,Japan,L,Japan,50,"Scala, Docker, Linux, Azure",PhD,14,Consulting,2024-02-10,2024-03-25,719,7.2,Cloud AI Solutions +AI12825,AI Architect,92533,AUD,124920,MI,FT,Australia,M,Australia,100,"Kubernetes, SQL, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-30,1982,5.1,Advanced Robotics +AI12826,Head of AI,170727,USD,170727,EX,CT,South Korea,S,France,0,"TensorFlow, Java, Computer Vision",Associate,15,Real Estate,2024-09-04,2024-11-03,829,5.8,DeepTech Ventures +AI12827,Machine Learning Researcher,64528,USD,64528,EN,CT,Finland,M,Finland,0,"Git, Java, Statistics",Bachelor,0,Consulting,2025-03-14,2025-04-02,1203,9.1,Quantum Computing Inc +AI12828,Robotics Engineer,86994,GBP,65246,EN,PT,United Kingdom,L,Malaysia,50,"Azure, AWS, GCP, Linux",Master,1,Automotive,2025-04-13,2025-05-02,1858,8.6,Cloud AI Solutions +AI12829,AI Architect,195324,USD,195324,EX,FL,Israel,L,Canada,50,"GCP, Spark, SQL, PyTorch, Computer Vision",Master,11,Technology,2024-06-13,2024-07-28,511,9.3,Digital Transformation LLC +AI12830,AI Architect,107212,EUR,91130,SE,CT,Netherlands,S,Germany,50,"Docker, Java, Mathematics",Associate,9,Education,2025-04-30,2025-05-28,1555,7.1,DataVision Ltd +AI12831,Data Scientist,63595,USD,63595,EN,CT,Ireland,M,Ireland,50,"Scala, Python, TensorFlow, Mathematics",Bachelor,0,Gaming,2024-01-14,2024-03-16,2066,7.9,Algorithmic Solutions +AI12832,Data Engineer,146168,USD,146168,SE,PT,United States,M,United States,50,"Tableau, Java, Azure, SQL, PyTorch",Associate,7,Media,2025-04-18,2025-05-15,1733,8.2,Smart Analytics +AI12833,AI Product Manager,23158,USD,23158,EN,FT,China,S,China,0,"Git, NLP, SQL",Master,1,Government,2024-03-17,2024-04-18,1055,8.3,Digital Transformation LLC +AI12834,Data Engineer,74146,EUR,63024,EN,FT,Austria,M,Austria,0,"Linux, Tableau, Git, R, Statistics",Bachelor,1,Media,2024-11-16,2024-12-24,2186,9.8,Future Systems +AI12835,NLP Engineer,244490,SGD,317837,EX,FL,Singapore,M,Vietnam,50,"Python, TensorFlow, AWS, Scala, PyTorch",Master,16,Consulting,2024-08-20,2024-09-05,1520,7.4,DeepTech Ventures +AI12836,Data Analyst,135650,USD,135650,MI,FT,United States,L,Czech Republic,0,"Scala, Azure, PyTorch, Deep Learning, Tableau",Master,2,Technology,2025-02-25,2025-03-23,1602,6.2,Machine Intelligence Group +AI12837,AI Product Manager,161057,EUR,136898,SE,PT,France,L,France,0,"Deep Learning, NLP, MLOps, Scala, TensorFlow",Associate,8,Retail,2025-02-26,2025-04-30,873,5.7,Future Systems +AI12838,AI Research Scientist,95999,SGD,124799,MI,FL,Singapore,L,Australia,50,"SQL, R, MLOps, NLP",Associate,4,Transportation,2024-03-27,2024-06-02,897,5.7,AI Innovations +AI12839,Autonomous Systems Engineer,75071,USD,75071,EN,CT,Sweden,L,Sweden,50,"Tableau, TensorFlow, PyTorch",Associate,0,Manufacturing,2025-04-25,2025-06-11,2289,8,Cloud AI Solutions +AI12840,AI Research Scientist,80156,USD,80156,EN,CT,Sweden,L,Sweden,100,"Scala, SQL, MLOps",Bachelor,0,Manufacturing,2024-04-21,2024-06-27,2425,5.1,Algorithmic Solutions +AI12841,NLP Engineer,77757,CHF,69981,EN,FL,Switzerland,M,Switzerland,0,"SQL, Kubernetes, TensorFlow, Git",PhD,0,Media,2024-01-07,2024-03-20,964,8.7,AI Innovations +AI12842,Machine Learning Engineer,56236,USD,56236,EN,PT,South Korea,M,South Korea,50,"Python, R, Data Visualization, Java, MLOps",Bachelor,1,Consulting,2025-03-15,2025-05-07,2054,9.7,Machine Intelligence Group +AI12843,Computer Vision Engineer,240245,JPY,26426950,EX,CT,Japan,M,Japan,100,"Scala, Java, R, Computer Vision, Git",PhD,14,Technology,2025-01-31,2025-04-01,1258,8.5,Future Systems +AI12844,Data Analyst,275028,USD,275028,EX,PT,Ireland,L,Ireland,100,"Deep Learning, Azure, GCP",Master,12,Manufacturing,2024-02-22,2024-04-02,1031,6.5,Digital Transformation LLC +AI12845,AI Consultant,186213,EUR,158281,EX,CT,Austria,L,Austria,100,"Data Visualization, Linux, SQL, Deep Learning",Bachelor,18,Media,2024-01-25,2024-03-19,2022,7.2,Algorithmic Solutions +AI12846,Data Engineer,287124,USD,287124,EX,FT,Norway,S,Norway,50,"Linux, Tableau, Hadoop, Computer Vision",Bachelor,15,Transportation,2025-02-11,2025-04-13,2175,6.8,Digital Transformation LLC +AI12847,Data Scientist,135404,CHF,121864,MI,PT,Switzerland,M,Switzerland,100,"SQL, Kubernetes, Tableau, Linux",Master,3,Transportation,2025-02-14,2025-04-05,2281,8.1,Quantum Computing Inc +AI12848,Principal Data Scientist,159276,EUR,135385,SE,PT,France,L,France,50,"Hadoop, Docker, Kubernetes, MLOps",PhD,8,Consulting,2024-11-12,2025-01-08,673,8.6,AI Innovations +AI12849,Data Engineer,93350,USD,93350,SE,FL,Sweden,S,Sweden,100,"Linux, Data Visualization, Python",Associate,8,Government,2025-01-28,2025-04-02,533,6.7,AI Innovations +AI12850,AI Product Manager,264276,USD,264276,EX,PT,Ireland,L,Nigeria,50,"Java, SQL, Deep Learning, Hadoop, Spark",Associate,10,Consulting,2025-01-09,2025-02-28,2452,7.7,Machine Intelligence Group +AI12851,ML Ops Engineer,31006,USD,31006,MI,CT,India,S,India,50,"Deep Learning, Python, AWS, Tableau, Spark",Bachelor,4,Manufacturing,2025-04-17,2025-05-19,1090,7.9,Advanced Robotics +AI12852,AI Architect,132059,USD,132059,SE,FT,Israel,M,Israel,50,"Spark, SQL, MLOps",PhD,8,Automotive,2025-01-23,2025-02-12,1688,7,Cloud AI Solutions +AI12853,NLP Engineer,85658,AUD,115638,MI,FL,Australia,L,Japan,50,"Python, NLP, Computer Vision, Git",Bachelor,2,Manufacturing,2024-04-03,2024-05-21,1069,8.1,Neural Networks Co +AI12854,Data Scientist,107273,EUR,91182,SE,PT,Germany,S,Germany,0,"Python, Git, Hadoop",Bachelor,6,Government,2024-07-11,2024-08-21,1704,8.7,Algorithmic Solutions +AI12855,Data Scientist,120446,EUR,102379,SE,CT,Netherlands,S,Netherlands,0,"Linux, Java, Git, Tableau",Bachelor,7,Manufacturing,2024-02-22,2024-04-23,1512,5.8,Future Systems +AI12856,Principal Data Scientist,92064,USD,92064,MI,FL,Israel,L,Israel,100,"Python, GCP, Computer Vision, TensorFlow",Bachelor,2,Real Estate,2025-04-30,2025-05-29,779,7.7,AI Innovations +AI12857,ML Ops Engineer,170651,USD,170651,EX,PT,Finland,S,Brazil,100,"AWS, Azure, Python, TensorFlow",Associate,17,Gaming,2024-05-08,2024-05-29,1131,8.1,DeepTech Ventures +AI12858,Principal Data Scientist,209732,USD,209732,EX,FL,United States,L,United States,0,"Python, Docker, Data Visualization, Azure",PhD,13,Healthcare,2024-09-09,2024-10-09,1392,8.9,Autonomous Tech +AI12859,Data Scientist,90595,EUR,77006,MI,FL,France,M,France,100,"Data Visualization, Docker, Tableau, SQL",Bachelor,2,Retail,2025-04-17,2025-05-23,1909,9.4,Cognitive Computing +AI12860,ML Ops Engineer,134103,GBP,100577,SE,PT,United Kingdom,L,United Kingdom,0,"GCP, Spark, Tableau",Associate,6,Telecommunications,2024-09-05,2024-10-15,2247,5.8,Predictive Systems +AI12861,AI Software Engineer,328767,USD,328767,EX,CT,Norway,M,Norway,50,"Git, Mathematics, Deep Learning, PyTorch",PhD,14,Gaming,2024-03-27,2024-04-23,813,8.1,TechCorp Inc +AI12862,Head of AI,201006,USD,201006,EX,CT,Israel,M,Denmark,0,"TensorFlow, Python, Docker",PhD,14,Transportation,2025-02-28,2025-04-20,999,5.7,DataVision Ltd +AI12863,Research Scientist,127726,JPY,14049860,SE,PT,Japan,S,Japan,50,"Mathematics, AWS, PyTorch, Deep Learning, Java",PhD,8,Gaming,2025-04-10,2025-04-30,742,6.3,Predictive Systems +AI12864,Computer Vision Engineer,269096,USD,269096,EX,FL,United States,L,United States,50,"TensorFlow, MLOps, Tableau",Associate,17,Education,2024-10-04,2024-11-24,1224,7.5,Cognitive Computing +AI12865,Data Engineer,149753,EUR,127290,SE,FT,Austria,L,China,100,"GCP, Spark, Scala, Data Visualization, Python",Master,7,Education,2024-11-28,2025-01-08,637,5.5,Future Systems +AI12866,ML Ops Engineer,145711,SGD,189424,SE,PT,Singapore,M,Singapore,100,"Scala, Docker, Statistics, Deep Learning, Computer Vision",Bachelor,5,Real Estate,2025-02-18,2025-04-01,2320,9.4,Predictive Systems +AI12867,AI Consultant,20533,USD,20533,EN,FT,India,S,India,100,"Scala, Kubernetes, Hadoop",Associate,0,Technology,2025-01-16,2025-02-02,1142,9.7,Future Systems +AI12868,NLP Engineer,80896,USD,80896,EN,CT,United States,L,United States,0,"Python, TensorFlow, Azure, Java, Tableau",PhD,0,Telecommunications,2024-02-09,2024-04-07,1088,6.5,Digital Transformation LLC +AI12869,Autonomous Systems Engineer,128356,EUR,109103,SE,FT,Netherlands,L,Netherlands,0,"NLP, TensorFlow, R, Computer Vision, Scala",Bachelor,5,Consulting,2024-12-27,2025-02-25,520,9.3,Cloud AI Solutions +AI12870,Data Engineer,118886,USD,118886,SE,FL,United States,S,Kenya,50,"Java, MLOps, Computer Vision, AWS, Azure",PhD,7,Education,2024-03-06,2024-03-26,1504,8.8,Future Systems +AI12871,AI Architect,115314,USD,115314,MI,FT,Denmark,S,Denmark,100,"Linux, Python, NLP, Git",Associate,2,Consulting,2024-11-16,2024-12-24,777,6,Quantum Computing Inc +AI12872,Data Scientist,132602,CHF,119342,MI,CT,Switzerland,S,Switzerland,100,"Python, Spark, Deep Learning",PhD,2,Consulting,2024-07-23,2024-08-12,2381,9.1,Advanced Robotics +AI12873,AI Software Engineer,145255,GBP,108941,EX,CT,United Kingdom,S,United Kingdom,50,"MLOps, Mathematics, Docker, PyTorch, TensorFlow",Associate,17,Automotive,2024-10-21,2024-11-20,2468,5.5,Cloud AI Solutions +AI12874,ML Ops Engineer,139099,USD,139099,SE,PT,South Korea,L,South Korea,0,"Spark, Azure, Data Visualization, GCP",Bachelor,8,Transportation,2025-03-16,2025-04-18,2132,7.1,Machine Intelligence Group +AI12875,AI Architect,112407,CHF,101166,MI,FL,Switzerland,M,Netherlands,100,"Hadoop, NLP, Tableau",Bachelor,3,Government,2025-01-10,2025-02-26,1032,8,Advanced Robotics +AI12876,Data Scientist,113716,USD,113716,MI,FL,Ireland,L,Ireland,100,"PyTorch, GCP, Statistics",Associate,4,Real Estate,2024-11-24,2024-12-16,2045,5.2,Machine Intelligence Group +AI12877,Data Scientist,45202,USD,45202,EN,FT,South Korea,S,South Korea,50,"Tableau, Java, Kubernetes, Azure, Scala",Master,0,Education,2024-02-17,2024-03-13,1242,6.1,Cloud AI Solutions +AI12878,Autonomous Systems Engineer,131630,USD,131630,EX,PT,Israel,M,Israel,50,"Git, Java, Linux, TensorFlow, Deep Learning",Master,13,Automotive,2025-01-24,2025-03-21,1311,5,TechCorp Inc +AI12879,Computer Vision Engineer,130641,JPY,14370510,MI,FT,Japan,L,Japan,50,"Python, Spark, Scala, Data Visualization, SQL",Associate,3,Real Estate,2024-12-18,2025-01-23,2057,6.3,TechCorp Inc +AI12880,Deep Learning Engineer,270691,GBP,203018,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Azure, Java, SQL, Computer Vision",Master,16,Education,2025-03-14,2025-04-22,1824,6.9,Neural Networks Co +AI12881,AI Product Manager,90830,USD,90830,MI,PT,United States,M,United States,100,"MLOps, Data Visualization, Python, SQL, GCP",Master,3,Education,2025-01-14,2025-02-11,1273,6.8,Smart Analytics +AI12882,AI Architect,155288,USD,155288,EX,CT,South Korea,S,Canada,50,"Python, Deep Learning, TensorFlow, Java, Statistics",PhD,18,Manufacturing,2025-01-27,2025-03-23,1295,7.8,Algorithmic Solutions +AI12883,NLP Engineer,55458,USD,55458,EN,CT,Finland,M,Finland,0,"Python, TensorFlow, Statistics",Associate,0,Healthcare,2024-02-11,2024-02-25,1132,6.2,Cloud AI Solutions +AI12884,Research Scientist,142729,USD,142729,MI,FL,Norway,M,Norway,100,"Kubernetes, MLOps, Scala, Computer Vision",Master,2,Transportation,2024-03-24,2024-05-13,2222,6.5,Smart Analytics +AI12885,Data Engineer,72858,USD,72858,EN,CT,Denmark,M,Switzerland,100,"SQL, R, Tableau, AWS, Computer Vision",Bachelor,0,Retail,2025-01-12,2025-02-06,1491,5.6,Future Systems +AI12886,Robotics Engineer,107428,AUD,145028,MI,FT,Australia,L,Australia,0,"Computer Vision, Python, Git, Kubernetes, Docker",Associate,3,Telecommunications,2024-06-09,2024-07-13,1024,9.4,Machine Intelligence Group +AI12887,Data Scientist,86669,EUR,73669,MI,FT,Netherlands,M,Netherlands,0,"Docker, Hadoop, MLOps, Git",Bachelor,3,Finance,2025-02-07,2025-03-21,1124,9.1,Digital Transformation LLC +AI12888,Research Scientist,128076,CAD,160095,EX,CT,Canada,M,Singapore,50,"Deep Learning, NLP, Data Visualization, Kubernetes",PhD,13,Media,2025-01-16,2025-03-10,923,9.5,DeepTech Ventures +AI12889,Machine Learning Engineer,106104,USD,106104,SE,PT,Israel,M,Israel,0,"Azure, SQL, Data Visualization, Python",Associate,5,Transportation,2024-03-23,2024-04-15,1567,9.3,Algorithmic Solutions +AI12890,Deep Learning Engineer,68721,USD,68721,MI,FL,Sweden,S,South Korea,50,"Scala, Spark, MLOps",Master,2,Energy,2024-05-15,2024-07-17,771,6.1,Future Systems +AI12891,NLP Engineer,86559,CAD,108199,MI,CT,Canada,M,Canada,50,"SQL, Kubernetes, Mathematics, Computer Vision, Azure",Associate,4,Gaming,2024-04-18,2024-06-28,2191,5,DeepTech Ventures +AI12892,ML Ops Engineer,61330,USD,61330,EN,FL,Israel,S,Israel,100,"NLP, PyTorch, Tableau, Scala, Java",PhD,1,Government,2024-03-06,2024-04-27,2174,5.7,Algorithmic Solutions +AI12893,Research Scientist,119858,AUD,161808,MI,PT,Australia,L,China,50,"Tableau, Statistics, Azure",Master,3,Media,2024-10-30,2024-11-13,1341,8.4,Quantum Computing Inc +AI12894,Robotics Engineer,118666,USD,118666,EN,FL,Norway,L,United States,0,"Scala, GCP, MLOps",PhD,1,Real Estate,2024-05-18,2024-07-03,1551,7.1,Digital Transformation LLC +AI12895,Autonomous Systems Engineer,25726,USD,25726,EN,FL,China,S,China,50,"TensorFlow, Linux, MLOps, R",Master,0,Transportation,2025-03-03,2025-03-22,2314,7.6,Machine Intelligence Group +AI12896,AI Specialist,29930,USD,29930,EN,CT,India,L,India,50,"Linux, Python, Tableau",Bachelor,0,Gaming,2024-04-21,2024-06-12,2416,7.5,DeepTech Ventures +AI12897,AI Architect,37505,USD,37505,MI,PT,India,M,India,0,"Mathematics, MLOps, Data Visualization",Bachelor,2,Media,2024-01-01,2024-01-22,1487,6.2,Predictive Systems +AI12898,Head of AI,116283,USD,116283,MI,CT,United States,S,Nigeria,0,"Git, Computer Vision, PyTorch, Hadoop",PhD,2,Automotive,2024-10-10,2024-12-09,1497,9.3,Neural Networks Co +AI12899,AI Product Manager,45147,USD,45147,SE,CT,India,S,India,0,"Python, TensorFlow, GCP",Associate,5,Real Estate,2024-05-06,2024-07-13,1498,5.7,Machine Intelligence Group +AI12900,Principal Data Scientist,66746,USD,66746,EN,CT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",PhD,0,Technology,2025-02-23,2025-04-21,1410,9.4,AI Innovations +AI12901,Data Analyst,61929,CAD,77411,EN,CT,Canada,M,Canada,100,"Git, Computer Vision, Statistics, Data Visualization, Java",Master,1,Retail,2024-06-06,2024-07-29,1877,6.8,Quantum Computing Inc +AI12902,Head of AI,210982,USD,210982,EX,FT,Sweden,M,Sweden,50,"Data Visualization, Tableau, Linux, TensorFlow, Java",Associate,11,Media,2024-03-04,2024-05-01,2082,9.4,Smart Analytics +AI12903,NLP Engineer,82621,SGD,107407,EN,FL,Singapore,L,Germany,100,"Tableau, PyTorch, TensorFlow, Python",Associate,1,Telecommunications,2025-03-15,2025-04-29,1755,7.7,AI Innovations +AI12904,Machine Learning Engineer,227131,EUR,193061,EX,FT,Germany,L,Germany,50,"Spark, PyTorch, Azure",Master,16,Automotive,2024-12-17,2025-01-21,640,7,Digital Transformation LLC +AI12905,Machine Learning Researcher,113462,USD,113462,MI,FL,United States,S,United States,0,"Azure, Tableau, Scala",Associate,2,Technology,2024-11-30,2024-12-19,2147,6,Algorithmic Solutions +AI12906,Machine Learning Researcher,146522,USD,146522,SE,PT,Denmark,M,Denmark,50,"Data Visualization, MLOps, Docker, Scala, R",Bachelor,7,Consulting,2024-12-31,2025-01-22,2267,8.2,Cloud AI Solutions +AI12907,AI Architect,310444,USD,310444,EX,FL,Denmark,M,Denmark,0,"NLP, TensorFlow, Java",PhD,17,Gaming,2025-02-07,2025-03-14,1768,5.4,Future Systems +AI12908,Machine Learning Engineer,212270,CAD,265338,EX,FL,Canada,S,Canada,50,"Scala, AWS, Computer Vision",PhD,10,Consulting,2024-12-01,2024-12-15,821,9.7,Autonomous Tech +AI12909,Principal Data Scientist,55426,USD,55426,MI,PT,South Korea,S,South Korea,0,"NLP, TensorFlow, PyTorch, Linux",Master,3,Technology,2025-01-25,2025-03-15,2111,9.6,Autonomous Tech +AI12910,NLP Engineer,284645,USD,284645,EX,PT,Denmark,M,Denmark,0,"SQL, Hadoop, Mathematics, MLOps, AWS",Bachelor,17,Automotive,2025-04-30,2025-05-15,1964,5.2,Advanced Robotics +AI12911,Machine Learning Engineer,91905,EUR,78119,MI,PT,France,M,France,100,"Kubernetes, MLOps, Linux, Java",Associate,3,Real Estate,2024-09-04,2024-10-07,1258,8.4,Neural Networks Co +AI12912,AI Consultant,46252,USD,46252,EN,FT,South Korea,S,South Korea,100,"Mathematics, Spark, MLOps, Computer Vision",Associate,1,Education,2024-07-15,2024-08-06,596,5.6,Digital Transformation LLC +AI12913,Data Engineer,140999,EUR,119849,SE,CT,Germany,L,Germany,0,"TensorFlow, Python, Hadoop",Master,6,Government,2024-04-19,2024-05-24,969,5.3,DataVision Ltd +AI12914,AI Architect,61460,USD,61460,EN,FT,Ireland,L,Philippines,100,"MLOps, Python, TensorFlow",PhD,0,Transportation,2024-12-28,2025-02-06,1746,8.3,TechCorp Inc +AI12915,AI Product Manager,107693,USD,107693,EN,FT,United States,L,United States,0,"Data Visualization, Kubernetes, NLP, AWS",Master,1,Telecommunications,2024-01-18,2024-02-22,1186,5.5,DataVision Ltd +AI12916,Deep Learning Engineer,202576,CAD,253220,EX,FT,Canada,L,Canada,100,"Azure, Deep Learning, GCP, Docker",Associate,15,Telecommunications,2024-09-09,2024-10-15,1817,9.4,DataVision Ltd +AI12917,AI Architect,61666,USD,61666,EN,FT,Israel,S,Israel,0,"Hadoop, R, Mathematics",Associate,1,Energy,2024-08-31,2024-09-15,2378,8.5,Cloud AI Solutions +AI12918,Data Scientist,40597,USD,40597,MI,FT,China,M,China,0,"R, MLOps, PyTorch",Master,4,Real Estate,2024-12-25,2025-03-01,1634,6.4,Cloud AI Solutions +AI12919,AI Research Scientist,136441,SGD,177373,SE,FL,Singapore,L,Singapore,0,"Docker, GCP, MLOps",Master,8,Automotive,2024-02-03,2024-04-05,1625,5.8,Predictive Systems +AI12920,Principal Data Scientist,64127,USD,64127,SE,PT,China,L,China,50,"Scala, TensorFlow, Kubernetes",Master,8,Gaming,2024-09-04,2024-10-11,581,7.2,Machine Intelligence Group +AI12921,ML Ops Engineer,104753,AUD,141417,SE,FL,Australia,M,Turkey,0,"GCP, Spark, Statistics",Bachelor,5,Gaming,2024-07-07,2024-08-15,1289,9.6,Quantum Computing Inc +AI12922,Principal Data Scientist,122222,USD,122222,MI,PT,Denmark,M,United Kingdom,50,"Docker, Deep Learning, Scala",Bachelor,2,Education,2024-07-30,2024-09-01,584,9.3,Predictive Systems +AI12923,NLP Engineer,101788,EUR,86520,SE,FL,France,M,France,50,"Data Visualization, Python, SQL, R, Java",Bachelor,9,Consulting,2024-08-30,2024-10-18,2421,9.7,AI Innovations +AI12924,Autonomous Systems Engineer,341521,CHF,307369,EX,FT,Switzerland,L,Australia,50,"Linux, Docker, SQL, GCP",Bachelor,11,Consulting,2024-11-01,2024-11-24,736,5.9,Cloud AI Solutions +AI12925,AI Specialist,63658,USD,63658,EN,PT,Israel,M,Israel,0,"Data Visualization, MLOps, Python, Java",PhD,0,Education,2024-04-18,2024-05-13,1176,9,Neural Networks Co +AI12926,Data Engineer,172241,USD,172241,EX,PT,Finland,M,Finland,50,"Scala, Hadoop, Data Visualization, NLP",Bachelor,11,Energy,2025-03-25,2025-04-20,1125,7.9,Algorithmic Solutions +AI12927,Data Engineer,80284,EUR,68241,MI,CT,Netherlands,M,Netherlands,100,"Linux, PyTorch, SQL",PhD,3,Energy,2024-11-19,2025-01-10,2146,8.8,Autonomous Tech +AI12928,Head of AI,82705,USD,82705,EN,FT,Sweden,L,Sweden,0,"Mathematics, Tableau, Hadoop, PyTorch",PhD,0,Finance,2024-03-09,2024-04-10,1351,8.1,Neural Networks Co +AI12929,ML Ops Engineer,82163,USD,82163,EN,PT,Finland,L,Finland,0,"Docker, MLOps, Deep Learning, Kubernetes, GCP",Associate,1,Manufacturing,2025-04-24,2025-06-19,1669,8.8,Algorithmic Solutions +AI12930,Principal Data Scientist,134609,USD,134609,SE,FT,Ireland,S,Ireland,100,"R, TensorFlow, Hadoop",Associate,9,Transportation,2025-02-10,2025-03-15,2238,7.6,Future Systems +AI12931,Machine Learning Researcher,50356,EUR,42803,EN,PT,Germany,S,Germany,0,"Git, TensorFlow, Data Visualization",Bachelor,1,Education,2025-04-13,2025-06-15,777,6.3,Digital Transformation LLC +AI12932,Robotics Engineer,100882,USD,100882,MI,CT,United States,S,United States,100,"Hadoop, Tableau, Git",Associate,3,Media,2024-11-07,2025-01-13,1996,6,Cloud AI Solutions +AI12933,AI Software Engineer,97133,USD,97133,SE,CT,Finland,M,Finland,100,"Computer Vision, Python, SQL, Docker",Associate,6,Education,2024-04-20,2024-05-18,2044,7.9,Cognitive Computing +AI12934,Data Engineer,169587,USD,169587,SE,PT,United States,L,United States,50,"R, GCP, SQL",Bachelor,6,Retail,2025-04-07,2025-05-13,612,7.6,Neural Networks Co +AI12935,AI Consultant,218131,EUR,185411,EX,CT,France,M,Turkey,0,"Hadoop, SQL, GCP, Git",Bachelor,10,Education,2025-02-18,2025-03-22,2034,8.5,Machine Intelligence Group +AI12936,NLP Engineer,103226,USD,103226,MI,CT,United States,M,Turkey,0,"Python, Hadoop, MLOps, Data Visualization, PyTorch",Bachelor,4,Retail,2024-09-23,2024-10-30,1512,6.2,AI Innovations +AI12937,Principal Data Scientist,100052,USD,100052,EN,PT,United States,L,United States,50,"PyTorch, R, Linux, Kubernetes, Scala",PhD,0,Consulting,2025-01-27,2025-04-08,1611,6.2,Algorithmic Solutions +AI12938,Deep Learning Engineer,166634,USD,166634,SE,FL,Norway,M,United States,0,"GCP, Python, Scala, Docker",Bachelor,8,Real Estate,2024-02-04,2024-02-29,673,9.3,Future Systems +AI12939,AI Consultant,116226,USD,116226,SE,FT,Sweden,M,Sweden,50,"PyTorch, Java, TensorFlow",Bachelor,6,Finance,2024-05-14,2024-07-11,1881,6.1,DeepTech Ventures +AI12940,NLP Engineer,95173,EUR,80897,SE,FL,Germany,S,Canada,0,"Scala, Java, Mathematics, Linux, Git",Master,6,Gaming,2024-08-21,2024-10-31,1306,9.8,Future Systems +AI12941,Data Scientist,164965,EUR,140220,EX,CT,Germany,S,Germany,0,"TensorFlow, Docker, Deep Learning, Python, Git",Bachelor,17,Consulting,2025-02-06,2025-03-09,1669,7.8,AI Innovations +AI12942,AI Architect,110208,CHF,99187,MI,CT,Switzerland,S,Switzerland,0,"SQL, Hadoop, R",PhD,4,Technology,2024-05-28,2024-07-06,712,9.8,AI Innovations +AI12943,AI Consultant,66541,USD,66541,EN,FT,United States,S,Brazil,100,"Kubernetes, Mathematics, NLP, SQL, Tableau",Bachelor,0,Consulting,2025-04-07,2025-05-14,2176,8.2,Digital Transformation LLC +AI12944,Computer Vision Engineer,349894,USD,349894,EX,FT,Norway,L,Norway,100,"SQL, Python, MLOps, Statistics",Master,14,Technology,2025-02-07,2025-03-15,1449,8.7,AI Innovations +AI12945,Machine Learning Engineer,186739,CHF,168065,SE,FT,Switzerland,S,Switzerland,0,"Deep Learning, Git, Java",PhD,9,Manufacturing,2024-05-22,2024-07-01,1850,7.5,Digital Transformation LLC +AI12946,Machine Learning Researcher,239337,SGD,311138,EX,FT,Singapore,S,Singapore,50,"Tableau, Java, NLP",Master,19,Education,2024-04-03,2024-04-29,2231,9.4,Algorithmic Solutions +AI12947,Machine Learning Researcher,36462,USD,36462,MI,FL,India,M,India,100,"TensorFlow, PyTorch, MLOps, GCP",PhD,4,Finance,2024-05-15,2024-07-10,2444,5.7,Machine Intelligence Group +AI12948,Data Analyst,91501,USD,91501,EN,CT,Denmark,M,Denmark,0,"Mathematics, R, Python",Master,1,Real Estate,2024-09-28,2024-10-18,747,5.5,DataVision Ltd +AI12949,Head of AI,112775,USD,112775,SE,CT,South Korea,L,Austria,0,"SQL, Computer Vision, Linux",Bachelor,5,Manufacturing,2024-10-03,2024-11-23,1899,8.5,Machine Intelligence Group +AI12950,Principal Data Scientist,114451,CAD,143064,SE,PT,Canada,L,Denmark,50,"Java, Hadoop, Tableau, Computer Vision, Statistics",PhD,9,Consulting,2024-02-04,2024-02-24,1992,8.1,Predictive Systems +AI12951,AI Specialist,106509,SGD,138462,SE,PT,Singapore,S,Singapore,0,"Kubernetes, SQL, Azure, PyTorch, TensorFlow",Associate,5,Consulting,2024-03-26,2024-05-09,2482,5.1,Future Systems +AI12952,AI Research Scientist,122296,JPY,13452560,SE,FL,Japan,S,Japan,50,"Kubernetes, SQL, Git, Data Visualization, NLP",Master,7,Retail,2024-06-17,2024-08-08,1647,9.2,DeepTech Ventures +AI12953,ML Ops Engineer,105130,USD,105130,EX,FL,South Korea,S,Egypt,0,"PyTorch, NLP, Python, Hadoop, GCP",Associate,18,Finance,2025-02-07,2025-04-21,1519,6,Advanced Robotics +AI12954,AI Consultant,54001,USD,54001,EN,PT,Israel,S,Israel,0,"SQL, Mathematics, TensorFlow, Python, Kubernetes",PhD,0,Gaming,2024-08-06,2024-09-01,2349,9.3,Digital Transformation LLC +AI12955,Data Scientist,48008,USD,48008,EN,FL,Finland,M,Singapore,50,"Data Visualization, Linux, Deep Learning, MLOps",Bachelor,1,Government,2024-02-20,2024-04-03,1739,8.7,Future Systems +AI12956,AI Software Engineer,48486,CAD,60608,EN,FT,Canada,S,Canada,0,"Spark, TensorFlow, SQL, Data Visualization, Kubernetes",Bachelor,1,Media,2025-01-18,2025-02-09,1337,10,Smart Analytics +AI12957,Machine Learning Researcher,270112,EUR,229595,EX,CT,Germany,L,Germany,0,"AWS, Python, Computer Vision",PhD,14,Manufacturing,2024-05-16,2024-07-01,855,7.7,DataVision Ltd +AI12958,AI Research Scientist,90538,EUR,76957,MI,FL,Germany,S,India,100,"Kubernetes, Hadoop, TensorFlow, Computer Vision",PhD,2,Real Estate,2024-02-03,2024-02-29,1388,9.1,Advanced Robotics +AI12959,Principal Data Scientist,151418,USD,151418,SE,FL,Israel,L,Israel,100,"Computer Vision, SQL, Scala, GCP, Spark",Master,8,Telecommunications,2024-06-07,2024-08-17,2032,10,Quantum Computing Inc +AI12960,Data Engineer,198647,CHF,178782,EX,FT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, Hadoop, SQL, AWS",PhD,10,Telecommunications,2025-02-12,2025-03-07,909,8.2,Autonomous Tech +AI12961,Deep Learning Engineer,156122,CAD,195153,SE,FT,Canada,L,Canada,100,"Spark, Tableau, Java, Data Visualization",Bachelor,5,Automotive,2025-01-16,2025-02-09,585,9.2,Predictive Systems +AI12962,ML Ops Engineer,164345,USD,164345,EX,PT,Israel,S,Israel,100,"Git, Kubernetes, Statistics",Associate,14,Education,2025-01-23,2025-02-09,2343,6.5,DataVision Ltd +AI12963,Computer Vision Engineer,156737,USD,156737,MI,CT,Denmark,L,Denmark,50,"Spark, R, SQL, Java, Mathematics",Master,2,Gaming,2024-10-24,2024-11-12,860,9.5,Quantum Computing Inc +AI12964,Research Scientist,134102,EUR,113987,SE,PT,Netherlands,M,Netherlands,50,"Data Visualization, Computer Vision, AWS, GCP, Statistics",Bachelor,9,Government,2024-10-06,2024-12-18,847,8.9,Future Systems +AI12965,Head of AI,112325,USD,112325,SE,FL,Israel,M,Israel,50,"Tableau, Azure, Python, Hadoop, Docker",PhD,9,Automotive,2025-02-07,2025-04-12,1786,5.7,Predictive Systems +AI12966,ML Ops Engineer,92446,USD,92446,EX,FT,China,S,New Zealand,50,"Spark, Python, Tableau, TensorFlow, GCP",Master,12,Technology,2025-03-05,2025-03-27,996,5.8,Cloud AI Solutions +AI12967,AI Research Scientist,262159,USD,262159,EX,FT,Ireland,L,Ireland,0,"Python, Spark, TensorFlow",Bachelor,18,Media,2025-04-27,2025-05-12,639,8.4,Predictive Systems +AI12968,Data Engineer,44890,USD,44890,MI,FL,China,M,China,0,"Hadoop, Data Visualization, MLOps, Deep Learning",PhD,4,Finance,2024-09-04,2024-11-04,1790,8.9,DeepTech Ventures +AI12969,AI Product Manager,217707,USD,217707,EX,PT,Ireland,S,Belgium,100,"Docker, Python, AWS, TensorFlow",Master,12,Telecommunications,2024-03-22,2024-04-05,1857,8.4,Autonomous Tech +AI12970,AI Product Manager,154903,USD,154903,EX,FT,Sweden,M,Brazil,50,"Scala, PyTorch, Spark, MLOps, Git",Bachelor,17,Energy,2025-02-03,2025-04-11,1604,7.5,Digital Transformation LLC +AI12971,Computer Vision Engineer,224171,USD,224171,EX,FL,United States,L,United States,50,"Deep Learning, Linux, Java, Python, SQL",Master,16,Education,2024-02-11,2024-04-24,1888,7.7,Autonomous Tech +AI12972,Principal Data Scientist,193696,USD,193696,EX,FL,Norway,M,Norway,100,"Mathematics, Deep Learning, Git, Spark",Associate,10,Manufacturing,2024-09-22,2024-11-11,1564,8.1,Cognitive Computing +AI12973,Robotics Engineer,75949,EUR,64557,EN,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, Docker",Master,0,Education,2024-07-07,2024-08-17,743,9.4,Cloud AI Solutions +AI12974,Data Scientist,54686,USD,54686,EN,FL,Ireland,S,Netherlands,50,"Scala, AWS, Python",Bachelor,1,Healthcare,2024-08-16,2024-10-05,1467,6.8,Machine Intelligence Group +AI12975,Principal Data Scientist,103836,EUR,88261,MI,CT,France,M,Argentina,0,"Azure, Python, Deep Learning",Bachelor,3,Manufacturing,2025-03-15,2025-04-14,2314,9.8,Machine Intelligence Group +AI12976,Machine Learning Researcher,80675,USD,80675,MI,FT,Ireland,S,Ireland,50,"Scala, Java, Kubernetes, Spark, Statistics",Bachelor,4,Retail,2024-05-18,2024-06-01,1182,6.5,DeepTech Ventures +AI12977,Computer Vision Engineer,96576,USD,96576,MI,FT,United States,S,Argentina,50,"GCP, Hadoop, SQL",PhD,4,Government,2024-09-16,2024-10-05,1345,7,Machine Intelligence Group +AI12978,AI Architect,186491,CAD,233114,EX,CT,Canada,L,Canada,0,"NLP, Docker, Tableau, Computer Vision",Associate,19,Consulting,2024-08-15,2024-10-07,912,9.7,DataVision Ltd +AI12979,ML Ops Engineer,112803,CHF,101523,EN,FL,Switzerland,M,Switzerland,0,"R, Tableau, Scala",Associate,1,Transportation,2025-04-13,2025-05-17,1292,5.9,Smart Analytics +AI12980,Data Scientist,66258,CAD,82823,EN,FL,Canada,S,Canada,50,"Scala, Python, Statistics",PhD,1,Manufacturing,2025-04-02,2025-06-01,1933,7.8,Smart Analytics +AI12981,AI Architect,122843,GBP,92132,MI,FL,United Kingdom,L,Ukraine,0,"SQL, Java, Python",PhD,4,Media,2024-01-28,2024-02-12,786,5.7,Autonomous Tech +AI12982,AI Research Scientist,70436,USD,70436,EX,PT,India,M,India,100,"NLP, PyTorch, Statistics, Linux",PhD,12,Finance,2024-10-06,2024-11-30,1345,6.4,Digital Transformation LLC +AI12983,Head of AI,111112,USD,111112,MI,FL,Sweden,L,United States,100,"Python, Tableau, SQL",Bachelor,2,Education,2024-08-27,2024-10-01,1822,8.5,Digital Transformation LLC +AI12984,NLP Engineer,62688,USD,62688,EN,FT,Ireland,S,Mexico,100,"Java, Docker, Statistics, Linux",Bachelor,0,Technology,2025-03-11,2025-03-31,1549,7.4,TechCorp Inc +AI12985,Principal Data Scientist,109993,AUD,148491,MI,FT,Australia,M,Australia,50,"MLOps, Git, NLP, Computer Vision",PhD,3,Energy,2024-01-04,2024-02-26,891,9,Quantum Computing Inc +AI12986,Robotics Engineer,90739,AUD,122498,MI,PT,Australia,M,Malaysia,100,"Computer Vision, NLP, MLOps, PyTorch, Docker",PhD,2,Retail,2024-09-13,2024-10-23,1603,8,TechCorp Inc +AI12987,NLP Engineer,116788,EUR,99270,SE,FL,France,M,France,50,"R, Kubernetes, Computer Vision, Hadoop, Docker",Associate,5,Education,2025-02-14,2025-03-14,2471,9.7,Quantum Computing Inc +AI12988,Data Scientist,89119,EUR,75751,MI,FL,Germany,M,Germany,100,"Hadoop, Linux, Tableau, Docker, Kubernetes",Bachelor,4,Telecommunications,2024-09-23,2024-11-23,2175,6.7,TechCorp Inc +AI12989,Machine Learning Engineer,80678,SGD,104881,MI,FT,Singapore,S,Singapore,100,"Git, SQL, Azure",Master,3,Real Estate,2025-04-23,2025-05-12,1070,9.1,Future Systems +AI12990,Head of AI,146187,EUR,124259,SE,PT,Austria,L,Austria,100,"SQL, MLOps, R",Associate,5,Education,2025-02-17,2025-04-21,1463,8.1,DataVision Ltd +AI12991,Machine Learning Engineer,77845,USD,77845,EX,CT,India,S,India,0,"GCP, Java, Data Visualization",PhD,12,Transportation,2024-02-29,2024-04-30,720,8.2,AI Innovations +AI12992,Autonomous Systems Engineer,73922,USD,73922,EN,FT,United States,M,United Kingdom,50,"TensorFlow, Python, Computer Vision, R, Hadoop",Bachelor,0,Healthcare,2024-01-13,2024-02-19,1487,5.1,Cloud AI Solutions +AI12993,Data Scientist,103867,EUR,88287,MI,PT,Netherlands,S,Netherlands,100,"Linux, Java, R",Master,2,Gaming,2024-06-24,2024-08-24,1252,5.4,DeepTech Ventures +AI12994,AI Research Scientist,125902,EUR,107017,EX,PT,France,S,France,50,"SQL, MLOps, Kubernetes, Mathematics, Computer Vision",PhD,13,Transportation,2025-02-07,2025-04-18,593,9.1,TechCorp Inc +AI12995,AI Architect,29129,USD,29129,MI,FT,India,M,India,0,"Spark, R, Hadoop",Associate,4,Automotive,2025-03-13,2025-04-11,1097,9.8,Digital Transformation LLC +AI12996,AI Software Engineer,43029,USD,43029,EN,PT,South Korea,S,South Korea,100,"Docker, Tableau, SQL",Bachelor,0,Healthcare,2024-02-03,2024-03-06,610,7.4,DeepTech Ventures +AI12997,Machine Learning Engineer,79088,USD,79088,EN,FT,Sweden,L,Sweden,0,"Data Visualization, Tableau, SQL, Mathematics",Bachelor,0,Media,2024-02-17,2024-04-13,1246,8.9,Advanced Robotics +AI12998,AI Specialist,49171,USD,49171,EN,FT,Sweden,S,Turkey,50,"Computer Vision, Python, MLOps",Bachelor,0,Automotive,2024-08-19,2024-09-27,1611,5.5,Digital Transformation LLC +AI12999,Data Analyst,62847,SGD,81701,EN,CT,Singapore,L,Singapore,100,"Git, TensorFlow, Tableau, Scala",PhD,1,Transportation,2024-01-01,2024-02-24,1985,7,Cognitive Computing +AI13000,AI Specialist,80522,USD,80522,SE,CT,South Korea,S,Ghana,100,"PyTorch, Docker, Azure, TensorFlow",Associate,6,Gaming,2025-03-11,2025-03-28,978,8.9,Quantum Computing Inc +AI13001,AI Consultant,64623,EUR,54930,EN,PT,Netherlands,S,Netherlands,50,"Mathematics, AWS, Docker, Statistics",PhD,0,Telecommunications,2024-04-15,2024-06-18,764,9.8,Quantum Computing Inc +AI13002,Machine Learning Engineer,138114,USD,138114,SE,CT,United States,S,United States,0,"MLOps, Linux, Kubernetes",PhD,8,Telecommunications,2024-07-17,2024-09-09,1795,5.7,Digital Transformation LLC +AI13003,AI Consultant,175938,AUD,237516,EX,FL,Australia,L,Australia,100,"Linux, Tableau, Git",Bachelor,12,Gaming,2024-05-23,2024-06-12,1700,9.3,Algorithmic Solutions +AI13004,Data Engineer,58622,USD,58622,EX,PT,China,S,Indonesia,0,"Hadoop, SQL, Computer Vision",Bachelor,17,Automotive,2025-04-30,2025-06-14,807,7.7,Future Systems +AI13005,Data Engineer,79766,GBP,59825,MI,FT,United Kingdom,M,United Kingdom,50,"Statistics, Java, TensorFlow, PyTorch, Computer Vision",PhD,4,Manufacturing,2024-05-13,2024-06-04,905,5.8,AI Innovations +AI13006,Machine Learning Researcher,89995,USD,89995,MI,CT,Norway,S,Norway,0,"TensorFlow, Statistics, R, Docker, Java",Bachelor,2,Government,2024-04-21,2024-06-17,641,5.6,Neural Networks Co +AI13007,NLP Engineer,160586,USD,160586,SE,FL,Ireland,L,Portugal,0,"Git, AWS, Mathematics",Master,7,Transportation,2024-06-17,2024-08-09,2063,6.9,Smart Analytics +AI13008,AI Specialist,109290,USD,109290,EX,FL,China,M,Switzerland,0,"Java, Python, Statistics, GCP, NLP",Master,11,Energy,2025-04-23,2025-05-13,2189,9.8,Cognitive Computing +AI13009,Robotics Engineer,222632,EUR,189237,EX,FL,Netherlands,M,Netherlands,0,"Azure, Kubernetes, GCP, SQL, Hadoop",Master,19,Finance,2024-11-13,2024-12-28,881,5.7,AI Innovations +AI13010,Research Scientist,154841,CHF,139357,MI,CT,Switzerland,L,Australia,0,"Hadoop, MLOps, Kubernetes, Java",Bachelor,4,Automotive,2024-06-24,2024-07-10,1923,6.5,Predictive Systems +AI13011,Machine Learning Engineer,350148,CHF,315133,EX,CT,Switzerland,M,Switzerland,0,"Java, Git, Azure",Associate,15,Finance,2024-08-24,2024-10-06,691,7.7,Smart Analytics +AI13012,AI Research Scientist,85240,USD,85240,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Hadoop, Mathematics",Bachelor,2,Finance,2025-01-09,2025-02-16,731,9.7,Future Systems +AI13013,Robotics Engineer,129453,GBP,97090,SE,FT,United Kingdom,M,United Kingdom,0,"MLOps, Git, Mathematics, Spark",Bachelor,7,Retail,2024-01-19,2024-03-26,2363,6.9,Predictive Systems +AI13014,Data Engineer,269378,SGD,350191,EX,FT,Singapore,M,Singapore,0,"NLP, Python, SQL, Data Visualization",Master,15,Energy,2024-07-27,2024-08-19,2033,8.8,AI Innovations +AI13015,Deep Learning Engineer,280599,USD,280599,EX,PT,Ireland,L,Ireland,0,"Linux, SQL, NLP, GCP",Master,16,Retail,2024-04-22,2024-07-02,893,7.5,DataVision Ltd +AI13016,Machine Learning Engineer,71137,EUR,60466,MI,FL,Netherlands,S,Netherlands,50,"Kubernetes, Computer Vision, SQL, Deep Learning, PyTorch",PhD,3,Education,2024-02-20,2024-03-14,676,9.4,Advanced Robotics +AI13017,Data Scientist,174913,EUR,148676,EX,CT,Netherlands,M,France,0,"NLP, Statistics, Hadoop",Bachelor,19,Manufacturing,2024-08-10,2024-09-04,840,5.5,Digital Transformation LLC +AI13018,Deep Learning Engineer,115630,USD,115630,SE,PT,Israel,S,Estonia,50,"Java, Data Visualization, Scala, Azure, GCP",Master,9,Gaming,2024-09-15,2024-10-26,2138,9.3,DataVision Ltd +AI13019,Robotics Engineer,70395,SGD,91514,EN,PT,Singapore,M,Singapore,100,"SQL, TensorFlow, Java, MLOps",Bachelor,0,Real Estate,2024-12-30,2025-01-20,1089,5.6,DeepTech Ventures +AI13020,Deep Learning Engineer,53458,EUR,45439,EN,FT,Austria,S,Austria,50,"TensorFlow, Python, MLOps, Statistics",Associate,0,Retail,2024-06-19,2024-07-15,1120,8.6,Smart Analytics +AI13021,AI Architect,28054,USD,28054,MI,FT,India,S,Nigeria,0,"Python, Java, TensorFlow",PhD,2,Technology,2024-04-12,2024-05-27,530,6.3,Machine Intelligence Group +AI13022,Head of AI,162934,EUR,138494,SE,CT,Germany,L,Philippines,0,"SQL, Data Visualization, Python, Azure",Master,7,Transportation,2024-09-18,2024-10-30,2064,7.5,Neural Networks Co +AI13023,NLP Engineer,111667,USD,111667,MI,FL,Norway,L,Norway,0,"NLP, Tableau, Azure, Git, Linux",Associate,3,Transportation,2025-01-06,2025-02-25,1817,9.1,Smart Analytics +AI13024,ML Ops Engineer,219405,EUR,186494,EX,FL,Netherlands,L,Netherlands,0,"Java, MLOps, TensorFlow, NLP, SQL",Master,14,Automotive,2024-03-05,2024-04-28,1117,6.1,Future Systems +AI13025,ML Ops Engineer,111552,USD,111552,MI,FL,Sweden,L,Sweden,50,"Scala, Python, GCP",Bachelor,2,Automotive,2024-05-15,2024-06-11,841,6.9,Advanced Robotics +AI13026,AI Consultant,123560,USD,123560,MI,PT,Norway,L,Norway,100,"Spark, Data Visualization, Azure, Java, Docker",Associate,2,Media,2024-04-24,2024-05-09,2045,7.7,Algorithmic Solutions +AI13027,AI Specialist,304170,USD,304170,EX,CT,Norway,M,Spain,50,"Python, Data Visualization, AWS, Docker, TensorFlow",Associate,17,Manufacturing,2024-04-28,2024-06-17,1464,8.9,Digital Transformation LLC +AI13028,AI Software Engineer,151323,USD,151323,EX,FL,South Korea,L,South Korea,0,"Python, TensorFlow, Data Visualization, Scala, AWS",PhD,10,Media,2024-11-14,2025-01-13,1035,5.6,Algorithmic Solutions +AI13029,Head of AI,57091,USD,57091,EN,FT,United States,S,United States,50,"R, Linux, Tableau, Git",PhD,1,Gaming,2024-03-13,2024-05-21,2015,7.2,Algorithmic Solutions +AI13030,Research Scientist,160113,USD,160113,SE,FL,Finland,L,Finland,0,"Kubernetes, Tableau, Computer Vision",Associate,6,Education,2024-09-02,2024-09-25,1518,5.5,Predictive Systems +AI13031,AI Consultant,69137,JPY,7605070,EN,PT,Japan,L,Japan,50,"Git, MLOps, Data Visualization, PyTorch, Azure",PhD,0,Consulting,2024-03-07,2024-05-15,1334,5.5,Future Systems +AI13032,Computer Vision Engineer,52465,AUD,70828,EN,FL,Australia,S,Canada,100,"Scala, Linux, AWS",PhD,0,Transportation,2025-02-12,2025-03-07,1863,7.9,TechCorp Inc +AI13033,Machine Learning Researcher,74221,JPY,8164310,MI,FT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization, Computer Vision",Associate,4,Retail,2025-02-17,2025-04-02,1139,5.2,AI Innovations +AI13034,Robotics Engineer,73237,USD,73237,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2024-02-22,2024-04-08,644,5.8,Quantum Computing Inc +AI13035,Data Scientist,116610,USD,116610,MI,FT,Finland,L,Finland,50,"Hadoop, SQL, Mathematics",PhD,2,Consulting,2024-06-17,2024-08-10,2042,5.3,Autonomous Tech +AI13036,AI Product Manager,155471,CAD,194339,SE,PT,Canada,L,Canada,50,"GCP, PyTorch, Java",Bachelor,8,Energy,2024-12-25,2025-01-17,1576,5.5,AI Innovations +AI13037,Robotics Engineer,53502,USD,53502,SE,CT,India,M,Finland,0,"PyTorch, TensorFlow, Tableau, AWS, Linux",Master,6,Government,2025-02-14,2025-04-24,2130,9.6,Machine Intelligence Group +AI13038,Autonomous Systems Engineer,174189,USD,174189,EX,PT,Ireland,L,United States,50,"R, Mathematics, Hadoop",PhD,16,Consulting,2024-10-05,2024-11-02,1656,8.7,Advanced Robotics +AI13039,Machine Learning Engineer,140960,SGD,183248,SE,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning, Java, R",PhD,9,Finance,2025-01-28,2025-03-07,2233,7.5,Smart Analytics +AI13040,Deep Learning Engineer,65603,SGD,85284,EN,PT,Singapore,S,Singapore,50,"Linux, AWS, Python",Associate,0,Finance,2024-08-01,2024-08-21,1584,5.1,Smart Analytics +AI13041,AI Specialist,280472,EUR,238401,EX,CT,Netherlands,L,Thailand,50,"R, NLP, Java, Data Visualization, Scala",PhD,17,Consulting,2024-07-30,2024-09-25,1827,6.7,Autonomous Tech +AI13042,Research Scientist,194338,EUR,165187,EX,CT,Germany,L,Philippines,100,"SQL, Hadoop, Kubernetes, Java, NLP",Master,17,Manufacturing,2025-01-31,2025-03-20,2167,5.9,Future Systems +AI13043,Autonomous Systems Engineer,162690,USD,162690,MI,FL,Norway,L,Norway,50,"Git, Linux, Docker",Associate,3,Real Estate,2025-04-08,2025-06-18,2084,6.3,TechCorp Inc +AI13044,Machine Learning Researcher,178197,USD,178197,SE,PT,Denmark,M,Colombia,0,"MLOps, Python, TensorFlow",Master,7,Media,2024-05-29,2024-07-07,2093,8.1,Cognitive Computing +AI13045,Machine Learning Researcher,75976,USD,75976,EX,FL,China,S,China,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,15,Transportation,2024-05-16,2024-07-28,1108,6,DeepTech Ventures +AI13046,Machine Learning Engineer,129457,JPY,14240270,SE,CT,Japan,S,Luxembourg,0,"Linux, Python, Git",Associate,8,Education,2024-01-04,2024-01-26,1084,9.9,Advanced Robotics +AI13047,Data Analyst,116495,CAD,145619,EX,FL,Canada,S,Canada,50,"Git, Python, SQL, Data Visualization, Spark",Bachelor,16,Consulting,2025-02-08,2025-03-31,1552,9.2,Neural Networks Co +AI13048,Head of AI,148839,USD,148839,EX,PT,Sweden,S,Sweden,0,"Hadoop, Spark, Deep Learning",Bachelor,17,Media,2024-03-17,2024-04-03,1358,5.5,DataVision Ltd +AI13049,AI Architect,123589,CHF,111230,MI,CT,Switzerland,M,Ireland,50,"Linux, Mathematics, Data Visualization, Docker, PyTorch",PhD,3,Government,2024-06-25,2024-08-22,1871,9.7,Advanced Robotics +AI13050,Deep Learning Engineer,83978,EUR,71381,EN,FT,France,L,France,50,"Python, Mathematics, Scala, Java, TensorFlow",PhD,1,Real Estate,2024-11-18,2024-12-21,1434,9.3,Algorithmic Solutions +AI13051,Principal Data Scientist,66441,EUR,56475,EN,PT,Germany,L,Germany,50,"Spark, Java, Statistics, R",PhD,0,Gaming,2024-08-28,2024-10-13,1565,6.3,TechCorp Inc +AI13052,Machine Learning Researcher,282786,EUR,240368,EX,PT,Netherlands,L,Netherlands,50,"Git, Python, TensorFlow",Master,14,Retail,2024-01-24,2024-03-14,1684,9.8,Predictive Systems +AI13053,Robotics Engineer,102501,CHF,92251,EN,FL,Switzerland,M,Switzerland,0,"SQL, GCP, Data Visualization, PyTorch, R",Master,1,Gaming,2024-09-07,2024-10-01,975,7.9,Cognitive Computing +AI13054,AI Software Engineer,71975,USD,71975,EN,FT,United States,M,Turkey,50,"AWS, Mathematics, Scala, Hadoop",Bachelor,1,Real Estate,2025-03-11,2025-04-05,2168,9.1,Smart Analytics +AI13055,Robotics Engineer,66498,USD,66498,MI,CT,South Korea,M,South Korea,0,"MLOps, PyTorch, Spark, NLP",PhD,3,Manufacturing,2024-07-07,2024-07-22,1418,7.1,Predictive Systems +AI13056,Research Scientist,88009,EUR,74808,EN,FT,Germany,L,Germany,0,"R, SQL, Azure",PhD,1,Technology,2025-03-09,2025-04-20,2288,5.1,DeepTech Ventures +AI13057,AI Consultant,163347,USD,163347,MI,CT,Norway,L,Ireland,100,"GCP, Python, Java, Docker",Master,4,Energy,2024-11-02,2024-11-25,984,8.5,Advanced Robotics +AI13058,Principal Data Scientist,80967,GBP,60725,EN,CT,United Kingdom,L,Luxembourg,100,"Deep Learning, Linux, Python, Hadoop",Associate,1,Technology,2024-11-01,2024-12-16,2453,5,Advanced Robotics +AI13059,AI Architect,108015,EUR,91813,MI,FL,Germany,M,Hungary,0,"Kubernetes, SQL, MLOps, Docker",Associate,4,Telecommunications,2024-08-15,2024-10-11,549,10,Future Systems +AI13060,AI Research Scientist,237965,USD,237965,EX,FT,Norway,L,Norway,100,"Tableau, MLOps, SQL, Linux, Java",Associate,12,Automotive,2024-09-18,2024-10-30,760,9.4,DeepTech Ventures +AI13061,Computer Vision Engineer,48996,USD,48996,MI,FL,China,L,China,100,"Java, Linux, Python",Associate,3,Manufacturing,2024-12-13,2025-01-22,2075,6.9,DeepTech Ventures +AI13062,Machine Learning Engineer,293914,CHF,264523,EX,CT,Switzerland,L,Estonia,50,"Statistics, Python, Linux",Bachelor,16,Manufacturing,2025-03-04,2025-04-15,1936,8.8,Algorithmic Solutions +AI13063,Research Scientist,68050,USD,68050,EN,FT,Ireland,M,Ireland,0,"Statistics, GCP, Deep Learning, Java, Python",Master,1,Healthcare,2024-12-29,2025-01-13,620,7,Digital Transformation LLC +AI13064,Machine Learning Researcher,66356,USD,66356,EN,PT,Ireland,M,Ireland,100,"Data Visualization, Docker, Python",Associate,0,Real Estate,2024-03-31,2024-05-26,1050,6.3,Cognitive Computing +AI13065,Data Analyst,68146,USD,68146,EN,FL,Finland,L,Thailand,0,"Python, Scala, Tableau",Associate,1,Real Estate,2024-09-20,2024-11-21,733,5.9,TechCorp Inc +AI13066,Data Scientist,133642,CAD,167053,SE,PT,Canada,L,Canada,50,"PyTorch, Statistics, Azure, Python",Bachelor,8,Technology,2025-04-27,2025-05-15,1623,5.8,Machine Intelligence Group +AI13067,AI Software Engineer,53834,USD,53834,SE,FT,China,M,China,0,"Git, GCP, Docker",Master,9,Government,2025-04-01,2025-06-03,2469,7.3,Cloud AI Solutions +AI13068,Head of AI,38246,USD,38246,EN,CT,South Korea,S,Turkey,100,"Git, Docker, SQL, Deep Learning, GCP",Master,1,Automotive,2024-06-15,2024-07-29,2133,7.9,Future Systems +AI13069,NLP Engineer,87601,JPY,9636110,EN,FL,Japan,L,Malaysia,0,"Spark, Git, Kubernetes",Master,1,Retail,2024-02-26,2024-04-05,521,6.7,AI Innovations +AI13070,AI Research Scientist,83658,AUD,112938,MI,FT,Australia,L,Australia,0,"Linux, TensorFlow, Hadoop, PyTorch",Associate,3,Healthcare,2024-06-30,2024-08-28,2162,5.8,Predictive Systems +AI13071,Robotics Engineer,109147,AUD,147348,SE,CT,Australia,S,Australia,0,"Mathematics, Git, Deep Learning, Spark, Linux",Associate,9,Transportation,2024-09-15,2024-10-26,1351,5.6,AI Innovations +AI13072,AI Specialist,61946,USD,61946,EN,PT,Israel,L,Vietnam,100,"Linux, Kubernetes, PyTorch",Associate,1,Technology,2025-04-19,2025-05-16,1210,6.7,AI Innovations +AI13073,Data Scientist,343823,CHF,309441,EX,CT,Switzerland,L,United Kingdom,0,"SQL, Docker, TensorFlow",PhD,16,Manufacturing,2024-07-14,2024-09-24,1773,6.3,Future Systems +AI13074,Data Analyst,109859,USD,109859,MI,PT,Norway,L,Denmark,50,"GCP, Docker, Computer Vision, Kubernetes, Linux",Master,4,Automotive,2024-05-04,2024-06-20,1533,7.7,Machine Intelligence Group +AI13075,Machine Learning Researcher,186936,EUR,158896,EX,CT,Germany,S,Germany,100,"GCP, AWS, MLOps, TensorFlow, Deep Learning",Bachelor,14,Automotive,2024-06-01,2024-06-16,1693,6,Quantum Computing Inc +AI13076,AI Specialist,56525,EUR,48046,EN,PT,France,M,France,50,"GCP, SQL, Data Visualization, Hadoop",Associate,1,Real Estate,2024-09-21,2024-10-26,715,5.9,Neural Networks Co +AI13077,Data Scientist,65610,CAD,82013,EN,FT,Canada,S,Canada,100,"Azure, Kubernetes, SQL, Docker",PhD,1,Education,2025-01-22,2025-02-18,642,6.6,Advanced Robotics +AI13078,Research Scientist,66543,USD,66543,EN,CT,Sweden,L,Sweden,50,"Data Visualization, Spark, TensorFlow, Java",Master,1,Education,2025-02-12,2025-03-17,1971,5.9,Cloud AI Solutions +AI13079,Head of AI,95195,GBP,71396,EN,CT,United Kingdom,L,Switzerland,50,"Statistics, PyTorch, SQL, GCP, Docker",Master,1,Education,2024-07-27,2024-08-27,1362,8.4,Predictive Systems +AI13080,Data Engineer,88191,USD,88191,MI,CT,Norway,S,Norway,0,"Java, Deep Learning, Python",PhD,2,Telecommunications,2024-09-30,2024-12-08,788,7.8,Machine Intelligence Group +AI13081,AI Software Engineer,85673,USD,85673,MI,FL,Finland,S,Finland,0,"Python, Hadoop, TensorFlow, Linux",PhD,4,Healthcare,2024-10-02,2024-10-17,917,5.6,Advanced Robotics +AI13082,Computer Vision Engineer,250835,USD,250835,EX,FT,Finland,L,Finland,0,"Hadoop, MLOps, R, Python",Master,14,Retail,2025-04-22,2025-07-03,918,9.8,Machine Intelligence Group +AI13083,Machine Learning Engineer,65750,EUR,55888,MI,FT,Austria,S,Austria,50,"Tableau, TensorFlow, Python, NLP, R",PhD,3,Automotive,2025-04-03,2025-05-27,2456,8.9,Future Systems +AI13084,Principal Data Scientist,96483,USD,96483,MI,PT,Norway,M,Norway,0,"Python, Kubernetes, Azure, Statistics, Linux",PhD,2,Media,2024-02-05,2024-02-28,605,8.1,TechCorp Inc +AI13085,Principal Data Scientist,111619,EUR,94876,MI,PT,Germany,L,Japan,0,"Computer Vision, PyTorch, NLP, TensorFlow, Kubernetes",Associate,3,Consulting,2025-03-10,2025-04-05,967,5.3,Machine Intelligence Group +AI13086,Data Analyst,68910,USD,68910,MI,FT,Sweden,S,France,100,"SQL, GCP, Tableau, TensorFlow",Associate,2,Technology,2024-04-12,2024-05-02,2143,6.5,Quantum Computing Inc +AI13087,Research Scientist,32232,USD,32232,MI,FL,India,M,Finland,0,"Linux, AWS, Hadoop, SQL",Master,4,Energy,2024-08-15,2024-10-12,1713,8.9,Digital Transformation LLC +AI13088,AI Product Manager,85895,USD,85895,MI,PT,South Korea,L,South Korea,100,"MLOps, Scala, Docker, AWS, Spark",Associate,4,Gaming,2024-07-16,2024-09-18,1126,5,Machine Intelligence Group +AI13089,AI Research Scientist,151896,EUR,129112,EX,PT,Netherlands,S,United Kingdom,100,"Kubernetes, Java, Scala",Associate,18,Media,2024-07-14,2024-09-15,2330,6.7,Advanced Robotics +AI13090,Computer Vision Engineer,282442,USD,282442,EX,CT,United States,M,United States,100,"SQL, Spark, Python, Docker",Master,15,Technology,2024-02-23,2024-03-25,1246,9.6,Autonomous Tech +AI13091,Data Analyst,132020,USD,132020,SE,PT,United States,M,United States,100,"SQL, Java, AWS, Spark",PhD,9,Transportation,2024-10-22,2024-12-30,1902,8.7,TechCorp Inc +AI13092,AI Research Scientist,118211,EUR,100479,SE,PT,Austria,S,Austria,50,"Hadoop, Mathematics, Python, Scala, TensorFlow",Associate,7,Government,2024-11-04,2024-12-26,1773,8.1,Neural Networks Co +AI13093,Machine Learning Engineer,95484,USD,95484,MI,FT,Sweden,L,Sweden,50,"Linux, Azure, Kubernetes, AWS, SQL",PhD,3,Media,2024-12-31,2025-02-19,2495,8,Cloud AI Solutions +AI13094,Deep Learning Engineer,211850,SGD,275405,EX,PT,Singapore,M,Singapore,50,"Tableau, Python, Linux, Computer Vision, TensorFlow",Master,11,Technology,2024-05-22,2024-06-19,1157,5.6,Advanced Robotics +AI13095,Research Scientist,120477,USD,120477,MI,PT,Denmark,S,Canada,0,"GCP, Kubernetes, TensorFlow, Spark, Data Visualization",PhD,4,Telecommunications,2024-11-21,2024-12-15,701,7.1,Predictive Systems +AI13096,NLP Engineer,218123,USD,218123,EX,FT,Ireland,M,Vietnam,0,"GCP, Azure, Python",Bachelor,17,Energy,2025-03-17,2025-04-24,1056,5.3,Advanced Robotics +AI13097,AI Software Engineer,98570,USD,98570,MI,FT,Sweden,M,Russia,100,"Scala, Computer Vision, Azure, Mathematics, Data Visualization",Master,2,Technology,2024-06-21,2024-08-03,672,8.2,Autonomous Tech +AI13098,AI Architect,81790,USD,81790,MI,FL,Israel,L,Thailand,50,"SQL, Kubernetes, Hadoop, PyTorch, GCP",Bachelor,4,Media,2024-06-30,2024-08-17,830,7.7,Digital Transformation LLC +AI13099,NLP Engineer,91536,CAD,114420,MI,FT,Canada,L,Canada,100,"Spark, Linux, TensorFlow, MLOps, Java",PhD,2,Real Estate,2024-04-11,2024-05-08,1728,9.3,Cognitive Computing +AI13100,AI Specialist,116205,EUR,98774,SE,PT,Austria,M,Austria,0,"Java, SQL, Data Visualization",Bachelor,8,Media,2025-01-23,2025-03-26,2388,9.5,Predictive Systems +AI13101,Principal Data Scientist,58576,EUR,49790,EN,CT,France,M,Hungary,100,"Docker, Linux, Data Visualization, GCP",PhD,0,Transportation,2024-09-13,2024-10-14,2244,7.6,Advanced Robotics +AI13102,AI Software Engineer,106840,CHF,96156,MI,PT,Switzerland,S,Switzerland,0,"Spark, Scala, SQL, Statistics, Deep Learning",Bachelor,4,Transportation,2024-10-09,2024-12-14,862,9.3,Future Systems +AI13103,Computer Vision Engineer,123259,CAD,154074,SE,FL,Canada,L,Canada,50,"Data Visualization, NLP, R",Associate,9,Automotive,2024-07-12,2024-08-10,1202,9.9,Predictive Systems +AI13104,Deep Learning Engineer,88273,JPY,9710030,MI,PT,Japan,M,Australia,50,"NLP, Docker, Computer Vision, SQL",Master,2,Real Estate,2024-04-08,2024-05-04,775,8.3,Cloud AI Solutions +AI13105,AI Specialist,133522,USD,133522,SE,PT,Denmark,M,Turkey,100,"Mathematics, R, Linux, Java",Associate,9,Finance,2024-12-28,2025-02-08,1878,6.2,Predictive Systems +AI13106,AI Consultant,159549,USD,159549,EX,FL,Finland,L,Finland,100,"Linux, PyTorch, MLOps, Java, Kubernetes",PhD,13,Media,2024-03-04,2024-04-15,1430,8.6,Machine Intelligence Group +AI13107,ML Ops Engineer,106103,CAD,132629,SE,FT,Canada,M,Canada,50,"Hadoop, PyTorch, MLOps",PhD,5,Automotive,2024-10-23,2024-12-21,1229,7.9,TechCorp Inc +AI13108,AI Consultant,98258,EUR,83519,SE,FL,France,M,France,50,"Docker, AWS, Tableau, Git",Associate,5,Telecommunications,2024-03-24,2024-05-25,2457,5.9,Cognitive Computing +AI13109,Autonomous Systems Engineer,125492,USD,125492,EX,FT,Ireland,S,Ireland,100,"Spark, Scala, MLOps, Linux",PhD,14,Retail,2025-03-27,2025-05-12,1351,8.2,Predictive Systems +AI13110,AI Research Scientist,166393,EUR,141434,EX,PT,Austria,S,Egypt,100,"AWS, Kubernetes, MLOps",Associate,15,Finance,2025-02-09,2025-04-20,1894,5.5,Neural Networks Co +AI13111,ML Ops Engineer,86105,EUR,73189,MI,FT,Austria,M,Austria,0,"Linux, Java, R, GCP",Bachelor,4,Healthcare,2024-08-27,2024-10-28,2399,7.6,Cloud AI Solutions +AI13112,Data Engineer,125111,USD,125111,SE,FT,Finland,S,Finland,0,"Scala, SQL, Mathematics, Statistics, Linux",Associate,5,Manufacturing,2024-01-14,2024-03-27,1070,5,DataVision Ltd +AI13113,ML Ops Engineer,103754,USD,103754,MI,FT,Sweden,M,Egypt,100,"Docker, Deep Learning, Python, Computer Vision, Git",Associate,2,Consulting,2025-04-22,2025-05-20,731,5.5,Machine Intelligence Group +AI13114,Research Scientist,65132,USD,65132,EN,PT,Sweden,M,Mexico,100,"Docker, Statistics, R, PyTorch, TensorFlow",Bachelor,1,Education,2025-04-16,2025-05-22,1489,9.5,DataVision Ltd +AI13115,AI Architect,195654,CHF,176089,EX,FT,Switzerland,S,Switzerland,100,"SQL, MLOps, Scala",Bachelor,11,Consulting,2024-06-08,2024-07-12,658,6.5,Autonomous Tech +AI13116,Data Engineer,65035,EUR,55280,EN,FL,Austria,S,Philippines,0,"TensorFlow, Data Visualization, Tableau, Scala",Associate,0,Energy,2024-11-12,2025-01-23,1952,9.1,Cognitive Computing +AI13117,AI Product Manager,248091,EUR,210877,EX,CT,France,L,France,50,"Statistics, Spark, SQL, Hadoop",PhD,15,Energy,2024-10-10,2024-12-10,860,5.9,Autonomous Tech +AI13118,Robotics Engineer,141327,EUR,120128,SE,FL,Austria,M,Philippines,0,"GCP, PyTorch, TensorFlow",Bachelor,9,Media,2024-07-29,2024-08-29,1588,7.3,Cloud AI Solutions +AI13119,Data Engineer,343050,USD,343050,EX,PT,Denmark,L,Denmark,100,"MLOps, Kubernetes, SQL",Associate,13,Media,2024-10-26,2024-11-26,1308,5.8,Cloud AI Solutions +AI13120,NLP Engineer,169592,USD,169592,SE,FL,Norway,M,Estonia,0,"Spark, SQL, Data Visualization, Deep Learning",Master,6,Education,2024-12-23,2025-01-27,1423,8.5,Quantum Computing Inc +AI13121,Computer Vision Engineer,73049,EUR,62092,EN,PT,Germany,M,Canada,0,"Mathematics, AWS, SQL",Master,0,Transportation,2024-09-25,2024-11-30,1971,5.8,Quantum Computing Inc +AI13122,Data Analyst,107795,USD,107795,MI,FT,United States,L,United States,0,"R, SQL, AWS",PhD,3,Education,2024-11-18,2024-12-29,1861,9.3,DataVision Ltd +AI13123,Principal Data Scientist,103946,AUD,140327,SE,FT,Australia,M,Australia,100,"Tableau, Python, Statistics",Master,6,Education,2024-10-15,2024-11-09,645,6.3,AI Innovations +AI13124,AI Specialist,141419,JPY,15556090,SE,PT,Japan,S,Japan,100,"Python, MLOps, TensorFlow, Kubernetes, Docker",Master,5,Finance,2024-09-20,2024-10-14,1712,5.6,Neural Networks Co +AI13125,Robotics Engineer,56273,USD,56273,SE,FT,China,S,China,0,"Linux, Python, TensorFlow, Computer Vision",Associate,8,Healthcare,2024-03-03,2024-03-21,1241,8.3,Cloud AI Solutions +AI13126,ML Ops Engineer,225699,AUD,304694,EX,FL,Australia,S,Australia,50,"Linux, Spark, Git, Mathematics, Python",Bachelor,18,Transportation,2024-06-09,2024-07-01,834,7.2,Cognitive Computing +AI13127,Autonomous Systems Engineer,191962,USD,191962,EX,FT,Israel,S,Israel,100,"Tableau, AWS, Statistics",Master,12,Technology,2025-03-15,2025-05-19,1939,9.3,DataVision Ltd +AI13128,Robotics Engineer,65172,EUR,55396,EN,PT,Austria,L,Austria,100,"Docker, Kubernetes, Java, R, Hadoop",PhD,0,Consulting,2024-05-13,2024-07-13,2202,6.3,DataVision Ltd +AI13129,Data Engineer,152054,AUD,205273,SE,FL,Australia,L,Australia,50,"Python, Kubernetes, R, Mathematics",Bachelor,8,Finance,2024-06-24,2024-08-02,685,10,Smart Analytics +AI13130,AI Product Manager,27800,USD,27800,EN,FT,India,M,Kenya,100,"AWS, Git, Python, SQL, Statistics",PhD,1,Media,2024-06-19,2024-08-28,2359,5.1,DataVision Ltd +AI13131,ML Ops Engineer,87373,AUD,117954,MI,PT,Australia,S,Australia,0,"Linux, Git, Scala, R",Master,3,Education,2024-03-01,2024-04-23,1287,9.8,DataVision Ltd +AI13132,AI Product Manager,121517,USD,121517,EX,FL,China,L,China,50,"Computer Vision, Git, MLOps, Tableau",Bachelor,17,Retail,2024-01-02,2024-01-26,714,5.2,Neural Networks Co +AI13133,Principal Data Scientist,95651,USD,95651,MI,FL,Sweden,S,Turkey,100,"GCP, Tableau, Spark",Master,4,Retail,2024-05-05,2024-06-09,1097,6.3,Quantum Computing Inc +AI13134,NLP Engineer,135229,EUR,114945,SE,CT,Germany,S,Singapore,0,"GCP, Docker, Tableau, Linux",Associate,5,Finance,2024-03-03,2024-04-19,1628,7.6,Predictive Systems +AI13135,Machine Learning Researcher,59742,USD,59742,EN,CT,South Korea,L,Italy,0,"Docker, Python, NLP, Kubernetes, Data Visualization",Associate,1,Automotive,2025-03-08,2025-05-01,2448,6.7,Predictive Systems +AI13136,Head of AI,285325,AUD,385189,EX,CT,Australia,L,Ireland,100,"Scala, Spark, GCP, Deep Learning, MLOps",Associate,14,Finance,2024-02-01,2024-03-18,1668,5.3,Cognitive Computing +AI13137,Machine Learning Engineer,177700,GBP,133275,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Python",PhD,14,Retail,2024-03-13,2024-05-11,504,8.2,Quantum Computing Inc +AI13138,AI Architect,129173,USD,129173,MI,PT,United States,L,United States,50,"Scala, MLOps, Spark, NLP",PhD,2,Technology,2024-08-20,2024-10-29,1608,6,Predictive Systems +AI13139,AI Product Manager,124365,EUR,105710,SE,FL,Germany,L,Germany,100,"Statistics, AWS, Java",Master,5,Real Estate,2025-03-21,2025-05-30,2132,9.4,Digital Transformation LLC +AI13140,Data Scientist,28510,USD,28510,EN,CT,India,L,India,100,"TensorFlow, Scala, Java, Python",Associate,0,Manufacturing,2024-01-19,2024-04-01,514,7.1,Future Systems +AI13141,Autonomous Systems Engineer,147366,AUD,198944,SE,CT,Australia,L,India,50,"PyTorch, AWS, TensorFlow, SQL",Master,8,Government,2024-05-16,2024-06-30,2032,9.6,Smart Analytics +AI13142,Data Engineer,54967,EUR,46722,EN,PT,Netherlands,S,Netherlands,0,"Linux, SQL, TensorFlow, Deep Learning, AWS",Master,1,Education,2024-03-17,2024-04-05,1683,6.5,AI Innovations +AI13143,Machine Learning Researcher,56049,EUR,47642,EN,PT,France,S,France,50,"Kubernetes, Linux, Git, Azure, Mathematics",Bachelor,0,Government,2024-09-14,2024-10-18,1354,8.9,Machine Intelligence Group +AI13144,Data Scientist,50627,USD,50627,EN,CT,Ireland,S,Ireland,100,"AWS, Git, Python",Bachelor,0,Finance,2024-09-29,2024-10-22,767,7,Quantum Computing Inc +AI13145,Principal Data Scientist,129562,JPY,14251820,SE,PT,Japan,L,Japan,100,"Deep Learning, Azure, NLP, Python",PhD,7,Media,2024-12-02,2024-12-22,1863,7.5,Smart Analytics +AI13146,Autonomous Systems Engineer,86193,USD,86193,MI,FL,Finland,M,Finland,50,"Kubernetes, Statistics, Python",Bachelor,2,Automotive,2024-03-16,2024-04-19,855,8.9,Quantum Computing Inc +AI13147,AI Research Scientist,242707,CAD,303384,EX,PT,Canada,L,Canada,50,"Python, Spark, PyTorch, R",Associate,13,Telecommunications,2025-02-19,2025-03-22,1183,5.7,Quantum Computing Inc +AI13148,Data Engineer,22180,USD,22180,EN,FL,China,S,China,100,"Statistics, Data Visualization, Git, Linux",Bachelor,1,Energy,2024-05-22,2024-08-01,2339,8.8,Digital Transformation LLC +AI13149,Computer Vision Engineer,144736,CHF,130262,MI,CT,Switzerland,L,Switzerland,50,"Git, Docker, Azure",Associate,2,Telecommunications,2024-10-23,2024-12-31,2474,8.9,Predictive Systems +AI13150,Data Scientist,89075,EUR,75714,MI,FT,Netherlands,M,Brazil,100,"Mathematics, SQL, NLP, Computer Vision",Associate,4,Telecommunications,2024-02-06,2024-04-17,1369,8.4,Algorithmic Solutions +AI13151,Research Scientist,146125,JPY,16073750,SE,CT,Japan,M,Vietnam,100,"Scala, Statistics, Azure",Bachelor,5,Manufacturing,2024-01-11,2024-02-22,1903,8.1,Quantum Computing Inc +AI13152,Data Analyst,57872,EUR,49191,EN,FT,France,S,Czech Republic,50,"Scala, Docker, Statistics, Spark",Master,1,Healthcare,2024-12-22,2025-01-06,1208,9.7,Cognitive Computing +AI13153,Machine Learning Researcher,49720,USD,49720,EX,PT,India,M,Finland,100,"Deep Learning, Python, Tableau",Master,16,Retail,2024-10-19,2024-11-05,1858,8.1,AI Innovations +AI13154,AI Architect,94893,USD,94893,EX,FL,China,S,Germany,50,"Docker, Python, AWS, TensorFlow",Master,11,Manufacturing,2024-08-29,2024-11-07,1073,6.1,AI Innovations +AI13155,NLP Engineer,124615,EUR,105923,SE,PT,Austria,S,Austria,100,"Git, SQL, Java",Bachelor,6,Retail,2025-01-30,2025-04-03,911,5.3,DeepTech Ventures +AI13156,Data Analyst,136314,CHF,122683,SE,CT,Switzerland,S,Switzerland,50,"Docker, R, AWS",PhD,7,Telecommunications,2024-04-19,2024-06-25,1481,6,Advanced Robotics +AI13157,Deep Learning Engineer,60206,EUR,51175,EN,FL,France,S,Philippines,50,"Data Visualization, Linux, Tableau",Associate,0,Consulting,2024-12-01,2025-01-06,912,8.4,DataVision Ltd +AI13158,AI Product Manager,99753,USD,99753,MI,FT,Ireland,M,Denmark,100,"SQL, Scala, Linux",Associate,2,Consulting,2025-04-13,2025-05-07,1352,9.4,DataVision Ltd +AI13159,Machine Learning Engineer,93871,AUD,126726,SE,FL,Australia,S,Australia,100,"Scala, Java, AWS",Bachelor,5,Finance,2025-04-15,2025-05-10,2344,9.1,Cognitive Computing +AI13160,Data Scientist,116623,EUR,99130,EX,PT,France,S,India,100,"AWS, NLP, MLOps, Linux, GCP",Bachelor,14,Retail,2024-07-12,2024-08-02,825,8.8,Quantum Computing Inc +AI13161,Robotics Engineer,102693,SGD,133501,SE,CT,Singapore,S,Singapore,100,"Tableau, R, Linux, Java, PyTorch",Master,5,Automotive,2024-05-27,2024-06-21,1700,8,Predictive Systems +AI13162,Head of AI,62122,USD,62122,EN,PT,Finland,M,Finland,100,"Spark, Scala, Azure, Statistics, MLOps",Bachelor,1,Gaming,2024-04-08,2024-06-05,854,8.2,Autonomous Tech +AI13163,NLP Engineer,58719,USD,58719,SE,CT,China,L,China,100,"Python, MLOps, Scala, Computer Vision, Statistics",Master,8,Real Estate,2025-03-01,2025-05-03,2172,9.7,Machine Intelligence Group +AI13164,AI Software Engineer,59864,USD,59864,EN,CT,Sweden,M,Mexico,50,"Deep Learning, SQL, Data Visualization, MLOps, PyTorch",PhD,1,Real Estate,2024-09-30,2024-10-16,906,9.1,DataVision Ltd +AI13165,Data Engineer,248769,CHF,223892,EX,CT,Switzerland,L,Switzerland,50,"Python, TensorFlow, SQL, Docker, AWS",Associate,12,Real Estate,2025-04-23,2025-05-09,1869,9.4,Algorithmic Solutions +AI13166,Head of AI,100787,USD,100787,MI,FL,Israel,L,Colombia,0,"Hadoop, Kubernetes, SQL, Computer Vision",Master,2,Media,2024-03-18,2024-04-12,878,9.6,Predictive Systems +AI13167,Deep Learning Engineer,90501,EUR,76926,MI,PT,Germany,L,Germany,50,"GCP, MLOps, Azure",Associate,4,Finance,2025-03-13,2025-04-12,1900,7.7,Advanced Robotics +AI13168,AI Product Manager,98721,USD,98721,MI,FT,Sweden,M,Belgium,50,"Data Visualization, PyTorch, NLP",Associate,3,Automotive,2024-09-17,2024-10-20,1279,6.1,Quantum Computing Inc +AI13169,ML Ops Engineer,216873,USD,216873,EX,FT,Sweden,L,Sweden,0,"TensorFlow, Linux, MLOps, Computer Vision",PhD,11,Automotive,2024-04-17,2024-06-14,500,9.5,Quantum Computing Inc +AI13170,AI Consultant,51793,EUR,44024,EN,PT,Austria,S,South Africa,50,"Statistics, Mathematics, GCP, Spark",Bachelor,1,Healthcare,2024-10-12,2024-11-27,625,9.8,Quantum Computing Inc +AI13171,Machine Learning Engineer,89005,EUR,75654,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Mathematics, NLP",Master,3,Telecommunications,2025-04-02,2025-04-29,1954,5.2,DeepTech Ventures +AI13172,Data Analyst,112200,USD,112200,SE,FL,Israel,M,Israel,100,"TensorFlow, Scala, Mathematics",Associate,9,Consulting,2025-01-13,2025-03-09,1087,5.2,TechCorp Inc +AI13173,AI Product Manager,93493,USD,93493,MI,FL,Ireland,S,Switzerland,50,"TensorFlow, Python, Tableau, Deep Learning",Bachelor,4,Technology,2024-09-14,2024-09-29,1688,5.5,TechCorp Inc +AI13174,Machine Learning Researcher,150175,AUD,202736,EX,PT,Australia,M,Australia,100,"Java, R, SQL",Master,17,Government,2024-12-20,2025-02-24,2485,8.3,TechCorp Inc +AI13175,AI Research Scientist,66666,CAD,83333,EN,CT,Canada,L,China,100,"Linux, TensorFlow, Deep Learning, Python",Associate,0,Finance,2024-07-05,2024-09-02,1773,6.9,Future Systems +AI13176,Robotics Engineer,101266,USD,101266,MI,FT,Finland,L,Finland,100,"MLOps, Git, Python, Statistics, Linux",PhD,4,Education,2024-09-13,2024-10-30,1769,5.8,Digital Transformation LLC +AI13177,Autonomous Systems Engineer,76613,USD,76613,EN,FT,United States,M,United States,50,"Linux, Java, TensorFlow, MLOps",Master,1,Telecommunications,2024-08-02,2024-09-02,1973,8.5,Digital Transformation LLC +AI13178,Machine Learning Researcher,49536,USD,49536,EX,PT,India,S,Austria,50,"Spark, Docker, R, Deep Learning",PhD,18,Real Estate,2024-11-24,2024-12-24,2071,8.5,Digital Transformation LLC +AI13179,Deep Learning Engineer,61260,USD,61260,SE,CT,China,L,China,0,"Scala, R, Python",Master,9,Automotive,2025-01-07,2025-03-04,859,6.5,Cognitive Computing +AI13180,AI Specialist,149430,USD,149430,EX,PT,Finland,L,Argentina,100,"R, Python, Java, PyTorch, Tableau",Associate,14,Media,2024-12-09,2024-12-29,1331,7.2,Neural Networks Co +AI13181,Data Scientist,123078,EUR,104616,SE,FT,Austria,L,Austria,0,"Docker, Git, Deep Learning, Statistics, Hadoop",Bachelor,6,Education,2024-08-21,2024-10-24,1714,9.4,Advanced Robotics +AI13182,Machine Learning Engineer,70132,EUR,59612,MI,FL,Austria,S,Thailand,0,"Computer Vision, NLP, Python",Bachelor,2,Automotive,2025-04-22,2025-05-12,1803,9.6,Future Systems +AI13183,Data Analyst,141806,USD,141806,MI,PT,United States,L,United States,100,"MLOps, Kubernetes, GCP, R",Associate,2,Energy,2025-01-03,2025-03-08,818,5.4,Smart Analytics +AI13184,AI Specialist,111124,USD,111124,EX,PT,China,M,Germany,50,"Python, Data Visualization, TensorFlow, Java",Associate,10,Consulting,2024-04-15,2024-05-07,1584,5.1,Predictive Systems +AI13185,Deep Learning Engineer,152448,EUR,129581,EX,FL,Germany,S,Germany,100,"GCP, Hadoop, NLP, Tableau, Computer Vision",PhD,10,Gaming,2024-06-20,2024-08-06,1048,6.7,Cloud AI Solutions +AI13186,ML Ops Engineer,147859,EUR,125680,EX,FL,Germany,S,Germany,0,"Kubernetes, Tableau, AWS, Computer Vision",PhD,13,Energy,2024-03-20,2024-04-04,1994,5.9,AI Innovations +AI13187,AI Architect,71833,CAD,89791,MI,FT,Canada,M,Belgium,100,"Java, SQL, Spark",Master,4,Telecommunications,2024-09-15,2024-11-25,2415,8.3,Predictive Systems +AI13188,Autonomous Systems Engineer,265945,USD,265945,EX,CT,Denmark,L,Denmark,0,"Data Visualization, AWS, Tableau",PhD,13,Real Estate,2024-02-05,2024-04-10,1051,8.5,Smart Analytics +AI13189,Deep Learning Engineer,182312,EUR,154965,EX,PT,Austria,L,Austria,100,"Python, Data Visualization, Statistics, MLOps",PhD,18,Telecommunications,2024-11-19,2024-12-11,1525,7.7,Smart Analytics +AI13190,Robotics Engineer,81783,USD,81783,MI,FL,Ireland,M,Israel,0,"Hadoop, Mathematics, MLOps",Master,2,Energy,2024-11-18,2025-01-03,1787,5.5,Cognitive Computing +AI13191,Computer Vision Engineer,283095,JPY,31140450,EX,PT,Japan,L,Japan,50,"Computer Vision, Python, MLOps, PyTorch",Bachelor,12,Manufacturing,2024-08-02,2024-08-28,2074,5.4,Future Systems +AI13192,AI Research Scientist,140169,EUR,119144,SE,CT,Austria,M,Austria,100,"PyTorch, Data Visualization, SQL",PhD,5,Retail,2025-01-20,2025-02-22,1103,7.7,Cognitive Computing +AI13193,Deep Learning Engineer,55566,EUR,47231,EN,CT,France,S,France,50,"Hadoop, Scala, Java",PhD,0,Energy,2024-06-03,2024-07-12,2240,7.9,Advanced Robotics +AI13194,ML Ops Engineer,312518,CHF,281266,EX,PT,Switzerland,L,New Zealand,50,"Python, GCP, NLP, SQL",Master,17,Finance,2024-09-23,2024-12-01,2430,5.9,Cloud AI Solutions +AI13195,Data Analyst,42317,USD,42317,EN,PT,South Korea,S,Russia,0,"GCP, Python, Git",Associate,0,Education,2025-02-05,2025-03-17,1394,10,Smart Analytics +AI13196,Autonomous Systems Engineer,115876,USD,115876,SE,CT,Finland,S,United States,0,"Git, Data Visualization, Deep Learning, MLOps",Bachelor,9,Energy,2025-03-20,2025-05-19,925,6,Cloud AI Solutions +AI13197,AI Software Engineer,59246,AUD,79982,EN,FT,Australia,L,Australia,0,"Docker, Spark, Data Visualization",PhD,0,Healthcare,2024-07-11,2024-08-30,830,9,Machine Intelligence Group +AI13198,Data Scientist,138647,GBP,103985,SE,PT,United Kingdom,M,Poland,50,"NLP, Docker, Kubernetes, Statistics",Master,7,Telecommunications,2024-03-21,2024-05-27,1264,6.5,Cloud AI Solutions +AI13199,AI Consultant,28360,USD,28360,EN,FL,China,M,Luxembourg,0,"Python, TensorFlow, PyTorch",Associate,0,Retail,2024-04-14,2024-05-08,1103,9.6,Cognitive Computing +AI13200,Autonomous Systems Engineer,197908,JPY,21769880,EX,FL,Japan,M,Japan,50,"Git, Linux, Azure, Data Visualization",Associate,16,Real Estate,2025-02-18,2025-04-15,1951,6.4,AI Innovations +AI13201,AI Software Engineer,181959,AUD,245645,EX,CT,Australia,S,Australia,50,"SQL, GCP, Azure, NLP, Spark",Associate,17,Consulting,2024-11-09,2024-12-19,1213,8.5,Machine Intelligence Group +AI13202,ML Ops Engineer,27691,USD,27691,EN,FL,India,M,India,100,"Kubernetes, TensorFlow, GCP, Statistics, Azure",Associate,1,Healthcare,2025-03-15,2025-04-13,1099,7.8,Quantum Computing Inc +AI13203,Research Scientist,142866,JPY,15715260,SE,CT,Japan,M,Japan,50,"Azure, AWS, Statistics, Scala",PhD,9,Government,2025-01-08,2025-01-24,2332,7.9,Smart Analytics +AI13204,Data Engineer,79744,CAD,99680,MI,PT,Canada,L,Japan,100,"Python, R, GCP, Azure, Spark",Bachelor,4,Real Estate,2024-01-13,2024-02-03,574,8.8,Autonomous Tech +AI13205,AI Architect,198736,USD,198736,EX,PT,United States,S,United States,0,"Linux, Mathematics, Git, NLP, Spark",Associate,18,Government,2024-09-01,2024-10-20,1551,7.1,Digital Transformation LLC +AI13206,Research Scientist,104891,USD,104891,MI,CT,Denmark,M,South Korea,100,"Data Visualization, Azure, GCP, SQL",Associate,2,Retail,2024-05-08,2024-07-17,1911,8.8,Machine Intelligence Group +AI13207,Data Scientist,61269,USD,61269,SE,FL,India,L,India,100,"PyTorch, TensorFlow, GCP",Bachelor,6,Real Estate,2024-01-08,2024-03-12,1695,6.8,AI Innovations +AI13208,Research Scientist,25071,USD,25071,MI,CT,India,S,India,50,"Linux, Deep Learning, Spark",Associate,2,Technology,2025-01-13,2025-03-08,1449,7.7,DeepTech Ventures +AI13209,Data Engineer,84490,CHF,76041,EN,FT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Tableau",PhD,0,Transportation,2024-06-22,2024-08-22,1823,7.3,Algorithmic Solutions +AI13210,AI Architect,58087,USD,58087,MI,PT,South Korea,S,Luxembourg,50,"NLP, Statistics, AWS, Kubernetes",Bachelor,2,Real Estate,2024-08-19,2024-09-29,2017,8.8,Future Systems +AI13211,Autonomous Systems Engineer,50417,EUR,42854,EN,CT,Austria,M,Austria,0,"Azure, Java, Data Visualization",PhD,0,Manufacturing,2024-05-04,2024-06-09,1748,7.7,Cloud AI Solutions +AI13212,AI Software Engineer,149113,SGD,193847,SE,CT,Singapore,M,Singapore,0,"Java, Docker, NLP, Statistics, Scala",Associate,7,Education,2025-01-17,2025-02-18,1353,8.8,Cognitive Computing +AI13213,AI Consultant,94092,EUR,79978,SE,PT,Austria,S,Austria,100,"Hadoop, Tableau, Computer Vision, Python",Bachelor,9,Finance,2024-07-03,2024-08-25,1449,8.6,TechCorp Inc +AI13214,Head of AI,185420,USD,185420,SE,PT,United States,L,Mexico,0,"SQL, Scala, Data Visualization",Associate,6,Consulting,2024-04-25,2024-07-03,1896,9.4,Autonomous Tech +AI13215,Data Analyst,93085,EUR,79122,MI,PT,Netherlands,M,Ghana,100,"Statistics, MLOps, Computer Vision, Java, AWS",Associate,3,Government,2025-01-13,2025-02-28,2006,10,Cognitive Computing +AI13216,NLP Engineer,102367,GBP,76775,MI,FL,United Kingdom,M,United Kingdom,0,"Azure, Spark, Docker",Master,3,Healthcare,2025-02-11,2025-04-14,2318,9.9,Advanced Robotics +AI13217,Machine Learning Engineer,213126,AUD,287720,EX,FT,Australia,L,Australia,100,"Python, Data Visualization, SQL, AWS",Master,18,Gaming,2025-02-17,2025-03-10,1670,5.7,Cognitive Computing +AI13218,Data Engineer,70624,USD,70624,MI,PT,South Korea,S,South Korea,100,"Linux, TensorFlow, Data Visualization",Associate,3,Transportation,2024-07-08,2024-09-13,511,7.5,Cognitive Computing +AI13219,Machine Learning Engineer,48905,EUR,41569,EN,FL,Netherlands,S,Vietnam,0,"Docker, Tableau, PyTorch, TensorFlow, NLP",Associate,1,Real Estate,2024-01-25,2024-03-01,847,9.9,Advanced Robotics +AI13220,Research Scientist,98101,JPY,10791110,SE,FL,Japan,S,Portugal,50,"SQL, Linux, R",PhD,8,Consulting,2024-05-23,2024-06-22,1283,7.4,Neural Networks Co +AI13221,AI Consultant,141464,EUR,120244,SE,PT,Austria,M,Austria,50,"MLOps, Data Visualization, Python, TensorFlow, Docker",Master,9,Automotive,2024-02-13,2024-04-10,1489,8.7,DeepTech Ventures +AI13222,AI Specialist,140338,USD,140338,SE,CT,United States,S,Colombia,0,"Hadoop, Kubernetes, MLOps, SQL",Bachelor,6,Education,2024-12-05,2025-01-05,1117,8,Quantum Computing Inc +AI13223,AI Research Scientist,102674,JPY,11294140,SE,FT,Japan,S,Japan,50,"Python, AWS, R",PhD,5,Automotive,2024-07-31,2024-10-02,503,9.4,Smart Analytics +AI13224,AI Consultant,50281,CAD,62851,EN,FL,Canada,M,Czech Republic,100,"Spark, TensorFlow, Python",PhD,1,Media,2024-05-19,2024-06-23,2064,6.4,AI Innovations +AI13225,ML Ops Engineer,126345,SGD,164249,SE,CT,Singapore,L,Singapore,0,"Python, Linux, Git, Computer Vision",Associate,6,Consulting,2025-01-09,2025-03-04,1300,6.5,Algorithmic Solutions +AI13226,Head of AI,310457,USD,310457,EX,FL,Denmark,M,Denmark,100,"Linux, Kubernetes, PyTorch, Hadoop, Azure",Bachelor,19,Energy,2024-08-04,2024-09-29,693,8,DataVision Ltd +AI13227,AI Architect,133886,USD,133886,SE,CT,Denmark,M,Mexico,100,"Python, NLP, Scala, Computer Vision",Associate,7,Real Estate,2024-07-06,2024-08-23,796,8.3,Cognitive Computing +AI13228,Research Scientist,266548,USD,266548,EX,FL,Finland,L,Finland,100,"Kubernetes, Azure, SQL, AWS",PhD,14,Real Estate,2024-03-04,2024-03-20,1603,5.2,Machine Intelligence Group +AI13229,ML Ops Engineer,45522,USD,45522,MI,FT,China,L,China,50,"Scala, Statistics, Data Visualization, Java, Mathematics",Bachelor,2,Telecommunications,2024-07-29,2024-09-04,534,9.7,Predictive Systems +AI13230,Principal Data Scientist,110658,GBP,82994,MI,PT,United Kingdom,L,United Kingdom,100,"Scala, Kubernetes, Spark, Docker",Associate,4,Transportation,2024-03-24,2024-06-01,2049,8.3,Digital Transformation LLC +AI13231,Research Scientist,80074,USD,80074,EN,FL,Denmark,L,Denmark,50,"Data Visualization, Linux, SQL",Bachelor,1,Manufacturing,2025-02-08,2025-03-10,1335,8,Machine Intelligence Group +AI13232,AI Architect,135856,USD,135856,SE,FL,Sweden,S,Sweden,100,"Azure, R, PyTorch, AWS",Associate,9,Government,2024-09-18,2024-10-02,2285,7.6,DeepTech Ventures +AI13233,Principal Data Scientist,116833,CAD,146041,SE,CT,Canada,S,Canada,50,"Tableau, Linux, AWS, MLOps",Bachelor,8,Consulting,2025-03-02,2025-05-07,1983,9.1,Quantum Computing Inc +AI13234,AI Architect,134634,USD,134634,MI,CT,United States,L,United States,0,"Kubernetes, Statistics, Spark",Master,2,Healthcare,2024-04-03,2024-05-07,1639,9.1,Cognitive Computing +AI13235,ML Ops Engineer,129280,CHF,116352,MI,FL,Switzerland,L,Switzerland,100,"Computer Vision, Tableau, TensorFlow, Python, Statistics",Master,4,Automotive,2024-06-19,2024-08-16,1739,9,AI Innovations +AI13236,Data Engineer,246914,USD,246914,EX,FL,Denmark,L,Thailand,50,"Java, PyTorch, Mathematics, NLP",Bachelor,17,Consulting,2024-11-09,2024-12-15,2011,5.5,Future Systems +AI13237,Research Scientist,94188,JPY,10360680,MI,FL,Japan,M,Turkey,100,"Linux, Python, MLOps, Hadoop, TensorFlow",PhD,4,Gaming,2024-03-17,2024-04-04,2004,6.4,Autonomous Tech +AI13238,Deep Learning Engineer,114774,AUD,154945,MI,FT,Australia,L,Australia,100,"Python, TensorFlow, NLP, Hadoop",Associate,4,Technology,2024-05-31,2024-08-05,1786,5.2,Smart Analytics +AI13239,ML Ops Engineer,59249,USD,59249,EN,CT,Ireland,L,Ireland,0,"SQL, R, Kubernetes",Master,1,Retail,2024-08-14,2024-08-28,516,8.2,DataVision Ltd +AI13240,Principal Data Scientist,81389,USD,81389,MI,PT,South Korea,L,Turkey,0,"SQL, Hadoop, Tableau, Data Visualization",Associate,2,Technology,2024-03-02,2024-05-04,892,7.9,DataVision Ltd +AI13241,Deep Learning Engineer,60315,USD,60315,EN,PT,United States,S,China,50,"Git, PyTorch, Kubernetes",Bachelor,1,Healthcare,2024-02-27,2024-03-25,902,7.3,Algorithmic Solutions +AI13242,Research Scientist,187520,SGD,243776,EX,PT,Singapore,M,Ghana,100,"Azure, Docker, SQL, Python",PhD,17,Finance,2025-04-09,2025-06-03,1424,6.4,AI Innovations +AI13243,Data Analyst,137040,USD,137040,MI,CT,Denmark,M,Denmark,0,"NLP, TensorFlow, Docker, GCP, Python",Master,3,Consulting,2024-08-30,2024-10-22,1172,5.7,DataVision Ltd +AI13244,Computer Vision Engineer,180365,SGD,234475,SE,FL,Singapore,L,Spain,0,"SQL, PyTorch, Tableau, MLOps",PhD,5,Healthcare,2024-08-04,2024-10-12,1304,6.4,AI Innovations +AI13245,AI Research Scientist,40180,USD,40180,EN,PT,China,L,China,50,"GCP, TensorFlow, Hadoop, Python, Kubernetes",Bachelor,1,Real Estate,2024-08-09,2024-09-10,1172,7.6,DeepTech Ventures +AI13246,AI Research Scientist,93313,JPY,10264430,MI,FL,Japan,S,Japan,50,"Python, Spark, Statistics, AWS, Mathematics",Master,2,Telecommunications,2025-01-12,2025-03-03,1062,6.3,Algorithmic Solutions +AI13247,Machine Learning Engineer,106766,SGD,138796,MI,FT,Singapore,M,Singapore,50,"Kubernetes, R, Docker, PyTorch, Git",Associate,3,Government,2024-01-27,2024-03-06,2237,6.4,Algorithmic Solutions +AI13248,Machine Learning Engineer,210437,USD,210437,EX,PT,Israel,L,Israel,100,"Tableau, Kubernetes, Java, Python",Bachelor,14,Telecommunications,2024-05-29,2024-07-18,2171,8,Cognitive Computing +AI13249,AI Product Manager,75988,JPY,8358680,MI,FT,Japan,S,Japan,100,"Kubernetes, NLP, Tableau, Data Visualization",PhD,2,Telecommunications,2024-03-05,2024-04-02,1882,5.4,Cognitive Computing +AI13250,Computer Vision Engineer,144385,JPY,15882350,SE,PT,Japan,S,Japan,50,"Deep Learning, Docker, Tableau, Kubernetes, Spark",Associate,6,Manufacturing,2024-09-04,2024-11-14,1730,7.3,Quantum Computing Inc +AI13251,NLP Engineer,90091,USD,90091,SE,CT,Israel,S,Japan,100,"TensorFlow, MLOps, AWS, Java",Bachelor,8,Finance,2024-06-28,2024-07-24,1937,5.9,Digital Transformation LLC +AI13252,Deep Learning Engineer,105779,USD,105779,SE,PT,Sweden,S,Sweden,0,"Azure, AWS, Computer Vision, Python, Docker",Bachelor,6,Transportation,2025-02-16,2025-04-04,2095,5.7,Quantum Computing Inc +AI13253,NLP Engineer,306666,USD,306666,EX,PT,Norway,L,Belgium,100,"Git, Mathematics, Spark, PyTorch, Statistics",PhD,15,Manufacturing,2024-12-16,2025-01-07,2167,6.7,DeepTech Ventures +AI13254,Machine Learning Researcher,53085,USD,53085,EN,PT,Finland,S,Finland,50,"Java, Tableau, Kubernetes",PhD,1,Telecommunications,2024-07-23,2024-09-23,1112,9.7,Future Systems +AI13255,AI Research Scientist,100104,EUR,85088,SE,FL,Austria,M,Denmark,0,"Python, Statistics, Hadoop",Master,5,Energy,2024-03-23,2024-04-24,1623,7,Predictive Systems +AI13256,NLP Engineer,271861,USD,271861,EX,FL,Norway,L,Norway,50,"Azure, Python, Java",Bachelor,15,Technology,2024-12-06,2025-02-01,2332,9.2,DeepTech Ventures +AI13257,Data Engineer,49399,USD,49399,EN,FT,South Korea,M,South Korea,50,"MLOps, Python, Tableau, AWS, Java",Associate,1,Energy,2024-06-19,2024-08-18,675,8.6,Smart Analytics +AI13258,Data Analyst,103468,JPY,11381480,SE,FT,Japan,S,Japan,100,"Hadoop, R, Scala",Associate,5,Technology,2024-08-24,2024-09-23,1561,9.3,Quantum Computing Inc +AI13259,Machine Learning Engineer,93578,USD,93578,MI,CT,United States,M,United States,50,"TensorFlow, AWS, Spark, Kubernetes, SQL",Associate,3,Retail,2024-11-07,2024-12-18,1889,9.3,Quantum Computing Inc +AI13260,Machine Learning Engineer,84233,EUR,71598,EN,CT,France,L,France,0,"Python, TensorFlow, Deep Learning, Statistics",PhD,1,Media,2024-07-11,2024-07-25,742,5.7,Cloud AI Solutions +AI13261,AI Consultant,112337,USD,112337,EN,CT,Denmark,L,Denmark,0,"Tableau, Linux, Kubernetes",PhD,1,Government,2024-07-11,2024-09-02,1248,9,Advanced Robotics +AI13262,AI Consultant,239391,USD,239391,EX,FT,Denmark,M,Sweden,50,"Hadoop, Scala, MLOps, R, Git",Bachelor,12,Energy,2025-04-29,2025-06-29,2480,5,DataVision Ltd +AI13263,Computer Vision Engineer,45215,USD,45215,EN,PT,South Korea,S,South Korea,0,"GCP, Linux, NLP, Hadoop",PhD,0,Media,2024-07-13,2024-09-13,1982,5.5,Neural Networks Co +AI13264,Machine Learning Researcher,48795,EUR,41476,EN,FT,France,S,Romania,50,"TensorFlow, Python, SQL, Kubernetes",Bachelor,1,Real Estate,2025-01-23,2025-03-11,1982,8.7,DataVision Ltd +AI13265,AI Consultant,119095,CHF,107186,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, Hadoop, GCP, Computer Vision, Azure",PhD,2,Telecommunications,2024-04-13,2024-05-30,958,8.9,Smart Analytics +AI13266,ML Ops Engineer,98669,GBP,74002,SE,CT,United Kingdom,S,United Kingdom,100,"MLOps, Python, Data Visualization",Master,9,Automotive,2024-05-10,2024-07-06,1095,8.3,TechCorp Inc +AI13267,AI Architect,128617,SGD,167202,SE,CT,Singapore,M,Netherlands,100,"Computer Vision, SQL, Data Visualization, Kubernetes, Docker",PhD,6,Retail,2024-08-17,2024-09-09,2213,8.5,DataVision Ltd +AI13268,Robotics Engineer,95556,USD,95556,MI,FT,Sweden,M,Sweden,0,"Kubernetes, Deep Learning, Linux",PhD,2,Manufacturing,2024-12-13,2025-01-31,1250,6.2,Advanced Robotics +AI13269,Machine Learning Engineer,200162,SGD,260211,EX,FL,Singapore,L,Singapore,50,"R, Spark, MLOps, Mathematics",PhD,11,Manufacturing,2025-01-23,2025-02-09,840,8.3,Autonomous Tech +AI13270,Principal Data Scientist,109357,EUR,92953,MI,PT,Netherlands,L,Norway,0,"NLP, Git, Java, MLOps",Associate,4,Government,2025-02-01,2025-03-30,2304,6.7,Quantum Computing Inc +AI13271,Head of AI,122021,USD,122021,MI,FT,Norway,M,United Kingdom,0,"Kubernetes, Python, Tableau",Master,2,Manufacturing,2024-08-19,2024-10-07,669,5.3,DataVision Ltd +AI13272,Head of AI,325087,CHF,292578,EX,PT,Switzerland,L,Ghana,100,"Python, Git, Tableau",Associate,11,Retail,2025-03-25,2025-05-21,2055,5.5,DataVision Ltd +AI13273,Machine Learning Engineer,168996,JPY,18589560,EX,FT,Japan,M,Chile,0,"Deep Learning, Scala, Spark, Python",Associate,16,Healthcare,2024-01-30,2024-03-25,1234,6.2,Digital Transformation LLC +AI13274,ML Ops Engineer,43570,USD,43570,EN,FT,South Korea,S,South Korea,50,"Java, SQL, Git, Data Visualization, Python",Master,0,Manufacturing,2024-03-31,2024-05-26,1032,6.9,Algorithmic Solutions +AI13275,AI Architect,149909,USD,149909,SE,PT,United States,L,United States,50,"GCP, Python, TensorFlow, Deep Learning, Tableau",PhD,9,Gaming,2025-03-25,2025-05-05,1503,5.8,Future Systems +AI13276,Computer Vision Engineer,82164,USD,82164,EN,FL,United States,S,Sweden,50,"TensorFlow, NLP, Linux, Statistics, Deep Learning",Bachelor,1,Transportation,2024-01-04,2024-01-27,1031,6,Digital Transformation LLC +AI13277,AI Consultant,92430,USD,92430,MI,CT,Israel,S,Brazil,100,"Data Visualization, Tableau, PyTorch, Python, Mathematics",Associate,4,Real Estate,2025-01-29,2025-02-12,1295,8.4,Autonomous Tech +AI13278,AI Specialist,49758,USD,49758,EN,FT,South Korea,S,South Korea,100,"R, Statistics, Hadoop, Git",Master,0,Healthcare,2024-11-03,2025-01-07,2206,7.6,Neural Networks Co +AI13279,AI Product Manager,74628,GBP,55971,EN,CT,United Kingdom,L,Russia,100,"Git, Hadoop, MLOps",PhD,1,Healthcare,2024-02-16,2024-03-14,1505,5.7,Cloud AI Solutions +AI13280,Robotics Engineer,128025,GBP,96019,MI,FT,United Kingdom,L,South Africa,50,"Python, Linux, Azure, Deep Learning",Master,2,Education,2024-03-30,2024-04-23,2160,7.1,Cognitive Computing +AI13281,Data Engineer,100244,EUR,85207,SE,CT,Germany,S,Netherlands,50,"R, SQL, Scala, Python",Master,8,Education,2024-08-14,2024-09-05,865,7,Future Systems +AI13282,Autonomous Systems Engineer,34992,USD,34992,MI,FL,India,S,Belgium,100,"PyTorch, Java, NLP",Associate,3,Retail,2024-02-17,2024-04-08,1855,9.9,DataVision Ltd +AI13283,AI Research Scientist,94904,EUR,80668,MI,CT,France,L,Israel,100,"GCP, Linux, Hadoop, Java",PhD,2,Healthcare,2024-05-04,2024-06-17,1361,9.8,Digital Transformation LLC +AI13284,Data Analyst,134647,JPY,14811170,EX,CT,Japan,S,Japan,0,"Kubernetes, Python, TensorFlow, Deep Learning",Associate,19,Automotive,2025-01-31,2025-03-28,1051,8.8,DataVision Ltd +AI13285,AI Consultant,47733,USD,47733,EN,FL,Finland,S,Argentina,50,"NLP, Python, Java, R, GCP",PhD,1,Transportation,2024-11-14,2024-12-17,2101,5.6,Neural Networks Co +AI13286,AI Research Scientist,126186,GBP,94640,SE,FT,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Deep Learning, Python, NLP",PhD,8,Manufacturing,2024-04-25,2024-06-21,706,5.2,Cloud AI Solutions +AI13287,Robotics Engineer,178018,USD,178018,EX,FL,Finland,M,Finland,50,"GCP, NLP, Scala, Java",Master,11,Education,2024-05-21,2024-06-30,600,6.7,AI Innovations +AI13288,Computer Vision Engineer,58807,EUR,49986,EN,FL,France,L,France,100,"Computer Vision, R, Python, Kubernetes, MLOps",Associate,1,Media,2024-06-09,2024-07-29,713,6.8,Cognitive Computing +AI13289,ML Ops Engineer,78517,EUR,66739,EN,FT,France,L,France,100,"GCP, Deep Learning, Linux",Master,0,Technology,2024-12-31,2025-02-15,692,9.8,Machine Intelligence Group +AI13290,Computer Vision Engineer,152471,EUR,129600,SE,FT,Germany,L,Germany,0,"Git, Statistics, Kubernetes, Linux, PyTorch",PhD,9,Automotive,2024-05-12,2024-05-28,632,6.8,DataVision Ltd +AI13291,AI Research Scientist,83053,USD,83053,EN,FT,Ireland,L,Ireland,0,"Kubernetes, Python, AWS, TensorFlow, Data Visualization",PhD,1,Transportation,2024-12-18,2025-02-03,1920,7.4,TechCorp Inc +AI13292,Deep Learning Engineer,55419,EUR,47106,EN,FL,Austria,S,Czech Republic,100,"Data Visualization, GCP, Kubernetes, R",Master,1,Real Estate,2025-01-19,2025-02-18,2179,8.7,Machine Intelligence Group +AI13293,Data Analyst,226088,CAD,282610,EX,CT,Canada,M,Latvia,0,"Tableau, Hadoop, Kubernetes, Mathematics, Scala",PhD,13,Retail,2024-02-24,2024-03-19,777,9.9,Cognitive Computing +AI13294,Machine Learning Researcher,140926,GBP,105695,SE,FT,United Kingdom,S,United Kingdom,100,"MLOps, PyTorch, Docker, Mathematics",Bachelor,5,Consulting,2024-03-17,2024-04-10,566,7.9,DataVision Ltd +AI13295,Machine Learning Researcher,97767,EUR,83102,SE,FT,Netherlands,S,Netherlands,50,"Linux, Git, MLOps, Computer Vision, Python",Associate,9,Automotive,2024-01-07,2024-02-23,1471,5.5,Neural Networks Co +AI13296,Data Scientist,100990,GBP,75743,SE,FL,United Kingdom,S,United Kingdom,100,"Python, Deep Learning, SQL, GCP",Associate,8,Technology,2024-10-31,2024-11-22,904,8.7,DeepTech Ventures +AI13297,Data Analyst,136795,GBP,102596,SE,PT,United Kingdom,M,United Kingdom,100,"MLOps, Hadoop, Scala, Linux, Java",Master,7,Telecommunications,2024-06-13,2024-06-29,2464,6.1,AI Innovations +AI13298,AI Architect,76815,USD,76815,MI,FT,Sweden,S,Sweden,100,"Mathematics, AWS, Hadoop, Deep Learning",Bachelor,3,Manufacturing,2024-09-24,2024-10-11,1123,5.5,Smart Analytics +AI13299,Head of AI,80644,USD,80644,EN,PT,United States,M,United States,50,"Python, TensorFlow, Tableau",PhD,1,Gaming,2024-08-17,2024-09-20,1924,10,TechCorp Inc +AI13300,Deep Learning Engineer,90240,JPY,9926400,MI,FL,Japan,S,Japan,50,"SQL, PyTorch, MLOps",Associate,3,Government,2024-09-16,2024-11-26,591,9.1,Machine Intelligence Group +AI13301,Machine Learning Engineer,199372,USD,199372,EX,PT,Norway,S,Luxembourg,0,"Python, Scala, NLP, Azure, Kubernetes",PhD,17,Technology,2024-07-05,2024-09-07,1177,8.6,Quantum Computing Inc +AI13302,Robotics Engineer,232839,EUR,197913,EX,CT,France,M,France,100,"Linux, GCP, R, Spark, Python",Master,10,Media,2024-12-12,2025-02-11,1555,6.9,Cloud AI Solutions +AI13303,AI Research Scientist,120541,USD,120541,MI,CT,Denmark,M,Denmark,100,"PyTorch, Kubernetes, Hadoop, NLP, GCP",Master,2,Consulting,2025-01-02,2025-01-30,2358,6.2,Predictive Systems +AI13304,ML Ops Engineer,94694,USD,94694,EN,CT,Norway,M,Romania,0,"Spark, Computer Vision, SQL",Associate,1,Gaming,2024-02-19,2024-05-02,1701,8.5,TechCorp Inc +AI13305,NLP Engineer,69183,AUD,93397,EN,PT,Australia,M,Japan,50,"Azure, Linux, PyTorch",Master,0,Finance,2024-08-25,2024-11-03,657,7.3,AI Innovations +AI13306,AI Software Engineer,101698,EUR,86443,SE,FT,Austria,M,China,100,"Linux, Python, Azure, TensorFlow, AWS",Master,6,Real Estate,2024-05-15,2024-06-20,976,7.9,Quantum Computing Inc +AI13307,Head of AI,131365,USD,131365,SE,FL,Israel,M,Israel,50,"Data Visualization, Spark, GCP, Docker",PhD,7,Gaming,2024-02-14,2024-04-15,1663,6.3,Quantum Computing Inc +AI13308,AI Consultant,130237,GBP,97678,SE,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, R, AWS",PhD,8,Finance,2024-01-14,2024-03-15,1184,10,TechCorp Inc +AI13309,AI Architect,171976,USD,171976,SE,FT,Ireland,L,Ireland,100,"Deep Learning, Azure, Spark",Associate,6,Energy,2024-04-23,2024-05-26,811,6.3,Quantum Computing Inc +AI13310,AI Product Manager,219348,USD,219348,EX,FT,Denmark,L,Denmark,50,"Python, TensorFlow, PyTorch, Docker, Statistics",Associate,18,Telecommunications,2024-02-28,2024-04-28,629,5.6,Autonomous Tech +AI13311,AI Research Scientist,215507,USD,215507,EX,FL,Israel,M,Israel,100,"Scala, TensorFlow, Azure, Python, PyTorch",PhD,19,Education,2024-07-10,2024-08-07,2042,7.6,Digital Transformation LLC +AI13312,Data Analyst,168512,USD,168512,SE,FL,Sweden,L,Canada,100,"GCP, Data Visualization, Python",PhD,7,Transportation,2024-04-23,2024-06-29,1881,9.1,Algorithmic Solutions +AI13313,AI Research Scientist,121328,JPY,13346080,SE,FL,Japan,S,Japan,0,"SQL, PyTorch, GCP, Tableau",Master,8,Real Estate,2024-04-18,2024-05-21,733,7.3,Machine Intelligence Group +AI13314,AI Software Engineer,289498,USD,289498,EX,PT,Denmark,M,Denmark,0,"Scala, GCP, Deep Learning, R",Associate,10,Healthcare,2024-12-23,2025-01-15,670,9.1,Digital Transformation LLC +AI13315,AI Research Scientist,109391,AUD,147678,SE,CT,Australia,S,Australia,50,"AWS, Kubernetes, Mathematics, Java",Bachelor,5,Technology,2024-07-09,2024-09-04,571,8.7,Neural Networks Co +AI13316,Head of AI,92796,USD,92796,MI,PT,South Korea,L,South Korea,100,"Data Visualization, TensorFlow, NLP, Kubernetes",Associate,4,Telecommunications,2024-02-15,2024-04-14,1608,9.6,Future Systems +AI13317,Computer Vision Engineer,254375,SGD,330688,EX,FT,Singapore,M,Singapore,0,"GCP, Scala, Git, R",Associate,19,Education,2024-05-08,2024-05-29,1024,6.5,Smart Analytics +AI13318,Machine Learning Researcher,64737,CAD,80921,MI,FL,Canada,S,Canada,0,"Git, Tableau, Python, Data Visualization, TensorFlow",Bachelor,2,Gaming,2024-01-31,2024-04-05,1165,6.2,Future Systems +AI13319,Robotics Engineer,101753,EUR,86490,SE,PT,Netherlands,S,Netherlands,50,"Kubernetes, NLP, Data Visualization, GCP, Linux",PhD,9,Real Estate,2025-04-07,2025-05-07,1334,7.5,Predictive Systems +AI13320,Autonomous Systems Engineer,208375,EUR,177119,EX,FT,Netherlands,M,Netherlands,100,"Git, Mathematics, Computer Vision",Bachelor,11,Education,2025-04-21,2025-06-24,977,9.1,Quantum Computing Inc +AI13321,Autonomous Systems Engineer,127596,AUD,172255,SE,FL,Australia,S,Netherlands,50,"SQL, PyTorch, Java",Master,6,Healthcare,2024-09-01,2024-11-02,2402,6.6,Digital Transformation LLC +AI13322,Data Analyst,231910,EUR,197124,EX,FL,France,L,France,50,"MLOps, PyTorch, Hadoop",Associate,12,Automotive,2024-09-29,2024-11-15,1309,9.4,Neural Networks Co +AI13323,ML Ops Engineer,40030,USD,40030,SE,FL,India,M,India,0,"GCP, Deep Learning, Kubernetes",Bachelor,5,Transportation,2024-11-08,2024-12-02,1632,5.6,Cloud AI Solutions +AI13324,AI Architect,108886,USD,108886,EX,FT,China,L,China,100,"NLP, Scala, SQL",Master,11,Technology,2024-03-22,2024-04-27,1355,6,DeepTech Ventures +AI13325,Data Scientist,25902,USD,25902,EN,PT,China,M,Romania,50,"TensorFlow, Linux, Hadoop",Bachelor,0,Technology,2024-12-03,2025-01-12,1563,6,Algorithmic Solutions +AI13326,AI Research Scientist,86757,AUD,117122,MI,CT,Australia,L,Australia,100,"Kubernetes, GCP, Data Visualization, Mathematics, SQL",Bachelor,3,Retail,2025-01-15,2025-03-04,1437,7,Smart Analytics +AI13327,Data Analyst,38963,USD,38963,MI,FT,China,M,China,0,"Kubernetes, Spark, Python, Linux, Mathematics",Associate,3,Automotive,2024-11-17,2024-12-02,1495,6.7,Machine Intelligence Group +AI13328,AI Architect,308292,CHF,277463,EX,FL,Switzerland,L,Switzerland,100,"Kubernetes, Spark, Tableau, Hadoop, Git",PhD,11,Education,2024-06-07,2024-07-04,1113,7.9,DeepTech Ventures +AI13329,AI Software Engineer,194259,CHF,174833,SE,FL,Switzerland,L,Ukraine,50,"Kubernetes, Scala, Statistics, Tableau, Spark",Associate,7,Gaming,2024-06-11,2024-07-30,2266,7.6,Algorithmic Solutions +AI13330,Machine Learning Researcher,90499,AUD,122174,EN,CT,Australia,L,Kenya,100,"Linux, Python, Mathematics, Kubernetes, Hadoop",PhD,0,Government,2025-02-01,2025-03-16,1479,7.1,Cognitive Computing +AI13331,AI Research Scientist,152866,EUR,129936,EX,FT,Netherlands,S,Nigeria,0,"Git, Linux, Kubernetes, Python",PhD,14,Consulting,2024-02-13,2024-04-24,1604,5.9,Future Systems +AI13332,AI Consultant,207262,USD,207262,EX,FT,Norway,M,United States,0,"PyTorch, TensorFlow, Spark, Python, Hadoop",Master,19,Media,2025-04-07,2025-06-18,1968,9,Quantum Computing Inc +AI13333,Autonomous Systems Engineer,97380,CAD,121725,MI,FT,Canada,L,Russia,100,"R, MLOps, Data Visualization, SQL, Mathematics",Bachelor,4,Consulting,2024-06-21,2024-07-13,2191,5.9,Algorithmic Solutions +AI13334,AI Software Engineer,163759,USD,163759,SE,PT,Denmark,L,Denmark,0,"Kubernetes, Docker, Scala, Hadoop, Statistics",Associate,5,Real Estate,2024-03-04,2024-04-02,2380,6.1,Digital Transformation LLC +AI13335,Machine Learning Researcher,121421,EUR,103208,SE,FL,France,S,France,0,"Java, Linux, Tableau, MLOps, Statistics",Associate,6,Telecommunications,2025-04-01,2025-05-06,595,7.4,Future Systems +AI13336,Data Engineer,43568,EUR,37033,EN,PT,France,S,China,50,"Statistics, GCP, Data Visualization, Java",Bachelor,0,Technology,2024-04-02,2024-06-09,880,9.1,Machine Intelligence Group +AI13337,Research Scientist,119350,USD,119350,EX,FT,China,L,China,0,"Java, NLP, Python, Kubernetes",Associate,10,Healthcare,2024-02-11,2024-03-29,1105,9.2,Predictive Systems +AI13338,Computer Vision Engineer,95494,USD,95494,SE,PT,South Korea,S,South Korea,50,"Python, TensorFlow, Java",Associate,6,Energy,2024-04-16,2024-05-16,2058,6,Predictive Systems +AI13339,Deep Learning Engineer,62202,EUR,52872,EN,CT,Germany,S,Germany,50,"Scala, SQL, Python, Java, NLP",Master,1,Media,2025-04-17,2025-06-22,997,6.6,TechCorp Inc +AI13340,AI Consultant,88967,USD,88967,EN,PT,Sweden,L,Turkey,50,"TensorFlow, Azure, Deep Learning, Computer Vision, Linux",PhD,1,Real Estate,2024-12-20,2025-02-09,2438,7.1,Autonomous Tech +AI13341,Robotics Engineer,63313,CAD,79141,EN,FT,Canada,M,Canada,100,"Kubernetes, PyTorch, Mathematics, Computer Vision, GCP",Bachelor,1,Telecommunications,2024-12-24,2025-02-28,1312,7.3,Quantum Computing Inc +AI13342,Autonomous Systems Engineer,59228,CAD,74035,EN,PT,Canada,S,Canada,0,"TensorFlow, Python, Java, Spark, Kubernetes",Associate,0,Retail,2024-07-23,2024-09-19,924,8.8,Algorithmic Solutions +AI13343,Autonomous Systems Engineer,125001,USD,125001,SE,CT,Israel,S,Israel,100,"AWS, Spark, Data Visualization, Git",Associate,8,Energy,2024-08-01,2024-09-07,1524,6.6,TechCorp Inc +AI13344,Principal Data Scientist,36642,USD,36642,EN,PT,China,L,China,100,"Python, Scala, Java",Master,0,Telecommunications,2024-10-28,2024-12-27,1096,5.9,Neural Networks Co +AI13345,Principal Data Scientist,113963,USD,113963,MI,PT,Denmark,M,Denmark,100,"Python, Data Visualization, AWS, Spark",PhD,2,Energy,2024-07-20,2024-09-26,1472,8.2,Autonomous Tech +AI13346,Machine Learning Engineer,135609,USD,135609,SE,FT,Denmark,M,Luxembourg,100,"R, Tableau, Statistics, NLP",Master,8,Healthcare,2024-01-29,2024-03-21,1855,8.7,AI Innovations +AI13347,Deep Learning Engineer,129508,GBP,97131,SE,FT,United Kingdom,M,United Kingdom,0,"Linux, Docker, PyTorch, R",Master,9,Transportation,2024-09-28,2024-11-13,1340,9,AI Innovations +AI13348,Head of AI,222566,JPY,24482260,EX,PT,Japan,S,Japan,0,"Docker, Deep Learning, SQL, MLOps",PhD,11,Gaming,2024-05-13,2024-07-15,766,6.3,Machine Intelligence Group +AI13349,AI Architect,263402,JPY,28974220,EX,PT,Japan,L,Japan,0,"Kubernetes, Java, R, Statistics",Associate,11,Education,2024-09-18,2024-10-15,2271,6.6,AI Innovations +AI13350,Computer Vision Engineer,60120,GBP,45090,EN,FL,United Kingdom,S,Ukraine,0,"MLOps, Computer Vision, GCP, Kubernetes",PhD,1,Telecommunications,2025-03-03,2025-05-10,1798,6.9,Autonomous Tech +AI13351,Machine Learning Engineer,76589,USD,76589,MI,FT,Finland,S,Finland,100,"Kubernetes, Git, SQL",Associate,2,Real Estate,2024-08-18,2024-10-29,2474,9.2,Algorithmic Solutions +AI13352,Deep Learning Engineer,73963,USD,73963,EN,FL,United States,L,United States,50,"Python, TensorFlow, Azure, Spark, PyTorch",Master,1,Finance,2024-09-24,2024-10-19,714,9.9,Quantum Computing Inc +AI13353,Machine Learning Researcher,320290,USD,320290,EX,FT,Denmark,L,Denmark,100,"Hadoop, Python, Scala, AWS",Bachelor,13,Media,2024-11-02,2024-12-29,1220,5.6,DeepTech Ventures +AI13354,Deep Learning Engineer,148841,JPY,16372510,SE,FL,Japan,L,Russia,0,"Kubernetes, Scala, Java, Spark, R",Associate,8,Real Estate,2024-07-22,2024-08-20,828,6.6,Neural Networks Co +AI13355,Head of AI,111086,USD,111086,EN,FL,Denmark,L,Denmark,100,"Computer Vision, Azure, Python, TensorFlow, GCP",Master,1,Automotive,2024-06-01,2024-07-19,2404,7,AI Innovations +AI13356,Computer Vision Engineer,259096,USD,259096,EX,FL,United States,M,United States,50,"Spark, Statistics, NLP, Python",Bachelor,17,Telecommunications,2024-07-23,2024-08-08,1084,7,Quantum Computing Inc +AI13357,Computer Vision Engineer,90325,CAD,112906,MI,PT,Canada,L,New Zealand,100,"Kubernetes, Deep Learning, Python, Data Visualization",Bachelor,4,Healthcare,2024-09-05,2024-10-04,1127,5.4,TechCorp Inc +AI13358,AI Product Manager,92718,SGD,120533,MI,CT,Singapore,L,Singapore,0,"Python, MLOps, Tableau, TensorFlow",Associate,2,Manufacturing,2024-07-11,2024-09-07,893,9.6,DeepTech Ventures +AI13359,Deep Learning Engineer,124245,USD,124245,SE,PT,Israel,M,Israel,0,"PyTorch, TensorFlow, Mathematics",Bachelor,6,Energy,2025-01-10,2025-02-16,2472,5,Cloud AI Solutions +AI13360,Data Scientist,235413,GBP,176560,EX,FT,United Kingdom,S,United Kingdom,0,"Java, Hadoop, Tableau",Bachelor,12,Education,2025-02-11,2025-03-15,1436,8,Quantum Computing Inc +AI13361,Machine Learning Engineer,137922,EUR,117234,SE,PT,France,L,France,0,"AWS, Kubernetes, MLOps, Scala, Python",Bachelor,9,Telecommunications,2024-09-11,2024-11-20,2186,9.5,Future Systems +AI13362,Data Scientist,123420,USD,123420,MI,FT,United States,M,United States,100,"Mathematics, SQL, PyTorch, GCP",Bachelor,3,Energy,2024-10-30,2024-12-31,855,8.3,Advanced Robotics +AI13363,AI Software Engineer,234411,USD,234411,EX,PT,Israel,L,Russia,50,"Spark, Computer Vision, Docker, Data Visualization, R",Bachelor,16,Manufacturing,2024-08-28,2024-09-24,2452,6.8,DataVision Ltd +AI13364,Deep Learning Engineer,28209,USD,28209,MI,PT,India,S,India,100,"Azure, Scala, Mathematics, Linux, SQL",Master,3,Transportation,2025-02-06,2025-03-31,1105,9.3,Future Systems +AI13365,Machine Learning Engineer,77044,USD,77044,EN,FL,Norway,S,France,100,"Azure, AWS, Git",PhD,1,Transportation,2025-01-31,2025-03-24,852,5.4,Autonomous Tech +AI13366,Principal Data Scientist,126485,JPY,13913350,SE,FT,Japan,M,Japan,50,"SQL, Kubernetes, PyTorch, Tableau, Deep Learning",Associate,8,Technology,2024-10-05,2024-12-04,2474,5.5,Neural Networks Co +AI13367,NLP Engineer,75977,USD,75977,EN,FL,Ireland,L,Ireland,50,"R, Git, TensorFlow, Computer Vision, Spark",PhD,1,Media,2024-10-09,2024-12-10,1540,7.5,AI Innovations +AI13368,Data Engineer,53042,EUR,45086,EN,CT,Austria,M,Mexico,0,"Python, TensorFlow, Scala, Azure",Associate,0,Education,2024-01-28,2024-03-09,1094,8.1,Digital Transformation LLC +AI13369,AI Product Manager,88798,EUR,75478,MI,FL,Netherlands,M,Nigeria,0,"Deep Learning, Azure, MLOps",Bachelor,3,Technology,2024-07-01,2024-07-26,2121,5.7,Cloud AI Solutions +AI13370,Autonomous Systems Engineer,133645,EUR,113598,EX,PT,Austria,S,Austria,0,"Spark, Python, TensorFlow",Bachelor,18,Retail,2024-06-05,2024-06-24,2153,9.9,Cloud AI Solutions +AI13371,Machine Learning Engineer,123940,USD,123940,SE,CT,Sweden,L,Sweden,50,"Computer Vision, NLP, Scala, Python, Kubernetes",Associate,8,Transportation,2024-03-08,2024-03-25,2348,8.9,Smart Analytics +AI13372,AI Product Manager,250927,USD,250927,EX,FL,Finland,L,Finland,50,"Python, Kubernetes, Tableau, Hadoop, Data Visualization",Master,11,Healthcare,2025-02-12,2025-03-07,1895,7.2,Algorithmic Solutions +AI13373,AI Research Scientist,68177,SGD,88630,EN,FL,Singapore,S,Singapore,0,"Tableau, SQL, Statistics, TensorFlow, Docker",Bachelor,0,Finance,2024-05-18,2024-07-12,1152,7.8,TechCorp Inc +AI13374,AI Software Engineer,92501,USD,92501,MI,FL,Israel,L,Israel,100,"Python, TensorFlow, Scala, Hadoop",Associate,2,Real Estate,2025-02-24,2025-04-21,535,7.1,Neural Networks Co +AI13375,Computer Vision Engineer,117573,EUR,99937,SE,CT,Netherlands,M,Indonesia,50,"Azure, GCP, Scala, Mathematics, Spark",Master,5,Real Estate,2024-09-24,2024-10-13,1801,7.8,Autonomous Tech +AI13376,AI Software Engineer,48867,USD,48867,EN,FL,South Korea,M,South Korea,100,"Data Visualization, Linux, AWS, PyTorch, Java",Master,1,Gaming,2024-04-10,2024-05-06,1455,8.8,Quantum Computing Inc +AI13377,AI Product Manager,65451,AUD,88359,EN,CT,Australia,S,Australia,50,"Hadoop, Data Visualization, TensorFlow, Mathematics, Azure",Associate,1,Transportation,2025-02-28,2025-04-18,973,8.5,Smart Analytics +AI13378,NLP Engineer,96257,EUR,81818,SE,CT,Austria,M,Thailand,100,"Scala, Linux, Tableau, Data Visualization",Bachelor,9,Technology,2024-11-22,2025-01-31,2016,9.9,DeepTech Ventures +AI13379,Computer Vision Engineer,64758,USD,64758,MI,FL,Israel,S,Israel,50,"Tableau, Spark, GCP, PyTorch, Data Visualization",Associate,4,Telecommunications,2024-07-17,2024-08-06,1475,9.7,Cognitive Computing +AI13380,AI Architect,76008,EUR,64607,EN,CT,Germany,M,Hungary,50,"Tableau, Kubernetes, Data Visualization",PhD,0,Manufacturing,2024-02-26,2024-04-03,2311,7.7,Future Systems +AI13381,ML Ops Engineer,61682,EUR,52430,EN,CT,Netherlands,S,Netherlands,50,"Python, Docker, Hadoop",PhD,0,Energy,2024-02-28,2024-03-27,1643,9.9,Cloud AI Solutions +AI13382,AI Specialist,193425,USD,193425,EX,FL,Ireland,S,Ireland,0,"NLP, PyTorch, Statistics, Spark, Mathematics",Bachelor,19,Media,2024-11-23,2024-12-24,1129,9.6,Advanced Robotics +AI13383,Computer Vision Engineer,96082,EUR,81670,SE,FL,France,M,France,0,"PyTorch, Mathematics, Python",Master,9,Energy,2024-08-15,2024-10-24,2178,6.7,Cloud AI Solutions +AI13384,AI Research Scientist,118266,CHF,106439,MI,CT,Switzerland,M,Turkey,50,"SQL, Mathematics, Spark, Kubernetes",Bachelor,3,Finance,2024-07-29,2024-09-22,1546,10,TechCorp Inc +AI13385,Head of AI,92143,AUD,124393,EN,FT,Australia,L,Australia,100,"Git, Docker, Kubernetes, Spark, GCP",Associate,1,Government,2024-03-27,2024-04-11,1750,5.5,Neural Networks Co +AI13386,Computer Vision Engineer,53657,SGD,69754,EN,FL,Singapore,S,Singapore,100,"PyTorch, GCP, Python",PhD,1,Gaming,2024-10-03,2024-11-27,1961,6.1,Predictive Systems +AI13387,AI Software Engineer,219960,USD,219960,EX,FT,United States,M,United States,100,"SQL, PyTorch, Kubernetes",Bachelor,17,Automotive,2024-03-14,2024-04-01,1905,8.2,Digital Transformation LLC +AI13388,AI Software Engineer,227427,USD,227427,EX,FT,Ireland,S,Ireland,0,"Scala, Git, Hadoop",Bachelor,15,Finance,2025-03-05,2025-03-23,1930,7.2,Machine Intelligence Group +AI13389,AI Research Scientist,140704,USD,140704,EX,PT,South Korea,L,South Korea,100,"SQL, Python, PyTorch, Azure, Mathematics",Bachelor,19,Retail,2024-10-08,2024-11-30,1659,6,Predictive Systems +AI13390,AI Architect,90170,USD,90170,EN,FL,Denmark,S,Norway,0,"R, Hadoop, Mathematics",PhD,1,Automotive,2025-01-27,2025-02-18,1589,7.9,Smart Analytics +AI13391,AI Architect,75174,AUD,101485,MI,FT,Australia,S,Australia,100,"GCP, Python, Tableau, MLOps",Associate,2,Consulting,2024-06-18,2024-07-25,2007,7.6,Digital Transformation LLC +AI13392,Data Scientist,98977,EUR,84130,MI,CT,Germany,S,Germany,100,"Deep Learning, Spark, Python",Associate,2,Retail,2025-02-10,2025-04-06,760,6.2,Advanced Robotics +AI13393,Data Engineer,92614,USD,92614,EN,PT,Norway,L,Norway,100,"SQL, Linux, MLOps, Python, GCP",Bachelor,1,Real Estate,2024-04-27,2024-06-06,2066,8,Advanced Robotics +AI13394,Research Scientist,24682,USD,24682,EN,CT,China,S,China,0,"AWS, Linux, TensorFlow",Bachelor,0,Government,2024-07-20,2024-09-27,1943,8.2,Neural Networks Co +AI13395,Head of AI,169552,USD,169552,EX,FT,Finland,S,Finland,100,"TensorFlow, Python, Tableau",Bachelor,11,Finance,2024-08-15,2024-10-27,1956,7.4,Digital Transformation LLC +AI13396,ML Ops Engineer,152388,EUR,129530,EX,PT,Germany,M,Germany,0,"PyTorch, GCP, Azure, SQL, Mathematics",Bachelor,14,Government,2024-05-28,2024-06-13,1778,7.6,Cognitive Computing +AI13397,Research Scientist,56108,EUR,47692,EN,FL,Netherlands,S,Netherlands,50,"NLP, Python, Java",Master,0,Automotive,2025-02-17,2025-04-14,576,5.4,Machine Intelligence Group +AI13398,AI Consultant,185781,USD,185781,SE,CT,Norway,M,Norway,100,"Computer Vision, Kubernetes, NLP, Java, TensorFlow",Bachelor,6,Real Estate,2024-03-26,2024-05-19,1329,9.7,AI Innovations +AI13399,ML Ops Engineer,175075,SGD,227598,EX,PT,Singapore,S,Singapore,0,"Spark, PyTorch, Docker, SQL",Associate,18,Telecommunications,2025-03-27,2025-05-23,588,6.2,DataVision Ltd +AI13400,AI Specialist,69174,USD,69174,EN,PT,United States,M,United States,100,"Kubernetes, Spark, Python, Java",PhD,0,Telecommunications,2024-03-20,2024-04-08,1954,9.9,Cognitive Computing +AI13401,Data Engineer,114304,CHF,102874,EN,FT,Switzerland,L,Switzerland,50,"R, Python, Mathematics, Java",Associate,0,Energy,2024-06-02,2024-06-16,634,7.5,Neural Networks Co +AI13402,AI Specialist,205622,EUR,174779,EX,FL,Netherlands,M,Netherlands,100,"Mathematics, SQL, Data Visualization",PhD,18,Healthcare,2025-04-11,2025-05-27,501,8,Quantum Computing Inc +AI13403,Computer Vision Engineer,162908,EUR,138472,SE,FT,France,L,Argentina,100,"Scala, Docker, Statistics",PhD,7,Consulting,2024-07-19,2024-09-19,2059,7,Autonomous Tech +AI13404,Principal Data Scientist,357781,USD,357781,EX,PT,Denmark,L,Denmark,100,"Python, TensorFlow, AWS, Computer Vision, Statistics",Associate,10,Government,2025-03-02,2025-03-25,994,10,DeepTech Ventures +AI13405,ML Ops Engineer,204495,USD,204495,EX,CT,Sweden,M,Sweden,0,"Python, Docker, Data Visualization",PhD,10,Telecommunications,2024-06-16,2024-07-08,2403,9.1,DeepTech Ventures +AI13406,AI Software Engineer,70678,GBP,53009,EN,FL,United Kingdom,M,United Kingdom,100,"Python, Hadoop, Git, TensorFlow, Statistics",Associate,0,Automotive,2025-04-30,2025-06-01,1363,7.6,Machine Intelligence Group +AI13407,Machine Learning Engineer,114963,EUR,97719,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Data Visualization, SQL, TensorFlow, Java",Master,4,Telecommunications,2024-09-17,2024-10-16,905,6.7,Future Systems +AI13408,Research Scientist,67163,USD,67163,EX,FL,India,S,India,100,"TensorFlow, Deep Learning, Tableau",Bachelor,17,Education,2025-04-03,2025-05-16,1435,8.1,Autonomous Tech +AI13409,Machine Learning Engineer,211419,SGD,274845,EX,FL,Singapore,S,Switzerland,100,"Hadoop, Java, NLP, TensorFlow, Kubernetes",PhD,12,Technology,2024-12-17,2025-01-05,1204,9.8,DataVision Ltd +AI13410,AI Software Engineer,134096,USD,134096,SE,FT,Sweden,L,Sweden,50,"Deep Learning, Docker, GCP, Data Visualization, AWS",Bachelor,6,Gaming,2025-01-27,2025-03-15,2282,5.1,Autonomous Tech +AI13411,AI Architect,146850,USD,146850,SE,PT,Finland,L,Finland,100,"Mathematics, PyTorch, Hadoop, Spark, TensorFlow",Master,8,Automotive,2024-04-28,2024-05-15,1904,7.5,Autonomous Tech +AI13412,Robotics Engineer,67285,JPY,7401350,EN,CT,Japan,M,Egypt,100,"NLP, Deep Learning, Hadoop, Computer Vision",Associate,0,Energy,2024-06-10,2024-07-11,1776,9.8,Future Systems +AI13413,Data Scientist,287563,USD,287563,EX,FL,United States,M,Spain,50,"Python, TensorFlow, Git, Hadoop",PhD,10,Energy,2024-10-21,2024-12-06,1959,5.3,DataVision Ltd +AI13414,Data Analyst,86376,USD,86376,MI,FT,Israel,L,Israel,50,"TensorFlow, Data Visualization, Statistics",Associate,3,Telecommunications,2024-04-21,2024-06-24,821,5.2,Digital Transformation LLC +AI13415,Data Engineer,78208,USD,78208,SE,FL,South Korea,S,South Korea,50,"GCP, PyTorch, NLP, MLOps, Java",Bachelor,7,Government,2024-06-13,2024-08-21,2037,6.7,Predictive Systems +AI13416,AI Research Scientist,83692,USD,83692,MI,CT,United States,S,Poland,100,"Git, Tableau, Data Visualization, Kubernetes",Master,2,Real Estate,2024-03-31,2024-05-15,1315,8.6,Autonomous Tech +AI13417,Robotics Engineer,143315,USD,143315,EX,FT,Ireland,M,Ireland,100,"Linux, Data Visualization, Docker",Associate,16,Healthcare,2024-10-09,2024-10-29,1430,8.1,Cognitive Computing +AI13418,AI Architect,75949,AUD,102531,EN,FL,Australia,L,Australia,0,"R, PyTorch, Docker",Bachelor,0,Technology,2024-11-21,2025-01-14,1323,5.7,Smart Analytics +AI13419,AI Architect,124751,EUR,106038,SE,FL,France,M,France,50,"Python, TensorFlow, Data Visualization, Hadoop",PhD,7,Healthcare,2024-10-23,2024-12-08,866,5.4,AI Innovations +AI13420,NLP Engineer,189998,EUR,161498,EX,FT,Netherlands,L,Ghana,50,"Kubernetes, SQL, Data Visualization, MLOps, PyTorch",Associate,17,Real Estate,2024-08-31,2024-09-23,1284,6.9,Advanced Robotics +AI13421,Data Engineer,193193,EUR,164214,EX,CT,France,L,France,50,"Linux, Azure, SQL, R, Java",Associate,14,Healthcare,2024-06-21,2024-07-10,1148,8.1,Digital Transformation LLC +AI13422,AI Consultant,180069,SGD,234090,EX,PT,Singapore,L,Singapore,50,"PyTorch, GCP, Hadoop",Master,11,Consulting,2024-09-29,2024-11-16,2011,7.2,Digital Transformation LLC +AI13423,Deep Learning Engineer,202205,USD,202205,EX,FT,Israel,L,Israel,0,"PyTorch, Spark, Python",PhD,14,Energy,2024-12-20,2025-01-21,1805,8.6,Advanced Robotics +AI13424,NLP Engineer,84851,USD,84851,EN,FL,Sweden,L,Sweden,50,"Kubernetes, Tableau, TensorFlow, GCP, Python",PhD,1,Gaming,2024-01-23,2024-02-26,691,7.6,Quantum Computing Inc +AI13425,Autonomous Systems Engineer,100135,GBP,75101,MI,FL,United Kingdom,S,United Kingdom,0,"Computer Vision, Scala, PyTorch, Linux",Associate,4,Retail,2024-06-22,2024-07-08,942,5.8,Smart Analytics +AI13426,Principal Data Scientist,149157,EUR,126783,SE,FT,Netherlands,L,Netherlands,0,"GCP, Docker, Data Visualization, Scala",Associate,9,Energy,2024-07-08,2024-09-14,2036,5.2,Quantum Computing Inc +AI13427,Data Engineer,255277,CAD,319096,EX,CT,Canada,L,Canada,50,"Kubernetes, NLP, R, Deep Learning",Bachelor,17,Retail,2024-08-22,2024-09-28,530,5,Advanced Robotics +AI13428,NLP Engineer,118601,CHF,106741,EN,CT,Switzerland,L,Switzerland,50,"Kubernetes, Git, SQL, TensorFlow",Master,1,Government,2024-07-25,2024-09-22,2069,5.3,TechCorp Inc +AI13429,AI Specialist,204430,AUD,275981,EX,FL,Australia,M,South Africa,0,"TensorFlow, Python, NLP, AWS, Git",Bachelor,16,Gaming,2024-05-25,2024-07-13,2183,8.1,Neural Networks Co +AI13430,AI Specialist,148777,USD,148777,SE,FT,Norway,S,India,0,"Java, Linux, PyTorch, NLP, Kubernetes",Master,5,Telecommunications,2025-04-24,2025-06-11,1673,8.5,Digital Transformation LLC +AI13431,AI Software Engineer,280124,USD,280124,EX,PT,Norway,L,Turkey,50,"Tableau, Data Visualization, Java, TensorFlow",PhD,19,Automotive,2024-12-15,2025-01-22,617,5.6,Advanced Robotics +AI13432,AI Software Engineer,68849,EUR,58522,EN,PT,Germany,L,Germany,100,"MLOps, Hadoop, Spark",Master,1,Energy,2025-03-14,2025-04-03,2099,8.6,Machine Intelligence Group +AI13433,AI Research Scientist,29926,USD,29926,MI,FT,India,L,India,50,"Statistics, Azure, Spark, PyTorch, Deep Learning",Master,4,Education,2024-05-06,2024-07-01,1172,7.6,Future Systems +AI13434,ML Ops Engineer,70863,USD,70863,EN,FT,Israel,L,Israel,50,"R, MLOps, SQL",PhD,0,Manufacturing,2025-02-23,2025-04-18,1950,7.9,Quantum Computing Inc +AI13435,Research Scientist,63834,USD,63834,EN,CT,Israel,M,Israel,0,"Java, GCP, MLOps, Deep Learning",Master,0,Transportation,2024-04-30,2024-07-09,922,9.3,Digital Transformation LLC +AI13436,Deep Learning Engineer,332210,CHF,298989,EX,FT,Switzerland,M,South Africa,100,"GCP, Deep Learning, Git",PhD,15,Energy,2025-02-03,2025-03-22,2134,10,Quantum Computing Inc +AI13437,AI Product Manager,67710,USD,67710,EN,PT,Denmark,S,Sweden,0,"Statistics, Linux, Data Visualization",Master,0,Manufacturing,2024-12-29,2025-02-24,1974,9.9,Future Systems +AI13438,Data Scientist,129621,EUR,110178,EX,CT,Austria,M,Argentina,0,"Git, Docker, Java, R, Hadoop",Bachelor,15,Real Estate,2024-01-25,2024-03-27,2066,9.4,Advanced Robotics +AI13439,Research Scientist,84399,USD,84399,MI,FL,Ireland,L,Switzerland,0,"AWS, MLOps, Python",Bachelor,4,Energy,2024-05-01,2024-07-01,1456,8.2,Machine Intelligence Group +AI13440,Research Scientist,140977,GBP,105733,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, PyTorch, Java",PhD,9,Media,2024-07-26,2024-10-04,1604,7.4,TechCorp Inc +AI13441,Research Scientist,130649,CHF,117584,EN,CT,Switzerland,L,Switzerland,0,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Retail,2024-04-03,2024-05-07,1426,5.7,Machine Intelligence Group +AI13442,AI Product Manager,94972,EUR,80726,MI,PT,France,L,New Zealand,100,"SQL, MLOps, Computer Vision, Linux, GCP",Bachelor,4,Consulting,2024-05-18,2024-06-12,1705,7.4,Predictive Systems +AI13443,AI Specialist,176030,EUR,149626,EX,PT,Austria,S,Finland,50,"Git, Scala, AWS",Master,18,Real Estate,2024-04-14,2024-06-13,1595,7.6,DeepTech Ventures +AI13444,Research Scientist,101314,USD,101314,SE,PT,Israel,M,Israel,100,"Linux, Spark, Computer Vision, MLOps, Python",PhD,9,Telecommunications,2024-10-10,2024-11-28,1405,6,Cloud AI Solutions +AI13445,AI Consultant,59806,EUR,50835,EN,PT,Germany,S,Germany,0,"Docker, Scala, Statistics",Associate,1,Consulting,2025-01-08,2025-01-24,965,6.3,Neural Networks Co +AI13446,Data Analyst,106748,USD,106748,SE,PT,Israel,S,Netherlands,100,"Scala, Python, Computer Vision, Tableau",Bachelor,5,Education,2024-04-23,2024-06-05,1187,7.4,TechCorp Inc +AI13447,Autonomous Systems Engineer,49405,CAD,61756,EN,PT,Canada,M,Canada,0,"Linux, Python, Tableau",PhD,0,Automotive,2025-01-10,2025-02-22,2350,5,Digital Transformation LLC +AI13448,Data Scientist,230116,SGD,299151,EX,PT,Singapore,L,Turkey,100,"Python, Java, Computer Vision, TensorFlow, GCP",Bachelor,18,Energy,2024-12-25,2025-02-15,1605,8,Autonomous Tech +AI13449,AI Specialist,155786,EUR,132418,SE,FL,Netherlands,M,United States,50,"NLP, SQL, MLOps",Bachelor,8,Education,2024-01-02,2024-01-26,1425,8.5,AI Innovations +AI13450,Data Scientist,78295,EUR,66551,MI,PT,Germany,M,Germany,0,"Scala, Python, Tableau, NLP, MLOps",Master,4,Technology,2024-08-02,2024-08-31,2422,6.2,Machine Intelligence Group +AI13451,ML Ops Engineer,116184,USD,116184,MI,CT,Ireland,L,Czech Republic,0,"SQL, MLOps, TensorFlow, Git, Data Visualization",PhD,4,Gaming,2024-03-22,2024-05-06,1048,8.4,DeepTech Ventures +AI13452,Machine Learning Engineer,70480,USD,70480,EN,FT,United States,S,United States,50,"Mathematics, Statistics, TensorFlow, PyTorch",Master,1,Media,2024-02-26,2024-03-24,1238,9.2,Quantum Computing Inc +AI13453,Machine Learning Engineer,257142,EUR,218571,EX,FL,France,L,South Korea,50,"Python, Kubernetes, GCP, R",PhD,10,Retail,2024-04-19,2024-05-06,2218,9.8,Advanced Robotics +AI13454,Head of AI,75895,CHF,68306,EN,PT,Switzerland,M,Spain,0,"Hadoop, AWS, Tableau",PhD,0,Energy,2024-10-11,2024-11-27,1842,7.3,DataVision Ltd +AI13455,Autonomous Systems Engineer,130146,JPY,14316060,MI,FL,Japan,L,Japan,0,"GCP, Docker, MLOps, Tableau, Hadoop",Bachelor,2,Telecommunications,2024-09-28,2024-10-18,2259,6.4,Quantum Computing Inc +AI13456,Head of AI,62607,USD,62607,SE,PT,China,S,China,0,"Spark, R, Linux, SQL",Bachelor,9,Media,2024-08-08,2024-10-04,2050,5.1,DataVision Ltd +AI13457,AI Specialist,213739,USD,213739,SE,CT,Denmark,L,Denmark,50,"SQL, Scala, Data Visualization, Linux, AWS",Associate,5,Energy,2024-03-28,2024-06-04,561,5.3,AI Innovations +AI13458,Research Scientist,239862,AUD,323814,EX,CT,Australia,L,Australia,50,"GCP, Hadoop, R",Bachelor,18,Government,2024-06-03,2024-07-22,713,5.4,AI Innovations +AI13459,Deep Learning Engineer,85775,EUR,72909,EN,FT,Austria,L,Colombia,50,"Spark, Data Visualization, Hadoop, Docker",Master,0,Retail,2024-06-15,2024-07-07,1378,6.3,Cognitive Computing +AI13460,Head of AI,52732,CAD,65915,EN,FL,Canada,M,Canada,100,"GCP, TensorFlow, Python, NLP",Bachelor,1,Finance,2025-02-04,2025-03-01,2406,6.5,AI Innovations +AI13461,Data Scientist,134420,SGD,174746,SE,FT,Singapore,M,Singapore,100,"Hadoop, SQL, Kubernetes",Bachelor,8,Education,2025-01-17,2025-03-06,1438,8.8,Quantum Computing Inc +AI13462,Robotics Engineer,261477,CHF,235329,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Python, GCP",Associate,12,Retail,2024-10-29,2024-12-02,1127,7,Cognitive Computing +AI13463,AI Consultant,163591,CHF,147232,SE,CT,Switzerland,M,Switzerland,100,"SQL, Hadoop, Scala, Deep Learning",Bachelor,9,Telecommunications,2024-09-24,2024-10-20,1728,8.4,Quantum Computing Inc +AI13464,AI Architect,140181,AUD,189244,SE,PT,Australia,M,Chile,0,"Azure, Tableau, Linux, Docker",Bachelor,9,Media,2024-03-23,2024-05-13,2319,6.6,Autonomous Tech +AI13465,Deep Learning Engineer,142202,AUD,191973,SE,PT,Australia,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, Statistics",Master,6,Real Estate,2024-03-20,2024-05-09,1741,9.8,Predictive Systems +AI13466,Research Scientist,157835,GBP,118376,EX,CT,United Kingdom,S,Italy,50,"GCP, AWS, Linux, Deep Learning, SQL",Master,16,Consulting,2024-02-25,2024-04-11,620,9.3,Cognitive Computing +AI13467,Deep Learning Engineer,186913,USD,186913,SE,FL,United States,L,United States,50,"TensorFlow, GCP, Deep Learning",Associate,8,Government,2024-02-04,2024-04-08,1879,9.4,Predictive Systems +AI13468,Machine Learning Engineer,133440,USD,133440,SE,FT,Sweden,S,Sweden,0,"Hadoop, Scala, Kubernetes, Mathematics, Python",Bachelor,9,Telecommunications,2025-03-15,2025-04-21,1873,5.5,DeepTech Ventures +AI13469,Robotics Engineer,138149,USD,138149,EX,CT,Ireland,S,New Zealand,50,"Deep Learning, Kubernetes, Computer Vision",PhD,10,Technology,2024-03-27,2024-05-11,617,6.3,AI Innovations +AI13470,Principal Data Scientist,130691,EUR,111087,SE,FL,Austria,L,Austria,0,"Kubernetes, Deep Learning, Java, AWS, Computer Vision",PhD,9,Media,2024-09-13,2024-10-24,1605,5.8,Machine Intelligence Group +AI13471,AI Research Scientist,87469,USD,87469,MI,PT,Israel,M,Israel,100,"Hadoop, SQL, Tableau, Azure, Kubernetes",Master,3,Government,2024-10-23,2024-11-28,2305,9.2,TechCorp Inc +AI13472,AI Specialist,106777,GBP,80083,MI,FL,United Kingdom,L,United Kingdom,0,"Deep Learning, SQL, Spark",PhD,3,Finance,2024-12-08,2024-12-26,1723,10,Neural Networks Co +AI13473,NLP Engineer,50461,USD,50461,SE,PT,China,M,China,100,"Data Visualization, Hadoop, Computer Vision",Associate,7,Finance,2024-04-01,2024-05-03,2354,5.8,Algorithmic Solutions +AI13474,Computer Vision Engineer,159609,EUR,135668,EX,FL,Austria,M,Indonesia,0,"Python, Git, TensorFlow",Associate,11,Consulting,2024-03-14,2024-03-29,1071,8.5,Predictive Systems +AI13475,Machine Learning Researcher,154149,EUR,131027,EX,PT,France,M,France,0,"Python, SQL, Linux, GCP",Master,18,Manufacturing,2024-07-14,2024-09-09,1775,8.5,Autonomous Tech +AI13476,AI Software Engineer,64819,GBP,48614,EN,FL,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Azure",Associate,1,Consulting,2024-05-16,2024-07-22,2036,5.7,TechCorp Inc +AI13477,Principal Data Scientist,125314,SGD,162908,MI,FL,Singapore,L,Singapore,100,"AWS, Azure, Spark, Computer Vision",Bachelor,2,Manufacturing,2024-11-03,2024-11-17,2038,9.1,Algorithmic Solutions +AI13478,AI Specialist,55051,USD,55051,EN,PT,Israel,S,Australia,100,"Scala, SQL, Azure",PhD,0,Technology,2024-11-01,2024-12-01,1137,7.1,Algorithmic Solutions +AI13479,AI Specialist,32595,USD,32595,MI,FT,India,L,India,100,"Hadoop, Java, NLP",Associate,4,Media,2024-04-13,2024-05-19,548,9.6,Digital Transformation LLC +AI13480,AI Architect,71110,EUR,60444,MI,FL,Netherlands,S,Belgium,100,"Git, R, TensorFlow",PhD,2,Finance,2024-06-25,2024-09-04,2334,7.8,Cognitive Computing +AI13481,AI Software Engineer,169547,JPY,18650170,EX,PT,Japan,S,Japan,100,"NLP, GCP, Tableau, PyTorch",Master,18,Finance,2024-03-09,2024-05-04,848,5.8,Algorithmic Solutions +AI13482,ML Ops Engineer,178084,CHF,160276,SE,CT,Switzerland,S,Switzerland,100,"Python, TensorFlow, AWS",Master,8,Real Estate,2025-03-29,2025-05-13,1319,8.4,Autonomous Tech +AI13483,AI Architect,62829,GBP,47122,EN,FL,United Kingdom,S,Romania,50,"NLP, Hadoop, Scala, SQL, GCP",PhD,1,Finance,2025-01-03,2025-01-24,1496,5.4,Neural Networks Co +AI13484,AI Research Scientist,159514,USD,159514,EX,CT,South Korea,M,South Korea,50,"Python, NLP, Mathematics, Git",Associate,17,Healthcare,2025-02-06,2025-04-13,2270,6.4,AI Innovations +AI13485,AI Architect,127374,USD,127374,MI,PT,Norway,S,Chile,50,"Python, MLOps, NLP, Linux, AWS",PhD,2,Finance,2024-04-24,2024-05-13,2290,6.2,Quantum Computing Inc +AI13486,ML Ops Engineer,123377,USD,123377,MI,FT,Sweden,L,Ireland,100,"Hadoop, Scala, Mathematics, Linux",Master,2,Automotive,2024-10-31,2024-12-05,603,5.5,TechCorp Inc +AI13487,AI Product Manager,131293,JPY,14442230,SE,CT,Japan,M,Japan,0,"Deep Learning, AWS, Python, Mathematics, Hadoop",Master,5,Retail,2024-06-16,2024-08-22,760,8,AI Innovations +AI13488,Data Engineer,69197,EUR,58817,EN,PT,Germany,M,Germany,50,"SQL, Docker, MLOps, Hadoop",Associate,0,Energy,2025-02-20,2025-03-25,1451,7.2,Advanced Robotics +AI13489,ML Ops Engineer,96379,EUR,81922,MI,FL,France,M,Argentina,100,"Tableau, Computer Vision, Docker",Associate,3,Transportation,2024-04-06,2024-06-07,557,7.9,Autonomous Tech +AI13490,Robotics Engineer,57105,USD,57105,EN,CT,Israel,L,Spain,50,"R, Tableau, SQL, Deep Learning",Associate,1,Media,2024-10-16,2024-12-07,2426,6.8,Machine Intelligence Group +AI13491,AI Consultant,41328,USD,41328,MI,FL,China,M,New Zealand,50,"Docker, SQL, Azure, Python, Mathematics",Master,2,Government,2024-02-10,2024-02-27,576,9.9,Machine Intelligence Group +AI13492,Data Scientist,119623,USD,119623,MI,CT,Denmark,L,Denmark,0,"Python, TensorFlow, Deep Learning, SQL",Bachelor,2,Technology,2025-04-29,2025-06-22,1740,6.8,DataVision Ltd +AI13493,Robotics Engineer,158417,USD,158417,EX,PT,Ireland,M,Ireland,50,"Python, Azure, TensorFlow",Associate,10,Technology,2025-01-18,2025-03-01,2083,8,Autonomous Tech +AI13494,Data Scientist,82345,AUD,111166,MI,FT,Australia,S,Australia,100,"Deep Learning, Tableau, Statistics",Bachelor,4,Gaming,2025-04-15,2025-05-22,2475,5.6,DataVision Ltd +AI13495,Computer Vision Engineer,28336,USD,28336,EN,CT,India,M,India,50,"Statistics, Mathematics, AWS",Bachelor,0,Telecommunications,2024-12-21,2025-02-04,2180,6.9,TechCorp Inc +AI13496,Computer Vision Engineer,176246,USD,176246,EX,FT,South Korea,S,South Korea,50,"Docker, Kubernetes, MLOps, Deep Learning",Bachelor,15,Retail,2025-01-16,2025-03-29,1879,5.4,Smart Analytics +AI13497,NLP Engineer,47000,USD,47000,SE,FL,India,S,India,100,"Python, NLP, TensorFlow, GCP",Master,7,Transportation,2025-03-26,2025-04-12,1770,8.1,AI Innovations +AI13498,ML Ops Engineer,47164,USD,47164,EN,FL,South Korea,M,South Korea,50,"Computer Vision, Deep Learning, Scala, Python",PhD,1,Media,2025-04-08,2025-05-29,2331,5.5,DataVision Ltd +AI13499,Principal Data Scientist,132818,SGD,172663,SE,CT,Singapore,M,Singapore,0,"Linux, MLOps, Scala, Data Visualization",PhD,5,Real Estate,2024-12-06,2025-01-29,1896,8.9,Neural Networks Co +AI13500,AI Specialist,85866,EUR,72986,MI,CT,Germany,L,Germany,100,"PyTorch, Deep Learning, Kubernetes, AWS, Computer Vision",PhD,3,Media,2024-11-23,2025-01-19,2172,8,Neural Networks Co +AI13501,NLP Engineer,92368,EUR,78513,SE,FL,Germany,S,Germany,100,"AWS, Linux, Spark",Master,8,Automotive,2024-06-05,2024-06-25,1291,6.5,Autonomous Tech +AI13502,Computer Vision Engineer,100531,USD,100531,SE,PT,South Korea,L,South Korea,0,"SQL, Docker, Python, MLOps",Associate,6,Consulting,2024-07-17,2024-08-12,988,6.4,Algorithmic Solutions +AI13503,Data Analyst,87818,USD,87818,MI,PT,Finland,S,Argentina,50,"Kubernetes, Azure, Java, Data Visualization, GCP",Associate,3,Energy,2025-04-15,2025-06-10,1287,9.1,Digital Transformation LLC +AI13504,Robotics Engineer,214112,AUD,289051,EX,CT,Australia,S,Australia,100,"Python, Mathematics, Hadoop, Scala, Azure",PhD,16,Telecommunications,2025-03-02,2025-03-24,1204,7.7,Future Systems +AI13505,Data Engineer,137081,JPY,15078910,SE,FL,Japan,L,Switzerland,100,"Tableau, Python, Scala, Spark",Bachelor,7,Automotive,2024-01-28,2024-03-22,1876,5.3,DataVision Ltd +AI13506,Data Analyst,53421,USD,53421,SE,PT,India,M,India,0,"Kubernetes, Git, NLP, TensorFlow, PyTorch",Associate,8,Healthcare,2024-08-02,2024-09-04,931,5.6,Autonomous Tech +AI13507,AI Architect,75794,GBP,56846,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Docker, Spark, Computer Vision, PyTorch",Associate,0,Gaming,2025-03-24,2025-04-24,1153,6.2,Cognitive Computing +AI13508,NLP Engineer,175103,EUR,148838,EX,CT,Austria,L,Austria,50,"Java, Scala, GCP",PhD,17,Telecommunications,2024-06-03,2024-07-02,1294,5.3,Neural Networks Co +AI13509,ML Ops Engineer,175669,CHF,158102,SE,FL,Switzerland,S,Switzerland,100,"TensorFlow, Git, SQL",PhD,6,Media,2024-08-29,2024-09-28,1991,7.7,Autonomous Tech +AI13510,AI Architect,152942,USD,152942,EX,CT,Israel,L,Israel,0,"Kubernetes, Java, Git",PhD,14,Transportation,2024-10-04,2024-10-25,2411,8.4,Future Systems +AI13511,AI Architect,115652,USD,115652,MI,PT,Finland,L,Finland,100,"Linux, SQL, PyTorch, GCP, TensorFlow",Master,4,Gaming,2025-04-16,2025-05-09,691,5.9,Cognitive Computing +AI13512,AI Product Manager,254643,EUR,216447,EX,CT,Netherlands,L,Netherlands,0,"Hadoop, Statistics, Linux, Data Visualization",Associate,17,Gaming,2024-03-05,2024-05-17,1152,6.3,Autonomous Tech +AI13513,Machine Learning Researcher,113576,EUR,96540,MI,PT,Germany,L,Latvia,0,"SQL, Linux, R, Hadoop, Computer Vision",Master,4,Media,2024-10-20,2024-11-21,1737,7.2,Smart Analytics +AI13514,Data Engineer,82775,USD,82775,EN,FL,Norway,M,Norway,100,"Mathematics, R, Docker, Spark, SQL",PhD,1,Telecommunications,2024-02-14,2024-03-18,1834,9.4,Quantum Computing Inc +AI13515,AI Architect,166158,USD,166158,SE,PT,Norway,S,Norway,100,"Java, MLOps, NLP, Git, Mathematics",PhD,5,Transportation,2024-11-05,2024-12-28,604,9.8,AI Innovations +AI13516,Computer Vision Engineer,128965,USD,128965,MI,FT,United States,L,United States,0,"GCP, TensorFlow, Mathematics, Computer Vision, AWS",PhD,4,Consulting,2024-10-04,2024-11-27,871,8,Autonomous Tech +AI13517,Data Scientist,117391,USD,117391,SE,CT,South Korea,M,South Korea,50,"Spark, TensorFlow, GCP",Associate,9,Telecommunications,2024-11-06,2025-01-14,1903,8.8,Autonomous Tech +AI13518,Data Analyst,270558,USD,270558,EX,FL,Norway,S,Norway,0,"GCP, Python, MLOps, Tableau, Kubernetes",Master,17,Media,2025-01-07,2025-03-07,2124,9.3,Neural Networks Co +AI13519,Data Engineer,190549,CAD,238186,EX,FL,Canada,S,Spain,50,"Python, Git, MLOps",Bachelor,10,Education,2024-08-18,2024-10-22,1395,6.6,AI Innovations +AI13520,Computer Vision Engineer,53483,USD,53483,EN,CT,South Korea,S,Thailand,0,"Python, Deep Learning, SQL",Bachelor,1,Gaming,2024-04-20,2024-06-01,1095,6.2,DataVision Ltd +AI13521,Computer Vision Engineer,119338,USD,119338,SE,FT,United States,S,Kenya,50,"TensorFlow, R, MLOps, Java, AWS",PhD,6,Gaming,2024-09-06,2024-11-05,2370,6.9,Cloud AI Solutions +AI13522,AI Architect,66333,USD,66333,MI,PT,South Korea,S,Thailand,100,"Statistics, Hadoop, Tableau, GCP",PhD,4,Education,2024-10-09,2024-11-12,1271,7.9,Predictive Systems +AI13523,Machine Learning Researcher,102503,GBP,76877,MI,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Scala, Docker, Java, Deep Learning",Master,4,Media,2024-01-23,2024-03-11,1799,6.3,Cloud AI Solutions +AI13524,AI Architect,135092,USD,135092,SE,CT,Finland,M,Finland,0,"Scala, SQL, PyTorch, Spark",Bachelor,8,Healthcare,2024-11-29,2024-12-25,2206,5.5,Cloud AI Solutions +AI13525,Machine Learning Engineer,102919,USD,102919,SE,CT,South Korea,S,South Korea,100,"GCP, Python, Java, Docker",PhD,5,Government,2024-06-09,2024-08-01,897,9.4,Cognitive Computing +AI13526,Principal Data Scientist,135359,SGD,175967,SE,CT,Singapore,M,Singapore,100,"TensorFlow, SQL, GCP, Java, Statistics",Bachelor,9,Transportation,2024-12-16,2025-02-11,1370,6.7,AI Innovations +AI13527,Machine Learning Engineer,125939,USD,125939,MI,CT,Norway,L,Norway,50,"Mathematics, Linux, Hadoop, TensorFlow",PhD,2,Retail,2025-01-19,2025-03-22,674,6.3,Autonomous Tech +AI13528,Research Scientist,187712,CHF,168941,SE,CT,Switzerland,S,Switzerland,0,"MLOps, R, Azure",Associate,8,Retail,2024-10-31,2024-12-06,1040,8,Advanced Robotics +AI13529,AI Research Scientist,243121,SGD,316057,EX,PT,Singapore,M,Singapore,50,"Java, SQL, Data Visualization",Associate,11,Transportation,2024-01-06,2024-03-04,716,5.8,AI Innovations +AI13530,AI Software Engineer,53273,USD,53273,SE,FT,India,M,India,50,"Python, Statistics, Hadoop, TensorFlow",PhD,6,Government,2024-12-27,2025-02-09,2149,7.2,Neural Networks Co +AI13531,Data Analyst,34231,USD,34231,EN,PT,China,L,China,0,"Kubernetes, Python, Git",Master,0,Education,2024-01-25,2024-03-09,2443,8.8,Algorithmic Solutions +AI13532,Research Scientist,64663,GBP,48497,EN,FT,United Kingdom,S,United Kingdom,0,"MLOps, Azure, TensorFlow, Deep Learning, Python",PhD,1,Manufacturing,2024-12-11,2025-02-16,2320,7.7,Cognitive Computing +AI13533,Robotics Engineer,145887,CHF,131298,SE,FL,Switzerland,S,Switzerland,50,"Deep Learning, SQL, PyTorch, Linux",Associate,7,Manufacturing,2024-12-23,2025-01-08,2106,6,Quantum Computing Inc +AI13534,Robotics Engineer,225404,GBP,169053,EX,FL,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning",Master,16,Technology,2025-03-07,2025-03-31,1137,8.3,Future Systems +AI13535,Machine Learning Researcher,118211,USD,118211,SE,FL,South Korea,M,South Korea,0,"Spark, GCP, SQL, MLOps",Master,5,Healthcare,2024-04-01,2024-05-24,817,8,DeepTech Ventures +AI13536,AI Product Manager,121319,USD,121319,MI,CT,Norway,M,Romania,50,"R, Tableau, Java, Git, Computer Vision",Associate,4,Consulting,2024-03-10,2024-05-14,737,7.2,Autonomous Tech +AI13537,Robotics Engineer,83754,JPY,9212940,MI,FL,Japan,S,Denmark,50,"Computer Vision, Kubernetes, Deep Learning",Bachelor,4,Manufacturing,2024-08-23,2024-10-25,2217,8.4,Neural Networks Co +AI13538,Head of AI,41420,USD,41420,SE,CT,India,M,India,100,"Java, Azure, MLOps, Hadoop, Spark",PhD,7,Retail,2024-03-24,2024-04-13,511,8.4,Advanced Robotics +AI13539,ML Ops Engineer,167184,USD,167184,SE,CT,Denmark,L,Nigeria,50,"Computer Vision, SQL, Python, Azure",Associate,7,Energy,2025-04-05,2025-05-14,1470,5.7,TechCorp Inc +AI13540,Data Engineer,79973,USD,79973,EN,FL,Norway,S,Norway,0,"Scala, Kubernetes, PyTorch",Associate,0,Retail,2024-02-29,2024-04-20,1710,7.4,DataVision Ltd +AI13541,Machine Learning Engineer,215068,USD,215068,SE,CT,Norway,L,Norway,50,"Python, TensorFlow, Computer Vision, Git, Linux",Master,5,Manufacturing,2024-07-15,2024-09-14,1303,9.2,Cloud AI Solutions +AI13542,AI Research Scientist,61811,USD,61811,EN,FT,Israel,S,Estonia,0,"Python, Tableau, Kubernetes",Master,0,Media,2025-02-18,2025-04-21,1234,8.9,DeepTech Ventures +AI13543,AI Architect,105290,SGD,136877,SE,FL,Singapore,S,Singapore,0,"SQL, Spark, Scala, Git, Azure",Associate,6,Telecommunications,2025-03-12,2025-05-21,1211,5.4,Quantum Computing Inc +AI13544,AI Consultant,87480,SGD,113724,MI,FL,Singapore,M,Singapore,100,"SQL, Tableau, Spark, PyTorch",Associate,3,Education,2024-12-24,2025-01-25,1963,7.2,Advanced Robotics +AI13545,Computer Vision Engineer,100005,CAD,125006,MI,FL,Canada,M,Romania,0,"Computer Vision, R, Linux, PyTorch, Git",PhD,3,Education,2024-11-14,2024-12-19,1834,6.6,Cognitive Computing +AI13546,Robotics Engineer,162358,CHF,146122,MI,CT,Switzerland,L,Switzerland,50,"SQL, Python, Tableau, MLOps, Spark",Bachelor,3,Finance,2024-01-23,2024-03-14,504,9.3,AI Innovations +AI13547,Machine Learning Researcher,158769,USD,158769,EX,FL,South Korea,S,Ireland,0,"MLOps, NLP, R, Python, Tableau",Associate,10,Government,2025-02-24,2025-03-31,1856,9,Cognitive Computing +AI13548,Machine Learning Engineer,231743,EUR,196982,EX,CT,Netherlands,S,Netherlands,100,"SQL, Scala, Docker, Mathematics, Computer Vision",Associate,12,Healthcare,2025-04-04,2025-05-12,1675,8.3,Advanced Robotics +AI13549,Robotics Engineer,198048,EUR,168341,EX,FL,Germany,L,Germany,100,"Java, MLOps, Git, Spark, Scala",PhD,14,Retail,2025-02-17,2025-04-30,2389,7.9,Neural Networks Co +AI13550,Computer Vision Engineer,170409,USD,170409,SE,FT,Norway,M,Norway,50,"Python, Data Visualization, PyTorch, Tableau, AWS",Bachelor,8,Technology,2024-03-22,2024-05-18,1565,8.9,Predictive Systems +AI13551,Data Scientist,137317,JPY,15104870,SE,FT,Japan,M,Japan,100,"Kubernetes, Spark, GCP, Python, Mathematics",Master,7,Real Estate,2025-04-16,2025-06-17,506,9.5,TechCorp Inc +AI13552,Data Analyst,215252,USD,215252,EX,FT,Norway,L,Norway,50,"Spark, Python, Data Visualization",PhD,16,Government,2025-03-02,2025-05-08,1376,7.6,DeepTech Ventures +AI13553,NLP Engineer,115357,AUD,155732,SE,PT,Australia,S,Colombia,100,"R, Kubernetes, SQL, Hadoop, Statistics",Master,6,Education,2025-02-13,2025-03-17,737,7.6,Smart Analytics +AI13554,NLP Engineer,78765,EUR,66950,MI,CT,Netherlands,M,Netherlands,100,"TensorFlow, Hadoop, Scala",Associate,2,Gaming,2025-01-01,2025-03-11,1847,6.3,Autonomous Tech +AI13555,Deep Learning Engineer,111065,CHF,99959,EN,CT,Switzerland,M,Switzerland,50,"Git, NLP, Scala, Computer Vision",Bachelor,0,Gaming,2024-02-06,2024-03-28,1593,7.4,Machine Intelligence Group +AI13556,Data Scientist,79550,USD,79550,SE,PT,China,L,China,100,"Tableau, Data Visualization, AWS",Associate,8,Government,2024-05-13,2024-07-24,2221,5.3,TechCorp Inc +AI13557,Data Analyst,155394,USD,155394,EX,PT,South Korea,S,New Zealand,50,"R, Tableau, Computer Vision",Associate,12,Healthcare,2025-01-03,2025-02-28,2068,7.5,Advanced Robotics +AI13558,Deep Learning Engineer,92899,USD,92899,MI,FL,Israel,L,Israel,100,"Java, MLOps, AWS",Bachelor,4,Manufacturing,2024-09-14,2024-10-24,1009,9.6,Digital Transformation LLC +AI13559,Data Engineer,94215,GBP,70661,MI,CT,United Kingdom,S,Argentina,50,"NLP, Mathematics, Kubernetes, MLOps",Bachelor,3,Technology,2024-12-30,2025-03-07,1513,8.3,Quantum Computing Inc +AI13560,Robotics Engineer,80817,AUD,109103,MI,PT,Australia,M,Nigeria,50,"Computer Vision, Linux, MLOps",PhD,3,Gaming,2024-09-29,2024-10-14,1084,8.4,DeepTech Ventures +AI13561,Machine Learning Researcher,142421,EUR,121058,EX,FT,Austria,S,Austria,100,"Spark, Scala, Deep Learning, TensorFlow, Azure",Associate,16,Healthcare,2024-07-13,2024-09-16,1113,5.2,Neural Networks Co +AI13562,AI Software Engineer,162016,SGD,210621,EX,FL,Singapore,M,France,50,"NLP, Python, TensorFlow, Spark",Bachelor,10,Gaming,2025-02-15,2025-03-29,2037,9,Quantum Computing Inc +AI13563,AI Specialist,240723,USD,240723,EX,CT,Ireland,M,Ireland,100,"Computer Vision, AWS, Kubernetes, Data Visualization, Git",PhD,17,Consulting,2024-02-07,2024-04-13,624,7.6,Cloud AI Solutions +AI13564,Computer Vision Engineer,177202,USD,177202,EX,FT,Denmark,M,United States,0,"Kubernetes, R, SQL, Java",Associate,11,Telecommunications,2025-01-09,2025-02-20,713,9.7,Digital Transformation LLC +AI13565,AI Software Engineer,19994,USD,19994,EN,PT,India,S,India,0,"Deep Learning, Mathematics, Scala",Associate,1,Consulting,2024-12-07,2025-01-07,1936,6.2,AI Innovations +AI13566,Research Scientist,87827,GBP,65870,MI,CT,United Kingdom,M,China,100,"Scala, R, AWS",Bachelor,4,Government,2025-03-13,2025-05-19,859,5.3,Digital Transformation LLC +AI13567,Data Engineer,246485,SGD,320431,EX,CT,Singapore,L,Singapore,50,"Kubernetes, Azure, Deep Learning, R",PhD,17,Real Estate,2025-01-02,2025-03-16,561,9,TechCorp Inc +AI13568,AI Architect,185718,JPY,20428980,EX,FL,Japan,S,Japan,50,"Scala, R, SQL, GCP, Mathematics",Associate,12,Technology,2024-01-31,2024-02-25,2094,7.8,Digital Transformation LLC +AI13569,AI Consultant,80076,USD,80076,SE,FT,China,L,Portugal,100,"Docker, Java, Statistics, Git",PhD,9,Manufacturing,2024-01-15,2024-02-12,1429,8.4,Advanced Robotics +AI13570,AI Software Engineer,184303,GBP,138227,SE,FL,United Kingdom,L,Mexico,0,"Python, Deep Learning, TensorFlow, Computer Vision, Kubernetes",Associate,5,Gaming,2024-10-28,2025-01-07,1685,6.5,TechCorp Inc +AI13571,Computer Vision Engineer,144334,CAD,180418,EX,CT,Canada,S,Canada,50,"Data Visualization, Java, Deep Learning",Associate,10,Government,2024-08-16,2024-10-01,1155,5.5,DeepTech Ventures +AI13572,Principal Data Scientist,136225,EUR,115791,SE,CT,Austria,L,Austria,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,9,Energy,2025-01-05,2025-03-08,1676,8.4,Smart Analytics +AI13573,Machine Learning Researcher,132186,USD,132186,SE,CT,Finland,M,Finland,100,"Java, NLP, AWS, Statistics",Associate,7,Manufacturing,2025-01-30,2025-03-03,1939,5.3,Advanced Robotics +AI13574,Deep Learning Engineer,125855,USD,125855,MI,CT,Sweden,L,Sweden,50,"R, TensorFlow, Kubernetes",Bachelor,3,Media,2024-12-21,2025-01-05,1426,9.5,Machine Intelligence Group +AI13575,Head of AI,56288,USD,56288,EN,FT,South Korea,S,South Korea,100,"Data Visualization, Java, Scala, Python, TensorFlow",PhD,0,Retail,2024-10-27,2024-12-20,2134,9.3,DataVision Ltd +AI13576,Data Scientist,249001,EUR,211651,EX,CT,Austria,L,Austria,0,"Tableau, Kubernetes, TensorFlow, Scala, AWS",Master,12,Telecommunications,2024-09-17,2024-11-26,1570,6.3,Predictive Systems +AI13577,Principal Data Scientist,132994,EUR,113045,EX,PT,Netherlands,S,Netherlands,100,"R, Computer Vision, NLP",Master,13,Healthcare,2025-04-22,2025-07-02,2196,8.9,TechCorp Inc +AI13578,AI Architect,108206,AUD,146078,MI,PT,Australia,M,Australia,50,"Tableau, Mathematics, Data Visualization, Python, Spark",Associate,2,Consulting,2024-06-30,2024-07-18,579,8.4,Quantum Computing Inc +AI13579,AI Consultant,55261,GBP,41446,EN,CT,United Kingdom,M,United Kingdom,100,"Python, Java, PyTorch",PhD,1,Telecommunications,2024-11-09,2024-12-14,831,5.7,Smart Analytics +AI13580,Head of AI,212757,EUR,180843,EX,FL,France,S,France,50,"Spark, Tableau, Scala, Linux",Master,10,Manufacturing,2024-05-19,2024-07-09,2126,7.6,Machine Intelligence Group +AI13581,Principal Data Scientist,115527,USD,115527,MI,PT,Denmark,S,United States,50,"SQL, Git, NLP, GCP, PyTorch",Associate,4,Education,2024-03-10,2024-05-20,785,5.8,Digital Transformation LLC +AI13582,Research Scientist,90576,USD,90576,EX,FT,China,S,Spain,50,"Linux, Hadoop, GCP",Associate,17,Telecommunications,2024-04-29,2024-07-01,652,5.8,Autonomous Tech +AI13583,NLP Engineer,68314,EUR,58067,EN,FL,Austria,S,Austria,50,"SQL, Linux, Computer Vision, Scala",Bachelor,0,Consulting,2024-02-02,2024-03-24,1389,9.8,Future Systems +AI13584,Data Analyst,80632,USD,80632,EN,FT,Norway,S,Norway,100,"Tableau, GCP, Linux",PhD,1,Media,2024-01-09,2024-02-12,845,9.2,Advanced Robotics +AI13585,Head of AI,85732,USD,85732,MI,PT,South Korea,L,South Korea,0,"Scala, MLOps, Tableau, SQL",Associate,4,Education,2024-03-17,2024-05-11,888,6.3,Digital Transformation LLC +AI13586,Machine Learning Engineer,89212,USD,89212,EN,CT,Denmark,M,Denmark,0,"TensorFlow, Data Visualization, Linux, PyTorch",Bachelor,1,Healthcare,2024-01-12,2024-02-27,2145,5.6,AI Innovations +AI13587,AI Product Manager,58528,USD,58528,SE,FL,India,L,India,50,"Hadoop, Git, PyTorch, Azure",PhD,5,Consulting,2024-10-31,2024-12-19,2079,9.9,Advanced Robotics +AI13588,Data Engineer,111013,EUR,94361,SE,PT,Netherlands,M,Mexico,100,"Scala, AWS, Java, Kubernetes, Deep Learning",Associate,5,Transportation,2025-03-11,2025-03-28,2267,9.5,Advanced Robotics +AI13589,ML Ops Engineer,161974,EUR,137678,SE,PT,France,L,Austria,0,"Statistics, R, Tableau",Bachelor,9,Finance,2024-02-26,2024-03-31,1545,6.2,Quantum Computing Inc +AI13590,AI Consultant,100290,USD,100290,MI,FT,Denmark,S,Denmark,0,"Kubernetes, Hadoop, PyTorch",Bachelor,2,Consulting,2024-04-13,2024-05-20,1342,5.8,Digital Transformation LLC +AI13591,Machine Learning Engineer,66642,USD,66642,EN,FL,Norway,M,Germany,50,"SQL, Hadoop, Tableau, Git, Scala",Associate,1,Finance,2025-02-23,2025-05-04,2080,5.4,Neural Networks Co +AI13592,Head of AI,162695,USD,162695,EX,PT,South Korea,M,Finland,0,"R, NLP, SQL",Associate,12,Government,2024-10-29,2024-12-06,2391,9.4,Smart Analytics +AI13593,AI Specialist,137077,EUR,116515,SE,FL,Austria,M,Austria,0,"Statistics, SQL, PyTorch, Deep Learning, Python",Associate,5,Transportation,2024-01-06,2024-03-17,1084,6.5,Advanced Robotics +AI13594,AI Software Engineer,132459,GBP,99344,SE,FL,United Kingdom,S,France,50,"Linux, Computer Vision, Deep Learning",Associate,8,Transportation,2024-08-25,2024-09-29,1483,5.4,AI Innovations +AI13595,Computer Vision Engineer,19457,USD,19457,EN,CT,India,S,India,0,"Scala, Kubernetes, Azure",PhD,0,Gaming,2025-04-09,2025-05-29,2272,8.1,TechCorp Inc +AI13596,Machine Learning Researcher,38912,USD,38912,MI,PT,India,L,India,50,"Mathematics, PyTorch, Python, Java, TensorFlow",PhD,2,Media,2024-10-30,2024-12-19,505,9.7,Advanced Robotics +AI13597,Data Scientist,111322,CAD,139153,MI,CT,Canada,L,Canada,100,"Docker, PyTorch, Computer Vision, AWS",Bachelor,4,Healthcare,2024-03-06,2024-05-02,1667,6.7,Machine Intelligence Group +AI13598,NLP Engineer,39729,USD,39729,MI,FL,China,S,China,100,"Python, Java, Docker",Bachelor,4,Education,2024-01-16,2024-02-08,820,7.6,Quantum Computing Inc +AI13599,Data Analyst,64601,USD,64601,EN,CT,Sweden,M,Sweden,100,"Java, MLOps, Kubernetes, Mathematics",Bachelor,1,Media,2024-09-14,2024-10-21,1542,5.8,Algorithmic Solutions +AI13600,Head of AI,199532,USD,199532,EX,PT,Ireland,S,Ireland,100,"Statistics, Hadoop, Spark",Associate,17,Finance,2024-10-17,2024-12-20,1422,9.4,Cloud AI Solutions +AI13601,ML Ops Engineer,204827,USD,204827,EX,PT,Norway,M,Malaysia,100,"MLOps, Mathematics, SQL",PhD,13,Education,2024-06-13,2024-08-11,1453,5.2,Algorithmic Solutions +AI13602,AI Software Engineer,131492,USD,131492,MI,CT,Norway,L,Norway,100,"Python, Linux, Docker, Git",PhD,3,Automotive,2025-01-26,2025-03-11,1257,5.2,Machine Intelligence Group +AI13603,Head of AI,200548,USD,200548,EX,CT,Ireland,M,Thailand,100,"SQL, NLP, PyTorch",PhD,17,Media,2024-05-22,2024-06-30,657,9,DeepTech Ventures +AI13604,Research Scientist,109537,SGD,142398,MI,PT,Singapore,L,Philippines,100,"PyTorch, Scala, NLP, Tableau",Master,3,Real Estate,2024-06-20,2024-07-08,1744,8.9,Autonomous Tech +AI13605,Deep Learning Engineer,169432,USD,169432,SE,PT,Ireland,L,Ireland,50,"Kubernetes, Python, Computer Vision",Master,6,Automotive,2024-09-12,2024-10-19,1222,6.2,Future Systems +AI13606,NLP Engineer,166233,USD,166233,EX,PT,United States,M,United States,0,"GCP, Azure, Computer Vision",Master,12,Government,2025-01-20,2025-02-05,1119,7.8,Machine Intelligence Group +AI13607,AI Consultant,67397,AUD,90986,MI,FT,Australia,S,Australia,50,"Scala, PyTorch, SQL",PhD,2,Technology,2025-03-16,2025-04-30,2214,8.1,DataVision Ltd +AI13608,AI Consultant,56703,USD,56703,SE,FT,China,S,China,0,"Git, R, Computer Vision",Bachelor,8,Manufacturing,2024-11-11,2024-12-21,2219,8.7,DeepTech Ventures +AI13609,Research Scientist,26374,USD,26374,EN,CT,China,S,China,0,"Kubernetes, Python, Scala, Deep Learning, Computer Vision",Associate,1,Government,2024-10-18,2024-11-24,575,9.3,Digital Transformation LLC +AI13610,AI Architect,45657,USD,45657,SE,CT,India,L,India,0,"Computer Vision, Deep Learning, R",Bachelor,9,Gaming,2024-01-16,2024-03-03,624,7.4,Digital Transformation LLC +AI13611,Computer Vision Engineer,39452,USD,39452,EN,CT,South Korea,S,Norway,50,"Git, NLP, Python",Associate,0,Education,2025-01-25,2025-02-28,1967,7.1,Machine Intelligence Group +AI13612,Data Analyst,123631,USD,123631,SE,PT,Sweden,S,Sweden,100,"TensorFlow, Mathematics, GCP",Bachelor,9,Healthcare,2024-02-25,2024-04-28,1819,7.7,DataVision Ltd +AI13613,ML Ops Engineer,102463,SGD,133202,MI,CT,Singapore,S,Singapore,100,"MLOps, Statistics, Scala, Data Visualization",Associate,2,Healthcare,2024-08-21,2024-09-15,799,7.2,Neural Networks Co +AI13614,Data Engineer,38458,USD,38458,MI,FT,China,M,China,100,"Azure, Computer Vision, Docker, PyTorch",Master,3,Manufacturing,2025-04-05,2025-05-30,2158,6,Autonomous Tech +AI13615,AI Software Engineer,50577,EUR,42990,EN,PT,Germany,S,Germany,50,"TensorFlow, R, Azure, AWS, NLP",Associate,0,Technology,2024-10-21,2024-12-28,1836,8.4,DeepTech Ventures +AI13616,Machine Learning Engineer,91272,AUD,123217,EN,FL,Australia,L,Malaysia,50,"Python, TensorFlow, Data Visualization",Master,0,Real Estate,2025-03-05,2025-04-03,1752,8.1,Quantum Computing Inc +AI13617,AI Software Engineer,92478,USD,92478,EN,CT,United States,L,United States,100,"Computer Vision, Statistics, MLOps",PhD,0,Automotive,2024-05-03,2024-06-24,1054,5.5,Cloud AI Solutions +AI13618,NLP Engineer,213025,USD,213025,EX,CT,Sweden,S,Sweden,100,"Python, Linux, GCP, Hadoop, PyTorch",Bachelor,10,Government,2025-02-15,2025-03-14,534,6.2,Algorithmic Solutions +AI13619,Autonomous Systems Engineer,240149,USD,240149,EX,FT,United States,L,United States,100,"SQL, GCP, Azure, NLP",PhD,15,Government,2024-10-28,2024-12-15,1242,5.9,Machine Intelligence Group +AI13620,Data Analyst,97727,EUR,83068,MI,PT,Austria,L,Austria,50,"Deep Learning, SQL, Data Visualization, PyTorch",Associate,3,Gaming,2025-04-25,2025-06-22,1949,9.7,Autonomous Tech +AI13621,Robotics Engineer,81590,CAD,101988,MI,CT,Canada,S,Netherlands,50,"Hadoop, Kubernetes, Mathematics",Associate,3,Government,2024-09-05,2024-11-03,1546,7.3,Cloud AI Solutions +AI13622,NLP Engineer,80741,AUD,109000,MI,FT,Australia,M,Colombia,100,"SQL, Python, MLOps",Bachelor,2,Technology,2024-08-29,2024-11-08,2250,7.9,DeepTech Ventures +AI13623,Head of AI,207242,USD,207242,EX,PT,Israel,S,Argentina,50,"Linux, Hadoop, Tableau",Associate,14,Manufacturing,2024-11-11,2024-12-18,2227,5.1,Cloud AI Solutions +AI13624,Principal Data Scientist,162118,USD,162118,EX,FL,Israel,S,Israel,100,"AWS, Docker, Mathematics",Associate,13,Telecommunications,2024-03-18,2024-05-07,1676,8.7,Autonomous Tech +AI13625,AI Software Engineer,95549,USD,95549,MI,FL,Israel,L,Israel,0,"Java, AWS, NLP, Tableau, Azure",Master,2,Gaming,2025-04-05,2025-06-14,1519,6.8,Advanced Robotics +AI13626,Autonomous Systems Engineer,22852,USD,22852,EN,PT,China,S,China,50,"Java, Spark, TensorFlow, Kubernetes",Master,0,Transportation,2024-11-11,2024-12-15,2127,7.1,Digital Transformation LLC +AI13627,Robotics Engineer,99707,USD,99707,EN,FT,United States,L,United States,0,"NLP, GCP, AWS, Git, Hadoop",Bachelor,1,Transportation,2024-03-02,2024-04-20,1827,5.9,Smart Analytics +AI13628,Autonomous Systems Engineer,82711,USD,82711,EN,FL,Finland,L,Finland,100,"Kubernetes, Python, Statistics, GCP, Java",Associate,1,Telecommunications,2024-03-23,2024-05-25,832,5.9,Autonomous Tech +AI13629,Data Analyst,114447,USD,114447,MI,PT,Norway,M,Norway,100,"Tableau, Linux, AWS",Associate,3,Transportation,2024-01-24,2024-02-27,2294,6.1,Predictive Systems +AI13630,Principal Data Scientist,80841,CAD,101051,MI,FL,Canada,S,Canada,50,"Hadoop, Git, MLOps, Statistics",Bachelor,3,Gaming,2025-01-10,2025-02-08,1943,7.7,DataVision Ltd +AI13631,Data Scientist,75011,USD,75011,EN,PT,Israel,L,Israel,100,"Tableau, Statistics, Computer Vision",Master,0,Transportation,2025-02-10,2025-03-21,1721,8.4,Neural Networks Co +AI13632,AI Specialist,48013,USD,48013,EX,PT,India,S,India,0,"TensorFlow, Scala, PyTorch, Statistics, Data Visualization",Bachelor,10,Healthcare,2024-03-05,2024-05-06,965,6.6,Cloud AI Solutions +AI13633,Head of AI,210553,EUR,178970,EX,CT,Germany,L,Germany,50,"Kubernetes, Scala, Data Visualization, Hadoop",Master,19,Consulting,2025-04-13,2025-05-07,956,7,Cloud AI Solutions +AI13634,Principal Data Scientist,68238,EUR,58002,EN,FT,Germany,S,Austria,100,"Kubernetes, Hadoop, PyTorch, AWS",Associate,0,Finance,2024-11-05,2025-01-16,1327,7.8,TechCorp Inc +AI13635,Autonomous Systems Engineer,211620,CHF,190458,SE,CT,Switzerland,M,Switzerland,50,"Java, Scala, SQL, Git",Bachelor,6,Telecommunications,2025-02-22,2025-04-19,709,8.4,Cloud AI Solutions +AI13636,AI Research Scientist,200684,USD,200684,EX,PT,Sweden,M,Sweden,50,"SQL, AWS, Hadoop",Associate,19,Telecommunications,2025-04-06,2025-06-08,1175,7.6,AI Innovations +AI13637,AI Software Engineer,91715,USD,91715,SE,PT,South Korea,S,Netherlands,100,"Tableau, Deep Learning, R, Python, TensorFlow",PhD,7,Education,2025-01-23,2025-02-06,1869,8.6,Neural Networks Co +AI13638,Principal Data Scientist,93185,JPY,10250350,EN,FL,Japan,L,Japan,50,"Python, AWS, Azure",Master,0,Technology,2025-04-13,2025-05-20,1885,9,AI Innovations +AI13639,Machine Learning Researcher,87268,USD,87268,EN,FT,Denmark,M,Denmark,100,"Azure, Java, SQL",Associate,1,Education,2025-01-31,2025-02-22,2387,6.9,Algorithmic Solutions +AI13640,Data Scientist,267540,CHF,240786,EX,PT,Switzerland,S,Switzerland,50,"MLOps, Tableau, Scala",Master,11,Telecommunications,2024-11-06,2024-11-29,2360,7.7,Autonomous Tech +AI13641,Data Engineer,126759,USD,126759,SE,FL,Sweden,M,Sweden,50,"Python, Docker, Data Visualization, PyTorch",Bachelor,7,Media,2024-02-08,2024-03-09,1723,6,Cognitive Computing +AI13642,Data Scientist,129742,USD,129742,SE,FT,Ireland,L,Ireland,50,"Linux, Mathematics, MLOps",Bachelor,9,Healthcare,2024-07-20,2024-08-23,1374,7.2,Digital Transformation LLC +AI13643,NLP Engineer,78149,GBP,58612,EN,FL,United Kingdom,M,United Kingdom,0,"R, AWS, TensorFlow, Mathematics",Master,0,Gaming,2024-04-24,2024-05-13,897,7.2,Cloud AI Solutions +AI13644,AI Consultant,84880,USD,84880,MI,FL,Norway,S,Norway,50,"SQL, GCP, NLP",Master,3,Finance,2024-03-22,2024-04-08,1412,8.2,Neural Networks Co +AI13645,Data Scientist,106468,USD,106468,EX,CT,China,L,China,50,"Linux, Docker, Tableau, Scala, GCP",Master,17,Finance,2024-03-09,2024-04-05,1740,9.2,DataVision Ltd +AI13646,AI Specialist,77051,USD,77051,EN,PT,Denmark,L,Mexico,50,"Hadoop, Docker, Kubernetes",PhD,1,Telecommunications,2024-12-28,2025-02-07,2495,6.8,TechCorp Inc +AI13647,AI Consultant,54386,AUD,73421,EN,FT,Australia,M,Australia,0,"PyTorch, TensorFlow, Git",Bachelor,1,Technology,2024-12-10,2025-01-19,561,9.2,Neural Networks Co +AI13648,Research Scientist,241352,SGD,313758,EX,CT,Singapore,L,Singapore,50,"Mathematics, Azure, Hadoop",Associate,12,Healthcare,2024-10-10,2024-11-02,1924,8.7,Algorithmic Solutions +AI13649,Computer Vision Engineer,122023,USD,122023,MI,CT,Denmark,S,Denmark,100,"Kubernetes, NLP, R, PyTorch, Docker",PhD,3,Finance,2024-10-11,2024-11-08,955,5.7,Neural Networks Co +AI13650,Computer Vision Engineer,69776,SGD,90709,MI,FT,Singapore,S,Ireland,0,"Java, Tableau, Hadoop, Scala, AWS",Master,4,Energy,2024-01-09,2024-03-11,602,8.3,DeepTech Ventures +AI13651,ML Ops Engineer,150163,USD,150163,SE,FL,Ireland,L,Ireland,100,"Kubernetes, Deep Learning, Azure",PhD,5,Transportation,2024-10-16,2024-12-22,868,7.7,Autonomous Tech +AI13652,Data Analyst,46451,CAD,58064,EN,CT,Canada,S,Canada,50,"NLP, Kubernetes, R, Java",Master,0,Manufacturing,2024-10-29,2024-11-15,718,8.2,Cognitive Computing +AI13653,Data Scientist,78071,AUD,105396,MI,PT,Australia,S,Australia,50,"Spark, Tableau, Java, Python",Associate,4,Consulting,2025-02-15,2025-04-21,648,9.9,Advanced Robotics +AI13654,Machine Learning Engineer,141974,USD,141974,SE,FL,South Korea,L,South Korea,100,"Spark, Tableau, PyTorch, Deep Learning, GCP",Associate,8,Finance,2024-03-15,2024-04-14,2050,8.6,Digital Transformation LLC +AI13655,Robotics Engineer,101301,JPY,11143110,MI,FT,Japan,L,Japan,50,"Tableau, SQL, GCP, Java",Bachelor,2,Automotive,2024-02-08,2024-02-27,1956,9.6,Cloud AI Solutions +AI13656,AI Architect,147615,USD,147615,SE,FL,Israel,L,Israel,100,"Docker, SQL, Kubernetes",Master,7,Healthcare,2024-12-01,2025-01-24,2115,5.3,Algorithmic Solutions +AI13657,Robotics Engineer,59247,USD,59247,EX,FT,India,M,Italy,100,"TensorFlow, PyTorch, Deep Learning",Associate,12,Gaming,2024-01-27,2024-03-09,1303,8.7,Digital Transformation LLC +AI13658,Computer Vision Engineer,68387,AUD,92322,EN,CT,Australia,S,Australia,0,"Scala, Git, SQL, Python, R",Associate,1,Real Estate,2025-03-29,2025-05-15,2393,9.4,Cognitive Computing +AI13659,Machine Learning Engineer,94339,SGD,122641,EN,FL,Singapore,L,Malaysia,50,"Git, SQL, GCP, Mathematics",Bachelor,1,Education,2024-02-27,2024-04-21,1382,6.9,Machine Intelligence Group +AI13660,Machine Learning Engineer,246518,SGD,320473,EX,FL,Singapore,L,Mexico,0,"Python, Kubernetes, Azure",Master,18,Consulting,2024-03-31,2024-05-07,594,8.7,TechCorp Inc +AI13661,Data Analyst,102322,USD,102322,MI,FT,Finland,M,Finland,100,"R, PyTorch, TensorFlow, Git",Master,2,Transportation,2024-03-19,2024-04-17,1537,9,Algorithmic Solutions +AI13662,Autonomous Systems Engineer,209756,USD,209756,EX,FT,United States,M,United States,100,"Tableau, Java, Kubernetes",PhD,10,Healthcare,2025-03-31,2025-05-19,1441,6.2,Advanced Robotics +AI13663,Data Scientist,130034,SGD,169044,SE,FT,Singapore,M,South Korea,100,"SQL, Linux, Git, Deep Learning, Statistics",Master,6,Gaming,2024-12-19,2025-02-15,1705,6.3,Predictive Systems +AI13664,AI Specialist,112402,EUR,95542,SE,PT,Germany,M,Germany,0,"Git, Python, Scala",Associate,7,Gaming,2024-12-30,2025-02-04,1356,5.6,AI Innovations +AI13665,Data Analyst,111935,USD,111935,SE,FL,Sweden,M,Sweden,50,"Deep Learning, Linux, Data Visualization, Statistics, Tableau",Bachelor,7,Real Estate,2024-10-26,2024-12-26,1616,7.5,AI Innovations +AI13666,ML Ops Engineer,210290,USD,210290,EX,PT,Finland,S,Finland,0,"Hadoop, Scala, Spark, Computer Vision",Bachelor,17,Real Estate,2024-04-15,2024-05-27,1321,6.2,Future Systems +AI13667,Data Engineer,156011,USD,156011,SE,PT,Norway,S,Norway,0,"Spark, Linux, Computer Vision, Python, Azure",Associate,9,Manufacturing,2024-09-28,2024-11-18,1382,8.2,AI Innovations +AI13668,Machine Learning Researcher,72835,USD,72835,EN,PT,United States,S,Italy,50,"Java, Scala, Deep Learning, Docker",Master,1,Healthcare,2024-01-03,2024-03-10,1536,9,Advanced Robotics +AI13669,Data Analyst,182390,USD,182390,SE,FL,Norway,M,Japan,50,"Tableau, Data Visualization, Azure, Docker",Associate,7,Real Estate,2024-04-23,2024-06-03,1277,5.7,Predictive Systems +AI13670,Machine Learning Researcher,69023,CAD,86279,EN,FL,Canada,M,Canada,50,"Scala, Python, Azure",Bachelor,1,Energy,2024-10-10,2024-11-03,2005,9.1,Cloud AI Solutions +AI13671,NLP Engineer,92468,GBP,69351,MI,FL,United Kingdom,M,United Kingdom,50,"Spark, Java, Data Visualization, GCP",PhD,3,Automotive,2024-06-13,2024-06-28,1890,8.1,Smart Analytics +AI13672,Research Scientist,65251,USD,65251,EN,CT,Israel,L,Israel,50,"PyTorch, Deep Learning, Spark",Master,0,Real Estate,2025-01-07,2025-02-15,651,5.6,Cognitive Computing +AI13673,AI Specialist,217187,USD,217187,EX,FL,Ireland,M,Ireland,100,"R, PyTorch, Data Visualization",Associate,15,Education,2024-03-17,2024-04-08,1446,8.3,Smart Analytics +AI13674,Autonomous Systems Engineer,54380,EUR,46223,EN,PT,Germany,S,Germany,0,"Linux, Python, Git, Statistics",Master,0,Finance,2025-01-01,2025-02-03,1960,9.6,DataVision Ltd +AI13675,AI Consultant,295717,EUR,251359,EX,CT,Netherlands,L,Netherlands,100,"Java, Data Visualization, Spark",Master,11,Finance,2024-12-19,2025-01-16,1535,9,Algorithmic Solutions +AI13676,NLP Engineer,122502,AUD,165378,SE,FT,Australia,M,Hungary,100,"NLP, TensorFlow, Hadoop",Associate,6,Consulting,2025-04-24,2025-05-09,2498,6.8,Algorithmic Solutions +AI13677,Deep Learning Engineer,109823,USD,109823,MI,CT,Sweden,L,Sweden,100,"Hadoop, AWS, Java, Statistics, Azure",Bachelor,3,Energy,2024-05-16,2024-07-01,976,8.4,Smart Analytics +AI13678,Autonomous Systems Engineer,82666,USD,82666,EN,FT,Finland,L,Finland,100,"Spark, Python, Azure, Java",PhD,0,Automotive,2025-04-08,2025-05-07,1809,7.3,Machine Intelligence Group +AI13679,Robotics Engineer,69269,GBP,51952,EN,FT,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python, Data Visualization",Master,1,Retail,2024-10-19,2024-12-20,1443,7.5,Smart Analytics +AI13680,AI Specialist,193819,USD,193819,EX,PT,Sweden,S,Sweden,50,"Linux, TensorFlow, Git, Kubernetes",PhD,11,Finance,2025-04-28,2025-05-28,630,7.4,Machine Intelligence Group +AI13681,Head of AI,104297,SGD,135586,MI,PT,Singapore,M,Singapore,100,"Java, R, AWS, Computer Vision, Statistics",PhD,4,Manufacturing,2025-02-23,2025-03-28,1501,8.7,Algorithmic Solutions +AI13682,NLP Engineer,64787,EUR,55069,EN,FL,France,S,France,0,"Hadoop, MLOps, Docker, Linux, TensorFlow",PhD,1,Energy,2025-02-08,2025-04-20,2254,7.7,DeepTech Ventures +AI13683,AI Architect,321641,USD,321641,EX,FT,Norway,M,Norway,100,"Git, TensorFlow, Scala",Bachelor,11,Education,2025-04-14,2025-06-22,1672,7.7,AI Innovations +AI13684,Computer Vision Engineer,55628,SGD,72316,EN,CT,Singapore,M,Turkey,100,"Azure, Java, R, Computer Vision, Hadoop",PhD,1,Healthcare,2025-04-18,2025-06-28,1517,5.8,Future Systems +AI13685,AI Architect,45870,USD,45870,MI,FT,China,S,Colombia,100,"AWS, Java, R, MLOps, SQL",Associate,3,Finance,2024-09-25,2024-11-27,530,5.4,Quantum Computing Inc +AI13686,AI Architect,152656,USD,152656,MI,FT,Denmark,L,Denmark,100,"MLOps, Kubernetes, PyTorch",Bachelor,3,Education,2024-03-03,2024-05-07,1022,7.1,Future Systems +AI13687,AI Software Engineer,26656,USD,26656,MI,FT,India,M,India,100,"Java, R, Data Visualization, Scala",Master,2,Retail,2025-01-27,2025-03-22,717,9.5,Advanced Robotics +AI13688,Data Analyst,146759,USD,146759,SE,PT,United States,L,United Kingdom,50,"R, Spark, Kubernetes, Python, AWS",Associate,7,Government,2024-08-10,2024-09-20,1615,8.4,TechCorp Inc +AI13689,AI Specialist,44241,CAD,55301,EN,FL,Canada,S,Canada,0,"Python, TensorFlow, PyTorch",Master,0,Finance,2025-01-01,2025-02-28,1287,6.1,TechCorp Inc +AI13690,Principal Data Scientist,124494,CHF,112045,EN,CT,Switzerland,L,Switzerland,50,"Linux, Hadoop, SQL, PyTorch, GCP",Bachelor,1,Media,2024-02-14,2024-03-12,1057,7.4,Cognitive Computing +AI13691,AI Specialist,83827,USD,83827,EX,PT,India,M,India,100,"Azure, Linux, Java, SQL",Bachelor,18,Automotive,2024-11-17,2024-12-01,1223,6.5,Advanced Robotics +AI13692,Machine Learning Researcher,133335,EUR,113335,SE,FL,Germany,M,Germany,100,"MLOps, Kubernetes, PyTorch, Statistics, SQL",PhD,8,Real Estate,2024-08-10,2024-09-29,1968,8.7,Future Systems +AI13693,Autonomous Systems Engineer,161531,EUR,137301,SE,FL,France,L,France,0,"Hadoop, Python, SQL, NLP",PhD,7,Retail,2024-12-06,2025-01-24,2300,5.5,Future Systems +AI13694,Deep Learning Engineer,80194,USD,80194,EN,FT,Ireland,M,Ireland,0,"SQL, R, Data Visualization",Master,0,Consulting,2024-12-28,2025-02-11,924,5.9,DataVision Ltd +AI13695,Data Scientist,181350,GBP,136013,EX,PT,United Kingdom,M,United Kingdom,0,"Tableau, Scala, NLP, TensorFlow",Bachelor,18,Consulting,2024-11-25,2025-01-11,2264,6.7,Predictive Systems +AI13696,AI Software Engineer,102985,USD,102985,MI,FT,Finland,M,Finland,50,"SQL, NLP, Git",PhD,3,Transportation,2025-02-20,2025-03-30,1591,8.7,Quantum Computing Inc +AI13697,AI Consultant,70147,USD,70147,EN,FT,Norway,M,Norway,0,"SQL, Scala, Git",Master,0,Education,2024-03-25,2024-04-30,598,9.5,Algorithmic Solutions +AI13698,Machine Learning Researcher,95188,SGD,123744,MI,PT,Singapore,L,Singapore,0,"Azure, PyTorch, Statistics, Hadoop, Java",Associate,3,Media,2024-12-04,2024-12-22,1227,9.4,Quantum Computing Inc +AI13699,Robotics Engineer,274623,USD,274623,EX,FL,United States,L,United States,50,"Python, PyTorch, Git, Azure, Java",Associate,14,Government,2024-02-08,2024-03-11,2135,6.4,Quantum Computing Inc +AI13700,Robotics Engineer,79001,EUR,67151,EN,CT,Germany,L,Germany,50,"Python, TensorFlow, NLP, Java",Master,1,Real Estate,2024-06-01,2024-07-07,1648,7.8,Digital Transformation LLC +AI13701,Autonomous Systems Engineer,133645,AUD,180421,SE,FL,Australia,M,Estonia,50,"Tableau, AWS, NLP, Docker",Bachelor,8,Education,2025-03-18,2025-05-26,706,9.9,AI Innovations +AI13702,Machine Learning Researcher,63052,USD,63052,SE,CT,China,S,China,0,"Computer Vision, Tableau, Data Visualization, NLP",Associate,5,Manufacturing,2024-08-12,2024-08-29,1774,6.5,Quantum Computing Inc +AI13703,AI Research Scientist,150556,AUD,203251,SE,PT,Australia,M,Australia,100,"SQL, Hadoop, Computer Vision, R",Associate,6,Technology,2024-11-02,2024-12-24,1164,8.4,Advanced Robotics +AI13704,AI Specialist,44619,USD,44619,SE,FL,China,S,China,50,"Java, TensorFlow, Git, AWS",PhD,6,Automotive,2025-04-15,2025-05-09,1572,7.6,AI Innovations +AI13705,Autonomous Systems Engineer,243017,USD,243017,EX,CT,Israel,L,Israel,0,"Scala, Data Visualization, Kubernetes, Computer Vision, Spark",Associate,12,Gaming,2024-03-09,2024-03-28,2181,8.1,Predictive Systems +AI13706,AI Specialist,201305,EUR,171109,EX,FT,Germany,L,Germany,0,"GCP, Git, PyTorch, SQL, Mathematics",Master,15,Automotive,2024-04-26,2024-06-08,1686,9.2,Quantum Computing Inc +AI13707,AI Research Scientist,94123,SGD,122360,EN,FL,Singapore,L,Singapore,50,"Java, SQL, Azure, MLOps, PyTorch",Master,0,Media,2024-01-05,2024-03-12,1613,5.4,Digital Transformation LLC +AI13708,Data Engineer,52016,GBP,39012,EN,FT,United Kingdom,S,Switzerland,100,"Azure, Kubernetes, Docker, AWS, Scala",PhD,0,Manufacturing,2024-10-14,2024-11-09,2014,6.2,Predictive Systems +AI13709,Computer Vision Engineer,48238,EUR,41002,EN,PT,France,S,Ireland,100,"Java, PyTorch, GCP",Master,0,Manufacturing,2024-03-23,2024-05-24,710,5.1,DataVision Ltd +AI13710,Data Analyst,189852,USD,189852,EX,CT,Ireland,M,Ireland,100,"Azure, Spark, SQL, Python",Master,12,Automotive,2024-07-21,2024-09-03,2343,8.2,AI Innovations +AI13711,Autonomous Systems Engineer,71233,CAD,89041,MI,FT,Canada,M,Vietnam,0,"Kubernetes, Computer Vision, Data Visualization, Azure, R",PhD,4,Transportation,2024-03-05,2024-05-04,979,8,Digital Transformation LLC +AI13712,Research Scientist,152809,EUR,129888,SE,PT,Germany,M,Germany,50,"Git, Java, R, NLP, Kubernetes",Associate,8,Real Estate,2025-01-17,2025-02-07,855,9.3,DataVision Ltd +AI13713,Principal Data Scientist,79844,USD,79844,MI,FL,Sweden,M,Sweden,50,"GCP, TensorFlow, Data Visualization, PyTorch, MLOps",Master,4,Retail,2024-11-04,2024-12-22,2002,5.7,DeepTech Ventures +AI13714,AI Specialist,90766,USD,90766,EN,CT,Sweden,L,Sweden,0,"Hadoop, Git, Spark, TensorFlow, GCP",PhD,1,Retail,2024-02-19,2024-04-22,2059,7.7,Neural Networks Co +AI13715,AI Specialist,94607,EUR,80416,MI,CT,France,M,France,50,"Linux, Spark, Azure",Associate,3,Education,2024-10-22,2024-12-14,1778,8.7,Smart Analytics +AI13716,Machine Learning Engineer,155537,JPY,17109070,SE,FT,Japan,L,Ireland,50,"Spark, Kubernetes, SQL, NLP",PhD,7,Gaming,2024-01-26,2024-02-14,1465,9.6,Algorithmic Solutions +AI13717,Principal Data Scientist,84059,GBP,63044,MI,FL,United Kingdom,M,Indonesia,0,"Spark, Python, TensorFlow, Hadoop",Bachelor,3,Media,2024-10-18,2024-12-03,1930,6.4,Smart Analytics +AI13718,Head of AI,214035,USD,214035,EX,FL,Israel,S,Israel,50,"Linux, MLOps, Hadoop, GCP, Python",PhD,12,Retail,2024-02-02,2024-02-22,1111,10,AI Innovations +AI13719,Machine Learning Engineer,62794,USD,62794,SE,FT,China,M,China,100,"Hadoop, Git, Docker, NLP",Associate,9,Telecommunications,2024-09-09,2024-09-24,858,10,Autonomous Tech +AI13720,Principal Data Scientist,78666,USD,78666,MI,FT,Sweden,S,Sweden,0,"Git, SQL, Python, R",Master,4,Automotive,2025-04-16,2025-05-18,1482,8.3,TechCorp Inc +AI13721,Head of AI,73536,JPY,8088960,EN,FT,Japan,M,Turkey,100,"Scala, Kubernetes, Java, PyTorch",PhD,0,Media,2024-08-15,2024-09-25,1805,8.9,Cloud AI Solutions +AI13722,Research Scientist,35544,USD,35544,MI,PT,China,M,Luxembourg,50,"Deep Learning, PyTorch, Java",Master,4,Education,2024-08-11,2024-10-22,1603,5.9,DeepTech Ventures +AI13723,AI Research Scientist,49579,USD,49579,EN,PT,South Korea,L,South Korea,50,"AWS, PyTorch, Scala, Linux",Associate,1,Automotive,2024-06-14,2024-08-20,2298,8.8,Digital Transformation LLC +AI13724,Data Engineer,37102,USD,37102,SE,PT,India,M,India,100,"Spark, Java, Git, Data Visualization, R",PhD,7,Finance,2024-07-23,2024-10-01,1467,5.6,Machine Intelligence Group +AI13725,Data Engineer,151791,CHF,136612,SE,FL,Switzerland,S,Switzerland,0,"Kubernetes, Mathematics, PyTorch, Spark",PhD,7,Media,2025-02-09,2025-04-23,1366,6.5,Cognitive Computing +AI13726,Head of AI,114945,USD,114945,SE,FT,Sweden,M,Sweden,100,"Computer Vision, Mathematics, NLP, PyTorch",Associate,7,Automotive,2025-02-01,2025-03-28,2374,9.5,AI Innovations +AI13727,Machine Learning Engineer,74998,CAD,93748,EN,FT,Canada,M,Canada,100,"Scala, Java, Docker",Associate,0,Transportation,2024-03-22,2024-05-02,1851,8.3,Digital Transformation LLC +AI13728,AI Software Engineer,119208,USD,119208,SE,FT,Israel,S,Israel,0,"Python, TensorFlow, Git",PhD,5,Gaming,2024-09-10,2024-11-12,762,6.6,Digital Transformation LLC +AI13729,Data Engineer,215124,USD,215124,EX,FL,Finland,M,Canada,100,"Data Visualization, Scala, AWS",Master,16,Manufacturing,2024-02-06,2024-02-26,626,8,Quantum Computing Inc +AI13730,Data Engineer,111381,JPY,12251910,SE,PT,Japan,M,Japan,50,"Scala, GCP, TensorFlow",PhD,6,Government,2024-01-05,2024-02-28,545,8.7,Future Systems +AI13731,AI Specialist,62659,EUR,53260,EN,FL,Germany,M,Germany,100,"Linux, Hadoop, Data Visualization, Python",PhD,0,Healthcare,2024-08-05,2024-09-19,1980,9.3,DeepTech Ventures +AI13732,Data Scientist,174509,EUR,148333,EX,PT,Austria,M,Austria,0,"Deep Learning, Hadoop, SQL",Associate,10,Manufacturing,2025-03-12,2025-04-12,1714,6.1,Cloud AI Solutions +AI13733,Principal Data Scientist,76295,USD,76295,SE,PT,China,L,China,0,"Python, SQL, AWS, Computer Vision",PhD,6,Real Estate,2024-09-30,2024-10-15,1025,6.9,TechCorp Inc +AI13734,Computer Vision Engineer,82190,CHF,73971,EN,CT,Switzerland,M,Malaysia,50,"Scala, Tableau, Python, Linux",Bachelor,1,Transportation,2024-06-27,2024-08-18,2364,5.3,Future Systems +AI13735,Data Scientist,60176,USD,60176,SE,FT,China,S,China,50,"R, Git, SQL",Bachelor,6,Finance,2024-07-30,2024-08-19,1300,9.1,Smart Analytics +AI13736,Computer Vision Engineer,91041,USD,91041,SE,FL,South Korea,S,Ukraine,100,"Computer Vision, Kubernetes, Git, Scala, Azure",Bachelor,8,Consulting,2024-10-06,2024-11-24,913,6.3,Quantum Computing Inc +AI13737,Robotics Engineer,51392,USD,51392,MI,FT,China,L,China,100,"Deep Learning, Hadoop, GCP",Master,2,Government,2024-01-03,2024-03-04,1175,8.8,Algorithmic Solutions +AI13738,Autonomous Systems Engineer,291795,USD,291795,EX,PT,Denmark,M,Denmark,50,"Scala, Statistics, AWS",Associate,13,Education,2025-03-18,2025-04-02,1768,7.8,Smart Analytics +AI13739,Head of AI,95963,USD,95963,EX,FL,India,L,India,0,"Kubernetes, Tableau, Hadoop",Bachelor,16,Energy,2024-10-21,2025-01-02,652,6.2,DeepTech Ventures +AI13740,AI Product Manager,48317,USD,48317,EN,FT,Ireland,S,Indonesia,50,"Python, TensorFlow, Mathematics",PhD,1,Media,2025-02-22,2025-04-20,1696,9.4,Quantum Computing Inc +AI13741,Machine Learning Researcher,66508,USD,66508,EN,FL,United States,S,Australia,100,"Docker, Python, PyTorch, Linux",PhD,1,Manufacturing,2025-02-04,2025-03-17,1858,6.4,Future Systems +AI13742,AI Architect,160872,EUR,136741,SE,FT,Germany,L,Israel,0,"AWS, Scala, SQL",Bachelor,5,Manufacturing,2024-02-02,2024-04-14,769,9.8,Cognitive Computing +AI13743,Autonomous Systems Engineer,170265,EUR,144725,EX,CT,Netherlands,S,Netherlands,0,"PyTorch, R, Deep Learning, Mathematics, NLP",PhD,14,Healthcare,2024-05-10,2024-07-21,2311,8.8,Algorithmic Solutions +AI13744,Computer Vision Engineer,67378,AUD,90960,EN,FT,Australia,M,Portugal,100,"Mathematics, PyTorch, Deep Learning, Data Visualization",Associate,0,Healthcare,2024-05-19,2024-07-26,2047,6.8,Digital Transformation LLC +AI13745,AI Consultant,201053,EUR,170895,EX,FL,Germany,L,Germany,0,"TensorFlow, Scala, SQL",Master,14,Gaming,2024-02-13,2024-04-08,793,5.1,Quantum Computing Inc +AI13746,Autonomous Systems Engineer,61127,EUR,51958,EN,FT,Germany,M,Germany,100,"Python, Azure, Tableau, MLOps, Computer Vision",Bachelor,0,Media,2025-04-04,2025-05-20,736,8.2,Predictive Systems +AI13747,Head of AI,132422,USD,132422,SE,CT,Ireland,M,Ireland,50,"Data Visualization, Python, Azure, Linux, R",Associate,7,Manufacturing,2024-12-16,2025-01-23,1166,9.4,Autonomous Tech +AI13748,Computer Vision Engineer,99521,EUR,84593,MI,CT,Netherlands,L,Netherlands,0,"Spark, SQL, Tableau, NLP, GCP",Master,3,Retail,2024-03-01,2024-04-05,1557,5.4,Advanced Robotics +AI13749,Data Engineer,187640,EUR,159494,EX,FT,France,M,United States,0,"MLOps, AWS, R",Associate,12,Manufacturing,2025-02-14,2025-03-09,1734,8.2,Cognitive Computing +AI13750,ML Ops Engineer,79512,CHF,71561,EN,FT,Switzerland,M,Switzerland,50,"SQL, GCP, Mathematics",Bachelor,1,Gaming,2024-11-03,2025-01-04,1933,6.2,Machine Intelligence Group +AI13751,ML Ops Engineer,76070,USD,76070,EN,FT,United States,M,United States,50,"SQL, Statistics, PyTorch, Spark, Kubernetes",Master,0,Energy,2025-04-30,2025-07-09,502,9.2,TechCorp Inc +AI13752,Research Scientist,214448,CHF,193003,SE,PT,Switzerland,M,Germany,0,"MLOps, PyTorch, TensorFlow, Docker",Master,6,Retail,2024-04-27,2024-06-01,1168,8.2,Smart Analytics +AI13753,ML Ops Engineer,197364,SGD,256573,EX,PT,Singapore,S,Singapore,100,"Linux, Docker, GCP, Hadoop, R",Master,13,Retail,2024-05-20,2024-07-04,689,9.1,Autonomous Tech +AI13754,Deep Learning Engineer,106426,EUR,90462,SE,CT,Netherlands,S,Kenya,100,"AWS, Kubernetes, Computer Vision, Python, Data Visualization",Associate,6,Energy,2024-08-26,2024-09-29,978,5.9,Cognitive Computing +AI13755,Computer Vision Engineer,64010,EUR,54409,MI,PT,France,S,France,100,"Data Visualization, PyTorch, Python, Azure, Docker",Master,3,Energy,2024-07-03,2024-09-10,1583,7.7,Predictive Systems +AI13756,AI Software Engineer,208320,USD,208320,EX,PT,Israel,L,Vietnam,50,"Kubernetes, Linux, TensorFlow",Bachelor,19,Energy,2024-10-06,2024-11-06,1807,6,Future Systems +AI13757,AI Product Manager,93335,USD,93335,MI,PT,Ireland,S,Ireland,0,"PyTorch, Kubernetes, Java, Deep Learning, Spark",Bachelor,4,Gaming,2025-04-08,2025-05-03,1110,5.6,Digital Transformation LLC +AI13758,AI Consultant,102368,USD,102368,SE,FT,Israel,S,Israel,0,"TensorFlow, Python, Data Visualization, Git, Hadoop",PhD,7,Gaming,2024-02-18,2024-04-18,1249,7.6,AI Innovations +AI13759,AI Product Manager,64929,EUR,55190,EN,PT,Netherlands,S,Netherlands,50,"Git, Java, Hadoop, SQL, Spark",Associate,0,Consulting,2025-01-18,2025-03-09,1113,5.9,AI Innovations +AI13760,AI Software Engineer,206784,USD,206784,EX,FL,Sweden,M,Sweden,100,"AWS, Linux, Scala, Statistics",Bachelor,17,Transportation,2024-04-06,2024-06-03,2115,6.2,DataVision Ltd +AI13761,Research Scientist,203979,USD,203979,EX,FT,South Korea,L,Latvia,100,"Git, Spark, MLOps, Docker",PhD,14,Real Estate,2024-03-30,2024-05-25,1655,7,Digital Transformation LLC +AI13762,Research Scientist,124710,CHF,112239,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, PyTorch, SQL, Deep Learning",PhD,2,Technology,2024-01-03,2024-02-05,1509,5.3,Cloud AI Solutions +AI13763,AI Software Engineer,60824,USD,60824,EN,FT,South Korea,L,Mexico,0,"PyTorch, Tableau, Deep Learning",Master,1,Automotive,2025-04-06,2025-06-12,1468,7,AI Innovations +AI13764,Robotics Engineer,133068,EUR,113108,EX,FT,France,S,France,0,"Hadoop, NLP, Mathematics, GCP",Associate,13,Finance,2024-08-25,2024-09-28,1755,7,Quantum Computing Inc +AI13765,Data Scientist,122346,USD,122346,SE,PT,Denmark,S,Chile,0,"Java, Kubernetes, GCP, SQL",Master,6,Gaming,2025-04-23,2025-06-25,1865,9.7,Future Systems +AI13766,Principal Data Scientist,180133,EUR,153113,EX,FT,Netherlands,L,Netherlands,100,"Python, Git, Kubernetes",Bachelor,14,Technology,2024-01-11,2024-03-01,1372,5.9,AI Innovations +AI13767,AI Product Manager,79220,USD,79220,MI,FT,Israel,L,Spain,0,"Mathematics, Kubernetes, Scala, Spark, TensorFlow",Associate,3,Transportation,2024-02-20,2024-03-12,2424,7.9,Algorithmic Solutions +AI13768,AI Research Scientist,129587,USD,129587,SE,FT,Israel,L,Israel,0,"AWS, Java, TensorFlow",Master,5,Consulting,2024-11-02,2025-01-11,2071,6.8,Cognitive Computing +AI13769,NLP Engineer,58088,USD,58088,EN,FT,South Korea,S,South Korea,0,"Hadoop, Computer Vision, Azure",Master,1,Transportation,2024-06-26,2024-07-22,1400,8.5,Machine Intelligence Group +AI13770,Computer Vision Engineer,202346,USD,202346,EX,CT,Norway,M,Spain,0,"Linux, NLP, Mathematics, Tableau, Spark",Bachelor,12,Technology,2024-03-18,2024-04-29,2120,8.8,Autonomous Tech +AI13771,Data Scientist,242484,USD,242484,EX,PT,Israel,L,Israel,100,"Computer Vision, PyTorch, Deep Learning, TensorFlow, MLOps",PhD,19,Government,2024-06-12,2024-07-02,938,9.3,AI Innovations +AI13772,AI Consultant,89975,GBP,67481,EN,FL,United Kingdom,L,United Kingdom,0,"SQL, Kubernetes, TensorFlow",Bachelor,1,Gaming,2024-11-05,2025-01-16,2206,8.6,TechCorp Inc +AI13773,NLP Engineer,89837,GBP,67378,MI,FL,United Kingdom,M,Finland,100,"NLP, Java, Data Visualization, Python, Deep Learning",Master,3,Energy,2024-10-08,2024-11-25,1152,8.9,Quantum Computing Inc +AI13774,NLP Engineer,218325,EUR,185576,EX,FT,Germany,M,Germany,100,"NLP, Scala, Git",Master,15,Manufacturing,2024-04-01,2024-06-11,2033,5.6,TechCorp Inc +AI13775,Robotics Engineer,75754,EUR,64391,EN,PT,Germany,M,Germany,100,"Git, Docker, Azure, GCP, Java",Bachelor,1,Government,2024-05-24,2024-08-03,1675,8.8,Future Systems +AI13776,Machine Learning Engineer,117509,EUR,99883,MI,FL,Austria,L,Australia,100,"Java, R, MLOps, Linux",Associate,4,Education,2024-04-20,2024-06-04,1885,7.8,Cloud AI Solutions +AI13777,Data Scientist,84791,USD,84791,EX,FT,India,M,Poland,0,"Python, Java, NLP, GCP",Bachelor,13,Retail,2024-07-03,2024-08-18,925,9.1,Predictive Systems +AI13778,Machine Learning Engineer,55644,USD,55644,EN,FL,South Korea,M,South Korea,100,"Statistics, Kubernetes, R, Linux",PhD,0,Education,2024-01-17,2024-03-23,800,7.5,Advanced Robotics +AI13779,Data Scientist,32651,USD,32651,MI,PT,India,L,India,50,"Computer Vision, NLP, Data Visualization, Python",Bachelor,3,Technology,2024-10-25,2024-12-28,1578,5.3,Neural Networks Co +AI13780,AI Software Engineer,207687,EUR,176534,EX,FT,Germany,M,Israel,50,"Python, Mathematics, Kubernetes",Bachelor,17,Finance,2024-04-19,2024-06-03,707,6.2,Cognitive Computing +AI13781,Machine Learning Engineer,251818,GBP,188864,EX,FT,United Kingdom,L,Latvia,100,"Deep Learning, Linux, Tableau, AWS",PhD,12,Telecommunications,2025-03-18,2025-05-13,775,6.7,Cognitive Computing +AI13782,Computer Vision Engineer,117307,USD,117307,MI,FL,Denmark,S,Denmark,0,"Git, Data Visualization, PyTorch, NLP, Java",PhD,4,Media,2024-08-30,2024-09-29,1371,7.6,Cloud AI Solutions +AI13783,Data Analyst,67912,JPY,7470320,EN,FT,Japan,S,Japan,0,"Scala, SQL, AWS, Docker",Master,0,Technology,2025-04-10,2025-05-14,2390,6,DataVision Ltd +AI13784,Data Engineer,221812,JPY,24399320,EX,FT,Japan,M,Japan,50,"Python, PyTorch, R, Mathematics",Bachelor,19,Gaming,2025-01-21,2025-03-24,1380,7.3,Autonomous Tech +AI13785,NLP Engineer,67496,USD,67496,SE,FT,China,M,Malaysia,100,"R, Hadoop, Computer Vision, Python, Scala",PhD,6,Transportation,2024-11-19,2024-12-15,862,8.1,Cognitive Computing +AI13786,Robotics Engineer,75744,CAD,94680,EN,CT,Canada,M,Canada,0,"Java, Linux, Mathematics",PhD,1,Energy,2024-07-28,2024-09-08,1383,9.6,AI Innovations +AI13787,Deep Learning Engineer,78980,SGD,102674,MI,CT,Singapore,S,Singapore,0,"SQL, PyTorch, Azure, R",PhD,4,Finance,2025-03-17,2025-04-15,1515,7.6,Neural Networks Co +AI13788,AI Consultant,138142,EUR,117421,SE,FL,Netherlands,S,South Africa,0,"Java, MLOps, Scala",PhD,6,Healthcare,2025-04-13,2025-06-14,1676,7.4,Smart Analytics +AI13789,ML Ops Engineer,183795,USD,183795,EX,CT,Sweden,M,Sweden,50,"Spark, Python, Tableau, Azure, GCP",Master,16,Energy,2024-06-20,2024-08-15,858,5.3,Digital Transformation LLC +AI13790,Autonomous Systems Engineer,181750,JPY,19992500,SE,FL,Japan,L,Japan,0,"GCP, Linux, Kubernetes, Scala",PhD,6,Consulting,2024-07-23,2024-09-07,1634,6.1,TechCorp Inc +AI13791,Autonomous Systems Engineer,122129,AUD,164874,SE,FT,Australia,S,Romania,100,"Spark, Kubernetes, MLOps",Master,6,Healthcare,2024-03-14,2024-04-03,685,5.9,Machine Intelligence Group +AI13792,Data Engineer,227275,CHF,204548,EX,CT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Deep Learning, Scala",Bachelor,16,Government,2024-04-10,2024-06-22,768,7.7,Neural Networks Co +AI13793,Machine Learning Engineer,164834,USD,164834,SE,FT,Denmark,S,Czech Republic,50,"SQL, Scala, Hadoop",PhD,9,Education,2024-01-01,2024-01-16,1996,7.8,Cognitive Computing +AI13794,Data Scientist,86870,CHF,78183,EN,FT,Switzerland,M,Brazil,50,"Java, Kubernetes, NLP",PhD,1,Consulting,2024-11-12,2025-01-21,983,5.4,Algorithmic Solutions +AI13795,ML Ops Engineer,75356,USD,75356,EN,FL,Sweden,L,Sweden,50,"Docker, PyTorch, Data Visualization, Azure",Associate,1,Consulting,2024-05-20,2024-07-06,845,9.2,Autonomous Tech +AI13796,AI Research Scientist,70888,USD,70888,MI,FT,Finland,M,Finland,100,"Spark, Mathematics, SQL, AWS",Bachelor,4,Healthcare,2024-11-22,2024-12-10,2303,5.4,DataVision Ltd +AI13797,Research Scientist,85683,AUD,115672,MI,FL,Australia,L,Philippines,100,"Scala, Python, Java, Docker, Data Visualization",Associate,3,Finance,2024-09-13,2024-11-22,1167,9.8,Future Systems +AI13798,Robotics Engineer,136342,EUR,115891,SE,CT,Austria,M,Australia,100,"TensorFlow, Java, MLOps",Bachelor,5,Energy,2024-06-07,2024-07-11,922,8.1,AI Innovations +AI13799,Deep Learning Engineer,308880,CHF,277992,EX,FT,Switzerland,S,Switzerland,0,"Deep Learning, Docker, AWS, Mathematics, Statistics",Associate,15,Automotive,2024-05-29,2024-07-01,1649,9.1,Smart Analytics +AI13800,Machine Learning Engineer,163206,USD,163206,EX,PT,United States,S,United States,50,"PyTorch, Linux, Azure, Hadoop, Kubernetes",Bachelor,19,Energy,2024-02-20,2024-04-18,2044,6.7,Cloud AI Solutions +AI13801,Data Engineer,268727,AUD,362781,EX,FT,Australia,L,Australia,100,"Kubernetes, SQL, Data Visualization, Tableau, Spark",Bachelor,13,Technology,2025-04-26,2025-06-21,1933,6.1,DeepTech Ventures +AI13802,AI Consultant,158218,CAD,197773,EX,PT,Canada,L,Canada,50,"GCP, Python, Computer Vision, Kubernetes, MLOps",Master,19,Technology,2024-03-23,2024-04-08,1759,7,AI Innovations +AI13803,Robotics Engineer,90014,GBP,67511,MI,FT,United Kingdom,S,United Kingdom,0,"Hadoop, Deep Learning, Linux, Java",PhD,3,Real Estate,2024-03-17,2024-04-30,2183,8.9,Cloud AI Solutions +AI13804,Deep Learning Engineer,350601,CHF,315541,EX,FL,Switzerland,M,Switzerland,50,"R, Computer Vision, Hadoop",Bachelor,17,Finance,2024-10-24,2025-01-05,674,7.5,Autonomous Tech +AI13805,Machine Learning Researcher,162040,USD,162040,EX,PT,Denmark,S,Denmark,0,"Statistics, Linux, Deep Learning",Bachelor,11,Government,2024-07-06,2024-08-25,808,6.6,Autonomous Tech +AI13806,AI Research Scientist,195569,CAD,244461,EX,FT,Canada,L,Canada,0,"Scala, TensorFlow, Java, Docker, SQL",Bachelor,14,Telecommunications,2024-01-26,2024-02-21,1230,5,DataVision Ltd +AI13807,AI Consultant,65095,USD,65095,EX,PT,China,S,China,50,"GCP, Mathematics, Python",Associate,14,Consulting,2024-08-05,2024-10-06,1770,5.3,Cognitive Computing +AI13808,Principal Data Scientist,135374,AUD,182755,SE,PT,Australia,S,Estonia,0,"Git, NLP, Linux, Hadoop",Master,6,Manufacturing,2025-02-14,2025-04-10,1991,6.5,Neural Networks Co +AI13809,Machine Learning Engineer,114011,USD,114011,SE,CT,South Korea,M,South Korea,0,"Kubernetes, Python, Linux, NLP",Associate,7,Gaming,2024-11-07,2024-12-28,1423,8.7,Machine Intelligence Group +AI13810,Data Engineer,67057,EUR,56998,MI,FT,Austria,S,Mexico,100,"NLP, Python, Hadoop, Linux, Azure",Associate,2,Education,2024-06-16,2024-08-01,1249,9.3,DeepTech Ventures +AI13811,AI Specialist,59067,EUR,50207,EN,FL,France,L,France,50,"Linux, MLOps, Spark, Python, Git",Bachelor,1,Retail,2024-10-07,2024-10-31,1401,9.7,Quantum Computing Inc +AI13812,AI Architect,178851,USD,178851,SE,FL,United States,L,United States,0,"Python, TensorFlow, GCP, Tableau",Associate,8,Consulting,2024-09-14,2024-11-01,2079,5.4,Neural Networks Co +AI13813,Robotics Engineer,91673,USD,91673,EX,FL,China,S,Spain,0,"Docker, Java, Linux",Master,12,Automotive,2025-03-26,2025-05-18,896,9.3,Machine Intelligence Group +AI13814,Machine Learning Researcher,176800,USD,176800,SE,FL,Norway,M,Austria,100,"Linux, NLP, Scala, Java",Bachelor,6,Manufacturing,2024-06-17,2024-08-03,807,8.2,Cognitive Computing +AI13815,AI Product Manager,56994,GBP,42746,EN,FL,United Kingdom,S,Spain,50,"Docker, Statistics, Scala, Java",Associate,1,Technology,2024-07-07,2024-08-16,1916,5.5,DeepTech Ventures +AI13816,AI Consultant,152056,EUR,129248,SE,CT,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Linux, GCP",Bachelor,7,Automotive,2024-03-08,2024-03-23,711,6.9,Predictive Systems +AI13817,Principal Data Scientist,77428,SGD,100656,MI,PT,Singapore,S,Singapore,100,"PyTorch, Linux, SQL, Data Visualization",Master,4,Government,2024-09-09,2024-10-03,994,9.7,Machine Intelligence Group +AI13818,Computer Vision Engineer,232854,AUD,314353,EX,PT,Australia,M,Turkey,50,"TensorFlow, AWS, Python, NLP",Master,14,Gaming,2024-03-27,2024-05-23,2158,5.8,Autonomous Tech +AI13819,AI Software Engineer,198603,CHF,178743,SE,FL,Switzerland,L,Turkey,100,"Spark, Git, Docker",Master,7,Technology,2025-01-28,2025-04-07,1864,8.2,Cognitive Computing +AI13820,AI Specialist,119402,USD,119402,SE,CT,Finland,L,Finland,100,"GCP, Scala, SQL, Tableau",Master,7,Telecommunications,2024-10-25,2024-12-17,742,8.4,Future Systems +AI13821,Machine Learning Engineer,62647,AUD,84573,EN,FL,Australia,M,Australia,50,"Azure, Git, Computer Vision, Tableau, Docker",Associate,1,Transportation,2024-03-19,2024-04-06,2182,5.9,TechCorp Inc +AI13822,AI Software Engineer,226045,USD,226045,EX,FL,Denmark,S,Latvia,100,"Hadoop, Scala, PyTorch",Associate,17,Education,2024-05-28,2024-07-25,664,7.2,Neural Networks Co +AI13823,Head of AI,220671,AUD,297906,EX,FL,Australia,L,Australia,0,"Kubernetes, MLOps, Mathematics, SQL",Bachelor,10,Energy,2024-10-29,2024-12-11,900,6,TechCorp Inc +AI13824,Principal Data Scientist,88695,CHF,79826,EN,PT,Switzerland,S,Switzerland,50,"NLP, SQL, R, Computer Vision, Docker",Associate,0,Real Estate,2024-07-31,2024-09-18,1805,5.8,DataVision Ltd +AI13825,NLP Engineer,55419,USD,55419,SE,PT,India,L,India,0,"Kubernetes, Computer Vision, Spark, Python, Docker",PhD,9,Energy,2024-04-17,2024-06-28,2238,9.1,AI Innovations +AI13826,AI Architect,121382,USD,121382,MI,FT,Norway,M,Finland,100,"SQL, Scala, Git, Computer Vision",Associate,4,Technology,2024-02-20,2024-03-05,1592,9.6,Digital Transformation LLC +AI13827,AI Research Scientist,80405,EUR,68344,EN,FL,Austria,L,Finland,0,"Azure, Git, Tableau, TensorFlow",Master,1,Education,2024-12-16,2025-01-09,2261,7.1,Predictive Systems +AI13828,NLP Engineer,234097,EUR,198982,EX,CT,France,L,Turkey,0,"Spark, Hadoop, SQL",Master,13,Gaming,2024-05-04,2024-06-14,1819,5.9,Future Systems +AI13829,Robotics Engineer,122139,USD,122139,SE,PT,Finland,M,Turkey,100,"GCP, Kubernetes, Hadoop, MLOps, Scala",Bachelor,8,Consulting,2024-09-08,2024-11-16,1113,9.6,Smart Analytics +AI13830,Autonomous Systems Engineer,61146,EUR,51974,EN,PT,Germany,L,Italy,100,"Computer Vision, Hadoop, Linux, SQL, Statistics",Bachelor,1,Education,2024-12-22,2025-03-03,2096,8.7,Autonomous Tech +AI13831,AI Research Scientist,72035,USD,72035,EN,FL,United States,S,United States,100,"Python, NLP, Docker, Kubernetes, Git",Associate,0,Gaming,2025-02-14,2025-04-22,2448,7,DeepTech Ventures +AI13832,Computer Vision Engineer,224347,USD,224347,EX,FT,Sweden,M,Belgium,50,"TensorFlow, GCP, Scala, R",Associate,19,Government,2025-04-03,2025-06-15,1747,8,Predictive Systems +AI13833,Principal Data Scientist,54240,USD,54240,SE,CT,China,S,Canada,100,"Spark, Python, PyTorch, SQL",Bachelor,5,Telecommunications,2024-08-16,2024-10-22,1611,7.8,Machine Intelligence Group +AI13834,Principal Data Scientist,153995,USD,153995,SE,FL,Denmark,M,Denmark,0,"GCP, Data Visualization, R",Associate,5,Retail,2024-09-07,2024-10-26,1386,9.7,Predictive Systems +AI13835,Autonomous Systems Engineer,196504,USD,196504,SE,FT,United States,L,United Kingdom,0,"Hadoop, Docker, TensorFlow, Mathematics, Git",Associate,6,Real Estate,2024-09-22,2024-10-06,2223,8.4,Predictive Systems +AI13836,Deep Learning Engineer,164839,GBP,123629,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, MLOps, R, GCP",Bachelor,10,Government,2024-12-24,2025-01-08,2256,10,AI Innovations +AI13837,NLP Engineer,57984,USD,57984,EN,PT,South Korea,M,South Korea,50,"Python, Mathematics, TensorFlow",Bachelor,0,Energy,2025-02-20,2025-05-03,2117,7.1,Advanced Robotics +AI13838,AI Architect,269893,EUR,229409,EX,PT,Netherlands,L,Germany,100,"Azure, Data Visualization, Git",PhD,13,Education,2025-03-24,2025-04-08,2342,5.2,Cloud AI Solutions +AI13839,Data Analyst,72103,EUR,61288,EN,FT,Netherlands,S,Netherlands,100,"Mathematics, Computer Vision, SQL, Kubernetes",Bachelor,1,Education,2025-02-13,2025-04-19,1864,5.7,Neural Networks Co +AI13840,Principal Data Scientist,130093,JPY,14310230,SE,PT,Japan,S,Japan,50,"Data Visualization, Git, Mathematics, Deep Learning, NLP",Master,7,Media,2024-12-05,2025-01-30,1903,8.2,Algorithmic Solutions +AI13841,AI Specialist,68572,USD,68572,EN,FT,Ireland,L,Ireland,100,"Kubernetes, Java, GCP, Mathematics, Scala",Associate,0,Technology,2024-12-15,2024-12-31,663,7.8,Cloud AI Solutions +AI13842,AI Architect,55431,EUR,47116,EN,FT,Germany,M,Germany,0,"PyTorch, Java, Statistics",Bachelor,1,Gaming,2024-05-01,2024-05-27,585,5.5,Future Systems +AI13843,AI Consultant,104409,AUD,140952,MI,FT,Australia,L,Hungary,100,"R, Python, GCP",Master,2,Finance,2024-07-06,2024-08-17,1477,6.3,Smart Analytics +AI13844,AI Product Manager,98179,USD,98179,MI,CT,Norway,S,Norway,100,"PyTorch, TensorFlow, Java, Hadoop",PhD,2,Technology,2024-10-30,2024-12-28,1392,9.2,Smart Analytics +AI13845,AI Product Manager,138780,USD,138780,EX,FT,Finland,S,New Zealand,0,"Deep Learning, Data Visualization, Python",PhD,11,Retail,2024-03-19,2024-05-12,2161,5.6,AI Innovations +AI13846,Principal Data Scientist,222699,CHF,200429,SE,PT,Switzerland,L,Switzerland,50,"Python, Linux, SQL",Bachelor,9,Retail,2025-01-22,2025-03-10,849,6.4,DeepTech Ventures +AI13847,AI Architect,50170,USD,50170,EN,PT,South Korea,L,South Korea,0,"PyTorch, Python, MLOps",Master,1,Retail,2025-04-16,2025-05-10,2460,7.6,Advanced Robotics +AI13848,Research Scientist,38746,USD,38746,MI,FT,China,S,Philippines,0,"R, Git, Tableau, Scala, Docker",PhD,4,Manufacturing,2025-03-10,2025-05-08,2240,5.9,Predictive Systems +AI13849,Principal Data Scientist,74319,USD,74319,EN,PT,Israel,M,Canada,100,"Python, Scala, AWS",Associate,0,Education,2025-02-20,2025-03-06,1598,9.8,Cognitive Computing +AI13850,Data Engineer,273668,JPY,30103480,EX,PT,Japan,L,Ghana,100,"Tableau, Spark, Deep Learning, GCP, Python",Bachelor,10,Education,2024-08-18,2024-09-08,2356,7.9,Cloud AI Solutions +AI13851,Data Engineer,66041,USD,66041,EN,PT,Denmark,M,Ukraine,100,"Mathematics, TensorFlow, Git, Python, Linux",Master,0,Telecommunications,2024-11-18,2024-12-30,1290,5.5,Advanced Robotics +AI13852,AI Product Manager,75268,EUR,63978,EN,PT,Germany,M,Germany,100,"Data Visualization, Scala, Statistics, NLP",Bachelor,1,Transportation,2024-12-18,2025-01-24,1933,7.4,Future Systems +AI13853,Robotics Engineer,177163,EUR,150589,EX,CT,Germany,M,Russia,100,"Java, Spark, Computer Vision, Docker",Master,13,Retail,2025-01-01,2025-02-11,1434,9.5,Advanced Robotics +AI13854,AI Software Engineer,169340,JPY,18627400,EX,CT,Japan,L,Japan,50,"Kubernetes, Computer Vision, Python, Scala",Master,16,Retail,2024-12-16,2025-02-18,903,9,DeepTech Ventures +AI13855,Research Scientist,150295,SGD,195384,SE,FT,Singapore,M,Malaysia,50,"R, Python, Data Visualization",Associate,5,Real Estate,2024-02-24,2024-04-01,1181,5.5,Neural Networks Co +AI13856,AI Product Manager,154260,CHF,138834,SE,FL,Switzerland,M,Germany,50,"GCP, Python, Tableau, Statistics, Mathematics",Associate,6,Gaming,2024-06-26,2024-07-13,1751,7.1,Predictive Systems +AI13857,AI Specialist,100497,CAD,125621,MI,CT,Canada,M,Canada,50,"TensorFlow, Python, Java",PhD,2,Retail,2024-12-24,2025-02-12,2099,6.5,DeepTech Ventures +AI13858,Machine Learning Engineer,193134,USD,193134,EX,FL,Sweden,L,South Korea,50,"Kubernetes, GCP, Python",Associate,14,Consulting,2024-08-13,2024-10-23,786,6.8,Algorithmic Solutions +AI13859,ML Ops Engineer,170026,CHF,153023,MI,FL,Switzerland,L,Switzerland,50,"Hadoop, Azure, Tableau, Data Visualization, Git",Bachelor,3,Automotive,2024-09-18,2024-11-07,2419,7.7,AI Innovations +AI13860,Data Analyst,237130,USD,237130,EX,FL,Finland,M,Hungary,50,"AWS, Hadoop, Tableau, Git",Associate,13,Technology,2024-01-23,2024-03-02,1588,7.8,Algorithmic Solutions +AI13861,Principal Data Scientist,122855,CHF,110570,MI,CT,Switzerland,S,Switzerland,100,"AWS, R, Git",PhD,4,Healthcare,2024-09-08,2024-11-18,1670,8.5,Smart Analytics +AI13862,AI Consultant,73055,CHF,65750,EN,FL,Switzerland,S,Egypt,50,"TensorFlow, Python, Docker, Statistics",PhD,0,Media,2024-08-22,2024-10-22,1510,8.9,Future Systems +AI13863,Research Scientist,38444,USD,38444,SE,CT,India,S,India,100,"PyTorch, Linux, TensorFlow, Data Visualization",Associate,9,Transportation,2024-06-14,2024-07-23,1791,9.6,Machine Intelligence Group +AI13864,Data Scientist,174441,USD,174441,EX,PT,Ireland,M,Romania,50,"Data Visualization, Azure, Python",Bachelor,11,Real Estate,2025-02-26,2025-03-27,1148,9.5,Future Systems +AI13865,AI Research Scientist,120189,USD,120189,SE,FL,Denmark,S,Denmark,0,"Python, SQL, Scala, TensorFlow, AWS",Master,5,Telecommunications,2025-04-06,2025-06-12,953,9.9,Future Systems +AI13866,Principal Data Scientist,112460,USD,112460,SE,PT,Ireland,S,Ireland,100,"Azure, Python, GCP, Scala, Mathematics",Associate,8,Technology,2024-08-17,2024-09-22,2399,9.8,Autonomous Tech +AI13867,AI Architect,230551,AUD,311244,EX,CT,Australia,M,Australia,100,"Spark, Statistics, Scala, Computer Vision, SQL",Bachelor,17,Education,2024-03-28,2024-05-17,1060,5.4,Neural Networks Co +AI13868,AI Research Scientist,143999,EUR,122399,SE,FL,Netherlands,L,Netherlands,0,"Deep Learning, Python, NLP, Hadoop, Java",PhD,6,Consulting,2024-05-05,2024-06-29,2418,8.8,Quantum Computing Inc +AI13869,AI Specialist,181922,CHF,163730,SE,CT,Switzerland,L,Hungary,50,"AWS, Git, Java",PhD,7,Transportation,2025-04-08,2025-06-03,1333,9.8,Cloud AI Solutions +AI13870,Autonomous Systems Engineer,121801,USD,121801,SE,FL,South Korea,L,France,0,"Python, TensorFlow, Computer Vision",Bachelor,8,Telecommunications,2024-04-09,2024-04-25,739,10,AI Innovations +AI13871,Research Scientist,158462,GBP,118847,SE,PT,United Kingdom,M,United Kingdom,0,"R, Python, PyTorch, Git, SQL",Master,9,Manufacturing,2024-04-12,2024-05-03,2349,9.4,Future Systems +AI13872,NLP Engineer,113678,USD,113678,SE,CT,Finland,L,Finland,0,"Python, Computer Vision, Linux, Azure",Bachelor,7,Education,2024-12-07,2025-02-04,1789,9.6,Future Systems +AI13873,ML Ops Engineer,151647,GBP,113735,SE,CT,United Kingdom,M,United Kingdom,50,"Git, R, Java",Bachelor,7,Telecommunications,2024-08-05,2024-09-18,1696,8.9,Quantum Computing Inc +AI13874,AI Software Engineer,111894,USD,111894,SE,FL,United States,S,United States,0,"Deep Learning, Kubernetes, Scala",PhD,8,Energy,2024-04-04,2024-04-22,1512,7.9,Advanced Robotics +AI13875,Autonomous Systems Engineer,99898,USD,99898,MI,PT,Sweden,M,Sweden,100,"Linux, Python, TensorFlow, Scala",PhD,3,Gaming,2024-08-24,2024-10-23,2166,7.9,TechCorp Inc +AI13876,Computer Vision Engineer,88708,USD,88708,MI,PT,Sweden,M,Egypt,50,"Computer Vision, MLOps, Java, Kubernetes, Docker",Master,2,Retail,2025-01-23,2025-04-02,788,8.2,Quantum Computing Inc +AI13877,AI Specialist,101550,JPY,11170500,MI,CT,Japan,M,Russia,0,"AWS, R, Deep Learning, Python",Master,4,Transportation,2024-05-27,2024-07-19,2250,7.9,TechCorp Inc +AI13878,ML Ops Engineer,69360,CAD,86700,EN,CT,Canada,L,Canada,100,"Kubernetes, Scala, Computer Vision",PhD,1,Retail,2024-05-19,2024-06-15,540,7.1,TechCorp Inc +AI13879,Robotics Engineer,124351,SGD,161656,SE,PT,Singapore,S,Singapore,100,"MLOps, SQL, Data Visualization, TensorFlow",Bachelor,6,Healthcare,2024-05-22,2024-06-11,2292,7.5,Quantum Computing Inc +AI13880,AI Specialist,174613,GBP,130960,EX,CT,United Kingdom,S,Finland,100,"SQL, Azure, NLP, Hadoop",Bachelor,17,Healthcare,2024-09-26,2024-10-15,2365,5.6,Machine Intelligence Group +AI13881,AI Software Engineer,164314,GBP,123236,SE,FT,United Kingdom,L,United Kingdom,0,"Git, Deep Learning, MLOps, Java",Bachelor,7,Healthcare,2025-01-11,2025-03-25,1645,8.6,TechCorp Inc +AI13882,NLP Engineer,33496,USD,33496,MI,FT,India,M,India,100,"PyTorch, Kubernetes, Deep Learning, MLOps, GCP",Associate,4,Telecommunications,2024-04-21,2024-07-01,1093,8,Advanced Robotics +AI13883,NLP Engineer,90700,USD,90700,EN,CT,United States,M,United States,50,"Tableau, Data Visualization, SQL, Python, GCP",Master,0,Government,2024-11-18,2025-01-20,1192,9.6,Neural Networks Co +AI13884,Machine Learning Researcher,43580,USD,43580,SE,PT,India,L,India,0,"Python, Computer Vision, Data Visualization",Associate,6,Healthcare,2025-01-19,2025-02-10,725,9.1,Future Systems +AI13885,Autonomous Systems Engineer,134932,USD,134932,SE,PT,United States,S,United States,0,"GCP, Python, PyTorch, Computer Vision, Hadoop",Master,8,Media,2024-04-05,2024-04-24,1152,5.6,TechCorp Inc +AI13886,Machine Learning Researcher,97649,USD,97649,MI,PT,Denmark,S,Denmark,100,"Python, Azure, GCP, Scala, Docker",Associate,2,Transportation,2024-02-26,2024-04-26,1846,9.1,Algorithmic Solutions +AI13887,Data Scientist,150764,EUR,128149,EX,FT,Germany,S,Ukraine,100,"Azure, Data Visualization, AWS, Python, Computer Vision",Bachelor,15,Healthcare,2024-10-24,2024-12-25,1536,9.2,Machine Intelligence Group +AI13888,Machine Learning Engineer,136387,GBP,102290,SE,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Statistics",PhD,9,Gaming,2025-01-20,2025-02-10,2089,9.9,Advanced Robotics +AI13889,AI Research Scientist,99958,USD,99958,MI,CT,United States,M,United States,100,"Linux, Kubernetes, Java, Computer Vision, NLP",Master,3,Government,2024-06-03,2024-07-14,1509,5.7,Neural Networks Co +AI13890,Autonomous Systems Engineer,98300,CAD,122875,SE,PT,Canada,S,Canada,0,"Python, Data Visualization, TensorFlow",Associate,7,Technology,2025-01-04,2025-03-07,566,5.5,Advanced Robotics +AI13891,Machine Learning Researcher,22579,USD,22579,EN,FT,India,S,India,100,"TensorFlow, SQL, Azure",Associate,0,Telecommunications,2024-05-19,2024-06-05,548,5.6,Future Systems +AI13892,Data Engineer,159778,USD,159778,SE,CT,Ireland,L,Romania,100,"Spark, Kubernetes, SQL, PyTorch",Bachelor,8,Manufacturing,2024-12-02,2025-02-11,1797,9.3,Autonomous Tech +AI13893,Autonomous Systems Engineer,52353,USD,52353,EX,CT,India,M,India,50,"R, Computer Vision, MLOps, Spark",Master,19,Government,2024-05-01,2024-06-16,2384,6.8,TechCorp Inc +AI13894,Data Scientist,82987,EUR,70539,MI,FT,Netherlands,M,Netherlands,0,"PyTorch, TensorFlow, NLP, R, Python",Master,2,Automotive,2025-02-09,2025-03-28,2186,9.1,Cognitive Computing +AI13895,Machine Learning Engineer,76339,USD,76339,SE,FL,South Korea,S,South Korea,50,"Python, GCP, Computer Vision",Associate,5,Healthcare,2025-02-19,2025-04-15,521,7.2,DeepTech Ventures +AI13896,Research Scientist,100750,USD,100750,EN,FL,Norway,L,Norway,50,"Azure, R, Docker",Master,1,Gaming,2024-09-26,2024-11-10,1045,7.3,Quantum Computing Inc +AI13897,Principal Data Scientist,73199,SGD,95159,EN,FT,Singapore,S,Singapore,50,"Python, PyTorch, Hadoop, Java",PhD,1,Government,2024-09-24,2024-11-02,668,5.6,Algorithmic Solutions +AI13898,Computer Vision Engineer,76495,USD,76495,EN,FT,United States,M,United States,100,"R, Docker, Data Visualization, NLP, PyTorch",Master,1,Automotive,2025-01-19,2025-03-12,1924,7.5,Algorithmic Solutions +AI13899,Machine Learning Researcher,101641,USD,101641,EN,FT,Norway,M,Norway,100,"Azure, NLP, SQL, Computer Vision, PyTorch",Bachelor,0,Technology,2024-01-03,2024-01-18,1481,5.7,Advanced Robotics +AI13900,Head of AI,66025,EUR,56121,EN,PT,Germany,M,Germany,50,"Python, R, TensorFlow, Statistics, AWS",Bachelor,1,Transportation,2024-07-20,2024-08-03,908,9,Machine Intelligence Group +AI13901,AI Product Manager,55150,USD,55150,SE,FT,India,L,India,100,"Hadoop, Tableau, Scala",Master,6,Energy,2025-02-20,2025-04-07,2055,9.2,DeepTech Ventures +AI13902,Data Engineer,132349,GBP,99262,EX,FT,United Kingdom,S,United Kingdom,50,"Spark, Tableau, AWS, Java",Master,17,Healthcare,2024-08-31,2024-10-30,750,5.6,Algorithmic Solutions +AI13903,AI Software Engineer,84903,EUR,72168,MI,PT,Netherlands,M,Netherlands,0,"Kubernetes, PyTorch, Data Visualization, Computer Vision",Bachelor,3,Manufacturing,2024-02-06,2024-04-15,761,5.5,Autonomous Tech +AI13904,Robotics Engineer,172144,JPY,18935840,SE,FT,Japan,L,Kenya,50,"Git, PyTorch, Java, Spark",Master,9,Telecommunications,2025-01-04,2025-02-06,710,6.3,TechCorp Inc +AI13905,AI Software Engineer,83302,SGD,108293,EN,PT,Singapore,M,Singapore,50,"Mathematics, Deep Learning, Python, Kubernetes, Azure",Bachelor,1,Media,2025-04-10,2025-05-09,2257,7.8,Cloud AI Solutions +AI13906,NLP Engineer,109085,CHF,98177,MI,CT,Switzerland,S,Australia,50,"SQL, Data Visualization, AWS, MLOps",Bachelor,3,Retail,2024-01-01,2024-02-09,1601,7.5,Neural Networks Co +AI13907,Machine Learning Engineer,354720,CHF,319248,EX,FT,Switzerland,M,Denmark,100,"SQL, Java, Linux",Master,17,Finance,2024-06-27,2024-07-19,1806,5.9,DeepTech Ventures +AI13908,Data Engineer,106171,EUR,90245,SE,PT,France,M,Ukraine,0,"Scala, Deep Learning, Computer Vision",Bachelor,5,Finance,2024-08-13,2024-09-08,1723,8.6,Cloud AI Solutions +AI13909,AI Specialist,86810,USD,86810,EX,PT,India,M,Germany,50,"Spark, PyTorch, Git, Data Visualization",Master,15,Energy,2024-05-29,2024-07-01,1002,8.6,Algorithmic Solutions +AI13910,Machine Learning Engineer,131624,USD,131624,SE,CT,Sweden,M,Ireland,50,"Docker, Linux, Kubernetes, NLP",PhD,8,Transportation,2024-02-11,2024-04-22,1531,9,DeepTech Ventures +AI13911,AI Research Scientist,68905,SGD,89577,EN,FL,Singapore,S,Singapore,50,"Kubernetes, R, TensorFlow, Statistics, Hadoop",Bachelor,0,Government,2024-03-06,2024-04-17,775,6.6,Predictive Systems +AI13912,Machine Learning Engineer,134463,GBP,100847,SE,FL,United Kingdom,M,Netherlands,0,"Spark, Linux, TensorFlow, Java",Bachelor,5,Manufacturing,2025-04-11,2025-05-04,1935,5.3,Quantum Computing Inc +AI13913,Principal Data Scientist,98904,USD,98904,EX,FL,India,L,India,0,"Git, GCP, Tableau, Spark, Scala",Master,14,Energy,2024-02-25,2024-04-09,1310,9.9,Digital Transformation LLC +AI13914,Data Engineer,257480,USD,257480,EX,FT,Norway,S,Japan,0,"GCP, Statistics, Linux, Scala, R",Master,13,Energy,2024-11-24,2025-01-09,890,5.5,Digital Transformation LLC +AI13915,AI Architect,117881,SGD,153245,SE,FL,Singapore,S,Singapore,0,"SQL, Git, Data Visualization, PyTorch, MLOps",Master,7,Government,2025-04-03,2025-06-01,680,9.4,Future Systems +AI13916,ML Ops Engineer,131840,EUR,112064,EX,CT,France,M,France,50,"Kubernetes, Java, Azure, Python, TensorFlow",PhD,13,Consulting,2024-07-24,2024-08-17,1098,8.7,AI Innovations +AI13917,Machine Learning Researcher,235864,SGD,306623,EX,PT,Singapore,S,Romania,0,"R, Data Visualization, GCP, Tableau",PhD,12,Technology,2024-12-30,2025-02-10,1394,8.7,DataVision Ltd +AI13918,Robotics Engineer,151764,EUR,128999,SE,FL,Germany,M,Germany,100,"Python, TensorFlow, Java, PyTorch, Mathematics",Associate,6,Media,2024-12-08,2025-01-21,2196,7.8,Future Systems +AI13919,AI Consultant,120897,USD,120897,MI,CT,Norway,L,Turkey,0,"GCP, Spark, Deep Learning",PhD,3,Retail,2025-03-16,2025-05-03,1528,5.6,DataVision Ltd +AI13920,Deep Learning Engineer,319778,USD,319778,EX,CT,Denmark,M,Denmark,0,"MLOps, Tableau, Linux, Git",Bachelor,18,Energy,2024-10-18,2024-11-05,1330,7.2,Cloud AI Solutions +AI13921,Data Engineer,213125,EUR,181156,EX,CT,Germany,M,Philippines,100,"TensorFlow, MLOps, GCP, Java",PhD,16,Energy,2025-01-11,2025-03-14,1895,8.2,TechCorp Inc +AI13922,AI Specialist,99994,EUR,84995,MI,PT,Netherlands,L,Czech Republic,50,"Computer Vision, AWS, TensorFlow, Python, R",Bachelor,2,Retail,2025-04-14,2025-06-13,1090,5.2,Algorithmic Solutions +AI13923,Deep Learning Engineer,42397,USD,42397,EN,FT,China,L,China,0,"TensorFlow, AWS, Azure, PyTorch",Master,1,Gaming,2024-03-01,2024-04-13,2322,6.3,AI Innovations +AI13924,Data Engineer,268816,GBP,201612,EX,CT,United Kingdom,M,United Kingdom,50,"Tableau, SQL, R, Docker, Kubernetes",Master,11,Telecommunications,2025-01-07,2025-03-02,1846,7.4,Cloud AI Solutions +AI13925,Machine Learning Engineer,146336,USD,146336,MI,CT,Denmark,L,United States,0,"PyTorch, R, Mathematics",Bachelor,4,Automotive,2024-11-15,2024-12-13,1227,8.2,Digital Transformation LLC +AI13926,ML Ops Engineer,163963,EUR,139369,EX,PT,Germany,M,Israel,100,"SQL, Data Visualization, Hadoop",PhD,15,Government,2024-08-13,2024-10-15,916,6.7,Predictive Systems +AI13927,Research Scientist,50533,USD,50533,SE,PT,India,M,India,0,"Statistics, R, Computer Vision, Hadoop, Git",Bachelor,5,Energy,2024-03-31,2024-05-29,1703,5.5,Smart Analytics +AI13928,AI Architect,82127,SGD,106765,EN,FT,Singapore,L,Colombia,50,"AWS, Spark, Linux, TensorFlow, Python",Master,0,Energy,2024-12-25,2025-01-23,2258,5.2,Cloud AI Solutions +AI13929,AI Consultant,116006,GBP,87005,SE,FT,United Kingdom,S,United Kingdom,50,"Python, PyTorch, Tableau, Mathematics, MLOps",Master,9,Education,2024-08-12,2024-10-10,1582,8,Algorithmic Solutions +AI13930,Robotics Engineer,126184,USD,126184,MI,PT,Norway,M,Norway,100,"Java, Linux, TensorFlow, R, Data Visualization",Master,4,Transportation,2024-11-14,2024-12-31,1710,5.6,Predictive Systems +AI13931,Machine Learning Researcher,160147,EUR,136125,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, TensorFlow, NLP, Statistics, Data Visualization",Master,7,Manufacturing,2024-04-13,2024-06-12,1699,5.9,Predictive Systems +AI13932,AI Product Manager,107865,SGD,140225,MI,CT,Singapore,M,Vietnam,100,"Python, Data Visualization, TensorFlow, PyTorch",Master,4,Gaming,2025-01-11,2025-02-26,1084,9.1,DeepTech Ventures +AI13933,AI Architect,187028,CHF,168325,SE,FT,Switzerland,S,Switzerland,0,"Python, Docker, Hadoop, Azure",Master,7,Transportation,2024-04-15,2024-06-12,1931,9,Machine Intelligence Group +AI13934,ML Ops Engineer,110875,CHF,99788,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, Python, Data Visualization",Master,3,Education,2024-12-13,2025-01-14,1288,7.1,Autonomous Tech +AI13935,Data Engineer,206757,USD,206757,EX,FL,United States,S,Ghana,0,"Scala, PyTorch, Data Visualization, GCP",PhD,13,Technology,2024-11-09,2024-12-02,1852,8.6,Advanced Robotics +AI13936,Machine Learning Engineer,56474,USD,56474,EN,FT,Ireland,M,Ireland,50,"Python, R, PyTorch",Bachelor,0,Government,2024-08-11,2024-09-09,1099,8.2,Cognitive Computing +AI13937,AI Specialist,85570,USD,85570,EX,FL,India,M,Italy,0,"PyTorch, TensorFlow, Linux, NLP",Bachelor,15,Automotive,2024-02-19,2024-04-21,689,7.9,Digital Transformation LLC +AI13938,Autonomous Systems Engineer,212458,CHF,191212,SE,FL,Switzerland,L,Switzerland,100,"Scala, Python, TensorFlow",Bachelor,6,Manufacturing,2024-06-06,2024-07-22,889,9.5,Advanced Robotics +AI13939,AI Architect,70580,SGD,91754,EN,PT,Singapore,S,Chile,100,"Azure, GCP, Python",Associate,1,Media,2024-01-16,2024-02-12,1169,9.8,AI Innovations +AI13940,Data Engineer,36309,USD,36309,SE,CT,India,S,Norway,100,"Linux, Git, Kubernetes, PyTorch, SQL",Master,9,Consulting,2024-05-21,2024-07-06,747,6.6,DeepTech Ventures +AI13941,Deep Learning Engineer,64560,USD,64560,EN,FT,Israel,M,Turkey,50,"Python, Data Visualization, Linux, Kubernetes, Computer Vision",Bachelor,0,Technology,2024-12-18,2025-02-16,1314,6,Smart Analytics +AI13942,Deep Learning Engineer,94949,EUR,80707,MI,CT,France,L,France,100,"R, Computer Vision, Data Visualization, Java",Bachelor,4,Transportation,2024-08-19,2024-09-25,979,6,Cloud AI Solutions +AI13943,Research Scientist,74347,USD,74347,MI,PT,South Korea,M,South Korea,50,"PyTorch, GCP, Scala, Java",Bachelor,3,Media,2024-10-04,2024-12-01,1926,7.9,AI Innovations +AI13944,AI Product Manager,321456,USD,321456,EX,FL,United States,L,United States,100,"Docker, GCP, Statistics",Master,15,Automotive,2024-10-25,2024-12-06,1311,8.6,Quantum Computing Inc +AI13945,Head of AI,72159,EUR,61335,EN,FT,Germany,L,Germany,0,"R, Spark, Mathematics",PhD,0,Retail,2024-04-16,2024-06-08,1412,8.4,Advanced Robotics +AI13946,Machine Learning Researcher,185190,USD,185190,EX,PT,Finland,S,Finland,100,"GCP, Scala, MLOps, Python, Azure",Bachelor,12,Automotive,2024-07-10,2024-09-20,977,8.5,Autonomous Tech +AI13947,AI Product Manager,150333,EUR,127783,SE,FT,Germany,L,Poland,0,"R, Azure, Git, Python",PhD,9,Automotive,2025-01-18,2025-02-24,1452,9.1,Quantum Computing Inc +AI13948,Research Scientist,265558,AUD,358503,EX,PT,Australia,L,Australia,0,"Java, Deep Learning, NLP",Master,12,Education,2024-06-07,2024-07-09,874,9.9,Cognitive Computing +AI13949,Machine Learning Researcher,82299,EUR,69954,MI,FT,Austria,L,Kenya,0,"Data Visualization, Deep Learning, Java",Master,2,Consulting,2024-11-14,2024-12-25,981,8.1,Cloud AI Solutions +AI13950,AI Specialist,148281,JPY,16310910,SE,FL,Japan,L,Japan,50,"Linux, Java, R, Kubernetes",PhD,5,Healthcare,2025-03-02,2025-03-17,892,7.8,Cognitive Computing +AI13951,AI Product Manager,33202,USD,33202,MI,FT,China,S,China,0,"Java, Python, Data Visualization, TensorFlow, Git",Bachelor,2,Education,2024-05-18,2024-07-19,821,8.5,Algorithmic Solutions +AI13952,AI Software Engineer,67300,USD,67300,EN,CT,Israel,M,Israel,0,"TensorFlow, Python, Linux, Statistics",Bachelor,0,Finance,2024-05-23,2024-06-25,2327,7.1,Cloud AI Solutions +AI13953,AI Product Manager,120081,USD,120081,MI,FL,Ireland,L,Ireland,100,"Data Visualization, R, Azure",Master,4,Real Estate,2024-01-15,2024-02-21,2086,7.6,Cognitive Computing +AI13954,Machine Learning Engineer,73036,EUR,62081,MI,CT,France,S,France,0,"Python, MLOps, Tableau",PhD,2,Technology,2025-04-08,2025-05-05,1365,9.2,AI Innovations +AI13955,Robotics Engineer,87908,USD,87908,EN,FT,Norway,S,Norway,100,"Kubernetes, Data Visualization, NLP, R, TensorFlow",Associate,0,Consulting,2024-11-29,2025-01-21,609,8.3,Quantum Computing Inc +AI13956,Machine Learning Researcher,70146,USD,70146,EX,PT,India,S,India,0,"Git, Python, Data Visualization, Linux, Scala",Bachelor,14,Education,2024-05-14,2024-07-25,669,5.5,DeepTech Ventures +AI13957,Principal Data Scientist,32133,USD,32133,MI,FL,India,S,India,100,"Azure, Python, Tableau, GCP",Bachelor,3,Media,2024-10-21,2024-12-25,1969,8.9,Algorithmic Solutions +AI13958,Data Scientist,108840,JPY,11972400,SE,CT,Japan,S,Japan,50,"TensorFlow, Kubernetes, GCP, Spark",Associate,8,Consulting,2024-06-17,2024-07-06,1758,7.5,Neural Networks Co +AI13959,Machine Learning Researcher,122926,EUR,104487,SE,PT,Netherlands,M,United States,0,"Kubernetes, Scala, Tableau",Master,9,Retail,2024-03-17,2024-04-03,1477,8.5,Autonomous Tech +AI13960,AI Product Manager,287863,CHF,259077,EX,PT,Switzerland,M,Norway,50,"Scala, Deep Learning, Hadoop",PhD,19,Automotive,2024-04-07,2024-05-24,1944,6.5,Predictive Systems +AI13961,Machine Learning Engineer,99266,USD,99266,SE,FT,Ireland,S,Ireland,50,"MLOps, Spark, PyTorch",Associate,7,Finance,2024-07-15,2024-08-10,2461,5.3,Neural Networks Co +AI13962,NLP Engineer,228899,JPY,25178890,EX,FT,Japan,M,China,50,"MLOps, Docker, Kubernetes, Python, AWS",PhD,18,Real Estate,2024-06-05,2024-07-28,2258,8.4,Advanced Robotics +AI13963,Data Scientist,162574,USD,162574,EX,PT,Ireland,M,Ireland,100,"Kubernetes, Spark, Tableau, Deep Learning",Bachelor,16,Real Estate,2024-10-29,2024-12-21,2146,6.7,AI Innovations +AI13964,Data Engineer,225255,USD,225255,EX,PT,Finland,L,Finland,100,"Deep Learning, Computer Vision, Tableau, Azure, Docker",PhD,13,Manufacturing,2024-06-12,2024-08-12,632,5.5,Autonomous Tech +AI13965,Head of AI,132938,CHF,119644,MI,FL,Switzerland,S,Switzerland,0,"Git, Azure, MLOps, Linux, R",PhD,2,Education,2025-02-04,2025-03-01,551,9.9,Smart Analytics +AI13966,AI Consultant,90671,USD,90671,SE,FT,Israel,S,Poland,50,"PyTorch, Kubernetes, TensorFlow, SQL",PhD,7,Finance,2025-02-08,2025-02-25,2316,9.8,Algorithmic Solutions +AI13967,AI Architect,179691,SGD,233598,EX,CT,Singapore,L,Singapore,0,"Scala, MLOps, Python",Bachelor,13,Telecommunications,2024-10-13,2024-12-18,1094,7.5,Cognitive Computing +AI13968,AI Specialist,80674,USD,80674,EX,FL,India,L,India,0,"Git, PyTorch, Hadoop",PhD,13,Real Estate,2024-06-30,2024-07-27,1834,9.6,Quantum Computing Inc +AI13969,Research Scientist,96450,CAD,120563,SE,PT,Canada,S,Canada,50,"Hadoop, Python, TensorFlow, Computer Vision",Master,9,Transportation,2024-03-17,2024-05-05,1744,5.3,TechCorp Inc +AI13970,AI Research Scientist,132495,USD,132495,SE,FL,Sweden,L,Sweden,50,"Kubernetes, Docker, NLP",Bachelor,9,Automotive,2024-10-12,2024-12-04,1918,8.9,Cloud AI Solutions +AI13971,Machine Learning Engineer,70645,CAD,88306,EN,CT,Canada,L,Canada,50,"Linux, Tableau, Python, PyTorch",Associate,1,Media,2025-03-27,2025-05-11,1527,9.3,Machine Intelligence Group +AI13972,Robotics Engineer,24476,USD,24476,EN,PT,China,S,China,50,"Statistics, Scala, Java, MLOps, Deep Learning",Associate,1,Telecommunications,2024-12-18,2025-01-21,996,7.5,Neural Networks Co +AI13973,Machine Learning Engineer,219297,SGD,285086,EX,FL,Singapore,L,Singapore,50,"Kubernetes, Scala, Spark, Deep Learning, Statistics",Associate,15,Automotive,2024-06-27,2024-07-25,705,6.6,Machine Intelligence Group +AI13974,Computer Vision Engineer,139564,GBP,104673,EX,PT,United Kingdom,S,United Kingdom,100,"Linux, GCP, Scala",PhD,15,Telecommunications,2025-03-10,2025-04-17,1455,9.2,Machine Intelligence Group +AI13975,NLP Engineer,232693,USD,232693,EX,FT,United States,S,United States,50,"Computer Vision, Python, TensorFlow, Java, R",PhD,14,Gaming,2024-06-29,2024-08-03,2116,7.7,AI Innovations +AI13976,Machine Learning Engineer,97324,USD,97324,MI,PT,Ireland,S,Sweden,50,"AWS, Linux, NLP, Kubernetes",PhD,3,Energy,2024-01-31,2024-04-01,970,6.7,Autonomous Tech +AI13977,AI Specialist,83572,USD,83572,MI,FT,South Korea,L,Italy,0,"Docker, Hadoop, Kubernetes, Statistics, R",Bachelor,3,Real Estate,2024-01-03,2024-03-13,2121,8.2,Cloud AI Solutions +AI13978,Computer Vision Engineer,119106,USD,119106,MI,FL,United States,M,Nigeria,100,"Tableau, Java, Python",Bachelor,2,Government,2025-04-19,2025-06-14,1345,7.8,Machine Intelligence Group +AI13979,Deep Learning Engineer,107752,SGD,140078,MI,PT,Singapore,L,Singapore,100,"AWS, Docker, Data Visualization, GCP, Kubernetes",Master,2,Energy,2024-06-08,2024-06-28,2045,5.3,Cloud AI Solutions +AI13980,AI Consultant,62312,SGD,81006,EN,FL,Singapore,M,Singapore,0,"Deep Learning, Data Visualization, Python, Tableau, MLOps",PhD,1,Education,2024-05-02,2024-05-26,1829,7.8,Neural Networks Co +AI13981,Principal Data Scientist,118029,USD,118029,SE,FT,Ireland,L,Ireland,0,"TensorFlow, SQL, Tableau",PhD,7,Retail,2024-05-14,2024-07-25,1262,7.4,TechCorp Inc +AI13982,Computer Vision Engineer,204810,AUD,276494,EX,FL,Australia,S,Australia,0,"AWS, Data Visualization, R, NLP",Master,18,Retail,2024-01-28,2024-03-03,727,6.1,Neural Networks Co +AI13983,Research Scientist,79470,EUR,67550,MI,FT,Netherlands,M,Portugal,100,"Deep Learning, Mathematics, MLOps, Java, GCP",Associate,3,Finance,2024-09-06,2024-10-18,2268,9.1,Future Systems +AI13984,Data Analyst,86228,AUD,116408,MI,CT,Australia,M,Switzerland,100,"Statistics, Spark, GCP, Git",PhD,2,Real Estate,2024-06-17,2024-07-02,1626,6.6,Neural Networks Co +AI13985,Data Engineer,118142,CAD,147678,MI,FT,Canada,L,Canada,100,"NLP, Python, Tableau",PhD,3,Retail,2024-02-16,2024-03-02,984,5.8,Smart Analytics +AI13986,Principal Data Scientist,149989,USD,149989,EX,CT,Israel,S,Israel,100,"AWS, PyTorch, Deep Learning, Mathematics",Bachelor,11,Energy,2024-09-14,2024-10-04,1455,6.8,TechCorp Inc +AI13987,Data Scientist,59094,USD,59094,EN,CT,South Korea,M,United States,0,"Kubernetes, Data Visualization, Git",Master,1,Retail,2024-07-09,2024-07-29,1869,8,Cognitive Computing +AI13988,Machine Learning Engineer,177285,USD,177285,SE,FL,Norway,L,Norway,0,"Scala, MLOps, Tableau, Data Visualization, R",Associate,8,Government,2024-03-30,2024-04-29,1226,8.2,Quantum Computing Inc +AI13989,Autonomous Systems Engineer,86720,USD,86720,EN,PT,Denmark,M,Denmark,0,"Computer Vision, Tableau, Scala",Master,1,Education,2024-04-01,2024-06-07,1124,6.8,Advanced Robotics +AI13990,Data Scientist,86353,USD,86353,EX,CT,China,L,China,0,"Computer Vision, Statistics, NLP, Tableau, Scala",Associate,17,Real Estate,2024-11-30,2025-01-08,1182,9.3,Cognitive Computing +AI13991,AI Specialist,43936,USD,43936,SE,PT,India,M,India,50,"Data Visualization, PyTorch, Docker, Hadoop, AWS",PhD,8,Real Estate,2025-03-07,2025-05-17,1226,6.7,Neural Networks Co +AI13992,Computer Vision Engineer,143556,USD,143556,EX,FT,Finland,M,Spain,100,"Data Visualization, Statistics, Python, Git",Master,16,Education,2025-03-05,2025-04-16,2169,8.9,Predictive Systems +AI13993,Robotics Engineer,78380,USD,78380,EX,PT,India,M,China,50,"Python, Java, PyTorch, Mathematics",PhD,18,Government,2024-12-24,2025-01-20,768,5.9,Predictive Systems +AI13994,AI Consultant,72730,EUR,61821,MI,FL,Austria,S,Austria,100,"GCP, SQL, Kubernetes, Data Visualization",Bachelor,2,Energy,2024-08-03,2024-09-03,519,7.1,Digital Transformation LLC +AI13995,Head of AI,290341,USD,290341,EX,CT,Sweden,L,Sweden,0,"Computer Vision, Python, MLOps",Associate,16,Retail,2024-06-15,2024-08-25,618,5.1,DataVision Ltd +AI13996,Data Engineer,217967,USD,217967,EX,CT,Ireland,S,Brazil,50,"PyTorch, AWS, TensorFlow",Master,17,Media,2024-09-18,2024-11-03,1350,8.7,Digital Transformation LLC +AI13997,Data Engineer,102309,USD,102309,EX,FL,India,L,India,100,"SQL, Python, Computer Vision, Mathematics",Bachelor,11,Technology,2024-05-17,2024-06-25,1370,8.2,Neural Networks Co +AI13998,Research Scientist,80525,EUR,68446,MI,FT,Netherlands,M,Indonesia,0,"Java, R, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-09,2180,7.3,Advanced Robotics +AI13999,Data Scientist,202160,USD,202160,SE,FT,United States,L,United States,100,"MLOps, Git, Tableau, Scala",Bachelor,6,Transportation,2025-04-12,2025-06-24,1769,7,Algorithmic Solutions +AI14000,Head of AI,220964,USD,220964,EX,FT,Sweden,S,Sweden,100,"PyTorch, Computer Vision, Hadoop, Python, Spark",PhD,19,Automotive,2024-11-14,2025-01-15,2217,8.3,Quantum Computing Inc +AI14001,AI Specialist,56149,USD,56149,EN,PT,Israel,L,Israel,100,"TensorFlow, NLP, Data Visualization, Scala",Master,0,Technology,2025-03-06,2025-04-20,2102,8.5,Algorithmic Solutions +AI14002,Principal Data Scientist,145157,CAD,181446,SE,FT,Canada,L,Canada,100,"Azure, Data Visualization, AWS, Kubernetes",PhD,9,Education,2025-01-16,2025-02-09,2214,5.6,Neural Networks Co +AI14003,Data Engineer,172667,USD,172667,SE,PT,Sweden,L,Mexico,0,"SQL, GCP, Java, Deep Learning",Bachelor,6,Education,2024-12-28,2025-01-17,1466,5.4,AI Innovations +AI14004,NLP Engineer,138247,AUD,186633,EX,FL,Australia,M,Chile,100,"SQL, Python, Computer Vision, NLP, Spark",Master,12,Consulting,2024-12-28,2025-02-25,1737,6,Machine Intelligence Group +AI14005,Robotics Engineer,129293,USD,129293,MI,PT,Norway,M,South Africa,0,"Mathematics, Linux, MLOps",Master,4,Media,2024-04-10,2024-05-06,1752,7,TechCorp Inc +AI14006,AI Specialist,106869,CAD,133586,SE,FT,Canada,M,New Zealand,100,"SQL, Python, Statistics, GCP, Kubernetes",Master,7,Media,2024-08-21,2024-10-15,1926,5.1,Machine Intelligence Group +AI14007,NLP Engineer,57671,EUR,49020,EN,FT,France,L,France,50,"Azure, Git, Hadoop",Associate,1,Healthcare,2025-04-02,2025-05-01,1741,6.8,DataVision Ltd +AI14008,AI Product Manager,279242,GBP,209432,EX,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Linux, Computer Vision",Master,12,Transportation,2024-10-21,2024-11-15,1138,6.9,Machine Intelligence Group +AI14009,Data Scientist,204632,JPY,22509520,EX,FT,Japan,L,Japan,100,"Scala, Spark, Deep Learning, Git, PyTorch",Associate,14,Retail,2025-02-27,2025-04-07,1462,9.9,AI Innovations +AI14010,Data Engineer,203509,EUR,172983,EX,FT,Germany,M,Germany,100,"Python, MLOps, Data Visualization, Scala, Tableau",Associate,11,Real Estate,2024-03-29,2024-05-25,1317,6.1,Machine Intelligence Group +AI14011,AI Research Scientist,76433,EUR,64968,EN,CT,Netherlands,S,Netherlands,50,"Python, Data Visualization, Hadoop, GCP",Associate,1,Technology,2025-04-23,2025-06-06,1324,7.1,TechCorp Inc +AI14012,Machine Learning Engineer,143395,CAD,179244,EX,FL,Canada,M,Singapore,0,"NLP, Data Visualization, Python",Associate,15,Energy,2025-01-28,2025-03-27,1767,7.8,AI Innovations +AI14013,Data Scientist,190317,USD,190317,EX,PT,United States,M,United States,0,"Tableau, Spark, R",PhD,13,Gaming,2024-10-23,2024-11-17,1196,6.9,Machine Intelligence Group +AI14014,Deep Learning Engineer,18052,USD,18052,EN,FL,India,M,Russia,50,"AWS, SQL, Computer Vision, NLP, Azure",Associate,0,Finance,2024-09-24,2024-11-05,1104,5,Machine Intelligence Group +AI14015,Data Analyst,157903,EUR,134218,SE,FL,Germany,L,Germany,50,"Hadoop, Linux, R",Associate,7,Energy,2024-02-29,2024-04-23,766,5.4,DataVision Ltd +AI14016,Deep Learning Engineer,208955,USD,208955,EX,FL,United States,L,United States,100,"Computer Vision, PyTorch, Git",Master,19,Consulting,2024-04-18,2024-06-22,2055,8.9,Autonomous Tech +AI14017,Research Scientist,34807,USD,34807,EN,CT,China,L,China,100,"Linux, R, Statistics, Kubernetes",Bachelor,1,Education,2025-02-23,2025-04-28,1827,7.1,Future Systems +AI14018,Research Scientist,81021,AUD,109378,MI,FT,Australia,S,Australia,100,"Linux, GCP, Mathematics, NLP",PhD,2,Energy,2024-12-18,2025-01-16,1620,9.9,Machine Intelligence Group +AI14019,Data Analyst,64631,EUR,54936,EN,CT,France,L,France,50,"Azure, Deep Learning, Scala, Computer Vision",Master,1,Healthcare,2024-07-28,2024-09-18,665,9.9,Smart Analytics +AI14020,AI Specialist,92162,USD,92162,EN,FT,Denmark,S,Denmark,0,"GCP, Data Visualization, Spark",PhD,0,Gaming,2024-06-16,2024-08-26,1011,9.5,Future Systems +AI14021,AI Product Manager,110327,USD,110327,MI,FT,Ireland,M,Ireland,100,"Tableau, Hadoop, Java, Spark, Deep Learning",Bachelor,2,Consulting,2024-09-18,2024-10-29,1272,7.4,Quantum Computing Inc +AI14022,Robotics Engineer,102765,USD,102765,MI,FL,Denmark,S,Denmark,0,"Linux, Git, Tableau",Bachelor,3,Technology,2025-02-10,2025-03-29,1076,8.5,DataVision Ltd +AI14023,Deep Learning Engineer,91759,USD,91759,EN,CT,United States,M,South Africa,100,"R, SQL, Hadoop",PhD,0,Automotive,2024-01-09,2024-03-01,2033,5,Digital Transformation LLC +AI14024,AI Product Manager,159836,USD,159836,EX,CT,Ireland,L,United States,50,"GCP, SQL, Hadoop",PhD,17,Consulting,2024-09-19,2024-11-09,2184,5.4,DataVision Ltd +AI14025,AI Software Engineer,120984,CHF,108886,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Kubernetes, AWS, MLOps, SQL",Associate,1,Real Estate,2024-12-20,2025-02-11,658,5.3,Predictive Systems +AI14026,Data Scientist,159881,USD,159881,SE,PT,Ireland,L,Ireland,0,"Scala, PyTorch, Azure, AWS, Statistics",Bachelor,5,Telecommunications,2025-04-07,2025-05-31,2464,6.7,Digital Transformation LLC +AI14027,NLP Engineer,89150,JPY,9806500,EN,FL,Japan,L,Japan,0,"Git, GCP, Mathematics, PyTorch, TensorFlow",Master,1,Gaming,2024-02-13,2024-04-24,691,5.7,Autonomous Tech +AI14028,AI Consultant,67892,EUR,57708,MI,CT,France,S,France,100,"Kubernetes, Docker, Java",Master,3,Finance,2025-03-14,2025-04-01,1181,5.6,Quantum Computing Inc +AI14029,ML Ops Engineer,92548,GBP,69411,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Mathematics, Computer Vision, R",Master,1,Transportation,2024-09-14,2024-11-16,1462,5.9,Neural Networks Co +AI14030,Head of AI,53496,USD,53496,EN,FT,South Korea,S,Israel,0,"Deep Learning, Python, Tableau",Master,1,Energy,2024-11-03,2024-11-21,1703,9,Cognitive Computing +AI14031,Computer Vision Engineer,70599,EUR,60009,MI,FL,Austria,S,Colombia,50,"Java, Scala, Azure",Associate,3,Gaming,2025-02-16,2025-04-22,661,6.9,Quantum Computing Inc +AI14032,ML Ops Engineer,61691,EUR,52437,MI,CT,Austria,S,Austria,100,"Kubernetes, Computer Vision, Java",Master,4,Finance,2024-06-22,2024-08-10,1223,9,TechCorp Inc +AI14033,Data Analyst,128526,USD,128526,SE,FL,Ireland,L,Ireland,50,"AWS, SQL, GCP, Java",Master,9,Gaming,2024-01-21,2024-02-16,2257,5.5,Smart Analytics +AI14034,Autonomous Systems Engineer,211888,JPY,23307680,EX,FT,Japan,M,Japan,50,"Linux, MLOps, Azure, Hadoop, Spark",Associate,14,Energy,2024-09-08,2024-10-15,2247,6.9,Predictive Systems +AI14035,Robotics Engineer,111691,CAD,139614,SE,FL,Canada,S,Canada,50,"Scala, Git, R, AWS",Bachelor,6,Telecommunications,2025-03-28,2025-05-12,1360,10,AI Innovations +AI14036,Data Scientist,38446,USD,38446,SE,PT,India,S,India,100,"Docker, Python, TensorFlow, GCP",Associate,9,Government,2024-10-08,2024-11-18,1097,5.3,TechCorp Inc +AI14037,NLP Engineer,90939,CAD,113674,MI,CT,Canada,L,Canada,50,"SQL, Data Visualization, MLOps, Git, Kubernetes",Master,4,Finance,2024-05-03,2024-06-16,592,9.7,Neural Networks Co +AI14038,AI Software Engineer,89119,CAD,111399,MI,FL,Canada,S,Canada,100,"R, Data Visualization, Statistics, Scala",Master,2,Real Estate,2024-03-15,2024-05-22,805,6.7,AI Innovations +AI14039,Principal Data Scientist,334067,USD,334067,EX,FT,Norway,L,Norway,50,"Python, Statistics, Git",Master,11,Media,2025-02-20,2025-03-12,929,9.1,Digital Transformation LLC +AI14040,Head of AI,168122,USD,168122,EX,FT,South Korea,S,South Korea,0,"Mathematics, Linux, Scala, Statistics, SQL",PhD,12,Manufacturing,2025-01-15,2025-03-21,2195,6.3,Neural Networks Co +AI14041,ML Ops Engineer,130674,CHF,117607,SE,PT,Switzerland,S,Switzerland,0,"Azure, Python, Tableau, GCP",Associate,9,Telecommunications,2025-01-05,2025-02-15,2192,5.3,TechCorp Inc +AI14042,Research Scientist,147848,EUR,125671,EX,CT,Austria,S,Austria,50,"Java, Azure, GCP",PhD,19,Automotive,2024-01-23,2024-02-11,1992,9.4,Neural Networks Co +AI14043,Data Engineer,206878,CHF,186190,EX,PT,Switzerland,M,United States,50,"Linux, TensorFlow, Python, Deep Learning",PhD,10,Telecommunications,2024-02-25,2024-03-27,2374,9.9,Neural Networks Co +AI14044,ML Ops Engineer,120770,USD,120770,MI,FT,Denmark,S,Denmark,0,"Statistics, Python, Computer Vision, PyTorch",Bachelor,4,Manufacturing,2025-02-20,2025-03-08,1180,7.4,Cloud AI Solutions +AI14045,ML Ops Engineer,209060,CAD,261325,EX,CT,Canada,S,Canada,50,"TensorFlow, Kubernetes, Scala",Associate,17,Technology,2024-12-02,2025-01-27,600,9.1,Predictive Systems +AI14046,Robotics Engineer,55846,USD,55846,EN,PT,Ireland,S,Ireland,0,"Deep Learning, Data Visualization, Tableau, Mathematics",Associate,1,Consulting,2024-12-05,2025-01-12,1994,6.8,TechCorp Inc +AI14047,Autonomous Systems Engineer,96258,USD,96258,MI,FL,Ireland,M,Ireland,50,"Scala, Data Visualization, Azure, NLP, Git",Associate,3,Manufacturing,2025-01-12,2025-01-28,1073,8,Machine Intelligence Group +AI14048,Principal Data Scientist,76228,AUD,102908,EN,CT,Australia,L,Australia,100,"SQL, Git, PyTorch, Tableau, Kubernetes",Bachelor,1,Government,2024-05-08,2024-06-03,1156,7.1,Autonomous Tech +AI14049,AI Research Scientist,202209,USD,202209,SE,PT,Norway,L,Estonia,100,"TensorFlow, Computer Vision, SQL, Java, Linux",Bachelor,6,Gaming,2025-04-17,2025-06-21,1599,6.4,TechCorp Inc +AI14050,Autonomous Systems Engineer,106972,CHF,96275,MI,PT,Switzerland,S,Egypt,100,"MLOps, Linux, Tableau, PyTorch, Hadoop",PhD,4,Finance,2024-01-09,2024-03-09,636,7.1,Advanced Robotics +AI14051,Computer Vision Engineer,79068,USD,79068,EX,FT,China,S,China,50,"Tableau, Deep Learning, PyTorch",PhD,16,Energy,2024-01-06,2024-02-04,1101,9.8,Quantum Computing Inc +AI14052,Autonomous Systems Engineer,101691,CHF,91522,MI,PT,Switzerland,S,Switzerland,50,"Java, Scala, Git, Statistics",Bachelor,2,Transportation,2024-09-01,2024-10-13,1488,5.8,Autonomous Tech +AI14053,AI Software Engineer,113366,SGD,147376,MI,PT,Singapore,L,Singapore,100,"Java, NLP, Spark, TensorFlow, Azure",Master,4,Manufacturing,2024-11-11,2024-12-04,772,8.5,Quantum Computing Inc +AI14054,ML Ops Engineer,309967,GBP,232475,EX,FL,United Kingdom,L,United Kingdom,50,"SQL, Java, Data Visualization, Hadoop, Computer Vision",Bachelor,18,Technology,2025-01-08,2025-02-20,830,6.8,Quantum Computing Inc +AI14055,AI Research Scientist,137461,EUR,116842,SE,CT,Netherlands,S,Luxembourg,50,"GCP, Python, TensorFlow, R",Associate,9,Healthcare,2025-01-06,2025-03-09,1144,8.2,AI Innovations +AI14056,AI Software Engineer,87443,USD,87443,EN,CT,United States,L,United States,0,"Computer Vision, Hadoop, Python, Kubernetes, Docker",Associate,0,Finance,2024-11-12,2024-12-06,2171,8.1,Digital Transformation LLC +AI14057,ML Ops Engineer,116059,SGD,150877,MI,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Azure, Computer Vision, Git",PhD,4,Retail,2024-07-05,2024-08-28,810,9.1,Advanced Robotics +AI14058,Principal Data Scientist,82475,USD,82475,EN,CT,Denmark,S,Netherlands,0,"GCP, SQL, Spark, Java, Mathematics",Associate,1,Retail,2025-02-19,2025-03-24,1099,9.4,Neural Networks Co +AI14059,Machine Learning Researcher,134959,USD,134959,SE,PT,Ireland,M,Ireland,50,"Git, Azure, MLOps, Linux",Bachelor,8,Finance,2024-02-26,2024-04-03,1639,9.7,AI Innovations +AI14060,NLP Engineer,295543,USD,295543,EX,FL,United States,L,Portugal,0,"SQL, Scala, Mathematics, Azure, Hadoop",Associate,14,Manufacturing,2024-03-10,2024-04-19,739,8.7,Smart Analytics +AI14061,Head of AI,69846,USD,69846,EN,FL,United States,M,Estonia,100,"Java, PyTorch, Scala, SQL",Associate,1,Finance,2024-11-09,2024-12-29,2048,8.7,DataVision Ltd +AI14062,Data Analyst,129073,JPY,14198030,SE,CT,Japan,L,Japan,100,"Linux, Data Visualization, Kubernetes, NLP, R",Bachelor,6,Transportation,2024-03-12,2024-04-27,1605,8.8,Machine Intelligence Group +AI14063,Principal Data Scientist,60030,EUR,51026,EN,CT,France,L,France,0,"Python, Java, Azure",PhD,1,Healthcare,2024-02-09,2024-04-13,810,5.2,Smart Analytics +AI14064,Machine Learning Engineer,90890,CAD,113613,MI,FL,Canada,L,Romania,50,"Statistics, Kubernetes, Python, TensorFlow",Master,2,Real Estate,2024-04-19,2024-06-12,1477,5.8,Neural Networks Co +AI14065,AI Architect,166381,USD,166381,SE,PT,Ireland,L,Germany,100,"Java, Data Visualization, AWS, Docker, Computer Vision",Bachelor,7,Media,2024-08-24,2024-09-19,2450,7.8,Smart Analytics +AI14066,AI Product Manager,281704,USD,281704,EX,FL,Ireland,L,New Zealand,100,"Computer Vision, Azure, Spark, AWS",Master,17,Energy,2024-09-24,2024-11-10,2033,9.6,DeepTech Ventures +AI14067,Computer Vision Engineer,132917,USD,132917,SE,FT,Ireland,S,Ireland,50,"SQL, Git, Python",Associate,7,Real Estate,2024-10-05,2024-11-07,980,5.5,AI Innovations +AI14068,AI Product Manager,29350,USD,29350,MI,FL,India,S,India,100,"Kubernetes, PyTorch, Hadoop, MLOps, Spark",Master,3,Education,2024-07-19,2024-09-18,1755,8.1,Quantum Computing Inc +AI14069,Data Analyst,72631,USD,72631,EN,FL,Norway,S,Norway,0,"Mathematics, Statistics, Kubernetes, Azure",PhD,0,Energy,2025-03-23,2025-04-09,1392,6.1,DataVision Ltd +AI14070,AI Research Scientist,57268,USD,57268,SE,FT,China,M,China,50,"TensorFlow, SQL, Data Visualization, GCP, Azure",Master,5,Retail,2024-02-18,2024-04-01,1414,7.5,Autonomous Tech +AI14071,AI Research Scientist,83126,CHF,74813,EN,FL,Switzerland,L,Sweden,0,"Python, TensorFlow, Scala, Kubernetes, Computer Vision",PhD,1,Transportation,2024-09-19,2024-10-28,1399,7.1,Advanced Robotics +AI14072,AI Product Manager,114645,USD,114645,MI,FL,Norway,M,Norway,0,"Git, SQL, MLOps",Master,4,Transportation,2024-11-23,2024-12-10,2416,6,DeepTech Ventures +AI14073,ML Ops Engineer,63688,USD,63688,EN,FT,Israel,S,Israel,50,"Data Visualization, Git, Computer Vision",PhD,1,Real Estate,2024-03-03,2024-04-06,1831,8.3,Advanced Robotics +AI14074,Research Scientist,122807,EUR,104386,SE,FT,Germany,S,Switzerland,0,"GCP, Docker, Statistics",Master,8,Healthcare,2025-02-26,2025-04-20,1672,6.2,Quantum Computing Inc +AI14075,Deep Learning Engineer,102173,USD,102173,SE,PT,Ireland,S,Ireland,100,"Azure, Linux, Git, Java, TensorFlow",Associate,7,Automotive,2024-07-29,2024-09-13,795,8.7,Quantum Computing Inc +AI14076,Computer Vision Engineer,139906,GBP,104930,SE,FT,United Kingdom,S,United Kingdom,0,"Git, Data Visualization, AWS, Computer Vision",PhD,8,Transportation,2024-12-23,2025-02-17,1359,8.9,DeepTech Ventures +AI14077,AI Architect,161399,JPY,17753890,EX,PT,Japan,S,Japan,100,"PyTorch, R, Kubernetes",Associate,15,Transportation,2024-12-26,2025-02-07,945,8.9,Advanced Robotics +AI14078,Principal Data Scientist,104420,EUR,88757,SE,PT,Austria,S,Netherlands,50,"Data Visualization, Statistics, Tableau",PhD,9,Healthcare,2025-04-11,2025-04-30,624,7.7,Quantum Computing Inc +AI14079,AI Software Engineer,88018,EUR,74815,MI,FT,Austria,L,Austria,100,"Spark, GCP, Scala",Bachelor,4,Gaming,2024-08-17,2024-09-12,1130,5.3,Smart Analytics +AI14080,AI Consultant,65855,USD,65855,SE,PT,China,M,China,0,"Java, Linux, MLOps",Associate,6,Automotive,2024-10-08,2024-11-26,2119,8.8,Cognitive Computing +AI14081,AI Software Engineer,153926,JPY,16931860,SE,PT,Japan,L,Japan,0,"Java, GCP, Mathematics, Docker, Python",Bachelor,7,Gaming,2024-02-27,2024-03-31,1128,8.4,Cloud AI Solutions +AI14082,Autonomous Systems Engineer,133543,SGD,173606,MI,FT,Singapore,L,Singapore,0,"NLP, GCP, Azure, Scala, Statistics",Bachelor,3,Real Estate,2024-10-18,2024-12-25,653,7.3,Machine Intelligence Group +AI14083,Machine Learning Researcher,132804,USD,132804,SE,PT,United States,M,United States,50,"Linux, Python, SQL, NLP, Computer Vision",Master,8,Transportation,2024-11-19,2024-12-14,965,8.5,Cloud AI Solutions +AI14084,Head of AI,185999,SGD,241799,EX,FT,Singapore,M,Singapore,0,"Git, Python, Statistics",Associate,11,Consulting,2024-03-07,2024-05-07,1393,8.7,Quantum Computing Inc +AI14085,Data Scientist,160037,USD,160037,SE,FT,Denmark,M,Denmark,100,"Java, Spark, Computer Vision",Bachelor,5,Real Estate,2024-06-11,2024-07-20,2246,5.4,Algorithmic Solutions +AI14086,Data Scientist,71318,SGD,92713,MI,FT,Singapore,S,Singapore,50,"Spark, Linux, NLP, AWS",Master,2,Energy,2024-10-28,2024-11-21,1534,9.5,Cloud AI Solutions +AI14087,Data Analyst,210874,GBP,158156,EX,CT,United Kingdom,L,United Kingdom,100,"SQL, PyTorch, Azure, Scala, Java",Bachelor,14,Manufacturing,2024-05-18,2024-07-18,551,9.9,Quantum Computing Inc +AI14088,Head of AI,171409,EUR,145698,SE,FT,Netherlands,L,Netherlands,0,"Tableau, Git, Kubernetes, AWS, GCP",Bachelor,7,Gaming,2025-01-28,2025-03-20,2499,7,Advanced Robotics +AI14089,Deep Learning Engineer,41300,USD,41300,EN,FL,South Korea,S,Chile,100,"Scala, Hadoop, Data Visualization, Spark",Associate,0,Automotive,2024-02-10,2024-03-28,1754,8.5,DeepTech Ventures +AI14090,NLP Engineer,61734,USD,61734,SE,FT,China,M,China,50,"Kubernetes, Scala, AWS",Associate,6,Automotive,2024-12-19,2025-01-07,2073,7.4,Smart Analytics +AI14091,Machine Learning Engineer,171718,CAD,214648,EX,FL,Canada,L,Romania,0,"GCP, PyTorch, Statistics, Spark",PhD,19,Media,2024-03-27,2024-04-11,1548,6.2,Advanced Robotics +AI14092,Research Scientist,72603,JPY,7986330,EN,FT,Japan,S,Japan,100,"NLP, Kubernetes, Data Visualization",Master,1,Telecommunications,2024-02-27,2024-04-23,1185,8.5,TechCorp Inc +AI14093,AI Research Scientist,147559,SGD,191827,SE,FT,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization, MLOps, NLP",PhD,7,Telecommunications,2025-03-05,2025-04-17,2433,6.6,Advanced Robotics +AI14094,Principal Data Scientist,117163,JPY,12887930,MI,PT,Japan,L,Spain,50,"SQL, Python, Data Visualization",Bachelor,4,Gaming,2024-01-27,2024-02-15,2052,7.4,Quantum Computing Inc +AI14095,Research Scientist,112263,EUR,95424,MI,FL,Netherlands,M,Netherlands,0,"Hadoop, R, TensorFlow",PhD,2,Energy,2024-12-21,2025-02-02,2463,9.3,Cloud AI Solutions +AI14096,AI Software Engineer,29429,USD,29429,EN,FL,China,M,China,0,"GCP, R, Statistics, Spark",Bachelor,1,Gaming,2024-12-16,2025-01-21,1928,8.6,Cloud AI Solutions +AI14097,Head of AI,125096,USD,125096,MI,FL,United States,L,United States,50,"Tableau, Scala, Kubernetes",PhD,4,Healthcare,2025-04-16,2025-06-12,896,6.1,Digital Transformation LLC +AI14098,Autonomous Systems Engineer,290902,JPY,31999220,EX,FT,Japan,L,Japan,50,"Hadoop, Java, R, Kubernetes",Bachelor,12,Education,2024-06-04,2024-07-30,2175,5.4,Neural Networks Co +AI14099,Deep Learning Engineer,139674,USD,139674,SE,FL,Sweden,M,Egypt,100,"TensorFlow, PyTorch, Tableau, Statistics, Mathematics",PhD,8,Transportation,2024-05-19,2024-07-31,978,5.3,Digital Transformation LLC +AI14100,Data Engineer,112288,USD,112288,SE,FT,Ireland,S,Singapore,50,"Linux, Deep Learning, Kubernetes",PhD,7,Manufacturing,2024-12-20,2025-01-27,544,8.8,Machine Intelligence Group +AI14101,AI Specialist,55248,USD,55248,EX,CT,India,M,Mexico,50,"Tableau, Python, TensorFlow, AWS",PhD,16,Technology,2025-02-12,2025-03-02,1131,7,Smart Analytics +AI14102,Data Engineer,222488,USD,222488,SE,PT,Norway,L,Norway,0,"Scala, Computer Vision, Mathematics, R, NLP",Master,5,Technology,2025-02-12,2025-04-21,854,5.3,Quantum Computing Inc +AI14103,AI Software Engineer,186626,USD,186626,SE,PT,Norway,L,Denmark,100,"MLOps, SQL, Kubernetes",Associate,9,Education,2024-03-30,2024-05-07,1277,8.1,Quantum Computing Inc +AI14104,Deep Learning Engineer,262649,JPY,28891390,EX,FT,Japan,L,Japan,0,"Python, Kubernetes, Docker, TensorFlow",Master,17,Gaming,2024-10-01,2024-11-01,773,7.2,Machine Intelligence Group +AI14105,ML Ops Engineer,103455,USD,103455,MI,CT,United States,S,United States,50,"Azure, GCP, Statistics, MLOps, Python",Bachelor,3,Education,2024-07-06,2024-09-16,2487,6.3,DataVision Ltd +AI14106,Data Scientist,122416,USD,122416,MI,FL,Norway,M,Norway,0,"Kubernetes, Java, PyTorch, SQL, Spark",Bachelor,3,Education,2024-12-12,2025-01-02,1535,9.5,Autonomous Tech +AI14107,AI Product Manager,126398,SGD,164317,SE,FT,Singapore,L,Belgium,50,"GCP, Statistics, Hadoop, TensorFlow",Associate,9,Real Estate,2024-06-13,2024-07-11,2140,6.6,Machine Intelligence Group +AI14108,Deep Learning Engineer,104577,USD,104577,EN,PT,Denmark,L,Denmark,0,"SQL, Docker, Azure, R",Bachelor,0,Transportation,2025-02-06,2025-02-24,2202,8.4,Future Systems +AI14109,Machine Learning Researcher,222225,GBP,166669,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, PyTorch, Scala, Kubernetes",PhD,12,Automotive,2024-11-03,2025-01-11,2381,8.1,DataVision Ltd +AI14110,Head of AI,153799,EUR,130729,EX,CT,Netherlands,S,Netherlands,100,"AWS, Spark, Kubernetes, SQL, Linux",Associate,12,Consulting,2025-03-24,2025-05-08,508,7.2,Predictive Systems +AI14111,Machine Learning Engineer,77712,GBP,58284,EN,CT,United Kingdom,L,Hungary,0,"Python, Kubernetes, Computer Vision, Deep Learning, Tableau",Bachelor,1,Automotive,2024-01-31,2024-04-08,938,7.4,Cognitive Computing +AI14112,Data Analyst,68332,USD,68332,EN,CT,Finland,M,Indonesia,0,"Docker, PyTorch, Data Visualization, Linux, Git",Associate,1,Government,2024-03-11,2024-03-25,1373,9.4,Digital Transformation LLC +AI14113,AI Consultant,81904,USD,81904,SE,FT,China,L,China,50,"GCP, Git, Mathematics, Data Visualization",Master,7,Technology,2024-11-08,2024-11-26,832,8.5,Machine Intelligence Group +AI14114,ML Ops Engineer,67175,GBP,50381,EN,PT,United Kingdom,M,United Kingdom,50,"Python, Kubernetes, SQL",Associate,1,Gaming,2024-10-29,2024-12-24,2341,6.8,Machine Intelligence Group +AI14115,Computer Vision Engineer,71427,USD,71427,EN,PT,Finland,L,South Africa,0,"Azure, PyTorch, Tableau",PhD,0,Healthcare,2024-01-21,2024-03-15,1801,7.8,Cloud AI Solutions +AI14116,Principal Data Scientist,163454,AUD,220663,EX,PT,Australia,S,Thailand,50,"Python, GCP, NLP",PhD,10,Automotive,2024-03-24,2024-05-30,2143,9.6,Algorithmic Solutions +AI14117,Robotics Engineer,70727,EUR,60118,MI,FL,Germany,S,Germany,0,"Linux, Computer Vision, Tableau, Azure, Python",PhD,4,Manufacturing,2025-04-21,2025-06-28,1474,8.3,Cognitive Computing +AI14118,Machine Learning Researcher,136745,SGD,177769,EX,PT,Singapore,S,Singapore,0,"Scala, Hadoop, Python, TensorFlow",PhD,14,Telecommunications,2024-01-26,2024-03-28,1093,5.3,DeepTech Ventures +AI14119,Autonomous Systems Engineer,122312,USD,122312,SE,PT,United States,M,Canada,50,"SQL, Git, AWS, GCP",Master,8,Manufacturing,2024-02-11,2024-04-21,2457,9.7,Quantum Computing Inc +AI14120,ML Ops Engineer,88018,SGD,114423,EN,CT,Singapore,L,Singapore,50,"Mathematics, Deep Learning, Java, Python, AWS",PhD,1,Education,2024-08-14,2024-10-25,2109,8.2,Predictive Systems +AI14121,AI Architect,107618,EUR,91475,SE,FT,France,S,France,0,"SQL, PyTorch, Tableau, Hadoop, Azure",PhD,8,Healthcare,2024-08-30,2024-10-27,2427,5.6,Advanced Robotics +AI14122,NLP Engineer,82542,GBP,61907,EN,PT,United Kingdom,L,United Kingdom,50,"Linux, Java, Scala, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-02,954,5.8,Future Systems +AI14123,NLP Engineer,37476,USD,37476,EN,PT,China,L,China,50,"Java, PyTorch, TensorFlow, Deep Learning",Associate,1,Consulting,2024-08-13,2024-09-10,2224,9.9,DeepTech Ventures +AI14124,Principal Data Scientist,24095,USD,24095,EN,PT,India,M,India,100,"Kubernetes, PyTorch, TensorFlow, Mathematics",Master,1,Healthcare,2024-05-30,2024-07-16,2200,6.9,Cognitive Computing +AI14125,Research Scientist,295505,GBP,221629,EX,FL,United Kingdom,L,Italy,50,"Python, Deep Learning, Java, Azure, GCP",Bachelor,19,Automotive,2024-08-27,2024-09-17,1366,7,Autonomous Tech +AI14126,Deep Learning Engineer,85346,JPY,9388060,EN,PT,Japan,L,Japan,100,"Scala, Java, Python, MLOps, TensorFlow",Associate,1,Manufacturing,2024-09-14,2024-11-16,1248,8.7,DeepTech Ventures +AI14127,Principal Data Scientist,142448,USD,142448,SE,PT,Finland,L,Finland,50,"Kubernetes, SQL, AWS, Git",Bachelor,7,Consulting,2024-08-21,2024-09-18,559,7.9,Predictive Systems +AI14128,ML Ops Engineer,60149,USD,60149,EN,CT,Sweden,L,Sweden,100,"Azure, SQL, TensorFlow",Associate,1,Government,2024-08-19,2024-10-11,2102,6,Future Systems +AI14129,Principal Data Scientist,92230,USD,92230,MI,FL,Israel,M,Israel,100,"Azure, Python, Java, Computer Vision",PhD,3,Gaming,2024-11-15,2024-12-01,1355,5.7,Smart Analytics +AI14130,Data Engineer,93635,EUR,79590,SE,CT,Austria,S,Austria,100,"Scala, GCP, Hadoop, Statistics",Associate,9,Consulting,2024-11-01,2024-11-26,568,7.3,Advanced Robotics +AI14131,NLP Engineer,109810,GBP,82358,SE,FT,United Kingdom,M,United Kingdom,50,"Mathematics, AWS, NLP",Master,9,Transportation,2024-09-29,2024-10-15,1683,9.8,Algorithmic Solutions +AI14132,Data Scientist,268003,EUR,227803,EX,CT,Austria,L,Austria,0,"R, Hadoop, Scala",PhD,14,Media,2024-04-12,2024-06-15,1657,6.2,Quantum Computing Inc +AI14133,AI Consultant,241976,EUR,205680,EX,FT,France,L,France,100,"Kubernetes, SQL, NLP, Java, Hadoop",Master,11,Gaming,2025-02-01,2025-03-26,2290,6.1,Predictive Systems +AI14134,Data Scientist,60314,GBP,45236,EN,PT,United Kingdom,M,Ireland,50,"Kubernetes, Git, Computer Vision, Hadoop",Master,0,Telecommunications,2024-10-28,2024-12-16,2263,8.5,Cloud AI Solutions +AI14135,Autonomous Systems Engineer,34598,USD,34598,MI,FT,China,M,Russia,100,"Linux, Mathematics, Java",Bachelor,2,Consulting,2025-03-08,2025-04-17,1270,6.7,Quantum Computing Inc +AI14136,Data Analyst,174612,USD,174612,EX,CT,Israel,M,Israel,100,"R, Git, Scala, Python, Mathematics",Associate,17,Healthcare,2024-04-20,2024-06-14,1197,9.4,Neural Networks Co +AI14137,AI Research Scientist,119374,USD,119374,SE,CT,Denmark,S,India,50,"Java, R, Data Visualization, Azure",Master,9,Transportation,2024-09-25,2024-10-15,1604,6.3,Smart Analytics +AI14138,Research Scientist,121158,GBP,90869,SE,PT,United Kingdom,M,Kenya,0,"PyTorch, TensorFlow, Computer Vision, Azure, Git",PhD,9,Manufacturing,2025-03-19,2025-05-25,1718,8.2,AI Innovations +AI14139,Robotics Engineer,126193,USD,126193,SE,FL,Ireland,M,Kenya,50,"TensorFlow, Linux, Java",Bachelor,5,Consulting,2024-10-05,2024-11-22,530,9.7,Predictive Systems +AI14140,ML Ops Engineer,41111,USD,41111,MI,FT,China,M,China,100,"SQL, Java, Git, Kubernetes, PyTorch",PhD,2,Consulting,2024-01-17,2024-03-01,2487,9.7,DataVision Ltd +AI14141,Autonomous Systems Engineer,22562,USD,22562,EN,CT,India,S,India,0,"Tableau, TensorFlow, Kubernetes",Bachelor,0,Retail,2024-12-16,2025-01-11,1698,7.5,TechCorp Inc +AI14142,Data Scientist,219263,USD,219263,EX,FT,Sweden,S,Sweden,50,"Azure, Mathematics, Data Visualization, Git",Master,14,Manufacturing,2024-11-06,2024-12-18,1340,5.1,TechCorp Inc +AI14143,Data Analyst,96400,SGD,125320,MI,CT,Singapore,S,Singapore,0,"Tableau, Scala, Python, TensorFlow",Bachelor,4,Telecommunications,2024-12-06,2024-12-29,927,6,Autonomous Tech +AI14144,Autonomous Systems Engineer,128818,USD,128818,SE,PT,Ireland,M,Norway,0,"GCP, Data Visualization, Computer Vision",Master,7,Telecommunications,2024-02-07,2024-03-05,1702,7.8,Neural Networks Co +AI14145,NLP Engineer,216334,USD,216334,EX,PT,Israel,M,Israel,50,"PyTorch, SQL, MLOps, TensorFlow, AWS",Bachelor,12,Real Estate,2024-02-04,2024-02-19,1082,6.2,Quantum Computing Inc +AI14146,Machine Learning Researcher,94530,USD,94530,MI,FT,United States,S,United States,100,"Git, Docker, Data Visualization",Bachelor,2,Manufacturing,2025-04-23,2025-06-24,2094,6.1,AI Innovations +AI14147,Head of AI,89370,EUR,75965,MI,FL,Germany,M,Germany,0,"TensorFlow, Java, Mathematics",PhD,3,Retail,2024-11-14,2025-01-26,650,8.2,Cloud AI Solutions +AI14148,Data Engineer,127066,AUD,171539,SE,FL,Australia,M,Kenya,50,"Python, AWS, Scala, TensorFlow, Git",PhD,6,Transportation,2025-01-12,2025-03-13,1023,7.8,Cognitive Computing +AI14149,Principal Data Scientist,110035,EUR,93530,MI,FT,Netherlands,L,Netherlands,100,"SQL, Python, Scala",Associate,4,Automotive,2024-09-15,2024-11-14,1887,7.8,TechCorp Inc +AI14150,Machine Learning Researcher,139926,USD,139926,EX,FT,South Korea,M,South Korea,100,"PyTorch, Git, TensorFlow, R, Computer Vision",Master,12,Education,2024-01-04,2024-02-04,1739,6.9,Smart Analytics +AI14151,Machine Learning Engineer,77667,USD,77667,MI,FL,Finland,S,Finland,0,"Statistics, GCP, NLP",Associate,4,Gaming,2024-08-16,2024-10-20,1023,8.6,Algorithmic Solutions +AI14152,Deep Learning Engineer,178132,USD,178132,EX,FT,Finland,M,United States,50,"Linux, Data Visualization, Kubernetes, TensorFlow, Python",Associate,16,Finance,2024-01-04,2024-01-27,505,5.8,Autonomous Tech +AI14153,AI Research Scientist,86792,EUR,73773,MI,PT,Austria,S,Austria,0,"Data Visualization, PyTorch, Spark, Kubernetes",Associate,3,Telecommunications,2025-02-25,2025-04-13,1744,7.6,Advanced Robotics +AI14154,Autonomous Systems Engineer,316782,CHF,285104,EX,FT,Switzerland,L,Argentina,50,"MLOps, Linux, Java",Associate,16,Real Estate,2024-06-11,2024-08-12,579,5.9,Predictive Systems +AI14155,Machine Learning Engineer,96906,USD,96906,MI,FT,Ireland,L,Ireland,50,"Linux, GCP, Kubernetes, AWS",Master,4,Real Estate,2024-09-21,2024-11-23,2050,7.7,Predictive Systems +AI14156,Computer Vision Engineer,69233,SGD,90003,EN,PT,Singapore,M,Singapore,50,"Linux, Docker, Tableau",Master,0,Gaming,2024-02-26,2024-04-03,1093,6.5,Future Systems +AI14157,Data Engineer,108244,EUR,92007,SE,FT,Netherlands,S,Netherlands,50,"R, NLP, Azure",Bachelor,8,Telecommunications,2024-03-02,2024-03-29,1838,7.9,Digital Transformation LLC +AI14158,Deep Learning Engineer,93348,EUR,79346,MI,FT,Austria,L,Austria,100,"Linux, Java, Spark, Python",Bachelor,2,Finance,2024-03-20,2024-04-12,1098,8.3,Autonomous Tech +AI14159,AI Product Manager,79789,USD,79789,EN,CT,United States,M,India,0,"Spark, Linux, Tableau, Computer Vision",Associate,1,Healthcare,2024-07-17,2024-09-15,618,8.8,Cloud AI Solutions +AI14160,Machine Learning Engineer,69277,JPY,7620470,EN,PT,Japan,L,Hungary,100,"Kubernetes, Scala, Spark",Master,1,Automotive,2024-04-20,2024-06-03,1022,7,Predictive Systems +AI14161,AI Research Scientist,182548,USD,182548,EX,PT,Norway,S,Vietnam,0,"Python, GCP, MLOps, Scala, Hadoop",Master,17,Telecommunications,2024-08-07,2024-09-01,1375,5.5,Autonomous Tech +AI14162,Head of AI,80971,EUR,68825,MI,CT,Netherlands,S,Norway,100,"GCP, Mathematics, Azure, Linux, NLP",Associate,2,Automotive,2025-03-11,2025-04-24,554,9.9,Quantum Computing Inc +AI14163,Deep Learning Engineer,84774,USD,84774,EN,FT,Norway,S,Spain,0,"MLOps, Python, SQL, Statistics, Azure",PhD,1,Real Estate,2024-07-25,2024-09-06,1881,5.2,DataVision Ltd +AI14164,ML Ops Engineer,88260,EUR,75021,MI,PT,Austria,M,Austria,100,"Docker, Mathematics, Scala, Statistics, Linux",Master,3,Consulting,2024-06-15,2024-08-14,2124,8.7,Future Systems +AI14165,Research Scientist,105933,USD,105933,EN,FL,Norway,L,Norway,100,"Git, Mathematics, Data Visualization, AWS",PhD,0,Technology,2025-03-14,2025-05-15,2088,6.2,Algorithmic Solutions +AI14166,AI Product Manager,252207,USD,252207,EX,FT,Norway,M,Norway,0,"Kubernetes, Azure, MLOps, Computer Vision, NLP",Master,15,Automotive,2025-02-08,2025-02-22,1166,8.9,Algorithmic Solutions +AI14167,AI Consultant,24594,USD,24594,EN,PT,India,L,India,0,"Python, AWS, SQL",Master,0,Transportation,2024-05-11,2024-07-01,1973,8.1,AI Innovations +AI14168,Head of AI,133353,SGD,173359,MI,FT,Singapore,L,Singapore,50,"Mathematics, Computer Vision, NLP, Tableau, Python",Master,2,Media,2024-06-25,2024-07-29,1940,8.6,Machine Intelligence Group +AI14169,ML Ops Engineer,116932,USD,116932,SE,FT,Israel,M,Israel,100,"Tableau, TensorFlow, Computer Vision, Spark, Statistics",Bachelor,6,Gaming,2025-02-03,2025-03-05,898,6.2,Algorithmic Solutions +AI14170,AI Research Scientist,169884,USD,169884,EX,FL,South Korea,L,South Korea,0,"Kubernetes, R, Python",PhD,16,Technology,2024-07-12,2024-07-30,1070,7.1,Machine Intelligence Group +AI14171,AI Specialist,171722,JPY,18889420,EX,PT,Japan,M,Estonia,50,"Kubernetes, Git, Computer Vision, Deep Learning, Spark",Associate,12,Education,2024-02-26,2024-04-11,2486,9.9,Cloud AI Solutions +AI14172,AI Consultant,303831,USD,303831,EX,FL,Norway,M,Norway,0,"AWS, MLOps, R",Bachelor,18,Automotive,2025-03-30,2025-06-04,1522,8.3,Cognitive Computing +AI14173,NLP Engineer,28602,USD,28602,EN,FL,China,S,China,100,"Python, Spark, Docker",Associate,1,Gaming,2024-08-01,2024-09-28,1209,5.2,Autonomous Tech +AI14174,AI Specialist,267508,EUR,227382,EX,FL,Netherlands,M,Netherlands,100,"Kubernetes, Scala, Statistics, Azure, Tableau",Master,16,Retail,2025-03-05,2025-03-23,1209,9.6,Future Systems +AI14175,ML Ops Engineer,115925,EUR,98536,SE,FL,Austria,L,Russia,100,"Python, TensorFlow, Mathematics, PyTorch, Spark",Bachelor,8,Consulting,2024-02-12,2024-03-26,1614,9.3,Future Systems +AI14176,Data Analyst,80656,USD,80656,MI,PT,Finland,S,Kenya,100,"Python, Deep Learning, Azure, SQL, Git",PhD,2,Real Estate,2024-02-22,2024-04-10,1277,8.1,Future Systems +AI14177,Machine Learning Engineer,27562,USD,27562,EN,FL,India,M,India,0,"TensorFlow, Deep Learning, Tableau, Kubernetes",Master,1,Manufacturing,2024-07-29,2024-08-22,1304,6.8,Advanced Robotics +AI14178,Principal Data Scientist,192999,EUR,164049,EX,PT,Austria,S,Austria,50,"MLOps, NLP, Linux, TensorFlow",PhD,19,Gaming,2024-12-18,2025-02-07,701,8.5,Advanced Robotics +AI14179,AI Consultant,254016,JPY,27941760,EX,FT,Japan,M,Japan,0,"Python, Kubernetes, Mathematics, Deep Learning",Bachelor,17,Energy,2024-03-14,2024-05-22,1852,9.1,Future Systems +AI14180,Data Analyst,63794,EUR,54225,EN,FT,Austria,S,Austria,50,"PyTorch, R, NLP, Python",Master,1,Healthcare,2024-08-25,2024-10-24,1738,8.1,Autonomous Tech +AI14181,Machine Learning Engineer,82068,GBP,61551,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, PyTorch, Spark, Deep Learning, Computer Vision",PhD,1,Consulting,2024-09-09,2024-10-21,1023,6.7,Autonomous Tech +AI14182,AI Product Manager,68103,CAD,85129,EN,CT,Canada,S,Canada,50,"Data Visualization, Docker, Python, Computer Vision, Hadoop",Bachelor,1,Automotive,2024-01-07,2024-02-29,2000,6.3,DataVision Ltd +AI14183,NLP Engineer,108322,USD,108322,SE,FT,Israel,S,Israel,100,"Python, TensorFlow, MLOps",Associate,5,Government,2024-02-23,2024-04-06,1554,8.9,Predictive Systems +AI14184,Principal Data Scientist,80835,USD,80835,EN,FT,Norway,M,Norway,0,"Statistics, Scala, Linux",Bachelor,0,Automotive,2024-07-20,2024-08-17,1986,5.4,AI Innovations +AI14185,Head of AI,114660,USD,114660,SE,CT,Ireland,S,Ireland,50,"R, Git, Deep Learning, SQL",Associate,8,Automotive,2025-02-08,2025-03-25,2061,9.5,TechCorp Inc +AI14186,AI Consultant,106582,GBP,79937,MI,CT,United Kingdom,L,Ukraine,100,"Hadoop, Scala, Computer Vision, Python",Master,3,Consulting,2024-09-12,2024-11-02,2032,8.1,Digital Transformation LLC +AI14187,Machine Learning Engineer,96014,EUR,81612,MI,CT,Germany,S,Germany,50,"Scala, Java, TensorFlow, Statistics, Deep Learning",PhD,4,Media,2024-09-16,2024-11-02,1645,8.4,Predictive Systems +AI14188,Robotics Engineer,91689,USD,91689,MI,CT,Ireland,M,Ireland,100,"PyTorch, TensorFlow, Mathematics, Statistics",Master,3,Technology,2024-02-18,2024-04-18,996,7,Future Systems +AI14189,Machine Learning Researcher,64501,SGD,83851,EN,FT,Singapore,S,Singapore,0,"Linux, Deep Learning, PyTorch, Mathematics, NLP",PhD,1,Real Estate,2024-05-01,2024-06-12,1800,9.5,DataVision Ltd +AI14190,NLP Engineer,75701,CAD,94626,EN,PT,Canada,L,Canada,50,"AWS, Git, Statistics",PhD,0,Finance,2024-04-19,2024-05-03,1321,5.8,Neural Networks Co +AI14191,Head of AI,45437,USD,45437,EN,PT,Israel,S,Israel,50,"Git, Deep Learning, Kubernetes",PhD,0,Automotive,2025-04-27,2025-06-06,1697,6.6,Cloud AI Solutions +AI14192,Machine Learning Researcher,74737,USD,74737,EN,PT,Finland,M,Germany,0,"GCP, Java, R, Docker",PhD,0,Media,2024-05-13,2024-07-15,2338,9.9,DataVision Ltd +AI14193,Computer Vision Engineer,57174,USD,57174,EN,FL,Finland,L,Finland,0,"NLP, SQL, Java, AWS",Master,1,Retail,2024-05-01,2024-07-06,1347,6.9,Cloud AI Solutions +AI14194,Research Scientist,152694,USD,152694,EX,PT,Sweden,M,Sweden,0,"Data Visualization, AWS, Java, SQL",Associate,14,Healthcare,2024-03-28,2024-05-23,776,9.2,Algorithmic Solutions +AI14195,Head of AI,118599,EUR,100809,SE,PT,France,L,Philippines,100,"Kubernetes, Scala, Tableau, GCP, Data Visualization",Bachelor,9,Automotive,2024-10-30,2024-11-20,1006,5.2,TechCorp Inc +AI14196,Research Scientist,87706,CHF,78935,EN,FL,Switzerland,S,Switzerland,0,"Kubernetes, NLP, GCP, Linux, Computer Vision",Associate,0,Energy,2025-02-11,2025-03-29,1980,6,Quantum Computing Inc +AI14197,Machine Learning Researcher,88238,EUR,75002,MI,FT,France,M,France,0,"Azure, PyTorch, AWS, GCP",Associate,3,Telecommunications,2024-11-27,2024-12-19,1198,8.9,Future Systems +AI14198,AI Specialist,92582,USD,92582,SE,FT,South Korea,S,South Korea,0,"NLP, Statistics, Hadoop",PhD,5,Healthcare,2025-03-16,2025-04-14,1582,9.9,Algorithmic Solutions +AI14199,Data Analyst,38341,USD,38341,MI,FT,China,M,China,100,"Kubernetes, Python, Deep Learning, MLOps",Associate,3,Automotive,2024-10-29,2024-12-08,2212,7.7,Cloud AI Solutions +AI14200,AI Architect,40454,USD,40454,SE,FT,India,M,India,0,"R, Azure, Java",PhD,9,Automotive,2025-04-20,2025-06-07,1755,6.9,Future Systems +AI14201,Robotics Engineer,67022,SGD,87129,EN,CT,Singapore,M,Singapore,50,"SQL, Java, AWS",Master,1,Healthcare,2025-02-09,2025-03-16,1201,8.7,Quantum Computing Inc +AI14202,Research Scientist,46195,USD,46195,EN,CT,South Korea,S,Norway,50,"Python, Linux, Java, Docker",PhD,0,Real Estate,2024-01-31,2024-03-23,1062,9.5,Neural Networks Co +AI14203,Machine Learning Engineer,184717,USD,184717,EX,FT,Sweden,L,Sweden,100,"Java, R, SQL, Spark, Mathematics",Master,16,Consulting,2024-11-13,2024-12-11,1866,7.5,Predictive Systems +AI14204,Machine Learning Researcher,84313,SGD,109607,EN,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Linux, Azure",Bachelor,0,Government,2024-11-20,2025-01-22,1994,7.4,Machine Intelligence Group +AI14205,Research Scientist,171948,JPY,18914280,EX,PT,Japan,M,China,0,"GCP, Spark, Docker, NLP, PyTorch",Bachelor,17,Telecommunications,2024-08-12,2024-10-04,938,7.8,Quantum Computing Inc +AI14206,Data Scientist,65079,EUR,55317,EN,PT,Netherlands,L,Sweden,50,"Scala, SQL, PyTorch, Hadoop, Azure",Bachelor,0,Consulting,2025-03-01,2025-05-02,507,6.6,TechCorp Inc +AI14207,Machine Learning Researcher,257240,USD,257240,EX,CT,United States,S,United States,100,"PyTorch, MLOps, NLP, Python",Master,15,Media,2025-04-29,2025-06-28,2003,5.1,Algorithmic Solutions +AI14208,Deep Learning Engineer,71462,AUD,96474,EN,PT,Australia,M,Colombia,100,"SQL, Linux, Mathematics",PhD,0,Healthcare,2024-04-23,2024-05-26,859,8.6,Digital Transformation LLC +AI14209,NLP Engineer,123699,USD,123699,MI,PT,United States,M,Ghana,100,"Git, PyTorch, TensorFlow, Kubernetes",Bachelor,3,Retail,2024-06-19,2024-08-02,1773,5.6,Autonomous Tech +AI14210,AI Architect,72589,USD,72589,EN,FL,Finland,M,Finland,100,"Linux, Python, Hadoop, TensorFlow",Associate,1,Energy,2024-02-29,2024-05-01,596,7,Quantum Computing Inc +AI14211,Data Engineer,128822,AUD,173910,SE,PT,Australia,S,Australia,50,"Data Visualization, Python, Git",Master,5,Manufacturing,2025-03-12,2025-04-02,1922,9.9,Algorithmic Solutions +AI14212,AI Consultant,76617,USD,76617,EN,FL,Sweden,M,Sweden,0,"Mathematics, Linux, Computer Vision, PyTorch",Associate,1,Automotive,2024-08-12,2024-09-19,1012,5.6,TechCorp Inc +AI14213,AI Specialist,93353,USD,93353,EN,PT,Norway,S,Norway,100,"Linux, Kubernetes, Scala",Associate,0,Retail,2025-02-09,2025-04-04,537,5.6,Autonomous Tech +AI14214,Deep Learning Engineer,128582,CHF,115724,MI,FT,Switzerland,L,Switzerland,50,"GCP, Python, Mathematics",Master,4,Transportation,2024-03-02,2024-05-14,1475,8,Machine Intelligence Group +AI14215,Data Analyst,105420,USD,105420,SE,CT,Israel,S,Israel,50,"Python, Kubernetes, Deep Learning, AWS, R",Master,8,Energy,2024-10-22,2024-12-12,1192,8.9,AI Innovations +AI14216,AI Specialist,158281,JPY,17410910,SE,FL,Japan,L,Japan,0,"Linux, AWS, GCP, Mathematics, Docker",Bachelor,5,Real Estate,2024-06-21,2024-08-03,2371,5.4,Neural Networks Co +AI14217,Robotics Engineer,90700,USD,90700,EN,PT,United States,M,United States,50,"PyTorch, TensorFlow, Computer Vision",PhD,1,Energy,2024-03-06,2024-03-27,1800,8.6,Quantum Computing Inc +AI14218,NLP Engineer,163549,USD,163549,SE,FL,Israel,L,Israel,100,"Java, MLOps, GCP",Master,9,Technology,2024-07-16,2024-09-05,1715,6.7,Machine Intelligence Group +AI14219,AI Architect,91126,USD,91126,EN,FL,Denmark,M,Denmark,50,"GCP, Kubernetes, Linux, Computer Vision, Python",PhD,0,Transportation,2024-05-01,2024-05-21,1952,5.9,Cognitive Computing +AI14220,AI Specialist,197097,USD,197097,SE,FL,Norway,L,Norway,0,"Java, Hadoop, TensorFlow",Associate,5,Healthcare,2024-05-28,2024-06-12,2047,5.8,Future Systems +AI14221,AI Architect,130848,USD,130848,SE,PT,Ireland,S,Ireland,50,"Python, Mathematics, Computer Vision, NLP, TensorFlow",PhD,7,Education,2024-09-10,2024-11-02,1856,9.1,DataVision Ltd +AI14222,Machine Learning Engineer,115185,EUR,97907,SE,PT,France,L,Switzerland,100,"Data Visualization, Python, TensorFlow, PyTorch",Bachelor,7,Education,2025-03-14,2025-03-31,1921,9.2,DeepTech Ventures +AI14223,AI Specialist,74184,USD,74184,MI,FT,Finland,S,Philippines,50,"Hadoop, Linux, Git, SQL, Java",PhD,2,Education,2025-03-27,2025-06-05,1287,7.9,AI Innovations +AI14224,Machine Learning Engineer,85351,EUR,72548,EN,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, GCP, NLP, Git",Bachelor,1,Real Estate,2024-12-04,2024-12-22,761,8.2,DataVision Ltd +AI14225,Autonomous Systems Engineer,65593,USD,65593,EN,PT,United States,S,United States,50,"Computer Vision, Azure, Data Visualization",Master,1,Media,2024-09-12,2024-10-22,2483,6,Predictive Systems +AI14226,Robotics Engineer,123894,USD,123894,SE,CT,Ireland,S,Ireland,50,"Spark, Azure, Tableau, SQL, PyTorch",Master,6,Government,2024-02-12,2024-02-27,1054,5.9,DataVision Ltd +AI14227,AI Architect,152751,USD,152751,MI,PT,Denmark,L,Denmark,100,"Scala, Computer Vision, SQL, Git, PyTorch",PhD,2,Energy,2024-04-14,2024-05-04,1986,9.9,Cloud AI Solutions +AI14228,AI Software Engineer,94949,USD,94949,MI,CT,Norway,S,Norway,0,"Python, MLOps, Spark, Scala, TensorFlow",Associate,3,Gaming,2024-01-03,2024-01-18,1610,9.6,Neural Networks Co +AI14229,Machine Learning Researcher,199664,USD,199664,EX,FL,South Korea,L,South Korea,0,"Kubernetes, Python, Linux",Associate,18,Healthcare,2024-10-11,2024-11-15,538,6.3,Future Systems +AI14230,Research Scientist,51090,USD,51090,EN,PT,South Korea,L,South Korea,50,"Git, Scala, Kubernetes, Statistics",Master,1,Manufacturing,2024-06-29,2024-08-26,1607,7.1,Predictive Systems +AI14231,Head of AI,80797,EUR,68677,MI,FL,Germany,S,Germany,100,"PyTorch, Azure, Hadoop, Tableau",Associate,4,Telecommunications,2024-01-20,2024-03-22,1039,9.1,Cognitive Computing +AI14232,AI Product Manager,148078,EUR,125866,SE,PT,France,L,India,100,"Data Visualization, Tableau, Azure, Python, GCP",Associate,5,Government,2024-09-27,2024-11-01,1476,5,DataVision Ltd +AI14233,Research Scientist,241116,EUR,204949,EX,CT,Netherlands,L,Netherlands,50,"Hadoop, Python, Spark, Kubernetes",Bachelor,15,Technology,2024-12-27,2025-02-03,1545,9.9,Cloud AI Solutions +AI14234,AI Specialist,71525,CAD,89406,MI,FL,Canada,M,Canada,100,"GCP, Azure, R, Data Visualization",Bachelor,4,Transportation,2024-01-05,2024-03-13,852,8.8,Cognitive Computing +AI14235,Machine Learning Researcher,228052,USD,228052,EX,FL,Denmark,S,Denmark,0,"Hadoop, Python, Computer Vision, Git, Scala",Bachelor,13,Real Estate,2025-02-07,2025-04-06,1439,7,TechCorp Inc +AI14236,Deep Learning Engineer,92722,SGD,120539,MI,FL,Singapore,L,Singapore,100,"MLOps, Spark, Data Visualization",Bachelor,3,Consulting,2024-03-20,2024-05-18,1536,9.8,Future Systems +AI14237,Principal Data Scientist,177606,JPY,19536660,SE,FL,Japan,L,Japan,50,"Scala, Spark, PyTorch, TensorFlow",Master,5,Government,2024-04-05,2024-05-02,2385,7.5,DataVision Ltd +AI14238,Deep Learning Engineer,65911,USD,65911,EN,CT,South Korea,L,South Korea,50,"PyTorch, Tableau, TensorFlow",PhD,1,Energy,2024-02-19,2024-03-30,1306,9.3,Autonomous Tech +AI14239,Machine Learning Engineer,91391,GBP,68543,MI,FT,United Kingdom,S,Mexico,0,"Scala, Python, MLOps, Kubernetes, TensorFlow",Bachelor,2,Healthcare,2024-01-11,2024-02-05,1946,9.2,Algorithmic Solutions +AI14240,Machine Learning Researcher,201317,USD,201317,EX,FT,Israel,M,Israel,50,"Hadoop, PyTorch, R, Tableau",Master,17,Gaming,2024-08-13,2024-10-07,2364,6.2,Neural Networks Co +AI14241,AI Research Scientist,63528,EUR,53999,EN,FT,France,M,France,50,"Scala, Python, PyTorch",PhD,1,Gaming,2025-01-11,2025-03-08,1363,8.2,Smart Analytics +AI14242,AI Consultant,74903,EUR,63668,EN,PT,Austria,L,Austria,0,"Git, Tableau, Python",Master,1,Education,2024-02-15,2024-04-27,1458,9.9,Algorithmic Solutions +AI14243,Computer Vision Engineer,33431,USD,33431,EN,PT,China,S,Latvia,0,"SQL, Spark, PyTorch, Deep Learning, Git",Associate,0,Automotive,2024-04-14,2024-05-30,1801,8.1,DataVision Ltd +AI14244,AI Software Engineer,58058,AUD,78378,EN,PT,Australia,S,Australia,50,"Git, TensorFlow, Deep Learning, MLOps, Scala",Bachelor,1,Energy,2025-03-09,2025-04-04,2334,5,Neural Networks Co +AI14245,NLP Engineer,125186,USD,125186,SE,FL,Ireland,L,Colombia,100,"R, Java, TensorFlow, Computer Vision, Hadoop",PhD,5,Manufacturing,2024-11-02,2025-01-13,2404,5.2,Neural Networks Co +AI14246,AI Research Scientist,157137,USD,157137,SE,CT,Denmark,L,Singapore,100,"Computer Vision, Linux, SQL",Associate,7,Automotive,2024-03-14,2024-03-30,644,6,Quantum Computing Inc +AI14247,Data Scientist,32212,USD,32212,MI,PT,India,M,India,0,"Scala, PyTorch, Azure, Hadoop, Linux",Bachelor,3,Energy,2024-05-04,2024-06-08,2216,6.5,Future Systems +AI14248,Head of AI,96262,USD,96262,MI,CT,Finland,L,Romania,0,"Spark, SQL, Kubernetes, Git, AWS",Bachelor,2,Manufacturing,2025-04-19,2025-06-02,749,8.3,DeepTech Ventures +AI14249,AI Specialist,87709,USD,87709,SE,CT,South Korea,M,Vietnam,100,"PyTorch, Kubernetes, Hadoop, AWS, SQL",Associate,7,Media,2024-07-24,2024-08-10,1821,6.8,Predictive Systems +AI14250,Robotics Engineer,150226,JPY,16524860,EX,FL,Japan,M,Japan,100,"Git, NLP, Data Visualization",Master,17,Government,2024-02-05,2024-03-15,642,9.7,Algorithmic Solutions +AI14251,AI Product Manager,68640,USD,68640,EN,PT,South Korea,L,South Korea,100,"Spark, Python, Tableau, MLOps, TensorFlow",PhD,0,Technology,2024-01-03,2024-03-07,1794,8.8,TechCorp Inc +AI14252,Data Analyst,54111,EUR,45994,EN,PT,France,M,Germany,0,"GCP, Data Visualization, Java, Computer Vision",PhD,0,Energy,2025-03-16,2025-04-30,2028,6.2,AI Innovations +AI14253,Computer Vision Engineer,144317,SGD,187612,EX,FT,Singapore,S,Ghana,50,"GCP, Git, Kubernetes, AWS",Associate,15,Gaming,2024-08-07,2024-10-10,969,6.8,Smart Analytics +AI14254,Principal Data Scientist,136724,AUD,184577,SE,FL,Australia,L,Australia,50,"Linux, Data Visualization, Python, Scala",Associate,8,Gaming,2024-11-08,2024-12-07,1981,9.5,Cognitive Computing +AI14255,Robotics Engineer,100385,EUR,85327,MI,CT,Austria,L,Russia,50,"Docker, Python, MLOps, TensorFlow, SQL",Bachelor,4,Technology,2024-02-10,2024-04-12,811,6.8,Autonomous Tech +AI14256,AI Specialist,90275,EUR,76734,EN,PT,Germany,L,Italy,100,"Git, Linux, TensorFlow, R, Computer Vision",Bachelor,0,Education,2025-01-08,2025-03-22,1806,6,DataVision Ltd +AI14257,Principal Data Scientist,180652,EUR,153554,EX,PT,Netherlands,S,Poland,100,"Deep Learning, AWS, Data Visualization, TensorFlow",Master,17,Real Estate,2024-07-31,2024-09-30,2331,7.9,Neural Networks Co +AI14258,Research Scientist,51128,EUR,43459,EN,FT,Germany,M,Germany,0,"SQL, Kubernetes, MLOps, GCP, Azure",Bachelor,0,Government,2024-09-23,2024-11-20,1099,6.9,Digital Transformation LLC +AI14259,Computer Vision Engineer,129737,EUR,110276,SE,FL,Austria,L,Austria,50,"Scala, Git, Kubernetes, TensorFlow, Python",PhD,9,Healthcare,2025-01-09,2025-02-11,1980,8.9,Autonomous Tech +AI14260,Machine Learning Researcher,81423,SGD,105850,EN,CT,Singapore,L,Canada,100,"Python, Kubernetes, Deep Learning, Docker",Associate,1,Healthcare,2024-11-20,2025-01-16,2142,5.5,Autonomous Tech +AI14261,Data Engineer,171399,CHF,154259,MI,FL,Switzerland,L,Poland,0,"PyTorch, SQL, TensorFlow, Tableau, Computer Vision",Master,2,Energy,2024-08-30,2024-11-02,1386,7.1,Algorithmic Solutions +AI14262,Principal Data Scientist,299540,USD,299540,EX,CT,Norway,L,Norway,100,"Spark, Linux, Data Visualization, Scala, PyTorch",PhD,16,Media,2024-07-29,2024-09-12,971,6.9,Machine Intelligence Group +AI14263,ML Ops Engineer,23079,USD,23079,MI,FL,India,S,India,50,"TensorFlow, Tableau, PyTorch",Associate,2,Real Estate,2024-12-15,2025-01-01,1015,6.9,Predictive Systems +AI14264,AI Software Engineer,160236,USD,160236,MI,PT,Norway,L,Mexico,0,"Deep Learning, Git, Kubernetes, Azure, Java",Associate,2,Gaming,2024-08-23,2024-10-26,2377,6.8,Machine Intelligence Group +AI14265,Machine Learning Researcher,75808,USD,75808,EN,FT,Sweden,L,Sweden,100,"Tableau, MLOps, Kubernetes, Hadoop, Azure",Associate,1,Media,2024-03-28,2024-05-31,1175,8.2,Future Systems +AI14266,Machine Learning Engineer,109582,USD,109582,MI,PT,Finland,L,Russia,50,"Computer Vision, Python, Java, R",PhD,3,Consulting,2025-01-10,2025-02-28,1714,8.8,Smart Analytics +AI14267,Robotics Engineer,85941,CAD,107426,MI,PT,Canada,M,Canada,0,"Scala, R, Data Visualization, Linux",Associate,2,Automotive,2025-01-17,2025-02-16,1525,7.9,DeepTech Ventures +AI14268,Computer Vision Engineer,160982,SGD,209277,SE,CT,Singapore,L,Turkey,100,"SQL, Azure, Statistics",Associate,5,Healthcare,2025-04-10,2025-05-05,642,9.5,Cognitive Computing +AI14269,AI Specialist,111319,GBP,83489,SE,CT,United Kingdom,S,United Kingdom,0,"Java, Azure, AWS, Spark, TensorFlow",Bachelor,7,Healthcare,2024-12-20,2025-02-26,913,8.1,TechCorp Inc +AI14270,NLP Engineer,99974,EUR,84978,SE,FT,France,M,France,0,"Python, Computer Vision, Tableau, Scala, Azure",Master,9,Finance,2024-01-11,2024-03-02,1351,8.9,TechCorp Inc +AI14271,AI Research Scientist,103001,CAD,128751,MI,PT,Canada,M,Finland,50,"Java, Kubernetes, PyTorch",Bachelor,4,Retail,2024-12-17,2025-01-01,963,9.7,Neural Networks Co +AI14272,AI Software Engineer,207251,EUR,176163,EX,PT,Austria,S,United States,100,"PyTorch, Computer Vision, Python, TensorFlow",Master,11,Technology,2024-08-17,2024-10-18,1504,9.1,Cloud AI Solutions +AI14273,ML Ops Engineer,65060,USD,65060,EN,FT,Finland,L,Finland,0,"AWS, Data Visualization, Hadoop",Master,1,Media,2025-03-15,2025-04-09,1904,7.6,TechCorp Inc +AI14274,AI Consultant,90343,EUR,76792,MI,CT,Austria,M,Austria,50,"Python, TensorFlow, Git",Master,3,Gaming,2024-05-26,2024-07-10,1702,6.8,Neural Networks Co +AI14275,AI Specialist,99304,USD,99304,SE,PT,Israel,M,Poland,50,"PyTorch, Git, Kubernetes",Bachelor,7,Manufacturing,2025-03-15,2025-04-23,1905,6.7,Machine Intelligence Group +AI14276,Robotics Engineer,79942,USD,79942,EN,PT,Sweden,M,Sweden,50,"Computer Vision, SQL, Kubernetes, Docker",PhD,1,Education,2024-10-29,2025-01-07,1330,9.8,Smart Analytics +AI14277,Computer Vision Engineer,105304,GBP,78978,SE,PT,United Kingdom,S,United Kingdom,50,"Azure, Linux, Hadoop, Mathematics, Kubernetes",Associate,8,Manufacturing,2025-01-18,2025-02-23,619,8.7,Future Systems +AI14278,Data Engineer,118101,USD,118101,SE,FL,Finland,M,Denmark,50,"TensorFlow, Spark, Statistics, Linux, AWS",Associate,7,Gaming,2024-11-06,2025-01-06,1101,5,Cloud AI Solutions +AI14279,AI Product Manager,64827,USD,64827,SE,FL,China,L,China,0,"Scala, Python, MLOps, Hadoop",Master,8,Finance,2025-02-11,2025-03-16,855,9.2,Algorithmic Solutions +AI14280,Head of AI,136792,USD,136792,MI,FL,Norway,L,United Kingdom,0,"Hadoop, Azure, Statistics",Master,4,Education,2024-11-15,2025-01-23,2468,8.3,Smart Analytics +AI14281,Deep Learning Engineer,125716,EUR,106859,SE,FL,France,L,France,0,"SQL, Python, Java, NLP, Spark",PhD,8,Education,2024-12-05,2025-01-07,1744,7.8,Algorithmic Solutions +AI14282,ML Ops Engineer,74299,USD,74299,EN,CT,Sweden,M,Sweden,0,"Java, Python, NLP",PhD,0,Consulting,2024-02-26,2024-05-05,2071,9.9,Digital Transformation LLC +AI14283,Machine Learning Engineer,279034,USD,279034,EX,FL,United States,L,Egypt,0,"Computer Vision, GCP, MLOps, NLP",Associate,19,Consulting,2024-09-05,2024-10-30,1323,6.5,Digital Transformation LLC +AI14284,Data Scientist,84474,GBP,63356,EN,FL,United Kingdom,M,United Kingdom,0,"Spark, NLP, TensorFlow",Associate,1,Education,2024-01-08,2024-02-02,1232,5.6,Neural Networks Co +AI14285,NLP Engineer,105225,USD,105225,EX,FL,China,L,Mexico,0,"MLOps, Azure, Kubernetes, NLP",Bachelor,17,Media,2024-02-17,2024-04-30,2011,9.9,Algorithmic Solutions +AI14286,Machine Learning Researcher,140938,USD,140938,SE,PT,South Korea,L,Romania,0,"Docker, Linux, Hadoop, NLP, R",PhD,6,Healthcare,2025-03-26,2025-05-04,804,7.2,TechCorp Inc +AI14287,Autonomous Systems Engineer,51274,USD,51274,EN,FT,South Korea,L,South Korea,50,"GCP, Azure, AWS, Deep Learning, Mathematics",Master,1,Technology,2024-10-08,2024-11-14,1708,9.1,DeepTech Ventures +AI14288,Data Scientist,78815,JPY,8669650,MI,PT,Japan,S,Japan,100,"Computer Vision, Java, NLP, Mathematics, Linux",PhD,3,Telecommunications,2024-04-07,2024-05-18,2219,9.4,Cloud AI Solutions +AI14289,Robotics Engineer,62675,USD,62675,EN,PT,Israel,L,Israel,50,"MLOps, Git, GCP",Associate,1,Healthcare,2025-01-10,2025-02-13,767,5.8,DeepTech Ventures +AI14290,Head of AI,44043,USD,44043,SE,FL,India,S,India,50,"Kubernetes, Scala, GCP, Python",Master,8,Media,2025-02-10,2025-04-17,1249,9.5,DataVision Ltd +AI14291,Machine Learning Engineer,91908,GBP,68931,MI,PT,United Kingdom,S,United Kingdom,100,"Data Visualization, Kubernetes, GCP, Scala",PhD,2,Real Estate,2024-06-08,2024-07-23,1802,9.7,DataVision Ltd +AI14292,Machine Learning Researcher,161960,EUR,137666,EX,CT,Austria,M,Austria,0,"Docker, Java, MLOps",PhD,14,Telecommunications,2024-10-31,2024-11-15,633,9.2,Future Systems +AI14293,AI Product Manager,59982,USD,59982,EN,FL,Israel,S,Indonesia,0,"AWS, Kubernetes, SQL, GCP, Data Visualization",PhD,0,Energy,2024-11-03,2024-12-06,1024,5.5,Neural Networks Co +AI14294,Data Analyst,73332,USD,73332,MI,FT,Israel,S,Malaysia,100,"Data Visualization, Statistics, Spark, Tableau",Associate,3,Energy,2024-01-17,2024-03-26,1881,6.4,Advanced Robotics +AI14295,Machine Learning Engineer,235865,USD,235865,EX,FT,Israel,M,Israel,0,"Hadoop, Linux, Kubernetes",PhD,17,Telecommunications,2024-12-15,2025-02-16,1931,7.2,DeepTech Ventures +AI14296,Computer Vision Engineer,62646,EUR,53249,EN,CT,France,L,Japan,50,"Hadoop, Statistics, Git",Bachelor,0,Government,2024-05-03,2024-05-21,2160,8.5,Autonomous Tech +AI14297,ML Ops Engineer,81857,USD,81857,MI,PT,United States,S,Finland,0,"TensorFlow, Linux, Python, Hadoop",Associate,2,Government,2025-03-31,2025-05-26,2393,9.2,Quantum Computing Inc +AI14298,Computer Vision Engineer,98405,AUD,132847,MI,PT,Australia,S,Denmark,0,"PyTorch, Computer Vision, Kubernetes, GCP, AWS",Master,4,Telecommunications,2025-02-17,2025-03-20,2240,8,Cognitive Computing +AI14299,Principal Data Scientist,52393,USD,52393,EN,FL,Sweden,S,Thailand,0,"Python, Kubernetes, TensorFlow",PhD,0,Transportation,2024-10-06,2024-11-27,969,9.3,Neural Networks Co +AI14300,Computer Vision Engineer,51076,USD,51076,EN,FL,Ireland,S,Ireland,0,"PyTorch, Deep Learning, SQL, GCP",Associate,0,Retail,2025-03-16,2025-05-19,1948,5.6,Quantum Computing Inc +AI14301,Data Engineer,109859,CHF,98873,EN,FT,Switzerland,L,Switzerland,0,"Mathematics, Scala, Tableau",Bachelor,0,Energy,2024-07-10,2024-09-16,620,7.6,DataVision Ltd +AI14302,Machine Learning Researcher,140133,SGD,182173,SE,PT,Singapore,S,Poland,50,"Scala, Java, Docker",Master,9,Healthcare,2024-05-15,2024-06-10,1824,8.6,Autonomous Tech +AI14303,Head of AI,233979,USD,233979,EX,FT,United States,S,United States,50,"MLOps, R, GCP, Linux",Bachelor,19,Gaming,2024-08-06,2024-10-18,1936,7.7,Quantum Computing Inc +AI14304,AI Architect,61640,EUR,52394,EN,FL,France,S,France,100,"Java, PyTorch, Azure",Associate,1,Manufacturing,2025-01-26,2025-03-09,1512,7.2,Advanced Robotics +AI14305,NLP Engineer,162855,EUR,138427,SE,PT,Germany,L,Germany,100,"Python, Spark, TensorFlow, Statistics, Git",Master,8,Healthcare,2024-11-29,2025-01-24,1320,5.5,Quantum Computing Inc +AI14306,Autonomous Systems Engineer,102016,EUR,86714,MI,FT,Austria,L,Austria,0,"Azure, Git, Python, Linux",Bachelor,2,Consulting,2024-04-10,2024-05-10,1178,7.1,AI Innovations +AI14307,Data Scientist,65504,CAD,81880,EN,PT,Canada,L,Canada,100,"Docker, Data Visualization, Tableau, TensorFlow, Mathematics",Associate,0,Technology,2024-12-08,2025-02-10,678,5.2,Digital Transformation LLC +AI14308,AI Product Manager,75588,USD,75588,MI,FT,South Korea,S,South Korea,0,"GCP, R, NLP",Bachelor,4,Technology,2024-04-17,2024-05-28,1720,8,TechCorp Inc +AI14309,AI Architect,112458,CAD,140573,SE,FL,Canada,M,Canada,50,"Docker, Computer Vision, PyTorch",Associate,6,Education,2024-01-23,2024-03-11,1021,8.7,Cloud AI Solutions +AI14310,Computer Vision Engineer,124536,EUR,105856,EX,PT,Austria,S,Denmark,100,"TensorFlow, Deep Learning, Data Visualization, Computer Vision, Java",PhD,10,Media,2024-10-01,2024-11-07,550,9.6,Cognitive Computing +AI14311,Head of AI,175373,EUR,149067,EX,FL,Germany,L,Germany,50,"Statistics, PyTorch, Deep Learning",Master,17,Transportation,2024-07-03,2024-08-29,1193,10,Neural Networks Co +AI14312,AI Architect,116773,USD,116773,MI,CT,Ireland,L,Argentina,100,"Java, Hadoop, MLOps",PhD,3,Finance,2024-11-21,2024-12-26,502,6.2,Smart Analytics +AI14313,Machine Learning Engineer,81273,EUR,69082,EN,CT,Netherlands,M,Japan,0,"R, SQL, NLP, Git, GCP",Master,0,Media,2024-07-06,2024-08-16,862,9.9,Predictive Systems +AI14314,Machine Learning Engineer,90934,USD,90934,MI,PT,United States,S,United States,50,"Linux, GCP, Statistics, Deep Learning",Master,2,Manufacturing,2024-09-10,2024-10-19,2041,6.1,DataVision Ltd +AI14315,Computer Vision Engineer,141213,SGD,183577,SE,FL,Singapore,S,Philippines,100,"AWS, Python, Statistics, TensorFlow",PhD,9,Telecommunications,2024-07-23,2024-08-26,661,6.1,Cognitive Computing +AI14316,Head of AI,275394,SGD,358012,EX,FL,Singapore,L,Romania,100,"Python, Spark, Git, TensorFlow",Bachelor,18,Healthcare,2024-05-24,2024-07-29,874,6.6,Digital Transformation LLC +AI14317,Principal Data Scientist,107900,CAD,134875,SE,PT,Canada,S,Canada,0,"PyTorch, Azure, Spark",Bachelor,6,Government,2025-01-04,2025-01-19,1643,6,Future Systems +AI14318,Research Scientist,94985,JPY,10448350,EN,FT,Japan,L,Germany,100,"Python, Git, Deep Learning, PyTorch",PhD,1,Transportation,2024-03-03,2024-03-23,675,7.4,Autonomous Tech +AI14319,Computer Vision Engineer,123657,JPY,13602270,SE,FL,Japan,M,Italy,0,"Git, PyTorch, TensorFlow",PhD,8,Transportation,2024-06-07,2024-07-05,1062,8.8,Cloud AI Solutions +AI14320,AI Specialist,18446,USD,18446,EN,FL,India,S,India,100,"PyTorch, Scala, Git, NLP",Master,1,Transportation,2024-01-03,2024-02-01,2179,7.4,TechCorp Inc +AI14321,Robotics Engineer,125558,USD,125558,EX,FL,China,L,Romania,50,"Spark, MLOps, SQL, Hadoop",Bachelor,14,Technology,2024-04-09,2024-04-23,1998,7,DataVision Ltd +AI14322,Data Engineer,55209,EUR,46928,EN,FT,France,L,France,0,"Deep Learning, Kubernetes, Git, Statistics",Bachelor,1,Media,2024-12-14,2025-01-29,1887,6.6,Algorithmic Solutions +AI14323,AI Research Scientist,233676,EUR,198625,EX,FL,France,L,France,50,"SQL, Hadoop, PyTorch, Tableau",PhD,11,Manufacturing,2024-04-26,2024-07-01,2101,6.6,Cognitive Computing +AI14324,Principal Data Scientist,30081,USD,30081,MI,FT,India,L,India,0,"SQL, Git, Docker",PhD,2,Education,2024-09-03,2024-10-21,2325,5.8,Autonomous Tech +AI14325,Robotics Engineer,155252,EUR,131964,EX,CT,Austria,M,Austria,50,"Kubernetes, Hadoop, Spark, Docker, Git",Associate,11,Real Estate,2024-01-24,2024-03-31,1042,9.8,Predictive Systems +AI14326,Machine Learning Researcher,132368,CAD,165460,SE,FT,Canada,M,Canada,100,"SQL, Git, Data Visualization, Java, Spark",Master,7,Finance,2025-02-24,2025-04-04,1828,5.2,DeepTech Ventures +AI14327,Computer Vision Engineer,84373,USD,84373,MI,CT,South Korea,M,South Korea,0,"SQL, Computer Vision, Kubernetes, MLOps, Python",PhD,2,Telecommunications,2024-07-26,2024-10-07,2348,6.8,Digital Transformation LLC +AI14328,AI Architect,264528,USD,264528,EX,CT,Denmark,M,Denmark,100,"GCP, Linux, Computer Vision",Associate,11,Gaming,2024-09-15,2024-11-27,2001,7.5,AI Innovations +AI14329,Data Engineer,29715,USD,29715,EN,CT,India,L,India,0,"Mathematics, Scala, Python, AWS, Data Visualization",PhD,0,Automotive,2025-04-06,2025-06-07,2490,9.3,Advanced Robotics +AI14330,AI Specialist,164165,EUR,139540,SE,CT,Germany,L,Germany,50,"Java, MLOps, Linux, Deep Learning",Bachelor,9,Consulting,2024-01-14,2024-02-05,1341,9.4,TechCorp Inc +AI14331,Research Scientist,223621,USD,223621,EX,FL,Denmark,L,Czech Republic,0,"Scala, Tableau, Kubernetes, R",PhD,11,Manufacturing,2024-12-14,2025-02-06,705,6,Neural Networks Co +AI14332,AI Architect,226374,SGD,294286,EX,FL,Singapore,S,Singapore,100,"Kubernetes, Python, Data Visualization",Bachelor,16,Finance,2024-01-11,2024-03-22,1812,8.8,AI Innovations +AI14333,Machine Learning Engineer,76615,USD,76615,EN,FT,Sweden,M,Norway,50,"Scala, Tableau, R, Azure, Linux",Master,0,Gaming,2024-08-01,2024-08-20,1375,5.9,Algorithmic Solutions +AI14334,AI Consultant,85551,CHF,76996,EN,PT,Switzerland,L,Switzerland,100,"PyTorch, Linux, TensorFlow",Master,0,Telecommunications,2024-12-19,2025-01-18,2033,8.9,TechCorp Inc +AI14335,AI Consultant,156675,GBP,117506,EX,FT,United Kingdom,M,France,50,"Hadoop, Scala, Linux, Computer Vision",Master,18,Finance,2024-09-03,2024-10-07,1584,9,Predictive Systems +AI14336,Principal Data Scientist,55271,EUR,46980,EN,FL,France,M,France,50,"Git, TensorFlow, PyTorch, Scala",Bachelor,0,Finance,2024-05-15,2024-06-11,1717,8.4,Cloud AI Solutions +AI14337,AI Software Engineer,166389,USD,166389,EX,FL,Finland,M,Ghana,50,"R, Python, Hadoop",Bachelor,12,Retail,2025-03-11,2025-04-15,2042,7.1,Predictive Systems +AI14338,NLP Engineer,82549,SGD,107314,EN,FL,Singapore,L,United States,0,"MLOps, Azure, Kubernetes, Tableau, Docker",Master,1,Consulting,2025-01-21,2025-03-24,1901,6.8,Smart Analytics +AI14339,Principal Data Scientist,76753,GBP,57565,EN,CT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, PyTorch",Master,1,Real Estate,2024-02-20,2024-04-02,975,9.2,Neural Networks Co +AI14340,AI Research Scientist,73157,EUR,62183,MI,PT,Netherlands,S,Netherlands,50,"Scala, SQL, Data Visualization, GCP, PyTorch",PhD,4,Finance,2025-01-21,2025-03-29,678,8,Cognitive Computing +AI14341,Data Analyst,116897,USD,116897,SE,FL,South Korea,M,Belgium,100,"PyTorch, TensorFlow, Git, GCP, Linux",PhD,6,Retail,2024-11-19,2025-01-26,1136,6.6,Future Systems +AI14342,AI Software Engineer,130794,USD,130794,SE,FL,Finland,L,Vietnam,0,"Python, AWS, Statistics, Computer Vision",PhD,9,Media,2024-08-25,2024-10-23,1247,8.4,DataVision Ltd +AI14343,Deep Learning Engineer,102032,JPY,11223520,MI,FL,Japan,M,Japan,100,"Kubernetes, Computer Vision, AWS, Azure",Associate,4,Healthcare,2025-01-30,2025-03-25,2399,8.4,AI Innovations +AI14344,AI Product Manager,142857,EUR,121428,SE,FT,Austria,L,South Africa,50,"SQL, Python, AWS, Java, TensorFlow",PhD,7,Consulting,2024-03-29,2024-05-11,2479,9.5,Cognitive Computing +AI14345,AI Research Scientist,187842,SGD,244195,EX,PT,Singapore,M,Singapore,50,"Hadoop, TensorFlow, Computer Vision, MLOps",PhD,14,Media,2025-01-24,2025-02-10,1075,7.9,Neural Networks Co +AI14346,AI Research Scientist,157194,SGD,204352,EX,FL,Singapore,S,Poland,100,"Python, Java, SQL",Bachelor,17,Automotive,2025-01-20,2025-02-05,2120,5.7,Cloud AI Solutions +AI14347,Deep Learning Engineer,104641,EUR,88945,MI,CT,Netherlands,S,Belgium,0,"SQL, Git, Kubernetes",Master,4,Transportation,2025-03-17,2025-04-25,2022,9.4,Advanced Robotics +AI14348,Machine Learning Engineer,70047,USD,70047,EN,CT,United States,S,Indonesia,100,"Deep Learning, Scala, AWS",Master,1,Manufacturing,2024-07-12,2024-08-14,1560,6.3,Algorithmic Solutions +AI14349,AI Consultant,174437,USD,174437,SE,CT,Norway,S,Egypt,0,"AWS, Docker, SQL, Git, Scala",Associate,5,Energy,2024-02-12,2024-04-05,1526,8.2,Algorithmic Solutions +AI14350,Head of AI,291903,AUD,394069,EX,FT,Australia,L,Australia,50,"Statistics, Scala, Deep Learning, Data Visualization, Mathematics",Bachelor,17,Government,2024-10-26,2024-11-10,2021,8.3,Machine Intelligence Group +AI14351,Data Engineer,257612,USD,257612,EX,CT,United States,S,Japan,50,"R, Deep Learning, Azure",Associate,19,Telecommunications,2024-04-01,2024-05-13,1277,9.2,Cloud AI Solutions +AI14352,ML Ops Engineer,138666,USD,138666,MI,FT,Norway,M,India,50,"Linux, Data Visualization, TensorFlow, Mathematics",Master,2,Telecommunications,2024-12-07,2025-02-04,1782,6.3,Cognitive Computing +AI14353,Autonomous Systems Engineer,139390,SGD,181207,SE,PT,Singapore,M,Singapore,50,"Python, TensorFlow, PyTorch, Azure, Linux",PhD,9,Retail,2025-01-21,2025-04-03,2156,9,Cloud AI Solutions +AI14354,Data Engineer,137009,EUR,116458,SE,CT,Austria,L,Austria,100,"Java, Spark, Computer Vision",Associate,9,Gaming,2024-03-21,2024-04-25,1105,9.6,Advanced Robotics +AI14355,AI Architect,154759,USD,154759,EX,FL,Ireland,M,Ireland,100,"SQL, PyTorch, GCP",Bachelor,17,Automotive,2024-04-06,2024-05-03,1786,7.4,Cognitive Computing +AI14356,Data Engineer,132746,SGD,172570,SE,CT,Singapore,M,Sweden,100,"Python, NLP, TensorFlow, PyTorch, Git",PhD,6,Technology,2024-02-14,2024-03-01,2443,7.7,Neural Networks Co +AI14357,Data Engineer,100856,GBP,75642,MI,FT,United Kingdom,L,United Kingdom,100,"SQL, Kubernetes, Deep Learning, Python",PhD,3,Government,2024-02-16,2024-04-09,763,8,AI Innovations +AI14358,Machine Learning Engineer,49761,GBP,37321,EN,FL,United Kingdom,S,Romania,50,"R, Tableau, SQL",Master,0,Education,2024-02-02,2024-02-23,1476,5.9,DeepTech Ventures +AI14359,Research Scientist,77665,GBP,58249,EN,CT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning, Hadoop",PhD,0,Education,2024-01-08,2024-02-20,654,7.7,Digital Transformation LLC +AI14360,Data Scientist,71610,USD,71610,EN,FT,Ireland,L,Italy,0,"Spark, AWS, SQL",PhD,0,Finance,2024-09-20,2024-10-13,1560,5.9,Cloud AI Solutions +AI14361,Head of AI,57686,CAD,72108,EN,FT,Canada,M,Canada,100,"Git, Mathematics, SQL, TensorFlow, Computer Vision",Master,1,Energy,2024-06-11,2024-08-06,2351,8.3,Smart Analytics +AI14362,Machine Learning Researcher,131219,EUR,111536,SE,CT,Netherlands,M,Netherlands,50,"Docker, PyTorch, Azure, Hadoop, TensorFlow",Master,6,Transportation,2024-06-12,2024-07-12,1918,7.8,Cognitive Computing +AI14363,Robotics Engineer,104036,AUD,140449,MI,FT,Australia,M,Australia,100,"Kubernetes, Computer Vision, NLP",Bachelor,3,Media,2024-12-11,2025-02-06,1735,7.2,Smart Analytics +AI14364,NLP Engineer,154548,USD,154548,EX,FT,Finland,L,India,50,"PyTorch, TensorFlow, Java",Master,18,Retail,2024-02-04,2024-03-05,1766,8.9,Autonomous Tech +AI14365,ML Ops Engineer,189083,USD,189083,EX,PT,Sweden,L,Sweden,50,"SQL, Linux, Statistics, Hadoop",PhD,19,Healthcare,2024-10-27,2024-11-11,1412,7.5,TechCorp Inc +AI14366,Head of AI,107559,USD,107559,SE,PT,Sweden,S,Sweden,0,"Azure, Kubernetes, Mathematics, Docker",Associate,6,Energy,2024-03-13,2024-05-05,1206,8.8,Quantum Computing Inc +AI14367,Machine Learning Engineer,197070,CAD,246338,EX,FT,Canada,S,Canada,100,"PyTorch, Hadoop, Python, Git",Bachelor,10,Government,2024-07-20,2024-09-10,1688,10,Digital Transformation LLC +AI14368,Data Analyst,158181,CAD,197726,SE,PT,Canada,L,Egypt,0,"Linux, R, MLOps",Bachelor,8,Telecommunications,2024-04-26,2024-06-18,799,6.6,Cloud AI Solutions +AI14369,Data Analyst,118102,EUR,100387,SE,FL,France,S,France,100,"R, Mathematics, Scala, Statistics",Bachelor,9,Healthcare,2024-04-13,2024-05-05,1809,6.9,AI Innovations +AI14370,Data Engineer,112990,USD,112990,MI,CT,Norway,S,Norway,0,"Linux, Java, PyTorch, Git, MLOps",Master,4,Transportation,2025-04-02,2025-04-26,2482,6.6,AI Innovations +AI14371,ML Ops Engineer,147657,JPY,16242270,EX,PT,Japan,M,Japan,50,"Spark, MLOps, Azure, SQL, Docker",Master,11,Education,2024-05-16,2024-06-25,1666,5.6,Machine Intelligence Group +AI14372,Machine Learning Engineer,145533,EUR,123703,SE,PT,Netherlands,M,China,100,"Python, TensorFlow, Docker",Associate,6,Education,2024-01-10,2024-02-28,730,7.6,Cognitive Computing +AI14373,Data Scientist,128282,USD,128282,MI,CT,Denmark,M,Russia,0,"Python, Scala, SQL",Bachelor,2,Retail,2024-10-04,2024-10-24,1809,8.2,DataVision Ltd +AI14374,Principal Data Scientist,118956,EUR,101113,SE,PT,Germany,L,Germany,50,"NLP, Deep Learning, Kubernetes",PhD,9,Consulting,2024-12-07,2024-12-30,1671,7.2,Future Systems +AI14375,AI Consultant,64457,USD,64457,EX,FT,China,M,China,50,"R, Python, Linux, Docker, MLOps",Bachelor,12,Finance,2024-08-06,2024-09-15,2061,6.6,DeepTech Ventures +AI14376,ML Ops Engineer,75849,EUR,64472,EN,CT,Netherlands,M,Netherlands,100,"Data Visualization, TensorFlow, Deep Learning, Tableau, Hadoop",Master,0,Automotive,2024-03-01,2024-03-23,1079,5.1,Neural Networks Co +AI14377,Data Engineer,137657,USD,137657,EX,FT,China,L,New Zealand,0,"Docker, Data Visualization, Tableau, R",Bachelor,18,Media,2024-10-31,2024-12-05,1668,7.7,Predictive Systems +AI14378,Robotics Engineer,144216,USD,144216,SE,PT,Sweden,M,Sweden,0,"Git, GCP, Tableau, PyTorch, Java",Bachelor,6,Consulting,2024-11-17,2025-01-07,2242,7.7,Cognitive Computing +AI14379,AI Consultant,113094,SGD,147022,SE,PT,Singapore,M,Singapore,0,"NLP, Kubernetes, GCP",Bachelor,5,Gaming,2024-07-30,2024-10-11,2205,5.1,Future Systems +AI14380,Data Engineer,138816,GBP,104112,SE,FT,United Kingdom,S,United Kingdom,100,"Data Visualization, R, Python",Bachelor,7,Gaming,2024-12-11,2025-02-10,1227,9.5,Cloud AI Solutions +AI14381,AI Research Scientist,105524,EUR,89695,SE,FT,France,S,France,50,"Python, Data Visualization, GCP, Mathematics",Bachelor,5,Telecommunications,2024-06-11,2024-08-17,1248,6.9,Future Systems +AI14382,Machine Learning Engineer,235370,JPY,25890700,EX,CT,Japan,L,Estonia,50,"Python, Azure, SQL, Spark, AWS",Master,19,Automotive,2024-02-07,2024-03-18,960,8.3,DataVision Ltd +AI14383,Machine Learning Engineer,53545,USD,53545,EN,FT,Finland,M,Finland,0,"Docker, Linux, Computer Vision",Master,0,Retail,2025-01-24,2025-03-25,520,9.6,Quantum Computing Inc +AI14384,Principal Data Scientist,246044,AUD,332159,EX,FL,Australia,L,Australia,50,"Statistics, R, Kubernetes, PyTorch",Master,10,Transportation,2024-04-06,2024-05-07,1758,5.3,TechCorp Inc +AI14385,Machine Learning Engineer,79749,EUR,67787,MI,FL,Austria,S,Austria,100,"Deep Learning, Data Visualization, Java, Tableau",Bachelor,3,Healthcare,2025-04-16,2025-06-05,2163,7.1,Digital Transformation LLC +AI14386,AI Product Manager,45513,USD,45513,MI,FL,China,S,China,50,"GCP, Spark, PyTorch, MLOps",PhD,2,Education,2024-11-09,2024-12-03,1131,9.9,Machine Intelligence Group +AI14387,ML Ops Engineer,147346,SGD,191550,SE,FT,Singapore,L,Singapore,50,"Kubernetes, Azure, Linux, Statistics, Spark",Associate,8,Telecommunications,2024-04-09,2024-05-03,1332,9.2,Advanced Robotics +AI14388,Autonomous Systems Engineer,96801,EUR,82281,MI,FL,Austria,M,Romania,50,"Statistics, PyTorch, Azure, Spark",Master,4,Government,2024-03-22,2024-05-26,616,7.2,Cognitive Computing +AI14389,Data Scientist,112083,USD,112083,MI,CT,Ireland,L,Ireland,50,"Tableau, SQL, Kubernetes, PyTorch",Bachelor,3,Transportation,2024-07-26,2024-09-25,1774,5.2,Advanced Robotics +AI14390,Computer Vision Engineer,119874,AUD,161830,MI,PT,Australia,L,Australia,50,"Git, PyTorch, Tableau, AWS",Bachelor,2,Healthcare,2025-04-12,2025-05-20,681,5.9,Advanced Robotics +AI14391,AI Product Manager,37440,USD,37440,SE,FT,India,M,India,0,"SQL, PyTorch, R, Statistics",Bachelor,5,Consulting,2024-07-03,2024-08-02,1668,8.8,Cognitive Computing +AI14392,AI Software Engineer,156018,USD,156018,SE,PT,United States,S,United States,100,"Spark, TensorFlow, Computer Vision",Master,7,Education,2024-01-01,2024-02-28,1438,8.6,Future Systems +AI14393,AI Architect,77323,USD,77323,MI,FT,Finland,S,Finland,100,"MLOps, AWS, GCP, Spark, Tableau",Master,3,Consulting,2024-03-05,2024-04-12,2405,7,Predictive Systems +AI14394,Machine Learning Researcher,157671,USD,157671,EX,PT,South Korea,S,South Korea,0,"GCP, R, Kubernetes",Master,11,Real Estate,2024-10-13,2024-11-17,1026,7.5,Digital Transformation LLC +AI14395,Deep Learning Engineer,107434,SGD,139664,MI,FT,Singapore,M,Singapore,50,"Hadoop, Docker, AWS, PyTorch",PhD,3,Energy,2024-07-25,2024-09-19,2130,7.5,Cloud AI Solutions +AI14396,Robotics Engineer,69805,EUR,59334,MI,FT,France,M,France,50,"SQL, Data Visualization, Azure, Spark",PhD,2,Media,2024-10-02,2024-10-16,1607,9.8,Advanced Robotics +AI14397,AI Research Scientist,80668,EUR,68568,MI,FL,Austria,L,Austria,100,"Hadoop, Tableau, SQL, NLP",PhD,4,Consulting,2025-02-06,2025-04-05,594,6,Digital Transformation LLC +AI14398,Head of AI,140967,EUR,119822,EX,FT,Germany,M,Philippines,100,"Data Visualization, R, SQL",Master,11,Finance,2024-04-10,2024-04-29,1541,6.4,Algorithmic Solutions +AI14399,Principal Data Scientist,112216,USD,112216,SE,PT,Sweden,M,Belgium,0,"Python, TensorFlow, Docker",Master,7,Real Estate,2024-08-12,2024-09-20,1853,7.9,TechCorp Inc +AI14400,Autonomous Systems Engineer,210828,JPY,23191080,EX,PT,Japan,S,Japan,50,"SQL, Python, R",Bachelor,19,Healthcare,2025-04-16,2025-06-28,2384,6.5,TechCorp Inc +AI14401,Principal Data Scientist,44332,USD,44332,SE,FL,India,S,India,0,"Git, MLOps, Tableau, Kubernetes, Computer Vision",Master,9,Manufacturing,2024-08-28,2024-09-21,942,9.8,AI Innovations +AI14402,Data Engineer,68896,EUR,58562,EN,FL,France,M,France,50,"Computer Vision, SQL, Kubernetes, Linux",Bachelor,1,Education,2024-09-01,2024-11-04,847,8,Future Systems +AI14403,Data Scientist,165554,CHF,148999,MI,FL,Switzerland,L,Netherlands,50,"SQL, Kubernetes, MLOps, Hadoop",Bachelor,4,Consulting,2024-06-05,2024-06-19,1740,8.3,Digital Transformation LLC +AI14404,AI Architect,114670,USD,114670,MI,PT,Denmark,S,Denmark,100,"Python, TensorFlow, MLOps, Docker",PhD,4,Government,2024-05-19,2024-06-09,1820,9.2,Algorithmic Solutions +AI14405,Data Analyst,97405,JPY,10714550,EN,PT,Japan,L,Ireland,50,"Spark, Linux, Data Visualization, Git",Master,1,Energy,2024-05-02,2024-06-27,2381,7.8,DataVision Ltd +AI14406,AI Specialist,92003,EUR,78203,SE,PT,France,S,Hungary,0,"SQL, Linux, Scala, Docker, Kubernetes",Master,8,Consulting,2024-07-03,2024-07-28,1265,6.2,Digital Transformation LLC +AI14407,Principal Data Scientist,85732,USD,85732,EN,FT,Denmark,S,Denmark,0,"Scala, Computer Vision, R, SQL",Master,0,Healthcare,2024-07-01,2024-08-01,2168,9,DataVision Ltd +AI14408,Data Analyst,158515,EUR,134738,EX,FT,Netherlands,M,Netherlands,50,"Java, Spark, Data Visualization, MLOps, Mathematics",PhD,16,Consulting,2024-08-10,2024-09-21,1073,8.2,Predictive Systems +AI14409,AI Specialist,119601,USD,119601,SE,CT,Sweden,M,Sweden,50,"Python, Hadoop, Data Visualization, Docker, Computer Vision",Associate,9,Consulting,2025-03-05,2025-05-04,1855,5.6,Machine Intelligence Group +AI14410,NLP Engineer,72330,EUR,61481,EN,PT,France,M,France,0,"Computer Vision, GCP, Docker",Bachelor,0,Transportation,2024-02-22,2024-04-01,1518,5.4,Machine Intelligence Group +AI14411,AI Specialist,109208,GBP,81906,SE,PT,United Kingdom,M,United Kingdom,100,"Tableau, Git, GCP, PyTorch",PhD,7,Energy,2024-02-01,2024-02-26,1993,7,Predictive Systems +AI14412,Computer Vision Engineer,59992,USD,59992,EX,PT,India,M,Turkey,100,"NLP, PyTorch, AWS, GCP, Java",Master,11,Consulting,2025-03-26,2025-05-29,901,8,Cognitive Computing +AI14413,Data Scientist,81724,USD,81724,EN,FL,Sweden,L,Sweden,0,"Java, Hadoop, Azure, Computer Vision, Git",PhD,1,Manufacturing,2024-05-20,2024-07-27,1347,8.9,TechCorp Inc +AI14414,Autonomous Systems Engineer,152556,USD,152556,SE,PT,Norway,S,Norway,0,"Deep Learning, SQL, Computer Vision, Scala, Azure",Master,5,Automotive,2025-02-27,2025-03-17,563,5.3,Advanced Robotics +AI14415,AI Consultant,93627,SGD,121715,MI,CT,Singapore,M,Singapore,50,"Data Visualization, TensorFlow, Scala",Bachelor,2,Media,2024-12-22,2025-01-18,2345,6.4,Predictive Systems +AI14416,AI Consultant,368934,USD,368934,EX,PT,Norway,L,Norway,0,"TensorFlow, Azure, PyTorch, Tableau, Python",Associate,12,Energy,2024-11-07,2025-01-03,594,8.8,Smart Analytics +AI14417,ML Ops Engineer,62871,USD,62871,EN,FT,Ireland,M,Thailand,100,"AWS, SQL, Python",Master,1,Media,2025-04-02,2025-04-24,2391,6.5,Machine Intelligence Group +AI14418,AI Software Engineer,163945,SGD,213129,EX,FT,Singapore,M,Germany,100,"GCP, Data Visualization, AWS",Associate,13,Technology,2024-01-10,2024-03-02,2184,8.1,Predictive Systems +AI14419,AI Software Engineer,282346,CHF,254111,EX,PT,Switzerland,S,Ireland,0,"Scala, TensorFlow, AWS, R",Bachelor,18,Finance,2025-02-06,2025-04-10,949,7.3,Neural Networks Co +AI14420,AI Architect,198337,USD,198337,EX,FT,Finland,L,Israel,100,"Kubernetes, Azure, Statistics, Git",Bachelor,17,Real Estate,2024-03-03,2024-03-25,2005,6.5,AI Innovations +AI14421,Data Analyst,75384,USD,75384,SE,FT,China,L,Turkey,50,"Kubernetes, Linux, Data Visualization",Master,9,Consulting,2024-10-06,2024-11-05,1413,9.4,Cloud AI Solutions +AI14422,NLP Engineer,209294,EUR,177900,EX,PT,Germany,M,Germany,100,"R, Python, AWS",Master,17,Energy,2024-10-27,2024-11-25,1635,8.9,Neural Networks Co +AI14423,Robotics Engineer,61021,USD,61021,EN,PT,Israel,M,Israel,100,"Tableau, Azure, Spark, Java",PhD,1,Telecommunications,2025-03-09,2025-04-03,715,6.4,Neural Networks Co +AI14424,AI Software Engineer,132259,GBP,99194,SE,FT,United Kingdom,S,United Kingdom,0,"Python, AWS, Data Visualization, Linux, GCP",Bachelor,8,Media,2024-06-09,2024-07-27,711,9.2,TechCorp Inc +AI14425,AI Specialist,131957,USD,131957,SE,PT,Sweden,S,Sweden,100,"Python, AWS, TensorFlow",PhD,9,Media,2024-09-19,2024-10-08,694,5.3,Machine Intelligence Group +AI14426,Deep Learning Engineer,87003,USD,87003,EN,PT,United States,L,United States,100,"Tableau, Docker, Hadoop, PyTorch, R",Bachelor,0,Education,2024-07-07,2024-08-17,1928,5.9,Smart Analytics +AI14427,AI Product Manager,220540,EUR,187459,EX,CT,Netherlands,S,Netherlands,50,"AWS, Linux, Kubernetes, Statistics, Mathematics",Associate,11,Education,2024-08-16,2024-09-06,1340,10,Algorithmic Solutions +AI14428,Data Analyst,167769,CHF,150992,SE,PT,Switzerland,L,Switzerland,50,"Hadoop, Java, NLP, Mathematics, Deep Learning",Associate,7,Government,2024-01-26,2024-03-16,1036,5.7,Machine Intelligence Group +AI14429,Head of AI,187950,USD,187950,EX,FL,South Korea,S,China,50,"Data Visualization, AWS, TensorFlow, Hadoop, Azure",Associate,19,Gaming,2024-12-24,2025-02-17,920,5.7,DeepTech Ventures +AI14430,ML Ops Engineer,58695,EUR,49891,EN,FT,Germany,S,Singapore,0,"Linux, Kubernetes, NLP, Mathematics",Master,0,Automotive,2024-02-21,2024-03-29,588,7.4,DeepTech Ventures +AI14431,Machine Learning Engineer,265749,USD,265749,EX,CT,Ireland,L,Ireland,0,"PyTorch, Java, MLOps, Scala, Azure",Bachelor,11,Gaming,2024-10-23,2024-11-23,697,8.8,DataVision Ltd +AI14432,Research Scientist,110493,EUR,93919,SE,PT,Germany,S,Germany,100,"R, NLP, Python",PhD,7,Healthcare,2025-01-11,2025-03-17,2345,6.9,Quantum Computing Inc +AI14433,Computer Vision Engineer,20337,USD,20337,EN,FT,India,S,Switzerland,0,"GCP, SQL, PyTorch",PhD,0,Consulting,2025-04-08,2025-05-31,1553,9.3,Algorithmic Solutions +AI14434,Computer Vision Engineer,123983,JPY,13638130,MI,CT,Japan,L,Japan,100,"Python, Kubernetes, Spark, Data Visualization",Associate,2,Gaming,2025-01-20,2025-02-19,830,9.8,Machine Intelligence Group +AI14435,AI Software Engineer,206076,USD,206076,EX,FL,United States,L,United States,0,"GCP, Scala, R",Master,14,Transportation,2025-01-22,2025-02-27,1893,5.4,Predictive Systems +AI14436,Computer Vision Engineer,76678,CAD,95848,MI,FT,Canada,S,Canada,100,"Linux, Deep Learning, Docker, TensorFlow",PhD,4,Media,2024-05-27,2024-07-02,1571,6.1,Autonomous Tech +AI14437,AI Specialist,108696,USD,108696,EX,CT,China,L,China,50,"SQL, Python, Git, Tableau",Associate,13,Education,2024-04-14,2024-05-10,1504,9.3,DataVision Ltd +AI14438,NLP Engineer,124557,CAD,155696,SE,FT,Canada,S,Canada,100,"Scala, PyTorch, SQL, Data Visualization",Associate,9,Technology,2024-10-08,2024-10-26,2225,9.7,Cloud AI Solutions +AI14439,Research Scientist,95689,EUR,81336,MI,PT,Germany,S,South Africa,0,"GCP, Azure, PyTorch, TensorFlow, AWS",Bachelor,4,Transportation,2024-05-16,2024-07-15,1331,7.1,Autonomous Tech +AI14440,AI Specialist,295651,SGD,384346,EX,FT,Singapore,L,Vietnam,0,"Python, GCP, Tableau, TensorFlow, Spark",PhD,15,Telecommunications,2024-10-10,2024-11-30,1805,6.3,DataVision Ltd +AI14441,AI Software Engineer,219218,CAD,274023,EX,PT,Canada,L,Canada,100,"Data Visualization, Scala, Mathematics, Java, AWS",Associate,10,Energy,2025-03-13,2025-04-26,2212,5.1,Predictive Systems +AI14442,Machine Learning Engineer,125323,CAD,156654,SE,CT,Canada,M,Canada,50,"PyTorch, TensorFlow, Scala, AWS, Java",Master,5,Telecommunications,2025-01-23,2025-03-22,1414,6,Smart Analytics +AI14443,Data Scientist,62189,EUR,52861,EN,CT,France,L,Ghana,0,"Python, TensorFlow, Linux, Azure",PhD,0,Healthcare,2025-03-02,2025-03-20,779,9.4,Cognitive Computing +AI14444,Research Scientist,82731,USD,82731,EN,FT,United States,M,Argentina,50,"Spark, MLOps, Scala",Master,1,Finance,2025-02-14,2025-03-10,2269,9.3,Digital Transformation LLC +AI14445,Data Engineer,104548,SGD,135912,SE,CT,Singapore,S,Singapore,100,"Python, TensorFlow, Deep Learning, MLOps",Associate,9,Real Estate,2024-02-06,2024-03-11,1024,6.9,Smart Analytics +AI14446,AI Research Scientist,186864,SGD,242923,EX,CT,Singapore,S,China,0,"Python, TensorFlow, Data Visualization, R",Associate,10,Retail,2024-12-30,2025-02-12,1927,8.8,Advanced Robotics +AI14447,Computer Vision Engineer,90839,CHF,81755,EN,PT,Switzerland,M,Switzerland,50,"Java, Azure, Deep Learning, Scala",PhD,0,Real Estate,2025-03-31,2025-05-22,1877,9,Advanced Robotics +AI14448,AI Consultant,70876,USD,70876,SE,CT,China,L,China,0,"Python, GCP, Git, Deep Learning",PhD,8,Retail,2024-09-18,2024-11-18,1534,8.4,AI Innovations +AI14449,Robotics Engineer,124242,EUR,105606,EX,FT,France,S,Spain,0,"Spark, Git, Python",Associate,13,Consulting,2025-02-17,2025-03-16,919,5.2,Autonomous Tech +AI14450,Deep Learning Engineer,82268,USD,82268,MI,PT,United States,S,United States,100,"R, MLOps, Hadoop, GCP",Master,4,Retail,2025-01-16,2025-03-19,2139,6.8,Cognitive Computing +AI14451,Data Scientist,108994,EUR,92645,MI,FL,Germany,L,Germany,100,"Deep Learning, NLP, Python",Bachelor,4,Media,2024-05-24,2024-06-12,777,5.2,Algorithmic Solutions +AI14452,Principal Data Scientist,88271,USD,88271,MI,FL,Israel,M,Israel,50,"SQL, R, Linux, Docker",Associate,3,Government,2024-12-21,2025-02-05,1348,5.6,Advanced Robotics +AI14453,Deep Learning Engineer,141697,GBP,106273,SE,FL,United Kingdom,M,United Kingdom,0,"Java, AWS, MLOps, Python, Computer Vision",PhD,8,Transportation,2024-10-20,2024-12-04,1060,6,Advanced Robotics +AI14454,AI Software Engineer,77206,CAD,96508,MI,FL,Canada,M,Canada,100,"Spark, Hadoop, Kubernetes, SQL",Master,2,Transportation,2024-03-17,2024-04-28,1765,6,DataVision Ltd +AI14455,Deep Learning Engineer,63781,USD,63781,EN,FT,Ireland,M,Ireland,0,"Scala, GCP, MLOps, Computer Vision, Linux",PhD,1,Consulting,2024-09-06,2024-09-22,2327,7.3,DataVision Ltd +AI14456,Autonomous Systems Engineer,107579,GBP,80684,MI,CT,United Kingdom,L,United Kingdom,0,"Linux, NLP, Spark, Python",Associate,2,Technology,2024-11-08,2024-12-27,654,6.3,DeepTech Ventures +AI14457,AI Architect,210771,CHF,189694,SE,FT,Switzerland,M,Switzerland,50,"Scala, Hadoop, Docker, Computer Vision, Spark",PhD,8,Technology,2024-02-17,2024-04-09,1854,8,Digital Transformation LLC +AI14458,Principal Data Scientist,71437,JPY,7858070,MI,CT,Japan,S,Poland,100,"Kubernetes, Scala, Docker",PhD,4,Healthcare,2024-06-23,2024-08-29,1933,5.2,Machine Intelligence Group +AI14459,Computer Vision Engineer,57340,USD,57340,EN,CT,Sweden,S,Sweden,0,"PyTorch, Python, Mathematics",Associate,1,Manufacturing,2025-03-10,2025-04-22,2221,6.5,TechCorp Inc +AI14460,Robotics Engineer,89880,CAD,112350,MI,CT,Canada,L,Japan,0,"GCP, Hadoop, Git, Tableau, PyTorch",Master,2,Technology,2024-09-28,2024-11-06,1323,8.9,AI Innovations +AI14461,ML Ops Engineer,68307,USD,68307,MI,CT,Israel,S,Israel,100,"AWS, Python, TensorFlow, PyTorch",PhD,4,Real Estate,2025-02-06,2025-03-01,2079,7.2,Cloud AI Solutions +AI14462,Autonomous Systems Engineer,149703,CAD,187129,EX,PT,Canada,S,Canada,0,"Hadoop, Java, Linux",Associate,15,Automotive,2024-05-15,2024-07-27,2181,6.4,AI Innovations +AI14463,ML Ops Engineer,31779,USD,31779,EN,CT,India,L,India,0,"Scala, Azure, Statistics, Python",Associate,1,Automotive,2024-12-22,2025-02-13,533,9.4,TechCorp Inc +AI14464,AI Product Manager,131531,GBP,98648,MI,PT,United Kingdom,L,United Kingdom,50,"Git, Data Visualization, Hadoop",PhD,4,Education,2024-03-01,2024-04-14,1022,5.8,Smart Analytics +AI14465,AI Product Manager,200424,CAD,250530,EX,PT,Canada,M,Canada,0,"MLOps, Python, Kubernetes, TensorFlow, Java",Master,17,Transportation,2024-11-15,2024-12-29,2202,6.9,Quantum Computing Inc +AI14466,Robotics Engineer,129718,GBP,97289,MI,FL,United Kingdom,L,Ukraine,100,"Statistics, SQL, MLOps, Hadoop, Scala",PhD,3,Retail,2024-06-15,2024-07-12,1936,6.9,Cloud AI Solutions +AI14467,AI Software Engineer,84762,USD,84762,MI,FL,Finland,S,Hungary,100,"Python, Computer Vision, Java, Deep Learning",Bachelor,3,Gaming,2024-03-06,2024-05-06,1062,6.3,Digital Transformation LLC +AI14468,Data Analyst,143526,CAD,179408,SE,FL,Canada,L,Austria,100,"Java, Kubernetes, AWS, PyTorch",Master,9,Education,2024-06-19,2024-07-05,1739,8.8,Algorithmic Solutions +AI14469,AI Consultant,134652,USD,134652,EX,PT,Finland,S,Finland,50,"MLOps, AWS, Git, SQL",Associate,18,Media,2024-03-21,2024-04-10,2226,7.2,AI Innovations +AI14470,Principal Data Scientist,72770,USD,72770,EN,FL,Finland,M,Finland,50,"SQL, PyTorch, Deep Learning, GCP, Mathematics",Master,1,Telecommunications,2025-02-01,2025-03-28,2147,8.6,Cloud AI Solutions +AI14471,Data Scientist,165036,CHF,148532,SE,FT,Switzerland,S,Switzerland,50,"Azure, Git, Data Visualization, TensorFlow, Kubernetes",Associate,9,Finance,2024-03-14,2024-04-18,973,8.5,Machine Intelligence Group +AI14472,Machine Learning Researcher,277879,USD,277879,EX,PT,Denmark,L,Denmark,50,"Data Visualization, Azure, R, SQL",Bachelor,10,Energy,2024-01-25,2024-03-31,2242,7.7,Cloud AI Solutions +AI14473,AI Specialist,292246,USD,292246,EX,FL,Ireland,L,Ireland,100,"AWS, Scala, Mathematics, MLOps",PhD,16,Consulting,2024-07-01,2024-08-04,1417,8.9,Machine Intelligence Group +AI14474,AI Software Engineer,122288,EUR,103945,MI,PT,Netherlands,L,Netherlands,50,"TensorFlow, Kubernetes, Scala",PhD,4,Consulting,2024-08-16,2024-09-22,1424,7,Autonomous Tech +AI14475,AI Architect,185384,USD,185384,EX,CT,Denmark,M,Denmark,100,"Spark, Deep Learning, Python",Associate,18,Telecommunications,2024-12-22,2025-01-09,734,9.1,AI Innovations +AI14476,AI Architect,204233,EUR,173598,EX,FL,Austria,S,Austria,0,"Git, Computer Vision, Tableau",Master,14,Finance,2024-03-22,2024-04-16,1045,7.6,Cognitive Computing +AI14477,AI Consultant,57991,CAD,72489,EN,CT,Canada,L,Austria,50,"Computer Vision, Python, Data Visualization",Bachelor,1,Telecommunications,2024-02-09,2024-04-01,2183,8.7,Advanced Robotics +AI14478,Autonomous Systems Engineer,235868,USD,235868,EX,FL,Finland,L,Finland,100,"Deep Learning, Scala, SQL",PhD,11,Technology,2025-01-30,2025-02-15,1745,5.8,Cognitive Computing +AI14479,Research Scientist,150822,EUR,128199,SE,FT,Netherlands,L,Netherlands,50,"Kubernetes, Scala, MLOps, Mathematics, Statistics",Master,7,Government,2024-05-20,2024-06-18,526,8.5,Machine Intelligence Group +AI14480,Machine Learning Researcher,112953,USD,112953,EN,FL,Denmark,L,Denmark,50,"Tableau, Statistics, Spark, MLOps, Git",Bachelor,0,Manufacturing,2024-01-25,2024-02-19,876,8.4,Algorithmic Solutions +AI14481,ML Ops Engineer,201083,AUD,271462,EX,PT,Australia,S,Colombia,0,"Java, Hadoop, SQL, Git, Docker",Associate,14,Real Estate,2024-07-03,2024-08-11,1486,7.3,Future Systems +AI14482,Machine Learning Engineer,63962,CAD,79953,MI,CT,Canada,S,Canada,50,"Azure, PyTorch, SQL, Computer Vision, Mathematics",Bachelor,2,Consulting,2025-02-08,2025-04-02,1369,8.1,Cognitive Computing +AI14483,AI Consultant,124552,CHF,112097,MI,CT,Switzerland,M,Switzerland,100,"SQL, Azure, Scala, Python",PhD,4,Telecommunications,2025-01-26,2025-03-02,1392,9,Predictive Systems +AI14484,Data Analyst,65428,USD,65428,EN,FL,Israel,M,Chile,50,"SQL, Hadoop, Mathematics, Computer Vision, Deep Learning",Associate,0,Real Estate,2025-04-06,2025-06-14,1254,6.9,DeepTech Ventures +AI14485,Computer Vision Engineer,122062,CHF,109856,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, TensorFlow, Statistics, R, Deep Learning",Bachelor,2,Telecommunications,2024-05-11,2024-06-15,2116,7.8,Smart Analytics +AI14486,AI Research Scientist,111469,AUD,150483,SE,FL,Australia,S,Brazil,0,"MLOps, Git, Kubernetes, NLP",PhD,8,Media,2025-03-25,2025-05-16,581,5.9,Machine Intelligence Group +AI14487,Deep Learning Engineer,181761,USD,181761,EX,FT,South Korea,M,South Korea,50,"Tableau, Computer Vision, Kubernetes",PhD,10,Government,2025-01-17,2025-02-08,1234,9.5,Cloud AI Solutions +AI14488,Data Analyst,116229,GBP,87172,SE,PT,United Kingdom,M,Latvia,100,"Kubernetes, Docker, MLOps, Git",Bachelor,8,Finance,2025-01-03,2025-02-16,1852,9.8,DataVision Ltd +AI14489,Data Scientist,82622,USD,82622,EN,CT,Finland,L,Finland,100,"SQL, Kubernetes, Statistics, Deep Learning, PyTorch",Master,0,Gaming,2025-01-20,2025-03-16,1749,8.5,Autonomous Tech +AI14490,AI Research Scientist,96369,USD,96369,EN,FL,Norway,L,Norway,50,"MLOps, Git, Python",PhD,0,Consulting,2024-01-30,2024-03-08,1367,9.4,Cognitive Computing +AI14491,Research Scientist,53103,USD,53103,EN,CT,Israel,M,Israel,0,"Tableau, Kubernetes, Scala, R, Mathematics",Bachelor,1,Consulting,2024-04-27,2024-07-04,1971,9.2,Algorithmic Solutions +AI14492,NLP Engineer,57126,EUR,48557,EN,PT,France,S,United Kingdom,50,"Python, Spark, NLP",Master,0,Media,2024-08-11,2024-10-23,1473,7.3,Machine Intelligence Group +AI14493,Machine Learning Engineer,94857,JPY,10434270,EN,PT,Japan,L,Japan,0,"AWS, Java, Scala, Spark",Bachelor,0,Automotive,2025-03-30,2025-05-04,1942,8.4,Advanced Robotics +AI14494,Research Scientist,99850,EUR,84873,SE,PT,Austria,S,Germany,100,"NLP, Java, Tableau, GCP",Master,7,Automotive,2024-10-14,2024-12-12,1764,9.5,Autonomous Tech +AI14495,Machine Learning Researcher,26941,USD,26941,EN,FT,India,L,India,50,"Kubernetes, Docker, Data Visualization, GCP",Bachelor,1,Healthcare,2024-01-29,2024-03-18,929,5.2,Autonomous Tech +AI14496,Principal Data Scientist,37543,USD,37543,MI,FT,India,L,Romania,100,"Data Visualization, Hadoop, TensorFlow",PhD,4,Manufacturing,2025-02-09,2025-03-27,1623,9.6,Cognitive Computing +AI14497,Head of AI,145765,USD,145765,SE,PT,Israel,L,Israel,50,"Python, TensorFlow, PyTorch",Associate,9,Energy,2024-07-07,2024-08-09,1970,7.4,Machine Intelligence Group +AI14498,Data Analyst,109358,USD,109358,SE,FT,Sweden,M,Ukraine,100,"Data Visualization, SQL, Kubernetes",Associate,6,Education,2025-03-23,2025-05-26,1121,6,Quantum Computing Inc +AI14499,Computer Vision Engineer,85375,USD,85375,EX,CT,China,M,Vietnam,0,"Hadoop, Java, Azure, GCP, Scala",Associate,16,Energy,2024-02-13,2024-04-14,1288,9.6,Autonomous Tech +AI14500,AI Research Scientist,34369,USD,34369,MI,FT,China,S,China,50,"Java, Kubernetes, Hadoop, Statistics",Associate,2,Finance,2024-10-24,2024-12-15,2200,8.1,Smart Analytics +AI14501,Head of AI,101172,USD,101172,MI,FT,United States,S,United States,100,"Python, NLP, TensorFlow, GCP",PhD,3,Finance,2024-10-26,2024-12-02,1033,5.6,AI Innovations +AI14502,Robotics Engineer,100350,USD,100350,EN,FT,Denmark,L,Denmark,50,"SQL, AWS, GCP",Bachelor,0,Manufacturing,2024-12-20,2025-03-03,1176,7.2,Cloud AI Solutions +AI14503,Computer Vision Engineer,53409,SGD,69432,EN,FL,Singapore,S,Singapore,50,"Hadoop, Java, PyTorch",PhD,1,Media,2024-06-25,2024-09-03,2077,7.7,Future Systems +AI14504,Head of AI,109264,USD,109264,MI,PT,Finland,L,Czech Republic,0,"Java, Linux, AWS",Bachelor,3,Finance,2024-03-29,2024-06-06,677,6.5,Digital Transformation LLC +AI14505,Research Scientist,67190,USD,67190,EN,FL,United States,M,United States,0,"SQL, Spark, Computer Vision",Master,0,Energy,2024-06-12,2024-07-13,1965,8.4,TechCorp Inc +AI14506,AI Architect,68547,JPY,7540170,EN,FT,Japan,S,Argentina,0,"Mathematics, PyTorch, Computer Vision",PhD,0,Automotive,2025-02-05,2025-03-18,1778,5.3,Cloud AI Solutions +AI14507,Machine Learning Researcher,86075,USD,86075,MI,PT,Israel,S,Israel,50,"Hadoop, Java, Mathematics",Master,2,Gaming,2024-05-15,2024-06-18,1624,9.5,Advanced Robotics +AI14508,ML Ops Engineer,71794,USD,71794,SE,FL,China,M,China,50,"GCP, Java, Python, Git, NLP",Master,8,Telecommunications,2024-07-21,2024-08-14,1256,8.3,Quantum Computing Inc +AI14509,AI Product Manager,89033,EUR,75678,MI,CT,Netherlands,S,Netherlands,0,"Data Visualization, R, SQL, Computer Vision",Bachelor,2,Media,2024-09-30,2024-10-17,1062,5.3,Digital Transformation LLC +AI14510,Principal Data Scientist,241780,GBP,181335,EX,FT,United Kingdom,S,United Kingdom,50,"SQL, Java, GCP, PyTorch",Associate,13,Gaming,2025-03-26,2025-06-02,1804,5.4,Advanced Robotics +AI14511,Head of AI,90029,GBP,67522,MI,PT,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, TensorFlow, Kubernetes",Associate,2,Media,2024-07-29,2024-08-25,1922,8.2,Machine Intelligence Group +AI14512,NLP Engineer,125238,USD,125238,SE,FL,Israel,S,Israel,0,"Hadoop, Spark, Kubernetes",Bachelor,9,Retail,2024-07-16,2024-09-27,764,8.6,AI Innovations +AI14513,ML Ops Engineer,60541,USD,60541,MI,FL,South Korea,S,South Korea,50,"Git, Linux, NLP",Bachelor,2,Automotive,2024-08-17,2024-09-17,1236,8.7,DataVision Ltd +AI14514,AI Specialist,45630,EUR,38786,EN,FT,France,S,France,0,"TensorFlow, GCP, Linux",Associate,1,Healthcare,2024-07-04,2024-07-29,676,6.1,Smart Analytics +AI14515,AI Consultant,159534,CHF,143581,SE,FL,Switzerland,M,Switzerland,0,"Deep Learning, GCP, R",Bachelor,6,Finance,2024-11-09,2025-01-21,1441,7.5,Algorithmic Solutions +AI14516,Data Analyst,68523,USD,68523,EN,FL,Ireland,M,Ireland,0,"Kubernetes, Deep Learning, Hadoop, Statistics",Bachelor,0,Energy,2024-11-15,2025-01-23,836,6.5,TechCorp Inc +AI14517,Computer Vision Engineer,93997,EUR,79897,MI,FT,Austria,M,Austria,50,"GCP, PyTorch, Data Visualization, SQL",Master,3,Transportation,2025-01-27,2025-03-02,1646,6.8,DeepTech Ventures +AI14518,Robotics Engineer,61638,EUR,52392,MI,FL,France,S,United Kingdom,100,"Java, Mathematics, AWS, Computer Vision",PhD,3,Automotive,2025-02-07,2025-03-14,2027,6.3,DeepTech Ventures +AI14519,Data Engineer,111944,USD,111944,SE,FL,Finland,L,Finland,100,"Hadoop, Spark, Java, Linux, MLOps",Associate,9,Consulting,2024-02-19,2024-04-24,1783,9.6,DataVision Ltd +AI14520,Computer Vision Engineer,99102,JPY,10901220,SE,FL,Japan,S,Japan,100,"Hadoop, MLOps, Git, Statistics",Associate,6,Government,2024-06-26,2024-08-05,2283,9.9,Smart Analytics +AI14521,AI Product Manager,66373,USD,66373,EN,FL,Ireland,S,Ireland,0,"Python, Docker, Git",Bachelor,0,Gaming,2024-12-27,2025-02-22,2425,6.7,DataVision Ltd +AI14522,Machine Learning Engineer,286837,USD,286837,EX,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Linux, PyTorch, GCP",Bachelor,10,Government,2024-01-06,2024-03-19,737,6.3,AI Innovations +AI14523,Computer Vision Engineer,163282,EUR,138790,EX,CT,France,M,France,100,"Scala, Python, Deep Learning, TensorFlow, AWS",PhD,12,Consulting,2025-01-27,2025-02-16,1004,6.4,Machine Intelligence Group +AI14524,Machine Learning Engineer,116441,USD,116441,SE,FT,South Korea,M,South Korea,100,"TensorFlow, Azure, Data Visualization",Master,9,Manufacturing,2025-02-28,2025-03-30,1732,5.6,Future Systems +AI14525,AI Software Engineer,72672,CAD,90840,EN,FT,Canada,M,China,0,"Scala, AWS, Computer Vision",Master,1,Media,2024-09-13,2024-10-15,789,5.4,Cloud AI Solutions +AI14526,Principal Data Scientist,125105,USD,125105,SE,FT,Sweden,S,Sweden,0,"R, Kubernetes, MLOps",PhD,8,Healthcare,2024-09-01,2024-10-22,623,5.4,Future Systems +AI14527,AI Architect,160966,SGD,209256,SE,CT,Singapore,L,Singapore,50,"Data Visualization, Docker, Statistics, Azure, MLOps",Bachelor,5,Manufacturing,2024-08-09,2024-10-12,1920,7.8,Cloud AI Solutions +AI14528,NLP Engineer,87326,CAD,109158,MI,CT,Canada,S,Canada,50,"Kubernetes, TensorFlow, SQL",PhD,4,Energy,2024-05-15,2024-06-07,754,7,Smart Analytics +AI14529,AI Product Manager,135601,USD,135601,SE,PT,Ireland,M,China,50,"Linux, Python, Statistics, AWS",Master,8,Gaming,2024-03-17,2024-04-17,1413,6.1,Algorithmic Solutions +AI14530,Principal Data Scientist,217533,CHF,195780,EX,PT,Switzerland,M,Romania,0,"GCP, Docker, SQL",Master,17,Finance,2025-03-26,2025-06-01,633,8.2,Cloud AI Solutions +AI14531,Head of AI,98113,EUR,83396,MI,FL,Austria,M,France,50,"Python, Tableau, Kubernetes, Linux, Java",Associate,3,Automotive,2024-10-30,2024-11-16,2184,8.1,DeepTech Ventures +AI14532,Autonomous Systems Engineer,81244,USD,81244,EN,PT,Israel,L,Hungary,50,"Spark, PyTorch, R, AWS, MLOps",Associate,1,Gaming,2024-02-01,2024-03-22,628,6.4,Autonomous Tech +AI14533,AI Architect,89895,EUR,76411,EN,CT,Netherlands,L,Italy,100,"Scala, Statistics, Java, Azure",PhD,0,Healthcare,2024-06-24,2024-08-11,1131,8,Autonomous Tech +AI14534,Research Scientist,171139,USD,171139,EX,FL,Sweden,M,Latvia,100,"TensorFlow, Git, SQL, Java, Python",Master,15,Technology,2024-06-10,2024-07-11,1799,9.7,Neural Networks Co +AI14535,Robotics Engineer,62756,SGD,81583,EN,FL,Singapore,M,Singapore,50,"Tableau, PyTorch, MLOps, TensorFlow, Linux",Master,0,Education,2024-06-04,2024-07-10,918,7.3,Smart Analytics +AI14536,Deep Learning Engineer,335964,CHF,302368,EX,CT,Switzerland,M,Switzerland,50,"R, Hadoop, Azure, GCP",PhD,11,Consulting,2025-02-20,2025-05-03,707,7.6,DataVision Ltd +AI14537,Data Scientist,106920,EUR,90882,MI,FT,Germany,M,United Kingdom,50,"Linux, AWS, Mathematics",Master,3,Healthcare,2024-09-17,2024-11-29,2132,7.3,Digital Transformation LLC +AI14538,Deep Learning Engineer,119575,EUR,101639,MI,CT,Austria,L,Austria,100,"Kubernetes, Java, Python, NLP, Spark",Bachelor,4,Energy,2024-12-04,2024-12-24,2163,6.1,AI Innovations +AI14539,Computer Vision Engineer,84559,USD,84559,EX,FT,China,M,China,50,"TensorFlow, SQL, Mathematics",PhD,10,Gaming,2025-04-15,2025-05-18,1877,8.6,Predictive Systems +AI14540,Head of AI,101252,USD,101252,MI,FL,Norway,M,Norway,100,"NLP, SQL, R, Docker",Associate,2,Media,2024-01-05,2024-03-01,1702,9.2,Digital Transformation LLC +AI14541,Deep Learning Engineer,236723,CHF,213051,EX,FL,Switzerland,L,Switzerland,0,"SQL, Scala, TensorFlow, GCP, Git",Master,17,Real Estate,2024-10-13,2024-11-13,2464,9.2,Machine Intelligence Group +AI14542,Data Analyst,244256,USD,244256,EX,FL,United States,S,United States,0,"Tableau, PyTorch, R",Bachelor,16,Finance,2024-07-03,2024-07-20,2238,5.9,Machine Intelligence Group +AI14543,Machine Learning Engineer,158103,EUR,134388,EX,FT,Germany,M,Denmark,50,"Hadoop, SQL, Java, GCP, PyTorch",PhD,11,Transportation,2025-01-30,2025-02-26,955,5.6,AI Innovations +AI14544,Head of AI,130549,EUR,110967,SE,CT,Germany,S,Germany,50,"R, GCP, Scala",Bachelor,5,Manufacturing,2025-03-06,2025-04-19,2156,7,TechCorp Inc +AI14545,AI Product Manager,175962,USD,175962,SE,FT,Denmark,M,Denmark,100,"Data Visualization, Docker, AWS, SQL, Linux",Master,7,Education,2025-03-23,2025-05-10,2102,5.9,Future Systems +AI14546,Head of AI,140334,USD,140334,EX,PT,Ireland,M,Ireland,100,"TensorFlow, Linux, Azure",PhD,13,Healthcare,2025-01-26,2025-03-27,1612,5.6,Cloud AI Solutions +AI14547,Machine Learning Engineer,83160,CHF,74844,EN,PT,Switzerland,M,Switzerland,50,"Docker, Linux, Deep Learning, TensorFlow, Git",Associate,0,Consulting,2024-12-10,2025-01-21,1282,9,Algorithmic Solutions +AI14548,Computer Vision Engineer,195354,AUD,263728,EX,CT,Australia,L,Indonesia,100,"Kubernetes, Scala, NLP, GCP, Tableau",Associate,19,Education,2025-04-21,2025-05-31,2365,9.6,AI Innovations +AI14549,AI Product Manager,62596,AUD,84505,EN,FL,Australia,L,Canada,100,"Python, Scala, Statistics",Bachelor,1,Consulting,2024-10-21,2024-12-22,1983,5.5,Algorithmic Solutions +AI14550,Machine Learning Engineer,246772,EUR,209756,EX,PT,Austria,L,Austria,100,"Deep Learning, Git, Scala, Java, Computer Vision",Associate,13,Energy,2024-10-24,2024-11-28,770,9.6,Cognitive Computing +AI14551,Data Engineer,59096,USD,59096,EN,CT,South Korea,S,South Korea,100,"Java, Hadoop, Data Visualization, Linux, Tableau",Master,1,Energy,2024-06-14,2024-08-19,2494,8,Predictive Systems +AI14552,Principal Data Scientist,144657,USD,144657,EX,FT,Sweden,S,Portugal,50,"NLP, Deep Learning, Data Visualization, Hadoop, SQL",Bachelor,12,Gaming,2024-02-12,2024-03-29,2372,9.8,AI Innovations +AI14553,Research Scientist,98312,USD,98312,EX,FT,China,L,China,100,"Scala, Python, NLP, R",Associate,17,Retail,2024-10-08,2024-11-24,574,9.4,Advanced Robotics +AI14554,Machine Learning Researcher,268721,EUR,228413,EX,CT,Germany,L,Germany,100,"Python, SQL, AWS",Master,10,Transportation,2024-12-16,2025-01-21,2163,5.8,Machine Intelligence Group +AI14555,Robotics Engineer,24804,USD,24804,EN,CT,China,S,Ukraine,50,"Python, Azure, TensorFlow, R",PhD,1,Real Estate,2024-06-09,2024-07-22,563,6.5,Cognitive Computing +AI14556,Robotics Engineer,116955,AUD,157889,SE,FT,Australia,S,Australia,100,"Python, Kubernetes, Data Visualization",Associate,8,Automotive,2025-03-15,2025-05-19,1300,9.5,Digital Transformation LLC +AI14557,Computer Vision Engineer,102088,EUR,86775,MI,CT,France,L,France,100,"Azure, GCP, SQL, Deep Learning, PyTorch",Associate,3,Healthcare,2025-04-02,2025-06-03,1698,6.4,Advanced Robotics +AI14558,Autonomous Systems Engineer,150619,EUR,128026,SE,CT,Germany,L,Germany,50,"Scala, Python, Mathematics, Deep Learning",Associate,7,Technology,2025-02-28,2025-03-30,1410,8.2,Neural Networks Co +AI14559,AI Specialist,110839,CAD,138549,MI,PT,Canada,L,Malaysia,50,"SQL, NLP, Kubernetes, Mathematics",Bachelor,4,Gaming,2025-04-15,2025-05-02,1293,6,Cloud AI Solutions +AI14560,Computer Vision Engineer,201264,CHF,181138,EX,PT,Switzerland,M,Germany,0,"GCP, Scala, SQL, Computer Vision",Master,15,Manufacturing,2024-11-01,2024-12-17,2398,9.8,Cloud AI Solutions +AI14561,Autonomous Systems Engineer,87432,USD,87432,EN,PT,United States,M,United States,100,"TensorFlow, GCP, MLOps",Master,0,Transportation,2024-09-30,2024-12-02,1262,5.5,Future Systems +AI14562,AI Software Engineer,63493,EUR,53969,EN,PT,Netherlands,L,Netherlands,50,"NLP, SQL, Linux",Associate,0,Real Estate,2024-10-14,2024-12-24,2168,9.5,Digital Transformation LLC +AI14563,Research Scientist,184467,JPY,20291370,EX,FL,Japan,L,Japan,50,"Mathematics, Kubernetes, Azure, Deep Learning",PhD,18,Government,2024-05-23,2024-06-11,872,5.7,Advanced Robotics +AI14564,AI Research Scientist,209096,EUR,177732,EX,FT,Germany,M,Germany,100,"Kubernetes, Azure, Spark, GCP, Java",PhD,19,Real Estate,2024-02-29,2024-04-25,1107,8.6,Algorithmic Solutions +AI14565,Research Scientist,98677,SGD,128280,MI,PT,Singapore,S,Singapore,100,"NLP, AWS, Kubernetes, SQL, GCP",Associate,2,Retail,2024-02-23,2024-03-20,741,5.5,Advanced Robotics +AI14566,ML Ops Engineer,99800,CAD,124750,SE,FL,Canada,M,Canada,50,"PyTorch, Spark, TensorFlow, Kubernetes",PhD,5,Real Estate,2024-11-10,2025-01-21,1041,9.6,Digital Transformation LLC +AI14567,AI Research Scientist,109379,USD,109379,MI,CT,Finland,L,Finland,100,"Java, SQL, Linux",PhD,3,Transportation,2025-01-01,2025-03-06,1690,6.2,TechCorp Inc +AI14568,Data Analyst,68608,USD,68608,SE,CT,China,L,China,0,"Hadoop, Python, TensorFlow",Associate,5,Telecommunications,2024-08-01,2024-09-10,2444,8.5,TechCorp Inc +AI14569,Head of AI,70451,USD,70451,EX,CT,India,S,India,100,"Linux, Azure, Deep Learning, GCP",Bachelor,19,Consulting,2024-02-28,2024-03-21,985,8.7,DataVision Ltd +AI14570,NLP Engineer,127444,USD,127444,SE,FT,Norway,S,Norway,0,"Python, TensorFlow, Mathematics, AWS",Bachelor,6,Healthcare,2024-10-08,2024-11-11,1031,9.7,Neural Networks Co +AI14571,AI Research Scientist,59585,GBP,44689,EN,CT,United Kingdom,M,Spain,0,"Linux, PyTorch, Statistics, Scala",Associate,1,Transportation,2024-10-02,2024-12-05,2342,7.6,TechCorp Inc +AI14572,Principal Data Scientist,129467,GBP,97100,MI,CT,United Kingdom,L,New Zealand,50,"R, Computer Vision, Mathematics, SQL",Bachelor,2,Technology,2024-12-27,2025-02-02,983,5.9,Machine Intelligence Group +AI14573,AI Architect,89818,CHF,80836,EN,FL,Switzerland,S,Romania,50,"Git, Python, AWS, Deep Learning",PhD,1,Energy,2024-04-01,2024-06-03,1846,5.6,Algorithmic Solutions +AI14574,AI Specialist,168508,USD,168508,EX,FL,Israel,S,Kenya,50,"Hadoop, PyTorch, SQL",Associate,18,Telecommunications,2024-07-26,2024-09-09,2122,5.1,Autonomous Tech +AI14575,Machine Learning Researcher,139480,GBP,104610,SE,PT,United Kingdom,L,Colombia,100,"Azure, Scala, NLP, Mathematics, PyTorch",Master,8,Healthcare,2024-01-04,2024-02-01,2378,8.2,TechCorp Inc +AI14576,Machine Learning Researcher,192002,EUR,163202,EX,FL,Austria,L,Austria,50,"GCP, TensorFlow, Deep Learning, Data Visualization, SQL",Bachelor,18,Education,2024-07-12,2024-08-08,559,7.7,Autonomous Tech +AI14577,NLP Engineer,58121,USD,58121,MI,CT,China,L,China,0,"Mathematics, R, Tableau, SQL",PhD,2,Healthcare,2025-01-12,2025-02-15,1764,8,DeepTech Ventures +AI14578,Research Scientist,134623,EUR,114430,EX,FL,France,S,France,0,"NLP, Data Visualization, Java, R",Associate,15,Education,2025-04-08,2025-05-05,1864,9.3,TechCorp Inc +AI14579,AI Architect,97785,USD,97785,MI,CT,Norway,S,Norway,0,"Java, PyTorch, TensorFlow, Python",PhD,4,Gaming,2024-03-28,2024-05-26,807,7.5,AI Innovations +AI14580,Principal Data Scientist,219292,AUD,296044,EX,FL,Australia,L,Australia,100,"SQL, Mathematics, GCP",Master,11,Real Estate,2024-01-16,2024-03-12,974,6.3,DeepTech Ventures +AI14581,Principal Data Scientist,52713,USD,52713,MI,CT,China,L,China,100,"MLOps, Python, Spark, Scala",Bachelor,2,Telecommunications,2024-05-13,2024-07-10,1083,9.5,Autonomous Tech +AI14582,AI Architect,318665,USD,318665,EX,FT,Denmark,M,Denmark,50,"AWS, PyTorch, Deep Learning",Bachelor,13,Healthcare,2024-11-02,2024-11-19,1618,8.7,Digital Transformation LLC +AI14583,Data Analyst,150768,CHF,135691,MI,FL,Switzerland,M,Switzerland,50,"Statistics, Scala, R, Kubernetes, Python",Master,4,Telecommunications,2024-09-28,2024-11-19,1321,9.3,Predictive Systems +AI14584,Robotics Engineer,130419,USD,130419,MI,CT,Denmark,M,Denmark,50,"Spark, Scala, Deep Learning, TensorFlow, NLP",PhD,2,Manufacturing,2024-11-10,2024-12-18,1361,5.6,Autonomous Tech +AI14585,Machine Learning Researcher,134257,USD,134257,MI,FL,Denmark,L,Sweden,50,"Python, AWS, Computer Vision, Azure",Associate,2,Telecommunications,2025-03-12,2025-05-06,1297,8.8,Digital Transformation LLC +AI14586,Robotics Engineer,88859,GBP,66644,MI,PT,United Kingdom,L,Latvia,50,"Java, R, MLOps, GCP, Scala",PhD,2,Finance,2024-09-12,2024-10-09,1916,6.4,Machine Intelligence Group +AI14587,Head of AI,124958,USD,124958,SE,FT,South Korea,M,South Korea,50,"Python, Scala, AWS, TensorFlow, Java",Master,8,Telecommunications,2024-09-10,2024-10-13,2029,9.9,Smart Analytics +AI14588,Data Engineer,173410,GBP,130058,SE,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,9,Healthcare,2024-02-11,2024-03-13,2108,8.5,Neural Networks Co +AI14589,AI Specialist,119770,EUR,101805,SE,PT,France,M,France,50,"Python, Mathematics, Azure, TensorFlow",Associate,7,Automotive,2025-04-17,2025-06-29,648,7.8,DeepTech Ventures +AI14590,Data Scientist,57438,EUR,48822,EN,FT,Netherlands,M,Netherlands,50,"Kubernetes, Deep Learning, Computer Vision, GCP",Master,1,Transportation,2024-08-16,2024-10-23,717,8.2,Digital Transformation LLC +AI14591,Machine Learning Engineer,168237,CAD,210296,EX,PT,Canada,S,Canada,100,"AWS, Java, R, Data Visualization",Associate,10,Government,2024-03-14,2024-05-09,2119,9.1,DeepTech Ventures +AI14592,Principal Data Scientist,198127,USD,198127,EX,FT,Sweden,M,Ireland,100,"Linux, Git, MLOps, Tableau, Computer Vision",PhD,19,Retail,2025-04-26,2025-05-10,2065,6.7,Advanced Robotics +AI14593,AI Software Engineer,91754,USD,91754,SE,FT,South Korea,S,South Korea,0,"Computer Vision, Tableau, AWS, Data Visualization, Python",Bachelor,5,Education,2024-10-23,2024-12-28,2354,9.8,Autonomous Tech +AI14594,AI Research Scientist,59433,CAD,74291,EN,FL,Canada,L,Romania,0,"Linux, Data Visualization, Deep Learning",PhD,1,Media,2025-01-12,2025-01-30,1618,9,Quantum Computing Inc +AI14595,AI Consultant,128719,EUR,109411,SE,CT,Germany,M,Germany,100,"Scala, SQL, Linux, Azure",Master,5,Consulting,2025-03-18,2025-05-26,1435,8.1,DataVision Ltd +AI14596,NLP Engineer,225590,CHF,203031,EX,FT,Switzerland,M,Switzerland,50,"Data Visualization, Statistics, SQL, Deep Learning, Mathematics",PhD,10,Healthcare,2024-08-17,2024-10-03,832,9.9,Machine Intelligence Group +AI14597,Data Engineer,327266,USD,327266,EX,FL,Norway,M,Norway,0,"Deep Learning, Python, Java, Computer Vision, SQL",Master,19,Consulting,2024-06-19,2024-08-03,1607,9.6,Quantum Computing Inc +AI14598,Computer Vision Engineer,77377,USD,77377,MI,FL,Ireland,M,Italy,100,"TensorFlow, Scala, Mathematics",Master,3,Manufacturing,2024-09-09,2024-11-13,1176,9.6,Autonomous Tech +AI14599,Research Scientist,172505,USD,172505,SE,FL,Norway,M,Norway,0,"Linux, Azure, Deep Learning, Python",Master,5,Automotive,2025-03-18,2025-04-29,789,5.2,Advanced Robotics +AI14600,Head of AI,97488,GBP,73116,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, Java, Kubernetes, TensorFlow",Master,4,Healthcare,2024-02-23,2024-04-12,506,9.9,Future Systems +AI14601,Head of AI,71688,USD,71688,EN,CT,Ireland,M,Ireland,100,"Data Visualization, Python, SQL, TensorFlow",Master,0,Telecommunications,2024-08-13,2024-09-13,518,9,Autonomous Tech +AI14602,Machine Learning Researcher,177939,USD,177939,EX,PT,Finland,L,United Kingdom,50,"Java, Hadoop, Computer Vision",Master,15,Government,2024-07-13,2024-08-31,2444,8.5,DeepTech Ventures +AI14603,Deep Learning Engineer,176846,CHF,159161,EX,CT,Switzerland,S,Switzerland,100,"Computer Vision, Docker, Data Visualization, Linux, Statistics",PhD,16,Consulting,2024-04-01,2024-06-05,1132,8.3,DataVision Ltd +AI14604,AI Consultant,75786,EUR,64418,MI,FL,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP, Java, Scala",PhD,2,Consulting,2024-12-22,2025-02-12,517,8.1,Algorithmic Solutions +AI14605,AI Consultant,57729,USD,57729,EN,CT,Finland,L,Finland,50,"Scala, Hadoop, Git, Data Visualization",Bachelor,1,Gaming,2024-01-05,2024-02-26,1690,5.2,Cloud AI Solutions +AI14606,Head of AI,103984,USD,103984,SE,FT,South Korea,S,South Africa,50,"Tableau, Azure, SQL, Java, Spark",Associate,8,Government,2024-11-24,2024-12-08,1783,9.7,Cognitive Computing +AI14607,NLP Engineer,109857,GBP,82393,SE,FL,United Kingdom,M,United Kingdom,50,"Kubernetes, Java, NLP",Master,8,Telecommunications,2024-02-25,2024-04-07,814,6,Cloud AI Solutions +AI14608,Data Analyst,211073,USD,211073,EX,CT,Ireland,S,Ireland,0,"GCP, Git, MLOps",PhD,11,Technology,2024-10-18,2024-11-02,674,9,Quantum Computing Inc +AI14609,Data Engineer,134522,USD,134522,SE,CT,Sweden,L,Sweden,0,"AWS, Hadoop, MLOps, Python",Master,5,Education,2025-03-14,2025-04-04,1612,5.7,Predictive Systems +AI14610,AI Architect,161100,CHF,144990,SE,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, AWS, MLOps, Scala",Associate,6,Transportation,2025-01-31,2025-03-14,1781,8,DeepTech Ventures +AI14611,Autonomous Systems Engineer,122301,EUR,103956,SE,FL,Germany,M,Germany,50,"Kubernetes, Python, Computer Vision",Associate,6,Government,2024-09-07,2024-10-23,2201,5.8,Autonomous Tech +AI14612,NLP Engineer,85699,EUR,72844,MI,FT,Germany,S,Mexico,50,"Kubernetes, Java, R, Docker, Statistics",PhD,2,Healthcare,2024-06-12,2024-07-09,1286,9.8,Quantum Computing Inc +AI14613,AI Consultant,70435,CAD,88044,EN,FL,Canada,M,India,0,"Linux, PyTorch, MLOps, R",Associate,1,Consulting,2025-02-02,2025-03-08,889,8.9,DeepTech Ventures +AI14614,Machine Learning Researcher,83577,EUR,71040,MI,FT,Austria,L,Austria,0,"Scala, Tableau, Python",PhD,2,Transportation,2024-05-12,2024-07-13,880,10,Digital Transformation LLC +AI14615,Machine Learning Researcher,224546,USD,224546,EX,CT,Denmark,L,Denmark,100,"PyTorch, AWS, TensorFlow",Associate,18,Real Estate,2024-11-18,2024-12-17,1647,5.1,Advanced Robotics +AI14616,AI Consultant,164191,JPY,18061010,SE,CT,Japan,L,Japan,100,"R, Linux, SQL, PyTorch, AWS",Bachelor,7,Technology,2024-01-02,2024-03-03,1513,7.5,DataVision Ltd +AI14617,AI Architect,234520,SGD,304876,EX,CT,Singapore,S,Singapore,0,"Tableau, Hadoop, Kubernetes, SQL, NLP",Master,14,Manufacturing,2024-03-23,2024-04-26,2487,8.6,Cloud AI Solutions +AI14618,Deep Learning Engineer,50375,USD,50375,SE,CT,China,S,China,100,"Python, Docker, Linux, Mathematics, Kubernetes",Bachelor,8,Technology,2024-08-29,2024-09-29,1638,9.7,Digital Transformation LLC +AI14619,Research Scientist,60031,EUR,51026,EN,CT,France,L,Vietnam,50,"Tableau, Data Visualization, AWS, Azure",Associate,1,Finance,2025-03-17,2025-05-24,1254,9.6,Quantum Computing Inc +AI14620,Computer Vision Engineer,38594,USD,38594,MI,FL,China,M,Hungary,100,"AWS, PyTorch, MLOps, NLP, Kubernetes",PhD,4,Automotive,2025-04-19,2025-06-06,2450,8.4,DeepTech Ventures +AI14621,AI Architect,115790,EUR,98422,SE,PT,Germany,M,Germany,0,"Scala, Python, AWS",Master,5,Gaming,2024-10-12,2024-12-11,2193,7.6,Advanced Robotics +AI14622,AI Product Manager,134490,USD,134490,SE,PT,Denmark,M,Denmark,50,"Python, Mathematics, Deep Learning, Git",PhD,7,Manufacturing,2024-02-22,2024-03-21,1593,7,Future Systems +AI14623,ML Ops Engineer,80936,USD,80936,MI,CT,United States,S,United States,100,"Docker, Python, AWS",PhD,3,Gaming,2024-11-01,2024-12-27,1341,8.3,TechCorp Inc +AI14624,Computer Vision Engineer,142227,USD,142227,SE,CT,Finland,M,Finland,0,"Spark, Tableau, Linux",PhD,5,Retail,2024-04-03,2024-05-13,2195,6.1,Quantum Computing Inc +AI14625,Data Analyst,301196,USD,301196,EX,FT,Norway,M,Australia,100,"Spark, TensorFlow, Azure, Docker, Tableau",Master,11,Education,2025-04-09,2025-05-24,664,7.3,Digital Transformation LLC +AI14626,AI Specialist,42683,USD,42683,SE,FL,India,M,India,0,"Mathematics, Kubernetes, Python",PhD,5,Telecommunications,2025-03-12,2025-05-06,527,9.5,TechCorp Inc +AI14627,Data Scientist,104271,USD,104271,SE,FT,South Korea,L,Chile,50,"R, Tableau, Scala, Deep Learning",PhD,9,Automotive,2024-10-09,2024-10-28,2307,7.7,Machine Intelligence Group +AI14628,Deep Learning Engineer,53911,USD,53911,SE,FT,India,L,India,50,"Java, Scala, Statistics, Azure, Python",PhD,9,Healthcare,2024-02-10,2024-04-15,1406,6.8,Advanced Robotics +AI14629,Data Scientist,119029,GBP,89272,MI,CT,United Kingdom,L,United Kingdom,50,"Java, PyTorch, Tableau, Deep Learning",Bachelor,3,Transportation,2024-10-27,2024-11-21,1815,8,Advanced Robotics +AI14630,Data Engineer,213288,EUR,181295,EX,CT,Germany,S,Germany,50,"SQL, Docker, GCP, AWS, R",Master,10,Government,2024-02-28,2024-04-02,879,8.5,Autonomous Tech +AI14631,AI Product Manager,109524,USD,109524,MI,PT,Denmark,S,Canada,50,"SQL, Docker, Statistics, Python",Master,3,Manufacturing,2024-05-03,2024-07-06,1628,6.9,Algorithmic Solutions +AI14632,AI Product Manager,58198,USD,58198,MI,CT,China,L,China,50,"Scala, Hadoop, Computer Vision, Java, Python",PhD,4,Automotive,2024-04-13,2024-06-11,1765,6.8,Quantum Computing Inc +AI14633,AI Research Scientist,113671,USD,113671,MI,CT,United States,L,Mexico,100,"Python, PyTorch, GCP, R",Master,3,Technology,2024-06-26,2024-09-05,1239,7.3,Digital Transformation LLC +AI14634,Head of AI,49824,USD,49824,SE,CT,India,M,India,0,"TensorFlow, GCP, SQL, Scala",Bachelor,6,Government,2024-12-28,2025-01-28,2279,9.9,Cloud AI Solutions +AI14635,Autonomous Systems Engineer,89500,EUR,76075,EN,PT,Netherlands,L,Netherlands,100,"Docker, Scala, Tableau",PhD,0,Gaming,2024-09-30,2024-11-12,935,5.9,Smart Analytics +AI14636,AI Research Scientist,224343,USD,224343,EX,FT,South Korea,L,South Korea,0,"Mathematics, AWS, Python, Deep Learning, Azure",Master,13,Technology,2024-11-12,2024-12-16,572,7.9,AI Innovations +AI14637,AI Consultant,175920,SGD,228696,EX,FT,Singapore,M,Singapore,50,"PyTorch, Azure, Mathematics, GCP",Master,14,Retail,2024-07-05,2024-07-25,956,8.7,Digital Transformation LLC +AI14638,Data Engineer,158352,AUD,213775,SE,FL,Australia,L,Australia,50,"TensorFlow, Python, Statistics, Git, Computer Vision",PhD,8,Gaming,2025-01-21,2025-03-21,1254,9,Cognitive Computing +AI14639,NLP Engineer,99340,USD,99340,EX,FT,China,S,China,0,"Computer Vision, Mathematics, PyTorch, TensorFlow",Master,19,Healthcare,2024-09-11,2024-10-11,535,7.4,Autonomous Tech +AI14640,Research Scientist,62050,JPY,6825500,EN,CT,Japan,M,Japan,50,"MLOps, PyTorch, Data Visualization, Docker",Bachelor,0,Education,2025-04-19,2025-06-13,2134,5.1,Machine Intelligence Group +AI14641,Head of AI,73299,USD,73299,EN,CT,United States,L,Argentina,100,"Python, Docker, SQL, Statistics",Master,1,Finance,2024-05-02,2024-06-12,2290,6.4,DeepTech Ventures +AI14642,AI Research Scientist,127142,EUR,108071,SE,CT,Austria,L,Austria,50,"Kubernetes, Java, Python, AWS",Bachelor,6,Transportation,2024-08-13,2024-10-23,1104,8.6,Predictive Systems +AI14643,AI Research Scientist,103463,USD,103463,SE,CT,Israel,S,Israel,100,"R, AWS, Computer Vision",Bachelor,6,Media,2024-03-16,2024-04-23,1690,6,Cloud AI Solutions +AI14644,Research Scientist,81210,USD,81210,MI,CT,South Korea,S,South Korea,100,"Kubernetes, Linux, Data Visualization",Associate,3,Telecommunications,2024-07-10,2024-07-27,1925,9,AI Innovations +AI14645,Data Engineer,26249,USD,26249,EN,CT,India,M,India,50,"R, SQL, Computer Vision, Hadoop, PyTorch",PhD,0,Finance,2025-01-09,2025-02-05,2316,9.9,DataVision Ltd +AI14646,Research Scientist,92398,AUD,124737,MI,CT,Australia,L,Australia,0,"Kubernetes, Spark, TensorFlow",Bachelor,4,Gaming,2024-06-09,2024-06-26,1440,5.3,Cognitive Computing +AI14647,Deep Learning Engineer,81062,GBP,60797,EN,FL,United Kingdom,L,United Kingdom,50,"Kubernetes, Azure, MLOps, Git, Statistics",Bachelor,1,Technology,2025-03-10,2025-05-05,2360,7.4,AI Innovations +AI14648,AI Software Engineer,194332,CHF,174899,SE,FT,Switzerland,L,Switzerland,50,"Python, Git, TensorFlow, SQL",Bachelor,9,Government,2024-06-15,2024-07-09,2134,9.5,TechCorp Inc +AI14649,AI Research Scientist,166789,JPY,18346790,SE,FL,Japan,L,United Kingdom,0,"Python, Scala, Statistics, GCP, Computer Vision",Bachelor,5,Telecommunications,2024-06-11,2024-07-08,989,8.4,Neural Networks Co +AI14650,AI Product Manager,271121,USD,271121,EX,FL,United States,L,United States,50,"Azure, Mathematics, NLP, Spark",Bachelor,19,Government,2024-11-10,2025-01-15,2193,9.6,DeepTech Ventures +AI14651,Principal Data Scientist,121488,EUR,103265,SE,FL,Germany,S,Germany,100,"Python, Kubernetes, Git, Deep Learning",PhD,6,Automotive,2024-07-31,2024-10-07,799,8,Smart Analytics +AI14652,Machine Learning Engineer,146495,AUD,197768,EX,CT,Australia,S,Australia,0,"GCP, Deep Learning, SQL, Kubernetes, Linux",Associate,13,Consulting,2024-12-08,2025-01-19,1963,5.9,Quantum Computing Inc +AI14653,AI Consultant,113007,USD,113007,MI,CT,Denmark,S,Estonia,100,"Python, Tableau, SQL",Bachelor,2,Media,2025-01-11,2025-03-12,1510,5.2,DataVision Ltd +AI14654,AI Research Scientist,79500,USD,79500,EN,CT,United States,L,Luxembourg,100,"SQL, Scala, Hadoop, Deep Learning",PhD,0,Government,2024-04-12,2024-05-16,1217,6.4,Autonomous Tech +AI14655,Autonomous Systems Engineer,84593,SGD,109971,MI,PT,Singapore,M,Singapore,0,"Linux, Git, SQL",Associate,2,Transportation,2024-12-03,2025-02-08,2411,7.9,TechCorp Inc +AI14656,Head of AI,87458,EUR,74339,MI,FL,France,L,France,50,"Deep Learning, Linux, NLP, Computer Vision, SQL",Master,3,Automotive,2024-06-16,2024-08-05,2258,8.2,DataVision Ltd +AI14657,AI Specialist,207998,USD,207998,EX,CT,Norway,L,Norway,100,"Kubernetes, MLOps, Python, Data Visualization, Docker",Bachelor,19,Media,2025-04-26,2025-07-01,2207,7.6,Machine Intelligence Group +AI14658,ML Ops Engineer,53800,GBP,40350,EN,FL,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, MLOps, NLP",PhD,1,Telecommunications,2024-10-05,2024-11-01,1568,9.7,Smart Analytics +AI14659,Machine Learning Researcher,56084,EUR,47671,EN,CT,Netherlands,M,Netherlands,50,"Tableau, Linux, Statistics",PhD,0,Media,2024-05-21,2024-07-31,1910,6.7,Digital Transformation LLC +AI14660,Robotics Engineer,92516,USD,92516,EN,FT,Norway,S,Norway,0,"Python, Kubernetes, MLOps, GCP, Spark",Bachelor,0,Retail,2025-02-16,2025-03-04,1766,9.7,Predictive Systems +AI14661,AI Product Manager,119724,USD,119724,EX,FL,China,M,China,0,"Docker, Python, MLOps",Associate,14,Telecommunications,2024-04-04,2024-05-04,1543,6.6,Cognitive Computing +AI14662,Machine Learning Researcher,104136,USD,104136,EX,FL,China,S,China,100,"Java, Computer Vision, NLP, R, MLOps",Bachelor,13,Manufacturing,2024-11-14,2025-01-02,647,8.6,Neural Networks Co +AI14663,Machine Learning Researcher,96383,USD,96383,MI,FT,Sweden,M,Sweden,0,"Spark, Git, Deep Learning, Computer Vision, Python",Associate,2,Media,2024-07-18,2024-09-26,543,8.5,Future Systems +AI14664,Robotics Engineer,75403,USD,75403,EN,FL,United States,L,United States,0,"Python, Data Visualization, TensorFlow, Computer Vision, Deep Learning",Bachelor,0,Transportation,2024-04-25,2024-05-26,2493,7.1,DataVision Ltd +AI14665,Machine Learning Researcher,100534,USD,100534,EN,FL,Denmark,M,Mexico,0,"Tableau, Git, Data Visualization",Master,1,Manufacturing,2024-09-15,2024-11-09,2459,7.8,Machine Intelligence Group +AI14666,Research Scientist,97918,USD,97918,MI,CT,Norway,S,Norway,0,"PyTorch, Python, Statistics, Git, Tableau",Associate,3,Government,2025-03-16,2025-04-15,1112,5.9,Machine Intelligence Group +AI14667,Principal Data Scientist,46643,USD,46643,EN,FL,Finland,S,Finland,50,"Data Visualization, Kubernetes, Python, Spark, NLP",Bachelor,1,Manufacturing,2024-08-22,2024-10-02,1297,9.3,DeepTech Ventures +AI14668,AI Product Manager,161683,EUR,137431,EX,FT,Germany,L,Germany,50,"Hadoop, SQL, Python, TensorFlow, MLOps",PhD,19,Energy,2024-04-30,2024-06-28,819,9.5,Cognitive Computing +AI14669,Data Scientist,78579,USD,78579,MI,CT,Israel,S,Israel,0,"Java, Data Visualization, MLOps, R, AWS",Associate,2,Telecommunications,2024-02-15,2024-04-20,1410,8.9,Predictive Systems +AI14670,AI Architect,98927,EUR,84088,MI,FT,Netherlands,S,Netherlands,0,"Tableau, GCP, Azure, Hadoop, Scala",Associate,3,Government,2024-01-29,2024-03-14,1021,8.2,Future Systems +AI14671,Computer Vision Engineer,74384,JPY,8182240,EN,FL,Japan,M,Japan,50,"Data Visualization, PyTorch, Deep Learning, NLP",Associate,1,Manufacturing,2024-08-08,2024-08-31,1730,8.2,Advanced Robotics +AI14672,AI Product Manager,203594,AUD,274852,EX,FT,Australia,L,Australia,0,"Java, Data Visualization, MLOps, SQL",Master,17,Technology,2024-01-13,2024-03-17,2249,9.3,TechCorp Inc +AI14673,Head of AI,304108,SGD,395340,EX,CT,Singapore,L,Singapore,0,"Python, TensorFlow, Kubernetes, Spark, Statistics",Bachelor,11,Retail,2024-12-25,2025-03-02,2030,7.1,Cloud AI Solutions +AI14674,AI Architect,128907,CAD,161134,SE,CT,Canada,M,Canada,0,"SQL, Azure, Python",Master,8,Energy,2025-02-19,2025-03-08,1987,6.9,DeepTech Ventures +AI14675,Machine Learning Researcher,103434,EUR,87919,MI,PT,Austria,M,Austria,100,"TensorFlow, Mathematics, Linux, SQL",PhD,2,Finance,2024-04-19,2024-05-27,1328,5.4,Digital Transformation LLC +AI14676,AI Specialist,126930,USD,126930,MI,FL,Norway,S,Norway,0,"Linux, Python, Computer Vision",Bachelor,2,Media,2025-02-11,2025-04-05,1625,7.2,Machine Intelligence Group +AI14677,Research Scientist,150089,EUR,127576,EX,FL,Germany,M,Germany,100,"Python, R, Java, Git, Tableau",Bachelor,19,Transportation,2025-02-22,2025-04-15,1964,7.4,Machine Intelligence Group +AI14678,Machine Learning Engineer,84084,CAD,105105,MI,FL,Canada,M,Singapore,0,"Java, PyTorch, Kubernetes, Azure, R",PhD,4,Media,2024-06-30,2024-09-01,1516,9.8,Algorithmic Solutions +AI14679,NLP Engineer,137388,USD,137388,SE,CT,South Korea,L,South Korea,100,"Docker, PyTorch, Kubernetes",Bachelor,8,Technology,2024-07-18,2024-09-02,2379,6.2,Advanced Robotics +AI14680,AI Consultant,70308,USD,70308,MI,PT,Finland,M,Finland,100,"SQL, Scala, Git, PyTorch",PhD,4,Real Estate,2024-07-21,2024-09-02,1317,8,TechCorp Inc +AI14681,AI Product Manager,121990,SGD,158587,MI,PT,Singapore,L,Ireland,50,"SQL, Linux, TensorFlow",Master,2,Technology,2024-03-06,2024-04-16,926,9,DataVision Ltd +AI14682,ML Ops Engineer,69409,USD,69409,EN,CT,Sweden,L,Sweden,0,"AWS, Mathematics, GCP, Azure",Master,1,Consulting,2024-06-09,2024-08-19,594,5.5,Future Systems +AI14683,AI Research Scientist,89827,USD,89827,EN,CT,Denmark,M,Denmark,0,"Tableau, Java, Data Visualization, Python",Master,1,Consulting,2024-10-17,2024-11-20,1703,9.2,Smart Analytics +AI14684,Head of AI,48806,USD,48806,SE,PT,China,S,China,50,"Python, Computer Vision, Hadoop, Scala, Git",Bachelor,6,Retail,2024-10-27,2024-12-17,1758,6.4,AI Innovations +AI14685,Head of AI,94120,CAD,117650,SE,FT,Canada,S,Canada,0,"PyTorch, SQL, NLP",Associate,6,Finance,2024-11-13,2025-01-19,2290,5.4,Quantum Computing Inc +AI14686,Data Analyst,175493,USD,175493,SE,FL,United States,L,United States,100,"Kubernetes, NLP, Scala, MLOps, Spark",PhD,5,Media,2024-05-26,2024-06-28,2336,5.7,Predictive Systems +AI14687,Data Scientist,257356,EUR,218753,EX,CT,Austria,L,Austria,50,"Python, Spark, Mathematics, Git",Master,16,Energy,2024-01-20,2024-02-12,2229,8.3,TechCorp Inc +AI14688,Computer Vision Engineer,200799,CAD,250999,EX,FL,Canada,M,Canada,50,"Linux, Tableau, Docker",Bachelor,15,Healthcare,2024-06-14,2024-07-05,1406,6.5,AI Innovations +AI14689,Data Scientist,210158,EUR,178634,EX,PT,Austria,M,Czech Republic,0,"SQL, PyTorch, Mathematics",Bachelor,15,Transportation,2024-11-22,2025-01-24,1727,8.6,Smart Analytics +AI14690,Autonomous Systems Engineer,46770,USD,46770,EN,FL,Sweden,S,Switzerland,0,"AWS, Kubernetes, Tableau, GCP, Linux",Associate,0,Healthcare,2024-11-28,2025-01-25,1620,5.6,TechCorp Inc +AI14691,Data Engineer,114132,CHF,102719,MI,CT,Switzerland,M,Switzerland,50,"Java, TensorFlow, SQL, Deep Learning",Associate,4,Real Estate,2024-05-24,2024-06-30,2162,7.2,AI Innovations +AI14692,Computer Vision Engineer,71064,USD,71064,EN,FT,Ireland,S,Ireland,0,"Docker, Python, TensorFlow, R",Master,1,Automotive,2024-06-11,2024-08-15,2497,5.7,Cloud AI Solutions +AI14693,Data Scientist,181541,SGD,236003,SE,FT,Singapore,L,Singapore,50,"Tableau, Hadoop, SQL, MLOps, Git",Master,5,Finance,2024-04-19,2024-05-06,1193,8.1,Future Systems +AI14694,Research Scientist,24046,USD,24046,EN,PT,China,S,China,100,"SQL, Python, Java, GCP, Computer Vision",PhD,0,Automotive,2025-02-24,2025-04-05,2443,7.6,Neural Networks Co +AI14695,AI Specialist,107262,USD,107262,SE,CT,South Korea,M,South Korea,50,"Java, Computer Vision, Mathematics",PhD,5,Government,2024-12-02,2024-12-30,2342,9.6,Neural Networks Co +AI14696,Head of AI,120857,USD,120857,SE,FL,South Korea,L,South Korea,50,"Python, TensorFlow, Deep Learning",PhD,9,Finance,2024-06-05,2024-07-05,1291,5.6,Algorithmic Solutions +AI14697,Head of AI,71387,CAD,89234,EN,CT,Canada,M,Canada,0,"Docker, Git, Python",Master,0,Finance,2024-02-11,2024-03-29,2059,5.9,Neural Networks Co +AI14698,Data Engineer,64859,USD,64859,MI,PT,South Korea,S,South Korea,0,"MLOps, Git, Python",PhD,4,Energy,2025-04-24,2025-06-14,2136,5.9,Neural Networks Co +AI14699,AI Consultant,69368,JPY,7630480,EN,FT,Japan,M,Japan,0,"Kubernetes, Computer Vision, Git",PhD,0,Consulting,2024-03-16,2024-04-22,550,8,Advanced Robotics +AI14700,AI Product Manager,57640,EUR,48994,EN,PT,Netherlands,M,Netherlands,50,"Java, Linux, Spark, Azure",Bachelor,0,Real Estate,2024-07-20,2024-08-11,2226,8,Cloud AI Solutions +AI14701,Research Scientist,100171,CAD,125214,SE,FT,Canada,S,Canada,0,"Git, MLOps, Linux, Data Visualization, Azure",Bachelor,5,Transportation,2024-02-08,2024-03-07,1994,5,Advanced Robotics +AI14702,Deep Learning Engineer,66219,SGD,86085,EN,CT,Singapore,S,Singapore,100,"GCP, Data Visualization, Azure, AWS",PhD,0,Retail,2024-12-23,2025-02-25,1170,6.5,Cognitive Computing +AI14703,Deep Learning Engineer,133384,EUR,113376,EX,PT,Austria,S,Austria,0,"Python, TensorFlow, Tableau",Master,11,Real Estate,2024-01-07,2024-03-03,1888,8.8,TechCorp Inc +AI14704,Machine Learning Researcher,133208,EUR,113227,SE,FL,Netherlands,L,Japan,100,"Git, Data Visualization, SQL",Bachelor,8,Media,2024-06-06,2024-08-17,640,7.6,Advanced Robotics +AI14705,AI Consultant,179309,USD,179309,EX,FT,Ireland,S,Ireland,0,"Data Visualization, R, Linux",Associate,15,Telecommunications,2024-01-18,2024-02-18,1899,8,DeepTech Ventures +AI14706,Principal Data Scientist,85394,JPY,9393340,MI,FL,Japan,S,Japan,0,"Azure, Scala, Deep Learning, GCP, AWS",PhD,4,Transportation,2024-09-29,2024-11-01,557,7.1,Digital Transformation LLC +AI14707,NLP Engineer,150883,AUD,203692,SE,FT,Australia,L,Australia,0,"Hadoop, Git, Spark, SQL, Python",PhD,5,Education,2024-12-26,2025-01-16,2237,7.9,Autonomous Tech +AI14708,Research Scientist,140306,JPY,15433660,EX,FL,Japan,S,Turkey,100,"Kubernetes, PyTorch, Data Visualization, Hadoop, Docker",Master,15,Finance,2025-03-04,2025-04-07,2469,8.7,Quantum Computing Inc +AI14709,ML Ops Engineer,132345,USD,132345,MI,CT,Norway,L,Switzerland,100,"MLOps, PyTorch, Data Visualization, Scala",Associate,3,Retail,2025-01-29,2025-03-14,1930,7.7,DataVision Ltd +AI14710,AI Specialist,81632,EUR,69387,EN,CT,Germany,L,Netherlands,0,"Scala, Python, NLP, Tableau, Git",PhD,0,Healthcare,2024-04-09,2024-04-26,1361,7.6,Future Systems +AI14711,Robotics Engineer,145334,SGD,188934,SE,FT,Singapore,M,Singapore,0,"NLP, Java, Python, Statistics, Deep Learning",PhD,9,Energy,2025-03-28,2025-05-21,2432,8.3,AI Innovations +AI14712,AI Product Manager,103134,CHF,92821,EN,CT,Switzerland,M,Switzerland,100,"Spark, R, GCP, TensorFlow, PyTorch",Master,0,Media,2024-09-14,2024-11-23,679,6.6,Digital Transformation LLC +AI14713,Machine Learning Engineer,73844,USD,73844,EN,PT,Denmark,M,Denmark,50,"SQL, Statistics, MLOps, Mathematics",Associate,0,Transportation,2024-04-03,2024-05-20,1162,7,DataVision Ltd +AI14714,NLP Engineer,53224,USD,53224,EN,PT,Israel,S,Israel,50,"Python, Mathematics, Kubernetes",Associate,0,Telecommunications,2024-11-29,2025-01-30,1152,7.7,TechCorp Inc +AI14715,NLP Engineer,96148,USD,96148,EN,FL,Norway,L,Norway,50,"SQL, GCP, Kubernetes, PyTorch",Associate,0,Transportation,2025-02-18,2025-05-02,1244,9.6,Advanced Robotics +AI14716,AI Research Scientist,61479,USD,61479,MI,FL,South Korea,M,South Korea,50,"Docker, Hadoop, TensorFlow, Spark",Master,3,Finance,2024-06-19,2024-07-15,1985,6,Predictive Systems +AI14717,AI Product Manager,89485,CHF,80537,EN,FL,Switzerland,L,Switzerland,50,"Scala, GCP, Statistics, Python",Master,1,Automotive,2025-03-13,2025-05-08,660,5.9,TechCorp Inc +AI14718,AI Specialist,119054,AUD,160723,MI,FT,Australia,L,Australia,100,"Git, Python, R",PhD,2,Manufacturing,2024-10-02,2024-11-15,1819,8.1,Neural Networks Co +AI14719,Data Scientist,39720,USD,39720,SE,FT,India,S,India,0,"R, Kubernetes, Python",Bachelor,9,Automotive,2024-01-14,2024-03-07,580,7.3,DeepTech Ventures +AI14720,Deep Learning Engineer,148540,GBP,111405,SE,FT,United Kingdom,L,United Kingdom,100,"Hadoop, Computer Vision, Git, Azure, Tableau",Master,5,Retail,2025-04-11,2025-05-09,643,6.5,Advanced Robotics +AI14721,AI Architect,67388,USD,67388,EN,PT,Ireland,S,Ireland,0,"MLOps, SQL, Linux, Git",Master,1,Media,2024-04-11,2024-05-19,835,5.6,Advanced Robotics +AI14722,Machine Learning Researcher,71198,USD,71198,MI,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, AWS",PhD,3,Government,2024-09-26,2024-10-28,2030,5.2,TechCorp Inc +AI14723,Computer Vision Engineer,114413,USD,114413,MI,PT,United States,L,United States,0,"MLOps, PyTorch, Kubernetes, TensorFlow, AWS",PhD,4,Real Estate,2024-07-12,2024-09-12,1436,7.9,Digital Transformation LLC +AI14724,AI Research Scientist,75404,USD,75404,EN,PT,United States,M,United States,50,"Python, Hadoop, Java, TensorFlow, Computer Vision",Associate,0,Transportation,2024-10-17,2024-11-16,2155,5.8,Quantum Computing Inc +AI14725,Data Scientist,72723,USD,72723,MI,FL,South Korea,M,South Korea,0,"Computer Vision, Python, SQL, R",Bachelor,3,Technology,2024-01-18,2024-02-13,2430,9.7,Predictive Systems +AI14726,Data Analyst,87914,USD,87914,EX,CT,China,M,China,100,"Spark, Python, Git, Docker",PhD,14,Technology,2024-08-22,2024-09-13,1342,6.6,Smart Analytics +AI14727,Machine Learning Engineer,121462,EUR,103243,SE,CT,Germany,L,Germany,0,"Kubernetes, Java, Computer Vision",Associate,7,Healthcare,2024-03-08,2024-04-08,1728,8.5,Future Systems +AI14728,AI Specialist,28481,USD,28481,EN,FL,China,S,China,50,"Scala, Spark, Git",Associate,0,Energy,2025-01-04,2025-02-12,2191,7.9,Advanced Robotics +AI14729,AI Consultant,168933,SGD,219613,EX,CT,Singapore,L,Singapore,0,"Linux, MLOps, Python, TensorFlow, NLP",Bachelor,11,Automotive,2024-05-22,2024-07-08,2084,9.9,Neural Networks Co +AI14730,AI Consultant,116189,USD,116189,MI,CT,Sweden,L,Sweden,50,"Python, GCP, Tableau, Deep Learning",PhD,3,Education,2024-05-04,2024-06-15,1686,6.9,Neural Networks Co +AI14731,Autonomous Systems Engineer,162901,USD,162901,EX,FL,Norway,S,Nigeria,0,"Scala, Kubernetes, Linux, NLP",PhD,12,Retail,2024-04-21,2024-05-14,1580,7.4,AI Innovations +AI14732,Data Scientist,312986,USD,312986,EX,CT,Norway,M,Norway,0,"Git, Docker, Deep Learning, Hadoop",Associate,17,Technology,2024-05-23,2024-07-21,2326,6.7,Autonomous Tech +AI14733,Data Engineer,118449,EUR,100682,SE,PT,France,L,France,100,"Python, TensorFlow, Azure, Computer Vision",Associate,8,Manufacturing,2024-02-27,2024-05-07,2232,6.7,DataVision Ltd +AI14734,AI Research Scientist,105386,EUR,89578,MI,PT,Germany,M,Germany,0,"Java, Mathematics, Kubernetes",Bachelor,2,Finance,2024-06-08,2024-08-14,1140,8.7,TechCorp Inc +AI14735,AI Specialist,79025,EUR,67171,MI,FL,Netherlands,S,Netherlands,50,"Python, MLOps, Git, TensorFlow",Bachelor,3,Technology,2024-02-05,2024-04-09,686,5.1,Predictive Systems +AI14736,Research Scientist,102196,USD,102196,MI,PT,Sweden,M,Russia,100,"Python, Spark, Hadoop, Statistics",Master,2,Gaming,2024-01-15,2024-03-10,1781,6.5,DeepTech Ventures +AI14737,NLP Engineer,67175,EUR,57099,EN,FL,Austria,S,Austria,50,"Deep Learning, PyTorch, Linux, Java, AWS",Bachelor,1,Retail,2024-08-25,2024-10-23,782,9.3,Machine Intelligence Group +AI14738,ML Ops Engineer,59042,AUD,79707,EN,CT,Australia,S,Australia,0,"Data Visualization, SQL, Statistics, MLOps, Spark",PhD,1,Manufacturing,2024-06-19,2024-08-02,1419,6.6,Machine Intelligence Group +AI14739,AI Consultant,245998,CHF,221398,EX,PT,Switzerland,S,Russia,100,"Python, Mathematics, Scala, GCP",Associate,15,Consulting,2024-04-12,2024-05-24,1628,9.4,Future Systems +AI14740,AI Specialist,48852,SGD,63508,EN,CT,Singapore,S,Singapore,0,"Docker, TensorFlow, Git, GCP, AWS",Master,0,Finance,2025-01-18,2025-02-25,2134,8.4,Digital Transformation LLC +AI14741,AI Software Engineer,133871,EUR,113790,SE,CT,Netherlands,S,Netherlands,100,"Python, TensorFlow, Statistics, PyTorch, Git",Master,9,Technology,2024-03-13,2024-05-22,736,5.1,Quantum Computing Inc +AI14742,Machine Learning Researcher,210751,CHF,189676,EX,FT,Switzerland,S,Switzerland,100,"SQL, GCP, Spark",Associate,16,Government,2024-09-12,2024-09-29,506,5,Cognitive Computing +AI14743,Machine Learning Researcher,178193,CHF,160374,SE,PT,Switzerland,S,South Africa,0,"Python, SQL, Azure, TensorFlow, Git",Associate,5,Consulting,2024-11-29,2025-01-11,2214,5.5,TechCorp Inc +AI14744,Robotics Engineer,119308,USD,119308,SE,FL,Sweden,M,Sweden,100,"Scala, R, Azure",Master,5,Manufacturing,2024-01-20,2024-02-26,857,7.9,Future Systems +AI14745,Robotics Engineer,153010,EUR,130059,EX,FT,Austria,L,Austria,50,"Python, SQL, Java, Docker",Master,17,Consulting,2024-07-12,2024-08-24,2272,9.5,Neural Networks Co +AI14746,Principal Data Scientist,52312,AUD,70621,EN,FL,Australia,S,Australia,50,"SQL, Kubernetes, Docker",Master,1,Transportation,2024-06-28,2024-08-29,1897,9.4,Quantum Computing Inc +AI14747,NLP Engineer,240647,AUD,324873,EX,FL,Australia,M,Sweden,0,"Docker, NLP, Linux, Python",Bachelor,17,Government,2025-03-06,2025-05-05,1227,9,Digital Transformation LLC +AI14748,Autonomous Systems Engineer,68811,EUR,58489,EN,FT,Germany,M,Germany,0,"Spark, Linux, GCP, Scala",Associate,1,Energy,2025-02-18,2025-03-05,791,9.9,Digital Transformation LLC +AI14749,Data Engineer,133800,SGD,173940,MI,FT,Singapore,L,Belgium,100,"SQL, Docker, Java, R",Bachelor,2,Manufacturing,2024-05-08,2024-06-23,944,5.6,DeepTech Ventures +AI14750,AI Research Scientist,110037,AUD,148550,MI,PT,Australia,L,Australia,50,"SQL, Kubernetes, Tableau, Hadoop",Associate,2,Telecommunications,2025-04-13,2025-05-29,1320,6,Autonomous Tech +AI14751,Machine Learning Researcher,43790,USD,43790,SE,PT,India,L,Chile,50,"R, SQL, GCP",Associate,6,Education,2024-05-16,2024-07-25,850,10,Cloud AI Solutions +AI14752,AI Specialist,101457,USD,101457,MI,CT,Ireland,M,Argentina,50,"Python, SQL, Azure",PhD,4,Education,2024-05-12,2024-06-29,2256,7.5,DataVision Ltd +AI14753,AI Specialist,82442,SGD,107175,MI,FL,Singapore,S,Singapore,100,"AWS, TensorFlow, Git",Associate,3,Transportation,2024-02-28,2024-03-16,2365,8.8,Machine Intelligence Group +AI14754,AI Product Manager,76359,USD,76359,EN,CT,Israel,L,Israel,0,"Hadoop, MLOps, Java, Computer Vision, Mathematics",PhD,0,Education,2024-01-31,2024-03-19,1856,9.6,Advanced Robotics +AI14755,AI Specialist,166212,USD,166212,SE,PT,Sweden,L,Sweden,100,"Linux, Spark, Computer Vision, Data Visualization, Python",PhD,7,Manufacturing,2024-04-24,2024-06-27,1511,7.3,Future Systems +AI14756,Head of AI,74070,EUR,62960,MI,FL,Austria,M,Austria,0,"Python, Statistics, Computer Vision",Master,4,Media,2024-01-01,2024-02-25,708,9.8,Cognitive Computing +AI14757,Machine Learning Researcher,23662,USD,23662,EN,FT,India,S,India,0,"SQL, Data Visualization, PyTorch",PhD,0,Real Estate,2024-10-02,2024-10-25,2397,7.1,Machine Intelligence Group +AI14758,Data Scientist,68764,EUR,58449,EN,FL,France,M,Estonia,0,"GCP, TensorFlow, Azure",Bachelor,1,Consulting,2024-09-09,2024-10-14,1164,7,Quantum Computing Inc +AI14759,Research Scientist,55947,USD,55947,EN,CT,Sweden,M,Sweden,100,"Mathematics, Java, PyTorch, Azure",Associate,0,Real Estate,2025-04-21,2025-05-19,806,9,Future Systems +AI14760,AI Product Manager,174977,CHF,157479,SE,PT,Switzerland,L,Switzerland,50,"Tableau, Computer Vision, Spark, Azure, SQL",Master,7,Automotive,2024-08-21,2024-10-11,1609,9.6,Predictive Systems +AI14761,Principal Data Scientist,141796,SGD,184335,SE,PT,Singapore,S,Singapore,50,"Scala, Spark, Python, TensorFlow, Computer Vision",Bachelor,8,Government,2024-04-05,2024-05-09,1338,8.1,AI Innovations +AI14762,Machine Learning Researcher,72370,USD,72370,EX,FL,China,S,China,0,"SQL, Python, Spark, Deep Learning, MLOps",Associate,11,Technology,2024-07-26,2024-08-23,1131,6.9,Autonomous Tech +AI14763,NLP Engineer,90342,EUR,76791,EN,FL,Germany,L,Argentina,50,"Kubernetes, NLP, SQL, PyTorch, R",Associate,0,Manufacturing,2024-08-19,2024-09-03,810,7.3,TechCorp Inc +AI14764,AI Software Engineer,65389,AUD,88275,EN,CT,Australia,S,Poland,0,"Java, Spark, Python, Azure, AWS",PhD,1,Energy,2024-03-02,2024-04-13,848,6.3,TechCorp Inc +AI14765,Robotics Engineer,191753,AUD,258867,EX,FT,Australia,S,Argentina,50,"R, Kubernetes, Scala, Deep Learning, Mathematics",Associate,18,Government,2024-05-06,2024-06-07,1998,5.8,Machine Intelligence Group +AI14766,Computer Vision Engineer,87202,GBP,65402,MI,FT,United Kingdom,S,United Kingdom,50,"Docker, SQL, Java, TensorFlow",Associate,4,Education,2024-04-20,2024-06-22,726,6.4,DeepTech Ventures +AI14767,Research Scientist,78313,USD,78313,MI,FL,Finland,M,Finland,50,"SQL, Data Visualization, Java",Associate,4,Education,2024-09-19,2024-11-04,1662,6.6,Neural Networks Co +AI14768,Principal Data Scientist,65799,USD,65799,EN,FT,United States,M,United States,0,"NLP, R, Kubernetes",PhD,0,Real Estate,2025-01-10,2025-03-14,1239,9.1,Advanced Robotics +AI14769,Research Scientist,29517,USD,29517,EN,CT,China,M,Mexico,50,"GCP, SQL, MLOps, NLP",Associate,0,Technology,2024-08-26,2024-11-05,2343,8.9,Digital Transformation LLC +AI14770,AI Product Manager,81826,USD,81826,EX,CT,India,L,India,0,"PyTorch, SQL, Kubernetes, Statistics",Associate,13,Transportation,2025-02-11,2025-04-07,1718,5.1,DeepTech Ventures +AI14771,Principal Data Scientist,117961,AUD,159247,MI,CT,Australia,L,Australia,100,"Data Visualization, GCP, Hadoop, MLOps",Bachelor,4,Education,2024-12-18,2025-01-01,1811,6.5,DeepTech Ventures +AI14772,AI Specialist,120810,USD,120810,EX,CT,China,L,Japan,100,"Mathematics, Python, Tableau",Bachelor,17,Automotive,2025-01-13,2025-01-27,2403,8.4,Cognitive Computing +AI14773,Data Analyst,43667,USD,43667,MI,FT,China,M,Israel,50,"Spark, Python, Docker, Git",Master,4,Education,2024-05-17,2024-06-22,1403,8.6,Predictive Systems +AI14774,Head of AI,128893,USD,128893,SE,FT,Finland,M,Finland,50,"Java, Linux, Deep Learning, Spark, Mathematics",Master,6,Transportation,2024-06-26,2024-07-13,1199,6.7,Quantum Computing Inc +AI14775,ML Ops Engineer,119069,CAD,148836,SE,FT,Canada,M,Canada,50,"PyTorch, GCP, TensorFlow",Bachelor,8,Energy,2024-07-24,2024-09-30,2205,7.6,Machine Intelligence Group +AI14776,NLP Engineer,66333,AUD,89550,EN,FL,Australia,M,Australia,100,"SQL, Kubernetes, Hadoop",Bachelor,1,Retail,2024-09-30,2024-10-21,2227,6.8,Algorithmic Solutions +AI14777,Machine Learning Researcher,89432,USD,89432,MI,FT,South Korea,L,South Korea,0,"GCP, Data Visualization, Kubernetes, Docker",Associate,2,Education,2025-02-28,2025-04-17,1204,8.6,Predictive Systems +AI14778,AI Consultant,56324,EUR,47875,EN,FL,Netherlands,S,Latvia,100,"Git, Mathematics, R",Associate,1,Retail,2024-01-18,2024-03-15,853,9.1,Machine Intelligence Group +AI14779,Research Scientist,145285,USD,145285,MI,FT,United States,L,United States,100,"R, Mathematics, Kubernetes, NLP",Associate,3,Gaming,2024-04-04,2024-05-07,1091,6.9,Future Systems +AI14780,AI Product Manager,227003,USD,227003,EX,FL,Israel,L,China,50,"SQL, AWS, GCP, Kubernetes",Associate,19,Education,2024-01-21,2024-03-23,858,5,Cloud AI Solutions +AI14781,Deep Learning Engineer,123976,EUR,105380,EX,CT,Germany,S,Germany,0,"Linux, Hadoop, Spark, Python",Bachelor,12,Education,2024-09-08,2024-11-08,742,7.2,Quantum Computing Inc +AI14782,Principal Data Scientist,63982,USD,63982,EN,PT,Sweden,S,Sweden,100,"Scala, TensorFlow, MLOps, Git, Computer Vision",Associate,1,Telecommunications,2024-07-08,2024-08-23,1255,8.9,TechCorp Inc +AI14783,Data Scientist,26617,USD,26617,EN,CT,India,M,India,0,"GCP, Kubernetes, Mathematics, NLP",Associate,0,Gaming,2025-04-21,2025-05-16,1994,8.2,Autonomous Tech +AI14784,Data Scientist,213307,CHF,191976,EX,FT,Switzerland,S,Switzerland,50,"Computer Vision, Python, TensorFlow, Linux",Bachelor,19,Education,2024-12-12,2025-02-21,2249,6.8,Cognitive Computing +AI14785,Machine Learning Engineer,68856,USD,68856,MI,CT,Finland,M,Finland,0,"GCP, Python, Spark",Associate,4,Government,2024-10-16,2024-10-31,1095,9.7,Autonomous Tech +AI14786,Head of AI,75179,USD,75179,EN,FT,United States,S,United States,0,"Kubernetes, Python, Linux, AWS, Deep Learning",PhD,0,Healthcare,2024-12-03,2025-01-22,1923,8.3,Autonomous Tech +AI14787,ML Ops Engineer,164858,AUD,222558,SE,FT,Australia,L,Australia,0,"AWS, Azure, PyTorch, Data Visualization",Bachelor,6,Gaming,2024-08-26,2024-10-31,1342,8.6,Autonomous Tech +AI14788,AI Software Engineer,70806,USD,70806,SE,FL,China,M,Germany,50,"Tableau, Spark, Scala",PhD,6,Manufacturing,2024-06-24,2024-08-16,1063,8.6,Digital Transformation LLC +AI14789,ML Ops Engineer,118788,USD,118788,SE,FT,Finland,L,Mexico,50,"Hadoop, Python, SQL",Master,7,Education,2025-04-29,2025-05-26,1420,9.1,Neural Networks Co +AI14790,AI Software Engineer,60352,AUD,81475,EN,FT,Australia,M,New Zealand,50,"Kubernetes, Java, MLOps, Azure",PhD,1,Energy,2024-01-29,2024-02-22,808,9.6,Digital Transformation LLC +AI14791,AI Software Engineer,87016,CAD,108770,MI,PT,Canada,L,South Korea,50,"Tableau, Docker, Java, GCP",Master,4,Healthcare,2024-02-16,2024-04-13,1869,6,Quantum Computing Inc +AI14792,Principal Data Scientist,192474,AUD,259840,EX,FL,Australia,M,Turkey,50,"Linux, R, Tableau",PhD,11,Finance,2024-01-21,2024-04-01,1558,7.5,Cloud AI Solutions +AI14793,Head of AI,83774,JPY,9215140,MI,FT,Japan,S,Japan,0,"NLP, TensorFlow, Scala, Docker",Associate,3,Energy,2024-10-06,2024-11-18,1800,6.6,Machine Intelligence Group +AI14794,Data Scientist,177589,CHF,159830,SE,CT,Switzerland,S,Switzerland,50,"Kubernetes, Python, TensorFlow, PyTorch, R",Associate,7,Education,2024-01-28,2024-04-03,1582,5.6,DeepTech Ventures +AI14795,Computer Vision Engineer,63063,USD,63063,EN,FT,Sweden,L,Argentina,50,"R, Hadoop, Linux, Statistics, Spark",PhD,1,Healthcare,2025-04-02,2025-04-24,557,7.9,Cognitive Computing +AI14796,AI Specialist,32842,USD,32842,MI,FT,India,L,Romania,100,"Python, Git, Data Visualization, Java, Statistics",Master,3,Telecommunications,2024-07-20,2024-08-26,2406,5.8,Cognitive Computing +AI14797,Robotics Engineer,307133,USD,307133,EX,FT,Norway,M,Norway,0,"PyTorch, Hadoop, Scala",Master,18,Manufacturing,2025-03-06,2025-05-11,1874,5.8,Neural Networks Co +AI14798,Deep Learning Engineer,260543,JPY,28659730,EX,CT,Japan,M,Latvia,100,"R, Mathematics, Deep Learning",PhD,17,Manufacturing,2025-01-16,2025-03-29,1213,5.5,Quantum Computing Inc +AI14799,AI Specialist,44958,USD,44958,SE,PT,China,S,China,0,"GCP, Azure, NLP",Associate,9,Gaming,2024-11-22,2025-01-17,684,6.2,Smart Analytics +AI14800,Head of AI,131487,AUD,177507,SE,CT,Australia,S,Australia,50,"Python, R, TensorFlow, Deep Learning",PhD,8,Real Estate,2025-04-24,2025-06-18,1130,7.6,Advanced Robotics +AI14801,AI Architect,59373,EUR,50467,EN,PT,Netherlands,M,Netherlands,100,"Python, Mathematics, TensorFlow, Kubernetes",Master,0,Consulting,2024-11-30,2025-01-05,1456,8.2,Smart Analytics +AI14802,Machine Learning Engineer,142471,USD,142471,SE,FT,Finland,M,Finland,50,"TensorFlow, Hadoop, Data Visualization, NLP",Associate,9,Technology,2024-11-18,2024-12-24,1489,6.2,Digital Transformation LLC +AI14803,AI Specialist,33282,USD,33282,MI,PT,India,L,India,50,"SQL, Azure, Kubernetes, Deep Learning",PhD,3,Energy,2024-12-21,2025-01-30,2210,6.1,Autonomous Tech +AI14804,AI Architect,70038,EUR,59532,MI,FL,Austria,M,Austria,50,"Git, PyTorch, Deep Learning",Associate,3,Finance,2024-03-12,2024-03-28,1625,8.5,Machine Intelligence Group +AI14805,Machine Learning Engineer,74946,USD,74946,EN,CT,Denmark,M,Austria,100,"SQL, Java, Azure",Bachelor,0,Government,2024-12-16,2025-02-02,2150,9.3,Algorithmic Solutions +AI14806,Data Scientist,45967,USD,45967,MI,FL,China,S,Ghana,50,"SQL, Computer Vision, AWS",PhD,3,Gaming,2024-11-19,2024-12-21,1627,7.2,Future Systems +AI14807,Principal Data Scientist,292646,SGD,380440,EX,PT,Singapore,L,Singapore,50,"GCP, Git, Azure",PhD,14,Energy,2024-04-23,2024-05-11,846,7.6,Neural Networks Co +AI14808,Data Scientist,133770,USD,133770,MI,PT,United States,L,United States,100,"Java, Mathematics, SQL, PyTorch, Docker",Bachelor,2,Retail,2024-05-19,2024-07-15,2117,7.4,Predictive Systems +AI14809,Principal Data Scientist,103086,USD,103086,MI,CT,Sweden,M,Sweden,0,"Mathematics, SQL, Tableau",Associate,3,Consulting,2024-03-10,2024-04-13,2029,5.9,Cognitive Computing +AI14810,Data Scientist,151977,USD,151977,EX,FT,Israel,S,Israel,100,"Java, PyTorch, Mathematics, Docker, Spark",Bachelor,18,Energy,2024-10-02,2024-10-24,792,7.3,Autonomous Tech +AI14811,AI Software Engineer,42791,USD,42791,MI,FL,India,L,Singapore,100,"Statistics, SQL, PyTorch, AWS",Master,2,Automotive,2024-06-29,2024-08-01,1814,6.1,Cognitive Computing +AI14812,Robotics Engineer,145130,USD,145130,EX,CT,Finland,M,Finland,50,"Java, Linux, Git, AWS",Associate,16,Transportation,2024-03-15,2024-04-30,1409,8.8,DataVision Ltd +AI14813,AI Specialist,50395,USD,50395,EN,CT,Finland,M,Thailand,0,"Git, NLP, Java, Python",PhD,1,Media,2024-12-28,2025-01-12,2037,9.8,TechCorp Inc +AI14814,Deep Learning Engineer,164649,EUR,139952,EX,FL,France,M,France,100,"Git, Python, Spark, Deep Learning",Associate,18,Energy,2025-03-20,2025-04-23,2316,9.6,Quantum Computing Inc +AI14815,Deep Learning Engineer,269435,EUR,229020,EX,PT,Netherlands,L,Netherlands,100,"Git, TensorFlow, Data Visualization",Associate,13,Real Estate,2024-10-23,2024-12-26,2295,9.9,Advanced Robotics +AI14816,Data Engineer,224881,USD,224881,SE,CT,Denmark,L,Denmark,0,"PyTorch, R, Docker, Statistics, Computer Vision",Bachelor,5,Technology,2024-05-16,2024-07-16,1110,9.6,AI Innovations +AI14817,Research Scientist,75931,JPY,8352410,EN,CT,Japan,S,Japan,50,"Azure, PyTorch, Mathematics, SQL, Python",Bachelor,1,Healthcare,2025-04-29,2025-07-02,1616,6.2,Algorithmic Solutions +AI14818,Machine Learning Researcher,138815,EUR,117993,SE,FT,Germany,M,Germany,100,"Statistics, Git, Data Visualization",Master,8,Energy,2025-04-13,2025-05-30,589,7.8,DataVision Ltd +AI14819,Head of AI,302646,CHF,272381,EX,PT,Switzerland,L,Switzerland,100,"Git, R, Hadoop",Associate,13,Finance,2024-03-08,2024-04-17,1931,7.7,Neural Networks Co +AI14820,Data Analyst,84254,AUD,113743,MI,PT,Australia,S,Australia,0,"Git, PyTorch, SQL",Bachelor,2,Education,2024-03-20,2024-05-22,1957,7,Cloud AI Solutions +AI14821,Robotics Engineer,91671,GBP,68753,MI,CT,United Kingdom,L,United Kingdom,100,"Spark, Tableau, Git, GCP",Associate,3,Retail,2024-08-29,2024-10-06,2086,5.6,AI Innovations +AI14822,NLP Engineer,140621,JPY,15468310,SE,PT,Japan,L,Japan,100,"Data Visualization, Python, Java, Statistics",Bachelor,8,Energy,2024-12-04,2025-01-11,1005,5.2,Neural Networks Co +AI14823,Robotics Engineer,93091,USD,93091,MI,PT,Israel,S,Israel,50,"Scala, AWS, Azure, Python",PhD,4,Telecommunications,2024-11-29,2024-12-20,2271,8,Cognitive Computing +AI14824,AI Architect,69964,USD,69964,MI,PT,Israel,S,Malaysia,100,"MLOps, PyTorch, Kubernetes, NLP, Mathematics",Bachelor,2,Consulting,2024-11-15,2025-01-24,2121,6.5,AI Innovations +AI14825,Deep Learning Engineer,235481,GBP,176611,EX,FL,United Kingdom,S,France,100,"Tableau, Linux, MLOps, Python",Master,14,Telecommunications,2024-02-01,2024-04-10,1339,7.5,Algorithmic Solutions +AI14826,Principal Data Scientist,104957,GBP,78718,MI,PT,United Kingdom,M,United Kingdom,0,"Computer Vision, PyTorch, SQL",PhD,3,Manufacturing,2024-06-09,2024-06-23,1178,7.2,Algorithmic Solutions +AI14827,AI Product Manager,70827,EUR,60203,EN,CT,Netherlands,L,Netherlands,0,"Scala, Hadoop, Python",Master,1,Gaming,2024-10-20,2024-12-06,1126,7.9,TechCorp Inc +AI14828,Data Engineer,125048,CAD,156310,SE,FL,Canada,M,Canada,0,"Python, Java, Docker",Master,8,Media,2025-04-26,2025-06-12,2044,7.3,DeepTech Ventures +AI14829,Research Scientist,212816,CAD,266020,EX,CT,Canada,M,Canada,50,"PyTorch, Python, Data Visualization, Kubernetes",Associate,15,Real Estate,2024-08-12,2024-09-29,658,6.7,Predictive Systems +AI14830,Head of AI,58316,USD,58316,EN,FT,Sweden,S,Germany,50,"Spark, Scala, GCP, Java, SQL",PhD,0,Gaming,2024-05-17,2024-07-18,2200,6.5,Future Systems +AI14831,NLP Engineer,100481,EUR,85409,MI,PT,Netherlands,L,Netherlands,100,"TensorFlow, Kubernetes, Spark",Associate,4,Manufacturing,2024-03-04,2024-04-20,2061,6.4,Cognitive Computing +AI14832,Head of AI,49599,USD,49599,MI,PT,China,L,China,100,"SQL, Kubernetes, GCP, Statistics, Hadoop",Master,2,Real Estate,2024-10-31,2024-12-15,708,5.8,DeepTech Ventures +AI14833,Data Analyst,79810,USD,79810,EN,PT,United States,S,Italy,50,"Python, Linux, NLP, TensorFlow, Hadoop",PhD,1,Healthcare,2025-03-24,2025-05-08,2386,6.8,DataVision Ltd +AI14834,AI Architect,57873,USD,57873,SE,FT,China,L,Luxembourg,50,"Kubernetes, Data Visualization, Java, PyTorch, NLP",Associate,9,Government,2024-07-13,2024-08-26,2487,5.4,Digital Transformation LLC +AI14835,Autonomous Systems Engineer,135214,SGD,175778,SE,CT,Singapore,S,Singapore,50,"R, SQL, Computer Vision, Java, Deep Learning",PhD,9,Education,2024-01-28,2024-03-01,2415,8.2,DataVision Ltd +AI14836,Principal Data Scientist,44068,USD,44068,EN,FL,South Korea,S,South Korea,50,"Git, Azure, Computer Vision",Associate,0,Energy,2024-05-30,2024-07-18,1291,6.8,Cloud AI Solutions +AI14837,ML Ops Engineer,218509,USD,218509,EX,CT,United States,S,Malaysia,100,"GCP, TensorFlow, Hadoop, Mathematics, SQL",PhD,19,Finance,2024-08-15,2024-09-04,2459,5.5,Autonomous Tech +AI14838,NLP Engineer,210813,CHF,189732,EX,CT,Switzerland,S,Switzerland,100,"NLP, Git, Data Visualization",Associate,10,Telecommunications,2024-03-25,2024-04-18,857,7.3,Digital Transformation LLC +AI14839,AI Architect,55157,SGD,71704,EN,FL,Singapore,S,Singapore,0,"Python, TensorFlow, Azure, Computer Vision",PhD,0,Finance,2024-06-01,2024-07-01,1582,9.5,Smart Analytics +AI14840,Deep Learning Engineer,70464,EUR,59894,EN,CT,France,M,France,0,"Mathematics, SQL, Tableau, PyTorch",Bachelor,1,Telecommunications,2025-04-27,2025-05-21,643,5.5,Smart Analytics +AI14841,Head of AI,55034,GBP,41276,EN,FL,United Kingdom,M,Sweden,100,"PyTorch, Docker, Data Visualization, Java, Spark",Bachelor,1,Government,2024-09-09,2024-10-05,1608,7,Digital Transformation LLC +AI14842,Machine Learning Engineer,278029,CHF,250226,EX,CT,Switzerland,M,Switzerland,100,"GCP, NLP, SQL, Python, Hadoop",Bachelor,10,Technology,2024-07-17,2024-08-17,1027,9,Smart Analytics +AI14843,ML Ops Engineer,100795,EUR,85676,SE,FT,Austria,S,France,100,"Python, SQL, NLP, Linux",Associate,7,Automotive,2025-04-26,2025-06-28,1660,5.5,AI Innovations +AI14844,Machine Learning Researcher,75234,USD,75234,MI,FL,South Korea,S,Malaysia,50,"Computer Vision, Python, Hadoop, AWS",PhD,3,Telecommunications,2024-05-28,2024-07-27,1864,5.6,DeepTech Ventures +AI14845,Machine Learning Researcher,149192,USD,149192,EX,FL,Sweden,S,Sweden,100,"Linux, Python, Data Visualization, TensorFlow",Master,16,Real Estate,2024-07-27,2024-09-08,646,5.8,Autonomous Tech +AI14846,AI Consultant,182753,USD,182753,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, AWS",Master,11,Real Estate,2025-02-27,2025-04-10,2315,10,DeepTech Ventures +AI14847,Principal Data Scientist,134537,EUR,114356,SE,PT,Austria,M,Austria,0,"Python, Tableau, Java, GCP, TensorFlow",Associate,7,Government,2025-04-03,2025-05-05,965,8.4,Predictive Systems +AI14848,ML Ops Engineer,97397,EUR,82787,MI,FT,Netherlands,L,Netherlands,0,"SQL, Kubernetes, Git",Associate,4,Transportation,2025-01-22,2025-03-29,549,10,AI Innovations +AI14849,AI Product Manager,37126,USD,37126,MI,PT,India,M,India,50,"R, Python, Statistics, Docker",PhD,2,Education,2024-05-30,2024-08-08,1709,8.7,Neural Networks Co +AI14850,AI Research Scientist,67086,USD,67086,MI,FT,South Korea,S,Egypt,50,"Computer Vision, Scala, NLP",Bachelor,3,Education,2024-02-27,2024-04-30,821,5.6,Future Systems +AI14851,AI Specialist,62522,USD,62522,EX,FT,India,S,Germany,100,"Spark, AWS, Scala",Associate,14,Consulting,2025-03-11,2025-04-27,1422,9.7,Future Systems +AI14852,AI Product Manager,107430,AUD,145031,SE,FT,Australia,S,Australia,0,"Git, NLP, Docker, Scala",Master,7,Healthcare,2024-09-02,2024-10-12,1641,9.6,Advanced Robotics +AI14853,AI Architect,115217,CAD,144021,SE,FT,Canada,S,Canada,0,"Kubernetes, SQL, Docker",Bachelor,7,Manufacturing,2024-10-18,2024-11-20,753,9.3,Digital Transformation LLC +AI14854,Head of AI,142120,USD,142120,SE,FT,Denmark,S,Denmark,0,"Scala, Python, AWS, TensorFlow",Associate,6,Healthcare,2024-09-29,2024-10-31,2135,5.2,Cognitive Computing +AI14855,AI Consultant,92445,CAD,115556,MI,FT,Canada,M,Canada,0,"R, TensorFlow, Scala, Git, Computer Vision",Master,4,Real Estate,2024-11-29,2025-01-06,2134,8.9,Digital Transformation LLC +AI14856,Data Scientist,41824,USD,41824,SE,CT,India,L,New Zealand,50,"MLOps, GCP, R, Azure",Associate,6,Retail,2024-05-17,2024-07-21,994,8.6,Autonomous Tech +AI14857,ML Ops Engineer,51207,CAD,64009,EN,FL,Canada,M,Canada,50,"SQL, PyTorch, Git, AWS",PhD,0,Healthcare,2025-01-10,2025-02-06,745,6.5,Cognitive Computing +AI14858,AI Software Engineer,96900,CHF,87210,MI,PT,Switzerland,S,Switzerland,100,"TensorFlow, Mathematics, Hadoop, Data Visualization",PhD,3,Consulting,2024-07-17,2024-08-28,2381,9.4,Smart Analytics +AI14859,Machine Learning Engineer,139440,EUR,118524,SE,FT,Austria,L,Portugal,50,"SQL, Deep Learning, Tableau, GCP",PhD,7,Education,2024-10-01,2024-11-07,898,8,AI Innovations +AI14860,Data Engineer,149725,USD,149725,SE,FT,Finland,L,Finland,100,"MLOps, Computer Vision, SQL, Mathematics, Data Visualization",Bachelor,5,Healthcare,2024-11-12,2025-01-01,1796,8.6,Quantum Computing Inc +AI14861,AI Software Engineer,95613,CHF,86052,EN,FL,Switzerland,S,Switzerland,100,"SQL, PyTorch, Data Visualization, Deep Learning",PhD,0,Manufacturing,2024-01-14,2024-02-05,2410,8.1,Machine Intelligence Group +AI14862,Deep Learning Engineer,84360,EUR,71706,MI,PT,Austria,M,Austria,50,"TensorFlow, Scala, Statistics",Bachelor,2,Media,2025-04-23,2025-05-31,1028,5,TechCorp Inc +AI14863,Principal Data Scientist,109354,EUR,92951,MI,CT,Austria,L,Austria,100,"Statistics, PyTorch, NLP, AWS, Linux",Master,3,Finance,2025-01-13,2025-02-17,1507,6.5,Predictive Systems +AI14864,AI Product Manager,49153,USD,49153,EN,FL,South Korea,M,South Korea,0,"TensorFlow, Deep Learning, Docker",Bachelor,0,Automotive,2024-02-26,2024-03-16,1274,6.4,Predictive Systems +AI14865,AI Specialist,79494,USD,79494,MI,FT,South Korea,M,Vietnam,100,"Kubernetes, SQL, Data Visualization, Mathematics",Bachelor,4,Government,2024-05-30,2024-08-05,1674,5.1,Future Systems +AI14866,AI Architect,99985,JPY,10998350,MI,PT,Japan,L,Japan,100,"Git, SQL, Hadoop",PhD,3,Real Estate,2024-09-14,2024-11-16,2196,8.1,Autonomous Tech +AI14867,Data Scientist,82532,JPY,9078520,EN,PT,Japan,L,Japan,50,"Hadoop, Python, Docker, Mathematics",Bachelor,0,Healthcare,2024-07-11,2024-08-09,1231,9.1,Autonomous Tech +AI14868,Autonomous Systems Engineer,295948,USD,295948,EX,FT,Norway,M,Romania,50,"SQL, Scala, Python",PhD,12,Healthcare,2024-05-01,2024-06-05,630,9.7,Quantum Computing Inc +AI14869,AI Architect,62843,USD,62843,MI,CT,Finland,S,Finland,50,"R, SQL, TensorFlow, AWS, Python",PhD,3,Manufacturing,2024-07-16,2024-07-30,2195,9.7,Predictive Systems +AI14870,Data Scientist,209564,CHF,188608,EX,FT,Switzerland,M,Switzerland,100,"TensorFlow, Git, Scala",Associate,17,Manufacturing,2024-08-23,2024-09-11,1446,5.4,Algorithmic Solutions +AI14871,NLP Engineer,152425,USD,152425,MI,FT,Denmark,L,Denmark,50,"Spark, R, SQL, Python",Bachelor,4,Manufacturing,2024-09-18,2024-11-29,911,5.9,Machine Intelligence Group +AI14872,Robotics Engineer,84147,USD,84147,MI,CT,South Korea,L,South Korea,50,"SQL, Python, Java, Git",PhD,4,Education,2024-10-08,2024-11-09,2252,8.4,Autonomous Tech +AI14873,Data Scientist,119112,USD,119112,MI,CT,Ireland,L,Ireland,100,"Scala, TensorFlow, Mathematics, Java",Associate,2,Consulting,2024-01-24,2024-03-24,945,8.6,Machine Intelligence Group +AI14874,Data Engineer,49882,USD,49882,SE,PT,China,S,China,50,"Java, PyTorch, Kubernetes",Master,8,Manufacturing,2024-06-02,2024-07-18,966,5.4,DeepTech Ventures +AI14875,Data Scientist,223969,USD,223969,EX,CT,Denmark,S,Russia,100,"SQL, Kubernetes, TensorFlow",Master,18,Real Estate,2024-08-30,2024-10-28,1774,6.1,Advanced Robotics +AI14876,Head of AI,118219,USD,118219,MI,PT,Norway,L,Norway,50,"Mathematics, Tableau, Python, Deep Learning, Kubernetes",PhD,2,Telecommunications,2024-07-14,2024-08-15,819,8.8,DataVision Ltd +AI14877,Research Scientist,53669,EUR,45619,EN,CT,Netherlands,S,Netherlands,100,"Scala, Mathematics, MLOps, Java",Master,1,Education,2025-01-28,2025-03-30,820,9.6,Machine Intelligence Group +AI14878,Research Scientist,103628,USD,103628,MI,FT,Ireland,L,Japan,50,"PyTorch, Mathematics, Spark, TensorFlow",Associate,4,Media,2024-12-27,2025-02-16,1923,5.3,Predictive Systems +AI14879,AI Specialist,56178,CAD,70223,EN,FT,Canada,S,Canada,0,"Linux, MLOps, Hadoop, PyTorch",Bachelor,0,Telecommunications,2024-05-02,2024-06-04,2267,9.5,Machine Intelligence Group +AI14880,AI Software Engineer,146442,USD,146442,SE,PT,United States,L,United States,50,"Spark, TensorFlow, Mathematics, MLOps, Data Visualization",Bachelor,9,Healthcare,2024-05-01,2024-06-12,2052,6.5,Cognitive Computing +AI14881,Computer Vision Engineer,63769,GBP,47827,EN,CT,United Kingdom,L,Norway,50,"PyTorch, Python, Data Visualization, SQL, Docker",Associate,1,Gaming,2024-01-30,2024-03-23,1175,8.2,Smart Analytics +AI14882,AI Software Engineer,24026,USD,24026,EN,FT,India,L,India,50,"Java, SQL, Hadoop, GCP",Master,0,Energy,2024-11-20,2025-01-31,1643,7.3,Cloud AI Solutions +AI14883,Deep Learning Engineer,128886,EUR,109553,SE,FL,France,S,France,0,"Kubernetes, Scala, Linux",Master,7,Healthcare,2025-02-11,2025-03-04,559,9.1,Future Systems +AI14884,Data Engineer,86675,EUR,73674,EN,CT,Netherlands,L,Ukraine,50,"Python, TensorFlow, MLOps, PyTorch, Spark",Master,0,Media,2025-03-19,2025-05-12,954,7.9,Smart Analytics +AI14885,Principal Data Scientist,112837,USD,112837,SE,FT,Finland,L,Ukraine,100,"Python, Java, Scala, AWS",Master,7,Government,2025-02-26,2025-03-25,1527,7.3,AI Innovations +AI14886,AI Specialist,79915,CAD,99894,MI,CT,Canada,L,Ireland,100,"PyTorch, Spark, Scala, SQL, TensorFlow",PhD,3,Government,2024-06-15,2024-07-24,1978,9.8,Algorithmic Solutions +AI14887,Principal Data Scientist,55583,EUR,47246,EN,CT,Germany,S,Germany,0,"SQL, Java, Statistics",Master,0,Government,2025-02-14,2025-03-04,1427,8.5,Quantum Computing Inc +AI14888,AI Consultant,102567,EUR,87182,MI,FL,France,L,France,0,"Scala, Mathematics, R, Hadoop, Computer Vision",PhD,2,Consulting,2024-01-15,2024-03-07,1168,7.6,Autonomous Tech +AI14889,Data Scientist,63765,EUR,54200,EN,FL,Austria,S,Austria,50,"Scala, Linux, NLP, Tableau",Associate,1,Healthcare,2024-11-23,2024-12-22,926,9.6,Quantum Computing Inc +AI14890,Research Scientist,109816,JPY,12079760,SE,PT,Japan,M,Japan,100,"Tableau, Python, Kubernetes, NLP",Bachelor,7,Gaming,2024-04-24,2024-06-23,2297,9.3,Predictive Systems +AI14891,Machine Learning Engineer,147705,EUR,125549,SE,FT,Austria,L,Turkey,100,"Spark, Kubernetes, Data Visualization",Associate,7,Telecommunications,2024-01-08,2024-02-19,1790,5.3,Machine Intelligence Group +AI14892,NLP Engineer,180262,USD,180262,EX,CT,South Korea,L,South Korea,100,"SQL, PyTorch, AWS, Deep Learning, TensorFlow",Master,14,Healthcare,2024-04-04,2024-05-06,984,8.7,Digital Transformation LLC +AI14893,Research Scientist,26108,USD,26108,MI,CT,India,M,Nigeria,50,"MLOps, Python, PyTorch, Java, SQL",Master,3,Retail,2024-01-12,2024-03-18,2323,7.5,TechCorp Inc +AI14894,Data Scientist,85429,AUD,115329,MI,FL,Australia,S,Portugal,50,"Computer Vision, TensorFlow, Python",Associate,2,Finance,2024-02-07,2024-03-04,1715,8.6,Digital Transformation LLC +AI14895,Data Scientist,85824,GBP,64368,EN,PT,United Kingdom,L,Sweden,0,"SQL, Spark, PyTorch, Mathematics",Associate,1,Healthcare,2024-01-15,2024-03-12,1941,7.1,Advanced Robotics +AI14896,Deep Learning Engineer,36761,USD,36761,MI,PT,China,S,China,0,"Python, Scala, Git",PhD,4,Government,2025-03-03,2025-03-22,1141,6.6,DeepTech Ventures +AI14897,Machine Learning Researcher,178346,USD,178346,SE,FL,United States,M,United States,50,"Java, NLP, MLOps",PhD,8,Technology,2025-01-22,2025-02-28,1669,10,Quantum Computing Inc +AI14898,Principal Data Scientist,210345,USD,210345,EX,FT,Denmark,L,Norway,0,"Mathematics, Hadoop, Kubernetes, Linux, Azure",PhD,19,Finance,2024-02-22,2024-05-01,1614,7,DeepTech Ventures +AI14899,AI Product Manager,219044,CAD,273805,EX,CT,Canada,L,Belgium,50,"Hadoop, R, Scala, Data Visualization",Master,18,Education,2024-01-26,2024-03-29,1456,7.7,Quantum Computing Inc +AI14900,Principal Data Scientist,64885,CAD,81106,EN,CT,Canada,L,South Africa,0,"AWS, Hadoop, R, Kubernetes",Associate,1,Retail,2024-06-10,2024-07-13,1036,8.2,Neural Networks Co +AI14901,Machine Learning Researcher,98266,JPY,10809260,EN,FT,Japan,L,Russia,0,"Linux, Statistics, Mathematics, Hadoop, PyTorch",PhD,0,Real Estate,2025-01-27,2025-04-05,1598,5.5,Advanced Robotics +AI14902,Head of AI,104995,USD,104995,SE,PT,Ireland,S,Ireland,50,"Scala, MLOps, Azure, Git, Computer Vision",PhD,6,Government,2025-04-04,2025-05-30,1420,9.8,Machine Intelligence Group +AI14903,Head of AI,150009,USD,150009,SE,PT,United States,S,United States,0,"Java, Deep Learning, TensorFlow",Associate,8,Gaming,2024-05-20,2024-07-31,1122,5.1,Autonomous Tech +AI14904,AI Architect,213345,USD,213345,SE,FL,Denmark,L,Ghana,50,"Python, Tableau, Azure, Spark, Kubernetes",Master,8,Telecommunications,2024-08-09,2024-09-30,1207,8.6,Neural Networks Co +AI14905,Machine Learning Engineer,105646,EUR,89799,MI,PT,Germany,M,Kenya,50,"Scala, Hadoop, AWS, Python, Statistics",Master,2,Consulting,2025-03-17,2025-04-19,884,8.6,Neural Networks Co +AI14906,Deep Learning Engineer,155943,EUR,132552,SE,PT,Germany,L,Germany,50,"Deep Learning, Spark, Git, Kubernetes",PhD,9,Gaming,2024-02-19,2024-03-20,1251,9.1,Future Systems +AI14907,Autonomous Systems Engineer,108937,EUR,92596,SE,FL,Germany,M,Ghana,0,"Python, TensorFlow, Kubernetes, Data Visualization, Computer Vision",Bachelor,7,Real Estate,2024-11-11,2024-11-29,2247,9.5,Predictive Systems +AI14908,Computer Vision Engineer,107249,CHF,96524,EN,PT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, SQL, Java, Scala",PhD,0,Consulting,2025-02-19,2025-04-02,2331,7.7,Neural Networks Co +AI14909,Machine Learning Engineer,92023,USD,92023,MI,FL,Ireland,S,Ireland,50,"TensorFlow, Java, SQL, R",PhD,3,Education,2025-03-06,2025-04-02,1052,5.7,DeepTech Ventures +AI14910,AI Architect,67935,USD,67935,MI,FT,Finland,S,Canada,100,"SQL, PyTorch, GCP",PhD,3,Energy,2024-01-06,2024-02-15,1292,5.1,Cognitive Computing +AI14911,AI Architect,35800,USD,35800,MI,CT,India,L,India,100,"TensorFlow, Mathematics, Azure, Scala, Java",Master,4,Technology,2024-10-26,2024-12-10,2131,9.1,DataVision Ltd +AI14912,Computer Vision Engineer,35601,USD,35601,SE,PT,India,S,India,50,"Python, MLOps, R, Statistics, Hadoop",Bachelor,6,Technology,2024-05-31,2024-07-15,729,7.6,AI Innovations +AI14913,Data Scientist,122019,EUR,103716,SE,PT,Netherlands,M,Netherlands,0,"Spark, PyTorch, GCP, Azure, Statistics",Master,7,Manufacturing,2024-05-13,2024-06-20,770,8.6,DataVision Ltd +AI14914,Data Analyst,65215,AUD,88040,EN,PT,Australia,S,Australia,50,"SQL, Scala, Computer Vision, Deep Learning",PhD,0,Manufacturing,2024-07-17,2024-08-19,1315,7.7,Future Systems +AI14915,Robotics Engineer,151010,USD,151010,SE,CT,Norway,S,Norway,50,"Hadoop, Spark, Data Visualization, SQL",Bachelor,9,Finance,2024-01-24,2024-02-22,2036,7.2,AI Innovations +AI14916,NLP Engineer,90626,USD,90626,MI,FT,Israel,L,Israel,0,"PyTorch, Docker, Deep Learning, GCP",Bachelor,4,Gaming,2024-10-06,2024-10-20,2024,7.5,Predictive Systems +AI14917,AI Research Scientist,114235,EUR,97100,MI,FT,Austria,L,Austria,100,"Hadoop, Python, NLP",Master,2,Transportation,2024-11-06,2024-12-21,1677,7.6,Advanced Robotics +AI14918,AI Consultant,99643,USD,99643,EN,FT,Norway,M,Norway,0,"TensorFlow, Kubernetes, GCP, Linux",Bachelor,0,Media,2024-08-02,2024-08-29,1430,5.1,TechCorp Inc +AI14919,Machine Learning Researcher,114099,USD,114099,SE,FT,United States,S,United States,0,"Hadoop, MLOps, SQL, Data Visualization",Bachelor,9,Automotive,2024-12-05,2025-02-11,589,5,Cloud AI Solutions +AI14920,Robotics Engineer,187262,SGD,243441,EX,FL,Singapore,M,Singapore,100,"Kubernetes, AWS, Git, Data Visualization",PhD,14,Automotive,2025-01-09,2025-03-14,1439,7.9,Advanced Robotics +AI14921,Data Scientist,41245,USD,41245,SE,FL,India,M,India,0,"GCP, Spark, Java, Data Visualization",Bachelor,8,Finance,2024-10-22,2024-12-30,2167,6.3,Algorithmic Solutions +AI14922,Autonomous Systems Engineer,60902,USD,60902,EN,FL,Denmark,S,Denmark,100,"GCP, SQL, Azure, Mathematics",PhD,1,Technology,2025-04-10,2025-05-31,1742,5.4,TechCorp Inc +AI14923,Data Engineer,57892,EUR,49208,EN,PT,France,M,France,0,"GCP, Spark, Git",Bachelor,1,Automotive,2024-11-18,2025-01-18,2050,7.4,Quantum Computing Inc +AI14924,AI Consultant,127852,CAD,159815,EX,PT,Canada,S,Ghana,100,"Azure, AWS, NLP, Computer Vision, TensorFlow",Associate,18,Transportation,2024-02-03,2024-03-01,1403,8.6,DataVision Ltd +AI14925,Data Analyst,214783,JPY,23626130,EX,CT,Japan,S,Japan,50,"R, Linux, Mathematics, MLOps, SQL",Master,12,Energy,2024-02-26,2024-04-23,2345,6.1,Predictive Systems +AI14926,Data Engineer,87394,EUR,74285,MI,PT,France,S,France,0,"Python, NLP, Deep Learning, Hadoop, Computer Vision",Associate,2,Automotive,2024-09-10,2024-11-05,1737,7.3,Autonomous Tech +AI14927,Autonomous Systems Engineer,98451,USD,98451,EN,FT,Norway,M,Norway,0,"SQL, Linux, Kubernetes, Azure, NLP",Associate,0,Real Estate,2024-10-04,2024-10-18,2299,6,Digital Transformation LLC +AI14928,NLP Engineer,74127,GBP,55595,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Hadoop, Data Visualization, NLP",Bachelor,0,Automotive,2024-12-18,2025-01-04,2454,7.4,Quantum Computing Inc +AI14929,Machine Learning Researcher,51492,USD,51492,EX,PT,India,S,India,50,"Docker, GCP, Computer Vision, Kubernetes",Bachelor,10,Media,2024-07-28,2024-10-06,2116,5.7,Advanced Robotics +AI14930,Head of AI,168869,SGD,219530,EX,PT,Singapore,S,Singapore,0,"Deep Learning, Docker, PyTorch, AWS",Associate,11,Automotive,2024-01-20,2024-02-28,956,8.3,AI Innovations +AI14931,AI Software Engineer,104543,JPY,11499730,SE,CT,Japan,S,Japan,0,"R, Azure, TensorFlow, MLOps",Master,9,Transportation,2024-09-20,2024-10-22,1456,6.1,Digital Transformation LLC +AI14932,AI Product Manager,88186,SGD,114642,MI,PT,Singapore,M,Mexico,50,"Java, Computer Vision, Linux, Data Visualization, PyTorch",Associate,4,Transportation,2024-06-11,2024-07-09,1523,9.3,Advanced Robotics +AI14933,Data Scientist,135656,USD,135656,EX,FT,Finland,S,Latvia,0,"Linux, SQL, Git, Python",PhD,12,Telecommunications,2024-08-17,2024-09-18,1864,5.9,AI Innovations +AI14934,AI Software Engineer,124876,EUR,106145,EX,FT,Germany,S,Germany,0,"Statistics, MLOps, AWS, Computer Vision, Linux",PhD,12,Government,2024-04-22,2024-06-29,540,5.8,Smart Analytics +AI14935,Data Engineer,75356,CAD,94195,EN,FT,Canada,M,Canada,100,"PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2025-04-25,2025-06-14,1057,9.3,Algorithmic Solutions +AI14936,Data Engineer,95193,EUR,80914,SE,CT,France,S,France,0,"Linux, Computer Vision, Git, Spark, TensorFlow",Associate,5,Technology,2025-03-22,2025-05-31,2416,9.1,Cloud AI Solutions +AI14937,Autonomous Systems Engineer,203347,SGD,264351,EX,PT,Singapore,L,Singapore,50,"Data Visualization, Python, Git, NLP",PhD,16,Energy,2024-08-31,2024-10-13,2016,5.3,Predictive Systems +AI14938,Machine Learning Researcher,95262,GBP,71447,MI,PT,United Kingdom,M,South Africa,100,"Kubernetes, Data Visualization, Spark",Associate,2,Retail,2024-02-01,2024-04-01,1027,8.3,Machine Intelligence Group +AI14939,Computer Vision Engineer,162617,USD,162617,MI,PT,Denmark,L,Denmark,50,"Hadoop, Kubernetes, Linux, Scala, Azure",Associate,2,Automotive,2024-12-05,2024-12-27,2086,5.3,Autonomous Tech +AI14940,AI Research Scientist,119770,GBP,89828,SE,FL,United Kingdom,S,Malaysia,100,"Java, Azure, AWS, Hadoop",Associate,9,Technology,2025-01-27,2025-04-02,2470,7.5,Autonomous Tech +AI14941,Data Scientist,220001,CAD,275001,EX,PT,Canada,L,Canada,100,"Java, Scala, MLOps, Kubernetes",Bachelor,19,Telecommunications,2024-06-15,2024-08-07,757,5.3,AI Innovations +AI14942,AI Consultant,64943,EUR,55202,EN,FL,France,S,France,100,"PyTorch, AWS, MLOps, Tableau",Master,1,Manufacturing,2024-08-11,2024-10-11,1367,8.7,Machine Intelligence Group +AI14943,Data Scientist,218883,EUR,186051,EX,FL,Netherlands,S,Netherlands,0,"Hadoop, Docker, Spark, Deep Learning",Master,10,Energy,2024-04-06,2024-05-03,1713,9.4,Autonomous Tech +AI14944,AI Research Scientist,86404,USD,86404,MI,FL,Israel,M,Switzerland,50,"Computer Vision, Docker, Python",Master,2,Manufacturing,2024-02-14,2024-03-16,2410,7.7,Quantum Computing Inc +AI14945,AI Architect,175545,SGD,228209,EX,PT,Singapore,S,Singapore,100,"Git, Statistics, Python, Mathematics, Scala",Master,13,Automotive,2024-07-30,2024-09-12,571,9.1,Autonomous Tech +AI14946,AI Product Manager,148458,USD,148458,MI,FL,Norway,L,Norway,100,"Azure, Python, Statistics",Master,4,Gaming,2024-06-10,2024-08-06,1292,6,Advanced Robotics +AI14947,Deep Learning Engineer,104899,EUR,89164,MI,CT,Austria,L,Austria,50,"Computer Vision, Python, Spark, R",Associate,2,Healthcare,2024-01-12,2024-03-25,1839,5.6,Future Systems +AI14948,Data Engineer,101094,USD,101094,SE,FL,Finland,S,Finland,0,"Spark, SQL, Linux",Master,5,Finance,2025-04-12,2025-05-06,723,6.3,Predictive Systems +AI14949,AI Product Manager,125424,USD,125424,SE,FL,Finland,M,Finland,50,"Linux, SQL, Python, Git",PhD,7,Consulting,2024-10-27,2025-01-02,2396,6.3,Advanced Robotics +AI14950,Autonomous Systems Engineer,82744,JPY,9101840,MI,PT,Japan,M,South Africa,0,"GCP, Docker, Java, SQL",PhD,4,Gaming,2024-01-23,2024-02-19,1773,7.4,Machine Intelligence Group +AI14951,Computer Vision Engineer,117343,USD,117343,MI,PT,Norway,L,Norway,100,"Docker, Computer Vision, MLOps",Associate,2,Energy,2024-04-02,2024-06-01,515,6.7,AI Innovations +AI14952,ML Ops Engineer,118354,USD,118354,MI,CT,Sweden,L,Sweden,0,"Python, TensorFlow, R",Master,2,Education,2024-11-27,2025-01-31,1583,5.6,Predictive Systems +AI14953,Autonomous Systems Engineer,124093,USD,124093,EX,CT,South Korea,S,South Korea,100,"SQL, TensorFlow, Data Visualization",Bachelor,14,Real Estate,2024-09-28,2024-11-21,1677,6.8,DeepTech Ventures +AI14954,Deep Learning Engineer,63367,SGD,82377,EN,CT,Singapore,S,Singapore,0,"Data Visualization, GCP, Mathematics, Statistics, Scala",Bachelor,0,Retail,2025-04-29,2025-06-07,2329,5.4,Future Systems +AI14955,Machine Learning Researcher,161652,USD,161652,SE,FL,Norway,M,France,50,"MLOps, Deep Learning, NLP, PyTorch",Bachelor,5,Healthcare,2024-03-02,2024-05-07,1578,8.2,Cloud AI Solutions +AI14956,AI Research Scientist,104435,USD,104435,SE,FT,South Korea,M,South Korea,50,"Python, TensorFlow, AWS, PyTorch, SQL",PhD,5,Education,2024-11-17,2025-01-21,1555,7.3,Future Systems +AI14957,Data Scientist,140824,EUR,119700,SE,CT,Netherlands,S,Australia,50,"Statistics, Mathematics, Python",Bachelor,7,Government,2025-01-24,2025-03-17,2252,5.9,Future Systems +AI14958,NLP Engineer,33429,USD,33429,MI,PT,China,S,China,0,"SQL, MLOps, Mathematics, TensorFlow, GCP",Master,4,Education,2025-04-20,2025-05-06,628,9.8,Cloud AI Solutions +AI14959,Data Engineer,56924,USD,56924,EX,FL,India,L,India,100,"Kubernetes, Scala, Mathematics, TensorFlow, Linux",Master,12,Media,2025-02-13,2025-02-27,632,8.4,Cognitive Computing +AI14960,AI Specialist,108996,USD,108996,EN,FT,Norway,L,India,50,"GCP, Spark, Python",PhD,1,Government,2024-07-04,2024-08-23,1049,6.1,Future Systems +AI14961,AI Specialist,159001,USD,159001,SE,FL,United States,M,United States,50,"Data Visualization, NLP, AWS, R",Master,9,Transportation,2024-02-25,2024-04-03,1217,7.9,AI Innovations +AI14962,Machine Learning Researcher,186143,USD,186143,EX,FL,Norway,S,Norway,50,"Linux, Spark, Data Visualization",Associate,10,Healthcare,2024-07-18,2024-08-29,1432,8.4,Machine Intelligence Group +AI14963,AI Specialist,67937,USD,67937,SE,CT,China,L,China,0,"GCP, NLP, Scala, R, Java",PhD,6,Healthcare,2024-03-11,2024-04-02,2287,7.1,Cognitive Computing +AI14964,Machine Learning Engineer,62318,USD,62318,EN,PT,South Korea,L,South Korea,0,"Linux, TensorFlow, Deep Learning, Scala",PhD,1,Energy,2024-07-06,2024-08-10,1687,8.4,TechCorp Inc +AI14965,Deep Learning Engineer,92518,USD,92518,MI,FL,Israel,M,Israel,50,"Python, Data Visualization, Linux, Azure",Bachelor,2,Gaming,2024-11-17,2024-12-04,1191,6.2,Cognitive Computing +AI14966,Research Scientist,212794,AUD,287272,EX,FL,Australia,M,Australia,50,"Tableau, Kubernetes, TensorFlow, Mathematics",Bachelor,11,Consulting,2024-12-25,2025-02-26,1380,9.5,Neural Networks Co +AI14967,Research Scientist,116954,USD,116954,EX,FL,South Korea,M,Czech Republic,0,"SQL, Python, Docker",Master,12,Finance,2024-06-11,2024-07-26,1484,7.9,Quantum Computing Inc +AI14968,AI Specialist,146064,USD,146064,SE,PT,Sweden,L,Sweden,0,"Kubernetes, SQL, Linux",Associate,8,Healthcare,2024-12-29,2025-02-06,1882,6.3,DeepTech Ventures +AI14969,Principal Data Scientist,105890,SGD,137657,MI,FL,Singapore,L,Luxembourg,100,"Python, Computer Vision, Tableau",PhD,4,Real Estate,2024-05-10,2024-06-04,2107,7.7,Neural Networks Co +AI14970,Data Analyst,62944,AUD,84974,EN,FL,Australia,S,Malaysia,100,"Docker, TensorFlow, Mathematics, AWS, SQL",Master,0,Automotive,2024-04-01,2024-06-12,1846,6.4,Machine Intelligence Group +AI14971,AI Research Scientist,142892,USD,142892,MI,FL,Denmark,L,Denmark,0,"Data Visualization, Scala, SQL, Kubernetes",Bachelor,4,Automotive,2024-09-20,2024-10-18,770,5.7,Neural Networks Co +AI14972,Data Engineer,182144,USD,182144,EX,FL,Denmark,M,Nigeria,100,"Python, NLP, TensorFlow, Docker",Associate,17,Telecommunications,2024-11-20,2025-01-24,1514,6.3,DataVision Ltd +AI14973,Computer Vision Engineer,184474,USD,184474,EX,PT,Finland,S,Finland,0,"Java, GCP, SQL, Docker, PyTorch",PhD,11,Real Estate,2024-03-31,2024-05-20,921,6.9,Cloud AI Solutions +AI14974,AI Architect,105686,USD,105686,SE,CT,South Korea,L,Japan,0,"Data Visualization, Docker, Spark",PhD,8,Technology,2024-09-07,2024-11-01,2269,6.3,Cloud AI Solutions +AI14975,Computer Vision Engineer,40256,USD,40256,EN,FL,South Korea,S,South Korea,100,"Tableau, Linux, PyTorch, GCP, Python",Master,1,Consulting,2024-11-26,2024-12-18,2172,9.6,Quantum Computing Inc +AI14976,AI Specialist,116503,USD,116503,MI,FL,Sweden,L,Sweden,0,"Kubernetes, Hadoop, GCP, Spark, Java",PhD,3,Government,2024-09-11,2024-11-05,2035,9.7,Cognitive Computing +AI14977,AI Specialist,161707,CAD,202134,EX,PT,Canada,L,Estonia,0,"MLOps, Java, Linux",Master,18,Consulting,2024-05-03,2024-06-26,1766,9,Smart Analytics +AI14978,AI Architect,176965,USD,176965,SE,FL,Denmark,M,Denmark,50,"Python, GCP, Hadoop, Statistics",Master,6,Healthcare,2024-03-20,2024-05-22,1431,5.3,Future Systems +AI14979,Data Analyst,165811,USD,165811,EX,FT,Ireland,M,Ireland,50,"Python, SQL, GCP",Associate,18,Telecommunications,2024-06-25,2024-07-21,840,6.7,TechCorp Inc +AI14980,Deep Learning Engineer,64531,JPY,7098410,EN,FT,Japan,M,United States,100,"PyTorch, TensorFlow, GCP",PhD,0,Healthcare,2024-11-30,2024-12-31,1047,9.2,Predictive Systems +AI14981,Data Scientist,102580,CHF,92322,EN,FT,Switzerland,S,Switzerland,50,"Java, AWS, Data Visualization, Statistics",Master,0,Education,2025-04-07,2025-06-04,2165,5.9,Predictive Systems +AI14982,NLP Engineer,203175,USD,203175,EX,PT,Israel,S,Israel,0,"Spark, Docker, PyTorch, Kubernetes",PhD,14,Automotive,2025-03-20,2025-05-13,1966,6,Predictive Systems +AI14983,Data Scientist,49068,USD,49068,EN,PT,Israel,M,Israel,0,"Kubernetes, GCP, Linux",PhD,0,Healthcare,2024-02-04,2024-04-08,1800,6,Algorithmic Solutions +AI14984,Research Scientist,224701,USD,224701,SE,FT,Denmark,L,Denmark,0,"PyTorch, Data Visualization, NLP, Statistics",Master,5,Gaming,2024-06-27,2024-08-24,2392,7.9,Predictive Systems +AI14985,Computer Vision Engineer,74923,USD,74923,MI,PT,Ireland,M,Ireland,100,"PyTorch, Linux, TensorFlow, GCP, Java",PhD,4,Manufacturing,2024-03-19,2024-05-19,1755,8.2,Digital Transformation LLC +AI14986,Computer Vision Engineer,87266,GBP,65450,EN,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, Computer Vision, MLOps, Azure",PhD,0,Telecommunications,2024-11-19,2024-12-24,2402,5.1,DataVision Ltd +AI14987,ML Ops Engineer,200074,EUR,170063,EX,CT,Austria,M,Austria,50,"MLOps, Kubernetes, Mathematics",Associate,18,Energy,2024-07-26,2024-08-16,2163,6.5,Cognitive Computing +AI14988,Data Analyst,108520,JPY,11937200,MI,FT,Japan,M,Japan,100,"SQL, Hadoop, Scala, Kubernetes, Mathematics",Associate,3,Education,2025-03-19,2025-05-16,914,8.3,Neural Networks Co +AI14989,Autonomous Systems Engineer,104423,SGD,135750,MI,FT,Singapore,M,Singapore,100,"Docker, Kubernetes, Azure, TensorFlow, Deep Learning",Bachelor,2,Technology,2024-07-14,2024-08-04,844,5.3,Cloud AI Solutions +AI14990,ML Ops Engineer,68334,EUR,58084,EN,FT,Germany,L,Australia,100,"Scala, SQL, Java, R",Bachelor,0,Gaming,2024-04-22,2024-06-19,1506,9.2,Smart Analytics +AI14991,AI Product Manager,58388,SGD,75904,EN,FT,Singapore,M,Singapore,50,"Deep Learning, Git, Data Visualization, Tableau",PhD,0,Real 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0AI00001Data Scientist219728USD219728EXPTSwedenMSweden0Python, Computer Vision, R, DockerAssociate13Transportation2024-09-232024-10-3111326.6TechCorp Inc
1AI00002Head of AI230237JPY25326070EXPTJapanLJapan50Kubernetes, MLOps, Tableau, PythonBachelor10Transportation2024-07-262024-09-1222998.5Cloud AI Solutions
2AI00003Data Engineer128890EUR109557EXCTGermanySGermany100Spark, Scala, Hadoop, PyTorch, GCPBachelor12Automotive2025-01-192025-03-2813295.5Quantum Computing Inc
3AI00004Computer Vision Engineer96349USD96349MIFLFinlandLFinland50MLOps, Linux, Tableau, PythonPhD2Automotive2024-07-202024-09-0611326.8Cognitive Computing
4AI00005Robotics Engineer63065EUR53605ENFTFranceSFrance100R, Scala, SQL, GCP, PythonAssociate0Finance2025-03-162025-05-0920119.3Advanced Robotics
...............................................................
14995AI14996AI Product Manager39171USD39171MICTChinaMChina50Azure, R, NLP, Docker, Computer VisionPhD4Consulting2025-01-072025-02-0711075.2Smart Analytics
14996AI14997AI Product Manager77555EUR65922ENCTNetherlandsMNetherlands50Python, TensorFlow, Mathematics, AWS, Computer...PhD0Energy2024-12-222025-02-1218709.7Autonomous Tech
14997AI14998Data Engineer28380USD28380ENFLIndiaMIndia50Azure, Kubernetes, Spark, Statistics, MLOpsAssociate1Government2024-05-042024-05-2115589.0Digital Transformation LLC
14998AI14999AI Specialist58764EUR49949ENPTFranceMFrance100MLOps, Statistics, Data Visualization, R, PythonMaster0Real Estate2024-05-082024-06-225468.4Machine Intelligence Group
14999AI15000Principal Data Scientist58623USD58623SEFTChinaMChina0AWS, Spark, Computer Vision, Data Visualizatio...PhD6Transportation2024-11-232024-12-1510349.7Quantum Computing Inc
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"df.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a4498be2-3f6d-463b-bede-2cb9cc7bbe9d", - "metadata": {}, - "outputs": [], - "source": [ - "df[" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:base] *", - "language": "python", - "name": "conda-base-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From e6cdb9e4fb38a56223858429312fd39b02ad7296 Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Tue, 9 Dec 2025 11:28:42 +0100 Subject: [PATCH 08/26] deleted every old docs --- ai_job_dataset1.csv | 15001 -------------------------------- first_project_data.ipynb | 666 -- notebooks/ai_job_dataset1.csv | 15001 -------------------------------- 3 files changed, 30668 deletions(-) delete mode 100644 ai_job_dataset1.csv delete mode 100644 first_project_data.ipynb delete mode 100644 notebooks/ai_job_dataset1.csv diff --git a/ai_job_dataset1.csv b/ai_job_dataset1.csv deleted file mode 100644 index 5c9e5669..00000000 --- a/ai_job_dataset1.csv +++ /dev/null @@ -1,15001 +0,0 @@ -job_id,job_title,salary_usd,salary_currency,salary_local,experience_level,employment_type,company_location,company_size,employee_residence,remote_ratio,required_skills,education_required,years_experience,industry,posting_date,application_deadline,job_description_length,benefits_score,company_name -AI00001,Data Scientist,219728,USD,219728,EX,PT,Sweden,M,Sweden,0,"Python, Computer Vision, R, Docker",Associate,13,Transportation,2024-09-23,2024-10-31,1132,6.6,TechCorp Inc -AI00002,Head of AI,230237,JPY,25326070,EX,PT,Japan,L,Japan,50,"Kubernetes, MLOps, Tableau, Python",Bachelor,10,Transportation,2024-07-26,2024-09-12,2299,8.5,Cloud AI Solutions -AI00003,Data Engineer,128890,EUR,109557,EX,CT,Germany,S,Germany,100,"Spark, Scala, Hadoop, PyTorch, GCP",Bachelor,12,Automotive,2025-01-19,2025-03-28,1329,5.5,Quantum Computing Inc -AI00004,Computer Vision Engineer,96349,USD,96349,MI,FL,Finland,L,Finland,50,"MLOps, Linux, Tableau, Python",PhD,2,Automotive,2024-07-20,2024-09-06,1132,6.8,Cognitive Computing -AI00005,Robotics Engineer,63065,EUR,53605,EN,FT,France,S,France,100,"R, Scala, SQL, GCP, Python",Associate,0,Finance,2025-03-16,2025-05-09,2011,9.3,Advanced Robotics -AI00006,Data Scientist,111794,SGD,145332,SE,CT,Singapore,S,Norway,50,"NLP, MLOps, TensorFlow",Master,7,Technology,2024-11-10,2025-01-20,1021,5.1,Cloud AI Solutions -AI00007,AI Consultant,113897,CAD,142371,SE,PT,Canada,L,Poland,50,"PyTorch, Linux, NLP",Associate,9,Gaming,2024-02-29,2024-04-21,2268,7.4,AI Innovations -AI00008,Head of AI,168639,AUD,227663,SE,FT,Australia,L,Vietnam,100,"Spark, SQL, Tableau, Computer Vision, Linux",Associate,9,Consulting,2024-02-26,2024-03-17,1497,5.5,TechCorp Inc -AI00009,Data Scientist,92624,JPY,10188640,MI,FT,Japan,L,Japan,50,"Kubernetes, SQL, Docker, Deep Learning",Bachelor,4,Government,2024-08-18,2024-10-03,1724,9.5,DataVision Ltd -AI00010,Machine Learning Engineer,215627,GBP,161720,EX,FT,United Kingdom,M,United Kingdom,50,"Git, Scala, GCP",PhD,10,Government,2025-01-18,2025-03-20,902,7.8,DeepTech Ventures -AI00011,Data Engineer,129706,USD,129706,MI,CT,Denmark,L,Denmark,0,"SQL, PyTorch, Statistics, TensorFlow, NLP",Bachelor,3,Consulting,2024-03-10,2024-05-17,2247,5.2,Cloud AI Solutions -AI00012,Deep Learning Engineer,76559,USD,76559,EN,FL,United States,S,United States,100,"Data Visualization, Mathematics, PyTorch, GCP",Bachelor,1,Government,2025-02-09,2025-04-14,694,8.3,Machine Intelligence Group -AI00013,Principal Data Scientist,185834,USD,185834,EX,CT,United States,L,United States,100,"Linux, Data Visualization, Python, TensorFlow",Associate,14,Telecommunications,2024-03-27,2024-06-03,1710,8.9,Autonomous Tech -AI00014,Principal Data Scientist,89801,USD,89801,MI,PT,Sweden,M,Belgium,100,"Linux, MLOps, Deep Learning",Master,3,Healthcare,2024-10-30,2025-01-06,1361,8.7,Cloud AI Solutions -AI00015,Principal Data Scientist,252601,USD,252601,EX,PT,Norway,L,Norway,100,"Kubernetes, SQL, AWS, Git, Computer Vision",Master,19,Gaming,2024-07-24,2024-08-14,572,5.1,TechCorp Inc -AI00016,AI Product Manager,20520,USD,20520,EN,FT,India,S,India,0,"Hadoop, Git, Computer Vision, Kubernetes, Data Visualization",Master,0,Gaming,2024-08-22,2024-10-05,2455,7.5,Predictive Systems -AI00017,Robotics Engineer,192789,CHF,173510,SE,PT,Switzerland,S,Switzerland,100,"Tableau, Git, Python, Java",Master,5,Healthcare,2024-03-27,2024-06-08,524,5.9,Quantum Computing Inc -AI00018,Machine Learning Researcher,107184,SGD,139339,SE,FL,Singapore,S,Singapore,50,"Azure, GCP, Computer Vision",Master,7,Automotive,2024-05-07,2024-05-28,2111,9.2,DeepTech Ventures -AI00019,Robotics Engineer,141909,EUR,120623,SE,FT,Netherlands,M,Netherlands,0,"Git, Kubernetes, MLOps, Spark",Associate,6,Healthcare,2024-12-22,2025-01-20,1601,7.8,Cloud AI Solutions -AI00020,Data Engineer,118238,USD,118238,SE,FL,Ireland,M,Ireland,100,"AWS, Python, Azure, SQL, Computer Vision",Associate,7,Education,2024-11-07,2025-01-02,2431,8.2,TechCorp Inc -AI00021,Data Scientist,155210,AUD,209534,SE,PT,Australia,L,Argentina,0,"Spark, NLP, AWS",Master,7,Energy,2025-01-24,2025-03-18,595,9.7,Neural Networks Co -AI00022,Data Engineer,96699,AUD,130544,SE,FT,Australia,S,Australia,0,"GCP, Linux, Mathematics",PhD,5,Technology,2025-03-29,2025-04-13,582,9.7,TechCorp Inc -AI00023,AI Software Engineer,161477,EUR,137255,SE,FT,France,L,France,50,"Mathematics, Spark, Linux",Bachelor,8,Real Estate,2025-02-04,2025-03-03,1861,9.5,DataVision Ltd -AI00024,AI Software Engineer,316709,USD,316709,EX,CT,Denmark,L,Denmark,50,"Data Visualization, Azure, Statistics",PhD,18,Transportation,2025-04-29,2025-06-21,1284,7.6,Autonomous Tech -AI00025,ML Ops Engineer,62089,CAD,77611,MI,CT,Canada,S,Singapore,50,"Python, GCP, Linux, SQL, Deep Learning",PhD,3,Media,2024-03-18,2024-04-25,2264,9.7,Predictive Systems -AI00026,Principal Data Scientist,77985,USD,77985,EN,CT,Denmark,S,Denmark,0,"SQL, TensorFlow, Computer Vision, Kubernetes",Associate,0,Automotive,2025-03-07,2025-04-03,655,9.4,Neural Networks Co -AI00027,Robotics Engineer,55315,EUR,47018,EN,PT,Austria,S,Austria,0,"Spark, Deep Learning, SQL, NLP, Python",PhD,0,Media,2025-01-09,2025-03-22,1107,9.5,Future Systems -AI00028,AI Architect,246647,SGD,320641,EX,PT,Singapore,M,Singapore,50,"Scala, Mathematics, SQL",Master,16,Telecommunications,2024-08-08,2024-08-26,2347,6.6,DeepTech Ventures -AI00029,Deep Learning Engineer,29050,USD,29050,EN,FT,China,S,Germany,0,"PyTorch, Kubernetes, Deep Learning, Hadoop",Associate,1,Consulting,2025-02-06,2025-03-19,555,5.2,AI Innovations -AI00030,Head of AI,120599,GBP,90449,MI,CT,United Kingdom,L,United Kingdom,50,"Linux, AWS, Python",Master,4,Energy,2024-09-21,2024-11-07,699,6.4,Quantum Computing Inc -AI00031,AI Specialist,277727,SGD,361045,EX,PT,Singapore,L,Singapore,50,"Python, Git, TensorFlow",Associate,13,Healthcare,2024-10-04,2024-11-05,529,9,Future Systems -AI00032,Data Engineer,158734,CAD,198418,EX,PT,Canada,S,South Korea,50,"Data Visualization, NLP, Computer Vision",Master,16,Retail,2024-05-20,2024-07-29,1607,6.2,Future Systems -AI00033,Data Engineer,139438,JPY,15338180,SE,FL,Japan,L,Japan,0,"Python, Spark, Git, Data Visualization, Docker",PhD,9,Retail,2025-03-16,2025-05-12,1826,9.9,Cognitive Computing -AI00034,Head of AI,131432,SGD,170862,SE,PT,Singapore,M,Sweden,50,"Kubernetes, Data Visualization, Deep Learning, Azure, Computer Vision",Master,5,Manufacturing,2024-05-03,2024-07-15,1134,5.3,Cognitive Computing -AI00035,Data Analyst,140290,USD,140290,MI,PT,Denmark,L,Denmark,50,"PyTorch, SQL, R, Azure",Associate,4,Real Estate,2024-07-18,2024-09-26,2437,5.7,DeepTech Ventures -AI00036,Research Scientist,90858,EUR,77229,MI,CT,France,L,France,50,"Scala, PyTorch, Deep Learning, Kubernetes, Java",Bachelor,2,Real Estate,2024-08-13,2024-09-13,1793,7.1,DataVision Ltd -AI00037,Autonomous Systems Engineer,126597,GBP,94948,SE,FL,United Kingdom,L,Singapore,50,"PyTorch, Java, TensorFlow, Computer Vision, SQL",Master,6,Government,2024-03-30,2024-04-13,2236,7.8,Machine Intelligence Group -AI00038,AI Architect,53274,USD,53274,EN,FL,Finland,M,Finland,100,"Spark, Python, Statistics, Hadoop, TensorFlow",Associate,0,Automotive,2025-03-22,2025-04-12,1444,6,Autonomous Tech -AI00039,Machine Learning Researcher,155357,USD,155357,EX,FL,Sweden,S,France,100,"TensorFlow, SQL, Computer Vision, Kubernetes",Bachelor,17,Real Estate,2024-12-11,2025-01-01,830,5.2,Cloud AI Solutions -AI00040,Principal Data Scientist,116292,EUR,98848,MI,FL,Netherlands,M,Hungary,50,"Java, Docker, Python",Bachelor,4,Gaming,2024-07-28,2024-09-06,2404,7.9,Quantum Computing Inc -AI00041,Computer Vision Engineer,140363,EUR,119309,SE,CT,Austria,L,Austria,100,"MLOps, Hadoop, TensorFlow, Kubernetes",Master,6,Manufacturing,2025-01-31,2025-04-06,1852,9.8,TechCorp Inc -AI00042,Research Scientist,162306,USD,162306,SE,CT,Israel,L,Luxembourg,0,"Statistics, SQL, Tableau, Hadoop, R",Master,9,Energy,2024-11-12,2024-12-08,1066,5.6,Neural Networks Co -AI00043,Data Analyst,134224,USD,134224,EX,FT,China,L,China,0,"Python, SQL, Git",Master,16,Technology,2024-10-13,2024-11-15,1743,6.6,Quantum Computing Inc -AI00044,Research Scientist,77500,GBP,58125,MI,CT,United Kingdom,S,Norway,0,"Mathematics, Hadoop, TensorFlow",PhD,3,Technology,2024-08-20,2024-10-29,811,10,Machine Intelligence Group -AI00045,Computer Vision Engineer,154083,USD,154083,SE,PT,Ireland,L,Ireland,50,"Hadoop, Python, Deep Learning",Associate,7,Manufacturing,2024-01-09,2024-02-16,1969,7.7,Neural Networks Co -AI00046,Machine Learning Engineer,79445,USD,79445,MI,FL,Ireland,M,Ireland,50,"Python, Statistics, TensorFlow, Computer Vision",Bachelor,4,Real Estate,2024-09-28,2024-10-16,511,7.2,Cloud AI Solutions -AI00047,Head of AI,157466,CHF,141719,SE,FL,Switzerland,M,Switzerland,100,"Git, Data Visualization, Spark, Computer Vision, Azure",Associate,8,Automotive,2024-01-21,2024-03-03,547,5.2,Future Systems -AI00048,Head of AI,38972,USD,38972,MI,FT,India,L,India,0,"Kubernetes, Mathematics, TensorFlow, MLOps",PhD,4,Real Estate,2024-01-28,2024-03-09,2163,7.1,AI Innovations -AI00049,Deep Learning Engineer,66090,CAD,82613,MI,PT,Canada,S,Canada,0,"AWS, SQL, R, Scala",PhD,3,Technology,2025-04-10,2025-04-29,1901,5.3,DeepTech Ventures -AI00050,Data Analyst,47943,USD,47943,MI,PT,China,L,China,50,"TensorFlow, Mathematics, NLP, Docker",PhD,2,Finance,2024-11-23,2025-01-13,2483,6.2,Smart Analytics -AI00051,ML Ops Engineer,217318,USD,217318,EX,PT,Ireland,M,Malaysia,100,"SQL, PyTorch, Hadoop",Bachelor,17,Finance,2024-11-14,2024-12-22,1647,7.8,Cognitive Computing -AI00052,AI Architect,84705,USD,84705,MI,CT,Norway,S,Norway,50,"Scala, Spark, PyTorch",PhD,3,Government,2024-12-19,2025-01-11,879,6.6,Autonomous Tech -AI00053,NLP Engineer,36076,USD,36076,SE,FT,India,M,India,50,"Python, TensorFlow, Data Visualization",Master,7,Media,2024-08-14,2024-09-23,580,7.5,Cognitive Computing -AI00054,AI Consultant,160216,USD,160216,EX,FT,Israel,L,Israel,100,"Deep Learning, Linux, Python, SQL",Master,15,Education,2024-05-09,2024-05-29,941,6,Predictive Systems -AI00055,Deep Learning Engineer,60826,GBP,45620,EN,FT,United Kingdom,S,United Kingdom,0,"SQL, Kubernetes, Azure",Bachelor,0,Energy,2024-11-02,2024-11-30,1731,6.3,Autonomous Tech -AI00056,Deep Learning Engineer,237320,GBP,177990,EX,PT,United Kingdom,M,United Kingdom,0,"Kubernetes, MLOps, Scala",Bachelor,16,Real Estate,2024-11-12,2024-12-28,991,7.7,DataVision Ltd -AI00057,Robotics Engineer,60243,EUR,51207,EN,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Linux, Mathematics",Master,1,Healthcare,2024-12-05,2024-12-20,1661,8.8,Future Systems -AI00058,Head of AI,74091,JPY,8150010,EN,PT,Japan,M,Japan,50,"Deep Learning, NLP, R, Linux, SQL",Bachelor,1,Consulting,2025-01-18,2025-03-23,1295,7.2,Quantum Computing Inc -AI00059,AI Specialist,68535,EUR,58255,EN,FT,France,L,France,100,"SQL, Scala, PyTorch",Associate,1,Media,2024-05-01,2024-06-17,1943,5.5,Machine Intelligence Group -AI00060,Robotics Engineer,99401,USD,99401,MI,FL,Norway,S,Norway,50,"Hadoop, Kubernetes, Data Visualization, Python, Linux",Bachelor,3,Healthcare,2024-03-20,2024-04-20,1371,9.4,Quantum Computing Inc -AI00061,Machine Learning Researcher,67632,USD,67632,EN,FT,Ireland,L,Ireland,0,"Linux, GCP, Deep Learning",Master,0,Government,2024-07-13,2024-08-10,2133,8.9,Advanced Robotics -AI00062,ML Ops Engineer,133163,EUR,113189,SE,CT,Netherlands,M,Netherlands,0,"SQL, Statistics, MLOps, PyTorch, Kubernetes",Associate,6,Media,2025-01-03,2025-01-21,2141,7.9,Neural Networks Co -AI00063,Robotics Engineer,125752,USD,125752,MI,FT,Norway,S,Norway,0,"NLP, Statistics, Scala",Master,4,Automotive,2024-05-17,2024-06-24,2390,6,Machine Intelligence Group -AI00064,AI Product Manager,70927,JPY,7801970,EN,CT,Japan,M,Japan,0,"Git, Computer Vision, Docker, SQL, Hadoop",Associate,1,Technology,2024-03-07,2024-04-05,1847,9.3,Quantum Computing Inc -AI00065,Data Engineer,80810,GBP,60608,EN,PT,United Kingdom,L,United Kingdom,0,"Azure, MLOps, Python, Linux, TensorFlow",Master,1,Energy,2024-10-30,2025-01-01,1476,5.4,Algorithmic Solutions -AI00066,Machine Learning Engineer,59614,SGD,77498,EN,CT,Singapore,S,Singapore,100,"Java, Kubernetes, GCP, Linux, Data Visualization",Associate,1,Healthcare,2024-11-07,2024-12-19,1581,7.3,Quantum Computing Inc -AI00067,Robotics Engineer,151907,EUR,129121,EX,FT,Germany,S,Ghana,50,"Python, R, MLOps",Associate,16,Media,2024-09-21,2024-10-16,1433,6.1,Quantum Computing Inc -AI00068,Data Scientist,76317,USD,76317,EX,CT,India,M,India,0,"TensorFlow, Deep Learning, Spark",Bachelor,14,Energy,2024-06-19,2024-07-15,1228,9.1,DataVision Ltd -AI00069,AI Research Scientist,160534,USD,160534,SE,FL,Denmark,M,Denmark,100,"GCP, SQL, MLOps",Master,9,Gaming,2024-06-10,2024-07-07,1651,8.3,Advanced Robotics -AI00070,AI Consultant,40687,USD,40687,MI,FT,India,L,India,50,"SQL, R, GCP, PyTorch, AWS",Master,3,Transportation,2024-07-16,2024-08-25,804,7.3,Algorithmic Solutions -AI00071,Computer Vision Engineer,129265,AUD,174508,SE,FL,Australia,S,Australia,0,"Java, Scala, TensorFlow",Master,5,Consulting,2025-04-06,2025-05-07,2410,6.9,DataVision Ltd -AI00072,NLP Engineer,94396,USD,94396,EX,PT,China,M,China,100,"Scala, Python, Tableau, Mathematics",Master,18,Government,2024-07-30,2024-08-18,1033,9.5,Advanced Robotics -AI00073,NLP Engineer,158237,USD,158237,EX,CT,South Korea,L,South Korea,0,"Python, NLP, GCP",Master,11,Finance,2025-01-24,2025-03-29,1676,6,Quantum Computing Inc -AI00074,Robotics Engineer,239068,USD,239068,EX,PT,Denmark,L,Denmark,50,"TensorFlow, Java, NLP, Hadoop, GCP",PhD,18,Media,2024-08-26,2024-10-30,1321,6.8,Autonomous Tech -AI00075,Robotics Engineer,81401,USD,81401,MI,FL,Finland,M,Belgium,0,"Java, Spark, Data Visualization, AWS, Git",Associate,2,Retail,2025-02-07,2025-04-11,1930,6.3,Future Systems -AI00076,AI Specialist,144229,CHF,129806,MI,FT,Switzerland,M,Japan,0,"Python, TensorFlow, MLOps, PyTorch",PhD,2,Media,2024-01-02,2024-03-02,1213,9.5,DeepTech Ventures -AI00077,AI Consultant,78936,EUR,67096,MI,FL,Germany,S,Germany,0,"Mathematics, Tableau, R, NLP, SQL",Bachelor,4,Consulting,2024-11-30,2025-01-03,697,6.9,Cloud AI Solutions -AI00078,AI Consultant,101054,USD,101054,SE,PT,South Korea,L,United Kingdom,0,"PyTorch, Python, TensorFlow",Bachelor,6,Healthcare,2025-02-04,2025-03-20,2396,8.8,DeepTech Ventures -AI00079,AI Specialist,91807,EUR,78036,SE,FT,Austria,S,Austria,50,"Linux, Azure, Scala, Python",Master,9,Education,2024-07-21,2024-09-13,1519,8.3,TechCorp Inc -AI00080,Machine Learning Engineer,49858,EUR,42379,EN,CT,Austria,S,Singapore,100,"PyTorch, Spark, Linux",Bachelor,1,Healthcare,2024-01-25,2024-04-02,1215,9.2,AI Innovations -AI00081,Robotics Engineer,80596,EUR,68507,EN,FT,Austria,L,Switzerland,0,"Kubernetes, Scala, PyTorch, Mathematics",Master,1,Education,2024-06-27,2024-08-26,1512,6.8,Digital Transformation LLC -AI00082,Head of AI,76026,USD,76026,MI,FT,Sweden,M,Sweden,50,"Tableau, SQL, R, Scala",PhD,4,Healthcare,2025-02-12,2025-03-24,1079,8,Predictive Systems -AI00083,Deep Learning Engineer,84841,USD,84841,MI,CT,Sweden,L,Sweden,0,"Azure, Linux, TensorFlow, GCP",Associate,4,Transportation,2024-11-18,2025-01-05,2456,5.7,Cognitive Computing -AI00084,Data Scientist,158900,CHF,143010,SE,FL,Switzerland,M,Switzerland,50,"Python, Statistics, Mathematics, Docker, TensorFlow",Associate,8,Finance,2024-06-14,2024-07-05,2367,6,Quantum Computing Inc -AI00085,Autonomous Systems Engineer,153858,EUR,130779,EX,CT,Germany,S,Germany,50,"MLOps, Azure, Java",Master,13,Gaming,2025-04-29,2025-06-21,2133,5.1,Cloud AI Solutions -AI00086,Data Scientist,115314,USD,115314,MI,CT,Denmark,M,Finland,0,"Java, Git, R, Azure",Bachelor,3,Real Estate,2024-06-01,2024-06-27,1783,7.9,Smart Analytics -AI00087,Machine Learning Engineer,181068,USD,181068,EX,FT,Israel,S,Israel,100,"R, Java, Hadoop, Mathematics",PhD,13,Transportation,2024-01-26,2024-03-25,1322,8.5,Machine Intelligence Group -AI00088,AI Software Engineer,119021,USD,119021,EN,FT,Denmark,L,Portugal,0,"Computer Vision, Docker, Linux, GCP",PhD,1,Transportation,2025-03-07,2025-05-10,1461,7.3,DataVision Ltd -AI00089,Data Analyst,219746,USD,219746,EX,FL,Israel,M,Czech Republic,100,"R, Python, Scala, TensorFlow",PhD,15,Finance,2024-07-02,2024-09-12,1485,7,Smart Analytics -AI00090,AI Consultant,115774,USD,115774,EX,FL,China,L,China,50,"Hadoop, Scala, NLP, PyTorch, SQL",Associate,10,Real Estate,2024-02-04,2024-03-09,1618,5.3,DataVision Ltd -AI00091,AI Consultant,130984,CHF,117886,EN,PT,Switzerland,L,Philippines,50,"MLOps, Deep Learning, Kubernetes, Azure, GCP",Bachelor,1,Retail,2024-01-08,2024-03-20,1774,5.3,DataVision Ltd -AI00092,ML Ops Engineer,191223,CHF,172101,EX,FT,Switzerland,S,Germany,0,"NLP, Azure, SQL",PhD,18,Healthcare,2024-04-07,2024-06-07,1926,6.8,Neural Networks Co -AI00093,AI Consultant,155502,USD,155502,SE,FT,Norway,M,Italy,50,"Python, NLP, AWS, Spark",PhD,9,Consulting,2025-01-29,2025-02-22,2449,7.6,Future Systems -AI00094,AI Specialist,86140,EUR,73219,MI,PT,Germany,L,South Korea,50,"Scala, Kubernetes, Deep Learning, AWS",Master,4,Real Estate,2025-03-11,2025-04-12,1816,7.3,Predictive Systems -AI00095,AI Architect,96028,GBP,72021,MI,FL,United Kingdom,L,Australia,0,"Data Visualization, MLOps, GCP, PyTorch",Bachelor,4,Healthcare,2025-03-09,2025-03-28,1878,6.6,Future Systems -AI00096,Principal Data Scientist,134920,USD,134920,SE,PT,United States,S,United States,0,"SQL, Mathematics, Data Visualization, Kubernetes",Associate,7,Consulting,2025-04-03,2025-05-12,1930,6.7,Predictive Systems -AI00097,Research Scientist,107694,USD,107694,SE,FL,Ireland,M,Estonia,50,"Spark, Linux, MLOps, R",Associate,5,Retail,2024-03-20,2024-04-22,2292,5.1,Future Systems -AI00098,Deep Learning Engineer,114301,USD,114301,MI,FT,Finland,L,Finland,0,"Tableau, MLOps, Python",Bachelor,4,Real Estate,2025-02-08,2025-03-05,1506,7.5,Digital Transformation LLC -AI00099,Machine Learning Researcher,92728,GBP,69546,MI,FT,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes, Azure",Bachelor,4,Transportation,2024-12-25,2025-02-05,1948,9.3,Cognitive Computing -AI00100,NLP Engineer,76826,SGD,99874,EN,PT,Singapore,M,Singapore,50,"Git, R, Statistics, PyTorch, Deep Learning",Bachelor,1,Government,2025-04-08,2025-05-10,804,7.4,Predictive Systems -AI00101,AI Consultant,48870,USD,48870,SE,PT,India,L,India,0,"Hadoop, Java, Azure, Spark, Statistics",Associate,7,Healthcare,2025-03-26,2025-05-16,1108,5.6,Cognitive Computing -AI00102,Data Scientist,89527,AUD,120861,MI,FT,Australia,L,United States,50,"Linux, Azure, SQL, R, Java",Master,4,Finance,2024-12-09,2024-12-30,1299,5.8,Predictive Systems -AI00103,Autonomous Systems Engineer,81103,AUD,109489,EN,CT,Australia,L,Australia,0,"Mathematics, SQL, Kubernetes",Master,0,Media,2024-05-26,2024-08-07,2055,7,Digital Transformation LLC -AI00104,Machine Learning Engineer,283428,USD,283428,EX,CT,Denmark,L,Denmark,0,"Python, TensorFlow, MLOps, Data Visualization",Associate,13,Healthcare,2025-03-10,2025-05-11,1275,5.1,Smart Analytics -AI00105,AI Product Manager,104906,USD,104906,MI,FL,United States,S,Portugal,50,"PyTorch, Java, Spark, Statistics",Bachelor,3,Technology,2025-01-26,2025-03-28,2101,8,Cognitive Computing -AI00106,AI Software Engineer,231496,USD,231496,EX,PT,Finland,L,Finland,50,"Tableau, R, Kubernetes",Master,18,Automotive,2025-02-13,2025-04-10,895,5.5,DataVision Ltd -AI00107,Robotics Engineer,147402,JPY,16214220,SE,FT,Japan,L,Japan,100,"Azure, GCP, Scala, R, Python",Bachelor,8,Automotive,2024-12-11,2025-02-01,593,7,Algorithmic Solutions -AI00108,Data Scientist,69331,EUR,58931,EN,FT,Austria,L,Austria,100,"AWS, Git, NLP, Java, Computer Vision",Master,1,Healthcare,2025-04-11,2025-05-21,639,8.8,AI Innovations -AI00109,AI Consultant,215842,EUR,183466,EX,CT,France,S,France,0,"Deep Learning, TensorFlow, Spark, Python",Bachelor,12,Healthcare,2024-12-19,2025-01-28,2098,6.7,Machine Intelligence Group -AI00110,Data Scientist,79833,USD,79833,SE,PT,South Korea,S,South Korea,0,"Java, SQL, PyTorch, TensorFlow, AWS",PhD,6,Healthcare,2024-01-04,2024-01-18,1284,5.7,Predictive Systems -AI00111,Data Scientist,304859,USD,304859,EX,FT,Norway,L,Norway,100,"Linux, SQL, Mathematics",Bachelor,15,Media,2025-03-22,2025-05-05,2460,6,Advanced Robotics -AI00112,Research Scientist,112217,EUR,95384,SE,CT,Germany,S,Israel,0,"Spark, Scala, Azure",Associate,8,Technology,2025-03-07,2025-04-23,1679,10,Digital Transformation LLC -AI00113,Head of AI,45738,USD,45738,EN,FL,South Korea,M,South Korea,100,"TensorFlow, Hadoop, Spark",Associate,0,Manufacturing,2024-03-17,2024-04-05,1481,9.5,DeepTech Ventures -AI00114,Machine Learning Researcher,195309,EUR,166013,EX,PT,Germany,S,Germany,50,"SQL, Tableau, PyTorch, NLP",Bachelor,18,Consulting,2024-12-14,2025-02-23,1277,5.3,DeepTech Ventures -AI00115,Data Scientist,141439,USD,141439,SE,FL,United States,L,United States,50,"Kubernetes, GCP, Git, SQL",PhD,9,Retail,2024-06-24,2024-07-13,1021,6.3,Digital Transformation LLC -AI00116,AI Consultant,125836,USD,125836,MI,FT,Norway,L,Norway,100,"Statistics, Kubernetes, Spark, GCP",Master,2,Transportation,2024-12-27,2025-02-22,1650,10,Predictive Systems -AI00117,Machine Learning Researcher,58213,USD,58213,EN,FT,Israel,S,Thailand,50,"Azure, Linux, Kubernetes",PhD,0,Telecommunications,2025-04-13,2025-06-08,1087,5.5,Cloud AI Solutions -AI00118,ML Ops Engineer,82191,EUR,69862,MI,CT,Germany,M,Germany,0,"Spark, GCP, Hadoop",Bachelor,2,Media,2024-08-05,2024-10-16,1906,9.5,Quantum Computing Inc -AI00119,Machine Learning Researcher,207975,AUD,280766,EX,CT,Australia,S,Colombia,0,"SQL, Azure, Computer Vision",Master,13,Telecommunications,2025-02-21,2025-04-07,1475,9.9,Future Systems -AI00120,Computer Vision Engineer,115664,USD,115664,SE,PT,Ireland,M,Ireland,0,"TensorFlow, R, Data Visualization",Bachelor,7,Automotive,2024-03-27,2024-05-15,1449,7.8,Smart Analytics -AI00121,AI Software Engineer,109337,USD,109337,SE,PT,Ireland,M,Ireland,50,"Data Visualization, PyTorch, Python, Mathematics, Git",Associate,9,Government,2025-04-26,2025-05-13,901,8.1,Predictive Systems -AI00122,Data Analyst,115386,USD,115386,SE,PT,Finland,M,Finland,100,"MLOps, Statistics, Hadoop, SQL",Associate,7,Energy,2024-09-02,2024-11-03,2387,6.7,Smart Analytics -AI00123,Autonomous Systems Engineer,64431,GBP,48323,EN,FT,United Kingdom,L,United Kingdom,50,"Git, Deep Learning, Python, Statistics, TensorFlow",Bachelor,1,Automotive,2025-01-25,2025-02-25,825,9,DeepTech Ventures -AI00124,Data Engineer,108088,USD,108088,SE,FL,United States,S,United States,100,"Tableau, Python, Docker, Azure",Bachelor,9,Consulting,2024-10-07,2024-12-15,1769,8,Smart Analytics -AI00125,ML Ops Engineer,228314,GBP,171236,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Hadoop, SQL, Statistics, TensorFlow",Master,16,Telecommunications,2024-10-18,2024-12-04,1005,6.5,Cognitive Computing -AI00126,Data Scientist,153260,AUD,206901,SE,CT,Australia,L,Australia,0,"MLOps, Java, NLP",Master,9,Education,2025-04-02,2025-05-04,1768,9.7,DataVision Ltd -AI00127,Data Scientist,63667,USD,63667,MI,CT,Israel,S,Norway,100,"R, Data Visualization, SQL, NLP",PhD,4,Energy,2025-03-20,2025-05-12,1336,7.9,Algorithmic Solutions -AI00128,Research Scientist,31185,USD,31185,MI,FL,China,S,Colombia,100,"AWS, GCP, NLP, SQL, Statistics",Associate,3,Healthcare,2025-03-11,2025-04-07,1510,9.2,Neural Networks Co -AI00129,Machine Learning Engineer,132167,EUR,112342,SE,PT,Germany,M,Germany,50,"MLOps, Docker, Linux, Computer Vision",Bachelor,9,Education,2024-08-04,2024-10-12,1110,6.2,Quantum Computing Inc -AI00130,AI Research Scientist,223349,JPY,24568390,EX,FL,Japan,L,Japan,100,"PyTorch, Mathematics, TensorFlow",Bachelor,11,Gaming,2024-07-31,2024-09-27,1489,5.9,Smart Analytics -AI00131,AI Architect,26957,USD,26957,EN,CT,India,M,India,100,"Azure, Computer Vision, Statistics",Bachelor,1,Transportation,2025-03-23,2025-04-17,2335,9.5,DataVision Ltd -AI00132,AI Software Engineer,93564,USD,93564,MI,CT,Sweden,S,Sweden,0,"PyTorch, Docker, Data Visualization, Scala, Computer Vision",Associate,2,Transportation,2025-03-25,2025-04-13,515,9.7,Advanced Robotics -AI00133,Computer Vision Engineer,113846,EUR,96769,SE,PT,France,S,France,100,"SQL, Git, R, Hadoop, Docker",Associate,6,Energy,2024-09-02,2024-10-30,2447,7.8,DataVision Ltd -AI00134,AI Specialist,147580,EUR,125443,EX,FL,France,M,France,0,"Linux, Deep Learning, Hadoop, Kubernetes, Docker",PhD,17,Telecommunications,2024-11-13,2025-01-10,2416,5.9,Cloud AI Solutions -AI00135,Data Engineer,50514,CAD,63143,EN,PT,Canada,M,Philippines,100,"SQL, PyTorch, Tableau, NLP",PhD,1,Automotive,2024-08-04,2024-08-28,2384,9,Cognitive Computing -AI00136,AI Product Manager,94158,EUR,80034,MI,FL,Germany,M,Vietnam,100,"PyTorch, R, Scala",Master,2,Education,2024-09-01,2024-10-10,867,5.5,Future Systems -AI00137,Principal Data Scientist,161009,EUR,136858,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, AWS, GCP",Associate,19,Transportation,2024-02-17,2024-03-17,1247,7.1,Cognitive Computing -AI00138,Data Analyst,91911,USD,91911,EX,FT,India,L,India,100,"PyTorch, SQL, Azure, Docker",Associate,15,Technology,2024-06-15,2024-08-15,2149,5.9,Cloud AI Solutions -AI00139,AI Specialist,248071,EUR,210860,EX,FL,Germany,M,Czech Republic,50,"Kubernetes, R, GCP",Bachelor,15,Consulting,2025-04-13,2025-04-29,616,7.6,Future Systems -AI00140,Autonomous Systems Engineer,150204,EUR,127673,SE,PT,Germany,M,Germany,50,"Docker, Linux, Kubernetes, Data Visualization",Bachelor,9,Transportation,2025-03-18,2025-04-12,1478,6.3,Neural Networks Co -AI00141,AI Product Manager,181517,EUR,154289,SE,CT,Netherlands,L,Netherlands,50,"SQL, Kubernetes, NLP, MLOps",PhD,9,Government,2024-08-13,2024-09-05,981,8.9,TechCorp Inc -AI00142,Data Analyst,64573,EUR,54887,EN,PT,France,L,France,100,"Kubernetes, GCP, Mathematics, Python",Master,1,Government,2024-07-19,2024-09-30,1495,9.2,AI Innovations -AI00143,ML Ops Engineer,89332,USD,89332,MI,CT,United States,S,United States,100,"Python, TensorFlow, Deep Learning, Docker, PyTorch",Bachelor,4,Finance,2024-08-20,2024-10-23,2011,6,Predictive Systems -AI00144,Machine Learning Engineer,118239,USD,118239,SE,FL,Sweden,S,Indonesia,50,"AWS, Hadoop, PyTorch, Statistics, Azure",PhD,9,Energy,2024-08-03,2024-09-22,576,8.1,Future Systems -AI00145,AI Specialist,103715,JPY,11408650,MI,FT,Japan,S,Japan,50,"Python, Azure, Statistics",Bachelor,4,Automotive,2024-12-11,2025-01-20,2224,9.3,Neural Networks Co -AI00146,AI Consultant,151680,AUD,204768,EX,FL,Australia,S,Australia,100,"Computer Vision, AWS, Kubernetes",Associate,14,Manufacturing,2024-06-20,2024-07-31,2439,6.9,Cognitive Computing -AI00147,Data Analyst,142589,EUR,121201,SE,FT,Netherlands,L,Netherlands,0,"Docker, Tableau, Kubernetes, Data Visualization, GCP",Master,8,Government,2024-10-25,2024-11-11,2431,6,Predictive Systems -AI00148,Research Scientist,63062,USD,63062,EN,PT,Sweden,L,Sweden,50,"PyTorch, R, Mathematics, Kubernetes",Associate,1,Real Estate,2024-09-05,2024-10-18,1558,6.7,Smart Analytics -AI00149,Data Engineer,80691,JPY,8876010,EN,CT,Japan,L,Japan,100,"Deep Learning, Computer Vision, PyTorch, Statistics, Spark",Master,1,Retail,2024-12-21,2025-01-04,624,8.1,DataVision Ltd -AI00150,Data Analyst,171580,JPY,18873800,SE,PT,Japan,L,Kenya,100,"SQL, Spark, MLOps",PhD,7,Manufacturing,2024-10-14,2024-12-09,1931,6.7,Predictive Systems -AI00151,Autonomous Systems Engineer,58331,USD,58331,SE,PT,China,M,Chile,0,"Hadoop, Java, NLP, Mathematics, Python",Master,5,Transportation,2024-11-23,2025-01-24,2002,6.1,Cognitive Computing -AI00152,Head of AI,85620,CAD,107025,MI,FT,Canada,L,Canada,100,"TensorFlow, GCP, MLOps, NLP",Associate,4,Healthcare,2025-01-22,2025-02-23,848,5.8,Quantum Computing Inc -AI00153,AI Consultant,220871,EUR,187740,EX,FT,Austria,M,Austria,0,"Linux, Tableau, Spark, Scala",Associate,14,Automotive,2024-06-28,2024-07-31,821,5.2,DeepTech Ventures -AI00154,ML Ops Engineer,93007,EUR,79056,MI,CT,France,M,France,50,"Docker, SQL, MLOps, GCP, Hadoop",Bachelor,4,Energy,2024-06-05,2024-07-23,1595,6.4,Cognitive Computing -AI00155,AI Specialist,191783,SGD,249318,EX,FT,Singapore,S,Singapore,100,"Java, GCP, PyTorch",PhD,14,Healthcare,2024-10-04,2024-10-27,2352,5.6,Advanced Robotics -AI00156,Head of AI,83683,USD,83683,MI,FL,Israel,S,Czech Republic,50,"Mathematics, Computer Vision, MLOps, Git, Deep Learning",Bachelor,3,Education,2024-05-15,2024-06-07,818,5.3,Smart Analytics -AI00157,Research Scientist,107869,USD,107869,SE,FL,Ireland,S,Ireland,50,"SQL, Linux, GCP",Associate,8,Finance,2024-02-17,2024-04-01,2148,7.3,Predictive Systems -AI00158,Autonomous Systems Engineer,73528,USD,73528,MI,PT,Sweden,S,Poland,0,"NLP, R, Git, MLOps",Associate,2,Finance,2024-03-01,2024-05-05,557,8,Algorithmic Solutions -AI00159,NLP Engineer,47642,USD,47642,MI,FL,China,L,Sweden,100,"Python, TensorFlow, NLP",PhD,3,Telecommunications,2024-11-22,2025-01-13,2171,8,DeepTech Ventures -AI00160,AI Software Engineer,179937,EUR,152946,SE,PT,Netherlands,L,Netherlands,50,"Python, TensorFlow, NLP, Kubernetes",Associate,6,Real Estate,2024-06-01,2024-07-29,774,8.1,Machine Intelligence Group -AI00161,Data Engineer,157066,CHF,141359,MI,PT,Switzerland,L,Sweden,0,"GCP, Docker, NLP, Data Visualization",PhD,2,Transportation,2024-05-01,2024-05-26,887,9,Neural Networks Co -AI00162,Data Scientist,57299,USD,57299,EN,CT,Israel,M,Israel,0,"PyTorch, Spark, TensorFlow",Bachelor,1,Retail,2024-01-17,2024-02-19,794,7.8,DataVision Ltd -AI00163,Data Engineer,176844,CAD,221055,EX,FL,Canada,L,France,50,"Linux, Scala, Tableau",PhD,10,Telecommunications,2024-06-08,2024-07-19,577,5.4,Digital Transformation LLC -AI00164,AI Research Scientist,64892,CAD,81115,EN,CT,Canada,M,Canada,50,"Kubernetes, Scala, Azure, Computer Vision",Associate,1,Transportation,2024-11-05,2025-01-03,1645,5.7,Algorithmic Solutions -AI00165,AI Specialist,63024,EUR,53570,EN,CT,Austria,L,Austria,0,"Git, Statistics, Data Visualization",Bachelor,1,Gaming,2024-04-04,2024-05-05,1745,9.2,Algorithmic Solutions -AI00166,Principal Data Scientist,136695,CHF,123026,MI,FL,Switzerland,S,Switzerland,50,"Linux, GCP, Tableau, Java",Bachelor,2,Gaming,2024-12-10,2024-12-27,1424,5.9,Algorithmic Solutions -AI00167,Data Scientist,69744,USD,69744,EN,PT,South Korea,L,South Korea,50,"Python, Docker, Tableau",Associate,1,Telecommunications,2024-12-30,2025-01-22,1077,8.4,Autonomous Tech -AI00168,AI Specialist,135137,EUR,114866,EX,FL,Austria,M,Austria,0,"Kubernetes, GCP, Data Visualization",PhD,18,Finance,2024-04-06,2024-05-17,1590,5.4,TechCorp Inc -AI00169,Computer Vision Engineer,143037,USD,143037,EX,FL,Sweden,S,Sweden,0,"Data Visualization, Linux, Azure, Java",PhD,13,Manufacturing,2024-05-24,2024-07-07,775,9.5,Autonomous Tech -AI00170,Machine Learning Engineer,113068,GBP,84801,SE,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, Java, Data Visualization, Kubernetes",Master,9,Gaming,2024-06-10,2024-07-05,1805,6.6,Machine Intelligence Group -AI00171,AI Software Engineer,113917,GBP,85438,SE,PT,United Kingdom,S,Russia,0,"SQL, Kubernetes, GCP",Master,9,Government,2024-10-07,2024-10-26,1720,7.3,Future Systems -AI00172,Head of AI,80311,USD,80311,EX,PT,India,M,India,50,"Git, GCP, Computer Vision, Kubernetes, Docker",Bachelor,13,Finance,2025-01-17,2025-03-11,1052,5,Smart Analytics -AI00173,Autonomous Systems Engineer,160261,EUR,136222,SE,CT,Germany,L,Germany,50,"AWS, Linux, Scala, GCP, Python",Associate,6,Education,2024-02-26,2024-04-16,748,9.9,Smart Analytics -AI00174,Research Scientist,152241,CHF,137017,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, SQL, Git, PyTorch, Computer Vision",Bachelor,8,Gaming,2024-04-05,2024-06-05,1807,5.9,AI Innovations -AI00175,Research Scientist,74172,USD,74172,MI,CT,Israel,M,Israel,100,"Statistics, Kubernetes, GCP, Spark",PhD,2,Government,2024-01-24,2024-03-22,1780,7.5,Algorithmic Solutions -AI00176,Computer Vision Engineer,105632,USD,105632,MI,FL,Finland,L,Norway,100,"AWS, R, MLOps",Bachelor,3,Government,2025-01-03,2025-01-30,2376,9.4,Machine Intelligence Group -AI00177,Principal Data Scientist,89515,SGD,116370,MI,CT,Singapore,L,South Africa,100,"PyTorch, NLP, Computer Vision",Associate,4,Gaming,2025-01-17,2025-03-29,2328,7.4,DataVision Ltd -AI00178,AI Software Engineer,102319,USD,102319,MI,FL,Denmark,M,Colombia,50,"Deep Learning, Mathematics, Data Visualization, NLP",Associate,4,Energy,2024-07-14,2024-08-01,1939,6.2,Cognitive Computing -AI00179,AI Software Engineer,110536,USD,110536,MI,CT,Denmark,M,France,50,"SQL, Spark, Mathematics, Linux, TensorFlow",Associate,2,Real Estate,2024-05-01,2024-06-22,1559,5.4,DeepTech Ventures -AI00180,NLP Engineer,176372,USD,176372,SE,FL,Denmark,S,Denmark,0,"SQL, AWS, Computer Vision",Bachelor,5,Technology,2024-05-02,2024-07-05,729,8,AI Innovations -AI00181,AI Software Engineer,58111,EUR,49394,EN,FT,Austria,S,Austria,100,"Docker, Linux, Java",Bachelor,0,Finance,2024-01-20,2024-02-17,889,5.6,Digital Transformation LLC -AI00182,AI Product Manager,39802,USD,39802,SE,PT,India,M,Spain,100,"Git, Hadoop, Linux",Associate,8,Consulting,2024-02-05,2024-03-06,2046,8.3,Digital Transformation LLC -AI00183,Head of AI,147385,EUR,125277,SE,FL,France,L,Denmark,50,"Java, Statistics, AWS, Scala",Master,9,Consulting,2024-03-08,2024-03-25,1576,8.6,Cloud AI Solutions -AI00184,Research Scientist,118122,USD,118122,EN,FT,Denmark,L,Denmark,0,"Git, Scala, MLOps, Docker, Hadoop",Associate,0,Automotive,2024-07-20,2024-09-06,2018,9.3,Cloud AI Solutions -AI00185,AI Architect,75225,AUD,101554,EN,FT,Australia,L,Russia,100,"Deep Learning, MLOps, Linux",Master,0,Real Estate,2024-10-10,2024-11-26,2399,7.5,Machine Intelligence Group -AI00186,AI Research Scientist,48325,CAD,60406,EN,FL,Canada,M,Canada,100,"Spark, TensorFlow, Hadoop",Associate,0,Manufacturing,2025-03-26,2025-06-07,1523,6.2,Algorithmic Solutions -AI00187,Data Scientist,64973,USD,64973,EN,CT,Sweden,L,Sweden,0,"Git, Spark, NLP, MLOps",Master,0,Energy,2024-03-08,2024-04-24,1016,6.4,AI Innovations -AI00188,Computer Vision Engineer,78182,AUD,105546,MI,PT,Australia,M,Australia,50,"Hadoop, Docker, Computer Vision, Linux",Associate,4,Retail,2024-03-22,2024-05-22,1582,7.9,Cloud AI Solutions -AI00189,Data Analyst,357875,USD,357875,EX,PT,Norway,L,Norway,50,"Git, AWS, Linux, Tableau, Java",Associate,10,Retail,2024-01-19,2024-02-27,1044,8,Advanced Robotics -AI00190,AI Software Engineer,61953,USD,61953,SE,FT,India,L,India,50,"AWS, NLP, Tableau, SQL, PyTorch",Associate,8,Finance,2024-08-20,2024-10-14,1469,6.3,Advanced Robotics -AI00191,AI Product Manager,236982,USD,236982,EX,FL,Denmark,L,Poland,0,"AWS, Kubernetes, Tableau",Master,10,Gaming,2025-03-20,2025-04-03,597,5.1,Smart Analytics -AI00192,Principal Data Scientist,90203,EUR,76673,MI,PT,Austria,S,Austria,50,"Python, R, MLOps, GCP",PhD,3,Finance,2025-03-08,2025-05-12,1774,7.5,Autonomous Tech -AI00193,NLP Engineer,109984,JPY,12098240,SE,CT,Japan,S,Switzerland,0,"Data Visualization, Linux, SQL",Associate,7,Energy,2024-08-07,2024-08-31,1535,8,DeepTech Ventures -AI00194,AI Specialist,146371,CAD,182964,EX,PT,Canada,S,Ireland,100,"MLOps, Python, Scala, Docker",PhD,14,Healthcare,2024-11-15,2024-12-17,2313,5.4,Machine Intelligence Group -AI00195,Deep Learning Engineer,268088,EUR,227875,EX,PT,Netherlands,M,Netherlands,0,"NLP, AWS, Tableau, Scala, Computer Vision",Associate,10,Finance,2024-11-04,2024-12-21,1385,9.5,Predictive Systems -AI00196,Data Engineer,97647,GBP,73235,MI,CT,United Kingdom,S,Norway,50,"Java, Data Visualization, Scala, R",PhD,4,Government,2024-02-27,2024-04-08,1305,6.2,DeepTech Ventures -AI00197,Principal Data Scientist,221711,EUR,188454,EX,FT,Germany,S,Turkey,0,"TensorFlow, Kubernetes, NLP, PyTorch",Bachelor,17,Gaming,2025-01-14,2025-03-16,1652,8.9,Machine Intelligence Group -AI00198,Data Scientist,78716,EUR,66909,EN,PT,Germany,L,Germany,100,"Azure, Statistics, Kubernetes, Java",Bachelor,0,Automotive,2024-07-12,2024-08-13,2401,8.2,DataVision Ltd -AI00199,Principal Data Scientist,169717,CHF,152745,SE,CT,Switzerland,S,Switzerland,50,"Spark, Scala, PyTorch, Statistics",Master,5,Education,2024-03-07,2024-04-03,1003,9.5,DeepTech Ventures -AI00200,Data Analyst,92798,EUR,78878,MI,CT,Austria,L,Austria,50,"Linux, Kubernetes, SQL, Git",PhD,4,Consulting,2024-09-07,2024-11-12,1685,6.4,Neural Networks Co -AI00201,AI Product Manager,37177,USD,37177,MI,FL,China,S,China,0,"R, AWS, Hadoop, Spark",Associate,2,Automotive,2024-06-13,2024-08-25,869,6.1,Digital Transformation LLC -AI00202,Data Analyst,85505,USD,85505,MI,CT,Israel,S,Israel,50,"Java, Linux, R",Bachelor,4,Gaming,2025-01-21,2025-03-28,1983,5.1,Future Systems -AI00203,Robotics Engineer,113625,EUR,96581,MI,FT,France,L,France,100,"R, Python, Data Visualization, Scala",Associate,3,Automotive,2024-12-13,2025-01-02,2036,5.8,Advanced Robotics -AI00204,ML Ops Engineer,121846,AUD,164492,SE,PT,Australia,L,Australia,50,"NLP, AWS, Docker, Python",Master,6,Retail,2025-02-06,2025-04-20,2213,7.4,DeepTech Ventures -AI00205,Robotics Engineer,115136,JPY,12664960,MI,FT,Japan,M,Japan,50,"Scala, Python, Mathematics",Bachelor,3,Finance,2024-08-09,2024-09-03,1542,6.3,Neural Networks Co -AI00206,Data Scientist,265646,EUR,225799,EX,FT,France,L,Canada,0,"PyTorch, Computer Vision, SQL, AWS",Bachelor,16,Healthcare,2024-12-28,2025-01-11,1473,9.4,Predictive Systems -AI00207,AI Consultant,92726,CHF,83453,EN,FT,Switzerland,L,Switzerland,0,"Kubernetes, R, GCP, MLOps, Mathematics",Bachelor,0,Telecommunications,2024-09-22,2024-11-17,2013,9.8,AI Innovations -AI00208,Research Scientist,50607,USD,50607,EN,FL,Israel,S,Israel,100,"Azure, Tableau, Kubernetes, Deep Learning, Computer Vision",Bachelor,0,Telecommunications,2024-06-10,2024-08-05,1801,8.6,Autonomous Tech -AI00209,Machine Learning Researcher,219875,USD,219875,EX,PT,Sweden,L,Sweden,50,"NLP, Kubernetes, Tableau, Linux, R",Master,15,Automotive,2024-09-12,2024-11-15,1609,8.4,TechCorp Inc -AI00210,Robotics Engineer,93342,USD,93342,EX,CT,China,M,China,100,"Spark, Python, Azure",Master,11,Transportation,2025-02-15,2025-04-02,1345,7.2,AI Innovations -AI00211,Data Scientist,99132,EUR,84262,MI,FL,Netherlands,L,Netherlands,50,"Python, Linux, R",PhD,3,Government,2024-05-17,2024-06-15,2121,9.7,Advanced Robotics -AI00212,Data Analyst,148775,SGD,193408,SE,CT,Singapore,L,France,0,"Java, PyTorch, Scala",Associate,5,Real Estate,2024-01-07,2024-01-26,1222,6.3,Smart Analytics -AI00213,Data Scientist,63090,USD,63090,EN,CT,Denmark,S,Denmark,100,"AWS, MLOps, Python, Tableau, Azure",Master,0,Retail,2024-01-25,2024-03-18,1913,5.4,Neural Networks Co -AI00214,Robotics Engineer,39782,USD,39782,EN,CT,China,L,China,0,"Data Visualization, NLP, Python, R, Computer Vision",Bachelor,1,Transportation,2024-10-30,2025-01-04,2183,8.9,Quantum Computing Inc -AI00215,AI Architect,240915,CAD,301144,EX,PT,Canada,L,Canada,0,"TensorFlow, Java, MLOps",Master,14,Energy,2024-02-23,2024-04-17,1222,7.3,Advanced Robotics -AI00216,Robotics Engineer,69061,SGD,89779,MI,FL,Singapore,S,France,100,"Data Visualization, Linux, Tableau, Mathematics, Kubernetes",Master,4,Real Estate,2024-12-17,2025-02-01,1319,6.9,Future Systems -AI00217,Machine Learning Engineer,146403,EUR,124443,SE,PT,Netherlands,L,Netherlands,100,"Python, Scala, Java, Computer Vision, Azure",PhD,5,Gaming,2024-01-04,2024-02-07,1031,8.4,Algorithmic Solutions -AI00218,AI Consultant,56884,USD,56884,EN,CT,Finland,M,Finland,100,"Python, Mathematics, Tableau, Kubernetes",Bachelor,1,Government,2024-08-08,2024-08-24,532,9.1,Autonomous Tech -AI00219,AI Consultant,172277,CHF,155049,SE,PT,Switzerland,L,Switzerland,0,"Hadoop, Spark, Kubernetes, PyTorch, Azure",Bachelor,9,Technology,2024-08-09,2024-08-26,1725,9.7,Quantum Computing Inc -AI00220,Data Engineer,254054,EUR,215946,EX,CT,Austria,L,Austria,100,"R, Tableau, Data Visualization, Spark",Bachelor,17,Education,2024-09-26,2024-11-08,1518,9.8,Digital Transformation LLC -AI00221,Machine Learning Researcher,97442,EUR,82826,SE,FT,Germany,S,Germany,50,"Computer Vision, Linux, TensorFlow",PhD,5,Retail,2024-07-07,2024-08-01,1164,5.5,DataVision Ltd -AI00222,NLP Engineer,84037,USD,84037,EX,PT,China,S,China,50,"Computer Vision, NLP, GCP",Bachelor,19,Retail,2024-01-24,2024-02-12,2292,6,Autonomous Tech -AI00223,Principal Data Scientist,104614,EUR,88922,MI,CT,Netherlands,S,Netherlands,50,"SQL, Python, Linux, Computer Vision, Hadoop",Bachelor,4,Telecommunications,2024-10-10,2024-12-09,1895,7.9,Digital Transformation LLC -AI00224,Data Scientist,103566,USD,103566,SE,CT,Finland,S,Finland,100,"Git, Linux, Java, Statistics",Bachelor,7,Manufacturing,2024-01-09,2024-03-04,1777,8,Predictive Systems -AI00225,Autonomous Systems Engineer,69417,USD,69417,EN,CT,Ireland,L,Canada,50,"Data Visualization, Java, Docker, Kubernetes",Master,0,Energy,2024-04-22,2024-05-12,1887,9.4,Cloud AI Solutions -AI00226,AI Product Manager,27748,USD,27748,EN,FT,China,S,Israel,100,"NLP, Java, TensorFlow",Master,0,Automotive,2024-12-09,2025-02-03,1984,5.8,Autonomous Tech -AI00227,NLP Engineer,245370,USD,245370,EX,FL,Sweden,M,Sweden,100,"Tableau, Java, TensorFlow",Master,14,Real Estate,2024-03-17,2024-04-03,2030,8.4,Cognitive Computing -AI00228,AI Software Engineer,86794,JPY,9547340,MI,FL,Japan,S,Japan,50,"Scala, SQL, Hadoop, Statistics, GCP",Bachelor,4,Finance,2025-02-25,2025-04-25,1875,8.2,Cloud AI Solutions -AI00229,Computer Vision Engineer,58554,USD,58554,EN,FT,Ireland,S,Ireland,0,"Linux, Java, R, SQL, Mathematics",Master,1,Healthcare,2024-11-20,2024-12-22,2448,9.3,Cognitive Computing -AI00230,AI Specialist,152077,GBP,114058,SE,FT,United Kingdom,L,Canada,50,"Kubernetes, Git, Statistics",PhD,6,Automotive,2024-01-30,2024-03-20,2336,9.6,Cognitive Computing -AI00231,Data Scientist,152349,JPY,16758390,EX,FT,Japan,S,Japan,50,"MLOps, Scala, Java",Associate,10,Healthcare,2024-08-04,2024-09-30,1703,5.5,Quantum Computing Inc -AI00232,Deep Learning Engineer,155935,USD,155935,EX,FL,Israel,S,Ghana,50,"Python, Hadoop, Git",Associate,17,Retail,2025-03-25,2025-04-27,661,8.8,Predictive Systems -AI00233,Deep Learning Engineer,299354,CHF,269419,EX,FL,Switzerland,S,Switzerland,100,"MLOps, Scala, Docker",Bachelor,14,Retail,2024-06-16,2024-07-31,572,6.8,Advanced Robotics -AI00234,Autonomous Systems Engineer,112130,JPY,12334300,SE,FT,Japan,M,Japan,100,"SQL, Azure, Deep Learning",Associate,5,Energy,2024-03-14,2024-05-14,2021,9.4,Cognitive Computing -AI00235,AI Product Manager,299005,GBP,224254,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, MLOps, Statistics, Computer Vision",Master,16,Transportation,2024-06-17,2024-08-17,687,9.5,Cloud AI Solutions -AI00236,AI Product Manager,57697,JPY,6346670,EN,FL,Japan,M,Japan,100,"Python, TensorFlow, Deep Learning, MLOps",PhD,1,Energy,2024-03-23,2024-05-01,1370,9.7,DataVision Ltd -AI00237,Deep Learning Engineer,140199,SGD,182259,EX,FT,Singapore,S,Singapore,0,"Docker, Data Visualization, Python",Associate,18,Manufacturing,2025-03-26,2025-04-22,568,6.7,Predictive Systems -AI00238,Computer Vision Engineer,107028,USD,107028,EX,CT,China,M,Ghana,50,"Git, Linux, Statistics, Mathematics",PhD,11,Education,2024-10-29,2025-01-01,1172,5.8,Future Systems -AI00239,Data Analyst,48978,USD,48978,EN,FL,South Korea,M,Switzerland,50,"Computer Vision, Kubernetes, Git",Associate,1,Gaming,2024-02-21,2024-04-21,647,7.3,Future Systems -AI00240,Principal Data Scientist,101366,EUR,86161,MI,FL,France,M,France,100,"Python, Data Visualization, Linux, Azure",Master,3,Manufacturing,2025-01-04,2025-01-20,1292,6.7,DataVision Ltd -AI00241,AI Research Scientist,79125,EUR,67256,MI,CT,Netherlands,S,Netherlands,100,"Computer Vision, GCP, NLP, Statistics",PhD,4,Media,2024-03-05,2024-05-14,510,7.8,Smart Analytics -AI00242,Machine Learning Engineer,51110,USD,51110,SE,FL,China,S,China,50,"TensorFlow, Mathematics, Deep Learning, Computer Vision, R",Master,6,Automotive,2024-03-22,2024-05-06,1861,9.8,Cloud AI Solutions -AI00243,Data Scientist,96374,EUR,81918,MI,PT,Germany,S,Germany,0,"Deep Learning, SQL, Git, PyTorch",Associate,3,Retail,2024-05-08,2024-06-08,744,8.8,TechCorp Inc -AI00244,Autonomous Systems Engineer,92286,SGD,119972,EN,PT,Singapore,L,Singapore,100,"AWS, Java, Python, Mathematics",PhD,0,Energy,2025-02-04,2025-04-05,830,8.3,Advanced Robotics -AI00245,Data Scientist,102456,USD,102456,SE,FL,Sweden,S,Sweden,100,"PyTorch, Git, R, Azure",PhD,7,Education,2024-08-31,2024-11-12,552,6.9,Algorithmic Solutions -AI00246,ML Ops Engineer,138420,USD,138420,EX,CT,Sweden,M,Sweden,50,"PyTorch, Docker, Data Visualization, GCP, TensorFlow",PhD,17,Transportation,2024-02-13,2024-03-21,1582,5.3,DataVision Ltd -AI00247,AI Software Engineer,203654,CAD,254568,EX,PT,Canada,L,Canada,100,"SQL, Kubernetes, Computer Vision, GCP",PhD,12,Retail,2024-01-19,2024-03-23,1049,8.1,Advanced Robotics -AI00248,Robotics Engineer,121706,EUR,103450,SE,FT,Austria,L,Austria,50,"Hadoop, Data Visualization, Python, TensorFlow, Mathematics",PhD,8,Real Estate,2024-12-31,2025-02-23,2066,9.1,Neural Networks Co -AI00249,AI Software Engineer,112939,SGD,146821,SE,CT,Singapore,S,Netherlands,0,"R, Azure, Computer Vision, Deep Learning",PhD,9,Consulting,2024-10-30,2024-11-21,2008,10,Smart Analytics -AI00250,AI Software Engineer,223145,EUR,189673,EX,CT,Germany,L,Brazil,50,"Kubernetes, Scala, MLOps, Statistics",Bachelor,19,Energy,2024-01-02,2024-01-26,2356,7.1,AI Innovations -AI00251,Data Engineer,198959,AUD,268595,EX,FT,Australia,M,Australia,0,"Spark, Python, Deep Learning, TensorFlow, Mathematics",Master,11,Telecommunications,2025-03-11,2025-04-04,1821,7.1,Neural Networks Co -AI00252,Machine Learning Engineer,249841,USD,249841,EX,CT,United States,M,United States,100,"Scala, Linux, Java, Data Visualization",Associate,14,Healthcare,2024-01-08,2024-01-29,2130,7,Machine Intelligence Group -AI00253,AI Architect,81300,CHF,73170,EN,CT,Switzerland,S,Switzerland,0,"SQL, Python, Scala",Master,0,Energy,2024-04-26,2024-06-02,1225,9,AI Innovations -AI00254,Machine Learning Engineer,89201,USD,89201,EX,CT,China,L,Colombia,0,"Kubernetes, Mathematics, Data Visualization, SQL",Master,16,Gaming,2025-02-15,2025-03-15,1146,5.7,TechCorp Inc -AI00255,Robotics Engineer,123827,CHF,111444,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, GCP, AWS, SQL, NLP",Master,4,Telecommunications,2025-01-14,2025-03-11,543,8.3,Quantum Computing Inc -AI00256,AI Product Manager,321014,USD,321014,EX,FL,Denmark,M,Denmark,100,"Hadoop, Scala, MLOps",Master,16,Finance,2024-04-02,2024-06-13,1990,5.3,Neural Networks Co -AI00257,ML Ops Engineer,195690,USD,195690,EX,PT,Ireland,L,Ireland,100,"Azure, Kubernetes, PyTorch",Associate,11,Education,2024-01-15,2024-03-12,1481,6.2,Neural Networks Co -AI00258,AI Software Engineer,88109,SGD,114542,MI,FL,Singapore,M,South Korea,100,"SQL, Hadoop, Tableau, Spark",Bachelor,2,Government,2025-03-24,2025-06-01,2164,9.9,AI Innovations -AI00259,Deep Learning Engineer,93310,EUR,79314,SE,PT,Germany,S,Germany,0,"TensorFlow, Statistics, Mathematics",Associate,8,Retail,2024-08-24,2024-10-22,1732,5.5,Smart Analytics -AI00260,Deep Learning Engineer,180162,EUR,153138,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, Java, Spark, NLP",Associate,12,Technology,2024-03-06,2024-04-29,2049,9.7,Autonomous Tech -AI00261,Deep Learning Engineer,324764,CHF,292288,EX,PT,Switzerland,M,Switzerland,0,"TensorFlow, Kubernetes, Docker, Tableau, Scala",Associate,14,Manufacturing,2024-08-05,2024-10-03,1915,8.2,Quantum Computing Inc -AI00262,AI Consultant,57105,SGD,74237,EN,FT,Singapore,M,India,0,"Scala, Data Visualization, Python, GCP",Associate,1,Telecommunications,2024-05-26,2024-08-01,2453,6.9,DataVision Ltd -AI00263,Research Scientist,131121,USD,131121,EX,PT,Finland,M,South Africa,100,"Data Visualization, R, Kubernetes",Bachelor,11,Education,2024-10-02,2024-12-04,1707,7.3,Digital Transformation LLC -AI00264,NLP Engineer,87993,USD,87993,SE,FL,Israel,S,Netherlands,50,"MLOps, Deep Learning, Azure, Kubernetes",Associate,6,Real Estate,2024-11-10,2025-01-04,1598,9.4,Cognitive Computing -AI00265,Data Analyst,77654,EUR,66006,EN,CT,Austria,L,Austria,50,"PyTorch, Hadoop, Tableau, Docker",Associate,1,Retail,2024-10-11,2024-12-03,1681,7.7,Neural Networks Co -AI00266,Machine Learning Engineer,47769,AUD,64488,EN,PT,Australia,S,Australia,50,"Java, Python, Data Visualization, Docker",Master,1,Transportation,2024-02-24,2024-04-01,2173,5.2,Neural Networks Co -AI00267,NLP Engineer,112750,GBP,84563,SE,PT,United Kingdom,S,United Kingdom,100,"Git, Statistics, Spark",Master,8,Real Estate,2024-04-14,2024-05-15,529,5.5,Predictive Systems -AI00268,AI Architect,63413,USD,63413,EN,PT,Denmark,S,Denmark,0,"Tableau, Hadoop, Statistics, MLOps",Associate,0,Gaming,2024-06-11,2024-08-09,2014,7.5,DataVision Ltd -AI00269,Robotics Engineer,96518,EUR,82040,SE,FT,Austria,S,Norway,0,"GCP, Deep Learning, Java, Statistics, Spark",Bachelor,5,Automotive,2024-02-20,2024-04-23,702,8.4,TechCorp Inc -AI00270,AI Research Scientist,136768,USD,136768,MI,PT,Norway,M,Norway,50,"Python, Java, SQL",Bachelor,4,Healthcare,2025-03-08,2025-04-01,2160,9.5,Smart Analytics -AI00271,Research Scientist,143660,CAD,179575,SE,FL,Canada,L,Canada,100,"Statistics, Java, Data Visualization, Azure",Master,8,Education,2024-01-22,2024-03-07,1728,6.7,Algorithmic Solutions -AI00272,Data Engineer,122612,SGD,159396,SE,FT,Singapore,S,Singapore,50,"GCP, Azure, Tableau, Computer Vision, Scala",Associate,9,Media,2024-10-26,2024-11-12,1794,5.8,TechCorp Inc -AI00273,Principal Data Scientist,224629,AUD,303249,EX,FL,Australia,S,Australia,100,"R, SQL, Kubernetes, Statistics, Linux",Master,15,Healthcare,2024-07-14,2024-07-31,2418,9.6,Cognitive Computing -AI00274,Computer Vision Engineer,110517,EUR,93939,SE,FT,France,L,France,50,"Python, TensorFlow, Hadoop, R",PhD,7,Manufacturing,2024-10-17,2024-11-27,2208,8.2,Advanced Robotics -AI00275,Robotics Engineer,78533,SGD,102093,EN,CT,Singapore,M,Singapore,100,"Deep Learning, Spark, Git",Bachelor,0,Government,2024-10-22,2024-12-24,1972,5.7,Future Systems -AI00276,Head of AI,282152,CHF,253937,EX,CT,Switzerland,S,United Kingdom,50,"Spark, Kubernetes, SQL",PhD,15,Energy,2024-03-23,2024-06-03,678,7,DeepTech Ventures -AI00277,Data Scientist,240352,CHF,216317,EX,CT,Switzerland,M,Switzerland,50,"TensorFlow, Spark, Computer Vision",PhD,18,Automotive,2024-06-24,2024-08-02,886,6.8,Cognitive Computing -AI00278,Computer Vision Engineer,87353,CHF,78618,EN,FL,Switzerland,M,Switzerland,50,"Java, Git, AWS",Associate,0,Technology,2025-03-17,2025-04-01,2072,7.5,DataVision Ltd -AI00279,Research Scientist,201368,EUR,171163,EX,FL,Austria,M,Austria,100,"Git, PyTorch, NLP",Associate,10,Transportation,2024-02-16,2024-03-15,2032,6.4,Cognitive Computing -AI00280,AI Consultant,102371,USD,102371,MI,FT,Sweden,M,Sweden,50,"Scala, Java, Linux, AWS",Associate,3,Telecommunications,2024-12-29,2025-02-22,2442,6.5,Cloud AI Solutions -AI00281,Machine Learning Engineer,160729,USD,160729,MI,FT,Denmark,L,Denmark,50,"Python, TensorFlow, Kubernetes, Mathematics, MLOps",PhD,3,Government,2024-03-22,2024-04-12,660,7.8,Cognitive Computing -AI00282,Data Analyst,127341,USD,127341,SE,CT,Ireland,L,Finland,0,"Python, Linux, TensorFlow, Java",Associate,8,Manufacturing,2025-01-07,2025-01-28,1241,6.4,Cognitive Computing -AI00283,AI Product Manager,132125,EUR,112306,SE,FT,Netherlands,L,Netherlands,50,"Deep Learning, Computer Vision, Tableau",Associate,6,Manufacturing,2024-06-13,2024-08-11,1042,7,Advanced Robotics -AI00284,Data Scientist,106892,CAD,133615,MI,PT,Canada,L,Canada,100,"MLOps, Python, Computer Vision, AWS",PhD,2,Gaming,2025-01-18,2025-03-19,2323,5.5,Digital Transformation LLC -AI00285,Machine Learning Researcher,101740,EUR,86479,MI,CT,Germany,L,Germany,100,"Scala, Python, Tableau",Master,3,Finance,2024-08-22,2024-09-18,1429,8.8,DeepTech Ventures -AI00286,Machine Learning Researcher,48965,USD,48965,MI,PT,China,M,China,0,"Python, TensorFlow, Spark, GCP",Bachelor,2,Automotive,2024-11-01,2024-12-26,1541,5.9,Future Systems -AI00287,Autonomous Systems Engineer,53173,USD,53173,EN,FL,Sweden,S,Sweden,50,"TensorFlow, Kubernetes, Python, Data Visualization, GCP",Master,0,Telecommunications,2024-02-09,2024-04-20,1299,8.3,Machine Intelligence Group -AI00288,Computer Vision Engineer,201645,EUR,171398,EX,PT,Netherlands,S,Netherlands,100,"Scala, Kubernetes, Data Visualization",Associate,17,Real Estate,2024-12-11,2025-01-11,1871,9.2,DataVision Ltd -AI00289,Robotics Engineer,47718,USD,47718,MI,FT,China,L,China,100,"R, Kubernetes, AWS, SQL, TensorFlow",Master,3,Retail,2025-01-03,2025-02-09,649,6.2,Neural Networks Co -AI00290,AI Architect,358613,USD,358613,EX,FL,Norway,L,Norway,0,"AWS, Java, Statistics",PhD,16,Telecommunications,2024-08-06,2024-09-17,1555,9.6,Autonomous Tech -AI00291,AI Product Manager,96280,USD,96280,EN,FL,United States,L,United States,50,"Spark, MLOps, SQL, PyTorch, Computer Vision",Bachelor,0,Technology,2024-10-13,2024-12-15,2353,6.2,Digital Transformation LLC -AI00292,ML Ops Engineer,87032,USD,87032,SE,PT,South Korea,S,Netherlands,50,"PyTorch, Linux, Deep Learning",Master,7,Manufacturing,2024-11-13,2025-01-02,1397,5.5,Algorithmic Solutions -AI00293,AI Architect,112059,JPY,12326490,SE,FT,Japan,S,Japan,50,"Docker, Python, Kubernetes, GCP, TensorFlow",Bachelor,9,Education,2024-06-21,2024-08-23,1799,7.3,Machine Intelligence Group -AI00294,AI Specialist,115102,EUR,97837,SE,FT,Austria,L,Austria,100,"Python, Linux, Kubernetes, Hadoop",PhD,7,Automotive,2024-05-10,2024-07-19,2334,9.2,DeepTech Ventures -AI00295,AI Specialist,271779,USD,271779,EX,CT,Ireland,L,Ireland,50,"Computer Vision, Azure, Data Visualization, NLP",Master,11,Automotive,2025-02-06,2025-03-23,1247,9,Cloud AI Solutions -AI00296,AI Research Scientist,66364,CAD,82955,MI,PT,Canada,S,Colombia,50,"Python, SQL, NLP",Bachelor,3,Gaming,2024-08-18,2024-09-01,1891,6.6,AI Innovations -AI00297,Deep Learning Engineer,131466,USD,131466,MI,PT,Norway,L,Norway,50,"R, AWS, Hadoop, NLP, Spark",PhD,2,Automotive,2024-01-02,2024-01-25,1013,7.9,TechCorp Inc -AI00298,Head of AI,42235,USD,42235,EN,FT,South Korea,S,Ghana,100,"Python, Data Visualization, Kubernetes",PhD,1,Government,2024-04-19,2024-06-27,2078,6.4,DeepTech Ventures -AI00299,Deep Learning Engineer,55844,EUR,47467,EN,FL,Netherlands,M,Estonia,50,"Java, NLP, Python, Deep Learning, Computer Vision",PhD,1,Transportation,2024-05-04,2024-07-10,976,7.9,Quantum Computing Inc -AI00300,Machine Learning Researcher,75499,USD,75499,EN,FT,Sweden,L,Sweden,0,"GCP, Linux, Deep Learning, Java, Kubernetes",PhD,1,Education,2024-10-02,2024-10-27,2054,9.6,Future Systems -AI00301,AI Architect,84962,SGD,110451,EN,CT,Singapore,L,Israel,50,"GCP, Data Visualization, Azure",Associate,1,Finance,2024-05-15,2024-06-29,1804,6.2,TechCorp Inc -AI00302,Data Analyst,144336,CHF,129902,MI,CT,Switzerland,M,Switzerland,0,"Data Visualization, Java, Mathematics, AWS",Bachelor,3,Gaming,2025-02-06,2025-03-30,1336,7.8,Machine Intelligence Group -AI00303,AI Consultant,52300,USD,52300,SE,PT,China,S,China,100,"Docker, TensorFlow, GCP",Bachelor,8,Consulting,2024-03-10,2024-04-19,800,9.1,DataVision Ltd -AI00304,Data Engineer,157426,EUR,133812,EX,PT,Austria,S,Turkey,100,"Scala, Tableau, Java",PhD,13,Manufacturing,2025-04-07,2025-05-16,1741,6.2,Cloud AI Solutions -AI00305,Deep Learning Engineer,174692,USD,174692,EX,CT,South Korea,M,Portugal,100,"Linux, Python, TensorFlow",PhD,12,Automotive,2025-04-20,2025-06-27,731,7.9,Autonomous Tech -AI00306,NLP Engineer,142293,USD,142293,MI,PT,Norway,L,Sweden,50,"Git, Java, Deep Learning, Linux, Mathematics",Master,2,Energy,2025-04-05,2025-06-01,1398,7.1,Quantum Computing Inc -AI00307,AI Architect,109818,USD,109818,SE,FL,South Korea,S,South Korea,0,"GCP, Git, Statistics",PhD,9,Consulting,2024-01-04,2024-02-02,2344,5,Advanced Robotics -AI00308,AI Research Scientist,69642,USD,69642,EN,FT,Norway,M,Norway,0,"Java, SQL, Scala, PyTorch, NLP",Master,0,Automotive,2024-01-19,2024-03-31,583,7.9,AI Innovations -AI00309,Principal Data Scientist,70652,EUR,60054,MI,FL,Netherlands,S,Netherlands,50,"Computer Vision, Scala, Mathematics",Master,2,Media,2024-10-30,2024-12-30,1086,9.1,Advanced Robotics -AI00310,Data Analyst,242235,GBP,181676,EX,FL,United Kingdom,L,United Kingdom,100,"R, PyTorch, Docker",Master,12,Education,2024-12-18,2025-03-01,2038,6,Machine Intelligence Group -AI00311,AI Architect,211982,SGD,275577,EX,FT,Singapore,S,Singapore,50,"Hadoop, AWS, Docker",PhD,19,Manufacturing,2024-01-12,2024-02-18,1352,6.8,Machine Intelligence Group -AI00312,Principal Data Scientist,88077,EUR,74865,EN,FL,Germany,L,Germany,100,"Python, GCP, TensorFlow, Mathematics, PyTorch",Bachelor,1,Transportation,2024-02-20,2024-04-18,986,8.2,Machine Intelligence Group -AI00313,Robotics Engineer,107261,EUR,91172,MI,CT,Germany,L,Germany,50,"Hadoop, Tableau, Java, Git",Associate,3,Manufacturing,2024-10-19,2024-11-04,1617,9.7,AI Innovations -AI00314,Computer Vision Engineer,284132,USD,284132,EX,FT,United States,M,United States,0,"Deep Learning, Docker, Hadoop, Data Visualization",Master,10,Government,2025-04-24,2025-07-06,1832,5.1,Autonomous Tech -AI00315,AI Software Engineer,105482,USD,105482,SE,CT,South Korea,M,South Korea,100,"SQL, Git, AWS",PhD,5,Consulting,2025-02-13,2025-04-25,1845,5.9,Cognitive Computing -AI00316,AI Architect,161728,GBP,121296,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, PyTorch",PhD,15,Finance,2025-03-03,2025-04-19,1932,8.6,DataVision Ltd -AI00317,Data Engineer,131352,USD,131352,SE,PT,Norway,S,Sweden,0,"Scala, MLOps, GCP, Java",Bachelor,9,Retail,2024-11-02,2024-12-13,1802,5.8,Machine Intelligence Group -AI00318,Data Analyst,161727,EUR,137468,SE,FT,Austria,L,Finland,100,"Docker, GCP, SQL",PhD,6,Technology,2025-01-26,2025-04-04,1940,5.9,Cognitive Computing -AI00319,Data Analyst,151527,USD,151527,SE,FL,United States,L,Romania,0,"Java, SQL, Kubernetes, Git",PhD,7,Retail,2024-07-18,2024-09-02,845,7.1,Machine Intelligence Group -AI00320,Machine Learning Researcher,112476,USD,112476,SE,FT,Israel,L,Israel,50,"Hadoop, Git, Statistics",Master,6,Consulting,2024-04-20,2024-05-10,2413,8.7,TechCorp Inc -AI00321,ML Ops Engineer,72913,CAD,91141,MI,FT,Canada,M,Canada,0,"R, SQL, Mathematics",PhD,3,Telecommunications,2025-04-01,2025-05-31,941,7,Cognitive Computing -AI00322,Data Analyst,68734,CAD,85918,EN,FT,Canada,L,Malaysia,100,"Computer Vision, Python, TensorFlow, Docker",PhD,1,Finance,2024-08-28,2024-10-24,805,8.5,Algorithmic Solutions -AI00323,NLP Engineer,179564,EUR,152629,EX,FL,Netherlands,S,Netherlands,50,"Python, AWS, Git",Bachelor,11,Government,2024-01-24,2024-03-17,654,9.1,Quantum Computing Inc -AI00324,Data Scientist,71265,GBP,53449,EN,PT,United Kingdom,S,United Kingdom,0,"PyTorch, TensorFlow, Azure, Computer Vision, Java",Bachelor,1,Automotive,2024-03-27,2024-05-12,2172,9.5,DeepTech Ventures -AI00325,Deep Learning Engineer,143064,USD,143064,SE,FL,South Korea,L,Denmark,100,"Scala, Python, TensorFlow",Master,8,Telecommunications,2024-02-26,2024-04-13,1887,7.2,DataVision Ltd -AI00326,Deep Learning Engineer,196042,EUR,166636,EX,CT,Austria,L,Italy,0,"Kubernetes, PyTorch, Tableau, Docker, Computer Vision",PhD,14,Consulting,2025-02-14,2025-03-20,911,7.3,Advanced Robotics -AI00327,Data Engineer,101946,USD,101946,SE,FL,Ireland,S,Ireland,0,"SQL, PyTorch, Data Visualization, Computer Vision",Bachelor,7,Finance,2025-02-14,2025-04-20,1521,7.1,Digital Transformation LLC -AI00328,Autonomous Systems Engineer,89020,GBP,66765,MI,FL,United Kingdom,S,Brazil,50,"Kubernetes, R, Git, AWS",PhD,4,Media,2024-09-06,2024-10-27,1497,9.2,Algorithmic Solutions -AI00329,Autonomous Systems Engineer,134011,JPY,14741210,SE,PT,Japan,S,Israel,100,"Deep Learning, Statistics, Spark",PhD,9,Energy,2024-08-10,2024-09-15,2405,8.8,TechCorp Inc -AI00330,Data Analyst,97657,SGD,126954,MI,CT,Singapore,M,Singapore,100,"Scala, Git, MLOps",Master,2,Gaming,2024-08-28,2024-09-15,2240,8.9,Predictive Systems -AI00331,Deep Learning Engineer,153990,USD,153990,EX,PT,South Korea,M,Luxembourg,50,"Scala, Git, Deep Learning, SQL, Kubernetes",Bachelor,14,Consulting,2024-06-29,2024-08-12,1020,5.7,Algorithmic Solutions -AI00332,Robotics Engineer,124696,EUR,105992,SE,FT,Netherlands,S,Argentina,100,"PyTorch, Python, Computer Vision",PhD,6,Automotive,2024-05-17,2024-07-09,1117,5.5,TechCorp Inc -AI00333,Robotics Engineer,94884,USD,94884,MI,PT,Ireland,S,Ireland,0,"Linux, Hadoop, GCP",Bachelor,2,Retail,2024-11-06,2024-12-19,961,9.2,Cognitive Computing -AI00334,AI Architect,101192,CHF,91073,EN,FT,Switzerland,M,Switzerland,50,"R, Scala, Kubernetes, Git",PhD,0,Transportation,2024-12-28,2025-01-28,1793,5.8,DeepTech Ventures -AI00335,AI Product Manager,106624,USD,106624,SE,FT,Ireland,M,Ireland,100,"Git, Statistics, Azure",Associate,6,Telecommunications,2025-02-02,2025-02-25,2175,5.2,Cognitive Computing -AI00336,Data Scientist,187401,GBP,140551,EX,FT,United Kingdom,M,Germany,100,"TensorFlow, Docker, Spark, Python",Bachelor,12,Energy,2024-10-24,2024-11-11,1400,9.5,TechCorp Inc -AI00337,Data Analyst,165694,USD,165694,EX,FL,United States,M,United States,100,"Python, Kubernetes, MLOps",Associate,15,Retail,2024-01-04,2024-03-15,2434,8.8,DataVision Ltd -AI00338,Machine Learning Engineer,122206,USD,122206,SE,FL,United States,M,United States,50,"Spark, AWS, Linux, SQL, PyTorch",Bachelor,6,Healthcare,2024-01-31,2024-03-06,2282,9.2,Algorithmic Solutions -AI00339,Data Engineer,91226,SGD,118594,MI,PT,Singapore,L,India,0,"Python, TensorFlow, PyTorch, SQL",Bachelor,2,Transportation,2024-12-06,2025-01-16,519,7.7,Autonomous Tech -AI00340,AI Product Manager,110449,CHF,99404,MI,FL,Switzerland,S,Switzerland,100,"Mathematics, Linux, NLP",Bachelor,3,Energy,2025-02-01,2025-02-19,1970,5.9,Algorithmic Solutions -AI00341,AI Architect,275705,EUR,234349,EX,FT,Netherlands,L,Netherlands,100,"MLOps, SQL, Kubernetes, Spark, Java",Bachelor,16,Finance,2024-04-25,2024-05-29,2299,5.4,Future Systems -AI00342,ML Ops Engineer,161670,USD,161670,EX,PT,Finland,M,Brazil,0,"MLOps, Python, TensorFlow, GCP",Associate,11,Technology,2024-08-13,2024-09-18,1061,5.9,Machine Intelligence Group -AI00343,Computer Vision Engineer,95328,GBP,71496,MI,PT,United Kingdom,S,United Kingdom,50,"MLOps, Spark, Git, Deep Learning",PhD,3,Technology,2025-03-25,2025-04-26,734,8.5,Smart Analytics -AI00344,AI Consultant,68548,EUR,58266,EN,PT,Germany,M,Germany,0,"Hadoop, Spark, Statistics, Tableau",Associate,1,Transportation,2025-02-24,2025-03-26,1762,7.8,Digital Transformation LLC -AI00345,AI Consultant,378502,USD,378502,EX,FT,Denmark,L,Denmark,0,"SQL, Mathematics, Scala, Hadoop",Bachelor,12,Consulting,2024-09-29,2024-12-01,2234,8.4,Future Systems -AI00346,NLP Engineer,76682,USD,76682,SE,CT,South Korea,S,South Korea,0,"PyTorch, Kubernetes, Azure, GCP",Master,7,Gaming,2024-09-25,2024-11-12,643,10,Machine Intelligence Group -AI00347,Deep Learning Engineer,108478,USD,108478,MI,CT,Sweden,L,Sweden,0,"Hadoop, Java, Docker, Deep Learning",Master,2,Transportation,2024-04-24,2024-05-10,1436,9.4,Cognitive Computing -AI00348,Research Scientist,114526,JPY,12597860,MI,FL,Japan,M,Belgium,0,"Python, TensorFlow, SQL, NLP",Associate,3,Real Estate,2024-02-16,2024-03-05,1095,5.8,Future Systems -AI00349,AI Specialist,75609,USD,75609,EN,PT,Norway,S,Norway,0,"AWS, Python, Git, Statistics",PhD,0,Government,2024-09-19,2024-11-30,2109,9.9,Algorithmic Solutions -AI00350,Data Analyst,214389,USD,214389,SE,FL,Denmark,L,Denmark,100,"Java, Kubernetes, Python, SQL",Associate,6,Retail,2025-04-29,2025-06-13,2348,8.8,Smart Analytics -AI00351,NLP Engineer,104396,USD,104396,SE,CT,Finland,S,Finland,100,"SQL, Azure, Data Visualization, NLP",Master,7,Telecommunications,2024-08-13,2024-10-15,1398,5.3,Quantum Computing Inc -AI00352,Principal Data Scientist,53469,EUR,45449,EN,PT,France,M,United Kingdom,50,"Docker, Statistics, Data Visualization",PhD,0,Government,2024-01-10,2024-02-20,1249,6,Smart Analytics -AI00353,Head of AI,327929,USD,327929,EX,FL,Denmark,L,Denmark,0,"TensorFlow, Python, Data Visualization, NLP, Tableau",PhD,14,Transportation,2024-02-19,2024-04-14,1000,6.5,Smart Analytics -AI00354,Data Scientist,87984,JPY,9678240,MI,PT,Japan,S,Japan,100,"Computer Vision, Git, Tableau, Data Visualization",Bachelor,2,Consulting,2024-01-08,2024-02-19,560,7.4,Algorithmic Solutions -AI00355,AI Architect,127823,JPY,14060530,SE,CT,Japan,S,Japan,0,"Linux, MLOps, Tableau",Associate,8,Automotive,2025-04-17,2025-05-24,1762,7.3,Future Systems -AI00356,Machine Learning Researcher,93295,AUD,125948,MI,FL,Australia,M,Australia,0,"Spark, Mathematics, Linux",Associate,4,Education,2024-02-10,2024-04-04,582,5.1,Algorithmic Solutions -AI00357,NLP Engineer,25560,USD,25560,MI,PT,India,M,India,50,"Kubernetes, Linux, Tableau, Mathematics",Master,2,Transportation,2024-02-29,2024-04-02,1775,7.5,Cognitive Computing -AI00358,Deep Learning Engineer,110777,GBP,83083,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, Python, GCP",PhD,3,Transportation,2024-07-10,2024-08-31,1446,8.5,Quantum Computing Inc -AI00359,AI Specialist,253223,EUR,215240,EX,FL,Germany,M,Germany,0,"Scala, Kubernetes, SQL, Hadoop, Docker",Bachelor,17,Retail,2024-07-24,2024-08-27,1970,5,Algorithmic Solutions -AI00360,ML Ops Engineer,234867,EUR,199637,EX,PT,Netherlands,M,Israel,0,"Spark, Statistics, MLOps, R",PhD,10,Automotive,2024-11-18,2024-12-27,826,5.1,Digital Transformation LLC -AI00361,AI Consultant,49385,USD,49385,EN,FT,Finland,S,Finland,50,"NLP, Statistics, Hadoop",Master,0,Media,2025-03-28,2025-04-13,1111,6.6,Advanced Robotics -AI00362,Data Scientist,59557,USD,59557,SE,CT,China,L,Denmark,100,"PyTorch, GCP, NLP, Spark",Bachelor,8,Telecommunications,2024-03-26,2024-06-06,977,6.3,TechCorp Inc -AI00363,AI Product Manager,95864,EUR,81484,SE,PT,France,S,France,0,"SQL, Hadoop, Tableau, Data Visualization",Master,6,Energy,2024-01-22,2024-03-27,1764,7.6,Predictive Systems -AI00364,AI Product Manager,217693,USD,217693,EX,PT,Israel,L,Israel,0,"GCP, MLOps, Scala, Kubernetes, Docker",Associate,18,Transportation,2024-04-15,2024-05-19,1099,9.7,Digital Transformation LLC -AI00365,ML Ops Engineer,108994,EUR,92645,MI,FL,France,L,France,100,"Kubernetes, Mathematics, Scala",Associate,2,Energy,2024-07-24,2024-08-31,1864,9.9,AI Innovations -AI00366,AI Software Engineer,75633,USD,75633,MI,FT,South Korea,S,Ghana,100,"Scala, Linux, NLP, R, Computer Vision",Associate,4,Gaming,2024-06-07,2024-06-27,1965,8.1,Advanced Robotics -AI00367,AI Research Scientist,62810,EUR,53389,EN,FL,Germany,S,Germany,100,"Deep Learning, Python, Tableau, Computer Vision, Statistics",Associate,0,Automotive,2025-02-13,2025-04-05,1004,9.7,Predictive Systems -AI00368,Data Engineer,151628,EUR,128884,EX,FT,France,S,France,100,"Python, TensorFlow, Java",Bachelor,15,Real Estate,2024-08-02,2024-09-30,539,8.3,AI Innovations -AI00369,AI Research Scientist,125355,SGD,162962,SE,FL,Singapore,M,Singapore,100,"Docker, NLP, AWS",Master,9,Transportation,2025-02-27,2025-05-07,2194,9.7,Quantum Computing Inc -AI00370,Principal Data Scientist,136102,USD,136102,SE,PT,Denmark,M,Denmark,100,"Linux, PyTorch, Tableau, Mathematics",PhD,7,Telecommunications,2024-03-08,2024-04-08,1973,5.1,Machine Intelligence Group -AI00371,Deep Learning Engineer,56934,EUR,48394,EN,PT,France,L,France,0,"Git, SQL, NLP, PyTorch",PhD,0,Automotive,2024-02-07,2024-03-26,1672,6.9,Advanced Robotics -AI00372,ML Ops Engineer,67190,EUR,57112,MI,FL,France,S,Italy,50,"Scala, Tableau, Python, Docker, Hadoop",Master,4,Gaming,2024-02-18,2024-04-06,1470,8.3,AI Innovations -AI00373,AI Software Engineer,125164,EUR,106389,SE,FL,Austria,L,Austria,50,"Azure, Deep Learning, MLOps, Linux",PhD,9,Transportation,2024-06-26,2024-08-24,2025,5.1,TechCorp Inc -AI00374,NLP Engineer,85407,SGD,111029,EN,PT,Singapore,L,Singapore,50,"Statistics, GCP, AWS, SQL",Master,1,Media,2024-07-08,2024-09-17,646,8.2,Autonomous Tech -AI00375,ML Ops Engineer,112057,JPY,12326270,SE,FL,Japan,S,Japan,0,"Python, TensorFlow, PyTorch, SQL, Deep Learning",Master,7,Manufacturing,2025-03-13,2025-04-03,789,8.5,Neural Networks Co -AI00376,ML Ops Engineer,95078,USD,95078,MI,CT,Denmark,M,Denmark,0,"SQL, MLOps, Scala",Bachelor,3,Automotive,2025-02-26,2025-04-21,1839,5.7,Quantum Computing Inc -AI00377,AI Product Manager,198651,USD,198651,EX,CT,Norway,M,Norway,100,"SQL, Spark, TensorFlow, Deep Learning, Kubernetes",Bachelor,18,Retail,2024-05-08,2024-05-27,2463,5.7,DeepTech Ventures -AI00378,AI Software Engineer,220998,JPY,24309780,EX,CT,Japan,S,India,50,"SQL, Linux, Tableau, Azure, Scala",Bachelor,12,Education,2024-05-04,2024-06-16,731,7.3,Cloud AI Solutions -AI00379,NLP Engineer,74126,USD,74126,EX,FT,India,S,India,100,"Scala, PyTorch, Docker, Deep Learning, SQL",PhD,12,Government,2024-09-22,2024-10-29,1926,7.5,Predictive Systems -AI00380,Machine Learning Engineer,75172,EUR,63896,MI,CT,Austria,S,Austria,100,"SQL, Kubernetes, Docker, NLP",Associate,4,Media,2024-09-09,2024-11-15,2261,8.5,Cognitive Computing -AI00381,Deep Learning Engineer,60975,EUR,51829,EN,FT,Austria,L,Austria,100,"SQL, Hadoop, Tableau, Kubernetes",Master,1,Transportation,2024-11-21,2025-01-29,620,9.6,Cloud AI Solutions -AI00382,Principal Data Scientist,89175,EUR,75799,MI,FT,Germany,L,Singapore,0,"Computer Vision, AWS, GCP, Deep Learning, Spark",PhD,2,Manufacturing,2024-01-11,2024-02-21,2215,8.9,Digital Transformation LLC -AI00383,Computer Vision Engineer,149285,EUR,126892,SE,FL,Netherlands,L,Netherlands,50,"Python, Mathematics, Kubernetes",PhD,5,Education,2025-01-06,2025-03-02,1359,5.4,Predictive Systems -AI00384,AI Product Manager,192204,EUR,163373,EX,FT,Germany,M,Germany,0,"Mathematics, Linux, SQL",Bachelor,13,Media,2025-02-01,2025-03-10,1161,6.7,Future Systems -AI00385,NLP Engineer,94197,CHF,84777,MI,PT,Switzerland,S,Norway,100,"Spark, TensorFlow, Deep Learning, GCP",Associate,4,Finance,2024-09-28,2024-10-28,1172,5.3,Future Systems -AI00386,Autonomous Systems Engineer,90408,EUR,76847,EN,FL,Germany,L,Czech Republic,100,"Linux, SQL, Git",PhD,1,Technology,2024-01-25,2024-03-10,892,7.1,Autonomous Tech -AI00387,ML Ops Engineer,72940,USD,72940,MI,FT,Ireland,S,Czech Republic,0,"GCP, Hadoop, Java",PhD,3,Technology,2024-03-24,2024-05-07,1913,8.1,DeepTech Ventures -AI00388,Machine Learning Engineer,140696,JPY,15476560,SE,PT,Japan,S,Japan,0,"AWS, Java, GCP",Master,9,Real Estate,2024-04-03,2024-04-25,1774,5.6,Neural Networks Co -AI00389,Robotics Engineer,210902,CHF,189812,EX,FT,Switzerland,S,Switzerland,0,"Java, NLP, TensorFlow, PyTorch, Git",Bachelor,12,Real Estate,2024-09-25,2024-11-28,982,9.8,Cognitive Computing -AI00390,Computer Vision Engineer,78559,SGD,102127,EN,FL,Singapore,M,Singapore,100,"Python, PyTorch, Computer Vision",Bachelor,0,Automotive,2024-12-03,2025-01-13,586,5,AI Innovations -AI00391,AI Consultant,32923,USD,32923,MI,FT,India,M,India,50,"Kubernetes, MLOps, PyTorch, Linux, AWS",Master,4,Gaming,2024-01-20,2024-03-26,1442,9.2,AI Innovations -AI00392,Research Scientist,112363,JPY,12359930,SE,FL,Japan,S,Ukraine,0,"Python, TensorFlow, Azure, NLP, Data Visualization",Bachelor,9,Finance,2024-04-26,2024-05-12,843,9.4,Autonomous Tech -AI00393,AI Consultant,188028,USD,188028,EX,CT,United States,L,United States,50,"Scala, SQL, NLP",Associate,11,Retail,2025-04-25,2025-06-22,852,8.9,Quantum Computing Inc -AI00394,AI Product Manager,165794,USD,165794,EX,FT,Norway,S,United States,100,"Python, Azure, R, Kubernetes",Bachelor,16,Gaming,2025-01-26,2025-03-16,903,8.6,Advanced Robotics -AI00395,ML Ops Engineer,109778,EUR,93311,MI,FL,Netherlands,L,Netherlands,50,"Scala, GCP, Mathematics",PhD,3,Media,2024-02-11,2024-02-28,2366,8.9,Smart Analytics -AI00396,Head of AI,162918,USD,162918,EX,FL,Ireland,L,Ireland,0,"Hadoop, AWS, Scala",Bachelor,17,Consulting,2024-10-16,2024-12-12,721,5.5,TechCorp Inc -AI00397,Autonomous Systems Engineer,219603,USD,219603,EX,PT,United States,M,United States,0,"Python, Mathematics, Data Visualization",PhD,12,Transportation,2024-05-06,2024-06-16,894,8.5,DeepTech Ventures -AI00398,Head of AI,304991,CHF,274492,EX,FT,Switzerland,L,Switzerland,100,"Azure, PyTorch, Kubernetes, NLP, Java",Associate,17,Manufacturing,2024-03-08,2024-04-15,2314,6.5,Algorithmic Solutions -AI00399,AI Research Scientist,99431,AUD,134232,SE,FL,Australia,S,Estonia,50,"Kubernetes, TensorFlow, SQL",Associate,5,Retail,2024-04-09,2024-05-19,1227,6.7,DeepTech Ventures -AI00400,Data Scientist,92131,USD,92131,MI,CT,Sweden,L,Sweden,0,"SQL, Git, Statistics",Bachelor,3,Retail,2024-04-29,2024-07-01,1590,6.2,Digital Transformation LLC -AI00401,Research Scientist,111236,JPY,12235960,MI,FL,Japan,M,Japan,100,"Python, Spark, Linux, TensorFlow, Java",Master,3,Media,2025-03-05,2025-04-08,1407,6.1,Cloud AI Solutions -AI00402,AI Research Scientist,263705,USD,263705,EX,CT,Norway,M,Norway,0,"SQL, Scala, Linux",Bachelor,10,Technology,2024-12-16,2025-01-24,870,6.3,Cognitive Computing -AI00403,Head of AI,37401,USD,37401,MI,CT,China,S,Colombia,0,"Linux, Deep Learning, Statistics",Bachelor,2,Real Estate,2025-03-27,2025-06-04,728,8.3,Smart Analytics -AI00404,ML Ops Engineer,122481,GBP,91861,MI,FT,United Kingdom,L,Mexico,50,"MLOps, Tableau, Hadoop, AWS",Bachelor,3,Healthcare,2025-02-03,2025-03-11,1575,8,DeepTech Ventures -AI00405,Deep Learning Engineer,29050,USD,29050,EN,FL,India,L,India,50,"Spark, Azure, TensorFlow, Mathematics",Master,0,Real Estate,2024-05-24,2024-06-10,1106,6.7,Neural Networks Co -AI00406,Principal Data Scientist,142280,GBP,106710,SE,FT,United Kingdom,L,United Kingdom,100,"NLP, SQL, GCP, Kubernetes",Bachelor,9,Transportation,2024-08-30,2024-10-04,1311,9.9,TechCorp Inc -AI00407,AI Consultant,75989,USD,75989,EN,PT,United States,L,United States,0,"SQL, Java, TensorFlow, MLOps",PhD,0,Healthcare,2024-09-25,2024-11-19,2338,6.3,TechCorp Inc -AI00408,Computer Vision Engineer,103477,SGD,134520,SE,PT,Singapore,S,Singapore,100,"Scala, Data Visualization, TensorFlow, Azure, Statistics",Associate,6,Gaming,2024-02-11,2024-03-28,2343,8.9,Advanced Robotics -AI00409,ML Ops Engineer,111121,USD,111121,MI,FT,United States,S,United States,100,"Docker, Scala, Git, R",Associate,3,Healthcare,2024-03-05,2024-03-22,1349,7.6,Algorithmic Solutions -AI00410,Data Engineer,357359,CHF,321623,EX,CT,Switzerland,M,Switzerland,100,"PyTorch, MLOps, R, Scala, Tableau",PhD,19,Consulting,2024-06-28,2024-08-06,1855,7.3,Machine Intelligence Group -AI00411,ML Ops Engineer,107663,CAD,134579,MI,FT,Canada,L,Canada,100,"Docker, SQL, AWS, Computer Vision, Deep Learning",Bachelor,2,Education,2024-08-06,2024-09-10,683,5.3,Algorithmic Solutions -AI00412,Data Scientist,83352,GBP,62514,MI,PT,United Kingdom,S,United Kingdom,0,"PyTorch, SQL, GCP, AWS, TensorFlow",Bachelor,2,Education,2024-10-12,2024-11-07,1599,6.6,Future Systems -AI00413,Deep Learning Engineer,55431,GBP,41573,EN,CT,United Kingdom,S,United Kingdom,100,"Data Visualization, Git, Computer Vision, Kubernetes",Master,0,Retail,2024-03-08,2024-04-26,721,9.9,Cognitive Computing -AI00414,Data Scientist,149644,EUR,127197,SE,CT,Germany,M,Germany,100,"Git, Kubernetes, Linux",Associate,9,Education,2024-03-19,2024-04-18,825,7.7,Algorithmic Solutions -AI00415,AI Software Engineer,94453,USD,94453,MI,FT,Ireland,S,Ireland,50,"Computer Vision, Spark, SQL, GCP",PhD,2,Gaming,2025-04-05,2025-06-01,1352,5.2,Machine Intelligence Group -AI00416,Robotics Engineer,40773,USD,40773,MI,FT,China,M,China,0,"Python, Kubernetes, Docker, GCP",Bachelor,2,Finance,2024-05-26,2024-06-14,2359,6,Neural Networks Co -AI00417,AI Consultant,94832,CAD,118540,MI,CT,Canada,L,Australia,50,"GCP, TensorFlow, Linux",PhD,2,Education,2025-03-21,2025-05-18,1023,8.7,Advanced Robotics -AI00418,AI Specialist,66884,EUR,56851,EN,CT,Austria,L,Austria,100,"TensorFlow, AWS, Python, Mathematics, Deep Learning",Master,1,Transportation,2024-10-28,2024-12-18,1927,7.9,Quantum Computing Inc -AI00419,ML Ops Engineer,222209,USD,222209,SE,FL,Norway,L,Norway,50,"TensorFlow, SQL, Deep Learning",PhD,7,Finance,2024-03-15,2024-05-07,1846,6.3,Autonomous Tech -AI00420,Robotics Engineer,181591,JPY,19975010,EX,FL,Japan,S,Romania,50,"Python, TensorFlow, Java, Linux",Associate,15,Real Estate,2024-06-06,2024-07-19,2025,7.4,Cognitive Computing -AI00421,AI Research Scientist,70146,USD,70146,EN,PT,Sweden,M,Sweden,0,"Python, Azure, Deep Learning, TensorFlow, Data Visualization",Bachelor,1,Healthcare,2025-03-29,2025-05-17,1790,7,Quantum Computing Inc -AI00422,AI Software Engineer,77528,USD,77528,MI,CT,Ireland,M,Ireland,100,"Python, Spark, TensorFlow, Statistics, Java",Bachelor,2,Gaming,2024-01-12,2024-03-05,950,6.7,Future Systems -AI00423,AI Software Engineer,133696,CAD,167120,EX,FL,Canada,M,Canada,50,"AWS, Deep Learning, R, Computer Vision",Master,15,Government,2024-09-21,2024-11-28,2050,6.5,Neural Networks Co -AI00424,Deep Learning Engineer,266317,USD,266317,EX,FL,Norway,M,Norway,0,"R, GCP, MLOps, Azure, Python",Associate,19,Technology,2024-05-16,2024-07-07,970,5.3,Predictive Systems -AI00425,Head of AI,171903,USD,171903,EX,CT,Israel,L,India,100,"Kubernetes, Spark, Docker, Scala, Hadoop",Master,19,Healthcare,2024-07-27,2024-09-03,2156,9.3,Advanced Robotics -AI00426,Research Scientist,134807,CAD,168509,EX,FL,Canada,M,Denmark,0,"GCP, Kubernetes, SQL, Azure, Computer Vision",Bachelor,17,Manufacturing,2024-08-22,2024-09-05,1624,8.8,Digital Transformation LLC -AI00427,AI Product Manager,123091,EUR,104627,SE,FL,France,S,France,0,"Scala, TensorFlow, Spark, SQL",Bachelor,6,Consulting,2025-02-13,2025-03-31,2071,6,Digital Transformation LLC -AI00428,Data Engineer,55885,USD,55885,SE,FT,China,S,China,50,"Python, R, MLOps, Kubernetes",Bachelor,9,Education,2024-08-30,2024-09-19,875,8,Neural Networks Co -AI00429,Robotics Engineer,190416,USD,190416,EX,PT,Israel,S,Israel,100,"Linux, Hadoop, Kubernetes, Computer Vision, Deep Learning",Master,11,Finance,2024-10-11,2024-11-20,1500,9.8,Quantum Computing Inc -AI00430,Deep Learning Engineer,155137,USD,155137,SE,FL,Norway,S,Argentina,100,"Git, PyTorch, TensorFlow, SQL, Python",Master,6,Real Estate,2025-02-20,2025-03-22,2010,6.3,Predictive Systems -AI00431,Deep Learning Engineer,233502,SGD,303553,EX,FL,Singapore,L,Singapore,0,"Azure, Hadoop, R",Bachelor,14,Gaming,2025-02-13,2025-02-27,1261,9.1,Neural Networks Co -AI00432,Autonomous Systems Engineer,106241,USD,106241,SE,FT,South Korea,L,South Korea,100,"SQL, NLP, Python, Java",Associate,7,Consulting,2024-04-19,2024-06-12,1827,8.3,Advanced Robotics -AI00433,Principal Data Scientist,170331,JPY,18736410,EX,PT,Japan,L,China,100,"Kubernetes, Python, Computer Vision, Deep Learning",Master,17,Transportation,2025-01-11,2025-02-01,602,5.6,Autonomous Tech -AI00434,Machine Learning Researcher,190752,USD,190752,SE,PT,Denmark,M,Denmark,100,"TensorFlow, Spark, Deep Learning",Master,9,Gaming,2025-01-05,2025-02-01,1336,7.6,DeepTech Ventures -AI00435,Machine Learning Engineer,57858,JPY,6364380,EN,FL,Japan,S,Japan,0,"SQL, Hadoop, AWS, Mathematics",Bachelor,0,Consulting,2024-10-15,2024-11-10,1143,8.3,DataVision Ltd -AI00436,AI Consultant,60290,EUR,51247,EN,FT,Germany,M,Germany,50,"Computer Vision, MLOps, R",Associate,0,Real Estate,2024-09-01,2024-09-22,1266,9.6,Autonomous Tech -AI00437,Machine Learning Researcher,78662,USD,78662,MI,CT,South Korea,L,Norway,0,"Spark, Computer Vision, Mathematics",PhD,2,Technology,2024-02-09,2024-04-12,1998,9.9,Cloud AI Solutions -AI00438,Deep Learning Engineer,68057,USD,68057,EN,CT,Denmark,S,Denmark,0,"R, MLOps, AWS, Python",Master,1,Real Estate,2024-03-15,2024-05-12,2060,6.3,Cognitive Computing -AI00439,Data Engineer,152822,USD,152822,SE,CT,United States,M,India,50,"Git, Mathematics, Docker",Master,5,Healthcare,2025-03-29,2025-04-14,1541,5.8,Advanced Robotics -AI00440,Head of AI,168351,USD,168351,SE,FL,Sweden,L,Sweden,100,"Docker, Spark, Data Visualization, GCP",Bachelor,7,Energy,2025-03-03,2025-03-17,1746,9.3,TechCorp Inc -AI00441,Machine Learning Researcher,280392,USD,280392,EX,FT,United States,M,United States,0,"Docker, Hadoop, Azure, Python, Scala",Associate,15,Government,2024-10-17,2024-12-06,1427,5.8,Neural Networks Co -AI00442,AI Specialist,165716,USD,165716,EX,FL,Finland,L,Norway,50,"Data Visualization, R, Java",PhD,18,Media,2025-04-18,2025-05-22,2251,6.2,Quantum Computing Inc -AI00443,Computer Vision Engineer,187794,USD,187794,EX,FT,Finland,M,Finland,0,"Git, AWS, SQL, Kubernetes",PhD,11,Energy,2024-09-17,2024-10-02,1284,9,Quantum Computing Inc -AI00444,NLP Engineer,245697,EUR,208842,EX,FT,Germany,L,Germany,0,"GCP, Python, Mathematics",PhD,10,Healthcare,2024-08-22,2024-09-07,2112,9,Cognitive Computing -AI00445,Data Analyst,79411,CAD,99264,MI,CT,Canada,S,Canada,0,"SQL, Linux, Git, PyTorch, NLP",Master,3,Retail,2025-01-16,2025-02-27,2121,7.8,DeepTech Ventures -AI00446,AI Software Engineer,117847,USD,117847,SE,FT,South Korea,L,South Korea,100,"Scala, Python, Hadoop, Docker",Associate,7,Finance,2024-12-03,2024-12-17,1511,5.3,Cloud AI Solutions -AI00447,Principal Data Scientist,112962,GBP,84722,SE,FT,United Kingdom,M,Canada,100,"SQL, Python, Kubernetes, TensorFlow, Docker",Associate,9,Media,2024-06-04,2024-06-29,905,6.9,Machine Intelligence Group -AI00448,AI Product Manager,166397,AUD,224636,SE,FT,Australia,L,Australia,100,"Git, NLP, GCP, TensorFlow, Python",Master,7,Real Estate,2024-11-10,2024-12-01,2239,5,DeepTech Ventures -AI00449,Machine Learning Engineer,135988,USD,135988,SE,PT,Denmark,M,Israel,100,"Azure, Scala, GCP, MLOps",Bachelor,5,Media,2024-01-09,2024-03-08,1645,9.9,Neural Networks Co -AI00450,AI Specialist,30929,USD,30929,MI,FT,India,M,India,100,"Git, Azure, Kubernetes, R, SQL",PhD,2,Consulting,2024-04-14,2024-05-07,1963,9.6,DataVision Ltd -AI00451,Machine Learning Engineer,112165,EUR,95340,SE,FL,Germany,M,Germany,50,"Azure, AWS, Spark",Master,5,Technology,2024-02-11,2024-03-05,2021,8.9,Smart Analytics -AI00452,Data Scientist,100758,EUR,85644,MI,FL,Germany,M,Germany,100,"Python, Scala, NLP, Spark",Associate,4,Telecommunications,2024-04-21,2024-05-24,1162,9.1,Predictive Systems -AI00453,Principal Data Scientist,83754,USD,83754,EN,PT,Norway,L,United Kingdom,100,"Mathematics, Computer Vision, Git",Master,0,Finance,2025-01-15,2025-02-06,2164,7.8,Cloud AI Solutions -AI00454,Head of AI,109895,CHF,98906,MI,PT,Switzerland,S,Switzerland,100,"Tableau, Scala, Python",Associate,4,Consulting,2024-03-08,2024-04-25,2487,8.9,AI Innovations -AI00455,Machine Learning Engineer,160760,EUR,136646,EX,FT,Netherlands,M,Netherlands,50,"NLP, Linux, TensorFlow, Data Visualization",Bachelor,11,Energy,2024-02-23,2024-04-19,1258,7.1,Algorithmic Solutions -AI00456,Machine Learning Engineer,167415,AUD,226010,SE,PT,Australia,L,Australia,100,"Linux, Python, TensorFlow",Bachelor,5,Energy,2024-11-15,2024-12-04,2488,6.7,DataVision Ltd -AI00457,Data Scientist,58948,AUD,79580,EN,CT,Australia,L,Australia,100,"Azure, NLP, PyTorch",Master,1,Healthcare,2024-07-13,2024-09-09,515,7.4,Cloud AI Solutions -AI00458,ML Ops Engineer,73406,USD,73406,MI,CT,South Korea,L,South Korea,0,"Mathematics, Java, R",Bachelor,3,Retail,2024-12-28,2025-01-15,677,6,DeepTech Ventures -AI00459,AI Software Engineer,153534,EUR,130504,EX,FT,Austria,L,Austria,100,"MLOps, Linux, Docker, PyTorch",Associate,19,Gaming,2024-06-04,2024-07-16,1625,7.5,Predictive Systems -AI00460,Data Scientist,81787,JPY,8996570,MI,PT,Japan,M,Japan,50,"Java, Spark, AWS, Linux, MLOps",PhD,4,Manufacturing,2025-03-08,2025-05-11,577,5.9,Predictive Systems -AI00461,Computer Vision Engineer,121967,USD,121967,MI,PT,Ireland,L,Ireland,0,"AWS, TensorFlow, Statistics, Mathematics",Master,4,Finance,2024-06-30,2024-08-19,914,6.5,Algorithmic Solutions -AI00462,Data Analyst,181438,JPY,19958180,EX,CT,Japan,S,Japan,50,"Java, Spark, TensorFlow",Associate,14,Real Estate,2025-01-25,2025-03-04,2075,5.5,Quantum Computing Inc -AI00463,Autonomous Systems Engineer,60296,USD,60296,EN,PT,Ireland,L,Ireland,50,"Spark, Azure, PyTorch, Python, TensorFlow",Master,1,Retail,2025-01-21,2025-02-26,635,7.3,Algorithmic Solutions -AI00464,AI Specialist,64191,USD,64191,EN,PT,Sweden,M,Vietnam,50,"Kubernetes, Linux, Data Visualization, PyTorch",Master,1,Healthcare,2024-11-26,2024-12-11,2243,5.6,Future Systems -AI00465,AI Research Scientist,96896,CHF,87206,EN,FL,Switzerland,S,Italy,50,"Python, Scala, Azure, Hadoop",PhD,0,Gaming,2024-09-25,2024-12-05,1137,7.4,Algorithmic Solutions -AI00466,Principal Data Scientist,78105,USD,78105,MI,PT,South Korea,M,South Korea,50,"Scala, SQL, Data Visualization",Bachelor,2,Healthcare,2025-02-14,2025-03-24,2258,5.2,Predictive Systems -AI00467,Robotics Engineer,71686,EUR,60933,EN,PT,Germany,S,Germany,50,"Kubernetes, PyTorch, Linux",Master,0,Retail,2024-09-21,2024-10-20,1282,8,Cognitive Computing -AI00468,AI Research Scientist,148827,EUR,126503,SE,PT,Germany,M,Australia,0,"Python, Spark, NLP, R",Associate,9,Finance,2024-11-27,2025-01-31,1119,5,Neural Networks Co -AI00469,Data Analyst,92179,CAD,115224,SE,FL,Canada,S,Canada,100,"Python, Tableau, TensorFlow, GCP",Associate,8,Transportation,2025-03-01,2025-05-01,2487,8.2,Cognitive Computing -AI00470,Computer Vision Engineer,75460,EUR,64141,MI,FL,Austria,M,Austria,50,"Computer Vision, NLP, Kubernetes",Bachelor,3,Retail,2024-09-27,2024-11-17,1175,6.1,Advanced Robotics -AI00471,AI Architect,146580,EUR,124593,EX,PT,Netherlands,M,Netherlands,50,"Git, Docker, Mathematics, SQL",Associate,17,Education,2024-10-23,2024-12-20,1494,9.8,DataVision Ltd -AI00472,Data Analyst,68722,USD,68722,EN,FL,United States,S,Finland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Technology,2025-01-11,2025-03-06,1575,6.3,Neural Networks Co -AI00473,ML Ops Engineer,60841,USD,60841,EN,CT,United States,S,United States,50,"NLP, Scala, AWS, SQL, Hadoop",PhD,1,Automotive,2025-03-22,2025-05-27,2340,5.4,Machine Intelligence Group -AI00474,Deep Learning Engineer,49130,USD,49130,EN,FL,Sweden,S,Luxembourg,50,"TensorFlow, Python, Data Visualization, Deep Learning, AWS",Master,0,Education,2025-04-12,2025-05-16,2022,9.1,Advanced Robotics -AI00475,AI Product Manager,162683,USD,162683,SE,FT,Finland,L,Finland,50,"Python, TensorFlow, NLP, Kubernetes, Statistics",Master,9,Consulting,2024-12-30,2025-03-07,1100,9.1,Algorithmic Solutions -AI00476,Data Analyst,151676,EUR,128925,SE,PT,Germany,M,Germany,50,"Java, Hadoop, Data Visualization, MLOps, TensorFlow",Master,8,Government,2024-12-07,2025-01-15,1822,8.9,Advanced Robotics -AI00477,Head of AI,140928,USD,140928,MI,CT,Norway,M,Philippines,50,"Linux, TensorFlow, Hadoop, Docker",Master,4,Education,2024-04-10,2024-06-22,1543,8.9,DeepTech Ventures -AI00478,AI Specialist,140382,AUD,189516,SE,FL,Australia,M,Colombia,100,"Mathematics, GCP, Python, TensorFlow, NLP",Associate,8,Finance,2024-09-26,2024-11-22,2458,6.8,Cloud AI Solutions -AI00479,Machine Learning Engineer,179691,USD,179691,EX,CT,Ireland,S,Egypt,0,"TensorFlow, PyTorch, Scala, AWS",Bachelor,18,Energy,2024-09-29,2024-10-26,2128,6.7,Predictive Systems -AI00480,Principal Data Scientist,132280,EUR,112438,SE,FL,France,L,France,100,"Docker, Linux, Tableau, Git",PhD,8,Retail,2024-10-24,2024-12-14,599,8.1,Future Systems -AI00481,Computer Vision Engineer,90861,USD,90861,MI,FL,Norway,S,Norway,0,"Linux, SQL, R, Git, AWS",Associate,4,Telecommunications,2024-05-23,2024-07-14,783,7.9,Predictive Systems -AI00482,Data Engineer,102239,USD,102239,EX,PT,China,L,China,50,"Hadoop, Linux, R",Master,11,Technology,2025-04-16,2025-05-04,1574,9.5,Predictive Systems -AI00483,Machine Learning Engineer,71795,EUR,61026,EN,CT,Germany,M,Germany,0,"Python, Computer Vision, Hadoop, GCP, SQL",Master,1,Energy,2024-06-17,2024-08-13,2350,5.4,AI Innovations -AI00484,NLP Engineer,55230,EUR,46946,EN,FL,France,L,France,0,"Tableau, Data Visualization, Git, Linux, Hadoop",PhD,1,Media,2024-03-17,2024-04-02,840,9,Cognitive Computing -AI00485,AI Consultant,56030,EUR,47626,EN,PT,Germany,M,United States,50,"Docker, Deep Learning, Kubernetes, Spark",Bachelor,1,Government,2024-07-22,2024-08-20,1612,7.1,Autonomous Tech -AI00486,Head of AI,99246,USD,99246,EX,PT,India,L,India,100,"Spark, SQL, PyTorch, Java",Associate,17,Real Estate,2024-09-15,2024-11-02,1339,7.8,Predictive Systems -AI00487,AI Product Manager,130136,CAD,162670,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, TensorFlow, Computer Vision, Hadoop",PhD,11,Consulting,2025-01-05,2025-01-31,2026,6.3,DeepTech Ventures -AI00488,AI Research Scientist,51311,JPY,5644210,EN,FL,Japan,S,Japan,100,"Tableau, Linux, TensorFlow, Data Visualization",PhD,1,Telecommunications,2025-01-15,2025-03-09,856,6.7,Digital Transformation LLC -AI00489,Machine Learning Engineer,59010,USD,59010,EN,FL,South Korea,S,South Korea,100,"Hadoop, Computer Vision, Mathematics, GCP, Git",Associate,1,Real Estate,2024-12-27,2025-02-09,1203,9.1,Quantum Computing Inc -AI00490,AI Research Scientist,139257,USD,139257,SE,CT,United States,L,United States,50,"Azure, TensorFlow, Kubernetes, Computer Vision, Hadoop",Master,5,Manufacturing,2024-02-27,2024-03-25,1275,7.4,DataVision Ltd -AI00491,Data Analyst,50920,USD,50920,EN,FL,Finland,S,Finland,0,"Git, Scala, SQL",Master,0,Manufacturing,2024-11-05,2024-12-13,2039,8.6,Smart Analytics -AI00492,AI Specialist,116377,CHF,104739,EN,CT,Switzerland,L,Indonesia,100,"Azure, Scala, Deep Learning, Computer Vision, Statistics",Associate,0,Finance,2025-01-16,2025-02-01,1586,7,DeepTech Ventures -AI00493,Principal Data Scientist,101911,CHF,91720,EN,FT,Switzerland,M,France,0,"Linux, GCP, NLP",Associate,0,Education,2024-11-06,2024-12-23,1975,7.1,Cognitive Computing -AI00494,Data Analyst,92714,EUR,78807,EN,PT,Netherlands,L,Portugal,50,"Java, Mathematics, Tableau, Spark, PyTorch",Master,1,Technology,2024-03-17,2024-03-31,1305,9.3,Neural Networks Co -AI00495,Head of AI,83757,GBP,62818,EN,CT,United Kingdom,L,United Kingdom,0,"Statistics, Mathematics, Data Visualization",Bachelor,0,Media,2024-08-09,2024-09-20,1023,5,Advanced Robotics -AI00496,AI Specialist,88018,CAD,110023,MI,PT,Canada,L,Canada,50,"MLOps, NLP, SQL, Data Visualization",Master,2,Energy,2025-04-03,2025-04-29,1955,5.2,DataVision Ltd -AI00497,Data Scientist,51864,USD,51864,EN,FT,Finland,S,Finland,100,"Computer Vision, Scala, Data Visualization",Master,1,Transportation,2024-03-05,2024-05-02,2470,6.3,Cloud AI Solutions -AI00498,Head of AI,96976,SGD,126069,MI,CT,Singapore,L,Indonesia,50,"Spark, Hadoop, Scala, Linux",Associate,4,Manufacturing,2024-06-03,2024-07-08,1038,9.4,Predictive Systems -AI00499,Computer Vision Engineer,120263,USD,120263,EX,FT,South Korea,M,Chile,100,"Python, GCP, Spark",Bachelor,13,Retail,2024-10-23,2024-12-08,2046,6.7,Predictive Systems -AI00500,Data Scientist,178114,CHF,160303,SE,PT,Switzerland,S,Colombia,0,"AWS, Java, GCP",PhD,9,Consulting,2024-11-17,2024-12-31,1369,5.7,Cognitive Computing -AI00501,AI Research Scientist,94379,AUD,127412,MI,CT,Australia,L,Australia,50,"TensorFlow, GCP, PyTorch",Master,3,Finance,2025-01-05,2025-01-28,784,7.9,DeepTech Ventures -AI00502,AI Software Engineer,268149,USD,268149,EX,FT,Norway,M,Norway,0,"Git, Python, Azure, Statistics, AWS",PhD,17,Media,2024-02-03,2024-03-15,1961,5.6,Machine Intelligence Group -AI00503,NLP Engineer,90472,CAD,113090,MI,CT,Canada,L,Canada,0,"Mathematics, AWS, Git, Kubernetes, SQL",Master,3,Finance,2024-10-07,2024-11-18,1473,8.7,Quantum Computing Inc -AI00504,AI Product Manager,86547,USD,86547,SE,FT,Israel,S,Israel,0,"Git, Computer Vision, NLP, R",PhD,7,Healthcare,2024-11-08,2025-01-02,1978,8.8,Machine Intelligence Group -AI00505,AI Consultant,150700,EUR,128095,SE,CT,France,L,India,0,"Computer Vision, Azure, Data Visualization, Scala",PhD,6,Retail,2024-06-08,2024-07-06,2425,8.1,Predictive Systems -AI00506,AI Specialist,216740,USD,216740,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Azure, Python, Linux, Docker",Bachelor,14,Healthcare,2025-04-14,2025-05-01,1701,5.3,TechCorp Inc -AI00507,AI Software Engineer,59227,EUR,50343,EN,FL,Netherlands,M,Netherlands,0,"Docker, Tableau, Kubernetes",PhD,1,Healthcare,2025-01-22,2025-02-19,624,9.7,TechCorp Inc -AI00508,AI Software Engineer,163281,CAD,204101,SE,PT,Canada,L,Canada,0,"Git, TensorFlow, Tableau",PhD,5,Transportation,2025-01-20,2025-02-18,2007,7.3,Advanced Robotics -AI00509,Data Engineer,66305,USD,66305,EN,FT,United States,S,Estonia,100,"GCP, Java, AWS, Data Visualization",PhD,1,Transportation,2024-11-09,2024-12-30,1348,6.9,Smart Analytics -AI00510,AI Consultant,126408,CAD,158010,SE,PT,Canada,L,Canada,100,"Spark, Python, GCP, SQL",Bachelor,6,Automotive,2024-08-11,2024-09-18,1300,6.6,Machine Intelligence Group -AI00511,NLP Engineer,144024,EUR,122420,SE,FL,Netherlands,L,Netherlands,100,"AWS, R, Deep Learning, Kubernetes",Associate,7,Automotive,2024-07-03,2024-08-09,1552,9.6,Smart Analytics -AI00512,AI Software Engineer,108805,USD,108805,SE,FT,South Korea,M,South Korea,0,"AWS, Azure, Linux, Mathematics",Master,6,Transportation,2024-12-25,2025-02-08,2105,8.1,Cognitive Computing -AI00513,Data Analyst,79093,EUR,67229,MI,PT,France,M,Ireland,50,"Linux, Java, Tableau",PhD,3,Energy,2024-08-11,2024-09-03,837,8.9,Cloud AI Solutions -AI00514,Machine Learning Engineer,295893,USD,295893,EX,PT,Denmark,S,Denmark,50,"Spark, Python, Java, NLP, TensorFlow",Bachelor,15,Retail,2024-04-13,2024-06-18,1210,7.9,Algorithmic Solutions -AI00515,AI Specialist,83000,JPY,9130000,MI,FT,Japan,M,Japan,50,"TensorFlow, Hadoop, Data Visualization",PhD,2,Education,2024-12-12,2025-01-23,1006,5.2,Quantum Computing Inc -AI00516,AI Software Engineer,80124,USD,80124,EN,CT,United States,M,United States,0,"R, AWS, Hadoop, Kubernetes",Master,0,Education,2024-11-07,2024-12-14,665,9.8,Autonomous Tech -AI00517,Data Engineer,69336,EUR,58936,EN,FL,Germany,L,Vietnam,0,"Mathematics, Spark, Python",Bachelor,1,Gaming,2024-12-28,2025-01-30,1975,9.8,Autonomous Tech -AI00518,Data Engineer,42380,USD,42380,SE,FL,India,L,United States,0,"Azure, Docker, Java, MLOps",Master,5,Telecommunications,2024-08-02,2024-09-18,1526,6.9,TechCorp Inc -AI00519,Data Scientist,149450,EUR,127033,EX,PT,Germany,M,Philippines,0,"Mathematics, Spark, Docker, Hadoop",Bachelor,18,Telecommunications,2024-09-10,2024-11-01,1201,7.7,Smart Analytics -AI00520,AI Software Engineer,285891,CHF,257302,EX,FT,Switzerland,S,Singapore,50,"Java, Python, MLOps, Linux, Azure",Master,16,Consulting,2024-08-22,2024-09-29,1105,5.8,Neural Networks Co -AI00521,Computer Vision Engineer,75240,USD,75240,EN,CT,South Korea,L,South Korea,100,"Mathematics, Hadoop, Docker",PhD,1,Telecommunications,2024-01-20,2024-02-03,1921,9.3,Algorithmic Solutions -AI00522,Data Scientist,124786,JPY,13726460,SE,FL,Japan,M,Japan,0,"NLP, AWS, Data Visualization, MLOps",Bachelor,7,Education,2024-03-20,2024-05-24,1442,8.3,Algorithmic Solutions -AI00523,Machine Learning Researcher,109043,CHF,98139,MI,FL,Switzerland,S,Switzerland,0,"GCP, Azure, Linux",Associate,3,Government,2025-03-08,2025-05-15,1570,5.6,Machine Intelligence Group -AI00524,Machine Learning Engineer,89035,USD,89035,SE,CT,Finland,S,Ireland,50,"SQL, Docker, NLP, Python",Associate,5,Telecommunications,2024-08-29,2024-09-20,864,6.6,Quantum Computing Inc -AI00525,Machine Learning Engineer,190529,USD,190529,EX,FL,Finland,M,Finland,50,"Linux, Spark, Tableau, Mathematics, Azure",Bachelor,19,Technology,2024-10-11,2024-11-03,1090,10,Neural Networks Co -AI00526,Machine Learning Engineer,169009,USD,169009,SE,PT,United States,M,Finland,100,"Docker, Kubernetes, Azure",Master,9,Healthcare,2024-11-21,2025-01-25,1366,9.7,TechCorp Inc -AI00527,Autonomous Systems Engineer,48714,USD,48714,EN,FT,Israel,S,Israel,100,"Git, R, Python, Mathematics",Master,1,Energy,2025-03-15,2025-04-01,530,8.6,Advanced Robotics -AI00528,ML Ops Engineer,97541,EUR,82910,SE,FT,Netherlands,S,Netherlands,0,"MLOps, Python, Kubernetes, TensorFlow",PhD,5,Manufacturing,2024-12-16,2025-01-21,1792,9.2,Predictive Systems -AI00529,Robotics Engineer,144493,EUR,122819,SE,CT,Germany,M,Germany,0,"Spark, Java, Deep Learning, R",PhD,5,Education,2025-04-18,2025-05-26,2224,7.1,TechCorp Inc -AI00530,Computer Vision Engineer,185421,USD,185421,EX,CT,Denmark,S,Nigeria,0,"PyTorch, SQL, Docker, TensorFlow",Associate,11,Media,2024-06-18,2024-08-03,1524,9.7,DeepTech Ventures -AI00531,Principal Data Scientist,287164,USD,287164,EX,FL,Sweden,L,Sweden,0,"Azure, TensorFlow, Statistics, PyTorch, R",Bachelor,18,Consulting,2024-08-31,2024-10-03,1681,8.4,AI Innovations -AI00532,AI Consultant,120968,JPY,13306480,SE,PT,Japan,S,Japan,0,"Azure, Hadoop, Scala, Computer Vision, Python",PhD,8,Healthcare,2024-10-25,2024-11-30,952,7.3,Advanced Robotics -AI00533,AI Research Scientist,135171,USD,135171,EX,CT,Sweden,S,Sweden,50,"Azure, Deep Learning, GCP, TensorFlow",Associate,14,Healthcare,2024-05-14,2024-05-31,1460,6.7,Cognitive Computing -AI00534,AI Architect,129545,CHF,116591,EN,PT,Switzerland,L,Finland,100,"Scala, Python, Computer Vision, Deep Learning",Master,1,Government,2024-03-14,2024-04-20,561,9.3,TechCorp Inc -AI00535,Data Analyst,97794,SGD,127132,MI,CT,Singapore,L,Singapore,50,"PyTorch, R, Data Visualization",PhD,2,Gaming,2024-04-04,2024-06-12,984,6.1,Autonomous Tech -AI00536,Deep Learning Engineer,145395,CAD,181744,EX,FL,Canada,M,Brazil,100,"Computer Vision, Data Visualization, Python, Spark, TensorFlow",PhD,18,Automotive,2024-07-27,2024-09-08,1959,7.5,TechCorp Inc -AI00537,Computer Vision Engineer,204217,USD,204217,EX,CT,Sweden,M,Kenya,50,"GCP, Deep Learning, R",Associate,11,Education,2024-09-28,2024-11-16,1581,7.2,Future Systems -AI00538,Autonomous Systems Engineer,98702,USD,98702,EN,FT,Denmark,L,Denmark,0,"Statistics, Kubernetes, R, SQL",Bachelor,0,Telecommunications,2025-02-17,2025-03-11,1517,9.4,Machine Intelligence Group -AI00539,Deep Learning Engineer,99895,GBP,74921,MI,CT,United Kingdom,S,New Zealand,0,"R, PyTorch, GCP, NLP, Git",Bachelor,3,Finance,2025-01-27,2025-03-20,2257,10,Machine Intelligence Group -AI00540,NLP Engineer,135571,EUR,115235,SE,FL,Netherlands,S,Netherlands,100,"Git, Spark, R, SQL, Tableau",PhD,8,Telecommunications,2024-07-13,2024-09-01,2391,8.7,Advanced Robotics -AI00541,AI Specialist,119266,USD,119266,SE,PT,Ireland,L,Ireland,50,"SQL, Python, Data Visualization",PhD,6,Government,2024-04-04,2024-05-21,1518,9.2,Digital Transformation LLC -AI00542,Research Scientist,110844,EUR,94217,SE,CT,Austria,L,Austria,50,"Scala, Statistics, MLOps, Deep Learning",Associate,8,Transportation,2025-02-07,2025-03-09,1353,9.6,DeepTech Ventures -AI00543,NLP Engineer,145736,EUR,123876,SE,FT,Netherlands,L,Ghana,50,"Linux, Python, NLP, TensorFlow",Master,9,Transportation,2025-01-16,2025-03-05,2348,6.1,Cloud AI Solutions -AI00544,AI Software Engineer,232735,EUR,197825,EX,PT,France,M,France,0,"Spark, PyTorch, TensorFlow, Deep Learning, Azure",Bachelor,11,Manufacturing,2025-04-15,2025-06-25,1449,9.7,Future Systems -AI00545,Machine Learning Researcher,56990,USD,56990,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Hadoop",PhD,1,Telecommunications,2024-02-17,2024-03-25,2274,6.2,Algorithmic Solutions -AI00546,AI Software Engineer,169605,USD,169605,EX,FT,Israel,M,Israel,0,"Data Visualization, AWS, TensorFlow, R, Linux",PhD,15,Real Estate,2024-05-17,2024-06-16,1672,6,Digital Transformation LLC -AI00547,Machine Learning Engineer,145138,USD,145138,SE,PT,Finland,L,United Kingdom,0,"PyTorch, Git, Python, AWS",PhD,8,Real Estate,2024-12-25,2025-02-16,793,5.2,AI Innovations -AI00548,Data Scientist,139121,EUR,118253,SE,FL,Germany,L,Germany,50,"Git, Kubernetes, Python, Linux",Bachelor,5,Finance,2024-10-20,2024-11-17,587,9.2,Cloud AI Solutions -AI00549,AI Product Manager,178631,USD,178631,EX,PT,Israel,S,Malaysia,100,"TensorFlow, Spark, Computer Vision, NLP",Bachelor,13,Automotive,2024-09-28,2024-11-18,1081,6.8,Machine Intelligence Group -AI00550,NLP Engineer,90723,SGD,117940,MI,PT,Singapore,S,New Zealand,0,"Linux, Scala, Git",Bachelor,4,Retail,2024-12-28,2025-01-20,2414,7.3,DataVision Ltd -AI00551,ML Ops Engineer,49069,USD,49069,MI,CT,China,M,China,100,"Python, Docker, TensorFlow",PhD,4,Automotive,2024-11-26,2025-02-06,1659,7.2,Autonomous Tech -AI00552,Deep Learning Engineer,68202,JPY,7502220,EN,FL,Japan,L,Japan,50,"TensorFlow, Java, AWS, R",Master,0,Automotive,2025-04-08,2025-05-08,1446,5.6,Cloud AI Solutions -AI00553,Data Analyst,116676,EUR,99175,MI,FL,Germany,L,Germany,0,"R, TensorFlow, Kubernetes, Scala, Statistics",Associate,3,Media,2024-03-25,2024-04-26,1460,5.8,Smart Analytics -AI00554,AI Specialist,153139,USD,153139,SE,FT,Finland,L,Finland,100,"Python, Spark, Scala, Deep Learning, Mathematics",PhD,7,Real Estate,2025-04-28,2025-05-21,609,6.8,Autonomous Tech -AI00555,Computer Vision Engineer,131402,EUR,111692,EX,FL,Netherlands,S,Netherlands,50,"MLOps, Tableau, SQL",Master,13,Media,2024-12-31,2025-03-14,1147,5.1,DeepTech Ventures -AI00556,Machine Learning Engineer,54607,EUR,46416,EN,CT,Austria,M,Austria,50,"Git, Java, Hadoop",Associate,1,Real Estate,2024-08-11,2024-10-18,1342,6.4,Advanced Robotics -AI00557,Autonomous Systems Engineer,71774,JPY,7895140,MI,CT,Japan,S,Egypt,100,"Java, Data Visualization, Deep Learning, MLOps, Spark",PhD,4,Government,2024-02-04,2024-03-17,2022,9.7,DataVision Ltd -AI00558,Data Engineer,110765,EUR,94150,SE,FL,Germany,S,China,0,"PyTorch, GCP, TensorFlow",PhD,6,Technology,2024-03-02,2024-03-21,721,5.4,AI Innovations -AI00559,Data Analyst,265991,USD,265991,EX,PT,United States,L,Vietnam,100,"AWS, Git, Docker, Azure, Computer Vision",Master,13,Finance,2024-07-24,2024-09-24,1528,7.7,DataVision Ltd -AI00560,AI Research Scientist,83839,USD,83839,MI,FL,Israel,L,Israel,50,"Scala, Spark, GCP, Azure, NLP",Bachelor,4,Real Estate,2024-03-09,2024-03-29,1589,7.2,DataVision Ltd -AI00561,Machine Learning Engineer,236251,SGD,307126,EX,PT,Singapore,L,Singapore,100,"Tableau, Mathematics, AWS, NLP, Deep Learning",Bachelor,13,Healthcare,2024-09-04,2024-10-08,678,8,Future Systems -AI00562,AI Research Scientist,241129,AUD,325524,EX,FT,Australia,M,Australia,100,"Python, Computer Vision, Git, Scala",Bachelor,16,Manufacturing,2025-02-27,2025-03-15,962,7.5,Cloud AI Solutions -AI00563,Machine Learning Researcher,159083,USD,159083,SE,PT,Israel,L,Israel,100,"Linux, Computer Vision, Data Visualization",Bachelor,7,Education,2024-11-27,2024-12-25,1205,6.5,Quantum Computing Inc -AI00564,Computer Vision Engineer,103506,USD,103506,SE,FL,South Korea,L,South Korea,0,"Tableau, Azure, AWS",Master,8,Healthcare,2024-09-05,2024-11-10,1490,9.1,Future Systems -AI00565,Principal Data Scientist,232495,USD,232495,EX,PT,Denmark,M,Denmark,0,"Deep Learning, AWS, Azure",Master,10,Real Estate,2025-02-01,2025-04-11,2289,8.2,Future Systems -AI00566,AI Research Scientist,112744,CHF,101470,EN,CT,Switzerland,L,Switzerland,50,"AWS, Kubernetes, Hadoop, Spark",Associate,1,Gaming,2025-01-20,2025-03-28,779,5.1,Cloud AI Solutions -AI00567,Autonomous Systems Engineer,129622,USD,129622,SE,PT,South Korea,L,South Korea,0,"GCP, R, Computer Vision, PyTorch, Git",PhD,5,Energy,2024-05-21,2024-07-30,1268,5.7,TechCorp Inc -AI00568,Machine Learning Engineer,100903,EUR,85768,SE,CT,Austria,S,Austria,0,"Docker, Python, AWS, Spark, TensorFlow",Bachelor,5,Education,2024-06-21,2024-08-28,683,8.2,Future Systems -AI00569,Principal Data Scientist,238019,EUR,202316,EX,FL,Austria,M,Estonia,0,"Python, Kubernetes, TensorFlow, Azure",Bachelor,11,Telecommunications,2025-02-18,2025-03-12,1577,9.7,Future Systems -AI00570,Machine Learning Engineer,41302,USD,41302,EN,PT,China,L,China,100,"GCP, Azure, NLP",Bachelor,0,Manufacturing,2024-02-09,2024-02-29,991,8,DataVision Ltd -AI00571,Deep Learning Engineer,128647,USD,128647,EX,CT,Ireland,S,Ireland,100,"SQL, Computer Vision, Python, AWS, Java",Associate,17,Real Estate,2025-01-16,2025-02-23,1579,7.8,Advanced Robotics -AI00572,AI Software Engineer,52696,EUR,44792,EN,FL,France,S,France,50,"Docker, Kubernetes, Python, GCP",PhD,0,Government,2024-06-06,2024-06-20,1102,5.6,Machine Intelligence Group -AI00573,Principal Data Scientist,229071,GBP,171803,EX,FT,United Kingdom,L,United Kingdom,0,"Java, Python, Data Visualization, MLOps",Associate,19,Education,2024-07-16,2024-08-19,629,8.8,Quantum Computing Inc -AI00574,Autonomous Systems Engineer,215282,USD,215282,EX,FL,Denmark,M,Denmark,50,"MLOps, NLP, Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-06-17,2024-08-13,528,7.8,Algorithmic Solutions -AI00575,Principal Data Scientist,199110,EUR,169244,EX,FT,France,S,Ukraine,0,"TensorFlow, Hadoop, Kubernetes, SQL",Master,10,Finance,2024-05-01,2024-06-16,908,5.5,Future Systems -AI00576,NLP Engineer,75004,USD,75004,EN,FT,United States,L,United States,50,"Computer Vision, Linux, Spark, Hadoop",Bachelor,1,Technology,2024-08-30,2024-09-27,786,8.5,Smart Analytics -AI00577,Research Scientist,149575,USD,149575,SE,PT,Israel,L,Israel,50,"Linux, PyTorch, Git, R",Master,6,Transportation,2024-03-11,2024-04-21,821,9.5,Cloud AI Solutions -AI00578,Deep Learning Engineer,138904,USD,138904,EX,CT,Israel,S,Israel,50,"Scala, Python, Deep Learning",Master,15,Telecommunications,2025-04-06,2025-05-31,1452,5.4,Autonomous Tech -AI00579,Computer Vision Engineer,133658,SGD,173755,SE,FL,Singapore,L,Singapore,50,"Kubernetes, R, Mathematics",Master,7,Telecommunications,2025-01-30,2025-04-09,1637,8.8,Cognitive Computing -AI00580,Research Scientist,148968,EUR,126623,EX,FT,Austria,S,Mexico,0,"Spark, Scala, Hadoop, Computer Vision",PhD,10,Education,2024-12-01,2025-01-28,2122,5.7,Neural Networks Co -AI00581,AI Product Manager,87661,JPY,9642710,MI,PT,Japan,S,Japan,100,"Data Visualization, Hadoop, PyTorch, NLP",Master,3,Finance,2024-04-30,2024-05-25,885,5.9,Cognitive Computing -AI00582,Data Analyst,235575,CAD,294469,EX,PT,Canada,L,Japan,0,"Scala, Tableau, Linux, PyTorch, Spark",Master,12,Technology,2024-02-13,2024-03-13,2033,6.8,Machine Intelligence Group -AI00583,Computer Vision Engineer,195175,USD,195175,EX,PT,Israel,S,Israel,100,"AWS, Spark, PyTorch, Kubernetes, Tableau",Master,14,Real Estate,2025-02-19,2025-03-28,1435,7.1,AI Innovations -AI00584,Data Engineer,143318,CAD,179148,SE,PT,Canada,M,Canada,100,"GCP, PyTorch, Tableau, Git",Master,8,Energy,2024-07-18,2024-08-01,2002,9.3,AI Innovations -AI00585,Machine Learning Engineer,102959,CHF,92663,EN,FL,Switzerland,L,Switzerland,100,"Scala, Hadoop, Docker",Master,1,Finance,2024-07-15,2024-08-26,1849,7.7,Advanced Robotics -AI00586,ML Ops Engineer,90379,AUD,122012,MI,FL,Australia,S,Italy,100,"Data Visualization, Docker, Python, TensorFlow",Master,4,Finance,2025-04-20,2025-07-02,1029,7.5,Predictive Systems -AI00587,Principal Data Scientist,71203,CAD,89004,EN,FT,Canada,M,Canada,100,"TensorFlow, Git, SQL, Kubernetes, Java",Associate,0,Energy,2025-03-24,2025-04-27,1537,6.2,Advanced Robotics -AI00588,AI Consultant,177188,EUR,150610,EX,FL,Netherlands,S,Netherlands,100,"Scala, AWS, Git",Bachelor,13,Manufacturing,2025-01-06,2025-01-23,1619,8.6,Machine Intelligence Group -AI00589,Machine Learning Engineer,95416,USD,95416,MI,CT,Sweden,M,Brazil,100,"Java, Docker, Computer Vision, Linux, Mathematics",Master,2,Technology,2024-05-24,2024-06-09,938,5.6,Cognitive Computing -AI00590,Head of AI,89044,USD,89044,EN,CT,Norway,L,Czech Republic,50,"SQL, PyTorch, Tableau",PhD,1,Government,2024-04-11,2024-06-19,1762,7.2,Quantum Computing Inc -AI00591,NLP Engineer,78263,EUR,66524,EN,PT,Netherlands,M,Ireland,100,"Python, TensorFlow, GCP",PhD,0,Energy,2024-07-10,2024-09-21,1563,6.9,Predictive Systems -AI00592,ML Ops Engineer,231654,JPY,25481940,EX,PT,Japan,M,Japan,0,"Python, Mathematics, GCP, Computer Vision, AWS",PhD,11,Finance,2024-09-08,2024-09-28,1880,10,Digital Transformation LLC -AI00593,NLP Engineer,149046,USD,149046,SE,PT,Sweden,L,Sweden,0,"Python, Kubernetes, TensorFlow, Computer Vision, PyTorch",Associate,9,Technology,2024-08-19,2024-09-30,2359,5.5,Predictive Systems -AI00594,Machine Learning Researcher,84232,CAD,105290,MI,CT,Canada,S,Canada,100,"GCP, Scala, Azure, Statistics",Master,4,Gaming,2024-12-23,2025-01-29,537,7,Machine Intelligence Group -AI00595,ML Ops Engineer,94348,CAD,117935,SE,FT,Canada,S,Canada,50,"GCP, SQL, Spark, Linux",Master,7,Energy,2024-03-02,2024-04-12,527,7.4,DataVision Ltd -AI00596,Data Engineer,128839,USD,128839,SE,FL,Finland,M,Finland,50,"Mathematics, Statistics, Deep Learning, Java, Kubernetes",PhD,6,Retail,2024-11-05,2025-01-13,2263,8.5,Algorithmic Solutions -AI00597,AI Architect,166829,EUR,141805,SE,FL,Netherlands,L,Netherlands,100,"AWS, Kubernetes, Deep Learning",Associate,5,Consulting,2024-11-02,2024-11-30,2187,9.3,Cloud AI Solutions -AI00598,AI Software Engineer,67959,GBP,50969,EN,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, NLP, TensorFlow, Spark",PhD,1,Real Estate,2024-01-02,2024-01-20,599,7.4,Machine Intelligence Group -AI00599,AI Architect,80303,AUD,108409,MI,FT,Australia,M,Australia,50,"Python, GCP, Git, Java, Mathematics",Bachelor,4,Healthcare,2024-08-09,2024-10-07,812,9.3,Smart Analytics -AI00600,Data Engineer,104350,EUR,88698,MI,FL,Netherlands,S,Netherlands,50,"MLOps, Mathematics, Git",Bachelor,2,Transportation,2024-02-04,2024-04-04,2112,7.4,Algorithmic Solutions -AI00601,AI Consultant,146664,EUR,124664,SE,PT,Netherlands,L,Netherlands,50,"Python, SQL, Computer Vision, Java",PhD,8,Automotive,2024-04-04,2024-05-29,589,8.1,Machine Intelligence Group -AI00602,AI Software Engineer,119423,EUR,101510,SE,PT,Germany,M,Germany,50,"GCP, TensorFlow, Computer Vision, AWS",Master,9,Gaming,2024-11-19,2024-12-31,1840,9,Algorithmic Solutions -AI00603,AI Consultant,31988,USD,31988,EN,PT,China,M,China,50,"Docker, Mathematics, Scala",PhD,0,Automotive,2024-01-14,2024-02-20,2450,6.1,Future Systems -AI00604,AI Architect,94563,GBP,70922,EN,FT,United Kingdom,L,United Kingdom,50,"Git, TensorFlow, Deep Learning, Azure, Computer Vision",Bachelor,1,Finance,2024-01-05,2024-03-01,1461,9.7,DeepTech Ventures -AI00605,Autonomous Systems Engineer,85269,USD,85269,EN,FL,Ireland,L,Ireland,50,"MLOps, Deep Learning, PyTorch",Bachelor,0,Technology,2024-02-11,2024-03-30,953,7.9,DeepTech Ventures -AI00606,AI Architect,87092,USD,87092,EN,PT,Israel,L,Israel,50,"Kubernetes, Statistics, Scala",PhD,0,Healthcare,2024-02-25,2024-04-14,1931,9.9,Predictive Systems -AI00607,Machine Learning Researcher,75721,USD,75721,EN,FT,Finland,L,China,100,"Docker, Git, Python, Mathematics",PhD,1,Manufacturing,2024-07-05,2024-09-12,2487,5.1,DeepTech Ventures -AI00608,Research Scientist,158003,USD,158003,SE,FT,Sweden,L,Sweden,0,"Python, SQL, Tableau, Data Visualization",Master,7,Government,2025-04-20,2025-06-22,634,5.9,Future Systems -AI00609,Autonomous Systems Engineer,189198,JPY,20811780,EX,FL,Japan,M,Japan,0,"Computer Vision, Spark, Data Visualization, Java",Associate,18,Finance,2024-03-27,2024-06-01,2153,6.9,AI Innovations -AI00610,Research Scientist,57287,EUR,48694,EN,FL,France,M,France,100,"AWS, PyTorch, Computer Vision, GCP, Scala",Associate,1,Technology,2024-10-15,2024-12-08,1413,7.1,Machine Intelligence Group -AI00611,AI Specialist,116891,GBP,87668,MI,FT,United Kingdom,L,Japan,0,"TensorFlow, PyTorch, GCP, NLP",Bachelor,2,Education,2024-12-31,2025-03-11,865,8.1,Autonomous Tech -AI00612,Autonomous Systems Engineer,86678,USD,86678,MI,FT,Sweden,S,Hungary,50,"AWS, Mathematics, GCP, Git",Associate,4,Telecommunications,2025-04-08,2025-05-19,1812,6.6,Autonomous Tech -AI00613,Research Scientist,237261,EUR,201672,EX,PT,Germany,L,Germany,50,"Mathematics, Scala, PyTorch",Bachelor,16,Government,2024-06-04,2024-07-26,686,7.1,Neural Networks Co -AI00614,Data Engineer,340350,CHF,306315,EX,FT,Switzerland,L,France,0,"Python, Spark, Deep Learning, Azure, TensorFlow",PhD,17,Gaming,2024-07-14,2024-08-13,2373,7.2,Algorithmic Solutions -AI00615,Data Scientist,143376,USD,143376,SE,FL,Norway,S,Norway,50,"PyTorch, Mathematics, Deep Learning, Linux, AWS",Associate,8,Transportation,2025-04-06,2025-05-25,1159,7.7,Advanced Robotics -AI00616,Robotics Engineer,212213,CHF,190992,SE,FL,Switzerland,M,Switzerland,0,"Azure, SQL, Kubernetes, NLP",Associate,9,Consulting,2024-03-19,2024-04-30,1213,6.8,Autonomous Tech -AI00617,Principal Data Scientist,147392,SGD,191610,SE,CT,Singapore,L,Finland,100,"NLP, MLOps, SQL, Linux",Associate,5,Automotive,2025-03-03,2025-03-23,1701,5.8,AI Innovations -AI00618,Machine Learning Engineer,93630,USD,93630,SE,PT,Finland,S,Finland,50,"Kubernetes, SQL, PyTorch",Master,6,Energy,2025-02-27,2025-03-24,1022,6.5,Neural Networks Co -AI00619,AI Software Engineer,99867,CHF,89880,EN,FT,Switzerland,M,Switzerland,0,"Python, Git, TensorFlow",Master,0,Healthcare,2024-06-27,2024-08-09,1864,6.4,Advanced Robotics -AI00620,NLP Engineer,167900,CHF,151110,MI,FL,Switzerland,L,India,100,"Python, AWS, TensorFlow, Data Visualization, Computer Vision",Bachelor,3,Automotive,2025-03-25,2025-05-22,2095,5,DeepTech Ventures -AI00621,Computer Vision Engineer,113585,USD,113585,MI,FL,Norway,S,Egypt,50,"Computer Vision, Python, Statistics, TensorFlow",Associate,4,Government,2024-12-12,2025-01-27,1077,8.5,Digital Transformation LLC -AI00622,AI Software Engineer,88040,GBP,66030,MI,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, AWS, PyTorch, Deep Learning, Data Visualization",PhD,2,Finance,2024-08-03,2024-10-04,1715,8.2,Quantum Computing Inc -AI00623,Autonomous Systems Engineer,234891,USD,234891,EX,CT,South Korea,L,South Korea,0,"Spark, Scala, Statistics, Computer Vision",Master,19,Retail,2024-08-26,2024-09-22,2055,7,Future Systems -AI00624,Machine Learning Researcher,55689,EUR,47336,EN,PT,Austria,L,Austria,50,"Python, Mathematics, Deep Learning, Linux, GCP",Master,1,Government,2024-11-28,2025-01-27,1296,7.5,Predictive Systems -AI00625,Deep Learning Engineer,192002,EUR,163202,EX,FT,France,S,Japan,50,"MLOps, Java, Linux, Hadoop, PyTorch",PhD,15,Education,2024-08-21,2024-09-19,1600,8.8,DataVision Ltd -AI00626,Research Scientist,88478,USD,88478,EX,CT,India,L,India,100,"R, AWS, Mathematics",Bachelor,12,Education,2024-02-05,2024-03-18,703,6.5,Neural Networks Co -AI00627,ML Ops Engineer,233768,EUR,198703,EX,FT,Austria,M,Austria,50,"Python, Azure, Scala, AWS",Master,13,Manufacturing,2024-10-06,2024-11-12,2390,5.4,Autonomous Tech -AI00628,Autonomous Systems Engineer,394510,CHF,355059,EX,PT,Switzerland,L,Switzerland,0,"MLOps, Java, Statistics, Deep Learning, SQL",Master,18,Finance,2024-02-15,2024-04-28,1628,9.6,Smart Analytics -AI00629,AI Research Scientist,96275,CHF,86648,EN,FT,Switzerland,S,Switzerland,0,"Python, NLP, GCP, Docker, Java",PhD,0,Gaming,2024-01-09,2024-02-16,2313,7.4,Neural Networks Co -AI00630,Data Scientist,67084,USD,67084,SE,PT,China,M,Japan,100,"SQL, MLOps, Java",Associate,5,Government,2024-06-21,2024-07-18,852,8.7,AI Innovations -AI00631,Head of AI,87326,USD,87326,MI,PT,South Korea,M,South Africa,100,"PyTorch, NLP, MLOps",PhD,3,Retail,2024-06-17,2024-07-21,1777,7,Future Systems -AI00632,Research Scientist,88829,USD,88829,MI,PT,Finland,M,Belgium,50,"SQL, Linux, Deep Learning, Scala",Master,3,Consulting,2024-04-23,2024-07-05,1733,7.3,Cognitive Computing -AI00633,Autonomous Systems Engineer,110532,USD,110532,MI,FL,Denmark,M,Denmark,50,"Computer Vision, Mathematics, NLP",PhD,3,Manufacturing,2024-09-27,2024-11-05,2039,8.5,Future Systems -AI00634,AI Product Manager,60357,USD,60357,EN,CT,South Korea,L,Belgium,0,"Azure, TensorFlow, NLP, Python, PyTorch",Associate,0,Media,2024-03-06,2024-04-05,562,9.6,DataVision Ltd -AI00635,AI Research Scientist,315064,CHF,283558,EX,FL,Switzerland,S,Switzerland,0,"NLP, Git, Scala, Hadoop, Docker",Bachelor,18,Real Estate,2024-04-15,2024-05-18,1191,9.6,Cognitive Computing -AI00636,AI Software Engineer,70097,USD,70097,EN,PT,Denmark,S,Denmark,100,"Git, Python, TensorFlow",PhD,0,Finance,2025-04-13,2025-06-10,2054,5.4,Quantum Computing Inc -AI00637,Principal Data Scientist,117235,USD,117235,SE,FL,Ireland,M,Ireland,50,"Scala, Git, Azure",PhD,6,Government,2025-01-24,2025-03-30,1962,7.4,Autonomous Tech -AI00638,Principal Data Scientist,65851,USD,65851,EN,FT,Sweden,S,Turkey,100,"Hadoop, Python, Statistics, Scala",Associate,0,Energy,2025-01-03,2025-03-06,692,8.3,Quantum Computing Inc -AI00639,Computer Vision Engineer,84191,JPY,9261010,MI,FL,Japan,M,Japan,100,"R, Docker, Git, GCP, Statistics",Master,2,Consulting,2024-07-20,2024-09-06,1495,8.2,TechCorp Inc -AI00640,NLP Engineer,134590,USD,134590,MI,FT,Norway,M,Norway,0,"Python, SQL, Docker, TensorFlow, Tableau",PhD,2,Manufacturing,2024-04-12,2024-06-07,1564,8.4,AI Innovations -AI00641,AI Product Manager,139686,AUD,188576,SE,FL,Australia,M,Australia,100,"NLP, SQL, GCP, Tableau",Master,6,Education,2024-03-25,2024-04-28,2364,8.3,Smart Analytics -AI00642,AI Software Engineer,115226,USD,115226,SE,PT,South Korea,L,South Korea,0,"Python, Kubernetes, TensorFlow",Bachelor,5,Telecommunications,2025-04-19,2025-05-03,1761,5.9,Quantum Computing Inc -AI00643,Deep Learning Engineer,262115,EUR,222798,EX,PT,Netherlands,L,Netherlands,0,"Java, GCP, Computer Vision",Associate,12,Consulting,2024-05-08,2024-07-07,736,9.2,Algorithmic Solutions -AI00644,Data Scientist,111532,EUR,94802,SE,FL,Austria,S,Austria,50,"NLP, Java, Computer Vision, R, Deep Learning",Master,6,Gaming,2024-07-03,2024-07-17,517,5.4,Algorithmic Solutions -AI00645,Research Scientist,267795,SGD,348134,EX,CT,Singapore,M,Egypt,50,"Java, Azure, Kubernetes, PyTorch, Docker",Associate,11,Transportation,2024-10-07,2024-11-10,1026,5.4,DeepTech Ventures -AI00646,AI Software Engineer,63052,EUR,53594,EN,FT,France,M,United Kingdom,100,"Scala, Python, MLOps",Master,0,Retail,2024-02-05,2024-03-22,1183,6.6,Cognitive Computing -AI00647,AI Architect,54424,USD,54424,EN,FL,United States,S,Austria,0,"R, Kubernetes, Mathematics, Hadoop, SQL",PhD,1,Energy,2024-01-02,2024-01-21,1220,9.2,DeepTech Ventures -AI00648,AI Software Engineer,67908,USD,67908,SE,FT,China,M,Colombia,100,"Git, Spark, AWS, Scala",Bachelor,6,Gaming,2024-01-21,2024-02-28,2163,9.4,Smart Analytics -AI00649,ML Ops Engineer,115395,GBP,86546,SE,FL,United Kingdom,S,United Kingdom,100,"R, Kubernetes, Data Visualization",Bachelor,6,Government,2024-10-28,2024-12-30,1312,7.8,Predictive Systems -AI00650,Data Scientist,122516,AUD,165397,SE,FT,Australia,S,South Africa,100,"Deep Learning, Python, Git, Kubernetes, GCP",Master,9,Transportation,2024-07-23,2024-10-03,2397,8.7,AI Innovations -AI00651,Machine Learning Researcher,118846,EUR,101019,SE,FL,France,S,France,50,"SQL, AWS, NLP, PyTorch, Computer Vision",PhD,5,Manufacturing,2024-10-06,2024-11-11,1725,9.3,Machine Intelligence Group -AI00652,Machine Learning Engineer,98835,USD,98835,MI,FT,Sweden,M,Sweden,0,"AWS, Deep Learning, TensorFlow",Bachelor,2,Consulting,2024-02-06,2024-03-15,705,9.3,Neural Networks Co -AI00653,Data Engineer,295640,USD,295640,EX,FT,United States,M,United States,0,"AWS, GCP, Git, SQL",Master,11,Media,2024-01-08,2024-02-14,1782,8.3,Machine Intelligence Group -AI00654,Machine Learning Engineer,136359,SGD,177267,SE,CT,Singapore,M,Singapore,50,"R, Deep Learning, MLOps",Bachelor,9,Telecommunications,2024-08-30,2024-09-28,769,9.6,TechCorp Inc -AI00655,Principal Data Scientist,187425,USD,187425,EX,CT,Sweden,L,Sweden,0,"SQL, TensorFlow, Docker, Python, GCP",PhD,13,Consulting,2025-02-05,2025-02-25,1415,9.3,Cognitive Computing -AI00656,Machine Learning Engineer,91932,USD,91932,MI,FL,Sweden,M,Sweden,50,"MLOps, Kubernetes, Tableau, Scala",PhD,2,Manufacturing,2024-09-06,2024-10-18,1272,6.8,TechCorp Inc -AI00657,AI Software Engineer,71409,USD,71409,EN,FT,United States,L,United States,0,"Git, Linux, Data Visualization, Deep Learning",PhD,0,Telecommunications,2024-01-23,2024-03-17,1482,9.7,Neural Networks Co -AI00658,Machine Learning Engineer,48739,USD,48739,EN,FL,Ireland,S,Latvia,50,"Python, TensorFlow, Linux, PyTorch",PhD,0,Retail,2024-03-28,2024-05-11,1628,5.1,Predictive Systems -AI00659,AI Architect,61632,EUR,52387,EN,CT,Germany,S,Colombia,50,"Spark, Kubernetes, Data Visualization, Hadoop",Bachelor,1,Real Estate,2025-02-05,2025-02-19,910,6.1,Cloud AI Solutions -AI00660,Machine Learning Researcher,98216,JPY,10803760,MI,CT,Japan,S,New Zealand,0,"Spark, Deep Learning, NLP, PyTorch, Data Visualization",PhD,4,Energy,2024-04-16,2024-06-22,1612,6.4,DataVision Ltd -AI00661,AI Product Manager,104633,EUR,88938,SE,FL,Germany,S,Germany,100,"PyTorch, Spark, Tableau, Data Visualization",Master,6,Education,2024-08-06,2024-10-17,1922,7.3,Digital Transformation LLC -AI00662,AI Software Engineer,41990,USD,41990,MI,CT,China,L,India,100,"Scala, Azure, Deep Learning, Spark, Git",Associate,2,Government,2024-07-30,2024-09-24,1928,9.8,Autonomous Tech -AI00663,Data Analyst,238728,SGD,310346,EX,CT,Singapore,S,Singapore,0,"Python, MLOps, TensorFlow, NLP, Tableau",Master,12,Gaming,2024-08-25,2024-10-04,2000,7.7,Algorithmic Solutions -AI00664,AI Consultant,329444,CHF,296500,EX,FL,Switzerland,M,Switzerland,100,"Hadoop, Scala, Linux, Python",Bachelor,14,Real Estate,2024-12-27,2025-02-10,1268,8,Smart Analytics -AI00665,Research Scientist,70081,USD,70081,EN,FT,Israel,L,Israel,100,"Hadoop, R, Tableau, Python",Bachelor,1,Government,2024-04-20,2024-06-20,1280,7.4,AI Innovations -AI00666,Head of AI,288084,USD,288084,EX,FT,Denmark,L,Denmark,0,"Docker, Hadoop, Linux",Associate,15,Education,2024-10-06,2024-12-15,1022,7.1,Autonomous Tech -AI00667,AI Consultant,65282,USD,65282,MI,FL,Israel,S,Israel,100,"Scala, Tableau, NLP",Associate,2,Consulting,2024-03-22,2024-05-19,2126,5.5,TechCorp Inc -AI00668,Machine Learning Engineer,126052,SGD,163868,SE,PT,Singapore,S,Singapore,50,"Java, Scala, MLOps, R, Linux",PhD,6,Consulting,2024-07-23,2024-09-18,1915,7.4,DataVision Ltd -AI00669,Data Scientist,247685,USD,247685,EX,PT,Ireland,M,South Africa,100,"Data Visualization, SQL, Linux, Scala",PhD,12,Automotive,2025-03-28,2025-05-31,1375,7.5,Cognitive Computing -AI00670,AI Software Engineer,80022,GBP,60017,MI,FL,United Kingdom,M,United Kingdom,0,"Linux, PyTorch, Python, Statistics, Deep Learning",Master,3,Energy,2024-03-11,2024-04-21,603,5.5,Smart Analytics -AI00671,Data Analyst,96062,SGD,124881,EN,CT,Singapore,L,Singapore,0,"SQL, Scala, Data Visualization",Associate,1,Finance,2024-09-11,2024-11-08,2460,8.6,Algorithmic Solutions -AI00672,Principal Data Scientist,174460,USD,174460,SE,FL,Denmark,L,Denmark,100,"R, Mathematics, Python, Data Visualization, Docker",Master,9,Media,2025-02-27,2025-04-16,960,8.7,Smart Analytics -AI00673,AI Software Engineer,183335,EUR,155835,EX,PT,Austria,M,Austria,100,"NLP, PyTorch, Hadoop, Tableau, SQL",PhD,12,Education,2024-04-24,2024-05-30,897,8.4,Neural Networks Co -AI00674,Data Engineer,223437,USD,223437,EX,FL,Sweden,M,Sweden,100,"Linux, R, SQL, AWS",Bachelor,18,Gaming,2025-02-14,2025-03-24,2274,6.2,Neural Networks Co -AI00675,AI Specialist,177360,USD,177360,SE,PT,Denmark,L,Turkey,50,"Azure, TensorFlow, SQL",Bachelor,6,Consulting,2024-07-23,2024-09-18,1564,7.1,AI Innovations -AI00676,AI Consultant,206532,JPY,22718520,EX,FT,Japan,M,Canada,100,"SQL, Deep Learning, MLOps, Linux",Bachelor,10,Technology,2024-02-22,2024-03-09,1130,6.4,Cloud AI Solutions -AI00677,Robotics Engineer,112216,EUR,95384,MI,CT,Austria,L,Austria,100,"Deep Learning, TensorFlow, Kubernetes",PhD,4,Energy,2024-12-10,2024-12-25,715,6.3,Algorithmic Solutions -AI00678,AI Software Engineer,55817,CAD,69771,EN,PT,Canada,S,Canada,100,"Python, Azure, Deep Learning, SQL",Associate,0,Technology,2025-01-24,2025-03-23,1550,6.1,Autonomous Tech -AI00679,AI Specialist,324267,USD,324267,EX,CT,Norway,L,Norway,50,"Scala, Java, Mathematics",PhD,11,Finance,2024-04-05,2024-06-05,1346,6.5,Predictive Systems -AI00680,NLP Engineer,76065,JPY,8367150,MI,FT,Japan,S,Japan,50,"R, SQL, Kubernetes, Java",PhD,4,Education,2025-02-21,2025-04-10,1473,5.6,Predictive Systems -AI00681,Machine Learning Researcher,146849,CHF,132164,SE,PT,Switzerland,M,Spain,0,"Azure, SQL, MLOps",PhD,8,Education,2024-07-17,2024-08-17,1337,7.4,Predictive Systems -AI00682,Head of AI,81041,SGD,105353,EN,FL,Singapore,M,India,50,"Kubernetes, SQL, PyTorch",PhD,0,Healthcare,2025-02-12,2025-04-21,722,5.5,Advanced Robotics -AI00683,Computer Vision Engineer,106945,USD,106945,EN,PT,United States,L,Malaysia,100,"Tableau, Java, AWS, Data Visualization, Scala",PhD,0,Government,2024-02-11,2024-04-01,615,9.4,Quantum Computing Inc -AI00684,Robotics Engineer,329543,USD,329543,EX,PT,Denmark,L,Singapore,100,"Data Visualization, Scala, Statistics, NLP, Hadoop",Associate,18,Technology,2024-08-01,2024-09-21,553,8.4,Neural Networks Co -AI00685,Machine Learning Engineer,92316,USD,92316,SE,CT,Israel,S,United States,100,"Kubernetes, Deep Learning, Scala, PyTorch, R",Associate,6,Transportation,2024-12-27,2025-03-08,834,7.2,Cognitive Computing -AI00686,AI Research Scientist,209495,JPY,23044450,EX,FL,Japan,S,Japan,100,"TensorFlow, AWS, Kubernetes",PhD,19,Government,2025-03-15,2025-05-18,1511,6.9,AI Innovations -AI00687,Data Analyst,201545,USD,201545,EX,CT,Ireland,L,Australia,0,"Scala, Mathematics, Spark, Kubernetes",PhD,17,Telecommunications,2024-09-16,2024-11-23,1552,6.7,Cloud AI Solutions -AI00688,Principal Data Scientist,122321,CAD,152901,SE,PT,Canada,S,Canada,0,"Hadoop, Python, Deep Learning",Master,6,Consulting,2024-09-28,2024-12-05,2048,6.1,Cloud AI Solutions -AI00689,Machine Learning Researcher,120647,CHF,108582,EN,CT,Switzerland,L,Switzerland,50,"Tableau, MLOps, Data Visualization",Bachelor,0,Manufacturing,2024-07-26,2024-10-04,1544,9.1,Algorithmic Solutions -AI00690,Data Analyst,56584,USD,56584,EN,FL,South Korea,S,Sweden,100,"Tableau, Mathematics, Kubernetes, Git",Bachelor,0,Consulting,2024-02-10,2024-04-17,1670,5.3,AI Innovations -AI00691,AI Architect,143314,CHF,128983,SE,CT,Switzerland,S,Australia,50,"Hadoop, Java, GCP",Bachelor,8,Finance,2024-09-02,2024-10-31,2319,8,Autonomous Tech -AI00692,NLP Engineer,130879,JPY,14396690,SE,PT,Japan,M,Japan,0,"Python, Azure, MLOps",Master,6,Real Estate,2024-04-12,2024-06-19,2280,5.4,Cloud AI Solutions -AI00693,Machine Learning Engineer,79223,AUD,106951,MI,FL,Australia,S,Egypt,100,"Java, Kubernetes, R, Azure",Associate,4,Government,2024-11-15,2024-12-29,1232,5.5,Quantum Computing Inc -AI00694,Deep Learning Engineer,145545,USD,145545,SE,FL,Norway,M,Norway,100,"Docker, Tableau, Hadoop, Computer Vision",Bachelor,5,Retail,2025-01-21,2025-03-14,1802,8.8,TechCorp Inc -AI00695,Computer Vision Engineer,100393,JPY,11043230,MI,PT,Japan,L,Japan,50,"Java, Spark, AWS",Master,3,Education,2024-09-07,2024-10-21,947,9.2,Neural Networks Co -AI00696,AI Software Engineer,197280,USD,197280,EX,FT,Ireland,S,Ireland,100,"TensorFlow, Kubernetes, Linux, NLP",Master,16,Telecommunications,2024-08-05,2024-09-08,777,6,Autonomous Tech -AI00697,Computer Vision Engineer,88090,USD,88090,MI,FT,South Korea,M,South Korea,100,"Python, Computer Vision, Scala, Spark, TensorFlow",Associate,3,Retail,2025-01-02,2025-02-08,1674,10,AI Innovations -AI00698,Computer Vision Engineer,69911,USD,69911,MI,FT,South Korea,S,South Korea,100,"Kubernetes, TensorFlow, GCP",Master,3,Automotive,2024-09-12,2024-11-16,582,7.3,DataVision Ltd -AI00699,ML Ops Engineer,218971,CHF,197074,EX,FL,Switzerland,M,Switzerland,0,"Mathematics, Python, Tableau, AWS",Associate,18,Telecommunications,2025-03-22,2025-04-06,1989,6.5,Digital Transformation LLC -AI00700,AI Product Manager,79860,EUR,67881,EN,FT,Austria,L,Austria,50,"Mathematics, NLP, Tableau, Java",Bachelor,0,Government,2025-04-26,2025-05-23,2214,7.6,TechCorp Inc -AI00701,AI Architect,118343,CAD,147929,SE,CT,Canada,M,Indonesia,100,"GCP, PyTorch, AWS, Tableau, Kubernetes",Master,9,Automotive,2024-11-03,2024-11-29,2230,5.7,Advanced Robotics -AI00702,Research Scientist,142832,USD,142832,SE,FL,Finland,L,Finland,100,"Spark, Deep Learning, Python, AWS",Bachelor,6,Consulting,2024-12-14,2025-02-24,2222,6,Neural Networks Co -AI00703,Computer Vision Engineer,103304,EUR,87808,SE,CT,France,S,South Korea,0,"Deep Learning, SQL, Mathematics, Kubernetes, Tableau",Master,9,Media,2024-08-06,2024-09-15,1382,9.6,Neural Networks Co -AI00704,NLP Engineer,51555,USD,51555,SE,FT,India,M,India,50,"Java, R, NLP",PhD,6,Technology,2024-12-15,2025-01-17,1452,8,AI Innovations -AI00705,Robotics Engineer,33564,USD,33564,MI,FT,India,L,Israel,0,"Scala, Tableau, Kubernetes, Deep Learning",Associate,4,Media,2024-03-30,2024-05-06,562,5.8,DataVision Ltd -AI00706,AI Specialist,46733,USD,46733,MI,FT,China,S,Ireland,50,"Scala, PyTorch, Data Visualization, SQL, Java",Associate,3,Media,2024-12-20,2025-02-09,777,9.4,Digital Transformation LLC -AI00707,AI Architect,163489,EUR,138966,SE,FL,Germany,L,Germany,50,"Spark, Python, TensorFlow, NLP",Bachelor,8,Technology,2024-11-16,2025-01-24,1573,9.4,Machine Intelligence Group -AI00708,AI Consultant,127499,SGD,165749,SE,CT,Singapore,M,Singapore,100,"Docker, R, GCP, Scala, Hadoop",Master,9,Government,2024-11-29,2025-01-22,830,9.8,AI Innovations -AI00709,Head of AI,169543,EUR,144112,SE,FT,Germany,L,Germany,50,"Statistics, Git, Linux, Hadoop, Kubernetes",PhD,8,Energy,2024-09-24,2024-10-28,1703,5.1,DeepTech Ventures -AI00710,AI Specialist,252321,EUR,214473,EX,FT,France,L,France,100,"Statistics, AWS, Azure",Bachelor,14,Education,2024-04-05,2024-05-07,966,9.9,Smart Analytics -AI00711,Robotics Engineer,83888,GBP,62916,MI,FT,United Kingdom,M,United Kingdom,100,"MLOps, Deep Learning, Docker, Spark",Master,2,Technology,2025-03-04,2025-04-02,1553,6.1,Quantum Computing Inc -AI00712,NLP Engineer,117983,AUD,159277,SE,FT,Australia,M,Finland,50,"Computer Vision, Data Visualization, Java",Associate,5,Media,2024-03-08,2024-04-07,2450,7.8,DeepTech Ventures -AI00713,Research Scientist,153305,SGD,199297,EX,FL,Singapore,M,Singapore,100,"R, Docker, Scala, Mathematics, PyTorch",PhD,19,Education,2025-03-03,2025-03-22,824,7.7,Smart Analytics -AI00714,Deep Learning Engineer,112643,JPY,12390730,SE,FT,Japan,S,Japan,50,"PyTorch, Python, TensorFlow, Mathematics, AWS",Associate,9,Gaming,2024-12-31,2025-03-13,1976,6.1,Predictive Systems -AI00715,AI Product Manager,64605,USD,64605,EN,FT,Norway,S,Norway,50,"Deep Learning, MLOps, Python",Associate,1,Gaming,2025-02-26,2025-03-14,875,8.6,Cloud AI Solutions -AI00716,Autonomous Systems Engineer,62679,EUR,53277,MI,CT,France,S,Ireland,50,"R, SQL, Kubernetes, Azure, TensorFlow",PhD,3,Consulting,2024-08-13,2024-09-08,819,7,Cognitive Computing -AI00717,AI Consultant,161602,EUR,137362,EX,PT,France,L,France,100,"Hadoop, Kubernetes, Git, Docker",Associate,11,Automotive,2024-02-20,2024-03-20,2361,9,Advanced Robotics -AI00718,Computer Vision Engineer,124703,GBP,93527,SE,PT,United Kingdom,M,Latvia,0,"AWS, PyTorch, Tableau",Bachelor,6,Healthcare,2024-09-30,2024-11-13,1138,8.4,Cognitive Computing -AI00719,Head of AI,200853,USD,200853,EX,FT,Israel,M,Israel,50,"R, Statistics, SQL, Deep Learning",Master,13,Technology,2024-11-11,2025-01-17,1274,7.5,Algorithmic Solutions -AI00720,ML Ops Engineer,34021,USD,34021,MI,PT,India,S,India,50,"Git, Python, GCP, SQL, Java",PhD,2,Energy,2024-02-15,2024-03-25,2324,5.3,Cognitive Computing -AI00721,Robotics Engineer,90355,EUR,76802,MI,CT,Germany,M,Germany,50,"Deep Learning, Data Visualization, NLP, R",Bachelor,2,Energy,2024-11-17,2024-12-20,2458,9.4,Future Systems -AI00722,Machine Learning Engineer,63360,USD,63360,EN,FL,Ireland,M,Ireland,100,"Computer Vision, MLOps, SQL, Docker, PyTorch",Master,1,Telecommunications,2024-10-22,2024-11-19,1383,5.1,DataVision Ltd -AI00723,Data Analyst,185352,USD,185352,EX,PT,Ireland,S,New Zealand,0,"Scala, MLOps, Data Visualization",Bachelor,10,Government,2024-09-27,2024-11-06,1306,6.1,Advanced Robotics -AI00724,AI Software Engineer,85462,SGD,111101,EN,FT,Singapore,L,Switzerland,50,"NLP, Kubernetes, Git",Master,1,Transportation,2024-05-11,2024-06-27,591,9.9,Predictive Systems -AI00725,AI Product Manager,119183,EUR,101306,SE,PT,Austria,L,Austria,100,"Git, MLOps, Spark, Linux, Hadoop",Associate,9,Telecommunications,2025-01-16,2025-02-23,2480,9.5,Digital Transformation LLC -AI00726,Machine Learning Engineer,116244,EUR,98807,SE,CT,Austria,M,Austria,50,"R, Kubernetes, Spark",Bachelor,6,Technology,2024-02-02,2024-03-04,1029,6.1,Algorithmic Solutions -AI00727,Machine Learning Researcher,287291,USD,287291,EX,FT,Norway,S,Norway,50,"Scala, R, Tableau",Master,19,Manufacturing,2024-08-27,2024-10-31,1944,9.3,Quantum Computing Inc -AI00728,Data Engineer,160191,EUR,136162,EX,FL,Germany,S,Germany,50,"Linux, Git, Statistics, Deep Learning, Java",PhD,17,Automotive,2024-11-28,2025-01-24,688,9.9,TechCorp Inc -AI00729,AI Architect,207916,USD,207916,EX,FL,South Korea,M,South Korea,100,"Kubernetes, Mathematics, Hadoop, Deep Learning",Master,15,Retail,2024-10-17,2024-11-25,1085,8.7,Algorithmic Solutions -AI00730,Deep Learning Engineer,215737,USD,215737,EX,CT,Israel,S,Israel,50,"Linux, Scala, Git, SQL",PhD,15,Manufacturing,2024-06-29,2024-08-27,1269,5.2,Neural Networks Co -AI00731,Principal Data Scientist,89008,USD,89008,EN,CT,Denmark,L,New Zealand,0,"PyTorch, AWS, MLOps",Master,0,Telecommunications,2024-01-04,2024-02-12,1540,8.3,Future Systems -AI00732,Principal Data Scientist,122155,GBP,91616,SE,PT,United Kingdom,S,United Kingdom,100,"PyTorch, Hadoop, Computer Vision",Bachelor,9,Media,2024-02-16,2024-03-27,1762,5.3,TechCorp Inc -AI00733,Data Scientist,40715,USD,40715,EN,FL,China,L,South Korea,0,"Python, NLP, Hadoop, Docker, Tableau",PhD,1,Technology,2024-07-06,2024-08-10,1018,7.9,Cloud AI Solutions -AI00734,Robotics Engineer,188499,CHF,169649,SE,PT,Switzerland,S,India,0,"Git, Data Visualization, Hadoop",Bachelor,9,Finance,2024-10-31,2024-11-18,870,6.6,Digital Transformation LLC -AI00735,AI Specialist,181167,GBP,135875,EX,PT,United Kingdom,M,Thailand,100,"Azure, MLOps, Mathematics, Docker",Bachelor,16,Transportation,2024-11-30,2025-01-25,1237,9.7,DataVision Ltd -AI00736,AI Software Engineer,137580,USD,137580,SE,CT,Denmark,M,Denmark,50,"Deep Learning, Kubernetes, AWS, Mathematics, GCP",PhD,7,Healthcare,2024-07-02,2024-09-06,1646,7.9,Neural Networks Co -AI00737,Autonomous Systems Engineer,81092,CAD,101365,EN,CT,Canada,L,India,0,"NLP, SQL, Statistics, Data Visualization, Scala",PhD,0,Finance,2025-04-27,2025-05-23,623,8.2,Digital Transformation LLC -AI00738,Principal Data Scientist,167011,EUR,141959,EX,PT,Germany,M,Russia,0,"Azure, MLOps, Python, Data Visualization, Mathematics",Master,16,Healthcare,2024-05-15,2024-06-12,2468,7.6,DeepTech Ventures -AI00739,Data Analyst,115690,SGD,150397,MI,CT,Singapore,M,Singapore,50,"Python, MLOps, Git",Master,2,Consulting,2024-11-25,2024-12-20,1357,6.2,Future Systems -AI00740,Head of AI,85081,JPY,9358910,MI,CT,Japan,M,Japan,100,"Docker, Git, Hadoop",Associate,3,Energy,2024-11-15,2024-11-29,1877,9.6,Smart Analytics -AI00741,AI Product Manager,204925,USD,204925,EX,CT,Norway,S,New Zealand,100,"TensorFlow, Azure, Scala, Kubernetes, Spark",PhD,13,Manufacturing,2025-03-10,2025-04-18,2392,5.3,Autonomous Tech -AI00742,NLP Engineer,71330,USD,71330,EN,FT,Ireland,M,Ireland,100,"Statistics, Kubernetes, Deep Learning, Scala, AWS",Master,1,Finance,2025-01-12,2025-02-03,1304,5.3,Smart Analytics -AI00743,ML Ops Engineer,147961,CHF,133165,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, Git, SQL",PhD,2,Gaming,2024-11-18,2025-01-27,2488,7,Digital Transformation LLC -AI00744,AI Architect,81537,EUR,69306,MI,PT,Germany,M,France,100,"GCP, Linux, Kubernetes",Associate,2,Media,2025-02-21,2025-03-08,1123,8.1,Quantum Computing Inc -AI00745,Autonomous Systems Engineer,169303,EUR,143908,EX,FL,Germany,M,Germany,0,"Linux, Kubernetes, AWS, Data Visualization",PhD,14,Transportation,2024-05-08,2024-07-09,1444,7,Machine Intelligence Group -AI00746,Autonomous Systems Engineer,79345,USD,79345,EN,FL,United States,L,United States,100,"Spark, Kubernetes, SQL, AWS",Associate,1,Gaming,2024-01-01,2024-03-03,2459,7.1,Cognitive Computing -AI00747,NLP Engineer,141710,EUR,120454,EX,FT,Austria,S,Argentina,100,"Azure, Python, Git, Docker",Master,12,Real Estate,2025-04-28,2025-06-20,975,7.4,AI Innovations -AI00748,Research Scientist,176540,USD,176540,EX,FT,Sweden,S,United States,0,"TensorFlow, Kubernetes, Git, Java, Docker",Master,16,Healthcare,2024-09-17,2024-11-19,738,5.5,Algorithmic Solutions -AI00749,Deep Learning Engineer,75872,SGD,98634,EN,FT,Singapore,S,Netherlands,0,"Hadoop, MLOps, Python, Computer Vision, Docker",Associate,0,Retail,2025-01-06,2025-01-30,1818,8.4,Digital Transformation LLC -AI00750,Machine Learning Researcher,39100,USD,39100,MI,CT,China,M,Netherlands,100,"SQL, Docker, Python, Mathematics",PhD,3,Energy,2025-04-08,2025-04-22,1101,5.7,DeepTech Ventures -AI00751,Data Analyst,60610,USD,60610,MI,PT,South Korea,S,South Korea,50,"PyTorch, Computer Vision, Mathematics, R",Associate,3,Finance,2025-03-23,2025-05-24,748,5.4,Digital Transformation LLC -AI00752,NLP Engineer,64997,USD,64997,EN,CT,Finland,L,Finland,50,"Computer Vision, TensorFlow, Java",PhD,0,Automotive,2024-12-01,2025-01-01,1749,7.9,Autonomous Tech -AI00753,Principal Data Scientist,79831,USD,79831,MI,FT,Finland,S,Finland,0,"Scala, Java, Kubernetes, Data Visualization, Git",Bachelor,4,Retail,2024-05-09,2024-06-22,1863,9.6,Autonomous Tech -AI00754,Data Analyst,75434,JPY,8297740,EN,FT,Japan,L,Austria,100,"Computer Vision, SQL, Linux, AWS, Mathematics",PhD,1,Technology,2025-04-23,2025-05-12,2180,7.3,DataVision Ltd -AI00755,NLP Engineer,135956,USD,135956,SE,PT,Israel,M,Israel,100,"Kubernetes, Scala, Computer Vision",Master,8,Transportation,2024-02-11,2024-04-20,1899,5.7,TechCorp Inc -AI00756,Machine Learning Engineer,91194,CAD,113993,MI,PT,Canada,S,Canada,0,"Azure, Spark, Linux, Scala, SQL",PhD,3,Media,2024-08-13,2024-09-20,689,9.9,Neural Networks Co -AI00757,Research Scientist,182045,USD,182045,EX,CT,Israel,S,India,100,"Computer Vision, Hadoop, Kubernetes, Spark, Statistics",PhD,10,Technology,2024-11-25,2025-01-26,1620,10,Digital Transformation LLC -AI00758,Data Engineer,143858,USD,143858,EX,FT,Israel,M,Israel,50,"Deep Learning, Kubernetes, Hadoop, Linux",Associate,10,Automotive,2025-01-03,2025-02-05,1182,7.8,Digital Transformation LLC -AI00759,Data Analyst,135781,USD,135781,SE,FT,Finland,M,Finland,100,"Linux, R, Hadoop, Computer Vision, Python",Master,7,Retail,2024-11-26,2025-02-03,1587,6.2,Cloud AI Solutions -AI00760,AI Product Manager,151948,USD,151948,MI,FL,Denmark,L,Germany,100,"Statistics, Computer Vision, NLP, Python, TensorFlow",Bachelor,3,Manufacturing,2024-11-11,2024-12-10,1738,6.3,Predictive Systems -AI00761,AI Research Scientist,97414,CAD,121768,SE,FL,Canada,S,Canada,0,"Tableau, R, SQL, GCP, Docker",Master,6,Healthcare,2024-08-04,2024-08-30,748,9.3,Autonomous Tech -AI00762,Autonomous Systems Engineer,44257,USD,44257,MI,PT,China,M,China,50,"Kubernetes, Hadoop, GCP, Scala, Azure",PhD,4,Manufacturing,2024-11-28,2024-12-23,1984,6.4,Autonomous Tech -AI00763,Machine Learning Researcher,183099,USD,183099,SE,FT,Denmark,M,Denmark,100,"GCP, Docker, MLOps, Tableau, PyTorch",Master,9,Manufacturing,2025-01-21,2025-02-11,542,8.9,Cloud AI Solutions -AI00764,AI Product Manager,66978,EUR,56931,EN,FT,France,M,France,50,"Azure, Linux, Statistics, NLP",Associate,0,Gaming,2025-04-06,2025-05-07,721,9.4,Cloud AI Solutions -AI00765,Computer Vision Engineer,58844,USD,58844,EN,PT,United States,S,Kenya,100,"SQL, Python, Mathematics",PhD,1,Technology,2024-03-15,2024-04-20,874,7.2,Digital Transformation LLC -AI00766,Data Scientist,86679,EUR,73677,EN,PT,France,L,France,50,"Scala, Docker, Spark, MLOps, NLP",PhD,1,Gaming,2024-04-09,2024-04-24,865,5.7,Cognitive Computing -AI00767,Research Scientist,102607,EUR,87216,MI,FL,Austria,L,Austria,50,"Scala, Python, Tableau, Statistics",Associate,4,Telecommunications,2025-04-16,2025-05-16,2191,8.4,Autonomous Tech -AI00768,AI Research Scientist,117860,USD,117860,MI,FL,Norway,S,Norway,0,"Linux, Python, Scala",Master,3,Consulting,2024-02-21,2024-03-23,1949,9.6,Cloud AI Solutions -AI00769,Data Engineer,53776,AUD,72598,EN,PT,Australia,M,Mexico,50,"PyTorch, Spark, TensorFlow",PhD,1,Energy,2025-03-31,2025-05-21,1959,10,Advanced Robotics -AI00770,Autonomous Systems Engineer,22245,USD,22245,EN,FL,India,S,India,100,"R, AWS, Mathematics, Deep Learning, MLOps",Bachelor,1,Automotive,2025-03-07,2025-04-27,2075,7.7,TechCorp Inc -AI00771,Deep Learning Engineer,86753,USD,86753,EN,CT,Denmark,S,Hungary,50,"Kubernetes, MLOps, SQL, Python",Bachelor,0,Consulting,2025-01-27,2025-03-19,527,8.3,Quantum Computing Inc -AI00772,Data Scientist,59445,CAD,74306,EN,PT,Canada,S,Canada,50,"Kubernetes, GCP, Java, Deep Learning, Statistics",Associate,0,Finance,2024-02-26,2024-03-21,1565,6.9,Autonomous Tech -AI00773,Machine Learning Researcher,181623,USD,181623,SE,FL,Norway,L,Norway,100,"Azure, Scala, Python, Git",Bachelor,7,Telecommunications,2024-02-14,2024-03-10,2148,9.1,Neural Networks Co -AI00774,Machine Learning Engineer,23848,USD,23848,EN,FL,China,S,Poland,0,"TensorFlow, Spark, NLP, Mathematics",Associate,1,Real Estate,2024-02-29,2024-04-17,1126,8.6,Machine Intelligence Group -AI00775,Head of AI,67555,USD,67555,SE,PT,China,L,China,100,"Mathematics, Scala, Java",PhD,5,Education,2024-11-30,2025-01-08,1445,8.8,Future Systems -AI00776,Autonomous Systems Engineer,156672,USD,156672,EX,FL,Sweden,L,Sweden,0,"Statistics, SQL, Python, AWS, Computer Vision",Associate,19,Real Estate,2025-03-23,2025-05-11,2253,7,AI Innovations -AI00777,Data Analyst,99310,USD,99310,EX,FT,China,S,Vietnam,50,"Scala, Java, Deep Learning",Associate,14,Transportation,2024-04-28,2024-05-28,1790,5.8,TechCorp Inc -AI00778,Data Scientist,106468,USD,106468,SE,FL,South Korea,S,Singapore,0,"Kubernetes, PyTorch, SQL, Computer Vision, Tableau",PhD,5,Energy,2025-02-07,2025-03-21,735,8.3,DataVision Ltd -AI00779,NLP Engineer,133549,JPY,14690390,SE,PT,Japan,L,Portugal,50,"Statistics, Docker, TensorFlow",Master,8,Government,2024-02-03,2024-03-05,762,7.5,Autonomous Tech -AI00780,AI Consultant,101850,USD,101850,EN,FL,Norway,L,Norway,50,"Mathematics, NLP, MLOps, Linux",PhD,1,Healthcare,2025-04-04,2025-04-24,1992,7.7,TechCorp Inc -AI00781,Data Analyst,135555,USD,135555,EX,FL,China,L,China,50,"Deep Learning, Scala, Python",Associate,18,Real Estate,2025-01-14,2025-02-16,1694,6.9,Advanced Robotics -AI00782,Data Scientist,194650,USD,194650,EX,CT,Norway,M,Norway,0,"GCP, Scala, PyTorch, SQL",Master,13,Automotive,2025-01-01,2025-01-16,1290,9.4,Cognitive Computing -AI00783,NLP Engineer,48184,USD,48184,SE,FT,India,S,India,50,"Kubernetes, Docker, Python, TensorFlow",PhD,8,Real Estate,2024-06-02,2024-07-06,526,7.4,Digital Transformation LLC -AI00784,NLP Engineer,102143,EUR,86822,MI,PT,Netherlands,S,Austria,100,"Docker, Git, Scala, Mathematics",Master,2,Technology,2024-10-02,2024-10-16,883,8.9,Cognitive Computing -AI00785,Data Engineer,130584,USD,130584,SE,FT,Finland,L,Hungary,0,"Kubernetes, Azure, Spark",PhD,6,Gaming,2024-05-29,2024-06-27,1303,8,Predictive Systems -AI00786,ML Ops Engineer,197290,USD,197290,SE,FL,Denmark,M,Nigeria,50,"Python, TensorFlow, Statistics, PyTorch, Deep Learning",Bachelor,5,Education,2024-08-30,2024-09-15,1376,8.8,TechCorp Inc -AI00787,AI Architect,57552,EUR,48919,EN,FL,Germany,M,Germany,50,"Hadoop, TensorFlow, Tableau",PhD,0,Retail,2024-04-21,2024-05-15,2185,5.4,Algorithmic Solutions -AI00788,AI Specialist,138325,USD,138325,SE,CT,Sweden,M,Sweden,0,"Azure, Spark, Data Visualization, R, Python",Master,7,Transportation,2024-10-25,2024-11-17,1112,5.6,Machine Intelligence Group -AI00789,AI Product Manager,62787,USD,62787,EN,FL,Norway,S,Singapore,0,"Hadoop, Scala, R, Python",Associate,1,Automotive,2024-09-11,2024-10-10,1204,5.1,Cloud AI Solutions -AI00790,AI Research Scientist,96898,EUR,82363,SE,FL,Austria,M,Austria,50,"Docker, Tableau, SQL, Deep Learning, MLOps",Bachelor,8,Healthcare,2024-09-15,2024-10-22,1719,6.3,Future Systems -AI00791,AI Software Engineer,101690,USD,101690,MI,CT,Norway,S,Norway,100,"Scala, Deep Learning, Git, TensorFlow",Bachelor,4,Telecommunications,2025-03-21,2025-05-01,2046,9.9,Predictive Systems -AI00792,Data Scientist,104342,USD,104342,MI,CT,United States,L,United States,50,"Azure, SQL, Python, AWS",Bachelor,2,Technology,2024-08-23,2024-09-21,2196,7.8,Future Systems -AI00793,Principal Data Scientist,182831,EUR,155406,EX,PT,Austria,S,Chile,100,"Kubernetes, Linux, Scala, Deep Learning, Azure",Master,18,Transportation,2024-12-22,2025-01-27,1334,5.8,Quantum Computing Inc -AI00794,AI Specialist,65362,EUR,55558,EN,PT,France,L,Japan,0,"TensorFlow, AWS, NLP, Data Visualization",Bachelor,1,Government,2024-09-12,2024-10-12,1819,5.2,Predictive Systems -AI00795,AI Software Engineer,116249,EUR,98812,SE,FL,France,M,France,50,"Scala, Java, MLOps, Azure",PhD,8,Finance,2024-05-02,2024-06-10,1595,8.6,Digital Transformation LLC -AI00796,Machine Learning Researcher,181065,USD,181065,EX,FL,Norway,S,Norway,0,"Java, R, Statistics, Linux, Mathematics",Master,19,Healthcare,2024-10-18,2024-11-03,2202,8,Machine Intelligence Group -AI00797,Data Engineer,110326,EUR,93777,SE,PT,France,S,France,0,"PyTorch, Hadoop, AWS, Python",Associate,8,Technology,2024-11-08,2024-12-14,739,9.3,Quantum Computing Inc -AI00798,AI Research Scientist,113275,EUR,96284,SE,FT,Netherlands,M,Netherlands,0,"Docker, Java, Tableau, Hadoop",Master,6,Consulting,2024-03-08,2024-04-17,1264,8,Quantum Computing Inc -AI00799,Autonomous Systems Engineer,86720,CAD,108400,SE,CT,Canada,S,Canada,0,"Spark, Kubernetes, SQL, Data Visualization",Bachelor,7,Consulting,2024-03-21,2024-05-18,821,6.7,Smart Analytics -AI00800,Deep Learning Engineer,88527,USD,88527,SE,CT,South Korea,M,South Korea,100,"Python, Docker, Linux, Spark, Scala",Master,8,Technology,2024-02-14,2024-04-27,1973,6.3,TechCorp Inc -AI00801,AI Software Engineer,75281,USD,75281,EN,FL,Finland,M,Finland,100,"Git, Python, Tableau, Spark",Associate,0,Technology,2024-07-12,2024-08-01,1666,8.4,Advanced Robotics -AI00802,Principal Data Scientist,63784,AUD,86108,EN,FL,Australia,L,Australia,100,"SQL, Deep Learning, Data Visualization, TensorFlow",Master,0,Healthcare,2025-02-14,2025-03-01,668,10,Quantum Computing Inc -AI00803,AI Product Manager,140500,SGD,182650,SE,CT,Singapore,L,Malaysia,0,"Kubernetes, Data Visualization, MLOps, Python, GCP",PhD,7,Energy,2024-12-15,2025-02-10,1733,8.6,Predictive Systems -AI00804,Deep Learning Engineer,30726,USD,30726,EN,FT,India,L,India,100,"Spark, Kubernetes, MLOps, Git",PhD,1,Telecommunications,2024-10-02,2024-10-18,782,7.9,Predictive Systems -AI00805,AI Specialist,242789,SGD,315626,EX,PT,Singapore,M,Singapore,50,"Data Visualization, Hadoop, MLOps, SQL",Associate,15,Manufacturing,2024-06-10,2024-07-03,592,8.7,DeepTech Ventures -AI00806,ML Ops Engineer,126827,USD,126827,EX,FT,South Korea,S,South Korea,0,"Python, Git, R, NLP, PyTorch",Master,17,Real Estate,2024-05-24,2024-06-19,2410,9.6,Digital Transformation LLC -AI00807,Robotics Engineer,77753,JPY,8552830,MI,CT,Japan,M,Japan,100,"Linux, Python, Java, Azure, Git",PhD,2,Automotive,2025-04-09,2025-06-19,845,9.4,Neural Networks Co -AI00808,Autonomous Systems Engineer,204502,USD,204502,EX,PT,United States,S,United States,100,"NLP, Linux, PyTorch",Master,13,Consulting,2024-11-23,2024-12-14,1899,9.7,Machine Intelligence Group -AI00809,Machine Learning Engineer,76869,EUR,65339,MI,PT,France,S,France,50,"SQL, Git, TensorFlow, Statistics",Bachelor,4,Healthcare,2025-03-11,2025-04-24,1199,7.6,AI Innovations -AI00810,Computer Vision Engineer,128192,USD,128192,SE,FT,Ireland,S,India,0,"R, SQL, PyTorch, Docker, Deep Learning",Bachelor,5,Energy,2024-11-01,2024-12-12,2010,5.4,Cognitive Computing -AI00811,Machine Learning Engineer,234782,CHF,211304,EX,PT,Switzerland,M,Switzerland,0,"Mathematics, SQL, MLOps, TensorFlow, Kubernetes",Associate,19,Education,2024-02-05,2024-03-25,1540,7.4,Quantum Computing Inc -AI00812,Robotics Engineer,243016,USD,243016,EX,CT,Norway,S,Norway,0,"SQL, Deep Learning, Data Visualization",PhD,14,Consulting,2024-04-20,2024-06-27,2207,5.9,Machine Intelligence Group -AI00813,ML Ops Engineer,232932,GBP,174699,EX,CT,United Kingdom,L,United Kingdom,50,"Statistics, Spark, Python, AWS, Azure",Bachelor,19,Education,2024-05-27,2024-07-02,2321,7.9,DeepTech Ventures -AI00814,AI Software Engineer,157713,EUR,134056,EX,FT,France,L,France,100,"Statistics, Azure, NLP, Data Visualization, Deep Learning",Associate,11,Real Estate,2024-03-29,2024-04-18,1275,7.3,Quantum Computing Inc -AI00815,Computer Vision Engineer,78731,GBP,59048,MI,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, PyTorch, SQL, Mathematics, Scala",Bachelor,4,Retail,2025-01-12,2025-01-26,893,9.7,DataVision Ltd -AI00816,Machine Learning Engineer,118802,CAD,148503,SE,PT,Canada,L,Canada,50,"GCP, Docker, Azure, Tableau, PyTorch",PhD,5,Telecommunications,2025-01-18,2025-02-08,2228,9.6,Digital Transformation LLC -AI00817,AI Software Engineer,86119,CHF,77507,EN,PT,Switzerland,M,Switzerland,50,"MLOps, Scala, Azure",Master,1,Retail,2025-03-14,2025-04-18,1655,7.2,Future Systems -AI00818,Head of AI,148519,GBP,111389,EX,CT,United Kingdom,M,United Kingdom,50,"MLOps, Java, Scala, R",PhD,19,Retail,2025-02-11,2025-02-26,1578,5.8,Neural Networks Co -AI00819,AI Research Scientist,48058,USD,48058,EN,PT,South Korea,S,South Korea,100,"Spark, Hadoop, TensorFlow, Data Visualization, Computer Vision",Associate,1,Manufacturing,2024-08-26,2024-11-06,1378,5.2,Future Systems -AI00820,AI Architect,68183,EUR,57956,EN,FT,France,M,France,0,"Mathematics, SQL, Spark, Kubernetes, PyTorch",PhD,0,Retail,2024-12-08,2025-02-11,1399,5.9,Algorithmic Solutions -AI00821,Principal Data Scientist,237151,GBP,177863,EX,FT,United Kingdom,S,United Kingdom,100,"Git, Computer Vision, Tableau, Azure",PhD,15,Energy,2025-04-02,2025-05-20,2094,9.5,Algorithmic Solutions -AI00822,Data Engineer,95252,USD,95252,MI,PT,Ireland,S,Ireland,50,"Scala, MLOps, SQL",Bachelor,4,Real Estate,2024-11-05,2024-12-17,1479,9.9,AI Innovations -AI00823,NLP Engineer,142166,JPY,15638260,SE,CT,Japan,L,Japan,50,"Python, TensorFlow, Computer Vision, AWS, Statistics",Master,5,Transportation,2024-11-02,2024-12-20,1946,6.1,DeepTech Ventures -AI00824,Machine Learning Engineer,107965,USD,107965,SE,CT,Sweden,S,Romania,100,"SQL, Kubernetes, MLOps, NLP, GCP",Bachelor,9,Healthcare,2024-08-16,2024-08-31,1211,7.3,Advanced Robotics -AI00825,ML Ops Engineer,239943,EUR,203952,EX,FT,Netherlands,L,Netherlands,50,"Azure, MLOps, R, Python, TensorFlow",Bachelor,12,Real Estate,2024-05-16,2024-07-11,602,9.1,Machine Intelligence Group -AI00826,Robotics Engineer,287023,USD,287023,EX,PT,Ireland,L,Ireland,100,"Computer Vision, Linux, GCP, Scala",Master,10,Education,2025-03-31,2025-04-29,543,7.4,Cloud AI Solutions -AI00827,AI Architect,108794,USD,108794,MI,FL,Norway,L,Ukraine,0,"Hadoop, Kubernetes, Docker, Statistics, SQL",Associate,4,Government,2024-09-27,2024-11-26,1050,5.9,Advanced Robotics -AI00828,AI Specialist,91776,USD,91776,EN,FT,United States,M,Germany,0,"Docker, Computer Vision, AWS, Python, TensorFlow",PhD,1,Technology,2024-03-19,2024-04-25,2314,6.1,Predictive Systems -AI00829,Robotics Engineer,61890,USD,61890,EN,PT,South Korea,L,Italy,0,"Java, R, SQL",Bachelor,1,Consulting,2024-12-20,2025-01-15,709,5.4,Advanced Robotics -AI00830,Data Analyst,345294,USD,345294,EX,FT,Norway,L,Norway,100,"Kubernetes, TensorFlow, GCP",PhD,11,Telecommunications,2025-02-03,2025-04-06,1012,6.6,DataVision Ltd -AI00831,AI Product Manager,78569,USD,78569,MI,CT,Israel,L,Israel,0,"Spark, PyTorch, MLOps, NLP, Kubernetes",Master,4,Healthcare,2024-11-20,2024-12-05,2033,7.4,DataVision Ltd -AI00832,Autonomous Systems Engineer,66673,EUR,56672,EN,PT,France,M,France,100,"Git, Scala, Python",Master,0,Telecommunications,2024-11-27,2024-12-14,1825,8.6,Future Systems -AI00833,Machine Learning Researcher,183500,CHF,165150,SE,CT,Switzerland,M,Switzerland,50,"TensorFlow, Python, Computer Vision, Statistics, Scala",PhD,8,Transportation,2025-01-24,2025-03-08,686,9.1,Digital Transformation LLC -AI00834,ML Ops Engineer,165234,SGD,214804,EX,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Python, NLP",Associate,10,Manufacturing,2024-05-07,2024-05-22,913,6,Future Systems -AI00835,Principal Data Scientist,119549,SGD,155414,MI,FT,Singapore,L,Singapore,100,"Kubernetes, NLP, MLOps",Master,2,Consulting,2024-11-05,2024-12-12,1344,5.7,Digital Transformation LLC -AI00836,NLP Engineer,325936,USD,325936,EX,PT,Norway,L,Norway,100,"Scala, Spark, Deep Learning",Bachelor,19,Government,2024-09-01,2024-11-04,1066,8.3,Cognitive Computing -AI00837,ML Ops Engineer,157221,SGD,204387,SE,FT,Singapore,L,Singapore,0,"PyTorch, Java, GCP, Python, Hadoop",Associate,7,Gaming,2025-02-24,2025-03-23,908,8.5,Future Systems -AI00838,Machine Learning Engineer,98221,USD,98221,SE,PT,South Korea,L,South Korea,0,"Python, Deep Learning, AWS, Statistics",Bachelor,6,Finance,2024-05-04,2024-06-10,1650,6.7,Algorithmic Solutions -AI00839,Autonomous Systems Engineer,155502,GBP,116627,EX,CT,United Kingdom,M,India,50,"Kubernetes, Java, Docker, Hadoop",Master,11,Healthcare,2025-03-18,2025-05-10,503,9.5,DeepTech Ventures -AI00840,Principal Data Scientist,276679,USD,276679,EX,FT,Denmark,L,Denmark,0,"PyTorch, GCP, MLOps, AWS, Mathematics",Master,11,Telecommunications,2024-07-11,2024-09-21,1457,8.7,Predictive Systems -AI00841,AI Product Manager,187955,EUR,159762,EX,CT,Germany,S,Turkey,0,"Docker, Git, Linux",Master,19,Manufacturing,2025-02-01,2025-04-04,2439,7.9,Smart Analytics -AI00842,Data Engineer,135585,USD,135585,MI,FT,Denmark,L,Denmark,100,"AWS, Python, GCP",Associate,4,Real Estate,2024-06-02,2024-08-11,2302,5.1,Cloud AI Solutions -AI00843,Machine Learning Researcher,138945,USD,138945,SE,PT,United States,L,Kenya,50,"Java, Azure, Data Visualization, NLP",Master,5,Transportation,2024-07-08,2024-08-01,1468,7.3,TechCorp Inc -AI00844,Autonomous Systems Engineer,89723,EUR,76265,MI,FL,Netherlands,S,Netherlands,50,"Python, PyTorch, Spark, TensorFlow",Associate,3,Education,2024-06-17,2024-08-12,914,5.3,Advanced Robotics -AI00845,Computer Vision Engineer,74250,USD,74250,EN,FL,United States,L,Colombia,100,"NLP, R, TensorFlow",Associate,0,Consulting,2024-09-22,2024-10-07,2179,5.3,Predictive Systems -AI00846,Machine Learning Researcher,209546,USD,209546,EX,FT,Norway,M,Norway,100,"NLP, SQL, PyTorch, Git, Spark",Associate,11,Telecommunications,2025-01-24,2025-02-23,2485,7.7,Smart Analytics -AI00847,AI Product Manager,137463,JPY,15120930,EX,FL,Japan,S,Japan,0,"AWS, Git, Python, NLP, Scala",Associate,13,Healthcare,2024-05-28,2024-06-11,1088,7.9,Autonomous Tech -AI00848,Head of AI,83657,USD,83657,EN,FT,Ireland,L,Ireland,0,"Python, MLOps, Data Visualization, Spark",Master,0,Government,2024-06-25,2024-08-14,1808,6.4,Predictive Systems -AI00849,Data Engineer,120560,USD,120560,MI,FT,United States,M,Vietnam,0,"Hadoop, MLOps, Spark, Kubernetes",Bachelor,3,Retail,2024-08-18,2024-09-15,1128,7.5,AI Innovations -AI00850,AI Architect,87119,USD,87119,SE,PT,Israel,S,Denmark,100,"Scala, Statistics, Java",Associate,7,Media,2025-04-05,2025-05-17,1585,8.6,AI Innovations -AI00851,Principal Data Scientist,71418,USD,71418,MI,FL,South Korea,L,South Korea,100,"AWS, Linux, R",Master,4,Government,2024-10-17,2024-12-22,1154,8.8,Predictive Systems -AI00852,AI Consultant,46727,USD,46727,EX,FT,India,S,India,50,"SQL, Docker, Python",Bachelor,19,Automotive,2024-08-31,2024-10-20,1896,6.9,Advanced Robotics -AI00853,Data Scientist,164321,USD,164321,EX,PT,Sweden,S,Netherlands,50,"Kubernetes, GCP, PyTorch",Master,16,Energy,2024-08-01,2024-09-10,2008,6.4,Predictive Systems -AI00854,AI Product Manager,80460,JPY,8850600,EN,FL,Japan,M,Indonesia,0,"Python, Scala, TensorFlow",Bachelor,1,Energy,2025-01-17,2025-03-02,2267,9.9,Quantum Computing Inc -AI00855,Robotics Engineer,99510,EUR,84584,SE,CT,France,S,France,50,"Deep Learning, SQL, PyTorch",Associate,8,Technology,2025-04-26,2025-06-26,2131,9.8,Neural Networks Co -AI00856,Head of AI,145409,CHF,130868,MI,PT,Switzerland,M,Switzerland,100,"Git, NLP, Tableau, Python",Associate,2,Energy,2024-06-03,2024-08-04,1347,8.8,Cognitive Computing -AI00857,Data Analyst,289465,USD,289465,EX,PT,United States,M,United States,50,"Docker, MLOps, Python, Statistics, SQL",Bachelor,13,Retail,2025-04-08,2025-05-20,1420,9.2,Digital Transformation LLC -AI00858,ML Ops Engineer,85216,JPY,9373760,EN,FT,Japan,M,Japan,0,"AWS, Data Visualization, Python",Bachelor,1,Telecommunications,2024-09-17,2024-10-23,797,8.8,Cognitive Computing -AI00859,AI Software Engineer,88921,CAD,111151,MI,CT,Canada,S,Canada,100,"SQL, Kubernetes, Azure, Hadoop",PhD,3,Technology,2024-09-01,2024-09-21,1630,8.8,Advanced Robotics -AI00860,NLP Engineer,65144,USD,65144,EN,FL,Sweden,L,Argentina,100,"Hadoop, MLOps, Docker, Deep Learning, Statistics",Associate,0,Retail,2024-09-16,2024-11-25,1121,5.5,Quantum Computing Inc -AI00861,Data Analyst,103403,USD,103403,MI,CT,Israel,M,Israel,50,"Tableau, SQL, Linux, NLP, Kubernetes",Bachelor,3,Technology,2024-01-14,2024-02-11,2139,6.6,Smart Analytics -AI00862,Deep Learning Engineer,121368,USD,121368,SE,FL,Israel,M,Israel,50,"Spark, Python, Data Visualization",PhD,8,Energy,2024-04-01,2024-05-29,1567,5.2,Predictive Systems -AI00863,Head of AI,168109,AUD,226947,SE,CT,Australia,L,Australia,50,"Data Visualization, GCP, SQL",Bachelor,7,Gaming,2025-01-25,2025-03-22,2457,9.6,Cognitive Computing -AI00864,Robotics Engineer,40616,USD,40616,MI,CT,China,S,Canada,0,"TensorFlow, Git, Python, Hadoop",Associate,2,Finance,2024-07-31,2024-08-27,2010,5.9,Neural Networks Co -AI00865,NLP Engineer,176886,CHF,159197,EX,CT,Switzerland,S,Switzerland,0,"PyTorch, Scala, Deep Learning, Computer Vision",Master,16,Real Estate,2024-02-18,2024-04-22,1045,9.8,DataVision Ltd -AI00866,Autonomous Systems Engineer,107548,EUR,91416,MI,CT,Germany,M,Germany,0,"Linux, Python, TensorFlow",Master,2,Consulting,2024-08-16,2024-10-17,1812,9.7,AI Innovations -AI00867,AI Software Engineer,313203,CHF,281883,EX,FL,Switzerland,S,Switzerland,50,"Kubernetes, Python, Mathematics, Java",Master,15,Finance,2025-04-02,2025-06-14,1078,6,Algorithmic Solutions -AI00868,AI Consultant,147571,EUR,125435,EX,FT,France,M,United States,0,"R, GCP, Git",Associate,12,Consulting,2024-12-14,2025-02-12,679,5,Advanced Robotics -AI00869,Deep Learning Engineer,239432,EUR,203517,EX,PT,France,M,France,100,"R, NLP, Java, Hadoop",Associate,19,Automotive,2024-06-03,2024-08-02,1371,8,Machine Intelligence Group -AI00870,Machine Learning Researcher,119559,USD,119559,MI,CT,United States,L,United States,0,"PyTorch, Linux, NLP, MLOps, Java",Bachelor,2,Real Estate,2025-03-31,2025-05-15,546,5.9,Quantum Computing Inc -AI00871,AI Consultant,72051,SGD,93666,EN,FT,Singapore,S,Singapore,100,"AWS, Kubernetes, Tableau, Azure, Java",Master,0,Education,2024-09-11,2024-10-07,2394,6,Future Systems -AI00872,Machine Learning Engineer,80766,AUD,109034,EN,FT,Australia,L,India,100,"Java, R, NLP, Azure",PhD,1,Media,2025-02-03,2025-02-18,845,7.2,Future Systems -AI00873,Computer Vision Engineer,75201,CHF,67681,EN,PT,Switzerland,M,Switzerland,100,"Data Visualization, SQL, Scala, Deep Learning, Hadoop",Associate,0,Telecommunications,2024-08-11,2024-10-21,505,6.5,Cloud AI Solutions -AI00874,Machine Learning Engineer,367330,CHF,330597,EX,PT,Switzerland,L,Belgium,100,"Kubernetes, SQL, Mathematics, Deep Learning, Computer Vision",Master,12,Finance,2025-01-25,2025-02-26,1732,6.1,Cloud AI Solutions -AI00875,AI Specialist,99824,CHF,89842,EN,FL,Switzerland,S,Switzerland,100,"Tableau, Linux, AWS, Python, Mathematics",Master,1,Manufacturing,2025-01-30,2025-03-15,1530,9.4,DataVision Ltd -AI00876,Computer Vision Engineer,183643,GBP,137732,EX,FL,United Kingdom,L,United Kingdom,50,"Git, Python, NLP",Bachelor,16,Transportation,2024-09-30,2024-10-22,1295,9.9,DataVision Ltd -AI00877,Research Scientist,86875,CAD,108594,MI,FL,Canada,L,Canada,0,"Kubernetes, NLP, SQL",Bachelor,2,Education,2025-01-27,2025-03-10,2499,8.1,DataVision Ltd -AI00878,AI Architect,92050,USD,92050,EN,PT,Denmark,S,Denmark,100,"Spark, Docker, Computer Vision, NLP, Data Visualization",PhD,0,Healthcare,2025-02-04,2025-03-26,1907,5,DataVision Ltd -AI00879,Machine Learning Engineer,188547,EUR,160265,EX,CT,Germany,S,Indonesia,100,"Hadoop, SQL, Computer Vision, PyTorch, Docker",Bachelor,10,Transportation,2024-07-01,2024-08-17,1395,7.2,Cloud AI Solutions -AI00880,Data Scientist,93400,USD,93400,MI,FT,Ireland,S,Ireland,0,"Scala, Azure, Data Visualization, PyTorch, Git",Bachelor,4,Government,2024-11-09,2025-01-08,1829,5.7,Machine Intelligence Group -AI00881,Data Scientist,121492,EUR,103268,SE,PT,Germany,M,Germany,50,"AWS, Tableau, Kubernetes, Python",Associate,5,Technology,2025-04-11,2025-06-15,799,6.4,Future Systems -AI00882,AI Software Engineer,214716,CAD,268395,EX,CT,Canada,M,Canada,100,"SQL, Java, Git, Scala, Spark",Bachelor,13,Transportation,2024-01-29,2024-04-02,1629,7.4,Smart Analytics -AI00883,Machine Learning Engineer,96552,USD,96552,MI,PT,Denmark,S,Chile,0,"Spark, Git, Data Visualization, Kubernetes, SQL",Bachelor,3,Transportation,2025-03-01,2025-04-25,1746,6.7,DataVision Ltd -AI00884,Research Scientist,82126,EUR,69807,MI,CT,France,M,France,50,"Tableau, Hadoop, Python, AWS",PhD,4,Energy,2024-06-20,2024-08-31,1435,6.3,AI Innovations -AI00885,ML Ops Engineer,101793,EUR,86524,MI,FT,France,L,France,50,"TensorFlow, Azure, Python, Deep Learning",PhD,3,Education,2024-07-14,2024-07-31,926,5.5,Future Systems -AI00886,AI Research Scientist,119593,CAD,149491,MI,PT,Canada,L,Canada,100,"Data Visualization, Python, Tableau",Master,3,Government,2024-02-17,2024-04-23,908,6.3,Autonomous Tech -AI00887,AI Software Engineer,83380,USD,83380,EX,FL,China,M,China,0,"R, Scala, AWS, Data Visualization",PhD,18,Education,2024-08-19,2024-09-06,848,9.6,Advanced Robotics -AI00888,NLP Engineer,104077,EUR,88465,MI,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, Docker, Azure",Associate,3,Transportation,2025-03-29,2025-05-19,821,6.8,Smart Analytics -AI00889,Research Scientist,107155,EUR,91082,SE,PT,France,M,France,100,"Scala, SQL, GCP, Git, Linux",Associate,5,Real Estate,2024-09-29,2024-11-03,2162,6.2,Autonomous Tech -AI00890,AI Architect,95613,USD,95613,EN,FL,Denmark,M,Denmark,50,"Hadoop, Docker, Scala",Associate,0,Consulting,2024-11-08,2024-12-06,1404,8.3,TechCorp Inc -AI00891,AI Research Scientist,79915,USD,79915,MI,CT,Israel,S,Israel,0,"PyTorch, Hadoop, TensorFlow",Master,2,Consulting,2024-01-08,2024-01-29,2279,9.7,Advanced Robotics -AI00892,ML Ops Engineer,152836,USD,152836,SE,FT,Israel,L,Israel,100,"Statistics, PyTorch, NLP, Git",Associate,9,Education,2024-01-25,2024-02-24,2225,5.8,Predictive Systems -AI00893,AI Research Scientist,201144,SGD,261487,EX,FT,Singapore,M,Singapore,50,"Linux, AWS, R, Deep Learning, Docker",Associate,10,Government,2024-11-09,2025-01-10,1814,7.9,TechCorp Inc -AI00894,Machine Learning Researcher,74068,USD,74068,MI,FT,Israel,S,Israel,100,"SQL, PyTorch, Linux",PhD,4,Healthcare,2024-11-11,2024-12-06,1384,5.9,Digital Transformation LLC -AI00895,Principal Data Scientist,94861,EUR,80632,MI,FT,Netherlands,S,Netherlands,50,"Git, Scala, Tableau, Spark",Master,2,Government,2024-06-01,2024-07-10,1711,5.7,Autonomous Tech -AI00896,Head of AI,89534,USD,89534,MI,FL,South Korea,M,Romania,100,"Azure, AWS, GCP, Git, Kubernetes",PhD,4,Consulting,2024-02-21,2024-04-30,1229,7.5,AI Innovations -AI00897,Research Scientist,121009,USD,121009,MI,PT,Denmark,L,Switzerland,50,"R, Scala, Computer Vision, Azure",Associate,2,Government,2024-10-17,2024-12-20,2092,7.5,Autonomous Tech -AI00898,AI Software Engineer,98503,USD,98503,MI,FT,Denmark,M,United Kingdom,100,"Kubernetes, Linux, Hadoop",Bachelor,3,Energy,2025-01-24,2025-03-07,2120,7.1,Algorithmic Solutions -AI00899,Autonomous Systems Engineer,92133,USD,92133,MI,FL,Finland,L,Finland,100,"R, Scala, GCP",Bachelor,2,Automotive,2024-08-24,2024-10-18,2014,6.8,Predictive Systems -AI00900,Research Scientist,108765,USD,108765,MI,PT,United States,M,United States,0,"Spark, TensorFlow, Java, Azure",Bachelor,4,Automotive,2024-06-24,2024-07-28,1043,8.9,Autonomous Tech -AI00901,Machine Learning Engineer,93440,CHF,84096,EN,CT,Switzerland,M,Switzerland,0,"Statistics, Git, Kubernetes, Python, Azure",Bachelor,0,Retail,2024-10-17,2024-11-20,659,6.1,Cloud AI Solutions -AI00902,AI Architect,88745,SGD,115369,MI,FT,Singapore,S,Singapore,100,"SQL, Deep Learning, GCP, MLOps, Spark",Associate,4,Finance,2025-03-02,2025-03-22,1741,9.5,Algorithmic Solutions -AI00903,Research Scientist,105976,USD,105976,SE,PT,Ireland,M,Ireland,100,"SQL, Hadoop, Kubernetes",Associate,7,Transportation,2024-03-16,2024-05-20,1015,7.6,Digital Transformation LLC -AI00904,NLP Engineer,59221,USD,59221,MI,PT,South Korea,S,South Korea,0,"Statistics, Spark, Tableau, Java",Associate,3,Media,2024-09-09,2024-10-19,1905,5.3,Quantum Computing Inc -AI00905,NLP Engineer,61996,USD,61996,EN,FT,Sweden,L,United States,100,"Scala, Kubernetes, Computer Vision, SQL",PhD,0,Gaming,2024-02-25,2024-03-23,2259,7.8,Quantum Computing Inc -AI00906,ML Ops Engineer,90426,EUR,76862,MI,FT,France,S,France,50,"Git, Data Visualization, Spark",Master,3,Real Estate,2025-04-02,2025-04-28,1535,6.2,Autonomous Tech -AI00907,AI Consultant,60924,EUR,51785,EN,PT,France,S,France,0,"Scala, Hadoop, Java",Associate,0,Healthcare,2024-08-09,2024-09-03,2378,7.5,Advanced Robotics -AI00908,Data Engineer,243192,CAD,303990,EX,CT,Canada,L,Canada,0,"Scala, Azure, Kubernetes, Java, Statistics",Bachelor,16,Automotive,2024-03-07,2024-05-19,1815,9,Machine Intelligence Group -AI00909,Deep Learning Engineer,166087,EUR,141174,EX,FT,France,L,France,0,"Mathematics, Git, Data Visualization, Scala",Associate,10,Finance,2024-01-20,2024-02-14,2264,9.3,Smart Analytics -AI00910,Research Scientist,85173,USD,85173,EN,CT,Finland,L,Finland,0,"Statistics, Java, NLP, Git",Bachelor,0,Real Estate,2024-07-18,2024-09-06,2477,5.6,Machine Intelligence Group -AI00911,AI Specialist,309247,CHF,278322,EX,CT,Switzerland,L,Switzerland,100,"Computer Vision, GCP, Statistics, Azure, TensorFlow",Associate,10,Telecommunications,2024-02-18,2024-03-26,749,5.1,Digital Transformation LLC -AI00912,Computer Vision Engineer,121556,EUR,103323,MI,FL,Germany,L,Germany,0,"Data Visualization, Scala, PyTorch",PhD,3,Gaming,2025-04-17,2025-05-04,1461,5.2,Neural Networks Co -AI00913,AI Consultant,89998,JPY,9899780,EN,CT,Japan,L,Japan,50,"Scala, TensorFlow, Linux",PhD,1,Technology,2024-06-11,2024-07-20,617,8,Cognitive Computing -AI00914,AI Architect,63415,EUR,53903,MI,FT,France,S,France,100,"Kubernetes, Scala, Hadoop, Java, NLP",Master,3,Energy,2025-02-19,2025-04-13,1601,5.4,Future Systems -AI00915,Data Scientist,132964,USD,132964,MI,PT,Denmark,M,Denmark,0,"Scala, Python, MLOps",Master,2,Energy,2024-04-01,2024-06-11,1070,6.9,Machine Intelligence Group -AI00916,ML Ops Engineer,65099,SGD,84629,EN,PT,Singapore,S,Singapore,50,"Linux, PyTorch, SQL",Associate,0,Transportation,2024-02-03,2024-02-21,2192,5.1,DataVision Ltd -AI00917,AI Product Manager,170410,USD,170410,EX,FT,South Korea,L,South Korea,100,"MLOps, PyTorch, Tableau, SQL",Associate,16,Healthcare,2024-01-25,2024-02-18,1497,9.6,DataVision Ltd -AI00918,Data Engineer,25440,USD,25440,EN,CT,India,M,India,0,"Kubernetes, Scala, AWS",Master,1,Gaming,2024-10-28,2024-11-12,987,6.4,Advanced Robotics -AI00919,Research Scientist,173489,JPY,19083790,SE,FT,Japan,L,France,50,"Git, SQL, Kubernetes, Mathematics, PyTorch",Bachelor,8,Energy,2025-01-12,2025-01-29,647,5,Cloud AI Solutions -AI00920,Computer Vision Engineer,216939,USD,216939,EX,FT,United States,L,United States,100,"GCP, Git, MLOps, Mathematics, Scala",Master,13,Real Estate,2024-02-18,2024-04-25,1487,5.8,Algorithmic Solutions -AI00921,Autonomous Systems Engineer,117695,USD,117695,SE,FL,United States,S,Austria,50,"Hadoop, Azure, Java, Linux, Deep Learning",Bachelor,9,Gaming,2024-04-30,2024-06-10,894,9.4,Neural Networks Co -AI00922,AI Specialist,78936,AUD,106564,MI,CT,Australia,M,Australia,100,"Python, Git, TensorFlow, Deep Learning",Associate,4,Telecommunications,2024-09-07,2024-11-13,1081,9,Cloud AI Solutions -AI00923,NLP Engineer,113661,USD,113661,EN,FT,Norway,L,Norway,50,"Python, PyTorch, Git, Linux",Associate,0,Manufacturing,2025-02-16,2025-04-25,1471,5.9,Quantum Computing Inc -AI00924,Computer Vision Engineer,226030,JPY,24863300,EX,FT,Japan,S,Japan,50,"Git, SQL, Spark",Bachelor,17,Energy,2025-01-04,2025-02-16,744,9.8,AI Innovations -AI00925,Machine Learning Researcher,162220,USD,162220,EX,CT,Finland,S,Russia,50,"Spark, Data Visualization, PyTorch",Master,17,Transportation,2024-01-27,2024-03-12,862,5.5,Future Systems -AI00926,Deep Learning Engineer,165689,USD,165689,EX,FT,Ireland,S,Ireland,0,"R, TensorFlow, GCP, Linux, Statistics",PhD,19,Automotive,2024-11-13,2024-11-29,567,9.5,Cognitive Computing -AI00927,Principal Data Scientist,319536,CHF,287582,EX,FT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Java, Tableau",PhD,16,Technology,2024-01-22,2024-02-17,1950,6,DeepTech Ventures -AI00928,Data Scientist,97294,USD,97294,SE,CT,Israel,M,Israel,50,"Azure, Java, Spark, Linux, R",PhD,7,Manufacturing,2024-07-17,2024-08-21,985,7.9,Quantum Computing Inc -AI00929,Machine Learning Researcher,94506,USD,94506,EN,FT,Denmark,L,Denmark,50,"Docker, Scala, Azure, Mathematics, MLOps",Associate,1,Consulting,2024-09-29,2024-11-06,2181,9.4,Quantum Computing Inc -AI00930,Data Engineer,122519,USD,122519,SE,PT,Israel,M,Israel,50,"Data Visualization, MLOps, Hadoop, Docker",Bachelor,8,Manufacturing,2024-07-19,2024-08-09,644,7.3,Machine Intelligence Group -AI00931,Autonomous Systems Engineer,61916,USD,61916,MI,FT,South Korea,S,South Korea,100,"Java, Statistics, GCP, Kubernetes, NLP",Associate,2,Energy,2024-10-16,2024-11-03,1639,5.1,Autonomous Tech -AI00932,Principal Data Scientist,78823,USD,78823,MI,FL,Israel,M,India,50,"Python, GCP, TensorFlow, Mathematics",Associate,4,Technology,2024-09-07,2024-09-26,756,5.2,Machine Intelligence Group -AI00933,Data Engineer,111124,USD,111124,EN,CT,Denmark,L,China,0,"Spark, GCP, Data Visualization",Master,0,Technology,2024-04-23,2024-07-01,1021,8.5,Neural Networks Co -AI00934,Robotics Engineer,91289,EUR,77596,EN,FL,Netherlands,L,Netherlands,0,"PyTorch, Spark, Azure, Kubernetes, Java",Master,0,Education,2024-02-06,2024-03-10,972,8.5,DataVision Ltd -AI00935,AI Specialist,195659,USD,195659,SE,PT,Norway,L,Norway,50,"Python, Hadoop, TensorFlow, Computer Vision",PhD,6,Media,2024-02-08,2024-03-18,1789,7,Future Systems -AI00936,Data Engineer,199412,EUR,169500,EX,PT,Germany,S,Norway,50,"Java, Scala, Docker",Bachelor,17,Government,2024-02-05,2024-03-08,1254,8.1,Smart Analytics -AI00937,Data Engineer,202421,USD,202421,EX,FL,Norway,L,Norway,100,"Kubernetes, Git, PyTorch",Master,19,Manufacturing,2024-11-22,2025-01-28,2135,6.4,Machine Intelligence Group -AI00938,Data Scientist,133682,GBP,100262,MI,FL,United Kingdom,L,United Kingdom,100,"Hadoop, Spark, MLOps, GCP, R",Associate,3,Manufacturing,2025-03-20,2025-05-05,2382,8,Autonomous Tech -AI00939,Data Analyst,205143,GBP,153857,EX,PT,United Kingdom,L,South Africa,0,"TensorFlow, Azure, NLP",Associate,11,Finance,2024-08-28,2024-10-29,2193,9.1,Future Systems -AI00940,Head of AI,27765,USD,27765,EN,CT,China,S,China,0,"MLOps, Deep Learning, Python, Tableau",Bachelor,1,Consulting,2025-01-15,2025-02-12,968,9.3,Cloud AI Solutions -AI00941,NLP Engineer,170181,USD,170181,EX,PT,Ireland,M,Ireland,100,"Deep Learning, Python, Azure, TensorFlow",Bachelor,11,Gaming,2024-12-26,2025-01-24,2089,8,DataVision Ltd -AI00942,ML Ops Engineer,103167,USD,103167,MI,CT,United States,M,United States,100,"AWS, Kubernetes, MLOps",Associate,2,Healthcare,2024-04-05,2024-04-21,1873,8,Predictive Systems -AI00943,ML Ops Engineer,194546,USD,194546,EX,PT,Sweden,L,Sweden,0,"TensorFlow, Docker, Python, Hadoop",Master,16,Retail,2025-01-07,2025-03-05,1532,7.2,Digital Transformation LLC -AI00944,Research Scientist,130072,USD,130072,EX,CT,Israel,S,Israel,100,"R, Data Visualization, Java",Master,13,Government,2024-10-14,2024-11-20,2006,5.4,Cloud AI Solutions -AI00945,AI Specialist,39197,USD,39197,EN,PT,China,L,Australia,0,"Kubernetes, Java, SQL, NLP",Associate,1,Energy,2024-05-17,2024-07-08,1770,6.7,Quantum Computing Inc -AI00946,Autonomous Systems Engineer,204421,EUR,173758,EX,FL,Austria,L,Austria,50,"PyTorch, Data Visualization, Azure",Master,14,Energy,2024-07-30,2024-09-05,2389,8.5,Neural Networks Co -AI00947,Head of AI,112925,CHF,101633,EN,FT,Switzerland,L,Switzerland,100,"SQL, GCP, Spark, Azure, Linux",Bachelor,0,Government,2024-11-07,2024-11-26,1221,5.7,DataVision Ltd -AI00948,Data Scientist,265788,SGD,345524,EX,FT,Singapore,M,Turkey,0,"MLOps, Data Visualization, Scala, Python, AWS",Associate,18,Technology,2025-01-26,2025-04-07,2270,5.4,Smart Analytics -AI00949,Machine Learning Researcher,98150,USD,98150,EN,FL,Denmark,L,Denmark,0,"Data Visualization, Java, Hadoop",PhD,1,Energy,2025-03-11,2025-04-27,1648,7.6,Autonomous Tech -AI00950,Data Engineer,126741,USD,126741,SE,FL,United States,S,Romania,50,"PyTorch, Data Visualization, Azure, Computer Vision",Master,9,Finance,2024-05-29,2024-07-20,1974,5.9,Predictive Systems -AI00951,ML Ops Engineer,75006,USD,75006,EN,FL,Israel,M,Austria,100,"MLOps, TensorFlow, Scala",Associate,1,Finance,2024-02-15,2024-03-01,1642,7.3,DeepTech Ventures -AI00952,AI Research Scientist,84346,EUR,71694,MI,FT,Austria,S,France,0,"Statistics, Spark, GCP",Associate,4,Manufacturing,2024-09-20,2024-10-27,2188,7.5,DataVision Ltd -AI00953,Autonomous Systems Engineer,48241,USD,48241,SE,PT,India,M,India,50,"SQL, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-03-16,2025-05-06,2398,9.9,Neural Networks Co -AI00954,Research Scientist,162681,EUR,138279,EX,CT,Germany,L,Germany,50,"Python, Scala, Data Visualization",Associate,18,Telecommunications,2025-02-21,2025-03-09,2201,9.8,Advanced Robotics -AI00955,Deep Learning Engineer,125204,JPY,13772440,SE,CT,Japan,S,Vietnam,100,"Data Visualization, Kubernetes, Scala, NLP",Master,7,Retail,2024-04-30,2024-05-20,2284,5.9,Cloud AI Solutions -AI00956,Machine Learning Engineer,140001,EUR,119001,SE,FT,Netherlands,M,Luxembourg,50,"Python, TensorFlow, GCP, Computer Vision, Java",Bachelor,8,Manufacturing,2024-12-14,2025-02-06,1825,6.5,Autonomous Tech -AI00957,AI Software Engineer,162125,AUD,218869,SE,FT,Australia,L,Austria,100,"Computer Vision, Docker, TensorFlow",Bachelor,8,Consulting,2024-12-10,2025-02-07,565,5.4,Predictive Systems -AI00958,Deep Learning Engineer,128132,SGD,166572,SE,FL,Singapore,S,Japan,100,"Python, NLP, TensorFlow",PhD,7,Technology,2024-08-10,2024-09-24,1112,6.2,Cognitive Computing -AI00959,NLP Engineer,225554,USD,225554,SE,FT,Denmark,L,Latvia,50,"PyTorch, R, Docker",Bachelor,8,Technology,2024-09-12,2024-11-17,1301,9.3,Cloud AI Solutions -AI00960,ML Ops Engineer,130639,EUR,111043,SE,FT,Germany,M,Germany,0,"Python, Hadoop, PyTorch, Git, TensorFlow",PhD,7,Healthcare,2024-09-12,2024-11-12,1996,6.9,TechCorp Inc -AI00961,Data Analyst,66422,USD,66422,EN,FT,United States,S,United States,0,"Python, Hadoop, Kubernetes",Associate,0,Retail,2024-05-13,2024-07-18,1765,5.4,Autonomous Tech -AI00962,AI Architect,54625,CAD,68281,EN,CT,Canada,S,Ireland,0,"Scala, SQL, GCP, Computer Vision, Mathematics",Bachelor,0,Technology,2024-05-01,2024-07-08,1946,5.7,Cloud AI Solutions -AI00963,ML Ops Engineer,135145,USD,135145,MI,PT,Norway,M,Norway,50,"SQL, Docker, PyTorch, GCP, Kubernetes",Bachelor,3,Automotive,2025-04-27,2025-05-15,998,7.5,Smart Analytics -AI00964,ML Ops Engineer,61177,CAD,76471,EN,FL,Canada,S,Canada,100,"Spark, R, AWS, GCP, MLOps",Bachelor,0,Consulting,2025-04-04,2025-05-30,1465,6.8,Cognitive Computing -AI00965,AI Product Manager,74961,USD,74961,EX,FT,China,L,China,100,"Kubernetes, Git, Java, Azure, Tableau",PhD,16,Consulting,2024-07-17,2024-09-05,954,6.8,Smart Analytics -AI00966,NLP Engineer,47280,USD,47280,MI,PT,China,M,China,100,"Computer Vision, TensorFlow, Statistics, Python",PhD,2,Finance,2025-03-30,2025-06-05,985,9.4,Algorithmic Solutions -AI00967,Research Scientist,141577,USD,141577,EX,PT,Finland,S,Finland,50,"AWS, SQL, Python",Associate,13,Transportation,2024-09-16,2024-10-16,1955,6.1,TechCorp Inc -AI00968,NLP Engineer,130504,CHF,117454,EN,FT,Switzerland,L,Philippines,100,"Spark, MLOps, Tableau, Git",Bachelor,0,Media,2025-02-11,2025-02-26,691,8.4,Neural Networks Co -AI00969,Research Scientist,107421,USD,107421,MI,CT,Norway,S,Norway,50,"Git, Docker, Tableau, PyTorch",Bachelor,2,Consulting,2024-08-02,2024-09-23,1782,8.9,DataVision Ltd -AI00970,Data Analyst,93042,USD,93042,MI,PT,United States,S,United States,50,"Statistics, Linux, Git, Hadoop, Mathematics",Master,2,Finance,2024-10-14,2024-11-02,803,5.2,DataVision Ltd -AI00971,AI Consultant,168047,USD,168047,EX,FL,Ireland,L,Ireland,0,"Data Visualization, Linux, Docker, Python, GCP",Master,11,Government,2024-06-25,2024-08-04,1693,9.7,Predictive Systems -AI00972,AI Specialist,27281,USD,27281,EN,PT,China,S,Latvia,100,"Java, SQL, Tableau, GCP",PhD,1,Telecommunications,2025-01-04,2025-03-01,1739,7.1,Advanced Robotics -AI00973,Research Scientist,99145,USD,99145,MI,FL,United States,M,United States,100,"Kubernetes, Mathematics, Data Visualization, MLOps, Hadoop",Master,4,Media,2025-01-20,2025-03-09,954,9.2,Advanced Robotics -AI00974,Deep Learning Engineer,121002,USD,121002,SE,PT,Finland,S,Finland,100,"AWS, NLP, Kubernetes",Master,8,Consulting,2024-03-07,2024-05-12,1557,8.6,Cognitive Computing -AI00975,Data Scientist,259814,USD,259814,EX,PT,Norway,M,Vietnam,50,"PyTorch, R, TensorFlow, AWS, Statistics",Associate,12,Automotive,2024-04-15,2024-05-07,1416,5,DeepTech Ventures -AI00976,Computer Vision Engineer,209072,EUR,177711,EX,CT,France,L,France,100,"TensorFlow, PyTorch, SQL, AWS",Bachelor,15,Transportation,2024-03-23,2024-05-16,1826,7,Predictive Systems -AI00977,AI Software Engineer,50802,USD,50802,SE,CT,China,M,Russia,50,"MLOps, Computer Vision, Data Visualization, Java",PhD,5,Energy,2024-10-13,2024-11-20,501,6.5,Cognitive Computing -AI00978,NLP Engineer,112292,JPY,12352120,MI,PT,Japan,M,Japan,100,"Docker, Hadoop, Kubernetes, AWS",Bachelor,2,Gaming,2024-09-04,2024-10-30,875,8.7,TechCorp Inc -AI00979,Machine Learning Engineer,255076,USD,255076,EX,PT,Ireland,L,Finland,0,"Azure, Docker, Scala",PhD,15,Finance,2024-12-15,2025-02-21,1651,6.2,Digital Transformation LLC -AI00980,Head of AI,75393,EUR,64084,MI,FL,Netherlands,S,Finland,50,"Scala, Hadoop, Linux, GCP",Master,2,Consulting,2024-12-15,2025-01-30,1146,5.1,Quantum Computing Inc -AI00981,Head of AI,96519,USD,96519,EN,FL,United States,L,United States,100,"TensorFlow, Tableau, Git, Scala",Master,1,Finance,2024-07-24,2024-09-08,984,9.6,Autonomous Tech -AI00982,Deep Learning Engineer,135767,USD,135767,SE,FL,Sweden,L,Ukraine,50,"Scala, Azure, Git, Python, R",Associate,7,Gaming,2024-09-05,2024-10-13,736,8.7,DataVision Ltd -AI00983,AI Research Scientist,169082,USD,169082,EX,FT,Finland,L,Finland,50,"GCP, Hadoop, Python, Tableau, Mathematics",Master,17,Finance,2024-02-10,2024-03-22,914,6.9,Quantum Computing Inc -AI00984,AI Software Engineer,91630,EUR,77886,MI,FL,Germany,L,United States,50,"SQL, Linux, Data Visualization, NLP",Bachelor,3,Finance,2024-12-31,2025-03-04,2243,5.6,Machine Intelligence Group -AI00985,Research Scientist,172863,USD,172863,EX,CT,United States,M,United States,100,"SQL, Scala, Kubernetes",Bachelor,13,Transportation,2024-10-24,2024-11-08,2023,8.9,DataVision Ltd -AI00986,Head of AI,103897,USD,103897,MI,FL,Finland,L,Finland,100,"Scala, Java, Git, Azure, R",Associate,3,Retail,2025-04-06,2025-05-02,1242,8.9,Future Systems -AI00987,Computer Vision Engineer,93834,CAD,117293,MI,PT,Canada,L,Canada,100,"TensorFlow, PyTorch, AWS",Associate,2,Gaming,2024-09-01,2024-10-21,1303,5.8,Smart Analytics -AI00988,Autonomous Systems Engineer,53634,GBP,40226,EN,CT,United Kingdom,S,United Kingdom,0,"SQL, Hadoop, Kubernetes",PhD,0,Telecommunications,2025-04-16,2025-06-15,1608,7.3,Machine Intelligence Group -AI00989,AI Research Scientist,127594,USD,127594,SE,FT,Finland,L,Finland,0,"Python, TensorFlow, Hadoop, PyTorch",Bachelor,8,Automotive,2024-12-19,2025-02-24,926,6.4,Future Systems -AI00990,AI Product Manager,292915,CHF,263624,EX,FT,Switzerland,L,Thailand,100,"Data Visualization, Python, R, Azure",Bachelor,16,Media,2025-01-14,2025-02-25,2345,8.2,Future Systems -AI00991,Data Scientist,174020,USD,174020,EX,FT,Israel,S,Israel,100,"TensorFlow, PyTorch, MLOps, Computer Vision",Bachelor,18,Media,2025-01-25,2025-04-08,2090,6.6,Cloud AI Solutions -AI00992,ML Ops Engineer,88526,EUR,75247,MI,CT,Germany,S,Egypt,100,"Python, Git, MLOps, NLP, Spark",Master,4,Real Estate,2025-03-05,2025-05-17,1279,7.6,Cognitive Computing -AI00993,AI Software Engineer,74475,AUD,100541,EN,PT,Australia,M,Australia,0,"TensorFlow, Data Visualization, R",Associate,1,Transportation,2024-09-09,2024-10-10,734,9.8,Neural Networks Co -AI00994,Deep Learning Engineer,96427,USD,96427,EX,CT,China,S,China,100,"Computer Vision, Hadoop, Statistics, Deep Learning",PhD,18,Automotive,2024-10-10,2024-11-10,1393,7.3,Cognitive Computing -AI00995,ML Ops Engineer,225810,SGD,293553,EX,FT,Singapore,S,India,100,"Data Visualization, Spark, Kubernetes",PhD,19,Gaming,2025-02-19,2025-04-15,1937,8.2,Cloud AI Solutions -AI00996,AI Research Scientist,168512,EUR,143235,EX,CT,Netherlands,S,Hungary,0,"Java, Linux, MLOps, Tableau",Bachelor,10,Consulting,2024-10-15,2024-11-29,929,6.5,Cognitive Computing -AI00997,Head of AI,168159,GBP,126119,EX,CT,United Kingdom,M,United Kingdom,50,"Azure, PyTorch, GCP, Deep Learning, Kubernetes",PhD,14,Finance,2024-05-26,2024-06-27,1479,5.4,Cognitive Computing -AI00998,Research Scientist,59148,CAD,73935,EN,CT,Canada,L,Canada,0,"AWS, R, PyTorch",PhD,1,Government,2024-11-07,2024-12-12,1951,7.1,Predictive Systems -AI00999,Data Analyst,65802,GBP,49352,EN,PT,United Kingdom,L,Ghana,100,"Azure, Hadoop, Git",PhD,0,Telecommunications,2024-03-20,2024-05-18,1364,6.8,DataVision Ltd -AI01000,AI Architect,110206,EUR,93675,MI,CT,France,L,France,100,"Git, R, Python, Azure, Tableau",PhD,4,Finance,2024-11-29,2025-01-07,903,6.5,Autonomous Tech -AI01001,Data Analyst,149976,EUR,127480,SE,FL,France,L,France,100,"GCP, Git, Data Visualization, PyTorch",Bachelor,9,Energy,2024-05-31,2024-08-07,1685,7.2,TechCorp Inc -AI01002,Principal Data Scientist,179731,AUD,242637,EX,CT,Australia,M,Australia,50,"Python, GCP, Kubernetes, Deep Learning",Bachelor,18,Education,2024-03-29,2024-05-12,2328,7.2,Algorithmic Solutions -AI01003,Research Scientist,148216,USD,148216,EX,FL,Israel,S,Israel,100,"Kubernetes, Python, Scala, Computer Vision",PhD,10,Telecommunications,2024-12-13,2025-02-14,1572,6.3,Machine Intelligence Group -AI01004,AI Research Scientist,69697,CAD,87121,MI,FL,Canada,S,Canada,0,"GCP, AWS, Hadoop, Statistics, Docker",PhD,4,Automotive,2025-01-05,2025-03-09,1809,6.1,Future Systems -AI01005,Autonomous Systems Engineer,193479,CHF,174131,SE,CT,Switzerland,S,Switzerland,50,"Computer Vision, Linux, Tableau, NLP",Associate,6,Manufacturing,2025-02-01,2025-04-12,1620,9,Predictive Systems -AI01006,Data Engineer,27327,USD,27327,EN,CT,India,M,India,100,"Hadoop, Python, SQL, Azure, Kubernetes",PhD,1,Gaming,2024-03-10,2024-04-08,858,8.8,AI Innovations -AI01007,Deep Learning Engineer,175817,USD,175817,SE,PT,Denmark,L,Denmark,50,"SQL, Python, GCP, Computer Vision",PhD,9,Automotive,2024-12-14,2025-02-05,2179,10,Future Systems -AI01008,AI Software Engineer,79605,EUR,67664,MI,FT,France,S,France,50,"Mathematics, SQL, Computer Vision",PhD,2,Technology,2024-05-03,2024-07-10,1656,9.9,Smart Analytics -AI01009,AI Specialist,136610,USD,136610,SE,FL,Denmark,M,Denmark,100,"NLP, Azure, Data Visualization, Kubernetes",Bachelor,6,Education,2024-10-29,2025-01-06,1763,9.8,TechCorp Inc -AI01010,Data Scientist,54165,EUR,46040,EN,CT,France,S,France,100,"PyTorch, Git, Mathematics, SQL",PhD,1,Healthcare,2024-12-17,2025-01-12,1474,7,DataVision Ltd -AI01011,AI Consultant,82548,USD,82548,EN,FL,Denmark,S,Malaysia,50,"R, Tableau, Kubernetes",Associate,1,Real Estate,2025-02-20,2025-03-18,1171,6.9,AI Innovations -AI01012,Research Scientist,149033,USD,149033,EX,FL,South Korea,M,South Korea,100,"SQL, R, Docker, Data Visualization",Bachelor,17,Technology,2024-06-15,2024-08-13,1619,9.1,Machine Intelligence Group -AI01013,Machine Learning Engineer,26672,USD,26672,MI,PT,India,M,India,50,"AWS, PyTorch, MLOps, Deep Learning",PhD,2,Real Estate,2024-11-21,2025-01-10,1601,9.1,Algorithmic Solutions -AI01014,AI Consultant,103610,USD,103610,MI,FT,Sweden,L,Sweden,50,"Mathematics, Python, TensorFlow, Scala",Associate,3,Government,2024-07-02,2024-08-27,859,6.4,Predictive Systems -AI01015,Principal Data Scientist,59901,GBP,44926,EN,CT,United Kingdom,M,Colombia,100,"R, Hadoop, Python, Computer Vision",Bachelor,1,Finance,2024-03-20,2024-05-27,2189,8.2,Cognitive Computing -AI01016,Machine Learning Engineer,84403,USD,84403,MI,FT,Finland,M,India,0,"Tableau, Spark, Python",PhD,4,Finance,2024-09-10,2024-11-05,2085,5.6,Neural Networks Co -AI01017,AI Product Manager,235236,EUR,199951,EX,FL,France,M,South Africa,50,"GCP, Python, Data Visualization, MLOps, TensorFlow",Associate,10,Healthcare,2024-09-01,2024-10-11,2164,7.5,Machine Intelligence Group -AI01018,AI Research Scientist,140841,USD,140841,SE,FL,United States,S,United States,100,"Python, TensorFlow, Kubernetes",PhD,9,Finance,2024-10-17,2024-11-29,1005,5.2,Future Systems -AI01019,Deep Learning Engineer,64188,EUR,54560,EN,PT,Austria,M,Austria,0,"Kubernetes, Scala, Mathematics, SQL",Bachelor,1,Media,2025-01-16,2025-02-01,2217,5.6,Digital Transformation LLC -AI01020,Principal Data Scientist,140677,CHF,126609,SE,FL,Switzerland,S,Switzerland,100,"Python, TensorFlow, GCP, PyTorch",PhD,6,Retail,2024-05-22,2024-06-14,1249,5.2,Machine Intelligence Group -AI01021,Research Scientist,275555,USD,275555,EX,FT,Ireland,L,Egypt,0,"R, Linux, Scala",Associate,15,Retail,2024-12-16,2025-01-14,801,6.9,TechCorp Inc -AI01022,AI Specialist,174133,CHF,156720,SE,FT,Switzerland,M,Switzerland,0,"R, Deep Learning, TensorFlow",Associate,8,Real Estate,2025-01-23,2025-02-18,1540,9.6,Smart Analytics -AI01023,Machine Learning Engineer,49918,USD,49918,EN,CT,South Korea,M,South Korea,0,"Git, Python, SQL",PhD,0,Manufacturing,2025-04-17,2025-05-07,1226,8.1,AI Innovations -AI01024,Computer Vision Engineer,211602,USD,211602,EX,FL,Norway,L,Turkey,50,"AWS, Hadoop, NLP, Computer Vision, Statistics",Master,16,Real Estate,2025-03-27,2025-04-30,1244,7.3,Neural Networks Co -AI01025,AI Software Engineer,192792,USD,192792,EX,FT,Israel,L,Ireland,50,"Scala, NLP, SQL, Linux, Docker",PhD,15,Technology,2024-06-12,2024-08-11,2314,6.2,Digital Transformation LLC -AI01026,AI Specialist,70846,EUR,60219,MI,CT,Austria,S,Turkey,100,"TensorFlow, Java, R",Associate,4,Gaming,2024-02-11,2024-04-07,1268,9.4,Digital Transformation LLC -AI01027,AI Architect,93783,USD,93783,EN,PT,United States,M,United States,100,"MLOps, Java, Azure, Mathematics, PyTorch",Bachelor,1,Finance,2024-05-19,2024-06-10,1828,10,Neural Networks Co -AI01028,AI Architect,41072,USD,41072,MI,FT,China,S,China,0,"R, Docker, MLOps",Associate,3,Telecommunications,2024-04-11,2024-05-24,2158,6.6,Advanced Robotics -AI01029,AI Architect,102805,CAD,128506,MI,PT,Canada,M,Switzerland,100,"Azure, TensorFlow, Data Visualization, NLP",Master,3,Education,2024-12-16,2025-02-02,1000,9.9,Autonomous Tech -AI01030,AI Product Manager,113537,USD,113537,MI,FT,Ireland,L,Ireland,0,"GCP, Scala, Hadoop",PhD,4,Media,2024-01-20,2024-03-21,1063,8.1,DeepTech Ventures -AI01031,Research Scientist,73590,USD,73590,EN,FL,Denmark,M,Denmark,100,"Python, Git, Tableau, R",Master,1,Retail,2024-11-01,2024-12-27,1490,9.2,Digital Transformation LLC -AI01032,Computer Vision Engineer,96582,USD,96582,EN,CT,Denmark,L,Denmark,100,"Java, Computer Vision, GCP",PhD,0,Real Estate,2024-08-27,2024-09-29,649,9.1,DataVision Ltd -AI01033,AI Research Scientist,62705,USD,62705,EN,PT,Israel,M,India,0,"Java, GCP, Linux, Spark, Python",Bachelor,0,Gaming,2024-10-19,2024-12-08,723,5.1,Smart Analytics -AI01034,AI Product Manager,77955,GBP,58466,EN,FT,United Kingdom,M,United Kingdom,50,"Data Visualization, Computer Vision, Scala",Master,0,Education,2024-06-07,2024-07-04,2444,7,Autonomous Tech -AI01035,Data Analyst,129874,AUD,175330,EX,FT,Australia,S,Australia,0,"Linux, Statistics, Computer Vision",PhD,15,Education,2024-11-16,2024-12-05,2443,7.5,Quantum Computing Inc -AI01036,AI Architect,106907,GBP,80180,MI,CT,United Kingdom,L,United Kingdom,100,"NLP, Java, SQL, Spark, Mathematics",Associate,4,Gaming,2024-12-08,2025-02-16,1589,7.3,Algorithmic Solutions -AI01037,AI Consultant,110152,USD,110152,MI,CT,United States,L,United States,0,"Tableau, Azure, R, NLP",Bachelor,4,Gaming,2024-02-24,2024-03-27,976,8.9,Cognitive Computing -AI01038,AI Research Scientist,49922,USD,49922,MI,FT,China,L,China,50,"Azure, Spark, Scala, SQL, Deep Learning",Bachelor,4,Government,2024-07-26,2024-09-14,1580,8.8,DataVision Ltd -AI01039,AI Software Engineer,84890,USD,84890,EN,CT,Ireland,L,Ireland,100,"GCP, Hadoop, Azure, Scala",PhD,0,Gaming,2024-05-28,2024-07-01,2159,9.2,Cloud AI Solutions -AI01040,Data Scientist,73564,EUR,62529,MI,PT,France,M,Singapore,50,"Scala, Tableau, Docker, SQL, Mathematics",Associate,4,Consulting,2024-04-05,2024-05-26,1702,7.5,Cognitive Computing -AI01041,Autonomous Systems Engineer,196201,USD,196201,SE,PT,United States,L,Philippines,0,"Git, Python, Java",Master,5,Consulting,2025-02-15,2025-04-07,1756,8.8,Cloud AI Solutions -AI01042,NLP Engineer,164425,USD,164425,SE,CT,Finland,L,Italy,0,"GCP, Docker, R, Git",Master,9,Education,2024-07-17,2024-09-02,1881,5.6,Autonomous Tech -AI01043,ML Ops Engineer,158518,JPY,17436980,SE,FT,Japan,L,United Kingdom,0,"GCP, NLP, Deep Learning, Docker, R",Bachelor,6,Healthcare,2025-02-06,2025-02-25,2218,7.2,Quantum Computing Inc -AI01044,Autonomous Systems Engineer,137246,USD,137246,MI,PT,Norway,M,Norway,100,"TensorFlow, Kubernetes, AWS, Linux, Docker",Bachelor,4,Consulting,2024-04-12,2024-05-14,609,8.4,Machine Intelligence Group -AI01045,NLP Engineer,222330,EUR,188981,EX,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Scala",Associate,15,Automotive,2025-04-08,2025-05-12,1335,9.6,Autonomous Tech -AI01046,ML Ops Engineer,73721,USD,73721,MI,FL,Israel,S,Sweden,100,"Java, Tableau, MLOps",Master,2,Real Estate,2025-03-06,2025-04-14,1797,5.2,Predictive Systems -AI01047,AI Software Engineer,125284,CHF,112756,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, SQL, Hadoop, Spark, Deep Learning",Associate,3,Healthcare,2024-02-01,2024-02-15,553,9.4,DeepTech Ventures -AI01048,AI Software Engineer,266424,USD,266424,EX,PT,Ireland,L,Ireland,50,"Azure, Scala, R, Tableau",PhD,17,Education,2024-04-19,2024-06-26,515,5.2,DataVision Ltd -AI01049,AI Consultant,158788,EUR,134970,EX,FL,France,S,France,50,"Linux, Mathematics, SQL",Associate,14,Automotive,2025-03-07,2025-04-12,559,7,Advanced Robotics -AI01050,Autonomous Systems Engineer,99628,SGD,129516,MI,FL,Singapore,S,Singapore,100,"PyTorch, AWS, Azure, Kubernetes, MLOps",Associate,3,Government,2024-07-22,2024-08-27,799,5.1,Smart Analytics -AI01051,AI Architect,52727,GBP,39545,EN,FT,United Kingdom,S,Austria,100,"Java, SQL, Linux",Bachelor,1,Energy,2025-03-17,2025-05-24,1166,9,Neural Networks Co -AI01052,AI Specialist,38473,USD,38473,MI,PT,India,L,India,100,"Tableau, Spark, Scala, NLP",Master,4,Manufacturing,2024-10-05,2024-11-03,2320,7.9,Smart Analytics -AI01053,Machine Learning Researcher,64133,USD,64133,EN,PT,United States,M,Sweden,0,"Azure, AWS, TensorFlow, Hadoop",Master,1,Real Estate,2024-09-24,2024-12-03,955,7.8,DataVision Ltd -AI01054,Data Analyst,47110,CAD,58888,EN,CT,Canada,S,Canada,50,"Java, Linux, Kubernetes, Azure",Bachelor,1,Media,2024-11-26,2025-01-06,844,8.4,Quantum Computing Inc -AI01055,Machine Learning Engineer,71783,EUR,61016,EN,CT,France,L,France,50,"Mathematics, SQL, Computer Vision",Associate,1,Media,2024-07-31,2024-10-07,524,8.8,Cognitive Computing -AI01056,AI Software Engineer,83829,USD,83829,EN,FL,Norway,S,India,50,"PyTorch, TensorFlow, Statistics, Hadoop, Python",Bachelor,0,Finance,2024-06-18,2024-08-29,1929,8.3,TechCorp Inc -AI01057,Robotics Engineer,91511,USD,91511,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, Mathematics, Spark",PhD,4,Technology,2024-11-17,2024-12-09,1221,5.7,Quantum Computing Inc -AI01058,ML Ops Engineer,198095,EUR,168381,EX,PT,France,S,France,50,"Git, R, Python, Scala",PhD,14,Education,2024-07-01,2024-08-27,1815,9.5,Machine Intelligence Group -AI01059,AI Product Manager,119407,USD,119407,SE,PT,Norway,S,Norway,0,"Git, Java, Tableau, Linux, Deep Learning",PhD,7,Manufacturing,2025-02-15,2025-03-24,2040,6.2,Algorithmic Solutions -AI01060,Data Engineer,87493,USD,87493,MI,FL,Denmark,S,Denmark,100,"MLOps, Hadoop, Linux, Scala",PhD,4,Energy,2024-12-04,2025-01-21,2032,6.5,Advanced Robotics -AI01061,Data Engineer,121335,USD,121335,SE,PT,Norway,S,Norway,50,"Python, Spark, Mathematics, SQL",Associate,7,Automotive,2024-12-06,2025-01-11,1573,7.9,DeepTech Ventures -AI01062,AI Architect,289174,SGD,375926,EX,FL,Singapore,L,Singapore,0,"Hadoop, SQL, Data Visualization, Deep Learning",Master,13,Retail,2025-02-04,2025-03-26,2451,8.5,Cognitive Computing -AI01063,Deep Learning Engineer,154280,USD,154280,SE,CT,Finland,L,Finland,0,"Data Visualization, Python, AWS",Bachelor,5,Education,2024-01-28,2024-03-21,547,9.6,Autonomous Tech -AI01064,Head of AI,62297,CAD,77871,EN,PT,Canada,S,Canada,100,"Mathematics, Hadoop, MLOps, Linux",Associate,0,Healthcare,2024-09-26,2024-11-02,2467,7.4,AI Innovations -AI01065,AI Software Engineer,114311,CAD,142889,MI,FL,Canada,L,Canada,50,"Mathematics, Computer Vision, Python",PhD,2,Telecommunications,2024-04-10,2024-04-27,1979,8.8,TechCorp Inc -AI01066,AI Research Scientist,163458,CAD,204323,SE,CT,Canada,L,Canada,50,"Azure, Python, Deep Learning, Spark",Master,7,Real Estate,2024-07-30,2024-10-05,1096,7.4,Cloud AI Solutions -AI01067,AI Software Engineer,107211,EUR,91129,MI,CT,France,L,Singapore,0,"Statistics, R, Computer Vision",Master,4,Government,2024-10-18,2024-11-13,678,8.4,Machine Intelligence Group -AI01068,Deep Learning Engineer,136382,USD,136382,MI,FL,Denmark,M,Spain,50,"AWS, Mathematics, NLP",PhD,2,Transportation,2024-10-03,2024-12-06,1219,6.1,AI Innovations -AI01069,Head of AI,249477,CHF,224529,EX,CT,Switzerland,S,Switzerland,50,"NLP, Hadoop, Python, Data Visualization, R",Associate,11,Government,2024-01-31,2024-03-01,1495,7.3,Predictive Systems -AI01070,Data Analyst,177617,EUR,150974,EX,PT,France,M,France,0,"AWS, TensorFlow, Data Visualization, Deep Learning",Master,11,Gaming,2024-12-13,2025-01-06,1493,8,Predictive Systems -AI01071,Computer Vision Engineer,66870,EUR,56840,EN,FL,Austria,M,Austria,0,"Azure, Deep Learning, Python, Git, Docker",Associate,1,Technology,2024-06-09,2024-07-08,2209,9.8,TechCorp Inc -AI01072,AI Software Engineer,79882,EUR,67900,MI,PT,Netherlands,M,Netherlands,0,"Spark, Hadoop, Git, Python, R",Associate,3,Education,2024-10-14,2024-11-16,1560,6.2,AI Innovations -AI01073,AI Research Scientist,114997,EUR,97747,MI,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Python",Bachelor,4,Telecommunications,2024-03-10,2024-03-25,1176,8.2,Predictive Systems -AI01074,Principal Data Scientist,67556,CHF,60800,EN,FT,Switzerland,S,Switzerland,100,"MLOps, Python, Hadoop, Kubernetes, Deep Learning",Master,1,Finance,2024-10-19,2024-12-07,885,6.6,Algorithmic Solutions -AI01075,Deep Learning Engineer,50726,USD,50726,SE,FT,India,M,Australia,0,"Java, AWS, R, Computer Vision, Git",Master,9,Telecommunications,2024-05-02,2024-05-18,556,8.3,Neural Networks Co -AI01076,Data Scientist,45956,EUR,39063,EN,FT,France,S,Italy,0,"Data Visualization, MLOps, AWS",PhD,1,Consulting,2024-11-12,2024-12-14,2065,6.6,Smart Analytics -AI01077,Data Engineer,29934,USD,29934,MI,FT,India,S,India,50,"SQL, Kubernetes, MLOps, Scala, Linux",Bachelor,2,Technology,2024-07-10,2024-08-01,2366,7,DataVision Ltd -AI01078,Deep Learning Engineer,89070,USD,89070,EX,PT,India,M,United Kingdom,0,"Python, Scala, Linux, GCP, Deep Learning",Associate,14,Technology,2025-02-23,2025-04-20,1673,8.1,Autonomous Tech -AI01079,AI Consultant,123195,EUR,104716,SE,FT,Germany,L,Chile,100,"GCP, SQL, Tableau, Spark, Mathematics",Bachelor,6,Finance,2024-12-16,2025-01-21,1581,8.6,Digital Transformation LLC -AI01080,Research Scientist,83392,USD,83392,MI,PT,South Korea,L,Singapore,100,"R, PyTorch, Tableau, Deep Learning, GCP",Associate,3,Automotive,2024-03-27,2024-06-05,1328,7.3,Digital Transformation LLC -AI01081,Principal Data Scientist,241040,USD,241040,EX,FT,Norway,S,Norway,100,"Azure, Linux, Data Visualization",PhD,18,Retail,2024-04-15,2024-06-08,2485,6.9,Cloud AI Solutions -AI01082,AI Consultant,226924,GBP,170193,EX,FL,United Kingdom,S,United Kingdom,100,"AWS, Docker, Kubernetes, Deep Learning, Tableau",Bachelor,17,Government,2024-08-30,2024-10-29,860,8.1,Neural Networks Co -AI01083,Data Analyst,28173,USD,28173,EN,FL,India,M,Singapore,100,"R, SQL, AWS",PhD,1,Gaming,2024-03-17,2024-04-23,2356,8.7,Predictive Systems -AI01084,Autonomous Systems Engineer,96863,EUR,82334,MI,PT,France,M,France,0,"Python, TensorFlow, Tableau",PhD,3,Government,2024-08-18,2024-10-19,1317,7.6,Future Systems -AI01085,ML Ops Engineer,126853,USD,126853,EX,FT,China,L,China,100,"AWS, Spark, NLP, Azure",PhD,13,Real Estate,2025-04-18,2025-05-12,2007,7.3,Algorithmic Solutions -AI01086,Principal Data Scientist,143421,USD,143421,SE,CT,United States,M,United States,100,"Azure, MLOps, Hadoop",Bachelor,6,Telecommunications,2024-11-07,2024-12-28,1193,9.5,DeepTech Ventures -AI01087,AI Consultant,20785,USD,20785,EN,PT,India,S,India,0,"Kubernetes, Spark, Azure, PyTorch",Master,1,Manufacturing,2024-12-24,2025-01-22,642,6.2,Cognitive Computing -AI01088,AI Research Scientist,67394,EUR,57285,EN,FT,Austria,M,Austria,100,"Tableau, Java, Python, Azure, R",PhD,0,Education,2024-11-07,2024-12-23,989,9.1,Algorithmic Solutions -AI01089,Data Engineer,93436,AUD,126139,MI,CT,Australia,L,Hungary,50,"Tableau, PyTorch, Scala, Azure",Master,3,Gaming,2024-01-21,2024-03-09,1503,6.1,Digital Transformation LLC -AI01090,ML Ops Engineer,95063,EUR,80804,MI,PT,France,M,France,100,"Kubernetes, Spark, Scala",Associate,2,Government,2024-09-08,2024-10-22,2378,9.6,Machine Intelligence Group -AI01091,Computer Vision Engineer,167478,USD,167478,EX,PT,United States,M,United States,100,"Statistics, Git, Docker",Bachelor,18,Healthcare,2024-03-16,2024-04-13,626,7.2,Machine Intelligence Group -AI01092,Autonomous Systems Engineer,139198,CHF,125278,SE,CT,Switzerland,S,Switzerland,100,"Java, Linux, Python, Hadoop, Azure",Master,5,Automotive,2024-02-27,2024-04-05,2301,9.1,Digital Transformation LLC -AI01093,Computer Vision Engineer,215699,USD,215699,EX,PT,Ireland,L,Ireland,0,"Computer Vision, Java, MLOps, AWS",Master,19,Automotive,2024-06-03,2024-06-30,2486,8.5,Advanced Robotics -AI01094,Research Scientist,138827,AUD,187416,EX,CT,Australia,S,Australia,100,"Docker, Data Visualization, Tableau, TensorFlow, AWS",Master,15,Manufacturing,2025-04-28,2025-05-28,1069,9.4,Machine Intelligence Group -AI01095,AI Consultant,79327,JPY,8725970,EN,PT,Japan,M,Japan,100,"AWS, TensorFlow, SQL, Computer Vision",Master,0,Real Estate,2025-02-26,2025-04-20,1008,7.3,Machine Intelligence Group -AI01096,AI Research Scientist,70002,USD,70002,EN,FT,Finland,L,Finland,50,"Mathematics, SQL, Data Visualization, MLOps",Master,1,Gaming,2024-12-31,2025-02-10,2355,9,Cognitive Computing -AI01097,AI Research Scientist,85342,EUR,72541,EN,FL,Netherlands,L,Netherlands,50,"Java, SQL, Spark",Associate,1,Energy,2024-11-25,2025-01-20,1783,6.7,TechCorp Inc -AI01098,AI Architect,116683,SGD,151688,SE,FT,Singapore,M,Singapore,100,"AWS, PyTorch, Python, Spark",Master,5,Automotive,2024-03-27,2024-05-12,2269,5.3,Cloud AI Solutions -AI01099,Head of AI,127338,EUR,108237,EX,CT,France,S,Estonia,50,"Scala, Spark, TensorFlow",Associate,19,Gaming,2024-03-09,2024-04-29,2085,5.1,Cloud AI Solutions -AI01100,Research Scientist,80026,USD,80026,SE,FT,South Korea,S,South Korea,100,"R, Java, Linux, GCP",Master,9,Healthcare,2024-04-24,2024-06-06,1833,6.7,Neural Networks Co -AI01101,Deep Learning Engineer,119475,CHF,107528,EN,PT,Switzerland,L,Switzerland,0,"Spark, Azure, Python",PhD,1,Gaming,2024-05-03,2024-07-14,2219,5.9,Predictive Systems -AI01102,ML Ops Engineer,254552,AUD,343645,EX,CT,Australia,L,Egypt,0,"Deep Learning, Python, Java, GCP, TensorFlow",Associate,12,Transportation,2024-04-23,2024-05-13,1757,5.6,Cognitive Computing -AI01103,Head of AI,118245,USD,118245,SE,PT,Ireland,M,Canada,0,"Mathematics, AWS, Data Visualization, Computer Vision",Master,6,Consulting,2024-08-16,2024-10-08,1898,9.3,Neural Networks Co -AI01104,AI Software Engineer,117254,EUR,99666,SE,FL,Austria,M,Austria,0,"SQL, Data Visualization, R, Spark, GCP",PhD,7,Government,2024-12-26,2025-02-18,2230,9.3,Autonomous Tech -AI01105,Data Scientist,256695,USD,256695,EX,FL,Ireland,L,Ireland,50,"MLOps, Scala, AWS",Bachelor,14,Automotive,2024-06-11,2024-07-26,617,9.1,Autonomous Tech -AI01106,Computer Vision Engineer,188203,USD,188203,EX,FL,Finland,M,Finland,0,"Hadoop, R, Python, Git",Bachelor,15,Real Estate,2024-08-12,2024-09-07,1201,9.4,Advanced Robotics -AI01107,Computer Vision Engineer,191049,USD,191049,EX,FL,United States,S,United States,0,"AWS, Linux, Azure",Bachelor,17,Education,2024-06-02,2024-07-06,887,7.7,AI Innovations -AI01108,AI Product Manager,75973,EUR,64577,EN,FT,Germany,M,Thailand,50,"SQL, NLP, Tableau",Master,1,Automotive,2024-08-16,2024-09-27,646,7.7,DataVision Ltd -AI01109,Machine Learning Researcher,205143,SGD,266686,EX,FT,Singapore,M,Singapore,100,"Scala, Docker, MLOps",PhD,14,Transportation,2024-08-04,2024-08-28,2458,9,Machine Intelligence Group -AI01110,AI Specialist,92600,USD,92600,SE,FT,Ireland,S,Ireland,0,"SQL, Java, Computer Vision",PhD,8,Healthcare,2024-03-03,2024-04-03,1281,6.1,Predictive Systems -AI01111,Research Scientist,307696,USD,307696,EX,CT,Denmark,L,Czech Republic,100,"Data Visualization, TensorFlow, Python, MLOps, Deep Learning",Bachelor,12,Government,2024-09-25,2024-10-17,526,7.3,Advanced Robotics -AI01112,Machine Learning Engineer,289667,USD,289667,EX,FL,United States,L,United States,0,"Mathematics, Scala, PyTorch",Master,15,Automotive,2024-10-26,2024-12-20,2369,6.6,Cognitive Computing -AI01113,AI Product Manager,104108,USD,104108,SE,FT,Sweden,S,Sweden,50,"Spark, Java, R, TensorFlow, SQL",PhD,9,Automotive,2025-01-02,2025-02-26,1083,6.1,Predictive Systems -AI01114,NLP Engineer,85459,USD,85459,EN,FT,Denmark,M,Denmark,50,"Statistics, Spark, PyTorch",Bachelor,1,Retail,2024-07-18,2024-08-13,2416,6.6,DataVision Ltd -AI01115,Computer Vision Engineer,48088,EUR,40875,EN,FT,France,M,France,0,"NLP, Scala, Java",Bachelor,0,Finance,2024-04-08,2024-05-19,1362,9.7,Smart Analytics -AI01116,AI Architect,103764,USD,103764,SE,PT,Sweden,S,Sweden,50,"SQL, Docker, AWS",Associate,9,Manufacturing,2024-11-15,2025-01-01,1227,9.4,Future Systems -AI01117,Deep Learning Engineer,135128,SGD,175666,SE,PT,Singapore,M,Singapore,100,"NLP, R, Azure, SQL, Java",Master,9,Government,2024-05-15,2024-07-11,693,6.1,Machine Intelligence Group -AI01118,NLP Engineer,78044,JPY,8584840,MI,PT,Japan,S,Japan,0,"TensorFlow, Azure, Python, Tableau",Bachelor,4,Gaming,2024-11-08,2024-12-12,1943,7.9,Autonomous Tech -AI01119,Research Scientist,77226,SGD,100394,MI,FT,Singapore,M,Singapore,0,"Scala, Spark, Computer Vision, Python, Tableau",PhD,3,Telecommunications,2024-07-16,2024-08-29,1506,6.6,Predictive Systems -AI01120,Machine Learning Engineer,149651,CAD,187064,EX,CT,Canada,M,Canada,100,"TensorFlow, Python, Kubernetes, MLOps, AWS",Associate,11,Gaming,2024-09-18,2024-11-15,943,7.9,DeepTech Ventures -AI01121,Machine Learning Engineer,183833,EUR,156258,EX,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, R",Associate,10,Healthcare,2025-03-24,2025-05-29,2012,9.6,Future Systems -AI01122,Computer Vision Engineer,104425,EUR,88761,MI,PT,Germany,L,China,0,"MLOps, Java, Python, Kubernetes, Computer Vision",Bachelor,4,Transportation,2024-07-30,2024-08-24,532,5.7,Quantum Computing Inc -AI01123,AI Consultant,163323,USD,163323,EX,CT,Sweden,S,Sweden,0,"NLP, Data Visualization, AWS, Python, TensorFlow",Bachelor,10,Gaming,2024-10-14,2024-11-11,1137,6.6,Autonomous Tech -AI01124,Data Engineer,136850,EUR,116323,EX,FT,Germany,S,Norway,0,"Tableau, Python, TensorFlow, Computer Vision, GCP",PhD,11,Healthcare,2024-08-14,2024-09-02,831,7.2,Cloud AI Solutions -AI01125,AI Consultant,133658,GBP,100244,SE,FL,United Kingdom,S,United Kingdom,100,"Kubernetes, SQL, GCP",PhD,8,Manufacturing,2024-05-17,2024-06-24,1514,6,Smart Analytics -AI01126,AI Specialist,168161,JPY,18497710,SE,FT,Japan,L,Japan,0,"Python, GCP, TensorFlow, Computer Vision, Hadoop",PhD,6,Government,2025-02-06,2025-03-12,2290,5.8,Cloud AI Solutions -AI01127,AI Research Scientist,87945,JPY,9673950,MI,FT,Japan,M,Japan,0,"Computer Vision, PyTorch, Data Visualization",Associate,2,Consulting,2025-04-30,2025-06-13,1525,6.3,Autonomous Tech -AI01128,Data Analyst,150603,USD,150603,SE,FL,Norway,M,Norway,50,"GCP, R, Computer Vision, Linux, SQL",Master,9,Healthcare,2024-05-14,2024-07-09,2451,9.6,Cloud AI Solutions -AI01129,Research Scientist,41667,USD,41667,MI,CT,China,M,China,100,"Data Visualization, Kubernetes, MLOps, TensorFlow",Master,3,Finance,2024-06-03,2024-08-12,1963,9,Cognitive Computing -AI01130,Machine Learning Researcher,270857,USD,270857,EX,FT,Denmark,L,Denmark,0,"Spark, PyTorch, Hadoop",Associate,14,Healthcare,2025-01-09,2025-02-17,1836,7.5,Machine Intelligence Group -AI01131,AI Product Manager,70021,JPY,7702310,EN,FL,Japan,M,South Korea,100,"SQL, Git, Python",Master,1,Automotive,2024-09-30,2024-11-08,2044,9,Machine Intelligence Group -AI01132,Deep Learning Engineer,180120,USD,180120,EX,FL,Finland,S,Finland,50,"PyTorch, R, Java, SQL",Bachelor,19,Gaming,2025-03-21,2025-04-27,2134,9.4,TechCorp Inc -AI01133,Data Analyst,109592,CAD,136990,SE,FT,Canada,S,Kenya,50,"GCP, Spark, AWS, Python, Mathematics",Master,8,Gaming,2024-04-30,2024-06-13,1754,8.9,TechCorp Inc -AI01134,NLP Engineer,248395,EUR,211136,EX,FL,Germany,M,Germany,100,"Kubernetes, Data Visualization, Java, Scala, MLOps",Master,11,Energy,2024-06-19,2024-08-31,2176,7.6,Digital Transformation LLC -AI01135,ML Ops Engineer,166428,EUR,141464,EX,FL,France,S,Luxembourg,50,"Linux, AWS, Deep Learning, Computer Vision",Bachelor,12,Real Estate,2024-10-28,2024-12-07,2272,9.4,DataVision Ltd -AI01136,AI Product Manager,64110,SGD,83343,EN,FL,Singapore,S,Ukraine,50,"Kubernetes, Statistics, Scala, Deep Learning",Master,1,Manufacturing,2024-02-23,2024-03-17,1013,7.7,Autonomous Tech -AI01137,NLP Engineer,89254,USD,89254,MI,CT,Israel,M,Israel,50,"Azure, PyTorch, Data Visualization, Computer Vision, Mathematics",Bachelor,2,Real Estate,2025-02-03,2025-03-03,736,5.6,Neural Networks Co -AI01138,ML Ops Engineer,89632,CAD,112040,SE,FT,Canada,S,Brazil,50,"PyTorch, Git, Python",Master,7,Technology,2024-09-11,2024-10-26,1963,8.9,Digital Transformation LLC -AI01139,Research Scientist,94147,JPY,10356170,MI,FL,Japan,S,Austria,100,"NLP, Python, GCP, Mathematics",Associate,4,Telecommunications,2024-07-04,2024-08-12,2179,9.7,DeepTech Ventures -AI01140,Data Scientist,95536,USD,95536,EX,PT,China,M,Poland,50,"PyTorch, TensorFlow, GCP, NLP",Bachelor,12,Consulting,2024-07-13,2024-08-13,2028,5.3,DataVision Ltd -AI01141,AI Specialist,128104,USD,128104,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, Git, Data Visualization",Master,6,Manufacturing,2024-03-16,2024-04-12,1759,6.7,DeepTech Ventures -AI01142,Data Analyst,224736,USD,224736,EX,FL,Denmark,S,South Africa,100,"Python, TensorFlow, SQL, Kubernetes, AWS",Associate,15,Manufacturing,2024-01-18,2024-02-12,617,6.5,Machine Intelligence Group -AI01143,Principal Data Scientist,132221,JPY,14544310,MI,FT,Japan,L,Japan,0,"Python, Git, GCP, NLP, Hadoop",PhD,4,Consulting,2024-09-26,2024-10-22,1834,9.4,Cloud AI Solutions -AI01144,AI Consultant,107463,EUR,91344,SE,FT,Austria,M,Ireland,0,"Data Visualization, PyTorch, Git, Computer Vision",PhD,7,Media,2025-03-17,2025-04-19,1360,6.3,DataVision Ltd -AI01145,Machine Learning Researcher,200093,CAD,250116,EX,FL,Canada,M,India,50,"Statistics, R, Tableau, Hadoop",Bachelor,18,Real Estate,2024-09-22,2024-11-06,1322,8.4,Advanced Robotics -AI01146,Machine Learning Engineer,168952,AUD,228085,SE,PT,Australia,L,Australia,100,"SQL, R, Hadoop, Docker",Master,7,Finance,2024-02-11,2024-02-25,1398,5.9,Digital Transformation LLC -AI01147,Deep Learning Engineer,223789,JPY,24616790,EX,FT,Japan,S,Japan,100,"Hadoop, SQL, Linux",Bachelor,10,Technology,2024-05-22,2024-06-16,1821,5.2,Machine Intelligence Group -AI01148,Data Engineer,121814,USD,121814,SE,CT,South Korea,L,South Korea,0,"Spark, Linux, Hadoop",PhD,7,Telecommunications,2024-04-11,2024-05-26,808,9.6,Predictive Systems -AI01149,NLP Engineer,188710,USD,188710,EX,PT,Finland,S,Finland,0,"SQL, Hadoop, Tableau",Associate,19,Transportation,2024-05-31,2024-07-28,2221,5.7,Smart Analytics -AI01150,AI Consultant,73645,AUD,99421,MI,PT,Australia,S,Australia,50,"Python, Spark, Data Visualization, NLP",Bachelor,3,Government,2024-03-23,2024-04-22,1750,9.6,Advanced Robotics -AI01151,ML Ops Engineer,167924,GBP,125943,EX,FL,United Kingdom,S,Ghana,0,"Hadoop, SQL, GCP, Scala, Computer Vision",Master,13,Education,2025-03-24,2025-05-11,2123,10,Future Systems -AI01152,NLP Engineer,104995,USD,104995,MI,FT,Sweden,L,Sweden,50,"Tableau, GCP, Mathematics",Bachelor,3,Media,2024-02-10,2024-02-29,2335,5.9,Algorithmic Solutions -AI01153,NLP Engineer,319365,CHF,287429,EX,FT,Switzerland,M,Switzerland,100,"Python, Linux, TensorFlow, AWS",Associate,15,Telecommunications,2024-08-01,2024-08-31,2420,7.4,Advanced Robotics -AI01154,Data Engineer,120902,USD,120902,SE,FL,South Korea,L,South Korea,0,"Linux, Python, MLOps, Spark, Mathematics",PhD,6,Healthcare,2024-12-15,2025-02-07,592,7.2,DataVision Ltd -AI01155,AI Research Scientist,93958,EUR,79864,MI,CT,Germany,M,Latvia,50,"SQL, Data Visualization, Scala",Master,3,Real Estate,2024-11-25,2025-02-04,2028,7.9,Advanced Robotics -AI01156,Machine Learning Researcher,204959,USD,204959,EX,CT,Denmark,L,Denmark,50,"TensorFlow, Python, GCP, R",Bachelor,10,Manufacturing,2025-03-27,2025-04-30,2354,6.1,Digital Transformation LLC -AI01157,Computer Vision Engineer,45750,USD,45750,MI,FL,China,M,Denmark,0,"Statistics, PyTorch, TensorFlow, Computer Vision, Deep Learning",PhD,2,Energy,2025-03-09,2025-03-24,972,7.4,TechCorp Inc -AI01158,Data Engineer,191169,EUR,162494,EX,CT,Germany,M,Egypt,100,"Scala, Java, Computer Vision, AWS",Associate,13,Gaming,2025-03-19,2025-04-03,2281,5.6,Algorithmic Solutions -AI01159,Robotics Engineer,187320,JPY,20605200,EX,PT,Japan,L,Spain,100,"Java, TensorFlow, Data Visualization",PhD,16,Education,2024-09-23,2024-11-10,701,8.8,Cloud AI Solutions -AI01160,AI Architect,45995,USD,45995,SE,FL,China,S,China,0,"Python, TensorFlow, Linux, Statistics",Bachelor,8,Telecommunications,2024-12-03,2024-12-22,1433,8.3,AI Innovations -AI01161,Principal Data Scientist,189388,EUR,160980,EX,FL,France,S,France,50,"TensorFlow, Python, PyTorch, AWS, R",Associate,10,Healthcare,2024-11-23,2025-01-20,2162,9.9,Digital Transformation LLC -AI01162,AI Research Scientist,77764,CHF,69988,EN,PT,Switzerland,M,Ghana,100,"Kubernetes, SQL, Data Visualization",Master,0,Finance,2024-11-28,2024-12-21,1143,8,Cognitive Computing -AI01163,Data Engineer,70260,EUR,59721,EN,FL,Germany,L,Germany,0,"Linux, Data Visualization, MLOps, Git",Master,1,Education,2024-12-05,2025-01-03,604,8,Cloud AI Solutions -AI01164,Autonomous Systems Engineer,59125,EUR,50256,EN,PT,Germany,S,Germany,50,"Scala, Python, Tableau, Computer Vision",PhD,1,Gaming,2024-10-22,2024-12-14,706,7.7,Smart Analytics -AI01165,Head of AI,85915,CHF,77324,EN,FL,Switzerland,S,Switzerland,0,"Python, Tableau, Java, AWS, Statistics",Associate,1,Telecommunications,2025-04-15,2025-05-29,1359,8.5,Cognitive Computing -AI01166,AI Software Engineer,161147,USD,161147,SE,FL,Israel,L,Israel,50,"Spark, Linux, Kubernetes, Hadoop, Python",Associate,9,Energy,2024-09-05,2024-11-03,1023,6.3,Cognitive Computing -AI01167,AI Consultant,145874,USD,145874,EX,PT,Israel,M,Israel,50,"GCP, Statistics, MLOps, Python, AWS",PhD,16,Education,2024-08-23,2024-11-01,1826,9.6,Smart Analytics -AI01168,Research Scientist,41928,USD,41928,MI,PT,India,L,India,50,"AWS, MLOps, NLP",Associate,3,Telecommunications,2024-07-06,2024-09-04,1539,7.1,Quantum Computing Inc -AI01169,NLP Engineer,244108,USD,244108,EX,CT,Denmark,S,Denmark,0,"Hadoop, Python, SQL",Associate,14,Transportation,2024-05-21,2024-06-29,974,8.9,AI Innovations -AI01170,NLP Engineer,74765,CHF,67289,EN,FT,Switzerland,M,Vietnam,50,"Tableau, Deep Learning, Kubernetes, AWS",Master,0,Retail,2025-04-20,2025-06-25,861,6.6,Quantum Computing Inc -AI01171,AI Software Engineer,111797,USD,111797,SE,CT,Finland,S,Finland,50,"Python, MLOps, Linux",Bachelor,8,Finance,2024-07-14,2024-09-06,778,7.1,Cognitive Computing -AI01172,AI Product Manager,129173,AUD,174384,SE,FL,Australia,M,Australia,100,"Scala, Spark, MLOps, Mathematics, Linux",PhD,8,Automotive,2024-08-12,2024-10-10,1154,9.1,Neural Networks Co -AI01173,Robotics Engineer,109849,USD,109849,SE,FL,Ireland,S,Ireland,0,"SQL, TensorFlow, MLOps",Master,5,Transportation,2024-11-08,2024-11-27,1872,9.3,Smart Analytics -AI01174,NLP Engineer,86314,CHF,77683,EN,FL,Switzerland,L,Switzerland,0,"Scala, Python, TensorFlow, Computer Vision",Bachelor,0,Retail,2025-01-30,2025-03-15,2197,9.2,Cognitive Computing -AI01175,AI Product Manager,134718,CHF,121246,MI,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Linux, R",Bachelor,4,Finance,2024-10-09,2024-11-11,2272,6.1,TechCorp Inc -AI01176,Machine Learning Researcher,146659,USD,146659,SE,CT,Sweden,M,Sweden,100,"TensorFlow, PyTorch, Kubernetes",Associate,6,Government,2025-01-24,2025-02-15,2107,8.3,DeepTech Ventures -AI01177,NLP Engineer,207301,GBP,155476,EX,FL,United Kingdom,M,United Kingdom,100,"Java, SQL, Spark, TensorFlow",Master,15,Real Estate,2024-01-06,2024-02-17,1385,6.5,DeepTech Ventures -AI01178,Data Scientist,86551,EUR,73568,MI,CT,Netherlands,S,Netherlands,100,"Scala, Statistics, SQL",PhD,2,Finance,2024-01-18,2024-02-14,752,8.8,Neural Networks Co -AI01179,AI Consultant,101086,SGD,131412,MI,FL,Singapore,L,Latvia,0,"Tableau, AWS, Hadoop, Kubernetes, SQL",Bachelor,2,Automotive,2024-11-02,2024-12-18,1462,10,Autonomous Tech -AI01180,Computer Vision Engineer,243742,USD,243742,EX,FL,Ireland,M,Ireland,100,"Linux, GCP, AWS",Master,16,Automotive,2024-10-18,2024-11-12,972,8.4,Future Systems -AI01181,AI Software Engineer,45910,EUR,39024,EN,FL,Austria,S,Austria,100,"Linux, Data Visualization, Git, Scala",Master,0,Automotive,2024-09-17,2024-10-25,1021,9.7,Machine Intelligence Group -AI01182,Principal Data Scientist,165181,EUR,140404,EX,CT,France,L,France,100,"TensorFlow, NLP, Hadoop, Kubernetes, Python",Bachelor,14,Finance,2024-01-07,2024-02-25,1029,6.7,Quantum Computing Inc -AI01183,Machine Learning Researcher,47299,AUD,63854,EN,PT,Australia,S,Australia,100,"SQL, Linux, Git, Tableau",Master,1,Telecommunications,2024-06-17,2024-07-23,2432,6.8,DeepTech Ventures -AI01184,AI Specialist,69234,CAD,86543,EN,FT,Canada,M,Ireland,100,"Computer Vision, Java, Data Visualization",PhD,0,Retail,2024-01-15,2024-02-13,1184,5,AI Innovations -AI01185,AI Product Manager,95021,SGD,123527,MI,FL,Singapore,L,Belgium,50,"MLOps, Tableau, Python, Docker",Bachelor,3,Telecommunications,2024-10-12,2024-10-26,2138,5.7,Future Systems -AI01186,Machine Learning Engineer,27279,USD,27279,EN,CT,India,L,India,0,"Statistics, Mathematics, Tableau",Associate,0,Real Estate,2024-02-27,2024-03-25,1258,6.5,TechCorp Inc -AI01187,Machine Learning Researcher,74665,SGD,97065,EN,FL,Singapore,S,Singapore,100,"R, Azure, PyTorch",PhD,0,Retail,2024-01-14,2024-03-05,1743,7.5,Advanced Robotics -AI01188,AI Consultant,105569,USD,105569,SE,CT,South Korea,M,France,0,"Python, Java, Data Visualization, Deep Learning",Associate,7,Manufacturing,2024-06-07,2024-07-06,765,6.9,Future Systems -AI01189,Principal Data Scientist,75073,USD,75073,EN,FL,Sweden,M,Sweden,0,"Python, R, Tableau, Data Visualization, AWS",Associate,1,Retail,2024-11-20,2025-01-28,1316,5.8,Future Systems -AI01190,AI Software Engineer,185794,USD,185794,EX,FT,Denmark,M,Singapore,100,"R, MLOps, Computer Vision, Git",PhD,18,Energy,2025-01-27,2025-02-13,691,7.1,DeepTech Ventures -AI01191,AI Specialist,222006,USD,222006,EX,FL,United States,S,New Zealand,100,"Hadoop, Spark, Mathematics",Bachelor,19,Energy,2025-02-19,2025-03-27,987,9.1,TechCorp Inc -AI01192,Robotics Engineer,95988,USD,95988,MI,PT,Ireland,M,Switzerland,0,"PyTorch, Linux, Scala, Mathematics, GCP",Master,2,Real Estate,2025-02-21,2025-03-18,1899,9.6,Autonomous Tech -AI01193,Autonomous Systems Engineer,75420,GBP,56565,EN,CT,United Kingdom,M,Israel,50,"Linux, Spark, TensorFlow, Python",Associate,1,Media,2024-07-03,2024-09-02,1590,5.9,Quantum Computing Inc -AI01194,AI Consultant,56066,CAD,70083,EN,FL,Canada,S,Japan,0,"Spark, Kubernetes, TensorFlow",PhD,0,Technology,2024-09-28,2024-10-28,1278,9.1,Neural Networks Co -AI01195,ML Ops Engineer,34199,USD,34199,MI,CT,India,S,India,100,"Java, Kubernetes, Azure, GCP",Associate,3,Energy,2025-02-11,2025-04-09,1150,6.6,DeepTech Ventures -AI01196,Robotics Engineer,123046,USD,123046,SE,PT,Israel,M,Israel,50,"Python, Docker, Data Visualization, MLOps, Deep Learning",Master,9,Media,2024-09-13,2024-10-08,1501,6.8,Predictive Systems -AI01197,Research Scientist,155715,EUR,132358,SE,CT,Austria,L,Brazil,100,"Java, Kubernetes, Docker",Associate,8,Manufacturing,2024-09-01,2024-10-31,1240,6.6,Cloud AI Solutions -AI01198,AI Architect,135052,CHF,121547,MI,CT,Switzerland,M,New Zealand,100,"GCP, Python, Git, Java, Computer Vision",PhD,4,Finance,2024-07-08,2024-09-15,1191,6.2,Smart Analytics -AI01199,AI Research Scientist,139723,GBP,104792,SE,PT,United Kingdom,L,Canada,100,"Kubernetes, Spark, MLOps",Associate,5,Finance,2024-06-27,2024-07-23,1731,9.7,Cloud AI Solutions -AI01200,AI Software Engineer,126789,USD,126789,SE,CT,Israel,S,Israel,50,"Hadoop, Git, Statistics",Bachelor,6,Healthcare,2024-07-31,2024-08-14,2157,5.9,DeepTech Ventures -AI01201,Data Analyst,51041,SGD,66353,EN,FT,Singapore,S,Singapore,100,"Statistics, AWS, Scala, PyTorch",PhD,1,Healthcare,2024-01-30,2024-02-19,1755,6.8,Cloud AI Solutions -AI01202,Machine Learning Engineer,66473,AUD,89739,EN,FT,Australia,M,Australia,100,"Docker, Kubernetes, Statistics, Spark",Master,0,Energy,2025-02-04,2025-02-20,2260,7.9,Future Systems -AI01203,AI Consultant,82798,JPY,9107780,EN,FT,Japan,L,Japan,50,"Azure, SQL, AWS",Master,0,Real Estate,2025-01-10,2025-03-06,1844,8.2,Quantum Computing Inc -AI01204,Machine Learning Researcher,208808,USD,208808,EX,CT,Ireland,M,Estonia,100,"Java, Python, PyTorch, SQL",Associate,16,Healthcare,2024-01-16,2024-02-29,2313,5.3,Autonomous Tech -AI01205,Principal Data Scientist,85454,USD,85454,EN,FT,Denmark,M,Denmark,100,"SQL, Scala, Kubernetes",PhD,0,Government,2024-12-20,2025-02-05,1407,7.8,Cloud AI Solutions -AI01206,Principal Data Scientist,312926,CHF,281633,EX,FT,Switzerland,S,Switzerland,100,"Kubernetes, Git, Mathematics, Hadoop, PyTorch",Bachelor,17,Media,2024-08-07,2024-10-14,1468,6.5,Predictive Systems -AI01207,Computer Vision Engineer,112468,USD,112468,EN,FT,Denmark,L,Italy,100,"R, Java, Linux",Master,0,Manufacturing,2024-11-13,2024-11-30,1081,9.1,Neural Networks Co -AI01208,Data Analyst,184835,USD,184835,EX,PT,Sweden,L,Sweden,100,"GCP, Python, TensorFlow, SQL",Bachelor,12,Consulting,2024-09-22,2024-10-31,570,6.7,Algorithmic Solutions -AI01209,Robotics Engineer,114775,EUR,97559,SE,PT,France,L,France,100,"Python, Git, TensorFlow, Data Visualization, Linux",Bachelor,7,Education,2024-06-20,2024-08-10,1743,9.4,Neural Networks Co -AI01210,Deep Learning Engineer,87755,CAD,109694,MI,PT,Canada,L,Portugal,100,"Deep Learning, Scala, Data Visualization, TensorFlow",Bachelor,3,Energy,2024-11-03,2024-12-15,1436,6.4,Predictive Systems -AI01211,AI Consultant,226988,SGD,295084,EX,CT,Singapore,S,Singapore,0,"Statistics, NLP, Linux",Master,12,Manufacturing,2024-05-03,2024-06-13,2480,5.1,Advanced Robotics -AI01212,Data Scientist,109751,CAD,137189,SE,PT,Canada,S,Denmark,100,"Azure, Kubernetes, Spark, Computer Vision",PhD,9,Energy,2024-09-01,2024-10-13,2171,7.1,Future Systems -AI01213,NLP Engineer,110714,USD,110714,EX,FL,China,M,China,100,"NLP, Scala, Kubernetes, Python",Master,15,Finance,2024-06-01,2024-08-13,835,7.9,TechCorp Inc -AI01214,AI Architect,243320,USD,243320,EX,CT,Israel,L,Israel,0,"NLP, Scala, Python, Computer Vision",PhD,16,Telecommunications,2024-09-17,2024-11-17,2026,5.8,DataVision Ltd -AI01215,Machine Learning Researcher,137660,USD,137660,SE,FT,Sweden,M,India,100,"Tableau, Kubernetes, SQL, Java",Associate,6,Technology,2024-07-19,2024-09-02,964,8.2,Future Systems -AI01216,Deep Learning Engineer,101137,USD,101137,MI,CT,Denmark,M,Belgium,50,"R, Azure, Deep Learning, SQL, Java",Master,2,Telecommunications,2025-01-02,2025-02-06,2016,10,DataVision Ltd -AI01217,Data Analyst,76750,EUR,65238,EN,FT,Netherlands,M,Netherlands,0,"Java, Git, Data Visualization",Bachelor,0,Gaming,2024-07-20,2024-09-01,723,6.9,Cognitive Computing -AI01218,Machine Learning Researcher,225610,USD,225610,EX,PT,Denmark,M,Denmark,50,"PyTorch, Deep Learning, TensorFlow",Associate,14,Telecommunications,2024-06-21,2024-08-10,810,7.1,Predictive Systems -AI01219,AI Consultant,250681,USD,250681,EX,FL,Denmark,S,Denmark,0,"TensorFlow, R, Spark, Python",PhD,15,Retail,2024-07-17,2024-09-22,818,6.3,Smart Analytics -AI01220,Deep Learning Engineer,68073,USD,68073,EN,PT,United States,M,United States,50,"MLOps, AWS, SQL, NLP, Statistics",Master,0,Technology,2024-03-11,2024-04-05,1104,5.4,TechCorp Inc -AI01221,Data Scientist,83363,EUR,70859,MI,FL,Germany,S,Germany,100,"Git, Linux, MLOps, Mathematics",Bachelor,2,Energy,2024-08-01,2024-09-15,2321,6.2,Cognitive Computing -AI01222,AI Architect,82241,USD,82241,EN,FL,United States,L,United States,0,"Spark, R, Deep Learning, Java, Git",Master,0,Education,2024-03-04,2024-05-09,515,9.9,Neural Networks Co -AI01223,AI Research Scientist,70446,USD,70446,EN,PT,South Korea,L,South Korea,0,"Python, Git, TensorFlow, GCP, PyTorch",Master,1,Energy,2024-11-08,2024-11-27,688,8.3,Digital Transformation LLC -AI01224,Machine Learning Researcher,91327,USD,91327,EN,PT,United States,M,United States,0,"Hadoop, Scala, Statistics, Git",Bachelor,0,Technology,2024-06-20,2024-07-15,703,5.6,Advanced Robotics -AI01225,Data Scientist,39389,USD,39389,MI,CT,India,L,India,0,"Data Visualization, SQL, Hadoop",Associate,4,Media,2024-10-03,2024-11-12,1197,9.6,Neural Networks Co -AI01226,Robotics Engineer,81525,EUR,69296,EN,CT,Netherlands,L,Netherlands,0,"AWS, Data Visualization, PyTorch",PhD,0,Finance,2025-04-03,2025-06-04,2353,5.8,DeepTech Ventures -AI01227,Data Analyst,64441,EUR,54775,EN,PT,Germany,S,Germany,50,"PyTorch, TensorFlow, Tableau, GCP",Associate,1,Retail,2024-10-15,2024-11-18,604,5.3,Cloud AI Solutions -AI01228,Data Scientist,154936,CAD,193670,SE,FL,Canada,L,Spain,0,"Data Visualization, Python, Scala, TensorFlow, Statistics",Master,7,Energy,2024-01-23,2024-03-19,1911,5.5,Autonomous Tech -AI01229,Machine Learning Engineer,252651,USD,252651,EX,CT,Finland,L,Finland,0,"Python, Java, MLOps, Computer Vision, Deep Learning",Associate,11,Media,2024-07-25,2024-09-09,1989,9.7,AI Innovations -AI01230,AI Research Scientist,85211,GBP,63908,MI,PT,United Kingdom,M,United Kingdom,0,"AWS, MLOps, Deep Learning, SQL",Bachelor,2,Energy,2024-08-28,2024-09-20,1984,6.7,Advanced Robotics -AI01231,Head of AI,75989,USD,75989,MI,CT,South Korea,S,South Korea,0,"PyTorch, TensorFlow, Docker, Hadoop",Associate,2,Telecommunications,2024-11-22,2025-01-08,1985,5.6,Algorithmic Solutions -AI01232,NLP Engineer,81874,USD,81874,MI,CT,Ireland,M,Ireland,50,"Azure, GCP, Statistics, PyTorch",Bachelor,2,Real Estate,2024-10-16,2024-12-09,1992,8.5,Autonomous Tech -AI01233,Robotics Engineer,159436,USD,159436,SE,CT,Israel,L,Australia,50,"TensorFlow, Data Visualization, Java, Azure",Associate,7,Telecommunications,2024-02-02,2024-03-12,1302,10,DeepTech Ventures -AI01234,AI Research Scientist,116597,USD,116597,SE,FT,Finland,M,Switzerland,50,"Deep Learning, Statistics, AWS",Associate,5,Media,2024-12-12,2025-01-11,762,8.9,Future Systems -AI01235,ML Ops Engineer,123943,JPY,13633730,SE,CT,Japan,M,Japan,50,"Python, TensorFlow, GCP, SQL, Git",PhD,9,Consulting,2024-08-04,2024-08-31,2347,8.3,DataVision Ltd -AI01236,Principal Data Scientist,142168,EUR,120843,SE,PT,France,M,France,50,"Mathematics, TensorFlow, Docker, NLP",Associate,9,Gaming,2024-05-21,2024-06-07,1546,7.3,TechCorp Inc -AI01237,Machine Learning Engineer,145212,USD,145212,MI,FT,United States,L,United Kingdom,50,"Linux, R, Deep Learning",Master,3,Finance,2024-01-14,2024-03-20,1063,7.7,Neural Networks Co -AI01238,Data Engineer,150880,JPY,16596800,SE,FT,Japan,L,Japan,100,"Mathematics, R, Data Visualization",Associate,6,Gaming,2024-12-11,2025-01-15,2362,6,Neural Networks Co -AI01239,ML Ops Engineer,78416,USD,78416,MI,FL,Israel,M,Israel,0,"Kubernetes, Python, Data Visualization, TensorFlow, AWS",PhD,4,Technology,2024-12-29,2025-03-11,521,8.6,Machine Intelligence Group -AI01240,Robotics Engineer,167446,EUR,142329,EX,CT,Netherlands,L,Netherlands,0,"Git, Azure, PyTorch, Deep Learning",Associate,13,Education,2025-04-28,2025-05-26,2462,5.7,DataVision Ltd -AI01241,AI Architect,136891,USD,136891,EX,FT,South Korea,S,South Korea,50,"Data Visualization, Java, Linux, AWS",Associate,13,Manufacturing,2024-11-09,2025-01-06,2072,6.3,Cloud AI Solutions -AI01242,AI Product Manager,56186,CAD,70233,EN,CT,Canada,L,Sweden,0,"Tableau, Deep Learning, Spark, TensorFlow, Hadoop",Bachelor,0,Retail,2024-02-09,2024-03-02,1179,7.5,Future Systems -AI01243,Data Scientist,89015,CAD,111269,MI,FL,Canada,L,India,100,"Kubernetes, Python, Azure",PhD,3,Transportation,2025-02-25,2025-03-24,1473,8.2,Cloud AI Solutions -AI01244,Principal Data Scientist,101256,GBP,75942,MI,CT,United Kingdom,L,Brazil,0,"PyTorch, Linux, Spark",PhD,4,Manufacturing,2024-10-28,2024-11-12,635,6.8,Digital Transformation LLC -AI01245,Machine Learning Engineer,223846,EUR,190269,EX,FL,Austria,M,Austria,50,"Hadoop, TensorFlow, Python",PhD,10,Finance,2024-11-02,2024-12-03,1775,8.2,Algorithmic Solutions -AI01246,Data Analyst,89705,CAD,112131,MI,PT,Canada,L,Canada,0,"Scala, Python, Kubernetes",Associate,4,Gaming,2024-11-23,2025-01-08,1486,8.3,DataVision Ltd -AI01247,Head of AI,173178,USD,173178,EX,FL,South Korea,L,South Korea,0,"Python, AWS, Statistics, Computer Vision, SQL",Associate,17,Real Estate,2025-03-10,2025-04-07,2301,6.6,TechCorp Inc -AI01248,Deep Learning Engineer,119123,USD,119123,SE,PT,Norway,S,Portugal,100,"Data Visualization, Python, TensorFlow",Associate,9,Automotive,2024-11-16,2025-01-05,2295,9.7,Autonomous Tech -AI01249,Robotics Engineer,205428,USD,205428,EX,FL,United States,L,United States,0,"R, Spark, Mathematics, TensorFlow, Deep Learning",Associate,10,Finance,2024-06-30,2024-08-22,1349,8.2,TechCorp Inc -AI01250,Deep Learning Engineer,107614,USD,107614,SE,FT,Israel,M,Switzerland,0,"Statistics, NLP, GCP, Python, PyTorch",Bachelor,5,Gaming,2024-04-02,2024-06-11,2346,7.6,Advanced Robotics -AI01251,AI Architect,96395,USD,96395,SE,FT,Israel,M,Israel,50,"Git, PyTorch, Statistics",PhD,5,Energy,2024-10-21,2024-11-27,824,5.4,Quantum Computing Inc -AI01252,Deep Learning Engineer,113420,USD,113420,EN,CT,Norway,L,Norway,50,"Spark, Hadoop, PyTorch, TensorFlow, NLP",Master,1,Technology,2024-07-10,2024-09-11,1658,7.3,DataVision Ltd -AI01253,Machine Learning Engineer,186496,USD,186496,EX,FL,Israel,L,Israel,100,"Azure, AWS, Computer Vision, Java",Bachelor,19,Finance,2024-04-02,2024-05-14,1245,9.2,Smart Analytics -AI01254,Research Scientist,212359,USD,212359,EX,FL,Finland,M,Finland,0,"PyTorch, NLP, Hadoop",Associate,13,Technology,2024-08-01,2024-08-31,508,8.3,TechCorp Inc -AI01255,Head of AI,48963,USD,48963,SE,CT,India,L,India,100,"Python, Computer Vision, TensorFlow",Associate,9,Telecommunications,2025-04-15,2025-05-27,1577,5.6,Quantum Computing Inc -AI01256,Principal Data Scientist,84644,EUR,71947,MI,FL,France,L,France,100,"NLP, Kubernetes, Python",Bachelor,4,Healthcare,2025-02-25,2025-04-03,1615,5.7,Quantum Computing Inc -AI01257,Robotics Engineer,129200,USD,129200,MI,CT,Denmark,L,Denmark,100,"Java, SQL, Kubernetes, Computer Vision",Associate,4,Manufacturing,2025-03-06,2025-05-16,1076,9.3,Neural Networks Co -AI01258,AI Research Scientist,131449,JPY,14459390,SE,FT,Japan,M,Japan,50,"SQL, Hadoop, NLP, Deep Learning, GCP",Associate,9,Retail,2025-02-25,2025-05-08,2118,7.4,Digital Transformation LLC -AI01259,Computer Vision Engineer,37726,USD,37726,EN,CT,China,L,United States,0,"Git, Python, PyTorch, GCP, AWS",PhD,1,Media,2024-03-18,2024-04-03,2339,9.5,Machine Intelligence Group -AI01260,Robotics Engineer,147408,USD,147408,SE,CT,United States,L,United States,0,"Scala, Python, AWS",Master,6,Media,2024-09-26,2024-11-18,652,6.5,DeepTech Ventures -AI01261,Autonomous Systems Engineer,68165,USD,68165,EN,PT,United States,S,Netherlands,0,"Azure, Linux, Computer Vision, R, Java",Bachelor,1,Finance,2024-07-30,2024-10-07,1978,8.5,Quantum Computing Inc -AI01262,Head of AI,153774,USD,153774,EX,FL,Finland,M,Finland,100,"Azure, Hadoop, AWS, Docker",Master,15,Automotive,2024-06-30,2024-08-18,1117,6.7,Quantum Computing Inc -AI01263,AI Consultant,139995,EUR,118996,EX,PT,Austria,S,Colombia,50,"Mathematics, Computer Vision, Linux, Scala, PyTorch",Associate,13,Government,2024-02-13,2024-04-18,546,9,Machine Intelligence Group -AI01264,Computer Vision Engineer,126306,CAD,157883,SE,CT,Canada,S,Vietnam,0,"Azure, R, TensorFlow, AWS, Deep Learning",Associate,6,Transportation,2024-04-20,2024-06-17,2177,8.8,Algorithmic Solutions -AI01265,Principal Data Scientist,142937,USD,142937,SE,FL,United States,S,United States,50,"Git, Python, R, MLOps, Statistics",Bachelor,5,Healthcare,2024-03-12,2024-05-15,1101,5.8,Cloud AI Solutions -AI01266,Data Analyst,157493,USD,157493,SE,FL,Norway,L,Norway,0,"PyTorch, Hadoop, TensorFlow",PhD,8,Media,2024-04-01,2024-04-30,1738,5.9,Algorithmic Solutions -AI01267,Research Scientist,81840,USD,81840,EN,FT,Denmark,S,Denmark,50,"Python, Docker, Deep Learning, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-07,558,8.5,Neural Networks Co -AI01268,AI Product Manager,120340,USD,120340,MI,CT,Norway,S,Norway,0,"Spark, TensorFlow, Python",Associate,2,Transportation,2024-12-18,2025-02-20,2435,9.3,Algorithmic Solutions -AI01269,Deep Learning Engineer,133498,GBP,100124,MI,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,3,Gaming,2024-04-02,2024-05-04,2347,9.6,Autonomous Tech -AI01270,Autonomous Systems Engineer,168321,EUR,143073,EX,PT,Netherlands,M,Netherlands,100,"Mathematics, R, NLP, Deep Learning",Master,18,Automotive,2025-02-13,2025-04-27,1845,7.9,Future Systems -AI01271,Machine Learning Engineer,128450,CAD,160563,SE,PT,Canada,M,Canada,50,"SQL, Hadoop, Git, AWS",Bachelor,7,Healthcare,2024-03-29,2024-05-23,552,6.2,DeepTech Ventures -AI01272,Robotics Engineer,71869,SGD,93430,EN,FT,Singapore,M,Luxembourg,100,"Tableau, Azure, Scala, Computer Vision",Associate,0,Energy,2024-10-23,2024-12-19,1601,7.9,Advanced Robotics -AI01273,AI Architect,86340,USD,86340,MI,FL,Sweden,M,Sweden,0,"AWS, Scala, Hadoop",Master,2,Consulting,2024-12-17,2025-02-05,1229,5,Smart Analytics -AI01274,AI Product Manager,73047,CAD,91309,EN,PT,Canada,M,Australia,100,"NLP, Computer Vision, Python, Hadoop, TensorFlow",Associate,1,Finance,2024-01-17,2024-02-04,1706,8.6,Predictive Systems -AI01275,Principal Data Scientist,125916,AUD,169987,MI,PT,Australia,L,Australia,50,"Tableau, Python, SQL",Master,3,Real Estate,2024-10-25,2024-12-04,1314,9.1,Autonomous Tech -AI01276,AI Software Engineer,107722,USD,107722,SE,PT,Finland,M,Finland,0,"GCP, R, Docker, SQL",PhD,6,Media,2024-08-04,2024-09-20,2439,5.2,DeepTech Ventures -AI01277,AI Architect,100220,USD,100220,MI,PT,Ireland,M,Ukraine,100,"Java, Azure, Spark, Mathematics",Associate,3,Real Estate,2025-04-12,2025-06-17,1841,9.7,DataVision Ltd -AI01278,Machine Learning Researcher,141420,USD,141420,EX,FL,Finland,S,Finland,50,"Linux, PyTorch, Hadoop",Associate,15,Telecommunications,2024-07-26,2024-10-07,877,9.3,Cognitive Computing -AI01279,ML Ops Engineer,43276,USD,43276,SE,FT,China,S,China,0,"AWS, Docker, Computer Vision, PyTorch, SQL",Bachelor,7,Finance,2025-01-26,2025-02-22,2494,6.5,Machine Intelligence Group -AI01280,ML Ops Engineer,101313,EUR,86116,SE,FT,Germany,S,Germany,50,"Statistics, Spark, Data Visualization",Associate,6,Government,2025-03-28,2025-05-08,937,9.9,DataVision Ltd -AI01281,Data Analyst,238881,EUR,203049,EX,FT,Austria,L,Austria,0,"PyTorch, NLP, Scala, Linux",PhD,13,Technology,2024-05-03,2024-07-09,897,7.5,Future Systems -AI01282,Data Scientist,144471,SGD,187812,SE,FL,Singapore,M,Singapore,100,"Java, Deep Learning, Azure",Associate,8,Real Estate,2024-04-01,2024-05-09,984,6,Neural Networks Co -AI01283,Head of AI,71781,EUR,61014,MI,CT,Austria,M,Estonia,100,"Docker, R, Linux, SQL",Bachelor,4,Education,2024-05-05,2024-06-15,2151,5.9,Quantum Computing Inc -AI01284,AI Architect,34334,USD,34334,MI,FT,India,M,Norway,50,"Hadoop, GCP, PyTorch, MLOps, TensorFlow",PhD,3,Government,2024-07-20,2024-08-07,1662,5.8,Neural Networks Co -AI01285,AI Research Scientist,59699,USD,59699,EN,PT,Sweden,L,Sweden,0,"Tableau, MLOps, Scala, Java, NLP",Master,1,Telecommunications,2024-03-09,2024-04-17,526,9.8,Autonomous Tech -AI01286,AI Specialist,74398,SGD,96717,EN,PT,Singapore,L,Denmark,50,"GCP, Kubernetes, Data Visualization, Deep Learning",PhD,1,Gaming,2024-07-05,2024-08-04,560,6.5,Smart Analytics -AI01287,Data Scientist,114132,USD,114132,MI,CT,Israel,L,Israel,100,"R, Spark, NLP, Hadoop",PhD,4,Real Estate,2024-04-02,2024-06-01,1575,7.8,Quantum Computing Inc -AI01288,AI Specialist,82988,USD,82988,EN,FL,Israel,L,United Kingdom,50,"NLP, TensorFlow, PyTorch, Deep Learning, AWS",PhD,1,Gaming,2024-11-05,2024-11-20,1031,5.3,Algorithmic Solutions -AI01289,Data Engineer,129184,USD,129184,MI,FT,Denmark,M,Denmark,100,"Scala, Java, Computer Vision, R, Tableau",Associate,4,Transportation,2024-06-19,2024-08-22,2210,8.1,Autonomous Tech -AI01290,Head of AI,122761,USD,122761,SE,PT,Sweden,S,Sweden,100,"Java, Scala, Mathematics",Master,7,Automotive,2024-07-17,2024-09-06,1608,9.1,TechCorp Inc -AI01291,Machine Learning Engineer,176080,USD,176080,EX,PT,South Korea,S,South Korea,50,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,10,Manufacturing,2024-08-08,2024-09-14,2453,7.3,Cognitive Computing -AI01292,AI Software Engineer,132322,USD,132322,MI,CT,Denmark,L,Denmark,0,"PyTorch, MLOps, Scala, Computer Vision",PhD,3,Healthcare,2024-09-08,2024-11-11,2323,6.5,Machine Intelligence Group -AI01293,Head of AI,220734,EUR,187624,EX,CT,Netherlands,S,Netherlands,50,"TensorFlow, Azure, Scala, Statistics",Associate,19,Media,2024-04-24,2024-05-20,1183,8.8,Advanced Robotics -AI01294,Deep Learning Engineer,210396,USD,210396,EX,PT,Ireland,S,Ireland,0,"Git, MLOps, Kubernetes, Java, Azure",PhD,10,Energy,2025-03-19,2025-04-05,1745,5.2,Future Systems -AI01295,Research Scientist,178095,USD,178095,SE,CT,Norway,L,New Zealand,100,"Python, Tableau, Azure, Statistics",Bachelor,9,Healthcare,2024-09-16,2024-10-12,1142,5.7,Machine Intelligence Group -AI01296,AI Consultant,130897,EUR,111262,EX,FL,France,S,France,50,"GCP, Linux, Data Visualization",Associate,11,Real Estate,2024-03-05,2024-03-30,1235,5.1,Advanced Robotics -AI01297,Computer Vision Engineer,278652,EUR,236854,EX,FL,Netherlands,L,Netherlands,100,"R, Kubernetes, NLP",PhD,14,Real Estate,2025-04-19,2025-05-29,1960,5.7,Cognitive Computing -AI01298,ML Ops Engineer,241681,USD,241681,EX,FL,Finland,L,Finland,0,"Kubernetes, Azure, AWS",Associate,10,Gaming,2024-10-25,2024-12-05,2150,6.3,TechCorp Inc -AI01299,Data Scientist,108165,USD,108165,MI,FL,Norway,S,Poland,50,"Data Visualization, Linux, MLOps, R, NLP",PhD,2,Media,2025-03-09,2025-05-16,962,7.7,Smart Analytics -AI01300,AI Research Scientist,37809,USD,37809,SE,CT,India,M,Estonia,0,"Hadoop, Data Visualization, NLP, Python, Docker",Bachelor,7,Government,2024-05-24,2024-06-13,1144,9.4,DeepTech Ventures -AI01301,Machine Learning Engineer,59161,USD,59161,SE,CT,China,L,China,100,"SQL, Tableau, Scala, Data Visualization",Bachelor,6,Consulting,2024-10-03,2024-11-01,848,9.8,Neural Networks Co -AI01302,Deep Learning Engineer,65717,AUD,88718,EN,FL,Australia,M,Australia,50,"Scala, Git, TensorFlow, Linux",PhD,1,Gaming,2024-08-25,2024-10-20,2168,8.9,Neural Networks Co -AI01303,Machine Learning Engineer,131415,USD,131415,EX,FL,South Korea,M,Czech Republic,0,"TensorFlow, Scala, Computer Vision",Master,14,Finance,2025-04-27,2025-06-20,686,9.2,DataVision Ltd -AI01304,NLP Engineer,165177,CHF,148659,SE,FL,Switzerland,S,Switzerland,0,"Azure, Kubernetes, NLP, AWS",PhD,6,Energy,2024-07-07,2024-09-09,2397,8.6,Algorithmic Solutions -AI01305,Machine Learning Researcher,134710,USD,134710,SE,PT,Finland,L,Finland,50,"Python, Hadoop, NLP",Associate,9,Automotive,2025-01-27,2025-03-22,898,5.9,Smart Analytics -AI01306,AI Specialist,132331,EUR,112481,SE,CT,France,L,France,100,"NLP, Scala, Kubernetes",Master,6,Automotive,2025-02-14,2025-03-17,1623,6,Quantum Computing Inc -AI01307,Machine Learning Researcher,25085,USD,25085,EN,CT,China,S,China,100,"TensorFlow, Scala, PyTorch, GCP, Git",Associate,1,Manufacturing,2024-07-31,2024-09-25,2291,5.2,DataVision Ltd -AI01308,AI Architect,81436,USD,81436,EN,FL,United States,M,United States,50,"Java, Docker, Tableau, Linux, Deep Learning",Associate,0,Technology,2024-11-25,2025-01-31,1081,8.4,Autonomous Tech -AI01309,Robotics Engineer,121581,JPY,13373910,SE,FT,Japan,M,Japan,100,"GCP, Kubernetes, AWS, Docker",Associate,8,Technology,2024-12-10,2025-01-31,1652,9.7,Quantum Computing Inc -AI01310,NLP Engineer,85043,USD,85043,MI,CT,South Korea,M,South Korea,100,"Kubernetes, PyTorch, Computer Vision, GCP, Git",Master,3,Telecommunications,2024-08-20,2024-10-26,1219,8,DeepTech Ventures -AI01311,Principal Data Scientist,77847,EUR,66170,EN,PT,Netherlands,L,Netherlands,50,"Mathematics, Linux, Scala, GCP, Kubernetes",Bachelor,0,Consulting,2024-07-31,2024-09-24,2283,7.1,Cloud AI Solutions -AI01312,Research Scientist,112294,EUR,95450,SE,FT,France,M,France,50,"Python, Java, Hadoop, Deep Learning",PhD,6,Government,2024-09-17,2024-11-16,2496,7.4,Smart Analytics -AI01313,Autonomous Systems Engineer,118482,USD,118482,SE,FT,Finland,M,Portugal,50,"Kubernetes, Docker, NLP, Python, Deep Learning",Master,7,Finance,2024-02-01,2024-02-20,1250,7.6,Neural Networks Co -AI01314,NLP Engineer,76423,USD,76423,EN,PT,United States,M,United States,0,"SQL, Data Visualization, Scala, GCP",Associate,1,Consulting,2024-05-27,2024-07-17,2180,8.7,Autonomous Tech -AI01315,Computer Vision Engineer,66969,EUR,56924,MI,CT,Austria,S,Israel,0,"Python, TensorFlow, Spark, Deep Learning",Associate,2,Government,2024-06-29,2024-08-20,2048,8.5,Predictive Systems -AI01316,AI Architect,88996,USD,88996,MI,FL,Ireland,L,Ireland,100,"SQL, Mathematics, Python",Bachelor,4,Finance,2024-01-12,2024-02-03,2325,8.4,Smart Analytics -AI01317,AI Architect,67741,GBP,50806,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Spark, Computer Vision, PyTorch, Linux",Master,0,Manufacturing,2024-07-24,2024-08-18,808,8.6,Smart Analytics -AI01318,AI Architect,104123,CHF,93711,EN,FL,Switzerland,M,Switzerland,0,"TensorFlow, Computer Vision, NLP",Master,0,Automotive,2024-09-16,2024-10-12,1848,5.4,TechCorp Inc -AI01319,AI Specialist,52117,SGD,67752,EN,FL,Singapore,S,Singapore,50,"Kubernetes, GCP, Linux",PhD,1,Government,2025-03-20,2025-05-17,1881,8.5,Cognitive Computing -AI01320,AI Specialist,107002,USD,107002,EN,CT,Denmark,L,South Korea,100,"GCP, R, Tableau, Statistics, Data Visualization",Bachelor,1,Retail,2024-03-12,2024-04-20,2188,9.9,Algorithmic Solutions -AI01321,Head of AI,171421,JPY,18856310,EX,FT,Japan,S,Japan,0,"Scala, Computer Vision, Tableau, Statistics",Bachelor,12,Education,2025-02-26,2025-04-27,867,7.3,Quantum Computing Inc -AI01322,Principal Data Scientist,102160,USD,102160,SE,FL,Finland,M,Norway,50,"Kubernetes, Scala, Tableau, MLOps",Associate,5,Transportation,2024-12-16,2025-02-04,1617,9.4,Advanced Robotics -AI01323,Robotics Engineer,78797,GBP,59098,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, TensorFlow, R",Associate,0,Automotive,2024-10-11,2024-12-01,708,9.2,DeepTech Ventures -AI01324,Machine Learning Researcher,143483,CAD,179354,SE,CT,Canada,M,Malaysia,0,"Linux, Deep Learning, PyTorch, Mathematics",PhD,8,Education,2025-03-18,2025-04-08,2064,6.2,Machine Intelligence Group -AI01325,Autonomous Systems Engineer,224567,USD,224567,SE,FL,Denmark,L,India,0,"Spark, Linux, Tableau, Data Visualization",Bachelor,7,Automotive,2025-02-03,2025-03-24,1751,7,Smart Analytics -AI01326,Autonomous Systems Engineer,141545,AUD,191086,SE,FL,Australia,L,Australia,0,"Computer Vision, Mathematics, Spark",Bachelor,8,Automotive,2024-10-16,2024-11-09,2451,7.8,Digital Transformation LLC -AI01327,Data Engineer,56427,USD,56427,EN,FT,Israel,M,Hungary,0,"Kubernetes, Tableau, SQL",Bachelor,1,Transportation,2025-01-26,2025-04-07,838,6.1,Future Systems -AI01328,Robotics Engineer,90510,USD,90510,MI,CT,Norway,S,China,100,"SQL, Spark, Mathematics",Bachelor,4,Retail,2024-03-05,2024-04-01,2031,7.2,Future Systems -AI01329,Research Scientist,158669,USD,158669,EX,PT,Israel,S,Israel,100,"SQL, Computer Vision, Docker, AWS, PyTorch",Associate,19,Manufacturing,2024-08-12,2024-08-28,1226,7.8,Digital Transformation LLC -AI01330,AI Software Engineer,74539,JPY,8199290,EN,FT,Japan,S,South Korea,50,"GCP, Java, SQL, R, AWS",PhD,1,Media,2024-12-11,2024-12-30,746,5.1,Neural Networks Co -AI01331,Computer Vision Engineer,124395,EUR,105736,SE,FL,Netherlands,S,Russia,0,"Spark, Git, SQL, Python, TensorFlow",Master,9,Energy,2025-04-15,2025-06-10,2301,9.2,DataVision Ltd -AI01332,AI Research Scientist,174114,USD,174114,EX,PT,United States,M,United States,0,"Data Visualization, MLOps, Tableau, Python, Kubernetes",Master,10,Real Estate,2024-05-15,2024-06-13,2132,7,Digital Transformation LLC -AI01333,Autonomous Systems Engineer,321202,CHF,289082,EX,CT,Switzerland,M,Switzerland,0,"Scala, Linux, Computer Vision",Master,19,Telecommunications,2024-01-14,2024-03-27,1102,9.8,Advanced Robotics -AI01334,NLP Engineer,73469,USD,73469,MI,FL,Sweden,S,Sweden,0,"Python, Hadoop, TensorFlow",Associate,3,Media,2024-02-02,2024-04-08,1664,8.2,DataVision Ltd -AI01335,ML Ops Engineer,142197,USD,142197,SE,PT,Sweden,L,Finland,50,"R, PyTorch, NLP, GCP",PhD,8,Media,2025-03-31,2025-05-14,1349,7.3,Digital Transformation LLC -AI01336,Machine Learning Researcher,157699,EUR,134044,EX,PT,France,S,France,50,"Python, GCP, Scala",Bachelor,19,Consulting,2024-11-05,2024-12-03,1625,7.9,Cognitive Computing -AI01337,Research Scientist,101213,USD,101213,SE,CT,Finland,S,Finland,100,"SQL, Scala, Statistics, Git",Associate,9,Real Estate,2025-04-06,2025-04-28,801,5.1,Predictive Systems -AI01338,AI Architect,84729,USD,84729,MI,CT,Sweden,S,New Zealand,100,"Scala, Spark, Hadoop, Python",Master,3,Automotive,2024-04-07,2024-05-31,1053,9.3,TechCorp Inc -AI01339,Robotics Engineer,87739,CHF,78965,EN,CT,Switzerland,M,Switzerland,0,"R, SQL, Java, Statistics, Linux",Master,0,Finance,2024-10-09,2024-10-28,2211,10,AI Innovations -AI01340,Autonomous Systems Engineer,30121,USD,30121,EN,FL,China,M,Spain,50,"R, Docker, PyTorch",PhD,0,Manufacturing,2024-04-08,2024-06-19,1586,8.1,Digital Transformation LLC -AI01341,Machine Learning Engineer,100916,JPY,11100760,MI,CT,Japan,S,Japan,50,"Scala, Python, MLOps",Bachelor,2,Real Estate,2024-03-17,2024-05-15,2096,5.6,DeepTech Ventures -AI01342,Computer Vision Engineer,55277,USD,55277,EN,FL,Israel,S,Israel,50,"Git, GCP, Kubernetes, Computer Vision, R",Bachelor,0,Finance,2024-08-28,2024-09-24,1348,6.9,DeepTech Ventures -AI01343,ML Ops Engineer,113420,USD,113420,MI,PT,Ireland,L,Romania,0,"Python, TensorFlow, Tableau, MLOps",Master,4,Manufacturing,2025-02-04,2025-03-31,858,7.3,Digital Transformation LLC -AI01344,Machine Learning Engineer,50194,USD,50194,EN,FL,Finland,M,Finland,0,"SQL, Java, Python, Scala, Deep Learning",Bachelor,1,Automotive,2025-02-08,2025-04-11,664,8.1,DataVision Ltd -AI01345,Head of AI,98859,USD,98859,EX,CT,India,L,India,50,"Azure, Python, Kubernetes, Statistics, Deep Learning",Associate,14,Consulting,2024-04-25,2024-06-20,1997,9.2,Predictive Systems -AI01346,Deep Learning Engineer,195373,CHF,175836,SE,FL,Switzerland,M,Switzerland,100,"PyTorch, Git, Tableau",Associate,7,Finance,2025-02-21,2025-03-21,555,7.2,Cloud AI Solutions -AI01347,AI Software Engineer,150038,AUD,202551,SE,CT,Australia,M,Australia,100,"SQL, TensorFlow, Mathematics, Python",Master,8,Automotive,2024-04-26,2024-05-21,2430,5.8,Autonomous Tech -AI01348,AI Software Engineer,46960,USD,46960,EN,PT,South Korea,S,Chile,100,"NLP, Azure, Data Visualization",PhD,1,Government,2024-05-21,2024-07-18,2271,9.1,Autonomous Tech -AI01349,Research Scientist,256508,EUR,218032,EX,FL,Germany,L,Germany,0,"R, Data Visualization, Docker, Scala, Deep Learning",Associate,14,Government,2024-07-04,2024-08-28,1511,7,DeepTech Ventures -AI01350,Principal Data Scientist,123766,GBP,92825,MI,CT,United Kingdom,L,United Kingdom,50,"Python, TensorFlow, R, Computer Vision, PyTorch",Bachelor,4,Retail,2024-06-14,2024-07-20,868,5.9,Neural Networks Co -AI01351,Data Analyst,138655,EUR,117857,SE,PT,Germany,L,Germany,50,"Deep Learning, NLP, Kubernetes, Hadoop",Master,9,Technology,2024-03-10,2024-04-09,1039,6.2,Digital Transformation LLC -AI01352,AI Software Engineer,112307,EUR,95461,MI,FT,Netherlands,M,Vietnam,0,"Python, Azure, Linux, TensorFlow, Java",Associate,3,Government,2024-05-04,2024-06-30,1320,9.4,Future Systems -AI01353,AI Product Manager,75008,USD,75008,EX,FT,India,L,New Zealand,50,"PyTorch, TensorFlow, Spark, Tableau, Scala",Bachelor,15,Retail,2024-09-23,2024-10-29,1493,8,Algorithmic Solutions -AI01354,Robotics Engineer,72038,USD,72038,MI,CT,South Korea,S,South Korea,50,"Python, Docker, AWS, GCP",PhD,3,Energy,2024-05-01,2024-06-26,2322,5.3,DeepTech Ventures -AI01355,AI Software Engineer,141038,USD,141038,SE,CT,Finland,M,Finland,100,"Statistics, MLOps, Python, Linux, Deep Learning",Bachelor,6,Transportation,2025-04-06,2025-04-25,1720,7.3,Algorithmic Solutions -AI01356,AI Research Scientist,113496,USD,113496,SE,CT,Israel,S,Israel,50,"R, Spark, TensorFlow",PhD,9,Real Estate,2024-10-29,2024-11-13,542,8.3,Neural Networks Co -AI01357,Computer Vision Engineer,100144,EUR,85122,SE,FL,France,S,France,0,"Tableau, PyTorch, TensorFlow",PhD,8,Healthcare,2024-09-18,2024-10-22,1494,5.8,Cloud AI Solutions -AI01358,AI Research Scientist,210470,SGD,273611,EX,PT,Singapore,M,Singapore,0,"PyTorch, Azure, Hadoop, Java",Bachelor,12,Real Estate,2024-07-05,2024-07-25,1609,8.3,Autonomous Tech -AI01359,Head of AI,66974,CAD,83718,MI,FT,Canada,S,Canada,100,"Python, Docker, TensorFlow, PyTorch",Master,3,Media,2024-07-03,2024-08-14,2141,7.4,Future Systems -AI01360,Autonomous Systems Engineer,137007,EUR,116456,SE,FT,Netherlands,L,Malaysia,100,"Scala, Computer Vision, SQL, PyTorch, Azure",Associate,8,Government,2025-03-10,2025-05-02,1033,6.7,Cognitive Computing -AI01361,Machine Learning Engineer,80135,USD,80135,MI,CT,Ireland,S,Ireland,50,"Data Visualization, GCP, AWS, SQL, NLP",PhD,4,Government,2024-07-23,2024-10-01,2267,8.8,Smart Analytics -AI01362,Research Scientist,158546,EUR,134764,SE,FT,Netherlands,M,Netherlands,50,"SQL, Hadoop, R, Computer Vision, Docker",Associate,9,Manufacturing,2024-02-03,2024-04-09,2352,9.9,Algorithmic Solutions -AI01363,Deep Learning Engineer,194317,USD,194317,EX,FT,Denmark,M,Denmark,100,"Git, GCP, Tableau, Kubernetes",Bachelor,19,Energy,2024-03-31,2024-06-02,1493,7.2,Digital Transformation LLC -AI01364,Head of AI,83493,EUR,70969,MI,CT,Netherlands,M,Netherlands,50,"Java, Spark, GCP",Master,2,Automotive,2024-05-26,2024-06-10,2305,6.9,Predictive Systems -AI01365,Data Analyst,104222,USD,104222,EN,FT,United States,L,Malaysia,100,"Spark, SQL, Azure, Git, Hadoop",PhD,1,Government,2024-12-06,2025-01-01,1541,5.3,AI Innovations -AI01366,Autonomous Systems Engineer,49854,USD,49854,MI,CT,China,L,China,100,"Python, Hadoop, Computer Vision, Spark, Kubernetes",Master,4,Automotive,2025-01-06,2025-01-28,2345,6.9,Cloud AI Solutions -AI01367,Autonomous Systems Engineer,158519,CAD,198149,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, Mathematics, Hadoop, AWS",Bachelor,14,Government,2025-03-07,2025-04-26,2403,9.8,TechCorp Inc -AI01368,Autonomous Systems Engineer,180734,USD,180734,SE,PT,United States,L,United States,50,"Java, Python, Linux",Master,6,Technology,2024-02-12,2024-04-09,2239,6.3,Machine Intelligence Group -AI01369,ML Ops Engineer,261993,USD,261993,EX,PT,Ireland,L,Russia,0,"SQL, GCP, Mathematics, NLP",Master,11,Telecommunications,2025-04-11,2025-05-10,2341,5.4,Cognitive Computing -AI01370,Robotics Engineer,98054,USD,98054,SE,FT,Finland,M,Finland,0,"PyTorch, SQL, Git, MLOps, AWS",Associate,9,Gaming,2024-01-08,2024-03-04,950,9.8,DataVision Ltd -AI01371,AI Product Manager,82903,USD,82903,MI,PT,South Korea,M,South Korea,50,"Mathematics, Docker, NLP",Bachelor,4,Gaming,2024-12-24,2025-03-05,2095,8.2,Algorithmic Solutions -AI01372,AI Software Engineer,121557,USD,121557,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Scala, Statistics, GCP",PhD,4,Education,2024-08-27,2024-10-09,1642,8.2,Cognitive Computing -AI01373,Data Analyst,172640,USD,172640,SE,FT,Norway,S,Norway,50,"Linux, Kubernetes, SQL",PhD,6,Manufacturing,2024-11-08,2024-12-31,1912,6.7,DataVision Ltd -AI01374,AI Product Manager,122704,EUR,104298,SE,FT,France,M,France,50,"Azure, Tableau, SQL, GCP, Git",PhD,9,Retail,2024-05-24,2024-07-10,1627,9.2,Future Systems -AI01375,Deep Learning Engineer,60832,JPY,6691520,EN,CT,Japan,S,Japan,0,"Tableau, Java, Python, Azure",Bachelor,1,Transportation,2024-06-07,2024-08-17,2416,5.8,AI Innovations -AI01376,AI Research Scientist,134265,USD,134265,EX,FL,South Korea,L,South Korea,0,"Kubernetes, GCP, Mathematics, AWS",Associate,19,Media,2024-09-27,2024-11-06,635,7.2,Cloud AI Solutions -AI01377,Machine Learning Engineer,65618,USD,65618,EN,FT,Denmark,S,Thailand,100,"R, Linux, Hadoop, Git, Computer Vision",Bachelor,1,Gaming,2025-03-15,2025-04-08,508,5.4,Neural Networks Co -AI01378,NLP Engineer,104745,GBP,78559,SE,FL,United Kingdom,S,Denmark,100,"Docker, Linux, Data Visualization, R",Bachelor,7,Government,2025-02-01,2025-03-13,1749,9.3,DataVision Ltd -AI01379,AI Software Engineer,53253,GBP,39940,EN,FL,United Kingdom,S,United Kingdom,50,"PyTorch, Spark, TensorFlow, Azure, Hadoop",Master,0,Technology,2025-04-11,2025-06-03,652,9,Cloud AI Solutions -AI01380,Computer Vision Engineer,166691,JPY,18336010,EX,PT,Japan,S,Japan,100,"Mathematics, Deep Learning, Scala, R, PyTorch",Master,14,Automotive,2024-05-17,2024-06-10,1849,7,DeepTech Ventures -AI01381,Computer Vision Engineer,146267,CAD,182834,EX,PT,Canada,M,Canada,0,"Scala, R, Docker",PhD,10,Gaming,2025-01-10,2025-02-13,2428,7,DeepTech Ventures -AI01382,AI Consultant,97969,USD,97969,SE,FT,Finland,M,Finland,0,"Spark, PyTorch, MLOps, Tableau",PhD,9,Energy,2024-06-09,2024-07-07,530,9.7,Advanced Robotics -AI01383,Principal Data Scientist,206614,CAD,258268,EX,PT,Canada,M,Ireland,100,"Hadoop, R, Kubernetes",Bachelor,14,Government,2024-02-11,2024-03-20,874,6.2,Machine Intelligence Group -AI01384,Data Analyst,78327,EUR,66578,MI,FT,Austria,M,Austria,0,"Data Visualization, NLP, Mathematics",PhD,3,Consulting,2024-06-29,2024-08-23,2076,5.7,AI Innovations -AI01385,Robotics Engineer,70510,EUR,59934,EN,PT,Austria,L,Turkey,0,"R, Python, TensorFlow, Tableau, Statistics",Bachelor,0,Gaming,2024-08-28,2024-09-29,912,7.1,DataVision Ltd -AI01386,Data Analyst,41791,USD,41791,SE,FT,India,M,India,100,"Linux, SQL, Mathematics, Hadoop",Bachelor,7,Media,2024-12-02,2025-01-11,2227,9.7,Algorithmic Solutions -AI01387,AI Consultant,115800,EUR,98430,MI,FL,Austria,L,Luxembourg,50,"Python, TensorFlow, Spark, PyTorch",Bachelor,3,Media,2025-02-02,2025-03-29,1284,7.9,Digital Transformation LLC -AI01388,Machine Learning Engineer,113860,USD,113860,SE,PT,Finland,L,Sweden,100,"SQL, PyTorch, Python, Docker",Associate,6,Healthcare,2024-05-02,2024-07-11,1096,8.5,AI Innovations -AI01389,Data Analyst,181595,USD,181595,SE,FT,United States,L,United States,100,"Docker, PyTorch, Data Visualization, Hadoop, Spark",Master,7,Automotive,2024-12-31,2025-03-10,1181,8.7,Digital Transformation LLC -AI01390,AI Product Manager,157567,EUR,133932,EX,FT,Austria,L,Israel,50,"Azure, Hadoop, Java, Deep Learning",Associate,18,Finance,2024-01-14,2024-02-22,2191,5.6,Quantum Computing Inc -AI01391,Autonomous Systems Engineer,124885,EUR,106152,MI,FL,Netherlands,L,Netherlands,0,"Linux, AWS, Spark, SQL, PyTorch",PhD,4,Automotive,2024-12-11,2025-01-11,1416,9.2,Smart Analytics -AI01392,NLP Engineer,123910,USD,123910,EX,FL,Ireland,S,Ireland,50,"PyTorch, Tableau, Computer Vision, Git",Bachelor,16,Transportation,2024-09-22,2024-11-24,1656,8,Neural Networks Co -AI01393,AI Specialist,137838,USD,137838,SE,FL,Sweden,L,Belgium,0,"Mathematics, MLOps, Tableau, Kubernetes, Python",PhD,8,Gaming,2024-07-12,2024-08-07,732,7.8,Cloud AI Solutions -AI01394,Data Engineer,313735,USD,313735,EX,FT,Denmark,M,Denmark,0,"NLP, Linux, Kubernetes",Associate,12,Healthcare,2024-12-16,2025-01-06,1940,6.7,Neural Networks Co -AI01395,Computer Vision Engineer,96380,USD,96380,EN,PT,Denmark,M,Ireland,50,"Kubernetes, Python, Statistics",Bachelor,0,Media,2024-10-12,2024-11-30,1399,9,Digital Transformation LLC -AI01396,Data Engineer,63171,EUR,53695,EN,CT,Netherlands,M,Netherlands,100,"Scala, Hadoop, AWS",Bachelor,0,Automotive,2024-12-24,2025-03-03,561,8.8,AI Innovations -AI01397,AI Specialist,123969,USD,123969,SE,FT,Sweden,S,Sweden,0,"SQL, PyTorch, GCP",Bachelor,9,Energy,2025-04-01,2025-04-22,1527,9.8,Quantum Computing Inc -AI01398,Data Analyst,54611,EUR,46419,EN,CT,France,M,France,0,"Python, Linux, TensorFlow, Computer Vision, PyTorch",PhD,0,Technology,2024-12-11,2024-12-26,865,9,Machine Intelligence Group -AI01399,Machine Learning Engineer,119705,USD,119705,MI,PT,Denmark,L,Switzerland,0,"MLOps, Python, R, AWS, Docker",Bachelor,3,Education,2024-03-23,2024-06-02,1556,7.2,Quantum Computing Inc -AI01400,Autonomous Systems Engineer,173697,CHF,156327,SE,FL,Switzerland,S,China,50,"Python, AWS, Scala",Associate,9,Media,2025-01-09,2025-03-23,927,8.2,Algorithmic Solutions -AI01401,Data Scientist,144553,AUD,195147,SE,CT,Australia,L,South Korea,0,"Data Visualization, R, Linux, MLOps",PhD,6,Telecommunications,2024-07-22,2024-09-21,1806,5.8,AI Innovations -AI01402,Research Scientist,76409,GBP,57307,MI,FL,United Kingdom,S,Brazil,50,"AWS, Hadoop, PyTorch",Master,2,Government,2024-10-29,2024-11-12,2125,8.3,DataVision Ltd -AI01403,NLP Engineer,105022,AUD,141780,SE,FT,Australia,M,Japan,0,"Mathematics, Python, Data Visualization, Deep Learning, GCP",PhD,8,Government,2024-01-11,2024-03-12,1947,8.4,Cognitive Computing -AI01404,Data Engineer,147919,AUD,199691,SE,PT,Australia,L,Australia,0,"TensorFlow, Linux, Azure, Mathematics",Bachelor,8,Manufacturing,2024-05-20,2024-07-28,1479,7.6,Neural Networks Co -AI01405,Data Engineer,105054,CHF,94549,EN,CT,Switzerland,L,Switzerland,100,"Azure, Java, Data Visualization",Master,0,Technology,2024-03-06,2024-04-21,740,5.3,Advanced Robotics -AI01406,AI Architect,168883,USD,168883,EX,PT,South Korea,S,South Korea,50,"PyTorch, Spark, R, TensorFlow",Bachelor,17,Government,2024-04-02,2024-04-28,1976,5.5,TechCorp Inc -AI01407,AI Architect,54905,USD,54905,EN,PT,Finland,S,Malaysia,50,"SQL, Python, Azure, Hadoop, Mathematics",PhD,0,Government,2025-02-24,2025-03-31,1770,6.6,Machine Intelligence Group -AI01408,Data Scientist,73214,USD,73214,EX,CT,China,M,China,50,"SQL, Statistics, PyTorch, AWS",Bachelor,19,Government,2024-01-14,2024-03-03,1326,8.6,Future Systems -AI01409,Computer Vision Engineer,75589,USD,75589,MI,PT,South Korea,S,South Korea,50,"Python, Statistics, Computer Vision, Linux",Bachelor,4,Automotive,2024-02-11,2024-04-16,2026,7.2,Digital Transformation LLC -AI01410,Robotics Engineer,104795,CHF,94316,EN,CT,Switzerland,M,Japan,50,"Deep Learning, TensorFlow, Python, Linux, Java",Master,1,Telecommunications,2025-04-06,2025-05-28,1865,6.6,Future Systems -AI01411,AI Architect,19456,USD,19456,EN,CT,India,S,India,0,"Java, GCP, AWS, Deep Learning, Spark",Associate,1,Automotive,2024-02-24,2024-03-11,1072,9.7,Autonomous Tech -AI01412,Data Engineer,212599,EUR,180709,EX,FT,Austria,S,Austria,50,"Python, Docker, SQL, Linux",Master,13,Automotive,2024-07-11,2024-07-27,1697,10,DeepTech Ventures -AI01413,AI Research Scientist,63226,JPY,6954860,EN,CT,Japan,M,Japan,0,"Hadoop, Python, TensorFlow, Deep Learning",Bachelor,1,Government,2024-10-04,2024-12-07,963,6.7,Cloud AI Solutions -AI01414,AI Architect,188891,USD,188891,SE,PT,United States,L,Portugal,0,"Python, SQL, Linux",Master,5,Automotive,2024-01-16,2024-03-01,2133,5.8,DeepTech Ventures -AI01415,Head of AI,45335,USD,45335,EN,FT,South Korea,S,South Korea,100,"NLP, SQL, Java, MLOps, Kubernetes",Bachelor,0,Manufacturing,2024-06-01,2024-06-17,1381,6.3,Predictive Systems -AI01416,NLP Engineer,114078,GBP,85559,MI,CT,United Kingdom,M,United Kingdom,50,"Java, TensorFlow, GCP",PhD,4,Technology,2024-05-01,2024-05-26,1203,6.5,Digital Transformation LLC -AI01417,AI Software Engineer,221905,USD,221905,EX,FL,Norway,L,Norway,0,"Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-11-19,2024-12-05,1585,5.9,Algorithmic Solutions -AI01418,Principal Data Scientist,34898,USD,34898,MI,FL,China,M,China,100,"Kubernetes, Linux, Git, SQL, R",PhD,4,Retail,2025-01-17,2025-02-14,1878,7.1,AI Innovations -AI01419,Autonomous Systems Engineer,288283,USD,288283,EX,FL,Ireland,L,Vietnam,50,"Tableau, Statistics, Spark, Kubernetes, Git",Master,17,Consulting,2024-01-31,2024-03-21,882,7.1,Cloud AI Solutions -AI01420,Robotics Engineer,75188,USD,75188,MI,FT,Ireland,M,Ukraine,50,"Python, Git, Azure",Associate,3,Government,2025-04-11,2025-05-26,1123,9,TechCorp Inc -AI01421,Principal Data Scientist,87149,USD,87149,EN,FL,Denmark,S,Italy,50,"Azure, Kubernetes, Docker, SQL, Data Visualization",Associate,1,Real Estate,2024-11-02,2024-11-18,1009,7.4,TechCorp Inc -AI01422,Robotics Engineer,91150,USD,91150,MI,CT,Norway,S,Norway,50,"Java, Python, Computer Vision",PhD,4,Retail,2024-06-05,2024-08-04,2308,7,Quantum Computing Inc -AI01423,Research Scientist,126040,AUD,170154,SE,FL,Australia,S,Australia,50,"Docker, SQL, Mathematics, Spark",Master,9,Manufacturing,2024-05-07,2024-06-21,2052,9.9,DeepTech Ventures -AI01424,AI Research Scientist,187737,USD,187737,EX,FT,Sweden,L,Sweden,0,"Java, R, Mathematics, Computer Vision",PhD,15,Government,2024-03-30,2024-04-25,1706,7,Machine Intelligence Group -AI01425,AI Product Manager,125535,USD,125535,MI,PT,United States,M,United States,0,"Hadoop, PyTorch, Scala, GCP",Bachelor,3,Retail,2024-06-17,2024-07-16,2147,7.7,TechCorp Inc -AI01426,AI Product Manager,373536,USD,373536,EX,FL,Norway,L,Norway,100,"NLP, Kubernetes, Spark",Master,10,Technology,2025-03-20,2025-05-22,730,9.4,DeepTech Ventures -AI01427,Deep Learning Engineer,100732,CHF,90659,EN,FT,Switzerland,M,Switzerland,100,"Tableau, Python, Hadoop, Kubernetes",PhD,1,Media,2024-06-16,2024-07-30,1200,10,Predictive Systems -AI01428,Data Engineer,212371,GBP,159278,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Kubernetes, Tableau, Hadoop, Scala",Bachelor,15,Consulting,2025-03-06,2025-03-20,615,9.5,Autonomous Tech -AI01429,AI Software Engineer,65466,EUR,55646,EN,PT,Germany,L,Germany,0,"Mathematics, PyTorch, Statistics",Master,1,Finance,2024-03-25,2024-05-04,1943,8.2,Quantum Computing Inc -AI01430,Computer Vision Engineer,109204,SGD,141965,MI,PT,Singapore,M,Nigeria,50,"Mathematics, Data Visualization, MLOps, Tableau",Associate,3,Retail,2024-09-15,2024-11-16,1841,5.3,AI Innovations -AI01431,Data Engineer,72736,JPY,8000960,MI,CT,Japan,S,Germany,50,"R, Python, Data Visualization, PyTorch",Associate,2,Telecommunications,2025-02-13,2025-03-21,1794,8.9,AI Innovations -AI01432,Autonomous Systems Engineer,20520,USD,20520,EN,FL,India,M,Israel,100,"R, Spark, Hadoop, Kubernetes, GCP",Associate,0,Gaming,2024-07-21,2024-08-07,2201,8.9,Cloud AI Solutions -AI01433,AI Architect,158930,USD,158930,EX,PT,Ireland,M,Ireland,100,"Spark, PyTorch, Mathematics",PhD,19,Transportation,2025-01-29,2025-03-23,965,7.9,DeepTech Ventures -AI01434,Principal Data Scientist,76074,CHF,68467,EN,FT,Switzerland,M,Switzerland,100,"Scala, Spark, MLOps",Master,0,Gaming,2024-06-14,2024-07-22,2169,6,Cognitive Computing -AI01435,Machine Learning Researcher,59343,EUR,50442,EN,FT,France,S,France,0,"NLP, Mathematics, Kubernetes, Computer Vision, Tableau",Bachelor,1,Government,2024-03-29,2024-05-11,690,8.2,Advanced Robotics -AI01436,Data Scientist,104447,USD,104447,MI,CT,United States,S,United States,100,"Deep Learning, Data Visualization, AWS, TensorFlow, Scala",Bachelor,2,Technology,2024-12-10,2025-02-15,1675,8.4,Neural Networks Co -AI01437,AI Software Engineer,43120,USD,43120,MI,PT,China,M,China,50,"AWS, Docker, NLP",Bachelor,4,Automotive,2024-03-04,2024-04-21,1871,8.9,DataVision Ltd -AI01438,Machine Learning Engineer,219852,EUR,186874,EX,FL,Austria,L,Austria,100,"Hadoop, Kubernetes, TensorFlow, GCP",Associate,14,Healthcare,2024-01-11,2024-03-11,1760,6.6,DataVision Ltd -AI01439,Data Engineer,40164,USD,40164,SE,CT,India,S,India,0,"Scala, Kubernetes, Git, Docker",Bachelor,7,Telecommunications,2024-11-21,2025-01-23,2230,5.9,Digital Transformation LLC -AI01440,Data Analyst,164110,SGD,213343,EX,FT,Singapore,S,Singapore,50,"SQL, Git, GCP",Associate,15,Gaming,2025-01-04,2025-02-01,1042,7.8,Future Systems -AI01441,Machine Learning Researcher,33846,USD,33846,MI,PT,China,S,China,100,"PyTorch, Hadoop, Statistics, AWS, Computer Vision",Bachelor,2,Transportation,2024-03-06,2024-03-22,804,6.8,Digital Transformation LLC -AI01442,Data Engineer,126266,USD,126266,MI,PT,Sweden,L,Sweden,100,"PyTorch, Spark, TensorFlow",Master,4,Energy,2024-06-28,2024-07-28,1765,6.6,Machine Intelligence Group -AI01443,Head of AI,98327,USD,98327,MI,PT,United States,L,United States,50,"R, Data Visualization, Mathematics",Associate,4,Education,2024-09-12,2024-10-04,1849,5.1,Neural Networks Co -AI01444,Data Scientist,77366,GBP,58025,MI,PT,United Kingdom,S,Japan,50,"Python, TensorFlow, NLP, Azure, AWS",PhD,3,Automotive,2024-06-19,2024-08-04,2357,5.6,Cognitive Computing -AI01445,ML Ops Engineer,76129,USD,76129,EN,FL,Denmark,S,Indonesia,50,"Hadoop, PyTorch, MLOps",Master,0,Education,2024-12-01,2024-12-15,788,7.8,Cloud AI Solutions -AI01446,AI Product Manager,134331,CHF,120898,MI,PT,Switzerland,L,Switzerland,100,"Java, Mathematics, TensorFlow",Associate,2,Energy,2024-01-11,2024-02-19,842,10,DeepTech Ventures -AI01447,Data Engineer,56083,EUR,47671,EN,FL,Austria,M,Austria,0,"Python, Statistics, SQL, R, Linux",Master,1,Transportation,2024-07-24,2024-08-16,1613,6.4,AI Innovations -AI01448,Robotics Engineer,147444,USD,147444,EX,CT,Finland,S,Finland,0,"Scala, Spark, Java",PhD,15,Technology,2025-04-18,2025-06-06,2271,5.6,Cloud AI Solutions -AI01449,AI Product Manager,92983,USD,92983,EN,CT,Norway,S,Ghana,50,"TensorFlow, Scala, GCP, Git",PhD,0,Education,2025-01-04,2025-01-26,1036,7.8,Neural Networks Co -AI01450,ML Ops Engineer,83859,EUR,71280,EN,FL,Austria,L,Austria,50,"Tableau, Hadoop, PyTorch",Bachelor,1,Real Estate,2025-01-18,2025-03-31,2435,8.2,Predictive Systems -AI01451,NLP Engineer,84786,EUR,72068,MI,FL,Germany,M,Ukraine,0,"Java, Linux, Statistics, Git",Master,2,Transportation,2025-02-04,2025-03-18,1912,9.2,Digital Transformation LLC -AI01452,Computer Vision Engineer,154829,EUR,131605,EX,CT,Germany,S,Kenya,100,"Tableau, AWS, Hadoop, Kubernetes, Git",Bachelor,11,Energy,2024-08-21,2024-10-30,2309,5.4,DataVision Ltd -AI01453,Machine Learning Engineer,216967,GBP,162725,EX,FT,United Kingdom,S,Chile,0,"R, Scala, NLP, Git, Docker",Bachelor,12,Education,2024-07-18,2024-09-29,1500,8.6,Future Systems -AI01454,Computer Vision Engineer,90170,USD,90170,MI,PT,Ireland,L,Ireland,100,"Git, TensorFlow, Deep Learning",Bachelor,3,Transportation,2024-04-12,2024-05-08,2067,5.6,TechCorp Inc -AI01455,AI Software Engineer,59279,SGD,77063,EN,PT,Singapore,M,Singapore,0,"Python, TensorFlow, PyTorch, Linux",Associate,1,Education,2025-02-22,2025-04-02,2481,9.2,Cloud AI Solutions -AI01456,AI Specialist,85165,USD,85165,EX,FL,China,L,China,100,"MLOps, Spark, Azure, TensorFlow",Bachelor,19,Automotive,2025-03-11,2025-04-29,1813,6.6,Digital Transformation LLC -AI01457,Machine Learning Researcher,58417,EUR,49654,EN,PT,Netherlands,S,United States,100,"Spark, Docker, GCP, Statistics, Python",PhD,1,Technology,2024-07-22,2024-09-17,1842,8.4,Smart Analytics -AI01458,Research Scientist,160456,EUR,136388,EX,CT,Netherlands,M,Netherlands,100,"Python, TensorFlow, MLOps, Spark, R",Master,11,Manufacturing,2024-04-08,2024-05-27,1814,5.4,Autonomous Tech -AI01459,Robotics Engineer,29590,USD,29590,EN,FT,China,S,South Korea,0,"Linux, Data Visualization, Java, Hadoop, NLP",Bachelor,1,Retail,2024-06-10,2024-08-07,1355,5.4,TechCorp Inc -AI01460,Deep Learning Engineer,242489,GBP,181867,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, Hadoop, Python, Mathematics, Docker",Bachelor,19,Telecommunications,2024-08-14,2024-09-04,985,5.8,Algorithmic Solutions -AI01461,ML Ops Engineer,136042,GBP,102032,SE,FT,United Kingdom,S,Austria,0,"Scala, Kubernetes, Linux, AWS",Bachelor,8,Gaming,2024-07-19,2024-09-08,2139,8.7,Future Systems -AI01462,AI Software Engineer,104200,CAD,130250,SE,FT,Canada,M,Canada,100,"Linux, Kubernetes, Scala",Master,9,Gaming,2025-03-26,2025-05-11,2429,6.3,Advanced Robotics -AI01463,Principal Data Scientist,137878,EUR,117196,SE,CT,Germany,L,Latvia,50,"R, SQL, Tableau, MLOps, Kubernetes",Master,7,Manufacturing,2025-03-10,2025-03-31,640,7.2,Cognitive Computing -AI01464,ML Ops Engineer,187710,USD,187710,SE,PT,Denmark,M,Denmark,50,"Git, NLP, SQL",Bachelor,8,Consulting,2025-02-15,2025-03-25,1597,7.4,Algorithmic Solutions -AI01465,AI Software Engineer,50439,USD,50439,SE,CT,India,M,India,100,"Spark, Python, TensorFlow, Statistics, Java",Master,7,Telecommunications,2024-01-08,2024-03-03,2331,7.7,Algorithmic Solutions -AI01466,AI Architect,29300,USD,29300,EN,FT,India,L,India,50,"Tableau, R, MLOps",PhD,1,Media,2024-11-03,2025-01-01,2378,8.5,Algorithmic Solutions -AI01467,Machine Learning Engineer,93689,USD,93689,EX,FT,China,S,China,0,"Python, TensorFlow, Mathematics, Kubernetes, Docker",Associate,18,Real Estate,2024-04-02,2024-05-26,2251,8.3,Smart Analytics -AI01468,Data Analyst,182500,USD,182500,EX,FL,United States,M,United States,0,"Mathematics, MLOps, Azure",Associate,16,Automotive,2024-11-22,2024-12-29,1397,9.6,Neural Networks Co -AI01469,Robotics Engineer,149041,AUD,201205,SE,FL,Australia,L,Australia,0,"PyTorch, TensorFlow, Scala, Git",PhD,8,Education,2025-03-10,2025-04-23,851,7.2,Digital Transformation LLC -AI01470,Computer Vision Engineer,43748,EUR,37186,EN,PT,France,S,Mexico,50,"Deep Learning, Java, SQL, Git, Docker",PhD,0,Education,2024-12-18,2025-01-30,692,9.5,AI Innovations -AI01471,Principal Data Scientist,54185,EUR,46057,EN,FT,Germany,S,India,0,"Computer Vision, PyTorch, Scala, GCP",Master,0,Telecommunications,2025-03-18,2025-05-29,755,6.8,TechCorp Inc -AI01472,NLP Engineer,69436,USD,69436,EX,PT,India,M,India,100,"Data Visualization, Kubernetes, Python",Associate,19,Automotive,2024-11-10,2024-12-04,748,8.4,Neural Networks Co -AI01473,Data Analyst,103188,USD,103188,EN,PT,United States,L,United States,0,"Git, Spark, Python, Java, GCP",PhD,1,Transportation,2024-03-24,2024-04-24,1596,5.6,Smart Analytics -AI01474,AI Research Scientist,116739,CHF,105065,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Java, Hadoop",Bachelor,0,Education,2025-01-21,2025-02-11,2191,6.3,Future Systems -AI01475,Deep Learning Engineer,73367,EUR,62362,EN,FL,Austria,M,Austria,0,"AWS, SQL, Tableau, PyTorch",Bachelor,1,Gaming,2024-11-30,2024-12-30,521,6.3,Predictive Systems -AI01476,Data Engineer,72979,JPY,8027690,EN,CT,Japan,S,Japan,50,"PyTorch, R, Docker, GCP, Azure",Associate,1,Retail,2025-02-21,2025-03-27,2262,6.5,Neural Networks Co -AI01477,Data Engineer,193939,USD,193939,EX,PT,Israel,M,Israel,100,"TensorFlow, Python, Hadoop, Tableau, Data Visualization",Bachelor,12,Technology,2025-01-28,2025-03-24,1382,8.6,DeepTech Ventures -AI01478,Research Scientist,151333,USD,151333,EX,FL,Ireland,M,Ireland,50,"Kubernetes, R, Statistics, GCP, Scala",Master,19,Gaming,2025-03-04,2025-05-04,503,5.8,Cognitive Computing -AI01479,Data Scientist,63229,USD,63229,SE,CT,China,S,China,100,"Scala, Java, Statistics, AWS, Kubernetes",Associate,6,Education,2024-12-17,2025-01-21,2342,9.8,Cognitive Computing -AI01480,Principal Data Scientist,188397,CHF,169557,SE,FT,Switzerland,S,Netherlands,50,"Git, PyTorch, AWS, Docker, GCP",Master,7,Healthcare,2024-09-02,2024-10-31,1198,9.6,AI Innovations -AI01481,Robotics Engineer,102987,USD,102987,MI,FT,Denmark,M,Denmark,0,"Python, GCP, MLOps, Azure, Hadoop",PhD,4,Retail,2024-07-28,2024-10-05,1017,6.5,DataVision Ltd -AI01482,AI Specialist,226210,USD,226210,SE,FT,Denmark,L,Denmark,50,"PyTorch, Scala, TensorFlow, AWS, Deep Learning",PhD,9,Manufacturing,2024-02-15,2024-03-29,2494,5.6,Future Systems -AI01483,AI Architect,18309,USD,18309,EN,FL,India,S,India,100,"PyTorch, Deep Learning, TensorFlow",Associate,0,Media,2024-10-14,2024-12-12,1247,7.6,DeepTech Ventures -AI01484,AI Software Engineer,210459,USD,210459,EX,CT,Israel,S,Israel,0,"Python, Computer Vision, NLP, Azure, Java",Master,17,Government,2025-02-19,2025-04-26,898,6.9,Advanced Robotics -AI01485,Robotics Engineer,70962,USD,70962,SE,CT,China,M,China,0,"Computer Vision, SQL, Linux",Associate,6,Consulting,2025-02-10,2025-03-22,1509,5.3,Machine Intelligence Group -AI01486,AI Research Scientist,71103,EUR,60438,MI,PT,Netherlands,S,New Zealand,0,"R, AWS, Kubernetes, Linux, Mathematics",Bachelor,3,Healthcare,2024-06-04,2024-08-16,1863,8.7,Predictive Systems -AI01487,Computer Vision Engineer,94344,USD,94344,EN,FT,Denmark,M,Argentina,50,"AWS, Tableau, SQL, PyTorch",Master,0,Education,2024-08-31,2024-09-27,1961,8.1,Predictive Systems -AI01488,Autonomous Systems Engineer,31310,USD,31310,EN,FT,China,M,China,100,"Tableau, Kubernetes, Scala",Bachelor,0,Healthcare,2025-03-16,2025-04-20,712,6.8,DataVision Ltd -AI01489,AI Product Manager,186865,USD,186865,EX,PT,Ireland,L,Ireland,100,"Data Visualization, Python, TensorFlow, AWS",PhD,17,Technology,2024-06-07,2024-08-14,1906,8,Cognitive Computing -AI01490,AI Product Manager,22689,USD,22689,EN,CT,India,S,India,50,"Deep Learning, SQL, MLOps, Data Visualization, Git",Bachelor,0,Finance,2024-08-20,2024-09-29,835,5.1,DataVision Ltd -AI01491,AI Product Manager,71875,USD,71875,EX,FT,China,M,China,50,"Hadoop, SQL, Data Visualization, TensorFlow",PhD,17,Healthcare,2024-01-30,2024-03-22,2427,8.7,DataVision Ltd -AI01492,AI Specialist,91093,USD,91093,EN,FT,Denmark,M,Denmark,50,"Tableau, SQL, Python",Master,1,Finance,2024-07-07,2024-07-22,1322,7.4,Cloud AI Solutions -AI01493,NLP Engineer,59983,USD,59983,MI,CT,South Korea,S,Colombia,50,"SQL, PyTorch, Tableau, Kubernetes",Master,3,Finance,2025-02-22,2025-04-04,1654,9.6,Smart Analytics -AI01494,AI Specialist,315917,CHF,284325,EX,FL,Switzerland,M,Switzerland,50,"Statistics, SQL, Tableau, Computer Vision, Docker",PhD,13,Media,2024-01-21,2024-03-01,870,7.4,Predictive Systems -AI01495,Robotics Engineer,49015,USD,49015,EN,FT,Ireland,S,Ireland,100,"Scala, Data Visualization, SQL, MLOps",Bachelor,1,Healthcare,2024-11-30,2025-01-28,920,5.1,Predictive Systems -AI01496,NLP Engineer,45174,USD,45174,EN,CT,South Korea,M,South Korea,50,"Python, Scala, SQL",Associate,0,Consulting,2024-07-27,2024-08-17,857,5.7,Quantum Computing Inc -AI01497,Head of AI,124375,USD,124375,MI,FL,Norway,L,Norway,0,"SQL, Computer Vision, Git, GCP, PyTorch",Master,3,Transportation,2024-10-22,2025-01-01,2017,6.1,TechCorp Inc -AI01498,Principal Data Scientist,24919,USD,24919,EN,CT,India,M,Indonesia,0,"TensorFlow, Tableau, GCP",Associate,0,Gaming,2024-07-25,2024-08-18,2434,7.3,Predictive Systems -AI01499,AI Architect,103196,EUR,87717,SE,FL,Austria,M,Austria,50,"SQL, Java, Kubernetes, Deep Learning",Master,9,Automotive,2025-04-08,2025-06-02,2102,8,DataVision Ltd -AI01500,Computer Vision Engineer,101200,USD,101200,EN,FL,Norway,M,Norway,100,"SQL, Computer Vision, PyTorch, Git, Tableau",Bachelor,1,Government,2024-11-04,2024-11-21,2344,6.9,Advanced Robotics -AI01501,Data Scientist,146547,USD,146547,SE,FT,Finland,L,Canada,100,"TensorFlow, NLP, Mathematics, Tableau, Kubernetes",Bachelor,9,Automotive,2024-10-30,2024-12-27,669,6.9,Machine Intelligence Group -AI01502,Autonomous Systems Engineer,72296,USD,72296,SE,CT,China,L,China,50,"Scala, AWS, NLP, Git, Python",Associate,8,Automotive,2025-03-21,2025-05-14,1029,9.8,Algorithmic Solutions -AI01503,ML Ops Engineer,63430,USD,63430,EN,FL,United States,S,Thailand,50,"GCP, Deep Learning, PyTorch, AWS",PhD,0,Automotive,2024-11-14,2025-01-08,2301,6.9,Machine Intelligence Group -AI01504,Computer Vision Engineer,266480,USD,266480,EX,FT,Israel,L,Israel,100,"SQL, Python, Tableau, Statistics",Bachelor,16,Consulting,2024-12-02,2025-01-20,1350,6.4,Predictive Systems -AI01505,Computer Vision Engineer,115622,EUR,98279,SE,CT,Austria,S,Austria,0,"Spark, Hadoop, Data Visualization, MLOps, Azure",Master,6,Transportation,2024-07-26,2024-08-18,589,7.9,DataVision Ltd -AI01506,NLP Engineer,59313,USD,59313,SE,FT,India,L,Philippines,0,"Data Visualization, GCP, Linux, Computer Vision",Master,7,Manufacturing,2024-12-26,2025-02-16,901,7.3,AI Innovations -AI01507,Research Scientist,106901,EUR,90866,MI,FL,Germany,L,Germany,50,"TensorFlow, Python, Statistics",PhD,3,Manufacturing,2025-04-14,2025-06-23,746,5.8,Smart Analytics -AI01508,NLP Engineer,179377,EUR,152470,EX,CT,Netherlands,S,Nigeria,0,"Data Visualization, GCP, Scala, R, AWS",Associate,11,Technology,2024-09-21,2024-10-23,1996,6.3,Algorithmic Solutions -AI01509,Data Engineer,98356,USD,98356,MI,CT,Sweden,M,Sweden,0,"NLP, PyTorch, Scala, Deep Learning",Associate,2,Technology,2024-12-12,2025-01-17,1771,6,Autonomous Tech -AI01510,Data Analyst,143818,SGD,186963,SE,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, TensorFlow, Statistics",Bachelor,8,Manufacturing,2024-05-16,2024-07-14,807,8,DeepTech Ventures -AI01511,AI Research Scientist,148765,CAD,185956,SE,PT,Canada,L,Canada,50,"Computer Vision, PyTorch, SQL",Associate,6,Gaming,2025-04-28,2025-07-10,1542,6.4,Quantum Computing Inc -AI01512,Research Scientist,88116,USD,88116,EN,FT,Norway,S,Singapore,0,"R, NLP, GCP",PhD,1,Telecommunications,2025-03-14,2025-03-29,2478,6.7,Predictive Systems -AI01513,Robotics Engineer,49914,USD,49914,EN,FL,South Korea,S,South Korea,50,"Hadoop, Python, Computer Vision",PhD,0,Telecommunications,2024-01-30,2024-04-11,1057,6.9,Quantum Computing Inc -AI01514,Autonomous Systems Engineer,39015,USD,39015,EN,PT,China,L,China,0,"R, Linux, SQL, PyTorch",PhD,0,Automotive,2024-10-27,2024-12-10,1371,6.3,Digital Transformation LLC -AI01515,AI Architect,88810,GBP,66608,MI,FL,United Kingdom,L,Russia,0,"Tableau, Scala, Spark",PhD,4,Finance,2024-07-25,2024-09-25,963,9.9,Predictive Systems -AI01516,Machine Learning Engineer,224663,USD,224663,EX,FL,United States,L,United States,50,"TensorFlow, Deep Learning, Computer Vision",Associate,19,Automotive,2024-11-28,2025-01-18,1986,9.9,DeepTech Ventures -AI01517,Data Scientist,63881,AUD,86239,EN,CT,Australia,L,Australia,0,"PyTorch, GCP, Computer Vision, AWS",Associate,0,Transportation,2024-10-24,2024-11-10,1505,9.4,Digital Transformation LLC -AI01518,Machine Learning Researcher,95307,USD,95307,SE,CT,South Korea,M,South Korea,0,"Hadoop, AWS, Scala, TensorFlow",Master,6,Energy,2024-09-22,2024-10-21,1156,8.5,DeepTech Ventures -AI01519,AI Software Engineer,102086,USD,102086,EN,PT,Norway,L,Norway,100,"Mathematics, Git, Java",PhD,0,Education,2024-01-16,2024-02-10,1340,8.2,Autonomous Tech -AI01520,Deep Learning Engineer,97103,AUD,131089,MI,PT,Australia,M,Australia,100,"Statistics, Tableau, Data Visualization",PhD,2,Technology,2024-12-31,2025-01-23,1745,8.3,Future Systems -AI01521,Data Scientist,174876,CHF,157388,SE,PT,Switzerland,M,Switzerland,100,"SQL, Spark, GCP, PyTorch, Azure",Bachelor,7,Retail,2024-05-23,2024-07-07,2247,7.3,Autonomous Tech -AI01522,Machine Learning Researcher,77585,EUR,65947,MI,FT,France,M,France,50,"GCP, Scala, Deep Learning",Associate,2,Gaming,2024-08-13,2024-10-15,2332,5.5,Machine Intelligence Group -AI01523,Robotics Engineer,83753,USD,83753,EN,PT,Denmark,M,Denmark,0,"Tableau, Spark, Python, MLOps",Master,0,Retail,2024-05-26,2024-07-02,1715,5.8,Algorithmic Solutions -AI01524,Deep Learning Engineer,191492,JPY,21064120,EX,FT,Japan,S,Japan,0,"Python, MLOps, Mathematics",Bachelor,11,Healthcare,2024-05-21,2024-07-26,1072,7.3,TechCorp Inc -AI01525,AI Consultant,71219,USD,71219,EN,FL,Israel,M,Israel,0,"PyTorch, SQL, TensorFlow, Scala, Python",PhD,0,Healthcare,2024-04-03,2024-05-25,1209,9.4,TechCorp Inc -AI01526,Computer Vision Engineer,143605,AUD,193867,SE,PT,Australia,L,Australia,50,"Git, TensorFlow, Computer Vision, MLOps, Deep Learning",Bachelor,9,Media,2024-03-27,2024-04-16,1914,6.8,Digital Transformation LLC -AI01527,Data Analyst,261388,USD,261388,EX,FL,Norway,L,Norway,100,"Tableau, Mathematics, Scala, Java, Computer Vision",Bachelor,11,Finance,2024-10-20,2024-12-27,688,10,DeepTech Ventures -AI01528,Data Engineer,115250,GBP,86438,MI,FT,United Kingdom,L,United Kingdom,0,"Java, Tableau, PyTorch, Statistics, Azure",Bachelor,3,Retail,2024-07-01,2024-08-03,1696,8.9,Algorithmic Solutions -AI01529,AI Research Scientist,214259,USD,214259,EX,FT,Ireland,M,Ireland,0,"Tableau, Linux, PyTorch, Docker, Deep Learning",Associate,16,Education,2024-10-07,2024-10-31,609,6.8,Algorithmic Solutions -AI01530,Machine Learning Researcher,50907,USD,50907,SE,FT,China,S,Poland,0,"Statistics, Scala, Deep Learning, NLP",Bachelor,6,Telecommunications,2024-04-23,2024-05-18,1329,6.2,DataVision Ltd -AI01531,NLP Engineer,157211,USD,157211,EX,CT,Israel,S,Israel,0,"Java, GCP, Computer Vision, Git, Hadoop",Master,11,Education,2024-11-10,2024-12-02,1072,8.1,Machine Intelligence Group -AI01532,ML Ops Engineer,110447,EUR,93880,MI,FT,Germany,M,Germany,50,"Java, Python, Git, SQL, Computer Vision",Bachelor,4,Gaming,2024-08-18,2024-10-19,666,6.9,Cognitive Computing -AI01533,ML Ops Engineer,108700,SGD,141310,MI,CT,Singapore,L,Singapore,0,"Git, NLP, Kubernetes, Statistics",Bachelor,4,Education,2024-09-23,2024-10-28,1849,8.3,Digital Transformation LLC -AI01534,Head of AI,67170,EUR,57095,EN,CT,France,L,Australia,100,"AWS, R, SQL, Mathematics",Master,1,Finance,2025-01-07,2025-03-07,832,6.6,Machine Intelligence Group -AI01535,Computer Vision Engineer,45079,USD,45079,SE,FL,China,S,China,0,"Data Visualization, Spark, Linux",Master,6,Energy,2024-09-15,2024-11-17,1064,6,Advanced Robotics -AI01536,AI Architect,97906,AUD,132173,MI,PT,Australia,S,Australia,100,"Linux, SQL, R, Computer Vision, Spark",Bachelor,3,Government,2024-04-28,2024-06-05,2486,5.6,TechCorp Inc -AI01537,Principal Data Scientist,88189,USD,88189,SE,PT,South Korea,S,South Korea,100,"Scala, Hadoop, Tableau, Git",Associate,8,Retail,2025-03-02,2025-04-20,1536,7.3,Machine Intelligence Group -AI01538,Robotics Engineer,103595,CAD,129494,MI,FT,Canada,M,Canada,0,"TensorFlow, Computer Vision, Python, MLOps",Associate,2,Consulting,2024-04-04,2024-05-20,657,6.9,Smart Analytics -AI01539,Data Analyst,113624,USD,113624,SE,CT,Finland,S,Sweden,50,"SQL, GCP, Linux, Tableau, Hadoop",Bachelor,8,Technology,2024-05-24,2024-06-23,2433,7.2,Smart Analytics -AI01540,Autonomous Systems Engineer,134364,SGD,174673,SE,CT,Singapore,M,Singapore,100,"Mathematics, NLP, Docker, Tableau, Git",Master,8,Healthcare,2024-12-22,2025-01-18,1559,7.7,Smart Analytics -AI01541,AI Product Manager,143237,AUD,193370,EX,FT,Australia,S,Australia,100,"Docker, Python, Kubernetes",PhD,12,Real Estate,2025-02-13,2025-03-31,723,6.6,Predictive Systems -AI01542,ML Ops Engineer,61187,CAD,76484,EN,FT,Canada,L,Canada,100,"TensorFlow, Computer Vision, SQL, Scala, Hadoop",Associate,0,Telecommunications,2024-08-21,2024-09-21,1196,7.9,Machine Intelligence Group -AI01543,Autonomous Systems Engineer,64608,USD,64608,EN,FT,South Korea,M,Colombia,50,"GCP, Python, Hadoop, TensorFlow",PhD,0,Government,2025-03-21,2025-05-16,2441,8.1,Smart Analytics -AI01544,Principal Data Scientist,311834,CHF,280651,EX,FT,Switzerland,L,Switzerland,0,"Kubernetes, Hadoop, Python, Data Visualization, Mathematics",Bachelor,14,Transportation,2024-02-29,2024-04-11,1088,7.6,DataVision Ltd -AI01545,Deep Learning Engineer,127894,USD,127894,MI,CT,Denmark,M,Denmark,50,"TensorFlow, Azure, GCP, Java",Master,4,Finance,2024-07-17,2024-09-04,538,8.3,Machine Intelligence Group -AI01546,Data Scientist,75336,GBP,56502,EN,FL,United Kingdom,S,United Kingdom,0,"NLP, Java, MLOps, Kubernetes",Bachelor,0,Telecommunications,2024-09-12,2024-10-21,2367,9.7,AI Innovations -AI01547,Research Scientist,66416,USD,66416,EN,FL,Ireland,S,Ireland,50,"R, SQL, Linux, Mathematics",Associate,1,Telecommunications,2024-04-05,2024-06-09,1592,8.4,AI Innovations -AI01548,AI Architect,49315,USD,49315,EN,FT,Israel,S,Israel,50,"GCP, Git, Data Visualization, Tableau, MLOps",Bachelor,0,Government,2024-11-05,2024-12-08,1778,6.7,Neural Networks Co -AI01549,AI Architect,130837,EUR,111211,SE,FT,Germany,S,Germany,100,"Python, TensorFlow, Deep Learning, Scala, Computer Vision",Master,9,Automotive,2024-02-03,2024-03-18,1032,7.6,DataVision Ltd -AI01550,Head of AI,93179,CAD,116474,SE,PT,Canada,S,Canada,0,"Kubernetes, NLP, MLOps, Spark, Hadoop",Associate,5,Gaming,2024-08-28,2024-10-20,2076,5.8,Future Systems -AI01551,Machine Learning Researcher,88696,EUR,75392,EN,PT,Netherlands,L,Netherlands,50,"Java, Mathematics, GCP",Bachelor,1,Consulting,2025-03-23,2025-04-11,896,5.3,Smart Analytics -AI01552,AI Specialist,125978,GBP,94484,SE,PT,United Kingdom,S,United Kingdom,100,"Azure, TensorFlow, Scala",Bachelor,8,Energy,2025-03-01,2025-05-12,1769,9.5,Predictive Systems -AI01553,Robotics Engineer,73015,EUR,62063,EN,CT,Netherlands,M,Netherlands,50,"Git, GCP, Tableau, MLOps",Bachelor,1,Gaming,2024-02-19,2024-04-26,647,5.7,Machine Intelligence Group -AI01554,Data Analyst,89921,EUR,76433,MI,CT,Austria,S,Austria,100,"R, NLP, Python",Bachelor,2,Finance,2024-12-07,2025-01-20,1779,5.3,Digital Transformation LLC -AI01555,AI Specialist,145615,USD,145615,SE,FL,Denmark,S,Denmark,50,"Deep Learning, MLOps, PyTorch, Git, Statistics",Master,8,Automotive,2024-08-16,2024-10-28,2383,5.3,Quantum Computing Inc -AI01556,Machine Learning Researcher,72798,EUR,61878,EN,PT,France,L,France,0,"Deep Learning, SQL, Tableau, Python",PhD,1,Finance,2024-02-26,2024-04-20,976,8.1,Algorithmic Solutions -AI01557,AI Architect,202771,EUR,172355,EX,FL,France,S,Estonia,0,"Linux, Spark, Computer Vision",Master,19,Gaming,2024-04-30,2024-06-04,1300,8.1,Machine Intelligence Group -AI01558,Computer Vision Engineer,101963,SGD,132552,MI,FL,Singapore,S,Singapore,50,"Data Visualization, Scala, Tableau, Java, Mathematics",PhD,2,Telecommunications,2025-01-27,2025-03-04,2401,8.7,Cloud AI Solutions -AI01559,Principal Data Scientist,131393,EUR,111684,SE,FL,Netherlands,L,Egypt,0,"Python, Data Visualization, TensorFlow",Associate,6,Gaming,2024-06-30,2024-09-04,1399,7.3,Predictive Systems -AI01560,Data Engineer,216001,USD,216001,SE,PT,Denmark,L,Philippines,100,"Java, GCP, Deep Learning, Docker, Spark",Associate,7,Education,2024-11-17,2024-12-05,2098,7.9,Machine Intelligence Group -AI01561,AI Research Scientist,165488,USD,165488,EX,FT,South Korea,S,Egypt,100,"Tableau, Computer Vision, Docker, Python",Associate,17,Finance,2024-01-01,2024-03-12,732,5,Smart Analytics -AI01562,AI Consultant,279330,SGD,363129,EX,FT,Singapore,L,Nigeria,100,"PyTorch, Mathematics, Docker, Statistics, R",Associate,11,Media,2024-08-26,2024-09-25,1724,5.4,Algorithmic Solutions -AI01563,Head of AI,120176,EUR,102150,SE,CT,Austria,M,Austria,0,"Computer Vision, AWS, Data Visualization, Linux, R",PhD,9,Retail,2024-04-16,2024-06-07,922,8.9,Advanced Robotics -AI01564,AI Architect,242800,EUR,206380,EX,FL,Netherlands,M,Netherlands,50,"Docker, Git, Data Visualization, MLOps",PhD,14,Finance,2024-07-09,2024-08-10,1726,8.7,Algorithmic Solutions -AI01565,Autonomous Systems Engineer,135978,AUD,183570,SE,FT,Australia,S,Romania,0,"Azure, GCP, Linux, Python",Associate,7,Gaming,2025-04-19,2025-05-08,1352,9.8,Machine Intelligence Group -AI01566,Computer Vision Engineer,233643,CHF,210279,SE,PT,Switzerland,L,Switzerland,100,"Linux, GCP, TensorFlow, Docker, Python",Master,6,Education,2024-03-30,2024-06-10,1082,9.4,Neural Networks Co -AI01567,AI Architect,63249,USD,63249,MI,FT,South Korea,M,South Korea,100,"Spark, Data Visualization, Kubernetes, Python, Docker",Associate,2,Education,2024-08-12,2024-09-15,839,6,TechCorp Inc -AI01568,Data Engineer,89516,USD,89516,EX,PT,India,L,India,0,"Java, R, MLOps, Spark",Master,11,Real Estate,2024-03-12,2024-05-08,1876,9.7,Algorithmic Solutions -AI01569,Principal Data Scientist,176954,EUR,150411,EX,FT,France,M,Australia,50,"SQL, Python, MLOps",Master,15,Transportation,2024-08-18,2024-09-20,1122,6,Cloud AI Solutions -AI01570,Head of AI,55961,USD,55961,MI,PT,China,L,China,50,"Spark, Kubernetes, MLOps, Azure, Data Visualization",Associate,3,Education,2024-10-01,2024-12-03,1474,8.7,Smart Analytics -AI01571,Head of AI,132864,GBP,99648,SE,FT,United Kingdom,M,United Kingdom,100,"Scala, Python, Tableau",Bachelor,6,Finance,2025-03-18,2025-04-08,616,5.8,DataVision Ltd -AI01572,Research Scientist,104418,AUD,140964,MI,CT,Australia,M,Austria,50,"R, Git, MLOps, Spark",Associate,4,Manufacturing,2025-02-20,2025-04-03,2135,5.3,Algorithmic Solutions -AI01573,Deep Learning Engineer,80490,AUD,108662,EN,FL,Australia,M,South Africa,0,"TensorFlow, Java, Git",Bachelor,0,Healthcare,2024-06-15,2024-07-11,1830,9.8,Cognitive Computing -AI01574,Head of AI,85744,USD,85744,MI,FT,Israel,L,Israel,50,"R, GCP, Mathematics",Bachelor,3,Automotive,2024-12-04,2025-01-09,1123,7.8,DeepTech Ventures -AI01575,Principal Data Scientist,101111,EUR,85944,SE,FL,Austria,S,Netherlands,100,"Docker, Mathematics, Tableau, Linux",Master,9,Education,2025-02-09,2025-02-24,1304,8.8,Future Systems -AI01576,Machine Learning Engineer,195573,CAD,244466,EX,FT,Canada,L,Canada,100,"Mathematics, GCP, Kubernetes",Master,18,Telecommunications,2024-03-07,2024-04-23,1002,6.4,DataVision Ltd -AI01577,Robotics Engineer,136148,AUD,183800,SE,FL,Australia,M,Indonesia,0,"Azure, Java, SQL, Python, Computer Vision",PhD,9,Retail,2024-06-14,2024-07-02,1581,8.4,Quantum Computing Inc -AI01578,AI Architect,108512,SGD,141066,MI,FT,Singapore,L,Denmark,50,"Computer Vision, Linux, Data Visualization, Java, Azure",Master,4,Government,2024-03-23,2024-04-10,2122,9.3,Machine Intelligence Group -AI01579,Data Engineer,216695,EUR,184191,EX,FL,Germany,S,Germany,0,"Java, Tableau, Python, Deep Learning",Master,16,Education,2024-08-11,2024-09-07,646,7,Digital Transformation LLC -AI01580,NLP Engineer,169781,CHF,152803,SE,CT,Switzerland,S,Switzerland,50,"Python, Hadoop, Linux",PhD,5,Telecommunications,2024-08-20,2024-10-18,2253,8.6,Cloud AI Solutions -AI01581,Robotics Engineer,306082,CHF,275474,EX,PT,Switzerland,L,Switzerland,0,"Spark, AWS, Statistics",PhD,19,Telecommunications,2025-03-12,2025-05-16,1909,8.5,AI Innovations -AI01582,AI Research Scientist,82438,CHF,74194,EN,CT,Switzerland,S,Switzerland,0,"PyTorch, Java, MLOps",Associate,0,Finance,2024-10-20,2024-12-26,1139,5.2,DataVision Ltd -AI01583,NLP Engineer,57552,USD,57552,EN,FT,Ireland,M,India,0,"R, SQL, Deep Learning, PyTorch, Git",Associate,0,Finance,2024-03-10,2024-05-05,2293,7.6,Predictive Systems -AI01584,Head of AI,54111,CAD,67639,EN,CT,Canada,M,Canada,50,"Statistics, Spark, TensorFlow, Scala, GCP",PhD,1,Technology,2025-03-11,2025-04-13,1725,9.3,TechCorp Inc -AI01585,AI Product Manager,139157,EUR,118283,SE,PT,Germany,M,Germany,0,"Java, Azure, Python, MLOps",Bachelor,7,Media,2025-03-06,2025-05-13,1081,9.7,Cognitive Computing -AI01586,Deep Learning Engineer,84808,EUR,72087,MI,FT,Austria,M,Austria,100,"Git, Linux, Hadoop, GCP, Python",PhD,4,Telecommunications,2024-04-25,2024-05-18,764,5.7,TechCorp Inc -AI01587,AI Software Engineer,141179,EUR,120002,SE,CT,Austria,M,Austria,100,"Java, Python, TensorFlow",Associate,7,Transportation,2024-04-07,2024-06-03,1342,6.3,Advanced Robotics -AI01588,Computer Vision Engineer,318090,USD,318090,EX,PT,United States,L,United States,0,"PyTorch, MLOps, Hadoop",Bachelor,14,Technology,2024-04-04,2024-04-23,1247,6,DeepTech Ventures -AI01589,Data Analyst,130980,EUR,111333,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, R, Linux",PhD,3,Healthcare,2024-07-04,2024-09-04,1109,10,DataVision Ltd -AI01590,Robotics Engineer,134292,USD,134292,EX,FT,Israel,S,Israel,0,"NLP, Git, Tableau, GCP",Bachelor,13,Government,2024-11-14,2025-01-17,696,8.4,Cognitive Computing -AI01591,AI Architect,137679,AUD,185867,EX,PT,Australia,M,Australia,50,"R, Linux, Python, Deep Learning",Associate,11,Gaming,2024-09-19,2024-10-31,1964,8.3,Autonomous Tech -AI01592,AI Product Manager,179453,EUR,152535,EX,FT,France,M,France,0,"SQL, Tableau, Azure, Kubernetes, Python",Bachelor,12,Technology,2024-02-27,2024-04-12,996,8.9,Digital Transformation LLC -AI01593,ML Ops Engineer,118618,USD,118618,SE,FL,Ireland,M,Ireland,50,"Python, Java, Git, Hadoop, Statistics",Associate,8,Healthcare,2025-03-29,2025-05-21,1265,7.8,Advanced Robotics -AI01594,Data Analyst,154250,USD,154250,SE,PT,Finland,L,Finland,0,"AWS, Mathematics, PyTorch, TensorFlow",Associate,7,Education,2024-11-15,2024-12-14,2495,9,DataVision Ltd -AI01595,Machine Learning Researcher,63563,USD,63563,MI,FT,South Korea,M,Romania,50,"Java, Data Visualization, SQL, MLOps, Python",PhD,4,Manufacturing,2025-03-13,2025-04-22,1537,5.7,Predictive Systems -AI01596,Head of AI,199854,GBP,149891,EX,FT,United Kingdom,S,United Kingdom,100,"NLP, Hadoop, Kubernetes, Docker",Master,18,Consulting,2024-10-21,2024-12-22,660,5.3,Smart Analytics -AI01597,ML Ops Engineer,123361,EUR,104857,SE,FL,Germany,L,Germany,0,"NLP, Spark, Hadoop, Python",Master,6,Media,2024-09-27,2024-10-14,1538,8.9,TechCorp Inc -AI01598,AI Consultant,103643,USD,103643,SE,CT,Finland,S,Portugal,0,"Linux, Azure, Python",Master,6,Manufacturing,2024-12-11,2025-02-19,858,8.8,Cognitive Computing -AI01599,Data Scientist,61632,USD,61632,MI,CT,South Korea,M,United Kingdom,0,"R, Git, Scala",Bachelor,4,Real Estate,2024-01-06,2024-02-16,607,6.5,DataVision Ltd -AI01600,Data Engineer,64782,USD,64782,EN,CT,South Korea,M,South Korea,50,"GCP, Azure, Data Visualization, Git",Master,0,Automotive,2025-02-04,2025-03-03,942,8.1,AI Innovations -AI01601,Machine Learning Engineer,160583,USD,160583,SE,FL,Norway,L,France,100,"Data Visualization, Spark, Kubernetes",Master,7,Healthcare,2024-01-24,2024-03-28,1801,8,Advanced Robotics -AI01602,NLP Engineer,259300,SGD,337090,EX,CT,Singapore,M,Singapore,100,"Spark, GCP, Azure, Python, Tableau",Master,16,Healthcare,2025-03-10,2025-05-12,1482,5.3,DeepTech Ventures -AI01603,AI Architect,99029,EUR,84175,MI,PT,Netherlands,M,Netherlands,100,"Hadoop, Azure, Python, TensorFlow, Git",Master,2,Healthcare,2024-08-18,2024-10-04,1003,9.3,Future Systems -AI01604,Principal Data Scientist,84037,USD,84037,EN,CT,Ireland,L,Ireland,100,"TensorFlow, PyTorch, SQL, Spark, Docker",Associate,1,Energy,2024-11-20,2024-12-31,1267,6.6,Smart Analytics -AI01605,Computer Vision Engineer,70093,USD,70093,MI,FT,South Korea,L,Egypt,0,"R, Azure, PyTorch",PhD,2,Consulting,2024-11-23,2025-01-06,945,9.4,Future Systems -AI01606,Head of AI,133209,EUR,113228,SE,FT,Germany,M,Malaysia,0,"Hadoop, Python, Linux, TensorFlow, Java",PhD,9,Healthcare,2025-02-14,2025-03-15,1859,6.7,Autonomous Tech -AI01607,Head of AI,116248,USD,116248,SE,FL,Sweden,M,Sweden,100,"Python, TensorFlow, PyTorch",Associate,9,Transportation,2024-08-10,2024-10-21,1971,5.7,AI Innovations -AI01608,Machine Learning Researcher,62383,CAD,77979,EN,PT,Canada,M,Canada,100,"Data Visualization, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Media,2024-06-18,2024-08-10,1148,9.2,Quantum Computing Inc -AI01609,AI Consultant,192600,CHF,173340,EX,CT,Switzerland,S,Switzerland,100,"Linux, MLOps, GCP, TensorFlow",Associate,12,Transportation,2024-06-09,2024-08-05,1620,8,Neural Networks Co -AI01610,Research Scientist,91590,CAD,114488,MI,PT,Canada,M,Canada,0,"Statistics, SQL, AWS, Mathematics, Azure",Associate,2,Telecommunications,2024-11-18,2025-01-06,770,7.2,Algorithmic Solutions -AI01611,AI Consultant,102798,USD,102798,SE,FL,South Korea,L,South Korea,50,"Spark, SQL, Statistics",Bachelor,7,Real Estate,2025-03-15,2025-04-07,1954,8.6,AI Innovations -AI01612,AI Architect,103697,EUR,88142,MI,FT,Germany,M,Germany,0,"SQL, Python, Hadoop, Computer Vision, GCP",Associate,2,Media,2024-05-18,2024-07-01,1173,9.2,Quantum Computing Inc -AI01613,Machine Learning Engineer,28499,USD,28499,MI,CT,India,S,Brazil,0,"Tableau, SQL, Scala, AWS, GCP",Master,2,Manufacturing,2024-01-26,2024-03-20,2350,8.9,DeepTech Ventures -AI01614,Research Scientist,69768,USD,69768,MI,PT,South Korea,L,Mexico,0,"Kubernetes, Docker, AWS, SQL, Python",Bachelor,3,Automotive,2024-10-03,2024-11-24,2257,7,Predictive Systems -AI01615,Research Scientist,71036,AUD,95899,MI,FT,Australia,S,Australia,100,"Azure, Scala, MLOps, Computer Vision, Data Visualization",PhD,4,Real Estate,2024-05-08,2024-06-04,1216,7.4,Advanced Robotics -AI01616,Data Scientist,121894,GBP,91421,SE,CT,United Kingdom,S,United Kingdom,50,"Linux, Python, Kubernetes, TensorFlow, Git",Master,7,Transportation,2024-04-12,2024-05-29,1233,5.3,Cognitive Computing -AI01617,AI Software Engineer,60930,EUR,51791,EN,FL,Austria,S,Austria,50,"Tableau, PyTorch, Scala, GCP",Master,0,Consulting,2024-05-14,2024-06-16,1096,9.8,TechCorp Inc -AI01618,Principal Data Scientist,124442,USD,124442,SE,CT,Finland,M,Finland,0,"Computer Vision, Docker, SQL, Mathematics, Hadoop",PhD,7,Consulting,2025-04-02,2025-06-08,970,8.2,Advanced Robotics -AI01619,Computer Vision Engineer,88420,USD,88420,MI,CT,Sweden,L,Sweden,50,"Git, Hadoop, Java",Bachelor,2,Manufacturing,2024-08-11,2024-09-04,2056,5.9,Future Systems -AI01620,AI Consultant,84817,USD,84817,EN,CT,Ireland,L,Ireland,100,"Python, GCP, SQL",Bachelor,0,Telecommunications,2024-12-12,2025-02-01,1659,5.3,Smart Analytics -AI01621,AI Consultant,155811,SGD,202554,SE,CT,Singapore,M,Singapore,0,"Tableau, Git, SQL, Statistics",Master,6,Education,2024-10-09,2024-12-10,1916,5.3,TechCorp Inc -AI01622,AI Product Manager,95395,USD,95395,MI,PT,Israel,M,Japan,0,"TensorFlow, Deep Learning, Python, Computer Vision, PyTorch",Master,3,Media,2024-11-14,2025-01-12,908,8.2,DataVision Ltd -AI01623,NLP Engineer,82987,EUR,70539,MI,FT,Germany,S,Germany,0,"Python, NLP, AWS, Computer Vision, R",Bachelor,2,Real Estate,2024-10-30,2024-11-24,2035,5.8,Cloud AI Solutions -AI01624,Data Scientist,161403,USD,161403,EX,FL,Finland,M,Finland,50,"SQL, Statistics, PyTorch, Deep Learning",PhD,15,Finance,2024-05-16,2024-07-15,1635,9.8,DataVision Ltd -AI01625,Robotics Engineer,151191,USD,151191,SE,FT,Denmark,S,Denmark,0,"NLP, Tableau, Scala, GCP",PhD,8,Energy,2025-04-01,2025-04-24,890,6.7,Digital Transformation LLC -AI01626,Machine Learning Researcher,92075,EUR,78264,SE,CT,France,S,France,100,"GCP, Java, R",Bachelor,6,Government,2024-11-02,2024-12-05,2261,7.7,Cloud AI Solutions -AI01627,Autonomous Systems Engineer,43996,USD,43996,MI,FL,China,S,China,100,"Python, Azure, TensorFlow, Hadoop",Master,2,Manufacturing,2024-02-22,2024-03-16,2422,7.2,DataVision Ltd -AI01628,AI Research Scientist,25803,USD,25803,EN,PT,India,M,India,50,"Kubernetes, MLOps, Azure, Linux, Computer Vision",Master,0,Technology,2024-12-30,2025-03-04,1599,7.1,DataVision Ltd -AI01629,Machine Learning Engineer,99682,USD,99682,EN,FL,United States,L,Ukraine,0,"SQL, Scala, Git",Associate,0,Technology,2025-03-12,2025-04-19,2193,5.3,AI Innovations -AI01630,Autonomous Systems Engineer,108655,USD,108655,EX,PT,China,L,China,0,"PyTorch, Mathematics, Spark, Java, Hadoop",Associate,17,Gaming,2024-05-11,2024-06-25,1410,7.9,Algorithmic Solutions -AI01631,Machine Learning Researcher,79605,AUD,107467,MI,PT,Australia,M,Australia,50,"GCP, Tableau, Data Visualization, MLOps, Python",Master,3,Real Estate,2024-05-29,2024-07-25,789,7,DeepTech Ventures -AI01632,AI Specialist,68143,EUR,57922,EN,PT,Netherlands,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2024-01-25,2024-02-23,1355,5.5,Future Systems -AI01633,ML Ops Engineer,177618,SGD,230903,EX,PT,Singapore,S,Singapore,0,"Hadoop, SQL, NLP",Bachelor,18,Energy,2024-02-08,2024-03-19,957,8.1,Neural Networks Co -AI01634,Robotics Engineer,220052,CAD,275065,EX,CT,Canada,L,Ghana,50,"Hadoop, Scala, Tableau",Master,17,Media,2025-01-02,2025-01-26,1422,9.1,DeepTech Ventures -AI01635,AI Software Engineer,83629,GBP,62722,MI,PT,United Kingdom,M,Denmark,100,"Python, Tableau, Deep Learning, Data Visualization, Hadoop",PhD,2,Gaming,2024-04-12,2024-05-24,2018,6.2,Autonomous Tech -AI01636,AI Software Engineer,162381,EUR,138024,SE,FT,Netherlands,L,Netherlands,0,"Scala, Python, GCP",Bachelor,6,Gaming,2024-09-19,2024-11-27,1315,5.4,DataVision Ltd -AI01637,Machine Learning Researcher,124109,USD,124109,SE,FT,Sweden,M,Sweden,0,"Python, Hadoop, Git, GCP",Bachelor,8,Transportation,2024-01-31,2024-03-22,1835,5.9,Predictive Systems -AI01638,AI Product Manager,59192,AUD,79909,EN,CT,Australia,M,Indonesia,0,"Linux, TensorFlow, PyTorch, Java, AWS",Associate,1,Media,2024-03-28,2024-04-15,1675,6.3,Smart Analytics -AI01639,AI Research Scientist,49329,USD,49329,SE,PT,India,M,India,0,"Hadoop, Tableau, Kubernetes, PyTorch, Computer Vision",Associate,7,Energy,2025-01-25,2025-03-17,1500,5.9,DataVision Ltd -AI01640,Autonomous Systems Engineer,76915,USD,76915,EX,FT,India,M,India,100,"Statistics, Python, TensorFlow, GCP",Associate,13,Government,2024-10-14,2024-12-13,1541,5.4,Quantum Computing Inc -AI01641,AI Product Manager,101027,USD,101027,EX,FT,China,M,China,100,"Java, Deep Learning, Python",Master,11,Media,2024-01-28,2024-03-06,882,8.8,Predictive Systems -AI01642,Machine Learning Engineer,238301,USD,238301,EX,FT,Norway,S,Norway,100,"Linux, SQL, PyTorch, AWS, Hadoop",PhD,13,Transportation,2024-10-08,2024-11-25,2043,5.7,Quantum Computing Inc -AI01643,Data Scientist,143521,USD,143521,SE,PT,Ireland,L,Luxembourg,50,"SQL, Docker, Azure, MLOps",Associate,5,Retail,2024-04-26,2024-05-23,2414,8.2,Neural Networks Co -AI01644,AI Research Scientist,139551,JPY,15350610,SE,FL,Japan,L,Luxembourg,100,"MLOps, TensorFlow, SQL, Linux",Bachelor,7,Education,2025-01-18,2025-03-10,1243,7,AI Innovations -AI01645,Autonomous Systems Engineer,85768,EUR,72903,EN,FL,Austria,L,Austria,50,"Hadoop, Statistics, NLP, Python",Master,1,Manufacturing,2025-04-09,2025-06-11,1439,9,Cloud AI Solutions -AI01646,Data Engineer,252548,USD,252548,EX,FL,United States,L,United States,50,"Kubernetes, Python, AWS, GCP",PhD,13,Consulting,2024-09-12,2024-10-12,2479,6.3,DeepTech Ventures -AI01647,AI Architect,116048,EUR,98641,MI,CT,Austria,L,Austria,0,"SQL, Azure, Computer Vision, Statistics",Bachelor,4,Government,2024-06-11,2024-07-18,526,9.6,Machine Intelligence Group -AI01648,Head of AI,29834,USD,29834,EN,PT,China,L,China,0,"SQL, Docker, NLP",Bachelor,0,Gaming,2024-05-01,2024-05-22,1564,9,DataVision Ltd -AI01649,Machine Learning Engineer,120609,CAD,150761,SE,FT,Canada,S,Canada,0,"Spark, PyTorch, Statistics",Bachelor,5,Energy,2024-06-11,2024-08-09,844,6.4,Algorithmic Solutions -AI01650,Robotics Engineer,79431,EUR,67516,MI,PT,Austria,L,Austria,0,"R, Hadoop, Azure, Java, Docker",Master,2,Real Estate,2024-04-04,2024-05-09,1677,5.6,Algorithmic Solutions -AI01651,Research Scientist,194187,CAD,242734,EX,CT,Canada,S,Canada,100,"Python, Computer Vision, Spark",Master,14,Telecommunications,2024-12-14,2024-12-29,2369,8.9,Machine Intelligence Group -AI01652,Principal Data Scientist,177785,USD,177785,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Python, Scala, Linux",Master,7,Energy,2024-05-16,2024-06-17,1684,9.6,AI Innovations -AI01653,Computer Vision Engineer,231560,USD,231560,EX,CT,Israel,L,Israel,100,"Spark, Git, SQL, TensorFlow, Azure",Associate,14,Media,2024-01-04,2024-02-03,881,7.6,Smart Analytics -AI01654,AI Software Engineer,114280,CHF,102852,MI,FT,Switzerland,M,Switzerland,0,"Statistics, Kubernetes, Tableau, Docker, Scala",PhD,4,Healthcare,2024-08-31,2024-10-05,695,6.9,Predictive Systems -AI01655,Deep Learning Engineer,75014,EUR,63762,EN,PT,Netherlands,S,Indonesia,100,"Python, Tableau, Azure",Bachelor,1,Finance,2024-11-23,2025-01-21,1349,7.1,TechCorp Inc -AI01656,Data Engineer,32244,USD,32244,EN,CT,India,L,India,100,"SQL, Docker, GCP, Computer Vision",Associate,0,Automotive,2024-05-23,2024-07-29,915,6.3,Cognitive Computing -AI01657,Data Engineer,130809,USD,130809,SE,CT,Sweden,L,Sweden,100,"Python, Git, Kubernetes, GCP",PhD,9,Real Estate,2025-04-30,2025-06-29,696,8.1,Advanced Robotics -AI01658,Data Scientist,194628,CAD,243285,EX,CT,Canada,M,Canada,0,"Git, SQL, Data Visualization, PyTorch, Azure",Associate,19,Real Estate,2024-03-03,2024-04-07,1807,8.9,Digital Transformation LLC -AI01659,Deep Learning Engineer,31750,USD,31750,EN,FL,China,M,Italy,100,"PyTorch, SQL, AWS",Bachelor,1,Energy,2024-11-23,2024-12-27,1036,5.4,Predictive Systems -AI01660,Autonomous Systems Engineer,72863,USD,72863,MI,CT,Israel,S,Netherlands,0,"Git, MLOps, Java, Mathematics",Bachelor,2,Healthcare,2024-04-12,2024-06-02,2466,5.9,Smart Analytics -AI01661,AI Architect,158698,EUR,134893,EX,CT,France,M,France,100,"SQL, Kubernetes, R",Bachelor,11,Manufacturing,2025-04-19,2025-06-10,1473,5.6,Neural Networks Co -AI01662,AI Consultant,70435,USD,70435,EN,CT,United States,L,Germany,0,"Computer Vision, Azure, MLOps, NLP, Git",PhD,0,Real Estate,2024-02-10,2024-04-19,1111,8.5,Smart Analytics -AI01663,Robotics Engineer,70871,USD,70871,MI,FT,Israel,M,Israel,100,"Computer Vision, Kubernetes, Git, PyTorch",Bachelor,2,Consulting,2024-10-18,2024-11-07,2450,7.5,Cloud AI Solutions -AI01664,AI Research Scientist,69256,USD,69256,EN,FT,Finland,L,Hungary,50,"Docker, Tableau, Kubernetes",Master,0,Retail,2025-01-01,2025-03-07,1772,8.3,Cloud AI Solutions -AI01665,Computer Vision Engineer,172569,EUR,146684,EX,CT,Germany,M,Germany,100,"Kubernetes, Spark, PyTorch, GCP",Bachelor,14,Consulting,2025-01-08,2025-02-02,2081,6,Predictive Systems -AI01666,Data Engineer,105421,USD,105421,MI,PT,Ireland,M,Netherlands,50,"R, SQL, Statistics, Java, Data Visualization",Master,4,Manufacturing,2024-10-18,2024-12-20,1129,5,Advanced Robotics -AI01667,Research Scientist,280936,USD,280936,EX,PT,Ireland,L,Ireland,0,"Spark, Python, TensorFlow, SQL, Linux",Bachelor,13,Finance,2024-01-27,2024-03-16,2149,7.9,AI Innovations -AI01668,AI Research Scientist,244804,USD,244804,EX,FT,Denmark,S,Denmark,100,"Azure, Computer Vision, TensorFlow, Python, GCP",PhD,12,Real Estate,2025-01-24,2025-03-17,2021,9.3,Advanced Robotics -AI01669,AI Architect,116583,USD,116583,MI,PT,United States,S,Colombia,100,"SQL, Computer Vision, Kubernetes, AWS, R",Bachelor,2,Transportation,2024-01-17,2024-01-31,2075,9.1,Digital Transformation LLC -AI01670,Computer Vision Engineer,44363,USD,44363,SE,CT,India,M,India,50,"Hadoop, Tableau, R, MLOps, AWS",PhD,9,Government,2024-10-25,2024-12-03,1663,6.6,Algorithmic Solutions -AI01671,Robotics Engineer,103234,GBP,77426,MI,FT,United Kingdom,S,Nigeria,50,"GCP, MLOps, Scala",Associate,4,Media,2024-06-25,2024-08-29,1363,8.2,Machine Intelligence Group -AI01672,AI Research Scientist,241862,USD,241862,EX,FL,Norway,M,France,0,"Scala, PyTorch, Docker, Mathematics, SQL",Master,17,Retail,2025-02-21,2025-04-22,1897,5.9,Machine Intelligence Group -AI01673,Data Scientist,61352,USD,61352,EX,PT,India,L,Argentina,100,"Python, SQL, MLOps",Master,19,Consulting,2025-01-31,2025-04-11,901,9.7,DataVision Ltd -AI01674,Principal Data Scientist,247449,USD,247449,EX,FT,Ireland,M,Ireland,50,"SQL, Mathematics, AWS, Linux, R",Bachelor,16,Manufacturing,2025-04-11,2025-05-19,1591,6.1,Smart Analytics -AI01675,NLP Engineer,91517,USD,91517,MI,CT,Denmark,S,Denmark,100,"Linux, PyTorch, Tableau",Bachelor,4,Energy,2025-01-05,2025-01-24,1982,6.5,Predictive Systems -AI01676,Deep Learning Engineer,231797,EUR,197027,EX,PT,Netherlands,L,Israel,100,"SQL, Java, Deep Learning, MLOps",Bachelor,13,Retail,2024-11-02,2024-11-18,1062,7.4,Cloud AI Solutions -AI01677,AI Software Engineer,29053,USD,29053,EN,FT,China,L,China,100,"Scala, GCP, NLP, PyTorch",Associate,1,Finance,2024-05-17,2024-06-15,503,5.3,Smart Analytics -AI01678,Data Scientist,38480,USD,38480,MI,FT,India,L,India,50,"Scala, Spark, PyTorch, AWS",Bachelor,2,Consulting,2025-03-25,2025-05-06,2254,5.6,Autonomous Tech -AI01679,Data Scientist,49357,USD,49357,EN,FT,Finland,S,Finland,0,"Java, Mathematics, Tableau, NLP, Deep Learning",Bachelor,1,Transportation,2024-07-02,2024-07-31,2422,5.9,DeepTech Ventures -AI01680,Data Analyst,100391,CAD,125489,SE,FT,Canada,M,Nigeria,50,"Hadoop, Linux, SQL",Bachelor,9,Government,2024-10-05,2024-12-02,1941,5.7,Algorithmic Solutions -AI01681,ML Ops Engineer,72840,CHF,65556,EN,FL,Switzerland,S,Switzerland,50,"Python, Git, Java, Docker",Associate,0,Gaming,2024-02-28,2024-03-19,2048,5,Autonomous Tech -AI01682,Data Scientist,265397,EUR,225587,EX,FL,Germany,L,Germany,100,"Scala, AWS, NLP, Statistics",Master,16,Retail,2024-07-24,2024-08-21,1192,5.9,Predictive Systems -AI01683,NLP Engineer,92492,AUD,124864,EN,FL,Australia,L,Australia,100,"Tableau, SQL, Git, Python",PhD,0,Consulting,2024-05-26,2024-07-24,1700,9.4,TechCorp Inc -AI01684,AI Specialist,110408,USD,110408,SE,CT,Sweden,S,Sweden,0,"Python, Linux, R, Computer Vision",Associate,7,Technology,2024-09-25,2024-12-01,2267,10,Quantum Computing Inc -AI01685,NLP Engineer,139699,EUR,118744,EX,FT,Germany,M,Ireland,50,"Azure, Deep Learning, Scala, Mathematics",Associate,19,Finance,2024-07-25,2024-08-31,582,9.1,Advanced Robotics -AI01686,ML Ops Engineer,80747,EUR,68635,MI,CT,Netherlands,S,Netherlands,50,"NLP, Data Visualization, Python, TensorFlow, Linux",Master,3,Telecommunications,2024-02-22,2024-03-09,1345,7.1,Cognitive Computing -AI01687,Data Scientist,86520,EUR,73542,MI,FL,Austria,S,Nigeria,100,"Python, Git, TensorFlow",Bachelor,4,Finance,2024-07-08,2024-09-05,1578,6.4,Machine Intelligence Group -AI01688,AI Specialist,55997,USD,55997,EX,CT,India,M,Israel,50,"NLP, Azure, Python",PhD,12,Manufacturing,2025-03-25,2025-05-28,1550,5.4,AI Innovations -AI01689,AI Software Engineer,107119,SGD,139255,MI,PT,Singapore,M,Singapore,100,"Kubernetes, MLOps, Java, TensorFlow",Bachelor,3,Transportation,2024-04-22,2024-06-21,2417,5.3,Advanced Robotics -AI01690,Research Scientist,117336,EUR,99736,SE,FT,Austria,S,Malaysia,0,"NLP, Scala, Python",Bachelor,9,Consulting,2024-08-23,2024-09-10,1052,6.3,DeepTech Ventures -AI01691,Head of AI,164003,EUR,139403,EX,PT,Austria,S,Vietnam,0,"NLP, Java, PyTorch, GCP",PhD,16,Education,2024-03-09,2024-03-25,645,6,TechCorp Inc -AI01692,Computer Vision Engineer,109093,USD,109093,MI,FL,Ireland,L,Ireland,50,"Statistics, Azure, Scala, GCP, NLP",Master,4,Manufacturing,2025-04-26,2025-06-12,2262,8.6,AI Innovations -AI01693,Machine Learning Researcher,60847,USD,60847,EN,FL,Ireland,M,Ireland,50,"Azure, Mathematics, Python",Associate,0,Manufacturing,2024-12-19,2025-02-26,1775,7.8,DeepTech Ventures -AI01694,AI Product Manager,64394,USD,64394,MI,FT,South Korea,S,South Africa,0,"Azure, Deep Learning, GCP, Spark, R",Bachelor,4,Gaming,2024-01-24,2024-02-20,1682,9.2,Digital Transformation LLC -AI01695,Principal Data Scientist,56336,USD,56336,EN,FT,Sweden,M,Sweden,100,"Python, MLOps, Git",Bachelor,1,Transportation,2024-12-15,2025-01-23,1402,9.9,Predictive Systems -AI01696,AI Consultant,151360,JPY,16649600,EX,PT,Japan,M,Japan,50,"Scala, Kubernetes, Computer Vision, NLP, Git",PhD,11,Transportation,2024-05-26,2024-07-29,2089,5.4,Digital Transformation LLC -AI01697,Head of AI,108867,EUR,92537,SE,FL,Netherlands,M,Netherlands,50,"Mathematics, Java, Spark",PhD,7,Automotive,2024-07-15,2024-09-15,1367,6.6,Cognitive Computing -AI01698,AI Consultant,163581,EUR,139044,SE,CT,Germany,L,Germany,50,"GCP, Computer Vision, Hadoop",PhD,8,Automotive,2024-10-15,2024-12-01,1213,8.5,Machine Intelligence Group -AI01699,AI Product Manager,111866,JPY,12305260,MI,FT,Japan,M,Japan,0,"Java, Kubernetes, SQL, Mathematics",Bachelor,2,Media,2024-11-04,2024-12-30,1683,9.3,Cloud AI Solutions -AI01700,NLP Engineer,56511,USD,56511,EN,CT,South Korea,L,Israel,50,"Kubernetes, Java, Deep Learning, Mathematics, Computer Vision",PhD,0,Media,2024-10-29,2024-11-30,2130,7.1,Future Systems -AI01701,NLP Engineer,40401,USD,40401,MI,CT,China,L,China,100,"TensorFlow, SQL, Mathematics, Linux",PhD,4,Healthcare,2024-05-11,2024-06-10,2122,9.1,TechCorp Inc -AI01702,Research Scientist,130250,CHF,117225,MI,FL,Switzerland,L,Hungary,0,"Data Visualization, GCP, Scala, Docker",PhD,2,Media,2024-03-30,2024-05-22,2139,5,Algorithmic Solutions -AI01703,Computer Vision Engineer,41173,USD,41173,MI,CT,China,S,Austria,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2025-04-29,2025-06-23,1174,6.2,Smart Analytics -AI01704,Data Engineer,69187,USD,69187,EN,FL,United States,S,United States,50,"Kubernetes, Spark, Java",Associate,0,Media,2024-01-31,2024-04-04,1954,9.2,Quantum Computing Inc -AI01705,NLP Engineer,80973,USD,80973,EX,FT,India,S,Australia,100,"Linux, Python, Tableau, Kubernetes, SQL",Associate,11,Energy,2024-04-07,2024-05-31,1601,7.7,Quantum Computing Inc -AI01706,AI Software Engineer,117099,USD,117099,SE,PT,Ireland,M,Ireland,50,"Spark, Java, Computer Vision, Tableau",Bachelor,7,Real Estate,2024-10-03,2024-10-20,672,6.3,DeepTech Ventures -AI01707,AI Architect,62738,USD,62738,EN,FL,Finland,S,Canada,0,"Git, SQL, GCP",Associate,1,Consulting,2024-02-06,2024-03-01,1244,9.7,Neural Networks Co -AI01708,AI Product Manager,120017,EUR,102014,MI,FT,Germany,L,Germany,100,"Java, Kubernetes, Deep Learning",Bachelor,4,Education,2025-02-03,2025-03-17,588,8.6,Digital Transformation LLC -AI01709,AI Architect,146456,USD,146456,MI,FL,United States,L,United States,0,"SQL, Spark, Linux",PhD,2,Real Estate,2024-08-20,2024-10-17,1112,5.3,Autonomous Tech -AI01710,Data Engineer,116585,AUD,157390,SE,FL,Australia,M,Australia,0,"Mathematics, Computer Vision, Linux, Kubernetes",Master,8,Energy,2024-02-26,2024-04-21,1405,8.2,DeepTech Ventures -AI01711,AI Architect,48908,EUR,41572,EN,FT,France,M,France,100,"Spark, TensorFlow, Python, NLP, Statistics",Master,1,Healthcare,2024-12-28,2025-03-06,739,7.1,Machine Intelligence Group -AI01712,Head of AI,140368,USD,140368,MI,FT,Norway,M,Norway,0,"Java, Linux, Statistics, GCP",Master,2,Manufacturing,2024-06-25,2024-08-09,1177,8.6,Future Systems -AI01713,Deep Learning Engineer,117338,JPY,12907180,MI,FL,Japan,L,Brazil,100,"PyTorch, SQL, Hadoop, Deep Learning, Kubernetes",Associate,3,Manufacturing,2024-12-07,2025-01-22,1586,6.8,Quantum Computing Inc -AI01714,Head of AI,25199,USD,25199,EN,PT,China,M,Germany,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Media,2024-04-18,2024-06-22,849,9.8,Machine Intelligence Group -AI01715,AI Architect,101321,EUR,86123,MI,FT,France,M,France,50,"Python, Statistics, Tableau",PhD,3,Gaming,2025-03-24,2025-04-20,2449,7.7,Predictive Systems -AI01716,Machine Learning Engineer,86336,USD,86336,MI,FT,Ireland,S,Ghana,0,"Deep Learning, SQL, Data Visualization, PyTorch",Master,4,Retail,2025-03-09,2025-05-21,1028,8.6,TechCorp Inc -AI01717,Machine Learning Researcher,104654,JPY,11511940,MI,FL,Japan,L,Japan,100,"Azure, Deep Learning, R",Master,2,Energy,2024-02-24,2024-04-20,739,8.1,Cognitive Computing -AI01718,AI Specialist,93107,USD,93107,MI,FT,Ireland,L,Mexico,0,"PyTorch, GCP, Tableau",Associate,3,Gaming,2024-03-18,2024-04-05,2334,9.5,Smart Analytics -AI01719,AI Consultant,113304,USD,113304,MI,CT,Norway,S,Norway,0,"SQL, Azure, PyTorch",Bachelor,3,Healthcare,2024-04-24,2024-05-19,517,6.1,Algorithmic Solutions -AI01720,Deep Learning Engineer,159382,USD,159382,EX,CT,Ireland,M,Ireland,100,"Java, Python, Computer Vision, R",Master,12,Transportation,2024-07-03,2024-07-18,617,8.7,Future Systems -AI01721,AI Specialist,112099,USD,112099,SE,FL,South Korea,M,South Korea,50,"Azure, Python, Computer Vision",Bachelor,9,Media,2024-07-03,2024-07-17,1317,8,Advanced Robotics -AI01722,Head of AI,106493,USD,106493,MI,PT,Norway,M,Norway,0,"Linux, Scala, PyTorch, MLOps, Tableau",Master,4,Real Estate,2025-03-27,2025-05-18,1839,7.1,AI Innovations -AI01723,AI Architect,76693,SGD,99701,EN,FT,Singapore,M,Singapore,100,"Mathematics, Statistics, PyTorch",PhD,1,Real Estate,2025-04-14,2025-05-02,740,8.4,Neural Networks Co -AI01724,NLP Engineer,145475,USD,145475,SE,CT,Finland,L,Latvia,100,"Spark, Java, Deep Learning, AWS",Associate,9,Energy,2025-02-11,2025-03-14,1076,8.5,DataVision Ltd -AI01725,Data Analyst,79166,GBP,59375,EN,FT,United Kingdom,L,United Kingdom,50,"Scala, Kubernetes, MLOps, Azure, AWS",PhD,0,Finance,2024-09-24,2024-10-08,1643,9.6,DeepTech Ventures -AI01726,AI Architect,187864,USD,187864,EX,FL,Sweden,M,Sweden,0,"Git, PyTorch, SQL, Scala",Associate,16,Gaming,2024-12-06,2025-01-07,921,6.1,Future Systems -AI01727,AI Consultant,50080,USD,50080,EN,CT,Israel,S,Israel,100,"Deep Learning, Python, Mathematics",Bachelor,1,Technology,2025-01-27,2025-04-06,2110,6.6,Autonomous Tech -AI01728,Autonomous Systems Engineer,103470,JPY,11381700,MI,CT,Japan,L,Japan,100,"Computer Vision, R, Kubernetes, Tableau",Master,2,Technology,2024-11-14,2024-12-09,1694,6.9,Predictive Systems -AI01729,Machine Learning Engineer,84323,USD,84323,MI,FT,Sweden,M,Sweden,50,"Kubernetes, Git, Statistics",Bachelor,3,Real Estate,2024-11-25,2025-01-08,1134,8,DeepTech Ventures -AI01730,Robotics Engineer,71020,CAD,88775,MI,PT,Canada,S,Czech Republic,100,"Java, Tableau, PyTorch, NLP, SQL",Bachelor,3,Manufacturing,2024-02-21,2024-04-23,1253,9.7,Future Systems -AI01731,NLP Engineer,74489,USD,74489,EX,FL,China,M,Austria,50,"Linux, Docker, SQL",PhD,11,Healthcare,2024-06-03,2024-07-24,1437,9.7,TechCorp Inc -AI01732,AI Product Manager,55564,AUD,75011,EN,FT,Australia,M,Australia,50,"SQL, PyTorch, Git, Azure, AWS",Bachelor,0,Transportation,2025-03-22,2025-06-02,2036,6.3,Predictive Systems -AI01733,AI Consultant,84737,USD,84737,EN,CT,United States,S,United States,0,"Spark, Data Visualization, Computer Vision",Bachelor,1,Telecommunications,2025-01-06,2025-02-02,1139,6.8,DeepTech Ventures -AI01734,AI Software Engineer,125029,EUR,106275,SE,FL,France,M,France,50,"SQL, Azure, Java, Spark, AWS",Master,5,Healthcare,2025-01-19,2025-03-23,1740,5.6,DataVision Ltd -AI01735,Robotics Engineer,93053,EUR,79095,MI,FL,France,S,France,0,"Spark, R, Data Visualization",PhD,3,Education,2025-01-06,2025-02-15,629,5.1,DeepTech Ventures -AI01736,AI Architect,116161,USD,116161,MI,FT,United States,S,United States,50,"SQL, PyTorch, GCP, Linux",PhD,2,Technology,2025-01-07,2025-02-22,1201,7.2,Predictive Systems -AI01737,AI Software Engineer,96819,USD,96819,MI,FT,United States,S,United States,0,"Spark, Python, Tableau, Kubernetes",PhD,3,Finance,2024-11-18,2025-01-12,1105,7.7,TechCorp Inc -AI01738,Computer Vision Engineer,21074,USD,21074,EN,CT,India,M,India,50,"Git, Azure, Data Visualization",Associate,0,Retail,2024-06-29,2024-07-30,1551,7.4,Algorithmic Solutions -AI01739,Data Scientist,131324,USD,131324,MI,PT,Denmark,M,Denmark,100,"Tableau, Deep Learning, GCP, Java",PhD,2,Transportation,2024-12-14,2025-02-16,2003,6,Digital Transformation LLC -AI01740,Principal Data Scientist,58660,USD,58660,EN,CT,Finland,M,Finland,50,"Hadoop, Spark, Tableau",PhD,1,Finance,2024-10-09,2024-11-22,1205,9.9,Digital Transformation LLC -AI01741,Machine Learning Engineer,132875,EUR,112944,MI,PT,Netherlands,L,Malaysia,50,"GCP, Python, Mathematics, Linux, SQL",PhD,4,Consulting,2024-08-28,2024-10-31,1392,6.1,Quantum Computing Inc -AI01742,Computer Vision Engineer,74316,USD,74316,MI,FT,South Korea,S,South Korea,50,"TensorFlow, GCP, Azure",Bachelor,3,Energy,2024-11-17,2025-01-04,1075,9.4,Advanced Robotics -AI01743,Data Engineer,65320,EUR,55522,EN,FT,France,S,France,100,"Java, Python, Git",Bachelor,1,Media,2024-04-01,2024-05-18,915,8.7,Digital Transformation LLC -AI01744,Autonomous Systems Engineer,128941,USD,128941,SE,CT,Finland,L,Finland,50,"TensorFlow, Spark, PyTorch",Master,7,Manufacturing,2025-01-26,2025-03-07,2349,7.6,Cognitive Computing -AI01745,Principal Data Scientist,42409,USD,42409,MI,CT,China,M,South Korea,100,"PyTorch, TensorFlow, NLP",Bachelor,2,Media,2024-04-16,2024-05-09,2188,9.6,Algorithmic Solutions -AI01746,NLP Engineer,76564,GBP,57423,EN,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, Azure, Scala",PhD,0,Government,2024-03-03,2024-04-13,1639,9.4,Neural Networks Co -AI01747,NLP Engineer,289808,EUR,246337,EX,FT,Netherlands,L,Luxembourg,100,"Statistics, TensorFlow, PyTorch, Data Visualization, Hadoop",PhD,17,Automotive,2025-03-17,2025-04-28,2224,6.3,Neural Networks Co -AI01748,Data Analyst,62042,CAD,77553,EN,FL,Canada,M,Kenya,50,"Python, Azure, Tableau",Bachelor,1,Government,2024-02-15,2024-03-21,1611,6.1,TechCorp Inc -AI01749,AI Product Manager,98976,EUR,84130,MI,FT,Netherlands,M,Netherlands,100,"Statistics, Python, Mathematics, Linux, Hadoop",PhD,4,Manufacturing,2024-11-08,2024-12-24,2377,6.9,Autonomous Tech -AI01750,AI Architect,122469,USD,122469,EX,FL,South Korea,M,South Korea,50,"Linux, Scala, Java, Deep Learning, Spark",Bachelor,19,Education,2024-09-05,2024-10-17,1048,7.1,Future Systems -AI01751,NLP Engineer,187847,USD,187847,EX,FT,Ireland,M,Ireland,50,"PyTorch, TensorFlow, SQL, R",PhD,16,Transportation,2024-01-27,2024-02-16,2318,10,DeepTech Ventures -AI01752,AI Consultant,157782,JPY,17356020,EX,FT,Japan,S,Japan,0,"Spark, NLP, GCP",Master,13,Transportation,2024-11-25,2025-01-06,670,9.1,Cognitive Computing -AI01753,Research Scientist,128659,USD,128659,MI,FL,Denmark,S,Mexico,50,"Python, Linux, Scala, TensorFlow",Bachelor,2,Gaming,2024-03-04,2024-05-03,1580,5.7,Algorithmic Solutions -AI01754,AI Architect,61499,USD,61499,EN,FL,Finland,M,Ukraine,100,"Scala, Data Visualization, SQL, Tableau, MLOps",PhD,0,Government,2024-08-12,2024-10-13,1241,6.6,Neural Networks Co -AI01755,Deep Learning Engineer,66190,USD,66190,EN,FL,Ireland,L,Ireland,50,"Computer Vision, Git, Tableau, Linux, Python",PhD,1,Telecommunications,2024-10-18,2024-11-22,642,9.5,Digital Transformation LLC -AI01756,Machine Learning Engineer,29153,USD,29153,EN,FL,China,M,China,0,"Hadoop, Linux, Deep Learning, Mathematics, Git",PhD,0,Media,2024-01-16,2024-02-14,1718,9.1,Predictive Systems -AI01757,Deep Learning Engineer,64431,JPY,7087410,EN,FT,Japan,S,Japan,0,"Java, Tableau, MLOps",Master,1,Gaming,2024-03-06,2024-04-13,1972,9.2,Machine Intelligence Group -AI01758,Data Analyst,330366,USD,330366,EX,FL,Denmark,L,Denmark,0,"NLP, SQL, Tableau, Docker",Bachelor,17,Gaming,2024-03-14,2024-04-20,736,7.9,DataVision Ltd -AI01759,Machine Learning Engineer,128575,USD,128575,MI,PT,United States,M,United States,0,"Linux, Kubernetes, Spark",Bachelor,3,Automotive,2025-04-26,2025-05-21,518,9.4,Cloud AI Solutions -AI01760,AI Software Engineer,150066,GBP,112550,SE,PT,United Kingdom,M,United Kingdom,100,"Java, NLP, AWS, R, SQL",Associate,9,Media,2024-04-28,2024-07-10,1608,9.3,Predictive Systems -AI01761,Data Engineer,147214,SGD,191378,SE,CT,Singapore,L,Singapore,0,"Azure, Tableau, Scala, NLP, SQL",Associate,6,Gaming,2024-06-12,2024-07-31,1222,7.4,Cognitive Computing -AI01762,Computer Vision Engineer,35538,USD,35538,EN,FT,China,M,New Zealand,100,"AWS, Git, PyTorch, Java",Bachelor,0,Consulting,2024-11-03,2024-11-17,1062,9.5,DeepTech Ventures -AI01763,ML Ops Engineer,131200,EUR,111520,SE,FL,Germany,S,Germany,100,"GCP, Scala, NLP, Computer Vision, AWS",PhD,7,Government,2024-10-23,2024-12-30,1286,6.9,DeepTech Ventures -AI01764,Computer Vision Engineer,65465,USD,65465,EN,FT,South Korea,M,Switzerland,100,"Java, Linux, Scala",Associate,1,Consulting,2024-08-08,2024-09-29,728,8.9,TechCorp Inc -AI01765,AI Software Engineer,239103,GBP,179327,EX,CT,United Kingdom,M,United Kingdom,50,"R, Python, TensorFlow, Computer Vision",Associate,12,Automotive,2024-07-04,2024-07-25,1486,9.7,AI Innovations -AI01766,Robotics Engineer,107447,EUR,91330,SE,FL,Germany,S,France,50,"Data Visualization, Spark, R",Master,8,Technology,2024-07-13,2024-07-31,633,8.4,AI Innovations -AI01767,Machine Learning Researcher,56221,USD,56221,MI,FT,South Korea,S,South Korea,100,"PyTorch, SQL, MLOps, Data Visualization, Statistics",Master,4,Real Estate,2024-10-18,2024-12-08,575,8.1,Predictive Systems -AI01768,Deep Learning Engineer,123027,AUD,166086,MI,CT,Australia,L,Australia,0,"Linux, Kubernetes, Tableau, Java",Associate,4,Technology,2024-07-27,2024-09-03,1040,5.2,Predictive Systems -AI01769,AI Research Scientist,117390,JPY,12912900,SE,FT,Japan,S,Japan,50,"Java, SQL, Scala, Kubernetes",PhD,5,Education,2024-10-23,2024-12-21,2199,7.3,Algorithmic Solutions -AI01770,Autonomous Systems Engineer,89124,EUR,75755,MI,PT,France,L,France,100,"Kubernetes, TensorFlow, AWS, Linux, Azure",Master,4,Finance,2025-04-15,2025-05-02,1308,9.1,DataVision Ltd -AI01771,AI Product Manager,251508,EUR,213782,EX,PT,France,L,France,0,"GCP, R, Tableau, Spark",Associate,15,Finance,2024-09-05,2024-11-07,2493,9,Future Systems -AI01772,AI Software Engineer,100520,USD,100520,EX,CT,China,L,China,100,"Azure, Python, SQL",Associate,15,Media,2024-07-27,2024-09-29,1705,6.9,DeepTech Ventures -AI01773,Data Scientist,348466,CHF,313619,EX,PT,Switzerland,M,Switzerland,100,"GCP, SQL, Tableau, Data Visualization",Bachelor,13,Energy,2024-02-28,2024-04-19,1875,7.4,TechCorp Inc -AI01774,Autonomous Systems Engineer,132749,USD,132749,SE,FL,Norway,S,Latvia,0,"Linux, Computer Vision, SQL",Bachelor,5,Government,2024-03-22,2024-05-26,2272,7.5,Digital Transformation LLC -AI01775,AI Specialist,63454,USD,63454,EN,FT,Sweden,M,Colombia,50,"Azure, NLP, Deep Learning",PhD,1,Government,2024-12-30,2025-01-26,1742,5.1,Advanced Robotics -AI01776,ML Ops Engineer,102787,EUR,87369,SE,CT,Germany,M,Egypt,100,"Data Visualization, SQL, Python, Computer Vision",Bachelor,5,Transportation,2024-08-21,2024-10-01,1436,7.7,AI Innovations -AI01777,NLP Engineer,19313,USD,19313,EN,FT,India,M,Australia,50,"Python, MLOps, Linux, Deep Learning, Computer Vision",Associate,1,Finance,2024-10-07,2024-10-30,1240,9.1,DeepTech Ventures -AI01778,Machine Learning Researcher,129410,USD,129410,SE,FL,Ireland,M,Ireland,100,"Hadoop, Spark, Python, Kubernetes",Master,5,Automotive,2025-04-23,2025-07-04,1559,6.1,DataVision Ltd -AI01779,NLP Engineer,172013,JPY,18921430,EX,FT,Japan,L,Japan,0,"TensorFlow, Tableau, Azure",Master,11,Manufacturing,2025-01-13,2025-02-08,597,8.1,Machine Intelligence Group -AI01780,Autonomous Systems Engineer,158074,USD,158074,EX,CT,South Korea,S,Estonia,50,"SQL, PyTorch, Deep Learning, Tableau",PhD,14,Government,2024-03-08,2024-04-08,2054,9.4,Smart Analytics -AI01781,Data Engineer,70476,SGD,91619,MI,FL,Singapore,S,Poland,50,"AWS, Deep Learning, Python, SQL",Associate,4,Telecommunications,2024-12-20,2025-01-07,2322,6.3,TechCorp Inc -AI01782,Principal Data Scientist,90948,USD,90948,MI,CT,Israel,L,Canada,100,"Linux, GCP, Tableau, Deep Learning",Master,3,Manufacturing,2024-10-25,2024-12-10,1802,5.7,Quantum Computing Inc -AI01783,Machine Learning Researcher,238184,EUR,202456,EX,CT,Netherlands,M,Romania,50,"Python, Java, GCP, TensorFlow",Bachelor,10,Technology,2024-07-08,2024-07-25,715,6,Machine Intelligence Group -AI01784,Computer Vision Engineer,142525,USD,142525,EX,CT,Finland,M,Finland,0,"PyTorch, Kubernetes, NLP, Java",Bachelor,14,Gaming,2024-03-08,2024-04-04,647,6.7,DeepTech Ventures -AI01785,Deep Learning Engineer,210001,EUR,178501,EX,FL,Netherlands,S,Romania,50,"Python, Spark, NLP, Mathematics, Deep Learning",Bachelor,12,Consulting,2024-01-20,2024-03-21,1318,6.8,Cloud AI Solutions -AI01786,Data Analyst,124024,USD,124024,MI,FL,Denmark,L,Indonesia,0,"Spark, Python, Hadoop",Master,4,Manufacturing,2024-07-27,2024-08-24,973,6,Advanced Robotics -AI01787,AI Product Manager,269130,USD,269130,EX,PT,Denmark,M,Denmark,0,"Spark, Tableau, GCP",Associate,17,Manufacturing,2025-04-28,2025-07-10,1322,6.4,Autonomous Tech -AI01788,AI Specialist,44705,USD,44705,SE,CT,India,M,China,100,"Hadoop, Statistics, Scala, Mathematics, Kubernetes",Bachelor,8,Energy,2024-06-02,2024-07-04,1945,9.4,Digital Transformation LLC -AI01789,Data Analyst,79352,EUR,67449,EN,PT,Netherlands,M,Netherlands,100,"MLOps, Java, Python",Bachelor,0,Finance,2025-03-19,2025-05-10,2050,9.5,Cloud AI Solutions -AI01790,AI Consultant,143377,JPY,15771470,SE,FL,Japan,M,Japan,50,"TensorFlow, Computer Vision, MLOps, Data Visualization, Python",PhD,7,Real Estate,2024-01-27,2024-02-19,786,5.3,Machine Intelligence Group -AI01791,Machine Learning Engineer,40231,USD,40231,MI,FL,China,M,Malaysia,100,"Tableau, TensorFlow, Scala, Python, Mathematics",Bachelor,4,Retail,2024-01-27,2024-02-12,967,7.5,Advanced Robotics -AI01792,Robotics Engineer,79846,GBP,59885,MI,PT,United Kingdom,M,Ukraine,50,"PyTorch, Kubernetes, Computer Vision, GCP, Linux",PhD,2,Energy,2024-05-28,2024-07-03,668,5.9,Advanced Robotics -AI01793,Research Scientist,138782,USD,138782,EX,FL,Ireland,S,Malaysia,0,"Azure, Spark, R, Statistics, SQL",PhD,12,Manufacturing,2025-01-29,2025-03-13,1957,9.3,DeepTech Ventures -AI01794,ML Ops Engineer,199769,EUR,169804,EX,CT,Austria,S,Portugal,0,"AWS, Python, PyTorch",Associate,18,Transportation,2024-06-13,2024-08-19,580,7.9,Machine Intelligence Group -AI01795,AI Research Scientist,305289,USD,305289,EX,FL,Denmark,L,France,100,"Docker, MLOps, Data Visualization",Associate,17,Technology,2025-04-11,2025-06-08,1208,9.1,Algorithmic Solutions -AI01796,AI Product Manager,230691,EUR,196087,EX,FT,Austria,M,Estonia,0,"Git, Python, Linux, Kubernetes, AWS",Master,17,Consulting,2025-02-22,2025-03-10,1625,8.6,Future Systems -AI01797,AI Product Manager,238615,JPY,26247650,EX,CT,Japan,L,Austria,0,"Kubernetes, Git, Java, GCP, SQL",Bachelor,19,Manufacturing,2024-07-04,2024-08-11,1578,8.1,Neural Networks Co -AI01798,Machine Learning Engineer,98044,USD,98044,SE,FT,Sweden,S,Sweden,100,"Scala, R, TensorFlow",Associate,7,Telecommunications,2024-02-06,2024-03-31,1120,5.1,Cloud AI Solutions -AI01799,AI Research Scientist,69231,AUD,93462,MI,PT,Australia,S,Australia,100,"Scala, Java, R, Deep Learning, SQL",Associate,3,Gaming,2024-08-19,2024-10-02,2261,9.7,Machine Intelligence Group -AI01800,NLP Engineer,233794,AUD,315622,EX,FT,Australia,L,Australia,50,"Azure, Spark, SQL, Mathematics",Master,19,Transportation,2024-01-14,2024-02-18,902,6.8,Neural Networks Co -AI01801,Computer Vision Engineer,145411,EUR,123599,SE,FT,Netherlands,S,Netherlands,50,"TensorFlow, SQL, Deep Learning, R",PhD,8,Manufacturing,2025-03-20,2025-05-19,1854,6.4,Advanced Robotics -AI01802,ML Ops Engineer,119952,USD,119952,SE,FT,United States,S,Russia,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,9,Finance,2024-10-14,2024-11-06,1828,8.2,Neural Networks Co -AI01803,AI Architect,152045,USD,152045,EX,PT,United States,S,United States,50,"Mathematics, Docker, Tableau",Associate,17,Retail,2024-10-22,2024-12-23,2178,7.6,Predictive Systems -AI01804,AI Software Engineer,60657,USD,60657,SE,FT,China,L,China,0,"Java, Data Visualization, Git, Statistics",Master,8,Government,2025-02-06,2025-03-10,2006,5.1,DeepTech Ventures -AI01805,AI Specialist,157794,USD,157794,EX,PT,South Korea,L,Argentina,50,"Java, Spark, MLOps, Statistics, Python",Associate,13,Media,2025-03-04,2025-04-16,2398,8.4,DataVision Ltd -AI01806,Data Engineer,37836,USD,37836,MI,FT,India,L,Sweden,50,"GCP, Mathematics, Hadoop",Bachelor,2,Finance,2025-04-23,2025-07-05,1374,7.8,Neural Networks Co -AI01807,AI Research Scientist,68797,USD,68797,MI,FL,Israel,S,United Kingdom,100,"TensorFlow, Docker, Git, R",Bachelor,2,Manufacturing,2024-04-02,2024-05-05,2438,5.1,Autonomous Tech -AI01808,Data Scientist,144648,EUR,122951,SE,FL,France,L,France,50,"GCP, Kubernetes, Docker, Spark, Azure",Associate,6,Government,2024-04-22,2024-05-29,1741,5.8,Cloud AI Solutions -AI01809,AI Architect,88724,USD,88724,EN,FT,Ireland,L,Ireland,0,"Scala, Python, Data Visualization",Bachelor,1,Telecommunications,2024-01-26,2024-03-12,2198,9.9,Digital Transformation LLC -AI01810,Data Engineer,186244,CHF,167620,SE,PT,Switzerland,S,Switzerland,50,"Python, Scala, Computer Vision, MLOps, Linux",Master,5,Media,2025-02-14,2025-04-13,2167,5,Neural Networks Co -AI01811,Deep Learning Engineer,88469,USD,88469,SE,FL,South Korea,S,Czech Republic,0,"Spark, R, Scala, Java",Master,6,Education,2025-02-26,2025-04-02,1641,5.2,Machine Intelligence Group -AI01812,Principal Data Scientist,310111,USD,310111,EX,CT,Norway,L,Norway,0,"Statistics, Computer Vision, NLP, Linux",Bachelor,19,Retail,2024-08-08,2024-10-02,1834,6.2,AI Innovations -AI01813,AI Consultant,98560,SGD,128128,SE,CT,Singapore,S,Switzerland,100,"Statistics, MLOps, Mathematics, GCP",PhD,5,Education,2024-11-25,2024-12-09,1838,9.6,AI Innovations -AI01814,AI Specialist,159392,USD,159392,SE,FT,Norway,M,Poland,0,"Java, R, PyTorch",Bachelor,6,Media,2024-10-13,2024-11-27,1842,8,Autonomous Tech -AI01815,Data Engineer,109927,USD,109927,MI,FT,Norway,S,Norway,0,"PyTorch, Kubernetes, TensorFlow, Git",Associate,2,Manufacturing,2025-03-20,2025-05-04,1979,5,Autonomous Tech -AI01816,AI Consultant,135881,EUR,115499,SE,PT,Germany,S,Germany,100,"PyTorch, SQL, NLP",Bachelor,9,Transportation,2025-03-17,2025-04-30,1232,8.4,TechCorp Inc -AI01817,Data Engineer,170048,USD,170048,EX,CT,United States,S,Israel,100,"Statistics, Linux, Tableau, R",PhD,16,Automotive,2024-02-20,2024-03-28,1561,9.8,Machine Intelligence Group -AI01818,Computer Vision Engineer,86374,USD,86374,EX,CT,India,M,India,50,"TensorFlow, Statistics, Scala, Python",PhD,12,Healthcare,2025-01-01,2025-02-09,1201,9.7,Advanced Robotics -AI01819,Computer Vision Engineer,79277,CAD,99096,MI,FT,Canada,S,Canada,100,"PyTorch, R, GCP, Java, Linux",Master,2,Real Estate,2024-05-10,2024-06-02,1121,9.6,AI Innovations -AI01820,Data Scientist,73902,USD,73902,MI,FT,Finland,S,Turkey,100,"Deep Learning, Scala, TensorFlow, MLOps",Master,2,Gaming,2024-02-03,2024-04-03,1351,9,Cognitive Computing -AI01821,Principal Data Scientist,61896,USD,61896,EN,FL,Ireland,M,Ghana,0,"Kubernetes, Azure, SQL, R, Docker",Associate,1,Automotive,2024-01-13,2024-02-12,1699,5.2,DeepTech Ventures -AI01822,AI Product Manager,57201,CAD,71501,EN,PT,Canada,L,Canada,100,"Linux, Tableau, MLOps, Azure",Bachelor,1,Healthcare,2024-12-08,2025-01-30,1408,6.3,AI Innovations -AI01823,Principal Data Scientist,72205,USD,72205,EN,CT,Sweden,M,Brazil,100,"Tableau, Docker, Spark, Kubernetes",Bachelor,0,Transportation,2024-03-31,2024-05-22,943,9.2,Quantum Computing Inc -AI01824,AI Specialist,45721,USD,45721,EN,FL,Israel,S,Singapore,0,"Azure, AWS, Docker",Master,1,Retail,2024-01-16,2024-02-09,2151,7.9,Quantum Computing Inc -AI01825,AI Research Scientist,76605,USD,76605,EN,CT,Denmark,M,Denmark,100,"Spark, Java, Deep Learning, Kubernetes, AWS",Master,1,Healthcare,2024-12-31,2025-03-06,1455,9.9,TechCorp Inc -AI01826,Data Engineer,90927,EUR,77288,MI,FL,Netherlands,L,Netherlands,0,"R, Git, Deep Learning",PhD,2,Automotive,2024-03-05,2024-04-25,777,6.5,Digital Transformation LLC -AI01827,ML Ops Engineer,129674,CAD,162093,SE,CT,Canada,L,Canada,50,"MLOps, Python, NLP, Linux, Hadoop",Master,5,Energy,2025-02-14,2025-04-20,1628,9.7,Smart Analytics -AI01828,Autonomous Systems Engineer,79647,USD,79647,EN,CT,Israel,L,Brazil,100,"Azure, Tableau, Spark",PhD,0,Automotive,2024-06-28,2024-09-03,1836,5.4,DeepTech Ventures -AI01829,Autonomous Systems Engineer,143268,USD,143268,SE,CT,United States,L,United States,100,"Scala, Docker, SQL, Git, MLOps",Bachelor,6,Finance,2024-04-22,2024-06-02,2000,7.5,Neural Networks Co -AI01830,Principal Data Scientist,55944,USD,55944,EN,CT,United States,S,United States,0,"Python, Scala, GCP",Master,1,Consulting,2024-04-21,2024-06-22,2218,8.8,Cloud AI Solutions -AI01831,Head of AI,147714,USD,147714,SE,PT,Denmark,M,Denmark,50,"R, Hadoop, Scala",PhD,7,Gaming,2024-03-05,2024-03-23,1834,5.2,Neural Networks Co -AI01832,AI Product Manager,62923,GBP,47192,EN,FL,United Kingdom,L,United Kingdom,100,"SQL, Statistics, MLOps",Master,0,Automotive,2024-05-17,2024-06-02,2457,5.2,Predictive Systems -AI01833,Deep Learning Engineer,195780,USD,195780,EX,FT,Denmark,S,Japan,100,"Java, PyTorch, Spark",PhD,13,Automotive,2024-04-24,2024-06-03,943,6.5,Machine Intelligence Group -AI01834,Data Analyst,127106,USD,127106,SE,CT,United States,S,Estonia,50,"Python, R, NLP, MLOps, Java",Bachelor,8,Automotive,2025-04-12,2025-06-06,935,5.4,Advanced Robotics -AI01835,Deep Learning Engineer,57038,USD,57038,EN,FT,South Korea,L,South Korea,100,"Data Visualization, R, Hadoop, PyTorch",Master,1,Media,2024-01-06,2024-02-01,2304,5.1,Predictive Systems -AI01836,AI Software Engineer,130998,USD,130998,SE,CT,South Korea,L,South Korea,100,"Data Visualization, PyTorch, Tableau, Git",Bachelor,8,Real Estate,2024-08-01,2024-09-15,1062,5.7,DeepTech Ventures -AI01837,Autonomous Systems Engineer,66589,EUR,56601,EN,FT,Austria,S,Austria,50,"Azure, NLP, GCP, PyTorch",Associate,1,Transportation,2024-11-03,2025-01-07,2290,5.9,AI Innovations -AI01838,Computer Vision Engineer,194996,EUR,165747,EX,CT,Netherlands,L,Malaysia,100,"Data Visualization, Docker, Git, PyTorch, Java",Associate,12,Gaming,2024-10-23,2024-12-10,1664,9.5,Cognitive Computing -AI01839,Data Engineer,152454,EUR,129586,SE,FT,Austria,L,Finland,0,"Statistics, Docker, Hadoop, R",Master,7,Real Estate,2024-08-03,2024-09-01,1068,8.1,DeepTech Ventures -AI01840,Data Analyst,72614,EUR,61722,EN,CT,Germany,S,Germany,50,"Tableau, GCP, MLOps, PyTorch, Git",Associate,0,Real Estate,2024-05-24,2024-07-09,1330,6.5,Predictive Systems -AI01841,Machine Learning Researcher,69406,EUR,58995,EN,CT,Netherlands,L,Netherlands,50,"Hadoop, PyTorch, Data Visualization, TensorFlow, Scala",Associate,1,Education,2024-08-26,2024-09-24,1163,6,Future Systems -AI01842,Machine Learning Engineer,109931,CHF,98938,MI,FL,Switzerland,S,Mexico,50,"TensorFlow, Git, Computer Vision",Master,4,Technology,2025-03-12,2025-05-04,1832,7.5,Future Systems -AI01843,AI Software Engineer,37793,USD,37793,EN,CT,China,M,China,50,"Python, TensorFlow, MLOps, Statistics, Scala",Bachelor,1,Retail,2024-02-05,2024-02-27,2034,8.8,DataVision Ltd -AI01844,Autonomous Systems Engineer,273120,USD,273120,EX,FL,Ireland,L,Ireland,100,"Mathematics, Linux, TensorFlow",Bachelor,15,Retail,2025-04-16,2025-06-27,910,8,Neural Networks Co -AI01845,ML Ops Engineer,105016,CHF,94514,MI,CT,Switzerland,M,Switzerland,100,"Scala, Mathematics, SQL",Master,3,Retail,2025-02-17,2025-04-13,1877,6.2,Cognitive Computing -AI01846,Machine Learning Engineer,231563,CAD,289454,EX,CT,Canada,M,Canada,0,"PyTorch, Hadoop, Kubernetes",Bachelor,10,Education,2024-05-05,2024-06-11,1289,7.7,Neural Networks Co -AI01847,NLP Engineer,120136,USD,120136,SE,CT,Finland,M,Finland,50,"Hadoop, Docker, SQL, TensorFlow, Tableau",Associate,5,Real Estate,2024-07-20,2024-09-19,1156,9.1,Quantum Computing Inc -AI01848,Robotics Engineer,25404,USD,25404,EN,FT,India,L,India,100,"Python, Azure, TensorFlow, GCP",Associate,0,Retail,2024-03-27,2024-04-13,650,8.1,Digital Transformation LLC -AI01849,Data Analyst,58557,JPY,6441270,EN,PT,Japan,M,Japan,100,"R, Docker, Computer Vision, Deep Learning, Hadoop",Associate,1,Government,2025-01-26,2025-02-21,1676,6.7,Predictive Systems -AI01850,AI Software Engineer,78957,EUR,67113,EN,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Java",Master,1,Telecommunications,2024-02-26,2024-04-12,540,8.2,Neural Networks Co -AI01851,NLP Engineer,22675,USD,22675,EN,FL,India,L,India,50,"GCP, R, Data Visualization",PhD,0,Transportation,2024-01-15,2024-03-27,2064,8.5,DataVision Ltd -AI01852,NLP Engineer,147152,USD,147152,SE,FT,Norway,S,Norway,0,"Scala, SQL, PyTorch, Computer Vision, Deep Learning",PhD,9,Finance,2024-10-11,2024-12-08,660,6.2,Cognitive Computing -AI01853,AI Architect,103466,EUR,87946,SE,FL,Austria,M,Austria,100,"Hadoop, Spark, PyTorch",Bachelor,9,Technology,2024-11-28,2024-12-31,1886,6.3,Machine Intelligence Group -AI01854,Machine Learning Researcher,78287,USD,78287,EN,FL,Ireland,M,Ireland,0,"Spark, AWS, Hadoop, Java",PhD,1,Real Estate,2025-02-21,2025-05-04,2397,9.4,Autonomous Tech -AI01855,AI Consultant,142221,EUR,120888,SE,CT,Germany,M,Germany,50,"Git, Kubernetes, Python, TensorFlow, Hadoop",Associate,9,Gaming,2024-07-21,2024-09-26,1266,9.3,Future Systems -AI01856,Machine Learning Engineer,82950,USD,82950,EN,FT,Norway,L,Germany,50,"Kubernetes, Data Visualization, SQL, Mathematics, GCP",Master,0,Gaming,2024-07-21,2024-08-24,800,6.1,Cognitive Computing -AI01857,AI Product Manager,124220,USD,124220,MI,CT,Ireland,L,Ireland,0,"Linux, Computer Vision, Tableau, Kubernetes",Associate,3,Government,2024-08-16,2024-10-11,2005,9.7,Cloud AI Solutions -AI01858,NLP Engineer,78087,CAD,97609,EN,FT,Canada,L,Belgium,50,"MLOps, R, Computer Vision",Bachelor,1,Technology,2024-02-09,2024-03-26,760,9.2,AI Innovations -AI01859,Machine Learning Researcher,50319,GBP,37739,EN,FT,United Kingdom,S,United Kingdom,50,"Deep Learning, MLOps, Java, Git",Bachelor,0,Government,2024-03-29,2024-05-17,2216,10,Smart Analytics -AI01860,Data Analyst,82880,EUR,70448,MI,PT,Netherlands,S,Turkey,0,"TensorFlow, Python, Spark, MLOps",Bachelor,3,Education,2024-05-31,2024-07-19,1846,7.1,Algorithmic Solutions -AI01861,AI Specialist,119491,USD,119491,MI,FT,Ireland,L,Ireland,50,"R, AWS, Spark, Linux, Computer Vision",Master,3,Automotive,2024-04-30,2024-06-27,1982,7.5,Future Systems -AI01862,AI Specialist,202791,USD,202791,SE,FT,United States,L,United States,0,"Kubernetes, Tableau, GCP",Bachelor,8,Technology,2025-02-27,2025-05-03,1627,5.7,DeepTech Ventures -AI01863,Autonomous Systems Engineer,203607,EUR,173066,EX,FL,France,M,Czech Republic,0,"Linux, Data Visualization, NLP",Bachelor,13,Automotive,2024-06-13,2024-08-25,615,8.8,AI Innovations -AI01864,ML Ops Engineer,76776,SGD,99809,EN,FT,Singapore,L,Singapore,0,"Computer Vision, R, Tableau, Linux",PhD,1,Gaming,2024-09-02,2024-10-02,2193,6.9,Neural Networks Co -AI01865,Data Analyst,66728,USD,66728,EN,FL,Sweden,S,Indonesia,100,"Scala, Kubernetes, Computer Vision, TensorFlow",PhD,1,Education,2024-08-17,2024-09-16,679,6.9,Autonomous Tech -AI01866,AI Software Engineer,135400,USD,135400,SE,FL,United States,S,Luxembourg,0,"Hadoop, Python, TensorFlow",Bachelor,5,Consulting,2024-11-09,2024-12-12,856,5.6,Cloud AI Solutions -AI01867,Research Scientist,123743,CAD,154679,SE,FT,Canada,S,Austria,50,"R, Java, Statistics, GCP, Git",Associate,7,Consulting,2024-07-21,2024-09-13,1360,5.3,Cloud AI Solutions -AI01868,Deep Learning Engineer,109631,USD,109631,MI,FL,Norway,S,Germany,50,"AWS, Computer Vision, Data Visualization, NLP",Master,3,Manufacturing,2025-04-05,2025-06-09,2205,6.4,Future Systems -AI01869,Principal Data Scientist,153283,USD,153283,SE,FL,Norway,L,Israel,100,"Python, NLP, Kubernetes, Mathematics",Associate,6,Automotive,2024-04-19,2024-06-02,2060,8.2,Algorithmic Solutions -AI01870,AI Consultant,96402,USD,96402,MI,CT,Norway,M,Norway,0,"Statistics, Scala, Tableau, Computer Vision",PhD,4,Healthcare,2024-07-15,2024-09-25,2089,9.6,Neural Networks Co -AI01871,Research Scientist,158028,USD,158028,SE,FT,Denmark,L,Denmark,100,"Hadoop, Python, TensorFlow",PhD,9,Retail,2024-02-25,2024-04-03,1515,7.3,Predictive Systems -AI01872,NLP Engineer,45538,USD,45538,SE,FL,India,S,India,50,"Git, TensorFlow, Java",Bachelor,8,Gaming,2024-02-06,2024-02-26,1204,9.4,TechCorp Inc -AI01873,AI Architect,115560,USD,115560,MI,FT,Finland,L,Finland,100,"Data Visualization, Linux, AWS, MLOps, Kubernetes",Master,3,Government,2024-03-24,2024-05-02,1753,9,TechCorp Inc -AI01874,AI Consultant,136534,EUR,116054,SE,PT,Germany,M,Germany,100,"Python, TensorFlow, Scala, Java",Master,6,Education,2024-12-19,2025-02-05,1155,7.6,TechCorp Inc -AI01875,AI Research Scientist,211480,USD,211480,EX,CT,Ireland,S,Philippines,50,"Git, TensorFlow, Data Visualization, Computer Vision, Kubernetes",Master,16,Education,2024-05-16,2024-07-17,847,6.5,Cognitive Computing -AI01876,Deep Learning Engineer,112194,USD,112194,SE,FL,Ireland,S,Ireland,50,"Git, Docker, Kubernetes, GCP, Tableau",Bachelor,7,Government,2024-01-27,2024-03-13,1418,8.8,Cloud AI Solutions -AI01877,Autonomous Systems Engineer,150077,USD,150077,EX,FT,Sweden,M,Italy,100,"R, GCP, Linux, Data Visualization, Azure",Bachelor,14,Manufacturing,2024-01-18,2024-03-02,1325,8.6,AI Innovations -AI01878,AI Consultant,125806,USD,125806,SE,CT,Sweden,S,Sweden,50,"Mathematics, Kubernetes, Computer Vision, R",Master,6,Technology,2024-01-01,2024-01-30,1313,5.8,Future Systems -AI01879,Head of AI,66045,USD,66045,EN,CT,Israel,S,Israel,0,"Java, Docker, Computer Vision, Linux, PyTorch",Bachelor,0,Energy,2024-02-17,2024-03-11,1759,9.8,Digital Transformation LLC -AI01880,AI Research Scientist,174743,USD,174743,SE,FT,Norway,S,Poland,0,"SQL, Python, AWS, Java",Bachelor,8,Automotive,2024-09-16,2024-10-31,2102,7.6,AI Innovations -AI01881,AI Product Manager,96725,EUR,82216,EN,CT,Netherlands,L,Romania,0,"Scala, Hadoop, Data Visualization, Azure",Bachelor,1,Consulting,2024-03-22,2024-04-24,2067,6.5,Smart Analytics -AI01882,Data Analyst,61494,USD,61494,EX,PT,India,S,India,50,"Scala, SQL, PyTorch, Statistics",Master,15,Gaming,2024-05-31,2024-06-28,700,9.2,Algorithmic Solutions -AI01883,Autonomous Systems Engineer,51504,CAD,64380,EN,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, Kubernetes",Bachelor,0,Finance,2024-02-16,2024-04-20,725,10,Future Systems -AI01884,Research Scientist,84676,USD,84676,EN,FL,Norway,L,Norway,50,"Hadoop, Git, Data Visualization, PyTorch",Bachelor,1,Automotive,2024-02-13,2024-03-08,2299,5.6,Neural Networks Co -AI01885,Data Engineer,116829,USD,116829,MI,FT,United States,S,United States,100,"GCP, MLOps, AWS",Bachelor,2,Manufacturing,2024-02-02,2024-02-23,2179,5.6,Algorithmic Solutions -AI01886,Machine Learning Researcher,253322,USD,253322,EX,FT,Norway,M,Norway,0,"PyTorch, SQL, MLOps, TensorFlow, Computer Vision",Associate,17,Consulting,2025-01-02,2025-01-29,928,6.3,AI Innovations -AI01887,Machine Learning Researcher,307829,CHF,277046,EX,CT,Switzerland,L,Switzerland,50,"Python, R, Computer Vision, Hadoop, NLP",Master,18,Healthcare,2024-07-09,2024-07-25,2073,9.3,Digital Transformation LLC -AI01888,Head of AI,74701,USD,74701,EN,PT,United States,L,United States,50,"SQL, Git, Java, Mathematics",Master,0,Telecommunications,2024-12-25,2025-02-10,2396,6.5,Cloud AI Solutions -AI01889,Machine Learning Researcher,77814,CAD,97268,MI,PT,Canada,S,Canada,100,"Python, MLOps, Git, Java",PhD,3,Technology,2024-03-23,2024-04-28,2111,5.3,Predictive Systems -AI01890,Head of AI,153857,USD,153857,SE,FL,Ireland,L,Ireland,50,"NLP, Linux, Scala",Master,5,Finance,2024-11-14,2024-12-18,2443,8.8,Autonomous Tech -AI01891,Head of AI,53752,EUR,45689,EN,FL,Netherlands,S,Netherlands,50,"R, Mathematics, SQL",PhD,0,Government,2024-02-26,2024-05-06,1201,5.2,Advanced Robotics -AI01892,Head of AI,67828,USD,67828,EN,PT,Denmark,S,Denmark,0,"PyTorch, Scala, TensorFlow",PhD,0,Government,2025-04-23,2025-07-01,2053,9,Cognitive Computing -AI01893,Machine Learning Engineer,98247,USD,98247,MI,PT,Ireland,S,Vietnam,50,"SQL, TensorFlow, Python, Computer Vision",Bachelor,2,Telecommunications,2025-03-30,2025-04-19,993,7,Digital Transformation LLC -AI01894,AI Product Manager,171970,USD,171970,SE,FL,United States,M,United States,100,"NLP, Linux, MLOps, TensorFlow, Python",PhD,5,Finance,2024-05-17,2024-07-16,698,9.9,Autonomous Tech -AI01895,Machine Learning Engineer,143515,JPY,15786650,SE,FL,Japan,S,Japan,50,"PyTorch, Linux, Tableau, Kubernetes, Spark",Bachelor,9,Consulting,2024-04-24,2024-07-02,2340,7.8,DeepTech Ventures -AI01896,Head of AI,39901,USD,39901,SE,CT,India,S,India,50,"Spark, AWS, Python, Deep Learning",Bachelor,6,Retail,2024-07-11,2024-09-12,685,6.5,Smart Analytics -AI01897,Autonomous Systems Engineer,117566,JPY,12932260,SE,FT,Japan,S,Ukraine,50,"Kubernetes, Python, NLP, Deep Learning, Mathematics",Master,8,Transportation,2025-03-31,2025-05-30,2123,5.2,Smart Analytics -AI01898,Head of AI,113872,CHF,102485,EN,FL,Switzerland,M,Switzerland,50,"SQL, AWS, Statistics, PyTorch",PhD,1,Retail,2024-12-17,2025-01-14,2123,8.5,AI Innovations -AI01899,Machine Learning Engineer,68525,USD,68525,EN,CT,Finland,L,Finland,100,"Mathematics, Kubernetes, R",Master,1,Telecommunications,2024-09-01,2024-09-30,1605,7.2,Advanced Robotics -AI01900,Data Analyst,143796,GBP,107847,SE,FT,United Kingdom,L,Belgium,50,"R, Scala, PyTorch, Git, Python",Master,7,Manufacturing,2024-08-19,2024-10-08,1811,5.6,Predictive Systems -AI01901,NLP Engineer,267822,GBP,200867,EX,CT,United Kingdom,M,Canada,100,"Tableau, Docker, AWS, NLP",Associate,16,Automotive,2024-08-19,2024-09-30,997,9.7,Digital Transformation LLC -AI01902,AI Research Scientist,92727,USD,92727,SE,FL,South Korea,M,Denmark,100,"MLOps, Data Visualization, Java",PhD,8,Retail,2024-01-05,2024-02-07,2179,8.6,Cloud AI Solutions -AI01903,AI Research Scientist,87977,EUR,74780,MI,FT,France,L,France,0,"Hadoop, Linux, Java",Master,3,Real Estate,2024-04-14,2024-05-07,1923,10,Future Systems -AI01904,Autonomous Systems Engineer,71922,EUR,61134,MI,PT,Germany,S,Germany,0,"AWS, Spark, Data Visualization, Git, Scala",PhD,3,Manufacturing,2025-03-07,2025-03-20,1861,9.3,Cognitive Computing -AI01905,Principal Data Scientist,31507,USD,31507,EN,FT,China,L,China,100,"Tableau, Linux, Python, Statistics, R",PhD,0,Gaming,2025-01-26,2025-04-02,1263,8.9,TechCorp Inc -AI01906,Principal Data Scientist,30492,USD,30492,EN,FL,China,M,China,100,"SQL, PyTorch, Tableau, Statistics",PhD,0,Healthcare,2024-10-04,2024-11-19,748,5.1,Advanced Robotics -AI01907,AI Research Scientist,116151,EUR,98728,MI,PT,Netherlands,M,Netherlands,50,"Azure, Linux, Computer Vision, Tableau",Master,3,Automotive,2025-04-16,2025-05-12,1794,9.6,Quantum Computing Inc -AI01908,Machine Learning Researcher,71966,CAD,89958,MI,FL,Canada,M,Canada,50,"Tableau, Python, TensorFlow, Computer Vision, Azure",Associate,2,Finance,2024-03-04,2024-05-05,779,6.1,Autonomous Tech -AI01909,Computer Vision Engineer,163401,GBP,122551,SE,FT,United Kingdom,L,United Kingdom,50,"Python, SQL, Linux",Master,6,Automotive,2024-09-18,2024-11-11,744,6.7,Quantum Computing Inc -AI01910,Robotics Engineer,61330,EUR,52131,EN,CT,France,M,Denmark,0,"Hadoop, Scala, Linux",PhD,1,Consulting,2024-08-09,2024-10-03,1120,9.6,TechCorp Inc -AI01911,Data Engineer,214921,USD,214921,EX,PT,Ireland,S,Ireland,0,"R, MLOps, SQL, Computer Vision, Docker",PhD,16,Media,2025-02-21,2025-04-17,793,8,Algorithmic Solutions -AI01912,AI Product Manager,76932,EUR,65392,EN,FL,Germany,M,Germany,100,"Tableau, TensorFlow, Docker, Spark, SQL",PhD,1,Government,2024-04-29,2024-06-29,614,6.6,Future Systems -AI01913,Research Scientist,169028,CAD,211285,EX,FT,Canada,S,Canada,0,"Java, Deep Learning, Computer Vision, Hadoop",Master,11,Gaming,2024-07-17,2024-09-24,1655,6.5,Smart Analytics -AI01914,Autonomous Systems Engineer,118035,AUD,159347,SE,PT,Australia,L,Australia,0,"Mathematics, Linux, Kubernetes, Python",Associate,9,Automotive,2024-04-18,2024-06-29,1343,8.9,DeepTech Ventures -AI01915,AI Product Manager,113938,USD,113938,MI,PT,Denmark,M,Denmark,100,"Data Visualization, GCP, TensorFlow",Associate,3,Finance,2024-12-02,2025-01-19,863,5.5,Smart Analytics -AI01916,Autonomous Systems Engineer,109615,CAD,137019,SE,FL,Canada,S,Canada,100,"Hadoop, Kubernetes, Scala, Statistics, GCP",PhD,7,Media,2025-03-26,2025-04-22,2420,9.6,Smart Analytics -AI01917,Data Analyst,27659,USD,27659,MI,PT,India,M,India,100,"NLP, Data Visualization, MLOps, Hadoop",Master,2,Healthcare,2024-10-03,2024-10-26,2282,6.1,Neural Networks Co -AI01918,AI Product Manager,67740,USD,67740,EN,PT,United States,S,Austria,100,"Python, Scala, Linux",PhD,0,Real Estate,2025-03-14,2025-05-16,1682,9.8,DeepTech Ventures -AI01919,Machine Learning Researcher,174654,USD,174654,SE,CT,Sweden,L,South Korea,50,"Scala, R, Hadoop, AWS, Python",Master,6,Energy,2024-02-21,2024-03-26,502,5.4,DeepTech Ventures -AI01920,Data Analyst,232730,CAD,290913,EX,FT,Canada,M,India,50,"Hadoop, Kubernetes, Data Visualization, Mathematics, Tableau",PhD,15,Technology,2024-03-11,2024-05-19,1522,5.4,Cognitive Computing -AI01921,Data Analyst,63711,EUR,54154,MI,PT,Austria,S,Austria,50,"Computer Vision, Data Visualization, Python, NLP, AWS",PhD,3,Energy,2025-02-02,2025-02-22,1411,7.5,DataVision Ltd -AI01922,Principal Data Scientist,116990,USD,116990,SE,CT,South Korea,M,South Korea,100,"Computer Vision, R, Scala, GCP, SQL",Associate,8,Media,2024-01-08,2024-03-05,731,6.6,Autonomous Tech -AI01923,AI Architect,105481,USD,105481,MI,CT,Israel,L,Israel,0,"PyTorch, SQL, Computer Vision, NLP, TensorFlow",Master,3,Manufacturing,2024-03-15,2024-04-23,2371,5.2,DeepTech Ventures -AI01924,Data Analyst,161259,EUR,137070,EX,CT,Netherlands,M,Netherlands,0,"Spark, SQL, MLOps",Associate,11,Education,2024-10-15,2024-12-05,1598,9.3,Advanced Robotics -AI01925,Research Scientist,121460,USD,121460,SE,FT,Ireland,L,Ireland,50,"Java, AWS, Mathematics",Bachelor,8,Healthcare,2024-08-28,2024-10-21,848,6.3,Digital Transformation LLC -AI01926,Data Engineer,70644,USD,70644,EN,FL,Sweden,M,Sweden,100,"Python, TensorFlow, Deep Learning",Master,1,Consulting,2025-03-14,2025-04-20,2323,7.4,Future Systems -AI01927,NLP Engineer,109579,GBP,82184,SE,CT,United Kingdom,M,United Kingdom,100,"Python, Docker, Mathematics, Linux, Hadoop",Bachelor,7,Real Estate,2024-10-12,2024-12-04,2482,8.3,Cognitive Computing -AI01928,Head of AI,90547,CAD,113184,MI,CT,Canada,S,United Kingdom,100,"Kubernetes, Docker, Tableau, Azure",PhD,4,Consulting,2024-10-26,2024-12-15,2228,6,Predictive Systems -AI01929,Machine Learning Researcher,218360,USD,218360,EX,PT,South Korea,L,South Korea,0,"GCP, PyTorch, Linux, Azure",Bachelor,18,Healthcare,2024-03-27,2024-04-11,960,6.4,Predictive Systems -AI01930,Robotics Engineer,140380,EUR,119323,SE,PT,Austria,M,Austria,100,"Kubernetes, Scala, R, Computer Vision",PhD,6,Media,2025-04-02,2025-05-10,2084,9.7,Neural Networks Co -AI01931,Computer Vision Engineer,119973,USD,119973,SE,FT,South Korea,L,South Korea,50,"Azure, Python, TensorFlow",Bachelor,7,Transportation,2024-02-18,2024-04-20,2141,6.7,TechCorp Inc -AI01932,NLP Engineer,102535,USD,102535,MI,CT,United States,S,United States,100,"Scala, Python, Linux, Tableau, Computer Vision",Bachelor,4,Energy,2024-01-04,2024-03-09,2029,7.7,DeepTech Ventures -AI01933,Machine Learning Researcher,106806,AUD,144188,MI,FT,Australia,L,Australia,50,"SQL, Java, Docker",Bachelor,2,Manufacturing,2025-03-02,2025-04-09,1517,8.7,Predictive Systems -AI01934,Deep Learning Engineer,54346,CAD,67933,EN,CT,Canada,S,Canada,100,"MLOps, TensorFlow, SQL, Scala",Associate,1,Media,2025-02-27,2025-03-22,1549,8.5,Future Systems -AI01935,AI Consultant,70194,USD,70194,SE,CT,China,L,China,0,"Linux, PyTorch, TensorFlow, AWS",PhD,6,Automotive,2024-07-08,2024-08-24,1557,6.3,Cloud AI Solutions -AI01936,Computer Vision Engineer,94729,EUR,80520,MI,FL,Netherlands,S,Argentina,100,"Data Visualization, Spark, Mathematics",PhD,3,Transportation,2025-03-21,2025-04-18,770,6.5,Neural Networks Co -AI01937,NLP Engineer,46286,USD,46286,EN,FT,Finland,S,Finland,100,"Python, Git, Kubernetes",Master,0,Transportation,2024-09-18,2024-11-20,2261,9.6,Algorithmic Solutions -AI01938,Machine Learning Engineer,166362,USD,166362,SE,CT,Norway,L,Denmark,50,"Data Visualization, PyTorch, Hadoop, Linux",Associate,9,Technology,2025-03-14,2025-04-03,884,6.9,Smart Analytics -AI01939,AI Software Engineer,185959,GBP,139469,EX,CT,United Kingdom,S,United Kingdom,100,"AWS, SQL, Data Visualization, Computer Vision",Master,12,Manufacturing,2024-04-21,2024-06-15,2359,6.1,Advanced Robotics -AI01940,AI Software Engineer,124415,USD,124415,SE,PT,South Korea,M,South Korea,50,"SQL, Spark, R",Associate,9,Media,2024-04-15,2024-05-30,2248,6.3,Advanced Robotics -AI01941,AI Architect,69802,USD,69802,EN,CT,Ireland,S,Netherlands,50,"Linux, Kubernetes, Python, TensorFlow, Data Visualization",Master,0,Transportation,2025-04-10,2025-05-24,1731,7.8,Machine Intelligence Group -AI01942,NLP Engineer,220589,USD,220589,EX,FL,United States,S,United States,50,"Scala, Spark, Linux, TensorFlow",Master,18,Telecommunications,2024-02-11,2024-03-30,1595,5.7,Autonomous Tech -AI01943,AI Specialist,80123,AUD,108166,MI,PT,Australia,S,Australia,0,"TensorFlow, Kubernetes, NLP, Linux",PhD,4,Manufacturing,2025-01-17,2025-02-27,1255,9.2,AI Innovations -AI01944,Data Scientist,116909,USD,116909,MI,FL,United States,S,Brazil,100,"MLOps, Linux, SQL, NLP",Bachelor,2,Telecommunications,2024-07-28,2024-10-08,2205,9.1,DataVision Ltd -AI01945,Machine Learning Engineer,43728,EUR,37169,EN,PT,Austria,S,Austria,0,"Java, Python, Azure, NLP",Bachelor,1,Government,2024-10-28,2025-01-06,2246,5.4,DataVision Ltd -AI01946,Autonomous Systems Engineer,64573,EUR,54887,EN,FT,Austria,L,Austria,50,"AWS, Java, NLP",PhD,0,Finance,2025-04-26,2025-06-30,2310,9,Future Systems -AI01947,NLP Engineer,117914,CHF,106123,MI,FL,Switzerland,S,Switzerland,100,"Hadoop, NLP, R",Bachelor,2,Transportation,2024-07-29,2024-10-10,1827,6.1,Autonomous Tech -AI01948,Autonomous Systems Engineer,152384,USD,152384,EX,CT,South Korea,L,Ukraine,100,"Kubernetes, R, Tableau",Bachelor,16,Real Estate,2025-01-19,2025-02-16,1687,6.3,Digital Transformation LLC -AI01949,AI Software Engineer,68312,EUR,58065,MI,FL,Austria,M,Austria,100,"Python, Deep Learning, Computer Vision, Spark, TensorFlow",PhD,3,Telecommunications,2025-03-31,2025-04-19,509,5.2,DataVision Ltd -AI01950,AI Specialist,85129,CAD,106411,MI,PT,Canada,M,Canada,100,"SQL, Kubernetes, Git, Statistics, Docker",Master,4,Real Estate,2024-01-01,2024-01-17,1017,8.8,Advanced Robotics -AI01951,AI Software Engineer,146496,CHF,131846,SE,CT,Switzerland,S,Switzerland,0,"R, Hadoop, Mathematics, Tableau",Bachelor,7,Consulting,2025-03-06,2025-04-12,1644,6.6,Autonomous Tech -AI01952,Research Scientist,120458,USD,120458,MI,FT,Norway,M,Norway,0,"SQL, PyTorch, AWS, Linux, Computer Vision",Master,4,Retail,2025-02-28,2025-03-31,650,5.8,AI Innovations -AI01953,AI Architect,306393,USD,306393,EX,PT,Denmark,M,United Kingdom,100,"Python, Scala, Computer Vision, Mathematics, TensorFlow",Master,12,Retail,2024-04-29,2024-05-27,2084,6.5,Quantum Computing Inc -AI01954,Data Analyst,119182,USD,119182,SE,FT,Ireland,M,Ireland,0,"Mathematics, Azure, Kubernetes, Git",Associate,6,Gaming,2024-08-02,2024-10-10,1648,5.6,Neural Networks Co -AI01955,AI Product Manager,190595,CHF,171536,EX,PT,Switzerland,S,Switzerland,100,"R, PyTorch, GCP, Tableau, Java",PhD,18,Automotive,2024-10-12,2024-11-06,668,5.2,Future Systems -AI01956,AI Product Manager,133627,AUD,180396,SE,PT,Australia,M,Indonesia,100,"Data Visualization, PyTorch, Spark, GCP",PhD,9,Transportation,2024-08-04,2024-10-13,1422,7.2,AI Innovations -AI01957,AI Specialist,102896,USD,102896,MI,FL,Norway,S,Israel,100,"TensorFlow, Azure, MLOps",Bachelor,2,Energy,2024-04-21,2024-05-05,1871,6.3,Machine Intelligence Group -AI01958,AI Consultant,53828,EUR,45754,EN,CT,France,S,France,100,"Hadoop, TensorFlow, Spark, Computer Vision, SQL",PhD,0,Technology,2024-03-17,2024-04-07,1829,6.3,DataVision Ltd -AI01959,Robotics Engineer,229532,EUR,195102,EX,FT,Netherlands,L,Austria,100,"PyTorch, Tableau, Linux, Python",Master,19,Finance,2025-01-02,2025-03-15,548,7.8,Cognitive Computing -AI01960,Machine Learning Researcher,50929,USD,50929,SE,FL,India,L,India,100,"Spark, Kubernetes, Azure, Deep Learning",Associate,7,Healthcare,2024-12-31,2025-01-30,1837,7.8,Machine Intelligence Group -AI01961,Autonomous Systems Engineer,119585,EUR,101647,SE,PT,Germany,S,Germany,50,"R, Kubernetes, Git",Master,5,Media,2025-02-27,2025-04-28,1402,6,Future Systems -AI01962,Deep Learning Engineer,94488,USD,94488,EN,FT,Denmark,M,New Zealand,0,"Linux, TensorFlow, SQL",Associate,0,Manufacturing,2025-03-24,2025-04-20,2344,7.6,Autonomous Tech -AI01963,Data Analyst,62316,EUR,52969,MI,PT,Austria,S,Austria,50,"Statistics, Python, Deep Learning, Git, TensorFlow",PhD,2,Manufacturing,2024-03-24,2024-04-07,602,6.4,Quantum Computing Inc -AI01964,ML Ops Engineer,108014,USD,108014,EN,PT,Denmark,L,Denmark,50,"MLOps, Spark, SQL, NLP",Bachelor,1,Real Estate,2024-05-07,2024-06-02,1694,8.3,Machine Intelligence Group -AI01965,Deep Learning Engineer,137340,EUR,116739,SE,CT,Netherlands,M,Netherlands,50,"Git, MLOps, Java",Associate,5,Automotive,2024-07-31,2024-09-16,776,9.1,DeepTech Ventures -AI01966,AI Consultant,51851,AUD,69999,EN,FL,Australia,M,Australia,50,"MLOps, Scala, Kubernetes, Python, TensorFlow",PhD,0,Education,2024-05-17,2024-07-20,2465,6.1,TechCorp Inc -AI01967,Machine Learning Engineer,158813,USD,158813,SE,PT,Norway,S,Norway,100,"Tableau, Git, Azure, Scala, GCP",Associate,7,Telecommunications,2024-05-17,2024-06-27,2495,6.8,TechCorp Inc -AI01968,NLP Engineer,272366,USD,272366,EX,CT,Norway,M,Norway,100,"Mathematics, TensorFlow, Tableau, Linux, R",Bachelor,11,Consulting,2025-02-25,2025-03-15,1869,5.8,Cloud AI Solutions -AI01969,AI Research Scientist,66656,USD,66656,EN,PT,Finland,S,France,0,"Kubernetes, PyTorch, Java, AWS, Deep Learning",Bachelor,0,Media,2025-02-16,2025-04-20,559,9.2,Neural Networks Co -AI01970,Computer Vision Engineer,97650,EUR,83003,MI,CT,Austria,M,Austria,100,"MLOps, Data Visualization, TensorFlow, Tableau, SQL",PhD,4,Healthcare,2024-08-31,2024-09-14,1105,5.2,Future Systems -AI01971,Data Scientist,198520,USD,198520,EX,FT,Sweden,L,Sweden,50,"Hadoop, PyTorch, Deep Learning, TensorFlow",Bachelor,15,Retail,2025-02-24,2025-03-24,1825,9.4,Machine Intelligence Group -AI01972,Computer Vision Engineer,113590,CHF,102231,MI,FL,Switzerland,M,France,0,"Git, Computer Vision, PyTorch",Bachelor,4,Gaming,2025-01-17,2025-03-20,2437,5.8,AI Innovations -AI01973,Data Scientist,153445,EUR,130428,EX,CT,France,S,France,0,"Python, Data Visualization, TensorFlow, Deep Learning",Master,10,Manufacturing,2025-03-25,2025-04-12,2026,7,Digital Transformation LLC -AI01974,Robotics Engineer,97324,SGD,126521,EN,FL,Singapore,L,Singapore,50,"Java, Tableau, Kubernetes",Bachelor,0,Manufacturing,2024-07-27,2024-09-23,1832,8.8,Algorithmic Solutions -AI01975,Research Scientist,44666,USD,44666,EN,PT,South Korea,S,South Korea,50,"Kubernetes, Python, AWS",Associate,0,Education,2024-11-06,2024-11-30,2233,6.3,Machine Intelligence Group -AI01976,Deep Learning Engineer,296548,USD,296548,EX,PT,United States,M,United States,100,"Tableau, Azure, Java",Bachelor,18,Technology,2024-06-15,2024-08-13,768,9.8,AI Innovations -AI01977,AI Architect,89790,EUR,76322,EN,CT,Netherlands,L,Netherlands,100,"SQL, Git, MLOps",PhD,0,Government,2024-06-11,2024-08-04,1109,9.6,Cognitive Computing -AI01978,ML Ops Engineer,146337,SGD,190238,SE,PT,Singapore,M,Portugal,0,"R, Data Visualization, Java, GCP, Python",Bachelor,9,Consulting,2024-07-09,2024-07-23,1346,5.6,Neural Networks Co -AI01979,Machine Learning Engineer,99555,CHF,89600,MI,PT,Switzerland,S,South Africa,100,"NLP, Docker, PyTorch",Master,4,Energy,2024-02-13,2024-03-05,1281,8.8,Future Systems -AI01980,NLP Engineer,153992,JPY,16939120,EX,FT,Japan,M,Japan,100,"Linux, GCP, MLOps, Data Visualization, Git",PhD,10,Media,2024-07-05,2024-07-27,1340,8.2,Algorithmic Solutions -AI01981,Deep Learning Engineer,103750,EUR,88188,MI,FT,Netherlands,S,Netherlands,100,"Python, Statistics, Mathematics, TensorFlow, Java",Bachelor,4,Government,2025-02-25,2025-04-05,1399,9.5,DataVision Ltd -AI01982,Principal Data Scientist,88704,USD,88704,MI,PT,Ireland,L,Ghana,0,"Linux, Hadoop, R, Mathematics, Kubernetes",Master,2,Real Estate,2024-01-31,2024-03-25,1929,5.3,Cloud AI Solutions -AI01983,Data Analyst,118310,JPY,13014100,MI,PT,Japan,L,Japan,100,"TensorFlow, Data Visualization, Statistics",Master,3,Telecommunications,2024-06-10,2024-08-06,1801,7.4,Smart Analytics -AI01984,Deep Learning Engineer,171397,EUR,145687,EX,FT,Germany,S,Germany,100,"Azure, Linux, Deep Learning",Master,17,Healthcare,2025-03-22,2025-05-23,1983,5.5,Future Systems -AI01985,AI Research Scientist,80403,CAD,100504,MI,CT,Canada,M,Canada,50,"Scala, Java, Deep Learning",Associate,3,Automotive,2025-02-09,2025-03-12,681,9.5,Algorithmic Solutions -AI01986,Robotics Engineer,118077,USD,118077,SE,FL,United States,S,Norway,50,"Statistics, Azure, TensorFlow",Master,6,Manufacturing,2024-05-24,2024-08-01,1654,5.7,TechCorp Inc -AI01987,Head of AI,103534,USD,103534,SE,FL,Sweden,M,Sweden,100,"SQL, Tableau, PyTorch",Associate,9,Technology,2024-12-04,2025-01-26,2035,7.6,Predictive Systems -AI01988,Computer Vision Engineer,101905,EUR,86619,MI,FT,Austria,M,Switzerland,100,"TensorFlow, Python, GCP",Associate,2,Consulting,2024-04-11,2024-05-22,1083,6.1,AI Innovations -AI01989,AI Research Scientist,182075,USD,182075,EX,CT,South Korea,L,Estonia,0,"Kubernetes, Mathematics, Tableau",PhD,18,Finance,2024-03-12,2024-04-19,979,7.8,DeepTech Ventures -AI01990,AI Research Scientist,230990,SGD,300287,EX,FL,Singapore,M,Singapore,0,"SQL, PyTorch, Computer Vision",Master,16,Government,2024-03-13,2024-04-04,574,8.7,Digital Transformation LLC -AI01991,Computer Vision Engineer,215816,EUR,183444,EX,PT,Germany,S,Germany,100,"Mathematics, PyTorch, NLP",PhD,19,Retail,2024-01-15,2024-02-23,2001,8.2,Cognitive Computing -AI01992,Research Scientist,83946,EUR,71354,EN,FL,Germany,L,Germany,50,"R, Spark, Statistics",PhD,1,Energy,2025-04-30,2025-05-30,726,5.2,DeepTech Ventures -AI01993,ML Ops Engineer,96785,USD,96785,MI,PT,Ireland,S,United Kingdom,0,"TensorFlow, R, SQL, Data Visualization, AWS",Bachelor,2,Telecommunications,2024-03-29,2024-05-27,712,5.5,TechCorp Inc -AI01994,Data Scientist,82495,EUR,70121,MI,PT,Netherlands,M,Malaysia,100,"Linux, Git, MLOps",PhD,3,Gaming,2025-03-10,2025-04-05,856,5.8,Neural Networks Co -AI01995,Machine Learning Engineer,131731,GBP,98798,MI,CT,United Kingdom,L,United Kingdom,0,"TensorFlow, AWS, Linux",PhD,3,Technology,2024-11-08,2024-12-31,814,8.2,Digital Transformation LLC -AI01996,Head of AI,56604,USD,56604,EN,CT,Israel,M,Israel,100,"Kubernetes, PyTorch, Statistics, NLP, TensorFlow",PhD,1,Retail,2024-11-17,2025-01-12,1845,7.4,Cognitive Computing -AI01997,Data Analyst,63776,USD,63776,EN,FL,Ireland,S,Ireland,100,"Spark, Mathematics, Java, Statistics, Python",Bachelor,1,Retail,2024-12-04,2025-01-15,2083,7.1,Digital Transformation LLC -AI01998,AI Architect,68800,CAD,86000,MI,CT,Canada,M,Canada,100,"PyTorch, R, Tableau, Deep Learning",Associate,4,Government,2024-08-15,2024-08-29,868,6.4,Smart Analytics -AI01999,AI Architect,45902,USD,45902,MI,CT,China,S,China,100,"SQL, Scala, Tableau, R",Associate,3,Transportation,2024-04-10,2024-06-17,2292,9,Autonomous Tech -AI02000,Data Scientist,87974,SGD,114366,MI,CT,Singapore,S,Singapore,100,"Mathematics, R, TensorFlow, Hadoop",PhD,4,Retail,2024-11-20,2025-01-31,1465,6.4,Quantum Computing Inc -AI02001,AI Architect,141156,USD,141156,SE,CT,Sweden,M,Sweden,100,"Azure, R, Deep Learning, Scala, Java",PhD,8,Manufacturing,2024-09-19,2024-10-03,928,6.4,Machine Intelligence Group -AI02002,Autonomous Systems Engineer,72809,CHF,65528,EN,CT,Switzerland,M,Switzerland,100,"Linux, Hadoop, Deep Learning, PyTorch, Computer Vision",PhD,1,Telecommunications,2024-05-09,2024-06-18,924,9,Advanced Robotics -AI02003,Autonomous Systems Engineer,74905,CHF,67415,EN,PT,Switzerland,M,South Korea,100,"Statistics, SQL, PyTorch, Deep Learning, Azure",Bachelor,1,Healthcare,2024-12-17,2025-02-06,1485,7.6,Neural Networks Co -AI02004,Deep Learning Engineer,83543,CAD,104429,MI,FL,Canada,L,Portugal,50,"Data Visualization, SQL, MLOps, PyTorch",PhD,4,Transportation,2024-09-28,2024-11-16,1281,5.5,AI Innovations -AI02005,ML Ops Engineer,74348,EUR,63196,EN,FL,France,L,France,0,"Kubernetes, Deep Learning, SQL, Python, NLP",PhD,0,Gaming,2024-02-12,2024-03-05,1746,8.1,DeepTech Ventures -AI02006,AI Product Manager,221177,USD,221177,EX,PT,Israel,M,Russia,50,"Python, Git, Data Visualization, Mathematics, GCP",Associate,10,Manufacturing,2024-08-12,2024-09-04,1529,9,DeepTech Ventures -AI02007,Machine Learning Engineer,188560,USD,188560,EX,FT,Israel,S,Israel,100,"Python, Kubernetes, NLP, Linux",PhD,14,Finance,2024-07-20,2024-08-06,1635,6.9,Cloud AI Solutions -AI02008,Principal Data Scientist,63698,JPY,7006780,EN,FL,Japan,M,Japan,0,"Computer Vision, Java, R",PhD,0,Media,2024-12-28,2025-03-02,1197,5.2,Neural Networks Co -AI02009,AI Architect,80238,USD,80238,EN,CT,Norway,L,Norway,50,"MLOps, Docker, GCP, Scala, PyTorch",Bachelor,0,Manufacturing,2024-12-29,2025-02-27,2410,5.4,Quantum Computing Inc -AI02010,Autonomous Systems Engineer,161051,EUR,136893,EX,PT,Austria,L,Austria,50,"Linux, Python, Scala",Bachelor,15,Education,2024-12-18,2025-01-22,1314,5.2,Smart Analytics -AI02011,NLP Engineer,130144,EUR,110622,SE,FT,Germany,S,Argentina,0,"GCP, PyTorch, TensorFlow, Python, Data Visualization",Bachelor,8,Finance,2024-02-04,2024-02-27,2268,5.5,Autonomous Tech -AI02012,AI Research Scientist,50319,USD,50319,EN,PT,Israel,S,Israel,0,"PyTorch, Java, Python, Mathematics, SQL",Bachelor,1,Media,2024-05-12,2024-05-30,782,7.7,DeepTech Ventures -AI02013,Machine Learning Researcher,256545,USD,256545,EX,CT,Sweden,L,Sweden,100,"PyTorch, SQL, Computer Vision, Spark, Azure",Bachelor,18,Healthcare,2025-02-02,2025-02-20,2493,6.9,Autonomous Tech -AI02014,AI Research Scientist,138961,USD,138961,SE,FT,South Korea,L,South Korea,0,"TensorFlow, Docker, SQL",Associate,6,Government,2024-04-11,2024-06-13,1018,8.6,TechCorp Inc -AI02015,Machine Learning Engineer,60037,EUR,51031,EN,CT,Germany,L,United Kingdom,0,"Mathematics, Scala, Data Visualization",Bachelor,0,Education,2024-07-25,2024-08-31,2188,6.3,AI Innovations -AI02016,AI Software Engineer,102110,USD,102110,MI,PT,Norway,M,Norway,0,"Git, Python, Java",Master,3,Retail,2024-11-17,2025-01-17,1311,8.1,AI Innovations -AI02017,Research Scientist,159317,EUR,135419,SE,FL,Germany,L,Germany,50,"Java, TensorFlow, PyTorch, Azure, GCP",PhD,9,Automotive,2025-02-25,2025-03-16,2179,5.8,Machine Intelligence Group -AI02018,Data Analyst,113026,EUR,96072,SE,PT,Netherlands,S,Netherlands,0,"R, GCP, Kubernetes, Spark, Linux",Bachelor,6,Technology,2024-12-19,2025-03-01,1999,9.2,Machine Intelligence Group -AI02019,Data Engineer,175703,USD,175703,SE,FL,Denmark,S,Denmark,50,"Deep Learning, Azure, Hadoop, SQL, Git",Bachelor,8,Telecommunications,2024-03-07,2024-04-19,1080,7,Autonomous Tech -AI02020,Deep Learning Engineer,79945,USD,79945,MI,CT,United States,S,Luxembourg,0,"Git, Statistics, Azure",Master,2,Retail,2024-02-21,2024-04-19,1292,7.3,Machine Intelligence Group -AI02021,Data Analyst,78895,AUD,106508,EN,FL,Australia,L,Australia,0,"MLOps, Kubernetes, TensorFlow, Python",PhD,1,Gaming,2024-03-03,2024-04-22,655,8.2,Neural Networks Co -AI02022,Head of AI,65331,USD,65331,EN,FT,Ireland,S,Ireland,50,"Azure, Kubernetes, AWS, MLOps, TensorFlow",PhD,0,Consulting,2024-06-29,2024-07-23,629,5.2,Advanced Robotics -AI02023,AI Software Engineer,88502,USD,88502,EN,PT,Denmark,L,Denmark,100,"Linux, Git, Deep Learning, SQL, Azure",PhD,0,Gaming,2024-03-06,2024-04-23,2419,8.8,Neural Networks Co -AI02024,AI Research Scientist,218753,SGD,284379,EX,FL,Singapore,M,Norway,0,"Git, Python, Mathematics",Bachelor,17,Media,2024-08-06,2024-09-06,1029,8.6,Cloud AI Solutions -AI02025,Machine Learning Researcher,286960,SGD,373048,EX,FL,Singapore,L,Singapore,50,"Scala, Mathematics, Data Visualization, Git, Python",PhD,13,Energy,2024-07-02,2024-07-19,1324,7.9,Future Systems -AI02026,Autonomous Systems Engineer,54703,USD,54703,EN,FL,Sweden,M,Sweden,0,"Hadoop, Git, Tableau, Scala",PhD,0,Gaming,2024-04-19,2024-06-07,2069,6.4,Advanced Robotics -AI02027,Machine Learning Engineer,119409,USD,119409,SE,PT,Finland,L,Belgium,0,"AWS, MLOps, Kubernetes, Azure, Spark",Bachelor,5,Technology,2024-07-27,2024-09-03,2467,6.3,Autonomous Tech -AI02028,AI Software Engineer,169745,CAD,212181,EX,CT,Canada,M,Canada,50,"Java, SQL, PyTorch",Master,16,Real Estate,2024-03-20,2024-05-06,2094,5.4,Digital Transformation LLC -AI02029,AI Product Manager,117185,EUR,99607,MI,FT,Austria,L,Brazil,50,"Java, Kubernetes, Scala, Computer Vision, Git",Associate,2,Gaming,2025-01-13,2025-02-04,1341,7.6,Quantum Computing Inc -AI02030,AI Specialist,67488,EUR,57365,EN,PT,Germany,L,Italy,0,"SQL, Azure, PyTorch, Docker, TensorFlow",Master,0,Education,2024-10-02,2024-11-21,1857,7.4,Algorithmic Solutions -AI02031,Data Analyst,237063,AUD,320035,EX,FT,Australia,L,Australia,0,"Azure, Java, NLP, Hadoop",Bachelor,12,Technology,2024-07-17,2024-09-09,2126,9.3,Future Systems -AI02032,Data Engineer,121918,EUR,103630,MI,FL,Germany,L,Germany,50,"Kubernetes, Statistics, Tableau",Associate,2,Gaming,2024-07-09,2024-08-08,1044,5.7,Autonomous Tech -AI02033,Deep Learning Engineer,147358,USD,147358,EX,CT,Ireland,S,Argentina,0,"AWS, Python, Kubernetes, TensorFlow, Docker",Master,19,Transportation,2025-02-22,2025-04-06,932,6.2,DeepTech Ventures -AI02034,Data Analyst,159954,SGD,207940,SE,CT,Singapore,M,Singapore,50,"R, Kubernetes, MLOps, AWS, PyTorch",Master,8,Energy,2024-10-10,2024-11-04,886,7.5,Future Systems -AI02035,Data Analyst,112591,USD,112591,SE,FL,South Korea,M,Thailand,0,"Azure, Scala, Data Visualization, Mathematics",Bachelor,5,Government,2024-04-21,2024-05-07,758,5.4,TechCorp Inc -AI02036,AI Consultant,51670,EUR,43920,EN,CT,France,M,France,50,"R, MLOps, TensorFlow, Hadoop",Bachelor,1,Energy,2024-03-25,2024-04-26,1983,9.2,Predictive Systems -AI02037,Data Analyst,54739,USD,54739,EN,CT,Finland,S,Finland,50,"Statistics, MLOps, Tableau, SQL, Linux",PhD,1,Consulting,2024-09-20,2024-11-06,2488,6.7,Future Systems -AI02038,Principal Data Scientist,93238,EUR,79252,SE,CT,France,S,France,0,"NLP, Docker, Python, AWS",Bachelor,5,Education,2024-07-13,2024-08-24,1683,6,DeepTech Ventures -AI02039,AI Research Scientist,84825,USD,84825,MI,FL,Ireland,L,Malaysia,100,"Kubernetes, Mathematics, Tableau, MLOps",Associate,2,Technology,2024-05-16,2024-07-20,1709,6.7,TechCorp Inc -AI02040,AI Software Engineer,78450,USD,78450,MI,FT,Sweden,S,Sweden,100,"Computer Vision, Python, Git, TensorFlow",Bachelor,4,Energy,2024-12-18,2025-01-01,505,5.5,AI Innovations -AI02041,Head of AI,66222,USD,66222,EN,FL,South Korea,L,South Korea,50,"SQL, Deep Learning, NLP, Python",PhD,1,Technology,2024-09-04,2024-10-10,692,9.7,Algorithmic Solutions -AI02042,ML Ops Engineer,87393,USD,87393,MI,FL,United States,S,China,100,"Docker, Kubernetes, Data Visualization, Mathematics, Hadoop",Associate,2,Automotive,2025-01-14,2025-02-13,703,9.5,Smart Analytics -AI02043,Data Scientist,293844,GBP,220383,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Git, Tableau",Master,13,Healthcare,2024-02-11,2024-03-20,905,5.1,Neural Networks Co -AI02044,NLP Engineer,89635,USD,89635,EX,CT,China,S,China,50,"NLP, Scala, SQL, Deep Learning, Azure",Master,17,Manufacturing,2024-02-02,2024-04-05,1941,6.3,Quantum Computing Inc -AI02045,Data Analyst,40827,USD,40827,SE,CT,India,M,Argentina,100,"Deep Learning, PyTorch, Scala, Computer Vision",Associate,8,Consulting,2024-01-21,2024-03-11,867,6.1,DataVision Ltd -AI02046,AI Architect,53958,USD,53958,MI,PT,China,L,New Zealand,50,"SQL, Docker, Tableau",Bachelor,2,Real Estate,2024-05-12,2024-07-15,2051,7.5,DeepTech Ventures -AI02047,Autonomous Systems Engineer,209986,EUR,178488,EX,PT,France,S,France,50,"Scala, Kubernetes, Data Visualization, SQL, R",Associate,15,Real Estate,2024-04-12,2024-05-11,1552,5.3,Smart Analytics -AI02048,Data Engineer,48509,USD,48509,EN,FL,Finland,S,Finland,0,"Git, Mathematics, Hadoop, AWS, Azure",Bachelor,1,Education,2025-03-30,2025-05-03,2109,9.7,TechCorp Inc -AI02049,Autonomous Systems Engineer,256412,USD,256412,EX,CT,Denmark,L,Germany,0,"Java, TensorFlow, Spark, AWS",PhD,18,Real Estate,2025-04-10,2025-05-21,2390,5.7,TechCorp Inc -AI02050,Research Scientist,54244,USD,54244,EN,FL,South Korea,M,South Korea,100,"Python, Java, Tableau, TensorFlow",Master,0,Manufacturing,2024-05-29,2024-06-30,896,5.3,Cloud AI Solutions -AI02051,AI Architect,58064,USD,58064,EN,FT,Sweden,S,Denmark,100,"Kubernetes, MLOps, Statistics",Bachelor,0,Real Estate,2025-03-11,2025-04-30,1851,6.3,Predictive Systems -AI02052,Data Analyst,89637,USD,89637,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, MLOps, Hadoop",Bachelor,8,Gaming,2025-01-01,2025-02-15,795,7.4,Quantum Computing Inc -AI02053,Autonomous Systems Engineer,74071,USD,74071,EN,FL,Denmark,S,Vietnam,100,"R, Computer Vision, PyTorch, GCP",Bachelor,1,Technology,2024-04-11,2024-04-30,1809,7.5,Algorithmic Solutions -AI02054,AI Consultant,89562,EUR,76128,MI,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, Python, SQL, TensorFlow",PhD,4,Retail,2024-10-02,2024-10-16,750,9.4,Neural Networks Co -AI02055,Research Scientist,199418,CHF,179476,SE,FT,Switzerland,L,Switzerland,0,"Python, R, GCP, Spark",PhD,9,Government,2024-03-01,2024-05-01,1597,9.1,Advanced Robotics -AI02056,Robotics Engineer,128887,EUR,109554,EX,PT,France,M,France,50,"Azure, AWS, Tableau",Bachelor,13,Consulting,2024-03-19,2024-04-26,963,8.3,AI Innovations -AI02057,Data Analyst,72518,EUR,61640,EN,PT,Germany,S,Germany,50,"Python, SQL, Tableau",Bachelor,1,Finance,2024-05-30,2024-07-16,506,6.3,DataVision Ltd -AI02058,Autonomous Systems Engineer,63237,EUR,53751,MI,CT,France,S,France,0,"NLP, Kubernetes, Scala, Git, Tableau",PhD,4,Automotive,2024-01-17,2024-02-19,737,6.6,DeepTech Ventures -AI02059,Deep Learning Engineer,135732,GBP,101799,SE,PT,United Kingdom,S,Switzerland,100,"Python, SQL, Java, Computer Vision",Bachelor,5,Government,2024-05-01,2024-07-03,1777,5.8,Cognitive Computing -AI02060,AI Software Engineer,99662,USD,99662,EX,CT,China,M,China,100,"Kubernetes, Azure, Python, Hadoop",Bachelor,12,Transportation,2024-02-04,2024-03-14,1974,5,TechCorp Inc -AI02061,AI Consultant,282892,USD,282892,EX,FL,Ireland,L,Israel,100,"Scala, Java, Kubernetes",Master,14,Real Estate,2024-01-23,2024-02-14,2335,9.5,TechCorp Inc -AI02062,Computer Vision Engineer,126107,USD,126107,MI,CT,Denmark,L,Denmark,100,"Azure, Scala, Kubernetes",PhD,4,Retail,2024-08-23,2024-10-30,1170,9.4,Quantum Computing Inc -AI02063,Research Scientist,157203,USD,157203,SE,FL,United States,M,United States,0,"Git, Python, Computer Vision, Mathematics, AWS",PhD,5,Technology,2024-10-21,2024-12-01,1718,6.6,TechCorp Inc -AI02064,AI Specialist,91180,USD,91180,EN,CT,Norway,M,Norway,0,"Java, GCP, AWS, Hadoop",Master,0,Consulting,2024-12-09,2025-01-23,1561,5.4,Digital Transformation LLC -AI02065,Data Scientist,102489,USD,102489,EX,CT,China,M,China,50,"Tableau, Git, Kubernetes, MLOps, Computer Vision",PhD,19,Retail,2024-08-04,2024-09-15,1000,5.7,Smart Analytics -AI02066,AI Architect,220299,USD,220299,EX,FT,Finland,L,Finland,100,"NLP, Scala, Data Visualization",Associate,18,Retail,2025-04-18,2025-06-27,994,9.8,Smart Analytics -AI02067,AI Specialist,83499,USD,83499,MI,FL,Israel,M,Israel,50,"Data Visualization, Linux, Python, TensorFlow, PyTorch",Master,4,Manufacturing,2025-01-03,2025-02-28,1120,8.5,Cloud AI Solutions -AI02068,AI Research Scientist,72075,EUR,61264,EN,FT,Germany,M,Germany,50,"MLOps, Azure, AWS, Deep Learning, R",Associate,1,Government,2024-08-02,2024-10-03,1635,6.1,Advanced Robotics -AI02069,Deep Learning Engineer,87037,EUR,73981,MI,CT,Netherlands,M,Netherlands,0,"Deep Learning, Docker, NLP, Hadoop",Master,2,Automotive,2024-10-06,2024-11-02,967,5.4,Smart Analytics -AI02070,AI Research Scientist,123099,USD,123099,MI,FT,Denmark,S,Denmark,0,"PyTorch, AWS, MLOps, Python",PhD,2,Consulting,2025-02-22,2025-05-04,1204,7.5,Autonomous Tech -AI02071,Machine Learning Engineer,104913,EUR,89176,SE,CT,Germany,S,China,0,"Kubernetes, Scala, NLP, Mathematics, TensorFlow",Associate,5,Technology,2024-08-13,2024-10-24,2478,7.5,Machine Intelligence Group -AI02072,Deep Learning Engineer,221690,EUR,188437,EX,CT,Austria,L,Mexico,50,"PyTorch, Python, Git, Spark, Azure",Bachelor,19,Telecommunications,2024-08-05,2024-08-29,1602,7.3,Digital Transformation LLC -AI02073,Data Scientist,113653,EUR,96605,SE,FL,Germany,S,Germany,0,"Data Visualization, Kubernetes, Mathematics",Master,8,Real Estate,2024-01-06,2024-03-09,2077,8.6,DataVision Ltd -AI02074,Computer Vision Engineer,250419,USD,250419,EX,PT,United States,L,United States,100,"Data Visualization, Python, Azure, Scala, GCP",Bachelor,18,Retail,2024-05-17,2024-06-08,2362,7.2,Algorithmic Solutions -AI02075,AI Consultant,108412,EUR,92150,SE,CT,France,S,France,100,"Java, Python, Data Visualization, Linux",Associate,8,Gaming,2024-09-14,2024-10-16,1441,8.1,Algorithmic Solutions -AI02076,AI Specialist,186753,EUR,158740,EX,FL,Netherlands,S,Netherlands,100,"Mathematics, SQL, PyTorch",Associate,16,Technology,2025-04-05,2025-06-01,2436,8.9,Advanced Robotics -AI02077,AI Product Manager,134362,GBP,100772,MI,FT,United Kingdom,L,Finland,100,"Tableau, Hadoop, R, Docker",Associate,3,Consulting,2024-04-04,2024-05-15,2222,7.5,Smart Analytics -AI02078,Data Scientist,157702,USD,157702,EX,CT,Sweden,S,Vietnam,0,"Python, TensorFlow, Data Visualization, PyTorch, Hadoop",PhD,19,Real Estate,2024-04-25,2024-07-07,2122,8,Algorithmic Solutions -AI02079,Data Scientist,69203,USD,69203,EN,FL,Israel,M,Israel,0,"Spark, Scala, Python, Kubernetes, Docker",Master,0,Manufacturing,2024-02-16,2024-04-03,1738,9.9,Advanced Robotics -AI02080,AI Product Manager,97206,GBP,72905,MI,FL,United Kingdom,M,New Zealand,0,"TensorFlow, Scala, Deep Learning, Statistics, AWS",PhD,2,Consulting,2024-03-04,2024-03-18,1813,9.6,Quantum Computing Inc -AI02081,Data Scientist,82737,USD,82737,SE,CT,China,L,Japan,50,"Python, R, TensorFlow",Bachelor,9,Government,2024-06-06,2024-08-17,2069,9.9,DeepTech Ventures -AI02082,Machine Learning Engineer,99693,USD,99693,SE,PT,Sweden,S,Sweden,0,"Docker, Scala, Git, AWS",PhD,7,Telecommunications,2024-08-29,2024-10-20,1189,8.3,Autonomous Tech -AI02083,Autonomous Systems Engineer,82795,USD,82795,EN,PT,Finland,L,Finland,0,"SQL, Git, PyTorch, Spark, GCP",Associate,1,Transportation,2024-08-22,2024-09-13,1102,9.8,AI Innovations -AI02084,AI Research Scientist,174298,USD,174298,EX,FL,Finland,M,United States,50,"TensorFlow, Kubernetes, Statistics, SQL, AWS",Bachelor,13,Technology,2024-09-06,2024-09-28,721,7,Advanced Robotics -AI02085,Machine Learning Researcher,270830,CHF,243747,EX,PT,Switzerland,M,Switzerland,100,"PyTorch, Kubernetes, Tableau, SQL, Spark",Bachelor,11,Consulting,2024-11-10,2024-12-22,1174,7.1,Predictive Systems -AI02086,Machine Learning Researcher,68593,USD,68593,MI,PT,Israel,M,Israel,50,"Docker, Tableau, GCP",Master,3,Transportation,2024-10-05,2024-12-07,1095,9.1,Cloud AI Solutions -AI02087,Machine Learning Engineer,67495,EUR,57371,EN,PT,Netherlands,S,Netherlands,50,"Python, Kubernetes, Computer Vision",Bachelor,1,Transportation,2025-01-18,2025-03-19,2058,6.2,Smart Analytics -AI02088,AI Product Manager,114616,GBP,85962,MI,FL,United Kingdom,M,United Kingdom,50,"Statistics, Kubernetes, GCP, NLP, TensorFlow",Master,3,Energy,2024-03-25,2024-04-15,869,5.6,Neural Networks Co -AI02089,Data Engineer,213578,USD,213578,EX,CT,Sweden,M,Japan,50,"PyTorch, Kubernetes, Hadoop, R",Associate,15,Energy,2025-04-14,2025-05-03,1459,8.6,Algorithmic Solutions -AI02090,AI Product Manager,212620,USD,212620,EX,CT,Denmark,L,Denmark,0,"GCP, PyTorch, Data Visualization, Computer Vision",Bachelor,16,Education,2024-09-10,2024-11-10,905,9.1,Cloud AI Solutions -AI02091,Computer Vision Engineer,56144,USD,56144,SE,CT,China,M,China,100,"SQL, Docker, PyTorch, Kubernetes",Master,6,Real Estate,2024-02-08,2024-03-04,2052,7.4,AI Innovations -AI02092,Research Scientist,81572,EUR,69336,MI,FL,Austria,L,Luxembourg,0,"Computer Vision, Linux, PyTorch, Scala",Master,2,Healthcare,2024-09-25,2024-10-31,2115,8,AI Innovations -AI02093,Head of AI,69805,EUR,59334,EN,FL,Germany,S,South Korea,100,"SQL, Linux, Java, TensorFlow",PhD,1,Government,2024-07-09,2024-07-27,1396,6.2,Autonomous Tech -AI02094,ML Ops Engineer,134815,EUR,114593,SE,CT,Netherlands,S,Vietnam,100,"Docker, Tableau, Git, Kubernetes",PhD,7,Transportation,2024-07-14,2024-08-13,1842,9.6,TechCorp Inc -AI02095,NLP Engineer,201072,EUR,170911,EX,PT,Germany,S,Norway,100,"Linux, PyTorch, Git, Mathematics, Statistics",Bachelor,12,Education,2025-02-09,2025-03-21,965,6.2,Autonomous Tech -AI02096,AI Research Scientist,295447,JPY,32499170,EX,FL,Japan,L,Japan,50,"Spark, Linux, Statistics, PyTorch",Master,13,Finance,2024-01-31,2024-03-26,2060,5.6,Neural Networks Co -AI02097,Deep Learning Engineer,76720,USD,76720,EX,FL,China,M,China,50,"SQL, Kubernetes, TensorFlow, Scala",Associate,14,Gaming,2025-02-25,2025-04-02,970,7.9,Neural Networks Co -AI02098,Machine Learning Engineer,125533,USD,125533,SE,FL,Denmark,S,Denmark,0,"Deep Learning, Java, Scala",PhD,8,Automotive,2024-10-11,2024-12-01,1268,9.5,Digital Transformation LLC -AI02099,Robotics Engineer,253018,CAD,316273,EX,FT,Canada,L,Nigeria,50,"R, PyTorch, SQL, Scala",Associate,17,Government,2024-12-31,2025-03-06,1852,7.6,Cognitive Computing -AI02100,AI Product Manager,133162,GBP,99872,SE,FT,United Kingdom,S,United Kingdom,50,"Python, NLP, SQL, Linux, Kubernetes",Bachelor,7,Gaming,2025-04-14,2025-05-17,779,7.6,Digital Transformation LLC -AI02101,AI Architect,91600,USD,91600,MI,FL,South Korea,L,South Korea,100,"Python, GCP, Scala, Docker, Computer Vision",PhD,4,Finance,2024-04-26,2024-05-30,621,7.1,DataVision Ltd -AI02102,AI Product Manager,157559,EUR,133925,EX,CT,Austria,L,Austria,0,"Azure, MLOps, Scala, Computer Vision",Bachelor,19,Telecommunications,2025-03-13,2025-05-23,873,7.5,DeepTech Ventures -AI02103,Data Scientist,171584,USD,171584,EX,CT,Finland,M,Finland,100,"PyTorch, Python, Statistics",PhD,13,Education,2024-08-28,2024-09-24,1690,6.8,Autonomous Tech -AI02104,ML Ops Engineer,156785,CAD,195981,EX,FT,Canada,M,Canada,50,"SQL, PyTorch, Linux, Tableau",Bachelor,16,Media,2024-03-31,2024-04-20,2139,6.3,DataVision Ltd -AI02105,Machine Learning Engineer,293023,USD,293023,EX,CT,Denmark,M,Australia,100,"Docker, Computer Vision, Python, NLP, Deep Learning",Master,12,Manufacturing,2024-08-10,2024-10-10,1377,8.6,Smart Analytics -AI02106,Principal Data Scientist,86508,JPY,9515880,EN,FT,Japan,L,Japan,0,"Computer Vision, TensorFlow, GCP",Master,0,Technology,2025-03-28,2025-06-09,1511,8.8,Cloud AI Solutions -AI02107,AI Software Engineer,81412,USD,81412,EX,FT,China,S,Philippines,0,"Tableau, Linux, MLOps, Spark, Mathematics",Master,18,Media,2024-06-10,2024-07-22,1689,8.6,Advanced Robotics -AI02108,NLP Engineer,186673,EUR,158672,EX,FT,Austria,S,Austria,50,"Docker, Linux, SQL",Associate,10,Healthcare,2024-07-12,2024-08-22,1860,10,Advanced Robotics -AI02109,Principal Data Scientist,112912,USD,112912,MI,PT,United States,L,United States,100,"SQL, Spark, Git",Bachelor,4,Education,2024-09-19,2024-10-15,631,8.3,Cloud AI Solutions -AI02110,Principal Data Scientist,51942,USD,51942,EN,PT,Sweden,M,Japan,0,"R, Linux, Git, GCP, Deep Learning",PhD,0,Energy,2024-01-24,2024-02-27,828,6,Quantum Computing Inc -AI02111,Research Scientist,127418,USD,127418,MI,FT,Norway,M,Norway,0,"Hadoop, Java, Data Visualization",Associate,3,Automotive,2025-03-05,2025-04-16,1167,6.1,Machine Intelligence Group -AI02112,Research Scientist,96844,USD,96844,EN,CT,Denmark,L,Denmark,50,"MLOps, Kubernetes, Python, TensorFlow, PyTorch",Bachelor,0,Finance,2025-01-23,2025-03-03,2403,7.9,Autonomous Tech -AI02113,Principal Data Scientist,205497,USD,205497,EX,PT,Norway,M,Belgium,100,"Spark, TensorFlow, Data Visualization",Master,13,Automotive,2024-03-12,2024-04-14,990,5.2,Future Systems -AI02114,Machine Learning Researcher,36123,USD,36123,MI,FT,China,S,China,50,"R, SQL, Git, PyTorch",Associate,3,Manufacturing,2025-01-10,2025-02-18,812,9.3,Quantum Computing Inc -AI02115,Data Engineer,26530,USD,26530,EN,PT,China,S,China,0,"Scala, MLOps, SQL",Master,0,Automotive,2025-03-26,2025-04-25,2428,7.5,DataVision Ltd -AI02116,Deep Learning Engineer,118399,CAD,147999,SE,FL,Canada,L,Canada,50,"PyTorch, Scala, R",Master,9,Technology,2024-09-27,2024-11-05,2031,6.9,Cloud AI Solutions -AI02117,Data Analyst,100255,GBP,75191,MI,FT,United Kingdom,M,India,100,"Git, SQL, TensorFlow",Bachelor,2,Consulting,2025-04-25,2025-05-14,1999,8.9,Smart Analytics -AI02118,Research Scientist,129800,SGD,168740,SE,FT,Singapore,L,Singapore,100,"SQL, Computer Vision, Tableau, Python",Associate,6,Consulting,2025-03-18,2025-05-11,1202,8.2,DataVision Ltd -AI02119,Data Engineer,165833,AUD,223875,SE,PT,Australia,L,Australia,100,"NLP, Hadoop, Tableau, TensorFlow, SQL",Associate,8,Consulting,2024-12-31,2025-03-13,604,8.2,DataVision Ltd -AI02120,Computer Vision Engineer,84617,EUR,71924,MI,FL,France,L,France,50,"Azure, Java, Statistics",Master,3,Healthcare,2024-06-24,2024-07-15,1313,8.4,DeepTech Ventures -AI02121,AI Product Manager,228358,USD,228358,EX,FL,Sweden,M,Sweden,50,"TensorFlow, SQL, Python, GCP",Master,19,Transportation,2024-10-01,2024-11-15,849,5.3,Predictive Systems -AI02122,Deep Learning Engineer,89402,CHF,80462,EN,FT,Switzerland,S,Ireland,100,"Java, Git, Kubernetes, Scala, Mathematics",Associate,0,Real Estate,2024-03-28,2024-05-18,1854,8.7,Digital Transformation LLC -AI02123,AI Software Engineer,251892,USD,251892,EX,FT,Finland,L,Finland,100,"Spark, Python, Computer Vision, Data Visualization",Master,14,Technology,2024-07-22,2024-08-20,1045,7.9,Algorithmic Solutions -AI02124,NLP Engineer,91223,USD,91223,MI,PT,Ireland,L,Ireland,100,"Python, R, Statistics, GCP",Associate,4,Energy,2024-06-14,2024-08-24,1730,5.3,Algorithmic Solutions -AI02125,Robotics Engineer,178163,EUR,151439,EX,FL,France,L,France,100,"Linux, Hadoop, NLP, Kubernetes",Bachelor,18,Media,2024-07-07,2024-08-30,610,7.8,Cognitive Computing -AI02126,Machine Learning Researcher,110328,USD,110328,MI,FL,Denmark,M,Denmark,50,"AWS, Data Visualization, Tableau, TensorFlow",Bachelor,2,Energy,2024-11-04,2025-01-02,2362,5.9,DeepTech Ventures -AI02127,Research Scientist,80058,USD,80058,EN,CT,Norway,L,Norway,0,"SQL, PyTorch, Statistics, NLP",Master,0,Consulting,2025-04-13,2025-05-08,2081,8.4,AI Innovations -AI02128,Machine Learning Researcher,81768,USD,81768,SE,CT,China,L,China,100,"Git, R, Computer Vision",Master,7,Consulting,2025-03-10,2025-04-23,1020,5.1,Digital Transformation LLC -AI02129,Computer Vision Engineer,273957,EUR,232863,EX,FT,Netherlands,L,Netherlands,100,"Kubernetes, Azure, Spark, GCP",PhD,13,Government,2024-07-10,2024-08-28,589,7,Advanced Robotics -AI02130,Principal Data Scientist,71171,JPY,7828810,MI,CT,Japan,S,Japan,100,"Python, Statistics, Scala, Git",Master,2,Gaming,2025-03-24,2025-04-30,2269,8.9,AI Innovations -AI02131,Research Scientist,262050,EUR,222743,EX,CT,Netherlands,M,China,50,"Python, R, Tableau, Mathematics, GCP",Bachelor,19,Real Estate,2024-05-09,2024-06-14,2049,6.9,Digital Transformation LLC -AI02132,Principal Data Scientist,74346,JPY,8178060,EN,FL,Japan,S,Japan,50,"Git, MLOps, Python, Scala, Computer Vision",Associate,0,Technology,2024-07-31,2024-08-26,1392,5.6,Cognitive Computing -AI02133,AI Architect,26055,USD,26055,EN,FT,India,M,United States,100,"Python, AWS, Data Visualization, NLP",Master,1,Manufacturing,2025-02-04,2025-04-14,2432,5.8,Smart Analytics -AI02134,Autonomous Systems Engineer,113953,USD,113953,MI,FT,Israel,L,Israel,50,"GCP, PyTorch, Tableau",Bachelor,2,Healthcare,2024-07-07,2024-09-05,1361,9.1,Cloud AI Solutions -AI02135,Data Engineer,176525,GBP,132394,SE,CT,United Kingdom,L,United Kingdom,0,"R, Scala, Data Visualization, Linux, PyTorch",Associate,7,Manufacturing,2024-03-15,2024-04-28,2353,9.3,Advanced Robotics -AI02136,Robotics Engineer,137979,CHF,124181,SE,CT,Switzerland,S,Netherlands,0,"Linux, Python, TensorFlow",Bachelor,6,Gaming,2024-10-26,2024-12-29,1773,9.3,Cloud AI Solutions -AI02137,Data Engineer,232117,GBP,174088,EX,PT,United Kingdom,M,United Kingdom,100,"Computer Vision, SQL, Java",Master,15,Government,2024-11-21,2024-12-16,945,6.7,Cognitive Computing -AI02138,Data Analyst,130819,USD,130819,EX,FT,Finland,M,Finland,100,"Java, R, Mathematics",PhD,15,Telecommunications,2024-09-08,2024-10-04,1792,8.5,Neural Networks Co -AI02139,Machine Learning Engineer,245291,GBP,183968,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Python, Docker, Linux, NLP",Master,17,Telecommunications,2024-11-21,2025-01-19,1549,9.1,Future Systems -AI02140,NLP Engineer,121783,EUR,103516,SE,CT,France,M,Colombia,0,"Mathematics, PyTorch, SQL, Linux",PhD,5,Energy,2024-03-19,2024-04-09,2367,9.4,Cloud AI Solutions -AI02141,Machine Learning Engineer,145307,SGD,188899,SE,PT,Singapore,S,Chile,0,"Scala, Hadoop, MLOps, NLP, Java",Bachelor,5,Gaming,2024-05-17,2024-07-17,1974,8.5,Future Systems -AI02142,Robotics Engineer,77107,USD,77107,EN,FL,Norway,M,Norway,50,"Tableau, Kubernetes, Data Visualization",Bachelor,0,Consulting,2024-08-12,2024-08-30,527,5.8,Digital Transformation LLC -AI02143,AI Architect,67501,CAD,84376,EN,CT,Canada,S,Canada,0,"NLP, Tableau, Scala, PyTorch, SQL",PhD,1,Technology,2024-12-23,2025-02-20,720,6.4,Algorithmic Solutions -AI02144,Robotics Engineer,67669,USD,67669,EX,CT,China,M,China,100,"Deep Learning, Docker, Tableau",Bachelor,14,Gaming,2024-04-28,2024-06-09,1412,9.3,Cognitive Computing -AI02145,Head of AI,100999,EUR,85849,MI,FL,France,L,France,0,"MLOps, PyTorch, Kubernetes, Azure",Associate,2,Energy,2024-02-09,2024-04-02,2384,6.4,Algorithmic Solutions -AI02146,AI Consultant,57275,USD,57275,SE,CT,China,L,China,0,"Python, R, Azure",Associate,7,Real Estate,2025-01-23,2025-04-01,1686,9.4,Quantum Computing Inc -AI02147,Data Analyst,116317,USD,116317,EX,FT,Finland,S,Finland,0,"Data Visualization, Hadoop, Spark, Azure",Master,19,Energy,2024-01-24,2024-03-13,2115,5.8,Algorithmic Solutions -AI02148,Autonomous Systems Engineer,72220,USD,72220,EN,FT,United States,S,Argentina,50,"Statistics, Kubernetes, Mathematics",Bachelor,1,Education,2024-04-01,2024-05-18,1403,9.8,Autonomous Tech -AI02149,Computer Vision Engineer,48520,USD,48520,MI,CT,China,L,China,0,"Data Visualization, Python, TensorFlow, GCP, PyTorch",Associate,4,Transportation,2024-08-17,2024-09-03,1182,8.9,Predictive Systems -AI02150,AI Architect,91794,SGD,119332,MI,FT,Singapore,S,Russia,100,"Docker, Python, TensorFlow",Associate,4,Government,2024-10-23,2024-11-18,1817,9.2,Machine Intelligence Group -AI02151,Head of AI,148235,EUR,126000,SE,FL,Netherlands,L,Ireland,100,"Data Visualization, TensorFlow, Docker, Git",Associate,7,Manufacturing,2024-08-20,2024-09-07,2094,6.2,Neural Networks Co -AI02152,AI Software Engineer,63004,EUR,53553,EN,FL,Germany,S,Germany,100,"Azure, PyTorch, Docker, Kubernetes",PhD,1,Healthcare,2025-03-17,2025-04-28,1850,8.4,Future Systems -AI02153,Principal Data Scientist,256279,USD,256279,EX,PT,Finland,L,Finland,0,"Kubernetes, Python, Java, Linux",Master,13,Healthcare,2024-11-17,2025-01-25,573,6.5,Cognitive Computing -AI02154,Machine Learning Engineer,100220,USD,100220,MI,PT,United States,M,United States,100,"Kubernetes, Git, Scala, Statistics, GCP",Bachelor,2,Automotive,2025-03-09,2025-04-19,1993,9.5,Advanced Robotics -AI02155,Deep Learning Engineer,97614,CAD,122018,SE,CT,Canada,S,Canada,50,"Azure, Scala, SQL, Git",Master,7,Healthcare,2024-06-05,2024-06-25,1140,9.9,Cognitive Computing -AI02156,Data Engineer,128100,USD,128100,SE,FL,Sweden,S,Switzerland,100,"Python, AWS, Git, MLOps",PhD,7,Consulting,2024-09-05,2024-09-24,1215,10,Cloud AI Solutions -AI02157,AI Specialist,78590,USD,78590,EN,FL,Denmark,M,Denmark,50,"Python, Data Visualization, TensorFlow",Bachelor,0,Transportation,2025-03-11,2025-04-11,1220,8.7,DataVision Ltd -AI02158,Research Scientist,56489,USD,56489,EN,CT,United States,S,India,0,"Hadoop, Scala, Tableau, GCP",Master,0,Consulting,2024-08-10,2024-09-05,501,8.1,Predictive Systems -AI02159,Head of AI,145462,GBP,109097,SE,PT,United Kingdom,S,United Kingdom,100,"Git, NLP, Azure",PhD,9,Energy,2025-03-15,2025-05-09,2279,5.1,Quantum Computing Inc -AI02160,Robotics Engineer,114141,USD,114141,SE,FT,South Korea,M,South Korea,100,"Git, Java, Deep Learning, Scala, Mathematics",Master,9,Transportation,2024-03-30,2024-04-17,1412,8.6,Digital Transformation LLC -AI02161,Data Scientist,122099,USD,122099,SE,PT,Israel,S,Israel,100,"Azure, GCP, Python, TensorFlow",Bachelor,9,Media,2024-04-29,2024-06-30,1064,5.2,Digital Transformation LLC -AI02162,Data Engineer,109552,SGD,142418,SE,PT,Singapore,M,Singapore,0,"Linux, SQL, Kubernetes, Azure, Python",Master,7,Telecommunications,2024-08-28,2024-10-17,897,5.1,DeepTech Ventures -AI02163,AI Product Manager,57229,EUR,48645,EN,FT,Germany,S,Germany,0,"Kubernetes, Spark, Computer Vision, PyTorch",Associate,1,Manufacturing,2024-08-22,2024-10-10,831,6.6,Quantum Computing Inc -AI02164,NLP Engineer,174350,EUR,148198,EX,FL,France,M,France,100,"Kubernetes, SQL, Docker, Spark, R",Master,12,Technology,2024-08-14,2024-08-29,2021,6.8,Cognitive Computing -AI02165,AI Consultant,131413,USD,131413,SE,FL,Finland,L,Finland,0,"Java, GCP, Kubernetes",Master,6,Media,2024-05-26,2024-07-15,2012,5.7,Algorithmic Solutions -AI02166,NLP Engineer,109502,CAD,136878,SE,FT,Canada,S,Canada,100,"Data Visualization, SQL, R, PyTorch",Associate,7,Education,2025-04-21,2025-06-27,1888,7.3,DataVision Ltd -AI02167,Autonomous Systems Engineer,29846,USD,29846,MI,FL,India,S,India,50,"Spark, Deep Learning, Computer Vision",Master,4,Finance,2024-08-31,2024-10-06,2061,7.4,Future Systems -AI02168,Computer Vision Engineer,155786,USD,155786,SE,FT,Denmark,M,Portugal,0,"R, Computer Vision, Linux, Deep Learning",Master,8,Transportation,2025-04-12,2025-05-06,2317,5.1,Algorithmic Solutions -AI02169,Data Scientist,84770,USD,84770,EX,FT,India,M,India,100,"AWS, Tableau, Git, Deep Learning",Bachelor,17,Finance,2024-11-25,2024-12-28,1787,7.4,Algorithmic Solutions -AI02170,Computer Vision Engineer,89112,USD,89112,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Java, Python",PhD,2,Technology,2024-07-22,2024-08-06,669,6.1,DeepTech Ventures -AI02171,AI Specialist,104744,USD,104744,EN,FT,Denmark,L,United States,0,"Docker, Python, Scala",Master,1,Technology,2025-01-27,2025-04-03,2167,8,Predictive Systems -AI02172,Data Analyst,199544,USD,199544,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Docker, Hadoop, GCP, Linux",Bachelor,11,Education,2025-03-11,2025-04-01,2130,9.5,Quantum Computing Inc -AI02173,Machine Learning Engineer,93564,EUR,79529,MI,CT,France,S,Hungary,100,"SQL, Azure, Tableau, Java, Statistics",Bachelor,3,Energy,2024-01-05,2024-02-03,1181,6,AI Innovations -AI02174,AI Specialist,109257,AUD,147497,MI,PT,Australia,M,Australia,100,"Linux, Git, Statistics, R",PhD,2,Energy,2024-09-15,2024-11-10,1854,8.5,Advanced Robotics -AI02175,AI Product Manager,233827,EUR,198753,EX,FT,Austria,L,Sweden,100,"Kubernetes, R, SQL, AWS",Associate,19,Retail,2024-04-17,2024-05-09,2089,8.7,Algorithmic Solutions -AI02176,AI Specialist,199622,USD,199622,SE,CT,United States,L,United States,0,"TensorFlow, Deep Learning, MLOps, Git, Kubernetes",PhD,8,Consulting,2024-11-04,2024-11-25,1993,10,Cognitive Computing -AI02177,Data Analyst,158846,USD,158846,EX,PT,Sweden,S,Ukraine,50,"Python, Git, Scala, NLP",Bachelor,10,Technology,2025-03-29,2025-04-20,1386,9.9,Neural Networks Co -AI02178,AI Software Engineer,43785,USD,43785,EN,PT,Israel,S,Israel,100,"Statistics, SQL, Spark, Tableau",Bachelor,0,Telecommunications,2024-05-23,2024-07-07,2022,8.6,Neural Networks Co -AI02179,AI Architect,101184,USD,101184,EX,PT,China,S,Estonia,100,"Data Visualization, Docker, Python, Kubernetes",Master,10,Healthcare,2025-03-16,2025-04-20,513,8.3,Machine Intelligence Group -AI02180,Principal Data Scientist,89965,USD,89965,EX,FT,India,L,India,0,"Python, SQL, Computer Vision, Docker, Java",Associate,16,Manufacturing,2025-02-21,2025-03-20,2467,7.2,AI Innovations -AI02181,Principal Data Scientist,73352,SGD,95358,EN,PT,Singapore,L,Brazil,50,"Docker, Data Visualization, Python, Mathematics, R",Bachelor,0,Finance,2025-02-14,2025-04-08,954,7,Digital Transformation LLC -AI02182,Head of AI,199823,USD,199823,EX,CT,Finland,L,India,0,"Azure, Computer Vision, TensorFlow",Bachelor,11,Transportation,2024-07-22,2024-08-20,2424,5.4,Neural Networks Co -AI02183,ML Ops Engineer,77392,GBP,58044,EN,FL,United Kingdom,M,Latvia,50,"Python, Azure, TensorFlow, Statistics, AWS",PhD,1,Technology,2024-02-26,2024-04-01,841,6.5,Algorithmic Solutions -AI02184,Machine Learning Researcher,75898,CAD,94873,EN,FT,Canada,M,Portugal,0,"Git, PyTorch, SQL, Python",PhD,0,Education,2024-02-03,2024-03-26,1178,8.2,AI Innovations -AI02185,Data Analyst,76715,USD,76715,EN,PT,Israel,L,Israel,50,"Tableau, Hadoop, Deep Learning",PhD,0,Energy,2025-03-24,2025-05-12,756,6.7,DataVision Ltd -AI02186,Machine Learning Engineer,99717,JPY,10968870,MI,PT,Japan,M,Japan,50,"GCP, Azure, Linux, Scala",Master,3,Media,2024-02-18,2024-04-11,1134,7.3,Neural Networks Co -AI02187,AI Research Scientist,181613,USD,181613,EX,FL,Israel,L,Israel,50,"Scala, Linux, Java",Bachelor,11,Consulting,2024-08-02,2024-09-21,514,7.4,Cloud AI Solutions -AI02188,Autonomous Systems Engineer,109710,EUR,93254,MI,PT,Netherlands,L,Australia,100,"SQL, Linux, PyTorch, NLP",Bachelor,2,Energy,2024-04-06,2024-04-27,2356,6.3,Digital Transformation LLC -AI02189,AI Product Manager,195849,JPY,21543390,EX,PT,Japan,L,Japan,0,"Scala, Statistics, NLP",PhD,11,Finance,2024-03-18,2024-05-17,1271,6.8,Future Systems -AI02190,Data Scientist,125807,USD,125807,SE,FT,Sweden,L,Indonesia,0,"Python, Data Visualization, Docker, NLP",PhD,8,Media,2024-05-05,2024-05-31,1151,5.8,Digital Transformation LLC -AI02191,Research Scientist,104357,CHF,93921,MI,PT,Switzerland,M,Switzerland,100,"Java, AWS, Mathematics, Hadoop",Master,3,Government,2025-01-23,2025-02-10,1996,9.6,Smart Analytics -AI02192,Data Scientist,176952,EUR,150409,EX,CT,Netherlands,S,Netherlands,50,"Java, MLOps, R, Linux, NLP",Master,12,Transportation,2025-02-24,2025-03-12,2382,9.7,Smart Analytics -AI02193,Head of AI,57405,EUR,48794,EN,FL,France,M,France,100,"PyTorch, Computer Vision, Git, Azure, Scala",Master,1,Technology,2024-08-31,2024-09-26,605,7,Quantum Computing Inc -AI02194,Data Analyst,130621,EUR,111028,EX,FL,France,S,France,0,"Linux, Hadoop, Python, Computer Vision, Git",PhD,16,Real Estate,2024-05-13,2024-07-22,1072,8.9,Smart Analytics -AI02195,Research Scientist,78485,CAD,98106,EN,PT,Canada,L,Canada,0,"Scala, SQL, Statistics, Hadoop",PhD,0,Retail,2024-07-27,2024-09-20,1057,8,AI Innovations -AI02196,AI Consultant,200595,CHF,180536,SE,CT,Switzerland,M,South Africa,50,"Hadoop, Python, Deep Learning, Azure",Master,5,Media,2024-05-20,2024-07-12,2146,9.2,DeepTech Ventures -AI02197,AI Architect,50119,EUR,42601,EN,FL,France,M,France,0,"Docker, Azure, Computer Vision",PhD,1,Energy,2025-01-03,2025-03-01,2042,5.7,Smart Analytics -AI02198,Computer Vision Engineer,78348,EUR,66596,EN,FL,Germany,L,Czech Republic,0,"Tableau, Java, Kubernetes",Master,1,Finance,2024-08-22,2024-09-09,867,7.6,TechCorp Inc -AI02199,AI Software Engineer,158752,USD,158752,MI,FL,Norway,L,China,0,"Python, GCP, TensorFlow, Computer Vision, PyTorch",PhD,2,Energy,2024-02-19,2024-04-02,751,8.1,Smart Analytics -AI02200,Data Scientist,35696,USD,35696,MI,CT,India,L,India,100,"Scala, TensorFlow, Python, Computer Vision, Kubernetes",PhD,3,Transportation,2024-12-22,2025-02-17,2146,9.8,DataVision Ltd -AI02201,AI Architect,81558,AUD,110103,MI,PT,Australia,S,Portugal,50,"Python, Kubernetes, Deep Learning, AWS, MLOps",Master,4,Media,2024-06-03,2024-07-17,1216,9.3,Cognitive Computing -AI02202,AI Architect,240445,JPY,26448950,EX,PT,Japan,L,Japan,0,"Data Visualization, NLP, Python",PhD,12,Finance,2024-10-11,2024-12-10,2060,5.2,Predictive Systems -AI02203,Research Scientist,60197,USD,60197,SE,FT,China,M,Indonesia,100,"PyTorch, NLP, Hadoop, Statistics, Kubernetes",Master,5,Energy,2024-04-26,2024-07-06,2308,5.2,Machine Intelligence Group -AI02204,Deep Learning Engineer,67887,USD,67887,EN,FT,Norway,M,Norway,0,"PyTorch, Java, Spark, Hadoop, GCP",Bachelor,1,Transportation,2024-11-20,2025-01-22,1444,7.6,Autonomous Tech -AI02205,AI Research Scientist,251281,CAD,314101,EX,FL,Canada,L,Canada,50,"Data Visualization, Python, Azure, Scala, Spark",PhD,11,Transportation,2024-09-16,2024-11-14,1947,8.9,AI Innovations -AI02206,Data Engineer,266985,CHF,240287,EX,CT,Switzerland,L,New Zealand,50,"Tableau, PyTorch, Statistics",PhD,19,Automotive,2025-04-11,2025-04-25,889,7.1,Machine Intelligence Group -AI02207,AI Consultant,129783,EUR,110316,MI,FL,Netherlands,L,Netherlands,0,"Spark, Git, Statistics, PyTorch",Associate,4,Education,2024-01-11,2024-03-22,1435,6.1,Neural Networks Co -AI02208,Data Analyst,79996,GBP,59997,EN,FL,United Kingdom,L,United Kingdom,100,"Azure, GCP, Data Visualization",PhD,1,Healthcare,2024-08-22,2024-10-25,2334,8.6,Autonomous Tech -AI02209,Data Engineer,86496,CAD,108120,MI,FT,Canada,S,Canada,100,"Scala, Java, Mathematics, AWS, TensorFlow",PhD,2,Government,2025-01-17,2025-02-19,777,8.7,Advanced Robotics -AI02210,ML Ops Engineer,114996,USD,114996,MI,FT,Israel,L,Israel,50,"Scala, NLP, Hadoop",Master,4,Technology,2024-10-05,2024-11-13,820,5.7,Predictive Systems -AI02211,AI Architect,124110,USD,124110,SE,FL,Israel,L,Israel,0,"GCP, R, Tableau, Data Visualization, Scala",Bachelor,8,Media,2025-01-09,2025-03-08,975,5.6,Autonomous Tech -AI02212,AI Software Engineer,99108,USD,99108,SE,FT,South Korea,S,South Korea,100,"TensorFlow, Azure, Java, PyTorch, Computer Vision",Bachelor,5,Finance,2024-11-07,2024-12-28,895,6.2,Future Systems -AI02213,AI Product Manager,141155,CHF,127040,MI,PT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Tableau",PhD,3,Real Estate,2024-01-09,2024-02-05,1858,6.8,Future Systems -AI02214,AI Product Manager,71602,USD,71602,EN,FT,Ireland,M,Ireland,100,"Git, Computer Vision, Python, TensorFlow, NLP",Associate,1,Manufacturing,2024-06-14,2024-07-14,1203,7.7,Algorithmic Solutions -AI02215,Machine Learning Researcher,99305,USD,99305,EN,FT,Norway,L,Norway,100,"Kubernetes, SQL, NLP, Statistics",Master,1,Finance,2024-03-17,2024-05-29,1286,7.3,Digital Transformation LLC -AI02216,Machine Learning Engineer,268561,EUR,228277,EX,FT,France,L,India,0,"Git, Python, TensorFlow, Linux",PhD,17,Gaming,2025-02-19,2025-03-12,2172,6.4,AI Innovations -AI02217,AI Software Engineer,101510,CHF,91359,EN,CT,Switzerland,L,Austria,100,"SQL, Hadoop, PyTorch, Deep Learning",PhD,0,Gaming,2024-02-10,2024-03-04,1555,7,Machine Intelligence Group -AI02218,Principal Data Scientist,270963,USD,270963,EX,CT,Denmark,L,Austria,0,"MLOps, Statistics, GCP, PyTorch, Scala",PhD,13,Transportation,2024-10-20,2024-12-23,2253,6.3,Autonomous Tech -AI02219,AI Specialist,79001,USD,79001,MI,CT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker",PhD,4,Retail,2024-10-15,2024-12-18,1577,8.2,Machine Intelligence Group -AI02220,Principal Data Scientist,51039,GBP,38279,EN,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, R, Computer Vision",Master,0,Energy,2024-07-10,2024-08-23,527,5.9,Digital Transformation LLC -AI02221,ML Ops Engineer,86750,EUR,73738,EN,PT,Netherlands,L,Austria,50,"Java, Linux, Azure, GCP",Master,1,Energy,2025-04-21,2025-06-24,2026,8.5,DeepTech Ventures -AI02222,Research Scientist,52962,CAD,66203,EN,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Data Visualization, Python, Spark",Associate,1,Telecommunications,2024-07-20,2024-09-30,1427,6.8,Smart Analytics -AI02223,AI Software Engineer,253468,USD,253468,EX,CT,Sweden,M,Sweden,100,"Scala, R, Data Visualization, NLP, Python",Bachelor,19,Gaming,2024-08-12,2024-10-03,2402,7.5,TechCorp Inc -AI02224,AI Specialist,122016,EUR,103714,SE,PT,Germany,L,Australia,50,"Kubernetes, Hadoop, Tableau, PyTorch",Bachelor,7,Education,2024-11-10,2024-11-24,2156,9.1,Smart Analytics -AI02225,Research Scientist,51691,AUD,69783,EN,FT,Australia,S,Malaysia,50,"PyTorch, Linux, Git, TensorFlow, Deep Learning",PhD,1,Manufacturing,2024-03-11,2024-04-11,2158,9.4,DeepTech Ventures -AI02226,Principal Data Scientist,119127,USD,119127,EX,FT,Israel,S,Israel,0,"SQL, Tableau, MLOps",PhD,13,Finance,2025-02-01,2025-04-03,2048,6.3,Autonomous Tech -AI02227,Computer Vision Engineer,190161,USD,190161,EX,FL,Israel,S,Israel,100,"Azure, AWS, Statistics, GCP, Tableau",Associate,15,Technology,2024-05-12,2024-06-23,741,7.6,Smart Analytics -AI02228,Computer Vision Engineer,241186,USD,241186,EX,FT,Denmark,S,Denmark,0,"SQL, TensorFlow, Mathematics",PhD,14,Telecommunications,2024-09-23,2024-11-03,2069,6.3,Advanced Robotics -AI02229,Research Scientist,103949,CAD,129936,SE,CT,Canada,M,Czech Republic,50,"Kubernetes, Java, Data Visualization, MLOps",Associate,8,Education,2024-09-05,2024-10-20,1017,7.6,Smart Analytics -AI02230,Deep Learning Engineer,199232,USD,199232,EX,FT,Sweden,M,Sweden,100,"PyTorch, Data Visualization, Deep Learning",Bachelor,14,Government,2024-06-01,2024-06-18,1509,7.4,Advanced Robotics -AI02231,AI Research Scientist,157050,USD,157050,EX,PT,Sweden,S,Finland,0,"Tableau, Hadoop, R, Linux",PhD,17,Retail,2024-08-19,2024-09-18,852,7.4,Predictive Systems -AI02232,Computer Vision Engineer,84353,USD,84353,MI,PT,Israel,S,Luxembourg,0,"Azure, AWS, Computer Vision",Bachelor,2,Media,2024-08-26,2024-10-07,1724,7.8,Machine Intelligence Group -AI02233,Robotics Engineer,192697,USD,192697,EX,CT,Denmark,S,Denmark,50,"Java, PyTorch, Mathematics, Data Visualization, SQL",Master,12,Healthcare,2025-02-14,2025-03-09,2434,8.7,DeepTech Ventures -AI02234,NLP Engineer,154367,CAD,192959,SE,FT,Canada,L,Mexico,100,"Git, SQL, GCP, Tableau",PhD,5,Transportation,2024-12-12,2025-01-18,1287,5.1,Neural Networks Co -AI02235,Principal Data Scientist,305641,CHF,275077,EX,PT,Switzerland,S,Switzerland,0,"R, NLP, MLOps, Scala, Docker",Master,19,Transportation,2024-12-26,2025-03-08,674,7.7,Neural Networks Co -AI02236,Computer Vision Engineer,337542,CHF,303788,EX,FL,Switzerland,L,Netherlands,50,"Python, NLP, Tableau",PhD,15,Real Estate,2024-10-26,2025-01-07,1813,6.9,Machine Intelligence Group -AI02237,AI Software Engineer,82530,USD,82530,MI,CT,Finland,M,Germany,100,"Java, GCP, Kubernetes, MLOps",Bachelor,2,Technology,2024-08-13,2024-08-27,1062,5.3,Future Systems -AI02238,AI Specialist,183461,USD,183461,EX,CT,South Korea,L,South Korea,100,"Hadoop, Deep Learning, Data Visualization, Java",PhD,10,Telecommunications,2024-07-15,2024-09-08,2037,7.7,Digital Transformation LLC -AI02239,ML Ops Engineer,112033,USD,112033,SE,CT,Israel,M,Israel,50,"GCP, SQL, Data Visualization, Linux, Scala",Bachelor,9,Transportation,2024-01-29,2024-02-19,775,9.4,Cognitive Computing -AI02240,Deep Learning Engineer,121109,EUR,102943,MI,FL,Germany,L,India,100,"PyTorch, Tableau, MLOps, Linux",PhD,3,Healthcare,2024-07-13,2024-09-06,1184,6.8,Digital Transformation LLC -AI02241,NLP Engineer,208944,EUR,177602,EX,FT,Austria,S,Austria,100,"Data Visualization, R, AWS, Azure",Bachelor,16,Technology,2024-09-27,2024-10-27,924,5.5,AI Innovations -AI02242,AI Product Manager,60646,CAD,75808,EN,PT,Canada,L,Canada,50,"TensorFlow, MLOps, Python, AWS",Master,1,Gaming,2024-01-17,2024-03-29,1189,6.8,Neural Networks Co -AI02243,AI Architect,83782,EUR,71215,MI,FT,Germany,M,Germany,100,"Kubernetes, Statistics, MLOps",Associate,2,Transportation,2024-07-14,2024-07-31,1645,7,Algorithmic Solutions -AI02244,Research Scientist,130792,USD,130792,EX,FL,Finland,S,United Kingdom,0,"Spark, Kubernetes, Data Visualization, Python, Linux",Associate,14,Gaming,2025-04-11,2025-04-26,697,8.4,AI Innovations -AI02245,Head of AI,98316,USD,98316,SE,FL,South Korea,M,South Korea,50,"Linux, Hadoop, SQL",Associate,9,Education,2025-02-16,2025-03-14,1669,7.8,Digital Transformation LLC -AI02246,AI Software Engineer,157782,EUR,134115,SE,PT,Netherlands,M,Netherlands,100,"Git, Python, SQL, Deep Learning, Spark",Bachelor,9,Retail,2025-01-01,2025-02-27,709,5.6,Smart Analytics -AI02247,Computer Vision Engineer,54428,USD,54428,EN,PT,South Korea,M,Netherlands,50,"TensorFlow, Mathematics, Tableau, Kubernetes, Linux",Master,0,Manufacturing,2024-10-26,2024-11-19,1158,5.2,DeepTech Ventures -AI02248,Autonomous Systems Engineer,90867,EUR,77237,MI,FT,Germany,L,Germany,50,"Azure, Git, Hadoop",PhD,2,Education,2025-04-16,2025-06-04,634,9.7,Advanced Robotics -AI02249,Machine Learning Researcher,67221,EUR,57138,EN,FT,Austria,S,Austria,50,"Scala, Hadoop, Computer Vision, GCP",Master,1,Technology,2024-05-05,2024-05-29,2072,7.1,Digital Transformation LLC -AI02250,Principal Data Scientist,154303,EUR,131158,EX,FL,France,M,France,100,"Linux, Git, Tableau",Master,17,Manufacturing,2024-05-23,2024-06-22,2153,7.8,Cloud AI Solutions -AI02251,Data Engineer,100244,CHF,90220,EN,FT,Switzerland,S,Russia,0,"Kubernetes, Java, Docker",Associate,1,Healthcare,2025-03-16,2025-05-11,1905,9.8,Machine Intelligence Group -AI02252,Principal Data Scientist,135424,USD,135424,SE,PT,Denmark,S,New Zealand,100,"Tableau, Azure, Git",PhD,5,Automotive,2024-07-08,2024-08-16,562,7,Quantum Computing Inc -AI02253,AI Research Scientist,61375,EUR,52169,EN,PT,France,S,France,100,"Computer Vision, Python, TensorFlow",Bachelor,0,Automotive,2024-12-20,2025-02-24,1802,9.5,Algorithmic Solutions -AI02254,AI Consultant,113261,USD,113261,MI,PT,Sweden,L,Sweden,0,"Tableau, Python, GCP, TensorFlow",PhD,4,Real Estate,2024-12-04,2025-01-12,1918,8.7,Autonomous Tech -AI02255,AI Product Manager,114736,EUR,97526,SE,PT,Austria,S,Mexico,0,"Python, Computer Vision, GCP, MLOps, Data Visualization",Master,9,Government,2024-04-21,2024-05-08,2032,5.1,Machine Intelligence Group -AI02256,NLP Engineer,48296,USD,48296,MI,PT,China,M,Chile,50,"SQL, Java, Python",Associate,2,Government,2024-08-27,2024-11-01,1041,6.4,Cognitive Computing -AI02257,AI Software Engineer,205168,USD,205168,EX,CT,Sweden,L,Sweden,100,"Spark, TensorFlow, NLP, Computer Vision",Associate,10,Real Estate,2024-10-27,2024-11-15,2325,7.7,Cognitive Computing -AI02258,Data Engineer,44379,USD,44379,SE,FL,China,S,China,0,"Python, Docker, Tableau, Kubernetes",Bachelor,7,Energy,2024-03-28,2024-05-16,2495,6.4,Neural Networks Co -AI02259,Head of AI,89555,AUD,120899,EN,FL,Australia,L,Austria,100,"Azure, Git, Computer Vision, SQL, Scala",Master,1,Telecommunications,2025-01-28,2025-02-28,608,8.8,Cloud AI Solutions -AI02260,Head of AI,186544,CAD,233180,EX,FL,Canada,L,South Africa,0,"AWS, Spark, PyTorch, Linux",Master,15,Automotive,2024-08-14,2024-09-08,990,9.5,Autonomous Tech -AI02261,Deep Learning Engineer,130260,USD,130260,MI,FL,Norway,M,Norway,50,"AWS, Deep Learning, Java, Linux",Associate,3,Finance,2024-04-28,2024-06-13,543,5.1,TechCorp Inc -AI02262,AI Specialist,61880,USD,61880,EX,FT,India,S,India,100,"Spark, Git, Scala",Bachelor,14,Media,2025-01-05,2025-03-18,2089,6.2,Smart Analytics -AI02263,Robotics Engineer,185105,EUR,157339,EX,FT,France,M,France,50,"TensorFlow, Data Visualization, Spark",PhD,11,Real Estate,2024-11-11,2024-12-16,944,6,Neural Networks Co -AI02264,AI Consultant,60068,EUR,51058,EN,CT,Netherlands,M,Netherlands,0,"Docker, Git, R, Linux, Scala",Bachelor,1,Technology,2024-03-07,2024-03-23,1856,5.8,Quantum Computing Inc -AI02265,AI Product Manager,152832,JPY,16811520,SE,FL,Japan,L,Japan,100,"Linux, PyTorch, TensorFlow",Master,9,Consulting,2025-02-01,2025-03-15,2241,7.9,TechCorp Inc -AI02266,AI Consultant,163684,AUD,220973,SE,CT,Australia,L,Belgium,0,"TensorFlow, Python, Spark, Java",Associate,5,Automotive,2024-05-01,2024-07-04,2186,9.7,Future Systems -AI02267,Machine Learning Engineer,51675,AUD,69761,EN,PT,Australia,M,Australia,50,"Git, Scala, Computer Vision, Java, Deep Learning",Bachelor,0,Healthcare,2025-01-08,2025-02-02,1966,5.3,Cloud AI Solutions -AI02268,Principal Data Scientist,270523,USD,270523,EX,PT,Norway,S,Thailand,100,"SQL, MLOps, PyTorch, TensorFlow, Tableau",Associate,12,Gaming,2024-06-16,2024-07-30,1569,9.7,TechCorp Inc -AI02269,Principal Data Scientist,138679,EUR,117877,SE,PT,France,M,Finland,100,"Statistics, Tableau, Linux",Master,8,Retail,2024-11-10,2024-12-30,681,6.2,Autonomous Tech -AI02270,Data Scientist,153448,GBP,115086,EX,PT,United Kingdom,S,United Kingdom,100,"PyTorch, TensorFlow, Hadoop, Kubernetes, R",Bachelor,16,Manufacturing,2024-11-26,2024-12-10,2074,9.7,Quantum Computing Inc -AI02271,Autonomous Systems Engineer,99198,CHF,89278,EN,FL,Switzerland,M,Malaysia,100,"PyTorch, NLP, Git, Azure, Mathematics",PhD,0,Education,2024-01-27,2024-03-20,916,6.3,DeepTech Ventures -AI02272,AI Architect,108736,EUR,92426,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, TensorFlow, Java, SQL, Azure",Associate,6,Automotive,2024-11-28,2024-12-21,1268,7.8,AI Innovations -AI02273,AI Product Manager,108349,EUR,92097,SE,PT,Netherlands,S,Netherlands,0,"Linux, MLOps, NLP",Bachelor,8,Education,2025-02-14,2025-04-25,944,5.1,Cloud AI Solutions -AI02274,AI Consultant,97976,USD,97976,SE,FL,Finland,M,Finland,100,"TensorFlow, Kubernetes, Deep Learning, Scala, Azure",Associate,9,Telecommunications,2024-01-05,2024-02-12,1332,5.6,TechCorp Inc -AI02275,Data Engineer,106852,USD,106852,MI,FT,Sweden,L,United States,50,"Kubernetes, SQL, GCP, Computer Vision",PhD,2,Automotive,2024-07-21,2024-09-01,2193,9.1,Algorithmic Solutions -AI02276,AI Research Scientist,157337,CHF,141603,SE,CT,Switzerland,S,Italy,100,"Scala, PyTorch, MLOps, SQL",Bachelor,5,Retail,2024-06-24,2024-07-30,1623,6.4,Digital Transformation LLC -AI02277,Data Engineer,119797,CHF,107817,EN,FT,Switzerland,L,Switzerland,50,"Python, Linux, Deep Learning",Associate,0,Telecommunications,2024-06-27,2024-07-27,624,6.4,Neural Networks Co -AI02278,Machine Learning Researcher,69161,USD,69161,EX,FL,India,M,India,100,"Deep Learning, TensorFlow, Kubernetes, Statistics",Master,15,Healthcare,2024-07-31,2024-09-18,997,5.6,Machine Intelligence Group -AI02279,Data Engineer,138491,AUD,186963,EX,FL,Australia,M,Australia,50,"Deep Learning, TensorFlow, Linux",Bachelor,18,Government,2024-12-19,2025-01-26,839,5.6,Autonomous Tech -AI02280,AI Product Manager,103654,GBP,77741,MI,FL,United Kingdom,M,United Kingdom,0,"GCP, Python, Docker",Associate,2,Real Estate,2025-04-05,2025-04-26,591,9.9,TechCorp Inc -AI02281,Deep Learning Engineer,61991,USD,61991,EN,CT,Ireland,S,Ireland,50,"Mathematics, Python, AWS, TensorFlow, Scala",Bachelor,0,Retail,2024-11-06,2025-01-11,2413,7.5,Autonomous Tech -AI02282,AI Research Scientist,81076,EUR,68915,EN,CT,Austria,L,Austria,100,"Python, Linux, MLOps, TensorFlow, Azure",Master,0,Consulting,2025-03-28,2025-06-09,927,7.4,Digital Transformation LLC -AI02283,Data Engineer,84481,USD,84481,MI,CT,Israel,S,Israel,100,"Mathematics, Data Visualization, TensorFlow",Master,4,Government,2024-06-24,2024-08-08,1198,8.5,Autonomous Tech -AI02284,Machine Learning Engineer,31910,USD,31910,MI,FL,China,S,Singapore,0,"TensorFlow, SQL, Mathematics, NLP",Bachelor,2,Technology,2024-04-05,2024-06-06,1846,7.7,Cognitive Computing -AI02285,Principal Data Scientist,103659,AUD,139940,MI,PT,Australia,L,Australia,50,"Docker, SQL, NLP, GCP, MLOps",Bachelor,2,Media,2024-03-02,2024-04-08,2362,9.8,Predictive Systems -AI02286,Machine Learning Researcher,241811,AUD,326445,EX,CT,Australia,L,Romania,0,"PyTorch, GCP, Python, Spark, MLOps",PhD,19,Government,2024-06-11,2024-08-06,2082,8.8,Smart Analytics -AI02287,Principal Data Scientist,85528,EUR,72699,MI,PT,Netherlands,M,Netherlands,50,"NLP, Mathematics, Java, R",Associate,3,Technology,2024-12-18,2025-01-21,927,8.4,Algorithmic Solutions -AI02288,Research Scientist,233646,SGD,303740,EX,CT,Singapore,M,Singapore,0,"Statistics, SQL, Computer Vision, Linux, Deep Learning",Bachelor,12,Real Estate,2024-06-23,2024-08-03,2210,5.6,Digital Transformation LLC -AI02289,AI Specialist,180558,USD,180558,EX,PT,Denmark,M,Denmark,100,"GCP, Computer Vision, Java",PhD,10,Finance,2025-04-24,2025-05-31,1812,6.5,DeepTech Ventures -AI02290,Data Scientist,94791,EUR,80572,MI,CT,Germany,L,Germany,100,"TensorFlow, Statistics, Kubernetes, PyTorch, R",Master,3,Government,2024-04-08,2024-05-05,1246,6.5,Machine Intelligence Group -AI02291,Robotics Engineer,189914,USD,189914,EX,FT,United States,M,United States,0,"TensorFlow, Hadoop, Linux, Scala",Bachelor,17,Energy,2025-04-27,2025-06-30,2134,7.6,TechCorp Inc -AI02292,Machine Learning Researcher,96777,GBP,72583,MI,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, PyTorch, Java",Associate,3,Education,2024-07-05,2024-07-19,2490,5.5,Quantum Computing Inc -AI02293,AI Architect,29644,USD,29644,MI,PT,India,L,Norway,100,"Hadoop, Python, SQL, Deep Learning, Azure",Associate,4,Gaming,2024-03-20,2024-04-26,825,8.1,Future Systems -AI02294,Autonomous Systems Engineer,191246,USD,191246,EX,CT,United States,L,Kenya,50,"TensorFlow, Python, AWS, R, PyTorch",Bachelor,16,Technology,2025-02-23,2025-05-06,2386,5.7,AI Innovations -AI02295,Data Analyst,74691,USD,74691,MI,CT,South Korea,L,South Korea,50,"MLOps, Tableau, AWS, Linux",Associate,4,Telecommunications,2024-01-09,2024-03-01,1718,7.9,Autonomous Tech -AI02296,NLP Engineer,94955,JPY,10445050,EN,PT,Japan,L,Japan,0,"Spark, R, MLOps, Kubernetes, Azure",Bachelor,1,Automotive,2024-12-19,2025-01-14,2392,9.9,Smart Analytics -AI02297,Robotics Engineer,174201,USD,174201,SE,PT,Norway,M,Norway,50,"Java, Docker, Tableau, Statistics, MLOps",Bachelor,9,Real Estate,2025-02-05,2025-03-14,1951,7.3,DataVision Ltd -AI02298,Machine Learning Researcher,110906,CHF,99815,MI,FL,Switzerland,M,Switzerland,100,"Linux, Spark, Hadoop",PhD,3,Energy,2024-10-05,2024-12-01,2406,9.8,Cloud AI Solutions -AI02299,Research Scientist,129560,SGD,168428,SE,CT,Singapore,S,Singapore,100,"Scala, Java, MLOps",Master,9,Government,2024-08-05,2024-10-02,2483,9.5,Quantum Computing Inc -AI02300,Deep Learning Engineer,56552,AUD,76345,EN,PT,Australia,M,Australia,0,"MLOps, Python, GCP, SQL, Linux",Master,1,Retail,2024-09-01,2024-10-01,1431,8,Machine Intelligence Group -AI02301,AI Product Manager,82665,USD,82665,SE,FT,China,L,Finland,100,"Kubernetes, R, Java, SQL, NLP",Master,6,Gaming,2024-01-26,2024-02-13,1960,7,DataVision Ltd -AI02302,AI Specialist,57257,USD,57257,EN,CT,Ireland,S,Ireland,50,"Deep Learning, MLOps, Hadoop, GCP",Bachelor,0,Healthcare,2024-04-12,2024-04-27,1328,9.7,Machine Intelligence Group -AI02303,Deep Learning Engineer,156738,USD,156738,SE,FT,United States,S,United States,50,"Spark, Scala, Mathematics",PhD,8,Transportation,2024-07-31,2024-08-22,1295,6.4,Cognitive Computing -AI02304,Data Analyst,105347,EUR,89545,SE,CT,Netherlands,S,Netherlands,0,"Linux, R, MLOps",Bachelor,6,Consulting,2024-01-27,2024-03-05,2296,9.4,Advanced Robotics -AI02305,AI Product Manager,223454,JPY,24579940,EX,FT,Japan,S,Japan,100,"Computer Vision, R, PyTorch, GCP",Associate,19,Retail,2025-02-25,2025-03-17,510,5.4,DeepTech Ventures -AI02306,Machine Learning Engineer,72740,USD,72740,MI,PT,Finland,M,Netherlands,0,"GCP, Linux, MLOps, Tableau",Bachelor,3,Media,2025-01-08,2025-02-14,2001,5.1,Autonomous Tech -AI02307,Research Scientist,107622,USD,107622,MI,PT,Ireland,L,Ireland,50,"Git, SQL, PyTorch",Associate,4,Telecommunications,2024-03-06,2024-04-05,602,5.9,TechCorp Inc -AI02308,Principal Data Scientist,150523,EUR,127945,EX,CT,France,S,France,100,"Java, NLP, AWS",Master,18,Education,2024-11-20,2024-12-30,1927,6.8,Neural Networks Co -AI02309,Data Scientist,134704,EUR,114498,SE,FT,Austria,L,Malaysia,0,"Statistics, SQL, GCP, NLP",PhD,5,Manufacturing,2024-08-02,2024-08-27,2230,9.1,AI Innovations -AI02310,Research Scientist,51843,USD,51843,EN,CT,Finland,S,Sweden,0,"Kubernetes, Hadoop, Java, Computer Vision, Tableau",Master,1,Technology,2024-08-25,2024-10-16,797,7.3,TechCorp Inc -AI02311,AI Research Scientist,81429,EUR,69215,MI,FL,Germany,M,Germany,50,"Linux, Git, GCP, AWS, Spark",Master,3,Healthcare,2025-02-14,2025-03-02,2079,5.8,AI Innovations -AI02312,Deep Learning Engineer,208862,CAD,261078,EX,FL,Canada,L,Canada,50,"MLOps, Tableau, Git, Python, Scala",Associate,13,Gaming,2024-06-20,2024-07-25,1901,5.6,Neural Networks Co -AI02313,Machine Learning Engineer,90374,USD,90374,SE,FT,Israel,S,Israel,50,"R, Tableau, Azure, SQL",Master,7,Media,2024-07-10,2024-09-17,1887,9.5,Algorithmic Solutions -AI02314,AI Consultant,61463,EUR,52244,MI,PT,France,S,France,100,"Scala, Azure, MLOps, Python",Associate,3,Finance,2024-11-24,2025-01-11,2182,6,Machine Intelligence Group -AI02315,Deep Learning Engineer,109194,USD,109194,SE,CT,Finland,M,Finland,50,"R, Computer Vision, GCP",Associate,7,Technology,2024-04-01,2024-06-05,1756,7.6,Quantum Computing Inc -AI02316,AI Software Engineer,170066,USD,170066,EX,CT,South Korea,S,Thailand,0,"Data Visualization, Python, PyTorch",Associate,18,Education,2024-05-31,2024-07-18,835,6.1,Quantum Computing Inc -AI02317,Machine Learning Engineer,130203,USD,130203,SE,FL,Sweden,M,Sweden,100,"SQL, Statistics, R, MLOps, Hadoop",Bachelor,5,Education,2024-04-27,2024-06-22,1041,8.1,Algorithmic Solutions -AI02318,Robotics Engineer,92631,USD,92631,MI,CT,United States,M,United States,50,"AWS, Java, Python, GCP, Tableau",Associate,2,Transportation,2024-12-12,2025-01-11,2185,7,Cloud AI Solutions -AI02319,Data Analyst,124406,EUR,105745,SE,CT,France,S,France,50,"Computer Vision, PyTorch, Linux, AWS, SQL",PhD,6,Transportation,2024-01-15,2024-02-21,1041,9.3,Quantum Computing Inc -AI02320,Machine Learning Researcher,81253,USD,81253,MI,FL,Israel,M,Israel,0,"Azure, Git, NLP, Deep Learning, TensorFlow",Bachelor,4,Retail,2024-11-18,2025-01-13,2045,7.4,DeepTech Ventures -AI02321,Data Analyst,94671,EUR,80470,MI,CT,Germany,M,Germany,0,"PyTorch, Kubernetes, Mathematics",Associate,4,Automotive,2024-07-01,2024-08-11,1911,8.4,Smart Analytics -AI02322,Data Scientist,104689,USD,104689,MI,FL,Ireland,M,Ireland,50,"Tableau, Python, TensorFlow, Hadoop",Bachelor,2,Gaming,2024-01-02,2024-03-05,1563,5.7,DeepTech Ventures -AI02323,Research Scientist,124477,EUR,105805,SE,PT,Netherlands,L,Netherlands,100,"Java, R, SQL, Git",Associate,7,Government,2024-02-22,2024-03-17,655,8.5,Future Systems -AI02324,Machine Learning Engineer,225013,EUR,191261,EX,PT,Netherlands,S,Argentina,0,"SQL, Python, Java",PhD,17,Transportation,2024-08-18,2024-09-09,1668,7,Future Systems -AI02325,AI Specialist,57156,USD,57156,EN,PT,Finland,M,Finland,100,"GCP, MLOps, PyTorch",PhD,0,Technology,2024-10-24,2024-12-09,1115,8.4,Machine Intelligence Group -AI02326,Robotics Engineer,75630,USD,75630,MI,PT,Israel,S,Israel,100,"NLP, Mathematics, MLOps, Docker",Associate,2,Finance,2024-11-30,2025-02-07,1371,5.3,Cognitive Computing -AI02327,Data Scientist,193038,USD,193038,EX,CT,Israel,M,Israel,50,"GCP, Linux, MLOps, Mathematics, AWS",PhD,12,Automotive,2024-08-30,2024-10-30,2331,8.4,Predictive Systems -AI02328,ML Ops Engineer,354091,USD,354091,EX,FT,Norway,L,Thailand,0,"Java, Scala, GCP, Mathematics, MLOps",Master,15,Gaming,2024-05-26,2024-06-24,2237,9.6,Autonomous Tech -AI02329,Computer Vision Engineer,116471,CAD,145589,MI,FL,Canada,L,Canada,50,"Statistics, Linux, Azure, Kubernetes, Computer Vision",Master,4,Real Estate,2025-03-04,2025-05-13,1445,6,Neural Networks Co -AI02330,Computer Vision Engineer,52386,EUR,44528,EN,PT,France,M,Thailand,100,"Python, Kubernetes, Data Visualization, TensorFlow",Master,1,Manufacturing,2025-04-27,2025-06-09,1561,8.3,Cloud AI Solutions -AI02331,AI Specialist,23595,USD,23595,EN,CT,China,S,China,100,"NLP, Python, TensorFlow",Associate,1,Retail,2024-08-13,2024-10-13,1556,7.7,Predictive Systems -AI02332,AI Research Scientist,123617,AUD,166883,EX,FL,Australia,S,Australia,0,"MLOps, Mathematics, Python, TensorFlow, Git",Associate,17,Transportation,2024-07-07,2024-09-07,838,5.6,Quantum Computing Inc -AI02333,Robotics Engineer,294173,USD,294173,EX,FT,United States,L,Switzerland,0,"SQL, GCP, Tableau, TensorFlow, Python",Master,16,Media,2025-01-25,2025-02-22,1739,5.6,DeepTech Ventures -AI02334,Data Engineer,158889,USD,158889,SE,FT,United States,L,Netherlands,100,"AWS, Hadoop, Deep Learning, Mathematics, SQL",Master,9,Technology,2024-01-20,2024-03-27,1615,6.4,Future Systems -AI02335,Research Scientist,92187,USD,92187,SE,PT,Israel,S,Spain,0,"Data Visualization, Computer Vision, GCP, Scala, NLP",PhD,8,Telecommunications,2024-08-25,2024-09-22,1474,5.5,Quantum Computing Inc -AI02336,ML Ops Engineer,266476,EUR,226505,EX,PT,France,L,France,0,"Azure, Hadoop, Data Visualization, Spark",Bachelor,18,Gaming,2024-02-22,2024-04-22,886,8.2,Autonomous Tech -AI02337,Data Scientist,64951,EUR,55208,EN,FL,Netherlands,S,Austria,0,"PyTorch, Kubernetes, Java, Azure, MLOps",Master,1,Media,2024-03-15,2024-04-23,1222,9.2,DeepTech Ventures -AI02338,AI Research Scientist,173215,EUR,147233,EX,CT,Netherlands,M,Netherlands,50,"Computer Vision, AWS, Python, TensorFlow, Data Visualization",PhD,19,Telecommunications,2024-02-15,2024-03-15,733,5.1,TechCorp Inc -AI02339,Machine Learning Researcher,114900,USD,114900,MI,PT,Denmark,M,Indonesia,0,"Python, Kubernetes, Git",Bachelor,3,Retail,2024-12-17,2025-02-27,1669,9.5,Future Systems -AI02340,AI Consultant,65123,USD,65123,MI,FT,Finland,S,Finland,0,"SQL, R, AWS, Python",PhD,3,Manufacturing,2025-02-10,2025-03-22,1882,9.2,Smart Analytics -AI02341,AI Consultant,176135,EUR,149715,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Deep Learning, SQL, NLP",Bachelor,17,Automotive,2024-02-18,2024-03-21,512,9.6,Neural Networks Co -AI02342,AI Specialist,128894,USD,128894,EX,FL,South Korea,M,South Korea,100,"Scala, AWS, MLOps, Data Visualization, Statistics",Bachelor,15,Telecommunications,2024-01-24,2024-03-25,2001,8.2,TechCorp Inc -AI02343,AI Specialist,140129,CAD,175161,EX,CT,Canada,M,Canada,0,"Java, Python, GCP",Bachelor,15,Finance,2024-03-19,2024-05-25,1796,6.1,AI Innovations -AI02344,Head of AI,211366,EUR,179661,EX,CT,Austria,S,Austria,100,"R, SQL, Kubernetes, Git, Tableau",Associate,17,Consulting,2025-03-30,2025-04-14,1025,6.6,Future Systems -AI02345,Data Scientist,89067,GBP,66800,MI,FT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Tableau, Git",Master,2,Government,2024-03-23,2024-06-03,1133,8,Predictive Systems -AI02346,Deep Learning Engineer,120608,AUD,162821,SE,FL,Australia,S,Spain,100,"Python, TensorFlow, Data Visualization",Master,9,Healthcare,2024-10-23,2024-11-26,2358,5.9,Advanced Robotics -AI02347,AI Research Scientist,173641,CAD,217051,EX,FL,Canada,S,Canada,0,"Python, Linux, Scala, TensorFlow, R",Bachelor,11,Healthcare,2025-01-20,2025-02-28,2102,5.6,DeepTech Ventures -AI02348,AI Research Scientist,93978,JPY,10337580,MI,PT,Japan,L,Austria,50,"Python, Git, Kubernetes, TensorFlow, Scala",PhD,2,Manufacturing,2025-02-06,2025-03-13,1541,5,Cognitive Computing -AI02349,Data Analyst,291451,CHF,262306,EX,PT,Switzerland,S,Switzerland,100,"Python, TensorFlow, PyTorch, SQL, Hadoop",Associate,18,Education,2024-10-05,2024-12-14,2356,5.5,Cognitive Computing -AI02350,Data Engineer,115058,USD,115058,MI,FL,Denmark,L,Denmark,100,"Scala, NLP, Python, Deep Learning",Master,4,Consulting,2024-03-26,2024-05-10,2092,7.1,Predictive Systems -AI02351,Head of AI,121394,USD,121394,MI,PT,Norway,M,Norway,100,"Linux, Kubernetes, MLOps, PyTorch",PhD,4,Gaming,2024-10-18,2024-12-23,1538,6.8,DeepTech Ventures -AI02352,AI Specialist,51431,USD,51431,MI,CT,China,L,China,50,"Deep Learning, Git, Mathematics, Data Visualization, R",Bachelor,4,Manufacturing,2024-05-31,2024-06-17,2302,7.1,Smart Analytics -AI02353,Robotics Engineer,90064,USD,90064,MI,FT,United States,M,United States,0,"Python, TensorFlow, Computer Vision, Kubernetes",Associate,3,Real Estate,2025-01-29,2025-03-28,1740,8.5,Future Systems -AI02354,Data Scientist,120867,JPY,13295370,SE,PT,Japan,S,Australia,50,"Java, R, Tableau",Associate,6,Retail,2024-03-31,2024-04-29,2008,5.7,Cloud AI Solutions -AI02355,Data Engineer,51975,EUR,44179,EN,FT,Netherlands,S,South Africa,100,"Git, Docker, MLOps",PhD,0,Retail,2024-03-21,2024-04-29,1266,5.5,Cognitive Computing -AI02356,AI Product Manager,125213,EUR,106431,SE,FL,Netherlands,S,Netherlands,50,"R, AWS, Azure",Associate,7,Manufacturing,2024-07-26,2024-09-20,1233,9.9,Machine Intelligence Group -AI02357,AI Specialist,73632,EUR,62587,EN,FL,Netherlands,L,Netherlands,100,"Git, Kubernetes, Spark",Master,0,Automotive,2024-09-23,2024-10-10,2163,7.7,DeepTech Ventures -AI02358,AI Consultant,147336,USD,147336,SE,CT,Israel,L,Israel,50,"Hadoop, Scala, PyTorch, TensorFlow, Python",Master,9,Healthcare,2024-03-12,2024-05-03,2452,8.1,Cloud AI Solutions -AI02359,Data Engineer,113940,JPY,12533400,SE,FL,Japan,S,France,0,"Java, AWS, Linux, GCP, Docker",Associate,7,Transportation,2024-01-28,2024-03-21,1981,6.4,TechCorp Inc -AI02360,Robotics Engineer,115793,EUR,98424,SE,PT,Netherlands,M,Austria,0,"GCP, Statistics, Hadoop",Associate,5,Retail,2025-04-16,2025-06-07,2490,6.9,Digital Transformation LLC -AI02361,Research Scientist,385250,CHF,346725,EX,CT,Switzerland,L,China,0,"Kubernetes, SQL, Docker, Java, Python",Associate,19,Retail,2024-12-31,2025-02-20,2183,6.5,Smart Analytics -AI02362,ML Ops Engineer,97449,EUR,82832,EN,FT,Netherlands,L,Belgium,50,"Linux, Tableau, Python, Deep Learning, TensorFlow",Associate,0,Manufacturing,2024-02-11,2024-03-10,665,5.2,Machine Intelligence Group -AI02363,Autonomous Systems Engineer,158205,EUR,134474,EX,CT,France,L,Mexico,100,"Scala, Linux, Docker, Statistics",Associate,12,Healthcare,2024-08-12,2024-08-27,656,8.8,Predictive Systems -AI02364,Machine Learning Researcher,227940,SGD,296322,EX,FL,Singapore,L,Finland,0,"GCP, Java, SQL",Associate,11,Consulting,2024-09-27,2024-11-13,1038,9.3,Smart Analytics -AI02365,AI Specialist,82774,USD,82774,MI,PT,Israel,L,Sweden,50,"TensorFlow, Java, Deep Learning, Spark",Associate,3,Technology,2024-02-27,2024-04-01,1190,7.9,TechCorp Inc -AI02366,Data Engineer,151102,CHF,135992,SE,CT,Switzerland,S,China,0,"SQL, TensorFlow, AWS, NLP",Associate,6,Real Estate,2024-12-19,2025-01-24,1992,8.7,Advanced Robotics -AI02367,Computer Vision Engineer,135010,USD,135010,MI,CT,Norway,M,Ireland,50,"Statistics, AWS, PyTorch, Data Visualization, Spark",PhD,4,Retail,2025-01-01,2025-02-03,589,6.2,Algorithmic Solutions -AI02368,Head of AI,99493,JPY,10944230,MI,FL,Japan,S,Japan,100,"Deep Learning, Tableau, SQL",PhD,2,Energy,2024-06-25,2024-07-22,2338,8.6,TechCorp Inc -AI02369,AI Product Manager,104842,GBP,78632,MI,CT,United Kingdom,L,Australia,50,"Azure, Scala, AWS, TensorFlow, Statistics",Master,2,Healthcare,2025-03-15,2025-05-26,1211,8.6,Cloud AI Solutions -AI02370,Head of AI,77587,USD,77587,EN,FT,Sweden,L,Estonia,100,"TensorFlow, Linux, R",Master,0,Manufacturing,2024-05-06,2024-06-05,2238,8,Smart Analytics -AI02371,ML Ops Engineer,94792,SGD,123230,MI,FL,Singapore,L,Singapore,50,"AWS, MLOps, Python, TensorFlow",Master,4,Transportation,2024-03-06,2024-05-11,695,6.8,Autonomous Tech -AI02372,AI Consultant,170382,EUR,144825,SE,PT,Netherlands,L,Netherlands,0,"Statistics, Scala, Java",PhD,6,Manufacturing,2024-12-09,2025-01-30,1927,7.3,Autonomous Tech -AI02373,AI Consultant,69714,USD,69714,EN,PT,Finland,M,Switzerland,100,"Scala, Linux, Python",Associate,0,Manufacturing,2024-04-15,2024-06-03,1972,5.9,Quantum Computing Inc -AI02374,AI Specialist,61848,USD,61848,EN,FT,Ireland,L,Ireland,100,"Hadoop, Data Visualization, Python, PyTorch, Deep Learning",PhD,0,Real Estate,2025-01-10,2025-03-05,651,8,Quantum Computing Inc -AI02375,Computer Vision Engineer,65280,EUR,55488,EN,CT,Netherlands,M,Netherlands,100,"Azure, PyTorch, Spark, SQL",PhD,0,Retail,2024-11-04,2024-12-08,1890,6.5,Neural Networks Co -AI02376,Deep Learning Engineer,67421,USD,67421,EN,PT,United States,S,Sweden,50,"Docker, Tableau, Kubernetes, SQL, GCP",PhD,0,Real Estate,2025-02-15,2025-04-10,2051,8.7,Advanced Robotics -AI02377,Data Engineer,276843,USD,276843,EX,FL,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, GCP",PhD,11,Retail,2024-08-10,2024-09-09,740,6.2,Cognitive Computing -AI02378,Computer Vision Engineer,86366,USD,86366,MI,CT,Norway,S,Norway,0,"Statistics, AWS, Kubernetes, Computer Vision, GCP",PhD,4,Education,2024-01-16,2024-03-28,1664,7.7,DataVision Ltd -AI02379,AI Specialist,113593,SGD,147671,SE,PT,Singapore,M,Singapore,100,"SQL, Data Visualization, Tableau, TensorFlow",PhD,9,Real Estate,2024-04-06,2024-06-16,1375,6,Neural Networks Co -AI02380,Autonomous Systems Engineer,248477,USD,248477,EX,CT,United States,L,Austria,100,"Git, TensorFlow, Linux, NLP, Docker",Associate,17,Telecommunications,2024-08-08,2024-08-28,2245,7.4,Machine Intelligence Group -AI02381,Head of AI,140516,USD,140516,SE,FL,Israel,M,Israel,0,"Python, Kubernetes, Tableau, AWS, Computer Vision",Bachelor,5,Real Estate,2024-02-06,2024-04-01,2138,5.8,Algorithmic Solutions -AI02382,ML Ops Engineer,101660,USD,101660,MI,CT,Israel,M,Israel,50,"Tableau, GCP, Hadoop",Master,4,Telecommunications,2025-01-08,2025-02-01,1455,5.1,AI Innovations -AI02383,NLP Engineer,59401,AUD,80191,EN,PT,Australia,S,Australia,0,"Statistics, Python, MLOps, Data Visualization",Associate,1,Real Estate,2025-02-22,2025-03-11,2022,6.2,DataVision Ltd -AI02384,Machine Learning Researcher,282872,CHF,254585,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, SQL, Mathematics",Master,16,Consulting,2024-10-20,2024-11-14,1004,7.7,TechCorp Inc -AI02385,AI Consultant,79004,USD,79004,EN,FL,Denmark,S,Denmark,50,"R, PyTorch, Mathematics",Bachelor,1,Government,2024-10-07,2024-11-22,1888,9,Digital Transformation LLC -AI02386,Autonomous Systems Engineer,90214,USD,90214,EX,CT,China,L,China,100,"Java, PyTorch, SQL, NLP",PhD,14,Healthcare,2024-11-23,2024-12-08,1536,6.3,Machine Intelligence Group -AI02387,NLP Engineer,177517,USD,177517,EX,PT,Denmark,S,Denmark,0,"PyTorch, Tableau, Java, GCP, R",PhD,10,Consulting,2024-05-02,2024-06-22,1170,9.2,TechCorp Inc -AI02388,Research Scientist,138067,USD,138067,SE,PT,Denmark,S,Denmark,100,"Linux, GCP, R, Mathematics",PhD,6,Automotive,2024-05-19,2024-07-17,1830,5.3,Predictive Systems -AI02389,AI Product Manager,175216,EUR,148934,SE,FL,Germany,L,Austria,100,"Linux, Statistics, Data Visualization",Bachelor,6,Retail,2024-10-24,2024-12-14,909,7.9,Quantum Computing Inc -AI02390,Machine Learning Engineer,67149,EUR,57077,EN,PT,France,M,France,0,"Data Visualization, Kubernetes, Spark",Master,0,Telecommunications,2024-12-10,2025-02-06,840,8.6,Advanced Robotics -AI02391,AI Consultant,65086,USD,65086,EN,CT,Sweden,L,Sweden,0,"Data Visualization, PyTorch, Kubernetes, Azure",Associate,1,Government,2024-11-10,2025-01-22,1761,8.1,Predictive Systems -AI02392,Principal Data Scientist,97236,USD,97236,MI,PT,Denmark,S,Ireland,0,"Spark, SQL, Computer Vision",PhD,3,Manufacturing,2024-10-15,2024-12-04,2272,6.9,Advanced Robotics -AI02393,Data Analyst,33499,USD,33499,MI,PT,India,L,India,50,"Data Visualization, R, Linux, GCP",Bachelor,2,Energy,2025-04-03,2025-05-15,1644,8.9,Quantum Computing Inc -AI02394,Data Analyst,83973,EUR,71377,MI,FL,France,S,France,0,"GCP, SQL, Git",PhD,2,Energy,2024-04-15,2024-06-18,2438,7.1,Neural Networks Co -AI02395,AI Software Engineer,77052,USD,77052,MI,CT,Ireland,S,Ireland,50,"GCP, Hadoop, TensorFlow, Deep Learning, AWS",Associate,2,Education,2024-10-08,2024-11-07,1146,9.3,Autonomous Tech -AI02396,NLP Engineer,121702,SGD,158213,SE,FT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Kubernetes, Data Visualization, Java",Bachelor,5,Transportation,2024-07-15,2024-08-09,1798,6.5,Advanced Robotics -AI02397,Data Scientist,226834,USD,226834,EX,CT,Norway,L,Norway,0,"PyTorch, SQL, NLP, R",Master,14,Finance,2024-11-19,2025-01-27,1368,8.2,DataVision Ltd -AI02398,AI Specialist,269663,GBP,202247,EX,FL,United Kingdom,L,Singapore,100,"Mathematics, Git, SQL, TensorFlow",Master,13,Government,2024-08-10,2024-09-15,1189,8.7,AI Innovations -AI02399,ML Ops Engineer,121309,USD,121309,SE,FT,Sweden,L,Sweden,100,"SQL, Deep Learning, Tableau",PhD,7,Real Estate,2024-09-11,2024-10-01,1599,7.5,AI Innovations -AI02400,Machine Learning Researcher,81603,USD,81603,MI,FT,South Korea,S,South Korea,100,"Python, Mathematics, Data Visualization, Scala, Azure",Bachelor,2,Consulting,2025-04-19,2025-06-11,927,9.5,Predictive Systems -AI02401,AI Architect,101849,USD,101849,MI,PT,Denmark,S,France,0,"Python, Azure, TensorFlow",PhD,2,Telecommunications,2024-07-16,2024-09-24,546,8.6,Algorithmic Solutions -AI02402,Deep Learning Engineer,184180,JPY,20259800,SE,PT,Japan,L,Ukraine,0,"Tableau, TensorFlow, GCP, Data Visualization",PhD,9,Automotive,2024-11-15,2024-12-28,2001,7.7,Algorithmic Solutions -AI02403,AI Architect,117248,USD,117248,EN,CT,Denmark,L,Denmark,100,"Docker, Kubernetes, Statistics, Tableau, Python",PhD,0,Education,2024-07-20,2024-08-07,624,7.9,Future Systems -AI02404,Machine Learning Researcher,95725,JPY,10529750,MI,CT,Japan,S,Japan,0,"AWS, Linux, Kubernetes, Data Visualization",Bachelor,4,Media,2025-03-27,2025-05-05,720,6.6,Smart Analytics -AI02405,Computer Vision Engineer,101075,EUR,85914,MI,CT,Germany,M,Germany,0,"TensorFlow, Statistics, Spark, Linux",Bachelor,2,Healthcare,2024-05-19,2024-06-18,2308,5.7,Autonomous Tech -AI02406,AI Architect,138619,CAD,173274,SE,PT,Canada,M,Canada,50,"Kubernetes, PyTorch, Linux, AWS",Bachelor,9,Telecommunications,2025-01-01,2025-01-15,690,7.3,Machine Intelligence Group -AI02407,Data Engineer,138645,AUD,187171,SE,CT,Australia,L,Australia,100,"Deep Learning, Mathematics, PyTorch",Bachelor,5,Finance,2024-10-28,2024-12-18,1590,9.7,TechCorp Inc -AI02408,AI Product Manager,55621,EUR,47278,EN,CT,Netherlands,M,Netherlands,50,"R, Python, Computer Vision, Deep Learning",Bachelor,1,Healthcare,2025-02-04,2025-04-04,684,7.8,Quantum Computing Inc -AI02409,Head of AI,135303,EUR,115008,SE,FL,Germany,L,Germany,100,"AWS, Git, SQL, Docker, Statistics",Bachelor,7,Retail,2024-09-14,2024-09-29,2317,7.9,Neural Networks Co -AI02410,Data Scientist,172436,USD,172436,SE,FT,United States,L,United States,50,"Tableau, Hadoop, Python",Associate,6,Real Estate,2025-03-07,2025-03-31,1364,5.4,Neural Networks Co -AI02411,Data Scientist,152590,AUD,205997,EX,PT,Australia,M,Australia,50,"GCP, Python, NLP, Computer Vision, Data Visualization",Bachelor,17,Finance,2024-08-12,2024-09-02,1932,9.5,DataVision Ltd -AI02412,AI Specialist,110412,USD,110412,SE,PT,Finland,L,Austria,50,"Docker, Spark, Hadoop, Git, SQL",Master,5,Healthcare,2024-03-01,2024-03-17,2307,8.4,Autonomous Tech -AI02413,Data Analyst,98339,GBP,73754,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, Python, Java, Linux",Bachelor,8,Retail,2024-05-09,2024-05-30,1819,7.5,Quantum Computing Inc -AI02414,Machine Learning Engineer,68002,USD,68002,EN,FT,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, Python",Bachelor,0,Consulting,2024-10-04,2024-11-29,1489,5.7,Cloud AI Solutions -AI02415,Data Engineer,187944,JPY,20673840,EX,CT,Japan,S,Germany,50,"Python, SQL, TensorFlow",Associate,10,Retail,2024-08-02,2024-08-29,1862,9.4,Cognitive Computing -AI02416,Autonomous Systems Engineer,50316,USD,50316,EN,CT,Sweden,S,France,100,"Linux, Docker, Data Visualization, PyTorch, Deep Learning",Bachelor,1,Education,2024-02-10,2024-04-07,1983,9.2,Neural Networks Co -AI02417,Data Analyst,104865,USD,104865,MI,FT,Denmark,M,Denmark,100,"NLP, Python, Java, Statistics",Master,2,Gaming,2024-09-02,2024-10-28,608,7.7,Cloud AI Solutions -AI02418,Deep Learning Engineer,79547,EUR,67615,MI,FL,France,S,France,50,"Statistics, Java, Data Visualization, Computer Vision, Linux",Bachelor,4,Government,2024-06-07,2024-08-17,2315,7.9,Future Systems -AI02419,Data Analyst,48817,USD,48817,EN,PT,Israel,S,Singapore,50,"Linux, R, Git, Kubernetes, Statistics",Bachelor,0,Energy,2024-01-02,2024-02-19,2161,8.2,Algorithmic Solutions -AI02420,Deep Learning Engineer,60358,EUR,51304,EN,FT,France,M,France,50,"Git, Scala, Tableau",PhD,1,Government,2025-01-24,2025-03-09,2400,8.9,DeepTech Ventures -AI02421,Data Scientist,36483,USD,36483,EN,CT,China,M,China,100,"AWS, Java, Tableau, Python",Bachelor,1,Real Estate,2024-12-19,2025-02-03,2044,7,Predictive Systems -AI02422,AI Specialist,34602,USD,34602,MI,CT,India,S,India,50,"Scala, TensorFlow, MLOps, Spark, Deep Learning",Bachelor,4,Consulting,2025-02-05,2025-02-21,2409,9.4,Advanced Robotics -AI02423,Data Scientist,183641,CHF,165277,SE,FL,Switzerland,S,Ukraine,50,"Mathematics, PyTorch, Spark, Scala, AWS",Master,8,Government,2025-01-11,2025-02-04,2248,9.1,AI Innovations -AI02424,Principal Data Scientist,137861,USD,137861,MI,CT,Denmark,M,Denmark,0,"Scala, Mathematics, Computer Vision, Deep Learning",Associate,4,Technology,2024-05-27,2024-07-17,988,8,Cloud AI Solutions -AI02425,Data Engineer,55797,EUR,47427,EN,PT,France,S,France,100,"GCP, Scala, Spark, Python",PhD,0,Manufacturing,2024-06-26,2024-08-06,2194,9.5,DeepTech Ventures -AI02426,Principal Data Scientist,60447,CAD,75559,EN,CT,Canada,L,Canada,50,"Scala, Tableau, Azure, Spark, SQL",Master,1,Retail,2024-03-05,2024-04-25,2068,7,DataVision Ltd -AI02427,Head of AI,188935,EUR,160595,EX,FT,Austria,L,Austria,0,"Java, AWS, R",PhD,14,Retail,2025-01-29,2025-03-12,1647,5,AI Innovations -AI02428,Data Engineer,74196,USD,74196,EX,FL,India,L,India,50,"TensorFlow, Python, Git, Hadoop",Associate,19,Education,2024-03-06,2024-04-22,910,8.1,Machine Intelligence Group -AI02429,AI Architect,171635,CHF,154472,SE,FL,Switzerland,S,Switzerland,100,"R, Tableau, Spark, SQL, Computer Vision",Bachelor,9,Gaming,2024-07-23,2024-09-07,2310,6.8,Neural Networks Co -AI02430,AI Architect,71217,EUR,60534,EN,CT,Netherlands,M,Netherlands,0,"Python, NLP, TensorFlow, AWS",Master,0,Government,2024-06-15,2024-07-02,2397,5.9,Quantum Computing Inc -AI02431,Data Scientist,55275,GBP,41456,EN,CT,United Kingdom,S,United Kingdom,0,"PyTorch, NLP, Java, Python, Docker",Bachelor,1,Technology,2025-04-02,2025-06-08,933,6.2,Autonomous Tech -AI02432,Machine Learning Engineer,63318,USD,63318,EN,CT,Ireland,S,Vietnam,50,"SQL, GCP, PyTorch, Kubernetes",Associate,1,Finance,2025-01-26,2025-02-25,937,9.7,Algorithmic Solutions -AI02433,AI Specialist,102417,USD,102417,MI,CT,South Korea,L,South Korea,50,"Linux, SQL, PyTorch",Master,2,Transportation,2024-08-15,2024-09-01,2253,8.2,AI Innovations -AI02434,Deep Learning Engineer,145507,USD,145507,SE,FT,Ireland,L,Ireland,0,"Deep Learning, Python, NLP, GCP, Git",Master,8,Real Estate,2024-07-08,2024-08-04,1577,8,Neural Networks Co -AI02435,Machine Learning Engineer,70110,EUR,59594,EN,FL,Germany,S,Finland,0,"Kubernetes, Python, Data Visualization",Master,1,Education,2025-01-01,2025-02-12,680,5.1,Autonomous Tech -AI02436,AI Research Scientist,171213,USD,171213,EX,CT,South Korea,M,South Korea,0,"Git, Docker, Deep Learning, Kubernetes, Statistics",PhD,10,Retail,2025-01-06,2025-02-28,731,5.8,Autonomous Tech -AI02437,Robotics Engineer,84500,USD,84500,MI,PT,Sweden,M,Turkey,0,"Spark, Python, TensorFlow, SQL",Associate,4,Consulting,2025-01-15,2025-03-22,1603,9.2,Cognitive Computing -AI02438,Machine Learning Researcher,156224,USD,156224,EX,FL,Israel,S,Israel,0,"Data Visualization, NLP, Java, R, Mathematics",Bachelor,15,Telecommunications,2024-07-07,2024-09-17,2135,9.7,Predictive Systems -AI02439,Research Scientist,92098,USD,92098,MI,FL,Sweden,S,Sweden,0,"TensorFlow, Mathematics, MLOps, Computer Vision",Associate,3,Retail,2025-04-23,2025-05-20,825,5.1,Future Systems -AI02440,Principal Data Scientist,167891,USD,167891,EX,FT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, Deep Learning",Master,15,Government,2024-03-16,2024-05-28,2352,7,Cognitive Computing -AI02441,Data Engineer,101538,SGD,131999,MI,CT,Singapore,S,France,0,"Kubernetes, Data Visualization, Python, Statistics, AWS",PhD,4,Telecommunications,2024-08-01,2024-10-07,2037,5.9,Machine Intelligence Group -AI02442,Computer Vision Engineer,156055,CAD,195069,SE,PT,Canada,L,Canada,100,"Python, SQL, TensorFlow, GCP",PhD,9,Consulting,2024-10-23,2024-12-21,865,9.5,DeepTech Ventures -AI02443,Principal Data Scientist,97531,EUR,82901,MI,PT,Germany,S,Malaysia,50,"Git, Scala, Python",PhD,4,Healthcare,2025-02-13,2025-03-29,1379,6.9,AI Innovations -AI02444,Deep Learning Engineer,66041,USD,66041,EN,CT,Sweden,S,Sweden,0,"GCP, Kubernetes, Docker",Associate,0,Telecommunications,2024-08-16,2024-10-25,746,7.9,AI Innovations -AI02445,Principal Data Scientist,78618,EUR,66825,EN,FL,Germany,M,Turkey,50,"Python, Azure, Scala, Hadoop",Master,1,Education,2025-04-25,2025-05-29,633,8.3,Advanced Robotics -AI02446,Data Scientist,63321,JPY,6965310,EN,CT,Japan,S,Japan,0,"Python, TensorFlow, PyTorch",Associate,1,Government,2024-05-03,2024-07-04,2329,8.4,Autonomous Tech -AI02447,Machine Learning Researcher,171661,AUD,231742,EX,CT,Australia,S,Australia,50,"PyTorch, Hadoop, Computer Vision",Bachelor,14,Government,2024-04-17,2024-06-06,2090,5.7,DeepTech Ventures -AI02448,Data Engineer,65836,CAD,82295,EN,CT,Canada,S,Luxembourg,100,"Scala, Statistics, PyTorch",Master,0,Energy,2025-03-21,2025-04-14,2090,5.3,Quantum Computing Inc -AI02449,Machine Learning Engineer,27320,USD,27320,EN,CT,India,L,India,0,"Python, Kubernetes, Tableau, PyTorch",Bachelor,0,Energy,2025-04-07,2025-06-15,1130,7.5,Cognitive Computing -AI02450,AI Specialist,135041,EUR,114785,SE,CT,Germany,S,Germany,100,"SQL, Kubernetes, Statistics, Hadoop",Associate,5,Energy,2024-07-20,2024-08-29,1002,5.8,Autonomous Tech -AI02451,AI Specialist,113501,USD,113501,SE,PT,United States,S,United States,0,"Spark, Docker, Python, Kubernetes",Master,5,Automotive,2024-01-29,2024-02-29,2412,9.8,Smart Analytics -AI02452,NLP Engineer,84009,USD,84009,EN,FT,Denmark,S,Denmark,50,"Kubernetes, R, Azure, AWS",Master,1,Retail,2024-12-07,2025-02-15,1122,6.1,TechCorp Inc -AI02453,Data Scientist,202038,CAD,252548,EX,FT,Canada,S,Canada,0,"Tableau, TensorFlow, Scala",Associate,17,Government,2024-10-08,2024-10-26,2244,7.4,Cloud AI Solutions -AI02454,AI Research Scientist,157447,USD,157447,SE,PT,Norway,M,Nigeria,0,"R, Python, Git, NLP, Java",Master,5,Healthcare,2024-02-18,2024-04-03,2450,8.4,Future Systems -AI02455,Research Scientist,69117,USD,69117,EX,FL,China,S,South Korea,50,"Scala, Docker, Kubernetes",PhD,16,Government,2025-04-12,2025-05-04,517,8.7,Neural Networks Co -AI02456,AI Consultant,85916,SGD,111691,MI,FT,Singapore,S,Ireland,50,"Scala, Python, Data Visualization, NLP",Associate,2,Gaming,2024-12-19,2025-02-21,2108,5.7,Predictive Systems -AI02457,NLP Engineer,208144,EUR,176922,EX,FL,France,S,France,100,"Hadoop, MLOps, Spark, Git",Master,16,Technology,2024-06-01,2024-07-03,922,9.3,Machine Intelligence Group -AI02458,Computer Vision Engineer,201845,CAD,252306,EX,FT,Canada,L,Canada,100,"Data Visualization, Kubernetes, Scala, AWS, TensorFlow",Associate,11,Energy,2024-11-29,2025-02-05,1453,6.8,Neural Networks Co -AI02459,AI Software Engineer,70992,AUD,95839,EN,FL,Australia,S,Austria,0,"R, Data Visualization, AWS, Scala",PhD,0,Media,2024-05-01,2024-05-20,1609,6.8,DeepTech Ventures -AI02460,Computer Vision Engineer,78762,EUR,66948,MI,FL,Netherlands,S,Malaysia,50,"AWS, Azure, Docker, Hadoop, TensorFlow",Associate,4,Gaming,2024-06-08,2024-06-26,1864,7.5,Advanced Robotics -AI02461,Autonomous Systems Engineer,124250,USD,124250,SE,CT,South Korea,M,United Kingdom,0,"Linux, PyTorch, Kubernetes",PhD,9,Finance,2025-04-16,2025-05-27,1031,7.5,Future Systems -AI02462,AI Architect,79482,USD,79482,EN,PT,Norway,M,South Korea,0,"Computer Vision, Spark, Linux, Deep Learning",Associate,0,Healthcare,2024-09-30,2024-10-14,1803,5.6,Neural Networks Co -AI02463,Machine Learning Engineer,139133,EUR,118263,SE,CT,France,M,France,0,"Hadoop, SQL, Computer Vision, PyTorch",Master,6,Energy,2024-09-11,2024-10-28,1604,7.3,Digital Transformation LLC -AI02464,Computer Vision Engineer,220326,USD,220326,EX,FT,Norway,L,Norway,100,"PyTorch, Linux, TensorFlow, Azure, Hadoop",Master,10,Retail,2025-03-12,2025-05-11,1484,5.1,Autonomous Tech -AI02465,Machine Learning Researcher,56936,USD,56936,SE,FT,China,L,China,0,"Spark, Python, Tableau",Associate,7,Automotive,2024-09-14,2024-11-24,2347,6.1,Machine Intelligence Group -AI02466,Data Scientist,186597,SGD,242576,EX,FL,Singapore,M,Singapore,100,"Git, PyTorch, TensorFlow, Hadoop",PhD,12,Manufacturing,2024-09-12,2024-10-28,796,8.1,Quantum Computing Inc -AI02467,Autonomous Systems Engineer,98276,EUR,83535,MI,CT,Netherlands,M,South Korea,100,"Computer Vision, Hadoop, SQL",Associate,4,Finance,2024-09-29,2024-12-04,1681,7.8,Quantum Computing Inc -AI02468,Machine Learning Researcher,265980,EUR,226083,EX,FT,Netherlands,M,Netherlands,0,"Azure, Kubernetes, Tableau, Computer Vision, Statistics",Master,18,Consulting,2025-01-20,2025-02-15,1629,7.3,Neural Networks Co -AI02469,Principal Data Scientist,28831,USD,28831,EN,CT,China,S,Kenya,0,"Computer Vision, SQL, PyTorch, Docker, TensorFlow",Master,1,Energy,2024-09-23,2024-11-10,1887,7,DeepTech Ventures -AI02470,Machine Learning Engineer,41710,USD,41710,SE,FT,India,S,Mexico,100,"Docker, Java, Hadoop",Master,5,Finance,2024-06-11,2024-07-17,1648,9.4,Advanced Robotics -AI02471,AI Software Engineer,183499,JPY,20184890,SE,FT,Japan,L,Japan,0,"NLP, Git, Python, Java",Associate,8,Technology,2024-05-07,2024-06-21,1918,6.6,Cognitive Computing -AI02472,NLP Engineer,106203,CAD,132754,SE,PT,Canada,S,Canada,50,"Scala, Hadoop, Tableau, SQL, Deep Learning",Associate,6,Telecommunications,2024-06-02,2024-06-25,869,8.1,DataVision Ltd -AI02473,AI Architect,165971,USD,165971,EX,FL,Denmark,S,Denmark,0,"Docker, Hadoop, GCP",Associate,16,Consulting,2024-02-24,2024-05-06,584,7.4,Neural Networks Co -AI02474,Deep Learning Engineer,124861,USD,124861,MI,PT,Denmark,L,Denmark,0,"Kubernetes, Deep Learning, Scala, Java",Associate,4,Retail,2025-01-28,2025-04-11,2295,6,Smart Analytics -AI02475,AI Research Scientist,90314,USD,90314,MI,CT,Ireland,S,Ireland,0,"MLOps, NLP, PyTorch, Kubernetes",Associate,2,Education,2024-01-01,2024-01-18,1471,5.2,Cognitive Computing -AI02476,Data Engineer,82549,USD,82549,EN,PT,Denmark,S,Denmark,100,"Tableau, Java, SQL, Computer Vision, Kubernetes",Associate,0,Manufacturing,2024-03-05,2024-04-14,2066,6.2,DataVision Ltd -AI02477,ML Ops Engineer,24960,USD,24960,EN,FT,India,M,Norway,100,"Kubernetes, Hadoop, Java, Mathematics, Deep Learning",Associate,0,Retail,2025-04-16,2025-05-19,1088,7.1,DeepTech Ventures -AI02478,Deep Learning Engineer,106178,AUD,143340,MI,PT,Australia,M,Australia,0,"PyTorch, GCP, Kubernetes, Statistics, Computer Vision",Associate,3,Government,2024-03-30,2024-06-10,1148,5.2,Cognitive Computing -AI02479,Principal Data Scientist,136353,CHF,122718,MI,FT,Switzerland,M,Switzerland,100,"NLP, Azure, Tableau",Bachelor,4,Technology,2024-04-25,2024-06-29,1915,6.1,Algorithmic Solutions -AI02480,Machine Learning Researcher,140620,USD,140620,MI,FT,Denmark,L,Denmark,50,"NLP, Spark, Scala",Master,4,Technology,2025-03-20,2025-04-15,825,5.1,Predictive Systems -AI02481,Machine Learning Researcher,261035,USD,261035,EX,FT,Finland,L,Finland,50,"Python, AWS, Statistics, TensorFlow, NLP",Master,10,Technology,2024-03-14,2024-04-08,1299,8,Algorithmic Solutions -AI02482,Robotics Engineer,119849,SGD,155804,MI,CT,Singapore,L,Singapore,0,"SQL, PyTorch, Computer Vision",Master,3,Government,2024-04-09,2024-05-27,1022,6.5,Smart Analytics -AI02483,AI Consultant,58782,EUR,49965,EN,CT,Germany,S,Germany,50,"Hadoop, Linux, SQL, Computer Vision",Associate,1,Telecommunications,2025-03-24,2025-04-26,1785,7.7,Machine Intelligence Group -AI02484,Autonomous Systems Engineer,77795,GBP,58346,EN,FL,United Kingdom,L,United Kingdom,100,"Tableau, Python, Mathematics, Scala",Master,0,Gaming,2024-12-02,2025-01-30,1815,6.5,AI Innovations -AI02485,Data Analyst,162430,EUR,138066,EX,FT,Austria,M,Austria,0,"SQL, Scala, AWS, MLOps, NLP",Bachelor,15,Retail,2025-02-04,2025-03-07,621,7.6,DeepTech Ventures -AI02486,Robotics Engineer,156099,JPY,17170890,SE,FT,Japan,M,Poland,0,"Deep Learning, PyTorch, R",Associate,7,Gaming,2025-01-07,2025-01-30,2171,6.5,Predictive Systems -AI02487,NLP Engineer,105660,USD,105660,SE,FL,South Korea,M,South Korea,0,"Spark, PyTorch, Tableau, Statistics, AWS",Bachelor,6,Government,2024-11-30,2024-12-28,1284,6.4,TechCorp Inc -AI02488,ML Ops Engineer,100617,USD,100617,MI,PT,Finland,M,Ireland,0,"Docker, Scala, Data Visualization, NLP",Associate,2,Manufacturing,2025-04-04,2025-05-20,871,6.8,Cognitive Computing -AI02489,Deep Learning Engineer,85747,JPY,9432170,EN,PT,Japan,L,Japan,0,"GCP, Linux, SQL",Associate,0,Government,2024-07-26,2024-08-21,1790,8.8,DataVision Ltd -AI02490,AI Product Manager,103946,SGD,135130,MI,CT,Singapore,M,Singapore,0,"SQL, AWS, Tableau, Java, R",Master,3,Finance,2025-01-14,2025-03-22,2223,9.5,Advanced Robotics -AI02491,Deep Learning Engineer,163429,USD,163429,SE,PT,United States,L,Colombia,100,"Statistics, GCP, TensorFlow, Tableau",PhD,6,Real Estate,2025-04-18,2025-06-25,829,9.2,TechCorp Inc -AI02492,NLP Engineer,134989,CHF,121490,SE,CT,Switzerland,S,Ghana,100,"Azure, Deep Learning, Docker",Bachelor,8,Transportation,2024-05-27,2024-07-16,1154,6.9,Digital Transformation LLC -AI02493,AI Architect,232913,USD,232913,EX,PT,Israel,L,Israel,0,"AWS, MLOps, Data Visualization",PhD,14,Consulting,2025-03-19,2025-04-16,955,5.3,Cloud AI Solutions -AI02494,Machine Learning Researcher,72913,CHF,65622,EN,PT,Switzerland,S,Switzerland,0,"Scala, Python, TensorFlow, Spark, Linux",Master,1,Automotive,2024-06-13,2024-08-24,913,5.9,Neural Networks Co -AI02495,NLP Engineer,62004,CAD,77505,EN,CT,Canada,S,Poland,50,"TensorFlow, Statistics, Hadoop",Master,0,Government,2025-03-09,2025-05-19,2303,7.7,TechCorp Inc -AI02496,Head of AI,54572,USD,54572,EN,FL,Israel,S,Finland,100,"NLP, Scala, PyTorch",Bachelor,0,Retail,2025-04-27,2025-07-03,2392,8,Advanced Robotics -AI02497,Data Scientist,304083,CHF,273675,EX,FL,Switzerland,S,Switzerland,100,"Kubernetes, AWS, Python, Git",Master,15,Transportation,2024-06-20,2024-08-18,1922,7,Autonomous Tech -AI02498,Head of AI,263203,AUD,355324,EX,FL,Australia,L,Australia,0,"Java, Kubernetes, Tableau",PhD,18,Automotive,2024-08-26,2024-09-25,1516,8.6,DeepTech Ventures -AI02499,Machine Learning Researcher,78835,EUR,67010,EN,CT,Germany,L,Brazil,0,"Computer Vision, AWS, Data Visualization, Hadoop, PyTorch",Associate,1,Retail,2024-09-28,2024-11-29,2474,9.1,DeepTech Ventures -AI02500,AI Specialist,91165,USD,91165,EX,PT,China,M,China,0,"AWS, Spark, Git",PhD,10,Education,2024-08-02,2024-08-28,700,9,Quantum Computing Inc -AI02501,Robotics Engineer,141371,USD,141371,SE,PT,Finland,M,Turkey,100,"Java, Git, Mathematics, GCP, Hadoop",Bachelor,7,Consulting,2024-10-25,2024-12-27,1708,5.6,Quantum Computing Inc -AI02502,AI Architect,176050,EUR,149643,EX,FL,Austria,S,Austria,0,"Python, MLOps, TensorFlow",Associate,14,Gaming,2024-04-03,2024-05-04,1629,6.5,Advanced Robotics -AI02503,Research Scientist,164808,USD,164808,SE,PT,Norway,S,Norway,50,"Docker, SQL, Kubernetes, Java",Master,6,Real Estate,2024-08-17,2024-09-11,705,6.4,Cognitive Computing -AI02504,Principal Data Scientist,73825,USD,73825,MI,FL,South Korea,S,South Korea,50,"Spark, SQL, Computer Vision",Associate,3,Manufacturing,2025-01-24,2025-02-18,1905,6.6,TechCorp Inc -AI02505,Data Scientist,56305,USD,56305,EN,FT,Finland,M,Finland,100,"Java, Statistics, Git, Hadoop",Bachelor,0,Consulting,2024-06-29,2024-07-22,904,7.7,Advanced Robotics -AI02506,Computer Vision Engineer,95982,SGD,124777,MI,FT,Singapore,S,Singapore,0,"Scala, Spark, Tableau, SQL",Master,4,Telecommunications,2024-04-20,2024-06-29,2187,7.5,Machine Intelligence Group -AI02507,Robotics Engineer,139813,EUR,118841,EX,FL,France,S,France,100,"Python, Linux, Kubernetes",Bachelor,12,Automotive,2024-08-06,2024-08-27,2393,6.7,Quantum Computing Inc -AI02508,AI Architect,103705,CAD,129631,MI,PT,Canada,L,Canada,0,"Docker, Java, PyTorch",Bachelor,2,Finance,2024-01-12,2024-03-12,1589,6.5,TechCorp Inc -AI02509,AI Product Manager,90682,EUR,77080,MI,FT,Austria,M,Austria,100,"Computer Vision, Tableau, GCP",Master,2,Transportation,2025-03-08,2025-04-06,2327,7.9,Algorithmic Solutions -AI02510,Autonomous Systems Engineer,71388,EUR,60680,EN,PT,Netherlands,S,Belgium,50,"Linux, Git, Kubernetes",Associate,1,Manufacturing,2024-09-19,2024-11-16,1567,7,TechCorp Inc -AI02511,Deep Learning Engineer,96336,USD,96336,MI,PT,Israel,M,Vietnam,100,"Java, Linux, Tableau, Scala",Master,2,Transportation,2024-10-28,2024-12-19,2444,9.1,Advanced Robotics -AI02512,Deep Learning Engineer,128679,USD,128679,EX,CT,Finland,M,Finland,0,"R, Python, Linux",Master,10,Transportation,2024-06-29,2024-08-04,1288,8.4,Neural Networks Co -AI02513,Robotics Engineer,109988,EUR,93490,MI,FL,France,L,France,50,"SQL, MLOps, Java, Azure",Master,3,Retail,2025-02-11,2025-04-11,2329,7.8,Autonomous Tech -AI02514,Robotics Engineer,146873,EUR,124842,SE,FT,Netherlands,L,Vietnam,50,"Kubernetes, SQL, AWS, GCP",PhD,9,Real Estate,2025-03-16,2025-04-24,1914,7.5,TechCorp Inc -AI02515,Machine Learning Engineer,165141,USD,165141,EX,PT,South Korea,M,South Korea,0,"Java, Python, Tableau, Linux, Deep Learning",Master,15,Consulting,2024-03-10,2024-04-14,1945,5.9,Autonomous Tech -AI02516,Machine Learning Engineer,77901,AUD,105166,EN,FT,Australia,M,Australia,100,"Python, AWS, Statistics",Associate,0,Energy,2024-10-18,2024-12-03,2251,7.8,Smart Analytics -AI02517,Research Scientist,94620,SGD,123006,EN,PT,Singapore,L,New Zealand,100,"Hadoop, Java, Spark",Associate,1,Automotive,2024-09-22,2024-12-04,1019,8.6,Cloud AI Solutions -AI02518,Principal Data Scientist,162374,GBP,121781,SE,CT,United Kingdom,L,United Kingdom,50,"Git, Azure, Computer Vision, Mathematics, PyTorch",Associate,9,Retail,2024-03-08,2024-04-16,1503,9.9,Smart Analytics -AI02519,Data Engineer,85536,USD,85536,EN,FL,Finland,L,Finland,100,"MLOps, GCP, SQL",PhD,1,Automotive,2025-01-19,2025-03-17,1202,5.8,Future Systems -AI02520,Research Scientist,132794,GBP,99596,SE,PT,United Kingdom,M,United States,100,"NLP, Git, Python, Mathematics",PhD,7,Telecommunications,2024-10-07,2024-12-05,1060,10,Quantum Computing Inc -AI02521,Head of AI,51202,CAD,64003,EN,CT,Canada,S,Canada,50,"Mathematics, Deep Learning, Kubernetes",PhD,0,Transportation,2024-06-09,2024-07-26,2084,9,Machine Intelligence Group -AI02522,Machine Learning Researcher,105407,USD,105407,MI,CT,Ireland,M,Ireland,0,"Git, Hadoop, Scala, Spark",Bachelor,3,Technology,2024-07-15,2024-08-01,515,6.2,Algorithmic Solutions -AI02523,NLP Engineer,94037,USD,94037,MI,CT,Finland,M,Finland,50,"GCP, Kubernetes, R",Associate,3,Automotive,2024-07-15,2024-08-04,2256,7.6,Advanced Robotics -AI02524,Data Engineer,206898,EUR,175863,EX,FT,Austria,S,Austria,100,"Mathematics, Linux, MLOps",Associate,13,Healthcare,2024-01-10,2024-03-14,527,9.1,Digital Transformation LLC -AI02525,Deep Learning Engineer,243562,CHF,219206,EX,PT,Switzerland,M,Switzerland,0,"Git, Java, Data Visualization",Master,19,Telecommunications,2024-02-01,2024-02-15,1421,5,Machine Intelligence Group -AI02526,Data Analyst,51859,USD,51859,EN,PT,Ireland,S,Luxembourg,100,"Git, PyTorch, Statistics, Docker, Python",Master,1,Technology,2025-03-09,2025-03-28,1458,8.8,Quantum Computing Inc -AI02527,ML Ops Engineer,86795,USD,86795,MI,PT,Sweden,S,Sweden,100,"Tableau, GCP, Linux, Computer Vision, Java",Bachelor,4,Retail,2024-08-02,2024-09-20,659,9.1,Digital Transformation LLC -AI02528,AI Research Scientist,81483,EUR,69261,MI,CT,Germany,M,Ireland,50,"Linux, AWS, Python",Bachelor,4,Gaming,2025-03-26,2025-04-13,1391,9.8,AI Innovations -AI02529,ML Ops Engineer,269686,CHF,242717,EX,PT,Switzerland,M,Portugal,50,"Python, NLP, SQL, Linux, Git",PhD,10,Healthcare,2024-09-29,2024-10-17,1421,9.8,AI Innovations -AI02530,AI Architect,55579,USD,55579,EN,PT,South Korea,S,South Korea,50,"MLOps, Python, Deep Learning",Master,0,Education,2024-10-13,2024-11-05,1101,8.8,Predictive Systems -AI02531,AI Software Engineer,60607,USD,60607,EN,FT,Ireland,L,Ireland,0,"Data Visualization, SQL, GCP, Python, Mathematics",PhD,0,Energy,2024-12-16,2025-02-18,2279,5.8,Machine Intelligence Group -AI02532,NLP Engineer,131631,EUR,111886,SE,PT,Germany,M,Germany,50,"AWS, Data Visualization, Azure",Associate,7,Manufacturing,2024-08-12,2024-09-12,697,8.4,DeepTech Ventures -AI02533,Machine Learning Engineer,54944,EUR,46702,EN,FT,Germany,S,Germany,100,"Statistics, SQL, Python",Bachelor,0,Energy,2025-01-21,2025-03-29,975,7,Cognitive Computing -AI02534,AI Software Engineer,191195,CHF,172076,SE,PT,Switzerland,M,Switzerland,100,"PyTorch, Python, Docker, Kubernetes, Hadoop",Master,5,Healthcare,2024-12-02,2024-12-24,2199,5.2,AI Innovations -AI02535,Data Engineer,120333,CAD,150416,EX,FT,Canada,S,Brazil,100,"Java, NLP, MLOps, TensorFlow",Master,13,Government,2024-01-20,2024-02-03,2326,7.2,Smart Analytics -AI02536,Deep Learning Engineer,65699,USD,65699,EX,FT,China,S,China,0,"Statistics, SQL, Docker",Associate,17,Telecommunications,2025-03-21,2025-04-12,2252,6.9,AI Innovations -AI02537,AI Architect,64976,USD,64976,EN,PT,Israel,M,Luxembourg,0,"Tableau, Azure, Linux, Data Visualization",Master,1,Transportation,2024-02-06,2024-03-12,979,8,Cognitive Computing -AI02538,Research Scientist,209582,USD,209582,EX,CT,Denmark,M,Denmark,0,"SQL, Linux, Computer Vision, AWS",Bachelor,10,Government,2025-02-15,2025-04-19,1382,6.4,Smart Analytics -AI02539,Data Scientist,145591,USD,145591,SE,PT,United States,S,Austria,0,"Tableau, Git, PyTorch",Bachelor,7,Healthcare,2024-08-24,2024-10-18,1653,9.9,TechCorp Inc -AI02540,AI Product Manager,291098,USD,291098,EX,FL,Denmark,M,Denmark,100,"AWS, Kubernetes, R, Python, Statistics",Associate,16,Technology,2024-07-26,2024-09-14,2086,8.7,Algorithmic Solutions -AI02541,Autonomous Systems Engineer,196197,USD,196197,EX,FT,Sweden,L,Sweden,50,"Python, SQL, Kubernetes",Associate,11,Telecommunications,2024-05-04,2024-05-18,2425,8.7,Quantum Computing Inc -AI02542,Principal Data Scientist,186336,USD,186336,EX,PT,South Korea,L,France,0,"R, Docker, Java",Bachelor,10,Healthcare,2024-06-20,2024-07-20,1557,5.9,DataVision Ltd -AI02543,Data Scientist,62080,USD,62080,SE,PT,India,L,India,100,"Spark, Statistics, Data Visualization, Azure, Computer Vision",Bachelor,8,Manufacturing,2024-03-05,2024-04-18,774,6.8,Smart Analytics -AI02544,AI Software Engineer,85101,USD,85101,EN,FT,Denmark,S,Ireland,0,"NLP, Deep Learning, Git, Azure, R",Associate,1,Healthcare,2025-04-27,2025-05-12,1077,7.4,Quantum Computing Inc -AI02545,Robotics Engineer,149817,AUD,202253,SE,FT,Australia,M,Australia,0,"PyTorch, Computer Vision, MLOps, Statistics, Mathematics",Bachelor,7,Media,2024-02-07,2024-03-02,964,7.3,Algorithmic Solutions -AI02546,AI Architect,73727,EUR,62668,EN,FL,Austria,L,Austria,50,"GCP, Java, NLP, Computer Vision, Statistics",Associate,0,Retail,2025-03-09,2025-04-04,2292,6.1,Algorithmic Solutions -AI02547,Machine Learning Researcher,95260,USD,95260,EX,FT,China,L,China,100,"Docker, Git, R, SQL",Master,14,Education,2024-09-22,2024-10-16,1846,9.7,AI Innovations -AI02548,AI Specialist,59469,USD,59469,EN,CT,United States,S,United States,0,"R, Mathematics, Data Visualization, Deep Learning",Master,1,Transportation,2024-09-05,2024-10-06,1302,5.1,Digital Transformation LLC -AI02549,Data Engineer,95741,USD,95741,MI,CT,Ireland,S,Ireland,50,"TensorFlow, Spark, R, AWS, Linux",Master,4,Technology,2024-11-08,2024-11-29,836,6.9,Predictive Systems -AI02550,Data Analyst,99330,CHF,89397,EN,FT,Switzerland,S,Vietnam,0,"Kubernetes, Scala, Deep Learning, GCP",Master,1,Telecommunications,2024-01-22,2024-02-21,636,6.5,AI Innovations -AI02551,Data Engineer,169622,USD,169622,EX,PT,United States,M,United States,100,"GCP, Mathematics, Java, PyTorch",Associate,10,Media,2025-04-10,2025-05-02,1878,5.7,Autonomous Tech -AI02552,NLP Engineer,34014,USD,34014,MI,CT,India,L,India,0,"AWS, R, Kubernetes",Master,2,Government,2024-10-16,2024-11-25,2084,5.6,Advanced Robotics -AI02553,Deep Learning Engineer,48009,EUR,40808,EN,CT,France,S,France,100,"Linux, Java, R, Tableau",Associate,1,Automotive,2024-06-20,2024-07-05,1365,8.1,Quantum Computing Inc -AI02554,Machine Learning Researcher,186879,USD,186879,EX,FL,Ireland,M,United States,0,"Tableau, R, Linux",PhD,13,Consulting,2024-10-22,2024-12-05,923,7.4,Machine Intelligence Group -AI02555,Machine Learning Engineer,43587,USD,43587,SE,CT,India,L,Kenya,100,"Mathematics, Tableau, Azure, Linux",Bachelor,6,Government,2024-07-03,2024-07-22,1803,7.8,Algorithmic Solutions -AI02556,AI Product Manager,296908,USD,296908,EX,FT,Denmark,M,Denmark,0,"Scala, PyTorch, AWS, SQL",Associate,17,Education,2024-01-14,2024-02-12,963,8.2,DeepTech Ventures -AI02557,Principal Data Scientist,185850,CHF,167265,SE,FL,Switzerland,L,Switzerland,0,"Linux, Kubernetes, PyTorch, Deep Learning, Docker",Associate,9,Manufacturing,2025-01-19,2025-02-27,1056,9.1,Advanced Robotics -AI02558,AI Specialist,171053,CAD,213816,EX,CT,Canada,M,Canada,50,"GCP, Kubernetes, Data Visualization, Scala",Associate,18,Finance,2024-04-10,2024-05-30,1822,6.7,Quantum Computing Inc -AI02559,ML Ops Engineer,149653,EUR,127205,EX,PT,France,L,France,0,"Computer Vision, Mathematics, Scala, Data Visualization, Python",PhD,13,Transportation,2024-11-02,2024-11-16,1909,5.8,TechCorp Inc -AI02560,AI Specialist,86772,USD,86772,MI,PT,United States,M,United States,0,"TensorFlow, Kubernetes, PyTorch, Azure",PhD,3,Government,2024-06-25,2024-07-14,934,6.9,AI Innovations -AI02561,Machine Learning Researcher,80745,EUR,68633,MI,FL,Austria,L,Austria,100,"Data Visualization, Python, Spark",Master,4,Healthcare,2024-08-07,2024-09-05,2274,7.6,Autonomous Tech -AI02562,Principal Data Scientist,88333,CAD,110416,MI,FT,Canada,L,Canada,100,"MLOps, GCP, Java, Hadoop",Master,3,Transportation,2024-10-31,2025-01-03,1219,7.5,Quantum Computing Inc -AI02563,Data Engineer,294564,CHF,265108,EX,FT,Switzerland,M,United States,0,"Git, Python, TensorFlow",Master,16,Healthcare,2024-02-28,2024-05-10,1523,9,DeepTech Ventures -AI02564,Autonomous Systems Engineer,151837,USD,151837,SE,FL,United States,S,Estonia,100,"SQL, Mathematics, Tableau, Git",Master,6,Automotive,2025-03-24,2025-04-23,1538,6.9,Algorithmic Solutions -AI02565,Deep Learning Engineer,258351,USD,258351,EX,FL,United States,M,United States,50,"Python, TensorFlow, Scala, Deep Learning",Associate,14,Transportation,2024-12-24,2025-02-14,2412,8.3,AI Innovations -AI02566,AI Specialist,93903,CAD,117379,SE,CT,Canada,S,Canada,50,"Java, MLOps, Statistics, Tableau, Linux",PhD,5,Education,2025-02-20,2025-04-17,968,5.6,Cloud AI Solutions -AI02567,AI Product Manager,129113,USD,129113,SE,CT,Israel,S,Israel,0,"Hadoop, Computer Vision, Kubernetes, R, Docker",Bachelor,9,Automotive,2024-09-30,2024-10-16,2205,8.5,Future Systems -AI02568,AI Software Engineer,86397,EUR,73437,EN,PT,Germany,L,Germany,0,"Computer Vision, Git, Kubernetes, PyTorch",Bachelor,1,Automotive,2024-07-19,2024-09-25,1310,6.3,Algorithmic Solutions -AI02569,Autonomous Systems Engineer,124460,USD,124460,SE,CT,Sweden,M,Brazil,100,"SQL, Scala, Python, AWS, Hadoop",Master,9,Healthcare,2024-06-08,2024-07-07,2132,9.4,AI Innovations -AI02570,Data Engineer,149448,EUR,127031,EX,FT,France,M,France,50,"MLOps, Mathematics, Data Visualization",Master,18,Retail,2024-03-30,2024-04-17,1536,9.8,DeepTech Ventures -AI02571,Data Engineer,58804,EUR,49983,EN,PT,Germany,M,Germany,0,"Statistics, Java, Spark",Associate,1,Healthcare,2024-04-24,2024-06-19,609,7,Cloud AI Solutions -AI02572,AI Consultant,79567,CHF,71610,EN,FL,Switzerland,S,United States,100,"TensorFlow, Deep Learning, Computer Vision",PhD,0,Retail,2024-07-18,2024-08-09,1174,7.3,DataVision Ltd -AI02573,AI Specialist,92586,EUR,78698,MI,PT,Austria,M,Austria,50,"Python, Deep Learning, Kubernetes, Computer Vision",Master,4,Energy,2024-10-19,2024-11-02,739,7.1,Neural Networks Co -AI02574,Data Engineer,88553,JPY,9740830,EN,PT,Japan,L,Italy,0,"PyTorch, Computer Vision, Deep Learning",Associate,0,Finance,2025-01-25,2025-03-24,903,7,DeepTech Ventures -AI02575,Deep Learning Engineer,180911,EUR,153774,EX,FT,Netherlands,M,Netherlands,50,"Kubernetes, Statistics, R, Python, Mathematics",Master,13,Retail,2024-09-29,2024-11-13,1874,6.6,TechCorp Inc -AI02576,Computer Vision Engineer,180125,USD,180125,SE,FL,United States,L,United States,100,"TensorFlow, SQL, Git, AWS",Associate,8,Automotive,2024-12-07,2024-12-21,2412,8.4,Machine Intelligence Group -AI02577,Computer Vision Engineer,52185,EUR,44357,EN,FT,France,S,France,50,"R, Spark, TensorFlow, Data Visualization, SQL",Master,1,Retail,2024-06-27,2024-08-22,2119,9.3,Smart Analytics -AI02578,Machine Learning Researcher,246154,EUR,209231,EX,CT,Austria,L,Austria,0,"Deep Learning, Computer Vision, TensorFlow, Scala",Associate,14,Finance,2025-01-05,2025-03-07,1880,9.6,Cognitive Computing -AI02579,AI Specialist,57512,EUR,48885,EN,FL,Netherlands,M,Australia,100,"Statistics, PyTorch, SQL, Scala, Data Visualization",Associate,0,Consulting,2024-03-23,2024-04-19,575,6.8,AI Innovations -AI02580,Head of AI,170182,CHF,153164,MI,FT,Switzerland,L,Switzerland,0,"TensorFlow, Java, GCP",Master,2,Retail,2024-02-07,2024-03-03,1519,6.4,Cloud AI Solutions -AI02581,Data Scientist,40011,USD,40011,MI,CT,China,M,China,100,"Linux, Tableau, Spark, Java",Associate,3,Finance,2024-07-25,2024-08-30,1950,9.5,DeepTech Ventures -AI02582,Machine Learning Engineer,112165,GBP,84124,SE,CT,United Kingdom,M,Japan,100,"GCP, Kubernetes, Java, SQL, Deep Learning",Associate,7,Finance,2024-07-22,2024-09-02,1763,5.6,Smart Analytics -AI02583,Head of AI,118931,USD,118931,SE,CT,Ireland,L,Ireland,100,"Python, GCP, Scala",PhD,8,Government,2024-09-21,2024-10-28,1210,9,Cognitive Computing -AI02584,AI Specialist,163364,USD,163364,SE,FL,Finland,L,Mexico,0,"PyTorch, Spark, TensorFlow",Bachelor,8,Government,2025-01-06,2025-02-18,1293,6.9,Cloud AI Solutions -AI02585,Data Scientist,131301,USD,131301,EX,FL,South Korea,S,South Korea,0,"Linux, Spark, Deep Learning, Kubernetes",PhD,18,Education,2024-04-10,2024-05-02,2382,7.5,Quantum Computing Inc -AI02586,AI Software Engineer,68441,USD,68441,MI,PT,Ireland,S,Ireland,50,"Kubernetes, Statistics, GCP, Tableau",Master,4,Real Estate,2024-10-02,2024-10-20,1488,8.3,DataVision Ltd -AI02587,Robotics Engineer,135907,USD,135907,MI,CT,United States,L,United States,0,"NLP, GCP, Tableau",PhD,2,Energy,2024-09-26,2024-11-28,597,6.5,Machine Intelligence Group -AI02588,AI Architect,99860,EUR,84881,SE,FT,France,M,France,100,"PyTorch, AWS, NLP, Java, Azure",Master,6,Telecommunications,2024-06-19,2024-08-27,654,8.9,Quantum Computing Inc -AI02589,NLP Engineer,91537,USD,91537,MI,FL,South Korea,L,Argentina,100,"PyTorch, Tableau, NLP, TensorFlow",PhD,3,Telecommunications,2025-03-21,2025-05-29,845,6.9,Future Systems -AI02590,AI Specialist,167565,USD,167565,SE,PT,United States,M,France,50,"Hadoop, Azure, Deep Learning",Master,5,Energy,2024-07-10,2024-08-21,916,6.8,Digital Transformation LLC -AI02591,Machine Learning Researcher,102636,SGD,133427,MI,PT,Singapore,L,Singapore,100,"SQL, MLOps, PyTorch, Data Visualization, TensorFlow",Associate,2,Energy,2024-10-20,2024-12-13,663,7.1,Future Systems -AI02592,AI Consultant,116030,EUR,98626,SE,CT,Germany,M,Germany,100,"TensorFlow, Linux, PyTorch, GCP, Azure",PhD,6,Media,2024-04-05,2024-05-13,1375,5.9,Machine Intelligence Group -AI02593,AI Architect,84644,CAD,105805,EN,PT,Canada,L,Canada,100,"Kubernetes, Python, Hadoop",Master,1,Government,2024-12-25,2025-02-16,2101,8.9,Predictive Systems -AI02594,Research Scientist,65082,AUD,87861,EN,CT,Australia,M,Nigeria,50,"Python, Deep Learning, Kubernetes, Linux",PhD,1,Energy,2024-07-17,2024-08-06,1907,8.2,DataVision Ltd -AI02595,AI Software Engineer,62534,AUD,84421,EN,PT,Australia,M,Australia,50,"Python, Git, TensorFlow",Master,0,Telecommunications,2024-11-26,2025-01-12,2305,6.5,DeepTech Ventures -AI02596,AI Specialist,241137,CHF,217023,SE,FT,Switzerland,L,Switzerland,50,"Spark, Kubernetes, Tableau, Python, Statistics",Master,5,Education,2024-12-05,2025-02-04,1926,7.6,Machine Intelligence Group -AI02597,AI Software Engineer,85906,USD,85906,EN,PT,Finland,L,Finland,50,"Statistics, Linux, Scala, Kubernetes",Associate,1,Media,2024-10-21,2024-11-27,1026,7.7,Cognitive Computing -AI02598,Data Scientist,99399,USD,99399,SE,FT,South Korea,S,Singapore,50,"R, Python, Mathematics",Master,9,Real Estate,2024-03-21,2024-04-10,1095,5,Machine Intelligence Group -AI02599,Machine Learning Engineer,69551,USD,69551,EN,FL,Denmark,S,Denmark,0,"Docker, Python, Hadoop, SQL",Associate,0,Transportation,2024-10-24,2024-11-21,1355,6.4,Quantum Computing Inc -AI02600,Autonomous Systems Engineer,98388,USD,98388,MI,FT,South Korea,L,South Korea,0,"Python, Computer Vision, TensorFlow",Bachelor,4,Energy,2024-07-23,2024-09-17,1870,5.8,Machine Intelligence Group -AI02601,NLP Engineer,59613,CAD,74516,EN,CT,Canada,M,Canada,100,"Computer Vision, R, Docker",PhD,1,Retail,2024-02-07,2024-03-06,1939,6.2,Advanced Robotics -AI02602,AI Software Engineer,84934,USD,84934,EN,FL,United States,S,United States,100,"Computer Vision, Deep Learning, Tableau, Linux",Master,0,Telecommunications,2024-08-16,2024-10-18,1161,6.7,Quantum Computing Inc -AI02603,Data Analyst,86399,USD,86399,EX,FT,India,L,India,50,"Docker, R, Linux",Associate,18,Technology,2024-07-23,2024-09-10,1885,7.5,AI Innovations -AI02604,Data Scientist,167659,AUD,226340,SE,FT,Australia,L,Australia,50,"Kubernetes, TensorFlow, Spark, SQL",PhD,8,Education,2024-12-30,2025-01-22,1211,6.1,Digital Transformation LLC -AI02605,Data Engineer,101084,AUD,136463,MI,CT,Australia,L,Australia,100,"Java, TensorFlow, AWS, Computer Vision",Bachelor,2,Manufacturing,2024-08-01,2024-09-11,724,8.4,Neural Networks Co -AI02606,AI Architect,32520,USD,32520,EN,CT,China,M,Romania,50,"GCP, Linux, Statistics",PhD,1,Technology,2025-02-02,2025-03-08,1144,6.9,Smart Analytics -AI02607,Data Scientist,109024,EUR,92670,SE,FT,Germany,S,Germany,100,"Azure, SQL, TensorFlow, Tableau, Deep Learning",Bachelor,6,Real Estate,2024-09-11,2024-11-10,931,7.8,Predictive Systems -AI02608,AI Consultant,130052,USD,130052,SE,CT,Norway,S,Portugal,100,"Python, PyTorch, Data Visualization, Kubernetes",Associate,8,Healthcare,2025-02-22,2025-03-09,1571,5.6,DeepTech Ventures -AI02609,Deep Learning Engineer,118889,EUR,101056,MI,PT,Austria,L,Austria,50,"Tableau, Deep Learning, Kubernetes",PhD,2,Energy,2024-04-11,2024-05-13,2266,9.5,Smart Analytics -AI02610,Robotics Engineer,120628,USD,120628,EX,FT,Finland,S,Egypt,100,"Hadoop, Linux, Azure, MLOps, Kubernetes",Associate,15,Automotive,2024-04-26,2024-06-12,1815,9.4,DataVision Ltd -AI02611,AI Specialist,74800,CAD,93500,EN,FT,Canada,L,Canada,0,"Azure, Hadoop, Kubernetes, TensorFlow, Statistics",PhD,0,Automotive,2024-07-20,2024-09-04,688,5.2,Quantum Computing Inc -AI02612,AI Software Engineer,64207,GBP,48155,EN,PT,United Kingdom,M,Portugal,0,"Docker, GCP, SQL, AWS",Associate,1,Technology,2024-10-24,2025-01-03,2149,8.1,AI Innovations -AI02613,Computer Vision Engineer,133828,CHF,120445,MI,FT,Switzerland,S,Indonesia,100,"Scala, Spark, Data Visualization, R, Git",Associate,2,Automotive,2025-01-26,2025-02-17,1345,8.3,Advanced Robotics -AI02614,AI Product Manager,79575,AUD,107426,EN,FL,Australia,L,Australia,0,"Linux, AWS, Scala, PyTorch, Docker",Bachelor,1,Energy,2024-01-10,2024-03-18,1969,7.7,Advanced Robotics -AI02615,Autonomous Systems Engineer,131921,AUD,178093,SE,CT,Australia,M,Australia,100,"PyTorch, AWS, Tableau",Bachelor,7,Healthcare,2024-04-25,2024-05-22,546,7.1,Predictive Systems -AI02616,Machine Learning Engineer,237422,USD,237422,EX,FL,Denmark,L,Vietnam,100,"Scala, TensorFlow, SQL, NLP",PhD,18,Retail,2024-08-31,2024-10-04,2210,7.3,Cloud AI Solutions -AI02617,Computer Vision Engineer,78318,EUR,66570,MI,FL,Germany,S,Germany,100,"Data Visualization, Python, Java",Bachelor,2,Manufacturing,2025-04-03,2025-06-10,1370,8.5,Cognitive Computing -AI02618,Autonomous Systems Engineer,108458,EUR,92189,MI,FL,Netherlands,L,Netherlands,100,"Docker, Java, Computer Vision",Bachelor,2,Manufacturing,2024-09-26,2024-11-10,524,7,Smart Analytics -AI02619,Data Analyst,263428,GBP,197571,EX,CT,United Kingdom,M,United Kingdom,100,"MLOps, GCP, Python, TensorFlow, Scala",PhD,18,Gaming,2024-04-28,2024-06-10,1293,5.8,Digital Transformation LLC -AI02620,AI Consultant,46582,USD,46582,MI,PT,China,S,China,100,"MLOps, Deep Learning, Python, NLP, Scala",Bachelor,3,Automotive,2024-03-12,2024-05-14,1625,6.3,DeepTech Ventures -AI02621,Robotics Engineer,169033,SGD,219743,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Data Visualization",PhD,17,Healthcare,2025-03-06,2025-03-24,1506,8.4,TechCorp Inc -AI02622,Machine Learning Researcher,59167,USD,59167,MI,FL,South Korea,S,South Korea,0,"Statistics, Git, Linux, GCP, Computer Vision",Bachelor,2,Telecommunications,2024-12-18,2025-02-14,965,7.3,AI Innovations -AI02623,Deep Learning Engineer,76863,SGD,99922,EN,PT,Singapore,S,Singapore,0,"AWS, Hadoop, NLP, Python, Scala",Master,0,Telecommunications,2024-11-17,2024-12-20,1525,6.4,Quantum Computing Inc -AI02624,Research Scientist,54769,USD,54769,EN,FL,South Korea,S,South Korea,0,"Python, Scala, Java",Bachelor,1,Consulting,2024-12-10,2025-02-10,1118,7.9,TechCorp Inc -AI02625,AI Product Manager,227468,USD,227468,EX,FT,United States,M,Colombia,50,"Linux, TensorFlow, Deep Learning",Master,14,Retail,2024-01-03,2024-03-10,1849,7.9,Algorithmic Solutions -AI02626,Deep Learning Engineer,27385,USD,27385,EN,FT,China,S,Malaysia,50,"TensorFlow, Python, R, Statistics, Spark",PhD,0,Consulting,2024-11-22,2025-01-28,1243,5.3,Quantum Computing Inc -AI02627,NLP Engineer,192062,USD,192062,EX,PT,Norway,M,Norway,100,"TensorFlow, SQL, Mathematics",PhD,10,Real Estate,2024-08-07,2024-09-27,1863,5.4,Cloud AI Solutions -AI02628,Data Analyst,84809,USD,84809,MI,FL,Israel,M,Israel,100,"TensorFlow, AWS, Python, Computer Vision, Scala",Associate,4,Automotive,2024-11-27,2024-12-31,519,8.3,Algorithmic Solutions -AI02629,Computer Vision Engineer,129372,USD,129372,SE,CT,Israel,M,Ukraine,50,"Deep Learning, MLOps, Azure, Java",Master,6,Transportation,2024-03-19,2024-04-04,2253,6.9,Neural Networks Co -AI02630,Principal Data Scientist,61768,CAD,77210,EN,FT,Canada,L,Canada,100,"Java, Git, Kubernetes, PyTorch, Data Visualization",Associate,1,Automotive,2024-02-26,2024-03-14,1170,7.5,Cloud AI Solutions -AI02631,AI Product Manager,33922,USD,33922,EN,CT,China,M,China,100,"Spark, Python, Git, Linux",Associate,0,Technology,2024-07-17,2024-08-15,590,7.1,Algorithmic Solutions -AI02632,Research Scientist,127911,USD,127911,SE,PT,Sweden,M,Sweden,100,"AWS, Python, TensorFlow, Statistics, Deep Learning",Bachelor,6,Real Estate,2024-08-14,2024-09-15,847,9.3,Future Systems -AI02633,AI Consultant,132207,EUR,112376,EX,CT,Austria,S,Austria,100,"Hadoop, Python, Statistics",Master,16,Automotive,2024-01-29,2024-03-16,1880,7.1,Cloud AI Solutions -AI02634,AI Specialist,60862,CAD,76078,EN,CT,Canada,S,United Kingdom,0,"SQL, Computer Vision, Tableau, PyTorch, Scala",PhD,1,Healthcare,2024-07-26,2024-09-06,1914,5.5,Autonomous Tech -AI02635,Machine Learning Researcher,30483,USD,30483,MI,FT,India,S,India,100,"Kubernetes, NLP, Linux",PhD,2,Finance,2024-12-21,2025-01-15,2424,9,TechCorp Inc -AI02636,AI Product Manager,99046,USD,99046,MI,FL,Denmark,S,Denmark,0,"MLOps, R, Kubernetes",Associate,4,Healthcare,2024-12-15,2025-01-30,990,8.9,Quantum Computing Inc -AI02637,AI Product Manager,126174,USD,126174,MI,CT,Denmark,S,New Zealand,0,"Data Visualization, Kubernetes, Scala, Python",Associate,3,Healthcare,2024-06-25,2024-08-27,877,6.1,Cognitive Computing -AI02638,Deep Learning Engineer,226713,USD,226713,EX,FT,Denmark,S,South Africa,50,"Python, TensorFlow, Docker, Mathematics",Bachelor,11,Education,2025-03-16,2025-05-04,760,8.7,Advanced Robotics -AI02639,Robotics Engineer,66662,SGD,86661,EN,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, Kubernetes, Spark, SQL",Bachelor,0,Consulting,2024-03-03,2024-03-28,2192,6.7,Autonomous Tech -AI02640,Machine Learning Engineer,156202,USD,156202,EX,CT,Ireland,S,China,0,"TensorFlow, Data Visualization, Python",Bachelor,14,Media,2024-05-14,2024-06-15,1849,6.6,Predictive Systems -AI02641,ML Ops Engineer,106445,USD,106445,SE,CT,South Korea,S,South Korea,50,"Docker, Deep Learning, Python, GCP, Mathematics",Master,9,Technology,2025-02-01,2025-03-31,2203,7.7,Advanced Robotics -AI02642,Research Scientist,57527,USD,57527,SE,CT,China,L,China,50,"R, SQL, Scala, Tableau, AWS",Associate,7,Telecommunications,2024-11-24,2024-12-18,1466,9.9,DataVision Ltd -AI02643,Data Analyst,71613,USD,71613,EN,CT,Ireland,L,Norway,0,"Azure, Python, GCP, TensorFlow, MLOps",Associate,1,Media,2024-05-12,2024-06-06,1682,8.8,Quantum Computing Inc -AI02644,Data Engineer,214057,USD,214057,SE,FT,Norway,L,Norway,0,"Scala, Deep Learning, Computer Vision, Data Visualization, Docker",PhD,9,Education,2024-12-11,2025-02-03,1422,7.3,DeepTech Ventures -AI02645,AI Research Scientist,113033,USD,113033,SE,PT,Finland,L,Finland,50,"MLOps, Spark, Azure",Bachelor,6,Media,2024-10-07,2024-10-21,1899,6.8,Advanced Robotics -AI02646,Computer Vision Engineer,83831,AUD,113172,MI,FT,Australia,L,Philippines,50,"Scala, Hadoop, Linux, SQL",Associate,4,Retail,2025-02-21,2025-03-25,904,5.3,Cloud AI Solutions -AI02647,Deep Learning Engineer,130289,USD,130289,SE,CT,United States,S,United States,0,"Kubernetes, Scala, Deep Learning",Associate,6,Government,2025-03-10,2025-04-15,2201,9.8,Algorithmic Solutions -AI02648,Data Engineer,128723,CAD,160904,SE,CT,Canada,S,Canada,100,"Scala, Tableau, Python",Master,7,Transportation,2024-09-11,2024-11-13,1131,5.8,DeepTech Ventures -AI02649,AI Consultant,197237,AUD,266270,EX,FL,Australia,S,Australia,0,"Hadoop, Python, Tableau, SQL",Associate,10,Telecommunications,2024-10-10,2024-12-10,2281,6.6,Future Systems -AI02650,Machine Learning Engineer,49680,USD,49680,MI,FL,China,L,China,100,"AWS, Spark, Tableau, NLP, Kubernetes",PhD,2,Finance,2024-02-26,2024-03-20,785,9.9,Future Systems -AI02651,Computer Vision Engineer,79494,USD,79494,MI,CT,United States,S,Indonesia,0,"Scala, Spark, Hadoop",Bachelor,3,Finance,2025-01-07,2025-02-24,1427,6.2,Algorithmic Solutions -AI02652,Data Engineer,120305,SGD,156397,MI,PT,Singapore,L,Singapore,0,"Computer Vision, SQL, Docker, Python, Hadoop",Bachelor,3,Education,2024-09-24,2024-10-18,1572,8.5,Algorithmic Solutions -AI02653,Research Scientist,109402,USD,109402,EX,FL,South Korea,S,South Korea,50,"Python, Scala, TensorFlow, Java, AWS",Bachelor,11,Telecommunications,2024-08-30,2024-10-25,2305,9,Machine Intelligence Group -AI02654,Computer Vision Engineer,131199,SGD,170559,MI,CT,Singapore,L,Russia,50,"R, Linux, Statistics, Spark",Bachelor,3,Consulting,2024-01-25,2024-03-19,593,7.2,TechCorp Inc -AI02655,Data Engineer,89303,USD,89303,MI,PT,Israel,L,Israel,0,"PyTorch, Mathematics, SQL, Scala, NLP",Associate,4,Energy,2024-03-25,2024-04-20,1319,8.3,TechCorp Inc -AI02656,AI Consultant,152868,AUD,206372,EX,FL,Australia,S,United States,0,"Hadoop, Java, Git, Statistics, Spark",PhD,13,Telecommunications,2025-02-13,2025-03-16,1303,6.8,Cloud AI Solutions -AI02657,Machine Learning Engineer,77521,USD,77521,MI,CT,South Korea,L,South Korea,50,"Spark, Hadoop, Tableau, MLOps, Linux",Associate,2,Finance,2025-01-25,2025-04-07,2414,8.6,DataVision Ltd -AI02658,ML Ops Engineer,140909,GBP,105682,SE,FT,United Kingdom,S,United Kingdom,100,"AWS, R, SQL",Master,9,Government,2024-01-14,2024-03-24,1248,9,Future Systems -AI02659,Data Engineer,156224,USD,156224,EX,CT,Finland,L,Finland,0,"Azure, Data Visualization, Statistics",PhD,18,Telecommunications,2024-09-21,2024-10-17,1780,9.1,DataVision Ltd -AI02660,AI Software Engineer,98611,SGD,128194,MI,FT,Singapore,M,Chile,100,"MLOps, Git, Kubernetes",Associate,3,Healthcare,2024-09-14,2024-10-16,1867,9.6,Algorithmic Solutions -AI02661,AI Research Scientist,129667,USD,129667,SE,CT,Ireland,M,South Korea,50,"Hadoop, Data Visualization, SQL, MLOps",Bachelor,7,Real Estate,2024-01-26,2024-02-17,2455,5.6,Cognitive Computing -AI02662,AI Research Scientist,143589,EUR,122051,SE,PT,Austria,M,Germany,50,"Scala, GCP, Computer Vision, Statistics, Tableau",PhD,5,Manufacturing,2024-03-04,2024-05-01,1222,6.3,Quantum Computing Inc -AI02663,Deep Learning Engineer,102918,USD,102918,EN,FT,United States,L,Luxembourg,100,"Python, TensorFlow, Deep Learning, R",Master,0,Finance,2025-04-08,2025-05-19,2329,7.7,DataVision Ltd -AI02664,NLP Engineer,233285,EUR,198292,EX,FT,Austria,L,Ukraine,100,"MLOps, R, Computer Vision",Master,10,Finance,2025-01-12,2025-02-20,1375,6.2,Neural Networks Co -AI02665,AI Research Scientist,161043,USD,161043,SE,FL,United States,M,United States,100,"PyTorch, Spark, Mathematics",Master,5,Energy,2024-07-18,2024-09-21,1559,9.8,Advanced Robotics -AI02666,AI Architect,184501,GBP,138376,EX,FL,United Kingdom,L,Russia,100,"Statistics, TensorFlow, Deep Learning",Associate,18,Consulting,2024-12-10,2025-01-13,1574,6.9,Digital Transformation LLC -AI02667,NLP Engineer,77968,USD,77968,EX,PT,India,S,India,50,"Deep Learning, Spark, MLOps, Hadoop, SQL",Bachelor,10,Retail,2024-03-06,2024-05-16,585,6.2,Digital Transformation LLC -AI02668,AI Architect,251626,USD,251626,EX,PT,United States,S,Argentina,50,"Mathematics, Data Visualization, MLOps, Docker",Bachelor,17,Media,2024-12-30,2025-02-08,2096,7.4,Neural Networks Co -AI02669,AI Product Manager,93801,USD,93801,MI,FL,Finland,L,Malaysia,100,"Python, Git, SQL, Docker",PhD,3,Retail,2024-01-24,2024-02-21,1501,8.3,AI Innovations -AI02670,Autonomous Systems Engineer,85270,USD,85270,EN,FL,United States,M,Indonesia,100,"Spark, Scala, AWS, Deep Learning",PhD,0,Government,2024-01-09,2024-01-24,1067,8.8,DataVision Ltd -AI02671,AI Product Manager,116844,USD,116844,EX,PT,South Korea,S,Malaysia,50,"Docker, Spark, Python, Java",Master,12,Transportation,2025-03-17,2025-04-17,2064,9.8,TechCorp Inc -AI02672,AI Consultant,115484,USD,115484,SE,FL,Finland,S,Finland,0,"Kubernetes, Spark, Git, Computer Vision, Java",Master,6,Gaming,2024-09-16,2024-10-28,1669,5.3,Digital Transformation LLC -AI02673,NLP Engineer,215938,USD,215938,EX,CT,Norway,M,Australia,100,"Linux, Kubernetes, Mathematics, SQL",Bachelor,15,Consulting,2024-01-06,2024-01-25,920,8.1,Smart Analytics -AI02674,Head of AI,112832,USD,112832,SE,FT,Ireland,S,Ireland,0,"R, SQL, Tableau, PyTorch, Java",Master,9,Consulting,2024-03-11,2024-05-17,1000,6.1,AI Innovations -AI02675,Principal Data Scientist,375327,CHF,337794,EX,CT,Switzerland,L,South Africa,0,"SQL, Python, Deep Learning, Kubernetes",Bachelor,12,Automotive,2025-02-23,2025-03-23,700,7.9,DeepTech Ventures -AI02676,AI Product Manager,167432,CHF,150689,SE,FL,Switzerland,M,United Kingdom,50,"Statistics, NLP, MLOps, Linux",Master,9,Healthcare,2024-11-02,2024-12-20,1081,7.9,Machine Intelligence Group -AI02677,Autonomous Systems Engineer,117408,CHF,105667,MI,PT,Switzerland,L,Switzerland,50,"Scala, MLOps, Hadoop, SQL",Master,2,Healthcare,2024-01-14,2024-03-16,2132,7.4,Neural Networks Co -AI02678,Research Scientist,76644,USD,76644,MI,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Data Visualization",Bachelor,3,Technology,2024-02-28,2024-04-09,2292,6,TechCorp Inc -AI02679,Autonomous Systems Engineer,80930,USD,80930,EN,FL,Finland,L,Finland,100,"Git, MLOps, Tableau",Associate,1,Consulting,2024-01-14,2024-03-14,1105,9.2,Predictive Systems -AI02680,ML Ops Engineer,96017,EUR,81614,MI,FL,Austria,M,Austria,0,"Python, Git, NLP, Mathematics, TensorFlow",Master,3,Energy,2024-09-23,2024-10-30,1268,9.5,Predictive Systems -AI02681,Deep Learning Engineer,85062,USD,85062,EN,PT,Denmark,L,Denmark,0,"Kubernetes, Statistics, Python, Java",PhD,0,Education,2024-05-05,2024-07-11,1703,6.8,Advanced Robotics -AI02682,Data Analyst,123126,EUR,104657,SE,FT,France,L,Luxembourg,50,"Linux, SQL, R",Bachelor,9,Manufacturing,2024-02-21,2024-03-25,2431,6.2,DataVision Ltd -AI02683,Robotics Engineer,131093,USD,131093,EX,FL,Finland,M,Finland,50,"PyTorch, Mathematics, Git, R",PhD,13,Real Estate,2024-06-10,2024-08-22,1037,9.8,Advanced Robotics -AI02684,Data Scientist,110151,JPY,12116610,MI,FL,Japan,M,Malaysia,0,"Git, AWS, Python, Kubernetes, Docker",Bachelor,2,Real Estate,2024-01-11,2024-02-05,1352,8.1,Algorithmic Solutions -AI02685,NLP Engineer,120418,CHF,108376,MI,FL,Switzerland,M,Switzerland,0,"GCP, Docker, Mathematics",Master,4,Technology,2025-04-25,2025-06-18,1356,8.8,Quantum Computing Inc -AI02686,Data Analyst,135377,USD,135377,EX,FL,South Korea,L,South Korea,100,"Spark, SQL, Linux, Azure, AWS",Master,10,Transportation,2024-09-16,2024-11-10,784,6.7,Autonomous Tech -AI02687,ML Ops Engineer,87833,USD,87833,MI,FT,Ireland,L,Ireland,50,"Git, Azure, MLOps, Python",PhD,3,Technology,2024-01-10,2024-02-21,2222,8,Advanced Robotics -AI02688,AI Architect,227660,EUR,193511,EX,FL,Germany,S,Germany,50,"Computer Vision, Python, Deep Learning",Bachelor,15,Government,2024-10-16,2024-11-03,1915,9.8,DataVision Ltd -AI02689,Deep Learning Engineer,133632,USD,133632,EX,FT,China,L,China,0,"NLP, Python, Mathematics, GCP",Associate,15,Telecommunications,2024-12-31,2025-01-18,850,8.8,AI Innovations -AI02690,AI Software Engineer,78480,USD,78480,EN,FT,Norway,M,Norway,50,"Spark, Git, Deep Learning, Docker",Associate,1,Healthcare,2024-07-22,2024-08-28,1560,7.4,DeepTech Ventures -AI02691,Head of AI,206088,EUR,175175,EX,FT,France,M,China,0,"Statistics, Tableau, SQL, Data Visualization, PyTorch",Associate,14,Healthcare,2024-03-27,2024-05-28,821,9.3,Future Systems -AI02692,Head of AI,153198,CAD,191498,SE,PT,Canada,L,Canada,100,"Linux, Mathematics, Deep Learning, PyTorch, Azure",Master,9,Transportation,2025-02-01,2025-02-21,1912,8.2,Machine Intelligence Group -AI02693,Head of AI,92186,EUR,78358,MI,FT,France,M,France,100,"Deep Learning, Python, Spark",PhD,2,Retail,2024-09-07,2024-09-28,612,7.8,Advanced Robotics -AI02694,Data Engineer,123240,USD,123240,SE,PT,Finland,M,Finland,0,"NLP, GCP, R",PhD,7,Media,2024-11-05,2024-11-25,2331,9.4,Quantum Computing Inc -AI02695,Data Analyst,77013,SGD,100117,MI,PT,Singapore,M,Singapore,50,"Hadoop, AWS, Linux",Bachelor,4,Retail,2024-06-29,2024-08-01,2245,5.3,Autonomous Tech -AI02696,AI Software Engineer,79315,AUD,107075,MI,PT,Australia,S,Australia,50,"Java, Scala, Hadoop",Master,3,Technology,2024-09-24,2024-10-26,928,7,Smart Analytics -AI02697,Autonomous Systems Engineer,82499,USD,82499,MI,PT,Israel,S,Israel,50,"Linux, Git, TensorFlow, PyTorch, R",Master,3,Energy,2024-12-23,2025-02-08,1156,8.6,DeepTech Ventures -AI02698,AI Research Scientist,89597,USD,89597,MI,CT,Ireland,M,Ireland,100,"PyTorch, Git, Tableau",Master,3,Gaming,2025-04-28,2025-06-27,638,9.4,Future Systems -AI02699,AI Consultant,79127,USD,79127,MI,CT,South Korea,L,South Africa,50,"Spark, Kubernetes, PyTorch, Mathematics, TensorFlow",Bachelor,4,Retail,2025-04-18,2025-06-01,660,9.8,Predictive Systems -AI02700,NLP Engineer,181523,EUR,154295,EX,FT,Germany,S,Germany,100,"Java, SQL, Mathematics",PhD,16,Automotive,2025-03-19,2025-04-25,1872,8.7,Smart Analytics -AI02701,Machine Learning Researcher,136263,USD,136263,EX,FT,Sweden,S,Italy,0,"MLOps, Docker, TensorFlow, Statistics",PhD,14,Technology,2024-06-22,2024-08-27,1042,8.8,DataVision Ltd -AI02702,Computer Vision Engineer,83502,JPY,9185220,MI,FL,Japan,M,Japan,0,"Data Visualization, Java, TensorFlow",Master,4,Education,2024-11-02,2024-11-24,1113,8,TechCorp Inc -AI02703,Autonomous Systems Engineer,80445,USD,80445,EN,FL,Israel,L,Vietnam,100,"Spark, Kubernetes, Linux, Deep Learning",Master,0,Automotive,2024-11-29,2025-01-13,1701,5.6,Algorithmic Solutions -AI02704,NLP Engineer,129262,EUR,109873,SE,CT,Germany,M,Germany,100,"Scala, Mathematics, Deep Learning",Bachelor,5,Education,2025-03-31,2025-06-03,1314,5.9,AI Innovations -AI02705,AI Research Scientist,318729,USD,318729,EX,CT,Denmark,L,Denmark,100,"SQL, PyTorch, MLOps, Scala",PhD,15,Transportation,2024-04-20,2024-06-26,1885,5.1,TechCorp Inc -AI02706,Head of AI,42907,USD,42907,SE,CT,India,S,India,50,"AWS, Spark, NLP",PhD,9,Energy,2025-01-08,2025-02-21,1752,6.7,Quantum Computing Inc -AI02707,AI Architect,35590,USD,35590,MI,CT,China,S,China,50,"Deep Learning, AWS, SQL, Kubernetes",PhD,2,Energy,2025-03-11,2025-04-17,2175,7.9,Machine Intelligence Group -AI02708,ML Ops Engineer,201427,USD,201427,EX,PT,Sweden,M,Sweden,0,"Python, SQL, MLOps, Azure",Bachelor,15,Media,2024-01-04,2024-02-17,1405,6.4,Smart Analytics -AI02709,Head of AI,206878,USD,206878,EX,PT,Israel,S,Portugal,100,"Java, R, Computer Vision, Git, GCP",PhD,11,Government,2024-05-17,2024-07-01,2015,7.1,Neural Networks Co -AI02710,Data Engineer,59555,AUD,80399,EN,FL,Australia,L,Sweden,0,"SQL, Deep Learning, Linux, Python, PyTorch",Master,0,Healthcare,2025-04-18,2025-06-12,631,8.4,Neural Networks Co -AI02711,Computer Vision Engineer,40698,USD,40698,MI,FL,China,L,Egypt,100,"R, PyTorch, Tableau, Scala",Associate,2,Healthcare,2025-04-19,2025-06-18,1730,6.9,Future Systems -AI02712,AI Consultant,60205,USD,60205,EN,FT,Ireland,S,Denmark,50,"AWS, Java, Data Visualization",Associate,1,Retail,2024-06-29,2024-07-18,2272,7,Cloud AI Solutions -AI02713,AI Research Scientist,153723,SGD,199840,EX,CT,Singapore,M,Singapore,0,"Deep Learning, Linux, Computer Vision",Associate,16,Transportation,2025-01-28,2025-04-02,743,5.1,DeepTech Ventures -AI02714,AI Architect,185811,USD,185811,EX,PT,Israel,S,Israel,50,"Hadoop, Kubernetes, Tableau, Spark",Associate,12,Government,2025-04-13,2025-05-26,513,6.5,Autonomous Tech -AI02715,AI Product Manager,49147,EUR,41775,EN,FL,Germany,S,Germany,0,"Data Visualization, Docker, Spark, TensorFlow, Statistics",PhD,1,Gaming,2024-02-05,2024-04-08,996,8.1,TechCorp Inc -AI02716,Computer Vision Engineer,102077,USD,102077,MI,PT,Norway,M,Norway,0,"Kubernetes, Java, Statistics, Mathematics",Bachelor,3,Education,2024-05-05,2024-05-26,2332,5.2,Cloud AI Solutions -AI02717,Robotics Engineer,62401,USD,62401,SE,CT,China,M,Kenya,100,"TensorFlow, Java, Azure, Tableau, R",PhD,6,Retail,2024-08-24,2024-09-25,889,5.4,Cloud AI Solutions -AI02718,AI Architect,107823,EUR,91650,SE,CT,Austria,M,Australia,50,"Statistics, PyTorch, Tableau, Scala",Associate,5,Media,2024-11-10,2024-12-26,1821,8.7,DeepTech Ventures -AI02719,AI Consultant,91347,EUR,77645,MI,CT,Austria,S,Austria,100,"AWS, Linux, Docker",PhD,3,Energy,2024-08-10,2024-10-11,539,6.3,DeepTech Ventures -AI02720,AI Specialist,51459,USD,51459,SE,PT,India,L,India,100,"R, Docker, Statistics, SQL",PhD,5,Transportation,2024-04-23,2024-05-30,1996,9,Smart Analytics -AI02721,AI Product Manager,81873,USD,81873,EN,FT,Denmark,M,Denmark,100,"Linux, Computer Vision, Data Visualization, Git",Associate,0,Healthcare,2024-08-19,2024-09-08,1229,9.3,Cloud AI Solutions -AI02722,ML Ops Engineer,83272,USD,83272,MI,CT,United States,S,United States,50,"Kubernetes, SQL, TensorFlow, NLP",Master,2,Real Estate,2024-05-23,2024-07-07,1214,5.3,Smart Analytics -AI02723,Machine Learning Researcher,116075,SGD,150898,SE,CT,Singapore,S,Singapore,50,"Python, Spark, Java, TensorFlow",Bachelor,7,Education,2024-08-23,2024-10-31,781,5.1,AI Innovations -AI02724,Head of AI,89742,USD,89742,SE,PT,Finland,S,Finland,0,"PyTorch, Statistics, Data Visualization, SQL",Bachelor,9,Telecommunications,2024-08-25,2024-09-19,1044,7.7,Smart Analytics -AI02725,Machine Learning Researcher,72250,USD,72250,EN,FL,Ireland,L,Nigeria,0,"MLOps, Git, PyTorch",Associate,1,Education,2024-10-28,2024-12-05,1070,8.1,Cloud AI Solutions -AI02726,AI Product Manager,89161,CHF,80245,EN,CT,Switzerland,M,Switzerland,100,"Kubernetes, Statistics, Tableau, Data Visualization",Master,1,Consulting,2025-03-04,2025-03-25,905,5.5,Digital Transformation LLC -AI02727,AI Software Engineer,248371,SGD,322882,EX,CT,Singapore,M,Singapore,100,"Spark, Python, Data Visualization, Kubernetes, Deep Learning",Master,19,Retail,2025-01-19,2025-03-05,628,9.1,Machine Intelligence Group -AI02728,Head of AI,237882,GBP,178412,EX,FL,United Kingdom,M,United Kingdom,0,"R, Linux, SQL, Mathematics, MLOps",PhD,12,Consulting,2024-11-11,2024-12-17,1603,7.7,Autonomous Tech -AI02729,AI Product Manager,234093,CHF,210684,SE,FT,Switzerland,L,Switzerland,0,"Data Visualization, TensorFlow, Statistics",Bachelor,8,Consulting,2025-03-21,2025-05-19,2420,5.4,Cloud AI Solutions -AI02730,Head of AI,69998,EUR,59498,EN,FT,France,M,France,50,"Azure, Kubernetes, Scala",Associate,1,Government,2024-07-17,2024-08-09,557,8.1,Algorithmic Solutions -AI02731,Principal Data Scientist,92320,EUR,78472,MI,FL,Netherlands,M,Norway,50,"R, SQL, Azure",Master,3,Government,2024-05-01,2024-06-25,2297,9.4,DeepTech Ventures -AI02732,Principal Data Scientist,61179,CAD,76474,EN,FT,Canada,S,Canada,100,"Hadoop, Kubernetes, MLOps, Docker",PhD,0,Media,2024-04-09,2024-05-11,1420,7.8,Autonomous Tech -AI02733,Deep Learning Engineer,61702,EUR,52447,MI,CT,France,S,France,50,"Java, Hadoop, Tableau, Kubernetes, AWS",Bachelor,3,Technology,2025-02-05,2025-02-20,1250,9,Autonomous Tech -AI02734,Autonomous Systems Engineer,85122,USD,85122,EN,FL,Norway,L,Norway,100,"PyTorch, TensorFlow, Azure, Git",Master,1,Energy,2024-03-29,2024-04-27,734,8,Quantum Computing Inc -AI02735,Data Analyst,78254,USD,78254,EN,PT,Denmark,M,Denmark,0,"TensorFlow, AWS, Hadoop",Bachelor,1,Technology,2025-01-25,2025-02-15,1718,8.4,Quantum Computing Inc -AI02736,AI Research Scientist,70895,USD,70895,EN,PT,Sweden,S,Sweden,50,"Scala, PyTorch, MLOps, SQL, Computer Vision",Associate,1,Government,2025-01-11,2025-03-18,1398,5.8,Future Systems -AI02737,Data Engineer,199927,USD,199927,SE,CT,Norway,L,Latvia,50,"SQL, Spark, PyTorch",Associate,6,Healthcare,2024-03-17,2024-04-02,1138,6.9,Cloud AI Solutions -AI02738,Deep Learning Engineer,170229,CAD,212786,EX,CT,Canada,M,United States,50,"Deep Learning, R, Hadoop, Kubernetes, SQL",Master,16,Retail,2024-03-29,2024-04-30,1109,8.8,Smart Analytics -AI02739,Data Engineer,154419,USD,154419,MI,FT,Norway,L,Norway,50,"Tableau, Computer Vision, Python, TensorFlow, Java",Master,4,Technology,2024-08-12,2024-10-08,1099,9.3,DataVision Ltd -AI02740,AI Product Manager,162643,EUR,138247,SE,CT,Netherlands,L,South Africa,100,"Python, TensorFlow, Tableau, PyTorch",PhD,9,Media,2024-03-24,2024-05-21,2247,7.3,Neural Networks Co -AI02741,Computer Vision Engineer,268185,JPY,29500350,EX,CT,Japan,L,Argentina,50,"Data Visualization, Spark, NLP",Bachelor,11,Automotive,2024-12-27,2025-01-16,942,8.7,TechCorp Inc -AI02742,Data Scientist,180863,GBP,135647,SE,PT,United Kingdom,L,United Kingdom,50,"Python, GCP, TensorFlow, NLP, PyTorch",Bachelor,5,Automotive,2024-01-21,2024-02-20,1397,7.6,Cognitive Computing -AI02743,Machine Learning Researcher,34377,USD,34377,EN,CT,China,L,China,0,"PyTorch, TensorFlow, Computer Vision, Mathematics",Bachelor,1,Real Estate,2024-03-01,2024-05-03,1626,5.8,Machine Intelligence Group -AI02744,Deep Learning Engineer,66309,USD,66309,EX,PT,China,M,China,100,"Spark, Tableau, Linux",Associate,12,Real Estate,2025-01-23,2025-04-05,2186,7.5,TechCorp Inc -AI02745,Computer Vision Engineer,151661,SGD,197159,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, NLP, Mathematics",Master,17,Automotive,2025-01-21,2025-03-24,2125,6,Algorithmic Solutions -AI02746,Principal Data Scientist,169405,JPY,18634550,EX,FL,Japan,M,Sweden,100,"R, Hadoop, Linux",Bachelor,10,Consulting,2024-02-12,2024-03-16,2077,9,DeepTech Ventures -AI02747,NLP Engineer,72571,JPY,7982810,EN,CT,Japan,S,Japan,50,"AWS, Hadoop, SQL, PyTorch",Associate,0,Consulting,2024-11-22,2025-01-29,1015,5,Machine Intelligence Group -AI02748,Data Scientist,240989,GBP,180742,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, TensorFlow, NLP, MLOps",PhD,15,Energy,2024-08-22,2024-10-13,2290,8.6,Future Systems -AI02749,Data Analyst,44658,USD,44658,EN,FL,Finland,S,Finland,0,"AWS, PyTorch, Tableau",Bachelor,1,Energy,2024-08-26,2024-10-14,1578,9.3,Smart Analytics -AI02750,Autonomous Systems Engineer,51559,EUR,43825,EN,CT,France,S,France,50,"Scala, Deep Learning, Computer Vision, PyTorch, SQL",PhD,1,Technology,2024-06-24,2024-07-27,2101,9.5,Cognitive Computing -AI02751,NLP Engineer,165686,CHF,149117,MI,CT,Switzerland,L,Switzerland,100,"Docker, Statistics, Python",Bachelor,2,Real Estate,2024-05-23,2024-06-23,1760,7.2,DeepTech Ventures -AI02752,Head of AI,105339,CHF,94805,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Git, Deep Learning, Data Visualization",Master,0,Healthcare,2024-08-02,2024-08-24,876,8,Algorithmic Solutions -AI02753,AI Software Engineer,209800,EUR,178330,EX,CT,Netherlands,M,Netherlands,0,"Kubernetes, Python, SQL",PhD,18,Consulting,2024-11-19,2024-12-05,2126,8.9,Predictive Systems -AI02754,AI Architect,118780,USD,118780,MI,FT,United States,M,United States,0,"SQL, Data Visualization, TensorFlow, MLOps",Associate,3,Consulting,2025-02-06,2025-03-13,933,6.8,Smart Analytics -AI02755,AI Consultant,125984,CAD,157480,SE,FL,Canada,S,Canada,100,"NLP, Java, Computer Vision",Bachelor,6,Finance,2024-10-30,2024-12-23,1473,9.1,Future Systems -AI02756,Research Scientist,121739,SGD,158261,SE,FT,Singapore,M,Singapore,0,"PyTorch, Java, Spark",PhD,6,Technology,2024-08-19,2024-10-25,1712,8.9,Cloud AI Solutions -AI02757,Deep Learning Engineer,141394,EUR,120185,SE,FT,Netherlands,M,Chile,50,"Hadoop, TensorFlow, Python",Bachelor,5,Telecommunications,2024-05-08,2024-06-01,1923,8.8,Cloud AI Solutions -AI02758,Machine Learning Researcher,74325,USD,74325,EN,FL,Norway,S,Norway,0,"Linux, MLOps, SQL, R",Master,0,Technology,2024-06-21,2024-08-02,2350,9.2,DataVision Ltd -AI02759,Head of AI,181015,SGD,235320,SE,PT,Singapore,L,Singapore,100,"Java, SQL, GCP",Master,7,Technology,2025-03-01,2025-03-26,968,6.6,Cognitive Computing -AI02760,NLP Engineer,54802,SGD,71243,EN,FT,Singapore,M,Singapore,0,"Scala, Python, Docker, Computer Vision",Bachelor,0,Healthcare,2025-03-24,2025-05-20,733,6.3,Smart Analytics -AI02761,Data Analyst,113391,JPY,12473010,MI,PT,Japan,M,Japan,100,"Scala, Data Visualization, Git, Spark",Master,3,Automotive,2024-04-11,2024-05-16,865,8.5,Future Systems -AI02762,NLP Engineer,171064,USD,171064,EX,CT,Ireland,L,Ireland,50,"AWS, PyTorch, Computer Vision, Hadoop, SQL",Bachelor,15,Consulting,2024-11-10,2024-12-27,1791,7.2,Cloud AI Solutions -AI02763,Head of AI,122125,USD,122125,MI,FT,Denmark,M,Denmark,100,"Scala, Tableau, Python, Linux",Bachelor,3,Media,2024-10-08,2024-12-18,1199,7.4,Cognitive Computing -AI02764,Machine Learning Engineer,133237,AUD,179870,SE,CT,Australia,S,Australia,50,"Python, Hadoop, Linux, Scala, Computer Vision",Associate,5,Retail,2024-04-22,2024-06-26,1707,8.4,Machine Intelligence Group -AI02765,Deep Learning Engineer,89475,JPY,9842250,EN,PT,Japan,L,Japan,100,"Python, TensorFlow, Git, Mathematics, Spark",PhD,1,Transportation,2025-01-01,2025-02-27,1924,5.1,DeepTech Ventures -AI02766,AI Product Manager,92805,USD,92805,MI,FL,United States,S,New Zealand,50,"Linux, Spark, Scala, MLOps",Associate,2,Government,2024-04-10,2024-06-21,1389,8,Digital Transformation LLC -AI02767,AI Product Manager,277302,AUD,374358,EX,PT,Australia,L,Australia,100,"Git, Statistics, TensorFlow, SQL, Kubernetes",Master,14,Finance,2024-03-27,2024-05-08,1139,5.7,Quantum Computing Inc -AI02768,AI Consultant,157131,USD,157131,SE,FT,Norway,L,Norway,50,"Spark, Tableau, Computer Vision, NLP",PhD,8,Automotive,2024-07-01,2024-08-31,1981,7.3,Cognitive Computing -AI02769,Machine Learning Engineer,124242,EUR,105606,SE,CT,France,S,Singapore,50,"Spark, Mathematics, MLOps",Master,6,Media,2024-04-29,2024-07-09,2466,9.1,Predictive Systems -AI02770,Robotics Engineer,165005,AUD,222757,EX,FL,Australia,L,Austria,0,"Mathematics, Computer Vision, Data Visualization, Statistics",PhD,18,Education,2024-08-08,2024-09-14,1077,7.9,Quantum Computing Inc -AI02771,Data Analyst,55240,EUR,46954,EN,CT,Austria,S,Austria,0,"Kubernetes, Deep Learning, Git",Bachelor,1,Finance,2024-06-24,2024-08-24,1766,9.7,Neural Networks Co -AI02772,Robotics Engineer,39042,USD,39042,SE,PT,India,M,Colombia,0,"Deep Learning, Linux, Java",Bachelor,6,Manufacturing,2025-02-28,2025-04-17,655,8.5,Autonomous Tech -AI02773,Machine Learning Researcher,64577,USD,64577,EX,FL,India,M,India,50,"NLP, SQL, Scala",Bachelor,15,Government,2024-03-01,2024-04-21,1560,6.6,Cognitive Computing -AI02774,Head of AI,50657,USD,50657,EN,CT,Israel,S,Israel,0,"Python, Java, Tableau, TensorFlow, Mathematics",PhD,0,Real Estate,2024-11-23,2024-12-14,1622,9.1,TechCorp Inc -AI02775,Machine Learning Engineer,108147,GBP,81110,SE,FL,United Kingdom,M,Switzerland,100,"MLOps, Kubernetes, R",Associate,6,Finance,2025-02-07,2025-02-25,690,5.1,Future Systems -AI02776,Robotics Engineer,186468,USD,186468,EX,FL,Norway,M,Norway,100,"TensorFlow, AWS, Data Visualization, Python",Master,17,Automotive,2024-09-06,2024-10-09,2476,5.1,Digital Transformation LLC -AI02777,Data Engineer,148941,EUR,126600,SE,PT,Germany,M,Germany,0,"Python, NLP, Docker, GCP",Bachelor,6,Media,2025-04-24,2025-05-18,2164,9.1,Digital Transformation LLC -AI02778,AI Software Engineer,61003,USD,61003,EN,FT,Norway,S,Norway,100,"Statistics, Computer Vision, Data Visualization",PhD,0,Manufacturing,2025-04-09,2025-05-26,847,7.2,Cloud AI Solutions -AI02779,ML Ops Engineer,130513,USD,130513,SE,PT,Ireland,L,Ireland,0,"Linux, Kubernetes, Scala, Java",Bachelor,9,Technology,2024-05-30,2024-06-22,1034,5.3,Future Systems -AI02780,AI Architect,218583,EUR,185796,EX,FT,France,L,France,100,"Hadoop, R, SQL, PyTorch, Git",PhD,18,Gaming,2024-05-06,2024-06-10,1862,9.4,Machine Intelligence Group -AI02781,AI Consultant,57623,USD,57623,EN,FT,Sweden,S,Sweden,50,"Tableau, AWS, Hadoop, Docker, Statistics",Bachelor,0,Media,2024-05-30,2024-06-20,973,9.8,Future Systems -AI02782,AI Product Manager,63893,USD,63893,EN,FL,South Korea,M,Australia,0,"Linux, Deep Learning, Java, SQL, AWS",PhD,1,Finance,2025-01-12,2025-01-27,984,9.8,Smart Analytics -AI02783,AI Consultant,198531,USD,198531,EX,FL,Norway,M,Norway,100,"AWS, Kubernetes, NLP, Statistics",Associate,12,Transportation,2025-04-14,2025-05-14,1650,9.5,Cognitive Computing -AI02784,Machine Learning Researcher,66355,SGD,86262,EN,FT,Singapore,S,Singapore,100,"Kubernetes, Tableau, Hadoop",PhD,1,Finance,2024-03-10,2024-03-28,762,8.1,Cognitive Computing -AI02785,Head of AI,71500,USD,71500,EN,FT,Finland,L,Finland,0,"R, Hadoop, Linux, SQL, Computer Vision",Master,1,Automotive,2025-01-26,2025-04-01,1426,6.3,AI Innovations -AI02786,AI Specialist,99853,USD,99853,MI,FT,Israel,L,Israel,0,"Computer Vision, Kubernetes, SQL, Docker",Master,2,Consulting,2025-01-07,2025-03-21,679,10,AI Innovations -AI02787,Autonomous Systems Engineer,160109,CHF,144098,SE,PT,Switzerland,M,Thailand,100,"MLOps, AWS, Spark, R",Master,5,Consulting,2024-02-18,2024-03-28,914,9,Digital Transformation LLC -AI02788,AI Specialist,126146,USD,126146,SE,CT,Sweden,M,United Kingdom,50,"PyTorch, TensorFlow, R, SQL, Spark",Master,9,Media,2025-03-06,2025-05-10,2264,8.7,Quantum Computing Inc -AI02789,AI Consultant,32128,USD,32128,EN,PT,China,L,China,50,"Python, Spark, MLOps, TensorFlow, Scala",Master,0,Media,2024-04-23,2024-07-02,1091,7.4,Future Systems -AI02790,AI Software Engineer,23707,USD,23707,EN,FL,India,M,Spain,0,"PyTorch, Hadoop, Deep Learning, Linux",Bachelor,1,Healthcare,2024-03-02,2024-04-27,1306,9.8,Predictive Systems -AI02791,Data Scientist,210918,CAD,263648,EX,FT,Canada,L,Japan,50,"Python, R, Docker, Linux",Master,10,Energy,2024-01-03,2024-01-31,881,7.5,Future Systems -AI02792,AI Architect,132476,EUR,112605,SE,CT,France,L,France,50,"PyTorch, Spark, Statistics, Python",PhD,6,Education,2024-10-16,2024-11-05,2332,7.4,Digital Transformation LLC -AI02793,Research Scientist,97049,EUR,82492,SE,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Git",PhD,5,Telecommunications,2025-01-10,2025-03-02,1819,8.1,Smart Analytics -AI02794,AI Software Engineer,52529,CAD,65661,EN,FT,Canada,M,Ireland,100,"MLOps, Spark, Tableau, Scala, Statistics",Master,0,Manufacturing,2024-03-06,2024-04-27,2052,5.1,Cognitive Computing -AI02795,Principal Data Scientist,204220,EUR,173587,EX,PT,Austria,S,Egypt,50,"Computer Vision, Deep Learning, Linux",Bachelor,12,Automotive,2024-03-24,2024-04-13,607,8.7,TechCorp Inc -AI02796,AI Software Engineer,132720,SGD,172536,SE,FL,Singapore,L,Singapore,50,"R, Hadoop, Tableau",Bachelor,8,Media,2024-08-04,2024-10-16,1384,6.8,Advanced Robotics -AI02797,Autonomous Systems Engineer,81244,USD,81244,MI,CT,Finland,L,Finland,50,"Docker, Hadoop, Statistics, Linux",Master,4,Manufacturing,2024-05-17,2024-06-27,1528,9.8,Machine Intelligence Group -AI02798,Machine Learning Researcher,161739,USD,161739,MI,FL,Norway,L,Norway,100,"NLP, Kubernetes, PyTorch, Docker, SQL",Master,3,Automotive,2024-04-06,2024-06-08,1521,6.4,DataVision Ltd -AI02799,ML Ops Engineer,71582,CAD,89478,MI,CT,Canada,S,Canada,0,"Kubernetes, Scala, AWS, TensorFlow",PhD,4,Manufacturing,2025-01-18,2025-02-05,865,9.2,DataVision Ltd -AI02800,Robotics Engineer,55770,USD,55770,SE,PT,China,S,China,0,"Docker, R, AWS, Python, Kubernetes",Bachelor,6,Manufacturing,2025-02-17,2025-03-12,1015,9.6,Smart Analytics -AI02801,AI Product Manager,176027,USD,176027,SE,CT,Norway,M,Norway,0,"R, SQL, Tableau",Bachelor,7,Government,2024-08-01,2024-10-05,1205,5.3,Machine Intelligence Group -AI02802,AI Product Manager,47687,USD,47687,SE,CT,India,L,Japan,0,"Data Visualization, TensorFlow, Statistics",Associate,9,Telecommunications,2024-07-20,2024-09-18,681,6.2,Advanced Robotics -AI02803,Autonomous Systems Engineer,60812,USD,60812,MI,PT,South Korea,M,South Korea,0,"R, Git, Deep Learning, GCP",Master,4,Finance,2024-07-02,2024-08-07,628,7.4,Predictive Systems -AI02804,Research Scientist,126567,JPY,13922370,MI,PT,Japan,L,Netherlands,50,"PyTorch, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-12-15,2024-12-29,2386,7.1,Cognitive Computing -AI02805,Research Scientist,97033,SGD,126143,MI,CT,Singapore,S,France,0,"Azure, GCP, Spark, Statistics, Computer Vision",Master,2,Real Estate,2025-02-08,2025-04-19,2196,9.6,Future Systems -AI02806,AI Specialist,70605,USD,70605,EN,FL,Norway,S,Norway,0,"Kubernetes, GCP, Spark, Tableau, Python",Bachelor,0,Consulting,2024-08-04,2024-09-14,1382,8.9,Autonomous Tech -AI02807,Deep Learning Engineer,121078,USD,121078,SE,FT,Israel,L,Israel,50,"Computer Vision, Azure, Data Visualization, Java",Bachelor,5,Retail,2024-06-11,2024-07-22,1033,5.9,DeepTech Ventures -AI02808,ML Ops Engineer,255771,USD,255771,EX,FT,Denmark,S,Denmark,0,"Azure, Kubernetes, Tableau, Python, Hadoop",Master,10,Transportation,2024-11-13,2025-01-14,1097,5.4,Machine Intelligence Group -AI02809,Data Engineer,111629,EUR,94885,SE,PT,France,L,France,50,"Tableau, Statistics, Spark",Master,9,Healthcare,2024-02-07,2024-03-13,1123,6.3,DeepTech Ventures -AI02810,Autonomous Systems Engineer,127275,USD,127275,MI,PT,Denmark,S,Denmark,100,"Java, AWS, SQL, NLP, Deep Learning",Associate,3,Automotive,2024-08-07,2024-09-19,2009,7,Smart Analytics -AI02811,Robotics Engineer,226295,USD,226295,EX,FL,Ireland,S,New Zealand,100,"Docker, Python, AWS",Associate,19,Consulting,2025-01-26,2025-02-12,615,7.6,Autonomous Tech -AI02812,AI Consultant,60249,USD,60249,EN,FL,Sweden,M,Sweden,50,"Scala, Mathematics, Tableau, Statistics, MLOps",Associate,0,Real Estate,2024-01-15,2024-03-05,2151,5.3,Quantum Computing Inc -AI02813,Principal Data Scientist,154394,USD,154394,SE,FL,United States,S,United States,0,"Kubernetes, Hadoop, Python, Azure",Master,5,Manufacturing,2024-04-19,2024-06-20,611,9.2,Digital Transformation LLC -AI02814,Deep Learning Engineer,77141,EUR,65570,MI,CT,Netherlands,S,Russia,0,"Kubernetes, Data Visualization, Mathematics",Associate,2,Automotive,2025-03-24,2025-04-09,1999,7.6,DataVision Ltd -AI02815,AI Product Manager,89813,EUR,76341,MI,PT,Austria,M,Austria,100,"GCP, Java, PyTorch",Associate,2,Technology,2024-06-20,2024-08-20,2490,8.9,Algorithmic Solutions -AI02816,Research Scientist,80989,USD,80989,MI,FT,Finland,S,Finland,0,"R, Statistics, Hadoop, Docker",PhD,4,Retail,2025-02-14,2025-04-25,540,8.4,DataVision Ltd -AI02817,Data Engineer,271778,CHF,244600,EX,PT,Switzerland,L,Switzerland,50,"AWS, Scala, Docker",Bachelor,12,Consulting,2024-03-23,2024-05-31,1285,5.1,Algorithmic Solutions -AI02818,AI Research Scientist,46378,USD,46378,SE,FL,India,S,India,100,"SQL, NLP, PyTorch",Associate,9,Finance,2025-01-26,2025-02-11,1773,9.2,Digital Transformation LLC -AI02819,Principal Data Scientist,101913,EUR,86626,MI,FL,Germany,L,Germany,50,"Spark, Java, MLOps, PyTorch",PhD,3,Telecommunications,2025-01-12,2025-03-23,2063,7.4,Quantum Computing Inc -AI02820,Data Analyst,29407,USD,29407,MI,PT,India,M,India,50,"SQL, TensorFlow, Tableau",PhD,4,Retail,2024-04-30,2024-06-23,2053,5.5,Predictive Systems -AI02821,AI Specialist,122457,USD,122457,EX,FL,South Korea,M,South Korea,0,"Scala, Deep Learning, R, Hadoop, Statistics",Master,12,Automotive,2024-03-13,2024-05-23,595,6.7,Machine Intelligence Group -AI02822,AI Research Scientist,121296,EUR,103102,SE,CT,France,M,Philippines,100,"Data Visualization, SQL, PyTorch",PhD,6,Technology,2024-02-12,2024-03-24,602,6.3,Neural Networks Co -AI02823,AI Specialist,154186,USD,154186,SE,CT,Norway,S,Norway,0,"Git, PyTorch, Tableau, MLOps",PhD,6,Gaming,2024-11-07,2024-12-15,1374,9.5,AI Innovations -AI02824,Robotics Engineer,215813,CAD,269766,EX,CT,Canada,S,Canada,0,"Python, Hadoop, SQL",Master,17,Government,2025-01-06,2025-02-04,664,6.1,TechCorp Inc -AI02825,Robotics Engineer,121313,SGD,157707,MI,FT,Singapore,L,Switzerland,50,"Git, NLP, PyTorch, Python",Associate,4,Gaming,2024-10-05,2024-11-20,1250,8,Predictive Systems -AI02826,Machine Learning Researcher,103697,JPY,11406670,MI,CT,Japan,S,Japan,0,"SQL, Scala, Hadoop, Azure",Bachelor,2,Energy,2024-01-30,2024-03-07,657,5.6,Algorithmic Solutions -AI02827,Research Scientist,148481,CHF,133633,MI,FT,Switzerland,M,Switzerland,0,"Python, MLOps, SQL, Java, Kubernetes",Bachelor,3,Manufacturing,2024-07-11,2024-09-16,1271,8.3,Future Systems -AI02828,AI Software Engineer,247799,USD,247799,EX,CT,Norway,S,Norway,50,"PyTorch, SQL, Linux, Hadoop",Associate,18,Media,2024-04-27,2024-06-30,717,7.8,Cognitive Computing -AI02829,Autonomous Systems Engineer,250860,USD,250860,EX,FL,United States,M,United States,50,"SQL, Tableau, Kubernetes, GCP",Associate,10,Transportation,2024-06-25,2024-07-11,891,7.8,Quantum Computing Inc -AI02830,Research Scientist,163167,AUD,220275,EX,CT,Australia,S,Australia,100,"Kubernetes, Java, GCP, SQL, AWS",Bachelor,19,Energy,2024-01-27,2024-04-03,1603,5.9,Autonomous Tech -AI02831,Principal Data Scientist,323671,USD,323671,EX,CT,United States,L,United States,50,"Computer Vision, Hadoop, Deep Learning",PhD,15,Telecommunications,2025-04-28,2025-06-15,1701,8.3,TechCorp Inc -AI02832,Robotics Engineer,70337,USD,70337,EN,FT,Norway,S,Norway,100,"Hadoop, NLP, SQL, Scala",Associate,1,Healthcare,2024-08-27,2024-10-10,888,9.2,Machine Intelligence Group -AI02833,Data Analyst,63357,EUR,53853,EN,FL,Germany,M,Egypt,100,"Mathematics, Data Visualization, Scala, SQL, Tableau",Bachelor,1,Government,2025-02-15,2025-03-29,2153,5.6,Digital Transformation LLC -AI02834,Head of AI,107154,USD,107154,SE,FL,Israel,S,Israel,0,"PyTorch, GCP, NLP, Java",Master,8,Healthcare,2024-06-22,2024-08-26,1412,6.5,TechCorp Inc -AI02835,AI Research Scientist,184525,USD,184525,SE,PT,Norway,M,Norway,0,"SQL, Python, AWS, TensorFlow",Master,5,Retail,2024-01-26,2024-02-09,2036,5.8,Algorithmic Solutions -AI02836,Robotics Engineer,94391,EUR,80232,MI,FL,Austria,L,Austria,100,"Spark, PyTorch, Python, MLOps",Master,3,Media,2025-01-05,2025-01-27,1704,5.7,Smart Analytics -AI02837,NLP Engineer,134275,USD,134275,SE,FL,South Korea,L,South Korea,0,"Spark, Azure, Computer Vision, Data Visualization, SQL",PhD,9,Automotive,2024-08-26,2024-11-05,1728,5.9,Autonomous Tech -AI02838,AI Consultant,211162,USD,211162,EX,FT,United States,M,United States,50,"Spark, Python, Tableau",PhD,19,Technology,2024-04-12,2024-05-17,2411,9.2,DataVision Ltd -AI02839,Computer Vision Engineer,70647,USD,70647,EN,PT,Ireland,L,Ireland,0,"Python, Statistics, Mathematics, Docker, TensorFlow",Bachelor,0,Education,2024-07-17,2024-09-10,1471,9.5,DataVision Ltd -AI02840,Principal Data Scientist,243402,USD,243402,EX,FT,Finland,L,Finland,0,"AWS, NLP, Docker, Linux",Bachelor,11,Consulting,2024-04-28,2024-05-12,2037,8.1,Digital Transformation LLC -AI02841,AI Product Manager,57000,USD,57000,EN,FL,South Korea,S,India,100,"Linux, SQL, Scala",Associate,0,Finance,2024-11-08,2025-01-03,1424,7.6,Smart Analytics -AI02842,Data Analyst,90610,USD,90610,MI,CT,Israel,S,Israel,50,"Kubernetes, Scala, Mathematics",PhD,4,Telecommunications,2025-02-14,2025-03-18,2329,9.1,Future Systems -AI02843,Research Scientist,240830,EUR,204706,EX,FL,Austria,L,Austria,50,"PyTorch, SQL, Java, Linux, Statistics",PhD,16,Manufacturing,2024-03-29,2024-04-13,563,9.3,Smart Analytics -AI02844,Robotics Engineer,205777,EUR,174910,EX,FL,Austria,L,Colombia,0,"GCP, Spark, TensorFlow, Git",Bachelor,11,Healthcare,2025-04-18,2025-05-27,1273,6.4,DataVision Ltd -AI02845,Machine Learning Researcher,52483,USD,52483,EN,FT,Finland,M,Finland,100,"Hadoop, Data Visualization, SQL",Bachelor,0,Manufacturing,2024-08-30,2024-09-21,1921,9.4,Neural Networks Co -AI02846,Principal Data Scientist,35085,USD,35085,MI,PT,India,M,India,50,"Python, TensorFlow, Mathematics, Hadoop",Associate,4,Media,2025-04-17,2025-05-05,525,9.2,Algorithmic Solutions -AI02847,Principal Data Scientist,170138,USD,170138,SE,PT,Ireland,L,Belgium,0,"Linux, Python, TensorFlow, AWS, Tableau",Master,7,Technology,2025-04-08,2025-05-22,1991,7.6,Advanced Robotics -AI02848,AI Software Engineer,86746,USD,86746,MI,FT,Ireland,M,Turkey,100,"Docker, SQL, Computer Vision",Associate,2,Consulting,2024-12-19,2025-02-26,2126,7.6,Predictive Systems -AI02849,Data Analyst,27601,USD,27601,MI,FT,India,S,India,50,"Python, TensorFlow, Mathematics, MLOps, SQL",Bachelor,4,Technology,2024-05-17,2024-07-06,2050,9.4,Future Systems -AI02850,Principal Data Scientist,114696,USD,114696,SE,FT,Sweden,S,Sweden,0,"Computer Vision, Java, Git, TensorFlow",Associate,7,Government,2025-02-28,2025-05-10,736,6,Neural Networks Co -AI02851,Data Analyst,123445,USD,123445,SE,FT,Finland,M,Canada,50,"Kubernetes, Python, AWS, SQL",Master,5,Telecommunications,2025-04-26,2025-06-15,1506,5.1,Quantum Computing Inc -AI02852,Head of AI,70615,USD,70615,EN,CT,South Korea,L,South Korea,50,"PyTorch, GCP, Linux, Spark",Associate,0,Automotive,2025-04-16,2025-06-19,1374,5.4,Neural Networks Co -AI02853,Data Scientist,190307,CAD,237884,EX,CT,Canada,L,Canada,100,"Statistics, Kubernetes, Azure",Master,17,Consulting,2024-03-30,2024-04-16,746,5.6,Cognitive Computing -AI02854,AI Software Engineer,319590,USD,319590,EX,FL,United States,L,United States,100,"PyTorch, MLOps, GCP",Master,19,Government,2024-01-01,2024-03-14,720,6.4,Cloud AI Solutions -AI02855,AI Research Scientist,207479,USD,207479,SE,PT,Norway,L,China,0,"NLP, Python, Computer Vision, Mathematics",Master,7,Technology,2024-06-03,2024-06-17,2025,6.2,Cloud AI Solutions -AI02856,AI Product Manager,131422,USD,131422,MI,FL,United States,L,Vietnam,50,"Java, Computer Vision, AWS",Associate,4,Gaming,2024-05-24,2024-07-17,1676,5.2,Digital Transformation LLC -AI02857,ML Ops Engineer,95848,EUR,81471,MI,PT,Germany,M,Thailand,0,"Linux, Spark, Deep Learning",Associate,4,Consulting,2024-09-08,2024-10-22,919,5.3,Predictive Systems -AI02858,Robotics Engineer,94145,JPY,10355950,MI,FL,Japan,L,Japan,50,"Python, R, Mathematics, Scala, NLP",PhD,4,Real Estate,2024-01-20,2024-03-09,721,7.5,AI Innovations -AI02859,AI Consultant,130395,CAD,162994,SE,CT,Canada,L,Canada,100,"GCP, Python, MLOps, Kubernetes",PhD,9,Real Estate,2024-12-01,2025-02-05,1098,6.4,Neural Networks Co -AI02860,Robotics Engineer,77116,EUR,65549,EN,CT,Germany,M,Germany,100,"Kubernetes, Computer Vision, Hadoop",Associate,0,Education,2024-03-23,2024-05-01,2136,5.7,Algorithmic Solutions -AI02861,Robotics Engineer,21922,USD,21922,EN,PT,India,L,Romania,50,"Spark, Java, GCP",Bachelor,0,Finance,2024-11-06,2025-01-12,624,5.3,TechCorp Inc -AI02862,AI Research Scientist,248823,USD,248823,EX,CT,United States,S,United States,100,"Python, Git, Mathematics, TensorFlow, Statistics",Bachelor,13,Education,2024-10-05,2024-12-01,990,6.8,Advanced Robotics -AI02863,Head of AI,36405,USD,36405,MI,PT,India,M,India,100,"Linux, Deep Learning, Python, NLP",Master,3,Automotive,2024-10-21,2024-11-13,2089,5.7,DataVision Ltd -AI02864,Principal Data Scientist,253609,EUR,215568,EX,CT,France,L,France,50,"Spark, Tableau, Linux, Python, R",PhD,15,Transportation,2024-10-23,2024-11-12,2390,6,Advanced Robotics -AI02865,NLP Engineer,203699,CHF,183329,SE,CT,Switzerland,M,China,0,"Python, Kubernetes, Computer Vision, TensorFlow, Statistics",PhD,5,Media,2025-02-04,2025-02-21,1665,7.3,Autonomous Tech -AI02866,Machine Learning Engineer,141871,CHF,127684,MI,FL,Switzerland,M,Estonia,100,"Scala, SQL, TensorFlow, Java",Bachelor,2,Finance,2024-01-19,2024-03-02,1034,7.5,Machine Intelligence Group -AI02867,AI Consultant,190310,AUD,256919,EX,PT,Australia,S,Australia,50,"Linux, PyTorch, R, Computer Vision, Python",PhD,10,Technology,2024-11-23,2024-12-18,793,9.6,Smart Analytics -AI02868,Data Scientist,68143,USD,68143,MI,CT,South Korea,S,China,50,"Mathematics, TensorFlow, Git, Python",PhD,2,Gaming,2024-12-29,2025-02-07,560,9.2,Autonomous Tech -AI02869,Robotics Engineer,74136,USD,74136,EN,FL,Ireland,L,Ireland,50,"Statistics, SQL, Azure",PhD,1,Automotive,2024-03-27,2024-06-01,886,9.6,DeepTech Ventures -AI02870,NLP Engineer,73619,EUR,62576,EN,CT,France,L,Estonia,0,"Kubernetes, R, MLOps",PhD,0,Telecommunications,2025-01-26,2025-04-04,1664,6.1,Digital Transformation LLC -AI02871,Research Scientist,77655,USD,77655,EN,PT,Denmark,M,Denmark,50,"Python, Spark, NLP, Java, SQL",Master,0,Media,2025-03-02,2025-05-04,859,9.1,Cloud AI Solutions -AI02872,NLP Engineer,123447,EUR,104930,SE,FL,Austria,S,Austria,50,"Python, TensorFlow, MLOps, Computer Vision",Associate,5,Retail,2024-11-21,2025-01-28,2155,9,Neural Networks Co -AI02873,AI Software Engineer,89174,USD,89174,MI,FL,United States,S,United States,50,"Linux, Statistics, SQL",PhD,4,Gaming,2024-04-10,2024-04-27,1358,7.6,Neural Networks Co -AI02874,Data Analyst,59752,USD,59752,SE,FT,India,L,India,100,"Deep Learning, SQL, Data Visualization, PyTorch, Hadoop",Associate,8,Retail,2024-07-17,2024-09-08,1777,6.7,Neural Networks Co -AI02875,AI Research Scientist,82657,USD,82657,EN,FT,United States,M,United States,100,"MLOps, Python, Linux, Deep Learning",Master,0,Consulting,2025-01-17,2025-03-14,1168,7.6,Digital Transformation LLC -AI02876,Data Analyst,60940,GBP,45705,EN,FL,United Kingdom,M,United Kingdom,50,"GCP, Statistics, Tableau, Data Visualization, NLP",Associate,1,Finance,2025-02-28,2025-04-30,1822,9.4,TechCorp Inc -AI02877,AI Specialist,147265,EUR,125175,EX,FT,Germany,M,Indonesia,50,"Kubernetes, Hadoop, PyTorch, Azure, Git",PhD,15,Real Estate,2024-04-11,2024-05-31,1634,7.4,Future Systems -AI02878,AI Research Scientist,87462,USD,87462,MI,PT,United States,M,Turkey,50,"Git, R, Mathematics, Linux",Associate,4,Telecommunications,2024-09-29,2024-11-18,808,5.4,DeepTech Ventures -AI02879,Principal Data Scientist,203296,CAD,254120,EX,FL,Canada,S,Canada,0,"Java, MLOps, R, Scala",Master,14,Telecommunications,2024-03-01,2024-04-12,1334,9.5,Machine Intelligence Group -AI02880,Machine Learning Researcher,102443,USD,102443,EN,FT,United States,L,Turkey,0,"NLP, TensorFlow, Data Visualization",PhD,0,Technology,2024-07-06,2024-08-13,2438,5.9,TechCorp Inc -AI02881,Autonomous Systems Engineer,165965,SGD,215755,EX,FL,Singapore,S,Singapore,50,"PyTorch, TensorFlow, Python, Statistics, Azure",Master,14,Healthcare,2024-03-31,2024-04-24,567,8.1,Algorithmic Solutions -AI02882,Computer Vision Engineer,142165,USD,142165,SE,FT,Israel,M,Thailand,0,"Python, Tableau, TensorFlow, Mathematics, PyTorch",Bachelor,6,Finance,2024-10-08,2024-12-12,544,8.6,DeepTech Ventures -AI02883,ML Ops Engineer,96944,SGD,126027,MI,FL,Singapore,S,Singapore,100,"Data Visualization, Linux, Scala, Azure",Associate,4,Consulting,2024-11-16,2025-01-19,2107,6,Quantum Computing Inc -AI02884,Data Analyst,101791,USD,101791,MI,FT,Norway,S,Norway,50,"R, Python, TensorFlow, Spark, Computer Vision",Bachelor,2,Technology,2024-04-23,2024-06-20,1704,7.1,Predictive Systems -AI02885,Data Engineer,24801,USD,24801,EN,FL,India,L,Estonia,100,"Scala, Spark, Python, Statistics",Bachelor,1,Manufacturing,2024-07-18,2024-08-18,2393,5.5,AI Innovations -AI02886,AI Specialist,76230,USD,76230,MI,CT,South Korea,M,South Korea,0,"GCP, PyTorch, Computer Vision",Master,3,Real Estate,2024-01-22,2024-03-16,1380,8.2,Future Systems -AI02887,AI Research Scientist,63817,CAD,79771,MI,FL,Canada,S,France,100,"PyTorch, Computer Vision, Mathematics",Bachelor,3,Consulting,2024-06-03,2024-08-12,1787,6.4,Algorithmic Solutions -AI02888,AI Specialist,65577,EUR,55740,MI,FL,Austria,S,Austria,0,"Scala, Mathematics, Linux, MLOps",Associate,3,Energy,2024-10-11,2024-11-04,1471,7.3,TechCorp Inc -AI02889,Autonomous Systems Engineer,114972,JPY,12646920,MI,FT,Japan,M,Japan,100,"Docker, Mathematics, Hadoop",PhD,3,Education,2024-01-25,2024-03-24,1490,7.5,Neural Networks Co -AI02890,AI Product Manager,87185,EUR,74107,SE,PT,Austria,S,Austria,100,"Spark, GCP, Git, Python",PhD,9,Consulting,2024-11-04,2024-12-27,2477,8.8,Autonomous Tech -AI02891,Deep Learning Engineer,212207,CHF,190986,SE,CT,Switzerland,M,Switzerland,100,"Tableau, Scala, Java, Spark, Linux",PhD,8,Gaming,2024-07-14,2024-08-24,519,6.9,Future Systems -AI02892,Machine Learning Engineer,90028,USD,90028,EN,PT,Denmark,L,Denmark,50,"R, SQL, PyTorch, Statistics, Kubernetes",Associate,1,Education,2024-12-24,2025-01-19,2044,7.2,DeepTech Ventures -AI02893,AI Product Manager,156876,JPY,17256360,SE,PT,Japan,L,Ireland,100,"Java, AWS, Computer Vision, Deep Learning",PhD,5,Gaming,2024-08-10,2024-08-28,1727,8.8,Neural Networks Co -AI02894,AI Consultant,116522,USD,116522,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Mathematics, Deep Learning",PhD,6,Manufacturing,2024-03-20,2024-05-09,2027,8.7,Neural Networks Co -AI02895,ML Ops Engineer,156992,CAD,196240,SE,FT,Canada,L,Denmark,0,"Data Visualization, Java, R",Associate,6,Technology,2025-01-28,2025-03-05,2468,9.3,Smart Analytics -AI02896,AI Architect,86246,USD,86246,EN,PT,Sweden,L,Denmark,0,"Java, Linux, Computer Vision, Python",PhD,0,Energy,2024-08-30,2024-09-15,1034,5,DeepTech Ventures -AI02897,Research Scientist,71217,EUR,60534,EN,CT,Austria,M,Israel,0,"GCP, Docker, Statistics, Kubernetes",PhD,1,Media,2024-12-13,2025-01-08,2027,7.4,Neural Networks Co -AI02898,AI Consultant,206746,EUR,175734,EX,CT,Netherlands,L,Netherlands,100,"AWS, Spark, Python",Associate,14,Government,2024-05-22,2024-06-24,1248,8.7,Algorithmic Solutions -AI02899,AI Consultant,169673,EUR,144222,EX,FL,Netherlands,S,Hungary,100,"Git, Scala, AWS",PhD,17,Technology,2024-02-11,2024-04-01,749,8.9,Algorithmic Solutions -AI02900,AI Product Manager,144440,GBP,108330,EX,FL,United Kingdom,S,United Kingdom,0,"NLP, Hadoop, Python",Associate,16,Gaming,2024-10-20,2024-11-19,1944,5.2,Cognitive Computing -AI02901,Machine Learning Engineer,153212,EUR,130230,EX,FT,France,L,France,100,"Deep Learning, Tableau, Python, TensorFlow, Data Visualization",PhD,16,Real Estate,2024-11-14,2025-01-01,1882,5.3,Future Systems -AI02902,Head of AI,204044,EUR,173437,EX,FL,France,S,France,0,"Python, Spark, Deep Learning",PhD,10,Education,2024-11-25,2025-01-31,788,9.1,Smart Analytics -AI02903,Autonomous Systems Engineer,151754,EUR,128991,SE,FT,Germany,L,Germany,100,"Scala, R, Tableau, SQL, GCP",Bachelor,7,Media,2025-04-30,2025-07-05,966,7.8,Quantum Computing Inc -AI02904,Computer Vision Engineer,31800,USD,31800,MI,FT,India,M,India,0,"Scala, Java, Statistics, Tableau",Associate,3,Gaming,2024-01-12,2024-02-28,977,8.8,Neural Networks Co -AI02905,Machine Learning Researcher,58310,JPY,6414100,EN,FL,Japan,M,Japan,0,"R, Docker, NLP, AWS, Hadoop",Bachelor,0,Retail,2024-09-22,2024-11-09,2121,9.9,TechCorp Inc -AI02906,Research Scientist,56624,USD,56624,EN,FL,South Korea,L,United Kingdom,100,"Hadoop, MLOps, Statistics, PyTorch",Bachelor,1,Government,2024-12-03,2024-12-27,2253,8.6,Cloud AI Solutions -AI02907,Machine Learning Researcher,150671,JPY,16573810,SE,FT,Japan,L,Denmark,50,"Mathematics, Scala, Git, Data Visualization, SQL",Bachelor,6,Gaming,2024-05-03,2024-07-07,2248,6.4,Quantum Computing Inc -AI02908,Deep Learning Engineer,202936,GBP,152202,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, SQL, Tableau, Computer Vision",Associate,15,Transportation,2025-03-01,2025-03-30,1479,8,AI Innovations -AI02909,Machine Learning Engineer,162469,AUD,219333,SE,FL,Australia,L,Australia,50,"Azure, Hadoop, Kubernetes, Python, TensorFlow",Master,9,Finance,2025-04-01,2025-05-26,2079,5.2,Future Systems -AI02910,Robotics Engineer,212416,USD,212416,EX,CT,Norway,L,Norway,50,"Linux, Azure, SQL, Statistics",PhD,15,Gaming,2024-05-19,2024-06-05,1563,6.3,Future Systems -AI02911,Robotics Engineer,109255,CHF,98330,MI,PT,Switzerland,S,Switzerland,50,"Deep Learning, Git, Statistics, PyTorch, Computer Vision",Master,3,Gaming,2024-11-15,2025-01-03,2497,5.6,Neural Networks Co -AI02912,Head of AI,88844,CAD,111055,MI,FT,Canada,S,Canada,0,"Azure, Spark, Tableau, GCP, AWS",PhD,3,Media,2024-01-26,2024-02-26,2105,6.8,DataVision Ltd -AI02913,Data Engineer,113440,USD,113440,SE,PT,South Korea,M,Luxembourg,50,"AWS, Tableau, Kubernetes, Docker",Bachelor,9,Automotive,2024-08-20,2024-09-14,2313,9.9,Autonomous Tech -AI02914,Data Engineer,98544,USD,98544,MI,PT,Sweden,L,Sweden,0,"Statistics, Azure, Git, AWS",Associate,2,Manufacturing,2024-09-21,2024-11-19,1775,6.1,AI Innovations -AI02915,Principal Data Scientist,216605,USD,216605,EX,FL,Israel,M,Israel,0,"Deep Learning, Python, Data Visualization, Hadoop, TensorFlow",Bachelor,17,Government,2024-01-05,2024-03-14,920,5.1,Digital Transformation LLC -AI02916,Data Analyst,43555,USD,43555,MI,FL,China,M,South Korea,50,"TensorFlow, GCP, Azure, Scala",Bachelor,4,Energy,2024-05-08,2024-07-02,1426,6.8,TechCorp Inc -AI02917,AI Product Manager,216702,USD,216702,EX,FL,Ireland,S,Ireland,50,"Git, Kubernetes, NLP, Hadoop",PhD,11,Education,2025-04-06,2025-06-17,1477,7.8,Smart Analytics -AI02918,NLP Engineer,172329,USD,172329,SE,CT,Norway,L,Norway,100,"Hadoop, Kubernetes, Scala, Java, PyTorch",PhD,7,Technology,2024-06-05,2024-07-23,2023,6.9,Autonomous Tech -AI02919,Data Scientist,162643,USD,162643,EX,CT,Ireland,M,Ireland,100,"R, GCP, SQL, Docker",Bachelor,17,Finance,2024-06-22,2024-07-13,809,5.2,Autonomous Tech -AI02920,Computer Vision Engineer,239531,CHF,215578,EX,FT,Switzerland,M,South Africa,0,"SQL, TensorFlow, Git",Associate,10,Media,2024-06-11,2024-08-16,2292,5.8,Autonomous Tech -AI02921,Deep Learning Engineer,169678,USD,169678,SE,PT,Norway,M,Norway,100,"TensorFlow, Python, Azure, Scala, NLP",Bachelor,8,Manufacturing,2024-06-15,2024-07-24,1276,6.1,Neural Networks Co -AI02922,Autonomous Systems Engineer,119875,USD,119875,MI,CT,Denmark,M,Denmark,50,"Computer Vision, SQL, PyTorch, R",Associate,4,Healthcare,2024-11-20,2025-01-05,2145,9.7,Cloud AI Solutions -AI02923,Machine Learning Researcher,136892,JPY,15058120,SE,FT,Japan,L,Japan,100,"TensorFlow, MLOps, R, AWS",Associate,8,Finance,2025-04-03,2025-05-03,953,5.8,Machine Intelligence Group -AI02924,Principal Data Scientist,213789,GBP,160342,EX,PT,United Kingdom,M,United Kingdom,100,"Data Visualization, Python, Tableau, Spark, Hadoop",Bachelor,15,Manufacturing,2024-10-26,2024-12-13,1726,6.5,Smart Analytics -AI02925,AI Product Manager,145769,GBP,109327,SE,PT,United Kingdom,S,United Kingdom,0,"Scala, Kubernetes, Statistics",Associate,7,Government,2025-01-07,2025-02-03,588,6.1,Algorithmic Solutions -AI02926,Principal Data Scientist,178902,USD,178902,EX,PT,Finland,S,Finland,0,"PyTorch, Python, Data Visualization",Associate,18,Media,2024-02-19,2024-04-24,1082,8.3,Cloud AI Solutions -AI02927,Machine Learning Researcher,57877,USD,57877,SE,PT,China,S,China,50,"MLOps, Linux, Docker, Deep Learning, Computer Vision",PhD,8,Gaming,2024-06-27,2024-07-28,2380,8.4,Algorithmic Solutions -AI02928,Autonomous Systems Engineer,74494,CAD,93118,MI,FT,Canada,S,Canada,100,"MLOps, AWS, Python",Bachelor,2,Retail,2024-11-05,2024-12-15,554,5.4,Algorithmic Solutions -AI02929,Data Analyst,23410,USD,23410,EN,CT,China,S,China,0,"Java, Kubernetes, NLP",PhD,0,Finance,2024-07-23,2024-09-07,1946,6.1,Advanced Robotics -AI02930,AI Specialist,144968,JPY,15946480,SE,PT,Japan,S,Japan,50,"Java, Computer Vision, Python, Data Visualization",Master,6,Consulting,2024-10-12,2024-12-24,1986,7.8,Neural Networks Co -AI02931,ML Ops Engineer,283252,CHF,254927,EX,FT,Switzerland,S,Switzerland,100,"TensorFlow, Azure, Deep Learning, Python, Linux",Master,18,Energy,2024-02-29,2024-04-18,2390,5.5,DeepTech Ventures -AI02932,Computer Vision Engineer,70074,GBP,52556,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, Statistics",Associate,0,Automotive,2025-03-03,2025-05-07,2141,9.7,DeepTech Ventures -AI02933,Autonomous Systems Engineer,111820,SGD,145366,SE,FL,Singapore,M,Mexico,100,"Kubernetes, Scala, PyTorch",Associate,5,Manufacturing,2024-11-01,2025-01-08,533,8.3,DeepTech Ventures -AI02934,ML Ops Engineer,190557,USD,190557,EX,CT,Israel,S,Israel,100,"Scala, Statistics, PyTorch, Docker",Master,12,Retail,2024-12-26,2025-01-13,798,6.9,Machine Intelligence Group -AI02935,Data Scientist,111831,USD,111831,SE,FL,Ireland,S,Ireland,50,"GCP, Tableau, Python",Associate,7,Manufacturing,2024-05-04,2024-06-24,533,8.3,Digital Transformation LLC -AI02936,Machine Learning Engineer,19152,USD,19152,EN,FT,India,M,India,100,"Java, Scala, Tableau, Data Visualization",Master,1,Gaming,2024-03-10,2024-05-01,1579,9.7,Smart Analytics -AI02937,Machine Learning Researcher,193150,USD,193150,EX,FL,Ireland,S,Ireland,100,"Python, TensorFlow, Tableau",PhD,12,Finance,2024-01-07,2024-02-22,911,7.8,Autonomous Tech -AI02938,Machine Learning Researcher,56802,USD,56802,EN,CT,South Korea,M,France,0,"Python, Scala, Statistics, Spark, Docker",Bachelor,1,Gaming,2024-11-17,2025-01-20,1044,8,TechCorp Inc -AI02939,Data Engineer,128940,EUR,109599,SE,CT,Germany,L,Germany,50,"SQL, PyTorch, Mathematics, Azure",Associate,5,Retail,2024-01-22,2024-03-12,2032,6.5,DataVision Ltd -AI02940,NLP Engineer,142396,USD,142396,SE,FL,Ireland,L,Philippines,100,"Tableau, Python, R, Docker",Master,6,Automotive,2024-05-14,2024-07-01,1925,8.3,Cloud AI Solutions -AI02941,Robotics Engineer,47879,USD,47879,SE,PT,China,S,China,100,"TensorFlow, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-09-18,1035,9.3,TechCorp Inc -AI02942,Data Analyst,129487,SGD,168333,SE,FL,Singapore,M,Singapore,0,"Linux, PyTorch, Data Visualization, Kubernetes",Associate,7,Telecommunications,2024-07-20,2024-09-01,803,6,Advanced Robotics -AI02943,Head of AI,272031,EUR,231226,EX,FL,France,L,France,0,"PyTorch, TensorFlow, Data Visualization",PhD,12,Healthcare,2024-05-15,2024-07-08,666,9.6,DataVision Ltd -AI02944,Data Analyst,125924,GBP,94443,SE,PT,United Kingdom,L,Australia,0,"Linux, Statistics, Git",Bachelor,6,Technology,2025-02-07,2025-03-09,780,6.9,Advanced Robotics -AI02945,Principal Data Scientist,24104,USD,24104,EN,FT,India,S,India,50,"Python, TensorFlow, Tableau, PyTorch",Associate,0,Media,2025-04-01,2025-05-31,860,5.2,Smart Analytics -AI02946,Principal Data Scientist,69920,EUR,59432,EN,FT,Germany,M,Germany,0,"SQL, Scala, Git, GCP",Bachelor,1,Telecommunications,2024-09-13,2024-10-25,2048,5.8,Neural Networks Co -AI02947,Data Scientist,99241,EUR,84355,SE,FT,Austria,S,Austria,50,"Kubernetes, Git, Mathematics",Bachelor,5,Manufacturing,2024-06-13,2024-08-06,803,9.8,Predictive Systems -AI02948,Principal Data Scientist,80687,CHF,72618,EN,CT,Switzerland,S,Switzerland,50,"AWS, NLP, Python, Mathematics, Scala",PhD,1,Automotive,2024-06-26,2024-07-26,1786,7.7,Algorithmic Solutions -AI02949,Deep Learning Engineer,45985,USD,45985,MI,FT,China,L,China,50,"Deep Learning, Python, Docker",PhD,2,Transportation,2024-04-28,2024-07-05,1598,8.6,TechCorp Inc -AI02950,NLP Engineer,71121,USD,71121,MI,PT,South Korea,M,Mexico,50,"Tableau, Deep Learning, TensorFlow, Python, Java",Associate,4,Technology,2024-08-20,2024-09-06,905,8.6,Algorithmic Solutions -AI02951,Principal Data Scientist,214331,USD,214331,EX,FL,Finland,L,Finland,50,"GCP, Python, TensorFlow, Docker, Statistics",Bachelor,10,Transportation,2024-03-02,2024-03-23,1877,8.9,Algorithmic Solutions -AI02952,NLP Engineer,179501,EUR,152576,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, Git, AWS, R, Java",Bachelor,9,Consulting,2024-04-13,2024-05-12,1341,8.5,DeepTech Ventures -AI02953,AI Specialist,213182,USD,213182,EX,FL,Denmark,L,United Kingdom,0,"Hadoop, R, GCP, Deep Learning",Bachelor,15,Real Estate,2024-10-26,2024-12-30,2424,9.3,Smart Analytics -AI02954,Data Analyst,257116,USD,257116,EX,CT,United States,M,Ghana,50,"NLP, R, SQL",PhD,16,Healthcare,2024-09-18,2024-10-19,2162,6.3,Autonomous Tech -AI02955,Principal Data Scientist,210838,EUR,179212,EX,FT,France,S,France,50,"SQL, Azure, Git",Associate,13,Government,2024-07-18,2024-09-26,723,8.1,DeepTech Ventures -AI02956,ML Ops Engineer,161032,USD,161032,SE,PT,Norway,S,Norway,0,"SQL, R, Java, AWS",Associate,5,Telecommunications,2024-01-14,2024-02-08,1827,7.6,Autonomous Tech -AI02957,Data Engineer,97860,EUR,83181,MI,FL,Austria,L,Chile,50,"PyTorch, Computer Vision, R",Bachelor,4,Healthcare,2024-09-19,2024-10-07,2445,6.1,Algorithmic Solutions -AI02958,Machine Learning Researcher,76742,GBP,57557,EN,FT,United Kingdom,S,United Kingdom,0,"GCP, Python, TensorFlow, NLP, Computer Vision",PhD,1,Energy,2024-10-26,2024-12-03,2112,5.1,Autonomous Tech -AI02959,AI Architect,124869,USD,124869,EX,CT,Sweden,S,Czech Republic,0,"Mathematics, Hadoop, GCP, Azure",Bachelor,19,Telecommunications,2024-04-11,2024-05-18,718,7.8,Smart Analytics -AI02960,Data Analyst,158246,USD,158246,SE,FT,Norway,L,South Korea,50,"Tableau, Spark, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-08-28,2024-09-28,939,9.5,TechCorp Inc -AI02961,Data Engineer,277909,USD,277909,EX,CT,Sweden,L,Sweden,0,"Python, Hadoop, Scala, TensorFlow",Master,16,Technology,2025-04-06,2025-06-06,1601,6.7,Neural Networks Co -AI02962,Principal Data Scientist,58343,EUR,49592,EN,FT,Germany,S,Germany,50,"SQL, Spark, Data Visualization",Bachelor,0,Education,2024-10-23,2024-12-01,535,6.5,Neural Networks Co -AI02963,AI Product Manager,98072,USD,98072,MI,PT,Sweden,L,Sweden,0,"TensorFlow, R, Statistics",Associate,4,Energy,2024-03-26,2024-05-19,710,7.8,Predictive Systems -AI02964,ML Ops Engineer,58209,USD,58209,SE,CT,India,L,India,50,"Kubernetes, Python, Spark",Bachelor,6,Government,2024-03-10,2024-05-15,621,7.8,Advanced Robotics -AI02965,Principal Data Scientist,101880,EUR,86598,SE,PT,Germany,S,Czech Republic,50,"Spark, Azure, Docker",PhD,7,Retail,2025-02-04,2025-04-03,1759,8.1,Cloud AI Solutions -AI02966,AI Architect,119812,USD,119812,MI,FL,United States,M,Italy,0,"Deep Learning, Git, Data Visualization, Statistics",Bachelor,4,Manufacturing,2024-02-02,2024-02-17,1503,7.7,TechCorp Inc -AI02967,Research Scientist,184524,USD,184524,EX,FL,Finland,S,Finland,100,"SQL, PyTorch, Deep Learning",Bachelor,12,Manufacturing,2024-10-15,2024-10-30,619,9.1,Smart Analytics -AI02968,AI Architect,212494,EUR,180620,EX,CT,Austria,M,Austria,50,"Spark, Mathematics, Java",Bachelor,19,Automotive,2024-01-03,2024-02-15,1929,6,Digital Transformation LLC -AI02969,NLP Engineer,83942,EUR,71351,MI,CT,Netherlands,S,Israel,0,"Linux, SQL, AWS",Bachelor,3,Finance,2025-04-05,2025-05-10,678,9.8,Machine Intelligence Group -AI02970,ML Ops Engineer,92507,GBP,69380,MI,PT,United Kingdom,L,Canada,100,"Git, Data Visualization, AWS, SQL",Master,3,Government,2025-04-01,2025-06-06,2111,7.5,Future Systems -AI02971,Machine Learning Researcher,71494,EUR,60770,MI,PT,France,M,South Africa,50,"R, Kubernetes, AWS, Python, Computer Vision",PhD,4,Education,2025-04-19,2025-05-31,738,8.3,Smart Analytics -AI02972,AI Product Manager,89952,AUD,121435,MI,FT,Australia,S,Australia,50,"Linux, Spark, Deep Learning",Master,2,Government,2024-07-18,2024-08-06,2280,8.2,Digital Transformation LLC -AI02973,AI Product Manager,74909,USD,74909,EX,CT,India,L,Argentina,100,"Statistics, Kubernetes, Git, GCP, Python",Master,17,Media,2024-02-28,2024-03-14,618,9.2,Algorithmic Solutions -AI02974,Data Scientist,121133,AUD,163530,SE,PT,Australia,M,Australia,100,"Python, Kubernetes, MLOps, Azure",Master,6,Manufacturing,2025-01-01,2025-03-13,1194,8.2,Autonomous Tech -AI02975,Head of AI,106190,SGD,138047,MI,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, Tableau",Bachelor,3,Finance,2024-03-05,2024-05-17,1987,7.2,AI Innovations -AI02976,AI Software Engineer,261845,EUR,222568,EX,FL,Netherlands,M,Netherlands,50,"Python, GCP, Hadoop",PhD,19,Automotive,2024-06-14,2024-08-05,1868,5.7,Quantum Computing Inc -AI02977,Robotics Engineer,104354,EUR,88701,MI,CT,Austria,L,Switzerland,100,"Java, Linux, TensorFlow, Hadoop",Associate,4,Transportation,2025-04-06,2025-04-23,611,9,TechCorp Inc -AI02978,AI Architect,86549,USD,86549,EN,FT,Sweden,L,Sweden,100,"Azure, PyTorch, Data Visualization, Kubernetes",Associate,1,Education,2025-01-27,2025-03-07,1075,6.2,DataVision Ltd -AI02979,ML Ops Engineer,170055,USD,170055,SE,FT,Sweden,L,Netherlands,100,"AWS, Linux, Scala, MLOps, Mathematics",Associate,6,Energy,2024-02-12,2024-03-31,2029,5.2,Machine Intelligence Group -AI02980,Computer Vision Engineer,92633,USD,92633,SE,FT,Israel,S,Israel,0,"Spark, Docker, Data Visualization, PyTorch",PhD,9,Real Estate,2024-05-08,2024-06-16,1790,7,DataVision Ltd -AI02981,Deep Learning Engineer,108025,EUR,91821,SE,FL,France,S,Vietnam,100,"Docker, Java, Linux, Statistics, Computer Vision",Bachelor,5,Manufacturing,2024-08-27,2024-10-11,856,8,Algorithmic Solutions -AI02982,NLP Engineer,231357,EUR,196653,EX,FT,France,L,France,100,"TensorFlow, Data Visualization, SQL, Scala",Master,10,Real Estate,2025-02-05,2025-03-18,771,7.4,Autonomous Tech -AI02983,AI Consultant,75714,AUD,102214,MI,PT,Australia,M,Australia,0,"Git, SQL, Computer Vision, Hadoop, Java",Associate,3,Real Estate,2025-04-25,2025-05-18,895,7.1,Neural Networks Co -AI02984,Machine Learning Researcher,48731,EUR,41421,EN,CT,Austria,S,Austria,100,"R, Hadoop, Docker, Computer Vision, Python",PhD,0,Real Estate,2024-10-05,2024-12-15,1480,9.2,Future Systems -AI02985,AI Architect,63620,EUR,54077,EN,FL,Austria,L,Austria,100,"Linux, Spark, NLP, Kubernetes",Master,1,Energy,2024-05-01,2024-06-14,1567,7.5,DataVision Ltd -AI02986,Deep Learning Engineer,146711,USD,146711,SE,FL,United States,S,United States,50,"R, NLP, Kubernetes",Bachelor,8,Retail,2024-04-09,2024-06-02,1302,6.2,Cloud AI Solutions -AI02987,Autonomous Systems Engineer,217093,USD,217093,EX,PT,Finland,M,Finland,0,"Scala, PyTorch, GCP",Associate,15,Government,2024-01-01,2024-03-13,1010,9.5,Predictive Systems -AI02988,Computer Vision Engineer,158838,EUR,135012,SE,FL,Netherlands,L,South Africa,100,"Hadoop, Python, R",Master,7,Media,2024-11-21,2025-01-20,814,6.7,Cloud AI Solutions -AI02989,Machine Learning Engineer,26471,USD,26471,MI,CT,India,S,India,50,"Tableau, Git, Python, Computer Vision",Master,3,Healthcare,2025-04-15,2025-05-24,2355,8.1,Machine Intelligence Group -AI02990,Principal Data Scientist,52315,EUR,44468,EN,FT,Germany,M,Germany,100,"AWS, Python, Tableau",Master,0,Technology,2024-01-02,2024-02-21,1188,9.6,Quantum Computing Inc -AI02991,Research Scientist,155395,USD,155395,SE,PT,Finland,L,Finland,100,"Git, NLP, Scala",Bachelor,7,Consulting,2024-07-05,2024-08-06,1078,6.3,Smart Analytics -AI02992,Deep Learning Engineer,103774,USD,103774,SE,CT,Sweden,M,Sweden,100,"Python, Java, TensorFlow",PhD,5,Manufacturing,2024-02-14,2024-03-18,738,8.7,Machine Intelligence Group -AI02993,AI Specialist,116286,USD,116286,SE,CT,Finland,M,Czech Republic,0,"AWS, Java, Statistics, Mathematics",Associate,7,Media,2025-04-27,2025-06-01,1491,6.7,Cognitive Computing -AI02994,ML Ops Engineer,75877,USD,75877,EN,CT,United States,S,United States,50,"NLP, Python, SQL, Git",Master,0,Healthcare,2025-01-11,2025-02-22,751,9.7,Future Systems -AI02995,Data Analyst,73643,AUD,99418,MI,FT,Australia,S,Indonesia,0,"Azure, Spark, MLOps",Bachelor,2,Consulting,2024-07-04,2024-07-27,1225,9.9,Advanced Robotics -AI02996,AI Specialist,252203,CHF,226983,EX,FL,Switzerland,L,Switzerland,50,"Hadoop, PyTorch, Java, Computer Vision, Mathematics",Bachelor,13,Automotive,2025-04-18,2025-06-12,1635,7.6,Predictive Systems -AI02997,AI Specialist,82912,USD,82912,MI,FT,Israel,M,Indonesia,0,"R, Tableau, Linux",Bachelor,4,Energy,2024-08-03,2024-08-25,2064,7.6,Advanced Robotics -AI02998,AI Specialist,152624,USD,152624,SE,FL,Ireland,L,Ireland,100,"R, Python, Git, GCP, Linux",Master,9,Retail,2024-11-28,2025-01-15,1068,5.4,Future Systems -AI02999,AI Architect,87630,USD,87630,MI,FT,South Korea,L,South Korea,100,"AWS, Linux, Deep Learning, R",Associate,2,Manufacturing,2024-05-01,2024-06-16,945,8.8,Cognitive Computing -AI03000,AI Research Scientist,234953,SGD,305439,EX,FL,Singapore,S,Singapore,50,"Linux, R, TensorFlow, Git, Tableau",PhD,12,Consulting,2024-04-14,2024-05-18,930,9,AI Innovations -AI03001,AI Research Scientist,121264,SGD,157643,SE,FL,Singapore,S,Singapore,0,"Spark, Kubernetes, GCP, TensorFlow",Master,7,Government,2024-01-14,2024-03-21,1534,9.8,Digital Transformation LLC -AI03002,Machine Learning Researcher,158964,USD,158964,MI,PT,Denmark,L,Denmark,0,"Scala, SQL, Java, Docker, PyTorch",Master,4,Education,2024-06-25,2024-07-10,638,7.6,Cloud AI Solutions -AI03003,Computer Vision Engineer,73586,JPY,8094460,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, Docker, Data Visualization",Bachelor,1,Retail,2024-11-26,2025-01-15,1557,7,DeepTech Ventures -AI03004,Machine Learning Engineer,230512,GBP,172884,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Kubernetes, Python",Master,13,Telecommunications,2024-05-26,2024-06-24,827,7,Advanced Robotics -AI03005,Autonomous Systems Engineer,125009,CAD,156261,SE,CT,Canada,S,Czech Republic,50,"Kubernetes, Computer Vision, SQL",PhD,7,Telecommunications,2025-01-28,2025-03-31,1710,5.3,Advanced Robotics -AI03006,AI Architect,262701,USD,262701,EX,PT,Sweden,L,Belgium,50,"Python, AWS, TensorFlow",Bachelor,19,Gaming,2024-12-02,2025-01-07,1868,9.6,Autonomous Tech -AI03007,ML Ops Engineer,266606,USD,266606,EX,CT,Denmark,S,Denmark,50,"Hadoop, Python, Tableau, Deep Learning",PhD,18,Automotive,2025-02-02,2025-03-30,1674,8.3,Smart Analytics -AI03008,NLP Engineer,140178,SGD,182231,SE,FT,Singapore,S,Singapore,100,"Tableau, Deep Learning, Hadoop, MLOps",Bachelor,5,Retail,2025-04-15,2025-06-20,2368,5.3,Future Systems -AI03009,NLP Engineer,187857,CAD,234821,EX,FL,Canada,L,Canada,0,"Deep Learning, Spark, Data Visualization, SQL, Kubernetes",Bachelor,18,Consulting,2024-07-21,2024-09-28,1818,5.9,Cognitive Computing -AI03010,Data Analyst,42710,USD,42710,MI,FT,China,M,Spain,100,"Java, R, Hadoop, Linux",PhD,2,Finance,2024-11-30,2025-01-16,691,9.8,Digital Transformation LLC -AI03011,Data Scientist,84841,EUR,72115,MI,PT,Netherlands,M,Netherlands,50,"Java, R, Tableau, SQL, Scala",Bachelor,4,Transportation,2024-03-02,2024-04-23,2405,7.6,Advanced Robotics -AI03012,AI Consultant,74980,EUR,63733,MI,CT,Austria,S,Austria,0,"SQL, PyTorch, R, Hadoop, Python",Bachelor,3,Telecommunications,2024-06-25,2024-08-19,1005,8.3,TechCorp Inc -AI03013,AI Consultant,84006,EUR,71405,MI,CT,France,M,Brazil,0,"Deep Learning, SQL, Mathematics",Master,3,Real Estate,2024-06-20,2024-08-04,1656,6.9,Digital Transformation LLC -AI03014,AI Consultant,174420,EUR,148257,EX,CT,France,S,Romania,100,"Kubernetes, Scala, Java, Spark",PhD,19,Education,2024-01-16,2024-03-23,1377,9.3,Future Systems -AI03015,Computer Vision Engineer,243382,USD,243382,EX,PT,Sweden,M,Sweden,50,"Linux, Kubernetes, Git, Docker, Python",Associate,19,Gaming,2024-04-22,2024-06-10,1260,8.7,Advanced Robotics -AI03016,AI Consultant,72001,EUR,61201,MI,PT,Austria,S,Austria,0,"Java, Hadoop, Scala, GCP",PhD,4,Government,2024-04-01,2024-05-16,698,9.4,Cloud AI Solutions -AI03017,AI Architect,349094,USD,349094,EX,PT,Denmark,L,Denmark,100,"PyTorch, Scala, NLP, Computer Vision",Bachelor,13,Healthcare,2024-03-04,2024-05-09,2490,8.9,Cloud AI Solutions -AI03018,Machine Learning Engineer,135760,USD,135760,SE,FT,Norway,S,Norway,50,"Azure, Linux, Docker, SQL",Bachelor,5,Consulting,2024-08-28,2024-09-30,1383,7.4,Quantum Computing Inc -AI03019,AI Research Scientist,127359,EUR,108255,SE,CT,France,L,France,50,"Computer Vision, Java, SQL",Master,9,Telecommunications,2024-06-19,2024-08-08,1050,5.7,Smart Analytics -AI03020,Data Engineer,97760,SGD,127088,SE,PT,Singapore,S,Ireland,0,"TensorFlow, GCP, Tableau, Computer Vision",PhD,6,Technology,2024-03-09,2024-04-17,2013,6.9,Machine Intelligence Group -AI03021,AI Software Engineer,217718,JPY,23948980,EX,FT,Japan,M,Japan,100,"MLOps, R, Computer Vision, Scala",Associate,13,Telecommunications,2024-08-08,2024-10-13,1785,9.8,Smart Analytics -AI03022,Deep Learning Engineer,129149,CAD,161436,SE,CT,Canada,S,Canada,100,"R, Kubernetes, Mathematics",Associate,5,Gaming,2025-04-18,2025-06-30,650,6.7,AI Innovations -AI03023,Data Analyst,66925,USD,66925,EN,PT,Ireland,S,Ireland,50,"SQL, Java, PyTorch, Git, Spark",Master,1,Technology,2024-05-26,2024-06-10,783,5.4,Digital Transformation LLC -AI03024,Data Engineer,87198,EUR,74118,MI,PT,Germany,S,Germany,50,"Git, R, Kubernetes, Spark",Bachelor,2,Gaming,2024-12-18,2025-01-25,1440,9.8,Autonomous Tech -AI03025,AI Software Engineer,94601,USD,94601,EN,PT,United States,L,United States,0,"AWS, Java, Deep Learning, Python, TensorFlow",PhD,0,Telecommunications,2025-01-20,2025-03-30,874,9.3,Neural Networks Co -AI03026,Principal Data Scientist,51043,USD,51043,EN,PT,South Korea,M,South Korea,100,"Data Visualization, AWS, TensorFlow, SQL, NLP",Associate,0,Gaming,2024-07-21,2024-08-30,1749,5.9,Smart Analytics -AI03027,Autonomous Systems Engineer,88860,EUR,75531,MI,CT,France,L,France,50,"Hadoop, Computer Vision, Mathematics, MLOps",Bachelor,3,Retail,2024-09-27,2024-12-08,1581,10,Machine Intelligence Group -AI03028,AI Specialist,91219,USD,91219,MI,FT,Sweden,S,Sweden,50,"GCP, Java, SQL, Deep Learning",PhD,4,Transportation,2025-04-16,2025-06-01,1553,5.8,Autonomous Tech -AI03029,AI Product Manager,23010,USD,23010,MI,FL,India,S,India,100,"Python, Computer Vision, Java",Master,4,Gaming,2024-08-24,2024-11-02,1484,7.7,Predictive Systems -AI03030,Autonomous Systems Engineer,84775,USD,84775,MI,PT,Finland,L,Finland,100,"PyTorch, SQL, Computer Vision",PhD,4,Consulting,2024-11-23,2024-12-08,1320,5.7,Neural Networks Co -AI03031,Machine Learning Researcher,182231,USD,182231,EX,FT,Norway,M,Norway,100,"Tableau, Computer Vision, NLP, Python, MLOps",PhD,11,Government,2024-02-16,2024-03-29,2292,8.2,Autonomous Tech -AI03032,Data Engineer,76682,USD,76682,EX,FT,India,M,India,0,"PyTorch, AWS, Data Visualization, Deep Learning",PhD,12,Finance,2025-04-25,2025-06-15,552,8.7,Neural Networks Co -AI03033,NLP Engineer,103728,EUR,88169,SE,CT,Austria,S,Austria,100,"R, Spark, TensorFlow",Master,8,Gaming,2024-05-01,2024-06-01,700,9.8,Digital Transformation LLC -AI03034,Machine Learning Engineer,108739,CHF,97865,EN,FT,Switzerland,L,Switzerland,0,"Scala, Linux, Computer Vision, Java",Associate,0,Telecommunications,2024-04-23,2024-06-11,829,6.3,Neural Networks Co -AI03035,AI Architect,127790,USD,127790,SE,PT,Israel,L,Israel,50,"GCP, R, Tableau",Master,8,Finance,2024-06-07,2024-07-18,880,6.2,Cloud AI Solutions -AI03036,Deep Learning Engineer,113774,USD,113774,MI,CT,United States,L,Belgium,50,"Data Visualization, R, Java, Tableau",Associate,3,Automotive,2024-04-28,2024-05-27,529,9.4,Algorithmic Solutions -AI03037,Research Scientist,119989,USD,119989,EN,FL,Denmark,L,Denmark,100,"Data Visualization, Linux, Tableau",Associate,1,Telecommunications,2024-07-15,2024-08-25,1170,6.1,Advanced Robotics -AI03038,Machine Learning Engineer,75024,USD,75024,MI,PT,Israel,S,Netherlands,100,"Tableau, Azure, AWS, SQL",Associate,4,Government,2025-04-13,2025-05-22,1521,9.3,Advanced Robotics -AI03039,Research Scientist,67687,USD,67687,EN,CT,Ireland,M,Indonesia,0,"R, Deep Learning, SQL, Data Visualization, Kubernetes",PhD,1,Media,2024-08-12,2024-10-08,508,5.4,AI Innovations -AI03040,Data Scientist,82087,USD,82087,MI,FL,United States,S,United States,100,"MLOps, Hadoop, Java, Spark, Tableau",PhD,4,Media,2024-10-11,2024-11-07,1535,6.8,AI Innovations -AI03041,Computer Vision Engineer,240800,USD,240800,EX,FL,Sweden,M,Sweden,50,"Kubernetes, Deep Learning, SQL, PyTorch",Bachelor,15,Consulting,2024-08-27,2024-09-11,2073,8,TechCorp Inc -AI03042,Principal Data Scientist,76214,EUR,64782,MI,PT,Germany,S,Germany,0,"Python, R, SQL, Kubernetes, Mathematics",PhD,3,Media,2025-02-26,2025-04-14,1646,6.7,Autonomous Tech -AI03043,AI Consultant,259438,CHF,233494,EX,PT,Switzerland,L,Switzerland,0,"Git, Scala, Hadoop, SQL",Bachelor,13,Energy,2024-01-19,2024-02-03,2304,5.3,Predictive Systems -AI03044,Data Engineer,245492,USD,245492,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Deep Learning, Mathematics, AWS",Master,17,Manufacturing,2024-07-24,2024-09-30,2187,8.1,Autonomous Tech -AI03045,ML Ops Engineer,102823,CAD,128529,MI,FL,Canada,M,Canada,100,"Linux, R, TensorFlow, Deep Learning, Data Visualization",Master,3,Manufacturing,2025-04-04,2025-04-24,1976,9.7,Digital Transformation LLC -AI03046,Deep Learning Engineer,283410,USD,283410,EX,FT,Ireland,L,Ireland,50,"Docker, Statistics, Deep Learning, R, SQL",Bachelor,18,Telecommunications,2024-01-27,2024-03-15,1313,7.1,Machine Intelligence Group -AI03047,Machine Learning Engineer,208241,USD,208241,EX,FT,Ireland,M,Kenya,50,"Kubernetes, Azure, Data Visualization",Bachelor,18,Automotive,2024-08-18,2024-10-22,2371,8.9,TechCorp Inc -AI03048,ML Ops Engineer,105274,GBP,78956,MI,PT,United Kingdom,S,Brazil,100,"Java, Git, R, Linux, SQL",PhD,3,Government,2025-01-08,2025-02-16,936,7.4,Neural Networks Co -AI03049,Principal Data Scientist,94841,USD,94841,MI,FL,Israel,L,Israel,0,"SQL, Java, Linux, NLP, Tableau",Bachelor,3,Media,2024-09-17,2024-11-12,651,6.1,Future Systems -AI03050,Autonomous Systems Engineer,114463,EUR,97294,MI,FT,Austria,L,Austria,50,"Python, Hadoop, SQL, Docker",Master,2,Consulting,2024-07-28,2024-09-23,2088,6.8,AI Innovations -AI03051,Data Engineer,158187,USD,158187,SE,PT,Denmark,S,Denmark,100,"SQL, R, Data Visualization, Docker",Bachelor,5,Telecommunications,2024-03-20,2024-05-21,835,6,Future Systems -AI03052,Principal Data Scientist,45177,USD,45177,EN,PT,South Korea,S,South Korea,50,"R, Linux, Python, Tableau, Mathematics",PhD,1,Education,2024-01-23,2024-02-06,1425,5.5,Smart Analytics -AI03053,Head of AI,147403,EUR,125293,SE,PT,Germany,L,Germany,50,"Kubernetes, Hadoop, NLP, Statistics, Python",Associate,8,Automotive,2024-04-26,2024-05-31,1232,8.4,Predictive Systems -AI03054,Deep Learning Engineer,103578,USD,103578,SE,FL,Ireland,S,Ireland,50,"TensorFlow, Linux, PyTorch, Tableau",PhD,5,Transportation,2024-10-16,2024-12-06,2330,8.9,Quantum Computing Inc -AI03055,Deep Learning Engineer,90139,AUD,121688,MI,FL,Australia,L,Australia,100,"R, Mathematics, Data Visualization, Linux, Kubernetes",Master,4,Telecommunications,2025-01-10,2025-02-08,1856,7.4,DataVision Ltd -AI03056,AI Product Manager,140051,EUR,119043,SE,FT,France,L,France,100,"Scala, Git, Statistics, Computer Vision, Python",Master,5,Automotive,2024-01-13,2024-03-02,1252,7.4,Quantum Computing Inc -AI03057,Head of AI,55899,USD,55899,EN,FT,Israel,M,Israel,50,"Tableau, Azure, Hadoop",Bachelor,0,Education,2024-06-01,2024-07-03,1765,8.2,Future Systems -AI03058,Machine Learning Engineer,228939,EUR,194598,EX,CT,Germany,M,Mexico,50,"NLP, AWS, Git, GCP, Mathematics",PhD,14,Transportation,2024-09-10,2024-10-20,2130,8.5,Neural Networks Co -AI03059,Computer Vision Engineer,169575,CHF,152618,SE,PT,Switzerland,S,Switzerland,50,"Tableau, Git, Computer Vision, Python, Statistics",Associate,8,Energy,2025-04-09,2025-06-16,1773,5.1,Autonomous Tech -AI03060,AI Specialist,92434,GBP,69326,EN,CT,United Kingdom,L,Vietnam,0,"Data Visualization, Spark, Computer Vision, SQL, PyTorch",Bachelor,0,Gaming,2024-10-27,2024-12-11,1856,7.4,TechCorp Inc -AI03061,NLP Engineer,45214,CAD,56518,EN,CT,Canada,S,Canada,100,"GCP, Computer Vision, Python, R, TensorFlow",PhD,1,Finance,2024-01-25,2024-03-23,2385,7.6,DeepTech Ventures -AI03062,Principal Data Scientist,125545,AUD,169486,MI,FT,Australia,L,Thailand,50,"Python, Git, TensorFlow, NLP",Associate,4,Technology,2024-09-14,2024-10-20,868,8.1,Future Systems -AI03063,AI Research Scientist,63222,USD,63222,EX,FT,India,M,India,100,"MLOps, TensorFlow, Tableau, Linux",PhD,15,Government,2024-03-21,2024-05-29,1313,5.4,Neural Networks Co -AI03064,Deep Learning Engineer,90458,USD,90458,MI,PT,Finland,L,Finland,0,"SQL, Python, NLP, Statistics",Master,2,Transportation,2024-10-26,2024-12-04,834,9.1,DataVision Ltd -AI03065,Data Analyst,53532,USD,53532,EN,PT,Sweden,S,Brazil,0,"Kubernetes, Statistics, Tableau, Mathematics, Java",Bachelor,1,Energy,2025-03-04,2025-04-17,1479,8.4,Algorithmic Solutions -AI03066,Computer Vision Engineer,111068,USD,111068,MI,FL,Norway,M,United States,100,"Data Visualization, Python, TensorFlow, Docker",Master,4,Telecommunications,2025-03-23,2025-04-24,618,8.8,Future Systems -AI03067,AI Research Scientist,51281,CAD,64101,EN,FT,Canada,M,Ireland,50,"SQL, Kubernetes, Scala, Mathematics",Master,0,Government,2025-01-25,2025-02-20,1572,6.7,Neural Networks Co -AI03068,Robotics Engineer,70333,USD,70333,EX,CT,India,S,India,100,"Tableau, Data Visualization, SQL, PyTorch",Bachelor,12,Finance,2024-05-13,2024-06-24,1694,7.8,Neural Networks Co -AI03069,Data Scientist,113289,USD,113289,MI,PT,Norway,M,Italy,50,"Python, Java, Hadoop, AWS, Kubernetes",Bachelor,4,Gaming,2024-09-17,2024-11-26,1355,7.9,Algorithmic Solutions -AI03070,Deep Learning Engineer,76340,USD,76340,EN,FT,Israel,L,Israel,100,"AWS, SQL, Python",Master,0,Retail,2024-07-29,2024-09-19,1293,8,Predictive Systems -AI03071,Deep Learning Engineer,83602,USD,83602,MI,CT,Finland,M,Finland,100,"Data Visualization, R, NLP, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-15,884,5.7,Quantum Computing Inc -AI03072,Machine Learning Researcher,140958,AUD,190293,EX,CT,Australia,M,Thailand,0,"Docker, Hadoop, Mathematics, Kubernetes",Master,15,Consulting,2024-05-31,2024-07-29,1825,7.2,DeepTech Ventures -AI03073,Machine Learning Engineer,224243,USD,224243,EX,FL,United States,L,United States,50,"Java, R, SQL, Data Visualization, Linux",PhD,17,Media,2024-06-25,2024-08-19,1126,7.2,Predictive Systems -AI03074,AI Product Manager,182443,USD,182443,EX,PT,Sweden,L,Sweden,50,"Computer Vision, Python, Tableau, Data Visualization",Bachelor,15,Technology,2024-10-26,2024-12-02,2303,6.3,Autonomous Tech -AI03075,Principal Data Scientist,116360,AUD,157086,SE,CT,Australia,S,Australia,0,"Mathematics, Kubernetes, Data Visualization, GCP, PyTorch",Master,9,Technology,2024-02-03,2024-03-03,1533,6.7,DeepTech Ventures -AI03076,Machine Learning Engineer,59186,SGD,76942,EN,CT,Singapore,S,Singapore,0,"Java, R, Computer Vision, Tableau, Statistics",Master,1,Government,2025-04-16,2025-06-27,1282,6.6,Digital Transformation LLC -AI03077,AI Product Manager,230221,CAD,287776,EX,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Python",Master,11,Manufacturing,2024-02-06,2024-04-07,883,7.7,Cognitive Computing -AI03078,AI Specialist,249223,EUR,211840,EX,FL,Germany,L,Chile,50,"Scala, TensorFlow, SQL, Kubernetes",Master,14,Retail,2025-04-13,2025-05-23,1427,6.4,Cognitive Computing -AI03079,Principal Data Scientist,170776,USD,170776,SE,CT,United States,M,United States,0,"Java, Data Visualization, R, Scala",Master,5,Gaming,2025-01-16,2025-02-03,1122,8.8,DeepTech Ventures -AI03080,Computer Vision Engineer,76117,EUR,64699,EN,FL,Germany,M,Estonia,0,"R, Git, Hadoop",Master,1,Consulting,2024-01-03,2024-02-07,1271,9.4,Algorithmic Solutions -AI03081,AI Research Scientist,65226,AUD,88055,EN,FT,Australia,L,Australia,0,"Kubernetes, PyTorch, Azure, SQL",PhD,0,Finance,2024-10-26,2024-11-28,684,5.5,Machine Intelligence Group -AI03082,Computer Vision Engineer,63087,EUR,53624,EN,PT,Austria,M,Austria,0,"Git, Azure, Statistics, GCP",Associate,1,Telecommunications,2024-12-19,2025-01-26,2458,8.8,Cloud AI Solutions -AI03083,Machine Learning Engineer,44772,USD,44772,MI,FL,China,M,China,50,"R, Java, Data Visualization",Master,4,Transportation,2024-01-01,2024-01-24,1106,9.3,Algorithmic Solutions -AI03084,Data Scientist,204283,AUD,275782,EX,FT,Australia,S,Brazil,100,"Python, Scala, Kubernetes, Docker",Associate,12,Retail,2024-04-21,2024-06-19,1045,8.5,Advanced Robotics -AI03085,Machine Learning Engineer,114299,USD,114299,SE,PT,Ireland,M,Portugal,100,"GCP, Java, MLOps",Bachelor,8,Transportation,2024-10-26,2024-11-22,1175,6.8,Future Systems -AI03086,AI Consultant,298889,USD,298889,EX,FT,Norway,L,Norway,50,"GCP, Statistics, Git, Hadoop",Associate,16,Consulting,2024-02-29,2024-04-06,1175,6.8,Cloud AI Solutions -AI03087,AI Specialist,71400,JPY,7854000,EN,FT,Japan,S,Japan,50,"Azure, Docker, MLOps",Bachelor,0,Manufacturing,2024-02-13,2024-03-13,2014,8.1,TechCorp Inc -AI03088,Research Scientist,69118,USD,69118,EN,FL,United States,S,United States,100,"Spark, TensorFlow, Git, Docker, Java",Associate,0,Telecommunications,2024-12-12,2025-02-16,739,6,DeepTech Ventures -AI03089,Robotics Engineer,47701,USD,47701,MI,PT,China,M,China,0,"Git, Linux, Mathematics, Kubernetes, Spark",Master,3,Education,2024-08-02,2024-08-17,2068,9.5,Advanced Robotics -AI03090,Data Scientist,162815,USD,162815,SE,FL,Norway,L,Norway,50,"Mathematics, Docker, Statistics",Bachelor,9,Gaming,2024-12-13,2025-01-30,1879,7.3,Predictive Systems -AI03091,Deep Learning Engineer,136275,CHF,122648,MI,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Spark",Associate,3,Automotive,2024-07-11,2024-09-07,506,7.9,Future Systems -AI03092,AI Specialist,77774,CAD,97218,MI,PT,Canada,S,Canada,0,"AWS, Deep Learning, Docker",PhD,2,Retail,2025-04-16,2025-06-09,675,6.2,Neural Networks Co -AI03093,Computer Vision Engineer,151655,JPY,16682050,EX,FT,Japan,S,Japan,0,"Scala, SQL, MLOps, Azure, Kubernetes",Bachelor,17,Energy,2025-02-04,2025-02-27,1886,9.8,DataVision Ltd -AI03094,AI Specialist,147631,USD,147631,SE,FT,Finland,L,Finland,50,"Scala, Deep Learning, Java, Azure, PyTorch",PhD,5,Automotive,2024-03-18,2024-04-10,834,7.5,Digital Transformation LLC -AI03095,Robotics Engineer,44181,USD,44181,EX,CT,India,S,India,100,"GCP, Kubernetes, PyTorch",PhD,15,Transportation,2024-03-28,2024-05-15,2429,8.4,Predictive Systems -AI03096,AI Specialist,92006,EUR,78205,MI,FL,Germany,M,Germany,100,"Spark, Linux, NLP, SQL, Python",PhD,2,Real Estate,2024-10-06,2024-11-10,1434,6,DeepTech Ventures -AI03097,Data Analyst,104944,EUR,89202,MI,CT,Germany,L,Germany,0,"Python, Deep Learning, Data Visualization, R",Master,3,Education,2024-03-10,2024-04-04,1885,6.2,Predictive Systems -AI03098,ML Ops Engineer,261580,USD,261580,EX,CT,United States,M,United States,50,"Linux, Docker, Data Visualization, GCP, SQL",Bachelor,10,Transportation,2024-11-29,2024-12-31,1601,5.1,Neural Networks Co -AI03099,AI Software Engineer,32682,USD,32682,MI,FT,India,L,India,0,"GCP, Kubernetes, Azure",Master,4,Real Estate,2024-06-08,2024-07-17,1624,8.3,Algorithmic Solutions -AI03100,Research Scientist,46243,USD,46243,EN,FT,Sweden,S,Sweden,0,"Hadoop, TensorFlow, Git",Bachelor,1,Real Estate,2025-02-09,2025-04-13,1897,8.6,Quantum Computing Inc -AI03101,AI Software Engineer,51801,CAD,64751,EN,CT,Canada,S,Canada,0,"R, SQL, Linux, Kubernetes, Hadoop",PhD,1,Government,2024-03-16,2024-04-13,1014,8.8,Smart Analytics -AI03102,AI Software Engineer,110654,SGD,143850,MI,PT,Singapore,M,Singapore,0,"Hadoop, Mathematics, Kubernetes, PyTorch",Associate,4,Technology,2024-07-31,2024-09-04,1544,7.4,Cognitive Computing -AI03103,Data Scientist,123362,USD,123362,SE,CT,Israel,S,Israel,0,"Linux, AWS, MLOps, Scala, Python",PhD,8,Energy,2024-03-23,2024-05-08,1021,6.9,Future Systems -AI03104,Principal Data Scientist,66961,USD,66961,MI,FT,South Korea,M,South Korea,100,"Hadoop, Computer Vision, Java, Linux, R",PhD,3,Retail,2024-11-23,2025-01-04,960,7.7,Machine Intelligence Group -AI03105,Autonomous Systems Engineer,96935,USD,96935,MI,FL,Denmark,S,South Korea,50,"AWS, Data Visualization, MLOps",PhD,2,Education,2024-04-02,2024-05-17,597,9.4,DeepTech Ventures -AI03106,NLP Engineer,165702,JPY,18227220,EX,PT,Japan,L,Japan,50,"SQL, R, Linux, PyTorch",Master,12,Retail,2024-08-13,2024-09-01,1511,5.4,Autonomous Tech -AI03107,Computer Vision Engineer,102570,CHF,92313,MI,PT,Switzerland,M,Switzerland,0,"R, SQL, Data Visualization, Computer Vision, Java",Master,4,Healthcare,2024-11-15,2024-12-27,2061,7,Cognitive Computing -AI03108,Principal Data Scientist,31054,USD,31054,MI,CT,India,S,India,50,"Azure, Scala, Java, Mathematics",PhD,4,Government,2025-04-06,2025-05-05,716,5.4,Cognitive Computing -AI03109,AI Software Engineer,26978,USD,26978,EN,CT,China,M,China,0,"Kubernetes, Linux, Mathematics, Hadoop, Scala",Bachelor,1,Healthcare,2024-12-22,2025-01-30,2254,5.5,Neural Networks Co -AI03110,Machine Learning Engineer,45155,USD,45155,SE,FT,China,S,China,50,"Computer Vision, Tableau, Azure, Kubernetes, Spark",Master,5,Gaming,2024-04-03,2024-05-07,582,9.2,Smart Analytics -AI03111,Deep Learning Engineer,84059,USD,84059,MI,FL,United States,S,United States,50,"Linux, Docker, TensorFlow",Bachelor,4,Manufacturing,2024-06-23,2024-07-09,1520,9.1,Future Systems -AI03112,AI Product Manager,66866,USD,66866,EX,FT,India,L,India,0,"Spark, TensorFlow, SQL",Master,13,Transportation,2024-08-09,2024-09-29,2158,9.9,Cloud AI Solutions -AI03113,AI Software Engineer,56427,USD,56427,EN,CT,Ireland,M,Belgium,0,"Docker, Mathematics, PyTorch, Scala",Associate,0,Media,2024-12-19,2025-02-05,568,8.4,Autonomous Tech -AI03114,Principal Data Scientist,91432,USD,91432,MI,FL,Israel,L,Chile,50,"Git, Hadoop, Computer Vision",PhD,3,Healthcare,2024-01-09,2024-03-19,958,7.4,AI Innovations -AI03115,ML Ops Engineer,117486,EUR,99863,SE,FL,France,L,France,50,"Python, R, Computer Vision, Data Visualization, Statistics",PhD,9,Automotive,2025-02-18,2025-04-13,1430,6.9,Digital Transformation LLC -AI03116,ML Ops Engineer,85568,USD,85568,MI,CT,Finland,M,Sweden,0,"Kubernetes, Spark, Tableau, Statistics",PhD,2,Finance,2025-04-11,2025-06-17,538,9.7,Cognitive Computing -AI03117,ML Ops Engineer,308132,EUR,261912,EX,FL,Netherlands,L,India,0,"Hadoop, MLOps, Spark, Linux, R",Associate,19,Retail,2025-04-04,2025-05-24,991,7.7,Future Systems -AI03118,Head of AI,262758,SGD,341585,EX,FL,Singapore,M,Singapore,100,"Python, Computer Vision, Scala",Master,19,Transportation,2024-08-31,2024-09-22,1556,7.2,Autonomous Tech -AI03119,Principal Data Scientist,61958,USD,61958,EX,FL,India,M,Canada,50,"Java, Python, Tableau, Kubernetes, Docker",Master,12,Gaming,2024-10-23,2024-12-27,1245,8.3,Digital Transformation LLC -AI03120,Data Engineer,116493,USD,116493,SE,FL,Ireland,M,Brazil,0,"Linux, AWS, SQL, Kubernetes",PhD,8,Transportation,2024-05-30,2024-07-13,2110,5.1,TechCorp Inc -AI03121,Machine Learning Engineer,174253,SGD,226529,EX,FT,Singapore,S,Singapore,100,"Hadoop, Azure, NLP",Bachelor,14,Education,2025-04-02,2025-04-16,783,5.7,Algorithmic Solutions -AI03122,Research Scientist,133772,USD,133772,SE,PT,United States,S,United States,50,"Kubernetes, PyTorch, GCP",Bachelor,7,Media,2024-04-19,2024-05-04,1741,7.8,Smart Analytics -AI03123,Machine Learning Engineer,183867,USD,183867,EX,FT,Israel,L,Israel,0,"Scala, Computer Vision, Tableau, AWS",PhD,15,Manufacturing,2024-10-05,2024-12-08,1829,6.4,Advanced Robotics -AI03124,Data Analyst,100550,JPY,11060500,MI,FL,Japan,L,Japan,100,"Tableau, Hadoop, Azure, PyTorch, TensorFlow",Associate,3,Transportation,2025-02-28,2025-04-15,842,6.9,Digital Transformation LLC -AI03125,Data Engineer,209570,EUR,178135,EX,FT,Austria,M,Austria,100,"SQL, Python, Java",Associate,10,Telecommunications,2025-01-04,2025-03-08,1946,6.3,Cognitive Computing -AI03126,Machine Learning Researcher,27770,USD,27770,EN,CT,India,L,India,50,"Deep Learning, PyTorch, MLOps, TensorFlow",PhD,0,Manufacturing,2025-01-31,2025-03-25,695,6.1,Machine Intelligence Group -AI03127,Head of AI,239820,SGD,311766,EX,PT,Singapore,M,Singapore,100,"Java, Python, NLP",Bachelor,13,Retail,2024-04-12,2024-06-01,1250,8.2,Future Systems -AI03128,Machine Learning Researcher,90202,USD,90202,EN,FL,Ireland,L,Ireland,50,"Kubernetes, MLOps, PyTorch",PhD,0,Consulting,2025-01-15,2025-03-16,1443,8.8,DataVision Ltd -AI03129,Computer Vision Engineer,47313,EUR,40216,EN,FL,Austria,S,Austria,0,"Python, NLP, TensorFlow",Master,0,Consulting,2025-03-22,2025-05-10,1996,7.4,Predictive Systems -AI03130,Data Analyst,57899,USD,57899,EN,CT,Israel,M,Israel,100,"R, Computer Vision, GCP",Bachelor,1,Healthcare,2024-02-18,2024-04-01,1649,7.8,Machine Intelligence Group -AI03131,ML Ops Engineer,181110,GBP,135833,SE,PT,United Kingdom,L,Mexico,0,"SQL, R, Scala",Bachelor,5,Consulting,2025-04-09,2025-04-29,692,7.4,Autonomous Tech -AI03132,Principal Data Scientist,81776,USD,81776,MI,PT,South Korea,L,South Korea,0,"SQL, Java, Docker, Tableau, Computer Vision",PhD,2,Finance,2024-09-28,2024-12-08,1310,8.1,Advanced Robotics -AI03133,ML Ops Engineer,144619,GBP,108464,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, AWS, Kubernetes",PhD,12,Retail,2025-03-02,2025-05-02,1415,5.4,Digital Transformation LLC -AI03134,AI Specialist,79986,EUR,67988,MI,FL,Germany,S,Germany,50,"Hadoop, Python, MLOps, NLP",Associate,2,Automotive,2024-01-10,2024-03-17,772,6.7,Predictive Systems -AI03135,AI Architect,70655,USD,70655,EN,FT,United States,M,United States,50,"Mathematics, Linux, SQL, AWS, Tableau",Master,1,Healthcare,2024-07-30,2024-09-01,2024,5.8,Future Systems -AI03136,AI Specialist,250855,USD,250855,EX,PT,United States,S,United States,0,"Spark, Git, Data Visualization, MLOps",Master,15,Energy,2024-04-05,2024-05-01,1802,6.1,Advanced Robotics -AI03137,Machine Learning Engineer,91522,GBP,68642,MI,CT,United Kingdom,M,United Kingdom,100,"Tableau, Azure, PyTorch, SQL, Deep Learning",Bachelor,2,Technology,2024-03-27,2024-05-07,1299,7.3,Digital Transformation LLC -AI03138,Principal Data Scientist,124095,CAD,155119,SE,FL,Canada,S,Ghana,50,"SQL, Scala, GCP",Master,9,Media,2024-05-31,2024-06-28,932,8.3,Cloud AI Solutions -AI03139,Computer Vision Engineer,84282,CAD,105353,MI,FT,Canada,M,Indonesia,50,"Scala, Linux, Kubernetes, Python",PhD,2,Energy,2024-07-22,2024-09-15,1571,6.4,Digital Transformation LLC -AI03140,Data Scientist,163240,USD,163240,SE,FL,United States,M,Russia,50,"Scala, SQL, Azure",Master,5,Government,2024-09-23,2024-11-10,896,8.1,Quantum Computing Inc -AI03141,Machine Learning Researcher,168185,USD,168185,SE,CT,Ireland,L,Ireland,50,"Computer Vision, Git, Python, TensorFlow",Bachelor,7,Consulting,2024-11-08,2024-12-06,2288,7.5,DataVision Ltd -AI03142,Robotics Engineer,116627,USD,116627,MI,CT,United States,S,United States,0,"TensorFlow, NLP, Azure, Linux, Mathematics",Master,3,Education,2024-03-07,2024-05-03,1812,9.9,Machine Intelligence Group -AI03143,AI Product Manager,101270,USD,101270,MI,FT,United States,S,United States,50,"Python, Azure, Tableau",Associate,2,Healthcare,2024-01-03,2024-02-12,602,7,Digital Transformation LLC -AI03144,ML Ops Engineer,65343,USD,65343,EN,CT,Sweden,M,Sweden,100,"GCP, SQL, Tableau",Bachelor,1,Media,2025-03-06,2025-05-15,818,9.8,Predictive Systems -AI03145,Computer Vision Engineer,137416,USD,137416,SE,FT,South Korea,L,Colombia,50,"SQL, Python, MLOps",PhD,9,Telecommunications,2024-07-28,2024-09-22,1997,8.8,Machine Intelligence Group -AI03146,Robotics Engineer,295909,EUR,251523,EX,FL,Netherlands,L,Netherlands,100,"Spark, TensorFlow, Tableau, AWS, Python",Bachelor,10,Healthcare,2024-08-09,2024-08-23,1672,9.7,AI Innovations -AI03147,Autonomous Systems Engineer,143218,USD,143218,SE,FL,Ireland,M,Finland,0,"SQL, Scala, Spark, Azure",PhD,8,Technology,2024-02-15,2024-03-01,1730,9.3,Neural Networks Co -AI03148,Head of AI,190216,EUR,161684,EX,FL,Netherlands,L,Netherlands,0,"Python, MLOps, Kubernetes",Associate,18,Manufacturing,2024-04-10,2024-04-27,2389,5.4,Smart Analytics -AI03149,Data Analyst,151114,JPY,16622540,EX,FT,Japan,S,Japan,50,"Spark, Statistics, Docker, Linux, Hadoop",Master,18,Gaming,2025-04-06,2025-05-03,1213,5.7,Algorithmic Solutions -AI03150,Robotics Engineer,77870,USD,77870,EN,CT,Norway,L,Norway,50,"TensorFlow, PyTorch, AWS, Deep Learning",PhD,0,Automotive,2025-01-12,2025-03-11,2177,5.8,Smart Analytics -AI03151,Robotics Engineer,49183,JPY,5410130,EN,FL,Japan,S,Japan,50,"Tableau, Statistics, Python, NLP, Computer Vision",Master,0,Consulting,2025-02-13,2025-02-27,2439,8.5,DeepTech Ventures -AI03152,Autonomous Systems Engineer,62143,USD,62143,EN,PT,Israel,M,Ukraine,100,"Python, GCP, Deep Learning",Associate,1,Education,2025-01-24,2025-02-24,2048,5.3,Quantum Computing Inc -AI03153,AI Software Engineer,121259,AUD,163700,SE,CT,Australia,M,Belgium,0,"Statistics, Git, Deep Learning, Data Visualization, GCP",PhD,5,Real Estate,2025-02-01,2025-03-03,2113,8.3,Advanced Robotics -AI03154,AI Software Engineer,128628,JPY,14149080,SE,PT,Japan,M,Japan,50,"Statistics, Python, Kubernetes, Git, TensorFlow",Bachelor,9,Telecommunications,2024-12-01,2024-12-21,2034,7.3,Cloud AI Solutions -AI03155,Research Scientist,115473,CAD,144341,SE,CT,Canada,M,Ukraine,50,"Python, Kubernetes, Azure, Spark, TensorFlow",Associate,8,Government,2025-01-21,2025-02-25,1666,9.7,Quantum Computing Inc -AI03156,Data Engineer,238600,USD,238600,EX,FT,Israel,M,Israel,0,"PyTorch, NLP, Python, GCP",Master,11,Media,2024-01-26,2024-03-31,1708,9.6,Advanced Robotics -AI03157,AI Product Manager,113103,CHF,101793,EN,PT,Switzerland,L,Switzerland,0,"SQL, Linux, NLP, Azure, PyTorch",Bachelor,1,Real Estate,2025-01-21,2025-03-19,1928,6.4,Advanced Robotics -AI03158,Deep Learning Engineer,47429,USD,47429,SE,PT,India,S,India,50,"R, Git, SQL, Docker",Associate,7,Government,2024-04-28,2024-06-19,1964,6.3,Algorithmic Solutions -AI03159,AI Research Scientist,274181,USD,274181,EX,PT,Israel,L,Philippines,0,"Scala, AWS, SQL, MLOps",Associate,17,Technology,2025-02-18,2025-03-10,780,9.2,Neural Networks Co -AI03160,Principal Data Scientist,139553,CAD,174441,SE,FT,Canada,M,Canada,50,"Kubernetes, Java, Spark",Bachelor,6,Consulting,2024-12-13,2025-02-03,2398,8.9,Digital Transformation LLC -AI03161,AI Product Manager,83557,USD,83557,MI,CT,Finland,S,Singapore,100,"NLP, Kubernetes, Hadoop, R",PhD,3,Consulting,2024-08-25,2024-10-14,2148,5.2,Autonomous Tech -AI03162,AI Consultant,211357,AUD,285332,EX,CT,Australia,S,Turkey,0,"Scala, Git, Spark, Python",Master,15,Transportation,2024-12-16,2025-02-09,2101,8.2,Digital Transformation LLC -AI03163,ML Ops Engineer,181722,CHF,163550,SE,PT,Switzerland,M,Switzerland,100,"Azure, R, GCP",PhD,8,Real Estate,2024-02-11,2024-04-04,1248,7.2,Machine Intelligence Group -AI03164,Computer Vision Engineer,137403,CAD,171754,SE,CT,Canada,M,Indonesia,0,"TensorFlow, Mathematics, Computer Vision, Python, GCP",Bachelor,8,Finance,2024-03-17,2024-04-07,2482,5.8,Quantum Computing Inc -AI03165,Principal Data Scientist,65926,SGD,85704,EN,CT,Singapore,S,Singapore,0,"Python, MLOps, GCP, Mathematics",Master,1,Transportation,2024-10-08,2024-12-03,666,7.8,DeepTech Ventures -AI03166,Head of AI,63867,USD,63867,EN,CT,Sweden,L,Italy,100,"MLOps, Tableau, GCP, PyTorch, TensorFlow",PhD,0,Real Estate,2025-04-01,2025-05-22,1004,9.7,Advanced Robotics -AI03167,Deep Learning Engineer,73754,EUR,62691,EN,CT,Germany,L,Germany,0,"Linux, R, Data Visualization",Associate,0,Real Estate,2024-07-26,2024-08-17,1181,7.4,Predictive Systems -AI03168,Data Analyst,100588,GBP,75441,MI,CT,United Kingdom,S,United Kingdom,0,"Git, AWS, SQL",Master,4,Government,2024-02-23,2024-03-08,722,9.7,AI Innovations -AI03169,Robotics Engineer,215335,USD,215335,EX,PT,Ireland,S,Ireland,100,"NLP, SQL, Tableau",Bachelor,19,Technology,2025-03-17,2025-04-07,1676,7.2,Quantum Computing Inc -AI03170,AI Architect,96892,GBP,72669,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Linux, PyTorch",PhD,1,Real Estate,2024-07-02,2024-09-03,680,7.3,Neural Networks Co -AI03171,Head of AI,203281,USD,203281,SE,CT,Norway,L,Norway,0,"SQL, Docker, Azure",PhD,9,Technology,2024-07-24,2024-09-30,875,8.7,Cloud AI Solutions -AI03172,Deep Learning Engineer,128930,CHF,116037,MI,PT,Switzerland,M,Switzerland,0,"SQL, PyTorch, GCP, Tableau, Deep Learning",Associate,3,Consulting,2024-12-20,2025-02-21,1288,5,Machine Intelligence Group -AI03173,AI Architect,59295,CAD,74119,EN,FL,Canada,S,Canada,50,"MLOps, Linux, SQL, Statistics",Bachelor,0,Consulting,2024-03-22,2024-04-20,1581,5.1,Algorithmic Solutions -AI03174,AI Architect,149462,CAD,186828,EX,CT,Canada,S,Canada,100,"Spark, Computer Vision, R, SQL",PhD,13,Real Estate,2024-05-28,2024-06-30,1196,7.9,Digital Transformation LLC -AI03175,Data Analyst,134389,USD,134389,EX,FL,South Korea,S,South Korea,50,"Python, Java, MLOps, GCP, Deep Learning",PhD,12,Manufacturing,2025-04-30,2025-05-26,2156,8,Quantum Computing Inc -AI03176,Deep Learning Engineer,77125,USD,77125,EN,FT,Sweden,L,Sweden,50,"Azure, SQL, Linux, Data Visualization, Git",Master,1,Telecommunications,2024-10-22,2024-12-11,2144,8.6,Machine Intelligence Group -AI03177,Autonomous Systems Engineer,177796,GBP,133347,EX,PT,United Kingdom,L,United Kingdom,0,"SQL, Tableau, GCP, AWS",Bachelor,12,Real Estate,2024-09-18,2024-10-03,1210,8.5,Algorithmic Solutions -AI03178,Robotics Engineer,146724,USD,146724,SE,CT,Denmark,M,Denmark,100,"Data Visualization, Python, MLOps, Kubernetes",Bachelor,5,Media,2024-09-01,2024-10-05,628,9.4,DeepTech Ventures -AI03179,Data Engineer,170330,USD,170330,SE,CT,Norway,M,Norway,100,"Git, Statistics, Spark, Python, MLOps",Master,6,Manufacturing,2024-05-06,2024-05-29,2072,7.8,Quantum Computing Inc -AI03180,Computer Vision Engineer,79412,USD,79412,MI,CT,South Korea,S,Finland,100,"NLP, Docker, SQL, Python",Master,3,Energy,2024-09-13,2024-10-22,1679,9.2,Future Systems -AI03181,AI Specialist,124306,EUR,105660,SE,FL,Netherlands,L,Netherlands,100,"Python, Azure, GCP, Mathematics, R",Associate,7,Finance,2024-11-02,2024-12-23,1981,6.4,TechCorp Inc -AI03182,Head of AI,119037,EUR,101181,SE,FT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, Tableau, Python, TensorFlow",Bachelor,7,Technology,2024-12-24,2025-01-16,1560,9.9,Algorithmic Solutions -AI03183,NLP Engineer,222977,EUR,189530,EX,FL,Germany,L,Germany,0,"NLP, Computer Vision, Data Visualization, Docker, SQL",PhD,13,Finance,2025-02-21,2025-03-24,869,9,Machine Intelligence Group -AI03184,Data Engineer,136646,CAD,170808,SE,PT,Canada,M,Canada,100,"Python, Docker, Hadoop, Deep Learning",PhD,9,Telecommunications,2024-05-03,2024-06-06,1317,8.4,Algorithmic Solutions -AI03185,AI Specialist,192004,JPY,21120440,EX,FT,Japan,L,France,0,"Kubernetes, AWS, PyTorch",Master,11,Real Estate,2024-05-25,2024-08-03,2244,6.5,Future Systems -AI03186,Research Scientist,270814,GBP,203111,EX,PT,United Kingdom,L,Sweden,0,"Spark, Deep Learning, Azure, Java, Tableau",Bachelor,17,Gaming,2024-05-18,2024-07-25,1890,6.6,Neural Networks Co -AI03187,AI Consultant,125599,USD,125599,SE,FL,Sweden,M,Sweden,0,"Computer Vision, Java, Data Visualization",Associate,8,Technology,2024-03-07,2024-04-17,723,7.7,TechCorp Inc -AI03188,Machine Learning Engineer,102825,USD,102825,MI,PT,Finland,L,United Kingdom,100,"Docker, Tableau, Hadoop, Computer Vision",Associate,3,Technology,2024-02-16,2024-04-02,1608,7.2,Cloud AI Solutions -AI03189,AI Research Scientist,233678,JPY,25704580,EX,FT,Japan,L,Malaysia,100,"MLOps, Azure, Tableau, NLP, PyTorch",Associate,15,Consulting,2024-08-04,2024-09-30,1310,6.8,Predictive Systems -AI03190,AI Consultant,92649,EUR,78752,MI,PT,Netherlands,M,Czech Republic,100,"Spark, Tableau, MLOps",Associate,4,Energy,2024-09-04,2024-09-23,644,9.9,Advanced Robotics -AI03191,AI Research Scientist,102702,EUR,87297,MI,CT,Germany,M,Germany,0,"GCP, Docker, Scala, Python",PhD,4,Automotive,2025-03-05,2025-04-18,765,7,Machine Intelligence Group -AI03192,Autonomous Systems Engineer,220138,SGD,286179,EX,PT,Singapore,S,Singapore,0,"Java, Linux, Scala, Kubernetes",Associate,10,Finance,2024-12-10,2025-01-28,1094,5.1,Machine Intelligence Group -AI03193,NLP Engineer,102269,SGD,132950,MI,PT,Singapore,L,Singapore,50,"SQL, Python, Deep Learning, Linux",Bachelor,3,Energy,2024-08-19,2024-10-31,1527,10,Cognitive Computing -AI03194,AI Software Engineer,164789,USD,164789,EX,FL,Denmark,S,Denmark,100,"Linux, Scala, Docker",Master,15,Retail,2024-02-22,2024-04-09,2219,9.6,DeepTech Ventures -AI03195,AI Software Engineer,37291,USD,37291,MI,FT,India,L,India,50,"PyTorch, TensorFlow, Docker, Hadoop, Linux",Associate,2,Consulting,2024-12-19,2025-01-27,2137,8.6,AI Innovations -AI03196,NLP Engineer,112266,USD,112266,MI,FT,United States,M,United States,50,"Azure, Kubernetes, AWS",Associate,3,Transportation,2025-03-18,2025-05-22,2235,5.7,Cloud AI Solutions -AI03197,NLP Engineer,67601,USD,67601,EN,FL,South Korea,L,Canada,0,"NLP, GCP, Scala",Associate,0,Finance,2024-01-26,2024-03-27,2022,5.7,Cognitive Computing -AI03198,AI Software Engineer,265839,CAD,332299,EX,CT,Canada,L,Canada,0,"Tableau, SQL, Hadoop, Computer Vision, PyTorch",Master,16,Technology,2024-07-12,2024-08-17,1079,9.9,Cloud AI Solutions -AI03199,Autonomous Systems Engineer,127393,CAD,159241,SE,FT,Canada,S,Canada,50,"SQL, Tableau, Docker, PyTorch",PhD,6,Finance,2025-03-02,2025-04-06,961,9.6,Digital Transformation LLC -AI03200,Machine Learning Engineer,79956,USD,79956,MI,FL,Israel,M,Israel,50,"SQL, Scala, Hadoop, Computer Vision, Python",Associate,3,Automotive,2024-05-05,2024-07-16,1366,7,AI Innovations -AI03201,AI Product Manager,64844,USD,64844,EN,PT,Finland,M,Finland,100,"MLOps, Linux, TensorFlow",Associate,0,Manufacturing,2025-03-11,2025-04-05,642,6.3,AI Innovations -AI03202,Data Analyst,255126,GBP,191345,EX,PT,United Kingdom,L,Netherlands,50,"Docker, MLOps, Data Visualization",Master,17,Technology,2024-02-26,2024-03-11,1055,5.4,Cognitive Computing -AI03203,Data Analyst,55235,USD,55235,EN,FL,Sweden,M,Sweden,100,"Scala, Kubernetes, NLP, Azure",Associate,0,Gaming,2025-01-19,2025-03-16,2002,6.9,Cognitive Computing -AI03204,AI Product Manager,179903,EUR,152918,SE,FT,Netherlands,L,Netherlands,0,"Linux, Scala, Java, Docker",Master,7,Media,2024-01-24,2024-03-30,759,6.3,Machine Intelligence Group -AI03205,Deep Learning Engineer,99326,USD,99326,MI,FT,Finland,L,Finland,100,"Tableau, R, Linux, Git, Java",PhD,2,Transportation,2024-11-09,2024-12-01,713,7.9,Algorithmic Solutions -AI03206,NLP Engineer,36397,USD,36397,MI,PT,China,S,China,100,"NLP, Tableau, Docker, MLOps, Data Visualization",Master,4,Gaming,2025-03-20,2025-05-18,863,9.6,Advanced Robotics -AI03207,Head of AI,55499,USD,55499,SE,FT,China,L,China,50,"Spark, R, Hadoop, Kubernetes",PhD,6,Consulting,2024-03-15,2024-04-29,2352,9.4,Future Systems -AI03208,Data Analyst,32595,USD,32595,MI,FT,India,M,Kenya,100,"Python, MLOps, Data Visualization, AWS",Master,3,Government,2024-09-08,2024-10-05,1738,6.4,Advanced Robotics -AI03209,AI Software Engineer,257447,USD,257447,EX,PT,United States,S,United States,0,"Python, PyTorch, TensorFlow, R",Master,19,Consulting,2024-04-07,2024-06-05,2080,6.7,Predictive Systems -AI03210,Research Scientist,92838,EUR,78912,MI,CT,Austria,M,Austria,0,"PyTorch, Azure, MLOps, GCP",Bachelor,2,Real Estate,2024-04-24,2024-05-10,957,7.2,Cloud AI Solutions -AI03211,ML Ops Engineer,90741,EUR,77130,MI,FT,Austria,S,Austria,0,"Tableau, NLP, GCP, Java",PhD,4,Retail,2024-05-05,2024-06-27,2471,7.1,Cloud AI Solutions -AI03212,Computer Vision Engineer,76319,USD,76319,SE,FL,South Korea,S,South Korea,0,"TensorFlow, Python, Docker, Java",Master,6,Media,2024-03-20,2024-05-24,839,6.4,Autonomous Tech -AI03213,AI Specialist,210418,EUR,178855,EX,FT,Austria,L,Austria,100,"Java, Azure, MLOps",Master,11,Government,2024-11-12,2024-12-14,1743,8.4,DataVision Ltd -AI03214,AI Software Engineer,196045,EUR,166638,EX,FL,Germany,M,Romania,0,"Docker, Python, Kubernetes",PhD,10,Education,2024-11-02,2024-11-23,512,5.2,Neural Networks Co -AI03215,Deep Learning Engineer,135969,CHF,122372,SE,FT,Switzerland,S,Belgium,100,"R, Kubernetes, Docker",PhD,8,Technology,2024-09-18,2024-10-09,1530,5.3,Future Systems -AI03216,Head of AI,48643,EUR,41347,EN,FT,Netherlands,S,Netherlands,100,"NLP, Scala, R, Tableau, Python",Bachelor,1,Retail,2024-03-11,2024-04-04,2102,7.5,DeepTech Ventures -AI03217,AI Architect,78066,USD,78066,EN,PT,Finland,L,Egypt,0,"Python, Data Visualization, Kubernetes",Bachelor,0,Real Estate,2025-03-24,2025-05-26,2098,7.9,TechCorp Inc -AI03218,Machine Learning Researcher,41677,USD,41677,EN,CT,South Korea,S,South Korea,100,"MLOps, R, Kubernetes, Deep Learning",Associate,0,Energy,2024-07-09,2024-09-15,1351,6.1,Autonomous Tech -AI03219,Deep Learning Engineer,93162,JPY,10247820,EN,FT,Japan,L,Japan,100,"Python, Deep Learning, Java",Master,0,Manufacturing,2024-09-06,2024-11-10,1406,9.7,Cognitive Computing -AI03220,Research Scientist,64788,EUR,55070,EN,PT,Germany,S,Hungary,50,"PyTorch, Statistics, Spark, SQL, GCP",Associate,0,Media,2024-11-18,2025-01-28,1017,6,Neural Networks Co -AI03221,AI Architect,154205,USD,154205,EX,CT,Ireland,S,Ireland,50,"Azure, AWS, GCP, Spark",Bachelor,19,Media,2024-10-15,2024-10-31,1369,7.8,Algorithmic Solutions -AI03222,Principal Data Scientist,143701,USD,143701,SE,CT,Israel,M,Israel,100,"Tableau, SQL, Scala, Azure",Associate,8,Media,2025-04-04,2025-06-14,557,6.2,DataVision Ltd -AI03223,Data Scientist,164876,CHF,148388,SE,PT,Switzerland,S,Switzerland,0,"Kubernetes, AWS, Scala, GCP",Bachelor,9,Government,2025-01-01,2025-01-16,1603,6.2,Neural Networks Co -AI03224,Autonomous Systems Engineer,35464,USD,35464,EN,FT,China,M,China,0,"Mathematics, Docker, Azure",PhD,1,Education,2024-02-03,2024-02-28,736,9.4,DeepTech Ventures -AI03225,AI Specialist,59626,USD,59626,EN,FL,Ireland,M,Ireland,0,"Linux, Java, Scala",Bachelor,1,Gaming,2025-03-15,2025-04-18,624,5.5,TechCorp Inc -AI03226,AI Specialist,307432,USD,307432,EX,FL,Norway,M,Norway,100,"Linux, Python, NLP",PhD,11,Manufacturing,2025-01-31,2025-03-30,2437,9.6,Digital Transformation LLC -AI03227,AI Architect,176090,USD,176090,SE,FL,Norway,S,Luxembourg,100,"Hadoop, AWS, Spark",Associate,6,Technology,2025-02-27,2025-04-07,2082,9.2,AI Innovations -AI03228,AI Architect,66682,USD,66682,EN,FL,United States,S,United States,0,"Scala, Java, NLP, R",Associate,0,Finance,2024-08-19,2024-09-24,1664,9.8,Digital Transformation LLC -AI03229,Data Analyst,39616,USD,39616,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Scala, Tableau, R, Python",PhD,0,Real Estate,2024-06-13,2024-07-30,550,8,DeepTech Ventures -AI03230,AI Product Manager,122403,CHF,110163,EN,PT,Switzerland,L,Singapore,100,"TensorFlow, Kubernetes, NLP",Associate,0,Finance,2024-01-23,2024-03-02,2351,8.2,Cognitive Computing -AI03231,Deep Learning Engineer,130431,USD,130431,SE,FT,Finland,M,Finland,100,"Linux, R, NLP",PhD,8,Government,2024-08-26,2024-11-07,1081,6.4,Smart Analytics -AI03232,AI Software Engineer,91342,EUR,77641,MI,PT,Germany,S,Germany,100,"Hadoop, SQL, Docker",Bachelor,4,Healthcare,2024-02-05,2024-04-15,524,6.7,TechCorp Inc -AI03233,AI Product Manager,34743,USD,34743,EN,FL,China,M,China,100,"R, Hadoop, PyTorch",Master,0,Real Estate,2024-03-08,2024-05-01,1698,7.9,Future Systems -AI03234,Computer Vision Engineer,75941,EUR,64550,MI,FT,France,S,France,100,"Statistics, R, Python, GCP",Master,3,Telecommunications,2024-06-30,2024-08-12,1131,6.5,Machine Intelligence Group -AI03235,AI Product Manager,53406,USD,53406,EN,CT,South Korea,M,South Korea,100,"NLP, Kubernetes, Python",Associate,0,Manufacturing,2025-03-01,2025-05-12,2231,9.6,Neural Networks Co -AI03236,Autonomous Systems Engineer,280999,CHF,252899,EX,FT,Switzerland,M,Switzerland,100,"Linux, Kubernetes, GCP, Python",Associate,18,Gaming,2024-06-11,2024-08-17,1120,9.3,Predictive Systems -AI03237,Computer Vision Engineer,211482,SGD,274927,EX,PT,Singapore,L,Singapore,50,"Scala, Statistics, Python",Bachelor,17,Education,2024-09-26,2024-11-06,1183,8,DeepTech Ventures -AI03238,AI Architect,188072,CHF,169265,EX,CT,Switzerland,S,Switzerland,100,"SQL, Kubernetes, Azure",Associate,11,Automotive,2025-02-15,2025-03-15,1142,5.9,Predictive Systems -AI03239,NLP Engineer,89391,EUR,75982,MI,FL,Germany,M,Germany,0,"SQL, Hadoop, Java",Bachelor,2,Consulting,2025-04-15,2025-04-29,2251,6.3,DeepTech Ventures -AI03240,Machine Learning Researcher,172617,CHF,155355,SE,FL,Switzerland,L,Switzerland,0,"Data Visualization, NLP, Azure",Associate,7,Real Estate,2024-11-08,2024-12-19,1254,6.3,Digital Transformation LLC -AI03241,Head of AI,247125,SGD,321263,EX,FT,Singapore,L,Singapore,100,"TensorFlow, Git, Java, Azure, NLP",PhD,18,Energy,2025-03-23,2025-04-11,616,6.1,Advanced Robotics -AI03242,AI Architect,58586,EUR,49798,EN,CT,Austria,L,Austria,0,"Python, AWS, Kubernetes, Scala, Statistics",PhD,0,Government,2025-02-10,2025-03-02,1313,8.6,Quantum Computing Inc -AI03243,AI Consultant,66857,USD,66857,EN,FT,United States,M,France,100,"GCP, Scala, Mathematics",Associate,0,Manufacturing,2024-04-16,2024-05-05,1143,8.9,DeepTech Ventures -AI03244,Machine Learning Engineer,61082,USD,61082,EN,FT,Ireland,S,Ireland,0,"MLOps, Data Visualization, PyTorch, Kubernetes, Python",PhD,1,Government,2024-10-19,2024-12-13,1334,6.9,DataVision Ltd -AI03245,Principal Data Scientist,109973,SGD,142965,MI,FL,Singapore,M,Singapore,100,"Kubernetes, MLOps, Spark, R, SQL",Associate,4,Real Estate,2024-03-04,2024-03-29,1826,9.1,Machine Intelligence Group -AI03246,Machine Learning Engineer,96154,GBP,72116,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, Data Visualization, Scala, Tableau",PhD,3,Telecommunications,2024-10-28,2024-12-15,1199,8.5,Smart Analytics -AI03247,Data Engineer,80737,EUR,68626,MI,CT,France,L,France,50,"Java, Python, Docker",PhD,3,Manufacturing,2024-08-25,2024-09-15,1683,7.5,Quantum Computing Inc -AI03248,Data Analyst,60211,USD,60211,EN,PT,Israel,S,Israel,50,"NLP, Deep Learning, PyTorch, Mathematics, Scala",PhD,0,Technology,2025-01-16,2025-03-09,1572,5.4,DataVision Ltd -AI03249,AI Research Scientist,77885,EUR,66202,MI,PT,Austria,M,Austria,50,"Docker, Azure, Kubernetes",Associate,2,Gaming,2024-09-16,2024-10-07,1002,8.5,Algorithmic Solutions -AI03250,Machine Learning Engineer,91640,CAD,114550,MI,PT,Canada,S,China,50,"PyTorch, TensorFlow, Java, MLOps, AWS",Bachelor,4,Education,2025-03-02,2025-04-13,2355,6.5,Digital Transformation LLC -AI03251,Principal Data Scientist,136201,CAD,170251,EX,FT,Canada,S,Canada,100,"Kubernetes, Java, MLOps",Associate,11,Healthcare,2024-09-24,2024-11-22,1786,9.9,Smart Analytics -AI03252,Machine Learning Researcher,100307,SGD,130399,SE,PT,Singapore,S,Singapore,100,"R, SQL, Statistics, PyTorch",Associate,8,Government,2024-04-16,2024-05-10,844,7.7,Cloud AI Solutions -AI03253,AI Specialist,71821,CAD,89776,EN,FT,Canada,L,Canada,0,"Azure, R, NLP, Hadoop, Git",Bachelor,0,Manufacturing,2024-08-27,2024-09-24,1281,7.9,Future Systems -AI03254,AI Software Engineer,92325,USD,92325,MI,CT,Finland,L,Finland,100,"TensorFlow, Python, Java, Linux",Bachelor,2,Telecommunications,2024-07-26,2024-08-28,1168,8.5,Digital Transformation LLC -AI03255,Machine Learning Researcher,128402,EUR,109142,SE,PT,Germany,S,Germany,0,"Spark, SQL, Azure, GCP, Deep Learning",PhD,5,Government,2025-01-18,2025-03-10,2118,6.3,Quantum Computing Inc -AI03256,Data Analyst,49741,USD,49741,EX,CT,India,M,India,0,"Docker, MLOps, Spark",Associate,12,Real Estate,2024-02-11,2024-04-19,1653,8.1,TechCorp Inc -AI03257,AI Software Engineer,189605,CHF,170645,SE,FT,Switzerland,S,Switzerland,0,"TensorFlow, Python, Tableau, Deep Learning",PhD,5,Real Estate,2025-02-06,2025-03-22,1625,6,Cognitive Computing -AI03258,Machine Learning Engineer,91412,SGD,118836,EN,FL,Singapore,L,United States,100,"Deep Learning, SQL, Hadoop",Associate,1,Education,2025-01-25,2025-03-19,966,7.7,Machine Intelligence Group -AI03259,Robotics Engineer,214536,USD,214536,SE,CT,Denmark,L,Poland,50,"SQL, Java, Statistics, Computer Vision, Deep Learning",PhD,8,Healthcare,2024-08-26,2024-10-23,1367,9.8,AI Innovations -AI03260,Machine Learning Researcher,93353,USD,93353,MI,PT,Norway,S,Norway,0,"Computer Vision, SQL, NLP, PyTorch, AWS",Associate,3,Education,2024-06-30,2024-07-30,2332,5.1,Autonomous Tech -AI03261,AI Architect,119157,USD,119157,SE,CT,Finland,L,Finland,100,"Kubernetes, PyTorch, GCP, Azure",Bachelor,7,Government,2024-01-07,2024-01-24,783,5.4,Advanced Robotics -AI03262,AI Specialist,262609,CHF,236348,EX,CT,Switzerland,L,Switzerland,50,"Hadoop, TensorFlow, PyTorch, Azure",Bachelor,16,Education,2024-05-11,2024-07-22,2100,5.6,Cloud AI Solutions -AI03263,AI Product Manager,69585,AUD,93940,EN,PT,Australia,S,Australia,100,"Computer Vision, Mathematics, Azure, R",PhD,0,Real Estate,2024-12-23,2025-01-20,1195,9.8,Machine Intelligence Group -AI03264,AI Product Manager,74761,AUD,100927,EN,PT,Australia,M,Australia,50,"MLOps, GCP, Docker, Python",Bachelor,0,Government,2024-12-07,2025-01-15,1022,6.9,AI Innovations -AI03265,ML Ops Engineer,162450,CHF,146205,SE,PT,Switzerland,M,Switzerland,0,"Spark, Git, Mathematics, Kubernetes, Python",Associate,7,Automotive,2024-07-06,2024-08-05,2224,6.5,Machine Intelligence Group -AI03266,Data Scientist,88851,USD,88851,EN,FL,Norway,S,Norway,100,"Data Visualization, Linux, Hadoop, Tableau",Bachelor,1,Retail,2025-03-30,2025-04-27,776,9.7,Quantum Computing Inc -AI03267,Autonomous Systems Engineer,91547,EUR,77815,EN,CT,Netherlands,L,Denmark,100,"PyTorch, Scala, Spark, SQL",Master,0,Finance,2025-02-22,2025-03-14,1399,6.3,DeepTech Ventures -AI03268,Principal Data Scientist,58081,EUR,49369,EN,FT,Germany,M,Germany,50,"TensorFlow, Kubernetes, Python, R",PhD,0,Technology,2024-12-27,2025-01-16,1995,8.1,Cloud AI Solutions -AI03269,Computer Vision Engineer,103246,EUR,87759,SE,PT,Austria,S,Austria,50,"Docker, Scala, GCP, AWS",Associate,5,Finance,2024-06-29,2024-08-28,1275,5,Quantum Computing Inc -AI03270,AI Research Scientist,32356,USD,32356,EN,CT,China,S,Estonia,100,"MLOps, R, Hadoop, SQL",PhD,0,Government,2025-01-11,2025-02-08,804,5.2,DeepTech Ventures -AI03271,AI Product Manager,48264,USD,48264,SE,FL,China,S,Hungary,0,"MLOps, PyTorch, Tableau, Data Visualization",Associate,7,Education,2024-08-02,2024-09-27,602,7.5,Neural Networks Co -AI03272,Research Scientist,66275,JPY,7290250,EN,PT,Japan,S,Japan,50,"Python, Tableau, SQL, MLOps",Master,1,Manufacturing,2024-10-01,2024-10-28,1057,7.8,Cloud AI Solutions -AI03273,Machine Learning Researcher,177406,JPY,19514660,EX,FT,Japan,L,Mexico,50,"Hadoop, Spark, Kubernetes",Master,14,Consulting,2024-09-12,2024-10-22,1985,8.4,Algorithmic Solutions -AI03274,Deep Learning Engineer,68779,USD,68779,EN,PT,United States,M,Poland,50,"Python, Git, NLP, Mathematics",PhD,0,Automotive,2024-05-24,2024-06-13,1842,9.1,Predictive Systems -AI03275,Robotics Engineer,93037,EUR,79081,MI,CT,France,M,France,0,"Git, Azure, Computer Vision, Python",PhD,2,Finance,2025-02-20,2025-03-23,1043,5.9,Cognitive Computing -AI03276,AI Product Manager,90694,CAD,113368,SE,CT,Canada,S,Canada,50,"R, Hadoop, Computer Vision, TensorFlow",Associate,8,Manufacturing,2024-12-30,2025-03-09,951,6.9,Quantum Computing Inc -AI03277,Autonomous Systems Engineer,197861,USD,197861,EX,FL,Israel,L,Malaysia,50,"Hadoop, MLOps, TensorFlow",Associate,17,Manufacturing,2025-03-25,2025-05-28,2052,7.2,DataVision Ltd -AI03278,AI Research Scientist,68932,USD,68932,MI,PT,South Korea,M,Chile,0,"Azure, Python, Linux",Master,2,Finance,2024-09-10,2024-10-02,2382,9.7,Quantum Computing Inc -AI03279,AI Software Engineer,83285,EUR,70792,MI,CT,France,M,France,100,"Data Visualization, SQL, R, NLP",Master,2,Media,2024-11-07,2024-12-02,886,9.7,Neural Networks Co -AI03280,NLP Engineer,161470,USD,161470,SE,CT,Israel,L,Israel,0,"Data Visualization, Kubernetes, Computer Vision",PhD,6,Retail,2025-01-18,2025-02-27,1896,9.2,Autonomous Tech -AI03281,NLP Engineer,101298,USD,101298,EN,FT,Norway,M,Norway,50,"NLP, GCP, Scala",Master,1,Technology,2024-12-27,2025-02-18,1133,9.3,Machine Intelligence Group -AI03282,AI Software Engineer,98441,USD,98441,MI,PT,United States,M,United States,0,"Mathematics, Java, Scala, Docker",PhD,2,Finance,2024-03-04,2024-05-15,1689,8.7,Digital Transformation LLC -AI03283,Principal Data Scientist,142540,USD,142540,SE,FT,South Korea,L,Czech Republic,0,"R, PyTorch, Linux, Mathematics",Master,6,Telecommunications,2024-07-19,2024-09-29,1555,8.7,Autonomous Tech -AI03284,Machine Learning Researcher,141976,USD,141976,SE,FT,Israel,M,Indonesia,50,"Git, Kubernetes, PyTorch",PhD,9,Telecommunications,2024-09-14,2024-10-29,2038,9.2,DeepTech Ventures -AI03285,Robotics Engineer,56123,USD,56123,EN,PT,Finland,M,Finland,50,"GCP, Python, AWS",Master,1,Manufacturing,2024-02-15,2024-04-28,503,5.1,Algorithmic Solutions -AI03286,NLP Engineer,93288,EUR,79295,MI,PT,Germany,L,Germany,0,"Statistics, Scala, Mathematics, Kubernetes",Bachelor,4,Gaming,2024-07-22,2024-08-28,2014,7.3,Machine Intelligence Group -AI03287,AI Consultant,111008,USD,111008,MI,FT,United States,S,United States,100,"Azure, R, Mathematics, NLP",Master,4,Consulting,2024-10-27,2024-12-20,2364,8.4,Smart Analytics -AI03288,NLP Engineer,188040,SGD,244452,EX,FT,Singapore,S,Singapore,0,"Scala, Git, SQL, Java, Mathematics",Associate,11,Transportation,2024-06-25,2024-08-12,2155,7.7,DataVision Ltd -AI03289,Computer Vision Engineer,37867,USD,37867,MI,PT,China,S,China,0,"Git, Statistics, Scala",PhD,4,Real Estate,2024-01-08,2024-02-04,2351,8.9,Predictive Systems -AI03290,AI Research Scientist,130573,USD,130573,EX,PT,Israel,S,India,100,"SQL, AWS, Python",Master,18,Finance,2024-02-02,2024-03-05,1006,5.4,Advanced Robotics -AI03291,AI Product Manager,84549,EUR,71867,EN,FL,Austria,L,Austria,50,"Linux, Mathematics, MLOps, Java, PyTorch",PhD,0,Transportation,2024-03-08,2024-04-22,1947,9.8,DataVision Ltd -AI03292,AI Specialist,115767,USD,115767,EN,PT,Denmark,L,Denmark,50,"PyTorch, Python, Linux, Mathematics",PhD,1,Gaming,2025-01-23,2025-03-25,2233,5.3,Autonomous Tech -AI03293,AI Consultant,229034,CHF,206131,SE,FL,Switzerland,L,Malaysia,50,"R, Statistics, Data Visualization, Deep Learning",PhD,5,Gaming,2024-02-08,2024-04-08,1422,9.4,DeepTech Ventures -AI03294,AI Research Scientist,128520,SGD,167076,SE,PT,Singapore,S,Singapore,0,"Scala, TensorFlow, Kubernetes, Docker, Mathematics",Master,6,Media,2024-12-27,2025-01-23,1971,6.5,AI Innovations -AI03295,Data Analyst,73935,EUR,62845,EN,FT,Netherlands,S,Netherlands,100,"Spark, PyTorch, Java, GCP",Associate,0,Government,2024-03-18,2024-04-10,806,8.6,Machine Intelligence Group -AI03296,AI Product Manager,113864,USD,113864,SE,FT,Ireland,S,Kenya,50,"R, Hadoop, SQL, Data Visualization",Master,6,Finance,2025-04-21,2025-06-25,859,5.3,Predictive Systems -AI03297,Computer Vision Engineer,98526,SGD,128084,SE,PT,Singapore,S,Singapore,50,"Azure, PyTorch, NLP",Associate,7,Manufacturing,2024-06-20,2024-08-21,974,8,Autonomous Tech -AI03298,Deep Learning Engineer,66726,USD,66726,EN,PT,Finland,M,Finland,100,"Docker, Computer Vision, Python, Spark",Bachelor,0,Real Estate,2024-06-17,2024-07-10,1308,7.8,Cloud AI Solutions -AI03299,Data Analyst,88638,AUD,119661,EN,CT,Australia,L,Sweden,100,"Mathematics, Deep Learning, Python, Java, TensorFlow",Master,1,Healthcare,2025-03-29,2025-06-03,835,7.6,DataVision Ltd -AI03300,Autonomous Systems Engineer,93012,USD,93012,MI,PT,United States,S,United States,50,"Kubernetes, Deep Learning, Git",PhD,3,Finance,2024-12-07,2024-12-21,1664,9.8,Cloud AI Solutions -AI03301,Computer Vision Engineer,78878,USD,78878,EN,FL,Denmark,L,Canada,50,"Scala, GCP, MLOps, Linux, Spark",Associate,0,Consulting,2025-01-17,2025-03-27,1459,9.1,Advanced Robotics -AI03302,NLP Engineer,82710,JPY,9098100,EN,FT,Japan,M,Japan,0,"Linux, Computer Vision, Tableau, NLP",Master,0,Gaming,2024-06-03,2024-07-20,1488,6.3,DeepTech Ventures -AI03303,Machine Learning Engineer,29961,USD,29961,EN,FT,China,S,Canada,100,"Data Visualization, Python, Kubernetes",Bachelor,1,Real Estate,2025-01-20,2025-02-15,1613,6.1,Future Systems -AI03304,NLP Engineer,273589,USD,273589,EX,FL,Denmark,M,Denmark,100,"R, Spark, GCP, Azure",PhD,11,Real Estate,2025-02-21,2025-04-11,763,7.4,Cognitive Computing -AI03305,AI Consultant,73518,JPY,8086980,EN,FL,Japan,M,Japan,0,"Data Visualization, NLP, AWS, Spark, Computer Vision",PhD,1,Real Estate,2024-11-14,2024-11-30,1298,7.4,AI Innovations -AI03306,Autonomous Systems Engineer,62379,JPY,6861690,EN,FT,Japan,L,Japan,50,"Deep Learning, Python, TensorFlow",Bachelor,1,Retail,2024-02-21,2024-03-26,1088,6,Autonomous Tech -AI03307,Data Analyst,73138,USD,73138,EX,CT,India,L,India,100,"PyTorch, GCP, MLOps, R, Deep Learning",Master,19,Real Estate,2024-01-14,2024-02-28,1574,9.4,Cloud AI Solutions -AI03308,Data Engineer,308012,EUR,261810,EX,FT,Netherlands,L,Israel,0,"Statistics, Spark, SQL, PyTorch, GCP",PhD,19,Automotive,2024-10-26,2024-11-29,852,8.5,Predictive Systems -AI03309,Robotics Engineer,72475,USD,72475,EN,FT,Israel,M,Israel,0,"Linux, TensorFlow, Python, Scala",Master,1,Retail,2024-11-04,2025-01-04,2425,8.7,Autonomous Tech -AI03310,Research Scientist,71202,USD,71202,EN,CT,Norway,S,Norway,0,"Hadoop, MLOps, Git, Linux, NLP",Master,0,Automotive,2025-02-02,2025-02-23,2495,7.8,Predictive Systems -AI03311,AI Research Scientist,178194,EUR,151465,EX,FT,Netherlands,M,Netherlands,100,"Deep Learning, Git, R",Associate,15,Retail,2024-07-18,2024-08-21,2376,7.5,DeepTech Ventures -AI03312,AI Consultant,26837,USD,26837,EN,CT,India,M,India,0,"PyTorch, SQL, Scala",Bachelor,0,Healthcare,2024-01-27,2024-03-06,1504,7.4,Advanced Robotics -AI03313,Principal Data Scientist,97019,USD,97019,MI,FL,Finland,M,Estonia,50,"NLP, Spark, Scala, Git",Bachelor,4,Retail,2025-02-11,2025-04-25,1089,6.5,DataVision Ltd -AI03314,Robotics Engineer,118655,EUR,100857,SE,FT,France,L,Czech Republic,0,"Computer Vision, Tableau, Scala",Bachelor,7,Consulting,2025-02-23,2025-03-27,822,7.4,Machine Intelligence Group -AI03315,AI Specialist,84059,JPY,9246490,MI,FT,Japan,S,Japan,100,"SQL, Docker, Mathematics, GCP",PhD,2,Healthcare,2025-04-04,2025-06-06,2331,5.4,Quantum Computing Inc -AI03316,AI Consultant,205243,CAD,256554,EX,FL,Canada,M,Poland,50,"Java, Tableau, Statistics, Mathematics",Master,11,Education,2025-03-12,2025-05-18,1170,8.7,Digital Transformation LLC -AI03317,AI Research Scientist,65453,USD,65453,MI,PT,Israel,S,Romania,50,"Python, PyTorch, GCP, Java, Deep Learning",PhD,4,Transportation,2024-02-06,2024-03-25,818,8.8,Neural Networks Co -AI03318,Computer Vision Engineer,103929,USD,103929,SE,CT,South Korea,M,South Korea,0,"Data Visualization, Python, Linux, Mathematics",Bachelor,9,Transportation,2024-01-12,2024-01-27,996,6.4,Smart Analytics -AI03319,Head of AI,83770,JPY,9214700,MI,PT,Japan,M,Russia,0,"Kubernetes, NLP, PyTorch",Master,3,Telecommunications,2025-01-31,2025-03-12,1521,6.7,AI Innovations -AI03320,AI Software Engineer,71511,EUR,60784,EN,FL,Germany,M,Germany,50,"Mathematics, R, Java, Git, Linux",Bachelor,1,Government,2024-01-24,2024-04-05,2237,5.2,Smart Analytics -AI03321,Robotics Engineer,86602,USD,86602,MI,FT,Sweden,S,Egypt,100,"PyTorch, TensorFlow, Data Visualization",Master,4,Government,2024-06-10,2024-08-21,1231,6.9,TechCorp Inc -AI03322,AI Consultant,57477,SGD,74720,EN,CT,Singapore,S,Singapore,50,"Python, Hadoop, MLOps, Deep Learning",Master,1,Finance,2024-05-20,2024-06-21,665,6.8,Neural Networks Co -AI03323,Machine Learning Engineer,104741,JPY,11521510,MI,FT,Japan,M,Japan,50,"Docker, Python, Computer Vision, Scala",PhD,4,Technology,2024-08-10,2024-09-12,595,6.6,DataVision Ltd -AI03324,Computer Vision Engineer,257714,USD,257714,EX,FT,Denmark,S,Denmark,100,"Python, Docker, Spark, Azure, Linux",Master,12,Finance,2024-07-22,2024-08-20,1875,5.9,Advanced Robotics -AI03325,Data Engineer,67170,JPY,7388700,EN,FL,Japan,S,Japan,100,"Kubernetes, Scala, NLP, Deep Learning",Bachelor,0,Retail,2024-10-22,2024-12-21,2375,6.8,Advanced Robotics -AI03326,Machine Learning Engineer,145681,EUR,123829,SE,PT,Austria,L,Austria,0,"TensorFlow, Computer Vision, Data Visualization",Associate,5,Consulting,2024-01-20,2024-03-29,808,7.1,DeepTech Ventures -AI03327,AI Specialist,118285,EUR,100542,MI,PT,Austria,L,Ireland,50,"Statistics, Scala, Data Visualization, Spark, Java",Bachelor,2,Government,2025-04-14,2025-05-07,1534,5.3,Cognitive Computing -AI03328,Principal Data Scientist,151221,USD,151221,SE,FL,United States,M,United States,0,"PyTorch, Scala, Hadoop, GCP",Master,6,Technology,2024-07-18,2024-08-17,638,8.6,Machine Intelligence Group -AI03329,Robotics Engineer,97110,CHF,87399,EN,FT,Switzerland,L,Switzerland,50,"Python, GCP, Mathematics",PhD,0,Healthcare,2024-04-25,2024-07-04,825,8.7,Cloud AI Solutions -AI03330,Research Scientist,142010,USD,142010,SE,CT,Israel,L,Israel,0,"Spark, Mathematics, Data Visualization, PyTorch, MLOps",Associate,9,Technology,2024-06-01,2024-07-18,590,5.7,Cloud AI Solutions -AI03331,AI Product Manager,221988,EUR,188690,EX,FT,Netherlands,S,Philippines,100,"Kubernetes, Data Visualization, Git, SQL",Associate,13,Technology,2025-02-15,2025-03-07,2002,9.2,DataVision Ltd -AI03332,AI Consultant,171046,USD,171046,EX,CT,United States,S,United States,100,"PyTorch, AWS, MLOps, Docker",PhD,13,Government,2024-10-09,2024-11-06,1843,6.9,Cloud AI Solutions -AI03333,Research Scientist,71257,USD,71257,EN,FT,South Korea,L,Kenya,50,"Data Visualization, AWS, Tableau, SQL",PhD,0,Technology,2025-02-17,2025-03-07,2459,8.3,TechCorp Inc -AI03334,ML Ops Engineer,109428,USD,109428,SE,PT,Ireland,S,Ireland,0,"Scala, SQL, NLP, Mathematics",Bachelor,5,Healthcare,2024-12-13,2024-12-29,2367,6.1,Smart Analytics -AI03335,Autonomous Systems Engineer,221626,AUD,299195,EX,CT,Australia,M,Romania,100,"Kubernetes, GCP, Data Visualization",Bachelor,13,Healthcare,2024-10-18,2024-11-24,1179,7.6,Machine Intelligence Group -AI03336,Deep Learning Engineer,189458,GBP,142094,EX,CT,United Kingdom,S,Portugal,0,"PyTorch, Spark, SQL, Hadoop, Mathematics",Master,10,Energy,2024-04-14,2024-05-09,1518,5.1,Smart Analytics -AI03337,Principal Data Scientist,200620,CHF,180558,EX,PT,Switzerland,M,Australia,50,"Computer Vision, AWS, Python, TensorFlow",PhD,17,Energy,2024-04-30,2024-07-01,1920,5.4,Machine Intelligence Group -AI03338,AI Specialist,205234,CAD,256543,EX,FT,Canada,S,Canada,50,"Hadoop, Azure, NLP",Bachelor,18,Energy,2024-12-23,2025-02-24,809,7.8,Neural Networks Co -AI03339,Research Scientist,247132,USD,247132,EX,PT,Israel,L,Israel,50,"Python, Kubernetes, SQL",PhD,10,Government,2024-04-21,2024-06-01,673,9.4,TechCorp Inc -AI03340,Deep Learning Engineer,97358,USD,97358,EN,CT,Norway,M,Canada,50,"PyTorch, AWS, Azure, Git, TensorFlow",Master,0,Telecommunications,2024-05-14,2024-07-06,1847,7.1,Quantum Computing Inc -AI03341,Head of AI,57152,SGD,74298,EN,FL,Singapore,M,Singapore,0,"Statistics, Git, Data Visualization",Master,0,Automotive,2024-01-15,2024-03-25,1629,9,Smart Analytics -AI03342,Data Engineer,103950,EUR,88358,SE,PT,France,M,France,100,"Spark, Hadoop, NLP",Master,8,Consulting,2024-06-12,2024-07-25,1220,7.7,Future Systems -AI03343,Principal Data Scientist,112737,AUD,152195,SE,FL,Australia,S,Australia,0,"NLP, Scala, Mathematics, Java, SQL",Bachelor,5,Transportation,2024-08-17,2024-10-12,820,9.9,Neural Networks Co -AI03344,AI Product Manager,81647,JPY,8981170,EN,PT,Japan,L,Denmark,50,"GCP, Tableau, SQL, Computer Vision, Azure",Master,1,Media,2025-03-15,2025-05-10,2037,9,Predictive Systems -AI03345,Autonomous Systems Engineer,80194,USD,80194,MI,PT,Finland,M,Finland,100,"Python, GCP, Statistics",Associate,3,Automotive,2024-06-29,2024-08-07,1331,6.4,Algorithmic Solutions -AI03346,Machine Learning Researcher,50217,USD,50217,SE,FT,India,L,India,0,"Scala, TensorFlow, Tableau",Master,7,Energy,2025-01-29,2025-03-25,677,8.8,Neural Networks Co -AI03347,AI Consultant,242187,SGD,314843,EX,FL,Singapore,S,Netherlands,100,"Statistics, Tableau, PyTorch, NLP",Bachelor,10,Healthcare,2025-03-11,2025-04-12,2106,5.2,Autonomous Tech -AI03348,Head of AI,140261,USD,140261,SE,FL,Norway,M,Norway,100,"Linux, TensorFlow, SQL, Deep Learning, Java",Bachelor,6,Manufacturing,2024-09-02,2024-10-27,640,8.4,Advanced Robotics -AI03349,Data Engineer,92105,USD,92105,MI,FT,Finland,S,Austria,50,"AWS, Hadoop, Spark, NLP, Git",PhD,4,Transportation,2024-12-18,2025-02-17,1207,9,Digital Transformation LLC -AI03350,Research Scientist,123667,USD,123667,SE,PT,Ireland,M,China,50,"PyTorch, Statistics, Azure",PhD,6,Energy,2024-05-21,2024-06-13,1651,9.9,Machine Intelligence Group -AI03351,Machine Learning Engineer,93495,USD,93495,MI,PT,United States,S,United States,0,"TensorFlow, Kubernetes, Hadoop, Azure, Scala",Bachelor,3,Telecommunications,2024-11-14,2025-01-18,1663,6.5,Digital Transformation LLC -AI03352,Research Scientist,164403,AUD,221944,EX,FT,Australia,L,Australia,0,"Python, Git, TensorFlow, Hadoop, Mathematics",Bachelor,14,Government,2025-01-26,2025-03-26,1244,6.3,AI Innovations -AI03353,Deep Learning Engineer,161726,GBP,121295,SE,PT,United Kingdom,M,Indonesia,50,"AWS, Python, Tableau, R",Bachelor,8,Manufacturing,2025-03-03,2025-03-26,1141,8.1,Advanced Robotics -AI03354,Data Engineer,65395,AUD,88283,EN,CT,Australia,S,Australia,100,"PyTorch, Statistics, SQL, AWS",Bachelor,0,Transportation,2025-02-12,2025-04-20,2277,5.7,DeepTech Ventures -AI03355,Research Scientist,163112,USD,163112,SE,PT,Finland,L,Finland,50,"Python, Linux, Java, R",PhD,8,Telecommunications,2024-06-08,2024-08-02,1351,5.6,Autonomous Tech -AI03356,NLP Engineer,120372,USD,120372,SE,PT,Sweden,S,Sweden,0,"Spark, MLOps, Deep Learning",Associate,7,Real Estate,2024-12-27,2025-03-07,1014,5.1,Smart Analytics -AI03357,AI Consultant,80130,USD,80130,EN,FT,Denmark,L,Denmark,100,"SQL, PyTorch, R",Associate,1,Gaming,2024-12-27,2025-02-28,2374,7.3,Advanced Robotics -AI03358,Deep Learning Engineer,69483,USD,69483,SE,CT,China,L,China,50,"Python, R, GCP, Docker",Master,6,Technology,2024-07-26,2024-08-19,733,6.5,Digital Transformation LLC -AI03359,AI Specialist,275292,USD,275292,EX,FL,Denmark,M,Denmark,50,"Git, PyTorch, MLOps, Spark, Kubernetes",Master,16,Government,2024-03-12,2024-03-28,572,9.9,Machine Intelligence Group -AI03360,Data Analyst,90173,EUR,76647,MI,CT,Germany,L,Germany,50,"Linux, Scala, Mathematics, AWS, SQL",Bachelor,4,Technology,2024-11-25,2025-01-29,1158,7.8,Quantum Computing Inc -AI03361,AI Consultant,115690,JPY,12725900,MI,CT,Japan,L,Latvia,100,"Spark, Scala, Tableau, SQL",Master,3,Automotive,2024-11-25,2025-02-05,2463,9.8,Neural Networks Co -AI03362,Machine Learning Engineer,52110,USD,52110,EN,CT,Sweden,M,Luxembourg,100,"Mathematics, Scala, Python, Kubernetes",Associate,0,Energy,2024-06-01,2024-08-07,838,5.6,Cloud AI Solutions -AI03363,Deep Learning Engineer,163804,USD,163804,SE,CT,Norway,M,Estonia,100,"R, Java, Azure, Mathematics, NLP",PhD,7,Energy,2024-04-24,2024-06-25,2440,8.9,AI Innovations -AI03364,Machine Learning Researcher,173688,EUR,147635,SE,PT,Netherlands,L,Netherlands,100,"R, Linux, Git",Associate,6,Media,2024-09-05,2024-10-08,2247,8.2,Autonomous Tech -AI03365,Machine Learning Researcher,244135,AUD,329582,EX,PT,Australia,M,Australia,100,"Linux, SQL, Git, Data Visualization",Master,17,Automotive,2024-12-24,2025-01-16,2027,7.7,Machine Intelligence Group -AI03366,Research Scientist,177041,USD,177041,EX,CT,Finland,S,Estonia,100,"Azure, R, Tableau, Hadoop",Associate,12,Transportation,2024-05-06,2024-05-30,959,7.9,Neural Networks Co -AI03367,Head of AI,113070,CHF,101763,MI,FL,Switzerland,M,Poland,0,"R, Kubernetes, Tableau",PhD,4,Technology,2024-09-10,2024-11-15,1787,8.8,DeepTech Ventures -AI03368,Machine Learning Engineer,34381,USD,34381,SE,CT,India,S,India,0,"Hadoop, Python, Statistics, Linux, AWS",PhD,6,Retail,2025-02-28,2025-03-20,2339,5.2,Machine Intelligence Group -AI03369,AI Architect,102804,USD,102804,EX,FL,China,M,China,100,"Computer Vision, Azure, MLOps, NLP",PhD,11,Government,2024-09-17,2024-11-15,1482,5.7,TechCorp Inc -AI03370,AI Architect,124994,EUR,106245,SE,CT,Netherlands,L,Ukraine,50,"Python, Spark, Tableau",Associate,9,Manufacturing,2024-03-11,2024-05-17,867,7.6,Neural Networks Co -AI03371,Autonomous Systems Engineer,48674,USD,48674,SE,FT,India,M,Ukraine,100,"Scala, NLP, TensorFlow, Java, Git",Associate,9,Technology,2025-02-14,2025-03-07,2390,8.8,DataVision Ltd -AI03372,Autonomous Systems Engineer,83060,GBP,62295,EN,FT,United Kingdom,M,United Kingdom,50,"Scala, Hadoop, Azure, Java",Associate,0,Manufacturing,2025-04-08,2025-04-26,920,5.2,Algorithmic Solutions -AI03373,Computer Vision Engineer,116877,SGD,151940,MI,PT,Singapore,L,Singapore,0,"Mathematics, Spark, PyTorch, Java, SQL",Master,2,Healthcare,2024-12-22,2025-02-21,1090,9.4,AI Innovations -AI03374,AI Consultant,49966,USD,49966,SE,CT,India,M,India,100,"AWS, Git, NLP, Spark",Associate,5,Consulting,2024-10-23,2024-12-03,2239,5.7,DataVision Ltd -AI03375,Machine Learning Engineer,109823,USD,109823,SE,CT,Ireland,S,France,0,"Azure, Linux, Data Visualization, Tableau",Associate,7,Real Estate,2024-09-09,2024-09-27,590,6.4,Digital Transformation LLC -AI03376,Computer Vision Engineer,89964,EUR,76469,MI,CT,Netherlands,M,Romania,100,"Java, GCP, Mathematics",Master,2,Energy,2024-03-26,2024-04-28,1914,7.8,Cloud AI Solutions -AI03377,NLP Engineer,99897,CHF,89907,EN,CT,Switzerland,S,Switzerland,0,"Tableau, SQL, Linux",Associate,1,Energy,2025-02-17,2025-04-16,501,5.5,TechCorp Inc -AI03378,AI Product Manager,112037,CHF,100833,EN,FT,Switzerland,M,Switzerland,0,"AWS, SQL, R, Computer Vision",Associate,1,Telecommunications,2024-02-13,2024-04-04,1799,5.3,DataVision Ltd -AI03379,Robotics Engineer,97555,USD,97555,MI,FL,Sweden,S,Ireland,0,"Deep Learning, AWS, Mathematics, Python",Bachelor,3,Education,2024-07-18,2024-08-05,1520,9.7,Autonomous Tech -AI03380,Deep Learning Engineer,51067,USD,51067,MI,FT,China,L,China,0,"AWS, Kubernetes, R",Bachelor,2,Real Estate,2024-09-29,2024-11-29,705,8.4,Quantum Computing Inc -AI03381,AI Software Engineer,74645,AUD,100771,EN,PT,Australia,M,Australia,50,"Kubernetes, Python, Data Visualization, Statistics, Deep Learning",Master,1,Government,2024-03-18,2024-05-12,652,8.5,Predictive Systems -AI03382,ML Ops Engineer,73008,JPY,8030880,MI,CT,Japan,S,Japan,50,"Java, Kubernetes, Azure",Master,3,Finance,2024-10-18,2024-12-14,1485,8.2,AI Innovations -AI03383,Autonomous Systems Engineer,31006,USD,31006,EN,FT,China,S,China,100,"Python, Data Visualization, Linux, MLOps",PhD,0,Government,2024-06-08,2024-07-24,1097,9.2,Machine Intelligence Group -AI03384,Data Scientist,101583,USD,101583,SE,PT,South Korea,S,Canada,0,"Python, Scala, Hadoop, AWS",Master,9,Government,2024-07-29,2024-09-02,1325,6.1,Smart Analytics -AI03385,Computer Vision Engineer,90261,USD,90261,MI,CT,Sweden,M,Romania,0,"Tableau, Kubernetes, Scala, AWS, Git",Associate,4,Retail,2024-07-08,2024-07-23,1414,6.5,Future Systems -AI03386,AI Product Manager,111512,GBP,83634,MI,FL,United Kingdom,M,Latvia,0,"Statistics, NLP, Linux, Kubernetes, Hadoop",Bachelor,2,Media,2024-05-26,2024-06-15,1256,6.6,Smart Analytics -AI03387,AI Software Engineer,135059,JPY,14856490,SE,PT,Japan,M,South Africa,0,"PyTorch, Computer Vision, Scala, Azure, Linux",PhD,8,Telecommunications,2024-06-01,2024-08-02,1857,8.1,DataVision Ltd -AI03388,AI Architect,188799,USD,188799,EX,CT,Denmark,S,Denmark,50,"Tableau, Docker, NLP, Kubernetes",Associate,13,Real Estate,2024-03-28,2024-04-14,953,9.3,Autonomous Tech -AI03389,Data Scientist,133225,USD,133225,SE,FL,Ireland,S,Ireland,50,"PyTorch, Spark, Docker",PhD,5,Telecommunications,2024-08-27,2024-09-18,573,7,Smart Analytics -AI03390,Autonomous Systems Engineer,60400,USD,60400,SE,FL,China,S,China,0,"Computer Vision, Git, Python",Bachelor,5,Healthcare,2024-12-11,2025-01-06,1043,5.6,DeepTech Ventures -AI03391,Data Scientist,114422,USD,114422,SE,FT,Ireland,M,Ireland,100,"Azure, Linux, Mathematics, Data Visualization",Bachelor,7,Real Estate,2024-06-22,2024-08-11,2321,5.9,Cognitive Computing -AI03392,Research Scientist,85322,USD,85322,EN,CT,Denmark,S,Denmark,100,"Kubernetes, Scala, Mathematics, Azure",Bachelor,1,Healthcare,2024-10-28,2024-12-19,2265,5.8,AI Innovations -AI03393,Head of AI,64462,EUR,54793,MI,FL,Austria,S,Colombia,0,"Scala, PyTorch, TensorFlow, NLP",Master,4,Gaming,2024-04-17,2024-05-24,640,7.8,DataVision Ltd -AI03394,Deep Learning Engineer,214640,CAD,268300,EX,CT,Canada,M,Canada,100,"PyTorch, Kubernetes, GCP, Statistics, AWS",Bachelor,13,Media,2025-01-01,2025-02-04,708,8.6,Algorithmic Solutions -AI03395,NLP Engineer,160700,USD,160700,EX,FT,Israel,M,Israel,100,"Spark, GCP, Scala",Bachelor,18,Consulting,2025-04-15,2025-05-22,1966,6.4,Digital Transformation LLC -AI03396,Machine Learning Researcher,114986,CAD,143733,SE,CT,Canada,S,Israel,0,"AWS, Kubernetes, Azure",PhD,9,Automotive,2024-05-31,2024-08-05,1103,9.5,Predictive Systems -AI03397,Robotics Engineer,160285,GBP,120214,SE,PT,United Kingdom,M,Ireland,50,"Kubernetes, Computer Vision, Python, Git, Mathematics",Master,9,Technology,2025-01-12,2025-03-09,1719,5.4,Digital Transformation LLC -AI03398,ML Ops Engineer,184764,AUD,249431,EX,FT,Australia,L,Argentina,100,"Kubernetes, Python, Scala, Git, TensorFlow",Master,17,Media,2024-07-16,2024-08-18,2153,5.3,Advanced Robotics -AI03399,Deep Learning Engineer,168868,CHF,151981,MI,FL,Switzerland,L,Switzerland,50,"Kubernetes, Deep Learning, Data Visualization",Bachelor,3,Technology,2025-04-12,2025-06-17,2054,7.7,Neural Networks Co -AI03400,AI Architect,59852,GBP,44889,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Tableau, Linux, Scala, Deep Learning",PhD,1,Manufacturing,2025-01-21,2025-04-02,1905,8.8,Quantum Computing Inc -AI03401,Computer Vision Engineer,127118,EUR,108050,SE,CT,Austria,S,France,100,"Spark, Statistics, AWS, GCP, Scala",PhD,6,Technology,2024-10-16,2024-11-04,610,6.6,Quantum Computing Inc -AI03402,Machine Learning Engineer,62015,USD,62015,EN,FL,Sweden,L,Sweden,50,"GCP, SQL, Deep Learning, Python",PhD,1,Consulting,2024-04-17,2024-05-12,1071,9.3,Future Systems -AI03403,AI Software Engineer,70434,EUR,59869,EN,FL,Austria,L,Austria,50,"Python, Spark, Git, Deep Learning, Tableau",Master,1,Telecommunications,2024-04-18,2024-05-13,2274,6.7,AI Innovations -AI03404,AI Software Engineer,102013,USD,102013,EX,PT,South Korea,S,South Korea,0,"Linux, AWS, R",Associate,17,Transportation,2025-04-06,2025-06-04,2244,7.6,AI Innovations -AI03405,AI Architect,178561,USD,178561,EX,CT,Finland,L,Philippines,50,"Data Visualization, Linux, Git, PyTorch",PhD,19,Education,2024-01-23,2024-03-13,651,8,DeepTech Ventures -AI03406,Head of AI,63698,USD,63698,EN,FL,South Korea,L,Kenya,100,"Linux, Python, TensorFlow, MLOps",Bachelor,0,Automotive,2024-02-15,2024-04-14,1653,6.8,Smart Analytics -AI03407,NLP Engineer,70117,USD,70117,EN,CT,Sweden,M,Ukraine,50,"SQL, Data Visualization, Scala, Computer Vision, Azure",Master,0,Real Estate,2024-10-05,2024-12-03,2200,6,Quantum Computing Inc -AI03408,AI Specialist,125886,USD,125886,SE,CT,Israel,L,Ukraine,0,"PyTorch, MLOps, TensorFlow, SQL, Computer Vision",Associate,5,Automotive,2024-10-15,2024-10-31,923,5.9,AI Innovations -AI03409,Head of AI,143263,EUR,121774,SE,CT,Germany,L,Germany,100,"Data Visualization, NLP, Java, PyTorch",PhD,9,Gaming,2024-06-28,2024-08-03,1811,8.7,Quantum Computing Inc -AI03410,Autonomous Systems Engineer,61495,USD,61495,MI,CT,South Korea,S,South Korea,100,"AWS, Hadoop, Mathematics",PhD,4,Finance,2024-12-27,2025-02-24,2423,8.6,Machine Intelligence Group -AI03411,Robotics Engineer,275523,USD,275523,EX,CT,Norway,S,Netherlands,0,"NLP, Scala, Hadoop, Data Visualization",PhD,17,Technology,2024-08-19,2024-09-16,891,8.9,AI Innovations -AI03412,Data Engineer,65593,EUR,55754,EN,CT,France,M,France,100,"Deep Learning, Data Visualization, PyTorch, Kubernetes, Tableau",Master,1,Telecommunications,2024-02-29,2024-04-26,1617,6.2,DataVision Ltd -AI03413,Robotics Engineer,63298,USD,63298,EN,FT,United States,S,United States,50,"Hadoop, Python, TensorFlow, PyTorch, Statistics",PhD,0,Manufacturing,2025-04-30,2025-06-25,1610,9.9,Predictive Systems -AI03414,AI Software Engineer,70299,EUR,59754,MI,PT,France,M,France,100,"SQL, PyTorch, TensorFlow",Bachelor,2,Energy,2025-01-19,2025-02-16,2016,8.4,Cloud AI Solutions -AI03415,Machine Learning Engineer,202655,SGD,263452,EX,FL,Singapore,M,Singapore,0,"Linux, Hadoop, Git",Bachelor,12,Energy,2024-02-17,2024-03-27,2364,8,Quantum Computing Inc -AI03416,AI Specialist,256495,USD,256495,EX,PT,Norway,L,Norway,0,"Python, TensorFlow, Hadoop, Java",Bachelor,13,Transportation,2024-03-08,2024-04-05,1154,8.7,Neural Networks Co -AI03417,AI Product Manager,84934,AUD,114661,EN,PT,Australia,L,Australia,100,"Spark, Linux, R",Master,0,Energy,2024-10-06,2024-11-06,1062,8.9,Smart Analytics -AI03418,Research Scientist,83381,EUR,70874,MI,FL,Germany,S,Germany,100,"Git, Python, TensorFlow, NLP",Bachelor,3,Real Estate,2024-04-20,2024-06-07,1342,9.7,Algorithmic Solutions -AI03419,Data Analyst,26293,USD,26293,EN,FT,India,M,India,50,"PyTorch, SQL, AWS",Bachelor,1,Technology,2025-03-19,2025-05-12,2348,6.2,DataVision Ltd -AI03420,Head of AI,114838,USD,114838,SE,CT,Sweden,S,Sweden,50,"NLP, Python, Computer Vision, R, Deep Learning",Associate,9,Automotive,2025-01-11,2025-02-14,1472,7.1,Smart Analytics -AI03421,AI Specialist,130423,AUD,176071,SE,PT,Australia,S,Australia,0,"Python, Git, TensorFlow",PhD,9,Automotive,2024-11-09,2024-12-22,1640,8.3,Smart Analytics -AI03422,Head of AI,73362,USD,73362,MI,CT,Israel,S,Romania,0,"Python, Data Visualization, TensorFlow",Associate,4,Energy,2024-04-11,2024-06-13,1395,9.4,Algorithmic Solutions -AI03423,Research Scientist,55846,USD,55846,MI,FL,China,L,Sweden,100,"Tableau, Python, Statistics",Master,2,Media,2024-08-15,2024-09-01,1702,7.3,TechCorp Inc -AI03424,AI Product Manager,216173,USD,216173,EX,FT,South Korea,L,Hungary,50,"Python, Git, TensorFlow, Linux",Associate,17,Automotive,2024-04-19,2024-06-07,2275,8.4,Autonomous Tech -AI03425,Data Engineer,184151,GBP,138113,EX,FT,United Kingdom,M,United Kingdom,0,"Python, Docker, Tableau, GCP",Associate,12,Energy,2024-05-11,2024-06-28,957,8.4,Smart Analytics -AI03426,AI Product Manager,109524,CAD,136905,MI,FL,Canada,L,Canada,0,"PyTorch, Hadoop, MLOps, Kubernetes, Linux",PhD,4,Telecommunications,2024-03-27,2024-05-01,1174,8,AI Innovations -AI03427,Research Scientist,83789,USD,83789,EN,FT,United States,M,Colombia,0,"Python, MLOps, SQL, NLP",PhD,0,Healthcare,2025-01-15,2025-02-13,2307,6.7,Digital Transformation LLC -AI03428,Computer Vision Engineer,163508,USD,163508,EX,PT,South Korea,S,South Korea,0,"Scala, R, Deep Learning, Azure",PhD,17,Energy,2025-02-22,2025-04-15,1992,7.7,Smart Analytics -AI03429,Principal Data Scientist,159674,CHF,143707,MI,CT,Switzerland,L,Switzerland,100,"Scala, SQL, Python, Tableau",Master,2,Retail,2024-05-08,2024-06-06,888,8.1,Autonomous Tech -AI03430,Machine Learning Engineer,72337,USD,72337,EN,FL,Norway,S,Finland,50,"Git, Spark, Docker, TensorFlow, Linux",Master,0,Technology,2024-08-23,2024-10-25,598,9.8,Smart Analytics -AI03431,AI Research Scientist,168105,EUR,142889,EX,CT,Germany,L,Germany,100,"Kubernetes, Scala, Python",PhD,10,Telecommunications,2024-01-12,2024-01-27,1693,8.2,Algorithmic Solutions -AI03432,Data Scientist,157793,USD,157793,SE,PT,United States,L,India,0,"Docker, SQL, Computer Vision, Java",Bachelor,7,Telecommunications,2024-01-20,2024-03-09,2041,8.3,Quantum Computing Inc -AI03433,Machine Learning Engineer,186928,USD,186928,SE,FL,Norway,L,Chile,100,"Computer Vision, Python, Kubernetes, AWS",Master,9,Retail,2024-11-01,2024-11-24,1184,5.4,AI Innovations -AI03434,AI Specialist,97344,USD,97344,MI,PT,Ireland,S,Philippines,0,"Docker, Python, Computer Vision",Bachelor,2,Finance,2024-12-02,2025-01-18,1143,6.9,Cognitive Computing -AI03435,AI Product Manager,47190,EUR,40112,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, GCP, AWS, Deep Learning",Associate,0,Finance,2024-12-16,2025-01-04,539,9.7,Neural Networks Co -AI03436,Data Scientist,64670,CAD,80838,EN,PT,Canada,M,Canada,50,"Git, Azure, SQL, Mathematics",PhD,1,Consulting,2024-10-04,2024-11-24,1319,6.8,Machine Intelligence Group -AI03437,AI Architect,126076,USD,126076,SE,CT,Finland,S,Finland,50,"Data Visualization, Python, Linux, Statistics, TensorFlow",PhD,8,Media,2024-05-14,2024-07-22,2017,9.8,Predictive Systems -AI03438,Principal Data Scientist,98433,AUD,132885,MI,CT,Australia,M,Australia,50,"Linux, PyTorch, AWS, Deep Learning, MLOps",Master,2,Media,2024-02-10,2024-04-15,2422,9,Machine Intelligence Group -AI03439,Robotics Engineer,31915,USD,31915,EN,CT,China,L,China,100,"Statistics, Spark, Kubernetes, R, SQL",Bachelor,0,Gaming,2024-08-31,2024-10-07,1804,9.6,Neural Networks Co -AI03440,Data Scientist,175657,USD,175657,SE,PT,Norway,S,Norway,100,"Data Visualization, Spark, MLOps",Bachelor,5,Government,2024-10-07,2024-11-29,1903,9.8,Digital Transformation LLC -AI03441,Deep Learning Engineer,200463,USD,200463,EX,FL,Israel,M,Israel,0,"Scala, Hadoop, Deep Learning, AWS",PhD,19,Media,2024-10-17,2024-12-16,885,5,Quantum Computing Inc -AI03442,Robotics Engineer,109629,USD,109629,SE,CT,South Korea,S,Poland,100,"MLOps, Kubernetes, GCP",Associate,6,Finance,2024-04-12,2024-05-19,811,6.7,DataVision Ltd -AI03443,NLP Engineer,80126,USD,80126,EN,FT,Finland,L,Australia,100,"AWS, Tableau, Linux, Data Visualization",Master,0,Automotive,2024-01-31,2024-02-14,1963,6.2,Future Systems -AI03444,Machine Learning Engineer,91862,GBP,68897,EN,FT,United Kingdom,L,Malaysia,100,"TensorFlow, NLP, Git",PhD,0,Healthcare,2024-07-10,2024-09-02,2134,6.2,DeepTech Ventures -AI03445,Data Scientist,102655,JPY,11292050,MI,CT,Japan,L,Canada,50,"Kubernetes, R, PyTorch, GCP, Java",Master,4,Retail,2025-01-12,2025-02-01,864,6.5,Cloud AI Solutions -AI03446,Data Scientist,147186,AUD,198701,SE,CT,Australia,M,Chile,50,"TensorFlow, Mathematics, Kubernetes, SQL, Statistics",PhD,5,Telecommunications,2025-04-26,2025-06-18,983,7.4,DataVision Ltd -AI03447,Research Scientist,184149,USD,184149,EX,FT,Ireland,S,Ireland,0,"GCP, SQL, Data Visualization, Mathematics",Bachelor,14,Automotive,2024-03-31,2024-04-26,645,6.8,Digital Transformation LLC -AI03448,Computer Vision Engineer,273048,USD,273048,EX,FL,Norway,M,Germany,50,"Python, Mathematics, Data Visualization, Computer Vision",Master,16,Energy,2024-12-15,2024-12-30,892,6.2,Cloud AI Solutions -AI03449,NLP Engineer,105192,GBP,78894,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, TensorFlow, Hadoop, Linux",Master,2,Media,2024-05-21,2024-06-27,845,5.2,DataVision Ltd -AI03450,Deep Learning Engineer,37406,USD,37406,MI,PT,India,M,India,0,"Git, Java, Linux, Python",Master,4,Education,2024-01-27,2024-03-01,1756,6.8,DataVision Ltd -AI03451,AI Specialist,27619,USD,27619,EN,FT,India,M,India,0,"Tableau, Python, R, Kubernetes",Bachelor,0,Government,2024-08-10,2024-10-11,570,8.8,Smart Analytics -AI03452,Machine Learning Researcher,94921,USD,94921,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Spark, Docker",PhD,8,Media,2024-04-04,2024-06-12,2257,5.4,Quantum Computing Inc -AI03453,Data Scientist,199186,USD,199186,EX,FT,Israel,M,Israel,0,"Docker, Kubernetes, Hadoop, Java",Master,13,Automotive,2024-05-26,2024-07-02,2222,9.8,Neural Networks Co -AI03454,ML Ops Engineer,118265,SGD,153745,SE,PT,Singapore,M,Belgium,50,"Kubernetes, R, PyTorch, Git",PhD,8,Energy,2024-08-31,2024-11-01,1950,7.6,Advanced Robotics -AI03455,Computer Vision Engineer,75240,SGD,97812,EN,CT,Singapore,L,Kenya,100,"Azure, Kubernetes, NLP, Computer Vision",Bachelor,1,Technology,2024-05-15,2024-06-30,826,9.8,AI Innovations -AI03456,Research Scientist,65569,USD,65569,EN,FL,Israel,M,Switzerland,50,"GCP, Java, MLOps",PhD,1,Gaming,2024-04-16,2024-06-20,2302,6.3,Predictive Systems -AI03457,Data Scientist,205247,USD,205247,EX,FL,Denmark,S,Denmark,0,"Docker, Kubernetes, Git, SQL",PhD,17,Real Estate,2024-01-16,2024-03-22,1888,7.3,Digital Transformation LLC -AI03458,Data Scientist,37999,USD,37999,MI,CT,India,L,India,100,"Statistics, GCP, MLOps",PhD,4,Government,2024-12-20,2025-01-20,1159,6.2,Quantum Computing Inc -AI03459,Data Engineer,136750,JPY,15042500,SE,CT,Japan,M,Japan,100,"Tableau, Linux, TensorFlow, MLOps",Associate,7,Consulting,2024-03-17,2024-04-10,939,6.6,Neural Networks Co -AI03460,AI Product Manager,55482,USD,55482,EN,FL,Finland,M,Finland,100,"Python, Data Visualization, TensorFlow, Deep Learning",Associate,1,Consulting,2025-02-28,2025-04-05,2469,7.1,DeepTech Ventures -AI03461,Principal Data Scientist,126580,AUD,170883,MI,CT,Australia,L,Australia,0,"Data Visualization, GCP, Computer Vision, Kubernetes",Bachelor,2,Consulting,2025-04-24,2025-06-07,1369,5.4,AI Innovations -AI03462,Deep Learning Engineer,45523,USD,45523,MI,PT,China,L,Switzerland,0,"Spark, GCP, Hadoop, SQL",PhD,2,Retail,2024-08-11,2024-10-17,733,7.2,Future Systems -AI03463,Computer Vision Engineer,69117,USD,69117,MI,PT,Finland,S,New Zealand,0,"Deep Learning, AWS, Docker",Master,4,Finance,2025-03-02,2025-03-30,1948,9.6,Algorithmic Solutions -AI03464,Robotics Engineer,147154,USD,147154,MI,PT,United States,L,United States,0,"MLOps, Scala, SQL, PyTorch, NLP",Master,3,Education,2025-03-07,2025-04-23,1786,8.8,Advanced Robotics -AI03465,Computer Vision Engineer,129411,EUR,109999,SE,CT,Germany,M,Germany,0,"Azure, SQL, NLP, Deep Learning",Associate,6,Retail,2024-04-02,2024-04-25,2001,7.2,Cloud AI Solutions -AI03466,NLP Engineer,103365,AUD,139543,SE,CT,Australia,S,Australia,0,"Hadoop, Statistics, GCP, MLOps, Spark",PhD,7,Education,2024-07-17,2024-09-21,1363,7.2,TechCorp Inc -AI03467,Machine Learning Researcher,155656,USD,155656,SE,FL,United States,L,United States,50,"Deep Learning, R, PyTorch, Docker, Linux",Master,8,Transportation,2025-02-23,2025-03-28,2452,7.1,Cloud AI Solutions -AI03468,Deep Learning Engineer,60372,EUR,51316,EN,PT,Netherlands,M,Netherlands,100,"SQL, GCP, Java",Bachelor,1,Gaming,2024-01-14,2024-02-19,1363,7.7,TechCorp Inc -AI03469,Machine Learning Engineer,90624,EUR,77030,SE,FT,Austria,S,Spain,50,"GCP, Hadoop, PyTorch",Associate,8,Retail,2025-02-24,2025-04-08,655,8.9,Autonomous Tech -AI03470,Principal Data Scientist,28839,USD,28839,EN,CT,China,S,Estonia,50,"Scala, Python, SQL",Master,1,Real Estate,2024-08-20,2024-10-18,1826,10,Cognitive Computing -AI03471,Data Analyst,95397,EUR,81087,MI,FT,Germany,S,Germany,50,"Deep Learning, R, Spark",Bachelor,3,Healthcare,2024-02-06,2024-02-21,705,5.3,DataVision Ltd -AI03472,ML Ops Engineer,265922,JPY,29251420,EX,CT,Japan,L,United States,0,"GCP, Tableau, AWS, SQL",Associate,16,Energy,2024-03-16,2024-05-01,1345,5.6,Predictive Systems -AI03473,NLP Engineer,123952,CHF,111557,MI,CT,Switzerland,M,Switzerland,50,"PyTorch, Java, Git, Computer Vision",Bachelor,2,Automotive,2024-05-14,2024-06-20,713,8.8,Cloud AI Solutions -AI03474,Data Scientist,243390,EUR,206882,EX,FT,Germany,M,Indonesia,100,"Linux, PyTorch, Tableau, Java, Git",Bachelor,12,Automotive,2024-12-01,2024-12-31,1715,9,Cognitive Computing -AI03475,Autonomous Systems Engineer,86886,JPY,9557460,MI,FT,Japan,M,Poland,100,"Kubernetes, Tableau, Azure, NLP, Python",Associate,2,Energy,2024-12-23,2025-02-26,1947,8.7,Machine Intelligence Group -AI03476,Machine Learning Researcher,86470,CHF,77823,EN,FT,Switzerland,S,Switzerland,0,"Python, Java, GCP, NLP",PhD,1,Education,2024-11-30,2024-12-14,1713,6.3,Cloud AI Solutions -AI03477,Principal Data Scientist,128696,EUR,109392,SE,PT,France,L,Malaysia,0,"Git, Linux, Data Visualization, PyTorch",Associate,6,Energy,2024-10-05,2024-11-14,1015,6.2,Autonomous Tech -AI03478,Data Analyst,108456,USD,108456,MI,CT,United States,L,United States,0,"TensorFlow, Deep Learning, Kubernetes, Python",Bachelor,2,Retail,2024-05-19,2024-07-04,1400,5.5,Machine Intelligence Group -AI03479,Data Engineer,114242,USD,114242,SE,FT,Ireland,M,Ireland,0,"Statistics, R, Scala",Master,9,Retail,2024-08-03,2024-09-22,2189,6.4,Smart Analytics -AI03480,Data Engineer,94224,USD,94224,MI,CT,Finland,L,Finland,0,"Spark, Scala, Computer Vision, Mathematics",PhD,2,Technology,2024-10-10,2024-12-14,540,9.2,TechCorp Inc -AI03481,Data Engineer,277483,SGD,360728,EX,FL,Singapore,L,Singapore,50,"MLOps, Spark, Data Visualization, Hadoop",Bachelor,19,Finance,2024-07-30,2024-09-09,770,9.7,Cognitive Computing -AI03482,Computer Vision Engineer,40704,USD,40704,MI,FT,China,M,China,50,"NLP, PyTorch, Tableau, Git, Docker",PhD,2,Media,2024-03-06,2024-05-10,795,6.8,TechCorp Inc -AI03483,Machine Learning Engineer,93238,EUR,79252,EN,CT,Netherlands,L,Portugal,100,"AWS, Statistics, Hadoop",PhD,1,Finance,2024-03-20,2024-05-24,2049,7.8,DeepTech Ventures -AI03484,Machine Learning Researcher,196588,CHF,176929,SE,FT,Switzerland,M,Estonia,0,"Data Visualization, Docker, R",Associate,9,Energy,2024-07-03,2024-09-04,1947,7.5,Autonomous Tech -AI03485,AI Software Engineer,90440,GBP,67830,MI,PT,United Kingdom,M,United Kingdom,50,"PyTorch, AWS, Computer Vision, NLP, GCP",Master,2,Energy,2025-03-19,2025-04-30,2326,6.6,Neural Networks Co -AI03486,AI Consultant,150604,USD,150604,MI,FT,Denmark,L,India,100,"Hadoop, Mathematics, GCP, Kubernetes, MLOps",Associate,2,Gaming,2024-09-03,2024-09-26,762,6.4,Advanced Robotics -AI03487,ML Ops Engineer,58876,USD,58876,SE,PT,India,L,India,0,"MLOps, GCP, SQL",Master,8,Government,2024-11-02,2025-01-02,730,6.3,AI Innovations -AI03488,AI Product Manager,28266,USD,28266,MI,CT,India,S,India,100,"NLP, Data Visualization, Tableau, Mathematics, MLOps",Master,2,Telecommunications,2025-01-26,2025-03-18,901,9.2,TechCorp Inc -AI03489,Research Scientist,83652,CAD,104565,MI,FL,Canada,M,Nigeria,100,"Azure, Tableau, Linux, AWS, Docker",Master,3,Energy,2025-02-01,2025-03-14,2027,6,AI Innovations -AI03490,AI Specialist,69368,USD,69368,EN,FT,Norway,S,Israel,50,"Spark, Python, Git, Azure",Associate,1,Manufacturing,2024-05-16,2024-06-08,1302,7.8,Autonomous Tech -AI03491,Head of AI,130656,USD,130656,SE,PT,Israel,L,Israel,50,"SQL, Mathematics, TensorFlow",PhD,9,Government,2025-02-21,2025-04-01,1038,5.4,Autonomous Tech -AI03492,AI Architect,168459,EUR,143190,SE,PT,Germany,L,Germany,0,"Spark, Hadoop, Scala, MLOps, R",Associate,6,Telecommunications,2024-04-07,2024-04-22,2246,7.9,Advanced Robotics -AI03493,Data Scientist,72394,AUD,97732,MI,CT,Australia,S,Ghana,100,"Deep Learning, GCP, SQL, Python",Master,4,Technology,2024-08-06,2024-08-28,882,6.4,Predictive Systems -AI03494,Principal Data Scientist,37641,USD,37641,MI,FL,India,M,India,0,"Python, Hadoop, SQL, Git, AWS",Master,2,Technology,2025-01-16,2025-03-08,897,5.7,Smart Analytics -AI03495,Deep Learning Engineer,109311,USD,109311,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Hadoop, Python, Linux",Bachelor,2,Government,2024-09-13,2024-11-21,2222,6.1,Algorithmic Solutions -AI03496,Machine Learning Engineer,237727,USD,237727,EX,FL,Denmark,M,Austria,50,"Python, NLP, Data Visualization",Bachelor,16,Telecommunications,2024-03-15,2024-05-25,728,7.3,Advanced Robotics -AI03497,AI Consultant,138467,USD,138467,EX,FT,Sweden,M,Sweden,0,"Python, Hadoop, SQL, Computer Vision",Associate,19,Technology,2024-07-21,2024-08-08,612,10,Digital Transformation LLC -AI03498,Head of AI,125705,EUR,106849,SE,FL,France,M,France,100,"PyTorch, Python, Scala",Bachelor,9,Energy,2024-11-06,2024-12-03,2098,8.1,AI Innovations -AI03499,ML Ops Engineer,107784,USD,107784,MI,PT,Norway,L,Norway,0,"SQL, Statistics, Data Visualization, Python, Mathematics",Bachelor,4,Technology,2024-07-07,2024-09-17,1589,5.9,TechCorp Inc -AI03500,Computer Vision Engineer,49527,USD,49527,SE,CT,India,M,India,0,"Python, Scala, AWS",Master,6,Media,2024-11-03,2025-01-11,1906,9.6,Advanced Robotics -AI03501,AI Software Engineer,73779,JPY,8115690,EN,PT,Japan,S,Poland,0,"Python, Azure, Statistics",Bachelor,1,Transportation,2024-07-05,2024-08-26,1183,10,Digital Transformation LLC -AI03502,AI Consultant,98422,USD,98422,MI,FL,United States,L,United States,50,"SQL, GCP, Statistics, Hadoop, Linux",PhD,3,Real Estate,2024-06-18,2024-07-16,2175,5.9,Algorithmic Solutions -AI03503,Principal Data Scientist,110310,SGD,143403,MI,PT,Singapore,L,Singapore,100,"PyTorch, Deep Learning, Spark",Associate,4,Retail,2025-02-28,2025-03-27,1821,6.7,Future Systems -AI03504,ML Ops Engineer,167443,EUR,142327,EX,FL,Austria,M,Austria,50,"R, Scala, NLP",Master,19,Transportation,2024-12-25,2025-01-21,2422,6.3,Cloud AI Solutions -AI03505,Machine Learning Engineer,135296,SGD,175885,SE,FT,Singapore,S,Singapore,0,"Spark, Kubernetes, Computer Vision",Associate,7,Media,2024-02-18,2024-03-07,2274,9.6,TechCorp Inc -AI03506,Data Scientist,101322,SGD,131719,MI,CT,Singapore,L,Singapore,100,"TensorFlow, Data Visualization, Git",Master,4,Technology,2024-10-30,2024-11-16,1477,9,AI Innovations -AI03507,AI Consultant,81204,AUD,109625,MI,FL,Australia,S,Australia,100,"Python, Hadoop, Linux, NLP, Statistics",PhD,2,Education,2024-01-07,2024-01-30,2214,5.5,DataVision Ltd -AI03508,Machine Learning Engineer,216778,USD,216778,EX,CT,United States,M,United States,100,"AWS, Azure, MLOps",Bachelor,12,Consulting,2024-06-22,2024-07-24,2366,6.3,DeepTech Ventures -AI03509,Computer Vision Engineer,176928,AUD,238853,EX,FL,Australia,M,Australia,100,"GCP, Git, Hadoop",PhD,14,Real Estate,2024-11-29,2025-01-15,1015,5.7,Neural Networks Co -AI03510,Research Scientist,76676,USD,76676,SE,PT,South Korea,S,Russia,0,"Java, SQL, MLOps, Mathematics, Hadoop",PhD,7,Retail,2024-05-27,2024-07-09,2390,9.1,Smart Analytics -AI03511,Data Analyst,167099,USD,167099,SE,PT,United States,L,United States,0,"R, Git, MLOps",PhD,7,Energy,2024-07-03,2024-07-30,720,8.7,Cognitive Computing -AI03512,ML Ops Engineer,89898,USD,89898,SE,CT,South Korea,M,South Korea,50,"SQL, Azure, Scala, MLOps, Python",Master,5,Transportation,2025-03-11,2025-03-30,1286,6,Quantum Computing Inc -AI03513,Robotics Engineer,123146,USD,123146,SE,PT,South Korea,M,South Korea,50,"Spark, Python, Linux, Statistics, Tableau",Master,9,Technology,2024-03-25,2024-05-03,1632,8,Predictive Systems -AI03514,ML Ops Engineer,244148,USD,244148,EX,FT,Denmark,L,Australia,50,"AWS, Python, TensorFlow, PyTorch, Scala",PhD,16,Transportation,2024-12-29,2025-01-14,1215,8.8,AI Innovations -AI03515,Machine Learning Researcher,212784,CHF,191506,EX,FT,Switzerland,S,Switzerland,50,"NLP, Linux, Python, R, TensorFlow",Bachelor,14,Manufacturing,2025-02-25,2025-04-06,689,9.1,Predictive Systems -AI03516,Principal Data Scientist,206443,AUD,278698,EX,PT,Australia,M,Australia,0,"Python, Kubernetes, GCP",Master,15,Gaming,2024-04-27,2024-06-19,2094,7.6,Future Systems -AI03517,ML Ops Engineer,55944,JPY,6153840,EN,FT,Japan,M,Japan,50,"MLOps, Java, R",Bachelor,0,Technology,2024-04-28,2024-05-26,1744,9.3,Machine Intelligence Group -AI03518,Autonomous Systems Engineer,71392,USD,71392,EN,FL,Sweden,S,Sweden,50,"Linux, Statistics, SQL, Git, Mathematics",Bachelor,1,Gaming,2024-05-05,2024-06-28,1567,8.5,Cloud AI Solutions -AI03519,Principal Data Scientist,126751,CAD,158439,SE,PT,Canada,M,Latvia,0,"Git, Java, R, GCP, SQL",Master,8,Technology,2025-01-24,2025-02-23,1506,7.2,Predictive Systems -AI03520,AI Specialist,99185,USD,99185,SE,CT,Finland,M,Finland,50,"GCP, Python, Linux, SQL",Bachelor,5,Retail,2024-01-20,2024-03-13,599,9.6,Cognitive Computing -AI03521,Machine Learning Engineer,218350,AUD,294773,EX,CT,Australia,S,Australia,0,"PyTorch, Tableau, TensorFlow",Master,16,Media,2024-10-28,2024-12-03,909,8.7,Algorithmic Solutions -AI03522,Principal Data Scientist,123624,SGD,160711,MI,PT,Singapore,L,Singapore,100,"PyTorch, Scala, Computer Vision, Spark",Associate,3,Automotive,2024-08-25,2024-09-25,1195,9.5,Cloud AI Solutions -AI03523,AI Research Scientist,150816,USD,150816,EX,PT,Ireland,S,Nigeria,50,"Python, AWS, Computer Vision, Docker, Data Visualization",PhD,18,Technology,2024-10-24,2024-12-09,1118,6.4,TechCorp Inc -AI03524,Computer Vision Engineer,248052,CAD,310065,EX,PT,Canada,L,Canada,0,"Docker, Scala, Data Visualization, Azure, Spark",Master,15,Real Estate,2024-08-08,2024-09-20,1640,6,Predictive Systems -AI03525,Research Scientist,174068,SGD,226288,SE,CT,Singapore,L,Singapore,100,"Mathematics, PyTorch, TensorFlow",Associate,9,Transportation,2024-12-06,2024-12-21,1050,8.7,Smart Analytics -AI03526,Data Analyst,202119,USD,202119,EX,CT,South Korea,L,South Korea,50,"NLP, Python, Spark, TensorFlow",Bachelor,13,Transportation,2024-07-08,2024-08-24,1755,6.6,Cloud AI Solutions -AI03527,AI Research Scientist,52293,USD,52293,EX,CT,India,M,India,50,"AWS, Docker, Statistics",Associate,10,Real Estate,2024-05-25,2024-07-01,2424,5.9,Quantum Computing Inc -AI03528,Machine Learning Researcher,127194,EUR,108115,EX,FL,France,S,France,100,"PyTorch, Docker, TensorFlow, Deep Learning",Associate,10,Real Estate,2024-01-05,2024-03-05,853,7.6,Neural Networks Co -AI03529,Machine Learning Researcher,133885,USD,133885,MI,FT,United States,L,United States,100,"Hadoop, Spark, Tableau",PhD,3,Automotive,2025-01-28,2025-02-23,1070,8.6,Digital Transformation LLC -AI03530,AI Software Engineer,134073,EUR,113962,SE,CT,France,M,France,0,"Hadoop, MLOps, Linux, Spark",Associate,9,Automotive,2024-07-17,2024-08-29,2452,8.7,Predictive Systems -AI03531,Data Analyst,128939,CAD,161174,SE,PT,Canada,L,Canada,100,"Data Visualization, Deep Learning, SQL, MLOps, Java",PhD,5,Telecommunications,2024-11-27,2025-01-24,824,5.1,DeepTech Ventures -AI03532,Data Scientist,65196,USD,65196,MI,PT,Ireland,S,Ireland,0,"GCP, Git, NLP, PyTorch, Statistics",PhD,4,Finance,2025-03-23,2025-04-15,1393,7.4,Cloud AI Solutions -AI03533,Deep Learning Engineer,122554,USD,122554,MI,FL,Ireland,L,Ireland,100,"Kubernetes, R, Python, AWS",Associate,2,Real Estate,2024-12-16,2025-02-05,1118,6.5,DeepTech Ventures -AI03534,NLP Engineer,72995,EUR,62046,EN,CT,Netherlands,S,Kenya,100,"Mathematics, R, Python, Docker, PyTorch",Master,1,Consulting,2024-07-24,2024-08-28,1205,8.6,DeepTech Ventures -AI03535,AI Architect,36919,USD,36919,SE,FT,India,M,India,100,"Hadoop, Scala, Python, Docker",PhD,9,Real Estate,2025-01-26,2025-03-26,842,8.7,Smart Analytics -AI03536,Computer Vision Engineer,111161,JPY,12227710,SE,CT,Japan,S,Japan,50,"Git, Linux, GCP, AWS, SQL",Bachelor,5,Technology,2024-03-01,2024-05-03,999,7.6,AI Innovations -AI03537,Principal Data Scientist,226559,USD,226559,EX,PT,South Korea,L,Argentina,50,"R, Python, Azure, SQL",PhD,11,Consulting,2024-01-27,2024-04-06,679,8,Future Systems -AI03538,AI Product Manager,194134,USD,194134,EX,FT,United States,M,United States,0,"Scala, Docker, Data Visualization, Kubernetes, PyTorch",Bachelor,11,Gaming,2024-08-19,2024-10-01,653,7.3,DataVision Ltd -AI03539,Machine Learning Engineer,48340,CAD,60425,EN,CT,Canada,S,Canada,100,"PyTorch, R, Data Visualization",Bachelor,0,Finance,2024-11-06,2024-12-21,2251,8.2,Future Systems -AI03540,ML Ops Engineer,93478,USD,93478,MI,FL,Sweden,S,Sweden,100,"AWS, SQL, Mathematics",PhD,4,Gaming,2024-01-25,2024-03-18,990,8.9,Cognitive Computing -AI03541,AI Specialist,135053,GBP,101290,SE,FT,United Kingdom,L,United Kingdom,0,"Azure, Deep Learning, TensorFlow",Bachelor,9,Education,2024-04-18,2024-06-23,974,5.4,DataVision Ltd -AI03542,AI Specialist,118702,AUD,160248,SE,CT,Australia,M,New Zealand,50,"AWS, MLOps, Hadoop, NLP, R",Master,5,Government,2025-01-21,2025-03-23,2213,8.3,Neural Networks Co -AI03543,Computer Vision Engineer,66189,USD,66189,EN,CT,Ireland,S,Ireland,0,"Scala, Kubernetes, Python",Associate,1,Education,2024-02-09,2024-03-03,1274,7.5,Quantum Computing Inc -AI03544,NLP Engineer,135922,USD,135922,SE,FL,Finland,M,Finland,100,"Hadoop, Statistics, Azure",Bachelor,8,Finance,2024-03-07,2024-04-24,2462,9.3,Autonomous Tech -AI03545,AI Research Scientist,220929,USD,220929,SE,FT,Denmark,L,Denmark,50,"Linux, Azure, Spark",Master,8,Energy,2024-01-17,2024-03-26,2021,5.8,Machine Intelligence Group -AI03546,NLP Engineer,82829,JPY,9111190,MI,FT,Japan,M,Japan,100,"Spark, Kubernetes, NLP, Hadoop",Associate,2,Technology,2025-04-05,2025-04-29,1930,7.3,Smart Analytics -AI03547,NLP Engineer,91897,AUD,124061,MI,PT,Australia,S,Australia,50,"MLOps, PyTorch, TensorFlow",PhD,3,Manufacturing,2024-09-30,2024-10-16,533,5.1,DataVision Ltd -AI03548,Research Scientist,120965,USD,120965,MI,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Kubernetes",Master,4,Media,2024-01-02,2024-02-08,2239,9.6,Advanced Robotics -AI03549,Machine Learning Engineer,310818,CHF,279736,EX,PT,Switzerland,S,Switzerland,100,"SQL, Python, MLOps, Java, Mathematics",Bachelor,18,Technology,2025-01-27,2025-03-30,1771,6.4,Smart Analytics -AI03550,Deep Learning Engineer,73677,EUR,62625,EN,FL,Austria,L,Austria,50,"SQL, Git, Linux, AWS",Bachelor,0,Technology,2024-07-30,2024-08-30,1254,6.4,Quantum Computing Inc -AI03551,Principal Data Scientist,71156,USD,71156,EN,CT,United States,L,India,0,"Azure, Mathematics, Kubernetes, Deep Learning, Data Visualization",Associate,0,Government,2024-02-17,2024-03-16,2491,7.6,Digital Transformation LLC -AI03552,AI Software Engineer,190140,EUR,161619,EX,PT,Germany,M,Germany,100,"MLOps, Data Visualization, Python, TensorFlow, Deep Learning",Master,17,Real Estate,2024-07-04,2024-07-26,1541,7.4,Future Systems -AI03553,ML Ops Engineer,133027,EUR,113073,SE,FT,Austria,L,Austria,50,"Spark, Linux, Java, PyTorch",Master,5,Telecommunications,2024-08-09,2024-08-27,901,6,Smart Analytics -AI03554,Research Scientist,232210,USD,232210,EX,PT,South Korea,L,Spain,50,"Scala, PyTorch, AWS, Spark, SQL",Master,15,Consulting,2024-08-07,2024-09-05,2085,5,Cognitive Computing -AI03555,Data Analyst,113916,GBP,85437,SE,FT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Hadoop, R, AWS",Associate,8,Energy,2024-05-12,2024-07-02,2364,6,AI Innovations -AI03556,Head of AI,228576,SGD,297149,EX,PT,Singapore,M,Singapore,0,"GCP, Java, SQL, Git",Associate,13,Education,2024-07-25,2024-09-03,1965,7.8,Smart Analytics -AI03557,Machine Learning Researcher,25011,USD,25011,EN,CT,China,M,Portugal,0,"SQL, Linux, Hadoop, Mathematics",PhD,1,Manufacturing,2024-09-01,2024-11-03,1692,9.1,Algorithmic Solutions -AI03558,AI Product Manager,139200,USD,139200,SE,PT,Sweden,M,Sweden,0,"Git, Azure, Tableau, MLOps",Master,5,Energy,2024-05-31,2024-07-16,1241,9.1,Machine Intelligence Group -AI03559,Computer Vision Engineer,292522,CHF,263270,EX,FL,Switzerland,S,Switzerland,0,"R, Java, Tableau, MLOps",Associate,15,Consulting,2024-01-01,2024-01-27,824,7,Machine Intelligence Group -AI03560,AI Specialist,159257,USD,159257,SE,FL,Denmark,L,Denmark,100,"R, TensorFlow, Data Visualization, Tableau, NLP",PhD,5,Healthcare,2024-10-03,2024-12-14,1309,9.8,Quantum Computing Inc -AI03561,AI Research Scientist,108189,USD,108189,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, Azure, GCP, Scala",Master,5,Media,2025-02-26,2025-03-30,1421,5.9,Neural Networks Co -AI03562,Robotics Engineer,112943,USD,112943,SE,CT,Sweden,M,Sweden,100,"SQL, Statistics, Tableau",Master,7,Media,2024-01-16,2024-02-02,1584,7.4,AI Innovations -AI03563,Data Engineer,101976,SGD,132569,MI,CT,Singapore,M,Singapore,50,"Python, Computer Vision, Git",Master,2,Technology,2024-08-24,2024-11-02,2384,6.8,Machine Intelligence Group -AI03564,Principal Data Scientist,90165,GBP,67624,EN,CT,United Kingdom,L,United Kingdom,100,"GCP, Hadoop, Statistics, Computer Vision",Bachelor,1,Technology,2024-05-21,2024-06-15,700,6.6,Cloud AI Solutions -AI03565,ML Ops Engineer,179183,JPY,19710130,EX,CT,Japan,S,Japan,100,"Scala, R, Kubernetes, Python, Docker",Master,18,Real Estate,2024-05-30,2024-06-27,1393,7.2,Digital Transformation LLC -AI03566,NLP Engineer,113638,EUR,96592,SE,PT,Netherlands,M,South Africa,50,"SQL, Python, TensorFlow, Statistics, PyTorch",Bachelor,5,Transportation,2025-04-18,2025-05-12,2288,5.5,Predictive Systems -AI03567,Data Analyst,50907,SGD,66179,EN,PT,Singapore,S,Singapore,0,"Hadoop, SQL, Statistics",Bachelor,0,Manufacturing,2025-03-29,2025-04-26,902,7.7,Smart Analytics -AI03568,AI Consultant,167654,EUR,142506,EX,PT,France,M,France,50,"Kubernetes, Mathematics, Linux, SQL",Bachelor,13,Consulting,2025-04-07,2025-05-27,2217,7.5,DeepTech Ventures -AI03569,Machine Learning Researcher,119056,CHF,107150,MI,FL,Switzerland,S,Switzerland,50,"Docker, Python, Tableau",Master,2,Gaming,2024-09-02,2024-11-02,2403,8.9,Autonomous Tech -AI03570,Autonomous Systems Engineer,95121,USD,95121,MI,PT,United States,M,Poland,0,"Python, TensorFlow, Azure, NLP",PhD,2,Retail,2025-01-26,2025-02-24,1927,7.1,Smart Analytics -AI03571,AI Architect,111821,JPY,12300310,MI,FL,Japan,L,Turkey,50,"Linux, AWS, MLOps, SQL",Master,4,Healthcare,2024-03-04,2024-04-30,1694,5.8,Cognitive Computing -AI03572,Principal Data Scientist,183873,GBP,137905,EX,FT,United Kingdom,M,United Kingdom,0,"PyTorch, Git, Computer Vision, Java, MLOps",Associate,18,Education,2024-07-04,2024-08-04,684,6.5,AI Innovations -AI03573,AI Architect,247623,CHF,222861,EX,FL,Switzerland,L,Switzerland,100,"Java, Statistics, R, SQL, MLOps",PhD,15,Retail,2024-12-12,2025-01-15,2363,9,Future Systems -AI03574,AI Product Manager,70419,USD,70419,SE,FL,China,M,China,0,"Hadoop, Scala, Tableau, PyTorch, Mathematics",PhD,5,Manufacturing,2024-02-15,2024-03-04,1299,5.4,Advanced Robotics -AI03575,AI Architect,80822,CAD,101028,MI,CT,Canada,M,Canada,50,"Kubernetes, Git, Python, Docker",Bachelor,2,Real Estate,2024-11-12,2024-12-22,2216,8.2,DataVision Ltd -AI03576,AI Research Scientist,116798,USD,116798,MI,FL,United States,L,United States,100,"Python, AWS, Tableau, Computer Vision",Associate,2,Media,2024-09-08,2024-11-09,1703,9,Advanced Robotics -AI03577,AI Consultant,32773,USD,32773,EN,PT,India,L,India,50,"Python, MLOps, R, Java",Master,1,Transportation,2024-11-20,2024-12-12,1687,5.4,Machine Intelligence Group -AI03578,AI Research Scientist,153325,AUD,206989,EX,PT,Australia,S,Australia,100,"Kubernetes, Deep Learning, Scala, Linux",Bachelor,18,Energy,2025-04-30,2025-07-11,951,9.7,DeepTech Ventures -AI03579,AI Consultant,139637,EUR,118691,SE,FL,Germany,L,Germany,0,"AWS, Hadoop, MLOps",Associate,9,Retail,2025-03-20,2025-04-09,2137,6.9,Neural Networks Co -AI03580,AI Product Manager,228479,CHF,205631,SE,FT,Switzerland,L,Switzerland,0,"Git, Linux, Spark, Python, GCP",Bachelor,6,Real Estate,2025-04-24,2025-05-30,630,7.4,DeepTech Ventures -AI03581,Data Analyst,213432,USD,213432,EX,FL,Denmark,S,Norway,0,"Kubernetes, NLP, Azure",PhD,14,Automotive,2024-11-14,2024-12-30,1371,9.8,TechCorp Inc -AI03582,Data Scientist,120417,USD,120417,SE,FL,Norway,S,Norway,50,"Python, TensorFlow, GCP, Statistics",Master,7,Real Estate,2024-09-01,2024-10-28,1954,8,Autonomous Tech -AI03583,Computer Vision Engineer,128062,USD,128062,MI,FL,Denmark,S,Denmark,50,"R, Spark, Statistics, Deep Learning",Master,3,Transportation,2024-07-19,2024-09-28,2040,8.6,Quantum Computing Inc -AI03584,AI Product Manager,152788,EUR,129870,SE,FT,France,L,France,100,"Statistics, Deep Learning, Java, Docker",Associate,8,Gaming,2024-08-17,2024-10-28,1390,7.1,Smart Analytics -AI03585,Data Engineer,151742,EUR,128981,EX,PT,France,L,France,0,"TensorFlow, Python, NLP",Bachelor,19,Gaming,2024-06-28,2024-07-21,816,8.9,DeepTech Ventures -AI03586,Robotics Engineer,127281,USD,127281,SE,FL,South Korea,L,South Korea,100,"Deep Learning, Kubernetes, Linux, Mathematics, Hadoop",PhD,8,Gaming,2024-12-15,2025-02-23,2078,7.3,Future Systems -AI03587,Autonomous Systems Engineer,95779,CAD,119724,MI,PT,Canada,M,Canada,50,"Python, Computer Vision, SQL",Associate,2,Real Estate,2025-01-07,2025-01-28,1351,6.2,Future Systems -AI03588,AI Software Engineer,127704,AUD,172400,SE,CT,Australia,L,Australia,0,"SQL, Python, Git, Statistics, MLOps",Associate,5,Automotive,2024-01-22,2024-02-17,2062,9.4,TechCorp Inc -AI03589,Computer Vision Engineer,119308,CAD,149135,SE,FL,Canada,S,Canada,50,"Computer Vision, Hadoop, Python, GCP",Bachelor,8,Education,2025-01-01,2025-01-15,564,8,Machine Intelligence Group -AI03590,ML Ops Engineer,62680,AUD,84618,EN,FT,Australia,M,Australia,50,"GCP, Java, SQL, R",Associate,1,Technology,2024-11-07,2024-12-18,2105,6.6,Advanced Robotics -AI03591,Data Scientist,272438,AUD,367791,EX,PT,Australia,L,Norway,50,"AWS, Scala, NLP, PyTorch",PhD,17,Consulting,2024-03-10,2024-04-13,1144,8.1,Cognitive Computing -AI03592,AI Software Engineer,174329,EUR,148180,SE,CT,Netherlands,L,Netherlands,100,"R, NLP, Java",Master,7,Energy,2024-04-30,2024-05-27,1675,7,Smart Analytics -AI03593,Computer Vision Engineer,46653,USD,46653,EN,CT,Israel,S,Israel,0,"Python, GCP, Statistics",Associate,0,Technology,2024-04-20,2024-06-27,2203,5.6,DeepTech Ventures -AI03594,Head of AI,173890,USD,173890,EX,FT,Israel,M,Israel,100,"MLOps, Python, TensorFlow, Data Visualization, GCP",Associate,17,Finance,2024-04-08,2024-05-19,1771,6.1,Cloud AI Solutions -AI03595,Deep Learning Engineer,338945,CHF,305051,EX,FT,Switzerland,M,Switzerland,50,"MLOps, Git, Statistics",Master,14,Government,2024-04-06,2024-06-02,817,9.6,Advanced Robotics -AI03596,AI Architect,140480,USD,140480,SE,PT,South Korea,L,South Korea,50,"Deep Learning, AWS, Tableau, Azure",Master,7,Retail,2024-06-19,2024-08-10,863,5.1,Cognitive Computing -AI03597,Data Engineer,92646,USD,92646,MI,FT,Israel,S,Israel,100,"Spark, R, Statistics",PhD,2,Education,2024-06-07,2024-08-18,832,6.9,Autonomous Tech -AI03598,Data Engineer,54404,USD,54404,EX,PT,India,M,India,0,"PyTorch, MLOps, TensorFlow",PhD,10,Media,2024-05-05,2024-07-17,875,8.9,Machine Intelligence Group -AI03599,AI Specialist,113043,GBP,84782,SE,CT,United Kingdom,M,United Kingdom,0,"Deep Learning, Computer Vision, Tableau, Spark",PhD,8,Consulting,2025-01-30,2025-04-05,1712,8.2,Digital Transformation LLC -AI03600,Data Analyst,159400,EUR,135490,EX,CT,France,S,Turkey,50,"Deep Learning, Mathematics, TensorFlow",Bachelor,14,Real Estate,2025-01-23,2025-02-21,1732,8.4,Machine Intelligence Group -AI03601,Deep Learning Engineer,31170,USD,31170,EN,FL,China,S,South Africa,0,"Kubernetes, TensorFlow, MLOps",PhD,0,Transportation,2024-11-01,2024-12-09,1498,8.8,Advanced Robotics -AI03602,Principal Data Scientist,108438,USD,108438,MI,FL,Sweden,M,Indonesia,0,"Docker, NLP, Python",Bachelor,2,Real Estate,2024-08-02,2024-08-19,1635,8.9,Smart Analytics -AI03603,AI Architect,111346,USD,111346,SE,FT,United States,S,Indonesia,50,"Scala, Python, TensorFlow, Kubernetes, Statistics",Bachelor,7,Retail,2024-11-11,2024-12-01,970,9,Predictive Systems -AI03604,Deep Learning Engineer,223449,USD,223449,EX,FT,Denmark,S,Denmark,0,"Linux, Computer Vision, Git",Associate,16,Real Estate,2024-03-13,2024-04-26,1483,5.9,AI Innovations -AI03605,Computer Vision Engineer,48324,USD,48324,EN,FT,Sweden,S,Poland,50,"Docker, Azure, Tableau, Kubernetes",Bachelor,0,Telecommunications,2024-10-10,2024-11-19,1822,9.4,AI Innovations -AI03606,Autonomous Systems Engineer,66696,AUD,90040,EN,FT,Australia,M,Australia,100,"Docker, Scala, Computer Vision, Git",Bachelor,1,Retail,2024-07-01,2024-07-29,1526,6.5,Smart Analytics -AI03607,AI Research Scientist,210386,USD,210386,EX,CT,Sweden,S,Sweden,50,"Java, Git, GCP",Bachelor,16,Consulting,2024-11-30,2025-02-01,883,8.6,DataVision Ltd -AI03608,Machine Learning Researcher,48698,USD,48698,MI,CT,China,M,China,0,"Python, Java, AWS, NLP",PhD,3,Finance,2024-11-22,2024-12-16,1110,8,Smart Analytics -AI03609,Machine Learning Researcher,60193,EUR,51164,EN,CT,Austria,M,Austria,50,"Python, TensorFlow, Azure, SQL, PyTorch",Bachelor,0,Government,2024-02-12,2024-03-01,526,5.1,Cognitive Computing -AI03610,AI Specialist,60740,USD,60740,EN,PT,United States,M,United States,100,"AWS, R, Deep Learning, Python, Scala",Bachelor,0,Consulting,2024-03-20,2024-05-12,1052,7.3,Future Systems -AI03611,AI Specialist,118920,USD,118920,MI,CT,Norway,S,Canada,0,"Deep Learning, SQL, Statistics, Mathematics, Java",Master,3,Education,2024-08-19,2024-09-15,1491,5.2,Future Systems -AI03612,Principal Data Scientist,87000,AUD,117450,EN,CT,Australia,L,Australia,100,"R, SQL, Tableau",Associate,1,Finance,2024-07-31,2024-09-05,1336,6.9,DataVision Ltd -AI03613,Deep Learning Engineer,204824,USD,204824,EX,CT,Israel,M,Israel,0,"Hadoop, Computer Vision, Python, MLOps, Kubernetes",Bachelor,12,Media,2024-09-20,2024-10-10,1610,8.8,Advanced Robotics -AI03614,Principal Data Scientist,87194,USD,87194,MI,PT,Norway,S,Norway,0,"Computer Vision, Python, Tableau",Associate,2,Technology,2024-07-18,2024-08-07,1333,9.5,Neural Networks Co -AI03615,Autonomous Systems Engineer,232255,USD,232255,EX,CT,Norway,L,Portugal,100,"Deep Learning, Azure, PyTorch",Associate,16,Automotive,2024-05-28,2024-06-28,2132,9,Digital Transformation LLC -AI03616,Data Engineer,101827,USD,101827,MI,FL,Sweden,L,Sweden,50,"Azure, Docker, Git, NLP",Master,4,Telecommunications,2024-10-05,2024-11-08,1136,7.7,Future Systems -AI03617,Head of AI,240245,GBP,180184,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, R, Data Visualization, Computer Vision",PhD,16,Retail,2024-05-06,2024-06-15,1309,8.9,DeepTech Ventures -AI03618,Data Scientist,167576,USD,167576,SE,CT,Sweden,L,Sweden,50,"Tableau, Hadoop, R, Python",Bachelor,9,Energy,2025-03-06,2025-04-25,1628,8.3,Neural Networks Co -AI03619,AI Research Scientist,215103,CAD,268879,EX,CT,Canada,M,Canada,0,"Python, Git, TensorFlow, Docker, Linux",Master,13,Finance,2024-05-31,2024-07-24,1236,8.7,Smart Analytics -AI03620,Machine Learning Engineer,48369,EUR,41114,EN,PT,Austria,S,Austria,0,"GCP, Kubernetes, SQL, Hadoop, Docker",PhD,1,Telecommunications,2024-06-05,2024-07-18,2049,6.2,Quantum Computing Inc -AI03621,Research Scientist,133879,SGD,174043,SE,FT,Singapore,S,Singapore,100,"Docker, Scala, GCP, Deep Learning",Bachelor,9,Automotive,2024-09-25,2024-11-22,1927,5.1,Machine Intelligence Group -AI03622,Machine Learning Researcher,28565,USD,28565,EN,FT,China,L,China,100,"Statistics, Linux, SQL, Scala",Master,0,Healthcare,2025-02-23,2025-03-27,1764,5.4,Cognitive Computing -AI03623,ML Ops Engineer,159550,USD,159550,MI,PT,Denmark,L,Belgium,50,"Tableau, Linux, Kubernetes",PhD,3,Consulting,2024-01-17,2024-03-19,844,9.1,DataVision Ltd -AI03624,ML Ops Engineer,78403,EUR,66643,MI,FL,Netherlands,M,Netherlands,0,"MLOps, GCP, Data Visualization, Git",PhD,2,Automotive,2025-04-11,2025-05-16,1044,6.9,Neural Networks Co -AI03625,Head of AI,87867,USD,87867,EN,CT,Sweden,L,Sweden,50,"Linux, Git, Statistics",Associate,0,Consulting,2025-04-26,2025-07-06,2334,9.2,Algorithmic Solutions -AI03626,Machine Learning Engineer,116358,USD,116358,SE,CT,Israel,L,Norway,50,"NLP, Kubernetes, Docker, Deep Learning, GCP",Bachelor,8,Telecommunications,2025-01-28,2025-03-21,2472,5.1,Future Systems -AI03627,ML Ops Engineer,198454,SGD,257990,EX,PT,Singapore,L,Singapore,50,"Hadoop, Statistics, Mathematics, Kubernetes, R",Bachelor,18,Gaming,2024-02-05,2024-03-06,1969,5.8,AI Innovations -AI03628,Data Analyst,118657,EUR,100858,SE,PT,Germany,M,Germany,100,"MLOps, SQL, Kubernetes, Mathematics",Associate,6,Gaming,2024-12-03,2025-01-19,1755,8.6,DataVision Ltd -AI03629,Research Scientist,86457,USD,86457,EN,CT,Israel,L,Israel,100,"Mathematics, Java, Git, Linux, Computer Vision",Bachelor,1,Media,2024-04-05,2024-05-18,750,8.2,Digital Transformation LLC -AI03630,AI Research Scientist,52898,EUR,44963,EN,PT,France,M,Poland,50,"Scala, Tableau, Computer Vision, Java, Git",PhD,1,Energy,2024-12-15,2025-01-14,1017,7,Machine Intelligence Group -AI03631,Deep Learning Engineer,25159,USD,25159,EN,PT,India,M,India,50,"Data Visualization, Spark, AWS",Master,0,Manufacturing,2024-04-02,2024-06-11,615,5.5,Predictive Systems -AI03632,AI Research Scientist,67708,USD,67708,MI,CT,Ireland,S,Ireland,50,"Python, Java, SQL, Linux",Bachelor,4,Transportation,2024-04-19,2024-05-17,1446,8.5,Smart Analytics -AI03633,Machine Learning Engineer,214023,USD,214023,EX,FL,Denmark,L,South Korea,0,"R, SQL, Tableau, AWS, Java",Bachelor,13,Energy,2025-03-28,2025-04-20,1796,5.7,AI Innovations -AI03634,AI Product Manager,110880,SGD,144144,SE,CT,Singapore,M,Singapore,0,"MLOps, R, Linux, Python",Master,7,Retail,2024-02-15,2024-03-15,843,8.1,Cognitive Computing -AI03635,Data Engineer,49214,USD,49214,EN,CT,South Korea,M,Sweden,50,"AWS, Linux, Kubernetes",PhD,1,Healthcare,2025-01-05,2025-01-21,1103,6.9,Quantum Computing Inc -AI03636,Robotics Engineer,65197,USD,65197,MI,PT,South Korea,S,South Korea,50,"PyTorch, Hadoop, TensorFlow, Java",Associate,4,Technology,2024-12-04,2025-01-15,903,6.8,Quantum Computing Inc -AI03637,AI Consultant,94494,AUD,127567,MI,PT,Australia,S,Spain,50,"Kubernetes, SQL, Tableau",PhD,2,Real Estate,2024-10-10,2024-12-16,1260,6.6,AI Innovations -AI03638,ML Ops Engineer,93560,CHF,84204,EN,FL,Switzerland,M,China,50,"Linux, AWS, Tableau, Spark, Git",Associate,1,Telecommunications,2024-08-20,2024-10-10,1422,7.3,Predictive Systems -AI03639,Deep Learning Engineer,65918,USD,65918,EN,CT,Ireland,S,Ireland,50,"Docker, Python, Mathematics, Kubernetes, Git",Master,1,Retail,2024-11-09,2025-01-18,1621,6,DataVision Ltd -AI03640,AI Product Manager,136380,EUR,115923,SE,FL,Austria,L,Austria,100,"Mathematics, Tableau, Scala",PhD,6,Consulting,2025-01-28,2025-04-04,1271,7.8,DataVision Ltd -AI03641,Computer Vision Engineer,58677,USD,58677,EN,FL,Finland,M,Finland,100,"R, PyTorch, Azure, SQL, Statistics",Master,1,Gaming,2024-06-04,2024-08-02,1115,9.4,Digital Transformation LLC -AI03642,AI Specialist,78838,USD,78838,MI,FT,Israel,M,Israel,0,"Deep Learning, GCP, Git, Python",Bachelor,2,Energy,2024-07-26,2024-09-13,792,8.9,Autonomous Tech -AI03643,AI Architect,269456,USD,269456,EX,CT,Norway,M,Norway,50,"Python, Scala, Azure, Deep Learning, Computer Vision",Bachelor,15,Telecommunications,2024-02-10,2024-04-03,1052,9.8,Cloud AI Solutions -AI03644,AI Research Scientist,134951,USD,134951,SE,FL,Sweden,L,Sweden,100,"Tableau, Deep Learning, GCP, Python, TensorFlow",Bachelor,9,Automotive,2024-01-28,2024-02-13,1296,8.8,Smart Analytics -AI03645,AI Specialist,71037,USD,71037,EN,PT,Ireland,S,Ireland,0,"Hadoop, R, Java",PhD,0,Healthcare,2025-01-27,2025-03-26,2034,8.9,Cognitive Computing -AI03646,Deep Learning Engineer,81347,CHF,73212,EN,FT,Switzerland,M,Finland,0,"Deep Learning, Kubernetes, Linux",PhD,1,Healthcare,2024-12-11,2025-01-15,2320,9,AI Innovations -AI03647,Deep Learning Engineer,42928,USD,42928,MI,PT,China,S,China,0,"Docker, Linux, TensorFlow",Bachelor,3,Government,2024-03-02,2024-05-08,1427,9.3,DeepTech Ventures -AI03648,AI Architect,133466,CAD,166833,SE,PT,Canada,L,Canada,0,"PyTorch, TensorFlow, Azure",Associate,7,Technology,2024-07-25,2024-09-16,1603,5.4,Cloud AI Solutions -AI03649,Robotics Engineer,199990,USD,199990,EX,FT,Norway,M,Norway,100,"Docker, Kubernetes, AWS, Java",Associate,10,Education,2024-11-13,2024-12-07,1983,5.9,Cloud AI Solutions -AI03650,Machine Learning Researcher,146195,USD,146195,EX,FT,Finland,S,Finland,50,"Spark, Statistics, Hadoop",Master,17,Healthcare,2024-10-04,2024-12-07,502,6.8,Digital Transformation LLC -AI03651,NLP Engineer,98140,EUR,83419,EN,FL,Netherlands,L,Netherlands,100,"Kubernetes, R, Tableau, Data Visualization, AWS",Master,1,Finance,2024-01-01,2024-02-06,1249,6,AI Innovations -AI03652,Data Analyst,37739,USD,37739,EN,PT,China,L,China,100,"Linux, Kubernetes, Data Visualization, MLOps",Associate,0,Retail,2024-02-24,2024-03-12,1183,9.1,Neural Networks Co -AI03653,Deep Learning Engineer,76141,USD,76141,MI,CT,Ireland,S,Ireland,50,"Docker, SQL, PyTorch",Associate,4,Manufacturing,2024-02-13,2024-03-10,1482,9.2,Algorithmic Solutions -AI03654,Robotics Engineer,168289,USD,168289,EX,PT,United States,S,United States,50,"Scala, NLP, Git, Kubernetes",Bachelor,15,Transportation,2024-03-11,2024-05-19,924,6,Smart Analytics -AI03655,ML Ops Engineer,35309,USD,35309,MI,CT,India,M,Belgium,0,"Linux, PyTorch, NLP",PhD,4,Government,2025-02-01,2025-03-24,1527,5.1,AI Innovations -AI03656,Head of AI,252143,EUR,214322,EX,CT,Netherlands,M,Netherlands,100,"Docker, Data Visualization, Hadoop, Statistics",Bachelor,13,Automotive,2025-03-08,2025-03-23,1165,5.5,Digital Transformation LLC -AI03657,Robotics Engineer,61954,USD,61954,EN,PT,Sweden,M,Sweden,100,"SQL, MLOps, PyTorch, Hadoop",Master,1,Education,2024-09-16,2024-11-28,1789,9.3,Quantum Computing Inc -AI03658,Deep Learning Engineer,128736,USD,128736,SE,FT,Sweden,S,Turkey,0,"Git, Hadoop, Mathematics, SQL, R",PhD,5,Finance,2024-09-20,2024-11-28,797,6.1,Machine Intelligence Group -AI03659,AI Product Manager,90524,EUR,76945,MI,CT,Germany,L,Philippines,50,"NLP, Java, Deep Learning, Git",Bachelor,3,Consulting,2024-08-02,2024-09-10,2227,5.1,Smart Analytics -AI03660,Machine Learning Researcher,164213,GBP,123160,EX,FT,United Kingdom,M,United Kingdom,0,"Git, Hadoop, MLOps",Associate,19,Retail,2024-07-30,2024-09-22,2447,7.1,Quantum Computing Inc -AI03661,Data Analyst,106152,SGD,137998,MI,FT,Singapore,L,Singapore,0,"R, Git, Linux",Associate,4,Transportation,2025-04-03,2025-06-14,1267,7.2,DeepTech Ventures -AI03662,Robotics Engineer,101811,EUR,86539,SE,CT,France,M,Brazil,50,"Kubernetes, Python, Tableau",Associate,9,Transportation,2024-03-31,2024-05-23,1113,8.1,Neural Networks Co -AI03663,Machine Learning Engineer,130689,JPY,14375790,SE,FT,Japan,M,Argentina,0,"R, Spark, Data Visualization, Statistics, Azure",Master,8,Manufacturing,2024-04-02,2024-05-23,594,9.8,Neural Networks Co -AI03664,NLP Engineer,134597,USD,134597,EX,FL,Finland,S,Finland,0,"GCP, Java, PyTorch",Associate,14,Gaming,2024-03-07,2024-04-01,1997,6.2,TechCorp Inc -AI03665,Data Scientist,127982,USD,127982,SE,PT,South Korea,L,South Korea,50,"Spark, Kubernetes, Git, Tableau, Python",Bachelor,9,Automotive,2024-04-01,2024-06-04,804,9.3,Cognitive Computing -AI03666,AI Software Engineer,76846,USD,76846,EN,PT,United States,L,Sweden,100,"NLP, Deep Learning, Spark, MLOps",Master,0,Manufacturing,2024-04-13,2024-05-17,590,5.2,Cognitive Computing -AI03667,AI Software Engineer,121507,USD,121507,SE,FL,United States,M,United States,100,"Tableau, Kubernetes, AWS, GCP",Associate,7,Telecommunications,2025-02-05,2025-04-09,1356,7.4,Machine Intelligence Group -AI03668,Principal Data Scientist,190021,USD,190021,EX,FL,Norway,S,Norway,100,"Deep Learning, Java, Spark, Git",Associate,15,Transportation,2024-03-23,2024-05-01,789,8.4,Digital Transformation LLC -AI03669,Robotics Engineer,146680,CAD,183350,SE,FT,Canada,L,Spain,50,"Scala, PyTorch, Computer Vision, Hadoop",Master,5,Energy,2024-04-06,2024-05-19,2431,9.9,Autonomous Tech -AI03670,Autonomous Systems Engineer,82088,GBP,61566,EN,CT,United Kingdom,M,United Kingdom,0,"AWS, Linux, MLOps",PhD,1,Manufacturing,2024-01-11,2024-02-08,1485,9.8,Algorithmic Solutions -AI03671,Computer Vision Engineer,142953,USD,142953,SE,CT,Ireland,L,Ireland,50,"Kubernetes, Java, MLOps, GCP, Mathematics",Bachelor,6,Technology,2024-01-16,2024-03-15,1720,8.7,Quantum Computing Inc -AI03672,AI Specialist,178787,USD,178787,EX,PT,Israel,S,Israel,0,"Docker, Data Visualization, NLP",PhD,15,Technology,2025-04-27,2025-06-07,1111,6.5,AI Innovations -AI03673,Data Engineer,216277,EUR,183835,EX,PT,Austria,M,Austria,100,"Git, Java, MLOps",Master,13,Telecommunications,2024-02-23,2024-03-30,1084,8.5,Cognitive Computing -AI03674,Data Scientist,94882,USD,94882,MI,FT,Finland,L,Finland,50,"Data Visualization, Java, Git, Python, SQL",PhD,3,Education,2025-01-15,2025-03-10,985,8.3,Smart Analytics -AI03675,Data Scientist,73031,GBP,54773,EN,PT,United Kingdom,L,United Kingdom,50,"Computer Vision, Tableau, Python, TensorFlow",Associate,1,Education,2024-11-10,2025-01-22,1425,8.3,Smart Analytics -AI03676,Data Engineer,126700,USD,126700,EX,PT,Sweden,S,Sweden,0,"Linux, Hadoop, Python, TensorFlow",Bachelor,17,Manufacturing,2024-05-18,2024-06-18,2292,7,Machine Intelligence Group -AI03677,Head of AI,95630,GBP,71723,MI,FT,United Kingdom,S,United Kingdom,100,"Scala, Mathematics, Java, Spark, AWS",Master,3,Finance,2024-10-28,2025-01-04,2231,7.4,Algorithmic Solutions -AI03678,Deep Learning Engineer,75175,USD,75175,EN,CT,United States,S,United States,100,"NLP, Linux, SQL",Bachelor,1,Transportation,2025-02-10,2025-03-24,807,5.4,DataVision Ltd -AI03679,Machine Learning Engineer,83872,USD,83872,MI,PT,Israel,L,Egypt,0,"Scala, R, Tableau, Mathematics, Linux",PhD,2,Healthcare,2024-07-17,2024-08-22,619,9.7,AI Innovations -AI03680,Data Scientist,156742,USD,156742,SE,FT,Israel,L,Israel,0,"Deep Learning, R, Java",Bachelor,8,Finance,2024-07-07,2024-08-06,857,9.1,Smart Analytics -AI03681,Principal Data Scientist,111290,USD,111290,SE,FT,Finland,M,Finland,50,"R, Kubernetes, Docker, GCP",PhD,6,Telecommunications,2025-01-30,2025-03-02,2301,6.7,Cloud AI Solutions -AI03682,Computer Vision Engineer,83694,GBP,62771,MI,CT,United Kingdom,M,United Kingdom,0,"Scala, SQL, Hadoop",Bachelor,3,Media,2025-03-28,2025-06-04,1440,7.2,AI Innovations -AI03683,Principal Data Scientist,63711,EUR,54154,EN,FT,France,M,France,50,"Scala, SQL, R",PhD,0,Telecommunications,2024-12-14,2025-01-20,1184,6,Algorithmic Solutions -AI03684,Machine Learning Engineer,108037,EUR,91831,MI,FL,Netherlands,M,Netherlands,100,"GCP, SQL, MLOps, Data Visualization",Associate,2,Real Estate,2024-03-29,2024-05-28,929,7.7,Cognitive Computing -AI03685,Machine Learning Engineer,151599,SGD,197079,SE,FL,Singapore,M,Philippines,0,"Hadoop, Scala, SQL, Kubernetes, AWS",Master,5,Healthcare,2025-04-05,2025-05-09,1044,7.1,Quantum Computing Inc -AI03686,AI Architect,113115,EUR,96148,MI,CT,Netherlands,L,Netherlands,50,"Docker, Spark, Hadoop, NLP",Bachelor,3,Energy,2024-04-18,2024-06-23,1096,6.1,Advanced Robotics -AI03687,Head of AI,213162,USD,213162,EX,FL,Israel,M,Israel,0,"Spark, Python, Tableau, Azure",PhD,18,Real Estate,2024-03-20,2024-05-22,744,9.6,Machine Intelligence Group -AI03688,Deep Learning Engineer,172013,AUD,232218,EX,CT,Australia,L,Italy,50,"R, TensorFlow, Linux, Spark, Mathematics",PhD,16,Manufacturing,2024-05-12,2024-06-04,1245,8.3,Cognitive Computing -AI03689,NLP Engineer,81655,USD,81655,EX,PT,China,L,China,0,"Python, Linux, Git, TensorFlow",Bachelor,12,Consulting,2024-12-10,2025-02-02,580,8.6,Advanced Robotics -AI03690,NLP Engineer,70576,EUR,59990,MI,FL,France,S,France,100,"Computer Vision, R, Azure",PhD,2,Energy,2024-07-11,2024-08-19,1274,9.2,Cognitive Computing -AI03691,Machine Learning Engineer,27457,USD,27457,MI,FL,India,M,India,0,"Kubernetes, Java, Azure",Bachelor,4,Education,2025-04-15,2025-06-27,1890,6,Quantum Computing Inc -AI03692,AI Product Manager,115606,SGD,150288,SE,CT,Singapore,M,France,100,"R, SQL, Scala, Mathematics",Associate,9,Retail,2024-11-21,2025-01-17,2279,8.3,Predictive Systems -AI03693,ML Ops Engineer,85378,EUR,72571,EN,PT,Austria,L,Austria,100,"Computer Vision, Git, Kubernetes",Associate,1,Government,2024-07-09,2024-09-08,500,6.6,DeepTech Ventures -AI03694,AI Specialist,305455,CHF,274910,EX,PT,Switzerland,M,Argentina,0,"Git, Azure, Statistics, R",Master,16,Healthcare,2024-03-29,2024-04-12,1280,5.2,DataVision Ltd -AI03695,Robotics Engineer,115424,USD,115424,MI,FT,Finland,L,Finland,0,"Python, Git, Deep Learning, Spark",Bachelor,4,Finance,2024-02-23,2024-03-23,2154,6.3,Autonomous Tech -AI03696,AI Consultant,73524,USD,73524,EN,FL,United States,S,Vietnam,0,"Python, PyTorch, NLP",Bachelor,0,Government,2024-03-05,2024-04-12,757,6.1,AI Innovations -AI03697,AI Research Scientist,164239,EUR,139603,EX,FT,Germany,M,Germany,50,"Python, Computer Vision, Azure, Java",Bachelor,17,Telecommunications,2024-01-09,2024-02-07,542,9.4,Smart Analytics -AI03698,Head of AI,187030,USD,187030,EX,FT,South Korea,S,South Korea,50,"Docker, Python, R, Kubernetes",PhD,17,Retail,2025-01-28,2025-03-06,2173,8.7,Cloud AI Solutions -AI03699,Principal Data Scientist,201791,AUD,272418,EX,CT,Australia,S,Australia,50,"PyTorch, AWS, Python, NLP",Bachelor,12,Automotive,2024-04-06,2024-04-30,1444,9.7,AI Innovations -AI03700,AI Product Manager,189693,USD,189693,EX,FT,Norway,M,Norway,0,"Computer Vision, PyTorch, Spark",Associate,13,Technology,2024-06-30,2024-09-03,2479,7.2,Autonomous Tech -AI03701,Data Engineer,65796,EUR,55927,EN,PT,Austria,L,Austria,0,"Spark, AWS, Linux, TensorFlow, Azure",Associate,1,Real Estate,2025-03-29,2025-06-09,765,9.1,Autonomous Tech -AI03702,Principal Data Scientist,50207,EUR,42676,EN,FT,France,S,France,50,"Docker, Scala, GCP, Mathematics",PhD,0,Gaming,2024-04-03,2024-05-17,2206,8.8,Future Systems -AI03703,Data Scientist,90924,EUR,77285,MI,CT,Germany,M,Germany,0,"Java, R, NLP, GCP, Linux",Bachelor,3,Technology,2024-05-01,2024-05-26,1171,5.2,Future Systems -AI03704,Autonomous Systems Engineer,66161,CAD,82701,MI,FT,Canada,S,Canada,100,"R, Hadoop, TensorFlow, Git, SQL",Associate,4,Education,2024-07-08,2024-08-31,1791,5,Smart Analytics -AI03705,Data Engineer,166384,AUD,224618,EX,CT,Australia,L,Netherlands,100,"NLP, R, Java, Azure",Bachelor,18,Technology,2024-03-24,2024-05-20,2322,9.5,Cognitive Computing -AI03706,Autonomous Systems Engineer,124008,USD,124008,SE,FL,United States,M,United States,50,"Computer Vision, Azure, PyTorch",Master,6,Technology,2024-11-25,2025-02-02,625,8.6,Smart Analytics -AI03707,AI Software Engineer,83812,USD,83812,MI,CT,Ireland,M,Ireland,0,"Kubernetes, SQL, Tableau",PhD,2,Gaming,2024-06-28,2024-09-09,1991,6,Machine Intelligence Group -AI03708,Computer Vision Engineer,142427,SGD,185155,SE,PT,Singapore,S,Singapore,100,"Git, Python, Tableau, Computer Vision",Bachelor,5,Automotive,2024-12-12,2024-12-27,1392,5.8,AI Innovations -AI03709,AI Consultant,186900,USD,186900,SE,PT,Denmark,M,Denmark,100,"PyTorch, Scala, MLOps, Linux",Bachelor,5,Retail,2024-08-17,2024-09-24,1593,7.9,DataVision Ltd -AI03710,AI Specialist,129050,CAD,161313,SE,CT,Canada,M,Canada,0,"SQL, Deep Learning, Kubernetes, Scala",PhD,9,Healthcare,2025-04-18,2025-05-04,835,9.8,Future Systems -AI03711,Machine Learning Engineer,274462,CHF,247016,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Hadoop, Tableau, MLOps",Bachelor,14,Energy,2025-03-17,2025-04-23,2406,6.4,Quantum Computing Inc -AI03712,AI Product Manager,62465,JPY,6871150,EN,CT,Japan,M,Japan,50,"Mathematics, PyTorch, Tableau, Computer Vision, Git",PhD,0,Telecommunications,2024-12-07,2025-01-03,955,7.6,Smart Analytics -AI03713,Principal Data Scientist,73182,USD,73182,MI,PT,Israel,M,Sweden,100,"Linux, TensorFlow, Scala, SQL, Spark",Associate,2,Retail,2025-03-25,2025-04-30,1570,7.7,Neural Networks Co -AI03714,Deep Learning Engineer,184437,GBP,138328,EX,FL,United Kingdom,S,United Kingdom,50,"Linux, Hadoop, Tableau",PhD,17,Consulting,2024-07-07,2024-08-16,1473,5.4,Predictive Systems -AI03715,Robotics Engineer,94373,GBP,70780,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, TensorFlow, Azure",Bachelor,2,Healthcare,2024-06-26,2024-08-01,1713,8.6,DataVision Ltd -AI03716,Autonomous Systems Engineer,222341,EUR,188990,EX,PT,Austria,M,Denmark,100,"Azure, Scala, Data Visualization",Bachelor,16,Media,2025-01-15,2025-03-23,1873,7.3,Machine Intelligence Group -AI03717,Deep Learning Engineer,54047,CAD,67559,EN,PT,Canada,M,Canada,0,"NLP, Deep Learning, Scala, AWS",Bachelor,0,Government,2024-10-26,2025-01-01,804,5.6,Cloud AI Solutions -AI03718,NLP Engineer,127771,USD,127771,SE,CT,Denmark,S,Denmark,50,"SQL, Azure, Linux",Associate,9,Education,2024-07-06,2024-07-21,677,9.1,DataVision Ltd -AI03719,AI Specialist,93985,EUR,79887,MI,CT,France,M,France,50,"Statistics, Kubernetes, MLOps, R",PhD,3,Gaming,2024-02-18,2024-04-07,548,7.2,DataVision Ltd -AI03720,ML Ops Engineer,66798,EUR,56778,MI,PT,Germany,S,Kenya,0,"NLP, SQL, PyTorch, Java, Computer Vision",Associate,4,Technology,2024-06-03,2024-07-24,1988,5.5,AI Innovations -AI03721,Machine Learning Engineer,155058,USD,155058,SE,FL,Sweden,L,Sweden,100,"Statistics, Kubernetes, GCP, AWS",PhD,7,Gaming,2025-03-15,2025-04-15,1894,5.5,Cloud AI Solutions -AI03722,ML Ops Engineer,280160,JPY,30817600,EX,PT,Japan,L,Japan,0,"Mathematics, Tableau, Linux, Data Visualization",PhD,15,Manufacturing,2024-10-02,2024-11-21,2398,5.6,TechCorp Inc -AI03723,Autonomous Systems Engineer,77244,EUR,65657,MI,FL,France,S,France,50,"Spark, Tableau, TensorFlow, Data Visualization",Associate,4,Manufacturing,2024-01-19,2024-03-23,769,8.2,Cloud AI Solutions -AI03724,Autonomous Systems Engineer,216834,USD,216834,EX,FL,Israel,M,Estonia,100,"Kubernetes, Mathematics, Python",PhD,11,Manufacturing,2025-04-20,2025-07-02,1824,6.6,DeepTech Ventures -AI03725,AI Product Manager,110485,USD,110485,MI,FT,United States,L,Norway,50,"Python, TensorFlow, Spark, PyTorch, NLP",Master,2,Transportation,2024-06-16,2024-07-24,2063,8.6,Neural Networks Co -AI03726,Computer Vision Engineer,43499,USD,43499,SE,FT,China,S,China,50,"SQL, Java, Kubernetes, TensorFlow, Tableau",Bachelor,7,Media,2025-03-24,2025-05-27,537,5.1,DeepTech Ventures -AI03727,Computer Vision Engineer,266981,GBP,200236,EX,PT,United Kingdom,L,United Kingdom,0,"Data Visualization, Java, Spark",Bachelor,13,Telecommunications,2024-10-06,2024-11-05,1978,9.5,Algorithmic Solutions -AI03728,Machine Learning Researcher,126042,USD,126042,SE,FT,Finland,M,Finland,50,"Git, Docker, MLOps, Mathematics, Kubernetes",Associate,8,Automotive,2024-08-28,2024-10-08,1314,7.2,Neural Networks Co -AI03729,AI Specialist,173706,CAD,217133,EX,FL,Canada,S,Canada,50,"Kubernetes, Python, Azure, R, Mathematics",Master,10,Media,2025-01-20,2025-02-22,2026,8.8,Cloud AI Solutions -AI03730,AI Architect,75161,AUD,101467,EN,FT,Australia,M,Portugal,0,"GCP, Python, NLP",Associate,0,Real Estate,2025-02-10,2025-04-22,2388,5.6,Cloud AI Solutions -AI03731,Autonomous Systems Engineer,115030,USD,115030,SE,FT,Israel,M,Israel,50,"Git, TensorFlow, Tableau, Docker",Associate,7,Media,2024-09-07,2024-10-15,623,7.8,Machine Intelligence Group -AI03732,AI Product Manager,151796,AUD,204925,SE,FT,Australia,M,Australia,0,"Python, Kubernetes, Tableau, Computer Vision",PhD,8,Real Estate,2025-03-24,2025-05-26,2435,6.3,Algorithmic Solutions -AI03733,AI Research Scientist,59337,USD,59337,SE,FL,China,M,China,100,"GCP, MLOps, Tableau, R, Hadoop",Master,8,Government,2024-12-23,2025-01-22,617,9.7,Advanced Robotics -AI03734,Robotics Engineer,84211,CHF,75790,EN,PT,Switzerland,L,Finland,100,"TensorFlow, Python, Git",Bachelor,0,Real Estate,2025-03-13,2025-05-18,2309,9.8,AI Innovations -AI03735,Data Analyst,121798,CAD,152248,SE,PT,Canada,S,Sweden,50,"Linux, Tableau, AWS",Associate,5,Media,2025-04-13,2025-06-06,2077,9.9,TechCorp Inc -AI03736,Principal Data Scientist,198790,USD,198790,EX,PT,Israel,M,Ireland,50,"Python, Data Visualization, TensorFlow, Deep Learning, AWS",Associate,11,Government,2024-08-12,2024-10-16,2155,7.2,Autonomous Tech -AI03737,Data Engineer,80590,USD,80590,EN,CT,Norway,L,Thailand,0,"SQL, Spark, MLOps, Statistics, Python",Bachelor,1,Gaming,2024-10-07,2024-11-03,865,8.8,Algorithmic Solutions -AI03738,Principal Data Scientist,158320,EUR,134572,EX,CT,Germany,M,Colombia,50,"SQL, Python, MLOps, Deep Learning",Associate,19,Automotive,2024-01-26,2024-03-16,2065,5.4,Machine Intelligence Group -AI03739,AI Software Engineer,28067,USD,28067,MI,CT,India,S,South Africa,0,"Python, Deep Learning, Scala, Azure, Git",Master,3,Real Estate,2024-12-31,2025-01-19,928,8.1,Quantum Computing Inc -AI03740,Machine Learning Researcher,221734,EUR,188474,EX,FL,France,M,France,100,"MLOps, Hadoop, Python",Bachelor,12,Media,2024-11-12,2024-12-30,1964,8.2,Digital Transformation LLC -AI03741,Research Scientist,66023,USD,66023,EN,CT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, R, Git, Data Visualization",Master,1,Energy,2024-06-22,2024-08-07,820,6,Smart Analytics -AI03742,Machine Learning Engineer,79053,EUR,67195,MI,PT,Austria,M,Austria,100,"Statistics, PyTorch, Azure, Linux, TensorFlow",Master,4,Finance,2024-01-26,2024-03-11,1071,7.5,Quantum Computing Inc -AI03743,AI Specialist,90414,USD,90414,SE,CT,South Korea,M,South Korea,100,"Statistics, TensorFlow, Hadoop",Master,9,Healthcare,2024-07-03,2024-07-28,2008,7.4,TechCorp Inc -AI03744,Head of AI,44966,EUR,38221,EN,CT,France,S,France,0,"PyTorch, TensorFlow, Kubernetes, Scala, Java",Bachelor,1,Healthcare,2024-06-16,2024-08-03,1948,7.6,Quantum Computing Inc -AI03745,Principal Data Scientist,135292,USD,135292,SE,FL,United States,M,Egypt,100,"Deep Learning, Kubernetes, AWS, Scala, NLP",Bachelor,6,Transportation,2024-06-25,2024-07-31,846,9.2,Cloud AI Solutions -AI03746,Principal Data Scientist,224798,EUR,191078,EX,PT,France,M,France,0,"Mathematics, Git, Docker",PhD,19,Media,2024-12-04,2024-12-26,802,6.9,Cloud AI Solutions -AI03747,Deep Learning Engineer,169956,AUD,229441,EX,FT,Australia,S,Australia,100,"Spark, Java, Docker, Computer Vision",Bachelor,10,Gaming,2025-01-26,2025-03-06,750,6.9,Predictive Systems -AI03748,Data Scientist,218143,SGD,283586,EX,FT,Singapore,L,Singapore,0,"Spark, Tableau, Python",Master,19,Energy,2024-05-10,2024-07-17,2434,5.6,AI Innovations -AI03749,AI Research Scientist,123186,EUR,104708,SE,PT,Germany,S,United States,0,"Git, Docker, SQL, Kubernetes",Bachelor,5,Consulting,2024-10-14,2024-11-07,1709,8,Digital Transformation LLC -AI03750,Robotics Engineer,69645,CAD,87056,MI,FT,Canada,S,Canada,100,"Git, Scala, Spark",PhD,2,Automotive,2024-09-09,2024-11-06,1857,8.9,Cloud AI Solutions -AI03751,Head of AI,157091,EUR,133527,EX,PT,Austria,L,Austria,0,"Statistics, Tableau, SQL, Hadoop",PhD,16,Telecommunications,2024-12-21,2025-01-24,888,9.3,TechCorp Inc -AI03752,AI Specialist,90830,EUR,77206,MI,CT,Germany,L,China,50,"Azure, PyTorch, NLP",Associate,4,Retail,2025-03-29,2025-05-26,1841,9.2,Advanced Robotics -AI03753,Deep Learning Engineer,249590,EUR,212152,EX,PT,Netherlands,M,Netherlands,0,"Hadoop, Docker, Data Visualization",PhD,17,Transportation,2025-03-10,2025-03-24,2428,6.1,DeepTech Ventures -AI03754,Computer Vision Engineer,123791,USD,123791,SE,PT,Israel,M,Israel,0,"Linux, AWS, MLOps, Azure, Kubernetes",Bachelor,7,Finance,2024-06-17,2024-08-20,1043,7,Machine Intelligence Group -AI03755,Head of AI,117223,USD,117223,SE,PT,Finland,S,Finland,100,"Docker, MLOps, Computer Vision, Statistics",Bachelor,5,Education,2024-10-17,2024-11-06,2009,9.4,Future Systems -AI03756,NLP Engineer,27366,USD,27366,MI,CT,India,S,India,100,"Data Visualization, Scala, R",PhD,3,Energy,2024-06-04,2024-08-09,2448,6.5,Smart Analytics -AI03757,Machine Learning Researcher,182032,EUR,154727,EX,CT,Austria,L,Austria,0,"MLOps, SQL, AWS, NLP, Spark",Master,13,Consulting,2024-07-27,2024-10-02,1455,8.9,Advanced Robotics -AI03758,Data Analyst,31017,USD,31017,MI,FT,India,L,India,0,"Java, SQL, Deep Learning, PyTorch, Azure",Master,2,Gaming,2024-09-14,2024-10-26,669,5.8,Machine Intelligence Group -AI03759,Head of AI,148948,USD,148948,EX,CT,Finland,S,Finland,100,"Spark, R, MLOps",PhD,16,Technology,2024-06-21,2024-08-14,2352,7.5,Predictive Systems -AI03760,Data Engineer,126217,CHF,113595,MI,CT,Switzerland,L,Switzerland,50,"TensorFlow, Kubernetes, NLP, Deep Learning, Statistics",Bachelor,3,Energy,2024-10-30,2024-12-14,1310,8.9,Neural Networks Co -AI03761,AI Research Scientist,85615,EUR,72773,MI,PT,France,M,France,100,"Deep Learning, NLP, MLOps, Statistics, Kubernetes",Master,3,Gaming,2024-10-17,2024-11-24,2387,9.4,Predictive Systems -AI03762,Deep Learning Engineer,224102,USD,224102,EX,CT,Sweden,M,Sweden,100,"Tableau, Computer Vision, R",Bachelor,17,Government,2024-04-24,2024-05-16,1525,10,Smart Analytics -AI03763,Autonomous Systems Engineer,67594,EUR,57455,EN,PT,Germany,M,Germany,0,"Git, Deep Learning, Python, Tableau",Associate,1,Retail,2024-11-03,2024-11-25,2297,9.8,Cloud AI Solutions -AI03764,Autonomous Systems Engineer,172931,EUR,146991,EX,CT,Germany,S,Germany,100,"Java, Scala, Statistics, Data Visualization",Bachelor,19,Real Estate,2024-08-15,2024-09-13,992,5.9,Future Systems -AI03765,AI Research Scientist,109233,SGD,142003,SE,FT,Singapore,S,Singapore,50,"Python, TensorFlow, R, SQL",PhD,9,Healthcare,2024-07-02,2024-09-12,1286,5.7,Quantum Computing Inc -AI03766,AI Architect,240499,SGD,312649,EX,FT,Singapore,L,Singapore,100,"Hadoop, PyTorch, SQL, R, MLOps",Associate,18,Media,2025-04-28,2025-05-27,2292,7.4,Advanced Robotics -AI03767,Autonomous Systems Engineer,92133,USD,92133,EN,PT,Denmark,M,Denmark,100,"Java, Git, Statistics, R",PhD,1,Education,2025-03-09,2025-05-08,1048,7.5,DeepTech Ventures -AI03768,Machine Learning Researcher,76049,USD,76049,EX,PT,India,M,India,50,"NLP, Python, Linux, Data Visualization",Bachelor,12,Telecommunications,2024-01-07,2024-02-06,1742,5.8,TechCorp Inc -AI03769,Machine Learning Researcher,272882,AUD,368391,EX,CT,Australia,L,Australia,50,"R, SQL, Spark",PhD,19,Transportation,2025-01-29,2025-03-22,656,6.3,Quantum Computing Inc -AI03770,AI Specialist,60278,USD,60278,MI,CT,South Korea,S,South Korea,100,"Spark, NLP, Linux, Kubernetes",Associate,2,Manufacturing,2024-08-11,2024-10-18,1855,9.2,Machine Intelligence Group -AI03771,AI Product Manager,232998,USD,232998,EX,FT,Norway,L,South Africa,50,"Git, SQL, Deep Learning, Scala",Associate,17,Government,2024-08-14,2024-10-18,1447,6.5,Quantum Computing Inc -AI03772,AI Software Engineer,125478,SGD,163121,SE,CT,Singapore,S,Singapore,100,"R, Linux, SQL, Statistics, Deep Learning",Master,9,Consulting,2025-03-23,2025-04-09,703,6.9,Smart Analytics -AI03773,AI Consultant,80666,EUR,68566,MI,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, SQL, R, GCP",Associate,3,Healthcare,2024-03-24,2024-05-11,1026,7.3,TechCorp Inc -AI03774,AI Software Engineer,130187,CHF,117168,MI,CT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Linux, SQL",Associate,4,Consulting,2024-11-19,2025-01-06,1055,5.3,Future Systems -AI03775,Data Analyst,112669,USD,112669,MI,FT,Finland,L,Japan,50,"SQL, Git, TensorFlow, NLP, AWS",Associate,4,Gaming,2025-01-02,2025-02-06,1107,8.8,Machine Intelligence Group -AI03776,AI Research Scientist,117310,CAD,146638,MI,FT,Canada,L,Canada,100,"Python, Azure, NLP",PhD,2,Technology,2024-11-27,2024-12-28,1372,7,Predictive Systems -AI03777,Autonomous Systems Engineer,104436,USD,104436,EN,FL,United States,L,United States,100,"Scala, PyTorch, SQL, AWS",Master,1,Consulting,2024-11-09,2024-12-07,2286,9.8,Cognitive Computing -AI03778,Robotics Engineer,151858,USD,151858,SE,FT,Denmark,L,Denmark,50,"GCP, Data Visualization, MLOps, SQL, Linux",Master,7,Education,2024-09-25,2024-10-12,2069,8,Cloud AI Solutions -AI03779,AI Software Engineer,300122,USD,300122,EX,FL,United States,L,United States,100,"Linux, Data Visualization, Kubernetes",Bachelor,11,Manufacturing,2025-04-12,2025-05-24,1771,8.4,Machine Intelligence Group -AI03780,Research Scientist,123704,USD,123704,MI,PT,United States,M,India,100,"Python, GCP, TensorFlow, Linux, PyTorch",PhD,4,Energy,2024-05-11,2024-05-27,1820,5.6,Quantum Computing Inc -AI03781,NLP Engineer,123407,CAD,154259,SE,PT,Canada,M,Canada,100,"Mathematics, Python, MLOps, SQL, Linux",Bachelor,7,Energy,2024-11-04,2024-11-23,2275,5.9,TechCorp Inc -AI03782,AI Research Scientist,113350,SGD,147355,SE,PT,Singapore,S,Singapore,100,"Scala, Mathematics, Data Visualization, Deep Learning, Java",Bachelor,8,Real Estate,2025-03-23,2025-05-19,1968,7.3,AI Innovations -AI03783,Principal Data Scientist,240944,JPY,26503840,EX,CT,Japan,M,Japan,50,"MLOps, Statistics, Linux",PhD,17,Education,2025-03-05,2025-03-23,1690,6.5,Smart Analytics -AI03784,Autonomous Systems Engineer,56468,USD,56468,MI,FT,China,L,China,100,"R, NLP, TensorFlow, Data Visualization",Master,2,Media,2024-09-06,2024-10-30,1620,9.1,Quantum Computing Inc -AI03785,AI Specialist,23467,USD,23467,EN,FL,India,S,India,0,"Azure, Linux, Computer Vision, AWS, Docker",Bachelor,1,Education,2025-03-22,2025-04-08,1780,8.7,Predictive Systems -AI03786,AI Product Manager,41589,USD,41589,SE,FT,India,S,India,100,"Java, GCP, Azure, PyTorch, Mathematics",PhD,5,Manufacturing,2024-05-18,2024-06-25,1576,7.1,TechCorp Inc -AI03787,Autonomous Systems Engineer,56436,USD,56436,SE,FL,India,L,South Korea,50,"Git, PyTorch, Azure, Data Visualization",PhD,6,Telecommunications,2024-03-05,2024-04-02,2128,8.9,Autonomous Tech -AI03788,Deep Learning Engineer,102052,USD,102052,EN,FT,Denmark,M,Denmark,50,"Scala, Computer Vision, GCP, Git",Master,0,Finance,2025-03-07,2025-03-26,2234,9.6,Cognitive Computing -AI03789,Data Engineer,140417,GBP,105313,SE,PT,United Kingdom,M,New Zealand,0,"SQL, MLOps, PyTorch",Bachelor,5,Energy,2024-10-03,2024-12-15,939,6.5,Predictive Systems -AI03790,Head of AI,62079,USD,62079,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Python, AWS",Master,0,Media,2024-01-29,2024-04-05,845,8.3,Advanced Robotics -AI03791,Robotics Engineer,181941,GBP,136456,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Hadoop, SQL",Bachelor,9,Transportation,2024-09-15,2024-11-16,1538,7.2,Cloud AI Solutions -AI03792,Deep Learning Engineer,48759,USD,48759,EN,CT,South Korea,S,South Korea,50,"Kubernetes, Deep Learning, Python",PhD,0,Gaming,2024-06-28,2024-07-21,891,6.7,Smart Analytics -AI03793,Data Engineer,94775,EUR,80559,SE,PT,France,S,France,50,"Statistics, AWS, Spark, Deep Learning",PhD,8,Retail,2024-07-01,2024-08-29,1544,6.4,AI Innovations -AI03794,AI Specialist,111479,JPY,12262690,SE,FL,Japan,S,Poland,100,"Git, Java, GCP, Deep Learning",Master,6,Technology,2024-06-18,2024-08-13,568,9.1,Algorithmic Solutions -AI03795,Data Analyst,196602,USD,196602,EX,CT,Finland,M,Philippines,50,"Statistics, PyTorch, Git, Mathematics",Master,15,Manufacturing,2024-05-29,2024-06-12,1304,5.3,Advanced Robotics -AI03796,Principal Data Scientist,264173,EUR,224547,EX,PT,France,L,France,100,"Mathematics, Python, TensorFlow, MLOps, NLP",PhD,15,Technology,2024-12-15,2025-02-17,2407,9.6,DeepTech Ventures -AI03797,Head of AI,69502,SGD,90353,EN,CT,Singapore,M,Singapore,0,"Hadoop, SQL, PyTorch, Scala, R",PhD,1,Education,2024-12-31,2025-01-23,1948,8.8,Smart Analytics -AI03798,ML Ops Engineer,130004,EUR,110503,SE,PT,Germany,S,Italy,50,"MLOps, SQL, Python",PhD,6,Retail,2024-01-06,2024-02-03,1868,9.7,AI Innovations -AI03799,AI Product Manager,225220,USD,225220,EX,CT,Finland,M,Finland,0,"GCP, Python, TensorFlow, Hadoop, Deep Learning",PhD,11,Real Estate,2024-11-18,2025-01-02,699,8.5,AI Innovations -AI03800,Robotics Engineer,96826,SGD,125874,MI,CT,Singapore,M,Singapore,0,"GCP, PyTorch, Azure, R",PhD,3,Finance,2024-04-13,2024-05-26,1526,5.2,Digital Transformation LLC -AI03801,Machine Learning Engineer,56293,EUR,47849,EN,FL,Germany,S,Estonia,50,"SQL, Data Visualization, R, Computer Vision, NLP",PhD,1,Technology,2024-05-16,2024-07-11,1637,5.2,DeepTech Ventures -AI03802,Principal Data Scientist,197669,USD,197669,EX,FT,Denmark,M,Denmark,50,"Kubernetes, PyTorch, SQL, Docker",Bachelor,17,Real Estate,2025-04-11,2025-05-24,909,7.5,TechCorp Inc -AI03803,Machine Learning Engineer,129726,SGD,168644,SE,FL,Singapore,M,Singapore,50,"Python, Scala, GCP, R",Master,8,Government,2024-08-30,2024-10-26,967,5.1,Autonomous Tech -AI03804,AI Product Manager,146815,USD,146815,EX,PT,Sweden,S,Indonesia,0,"Computer Vision, PyTorch, Scala",Master,12,Consulting,2025-03-02,2025-04-17,850,5.4,Machine Intelligence Group -AI03805,Data Scientist,108448,USD,108448,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, AWS, NLP, Computer Vision",Master,5,Real Estate,2024-04-18,2024-05-12,2123,9.9,DataVision Ltd -AI03806,NLP Engineer,56987,GBP,42740,EN,CT,United Kingdom,S,Romania,0,"Linux, Tableau, TensorFlow, Deep Learning, Git",Master,0,Manufacturing,2024-02-05,2024-02-29,579,5.1,DeepTech Ventures -AI03807,Research Scientist,109575,USD,109575,SE,CT,Finland,S,Finland,0,"Hadoop, SQL, Python, Tableau, Deep Learning",Bachelor,6,Automotive,2024-10-19,2024-12-13,2369,9.7,Machine Intelligence Group -AI03808,AI Research Scientist,61632,USD,61632,EN,CT,Israel,L,Israel,50,"GCP, R, Tableau, Data Visualization, PyTorch",Bachelor,1,Real Estate,2024-10-26,2024-12-29,1601,6.6,Cognitive Computing -AI03809,Research Scientist,86859,USD,86859,MI,CT,Sweden,M,Sweden,0,"NLP, R, AWS, Linux, Deep Learning",Master,4,Technology,2024-06-27,2024-08-25,1979,7.7,Predictive Systems -AI03810,Data Analyst,93901,EUR,79816,MI,PT,Austria,M,Austria,100,"Python, Scala, Git",Bachelor,2,Gaming,2024-04-22,2024-05-17,2379,5,DeepTech Ventures -AI03811,Machine Learning Researcher,78383,USD,78383,SE,CT,South Korea,S,Austria,0,"Azure, Python, MLOps, R",Bachelor,9,Government,2024-10-30,2024-12-25,2250,6.8,Algorithmic Solutions -AI03812,Data Scientist,105143,USD,105143,EX,CT,China,L,China,0,"Deep Learning, Tableau, TensorFlow, R",Bachelor,13,Manufacturing,2024-06-08,2024-07-22,1396,9.6,Cognitive Computing -AI03813,AI Product Manager,113830,EUR,96756,SE,PT,France,M,Ukraine,0,"SQL, Hadoop, TensorFlow, Data Visualization, Linux",Associate,5,Healthcare,2024-10-06,2024-11-15,2416,7.3,Cloud AI Solutions -AI03814,Research Scientist,104205,EUR,88574,MI,FT,Netherlands,M,Romania,0,"Python, Docker, Tableau",Bachelor,4,Education,2025-02-10,2025-04-12,1015,6.6,Autonomous Tech -AI03815,Data Scientist,76948,USD,76948,MI,FL,Finland,S,Finland,0,"Deep Learning, Python, GCP, TensorFlow, Linux",Associate,3,Healthcare,2024-07-30,2024-09-14,2006,9.8,DataVision Ltd -AI03816,Data Scientist,158361,CAD,197951,SE,FT,Canada,L,Austria,100,"Spark, Python, Tableau, TensorFlow, GCP",Master,6,Energy,2024-06-26,2024-08-25,950,7.2,Digital Transformation LLC -AI03817,ML Ops Engineer,246286,USD,246286,EX,PT,Sweden,M,Sweden,100,"Scala, Spark, PyTorch, GCP",Associate,15,Gaming,2024-05-17,2024-07-22,1743,9.9,Advanced Robotics -AI03818,AI Architect,29444,USD,29444,MI,PT,India,M,India,50,"Git, Python, MLOps, NLP",Associate,3,Technology,2025-01-21,2025-02-24,1338,5.3,Machine Intelligence Group -AI03819,Data Scientist,65572,USD,65572,EX,PT,India,L,India,100,"NLP, Kubernetes, Data Visualization",PhD,10,Manufacturing,2025-03-06,2025-05-12,1167,8.5,Autonomous Tech -AI03820,AI Research Scientist,89996,EUR,76497,MI,FL,Austria,M,Austria,0,"MLOps, GCP, Python, TensorFlow, Computer Vision",PhD,3,Energy,2024-06-03,2024-07-11,1872,8.5,Neural Networks Co -AI03821,Head of AI,251600,EUR,213860,EX,FL,Germany,M,Germany,50,"PyTorch, Kubernetes, NLP",Associate,16,Energy,2024-07-03,2024-07-22,634,8.1,Advanced Robotics -AI03822,Principal Data Scientist,97239,GBP,72929,EN,FL,United Kingdom,L,United Kingdom,0,"Hadoop, Scala, Spark, TensorFlow, Tableau",Bachelor,0,Transportation,2024-09-19,2024-11-14,1174,7.8,Cloud AI Solutions -AI03823,Research Scientist,117805,JPY,12958550,SE,FL,Japan,S,Japan,100,"Linux, Azure, Python, Computer Vision",Associate,8,Energy,2024-07-31,2024-09-28,1354,7.7,Autonomous Tech -AI03824,Deep Learning Engineer,124143,USD,124143,MI,CT,United States,M,Finland,100,"Scala, Python, Computer Vision",PhD,2,Automotive,2024-03-20,2024-04-26,1879,9.1,Quantum Computing Inc -AI03825,Robotics Engineer,119551,USD,119551,SE,PT,Sweden,S,Sweden,50,"AWS, Azure, Python, TensorFlow, MLOps",PhD,9,Media,2024-03-28,2024-04-22,1443,8.8,DataVision Ltd -AI03826,NLP Engineer,122489,USD,122489,MI,PT,Ireland,L,Mexico,50,"Linux, Git, Tableau",Master,2,Retail,2024-01-20,2024-02-24,2181,8.3,AI Innovations -AI03827,AI Product Manager,297922,USD,297922,EX,CT,Denmark,L,Denmark,0,"Linux, Java, Tableau, Spark",Master,19,Finance,2024-02-01,2024-02-17,868,9.1,Cloud AI Solutions -AI03828,Autonomous Systems Engineer,284790,CHF,256311,EX,FT,Switzerland,M,Switzerland,100,"Tableau, Computer Vision, Git, MLOps, GCP",Associate,12,Real Estate,2024-03-17,2024-05-02,1087,6,DeepTech Ventures -AI03829,Machine Learning Engineer,140500,SGD,182650,SE,FT,Singapore,S,Singapore,100,"Scala, GCP, Data Visualization, Deep Learning, Mathematics",PhD,8,Energy,2024-11-11,2024-12-25,2434,7.7,AI Innovations -AI03830,NLP Engineer,116663,CHF,104997,MI,PT,Switzerland,S,Finland,50,"Kubernetes, Java, Spark",Master,4,Technology,2025-04-06,2025-06-05,899,6.3,Algorithmic Solutions -AI03831,AI Product Manager,136106,USD,136106,SE,FT,Norway,S,Norway,0,"TensorFlow, Statistics, Linux",Bachelor,6,Energy,2024-01-17,2024-02-09,1312,8.2,AI Innovations -AI03832,AI Specialist,120352,AUD,162475,SE,FL,Australia,S,United Kingdom,0,"Python, TensorFlow, Data Visualization",Associate,8,Technology,2025-02-22,2025-04-20,1026,5.1,Algorithmic Solutions -AI03833,Principal Data Scientist,115824,USD,115824,EX,PT,Finland,S,Finland,100,"Azure, Mathematics, GCP",Associate,10,Energy,2024-10-24,2024-12-23,1678,9.8,Advanced Robotics -AI03834,Data Engineer,192495,USD,192495,EX,PT,Israel,S,Israel,100,"SQL, Data Visualization, Spark, PyTorch",Associate,16,Government,2025-02-21,2025-03-13,1136,9.2,Autonomous Tech -AI03835,AI Consultant,70175,USD,70175,EN,CT,Finland,L,Finland,50,"Python, TensorFlow, MLOps, Tableau",Associate,0,Gaming,2024-03-27,2024-05-07,1939,5.9,Digital Transformation LLC -AI03836,Deep Learning Engineer,36741,USD,36741,MI,FL,India,M,India,100,"Azure, AWS, Spark, Hadoop, GCP",PhD,3,Consulting,2024-01-13,2024-02-01,825,8.6,Quantum Computing Inc -AI03837,Research Scientist,60568,USD,60568,EN,CT,Finland,L,Finland,100,"TensorFlow, SQL, Spark, Mathematics",Master,1,Government,2024-03-06,2024-04-17,1308,5.3,DeepTech Ventures -AI03838,Autonomous Systems Engineer,56833,USD,56833,EN,CT,Israel,M,Israel,50,"Statistics, Mathematics, Deep Learning, Python, TensorFlow",Associate,1,Gaming,2025-02-06,2025-03-19,1659,9.3,Machine Intelligence Group -AI03839,AI Research Scientist,138563,SGD,180132,SE,FT,Singapore,S,Singapore,100,"Tableau, SQL, Computer Vision",Associate,5,Consulting,2024-02-17,2024-03-16,1786,6.1,Machine Intelligence Group -AI03840,Autonomous Systems Engineer,69031,EUR,58676,MI,FL,Germany,S,Germany,50,"NLP, TensorFlow, Scala, Mathematics, R",PhD,3,Telecommunications,2024-09-25,2024-11-09,1921,7.4,Future Systems -AI03841,Principal Data Scientist,49258,USD,49258,EN,CT,Sweden,S,Sweden,100,"R, Docker, Python, Scala, Kubernetes",Bachelor,1,Consulting,2025-01-30,2025-04-04,1364,8.6,Advanced Robotics -AI03842,Machine Learning Engineer,177507,USD,177507,EX,FT,Sweden,M,Sweden,50,"Deep Learning, SQL, PyTorch, Git",Master,16,Gaming,2025-03-13,2025-04-11,1788,7,Cloud AI Solutions -AI03843,Robotics Engineer,278819,USD,278819,EX,CT,Denmark,M,Netherlands,100,"Computer Vision, Hadoop, R",Bachelor,12,Finance,2024-01-23,2024-03-02,1360,6.4,Algorithmic Solutions -AI03844,Data Analyst,101827,JPY,11200970,MI,PT,Japan,M,Japan,50,"Azure, PyTorch, MLOps, Python",Bachelor,4,Gaming,2024-06-07,2024-07-20,1347,5.8,Advanced Robotics -AI03845,Data Engineer,84062,SGD,109281,EN,CT,Singapore,L,Singapore,0,"Kubernetes, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Real Estate,2024-04-26,2024-05-27,2252,8.9,Cognitive Computing -AI03846,Deep Learning Engineer,102646,CHF,92381,MI,PT,Switzerland,S,Spain,50,"Hadoop, Linux, SQL, Python, Java",Bachelor,4,Healthcare,2024-12-26,2025-01-15,2383,6.6,AI Innovations -AI03847,AI Architect,95477,USD,95477,MI,CT,Norway,M,Norway,0,"GCP, TensorFlow, MLOps",Master,4,Gaming,2024-05-23,2024-08-01,1534,8.4,DeepTech Ventures -AI03848,Autonomous Systems Engineer,46111,USD,46111,SE,FL,China,S,China,0,"Spark, Kubernetes, Linux, Mathematics",Master,6,Transportation,2025-01-07,2025-01-25,518,5.9,Machine Intelligence Group -AI03849,Machine Learning Researcher,97023,EUR,82470,MI,FL,Netherlands,M,South Korea,50,"Python, TensorFlow, Linux, PyTorch, Mathematics",PhD,3,Retail,2024-07-31,2024-09-17,2239,8.7,DataVision Ltd -AI03850,Robotics Engineer,220428,USD,220428,EX,CT,Finland,M,Russia,100,"PyTorch, NLP, Statistics, TensorFlow",PhD,18,Energy,2025-01-14,2025-02-15,2110,8.2,Future Systems -AI03851,Data Analyst,111944,USD,111944,MI,FT,United States,L,Japan,50,"GCP, Java, Python, Tableau",PhD,4,Energy,2024-01-19,2024-03-13,1258,6.3,Algorithmic Solutions -AI03852,AI Product Manager,186617,GBP,139963,EX,FL,United Kingdom,L,United Kingdom,100,"AWS, Mathematics, Python",Bachelor,18,Government,2024-01-14,2024-03-23,1910,6.5,Smart Analytics -AI03853,Data Analyst,161013,EUR,136861,EX,FL,Netherlands,M,Netherlands,100,"SQL, Spark, NLP",Bachelor,18,Real Estate,2024-07-04,2024-08-13,1215,7.1,Digital Transformation LLC -AI03854,Principal Data Scientist,30458,USD,30458,MI,FL,India,S,India,100,"Kubernetes, NLP, SQL",Master,2,Consulting,2024-07-30,2024-09-27,1135,8.8,Algorithmic Solutions -AI03855,Research Scientist,64590,USD,64590,EN,FL,Israel,S,Israel,100,"Kubernetes, MLOps, Computer Vision, Azure",PhD,0,Technology,2024-01-17,2024-03-23,2116,9.5,Quantum Computing Inc -AI03856,ML Ops Engineer,113088,USD,113088,SE,PT,South Korea,S,Russia,0,"PyTorch, Kubernetes, Scala, Java, AWS",PhD,6,Automotive,2024-06-19,2024-07-07,2410,8.2,Autonomous Tech -AI03857,Research Scientist,110516,EUR,93939,MI,CT,Netherlands,L,Netherlands,0,"Python, SQL, Java, GCP, Docker",Associate,3,Media,2025-04-16,2025-05-10,1068,7.3,Future Systems -AI03858,Data Analyst,33400,USD,33400,EN,PT,China,S,China,0,"Statistics, Docker, PyTorch, AWS, Python",Associate,1,Consulting,2024-08-30,2024-10-12,2143,9.2,DataVision Ltd -AI03859,Research Scientist,57862,CAD,72328,EN,FT,Canada,M,Canada,0,"GCP, Mathematics, Kubernetes, Statistics",Master,1,Gaming,2024-07-12,2024-09-14,1817,6.1,Digital Transformation LLC -AI03860,Machine Learning Engineer,111403,EUR,94693,SE,FL,Germany,M,South Africa,50,"NLP, GCP, AWS, SQL, Python",Associate,5,Retail,2024-09-26,2024-11-15,2297,8.5,Future Systems -AI03861,AI Consultant,51736,EUR,43976,EN,FT,Netherlands,S,Netherlands,50,"Data Visualization, Kubernetes, Docker, Statistics",Bachelor,0,Government,2024-07-08,2024-08-01,982,5.1,Digital Transformation LLC -AI03862,Data Engineer,23717,USD,23717,EN,FL,India,M,India,50,"Tableau, Azure, R",Bachelor,0,Gaming,2024-05-27,2024-06-26,2332,7.6,Advanced Robotics -AI03863,Principal Data Scientist,109386,USD,109386,MI,FL,Ireland,M,Ireland,0,"Computer Vision, PyTorch, Kubernetes",Master,2,Government,2025-03-28,2025-05-26,1823,6.5,Advanced Robotics -AI03864,Deep Learning Engineer,74878,CAD,93598,MI,PT,Canada,M,Canada,50,"Python, Java, GCP",Bachelor,4,Government,2024-03-24,2024-04-15,2256,7.7,Predictive Systems -AI03865,Autonomous Systems Engineer,65141,USD,65141,EX,FT,India,M,India,0,"Java, R, SQL",Associate,16,Gaming,2024-12-07,2025-01-28,1317,9.2,Cloud AI Solutions -AI03866,AI Architect,128867,CHF,115980,MI,PT,Switzerland,M,Switzerland,50,"Spark, TensorFlow, SQL, Python",Bachelor,4,Energy,2024-10-06,2024-12-06,2112,5.2,DeepTech Ventures -AI03867,Data Analyst,90726,CHF,81653,EN,CT,Switzerland,S,Hungary,100,"Computer Vision, Java, Docker",Associate,1,Telecommunications,2024-09-24,2024-11-07,601,7.2,DeepTech Ventures -AI03868,Deep Learning Engineer,194760,USD,194760,EX,FT,Israel,M,Israel,100,"Python, Tableau, Git, TensorFlow",Master,17,Technology,2024-04-17,2024-05-18,2424,5.2,TechCorp Inc -AI03869,Autonomous Systems Engineer,107056,USD,107056,SE,CT,Ireland,S,Switzerland,0,"TensorFlow, Hadoop, PyTorch, Azure, GCP",Bachelor,5,Healthcare,2024-11-13,2024-12-05,1395,7.6,Future Systems -AI03870,Principal Data Scientist,108594,CAD,135743,SE,FT,Canada,M,South Africa,50,"Hadoop, TensorFlow, Kubernetes",Bachelor,9,Automotive,2025-03-02,2025-03-21,1796,9.7,DataVision Ltd -AI03871,Data Engineer,79163,EUR,67289,MI,CT,Germany,S,Germany,50,"Mathematics, Linux, R, Docker",Master,2,Technology,2024-12-24,2025-02-26,948,8.6,Advanced Robotics -AI03872,Principal Data Scientist,32589,USD,32589,EN,FT,China,M,China,100,"Java, Spark, Tableau, Hadoop, R",PhD,0,Finance,2024-09-08,2024-09-28,2482,6.1,Machine Intelligence Group -AI03873,Machine Learning Researcher,151184,USD,151184,SE,PT,United States,L,United States,50,"Python, Statistics, Computer Vision, TensorFlow, Spark",Associate,9,Telecommunications,2024-06-19,2024-08-19,1282,8.1,Autonomous Tech -AI03874,AI Research Scientist,80519,USD,80519,SE,PT,South Korea,S,South Korea,100,"GCP, Python, Docker, Computer Vision",Bachelor,7,Finance,2024-10-27,2024-12-28,1784,8.5,Future Systems -AI03875,Autonomous Systems Engineer,67798,USD,67798,EN,FT,Finland,S,Finland,50,"NLP, Mathematics, Linux",Bachelor,1,Consulting,2024-02-04,2024-04-17,1593,9,Predictive Systems -AI03876,Data Engineer,142055,JPY,15626050,SE,PT,Japan,L,Japan,0,"Python, Deep Learning, MLOps, Scala, Linux",Master,5,Retail,2024-08-09,2024-09-24,2229,6,Smart Analytics -AI03877,Data Scientist,120576,GBP,90432,SE,PT,United Kingdom,M,United Kingdom,50,"AWS, TensorFlow, Scala, Tableau",Associate,5,Finance,2025-01-15,2025-02-08,2007,6.4,Cloud AI Solutions -AI03878,Principal Data Scientist,125509,USD,125509,MI,FT,Norway,M,Norway,0,"MLOps, Statistics, Kubernetes",PhD,3,Transportation,2024-12-23,2025-01-27,2272,8.5,Advanced Robotics -AI03879,Data Analyst,55931,USD,55931,EX,PT,India,M,Vietnam,50,"Linux, Docker, AWS, Python",Associate,13,Finance,2024-03-07,2024-04-22,2317,8,DataVision Ltd -AI03880,Machine Learning Researcher,231123,JPY,25423530,EX,FT,Japan,L,Japan,50,"NLP, R, SQL, Tableau",Bachelor,13,Consulting,2024-07-09,2024-08-06,1704,6.8,DeepTech Ventures -AI03881,AI Product Manager,228322,USD,228322,EX,FT,South Korea,L,South Korea,0,"Kubernetes, Statistics, MLOps, SQL",Bachelor,17,Education,2025-02-25,2025-04-21,1258,9,Machine Intelligence Group -AI03882,Research Scientist,143444,USD,143444,EX,PT,Finland,S,Russia,0,"TensorFlow, Scala, Linux, PyTorch",Bachelor,14,Finance,2024-04-21,2024-05-30,1040,8.8,Future Systems -AI03883,AI Product Manager,72811,AUD,98295,EN,FT,Australia,M,Australia,0,"PyTorch, SQL, Java, Statistics, Azure",Associate,0,Manufacturing,2024-04-23,2024-06-17,1188,9.5,Quantum Computing Inc -AI03884,Research Scientist,53482,USD,53482,SE,FL,China,S,China,0,"Python, Git, Hadoop, Scala",Bachelor,5,Automotive,2024-01-20,2024-03-15,1359,6.2,Quantum Computing Inc -AI03885,Computer Vision Engineer,69221,AUD,93448,EN,PT,Australia,S,Australia,0,"Python, MLOps, Docker",Bachelor,1,Media,2024-01-14,2024-02-20,2077,5.7,TechCorp Inc -AI03886,ML Ops Engineer,171506,USD,171506,SE,CT,Norway,L,Mexico,50,"Data Visualization, Kubernetes, GCP, Scala",Master,5,Transportation,2024-02-24,2024-03-14,2170,7.8,Smart Analytics -AI03887,Data Analyst,149279,EUR,126887,EX,FT,France,S,France,100,"Kubernetes, Hadoop, Computer Vision, Python, Statistics",PhD,18,Technology,2024-10-01,2024-11-09,1669,9.7,DataVision Ltd -AI03888,AI Architect,123862,EUR,105283,SE,FT,France,M,France,50,"TensorFlow, SQL, Deep Learning, MLOps, Spark",PhD,5,Transportation,2024-07-07,2024-09-04,1315,8.1,DataVision Ltd -AI03889,Data Scientist,261986,USD,261986,EX,PT,Israel,L,Israel,50,"Hadoop, Kubernetes, Java, R",PhD,12,Energy,2025-02-11,2025-03-07,2344,8.3,Machine Intelligence Group -AI03890,Principal Data Scientist,158894,AUD,214507,EX,PT,Australia,S,Austria,0,"Kubernetes, SQL, Linux, Java, PyTorch",PhD,15,Media,2024-04-21,2024-06-17,1938,5.8,Digital Transformation LLC -AI03891,Deep Learning Engineer,137974,EUR,117278,SE,CT,Austria,L,Hungary,50,"Docker, Scala, Hadoop, Git",PhD,6,Telecommunications,2024-08-29,2024-11-07,2039,6.1,Digital Transformation LLC -AI03892,Head of AI,90760,JPY,9983600,MI,CT,Japan,L,Japan,100,"Hadoop, Tableau, Docker",PhD,4,Education,2024-12-17,2025-02-13,1338,9.3,DeepTech Ventures -AI03893,Data Engineer,137606,SGD,178888,SE,CT,Singapore,L,Latvia,0,"GCP, Python, Mathematics, MLOps",Associate,6,Telecommunications,2024-08-24,2024-10-18,858,8.8,Future Systems -AI03894,Deep Learning Engineer,133207,EUR,113226,EX,FL,France,S,France,50,"SQL, Python, TensorFlow",Master,19,Government,2024-10-02,2024-11-27,629,8.3,Machine Intelligence Group -AI03895,AI Product Manager,100495,USD,100495,EX,FT,India,L,India,50,"PyTorch, MLOps, Java, NLP, Scala",PhD,10,Media,2025-03-12,2025-05-17,2399,6.6,Digital Transformation LLC -AI03896,AI Product Manager,91306,EUR,77610,MI,CT,Germany,S,Germany,0,"Tableau, Python, Hadoop, Mathematics",Master,2,Energy,2025-01-24,2025-02-15,2200,5.4,TechCorp Inc -AI03897,AI Specialist,331986,USD,331986,EX,PT,United States,L,Indonesia,0,"PyTorch, Mathematics, MLOps, SQL",Bachelor,11,Consulting,2024-11-18,2025-01-19,2486,5,Machine Intelligence Group -AI03898,AI Software Engineer,75194,EUR,63915,MI,CT,Germany,M,India,0,"Python, TensorFlow, Spark, Azure",PhD,4,Real Estate,2024-08-27,2024-10-07,610,8,Advanced Robotics -AI03899,AI Product Manager,89154,USD,89154,EN,PT,Denmark,M,Singapore,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Technology,2024-03-28,2024-05-28,1881,5.9,DataVision Ltd -AI03900,AI Consultant,64299,USD,64299,EN,PT,South Korea,M,South Korea,50,"Git, Data Visualization, TensorFlow",Bachelor,0,Transportation,2024-08-15,2024-09-18,683,7.8,TechCorp Inc -AI03901,AI Specialist,137294,EUR,116700,SE,FT,Germany,L,Germany,100,"GCP, TensorFlow, MLOps, Mathematics, SQL",Bachelor,8,Government,2024-06-10,2024-07-30,1946,6.4,TechCorp Inc -AI03902,Data Scientist,101275,USD,101275,MI,FL,Ireland,M,Ireland,0,"Git, Kubernetes, Computer Vision, Deep Learning",Associate,2,Technology,2025-01-30,2025-03-29,795,8.7,Cloud AI Solutions -AI03903,Autonomous Systems Engineer,139984,USD,139984,MI,PT,United States,L,United States,100,"Spark, SQL, Mathematics, Docker, Deep Learning",PhD,2,Retail,2024-02-09,2024-04-11,930,8.9,Future Systems -AI03904,Deep Learning Engineer,151316,EUR,128619,EX,FL,France,S,United States,100,"Hadoop, SQL, Deep Learning",Master,12,Consulting,2025-01-04,2025-02-25,2299,6.4,Advanced Robotics -AI03905,NLP Engineer,84471,USD,84471,EN,PT,Denmark,M,Ireland,100,"Python, Git, GCP, Spark",Master,1,Finance,2024-05-14,2024-06-24,796,5.6,AI Innovations -AI03906,Data Engineer,104379,GBP,78284,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Statistics, R, PyTorch",Bachelor,5,Transportation,2024-02-03,2024-03-11,2366,6.3,Machine Intelligence Group -AI03907,Principal Data Scientist,252832,USD,252832,EX,PT,Denmark,S,Denmark,50,"Scala, TensorFlow, Tableau",PhD,10,Energy,2024-10-14,2024-12-24,1983,8.7,Cognitive Computing -AI03908,Machine Learning Researcher,214285,EUR,182142,EX,FT,Germany,L,Chile,100,"Git, Azure, Data Visualization, R, Computer Vision",Master,17,Manufacturing,2024-05-17,2024-07-20,1999,9.6,DataVision Ltd -AI03909,Data Engineer,100489,USD,100489,EN,CT,Norway,L,Norway,100,"Kubernetes, MLOps, SQL, TensorFlow, R",Associate,0,Automotive,2024-10-22,2024-11-30,1403,7.7,AI Innovations -AI03910,Research Scientist,116902,AUD,157818,SE,FT,Australia,M,Australia,50,"GCP, Mathematics, Data Visualization",PhD,8,Real Estate,2024-07-04,2024-08-06,739,6,DataVision Ltd -AI03911,Data Scientist,98004,USD,98004,EN,PT,Norway,M,Israel,0,"Git, AWS, GCP, Deep Learning, Docker",Master,1,Telecommunications,2024-07-22,2024-09-24,2303,6.7,Machine Intelligence Group -AI03912,ML Ops Engineer,216802,USD,216802,EX,FL,United States,S,United States,50,"Python, TensorFlow, Tableau, PyTorch, Azure",PhD,15,Education,2025-03-11,2025-04-21,869,6,Smart Analytics -AI03913,Principal Data Scientist,97639,USD,97639,MI,FT,Sweden,M,United States,50,"Python, TensorFlow, Spark",Master,4,Energy,2024-12-15,2025-02-15,1662,8.8,Quantum Computing Inc -AI03914,AI Specialist,112321,USD,112321,MI,CT,Israel,L,Israel,0,"Mathematics, GCP, Computer Vision, TensorFlow, Spark",PhD,4,Gaming,2024-02-11,2024-03-21,2160,6,Predictive Systems -AI03915,Data Engineer,192260,AUD,259551,EX,FT,Australia,S,Finland,0,"Tableau, MLOps, GCP, Scala",Bachelor,18,Automotive,2024-10-04,2024-12-14,1151,9.4,Quantum Computing Inc -AI03916,Head of AI,109993,AUD,148491,MI,PT,Australia,L,Australia,50,"SQL, Linux, AWS",Associate,4,Telecommunications,2024-02-06,2024-04-12,1361,8.9,Autonomous Tech -AI03917,AI Product Manager,65943,USD,65943,MI,FL,Sweden,S,Sweden,50,"Python, Kubernetes, Java, Hadoop",Master,2,Finance,2024-08-26,2024-10-09,861,9.3,DeepTech Ventures -AI03918,AI Software Engineer,90867,SGD,118127,MI,PT,Singapore,M,Singapore,100,"SQL, Scala, GCP, Kubernetes, Tableau",Associate,3,Education,2024-11-22,2024-12-23,1269,9.5,DataVision Ltd -AI03919,ML Ops Engineer,84856,USD,84856,EX,FT,India,M,India,100,"AWS, Azure, Spark, Data Visualization, Deep Learning",Bachelor,13,Automotive,2025-03-16,2025-05-05,1793,9.5,Future Systems -AI03920,Data Analyst,171549,EUR,145817,EX,FT,France,M,South Africa,0,"Spark, Linux, Tableau, TensorFlow, Data Visualization",Bachelor,11,Manufacturing,2024-08-12,2024-09-15,1377,5.2,AI Innovations -AI03921,AI Research Scientist,191772,EUR,163006,EX,FL,Germany,M,Thailand,0,"Docker, Statistics, Scala, Kubernetes",Bachelor,19,Telecommunications,2024-07-22,2024-08-14,1912,8.4,Advanced Robotics -AI03922,Robotics Engineer,111326,USD,111326,SE,FT,Ireland,S,Ireland,100,"Computer Vision, SQL, Git, Deep Learning, GCP",Bachelor,6,Retail,2024-08-17,2024-09-16,565,7.3,Cognitive Computing -AI03923,Robotics Engineer,180543,JPY,19859730,EX,CT,Japan,M,Japan,50,"SQL, Deep Learning, Python, NLP",Associate,16,Transportation,2024-06-26,2024-07-13,1493,7.1,Predictive Systems -AI03924,AI Research Scientist,35560,USD,35560,EN,FT,China,M,China,50,"Kubernetes, Azure, Python, Deep Learning",Bachelor,1,Energy,2024-06-21,2024-08-09,983,5.7,Future Systems -AI03925,AI Software Engineer,80024,USD,80024,SE,PT,China,L,China,0,"Hadoop, Linux, Data Visualization",PhD,8,Manufacturing,2024-06-06,2024-06-23,1425,10,Machine Intelligence Group -AI03926,AI Architect,62790,USD,62790,EN,PT,Finland,M,Norway,100,"Python, TensorFlow, AWS, Docker",Master,1,Healthcare,2024-09-01,2024-11-12,1164,8.4,Advanced Robotics -AI03927,NLP Engineer,172119,USD,172119,SE,FT,Norway,M,Norway,0,"MLOps, Mathematics, Tableau, Docker, Azure",Associate,5,Finance,2024-03-05,2024-03-20,727,5.8,Quantum Computing Inc -AI03928,AI Software Engineer,144594,USD,144594,EX,FT,Finland,S,Finland,100,"PyTorch, Python, Azure",Associate,14,Finance,2025-04-30,2025-06-24,1107,6.8,Algorithmic Solutions -AI03929,Autonomous Systems Engineer,59241,EUR,50355,EN,FL,France,S,France,50,"Git, PyTorch, Hadoop, Azure, Deep Learning",Bachelor,0,Transportation,2024-01-30,2024-03-19,2005,9.1,Neural Networks Co -AI03930,Research Scientist,114166,EUR,97041,SE,CT,Netherlands,M,Netherlands,0,"SQL, GCP, NLP, Statistics",Bachelor,9,Media,2024-03-05,2024-04-15,2009,6.8,Cloud AI Solutions -AI03931,AI Product Manager,32706,USD,32706,EN,CT,China,S,Hungary,0,"Hadoop, R, SQL",PhD,1,Manufacturing,2024-03-07,2024-04-26,1525,8.4,Smart Analytics -AI03932,AI Research Scientist,120324,USD,120324,SE,FL,Sweden,M,Sweden,0,"PyTorch, TensorFlow, Tableau, SQL",PhD,8,Real Estate,2024-08-24,2024-10-08,1364,8.8,Algorithmic Solutions -AI03933,NLP Engineer,59232,CAD,74040,EN,PT,Canada,L,Austria,50,"Java, Computer Vision, Mathematics, Hadoop",Master,0,Manufacturing,2025-01-16,2025-03-22,1616,8.4,Neural Networks Co -AI03934,AI Architect,221142,CHF,199028,EX,PT,Switzerland,M,Switzerland,50,"PyTorch, Statistics, TensorFlow",Associate,18,Real Estate,2025-02-25,2025-03-29,1739,5.6,Neural Networks Co -AI03935,Research Scientist,48487,USD,48487,EN,CT,Israel,S,Israel,50,"Mathematics, AWS, Data Visualization, Azure, Git",Associate,1,Manufacturing,2025-03-07,2025-04-18,1412,7.8,DeepTech Ventures -AI03936,Machine Learning Researcher,145495,SGD,189144,SE,FT,Singapore,M,Singapore,0,"NLP, Hadoop, Linux",Bachelor,8,Healthcare,2024-10-25,2024-12-07,1094,5,Algorithmic Solutions -AI03937,Autonomous Systems Engineer,64092,SGD,83320,EN,FL,Singapore,L,Kenya,50,"Kubernetes, SQL, Spark, Python, Statistics",Associate,0,Consulting,2024-10-11,2024-12-15,779,7.3,Predictive Systems -AI03938,Data Analyst,135974,USD,135974,SE,CT,Denmark,S,Kenya,0,"Hadoop, Tableau, Python, Mathematics",Master,9,Education,2024-11-09,2024-12-31,2321,7.6,Quantum Computing Inc -AI03939,AI Product Manager,215605,USD,215605,EX,FL,Israel,M,Israel,0,"Java, R, SQL",Master,12,Technology,2024-12-16,2025-01-26,1940,5.6,Predictive Systems -AI03940,Principal Data Scientist,109621,USD,109621,MI,PT,United States,L,Singapore,0,"SQL, AWS, Git, MLOps, GCP",Bachelor,2,Energy,2024-12-20,2025-01-05,849,9.8,Future Systems -AI03941,AI Specialist,155788,USD,155788,SE,FT,United States,S,United States,0,"SQL, Data Visualization, Scala, Azure, Linux",Associate,6,Gaming,2024-06-07,2024-07-29,2489,7.7,Autonomous Tech -AI03942,Research Scientist,114493,USD,114493,SE,FT,Israel,L,Luxembourg,0,"Spark, NLP, Python, Deep Learning",Associate,9,Manufacturing,2024-06-22,2024-07-06,1482,6.2,Digital Transformation LLC -AI03943,AI Architect,127669,EUR,108519,SE,FT,Germany,S,Finland,100,"Mathematics, Kubernetes, Statistics, GCP, Tableau",Master,7,Government,2025-04-23,2025-07-03,1199,8.5,TechCorp Inc -AI03944,Machine Learning Engineer,184048,SGD,239262,EX,CT,Singapore,M,Singapore,0,"TensorFlow, R, Azure, GCP, Hadoop",Master,11,Technology,2024-01-24,2024-02-10,924,6.6,Algorithmic Solutions -AI03945,Machine Learning Engineer,62821,USD,62821,MI,FL,Finland,S,Finland,100,"Python, Linux, Scala, Kubernetes, TensorFlow",PhD,2,Transportation,2025-04-04,2025-05-30,1805,7.6,Autonomous Tech -AI03946,Data Analyst,116061,USD,116061,MI,FL,Norway,M,Norway,50,"Scala, Statistics, Python, Git",PhD,2,Gaming,2024-05-07,2024-07-11,1188,9.5,Predictive Systems -AI03947,Deep Learning Engineer,68069,JPY,7487590,EN,CT,Japan,M,Japan,100,"Docker, R, Deep Learning, Statistics, Mathematics",PhD,1,Consulting,2024-10-10,2024-10-31,2039,8.5,Future Systems -AI03948,ML Ops Engineer,55034,USD,55034,EN,FL,South Korea,S,Czech Republic,100,"R, GCP, Statistics, SQL, Tableau",Bachelor,1,Media,2024-09-27,2024-11-07,1092,8.6,Advanced Robotics -AI03949,AI Product Manager,197089,EUR,167526,EX,FT,Germany,M,Germany,100,"Hadoop, TensorFlow, Tableau, Data Visualization, Kubernetes",Bachelor,13,Government,2024-04-28,2024-06-26,1527,9,Quantum Computing Inc -AI03950,Data Analyst,63965,EUR,54370,EN,FL,Austria,S,Austria,100,"SQL, Spark, PyTorch, AWS, Java",Master,1,Consulting,2024-11-17,2024-12-02,1541,9.2,Cognitive Computing -AI03951,Research Scientist,88359,CHF,79523,EN,FT,Switzerland,S,Switzerland,100,"TensorFlow, Python, NLP",Associate,0,Real Estate,2024-11-04,2024-11-19,1376,6.4,Machine Intelligence Group -AI03952,ML Ops Engineer,58746,USD,58746,EN,CT,Ireland,S,Ireland,50,"SQL, Python, NLP, Scala, Git",Associate,1,Retail,2024-10-16,2024-11-21,748,9,Future Systems -AI03953,ML Ops Engineer,84148,USD,84148,EX,FT,China,M,China,50,"Tableau, PyTorch, Azure, Linux, NLP",Bachelor,17,Retail,2024-08-26,2024-11-05,1420,5.2,Neural Networks Co -AI03954,Machine Learning Engineer,106957,CHF,96261,EN,FL,Switzerland,M,Switzerland,50,"R, PyTorch, Computer Vision",Master,1,Healthcare,2024-11-27,2024-12-12,1030,6.4,Future Systems -AI03955,Autonomous Systems Engineer,83304,CAD,104130,MI,PT,Canada,S,Denmark,50,"GCP, Scala, Data Visualization, TensorFlow",PhD,3,Education,2024-03-30,2024-05-01,943,6.3,TechCorp Inc -AI03956,Principal Data Scientist,169228,USD,169228,EX,FL,United States,M,United States,100,"Python, Azure, Mathematics",Bachelor,10,Education,2024-04-02,2024-05-11,1923,9.7,TechCorp Inc -AI03957,Deep Learning Engineer,87246,CAD,109058,MI,CT,Canada,S,Nigeria,50,"Deep Learning, Python, Mathematics, MLOps",Master,3,Gaming,2024-05-01,2024-06-26,916,9.4,DataVision Ltd -AI03958,Research Scientist,71057,GBP,53293,EN,PT,United Kingdom,M,United Kingdom,100,"Python, PyTorch, Kubernetes, Azure, SQL",PhD,0,Retail,2024-03-04,2024-05-13,1746,7.6,AI Innovations -AI03959,Data Engineer,197354,CAD,246693,EX,CT,Canada,M,Mexico,50,"SQL, R, Tableau, Statistics, Scala",Associate,11,Energy,2024-01-30,2024-03-18,2412,8.8,DeepTech Ventures -AI03960,Research Scientist,128498,USD,128498,EX,FL,Israel,S,China,0,"Mathematics, SQL, Linux",Bachelor,15,Technology,2024-04-29,2024-06-08,1531,9,Advanced Robotics -AI03961,AI Architect,186865,USD,186865,SE,CT,Denmark,L,Denmark,0,"TensorFlow, Azure, NLP, Git, SQL",Master,8,Telecommunications,2024-11-07,2024-12-21,1088,5.3,Quantum Computing Inc -AI03962,AI Research Scientist,107253,USD,107253,MI,FT,United States,M,Russia,100,"Linux, Computer Vision, Python, Data Visualization, Git",PhD,2,Automotive,2024-01-25,2024-03-27,2074,9.8,TechCorp Inc -AI03963,NLP Engineer,63687,USD,63687,MI,FL,Israel,S,Israel,50,"Computer Vision, Kubernetes, SQL, Deep Learning",PhD,4,Education,2024-07-18,2024-09-05,1291,9.5,Neural Networks Co -AI03964,Principal Data Scientist,79216,USD,79216,MI,FT,Israel,S,Israel,100,"PyTorch, Linux, Data Visualization",Associate,2,Education,2024-06-12,2024-07-20,1511,6,Autonomous Tech -AI03965,Data Scientist,231383,USD,231383,EX,FT,Israel,L,Israel,0,"GCP, TensorFlow, Scala, Python, Data Visualization",Master,11,Technology,2024-02-21,2024-04-07,2362,8.9,Smart Analytics -AI03966,Data Engineer,43977,USD,43977,SE,PT,India,S,Sweden,100,"Scala, Data Visualization, Tableau, Java",Bachelor,9,Automotive,2025-04-22,2025-05-15,1455,8.7,DeepTech Ventures -AI03967,Principal Data Scientist,58328,USD,58328,SE,FT,China,M,China,50,"Data Visualization, Scala, Linux, Java",Bachelor,8,Telecommunications,2024-10-09,2024-12-13,860,6.6,DataVision Ltd -AI03968,Machine Learning Engineer,26547,USD,26547,EN,PT,India,L,Turkey,0,"Python, Azure, SQL, Computer Vision",Master,1,Finance,2025-04-01,2025-05-25,976,7.8,TechCorp Inc -AI03969,Autonomous Systems Engineer,55423,USD,55423,EN,CT,South Korea,S,Australia,0,"Docker, SQL, Java, PyTorch, Linux",Master,0,Real Estate,2024-12-12,2025-01-12,1325,7,Advanced Robotics -AI03970,Machine Learning Engineer,24833,USD,24833,MI,FT,India,S,Mexico,0,"R, SQL, Data Visualization",Master,3,Media,2024-12-20,2025-03-03,2055,9.3,Advanced Robotics -AI03971,Principal Data Scientist,110197,USD,110197,MI,FL,United States,M,United States,100,"R, PyTorch, Scala",PhD,3,Real Estate,2025-01-02,2025-03-01,1672,8.7,Machine Intelligence Group -AI03972,AI Architect,72964,USD,72964,EN,FL,Israel,M,Ukraine,100,"AWS, Spark, MLOps, Scala",Associate,0,Government,2024-03-07,2024-04-04,2318,9.2,AI Innovations -AI03973,Robotics Engineer,59921,USD,59921,EN,CT,Sweden,M,Spain,50,"Data Visualization, Python, TensorFlow, Docker, Statistics",Bachelor,1,Finance,2024-11-02,2025-01-11,1707,8.4,Smart Analytics -AI03974,AI Software Engineer,56383,EUR,47926,EN,CT,Austria,S,Argentina,100,"Azure, AWS, NLP, Spark",PhD,0,Telecommunications,2024-12-05,2025-02-15,1841,8.8,Digital Transformation LLC -AI03975,AI Specialist,71225,USD,71225,EX,FL,India,S,India,0,"Git, MLOps, Deep Learning, Python",Master,19,Government,2024-10-14,2024-11-01,987,6.9,Cloud AI Solutions -AI03976,AI Consultant,64188,USD,64188,EN,CT,Sweden,M,Sweden,50,"Statistics, Hadoop, R, TensorFlow",Bachelor,1,Consulting,2024-06-04,2024-06-26,1597,7.2,AI Innovations -AI03977,Machine Learning Researcher,111850,USD,111850,MI,FT,Norway,S,Norway,0,"MLOps, Python, TensorFlow",PhD,2,Real Estate,2024-02-25,2024-03-21,2475,6.4,Algorithmic Solutions -AI03978,Machine Learning Engineer,193873,EUR,164792,EX,FT,Netherlands,M,Netherlands,0,"Scala, Kubernetes, Deep Learning, Java",Master,12,Real Estate,2024-11-10,2025-01-11,2444,8.6,Machine Intelligence Group -AI03979,Head of AI,69980,USD,69980,EX,CT,China,M,China,50,"Mathematics, PyTorch, Statistics, Kubernetes, Hadoop",PhD,17,Technology,2024-01-03,2024-02-05,1838,8.5,Future Systems -AI03980,AI Specialist,17744,USD,17744,EN,FT,India,S,Kenya,0,"AWS, Git, NLP",Master,1,Media,2025-03-11,2025-04-09,1086,7.8,DeepTech Ventures -AI03981,Research Scientist,55353,EUR,47050,EN,PT,France,L,France,100,"PyTorch, TensorFlow, Java, SQL, Mathematics",Associate,0,Consulting,2024-10-17,2024-12-10,1210,8.2,Neural Networks Co -AI03982,AI Specialist,29786,USD,29786,EN,PT,China,M,Latvia,50,"Spark, Statistics, Data Visualization",Bachelor,0,Telecommunications,2024-11-17,2025-01-19,2453,7.3,Advanced Robotics -AI03983,Machine Learning Researcher,75425,EUR,64111,MI,FT,France,M,France,100,"Python, Kubernetes, Deep Learning, Hadoop, R",Master,4,Telecommunications,2025-01-06,2025-02-04,1488,9.1,DeepTech Ventures -AI03984,Data Engineer,154886,EUR,131653,EX,FT,Austria,S,Australia,0,"Git, SQL, Python",Master,13,Gaming,2024-03-04,2024-04-17,2028,9.6,Advanced Robotics -AI03985,Data Engineer,99073,CAD,123841,SE,FT,Canada,M,Canada,0,"Git, Kubernetes, SQL, PyTorch, Hadoop",PhD,9,Automotive,2025-03-07,2025-04-25,1381,6.4,Quantum Computing Inc -AI03986,Head of AI,73454,EUR,62436,EN,FT,France,M,France,0,"Azure, Java, Docker",Bachelor,0,Telecommunications,2024-02-04,2024-02-29,2135,8.8,DataVision Ltd -AI03987,AI Consultant,59838,USD,59838,SE,CT,China,S,China,100,"Kubernetes, PyTorch, Linux, Computer Vision, MLOps",Associate,9,Government,2024-10-19,2024-12-31,2206,7.2,TechCorp Inc -AI03988,AI Consultant,87537,USD,87537,MI,FT,Israel,M,South Korea,0,"Java, Scala, Deep Learning, Azure",Master,2,Energy,2025-02-28,2025-04-22,2433,8.3,Predictive Systems -AI03989,AI Architect,26899,USD,26899,EN,CT,India,M,Estonia,0,"Scala, NLP, Docker",Master,0,Healthcare,2024-05-09,2024-07-19,1252,5.6,DataVision Ltd -AI03990,AI Architect,89970,USD,89970,SE,PT,South Korea,S,Germany,0,"R, MLOps, AWS",Bachelor,7,Telecommunications,2024-11-08,2025-01-03,809,5.6,Cognitive Computing -AI03991,Deep Learning Engineer,135427,USD,135427,SE,FL,Finland,L,Finland,50,"Java, GCP, Scala",PhD,6,Government,2025-03-24,2025-05-14,1411,6.9,Machine Intelligence Group -AI03992,NLP Engineer,55414,EUR,47102,EN,PT,Austria,M,Latvia,0,"Hadoop, Python, Spark, TensorFlow",PhD,0,Transportation,2025-01-27,2025-02-21,977,8.9,DataVision Ltd -AI03993,AI Architect,214757,CHF,193281,SE,CT,Switzerland,M,Switzerland,100,"Tableau, TensorFlow, Kubernetes, Azure",PhD,8,Energy,2024-08-26,2024-09-11,2055,8.7,Cloud AI Solutions -AI03994,AI Specialist,165695,USD,165695,SE,FL,United States,M,United States,50,"MLOps, Kubernetes, Deep Learning, Git",Associate,5,Finance,2025-02-24,2025-04-26,1087,7.7,Algorithmic Solutions -AI03995,AI Research Scientist,88990,USD,88990,EN,CT,Denmark,M,Denmark,50,"Python, TensorFlow, AWS",Master,0,Government,2025-02-19,2025-03-07,697,5.4,Advanced Robotics -AI03996,Head of AI,74202,GBP,55652,EN,FT,United Kingdom,M,United Kingdom,0,"Python, Kubernetes, GCP, Spark",Associate,1,Consulting,2025-01-24,2025-03-26,1970,6.7,Cognitive Computing -AI03997,Computer Vision Engineer,127421,USD,127421,EX,FT,Finland,S,Netherlands,100,"SQL, Docker, Tableau, PyTorch",Master,11,Healthcare,2024-04-12,2024-04-29,920,9.1,DeepTech Ventures -AI03998,Computer Vision Engineer,278984,CHF,251086,EX,PT,Switzerland,L,Austria,0,"Python, TensorFlow, MLOps, GCP, Data Visualization",Master,14,Finance,2024-02-11,2024-03-09,595,6.2,Smart Analytics -AI03999,Autonomous Systems Engineer,158896,USD,158896,SE,FT,Norway,S,Norway,0,"Data Visualization, Tableau, Hadoop, MLOps",Master,9,Technology,2024-03-19,2024-05-23,541,5.4,TechCorp Inc -AI04000,Robotics Engineer,135260,USD,135260,MI,FT,United States,L,United States,0,"Scala, Python, Hadoop, TensorFlow",PhD,2,Consulting,2024-01-29,2024-02-19,1479,5.3,TechCorp Inc -AI04001,AI Architect,75021,EUR,63768,MI,FT,Austria,S,Colombia,50,"Java, R, Data Visualization, NLP",Bachelor,2,Government,2024-02-01,2024-03-04,1164,9.1,Machine Intelligence Group -AI04002,Head of AI,154992,EUR,131743,EX,FL,Austria,S,Austria,50,"Linux, Git, Spark",Associate,19,Automotive,2025-03-28,2025-04-22,1595,6.9,DataVision Ltd -AI04003,Robotics Engineer,190121,JPY,20913310,EX,FL,Japan,L,Japan,100,"Git, Linux, Deep Learning",PhD,11,Government,2024-04-16,2024-06-21,1539,7.5,Predictive Systems -AI04004,Machine Learning Engineer,385410,CHF,346869,EX,FL,Switzerland,L,Switzerland,0,"Data Visualization, Java, GCP",Bachelor,16,Real Estate,2024-12-18,2025-01-04,849,5.5,Cognitive Computing -AI04005,Computer Vision Engineer,100524,USD,100524,SE,FT,Israel,S,Chile,50,"TensorFlow, Hadoop, Kubernetes",Master,5,Real Estate,2025-03-09,2025-05-15,1296,7.4,DeepTech Ventures -AI04006,Machine Learning Researcher,277819,USD,277819,EX,PT,Denmark,M,Denmark,100,"Data Visualization, Python, SQL, Hadoop",Master,14,Gaming,2025-03-22,2025-05-02,1616,9.1,Autonomous Tech -AI04007,NLP Engineer,65703,AUD,88699,EN,FL,Australia,S,Australia,50,"Hadoop, TensorFlow, Python, NLP",Associate,1,Finance,2024-01-21,2024-03-02,532,8.9,Machine Intelligence Group -AI04008,Data Scientist,132522,EUR,112644,SE,FT,France,L,France,50,"Scala, PyTorch, Java, Deep Learning, Mathematics",PhD,6,Transportation,2024-04-13,2024-06-10,1844,7.3,TechCorp Inc -AI04009,Autonomous Systems Engineer,165364,EUR,140559,EX,FL,France,S,France,0,"Computer Vision, Tableau, Hadoop, R, Deep Learning",Master,11,Transportation,2025-04-07,2025-06-14,1602,5.7,Digital Transformation LLC -AI04010,Principal Data Scientist,106407,AUD,143649,SE,CT,Australia,S,Australia,0,"PyTorch, Hadoop, SQL, Azure",PhD,9,Technology,2024-08-07,2024-09-11,1007,5.1,Predictive Systems -AI04011,Autonomous Systems Engineer,72285,JPY,7951350,EN,CT,Japan,M,Turkey,50,"Python, Spark, Hadoop, Computer Vision, TensorFlow",Bachelor,0,Education,2024-02-16,2024-03-17,2400,6.7,Algorithmic Solutions -AI04012,Principal Data Scientist,105498,USD,105498,SE,FT,Finland,S,Finland,0,"Linux, R, Statistics, SQL, Java",Associate,8,Telecommunications,2024-03-20,2024-05-17,1901,9.7,DeepTech Ventures -AI04013,Autonomous Systems Engineer,93513,EUR,79486,MI,CT,Netherlands,S,Netherlands,50,"R, Python, Tableau, Git",Bachelor,3,Energy,2024-10-14,2024-11-17,915,7.7,Cognitive Computing -AI04014,Data Scientist,56370,USD,56370,EN,PT,Finland,M,Finland,0,"MLOps, Python, Docker",PhD,0,Real Estate,2024-02-08,2024-03-27,722,7.5,Future Systems -AI04015,Computer Vision Engineer,111901,EUR,95116,MI,FT,France,L,Indonesia,50,"Scala, Linux, Java, Git, Statistics",Associate,2,Healthcare,2025-03-14,2025-04-07,750,9.7,Cognitive Computing -AI04016,AI Product Manager,250059,USD,250059,EX,CT,Denmark,S,Denmark,0,"Python, TensorFlow, Hadoop, Mathematics, Computer Vision",Associate,18,Telecommunications,2024-09-18,2024-10-22,2174,6.3,Neural Networks Co -AI04017,Research Scientist,273161,USD,273161,EX,CT,Denmark,M,Switzerland,50,"PyTorch, Tableau, Deep Learning, Statistics",Bachelor,19,Consulting,2024-11-21,2024-12-06,612,5.3,Quantum Computing Inc -AI04018,Data Engineer,132189,EUR,112361,SE,FL,Germany,S,Estonia,100,"Linux, Data Visualization, Scala",Master,8,Education,2025-01-23,2025-03-28,1573,6.8,Autonomous Tech -AI04019,AI Architect,66589,EUR,56601,EN,PT,Germany,M,Germany,50,"Linux, Java, NLP",Associate,0,Real Estate,2024-04-14,2024-05-18,1587,9.5,Smart Analytics -AI04020,Data Analyst,60676,EUR,51575,EN,FL,France,M,Singapore,0,"Computer Vision, GCP, Python, Spark, TensorFlow",Bachelor,0,Education,2024-05-27,2024-06-23,1379,8.3,Quantum Computing Inc -AI04021,Principal Data Scientist,109570,CAD,136963,SE,CT,Canada,M,Romania,0,"GCP, Azure, Data Visualization, AWS",PhD,9,Government,2024-12-17,2025-01-15,2415,5.9,DeepTech Ventures -AI04022,Machine Learning Engineer,58052,USD,58052,EN,FT,Israel,S,France,50,"Git, Statistics, MLOps, Azure",Associate,1,Consulting,2024-08-18,2024-10-19,1438,7.2,DeepTech Ventures -AI04023,AI Research Scientist,98945,EUR,84103,MI,FL,Austria,M,Austria,0,"MLOps, PyTorch, Git, AWS",Associate,3,Manufacturing,2024-12-06,2025-01-26,1831,9.1,Algorithmic Solutions -AI04024,AI Product Manager,199637,USD,199637,EX,CT,Israel,L,Israel,100,"Java, Linux, Hadoop",Bachelor,12,Consulting,2024-02-08,2024-02-24,2356,9.9,TechCorp Inc -AI04025,AI Software Engineer,78109,USD,78109,MI,PT,Finland,S,Finland,50,"NLP, Git, Hadoop, Docker",Master,4,Consulting,2024-04-07,2024-05-19,1816,8.6,Predictive Systems -AI04026,AI Software Engineer,73974,USD,73974,MI,FL,Israel,M,Malaysia,0,"Python, GCP, Tableau",Associate,4,Automotive,2024-03-20,2024-04-14,1538,6,Cloud AI Solutions -AI04027,AI Software Engineer,134116,EUR,113999,SE,PT,France,M,France,100,"NLP, SQL, MLOps",Bachelor,7,Manufacturing,2024-05-25,2024-06-16,832,5.2,Digital Transformation LLC -AI04028,Deep Learning Engineer,135851,USD,135851,SE,CT,Finland,L,Ghana,100,"Docker, AWS, Tableau, GCP, TensorFlow",Associate,7,Consulting,2024-09-21,2024-10-14,543,8.9,Digital Transformation LLC -AI04029,Deep Learning Engineer,142460,USD,142460,SE,PT,Ireland,M,Thailand,100,"Tableau, Statistics, Linux, Mathematics, Deep Learning",Master,5,Education,2024-04-02,2024-04-20,697,6.5,AI Innovations -AI04030,Head of AI,69316,USD,69316,EN,PT,Denmark,S,Japan,50,"SQL, Spark, GCP",Associate,0,Government,2024-04-05,2024-04-24,862,8.1,DataVision Ltd -AI04031,Deep Learning Engineer,82158,EUR,69834,EN,FT,France,L,France,50,"AWS, MLOps, SQL, PyTorch, Git",Associate,1,Retail,2024-05-17,2024-06-22,1467,5.6,Machine Intelligence Group -AI04032,AI Product Manager,167922,USD,167922,SE,PT,Ireland,L,Ireland,100,"SQL, AWS, MLOps",Master,5,Healthcare,2024-12-03,2024-12-24,824,9.4,Quantum Computing Inc -AI04033,NLP Engineer,142118,EUR,120800,SE,FL,Austria,L,Austria,100,"Python, Git, SQL, AWS",Associate,8,Manufacturing,2024-07-06,2024-08-18,1172,5.8,Cognitive Computing -AI04034,Deep Learning Engineer,215397,USD,215397,EX,FT,Israel,S,Israel,50,"Data Visualization, Statistics, Hadoop, Deep Learning, Docker",Associate,15,Retail,2024-10-07,2024-12-07,2434,7.6,Quantum Computing Inc -AI04035,Research Scientist,294594,CHF,265135,EX,FT,Switzerland,L,China,0,"Data Visualization, AWS, SQL, PyTorch, Java",Associate,10,Manufacturing,2024-06-23,2024-07-07,1111,5.5,TechCorp Inc -AI04036,AI Specialist,63057,USD,63057,EN,CT,United States,M,United States,50,"NLP, Scala, Data Visualization",Associate,1,Energy,2024-07-30,2024-08-27,2384,10,Cloud AI Solutions -AI04037,ML Ops Engineer,217874,EUR,185193,EX,FL,Austria,M,Portugal,100,"Java, Hadoop, Computer Vision, R, Python",Master,19,Education,2024-08-26,2024-10-09,2330,9.6,Smart Analytics -AI04038,Autonomous Systems Engineer,32792,USD,32792,SE,PT,India,S,India,50,"GCP, Python, SQL, R",Associate,8,Gaming,2024-10-05,2024-12-16,2354,7.7,Advanced Robotics -AI04039,ML Ops Engineer,116266,JPY,12789260,SE,CT,Japan,M,Japan,100,"Kubernetes, Linux, Data Visualization, NLP, Docker",PhD,7,Education,2025-02-08,2025-03-07,1459,6,Future Systems -AI04040,AI Research Scientist,70410,EUR,59849,EN,FL,Austria,L,Austria,50,"PyTorch, Kubernetes, Docker, TensorFlow",PhD,1,Technology,2024-11-11,2024-12-14,1600,5.3,DeepTech Ventures -AI04041,Data Analyst,56897,CAD,71121,EN,FL,Canada,L,Canada,100,"Java, MLOps, R",PhD,1,Consulting,2024-09-04,2024-09-27,2164,8.6,Cognitive Computing -AI04042,Autonomous Systems Engineer,135997,CHF,122397,MI,PT,Switzerland,S,Ghana,100,"Linux, Python, Kubernetes, MLOps, Data Visualization",Associate,3,Technology,2024-05-14,2024-07-09,1556,7.9,Cloud AI Solutions -AI04043,Machine Learning Engineer,50494,USD,50494,EN,FT,Israel,S,Israel,100,"Git, Tableau, PyTorch, Kubernetes, Spark",Associate,1,Media,2024-09-07,2024-10-01,2213,6,DataVision Ltd -AI04044,AI Research Scientist,144481,GBP,108361,EX,PT,United Kingdom,S,United Kingdom,0,"Git, Linux, Data Visualization, Azure",Bachelor,13,Retail,2024-10-06,2024-12-06,1779,5.1,DeepTech Ventures -AI04045,Principal Data Scientist,102340,USD,102340,MI,FT,Ireland,M,Ireland,50,"GCP, Computer Vision, Linux, Tableau",PhD,3,Retail,2024-06-04,2024-06-24,807,5.4,TechCorp Inc -AI04046,AI Research Scientist,289309,USD,289309,EX,FL,Denmark,S,Denmark,50,"Python, Azure, Tableau, Mathematics",Associate,19,Finance,2025-03-07,2025-04-25,557,7.2,Machine Intelligence Group -AI04047,AI Specialist,86564,GBP,64923,EN,PT,United Kingdom,L,United Kingdom,0,"Linux, Azure, TensorFlow",Associate,0,Education,2024-05-22,2024-06-30,2341,6.6,Cognitive Computing -AI04048,Computer Vision Engineer,105245,GBP,78934,MI,CT,United Kingdom,L,United Kingdom,0,"Spark, R, Computer Vision, Deep Learning, Python",Master,3,Government,2025-03-07,2025-04-04,2141,7.9,AI Innovations -AI04049,Principal Data Scientist,135249,USD,135249,EX,FT,Sweden,S,Sweden,100,"Mathematics, Git, Spark, SQL, PyTorch",Master,14,Energy,2024-09-23,2024-10-20,1386,8.8,Predictive Systems -AI04050,AI Research Scientist,351014,CHF,315913,EX,FT,Switzerland,L,Egypt,50,"Statistics, MLOps, Python, TensorFlow",Master,10,Consulting,2024-10-25,2024-12-13,922,5.8,Quantum Computing Inc -AI04051,Data Scientist,170313,GBP,127735,SE,PT,United Kingdom,L,United Kingdom,0,"Azure, Scala, Statistics, SQL, Deep Learning",Master,5,Gaming,2024-07-27,2024-08-29,1363,5.6,Algorithmic Solutions -AI04052,Autonomous Systems Engineer,96839,USD,96839,MI,FL,Israel,L,Israel,0,"Scala, Data Visualization, Computer Vision",Associate,3,Automotive,2025-02-16,2025-03-31,2388,9.8,DeepTech Ventures -AI04053,Machine Learning Engineer,112039,USD,112039,EX,CT,South Korea,M,South Korea,0,"TensorFlow, GCP, Scala",Bachelor,16,Finance,2024-10-01,2024-12-06,1359,5.5,Future Systems -AI04054,Autonomous Systems Engineer,161578,GBP,121184,SE,FL,United Kingdom,L,United Kingdom,50,"Python, Linux, Kubernetes, Git, GCP",PhD,9,Energy,2024-03-23,2024-04-19,538,8.7,Quantum Computing Inc -AI04055,Deep Learning Engineer,162342,USD,162342,SE,CT,United States,L,United States,0,"Deep Learning, SQL, Scala",Associate,7,Manufacturing,2025-03-11,2025-05-06,1837,6.3,Autonomous Tech -AI04056,AI Software Engineer,81152,CAD,101440,MI,FL,Canada,M,Indonesia,50,"Mathematics, Hadoop, SQL, Python, Data Visualization",Master,3,Media,2024-01-16,2024-03-15,1532,5.1,DeepTech Ventures -AI04057,Robotics Engineer,146791,EUR,124772,SE,PT,Germany,L,Germany,50,"MLOps, Git, Kubernetes",Bachelor,6,Media,2024-11-07,2024-12-21,661,6.9,Predictive Systems -AI04058,AI Architect,231457,SGD,300894,EX,FL,Singapore,M,Singapore,0,"Computer Vision, TensorFlow, Linux, Tableau",Associate,13,Manufacturing,2024-01-28,2024-03-28,671,6.5,Cognitive Computing -AI04059,Data Scientist,114857,EUR,97628,SE,PT,Austria,S,Argentina,0,"Python, TensorFlow, Tableau, NLP",Associate,7,Manufacturing,2024-06-26,2024-07-27,1809,9.5,Future Systems -AI04060,Computer Vision Engineer,73750,USD,73750,EX,CT,China,L,China,50,"Spark, PyTorch, SQL, Computer Vision",Associate,15,Gaming,2024-07-29,2024-09-12,1258,9.7,TechCorp Inc -AI04061,Data Engineer,87162,SGD,113311,EN,FL,Singapore,L,Singapore,50,"Computer Vision, Spark, Python, Scala",Bachelor,0,Real Estate,2024-10-20,2024-11-29,979,9.8,Autonomous Tech -AI04062,Machine Learning Engineer,85264,USD,85264,EX,CT,China,M,China,50,"Linux, Java, Docker, SQL, Git",Master,17,Education,2025-01-09,2025-02-11,1762,8.9,Digital Transformation LLC -AI04063,Principal Data Scientist,72355,CAD,90444,EN,FL,Canada,M,Canada,0,"Git, MLOps, Kubernetes, Hadoop",Associate,0,Energy,2024-11-15,2025-01-27,1357,5.3,TechCorp Inc -AI04064,ML Ops Engineer,83615,AUD,112880,MI,CT,Australia,S,Australia,50,"Git, Hadoop, Mathematics",Associate,4,Retail,2024-01-09,2024-02-05,2152,9.3,DataVision Ltd -AI04065,Machine Learning Researcher,201139,USD,201139,SE,FT,United States,L,Denmark,0,"Python, Azure, TensorFlow, Hadoop",PhD,8,Energy,2025-03-07,2025-04-17,2236,8.2,Digital Transformation LLC -AI04066,Research Scientist,227744,USD,227744,EX,FT,Denmark,M,Denmark,50,"Docker, Mathematics, R, SQL, Computer Vision",Bachelor,11,Media,2025-02-23,2025-04-26,656,9.3,Predictive Systems -AI04067,Research Scientist,50231,CAD,62789,EN,PT,Canada,M,Canada,100,"Scala, Spark, SQL, Mathematics",Associate,1,Media,2024-07-17,2024-07-31,572,7.1,Machine Intelligence Group -AI04068,Data Analyst,149410,EUR,126999,EX,FT,Austria,M,Austria,50,"Kubernetes, PyTorch, MLOps",PhD,15,Automotive,2024-04-20,2024-06-19,941,9.2,AI Innovations -AI04069,Data Engineer,322650,CHF,290385,EX,FL,Switzerland,S,Switzerland,50,"NLP, Linux, Python",PhD,18,Consulting,2024-07-24,2024-08-24,1900,6.3,Autonomous Tech -AI04070,Head of AI,138075,CAD,172594,SE,FL,Canada,L,Canada,50,"GCP, Kubernetes, Data Visualization, SQL",Bachelor,8,Technology,2025-03-05,2025-04-21,2390,6.1,Cloud AI Solutions -AI04071,Data Engineer,70492,USD,70492,MI,FL,South Korea,L,South Korea,0,"NLP, R, Kubernetes, Linux, TensorFlow",Bachelor,4,Media,2024-09-10,2024-11-05,1832,8.5,DataVision Ltd -AI04072,AI Architect,50946,USD,50946,EN,FT,South Korea,S,South Korea,0,"Deep Learning, Java, Computer Vision, AWS, Kubernetes",Associate,0,Transportation,2024-05-11,2024-07-06,1102,7.1,Autonomous Tech -AI04073,AI Architect,74567,JPY,8202370,EN,FT,Japan,M,Sweden,0,"TensorFlow, Linux, Python, SQL, AWS",Associate,1,Manufacturing,2024-02-19,2024-03-15,514,5.3,Cognitive Computing -AI04074,Machine Learning Engineer,63683,AUD,85972,EN,CT,Australia,L,Australia,100,"Python, NLP, GCP, Mathematics, Git",Associate,0,Government,2024-12-08,2025-01-07,1692,5.7,TechCorp Inc -AI04075,AI Product Manager,93281,USD,93281,EN,FT,United States,L,Ukraine,100,"Hadoop, Python, Azure, Spark, Statistics",Bachelor,1,Technology,2024-08-20,2024-10-15,1066,6.7,Cloud AI Solutions -AI04076,Deep Learning Engineer,86606,CAD,108258,MI,PT,Canada,S,Ireland,0,"Docker, Scala, Linux",Bachelor,3,Media,2024-05-08,2024-06-29,573,6.2,Smart Analytics -AI04077,AI Software Engineer,114314,EUR,97167,SE,CT,France,M,France,100,"Azure, Git, Hadoop, Data Visualization, Mathematics",PhD,7,Media,2024-09-26,2024-11-11,743,5.1,AI Innovations -AI04078,Machine Learning Researcher,44105,USD,44105,SE,PT,India,L,India,0,"Java, Hadoop, MLOps",PhD,6,Retail,2024-07-10,2024-09-01,724,5.7,Future Systems -AI04079,AI Specialist,87807,EUR,74636,MI,FT,Austria,L,Austria,50,"PyTorch, Git, Java, Scala, TensorFlow",Bachelor,3,Automotive,2024-03-30,2024-04-19,2006,7.2,AI Innovations -AI04080,Principal Data Scientist,105998,AUD,143097,MI,FT,Australia,L,Australia,100,"Spark, Tableau, GCP, Linux, Hadoop",Bachelor,4,Energy,2024-09-05,2024-11-16,1627,7.3,Cloud AI Solutions -AI04081,Deep Learning Engineer,205845,CHF,185261,SE,CT,Switzerland,M,Portugal,0,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Associate,9,Telecommunications,2024-03-05,2024-04-06,2211,8.5,Machine Intelligence Group -AI04082,AI Architect,108031,SGD,140440,SE,CT,Singapore,S,Singapore,50,"Mathematics, Azure, PyTorch",Associate,6,Manufacturing,2024-09-20,2024-10-30,1358,9.2,DeepTech Ventures -AI04083,AI Consultant,43599,USD,43599,MI,PT,China,S,China,50,"MLOps, R, TensorFlow, SQL, GCP",Associate,4,Media,2024-02-23,2024-05-01,2059,6.4,Quantum Computing Inc -AI04084,Data Scientist,100782,GBP,75587,MI,FL,United Kingdom,S,United Kingdom,100,"Mathematics, R, SQL, Spark",Bachelor,3,Manufacturing,2025-02-21,2025-04-09,2245,9.9,Algorithmic Solutions -AI04085,Autonomous Systems Engineer,124064,SGD,161283,SE,PT,Singapore,S,Israel,50,"Java, Scala, NLP, Azure",PhD,8,Gaming,2024-12-25,2025-02-16,1257,7.4,DataVision Ltd -AI04086,Head of AI,32020,USD,32020,EN,FL,China,L,China,100,"SQL, Hadoop, PyTorch, Linux",Associate,1,Media,2024-01-09,2024-01-30,878,8.5,Algorithmic Solutions -AI04087,Machine Learning Engineer,88815,USD,88815,MI,FL,Finland,M,Finland,50,"Linux, Java, Git, Mathematics, NLP",Bachelor,3,Finance,2024-08-21,2024-10-25,2150,6.1,Digital Transformation LLC -AI04088,Data Analyst,102567,CHF,92310,MI,FT,Switzerland,M,Switzerland,50,"Hadoop, Python, PyTorch",Master,4,Consulting,2025-01-14,2025-03-03,1066,7.6,Predictive Systems -AI04089,Computer Vision Engineer,72234,USD,72234,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, SQL, Python, Kubernetes",Associate,1,Telecommunications,2024-03-08,2024-05-01,1659,9.1,Algorithmic Solutions -AI04090,NLP Engineer,284726,CHF,256253,EX,FL,Switzerland,M,Italy,0,"Python, PyTorch, TensorFlow",Master,15,Gaming,2025-02-28,2025-05-07,697,6.5,Algorithmic Solutions -AI04091,Principal Data Scientist,103801,EUR,88231,MI,CT,Netherlands,M,Russia,50,"NLP, AWS, Linux, Statistics, Computer Vision",Master,3,Telecommunications,2025-02-22,2025-03-08,1806,5.2,Neural Networks Co -AI04092,AI Specialist,211598,EUR,179858,EX,FT,Germany,L,Israel,50,"TensorFlow, Scala, Hadoop, Deep Learning, PyTorch",Master,10,Manufacturing,2024-11-18,2025-01-20,1067,6.5,Cloud AI Solutions -AI04093,Principal Data Scientist,65479,GBP,49109,EN,CT,United Kingdom,M,Portugal,50,"GCP, Kubernetes, SQL",Associate,1,Manufacturing,2024-08-06,2024-10-05,2120,8.9,DataVision Ltd -AI04094,ML Ops Engineer,55701,CAD,69626,EN,CT,Canada,S,Canada,50,"Azure, PyTorch, Git",Associate,1,Energy,2024-10-09,2024-12-21,1684,9,TechCorp Inc -AI04095,Machine Learning Researcher,265222,CHF,238700,EX,CT,Switzerland,S,Switzerland,0,"Git, Azure, Spark, Mathematics, AWS",Master,14,Gaming,2025-03-09,2025-03-27,1418,9.8,TechCorp Inc -AI04096,NLP Engineer,33734,USD,33734,MI,FT,China,S,China,50,"R, SQL, NLP, Azure",Associate,4,Gaming,2024-04-27,2024-06-29,964,7.2,Smart Analytics -AI04097,AI Software Engineer,69684,USD,69684,MI,FT,South Korea,S,Spain,50,"Git, R, Tableau, SQL",Bachelor,3,Energy,2025-02-01,2025-03-03,850,7.1,Future Systems -AI04098,AI Specialist,96701,AUD,130546,MI,FT,Australia,L,Australia,50,"PyTorch, Hadoop, Git",Master,4,Technology,2024-07-20,2024-09-30,1167,9.2,Predictive Systems -AI04099,Deep Learning Engineer,180946,USD,180946,EX,FL,Ireland,M,Ireland,50,"Scala, AWS, Git, Hadoop",Bachelor,19,Finance,2024-12-14,2025-01-31,1194,8.5,Advanced Robotics -AI04100,Data Analyst,166915,USD,166915,EX,FL,Finland,M,Finland,100,"Java, PyTorch, Kubernetes, Mathematics, Data Visualization",Associate,12,Technology,2025-02-04,2025-04-08,880,5.2,AI Innovations -AI04101,Autonomous Systems Engineer,121685,USD,121685,SE,FL,Sweden,M,Sweden,0,"Data Visualization, Deep Learning, Python, Statistics",Bachelor,9,Consulting,2024-03-13,2024-05-15,1830,5.2,TechCorp Inc -AI04102,Research Scientist,167790,USD,167790,SE,FL,Norway,L,Norway,100,"Linux, NLP, Python",Bachelor,6,Government,2025-02-27,2025-03-16,1947,9.7,DeepTech Ventures -AI04103,Robotics Engineer,80516,EUR,68439,EN,CT,Netherlands,M,Netherlands,0,"Scala, Git, SQL, Python",PhD,1,Media,2024-09-13,2024-10-21,1007,6,Cognitive Computing -AI04104,Data Scientist,100310,GBP,75233,MI,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Docker, GCP",Associate,2,Education,2024-01-18,2024-03-05,1460,7.7,Cognitive Computing -AI04105,Research Scientist,120643,USD,120643,SE,FT,Sweden,M,Sweden,0,"Docker, R, Deep Learning, Java, Computer Vision",Associate,6,Technology,2025-04-21,2025-06-23,817,7.2,Cognitive Computing -AI04106,AI Architect,68168,EUR,57943,MI,PT,Austria,S,Austria,100,"PyTorch, Linux, SQL, GCP, R",Bachelor,3,Telecommunications,2025-01-09,2025-02-22,2194,5.9,TechCorp Inc -AI04107,Data Engineer,103407,USD,103407,EX,FL,India,L,India,0,"Python, NLP, Statistics",Master,17,Government,2024-10-30,2024-12-23,2100,6.4,Cognitive Computing -AI04108,Principal Data Scientist,79353,JPY,8728830,EN,FT,Japan,M,Japan,0,"GCP, PyTorch, NLP",PhD,0,Telecommunications,2024-05-04,2024-06-19,1235,7,AI Innovations -AI04109,Principal Data Scientist,215826,GBP,161870,EX,FT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Azure, R, Statistics",Associate,14,Telecommunications,2024-04-03,2024-05-25,886,8.7,DeepTech Ventures -AI04110,Data Analyst,124330,EUR,105681,MI,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Deep Learning",Master,3,Retail,2024-12-12,2025-02-19,1635,5.3,Advanced Robotics -AI04111,Machine Learning Engineer,53595,EUR,45556,EN,FT,France,M,Luxembourg,100,"NLP, Git, Docker, Hadoop, Spark",Master,0,Consulting,2024-09-19,2024-11-06,1568,5.2,Advanced Robotics -AI04112,AI Research Scientist,141469,EUR,120249,EX,FL,Germany,S,Germany,0,"R, Python, Computer Vision",Master,14,Transportation,2024-06-08,2024-08-02,1693,6.5,Predictive Systems -AI04113,Computer Vision Engineer,115046,USD,115046,MI,FT,Sweden,L,Sweden,100,"Kubernetes, AWS, GCP, Scala",Master,4,Media,2025-03-14,2025-05-23,739,8,Predictive Systems -AI04114,Machine Learning Engineer,147907,CHF,133116,MI,PT,Switzerland,M,Egypt,0,"SQL, AWS, Scala, Tableau",Associate,4,Automotive,2025-03-11,2025-04-01,1372,8.8,Machine Intelligence Group -AI04115,AI Product Manager,50641,USD,50641,EX,FL,India,S,Hungary,50,"Data Visualization, GCP, R, Hadoop",PhD,19,Healthcare,2024-06-19,2024-08-25,1905,9.3,DataVision Ltd -AI04116,AI Product Manager,214441,EUR,182275,EX,FL,Netherlands,M,Philippines,0,"Linux, Scala, Python, NLP, Mathematics",PhD,10,Manufacturing,2024-02-19,2024-03-29,2265,6.3,Future Systems -AI04117,Computer Vision Engineer,114417,GBP,85813,MI,FL,United Kingdom,M,United Kingdom,50,"Python, R, Mathematics",PhD,2,Technology,2024-03-28,2024-05-14,2050,9.9,Digital Transformation LLC -AI04118,AI Consultant,112932,JPY,12422520,MI,FT,Japan,L,Japan,100,"Scala, Computer Vision, NLP, PyTorch, Spark",Bachelor,4,Healthcare,2025-03-03,2025-04-08,2449,9.3,Autonomous Tech -AI04119,ML Ops Engineer,72211,USD,72211,EN,CT,Israel,L,Israel,0,"Git, Scala, SQL, Mathematics",Bachelor,0,Retail,2024-04-16,2024-05-05,2062,9.8,Cognitive Computing -AI04120,Deep Learning Engineer,182222,AUD,246000,EX,CT,Australia,L,Spain,100,"Azure, Deep Learning, Java",Master,18,Energy,2024-10-01,2024-11-06,1155,7.2,AI Innovations -AI04121,Machine Learning Engineer,83596,EUR,71057,EN,FT,Germany,L,Germany,50,"Data Visualization, NLP, Kubernetes, Python",PhD,0,Government,2025-01-04,2025-03-18,1822,5.2,Future Systems -AI04122,NLP Engineer,109011,CHF,98110,EN,FT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Data Visualization, R",Associate,1,Consulting,2024-01-25,2024-03-12,2002,8.6,DataVision Ltd -AI04123,Deep Learning Engineer,74573,AUD,100674,EN,PT,Australia,L,Australia,0,"Git, Python, Mathematics, Tableau, Docker",PhD,0,Retail,2024-10-21,2024-12-26,926,8.1,Cognitive Computing -AI04124,Principal Data Scientist,117158,EUR,99584,MI,PT,Netherlands,L,Philippines,50,"Python, TensorFlow, Git, Computer Vision, Azure",Master,2,Consulting,2024-11-19,2024-12-17,1918,6.4,Future Systems -AI04125,Head of AI,84442,JPY,9288620,MI,FL,Japan,M,Sweden,50,"SQL, TensorFlow, Mathematics",PhD,2,Telecommunications,2024-12-30,2025-02-23,1372,6.8,Cloud AI Solutions -AI04126,Machine Learning Researcher,64765,USD,64765,EX,FL,India,L,Brazil,100,"PyTorch, Scala, Hadoop, Computer Vision",PhD,11,Media,2024-05-14,2024-06-24,1270,5.8,Algorithmic Solutions -AI04127,Data Scientist,161364,USD,161364,SE,FT,Norway,S,Norway,100,"AWS, MLOps, SQL, Azure",Bachelor,9,Real Estate,2024-02-27,2024-04-29,1176,6.5,Algorithmic Solutions -AI04128,Data Scientist,259567,AUD,350415,EX,PT,Australia,L,Australia,0,"GCP, Docker, Python, Azure, Data Visualization",Master,11,Government,2025-03-23,2025-05-11,789,10,Smart Analytics -AI04129,Machine Learning Engineer,58926,USD,58926,MI,FT,South Korea,S,Finland,0,"Statistics, PyTorch, Java, Scala, Azure",Bachelor,3,Education,2024-05-19,2024-07-04,1330,9.8,Smart Analytics -AI04130,Machine Learning Researcher,205317,USD,205317,SE,FL,United States,L,Argentina,100,"Scala, AWS, Tableau",Associate,7,Government,2024-10-25,2024-12-18,2425,7.3,Neural Networks Co -AI04131,Robotics Engineer,142793,CHF,128514,MI,PT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Mathematics, Statistics, GCP",Bachelor,4,Telecommunications,2024-06-19,2024-08-18,1439,7,Algorithmic Solutions -AI04132,AI Architect,48948,USD,48948,SE,FL,India,L,India,50,"Git, GCP, Python, AWS, NLP",Bachelor,5,Technology,2024-08-30,2024-09-19,2439,8.5,Neural Networks Co -AI04133,Machine Learning Engineer,101284,USD,101284,MI,FL,Ireland,M,Ireland,0,"Kubernetes, Docker, R, Azure",Bachelor,2,Finance,2024-05-07,2024-06-14,2361,7.2,Future Systems -AI04134,Autonomous Systems Engineer,94804,USD,94804,MI,CT,South Korea,L,Vietnam,100,"SQL, PyTorch, GCP",Associate,2,Finance,2025-04-20,2025-06-25,1817,8.7,Cognitive Computing -AI04135,AI Consultant,55274,SGD,71856,EN,FT,Singapore,S,Singapore,0,"Python, TensorFlow, Spark, Deep Learning",Associate,1,Real Estate,2024-12-13,2025-02-04,1539,8.1,DataVision Ltd -AI04136,Machine Learning Engineer,46056,EUR,39148,EN,CT,France,S,France,100,"Kubernetes, Scala, GCP",Associate,1,Government,2024-07-03,2024-09-12,2123,7.8,Smart Analytics -AI04137,AI Research Scientist,71471,SGD,92912,EN,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, NLP, Deep Learning, Scala",Master,0,Education,2024-07-31,2024-09-20,989,6.3,Quantum Computing Inc -AI04138,Data Analyst,173574,AUD,234325,EX,CT,Australia,S,Australia,0,"Linux, Hadoop, R",Master,12,Finance,2025-03-07,2025-04-30,832,5.8,AI Innovations -AI04139,AI Software Engineer,228777,CAD,285971,EX,PT,Canada,L,Canada,0,"Scala, Deep Learning, Data Visualization, Kubernetes, Statistics",PhD,18,Energy,2024-10-02,2024-10-24,2368,8.5,Algorithmic Solutions -AI04140,Data Engineer,218206,AUD,294578,EX,FL,Australia,M,Australia,0,"Linux, TensorFlow, Statistics, Python, Computer Vision",PhD,17,Technology,2025-04-27,2025-06-05,2119,5.6,Digital Transformation LLC -AI04141,Autonomous Systems Engineer,218548,EUR,185766,EX,CT,Netherlands,L,Netherlands,100,"Git, Hadoop, Linux",Master,11,Energy,2024-11-08,2025-01-09,1487,9.7,Digital Transformation LLC -AI04142,Data Scientist,137310,EUR,116714,SE,FT,France,M,France,100,"Scala, NLP, Java, Kubernetes, Linux",PhD,5,Government,2024-10-27,2024-12-13,1017,5.8,Advanced Robotics -AI04143,Research Scientist,112353,EUR,95500,MI,CT,Netherlands,L,Netherlands,0,"PyTorch, GCP, Mathematics, Deep Learning",Associate,2,Media,2024-11-18,2025-01-29,1367,9.6,Algorithmic Solutions -AI04144,Data Analyst,217691,EUR,185037,EX,FT,Germany,M,Germany,50,"R, SQL, NLP",PhD,10,Real Estate,2025-01-17,2025-03-04,1455,9.8,Machine Intelligence Group -AI04145,Data Engineer,82416,EUR,70054,MI,FL,France,L,France,100,"Git, Tableau, Hadoop, Java, Linux",PhD,2,Telecommunications,2024-07-25,2024-08-08,1499,9.1,Machine Intelligence Group -AI04146,Data Engineer,271408,USD,271408,EX,CT,Finland,L,Finland,50,"Kubernetes, R, SQL",Associate,19,Real Estate,2025-02-22,2025-05-04,2037,5.3,Neural Networks Co -AI04147,Robotics Engineer,50767,USD,50767,EN,FT,Israel,M,Israel,100,"Kubernetes, Git, Python",Master,0,Government,2024-08-13,2024-10-04,735,9.7,DeepTech Ventures -AI04148,Computer Vision Engineer,110614,EUR,94022,SE,FT,France,L,France,100,"SQL, Python, Kubernetes",Master,6,Real Estate,2024-12-11,2025-01-01,1473,5.7,Autonomous Tech -AI04149,Computer Vision Engineer,92141,EUR,78320,MI,CT,Netherlands,M,Spain,100,"Scala, Python, Statistics, Deep Learning",PhD,3,Technology,2024-04-18,2024-05-15,1681,6.9,DeepTech Ventures -AI04150,Machine Learning Engineer,48318,USD,48318,EN,FL,South Korea,M,South Korea,50,"Spark, Kubernetes, Statistics",PhD,1,Retail,2025-04-08,2025-04-22,871,5.6,Cloud AI Solutions -AI04151,Research Scientist,263753,EUR,224190,EX,FL,Austria,L,Austria,100,"Linux, Python, Git, Spark",Bachelor,11,Automotive,2024-04-23,2024-06-02,850,8.3,Algorithmic Solutions -AI04152,Machine Learning Researcher,273323,CHF,245991,EX,PT,Switzerland,M,Switzerland,50,"SQL, Statistics, Tableau",PhD,12,Automotive,2025-04-10,2025-05-26,991,8.7,Machine Intelligence Group -AI04153,Research Scientist,62268,USD,62268,MI,FT,Finland,S,Vietnam,0,"Docker, SQL, Spark, Linux",Associate,2,Transportation,2025-02-21,2025-04-13,1843,6.9,Cognitive Computing -AI04154,NLP Engineer,116686,USD,116686,MI,FT,Ireland,L,Ireland,50,"Azure, SQL, Data Visualization, Python, Kubernetes",Master,2,Finance,2025-04-16,2025-06-21,2006,9.9,Smart Analytics -AI04155,AI Research Scientist,129353,EUR,109950,SE,FL,Germany,M,Germany,0,"Python, Deep Learning, Java",PhD,9,Finance,2024-12-29,2025-03-08,2476,8.5,Smart Analytics -AI04156,Principal Data Scientist,267772,EUR,227606,EX,FT,Netherlands,L,Netherlands,0,"Python, R, MLOps, GCP, Kubernetes",Master,15,Real Estate,2024-12-28,2025-02-11,1950,7.8,Quantum Computing Inc -AI04157,AI Architect,59923,EUR,50935,EN,CT,Netherlands,M,Netherlands,100,"R, Java, Mathematics, MLOps, NLP",Associate,1,Consulting,2025-02-04,2025-04-06,1615,7.1,AI Innovations -AI04158,Data Analyst,75531,USD,75531,EX,CT,India,L,India,0,"Java, R, Spark, MLOps",PhD,11,Manufacturing,2024-11-09,2025-01-18,1354,9.1,Quantum Computing Inc -AI04159,AI Specialist,71196,USD,71196,EN,FL,Israel,L,Chile,0,"Data Visualization, Deep Learning, Docker",Master,1,Transportation,2024-01-27,2024-03-21,2117,9.2,Neural Networks Co -AI04160,AI Specialist,88243,USD,88243,MI,FL,Sweden,S,Germany,50,"SQL, Java, PyTorch",Master,2,Automotive,2024-10-03,2024-10-24,1074,9,Future Systems -AI04161,Robotics Engineer,105621,JPY,11618310,SE,PT,Japan,S,Japan,100,"Python, R, GCP, MLOps, TensorFlow",Associate,7,Gaming,2024-06-03,2024-07-28,889,5.6,AI Innovations -AI04162,AI Product Manager,98658,CAD,123323,SE,CT,Canada,S,Canada,0,"SQL, Scala, Python",Associate,5,Consulting,2024-02-09,2024-03-23,1266,6.2,Algorithmic Solutions -AI04163,Machine Learning Researcher,61301,USD,61301,EX,FL,India,L,India,100,"Python, TensorFlow, GCP",Associate,10,Education,2024-03-19,2024-05-10,1512,7.6,Cognitive Computing -AI04164,Head of AI,170872,USD,170872,EX,FT,Norway,S,Norway,0,"AWS, Hadoop, Data Visualization",PhD,16,Consulting,2024-06-10,2024-07-06,1985,10,Smart Analytics -AI04165,AI Software Engineer,56083,USD,56083,EN,FT,South Korea,L,Nigeria,0,"Kubernetes, Hadoop, Statistics",Bachelor,1,Education,2024-12-06,2025-02-02,1313,8.6,DeepTech Ventures -AI04166,AI Architect,71351,EUR,60648,EN,FL,Netherlands,S,Netherlands,0,"Python, TensorFlow, Computer Vision, PyTorch, SQL",PhD,1,Finance,2024-11-15,2025-01-20,1598,6.3,Cloud AI Solutions -AI04167,Deep Learning Engineer,131806,AUD,177938,SE,CT,Australia,L,Australia,0,"TensorFlow, Linux, Java",Bachelor,6,Retail,2024-08-13,2024-10-04,2368,6.9,Neural Networks Co -AI04168,Head of AI,85952,USD,85952,EN,CT,Norway,M,Norway,50,"NLP, Data Visualization, TensorFlow, Linux",PhD,1,Automotive,2024-01-07,2024-02-24,1437,7.8,Cloud AI Solutions -AI04169,Head of AI,177858,SGD,231215,SE,FT,Singapore,L,Singapore,0,"TensorFlow, Mathematics, Docker, Tableau, Deep Learning",Associate,8,Education,2024-10-02,2024-10-23,1797,9.6,DeepTech Ventures -AI04170,Head of AI,210574,USD,210574,SE,FL,Denmark,L,Chile,0,"Hadoop, Scala, Python, Computer Vision, Deep Learning",Associate,9,Government,2024-08-24,2024-10-31,874,6.1,TechCorp Inc -AI04171,Computer Vision Engineer,96894,USD,96894,MI,FT,South Korea,L,Vietnam,100,"Scala, Spark, Data Visualization",Master,4,Gaming,2024-11-18,2025-01-25,1945,5.2,AI Innovations -AI04172,AI Research Scientist,137829,AUD,186069,EX,FL,Australia,M,Australia,100,"GCP, Hadoop, PyTorch, Spark, R",Bachelor,16,Energy,2024-11-03,2024-12-28,1831,7.4,Neural Networks Co -AI04173,Data Analyst,99906,USD,99906,MI,CT,Israel,M,Israel,50,"Kubernetes, SQL, Python, Deep Learning",Bachelor,4,Education,2024-05-30,2024-07-27,517,8,DeepTech Ventures -AI04174,AI Consultant,78189,CAD,97736,EN,FT,Canada,L,Canada,50,"Docker, GCP, Java, Mathematics",Bachelor,1,Retail,2024-06-21,2024-07-29,2449,5.3,DeepTech Ventures -AI04175,Head of AI,221259,JPY,24338490,EX,CT,Japan,L,Austria,100,"Python, SQL, Scala, Tableau",PhD,12,Energy,2025-01-22,2025-02-15,1106,8.1,AI Innovations -AI04176,Data Engineer,69907,GBP,52430,EN,CT,United Kingdom,S,United Kingdom,100,"GCP, Git, SQL, NLP",Bachelor,1,Retail,2024-09-15,2024-11-01,531,7,Predictive Systems -AI04177,Computer Vision Engineer,114573,EUR,97387,MI,CT,Germany,L,Germany,0,"Scala, TensorFlow, SQL",Master,4,Manufacturing,2024-02-22,2024-03-24,1045,8.9,Algorithmic Solutions -AI04178,Autonomous Systems Engineer,91770,CAD,114713,SE,PT,Canada,S,Canada,100,"Python, Deep Learning, TensorFlow, Hadoop, GCP",Master,7,Finance,2025-02-08,2025-03-04,1669,9.5,Autonomous Tech -AI04179,AI Research Scientist,97661,EUR,83012,SE,FT,Germany,S,Germany,0,"Scala, Data Visualization, Git, AWS, Hadoop",PhD,5,Healthcare,2024-12-24,2025-02-02,1681,7.9,Cognitive Computing -AI04180,Machine Learning Researcher,93001,USD,93001,SE,FT,Israel,S,Israel,0,"R, Kubernetes, AWS",Master,8,Healthcare,2024-05-23,2024-08-01,2033,7.1,Cloud AI Solutions -AI04181,Machine Learning Researcher,138207,CAD,172759,EX,FL,Canada,S,Canada,50,"AWS, Java, Data Visualization",Bachelor,19,Healthcare,2024-01-30,2024-02-22,1932,5.6,Future Systems -AI04182,ML Ops Engineer,87070,EUR,74010,MI,FT,Austria,L,Ghana,0,"Data Visualization, Kubernetes, SQL, Deep Learning, GCP",Bachelor,4,Real Estate,2024-02-17,2024-03-08,1838,5.7,Future Systems -AI04183,Research Scientist,102685,USD,102685,SE,FT,South Korea,S,Indonesia,0,"NLP, Kubernetes, PyTorch, Azure, Tableau",Bachelor,9,Consulting,2024-10-03,2024-11-26,1996,9,DataVision Ltd -AI04184,AI Consultant,36735,USD,36735,MI,CT,India,M,India,0,"Python, AWS, Data Visualization, TensorFlow, Spark",Associate,2,Media,2025-02-12,2025-03-19,1482,7.2,Cognitive Computing -AI04185,Machine Learning Researcher,141810,EUR,120539,EX,PT,Germany,M,Germany,100,"Kubernetes, Azure, Statistics, R, Tableau",Associate,18,Telecommunications,2024-04-09,2024-06-16,1488,5.2,Algorithmic Solutions -AI04186,Head of AI,44764,USD,44764,EN,FT,South Korea,M,South Korea,50,"Spark, Kubernetes, NLP, Python, Linux",Associate,1,Energy,2025-02-08,2025-02-27,910,9.1,Future Systems -AI04187,Machine Learning Engineer,251178,EUR,213501,EX,FL,Austria,L,Austria,0,"GCP, Scala, SQL, Deep Learning",Associate,15,Government,2024-08-10,2024-09-30,674,5,Digital Transformation LLC -AI04188,Autonomous Systems Engineer,293534,USD,293534,EX,CT,Norway,M,Norway,50,"Java, PyTorch, AWS, R, Hadoop",Associate,19,Healthcare,2025-04-13,2025-05-31,1581,5.8,DataVision Ltd -AI04189,Data Scientist,47064,USD,47064,EN,PT,Ireland,S,Ireland,0,"Python, Linux, Computer Vision, Azure",Master,1,Technology,2024-04-16,2024-05-26,941,9.6,TechCorp Inc -AI04190,NLP Engineer,133682,SGD,173787,SE,PT,Singapore,M,Singapore,100,"Data Visualization, Kubernetes, R, AWS, NLP",Master,6,Technology,2024-12-05,2025-02-11,1401,8.7,TechCorp Inc -AI04191,Machine Learning Researcher,104881,GBP,78661,SE,CT,United Kingdom,S,United Kingdom,0,"R, Scala, Linux",PhD,5,Real Estate,2024-12-20,2025-01-26,2075,7.9,Future Systems -AI04192,Data Scientist,93613,USD,93613,EX,FT,India,L,India,100,"Azure, PyTorch, Hadoop",Bachelor,11,Technology,2025-01-05,2025-02-06,672,5.7,AI Innovations -AI04193,AI Architect,207719,USD,207719,EX,FT,Sweden,S,Sweden,50,"Tableau, AWS, PyTorch",Associate,17,Consulting,2024-10-02,2024-12-12,1642,5.8,Autonomous Tech -AI04194,Data Scientist,169583,JPY,18654130,EX,FT,Japan,S,Japan,100,"Python, Statistics, Azure, Tableau, Scala",Associate,15,Transportation,2024-12-09,2025-02-18,2352,7.7,Digital Transformation LLC -AI04195,Data Scientist,102146,CHF,91931,EN,FT,Switzerland,M,Japan,0,"Python, Deep Learning, R",PhD,1,Technology,2025-01-07,2025-02-20,2109,5.2,Machine Intelligence Group -AI04196,AI Product Manager,171881,AUD,232039,SE,FL,Australia,L,Australia,50,"PyTorch, AWS, Data Visualization, Git, Deep Learning",PhD,6,Consulting,2024-05-12,2024-07-24,1188,8.1,AI Innovations -AI04197,Data Scientist,24066,USD,24066,EN,FT,India,S,France,0,"TensorFlow, Computer Vision, Python",Master,0,Finance,2024-12-26,2025-01-09,838,7.7,Cloud AI Solutions -AI04198,AI Architect,149018,EUR,126665,EX,PT,France,L,France,0,"TensorFlow, Docker, Spark, NLP",Associate,18,Finance,2024-09-03,2024-09-22,2468,7.6,Future Systems -AI04199,Principal Data Scientist,119622,AUD,161490,SE,PT,Australia,S,Australia,100,"AWS, Scala, Kubernetes, Mathematics",Bachelor,5,Consulting,2024-01-01,2024-03-14,1210,6.5,Smart Analytics -AI04200,Machine Learning Researcher,135418,USD,135418,SE,FT,Sweden,M,Sweden,0,"Kubernetes, GCP, Docker",PhD,8,Gaming,2024-02-15,2024-04-09,2215,6.1,Algorithmic Solutions -AI04201,Robotics Engineer,80410,GBP,60308,MI,PT,United Kingdom,M,United Kingdom,100,"Scala, PyTorch, NLP",Bachelor,2,Retail,2024-05-12,2024-07-04,2221,8,Predictive Systems -AI04202,AI Architect,158403,JPY,17424330,SE,PT,Japan,M,Netherlands,0,"R, Kubernetes, Git",PhD,6,Real Estate,2024-03-15,2024-05-05,2333,8.8,Machine Intelligence Group -AI04203,Deep Learning Engineer,143401,EUR,121891,EX,CT,Austria,M,Austria,50,"Git, Computer Vision, Statistics, Kubernetes, Java",PhD,18,Telecommunications,2024-01-26,2024-04-04,2218,9.7,Advanced Robotics -AI04204,NLP Engineer,72505,USD,72505,MI,CT,Israel,S,Israel,0,"SQL, Linux, Scala",Bachelor,2,Gaming,2025-04-26,2025-06-01,2155,6.3,Digital Transformation LLC -AI04205,Principal Data Scientist,101052,EUR,85894,MI,CT,France,L,France,100,"Java, Python, Mathematics, GCP, Spark",Bachelor,3,Real Estate,2024-09-09,2024-11-13,2376,6,Algorithmic Solutions -AI04206,Robotics Engineer,90464,CAD,113080,MI,FT,Canada,S,Canada,50,"Scala, Kubernetes, Mathematics, Tableau, Hadoop",Master,3,Finance,2024-11-29,2025-01-16,1450,5.1,DeepTech Ventures -AI04207,Machine Learning Engineer,155870,USD,155870,EX,CT,Finland,M,Finland,100,"GCP, SQL, PyTorch, Data Visualization",Bachelor,18,Technology,2024-06-03,2024-08-08,2068,8.4,TechCorp Inc -AI04208,Autonomous Systems Engineer,86105,USD,86105,EX,FL,India,M,India,100,"TensorFlow, Linux, Azure, Kubernetes, Spark",Associate,16,Finance,2025-01-30,2025-03-07,2236,7.9,Algorithmic Solutions -AI04209,AI Software Engineer,60304,EUR,51258,EN,PT,Germany,M,Germany,100,"SQL, Scala, Azure",Master,1,Media,2024-09-27,2024-12-04,1530,8.9,Algorithmic Solutions -AI04210,NLP Engineer,158258,USD,158258,SE,CT,Denmark,S,Denmark,50,"NLP, MLOps, Python, Deep Learning",Master,8,Finance,2024-07-18,2024-08-18,1416,9.5,Future Systems -AI04211,Robotics Engineer,139108,USD,139108,SE,FT,Denmark,M,Hungary,50,"GCP, R, Spark, Data Visualization, Docker",PhD,7,Healthcare,2024-05-05,2024-05-19,2202,7.9,Advanced Robotics -AI04212,Robotics Engineer,127647,GBP,95735,SE,FL,United Kingdom,L,United Kingdom,50,"SQL, Kubernetes, TensorFlow, AWS, R",Master,8,Gaming,2024-06-22,2024-07-14,1248,8.1,Smart Analytics -AI04213,NLP Engineer,113026,CAD,141283,SE,FT,Canada,L,Canada,50,"NLP, Linux, Python, Deep Learning, Java",Associate,8,Gaming,2025-01-09,2025-02-21,1025,8.4,AI Innovations -AI04214,NLP Engineer,160446,USD,160446,EX,FT,United States,M,United States,50,"Mathematics, SQL, MLOps, PyTorch",Associate,16,Manufacturing,2024-04-26,2024-07-07,2148,5.5,AI Innovations -AI04215,Research Scientist,170414,USD,170414,SE,FT,Denmark,S,Denmark,50,"Kubernetes, Azure, Computer Vision",Associate,5,Gaming,2024-08-14,2024-09-16,2394,8.1,Predictive Systems -AI04216,Robotics Engineer,153701,USD,153701,EX,FT,Finland,L,France,100,"Spark, Kubernetes, Statistics",PhD,15,Telecommunications,2024-08-04,2024-09-08,641,6.6,Neural Networks Co -AI04217,AI Research Scientist,66536,SGD,86497,EN,FT,Singapore,M,Singapore,50,"Mathematics, SQL, Kubernetes",Bachelor,1,Government,2024-03-17,2024-04-17,952,9.9,Cloud AI Solutions -AI04218,Autonomous Systems Engineer,144573,USD,144573,EX,CT,South Korea,S,South Korea,100,"Linux, Statistics, GCP, Python, Computer Vision",PhD,18,Energy,2024-11-30,2025-02-10,1931,8,Quantum Computing Inc -AI04219,Autonomous Systems Engineer,39124,USD,39124,SE,FT,India,M,India,0,"Deep Learning, MLOps, Statistics, Spark",Master,5,Manufacturing,2024-10-12,2024-11-15,2309,5.7,Quantum Computing Inc -AI04220,Machine Learning Researcher,148877,EUR,126545,SE,FL,Netherlands,L,Netherlands,50,"Hadoop, Docker, NLP",Associate,5,Consulting,2024-06-28,2024-08-17,1349,9.8,Smart Analytics -AI04221,Research Scientist,62439,AUD,84293,EN,FT,Australia,S,Australia,100,"Java, Python, Kubernetes, GCP",Bachelor,1,Technology,2024-06-05,2024-06-29,1944,7.9,DeepTech Ventures -AI04222,Data Analyst,70705,USD,70705,MI,PT,South Korea,M,South Korea,0,"Data Visualization, Hadoop, Tableau, Mathematics, Linux",PhD,4,Healthcare,2025-01-21,2025-03-04,2030,5.6,DataVision Ltd -AI04223,AI Software Engineer,136064,USD,136064,EX,PT,Israel,M,Israel,100,"SQL, Python, Tableau",Master,13,Energy,2024-12-26,2025-01-14,2276,9.4,DataVision Ltd -AI04224,Machine Learning Researcher,114102,GBP,85577,SE,CT,United Kingdom,S,United Kingdom,50,"GCP, AWS, NLP",Bachelor,9,Manufacturing,2025-02-20,2025-03-15,515,9.1,Neural Networks Co -AI04225,ML Ops Engineer,48875,USD,48875,SE,CT,China,S,Germany,0,"Spark, PyTorch, Java, NLP",Associate,7,Education,2024-05-15,2024-06-07,843,10,Neural Networks Co -AI04226,ML Ops Engineer,66920,USD,66920,EN,CT,Denmark,M,Kenya,0,"Deep Learning, Linux, Computer Vision",Bachelor,1,Gaming,2025-02-18,2025-04-04,1486,7,AI Innovations -AI04227,Deep Learning Engineer,60046,USD,60046,EN,FT,United States,S,Australia,0,"Git, Scala, NLP, SQL, Azure",Bachelor,1,Transportation,2025-04-27,2025-06-06,992,7.9,Machine Intelligence Group -AI04228,Machine Learning Engineer,65824,EUR,55950,MI,FL,France,S,France,0,"Azure, GCP, Mathematics, Scala, TensorFlow",Associate,4,Government,2024-03-31,2024-05-26,639,9.4,Predictive Systems -AI04229,Computer Vision Engineer,92205,USD,92205,MI,FL,Finland,M,Finland,0,"Git, Spark, Deep Learning, AWS",Bachelor,4,Transportation,2024-06-18,2024-08-03,1381,5.8,DataVision Ltd -AI04230,Principal Data Scientist,69016,EUR,58664,MI,FL,Germany,S,Germany,50,"Spark, Linux, Kubernetes, Mathematics",Associate,2,Finance,2024-03-20,2024-04-26,954,6,Machine Intelligence Group -AI04231,AI Consultant,71384,USD,71384,EN,FL,Ireland,M,Ireland,100,"Python, Java, Deep Learning",PhD,0,Finance,2024-01-12,2024-02-27,1060,7.8,DataVision Ltd -AI04232,Data Scientist,63659,EUR,54110,EN,PT,Germany,S,United States,100,"GCP, SQL, Tableau, MLOps",Associate,0,Technology,2024-11-29,2025-01-18,1082,9.9,DeepTech Ventures -AI04233,AI Research Scientist,117611,GBP,88208,SE,FL,United Kingdom,M,Vietnam,0,"PyTorch, Tableau, Hadoop, TensorFlow, Statistics",Associate,7,Media,2025-01-05,2025-01-24,1849,6.6,Digital Transformation LLC -AI04234,Deep Learning Engineer,48074,USD,48074,EN,FL,Sweden,S,Sweden,0,"PyTorch, Python, Spark, Azure, SQL",Bachelor,0,Government,2024-12-26,2025-01-23,606,7.4,Future Systems -AI04235,Principal Data Scientist,122232,EUR,103897,SE,CT,Germany,S,Colombia,0,"R, Java, GCP, Python, Hadoop",Associate,8,Automotive,2025-02-27,2025-03-13,1471,5,Digital Transformation LLC -AI04236,Head of AI,197539,EUR,167908,EX,FL,France,L,Turkey,0,"Kubernetes, PyTorch, Docker, TensorFlow, Python",Master,13,Consulting,2025-01-01,2025-02-26,904,7,Cloud AI Solutions -AI04237,AI Specialist,255683,EUR,217331,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Tableau, Azure",Associate,18,Telecommunications,2024-03-15,2024-04-25,1130,9,Cognitive Computing -AI04238,Machine Learning Engineer,77121,USD,77121,EN,FL,Israel,L,Hungary,100,"SQL, Azure, PyTorch",Associate,1,Consulting,2024-10-06,2024-12-18,2312,6.9,Predictive Systems -AI04239,ML Ops Engineer,52575,USD,52575,MI,FL,China,L,South Africa,50,"Hadoop, Git, Python, Kubernetes",Bachelor,4,Finance,2025-01-23,2025-03-16,624,9.7,Machine Intelligence Group -AI04240,Autonomous Systems Engineer,86907,EUR,73871,SE,CT,Austria,S,Austria,100,"Spark, Data Visualization, AWS, R",Associate,6,Retail,2024-01-18,2024-03-11,733,7.3,Advanced Robotics -AI04241,Computer Vision Engineer,148771,EUR,126455,SE,CT,Germany,M,Germany,0,"Spark, Kubernetes, Deep Learning",Associate,6,Retail,2025-02-12,2025-02-26,2370,9.4,Autonomous Tech -AI04242,Deep Learning Engineer,124742,EUR,106031,SE,FL,Netherlands,L,Netherlands,0,"Python, Scala, Linux, Tableau, TensorFlow",Bachelor,7,Media,2024-11-13,2025-01-07,972,5.2,Cognitive Computing -AI04243,AI Specialist,80538,USD,80538,MI,PT,Sweden,M,Sweden,0,"Hadoop, Azure, Computer Vision, SQL, R",Bachelor,3,Manufacturing,2024-05-26,2024-07-25,1372,7.4,TechCorp Inc -AI04244,Deep Learning Engineer,261998,CHF,235798,EX,FT,Switzerland,S,Switzerland,0,"NLP, R, Computer Vision, Python, Azure",Bachelor,13,Energy,2024-01-21,2024-03-29,751,8.6,Future Systems -AI04245,Data Scientist,161380,JPY,17751800,EX,FT,Japan,M,Japan,0,"Python, Scala, Computer Vision, Hadoop",Master,13,Media,2024-05-14,2024-06-26,1306,6.2,Digital Transformation LLC -AI04246,Research Scientist,114449,USD,114449,SE,PT,Ireland,S,Thailand,0,"Scala, Git, SQL, NLP",PhD,8,Telecommunications,2024-04-22,2024-06-30,683,7.6,Autonomous Tech -AI04247,Robotics Engineer,65542,AUD,88482,EN,FT,Australia,M,Malaysia,0,"Java, Deep Learning, PyTorch, Data Visualization, Tableau",Associate,1,Education,2024-06-29,2024-09-01,1053,7,Predictive Systems -AI04248,Machine Learning Researcher,177905,JPY,19569550,EX,CT,Japan,M,Japan,100,"Kubernetes, SQL, Deep Learning",Bachelor,10,Transportation,2024-01-12,2024-03-07,1848,9.9,Cloud AI Solutions -AI04249,NLP Engineer,89958,SGD,116945,EN,FL,Singapore,L,Singapore,0,"Java, Docker, Deep Learning",Bachelor,1,Automotive,2025-01-04,2025-03-08,993,7.6,AI Innovations -AI04250,Data Scientist,50166,USD,50166,EN,CT,South Korea,S,South Korea,100,"Deep Learning, R, MLOps, Tableau, Scala",Associate,0,Automotive,2024-09-20,2024-11-21,1812,6.3,Cognitive Computing -AI04251,Research Scientist,153548,USD,153548,MI,FT,Denmark,L,Denmark,50,"Statistics, Spark, SQL",PhD,3,Manufacturing,2024-12-03,2025-01-01,977,6,Neural Networks Co -AI04252,AI Research Scientist,199709,CHF,179738,SE,CT,Switzerland,M,Switzerland,100,"GCP, R, NLP, Deep Learning",Associate,9,Consulting,2024-09-29,2024-11-07,992,5.7,Digital Transformation LLC -AI04253,Research Scientist,106748,USD,106748,SE,PT,South Korea,M,South Korea,50,"Scala, Kubernetes, SQL, NLP",Associate,5,Finance,2024-08-11,2024-10-05,501,5.7,Predictive Systems -AI04254,AI Consultant,164745,CHF,148271,SE,PT,Switzerland,S,Switzerland,100,"Computer Vision, NLP, Kubernetes, Scala, Java",Associate,6,Consulting,2024-04-08,2024-05-09,2246,7.6,Cloud AI Solutions -AI04255,Principal Data Scientist,74190,EUR,63062,MI,FL,Austria,S,Austria,0,"Java, PyTorch, Docker, Computer Vision, GCP",Associate,4,Energy,2024-06-10,2024-06-28,1983,9.9,Digital Transformation LLC -AI04256,AI Specialist,77889,EUR,66206,EN,FT,Netherlands,L,Netherlands,100,"Linux, Mathematics, MLOps",Associate,1,Transportation,2024-05-29,2024-07-24,517,6.5,Autonomous Tech -AI04257,Autonomous Systems Engineer,172285,EUR,146442,EX,PT,Austria,S,Austria,100,"Python, Java, Git, AWS, TensorFlow",Master,10,Automotive,2024-05-20,2024-07-15,1924,7.6,Machine Intelligence Group -AI04258,Robotics Engineer,192684,JPY,21195240,EX,FL,Japan,S,Japan,100,"Mathematics, TensorFlow, Deep Learning, Git, Spark",Associate,17,Manufacturing,2024-04-02,2024-05-25,509,5.2,Advanced Robotics -AI04259,Machine Learning Engineer,62085,USD,62085,SE,PT,China,L,China,50,"NLP, PyTorch, Kubernetes, Linux, SQL",Bachelor,6,Technology,2024-11-25,2025-01-24,2146,9.1,AI Innovations -AI04260,Autonomous Systems Engineer,70641,USD,70641,SE,FT,China,M,China,50,"Statistics, R, Python, Git",Master,9,Retail,2024-02-10,2024-03-13,960,9.9,Neural Networks Co -AI04261,Deep Learning Engineer,57845,AUD,78091,EN,CT,Australia,S,Australia,50,"Statistics, Python, PyTorch, R, Spark",Associate,1,Technology,2025-04-19,2025-05-15,1260,5.4,Quantum Computing Inc -AI04262,Deep Learning Engineer,70641,USD,70641,EX,PT,India,S,India,0,"Statistics, Tableau, R, Spark, GCP",Associate,18,Government,2024-10-30,2024-11-19,623,9.6,Autonomous Tech -AI04263,NLP Engineer,266056,SGD,345873,EX,FL,Singapore,L,Singapore,50,"SQL, PyTorch, NLP, Python",Associate,13,Transportation,2024-02-02,2024-03-01,1761,9.8,Digital Transformation LLC -AI04264,AI Software Engineer,39810,USD,39810,MI,PT,China,L,India,100,"PyTorch, Spark, Data Visualization, Kubernetes",Master,3,Telecommunications,2024-10-30,2024-12-17,1598,7.4,Algorithmic Solutions -AI04265,ML Ops Engineer,46834,USD,46834,MI,FT,China,L,China,0,"Git, GCP, AWS, Mathematics",Bachelor,3,Media,2024-06-30,2024-08-02,2086,7.2,AI Innovations -AI04266,Autonomous Systems Engineer,151336,GBP,113502,SE,FT,United Kingdom,L,United Kingdom,100,"Kubernetes, Python, Scala, GCP",Bachelor,7,Technology,2025-03-26,2025-04-16,930,7.3,Cloud AI Solutions -AI04267,AI Consultant,76149,EUR,64727,EN,PT,Austria,L,Austria,0,"Linux, Hadoop, Statistics, Scala, Mathematics",PhD,0,Technology,2025-04-08,2025-06-09,2299,9.7,Cognitive Computing -AI04268,AI Specialist,132231,USD,132231,EX,PT,Israel,S,Israel,100,"Tableau, Python, TensorFlow",Master,11,Automotive,2024-09-20,2024-11-24,526,6.7,Cognitive Computing -AI04269,AI Consultant,163387,USD,163387,SE,CT,Denmark,M,Denmark,50,"R, AWS, Git, Data Visualization",Bachelor,7,Transportation,2024-08-19,2024-10-30,635,5.8,DataVision Ltd -AI04270,Deep Learning Engineer,63017,SGD,81922,EN,CT,Singapore,M,Singapore,50,"Spark, Python, Java, Docker, Scala",Associate,1,Media,2024-12-10,2025-02-10,2238,5.3,Predictive Systems -AI04271,NLP Engineer,33704,USD,33704,MI,FT,India,S,Austria,0,"Java, Python, Mathematics, Git",PhD,4,Technology,2024-10-13,2024-12-18,1957,9.6,Smart Analytics -AI04272,NLP Engineer,199909,USD,199909,EX,CT,Finland,M,Finland,100,"Spark, Git, Linux, Statistics",Master,10,Technology,2024-08-31,2024-09-21,2126,7.7,Future Systems -AI04273,AI Specialist,109037,USD,109037,MI,PT,United States,M,United States,0,"Kubernetes, Python, PyTorch",PhD,2,Consulting,2024-04-29,2024-06-25,1905,6.3,Algorithmic Solutions -AI04274,Data Analyst,79918,EUR,67930,EN,FT,France,L,France,50,"Spark, Computer Vision, AWS, SQL",Associate,0,Gaming,2024-03-12,2024-04-05,2142,6.6,DataVision Ltd -AI04275,Data Analyst,140756,EUR,119643,EX,CT,Austria,S,Romania,50,"MLOps, Python, Tableau",PhD,12,Education,2025-03-06,2025-03-28,1437,5.1,Autonomous Tech -AI04276,Research Scientist,193092,CAD,241365,EX,CT,Canada,S,France,0,"Scala, Git, Data Visualization, Mathematics, Tableau",Associate,14,Automotive,2024-10-29,2024-11-12,2415,9.2,Quantum Computing Inc -AI04277,Head of AI,152328,USD,152328,MI,FT,Norway,L,Norway,50,"Java, Python, AWS",Associate,4,Healthcare,2024-10-09,2024-12-07,1932,6.3,Advanced Robotics -AI04278,NLP Engineer,115808,USD,115808,MI,FL,Norway,L,Norway,100,"Python, TensorFlow, Mathematics, Scala",Bachelor,3,Telecommunications,2024-03-27,2024-04-29,1892,7.4,Cognitive Computing -AI04279,Head of AI,123117,EUR,104649,SE,CT,Austria,S,Austria,50,"Git, AWS, Docker",Bachelor,6,Automotive,2025-01-14,2025-03-02,951,6.4,DataVision Ltd -AI04280,AI Architect,48031,USD,48031,EN,CT,Israel,S,New Zealand,100,"PyTorch, Mathematics, MLOps, SQL, Deep Learning",PhD,1,Automotive,2024-05-15,2024-06-08,1171,6.9,DeepTech Ventures -AI04281,Research Scientist,267720,USD,267720,EX,FL,United States,S,United States,100,"Tableau, Scala, Hadoop, SQL, Kubernetes",Master,16,Technology,2024-07-19,2024-08-30,2497,9.6,Neural Networks Co -AI04282,Head of AI,130274,JPY,14330140,SE,FT,Japan,L,Luxembourg,50,"SQL, Docker, PyTorch, Git",Master,5,Government,2025-04-21,2025-06-04,2222,5.6,Neural Networks Co -AI04283,Deep Learning Engineer,217100,USD,217100,SE,CT,Norway,L,Hungary,0,"Java, Computer Vision, SQL, NLP, Linux",Master,9,Retail,2025-03-08,2025-04-15,593,5.2,Autonomous Tech -AI04284,AI Software Engineer,69518,USD,69518,EN,FT,Denmark,S,Denmark,100,"NLP, SQL, Linux, Scala",Bachelor,1,Education,2024-03-09,2024-03-25,1880,7.4,Cognitive Computing -AI04285,AI Specialist,149647,CAD,187059,EX,FL,Canada,S,Canada,0,"Spark, SQL, Python, Computer Vision",Associate,14,Finance,2025-03-12,2025-05-15,2155,9.2,Digital Transformation LLC -AI04286,NLP Engineer,56185,SGD,73041,EN,PT,Singapore,S,New Zealand,50,"Kubernetes, Data Visualization, Python, TensorFlow, GCP",Bachelor,1,Transportation,2025-04-11,2025-06-10,1919,5.2,Future Systems -AI04287,Head of AI,47695,USD,47695,EN,FT,Sweden,S,Sweden,50,"Spark, Kubernetes, NLP, TensorFlow, Deep Learning",PhD,0,Gaming,2024-01-14,2024-02-24,1378,7.9,DeepTech Ventures -AI04288,AI Specialist,100301,EUR,85256,SE,PT,Germany,S,Germany,50,"Hadoop, Kubernetes, Scala, Computer Vision",PhD,7,Retail,2024-07-17,2024-08-31,1403,9.4,Quantum Computing Inc -AI04289,Machine Learning Engineer,66736,USD,66736,MI,FL,South Korea,M,South Korea,100,"Linux, Kubernetes, Data Visualization, Hadoop, Computer Vision",PhD,4,Gaming,2024-08-25,2024-09-20,754,5.8,Future Systems -AI04290,Principal Data Scientist,71795,JPY,7897450,EN,FL,Japan,L,Egypt,50,"SQL, PyTorch, TensorFlow, Azure",PhD,1,Government,2024-03-21,2024-04-26,2175,5.4,Cognitive Computing -AI04291,ML Ops Engineer,40743,USD,40743,MI,FT,China,M,China,50,"SQL, PyTorch, Data Visualization, Scala",PhD,4,Consulting,2024-05-01,2024-06-09,1212,5.2,Quantum Computing Inc -AI04292,Deep Learning Engineer,50361,EUR,42807,EN,FT,France,M,Belgium,100,"Linux, SQL, Hadoop, Python, Computer Vision",Bachelor,1,Media,2024-09-02,2024-09-25,607,7.3,Algorithmic Solutions -AI04293,Computer Vision Engineer,25504,USD,25504,EN,CT,India,S,India,100,"Python, Deep Learning, NLP, Mathematics, Spark",Master,0,Manufacturing,2024-12-01,2025-01-31,1174,6.5,Algorithmic Solutions -AI04294,Robotics Engineer,100549,USD,100549,SE,FT,South Korea,S,Spain,50,"Kubernetes, Statistics, Spark",Master,5,Healthcare,2024-07-23,2024-09-25,1869,8.2,Autonomous Tech -AI04295,Machine Learning Engineer,96451,EUR,81983,SE,PT,Austria,S,Austria,50,"Deep Learning, Git, Python",Master,7,Transportation,2024-12-23,2025-02-16,1078,7.9,Quantum Computing Inc -AI04296,NLP Engineer,94478,USD,94478,SE,FL,Sweden,S,Sweden,0,"Data Visualization, Computer Vision, Kubernetes",Bachelor,9,Media,2024-04-18,2024-06-14,677,8.3,Autonomous Tech -AI04297,Data Analyst,69250,EUR,58863,EN,CT,Netherlands,S,Ukraine,100,"Linux, PyTorch, R, Java, Git",Master,1,Automotive,2025-01-17,2025-03-05,1851,5.7,DataVision Ltd -AI04298,Data Analyst,99816,USD,99816,MI,CT,Ireland,L,Estonia,100,"Docker, Python, MLOps, Linux, TensorFlow",PhD,2,Retail,2024-02-29,2024-04-10,1889,9.9,Advanced Robotics -AI04299,Data Scientist,151190,USD,151190,SE,FL,Sweden,M,Sweden,100,"Kubernetes, Hadoop, Scala",Bachelor,7,Automotive,2024-04-24,2024-05-23,1258,9.2,Algorithmic Solutions -AI04300,Principal Data Scientist,234904,JPY,25839440,EX,PT,Japan,S,Japan,50,"Kubernetes, Data Visualization, Spark, Docker",PhD,15,Manufacturing,2024-08-03,2024-09-25,1974,9.6,Autonomous Tech -AI04301,AI Architect,100583,CHF,90525,EN,CT,Switzerland,L,China,100,"Computer Vision, AWS, Scala",Bachelor,1,Government,2024-05-11,2024-07-03,1471,8,DeepTech Ventures -AI04302,Head of AI,193990,USD,193990,EX,PT,United States,L,Israel,0,"Python, Kubernetes, Tableau",Associate,15,Consulting,2024-12-25,2025-03-03,2132,8.8,Digital Transformation LLC -AI04303,AI Product Manager,138206,EUR,117475,SE,FL,France,L,United Kingdom,100,"Statistics, PyTorch, Computer Vision, Mathematics, TensorFlow",Associate,7,Education,2025-03-24,2025-05-05,2261,8.5,Neural Networks Co -AI04304,Data Analyst,130833,AUD,176625,SE,PT,Australia,M,Austria,50,"Git, Scala, TensorFlow, AWS, R",Associate,6,Telecommunications,2024-12-06,2025-02-08,1325,6.7,DataVision Ltd -AI04305,Data Scientist,178524,USD,178524,SE,PT,Denmark,M,Sweden,50,"Python, Azure, Tableau, Hadoop",PhD,9,Healthcare,2024-01-31,2024-03-14,1457,7,Quantum Computing Inc -AI04306,NLP Engineer,58009,USD,58009,EN,FT,South Korea,S,South Korea,0,"Data Visualization, Git, Hadoop, SQL",PhD,0,Finance,2024-04-12,2024-05-18,650,9.2,Predictive Systems -AI04307,Autonomous Systems Engineer,51134,USD,51134,MI,CT,China,L,China,100,"TensorFlow, Statistics, Deep Learning",Bachelor,2,Education,2024-09-22,2024-11-21,2371,9,Future Systems -AI04308,Data Engineer,121528,EUR,103299,SE,FT,Germany,M,Germany,100,"TensorFlow, Kubernetes, Computer Vision, Tableau, Data Visualization",Associate,7,Energy,2025-04-03,2025-06-07,1250,5.6,Advanced Robotics -AI04309,NLP Engineer,161005,USD,161005,SE,CT,Israel,L,Israel,50,"Spark, PyTorch, Tableau",Bachelor,8,Transportation,2024-09-14,2024-10-22,2281,8.4,DeepTech Ventures -AI04310,Head of AI,172723,GBP,129542,EX,FL,United Kingdom,M,Ireland,50,"SQL, Git, PyTorch, Linux, Data Visualization",Bachelor,11,Media,2024-03-12,2024-05-19,2264,8.2,Advanced Robotics -AI04311,AI Consultant,124515,EUR,105838,EX,CT,Austria,S,Latvia,100,"Docker, Linux, Data Visualization, SQL",PhD,13,Transportation,2025-02-24,2025-05-06,2164,6.2,Cloud AI Solutions -AI04312,AI Research Scientist,80001,CAD,100001,EN,CT,Canada,L,Canada,0,"Docker, Kubernetes, Spark",Bachelor,1,Manufacturing,2024-01-19,2024-02-02,827,6,Neural Networks Co -AI04313,ML Ops Engineer,106148,EUR,90226,SE,CT,Netherlands,S,Ghana,0,"SQL, TensorFlow, Hadoop",Master,8,Education,2024-12-05,2025-02-10,1912,5.4,Cognitive Computing -AI04314,Computer Vision Engineer,88162,EUR,74938,MI,FL,France,M,France,50,"Data Visualization, Scala, GCP, Python, PyTorch",Master,2,Real Estate,2025-04-16,2025-05-29,1187,5.3,DeepTech Ventures -AI04315,Principal Data Scientist,80965,USD,80965,MI,CT,Israel,S,Argentina,0,"Tableau, Linux, Azure",Master,3,Gaming,2025-03-16,2025-04-03,1786,6,Predictive Systems -AI04316,AI Software Engineer,102591,USD,102591,MI,FL,Sweden,L,Sweden,50,"Docker, SQL, Hadoop, PyTorch",Bachelor,3,Real Estate,2024-06-14,2024-07-17,1331,6.2,Autonomous Tech -AI04317,Data Analyst,83458,CAD,104323,EN,FL,Canada,L,Romania,0,"Mathematics, Kubernetes, MLOps, Hadoop",Bachelor,0,Consulting,2024-06-14,2024-08-21,1749,6.3,Quantum Computing Inc -AI04318,Machine Learning Engineer,131559,EUR,111825,SE,CT,Germany,S,Austria,0,"Hadoop, Linux, Docker",PhD,5,Transportation,2024-01-12,2024-02-25,1897,8.8,Predictive Systems -AI04319,Robotics Engineer,103944,USD,103944,MI,FT,Finland,M,Finland,100,"Linux, MLOps, Computer Vision",PhD,2,Government,2024-10-04,2024-12-14,661,5.1,Smart Analytics -AI04320,AI Specialist,92612,USD,92612,EX,FL,China,S,China,0,"Java, Kubernetes, Python, Git",Bachelor,18,Consulting,2024-12-05,2025-02-02,2154,8.7,Autonomous Tech -AI04321,AI Product Manager,91367,USD,91367,SE,PT,South Korea,M,Luxembourg,100,"Azure, TensorFlow, Tableau, Hadoop",Master,5,Healthcare,2024-03-16,2024-05-04,1310,9.8,TechCorp Inc -AI04322,Deep Learning Engineer,102393,CHF,92154,EN,FL,Switzerland,L,Romania,100,"Azure, Deep Learning, Linux, Tableau, SQL",PhD,1,Consulting,2025-04-29,2025-06-12,1531,7.9,Digital Transformation LLC -AI04323,Computer Vision Engineer,126897,EUR,107862,EX,PT,Austria,S,Austria,50,"Python, SQL, Linux",Bachelor,17,Transportation,2024-07-30,2024-08-21,2068,9.9,Future Systems -AI04324,Deep Learning Engineer,49677,USD,49677,EN,FL,Israel,S,Canada,50,"Tableau, Docker, Kubernetes, Scala, Deep Learning",Bachelor,0,Manufacturing,2024-07-04,2024-08-30,2192,9.4,DataVision Ltd -AI04325,Data Scientist,220260,USD,220260,EX,FT,Sweden,S,Sweden,100,"Data Visualization, TensorFlow, Java, Docker",Master,19,Real Estate,2024-06-24,2024-08-24,1627,5.8,Autonomous Tech -AI04326,NLP Engineer,124924,USD,124924,SE,FL,South Korea,M,Singapore,50,"Linux, SQL, PyTorch",Master,6,Consulting,2024-11-13,2024-12-11,2445,8.4,Machine Intelligence Group -AI04327,Autonomous Systems Engineer,221162,USD,221162,SE,FT,Denmark,L,Denmark,100,"PyTorch, Scala, TensorFlow",PhD,8,Government,2024-07-18,2024-09-24,2325,9.6,Predictive Systems -AI04328,Deep Learning Engineer,68143,EUR,57922,EN,FT,France,S,Colombia,100,"Scala, TensorFlow, Azure, Mathematics",PhD,0,Energy,2024-06-07,2024-06-28,504,7.4,DataVision Ltd -AI04329,Machine Learning Engineer,139571,USD,139571,MI,FL,Denmark,L,Germany,0,"Kubernetes, Spark, PyTorch, Docker, AWS",Associate,2,Healthcare,2024-03-23,2024-05-26,2296,8.7,Advanced Robotics -AI04330,Data Analyst,75216,EUR,63934,MI,CT,Austria,M,Austria,50,"Scala, SQL, PyTorch",Associate,4,Education,2024-05-30,2024-08-04,2468,5.5,TechCorp Inc -AI04331,Data Scientist,185001,USD,185001,EX,CT,Denmark,S,Denmark,100,"Mathematics, Python, NLP",Bachelor,16,Gaming,2025-01-16,2025-03-25,1924,8,Smart Analytics -AI04332,AI Software Engineer,92328,JPY,10156080,MI,CT,Japan,L,Japan,50,"Python, GCP, Docker, Data Visualization, Linux",Master,2,Gaming,2024-01-28,2024-04-10,914,8.2,Predictive Systems -AI04333,AI Product Manager,100927,USD,100927,MI,FT,Denmark,S,Canada,50,"Docker, Tableau, Python, Linux, Mathematics",Bachelor,4,Energy,2025-03-20,2025-04-04,787,8.1,AI Innovations -AI04334,Deep Learning Engineer,99845,SGD,129799,MI,CT,Singapore,L,Singapore,0,"Python, Computer Vision, Scala, Docker",PhD,4,Automotive,2024-08-31,2024-10-08,812,8.4,Neural Networks Co -AI04335,Autonomous Systems Engineer,77405,EUR,65794,EN,CT,Germany,L,Austria,0,"Data Visualization, R, Java, Spark, Linux",Bachelor,0,Consulting,2024-05-01,2024-06-13,649,6,Algorithmic Solutions -AI04336,Deep Learning Engineer,60738,GBP,45554,EN,PT,United Kingdom,S,United Kingdom,50,"Python, Docker, AWS, TensorFlow",Master,0,Automotive,2024-03-22,2024-04-26,555,5.7,Digital Transformation LLC -AI04337,AI Software Engineer,105471,JPY,11601810,MI,FL,Japan,L,Japan,0,"Git, Deep Learning, Statistics",Master,4,Energy,2024-06-18,2024-08-02,1116,6.6,Machine Intelligence Group -AI04338,Deep Learning Engineer,159419,USD,159419,EX,FL,Israel,S,Ghana,0,"Deep Learning, SQL, Tableau, Linux",Master,18,Healthcare,2024-01-03,2024-01-28,925,9.1,AI Innovations -AI04339,ML Ops Engineer,90738,SGD,117959,MI,PT,Singapore,M,Singapore,0,"Spark, GCP, Tableau",Bachelor,3,Energy,2024-12-14,2025-01-14,2148,9,Future Systems -AI04340,Machine Learning Engineer,90479,USD,90479,MI,FT,Finland,S,Austria,50,"Java, Python, GCP, Mathematics, TensorFlow",Bachelor,3,Media,2025-02-13,2025-04-22,2020,8.3,Advanced Robotics -AI04341,NLP Engineer,155058,USD,155058,SE,FL,Ireland,L,Ireland,100,"Data Visualization, Python, SQL",Associate,9,Manufacturing,2024-11-21,2024-12-28,1821,8.5,Machine Intelligence Group -AI04342,AI Research Scientist,85529,USD,85529,MI,CT,Israel,S,Israel,50,"Deep Learning, Mathematics, GCP, Kubernetes, Git",Master,2,Consulting,2024-01-12,2024-02-28,1458,7.7,Quantum Computing Inc -AI04343,AI Research Scientist,86082,SGD,111907,MI,FL,Singapore,S,Singapore,100,"Hadoop, Deep Learning, Computer Vision, PyTorch, R",Master,4,Transportation,2025-01-27,2025-03-26,1346,5.7,DataVision Ltd -AI04344,Autonomous Systems Engineer,96560,USD,96560,EN,FT,Norway,L,Norway,50,"R, Spark, SQL, Deep Learning, Python",PhD,1,Automotive,2024-09-22,2024-11-24,1139,8.2,Machine Intelligence Group -AI04345,Research Scientist,83531,EUR,71001,EN,PT,Austria,L,Ghana,100,"TensorFlow, Kubernetes, Mathematics, NLP",Bachelor,0,Gaming,2024-12-04,2025-01-15,1024,5.5,Predictive Systems -AI04346,AI Research Scientist,113892,EUR,96808,SE,FL,Germany,S,Singapore,100,"Data Visualization, Scala, Deep Learning, Docker",Bachelor,8,Automotive,2025-02-16,2025-03-05,863,8,DeepTech Ventures -AI04347,Data Engineer,261519,JPY,28767090,EX,CT,Japan,M,Japan,50,"R, PyTorch, Scala",PhD,18,Media,2024-07-10,2024-08-28,1671,5.4,Neural Networks Co -AI04348,AI Consultant,112036,USD,112036,MI,CT,Israel,L,Israel,50,"Python, MLOps, TensorFlow",PhD,4,Transportation,2025-02-11,2025-04-25,2093,6.4,Autonomous Tech -AI04349,Data Analyst,91847,USD,91847,EN,PT,Sweden,L,Sweden,100,"Deep Learning, Java, Tableau, PyTorch, Git",Associate,0,Government,2024-02-17,2024-03-15,1937,9.1,Cognitive Computing -AI04350,NLP Engineer,58336,USD,58336,EN,FL,Sweden,S,Sweden,0,"TensorFlow, Java, R",Associate,1,Consulting,2025-02-27,2025-05-03,1310,5.9,Digital Transformation LLC -AI04351,AI Research Scientist,66684,USD,66684,EN,CT,Ireland,M,Ireland,0,"SQL, Python, AWS, TensorFlow",Associate,1,Technology,2025-03-07,2025-04-19,533,7.4,Cloud AI Solutions -AI04352,Research Scientist,91813,USD,91813,MI,PT,Ireland,M,Ireland,0,"R, Mathematics, Tableau, NLP, Data Visualization",Bachelor,3,Gaming,2024-12-26,2025-02-18,1649,7.9,TechCorp Inc -AI04353,AI Consultant,138037,USD,138037,SE,CT,United States,M,United States,0,"Azure, TensorFlow, GCP",Master,7,Transportation,2024-03-25,2024-04-27,1243,7.5,Autonomous Tech -AI04354,Data Analyst,118721,USD,118721,EN,CT,Denmark,L,New Zealand,50,"Hadoop, Tableau, Azure, MLOps, PyTorch",Associate,1,Real Estate,2025-03-21,2025-04-15,2159,7.7,Digital Transformation LLC -AI04355,NLP Engineer,70536,USD,70536,EN,FL,Israel,L,Ghana,50,"Azure, Scala, Docker",Master,1,Technology,2024-04-20,2024-06-05,2136,8.6,Future Systems -AI04356,Research Scientist,96320,EUR,81872,MI,PT,France,L,France,0,"Kubernetes, TensorFlow, NLP",Associate,4,Gaming,2024-12-26,2025-02-28,1277,5.5,TechCorp Inc -AI04357,Head of AI,134322,EUR,114174,SE,FT,Austria,L,Austria,100,"GCP, Deep Learning, Git, Python",Bachelor,8,Consulting,2024-02-03,2024-04-13,848,6.9,Autonomous Tech -AI04358,Robotics Engineer,61853,USD,61853,EN,FL,United States,M,United States,100,"Spark, R, Data Visualization",Master,0,Finance,2024-04-10,2024-05-17,1366,7.6,TechCorp Inc -AI04359,Robotics Engineer,118786,EUR,100968,SE,CT,Austria,S,Austria,0,"Scala, SQL, Computer Vision",Bachelor,5,Consulting,2024-07-22,2024-08-19,818,8.3,Cognitive Computing -AI04360,Autonomous Systems Engineer,63582,USD,63582,EN,FL,Ireland,S,Ireland,50,"Spark, AWS, GCP",PhD,1,Media,2024-01-11,2024-03-21,2243,9.4,Cognitive Computing -AI04361,Machine Learning Engineer,120025,AUD,162034,SE,FT,Australia,L,Norway,50,"PyTorch, Kubernetes, Spark, Java, Mathematics",Bachelor,8,Transportation,2025-03-13,2025-04-02,2126,7.5,Quantum Computing Inc -AI04362,Data Analyst,69623,EUR,59180,MI,CT,France,S,France,0,"Python, SQL, Java, R, AWS",PhD,2,Real Estate,2024-12-02,2025-01-02,1244,9.6,Machine Intelligence Group -AI04363,AI Architect,84572,USD,84572,EN,CT,Denmark,M,Denmark,50,"NLP, Computer Vision, Data Visualization, Deep Learning",Master,0,Finance,2024-07-03,2024-08-31,1897,8,Machine Intelligence Group -AI04364,Machine Learning Engineer,75649,USD,75649,SE,CT,China,L,China,100,"TensorFlow, Linux, Spark, Python, Azure",PhD,8,Transportation,2024-07-23,2024-09-19,1102,5.3,Smart Analytics -AI04365,AI Software Engineer,101898,USD,101898,EN,FL,Norway,M,Netherlands,50,"Python, Scala, Docker, Mathematics, AWS",Bachelor,1,Automotive,2024-03-26,2024-04-18,2051,5.1,Smart Analytics -AI04366,AI Product Manager,146918,EUR,124880,SE,FT,Netherlands,M,Kenya,50,"R, MLOps, PyTorch, NLP",Master,6,Energy,2024-02-18,2024-03-08,770,10,Advanced Robotics -AI04367,Principal Data Scientist,48437,USD,48437,SE,PT,India,S,Norway,100,"Hadoop, Linux, Azure, Computer Vision",PhD,6,Government,2024-12-31,2025-01-23,1949,8.8,DeepTech Ventures -AI04368,AI Software Engineer,156021,USD,156021,EX,CT,Israel,L,Ireland,100,"Scala, Python, SQL",Associate,15,Energy,2024-10-16,2024-12-16,2144,9,DataVision Ltd -AI04369,Research Scientist,142101,USD,142101,SE,PT,Sweden,L,Sweden,100,"Kubernetes, Java, Data Visualization",Master,7,Energy,2024-01-16,2024-03-26,623,6.7,Advanced Robotics -AI04370,AI Research Scientist,85556,EUR,72723,MI,PT,Germany,L,Germany,0,"TensorFlow, Tableau, Python, GCP",Associate,4,Telecommunications,2024-11-06,2025-01-04,1206,8.4,Quantum Computing Inc -AI04371,AI Research Scientist,36647,USD,36647,MI,PT,China,S,Turkey,0,"Java, AWS, GCP, Computer Vision",PhD,2,Retail,2025-03-11,2025-04-20,2008,7.2,Digital Transformation LLC -AI04372,Data Scientist,82294,EUR,69950,MI,CT,Austria,L,Denmark,50,"Spark, Mathematics, Deep Learning, Computer Vision",Master,2,Finance,2024-02-01,2024-03-25,1644,7.3,Predictive Systems -AI04373,AI Specialist,91519,AUD,123551,MI,FL,Australia,L,Australia,100,"Data Visualization, GCP, AWS, Docker",Bachelor,2,Real Estate,2025-04-13,2025-06-10,2219,6.2,Digital Transformation LLC -AI04374,Data Analyst,67529,USD,67529,SE,CT,China,L,Kenya,0,"Spark, Linux, Data Visualization, Scala",Master,7,Consulting,2025-01-24,2025-02-13,1676,6,AI Innovations -AI04375,Data Engineer,194639,USD,194639,EX,FT,Ireland,L,Ireland,0,"Tableau, NLP, SQL",Bachelor,13,Manufacturing,2024-05-04,2024-07-13,1333,5.7,Algorithmic Solutions -AI04376,AI Product Manager,194962,USD,194962,EX,FL,South Korea,M,South Korea,0,"Tableau, Azure, PyTorch, AWS",PhD,17,Real Estate,2024-12-12,2025-02-01,513,6.2,TechCorp Inc -AI04377,Machine Learning Engineer,68003,CAD,85004,MI,FL,Canada,M,Canada,0,"PyTorch, Linux, TensorFlow, Spark",PhD,3,Gaming,2024-08-11,2024-08-26,534,6.1,Digital Transformation LLC -AI04378,Data Engineer,160113,USD,160113,SE,FL,United States,L,United States,100,"Python, Scala, Azure, AWS",Master,7,Automotive,2024-10-07,2024-11-30,1941,6.5,DeepTech Ventures -AI04379,Head of AI,51041,USD,51041,EN,FT,Ireland,S,Ireland,50,"Hadoop, Linux, Mathematics",Associate,0,Government,2025-01-06,2025-01-24,1849,7.6,Autonomous Tech -AI04380,Robotics Engineer,123576,USD,123576,MI,CT,Denmark,S,Denmark,0,"Java, R, Tableau, AWS",Bachelor,3,Healthcare,2024-04-11,2024-05-21,1068,8.6,Advanced Robotics -AI04381,Machine Learning Researcher,76765,EUR,65250,MI,FT,Netherlands,M,Australia,100,"R, SQL, Tableau, Docker, Deep Learning",Associate,2,Finance,2024-10-25,2024-12-25,1685,6.4,TechCorp Inc -AI04382,Data Scientist,212410,USD,212410,EX,CT,Israel,L,Israel,100,"Hadoop, Azure, Statistics",Bachelor,17,Retail,2024-09-28,2024-11-01,1414,9.4,Cognitive Computing -AI04383,Computer Vision Engineer,64240,USD,64240,SE,PT,China,M,China,50,"Hadoop, Scala, PyTorch",Bachelor,8,Retail,2024-09-01,2024-10-28,2324,6.4,Neural Networks Co -AI04384,Autonomous Systems Engineer,132240,USD,132240,EX,CT,Finland,M,Spain,0,"Tableau, Python, Spark, Statistics",PhD,16,Real Estate,2024-08-22,2024-10-19,1289,8.4,Quantum Computing Inc -AI04385,Machine Learning Engineer,90724,CAD,113405,MI,PT,Canada,S,Belgium,0,"Python, GCP, TensorFlow, Spark, AWS",Master,3,Telecommunications,2024-06-29,2024-08-26,1928,7.8,Cloud AI Solutions -AI04386,Machine Learning Researcher,210905,USD,210905,EX,FT,Norway,L,Norway,100,"PyTorch, TensorFlow, Tableau, Data Visualization, Python",Master,12,Real Estate,2024-03-24,2024-05-11,1507,8.1,Cloud AI Solutions -AI04387,AI Product Manager,113235,AUD,152867,SE,PT,Australia,S,Argentina,0,"Python, TensorFlow, Azure",Master,7,Gaming,2024-03-03,2024-04-25,617,8,Algorithmic Solutions -AI04388,AI Software Engineer,167568,EUR,142433,EX,PT,France,S,United States,50,"Mathematics, PyTorch, SQL, Git, Docker",PhD,19,Government,2025-04-20,2025-05-13,1087,6.4,Quantum Computing Inc -AI04389,Data Engineer,60687,USD,60687,EN,FL,Finland,M,Finland,0,"AWS, NLP, Statistics, Python, Deep Learning",PhD,1,Consulting,2024-07-28,2024-09-29,1930,5.3,Advanced Robotics -AI04390,Computer Vision Engineer,140330,USD,140330,EX,PT,Finland,S,Belgium,50,"Python, Scala, Hadoop, Computer Vision, TensorFlow",PhD,16,Technology,2024-08-13,2024-10-12,1619,7.5,DeepTech Ventures -AI04391,Machine Learning Researcher,87316,EUR,74219,MI,FL,Netherlands,S,Netherlands,50,"Data Visualization, Azure, Git",Bachelor,2,Automotive,2024-04-25,2024-06-13,558,7,Cloud AI Solutions -AI04392,AI Software Engineer,103223,USD,103223,EN,CT,United States,L,United States,50,"Linux, Docker, NLP, Computer Vision, Kubernetes",Bachelor,0,Real Estate,2024-12-01,2025-02-02,1214,5,Advanced Robotics -AI04393,Head of AI,259484,GBP,194613,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, Hadoop, TensorFlow, GCP",PhD,19,Energy,2025-01-04,2025-03-16,1671,5.7,Predictive Systems -AI04394,Machine Learning Researcher,83379,USD,83379,EN,FL,United States,S,United States,100,"Tableau, Scala, SQL",PhD,1,Energy,2024-04-16,2024-05-07,831,6.5,Predictive Systems -AI04395,ML Ops Engineer,108902,GBP,81677,MI,FT,United Kingdom,M,United Kingdom,0,"Linux, MLOps, Data Visualization",Bachelor,3,Technology,2024-04-27,2024-06-13,1500,9.9,Future Systems -AI04396,Data Engineer,56324,USD,56324,EN,FT,Finland,L,Finland,0,"R, SQL, MLOps, Linux",PhD,1,Gaming,2024-02-29,2024-03-16,1319,9.6,Cognitive Computing -AI04397,Principal Data Scientist,117902,EUR,100217,MI,FL,Netherlands,L,Netherlands,100,"Deep Learning, Python, NLP",Bachelor,4,Technology,2024-09-06,2024-10-22,2283,5.6,Algorithmic Solutions -AI04398,AI Software Engineer,113637,EUR,96591,MI,FT,Netherlands,L,Netherlands,50,"Scala, SQL, Statistics",Master,3,Retail,2025-02-15,2025-03-31,1625,7.6,Neural Networks Co -AI04399,AI Specialist,100672,EUR,85571,MI,PT,Germany,M,Israel,100,"R, SQL, TensorFlow",Associate,3,Retail,2024-12-11,2025-02-16,1012,8.1,Cognitive Computing -AI04400,Robotics Engineer,59217,JPY,6513870,EN,FL,Japan,S,Nigeria,100,"SQL, R, Data Visualization",Bachelor,0,Technology,2024-05-26,2024-07-02,1332,6.2,Cloud AI Solutions -AI04401,AI Specialist,180746,USD,180746,EX,FL,Ireland,L,Ireland,0,"Scala, Azure, NLP",Bachelor,18,Finance,2024-02-29,2024-04-12,778,9,Cognitive Computing -AI04402,NLP Engineer,76000,AUD,102600,EN,FT,Australia,M,Russia,50,"Azure, Hadoop, Tableau",Bachelor,1,Retail,2025-02-21,2025-03-30,1457,9,Digital Transformation LLC -AI04403,AI Consultant,158289,CAD,197861,EX,CT,Canada,S,Canada,50,"Azure, Python, AWS, TensorFlow",Associate,19,Finance,2024-03-29,2024-05-07,904,6.7,Autonomous Tech -AI04404,AI Software Engineer,210409,USD,210409,EX,CT,South Korea,L,Denmark,100,"Git, Statistics, Azure, SQL, Computer Vision",Bachelor,12,Telecommunications,2024-05-24,2024-06-13,1401,9.6,AI Innovations -AI04405,Data Analyst,72009,USD,72009,MI,CT,Ireland,S,Ireland,0,"Kubernetes, Tableau, TensorFlow, MLOps, Python",PhD,2,Healthcare,2025-01-15,2025-02-17,1726,7,AI Innovations -AI04406,Computer Vision Engineer,216981,SGD,282075,EX,FT,Singapore,L,Estonia,0,"SQL, MLOps, Git, Docker",Master,12,Government,2025-02-02,2025-02-20,884,5.1,Cognitive Computing -AI04407,AI Architect,125378,USD,125378,MI,FL,Denmark,M,Denmark,100,"Spark, Computer Vision, NLP, R",Bachelor,4,Consulting,2024-07-28,2024-08-17,1609,8.1,Advanced Robotics -AI04408,Machine Learning Researcher,80879,USD,80879,MI,CT,United States,S,United States,50,"AWS, Tableau, Linux",PhD,3,Automotive,2024-10-17,2024-12-25,1607,8.5,Cloud AI Solutions -AI04409,Data Scientist,304522,SGD,395879,EX,FT,Singapore,L,Vietnam,0,"TensorFlow, Python, Tableau, Docker",Master,10,Consulting,2025-03-09,2025-05-03,2161,9.3,Autonomous Tech -AI04410,Autonomous Systems Engineer,106646,USD,106646,MI,FT,Sweden,M,Sweden,50,"Java, Kubernetes, Tableau, SQL",PhD,3,Automotive,2025-02-15,2025-03-23,2468,7,Neural Networks Co -AI04411,AI Architect,91413,SGD,118837,MI,PT,Singapore,M,Spain,100,"Mathematics, Computer Vision, NLP, TensorFlow",PhD,4,Technology,2024-11-24,2025-01-13,881,9,Neural Networks Co -AI04412,Deep Learning Engineer,224651,USD,224651,EX,FL,Denmark,L,Denmark,100,"Git, Kubernetes, Python",Bachelor,19,Technology,2024-12-11,2025-02-14,1208,9.4,DataVision Ltd -AI04413,AI Architect,130860,USD,130860,EX,PT,South Korea,L,South Korea,50,"TensorFlow, Docker, MLOps, Kubernetes, Data Visualization",PhD,13,Education,2025-03-19,2025-04-27,1934,7.1,Smart Analytics -AI04414,Machine Learning Researcher,46877,USD,46877,EN,CT,Israel,S,Israel,100,"NLP, TensorFlow, Mathematics, MLOps",PhD,0,Consulting,2024-05-28,2024-06-13,2354,7,Digital Transformation LLC -AI04415,Deep Learning Engineer,179047,EUR,152190,EX,PT,France,M,France,0,"NLP, Docker, Mathematics, Computer Vision, PyTorch",Master,18,Media,2024-10-13,2024-10-27,2472,9.9,Machine Intelligence Group -AI04416,Data Engineer,104146,EUR,88524,SE,FL,Austria,M,Turkey,0,"Docker, Python, Mathematics",PhD,8,Technology,2024-03-15,2024-05-04,1388,5,Machine Intelligence Group -AI04417,AI Consultant,31567,USD,31567,MI,FL,India,S,India,0,"Kubernetes, Git, GCP, Linux",Bachelor,2,Manufacturing,2025-01-23,2025-03-27,1204,6.6,DataVision Ltd -AI04418,Principal Data Scientist,97690,USD,97690,SE,FL,South Korea,S,Kenya,100,"Linux, Computer Vision, Deep Learning, Kubernetes",PhD,7,Transportation,2024-08-22,2024-09-17,2486,6.6,Autonomous Tech -AI04419,Head of AI,62371,AUD,84201,EN,FT,Australia,M,Australia,50,"Azure, NLP, SQL",PhD,0,Technology,2024-09-13,2024-10-11,1120,7.4,DeepTech Ventures -AI04420,AI Product Manager,262516,CHF,236264,EX,FL,Switzerland,L,Switzerland,50,"Scala, Spark, Docker, Kubernetes",Bachelor,19,Media,2024-09-02,2024-10-15,614,9.1,Cognitive Computing -AI04421,AI Specialist,75844,CAD,94805,MI,FL,Canada,S,India,100,"TensorFlow, Kubernetes, Tableau",Associate,2,Energy,2024-05-27,2024-07-01,2116,9.7,Future Systems -AI04422,Data Scientist,131997,JPY,14519670,SE,FL,Japan,L,Thailand,0,"Kubernetes, PyTorch, Computer Vision",Master,5,Government,2024-07-10,2024-08-23,1204,6.1,Smart Analytics -AI04423,Principal Data Scientist,103953,EUR,88360,MI,FT,Netherlands,M,Netherlands,0,"SQL, NLP, PyTorch, Computer Vision, Hadoop",Master,3,Transportation,2024-12-25,2025-01-28,1919,5.8,TechCorp Inc -AI04424,AI Specialist,177676,USD,177676,SE,PT,Denmark,L,Denmark,0,"Azure, Java, Python, Linux, Statistics",Bachelor,8,Finance,2024-11-21,2024-12-30,2199,9.3,Algorithmic Solutions -AI04425,AI Product Manager,122946,AUD,165977,SE,PT,Australia,S,Australia,0,"Spark, Kubernetes, Git, Java, GCP",PhD,9,Education,2024-12-26,2025-02-23,835,7.1,TechCorp Inc -AI04426,Head of AI,202266,USD,202266,EX,CT,Israel,S,Israel,50,"GCP, Computer Vision, SQL, Azure",Associate,12,Healthcare,2024-08-02,2024-09-17,1550,5.9,AI Innovations -AI04427,Machine Learning Engineer,42862,USD,42862,SE,FL,India,S,Russia,100,"Git, Java, Kubernetes, R, Mathematics",Bachelor,5,Gaming,2024-11-08,2025-01-17,1330,6.6,DeepTech Ventures -AI04428,Data Scientist,221324,USD,221324,SE,FT,Norway,L,Spain,100,"Spark, R, Tableau, Python, Linux",Bachelor,7,Retail,2025-04-01,2025-04-29,1133,7.6,Predictive Systems -AI04429,Machine Learning Researcher,129064,SGD,167783,MI,CT,Singapore,L,Hungary,100,"Python, Hadoop, Statistics",Bachelor,4,Manufacturing,2024-07-07,2024-09-17,2002,5.8,TechCorp Inc -AI04430,Computer Vision Engineer,116116,CAD,145145,SE,FT,Canada,L,Singapore,100,"AWS, SQL, Deep Learning, Kubernetes",PhD,8,Manufacturing,2024-06-25,2024-07-12,849,8.3,Algorithmic Solutions -AI04431,Data Scientist,204614,AUD,276229,EX,CT,Australia,L,Australia,0,"Linux, MLOps, NLP, PyTorch",Associate,19,Telecommunications,2025-04-07,2025-04-23,1784,9.7,Neural Networks Co -AI04432,Data Engineer,44008,USD,44008,EX,FT,India,S,India,100,"TensorFlow, Python, Java, Scala, Azure",PhD,15,Transportation,2024-03-12,2024-04-08,1391,5.9,Smart Analytics -AI04433,AI Research Scientist,59937,USD,59937,SE,PT,China,M,Indonesia,100,"PyTorch, TensorFlow, Git",Bachelor,9,Technology,2024-08-21,2024-11-02,798,9.2,Predictive Systems -AI04434,AI Product Manager,86443,USD,86443,MI,PT,Israel,S,Belgium,50,"SQL, Java, MLOps",Master,4,Technology,2024-10-15,2024-11-10,1882,5.9,Digital Transformation LLC -AI04435,AI Specialist,104949,SGD,136434,SE,FL,Singapore,S,Singapore,50,"Java, Linux, Spark",Bachelor,6,Manufacturing,2024-06-07,2024-08-15,855,9.8,Digital Transformation LLC -AI04436,Principal Data Scientist,186813,USD,186813,EX,CT,Ireland,S,France,100,"NLP, Linux, Java",Bachelor,17,Healthcare,2024-01-03,2024-03-12,958,8.6,Algorithmic Solutions -AI04437,AI Specialist,211822,JPY,23300420,EX,FL,Japan,L,Indonesia,50,"Computer Vision, Hadoop, Python, SQL",Bachelor,13,Transportation,2024-03-23,2024-05-05,2204,9.4,Cognitive Computing -AI04438,AI Consultant,153646,SGD,199740,EX,FL,Singapore,M,Romania,100,"Mathematics, PyTorch, MLOps",Master,18,Real Estate,2024-01-07,2024-03-14,607,7.6,DeepTech Ventures -AI04439,Data Analyst,117982,USD,117982,SE,PT,Israel,M,Israel,0,"Python, Linux, R, TensorFlow",PhD,5,Gaming,2024-02-18,2024-04-23,752,9.9,Quantum Computing Inc -AI04440,Data Engineer,133740,SGD,173862,SE,FL,Singapore,S,Mexico,0,"Java, SQL, Mathematics, Deep Learning",Associate,9,Government,2025-01-10,2025-01-24,2271,7.8,Algorithmic Solutions -AI04441,Machine Learning Researcher,84175,USD,84175,EN,FL,Denmark,S,Chile,0,"Azure, Mathematics, MLOps, Scala, Git",Bachelor,1,Healthcare,2024-02-17,2024-04-07,2409,6.9,Smart Analytics -AI04442,Computer Vision Engineer,87366,GBP,65525,MI,CT,United Kingdom,S,Vietnam,0,"Azure, Python, Data Visualization, Mathematics, Computer Vision",Bachelor,2,Consulting,2024-11-26,2024-12-11,1180,10,Digital Transformation LLC -AI04443,Autonomous Systems Engineer,110287,USD,110287,MI,CT,Sweden,L,Vietnam,50,"GCP, Spark, Azure, PyTorch",Bachelor,4,Retail,2025-02-14,2025-03-21,674,7.8,Quantum Computing Inc -AI04444,Data Scientist,104258,USD,104258,SE,CT,South Korea,L,South Korea,0,"Statistics, Kubernetes, R, Java",Associate,8,Automotive,2024-10-26,2024-12-01,2028,9.2,Machine Intelligence Group -AI04445,AI Software Engineer,114211,USD,114211,EN,FT,Denmark,L,Ireland,100,"Python, Kubernetes, Docker",PhD,0,Healthcare,2025-01-07,2025-03-10,1349,9,DeepTech Ventures -AI04446,Head of AI,194011,EUR,164909,EX,PT,France,L,France,100,"PyTorch, Python, NLP, Hadoop",Master,18,Healthcare,2025-04-08,2025-06-06,814,8.4,Algorithmic Solutions -AI04447,Principal Data Scientist,293192,USD,293192,EX,FL,Sweden,L,Sweden,50,"Azure, AWS, Linux, Scala, R",Associate,13,Technology,2024-12-07,2025-01-29,2000,8.4,Future Systems -AI04448,Robotics Engineer,53874,EUR,45793,EN,FL,France,S,France,100,"GCP, R, Statistics",PhD,1,Manufacturing,2024-03-15,2024-04-01,503,6.9,TechCorp Inc -AI04449,Robotics Engineer,88454,USD,88454,SE,CT,Finland,S,Finland,0,"Docker, Hadoop, GCP, Java, Scala",PhD,7,Media,2025-04-25,2025-06-28,2354,5.2,Predictive Systems -AI04450,Robotics Engineer,161911,SGD,210484,EX,CT,Singapore,S,Singapore,50,"SQL, Scala, Linux, Azure",Associate,11,Healthcare,2024-11-04,2025-01-11,1397,8.7,DeepTech Ventures -AI04451,AI Consultant,64565,USD,64565,MI,FT,South Korea,S,South Korea,100,"Hadoop, Git, Tableau, NLP, Azure",PhD,4,Gaming,2024-09-13,2024-10-18,2397,8.1,DeepTech Ventures -AI04452,Data Scientist,47708,USD,47708,EN,CT,Israel,S,Philippines,100,"Python, TensorFlow, Azure, Linux",Bachelor,1,Technology,2024-06-13,2024-07-03,1203,9.5,DeepTech Ventures -AI04453,AI Product Manager,140313,SGD,182407,SE,FL,Singapore,M,Singapore,50,"Mathematics, Scala, Deep Learning",Master,6,Energy,2024-08-15,2024-09-27,1946,6.2,Neural Networks Co -AI04454,AI Software Engineer,94235,JPY,10365850,EN,FL,Japan,L,Spain,100,"R, Tableau, Python, Azure, TensorFlow",Associate,1,Consulting,2024-05-05,2024-07-07,2010,9.2,Machine Intelligence Group -AI04455,Data Engineer,57467,USD,57467,MI,CT,South Korea,S,South Korea,0,"Computer Vision, Spark, Docker, Hadoop, Python",PhD,3,Government,2024-07-21,2024-08-18,1968,8,Neural Networks Co -AI04456,AI Research Scientist,129225,SGD,167993,SE,PT,Singapore,M,Finland,0,"Hadoop, Python, PyTorch, Git",Associate,9,Healthcare,2025-03-22,2025-05-16,1335,5.9,DeepTech Ventures -AI04457,Data Scientist,157816,USD,157816,EX,PT,Ireland,M,Ireland,100,"Scala, GCP, AWS",Bachelor,12,Manufacturing,2025-04-22,2025-06-12,733,10,Neural Networks Co -AI04458,Data Engineer,77796,EUR,66127,MI,FL,Austria,S,Austria,50,"Python, TensorFlow, Tableau",Bachelor,2,Automotive,2024-01-09,2024-01-26,832,5.4,Predictive Systems -AI04459,Deep Learning Engineer,202840,EUR,172414,EX,FT,Netherlands,S,Netherlands,0,"Git, Spark, Computer Vision, Tableau, Java",Associate,17,Manufacturing,2025-02-22,2025-03-18,1954,8.6,Smart Analytics -AI04460,Data Scientist,77051,AUD,104019,EN,FL,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch",Master,0,Media,2024-09-30,2024-11-08,2129,5.6,Advanced Robotics -AI04461,AI Specialist,105395,AUD,142283,MI,FT,Australia,L,Australia,50,"Linux, Git, Kubernetes, NLP, Python",Master,2,Transportation,2024-06-25,2024-08-27,1203,7.1,TechCorp Inc -AI04462,AI Research Scientist,83359,EUR,70855,EN,FL,Netherlands,M,Netherlands,100,"Kubernetes, Java, Data Visualization",Bachelor,0,Real Estate,2025-01-21,2025-02-19,1507,5.4,Machine Intelligence Group -AI04463,Machine Learning Engineer,98213,CHF,88392,EN,CT,Switzerland,L,Switzerland,0,"Java, SQL, Kubernetes, PyTorch",Associate,1,Media,2024-12-23,2025-01-23,1844,8.8,Cognitive Computing -AI04464,AI Software Engineer,39868,USD,39868,MI,FL,China,S,China,100,"R, Docker, TensorFlow, Git",Master,2,Automotive,2024-09-25,2024-11-20,526,5.1,Future Systems -AI04465,Computer Vision Engineer,246512,USD,246512,EX,CT,Norway,M,Norway,0,"Data Visualization, Git, Linux",Bachelor,19,Manufacturing,2025-01-24,2025-03-24,2255,10,Quantum Computing Inc -AI04466,AI Software Engineer,77063,USD,77063,EX,CT,India,M,India,50,"MLOps, Git, Kubernetes",Associate,18,Media,2025-03-31,2025-05-21,680,9.8,Advanced Robotics -AI04467,Principal Data Scientist,60066,EUR,51056,EN,PT,Germany,L,Germany,50,"Deep Learning, Scala, Data Visualization",Associate,0,Media,2024-11-03,2024-11-25,1884,9.6,Quantum Computing Inc -AI04468,NLP Engineer,93900,USD,93900,MI,CT,Ireland,L,Ireland,50,"Linux, AWS, NLP, Git",Bachelor,3,Retail,2024-11-04,2024-12-02,918,5.8,DeepTech Ventures -AI04469,Machine Learning Engineer,132017,EUR,112214,SE,PT,Germany,L,China,50,"GCP, Statistics, SQL, TensorFlow",PhD,7,Technology,2025-03-15,2025-05-08,1645,9.5,Cognitive Computing -AI04470,Head of AI,94447,USD,94447,MI,CT,Norway,S,Norway,0,"Kubernetes, SQL, TensorFlow, PyTorch",Master,4,Education,2024-11-14,2025-01-04,1613,7.8,Cognitive Computing -AI04471,AI Software Engineer,65304,USD,65304,EX,FL,India,M,India,50,"MLOps, Python, TensorFlow, Docker",Associate,12,Finance,2024-07-19,2024-08-04,574,5.8,Cognitive Computing -AI04472,AI Software Engineer,172150,EUR,146328,SE,FL,Netherlands,L,Netherlands,100,"Spark, PyTorch, Data Visualization, Computer Vision",Associate,9,Transportation,2024-11-26,2024-12-10,2024,5.7,Digital Transformation LLC -AI04473,NLP Engineer,88827,USD,88827,MI,FT,Ireland,M,Ireland,50,"Computer Vision, R, Azure, Deep Learning, MLOps",Bachelor,4,Retail,2024-07-13,2024-09-06,2422,7.2,Future Systems -AI04474,Data Engineer,144886,AUD,195596,SE,FT,Australia,L,Australia,0,"Git, GCP, Linux, Computer Vision",Master,8,Manufacturing,2024-07-09,2024-09-11,1834,8.3,Future Systems -AI04475,Research Scientist,133043,USD,133043,EX,FL,Israel,S,France,0,"Python, Deep Learning, Java",PhD,16,Transportation,2024-04-05,2024-06-06,2319,8.8,Advanced Robotics -AI04476,AI Software Engineer,127811,EUR,108639,SE,FL,Netherlands,L,Ireland,50,"Scala, Azure, Docker, AWS, Mathematics",Associate,7,Automotive,2024-11-27,2024-12-24,1278,9.6,Quantum Computing Inc -AI04477,Computer Vision Engineer,103521,CAD,129401,SE,CT,Canada,S,Canada,50,"R, Java, Tableau, Docker",Associate,7,Real Estate,2024-01-04,2024-02-16,2044,5.6,Predictive Systems -AI04478,Research Scientist,54480,SGD,70824,EN,FL,Singapore,M,Singapore,50,"Spark, TensorFlow, MLOps, Python",Master,1,Education,2025-01-30,2025-02-17,1495,9.3,Autonomous Tech -AI04479,Principal Data Scientist,74709,EUR,63503,MI,FL,France,M,France,50,"Scala, Git, MLOps, Statistics",Bachelor,4,Technology,2024-09-11,2024-10-15,1967,5.8,Machine Intelligence Group -AI04480,Computer Vision Engineer,59379,USD,59379,EN,FL,Israel,S,Czech Republic,100,"Java, Computer Vision, MLOps",PhD,1,Government,2025-01-18,2025-02-14,2335,8,Advanced Robotics -AI04481,AI Product Manager,61440,USD,61440,SE,FT,China,M,Japan,0,"Scala, Mathematics, Java",PhD,5,Telecommunications,2024-08-17,2024-10-11,1501,8,Neural Networks Co -AI04482,Autonomous Systems Engineer,134360,GBP,100770,EX,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Python, NLP, TensorFlow, Java",Master,17,Gaming,2024-04-11,2024-05-05,2337,7,Autonomous Tech -AI04483,AI Product Manager,225183,JPY,24770130,EX,FL,Japan,S,Japan,50,"Data Visualization, MLOps, TensorFlow",PhD,13,Energy,2024-10-12,2024-12-17,729,8.6,Algorithmic Solutions -AI04484,Principal Data Scientist,262051,CAD,327564,EX,FT,Canada,L,Colombia,100,"R, Tableau, Statistics, Hadoop, SQL",Bachelor,18,Government,2025-01-30,2025-02-20,678,5.4,Digital Transformation LLC -AI04485,ML Ops Engineer,51148,USD,51148,MI,FL,China,L,Norway,50,"Docker, MLOps, Hadoop, R, Azure",Bachelor,3,Energy,2024-11-06,2024-12-17,1629,9.4,Smart Analytics -AI04486,Deep Learning Engineer,50384,USD,50384,SE,CT,India,L,Finland,100,"Azure, NLP, Spark, Tableau",Bachelor,9,Technology,2024-11-21,2024-12-31,1978,7.9,Algorithmic Solutions -AI04487,Autonomous Systems Engineer,45747,CAD,57184,EN,PT,Canada,S,Philippines,0,"Azure, Docker, Deep Learning, Data Visualization, Python",Master,1,Manufacturing,2024-09-27,2024-12-03,2476,8.3,AI Innovations -AI04488,AI Architect,27660,USD,27660,EN,CT,China,M,China,50,"PyTorch, Git, Hadoop",Master,0,Healthcare,2024-09-12,2024-10-31,2159,7.4,Future Systems -AI04489,Machine Learning Researcher,66412,USD,66412,EN,CT,Finland,L,Finland,0,"Python, Linux, Spark, NLP",Associate,1,Gaming,2024-10-27,2024-11-26,1366,7.1,Autonomous Tech -AI04490,Computer Vision Engineer,286005,USD,286005,EX,CT,Ireland,L,Ireland,100,"R, Python, TensorFlow, PyTorch",Associate,15,Telecommunications,2024-03-06,2024-05-04,1637,9.4,Digital Transformation LLC -AI04491,Data Scientist,162115,EUR,137798,EX,PT,Austria,S,South Africa,50,"Hadoop, PyTorch, Git, R",Master,15,Automotive,2024-09-21,2024-10-27,780,6.4,AI Innovations -AI04492,Autonomous Systems Engineer,179992,JPY,19799120,EX,FL,Japan,M,Japan,50,"Scala, Azure, Deep Learning, Data Visualization",Master,10,Media,2025-01-23,2025-02-12,2176,8.4,Future Systems -AI04493,Data Analyst,52604,USD,52604,EN,FL,Sweden,S,Finland,50,"NLP, Scala, Data Visualization, Kubernetes",Bachelor,1,Energy,2025-01-15,2025-02-20,2181,9.8,DataVision Ltd -AI04494,AI Consultant,135693,USD,135693,MI,FL,Norway,L,Switzerland,0,"Kubernetes, PyTorch, GCP, Scala",Bachelor,2,Healthcare,2024-05-16,2024-05-30,1410,7.8,Autonomous Tech -AI04495,Data Scientist,132806,USD,132806,SE,CT,Norway,M,Norway,100,"Java, PyTorch, Data Visualization, Deep Learning, GCP",PhD,5,Government,2024-08-09,2024-09-10,745,10,TechCorp Inc -AI04496,AI Consultant,119154,CHF,107239,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Tableau, PyTorch",PhD,3,Technology,2024-04-25,2024-07-05,1701,5.6,TechCorp Inc -AI04497,NLP Engineer,116153,CHF,104538,EN,FT,Switzerland,L,Switzerland,0,"PyTorch, SQL, Docker, Deep Learning",PhD,1,Telecommunications,2024-05-22,2024-07-08,2130,5.5,DataVision Ltd -AI04498,AI Product Manager,122285,USD,122285,SE,FL,Norway,S,South Africa,50,"Computer Vision, R, Java, Azure",PhD,7,Consulting,2024-08-05,2024-10-07,1831,8.3,Digital Transformation LLC -AI04499,AI Research Scientist,87146,USD,87146,SE,FL,South Korea,M,South Korea,0,"R, Linux, MLOps, Mathematics, Git",Bachelor,7,Retail,2025-01-06,2025-03-05,2199,5.7,AI Innovations -AI04500,Head of AI,101820,AUD,137457,MI,CT,Australia,M,Ukraine,50,"AWS, Statistics, Data Visualization",Associate,4,Technology,2025-03-18,2025-04-17,1073,6.2,AI Innovations -AI04501,AI Research Scientist,76032,EUR,64627,MI,FL,France,M,Netherlands,100,"PyTorch, GCP, TensorFlow, NLP, Python",Bachelor,3,Consulting,2024-09-08,2024-10-08,1911,8.6,Digital Transformation LLC -AI04502,AI Software Engineer,138064,JPY,15187040,SE,FL,Japan,L,Japan,100,"GCP, PyTorch, Spark",Bachelor,5,Government,2024-02-22,2024-03-17,1028,8.1,Smart Analytics -AI04503,Research Scientist,131574,AUD,177625,SE,FL,Australia,L,Philippines,0,"Python, Spark, Azure, Linux",Bachelor,6,Finance,2024-09-30,2024-11-24,1280,6.4,Digital Transformation LLC -AI04504,Head of AI,366922,CHF,330230,EX,FL,Switzerland,L,Malaysia,0,"TensorFlow, Computer Vision, Hadoop, Python, MLOps",Bachelor,14,Real Estate,2024-01-21,2024-02-06,2396,9.3,Quantum Computing Inc -AI04505,AI Consultant,113179,USD,113179,EN,FT,Denmark,L,Denmark,0,"Git, Docker, Hadoop",Bachelor,1,Automotive,2024-06-26,2024-07-25,1016,8.2,DeepTech Ventures -AI04506,Robotics Engineer,249140,AUD,336339,EX,FL,Australia,L,Australia,100,"Scala, Statistics, NLP",PhD,18,Transportation,2024-07-22,2024-08-22,1206,6.1,Algorithmic Solutions -AI04507,Principal Data Scientist,171609,EUR,145868,EX,FT,Netherlands,M,Germany,50,"Spark, SQL, Java, MLOps, Linux",Bachelor,10,Education,2024-04-27,2024-06-17,2287,7.4,Smart Analytics -AI04508,Machine Learning Engineer,105792,EUR,89923,SE,FL,France,S,Portugal,50,"Spark, NLP, Git, Computer Vision",Master,6,Telecommunications,2024-05-31,2024-07-25,2141,5.3,Cognitive Computing -AI04509,Machine Learning Researcher,173700,USD,173700,EX,FT,South Korea,M,Luxembourg,100,"MLOps, Python, Data Visualization, Mathematics, Linux",Bachelor,19,Finance,2024-01-18,2024-03-02,529,6.5,Predictive Systems -AI04510,Data Analyst,97074,EUR,82513,MI,PT,Netherlands,L,Netherlands,100,"Data Visualization, Linux, Python, MLOps, SQL",Associate,4,Automotive,2025-01-16,2025-02-09,1335,8.4,Smart Analytics -AI04511,Machine Learning Researcher,22207,USD,22207,EN,CT,India,M,India,100,"Deep Learning, Git, Mathematics",Master,1,Energy,2024-03-19,2024-05-08,602,9.6,TechCorp Inc -AI04512,Machine Learning Researcher,166711,USD,166711,SE,PT,Ireland,L,Ireland,100,"Spark, PyTorch, NLP, TensorFlow",Bachelor,8,Consulting,2024-12-01,2024-12-17,886,7.1,Advanced Robotics -AI04513,Machine Learning Researcher,91344,EUR,77642,MI,PT,Germany,S,Austria,100,"Spark, Python, Data Visualization",PhD,4,Telecommunications,2024-01-27,2024-03-30,1213,9.8,TechCorp Inc -AI04514,Data Scientist,171048,USD,171048,SE,FT,Denmark,L,Denmark,0,"PyTorch, SQL, Spark, TensorFlow, Data Visualization",PhD,7,Gaming,2024-12-19,2025-01-04,1329,7.1,Algorithmic Solutions -AI04515,AI Software Engineer,129514,USD,129514,EX,PT,Israel,M,Israel,0,"Python, AWS, GCP, R",Bachelor,14,Real Estate,2025-02-14,2025-04-06,2310,6.5,Future Systems -AI04516,AI Research Scientist,70909,USD,70909,MI,FL,Ireland,S,Ireland,100,"AWS, MLOps, PyTorch, TensorFlow",Master,4,Telecommunications,2024-11-09,2024-12-08,926,6.6,AI Innovations -AI04517,Deep Learning Engineer,55311,EUR,47014,EN,FT,France,M,France,0,"Java, MLOps, TensorFlow, Statistics",Master,1,Healthcare,2024-07-29,2024-09-25,1413,5.2,Smart Analytics -AI04518,Deep Learning Engineer,61598,USD,61598,EX,FT,India,M,India,50,"Linux, Deep Learning, NLP",Bachelor,18,Gaming,2024-04-06,2024-06-04,2247,7,Machine Intelligence Group -AI04519,AI Product Manager,129700,USD,129700,MI,CT,Norway,L,South Korea,0,"Tableau, SQL, Docker",Master,2,Consulting,2025-02-13,2025-03-25,1327,8.3,Autonomous Tech -AI04520,AI Specialist,135809,EUR,115438,SE,FT,Netherlands,S,Netherlands,0,"Scala, R, SQL, Data Visualization, Git",Associate,6,Consulting,2025-03-28,2025-04-22,695,7.3,Autonomous Tech -AI04521,Deep Learning Engineer,238500,EUR,202725,EX,FL,Netherlands,S,South Korea,0,"Linux, Computer Vision, Kubernetes",Associate,18,Transportation,2024-04-01,2024-05-27,1845,6,AI Innovations -AI04522,Head of AI,50048,SGD,65062,EN,FT,Singapore,S,Czech Republic,50,"PyTorch, TensorFlow, Docker",Associate,0,Energy,2024-05-14,2024-06-03,680,7.1,Algorithmic Solutions -AI04523,Autonomous Systems Engineer,164914,USD,164914,SE,PT,United States,L,United States,50,"Hadoop, TensorFlow, Linux, MLOps, GCP",Master,8,Consulting,2024-03-04,2024-04-22,917,7.1,Cloud AI Solutions -AI04524,AI Consultant,181134,CAD,226418,EX,CT,Canada,M,Canada,0,"Git, PyTorch, GCP, AWS, Mathematics",Master,19,Healthcare,2024-01-15,2024-02-05,2366,5.9,Machine Intelligence Group -AI04525,AI Specialist,81453,EUR,69235,EN,FL,Netherlands,L,Netherlands,50,"TensorFlow, Java, Deep Learning, Tableau",Associate,1,Education,2025-02-09,2025-03-27,2323,9.2,DataVision Ltd -AI04526,Machine Learning Researcher,52632,USD,52632,EN,FL,Israel,S,Israel,50,"SQL, Spark, Tableau, Scala",PhD,0,Retail,2024-03-15,2024-04-16,585,8.8,Neural Networks Co -AI04527,Data Analyst,77848,USD,77848,EN,FL,Denmark,L,Denmark,50,"SQL, GCP, PyTorch, Java",PhD,0,Government,2025-02-04,2025-03-16,1735,6.9,DataVision Ltd -AI04528,Autonomous Systems Engineer,117315,USD,117315,SE,PT,Sweden,M,Singapore,0,"Computer Vision, Java, MLOps, Kubernetes, Docker",PhD,5,Retail,2024-08-23,2024-10-07,1852,9,DeepTech Ventures -AI04529,AI Architect,166998,USD,166998,SE,CT,Denmark,S,Israel,100,"MLOps, Linux, Data Visualization, Computer Vision",Associate,7,Manufacturing,2025-02-18,2025-04-09,1054,7.3,Neural Networks Co -AI04530,Head of AI,174172,GBP,130629,SE,CT,United Kingdom,L,United Kingdom,50,"TensorFlow, Python, Linux, Hadoop, Statistics",Associate,8,Healthcare,2024-11-09,2024-12-24,574,5.7,Machine Intelligence Group -AI04531,ML Ops Engineer,93049,CAD,116311,MI,CT,Canada,M,Canada,100,"PyTorch, Data Visualization, SQL, Kubernetes",Bachelor,2,Consulting,2025-04-27,2025-05-12,812,7.4,DeepTech Ventures -AI04532,Robotics Engineer,139395,USD,139395,SE,FL,Sweden,L,Sweden,100,"Docker, SQL, Scala, MLOps, Kubernetes",Master,6,Retail,2024-01-08,2024-02-04,1681,6.5,Algorithmic Solutions -AI04533,AI Software Engineer,207936,USD,207936,SE,FT,Norway,L,Norway,100,"Hadoop, Python, AWS, Linux",Bachelor,6,Technology,2024-11-16,2024-12-12,2030,5,Cognitive Computing -AI04534,Machine Learning Engineer,188512,EUR,160235,EX,CT,Austria,M,Austria,50,"Docker, Git, SQL, Spark, Linux",Master,18,Healthcare,2024-04-03,2024-06-09,1323,9.7,Smart Analytics -AI04535,AI Specialist,176564,GBP,132423,EX,FT,United Kingdom,M,Egypt,0,"Azure, Kubernetes, Linux, SQL",PhD,11,Finance,2024-01-11,2024-02-21,631,7.3,Predictive Systems -AI04536,Research Scientist,156332,GBP,117249,SE,CT,United Kingdom,L,Denmark,100,"Kubernetes, Mathematics, Hadoop, MLOps",Bachelor,7,Manufacturing,2025-02-19,2025-04-25,1511,10,Cognitive Computing -AI04537,Data Scientist,113860,USD,113860,MI,FL,United States,M,United States,50,"Tableau, Kubernetes, Java, MLOps",Bachelor,4,Finance,2024-09-16,2024-11-20,1497,9,DeepTech Ventures -AI04538,Data Scientist,95951,USD,95951,MI,FL,Finland,L,Finland,0,"SQL, Mathematics, Kubernetes, Python",Master,2,Media,2024-10-14,2024-12-07,2141,8.2,AI Innovations -AI04539,Data Engineer,177286,CHF,159557,SE,CT,Switzerland,S,Switzerland,50,"Scala, GCP, SQL, MLOps",Associate,7,Manufacturing,2024-04-28,2024-06-22,2473,9.8,Predictive Systems -AI04540,AI Software Engineer,53681,CAD,67101,EN,CT,Canada,M,Canada,50,"Tableau, Azure, Java, Data Visualization",Associate,0,Energy,2024-05-04,2024-05-26,2123,8.3,AI Innovations -AI04541,AI Research Scientist,130939,AUD,176768,SE,FL,Australia,M,Ireland,100,"Data Visualization, GCP, SQL, NLP, Linux",Bachelor,5,Automotive,2024-07-18,2024-09-10,562,6.6,Autonomous Tech -AI04542,Principal Data Scientist,39395,USD,39395,SE,PT,India,M,India,0,"Spark, Data Visualization, Linux, Deep Learning",PhD,7,Transportation,2024-10-05,2024-10-28,1164,8.6,Algorithmic Solutions -AI04543,AI Architect,123582,USD,123582,MI,FL,Norway,M,Norway,0,"Scala, Java, Spark, Mathematics",PhD,3,Manufacturing,2025-03-21,2025-04-10,630,9.6,Predictive Systems -AI04544,AI Research Scientist,136808,EUR,116287,EX,CT,Netherlands,S,Netherlands,0,"Git, TensorFlow, Scala, GCP, Python",PhD,17,Manufacturing,2024-02-20,2024-03-10,2222,8.2,Advanced Robotics -AI04545,Computer Vision Engineer,38736,USD,38736,SE,FT,India,S,India,100,"Python, Java, TensorFlow, Computer Vision, AWS",Bachelor,5,Retail,2025-03-25,2025-04-29,544,9,TechCorp Inc -AI04546,Data Engineer,111692,USD,111692,SE,CT,Ireland,M,Ireland,0,"Python, Scala, Statistics, NLP, Git",Associate,8,Manufacturing,2025-01-27,2025-03-22,2475,5.5,AI Innovations -AI04547,Robotics Engineer,320350,CHF,288315,EX,FT,Switzerland,M,Switzerland,100,"MLOps, PyTorch, Python, Spark",Bachelor,16,Energy,2024-07-25,2024-09-30,2313,6.9,Digital Transformation LLC -AI04548,Data Scientist,148284,EUR,126041,EX,FL,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,14,Consulting,2024-01-26,2024-03-04,1188,5.7,TechCorp Inc -AI04549,AI Research Scientist,164350,USD,164350,EX,FL,Israel,S,Israel,50,"Java, Docker, Azure, Computer Vision, AWS",Master,19,Consulting,2025-04-20,2025-06-23,2272,9.9,Quantum Computing Inc -AI04550,AI Specialist,300752,CHF,270677,EX,FT,Switzerland,L,Switzerland,100,"Mathematics, Hadoop, Data Visualization, R",Associate,14,Retail,2024-08-16,2024-08-30,1923,9.1,Smart Analytics -AI04551,Research Scientist,71687,USD,71687,SE,CT,China,L,Singapore,0,"Docker, AWS, Computer Vision, Java",Associate,7,Education,2024-02-24,2024-04-25,1076,8,Cloud AI Solutions -AI04552,Robotics Engineer,78911,CAD,98639,MI,FL,Canada,S,Canada,100,"Data Visualization, Python, GCP",PhD,4,Government,2024-10-21,2024-11-17,1168,9.7,Machine Intelligence Group -AI04553,Machine Learning Researcher,85224,USD,85224,MI,CT,Israel,L,Israel,50,"NLP, Hadoop, GCP",Bachelor,4,Consulting,2024-12-18,2025-02-27,1115,7,Cloud AI Solutions -AI04554,AI Research Scientist,30653,USD,30653,MI,PT,India,S,India,100,"Java, TensorFlow, R, GCP",Bachelor,2,Media,2025-03-06,2025-04-14,2316,9.7,Neural Networks Co -AI04555,AI Consultant,125667,USD,125667,MI,FT,Sweden,L,Ireland,100,"Java, Computer Vision, MLOps, Tableau",Bachelor,3,Healthcare,2024-08-06,2024-09-08,1356,7.9,Quantum Computing Inc -AI04556,Data Scientist,59008,USD,59008,EN,FT,Finland,M,Argentina,100,"MLOps, Python, Java, AWS, TensorFlow",Bachelor,1,Education,2024-01-03,2024-03-02,816,8.3,Machine Intelligence Group -AI04557,Head of AI,87615,USD,87615,MI,FL,Norway,S,Norway,100,"Linux, Computer Vision, Statistics, Deep Learning",Bachelor,3,Education,2024-03-18,2024-04-27,2060,6.4,Algorithmic Solutions -AI04558,AI Specialist,64656,USD,64656,SE,FL,China,M,China,0,"NLP, SQL, Spark, TensorFlow, MLOps",PhD,7,Government,2024-11-29,2024-12-24,1692,5.7,TechCorp Inc -AI04559,NLP Engineer,236797,JPY,26047670,EX,CT,Japan,S,Turkey,50,"Scala, Java, Python, Kubernetes",Master,17,Automotive,2024-03-20,2024-05-11,1015,8.6,Autonomous Tech -AI04560,AI Research Scientist,69325,EUR,58926,EN,FT,Germany,L,United Kingdom,0,"SQL, MLOps, Spark, Computer Vision",Associate,0,Finance,2024-06-12,2024-08-02,1048,9.9,TechCorp Inc -AI04561,Research Scientist,100014,USD,100014,SE,FL,South Korea,S,South Korea,50,"Scala, Java, Deep Learning, NLP",Associate,7,Finance,2024-02-23,2024-03-14,1690,9.1,AI Innovations -AI04562,ML Ops Engineer,145257,EUR,123468,SE,FT,France,L,France,50,"SQL, MLOps, Python, NLP",Bachelor,5,Transportation,2025-04-21,2025-06-14,1793,7.5,Cloud AI Solutions -AI04563,Robotics Engineer,129098,SGD,167827,SE,CT,Singapore,M,Singapore,100,"AWS, TensorFlow, Python, Tableau, Statistics",Master,9,Real Estate,2024-04-25,2024-05-22,513,6.6,Autonomous Tech -AI04564,AI Research Scientist,58400,USD,58400,EX,FL,India,M,Australia,0,"R, Mathematics, Computer Vision",Master,15,Real Estate,2024-12-04,2025-01-23,1072,6.4,Machine Intelligence Group -AI04565,Data Engineer,146073,USD,146073,EX,CT,Israel,S,Israel,100,"Docker, Kubernetes, GCP",Bachelor,19,Manufacturing,2024-09-01,2024-09-23,2328,5.9,DataVision Ltd -AI04566,ML Ops Engineer,110488,EUR,93915,SE,FL,Germany,M,Germany,100,"MLOps, NLP, SQL",PhD,9,Manufacturing,2025-02-23,2025-05-05,2166,7.7,Cloud AI Solutions -AI04567,Data Analyst,71058,USD,71058,EN,FL,Norway,M,United States,100,"Computer Vision, SQL, NLP",Master,0,Consulting,2024-04-04,2024-06-14,1040,6.3,Cloud AI Solutions -AI04568,Machine Learning Engineer,231110,SGD,300443,EX,FT,Singapore,L,Singapore,100,"Hadoop, Scala, GCP, PyTorch",Associate,17,Energy,2024-12-14,2025-01-17,2122,8.3,TechCorp Inc -AI04569,Data Engineer,138306,EUR,117560,SE,CT,Germany,L,Germany,100,"Java, Kubernetes, AWS",Master,8,Finance,2025-04-27,2025-05-30,1642,9.6,Algorithmic Solutions -AI04570,Principal Data Scientist,187455,CHF,168710,EX,PT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Azure, Deep Learning, Tableau",PhD,12,Energy,2024-04-18,2024-06-05,2092,8.1,Autonomous Tech -AI04571,Autonomous Systems Engineer,94272,CHF,84845,EN,FT,Switzerland,L,Switzerland,100,"Statistics, SQL, Hadoop, Scala, Data Visualization",PhD,1,Government,2024-03-02,2024-04-04,1216,7.8,DeepTech Ventures -AI04572,ML Ops Engineer,136910,EUR,116374,EX,FT,Germany,S,Philippines,100,"Java, AWS, Computer Vision",Bachelor,17,Consulting,2024-10-15,2024-11-27,1487,5.6,Cloud AI Solutions -AI04573,AI Product Manager,155455,CAD,194319,EX,PT,Canada,L,Luxembourg,0,"Java, GCP, Kubernetes, AWS, NLP",Bachelor,16,Transportation,2024-06-01,2024-06-15,625,5.7,Predictive Systems -AI04574,Machine Learning Engineer,218908,JPY,24079880,EX,FT,Japan,S,Japan,100,"Tableau, AWS, MLOps",Associate,14,Finance,2025-01-11,2025-02-25,1370,6.6,Neural Networks Co -AI04575,AI Specialist,58456,EUR,49688,EN,FL,Austria,S,Austria,0,"Scala, Computer Vision, Statistics",Associate,1,Media,2024-12-27,2025-01-16,1460,6.5,Quantum Computing Inc -AI04576,ML Ops Engineer,79370,GBP,59528,EN,CT,United Kingdom,M,Chile,50,"PyTorch, TensorFlow, R",PhD,1,Technology,2025-01-12,2025-03-13,2208,5.9,DeepTech Ventures -AI04577,Head of AI,56598,USD,56598,SE,FT,China,L,China,50,"MLOps, Git, Java, TensorFlow",PhD,8,Retail,2024-02-18,2024-03-28,1009,8.7,DeepTech Ventures -AI04578,Machine Learning Researcher,164862,USD,164862,EX,FL,United States,M,United States,50,"NLP, Linux, Kubernetes, SQL, MLOps",Master,11,Manufacturing,2024-07-28,2024-09-18,1904,6.9,Algorithmic Solutions -AI04579,AI Consultant,78776,USD,78776,MI,PT,South Korea,L,Chile,100,"Data Visualization, MLOps, AWS",Associate,3,Technology,2025-01-11,2025-02-25,2434,7.7,Predictive Systems -AI04580,Principal Data Scientist,107481,GBP,80611,MI,FT,United Kingdom,M,Canada,50,"Linux, R, Python",Master,4,Manufacturing,2024-06-19,2024-08-24,2101,6.1,Cloud AI Solutions -AI04581,AI Specialist,165800,GBP,124350,EX,FL,United Kingdom,M,United Kingdom,50,"Git, Linux, Deep Learning, MLOps, AWS",Associate,11,Energy,2024-09-08,2024-09-26,883,8.3,AI Innovations -AI04582,Data Scientist,114567,EUR,97382,MI,FL,Netherlands,L,Netherlands,100,"Java, Linux, Python, Hadoop, MLOps",Bachelor,4,Technology,2024-10-23,2024-12-23,931,9.8,Digital Transformation LLC -AI04583,Research Scientist,45528,EUR,38699,EN,FL,France,S,France,100,"Python, Azure, Data Visualization, Deep Learning",Bachelor,1,Telecommunications,2024-12-24,2025-02-18,1363,8.7,Neural Networks Co -AI04584,Computer Vision Engineer,156683,GBP,117512,SE,FT,United Kingdom,M,Nigeria,100,"Computer Vision, AWS, Kubernetes, MLOps, Deep Learning",Bachelor,7,Finance,2024-01-22,2024-03-28,1328,8.6,Digital Transformation LLC -AI04585,Machine Learning Engineer,38720,USD,38720,SE,FL,India,S,India,50,"Kubernetes, Linux, Computer Vision, TensorFlow, NLP",PhD,8,Consulting,2024-04-12,2024-04-30,785,8.3,Cognitive Computing -AI04586,ML Ops Engineer,114629,AUD,154749,SE,FL,Australia,M,Australia,0,"R, Azure, SQL",Master,7,Technology,2025-04-19,2025-05-10,1688,5.4,Neural Networks Co -AI04587,Computer Vision Engineer,57392,CAD,71740,EN,FT,Canada,L,Canada,0,"Tableau, SQL, Kubernetes, Hadoop",Associate,1,Gaming,2024-11-30,2025-01-07,1624,6.3,Advanced Robotics -AI04588,Data Scientist,341117,USD,341117,EX,FL,Norway,L,Norway,50,"Linux, Docker, Kubernetes",Bachelor,18,Telecommunications,2024-01-06,2024-01-24,790,8.5,DataVision Ltd -AI04589,ML Ops Engineer,86046,GBP,64535,MI,CT,United Kingdom,S,United Kingdom,0,"Git, R, Spark, Deep Learning, Data Visualization",Bachelor,3,Transportation,2025-01-12,2025-02-21,1892,9.8,Algorithmic Solutions -AI04590,Computer Vision Engineer,149937,USD,149937,EX,PT,South Korea,S,South Korea,50,"Hadoop, Git, SQL",Master,18,Gaming,2024-07-31,2024-10-10,2454,5.1,Machine Intelligence Group -AI04591,Principal Data Scientist,80029,SGD,104038,EN,CT,Singapore,M,Ghana,0,"TensorFlow, MLOps, Data Visualization, Java",Associate,0,Technology,2025-02-26,2025-05-05,2367,9.5,Quantum Computing Inc -AI04592,Machine Learning Engineer,165691,GBP,124268,SE,PT,United Kingdom,L,Ukraine,0,"Scala, Tableau, SQL",Bachelor,9,Healthcare,2024-05-01,2024-06-09,1945,6,Advanced Robotics -AI04593,Autonomous Systems Engineer,141765,EUR,120500,SE,FL,Netherlands,M,Netherlands,0,"Python, PyTorch, Tableau",PhD,7,Telecommunications,2024-06-05,2024-07-31,1988,8.6,Algorithmic Solutions -AI04594,AI Research Scientist,47675,USD,47675,EN,PT,Ireland,S,Ireland,100,"Git, AWS, R, Mathematics, Kubernetes",Master,0,Energy,2024-02-08,2024-03-06,1872,8,Smart Analytics -AI04595,Data Analyst,114484,USD,114484,EX,CT,China,L,China,0,"Spark, PyTorch, Tableau",Bachelor,13,Consulting,2024-12-14,2025-02-08,2154,6.9,Neural Networks Co -AI04596,Machine Learning Engineer,88276,EUR,75035,MI,FT,Austria,S,Norway,100,"TensorFlow, SQL, R, Tableau",Master,4,Healthcare,2024-05-29,2024-06-26,2038,8.3,Cognitive Computing -AI04597,Autonomous Systems Engineer,174969,USD,174969,SE,FT,Sweden,L,Sweden,50,"Java, Azure, R",Associate,8,Telecommunications,2024-11-02,2024-11-18,2445,9.2,Digital Transformation LLC -AI04598,NLP Engineer,193261,USD,193261,EX,FT,South Korea,L,South Korea,50,"Data Visualization, Spark, R, Mathematics, Linux",Associate,10,Education,2024-12-23,2025-03-06,1301,8.7,DataVision Ltd -AI04599,Deep Learning Engineer,58905,USD,58905,EX,CT,India,S,Hungary,100,"SQL, NLP, PyTorch",PhD,12,Automotive,2024-03-26,2024-06-01,1885,5.1,DeepTech Ventures -AI04600,AI Software Engineer,155003,CAD,193754,SE,CT,Canada,L,South Korea,50,"Azure, AWS, Docker",Master,5,Education,2025-04-11,2025-06-16,1609,5.7,Autonomous Tech -AI04601,AI Research Scientist,137955,USD,137955,MI,PT,United States,L,Turkey,50,"TensorFlow, Python, PyTorch, Linux, NLP",PhD,2,Healthcare,2025-04-23,2025-05-24,1334,9.6,AI Innovations -AI04602,NLP Engineer,127644,USD,127644,SE,CT,Finland,M,Finland,100,"MLOps, SQL, Computer Vision",Master,6,Consulting,2024-08-08,2024-10-19,1112,7.2,Future Systems -AI04603,Data Scientist,131769,EUR,112004,SE,FT,France,M,Romania,0,"Python, AWS, MLOps, GCP, SQL",Associate,7,Education,2024-07-11,2024-09-04,1615,9.2,AI Innovations -AI04604,AI Consultant,69280,CAD,86600,MI,FL,Canada,S,Canada,100,"GCP, Azure, Spark",Associate,4,Education,2024-05-26,2024-08-04,2319,8.4,Cloud AI Solutions -AI04605,Computer Vision Engineer,298482,USD,298482,EX,FT,United States,M,United States,0,"Mathematics, Deep Learning, MLOps, PyTorch, AWS",PhD,10,Real Estate,2024-08-11,2024-09-03,2282,9.1,Cognitive Computing -AI04606,Principal Data Scientist,91961,USD,91961,SE,FT,Ireland,S,Ireland,0,"Scala, GCP, Spark, SQL, Mathematics",Master,5,Education,2024-09-08,2024-10-30,781,9,Quantum Computing Inc -AI04607,Research Scientist,108071,EUR,91860,MI,FL,France,L,France,0,"Docker, AWS, GCP, Computer Vision, Azure",Master,4,Education,2024-07-26,2024-09-28,843,8.8,DeepTech Ventures -AI04608,Principal Data Scientist,89067,USD,89067,MI,CT,Denmark,S,India,0,"Python, TensorFlow, AWS, Computer Vision, SQL",PhD,2,Telecommunications,2025-01-06,2025-03-05,1228,8.5,Neural Networks Co -AI04609,Data Engineer,80773,USD,80773,MI,FT,South Korea,S,South Korea,50,"Python, Kubernetes, NLP, Tableau",Master,2,Real Estate,2024-11-01,2024-11-16,1040,5,AI Innovations -AI04610,Machine Learning Researcher,246330,CHF,221697,EX,PT,Switzerland,M,Switzerland,100,"Scala, PyTorch, AWS",Master,17,Government,2025-01-11,2025-03-04,2363,6,Autonomous Tech -AI04611,AI Software Engineer,158632,USD,158632,EX,FL,Sweden,L,Australia,50,"AWS, Kubernetes, TensorFlow, Statistics, SQL",PhD,16,Automotive,2025-03-16,2025-04-19,969,9.8,Quantum Computing Inc -AI04612,Computer Vision Engineer,55191,GBP,41393,EN,FT,United Kingdom,M,United Kingdom,100,"Hadoop, Java, Computer Vision, Spark",Associate,0,Manufacturing,2025-04-03,2025-06-05,2166,6,Autonomous Tech -AI04613,Data Analyst,290447,USD,290447,EX,PT,Norway,L,Norway,100,"R, Mathematics, Scala, PyTorch",Bachelor,17,Energy,2025-03-16,2025-05-13,2278,6.3,Smart Analytics -AI04614,ML Ops Engineer,162470,EUR,138100,EX,PT,Germany,M,Germany,100,"NLP, Docker, GCP",PhD,16,Manufacturing,2024-03-01,2024-05-08,2135,8.3,DeepTech Ventures -AI04615,Data Engineer,237565,USD,237565,EX,CT,Sweden,L,Spain,0,"Spark, Docker, Scala, Computer Vision, Tableau",PhD,13,Energy,2024-09-17,2024-10-29,1692,7.5,Digital Transformation LLC -AI04616,NLP Engineer,74020,USD,74020,MI,FT,Finland,M,Indonesia,100,"SQL, Spark, NLP, Data Visualization, Computer Vision",Master,2,Automotive,2024-03-06,2024-05-13,553,8.5,TechCorp Inc -AI04617,Principal Data Scientist,184394,USD,184394,EX,CT,Sweden,M,Sweden,0,"Spark, Kubernetes, MLOps, NLP, PyTorch",Bachelor,16,Healthcare,2024-04-03,2024-06-08,659,7.3,Autonomous Tech -AI04618,Data Scientist,195735,USD,195735,EX,FT,Norway,M,Norway,0,"Kubernetes, SQL, NLP",Master,14,Real Estate,2024-02-01,2024-03-07,2095,5.8,Cognitive Computing -AI04619,Machine Learning Engineer,321668,USD,321668,EX,FT,Norway,M,Norway,50,"TensorFlow, Git, Python, R",Associate,17,Finance,2024-05-14,2024-06-13,1411,5.6,Quantum Computing Inc -AI04620,Data Analyst,132287,USD,132287,EX,FL,South Korea,L,South Korea,100,"R, Java, NLP",Associate,16,Energy,2025-03-08,2025-04-02,520,7.3,Neural Networks Co -AI04621,AI Architect,70147,CHF,63132,EN,PT,Switzerland,S,China,0,"TensorFlow, NLP, Linux",Master,1,Transportation,2024-05-17,2024-06-18,887,9.1,Autonomous Tech -AI04622,Head of AI,58977,USD,58977,SE,FL,China,L,China,50,"Docker, GCP, Tableau, Computer Vision, Statistics",PhD,7,Consulting,2025-03-15,2025-05-01,1835,6.9,DeepTech Ventures -AI04623,Head of AI,115529,GBP,86647,MI,FT,United Kingdom,M,United Kingdom,50,"Java, Data Visualization, AWS",Master,2,Automotive,2024-05-03,2024-05-30,1604,5.3,Predictive Systems -AI04624,AI Specialist,123402,USD,123402,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Mathematics",Bachelor,5,Gaming,2024-02-15,2024-03-13,697,8.5,DataVision Ltd -AI04625,Robotics Engineer,81236,USD,81236,MI,PT,Sweden,S,Italy,0,"Scala, Deep Learning, Tableau, R, Python",Bachelor,3,Automotive,2024-10-06,2024-11-13,1216,8.6,Predictive Systems -AI04626,Deep Learning Engineer,23762,USD,23762,EN,FT,China,S,China,50,"Computer Vision, Kubernetes, SQL",Associate,1,Automotive,2024-05-10,2024-06-11,1602,8.5,Quantum Computing Inc -AI04627,Head of AI,80966,USD,80966,EN,CT,Norway,M,Norway,0,"Git, Kubernetes, Hadoop",Associate,1,Education,2024-03-20,2024-05-14,2283,6.1,Quantum Computing Inc -AI04628,AI Product Manager,184463,USD,184463,EX,FT,Denmark,M,United Kingdom,0,"Spark, Statistics, Linux, Java, Deep Learning",Master,10,Finance,2024-07-10,2024-08-22,944,9.5,Future Systems -AI04629,Machine Learning Engineer,80922,CHF,72830,EN,FL,Switzerland,S,Switzerland,100,"R, Azure, MLOps, Tableau, AWS",Bachelor,0,Automotive,2024-10-08,2024-11-21,1763,6.1,TechCorp Inc -AI04630,Data Engineer,225786,SGD,293522,EX,FL,Singapore,L,Netherlands,50,"Python, Spark, Deep Learning, Statistics",Bachelor,12,Transportation,2024-11-20,2024-12-20,2261,5.7,Advanced Robotics -AI04631,AI Specialist,174292,USD,174292,EX,FT,Sweden,S,Colombia,50,"Kubernetes, R, Data Visualization",PhD,10,Energy,2024-07-05,2024-08-16,1578,5.5,Future Systems -AI04632,AI Architect,141209,USD,141209,SE,FL,Finland,M,Finland,50,"Java, PyTorch, Tableau",Associate,9,Government,2025-03-15,2025-03-31,1379,5.6,TechCorp Inc -AI04633,AI Architect,33494,USD,33494,EN,FT,China,M,Chile,0,"R, MLOps, SQL, NLP",PhD,1,Gaming,2025-04-18,2025-05-05,2021,8.1,Algorithmic Solutions -AI04634,Head of AI,102081,GBP,76561,MI,FL,United Kingdom,L,Romania,100,"TensorFlow, Git, Spark, Data Visualization",Master,4,Manufacturing,2024-08-05,2024-09-27,1236,5.9,Cloud AI Solutions -AI04635,Computer Vision Engineer,142338,EUR,120987,SE,PT,Netherlands,M,Netherlands,100,"Scala, Kubernetes, Azure, Python",Master,6,Real Estate,2024-04-29,2024-07-02,1165,5.7,Neural Networks Co -AI04636,Robotics Engineer,111416,USD,111416,MI,FL,United States,S,United States,50,"Linux, Java, MLOps, Azure",Bachelor,3,Telecommunications,2024-11-08,2024-12-21,1032,6.8,AI Innovations -AI04637,Data Analyst,171510,USD,171510,EX,CT,Sweden,S,Austria,0,"SQL, Git, PyTorch, TensorFlow, Tableau",Master,14,Gaming,2024-05-10,2024-07-02,845,6.8,Predictive Systems -AI04638,Robotics Engineer,32757,USD,32757,EN,CT,China,S,Philippines,0,"Spark, Linux, PyTorch, Mathematics, Python",PhD,0,Energy,2024-04-27,2024-06-13,1275,9.6,TechCorp Inc -AI04639,Data Analyst,78323,GBP,58742,MI,CT,United Kingdom,S,United States,0,"TensorFlow, GCP, Mathematics, Java, Linux",Bachelor,3,Real Estate,2025-04-17,2025-05-09,942,8.2,DataVision Ltd -AI04640,Robotics Engineer,68649,GBP,51487,EN,FL,United Kingdom,S,Austria,0,"Hadoop, Git, Spark, PyTorch, Linux",PhD,1,Finance,2024-11-02,2024-12-07,1578,9.7,AI Innovations -AI04641,Deep Learning Engineer,82078,AUD,110805,MI,FL,Australia,M,Australia,50,"PyTorch, Java, Scala, Computer Vision, R",Bachelor,2,Energy,2025-03-30,2025-05-07,1484,6.2,Future Systems -AI04642,AI Software Engineer,65931,USD,65931,EN,CT,Denmark,S,Denmark,0,"Kubernetes, PyTorch, Mathematics, Linux, Git",Master,1,Media,2024-06-24,2024-08-13,691,6.8,DataVision Ltd -AI04643,Research Scientist,207846,USD,207846,EX,PT,South Korea,L,South Korea,50,"Linux, MLOps, SQL, Scala",Bachelor,15,Gaming,2024-06-12,2024-07-11,1452,6.7,Autonomous Tech -AI04644,Principal Data Scientist,107642,GBP,80732,MI,PT,United Kingdom,M,United Kingdom,0,"PyTorch, TensorFlow, Python, R, Data Visualization",Bachelor,4,Healthcare,2024-06-30,2024-07-31,2023,5.9,Cloud AI Solutions -AI04645,Head of AI,51450,EUR,43733,EN,PT,Germany,M,Germany,100,"Kubernetes, SQL, Tableau, MLOps, Deep Learning",PhD,0,Finance,2024-08-13,2024-08-31,1211,8.3,DeepTech Ventures -AI04646,Data Scientist,79522,CAD,99403,EN,CT,Canada,L,Germany,100,"Hadoop, Data Visualization, GCP",PhD,0,Gaming,2024-09-24,2024-11-29,802,8.6,Cloud AI Solutions -AI04647,Machine Learning Engineer,100881,USD,100881,MI,FT,Sweden,L,Sweden,100,"R, Azure, Kubernetes, Hadoop",Bachelor,4,Real Estate,2024-03-22,2024-04-21,631,5.3,Advanced Robotics -AI04648,Research Scientist,89648,USD,89648,MI,PT,Ireland,L,Japan,50,"Data Visualization, NLP, Scala, Python",Bachelor,2,Healthcare,2025-03-22,2025-04-18,785,9.6,Neural Networks Co -AI04649,Principal Data Scientist,227077,JPY,24978470,EX,FT,Japan,S,Japan,50,"NLP, PyTorch, GCP, Azure, AWS",Associate,16,Healthcare,2024-06-07,2024-08-15,1178,6.9,Autonomous Tech -AI04650,Data Scientist,141613,EUR,120371,SE,CT,France,L,Mexico,50,"Git, SQL, AWS",Associate,5,Technology,2024-06-13,2024-07-05,1876,9.5,Advanced Robotics -AI04651,AI Specialist,197086,USD,197086,SE,PT,Denmark,L,Denmark,50,"AWS, Linux, PyTorch, Spark",Associate,8,Retail,2024-05-20,2024-06-18,2105,7.5,Smart Analytics -AI04652,Research Scientist,34933,USD,34933,MI,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, Linux, Java",PhD,2,Media,2025-03-20,2025-04-07,683,9.8,AI Innovations -AI04653,AI Consultant,57403,AUD,77494,EN,PT,Australia,M,Australia,0,"Computer Vision, Java, Git, Hadoop",Associate,0,Automotive,2024-09-11,2024-10-22,584,8,TechCorp Inc -AI04654,Robotics Engineer,217171,GBP,162878,EX,FL,United Kingdom,S,United Kingdom,0,"R, Java, Data Visualization, Git, TensorFlow",Master,16,Healthcare,2024-04-24,2024-07-01,836,6.2,AI Innovations -AI04655,Computer Vision Engineer,85086,USD,85086,EX,FL,China,L,China,50,"Tableau, GCP, Python, Azure",Associate,19,Finance,2024-05-03,2024-07-02,1158,9.4,Quantum Computing Inc -AI04656,AI Product Manager,77309,GBP,57982,EN,CT,United Kingdom,L,Netherlands,50,"Python, R, Computer Vision, NLP, Java",Associate,1,Healthcare,2024-07-30,2024-09-21,936,9.9,Advanced Robotics -AI04657,AI Software Engineer,152616,EUR,129724,SE,FT,Netherlands,M,Malaysia,0,"Git, Scala, Deep Learning, Linux, R",Bachelor,5,Education,2024-05-30,2024-07-22,801,9.5,Cloud AI Solutions -AI04658,AI Architect,80354,CAD,100443,MI,FT,Canada,M,Canada,100,"SQL, AWS, MLOps, Linux, Python",Bachelor,3,Government,2025-02-12,2025-03-25,2160,5.3,AI Innovations -AI04659,Principal Data Scientist,130383,USD,130383,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, TensorFlow, Mathematics, Python",PhD,9,Automotive,2024-04-16,2024-06-10,1167,5.6,TechCorp Inc -AI04660,AI Consultant,191150,AUD,258053,EX,PT,Australia,M,India,0,"Kubernetes, Linux, Tableau",Associate,11,Healthcare,2024-12-12,2025-02-09,2246,5,TechCorp Inc -AI04661,AI Specialist,77392,EUR,65783,MI,CT,Germany,S,Germany,50,"TensorFlow, Python, Azure, GCP",Master,4,Telecommunications,2024-05-07,2024-06-23,786,8.2,TechCorp Inc -AI04662,Data Scientist,72963,USD,72963,EN,CT,Israel,L,Israel,50,"Scala, TensorFlow, Deep Learning",Bachelor,0,Energy,2024-09-22,2024-10-31,1307,9.4,Smart Analytics -AI04663,AI Consultant,77791,AUD,105018,EN,FT,Australia,M,Australia,50,"Computer Vision, Git, Azure, Kubernetes, Statistics",Master,0,Real Estate,2024-04-06,2024-04-30,1900,7.2,DataVision Ltd -AI04664,Robotics Engineer,150499,EUR,127924,EX,CT,Austria,L,Russia,100,"Scala, Kubernetes, PyTorch, TensorFlow",Associate,17,Technology,2024-08-04,2024-10-07,1341,9.2,TechCorp Inc -AI04665,Principal Data Scientist,79579,USD,79579,MI,FT,Sweden,M,Sweden,0,"Linux, Python, GCP",PhD,4,Media,2025-01-16,2025-03-01,1594,6.1,DeepTech Ventures -AI04666,AI Software Engineer,251411,EUR,213699,EX,CT,Germany,L,Germany,100,"Python, Kubernetes, TensorFlow, GCP, Scala",Master,11,Retail,2024-02-07,2024-04-13,581,8.3,Autonomous Tech -AI04667,AI Specialist,54870,USD,54870,MI,FT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker, Linux",Master,3,Transportation,2024-05-24,2024-07-18,1639,8.5,Machine Intelligence Group -AI04668,ML Ops Engineer,104878,EUR,89146,SE,FL,France,S,France,0,"PyTorch, Mathematics, Linux, Git, Deep Learning",Master,9,Healthcare,2025-04-15,2025-05-31,597,9.6,Cognitive Computing -AI04669,Data Scientist,76528,USD,76528,MI,FL,South Korea,L,Sweden,50,"TensorFlow, PyTorch, Docker, NLP, Computer Vision",Master,2,Automotive,2024-05-09,2024-06-14,1549,5.7,Cognitive Computing -AI04670,Autonomous Systems Engineer,372494,CHF,335245,EX,FL,Switzerland,L,Switzerland,50,"Kubernetes, Scala, Java, Git, MLOps",Associate,18,Media,2024-01-15,2024-02-24,1253,8.8,Predictive Systems -AI04671,Machine Learning Engineer,135702,USD,135702,SE,PT,Finland,M,Belgium,100,"Scala, Git, Computer Vision",Bachelor,5,Telecommunications,2024-07-23,2024-08-21,563,8.4,Predictive Systems -AI04672,AI Software Engineer,75693,USD,75693,EN,FT,Denmark,S,Denmark,100,"PyTorch, Kubernetes, Azure",Associate,1,Automotive,2025-04-19,2025-06-09,690,9.8,Machine Intelligence Group -AI04673,Data Scientist,104982,USD,104982,EN,FL,Norway,L,Norway,50,"Java, Tableau, Mathematics, Scala",Bachelor,1,Transportation,2025-03-16,2025-04-20,1806,5.6,Advanced Robotics -AI04674,Research Scientist,244711,EUR,208004,EX,FT,Austria,L,Austria,50,"SQL, NLP, MLOps",Master,12,Government,2024-08-29,2024-10-07,2403,8.7,Future Systems -AI04675,Machine Learning Researcher,45500,USD,45500,EN,CT,South Korea,S,South Korea,50,"TensorFlow, Python, AWS",Master,1,Transportation,2024-01-09,2024-02-24,670,6.9,Autonomous Tech -AI04676,Machine Learning Engineer,117161,USD,117161,EX,FL,Israel,S,Russia,100,"R, Hadoop, Python",Bachelor,14,Automotive,2024-08-06,2024-08-26,1132,5.6,TechCorp Inc -AI04677,ML Ops Engineer,69868,CAD,87335,EN,CT,Canada,M,Turkey,100,"TensorFlow, SQL, Azure, AWS",Master,0,Manufacturing,2024-10-06,2024-11-05,1205,7.8,TechCorp Inc -AI04678,Data Engineer,64406,EUR,54745,EN,CT,Austria,M,Austria,50,"Deep Learning, Kubernetes, R",Bachelor,1,Healthcare,2024-09-07,2024-10-23,1125,9.2,Autonomous Tech -AI04679,AI Consultant,237645,EUR,201998,EX,FL,Netherlands,M,Netherlands,100,"Python, TensorFlow, Deep Learning, NLP",Associate,19,Technology,2025-03-22,2025-04-29,1161,5.5,Autonomous Tech -AI04680,AI Product Manager,49582,USD,49582,EN,FL,Finland,S,Finland,100,"GCP, Java, Python",Master,0,Manufacturing,2024-11-10,2024-11-25,1340,7.8,AI Innovations -AI04681,Data Scientist,83059,USD,83059,MI,PT,Ireland,S,Russia,100,"PyTorch, Data Visualization, Scala, GCP, Mathematics",Associate,3,Transportation,2024-01-02,2024-03-08,837,8.6,Cloud AI Solutions -AI04682,AI Specialist,136959,USD,136959,SE,FT,Ireland,L,Ireland,100,"Mathematics, Git, Statistics",Associate,6,Transportation,2024-02-22,2024-04-03,2084,7.6,Predictive Systems -AI04683,Autonomous Systems Engineer,107694,USD,107694,MI,FT,Denmark,S,Italy,0,"SQL, Mathematics, Tableau, Azure, MLOps",PhD,3,Retail,2024-12-24,2025-01-15,1759,8.1,TechCorp Inc -AI04684,AI Architect,179863,SGD,233822,EX,FT,Singapore,S,Singapore,0,"Data Visualization, Python, TensorFlow, Computer Vision",PhD,13,Telecommunications,2024-08-17,2024-10-29,1456,8.9,Future Systems -AI04685,Principal Data Scientist,138581,USD,138581,SE,CT,Sweden,L,Sweden,0,"Java, R, Linux, Git, MLOps",Master,5,Technology,2024-06-18,2024-08-29,602,9.3,Autonomous Tech -AI04686,Robotics Engineer,167250,GBP,125438,SE,FT,United Kingdom,L,Denmark,100,"Linux, Kubernetes, Computer Vision, Deep Learning, Data Visualization",Master,8,Finance,2024-02-26,2024-04-02,1324,6.9,TechCorp Inc -AI04687,ML Ops Engineer,73285,CAD,91606,MI,FL,Canada,S,Canada,0,"Statistics, AWS, SQL, MLOps",Bachelor,4,Telecommunications,2025-02-19,2025-04-19,1577,7.6,Digital Transformation LLC -AI04688,Machine Learning Researcher,90517,USD,90517,MI,PT,Finland,M,Sweden,50,"NLP, AWS, Scala",Master,3,Retail,2024-05-09,2024-07-02,1600,5.8,Future Systems -AI04689,AI Specialist,137917,USD,137917,EX,FT,Ireland,S,Spain,100,"TensorFlow, SQL, Linux, Python",PhD,17,Automotive,2025-01-01,2025-02-04,1945,6,Cloud AI Solutions -AI04690,AI Architect,113385,EUR,96377,MI,FL,Netherlands,M,Netherlands,100,"Data Visualization, SQL, Git",Bachelor,2,Real Estate,2024-08-12,2024-10-10,1861,7.3,Cognitive Computing -AI04691,Research Scientist,91903,USD,91903,MI,FL,South Korea,L,South Korea,0,"GCP, Git, Tableau",Master,4,Manufacturing,2024-10-24,2024-12-09,1403,5.4,Future Systems -AI04692,Autonomous Systems Engineer,62142,USD,62142,EN,FL,Denmark,S,Denmark,100,"SQL, R, Computer Vision, Statistics",Associate,1,Finance,2024-12-25,2025-02-19,897,8.4,Advanced Robotics -AI04693,Head of AI,162597,EUR,138207,EX,CT,Austria,M,Austria,0,"Computer Vision, MLOps, Python",Associate,13,Technology,2024-02-14,2024-04-04,2369,5,Cognitive Computing -AI04694,AI Product Manager,277090,CHF,249381,EX,PT,Switzerland,S,Switzerland,100,"PyTorch, Deep Learning, Azure",Associate,18,Gaming,2024-07-14,2024-08-10,1405,7.3,DeepTech Ventures -AI04695,AI Architect,111361,EUR,94657,SE,PT,Germany,S,Nigeria,100,"Linux, Scala, Statistics, Python, Computer Vision",Bachelor,7,Media,2024-12-28,2025-02-22,566,5.9,Digital Transformation LLC -AI04696,Data Engineer,124750,USD,124750,SE,CT,Sweden,S,Sweden,50,"Hadoop, Python, NLP",Master,9,Government,2024-03-08,2024-04-13,1770,9.3,Smart Analytics -AI04697,AI Architect,59624,USD,59624,MI,FL,South Korea,M,Netherlands,100,"SQL, Data Visualization, Java, Docker, Linux",PhD,3,Transportation,2024-05-13,2024-06-07,776,5.7,Neural Networks Co -AI04698,AI Consultant,176619,USD,176619,SE,FT,Norway,M,Norway,0,"Git, AWS, Kubernetes, Hadoop",PhD,6,Consulting,2024-08-25,2024-10-17,1981,7.1,Predictive Systems -AI04699,Head of AI,60007,USD,60007,EX,CT,China,S,China,0,"Python, Data Visualization, TensorFlow, Java, Mathematics",Master,17,Education,2025-03-16,2025-04-08,1337,8,Cloud AI Solutions -AI04700,Head of AI,76104,EUR,64688,EN,FL,Germany,M,Germany,0,"Spark, NLP, Deep Learning, Hadoop, Kubernetes",Bachelor,0,Government,2024-01-21,2024-02-26,1394,6.7,Algorithmic Solutions -AI04701,NLP Engineer,116281,USD,116281,SE,CT,Ireland,S,Ireland,100,"Data Visualization, Kubernetes, NLP, Python, Deep Learning",PhD,8,Energy,2024-10-26,2024-12-12,1894,7,Advanced Robotics -AI04702,Autonomous Systems Engineer,67934,USD,67934,EN,FL,Ireland,S,Ireland,0,"SQL, Kubernetes, Python",Associate,1,Transportation,2024-08-05,2024-09-09,946,7.4,Digital Transformation LLC -AI04703,Data Analyst,62548,EUR,53166,EN,FL,Netherlands,M,Singapore,100,"Data Visualization, PyTorch, AWS, Python, Hadoop",PhD,1,Government,2024-11-12,2025-01-21,1149,8.5,Cognitive Computing -AI04704,Machine Learning Researcher,32890,USD,32890,EN,CT,China,L,China,100,"Hadoop, Mathematics, Kubernetes",Bachelor,0,Energy,2025-02-15,2025-03-24,802,9,AI Innovations -AI04705,Computer Vision Engineer,82416,USD,82416,MI,PT,Sweden,S,Sweden,0,"Tableau, GCP, Docker, Kubernetes, Statistics",Master,2,Finance,2024-11-05,2025-01-05,1089,6.6,Predictive Systems -AI04706,Machine Learning Engineer,143048,CAD,178810,SE,PT,Canada,M,Nigeria,50,"R, SQL, AWS, GCP, Data Visualization",Associate,8,Manufacturing,2024-09-19,2024-10-29,571,9.8,Quantum Computing Inc -AI04707,Deep Learning Engineer,76432,USD,76432,EX,CT,India,M,India,100,"MLOps, Kubernetes, SQL, R",Bachelor,11,Technology,2024-11-14,2025-01-14,1773,5,Advanced Robotics -AI04708,ML Ops Engineer,91651,EUR,77903,MI,FT,Germany,L,Belgium,50,"Hadoop, Spark, Data Visualization, Statistics",Bachelor,2,Energy,2024-03-13,2024-04-21,2373,5.1,Autonomous Tech -AI04709,Data Engineer,119672,CHF,107705,EN,PT,Switzerland,L,Switzerland,50,"Mathematics, R, NLP",Associate,0,Energy,2025-02-25,2025-04-11,2305,6.2,Quantum Computing Inc -AI04710,AI Consultant,91372,USD,91372,SE,FL,Finland,S,Finland,0,"Python, GCP, Linux, TensorFlow, R",Master,9,Automotive,2024-04-06,2024-05-29,2201,9.8,Smart Analytics -AI04711,AI Specialist,136154,CHF,122539,MI,FT,Switzerland,M,Switzerland,0,"PyTorch, Docker, Kubernetes, SQL",Associate,2,Technology,2024-09-03,2024-11-05,2425,6.2,Autonomous Tech -AI04712,Robotics Engineer,48395,USD,48395,EX,CT,India,S,United Kingdom,50,"Deep Learning, Azure, Spark, Python",Associate,13,Education,2024-11-21,2024-12-20,2192,5.2,Algorithmic Solutions -AI04713,Machine Learning Engineer,105774,USD,105774,EN,FL,United States,L,United States,0,"PyTorch, MLOps, Docker",Associate,1,Automotive,2024-10-31,2025-01-05,2274,7.1,Digital Transformation LLC -AI04714,Data Analyst,160016,USD,160016,SE,FT,Denmark,S,Denmark,50,"Kubernetes, TensorFlow, Docker, Statistics, Computer Vision",Associate,8,Government,2024-01-31,2024-02-17,1543,8.7,Future Systems -AI04715,Autonomous Systems Engineer,206793,CHF,186114,SE,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Kubernetes",Bachelor,9,Retail,2024-09-04,2024-10-09,1451,7.9,Predictive Systems -AI04716,AI Architect,86168,USD,86168,EX,CT,India,L,India,100,"Mathematics, GCP, Data Visualization, Spark, Java",Bachelor,11,Technology,2024-12-08,2025-02-08,2468,7.7,Cloud AI Solutions -AI04717,AI Consultant,123853,USD,123853,SE,PT,Sweden,L,Sweden,100,"Computer Vision, Python, TensorFlow, Spark, Deep Learning",PhD,7,Retail,2024-04-27,2024-06-29,2048,8,Autonomous Tech -AI04718,AI Specialist,78399,SGD,101919,EN,PT,Singapore,L,Singapore,0,"SQL, GCP, MLOps, Deep Learning",Bachelor,0,Real Estate,2025-03-20,2025-05-19,962,9.3,Predictive Systems -AI04719,Machine Learning Engineer,138128,SGD,179566,SE,FL,Singapore,M,Ukraine,50,"Kubernetes, Deep Learning, TensorFlow",Master,6,Automotive,2025-02-15,2025-03-13,1918,8.5,Algorithmic Solutions -AI04720,Data Engineer,90321,CAD,112901,MI,FL,Canada,S,Canada,50,"Python, Linux, GCP, Hadoop",Master,2,Consulting,2024-06-05,2024-06-26,2352,9.8,Machine Intelligence Group -AI04721,NLP Engineer,90443,CAD,113054,MI,FT,Canada,L,Canada,0,"Git, Hadoop, Azure, Tableau, Java",Associate,2,Retail,2025-04-08,2025-06-15,1599,8.2,Smart Analytics -AI04722,ML Ops Engineer,121587,EUR,103349,SE,PT,Austria,M,Austria,50,"Docker, Python, MLOps, Git",Master,8,Government,2025-02-22,2025-04-16,1807,7.7,Autonomous Tech -AI04723,Principal Data Scientist,226775,CHF,204098,SE,PT,Switzerland,L,Switzerland,0,"Scala, Deep Learning, Statistics",Associate,8,Telecommunications,2024-11-30,2025-01-26,819,5.3,Future Systems -AI04724,AI Research Scientist,97958,USD,97958,SE,PT,Ireland,S,Ireland,50,"Kubernetes, Python, Data Visualization, MLOps",PhD,5,Gaming,2024-12-02,2025-02-11,1617,9.8,Predictive Systems -AI04725,Deep Learning Engineer,59895,SGD,77864,EN,CT,Singapore,S,Singapore,50,"Python, TensorFlow, Computer Vision, Azure",PhD,1,Real Estate,2024-08-03,2024-08-23,1154,6.8,Neural Networks Co -AI04726,Deep Learning Engineer,96051,USD,96051,MI,CT,Norway,S,Norway,50,"GCP, Hadoop, Deep Learning, Computer Vision",Bachelor,3,Telecommunications,2024-04-15,2024-05-15,1776,6.5,TechCorp Inc -AI04727,Data Analyst,194676,USD,194676,EX,FT,United States,S,Russia,100,"GCP, SQL, Statistics, Java",PhD,13,Transportation,2025-04-26,2025-06-26,1204,9.7,Machine Intelligence Group -AI04728,Principal Data Scientist,83606,SGD,108688,EN,CT,Singapore,M,Singapore,100,"Python, Kubernetes, Hadoop",Associate,0,Gaming,2025-02-24,2025-03-29,2429,5.2,Machine Intelligence Group -AI04729,AI Product Manager,35409,USD,35409,EN,FT,China,L,China,0,"Spark, Kubernetes, Deep Learning",Master,0,Technology,2024-06-13,2024-07-04,2134,5.4,Future Systems -AI04730,AI Product Manager,75374,USD,75374,MI,FL,Ireland,S,Kenya,50,"R, NLP, AWS, Java",Bachelor,2,Manufacturing,2025-02-09,2025-04-03,701,7.6,Cognitive Computing -AI04731,Principal Data Scientist,79994,USD,79994,EX,FT,China,L,China,0,"Hadoop, Python, NLP",Master,17,Real Estate,2024-05-02,2024-07-07,597,8,Autonomous Tech -AI04732,Deep Learning Engineer,78389,EUR,66631,MI,CT,France,S,France,50,"R, Java, Deep Learning, Statistics, Docker",Master,4,Energy,2025-04-30,2025-06-14,2477,5.9,DeepTech Ventures -AI04733,Head of AI,295681,USD,295681,EX,FT,Denmark,L,Denmark,100,"Tableau, Linux, Git",Master,10,Healthcare,2024-05-26,2024-06-27,524,9.4,Digital Transformation LLC -AI04734,AI Software Engineer,126906,EUR,107870,SE,PT,Germany,L,South Korea,100,"Spark, SQL, Azure",PhD,5,Real Estate,2025-04-29,2025-06-05,1181,9.6,Advanced Robotics -AI04735,AI Architect,158136,EUR,134416,EX,CT,Germany,M,Germany,50,"Kubernetes, Python, Linux, Docker",PhD,19,Manufacturing,2024-11-21,2024-12-17,1866,10,Advanced Robotics -AI04736,Computer Vision Engineer,147980,USD,147980,SE,FL,Norway,S,Norway,50,"Python, NLP, Azure",Master,9,Government,2024-07-06,2024-08-17,1488,6.4,Predictive Systems -AI04737,Head of AI,90573,USD,90573,MI,CT,Norway,S,Norway,0,"SQL, Kubernetes, Tableau",Associate,2,Gaming,2024-06-18,2024-08-07,883,5.2,Cloud AI Solutions -AI04738,Machine Learning Researcher,287295,USD,287295,EX,FL,Norway,L,Switzerland,100,"Azure, Data Visualization, Python, TensorFlow, AWS",PhD,10,Healthcare,2024-07-23,2024-08-08,1834,6,Cognitive Computing -AI04739,Deep Learning Engineer,206996,EUR,175947,EX,PT,Netherlands,L,Netherlands,50,"Mathematics, Data Visualization, Java, Docker",PhD,18,Real Estate,2024-08-09,2024-09-06,865,8.7,DataVision Ltd -AI04740,Autonomous Systems Engineer,122080,SGD,158704,SE,PT,Singapore,M,Romania,100,"Tableau, Mathematics, GCP",Bachelor,5,Transportation,2024-11-12,2024-11-28,1587,9.6,Digital Transformation LLC -AI04741,Computer Vision Engineer,70756,USD,70756,EN,FT,United States,S,United States,50,"NLP, TensorFlow, Azure",Associate,0,Finance,2024-01-04,2024-02-05,1760,7.6,Neural Networks Co -AI04742,AI Architect,97152,CHF,87437,EN,FT,Switzerland,L,Switzerland,0,"Python, Data Visualization, TensorFlow",Bachelor,0,Automotive,2024-07-27,2024-09-02,1520,6.2,Quantum Computing Inc -AI04743,Machine Learning Engineer,166402,EUR,141442,SE,CT,Netherlands,L,Netherlands,100,"Linux, R, Scala, Azure, SQL",Bachelor,6,Media,2024-08-30,2024-10-23,1184,8.5,AI Innovations -AI04744,AI Research Scientist,67835,JPY,7461850,EN,FT,Japan,L,Japan,0,"Spark, Docker, Python",Associate,1,Automotive,2024-12-22,2025-01-08,620,9.2,Digital Transformation LLC -AI04745,Data Scientist,149496,EUR,127072,EX,PT,Austria,M,Austria,100,"Computer Vision, AWS, Python, TensorFlow",PhD,13,Consulting,2024-09-02,2024-10-14,1813,10,Future Systems -AI04746,AI Software Engineer,261114,USD,261114,EX,FT,Finland,L,Finland,100,"Computer Vision, Python, Docker, Deep Learning, Linux",Bachelor,10,Government,2025-01-27,2025-03-29,573,5.6,AI Innovations -AI04747,Machine Learning Researcher,39992,USD,39992,EN,CT,China,L,China,0,"GCP, Computer Vision, Data Visualization, Python",PhD,1,Manufacturing,2025-02-24,2025-05-05,2160,6.3,Predictive Systems -AI04748,NLP Engineer,127090,JPY,13979900,SE,FT,Japan,M,Japan,100,"Tableau, Hadoop, Computer Vision, Azure, Deep Learning",Master,6,Automotive,2024-05-05,2024-05-20,1570,8.1,Cognitive Computing -AI04749,Data Analyst,25060,USD,25060,EN,FT,India,M,India,100,"Hadoop, Spark, SQL, NLP, Docker",PhD,1,Gaming,2024-04-14,2024-06-13,1845,9.4,Neural Networks Co -AI04750,NLP Engineer,121674,JPY,13384140,SE,CT,Japan,M,Indonesia,50,"Python, Tableau, Hadoop",Master,5,Real Estate,2024-02-03,2024-03-22,1668,8.7,Quantum Computing Inc -AI04751,AI Product Manager,60372,JPY,6640920,EN,FT,Japan,M,Japan,100,"GCP, Git, NLP, Python, SQL",Associate,0,Retail,2025-04-15,2025-05-23,1562,8.1,AI Innovations -AI04752,Data Engineer,277451,USD,277451,EX,FT,Norway,S,China,100,"Docker, SQL, PyTorch",Bachelor,11,Retail,2024-03-25,2024-06-03,2111,7.8,Future Systems -AI04753,Research Scientist,112653,JPY,12391830,MI,FL,Japan,L,Japan,100,"Python, SQL, Java, Spark",Bachelor,2,Energy,2024-12-25,2025-02-06,2007,8.1,Future Systems -AI04754,AI Consultant,65378,EUR,55571,EN,PT,Austria,S,Austria,100,"PyTorch, Git, MLOps, TensorFlow",Bachelor,0,Healthcare,2025-03-15,2025-05-12,990,7.1,Future Systems -AI04755,Data Engineer,70603,USD,70603,EN,FL,Ireland,M,Chile,50,"NLP, Deep Learning, Git, Kubernetes",PhD,1,Media,2025-01-03,2025-02-12,1881,7.6,Smart Analytics -AI04756,Head of AI,190525,USD,190525,EX,FT,Denmark,S,Estonia,0,"Python, Deep Learning, MLOps, Azure",Bachelor,15,Gaming,2025-02-21,2025-03-16,2332,7.2,Smart Analytics -AI04757,Research Scientist,61699,EUR,52444,EN,FT,Netherlands,M,Netherlands,50,"R, Tableau, Kubernetes",Bachelor,1,Automotive,2024-09-03,2024-10-30,594,8.8,Machine Intelligence Group -AI04758,AI Research Scientist,273689,GBP,205267,EX,FT,United Kingdom,L,Czech Republic,100,"Azure, Linux, Hadoop, Java, Python",PhD,10,Manufacturing,2025-02-02,2025-04-14,2382,6.3,DeepTech Ventures -AI04759,Machine Learning Researcher,99938,USD,99938,MI,CT,United States,M,United States,0,"Azure, Kubernetes, Deep Learning",PhD,3,Retail,2024-09-13,2024-11-02,2160,6.9,Future Systems -AI04760,Robotics Engineer,109758,USD,109758,MI,FT,Ireland,M,Ireland,0,"SQL, NLP, Tableau, Computer Vision, PyTorch",Bachelor,4,Retail,2024-08-14,2024-10-01,1696,5.1,Advanced Robotics -AI04761,AI Consultant,107303,USD,107303,MI,CT,Israel,L,Singapore,50,"TensorFlow, SQL, NLP, Git",PhD,3,Energy,2025-02-28,2025-04-29,1075,8.2,Algorithmic Solutions -AI04762,Data Analyst,89290,USD,89290,EN,FT,Ireland,L,Ireland,50,"Scala, Kubernetes, Tableau",PhD,0,Finance,2024-02-15,2024-04-01,2246,7,Autonomous Tech -AI04763,Data Scientist,172273,USD,172273,EX,PT,Israel,S,Israel,0,"Java, Tableau, Docker",Associate,10,Government,2025-01-26,2025-03-28,1270,9.4,Machine Intelligence Group -AI04764,AI Product Manager,98723,AUD,133276,MI,FL,Australia,L,Australia,50,"Data Visualization, GCP, Scala, MLOps",Master,4,Real Estate,2024-05-08,2024-05-22,824,5.3,Cloud AI Solutions -AI04765,Autonomous Systems Engineer,64219,USD,64219,EN,FT,Ireland,S,Ireland,0,"Linux, Spark, Tableau",PhD,1,Government,2024-01-12,2024-02-18,885,9.1,Predictive Systems -AI04766,Principal Data Scientist,163057,JPY,17936270,SE,FT,Japan,L,Japan,100,"Spark, SQL, Docker, Linux",Master,7,Government,2025-04-20,2025-05-09,1937,8.5,Quantum Computing Inc -AI04767,Machine Learning Engineer,175853,EUR,149475,EX,CT,Netherlands,L,Philippines,100,"PyTorch, AWS, SQL, Python",Master,16,Automotive,2024-02-11,2024-04-12,505,7.7,Cognitive Computing -AI04768,Computer Vision Engineer,24322,USD,24322,EN,PT,India,S,Canada,0,"Azure, MLOps, Python",Associate,1,Finance,2024-07-12,2024-08-28,631,10,Predictive Systems -AI04769,Autonomous Systems Engineer,296894,GBP,222671,EX,CT,United Kingdom,L,United Kingdom,0,"MLOps, SQL, Python, Tableau, Git",Associate,12,Education,2024-12-12,2025-01-04,1608,7.2,TechCorp Inc -AI04770,Deep Learning Engineer,102705,AUD,138652,MI,PT,Australia,M,Australia,0,"SQL, Azure, R",Bachelor,4,Government,2025-01-18,2025-03-27,2238,6.7,Advanced Robotics -AI04771,AI Software Engineer,80745,SGD,104969,MI,CT,Singapore,S,Singapore,50,"Kubernetes, Python, TensorFlow, Statistics",Associate,4,Technology,2024-01-28,2024-03-23,1996,6,Digital Transformation LLC -AI04772,AI Specialist,135774,USD,135774,EX,FT,Ireland,S,Ireland,50,"Computer Vision, Kubernetes, Git",PhD,14,Government,2024-02-27,2024-03-15,927,6.8,Predictive Systems -AI04773,AI Architect,66185,GBP,49639,EN,CT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow, PyTorch",PhD,0,Manufacturing,2024-04-03,2024-06-11,2185,7.8,Autonomous Tech -AI04774,Computer Vision Engineer,142177,USD,142177,MI,FL,Denmark,M,Denmark,0,"Kubernetes, TensorFlow, Docker",PhD,2,Telecommunications,2024-10-16,2024-12-09,2400,8.8,DeepTech Ventures -AI04775,Head of AI,85696,USD,85696,MI,CT,Israel,S,Denmark,100,"Data Visualization, Docker, PyTorch, MLOps, AWS",Master,3,Healthcare,2024-09-16,2024-10-25,1250,8.2,Predictive Systems -AI04776,Data Analyst,148270,GBP,111203,SE,FL,United Kingdom,M,United Kingdom,100,"TensorFlow, Hadoop, MLOps, Statistics",Associate,6,Media,2024-03-16,2024-04-12,583,9.5,Cognitive Computing -AI04777,NLP Engineer,133788,USD,133788,SE,FL,Denmark,S,Ukraine,100,"Linux, Azure, Docker, Computer Vision",PhD,8,Gaming,2025-04-15,2025-05-24,2156,6,Machine Intelligence Group -AI04778,AI Specialist,162677,GBP,122008,EX,FL,United Kingdom,S,United Kingdom,50,"R, Python, Linux",Master,17,Healthcare,2025-03-23,2025-04-20,2094,7.5,Advanced Robotics -AI04779,Autonomous Systems Engineer,152781,USD,152781,SE,CT,Finland,L,Egypt,0,"SQL, PyTorch, NLP, Computer Vision, Deep Learning",Master,9,Technology,2024-07-31,2024-08-21,1388,7.3,Neural Networks Co -AI04780,Research Scientist,91758,EUR,77994,EN,CT,Germany,L,Germany,0,"Scala, PyTorch, Spark",Bachelor,1,Telecommunications,2024-06-09,2024-07-29,2194,9.1,Autonomous Tech -AI04781,AI Architect,151164,CHF,136048,MI,FL,Switzerland,M,Switzerland,100,"Python, Linux, Computer Vision, Tableau",Associate,2,Finance,2024-09-17,2024-11-04,1670,7.9,DeepTech Ventures -AI04782,AI Product Manager,71129,GBP,53347,EN,CT,United Kingdom,S,Spain,50,"SQL, R, Kubernetes",Associate,1,Education,2025-04-22,2025-06-19,1826,7.3,Autonomous Tech -AI04783,Data Scientist,133851,GBP,100388,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, AWS, Hadoop",Master,8,Gaming,2024-07-27,2024-08-14,1570,9.4,Neural Networks Co -AI04784,Principal Data Scientist,60769,USD,60769,MI,FT,South Korea,S,Spain,0,"Data Visualization, Deep Learning, TensorFlow, SQL, Git",Associate,2,Retail,2024-10-03,2024-12-13,2176,7.5,DataVision Ltd -AI04785,AI Research Scientist,184176,EUR,156550,EX,CT,Netherlands,L,Netherlands,100,"Git, NLP, Tableau, SQL, Linux",Associate,15,Manufacturing,2024-06-04,2024-07-16,1994,5.6,TechCorp Inc -AI04786,NLP Engineer,225359,USD,225359,EX,FL,Israel,M,Indonesia,100,"R, Git, AWS",Associate,18,Healthcare,2024-10-25,2024-11-28,1608,6.1,AI Innovations -AI04787,Autonomous Systems Engineer,257030,USD,257030,EX,PT,United States,S,Romania,50,"Git, Linux, Python",PhD,18,Manufacturing,2025-01-20,2025-03-15,1880,6.3,Algorithmic Solutions -AI04788,Data Scientist,106616,SGD,138601,SE,FT,Singapore,S,Sweden,0,"Python, Mathematics, Java, Computer Vision",Associate,8,Retail,2024-02-22,2024-04-22,1948,6.5,DeepTech Ventures -AI04789,Machine Learning Engineer,28056,USD,28056,EN,CT,China,S,China,0,"NLP, Kubernetes, Java",Bachelor,0,Gaming,2024-03-29,2024-05-13,2016,7.1,DataVision Ltd -AI04790,AI Consultant,149551,EUR,127118,SE,CT,France,L,France,0,"Spark, R, SQL, Hadoop",Associate,9,Gaming,2025-01-09,2025-03-17,1387,8.7,Digital Transformation LLC -AI04791,Machine Learning Engineer,72604,AUD,98015,EN,PT,Australia,S,Australia,50,"Tableau, Mathematics, MLOps, Python, TensorFlow",Associate,1,Technology,2024-06-12,2024-07-08,1177,5.6,AI Innovations -AI04792,Principal Data Scientist,57678,USD,57678,EN,FT,Finland,L,Finland,0,"Spark, Java, Statistics, Linux",Bachelor,1,Consulting,2024-12-09,2025-02-20,1801,6.7,Machine Intelligence Group -AI04793,Robotics Engineer,56249,USD,56249,EN,FL,Israel,S,Israel,50,"Python, Tableau, TensorFlow, Data Visualization, Mathematics",Bachelor,1,Transportation,2024-03-01,2024-04-21,537,7.6,Machine Intelligence Group -AI04794,ML Ops Engineer,100701,USD,100701,EX,FL,China,L,France,0,"SQL, Git, Spark, Linux",Associate,13,Media,2024-12-18,2025-01-04,2279,9.3,DataVision Ltd -AI04795,Machine Learning Engineer,86400,USD,86400,EN,CT,United States,M,Kenya,100,"Scala, Deep Learning, Java",Master,0,Retail,2024-01-29,2024-02-21,1913,7.1,AI Innovations -AI04796,AI Specialist,161695,JPY,17786450,SE,CT,Japan,L,Japan,0,"NLP, Docker, Tableau, R",Bachelor,6,Finance,2024-10-12,2024-11-10,2341,7.2,Cognitive Computing -AI04797,AI Consultant,101102,JPY,11121220,MI,PT,Japan,L,Japan,100,"Linux, Data Visualization, PyTorch, Statistics",Master,3,Telecommunications,2024-03-14,2024-04-01,1091,8.8,DeepTech Ventures -AI04798,AI Architect,72270,USD,72270,EN,FL,Ireland,M,Ireland,0,"Deep Learning, R, PyTorch",Associate,1,Energy,2025-03-26,2025-04-25,913,7.9,TechCorp Inc -AI04799,Machine Learning Engineer,53789,USD,53789,EN,PT,South Korea,M,South Korea,0,"SQL, Spark, Tableau",Bachelor,0,Energy,2024-11-19,2025-01-20,1724,5.2,Future Systems -AI04800,Computer Vision Engineer,104468,USD,104468,MI,FL,South Korea,L,South Korea,100,"Java, SQL, Hadoop",Master,2,Retail,2024-09-08,2024-10-25,1169,7.9,Future Systems -AI04801,ML Ops Engineer,225913,USD,225913,EX,FT,Ireland,S,Ireland,100,"Azure, SQL, TensorFlow, Python",Associate,17,Energy,2025-01-30,2025-02-24,2216,6.7,Neural Networks Co -AI04802,AI Specialist,178459,USD,178459,SE,FL,Norway,L,France,100,"SQL, AWS, Computer Vision, GCP, Data Visualization",Master,8,Gaming,2024-05-21,2024-06-07,879,7.1,Quantum Computing Inc -AI04803,Principal Data Scientist,168120,USD,168120,EX,FT,United States,S,United States,0,"Computer Vision, Docker, AWS, Python",PhD,19,Education,2024-11-12,2024-12-16,996,6.9,Quantum Computing Inc -AI04804,AI Specialist,66095,USD,66095,EN,PT,United States,S,Egypt,100,"GCP, Git, Hadoop, Tableau, PyTorch",PhD,0,Manufacturing,2024-08-31,2024-10-07,2130,7.6,Predictive Systems -AI04805,AI Architect,288067,USD,288067,EX,PT,United States,L,United States,0,"SQL, MLOps, PyTorch, Azure",Associate,18,Telecommunications,2024-04-01,2024-05-22,1686,7.8,Autonomous Tech -AI04806,Deep Learning Engineer,18634,USD,18634,EN,FL,India,S,Ireland,50,"Java, Docker, GCP",Master,1,Transportation,2024-09-13,2024-11-20,1978,9.2,Advanced Robotics -AI04807,Research Scientist,66098,USD,66098,EX,FT,China,M,China,0,"Python, Azure, MLOps, TensorFlow, Docker",Master,18,Manufacturing,2025-01-09,2025-02-26,639,7.5,Machine Intelligence Group -AI04808,Computer Vision Engineer,43744,EUR,37182,EN,FL,Austria,S,Austria,0,"Azure, Linux, PyTorch",Bachelor,1,Government,2024-08-27,2024-11-05,1325,7.1,Future Systems -AI04809,Computer Vision Engineer,57278,EUR,48686,EN,PT,Netherlands,M,Netherlands,50,"Deep Learning, Hadoop, GCP",Bachelor,0,Transportation,2024-03-30,2024-05-29,1116,6.2,Cloud AI Solutions -AI04810,AI Product Manager,59918,GBP,44939,EN,FT,United Kingdom,S,United Kingdom,50,"Python, Spark, Git, Deep Learning",Associate,0,Real Estate,2024-07-10,2024-09-04,1899,5.1,Advanced Robotics -AI04811,Data Scientist,68180,EUR,57953,EN,FT,Austria,M,Austria,0,"Python, Azure, Scala",Master,1,Manufacturing,2025-04-16,2025-06-15,563,9.4,Neural Networks Co -AI04812,AI Software Engineer,97864,GBP,73398,SE,PT,United Kingdom,S,United Kingdom,100,"Linux, Spark, GCP",Associate,6,Finance,2024-09-25,2024-10-25,2473,5.3,Advanced Robotics -AI04813,Research Scientist,113546,USD,113546,MI,FT,Ireland,L,Ireland,100,"Azure, Kubernetes, Statistics",Master,3,Healthcare,2024-04-27,2024-05-22,2269,5.8,AI Innovations -AI04814,Deep Learning Engineer,237348,JPY,26108280,EX,PT,Japan,S,Japan,50,"MLOps, Java, Spark, Azure",Master,10,Manufacturing,2025-03-13,2025-03-30,803,9.1,TechCorp Inc -AI04815,AI Architect,251015,SGD,326320,EX,FL,Singapore,M,Singapore,0,"PyTorch, Statistics, Azure, SQL",Associate,11,Government,2024-02-03,2024-04-15,1783,6,Cognitive Computing -AI04816,Machine Learning Engineer,78579,CAD,98224,MI,CT,Canada,M,Canada,100,"MLOps, Hadoop, Statistics, PyTorch, Mathematics",Bachelor,4,Government,2024-02-09,2024-03-09,1867,5.4,Future Systems -AI04817,Principal Data Scientist,85161,USD,85161,MI,CT,Ireland,M,Ireland,0,"PyTorch, TensorFlow, Statistics",Master,4,Telecommunications,2025-02-24,2025-03-29,1322,8.9,Future Systems -AI04818,Machine Learning Researcher,190172,EUR,161646,EX,FL,Netherlands,M,Netherlands,0,"Java, Computer Vision, Spark, GCP, Kubernetes",Bachelor,19,Technology,2024-05-02,2024-07-13,1469,9,Cognitive Computing -AI04819,AI Specialist,100405,JPY,11044550,MI,PT,Japan,L,Japan,50,"Python, Git, Tableau",PhD,3,Energy,2024-09-02,2024-11-14,1833,7.2,DataVision Ltd -AI04820,AI Research Scientist,42239,USD,42239,MI,FT,China,L,China,100,"Git, PyTorch, Azure",Bachelor,2,Energy,2024-03-19,2024-05-07,1606,6.7,DataVision Ltd -AI04821,Research Scientist,287260,USD,287260,EX,CT,Ireland,L,Malaysia,50,"Docker, PyTorch, Computer Vision",Master,14,Manufacturing,2024-06-26,2024-07-18,1892,7.2,Future Systems -AI04822,Data Analyst,198733,AUD,268290,EX,FL,Australia,M,Australia,100,"PyTorch, Computer Vision, AWS, Scala, Kubernetes",Associate,11,Media,2024-04-01,2024-04-22,1667,6.9,Future Systems -AI04823,Robotics Engineer,258415,EUR,219653,EX,CT,France,L,France,0,"MLOps, Scala, Spark",Master,17,Gaming,2024-01-21,2024-02-10,1407,5.7,Neural Networks Co -AI04824,AI Specialist,82073,USD,82073,MI,PT,Finland,M,Finland,100,"Python, TensorFlow, MLOps",Bachelor,3,Finance,2024-07-20,2024-08-25,1654,7.1,Cognitive Computing -AI04825,Deep Learning Engineer,111443,USD,111443,SE,FT,Israel,S,Japan,100,"GCP, SQL, Kubernetes, AWS",PhD,8,Consulting,2024-07-26,2024-09-14,500,8.3,Autonomous Tech -AI04826,AI Architect,200094,JPY,22010340,EX,CT,Japan,L,Japan,0,"Java, PyTorch, Azure, SQL",Bachelor,14,Education,2025-04-11,2025-05-19,1610,8.3,Cloud AI Solutions -AI04827,AI Product Manager,248923,EUR,211585,EX,PT,Germany,M,Nigeria,100,"Linux, Deep Learning, Mathematics, Docker",Master,19,Government,2024-07-25,2024-08-18,555,8.8,Cognitive Computing -AI04828,Computer Vision Engineer,72550,GBP,54413,EN,PT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Computer Vision, Git",Bachelor,1,Media,2024-12-22,2025-01-18,702,9.9,Machine Intelligence Group -AI04829,Deep Learning Engineer,206051,EUR,175143,EX,FL,Austria,L,Austria,100,"GCP, Hadoop, Deep Learning",Associate,13,Retail,2024-11-09,2024-12-22,1120,8.1,Advanced Robotics -AI04830,AI Software Engineer,141826,USD,141826,SE,CT,Sweden,M,Sweden,100,"Java, Scala, Mathematics",Bachelor,7,Finance,2024-12-18,2025-02-07,1838,7.2,DataVision Ltd -AI04831,ML Ops Engineer,196522,EUR,167044,EX,FT,France,S,France,100,"Python, Docker, Statistics",Master,18,Finance,2025-01-18,2025-02-25,708,7.9,Neural Networks Co -AI04832,Machine Learning Researcher,104082,SGD,135307,MI,PT,Singapore,M,Portugal,0,"AWS, R, Azure, Python, Git",PhD,2,Automotive,2024-11-26,2024-12-30,765,6.5,TechCorp Inc -AI04833,ML Ops Engineer,256314,USD,256314,EX,FL,United States,S,United States,0,"Mathematics, R, Deep Learning",Bachelor,11,Consulting,2024-05-23,2024-07-23,2116,9.7,Predictive Systems -AI04834,Computer Vision Engineer,62614,USD,62614,EX,PT,India,M,India,100,"TensorFlow, Git, Java, Computer Vision, Scala",Associate,15,Manufacturing,2024-05-14,2024-07-21,1318,7.9,Cloud AI Solutions -AI04835,AI Product Manager,104089,JPY,11449790,MI,PT,Japan,S,Japan,100,"Git, Docker, Data Visualization, Kubernetes, Scala",Associate,3,Government,2024-06-24,2024-08-16,1828,6.6,DeepTech Ventures -AI04836,ML Ops Engineer,52607,USD,52607,SE,FL,China,S,Vietnam,0,"Python, Statistics, Deep Learning, Scala",PhD,7,Telecommunications,2024-08-29,2024-09-18,2113,7.1,TechCorp Inc -AI04837,ML Ops Engineer,131333,USD,131333,SE,FT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Computer Vision",Master,6,Energy,2025-01-09,2025-02-25,1082,7.7,Predictive Systems -AI04838,Data Engineer,369918,CHF,332926,EX,CT,Switzerland,L,Switzerland,0,"Scala, Java, Deep Learning",Associate,18,Finance,2025-03-23,2025-06-03,2322,6,Machine Intelligence Group -AI04839,Computer Vision Engineer,288629,USD,288629,EX,PT,Sweden,L,Sweden,50,"PyTorch, MLOps, GCP",Associate,19,Telecommunications,2024-04-02,2024-05-27,1934,5.5,TechCorp Inc -AI04840,AI Consultant,186990,EUR,158942,EX,CT,Germany,S,Germany,100,"SQL, Data Visualization, Linux, Scala",PhD,16,Automotive,2025-04-02,2025-05-12,1952,9.8,DataVision Ltd -AI04841,AI Specialist,122223,USD,122223,SE,FT,Sweden,S,Sweden,100,"Data Visualization, Linux, PyTorch",PhD,7,Transportation,2025-03-26,2025-05-22,2384,6.8,DataVision Ltd -AI04842,Computer Vision Engineer,116177,USD,116177,SE,PT,Ireland,S,Ireland,100,"Git, Mathematics, Computer Vision, Java, Deep Learning",PhD,8,Consulting,2024-05-28,2024-06-22,939,9.8,Quantum Computing Inc -AI04843,Research Scientist,155331,USD,155331,EX,FT,Israel,M,Israel,0,"Statistics, Computer Vision, NLP, SQL, Data Visualization",Bachelor,15,Consulting,2024-04-17,2024-05-19,1147,5.7,Autonomous Tech -AI04844,Computer Vision Engineer,157720,EUR,134062,EX,PT,Austria,L,United States,50,"Python, GCP, Tableau, TensorFlow",Bachelor,11,Real Estate,2024-10-24,2024-12-27,1805,6.7,Predictive Systems -AI04845,AI Consultant,80697,CHF,72627,EN,PT,Switzerland,M,Switzerland,100,"PyTorch, Azure, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-10-08,2024-12-02,2026,6.8,Machine Intelligence Group -AI04846,Data Analyst,95727,EUR,81368,EN,FT,Netherlands,L,Netherlands,50,"PyTorch, Spark, Computer Vision",PhD,0,Government,2024-01-15,2024-03-03,1960,6.1,DeepTech Ventures -AI04847,NLP Engineer,303364,USD,303364,EX,FL,Norway,L,Norway,50,"Java, R, Spark, Docker, Deep Learning",Bachelor,18,Manufacturing,2024-10-10,2024-11-12,930,5.4,Machine Intelligence Group -AI04848,Robotics Engineer,130193,JPY,14321230,SE,FL,Japan,M,Japan,0,"Spark, Python, R, AWS, Statistics",Bachelor,5,Government,2025-04-16,2025-06-03,1110,8.1,DeepTech Ventures -AI04849,Data Scientist,87100,CAD,108875,MI,PT,Canada,S,Canada,0,"R, GCP, Azure, Linux, Kubernetes",Associate,3,Automotive,2024-05-14,2024-06-03,2350,5.4,Quantum Computing Inc -AI04850,Principal Data Scientist,253609,SGD,329692,EX,CT,Singapore,M,Singapore,100,"Tableau, Deep Learning, Hadoop",PhD,13,Telecommunications,2024-01-09,2024-02-12,723,5.2,TechCorp Inc -AI04851,Deep Learning Engineer,111947,CAD,139934,MI,PT,Canada,L,Canada,0,"Spark, NLP, Python, Kubernetes, Mathematics",PhD,2,Transportation,2024-10-08,2024-12-08,1637,7.6,Advanced Robotics -AI04852,ML Ops Engineer,149929,SGD,194908,SE,FL,Singapore,L,Singapore,50,"Deep Learning, AWS, Mathematics, GCP, Python",Master,8,Media,2025-04-11,2025-05-06,2130,5.6,AI Innovations -AI04853,AI Product Manager,101866,SGD,132426,MI,FT,Singapore,L,Singapore,0,"SQL, NLP, R",PhD,3,Gaming,2024-04-24,2024-05-19,1461,8.5,Algorithmic Solutions -AI04854,Research Scientist,77165,AUD,104173,MI,PT,Australia,S,Australia,100,"Tableau, Git, Docker, PyTorch, Linux",Master,4,Media,2024-12-02,2025-01-21,1863,7.6,Machine Intelligence Group -AI04855,Computer Vision Engineer,121396,EUR,103187,SE,FL,Germany,M,Canada,50,"Data Visualization, PyTorch, TensorFlow, Statistics, Java",Master,7,Gaming,2024-07-01,2024-07-26,1567,8.8,Advanced Robotics -AI04856,Machine Learning Researcher,136213,USD,136213,SE,FT,Ireland,L,Ireland,50,"Deep Learning, TensorFlow, R, MLOps, Git",Associate,5,Retail,2024-06-23,2024-08-25,2377,8.5,Future Systems -AI04857,AI Architect,145362,USD,145362,SE,CT,Sweden,L,Sweden,50,"R, PyTorch, GCP",Associate,5,Manufacturing,2025-03-11,2025-04-21,939,5.6,Autonomous Tech -AI04858,Head of AI,53624,CAD,67030,EN,FL,Canada,S,Canada,100,"Spark, R, Computer Vision, Data Visualization",PhD,0,Energy,2024-06-02,2024-07-21,2033,6.9,Algorithmic Solutions -AI04859,NLP Engineer,85771,EUR,72905,MI,FT,Austria,L,Austria,0,"Kubernetes, Python, AWS, GCP, Linux",Associate,4,Retail,2024-01-09,2024-03-09,1532,5.3,Quantum Computing Inc -AI04860,Data Analyst,181719,EUR,154461,EX,FT,Germany,L,Germany,0,"Spark, NLP, Data Visualization, Statistics, R",PhD,16,Education,2024-01-20,2024-04-02,820,9,Smart Analytics -AI04861,AI Research Scientist,69580,EUR,59143,MI,PT,Austria,S,Austria,0,"Java, Docker, GCP, Computer Vision, Git",Master,2,Consulting,2025-03-31,2025-06-05,1398,9.3,AI Innovations -AI04862,Data Engineer,132740,EUR,112829,SE,FL,Austria,L,Austria,50,"Kubernetes, AWS, GCP, SQL",Bachelor,7,Gaming,2025-01-29,2025-04-09,1832,6.4,Quantum Computing Inc -AI04863,Principal Data Scientist,130258,CAD,162823,SE,CT,Canada,M,Canada,50,"Data Visualization, Python, TensorFlow",Master,7,Telecommunications,2025-04-28,2025-07-01,1257,6.4,Autonomous Tech -AI04864,Computer Vision Engineer,116709,USD,116709,SE,PT,Israel,S,Russia,50,"SQL, Python, R, AWS, Tableau",PhD,9,Manufacturing,2024-06-23,2024-08-31,1408,6.5,Predictive Systems -AI04865,Research Scientist,80310,EUR,68264,MI,CT,Netherlands,M,Netherlands,0,"SQL, Docker, AWS",Associate,3,Automotive,2024-07-07,2024-09-04,1673,7.5,TechCorp Inc -AI04866,Robotics Engineer,185837,EUR,157961,EX,FL,Austria,M,Austria,100,"Scala, Kubernetes, NLP",Associate,13,Media,2024-05-23,2024-07-09,2427,9.4,Machine Intelligence Group -AI04867,Data Engineer,73290,EUR,62297,EN,CT,Netherlands,M,Netherlands,0,"Java, Mathematics, R",Master,0,Media,2024-12-31,2025-02-03,2265,8.4,Advanced Robotics -AI04868,AI Research Scientist,115082,GBP,86312,MI,PT,United Kingdom,M,United Kingdom,100,"R, MLOps, Git, Linux",Bachelor,2,Finance,2024-12-17,2025-02-06,2229,5.5,Digital Transformation LLC -AI04869,Machine Learning Researcher,239030,AUD,322691,EX,PT,Australia,L,Australia,50,"SQL, TensorFlow, PyTorch, Computer Vision, Mathematics",Associate,11,Automotive,2025-04-09,2025-05-09,1765,6.8,Cloud AI Solutions -AI04870,AI Software Engineer,78991,EUR,67142,MI,CT,Austria,L,Austria,50,"Kubernetes, Java, SQL, Statistics",Bachelor,4,Telecommunications,2025-04-15,2025-05-24,1694,5.1,Predictive Systems -AI04871,Head of AI,174805,USD,174805,EX,PT,Sweden,S,Sweden,100,"Spark, Azure, Scala, Deep Learning",Master,19,Media,2025-01-06,2025-02-01,2055,6.3,DataVision Ltd -AI04872,Machine Learning Researcher,181104,CHF,162994,SE,CT,Switzerland,S,Switzerland,50,"Python, Docker, NLP, AWS, Computer Vision",PhD,9,Consulting,2024-08-23,2024-10-25,2359,7.1,Future Systems -AI04873,AI Architect,115681,USD,115681,SE,PT,Finland,L,Ghana,0,"GCP, Scala, Python",Master,9,Consulting,2024-02-18,2024-04-11,1305,6.7,DeepTech Ventures -AI04874,Robotics Engineer,43208,USD,43208,EN,PT,China,L,China,100,"Scala, Python, Kubernetes, Hadoop",PhD,1,Education,2024-10-29,2025-01-08,2363,5.3,Advanced Robotics -AI04875,AI Specialist,94668,USD,94668,MI,PT,Sweden,S,Sweden,100,"Spark, SQL, Python",Bachelor,4,Manufacturing,2024-12-25,2025-03-06,2189,5.5,Advanced Robotics -AI04876,Principal Data Scientist,88758,EUR,75444,EN,FL,Germany,L,Germany,0,"AWS, Computer Vision, Spark, Java",Master,1,Technology,2024-06-08,2024-07-04,1959,9,Future Systems -AI04877,Data Scientist,107851,EUR,91673,SE,FT,Austria,S,Austria,0,"Statistics, PyTorch, Mathematics",Associate,9,Consulting,2025-02-13,2025-03-24,952,8.1,Predictive Systems -AI04878,Research Scientist,77521,USD,77521,EN,PT,Denmark,L,Japan,0,"Hadoop, Git, Mathematics, Computer Vision",Bachelor,0,Manufacturing,2024-08-27,2024-10-18,1875,6.6,Predictive Systems -AI04879,NLP Engineer,48915,USD,48915,EN,FL,Finland,M,Finland,50,"Kubernetes, Docker, Statistics, Azure, SQL",PhD,0,Transportation,2025-01-15,2025-03-21,2032,8.8,TechCorp Inc -AI04880,AI Specialist,144329,USD,144329,EX,FL,Ireland,S,Ireland,50,"Azure, SQL, TensorFlow, R, Statistics",Master,12,Media,2024-05-03,2024-06-11,1802,9,Algorithmic Solutions -AI04881,Deep Learning Engineer,74868,AUD,101072,MI,CT,Australia,S,Australia,50,"Python, TensorFlow, Java, PyTorch",PhD,4,Retail,2025-04-04,2025-06-11,1782,5.1,Smart Analytics -AI04882,AI Consultant,173810,AUD,234644,SE,PT,Australia,L,Australia,50,"TensorFlow, SQL, Linux, Git",Bachelor,7,Government,2024-03-27,2024-05-04,703,9.5,Advanced Robotics -AI04883,Computer Vision Engineer,119626,USD,119626,SE,CT,Israel,S,Ukraine,50,"Kubernetes, Statistics, Scala",Master,5,Finance,2025-04-29,2025-07-07,1482,7.8,Algorithmic Solutions -AI04884,Head of AI,55331,USD,55331,EN,CT,Finland,S,Finland,50,"Git, Spark, Python",Associate,0,Technology,2024-12-23,2025-03-01,853,6.3,Digital Transformation LLC -AI04885,Research Scientist,126364,EUR,107409,MI,FL,Germany,L,Germany,0,"Statistics, Python, Computer Vision",Master,2,Finance,2024-06-22,2024-08-08,1656,5.6,DeepTech Ventures -AI04886,Autonomous Systems Engineer,193012,USD,193012,EX,PT,Sweden,M,Sweden,50,"Spark, Docker, MLOps, GCP, Kubernetes",PhD,12,Energy,2024-07-03,2024-08-30,1282,8.1,DataVision Ltd -AI04887,Machine Learning Engineer,50277,USD,50277,SE,CT,China,M,China,50,"GCP, Tableau, SQL, Git",PhD,7,Media,2024-07-23,2024-09-01,1771,9.9,AI Innovations -AI04888,Computer Vision Engineer,52691,USD,52691,EN,CT,Sweden,S,Italy,0,"PyTorch, Computer Vision, Tableau, TensorFlow",Bachelor,0,Education,2024-10-17,2024-11-05,1506,6.4,Machine Intelligence Group -AI04889,Head of AI,88745,EUR,75433,MI,CT,Austria,M,Austria,50,"AWS, Spark, Hadoop, Azure, Scala",Master,3,Energy,2025-03-19,2025-05-26,1029,8.9,Predictive Systems -AI04890,AI Research Scientist,69741,EUR,59280,EN,FL,France,M,France,0,"PyTorch, TensorFlow, Kubernetes, NLP, GCP",Bachelor,1,Technology,2024-05-15,2024-07-18,1172,6.8,Autonomous Tech -AI04891,Research Scientist,103812,SGD,134956,SE,PT,Singapore,S,Singapore,50,"GCP, Kubernetes, Docker, Mathematics",Bachelor,7,Energy,2024-06-25,2024-08-14,1953,9.6,Predictive Systems -AI04892,AI Product Manager,110207,USD,110207,EN,PT,Denmark,L,Denmark,0,"PyTorch, Hadoop, Data Visualization, AWS, SQL",PhD,1,Finance,2025-03-17,2025-04-11,1555,6.1,Autonomous Tech -AI04893,Data Engineer,90086,USD,90086,EN,CT,United States,L,United States,50,"Python, Data Visualization, Mathematics, TensorFlow",Master,1,Manufacturing,2024-01-30,2024-03-10,1449,5.4,Digital Transformation LLC -AI04894,Computer Vision Engineer,69149,USD,69149,MI,FT,Finland,M,Kenya,100,"Spark, Python, TensorFlow, GCP",Master,4,Telecommunications,2024-04-12,2024-06-21,1681,7.5,Predictive Systems -AI04895,Robotics Engineer,62098,USD,62098,EX,FL,India,M,India,0,"Deep Learning, MLOps, TensorFlow",Associate,16,Energy,2025-04-13,2025-04-28,2374,8.2,Autonomous Tech -AI04896,AI Research Scientist,58340,EUR,49589,EN,PT,Germany,S,Germany,50,"SQL, MLOps, Tableau, AWS, Azure",PhD,0,Automotive,2024-03-20,2024-05-01,1877,5,Advanced Robotics -AI04897,Machine Learning Researcher,27753,USD,27753,EN,FL,China,M,Chile,0,"SQL, Data Visualization, Python, Kubernetes",PhD,1,Telecommunications,2024-07-30,2024-10-05,853,8.1,DataVision Ltd -AI04898,Data Engineer,94238,EUR,80102,MI,FL,France,L,France,100,"Mathematics, Linux, Azure, Python, TensorFlow",Bachelor,2,Transportation,2024-07-19,2024-08-13,1185,6.9,Algorithmic Solutions -AI04899,AI Research Scientist,90515,USD,90515,SE,CT,South Korea,M,South Korea,0,"Python, TensorFlow, Data Visualization",PhD,6,Media,2024-03-04,2024-05-14,1338,9.1,Autonomous Tech -AI04900,Research Scientist,252088,USD,252088,EX,FL,Ireland,M,Ireland,100,"Mathematics, NLP, Scala, PyTorch, Docker",Master,12,Government,2024-03-11,2024-04-30,1589,7.5,DataVision Ltd -AI04901,Computer Vision Engineer,123498,AUD,166722,EX,FT,Australia,S,Australia,50,"Linux, PyTorch, TensorFlow, Data Visualization, SQL",PhD,19,Media,2025-01-02,2025-01-20,2319,7.5,Smart Analytics -AI04902,Machine Learning Engineer,97399,GBP,73049,SE,PT,United Kingdom,S,United Kingdom,0,"Kubernetes, SQL, R",Bachelor,8,Manufacturing,2024-12-24,2025-01-30,1269,7.4,Cognitive Computing -AI04903,AI Product Manager,122301,SGD,158991,MI,FL,Singapore,L,Singapore,100,"Scala, Python, TensorFlow, AWS",PhD,4,Education,2024-04-04,2024-05-22,2205,7.2,Future Systems -AI04904,Computer Vision Engineer,102239,SGD,132911,MI,PT,Singapore,S,Belgium,50,"Mathematics, Docker, AWS",Associate,4,Manufacturing,2024-07-20,2024-09-28,1780,9,AI Innovations -AI04905,Computer Vision Engineer,194401,JPY,21384110,EX,FL,Japan,S,Nigeria,0,"Java, Python, GCP, AWS",PhD,19,Real Estate,2024-10-12,2024-11-20,2140,5.9,AI Innovations -AI04906,Machine Learning Researcher,88107,USD,88107,EN,PT,Denmark,L,France,50,"Hadoop, Scala, Spark",PhD,0,Technology,2024-07-27,2024-09-15,889,6.7,Autonomous Tech -AI04907,AI Software Engineer,147607,USD,147607,SE,FL,Finland,L,Finland,0,"Python, NLP, GCP, Computer Vision",PhD,7,Automotive,2024-05-24,2024-06-26,2274,8.1,Advanced Robotics -AI04908,AI Product Manager,62399,USD,62399,EN,FT,South Korea,L,South Korea,100,"Python, Data Visualization, R",Master,1,Technology,2025-03-08,2025-05-04,1926,9.4,Machine Intelligence Group -AI04909,AI Consultant,178097,CHF,160287,EX,FL,Switzerland,S,Latvia,50,"Git, PyTorch, Hadoop",PhD,16,Education,2024-03-02,2024-03-22,1043,6.6,Digital Transformation LLC -AI04910,Autonomous Systems Engineer,121196,EUR,103017,SE,FL,Netherlands,S,Netherlands,100,"Docker, Linux, Computer Vision",Master,9,Automotive,2025-03-02,2025-04-27,639,6.4,Quantum Computing Inc -AI04911,ML Ops Engineer,196124,USD,196124,EX,CT,Ireland,L,Ireland,0,"PyTorch, R, AWS",Bachelor,11,Retail,2024-11-14,2024-12-18,1350,5.4,TechCorp Inc -AI04912,Deep Learning Engineer,133436,EUR,113421,EX,FL,Germany,S,United States,100,"Computer Vision, Python, Linux",Bachelor,12,Finance,2024-04-23,2024-06-06,708,5.6,Quantum Computing Inc -AI04913,Research Scientist,63143,JPY,6945730,EN,CT,Japan,S,Japan,0,"Git, Hadoop, Data Visualization, GCP",Bachelor,0,Consulting,2024-01-23,2024-02-09,844,9.7,Future Systems -AI04914,Data Engineer,101308,USD,101308,SE,CT,Finland,M,Finland,100,"SQL, NLP, Statistics, Hadoop",Master,9,Transportation,2024-01-28,2024-03-09,1781,9.5,TechCorp Inc -AI04915,Head of AI,129700,USD,129700,EX,PT,Israel,M,Israel,100,"Mathematics, PyTorch, Computer Vision, Azure, NLP",Bachelor,10,Education,2024-12-07,2025-02-11,819,7.3,Future Systems -AI04916,Data Scientist,82759,GBP,62069,MI,FT,United Kingdom,M,Italy,100,"Azure, Kubernetes, Docker",Associate,3,Technology,2024-09-08,2024-10-17,2024,9,AI Innovations -AI04917,Principal Data Scientist,58384,USD,58384,EN,CT,Sweden,S,Sweden,0,"R, MLOps, Hadoop, Computer Vision",PhD,0,Manufacturing,2024-11-21,2025-01-20,1210,9.6,Predictive Systems -AI04918,NLP Engineer,57840,USD,57840,SE,PT,China,M,China,50,"Kubernetes, PyTorch, Statistics, Docker, Azure",Master,7,Telecommunications,2024-08-17,2024-10-13,1991,5,Machine Intelligence Group -AI04919,AI Architect,67529,USD,67529,EN,FL,Ireland,M,Ireland,0,"Linux, GCP, Mathematics, Deep Learning",PhD,0,Energy,2024-09-27,2024-11-19,1391,5.9,Advanced Robotics -AI04920,Autonomous Systems Engineer,103319,EUR,87821,MI,CT,Netherlands,M,Spain,50,"Kubernetes, Tableau, Java, Computer Vision",Associate,2,Gaming,2024-05-04,2024-06-07,744,6.7,Machine Intelligence Group -AI04921,Data Analyst,264281,USD,264281,EX,FL,Israel,L,Israel,100,"Hadoop, Docker, PyTorch, Spark, Tableau",Associate,16,Healthcare,2024-02-19,2024-03-24,2369,8.6,Quantum Computing Inc -AI04922,Robotics Engineer,90375,USD,90375,EN,FT,Norway,S,Hungary,100,"Statistics, TensorFlow, R, MLOps",PhD,1,Energy,2025-03-11,2025-05-09,2386,9.1,Algorithmic Solutions -AI04923,Machine Learning Researcher,168030,CAD,210038,EX,FT,Canada,L,Canada,100,"GCP, Spark, Deep Learning, TensorFlow, Hadoop",PhD,18,Education,2024-08-02,2024-08-17,1548,9.9,Cognitive Computing -AI04924,AI Architect,144693,USD,144693,SE,CT,United States,S,United States,100,"AWS, Azure, PyTorch",PhD,7,Transportation,2025-01-19,2025-02-28,1380,8.6,Algorithmic Solutions -AI04925,NLP Engineer,169169,EUR,143794,EX,FT,Netherlands,S,Netherlands,100,"Scala, AWS, R",Bachelor,17,Government,2024-10-29,2024-12-16,1867,7.8,Cognitive Computing -AI04926,AI Research Scientist,97205,EUR,82624,MI,PT,Austria,L,Austria,100,"MLOps, Hadoop, Java",Bachelor,2,Automotive,2024-12-04,2025-01-05,1638,8.1,DeepTech Ventures -AI04927,AI Consultant,116462,USD,116462,SE,FL,United States,S,United States,100,"Hadoop, Docker, NLP, Kubernetes, Computer Vision",Master,5,Manufacturing,2024-12-17,2025-02-18,936,9.5,Advanced Robotics -AI04928,AI Research Scientist,161251,USD,161251,EX,CT,United States,S,United States,0,"Tableau, Statistics, TensorFlow, Data Visualization, AWS",Associate,13,Transportation,2024-11-04,2025-01-12,2473,10,Cognitive Computing -AI04929,AI Software Engineer,127524,USD,127524,SE,FL,Sweden,M,Sweden,50,"Deep Learning, SQL, MLOps",Bachelor,8,Gaming,2024-11-25,2025-01-10,845,5.6,TechCorp Inc -AI04930,Autonomous Systems Engineer,40391,USD,40391,MI,CT,India,L,Czech Republic,100,"AWS, PyTorch, Linux, Mathematics, Data Visualization",Master,4,Energy,2024-02-05,2024-04-02,1473,9.8,Neural Networks Co -AI04931,Data Engineer,125657,USD,125657,SE,FT,Finland,S,Hungary,50,"Python, Azure, SQL",PhD,9,Automotive,2024-03-11,2024-03-30,1378,9,Neural Networks Co -AI04932,Computer Vision Engineer,220521,GBP,165391,EX,FL,United Kingdom,S,Poland,100,"AWS, Python, TensorFlow, Statistics",PhD,15,Finance,2024-03-01,2024-04-05,1224,7.4,Autonomous Tech -AI04933,AI Software Engineer,75300,GBP,56475,EN,FL,United Kingdom,S,United Kingdom,50,"GCP, R, Mathematics, Hadoop",Bachelor,0,Real Estate,2025-02-13,2025-04-27,1543,7.5,Machine Intelligence Group -AI04934,Data Analyst,89549,USD,89549,MI,PT,Ireland,L,Vietnam,100,"PyTorch, TensorFlow, Mathematics, Docker",Master,3,Consulting,2025-02-01,2025-04-03,1192,6.1,Cognitive Computing -AI04935,AI Research Scientist,230750,GBP,173063,EX,FL,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Git",Master,18,Retail,2024-07-26,2024-08-25,828,5.6,TechCorp Inc -AI04936,Computer Vision Engineer,43742,USD,43742,MI,CT,China,M,China,100,"Kubernetes, GCP, Scala",PhD,4,Finance,2024-02-28,2024-04-03,568,8.1,Advanced Robotics -AI04937,Machine Learning Engineer,73505,USD,73505,EN,FT,Ireland,L,Israel,100,"Kubernetes, GCP, SQL, Azure",Master,1,Energy,2025-02-15,2025-04-19,1617,8.5,AI Innovations -AI04938,ML Ops Engineer,93032,USD,93032,MI,CT,Israel,S,Ireland,100,"SQL, R, Tableau",Bachelor,2,Real Estate,2024-09-23,2024-11-05,697,8.4,Smart Analytics -AI04939,Machine Learning Researcher,310945,CHF,279851,EX,FL,Switzerland,S,Poland,0,"Kubernetes, Scala, Azure",Bachelor,18,Retail,2024-09-03,2024-10-20,1636,7.5,Smart Analytics -AI04940,Principal Data Scientist,91705,USD,91705,MI,FL,Israel,S,Israel,0,"Computer Vision, Kubernetes, GCP, R",PhD,2,Gaming,2024-05-31,2024-08-09,1029,9.7,Cloud AI Solutions -AI04941,AI Consultant,84567,USD,84567,EN,FL,Norway,L,Norway,50,"R, SQL, Azure, Deep Learning, Linux",Associate,0,Education,2024-04-16,2024-06-03,1320,9.6,Digital Transformation LLC -AI04942,AI Architect,77592,EUR,65953,EN,FT,Austria,L,Vietnam,100,"Docker, Hadoop, Tableau",Master,1,Automotive,2024-07-22,2024-09-16,1129,8.7,DeepTech Ventures -AI04943,Head of AI,106660,USD,106660,SE,FL,Sweden,M,Chile,100,"MLOps, Statistics, AWS, NLP, Computer Vision",Associate,9,Retail,2024-06-15,2024-07-05,1054,9.8,AI Innovations -AI04944,Data Engineer,46462,USD,46462,MI,PT,China,L,China,100,"Kubernetes, Git, Statistics",Bachelor,3,Consulting,2024-12-02,2025-01-04,2365,6.6,Neural Networks Co -AI04945,Autonomous Systems Engineer,131368,GBP,98526,SE,PT,United Kingdom,M,Luxembourg,50,"Git, Azure, GCP, Python, AWS",Bachelor,9,Manufacturing,2024-08-10,2024-10-13,503,5,Cognitive Computing -AI04946,Data Scientist,78787,USD,78787,MI,PT,South Korea,S,South Korea,50,"Kubernetes, PyTorch, MLOps, SQL",Master,3,Retail,2024-11-25,2025-01-12,1588,6.4,Cloud AI Solutions -AI04947,ML Ops Engineer,57111,USD,57111,EN,PT,Sweden,M,Sweden,100,"Java, Azure, PyTorch, Scala",Master,1,Automotive,2025-02-24,2025-04-26,931,9,Quantum Computing Inc -AI04948,Deep Learning Engineer,70529,USD,70529,EN,FL,United States,L,United States,100,"Computer Vision, R, SQL",Master,0,Retail,2024-09-17,2024-11-05,1367,8.8,Cognitive Computing -AI04949,Principal Data Scientist,166422,USD,166422,SE,FT,Ireland,L,United States,100,"Spark, Tableau, R, SQL",PhD,6,Transportation,2024-07-20,2024-09-25,1832,5.5,Future Systems -AI04950,Deep Learning Engineer,132627,JPY,14588970,SE,CT,Japan,S,Japan,100,"R, Kubernetes, Python",Bachelor,9,Finance,2025-03-22,2025-05-06,2345,9.9,Advanced Robotics -AI04951,AI Product Manager,79266,USD,79266,EN,PT,Ireland,M,Ireland,0,"Statistics, Kubernetes, Computer Vision, Python, Git",PhD,0,Automotive,2025-04-29,2025-05-15,1442,6.4,AI Innovations -AI04952,Data Analyst,159779,EUR,135812,EX,CT,Germany,L,Portugal,50,"Azure, Python, Docker, Hadoop, Linux",PhD,12,Government,2024-10-14,2024-11-18,975,7.5,Digital Transformation LLC -AI04953,Principal Data Scientist,139290,USD,139290,SE,CT,United States,S,United States,0,"Tableau, SQL, Scala, Computer Vision, Java",Master,8,Education,2024-10-16,2024-11-17,1978,7.6,AI Innovations -AI04954,Robotics Engineer,231125,CHF,208013,EX,CT,Switzerland,S,Romania,100,"SQL, NLP, Tableau",Master,16,Healthcare,2024-05-05,2024-05-26,1244,9.1,Predictive Systems -AI04955,AI Architect,122595,GBP,91946,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Kubernetes, Scala, Deep Learning",Master,3,Energy,2024-09-02,2024-11-04,2102,8,Algorithmic Solutions -AI04956,Data Analyst,68427,USD,68427,EN,CT,Ireland,S,Ireland,0,"AWS, Linux, SQL",Bachelor,1,Retail,2024-07-20,2024-09-11,1893,6.4,Cognitive Computing -AI04957,Head of AI,202722,USD,202722,EX,FL,Finland,L,Finland,100,"AWS, Git, Python, Deep Learning, Spark",Bachelor,16,Healthcare,2024-06-27,2024-08-21,1923,6.2,Neural Networks Co -AI04958,Data Scientist,108147,EUR,91925,SE,FT,Austria,M,Latvia,50,"Data Visualization, PyTorch, MLOps",PhD,7,Finance,2024-09-26,2024-11-15,626,8.1,Machine Intelligence Group -AI04959,ML Ops Engineer,115437,AUD,155840,SE,FT,Australia,S,Australia,100,"TensorFlow, Hadoop, Mathematics, SQL",Master,6,Automotive,2024-12-13,2025-02-08,1204,9.8,Predictive Systems -AI04960,Head of AI,77217,GBP,57913,MI,PT,United Kingdom,S,United Kingdom,50,"Hadoop, Java, SQL, AWS",Bachelor,4,Finance,2024-10-16,2024-11-02,1484,9.7,DeepTech Ventures -AI04961,AI Software Engineer,57529,USD,57529,EN,CT,Israel,L,Kenya,100,"MLOps, TensorFlow, Kubernetes, Data Visualization",PhD,1,Manufacturing,2024-03-15,2024-03-29,928,8.4,Smart Analytics -AI04962,Principal Data Scientist,113427,EUR,96413,MI,PT,France,L,France,100,"SQL, Data Visualization, TensorFlow, Scala, R",Bachelor,4,Transportation,2024-01-13,2024-03-10,794,6.3,TechCorp Inc -AI04963,Autonomous Systems Engineer,71693,USD,71693,EN,PT,Denmark,M,Denmark,50,"Python, Deep Learning, Mathematics, PyTorch, AWS",PhD,0,Gaming,2024-06-08,2024-07-27,2047,7.3,Digital Transformation LLC -AI04964,ML Ops Engineer,151134,EUR,128464,SE,CT,Germany,M,Germany,0,"PyTorch, Git, TensorFlow",PhD,9,Healthcare,2024-12-05,2025-01-31,1045,9.7,DataVision Ltd -AI04965,AI Product Manager,135496,EUR,115172,EX,CT,France,M,France,0,"GCP, Data Visualization, Scala, Git",PhD,18,Consulting,2024-01-23,2024-02-15,938,7.3,Future Systems -AI04966,NLP Engineer,93530,USD,93530,EX,CT,India,L,India,100,"R, Tableau, Data Visualization, Python, PyTorch",Associate,10,Finance,2024-07-13,2024-08-22,1866,8.2,TechCorp Inc -AI04967,AI Research Scientist,194766,JPY,21424260,EX,PT,Japan,L,Japan,50,"Kubernetes, Spark, PyTorch, TensorFlow",PhD,17,Government,2024-02-20,2024-04-03,1832,7,Smart Analytics -AI04968,Data Engineer,214036,JPY,23543960,EX,PT,Japan,M,Netherlands,0,"Deep Learning, SQL, Spark",Associate,15,Healthcare,2025-02-27,2025-04-29,2309,5.8,Neural Networks Co -AI04969,AI Consultant,33244,USD,33244,EN,CT,China,M,China,50,"Deep Learning, Scala, Tableau, Computer Vision",Associate,0,Gaming,2024-08-03,2024-09-29,1665,7.8,Algorithmic Solutions -AI04970,AI Specialist,133388,USD,133388,SE,FL,Denmark,M,Denmark,100,"Computer Vision, Hadoop, Tableau, TensorFlow, Python",Bachelor,6,Telecommunications,2024-02-10,2024-03-09,623,8.1,Algorithmic Solutions -AI04971,Research Scientist,44185,USD,44185,EN,FT,Israel,S,New Zealand,0,"AWS, Scala, Mathematics, TensorFlow, Hadoop",Master,1,Technology,2024-10-07,2024-12-01,781,5.7,Future Systems -AI04972,AI Architect,89882,EUR,76400,SE,CT,Austria,S,Malaysia,50,"AWS, Azure, GCP, Statistics",Master,8,Healthcare,2024-05-14,2024-07-11,1075,8,Smart Analytics -AI04973,Data Engineer,167159,GBP,125369,EX,PT,United Kingdom,L,United Kingdom,100,"Computer Vision, Git, AWS",Associate,10,Telecommunications,2024-12-05,2025-01-08,1609,7.3,Advanced Robotics -AI04974,Autonomous Systems Engineer,110919,USD,110919,SE,FT,South Korea,M,Australia,50,"Scala, Mathematics, Deep Learning, Computer Vision",Associate,9,Technology,2024-08-09,2024-09-17,1747,6.7,Future Systems -AI04975,AI Consultant,153715,USD,153715,SE,FT,Israel,L,Turkey,0,"MLOps, Linux, Kubernetes",Associate,7,Energy,2024-12-09,2025-01-07,2330,6.8,Quantum Computing Inc -AI04976,AI Consultant,132249,USD,132249,SE,CT,Sweden,M,Ireland,50,"Kubernetes, Git, Spark",Associate,6,Retail,2024-06-21,2024-08-01,690,5.4,Smart Analytics -AI04977,NLP Engineer,231132,USD,231132,EX,FT,Denmark,S,Denmark,0,"Python, Git, Docker, Hadoop, Statistics",Bachelor,14,Media,2024-10-18,2024-12-24,1890,6.3,Neural Networks Co -AI04978,AI Consultant,85300,EUR,72505,EN,CT,France,L,France,50,"Java, Data Visualization, PyTorch, AWS",Associate,0,Energy,2024-04-24,2024-05-21,1221,6.4,Machine Intelligence Group -AI04979,AI Product Manager,128111,USD,128111,EX,CT,Sweden,S,Mexico,100,"Java, R, Computer Vision, Statistics, Kubernetes",Associate,15,Education,2025-03-22,2025-05-06,1631,7.6,Future Systems -AI04980,AI Architect,61852,SGD,80408,EN,FT,Singapore,S,Canada,50,"MLOps, SQL, Git, PyTorch",Bachelor,1,Energy,2024-09-11,2024-09-27,2061,5.6,DataVision Ltd -AI04981,Data Scientist,59300,USD,59300,EN,FL,Israel,S,Sweden,0,"PyTorch, Spark, Tableau, MLOps, SQL",Associate,0,Energy,2024-01-08,2024-03-18,1348,9.3,Machine Intelligence Group -AI04982,Machine Learning Researcher,126739,SGD,164761,SE,PT,Singapore,S,Singapore,50,"Git, TensorFlow, SQL",Associate,5,Media,2024-11-29,2025-01-31,554,8.3,Machine Intelligence Group -AI04983,Computer Vision Engineer,80800,USD,80800,EN,CT,Denmark,M,Denmark,50,"Python, Kubernetes, NLP, Statistics",Associate,0,Gaming,2024-03-25,2024-04-28,594,6,Quantum Computing Inc -AI04984,NLP Engineer,85451,AUD,115359,MI,FT,Australia,S,Luxembourg,50,"Kubernetes, Linux, Python",Bachelor,3,Government,2024-06-02,2024-08-05,2249,7.8,DeepTech Ventures -AI04985,AI Product Manager,82153,USD,82153,EN,CT,United States,M,Estonia,50,"Hadoop, TensorFlow, AWS",Associate,0,Telecommunications,2024-03-14,2024-05-17,927,6,DataVision Ltd -AI04986,Machine Learning Researcher,79663,USD,79663,MI,FL,Ireland,S,Ireland,100,"Java, R, MLOps, SQL, Statistics",Associate,2,Energy,2024-08-06,2024-08-21,1985,7.7,Future Systems -AI04987,Robotics Engineer,141209,EUR,120028,SE,PT,Austria,L,Austria,0,"Hadoop, Linux, PyTorch, Java, Mathematics",Master,8,Energy,2025-04-24,2025-05-10,2143,7.8,TechCorp Inc -AI04988,Machine Learning Researcher,47558,USD,47558,EX,FT,India,S,India,0,"NLP, Tableau, Spark, TensorFlow, Statistics",Bachelor,12,Healthcare,2024-02-03,2024-04-05,1793,9,Predictive Systems -AI04989,Machine Learning Researcher,134887,USD,134887,MI,FT,Denmark,L,Denmark,100,"Data Visualization, Scala, Java, R, Computer Vision",PhD,2,Government,2025-03-13,2025-04-23,2069,9.1,Machine Intelligence Group -AI04990,AI Research Scientist,216990,USD,216990,EX,PT,Finland,M,Finland,50,"Hadoop, SQL, Computer Vision, Scala",Master,19,Technology,2024-04-13,2024-05-19,2371,5.6,TechCorp Inc -AI04991,Machine Learning Engineer,270223,EUR,229690,EX,CT,France,L,France,50,"Linux, Python, Deep Learning, Hadoop",Associate,15,Consulting,2024-02-25,2024-05-08,820,8.2,Digital Transformation LLC -AI04992,AI Product Manager,123617,USD,123617,SE,PT,Sweden,S,Indonesia,50,"Python, Hadoop, TensorFlow, PyTorch",Bachelor,8,Technology,2024-11-14,2024-12-13,1367,9,Advanced Robotics -AI04993,Deep Learning Engineer,179200,CHF,161280,SE,CT,Switzerland,M,Switzerland,50,"Python, Linux, Git, R, TensorFlow",Master,6,Media,2024-10-31,2025-01-02,654,9.1,Quantum Computing Inc -AI04994,Robotics Engineer,123515,USD,123515,SE,FL,Finland,M,Finland,0,"Spark, Kubernetes, Scala, Mathematics, Linux",Master,5,Retail,2025-03-29,2025-05-08,736,9.6,Cloud AI Solutions -AI04995,AI Research Scientist,101862,AUD,137514,MI,PT,Australia,L,Ukraine,100,"Git, Python, Computer Vision, TensorFlow, PyTorch",Associate,3,Transportation,2024-04-13,2024-05-22,1831,5.3,Predictive Systems -AI04996,AI Consultant,183450,USD,183450,EX,PT,United States,S,United States,50,"GCP, Computer Vision, SQL",Bachelor,17,Government,2024-06-17,2024-07-12,902,6.3,Neural Networks Co -AI04997,Machine Learning Engineer,81041,SGD,105353,EN,PT,Singapore,L,Singapore,0,"MLOps, PyTorch, Python, TensorFlow",Associate,1,Finance,2024-06-29,2024-08-16,1494,9.3,Autonomous Tech -AI04998,AI Software Engineer,80467,USD,80467,EX,PT,India,S,India,0,"Mathematics, Linux, Git, PyTorch",Master,14,Manufacturing,2024-11-22,2024-12-25,2205,6.8,Predictive Systems -AI04999,AI Software Engineer,88669,AUD,119703,MI,CT,Australia,L,Australia,100,"Python, Hadoop, MLOps",Master,3,Real Estate,2024-05-30,2024-08-10,1427,5.5,DataVision Ltd -AI05000,Machine Learning Researcher,113313,USD,113313,MI,FT,Sweden,L,Sweden,100,"Scala, SQL, PyTorch, R",PhD,3,Education,2024-09-27,2024-11-25,1895,9.5,Digital Transformation LLC -AI05001,Research Scientist,306192,USD,306192,EX,FT,Denmark,L,Denmark,0,"PyTorch, Azure, Tableau, Scala",PhD,11,Automotive,2025-02-25,2025-03-20,2405,5.5,Smart Analytics -AI05002,Head of AI,190624,USD,190624,EX,CT,Denmark,S,Denmark,50,"Kubernetes, Tableau, Python, Hadoop",Bachelor,15,Automotive,2024-10-22,2024-12-06,1947,7.2,Cloud AI Solutions -AI05003,NLP Engineer,68152,SGD,88598,EN,FT,Singapore,L,Egypt,0,"R, Azure, Kubernetes, Linux",PhD,0,Telecommunications,2024-03-20,2024-05-06,1227,9.1,Algorithmic Solutions -AI05004,Principal Data Scientist,91590,USD,91590,EN,CT,United States,L,Kenya,0,"PyTorch, SQL, Kubernetes, Java, AWS",Associate,1,Media,2024-06-27,2024-07-19,578,6.6,Autonomous Tech -AI05005,AI Research Scientist,50730,EUR,43121,EN,FT,Netherlands,S,Netherlands,0,"R, Java, Data Visualization, NLP",PhD,1,Real Estate,2024-04-28,2024-05-15,1020,5.7,TechCorp Inc -AI05006,Robotics Engineer,57915,GBP,43436,EN,FL,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, AWS, Mathematics, Git",Associate,0,Finance,2025-03-02,2025-04-20,2451,8.9,Future Systems -AI05007,AI Architect,74536,AUD,100624,MI,FL,Australia,S,Turkey,0,"Kubernetes, Docker, Data Visualization",PhD,2,Retail,2025-02-19,2025-04-26,1612,9.3,Predictive Systems -AI05008,Data Engineer,179315,USD,179315,SE,FL,Denmark,L,Denmark,0,"Python, TensorFlow, Linux, PyTorch",PhD,8,Education,2024-09-14,2024-10-29,925,5.3,Digital Transformation LLC -AI05009,ML Ops Engineer,19776,USD,19776,EN,FT,India,M,Japan,50,"Docker, Scala, GCP, MLOps",Bachelor,0,Consulting,2024-07-30,2024-09-17,604,8.3,DataVision Ltd -AI05010,Data Analyst,73489,EUR,62466,EN,CT,Netherlands,S,Ireland,0,"Computer Vision, Tableau, Linux, Git, Deep Learning",Master,0,Education,2024-11-23,2025-01-04,1966,9.7,DeepTech Ventures -AI05011,AI Product Manager,67007,JPY,7370770,EN,CT,Japan,S,Japan,100,"SQL, TensorFlow, Data Visualization, NLP, Linux",Bachelor,1,Finance,2024-10-18,2024-12-25,1765,8.2,Advanced Robotics -AI05012,Machine Learning Engineer,26216,USD,26216,EN,PT,China,M,China,50,"Hadoop, Data Visualization, Python, Statistics, Mathematics",Associate,1,Gaming,2024-08-16,2024-10-25,2458,6.5,Cognitive Computing -AI05013,ML Ops Engineer,80593,CAD,100741,MI,CT,Canada,L,Canada,100,"Hadoop, SQL, Java",Associate,3,Government,2024-06-09,2024-07-02,714,5.3,Machine Intelligence Group -AI05014,Principal Data Scientist,251940,AUD,340119,EX,FL,Australia,L,Australia,50,"NLP, R, Statistics, SQL, Data Visualization",Master,12,Manufacturing,2025-01-01,2025-01-21,2150,7.3,Advanced Robotics -AI05015,Data Scientist,271778,USD,271778,EX,FT,Ireland,L,Ukraine,0,"AWS, Linux, Python, TensorFlow, Computer Vision",Bachelor,17,Automotive,2024-05-06,2024-06-18,1477,8.3,Algorithmic Solutions -AI05016,AI Research Scientist,136680,EUR,116178,SE,FT,Austria,M,Austria,100,"Linux, Scala, Mathematics, Hadoop, Java",Associate,7,Energy,2024-06-27,2024-07-24,1821,6.7,Digital Transformation LLC -AI05017,AI Architect,90736,USD,90736,MI,CT,South Korea,M,Colombia,50,"Data Visualization, Git, R",Bachelor,3,Finance,2025-02-04,2025-03-18,1998,7.6,Future Systems -AI05018,Machine Learning Engineer,176612,USD,176612,EX,FT,Norway,M,Norway,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,12,Real Estate,2025-01-06,2025-01-23,1705,9.6,Digital Transformation LLC -AI05019,NLP Engineer,86142,USD,86142,SE,PT,South Korea,M,Czech Republic,100,"Computer Vision, NLP, Tableau, Data Visualization, MLOps",Master,6,Technology,2024-05-29,2024-07-19,2196,5.1,Advanced Robotics -AI05020,AI Research Scientist,71454,SGD,92890,MI,PT,Singapore,S,Singapore,100,"Scala, Linux, Data Visualization",Bachelor,4,Gaming,2024-02-21,2024-03-23,1063,6.1,Advanced Robotics -AI05021,AI Software Engineer,70698,USD,70698,EN,FT,Norway,S,Norway,100,"TensorFlow, Data Visualization, SQL, Hadoop, R",PhD,0,Real Estate,2024-08-07,2024-10-12,515,9.9,Algorithmic Solutions -AI05022,Computer Vision Engineer,70125,EUR,59606,EN,CT,Germany,M,United States,0,"TensorFlow, Tableau, GCP, Spark, Linux",Associate,0,Manufacturing,2025-04-14,2025-06-25,525,7.9,Machine Intelligence Group -AI05023,AI Specialist,164581,AUD,222184,EX,CT,Australia,S,Australia,100,"Tableau, Linux, PyTorch, TensorFlow, Computer Vision",Bachelor,11,Automotive,2025-02-04,2025-03-02,1128,9.7,TechCorp Inc -AI05024,NLP Engineer,125674,GBP,94256,SE,FL,United Kingdom,L,United Kingdom,100,"Computer Vision, MLOps, Git",Bachelor,6,Media,2024-08-16,2024-10-22,1388,8.8,Quantum Computing Inc -AI05025,Robotics Engineer,108470,CHF,97623,EN,FL,Switzerland,L,Switzerland,100,"Spark, Tableau, Docker, Deep Learning, NLP",Master,1,Telecommunications,2024-04-30,2024-07-10,1708,6.5,Quantum Computing Inc -AI05026,AI Architect,68849,USD,68849,EN,PT,United States,S,United States,0,"PyTorch, AWS, Computer Vision",Associate,0,Healthcare,2024-04-12,2024-06-09,1204,10,TechCorp Inc -AI05027,Autonomous Systems Engineer,101825,JPY,11200750,SE,CT,Japan,S,Japan,50,"MLOps, Java, Data Visualization, Linux, Scala",Bachelor,8,Real Estate,2025-02-27,2025-04-05,960,9.7,Future Systems -AI05028,Deep Learning Engineer,351728,USD,351728,EX,CT,Norway,L,Norway,0,"Tableau, Spark, Python, SQL",Bachelor,17,Real Estate,2024-09-22,2024-10-13,1508,5.3,Quantum Computing Inc -AI05029,Machine Learning Researcher,97819,USD,97819,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Git, GCP, Linux",Bachelor,9,Retail,2024-08-28,2024-09-14,1494,7.2,AI Innovations -AI05030,Data Scientist,163331,USD,163331,SE,FL,United States,M,United States,50,"TensorFlow, Git, Data Visualization, Kubernetes",Master,6,Healthcare,2025-04-29,2025-05-21,1419,9.5,Advanced Robotics -AI05031,Head of AI,93720,USD,93720,MI,CT,United States,M,United States,100,"Linux, Spark, SQL, PyTorch",PhD,4,Government,2024-12-19,2025-01-19,1659,9.1,Machine Intelligence Group -AI05032,NLP Engineer,108820,EUR,92497,MI,PT,Netherlands,M,Netherlands,50,"Kubernetes, Computer Vision, R, GCP, Hadoop",Master,2,Gaming,2024-12-14,2025-02-09,2389,9.4,AI Innovations -AI05033,AI Consultant,23491,USD,23491,EN,FL,India,S,India,0,"R, PyTorch, TensorFlow, Statistics",Bachelor,0,Healthcare,2024-02-07,2024-03-31,1921,7,TechCorp Inc -AI05034,Robotics Engineer,38464,USD,38464,SE,CT,India,M,Israel,100,"Python, TensorFlow, Statistics, PyTorch, Mathematics",PhD,6,Real Estate,2024-09-16,2024-10-17,1319,6.5,TechCorp Inc -AI05035,Data Analyst,121725,USD,121725,SE,PT,South Korea,M,South Korea,0,"Linux, TensorFlow, MLOps, Git, NLP",Bachelor,5,Government,2024-11-20,2024-12-23,1624,7.8,TechCorp Inc -AI05036,Computer Vision Engineer,121877,CHF,109689,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Deep Learning, Data Visualization",Bachelor,3,Finance,2024-03-21,2024-06-01,1183,6.6,Future Systems -AI05037,Machine Learning Researcher,96000,USD,96000,EN,CT,Norway,M,Norway,50,"Scala, Deep Learning, Computer Vision, GCP, Git",Bachelor,0,Retail,2024-01-27,2024-02-24,1635,8,Advanced Robotics -AI05038,Robotics Engineer,46573,USD,46573,SE,FT,China,S,China,100,"AWS, Linux, PyTorch, GCP",PhD,9,Government,2024-03-22,2024-05-09,830,9.9,Predictive Systems -AI05039,AI Architect,203167,EUR,172692,EX,CT,Austria,M,Austria,50,"SQL, PyTorch, Java, Hadoop",Associate,17,Education,2024-09-14,2024-10-09,865,9.6,DeepTech Ventures -AI05040,Data Scientist,177459,CHF,159713,SE,CT,Switzerland,S,Switzerland,50,"Spark, R, Hadoop, Linux, Mathematics",Bachelor,6,Telecommunications,2024-09-15,2024-10-29,740,9.4,Future Systems -AI05041,Machine Learning Engineer,41556,USD,41556,MI,FT,China,S,China,50,"Python, TensorFlow, Azure, Kubernetes",Associate,3,Gaming,2024-01-04,2024-03-05,1652,6.1,Quantum Computing Inc -AI05042,Data Scientist,152796,USD,152796,EX,PT,Sweden,M,Sweden,100,"Linux, Hadoop, Python",Master,10,Automotive,2025-02-17,2025-04-09,2123,8.4,Cognitive Computing -AI05043,Robotics Engineer,70161,JPY,7717710,EN,PT,Japan,L,Japan,0,"Spark, PyTorch, GCP, Scala, Statistics",PhD,0,Manufacturing,2024-01-18,2024-02-05,1333,6.3,DataVision Ltd -AI05044,ML Ops Engineer,66092,CAD,82615,EN,PT,Canada,S,Sweden,100,"SQL, Scala, NLP",PhD,1,Transportation,2024-03-07,2024-03-31,2308,5.6,Future Systems -AI05045,Data Engineer,271475,SGD,352918,EX,FL,Singapore,L,Singapore,0,"Git, Docker, Hadoop",Associate,10,Media,2024-08-25,2024-10-08,1142,7.1,DataVision Ltd -AI05046,AI Architect,71751,JPY,7892610,EN,CT,Japan,L,Japan,0,"Java, MLOps, Git, Computer Vision, Kubernetes",Associate,1,Real Estate,2024-08-08,2024-09-24,1649,8.1,DeepTech Ventures -AI05047,Research Scientist,91975,USD,91975,EX,PT,China,S,China,0,"Azure, Docker, Mathematics, Statistics, GCP",Bachelor,10,Technology,2024-03-28,2024-05-08,735,8.1,Autonomous Tech -AI05048,Machine Learning Researcher,139317,EUR,118419,SE,FL,France,M,France,100,"Python, Kubernetes, Data Visualization",Bachelor,9,Consulting,2024-09-02,2024-10-04,2142,7.9,Future Systems -AI05049,Machine Learning Researcher,56279,EUR,47837,EN,CT,Netherlands,S,Indonesia,0,"Docker, Python, Data Visualization, Deep Learning",Bachelor,1,Technology,2024-05-07,2024-07-06,2433,7.6,Cloud AI Solutions -AI05050,Head of AI,212031,AUD,286242,EX,PT,Australia,M,Australia,100,"AWS, Statistics, Git, SQL",Associate,15,Gaming,2025-03-10,2025-04-16,1142,7.9,Autonomous Tech -AI05051,AI Research Scientist,261631,AUD,353202,EX,FT,Australia,L,New Zealand,50,"Computer Vision, NLP, GCP",Associate,10,Technology,2024-07-31,2024-08-18,982,6.6,Cognitive Computing -AI05052,Machine Learning Researcher,41755,USD,41755,MI,FL,China,M,China,100,"NLP, SQL, TensorFlow, Linux, Computer Vision",Associate,4,Gaming,2024-10-21,2024-11-30,1171,7.6,Advanced Robotics -AI05053,Computer Vision Engineer,78608,EUR,66817,EN,PT,Netherlands,M,Malaysia,50,"Data Visualization, Scala, Java, Computer Vision, Tableau",PhD,0,Energy,2025-01-20,2025-03-10,642,9.9,Digital Transformation LLC -AI05054,Head of AI,37889,USD,37889,SE,FT,India,M,India,100,"Scala, Deep Learning, MLOps, Python",Associate,8,Retail,2024-02-19,2024-04-03,856,8.9,DataVision Ltd -AI05055,Data Scientist,97397,USD,97397,EN,CT,United States,L,Brazil,50,"Git, Deep Learning, TensorFlow",PhD,1,Finance,2025-04-02,2025-05-05,1562,9.5,Cognitive Computing -AI05056,Data Analyst,265023,USD,265023,EX,CT,Denmark,S,Spain,50,"Git, Docker, Statistics",Master,16,Manufacturing,2024-12-15,2025-01-12,1294,7.7,DataVision Ltd -AI05057,Machine Learning Researcher,143323,AUD,193486,SE,FL,Australia,M,Australia,0,"Tableau, Java, Git",Bachelor,5,Energy,2024-10-31,2025-01-06,729,7,Machine Intelligence Group -AI05058,Head of AI,97000,EUR,82450,SE,CT,France,M,France,0,"Java, SQL, Python, Docker",Associate,5,Technology,2024-01-10,2024-02-03,2147,6.5,Neural Networks Co -AI05059,AI Software Engineer,46374,USD,46374,EN,CT,Ireland,S,United States,100,"PyTorch, Kubernetes, Docker",Bachelor,1,Telecommunications,2024-07-03,2024-09-10,2065,8.9,Smart Analytics -AI05060,AI Architect,229381,EUR,194974,EX,CT,France,M,France,50,"Python, TensorFlow, Scala",PhD,19,Technology,2024-10-01,2024-10-23,1365,9,Digital Transformation LLC -AI05061,Computer Vision Engineer,158873,JPY,17476030,SE,FL,Japan,M,Japan,50,"GCP, Java, Azure",Bachelor,6,Education,2024-06-07,2024-07-04,2166,9.1,Future Systems -AI05062,Machine Learning Engineer,69868,USD,69868,EN,PT,Norway,M,India,50,"Kubernetes, AWS, GCP",Associate,0,Education,2024-02-23,2024-03-26,1959,7.7,DeepTech Ventures -AI05063,AI Specialist,101000,CHF,90900,EN,PT,Switzerland,S,Switzerland,0,"PyTorch, TensorFlow, Python, Git",Bachelor,0,Consulting,2024-12-31,2025-02-13,2181,5.7,Digital Transformation LLC -AI05064,Data Engineer,81849,SGD,106404,EN,CT,Singapore,M,Singapore,100,"NLP, PyTorch, Statistics, Hadoop",PhD,1,Automotive,2024-07-21,2024-09-24,1881,7.7,Smart Analytics -AI05065,AI Architect,134380,GBP,100785,SE,CT,United Kingdom,L,United Kingdom,100,"Git, Azure, Statistics, NLP",PhD,5,Telecommunications,2025-03-04,2025-04-12,2293,5.6,TechCorp Inc -AI05066,Data Scientist,167829,CHF,151046,SE,PT,Switzerland,M,Switzerland,50,"Hadoop, PyTorch, Git, Data Visualization, Docker",Master,7,Government,2024-06-17,2024-08-09,1514,6.7,AI Innovations -AI05067,Machine Learning Engineer,24678,USD,24678,EN,PT,China,S,China,0,"Python, SQL, PyTorch",Master,0,Healthcare,2024-03-22,2024-04-05,1955,9,Predictive Systems -AI05068,Autonomous Systems Engineer,54248,SGD,70522,EN,CT,Singapore,S,Singapore,50,"Scala, Docker, MLOps, AWS, SQL",Bachelor,0,Technology,2024-10-14,2024-12-06,1096,5.5,DeepTech Ventures -AI05069,Head of AI,99288,EUR,84395,SE,CT,Austria,S,Austria,100,"Kubernetes, Spark, AWS",PhD,6,Healthcare,2024-04-04,2024-05-22,2422,7.6,Machine Intelligence Group -AI05070,AI Product Manager,189688,USD,189688,EX,FL,United States,S,United States,100,"Scala, TensorFlow, Mathematics, NLP, Linux",Master,11,Consulting,2024-06-01,2024-06-27,1807,9.8,Smart Analytics -AI05071,Machine Learning Engineer,89528,JPY,9848080,MI,CT,Japan,M,Russia,50,"SQL, Python, Tableau, Java, Docker",Bachelor,3,Government,2024-05-19,2024-06-26,1088,5.4,Advanced Robotics -AI05072,AI Consultant,88720,USD,88720,MI,FT,United States,S,United States,0,"Statistics, Python, TensorFlow, PyTorch, Hadoop",PhD,3,Finance,2025-04-27,2025-07-03,2198,5.6,Algorithmic Solutions -AI05073,NLP Engineer,72059,USD,72059,EN,FT,Sweden,S,Sweden,50,"Git, Scala, Tableau, Computer Vision",Associate,0,Technology,2024-04-26,2024-05-15,2043,8,Predictive Systems -AI05074,Machine Learning Researcher,50803,EUR,43183,EN,PT,France,S,France,0,"TensorFlow, Git, Statistics, SQL",Master,0,Finance,2024-02-18,2024-04-15,1539,9.3,Cloud AI Solutions -AI05075,AI Consultant,24223,USD,24223,EN,FL,India,S,India,100,"Statistics, Hadoop, MLOps, Azure",Associate,1,Gaming,2025-04-03,2025-04-29,2463,8,Cognitive Computing -AI05076,Deep Learning Engineer,121910,USD,121910,MI,FL,Denmark,M,Denmark,100,"Data Visualization, PyTorch, Spark, TensorFlow, SQL",PhD,2,Retail,2025-03-05,2025-05-11,1058,5.9,Machine Intelligence Group -AI05077,Autonomous Systems Engineer,27869,USD,27869,MI,FT,India,M,India,100,"NLP, Docker, Python, Azure",Bachelor,2,Retail,2024-12-03,2025-01-15,1498,9.5,Advanced Robotics -AI05078,Data Scientist,79781,USD,79781,SE,FL,China,L,China,100,"PyTorch, NLP, Data Visualization",PhD,7,Government,2024-05-27,2024-07-28,1915,7.4,Smart Analytics -AI05079,Computer Vision Engineer,94380,CAD,117975,MI,PT,Canada,L,Canada,100,"Git, Hadoop, Python",Master,3,Government,2024-11-23,2025-01-23,943,6.6,Neural Networks Co -AI05080,Deep Learning Engineer,57159,GBP,42869,EN,FL,United Kingdom,S,Netherlands,50,"R, Azure, Tableau, NLP, Linux",Master,1,Healthcare,2024-01-08,2024-02-25,766,6.6,Cloud AI Solutions -AI05081,AI Software Engineer,70183,USD,70183,EX,FT,China,S,China,100,"Statistics, NLP, TensorFlow, Git",Associate,18,Technology,2025-02-20,2025-04-14,1019,7.4,Predictive Systems -AI05082,AI Research Scientist,63741,USD,63741,EN,PT,Finland,L,Finland,0,"Java, Python, Hadoop",Bachelor,1,Healthcare,2024-01-27,2024-02-10,2032,6.1,AI Innovations -AI05083,AI Product Manager,125484,AUD,169403,SE,FT,Australia,L,Australia,100,"PyTorch, TensorFlow, NLP, Git, Spark",Master,6,Gaming,2024-11-29,2024-12-26,1576,8.1,TechCorp Inc -AI05084,Head of AI,165739,JPY,18231290,SE,FT,Japan,L,Japan,50,"R, Python, NLP, TensorFlow",Bachelor,5,Energy,2024-12-09,2025-02-16,2291,9.6,Digital Transformation LLC -AI05085,ML Ops Engineer,70983,EUR,60336,EN,PT,Austria,M,Austria,100,"Deep Learning, Python, MLOps, Java, TensorFlow",Associate,0,Finance,2024-04-05,2024-04-26,1418,5.4,Predictive Systems -AI05086,AI Specialist,110016,GBP,82512,MI,PT,United Kingdom,L,United Kingdom,0,"Python, Hadoop, TensorFlow",PhD,4,Real Estate,2025-04-30,2025-05-28,2127,8.4,Algorithmic Solutions -AI05087,Data Engineer,123436,CHF,111092,EN,PT,Switzerland,L,Switzerland,100,"Kubernetes, Java, Statistics, NLP, Docker",PhD,0,Technology,2025-02-26,2025-04-15,1329,9.2,Smart Analytics -AI05088,Deep Learning Engineer,81729,USD,81729,MI,CT,Ireland,M,Thailand,100,"Java, Azure, NLP, SQL, AWS",Associate,3,Technology,2024-03-06,2024-04-25,552,6.2,Machine Intelligence Group -AI05089,Principal Data Scientist,24353,USD,24353,EN,FT,China,S,China,100,"R, SQL, NLP",Bachelor,1,Finance,2024-02-16,2024-04-27,1050,8.8,DeepTech Ventures -AI05090,AI Consultant,48696,USD,48696,EN,CT,South Korea,L,Mexico,50,"Hadoop, Tableau, Spark, MLOps",PhD,1,Consulting,2025-02-26,2025-03-24,1665,7.6,Cloud AI Solutions -AI05091,AI Software Engineer,114364,CHF,102928,EN,PT,Switzerland,L,South Africa,100,"MLOps, PyTorch, NLP, Mathematics",PhD,0,Telecommunications,2024-01-11,2024-03-15,1731,8.4,Advanced Robotics -AI05092,AI Architect,93835,USD,93835,EN,CT,United States,M,Argentina,50,"Docker, MLOps, Git",Bachelor,1,Real Estate,2025-02-05,2025-03-06,1431,6.9,Autonomous Tech -AI05093,AI Architect,170109,USD,170109,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Computer Vision, Tableau, Python, Azure",Associate,8,Consulting,2025-03-14,2025-05-21,1430,8.9,Predictive Systems -AI05094,Principal Data Scientist,89443,JPY,9838730,EN,FT,Japan,L,Romania,0,"Git, AWS, R",PhD,0,Automotive,2025-02-09,2025-02-27,2366,7,Future Systems -AI05095,AI Specialist,252682,CHF,227414,EX,CT,Switzerland,L,Switzerland,50,"Git, SQL, GCP",Bachelor,12,Education,2025-03-28,2025-05-30,969,8.2,Machine Intelligence Group -AI05096,Machine Learning Engineer,133737,JPY,14711070,SE,CT,Japan,M,Japan,0,"Azure, GCP, Spark, MLOps, AWS",PhD,9,Retail,2024-12-23,2025-02-22,1774,6.6,Cognitive Computing -AI05097,NLP Engineer,73390,USD,73390,EN,CT,Israel,L,Brazil,0,"SQL, TensorFlow, Tableau, AWS",PhD,1,Consulting,2024-01-10,2024-03-08,2396,6.3,Algorithmic Solutions -AI05098,Deep Learning Engineer,215737,EUR,183376,EX,FT,Germany,M,Ghana,100,"Computer Vision, PyTorch, Python, AWS",Associate,13,Telecommunications,2024-07-14,2024-08-14,670,6.4,Machine Intelligence Group -AI05099,Data Analyst,154884,CHF,139396,MI,FL,Switzerland,L,Switzerland,100,"Scala, Java, AWS, PyTorch",PhD,3,Technology,2024-05-18,2024-06-26,1197,7.6,Autonomous Tech -AI05100,AI Specialist,63606,EUR,54065,MI,FT,France,S,India,0,"Scala, Spark, Git, Computer Vision",Associate,2,Media,2024-08-18,2024-09-29,1449,5.6,Machine Intelligence Group -AI05101,AI Software Engineer,26739,USD,26739,MI,FL,India,S,India,50,"Python, SQL, Linux",PhD,2,Automotive,2024-09-10,2024-10-28,2446,5.6,Smart Analytics -AI05102,AI Research Scientist,38550,USD,38550,SE,PT,India,S,Argentina,50,"Kubernetes, TensorFlow, Git",Master,7,Energy,2024-07-13,2024-09-09,503,9.6,Advanced Robotics -AI05103,Machine Learning Engineer,74739,USD,74739,MI,FT,South Korea,M,South Korea,0,"AWS, Computer Vision, R",PhD,3,Retail,2024-06-21,2024-08-02,1362,7.5,Digital Transformation LLC -AI05104,AI Architect,160816,CHF,144734,MI,FT,Switzerland,L,Switzerland,50,"Scala, Java, AWS, Computer Vision",PhD,3,Technology,2024-01-11,2024-02-23,1597,8.3,DeepTech Ventures -AI05105,Research Scientist,73482,USD,73482,EN,PT,United States,S,Colombia,100,"Computer Vision, Tableau, TensorFlow, GCP",PhD,0,Government,2024-05-17,2024-06-29,1698,8.2,Smart Analytics -AI05106,Deep Learning Engineer,53504,USD,53504,EN,PT,Finland,S,Finland,100,"Data Visualization, Azure, Tableau, Docker, PyTorch",PhD,1,Manufacturing,2025-03-01,2025-04-05,1171,6.5,Cognitive Computing -AI05107,AI Architect,58640,EUR,49844,EN,FL,Germany,S,Malaysia,50,"Mathematics, Linux, PyTorch",Associate,1,Manufacturing,2025-03-03,2025-04-21,2294,9.3,Advanced Robotics -AI05108,Principal Data Scientist,110169,EUR,93644,SE,CT,France,S,Switzerland,100,"Java, SQL, Mathematics, MLOps, Deep Learning",Bachelor,5,Energy,2024-04-23,2024-06-28,2276,6.2,Cloud AI Solutions -AI05109,Data Engineer,61539,EUR,52308,EN,FT,Netherlands,S,Netherlands,50,"PyTorch, Docker, Tableau, Mathematics, Azure",Master,0,Gaming,2024-12-15,2025-02-10,972,5.9,Advanced Robotics -AI05110,AI Product Manager,33132,USD,33132,EN,FT,China,M,China,0,"Deep Learning, TensorFlow, Linux, MLOps, Python",Master,0,Finance,2024-02-07,2024-04-04,1289,6,Smart Analytics -AI05111,NLP Engineer,50597,USD,50597,EN,FT,Ireland,S,Ireland,100,"Tableau, GCP, Git, MLOps, Java",Master,0,Healthcare,2025-02-25,2025-04-05,1056,8,Smart Analytics -AI05112,AI Product Manager,138723,SGD,180340,SE,CT,Singapore,S,Norway,0,"Spark, PyTorch, Mathematics",Associate,7,Technology,2025-04-16,2025-05-18,1946,5.5,Predictive Systems -AI05113,ML Ops Engineer,96580,USD,96580,EX,PT,China,L,China,50,"Computer Vision, GCP, Hadoop",Associate,17,Real Estate,2025-03-14,2025-05-13,608,5.5,DataVision Ltd -AI05114,Principal Data Scientist,75245,GBP,56434,EN,FL,United Kingdom,M,United Kingdom,100,"Deep Learning, Python, Linux, Kubernetes",Master,0,Finance,2025-02-21,2025-04-07,579,6.3,Cognitive Computing -AI05115,AI Research Scientist,100596,USD,100596,EN,FL,Denmark,L,Switzerland,100,"PyTorch, Java, MLOps",Bachelor,0,Real Estate,2025-02-17,2025-03-26,1945,7.3,DeepTech Ventures -AI05116,Principal Data Scientist,82608,USD,82608,EN,FT,Sweden,L,Sweden,50,"Data Visualization, Docker, Mathematics",Master,0,Healthcare,2024-01-14,2024-02-28,2416,7.5,DataVision Ltd -AI05117,Principal Data Scientist,86868,EUR,73838,MI,PT,Austria,M,Estonia,50,"Python, Deep Learning, Kubernetes, Statistics, Hadoop",PhD,3,Transportation,2024-06-12,2024-07-13,1798,8.4,Smart Analytics -AI05118,Data Engineer,92090,USD,92090,EN,FT,Denmark,M,Denmark,0,"Data Visualization, AWS, Azure",Associate,0,Gaming,2025-02-20,2025-04-19,2090,6.2,DataVision Ltd -AI05119,AI Research Scientist,125783,USD,125783,MI,PT,Denmark,M,Denmark,50,"Spark, TensorFlow, Deep Learning, Tableau",Master,2,Retail,2024-02-14,2024-04-27,2313,8.6,TechCorp Inc -AI05120,Machine Learning Researcher,168390,SGD,218907,EX,FT,Singapore,S,Singapore,50,"TensorFlow, NLP, Git, GCP, Spark",Master,18,Telecommunications,2024-06-25,2024-07-11,635,5.4,Future Systems -AI05121,AI Product Manager,193710,CHF,174339,SE,FT,Switzerland,L,Turkey,0,"Python, Kubernetes, Data Visualization",Bachelor,8,Finance,2024-09-20,2024-10-14,696,5.2,Neural Networks Co -AI05122,Robotics Engineer,86414,USD,86414,MI,CT,Ireland,S,Thailand,50,"Python, Linux, Data Visualization, Deep Learning",PhD,4,Energy,2024-09-09,2024-10-10,644,6.2,AI Innovations -AI05123,AI Software Engineer,136589,CAD,170736,SE,FT,Canada,M,Canada,100,"Java, Scala, MLOps, Statistics",Bachelor,8,Energy,2024-02-18,2024-04-17,2280,6.5,Neural Networks Co -AI05124,Research Scientist,116556,AUD,157351,MI,PT,Australia,L,Australia,0,"Hadoop, AWS, Java, Computer Vision",Bachelor,4,Government,2024-12-10,2025-01-17,1582,8.8,Advanced Robotics -AI05125,AI Research Scientist,147616,EUR,125474,SE,FT,France,L,France,50,"Git, Azure, MLOps, Python",Master,9,Telecommunications,2025-01-16,2025-03-05,1224,6.1,AI Innovations -AI05126,ML Ops Engineer,167103,JPY,18381330,EX,CT,Japan,L,Colombia,100,"PyTorch, Git, NLP",Master,19,Manufacturing,2024-01-10,2024-02-24,918,6.5,Digital Transformation LLC -AI05127,Research Scientist,187756,USD,187756,EX,PT,Norway,M,Norway,0,"Scala, SQL, MLOps, Kubernetes",PhD,13,Government,2025-03-21,2025-04-30,635,9.7,Neural Networks Co -AI05128,ML Ops Engineer,25560,USD,25560,EN,FL,India,S,India,0,"Git, Java, Hadoop, AWS",Bachelor,0,Finance,2024-12-17,2025-02-09,1801,9.3,Predictive Systems -AI05129,Data Analyst,64206,USD,64206,MI,CT,South Korea,S,South Korea,100,"SQL, R, Scala",Bachelor,3,Media,2024-10-15,2024-12-14,1941,9.9,Digital Transformation LLC -AI05130,AI Architect,118221,EUR,100488,MI,PT,Germany,L,Germany,100,"Statistics, GCP, Mathematics, R, NLP",Master,4,Consulting,2024-12-08,2025-01-22,2017,5.7,Digital Transformation LLC -AI05131,Data Analyst,104839,JPY,11532290,MI,CT,Japan,M,Japan,100,"Java, Linux, Data Visualization, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-25,1810,5.9,Autonomous Tech -AI05132,AI Architect,86714,USD,86714,MI,CT,South Korea,L,South Korea,0,"GCP, Linux, Hadoop, TensorFlow, Data Visualization",Master,2,Education,2024-10-25,2024-11-20,1338,6.7,Cloud AI Solutions -AI05133,AI Research Scientist,110353,USD,110353,MI,CT,Norway,S,Norway,50,"PyTorch, AWS, SQL, R, MLOps",Bachelor,4,Retail,2025-04-25,2025-06-10,877,9.9,Predictive Systems -AI05134,Machine Learning Researcher,61142,USD,61142,EN,PT,Finland,M,Germany,50,"Mathematics, Linux, R, Java",Bachelor,1,Consulting,2024-10-04,2024-10-29,933,7.5,DataVision Ltd -AI05135,ML Ops Engineer,155690,USD,155690,SE,CT,Norway,L,Ukraine,0,"R, Git, Data Visualization, Python, Spark",Bachelor,6,Education,2025-01-20,2025-02-16,619,6.5,AI Innovations -AI05136,Research Scientist,117303,USD,117303,EX,FL,China,L,China,0,"Python, Git, Azure, Deep Learning, TensorFlow",Master,17,Energy,2024-06-16,2024-08-14,1415,6.9,Quantum Computing Inc -AI05137,Data Scientist,55265,CAD,69081,EN,CT,Canada,M,Canada,100,"Java, Kubernetes, NLP, Spark",Master,1,Automotive,2024-12-12,2024-12-27,1241,9.6,Algorithmic Solutions -AI05138,Data Analyst,76310,USD,76310,EX,CT,India,L,India,100,"Git, Python, MLOps",Master,19,Telecommunications,2024-11-17,2024-12-27,786,8.4,Cloud AI Solutions -AI05139,Autonomous Systems Engineer,93083,SGD,121008,EN,FT,Singapore,L,Egypt,50,"Azure, AWS, Deep Learning, Git",Master,1,Technology,2024-08-06,2024-09-28,2421,6.5,Machine Intelligence Group -AI05140,Research Scientist,133350,USD,133350,SE,CT,Norway,S,Norway,100,"Computer Vision, Docker, PyTorch",PhD,7,Transportation,2025-02-25,2025-03-26,1457,8.7,Machine Intelligence Group -AI05141,Computer Vision Engineer,86337,USD,86337,MI,CT,Finland,S,United Kingdom,0,"Hadoop, SQL, Data Visualization, PyTorch",Master,2,Telecommunications,2025-01-18,2025-02-18,1291,8.2,DataVision Ltd -AI05142,Data Scientist,86313,USD,86313,MI,CT,Ireland,M,Ireland,100,"Data Visualization, R, GCP, Python, Computer Vision",PhD,2,Retail,2024-05-12,2024-06-19,2120,7.6,Neural Networks Co -AI05143,ML Ops Engineer,57198,USD,57198,SE,CT,China,M,China,0,"Mathematics, Scala, Kubernetes",PhD,7,Education,2024-05-14,2024-06-21,2017,5.4,DataVision Ltd -AI05144,AI Software Engineer,60582,JPY,6664020,EN,FT,Japan,S,Japan,0,"NLP, Deep Learning, Azure, Python",PhD,1,Education,2024-07-16,2024-08-21,1597,9.4,Advanced Robotics -AI05145,Head of AI,55380,EUR,47073,EN,CT,Austria,M,Austria,0,"Git, GCP, AWS, Mathematics",Bachelor,0,Gaming,2025-03-10,2025-03-26,1708,6.8,DeepTech Ventures -AI05146,AI Research Scientist,48341,USD,48341,SE,FL,India,M,India,0,"Kubernetes, GCP, MLOps, Docker",Associate,7,Technology,2024-06-11,2024-07-23,1819,7.5,AI Innovations -AI05147,AI Product Manager,251565,USD,251565,EX,FT,Norway,L,Norway,50,"GCP, Python, Statistics",Master,17,Healthcare,2024-05-10,2024-06-28,1282,8,Advanced Robotics -AI05148,Machine Learning Researcher,236217,CHF,212595,EX,PT,Switzerland,S,Switzerland,50,"Tableau, Kubernetes, AWS, Mathematics, Scala",Bachelor,13,Education,2025-04-16,2025-06-03,1026,9.3,Digital Transformation LLC -AI05149,Autonomous Systems Engineer,91231,USD,91231,SE,CT,South Korea,M,Colombia,100,"Spark, Scala, MLOps",Master,6,Healthcare,2024-02-04,2024-03-04,1711,7,Neural Networks Co -AI05150,Machine Learning Researcher,61130,USD,61130,EN,FL,Israel,S,Nigeria,0,"SQL, MLOps, Computer Vision, Python, GCP",Bachelor,0,Manufacturing,2024-11-24,2025-01-10,1637,9,AI Innovations -AI05151,Computer Vision Engineer,62398,CAD,77998,EN,CT,Canada,L,Canada,50,"Data Visualization, Linux, Spark",Master,1,Healthcare,2024-06-03,2024-07-05,1982,9.2,AI Innovations -AI05152,Research Scientist,176242,EUR,149806,EX,FL,France,M,South Africa,50,"Python, Hadoop, GCP",Bachelor,14,Education,2025-02-04,2025-04-05,1846,8.2,Neural Networks Co -AI05153,Data Analyst,153418,EUR,130405,EX,FL,France,M,France,100,"MLOps, R, Scala",Bachelor,13,Government,2025-03-26,2025-04-15,844,7.6,DeepTech Ventures -AI05154,Data Scientist,81657,CAD,102071,MI,CT,Canada,S,New Zealand,50,"Scala, Git, Python",Master,2,Energy,2024-08-31,2024-10-12,2064,6.7,Algorithmic Solutions -AI05155,Data Analyst,69844,USD,69844,EN,PT,Israel,L,Israel,100,"Java, SQL, PyTorch, Computer Vision, Hadoop",Bachelor,0,Technology,2025-04-16,2025-05-16,910,7.3,TechCorp Inc -AI05156,AI Consultant,91682,EUR,77930,MI,FT,Netherlands,M,Netherlands,50,"NLP, Linux, Azure, Deep Learning",Associate,4,Gaming,2024-10-02,2024-11-27,1604,5.1,Smart Analytics -AI05157,Computer Vision Engineer,69595,AUD,93953,MI,FT,Australia,S,Russia,50,"PyTorch, TensorFlow, Tableau, AWS, Hadoop",Bachelor,3,Transportation,2024-03-19,2024-04-14,774,8.7,Predictive Systems -AI05158,AI Software Engineer,101742,USD,101742,EN,CT,Norway,L,Spain,100,"Linux, SQL, Tableau, Java",Bachelor,0,Retail,2024-10-03,2024-11-20,1067,9.2,Algorithmic Solutions -AI05159,Head of AI,97961,USD,97961,MI,PT,Israel,L,Israel,0,"AWS, Azure, Git, Mathematics",PhD,4,Education,2024-02-14,2024-04-01,1688,8.1,Future Systems -AI05160,AI Consultant,106022,JPY,11662420,MI,FT,Japan,M,Romania,100,"R, SQL, Data Visualization",Master,3,Energy,2024-08-11,2024-09-29,1832,6.4,AI Innovations -AI05161,ML Ops Engineer,46651,USD,46651,MI,PT,China,M,China,50,"Java, Tableau, PyTorch, Computer Vision",Bachelor,2,Telecommunications,2025-03-15,2025-04-17,807,7.3,Algorithmic Solutions -AI05162,Robotics Engineer,124553,CAD,155691,SE,PT,Canada,L,Canada,0,"Mathematics, Linux, Python, Deep Learning, Kubernetes",PhD,9,Manufacturing,2024-06-03,2024-07-31,922,9.8,DeepTech Ventures -AI05163,ML Ops Engineer,104780,EUR,89063,SE,PT,Austria,S,Austria,100,"Git, Python, Spark",Bachelor,8,Education,2024-07-02,2024-09-06,926,6.4,Autonomous Tech -AI05164,AI Specialist,114730,AUD,154886,SE,CT,Australia,S,Brazil,100,"SQL, R, PyTorch",Master,5,Retail,2024-05-13,2024-06-27,787,6.3,Machine Intelligence Group -AI05165,Research Scientist,162856,EUR,138428,SE,CT,France,L,France,0,"Git, Spark, Kubernetes, Statistics, Azure",Bachelor,5,Telecommunications,2024-10-14,2024-11-15,635,9.7,TechCorp Inc -AI05166,Robotics Engineer,125641,USD,125641,SE,FL,Sweden,S,Vietnam,100,"PyTorch, Computer Vision, AWS, SQL, MLOps",Associate,5,Education,2024-11-09,2025-01-20,1422,8,Cognitive Computing -AI05167,Machine Learning Engineer,89881,CHF,80893,EN,CT,Switzerland,L,Australia,0,"Data Visualization, TensorFlow, Azure",Bachelor,1,Telecommunications,2024-12-14,2025-01-22,993,5.3,TechCorp Inc -AI05168,AI Consultant,289064,USD,289064,EX,FL,United States,L,United States,50,"R, SQL, Tableau, MLOps, Docker",Master,17,Education,2024-04-04,2024-05-13,581,6.2,Machine Intelligence Group -AI05169,AI Specialist,226888,USD,226888,EX,FT,Sweden,S,Denmark,0,"Java, SQL, Data Visualization, PyTorch, Computer Vision",Master,13,Technology,2024-09-15,2024-10-27,2487,8.4,Cloud AI Solutions -AI05170,Principal Data Scientist,153723,EUR,130665,EX,CT,Netherlands,M,Netherlands,50,"Statistics, Spark, Python",Associate,13,Retail,2024-12-28,2025-03-05,1731,8.8,DeepTech Ventures -AI05171,AI Research Scientist,220723,SGD,286940,EX,FT,Singapore,S,Canada,50,"Mathematics, Python, Tableau",Associate,13,Media,2024-02-29,2024-04-19,1833,8,Future Systems -AI05172,Data Analyst,93378,EUR,79371,MI,FT,France,L,South Africa,100,"Spark, GCP, Scala, Computer Vision, Deep Learning",Master,3,Gaming,2024-08-06,2024-08-21,1938,6,TechCorp Inc -AI05173,ML Ops Engineer,162034,GBP,121526,SE,FT,United Kingdom,L,United Kingdom,50,"SQL, TensorFlow, Data Visualization",PhD,5,Media,2024-07-28,2024-08-30,1441,10,Cloud AI Solutions -AI05174,Head of AI,117365,USD,117365,SE,PT,Ireland,S,Ireland,100,"Statistics, Data Visualization, Git",Bachelor,5,Retail,2024-07-25,2024-09-04,1472,7.2,Autonomous Tech -AI05175,Machine Learning Engineer,128624,USD,128624,MI,PT,Denmark,M,Denmark,50,"GCP, Java, Azure, Linux",Master,2,Consulting,2025-04-15,2025-05-24,527,8.9,Quantum Computing Inc -AI05176,Head of AI,112504,EUR,95628,SE,PT,France,M,Austria,50,"Deep Learning, Docker, Computer Vision, Azure, Kubernetes",Bachelor,9,Education,2024-02-16,2024-03-28,1791,5.2,Digital Transformation LLC -AI05177,Data Analyst,91750,USD,91750,MI,CT,Norway,S,Norway,0,"Mathematics, TensorFlow, Computer Vision",Master,4,Transportation,2025-02-08,2025-03-09,1374,10,Neural Networks Co -AI05178,Machine Learning Engineer,216192,USD,216192,EX,FT,South Korea,L,South Korea,100,"Hadoop, Spark, NLP, Computer Vision",Bachelor,15,Gaming,2024-03-03,2024-04-12,508,6.2,Advanced Robotics -AI05179,Principal Data Scientist,102086,USD,102086,SE,FT,Israel,S,Israel,50,"Scala, Java, Azure, Data Visualization, TensorFlow",Associate,5,Finance,2024-04-21,2024-06-10,1342,6.2,Machine Intelligence Group -AI05180,Machine Learning Engineer,150372,USD,150372,SE,PT,Israel,L,Israel,0,"Scala, R, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-08-12,2306,7,Algorithmic Solutions -AI05181,Data Analyst,132314,USD,132314,MI,FT,Norway,L,Turkey,100,"PyTorch, Scala, GCP, Mathematics",Bachelor,4,Automotive,2024-09-21,2024-10-14,1172,9.6,Cloud AI Solutions -AI05182,Data Analyst,103230,USD,103230,MI,PT,Sweden,M,Sweden,100,"Java, Scala, Kubernetes, NLP",Bachelor,2,Telecommunications,2024-03-27,2024-05-22,1418,9.9,Algorithmic Solutions -AI05183,AI Architect,120695,CAD,150869,SE,FL,Canada,L,Hungary,50,"GCP, NLP, Azure",Associate,8,Government,2024-08-16,2024-09-30,1328,5.8,Advanced Robotics -AI05184,Machine Learning Engineer,182121,USD,182121,EX,FT,Ireland,M,Austria,100,"Data Visualization, PyTorch, TensorFlow",Associate,19,Energy,2025-04-22,2025-05-07,2017,8.9,Neural Networks Co -AI05185,AI Architect,73616,CHF,66254,EN,PT,Switzerland,S,Argentina,100,"PyTorch, TensorFlow, Docker, Hadoop, Mathematics",PhD,0,Automotive,2024-03-06,2024-04-03,1044,9,Future Systems -AI05186,NLP Engineer,80112,USD,80112,EN,FT,Sweden,M,Denmark,50,"SQL, Python, Scala",Master,0,Telecommunications,2024-01-01,2024-02-06,2050,9.3,Algorithmic Solutions -AI05187,Data Scientist,95409,GBP,71557,MI,FL,United Kingdom,S,United Kingdom,100,"SQL, GCP, Computer Vision",Master,2,Automotive,2024-09-26,2024-11-25,1359,7.1,Predictive Systems -AI05188,NLP Engineer,120427,USD,120427,SE,FT,Israel,L,Israel,100,"Kubernetes, Spark, Java, TensorFlow, Statistics",Bachelor,5,Government,2024-08-12,2024-09-08,2168,9.9,Future Systems -AI05189,AI Research Scientist,38463,USD,38463,SE,CT,India,M,India,0,"Docker, Tableau, Java",Master,6,Gaming,2024-03-06,2024-05-09,2482,9.3,Algorithmic Solutions -AI05190,AI Software Engineer,38200,USD,38200,MI,FT,India,L,India,100,"PyTorch, Tableau, GCP",Bachelor,2,Media,2024-10-24,2024-12-03,1106,5.2,Smart Analytics -AI05191,Head of AI,74370,USD,74370,EN,CT,Ireland,M,Ireland,100,"Python, AWS, MLOps",Bachelor,0,Education,2025-01-10,2025-02-27,2007,9.1,Quantum Computing Inc -AI05192,AI Software Engineer,96885,EUR,82352,MI,FL,Germany,M,Germany,0,"R, Deep Learning, SQL, Statistics",Associate,3,Media,2024-01-17,2024-02-26,2017,5.8,Quantum Computing Inc -AI05193,AI Specialist,23564,USD,23564,EN,FL,India,M,Australia,0,"Linux, Python, Tableau, Hadoop",PhD,1,Healthcare,2025-04-19,2025-05-17,514,6.8,Neural Networks Co -AI05194,Machine Learning Engineer,135679,EUR,115327,SE,FL,Austria,M,Austria,50,"Python, Java, Computer Vision",Master,9,Media,2025-04-27,2025-06-17,1647,9.2,DeepTech Ventures -AI05195,ML Ops Engineer,85715,USD,85715,MI,CT,Finland,L,Ghana,100,"MLOps, Deep Learning, R",Master,2,Energy,2025-02-24,2025-05-03,2049,7.3,Digital Transformation LLC -AI05196,Machine Learning Researcher,127789,CAD,159736,SE,CT,Canada,S,Canada,100,"SQL, Python, NLP, Scala",PhD,6,Healthcare,2024-10-10,2024-12-14,1217,7.2,Algorithmic Solutions -AI05197,Data Engineer,186154,CHF,167539,SE,FT,Switzerland,S,Switzerland,100,"Statistics, Kubernetes, Linux",Bachelor,9,Energy,2025-01-08,2025-02-23,1306,7.4,Smart Analytics -AI05198,Research Scientist,202606,USD,202606,EX,CT,United States,L,United States,50,"Mathematics, TensorFlow, Linux, Docker, R",Master,17,Education,2024-10-15,2024-11-25,898,5.2,Machine Intelligence Group -AI05199,Data Engineer,80486,USD,80486,EX,FL,China,L,China,0,"Python, AWS, GCP, Java",Bachelor,13,Automotive,2024-08-24,2024-10-26,2297,8.4,Cloud AI Solutions -AI05200,Principal Data Scientist,23519,USD,23519,EN,FT,India,S,India,0,"Computer Vision, MLOps, Statistics",Bachelor,0,Real Estate,2024-04-23,2024-06-08,1217,7.9,DeepTech Ventures -AI05201,Head of AI,54022,CAD,67528,EN,CT,Canada,S,Colombia,50,"Spark, Tableau, Deep Learning, Python",Associate,0,Finance,2024-08-25,2024-10-09,1620,5.2,Future Systems -AI05202,Deep Learning Engineer,94661,USD,94661,MI,CT,South Korea,L,South Korea,0,"Spark, Python, Java, Linux",Bachelor,3,Transportation,2024-09-26,2024-10-30,1281,8.3,TechCorp Inc -AI05203,AI Architect,92817,JPY,10209870,EN,FL,Japan,L,Finland,50,"Scala, Git, GCP, Hadoop",Associate,0,Education,2024-01-19,2024-03-08,2205,8.7,Algorithmic Solutions -AI05204,AI Product Manager,183387,SGD,238403,EX,FL,Singapore,S,Singapore,50,"NLP, Tableau, Spark",Associate,14,Transportation,2024-04-28,2024-05-30,1925,5.2,Future Systems -AI05205,Research Scientist,39823,USD,39823,MI,FT,China,S,China,0,"R, Python, Kubernetes, GCP",Bachelor,3,Energy,2024-02-22,2024-04-06,1780,6.6,Quantum Computing Inc -AI05206,Principal Data Scientist,204455,USD,204455,EX,CT,Denmark,S,Denmark,50,"Java, Python, Data Visualization, Kubernetes",Associate,16,Gaming,2025-03-04,2025-03-29,1148,5.5,Autonomous Tech -AI05207,ML Ops Engineer,61232,USD,61232,SE,PT,China,L,Australia,100,"Spark, Azure, Computer Vision",Master,8,Education,2024-09-20,2024-11-17,544,7.3,Autonomous Tech -AI05208,Research Scientist,112367,EUR,95512,SE,FT,France,M,France,100,"Hadoop, Python, Linux, NLP",Bachelor,6,Manufacturing,2024-07-02,2024-08-26,547,6.7,Cognitive Computing -AI05209,Data Analyst,73735,EUR,62675,EN,FL,Germany,L,Germany,0,"Python, PyTorch, Java, Computer Vision",Master,1,Education,2024-06-08,2024-08-04,971,8.9,Autonomous Tech -AI05210,Robotics Engineer,294725,USD,294725,EX,FL,United States,M,United States,0,"Spark, PyTorch, NLP",PhD,11,Healthcare,2024-04-20,2024-05-16,1054,7.2,Autonomous Tech -AI05211,Data Analyst,242630,USD,242630,EX,CT,Denmark,M,Denmark,0,"Kubernetes, Python, Statistics, TensorFlow, Data Visualization",Bachelor,15,Consulting,2024-12-01,2024-12-26,2423,9,Quantum Computing Inc -AI05212,Data Engineer,86849,USD,86849,SE,FT,South Korea,S,South Korea,100,"Scala, Hadoop, Kubernetes, SQL",Associate,6,Education,2024-07-05,2024-08-24,1936,6.7,Cloud AI Solutions -AI05213,AI Specialist,48264,USD,48264,SE,FL,India,M,India,0,"Python, Deep Learning, TensorFlow, Docker",Bachelor,7,Media,2024-11-20,2025-01-24,1965,7.5,AI Innovations -AI05214,ML Ops Engineer,66226,JPY,7284860,EN,PT,Japan,S,Finland,0,"Python, Kubernetes, TensorFlow",Associate,1,Retail,2024-08-17,2024-10-28,584,8.5,Neural Networks Co -AI05215,AI Software Engineer,59484,USD,59484,EX,CT,India,S,France,0,"Linux, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-01-28,2024-02-26,528,6.2,TechCorp Inc -AI05216,AI Software Engineer,75033,GBP,56275,MI,FL,United Kingdom,S,United Kingdom,50,"Git, TensorFlow, Deep Learning",PhD,4,Manufacturing,2025-01-18,2025-02-05,1597,7.4,Cognitive Computing -AI05217,Principal Data Scientist,53070,USD,53070,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Java, GCP, Git",Master,1,Retail,2024-04-02,2024-06-14,2279,5.2,Algorithmic Solutions -AI05218,Autonomous Systems Engineer,80312,USD,80312,MI,PT,Ireland,S,Ireland,0,"Statistics, TensorFlow, Deep Learning, Kubernetes, Mathematics",Master,3,Automotive,2024-03-28,2024-05-26,1395,6.1,DataVision Ltd -AI05219,AI Research Scientist,61589,USD,61589,EN,PT,Finland,S,Finland,100,"Linux, Python, Docker, Deep Learning, MLOps",PhD,0,Education,2025-01-28,2025-04-09,682,7.7,DataVision Ltd -AI05220,Machine Learning Researcher,64464,USD,64464,EN,PT,South Korea,L,South Korea,50,"Kubernetes, Scala, Data Visualization",PhD,1,Retail,2024-02-29,2024-04-22,1904,8.9,Algorithmic Solutions -AI05221,Data Engineer,155127,CHF,139614,MI,PT,Switzerland,M,Switzerland,100,"AWS, Python, MLOps, TensorFlow, PyTorch",PhD,3,Transportation,2024-02-07,2024-03-24,644,6.3,DeepTech Ventures -AI05222,Research Scientist,218691,EUR,185887,EX,CT,Germany,S,Germany,100,"Linux, Statistics, Hadoop, Spark, MLOps",PhD,12,Technology,2024-01-23,2024-03-05,795,6,Future Systems -AI05223,Robotics Engineer,204587,CHF,184128,SE,PT,Switzerland,L,Switzerland,0,"Python, Computer Vision, TensorFlow, Linux",PhD,9,Telecommunications,2024-09-30,2024-10-20,1680,6.9,AI Innovations -AI05224,Robotics Engineer,113415,EUR,96403,SE,PT,Austria,S,Austria,0,"Kubernetes, Scala, Tableau, Mathematics, AWS",PhD,9,Telecommunications,2024-01-18,2024-02-22,2041,8.4,Smart Analytics -AI05225,AI Consultant,111108,USD,111108,SE,FT,South Korea,S,South Korea,0,"Linux, GCP, Mathematics, Computer Vision, MLOps",Associate,5,Automotive,2025-03-08,2025-04-14,2348,8.4,Advanced Robotics -AI05226,AI Product Manager,162371,GBP,121778,EX,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Azure, PyTorch",Associate,13,Consulting,2024-09-01,2024-11-13,2361,9.6,Smart Analytics -AI05227,Data Engineer,78542,USD,78542,EN,PT,Sweden,M,Sweden,100,"R, MLOps, SQL",Master,0,Technology,2024-07-25,2024-08-26,1736,9.6,Autonomous Tech -AI05228,Data Analyst,111272,CHF,100145,MI,CT,Switzerland,M,Italy,0,"R, Spark, Statistics, GCP",Master,2,Finance,2024-07-01,2024-08-04,584,6.6,Machine Intelligence Group -AI05229,Machine Learning Researcher,141413,USD,141413,SE,PT,United States,M,Nigeria,50,"PyTorch, NLP, Scala, GCP, Azure",Associate,9,Government,2025-01-01,2025-03-02,2468,8.9,Autonomous Tech -AI05230,Robotics Engineer,153448,USD,153448,MI,CT,Norway,L,Norway,0,"Scala, Java, MLOps",Associate,4,Telecommunications,2024-02-02,2024-02-24,1035,5.9,Predictive Systems -AI05231,AI Consultant,126522,EUR,107544,SE,CT,Austria,L,Austria,0,"Python, AWS, Data Visualization, Docker, Computer Vision",Bachelor,9,Government,2024-06-13,2024-08-08,1749,9.2,Autonomous Tech -AI05232,Data Analyst,75216,USD,75216,MI,PT,Finland,S,India,0,"Kubernetes, SQL, Scala, GCP, TensorFlow",Bachelor,2,Government,2025-03-04,2025-04-29,979,7,TechCorp Inc -AI05233,Data Analyst,157426,JPY,17316860,EX,FT,Japan,M,Ghana,0,"Deep Learning, Azure, Spark",Bachelor,19,Education,2024-05-10,2024-05-30,1193,5,TechCorp Inc -AI05234,Research Scientist,78696,USD,78696,EN,PT,United States,S,Sweden,0,"Azure, R, Git",Bachelor,1,Government,2024-10-04,2024-12-15,898,6.6,Digital Transformation LLC -AI05235,Robotics Engineer,113402,USD,113402,EX,CT,China,M,China,0,"SQL, Python, Git",Associate,18,Gaming,2025-03-27,2025-05-27,2353,6.1,Machine Intelligence Group -AI05236,Machine Learning Researcher,86790,CHF,78111,EN,CT,Switzerland,M,Switzerland,100,"Python, NLP, TensorFlow",Master,1,Real Estate,2024-11-12,2025-01-18,1071,9.3,DeepTech Ventures -AI05237,Machine Learning Researcher,85140,USD,85140,EN,PT,United States,S,Spain,100,"Git, Spark, Java, SQL, GCP",PhD,0,Education,2025-03-29,2025-05-18,2413,9.7,DataVision Ltd -AI05238,Robotics Engineer,80679,EUR,68577,EN,FT,Austria,L,Austria,100,"R, Git, Tableau",Bachelor,1,Telecommunications,2024-06-23,2024-08-14,1374,8.3,Cloud AI Solutions -AI05239,AI Specialist,207222,USD,207222,EX,CT,Ireland,S,Ireland,100,"Spark, GCP, Data Visualization, Kubernetes, Python",PhD,19,Finance,2024-09-07,2024-10-19,1846,5.3,Autonomous Tech -AI05240,Principal Data Scientist,121677,SGD,158180,MI,PT,Singapore,L,Singapore,50,"Python, R, SQL, Linux",Bachelor,3,Education,2024-03-18,2024-05-23,1099,8.9,Cloud AI Solutions -AI05241,AI Research Scientist,190049,USD,190049,EX,PT,Sweden,M,Sweden,100,"Statistics, Mathematics, Tableau",Master,18,Finance,2025-01-29,2025-03-21,1642,8.9,AI Innovations -AI05242,Data Engineer,77584,USD,77584,EN,PT,Norway,S,Malaysia,100,"Python, AWS, MLOps",Master,0,Government,2024-02-08,2024-04-04,2356,6.9,Future Systems -AI05243,AI Software Engineer,120788,USD,120788,EX,FT,Finland,S,Finland,50,"AWS, TensorFlow, Linux",Master,16,Consulting,2024-02-28,2024-05-05,1853,9.4,Autonomous Tech -AI05244,Deep Learning Engineer,46291,USD,46291,SE,CT,India,S,India,0,"Linux, Deep Learning, R",Bachelor,8,Telecommunications,2025-01-17,2025-03-07,1918,9.6,Quantum Computing Inc -AI05245,Computer Vision Engineer,74298,USD,74298,EN,PT,Israel,L,Israel,100,"Python, Computer Vision, TensorFlow, Linux, Statistics",Associate,0,Energy,2024-05-31,2024-07-12,2312,9.2,Cloud AI Solutions -AI05246,Machine Learning Researcher,166410,USD,166410,SE,FL,Denmark,S,Denmark,100,"Computer Vision, GCP, Scala, Statistics",Associate,7,Finance,2025-01-07,2025-03-06,1366,5.5,DeepTech Ventures -AI05247,Data Analyst,30796,USD,30796,EN,FL,China,S,China,0,"PyTorch, Hadoop, TensorFlow, Docker",PhD,0,Manufacturing,2024-09-30,2024-11-23,1747,5.9,Advanced Robotics -AI05248,Machine Learning Researcher,60780,USD,60780,EN,FT,Sweden,S,Sweden,0,"Azure, Tableau, Mathematics, Data Visualization, Python",PhD,1,Real Estate,2024-01-30,2024-03-11,546,7,AI Innovations -AI05249,Data Engineer,59678,USD,59678,EN,CT,South Korea,L,South Korea,0,"Azure, Kubernetes, Spark, Scala",Master,1,Retail,2024-02-03,2024-03-05,644,7.9,Neural Networks Co -AI05250,Principal Data Scientist,253960,USD,253960,EX,PT,Sweden,L,Sweden,100,"Linux, Git, R, SQL",Master,17,Healthcare,2024-10-24,2024-11-30,1172,6.9,DeepTech Ventures -AI05251,AI Specialist,87660,USD,87660,EN,CT,Sweden,L,Sweden,0,"Hadoop, TensorFlow, PyTorch, GCP, Linux",PhD,1,Energy,2024-07-05,2024-08-07,2016,5.3,DeepTech Ventures -AI05252,AI Architect,210655,USD,210655,EX,CT,Sweden,S,Sweden,50,"SQL, Spark, Tableau, AWS, Git",PhD,13,Automotive,2024-11-17,2025-01-18,1041,7.2,Neural Networks Co -AI05253,Principal Data Scientist,144360,USD,144360,SE,FL,Sweden,M,Sweden,50,"Kubernetes, Docker, Java",Master,9,Manufacturing,2024-04-18,2024-05-03,562,6.9,TechCorp Inc -AI05254,Computer Vision Engineer,57145,USD,57145,EN,FL,Israel,M,Austria,50,"Linux, R, SQL, PyTorch, Java",Associate,0,Retail,2024-02-29,2024-03-31,516,8,Cognitive Computing -AI05255,Computer Vision Engineer,196565,USD,196565,EX,FL,Denmark,S,Denmark,0,"Deep Learning, PyTorch, Linux",Associate,18,Government,2024-07-19,2024-09-08,1595,8.9,Cloud AI Solutions -AI05256,Computer Vision Engineer,78696,CHF,70826,EN,FL,Switzerland,S,Kenya,50,"Spark, Azure, Java, TensorFlow, Kubernetes",Bachelor,0,Real Estate,2024-04-13,2024-06-14,842,8.2,Quantum Computing Inc -AI05257,Autonomous Systems Engineer,69517,USD,69517,SE,PT,China,M,Thailand,50,"AWS, R, Tableau, Deep Learning",Bachelor,8,Healthcare,2025-03-26,2025-05-01,1621,9.5,Cognitive Computing -AI05258,Autonomous Systems Engineer,80960,USD,80960,MI,PT,Israel,S,Israel,50,"Kubernetes, Docker, Tableau, Java, NLP",Master,3,Healthcare,2024-12-31,2025-02-18,1893,9.3,Digital Transformation LLC -AI05259,Data Engineer,111422,EUR,94709,MI,CT,Germany,L,Germany,100,"Kubernetes, Docker, Java, R",PhD,2,Manufacturing,2024-06-15,2024-08-19,1824,5.3,DeepTech Ventures -AI05260,Robotics Engineer,112063,USD,112063,SE,CT,Israel,L,Israel,0,"Git, R, Computer Vision",Bachelor,9,Energy,2025-04-19,2025-06-13,1840,8.6,Machine Intelligence Group -AI05261,AI Architect,206889,USD,206889,EX,PT,United States,S,United States,100,"Scala, GCP, NLP, Python, Kubernetes",Bachelor,10,Telecommunications,2024-06-11,2024-08-11,979,6.2,Neural Networks Co -AI05262,Autonomous Systems Engineer,58383,EUR,49626,EN,CT,Austria,L,Austria,100,"Python, TensorFlow, Tableau, Data Visualization",Bachelor,0,Manufacturing,2024-05-11,2024-07-23,879,9.4,Machine Intelligence Group -AI05263,AI Consultant,176960,USD,176960,SE,CT,Denmark,S,Denmark,0,"Scala, Hadoop, SQL, Kubernetes, Azure",Master,7,Manufacturing,2024-06-14,2024-07-12,1584,5.3,Digital Transformation LLC -AI05264,Research Scientist,68995,EUR,58646,MI,FL,Austria,M,Netherlands,100,"R, Linux, Scala, SQL",Associate,4,Consulting,2025-04-24,2025-07-04,2408,9.5,AI Innovations -AI05265,ML Ops Engineer,130169,CAD,162711,SE,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Deep Learning",PhD,9,Transportation,2024-06-02,2024-08-02,747,8,DataVision Ltd -AI05266,Data Engineer,51950,USD,51950,SE,CT,China,S,China,0,"Java, Git, Kubernetes, Python",Bachelor,9,Government,2024-12-18,2025-02-26,1106,7.8,DataVision Ltd -AI05267,AI Software Engineer,95065,USD,95065,MI,FL,Norway,S,Norway,100,"Linux, Kubernetes, Scala, GCP, Statistics",Bachelor,2,Automotive,2024-02-12,2024-03-04,967,9.6,Quantum Computing Inc -AI05268,AI Product Manager,78158,USD,78158,EN,PT,Ireland,M,Ireland,50,"R, SQL, Scala, PyTorch",Associate,1,Education,2024-06-11,2024-07-27,571,8.1,Advanced Robotics -AI05269,AI Architect,156925,EUR,133386,EX,PT,Germany,L,Switzerland,0,"Git, Hadoop, SQL, Linux, Azure",Associate,14,Retail,2024-10-13,2024-12-17,1184,6.8,Machine Intelligence Group -AI05270,Machine Learning Engineer,57461,USD,57461,SE,PT,China,S,China,100,"Data Visualization, SQL, Tableau, Java, GCP",Bachelor,6,Real Estate,2024-05-15,2024-06-29,1779,5.4,Quantum Computing Inc -AI05271,AI Architect,178905,CHF,161015,MI,CT,Switzerland,L,Switzerland,100,"Java, Azure, SQL",Master,4,Telecommunications,2024-06-24,2024-08-11,1733,5.8,Cloud AI Solutions -AI05272,Deep Learning Engineer,72036,EUR,61231,MI,PT,France,M,France,50,"R, Scala, Java, Docker, Kubernetes",PhD,4,Government,2024-03-17,2024-04-28,2121,5.1,Cognitive Computing -AI05273,AI Software Engineer,28532,USD,28532,EN,CT,China,S,China,50,"Spark, Data Visualization, SQL",PhD,1,Energy,2025-01-14,2025-02-04,551,6.3,Smart Analytics -AI05274,Research Scientist,102165,USD,102165,MI,FL,Ireland,M,Australia,50,"SQL, Docker, Data Visualization, GCP",PhD,2,Consulting,2024-04-26,2024-07-03,907,6.1,Future Systems -AI05275,AI Specialist,54248,USD,54248,EN,FT,Sweden,M,Sweden,100,"SQL, Scala, Docker, Kubernetes, Computer Vision",PhD,0,Finance,2025-04-27,2025-06-05,1496,7.7,Cognitive Computing -AI05276,AI Architect,133384,USD,133384,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Scala, TensorFlow, Linux, Deep Learning",Associate,8,Automotive,2025-02-16,2025-03-08,1747,5.8,Digital Transformation LLC -AI05277,Head of AI,166944,JPY,18363840,SE,CT,Japan,L,Japan,0,"SQL, Git, Mathematics",PhD,9,Transportation,2024-12-14,2025-02-25,594,5.2,TechCorp Inc -AI05278,Data Engineer,72269,USD,72269,EN,PT,South Korea,L,Mexico,50,"GCP, Spark, Linux, Computer Vision",Bachelor,1,Technology,2024-05-14,2024-07-03,1113,6,Cloud AI Solutions -AI05279,AI Specialist,39537,USD,39537,SE,FT,India,M,Nigeria,50,"Git, AWS, MLOps, Data Visualization",Associate,5,Manufacturing,2024-07-12,2024-08-07,1801,9.6,Autonomous Tech -AI05280,AI Specialist,206054,USD,206054,EX,FT,Ireland,S,Nigeria,50,"Azure, Hadoop, TensorFlow",Bachelor,12,Manufacturing,2024-03-03,2024-03-19,1141,8.2,Cognitive Computing -AI05281,Autonomous Systems Engineer,94121,CAD,117651,SE,FL,Canada,S,Belgium,50,"Deep Learning, Docker, Scala, Tableau, TensorFlow",Associate,7,Transportation,2025-02-10,2025-02-24,2387,7.9,Advanced Robotics -AI05282,Deep Learning Engineer,110533,AUD,149220,SE,PT,Australia,M,Italy,0,"Linux, TensorFlow, Python",Master,7,Government,2025-01-13,2025-03-20,1907,7.1,Machine Intelligence Group -AI05283,Data Scientist,106010,CHF,95409,MI,CT,Switzerland,M,Switzerland,100,"PyTorch, Statistics, SQL, Deep Learning",PhD,3,Automotive,2024-11-22,2024-12-22,1805,8.2,Autonomous Tech -AI05284,AI Software Engineer,213187,EUR,181209,EX,CT,France,L,France,100,"Linux, Spark, MLOps",PhD,18,Real Estate,2025-01-29,2025-04-02,1803,7.3,Cognitive Computing -AI05285,Research Scientist,103681,USD,103681,EX,PT,China,L,China,100,"PyTorch, Hadoop, Scala, GCP",Associate,17,Gaming,2024-08-03,2024-09-04,2335,7.7,Cognitive Computing -AI05286,Deep Learning Engineer,350954,CHF,315859,EX,FT,Switzerland,L,Switzerland,50,"R, Statistics, PyTorch",PhD,18,Education,2024-09-03,2024-09-25,1159,5.3,Neural Networks Co -AI05287,Robotics Engineer,166456,USD,166456,SE,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Data Visualization, SQL, Statistics",Master,6,Government,2025-04-20,2025-05-26,747,8.1,TechCorp Inc -AI05288,Machine Learning Researcher,127694,USD,127694,SE,FT,Israel,M,Israel,100,"Java, Deep Learning, Statistics",Associate,5,Education,2024-07-27,2024-09-01,1919,9.3,TechCorp Inc -AI05289,AI Architect,44798,USD,44798,SE,CT,India,M,Norway,50,"PyTorch, Azure, Tableau, Spark",Bachelor,5,Technology,2025-01-25,2025-04-08,1375,9.5,Quantum Computing Inc -AI05290,Machine Learning Engineer,97713,USD,97713,MI,FL,Sweden,L,Germany,100,"R, Python, Deep Learning, Computer Vision, Mathematics",Bachelor,2,Gaming,2024-04-15,2024-06-18,2136,8.7,Future Systems -AI05291,AI Research Scientist,104377,EUR,88720,MI,CT,Netherlands,S,Vietnam,50,"Python, Data Visualization, TensorFlow",Master,3,Media,2024-10-28,2024-12-08,1813,6.8,Cloud AI Solutions -AI05292,AI Architect,50775,CAD,63469,EN,FL,Canada,S,Canada,50,"Mathematics, PyTorch, GCP",Master,1,Transportation,2025-04-03,2025-05-06,1795,6.7,Quantum Computing Inc -AI05293,NLP Engineer,212513,USD,212513,EX,FL,South Korea,L,India,50,"Python, AWS, Tableau",Associate,10,Technology,2024-06-28,2024-08-27,2002,7.1,DataVision Ltd -AI05294,Robotics Engineer,33907,USD,33907,MI,PT,India,S,Colombia,100,"MLOps, R, Docker",Bachelor,2,Education,2024-10-13,2024-12-02,1146,8.3,Future Systems -AI05295,AI Specialist,130049,AUD,175566,SE,FT,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch, AWS",Master,6,Consulting,2024-05-28,2024-07-26,1484,8,TechCorp Inc -AI05296,Research Scientist,214956,USD,214956,EX,FT,Norway,S,Thailand,50,"AWS, PyTorch, GCP, Statistics",Master,13,Energy,2025-01-05,2025-01-26,1776,9.6,Smart Analytics -AI05297,Data Scientist,131854,USD,131854,SE,CT,United States,M,United States,100,"Data Visualization, MLOps, Tableau, PyTorch",Associate,9,Manufacturing,2025-01-27,2025-04-02,533,9.5,DataVision Ltd -AI05298,Computer Vision Engineer,71723,JPY,7889530,EN,FT,Japan,L,Japan,100,"Computer Vision, NLP, Spark, GCP",Master,0,Technology,2024-09-02,2024-09-19,666,5.5,Digital Transformation LLC -AI05299,Principal Data Scientist,96917,USD,96917,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Git, Hadoop, PyTorch",Master,8,Transportation,2024-12-18,2025-01-28,1627,5.8,DataVision Ltd -AI05300,AI Product Manager,74302,USD,74302,MI,PT,South Korea,L,South Korea,100,"R, Python, Git",PhD,3,Finance,2025-04-24,2025-05-25,752,8.7,Machine Intelligence Group -AI05301,Computer Vision Engineer,284665,USD,284665,EX,CT,Denmark,M,France,50,"Data Visualization, Java, Scala, MLOps",Bachelor,14,Automotive,2024-06-22,2024-07-09,2464,7.9,Neural Networks Co -AI05302,AI Architect,83787,EUR,71219,MI,PT,France,S,France,0,"SQL, R, AWS, Deep Learning, Hadoop",PhD,3,Healthcare,2024-10-12,2024-11-17,2212,8,Future Systems -AI05303,Machine Learning Engineer,85475,GBP,64106,MI,CT,United Kingdom,M,Mexico,100,"Tableau, GCP, NLP, Spark, Java",PhD,2,Healthcare,2024-05-12,2024-07-13,536,8.5,DataVision Ltd -AI05304,Principal Data Scientist,173819,EUR,147746,EX,PT,Austria,S,Austria,100,"Kubernetes, Statistics, PyTorch, GCP, Linux",Master,14,Education,2024-12-08,2025-02-19,2412,9,Quantum Computing Inc -AI05305,Data Scientist,94067,EUR,79957,MI,PT,Germany,M,Germany,50,"NLP, R, Tableau, Docker, AWS",PhD,4,Healthcare,2025-02-13,2025-03-10,1782,6.6,Cognitive Computing -AI05306,AI Consultant,301786,JPY,33196460,EX,FL,Japan,L,Japan,0,"Deep Learning, Git, Scala, Python",PhD,11,Retail,2025-04-03,2025-04-18,902,9.6,Neural Networks Co -AI05307,AI Research Scientist,86235,EUR,73300,EN,CT,Netherlands,L,Netherlands,100,"SQL, Kubernetes, PyTorch",Associate,1,Retail,2024-02-15,2024-03-04,1324,8.2,DeepTech Ventures -AI05308,Head of AI,165965,USD,165965,EX,FT,Israel,S,Israel,0,"TensorFlow, Azure, Linux",Associate,12,Government,2024-03-01,2024-04-19,1525,5.6,Smart Analytics -AI05309,Machine Learning Engineer,85823,USD,85823,EN,CT,Denmark,M,Denmark,100,"PyTorch, Azure, Data Visualization",Associate,1,Education,2024-07-30,2024-10-08,1458,6.7,Smart Analytics -AI05310,AI Software Engineer,85037,USD,85037,EX,FL,China,L,China,0,"Mathematics, Hadoop, Data Visualization",Bachelor,16,Retail,2024-12-03,2025-01-16,1818,7.9,AI Innovations -AI05311,AI Research Scientist,61149,USD,61149,MI,PT,South Korea,M,Germany,0,"SQL, Kubernetes, PyTorch",Bachelor,2,Media,2024-03-25,2024-06-05,1921,9.4,Advanced Robotics -AI05312,AI Specialist,92493,CAD,115616,MI,CT,Canada,L,Canada,50,"Linux, PyTorch, Git",PhD,3,Consulting,2024-08-13,2024-09-12,1208,7.6,AI Innovations -AI05313,Principal Data Scientist,114033,JPY,12543630,MI,FT,Japan,L,Japan,100,"Tableau, R, MLOps",PhD,4,Automotive,2025-01-24,2025-03-31,1016,7.8,Predictive Systems -AI05314,NLP Engineer,53893,EUR,45809,EN,CT,Germany,S,United Kingdom,0,"Python, Spark, Hadoop",Bachelor,1,Gaming,2024-02-20,2024-03-07,2172,7.6,Machine Intelligence Group -AI05315,ML Ops Engineer,84318,USD,84318,EN,PT,Finland,L,Romania,100,"TensorFlow, Computer Vision, Tableau",PhD,1,Automotive,2024-11-02,2024-12-09,785,7.4,TechCorp Inc -AI05316,Deep Learning Engineer,102359,CAD,127949,SE,CT,Canada,S,Canada,50,"GCP, R, Git, Kubernetes",Bachelor,9,Education,2025-04-24,2025-05-27,1201,7.1,Quantum Computing Inc -AI05317,Data Analyst,37425,USD,37425,EN,CT,China,M,China,100,"SQL, R, Tableau, Azure, PyTorch",Master,1,Manufacturing,2024-04-03,2024-06-08,1464,9.5,Advanced Robotics -AI05318,AI Specialist,78231,USD,78231,EN,CT,Denmark,M,Thailand,100,"Deep Learning, GCP, Python, Data Visualization, Docker",Bachelor,0,Manufacturing,2024-06-01,2024-07-06,2337,5.8,Algorithmic Solutions -AI05319,Machine Learning Engineer,62558,EUR,53174,EN,CT,Netherlands,M,Norway,50,"R, SQL, AWS, MLOps, Docker",Master,1,Transportation,2025-03-30,2025-04-20,2055,7.8,Future Systems -AI05320,Deep Learning Engineer,123579,CAD,154474,SE,FL,Canada,L,Canada,0,"Hadoop, Tableau, GCP, Deep Learning",PhD,5,Technology,2024-10-24,2024-12-15,785,9.3,TechCorp Inc -AI05321,Deep Learning Engineer,83741,CAD,104676,MI,FL,Canada,M,Canada,100,"NLP, Docker, Git",Master,3,Automotive,2025-03-04,2025-05-06,2180,5.3,Quantum Computing Inc -AI05322,Principal Data Scientist,103613,USD,103613,SE,PT,Sweden,S,Spain,50,"Linux, TensorFlow, Hadoop, Computer Vision, Tableau",PhD,7,Automotive,2024-01-10,2024-02-11,1225,10,Algorithmic Solutions -AI05323,Deep Learning Engineer,122345,USD,122345,SE,FT,Israel,S,Israel,0,"SQL, Python, TensorFlow, Git, PyTorch",Associate,9,Manufacturing,2024-02-20,2024-04-15,563,8.7,Autonomous Tech -AI05324,AI Software Engineer,125817,CHF,113235,EN,FT,Switzerland,L,Singapore,0,"Tableau, Scala, Python",Associate,0,Finance,2024-06-25,2024-07-12,2037,6.9,Neural Networks Co -AI05325,AI Research Scientist,83848,USD,83848,MI,CT,Sweden,S,Nigeria,50,"Python, Git, TensorFlow, Deep Learning",Bachelor,2,Media,2024-04-21,2024-07-01,1561,8.1,Predictive Systems -AI05326,Data Analyst,126646,EUR,107649,SE,FT,Netherlands,L,Netherlands,100,"Hadoop, Spark, Linux",Associate,5,Manufacturing,2024-03-20,2024-04-09,2308,7.6,DataVision Ltd -AI05327,AI Product Manager,216544,USD,216544,EX,FT,United States,M,United States,100,"Kubernetes, SQL, Azure, Linux, PyTorch",Associate,14,Transportation,2024-07-25,2024-09-23,1367,5.1,Cloud AI Solutions -AI05328,AI Research Scientist,254248,EUR,216111,EX,FL,Austria,L,Austria,50,"R, Docker, Data Visualization, MLOps, Spark",PhD,13,Automotive,2024-11-17,2025-01-29,2380,8,Machine Intelligence Group -AI05329,Deep Learning Engineer,238603,GBP,178952,EX,FT,United Kingdom,L,United Kingdom,0,"R, Hadoop, SQL, Azure, Tableau",Bachelor,16,Energy,2024-05-10,2024-05-25,1566,8.9,Cloud AI Solutions -AI05330,NLP Engineer,71862,USD,71862,EN,FT,Sweden,M,Austria,50,"SQL, PyTorch, MLOps, NLP, GCP",PhD,1,Automotive,2024-12-15,2025-01-10,2276,9.3,Autonomous Tech -AI05331,Autonomous Systems Engineer,43525,USD,43525,SE,CT,China,S,Philippines,50,"Python, SQL, R, Git, TensorFlow",Master,6,Gaming,2024-09-23,2024-10-19,2248,7.1,Smart Analytics -AI05332,Computer Vision Engineer,133643,EUR,113597,SE,FL,Austria,L,Austria,0,"Python, MLOps, Kubernetes",Associate,5,Healthcare,2025-02-05,2025-03-08,1300,7,Digital Transformation LLC -AI05333,Machine Learning Researcher,209974,SGD,272966,EX,PT,Singapore,S,Singapore,0,"Python, GCP, Scala, SQL",Master,18,Consulting,2024-10-27,2024-11-24,2148,10,Quantum Computing Inc -AI05334,AI Consultant,188802,CAD,236003,EX,FT,Canada,L,Austria,50,"Kubernetes, NLP, PyTorch, Git",Bachelor,14,Automotive,2024-02-27,2024-04-15,1309,8.3,Machine Intelligence Group -AI05335,ML Ops Engineer,109423,USD,109423,MI,FT,Norway,S,Czech Republic,0,"Java, Linux, Computer Vision",Associate,4,Telecommunications,2025-01-05,2025-01-19,1573,5.2,Digital Transformation LLC -AI05336,Data Scientist,193402,SGD,251423,EX,CT,Singapore,L,Singapore,0,"Hadoop, Python, Kubernetes",Bachelor,13,Healthcare,2024-08-27,2024-09-23,1658,8.9,TechCorp Inc -AI05337,Deep Learning Engineer,68104,EUR,57888,EN,FL,France,L,France,100,"Scala, Docker, Mathematics, Spark",PhD,0,Real Estate,2025-01-01,2025-02-23,2350,5.2,Future Systems -AI05338,AI Consultant,115997,USD,115997,MI,FT,United States,M,United States,0,"Linux, Scala, Mathematics, GCP, Deep Learning",Bachelor,4,Gaming,2024-06-27,2024-07-13,2145,8.7,DataVision Ltd -AI05339,AI Specialist,87942,USD,87942,MI,FT,South Korea,M,New Zealand,50,"R, MLOps, SQL, AWS, Scala",PhD,4,Education,2024-03-10,2024-03-27,1259,6.9,Autonomous Tech -AI05340,Machine Learning Engineer,303218,USD,303218,EX,CT,Denmark,L,Denmark,50,"R, Git, Scala",PhD,18,Government,2024-12-15,2025-02-02,1087,9.7,DataVision Ltd -AI05341,Research Scientist,63427,USD,63427,MI,CT,South Korea,S,South Korea,100,"Spark, Hadoop, R",Bachelor,2,Finance,2024-04-14,2024-05-25,952,7.2,Machine Intelligence Group -AI05342,Principal Data Scientist,148375,GBP,111281,SE,FT,United Kingdom,L,United Kingdom,0,"Mathematics, Python, Linux, Hadoop, TensorFlow",Bachelor,6,Education,2025-02-24,2025-04-29,609,7.3,Machine Intelligence Group -AI05343,Machine Learning Researcher,91410,CAD,114263,MI,FL,Canada,M,Canada,0,"GCP, Python, Spark",PhD,2,Transportation,2024-02-11,2024-04-24,1107,5.9,AI Innovations -AI05344,Data Engineer,217295,USD,217295,EX,FL,United States,L,United States,50,"TensorFlow, Java, Scala",Associate,14,Education,2024-01-27,2024-02-23,1243,9.1,Future Systems -AI05345,AI Consultant,65815,AUD,88850,EN,PT,Australia,L,Kenya,50,"Scala, AWS, Git, Computer Vision, Azure",Bachelor,0,Consulting,2025-04-07,2025-05-17,2254,5.6,TechCorp Inc -AI05346,Research Scientist,185973,SGD,241765,EX,CT,Singapore,S,Singapore,0,"NLP, Deep Learning, Git",Associate,13,Real Estate,2025-04-29,2025-06-08,940,5.5,DeepTech Ventures -AI05347,Principal Data Scientist,113175,USD,113175,SE,PT,Finland,S,Finland,100,"TensorFlow, Deep Learning, PyTorch, MLOps, Hadoop",Master,7,Government,2024-08-28,2024-10-29,722,8.4,DeepTech Ventures -AI05348,Deep Learning Engineer,198579,USD,198579,EX,FT,Denmark,S,Denmark,50,"Data Visualization, Docker, Spark, Python, Java",Master,14,Healthcare,2025-03-29,2025-06-08,1705,8.2,Smart Analytics -AI05349,Machine Learning Researcher,25817,USD,25817,EN,CT,India,M,India,0,"MLOps, Scala, Linux, Azure",Bachelor,0,Media,2025-04-08,2025-04-23,1618,7.7,DeepTech Ventures -AI05350,Head of AI,81249,USD,81249,MI,CT,Sweden,M,Ukraine,50,"Computer Vision, R, GCP",Associate,3,Manufacturing,2024-04-08,2024-06-07,1936,9.5,Autonomous Tech -AI05351,Data Analyst,107111,AUD,144600,SE,CT,Australia,S,Australia,100,"Python, Docker, Linux, Statistics, GCP",Associate,7,Finance,2024-06-22,2024-09-01,671,5,Digital Transformation LLC -AI05352,AI Software Engineer,158552,USD,158552,SE,CT,Norway,M,United Kingdom,0,"Git, Python, GCP",Bachelor,7,Technology,2024-11-25,2025-01-14,2214,7.6,TechCorp Inc -AI05353,Autonomous Systems Engineer,209929,USD,209929,EX,CT,United States,M,United States,0,"Azure, Python, Spark, GCP",PhD,14,Transportation,2024-11-24,2025-02-01,1931,5.2,DeepTech Ventures -AI05354,AI Research Scientist,288133,GBP,216100,EX,CT,United Kingdom,L,United Kingdom,0,"Scala, Data Visualization, AWS, Computer Vision",Master,13,Real Estate,2025-02-02,2025-03-05,1068,8.8,Advanced Robotics -AI05355,Head of AI,243777,JPY,26815470,EX,FT,Japan,M,Japan,50,"Mathematics, R, NLP, Linux, SQL",Bachelor,13,Gaming,2025-01-29,2025-02-24,2295,7.8,Digital Transformation LLC -AI05356,Data Engineer,54043,AUD,72958,EN,FT,Australia,M,Germany,50,"Kubernetes, Deep Learning, Git, Hadoop",Associate,0,Manufacturing,2024-02-20,2024-03-05,855,9.4,Cognitive Computing -AI05357,Data Analyst,82069,USD,82069,MI,FL,Ireland,M,Ireland,100,"MLOps, PyTorch, TensorFlow",Associate,3,Retail,2025-01-27,2025-02-28,1505,9.7,Advanced Robotics -AI05358,ML Ops Engineer,65179,USD,65179,MI,CT,Ireland,S,Ireland,50,"SQL, Hadoop, Tableau",PhD,3,Telecommunications,2024-03-09,2024-04-08,2284,5.1,Future Systems -AI05359,AI Specialist,162962,USD,162962,SE,PT,Sweden,L,Poland,0,"Spark, Scala, PyTorch, NLP, GCP",Bachelor,8,Healthcare,2025-02-14,2025-04-26,1367,5.9,Smart Analytics -AI05360,AI Specialist,91928,USD,91928,EX,FT,China,L,China,50,"PyTorch, Scala, Tableau, Linux, NLP",Master,10,Government,2025-04-12,2025-05-07,1517,6.3,DeepTech Ventures -AI05361,AI Architect,134846,USD,134846,SE,PT,United States,M,United States,100,"PyTorch, Git, MLOps, SQL, Java",Master,6,Retail,2024-08-29,2024-09-13,1153,9.9,DataVision Ltd -AI05362,Data Analyst,22186,USD,22186,EN,PT,India,L,Spain,0,"Computer Vision, TensorFlow, NLP, SQL, Mathematics",Bachelor,1,Retail,2024-04-13,2024-06-15,512,8,Quantum Computing Inc -AI05363,Research Scientist,61335,USD,61335,SE,PT,China,L,China,0,"Java, PyTorch, Statistics",Associate,9,Retail,2024-03-05,2024-03-26,733,8.9,TechCorp Inc -AI05364,AI Specialist,246778,EUR,209761,EX,FT,Germany,L,New Zealand,100,"Kubernetes, PyTorch, NLP, TensorFlow",Master,15,Gaming,2025-01-20,2025-03-28,506,5.1,Quantum Computing Inc -AI05365,AI Architect,104343,GBP,78257,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Data Visualization, Java, GCP",Master,3,Retail,2024-05-21,2024-08-01,812,7.3,Autonomous Tech -AI05366,AI Architect,130307,USD,130307,MI,PT,Denmark,L,Denmark,50,"Linux, AWS, Java",PhD,2,Telecommunications,2024-08-05,2024-10-08,1924,6.6,DeepTech Ventures -AI05367,Computer Vision Engineer,83046,USD,83046,EN,FL,Norway,S,Norway,50,"SQL, Linux, Git, PyTorch, Deep Learning",Master,0,Retail,2025-03-05,2025-05-15,2443,6.4,Digital Transformation LLC -AI05368,AI Specialist,157446,USD,157446,MI,PT,Norway,L,Norway,100,"MLOps, Python, Tableau, Kubernetes, Data Visualization",Master,3,Healthcare,2024-08-29,2024-10-25,1804,5.7,Cognitive Computing -AI05369,Machine Learning Researcher,297092,JPY,32680120,EX,FL,Japan,L,Japan,0,"Spark, GCP, Python, Mathematics",Associate,16,Finance,2024-08-07,2024-10-07,989,8.6,Future Systems -AI05370,AI Product Manager,68384,USD,68384,MI,CT,Finland,S,Finland,100,"Python, Linux, MLOps, Kubernetes, TensorFlow",Master,2,Transportation,2025-01-17,2025-03-14,1050,6.4,DataVision Ltd -AI05371,ML Ops Engineer,92089,USD,92089,EX,FL,India,L,India,50,"Docker, Hadoop, SQL, Azure, Java",PhD,17,Automotive,2024-08-13,2024-09-04,764,6,Neural Networks Co -AI05372,Deep Learning Engineer,136227,EUR,115793,SE,FT,Netherlands,L,Netherlands,0,"Statistics, Scala, Deep Learning",PhD,6,Healthcare,2024-01-01,2024-02-29,1685,9.2,Neural Networks Co -AI05373,AI Product Manager,129513,USD,129513,SE,PT,Ireland,M,Australia,100,"Python, Docker, Mathematics",PhD,7,Government,2024-10-18,2024-11-29,1009,7.8,Cloud AI Solutions -AI05374,AI Specialist,135626,USD,135626,SE,PT,Israel,M,Vietnam,50,"Scala, Hadoop, Computer Vision, Deep Learning",PhD,7,Manufacturing,2025-03-27,2025-06-08,1852,8,Advanced Robotics -AI05375,AI Specialist,43215,USD,43215,SE,FL,China,S,Hungary,50,"PyTorch, Python, Linux",Master,9,Energy,2024-08-16,2024-10-05,714,8.1,Smart Analytics -AI05376,AI Research Scientist,70887,EUR,60254,MI,FT,Germany,S,Germany,50,"Python, Java, AWS, Scala, SQL",Associate,4,Retail,2025-02-15,2025-04-17,610,5.4,Smart Analytics -AI05377,ML Ops Engineer,288695,CHF,259826,EX,PT,Switzerland,L,Switzerland,0,"Spark, Linux, Statistics, Mathematics",Master,16,Transportation,2024-03-12,2024-05-19,1570,6,TechCorp Inc -AI05378,Data Engineer,85081,CHF,76573,EN,FT,Switzerland,S,Nigeria,50,"Java, PyTorch, AWS",PhD,1,Energy,2025-03-16,2025-05-10,1736,5.3,Advanced Robotics -AI05379,NLP Engineer,111446,USD,111446,MI,CT,Israel,L,Israel,100,"Spark, MLOps, Scala, AWS",Master,4,Energy,2024-06-17,2024-07-13,513,7.5,Predictive Systems -AI05380,Data Analyst,66898,USD,66898,MI,CT,Israel,S,Israel,50,"Git, Spark, R, PyTorch",Master,3,Gaming,2024-12-01,2025-01-02,1269,6.9,Predictive Systems -AI05381,AI Product Manager,37660,USD,37660,EN,FL,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-07-28,2024-09-17,835,8.5,Neural Networks Co -AI05382,Autonomous Systems Engineer,79062,EUR,67203,EN,PT,Netherlands,L,Finland,50,"NLP, SQL, TensorFlow, Scala, PyTorch",Master,0,Healthcare,2024-07-06,2024-08-07,2128,9.7,Predictive Systems -AI05383,Deep Learning Engineer,125125,SGD,162663,MI,PT,Singapore,L,Singapore,0,"Java, Git, Tableau, Scala",PhD,4,Healthcare,2024-03-03,2024-04-17,1935,6,Advanced Robotics -AI05384,Research Scientist,137554,JPY,15130940,SE,FT,Japan,M,Japan,0,"Data Visualization, Kubernetes, Computer Vision",Bachelor,8,Transportation,2024-09-23,2024-11-04,812,6.2,DeepTech Ventures -AI05385,AI Specialist,95923,EUR,81535,MI,FT,France,M,France,0,"NLP, Git, Mathematics",Associate,2,Transportation,2024-11-03,2024-11-21,667,9.2,DeepTech Ventures -AI05386,Autonomous Systems Engineer,126145,GBP,94609,SE,PT,United Kingdom,L,United Kingdom,50,"Git, Mathematics, NLP",PhD,7,Media,2024-01-15,2024-02-29,1112,6.3,Machine Intelligence Group -AI05387,Principal Data Scientist,98692,USD,98692,SE,PT,Ireland,S,Ireland,0,"Deep Learning, Scala, Computer Vision",Bachelor,5,Gaming,2025-02-02,2025-04-09,1354,6.7,Algorithmic Solutions -AI05388,Head of AI,200999,EUR,170849,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Computer Vision, PyTorch, Git",Master,16,Consulting,2025-03-29,2025-04-29,1230,6.6,Future Systems -AI05389,Head of AI,54737,GBP,41053,EN,CT,United Kingdom,M,South Africa,50,"Python, Kubernetes, Scala",Associate,1,Telecommunications,2024-12-10,2025-01-01,2060,9.6,Quantum Computing Inc -AI05390,Machine Learning Engineer,202067,SGD,262687,EX,FT,Singapore,M,Brazil,100,"R, Scala, Python",Associate,18,Technology,2024-09-02,2024-09-17,2350,7.9,Neural Networks Co -AI05391,AI Research Scientist,247645,CAD,309556,EX,PT,Canada,L,Canada,100,"R, Mathematics, Python, Statistics",Associate,12,Gaming,2024-06-08,2024-07-02,935,8,Future Systems -AI05392,Data Engineer,136820,GBP,102615,SE,PT,United Kingdom,L,United Kingdom,100,"TensorFlow, Tableau, Computer Vision, Scala",Master,9,Real Estate,2025-03-27,2025-05-27,1477,6.5,Machine Intelligence Group -AI05393,Robotics Engineer,118345,USD,118345,EX,PT,Israel,S,Israel,0,"MLOps, Data Visualization, Linux, Docker, GCP",Associate,15,Media,2024-02-13,2024-04-18,1177,9.5,Neural Networks Co -AI05394,Computer Vision Engineer,86939,JPY,9563290,EN,CT,Japan,L,Japan,100,"Kubernetes, R, Hadoop, SQL, Deep Learning",PhD,1,Automotive,2024-08-14,2024-09-28,1232,7.2,Digital Transformation LLC -AI05395,Research Scientist,85462,JPY,9400820,EN,PT,Japan,M,Japan,100,"Kubernetes, Docker, NLP, Statistics, GCP",Associate,0,Government,2025-02-25,2025-04-11,1813,6.4,Algorithmic Solutions -AI05396,AI Research Scientist,75148,CHF,67633,EN,FL,Switzerland,M,Colombia,0,"NLP, Java, Kubernetes, Git",Master,1,Gaming,2025-01-14,2025-02-08,1792,10,Machine Intelligence Group -AI05397,Principal Data Scientist,253163,USD,253163,EX,FL,Denmark,L,Denmark,50,"TensorFlow, Git, Data Visualization",PhD,19,Real Estate,2024-06-06,2024-08-16,1330,5.2,TechCorp Inc -AI05398,AI Architect,30114,USD,30114,EN,FL,China,L,Finland,100,"Statistics, PyTorch, Java, Azure, TensorFlow",Master,1,Telecommunications,2024-11-16,2025-01-19,2090,8,Smart Analytics -AI05399,Computer Vision Engineer,176415,USD,176415,EX,CT,Finland,M,Finland,0,"GCP, NLP, Deep Learning, Spark",PhD,12,Telecommunications,2025-02-20,2025-04-21,1544,8.9,TechCorp Inc -AI05400,AI Specialist,73489,EUR,62466,MI,FT,Germany,M,Germany,50,"SQL, Java, Spark, TensorFlow, R",Associate,4,Automotive,2024-06-02,2024-07-03,2185,8.2,TechCorp Inc -AI05401,ML Ops Engineer,115294,USD,115294,SE,FT,Finland,M,Canada,100,"Azure, MLOps, Scala",Master,7,Real Estate,2024-03-21,2024-04-21,1538,7.8,Neural Networks Co -AI05402,Data Engineer,74479,SGD,96823,EN,FL,Singapore,L,Singapore,100,"SQL, Python, Statistics, Git",Associate,0,Gaming,2024-11-10,2024-12-01,1859,7.7,Smart Analytics -AI05403,AI Software Engineer,97495,USD,97495,SE,FT,Sweden,S,Sweden,0,"Spark, Git, Scala, Computer Vision",Associate,8,Government,2024-09-29,2024-11-25,899,6.9,DeepTech Ventures -AI05404,Principal Data Scientist,63891,USD,63891,EN,FL,Norway,S,Norway,100,"MLOps, SQL, Scala, GCP, Python",Associate,0,Manufacturing,2024-05-15,2024-06-09,1557,6.1,Smart Analytics -AI05405,Data Analyst,49339,CAD,61674,EN,PT,Canada,S,Canada,50,"Kubernetes, MLOps, Git, NLP, Scala",Master,1,Transportation,2024-05-21,2024-06-05,1652,6.6,Advanced Robotics -AI05406,Autonomous Systems Engineer,114592,USD,114592,EX,FL,China,L,Estonia,0,"Scala, NLP, Kubernetes",Master,12,Media,2024-04-14,2024-06-26,967,5.2,DataVision Ltd -AI05407,Data Scientist,44734,USD,44734,SE,FT,India,M,India,50,"NLP, MLOps, Scala, Python, Java",Master,6,Media,2024-11-01,2024-12-12,2496,7.7,Predictive Systems -AI05408,AI Architect,191311,USD,191311,EX,FL,Israel,S,Israel,50,"SQL, Kubernetes, GCP",Master,14,Consulting,2025-03-28,2025-04-21,873,8.3,Predictive Systems -AI05409,Data Engineer,198417,USD,198417,EX,FT,Finland,L,Switzerland,0,"Statistics, Kubernetes, Spark, R",Bachelor,16,Consulting,2024-05-20,2024-07-21,2466,9,Quantum Computing Inc -AI05410,AI Specialist,104925,JPY,11541750,SE,PT,Japan,S,Nigeria,0,"Git, MLOps, Scala, Python",Master,6,Media,2024-04-10,2024-05-05,2391,7.8,Neural Networks Co -AI05411,Research Scientist,221209,EUR,188028,EX,FT,Austria,L,Austria,0,"PyTorch, Data Visualization, MLOps",Bachelor,12,Technology,2024-02-28,2024-04-13,1267,8.2,TechCorp Inc -AI05412,NLP Engineer,85694,EUR,72840,MI,FT,Austria,S,Austria,0,"PyTorch, TensorFlow, MLOps, Hadoop, Python",PhD,3,Technology,2025-02-15,2025-04-14,1832,8.5,Neural Networks Co -AI05413,Research Scientist,148534,USD,148534,SE,FT,United States,S,United States,0,"R, Scala, SQL, Azure",PhD,9,Energy,2024-11-06,2025-01-16,1625,5.3,Neural Networks Co -AI05414,Machine Learning Engineer,79799,USD,79799,MI,FT,Israel,L,Israel,0,"Mathematics, AWS, NLP, PyTorch",Master,2,Manufacturing,2024-02-27,2024-04-09,1588,5.1,DataVision Ltd -AI05415,Robotics Engineer,42345,USD,42345,MI,PT,China,S,China,100,"Python, TensorFlow, Deep Learning, Tableau, Azure",Associate,4,Media,2024-06-02,2024-07-11,1265,9.9,Quantum Computing Inc -AI05416,Deep Learning Engineer,120846,CHF,108761,MI,CT,Switzerland,L,Egypt,50,"PyTorch, Java, TensorFlow, Docker",Master,3,Telecommunications,2024-06-09,2024-08-03,1725,6,Algorithmic Solutions -AI05417,AI Specialist,23612,USD,23612,EN,FL,India,S,Thailand,50,"SQL, Kubernetes, Tableau, Git",Associate,1,Gaming,2024-08-18,2024-09-06,2269,8,Autonomous Tech -AI05418,Deep Learning Engineer,166613,GBP,124960,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, Tableau, PyTorch, Data Visualization",Master,12,Technology,2024-06-03,2024-06-28,1513,9.9,Machine Intelligence Group -AI05419,Principal Data Scientist,56615,AUD,76430,EN,CT,Australia,M,Australia,100,"Spark, Statistics, Computer Vision, Python, MLOps",PhD,0,Telecommunications,2025-04-20,2025-06-26,1809,5.8,Algorithmic Solutions -AI05420,AI Specialist,78519,AUD,106001,MI,FT,Australia,M,Australia,100,"TensorFlow, Kubernetes, Computer Vision, Docker",PhD,4,Consulting,2024-04-30,2024-06-08,1672,6,DeepTech Ventures -AI05421,Data Engineer,176102,CAD,220128,EX,FT,Canada,S,Canada,50,"Kubernetes, Docker, AWS",PhD,11,Media,2025-01-11,2025-03-05,2408,9.4,Cognitive Computing -AI05422,AI Product Manager,39202,USD,39202,MI,CT,China,L,China,100,"NLP, Docker, Azure, Hadoop",Bachelor,3,Gaming,2024-09-17,2024-10-20,2380,9.3,Machine Intelligence Group -AI05423,Machine Learning Engineer,52424,USD,52424,EN,CT,Finland,S,Finland,100,"R, Kubernetes, Java, SQL, Docker",Associate,1,Energy,2025-03-03,2025-04-26,1801,6.4,Smart Analytics -AI05424,AI Research Scientist,74687,SGD,97093,EN,PT,Singapore,S,United States,0,"AWS, Tableau, Docker, Computer Vision",PhD,1,Consulting,2025-03-08,2025-04-02,2295,8,Algorithmic Solutions -AI05425,Computer Vision Engineer,231540,CAD,289425,EX,PT,Canada,L,Canada,100,"Java, Kubernetes, Hadoop, Mathematics, Scala",Associate,12,Education,2025-03-21,2025-04-29,2222,7.1,Neural Networks Co -AI05426,Data Analyst,156641,USD,156641,SE,FT,Norway,S,China,50,"Statistics, TensorFlow, Python, GCP",PhD,6,Transportation,2024-12-20,2025-01-20,717,9.2,TechCorp Inc -AI05427,Data Engineer,119985,CAD,149981,SE,FT,Canada,M,Canada,100,"Git, Deep Learning, Hadoop, NLP, Kubernetes",Associate,9,Transportation,2024-09-07,2024-10-07,1933,9.6,Advanced Robotics -AI05428,Autonomous Systems Engineer,131450,AUD,177458,EX,FT,Australia,S,Australia,100,"Hadoop, Linux, Computer Vision, Deep Learning, Kubernetes",PhD,11,Telecommunications,2024-05-02,2024-06-20,962,8.7,Digital Transformation LLC -AI05429,Machine Learning Engineer,179649,CAD,224561,EX,CT,Canada,M,Canada,50,"Linux, Kubernetes, Data Visualization, AWS",PhD,16,Manufacturing,2024-02-14,2024-03-31,1284,6.3,DeepTech Ventures -AI05430,Deep Learning Engineer,113259,EUR,96270,SE,PT,Austria,L,Switzerland,50,"Java, TensorFlow, Azure, Computer Vision",Bachelor,9,Automotive,2024-07-16,2024-09-04,514,8,Predictive Systems -AI05431,Head of AI,90625,CAD,113281,MI,CT,Canada,M,Canada,50,"SQL, Hadoop, R, Java, Python",Bachelor,4,Consulting,2024-04-19,2024-07-01,2289,7.7,Digital Transformation LLC -AI05432,Computer Vision Engineer,115445,USD,115445,MI,FL,Ireland,L,Ireland,100,"AWS, Hadoop, Data Visualization",Bachelor,2,Gaming,2024-09-10,2024-10-03,1925,5.1,Predictive Systems -AI05433,Deep Learning Engineer,82908,EUR,70472,MI,FL,Austria,S,Austria,0,"Python, Spark, SQL, Hadoop, Mathematics",Associate,4,Transportation,2025-02-06,2025-03-17,2093,8.2,Machine Intelligence Group -AI05434,Machine Learning Engineer,104007,CHF,93606,EN,CT,Switzerland,L,India,0,"Python, Scala, Data Visualization, Hadoop, Linux",PhD,0,Finance,2024-09-04,2024-10-11,1160,5.5,Smart Analytics -AI05435,Research Scientist,90940,AUD,122769,MI,PT,Australia,M,Australia,50,"Hadoop, Python, GCP",Bachelor,3,Media,2024-01-04,2024-03-13,2095,5.1,Digital Transformation LLC -AI05436,AI Product Manager,28492,USD,28492,EN,FT,China,L,China,50,"Python, SQL, Statistics",Associate,1,Healthcare,2024-08-08,2024-09-20,2004,7.6,Future Systems -AI05437,ML Ops Engineer,84521,CHF,76069,EN,FL,Switzerland,S,Switzerland,100,"Git, AWS, Kubernetes, MLOps, Tableau",PhD,0,Media,2025-04-01,2025-06-07,740,7.9,Smart Analytics -AI05438,AI Software Engineer,125527,USD,125527,SE,PT,Finland,L,Argentina,0,"PyTorch, Kubernetes, Docker",Associate,6,Gaming,2024-01-20,2024-03-14,1985,8.9,Cognitive Computing -AI05439,Machine Learning Researcher,98155,SGD,127602,MI,FL,Singapore,S,Singapore,0,"Spark, NLP, Python, TensorFlow, Data Visualization",Associate,2,Finance,2025-03-10,2025-04-13,1473,6.1,Smart Analytics -AI05440,Computer Vision Engineer,54723,SGD,71140,EN,FT,Singapore,M,Singapore,0,"SQL, Git, Hadoop, PyTorch, AWS",Master,0,Real Estate,2024-08-14,2024-10-17,1181,6.8,Machine Intelligence Group -AI05441,AI Research Scientist,132179,GBP,99134,SE,FT,United Kingdom,L,United Kingdom,50,"Python, Linux, Deep Learning, Scala",Associate,9,Manufacturing,2025-02-05,2025-03-02,954,7.6,Smart Analytics -AI05442,Data Engineer,99414,JPY,10935540,MI,CT,Japan,S,South Africa,100,"SQL, Kubernetes, Linux, Hadoop",Associate,2,Real Estate,2025-03-25,2025-05-29,1582,6.3,Predictive Systems -AI05443,Computer Vision Engineer,162201,USD,162201,SE,PT,Israel,L,Ireland,50,"NLP, Azure, Hadoop, Python",PhD,6,Finance,2024-02-02,2024-03-30,1047,9.2,Digital Transformation LLC -AI05444,Data Engineer,61351,USD,61351,EN,PT,Israel,L,Israel,50,"AWS, GCP, MLOps, PyTorch, SQL",Master,0,Gaming,2024-09-01,2024-09-15,2430,8.2,Advanced Robotics -AI05445,Machine Learning Engineer,23989,USD,23989,EN,FL,India,S,India,100,"SQL, R, PyTorch, NLP, Computer Vision",Bachelor,1,Automotive,2024-10-13,2024-11-17,1139,9.5,DataVision Ltd -AI05446,Robotics Engineer,65446,USD,65446,MI,CT,Finland,S,Finland,50,"Python, Git, Mathematics",PhD,3,Education,2024-03-30,2024-04-19,879,6,Predictive Systems -AI05447,ML Ops Engineer,160753,USD,160753,MI,FL,Denmark,L,Denmark,100,"Tableau, Docker, Hadoop, MLOps, GCP",Bachelor,2,Telecommunications,2024-07-31,2024-09-15,1572,7.3,Cloud AI Solutions -AI05448,ML Ops Engineer,159740,AUD,215649,SE,CT,Australia,L,Australia,100,"GCP, Spark, PyTorch",Bachelor,5,Telecommunications,2024-05-29,2024-07-11,1719,5.4,Future Systems -AI05449,Research Scientist,86339,EUR,73388,EN,PT,Austria,L,Austria,100,"Data Visualization, Python, Git, TensorFlow",PhD,1,Manufacturing,2024-01-24,2024-04-03,2369,7.3,Machine Intelligence Group -AI05450,Principal Data Scientist,223810,USD,223810,EX,PT,Israel,M,New Zealand,100,"Statistics, Data Visualization, Python",Bachelor,13,Gaming,2024-08-06,2024-10-18,1937,10,Algorithmic Solutions -AI05451,Robotics Engineer,156078,EUR,132666,EX,FT,Austria,M,Austria,0,"Java, Hadoop, R, AWS",Bachelor,13,Finance,2024-08-23,2024-10-31,1683,9.4,Algorithmic Solutions -AI05452,Principal Data Scientist,95770,CHF,86193,EN,PT,Switzerland,M,Switzerland,100,"Kubernetes, Hadoop, Data Visualization",Bachelor,0,Government,2024-05-12,2024-07-06,1591,9.7,Predictive Systems -AI05453,Deep Learning Engineer,94666,JPY,10413260,EN,FT,Japan,L,Japan,50,"Mathematics, Spark, Python, TensorFlow, PyTorch",Bachelor,1,Consulting,2025-03-27,2025-05-14,2335,7.4,Digital Transformation LLC -AI05454,AI Software Engineer,74801,SGD,97241,EN,FL,Singapore,L,Philippines,50,"Git, GCP, Docker, Mathematics",Associate,0,Manufacturing,2025-02-20,2025-04-28,1151,6.9,Digital Transformation LLC -AI05455,Research Scientist,106506,EUR,90530,SE,FT,Austria,S,Austria,0,"Linux, R, Git",PhD,8,Transportation,2024-05-18,2024-07-12,734,9.2,Neural Networks Co -AI05456,Computer Vision Engineer,150029,SGD,195038,SE,FL,Singapore,L,Singapore,100,"GCP, Kubernetes, Java",Associate,7,Manufacturing,2025-01-24,2025-03-15,1856,7.4,Autonomous Tech -AI05457,NLP Engineer,200851,USD,200851,SE,FT,United States,L,Switzerland,50,"GCP, AWS, PyTorch",Bachelor,5,Transportation,2024-12-15,2025-01-10,2386,7,DeepTech Ventures -AI05458,Machine Learning Researcher,99863,GBP,74897,MI,PT,United Kingdom,S,United Kingdom,0,"AWS, Git, Spark",PhD,2,Transportation,2024-11-26,2024-12-29,2303,7.6,Digital Transformation LLC -AI05459,Head of AI,39799,USD,39799,SE,PT,India,S,Kenya,50,"Computer Vision, SQL, Kubernetes, GCP",Associate,5,Manufacturing,2024-07-26,2024-09-30,1362,7,AI Innovations -AI05460,Data Engineer,96455,USD,96455,MI,PT,Denmark,S,Italy,50,"Statistics, Kubernetes, Linux, SQL, Data Visualization",PhD,4,Education,2024-07-24,2024-09-05,1910,6.3,Algorithmic Solutions -AI05461,Data Analyst,158698,USD,158698,EX,PT,South Korea,S,South Korea,50,"Scala, R, MLOps, Spark",Associate,19,Telecommunications,2024-03-25,2024-04-10,1132,6.3,Future Systems -AI05462,Machine Learning Researcher,180104,EUR,153088,EX,FT,Germany,M,Germany,0,"R, GCP, Git, Statistics",PhD,11,Government,2025-01-04,2025-02-09,2103,6.5,Autonomous Tech -AI05463,ML Ops Engineer,60136,EUR,51116,EN,PT,Netherlands,M,Netherlands,50,"SQL, Linux, AWS",PhD,0,Healthcare,2024-05-23,2024-08-01,691,9.7,Advanced Robotics -AI05464,AI Product Manager,183029,USD,183029,EX,FL,Israel,S,Israel,100,"Scala, TensorFlow, Tableau, MLOps, Kubernetes",Bachelor,19,Manufacturing,2024-01-05,2024-01-23,1507,6.7,Machine Intelligence Group -AI05465,AI Product Manager,114370,EUR,97215,MI,FL,Netherlands,M,Romania,50,"Linux, Kubernetes, Statistics, Python",Master,4,Retail,2025-02-19,2025-03-14,1343,8.5,AI Innovations -AI05466,Head of AI,54599,USD,54599,MI,CT,China,L,Netherlands,100,"Statistics, Docker, Python",Bachelor,2,Gaming,2024-04-23,2024-07-02,1436,6.1,Cloud AI Solutions -AI05467,AI Consultant,149215,EUR,126833,EX,CT,Germany,S,Germany,100,"TensorFlow, Deep Learning, Computer Vision, Tableau, SQL",PhD,12,Technology,2024-09-30,2024-11-10,1897,7,AI Innovations -AI05468,Data Analyst,36117,USD,36117,MI,FT,China,S,China,0,"Python, Azure, SQL, R, Mathematics",PhD,2,Consulting,2024-06-03,2024-07-28,1999,5.4,Cognitive Computing -AI05469,NLP Engineer,58126,EUR,49407,EN,PT,Austria,L,Philippines,100,"Python, SQL, Tableau, AWS, Kubernetes",Master,0,Finance,2025-03-17,2025-05-04,1896,5.7,Advanced Robotics -AI05470,AI Specialist,72607,AUD,98019,MI,CT,Australia,M,Australia,0,"Python, TensorFlow, AWS",Master,2,Real Estate,2025-02-11,2025-03-01,1088,7.4,TechCorp Inc -AI05471,Data Analyst,71757,CAD,89696,MI,FL,Canada,S,Kenya,0,"Statistics, PyTorch, Computer Vision, R, Git",Master,2,Media,2024-03-01,2024-04-26,2146,6.5,Future Systems -AI05472,Deep Learning Engineer,105689,EUR,89836,SE,FL,Germany,M,Germany,50,"R, Kubernetes, Mathematics, NLP",Master,9,Real Estate,2024-11-28,2025-01-13,758,5.1,Quantum Computing Inc -AI05473,Head of AI,42540,USD,42540,MI,FL,India,L,Egypt,100,"Python, Data Visualization, R, Spark, Java",PhD,2,Healthcare,2024-03-08,2024-04-06,1622,5.5,Digital Transformation LLC -AI05474,AI Architect,123577,EUR,105040,EX,FT,Austria,S,Portugal,0,"Python, R, NLP",PhD,12,Government,2024-10-17,2024-12-03,1020,6.6,Machine Intelligence Group -AI05475,AI Architect,236155,CAD,295194,EX,FT,Canada,L,Canada,0,"Scala, Spark, SQL",Master,16,Retail,2024-08-16,2024-09-26,1079,5,TechCorp Inc -AI05476,Machine Learning Engineer,70398,EUR,59838,EN,CT,Austria,L,Romania,100,"PyTorch, Spark, SQL, Mathematics",Master,1,Healthcare,2024-09-24,2024-11-20,1778,8,Machine Intelligence Group -AI05477,Data Scientist,146441,USD,146441,EX,FT,Israel,S,Israel,100,"AWS, Scala, Data Visualization, Java",Master,18,Technology,2024-11-13,2024-11-30,551,8.3,Machine Intelligence Group -AI05478,AI Specialist,47127,USD,47127,SE,CT,India,M,India,0,"Statistics, Azure, Git",PhD,6,Finance,2025-01-31,2025-03-17,1325,8,Algorithmic Solutions -AI05479,AI Product Manager,142445,EUR,121078,EX,FT,Austria,M,Austria,0,"Java, Tableau, Docker, Statistics",Master,10,Telecommunications,2024-05-10,2024-06-08,1295,7.5,Advanced Robotics -AI05480,AI Consultant,67586,USD,67586,SE,FL,China,M,China,0,"Mathematics, MLOps, Python, PyTorch, Tableau",PhD,9,Automotive,2025-04-26,2025-06-04,1573,5.5,Smart Analytics -AI05481,Research Scientist,176023,USD,176023,SE,FL,Denmark,S,Denmark,0,"Azure, SQL, Python, Kubernetes, Deep Learning",PhD,6,Real Estate,2024-07-26,2024-09-18,749,6.7,Advanced Robotics -AI05482,Machine Learning Engineer,21634,USD,21634,EN,FT,China,S,China,100,"Azure, SQL, R, Mathematics",Associate,1,Consulting,2024-09-26,2024-12-04,1237,9.1,Digital Transformation LLC -AI05483,ML Ops Engineer,105516,USD,105516,SE,FT,South Korea,S,Malaysia,50,"Azure, SQL, GCP",Associate,9,Technology,2024-07-31,2024-08-27,2063,7.3,Digital Transformation LLC -AI05484,Research Scientist,144381,USD,144381,EX,PT,Ireland,M,Ireland,0,"R, SQL, Docker",PhD,17,Telecommunications,2024-03-27,2024-04-28,1007,9,Advanced Robotics -AI05485,Deep Learning Engineer,76971,USD,76971,MI,FT,Israel,S,Belgium,0,"Python, Scala, Deep Learning",Associate,3,Automotive,2024-07-08,2024-07-26,1221,6.3,DeepTech Ventures -AI05486,AI Research Scientist,69347,USD,69347,SE,FL,China,L,Austria,50,"Data Visualization, Computer Vision, TensorFlow",Associate,6,Retail,2024-09-16,2024-10-29,2123,5.3,Smart Analytics -AI05487,ML Ops Engineer,63587,JPY,6994570,EN,CT,Japan,S,Japan,50,"Computer Vision, PyTorch, Kubernetes, Java, Spark",Master,1,Finance,2025-01-01,2025-03-12,1372,9.2,Advanced Robotics -AI05488,AI Consultant,159882,EUR,135900,SE,CT,Germany,L,Finland,50,"PyTorch, Tableau, R, Data Visualization",Bachelor,9,Media,2024-11-26,2025-01-30,895,6,Predictive Systems -AI05489,Head of AI,63760,USD,63760,EN,FT,Ireland,M,Ireland,100,"Kubernetes, Python, Tableau",Master,0,Telecommunications,2024-12-18,2025-02-06,1750,9.6,Algorithmic Solutions -AI05490,AI Software Engineer,91323,JPY,10045530,MI,CT,Japan,S,Japan,0,"Linux, AWS, Python",Bachelor,3,Healthcare,2025-01-02,2025-03-10,2170,5.1,DataVision Ltd -AI05491,Principal Data Scientist,95852,SGD,124608,MI,CT,Singapore,S,Singapore,100,"TensorFlow, Azure, Git",Associate,2,Media,2024-04-18,2024-06-02,2250,9.5,Autonomous Tech -AI05492,AI Research Scientist,142643,USD,142643,EX,FT,Ireland,M,Germany,50,"Data Visualization, Statistics, Linux",PhD,19,Telecommunications,2024-09-19,2024-11-09,1075,8.6,Advanced Robotics -AI05493,AI Research Scientist,183011,USD,183011,EX,PT,Finland,S,Luxembourg,100,"SQL, MLOps, TensorFlow, AWS",Bachelor,18,Education,2025-01-01,2025-02-23,1368,5.2,Quantum Computing Inc -AI05494,AI Product Manager,60370,USD,60370,EN,PT,United States,S,United States,50,"NLP, R, Linux, SQL",PhD,0,Technology,2024-01-24,2024-03-07,1727,9.5,Future Systems -AI05495,AI Software Engineer,296283,JPY,32591130,EX,CT,Japan,L,Egypt,50,"Git, SQL, Computer Vision, Mathematics",PhD,13,Media,2024-07-26,2024-08-22,947,7.8,Neural Networks Co -AI05496,NLP Engineer,89935,JPY,9892850,EN,CT,Japan,L,Switzerland,100,"MLOps, Python, Computer Vision, Spark",Master,0,Government,2024-10-12,2024-11-04,2250,8.7,Future Systems -AI05497,Data Analyst,94666,CHF,85199,EN,CT,Switzerland,L,Switzerland,50,"Scala, Tableau, AWS, Computer Vision, TensorFlow",PhD,0,Media,2024-04-28,2024-05-24,1878,6.1,Neural Networks Co -AI05498,Machine Learning Engineer,86209,USD,86209,EN,CT,United States,M,United States,0,"Hadoop, Linux, SQL, NLP, Kubernetes",Bachelor,0,Real Estate,2025-01-12,2025-03-01,1116,8,Digital Transformation LLC -AI05499,Machine Learning Engineer,81814,GBP,61361,EN,FT,United Kingdom,M,United Kingdom,0,"Linux, Azure, Scala",Associate,1,Real Estate,2024-11-22,2024-12-06,1079,8.5,Predictive Systems -AI05500,Data Engineer,122880,EUR,104448,SE,FT,Austria,S,Japan,50,"Scala, Python, Data Visualization, Deep Learning, TensorFlow",PhD,5,Transportation,2024-03-02,2024-05-08,907,5.3,Smart Analytics -AI05501,Data Analyst,161377,CHF,145239,SE,PT,Switzerland,M,Switzerland,0,"Linux, Spark, TensorFlow, Python, Tableau",Associate,5,Government,2025-02-20,2025-03-31,900,9.9,Quantum Computing Inc -AI05502,AI Consultant,64242,JPY,7066620,EN,FL,Japan,S,Japan,0,"Computer Vision, Kubernetes, SQL",Bachelor,1,Real Estate,2024-09-25,2024-11-14,526,6,DeepTech Ventures -AI05503,Robotics Engineer,142995,EUR,121546,SE,CT,Netherlands,M,Ukraine,50,"Computer Vision, Statistics, Kubernetes",Bachelor,5,Government,2024-08-26,2024-10-05,1795,7.9,Autonomous Tech -AI05504,Autonomous Systems Engineer,108977,CAD,136221,SE,PT,Canada,S,Chile,50,"Azure, Computer Vision, NLP, SQL, Mathematics",PhD,7,Education,2025-04-17,2025-06-25,1497,5.4,Predictive Systems -AI05505,Deep Learning Engineer,32809,USD,32809,EN,PT,China,M,China,50,"Statistics, Python, Tableau, Docker, AWS",Bachelor,1,Transportation,2025-01-22,2025-03-08,1052,5.1,Machine Intelligence Group -AI05506,Computer Vision Engineer,236299,GBP,177224,EX,PT,United Kingdom,L,United Kingdom,0,"PyTorch, SQL, Data Visualization, Hadoop",Bachelor,13,Automotive,2024-05-20,2024-07-28,1337,9.6,Future Systems -AI05507,Machine Learning Engineer,133957,USD,133957,MI,CT,Norway,M,Norway,100,"Tableau, Kubernetes, Python, Deep Learning, Azure",Bachelor,3,Transportation,2024-04-29,2024-05-29,1599,8.3,AI Innovations -AI05508,Data Scientist,62909,GBP,47182,EN,PT,United Kingdom,L,United Kingdom,0,"Computer Vision, GCP, MLOps, Statistics, Deep Learning",Bachelor,0,Technology,2025-01-19,2025-03-07,928,8.7,Machine Intelligence Group -AI05509,Machine Learning Engineer,147022,SGD,191129,EX,CT,Singapore,S,Singapore,100,"SQL, PyTorch, NLP, Docker",PhD,15,Manufacturing,2024-12-03,2025-01-02,679,8.9,Neural Networks Co -AI05510,Machine Learning Engineer,144913,EUR,123176,SE,FL,France,L,France,50,"Data Visualization, Git, Spark, Computer Vision",Associate,8,Technology,2025-04-19,2025-06-05,578,8.9,Cognitive Computing -AI05511,AI Specialist,45877,USD,45877,SE,FT,India,M,India,0,"Python, Docker, GCP",PhD,7,Automotive,2024-08-28,2024-09-29,1780,9.7,Algorithmic Solutions -AI05512,Principal Data Scientist,33228,USD,33228,EN,FT,China,S,China,100,"Kubernetes, SQL, Git, Statistics",Associate,1,Media,2024-06-09,2024-07-03,642,6.8,Cloud AI Solutions -AI05513,Machine Learning Researcher,87357,USD,87357,MI,FL,South Korea,M,South Korea,0,"MLOps, Hadoop, NLP, Mathematics",Bachelor,2,Retail,2024-07-25,2024-09-09,1707,7.2,TechCorp Inc -AI05514,AI Product Manager,57116,USD,57116,EN,FT,Finland,M,Finland,100,"NLP, Java, Spark, Kubernetes",PhD,0,Real Estate,2024-06-16,2024-08-23,2471,8.4,Smart Analytics -AI05515,Machine Learning Engineer,67628,GBP,50721,EN,CT,United Kingdom,L,Philippines,0,"Kubernetes, Java, R, Deep Learning",PhD,1,Transportation,2024-04-22,2024-06-05,1168,6.2,Smart Analytics -AI05516,AI Specialist,51699,JPY,5686890,EN,PT,Japan,S,Japan,0,"Tableau, R, PyTorch",Master,0,Transportation,2024-12-30,2025-03-06,1456,6.5,Cloud AI Solutions -AI05517,AI Research Scientist,158696,USD,158696,EX,PT,Sweden,S,Singapore,0,"Git, TensorFlow, Computer Vision, Linux, Python",PhD,16,Automotive,2024-08-16,2024-09-28,1409,6.4,Predictive Systems -AI05518,AI Specialist,181010,EUR,153859,EX,CT,Austria,L,Austria,50,"Azure, Tableau, Python",Bachelor,18,Retail,2025-01-13,2025-01-31,1209,9.6,DeepTech Ventures -AI05519,ML Ops Engineer,143355,USD,143355,SE,FL,Ireland,M,United States,100,"Python, Kubernetes, NLP",Bachelor,8,Manufacturing,2025-03-02,2025-04-09,973,8.8,AI Innovations -AI05520,Data Scientist,94621,USD,94621,MI,CT,Israel,M,South Africa,100,"Data Visualization, Git, Linux, AWS",Master,2,Consulting,2024-09-25,2024-11-17,1804,6.1,Machine Intelligence Group -AI05521,Data Engineer,50440,USD,50440,SE,FT,China,M,China,100,"SQL, PyTorch, Mathematics, Git",Associate,6,Real Estate,2024-10-24,2024-11-17,1306,6.9,DeepTech Ventures -AI05522,Autonomous Systems Engineer,39850,USD,39850,MI,CT,China,L,China,50,"SQL, Computer Vision, Statistics",Master,4,Energy,2024-07-16,2024-08-30,1706,6.3,Neural Networks Co -AI05523,Data Analyst,129312,USD,129312,SE,CT,Finland,M,Finland,100,"Docker, MLOps, Python, Java, Tableau",PhD,9,Real Estate,2024-12-07,2025-02-11,2388,6.2,DeepTech Ventures -AI05524,ML Ops Engineer,262770,EUR,223355,EX,FT,France,L,Philippines,100,"Git, MLOps, Tableau, Scala, Kubernetes",Bachelor,11,Real Estate,2025-01-22,2025-03-31,942,9.9,Cognitive Computing -AI05525,Principal Data Scientist,95183,JPY,10470130,MI,FT,Japan,S,Japan,100,"Tableau, Python, AWS, TensorFlow, Deep Learning",Associate,3,Consulting,2024-07-23,2024-09-01,1428,9.6,Smart Analytics -AI05526,Data Analyst,40242,USD,40242,MI,PT,India,L,India,0,"PyTorch, Azure, Tableau, Kubernetes, TensorFlow",PhD,2,Telecommunications,2024-07-02,2024-07-24,1322,6.8,Autonomous Tech -AI05527,Machine Learning Researcher,164259,JPY,18068490,EX,FT,Japan,S,Colombia,100,"Docker, Kubernetes, NLP, PyTorch, TensorFlow",Associate,19,Gaming,2024-11-05,2024-11-27,2246,8.8,Advanced Robotics -AI05528,Machine Learning Engineer,102309,USD,102309,SE,FT,Finland,M,Finland,100,"Data Visualization, NLP, Python, Hadoop",Master,8,Education,2024-03-04,2024-05-11,939,7.1,Predictive Systems -AI05529,Head of AI,53973,USD,53973,EN,FL,Ireland,S,Thailand,0,"Python, TensorFlow, MLOps",PhD,0,Technology,2025-02-03,2025-03-05,611,7.2,Cognitive Computing -AI05530,AI Product Manager,54973,USD,54973,SE,FT,India,L,India,0,"Scala, Data Visualization, Azure, PyTorch",PhD,7,Automotive,2024-11-12,2024-12-08,1043,9.6,Digital Transformation LLC -AI05531,NLP Engineer,187522,USD,187522,EX,CT,Finland,S,Finland,0,"Scala, Linux, Spark, PyTorch, MLOps",Bachelor,10,Media,2024-11-27,2024-12-31,1802,7.4,Future Systems -AI05532,NLP Engineer,57683,EUR,49031,EN,CT,Austria,S,Austria,0,"R, GCP, Mathematics, Deep Learning",Bachelor,0,Finance,2024-04-04,2024-04-30,1641,5.4,Cloud AI Solutions -AI05533,AI Architect,78473,USD,78473,MI,FL,South Korea,L,South Korea,50,"Kubernetes, Deep Learning, R, Tableau",Bachelor,3,Automotive,2024-07-31,2024-10-03,1798,5.2,DataVision Ltd -AI05534,Computer Vision Engineer,55008,SGD,71510,EN,CT,Singapore,S,Portugal,100,"Mathematics, Azure, Computer Vision",Bachelor,1,Technology,2024-12-16,2025-02-20,1194,9.6,TechCorp Inc -AI05535,Computer Vision Engineer,76394,USD,76394,EN,FL,Norway,S,Norway,100,"Python, Computer Vision, SQL, Docker",PhD,0,Government,2024-01-16,2024-03-04,2400,8.2,Smart Analytics -AI05536,AI Research Scientist,102251,USD,102251,SE,CT,Finland,M,France,100,"MLOps, NLP, R, Data Visualization",Associate,6,Government,2025-01-07,2025-02-08,1801,6.7,Quantum Computing Inc -AI05537,Head of AI,225096,USD,225096,EX,FT,Ireland,L,Ireland,50,"PyTorch, AWS, TensorFlow, Mathematics, Scala",Master,15,Education,2024-05-01,2024-07-01,726,5.7,DeepTech Ventures -AI05538,Principal Data Scientist,204843,CHF,184359,SE,PT,Switzerland,L,Brazil,100,"PyTorch, Scala, Java",PhD,6,Finance,2025-01-06,2025-02-14,1120,7.8,TechCorp Inc -AI05539,Principal Data Scientist,138580,USD,138580,SE,CT,Norway,M,Norway,50,"R, SQL, PyTorch",Master,6,Education,2024-08-09,2024-10-11,944,6.5,DeepTech Ventures -AI05540,Head of AI,85499,EUR,72674,EN,FL,Netherlands,L,Netherlands,50,"PyTorch, TensorFlow, Hadoop",Associate,1,Finance,2024-03-02,2024-03-27,767,5.8,Algorithmic Solutions -AI05541,Machine Learning Researcher,83346,SGD,108350,EN,CT,Singapore,M,Singapore,100,"NLP, Kubernetes, TensorFlow, Docker",Master,0,Finance,2024-04-10,2024-05-23,723,9.1,DeepTech Ventures -AI05542,NLP Engineer,115766,USD,115766,MI,PT,Norway,S,Norway,50,"Tableau, SQL, Azure, PyTorch",PhD,2,Consulting,2024-08-11,2024-10-17,1493,7.2,DataVision Ltd -AI05543,Data Analyst,205113,USD,205113,SE,CT,Denmark,L,Denmark,50,"Java, Spark, NLP",PhD,7,Gaming,2025-03-18,2025-04-17,1640,7.7,AI Innovations -AI05544,AI Software Engineer,160912,USD,160912,SE,FT,Sweden,L,Sweden,100,"Git, GCP, Hadoop, Azure, Statistics",PhD,6,Finance,2024-02-27,2024-04-22,856,6,Predictive Systems -AI05545,AI Research Scientist,142229,USD,142229,SE,PT,Finland,L,Finland,50,"Statistics, Tableau, Computer Vision, Java, Python",Bachelor,6,Real Estate,2024-02-07,2024-03-19,1243,6,Predictive Systems -AI05546,Deep Learning Engineer,79913,USD,79913,MI,FT,Finland,S,Finland,0,"SQL, AWS, Scala",Bachelor,2,Gaming,2024-04-21,2024-05-21,1381,5.6,Digital Transformation LLC -AI05547,Data Scientist,105268,USD,105268,MI,CT,Denmark,M,Denmark,100,"Kubernetes, GCP, Mathematics, Computer Vision, Hadoop",Master,3,Telecommunications,2024-10-25,2024-12-11,1041,6.4,Neural Networks Co -AI05548,Research Scientist,222239,SGD,288911,EX,CT,Singapore,S,Singapore,100,"Spark, Python, R, Computer Vision",Master,11,Technology,2025-02-22,2025-03-08,1199,9.6,AI Innovations -AI05549,Computer Vision Engineer,95349,USD,95349,MI,PT,Sweden,S,Sweden,100,"R, Statistics, Hadoop",Master,3,Telecommunications,2024-05-08,2024-06-18,913,7.2,AI Innovations -AI05550,Machine Learning Engineer,276306,USD,276306,EX,CT,United States,L,United States,0,"TensorFlow, R, Azure",Associate,13,Government,2024-07-21,2024-09-08,880,7.6,DataVision Ltd -AI05551,Head of AI,86349,USD,86349,MI,FL,Finland,S,Finland,100,"Git, Java, Computer Vision, Mathematics, Spark",Master,2,Transportation,2024-06-24,2024-08-13,744,6.4,Autonomous Tech -AI05552,AI Product Manager,200534,USD,200534,EX,FT,United States,S,Luxembourg,50,"Linux, Kubernetes, Python, Mathematics",Bachelor,15,Manufacturing,2024-07-22,2024-09-01,1411,7.1,Autonomous Tech -AI05553,ML Ops Engineer,130848,GBP,98136,SE,PT,United Kingdom,M,United Kingdom,50,"Tableau, Spark, Python, Computer Vision",Associate,7,Transportation,2024-11-18,2025-01-19,506,8.6,Neural Networks Co -AI05554,ML Ops Engineer,137574,USD,137574,SE,FL,Denmark,M,Denmark,100,"Python, MLOps, Scala",Master,9,Gaming,2024-02-05,2024-03-25,2456,6,AI Innovations -AI05555,AI Research Scientist,64547,EUR,54865,MI,PT,France,S,France,100,"Data Visualization, SQL, Statistics",Bachelor,4,Real Estate,2024-10-06,2024-11-08,1689,5.6,Cloud AI Solutions -AI05556,AI Specialist,220582,CHF,198524,SE,FL,Switzerland,L,Switzerland,50,"Data Visualization, Python, Hadoop, MLOps, TensorFlow",Master,9,Education,2025-04-29,2025-05-30,1189,7.7,Autonomous Tech -AI05557,Machine Learning Engineer,68236,EUR,58001,EN,CT,France,M,France,100,"Docker, Deep Learning, Java",Associate,1,Manufacturing,2024-03-04,2024-04-25,2050,8.7,DeepTech Ventures -AI05558,Machine Learning Engineer,102411,CHF,92170,MI,FT,Switzerland,S,Switzerland,0,"Python, SQL, Linux, Azure",Bachelor,3,Real Estate,2024-03-20,2024-04-10,2337,8.1,Neural Networks Co -AI05559,Data Analyst,98866,JPY,10875260,MI,FL,Japan,S,Japan,50,"Python, Mathematics, Scala",Master,3,Real Estate,2025-04-23,2025-05-20,1232,8.7,DeepTech Ventures -AI05560,AI Research Scientist,71678,USD,71678,EN,CT,Norway,S,Norway,50,"Java, Kubernetes, TensorFlow, GCP, Spark",Bachelor,0,Education,2025-02-21,2025-03-23,2418,8.2,DeepTech Ventures -AI05561,Principal Data Scientist,38368,USD,38368,MI,PT,India,L,Ghana,50,"PyTorch, Java, Docker, Kubernetes, GCP",Master,4,Finance,2024-02-16,2024-04-22,1578,9.7,DataVision Ltd -AI05562,Autonomous Systems Engineer,53056,EUR,45098,EN,PT,Germany,M,Germany,100,"Python, MLOps, NLP, TensorFlow",Associate,0,Automotive,2024-12-27,2025-02-05,1918,6.2,Predictive Systems -AI05563,Research Scientist,77960,USD,77960,MI,FT,Finland,S,India,50,"NLP, Kubernetes, Git",PhD,3,Media,2024-08-25,2024-09-30,2354,5.9,DataVision Ltd -AI05564,Computer Vision Engineer,137750,USD,137750,EX,FL,Israel,S,Israel,50,"Hadoop, TensorFlow, Data Visualization, MLOps",Bachelor,15,Transportation,2024-12-13,2025-01-07,686,9.3,AI Innovations -AI05565,Deep Learning Engineer,70399,USD,70399,EN,PT,Finland,L,Singapore,0,"Spark, SQL, Kubernetes",Master,0,Media,2024-06-06,2024-07-02,885,5.8,TechCorp Inc -AI05566,Data Scientist,81497,USD,81497,EX,CT,China,L,China,50,"Azure, Java, Computer Vision, Kubernetes, R",Bachelor,16,Gaming,2024-06-17,2024-08-04,897,8.5,Future Systems -AI05567,Autonomous Systems Engineer,97979,USD,97979,SE,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, Statistics",Master,5,Education,2024-03-11,2024-05-04,1745,5.1,Cloud AI Solutions -AI05568,Machine Learning Engineer,74733,CHF,67260,EN,FT,Switzerland,M,Switzerland,0,"Linux, GCP, PyTorch",Bachelor,0,Retail,2025-04-07,2025-06-01,2308,9.4,Neural Networks Co -AI05569,AI Consultant,34474,USD,34474,MI,FL,India,S,India,100,"Scala, NLP, Java, R, Kubernetes",Associate,3,Education,2025-01-15,2025-02-05,2489,7.9,Quantum Computing Inc -AI05570,Machine Learning Researcher,138565,EUR,117780,EX,CT,France,S,Vietnam,0,"NLP, Docker, Java",Bachelor,11,Media,2024-05-07,2024-06-08,2445,7.8,Digital Transformation LLC -AI05571,Head of AI,91979,USD,91979,MI,FL,Finland,M,Finland,100,"SQL, Computer Vision, Git, Python, Azure",Master,4,Automotive,2024-01-31,2024-03-17,1365,6.3,Predictive Systems -AI05572,AI Product Manager,156226,CHF,140603,MI,FL,Switzerland,L,Philippines,50,"SQL, R, Python",PhD,3,Energy,2024-07-14,2024-09-15,563,7.9,DataVision Ltd -AI05573,Robotics Engineer,220616,SGD,286801,EX,FL,Singapore,S,United States,0,"Linux, NLP, Kubernetes, Scala, SQL",Master,18,Consulting,2024-04-03,2024-05-22,793,6.6,Neural Networks Co -AI05574,Data Engineer,125635,CHF,113072,MI,FL,Switzerland,S,Switzerland,100,"NLP, Python, Scala, GCP",Master,2,Technology,2024-04-24,2024-06-25,569,8.4,TechCorp Inc -AI05575,Data Scientist,141071,EUR,119910,SE,FL,France,L,Austria,0,"Spark, Azure, SQL",PhD,5,Education,2024-07-09,2024-08-16,1177,9.1,Advanced Robotics -AI05576,NLP Engineer,77457,USD,77457,EN,CT,Ireland,M,France,0,"Azure, Mathematics, Python",Bachelor,1,Real Estate,2025-02-26,2025-03-26,1430,6.1,Machine Intelligence Group -AI05577,Computer Vision Engineer,81274,EUR,69083,MI,FL,Austria,L,Austria,100,"Docker, AWS, GCP, PyTorch, Scala",Associate,4,Energy,2024-03-25,2024-04-22,1457,6.7,Neural Networks Co -AI05578,Robotics Engineer,123555,USD,123555,SE,FT,Ireland,S,Ireland,50,"TensorFlow, Git, NLP",Bachelor,7,Finance,2024-06-28,2024-08-29,2138,6.9,DeepTech Ventures -AI05579,AI Product Manager,107981,USD,107981,SE,PT,Finland,M,Finland,100,"Data Visualization, Python, GCP, MLOps, Deep Learning",Master,9,Finance,2024-09-21,2024-10-28,910,5.2,AI Innovations -AI05580,Research Scientist,91339,USD,91339,EN,PT,Sweden,L,Luxembourg,50,"Hadoop, Kubernetes, Computer Vision, TensorFlow, GCP",Bachelor,0,Finance,2025-01-25,2025-04-04,1507,7.5,DataVision Ltd -AI05581,Principal Data Scientist,137460,CHF,123714,MI,CT,Switzerland,L,Switzerland,50,"Python, Hadoop, Git, TensorFlow, PyTorch",Master,3,Healthcare,2025-04-19,2025-05-25,1966,7.9,Neural Networks Co -AI05582,Data Scientist,104465,USD,104465,MI,PT,Norway,M,Netherlands,0,"Statistics, Git, SQL",Bachelor,2,Finance,2024-10-03,2024-11-12,820,7.7,Autonomous Tech -AI05583,Robotics Engineer,77385,USD,77385,MI,FL,Sweden,S,Spain,100,"Git, GCP, MLOps, Deep Learning, Kubernetes",Associate,3,Transportation,2024-02-29,2024-04-20,1137,7.6,Advanced Robotics -AI05584,Machine Learning Engineer,26283,USD,26283,EN,FT,China,S,Colombia,50,"Python, TensorFlow, Kubernetes, PyTorch",PhD,0,Energy,2025-03-31,2025-05-10,714,8.6,Predictive Systems -AI05585,Data Scientist,132539,USD,132539,SE,PT,Denmark,M,Denmark,100,"Data Visualization, Kubernetes, Docker",Master,6,Media,2024-11-04,2024-12-05,2172,10,DeepTech Ventures -AI05586,AI Product Manager,59940,EUR,50949,EN,CT,Netherlands,M,Spain,100,"Python, R, Computer Vision, Git, Azure",Bachelor,0,Finance,2025-01-19,2025-03-25,953,6.9,AI Innovations -AI05587,NLP Engineer,308476,USD,308476,EX,FL,Denmark,M,Ukraine,100,"Data Visualization, TensorFlow, Python",Bachelor,13,Education,2024-05-14,2024-06-09,807,6.4,Future Systems -AI05588,Machine Learning Engineer,117756,GBP,88317,SE,FT,United Kingdom,M,United Kingdom,0,"Tableau, Python, Azure, Statistics, Scala",Master,7,Real Estate,2024-12-06,2025-01-28,1370,7.8,TechCorp Inc -AI05589,Robotics Engineer,95582,USD,95582,EN,PT,Norway,M,Norway,50,"TensorFlow, Statistics, Deep Learning",Master,0,Education,2025-01-13,2025-03-11,1148,5,DeepTech Ventures -AI05590,Deep Learning Engineer,152384,USD,152384,MI,CT,Norway,L,Norway,0,"AWS, PyTorch, Linux, GCP, Computer Vision",Associate,4,Energy,2024-08-23,2024-09-30,2279,7.3,Machine Intelligence Group -AI05591,Data Engineer,149481,USD,149481,SE,CT,Denmark,S,Indonesia,0,"MLOps, Tableau, Hadoop, SQL, R",Master,7,Automotive,2024-05-31,2024-08-10,1674,5.9,DataVision Ltd -AI05592,Robotics Engineer,133014,CHF,119713,MI,FT,Switzerland,M,Switzerland,0,"Hadoop, Scala, Data Visualization, PyTorch",Bachelor,4,Media,2024-04-24,2024-05-20,1451,6.1,Autonomous Tech -AI05593,Computer Vision Engineer,80242,SGD,104315,MI,FT,Singapore,M,Singapore,100,"SQL, Linux, Python, AWS",Master,3,Real Estate,2024-04-12,2024-06-01,956,7,Future Systems -AI05594,AI Product Manager,71080,USD,71080,EN,FL,United States,M,United States,100,"AWS, Kubernetes, TensorFlow",Bachelor,1,Energy,2024-03-04,2024-04-18,895,8.4,Neural Networks Co -AI05595,Robotics Engineer,158297,USD,158297,EX,FT,Sweden,M,Sweden,100,"MLOps, R, Python",PhD,16,Finance,2024-04-14,2024-06-08,1393,6.1,DataVision Ltd -AI05596,Computer Vision Engineer,64920,AUD,87642,EN,FL,Australia,M,Australia,50,"Deep Learning, Linux, Spark, GCP",Bachelor,1,Retail,2024-02-24,2024-04-02,1085,8.3,DeepTech Ventures -AI05597,AI Research Scientist,82287,USD,82287,SE,FT,South Korea,S,South Korea,0,"Kubernetes, TensorFlow, Deep Learning",Master,5,Energy,2024-08-23,2024-09-20,1089,9.3,DataVision Ltd -AI05598,Data Analyst,108508,USD,108508,MI,FT,Finland,L,Finland,50,"Python, GCP, NLP, Spark",PhD,2,Energy,2025-04-04,2025-06-09,929,9.3,DeepTech Ventures -AI05599,Data Analyst,86007,AUD,116109,MI,PT,Australia,M,Australia,50,"Spark, Docker, Data Visualization",Associate,3,Media,2024-07-25,2024-09-17,992,9.4,DeepTech Ventures -AI05600,Principal Data Scientist,157752,USD,157752,SE,CT,Denmark,M,Denmark,50,"R, Scala, PyTorch, Mathematics",Master,9,Real Estate,2024-08-09,2024-10-10,1080,5.6,Algorithmic Solutions -AI05601,Autonomous Systems Engineer,91594,USD,91594,MI,FL,Finland,M,Hungary,0,"Git, Hadoop, MLOps",Bachelor,3,Finance,2024-05-10,2024-06-11,1794,6.4,Predictive Systems -AI05602,Autonomous Systems Engineer,74217,USD,74217,MI,FL,Finland,M,India,50,"GCP, Tableau, Hadoop",PhD,2,Manufacturing,2024-02-22,2024-04-09,683,5.6,TechCorp Inc -AI05603,AI Research Scientist,284154,GBP,213116,EX,CT,United Kingdom,L,United Kingdom,50,"Linux, Java, Data Visualization",Bachelor,15,Consulting,2024-11-29,2025-01-28,725,6.4,AI Innovations -AI05604,AI Software Engineer,163958,USD,163958,EX,FT,South Korea,L,South Korea,50,"Scala, PyTorch, Data Visualization, MLOps",PhD,13,Manufacturing,2024-11-03,2024-11-23,596,8,TechCorp Inc -AI05605,ML Ops Engineer,62034,CAD,77543,EN,PT,Canada,S,Canada,0,"Linux, SQL, Docker, PyTorch, Deep Learning",Associate,1,Real Estate,2025-01-27,2025-02-18,1422,9.4,Advanced Robotics -AI05606,AI Software Engineer,166512,CAD,208140,EX,FT,Canada,S,Ireland,0,"Python, Java, Computer Vision",Master,10,Consulting,2024-02-19,2024-04-24,624,8.8,Future Systems -AI05607,AI Product Manager,209138,USD,209138,EX,PT,Ireland,L,Ireland,100,"Python, Spark, MLOps",Associate,10,Telecommunications,2024-12-17,2025-02-05,790,8.5,DataVision Ltd -AI05608,AI Product Manager,149550,USD,149550,SE,PT,United States,S,United States,100,"Computer Vision, PyTorch, Spark",PhD,7,Technology,2024-08-13,2024-09-02,2025,6.8,Machine Intelligence Group -AI05609,ML Ops Engineer,162213,EUR,137881,EX,FT,Germany,M,Germany,50,"R, Kubernetes, Docker, Tableau, TensorFlow",Bachelor,14,Government,2024-06-14,2024-08-01,979,6,Smart Analytics -AI05610,Robotics Engineer,179531,USD,179531,EX,CT,Norway,M,Latvia,50,"Kubernetes, Deep Learning, Computer Vision, Java",Bachelor,14,Manufacturing,2024-06-09,2024-08-15,1650,7.2,Algorithmic Solutions -AI05611,Data Analyst,206536,USD,206536,EX,FL,South Korea,M,South Korea,50,"Linux, Python, Git, TensorFlow",PhD,12,Healthcare,2024-01-21,2024-02-10,1380,5.6,DataVision Ltd -AI05612,AI Specialist,33744,USD,33744,SE,FT,India,S,India,100,"TensorFlow, Deep Learning, Computer Vision",Associate,7,Manufacturing,2024-12-16,2025-02-26,1221,5.4,Algorithmic Solutions -AI05613,AI Consultant,60562,USD,60562,EN,PT,Israel,L,France,0,"SQL, Statistics, PyTorch, Deep Learning, R",PhD,1,Healthcare,2025-01-07,2025-02-07,1322,7.6,Advanced Robotics -AI05614,AI Software Engineer,55911,AUD,75480,EN,FL,Australia,M,Australia,0,"Spark, Kubernetes, Linux, Hadoop",PhD,0,Manufacturing,2024-02-28,2024-03-26,1136,5.1,Neural Networks Co -AI05615,Autonomous Systems Engineer,95326,USD,95326,MI,FL,South Korea,L,South Korea,50,"R, Kubernetes, MLOps",Associate,4,Retail,2024-11-29,2025-01-29,953,7,AI Innovations -AI05616,Machine Learning Engineer,185388,JPY,20392680,EX,CT,Japan,L,Japan,0,"TensorFlow, Python, MLOps, Spark",PhD,17,Manufacturing,2024-07-28,2024-09-26,2466,9.2,Predictive Systems -AI05617,Research Scientist,150527,EUR,127948,SE,CT,Netherlands,M,Switzerland,100,"Linux, AWS, Tableau, Docker, Mathematics",PhD,7,Healthcare,2024-12-20,2025-02-10,545,5.5,Quantum Computing Inc -AI05618,ML Ops Engineer,119633,USD,119633,EX,FL,China,M,China,100,"Java, PyTorch, Hadoop, Git",Master,11,Finance,2024-07-22,2024-08-20,2109,7,TechCorp Inc -AI05619,Data Scientist,227078,USD,227078,SE,FL,Norway,L,Norway,50,"Git, Spark, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-06-21,2024-07-11,1035,8,Cloud AI Solutions -AI05620,AI Product Manager,195528,USD,195528,SE,FL,Denmark,M,Argentina,0,"PyTorch, Python, NLP, Azure, Spark",Associate,7,Media,2024-09-27,2024-10-22,532,8,TechCorp Inc -AI05621,Data Scientist,123024,CAD,153780,SE,FL,Canada,M,Canada,100,"Hadoop, Spark, Python, Git",Master,7,Finance,2024-12-21,2025-02-20,1417,5,Smart Analytics -AI05622,Research Scientist,151053,USD,151053,MI,FT,Denmark,L,Philippines,50,"AWS, Kubernetes, SQL",PhD,2,Technology,2024-06-13,2024-07-09,628,8.1,DataVision Ltd -AI05623,AI Architect,116626,JPY,12828860,SE,PT,Japan,S,Japan,50,"Scala, Kubernetes, NLP, Statistics, R",PhD,7,Telecommunications,2024-11-06,2024-12-30,791,7.1,Advanced Robotics -AI05624,ML Ops Engineer,97656,EUR,83008,MI,FL,Austria,M,Austria,100,"Kubernetes, Java, R",PhD,4,Retail,2025-02-20,2025-03-13,2400,8,Digital Transformation LLC -AI05625,Research Scientist,94494,EUR,80320,EN,PT,Netherlands,L,Netherlands,100,"Scala, Spark, Java, Computer Vision, Git",PhD,1,Consulting,2025-04-24,2025-05-13,1566,9.9,DeepTech Ventures -AI05626,ML Ops Engineer,43321,USD,43321,SE,PT,India,L,India,100,"TensorFlow, Azure, Git",Master,9,Telecommunications,2024-09-06,2024-10-04,1763,8.8,DataVision Ltd -AI05627,AI Software Engineer,58243,EUR,49507,EN,FL,Germany,S,Malaysia,100,"Kubernetes, GCP, Computer Vision, MLOps",PhD,0,Energy,2024-11-02,2024-12-16,535,8.6,TechCorp Inc -AI05628,Machine Learning Engineer,106076,USD,106076,SE,FT,Israel,M,Malaysia,0,"GCP, Azure, SQL, Docker",Associate,6,Government,2024-08-06,2024-10-14,830,7.9,DeepTech Ventures -AI05629,Head of AI,124280,USD,124280,SE,CT,Israel,M,Malaysia,100,"Git, Python, Kubernetes, MLOps",Associate,7,Automotive,2024-08-01,2024-08-16,1666,9.3,Machine Intelligence Group -AI05630,Robotics Engineer,237713,GBP,178285,EX,FT,United Kingdom,M,Denmark,50,"Java, TensorFlow, Tableau, NLP, Mathematics",Bachelor,18,Education,2025-02-05,2025-03-04,861,7.6,Autonomous Tech -AI05631,AI Product Manager,133896,USD,133896,SE,FL,Sweden,S,Sweden,50,"Spark, SQL, TensorFlow, Computer Vision, Python",PhD,5,Technology,2024-11-20,2024-12-16,2374,5.1,Algorithmic Solutions -AI05632,AI Software Engineer,116023,JPY,12762530,SE,PT,Japan,M,Japan,0,"Tableau, Hadoop, Python, TensorFlow, Deep Learning",Associate,7,Finance,2024-11-09,2025-01-15,2298,5.3,Cognitive Computing -AI05633,Computer Vision Engineer,96751,USD,96751,MI,CT,United States,S,Indonesia,50,"Data Visualization, Python, Java",Bachelor,4,Energy,2025-02-07,2025-03-04,1001,9,Digital Transformation LLC -AI05634,Computer Vision Engineer,134644,EUR,114447,SE,PT,Austria,L,Brazil,50,"Kubernetes, Data Visualization, Tableau, MLOps, Deep Learning",PhD,8,Media,2025-04-25,2025-06-22,1118,6.3,Advanced Robotics -AI05635,Principal Data Scientist,102778,JPY,11305580,MI,FT,Japan,M,Kenya,50,"Spark, SQL, TensorFlow, Azure",Bachelor,2,Healthcare,2025-01-07,2025-01-27,1080,6.1,AI Innovations -AI05636,AI Product Manager,103788,USD,103788,EN,FT,Norway,M,Norway,100,"Kubernetes, TensorFlow, Azure, Tableau",PhD,1,Transportation,2024-07-09,2024-09-17,2278,9.7,Quantum Computing Inc -AI05637,Machine Learning Researcher,43133,USD,43133,EN,CT,China,L,China,100,"AWS, Hadoop, Deep Learning, PyTorch",Associate,1,Gaming,2025-03-02,2025-05-04,1800,9.8,Quantum Computing Inc -AI05638,Research Scientist,186168,EUR,158243,EX,PT,Germany,S,Germany,100,"SQL, Python, MLOps",Master,10,Healthcare,2024-07-01,2024-08-26,655,7,Algorithmic Solutions -AI05639,AI Specialist,269018,GBP,201764,EX,FT,United Kingdom,M,United Kingdom,0,"Hadoop, Deep Learning, Azure, Python, NLP",Associate,18,Real Estate,2024-08-08,2024-09-02,2032,9,DataVision Ltd -AI05640,AI Software Engineer,168038,USD,168038,SE,FL,Denmark,L,Denmark,100,"Azure, Deep Learning, Python",PhD,6,Media,2024-08-24,2024-11-03,797,9.9,Smart Analytics -AI05641,Machine Learning Engineer,63639,USD,63639,EN,FL,South Korea,M,South Korea,100,"Python, Hadoop, Linux, Computer Vision",Associate,0,Manufacturing,2024-08-08,2024-09-23,816,9.5,Algorithmic Solutions -AI05642,AI Specialist,204416,USD,204416,EX,PT,Israel,L,Canada,50,"AWS, Java, TensorFlow, Azure, SQL",Bachelor,16,Consulting,2024-02-02,2024-03-17,1641,6.1,DataVision Ltd -AI05643,AI Research Scientist,28315,USD,28315,MI,CT,India,S,India,0,"AWS, Scala, R, Git",Bachelor,3,Transportation,2024-10-31,2024-12-09,2250,6.6,Algorithmic Solutions -AI05644,Autonomous Systems Engineer,69096,USD,69096,EN,FL,United States,L,United States,100,"Git, Mathematics, TensorFlow, Linux",Bachelor,0,Consulting,2024-07-01,2024-07-28,804,5.5,Smart Analytics -AI05645,Data Analyst,72148,USD,72148,MI,FL,South Korea,L,South Korea,100,"Kubernetes, Git, MLOps, R, Computer Vision",Associate,2,Education,2025-04-12,2025-05-02,1906,7.6,Cloud AI Solutions -AI05646,Research Scientist,155411,USD,155411,SE,PT,Norway,M,Norway,100,"TensorFlow, Scala, MLOps",Bachelor,9,Gaming,2025-04-17,2025-06-23,835,5.2,TechCorp Inc -AI05647,Autonomous Systems Engineer,119240,USD,119240,MI,FL,Ireland,L,Indonesia,0,"Computer Vision, Data Visualization, Hadoop, Kubernetes, Deep Learning",Master,4,Technology,2024-01-16,2024-02-11,674,6,Smart Analytics -AI05648,Autonomous Systems Engineer,57600,USD,57600,EX,CT,India,S,Vietnam,100,"Hadoop, PyTorch, Spark",Master,10,Real Estate,2025-01-18,2025-02-19,1769,9.1,DeepTech Ventures -AI05649,Computer Vision Engineer,53542,USD,53542,EN,CT,Ireland,S,Ireland,50,"Scala, Azure, Python",PhD,0,Consulting,2025-03-24,2025-04-19,2480,8.8,Smart Analytics -AI05650,AI Consultant,151442,USD,151442,EX,PT,Finland,L,Chile,0,"Python, Spark, Computer Vision",PhD,15,Technology,2024-12-17,2025-02-25,2014,9.9,Cognitive Computing -AI05651,Data Analyst,113037,USD,113037,SE,CT,South Korea,S,Vietnam,100,"Kubernetes, PyTorch, GCP",Associate,5,Telecommunications,2024-01-26,2024-03-05,1389,7,Smart Analytics -AI05652,AI Consultant,63321,AUD,85483,EN,PT,Australia,M,Australia,50,"Data Visualization, Computer Vision, Docker, R",PhD,0,Energy,2024-03-27,2024-05-19,2054,6.5,Cloud AI Solutions -AI05653,Head of AI,216696,EUR,184192,EX,PT,Netherlands,L,Argentina,100,"R, SQL, Deep Learning, Spark, Linux",Associate,10,Energy,2024-04-11,2024-05-08,2464,5.3,Autonomous Tech -AI05654,AI Consultant,68832,CAD,86040,MI,CT,Canada,S,Canada,0,"Tableau, Linux, TensorFlow, Data Visualization, Hadoop",Bachelor,3,Telecommunications,2024-01-13,2024-01-29,2000,8.1,Predictive Systems -AI05655,AI Product Manager,125853,JPY,13843830,SE,CT,Japan,L,Japan,50,"Scala, R, Docker, Computer Vision",Bachelor,7,Finance,2024-06-17,2024-08-17,645,5.4,Future Systems -AI05656,AI Architect,90307,USD,90307,MI,FL,South Korea,L,South Korea,100,"Git, SQL, GCP, Azure",PhD,2,Telecommunications,2024-03-06,2024-05-15,1785,8.2,Digital Transformation LLC -AI05657,AI Software Engineer,208536,USD,208536,EX,CT,Norway,L,Norway,0,"Computer Vision, MLOps, Git",Bachelor,11,Consulting,2024-11-30,2025-01-27,1876,9.1,Predictive Systems -AI05658,Data Engineer,79479,USD,79479,SE,PT,China,L,Finland,50,"MLOps, PyTorch, Kubernetes",Master,9,Education,2024-02-12,2024-03-25,861,6,Algorithmic Solutions -AI05659,AI Product Manager,145587,JPY,16014570,SE,FL,Japan,S,Japan,50,"SQL, PyTorch, TensorFlow, Hadoop, Tableau",Bachelor,7,Retail,2025-03-07,2025-03-22,1397,9.9,Autonomous Tech -AI05660,Robotics Engineer,237771,USD,237771,EX,PT,South Korea,L,South Korea,50,"Linux, Python, MLOps",Bachelor,15,Education,2025-02-06,2025-04-20,1107,5.9,Quantum Computing Inc -AI05661,AI Specialist,131882,CHF,118694,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Scala, R",Associate,4,Technology,2024-04-21,2024-05-13,1742,7.2,Predictive Systems -AI05662,Principal Data Scientist,194531,USD,194531,SE,PT,Denmark,L,South Korea,100,"PyTorch, Hadoop, Tableau, Azure, TensorFlow",Associate,5,Finance,2024-07-09,2024-08-12,2058,8.9,Smart Analytics -AI05663,Robotics Engineer,170274,CHF,153247,MI,FL,Switzerland,L,Switzerland,0,"SQL, Kubernetes, Scala, Data Visualization, PyTorch",PhD,3,Consulting,2024-04-28,2024-05-22,1146,9.7,DataVision Ltd -AI05664,AI Architect,238256,GBP,178692,EX,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Java, Tableau, Deep Learning",Master,18,Healthcare,2024-01-28,2024-03-03,1005,7.2,Machine Intelligence Group -AI05665,NLP Engineer,98574,USD,98574,MI,FL,United States,S,United States,50,"GCP, Statistics, Hadoop",PhD,4,Finance,2025-03-30,2025-05-12,916,9.1,Machine Intelligence Group -AI05666,Head of AI,84725,EUR,72016,MI,PT,Germany,L,Germany,50,"Java, Scala, Hadoop, Linux, AWS",Master,3,Energy,2024-06-14,2024-07-27,1296,6.4,Quantum Computing Inc -AI05667,AI Consultant,237420,USD,237420,EX,FL,United States,L,United States,50,"PyTorch, NLP, MLOps, Mathematics, Kubernetes",Associate,17,Energy,2025-04-20,2025-06-04,2368,7.6,DataVision Ltd -AI05668,Research Scientist,94852,SGD,123308,MI,CT,Singapore,M,Singapore,0,"TensorFlow, Scala, Kubernetes, NLP, Python",PhD,3,Media,2024-12-25,2025-01-12,1503,9.1,TechCorp Inc -AI05669,NLP Engineer,53187,EUR,45209,EN,PT,Austria,M,Austria,0,"Python, Docker, NLP",Bachelor,1,Government,2024-10-02,2024-11-02,2170,8.4,Cognitive Computing -AI05670,Head of AI,85325,USD,85325,EN,FT,Norway,L,Norway,100,"MLOps, GCP, Kubernetes, Hadoop, SQL",Bachelor,0,Transportation,2024-10-16,2024-11-24,2270,9.4,Autonomous Tech -AI05671,Data Analyst,84861,EUR,72132,MI,PT,France,M,France,100,"Scala, Hadoop, Computer Vision, Data Visualization",Associate,3,Technology,2025-02-26,2025-04-29,1644,8.7,Autonomous Tech -AI05672,Machine Learning Engineer,110677,EUR,94075,MI,CT,Netherlands,M,Netherlands,0,"PyTorch, Docker, Tableau",Master,4,Consulting,2024-06-30,2024-08-16,500,7.2,Digital Transformation LLC -AI05673,Machine Learning Engineer,55583,EUR,47246,EN,FL,France,S,France,0,"Statistics, PyTorch, R",PhD,0,Healthcare,2024-04-19,2024-05-14,602,8.8,Cloud AI Solutions -AI05674,Deep Learning Engineer,103137,SGD,134078,MI,CT,Singapore,S,United Kingdom,100,"R, GCP, SQL",PhD,3,Gaming,2025-03-18,2025-04-20,546,7.8,AI Innovations -AI05675,Autonomous Systems Engineer,94118,SGD,122353,MI,FT,Singapore,M,Singapore,100,"GCP, Docker, PyTorch, SQL",Bachelor,4,Real Estate,2024-05-23,2024-06-13,1065,6.1,Future Systems -AI05676,AI Product Manager,263320,USD,263320,EX,FL,Ireland,L,Ireland,100,"Data Visualization, Azure, Git, Python, Spark",Bachelor,12,Telecommunications,2025-03-11,2025-05-21,1510,8.9,Predictive Systems -AI05677,Principal Data Scientist,81751,USD,81751,EX,FT,China,S,Indonesia,50,"Statistics, Data Visualization, SQL, Python, Tableau",PhD,19,Real Estate,2024-01-16,2024-03-20,2349,9.8,DeepTech Ventures -AI05678,AI Product Manager,69515,USD,69515,EN,PT,Israel,M,Japan,100,"Python, SQL, Tableau, R, AWS",Master,1,Government,2024-05-14,2024-06-03,1662,6,TechCorp Inc -AI05679,AI Consultant,102539,USD,102539,SE,PT,Ireland,M,New Zealand,50,"Linux, TensorFlow, PyTorch, Data Visualization",Associate,7,Technology,2024-06-29,2024-08-26,1816,9.1,Neural Networks Co -AI05680,AI Consultant,83366,EUR,70861,MI,PT,Germany,M,Germany,50,"Python, Computer Vision, AWS",Associate,3,Telecommunications,2024-11-28,2025-01-28,1453,5.1,Digital Transformation LLC -AI05681,Data Analyst,103994,JPY,11439340,MI,CT,Japan,S,Japan,50,"Linux, Scala, R",Bachelor,3,Energy,2025-04-03,2025-05-27,1046,7.6,TechCorp Inc -AI05682,AI Specialist,63790,USD,63790,EN,PT,Ireland,M,Ireland,0,"SQL, Spark, Computer Vision",Associate,1,Technology,2024-05-14,2024-07-11,1573,8,Algorithmic Solutions -AI05683,Computer Vision Engineer,223100,EUR,189635,EX,PT,Netherlands,S,Thailand,100,"AWS, Data Visualization, Tableau, Hadoop, Statistics",Associate,12,Finance,2024-09-23,2024-11-18,698,6.7,Predictive Systems -AI05684,Robotics Engineer,60827,USD,60827,EN,FT,Sweden,S,Sweden,100,"Scala, Spark, Kubernetes, Docker, NLP",Associate,0,Manufacturing,2024-03-04,2024-03-21,1247,7.5,AI Innovations -AI05685,AI Architect,77717,USD,77717,MI,FT,United States,S,Mexico,0,"Hadoop, Scala, TensorFlow",Master,3,Transportation,2024-03-08,2024-05-13,1519,9.4,Machine Intelligence Group -AI05686,Machine Learning Engineer,97963,USD,97963,MI,CT,South Korea,L,Kenya,100,"Git, TensorFlow, Tableau, Data Visualization",Associate,3,Energy,2024-12-13,2025-01-05,2218,5.8,Cognitive Computing -AI05687,Data Engineer,214315,USD,214315,EX,PT,United States,M,United States,0,"PyTorch, Azure, Kubernetes, Deep Learning, TensorFlow",Associate,18,Media,2024-11-08,2024-12-25,1940,6.2,Quantum Computing Inc -AI05688,Autonomous Systems Engineer,71291,USD,71291,EN,FL,Denmark,M,Denmark,100,"Docker, Scala, AWS, Python",Master,0,Consulting,2024-07-27,2024-08-31,1540,9.6,Quantum Computing Inc -AI05689,Data Scientist,87518,USD,87518,EN,CT,United States,L,Vietnam,0,"AWS, PyTorch, Scala, Hadoop",Bachelor,1,Healthcare,2024-12-13,2025-01-04,906,5.9,AI Innovations -AI05690,Machine Learning Researcher,149558,USD,149558,SE,FL,United States,S,United States,0,"Azure, SQL, TensorFlow, Kubernetes",Bachelor,5,Media,2024-07-27,2024-09-12,2478,7.1,AI Innovations -AI05691,AI Consultant,107945,AUD,145726,MI,FT,Australia,M,Australia,0,"Hadoop, Computer Vision, Kubernetes, Tableau, Azure",PhD,2,Manufacturing,2024-04-25,2024-07-02,2267,5.8,Autonomous Tech -AI05692,Machine Learning Engineer,63957,USD,63957,EX,FT,China,S,Australia,50,"Linux, Tableau, TensorFlow, Computer Vision",PhD,12,Education,2024-02-01,2024-03-24,2482,9.6,Autonomous Tech -AI05693,AI Architect,93563,EUR,79529,MI,CT,Germany,S,Germany,0,"Data Visualization, Python, SQL, Kubernetes",Associate,3,Media,2024-06-24,2024-08-24,953,9,Cloud AI Solutions -AI05694,AI Research Scientist,161134,EUR,136964,SE,FT,France,L,France,100,"R, Data Visualization, Python, Docker",PhD,6,Real Estate,2024-08-04,2024-09-01,2303,5.8,Machine Intelligence Group -AI05695,Principal Data Scientist,212931,CAD,266164,EX,FT,Canada,S,New Zealand,0,"SQL, Linux, Python",Master,12,Technology,2024-04-13,2024-05-18,1452,6.8,TechCorp Inc -AI05696,AI Product Manager,119167,USD,119167,MI,CT,Denmark,M,Denmark,100,"Linux, Azure, MLOps, Kubernetes",Master,2,Automotive,2024-04-27,2024-06-12,1621,9.3,DataVision Ltd -AI05697,Head of AI,102382,USD,102382,EN,FT,Denmark,M,Denmark,100,"Tableau, Spark, NLP, PyTorch, Computer Vision",PhD,1,Government,2025-02-21,2025-05-02,1096,5.2,Predictive Systems -AI05698,AI Specialist,69931,USD,69931,MI,PT,Finland,S,Finland,100,"Kubernetes, GCP, Computer Vision, AWS",PhD,4,Transportation,2025-03-25,2025-05-23,1511,5.2,Predictive Systems -AI05699,Autonomous Systems Engineer,61743,SGD,80266,EN,CT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Tableau",PhD,1,Technology,2024-11-28,2025-01-03,1091,10,Predictive Systems -AI05700,AI Product Manager,70132,AUD,94678,MI,FT,Australia,S,Australia,50,"Scala, Data Visualization, Docker, R",Associate,4,Transportation,2024-01-12,2024-02-23,2242,5.7,Digital Transformation LLC -AI05701,Robotics Engineer,96886,JPY,10657460,MI,FT,Japan,S,Japan,0,"Git, Hadoop, SQL, Python, Kubernetes",Master,3,Consulting,2024-03-13,2024-05-22,1366,8.7,Future Systems -AI05702,AI Research Scientist,200782,EUR,170665,EX,PT,Netherlands,M,Switzerland,50,"Linux, Java, Kubernetes, TensorFlow",PhD,15,Consulting,2025-03-07,2025-05-13,840,5.2,Digital Transformation LLC -AI05703,Data Analyst,23579,USD,23579,EN,FL,India,L,India,50,"Java, PyTorch, Statistics, Deep Learning",Associate,0,Transportation,2025-02-04,2025-03-03,1565,9.2,Cloud AI Solutions -AI05704,NLP Engineer,55614,AUD,75079,EN,PT,Australia,M,Australia,0,"Java, Hadoop, NLP, Linux",Bachelor,1,Consulting,2024-12-16,2025-02-18,2492,8,Algorithmic Solutions -AI05705,AI Product Manager,150781,EUR,128164,SE,FL,Germany,M,Nigeria,100,"Spark, Tableau, Hadoop, Computer Vision",Master,5,Retail,2024-07-22,2024-09-02,1421,5.3,Cognitive Computing -AI05706,AI Specialist,131468,EUR,111748,SE,CT,Austria,L,Luxembourg,0,"Kubernetes, PyTorch, MLOps, GCP, R",Master,8,Technology,2024-12-27,2025-01-31,2220,8.5,Advanced Robotics -AI05707,Deep Learning Engineer,72393,EUR,61534,EN,FT,France,M,France,0,"PyTorch, Kubernetes, SQL, Scala",Bachelor,1,Energy,2024-02-10,2024-03-22,2211,9.4,Cloud AI Solutions -AI05708,NLP Engineer,139017,USD,139017,SE,PT,Sweden,L,Sweden,100,"MLOps, Computer Vision, R, PyTorch",Associate,5,Manufacturing,2025-02-27,2025-05-02,1808,9.8,Autonomous Tech -AI05709,Principal Data Scientist,112229,USD,112229,MI,FL,Denmark,S,Denmark,50,"Scala, GCP, SQL, Hadoop, Data Visualization",Bachelor,4,Technology,2024-03-03,2024-05-13,702,8.6,Digital Transformation LLC -AI05710,ML Ops Engineer,88643,USD,88643,MI,FL,South Korea,M,South Korea,100,"MLOps, Data Visualization, Azure, AWS",Associate,4,Manufacturing,2024-12-20,2025-01-16,2308,7.5,Cognitive Computing -AI05711,Head of AI,119522,USD,119522,MI,CT,Denmark,S,United States,0,"Deep Learning, Docker, Git, Mathematics",Associate,4,Finance,2025-01-09,2025-03-08,1799,5.9,Predictive Systems -AI05712,NLP Engineer,146464,EUR,124494,SE,CT,Netherlands,M,Denmark,100,"MLOps, AWS, SQL",PhD,6,Real Estate,2024-05-24,2024-07-21,2415,9.5,Cloud AI Solutions -AI05713,Data Scientist,98192,CAD,122740,SE,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP, R, Computer Vision",PhD,6,Telecommunications,2024-07-25,2024-08-11,1143,9.1,Cloud AI Solutions -AI05714,Machine Learning Engineer,80479,USD,80479,EN,FT,Norway,L,Norway,100,"Kubernetes, NLP, Spark, Deep Learning",Associate,1,Healthcare,2025-04-26,2025-07-02,1630,8.7,Future Systems -AI05715,Data Engineer,152265,EUR,129425,EX,FT,Netherlands,S,Netherlands,50,"MLOps, Python, Computer Vision, Linux, TensorFlow",Master,12,Media,2025-04-16,2025-05-25,1049,9.7,AI Innovations -AI05716,AI Software Engineer,77835,USD,77835,EN,FT,Norway,S,Norway,0,"Azure, Python, GCP, TensorFlow",PhD,1,Technology,2024-01-10,2024-03-11,1316,5.8,Quantum Computing Inc -AI05717,AI Architect,63922,JPY,7031420,EN,FT,Japan,L,Japan,50,"NLP, Python, TensorFlow, Linux",Master,1,Energy,2025-04-21,2025-05-12,1569,8.7,AI Innovations -AI05718,NLP Engineer,257100,JPY,28281000,EX,FL,Japan,L,Finland,0,"TensorFlow, Tableau, Docker, NLP",Associate,15,Automotive,2025-02-04,2025-04-12,876,9.3,DeepTech Ventures -AI05719,Deep Learning Engineer,88350,USD,88350,MI,FT,Finland,L,China,50,"Python, Linux, Statistics, Computer Vision",Associate,4,Transportation,2024-07-04,2024-08-20,986,7.7,Neural Networks Co -AI05720,AI Specialist,99465,USD,99465,MI,FL,Denmark,S,France,50,"GCP, Data Visualization, Spark, R",Bachelor,4,Government,2025-03-31,2025-05-09,1730,5.3,Algorithmic Solutions -AI05721,NLP Engineer,179088,USD,179088,EX,CT,Norway,S,Romania,50,"Python, SQL, Deep Learning, Git, Docker",Bachelor,14,Media,2024-07-11,2024-07-26,1923,8.1,Predictive Systems -AI05722,Data Engineer,159540,USD,159540,SE,FT,Denmark,L,Denmark,100,"Mathematics, Git, NLP",Associate,6,Energy,2024-10-06,2024-11-16,1350,9,AI Innovations -AI05723,Deep Learning Engineer,37477,USD,37477,MI,FT,India,M,India,50,"Spark, Scala, Linux, Deep Learning, SQL",PhD,2,Automotive,2024-05-24,2024-07-26,2369,9.3,Predictive Systems -AI05724,Research Scientist,133739,SGD,173861,MI,PT,Singapore,L,Russia,0,"Computer Vision, AWS, Kubernetes",Associate,4,Education,2025-02-08,2025-02-28,865,7.1,Advanced Robotics -AI05725,AI Research Scientist,373674,CHF,336307,EX,FT,Switzerland,L,Switzerland,50,"R, Python, Statistics, Scala, Deep Learning",Associate,16,Automotive,2024-04-19,2024-05-21,626,9.6,Cloud AI Solutions -AI05726,Head of AI,57593,USD,57593,MI,PT,South Korea,S,China,100,"Docker, Linux, AWS, Scala",Associate,3,Retail,2024-11-01,2024-12-15,1985,8.3,TechCorp Inc -AI05727,Machine Learning Researcher,62998,USD,62998,SE,FT,China,S,China,0,"Statistics, Scala, NLP, MLOps, Azure",Bachelor,7,Real Estate,2024-12-01,2025-02-01,1256,7.4,Machine Intelligence Group -AI05728,Research Scientist,99028,SGD,128736,SE,CT,Singapore,S,Singapore,100,"Docker, Spark, AWS",PhD,5,Retail,2024-12-26,2025-01-29,1673,9.8,Advanced Robotics -AI05729,Data Analyst,283076,USD,283076,EX,CT,Norway,S,Norway,50,"NLP, Deep Learning, Spark, MLOps",Master,15,Finance,2024-01-19,2024-02-05,1350,7.5,Cloud AI Solutions -AI05730,Data Scientist,77013,USD,77013,MI,FL,South Korea,L,South Korea,0,"Statistics, Mathematics, Java",Master,2,Retail,2024-10-12,2024-11-16,916,7.2,TechCorp Inc -AI05731,Computer Vision Engineer,88457,USD,88457,MI,FT,South Korea,L,South Korea,100,"Python, Kubernetes, Spark, GCP",Master,4,Healthcare,2024-09-01,2024-09-19,2182,5.6,Cognitive Computing -AI05732,Machine Learning Researcher,99330,USD,99330,MI,CT,South Korea,L,South Korea,0,"Computer Vision, GCP, Kubernetes, SQL",Bachelor,4,Government,2024-10-21,2024-11-27,2415,9.3,AI Innovations -AI05733,Data Scientist,65665,USD,65665,EN,CT,Israel,S,Israel,0,"Python, Azure, Statistics",PhD,1,Government,2024-10-29,2024-12-23,1506,7.6,Autonomous Tech -AI05734,AI Architect,92187,USD,92187,MI,FT,Israel,M,Israel,0,"Hadoop, NLP, MLOps",PhD,3,Manufacturing,2024-02-20,2024-04-23,1555,5.9,Smart Analytics -AI05735,ML Ops Engineer,72655,USD,72655,MI,FT,Israel,M,Israel,100,"GCP, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2024-11-02,2024-12-22,1742,6.7,DeepTech Ventures -AI05736,ML Ops Engineer,117047,CAD,146309,SE,FL,Canada,M,Canada,100,"Linux, SQL, Computer Vision, Kubernetes, PyTorch",Bachelor,6,Healthcare,2024-07-03,2024-09-06,2314,9,TechCorp Inc -AI05737,Data Analyst,66295,USD,66295,EN,FT,Israel,L,Israel,50,"GCP, Linux, Spark",Master,1,Media,2025-02-12,2025-04-10,1387,5.2,Neural Networks Co -AI05738,AI Specialist,159977,USD,159977,SE,CT,United States,L,United States,100,"SQL, Docker, Mathematics, Computer Vision, AWS",Associate,9,Finance,2025-04-13,2025-06-13,1434,9,Cognitive Computing -AI05739,ML Ops Engineer,213245,EUR,181258,EX,CT,Netherlands,S,Netherlands,100,"SQL, Hadoop, Tableau",Bachelor,17,Finance,2025-03-21,2025-04-22,1998,9,DeepTech Ventures -AI05740,Head of AI,119945,EUR,101953,EX,CT,Austria,S,United States,50,"Java, SQL, Git, Docker",PhD,10,Transportation,2024-02-13,2024-03-11,1193,6.3,Algorithmic Solutions -AI05741,Robotics Engineer,216153,USD,216153,EX,PT,Finland,L,Nigeria,100,"TensorFlow, Python, Data Visualization, Statistics",Master,10,Retail,2024-07-03,2024-07-22,2438,8.4,Smart Analytics -AI05742,Data Analyst,40020,USD,40020,MI,FT,India,L,India,50,"Python, SQL, Computer Vision, Git, Linux",Master,4,Healthcare,2025-03-14,2025-05-26,666,5.6,Neural Networks Co -AI05743,AI Architect,92086,CAD,115108,MI,CT,Canada,L,Switzerland,0,"NLP, Kubernetes, Python, Git",PhD,2,Consulting,2024-04-28,2024-06-23,1486,8.5,Predictive Systems -AI05744,AI Product Manager,200654,GBP,150491,EX,FT,United Kingdom,M,Luxembourg,100,"Git, Java, Scala",Master,19,Consulting,2024-12-13,2025-02-04,1872,9.7,TechCorp Inc -AI05745,Computer Vision Engineer,68829,USD,68829,EN,CT,United States,S,United States,100,"Scala, Hadoop, TensorFlow",PhD,1,Gaming,2024-10-27,2024-12-04,1492,9.3,Cognitive Computing -AI05746,Head of AI,197686,USD,197686,EX,CT,Norway,M,Norway,50,"Kubernetes, Docker, Data Visualization, Git, Hadoop",PhD,17,Energy,2024-03-03,2024-04-24,2251,5.2,Advanced Robotics -AI05747,AI Product Manager,165557,USD,165557,EX,PT,Finland,M,Finland,0,"TensorFlow, Spark, Tableau, Computer Vision, MLOps",Associate,12,Retail,2025-03-19,2025-05-30,1803,5.4,Smart Analytics -AI05748,AI Architect,66906,USD,66906,EN,CT,Ireland,S,Argentina,100,"Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-12-13,2025-02-19,1384,8.8,TechCorp Inc -AI05749,AI Software Engineer,59768,USD,59768,EX,FT,China,S,China,100,"SQL, Linux, Git, Mathematics",PhD,16,Consulting,2024-07-11,2024-08-27,793,8.3,Cognitive Computing -AI05750,AI Architect,139169,GBP,104377,SE,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, GCP, Computer Vision, Azure, Kubernetes",Associate,7,Transportation,2024-08-22,2024-09-10,1739,10,Future Systems -AI05751,NLP Engineer,177662,JPY,19542820,EX,FL,Japan,L,Japan,50,"MLOps, Statistics, PyTorch, Spark, Java",PhD,14,Transportation,2025-02-13,2025-03-14,1326,8.3,Machine Intelligence Group -AI05752,ML Ops Engineer,81894,JPY,9008340,MI,FL,Japan,S,Turkey,0,"Python, TensorFlow, Docker, Mathematics",PhD,2,Manufacturing,2024-12-30,2025-01-24,808,9.2,AI Innovations -AI05753,Computer Vision Engineer,213516,USD,213516,EX,PT,Israel,L,Japan,50,"AWS, Docker, Mathematics, Python",Associate,10,Automotive,2024-12-03,2025-02-11,907,7.4,Algorithmic Solutions -AI05754,Deep Learning Engineer,231165,EUR,196490,EX,FL,Austria,M,Sweden,0,"Python, SQL, Azure",Master,17,Energy,2025-02-03,2025-03-01,1994,9.8,Machine Intelligence Group -AI05755,AI Specialist,110726,AUD,149480,SE,PT,Australia,S,Estonia,50,"Deep Learning, Java, NLP",PhD,8,Transportation,2024-04-27,2024-05-14,2129,5.1,Neural Networks Co -AI05756,Research Scientist,83571,USD,83571,EX,PT,China,L,China,50,"MLOps, PyTorch, Git, Scala, Linux",Master,18,Finance,2024-02-25,2024-04-13,2311,8,Predictive Systems -AI05757,NLP Engineer,232736,USD,232736,EX,FT,Denmark,M,Denmark,0,"Hadoop, Deep Learning, NLP, Python, TensorFlow",Master,17,Healthcare,2024-10-06,2024-12-08,577,6.9,Neural Networks Co -AI05758,Robotics Engineer,127623,AUD,172291,SE,CT,Australia,S,Australia,50,"Data Visualization, Kubernetes, Java, Deep Learning, Docker",Bachelor,7,Transportation,2024-09-21,2024-11-05,2226,6.7,TechCorp Inc -AI05759,Computer Vision Engineer,120233,USD,120233,MI,CT,United States,M,United States,100,"Python, R, Tableau, AWS, Hadoop",Bachelor,4,Consulting,2025-01-25,2025-03-04,2398,8.8,Neural Networks Co -AI05760,NLP Engineer,138054,CAD,172568,EX,FL,Canada,M,Canada,0,"Spark, TensorFlow, PyTorch, NLP, Docker",Master,11,Manufacturing,2024-11-10,2024-12-08,2103,10,Machine Intelligence Group -AI05761,AI Specialist,217066,USD,217066,EX,FL,United States,M,Ukraine,100,"GCP, Scala, Data Visualization",PhD,14,Gaming,2025-01-09,2025-02-23,1157,8.5,Algorithmic Solutions -AI05762,Data Analyst,210737,USD,210737,EX,CT,Israel,S,Sweden,50,"Statistics, Mathematics, PyTorch, AWS, Computer Vision",PhD,10,Government,2024-01-22,2024-04-03,2498,8,Machine Intelligence Group -AI05763,Research Scientist,69613,SGD,90497,EN,PT,Singapore,L,Singapore,50,"Python, GCP, Azure",Master,1,Automotive,2024-03-22,2024-05-16,1729,8.4,Algorithmic Solutions -AI05764,AI Product Manager,93437,USD,93437,MI,FL,Finland,M,Finland,50,"Kubernetes, Python, Mathematics, Docker",PhD,3,Healthcare,2025-01-03,2025-02-24,1095,9.6,Future Systems -AI05765,AI Architect,111139,CHF,100025,MI,FT,Switzerland,M,Czech Republic,100,"Kubernetes, Azure, Data Visualization, Python",Bachelor,2,Retail,2024-01-28,2024-03-14,690,7.8,TechCorp Inc -AI05766,AI Architect,91789,EUR,78021,SE,CT,France,S,Belgium,50,"NLP, SQL, Python, TensorFlow",PhD,6,Manufacturing,2024-07-01,2024-07-21,2003,7.1,TechCorp Inc -AI05767,Deep Learning Engineer,103244,AUD,139379,SE,CT,Australia,M,Australia,50,"Python, TensorFlow, Spark, GCP",Bachelor,5,Finance,2024-07-21,2024-08-08,601,6.1,Future Systems -AI05768,Data Analyst,134116,USD,134116,SE,CT,South Korea,L,South Korea,50,"GCP, Git, Java",Associate,9,Retail,2024-07-27,2024-09-22,2148,9.4,Autonomous Tech -AI05769,Machine Learning Engineer,97581,USD,97581,EX,FT,China,M,China,50,"Spark, AWS, Deep Learning",Associate,10,Retail,2024-06-18,2024-07-12,1179,8.8,Neural Networks Co -AI05770,Autonomous Systems Engineer,62705,USD,62705,SE,FT,China,M,China,100,"Java, PyTorch, AWS, Spark",Associate,8,Media,2024-05-11,2024-06-07,1072,6.8,Autonomous Tech -AI05771,Principal Data Scientist,101330,EUR,86131,MI,CT,Netherlands,M,Netherlands,100,"Kubernetes, AWS, Spark, Computer Vision",Bachelor,2,Retail,2024-12-07,2025-02-01,2469,8.4,Algorithmic Solutions -AI05772,Deep Learning Engineer,96335,USD,96335,MI,FT,Norway,M,Norway,0,"Linux, AWS, Git, Scala",Associate,4,Gaming,2024-06-16,2024-08-18,1862,6.3,Digital Transformation LLC -AI05773,Research Scientist,139068,USD,139068,MI,CT,Norway,L,Norway,50,"PyTorch, Spark, TensorFlow, Deep Learning",Master,4,Telecommunications,2024-10-10,2024-10-25,1147,9.1,Algorithmic Solutions -AI05774,AI Architect,70157,USD,70157,EN,FL,United States,S,Vietnam,100,"Spark, Python, Docker, Tableau",PhD,0,Media,2024-08-31,2024-11-12,623,9.2,Algorithmic Solutions -AI05775,AI Specialist,74222,EUR,63089,MI,CT,Germany,M,Ireland,50,"Data Visualization, Tableau, Computer Vision",Associate,3,Consulting,2024-03-27,2024-04-20,1609,8.5,Quantum Computing Inc -AI05776,Autonomous Systems Engineer,53889,USD,53889,SE,CT,India,M,India,50,"NLP, Python, PyTorch, AWS",PhD,9,Manufacturing,2024-12-13,2025-02-06,1295,7.1,TechCorp Inc -AI05777,AI Consultant,59745,AUD,80656,EN,PT,Australia,S,Australia,0,"AWS, Data Visualization, Linux",PhD,1,Real Estate,2025-01-21,2025-03-04,2003,6.5,Smart Analytics -AI05778,Machine Learning Engineer,93809,USD,93809,MI,CT,Denmark,M,Denmark,0,"SQL, PyTorch, GCP, R, Linux",Bachelor,4,Government,2024-09-07,2024-10-10,500,8.2,Predictive Systems -AI05779,Research Scientist,56388,EUR,47930,EN,FL,Austria,L,South Korea,100,"Data Visualization, Computer Vision, GCP, TensorFlow, Tableau",Associate,1,Real Estate,2024-05-20,2024-07-16,733,8.8,Smart Analytics -AI05780,Machine Learning Researcher,73376,USD,73376,EX,FT,China,S,China,0,"Computer Vision, Git, Hadoop, NLP, Linux",PhD,16,Energy,2024-06-18,2024-07-02,1032,5.5,Digital Transformation LLC -AI05781,NLP Engineer,246014,USD,246014,EX,PT,Finland,L,Finland,0,"AWS, Kubernetes, Git, Java",Bachelor,11,Education,2024-03-09,2024-04-11,1900,8.7,DataVision Ltd -AI05782,Data Engineer,75181,CAD,93976,MI,FT,Canada,M,Canada,100,"Spark, NLP, Python, TensorFlow",Master,4,Finance,2024-12-06,2025-02-06,936,9.9,Cloud AI Solutions -AI05783,Research Scientist,175703,USD,175703,EX,PT,Israel,M,Thailand,0,"Git, Spark, Data Visualization, SQL",Bachelor,16,Retail,2024-07-18,2024-09-04,1971,8.4,TechCorp Inc -AI05784,Deep Learning Engineer,120364,CAD,150455,SE,FT,Canada,M,Portugal,100,"NLP, TensorFlow, Scala",PhD,7,Technology,2024-08-23,2024-10-24,635,5.7,DeepTech Ventures -AI05785,Computer Vision Engineer,76445,USD,76445,MI,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Hadoop, NLP, Statistics",Bachelor,2,Government,2024-06-30,2024-08-24,787,9.2,Digital Transformation LLC -AI05786,AI Software Engineer,93159,CHF,83843,EN,PT,Switzerland,M,Switzerland,50,"Scala, Azure, GCP, SQL, Mathematics",PhD,0,Government,2024-10-20,2024-12-20,1154,8.3,Advanced Robotics -AI05787,Machine Learning Researcher,157430,EUR,133816,SE,FT,Germany,L,Italy,0,"SQL, Spark, TensorFlow, Linux",PhD,5,Real Estate,2024-07-15,2024-09-09,1632,9.9,Predictive Systems -AI05788,NLP Engineer,97775,EUR,83109,MI,FL,Germany,L,Germany,100,"Spark, Statistics, Git",Associate,2,Education,2025-01-05,2025-03-17,1419,8.2,Quantum Computing Inc -AI05789,NLP Engineer,59315,USD,59315,EN,FT,Sweden,S,Thailand,50,"R, Linux, Tableau, Kubernetes, AWS",Bachelor,0,Education,2024-05-24,2024-08-01,2125,9.9,Neural Networks Co -AI05790,AI Product Manager,135321,EUR,115023,SE,FT,France,L,France,50,"Hadoop, Python, Mathematics, Data Visualization",Bachelor,8,Transportation,2024-04-17,2024-06-01,1089,8.6,Smart Analytics -AI05791,AI Software Engineer,54243,SGD,70516,EN,PT,Singapore,S,Czech Republic,100,"TensorFlow, Tableau, Mathematics",Bachelor,0,Telecommunications,2024-01-17,2024-02-11,1715,9,Algorithmic Solutions -AI05792,AI Architect,66510,SGD,86463,EN,PT,Singapore,L,Singapore,0,"NLP, Linux, Statistics",Bachelor,0,Government,2025-02-10,2025-04-16,890,8.8,Autonomous Tech -AI05793,Data Engineer,290571,USD,290571,EX,CT,Norway,M,Norway,50,"R, TensorFlow, Git",Bachelor,11,Healthcare,2024-07-26,2024-08-12,1050,5.6,Cognitive Computing -AI05794,Machine Learning Researcher,174210,USD,174210,SE,CT,United States,L,United States,50,"Java, GCP, Hadoop, Deep Learning",Associate,6,Telecommunications,2024-11-09,2024-12-17,718,5.2,DataVision Ltd -AI05795,Autonomous Systems Engineer,187877,USD,187877,SE,FL,United States,L,Latvia,100,"Git, Data Visualization, SQL",PhD,8,Technology,2024-06-23,2024-07-29,1005,7.8,Cognitive Computing -AI05796,AI Product Manager,238675,EUR,202874,EX,CT,Netherlands,M,Netherlands,100,"Git, Data Visualization, Spark, R, Computer Vision",PhD,12,Energy,2025-01-09,2025-02-26,1576,7.2,Algorithmic Solutions -AI05797,Machine Learning Researcher,115479,EUR,98157,SE,CT,France,L,France,100,"Deep Learning, Azure, PyTorch, Kubernetes",Associate,8,Government,2025-01-01,2025-01-19,883,8.1,Algorithmic Solutions -AI05798,AI Consultant,89054,USD,89054,MI,CT,United States,S,United States,0,"Git, SQL, PyTorch",Associate,3,Healthcare,2024-10-22,2024-11-23,1689,9.2,AI Innovations -AI05799,Deep Learning Engineer,161406,USD,161406,SE,CT,Israel,L,Israel,0,"AWS, Computer Vision, MLOps, Python, Mathematics",Master,5,Finance,2024-03-30,2024-06-04,911,6.6,Advanced Robotics -AI05800,AI Research Scientist,64215,GBP,48161,EN,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, Mathematics, GCP, Scala, NLP",Bachelor,0,Automotive,2024-03-30,2024-05-26,1193,5.7,Future Systems -AI05801,Autonomous Systems Engineer,64511,USD,64511,MI,FL,South Korea,M,Vietnam,100,"Python, TensorFlow, Spark, PyTorch",Associate,4,Real Estate,2024-02-19,2024-04-30,1416,8.6,Digital Transformation LLC -AI05802,Autonomous Systems Engineer,126060,USD,126060,EX,CT,China,L,China,50,"Scala, Docker, GCP, Git",Associate,18,Real Estate,2024-06-27,2024-09-04,2144,6.8,Algorithmic Solutions -AI05803,Autonomous Systems Engineer,54920,USD,54920,EN,CT,South Korea,S,Norway,0,"Data Visualization, Python, Docker, Java",PhD,1,Real Estate,2024-03-28,2024-04-22,510,9,DeepTech Ventures -AI05804,AI Research Scientist,266720,GBP,200040,EX,CT,United Kingdom,M,Hungary,0,"Kubernetes, SQL, Docker, Tableau",Bachelor,16,Telecommunications,2024-04-08,2024-05-19,1513,7.1,DeepTech Ventures -AI05805,Principal Data Scientist,54944,AUD,74174,EN,FL,Australia,M,Australia,50,"Azure, Spark, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-02-10,2024-03-08,708,6.3,DeepTech Ventures -AI05806,AI Product Manager,152987,USD,152987,SE,FL,Norway,S,Norway,100,"NLP, MLOps, Data Visualization",Associate,6,Government,2024-03-09,2024-04-10,1687,8.5,Quantum Computing Inc -AI05807,AI Consultant,158814,CHF,142933,SE,CT,Switzerland,M,Switzerland,50,"Azure, Kubernetes, Linux, Docker, Mathematics",Bachelor,8,Retail,2024-12-27,2025-03-10,1650,9.7,Advanced Robotics -AI05808,AI Software Engineer,92910,USD,92910,EX,CT,China,S,India,100,"MLOps, Hadoop, Spark, Deep Learning, Python",Bachelor,15,Consulting,2024-03-19,2024-04-26,1516,8.9,Machine Intelligence Group -AI05809,Autonomous Systems Engineer,209901,USD,209901,EX,CT,Denmark,L,Denmark,50,"Scala, Java, Azure, Deep Learning",Associate,13,Manufacturing,2024-01-05,2024-02-27,761,6.8,Smart Analytics -AI05810,Computer Vision Engineer,82999,AUD,112049,EN,FL,Australia,L,Australia,0,"Scala, Statistics, Data Visualization",Master,0,Telecommunications,2024-05-28,2024-06-23,2391,9.1,TechCorp Inc -AI05811,Computer Vision Engineer,28848,USD,28848,EN,CT,China,L,Ukraine,50,"Docker, Scala, Linux, Java",Bachelor,1,Energy,2024-03-13,2024-05-21,2267,6.6,Autonomous Tech -AI05812,Computer Vision Engineer,65556,AUD,88501,EN,PT,Australia,M,Latvia,100,"Kubernetes, Java, NLP, AWS",Master,1,Gaming,2024-03-11,2024-04-18,1984,7.5,DataVision Ltd -AI05813,Autonomous Systems Engineer,130176,USD,130176,SE,PT,United States,M,United States,0,"TensorFlow, Spark, Git, Java, AWS",Associate,6,Government,2025-01-31,2025-03-08,789,6.5,Predictive Systems -AI05814,Principal Data Scientist,101126,USD,101126,SE,FT,Finland,M,Philippines,0,"Kubernetes, Docker, SQL, PyTorch",Associate,9,Automotive,2025-01-29,2025-04-11,2420,8.2,Future Systems -AI05815,NLP Engineer,116327,USD,116327,SE,CT,United States,S,United States,100,"SQL, MLOps, Java, AWS, TensorFlow",Bachelor,7,Telecommunications,2024-03-03,2024-03-31,1709,7.6,Cloud AI Solutions -AI05816,AI Consultant,70463,EUR,59894,MI,PT,Austria,M,Japan,100,"Scala, Hadoop, Git, Azure, MLOps",Bachelor,3,Healthcare,2024-07-27,2024-08-23,1950,8.2,Autonomous Tech -AI05817,Machine Learning Engineer,66266,CAD,82833,EN,CT,Canada,M,Canada,0,"Tableau, Python, Kubernetes, Mathematics",Bachelor,1,Telecommunications,2024-12-16,2025-01-09,986,8.2,Quantum Computing Inc -AI05818,Head of AI,61462,EUR,52243,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Python, Spark",Associate,1,Manufacturing,2024-08-25,2024-10-14,1730,8.2,Digital Transformation LLC -AI05819,ML Ops Engineer,169366,USD,169366,EX,PT,Sweden,S,Brazil,50,"GCP, Spark, Tableau",Associate,18,Automotive,2024-12-15,2025-02-01,1988,9.5,Quantum Computing Inc -AI05820,Computer Vision Engineer,128994,JPY,14189340,SE,FL,Japan,L,Japan,100,"PyTorch, Mathematics, Azure",Associate,9,Technology,2024-09-19,2024-10-30,1049,7.5,Algorithmic Solutions -AI05821,Machine Learning Engineer,93837,USD,93837,EN,FT,Norway,M,Norway,50,"Scala, AWS, MLOps",PhD,0,Transportation,2025-02-16,2025-04-11,1859,8.1,Advanced Robotics -AI05822,Robotics Engineer,199989,AUD,269985,EX,FL,Australia,M,Australia,50,"Tableau, Azure, NLP, Linux, Python",Master,11,Technology,2024-10-20,2024-12-26,1214,9.7,Digital Transformation LLC -AI05823,Research Scientist,120387,EUR,102329,SE,FL,France,M,France,0,"Linux, SQL, NLP, PyTorch, Hadoop",Associate,8,Finance,2025-01-17,2025-03-22,2031,6.2,Algorithmic Solutions -AI05824,AI Consultant,73237,EUR,62251,EN,CT,Netherlands,M,Netherlands,100,"MLOps, Hadoop, Scala, Computer Vision, TensorFlow",PhD,1,Energy,2024-03-06,2024-04-10,898,7.5,Predictive Systems -AI05825,Robotics Engineer,201799,EUR,171529,EX,CT,Germany,M,Germany,0,"AWS, PyTorch, Mathematics, TensorFlow",Bachelor,19,Gaming,2024-07-28,2024-08-14,1838,9.7,AI Innovations -AI05826,Deep Learning Engineer,134094,USD,134094,EX,FL,South Korea,S,South Korea,100,"Spark, Tableau, SQL, PyTorch, Computer Vision",Bachelor,15,Education,2024-01-08,2024-02-16,1396,5.3,Algorithmic Solutions -AI05827,Machine Learning Engineer,93152,CHF,83837,MI,CT,Switzerland,S,Norway,0,"TensorFlow, AWS, Spark, Statistics",Associate,4,Finance,2024-08-30,2024-09-15,1329,7.2,Cognitive Computing -AI05828,AI Consultant,50681,CAD,63351,EN,FL,Canada,S,Canada,50,"MLOps, Deep Learning, Linux, Hadoop",PhD,0,Education,2024-03-18,2024-04-17,640,6.9,Smart Analytics -AI05829,Autonomous Systems Engineer,153066,EUR,130106,SE,CT,Netherlands,L,Netherlands,0,"Docker, Computer Vision, Azure, Tableau",Associate,7,Education,2025-02-06,2025-04-06,2226,7.4,Smart Analytics -AI05830,Data Scientist,113891,USD,113891,MI,FT,Norway,L,Germany,0,"Docker, Statistics, Git, Spark",Master,4,Healthcare,2024-01-30,2024-03-15,1612,9.8,Digital Transformation LLC -AI05831,Machine Learning Engineer,182667,CAD,228334,EX,FL,Canada,S,Canada,50,"Data Visualization, Scala, Python, Tableau",PhD,19,Education,2024-02-06,2024-03-27,693,8.4,DeepTech Ventures -AI05832,Deep Learning Engineer,85673,USD,85673,SE,CT,South Korea,M,Finland,0,"SQL, Linux, Python",Master,9,Energy,2024-10-15,2024-11-22,2316,8.3,Smart Analytics -AI05833,ML Ops Engineer,141382,USD,141382,MI,PT,Norway,M,South Korea,50,"TensorFlow, Azure, Kubernetes, Deep Learning, MLOps",Bachelor,4,Healthcare,2025-01-15,2025-02-23,1098,6.7,DeepTech Ventures -AI05834,Research Scientist,104303,CAD,130379,SE,FL,Canada,S,Canada,100,"Kubernetes, Git, Hadoop, TensorFlow",Associate,5,Gaming,2024-08-13,2024-09-14,2000,7,Algorithmic Solutions -AI05835,AI Consultant,105290,EUR,89497,SE,CT,Netherlands,S,Netherlands,0,"Java, PyTorch, Azure, GCP",PhD,6,Technology,2024-09-09,2024-10-16,2185,8.7,TechCorp Inc -AI05836,ML Ops Engineer,110705,EUR,94099,MI,FT,Netherlands,L,United Kingdom,50,"Docker, Data Visualization, PyTorch",Master,2,Automotive,2024-05-18,2024-07-20,1968,9.5,Digital Transformation LLC -AI05837,Autonomous Systems Engineer,98458,USD,98458,SE,FT,South Korea,S,South Korea,0,"Spark, R, Java, Mathematics, Azure",Associate,5,Real Estate,2024-08-21,2024-10-15,2455,6,AI Innovations -AI05838,Computer Vision Engineer,80189,CHF,72170,EN,CT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Azure, Hadoop",Associate,0,Automotive,2024-08-28,2024-10-11,2452,6.4,Advanced Robotics -AI05839,AI Consultant,152024,EUR,129220,EX,FT,France,L,Thailand,0,"Deep Learning, MLOps, Linux, Kubernetes",Bachelor,12,Finance,2024-01-17,2024-03-13,2051,6.3,Algorithmic Solutions -AI05840,Computer Vision Engineer,144136,USD,144136,EX,PT,Sweden,S,Egypt,0,"Git, Kubernetes, AWS",Master,15,Media,2024-10-17,2024-11-25,756,9.7,DataVision Ltd -AI05841,Head of AI,68248,USD,68248,EN,FT,Ireland,M,Ireland,100,"PyTorch, Scala, Computer Vision, AWS, Deep Learning",Bachelor,0,Technology,2025-02-24,2025-04-09,1649,6.8,Algorithmic Solutions -AI05842,Autonomous Systems Engineer,162400,CAD,203000,EX,CT,Canada,M,Canada,0,"R, Kubernetes, Linux, Tableau, Hadoop",PhD,18,Education,2024-06-05,2024-07-24,1538,7.5,Cloud AI Solutions -AI05843,Computer Vision Engineer,271814,EUR,231042,EX,CT,Austria,L,Austria,0,"MLOps, SQL, Linux",Bachelor,12,Energy,2024-11-30,2025-01-31,1677,5.9,Neural Networks Co -AI05844,Autonomous Systems Engineer,145196,USD,145196,SE,PT,Israel,L,Israel,50,"R, SQL, Java",Bachelor,7,Telecommunications,2024-04-26,2024-06-04,1164,6.3,Predictive Systems -AI05845,Machine Learning Researcher,204480,EUR,173808,EX,FT,Netherlands,S,Ghana,100,"Docker, Kubernetes, Spark",Master,16,Gaming,2024-08-08,2024-09-10,858,9.8,Digital Transformation LLC -AI05846,Head of AI,60712,EUR,51605,EN,CT,France,M,France,50,"MLOps, Python, Docker",Master,1,Government,2024-04-29,2024-06-30,579,6.3,Predictive Systems -AI05847,AI Research Scientist,142958,CAD,178698,SE,CT,Canada,L,Latvia,50,"Java, SQL, Data Visualization, Docker",Master,8,Education,2024-08-30,2024-10-14,649,5.9,Predictive Systems -AI05848,Deep Learning Engineer,73847,USD,73847,MI,FL,Ireland,S,Ireland,50,"Git, Deep Learning, Data Visualization, Computer Vision",Master,3,Energy,2024-01-17,2024-02-07,834,5.7,AI Innovations -AI05849,Deep Learning Engineer,44043,USD,44043,MI,PT,India,L,India,50,"Git, Azure, Spark, Kubernetes",Bachelor,3,Transportation,2024-06-19,2024-07-04,1303,5.9,Neural Networks Co -AI05850,AI Product Manager,230859,CHF,207773,SE,CT,Switzerland,L,Switzerland,50,"Azure, TensorFlow, Data Visualization, NLP",PhD,5,Retail,2025-04-23,2025-06-02,2335,7.8,Algorithmic Solutions -AI05851,Principal Data Scientist,31387,USD,31387,MI,FT,India,M,India,0,"Mathematics, Tableau, MLOps, SQL, Linux",Master,3,Government,2025-03-02,2025-03-28,1711,5.1,Quantum Computing Inc -AI05852,AI Consultant,69067,CAD,86334,EN,PT,Canada,M,Israel,100,"Python, TensorFlow, PyTorch, AWS",Master,0,Gaming,2024-05-02,2024-07-02,1204,8.2,Predictive Systems -AI05853,Principal Data Scientist,131432,USD,131432,SE,FT,Sweden,S,Canada,100,"Linux, PyTorch, Deep Learning, Python",Master,9,Gaming,2024-10-19,2024-12-12,2263,6.5,Autonomous Tech -AI05854,AI Consultant,83942,USD,83942,MI,CT,Ireland,M,Ireland,0,"Python, Docker, Linux, Kubernetes, Git",Master,4,Automotive,2024-11-29,2025-01-05,1333,9.9,Advanced Robotics -AI05855,AI Specialist,261743,JPY,28791730,EX,CT,Japan,M,Japan,0,"NLP, Scala, Linux",Bachelor,14,Transportation,2024-08-17,2024-09-14,1461,6.8,Machine Intelligence Group -AI05856,Autonomous Systems Engineer,81198,USD,81198,EN,FL,Finland,L,Finland,100,"Hadoop, SQL, Data Visualization, Tableau",PhD,0,Media,2024-08-27,2024-09-15,1880,10,Smart Analytics -AI05857,AI Consultant,99681,JPY,10964910,MI,PT,Japan,M,Japan,100,"Linux, PyTorch, SQL, Java",PhD,2,Consulting,2024-10-01,2024-11-26,2486,5.6,Future Systems -AI05858,Principal Data Scientist,116363,EUR,98909,MI,CT,Netherlands,L,Netherlands,100,"Java, Python, Computer Vision",Bachelor,4,Automotive,2025-02-26,2025-04-21,1595,6.8,Machine Intelligence Group -AI05859,AI Architect,167056,USD,167056,SE,CT,Denmark,S,Denmark,100,"Java, SQL, Data Visualization, Git, Deep Learning",Master,5,Consulting,2024-03-25,2024-04-11,2492,9.8,Machine Intelligence Group -AI05860,AI Architect,44476,EUR,37805,EN,FT,Austria,S,Austria,50,"Java, Kubernetes, Scala, Python",Bachelor,1,Government,2025-01-16,2025-03-04,1671,8.9,Quantum Computing Inc -AI05861,Data Scientist,85390,AUD,115277,EN,PT,Australia,L,Australia,0,"SQL, Azure, Mathematics, AWS",Master,0,Consulting,2024-04-28,2024-05-24,1172,5,Quantum Computing Inc -AI05862,NLP Engineer,151511,CHF,136360,SE,PT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Tableau, Docker",Bachelor,5,Manufacturing,2024-04-23,2024-06-24,2354,9.9,Advanced Robotics -AI05863,AI Product Manager,112471,JPY,12371810,MI,FT,Japan,L,Nigeria,100,"NLP, Azure, AWS",Associate,4,Healthcare,2025-03-30,2025-04-14,809,5.1,DataVision Ltd -AI05864,ML Ops Engineer,172627,CHF,155364,SE,CT,Switzerland,M,Switzerland,0,"NLP, Tableau, Mathematics",Associate,8,Telecommunications,2024-12-10,2024-12-27,1336,6,DeepTech Ventures -AI05865,NLP Engineer,233363,USD,233363,EX,FT,Finland,L,Finland,0,"SQL, Computer Vision, TensorFlow",Master,10,Retail,2024-04-08,2024-05-18,2008,6.6,Cognitive Computing -AI05866,Machine Learning Researcher,116985,EUR,99437,SE,PT,Austria,S,United Kingdom,100,"Mathematics, Git, Docker, SQL",Bachelor,5,Finance,2025-01-11,2025-02-19,2373,7.7,Algorithmic Solutions -AI05867,Computer Vision Engineer,184253,GBP,138190,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Java, Linux",Bachelor,6,Finance,2024-05-01,2024-07-05,2168,7.1,Cloud AI Solutions -AI05868,AI Specialist,118246,USD,118246,MI,FL,Norway,S,Sweden,50,"Linux, SQL, Mathematics",PhD,4,Education,2024-07-12,2024-08-04,1005,7.9,Machine Intelligence Group -AI05869,AI Software Engineer,173631,CHF,156268,SE,FT,Switzerland,L,Austria,100,"MLOps, Git, Azure, NLP, Statistics",Bachelor,5,Real Estate,2025-01-31,2025-03-19,1567,9.5,Digital Transformation LLC -AI05870,Computer Vision Engineer,105596,USD,105596,MI,PT,Finland,L,Finland,0,"Azure, Scala, Java, Kubernetes",Associate,2,Automotive,2024-12-26,2025-01-13,2408,9.6,Autonomous Tech -AI05871,AI Product Manager,239497,USD,239497,EX,CT,Finland,L,Finland,0,"R, Tableau, Kubernetes",PhD,18,Media,2024-04-12,2024-05-03,1848,7.6,Predictive Systems -AI05872,Research Scientist,60880,USD,60880,EN,FT,South Korea,M,Mexico,50,"SQL, Deep Learning, Hadoop, GCP, PyTorch",Master,0,Gaming,2024-02-14,2024-04-08,1842,6.6,Smart Analytics -AI05873,Machine Learning Researcher,192915,CHF,173624,EX,FT,Switzerland,S,Switzerland,50,"MLOps, Azure, Spark, Python, PyTorch",Associate,14,Government,2024-08-06,2024-09-05,1358,9.1,DataVision Ltd -AI05874,NLP Engineer,62398,USD,62398,MI,FT,Israel,S,Israel,0,"AWS, Linux, Deep Learning, R",Bachelor,2,Gaming,2025-03-18,2025-04-08,1025,9.2,Predictive Systems -AI05875,Machine Learning Researcher,87874,USD,87874,MI,CT,Sweden,S,Sweden,0,"Hadoop, NLP, SQL, Kubernetes",Bachelor,2,Healthcare,2024-02-13,2024-03-15,2305,7.8,Future Systems -AI05876,Computer Vision Engineer,76770,GBP,57578,EN,FL,United Kingdom,L,United Kingdom,0,"Python, Azure, SQL",PhD,0,Healthcare,2024-03-21,2024-05-20,669,9.3,Cognitive Computing -AI05877,AI Software Engineer,134200,EUR,114070,SE,CT,France,M,France,0,"Python, TensorFlow, Tableau, SQL",PhD,5,Real Estate,2024-04-15,2024-05-19,1184,8.2,Cloud AI Solutions -AI05878,Machine Learning Engineer,120552,EUR,102469,SE,CT,Netherlands,S,Netherlands,100,"R, Java, AWS, Computer Vision, GCP",Associate,7,Consulting,2024-05-11,2024-06-03,2434,6.5,Smart Analytics -AI05879,AI Specialist,52784,USD,52784,EN,FL,Sweden,S,Sweden,100,"NLP, Kubernetes, SQL, TensorFlow, Tableau",Associate,1,Gaming,2024-07-31,2024-09-23,1275,7.3,Neural Networks Co -AI05880,AI Product Manager,70428,USD,70428,EN,PT,Israel,L,Israel,0,"Hadoop, R, Deep Learning, NLP, GCP",PhD,1,Government,2024-04-25,2024-05-14,1514,8.1,Advanced Robotics -AI05881,Autonomous Systems Engineer,80363,JPY,8839930,MI,CT,Japan,M,France,100,"AWS, Spark, SQL",Associate,3,Transportation,2024-04-04,2024-05-15,1293,5.9,DeepTech Ventures -AI05882,Machine Learning Engineer,168502,CAD,210628,EX,CT,Canada,L,South Africa,0,"Hadoop, Kubernetes, Java, Mathematics",Master,16,Education,2024-08-17,2024-09-23,1036,9.5,Autonomous Tech -AI05883,NLP Engineer,95415,USD,95415,MI,FT,United States,S,United States,50,"Docker, Scala, Git, Tableau, GCP",Associate,2,Technology,2024-08-06,2024-09-26,1802,9.8,TechCorp Inc -AI05884,Principal Data Scientist,57820,GBP,43365,EN,FL,United Kingdom,S,United Kingdom,100,"GCP, SQL, PyTorch",Bachelor,1,Energy,2024-01-18,2024-02-03,1681,9.2,Autonomous Tech -AI05885,AI Consultant,274165,JPY,30158150,EX,FT,Japan,L,Ukraine,100,"Docker, Python, Spark, Git",Master,16,Automotive,2025-01-30,2025-03-16,2388,7.6,Future Systems -AI05886,ML Ops Engineer,242363,USD,242363,EX,FL,Israel,L,Israel,50,"PyTorch, SQL, Linux, Docker, Azure",Bachelor,16,Manufacturing,2024-10-03,2024-10-24,934,8.1,Future Systems -AI05887,AI Consultant,182784,SGD,237619,EX,CT,Singapore,L,Latvia,0,"MLOps, Kubernetes, NLP, Git, Hadoop",Bachelor,18,Media,2024-01-03,2024-02-27,972,5.2,Advanced Robotics -AI05888,AI Architect,76429,SGD,99358,MI,CT,Singapore,S,Singapore,100,"Computer Vision, Hadoop, Tableau, Spark, Data Visualization",Associate,3,Education,2024-05-11,2024-07-12,1395,8.9,Quantum Computing Inc -AI05889,AI Product Manager,66004,USD,66004,SE,FL,China,L,China,50,"Statistics, Python, Data Visualization, MLOps, TensorFlow",Bachelor,7,Media,2024-01-21,2024-02-19,503,6.2,Machine Intelligence Group -AI05890,Principal Data Scientist,151148,GBP,113361,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Docker, Data Visualization, Computer Vision, Azure",Bachelor,7,Manufacturing,2024-10-21,2024-12-30,1588,9.1,Predictive Systems -AI05891,Data Engineer,168460,USD,168460,EX,FT,South Korea,S,Argentina,100,"Docker, Hadoop, Git, PyTorch, Deep Learning",Bachelor,14,Real Estate,2025-01-01,2025-03-05,1317,8.4,Smart Analytics -AI05892,AI Architect,124855,USD,124855,EX,FT,Israel,S,Israel,0,"Git, Python, AWS",Master,16,Education,2024-07-16,2024-09-21,879,6,Machine Intelligence Group -AI05893,Autonomous Systems Engineer,154883,CHF,139395,MI,FT,Switzerland,M,Switzerland,50,"Python, Spark, Kubernetes",PhD,4,Media,2024-10-25,2025-01-05,1623,6.2,Digital Transformation LLC -AI05894,Robotics Engineer,241392,EUR,205183,EX,PT,Austria,L,Austria,50,"Git, GCP, Linux",Associate,18,Gaming,2025-01-11,2025-01-26,2393,7.9,Advanced Robotics -AI05895,AI Specialist,147818,EUR,125645,EX,CT,France,S,Czech Republic,50,"R, Tableau, Kubernetes, SQL, Deep Learning",Bachelor,16,Transportation,2024-05-11,2024-06-26,921,5.9,Quantum Computing Inc -AI05896,Computer Vision Engineer,89182,USD,89182,EN,CT,Ireland,L,Ireland,50,"PyTorch, Hadoop, Python, Deep Learning, MLOps",PhD,0,Media,2025-02-07,2025-03-25,575,6.5,Cognitive Computing -AI05897,Robotics Engineer,48483,USD,48483,EN,FT,South Korea,S,South Korea,50,"Python, Data Visualization, Spark",PhD,1,Automotive,2025-03-07,2025-04-02,1954,6.1,Advanced Robotics -AI05898,Machine Learning Engineer,39290,USD,39290,MI,CT,China,M,Argentina,100,"Scala, Hadoop, NLP",Master,4,Finance,2025-02-08,2025-03-07,2097,9.5,DataVision Ltd -AI05899,Data Analyst,60878,EUR,51746,EN,FT,Austria,L,Austria,50,"Git, Java, TensorFlow, Statistics",Bachelor,1,Energy,2024-09-18,2024-11-01,639,7.1,Autonomous Tech -AI05900,Computer Vision Engineer,232706,JPY,25597660,EX,PT,Japan,S,Japan,50,"Python, TensorFlow, Kubernetes, Azure, Data Visualization",PhD,14,Real Estate,2024-06-23,2024-08-05,1494,6.7,Quantum Computing Inc -AI05901,AI Research Scientist,52076,EUR,44265,EN,PT,Austria,M,Ireland,50,"Statistics, TensorFlow, SQL, MLOps",Bachelor,0,Technology,2024-09-19,2024-10-07,971,8.7,Future Systems -AI05902,Data Engineer,198461,CAD,248076,EX,PT,Canada,M,Canada,50,"Java, Kubernetes, PyTorch, Statistics",Associate,11,Finance,2024-04-16,2024-06-13,580,5.6,Predictive Systems -AI05903,Computer Vision Engineer,37606,USD,37606,EN,PT,China,L,China,100,"AWS, Git, SQL",PhD,0,Telecommunications,2024-04-03,2024-05-26,1982,7.8,Digital Transformation LLC -AI05904,AI Consultant,238598,EUR,202808,EX,FT,France,L,France,100,"Linux, Git, Spark",Master,13,Retail,2025-04-15,2025-05-12,567,9,TechCorp Inc -AI05905,AI Research Scientist,117613,EUR,99971,MI,FL,France,L,France,100,"Azure, Kubernetes, Tableau, Computer Vision, Deep Learning",Master,4,Energy,2024-11-25,2024-12-25,1812,8.4,Quantum Computing Inc -AI05906,AI Product Manager,296254,USD,296254,EX,FT,Norway,S,Norway,0,"Python, TensorFlow, PyTorch, Computer Vision",Bachelor,14,Consulting,2024-09-17,2024-11-04,2170,6.2,Quantum Computing Inc -AI05907,AI Product Manager,118508,EUR,100732,SE,FL,Netherlands,S,Netherlands,50,"Kubernetes, Linux, NLP",Associate,7,Government,2025-03-21,2025-05-21,1770,9.9,Digital Transformation LLC -AI05908,Research Scientist,90559,EUR,76975,MI,FT,Germany,M,Germany,50,"Spark, TensorFlow, Git, Mathematics",Bachelor,3,Telecommunications,2024-11-13,2024-12-23,1180,6.2,Machine Intelligence Group -AI05909,NLP Engineer,194311,JPY,21374210,EX,CT,Japan,M,Japan,0,"MLOps, GCP, AWS, Azure, Git",Associate,11,Retail,2025-02-19,2025-05-01,953,7.7,Advanced Robotics -AI05910,Robotics Engineer,96127,USD,96127,MI,FL,Ireland,S,Ireland,0,"Linux, SQL, Data Visualization, PyTorch",Master,3,Media,2025-01-02,2025-02-18,1209,7.8,Advanced Robotics -AI05911,Research Scientist,237774,AUD,320995,EX,FT,Australia,L,Australia,100,"R, Linux, Mathematics, Java",Bachelor,19,Finance,2025-01-23,2025-02-14,2373,7.3,TechCorp Inc -AI05912,AI Product Manager,114455,JPY,12590050,SE,PT,Japan,S,Russia,50,"GCP, Data Visualization, Scala, PyTorch",Associate,5,Gaming,2024-04-14,2024-06-19,1943,9,Quantum Computing Inc -AI05913,AI Specialist,70786,CHF,63707,EN,CT,Switzerland,S,Switzerland,0,"R, Java, Azure, Computer Vision",PhD,0,Finance,2025-03-20,2025-04-19,699,5.4,Autonomous Tech -AI05914,AI Software Engineer,38502,USD,38502,MI,FL,China,M,China,50,"GCP, PyTorch, Data Visualization, TensorFlow",Associate,3,Manufacturing,2024-07-19,2024-09-11,776,9.1,Neural Networks Co -AI05915,AI Architect,75059,USD,75059,MI,CT,South Korea,S,South Korea,50,"Git, SQL, MLOps, Mathematics",PhD,3,Education,2024-10-14,2024-12-16,988,5.1,Quantum Computing Inc -AI05916,AI Research Scientist,22820,USD,22820,EN,FL,India,M,India,100,"MLOps, PyTorch, Tableau, AWS, Scala",Associate,1,Consulting,2024-01-17,2024-03-15,2336,7.6,Autonomous Tech -AI05917,NLP Engineer,88433,USD,88433,MI,FL,Israel,S,Israel,0,"Computer Vision, Docker, Mathematics, AWS",PhD,4,Gaming,2024-11-30,2025-01-15,1395,5.4,TechCorp Inc -AI05918,AI Product Manager,202400,AUD,273240,EX,PT,Australia,S,Australia,50,"Python, Azure, Deep Learning",Master,14,Telecommunications,2024-12-06,2025-01-03,636,6,TechCorp Inc -AI05919,ML Ops Engineer,158886,EUR,135053,EX,FT,France,S,Chile,50,"Spark, Linux, NLP",Bachelor,15,Gaming,2024-11-08,2025-01-16,1540,9,Autonomous Tech -AI05920,AI Specialist,101963,EUR,86669,MI,CT,Netherlands,L,Netherlands,50,"Data Visualization, SQL, Python, Spark, Deep Learning",Master,2,Education,2025-04-20,2025-05-16,1011,5.9,Advanced Robotics -AI05921,AI Consultant,86650,USD,86650,MI,FT,Finland,M,Finland,50,"Kubernetes, Git, Azure, NLP, Scala",PhD,4,Manufacturing,2024-08-22,2024-10-31,1975,8.3,Smart Analytics -AI05922,AI Software Engineer,263809,AUD,356142,EX,FT,Australia,L,Ghana,50,"Scala, Python, Computer Vision",Master,13,Gaming,2025-04-28,2025-06-15,512,7.1,Algorithmic Solutions -AI05923,AI Architect,92448,USD,92448,MI,CT,United States,M,United States,0,"GCP, R, PyTorch, SQL",Bachelor,4,Gaming,2024-04-06,2024-04-21,501,6.8,Machine Intelligence Group -AI05924,Machine Learning Engineer,209496,JPY,23044560,EX,FL,Japan,S,Japan,100,"TensorFlow, Spark, Computer Vision, Linux",Master,18,Government,2025-02-07,2025-02-25,1382,7.2,Autonomous Tech -AI05925,Robotics Engineer,72371,AUD,97701,MI,CT,Australia,M,Australia,0,"TensorFlow, Docker, Computer Vision, Linux",Master,4,Telecommunications,2024-12-03,2025-01-12,899,6.9,Future Systems -AI05926,AI Consultant,21755,USD,21755,EN,FL,India,S,India,0,"Azure, TensorFlow, Tableau, Mathematics, PyTorch",Associate,0,Finance,2024-11-27,2025-01-21,1420,8.1,Autonomous Tech -AI05927,Data Engineer,92976,USD,92976,MI,PT,Sweden,M,Sweden,0,"Tableau, Mathematics, Scala, Computer Vision",PhD,3,Automotive,2025-03-01,2025-04-16,900,8.9,Algorithmic Solutions -AI05928,Machine Learning Engineer,148362,AUD,200289,SE,CT,Australia,L,Belgium,100,"Python, Deep Learning, Spark, Mathematics",Bachelor,6,Retail,2024-12-27,2025-01-25,841,6.3,DataVision Ltd -AI05929,Data Analyst,50796,AUD,68575,EN,FL,Australia,S,Australia,100,"SQL, Kubernetes, MLOps",PhD,0,Transportation,2025-04-28,2025-06-12,1502,7,Digital Transformation LLC -AI05930,Autonomous Systems Engineer,123224,AUD,166352,SE,CT,Australia,L,Australia,100,"Python, Kubernetes, Data Visualization, Java",PhD,5,Finance,2024-12-08,2025-01-05,2333,8.8,Predictive Systems -AI05931,Principal Data Scientist,230556,JPY,25361160,EX,FT,Japan,M,Japan,100,"Git, SQL, Scala, MLOps",PhD,18,Telecommunications,2025-02-08,2025-03-25,2163,7.1,Autonomous Tech -AI05932,AI Research Scientist,148164,USD,148164,SE,CT,Denmark,M,Denmark,100,"Java, Hadoop, Mathematics",Associate,6,Retail,2025-02-26,2025-03-31,606,8,Advanced Robotics -AI05933,AI Research Scientist,80479,USD,80479,MI,FL,Finland,S,Poland,0,"Linux, Docker, NLP, Kubernetes, Tableau",Master,4,Energy,2024-05-31,2024-07-12,2043,6.1,Machine Intelligence Group -AI05934,Machine Learning Engineer,109612,USD,109612,SE,PT,Sweden,M,Argentina,50,"Python, Data Visualization, Git, Spark, GCP",Bachelor,6,Transportation,2024-06-27,2024-08-13,1783,10,Neural Networks Co -AI05935,Research Scientist,194931,JPY,21442410,EX,FT,Japan,M,Japan,0,"Azure, Python, Computer Vision",Master,10,Media,2024-07-07,2024-09-13,799,5.7,Quantum Computing Inc -AI05936,Head of AI,111273,SGD,144655,SE,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Docker, Data Visualization",Associate,5,Healthcare,2024-10-12,2024-11-19,893,6.7,Cloud AI Solutions -AI05937,Computer Vision Engineer,52668,EUR,44768,EN,FT,Austria,S,Australia,100,"TensorFlow, Kubernetes, GCP",Associate,0,Education,2025-02-17,2025-03-17,2461,7.1,Algorithmic Solutions -AI05938,AI Specialist,190969,EUR,162324,EX,FL,Netherlands,S,Canada,0,"Docker, Java, Mathematics, PyTorch, TensorFlow",Master,14,Media,2024-02-13,2024-03-31,1311,6.6,Advanced Robotics -AI05939,Research Scientist,211110,CHF,189999,EX,FT,Switzerland,S,Switzerland,100,"SQL, Git, Tableau, Statistics",Associate,14,Energy,2025-03-04,2025-05-09,1747,8.1,Cloud AI Solutions -AI05940,Data Scientist,99999,CHF,89999,EN,FL,Switzerland,S,Switzerland,50,"PyTorch, Linux, Hadoop",Associate,0,Real Estate,2025-04-11,2025-05-13,788,9.6,Neural Networks Co -AI05941,AI Software Engineer,108942,USD,108942,MI,CT,Norway,L,Norway,50,"Linux, Kubernetes, Python, TensorFlow",Bachelor,4,Government,2024-12-09,2025-01-16,926,7.4,Neural Networks Co -AI05942,ML Ops Engineer,131962,AUD,178149,SE,CT,Australia,S,Australia,50,"Java, TensorFlow, Docker, GCP",Associate,9,Gaming,2024-03-14,2024-04-20,550,7.8,Predictive Systems -AI05943,Computer Vision Engineer,76651,EUR,65153,MI,FL,Austria,S,Austria,100,"AWS, Tableau, Kubernetes",Associate,2,Consulting,2024-10-07,2024-11-28,2276,9.3,DataVision Ltd -AI05944,Deep Learning Engineer,98325,USD,98325,EN,PT,Norway,L,Sweden,0,"MLOps, GCP, Python, Mathematics, TensorFlow",Master,1,Media,2024-02-23,2024-03-10,534,5.5,Quantum Computing Inc -AI05945,Robotics Engineer,62079,USD,62079,SE,FL,China,M,China,100,"Scala, Git, Kubernetes, SQL",Master,8,Healthcare,2024-03-28,2024-04-23,1221,8.8,Advanced Robotics -AI05946,ML Ops Engineer,95740,USD,95740,EN,CT,Denmark,L,Denmark,0,"NLP, Spark, SQL, Python",Bachelor,1,Gaming,2025-01-20,2025-03-21,1209,6.5,Future Systems -AI05947,AI Product Manager,105725,USD,105725,SE,CT,Finland,S,Norway,100,"Spark, Git, Linux",PhD,6,Telecommunications,2025-02-16,2025-03-11,615,10,Advanced Robotics -AI05948,Robotics Engineer,187160,CHF,168444,SE,PT,Switzerland,M,Sweden,0,"Python, Git, TensorFlow",PhD,9,Gaming,2024-03-19,2024-04-02,2451,8.5,Autonomous Tech -AI05949,Principal Data Scientist,222856,USD,222856,EX,CT,Ireland,M,Ireland,0,"Python, Data Visualization, TensorFlow, Scala",Bachelor,14,Government,2025-04-01,2025-05-13,1792,8.4,AI Innovations -AI05950,Head of AI,73259,USD,73259,MI,FT,South Korea,S,South Korea,0,"Git, Java, Python",Master,2,Finance,2024-04-16,2024-06-28,1797,5.5,DataVision Ltd -AI05951,Data Engineer,117240,USD,117240,SE,PT,Ireland,S,Ireland,50,"GCP, R, Deep Learning, Tableau",Associate,7,Technology,2024-09-19,2024-11-13,2169,6,Algorithmic Solutions -AI05952,AI Product Manager,124299,USD,124299,SE,FT,Finland,M,Finland,50,"TensorFlow, Python, Mathematics, Statistics, AWS",PhD,8,Finance,2024-04-16,2024-05-04,2498,7,Autonomous Tech -AI05953,Robotics Engineer,67930,EUR,57741,EN,PT,Netherlands,S,Netherlands,50,"SQL, AWS, Data Visualization, R",Master,0,Media,2024-11-19,2024-12-12,663,6.2,Machine Intelligence Group -AI05954,NLP Engineer,85388,EUR,72580,EN,FT,Germany,L,Germany,100,"Java, Azure, Hadoop, Spark",Bachelor,1,Finance,2024-03-16,2024-04-17,610,7.8,Advanced Robotics -AI05955,Machine Learning Researcher,42537,USD,42537,EN,CT,South Korea,S,South Korea,50,"GCP, Kubernetes, Python, Azure, Statistics",Bachelor,1,Manufacturing,2025-02-22,2025-04-25,2004,6.3,Neural Networks Co -AI05956,AI Software Engineer,109665,CAD,137081,SE,FT,Canada,M,Canada,100,"Java, Kubernetes, Mathematics",PhD,9,Real Estate,2024-10-03,2024-12-02,2250,7.3,Neural Networks Co -AI05957,Data Scientist,78478,USD,78478,EN,FT,Norway,M,China,50,"Mathematics, Kubernetes, Docker, Azure, Scala",Associate,1,Automotive,2024-06-28,2024-08-16,1775,6,DataVision Ltd -AI05958,Principal Data Scientist,127696,USD,127696,SE,FT,Finland,L,Finland,0,"Azure, Mathematics, Linux, MLOps, Tableau",Master,5,Gaming,2024-08-14,2024-09-26,610,9.3,Neural Networks Co -AI05959,AI Product Manager,75623,USD,75623,MI,PT,South Korea,S,South Korea,0,"Scala, Kubernetes, Git",PhD,3,Transportation,2024-03-03,2024-04-22,2215,9.3,Cognitive Computing -AI05960,Deep Learning Engineer,221113,AUD,298503,EX,FT,Australia,L,Australia,0,"AWS, Spark, MLOps, Python",Master,19,Gaming,2024-11-03,2024-12-24,1616,5.9,TechCorp Inc -AI05961,Deep Learning Engineer,171238,CAD,214048,EX,CT,Canada,L,Canada,50,"PyTorch, Spark, Tableau, MLOps",Bachelor,14,Automotive,2025-02-05,2025-04-08,1948,9.9,Digital Transformation LLC -AI05962,Robotics Engineer,201912,USD,201912,EX,FT,Israel,L,Israel,100,"GCP, R, PyTorch, Spark, Mathematics",PhD,18,Energy,2025-03-11,2025-04-03,1298,5.7,DataVision Ltd -AI05963,AI Research Scientist,205861,USD,205861,EX,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Kubernetes, Azure, Tableau",Bachelor,15,Media,2025-04-16,2025-06-02,1682,7,Cloud AI Solutions -AI05964,Deep Learning Engineer,302543,USD,302543,EX,PT,Norway,L,Norway,0,"Python, Azure, TensorFlow",PhD,12,Automotive,2024-04-26,2024-05-31,582,8.1,Machine Intelligence Group -AI05965,ML Ops Engineer,115521,EUR,98193,MI,PT,Austria,L,Austria,0,"Azure, Git, Scala, Java",PhD,4,Telecommunications,2024-05-11,2024-07-13,2101,9.5,Cognitive Computing -AI05966,Data Engineer,50057,USD,50057,SE,PT,China,M,China,100,"PyTorch, Tableau, TensorFlow, Azure",Bachelor,9,Retail,2024-03-05,2024-05-12,722,9.3,Cloud AI Solutions -AI05967,Computer Vision Engineer,139280,EUR,118388,SE,CT,Austria,M,Austria,0,"GCP, PyTorch, Data Visualization, Statistics, R",Associate,9,Real Estate,2024-07-06,2024-08-12,2434,6.5,Neural Networks Co -AI05968,AI Research Scientist,80202,USD,80202,EN,CT,Denmark,S,Denmark,0,"Spark, SQL, R, Deep Learning",PhD,1,Government,2024-01-15,2024-03-19,1892,8.2,TechCorp Inc -AI05969,Computer Vision Engineer,115152,USD,115152,SE,PT,Ireland,S,Ireland,100,"Spark, Git, NLP",Associate,7,Media,2024-01-15,2024-02-29,1179,7.3,AI Innovations -AI05970,Deep Learning Engineer,104936,SGD,136417,MI,FL,Singapore,M,Singapore,50,"Java, AWS, PyTorch",Associate,3,Automotive,2024-11-07,2025-01-05,1188,6.7,Future Systems -AI05971,Robotics Engineer,292055,USD,292055,EX,PT,Norway,L,Norway,100,"Kubernetes, Git, Computer Vision, Deep Learning, Mathematics",Master,10,Media,2025-01-20,2025-02-08,1589,9.8,Algorithmic Solutions -AI05972,ML Ops Engineer,129611,USD,129611,SE,PT,Sweden,S,Sweden,100,"AWS, Hadoop, NLP",Bachelor,8,Real Estate,2024-03-02,2024-04-23,1529,8.9,Autonomous Tech -AI05973,Computer Vision Engineer,56599,USD,56599,SE,CT,China,L,China,100,"Python, MLOps, Data Visualization, Deep Learning, R",Bachelor,9,Education,2024-11-23,2024-12-13,2269,7.7,Predictive Systems -AI05974,AI Software Engineer,66137,CAD,82671,MI,FL,Canada,S,Italy,0,"Kubernetes, AWS, Azure",PhD,3,Real Estate,2024-02-23,2024-04-28,508,5.8,DeepTech Ventures -AI05975,AI Specialist,83658,CAD,104573,MI,FT,Canada,L,Canada,0,"R, SQL, PyTorch, NLP",PhD,2,Gaming,2025-04-21,2025-05-23,1619,6.4,Autonomous Tech -AI05976,Autonomous Systems Engineer,197361,USD,197361,SE,FL,Denmark,L,Denmark,100,"Statistics, PyTorch, Kubernetes",PhD,7,Finance,2024-02-04,2024-03-26,1427,8.2,TechCorp Inc -AI05977,AI Architect,283431,EUR,240916,EX,PT,Germany,L,Germany,100,"Computer Vision, Kubernetes, R",Associate,19,Technology,2024-01-03,2024-02-29,2104,5,Machine Intelligence Group -AI05978,Head of AI,83530,JPY,9188300,EN,FT,Japan,L,Japan,0,"Spark, Java, Hadoop, Scala",Bachelor,1,Finance,2024-01-02,2024-02-01,629,8,Predictive Systems -AI05979,NLP Engineer,197715,EUR,168058,EX,FL,France,M,France,0,"Python, Linux, Hadoop",Associate,10,Energy,2025-03-05,2025-04-22,2465,8.4,DeepTech Ventures -AI05980,NLP Engineer,88355,EUR,75102,MI,FL,Netherlands,S,Portugal,100,"Data Visualization, Azure, R, MLOps",Master,3,Real Estate,2024-11-27,2024-12-26,2128,7.7,Autonomous Tech -AI05981,Data Analyst,30619,USD,30619,EN,PT,India,L,India,50,"AWS, Linux, Spark, Java",Master,1,Finance,2024-03-27,2024-05-02,1811,9.9,Cloud AI Solutions -AI05982,NLP Engineer,206289,EUR,175346,EX,FL,Austria,S,Netherlands,0,"Scala, MLOps, NLP",Associate,14,Education,2024-09-03,2024-10-03,1611,8.5,Autonomous Tech -AI05983,Head of AI,27137,USD,27137,EN,CT,China,M,Russia,100,"NLP, Git, Hadoop, Computer Vision, Scala",Master,0,Energy,2025-01-14,2025-03-11,1238,5.4,Advanced Robotics -AI05984,Data Engineer,107037,CAD,133796,SE,FL,Canada,M,Canada,0,"GCP, Scala, NLP, Spark",Bachelor,5,Retail,2025-04-30,2025-06-04,2340,6.8,Neural Networks Co -AI05985,NLP Engineer,134388,USD,134388,SE,FL,South Korea,L,Kenya,50,"GCP, Docker, Python",Associate,6,Manufacturing,2024-06-26,2024-08-27,1415,6.3,Cognitive Computing -AI05986,Data Analyst,154970,EUR,131725,SE,PT,Netherlands,M,Netherlands,0,"Tableau, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-02-17,2024-03-25,1795,5.9,Cloud AI Solutions -AI05987,Autonomous Systems Engineer,127560,USD,127560,MI,CT,United States,L,United States,0,"GCP, AWS, Hadoop",Bachelor,4,Healthcare,2024-02-01,2024-02-26,727,6.2,Digital Transformation LLC -AI05988,Head of AI,71171,AUD,96081,EN,FT,Australia,S,Belgium,100,"Git, SQL, Azure, Spark, Scala",PhD,0,Finance,2024-08-20,2024-09-17,608,8.1,Neural Networks Co -AI05989,ML Ops Engineer,249331,USD,249331,EX,FL,United States,M,United States,0,"Scala, Kubernetes, Mathematics, Python",Bachelor,12,Telecommunications,2024-02-20,2024-04-13,1618,8.7,DataVision Ltd -AI05990,Research Scientist,130515,SGD,169670,SE,PT,Singapore,S,Singapore,0,"NLP, Deep Learning, Statistics",Associate,6,Manufacturing,2025-04-01,2025-05-16,2354,7,TechCorp Inc -AI05991,ML Ops Engineer,57678,EUR,49026,EN,FT,Austria,M,Austria,0,"Statistics, TensorFlow, Data Visualization, Mathematics, Computer Vision",Bachelor,1,Government,2024-05-25,2024-07-05,1904,7.2,Cloud AI Solutions -AI05992,AI Product Manager,269938,USD,269938,EX,FL,Denmark,S,Denmark,50,"Python, Kubernetes, MLOps",Master,16,Transportation,2024-02-08,2024-02-28,789,9.6,Algorithmic Solutions -AI05993,Computer Vision Engineer,63932,USD,63932,SE,FL,China,S,China,0,"GCP, MLOps, Hadoop, NLP",Associate,5,Government,2024-09-13,2024-11-14,753,9.6,Smart Analytics -AI05994,Principal Data Scientist,151633,USD,151633,EX,PT,Sweden,S,Philippines,0,"Python, R, Git",PhD,14,Telecommunications,2024-03-24,2024-04-26,1334,6.4,Advanced Robotics -AI05995,AI Research Scientist,149659,EUR,127210,EX,FT,Austria,L,Poland,100,"TensorFlow, Hadoop, Data Visualization, Docker",Master,14,Energy,2024-10-02,2024-12-03,809,9.1,Cloud AI Solutions -AI05996,AI Architect,63919,USD,63919,EX,FL,China,S,Luxembourg,50,"SQL, MLOps, Kubernetes, Azure",PhD,17,Consulting,2025-04-01,2025-05-30,860,5.8,Algorithmic Solutions -AI05997,Head of AI,189843,USD,189843,EX,PT,Denmark,S,Sweden,100,"TensorFlow, Kubernetes, GCP, Statistics, PyTorch",Associate,11,Retail,2024-01-31,2024-03-21,2054,8.8,AI Innovations -AI05998,NLP Engineer,72310,EUR,61464,MI,PT,Germany,M,Philippines,0,"MLOps, SQL, PyTorch, AWS, Linux",Associate,4,Media,2024-04-24,2024-06-16,1435,8.2,Digital Transformation LLC -AI05999,Computer Vision Engineer,90085,GBP,67564,MI,CT,United Kingdom,M,United Kingdom,50,"Linux, Git, R, Python",Associate,3,Government,2024-03-06,2024-04-23,2417,5.2,Cognitive Computing -AI06000,Head of AI,84107,USD,84107,MI,CT,Israel,M,Israel,0,"R, SQL, Computer Vision",Master,3,Retail,2024-05-21,2024-06-30,1588,5.3,Neural Networks Co -AI06001,AI Architect,99493,USD,99493,MI,CT,United States,M,United States,0,"Python, Git, R",PhD,3,Manufacturing,2025-04-12,2025-06-02,1258,6.7,Algorithmic Solutions -AI06002,Computer Vision Engineer,76756,EUR,65243,MI,PT,Netherlands,S,Netherlands,0,"Deep Learning, Python, Linux, SQL",Bachelor,4,Media,2025-01-17,2025-03-16,1000,5.4,Autonomous Tech -AI06003,Robotics Engineer,74296,GBP,55722,EN,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Spark, R, Data Visualization, Git",Master,1,Automotive,2025-03-09,2025-05-16,2465,6.7,Cloud AI Solutions -AI06004,Machine Learning Engineer,139465,JPY,15341150,SE,FT,Japan,L,Japan,100,"Azure, Docker, Java, Computer Vision, AWS",PhD,5,Healthcare,2025-04-02,2025-05-28,1680,5.3,Neural Networks Co -AI06005,Deep Learning Engineer,124464,AUD,168026,MI,CT,Australia,L,Russia,100,"Python, Hadoop, Data Visualization, Scala, Kubernetes",Bachelor,3,Retail,2024-10-20,2024-12-14,2113,8.2,Advanced Robotics -AI06006,NLP Engineer,169364,SGD,220173,SE,FL,Singapore,L,Estonia,0,"PyTorch, SQL, Tableau, TensorFlow, R",Master,7,Consulting,2024-11-08,2025-01-13,2464,6,TechCorp Inc -AI06007,ML Ops Engineer,104092,EUR,88478,MI,FL,France,L,France,50,"NLP, Docker, TensorFlow, Python, Azure",PhD,2,Retail,2025-01-20,2025-03-18,1428,8.3,Algorithmic Solutions -AI06008,AI Architect,236270,SGD,307151,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization",Associate,14,Healthcare,2024-01-02,2024-03-13,1176,6.9,DeepTech Ventures -AI06009,Machine Learning Researcher,127297,EUR,108202,SE,FT,Germany,L,Germany,50,"TensorFlow, Statistics, Computer Vision",Bachelor,8,Healthcare,2024-10-26,2024-12-21,1450,8.5,TechCorp Inc -AI06010,AI Architect,59837,USD,59837,SE,CT,China,S,China,50,"R, Tableau, Python, TensorFlow",PhD,8,Healthcare,2024-12-01,2025-01-26,1409,7.7,Neural Networks Co -AI06011,Head of AI,101553,EUR,86320,MI,PT,Austria,M,Austria,50,"Kubernetes, Linux, Deep Learning, Mathematics, Tableau",PhD,2,Telecommunications,2024-04-20,2024-05-26,1360,8.4,Quantum Computing Inc -AI06012,Data Analyst,308290,USD,308290,EX,PT,United States,L,Singapore,50,"Scala, Linux, SQL, PyTorch",Master,17,Consulting,2025-02-20,2025-03-26,2200,8.4,Smart Analytics -AI06013,Deep Learning Engineer,151359,USD,151359,SE,PT,Sweden,L,Sweden,50,"R, Scala, Statistics, Kubernetes, SQL",Bachelor,5,Retail,2024-10-15,2024-12-18,1006,8.4,Neural Networks Co -AI06014,AI Research Scientist,130025,EUR,110521,SE,FT,Germany,L,Germany,0,"PyTorch, SQL, R, Hadoop, Git",Master,7,Media,2024-02-24,2024-03-09,841,6.9,Future Systems -AI06015,ML Ops Engineer,257725,USD,257725,EX,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Azure",Associate,14,Retail,2024-12-07,2025-01-22,666,5.9,Smart Analytics -AI06016,Data Scientist,71138,USD,71138,EN,FT,Norway,M,Norway,50,"SQL, Python, Data Visualization, Mathematics, Linux",Bachelor,0,Automotive,2024-03-07,2024-04-13,2470,7.2,AI Innovations -AI06017,AI Product Manager,148695,USD,148695,SE,CT,Denmark,S,Denmark,50,"MLOps, AWS, R",Associate,8,Energy,2024-03-12,2024-05-20,705,7.3,Quantum Computing Inc -AI06018,Research Scientist,141557,USD,141557,SE,FL,United States,S,United States,50,"Tableau, MLOps, R, SQL",Associate,8,Automotive,2024-04-22,2024-05-09,1135,6.6,Digital Transformation LLC -AI06019,Data Analyst,38669,USD,38669,SE,CT,India,S,United Kingdom,0,"Tableau, Java, Deep Learning, Python, Mathematics",Bachelor,6,Manufacturing,2024-04-23,2024-05-16,2029,5.5,DeepTech Ventures -AI06020,ML Ops Engineer,68663,USD,68663,MI,PT,Israel,M,Czech Republic,0,"PyTorch, Kubernetes, Git, TensorFlow",Master,4,Finance,2025-04-16,2025-05-28,676,6.5,Digital Transformation LLC -AI06021,AI Specialist,44333,USD,44333,MI,FL,India,L,Canada,50,"Scala, Linux, Python",Master,3,Consulting,2025-02-06,2025-02-27,566,9.2,Cloud AI Solutions -AI06022,AI Architect,142509,USD,142509,SE,CT,Denmark,S,Denmark,100,"Computer Vision, TensorFlow, Mathematics, NLP",Associate,5,Telecommunications,2024-08-23,2024-10-30,1296,6.9,Cloud AI Solutions -AI06023,Robotics Engineer,55014,USD,55014,MI,CT,China,L,Ireland,0,"R, Python, Tableau",PhD,2,Healthcare,2024-08-13,2024-10-02,2362,9.8,Autonomous Tech -AI06024,AI Consultant,195813,JPY,21539430,EX,FL,Japan,M,Turkey,100,"GCP, Python, AWS, SQL, TensorFlow",Associate,14,Automotive,2024-01-05,2024-01-29,2233,8.2,AI Innovations -AI06025,Data Scientist,43954,USD,43954,SE,FL,China,S,Romania,100,"Java, Linux, Mathematics, Data Visualization",PhD,6,Energy,2024-03-29,2024-06-03,1318,7.5,Machine Intelligence Group -AI06026,Autonomous Systems Engineer,99890,CAD,124863,MI,FL,Canada,L,Canada,50,"Git, SQL, Computer Vision",PhD,3,Media,2024-10-13,2024-11-23,1008,6.3,Algorithmic Solutions -AI06027,AI Specialist,178380,JPY,19621800,SE,CT,Japan,L,Japan,0,"Git, MLOps, TensorFlow, Python, Tableau",Bachelor,8,Media,2025-03-26,2025-04-22,1368,6.1,Neural Networks Co -AI06028,Principal Data Scientist,121764,USD,121764,SE,FT,Finland,S,South Africa,100,"GCP, Hadoop, Python, TensorFlow, Kubernetes",Master,8,Media,2024-12-17,2025-01-05,2150,5.6,AI Innovations -AI06029,AI Research Scientist,148778,JPY,16365580,EX,FT,Japan,M,Japan,100,"Linux, Java, Data Visualization, Tableau, Kubernetes",Associate,15,Media,2024-03-28,2024-05-07,966,5.3,Digital Transformation LLC -AI06030,ML Ops Engineer,139963,CHF,125967,SE,PT,Switzerland,S,Portugal,100,"Hadoop, NLP, Java, Computer Vision",Master,9,Real Estate,2024-08-31,2024-10-15,1961,7.4,AI Innovations -AI06031,Deep Learning Engineer,75640,GBP,56730,EN,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, Hadoop, Spark",PhD,1,Finance,2024-09-10,2024-11-13,2183,8,Cloud AI Solutions -AI06032,AI Research Scientist,78384,USD,78384,MI,FL,Ireland,M,Ireland,50,"GCP, Spark, Data Visualization",Associate,3,Transportation,2024-04-30,2024-06-01,712,6.2,DataVision Ltd -AI06033,AI Research Scientist,50999,USD,50999,MI,FL,China,L,China,100,"Python, NLP, Kubernetes",PhD,3,Manufacturing,2024-07-26,2024-08-22,1225,5.9,DeepTech Ventures -AI06034,AI Research Scientist,61119,EUR,51951,EN,FL,Germany,L,South Africa,50,"GCP, Scala, TensorFlow, Python, Mathematics",PhD,0,Media,2025-03-20,2025-04-11,1428,8.5,Neural Networks Co -AI06035,AI Architect,99511,SGD,129364,MI,FT,Singapore,L,Latvia,100,"R, Java, Tableau, Python, Linux",Bachelor,4,Finance,2024-04-19,2024-06-06,2368,6.8,Neural Networks Co -AI06036,Deep Learning Engineer,208119,EUR,176901,EX,PT,Germany,S,Germany,0,"PyTorch, Spark, Scala, Java",Associate,12,Technology,2024-05-13,2024-06-24,2228,7,Predictive Systems -AI06037,NLP Engineer,64737,USD,64737,EN,FL,South Korea,L,Egypt,0,"SQL, NLP, MLOps, GCP, Tableau",Associate,1,Real Estate,2024-09-08,2024-09-24,1189,6.3,Machine Intelligence Group -AI06038,Deep Learning Engineer,85166,USD,85166,EX,PT,China,L,China,0,"Java, PyTorch, Mathematics, AWS",PhD,12,Real Estate,2024-03-16,2024-05-04,1675,6.2,Quantum Computing Inc -AI06039,AI Specialist,132470,EUR,112600,MI,FT,Netherlands,L,Belgium,100,"Deep Learning, Kubernetes, GCP, Statistics, Computer Vision",Bachelor,2,Consulting,2024-10-15,2024-12-27,1763,7,Advanced Robotics -AI06040,AI Product Manager,27118,USD,27118,EN,FL,China,S,China,0,"Data Visualization, Python, TensorFlow, Spark",PhD,1,Consulting,2024-06-20,2024-08-19,2259,8.4,Neural Networks Co -AI06041,Head of AI,189995,EUR,161496,EX,FL,Germany,S,Denmark,100,"Scala, GCP, Java, Linux",PhD,13,Finance,2025-02-25,2025-03-13,2204,9,Machine Intelligence Group -AI06042,NLP Engineer,182291,CAD,227864,EX,FL,Canada,M,Turkey,50,"GCP, Java, SQL, NLP, Docker",PhD,15,Media,2025-04-25,2025-06-06,1075,6.7,DataVision Ltd -AI06043,AI Specialist,58125,AUD,78469,EN,FL,Australia,M,Argentina,100,"Python, Mathematics, TensorFlow, Azure, Linux",Associate,0,Technology,2024-07-24,2024-08-29,751,7.1,DataVision Ltd -AI06044,Deep Learning Engineer,304701,CHF,274231,EX,PT,Switzerland,M,Switzerland,100,"Git, Linux, Tableau",Associate,15,Energy,2024-08-08,2024-10-14,990,7.1,Digital Transformation LLC -AI06045,Machine Learning Engineer,28807,USD,28807,EN,PT,India,L,India,50,"R, Python, Docker",Master,0,Retail,2024-04-06,2024-06-09,2227,8.6,Algorithmic Solutions -AI06046,AI Research Scientist,119295,CHF,107366,MI,FT,Switzerland,S,Switzerland,100,"Mathematics, TensorFlow, NLP, Scala",Master,4,Government,2024-12-20,2025-01-05,1352,6.2,Neural Networks Co -AI06047,Data Engineer,75061,EUR,63802,MI,CT,Germany,S,Germany,100,"Python, Statistics, Linux, Spark, Deep Learning",Master,4,Gaming,2025-03-25,2025-05-31,2222,7.7,DeepTech Ventures -AI06048,Principal Data Scientist,134979,EUR,114732,SE,FL,Austria,M,Netherlands,50,"Mathematics, PyTorch, Tableau, Linux",Master,7,Government,2024-06-11,2024-08-07,1909,8.4,DeepTech Ventures -AI06049,Computer Vision Engineer,138134,GBP,103601,SE,FL,United Kingdom,S,United Kingdom,50,"SQL, Kubernetes, Python",Master,6,Real Estate,2024-02-01,2024-02-28,507,5.4,Smart Analytics -AI06050,Head of AI,71317,USD,71317,EN,PT,Ireland,M,Ireland,100,"Deep Learning, Data Visualization, Linux",Associate,1,Education,2025-04-20,2025-06-20,2132,9.6,AI Innovations -AI06051,Robotics Engineer,238482,JPY,26233020,EX,FL,Japan,S,Japan,100,"Data Visualization, Git, Kubernetes, NLP, Python",Master,17,Manufacturing,2024-02-06,2024-03-01,1858,8.4,Future Systems -AI06052,Computer Vision Engineer,217112,EUR,184545,EX,PT,France,L,France,100,"Mathematics, Python, Azure, Linux",Bachelor,17,Retail,2025-01-11,2025-02-09,2235,7.7,Predictive Systems -AI06053,AI Architect,91189,AUD,123105,MI,FT,Australia,S,Australia,50,"MLOps, Kubernetes, R, SQL",Master,4,Government,2025-03-19,2025-05-24,1179,6,Digital Transformation LLC -AI06054,AI Software Engineer,31432,USD,31432,MI,PT,India,M,India,0,"Python, Statistics, TensorFlow, Kubernetes, Azure",PhD,2,Finance,2025-03-14,2025-04-09,1250,7.7,Future Systems -AI06055,AI Software Engineer,203827,EUR,173253,EX,FL,Austria,L,Austria,100,"PyTorch, Python, TensorFlow, Statistics, Data Visualization",Associate,19,Finance,2024-07-13,2024-09-09,2138,7.5,Predictive Systems -AI06056,Data Engineer,78958,EUR,67114,MI,CT,France,M,Ukraine,50,"Mathematics, Azure, Tableau, NLP",Master,3,Education,2024-07-08,2024-08-17,2012,8.5,TechCorp Inc -AI06057,Robotics Engineer,100020,AUD,135027,SE,FT,Australia,S,Australia,50,"Kubernetes, NLP, R, Computer Vision",PhD,9,Finance,2024-08-15,2024-09-09,1515,8.7,Advanced Robotics -AI06058,AI Consultant,168504,USD,168504,EX,FT,Israel,L,Israel,100,"R, SQL, Hadoop, Docker",Bachelor,17,Government,2024-10-15,2024-11-07,1388,9.3,Machine Intelligence Group -AI06059,Deep Learning Engineer,59253,USD,59253,EN,CT,Finland,S,New Zealand,100,"Kubernetes, Computer Vision, TensorFlow",Bachelor,1,Finance,2024-04-02,2024-06-11,2238,6.6,DataVision Ltd -AI06060,Computer Vision Engineer,74984,USD,74984,EX,FT,China,S,Turkey,50,"Hadoop, Data Visualization, Git",PhD,15,Education,2024-07-14,2024-09-23,1980,8.3,Cloud AI Solutions -AI06061,Robotics Engineer,236625,USD,236625,EX,CT,Finland,M,Portugal,100,"Hadoop, Deep Learning, TensorFlow, SQL",Master,15,Energy,2024-09-07,2024-11-09,1087,6.7,Neural Networks Co -AI06062,AI Product Manager,111066,USD,111066,SE,FT,United States,S,United States,0,"SQL, Scala, MLOps",Master,6,Automotive,2025-03-28,2025-05-29,2442,7.6,Cloud AI Solutions -AI06063,AI Research Scientist,123116,USD,123116,MI,PT,Denmark,M,Denmark,100,"Git, Java, NLP",Master,4,Healthcare,2024-02-03,2024-02-26,694,5.7,Advanced Robotics -AI06064,AI Software Engineer,72971,EUR,62025,EN,CT,Netherlands,S,Finland,50,"Git, AWS, Data Visualization, Java",Bachelor,1,Gaming,2024-11-10,2024-11-28,1884,9,AI Innovations -AI06065,Head of AI,73070,CAD,91338,EN,FL,Canada,L,Canada,100,"Linux, Azure, Python",Bachelor,0,Retail,2024-03-06,2024-05-18,1253,6.3,Advanced Robotics -AI06066,Data Engineer,73301,USD,73301,EN,CT,Israel,M,Ukraine,50,"R, Git, Tableau",PhD,0,Manufacturing,2024-12-07,2025-01-16,1946,9.1,AI Innovations -AI06067,Research Scientist,46090,USD,46090,MI,FT,China,L,China,50,"TensorFlow, Kubernetes, Mathematics, PyTorch, AWS",PhD,3,Media,2024-09-03,2024-10-13,2485,8.4,Digital Transformation LLC -AI06068,Principal Data Scientist,268531,USD,268531,EX,FT,Sweden,L,Sweden,50,"SQL, GCP, Statistics",PhD,11,Media,2025-02-13,2025-04-20,1051,5.8,Autonomous Tech -AI06069,Robotics Engineer,116014,CHF,104413,MI,PT,Switzerland,M,Switzerland,100,"Docker, Hadoop, NLP, Kubernetes, Scala",PhD,3,Manufacturing,2024-08-14,2024-10-07,1865,6.8,Cloud AI Solutions -AI06070,Data Analyst,112161,USD,112161,MI,FT,Sweden,L,Sweden,0,"R, Spark, SQL, GCP",Bachelor,2,Gaming,2024-04-03,2024-05-16,2499,9.1,Predictive Systems -AI06071,AI Specialist,62287,USD,62287,EX,FT,India,L,Luxembourg,100,"Tableau, Computer Vision, GCP, Data Visualization",Associate,17,Automotive,2024-07-12,2024-08-10,2286,6.4,Quantum Computing Inc -AI06072,NLP Engineer,71300,USD,71300,EN,FL,Israel,M,Israel,50,"GCP, Spark, PyTorch",Bachelor,0,Consulting,2024-10-19,2024-11-26,2200,6.2,Future Systems -AI06073,Machine Learning Engineer,65583,USD,65583,MI,PT,Finland,S,Russia,0,"R, Kubernetes, Mathematics",Associate,2,Media,2025-02-21,2025-04-14,733,8.9,Future Systems -AI06074,Autonomous Systems Engineer,175971,EUR,149575,EX,PT,Austria,S,Austria,100,"Kubernetes, Computer Vision, GCP, SQL",Bachelor,11,Retail,2025-03-21,2025-05-23,1930,9.4,DeepTech Ventures -AI06075,Robotics Engineer,29541,USD,29541,MI,PT,India,M,India,0,"Python, Docker, Linux",Master,3,Gaming,2025-04-02,2025-04-20,1449,6.3,Advanced Robotics -AI06076,Computer Vision Engineer,76318,USD,76318,MI,PT,South Korea,M,Norway,0,"PyTorch, Java, TensorFlow",Master,2,Technology,2025-02-08,2025-03-07,1449,7.9,DeepTech Ventures -AI06077,AI Consultant,257587,USD,257587,EX,PT,Denmark,S,Denmark,50,"Hadoop, Linux, Deep Learning, Scala, R",Bachelor,11,Healthcare,2024-02-05,2024-03-09,1770,5.1,Smart Analytics -AI06078,Autonomous Systems Engineer,188465,EUR,160195,EX,CT,Austria,S,Austria,50,"Hadoop, Python, NLP",PhD,12,Healthcare,2024-02-06,2024-03-19,1220,8.7,Cloud AI Solutions -AI06079,Robotics Engineer,106976,USD,106976,MI,CT,Ireland,L,Ireland,50,"Java, Kubernetes, GCP, Deep Learning, MLOps",PhD,4,Consulting,2024-11-30,2025-01-12,1164,8.7,AI Innovations -AI06080,Autonomous Systems Engineer,142983,EUR,121536,EX,CT,Germany,M,Germany,50,"TensorFlow, Mathematics, GCP, Python",Master,13,Technology,2024-06-20,2024-08-16,1906,6.4,Predictive Systems -AI06081,AI Research Scientist,61577,USD,61577,EN,CT,Sweden,S,Israel,100,"Python, Tableau, Kubernetes, Scala",PhD,0,Finance,2025-04-13,2025-05-05,2097,5.8,Autonomous Tech -AI06082,Machine Learning Engineer,89159,AUD,120365,MI,FL,Australia,S,Australia,0,"Git, AWS, Data Visualization, Hadoop, Tableau",PhD,2,Government,2024-02-25,2024-04-05,2019,7.9,Algorithmic Solutions -AI06083,AI Research Scientist,98446,USD,98446,EN,FT,Denmark,M,Denmark,100,"Kubernetes, Linux, Scala, Mathematics, MLOps",Associate,0,Technology,2024-07-13,2024-09-22,2393,6.7,DataVision Ltd -AI06084,Machine Learning Engineer,50109,GBP,37582,EN,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, Kubernetes, NLP",Bachelor,1,Healthcare,2025-01-04,2025-02-18,2307,5.3,Cognitive Computing -AI06085,Machine Learning Researcher,78378,USD,78378,MI,FL,South Korea,S,South Korea,0,"Git, Deep Learning, Kubernetes, SQL",Master,4,Media,2024-06-25,2024-09-06,1328,9.3,DataVision Ltd -AI06086,Deep Learning Engineer,72771,CAD,90964,MI,CT,Canada,S,Canada,50,"PyTorch, TensorFlow, Data Visualization",Associate,4,Automotive,2025-03-24,2025-06-04,2063,6.6,Future Systems -AI06087,Data Engineer,269658,USD,269658,EX,CT,Finland,L,Finland,0,"SQL, Hadoop, R, GCP",Bachelor,18,Consulting,2024-09-14,2024-10-25,2037,5.7,Cognitive Computing -AI06088,ML Ops Engineer,94499,CAD,118124,SE,PT,Canada,S,United Kingdom,50,"Data Visualization, MLOps, Git",PhD,6,Media,2024-06-26,2024-08-21,2299,8.2,TechCorp Inc -AI06089,Autonomous Systems Engineer,98191,EUR,83462,MI,FT,France,M,France,0,"Scala, PyTorch, SQL",Master,2,Gaming,2024-10-23,2024-11-10,1994,6.3,Smart Analytics -AI06090,AI Software Engineer,52424,EUR,44560,EN,FL,France,M,Vietnam,50,"Kubernetes, Docker, Tableau, PyTorch, Java",Bachelor,1,Gaming,2024-02-28,2024-05-08,1715,8.9,DeepTech Ventures -AI06091,AI Consultant,58246,EUR,49509,EN,PT,Germany,M,Belgium,0,"Hadoop, Spark, NLP",Master,1,Transportation,2024-09-06,2024-11-12,859,8.7,Quantum Computing Inc -AI06092,Head of AI,267949,AUD,361731,EX,CT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, Python",Bachelor,10,Telecommunications,2024-03-12,2024-04-30,707,9.7,Machine Intelligence Group -AI06093,Machine Learning Engineer,70389,USD,70389,EN,FT,Sweden,S,Thailand,100,"Hadoop, Computer Vision, NLP, Azure, Spark",Master,0,Media,2025-02-27,2025-04-12,861,6.6,Cloud AI Solutions -AI06094,Computer Vision Engineer,189799,USD,189799,EX,FL,Denmark,M,Denmark,100,"Hadoop, Python, TensorFlow, MLOps",Bachelor,17,Energy,2024-08-16,2024-10-16,1028,8.6,Machine Intelligence Group -AI06095,Deep Learning Engineer,71097,USD,71097,EN,CT,South Korea,L,South Korea,0,"SQL, TensorFlow, GCP",Master,0,Media,2025-04-02,2025-06-13,1765,8.6,Cognitive Computing -AI06096,ML Ops Engineer,129008,GBP,96756,MI,CT,United Kingdom,L,United Kingdom,0,"SQL, Hadoop, MLOps, Git",Master,4,Government,2025-04-15,2025-05-30,1561,10,Algorithmic Solutions -AI06097,Robotics Engineer,75236,EUR,63951,MI,FL,Netherlands,S,Netherlands,0,"MLOps, Spark, Docker",Associate,3,Consulting,2024-08-04,2024-08-30,664,9.2,Machine Intelligence Group -AI06098,Autonomous Systems Engineer,169125,USD,169125,EX,CT,Denmark,S,Denmark,0,"Data Visualization, Spark, PyTorch, Hadoop, Python",Bachelor,11,Education,2025-02-13,2025-04-10,2098,8.5,Neural Networks Co -AI06099,AI Software Engineer,109880,USD,109880,SE,CT,Israel,M,Israel,100,"SQL, Hadoop, NLP, Deep Learning",Bachelor,9,Gaming,2024-10-11,2024-11-07,804,9.5,Smart Analytics -AI06100,NLP Engineer,122068,USD,122068,MI,PT,United States,L,United States,100,"Kubernetes, Tableau, SQL",PhD,3,Consulting,2024-04-07,2024-04-26,1213,7.9,Cognitive Computing -AI06101,AI Specialist,62513,USD,62513,SE,FL,China,S,Romania,0,"Python, Scala, R, Hadoop, SQL",Associate,8,Consulting,2025-02-28,2025-04-09,1022,8.5,Neural Networks Co -AI06102,AI Software Engineer,67497,USD,67497,EN,CT,Denmark,M,Denmark,100,"Scala, Spark, R",Master,1,Energy,2024-07-05,2024-09-03,1542,8,Digital Transformation LLC -AI06103,Robotics Engineer,68328,USD,68328,SE,FL,China,M,China,50,"R, Java, Tableau",Associate,9,Telecommunications,2024-02-06,2024-03-13,630,6.4,DeepTech Ventures -AI06104,Research Scientist,73887,CAD,92359,EN,PT,Canada,M,Canada,0,"NLP, SQL, R, PyTorch",Bachelor,0,Healthcare,2024-03-30,2024-06-03,2057,6.9,DataVision Ltd -AI06105,Deep Learning Engineer,85387,EUR,72579,MI,PT,France,M,France,50,"Azure, Python, Spark",Master,4,Technology,2024-02-27,2024-03-27,541,7.3,Digital Transformation LLC -AI06106,Data Engineer,81892,JPY,9008120,MI,FT,Japan,S,Japan,0,"NLP, Kubernetes, Data Visualization",PhD,3,Consulting,2024-06-30,2024-07-28,1150,7.3,DeepTech Ventures -AI06107,Autonomous Systems Engineer,125416,SGD,163041,SE,FL,Singapore,S,South Korea,0,"SQL, Python, Azure, Deep Learning",PhD,9,Energy,2024-10-23,2024-12-05,1037,5.6,Algorithmic Solutions -AI06108,Research Scientist,362104,USD,362104,EX,FL,Norway,L,Norway,0,"TensorFlow, Docker, PyTorch",Bachelor,14,Finance,2024-05-23,2024-07-24,2245,8.5,Algorithmic Solutions -AI06109,Machine Learning Engineer,109467,EUR,93047,SE,FT,France,S,France,0,"TensorFlow, Docker, Python",Bachelor,5,Government,2025-01-07,2025-03-12,1615,8.2,Neural Networks Co -AI06110,AI Software Engineer,74992,USD,74992,MI,FT,Israel,S,Denmark,100,"R, SQL, MLOps, AWS",Bachelor,2,Education,2024-10-09,2024-12-15,1285,7.3,Machine Intelligence Group -AI06111,AI Research Scientist,83813,USD,83813,EX,CT,China,S,China,50,"Python, Mathematics, TensorFlow, Data Visualization, Computer Vision",Bachelor,15,Education,2024-01-23,2024-03-07,1797,6.7,Quantum Computing Inc -AI06112,Data Scientist,98188,CHF,88369,EN,FT,Switzerland,S,Switzerland,100,"Spark, PyTorch, TensorFlow, Hadoop",Master,0,Gaming,2024-05-16,2024-06-11,1249,8.7,Advanced Robotics -AI06113,AI Architect,120407,USD,120407,EX,FT,Finland,S,Italy,0,"Deep Learning, R, MLOps, Computer Vision, Azure",PhD,17,Education,2024-11-17,2024-12-31,763,8.5,Algorithmic Solutions -AI06114,Deep Learning Engineer,187126,EUR,159057,EX,PT,France,M,France,0,"Linux, Docker, Computer Vision",Bachelor,18,Energy,2024-04-24,2024-06-23,2499,8.6,AI Innovations -AI06115,Autonomous Systems Engineer,55832,USD,55832,SE,FT,China,M,China,100,"Spark, Statistics, MLOps",PhD,9,Media,2025-03-27,2025-05-29,1242,5.5,Cognitive Computing -AI06116,Data Scientist,99693,USD,99693,MI,FL,Norway,S,Denmark,100,"TensorFlow, PyTorch, MLOps, GCP",Bachelor,2,Automotive,2024-03-06,2024-04-27,580,6.6,Smart Analytics -AI06117,Principal Data Scientist,111940,AUD,151119,SE,PT,Australia,M,South Korea,100,"Python, R, GCP, TensorFlow, Linux",Bachelor,8,Energy,2024-05-05,2024-06-15,601,9.9,Neural Networks Co -AI06118,AI Consultant,350058,USD,350058,EX,CT,Norway,L,Malaysia,50,"SQL, TensorFlow, Data Visualization, Hadoop",PhD,19,Healthcare,2024-02-19,2024-04-02,2435,8.6,Predictive Systems -AI06119,AI Product Manager,118196,EUR,100467,SE,PT,Germany,S,Germany,0,"Computer Vision, Tableau, SQL, Deep Learning, Linux",Bachelor,7,Technology,2024-07-15,2024-09-25,960,7.6,Advanced Robotics -AI06120,Data Analyst,149669,USD,149669,EX,FT,South Korea,L,South Korea,0,"AWS, GCP, Git, Computer Vision, Hadoop",Associate,18,Government,2025-01-14,2025-02-27,1730,7.8,Future Systems -AI06121,AI Architect,207625,CHF,186863,EX,PT,Switzerland,S,Switzerland,0,"GCP, Statistics, NLP, Computer Vision, Spark",Master,10,Transportation,2025-03-30,2025-05-02,2116,8.4,DeepTech Ventures -AI06122,AI Specialist,179611,CHF,161650,SE,PT,Switzerland,M,Switzerland,100,"Scala, TensorFlow, GCP",Associate,5,Media,2025-03-08,2025-04-07,1131,8.8,TechCorp Inc -AI06123,Deep Learning Engineer,72594,USD,72594,MI,FT,Israel,S,Israel,100,"PyTorch, Computer Vision, Tableau, AWS, SQL",Bachelor,4,Education,2024-04-01,2024-05-30,1372,7.6,TechCorp Inc -AI06124,Data Engineer,74990,USD,74990,MI,FL,Ireland,S,Ireland,100,"Spark, Statistics, Data Visualization, Linux",Associate,4,Transportation,2025-01-06,2025-03-19,1208,8.6,Digital Transformation LLC -AI06125,Principal Data Scientist,128233,USD,128233,SE,PT,United States,S,New Zealand,100,"AWS, MLOps, Mathematics",Bachelor,9,Automotive,2024-12-17,2025-01-26,505,9.1,DataVision Ltd -AI06126,AI Specialist,211020,USD,211020,EX,FT,Denmark,S,Denmark,100,"Git, Python, Deep Learning, Computer Vision",Bachelor,19,Technology,2024-08-17,2024-10-08,717,8.6,Quantum Computing Inc -AI06127,Data Engineer,81260,USD,81260,MI,FL,Sweden,S,Sweden,100,"Hadoop, Azure, Mathematics, TensorFlow, MLOps",Master,4,Gaming,2025-02-15,2025-03-05,733,9.9,DataVision Ltd -AI06128,Data Analyst,119633,EUR,101688,SE,PT,France,M,Thailand,50,"SQL, Kubernetes, Linux",Bachelor,7,Government,2024-01-18,2024-03-20,1998,7.5,Cognitive Computing -AI06129,Machine Learning Engineer,73814,USD,73814,MI,PT,Finland,M,Finland,100,"Python, Spark, TensorFlow, Data Visualization, AWS",PhD,4,Technology,2024-02-19,2024-04-20,1409,8.1,DataVision Ltd -AI06130,AI Specialist,288274,EUR,245033,EX,FT,Germany,L,Indonesia,0,"GCP, SQL, AWS",Associate,13,Automotive,2024-09-29,2024-11-30,1683,9.7,Cloud AI Solutions -AI06131,AI Architect,194644,USD,194644,EX,PT,United States,M,United States,100,"Python, Spark, R, Data Visualization, Scala",Master,19,Energy,2024-04-27,2024-06-20,585,9.8,Neural Networks Co -AI06132,AI Software Engineer,116370,JPY,12800700,MI,FL,Japan,M,Japan,100,"AWS, Scala, GCP",Master,4,Gaming,2025-04-07,2025-05-27,1512,9.3,AI Innovations -AI06133,Robotics Engineer,58648,USD,58648,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Mathematics, Spark",PhD,0,Retail,2024-09-14,2024-10-31,2333,7.3,Smart Analytics -AI06134,Head of AI,94136,EUR,80016,MI,FT,France,L,France,0,"SQL, PyTorch, Docker, Statistics",Associate,2,Technology,2024-08-17,2024-10-02,1740,5.9,Neural Networks Co -AI06135,ML Ops Engineer,60881,JPY,6696910,EN,FT,Japan,S,Japan,50,"SQL, AWS, Tableau, R, NLP",Associate,1,Retail,2024-05-13,2024-07-08,2420,9.3,Advanced Robotics -AI06136,NLP Engineer,134266,USD,134266,SE,CT,United States,S,United States,0,"Tableau, GCP, TensorFlow, Docker",PhD,6,Media,2024-04-22,2024-05-09,2340,9.2,Advanced Robotics -AI06137,Head of AI,61969,USD,61969,SE,PT,China,S,China,50,"Kubernetes, SQL, Deep Learning, Statistics, MLOps",Master,7,Energy,2024-08-05,2024-09-14,903,7,Algorithmic Solutions -AI06138,Machine Learning Engineer,122843,CAD,153554,SE,FT,Canada,S,Canada,0,"R, Java, Data Visualization, Python, AWS",Bachelor,9,Healthcare,2025-01-07,2025-02-14,1013,5.8,Quantum Computing Inc -AI06139,AI Specialist,127779,USD,127779,SE,CT,Finland,L,Finland,50,"Docker, Data Visualization, Python",Bachelor,8,Consulting,2025-03-06,2025-04-27,2111,5.8,Machine Intelligence Group -AI06140,AI Architect,27705,USD,27705,MI,FT,India,M,Spain,50,"Linux, Tableau, NLP, Azure",Master,2,Retail,2024-02-21,2024-04-12,1650,6.3,Digital Transformation LLC -AI06141,AI Architect,31007,USD,31007,MI,PT,India,S,India,50,"Python, Docker, Deep Learning, Java, NLP",Bachelor,3,Finance,2025-04-23,2025-05-30,1414,9.3,Cognitive Computing -AI06142,Head of AI,159103,USD,159103,SE,CT,Denmark,L,China,0,"GCP, Hadoop, SQL",PhD,9,Manufacturing,2024-08-25,2024-09-13,1683,6.3,Quantum Computing Inc -AI06143,AI Specialist,81172,USD,81172,MI,FT,Ireland,M,Ireland,50,"Python, Docker, Deep Learning, Azure, GCP",Associate,3,Consulting,2024-05-24,2024-07-10,710,8,TechCorp Inc -AI06144,Deep Learning Engineer,38128,USD,38128,EN,PT,China,L,Canada,100,"Docker, TensorFlow, Hadoop",Associate,0,Media,2024-04-09,2024-06-19,1299,6,AI Innovations -AI06145,Data Engineer,128255,EUR,109017,SE,FT,Germany,S,India,100,"Statistics, Kubernetes, R, GCP",Associate,6,Gaming,2024-03-16,2024-04-27,1216,7.4,TechCorp Inc -AI06146,ML Ops Engineer,101526,USD,101526,SE,FT,Finland,S,Finland,0,"Hadoop, PyTorch, Java, Statistics",Master,7,Media,2024-09-28,2024-10-20,1406,5.7,Algorithmic Solutions -AI06147,Robotics Engineer,46864,AUD,63266,EN,FL,Australia,S,Australia,100,"Azure, Kubernetes, Python, Deep Learning",PhD,1,Telecommunications,2024-11-04,2024-12-30,540,6.2,Smart Analytics -AI06148,Autonomous Systems Engineer,115707,CHF,104136,MI,CT,Switzerland,M,South Africa,50,"NLP, Python, SQL, TensorFlow",Master,3,Media,2024-04-07,2024-05-14,1458,6.7,DeepTech Ventures -AI06149,Data Engineer,94886,USD,94886,MI,FT,Sweden,L,Norway,100,"Statistics, Git, Spark",Bachelor,2,Automotive,2024-01-16,2024-01-31,1256,6.2,Neural Networks Co -AI06150,AI Research Scientist,66330,USD,66330,EN,FL,Ireland,M,Norway,50,"Python, AWS, Azure",Master,1,Real Estate,2024-01-16,2024-02-23,1111,8,Quantum Computing Inc -AI06151,Machine Learning Researcher,66467,EUR,56497,MI,PT,Austria,S,Austria,50,"Linux, SQL, Computer Vision, PyTorch",Bachelor,2,Education,2024-12-27,2025-02-15,1854,5.5,Neural Networks Co -AI06152,Data Scientist,112672,SGD,146474,MI,FT,Singapore,L,Singapore,100,"NLP, Python, Linux, GCP, Git",Associate,2,Education,2024-10-07,2024-11-28,1006,9.8,Digital Transformation LLC -AI06153,Deep Learning Engineer,92337,EUR,78486,MI,FT,Netherlands,M,Netherlands,50,"Mathematics, GCP, Computer Vision, Python",Bachelor,2,Gaming,2024-04-02,2024-05-15,1553,7.1,Smart Analytics -AI06154,ML Ops Engineer,77521,EUR,65893,EN,FL,Germany,L,Japan,100,"Deep Learning, Mathematics, Data Visualization, SQL, Azure",Associate,0,Telecommunications,2024-01-03,2024-03-15,573,7.7,Digital Transformation LLC -AI06155,AI Research Scientist,323583,CHF,291225,EX,FL,Switzerland,L,Kenya,0,"Azure, Java, AWS, Mathematics",Master,13,Manufacturing,2024-05-20,2024-07-29,1566,8.7,Cloud AI Solutions -AI06156,ML Ops Engineer,123796,GBP,92847,MI,FL,United Kingdom,L,Ukraine,0,"Python, Java, Azure",PhD,4,Media,2024-11-05,2024-12-27,2211,6.3,Advanced Robotics -AI06157,Data Engineer,191974,USD,191974,EX,FT,United States,L,United States,100,"Scala, Python, Git, AWS, Spark",Associate,15,Transportation,2024-06-12,2024-08-14,2068,8.2,Neural Networks Co -AI06158,Machine Learning Engineer,92459,USD,92459,MI,CT,Sweden,L,Sweden,0,"Deep Learning, Data Visualization, Statistics, Computer Vision, Azure",Bachelor,3,Energy,2024-03-03,2024-05-12,1148,5.1,Cognitive Computing -AI06159,Deep Learning Engineer,99147,EUR,84275,MI,FT,Germany,S,Germany,50,"Scala, TensorFlow, Spark",Associate,2,Gaming,2025-03-04,2025-04-08,1132,7.1,Machine Intelligence Group -AI06160,Principal Data Scientist,86412,CHF,77771,EN,CT,Switzerland,L,Turkey,0,"AWS, Azure, Git, Data Visualization, SQL",Master,0,Real Estate,2025-03-13,2025-04-06,2437,5.2,Algorithmic Solutions -AI06161,Machine Learning Engineer,208435,USD,208435,EX,FL,Finland,S,Czech Republic,100,"GCP, Scala, SQL",Master,19,Energy,2025-01-03,2025-02-18,2064,5.1,Algorithmic Solutions -AI06162,Head of AI,126593,CHF,113934,MI,FT,Switzerland,M,Switzerland,0,"Spark, Git, Linux",PhD,3,Education,2024-12-21,2025-01-12,1142,7,Neural Networks Co -AI06163,ML Ops Engineer,141683,USD,141683,SE,FL,Denmark,S,Denmark,100,"MLOps, NLP, Python, SQL, R",Associate,7,Finance,2024-02-21,2024-04-15,961,8.5,AI Innovations -AI06164,Data Engineer,72525,USD,72525,EN,PT,Norway,M,Austria,50,"Scala, Statistics, Git, SQL, Linux",PhD,1,Media,2024-04-11,2024-06-07,2328,5.4,Autonomous Tech -AI06165,Head of AI,210148,EUR,178626,EX,FL,Netherlands,S,Netherlands,50,"Git, Linux, Deep Learning, Data Visualization",Associate,16,Technology,2024-11-30,2025-01-04,1851,7.5,Algorithmic Solutions -AI06166,Data Engineer,100933,USD,100933,EX,CT,India,L,India,50,"Hadoop, MLOps, Docker, Git, Spark",Master,18,Government,2024-04-04,2024-05-21,1702,8,AI Innovations -AI06167,AI Product Manager,133499,USD,133499,SE,FT,Denmark,M,Denmark,100,"Spark, PyTorch, Linux",PhD,6,Manufacturing,2024-11-27,2024-12-29,1819,9.2,Algorithmic Solutions -AI06168,Computer Vision Engineer,143384,USD,143384,EX,PT,South Korea,S,South Korea,0,"MLOps, GCP, Docker, Statistics",PhD,19,Technology,2024-01-15,2024-02-23,1599,9.1,Cognitive Computing -AI06169,Head of AI,83098,USD,83098,EN,FL,Denmark,S,Denmark,50,"Linux, SQL, Spark",Associate,0,Telecommunications,2024-02-21,2024-03-12,1501,6.1,DeepTech Ventures -AI06170,ML Ops Engineer,58485,USD,58485,EN,CT,South Korea,S,South Korea,50,"NLP, Azure, Python",Master,1,Government,2024-09-02,2024-10-17,2191,7.2,Advanced Robotics -AI06171,AI Architect,43970,USD,43970,MI,PT,China,M,Luxembourg,0,"Computer Vision, MLOps, NLP, Statistics, PyTorch",PhD,4,Consulting,2025-01-29,2025-03-02,780,7.5,AI Innovations -AI06172,Head of AI,410273,CHF,369246,EX,FT,Switzerland,L,Switzerland,50,"Python, TensorFlow, Deep Learning",PhD,19,Education,2024-03-01,2024-03-28,1739,7,Machine Intelligence Group -AI06173,Principal Data Scientist,76227,SGD,99095,EN,CT,Singapore,L,Canada,50,"Python, Azure, TensorFlow, Java, Docker",Bachelor,0,Real Estate,2024-07-11,2024-09-12,1081,6.2,Predictive Systems -AI06174,Deep Learning Engineer,121236,CAD,151545,SE,FL,Canada,M,Canada,0,"TensorFlow, Linux, Python, MLOps",Bachelor,7,Energy,2024-02-10,2024-04-19,526,6.8,Cognitive Computing -AI06175,Computer Vision Engineer,82912,AUD,111931,EN,CT,Australia,L,Australia,50,"Python, Kubernetes, Tableau, TensorFlow, Deep Learning",Master,1,Consulting,2025-04-15,2025-05-28,1620,8.3,DeepTech Ventures -AI06176,Autonomous Systems Engineer,227232,AUD,306763,EX,FL,Australia,L,Australia,100,"Python, MLOps, SQL, Spark",Associate,14,Finance,2024-07-22,2024-09-21,1893,6,Cloud AI Solutions -AI06177,AI Specialist,46804,USD,46804,SE,FL,India,S,Italy,0,"Hadoop, Docker, Linux",Master,7,Real Estate,2024-06-02,2024-07-20,2125,6.9,Digital Transformation LLC -AI06178,Machine Learning Engineer,269514,USD,269514,EX,PT,Denmark,L,Denmark,50,"Java, Kubernetes, Data Visualization, Docker, GCP",PhD,16,Automotive,2024-07-21,2024-09-01,1570,9.7,Cloud AI Solutions -AI06179,NLP Engineer,37274,USD,37274,SE,CT,India,S,India,100,"GCP, R, Git, NLP",PhD,7,Technology,2024-01-29,2024-03-06,1576,8,TechCorp Inc -AI06180,Deep Learning Engineer,27007,USD,27007,EN,CT,China,M,China,50,"SQL, PyTorch, Git, Deep Learning, Azure",PhD,1,Finance,2024-12-06,2024-12-25,587,7.2,TechCorp Inc -AI06181,Research Scientist,80678,USD,80678,EX,PT,India,S,India,100,"R, Tableau, SQL",PhD,14,Gaming,2024-02-04,2024-04-11,1900,8.5,AI Innovations -AI06182,Data Engineer,270264,CHF,243238,EX,CT,Switzerland,M,Switzerland,0,"NLP, MLOps, Statistics, Scala",PhD,14,Retail,2024-10-28,2024-12-04,578,9.9,TechCorp Inc -AI06183,AI Product Manager,63878,EUR,54296,MI,FL,France,S,France,50,"Azure, Deep Learning, MLOps, TensorFlow, Kubernetes",PhD,3,Retail,2025-04-21,2025-05-16,2333,6,DataVision Ltd -AI06184,Research Scientist,280852,CHF,252767,EX,CT,Switzerland,L,Switzerland,0,"Git, Scala, Tableau, Linux, Statistics",Master,15,Transportation,2025-02-28,2025-05-04,562,9.8,Digital Transformation LLC -AI06185,Head of AI,103833,USD,103833,MI,FL,Ireland,M,Ireland,0,"PyTorch, Linux, Spark, Tableau, Deep Learning",Associate,3,Manufacturing,2024-05-18,2024-07-06,1743,7.9,Neural Networks Co -AI06186,AI Product Manager,200183,AUD,270247,EX,PT,Australia,S,Australia,50,"AWS, Python, Scala, Spark, Deep Learning",PhD,10,Retail,2024-06-06,2024-07-03,1737,6.9,Algorithmic Solutions -AI06187,Machine Learning Researcher,76963,USD,76963,EX,PT,India,M,India,100,"Kubernetes, Hadoop, Docker, Deep Learning, Statistics",PhD,15,Gaming,2025-04-01,2025-05-23,2228,6.1,TechCorp Inc -AI06188,NLP Engineer,119389,USD,119389,SE,PT,Sweden,M,Sweden,100,"Kubernetes, AWS, Python",Master,7,Healthcare,2024-04-06,2024-06-04,1618,6.8,AI Innovations -AI06189,Machine Learning Researcher,187897,EUR,159712,EX,FL,France,M,France,50,"Hadoop, GCP, Scala, Python, TensorFlow",Associate,18,Manufacturing,2024-04-02,2024-06-07,2109,5.5,TechCorp Inc -AI06190,AI Architect,82319,AUD,111131,MI,FL,Australia,M,Denmark,0,"Spark, Java, PyTorch, Docker, AWS",PhD,4,Manufacturing,2025-04-10,2025-06-01,2081,9.6,Predictive Systems -AI06191,Computer Vision Engineer,145319,USD,145319,SE,FT,Norway,M,Norway,100,"Java, MLOps, Linux, Python, GCP",Bachelor,7,Technology,2024-05-05,2024-05-27,549,7.3,Quantum Computing Inc -AI06192,Deep Learning Engineer,159987,EUR,135989,EX,FT,Germany,M,Germany,100,"Spark, Kubernetes, Deep Learning",PhD,15,Media,2024-11-22,2025-01-06,1827,8.1,DataVision Ltd -AI06193,AI Specialist,68999,USD,68999,EN,FT,United States,S,Russia,50,"Scala, Git, Data Visualization",Bachelor,0,Energy,2024-12-01,2025-02-10,2474,7.9,Predictive Systems -AI06194,Data Engineer,96411,JPY,10605210,MI,FT,Japan,M,Japan,100,"Statistics, Java, Git",Master,2,Education,2024-03-13,2024-05-24,1125,7.2,Advanced Robotics -AI06195,Robotics Engineer,262229,USD,262229,EX,PT,Sweden,L,Sweden,50,"Git, Kubernetes, Scala",PhD,17,Healthcare,2024-09-25,2024-12-05,1786,6,Advanced Robotics -AI06196,Data Analyst,77309,USD,77309,MI,CT,Israel,M,Israel,100,"SQL, Java, Python, Data Visualization",Associate,2,Automotive,2024-11-10,2025-01-19,823,6.1,Cloud AI Solutions -AI06197,Robotics Engineer,327821,USD,327821,EX,PT,Denmark,L,Denmark,0,"Azure, Python, MLOps, Scala",PhD,13,Gaming,2024-01-08,2024-02-17,2292,6.7,Future Systems -AI06198,NLP Engineer,97172,GBP,72879,EN,PT,United Kingdom,L,United Kingdom,100,"Statistics, Linux, Mathematics, Tableau, Kubernetes",PhD,0,Retail,2024-02-14,2024-04-02,819,7.2,DeepTech Ventures -AI06199,Autonomous Systems Engineer,58968,EUR,50123,EN,PT,Germany,L,Germany,50,"PyTorch, Java, TensorFlow, R, GCP",Associate,0,Telecommunications,2024-07-09,2024-08-09,2302,6.4,DataVision Ltd -AI06200,Machine Learning Researcher,209608,AUD,282971,EX,FL,Australia,M,Australia,0,"NLP, Python, Hadoop, Kubernetes",Master,18,Automotive,2025-03-04,2025-04-28,1596,5.5,Digital Transformation LLC -AI06201,Head of AI,47165,EUR,40090,EN,PT,Austria,S,Austria,0,"Python, TensorFlow, SQL",Bachelor,0,Finance,2025-02-12,2025-03-30,1483,6.5,Smart Analytics -AI06202,Data Engineer,95552,USD,95552,EN,FT,United States,L,United States,0,"Python, Computer Vision, Scala, TensorFlow, Git",Master,1,Media,2024-09-30,2024-11-30,1965,5.8,Cloud AI Solutions -AI06203,NLP Engineer,140834,EUR,119709,SE,PT,France,M,France,0,"NLP, TensorFlow, Java, Data Visualization, Mathematics",PhD,5,Finance,2024-01-21,2024-03-01,727,9.9,TechCorp Inc -AI06204,NLP Engineer,50964,USD,50964,EN,CT,Finland,M,Israel,100,"Docker, Azure, NLP, Linux",Associate,0,Consulting,2024-03-14,2024-03-31,1190,7.1,Cognitive Computing -AI06205,Machine Learning Researcher,141955,USD,141955,EX,FT,Israel,M,Israel,0,"TensorFlow, Spark, Hadoop, Python",PhD,12,Government,2024-11-10,2025-01-11,1814,6.9,DataVision Ltd -AI06206,Research Scientist,79587,USD,79587,MI,FT,Israel,M,Israel,50,"PyTorch, SQL, NLP",Associate,4,Transportation,2024-03-31,2024-06-03,1811,8.9,DataVision Ltd -AI06207,Data Engineer,114995,USD,114995,EX,PT,China,L,China,100,"Kubernetes, Data Visualization, SQL, Python",Bachelor,17,Consulting,2025-02-15,2025-04-23,566,6.2,DataVision Ltd -AI06208,ML Ops Engineer,65857,USD,65857,EN,PT,Israel,S,Malaysia,0,"Deep Learning, TensorFlow, Computer Vision",PhD,0,Media,2025-04-20,2025-06-08,1998,9.3,Predictive Systems -AI06209,AI Consultant,58926,USD,58926,EN,FT,Ireland,M,Portugal,100,"Scala, NLP, GCP, Hadoop",Associate,1,Manufacturing,2025-04-14,2025-05-12,597,9.8,Autonomous Tech -AI06210,AI Software Engineer,275093,USD,275093,EX,FL,Denmark,S,Denmark,100,"Git, Hadoop, Mathematics",Master,16,Government,2024-04-02,2024-06-11,2078,8.7,Neural Networks Co -AI06211,Machine Learning Engineer,220073,EUR,187062,EX,FL,Netherlands,L,Netherlands,50,"Python, Java, SQL, PyTorch",Bachelor,18,Energy,2024-11-23,2025-01-02,1489,5.1,Cloud AI Solutions -AI06212,Robotics Engineer,58905,GBP,44179,EN,FT,United Kingdom,S,New Zealand,50,"Python, Linux, Azure, AWS, Java",Associate,1,Finance,2024-06-06,2024-07-31,1625,7.1,Predictive Systems -AI06213,Principal Data Scientist,264666,USD,264666,EX,CT,Norway,M,Norway,100,"Git, NLP, SQL, PyTorch",PhD,11,Healthcare,2025-01-14,2025-02-27,1025,6.9,DeepTech Ventures -AI06214,Data Analyst,149181,EUR,126804,EX,PT,Austria,M,Austria,50,"SQL, Spark, Data Visualization, TensorFlow, GCP",Master,17,Healthcare,2024-07-24,2024-08-29,985,9.9,Future Systems -AI06215,ML Ops Engineer,92326,USD,92326,EN,FL,Sweden,L,Sweden,0,"Scala, Java, NLP",Associate,1,Gaming,2024-01-27,2024-04-04,2411,5.3,Autonomous Tech -AI06216,Autonomous Systems Engineer,103737,USD,103737,MI,FT,United States,S,United States,0,"Kubernetes, Docker, Deep Learning",Bachelor,4,Automotive,2024-10-21,2024-11-11,1472,8.1,TechCorp Inc -AI06217,AI Consultant,105787,EUR,89919,SE,PT,France,M,France,100,"Computer Vision, GCP, Deep Learning, PyTorch",Bachelor,9,Healthcare,2024-10-27,2025-01-03,1053,5.4,Digital Transformation LLC -AI06218,Data Engineer,121968,USD,121968,MI,FL,Denmark,M,Denmark,50,"SQL, TensorFlow, Linux",Associate,4,Retail,2025-03-22,2025-06-03,2484,7.9,Cloud AI Solutions -AI06219,Computer Vision Engineer,308831,CHF,277948,EX,FL,Switzerland,S,Switzerland,50,"GCP, Deep Learning, Python, Kubernetes, TensorFlow",PhD,17,Government,2025-01-03,2025-02-25,1901,8.6,Neural Networks Co -AI06220,AI Product Manager,52330,USD,52330,EN,PT,Sweden,M,Sweden,0,"GCP, Tableau, NLP",Associate,1,Gaming,2024-06-29,2024-08-27,623,9.9,Cloud AI Solutions -AI06221,NLP Engineer,105139,EUR,89368,MI,PT,Germany,M,Germany,0,"AWS, Java, Mathematics",Bachelor,2,Automotive,2024-01-09,2024-03-14,806,5.2,Predictive Systems -AI06222,AI Consultant,57833,USD,57833,MI,FT,China,L,Nigeria,100,"Java, Statistics, Tableau",PhD,3,Healthcare,2024-02-26,2024-03-23,1963,6.2,Quantum Computing Inc -AI06223,ML Ops Engineer,136814,CHF,123133,MI,FT,Switzerland,M,Switzerland,50,"GCP, Linux, Statistics, Mathematics",PhD,3,Manufacturing,2024-04-02,2024-05-02,1076,9.1,AI Innovations -AI06224,AI Architect,158438,USD,158438,EX,FL,South Korea,M,Malaysia,100,"Hadoop, MLOps, Java, Python, TensorFlow",Master,15,Retail,2025-03-16,2025-05-18,2329,5.3,AI Innovations -AI06225,NLP Engineer,45309,USD,45309,EN,PT,South Korea,M,South Korea,50,"PyTorch, Git, Kubernetes, Statistics, Deep Learning",Master,0,Finance,2024-03-18,2024-04-08,1552,6.5,Cloud AI Solutions -AI06226,AI Software Engineer,45432,USD,45432,EN,CT,Israel,S,Israel,100,"TensorFlow, Spark, Linux, Deep Learning, Java",Master,1,Manufacturing,2024-06-27,2024-08-22,555,6.4,DeepTech Ventures -AI06227,AI Product Manager,109543,CHF,98589,EN,FL,Switzerland,L,Estonia,100,"Docker, Git, Kubernetes, TensorFlow",PhD,0,Healthcare,2024-05-29,2024-07-02,1108,7.6,Cognitive Computing -AI06228,Head of AI,174342,USD,174342,EX,FT,Israel,M,Mexico,100,"Statistics, SQL, Data Visualization",Bachelor,13,Manufacturing,2024-05-14,2024-07-16,1145,6.4,Autonomous Tech -AI06229,Head of AI,52826,EUR,44902,EN,PT,Germany,M,Italy,0,"Linux, Computer Vision, SQL, Spark, PyTorch",Associate,1,Finance,2024-04-12,2024-05-09,1680,8.7,Predictive Systems -AI06230,AI Research Scientist,43403,USD,43403,MI,FT,China,S,China,0,"Git, NLP, Docker, TensorFlow, AWS",Bachelor,3,Technology,2024-01-20,2024-03-04,2127,5.5,Cognitive Computing -AI06231,AI Specialist,58657,AUD,79187,EN,FT,Australia,L,Australia,50,"Kubernetes, Scala, Linux, Spark",Associate,1,Finance,2024-03-10,2024-05-05,2476,6.8,Quantum Computing Inc -AI06232,ML Ops Engineer,334601,CHF,301141,EX,CT,Switzerland,L,Indonesia,0,"PyTorch, Azure, MLOps",Master,14,Gaming,2024-08-01,2024-09-21,1260,7.9,Predictive Systems -AI06233,Computer Vision Engineer,91169,AUD,123078,MI,FL,Australia,M,Australia,50,"SQL, PyTorch, R, Java",Master,2,Gaming,2024-06-07,2024-06-24,1508,6.8,DeepTech Ventures -AI06234,Machine Learning Engineer,89246,EUR,75859,MI,CT,France,S,France,0,"Spark, Hadoop, Git, SQL",Associate,3,Energy,2024-07-11,2024-09-11,817,7.5,Algorithmic Solutions -AI06235,AI Consultant,70820,AUD,95607,EN,CT,Australia,L,Australia,100,"Tableau, Linux, R, Azure, Scala",Master,1,Transportation,2024-08-24,2024-10-30,2272,9.1,Cognitive Computing -AI06236,Data Engineer,127145,SGD,165289,SE,CT,Singapore,L,Singapore,50,"NLP, Python, SQL, Docker, GCP",PhD,7,Retail,2025-04-29,2025-06-14,1599,6.3,Future Systems -AI06237,Computer Vision Engineer,74447,GBP,55835,EN,CT,United Kingdom,S,United Kingdom,100,"Linux, Data Visualization, TensorFlow",Bachelor,1,Technology,2024-01-21,2024-02-12,1024,9.2,DataVision Ltd -AI06238,AI Product Manager,85168,GBP,63876,MI,FT,United Kingdom,M,Austria,100,"Python, MLOps, Java, Computer Vision, Git",PhD,3,Energy,2024-08-04,2024-09-28,2129,6.1,Digital Transformation LLC -AI06239,AI Consultant,333929,CHF,300536,EX,CT,Switzerland,L,Switzerland,100,"SQL, PyTorch, MLOps, Computer Vision, AWS",PhD,14,Transportation,2024-03-31,2024-06-03,1031,9.5,Smart Analytics -AI06240,Deep Learning Engineer,119472,EUR,101551,SE,FT,Austria,M,Denmark,100,"Python, Spark, TensorFlow",Master,7,Retail,2024-03-17,2024-05-16,914,8.2,Neural Networks Co -AI06241,Machine Learning Engineer,185566,USD,185566,EX,CT,United States,M,Ireland,100,"Kubernetes, Statistics, R, Docker, Computer Vision",Associate,13,Real Estate,2024-01-09,2024-03-18,669,5.1,AI Innovations -AI06242,Deep Learning Engineer,98638,AUD,133161,SE,CT,Australia,S,Philippines,50,"Mathematics, Python, GCP, Azure",Associate,7,Healthcare,2024-10-07,2024-11-12,1188,5.6,Neural Networks Co -AI06243,Machine Learning Engineer,96950,EUR,82408,MI,PT,Netherlands,L,Netherlands,50,"Python, MLOps, Data Visualization",Master,2,Automotive,2024-06-22,2024-07-29,2329,7.2,Machine Intelligence Group -AI06244,AI Product Manager,55210,GBP,41408,EN,FT,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, Mathematics, Java",Associate,0,Healthcare,2024-04-23,2024-07-01,2059,6.1,Autonomous Tech -AI06245,Robotics Engineer,231279,USD,231279,EX,FL,South Korea,L,South Korea,0,"Git, TensorFlow, Python",Bachelor,19,Consulting,2024-10-07,2024-12-06,2187,8.7,Digital Transformation LLC -AI06246,ML Ops Engineer,125808,USD,125808,MI,FT,Denmark,L,Denmark,100,"NLP, Scala, Python",PhD,4,Education,2024-03-25,2024-05-16,532,6.3,Advanced Robotics -AI06247,Head of AI,201000,SGD,261300,EX,CT,Singapore,M,Singapore,100,"NLP, Java, Docker, Deep Learning",Bachelor,10,Education,2024-06-12,2024-08-13,598,5.9,Predictive Systems -AI06248,Machine Learning Researcher,235015,SGD,305520,EX,CT,Singapore,S,Singapore,0,"MLOps, Java, R, Kubernetes, Data Visualization",PhD,10,Finance,2024-10-18,2024-12-06,1281,8.8,Machine Intelligence Group -AI06249,Research Scientist,104461,AUD,141022,SE,PT,Australia,S,Australia,100,"PyTorch, SQL, AWS, Python, Deep Learning",Bachelor,7,Real Estate,2024-10-25,2024-12-24,949,6.9,TechCorp Inc -AI06250,AI Consultant,120951,USD,120951,MI,FT,Sweden,L,Sweden,100,"Deep Learning, Docker, R, Linux, MLOps",Associate,4,Education,2024-05-03,2024-06-20,1048,5.2,DeepTech Ventures -AI06251,Deep Learning Engineer,94126,USD,94126,MI,CT,Ireland,S,Ireland,100,"Statistics, Spark, Java, Deep Learning",Bachelor,4,Automotive,2024-09-30,2024-11-19,1008,5.6,Digital Transformation LLC -AI06252,Machine Learning Researcher,188011,USD,188011,EX,FL,Finland,S,Finland,100,"Git, Mathematics, Scala, PyTorch",Bachelor,16,Retail,2025-01-12,2025-03-08,2175,6.1,Digital Transformation LLC -AI06253,NLP Engineer,143061,USD,143061,SE,PT,Norway,M,China,0,"Statistics, Python, Tableau, Linux",PhD,9,Technology,2024-12-22,2025-02-05,1284,7.8,AI Innovations -AI06254,NLP Engineer,206350,EUR,175398,EX,CT,France,S,France,0,"Kubernetes, GCP, Hadoop, Statistics",Master,16,Gaming,2025-04-13,2025-05-21,919,6.7,Smart Analytics -AI06255,Data Analyst,60881,AUD,82189,EN,CT,Australia,S,Australia,0,"Scala, Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-03-26,2024-05-02,672,10,Smart Analytics -AI06256,Data Analyst,103178,EUR,87701,MI,FT,Austria,L,Austria,0,"Azure, Hadoop, AWS, Statistics",Bachelor,3,Finance,2025-04-08,2025-05-28,687,6.4,DataVision Ltd -AI06257,AI Software Engineer,81446,SGD,105880,MI,FL,Singapore,S,Singapore,100,"Docker, Hadoop, Data Visualization, Java, R",Bachelor,2,Healthcare,2025-01-28,2025-03-28,801,5.3,TechCorp Inc -AI06258,ML Ops Engineer,304317,GBP,228238,EX,FT,United Kingdom,L,Denmark,100,"GCP, Linux, Git",PhD,13,Transportation,2024-06-11,2024-07-10,1876,9.3,Cognitive Computing -AI06259,NLP Engineer,37648,USD,37648,SE,FL,India,S,India,50,"Spark, Scala, Git, Python, Azure",Bachelor,5,Technology,2024-09-29,2024-12-02,1398,5.8,Quantum Computing Inc -AI06260,AI Architect,88718,GBP,66539,EN,CT,United Kingdom,L,United Kingdom,50,"Linux, Scala, Computer Vision",Associate,1,Consulting,2024-02-03,2024-02-17,946,9.1,Smart Analytics -AI06261,AI Consultant,36001,USD,36001,MI,FL,China,M,Ukraine,100,"Git, Mathematics, Spark",PhD,4,Finance,2024-01-26,2024-03-22,986,5.3,Advanced Robotics -AI06262,ML Ops Engineer,78519,CAD,98149,MI,CT,Canada,L,Canada,0,"Linux, Deep Learning, Python, TensorFlow",Associate,2,Transportation,2024-09-30,2024-10-20,870,7.7,AI Innovations -AI06263,AI Product Manager,109953,CHF,98958,MI,FT,Switzerland,M,Switzerland,0,"Java, Docker, Kubernetes, Scala",Master,4,Consulting,2025-01-22,2025-03-11,852,6.5,Algorithmic Solutions -AI06264,Head of AI,105406,AUD,142298,SE,CT,Australia,S,Australia,100,"Docker, MLOps, NLP, Java, R",Master,7,Telecommunications,2024-01-19,2024-03-27,2213,7.6,Quantum Computing Inc -AI06265,AI Specialist,70408,USD,70408,EN,FT,Israel,L,South Korea,0,"Mathematics, AWS, Data Visualization, Docker",Bachelor,0,Gaming,2024-06-27,2024-07-12,562,8.7,AI Innovations -AI06266,AI Architect,220323,USD,220323,EX,PT,Sweden,S,Sweden,0,"PyTorch, Linux, Tableau, Computer Vision",Associate,13,Transportation,2025-04-26,2025-06-01,1088,8.3,Neural Networks Co -AI06267,AI Architect,163354,EUR,138851,EX,PT,France,M,France,0,"Azure, AWS, GCP",Associate,10,Telecommunications,2024-12-15,2024-12-29,814,8.2,AI Innovations -AI06268,Autonomous Systems Engineer,89007,SGD,115709,MI,CT,Singapore,L,Singapore,100,"SQL, Spark, Scala, Azure",Master,4,Finance,2024-01-04,2024-01-28,837,8.8,Quantum Computing Inc -AI06269,Computer Vision Engineer,89914,AUD,121384,EN,FT,Australia,L,Australia,50,"AWS, Scala, GCP",Associate,1,Technology,2024-12-16,2025-02-17,1937,5.5,Machine Intelligence Group -AI06270,NLP Engineer,117917,USD,117917,SE,FL,Israel,M,Israel,0,"Python, NLP, Git",Master,8,Consulting,2024-07-22,2024-09-06,701,9.3,Cognitive Computing -AI06271,AI Specialist,86279,AUD,116477,MI,FT,Australia,S,Australia,0,"AWS, Docker, Git, Data Visualization",Bachelor,3,Gaming,2025-01-25,2025-03-07,828,6.5,AI Innovations -AI06272,Computer Vision Engineer,232296,USD,232296,EX,CT,Denmark,S,Denmark,0,"Statistics, Kubernetes, Linux, NLP",Associate,15,Manufacturing,2024-05-31,2024-07-09,2320,5.7,AI Innovations -AI06273,Principal Data Scientist,84539,USD,84539,MI,PT,Israel,S,Israel,0,"R, Scala, Data Visualization, Java, Statistics",Associate,3,Consulting,2024-05-14,2024-07-11,1864,5.8,TechCorp Inc -AI06274,Autonomous Systems Engineer,191852,CHF,172667,SE,FT,Switzerland,S,Switzerland,50,"Spark, PyTorch, Mathematics, Data Visualization, MLOps",Associate,7,Government,2024-10-11,2024-11-16,1459,9.6,Cognitive Computing -AI06275,Head of AI,271790,USD,271790,EX,CT,Denmark,S,Denmark,50,"NLP, Scala, Git",Master,16,Finance,2024-12-15,2025-02-25,609,6.1,Cloud AI Solutions -AI06276,Head of AI,69511,USD,69511,EN,CT,Ireland,M,Ireland,50,"Python, Docker, Computer Vision, Statistics, GCP",PhD,1,Finance,2024-03-02,2024-03-24,2017,6.3,AI Innovations -AI06277,AI Research Scientist,92982,USD,92982,EN,PT,Denmark,M,Denmark,0,"Linux, PyTorch, Hadoop",PhD,1,Manufacturing,2025-03-18,2025-04-02,2141,7.1,Digital Transformation LLC -AI06278,Machine Learning Researcher,123526,EUR,104997,EX,FL,Germany,S,Germany,0,"Docker, Linux, Data Visualization, Statistics",PhD,10,Automotive,2024-03-03,2024-05-01,856,5.5,Smart Analytics -AI06279,AI Consultant,184103,SGD,239334,SE,PT,Singapore,L,Singapore,100,"Kubernetes, Spark, Tableau, Hadoop, Docker",Master,5,Gaming,2024-08-14,2024-09-25,2427,7.2,Cloud AI Solutions -AI06280,AI Research Scientist,58966,USD,58966,MI,FL,China,L,Estonia,50,"Spark, AWS, Azure, Mathematics",Associate,2,Technology,2024-02-12,2024-04-14,2263,8.1,Cognitive Computing -AI06281,Robotics Engineer,118203,USD,118203,SE,PT,Ireland,M,Ireland,50,"Docker, Kubernetes, Data Visualization, GCP, Deep Learning",PhD,6,Finance,2024-02-16,2024-03-31,1541,9.4,TechCorp Inc -AI06282,Machine Learning Researcher,307747,USD,307747,EX,PT,Norway,L,Norway,0,"PyTorch, Spark, Data Visualization, AWS",PhD,11,Transportation,2024-12-23,2025-02-04,1840,7.3,Advanced Robotics -AI06283,Computer Vision Engineer,180858,JPY,19894380,EX,PT,Japan,L,Japan,100,"TensorFlow, Java, NLP, Docker, Computer Vision",Associate,14,Healthcare,2024-08-31,2024-09-26,1599,6,Machine Intelligence Group -AI06284,NLP Engineer,93668,SGD,121768,EN,FL,Singapore,L,Singapore,0,"Docker, PyTorch, Statistics",PhD,0,Media,2025-03-21,2025-04-22,1615,5.8,AI Innovations -AI06285,Computer Vision Engineer,74686,USD,74686,MI,FL,Ireland,S,Ireland,50,"Python, PyTorch, GCP, Deep Learning",Master,4,Government,2024-01-20,2024-03-19,2252,8.7,Digital Transformation LLC -AI06286,ML Ops Engineer,116392,USD,116392,SE,FL,South Korea,M,South Korea,50,"Hadoop, Scala, Python, R, Statistics",PhD,6,Media,2025-01-25,2025-03-28,1578,7.9,DataVision Ltd -AI06287,AI Architect,76585,GBP,57439,EN,CT,United Kingdom,M,Russia,100,"Tableau, Deep Learning, Git, SQL",Bachelor,1,Retail,2025-03-05,2025-04-16,911,9.1,Neural Networks Co -AI06288,Computer Vision Engineer,178074,CAD,222593,EX,FL,Canada,S,Canada,0,"Linux, SQL, Hadoop, PyTorch, Kubernetes",Master,19,Gaming,2025-01-29,2025-02-12,1184,6.6,Smart Analytics -AI06289,AI Consultant,28737,USD,28737,EN,PT,China,M,China,100,"GCP, R, Data Visualization",PhD,1,Media,2025-04-03,2025-06-14,1804,5.1,AI Innovations -AI06290,AI Research Scientist,175508,USD,175508,EX,CT,Ireland,S,Norway,100,"Kubernetes, AWS, Deep Learning, MLOps, SQL",PhD,19,Finance,2025-03-02,2025-04-29,2085,6,DataVision Ltd -AI06291,AI Product Manager,52615,USD,52615,EN,FL,South Korea,M,South Korea,50,"Data Visualization, MLOps, SQL",Associate,1,Finance,2024-07-10,2024-08-02,1516,7.9,DataVision Ltd -AI06292,ML Ops Engineer,177787,USD,177787,SE,PT,Norway,M,Norway,100,"Python, MLOps, Scala, R",Master,7,Finance,2025-01-07,2025-03-17,1543,7.3,Smart Analytics -AI06293,Robotics Engineer,67831,EUR,57656,EN,FL,France,S,France,100,"Python, Git, Hadoop, Spark",Master,0,Real Estate,2024-01-05,2024-02-03,673,5.5,Autonomous Tech -AI06294,Data Engineer,79450,USD,79450,EN,PT,Sweden,L,Finland,100,"Mathematics, Java, Python",Master,1,Retail,2024-03-19,2024-05-21,873,8.6,Digital Transformation LLC -AI06295,AI Research Scientist,61213,USD,61213,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Tableau, Linux, Statistics",Bachelor,0,Consulting,2024-11-16,2025-01-14,842,8.2,Neural Networks Co -AI06296,ML Ops Engineer,142856,USD,142856,SE,FL,United States,M,United States,50,"Git, SQL, Data Visualization, Linux, AWS",Associate,6,Government,2024-09-16,2024-11-24,1332,6.9,Predictive Systems -AI06297,AI Architect,49252,CAD,61565,EN,FT,Canada,S,Canada,50,"Java, R, GCP, SQL, Docker",Master,0,Finance,2024-12-20,2025-01-24,2021,8.7,Neural Networks Co -AI06298,ML Ops Engineer,102093,USD,102093,EX,PT,China,S,Netherlands,0,"Kubernetes, Python, R, Java",Associate,13,Consulting,2024-02-24,2024-04-07,902,7.4,AI Innovations -AI06299,Data Scientist,152000,USD,152000,SE,PT,United States,S,United States,100,"Azure, Mathematics, Python, TensorFlow",PhD,8,Retail,2025-01-10,2025-02-20,839,7.6,AI Innovations -AI06300,AI Research Scientist,145423,AUD,196321,SE,FT,Australia,L,Australia,100,"Mathematics, Git, Python, TensorFlow",PhD,7,Manufacturing,2024-06-24,2024-08-22,1828,8.8,DeepTech Ventures -AI06301,AI Architect,65475,USD,65475,SE,FT,China,M,China,0,"Linux, Computer Vision, R, Statistics",PhD,7,Technology,2024-12-30,2025-03-04,2327,9.9,Neural Networks Co -AI06302,ML Ops Engineer,240444,GBP,180333,EX,CT,United Kingdom,M,United Kingdom,0,"Git, SQL, R, NLP",PhD,19,Education,2024-09-12,2024-11-02,2186,6,AI Innovations -AI06303,Autonomous Systems Engineer,82512,EUR,70135,EN,FT,Germany,L,Germany,50,"Azure, AWS, MLOps",Master,1,Consulting,2025-03-08,2025-04-01,609,9.9,DeepTech Ventures -AI06304,AI Software Engineer,130547,JPY,14360170,MI,CT,Japan,L,Japan,100,"PyTorch, GCP, Kubernetes, AWS",PhD,2,Media,2025-02-03,2025-03-02,1276,6.2,TechCorp Inc -AI06305,Data Engineer,88285,EUR,75042,EN,FL,Germany,L,Germany,50,"Azure, R, Deep Learning, Linux",PhD,0,Education,2024-12-07,2025-02-14,2151,5,Cloud AI Solutions -AI06306,AI Software Engineer,127722,USD,127722,EX,PT,South Korea,S,South Korea,50,"SQL, Kubernetes, MLOps, Computer Vision, NLP",Associate,16,Transportation,2024-07-02,2024-08-04,2126,5.6,Quantum Computing Inc -AI06307,AI Consultant,267077,USD,267077,EX,PT,Norway,M,Norway,50,"Python, Kubernetes, Azure",Bachelor,18,Telecommunications,2025-04-01,2025-05-14,766,8.4,DeepTech Ventures -AI06308,ML Ops Engineer,178106,EUR,151390,EX,CT,Germany,L,Germany,0,"Spark, Git, Tableau, Python",Associate,19,Energy,2025-03-29,2025-04-23,814,5.2,Autonomous Tech -AI06309,Principal Data Scientist,160177,USD,160177,SE,CT,Denmark,L,Israel,100,"AWS, Git, Python, Tableau, GCP",Master,7,Manufacturing,2024-08-28,2024-09-28,1921,6,Future Systems -AI06310,Data Engineer,123876,USD,123876,SE,FT,Israel,S,Israel,0,"SQL, Linux, MLOps, TensorFlow",PhD,9,Transportation,2024-03-30,2024-05-28,1307,8.5,Advanced Robotics -AI06311,Machine Learning Researcher,51598,USD,51598,EN,PT,Finland,M,Finland,0,"Data Visualization, Git, Python, Kubernetes",Associate,0,Telecommunications,2024-05-14,2024-07-13,2313,9.1,Cloud AI Solutions -AI06312,Deep Learning Engineer,127577,USD,127577,SE,FL,Israel,S,Israel,50,"Tableau, AWS, Azure, Python",Associate,6,Technology,2024-08-29,2024-09-20,2494,9.5,Digital Transformation LLC -AI06313,Machine Learning Researcher,64037,GBP,48028,EN,CT,United Kingdom,M,United Kingdom,100,"Spark, Python, Data Visualization",Associate,1,Gaming,2024-03-21,2024-05-16,1649,5.9,DeepTech Ventures -AI06314,AI Consultant,27121,USD,27121,EN,CT,India,L,India,50,"Tableau, Kubernetes, Azure, Scala",Bachelor,1,Retail,2024-09-21,2024-10-17,2379,7.9,AI Innovations -AI06315,AI Software Engineer,177989,USD,177989,SE,CT,United States,L,United States,100,"Python, Scala, TensorFlow, Linux, GCP",Master,6,Healthcare,2024-10-12,2024-11-07,522,7.8,Smart Analytics -AI06316,AI Software Engineer,84799,USD,84799,EN,FL,United States,S,United States,100,"NLP, R, Scala, Linux",Bachelor,0,Technology,2024-12-12,2025-02-14,809,6.8,Cognitive Computing -AI06317,ML Ops Engineer,130027,USD,130027,SE,PT,Israel,L,Israel,50,"R, TensorFlow, Tableau, Computer Vision",PhD,8,Real Estate,2024-04-18,2024-05-02,627,6.5,Future Systems -AI06318,Data Engineer,116389,CAD,145486,SE,PT,Canada,S,Canada,0,"Deep Learning, Java, Scala",Master,5,Automotive,2024-01-25,2024-03-27,583,9.2,Machine Intelligence Group -AI06319,AI Product Manager,16795,USD,16795,EN,FL,India,S,India,100,"R, Hadoop, SQL",Bachelor,0,Real Estate,2025-04-27,2025-06-12,1009,5.1,Algorithmic Solutions -AI06320,Research Scientist,79356,JPY,8729160,MI,FL,Japan,S,Japan,50,"Statistics, Git, MLOps",Associate,4,Real Estate,2024-05-07,2024-06-02,1580,7.1,Algorithmic Solutions -AI06321,AI Research Scientist,71342,SGD,92745,EN,PT,Singapore,L,Belgium,50,"Git, Kubernetes, GCP, Mathematics, Azure",Bachelor,0,Automotive,2024-05-19,2024-07-15,1611,9.4,Digital Transformation LLC -AI06322,Data Engineer,66947,GBP,50210,EN,FT,United Kingdom,M,United Kingdom,0,"R, Mathematics, Kubernetes, Deep Learning, NLP",Bachelor,0,Consulting,2024-02-24,2024-04-03,1935,8.7,Autonomous Tech -AI06323,Machine Learning Engineer,66042,USD,66042,EN,FT,Israel,S,Israel,0,"SQL, GCP, Linux, Tableau",Bachelor,1,Healthcare,2025-04-06,2025-05-09,521,9.6,DataVision Ltd -AI06324,AI Software Engineer,232173,CHF,208956,EX,FT,Switzerland,S,Switzerland,0,"Git, PyTorch, Mathematics, Hadoop, Azure",Bachelor,18,Technology,2024-03-31,2024-05-08,2066,8.1,TechCorp Inc -AI06325,Data Scientist,108812,GBP,81609,SE,FT,United Kingdom,S,Turkey,100,"SQL, R, Data Visualization, Azure",Associate,5,Technology,2025-01-05,2025-01-26,654,6.5,Digital Transformation LLC -AI06326,Research Scientist,96625,USD,96625,MI,PT,Ireland,S,Norway,0,"R, Computer Vision, Data Visualization",Master,2,Consulting,2024-06-30,2024-07-28,777,7.6,Quantum Computing Inc -AI06327,Data Scientist,256663,SGD,333662,EX,FL,Singapore,M,Singapore,0,"Python, Linux, TensorFlow, Mathematics",Master,14,Automotive,2024-07-19,2024-09-03,1871,9.5,Autonomous Tech -AI06328,Machine Learning Researcher,92568,USD,92568,MI,CT,Ireland,S,Ireland,0,"Azure, Python, MLOps, Kubernetes",Master,3,Manufacturing,2024-03-30,2024-05-28,2342,9.9,Advanced Robotics -AI06329,Computer Vision Engineer,85546,EUR,72714,MI,CT,France,M,Netherlands,50,"Spark, Python, SQL",Associate,3,Real Estate,2025-04-10,2025-05-17,1014,9.9,Future Systems -AI06330,Data Engineer,185667,USD,185667,EX,PT,Ireland,L,Ireland,0,"SQL, Deep Learning, Hadoop, TensorFlow, Mathematics",Master,15,Transportation,2025-03-07,2025-03-21,1512,9.8,Future Systems -AI06331,AI Research Scientist,94718,USD,94718,SE,CT,Israel,S,Israel,0,"PyTorch, NLP, GCP",Associate,9,Government,2024-03-05,2024-03-22,860,6.4,Algorithmic Solutions -AI06332,Research Scientist,153864,AUD,207716,SE,CT,Australia,L,Australia,100,"Linux, PyTorch, Spark, NLP",Bachelor,5,Energy,2024-03-17,2024-04-29,986,5.1,TechCorp Inc -AI06333,Computer Vision Engineer,49125,SGD,63863,EN,FL,Singapore,S,Singapore,100,"MLOps, Python, TensorFlow",Master,1,Energy,2025-02-20,2025-04-04,1236,8,TechCorp Inc -AI06334,AI Software Engineer,79549,SGD,103414,EN,PT,Singapore,M,Singapore,100,"Python, R, Kubernetes, Computer Vision",Master,1,Transportation,2024-08-03,2024-08-19,1979,8,Cognitive Computing -AI06335,AI Research Scientist,95354,USD,95354,MI,FL,Sweden,S,Sweden,0,"Scala, Kubernetes, Spark, Hadoop",Associate,3,Manufacturing,2024-06-18,2024-07-13,2489,9.8,DeepTech Ventures -AI06336,AI Architect,91154,CHF,82039,EN,FL,Switzerland,L,Switzerland,100,"AWS, Azure, Python, Java",Master,1,Finance,2024-05-19,2024-06-17,1997,7.1,Autonomous Tech -AI06337,AI Specialist,76991,GBP,57743,EN,PT,United Kingdom,M,United Kingdom,50,"Java, Scala, Azure, Hadoop, Computer Vision",PhD,1,Technology,2024-02-21,2024-03-13,2053,9,Machine Intelligence Group -AI06338,AI Software Engineer,64003,USD,64003,EN,FL,Israel,M,Israel,100,"R, Git, Statistics, MLOps",Bachelor,1,Energy,2024-12-19,2025-01-22,1438,9.1,Neural Networks Co -AI06339,AI Product Manager,107493,EUR,91369,MI,FT,Netherlands,M,Netherlands,100,"Scala, Spark, Deep Learning",Master,2,Gaming,2024-04-10,2024-05-24,1960,9.6,Machine Intelligence Group -AI06340,Machine Learning Researcher,54975,JPY,6047250,EN,CT,Japan,S,Japan,0,"Hadoop, Git, Python",PhD,1,Real Estate,2025-04-13,2025-05-24,702,7.9,Future Systems -AI06341,AI Research Scientist,157422,USD,157422,SE,PT,Norway,L,Norway,50,"Spark, Statistics, PyTorch, Kubernetes",Master,8,Telecommunications,2024-10-16,2024-12-09,616,5.9,Digital Transformation LLC -AI06342,Computer Vision Engineer,289891,USD,289891,EX,FL,Norway,L,Finland,100,"Kubernetes, TensorFlow, PyTorch",Associate,11,Finance,2024-08-01,2024-09-09,1979,9.5,Machine Intelligence Group -AI06343,AI Research Scientist,111548,CHF,100393,EN,PT,Switzerland,M,Australia,100,"NLP, R, Hadoop, Java",PhD,0,Gaming,2024-08-07,2024-09-14,1085,8.2,AI Innovations -AI06344,Computer Vision Engineer,89985,EUR,76487,MI,PT,Austria,L,Austria,50,"Computer Vision, Spark, MLOps",Bachelor,4,Real Estate,2024-04-19,2024-06-13,2089,8.6,TechCorp Inc -AI06345,Data Engineer,67846,USD,67846,EN,FL,Finland,S,Finland,100,"Hadoop, MLOps, Computer Vision, SQL, Java",Bachelor,1,Healthcare,2024-04-21,2024-06-19,2207,5.6,Algorithmic Solutions -AI06346,Autonomous Systems Engineer,54041,EUR,45935,EN,PT,Austria,S,Austria,0,"TensorFlow, Scala, Kubernetes, Tableau",PhD,1,Transportation,2024-11-28,2024-12-24,919,7,Neural Networks Co -AI06347,Autonomous Systems Engineer,72359,USD,72359,SE,PT,China,L,China,0,"PyTorch, Computer Vision, Java, AWS",PhD,7,Government,2025-03-13,2025-05-07,1032,6.8,Cognitive Computing -AI06348,NLP Engineer,123879,USD,123879,SE,PT,Finland,S,Austria,0,"AWS, Hadoop, Mathematics",Associate,8,Media,2025-04-30,2025-07-02,828,7.2,Predictive Systems -AI06349,AI Product Manager,166701,USD,166701,SE,FL,Ireland,L,Ghana,100,"NLP, Git, Hadoop, PyTorch",Associate,8,Transportation,2024-12-11,2024-12-30,2134,5.5,Quantum Computing Inc -AI06350,AI Product Manager,129156,CAD,161445,SE,PT,Canada,S,Nigeria,50,"PyTorch, SQL, TensorFlow, Kubernetes",Bachelor,8,Education,2024-02-11,2024-03-16,1419,8.9,Cloud AI Solutions -AI06351,NLP Engineer,120933,USD,120933,MI,FL,Denmark,M,Denmark,50,"Mathematics, Computer Vision, GCP, PyTorch, SQL",Bachelor,4,Media,2025-03-23,2025-05-09,1949,5.5,Advanced Robotics -AI06352,Computer Vision Engineer,81946,USD,81946,EN,PT,Finland,L,Indonesia,100,"Deep Learning, Data Visualization, PyTorch, MLOps, Computer Vision",PhD,0,Media,2024-06-12,2024-08-18,814,8.1,AI Innovations -AI06353,Machine Learning Engineer,70100,USD,70100,EN,FT,Sweden,L,Sweden,100,"R, Linux, Mathematics, TensorFlow",Master,1,Telecommunications,2024-08-28,2024-10-07,1311,6.1,Digital Transformation LLC -AI06354,Machine Learning Engineer,159640,CHF,143676,MI,CT,Switzerland,L,Mexico,50,"Hadoop, Python, Azure, Linux, Java",Associate,3,Government,2024-04-01,2024-05-10,915,8.4,Algorithmic Solutions -AI06355,AI Architect,137323,USD,137323,SE,CT,United States,S,United States,100,"Tableau, Deep Learning, Git",Bachelor,5,Media,2025-01-16,2025-03-10,2296,5.5,DataVision Ltd -AI06356,AI Specialist,173170,USD,173170,SE,FL,Norway,S,Germany,100,"Git, Linux, Python, Tableau",Master,6,Consulting,2024-02-12,2024-04-20,501,8.8,DataVision Ltd -AI06357,Data Engineer,72402,SGD,94123,EN,CT,Singapore,M,Argentina,0,"MLOps, Mathematics, Statistics, Scala",Bachelor,0,Telecommunications,2024-12-27,2025-03-08,1616,6.4,DataVision Ltd -AI06358,AI Software Engineer,138464,CAD,173080,SE,FL,Canada,L,Canada,100,"Azure, R, Statistics, Spark, TensorFlow",PhD,8,Automotive,2025-04-02,2025-05-28,2151,8.2,Machine Intelligence Group -AI06359,Research Scientist,132681,USD,132681,SE,FL,Israel,M,Japan,100,"Git, Java, AWS",Associate,6,Gaming,2024-05-25,2024-06-19,1871,9.8,Cognitive Computing -AI06360,Data Engineer,255255,USD,255255,EX,FL,Denmark,M,Nigeria,100,"Azure, GCP, Statistics, SQL, Deep Learning",Bachelor,16,Media,2025-03-12,2025-05-03,1099,6.1,Autonomous Tech -AI06361,Data Scientist,65881,EUR,55999,EN,FT,Netherlands,L,Netherlands,100,"Python, GCP, Data Visualization",PhD,1,Media,2025-01-08,2025-03-05,704,5.1,Advanced Robotics -AI06362,Data Analyst,100927,USD,100927,SE,FT,Israel,M,Israel,100,"Python, Data Visualization, Mathematics, SQL, Java",Bachelor,6,Telecommunications,2024-08-03,2024-08-21,1875,7.6,TechCorp Inc -AI06363,ML Ops Engineer,158295,USD,158295,EX,FL,Ireland,M,Finland,0,"Tableau, Docker, SQL",Associate,18,Telecommunications,2024-04-27,2024-05-18,1494,9.9,DataVision Ltd -AI06364,NLP Engineer,62963,GBP,47222,EN,FL,United Kingdom,M,United Kingdom,50,"Scala, Java, R, SQL",Master,0,Telecommunications,2024-02-06,2024-04-14,535,6.2,Neural Networks Co -AI06365,Machine Learning Researcher,100228,USD,100228,MI,FT,Israel,L,Israel,100,"Java, Mathematics, TensorFlow, Python",Bachelor,2,Consulting,2024-12-24,2025-01-12,1774,5.4,Quantum Computing Inc -AI06366,Computer Vision Engineer,74437,EUR,63271,EN,PT,France,M,Spain,0,"Kubernetes, Python, Spark, Linux, SQL",Bachelor,1,Energy,2024-07-30,2024-09-13,1328,6.8,Cognitive Computing -AI06367,Computer Vision Engineer,82236,USD,82236,EX,CT,China,M,China,50,"MLOps, SQL, Statistics, Scala",Associate,16,Healthcare,2024-08-21,2024-10-10,2143,5.8,Algorithmic Solutions -AI06368,Data Analyst,161597,EUR,137357,EX,FT,Germany,L,Portugal,100,"PyTorch, Mathematics, Hadoop, NLP",Master,10,Technology,2024-09-02,2024-10-16,1862,5.3,Smart Analytics -AI06369,Research Scientist,158726,USD,158726,EX,FT,United States,S,United States,0,"Kubernetes, R, Computer Vision, Deep Learning, Statistics",Associate,19,Energy,2024-06-24,2024-08-20,1436,7.4,Autonomous Tech -AI06370,Robotics Engineer,42660,USD,42660,SE,FT,India,M,India,0,"NLP, SQL, Git, PyTorch",Master,6,Consulting,2024-08-21,2024-09-14,1864,5.6,Cognitive Computing -AI06371,Head of AI,201912,CHF,181721,EX,FL,Switzerland,S,Switzerland,100,"Python, R, Data Visualization, Computer Vision",PhD,14,Healthcare,2024-10-19,2024-11-23,755,7.7,Predictive Systems -AI06372,AI Research Scientist,16975,USD,16975,EN,FL,India,S,India,50,"Deep Learning, SQL, MLOps, R, Docker",Bachelor,1,Telecommunications,2024-04-07,2024-05-27,1613,8.3,Quantum Computing Inc -AI06373,Data Analyst,65768,USD,65768,EN,FT,United States,M,Czech Republic,0,"Java, Hadoop, Kubernetes, Computer Vision, Statistics",Bachelor,1,Education,2024-06-05,2024-07-05,589,5.9,AI Innovations -AI06374,Machine Learning Engineer,31201,USD,31201,MI,FL,India,M,India,0,"Linux, GCP, Data Visualization",Bachelor,4,Retail,2024-01-18,2024-02-12,1186,6.2,Advanced Robotics -AI06375,AI Research Scientist,99393,EUR,84484,MI,FL,France,L,China,50,"Mathematics, Docker, Python, TensorFlow, Tableau",Master,2,Consulting,2024-08-13,2024-09-20,523,8.9,DeepTech Ventures -AI06376,Data Analyst,184065,EUR,156455,EX,FT,Germany,L,Germany,50,"Kubernetes, PyTorch, Tableau, Mathematics",PhD,12,Gaming,2025-04-03,2025-05-13,703,6.7,TechCorp Inc -AI06377,AI Specialist,173893,USD,173893,SE,CT,Norway,M,Norway,0,"AWS, Mathematics, Python",Master,6,Gaming,2024-05-27,2024-08-03,1454,5.5,Cloud AI Solutions -AI06378,NLP Engineer,112570,USD,112570,SE,FL,South Korea,S,Romania,50,"Spark, Git, MLOps, Scala",PhD,6,Technology,2025-01-29,2025-02-20,1131,8.1,TechCorp Inc -AI06379,AI Product Manager,86672,USD,86672,MI,CT,Finland,M,Finland,50,"Git, R, Docker, AWS",Bachelor,2,Automotive,2024-08-28,2024-10-27,849,7.3,Future Systems -AI06380,Data Scientist,225977,USD,225977,SE,FL,Norway,L,Argentina,50,"Linux, Data Visualization, Spark",PhD,9,Consulting,2024-11-21,2024-12-05,1561,5.2,Digital Transformation LLC -AI06381,AI Consultant,65278,AUD,88125,MI,CT,Australia,S,Austria,100,"AWS, Data Visualization, Tableau",Master,4,Real Estate,2024-02-20,2024-03-09,1960,5.2,Predictive Systems -AI06382,Robotics Engineer,103808,EUR,88237,SE,CT,Austria,S,Norway,100,"Data Visualization, MLOps, Tableau, PyTorch",PhD,7,Education,2024-06-21,2024-07-08,2354,8.6,TechCorp Inc -AI06383,Data Analyst,202963,CAD,253704,EX,FL,Canada,M,Canada,50,"Deep Learning, Scala, Python, Mathematics",Bachelor,11,Technology,2024-03-02,2024-04-12,568,5.6,Neural Networks Co -AI06384,ML Ops Engineer,85463,USD,85463,EX,FT,China,S,China,100,"Scala, Kubernetes, Deep Learning, NLP",Associate,15,Healthcare,2024-08-22,2024-10-15,1703,7.8,TechCorp Inc -AI06385,AI Consultant,104466,USD,104466,EN,FT,Norway,L,Norway,100,"Kubernetes, PyTorch, Hadoop, Computer Vision",PhD,1,Healthcare,2025-01-22,2025-03-04,1730,6.4,Algorithmic Solutions -AI06386,Machine Learning Engineer,63202,USD,63202,MI,FL,South Korea,M,Poland,50,"Python, SQL, Statistics, Spark",Bachelor,3,Telecommunications,2025-03-08,2025-04-10,2044,6.1,Neural Networks Co -AI06387,Head of AI,120132,USD,120132,SE,PT,Norway,S,Norway,0,"Java, SQL, Python, R, Linux",Bachelor,5,Education,2024-03-25,2024-05-09,1500,5,Autonomous Tech -AI06388,Robotics Engineer,83672,CHF,75305,EN,CT,Switzerland,S,India,100,"NLP, Data Visualization, Tableau",Bachelor,1,Automotive,2024-12-11,2024-12-25,2484,6,DeepTech Ventures -AI06389,Data Analyst,74974,USD,74974,EN,FT,Norway,S,Norway,0,"SQL, Computer Vision, R, Hadoop",PhD,1,Healthcare,2024-03-20,2024-05-27,899,8,DeepTech Ventures -AI06390,Research Scientist,70564,USD,70564,EN,CT,Sweden,S,Sweden,50,"SQL, Data Visualization, GCP, MLOps",Master,0,Government,2024-02-26,2024-05-08,2322,8.4,Neural Networks Co -AI06391,AI Consultant,181975,SGD,236568,SE,FL,Singapore,L,South Korea,0,"Azure, Java, Hadoop, PyTorch",Master,6,Transportation,2024-04-30,2024-06-30,2186,5.1,Digital Transformation LLC -AI06392,Data Scientist,125178,CHF,112660,EN,CT,Switzerland,L,Switzerland,100,"Docker, Azure, SQL, Computer Vision",Bachelor,1,Government,2025-03-10,2025-05-04,1828,8,Smart Analytics -AI06393,AI Software Engineer,118802,USD,118802,EX,FT,South Korea,M,Estonia,0,"GCP, Docker, Computer Vision",PhD,10,Education,2024-08-29,2024-10-17,2036,8.6,Cognitive Computing -AI06394,Autonomous Systems Engineer,96565,USD,96565,SE,FL,Ireland,S,Ireland,50,"Mathematics, Python, TensorFlow, Spark, Hadoop",Master,9,Healthcare,2025-03-24,2025-05-18,1179,6.5,Cognitive Computing -AI06395,NLP Engineer,31256,USD,31256,EN,FL,China,S,Singapore,0,"AWS, Docker, Linux, Kubernetes",PhD,1,Energy,2025-04-18,2025-06-06,1804,5.5,Future Systems -AI06396,Data Engineer,75314,USD,75314,EN,FL,Finland,M,Finland,50,"Tableau, PyTorch, Statistics, NLP",PhD,1,Media,2024-10-29,2024-11-12,1581,7.3,Smart Analytics -AI06397,Research Scientist,51533,USD,51533,EN,FT,Sweden,M,Nigeria,0,"Computer Vision, AWS, GCP, Kubernetes",Associate,1,Finance,2024-12-29,2025-01-13,2031,10,Cloud AI Solutions -AI06398,Data Engineer,121829,USD,121829,MI,CT,Ireland,L,Ireland,0,"Python, Docker, Mathematics, Kubernetes",Associate,2,Automotive,2024-07-10,2024-08-01,2140,6.7,Future Systems -AI06399,AI Research Scientist,138335,EUR,117585,EX,PT,Germany,M,Germany,100,"Kubernetes, Spark, Statistics",Associate,19,Transportation,2025-04-21,2025-05-13,808,6.3,Quantum Computing Inc -AI06400,Data Engineer,143264,EUR,121774,SE,CT,Netherlands,M,Netherlands,50,"Hadoop, GCP, NLP",Bachelor,9,Healthcare,2024-02-05,2024-03-21,1023,9.2,Autonomous Tech -AI06401,Principal Data Scientist,121815,EUR,103543,SE,CT,Germany,L,Germany,50,"Scala, Python, Spark, MLOps",Associate,7,Manufacturing,2024-10-11,2024-12-13,1914,9.1,Digital Transformation LLC -AI06402,AI Consultant,49981,USD,49981,EN,PT,Finland,S,Thailand,0,"Python, AWS, SQL, NLP",PhD,1,Energy,2024-12-12,2025-02-17,1018,9.2,DataVision Ltd -AI06403,AI Specialist,150416,EUR,127854,EX,FL,Germany,M,Germany,100,"AWS, Python, TensorFlow, PyTorch, GCP",PhD,13,Telecommunications,2024-05-02,2024-07-03,2420,5.3,Quantum Computing Inc -AI06404,AI Software Engineer,121297,CHF,109167,EN,PT,Switzerland,L,Switzerland,0,"Scala, Docker, Mathematics, AWS, Java",PhD,0,Consulting,2024-06-06,2024-06-27,2283,6.8,AI Innovations -AI06405,Deep Learning Engineer,213889,AUD,288750,EX,FL,Australia,S,Australia,50,"Git, Mathematics, PyTorch, Java",Associate,11,Technology,2024-04-30,2024-06-15,2273,7.6,Algorithmic Solutions -AI06406,Deep Learning Engineer,130442,USD,130442,MI,CT,United States,L,United States,50,"Statistics, Git, PyTorch",PhD,2,Gaming,2024-03-19,2024-05-10,1768,5.4,Algorithmic Solutions -AI06407,Computer Vision Engineer,206439,CAD,258049,EX,FT,Canada,S,Canada,0,"Linux, Deep Learning, NLP",Master,10,Government,2024-01-18,2024-02-03,1229,8.2,AI Innovations -AI06408,Data Analyst,34594,USD,34594,EN,PT,China,L,China,100,"NLP, AWS, Azure, Python",Associate,0,Automotive,2025-04-20,2025-06-24,624,7,AI Innovations -AI06409,Deep Learning Engineer,162384,USD,162384,SE,PT,Israel,L,Kenya,100,"GCP, SQL, Linux",PhD,6,Automotive,2024-12-10,2025-02-19,2298,7.3,Advanced Robotics -AI06410,Data Analyst,102488,CAD,128110,SE,FT,Canada,M,Canada,50,"Statistics, MLOps, TensorFlow, Data Visualization, Spark",Associate,5,Consulting,2024-10-13,2024-11-13,680,8.7,TechCorp Inc -AI06411,ML Ops Engineer,156199,USD,156199,EX,FL,Finland,S,Finland,50,"R, Data Visualization, Docker",PhD,17,Automotive,2024-12-11,2025-02-11,2456,7.6,AI Innovations -AI06412,AI Software Engineer,150000,USD,150000,EX,FT,South Korea,L,South Korea,100,"Kubernetes, Azure, Spark",Associate,16,Government,2025-04-01,2025-04-23,939,9.9,Autonomous Tech -AI06413,Data Scientist,111963,CAD,139954,SE,FT,Canada,L,Canada,100,"Statistics, Scala, Linux",Master,5,Finance,2024-09-15,2024-10-08,638,6.8,Cloud AI Solutions -AI06414,Data Engineer,67558,USD,67558,MI,FL,Sweden,S,Sweden,50,"NLP, Python, Mathematics, AWS, Scala",Bachelor,3,Education,2024-02-01,2024-02-27,2198,5.2,Future Systems -AI06415,Data Scientist,75401,EUR,64091,MI,FL,France,M,France,100,"SQL, Linux, Kubernetes, Java, PyTorch",Bachelor,3,Automotive,2024-01-06,2024-01-25,2376,5.6,AI Innovations -AI06416,AI Research Scientist,77098,CHF,69388,EN,FL,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, GCP, Statistics",Master,1,Healthcare,2024-02-10,2024-04-19,1408,5.9,Future Systems -AI06417,Data Engineer,129667,GBP,97250,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Git, NLP, AWS",Associate,4,Telecommunications,2024-04-08,2024-05-17,1925,9.2,AI Innovations -AI06418,Robotics Engineer,62417,EUR,53054,EN,FL,Netherlands,M,Netherlands,100,"Python, R, Docker",PhD,0,Government,2024-07-22,2024-08-11,1830,6.3,Machine Intelligence Group -AI06419,AI Consultant,161660,JPY,17782600,SE,PT,Japan,M,Romania,0,"Computer Vision, Python, GCP",PhD,6,Real Estate,2024-05-04,2024-05-18,1197,6.1,Advanced Robotics -AI06420,Computer Vision Engineer,85425,AUD,115324,MI,PT,Australia,S,Australia,0,"Spark, Git, Python, Computer Vision, NLP",Associate,4,Consulting,2024-08-12,2024-10-07,1642,8.8,DeepTech Ventures -AI06421,AI Product Manager,269941,CHF,242947,EX,PT,Switzerland,S,Switzerland,0,"SQL, GCP, NLP, Spark",PhD,17,Finance,2024-01-06,2024-03-12,2138,7.5,Advanced Robotics -AI06422,Data Analyst,349432,USD,349432,EX,FT,Denmark,L,Denmark,0,"SQL, Linux, GCP, Hadoop, R",Associate,17,Energy,2024-10-17,2024-12-13,1557,9.9,Quantum Computing Inc -AI06423,Autonomous Systems Engineer,52126,USD,52126,SE,CT,China,S,Brazil,100,"Hadoop, Git, Java",Master,9,Government,2024-09-18,2024-11-02,1709,8,Predictive Systems -AI06424,AI Product Manager,166822,EUR,141799,EX,PT,Germany,M,Germany,0,"Hadoop, Data Visualization, Scala",PhD,11,Consulting,2025-01-23,2025-02-17,2222,5.9,Digital Transformation LLC -AI06425,Robotics Engineer,136925,AUD,184849,EX,CT,Australia,S,Australia,100,"MLOps, AWS, Python, Scala",Associate,17,Healthcare,2024-09-08,2024-09-30,2197,7.5,Advanced Robotics -AI06426,Deep Learning Engineer,98877,CAD,123596,MI,FT,Canada,L,Canada,100,"TensorFlow, Azure, Linux, Git",Master,2,Energy,2024-01-06,2024-03-18,871,5.4,Digital Transformation LLC -AI06427,Deep Learning Engineer,168236,EUR,143001,EX,FT,France,M,France,100,"AWS, Kubernetes, PyTorch",Bachelor,18,Telecommunications,2024-04-08,2024-05-15,1463,7.3,Advanced Robotics -AI06428,Machine Learning Engineer,102521,CAD,128151,MI,PT,Canada,L,Canada,100,"Kubernetes, R, SQL, Python",Bachelor,3,Gaming,2024-04-24,2024-06-19,697,6.9,Machine Intelligence Group -AI06429,Robotics Engineer,106928,USD,106928,MI,PT,Norway,M,Vietnam,0,"TensorFlow, Statistics, Spark",Associate,4,Real Estate,2024-11-10,2025-01-18,829,7.9,DeepTech Ventures -AI06430,Data Scientist,76026,GBP,57020,EN,FL,United Kingdom,S,United Kingdom,100,"Python, Docker, AWS, TensorFlow",PhD,0,Healthcare,2024-02-06,2024-03-14,2063,8.2,Algorithmic Solutions -AI06431,AI Specialist,88213,USD,88213,EN,FT,Sweden,L,Sweden,100,"Linux, TensorFlow, Computer Vision, Python, Hadoop",PhD,1,Energy,2024-05-03,2024-05-19,1771,8.7,Quantum Computing Inc -AI06432,AI Architect,82027,USD,82027,EN,FL,Sweden,L,Romania,0,"Mathematics, Hadoop, Scala",Associate,0,Media,2025-01-10,2025-01-25,2035,6.7,Advanced Robotics -AI06433,Robotics Engineer,109435,USD,109435,EN,FT,Denmark,L,Denmark,100,"Mathematics, GCP, Linux, MLOps, Python",PhD,1,Real Estate,2024-01-10,2024-03-01,545,8.5,Cognitive Computing -AI06434,Autonomous Systems Engineer,123502,AUD,166728,MI,FL,Australia,L,Sweden,100,"Python, Kubernetes, Deep Learning, Computer Vision, Hadoop",Associate,2,Education,2024-07-29,2024-08-27,1793,8,DataVision Ltd -AI06435,Autonomous Systems Engineer,80462,USD,80462,EN,PT,United States,S,Brazil,100,"Kubernetes, AWS, Hadoop",Associate,1,Consulting,2024-12-24,2025-01-24,1904,7.9,Machine Intelligence Group -AI06436,Machine Learning Engineer,109229,USD,109229,MI,PT,Ireland,M,Ireland,50,"Statistics, TensorFlow, Azure, GCP",PhD,4,Telecommunications,2024-04-09,2024-05-02,2303,9.2,Advanced Robotics -AI06437,AI Consultant,159957,EUR,135963,SE,FL,Netherlands,L,Netherlands,50,"GCP, TensorFlow, SQL, Computer Vision, Hadoop",Associate,9,Consulting,2024-07-17,2024-09-06,1452,5.2,Cloud AI Solutions -AI06438,Head of AI,65788,USD,65788,MI,CT,Sweden,S,Portugal,0,"Git, Tableau, Python",PhD,2,Retail,2024-10-17,2024-12-20,1066,9,Predictive Systems -AI06439,AI Software Engineer,100348,USD,100348,MI,FT,Ireland,L,Ireland,100,"Hadoop, Python, Git, AWS, Docker",Bachelor,2,Retail,2024-07-02,2024-09-07,2267,8,Digital Transformation LLC -AI06440,Computer Vision Engineer,47408,USD,47408,SE,FT,China,S,China,50,"NLP, Tableau, Python",Master,6,Gaming,2024-06-14,2024-08-26,2076,6.8,Machine Intelligence Group -AI06441,ML Ops Engineer,104139,USD,104139,SE,FT,Finland,M,Romania,100,"Python, TensorFlow, Statistics, Git",Associate,7,Energy,2024-10-29,2024-12-22,2233,9.6,Autonomous Tech -AI06442,AI Product Manager,88730,JPY,9760300,EN,FL,Japan,L,Japan,0,"R, Spark, MLOps, TensorFlow",PhD,1,Media,2024-05-23,2024-06-30,888,7.2,DataVision Ltd -AI06443,AI Product Manager,352205,USD,352205,EX,FT,Denmark,L,Denmark,100,"Computer Vision, Python, Tableau, NLP",Bachelor,16,Media,2024-10-27,2024-11-28,1380,6.6,Neural Networks Co -AI06444,AI Research Scientist,98921,EUR,84083,MI,FT,Austria,L,Austria,0,"Kubernetes, TensorFlow, Computer Vision, Git, NLP",PhD,2,Finance,2024-11-25,2025-01-28,2210,6.2,DeepTech Ventures -AI06445,Robotics Engineer,183596,EUR,156057,EX,CT,Netherlands,S,Netherlands,100,"Hadoop, Scala, Mathematics",Bachelor,19,Energy,2024-01-01,2024-03-11,1209,8.8,DataVision Ltd -AI06446,AI Architect,80147,USD,80147,MI,CT,Sweden,M,Denmark,50,"Python, Spark, GCP, Deep Learning, MLOps",PhD,2,Automotive,2024-03-28,2024-04-27,2364,6.9,Cloud AI Solutions -AI06447,Head of AI,38802,USD,38802,EN,FL,South Korea,S,South Korea,50,"Data Visualization, Git, Spark",Master,0,Manufacturing,2024-12-28,2025-02-14,1953,9.4,Quantum Computing Inc -AI06448,Robotics Engineer,42256,USD,42256,EN,FT,South Korea,M,South Korea,50,"PyTorch, GCP, SQL, Data Visualization",Bachelor,1,Automotive,2024-04-04,2024-05-22,2290,7.2,DataVision Ltd -AI06449,Machine Learning Researcher,295649,JPY,32521390,EX,FL,Japan,L,Japan,100,"Git, Mathematics, R, Python, Azure",Associate,10,Technology,2024-11-14,2025-01-12,2439,7.2,Cloud AI Solutions -AI06450,Head of AI,139693,GBP,104770,SE,PT,United Kingdom,S,United Kingdom,0,"GCP, Git, Tableau, MLOps",Master,5,Media,2025-03-24,2025-04-22,1262,5,AI Innovations -AI06451,Deep Learning Engineer,252118,USD,252118,EX,FT,Norway,S,Norway,50,"Hadoop, Computer Vision, Python",Associate,12,Automotive,2024-12-02,2025-02-03,1914,5.3,DataVision Ltd -AI06452,Research Scientist,96310,USD,96310,MI,FL,South Korea,L,South Korea,100,"Python, NLP, TensorFlow",Master,3,Real Estate,2024-09-30,2024-10-15,880,7.3,Advanced Robotics -AI06453,Machine Learning Researcher,97905,USD,97905,EX,FL,China,M,United States,50,"Python, Git, Statistics, Computer Vision, Linux",Bachelor,11,Consulting,2024-08-08,2024-09-15,1148,8.1,Smart Analytics -AI06454,AI Product Manager,74082,GBP,55562,EN,PT,United Kingdom,L,United Kingdom,50,"Python, Spark, Tableau, Mathematics, Linux",Master,0,Automotive,2024-08-27,2024-10-01,1197,9.4,Cloud AI Solutions -AI06455,ML Ops Engineer,189768,CHF,170791,SE,FL,Switzerland,S,Switzerland,100,"AWS, Linux, MLOps",Associate,5,Consulting,2024-01-19,2024-03-23,1493,9.4,AI Innovations -AI06456,AI Software Engineer,66570,USD,66570,EN,CT,Sweden,S,Philippines,50,"Computer Vision, GCP, Tableau",Master,1,Telecommunications,2024-07-07,2024-09-08,1957,5.9,Digital Transformation LLC -AI06457,Machine Learning Researcher,326160,CHF,293544,EX,FL,Switzerland,M,Indonesia,100,"Python, Java, Azure",Associate,16,Gaming,2025-01-04,2025-03-02,902,5.9,Cognitive Computing -AI06458,AI Research Scientist,78922,JPY,8681420,EN,FT,Japan,M,Japan,50,"Deep Learning, Computer Vision, PyTorch",Associate,0,Retail,2024-10-15,2024-12-27,1123,5.8,Quantum Computing Inc -AI06459,Data Analyst,49976,USD,49976,MI,PT,China,M,China,100,"Python, GCP, Tableau, SQL",Bachelor,2,Government,2024-12-24,2025-02-03,2010,8.6,Quantum Computing Inc -AI06460,Machine Learning Researcher,64771,USD,64771,EX,CT,China,M,China,50,"Tableau, Python, AWS, Spark, TensorFlow",PhD,10,Government,2025-04-03,2025-05-02,2118,9.9,Neural Networks Co -AI06461,Data Scientist,77752,EUR,66089,EN,CT,Netherlands,M,Netherlands,0,"R, GCP, Tableau, Python, AWS",Master,1,Transportation,2024-01-15,2024-03-05,818,8.1,TechCorp Inc -AI06462,AI Consultant,101180,AUD,136593,SE,CT,Australia,S,India,100,"Java, Data Visualization, PyTorch, Kubernetes, TensorFlow",Associate,5,Telecommunications,2024-04-24,2024-05-13,1032,8.6,Future Systems -AI06463,Computer Vision Engineer,207576,EUR,176440,EX,FL,France,L,France,50,"Statistics, NLP, Scala, Data Visualization",Associate,10,Manufacturing,2025-04-30,2025-05-21,716,8.2,Advanced Robotics -AI06464,AI Software Engineer,30028,USD,30028,MI,FL,India,L,India,50,"Tableau, Kubernetes, GCP, R, Deep Learning",Bachelor,4,Media,2024-01-15,2024-03-04,1402,9.2,Smart Analytics -AI06465,Robotics Engineer,243505,CAD,304381,EX,FT,Canada,L,Canada,50,"Spark, Scala, SQL, Java",Bachelor,12,Finance,2024-07-29,2024-09-12,2274,5.4,TechCorp Inc -AI06466,Robotics Engineer,51214,USD,51214,EN,FT,Finland,S,Finland,0,"Azure, GCP, Java",Master,1,Retail,2024-06-22,2024-07-06,802,7.3,Quantum Computing Inc -AI06467,Data Scientist,76863,CHF,69177,EN,CT,Switzerland,M,Switzerland,0,"Scala, Git, Statistics",Associate,0,Energy,2024-02-05,2024-03-24,1557,7.6,Predictive Systems -AI06468,Machine Learning Engineer,179636,USD,179636,SE,FL,United States,L,United States,0,"Mathematics, Linux, Hadoop, Deep Learning",Master,8,Consulting,2024-12-16,2025-01-29,2432,6.7,Predictive Systems -AI06469,Robotics Engineer,30950,USD,30950,MI,PT,India,L,France,50,"R, SQL, Statistics",PhD,3,Consulting,2024-02-08,2024-03-15,1262,9.1,AI Innovations -AI06470,Principal Data Scientist,148429,USD,148429,SE,CT,Finland,L,South Africa,100,"PyTorch, Computer Vision, TensorFlow, SQL, Java",Associate,5,Manufacturing,2024-08-16,2024-09-13,717,8.9,TechCorp Inc -AI06471,AI Specialist,49035,EUR,41680,EN,FL,Austria,S,Netherlands,100,"Azure, Linux, MLOps",Master,1,Government,2024-11-20,2024-12-28,1457,8.6,Machine Intelligence Group -AI06472,AI Specialist,75189,SGD,97746,EN,CT,Singapore,M,Norway,0,"Mathematics, Azure, TensorFlow, Computer Vision, Hadoop",Master,0,Transportation,2024-12-02,2025-01-04,598,5.7,DeepTech Ventures -AI06473,Robotics Engineer,71967,GBP,53975,EN,PT,United Kingdom,L,United Kingdom,0,"Scala, Tableau, Hadoop, MLOps, NLP",Associate,0,Gaming,2024-05-18,2024-07-10,1985,8.9,Advanced Robotics -AI06474,NLP Engineer,190712,CAD,238390,EX,CT,Canada,S,Canada,50,"PyTorch, R, Kubernetes, Azure",Master,12,Media,2024-12-21,2025-01-10,1967,9.3,DataVision Ltd -AI06475,NLP Engineer,297771,GBP,223328,EX,FL,United Kingdom,L,United Kingdom,50,"AWS, Linux, PyTorch, Azure",PhD,14,Gaming,2025-02-24,2025-03-21,1502,5.7,Future Systems -AI06476,AI Specialist,156829,USD,156829,EX,FT,South Korea,S,South Korea,0,"SQL, Scala, Deep Learning, GCP",Associate,13,Consulting,2025-04-19,2025-05-17,762,7.6,AI Innovations -AI06477,ML Ops Engineer,143894,EUR,122310,EX,CT,France,M,Indonesia,0,"Python, TensorFlow, Computer Vision, Spark",PhD,18,Automotive,2025-04-21,2025-05-12,1614,7.7,Predictive Systems -AI06478,AI Software Engineer,150682,CHF,135614,MI,CT,Switzerland,M,Switzerland,100,"Java, PyTorch, Azure",Master,3,Education,2024-01-15,2024-02-13,1957,6.2,Algorithmic Solutions -AI06479,AI Product Manager,72926,USD,72926,EN,CT,United States,M,United States,0,"Python, Kubernetes, TensorFlow, Mathematics, Docker",PhD,1,Consulting,2024-08-26,2024-09-23,2383,9.7,Future Systems -AI06480,AI Specialist,50034,USD,50034,MI,FL,China,M,China,50,"Computer Vision, Azure, Kubernetes, Scala, MLOps",Associate,3,Healthcare,2025-04-14,2025-05-24,1718,9.8,DataVision Ltd -AI06481,Machine Learning Engineer,227301,USD,227301,EX,FL,Sweden,M,Sweden,0,"Linux, Tableau, R, Docker, Statistics",Bachelor,12,Manufacturing,2024-03-16,2024-05-07,1933,9.2,Future Systems -AI06482,Data Engineer,177520,GBP,133140,SE,FL,United Kingdom,L,Portugal,0,"Scala, Mathematics, Spark, Kubernetes",Associate,7,Retail,2024-12-03,2025-01-10,1975,8.3,Machine Intelligence Group -AI06483,AI Product Manager,290219,CHF,261197,EX,FT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Linux, TensorFlow",Associate,19,Finance,2024-07-22,2024-09-22,513,5.8,DataVision Ltd -AI06484,AI Research Scientist,178653,EUR,151855,EX,CT,Austria,L,Germany,0,"GCP, Kubernetes, Python",Master,18,Healthcare,2025-01-20,2025-02-14,1825,7.3,Autonomous Tech -AI06485,AI Product Manager,122006,EUR,103705,SE,CT,Germany,M,Germany,0,"Git, NLP, Linux, Scala, Data Visualization",Associate,8,Finance,2025-02-07,2025-04-09,1514,9.6,Neural Networks Co -AI06486,Robotics Engineer,168307,GBP,126230,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, SQL",Master,12,Finance,2024-12-01,2024-12-30,1505,9.9,DeepTech Ventures -AI06487,Principal Data Scientist,124629,USD,124629,EX,FT,South Korea,M,South Korea,50,"Git, Python, Azure",PhD,19,Real Estate,2024-12-02,2025-02-12,1102,8.1,Algorithmic Solutions -AI06488,Data Engineer,137796,EUR,117127,EX,CT,Austria,S,Austria,0,"Statistics, TensorFlow, Kubernetes, Linux",PhD,13,Government,2024-08-04,2024-08-28,1582,6.4,DeepTech Ventures -AI06489,AI Specialist,81533,EUR,69303,EN,CT,France,L,France,0,"Data Visualization, Docker, Tableau",Bachelor,1,Telecommunications,2025-04-08,2025-05-21,1781,5.6,Future Systems -AI06490,Principal Data Scientist,86860,USD,86860,EX,CT,China,S,Estonia,50,"SQL, Git, Kubernetes, Deep Learning",Master,18,Consulting,2024-09-02,2024-10-17,1805,7.6,AI Innovations -AI06491,Data Engineer,81781,EUR,69514,EN,FL,Netherlands,L,Netherlands,100,"PyTorch, Computer Vision, Deep Learning, TensorFlow, Azure",PhD,1,Telecommunications,2025-01-15,2025-03-04,2388,5.5,Predictive Systems -AI06492,AI Product Manager,140704,USD,140704,SE,FL,Finland,M,Finland,0,"PyTorch, SQL, Deep Learning, Tableau, NLP",Bachelor,8,Retail,2024-02-05,2024-03-24,1057,5.1,Cognitive Computing -AI06493,AI Specialist,61576,EUR,52340,EN,FL,Germany,S,Germany,50,"Spark, Linux, Git, R, Deep Learning",PhD,0,Consulting,2024-04-02,2024-04-25,698,9.1,Cloud AI Solutions -AI06494,AI Research Scientist,29955,USD,29955,EN,CT,China,M,Netherlands,50,"Hadoop, SQL, Azure, Kubernetes, Tableau",Associate,0,Transportation,2025-02-28,2025-03-26,1800,8.1,DataVision Ltd -AI06495,Computer Vision Engineer,107488,EUR,91365,SE,PT,Netherlands,S,Turkey,0,"Mathematics, Docker, Kubernetes, SQL, TensorFlow",Associate,6,Transportation,2024-03-27,2024-04-20,503,9.8,Autonomous Tech -AI06496,AI Specialist,18247,USD,18247,EN,PT,India,S,India,0,"Scala, Python, Computer Vision, Deep Learning, TensorFlow",Master,1,Gaming,2024-10-09,2024-10-30,1178,7.9,Algorithmic Solutions -AI06497,Machine Learning Engineer,141464,USD,141464,MI,FT,Norway,M,Norway,100,"Git, Java, AWS",PhD,2,Real Estate,2024-02-03,2024-03-11,1296,6.7,AI Innovations -AI06498,AI Product Manager,41759,USD,41759,SE,FL,India,S,India,100,"Mathematics, Scala, MLOps, Statistics, Linux",Master,6,Gaming,2024-01-26,2024-03-05,1858,7.6,Cloud AI Solutions -AI06499,Data Analyst,55004,JPY,6050440,EN,PT,Japan,M,Japan,100,"Git, Kubernetes, NLP",Associate,1,Gaming,2024-02-14,2024-03-20,2454,7,DeepTech Ventures -AI06500,AI Consultant,43128,USD,43128,MI,CT,China,M,China,100,"TensorFlow, Java, Azure, Mathematics, AWS",PhD,4,Transportation,2024-01-22,2024-02-20,871,7.8,Machine Intelligence Group -AI06501,AI Consultant,82614,EUR,70222,EN,CT,Germany,L,Vietnam,100,"Azure, Kubernetes, SQL",Bachelor,1,Real Estate,2024-03-17,2024-05-26,2454,7.5,Smart Analytics -AI06502,AI Research Scientist,306002,EUR,260102,EX,PT,Netherlands,L,Netherlands,100,"Linux, Hadoop, Azure, Deep Learning",Associate,17,Automotive,2024-12-17,2025-02-08,1412,9.2,Cloud AI Solutions -AI06503,Deep Learning Engineer,129451,USD,129451,SE,PT,Ireland,S,Austria,50,"Python, Linux, Deep Learning, Git, Computer Vision",Bachelor,8,Automotive,2024-10-15,2024-11-05,1411,10,Cognitive Computing -AI06504,AI Architect,192815,CHF,173534,EX,FL,Switzerland,M,Switzerland,50,"Git, SQL, TensorFlow",Master,11,Retail,2024-01-02,2024-01-29,2257,8.8,Autonomous Tech -AI06505,Research Scientist,133972,USD,133972,EX,FT,Israel,M,Singapore,0,"AWS, Kubernetes, Mathematics",Bachelor,12,Healthcare,2024-05-14,2024-06-12,1654,6.5,Digital Transformation LLC -AI06506,Data Scientist,77616,USD,77616,MI,FL,South Korea,S,South Korea,50,"AWS, TensorFlow, Scala, Tableau, Deep Learning",Master,4,Technology,2025-04-07,2025-06-12,665,5.5,Machine Intelligence Group -AI06507,Principal Data Scientist,47133,USD,47133,EN,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Spark, NLP, Java",Associate,1,Energy,2025-03-14,2025-04-03,533,5.1,Cognitive Computing -AI06508,Research Scientist,70801,USD,70801,MI,CT,South Korea,S,South Korea,100,"Tableau, Python, Java",Associate,3,Retail,2024-07-18,2024-08-10,1335,6.1,DeepTech Ventures -AI06509,AI Specialist,120997,USD,120997,SE,FL,Finland,M,Finland,50,"AWS, Deep Learning, SQL, Scala",Associate,9,Automotive,2024-05-03,2024-07-06,2203,6.7,Digital Transformation LLC -AI06510,AI Product Manager,263003,EUR,223553,EX,FL,Austria,L,Austria,100,"Scala, R, Hadoop, Deep Learning",Bachelor,15,Real Estate,2024-02-01,2024-03-18,851,6.6,Neural Networks Co -AI06511,AI Consultant,48759,GBP,36569,EN,PT,United Kingdom,S,Australia,50,"Azure, Java, Linux",PhD,0,Transportation,2024-08-30,2024-10-04,1794,7.8,Cognitive Computing -AI06512,Machine Learning Engineer,195629,GBP,146722,EX,CT,United Kingdom,S,United Kingdom,100,"R, GCP, Git",Associate,17,Energy,2024-12-30,2025-02-21,1765,8,Algorithmic Solutions -AI06513,AI Research Scientist,161173,USD,161173,SE,PT,Norway,L,Norway,0,"Computer Vision, AWS, Linux, Spark",Bachelor,9,Gaming,2024-10-01,2024-11-09,968,9.3,Digital Transformation LLC -AI06514,AI Consultant,94896,USD,94896,SE,CT,South Korea,S,South Korea,100,"Python, MLOps, Azure, Tableau",Associate,7,Finance,2024-02-05,2024-03-06,1668,5.9,Cognitive Computing -AI06515,AI Architect,47417,USD,47417,EN,FL,Israel,S,Israel,0,"Spark, Docker, Computer Vision",Bachelor,1,Retail,2025-02-14,2025-03-27,1934,6.2,AI Innovations -AI06516,Deep Learning Engineer,90359,AUD,121985,MI,FL,Australia,S,Australia,50,"Kubernetes, MLOps, Hadoop",Master,3,Government,2024-12-24,2025-02-05,1562,8.3,Advanced Robotics -AI06517,AI Research Scientist,123662,GBP,92747,MI,FL,United Kingdom,L,China,50,"Linux, Data Visualization, Hadoop",Master,2,Energy,2024-07-02,2024-07-21,2185,9,Predictive Systems -AI06518,Machine Learning Researcher,146667,AUD,198000,SE,PT,Australia,M,Australia,50,"R, PyTorch, Linux, Mathematics",Bachelor,5,Retail,2024-03-28,2024-04-18,2204,6.1,Digital Transformation LLC -AI06519,Data Scientist,66452,EUR,56484,EN,FT,Germany,S,Germany,50,"Java, Kubernetes, Tableau, NLP",Associate,0,Government,2024-12-04,2025-01-09,1711,8,Algorithmic Solutions -AI06520,Principal Data Scientist,50813,GBP,38110,EN,CT,United Kingdom,S,United Kingdom,0,"Python, Mathematics, Data Visualization, Spark, TensorFlow",Associate,1,Healthcare,2024-12-11,2025-01-30,880,6.1,DeepTech Ventures -AI06521,AI Research Scientist,226711,USD,226711,EX,PT,Sweden,L,Sweden,50,"SQL, Tableau, Python",Master,17,Consulting,2025-03-27,2025-04-14,1098,6.8,DeepTech Ventures -AI06522,AI Specialist,145967,EUR,124072,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Python, Hadoop, Docker",PhD,15,Education,2025-02-04,2025-02-24,913,5.1,Predictive Systems -AI06523,Machine Learning Engineer,214976,USD,214976,EX,CT,Sweden,S,Sweden,0,"Python, Kubernetes, PyTorch",Master,11,Manufacturing,2024-04-16,2024-06-01,2129,7,Cognitive Computing -AI06524,AI Specialist,60294,USD,60294,MI,CT,South Korea,S,South Korea,100,"R, SQL, Tableau",Associate,4,Transportation,2024-03-26,2024-05-28,1820,7.8,Algorithmic Solutions -AI06525,NLP Engineer,100722,USD,100722,MI,CT,Norway,S,Thailand,100,"Python, Azure, Computer Vision, Docker",Master,3,Real Estate,2024-08-20,2024-10-17,1877,6.2,Digital Transformation LLC -AI06526,Machine Learning Engineer,100577,EUR,85490,MI,FL,Netherlands,S,Netherlands,50,"SQL, Scala, Computer Vision, Data Visualization, PyTorch",Bachelor,3,Automotive,2024-04-12,2024-06-05,717,7.7,Future Systems -AI06527,Autonomous Systems Engineer,117696,USD,117696,MI,FL,United States,M,United States,0,"Linux, MLOps, Java, SQL, PyTorch",Associate,3,Energy,2024-12-30,2025-02-11,1640,5.8,Machine Intelligence Group -AI06528,Head of AI,184939,USD,184939,EX,PT,Finland,L,Finland,50,"R, SQL, PyTorch, TensorFlow, Tableau",Master,19,Gaming,2024-03-07,2024-04-18,1259,7.7,Autonomous Tech -AI06529,AI Software Engineer,279576,USD,279576,EX,PT,Norway,S,Netherlands,50,"SQL, PyTorch, Java, Data Visualization, AWS",Bachelor,13,Automotive,2024-03-12,2024-05-03,2005,6,Smart Analytics -AI06530,Data Analyst,223224,USD,223224,SE,PT,Norway,L,Norway,0,"Spark, Mathematics, R, TensorFlow, GCP",Bachelor,6,Government,2024-07-04,2024-09-09,2433,8.4,Cloud AI Solutions -AI06531,Robotics Engineer,154533,USD,154533,EX,FL,South Korea,M,South Korea,100,"Hadoop, AWS, Computer Vision, Azure",Bachelor,18,Gaming,2024-11-26,2025-01-27,2073,5,AI Innovations -AI06532,AI Architect,175373,SGD,227985,EX,FL,Singapore,M,Singapore,0,"SQL, Deep Learning, Kubernetes",Master,11,Healthcare,2024-11-29,2024-12-17,1476,7,Quantum Computing Inc -AI06533,Data Analyst,71134,USD,71134,SE,CT,China,M,China,0,"Linux, Deep Learning, Data Visualization",Bachelor,7,Real Estate,2024-06-29,2024-08-17,727,7.5,Predictive Systems -AI06534,AI Product Manager,61514,EUR,52287,EN,FL,Netherlands,S,Netherlands,100,"TensorFlow, Kubernetes, Data Visualization, Spark, SQL",PhD,0,Telecommunications,2024-10-15,2024-11-22,1193,7.5,Predictive Systems -AI06535,AI Architect,95381,USD,95381,MI,PT,Sweden,S,Sweden,50,"SQL, Scala, Data Visualization",Associate,4,Finance,2025-02-24,2025-03-14,1983,9,Neural Networks Co -AI06536,Machine Learning Researcher,190339,USD,190339,EX,PT,Norway,S,Norway,50,"Tableau, R, AWS",Bachelor,15,Transportation,2024-05-24,2024-07-12,2438,9,Smart Analytics -AI06537,AI Research Scientist,228266,GBP,171200,EX,FL,United Kingdom,M,Austria,0,"Tableau, Scala, Java, Azure",Master,15,Education,2024-04-01,2024-05-03,2081,7.6,Smart Analytics -AI06538,AI Specialist,201526,USD,201526,SE,PT,United States,L,Thailand,50,"Kubernetes, Spark, SQL, Statistics, Mathematics",Associate,5,Healthcare,2024-10-19,2024-11-21,2490,7.2,AI Innovations -AI06539,Data Engineer,165854,USD,165854,EX,FL,Denmark,S,Denmark,0,"Linux, Azure, Mathematics",PhD,18,Real Estate,2024-10-13,2024-11-22,2073,8,Advanced Robotics -AI06540,Head of AI,50399,USD,50399,MI,FT,China,M,Chile,50,"Linux, GCP, Data Visualization",Master,4,Energy,2024-03-30,2024-05-21,2432,7.6,TechCorp Inc -AI06541,Research Scientist,146895,USD,146895,SE,FL,Ireland,M,Ireland,0,"Git, PyTorch, SQL, AWS, Mathematics",PhD,5,Transportation,2024-03-03,2024-04-25,1660,6.8,Cognitive Computing -AI06542,Machine Learning Engineer,141242,USD,141242,EX,FL,Ireland,M,Ireland,0,"Hadoop, Java, PyTorch, TensorFlow",Associate,19,Finance,2025-03-30,2025-04-17,1744,7.6,Smart Analytics -AI06543,AI Research Scientist,227276,GBP,170457,EX,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, Computer Vision, Statistics, Python, R",Master,19,Media,2025-01-02,2025-01-30,640,8.4,Algorithmic Solutions -AI06544,AI Software Engineer,91381,EUR,77674,MI,PT,Netherlands,S,Netherlands,50,"SQL, Computer Vision, Java, R",Master,3,Gaming,2025-03-31,2025-06-04,1247,7.4,AI Innovations -AI06545,Data Analyst,127378,USD,127378,SE,PT,Israel,M,Israel,100,"Statistics, Kubernetes, Data Visualization, Git, PyTorch",Associate,6,Retail,2024-09-28,2024-10-24,2487,8.6,Machine Intelligence Group -AI06546,Principal Data Scientist,67976,USD,67976,EN,FL,Israel,S,Hungary,0,"Python, TensorFlow, Kubernetes",PhD,1,Automotive,2024-07-09,2024-08-06,1680,6.5,Future Systems -AI06547,AI Specialist,213311,CHF,191980,SE,FT,Switzerland,M,Switzerland,100,"Linux, Azure, Kubernetes",Associate,9,Manufacturing,2025-04-15,2025-05-12,2384,8.4,DeepTech Ventures -AI06548,Machine Learning Engineer,68136,EUR,57916,EN,CT,France,S,Nigeria,100,"Kubernetes, Git, Azure, NLP, Deep Learning",Master,0,Gaming,2024-04-01,2024-06-08,976,6.7,Autonomous Tech -AI06549,Robotics Engineer,137648,USD,137648,MI,CT,Norway,L,Norway,100,"SQL, Python, GCP, NLP, Mathematics",Master,2,Finance,2025-03-22,2025-05-07,1030,6.4,Neural Networks Co -AI06550,AI Software Engineer,176624,USD,176624,EX,FT,Sweden,S,Sweden,0,"SQL, Azure, Tableau",Master,18,Transportation,2024-02-02,2024-03-19,1038,7.1,TechCorp Inc -AI06551,Robotics Engineer,117861,USD,117861,EX,FL,Finland,S,Finland,0,"Python, Scala, Java",Bachelor,19,Energy,2024-12-17,2025-01-21,823,7.2,DeepTech Ventures -AI06552,Computer Vision Engineer,95983,USD,95983,MI,FL,Israel,L,Israel,100,"PyTorch, Docker, Tableau, MLOps, Linux",Associate,3,Media,2025-04-07,2025-04-27,678,5.9,Neural Networks Co -AI06553,Head of AI,127320,EUR,108222,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Deep Learning, Computer Vision, Python, R",PhD,8,Healthcare,2024-06-22,2024-08-24,980,6.6,Neural Networks Co -AI06554,Data Analyst,156695,EUR,133191,EX,FT,Austria,M,Japan,100,"Azure, Python, Scala",Associate,17,Telecommunications,2024-09-05,2024-10-05,1229,6.2,DeepTech Ventures -AI06555,ML Ops Engineer,70934,USD,70934,EN,PT,United States,S,United States,50,"AWS, Git, TensorFlow, SQL, Mathematics",Bachelor,0,Media,2024-09-14,2024-10-07,2413,8.2,Future Systems -AI06556,Research Scientist,160766,USD,160766,EX,FL,Israel,L,Israel,50,"Python, TensorFlow, Spark, Linux",PhD,19,Transportation,2024-08-07,2024-09-27,2169,9.9,AI Innovations -AI06557,Autonomous Systems Engineer,112463,USD,112463,SE,PT,Finland,M,Finland,0,"GCP, PyTorch, MLOps",Bachelor,8,Finance,2024-03-30,2024-05-13,1069,7.4,Predictive Systems -AI06558,NLP Engineer,143144,USD,143144,SE,PT,Sweden,M,Sweden,100,"Spark, Git, Tableau",Master,6,Finance,2025-01-13,2025-02-18,892,9.5,DataVision Ltd -AI06559,Principal Data Scientist,38842,USD,38842,MI,FL,China,M,China,50,"MLOps, Python, TensorFlow, PyTorch",Associate,3,Technology,2024-07-21,2024-08-21,2083,9,Algorithmic Solutions -AI06560,Machine Learning Engineer,64116,GBP,48087,EN,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Computer Vision, Kubernetes, Docker",Master,0,Media,2024-07-09,2024-08-12,2386,5.8,Cognitive Computing -AI06561,AI Software Engineer,88010,USD,88010,MI,CT,South Korea,L,South Korea,0,"Python, TensorFlow, Hadoop",Associate,2,Consulting,2024-07-12,2024-07-27,2443,7,Smart Analytics -AI06562,Head of AI,95648,USD,95648,MI,FT,Norway,S,Norway,0,"Scala, Hadoop, Docker, Computer Vision, GCP",Master,4,Healthcare,2024-11-04,2025-01-14,2231,5.3,AI Innovations -AI06563,Deep Learning Engineer,97522,SGD,126779,EN,FT,Singapore,L,Singapore,50,"Git, Python, Statistics, TensorFlow, Mathematics",Master,1,Media,2024-10-06,2024-10-31,1772,6.6,DeepTech Ventures -AI06564,Data Analyst,31058,USD,31058,EN,CT,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-06-07,2024-07-18,605,9.6,Advanced Robotics -AI06565,Research Scientist,278889,CHF,251000,EX,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, Kubernetes, Statistics, Docker",Associate,10,Transportation,2025-01-28,2025-03-16,724,5.2,DeepTech Ventures -AI06566,Data Scientist,83674,SGD,108776,EN,CT,Singapore,L,Singapore,100,"Kubernetes, Scala, Data Visualization, MLOps, GCP",Bachelor,0,Government,2024-11-02,2024-11-20,1581,6.9,Cloud AI Solutions -AI06567,AI Specialist,59348,JPY,6528280,EN,CT,Japan,M,Japan,0,"Hadoop, Java, Linux",Bachelor,0,Telecommunications,2024-12-27,2025-02-05,2315,7.8,Digital Transformation LLC -AI06568,Robotics Engineer,178661,CHF,160795,EX,FL,Switzerland,S,Netherlands,100,"AWS, Linux, NLP",Associate,18,Telecommunications,2024-07-11,2024-09-19,1704,7.8,Predictive Systems -AI06569,AI Specialist,150401,AUD,203041,EX,PT,Australia,M,Italy,0,"Mathematics, PyTorch, MLOps, AWS, TensorFlow",Master,13,Transportation,2024-05-10,2024-07-11,1135,6.6,Advanced Robotics -AI06570,AI Research Scientist,62718,EUR,53310,EN,FL,Austria,L,Austria,50,"MLOps, Scala, TensorFlow, SQL",Associate,1,Consulting,2025-04-12,2025-06-10,896,7,Cognitive Computing -AI06571,Deep Learning Engineer,68205,EUR,57974,EN,PT,Austria,L,Singapore,0,"Docker, GCP, SQL, Git, Statistics",Master,1,Telecommunications,2024-05-26,2024-08-01,2360,7.1,DeepTech Ventures -AI06572,Data Analyst,58067,USD,58067,EN,CT,Israel,L,Israel,50,"MLOps, R, Docker, Python, AWS",PhD,1,Retail,2024-03-26,2024-04-28,833,5.3,Cloud AI Solutions -AI06573,AI Product Manager,94059,SGD,122277,MI,CT,Singapore,S,Singapore,50,"Python, GCP, Statistics, Computer Vision, Kubernetes",Associate,4,Telecommunications,2024-06-27,2024-08-25,1033,9.2,AI Innovations -AI06574,Machine Learning Researcher,124056,USD,124056,SE,FL,Denmark,S,Denmark,100,"Python, Kubernetes, TensorFlow, Scala, Git",Master,5,Technology,2024-09-22,2024-10-06,1381,9.8,Cognitive Computing -AI06575,Principal Data Scientist,103972,USD,103972,EN,FT,Denmark,L,Denmark,100,"Kubernetes, Data Visualization, Hadoop",Associate,1,Healthcare,2024-01-03,2024-03-01,2122,8.4,Predictive Systems -AI06576,AI Research Scientist,120733,SGD,156953,SE,FL,Singapore,M,Singapore,50,"Hadoop, Git, Statistics",Bachelor,8,Automotive,2025-04-20,2025-05-10,2362,6,Advanced Robotics -AI06577,Autonomous Systems Engineer,49939,JPY,5493290,EN,PT,Japan,S,Poland,50,"Java, SQL, Tableau",Master,0,Gaming,2024-08-13,2024-10-22,1862,6.5,Predictive Systems -AI06578,Machine Learning Engineer,131946,USD,131946,EX,PT,Finland,M,Nigeria,0,"AWS, Python, GCP, Scala, Computer Vision",Master,17,Technology,2024-01-30,2024-03-10,1122,8.4,Cloud AI Solutions -AI06579,Principal Data Scientist,74473,CHF,67026,EN,CT,Switzerland,S,Russia,0,"GCP, Computer Vision, SQL, Deep Learning",PhD,1,Gaming,2024-06-19,2024-08-18,1120,6,Digital Transformation LLC -AI06580,ML Ops Engineer,42235,USD,42235,EN,FT,South Korea,M,South Korea,0,"TensorFlow, Tableau, SQL, NLP",Associate,0,Government,2024-02-10,2024-02-29,623,7.1,DeepTech Ventures -AI06581,AI Software Engineer,100391,USD,100391,EX,PT,China,S,China,100,"Python, R, Data Visualization",Master,16,Retail,2024-12-02,2025-02-05,2094,5.7,Autonomous Tech -AI06582,Data Analyst,224884,USD,224884,EX,CT,Ireland,L,Chile,50,"Linux, Python, TensorFlow",Master,17,Manufacturing,2025-03-29,2025-04-12,2203,7.8,Advanced Robotics -AI06583,AI Specialist,138421,USD,138421,SE,PT,Finland,L,Switzerland,0,"Deep Learning, Hadoop, PyTorch",Bachelor,8,Manufacturing,2024-05-10,2024-05-29,1120,8.3,Future Systems -AI06584,Data Analyst,73596,EUR,62557,MI,PT,Germany,S,Germany,50,"Scala, Kubernetes, Tableau, MLOps, GCP",Bachelor,3,Energy,2024-02-07,2024-03-02,783,6.4,Autonomous Tech -AI06585,AI Product Manager,118358,USD,118358,MI,CT,Ireland,L,Ireland,50,"Scala, Python, TensorFlow, AWS",Associate,4,Finance,2025-04-27,2025-06-29,1805,9.6,Autonomous Tech -AI06586,Autonomous Systems Engineer,60553,USD,60553,SE,CT,China,L,France,50,"Python, Data Visualization, Scala",PhD,5,Energy,2024-10-05,2024-12-01,688,6.9,Predictive Systems -AI06587,Principal Data Scientist,151705,EUR,128949,SE,FL,Netherlands,L,Kenya,0,"Deep Learning, Tableau, MLOps",Bachelor,9,Telecommunications,2024-06-10,2024-08-21,1911,9.3,Digital Transformation LLC -AI06588,AI Specialist,119879,EUR,101897,MI,FT,Germany,L,Germany,50,"Python, Java, Azure, Scala, R",Master,4,Manufacturing,2024-06-15,2024-07-29,1659,7.1,Autonomous Tech -AI06589,Head of AI,79545,EUR,67613,MI,FL,France,L,France,100,"Spark, Python, Computer Vision, Data Visualization, Docker",PhD,3,Consulting,2025-03-25,2025-05-06,2147,9.2,Quantum Computing Inc -AI06590,Data Analyst,59043,USD,59043,EN,FT,Finland,L,Ukraine,50,"Scala, Kubernetes, SQL, Linux",PhD,1,Real Estate,2024-06-01,2024-06-24,2127,7,AI Innovations -AI06591,ML Ops Engineer,103365,GBP,77524,MI,PT,United Kingdom,M,United Kingdom,50,"MLOps, Hadoop, Statistics",Master,3,Manufacturing,2024-05-12,2024-07-12,2256,9,Smart Analytics -AI06592,AI Software Engineer,94572,EUR,80386,MI,CT,Netherlands,M,Netherlands,0,"Java, SQL, Git, Hadoop",Master,3,Telecommunications,2025-03-24,2025-04-07,2391,6.5,DataVision Ltd -AI06593,AI Software Engineer,95620,CHF,86058,MI,CT,Switzerland,S,South Africa,100,"R, Tableau, Python, TensorFlow",Master,3,Energy,2024-09-08,2024-10-11,814,6.6,Quantum Computing Inc -AI06594,AI Consultant,333608,USD,333608,EX,FL,United States,L,United States,50,"Kubernetes, Java, NLP, R",Associate,13,Retail,2024-02-23,2024-03-17,677,6.6,Predictive Systems -AI06595,Data Analyst,125818,USD,125818,SE,FT,Norway,S,Norway,50,"SQL, TensorFlow, AWS, Python, Linux",Master,6,Telecommunications,2025-04-04,2025-05-14,2303,7.8,Quantum Computing Inc -AI06596,Robotics Engineer,79536,USD,79536,MI,CT,United States,S,United States,50,"Scala, Kubernetes, Deep Learning, Mathematics, Data Visualization",PhD,4,Telecommunications,2025-03-14,2025-05-18,2441,7.3,Predictive Systems -AI06597,Machine Learning Researcher,112134,USD,112134,MI,CT,Denmark,M,Denmark,0,"Scala, SQL, Mathematics, Java, Python",Associate,3,Consulting,2024-12-30,2025-02-18,1804,7.7,Cloud AI Solutions -AI06598,Robotics Engineer,286727,USD,286727,EX,FL,Ireland,L,Ireland,100,"Java, NLP, Data Visualization",PhD,11,Technology,2024-12-01,2025-01-07,2222,5.2,TechCorp Inc -AI06599,AI Product Manager,86549,EUR,73567,EN,PT,Netherlands,L,Netherlands,100,"Linux, Git, Data Visualization, Python, Computer Vision",PhD,0,Retail,2024-03-27,2024-05-18,1317,8.5,Neural Networks Co -AI06600,Computer Vision Engineer,137974,USD,137974,MI,PT,Norway,M,Norway,0,"Python, R, GCP, AWS, Kubernetes",PhD,2,Manufacturing,2024-10-15,2024-10-29,1016,5.2,Digital Transformation LLC -AI06601,Principal Data Scientist,48191,USD,48191,EN,FT,Israel,S,Israel,50,"R, Scala, TensorFlow, Git",Bachelor,0,Government,2024-03-19,2024-05-06,1811,6.9,DeepTech Ventures -AI06602,Robotics Engineer,137089,EUR,116526,EX,CT,Germany,S,Germany,50,"Java, PyTorch, Hadoop",Master,10,Manufacturing,2025-02-05,2025-04-07,523,9.5,Predictive Systems -AI06603,ML Ops Engineer,146050,JPY,16065500,EX,CT,Japan,S,Japan,50,"SQL, Hadoop, Statistics, PyTorch",Master,16,Gaming,2025-02-10,2025-04-20,1060,8.9,Future Systems -AI06604,Machine Learning Researcher,83076,EUR,70615,EN,CT,Austria,L,Ukraine,0,"Hadoop, Python, GCP",Associate,0,Government,2024-05-17,2024-06-23,1739,9.8,Neural Networks Co -AI06605,Data Scientist,184817,SGD,240262,EX,CT,Singapore,S,Singapore,0,"Python, Scala, Hadoop",Associate,11,Energy,2024-08-24,2024-10-13,1726,7.4,DataVision Ltd -AI06606,Head of AI,76584,EUR,65096,MI,CT,Austria,M,Poland,50,"Kubernetes, Statistics, AWS",Associate,4,Manufacturing,2025-02-04,2025-04-02,1410,5.8,Autonomous Tech -AI06607,NLP Engineer,79065,USD,79065,EN,PT,Sweden,L,Sweden,100,"Python, Scala, Linux",Associate,0,Finance,2024-07-23,2024-09-30,2099,9.3,Future Systems -AI06608,Data Scientist,118313,EUR,100566,MI,PT,France,L,France,100,"Mathematics, SQL, Python",Bachelor,3,Healthcare,2024-11-06,2024-12-21,554,5,DataVision Ltd -AI06609,Data Scientist,177046,USD,177046,EX,FT,Israel,M,Israel,100,"Git, Tableau, Linux, Python",Bachelor,17,Energy,2024-10-10,2024-11-12,2366,5.8,Future Systems -AI06610,Machine Learning Researcher,38680,USD,38680,MI,FL,China,S,China,100,"MLOps, PyTorch, GCP",Associate,2,Real Estate,2024-10-12,2024-12-05,2445,5.7,Machine Intelligence Group -AI06611,AI Architect,161186,EUR,137008,SE,FL,Netherlands,M,Sweden,100,"Python, TensorFlow, NLP, Deep Learning, Statistics",Associate,7,Healthcare,2024-09-22,2024-11-01,1454,8.9,Predictive Systems -AI06612,Data Scientist,121651,EUR,103403,SE,FL,Netherlands,M,Netherlands,100,"Hadoop, GCP, Tableau, Docker, PyTorch",Bachelor,9,Transportation,2024-07-09,2024-07-29,1405,6.6,Autonomous Tech -AI06613,Autonomous Systems Engineer,134960,JPY,14845600,SE,PT,Japan,S,Japan,50,"Java, Tableau, Azure",PhD,6,Energy,2024-06-22,2024-07-27,657,6.7,Advanced Robotics -AI06614,AI Research Scientist,52748,USD,52748,EN,CT,Israel,M,Israel,0,"SQL, Kubernetes, Python, AWS",Master,1,Manufacturing,2025-03-02,2025-05-08,1280,9.5,Cognitive Computing -AI06615,AI Software Engineer,77009,CAD,96261,MI,PT,Canada,M,Canada,100,"Deep Learning, Kubernetes, Mathematics",Bachelor,2,Media,2024-03-01,2024-04-06,2072,9,Smart Analytics -AI06616,Data Analyst,101929,SGD,132508,SE,FT,Singapore,S,Luxembourg,50,"MLOps, Java, Data Visualization",Master,5,Manufacturing,2024-02-22,2024-03-22,1996,9.2,Smart Analytics -AI06617,AI Software Engineer,118002,EUR,100302,SE,PT,France,L,Czech Republic,0,"Kubernetes, GCP, Azure, Java, R",Master,6,Real Estate,2024-09-19,2024-11-13,1549,9.7,Advanced Robotics -AI06618,Machine Learning Engineer,138903,SGD,180574,EX,PT,Singapore,S,Singapore,100,"Tableau, Java, Deep Learning",Associate,11,Energy,2024-03-13,2024-04-22,2245,9.3,DataVision Ltd -AI06619,AI Architect,279851,JPY,30783610,EX,PT,Japan,L,Japan,50,"Spark, SQL, Linux",Associate,10,Automotive,2024-02-01,2024-03-05,2260,8.4,AI Innovations -AI06620,Principal Data Scientist,168724,EUR,143415,EX,PT,Austria,L,Austria,0,"TensorFlow, Tableau, R, Java, Linux",PhD,18,Real Estate,2024-09-15,2024-11-07,942,7,DeepTech Ventures -AI06621,AI Software Engineer,305904,SGD,397675,EX,PT,Singapore,L,Australia,100,"Scala, Data Visualization, R",Master,10,Gaming,2024-01-15,2024-03-27,1819,8.8,Neural Networks Co -AI06622,Robotics Engineer,27196,USD,27196,EN,FT,China,M,China,100,"Linux, NLP, Tableau, Spark",Associate,1,Telecommunications,2025-04-22,2025-05-08,503,8.7,AI Innovations -AI06623,Machine Learning Engineer,108913,USD,108913,SE,CT,South Korea,M,Portugal,100,"GCP, Scala, Statistics, Python",Bachelor,5,Real Estate,2024-03-24,2024-04-24,1058,6.2,Autonomous Tech -AI06624,Computer Vision Engineer,133154,CAD,166443,EX,PT,Canada,M,Estonia,50,"Hadoop, Scala, PyTorch",Associate,10,Media,2024-12-19,2025-01-20,968,5.7,Autonomous Tech -AI06625,AI Research Scientist,253346,SGD,329350,EX,PT,Singapore,L,Estonia,50,"Spark, PyTorch, Kubernetes, Hadoop",Master,17,Gaming,2025-02-10,2025-04-16,1851,10,Cognitive Computing -AI06626,Autonomous Systems Engineer,257998,JPY,28379780,EX,CT,Japan,M,Nigeria,100,"MLOps, Mathematics, AWS, NLP, Linux",PhD,18,Manufacturing,2024-12-22,2025-02-23,1851,6.8,Predictive Systems -AI06627,AI Research Scientist,118724,USD,118724,SE,FL,South Korea,M,South Korea,0,"Hadoop, Docker, Mathematics, Computer Vision, Scala",Bachelor,6,Finance,2025-03-10,2025-03-25,1941,8,Cognitive Computing -AI06628,Data Scientist,88590,GBP,66443,EN,PT,United Kingdom,L,United Kingdom,100,"Data Visualization, Docker, Linux",PhD,0,Transportation,2024-08-13,2024-10-16,881,8.5,AI Innovations -AI06629,Data Scientist,45950,EUR,39058,EN,FT,Germany,S,Germany,100,"Linux, Java, Python, TensorFlow",Master,0,Manufacturing,2024-08-28,2024-11-04,1012,9.8,Autonomous Tech -AI06630,AI Consultant,202145,SGD,262789,EX,CT,Singapore,M,Singapore,50,"Spark, Python, Tableau, Git, TensorFlow",Associate,18,Retail,2025-03-04,2025-04-04,1103,9.7,Machine Intelligence Group -AI06631,ML Ops Engineer,354485,CHF,319037,EX,FL,Switzerland,M,Finland,50,"MLOps, Docker, AWS, SQL",Associate,12,Finance,2024-04-11,2024-05-15,1424,5.4,Quantum Computing Inc -AI06632,AI Architect,145381,EUR,123574,SE,FT,Netherlands,M,Netherlands,100,"TensorFlow, Python, Computer Vision, PyTorch, Git",Bachelor,6,Technology,2024-07-30,2024-09-08,2076,6.1,DeepTech Ventures -AI06633,AI Research Scientist,80273,USD,80273,SE,CT,China,L,China,50,"Azure, NLP, Scala",Associate,7,Energy,2024-09-12,2024-10-21,1925,8.7,Algorithmic Solutions -AI06634,Computer Vision Engineer,93627,CAD,117034,MI,CT,Canada,L,Netherlands,50,"Linux, Docker, Data Visualization",PhD,2,Retail,2024-03-21,2024-05-31,2091,8.7,DeepTech Ventures -AI06635,Machine Learning Researcher,101958,EUR,86664,MI,PT,Germany,L,Germany,50,"SQL, Docker, Java, NLP",Associate,4,Real Estate,2024-02-22,2024-03-17,1416,7.1,Smart Analytics -AI06636,Machine Learning Engineer,310491,EUR,263917,EX,PT,Netherlands,L,Netherlands,50,"SQL, Hadoop, PyTorch",Associate,14,Education,2024-05-13,2024-06-25,2239,7.4,Cloud AI Solutions -AI06637,Machine Learning Researcher,92455,GBP,69341,EN,PT,United Kingdom,L,Colombia,50,"Scala, Linux, Statistics, Java, Docker",Associate,1,Manufacturing,2025-04-09,2025-04-26,1369,7.4,Future Systems -AI06638,Data Engineer,106939,USD,106939,EX,PT,China,M,China,50,"Hadoop, Computer Vision, PyTorch, Data Visualization, R",Master,11,Manufacturing,2024-09-14,2024-11-18,1333,9.9,Digital Transformation LLC -AI06639,AI Product Manager,194351,EUR,165198,EX,FT,Austria,M,Austria,100,"GCP, Azure, SQL, TensorFlow, Statistics",Bachelor,16,Automotive,2025-01-03,2025-03-07,1968,7.8,Future Systems -AI06640,Machine Learning Engineer,110209,USD,110209,EX,PT,China,L,China,100,"R, Scala, Python",Associate,15,Education,2025-03-25,2025-06-01,951,9.1,Future Systems -AI06641,Data Engineer,274986,USD,274986,EX,FT,Finland,L,Finland,50,"Scala, Deep Learning, MLOps",Associate,10,Media,2024-01-31,2024-02-23,1539,6.5,Digital Transformation LLC -AI06642,Deep Learning Engineer,292272,AUD,394567,EX,CT,Australia,L,Luxembourg,0,"Computer Vision, GCP, Azure",Associate,17,Technology,2025-02-23,2025-04-11,1628,7.1,Machine Intelligence Group -AI06643,AI Specialist,70159,USD,70159,EN,PT,Finland,M,Finland,0,"Kubernetes, Spark, Python",PhD,1,Education,2024-03-27,2024-05-05,1064,8.9,Advanced Robotics -AI06644,NLP Engineer,57113,USD,57113,EN,PT,Ireland,M,Hungary,0,"Java, Tableau, Scala",Associate,0,Finance,2024-12-15,2025-02-08,1510,8.6,Cognitive Computing -AI06645,Machine Learning Engineer,67207,USD,67207,EN,CT,Israel,L,Israel,0,"Azure, Data Visualization, Git, Java, R",Associate,1,Automotive,2024-03-02,2024-04-27,1753,5.3,Neural Networks Co -AI06646,AI Product Manager,62513,USD,62513,EN,FT,Israel,M,Israel,50,"Java, MLOps, Azure",PhD,0,Education,2025-04-28,2025-05-15,935,7.3,Predictive Systems -AI06647,AI Software Engineer,120652,USD,120652,MI,PT,Norway,L,Ireland,50,"Kubernetes, Azure, Deep Learning, PyTorch, R",Associate,3,Media,2024-09-07,2024-11-15,2101,8.4,Machine Intelligence Group -AI06648,AI Research Scientist,28595,USD,28595,EN,CT,India,L,India,50,"SQL, Data Visualization, Kubernetes, Spark",Master,1,Gaming,2024-02-20,2024-03-21,588,8.7,Algorithmic Solutions -AI06649,Autonomous Systems Engineer,32487,USD,32487,MI,FT,India,L,India,50,"Spark, Azure, Statistics, Docker",Associate,2,Gaming,2024-07-11,2024-08-26,2166,6.5,TechCorp Inc -AI06650,ML Ops Engineer,124352,SGD,161658,MI,FT,Singapore,L,South Africa,100,"Python, Git, Tableau, TensorFlow, Deep Learning",Associate,2,Education,2024-03-11,2024-04-11,1805,6.1,Autonomous Tech -AI06651,Research Scientist,106533,USD,106533,MI,FT,Ireland,M,Czech Republic,0,"Hadoop, SQL, AWS, MLOps",Associate,2,Telecommunications,2024-01-20,2024-03-12,870,8.6,Advanced Robotics -AI06652,Robotics Engineer,207708,EUR,176552,EX,PT,Austria,L,Austria,50,"Tableau, GCP, AWS, MLOps, Data Visualization",Bachelor,15,Healthcare,2024-04-09,2024-05-01,2248,6.6,Autonomous Tech -AI06653,Machine Learning Engineer,66074,EUR,56163,EN,FL,Netherlands,L,Netherlands,100,"Docker, Git, Statistics, Python",PhD,0,Retail,2024-01-16,2024-01-30,2044,7.4,Quantum Computing Inc -AI06654,Head of AI,73696,USD,73696,EN,FT,Ireland,M,Ireland,0,"Java, GCP, Azure",PhD,0,Retail,2025-01-20,2025-02-25,1925,6.8,Advanced Robotics -AI06655,AI Product Manager,88897,GBP,66673,EN,PT,United Kingdom,L,United Kingdom,100,"Linux, Statistics, GCP, PyTorch",Master,1,Gaming,2025-03-06,2025-03-25,1828,7.3,Machine Intelligence Group -AI06656,AI Specialist,155437,USD,155437,EX,FL,Finland,M,Turkey,50,"Python, Azure, Git, GCP",Associate,15,Manufacturing,2024-05-22,2024-06-16,1408,8.5,Smart Analytics -AI06657,AI Software Engineer,64451,USD,64451,MI,PT,Finland,S,Finland,100,"Azure, PyTorch, Mathematics, GCP, TensorFlow",Bachelor,3,Real Estate,2024-09-05,2024-10-05,843,7.6,Autonomous Tech -AI06658,AI Specialist,105020,USD,105020,SE,PT,South Korea,M,South Korea,100,"Tableau, NLP, Scala",Bachelor,7,Finance,2024-04-28,2024-07-01,2434,5.1,Advanced Robotics -AI06659,AI Architect,116832,USD,116832,SE,FL,Finland,S,Finland,100,"Statistics, GCP, Azure, Hadoop, Mathematics",Master,9,Healthcare,2024-11-21,2024-12-27,885,8.7,Machine Intelligence Group -AI06660,AI Research Scientist,59624,USD,59624,SE,PT,India,L,Chile,0,"PyTorch, Docker, AWS, Tableau",Associate,9,Real Estate,2024-12-26,2025-02-08,597,5.3,DataVision Ltd -AI06661,Machine Learning Researcher,200837,EUR,170711,EX,CT,Germany,S,Vietnam,0,"Kubernetes, Azure, Computer Vision",Master,19,Telecommunications,2024-04-17,2024-05-17,629,9.9,TechCorp Inc -AI06662,Data Analyst,353742,USD,353742,EX,CT,Denmark,L,Denmark,100,"Data Visualization, Azure, Tableau",Associate,16,Consulting,2024-04-07,2024-05-22,1671,7.4,AI Innovations -AI06663,Machine Learning Researcher,118225,GBP,88669,SE,PT,United Kingdom,M,Singapore,0,"Git, Spark, AWS",Master,9,Transportation,2025-03-26,2025-05-25,2351,8.5,AI Innovations -AI06664,ML Ops Engineer,47080,USD,47080,MI,FL,China,M,China,100,"Spark, SQL, R, Docker",Bachelor,4,Media,2024-02-20,2024-03-09,2184,6.6,TechCorp Inc -AI06665,AI Specialist,51135,USD,51135,SE,CT,India,L,Czech Republic,0,"Data Visualization, Scala, PyTorch, Git",Associate,7,Retail,2024-12-23,2025-01-12,1475,8.4,Predictive Systems -AI06666,AI Research Scientist,155505,USD,155505,SE,CT,Israel,L,Israel,50,"R, Hadoop, SQL",PhD,6,Real Estate,2025-03-16,2025-04-30,2108,6.8,Future Systems -AI06667,Robotics Engineer,69674,JPY,7664140,MI,CT,Japan,S,Japan,100,"MLOps, AWS, Java",Bachelor,2,Consulting,2024-09-15,2024-10-05,2064,7,AI Innovations -AI06668,Computer Vision Engineer,124927,JPY,13741970,SE,CT,Japan,L,Brazil,0,"Python, Linux, Computer Vision",PhD,5,Manufacturing,2024-04-02,2024-04-17,1126,7.8,DataVision Ltd -AI06669,AI Architect,112130,USD,112130,MI,PT,United States,L,United States,50,"Statistics, AWS, Azure, MLOps, Java",Bachelor,3,Gaming,2024-06-01,2024-08-01,2120,9,Cognitive Computing -AI06670,AI Software Engineer,104109,USD,104109,EX,CT,China,L,China,100,"Kubernetes, Spark, Data Visualization, Docker",PhD,13,Technology,2025-01-28,2025-03-18,759,6.5,Algorithmic Solutions -AI06671,AI Architect,47100,EUR,40035,EN,FT,Austria,S,New Zealand,0,"Kubernetes, Deep Learning, Computer Vision",Master,0,Media,2025-04-01,2025-04-25,2189,8.6,DataVision Ltd -AI06672,Research Scientist,176096,USD,176096,EX,CT,Sweden,L,Sweden,0,"Python, TensorFlow, PyTorch, NLP, Spark",Bachelor,10,Education,2024-08-13,2024-10-08,2428,9.4,DeepTech Ventures -AI06673,Robotics Engineer,52718,EUR,44810,EN,CT,France,S,France,0,"R, Kubernetes, Spark, SQL",Associate,1,Manufacturing,2025-02-23,2025-03-28,1176,6.6,Cloud AI Solutions -AI06674,Deep Learning Engineer,103610,USD,103610,EN,FT,Norway,L,Norway,100,"Kubernetes, Scala, NLP, PyTorch",Associate,1,Consulting,2025-02-19,2025-03-11,1742,9.3,Autonomous Tech -AI06675,Robotics Engineer,121009,USD,121009,MI,FT,Denmark,L,Denmark,0,"MLOps, Spark, Computer Vision, Linux, AWS",Master,2,Telecommunications,2025-02-04,2025-04-18,2066,8.3,Machine Intelligence Group -AI06676,Research Scientist,41556,USD,41556,MI,FT,India,L,India,50,"Python, PyTorch, Git, Java, Mathematics",Bachelor,4,Manufacturing,2025-01-28,2025-03-30,1688,8.6,Future Systems -AI06677,AI Consultant,185304,GBP,138978,EX,FT,United Kingdom,L,Czech Republic,0,"SQL, Hadoop, MLOps",PhD,16,Automotive,2024-10-23,2024-12-27,1002,6.6,Autonomous Tech -AI06678,Data Engineer,53652,USD,53652,EN,CT,Israel,S,Israel,0,"Azure, TensorFlow, SQL, Java",Bachelor,0,Finance,2024-01-10,2024-03-06,1224,5.8,Machine Intelligence Group -AI06679,ML Ops Engineer,92383,USD,92383,EN,FT,Denmark,L,Denmark,0,"AWS, PyTorch, GCP, Statistics",Master,1,Automotive,2024-06-10,2024-07-11,1190,5.7,Future Systems -AI06680,Robotics Engineer,63352,EUR,53849,EN,FT,Austria,S,Brazil,0,"Tableau, Data Visualization, Docker",Bachelor,1,Real Estate,2024-12-21,2025-02-08,1985,9.5,Quantum Computing Inc -AI06681,Data Analyst,177446,EUR,150829,EX,PT,Netherlands,L,China,50,"SQL, Tableau, Mathematics, MLOps, R",Associate,14,Education,2024-08-22,2024-10-24,1232,5.4,Predictive Systems -AI06682,NLP Engineer,141780,USD,141780,SE,PT,Finland,M,Finland,50,"Python, TensorFlow, Hadoop, Computer Vision",Associate,8,Automotive,2024-09-11,2024-11-06,1148,5.2,DeepTech Ventures -AI06683,Data Scientist,106379,USD,106379,EX,CT,South Korea,S,South Korea,0,"Hadoop, Docker, NLP, MLOps",Master,19,Technology,2024-01-12,2024-03-23,1018,6,Advanced Robotics -AI06684,AI Architect,126231,EUR,107296,MI,PT,Netherlands,L,Netherlands,0,"Git, Deep Learning, Docker",Bachelor,2,Consulting,2024-06-18,2024-07-25,2285,7.4,Cloud AI Solutions -AI06685,NLP Engineer,98327,CHF,88494,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Linux, Mathematics, Data Visualization, Hadoop",Associate,0,Consulting,2024-07-13,2024-08-13,641,5.1,Machine Intelligence Group -AI06686,Robotics Engineer,48433,EUR,41168,EN,PT,France,S,France,0,"PyTorch, Mathematics, Spark, Data Visualization, Kubernetes",PhD,0,Education,2025-03-11,2025-04-01,995,5.1,Algorithmic Solutions -AI06687,NLP Engineer,98587,USD,98587,MI,FT,Sweden,M,Latvia,0,"PyTorch, Kubernetes, Java, TensorFlow, Mathematics",Associate,2,Telecommunications,2024-04-29,2024-07-10,1796,6.9,Quantum Computing Inc -AI06688,AI Consultant,126335,SGD,164236,MI,FL,Singapore,L,Estonia,100,"Kubernetes, GCP, MLOps",Master,4,Gaming,2024-05-02,2024-06-15,1252,5.6,Machine Intelligence Group -AI06689,Principal Data Scientist,155034,USD,155034,SE,FT,Sweden,L,Belgium,100,"AWS, Git, SQL, Scala",Associate,6,Automotive,2025-02-09,2025-03-07,1045,5.5,Autonomous Tech -AI06690,Machine Learning Researcher,68806,USD,68806,EN,FT,Denmark,S,Denmark,50,"Linux, Git, MLOps, R, NLP",PhD,0,Education,2024-01-10,2024-02-24,1873,8.9,Advanced Robotics -AI06691,Robotics Engineer,161126,EUR,136957,EX,FT,Germany,L,Australia,0,"R, AWS, SQL, Git",PhD,16,Manufacturing,2025-02-12,2025-04-01,1563,9.9,Cognitive Computing -AI06692,Principal Data Scientist,61977,USD,61977,EN,PT,South Korea,M,Netherlands,0,"Scala, Tableau, R, MLOps, Java",Master,1,Gaming,2025-02-03,2025-04-12,535,8.1,Cloud AI Solutions -AI06693,Robotics Engineer,92188,AUD,124454,SE,FT,Australia,S,Australia,100,"NLP, Docker, Scala, Azure",PhD,9,Real Estate,2025-04-28,2025-05-24,2170,5.3,Machine Intelligence Group -AI06694,Data Analyst,34860,USD,34860,SE,FT,India,S,Italy,100,"NLP, PyTorch, Kubernetes",Associate,7,Government,2025-03-11,2025-05-02,2487,7.3,Machine Intelligence Group -AI06695,Data Scientist,65877,USD,65877,EN,FT,Finland,M,Finland,0,"Computer Vision, Statistics, Linux, Git, Data Visualization",Bachelor,0,Government,2024-03-28,2024-05-23,1899,7.2,Future Systems -AI06696,Data Analyst,126854,AUD,171253,SE,CT,Australia,S,Australia,100,"TensorFlow, PyTorch, Statistics",Master,9,Retail,2024-09-02,2024-10-15,1528,6.9,Algorithmic Solutions -AI06697,Machine Learning Researcher,242745,USD,242745,EX,FT,Israel,L,Israel,0,"GCP, Python, NLP, SQL",Master,18,Media,2024-03-20,2024-04-14,1897,5.4,Autonomous Tech -AI06698,Research Scientist,91867,USD,91867,EX,CT,China,L,Ireland,0,"Kubernetes, Git, Linux, Computer Vision, Azure",Master,17,Media,2024-03-21,2024-05-10,1486,8.7,Quantum Computing Inc -AI06699,Computer Vision Engineer,134543,USD,134543,EX,PT,Israel,S,Israel,50,"SQL, Hadoop, Tableau, Deep Learning",Master,14,Education,2024-05-14,2024-07-20,2330,8.2,Smart Analytics -AI06700,AI Product Manager,193446,USD,193446,EX,PT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Mathematics",Master,13,Government,2024-04-09,2024-06-06,1027,6.2,AI Innovations -AI06701,Machine Learning Engineer,60381,USD,60381,SE,CT,China,S,China,100,"SQL, Docker, Statistics, Tableau",Master,5,Technology,2024-06-10,2024-07-10,2340,9,DataVision Ltd -AI06702,Data Engineer,163915,AUD,221285,SE,CT,Australia,L,Australia,50,"Scala, Azure, Tableau, Python",PhD,8,Real Estate,2024-09-18,2024-11-20,1260,9.1,Advanced Robotics -AI06703,AI Research Scientist,68470,EUR,58200,MI,FT,France,S,France,100,"Kubernetes, Git, Mathematics, PyTorch",PhD,4,Media,2024-03-20,2024-05-22,2278,7,Neural Networks Co -AI06704,AI Product Manager,161796,USD,161796,EX,FL,Norway,S,Switzerland,0,"Docker, PyTorch, Git, Deep Learning",Bachelor,13,Energy,2024-10-01,2024-11-28,529,5.1,Quantum Computing Inc -AI06705,Data Engineer,179771,USD,179771,EX,FL,Sweden,S,South Korea,0,"SQL, Hadoop, PyTorch",Master,12,Healthcare,2024-04-03,2024-05-12,508,7.4,Autonomous Tech -AI06706,AI Software Engineer,93524,USD,93524,EN,FT,Norway,M,Norway,100,"Computer Vision, Docker, Git, Spark",Bachelor,0,Retail,2024-03-09,2024-04-23,1533,7.2,DeepTech Ventures -AI06707,AI Architect,165207,USD,165207,SE,FL,Denmark,S,Germany,100,"Java, Kubernetes, Tableau, Scala, Computer Vision",Master,5,Automotive,2025-03-10,2025-04-07,946,6.8,TechCorp Inc -AI06708,Data Analyst,63790,GBP,47843,EN,PT,United Kingdom,M,United Kingdom,50,"Java, SQL, GCP, Docker",Associate,1,Government,2025-02-06,2025-03-28,644,8.1,Autonomous Tech -AI06709,Autonomous Systems Engineer,166660,USD,166660,EX,CT,Finland,S,Finland,50,"MLOps, Deep Learning, Linux",PhD,11,Government,2025-01-14,2025-02-21,715,9.7,Digital Transformation LLC -AI06710,AI Product Manager,65921,USD,65921,MI,PT,Finland,S,Finland,0,"AWS, Python, Deep Learning, Computer Vision, TensorFlow",Master,4,Retail,2025-01-22,2025-03-19,905,6.7,DataVision Ltd -AI06711,AI Product Manager,126851,EUR,107823,SE,FL,Austria,L,Austria,100,"Mathematics, Computer Vision, PyTorch",PhD,7,Consulting,2024-10-12,2024-11-06,2223,9.8,Neural Networks Co -AI06712,Machine Learning Researcher,90333,USD,90333,SE,FT,Israel,S,Nigeria,100,"SQL, Spark, Deep Learning, Computer Vision",Master,9,Real Estate,2024-10-07,2024-11-05,2265,8.1,Digital Transformation LLC -AI06713,AI Consultant,70882,CAD,88603,EN,FL,Canada,M,Canada,0,"Computer Vision, Scala, SQL, Azure",PhD,1,Media,2024-12-04,2025-02-09,598,7.2,DataVision Ltd -AI06714,AI Specialist,196013,EUR,166611,EX,FL,Austria,M,Austria,100,"PyTorch, Python, Computer Vision",Associate,13,Government,2024-06-22,2024-08-09,1413,8.6,TechCorp Inc -AI06715,AI Software Engineer,81980,EUR,69683,EN,FL,Austria,L,Chile,50,"Kubernetes, Data Visualization, Scala, MLOps, Docker",PhD,1,Media,2024-11-27,2024-12-14,1918,8.3,Cognitive Computing -AI06716,Data Engineer,58677,EUR,49875,EN,PT,Germany,S,Germany,100,"Hadoop, SQL, TensorFlow, Python, Tableau",Associate,1,Telecommunications,2024-07-11,2024-09-09,2173,9.9,AI Innovations -AI06717,Head of AI,73309,EUR,62313,EN,CT,France,M,France,100,"Docker, Computer Vision, MLOps, Python",Associate,0,Telecommunications,2024-02-18,2024-04-13,1884,6.2,Algorithmic Solutions -AI06718,Deep Learning Engineer,201876,CHF,181688,SE,FT,Switzerland,M,Switzerland,0,"SQL, Hadoop, Python, Computer Vision, Statistics",PhD,7,Media,2025-02-08,2025-04-19,2072,9.8,Algorithmic Solutions -AI06719,Computer Vision Engineer,65018,USD,65018,EN,CT,Ireland,S,Ireland,100,"Python, Java, Spark, Linux, Hadoop",Associate,0,Consulting,2024-10-22,2024-11-15,2365,9,DeepTech Ventures -AI06720,Robotics Engineer,161696,GBP,121272,SE,FT,United Kingdom,L,United Kingdom,50,"Hadoop, SQL, Linux, Java, AWS",Master,6,Manufacturing,2024-05-14,2024-06-09,1123,5.1,Cognitive Computing -AI06721,Head of AI,59865,USD,59865,SE,CT,China,S,China,0,"SQL, Python, Docker, TensorFlow, Statistics",Bachelor,7,Healthcare,2024-11-20,2025-01-26,1696,7,Advanced Robotics -AI06722,Principal Data Scientist,73349,GBP,55012,MI,PT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow",Master,3,Retail,2024-10-20,2024-12-16,1212,9.7,Predictive Systems -AI06723,AI Consultant,62324,CAD,77905,EN,FL,Canada,S,Canada,100,"Mathematics, SQL, Azure, PyTorch, Scala",PhD,1,Energy,2024-01-27,2024-02-20,1034,7.5,Autonomous Tech -AI06724,AI Software Engineer,125505,USD,125505,MI,FL,Denmark,M,Denmark,50,"PyTorch, Scala, AWS",Bachelor,2,Government,2024-09-21,2024-11-10,1131,7.5,Quantum Computing Inc -AI06725,Data Scientist,124940,USD,124940,MI,CT,Ireland,L,Ireland,100,"Computer Vision, Kubernetes, NLP, Hadoop, Mathematics",Associate,4,Technology,2025-04-06,2025-05-29,1172,8.8,Autonomous Tech -AI06726,Machine Learning Engineer,62978,EUR,53531,EN,CT,Germany,S,Germany,100,"Statistics, Linux, Computer Vision, Deep Learning",PhD,1,Energy,2024-10-20,2024-12-18,889,8.9,Autonomous Tech -AI06727,Head of AI,146869,CAD,183586,EX,FL,Canada,S,Indonesia,50,"Tableau, Scala, Kubernetes, Data Visualization",Master,18,Healthcare,2024-05-12,2024-07-14,595,6.9,Quantum Computing Inc -AI06728,Robotics Engineer,216474,AUD,292240,EX,FT,Australia,M,India,100,"AWS, Kubernetes, Hadoop, Tableau",Bachelor,10,Media,2024-08-23,2024-09-11,1460,7.9,Cognitive Computing -AI06729,Machine Learning Researcher,91542,GBP,68657,MI,FL,United Kingdom,S,Ukraine,50,"TensorFlow, Statistics, Mathematics",PhD,3,Consulting,2024-08-17,2024-09-05,2001,6.9,Quantum Computing Inc -AI06730,Research Scientist,104890,CAD,131113,MI,FL,Canada,L,Canada,0,"Scala, Kubernetes, MLOps, Computer Vision, Git",Associate,4,Automotive,2024-04-29,2024-07-08,1658,5.3,DataVision Ltd -AI06731,AI Product Manager,74588,EUR,63400,MI,FL,France,S,France,100,"Scala, Linux, Git, TensorFlow, Deep Learning",Bachelor,4,Finance,2024-09-16,2024-11-04,1680,5.4,Future Systems -AI06732,Data Scientist,142343,EUR,120992,EX,PT,Germany,S,Germany,50,"Hadoop, Spark, MLOps",PhD,19,Media,2024-08-21,2024-09-18,1251,9.5,Digital Transformation LLC -AI06733,Deep Learning Engineer,161000,GBP,120750,EX,CT,United Kingdom,S,United Kingdom,50,"Git, Statistics, SQL, Deep Learning",Bachelor,13,Government,2024-09-08,2024-10-13,1604,8,DeepTech Ventures -AI06734,Autonomous Systems Engineer,214330,AUD,289346,EX,FT,Australia,S,Spain,50,"Python, TensorFlow, SQL",Bachelor,16,Education,2024-04-04,2024-05-09,2467,6.7,Cloud AI Solutions -AI06735,Deep Learning Engineer,103678,EUR,88126,SE,CT,France,M,Denmark,100,"Python, Git, TensorFlow, SQL, MLOps",Bachelor,9,Energy,2024-06-25,2024-09-02,514,5.5,Predictive Systems -AI06736,Principal Data Scientist,54303,USD,54303,EN,FL,South Korea,M,Israel,100,"PyTorch, Data Visualization, Tableau, Deep Learning, Scala",PhD,0,Retail,2024-01-24,2024-03-27,1109,6.8,Advanced Robotics -AI06737,NLP Engineer,56474,USD,56474,EN,CT,Sweden,M,Sweden,50,"PyTorch, Kubernetes, Hadoop, Mathematics, SQL",Associate,0,Technology,2024-05-23,2024-08-02,1477,6,Neural Networks Co -AI06738,NLP Engineer,300349,GBP,225262,EX,PT,United Kingdom,L,United Kingdom,0,"Java, Data Visualization, Hadoop, Python",Bachelor,18,Media,2024-05-22,2024-07-11,827,7.5,Cloud AI Solutions -AI06739,AI Consultant,44528,EUR,37849,EN,FT,France,S,France,100,"R, MLOps, Data Visualization, Kubernetes",Master,1,Finance,2024-04-01,2024-05-07,1942,5.5,DeepTech Ventures -AI06740,Machine Learning Researcher,118343,USD,118343,SE,FT,Israel,M,Israel,100,"Mathematics, MLOps, Data Visualization",PhD,6,Healthcare,2024-07-30,2024-09-03,1236,8.3,Advanced Robotics -AI06741,AI Architect,125950,USD,125950,MI,FT,Denmark,L,Poland,50,"SQL, AWS, NLP",Bachelor,4,Technology,2025-01-30,2025-03-01,1563,6,Neural Networks Co -AI06742,AI Research Scientist,61502,USD,61502,EN,CT,Israel,M,Austria,50,"R, Python, Java, GCP",Master,1,Media,2025-01-01,2025-01-28,2019,9.1,Quantum Computing Inc -AI06743,Head of AI,44859,EUR,38130,EN,CT,France,S,France,0,"Azure, Tableau, GCP",PhD,1,Healthcare,2024-11-21,2024-12-31,1364,5.3,Advanced Robotics -AI06744,Autonomous Systems Engineer,119175,JPY,13109250,MI,CT,Japan,L,Japan,100,"Kubernetes, Python, MLOps",Bachelor,4,Automotive,2025-04-21,2025-06-27,1528,6.9,Algorithmic Solutions -AI06745,Research Scientist,90723,USD,90723,MI,PT,United States,M,United States,0,"Hadoop, Mathematics, Tableau",Master,3,Government,2024-07-23,2024-10-01,1136,5.5,Quantum Computing Inc -AI06746,Robotics Engineer,239693,EUR,203739,EX,CT,France,L,China,100,"AWS, Scala, Statistics, Spark",PhD,11,Healthcare,2025-02-06,2025-03-01,2160,5.9,DeepTech Ventures -AI06747,Autonomous Systems Engineer,89947,CHF,80952,EN,FT,Switzerland,L,Australia,0,"AWS, Python, MLOps",Bachelor,0,Energy,2024-03-01,2024-05-02,1832,5.7,DataVision Ltd -AI06748,AI Architect,78388,USD,78388,MI,CT,Finland,S,Finland,50,"MLOps, Tableau, Python",Associate,3,Consulting,2024-08-23,2024-10-11,1416,9,TechCorp Inc -AI06749,Deep Learning Engineer,205050,USD,205050,SE,FL,United States,L,United States,100,"Kubernetes, Deep Learning, PyTorch, TensorFlow, SQL",Bachelor,7,Retail,2024-02-28,2024-04-22,2190,5.3,Autonomous Tech -AI06750,Data Scientist,91998,EUR,78198,MI,FL,Netherlands,M,Netherlands,0,"Data Visualization, Python, GCP",PhD,4,Education,2024-03-25,2024-05-20,1349,5.6,Cloud AI Solutions -AI06751,Data Engineer,226755,USD,226755,EX,PT,Finland,L,Finland,0,"Git, PyTorch, SQL, TensorFlow",Master,13,Gaming,2024-12-27,2025-02-28,564,6.4,Algorithmic Solutions -AI06752,NLP Engineer,123422,USD,123422,MI,FT,Denmark,S,Denmark,100,"Python, AWS, TensorFlow, Data Visualization, GCP",Associate,4,Telecommunications,2024-11-16,2024-12-12,2296,6.2,Cloud AI Solutions -AI06753,Data Engineer,206557,USD,206557,SE,FT,Norway,L,Norway,0,"PyTorch, Kubernetes, AWS, Azure, Computer Vision",PhD,9,Automotive,2025-02-18,2025-03-25,2426,6.9,TechCorp Inc -AI06754,Computer Vision Engineer,97955,USD,97955,EN,PT,Denmark,L,Kenya,100,"SQL, Linux, Azure, Spark, Deep Learning",Associate,1,Consulting,2024-07-05,2024-09-01,2218,9.7,Neural Networks Co -AI06755,Robotics Engineer,113968,AUD,153857,SE,CT,Australia,M,Australia,0,"Docker, Java, Python, Azure",Bachelor,9,Telecommunications,2024-06-12,2024-07-17,1975,5.5,Predictive Systems -AI06756,Autonomous Systems Engineer,73215,CAD,91519,EN,PT,Canada,M,Canada,0,"Scala, Python, Tableau",Master,0,Education,2024-06-28,2024-09-06,1660,7.5,Machine Intelligence Group -AI06757,Data Analyst,79628,CAD,99535,EN,FT,Canada,L,Japan,50,"Python, Docker, Computer Vision, Mathematics, Statistics",Bachelor,0,Technology,2024-06-02,2024-06-26,913,9.9,DataVision Ltd -AI06758,Data Engineer,177463,USD,177463,SE,CT,Norway,L,Norway,50,"Kubernetes, Mathematics, NLP, TensorFlow, Computer Vision",PhD,7,Technology,2025-02-24,2025-04-13,849,5.5,Future Systems -AI06759,AI Architect,126055,SGD,163872,SE,PT,Singapore,L,Luxembourg,50,"PyTorch, Scala, Tableau",PhD,5,Education,2024-11-03,2024-12-26,1623,6.6,AI Innovations -AI06760,AI Consultant,41096,USD,41096,SE,PT,India,M,Japan,0,"Scala, Java, Docker, Deep Learning",Associate,7,Real Estate,2024-05-14,2024-07-13,629,8.5,Machine Intelligence Group -AI06761,Principal Data Scientist,141579,AUD,191132,EX,FL,Australia,S,Australia,100,"R, Kubernetes, NLP, SQL",Master,10,Energy,2024-07-28,2024-10-09,608,7.9,Advanced Robotics -AI06762,Principal Data Scientist,117805,CAD,147256,EX,PT,Canada,S,Israel,50,"Python, Scala, MLOps, Linux",Associate,17,Media,2024-04-12,2024-06-08,1141,8.5,Advanced Robotics -AI06763,ML Ops Engineer,76368,USD,76368,SE,FT,China,L,Portugal,50,"Computer Vision, Java, Kubernetes, MLOps, Deep Learning",Bachelor,6,Healthcare,2024-07-06,2024-09-11,2307,9.9,TechCorp Inc -AI06764,NLP Engineer,66318,USD,66318,EN,FL,South Korea,M,Finland,0,"Hadoop, SQL, Computer Vision",Associate,1,Technology,2024-09-28,2024-12-07,548,5.5,Neural Networks Co -AI06765,AI Research Scientist,170692,USD,170692,EX,CT,Ireland,S,Ireland,0,"GCP, AWS, Deep Learning, PyTorch",PhD,15,Transportation,2024-05-15,2024-07-16,706,6.8,Machine Intelligence Group -AI06766,Computer Vision Engineer,289060,SGD,375778,EX,FL,Singapore,L,Singapore,0,"SQL, Git, Computer Vision, Statistics",Master,15,Real Estate,2024-04-28,2024-06-17,2412,8.6,DataVision Ltd -AI06767,Data Analyst,120746,USD,120746,SE,CT,Sweden,S,Sweden,0,"PyTorch, Python, Deep Learning, GCP, NLP",Associate,9,Technology,2024-12-21,2025-01-06,2167,5.5,Machine Intelligence Group -AI06768,Principal Data Scientist,97475,JPY,10722250,MI,FT,Japan,S,Japan,0,"Java, Kubernetes, SQL, Python",Bachelor,4,Finance,2025-01-02,2025-03-11,627,6.8,DataVision Ltd -AI06769,Computer Vision Engineer,228776,USD,228776,EX,FL,Israel,M,Israel,100,"TensorFlow, Python, Scala, Java",Bachelor,18,Manufacturing,2024-04-15,2024-06-22,1406,5.1,Digital Transformation LLC -AI06770,AI Specialist,224210,CAD,280263,EX,FL,Canada,M,Canada,100,"Statistics, Spark, Python, PyTorch",PhD,10,Manufacturing,2024-07-13,2024-09-02,1369,8.2,Quantum Computing Inc -AI06771,Head of AI,71016,USD,71016,EN,CT,Finland,L,Finland,50,"Git, Linux, Tableau",Master,0,Energy,2024-08-26,2024-10-26,2128,5.4,DataVision Ltd -AI06772,AI Product Manager,157055,USD,157055,MI,FT,Norway,L,Latvia,50,"PyTorch, Kubernetes, Statistics",Master,4,Energy,2024-02-13,2024-03-07,679,6.4,Digital Transformation LLC -AI06773,AI Specialist,78910,USD,78910,MI,FL,Israel,S,Latvia,0,"Azure, Deep Learning, Computer Vision",Associate,4,Telecommunications,2025-02-26,2025-04-19,913,5.8,DataVision Ltd -AI06774,AI Product Manager,133220,USD,133220,EX,FT,Finland,S,Estonia,50,"Hadoop, Docker, NLP, Git, PyTorch",PhD,10,Government,2024-02-16,2024-03-28,960,5.1,Quantum Computing Inc -AI06775,Machine Learning Engineer,102537,EUR,87156,MI,FL,France,M,France,100,"Spark, Java, Mathematics",Bachelor,3,Gaming,2025-02-27,2025-04-25,2295,7.7,Cognitive Computing -AI06776,Autonomous Systems Engineer,95026,USD,95026,EN,FT,United States,L,Latvia,50,"Git, Python, Azure",Master,0,Real Estate,2024-06-02,2024-07-14,968,8.4,Neural Networks Co -AI06777,AI Research Scientist,163095,USD,163095,EX,FT,Finland,L,Finland,50,"Git, AWS, MLOps, Statistics",Bachelor,17,Retail,2024-02-15,2024-03-01,1932,8,Algorithmic Solutions -AI06778,Data Scientist,86115,JPY,9472650,MI,FT,Japan,S,Japan,50,"R, Spark, Linux, Data Visualization",Associate,2,Education,2024-10-15,2024-11-03,2194,6.4,Cloud AI Solutions -AI06779,Robotics Engineer,81518,EUR,69290,MI,PT,France,S,France,50,"Computer Vision, Docker, Azure",PhD,2,Finance,2024-03-26,2024-04-23,724,5.6,Autonomous Tech -AI06780,Head of AI,112582,EUR,95695,SE,PT,Austria,S,Austria,100,"Spark, AWS, Docker",PhD,5,Media,2025-01-11,2025-03-09,569,5.7,Digital Transformation LLC -AI06781,Data Engineer,179222,USD,179222,SE,PT,Norway,L,Argentina,100,"Spark, Statistics, PyTorch, SQL, TensorFlow",PhD,8,Retail,2024-03-07,2024-05-02,619,7.4,Algorithmic Solutions -AI06782,AI Research Scientist,267085,CHF,240377,EX,FL,Switzerland,L,Argentina,0,"AWS, PyTorch, Statistics",PhD,14,Transportation,2024-11-18,2025-01-06,591,6.7,DeepTech Ventures -AI06783,AI Specialist,72647,USD,72647,EN,FL,South Korea,L,Estonia,50,"Azure, Spark, Scala, Linux",Bachelor,0,Manufacturing,2024-07-03,2024-07-21,2440,8,Algorithmic Solutions -AI06784,Principal Data Scientist,157364,SGD,204573,EX,CT,Singapore,M,Singapore,0,"Azure, MLOps, Data Visualization, Hadoop",Bachelor,18,Finance,2024-01-23,2024-03-16,2250,9.9,Future Systems -AI06785,Research Scientist,147887,GBP,110915,SE,PT,United Kingdom,L,Chile,100,"Linux, Spark, NLP, Python",Bachelor,7,Education,2024-09-22,2024-11-26,1467,9.6,Advanced Robotics -AI06786,AI Specialist,93908,JPY,10329880,MI,PT,Japan,L,Japan,0,"Hadoop, Deep Learning, Java, Kubernetes",Bachelor,4,Technology,2025-03-28,2025-05-27,1495,6.4,DataVision Ltd -AI06787,Data Scientist,221005,USD,221005,SE,FL,Norway,L,New Zealand,0,"SQL, NLP, Statistics, Deep Learning, R",Associate,9,Energy,2024-07-11,2024-08-06,1072,6.3,Neural Networks Co -AI06788,AI Consultant,188472,USD,188472,SE,FL,Denmark,M,Denmark,0,"Git, AWS, Mathematics, NLP",PhD,8,Finance,2024-04-16,2024-06-13,769,8,DataVision Ltd -AI06789,AI Research Scientist,134644,USD,134644,SE,FL,South Korea,L,South Korea,100,"Scala, TensorFlow, Kubernetes, Statistics, R",PhD,9,Real Estate,2024-10-22,2024-12-15,1688,7.9,DataVision Ltd -AI06790,ML Ops Engineer,158617,AUD,214133,EX,CT,Australia,L,Australia,50,"Python, AWS, TensorFlow",Bachelor,11,Healthcare,2024-06-16,2024-08-11,2165,8.6,Quantum Computing Inc -AI06791,ML Ops Engineer,80635,USD,80635,MI,FT,Israel,L,Canada,50,"Spark, Azure, Data Visualization, Computer Vision",PhD,3,Consulting,2024-12-26,2025-01-23,2490,9.8,Predictive Systems -AI06792,Machine Learning Researcher,186187,SGD,242043,EX,PT,Singapore,M,Singapore,50,"Computer Vision, Git, Python, Deep Learning",Associate,18,Technology,2025-02-26,2025-04-05,1822,5.2,Machine Intelligence Group -AI06793,Computer Vision Engineer,101105,EUR,85939,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP",Bachelor,4,Real Estate,2024-01-19,2024-03-25,888,9.7,Machine Intelligence Group -AI06794,Data Scientist,178163,USD,178163,EX,FT,Ireland,L,Ireland,0,"GCP, TensorFlow, Linux",PhD,15,Manufacturing,2024-06-04,2024-08-07,979,8.8,Cloud AI Solutions -AI06795,ML Ops Engineer,63735,EUR,54175,EN,PT,France,L,France,0,"SQL, PyTorch, Data Visualization",Master,0,Healthcare,2024-05-04,2024-06-12,2161,9.4,Autonomous Tech -AI06796,AI Consultant,148327,CHF,133494,MI,FL,Switzerland,M,Canada,0,"Azure, Scala, Linux",Master,3,Energy,2024-03-23,2024-04-07,1743,8.7,Algorithmic Solutions -AI06797,Computer Vision Engineer,70092,USD,70092,MI,PT,Finland,S,Chile,100,"Java, SQL, Tableau",Bachelor,2,Technology,2025-01-23,2025-03-03,899,5.8,Cognitive Computing -AI06798,AI Research Scientist,168805,USD,168805,SE,PT,Sweden,L,Sweden,50,"AWS, SQL, Data Visualization, Computer Vision",Bachelor,5,Energy,2024-05-07,2024-06-08,1562,10,Algorithmic Solutions -AI06799,AI Product Manager,167702,CAD,209628,EX,PT,Canada,S,Germany,50,"Python, MLOps, TensorFlow, NLP",Associate,16,Gaming,2024-06-26,2024-08-11,1409,9.6,TechCorp Inc -AI06800,Robotics Engineer,77196,EUR,65617,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Spark, Computer Vision, SQL, GCP",Master,3,Energy,2025-01-17,2025-02-05,566,9.7,Quantum Computing Inc -AI06801,AI Product Manager,60668,EUR,51568,EN,FL,Austria,M,Austria,0,"Python, Java, NLP, Azure",Bachelor,0,Telecommunications,2024-07-03,2024-07-22,934,8.5,Autonomous Tech -AI06802,Machine Learning Researcher,238168,AUD,321527,EX,FL,Australia,L,Australia,0,"SQL, Git, Deep Learning",Master,14,Energy,2024-04-05,2024-05-07,1426,7.2,Cognitive Computing -AI06803,Principal Data Scientist,80987,SGD,105283,MI,PT,Singapore,S,Singapore,0,"SQL, Git, NLP, Deep Learning",Bachelor,4,Manufacturing,2024-12-08,2025-02-11,1153,8.3,Autonomous Tech -AI06804,Autonomous Systems Engineer,58908,USD,58908,EN,FL,United States,S,Hungary,100,"PyTorch, TensorFlow, R",Bachelor,1,Gaming,2024-02-06,2024-04-08,1768,5.7,Algorithmic Solutions -AI06805,Machine Learning Engineer,56978,GBP,42734,EN,PT,United Kingdom,S,United Kingdom,0,"NLP, Spark, Python, Hadoop",PhD,1,Manufacturing,2025-01-16,2025-02-20,1809,6.3,Algorithmic Solutions -AI06806,Autonomous Systems Engineer,149583,USD,149583,EX,PT,Israel,M,Israel,50,"TensorFlow, Azure, PyTorch",Master,12,Manufacturing,2024-08-16,2024-10-27,1499,9.5,Digital Transformation LLC -AI06807,Robotics Engineer,275970,USD,275970,EX,CT,Ireland,L,Ireland,50,"Tableau, Scala, R",Bachelor,16,Real Estate,2025-02-18,2025-04-26,2306,5.3,Autonomous Tech -AI06808,Head of AI,154006,EUR,130905,EX,CT,Germany,M,Germany,100,"TensorFlow, Hadoop, AWS, SQL",PhD,12,Energy,2024-07-26,2024-08-17,1303,7.7,Advanced Robotics -AI06809,Principal Data Scientist,131751,JPY,14492610,MI,FT,Japan,L,Japan,0,"Kubernetes, Python, R",Master,4,Automotive,2024-11-12,2024-12-29,2127,6.3,Future Systems -AI06810,Robotics Engineer,163158,JPY,17947380,SE,FL,Japan,L,Mexico,50,"Mathematics, Tableau, Kubernetes",Master,7,Transportation,2024-01-27,2024-03-08,885,6.8,Digital Transformation LLC -AI06811,Principal Data Scientist,52986,USD,52986,EN,PT,Sweden,M,Thailand,0,"SQL, Hadoop, MLOps",Associate,1,Real Estate,2024-09-08,2024-10-02,1605,5.5,Digital Transformation LLC -AI06812,NLP Engineer,326359,CHF,293723,EX,PT,Switzerland,L,Switzerland,0,"Linux, Python, Data Visualization, Computer Vision, Scala",Bachelor,11,Government,2024-05-27,2024-07-26,904,6.1,Cognitive Computing -AI06813,NLP Engineer,78523,USD,78523,EN,FT,Israel,L,United States,100,"Deep Learning, PyTorch, SQL",Associate,1,Technology,2024-10-13,2024-11-24,1039,5.8,AI Innovations -AI06814,NLP Engineer,104203,SGD,135464,MI,FL,Singapore,M,Singapore,100,"Statistics, Python, NLP, Spark, Data Visualization",Bachelor,4,Government,2024-03-19,2024-05-01,937,8,AI Innovations -AI06815,Data Engineer,39561,USD,39561,SE,PT,India,S,India,100,"TensorFlow, Git, Data Visualization",PhD,9,Automotive,2024-08-04,2024-09-18,1448,7.4,Predictive Systems -AI06816,AI Research Scientist,80731,EUR,68621,EN,PT,Austria,L,Austria,100,"Kubernetes, GCP, Java",Bachelor,0,Education,2024-02-07,2024-04-19,2243,9.4,Advanced Robotics -AI06817,Research Scientist,138085,EUR,117372,EX,FT,Austria,M,Austria,100,"SQL, NLP, Kubernetes, R",Associate,14,Transportation,2024-08-10,2024-09-30,875,5.5,Advanced Robotics -AI06818,ML Ops Engineer,77251,GBP,57938,EN,PT,United Kingdom,M,United Kingdom,50,"Data Visualization, Tableau, Python, TensorFlow, Linux",Master,0,Finance,2024-05-02,2024-06-08,1189,7.5,Future Systems -AI06819,Data Engineer,82330,JPY,9056300,EN,CT,Japan,L,Brazil,0,"Azure, PyTorch, Tableau, Data Visualization, Scala",PhD,0,Media,2024-11-10,2025-01-06,988,7.9,Neural Networks Co -AI06820,Data Engineer,78143,EUR,66422,EN,FT,Netherlands,L,India,0,"PyTorch, Hadoop, Tableau, MLOps",PhD,0,Consulting,2024-01-05,2024-03-12,1227,7.5,Algorithmic Solutions -AI06821,Computer Vision Engineer,143711,USD,143711,SE,PT,Israel,M,Israel,100,"Computer Vision, GCP, Statistics, Python, Mathematics",Bachelor,8,Finance,2025-03-22,2025-05-08,1997,7.8,Neural Networks Co -AI06822,Autonomous Systems Engineer,33586,USD,33586,EN,FL,China,S,China,0,"PyTorch, Computer Vision, Linux, Deep Learning, NLP",Bachelor,0,Retail,2024-05-27,2024-07-23,942,7.2,Algorithmic Solutions -AI06823,Research Scientist,22293,USD,22293,EN,FL,India,L,India,50,"SQL, MLOps, PyTorch",PhD,1,Gaming,2024-07-14,2024-09-22,753,8.4,DeepTech Ventures -AI06824,ML Ops Engineer,98076,JPY,10788360,MI,CT,Japan,L,Japan,0,"Docker, Kubernetes, Data Visualization, TensorFlow, Azure",Master,4,Media,2025-04-22,2025-06-27,1933,7.9,Cloud AI Solutions -AI06825,Machine Learning Engineer,98006,EUR,83305,SE,FL,Netherlands,S,Netherlands,100,"SQL, Spark, PyTorch, R, TensorFlow",Bachelor,5,Consulting,2024-03-24,2024-04-14,1977,8.6,Autonomous Tech -AI06826,Data Scientist,66357,USD,66357,EN,FL,South Korea,M,New Zealand,100,"Java, SQL, Tableau",Associate,1,Gaming,2024-08-31,2024-09-16,2478,8.7,DeepTech Ventures -AI06827,AI Architect,193061,CHF,173755,SE,PT,Switzerland,L,Romania,50,"Computer Vision, Statistics, MLOps, NLP, Kubernetes",Master,5,Finance,2024-08-18,2024-10-16,1911,5.8,Autonomous Tech -AI06828,AI Software Engineer,220816,USD,220816,EX,CT,Sweden,M,Sweden,100,"AWS, Hadoop, Deep Learning",PhD,16,Transportation,2024-10-03,2024-11-03,610,5.9,Predictive Systems -AI06829,AI Software Engineer,130692,USD,130692,SE,FL,Sweden,L,Sweden,0,"Python, Linux, Tableau, Java, NLP",Master,9,Finance,2024-12-28,2025-03-08,1297,9.7,Algorithmic Solutions -AI06830,Machine Learning Researcher,207792,CHF,187013,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, SQL, Java",Associate,9,Gaming,2024-06-17,2024-08-10,1818,6.8,Advanced Robotics -AI06831,Data Scientist,65685,USD,65685,EN,PT,United States,S,United States,100,"Azure, SQL, NLP, Python",Master,1,Consulting,2024-01-01,2024-03-10,1366,9.2,Neural Networks Co -AI06832,AI Architect,125757,EUR,106893,SE,CT,Germany,L,Germany,0,"PyTorch, Computer Vision, GCP, Linux",Associate,6,Real Estate,2025-03-02,2025-04-24,1445,6.4,Quantum Computing Inc -AI06833,Head of AI,85426,EUR,72612,EN,CT,Netherlands,L,Netherlands,50,"Java, Python, Tableau",PhD,0,Real Estate,2024-03-22,2024-04-16,551,8.8,Autonomous Tech -AI06834,AI Specialist,25694,USD,25694,EN,FT,India,L,India,100,"AWS, Hadoop, NLP, Java",Bachelor,1,Technology,2025-02-10,2025-03-30,2280,8.3,Algorithmic Solutions -AI06835,Deep Learning Engineer,175415,CHF,157874,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, SQL, Azure",PhD,8,Telecommunications,2025-02-18,2025-03-09,1460,8.6,Neural Networks Co -AI06836,AI Product Manager,123361,USD,123361,SE,PT,Sweden,S,Estonia,50,"Spark, Python, Computer Vision, Kubernetes",Master,5,Consulting,2024-10-15,2024-10-30,1859,6.3,Quantum Computing Inc -AI06837,Robotics Engineer,158738,JPY,17461180,EX,FT,Japan,S,Japan,50,"Docker, Deep Learning, Scala, Spark",PhD,14,Media,2024-04-04,2024-05-13,1906,6,Digital Transformation LLC -AI06838,AI Research Scientist,83310,EUR,70814,EN,PT,Netherlands,L,Netherlands,50,"Linux, Statistics, TensorFlow",Master,0,Gaming,2025-02-04,2025-03-26,1650,10,DeepTech Ventures -AI06839,AI Architect,90940,EUR,77299,MI,FT,Germany,L,Germany,0,"Hadoop, Python, Deep Learning",PhD,3,Finance,2024-06-06,2024-07-03,2371,7,Neural Networks Co -AI06840,Principal Data Scientist,78709,USD,78709,EN,FL,Finland,L,Finland,50,"Tableau, Python, Scala",Master,1,Automotive,2024-10-08,2024-10-28,505,8,Predictive Systems -AI06841,Principal Data Scientist,23429,USD,23429,MI,CT,India,S,India,50,"Python, Azure, Deep Learning, Java, Scala",Bachelor,3,Media,2025-01-26,2025-03-18,2362,9,Autonomous Tech -AI06842,Data Scientist,56096,USD,56096,SE,PT,China,L,France,50,"Deep Learning, Python, Data Visualization, Statistics, Linux",Bachelor,5,Media,2024-05-20,2024-06-07,1141,6.5,Algorithmic Solutions -AI06843,Machine Learning Researcher,79608,USD,79608,MI,FL,South Korea,S,South Korea,100,"GCP, Linux, NLP, Data Visualization, Mathematics",Associate,2,Finance,2024-04-11,2024-05-28,1325,8,Neural Networks Co -AI06844,ML Ops Engineer,62288,USD,62288,EN,FL,Finland,M,Finland,100,"Spark, Scala, GCP",Bachelor,1,Government,2025-01-05,2025-01-29,1712,7.1,Quantum Computing Inc -AI06845,NLP Engineer,231007,AUD,311859,EX,FL,Australia,L,Australia,0,"TensorFlow, Linux, PyTorch, Spark, SQL",Bachelor,15,Automotive,2024-03-26,2024-05-04,1826,8.5,Digital Transformation LLC -AI06846,Principal Data Scientist,100308,USD,100308,EN,FT,United States,L,Australia,100,"Computer Vision, Scala, MLOps, NLP",Master,0,Energy,2024-03-18,2024-04-05,2263,9.2,TechCorp Inc -AI06847,AI Consultant,106652,EUR,90654,MI,PT,Austria,L,Austria,100,"Python, Hadoop, Linux, TensorFlow",PhD,4,Transportation,2025-01-24,2025-03-04,897,9.5,Cognitive Computing -AI06848,Research Scientist,75358,USD,75358,MI,FL,South Korea,M,South Korea,100,"Data Visualization, Python, TensorFlow, Git, Computer Vision",PhD,4,Retail,2024-07-22,2024-09-30,2175,7.9,Autonomous Tech -AI06849,ML Ops Engineer,20791,USD,20791,EN,FL,India,S,India,0,"Computer Vision, MLOps, Data Visualization",Bachelor,0,Automotive,2025-02-22,2025-04-20,946,6.2,Autonomous Tech -AI06850,Principal Data Scientist,97537,EUR,82906,SE,FL,Germany,S,Germany,100,"Deep Learning, Computer Vision, Azure",Associate,6,Gaming,2024-11-09,2025-01-11,704,5.2,Cloud AI Solutions -AI06851,Autonomous Systems Engineer,137228,AUD,185258,SE,CT,Australia,S,Australia,0,"Computer Vision, Azure, AWS",Master,7,Healthcare,2024-03-29,2024-05-14,2399,8.3,DeepTech Ventures -AI06852,AI Consultant,130679,AUD,176417,EX,FL,Australia,S,France,100,"Hadoop, Data Visualization, Python",PhD,19,Telecommunications,2024-05-03,2024-07-06,2270,7.7,Cloud AI Solutions -AI06853,Research Scientist,212506,EUR,180630,EX,CT,Germany,M,Indonesia,50,"Scala, SQL, Linux, AWS",Bachelor,11,Media,2024-05-10,2024-07-13,2220,5.3,Quantum Computing Inc -AI06854,AI Research Scientist,107510,CHF,96759,EN,PT,Switzerland,M,Romania,0,"Kubernetes, MLOps, Docker, AWS",PhD,0,Energy,2024-12-06,2024-12-20,1845,9.5,Algorithmic Solutions -AI06855,Autonomous Systems Engineer,75716,EUR,64359,EN,FL,France,L,Indonesia,100,"SQL, Hadoop, PyTorch",Associate,0,Government,2024-04-30,2024-06-08,2217,5,Autonomous Tech -AI06856,AI Software Engineer,86830,EUR,73806,SE,CT,France,S,France,100,"Statistics, AWS, R, GCP, Azure",Master,6,Automotive,2024-07-14,2024-08-18,1611,5.3,Cognitive Computing -AI06857,Research Scientist,148673,USD,148673,SE,FL,Norway,S,Hungary,100,"Data Visualization, Spark, Python",Bachelor,6,Automotive,2024-07-03,2024-07-19,1209,7.6,Cognitive Computing -AI06858,Data Analyst,128336,USD,128336,EX,FT,Israel,M,Israel,0,"Python, TensorFlow, Mathematics",Associate,18,Gaming,2024-01-08,2024-02-08,1804,5.6,Smart Analytics -AI06859,Data Scientist,281503,USD,281503,EX,CT,United States,M,United States,0,"Deep Learning, GCP, Statistics, Kubernetes, PyTorch",PhD,11,Gaming,2024-11-17,2024-12-02,1099,6.8,Future Systems -AI06860,Robotics Engineer,59139,EUR,50268,EN,CT,Austria,S,Austria,50,"R, MLOps, Azure, NLP, Linux",Associate,1,Finance,2024-10-10,2024-11-25,685,7.9,Algorithmic Solutions -AI06861,Data Engineer,76076,AUD,102703,EN,PT,Australia,L,Australia,0,"TensorFlow, Docker, Kubernetes",Master,1,Energy,2025-01-16,2025-02-11,544,8.6,DataVision Ltd -AI06862,Deep Learning Engineer,116557,USD,116557,SE,FT,South Korea,M,South Korea,50,"Git, SQL, PyTorch",Master,7,Energy,2024-11-26,2025-01-18,1024,9.1,DataVision Ltd -AI06863,Research Scientist,153326,USD,153326,SE,CT,Israel,L,Israel,0,"Data Visualization, Deep Learning, MLOps, Python",Associate,9,Automotive,2024-04-30,2024-06-25,1225,5.5,Cognitive Computing -AI06864,Principal Data Scientist,145710,CHF,131139,SE,FT,Switzerland,S,Finland,100,"Hadoop, GCP, Linux, Kubernetes",Bachelor,7,Consulting,2024-11-06,2024-11-30,1025,6.8,Cloud AI Solutions -AI06865,AI Software Engineer,208806,EUR,177485,EX,FT,Netherlands,L,Poland,100,"Tableau, Scala, Python",Associate,15,Education,2024-09-03,2024-10-09,833,8.3,Digital Transformation LLC -AI06866,Robotics Engineer,59495,USD,59495,EN,FL,Norway,S,Norway,100,"Statistics, GCP, Computer Vision",PhD,1,Consulting,2024-06-27,2024-08-16,2122,8.7,Smart Analytics -AI06867,Research Scientist,161310,AUD,217769,EX,PT,Australia,M,Australia,50,"Deep Learning, Computer Vision, Data Visualization",PhD,12,Technology,2024-12-09,2025-01-05,2010,8.5,Quantum Computing Inc -AI06868,Research Scientist,63732,EUR,54172,EN,FT,Austria,M,China,100,"Spark, Python, Docker, TensorFlow",PhD,1,Manufacturing,2025-03-19,2025-04-08,2143,8.2,DataVision Ltd -AI06869,Data Analyst,144081,USD,144081,SE,PT,Sweden,M,Sweden,0,"Docker, TensorFlow, GCP",Master,6,Telecommunications,2024-10-15,2024-11-12,1553,8.2,Cloud AI Solutions -AI06870,Computer Vision Engineer,81528,USD,81528,MI,FT,South Korea,L,South Korea,50,"Python, Java, Mathematics, Linux",PhD,4,Telecommunications,2024-03-26,2024-04-28,605,6.9,DataVision Ltd -AI06871,Machine Learning Researcher,23844,USD,23844,EN,FL,India,L,India,0,"GCP, AWS, Data Visualization, Statistics, Spark",Bachelor,1,Automotive,2024-08-23,2024-09-25,2315,6.8,Machine Intelligence Group -AI06872,Deep Learning Engineer,46652,USD,46652,MI,CT,China,M,China,100,"Spark, Scala, Git, NLP, Hadoop",PhD,2,Government,2024-06-21,2024-08-28,632,6.8,Quantum Computing Inc -AI06873,Robotics Engineer,63871,USD,63871,MI,CT,Finland,S,Finland,100,"PyTorch, Statistics, Kubernetes",Master,3,Finance,2025-03-13,2025-05-09,2415,7.8,AI Innovations -AI06874,Head of AI,86503,USD,86503,MI,PT,Ireland,M,Ireland,0,"Python, TensorFlow, Computer Vision",Master,2,Transportation,2025-01-16,2025-02-07,1848,6,Machine Intelligence Group -AI06875,Data Engineer,68882,AUD,92991,EN,CT,Australia,M,Australia,100,"Hadoop, Deep Learning, Spark, PyTorch, Statistics",Associate,0,Transportation,2024-08-30,2024-10-11,2401,5.3,Future Systems -AI06876,ML Ops Engineer,120496,EUR,102422,SE,FT,Germany,S,Germany,0,"Data Visualization, Mathematics, R",Master,6,Automotive,2024-12-31,2025-01-26,2097,7,Machine Intelligence Group -AI06877,Data Scientist,67737,EUR,57576,EN,FL,Germany,S,Denmark,50,"Linux, Data Visualization, Docker",Bachelor,0,Consulting,2024-01-31,2024-03-30,1686,7.3,Cloud AI Solutions -AI06878,Head of AI,58637,EUR,49841,EN,FL,Netherlands,S,Thailand,50,"Statistics, Computer Vision, NLP, Git, Kubernetes",Master,1,Technology,2024-06-29,2024-09-04,540,10,Neural Networks Co -AI06879,AI Specialist,130820,EUR,111197,SE,FL,Austria,M,Sweden,0,"Computer Vision, SQL, Statistics, Git",Associate,7,Healthcare,2024-06-24,2024-08-22,913,9.1,Digital Transformation LLC -AI06880,Deep Learning Engineer,101122,USD,101122,MI,CT,Sweden,M,Sweden,0,"Git, Kubernetes, SQL",PhD,3,Automotive,2024-11-20,2025-01-11,1832,7,DeepTech Ventures -AI06881,AI Architect,130892,USD,130892,SE,PT,Finland,L,Finland,0,"Git, R, TensorFlow, Python, PyTorch",PhD,6,Real Estate,2024-07-07,2024-08-29,2367,5.1,Smart Analytics -AI06882,AI Product Manager,26937,USD,26937,EN,CT,India,L,Portugal,0,"R, AWS, Python, Mathematics",Associate,1,Government,2025-04-30,2025-05-25,1341,9.1,Smart Analytics -AI06883,AI Research Scientist,90590,GBP,67943,MI,FT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Azure, Hadoop",Master,3,Real Estate,2024-05-27,2024-08-03,1264,6.8,Quantum Computing Inc -AI06884,AI Consultant,121858,USD,121858,SE,FT,Sweden,S,Sweden,50,"Kubernetes, PyTorch, Statistics, R, Java",Associate,7,Manufacturing,2024-02-09,2024-02-23,1435,6.9,Cognitive Computing -AI06885,Research Scientist,102740,EUR,87329,SE,CT,Netherlands,S,Netherlands,100,"PyTorch, SQL, Linux, Statistics",Bachelor,8,Automotive,2024-05-29,2024-07-23,1550,8.3,DataVision Ltd -AI06886,Data Scientist,250788,USD,250788,EX,FL,Denmark,S,United States,0,"Spark, Tableau, Python, Scala, GCP",Bachelor,11,Consulting,2024-03-25,2024-05-26,626,6.3,DeepTech Ventures -AI06887,Research Scientist,45176,USD,45176,SE,FL,India,S,United Kingdom,0,"Python, Spark, NLP, Data Visualization",PhD,6,Gaming,2024-01-06,2024-01-25,1783,8.5,DeepTech Ventures -AI06888,AI Specialist,107442,USD,107442,SE,FT,South Korea,M,South Korea,0,"Mathematics, Kubernetes, Python, Docker, Data Visualization",Associate,7,Telecommunications,2024-04-22,2024-06-28,1030,5.7,Advanced Robotics -AI06889,Computer Vision Engineer,193572,EUR,164536,EX,FT,Austria,M,Singapore,0,"PyTorch, SQL, GCP",Associate,11,Healthcare,2024-12-13,2025-01-02,1285,6,Future Systems -AI06890,AI Consultant,93956,USD,93956,EX,PT,India,L,India,0,"Azure, PyTorch, TensorFlow, Docker, Git",Master,16,Automotive,2024-03-18,2024-04-07,1868,9.9,DataVision Ltd -AI06891,Autonomous Systems Engineer,77210,EUR,65629,EN,FT,Netherlands,M,Netherlands,0,"Data Visualization, Java, Linux",Associate,1,Technology,2024-08-21,2024-10-04,1539,6.8,Algorithmic Solutions -AI06892,AI Consultant,59058,USD,59058,EX,CT,India,L,Malaysia,50,"NLP, Kubernetes, PyTorch, Git, Tableau",Bachelor,12,Gaming,2024-06-20,2024-08-30,1756,9.9,DeepTech Ventures -AI06893,Machine Learning Researcher,285291,CHF,256762,EX,FT,Switzerland,M,Switzerland,50,"PyTorch, Linux, TensorFlow, Mathematics",Bachelor,12,Technology,2024-03-17,2024-04-25,2134,8.6,Digital Transformation LLC -AI06894,Data Analyst,92251,USD,92251,MI,FT,Sweden,S,Sweden,100,"Python, Tableau, Java, Statistics",PhD,3,Government,2024-09-25,2024-11-26,1721,5.4,Autonomous Tech -AI06895,Machine Learning Engineer,138851,CAD,173564,SE,PT,Canada,L,Canada,50,"Python, Azure, Statistics, Linux",Master,7,Manufacturing,2024-08-14,2024-10-03,2484,5.7,Cloud AI Solutions -AI06896,Deep Learning Engineer,208953,EUR,177610,EX,FT,Netherlands,S,Netherlands,0,"Git, Docker, Scala",PhD,12,Government,2024-02-16,2024-03-28,2051,9.4,Quantum Computing Inc -AI06897,NLP Engineer,187224,CHF,168502,SE,FT,Switzerland,M,Switzerland,100,"Git, Scala, Java",Bachelor,8,Healthcare,2025-02-15,2025-04-14,1158,9.9,Machine Intelligence Group -AI06898,Principal Data Scientist,266395,USD,266395,EX,PT,Sweden,L,Sweden,0,"SQL, Spark, PyTorch, Linux",Bachelor,12,Automotive,2024-03-05,2024-04-05,936,8.4,Smart Analytics -AI06899,AI Specialist,88761,USD,88761,MI,FT,Sweden,S,Brazil,0,"AWS, Linux, Deep Learning, Mathematics",Master,2,Media,2024-01-06,2024-01-28,2134,7.1,Predictive Systems -AI06900,Machine Learning Engineer,81928,USD,81928,EX,CT,China,M,China,50,"Git, Tableau, SQL, Mathematics, Kubernetes",Bachelor,10,Government,2024-08-05,2024-08-25,1453,9.6,Neural Networks Co -AI06901,Machine Learning Researcher,127931,SGD,166310,SE,CT,Singapore,L,Singapore,50,"MLOps, Python, Kubernetes",Master,7,Finance,2024-07-23,2024-10-02,1159,6.3,Predictive Systems -AI06902,Data Analyst,107379,CHF,96641,EN,FT,Switzerland,L,Switzerland,0,"R, Git, Tableau, Azure",Associate,0,Real Estate,2024-09-29,2024-11-23,890,8.2,Smart Analytics -AI06903,Principal Data Scientist,82295,USD,82295,SE,PT,China,L,China,0,"Java, Kubernetes, PyTorch, MLOps",Associate,9,Manufacturing,2024-11-29,2025-02-10,1560,8.6,Neural Networks Co -AI06904,AI Product Manager,91254,EUR,77566,MI,FL,Netherlands,M,Netherlands,100,"Python, Azure, Tableau, SQL",PhD,3,Consulting,2024-02-28,2024-04-28,1098,6.6,Smart Analytics -AI06905,Data Engineer,139532,USD,139532,MI,CT,Denmark,L,Italy,100,"Tableau, TensorFlow, Kubernetes",Associate,2,Telecommunications,2025-04-23,2025-05-19,1554,7.5,Predictive Systems -AI06906,Data Scientist,105160,JPY,11567600,MI,FT,Japan,L,Japan,50,"Scala, AWS, Data Visualization, NLP",Master,2,Energy,2024-03-16,2024-05-11,2229,5.2,Cognitive Computing -AI06907,Research Scientist,123788,JPY,13616680,MI,FT,Japan,L,Japan,100,"Python, SQL, Linux, Deep Learning, Mathematics",Master,3,Real Estate,2025-01-17,2025-02-01,651,8.2,TechCorp Inc -AI06908,Research Scientist,108313,EUR,92066,MI,FL,Netherlands,L,Netherlands,0,"PyTorch, SQL, Kubernetes, R",Bachelor,2,Manufacturing,2025-01-21,2025-02-27,2052,5.7,Predictive Systems -AI06909,Robotics Engineer,105151,USD,105151,SE,CT,Ireland,M,Ireland,50,"Git, TensorFlow, Tableau, SQL, Deep Learning",Bachelor,9,Government,2024-09-09,2024-10-11,1671,6.4,Neural Networks Co -AI06910,Principal Data Scientist,55680,USD,55680,EX,PT,India,M,India,50,"Computer Vision, Hadoop, Azure",Master,12,Manufacturing,2024-08-30,2024-09-17,1329,7.2,DataVision Ltd -AI06911,AI Consultant,141286,JPY,15541460,SE,FL,Japan,S,Japan,100,"Kubernetes, Git, Hadoop",Bachelor,6,Education,2024-06-10,2024-08-07,1364,9.3,TechCorp Inc -AI06912,Machine Learning Engineer,87004,CAD,108755,SE,PT,Canada,S,Norway,0,"Linux, Data Visualization, TensorFlow",Master,8,Retail,2024-09-02,2024-11-02,581,7.4,Advanced Robotics -AI06913,Data Analyst,101540,USD,101540,MI,FL,Sweden,M,India,0,"Linux, Python, R, Java",Master,3,Gaming,2024-12-25,2025-02-06,1662,5.5,Autonomous Tech -AI06914,Research Scientist,176009,USD,176009,SE,PT,Norway,L,Norway,50,"Azure, Java, Scala, Kubernetes",Associate,6,Education,2024-06-02,2024-07-24,2272,6.3,Autonomous Tech -AI06915,Deep Learning Engineer,85561,GBP,64171,EN,PT,United Kingdom,L,Switzerland,50,"R, Kubernetes, Data Visualization",Bachelor,0,Healthcare,2024-12-18,2025-01-04,826,9.2,Smart Analytics -AI06916,Deep Learning Engineer,102426,USD,102426,MI,CT,Ireland,L,Ireland,50,"Computer Vision, Tableau, Linux",Master,3,Automotive,2024-10-13,2024-12-08,1346,8.4,AI Innovations -AI06917,Data Analyst,103962,USD,103962,EN,FT,Norway,L,Norway,0,"SQL, Java, Git, Deep Learning",Associate,1,Retail,2024-05-17,2024-06-20,1235,9.3,Cognitive Computing -AI06918,Head of AI,81801,USD,81801,MI,CT,Israel,M,Israel,50,"MLOps, Kubernetes, SQL, PyTorch",PhD,4,Real Estate,2024-11-03,2025-01-06,1081,6.7,AI Innovations -AI06919,Deep Learning Engineer,141646,USD,141646,SE,FL,Ireland,L,Ireland,0,"Java, SQL, MLOps, Azure",Associate,5,Automotive,2024-08-21,2024-10-11,1664,5.9,Digital Transformation LLC -AI06920,Machine Learning Engineer,197459,USD,197459,EX,CT,Israel,L,Israel,50,"Java, PyTorch, Tableau, Deep Learning",Master,12,Healthcare,2025-03-03,2025-03-23,1470,6.1,Quantum Computing Inc -AI06921,Deep Learning Engineer,86119,EUR,73201,MI,CT,Austria,L,Italy,0,"Azure, Python, Computer Vision, NLP, Tableau",PhD,2,Healthcare,2024-12-06,2024-12-31,665,9.6,Smart Analytics -AI06922,Autonomous Systems Engineer,54196,EUR,46067,EN,CT,Germany,S,Germany,50,"Kubernetes, Statistics, NLP, Azure",Master,1,Real Estate,2025-01-10,2025-02-27,1458,6.9,DataVision Ltd -AI06923,Machine Learning Engineer,83714,USD,83714,EN,FL,Denmark,M,France,100,"Hadoop, TensorFlow, Kubernetes, PyTorch, Git",PhD,1,Finance,2024-09-01,2024-09-25,1593,7,Future Systems -AI06924,Deep Learning Engineer,156483,GBP,117362,SE,CT,United Kingdom,M,United Kingdom,50,"Spark, Hadoop, Linux",Master,7,Technology,2024-10-10,2024-10-30,1052,7.2,TechCorp Inc -AI06925,AI Architect,147145,USD,147145,SE,FT,Norway,S,Norway,0,"Deep Learning, Python, Git, TensorFlow, AWS",PhD,8,Transportation,2024-12-30,2025-02-28,2183,5.1,Smart Analytics -AI06926,NLP Engineer,278709,EUR,236903,EX,FL,Netherlands,L,Brazil,50,"PyTorch, SQL, AWS, R, Java",Associate,18,Transportation,2025-01-24,2025-03-26,2323,6.1,Cloud AI Solutions -AI06927,Computer Vision Engineer,163345,EUR,138843,EX,PT,Austria,S,Austria,100,"Hadoop, Git, Python",Bachelor,14,Automotive,2024-07-23,2024-08-24,2230,9.2,Cloud AI Solutions -AI06928,AI Product Manager,97503,AUD,131629,SE,CT,Australia,S,Australia,50,"Deep Learning, Docker, Java, AWS",Bachelor,6,Manufacturing,2025-01-01,2025-01-20,2440,5.6,Quantum Computing Inc -AI06929,Machine Learning Researcher,173549,CHF,156194,SE,FL,Switzerland,L,Germany,50,"Kubernetes, Scala, Spark",Bachelor,9,Consulting,2025-01-20,2025-03-03,2076,8.6,Advanced Robotics -AI06930,AI Product Manager,229619,GBP,172214,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Hadoop, Java",Associate,18,Government,2025-01-19,2025-02-07,1585,9.7,DeepTech Ventures -AI06931,Computer Vision Engineer,197390,USD,197390,SE,PT,Denmark,M,Denmark,0,"GCP, MLOps, Git, Computer Vision, Java",Master,5,Government,2024-10-20,2024-12-21,1655,9.9,Digital Transformation LLC -AI06932,Computer Vision Engineer,53391,EUR,45382,EN,FL,Austria,S,Romania,50,"Kubernetes, Linux, Tableau, SQL, Statistics",Bachelor,0,Government,2024-11-17,2024-12-18,2141,6.9,Smart Analytics -AI06933,AI Software Engineer,70421,EUR,59858,MI,FL,France,S,Colombia,0,"SQL, Scala, NLP",Associate,3,Energy,2024-12-25,2025-02-04,2200,7.2,Digital Transformation LLC -AI06934,Machine Learning Engineer,82065,USD,82065,EN,PT,Sweden,L,Romania,0,"Docker, Java, Tableau, Hadoop, NLP",Bachelor,1,Automotive,2025-02-21,2025-04-23,1455,9.8,DataVision Ltd -AI06935,NLP Engineer,114605,USD,114605,SE,FL,Israel,L,Israel,0,"GCP, MLOps, R",Master,6,Gaming,2024-06-27,2024-08-24,1238,5.2,DeepTech Ventures -AI06936,AI Architect,209622,CAD,262028,EX,PT,Canada,M,Ireland,0,"Tableau, PyTorch, Kubernetes",Master,17,Manufacturing,2024-06-09,2024-07-10,1344,6.2,Neural Networks Co -AI06937,Computer Vision Engineer,159369,USD,159369,MI,PT,Denmark,L,Denmark,0,"TensorFlow, SQL, R",Bachelor,2,Education,2024-03-18,2024-05-10,1590,7.7,Cognitive Computing -AI06938,Head of AI,287596,USD,287596,EX,FT,Sweden,L,Sweden,0,"Hadoop, Linux, Docker, Data Visualization",Associate,11,Energy,2024-01-01,2024-02-18,714,9.1,Digital Transformation LLC -AI06939,AI Product Manager,145099,EUR,123334,SE,PT,Germany,L,Germany,100,"TensorFlow, Scala, Linux",Associate,5,Government,2024-04-29,2024-06-28,1557,6.3,Predictive Systems -AI06940,ML Ops Engineer,265723,EUR,225865,EX,PT,Germany,L,Germany,0,"Kubernetes, Mathematics, Data Visualization",Master,16,Real Estate,2025-04-30,2025-06-25,645,5.8,Advanced Robotics -AI06941,Data Scientist,146927,EUR,124888,SE,PT,Germany,L,Germany,0,"TensorFlow, Hadoop, Linux, AWS, Computer Vision",Bachelor,5,Healthcare,2024-01-14,2024-03-16,927,7.7,Advanced Robotics -AI06942,AI Research Scientist,55638,USD,55638,MI,CT,China,L,China,50,"Scala, GCP, Data Visualization, Computer Vision",Associate,2,Transportation,2025-01-09,2025-03-18,2069,7.5,Smart Analytics -AI06943,Head of AI,147236,USD,147236,SE,FT,Norway,M,Norway,100,"TensorFlow, Linux, Java",Bachelor,8,Automotive,2024-11-03,2024-12-23,1031,8.6,Advanced Robotics -AI06944,AI Research Scientist,195009,EUR,165758,EX,FL,France,S,New Zealand,100,"Java, Data Visualization, Python",PhD,18,Energy,2025-02-25,2025-05-07,2121,5.3,Advanced Robotics -AI06945,AI Consultant,75991,EUR,64592,EN,FL,France,L,France,50,"Git, SQL, Java",Bachelor,1,Transportation,2024-02-08,2024-03-13,550,8.8,Predictive Systems -AI06946,Research Scientist,188727,USD,188727,EX,CT,Ireland,M,Ireland,0,"Scala, R, PyTorch",Bachelor,12,Telecommunications,2025-01-23,2025-03-28,1066,8.6,Autonomous Tech -AI06947,Machine Learning Researcher,122620,USD,122620,MI,FT,Denmark,L,Denmark,0,"Kubernetes, Spark, Python, Tableau, Linux",Master,3,Consulting,2024-03-03,2024-05-10,1623,8.8,Predictive Systems -AI06948,Computer Vision Engineer,169343,USD,169343,SE,CT,Ireland,L,Hungary,0,"Mathematics, Git, Java",Bachelor,8,Gaming,2024-01-10,2024-03-05,630,7.5,Future Systems -AI06949,AI Architect,76731,CAD,95914,EN,FT,Canada,L,Canada,100,"Azure, Kubernetes, Git",Associate,0,Real Estate,2024-03-12,2024-04-19,1818,8.1,Machine Intelligence Group -AI06950,Machine Learning Researcher,257911,USD,257911,EX,FL,Ireland,L,Mexico,100,"Python, Kubernetes, AWS, Azure, GCP",Bachelor,10,Real Estate,2024-02-02,2024-02-19,1181,9.7,Smart Analytics -AI06951,Head of AI,163774,AUD,221095,EX,FT,Australia,S,Australia,50,"Computer Vision, R, Tableau",Associate,18,Transportation,2024-07-14,2024-08-29,1817,7.5,Cognitive Computing -AI06952,Computer Vision Engineer,31330,USD,31330,EN,FL,China,M,China,0,"R, Spark, Statistics",Master,1,Education,2024-09-25,2024-10-18,2401,10,TechCorp Inc -AI06953,Data Scientist,145202,USD,145202,SE,FT,Israel,L,Poland,0,"Spark, AWS, Deep Learning",Bachelor,6,Gaming,2025-04-21,2025-06-20,728,5,Autonomous Tech -AI06954,Robotics Engineer,89064,SGD,115783,EN,PT,Singapore,L,Singapore,100,"SQL, Python, Computer Vision, Deep Learning",Bachelor,0,Retail,2025-04-13,2025-05-21,1888,7.8,Algorithmic Solutions -AI06955,Data Analyst,132621,USD,132621,SE,PT,Finland,L,Finland,50,"Scala, Docker, Spark, Statistics",Master,7,Education,2025-02-03,2025-03-11,1598,7.3,Quantum Computing Inc -AI06956,NLP Engineer,84808,USD,84808,EN,CT,Sweden,L,Sweden,100,"SQL, NLP, Spark, Hadoop",Bachelor,0,Government,2024-01-04,2024-01-24,2408,8.7,Machine Intelligence Group -AI06957,AI Consultant,59952,USD,59952,EN,FT,Norway,S,Norway,100,"Kubernetes, NLP, Data Visualization",Associate,1,Media,2025-01-31,2025-04-13,1048,5.1,DataVision Ltd -AI06958,Deep Learning Engineer,100845,USD,100845,MI,FT,Finland,M,Germany,0,"TensorFlow, Mathematics, Java, Linux",Master,2,Media,2024-11-25,2024-12-31,1984,9.4,TechCorp Inc -AI06959,Machine Learning Engineer,98597,EUR,83807,MI,CT,Netherlands,M,Japan,100,"GCP, Scala, R",Bachelor,3,Retail,2024-12-24,2025-01-13,1549,8.5,Future Systems -AI06960,Data Engineer,142965,EUR,121520,SE,FT,Germany,M,Nigeria,0,"Kubernetes, Linux, Azure, GCP, Git",PhD,5,Automotive,2024-06-24,2024-08-13,2341,6.4,TechCorp Inc -AI06961,Machine Learning Researcher,84811,GBP,63608,EN,PT,United Kingdom,L,United Kingdom,100,"Tableau, MLOps, NLP, Linux",PhD,1,Retail,2024-08-10,2024-09-11,1114,6.6,Neural Networks Co -AI06962,AI Software Engineer,150732,USD,150732,SE,CT,Denmark,M,Italy,100,"MLOps, Git, GCP, R, Python",Associate,5,Automotive,2025-01-23,2025-02-20,1915,6.6,Cloud AI Solutions -AI06963,AI Research Scientist,146631,AUD,197952,SE,FT,Australia,M,Australia,50,"Scala, Data Visualization, Linux, SQL",Master,8,Gaming,2024-01-23,2024-03-01,1304,5.2,Digital Transformation LLC -AI06964,AI Consultant,87006,CAD,108758,EN,FT,Canada,L,Canada,100,"Docker, Statistics, Computer Vision, Linux, Deep Learning",PhD,1,Education,2024-11-20,2025-01-03,1023,7.8,Cognitive Computing -AI06965,ML Ops Engineer,93917,AUD,126788,SE,CT,Australia,S,France,100,"Git, Python, NLP",Master,5,Manufacturing,2024-06-17,2024-07-07,1248,9.7,Smart Analytics -AI06966,Data Analyst,168686,EUR,143383,EX,FL,Netherlands,S,Netherlands,50,"Statistics, Python, Git, Linux, SQL",Bachelor,12,Real Estate,2025-01-09,2025-02-01,2404,7.4,AI Innovations -AI06967,Research Scientist,128330,GBP,96248,SE,PT,United Kingdom,S,South Africa,50,"Azure, Mathematics, Kubernetes, Deep Learning",Associate,6,Gaming,2025-02-28,2025-05-05,1920,6.8,TechCorp Inc -AI06968,Data Engineer,111839,SGD,145391,SE,PT,Singapore,S,Singapore,50,"Scala, MLOps, Docker, Hadoop, Statistics",PhD,9,Retail,2024-03-02,2024-03-21,2328,7.3,Predictive Systems -AI06969,AI Software Engineer,187884,USD,187884,EX,PT,South Korea,L,Malaysia,50,"TensorFlow, SQL, Mathematics",Master,18,Consulting,2025-01-31,2025-03-09,675,9,AI Innovations -AI06970,AI Specialist,50117,USD,50117,MI,FT,China,M,China,0,"Python, AWS, Kubernetes, MLOps",Bachelor,4,Consulting,2024-05-19,2024-07-15,1362,6.3,Advanced Robotics -AI06971,Data Scientist,355672,CHF,320105,EX,CT,Switzerland,L,Philippines,0,"Tableau, SQL, Kubernetes, PyTorch",Master,16,Automotive,2025-04-25,2025-05-27,776,8.2,Machine Intelligence Group -AI06972,Deep Learning Engineer,114352,AUD,154375,MI,PT,Australia,L,Australia,0,"PyTorch, Scala, Azure, AWS, TensorFlow",Master,4,Gaming,2025-01-23,2025-03-12,2361,9.8,Quantum Computing Inc -AI06973,Data Engineer,167395,USD,167395,EX,CT,United States,M,United States,0,"Spark, Git, Computer Vision, Data Visualization",Bachelor,17,Retail,2024-02-18,2024-04-03,683,8.9,Cloud AI Solutions -AI06974,Autonomous Systems Engineer,172621,JPY,18988310,SE,PT,Japan,L,Japan,100,"Python, SQL, R",Associate,6,Energy,2025-04-30,2025-06-08,813,9.7,Algorithmic Solutions -AI06975,AI Architect,64356,USD,64356,MI,CT,Finland,S,Finland,100,"Deep Learning, MLOps, PyTorch, Tableau",Master,2,Finance,2024-11-09,2025-01-14,1866,6.1,Machine Intelligence Group -AI06976,Data Scientist,54970,USD,54970,EX,PT,India,M,Belgium,50,"SQL, TensorFlow, Linux, Tableau, Java",PhD,13,Transportation,2024-09-02,2024-10-04,821,7.6,Autonomous Tech -AI06977,Deep Learning Engineer,101375,CHF,91238,EN,CT,Switzerland,L,Switzerland,100,"R, PyTorch, Mathematics, Hadoop, Azure",Associate,1,Government,2025-02-09,2025-02-28,1818,7.6,Algorithmic Solutions -AI06978,Computer Vision Engineer,162080,USD,162080,EX,CT,Finland,S,Finland,50,"TensorFlow, Docker, Mathematics, Linux, AWS",PhD,11,Telecommunications,2025-01-01,2025-03-02,688,9.3,DataVision Ltd -AI06979,AI Product Manager,81146,USD,81146,SE,FT,South Korea,S,South Korea,100,"Tableau, Git, Docker, PyTorch, Data Visualization",Associate,5,Manufacturing,2024-05-31,2024-06-29,540,8.6,Quantum Computing Inc -AI06980,Autonomous Systems Engineer,144815,USD,144815,SE,PT,United States,S,United States,50,"R, NLP, Java",PhD,8,Transportation,2025-02-02,2025-02-23,1685,7.9,Future Systems -AI06981,ML Ops Engineer,145112,USD,145112,SE,FT,Ireland,M,Ireland,100,"Kubernetes, Git, Deep Learning, PyTorch, Docker",PhD,9,Transportation,2024-12-23,2025-02-09,1411,5.7,Digital Transformation LLC -AI06982,Principal Data Scientist,66759,USD,66759,EX,FL,China,S,China,100,"TensorFlow, Git, Azure, Spark",PhD,12,Finance,2024-11-29,2025-01-31,1327,9.9,Advanced Robotics -AI06983,Machine Learning Engineer,163174,EUR,138698,EX,PT,Germany,S,United Kingdom,100,"Linux, PyTorch, Git, Mathematics, Deep Learning",PhD,11,Energy,2024-05-04,2024-05-22,2045,5.1,AI Innovations -AI06984,Deep Learning Engineer,112919,CHF,101627,EN,CT,Switzerland,L,Switzerland,100,"R, SQL, Azure",Master,1,Transportation,2025-03-31,2025-06-10,625,6.7,Predictive Systems -AI06985,Principal Data Scientist,113118,SGD,147053,MI,PT,Singapore,M,Japan,50,"Git, Data Visualization, Scala, Azure, Kubernetes",Associate,4,Manufacturing,2024-02-20,2024-03-27,1777,8.6,Machine Intelligence Group -AI06986,Robotics Engineer,64270,USD,64270,EN,FL,Sweden,L,Sweden,0,"NLP, Git, Java",Associate,0,Healthcare,2024-07-19,2024-08-27,598,9.2,AI Innovations -AI06987,Deep Learning Engineer,167528,USD,167528,SE,CT,Denmark,M,Denmark,50,"Scala, Azure, Mathematics, PyTorch, Statistics",Master,5,Retail,2024-09-21,2024-10-11,1659,5.8,Smart Analytics -AI06988,ML Ops Engineer,82676,CAD,103345,MI,FL,Canada,S,Sweden,100,"Data Visualization, Spark, R, SQL",Master,4,Technology,2024-02-23,2024-03-21,1707,6.4,Cloud AI Solutions -AI06989,Computer Vision Engineer,148614,EUR,126322,SE,CT,Austria,L,Austria,50,"PyTorch, Kubernetes, Git",Associate,9,Gaming,2024-04-05,2024-05-24,1048,7.8,Autonomous Tech -AI06990,Machine Learning Engineer,75332,USD,75332,MI,CT,Finland,M,Australia,100,"TensorFlow, SQL, R, Deep Learning, NLP",Associate,3,Energy,2024-12-09,2025-01-18,2177,5.7,Quantum Computing Inc -AI06991,Head of AI,170124,CHF,153112,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, MLOps, Kubernetes, PyTorch, NLP",PhD,4,Consulting,2025-01-16,2025-03-25,2424,6.5,DataVision Ltd -AI06992,Principal Data Scientist,103653,USD,103653,MI,FT,Israel,M,Israel,0,"R, Git, Statistics",PhD,2,Automotive,2024-08-22,2024-09-26,1801,6.7,Future Systems -AI06993,AI Architect,30142,USD,30142,MI,FL,India,L,India,0,"TensorFlow, Git, SQL, Hadoop",Associate,4,Telecommunications,2025-01-27,2025-03-03,1476,7.8,Digital Transformation LLC -AI06994,Machine Learning Researcher,54940,USD,54940,EN,CT,South Korea,M,Brazil,100,"Git, R, Computer Vision, Java",Master,1,Government,2024-09-06,2024-09-30,2122,9.9,Machine Intelligence Group -AI06995,Principal Data Scientist,84125,USD,84125,MI,FL,United States,S,United States,0,"Hadoop, Linux, Data Visualization, Tableau",Master,3,Media,2024-05-24,2024-06-23,1222,7.4,Cloud AI Solutions -AI06996,NLP Engineer,221441,EUR,188225,EX,FT,France,L,Nigeria,100,"Git, SQL, Spark, Tableau, Kubernetes",Bachelor,19,Media,2024-11-02,2025-01-11,1718,5.9,Future Systems -AI06997,AI Software Engineer,64993,EUR,55244,EN,FT,Netherlands,S,Hungary,0,"Git, Java, Kubernetes",Bachelor,0,Media,2024-01-23,2024-03-24,2180,5.8,Future Systems -AI06998,Research Scientist,114387,CAD,142984,MI,FL,Canada,L,Canada,100,"Java, Scala, Tableau, NLP",Associate,2,Retail,2024-09-04,2024-10-21,2379,5.8,Quantum Computing Inc -AI06999,Data Analyst,87162,SGD,113311,EN,PT,Singapore,L,Luxembourg,50,"GCP, PyTorch, Python",Master,1,Gaming,2024-08-04,2024-09-10,2232,8.4,Autonomous Tech -AI07000,Head of AI,117970,USD,117970,MI,FL,United States,L,Philippines,100,"Mathematics, Java, Python",Bachelor,2,Finance,2024-03-27,2024-04-27,2075,5.6,AI Innovations -AI07001,AI Research Scientist,111336,USD,111336,SE,CT,Ireland,S,Ireland,0,"Tableau, TensorFlow, Scala, Git, Azure",PhD,7,Telecommunications,2024-03-14,2024-05-02,1486,5.5,Algorithmic Solutions -AI07002,Machine Learning Researcher,86134,GBP,64601,MI,FL,United Kingdom,S,United Kingdom,0,"TensorFlow, AWS, Azure",Associate,4,Energy,2024-10-31,2024-11-26,2104,6.7,Neural Networks Co -AI07003,Data Engineer,159132,USD,159132,EX,CT,Finland,M,Finland,50,"R, MLOps, SQL",PhD,18,Manufacturing,2024-08-31,2024-10-04,1832,9,DataVision Ltd -AI07004,Autonomous Systems Engineer,88313,USD,88313,EN,CT,United States,M,United States,0,"PyTorch, TensorFlow, Azure, AWS",Associate,1,Telecommunications,2024-12-10,2025-02-12,2142,7.1,DeepTech Ventures -AI07005,AI Product Manager,147619,USD,147619,EX,FL,United States,S,United States,0,"Java, SQL, Hadoop, Git, GCP",Associate,17,Education,2024-06-29,2024-07-15,1756,5.6,Quantum Computing Inc -AI07006,Machine Learning Engineer,41968,USD,41968,MI,CT,India,L,India,50,"Data Visualization, Kubernetes, Azure",PhD,4,Media,2025-03-13,2025-05-10,2229,9.9,Neural Networks Co -AI07007,Data Scientist,68997,USD,68997,EN,CT,South Korea,L,New Zealand,50,"TensorFlow, Python, Tableau, GCP",Bachelor,1,Manufacturing,2024-08-04,2024-10-07,2237,6.6,Advanced Robotics -AI07008,Data Scientist,81660,USD,81660,EN,FL,Israel,L,Israel,50,"Git, Deep Learning, SQL, Linux, Kubernetes",Master,0,Government,2024-03-15,2024-03-30,2337,5.7,Future Systems -AI07009,Autonomous Systems Engineer,151107,GBP,113330,SE,CT,United Kingdom,M,United Kingdom,100,"Deep Learning, AWS, MLOps",Master,7,Government,2024-07-07,2024-09-18,1900,5.9,Algorithmic Solutions -AI07010,Deep Learning Engineer,54435,USD,54435,EN,FT,Sweden,M,Egypt,50,"MLOps, SQL, PyTorch, GCP",PhD,0,Healthcare,2025-01-25,2025-03-20,1222,8.2,Cloud AI Solutions -AI07011,NLP Engineer,295862,EUR,251483,EX,FT,Netherlands,L,Netherlands,0,"Hadoop, GCP, Tableau, Docker, Scala",PhD,16,Technology,2024-04-07,2024-05-18,1139,8,TechCorp Inc -AI07012,AI Product Manager,110402,EUR,93842,SE,FL,France,M,France,100,"R, SQL, Mathematics",Master,9,Energy,2024-06-24,2024-07-29,2427,7.1,Algorithmic Solutions -AI07013,Data Scientist,97747,CAD,122184,MI,PT,Canada,M,Finland,0,"TensorFlow, Mathematics, Python",PhD,4,Manufacturing,2024-07-21,2024-09-12,1776,9.7,Cognitive Computing -AI07014,AI Consultant,57591,EUR,48952,EN,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Spark, Deep Learning, Statistics",Associate,1,Retail,2024-10-31,2025-01-06,1101,9.9,Machine Intelligence Group -AI07015,Autonomous Systems Engineer,202829,USD,202829,EX,FT,Finland,S,Finland,100,"Kubernetes, Python, Linux, GCP",Associate,11,Finance,2024-02-07,2024-03-12,840,6.5,Machine Intelligence Group -AI07016,Autonomous Systems Engineer,49667,CAD,62084,EN,FT,Canada,M,Canada,0,"Data Visualization, Git, R, AWS",Bachelor,0,Education,2024-10-04,2024-11-11,1038,6.7,DataVision Ltd -AI07017,Principal Data Scientist,107663,CHF,96897,EN,PT,Switzerland,L,Switzerland,50,"PyTorch, SQL, NLP",Bachelor,0,Retail,2025-02-26,2025-04-14,1016,6.2,Neural Networks Co -AI07018,Data Engineer,114200,USD,114200,SE,CT,Israel,S,Singapore,100,"Hadoop, Computer Vision, Java, R, Statistics",Associate,6,Retail,2024-05-17,2024-06-11,2297,6.9,Cloud AI Solutions -AI07019,NLP Engineer,195219,GBP,146414,EX,CT,United Kingdom,L,United Kingdom,50,"PyTorch, Hadoop, R, Linux",Associate,11,Consulting,2024-08-13,2024-08-29,1251,9.3,Quantum Computing Inc -AI07020,Principal Data Scientist,174084,JPY,19149240,EX,CT,Japan,M,Japan,100,"Git, NLP, Tableau, Hadoop",Master,10,Transportation,2024-07-07,2024-08-04,877,5.5,Predictive Systems -AI07021,Computer Vision Engineer,86465,EUR,73495,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Hadoop, Scala",PhD,1,Energy,2025-01-19,2025-03-16,1607,9.6,Smart Analytics -AI07022,Head of AI,112857,USD,112857,MI,FL,United States,M,United States,50,"Kubernetes, TensorFlow, NLP, MLOps, Git",Master,3,Telecommunications,2024-08-15,2024-10-06,1126,8.7,TechCorp Inc -AI07023,Robotics Engineer,122484,EUR,104111,MI,CT,Netherlands,L,Indonesia,50,"Git, Mathematics, Python, Data Visualization",Associate,2,Transportation,2024-08-19,2024-10-27,814,5.7,Machine Intelligence Group -AI07024,NLP Engineer,165700,USD,165700,SE,CT,United States,M,United States,0,"Git, Tableau, R, SQL, Scala",Associate,7,Gaming,2024-12-28,2025-02-21,656,7.1,Predictive Systems -AI07025,Principal Data Scientist,168066,USD,168066,SE,PT,Denmark,S,Denmark,50,"Spark, MLOps, Python, Tableau",Master,6,Technology,2024-10-29,2024-12-28,1679,7.2,Autonomous Tech -AI07026,AI Software Engineer,76293,SGD,99181,EN,PT,Singapore,S,Singapore,0,"MLOps, Azure, Docker, AWS, NLP",Associate,1,Manufacturing,2024-03-07,2024-03-28,567,7.6,TechCorp Inc -AI07027,Principal Data Scientist,52755,AUD,71219,EN,FL,Australia,S,Nigeria,50,"PyTorch, Docker, Mathematics",Master,1,Telecommunications,2024-11-14,2025-01-10,2140,7.9,DataVision Ltd -AI07028,NLP Engineer,194324,SGD,252621,EX,CT,Singapore,S,Singapore,100,"Java, Python, Statistics",Master,12,Finance,2024-12-08,2025-01-19,1413,5.9,Machine Intelligence Group -AI07029,Deep Learning Engineer,118307,CAD,147884,SE,FT,Canada,M,Canada,100,"TensorFlow, Java, Git",Bachelor,9,Manufacturing,2024-04-03,2024-06-09,977,7.9,Cognitive Computing -AI07030,ML Ops Engineer,96881,AUD,130789,MI,PT,Australia,M,Egypt,0,"Mathematics, Kubernetes, R",Master,4,Consulting,2025-04-08,2025-06-05,628,8.5,Smart Analytics -AI07031,Autonomous Systems Engineer,57804,USD,57804,SE,FT,China,M,China,50,"Git, Python, Statistics, Azure",Bachelor,5,Government,2024-03-12,2024-04-09,1288,6.5,Cloud AI Solutions -AI07032,Autonomous Systems Engineer,51971,USD,51971,EN,PT,Ireland,S,Ireland,100,"Azure, Kubernetes, SQL, PyTorch",Master,0,Government,2025-04-28,2025-06-03,1884,5.3,Predictive Systems -AI07033,Machine Learning Researcher,175177,SGD,227730,SE,PT,Singapore,L,Singapore,50,"MLOps, Mathematics, SQL, Computer Vision, Kubernetes",Bachelor,8,Media,2024-04-08,2024-05-22,1954,7.7,Quantum Computing Inc -AI07034,Deep Learning Engineer,119721,USD,119721,SE,CT,Norway,S,Russia,0,"TensorFlow, Python, Azure, Kubernetes",Master,7,Media,2024-04-28,2024-06-30,812,8.4,Autonomous Tech -AI07035,AI Product Manager,227954,USD,227954,EX,FT,Israel,L,Israel,0,"Java, R, GCP",Associate,17,Education,2024-04-20,2024-06-22,859,8.5,Machine Intelligence Group -AI07036,Autonomous Systems Engineer,78211,USD,78211,EN,PT,United States,L,United States,0,"TensorFlow, MLOps, Hadoop",PhD,1,Transportation,2025-02-01,2025-03-05,1038,8.4,Cloud AI Solutions -AI07037,AI Research Scientist,175370,EUR,149065,SE,FL,Netherlands,L,Netherlands,0,"Statistics, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-03-13,2024-05-23,1321,8.8,Digital Transformation LLC -AI07038,AI Product Manager,74020,CAD,92525,MI,PT,Canada,S,Canada,50,"PyTorch, Spark, SQL",Bachelor,2,Media,2024-06-29,2024-08-27,932,5.7,Autonomous Tech -AI07039,AI Consultant,66966,GBP,50225,EN,CT,United Kingdom,L,France,0,"SQL, Deep Learning, PyTorch, Java",PhD,0,Education,2024-05-20,2024-07-14,1481,7.2,Advanced Robotics -AI07040,NLP Engineer,73557,EUR,62523,EN,FT,Germany,M,Germany,50,"R, Data Visualization, Linux",Associate,0,Automotive,2024-04-08,2024-05-06,2105,7.3,Future Systems -AI07041,AI Architect,73095,SGD,95024,EN,PT,Singapore,M,Egypt,50,"MLOps, Git, R",Bachelor,1,Healthcare,2024-11-22,2025-01-17,2409,8.5,Advanced Robotics -AI07042,Research Scientist,57811,USD,57811,EN,FL,South Korea,M,South Korea,100,"Python, Linux, Data Visualization, Tableau, R",Master,1,Healthcare,2025-01-01,2025-02-07,1723,7.7,AI Innovations -AI07043,Machine Learning Researcher,235424,EUR,200110,EX,FL,Netherlands,M,Netherlands,100,"Java, Python, Tableau",Master,19,Education,2025-01-26,2025-03-26,1778,9.9,Algorithmic Solutions -AI07044,Robotics Engineer,140023,AUD,189031,SE,FT,Australia,L,Australia,50,"Java, Git, Mathematics",PhD,5,Consulting,2025-04-11,2025-05-25,1371,5.5,AI Innovations -AI07045,Data Engineer,142826,USD,142826,SE,CT,Norway,M,Norway,50,"Deep Learning, Python, TensorFlow, Computer Vision",PhD,9,Energy,2024-02-15,2024-03-20,1317,7.4,Machine Intelligence Group -AI07046,Autonomous Systems Engineer,89624,USD,89624,MI,FL,South Korea,M,Netherlands,0,"Scala, Python, Azure, NLP",Bachelor,3,Transportation,2025-01-13,2025-03-19,1805,5.6,TechCorp Inc -AI07047,Computer Vision Engineer,80501,USD,80501,EN,PT,Denmark,M,Portugal,50,"Deep Learning, Data Visualization, R",Bachelor,0,Finance,2025-03-01,2025-05-01,1126,5.3,Machine Intelligence Group -AI07048,Data Engineer,95043,USD,95043,EN,FT,United States,L,United States,100,"SQL, AWS, Deep Learning, Linux",Associate,0,Finance,2024-04-25,2024-06-03,1627,6.6,Future Systems -AI07049,Deep Learning Engineer,134255,SGD,174532,MI,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning",PhD,2,Automotive,2024-06-30,2024-09-07,913,6.3,Predictive Systems -AI07050,Machine Learning Researcher,108386,CHF,97547,EN,FT,Switzerland,M,Switzerland,100,"Statistics, Tableau, Java, SQL, Python",PhD,0,Transportation,2024-10-25,2024-11-18,1501,5.8,Cloud AI Solutions -AI07051,Robotics Engineer,205581,USD,205581,EX,FL,Israel,M,Israel,50,"Spark, SQL, Python, Statistics",PhD,13,Transportation,2024-12-31,2025-02-20,2163,5.2,Cloud AI Solutions -AI07052,Deep Learning Engineer,115712,EUR,98355,MI,PT,France,L,France,100,"AWS, TensorFlow, Mathematics, SQL",PhD,2,Energy,2024-09-15,2024-10-19,1798,8.3,Predictive Systems -AI07053,AI Software Engineer,41871,USD,41871,MI,FT,China,S,China,0,"Scala, Python, Java, Hadoop",Bachelor,4,Real Estate,2025-03-21,2025-04-04,2356,6.7,DataVision Ltd -AI07054,ML Ops Engineer,89638,CAD,112048,SE,FL,Canada,S,Canada,0,"R, Java, GCP, Spark, Mathematics",Associate,5,Technology,2024-12-15,2025-02-16,2116,8.6,Algorithmic Solutions -AI07055,Machine Learning Engineer,62796,USD,62796,EN,FT,South Korea,L,South Korea,100,"SQL, Tableau, PyTorch",Associate,0,Transportation,2024-01-31,2024-02-28,539,6.6,Algorithmic Solutions -AI07056,AI Product Manager,174278,JPY,19170580,EX,PT,Japan,L,Japan,0,"Python, MLOps, TensorFlow, Git",PhD,13,Media,2024-08-08,2024-10-16,1840,8.2,Neural Networks Co -AI07057,AI Product Manager,236382,JPY,26002020,EX,PT,Japan,M,Argentina,50,"Scala, Tableau, Python, Computer Vision, Deep Learning",PhD,15,Technology,2024-04-06,2024-04-24,821,8.4,Future Systems -AI07058,Computer Vision Engineer,119050,USD,119050,EX,FL,Finland,S,Finland,50,"Spark, Statistics, Computer Vision, Git",Bachelor,15,Technology,2024-09-24,2024-11-06,850,7.1,TechCorp Inc -AI07059,Autonomous Systems Engineer,139306,SGD,181098,SE,PT,Singapore,L,Singapore,50,"Spark, SQL, PyTorch",Bachelor,8,Real Estate,2025-01-10,2025-03-21,723,8,DeepTech Ventures -AI07060,AI Research Scientist,146203,USD,146203,SE,CT,Denmark,M,Denmark,0,"Linux, GCP, Python, Data Visualization, Mathematics",Master,6,Energy,2024-05-06,2024-07-05,1191,8.2,Predictive Systems -AI07061,Research Scientist,91867,EUR,78087,MI,PT,Austria,M,Ireland,100,"Scala, MLOps, Docker",Associate,3,Retail,2024-08-26,2024-10-10,623,7.2,Cloud AI Solutions -AI07062,NLP Engineer,139325,USD,139325,SE,PT,Norway,M,Norway,100,"NLP, PyTorch, TensorFlow",Master,5,Automotive,2024-08-29,2024-11-03,1668,9.3,Predictive Systems -AI07063,Robotics Engineer,368470,USD,368470,EX,PT,Norway,L,Australia,0,"Docker, Deep Learning, SQL",Associate,11,Technology,2024-08-31,2024-10-09,1117,8.5,Digital Transformation LLC -AI07064,AI Research Scientist,79264,USD,79264,MI,FL,South Korea,M,Germany,50,"Java, Python, Kubernetes, Mathematics",Master,2,Technology,2025-04-16,2025-06-02,1050,6,Future Systems -AI07065,Robotics Engineer,213820,USD,213820,EX,CT,Finland,L,Sweden,0,"Kubernetes, Linux, Mathematics, Java",Associate,17,Consulting,2024-06-11,2024-07-05,1605,8.6,Future Systems -AI07066,AI Consultant,91365,AUD,123343,MI,CT,Australia,S,Ireland,100,"Git, Scala, GCP, Computer Vision",Bachelor,2,Consulting,2024-10-05,2024-11-11,634,7.6,Predictive Systems -AI07067,Machine Learning Researcher,135173,EUR,114897,SE,PT,Germany,L,Germany,100,"PyTorch, Linux, Java",Associate,6,Finance,2025-01-21,2025-03-27,1073,6,Smart Analytics -AI07068,Deep Learning Engineer,68488,AUD,92459,EN,FT,Australia,S,Australia,50,"R, Docker, Scala, Statistics, MLOps",Bachelor,0,Government,2024-07-16,2024-09-04,1631,6.4,Cloud AI Solutions -AI07069,AI Software Engineer,117333,EUR,99733,SE,CT,Austria,S,Austria,100,"Scala, TensorFlow, Python, PyTorch",Associate,9,Transportation,2024-09-15,2024-10-05,1294,5.1,Digital Transformation LLC -AI07070,Deep Learning Engineer,99292,USD,99292,MI,PT,Finland,L,Finland,0,"Kubernetes, Scala, Statistics",Associate,3,Healthcare,2024-07-13,2024-09-08,939,8.4,Cloud AI Solutions -AI07071,NLP Engineer,215599,USD,215599,SE,CT,Denmark,L,Denmark,100,"MLOps, Git, PyTorch, Java, Scala",Associate,8,Transportation,2024-09-25,2024-11-01,1492,7,TechCorp Inc -AI07072,ML Ops Engineer,159635,USD,159635,EX,FL,South Korea,M,South Korea,0,"Kubernetes, PyTorch, Docker",PhD,10,Real Estate,2024-05-27,2024-07-16,1395,9,Autonomous Tech -AI07073,AI Product Manager,108321,AUD,146233,MI,FL,Australia,L,Brazil,0,"Computer Vision, Hadoop, Git, Kubernetes",Master,2,Real Estate,2024-05-07,2024-06-10,1705,5.7,Smart Analytics -AI07074,Computer Vision Engineer,76476,CAD,95595,MI,FT,Canada,M,Canada,100,"SQL, Python, Docker, AWS",Associate,2,Consulting,2025-01-28,2025-03-03,543,8.9,AI Innovations -AI07075,Head of AI,83952,AUD,113335,MI,PT,Australia,M,Australia,50,"Kubernetes, Azure, AWS, Deep Learning, Java",Associate,2,Real Estate,2025-03-03,2025-04-06,2076,6.5,Advanced Robotics -AI07076,AI Research Scientist,235700,USD,235700,EX,FT,Israel,L,Ghana,0,"Kubernetes, Python, NLP",Associate,12,Energy,2024-04-21,2024-06-12,1601,8.1,Predictive Systems -AI07077,AI Specialist,131627,USD,131627,SE,FT,United States,M,United States,100,"Hadoop, Kubernetes, Statistics",PhD,6,Real Estate,2024-07-22,2024-08-30,758,7.7,Smart Analytics -AI07078,AI Architect,178535,EUR,151755,EX,CT,Austria,M,Japan,0,"MLOps, Git, Java, Kubernetes, Computer Vision",PhD,12,Automotive,2024-11-13,2025-01-13,1594,5.8,Advanced Robotics -AI07079,AI Architect,209551,USD,209551,EX,PT,Denmark,S,Denmark,0,"Hadoop, Python, Statistics, Linux, Data Visualization",Master,11,Real Estate,2024-03-14,2024-05-04,772,9.6,Machine Intelligence Group -AI07080,AI Software Engineer,84533,EUR,71853,MI,CT,Austria,L,Austria,100,"Python, GCP, TensorFlow",Associate,4,Healthcare,2024-09-07,2024-10-12,860,6.1,Neural Networks Co -AI07081,AI Architect,25457,USD,25457,EN,FL,China,M,Chile,0,"NLP, Linux, SQL",Bachelor,0,Finance,2024-11-01,2024-12-12,1856,5.6,DataVision Ltd -AI07082,Data Analyst,91380,USD,91380,EN,PT,Denmark,M,Denmark,0,"Scala, Tableau, Java, SQL",Associate,0,Media,2024-10-13,2024-11-04,925,7.6,Predictive Systems -AI07083,NLP Engineer,60940,GBP,45705,EN,FT,United Kingdom,S,United Kingdom,50,"Scala, GCP, Tableau, Mathematics",Bachelor,1,Real Estate,2024-11-10,2025-01-20,867,7.8,Smart Analytics -AI07084,Machine Learning Researcher,86902,USD,86902,MI,FL,United States,M,India,50,"R, GCP, Azure, SQL",Associate,3,Consulting,2024-05-04,2024-05-31,538,5.8,Smart Analytics -AI07085,AI Product Manager,119818,USD,119818,MI,PT,United States,M,China,50,"NLP, Data Visualization, Java",Master,3,Energy,2024-11-25,2024-12-30,1964,6.1,Quantum Computing Inc -AI07086,Autonomous Systems Engineer,35047,USD,35047,MI,FT,India,L,India,50,"Python, SQL, TensorFlow, NLP, Deep Learning",Bachelor,3,Real Estate,2024-05-15,2024-06-24,1946,7.6,DataVision Ltd -AI07087,Machine Learning Researcher,175805,GBP,131854,EX,CT,United Kingdom,M,United Kingdom,100,"Statistics, Hadoop, NLP",Bachelor,10,Healthcare,2024-07-02,2024-08-24,1033,7.7,DeepTech Ventures -AI07088,AI Research Scientist,45668,EUR,38818,EN,PT,France,S,France,100,"Azure, MLOps, Scala",Associate,1,Real Estate,2024-05-28,2024-06-20,1406,6.6,Predictive Systems -AI07089,Research Scientist,149817,CAD,187271,EX,PT,Canada,S,Canada,50,"R, Hadoop, MLOps, Java",Bachelor,18,Finance,2024-05-02,2024-06-25,957,6.3,Machine Intelligence Group -AI07090,ML Ops Engineer,82947,GBP,62210,EN,FT,United Kingdom,M,Hungary,50,"Python, Java, Data Visualization, Statistics, Tableau",PhD,0,Education,2024-08-15,2024-09-15,2320,8.3,Algorithmic Solutions -AI07091,AI Research Scientist,85406,CHF,76865,EN,CT,Switzerland,S,Latvia,50,"SQL, AWS, NLP, Scala",Bachelor,1,Healthcare,2024-10-15,2024-11-06,1504,5.9,TechCorp Inc -AI07092,Autonomous Systems Engineer,87146,USD,87146,MI,FL,Ireland,M,Ireland,0,"MLOps, Scala, R, Azure, Computer Vision",PhD,3,Healthcare,2024-06-08,2024-08-16,2101,6.4,Predictive Systems -AI07093,NLP Engineer,69088,AUD,93269,EN,PT,Australia,S,Australia,0,"SQL, Mathematics, Spark, Kubernetes, Git",Associate,0,Gaming,2024-04-07,2024-05-01,1029,7.1,Neural Networks Co -AI07094,AI Consultant,37599,USD,37599,MI,FL,China,S,Romania,100,"Python, TensorFlow, Git, AWS",PhD,3,Government,2024-06-10,2024-08-03,1308,7.8,Cognitive Computing -AI07095,Computer Vision Engineer,87778,USD,87778,EX,FL,China,S,China,0,"NLP, Data Visualization, Tableau, Linux, PyTorch",Bachelor,12,Government,2024-07-03,2024-09-07,578,7.8,Smart Analytics -AI07096,AI Research Scientist,141646,USD,141646,SE,FL,Israel,L,Israel,0,"Azure, Java, R, Data Visualization, Computer Vision",Master,8,Telecommunications,2024-10-11,2024-11-10,784,8,DeepTech Ventures -AI07097,Head of AI,64214,USD,64214,EN,FL,Finland,S,Poland,0,"Docker, Azure, Deep Learning",Bachelor,1,Consulting,2025-02-10,2025-04-06,2117,5.9,DataVision Ltd -AI07098,Data Engineer,167315,GBP,125486,EX,PT,United Kingdom,M,United Kingdom,50,"Git, Data Visualization, Kubernetes, Mathematics, PyTorch",Master,17,Finance,2024-08-14,2024-10-19,1552,5.7,Digital Transformation LLC -AI07099,AI Consultant,48070,USD,48070,SE,PT,India,L,Poland,50,"SQL, AWS, Data Visualization, Docker, PyTorch",PhD,5,Consulting,2024-10-13,2024-10-27,1908,5.6,Quantum Computing Inc -AI07100,Autonomous Systems Engineer,274846,USD,274846,EX,PT,Norway,M,Norway,0,"Scala, Kubernetes, Data Visualization",Master,11,Media,2024-12-05,2025-01-30,855,9.1,Predictive Systems -AI07101,Deep Learning Engineer,116699,SGD,151709,MI,FT,Singapore,M,Brazil,100,"Kubernetes, Python, Spark, Data Visualization, Deep Learning",Bachelor,2,Automotive,2024-02-10,2024-04-14,1991,8.2,Cloud AI Solutions -AI07102,AI Architect,192135,GBP,144101,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Linux, Docker, Spark",Master,15,Government,2024-04-27,2024-05-20,1558,8.3,Neural Networks Co -AI07103,Computer Vision Engineer,129329,EUR,109930,SE,PT,Netherlands,L,Ireland,100,"SQL, Scala, Computer Vision",Bachelor,5,Healthcare,2024-09-21,2024-10-17,1464,7,Cognitive Computing -AI07104,AI Architect,119619,USD,119619,SE,FL,Norway,S,New Zealand,100,"Docker, Kubernetes, Tableau, Mathematics",PhD,9,Automotive,2024-01-30,2024-03-17,1182,5.4,Smart Analytics -AI07105,Machine Learning Researcher,164906,CHF,148415,SE,FL,Switzerland,M,Switzerland,50,"R, SQL, TensorFlow, Tableau, NLP",PhD,7,Retail,2025-04-22,2025-06-10,1394,8.5,Cloud AI Solutions -AI07106,Data Analyst,93246,EUR,79259,SE,PT,Germany,S,Australia,50,"Python, MLOps, Deep Learning, Computer Vision, GCP",Bachelor,7,Education,2024-12-17,2025-01-07,2269,9.7,Digital Transformation LLC -AI07107,Data Engineer,84575,USD,84575,EX,FL,India,L,Argentina,50,"Python, Computer Vision, Java",Associate,13,Transportation,2025-03-25,2025-05-15,1161,5.1,Advanced Robotics -AI07108,AI Specialist,120060,CAD,150075,SE,FL,Canada,M,Canada,0,"Data Visualization, Hadoop, Python, Git",Bachelor,9,Real Estate,2025-04-25,2025-07-07,907,6,Cognitive Computing -AI07109,Deep Learning Engineer,122916,USD,122916,SE,FT,Israel,S,South Korea,100,"Data Visualization, GCP, Linux, PyTorch, Git",Bachelor,5,Manufacturing,2025-02-16,2025-04-20,1429,6.1,Digital Transformation LLC -AI07110,Autonomous Systems Engineer,86361,SGD,112269,MI,CT,Singapore,M,Romania,0,"Python, GCP, Scala, R",Associate,4,Finance,2024-11-16,2024-12-14,741,8.5,Digital Transformation LLC -AI07111,Robotics Engineer,114870,CAD,143588,SE,CT,Canada,S,Canada,100,"PyTorch, Azure, AWS",Associate,8,Education,2025-04-11,2025-05-31,671,9.5,Cognitive Computing -AI07112,Autonomous Systems Engineer,174174,JPY,19159140,EX,FL,Japan,L,Vietnam,100,"Azure, Python, TensorFlow",Bachelor,15,Healthcare,2025-02-06,2025-03-21,1297,6.4,Future Systems -AI07113,Robotics Engineer,174611,USD,174611,EX,CT,Finland,M,Czech Republic,0,"Azure, Git, PyTorch",PhD,18,Technology,2025-04-13,2025-05-02,2132,9.4,Cloud AI Solutions -AI07114,AI Product Manager,79305,USD,79305,MI,FT,Ireland,S,China,100,"R, MLOps, Scala, Mathematics",Associate,4,Government,2024-08-13,2024-09-02,2145,8.8,Neural Networks Co -AI07115,AI Product Manager,104456,USD,104456,SE,FT,South Korea,M,South Korea,50,"Python, Deep Learning, MLOps, TensorFlow",PhD,5,Government,2024-04-09,2024-05-26,1561,9.2,Predictive Systems -AI07116,AI Product Manager,134807,USD,134807,SE,FT,Israel,M,Romania,100,"SQL, AWS, PyTorch",Bachelor,6,Transportation,2025-03-14,2025-04-18,1452,9.1,TechCorp Inc -AI07117,AI Architect,149312,USD,149312,MI,FT,Denmark,L,Denmark,100,"Deep Learning, PyTorch, Mathematics",Master,2,Education,2024-06-26,2024-07-13,549,9.2,DataVision Ltd -AI07118,Research Scientist,138822,USD,138822,MI,CT,Denmark,L,Denmark,100,"Scala, Docker, Azure, Python",Master,4,Telecommunications,2024-04-08,2024-06-11,1428,6.6,Smart Analytics -AI07119,AI Research Scientist,87558,AUD,118203,EN,CT,Australia,L,Australia,0,"NLP, Kubernetes, AWS",PhD,1,Transportation,2024-06-11,2024-08-23,1979,7.5,Neural Networks Co -AI07120,AI Software Engineer,48577,EUR,41290,EN,PT,France,S,Russia,50,"TensorFlow, Scala, Deep Learning, Git",Associate,0,Gaming,2024-09-26,2024-10-11,617,7.6,AI Innovations -AI07121,Machine Learning Engineer,247655,EUR,210507,EX,PT,Germany,M,Germany,50,"Azure, Git, Python",PhD,14,Automotive,2024-07-28,2024-08-16,1618,6.5,Quantum Computing Inc -AI07122,Robotics Engineer,108278,GBP,81209,MI,PT,United Kingdom,M,United Kingdom,50,"Scala, R, SQL, AWS, Tableau",Master,2,Manufacturing,2024-05-03,2024-06-19,799,9.8,TechCorp Inc -AI07123,NLP Engineer,78812,EUR,66990,EN,FL,Germany,L,Germany,0,"R, AWS, Linux",Associate,0,Finance,2025-03-22,2025-05-11,1619,6.9,AI Innovations -AI07124,AI Specialist,116018,USD,116018,MI,PT,Sweden,L,Sweden,0,"PyTorch, Scala, Computer Vision, Mathematics",Bachelor,3,Automotive,2024-04-25,2024-06-25,2267,6.5,Algorithmic Solutions -AI07125,AI Research Scientist,27858,USD,27858,EN,FL,India,M,India,0,"SQL, R, PyTorch",Master,1,Gaming,2024-11-22,2025-01-20,1457,7.7,Cloud AI Solutions -AI07126,AI Consultant,60002,JPY,6600220,EN,CT,Japan,S,Japan,50,"Scala, PyTorch, Statistics, Spark",PhD,0,Government,2025-03-31,2025-05-08,660,6,DeepTech Ventures -AI07127,AI Specialist,167636,CHF,150872,SE,CT,Switzerland,L,Switzerland,0,"Python, Linux, Hadoop, Statistics, Mathematics",Associate,5,Real Estate,2024-02-19,2024-04-15,2370,7.1,Cloud AI Solutions -AI07128,AI Research Scientist,89617,USD,89617,MI,PT,Norway,S,Norway,0,"SQL, GCP, Python, Java, Git",Master,4,Media,2024-10-28,2024-12-24,2284,6.2,Cognitive Computing -AI07129,AI Consultant,133164,EUR,113189,SE,PT,France,L,Germany,100,"Computer Vision, Python, MLOps",Associate,7,Government,2025-03-09,2025-03-25,1886,9.1,Machine Intelligence Group -AI07130,ML Ops Engineer,91502,USD,91502,MI,PT,Finland,M,Finland,0,"Scala, Hadoop, AWS, Spark",Associate,2,Education,2024-04-01,2024-06-05,2387,5.4,Digital Transformation LLC -AI07131,AI Specialist,127869,USD,127869,SE,CT,South Korea,L,South Korea,0,"AWS, Python, Scala, Data Visualization",PhD,7,Manufacturing,2025-02-18,2025-04-04,773,9.6,Predictive Systems -AI07132,AI Architect,127426,CHF,114683,EN,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, NLP",Bachelor,0,Finance,2024-07-27,2024-10-02,1623,6.4,Neural Networks Co -AI07133,Data Analyst,210284,SGD,273369,EX,CT,Singapore,L,Singapore,50,"Java, TensorFlow, Statistics",Master,15,Gaming,2024-06-15,2024-08-07,2166,8.8,Machine Intelligence Group -AI07134,Machine Learning Engineer,78163,USD,78163,EN,PT,Ireland,M,Ireland,50,"SQL, Python, TensorFlow, PyTorch",Bachelor,1,Manufacturing,2024-07-27,2024-08-17,510,9.5,Predictive Systems -AI07135,AI Software Engineer,134757,USD,134757,MI,PT,Norway,L,China,50,"Scala, Mathematics, Git",Associate,4,Manufacturing,2024-08-27,2024-10-09,1181,8.6,TechCorp Inc -AI07136,Autonomous Systems Engineer,71562,CAD,89453,MI,PT,Canada,S,Canada,0,"Hadoop, R, Linux, Computer Vision",Bachelor,4,Gaming,2024-08-25,2024-09-20,2480,6.7,DeepTech Ventures -AI07137,Machine Learning Engineer,47242,CAD,59053,EN,FL,Canada,S,Canada,100,"AWS, Docker, GCP",Master,1,Automotive,2024-06-05,2024-07-01,1580,5.9,DataVision Ltd -AI07138,Head of AI,57033,USD,57033,EX,FT,India,M,Mexico,0,"Scala, PyTorch, Statistics",Bachelor,16,Transportation,2025-02-19,2025-04-04,1212,7,Quantum Computing Inc -AI07139,Data Analyst,119717,USD,119717,SE,PT,Sweden,S,Sweden,100,"GCP, TensorFlow, Python, Kubernetes",PhD,5,Healthcare,2024-03-04,2024-04-11,1807,7.8,Digital Transformation LLC -AI07140,Data Analyst,127727,USD,127727,SE,FL,Sweden,S,Sweden,0,"AWS, PyTorch, Java",Associate,9,Transportation,2024-03-12,2024-05-05,1142,5.6,DeepTech Ventures -AI07141,Machine Learning Engineer,78754,USD,78754,EN,CT,Finland,L,Finland,50,"NLP, SQL, Mathematics, MLOps, PyTorch",Bachelor,1,Energy,2024-10-05,2024-11-27,1435,9.9,Advanced Robotics -AI07142,Autonomous Systems Engineer,76900,USD,76900,MI,FL,Finland,M,Finland,50,"Kubernetes, PyTorch, Git, Linux",Bachelor,3,Government,2024-01-01,2024-01-16,1848,9.7,Algorithmic Solutions -AI07143,NLP Engineer,140463,USD,140463,SE,FT,Ireland,L,Ireland,50,"Data Visualization, TensorFlow, SQL, Git, Scala",PhD,8,Government,2024-04-01,2024-05-10,2156,6.9,Cognitive Computing -AI07144,AI Software Engineer,107972,AUD,145762,SE,FL,Australia,S,Romania,0,"TensorFlow, SQL, Mathematics, Linux",Associate,5,Retail,2025-02-04,2025-02-26,1598,9.4,Machine Intelligence Group -AI07145,Deep Learning Engineer,210162,USD,210162,EX,PT,United States,L,United States,100,"Java, Computer Vision, Python, Hadoop, Scala",Associate,12,Manufacturing,2025-03-06,2025-05-12,2178,9.7,Quantum Computing Inc -AI07146,Data Analyst,199015,CAD,248769,EX,PT,Canada,S,Egypt,50,"Git, TensorFlow, Mathematics, Spark",Master,13,Retail,2024-12-08,2025-02-05,722,7.8,DeepTech Ventures -AI07147,Data Analyst,214251,USD,214251,EX,PT,Ireland,M,Argentina,0,"Python, MLOps, GCP, Statistics, Linux",Master,14,Automotive,2024-04-13,2024-05-26,838,6.6,DataVision Ltd -AI07148,AI Research Scientist,200251,USD,200251,EX,FT,Sweden,M,Sweden,50,"MLOps, Hadoop, NLP, Data Visualization, R",Master,17,Government,2025-02-01,2025-04-09,693,10,Predictive Systems -AI07149,Machine Learning Engineer,56919,AUD,76841,EN,CT,Australia,S,Australia,0,"R, SQL, Git, Mathematics, Kubernetes",Bachelor,1,Technology,2024-06-07,2024-07-31,605,8.9,Quantum Computing Inc -AI07150,ML Ops Engineer,52483,USD,52483,EN,FT,Sweden,M,Sweden,0,"Spark, Mathematics, Data Visualization",Associate,1,Retail,2025-03-01,2025-03-18,2260,8.9,DataVision Ltd -AI07151,Computer Vision Engineer,124533,USD,124533,SE,CT,United States,S,South Africa,0,"Python, TensorFlow, Hadoop, Java",PhD,9,Telecommunications,2024-01-03,2024-01-19,1465,5.4,Future Systems -AI07152,NLP Engineer,122990,AUD,166037,MI,FT,Australia,L,Australia,100,"MLOps, Scala, Statistics",Associate,2,Finance,2025-02-01,2025-03-26,1567,9.2,Predictive Systems -AI07153,Head of AI,149199,USD,149199,EX,PT,Sweden,M,Chile,0,"PyTorch, Scala, Statistics",Bachelor,12,Energy,2024-10-24,2024-11-07,1675,6.6,Neural Networks Co -AI07154,NLP Engineer,82914,EUR,70477,MI,CT,Germany,S,Latvia,100,"Tableau, PyTorch, Kubernetes, GCP, AWS",Bachelor,3,Government,2024-02-19,2024-04-08,1754,5.9,Advanced Robotics -AI07155,Data Scientist,73131,EUR,62161,EN,PT,Austria,M,New Zealand,100,"Azure, Deep Learning, Git, Hadoop",Bachelor,1,Automotive,2024-03-26,2024-04-14,1533,5.3,Algorithmic Solutions -AI07156,AI Software Engineer,84202,JPY,9262220,EN,PT,Japan,M,Japan,50,"Spark, Docker, GCP, AWS, Hadoop",Bachelor,0,Real Estate,2024-11-15,2024-12-02,1057,8.8,Predictive Systems -AI07157,Autonomous Systems Engineer,196071,GBP,147053,EX,PT,United Kingdom,S,Kenya,0,"Linux, SQL, Deep Learning, Python, R",Associate,17,Transportation,2024-06-19,2024-08-27,741,8.2,Algorithmic Solutions -AI07158,AI Software Engineer,56307,USD,56307,EN,PT,Israel,M,Israel,100,"Python, Docker, Hadoop, Git",Bachelor,0,Real Estate,2025-01-27,2025-03-14,1013,6.1,Algorithmic Solutions -AI07159,Robotics Engineer,118127,USD,118127,EX,PT,China,L,China,0,"Python, Docker, MLOps",PhD,10,Energy,2024-12-20,2025-01-15,788,6.3,Cloud AI Solutions -AI07160,Deep Learning Engineer,286081,AUD,386209,EX,CT,Australia,L,Australia,0,"Statistics, Spark, TensorFlow, Linux, Docker",PhD,10,Automotive,2025-01-01,2025-02-22,1102,7.4,DataVision Ltd -AI07161,Data Analyst,38151,USD,38151,MI,FT,China,S,China,0,"PyTorch, TensorFlow, Statistics, Mathematics",Associate,4,Media,2024-10-09,2024-11-24,633,5.2,Cloud AI Solutions -AI07162,AI Product Manager,51436,JPY,5657960,EN,PT,Japan,S,Japan,0,"SQL, GCP, Kubernetes, Docker, Mathematics",Master,1,Manufacturing,2025-02-04,2025-02-20,1703,5.6,Future Systems -AI07163,Head of AI,179375,CHF,161438,MI,PT,Switzerland,L,New Zealand,0,"Python, Computer Vision, Linux, Azure, Deep Learning",Bachelor,3,Real Estate,2024-10-28,2024-12-07,501,9.2,Neural Networks Co -AI07164,AI Research Scientist,224945,USD,224945,EX,FL,Israel,M,Israel,100,"Docker, SQL, PyTorch, Java",PhD,16,Education,2024-08-28,2024-10-23,2317,9.1,Machine Intelligence Group -AI07165,AI Architect,199077,USD,199077,EX,FT,Sweden,S,India,100,"Computer Vision, Tableau, Data Visualization",Associate,14,Retail,2024-11-14,2024-12-25,2448,6.7,Cognitive Computing -AI07166,Data Engineer,154017,USD,154017,SE,PT,United States,L,United States,50,"Python, SQL, Spark, MLOps, TensorFlow",Associate,9,Transportation,2024-08-07,2024-09-11,1991,6.4,AI Innovations -AI07167,Data Engineer,187633,JPY,20639630,EX,CT,Japan,S,Japan,100,"Tableau, Scala, NLP, TensorFlow",Bachelor,17,Consulting,2024-09-28,2024-10-12,1306,8.4,Cloud AI Solutions -AI07168,Research Scientist,113467,USD,113467,MI,FL,Norway,M,Norway,50,"Azure, AWS, NLP, Deep Learning, GCP",Associate,4,Manufacturing,2024-02-16,2024-03-31,1916,8.6,Future Systems -AI07169,AI Product Manager,97170,USD,97170,MI,FL,Sweden,M,Sweden,100,"Kubernetes, GCP, SQL",PhD,4,Consulting,2024-07-01,2024-08-18,1337,6,Autonomous Tech -AI07170,AI Specialist,117600,USD,117600,MI,FT,Norway,S,Norway,50,"Java, Azure, Kubernetes",PhD,2,Technology,2024-09-11,2024-11-01,536,5.1,Neural Networks Co -AI07171,ML Ops Engineer,175430,CAD,219288,EX,CT,Canada,S,Canada,100,"Hadoop, R, SQL",Master,13,Finance,2025-03-17,2025-05-12,2082,9.2,Advanced Robotics -AI07172,Research Scientist,92546,EUR,78664,MI,FL,Netherlands,L,Netherlands,0,"R, Java, SQL",PhD,4,Transportation,2025-03-03,2025-03-17,1865,5.2,Cloud AI Solutions -AI07173,NLP Engineer,78042,USD,78042,MI,FL,United States,S,United States,100,"Python, GCP, TensorFlow, AWS, Deep Learning",Associate,2,Automotive,2024-03-21,2024-04-07,1251,6.2,DataVision Ltd -AI07174,Head of AI,60141,USD,60141,SE,FT,China,S,China,0,"Azure, AWS, Deep Learning, Computer Vision, GCP",PhD,5,Education,2025-01-03,2025-02-16,834,9.5,DeepTech Ventures -AI07175,Computer Vision Engineer,74219,EUR,63086,MI,FT,France,M,France,100,"Spark, NLP, Scala, PyTorch",Master,4,Gaming,2024-11-06,2025-01-03,577,5.7,Future Systems -AI07176,Data Scientist,117670,USD,117670,SE,PT,Finland,M,Finland,0,"Azure, TensorFlow, SQL, Tableau, Deep Learning",Associate,9,Manufacturing,2024-03-07,2024-03-25,585,9.5,Predictive Systems -AI07177,AI Product Manager,43045,USD,43045,EN,PT,South Korea,S,South Korea,100,"Mathematics, Data Visualization, Git, Linux",Associate,0,Healthcare,2024-05-22,2024-06-18,1964,5.9,Future Systems -AI07178,Computer Vision Engineer,204977,USD,204977,EX,FT,Israel,L,Israel,0,"NLP, Docker, Tableau, TensorFlow",Master,13,Retail,2024-01-23,2024-04-01,1912,8.8,Autonomous Tech -AI07179,Data Scientist,99117,USD,99117,MI,PT,Sweden,S,Sweden,50,"Azure, TensorFlow, AWS, Linux",Associate,3,Technology,2024-08-07,2024-08-30,1543,7.4,Autonomous Tech -AI07180,AI Product Manager,71043,USD,71043,EN,FT,Ireland,L,Ireland,50,"Data Visualization, Python, Spark, MLOps",Associate,1,Healthcare,2024-04-28,2024-07-01,2161,9.5,Algorithmic Solutions -AI07181,Machine Learning Engineer,245455,SGD,319092,EX,FL,Singapore,M,Singapore,0,"Git, Azure, Scala",PhD,19,Government,2025-04-25,2025-05-26,1625,7.6,Future Systems -AI07182,NLP Engineer,100152,USD,100152,MI,FL,South Korea,L,South Korea,50,"Java, Spark, Kubernetes",Bachelor,2,Government,2025-03-14,2025-04-16,529,6.5,Advanced Robotics -AI07183,Machine Learning Researcher,184471,EUR,156800,SE,PT,Netherlands,L,Singapore,100,"Python, MLOps, Statistics, Mathematics, Kubernetes",Associate,5,Gaming,2025-02-09,2025-04-13,1628,6.2,Future Systems -AI07184,Research Scientist,192741,EUR,163830,EX,FL,Austria,L,India,100,"Scala, Tableau, SQL, AWS",PhD,14,Real Estate,2024-12-25,2025-01-21,893,6.8,Neural Networks Co -AI07185,Autonomous Systems Engineer,130456,USD,130456,SE,FT,Norway,S,Norway,0,"Mathematics, Spark, NLP, Linux, Git",PhD,7,Healthcare,2025-03-21,2025-04-26,1191,8,Neural Networks Co -AI07186,ML Ops Engineer,131122,USD,131122,MI,CT,Denmark,M,Denmark,50,"Scala, Docker, Kubernetes",Associate,3,Gaming,2024-06-15,2024-08-08,2321,6.7,TechCorp Inc -AI07187,AI Research Scientist,92768,USD,92768,MI,FT,Ireland,S,Ireland,0,"Mathematics, R, SQL",Master,4,Finance,2024-08-20,2024-10-19,774,9.9,DeepTech Ventures -AI07188,AI Architect,117822,USD,117822,SE,FL,Israel,M,Israel,0,"Python, Spark, NLP, SQL, AWS",Associate,7,Telecommunications,2024-07-06,2024-09-11,690,9.3,Future Systems -AI07189,Data Scientist,220795,EUR,187676,EX,CT,Austria,L,Austria,100,"Kubernetes, Python, Tableau",Master,15,Transportation,2024-07-06,2024-08-04,1166,8.1,Digital Transformation LLC -AI07190,AI Specialist,71908,CAD,89885,MI,CT,Canada,M,Canada,0,"Python, TensorFlow, MLOps, Linux, Hadoop",Bachelor,4,Telecommunications,2024-06-19,2024-07-25,1717,9,DeepTech Ventures -AI07191,AI Consultant,217854,USD,217854,EX,FL,Denmark,L,Denmark,0,"Statistics, AWS, Hadoop, Docker, GCP",PhD,19,Media,2024-05-24,2024-07-28,2421,9.4,Machine Intelligence Group -AI07192,Head of AI,50633,JPY,5569630,EN,CT,Japan,S,Japan,0,"R, PyTorch, GCP",Master,0,Manufacturing,2024-05-15,2024-07-20,1102,7,Digital Transformation LLC -AI07193,Data Scientist,67836,CAD,84795,EN,CT,Canada,S,Indonesia,100,"Azure, Python, NLP, Docker",Bachelor,0,Telecommunications,2025-02-13,2025-04-05,2052,7.7,Autonomous Tech -AI07194,Deep Learning Engineer,120724,AUD,162977,MI,PT,Australia,L,Australia,50,"Scala, Java, Kubernetes, Mathematics",PhD,2,Government,2024-11-22,2025-01-30,1133,6.4,Quantum Computing Inc -AI07195,Head of AI,117611,USD,117611,MI,FL,Denmark,S,Denmark,50,"SQL, Mathematics, R, PyTorch",Bachelor,4,Consulting,2024-11-01,2025-01-04,2446,9.4,Autonomous Tech -AI07196,Autonomous Systems Engineer,143600,USD,143600,EX,CT,Ireland,S,Ireland,50,"MLOps, Python, Statistics",Master,12,Automotive,2024-11-11,2025-01-08,907,7.1,Advanced Robotics -AI07197,Deep Learning Engineer,54479,SGD,70823,EN,FL,Singapore,M,Singapore,50,"MLOps, Linux, Azure",Bachelor,0,Manufacturing,2024-06-15,2024-07-18,1974,6.7,Future Systems -AI07198,AI Research Scientist,234608,JPY,25806880,EX,FL,Japan,S,Japan,50,"Spark, Python, Docker, GCP",Associate,17,Telecommunications,2024-10-08,2024-12-16,558,8,Cognitive Computing -AI07199,Computer Vision Engineer,58879,EUR,50047,EN,FL,Germany,L,Germany,100,"TensorFlow, Spark, PyTorch, Git",Master,0,Government,2025-01-03,2025-02-24,1177,7.5,Cloud AI Solutions -AI07200,Principal Data Scientist,94161,USD,94161,MI,FT,Denmark,S,Denmark,50,"Java, SQL, Tableau, Azure, Spark",Associate,3,Energy,2024-06-30,2024-09-02,1398,5.2,Autonomous Tech -AI07201,Head of AI,83285,USD,83285,MI,FL,Ireland,S,Ireland,50,"R, Java, Spark, TensorFlow, Kubernetes",Master,3,Retail,2025-03-07,2025-04-21,2452,8.8,Neural Networks Co -AI07202,AI Software Engineer,203713,AUD,275013,EX,FL,Australia,M,Australia,50,"Mathematics, Kubernetes, MLOps",PhD,14,Transportation,2024-11-21,2025-01-04,594,7.1,Autonomous Tech -AI07203,Data Scientist,31793,USD,31793,MI,PT,China,S,China,100,"MLOps, Docker, Linux, Tableau, Data Visualization",Master,2,Government,2024-05-21,2024-06-24,718,5.4,DataVision Ltd -AI07204,Principal Data Scientist,48887,USD,48887,SE,PT,India,L,India,50,"PyTorch, Tableau, Hadoop, AWS",PhD,9,Technology,2025-04-24,2025-06-04,1126,8.2,Digital Transformation LLC -AI07205,Principal Data Scientist,106359,AUD,143585,MI,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, SQL, GCP",Master,4,Technology,2025-03-20,2025-05-19,905,5.7,TechCorp Inc -AI07206,Deep Learning Engineer,115364,USD,115364,SE,CT,Israel,M,Australia,50,"Python, Java, Deep Learning, TensorFlow",Master,8,Manufacturing,2024-03-05,2024-05-01,844,6.7,Quantum Computing Inc -AI07207,Research Scientist,135236,EUR,114951,SE,CT,Germany,S,Germany,0,"MLOps, Spark, Python, Git",Bachelor,5,Education,2024-08-20,2024-10-31,2100,7.1,Advanced Robotics -AI07208,Data Analyst,196882,EUR,167350,EX,FL,Netherlands,L,Netherlands,100,"Computer Vision, Hadoop, Statistics, TensorFlow",Master,11,Real Estate,2024-05-06,2024-06-26,2375,8.3,DeepTech Ventures -AI07209,AI Specialist,52592,GBP,39444,EN,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Scala, SQL, NLP",PhD,0,Transportation,2024-12-26,2025-02-02,1544,8.8,Future Systems -AI07210,Machine Learning Researcher,130809,JPY,14388990,SE,CT,Japan,L,Japan,0,"PyTorch, SQL, Git, Hadoop, Mathematics",Associate,7,Healthcare,2024-02-15,2024-03-25,897,6.4,AI Innovations -AI07211,Data Engineer,83254,EUR,70766,EN,FL,Germany,L,Germany,50,"PyTorch, NLP, Deep Learning, Python, MLOps",Master,1,Technology,2024-01-01,2024-02-27,798,9.4,Predictive Systems -AI07212,Deep Learning Engineer,116639,USD,116639,MI,PT,Denmark,S,Denmark,50,"Tableau, Java, MLOps, Hadoop, Azure",Associate,3,Retail,2024-06-28,2024-07-14,892,6,Cloud AI Solutions -AI07213,Data Engineer,188382,CHF,169544,SE,FL,Switzerland,M,Portugal,0,"MLOps, PyTorch, Mathematics, TensorFlow",Bachelor,6,Consulting,2024-06-02,2024-07-11,2297,6.8,Cognitive Computing -AI07214,AI Software Engineer,126123,SGD,163960,SE,PT,Singapore,L,Romania,100,"Scala, Tableau, Python, Data Visualization",Master,7,Healthcare,2025-04-22,2025-06-26,686,8.1,Quantum Computing Inc -AI07215,AI Product Manager,108451,USD,108451,SE,FT,South Korea,M,South Korea,0,"NLP, Docker, SQL, Git",PhD,6,Technology,2024-06-15,2024-08-19,2311,6.2,Future Systems -AI07216,Computer Vision Engineer,241452,EUR,205234,EX,FL,Netherlands,L,Netherlands,0,"Python, Tableau, Deep Learning",Master,11,Finance,2024-09-23,2024-10-15,1584,6.5,Advanced Robotics -AI07217,Robotics Engineer,95945,EUR,81553,MI,CT,Netherlands,S,Netherlands,0,"SQL, Linux, Tableau",Master,2,Consulting,2024-01-02,2024-02-23,1803,10,Machine Intelligence Group -AI07218,Data Scientist,92299,AUD,124604,MI,PT,Australia,L,Portugal,50,"Deep Learning, Scala, SQL, Git",Associate,3,Finance,2024-07-08,2024-08-16,1353,7.7,Neural Networks Co -AI07219,Data Engineer,92328,USD,92328,MI,FT,Israel,M,Ukraine,0,"Java, Python, Hadoop, Spark",Associate,4,Automotive,2024-01-02,2024-02-02,1233,5,AI Innovations -AI07220,AI Consultant,63650,USD,63650,EN,FT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, Mathematics",Associate,1,Government,2024-05-17,2024-06-07,2110,7.3,Quantum Computing Inc -AI07221,AI Consultant,240627,EUR,204533,EX,FT,Netherlands,M,Netherlands,0,"Data Visualization, Spark, Scala, Deep Learning",PhD,18,Retail,2024-06-26,2024-07-19,1850,5.1,AI Innovations -AI07222,AI Specialist,113824,USD,113824,MI,PT,Norway,L,Norway,100,"AWS, Docker, Azure, Computer Vision",PhD,4,Consulting,2024-11-18,2025-01-06,2039,8.2,Algorithmic Solutions -AI07223,Data Analyst,102248,CHF,92023,MI,CT,Switzerland,S,Spain,0,"AWS, Mathematics, Hadoop",PhD,2,Real Estate,2024-03-09,2024-03-30,1863,9.9,Smart Analytics -AI07224,Machine Learning Researcher,72700,USD,72700,MI,PT,South Korea,S,South Korea,100,"Python, Hadoop, Linux, Scala, Java",PhD,4,Consulting,2024-11-18,2024-12-04,1842,5.6,Advanced Robotics -AI07225,AI Product Manager,101760,USD,101760,MI,FL,Ireland,L,Ireland,50,"Scala, Git, Statistics, Computer Vision, Kubernetes",Associate,3,Retail,2024-02-19,2024-03-13,2062,6.9,Digital Transformation LLC -AI07226,Machine Learning Researcher,75850,USD,75850,MI,PT,Israel,S,Israel,0,"Deep Learning, Java, Git, Mathematics, R",Bachelor,4,Retail,2024-05-03,2024-06-26,969,8.4,Cloud AI Solutions -AI07227,Robotics Engineer,54596,EUR,46407,EN,FL,Austria,M,Austria,100,"NLP, Python, Deep Learning",Bachelor,1,Technology,2025-01-12,2025-03-13,1823,9.4,Algorithmic Solutions -AI07228,AI Research Scientist,133583,AUD,180337,EX,PT,Australia,S,Australia,100,"Hadoop, SQL, Spark",Bachelor,11,Retail,2024-10-04,2024-10-18,1642,6.8,Digital Transformation LLC -AI07229,Autonomous Systems Engineer,75968,CAD,94960,MI,FL,Canada,M,Canada,100,"Mathematics, Docker, Python, Hadoop",Master,4,Manufacturing,2024-07-11,2024-08-17,1020,8,Quantum Computing Inc -AI07230,AI Product Manager,142238,AUD,192021,SE,FT,Australia,L,Australia,50,"GCP, R, Mathematics",PhD,7,Government,2024-07-03,2024-08-16,978,6.3,AI Innovations -AI07231,Machine Learning Engineer,211317,USD,211317,EX,FL,Israel,L,Israel,0,"MLOps, Mathematics, SQL, AWS",Master,13,Consulting,2025-01-18,2025-03-18,990,6.7,Autonomous Tech -AI07232,Data Engineer,260422,EUR,221359,EX,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Data Visualization, Spark",PhD,15,Education,2024-06-17,2024-08-13,2056,9.5,Machine Intelligence Group -AI07233,Autonomous Systems Engineer,203781,CAD,254726,EX,FL,Canada,S,Canada,0,"Linux, Java, Data Visualization, MLOps, Hadoop",PhD,11,Healthcare,2024-11-19,2024-12-19,1698,10,Neural Networks Co -AI07234,Machine Learning Engineer,53311,USD,53311,SE,PT,India,M,India,0,"Spark, SQL, Kubernetes, Python, Computer Vision",Associate,8,Transportation,2025-04-19,2025-06-15,727,5.4,Cloud AI Solutions -AI07235,AI Product Manager,111471,JPY,12261810,SE,FL,Japan,S,Japan,100,"SQL, Java, R, Scala",Bachelor,6,Healthcare,2024-05-15,2024-07-21,597,7.5,Predictive Systems -AI07236,Robotics Engineer,195168,EUR,165893,EX,PT,Germany,S,Spain,50,"Python, Docker, AWS",Master,11,Government,2024-12-29,2025-02-03,1452,8.2,Advanced Robotics -AI07237,AI Product Manager,48863,USD,48863,EN,FL,Finland,S,Finland,50,"Python, SQL, Hadoop",Bachelor,0,Transportation,2025-03-31,2025-05-22,870,7.7,Advanced Robotics -AI07238,AI Consultant,272513,CHF,245262,EX,CT,Switzerland,L,Switzerland,50,"PyTorch, AWS, NLP, SQL",Master,16,Real Estate,2024-10-19,2024-12-16,2456,9.1,AI Innovations -AI07239,ML Ops Engineer,180571,USD,180571,EX,CT,Sweden,L,Turkey,0,"GCP, TensorFlow, NLP, SQL, Tableau",Bachelor,19,Gaming,2025-03-18,2025-05-26,642,7.3,Algorithmic Solutions -AI07240,Data Scientist,177014,USD,177014,SE,FT,Denmark,L,Denmark,50,"Data Visualization, R, Deep Learning",Master,7,Automotive,2024-12-17,2024-12-31,2171,6.1,Predictive Systems -AI07241,Research Scientist,105629,USD,105629,EN,FL,United States,L,Finland,50,"SQL, NLP, Git, PyTorch",Bachelor,0,Real Estate,2024-10-28,2024-11-19,1188,8.6,Cognitive Computing -AI07242,NLP Engineer,201624,USD,201624,EX,FL,Ireland,S,Latvia,50,"Scala, Spark, Kubernetes, TensorFlow, Statistics",Bachelor,11,Technology,2024-10-09,2024-12-13,1376,7.5,Predictive Systems -AI07243,NLP Engineer,131783,EUR,112016,SE,CT,France,L,South Africa,100,"Java, GCP, Tableau, Scala",Associate,5,Gaming,2025-04-30,2025-07-04,548,8.6,DeepTech Ventures -AI07244,NLP Engineer,75289,USD,75289,EN,FL,Sweden,L,Sweden,100,"Linux, PyTorch, R, Python, Mathematics",Bachelor,0,Energy,2024-03-02,2024-04-28,1011,8.3,Quantum Computing Inc -AI07245,Data Scientist,336868,USD,336868,EX,PT,Norway,L,Norway,100,"Spark, NLP, Tableau, Docker",Master,14,Media,2024-06-21,2024-08-03,902,8.1,Digital Transformation LLC -AI07246,AI Research Scientist,163534,EUR,139004,SE,FL,Germany,L,Germany,0,"GCP, Hadoop, Docker, Deep Learning, SQL",Master,7,Consulting,2024-07-13,2024-08-06,1179,6.7,Machine Intelligence Group -AI07247,Data Engineer,116592,USD,116592,SE,FT,Finland,S,China,100,"Git, Spark, NLP, Kubernetes",PhD,9,Healthcare,2025-03-10,2025-04-17,2130,8.6,Cloud AI Solutions -AI07248,AI Consultant,124845,JPY,13732950,SE,FL,Japan,L,New Zealand,0,"Kubernetes, Data Visualization, Python, AWS, MLOps",Bachelor,9,Technology,2024-10-16,2024-12-10,1028,7.3,Machine Intelligence Group -AI07249,Robotics Engineer,130238,USD,130238,EX,PT,Sweden,S,Sweden,100,"SQL, Kubernetes, PyTorch, Git",Master,10,Consulting,2024-07-01,2024-07-16,1080,8.9,Digital Transformation LLC -AI07250,Data Engineer,190431,CAD,238039,EX,PT,Canada,M,Canada,50,"Spark, Scala, SQL",Master,19,Healthcare,2024-10-22,2024-11-19,2125,7.1,Quantum Computing Inc -AI07251,Research Scientist,21657,USD,21657,EN,CT,India,L,India,50,"TensorFlow, Java, PyTorch, GCP",Bachelor,0,Real Estate,2024-01-08,2024-02-04,790,5.1,DataVision Ltd -AI07252,Data Engineer,120635,USD,120635,MI,PT,Ireland,L,Ireland,100,"Linux, R, SQL, Deep Learning",PhD,4,Media,2025-02-26,2025-03-18,1761,7,Machine Intelligence Group -AI07253,AI Research Scientist,86185,USD,86185,MI,FL,Israel,L,Israel,50,"Statistics, Computer Vision, Data Visualization, Scala, MLOps",Bachelor,4,Government,2024-09-06,2024-11-18,552,5.6,Neural Networks Co -AI07254,AI Software Engineer,165333,CAD,206666,SE,FL,Canada,L,Australia,0,"Linux, Spark, TensorFlow",Associate,9,Energy,2024-09-01,2024-10-26,2165,6.6,Autonomous Tech -AI07255,Head of AI,160948,USD,160948,EX,FL,Finland,L,Finland,50,"Deep Learning, Kubernetes, Java, Hadoop",Master,15,Finance,2024-12-08,2025-01-19,726,6.3,DeepTech Ventures -AI07256,Deep Learning Engineer,74480,CHF,67032,EN,CT,Switzerland,M,Switzerland,50,"Java, Linux, TensorFlow, AWS, NLP",PhD,1,Energy,2024-04-23,2024-06-30,1898,7.9,Predictive Systems -AI07257,Data Scientist,64243,CAD,80304,EN,PT,Canada,L,Canada,0,"Computer Vision, Python, TensorFlow",Bachelor,0,Finance,2024-10-26,2024-12-21,1629,5.5,DeepTech Ventures -AI07258,Data Engineer,86729,USD,86729,MI,CT,Sweden,S,Switzerland,100,"Computer Vision, Mathematics, Kubernetes, Tableau",Bachelor,4,Manufacturing,2024-08-16,2024-10-01,1998,7.1,Algorithmic Solutions -AI07259,AI Specialist,72797,JPY,8007670,EN,PT,Japan,M,Japan,50,"SQL, GCP, Tableau, TensorFlow, Data Visualization",Master,1,Consulting,2024-09-28,2024-11-02,1471,8,DeepTech Ventures -AI07260,Research Scientist,124502,SGD,161853,SE,PT,Singapore,S,Singapore,100,"Deep Learning, Scala, Computer Vision, SQL, PyTorch",Associate,6,Education,2024-01-02,2024-01-28,619,9.5,Advanced Robotics -AI07261,AI Software Engineer,271059,AUD,365930,EX,CT,Australia,L,Philippines,100,"Git, Azure, Python, TensorFlow",Bachelor,12,Finance,2025-01-19,2025-02-15,1510,5.3,Cognitive Computing -AI07262,AI Product Manager,108790,EUR,92472,MI,CT,Netherlands,M,United States,0,"Kubernetes, Python, Tableau",PhD,3,Media,2024-05-04,2024-05-23,1626,9.1,Predictive Systems -AI07263,AI Product Manager,259708,AUD,350606,EX,PT,Australia,L,Australia,0,"Spark, Kubernetes, Statistics",PhD,17,Healthcare,2025-02-20,2025-03-17,2391,6.6,AI Innovations -AI07264,ML Ops Engineer,83606,USD,83606,EN,CT,United States,S,Germany,100,"TensorFlow, Tableau, Python, Computer Vision",Master,1,Consulting,2025-03-22,2025-05-14,1408,9.1,Cloud AI Solutions -AI07265,Robotics Engineer,160120,AUD,216162,SE,FT,Australia,L,Australia,50,"R, GCP, Deep Learning",Master,5,Manufacturing,2024-06-07,2024-07-16,1221,8.2,Cloud AI Solutions -AI07266,Robotics Engineer,97279,USD,97279,MI,PT,Israel,M,Israel,0,"Kubernetes, Python, Deep Learning, Data Visualization, Java",Master,2,Gaming,2024-05-10,2024-06-19,1144,6.4,Quantum Computing Inc -AI07267,AI Research Scientist,120260,USD,120260,SE,PT,Sweden,S,Sweden,50,"Computer Vision, MLOps, Deep Learning, Spark, PyTorch",Associate,9,Consulting,2024-03-07,2024-04-21,1969,5.4,DataVision Ltd -AI07268,Research Scientist,70585,AUD,95290,EN,FT,Australia,L,Estonia,50,"Mathematics, Hadoop, GCP, PyTorch",Associate,1,Retail,2024-08-18,2024-10-20,1909,6,TechCorp Inc -AI07269,Machine Learning Engineer,88166,AUD,119024,MI,CT,Australia,S,Australia,100,"Python, TensorFlow, Linux",Associate,2,Finance,2024-03-22,2024-05-21,1056,6.5,Smart Analytics -AI07270,Machine Learning Researcher,112078,USD,112078,MI,PT,United States,S,Japan,50,"Hadoop, GCP, Kubernetes, Tableau",Master,3,Technology,2025-03-16,2025-04-25,2346,5.1,Cognitive Computing -AI07271,AI Product Manager,33267,USD,33267,MI,CT,China,S,China,50,"Spark, AWS, Deep Learning",Master,2,Media,2024-06-08,2024-07-27,773,6.7,AI Innovations -AI07272,Machine Learning Researcher,118202,USD,118202,MI,PT,Norway,M,Norway,100,"Docker, Deep Learning, PyTorch",Bachelor,4,Media,2024-02-23,2024-04-29,1741,7,Future Systems -AI07273,Machine Learning Researcher,83199,USD,83199,MI,FT,Ireland,S,Ireland,0,"Kubernetes, Docker, Python, Computer Vision",PhD,4,Automotive,2025-03-20,2025-04-17,1720,7.2,Digital Transformation LLC -AI07274,Deep Learning Engineer,64159,CAD,80199,EN,PT,Canada,M,Canada,0,"Python, Kubernetes, AWS",Bachelor,1,Education,2024-03-28,2024-05-04,1069,5.8,Autonomous Tech -AI07275,ML Ops Engineer,67930,USD,67930,MI,FL,South Korea,S,South Korea,100,"Statistics, TensorFlow, R, Deep Learning, Tableau",Master,4,Real Estate,2024-06-18,2024-08-19,618,7.1,Future Systems -AI07276,Principal Data Scientist,118438,GBP,88829,SE,FT,United Kingdom,M,United Kingdom,50,"Spark, Kubernetes, Mathematics, Tableau",Master,9,Automotive,2024-02-10,2024-04-03,1557,6.5,Cognitive Computing -AI07277,AI Product Manager,49451,USD,49451,SE,PT,India,L,India,0,"SQL, Python, PyTorch",Master,5,Media,2024-04-25,2024-05-28,1974,7,Machine Intelligence Group -AI07278,Head of AI,199445,USD,199445,SE,PT,Norway,L,Norway,0,"NLP, Azure, Spark, Scala, Tableau",PhD,5,Healthcare,2024-12-29,2025-01-14,2056,7,Smart Analytics -AI07279,AI Software Engineer,151206,USD,151206,EX,CT,Sweden,S,Sweden,100,"NLP, R, Kubernetes, Mathematics",Master,14,Energy,2024-12-23,2025-02-15,1491,8.2,Predictive Systems -AI07280,AI Product Manager,129233,JPY,14215630,SE,PT,Japan,S,Japan,50,"SQL, Tableau, Spark",Master,6,Telecommunications,2024-11-17,2024-12-30,1828,6,Cloud AI Solutions -AI07281,Data Engineer,126854,EUR,107826,MI,PT,Germany,L,Denmark,50,"Linux, Kubernetes, Docker, Hadoop",Bachelor,4,Retail,2024-01-23,2024-04-02,1955,6.9,Predictive Systems -AI07282,NLP Engineer,85718,CAD,107148,MI,PT,Canada,M,Canada,50,"GCP, Linux, Spark, PyTorch, R",Bachelor,3,Automotive,2025-01-23,2025-03-28,2152,5.8,Neural Networks Co -AI07283,ML Ops Engineer,79085,USD,79085,MI,FT,South Korea,L,Vietnam,100,"Data Visualization, Mathematics, Python, Git",PhD,4,Consulting,2025-02-11,2025-04-01,2363,5.5,Future Systems -AI07284,Robotics Engineer,95382,USD,95382,MI,FL,Sweden,M,Sweden,100,"Git, TensorFlow, Tableau, Docker, PyTorch",Bachelor,2,Education,2025-03-17,2025-04-21,1788,8.1,TechCorp Inc -AI07285,AI Consultant,114244,GBP,85683,MI,CT,United Kingdom,L,United Kingdom,100,"SQL, Scala, Deep Learning, Tableau",Bachelor,3,Manufacturing,2024-10-28,2024-12-12,1445,6.4,DeepTech Ventures -AI07286,Principal Data Scientist,86971,SGD,113062,EN,FT,Singapore,L,Singapore,0,"Docker, Git, MLOps",Associate,1,Gaming,2024-08-10,2024-09-24,2324,5,AI Innovations -AI07287,AI Product Manager,113959,SGD,148147,SE,PT,Singapore,M,Czech Republic,50,"Python, Mathematics, SQL",Bachelor,7,Consulting,2024-08-13,2024-10-08,1989,8.8,Algorithmic Solutions -AI07288,ML Ops Engineer,138785,USD,138785,SE,FL,South Korea,L,South Korea,0,"Deep Learning, Computer Vision, PyTorch, Java, MLOps",Master,9,Retail,2024-10-20,2024-12-07,1829,7.1,TechCorp Inc -AI07289,Robotics Engineer,122279,GBP,91709,MI,FT,United Kingdom,L,Ukraine,100,"Hadoop, AWS, MLOps, Scala",Associate,4,Retail,2024-06-13,2024-08-01,1295,8.6,DataVision Ltd -AI07290,NLP Engineer,46233,EUR,39298,EN,PT,Austria,S,Austria,100,"Computer Vision, AWS, Git, Tableau",Bachelor,0,Education,2024-07-16,2024-08-11,1131,7.3,Smart Analytics -AI07291,Machine Learning Researcher,298282,USD,298282,EX,FT,Denmark,L,Denmark,50,"Kubernetes, SQL, GCP, PyTorch, Mathematics",Associate,17,Telecommunications,2024-01-30,2024-03-27,1484,5.5,Machine Intelligence Group -AI07292,AI Architect,20587,USD,20587,EN,FL,India,M,Estonia,0,"Kubernetes, R, Computer Vision, Deep Learning",Associate,1,Energy,2024-12-05,2024-12-22,773,8.9,Algorithmic Solutions -AI07293,Data Scientist,85412,USD,85412,MI,PT,Ireland,L,Indonesia,100,"Deep Learning, Statistics, NLP, Kubernetes",Master,2,Government,2025-03-28,2025-06-06,2482,9.8,TechCorp Inc -AI07294,Deep Learning Engineer,164904,EUR,140168,SE,CT,Netherlands,L,Netherlands,100,"SQL, PyTorch, AWS, Scala, Java",Bachelor,9,Healthcare,2024-06-17,2024-08-03,2150,7.8,DataVision Ltd -AI07295,Principal Data Scientist,153719,EUR,130661,EX,FT,Austria,M,Austria,50,"SQL, AWS, Deep Learning, NLP, PyTorch",Associate,10,Healthcare,2024-10-21,2024-12-01,757,9,Predictive Systems -AI07296,Data Analyst,128775,EUR,109459,MI,CT,Netherlands,L,China,0,"Hadoop, PyTorch, Data Visualization, NLP",Master,3,Education,2025-01-07,2025-03-08,2131,7.3,Advanced Robotics -AI07297,AI Architect,74122,EUR,63004,MI,FT,Netherlands,S,Netherlands,50,"Azure, Kubernetes, GCP",Bachelor,3,Technology,2024-01-30,2024-02-28,1960,5.7,Cloud AI Solutions -AI07298,NLP Engineer,153979,USD,153979,EX,CT,Sweden,M,Sweden,50,"Python, Docker, MLOps",PhD,14,Automotive,2025-04-30,2025-07-04,698,9.7,AI Innovations -AI07299,Data Scientist,130397,CHF,117357,SE,CT,Switzerland,S,Switzerland,50,"Statistics, Hadoop, Azure, Java",PhD,9,Manufacturing,2025-02-27,2025-03-25,897,5.8,TechCorp Inc -AI07300,Autonomous Systems Engineer,79354,GBP,59516,EN,FT,United Kingdom,M,Ireland,0,"TensorFlow, Statistics, Docker",PhD,1,Media,2025-02-22,2025-03-12,1379,7.5,Quantum Computing Inc -AI07301,Data Scientist,120736,USD,120736,MI,FL,Ireland,L,Israel,0,"Azure, Linux, NLP",Associate,3,Energy,2024-11-08,2025-01-02,2417,6,Autonomous Tech -AI07302,Research Scientist,92591,USD,92591,SE,FT,Finland,S,Portugal,0,"Deep Learning, Python, GCP",Bachelor,6,Real Estate,2024-06-13,2024-07-23,1341,6.6,Smart Analytics -AI07303,Robotics Engineer,167422,USD,167422,SE,FL,Denmark,S,Denmark,100,"Python, Mathematics, Tableau, Deep Learning, SQL",Master,7,Gaming,2024-11-11,2024-12-18,1682,5.5,Cloud AI Solutions -AI07304,Research Scientist,43875,USD,43875,SE,CT,China,S,China,0,"Statistics, Kubernetes, SQL",Master,6,Healthcare,2024-11-25,2025-01-11,2385,9.1,Algorithmic Solutions -AI07305,Data Engineer,154370,EUR,131215,SE,PT,Austria,L,Austria,0,"Python, Spark, Statistics, Deep Learning, Java",Master,7,Education,2024-10-31,2024-12-07,1667,6,Future Systems -AI07306,Computer Vision Engineer,89756,CAD,112195,MI,PT,Canada,S,Canada,0,"Data Visualization, SQL, Azure, Kubernetes, Mathematics",PhD,2,Energy,2024-08-10,2024-09-19,2415,7.2,Advanced Robotics -AI07307,AI Specialist,58025,EUR,49321,EN,CT,Germany,S,Luxembourg,100,"R, SQL, NLP, Hadoop",Bachelor,1,Government,2024-10-08,2024-12-10,1563,7.1,DataVision Ltd -AI07308,Computer Vision Engineer,52365,EUR,44510,EN,PT,Netherlands,S,Netherlands,0,"Tableau, Linux, SQL, PyTorch",PhD,1,Manufacturing,2025-04-17,2025-05-03,1878,6.7,Machine Intelligence Group -AI07309,Research Scientist,252611,EUR,214719,EX,FL,Netherlands,L,Netherlands,100,"AWS, Data Visualization, MLOps, Spark",Associate,18,Media,2024-05-22,2024-06-28,787,9.3,DeepTech Ventures -AI07310,AI Consultant,292045,JPY,32124950,EX,FT,Japan,L,Japan,50,"Python, Scala, Hadoop, Linux, GCP",Bachelor,15,Telecommunications,2024-12-17,2025-02-16,1701,5.5,Autonomous Tech -AI07311,Research Scientist,180417,SGD,234542,EX,FL,Singapore,S,Singapore,100,"TensorFlow, Java, Tableau",Master,15,Transportation,2025-04-08,2025-04-23,1308,8.1,DataVision Ltd -AI07312,Deep Learning Engineer,65703,USD,65703,EN,FT,Ireland,S,United States,100,"Hadoop, Computer Vision, SQL, R, PyTorch",PhD,1,Gaming,2024-08-24,2024-09-07,1472,9.4,DataVision Ltd -AI07313,ML Ops Engineer,33627,USD,33627,MI,FT,India,L,India,0,"Hadoop, AWS, Kubernetes, NLP, Azure",Master,3,Automotive,2024-12-06,2025-01-03,1675,9.2,Neural Networks Co -AI07314,NLP Engineer,117069,CHF,105362,MI,PT,Switzerland,M,Nigeria,50,"PyTorch, GCP, Deep Learning, Docker, Tableau",Master,3,Automotive,2024-02-03,2024-03-01,1738,8.6,Predictive Systems -AI07315,Deep Learning Engineer,109443,EUR,93027,SE,CT,France,S,France,50,"Kubernetes, Python, Scala",PhD,8,Healthcare,2025-01-11,2025-03-04,2280,8.7,Digital Transformation LLC -AI07316,AI Software Engineer,114421,EUR,97258,MI,FL,Austria,L,Luxembourg,0,"Python, Tableau, Linux, Hadoop",Master,3,Manufacturing,2024-05-10,2024-07-14,1941,5.7,Neural Networks Co -AI07317,Head of AI,297806,USD,297806,EX,FT,United States,M,China,0,"Data Visualization, PyTorch, Tableau, GCP",Bachelor,15,Media,2024-11-07,2024-12-13,1644,9.3,DataVision Ltd -AI07318,Autonomous Systems Engineer,96103,JPY,10571330,MI,FL,Japan,M,Japan,0,"Java, Scala, Hadoop",Master,2,Technology,2024-08-30,2024-10-13,993,6.2,Advanced Robotics -AI07319,AI Consultant,104183,EUR,88556,MI,PT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, Scala",PhD,4,Automotive,2024-05-30,2024-07-27,1802,8.3,Quantum Computing Inc -AI07320,Research Scientist,203843,CHF,183459,SE,FT,Switzerland,L,Switzerland,100,"Docker, GCP, Hadoop, Computer Vision",Master,6,Transportation,2025-03-31,2025-05-17,1710,8.4,TechCorp Inc -AI07321,AI Specialist,159445,CHF,143501,SE,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Java, GCP",Master,9,Consulting,2025-04-17,2025-06-21,823,7.8,DeepTech Ventures -AI07322,Computer Vision Engineer,98252,USD,98252,SE,CT,Finland,S,Finland,50,"Azure, Tableau, AWS, Linux",Bachelor,7,Gaming,2024-12-14,2025-01-24,1131,6.2,Advanced Robotics -AI07323,Data Engineer,140598,USD,140598,SE,FL,Sweden,L,Switzerland,50,"Python, PyTorch, Docker",PhD,5,Energy,2024-02-08,2024-04-07,1530,6.6,Quantum Computing Inc -AI07324,Data Engineer,122530,USD,122530,SE,FT,Ireland,S,Ireland,0,"SQL, Tableau, Deep Learning",Master,5,Consulting,2025-03-06,2025-03-30,1123,8.1,Advanced Robotics -AI07325,AI Specialist,79216,USD,79216,EN,FT,United States,S,United States,100,"Kubernetes, Java, MLOps",Associate,0,Government,2024-11-24,2025-01-16,1296,5.6,Autonomous Tech -AI07326,AI Software Engineer,208065,USD,208065,EX,FT,South Korea,M,South Korea,100,"Azure, TensorFlow, R, Tableau",Master,14,Real Estate,2025-02-06,2025-04-03,1320,7.5,Digital Transformation LLC -AI07327,Data Engineer,212005,EUR,180204,EX,PT,Germany,M,Germany,0,"GCP, R, Python",PhD,10,Retail,2024-06-10,2024-07-16,1605,5.2,TechCorp Inc -AI07328,Computer Vision Engineer,142069,EUR,120759,SE,PT,Netherlands,L,Netherlands,0,"Data Visualization, Kubernetes, Scala, Python, Mathematics",Bachelor,7,Consulting,2024-11-23,2024-12-18,2476,5.3,Algorithmic Solutions -AI07329,NLP Engineer,189432,USD,189432,EX,PT,Israel,S,Nigeria,50,"GCP, R, SQL, TensorFlow, Java",Master,17,Manufacturing,2024-06-21,2024-08-15,1030,6.3,AI Innovations -AI07330,AI Architect,148090,USD,148090,EX,PT,United States,S,United States,100,"Mathematics, MLOps, Data Visualization, TensorFlow",Associate,13,Media,2025-01-26,2025-04-03,1491,8.1,Cognitive Computing -AI07331,Autonomous Systems Engineer,90214,AUD,121789,MI,FL,Australia,M,Singapore,100,"R, AWS, MLOps, Git",Bachelor,2,Government,2025-02-01,2025-03-13,1301,5.2,Algorithmic Solutions -AI07332,Autonomous Systems Engineer,179077,CAD,223846,EX,FT,Canada,M,Austria,100,"SQL, Data Visualization, MLOps, Mathematics, Java",Bachelor,11,Telecommunications,2024-01-21,2024-02-18,1876,5.3,DeepTech Ventures -AI07333,NLP Engineer,49419,AUD,66716,EN,PT,Australia,S,Australia,50,"AWS, Linux, Kubernetes, Git",Associate,1,Transportation,2025-03-31,2025-05-20,1252,7.8,Algorithmic Solutions -AI07334,Robotics Engineer,121147,USD,121147,SE,FL,Sweden,S,Sweden,50,"SQL, TensorFlow, Java, Scala",Associate,8,Retail,2025-02-22,2025-03-28,1565,9.6,Algorithmic Solutions -AI07335,AI Architect,246001,USD,246001,EX,FL,Ireland,M,Ireland,100,"Mathematics, GCP, SQL",Associate,17,Technology,2025-01-31,2025-03-07,955,6.3,Neural Networks Co -AI07336,Principal Data Scientist,52336,USD,52336,EN,PT,Israel,M,Israel,0,"Data Visualization, Statistics, NLP, Python, Computer Vision",Master,1,Government,2024-12-20,2025-02-01,1645,8.1,Machine Intelligence Group -AI07337,ML Ops Engineer,43262,EUR,36773,EN,PT,France,S,France,100,"Java, Git, Kubernetes, Python",Master,0,Transportation,2024-11-14,2025-01-11,639,5,Cloud AI Solutions -AI07338,Research Scientist,107059,EUR,91000,MI,PT,France,L,France,50,"Python, Java, NLP, AWS",Bachelor,4,Real Estate,2024-05-04,2024-05-18,654,5.4,Machine Intelligence Group -AI07339,Autonomous Systems Engineer,77881,EUR,66199,MI,CT,France,S,Sweden,0,"GCP, Java, Python, Deep Learning",Bachelor,3,Consulting,2024-08-15,2024-09-21,1815,5.6,Cognitive Computing -AI07340,Head of AI,77351,CAD,96689,MI,PT,Canada,M,Italy,0,"PyTorch, TensorFlow, MLOps",Associate,2,Finance,2024-03-15,2024-04-25,1356,9.2,Cloud AI Solutions -AI07341,Principal Data Scientist,148317,USD,148317,EX,FT,United States,S,China,0,"MLOps, Tableau, Python, Docker, Linux",Bachelor,10,Government,2024-01-12,2024-02-04,1930,9.4,Neural Networks Co -AI07342,AI Research Scientist,185184,CHF,166666,SE,FL,Switzerland,M,Switzerland,0,"MLOps, Mathematics, Python, TensorFlow",PhD,9,Healthcare,2024-11-01,2024-12-22,1638,6.6,Quantum Computing Inc -AI07343,AI Consultant,215064,EUR,182804,EX,CT,Austria,L,Austria,50,"PyTorch, SQL, Spark, Computer Vision, Mathematics",PhD,11,Telecommunications,2024-07-12,2024-07-26,581,8.7,Algorithmic Solutions -AI07344,Deep Learning Engineer,38054,USD,38054,EN,FL,South Korea,S,South Korea,100,"Computer Vision, Kubernetes, Mathematics",Associate,0,Government,2024-12-07,2024-12-23,1966,7.2,Predictive Systems -AI07345,Data Engineer,297668,SGD,386968,EX,FT,Singapore,L,Ireland,50,"Kubernetes, SQL, Docker",Master,16,Healthcare,2025-04-16,2025-05-04,1714,7.5,Digital Transformation LLC -AI07346,Machine Learning Engineer,72953,SGD,94839,EN,FT,Singapore,S,Russia,0,"Deep Learning, Data Visualization, Hadoop",Bachelor,1,Consulting,2024-08-17,2024-10-20,706,8.1,AI Innovations -AI07347,ML Ops Engineer,145761,EUR,123897,SE,FT,Netherlands,L,Netherlands,50,"Linux, Hadoop, Mathematics",PhD,8,Healthcare,2024-03-16,2024-04-01,756,5.4,DeepTech Ventures -AI07348,Computer Vision Engineer,203224,USD,203224,SE,PT,Norway,L,Norway,0,"AWS, Azure, Hadoop, Spark",Associate,6,Energy,2024-07-26,2024-08-27,1287,7.6,DataVision Ltd -AI07349,Computer Vision Engineer,242702,EUR,206297,EX,CT,Netherlands,L,Netherlands,0,"SQL, AWS, Computer Vision, Kubernetes, Spark",Associate,14,Finance,2024-05-31,2024-08-10,882,8.1,Smart Analytics -AI07350,Machine Learning Engineer,46733,CAD,58416,EN,FT,Canada,S,Canada,0,"GCP, Linux, Hadoop",Master,0,Automotive,2024-09-16,2024-11-07,698,9.2,Digital Transformation LLC -AI07351,Machine Learning Researcher,85044,USD,85044,MI,CT,Norway,S,Norway,0,"Computer Vision, Linux, SQL, TensorFlow",Master,2,Transportation,2024-09-14,2024-09-28,933,5.4,Machine Intelligence Group -AI07352,AI Specialist,90679,EUR,77077,MI,PT,France,L,Sweden,0,"PyTorch, Deep Learning, Azure, Computer Vision",Associate,4,Technology,2024-09-25,2024-11-05,2118,6.7,Quantum Computing Inc -AI07353,ML Ops Engineer,81449,EUR,69232,MI,CT,Netherlands,M,Netherlands,0,"Linux, Java, Computer Vision",Associate,2,Transportation,2024-09-17,2024-11-27,1721,8.7,Autonomous Tech -AI07354,ML Ops Engineer,79173,EUR,67297,EN,CT,France,L,France,50,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Energy,2025-01-10,2025-03-19,1994,7.1,Quantum Computing Inc -AI07355,Machine Learning Researcher,266789,USD,266789,EX,FL,Denmark,M,Denmark,100,"Kubernetes, Linux, Tableau, TensorFlow",PhD,16,Government,2024-08-28,2024-10-23,693,9.9,Machine Intelligence Group -AI07356,Machine Learning Researcher,170028,CHF,153025,SE,FL,Switzerland,S,Switzerland,50,"Azure, Deep Learning, Tableau, R",Associate,8,Gaming,2024-10-10,2024-12-10,1166,7.2,Predictive Systems -AI07357,AI Software Engineer,26042,USD,26042,EN,PT,India,L,Vietnam,50,"Kubernetes, Git, Mathematics, Python",PhD,0,Transportation,2025-01-01,2025-02-25,2059,5.7,Cognitive Computing -AI07358,NLP Engineer,192917,EUR,163979,EX,PT,France,M,France,50,"Kubernetes, Linux, GCP, Java, R",Bachelor,15,Consulting,2025-04-16,2025-05-10,1803,9.1,DataVision Ltd -AI07359,Head of AI,106638,USD,106638,MI,CT,Finland,L,Czech Republic,100,"Kubernetes, MLOps, Deep Learning, Python",Bachelor,2,Finance,2024-07-26,2024-08-09,1911,9.4,DataVision Ltd -AI07360,Machine Learning Researcher,76474,USD,76474,EX,FL,India,M,India,50,"Git, Statistics, Computer Vision, Deep Learning, R",Bachelor,10,Energy,2024-01-14,2024-02-27,585,7.9,Quantum Computing Inc -AI07361,AI Architect,177950,USD,177950,SE,FT,United States,M,United States,50,"TensorFlow, R, AWS, Mathematics, Computer Vision",PhD,5,Media,2024-11-04,2024-12-09,2298,6.1,Advanced Robotics -AI07362,Machine Learning Researcher,104483,CHF,94035,MI,FL,Switzerland,S,Switzerland,50,"MLOps, Kubernetes, Tableau, Hadoop, Mathematics",Associate,2,Healthcare,2024-10-19,2024-12-13,2315,6.7,Smart Analytics -AI07363,ML Ops Engineer,64384,JPY,7082240,EN,FL,Japan,L,Turkey,0,"Python, TensorFlow, MLOps, GCP",Associate,1,Education,2024-12-06,2024-12-20,1208,6.2,Cognitive Computing -AI07364,AI Consultant,50482,SGD,65627,EN,PT,Singapore,S,Singapore,100,"PyTorch, Hadoop, Deep Learning",Associate,1,Real Estate,2024-09-22,2024-11-01,2204,7.6,Algorithmic Solutions -AI07365,Data Scientist,151120,EUR,128452,SE,FL,Germany,L,Germany,50,"Linux, R, SQL, Spark, TensorFlow",Bachelor,5,Healthcare,2024-08-11,2024-09-26,1422,8.1,Autonomous Tech -AI07366,AI Research Scientist,145148,USD,145148,MI,FL,Norway,L,Norway,50,"TensorFlow, Spark, Computer Vision, Linux",Associate,3,Media,2025-03-06,2025-04-15,2298,8,Algorithmic Solutions -AI07367,Machine Learning Researcher,46232,CAD,57790,EN,PT,Canada,S,Canada,100,"Data Visualization, Azure, PyTorch",Master,0,Telecommunications,2024-07-28,2024-09-01,1275,8.8,Quantum Computing Inc -AI07368,Data Engineer,192522,CAD,240653,EX,FT,Canada,L,Canada,100,"Kubernetes, GCP, AWS, Git, NLP",Master,10,Finance,2024-10-19,2024-12-31,2175,8.2,Algorithmic Solutions -AI07369,Machine Learning Researcher,227433,USD,227433,EX,FT,Sweden,L,Sweden,0,"Python, R, SQL",Associate,18,Government,2024-10-07,2024-11-11,543,7.2,DeepTech Ventures -AI07370,Data Analyst,104134,USD,104134,SE,PT,Finland,M,Finland,0,"AWS, Git, Java, Azure, Python",Associate,5,Energy,2024-11-17,2024-12-20,1295,7.5,Cloud AI Solutions -AI07371,Computer Vision Engineer,193260,USD,193260,SE,PT,Norway,L,Norway,0,"Computer Vision, Data Visualization, Python",Master,7,Finance,2024-06-01,2024-08-04,1662,8.4,Digital Transformation LLC -AI07372,AI Research Scientist,215088,EUR,182825,EX,CT,Germany,M,Germany,50,"Scala, NLP, R, GCP, Python",Associate,15,Gaming,2024-01-20,2024-03-26,1288,6.2,Machine Intelligence Group -AI07373,Autonomous Systems Engineer,74692,USD,74692,MI,FT,Sweden,M,Sweden,0,"SQL, Linux, Statistics",Associate,4,Technology,2024-05-28,2024-08-05,1682,7.3,DataVision Ltd -AI07374,Deep Learning Engineer,89378,EUR,75971,MI,FT,France,S,France,50,"Linux, GCP, Computer Vision",Bachelor,2,Technology,2024-10-01,2024-12-05,2365,5,Advanced Robotics -AI07375,AI Consultant,222964,USD,222964,EX,FL,Finland,L,Colombia,0,"R, Spark, Linux, Java",Bachelor,17,Finance,2024-10-15,2024-12-04,1826,6.1,Machine Intelligence Group -AI07376,Robotics Engineer,219494,USD,219494,EX,CT,Ireland,L,Hungary,50,"AWS, Azure, SQL, Statistics, Git",Associate,17,Transportation,2024-07-05,2024-08-21,996,5.5,Neural Networks Co -AI07377,AI Research Scientist,132643,EUR,112747,SE,CT,Netherlands,M,Netherlands,50,"TensorFlow, NLP, Linux, GCP, Data Visualization",Associate,9,Telecommunications,2024-07-08,2024-09-03,920,8.3,AI Innovations -AI07378,Data Engineer,54621,USD,54621,EX,PT,India,M,Brazil,0,"Hadoop, Python, R, SQL",Associate,18,Real Estate,2024-07-08,2024-08-09,1912,5.8,DataVision Ltd -AI07379,Deep Learning Engineer,149274,GBP,111956,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, Java, PyTorch, Spark, Docker",PhD,5,Energy,2024-11-02,2025-01-09,834,5.2,Cloud AI Solutions -AI07380,AI Software Engineer,79871,SGD,103832,EN,FL,Singapore,L,Singapore,50,"MLOps, SQL, Azure, Mathematics",PhD,0,Retail,2025-04-30,2025-05-18,2489,5.3,Algorithmic Solutions -AI07381,Data Engineer,240902,USD,240902,EX,PT,Sweden,M,Philippines,100,"GCP, Data Visualization, Python",PhD,12,Automotive,2025-01-05,2025-01-23,1762,7.9,DeepTech Ventures -AI07382,Principal Data Scientist,88819,CAD,111024,MI,FL,Canada,M,Canada,100,"Kubernetes, PyTorch, Git",PhD,3,Gaming,2025-01-26,2025-03-13,1594,8.5,Smart Analytics -AI07383,AI Software Engineer,245168,JPY,26968480,EX,FT,Japan,L,Norway,100,"SQL, AWS, Linux, Spark",PhD,11,Telecommunications,2024-10-04,2024-11-17,1753,7,Machine Intelligence Group -AI07384,Research Scientist,226851,USD,226851,EX,FL,Finland,L,Finland,50,"Azure, Linux, Data Visualization, Git, Kubernetes",Associate,17,Consulting,2025-01-17,2025-03-15,1652,9.6,DataVision Ltd -AI07385,AI Architect,65693,USD,65693,MI,PT,South Korea,M,Russia,50,"Linux, Hadoop, Computer Vision",Bachelor,2,Energy,2024-02-22,2024-03-10,910,8.2,Cloud AI Solutions -AI07386,Computer Vision Engineer,173491,EUR,147467,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, Mathematics, Statistics",PhD,9,Gaming,2025-04-01,2025-06-09,515,8.3,AI Innovations -AI07387,Head of AI,78460,CAD,98075,MI,PT,Canada,M,Argentina,50,"Scala, Hadoop, Deep Learning",Bachelor,3,Automotive,2025-01-16,2025-03-30,2303,5.9,Cloud AI Solutions -AI07388,AI Specialist,87156,USD,87156,MI,FT,Sweden,M,Czech Republic,0,"Computer Vision, Scala, Python, TensorFlow",PhD,2,Transportation,2024-03-27,2024-05-18,2028,8.5,AI Innovations -AI07389,Data Engineer,251231,CHF,226108,EX,PT,Switzerland,S,Switzerland,100,"Docker, Linux, Python, Data Visualization, TensorFlow",PhD,17,Media,2024-03-28,2024-05-17,1025,8.3,AI Innovations -AI07390,Data Engineer,75609,USD,75609,EN,FT,Denmark,M,Denmark,50,"Docker, Spark, R, Hadoop",PhD,1,Gaming,2025-04-20,2025-06-25,1240,9.5,Predictive Systems -AI07391,Data Scientist,85774,USD,85774,MI,CT,Sweden,M,Latvia,50,"MLOps, Linux, Mathematics",Bachelor,4,Telecommunications,2024-05-04,2024-07-03,1310,6.9,Smart Analytics -AI07392,Robotics Engineer,270769,USD,270769,EX,PT,Israel,L,Israel,100,"Kubernetes, R, MLOps",PhD,14,Gaming,2025-01-07,2025-03-21,1665,9.4,DataVision Ltd -AI07393,Data Scientist,56999,USD,56999,EN,CT,United States,S,United States,50,"Spark, Data Visualization, AWS, Kubernetes, Hadoop",Associate,1,Transportation,2024-07-25,2024-08-28,1690,5.6,Smart Analytics -AI07394,ML Ops Engineer,95205,EUR,80924,SE,PT,Germany,S,Germany,0,"Python, Scala, MLOps, Statistics",Associate,5,Real Estate,2024-01-19,2024-02-09,923,7.5,Future Systems -AI07395,Data Analyst,116878,USD,116878,SE,FL,South Korea,L,South Korea,100,"Python, TensorFlow, Data Visualization, Computer Vision, Azure",PhD,8,Telecommunications,2024-07-27,2024-10-03,1058,8.2,DataVision Ltd -AI07396,Autonomous Systems Engineer,92083,CAD,115104,MI,FT,Canada,S,Canada,0,"Kubernetes, Linux, R",Bachelor,3,Finance,2024-05-25,2024-07-02,1467,7,Digital Transformation LLC -AI07397,Head of AI,89908,USD,89908,EN,FT,Denmark,L,Denmark,50,"Git, Azure, SQL, Kubernetes",Bachelor,1,Media,2024-01-26,2024-03-01,989,9.4,AI Innovations -AI07398,AI Architect,82155,EUR,69832,MI,CT,France,M,France,50,"Linux, Git, Computer Vision, PyTorch",Associate,2,Real Estate,2024-05-16,2024-06-21,2168,5.9,Future Systems -AI07399,Research Scientist,250839,USD,250839,EX,FT,Finland,L,Finland,100,"SQL, Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,15,Real Estate,2024-02-08,2024-03-25,1727,6.1,Future Systems -AI07400,Autonomous Systems Engineer,141610,USD,141610,SE,FT,United States,L,United States,100,"Python, TensorFlow, Data Visualization, MLOps",PhD,7,Manufacturing,2025-02-07,2025-03-15,2115,8.5,Predictive Systems -AI07401,ML Ops Engineer,134017,USD,134017,SE,FT,Denmark,S,Denmark,0,"Linux, SQL, Statistics, R",PhD,9,Government,2025-02-14,2025-03-31,1735,5.1,Advanced Robotics -AI07402,AI Specialist,287847,EUR,244670,EX,FL,Netherlands,L,Netherlands,100,"SQL, TensorFlow, PyTorch",Master,19,Manufacturing,2024-09-22,2024-10-20,1149,5.7,DataVision Ltd -AI07403,AI Research Scientist,72341,USD,72341,EX,FT,India,M,Turkey,100,"GCP, Computer Vision, Spark, Java, R",Bachelor,15,Telecommunications,2024-08-11,2024-09-10,2228,8,AI Innovations -AI07404,ML Ops Engineer,196644,EUR,167147,EX,CT,France,S,Turkey,0,"GCP, Computer Vision, Data Visualization, Scala",Bachelor,16,Finance,2024-07-11,2024-08-16,2103,5.2,DataVision Ltd -AI07405,AI Consultant,80695,GBP,60521,MI,FT,United Kingdom,M,United Kingdom,100,"NLP, Computer Vision, PyTorch, TensorFlow",Bachelor,4,Manufacturing,2025-02-13,2025-03-05,1974,5.5,Autonomous Tech -AI07406,Robotics Engineer,112650,USD,112650,EN,FL,Denmark,L,Denmark,50,"Kubernetes, Hadoop, Mathematics, Git",Associate,0,Transportation,2024-03-12,2024-04-20,1124,7,Algorithmic Solutions -AI07407,AI Product Manager,138862,USD,138862,MI,FT,United States,L,United States,50,"Hadoop, Mathematics, MLOps",Associate,3,Transportation,2024-07-18,2024-08-03,1894,6.7,Quantum Computing Inc -AI07408,Machine Learning Engineer,92680,CHF,83412,EN,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, MLOps, SQL, Deep Learning",Bachelor,1,Real Estate,2024-05-10,2024-07-01,974,8.1,Cognitive Computing -AI07409,AI Software Engineer,106542,USD,106542,EN,CT,United States,L,United States,0,"Scala, PyTorch, Data Visualization, Tableau",Bachelor,0,Healthcare,2024-05-16,2024-06-19,1892,5.1,Advanced Robotics -AI07410,Machine Learning Engineer,57987,EUR,49289,EN,CT,Germany,S,United States,0,"Docker, Mathematics, TensorFlow",PhD,0,Manufacturing,2025-04-15,2025-05-07,2129,8.9,DeepTech Ventures -AI07411,Machine Learning Engineer,224659,USD,224659,EX,PT,Finland,L,Vietnam,50,"SQL, PyTorch, Kubernetes",Associate,15,Education,2024-08-30,2024-09-14,585,6.2,Quantum Computing Inc -AI07412,AI Consultant,223546,CHF,201191,EX,FT,Switzerland,M,South Korea,100,"TensorFlow, Azure, AWS, GCP, MLOps",PhD,12,Retail,2024-07-08,2024-08-07,1511,9,Digital Transformation LLC -AI07413,AI Research Scientist,151758,CHF,136582,MI,CT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Azure, Computer Vision, NLP",Master,3,Education,2024-04-09,2024-05-05,946,9.4,Quantum Computing Inc -AI07414,AI Specialist,46742,USD,46742,EN,CT,Sweden,S,Italy,50,"NLP, Deep Learning, SQL, Tableau, Hadoop",Master,1,Retail,2024-04-24,2024-07-06,1123,6.7,Algorithmic Solutions -AI07415,AI Software Engineer,159242,USD,159242,EX,PT,Finland,S,Finland,100,"Kubernetes, Deep Learning, Data Visualization, GCP",Associate,10,Real Estate,2024-12-31,2025-02-08,1926,6.1,Future Systems -AI07416,Data Analyst,87254,USD,87254,EN,FT,Norway,S,Brazil,0,"Hadoop, Scala, Data Visualization, SQL",Associate,1,Retail,2024-08-12,2024-10-08,992,6.8,Cloud AI Solutions -AI07417,AI Research Scientist,62366,USD,62366,EN,CT,Finland,M,Singapore,50,"Spark, SQL, Hadoop, AWS",PhD,1,Gaming,2024-02-21,2024-04-02,1969,5.4,Cognitive Computing -AI07418,Data Scientist,194278,USD,194278,SE,FL,Norway,L,Israel,50,"Java, Statistics, Deep Learning, Tableau",Master,7,Media,2024-10-24,2024-12-09,809,8.9,Autonomous Tech -AI07419,AI Product Manager,107060,SGD,139178,SE,CT,Singapore,S,Singapore,100,"Statistics, R, Spark, Deep Learning, Linux",PhD,9,Retail,2025-01-31,2025-04-09,884,9.5,Machine Intelligence Group -AI07420,AI Product Manager,125649,USD,125649,SE,FL,Ireland,L,Ireland,50,"Linux, Spark, Data Visualization, NLP",PhD,5,Automotive,2025-03-29,2025-06-06,1974,10,Machine Intelligence Group -AI07421,AI Architect,151908,USD,151908,EX,PT,Sweden,M,Sweden,100,"Tableau, Computer Vision, PyTorch, SQL, Python",Bachelor,10,Gaming,2024-02-24,2024-05-01,1600,9.1,Machine Intelligence Group -AI07422,ML Ops Engineer,207008,CHF,186307,SE,CT,Switzerland,M,Switzerland,0,"Hadoop, MLOps, Deep Learning, GCP",PhD,7,Retail,2024-05-05,2024-06-01,1235,9,Smart Analytics -AI07423,Data Scientist,93359,CHF,84023,EN,CT,Switzerland,S,Switzerland,100,"Linux, Kubernetes, SQL, Java, Deep Learning",Bachelor,1,Telecommunications,2025-01-02,2025-02-02,1179,9.9,TechCorp Inc -AI07424,AI Research Scientist,102494,AUD,138367,MI,FL,Australia,L,Australia,0,"SQL, R, Mathematics, Linux",Master,4,Automotive,2024-07-18,2024-08-23,1974,5.4,Cloud AI Solutions -AI07425,NLP Engineer,82281,EUR,69939,MI,FL,France,M,France,50,"SQL, Spark, Hadoop",PhD,4,Technology,2024-08-16,2024-09-18,828,6,Algorithmic Solutions -AI07426,Deep Learning Engineer,148607,USD,148607,SE,FT,Finland,L,Finland,0,"Git, Spark, NLP, Computer Vision",Bachelor,9,Finance,2024-10-18,2024-11-04,1627,8.7,AI Innovations -AI07427,Autonomous Systems Engineer,97107,USD,97107,MI,FL,Finland,M,Finland,50,"PyTorch, NLP, Kubernetes, Azure",PhD,4,Finance,2025-01-23,2025-03-19,596,7.2,Neural Networks Co -AI07428,Data Engineer,156750,USD,156750,SE,CT,Norway,S,Norway,50,"Java, Tableau, Scala",PhD,6,Gaming,2024-06-24,2024-07-20,617,6.3,Future Systems -AI07429,Data Scientist,43046,USD,43046,MI,CT,China,M,Mexico,100,"Hadoop, Kubernetes, NLP",Master,4,Telecommunications,2024-07-28,2024-09-04,532,7.9,Advanced Robotics -AI07430,Autonomous Systems Engineer,259249,CAD,324061,EX,FL,Canada,L,Canada,50,"Data Visualization, Linux, SQL, R",Master,13,Real Estate,2024-11-16,2025-01-19,1880,8.9,Neural Networks Co -AI07431,Research Scientist,76203,USD,76203,MI,FT,Sweden,S,Sweden,0,"TensorFlow, R, Git, AWS, Computer Vision",PhD,2,Government,2024-01-09,2024-03-20,2304,9,Predictive Systems -AI07432,Data Engineer,145647,USD,145647,SE,PT,Denmark,M,Philippines,100,"Data Visualization, TensorFlow, Kubernetes, NLP, Deep Learning",PhD,8,Transportation,2024-07-05,2024-09-09,1327,8.5,Algorithmic Solutions -AI07433,AI Specialist,61066,EUR,51906,EN,CT,Netherlands,S,Portugal,0,"Scala, Computer Vision, Python, Docker, TensorFlow",Master,1,Technology,2024-03-15,2024-05-11,2259,6.9,Digital Transformation LLC -AI07434,AI Specialist,186576,USD,186576,SE,CT,Norway,M,Norway,100,"Git, Azure, Data Visualization, PyTorch",PhD,6,Automotive,2025-04-15,2025-06-04,1906,8.8,TechCorp Inc -AI07435,Machine Learning Researcher,132277,USD,132277,SE,CT,Ireland,L,Ireland,0,"Docker, GCP, Linux",Bachelor,9,Telecommunications,2024-04-04,2024-05-05,820,8.4,Machine Intelligence Group -AI07436,NLP Engineer,170334,USD,170334,SE,FL,United States,M,Poland,50,"Spark, R, Git",Bachelor,7,Retail,2025-02-01,2025-03-04,807,6,Cognitive Computing -AI07437,AI Research Scientist,124463,USD,124463,SE,CT,South Korea,M,South Korea,100,"TensorFlow, SQL, NLP, MLOps, Deep Learning",PhD,8,Finance,2024-04-24,2024-05-19,2246,6.2,Cognitive Computing -AI07438,AI Specialist,82706,USD,82706,MI,CT,Sweden,S,Sweden,50,"MLOps, Deep Learning, TensorFlow, NLP",PhD,4,Healthcare,2024-11-15,2025-01-18,756,9,Cognitive Computing -AI07439,AI Architect,250961,CHF,225865,EX,FL,Switzerland,M,Switzerland,100,"Spark, MLOps, Kubernetes, Linux",Bachelor,13,Real Estate,2024-04-07,2024-05-06,1666,9.8,Neural Networks Co -AI07440,AI Consultant,77065,EUR,65505,EN,CT,Germany,L,Denmark,50,"TensorFlow, SQL, AWS",PhD,0,Automotive,2025-04-28,2025-06-26,2078,5.5,Autonomous Tech -AI07441,AI Consultant,60980,AUD,82323,EN,FL,Australia,M,Norway,100,"Python, NLP, TensorFlow, Deep Learning",PhD,1,Energy,2024-10-27,2024-11-30,1528,7.9,Algorithmic Solutions -AI07442,Principal Data Scientist,122642,JPY,13490620,SE,FT,Japan,M,Canada,0,"MLOps, Java, Data Visualization, Hadoop, Python",Associate,6,Automotive,2024-09-04,2024-11-04,1486,8.7,Smart Analytics -AI07443,Machine Learning Researcher,126416,USD,126416,MI,FT,Norway,S,Norway,0,"Spark, Mathematics, Python",Master,2,Retail,2024-06-03,2024-07-07,1354,7.2,DataVision Ltd -AI07444,Data Analyst,43069,USD,43069,EN,FT,China,L,China,50,"Java, Python, Git, Spark, TensorFlow",Bachelor,1,Real Estate,2024-05-15,2024-07-09,2034,8.9,Autonomous Tech -AI07445,AI Product Manager,191754,SGD,249280,EX,FL,Singapore,L,Singapore,0,"Spark, MLOps, Docker, NLP, TensorFlow",Master,19,Manufacturing,2024-01-26,2024-03-13,1056,6.3,Future Systems -AI07446,Principal Data Scientist,89978,SGD,116971,MI,PT,Singapore,S,Singapore,100,"PyTorch, TensorFlow, Data Visualization, Computer Vision",PhD,4,Gaming,2025-03-19,2025-05-31,2223,6.2,Predictive Systems -AI07447,Deep Learning Engineer,69497,SGD,90346,EN,CT,Singapore,M,Singapore,0,"Tableau, Python, TensorFlow, NLP, Computer Vision",Associate,1,Education,2024-11-02,2024-12-27,2304,7,Digital Transformation LLC -AI07448,NLP Engineer,68144,CAD,85180,EN,CT,Canada,L,Poland,100,"Kubernetes, Scala, GCP, Docker, Hadoop",PhD,0,Gaming,2024-09-03,2024-11-09,1002,5.6,Predictive Systems -AI07449,Machine Learning Researcher,245939,JPY,27053290,EX,FL,Japan,L,Japan,50,"SQL, Data Visualization, Python",PhD,15,Retail,2025-04-07,2025-06-19,1029,6.1,Cloud AI Solutions -AI07450,Computer Vision Engineer,143618,EUR,122075,EX,CT,France,M,France,100,"Docker, GCP, NLP, Azure, Kubernetes",Master,12,Energy,2024-01-11,2024-03-02,1998,6.3,Cloud AI Solutions -AI07451,AI Software Engineer,118901,EUR,101066,MI,FL,Netherlands,L,Netherlands,100,"Linux, Java, Statistics",Bachelor,4,Transportation,2024-02-11,2024-03-09,2248,5.5,Algorithmic Solutions -AI07452,AI Research Scientist,31907,USD,31907,MI,PT,India,S,India,0,"MLOps, Spark, Linux, Data Visualization, NLP",PhD,4,Real Estate,2025-03-26,2025-05-25,2009,8.9,Quantum Computing Inc -AI07453,AI Specialist,165521,USD,165521,EX,PT,Sweden,M,Sweden,0,"Computer Vision, R, Linux",Master,16,Healthcare,2024-02-17,2024-03-09,993,9.5,Neural Networks Co -AI07454,Principal Data Scientist,143655,USD,143655,SE,FL,Finland,L,Finland,100,"MLOps, Spark, Java, NLP, SQL",Associate,7,Media,2024-01-01,2024-02-16,1009,5.6,DeepTech Ventures -AI07455,Data Engineer,18305,USD,18305,EN,CT,India,M,India,0,"SQL, AWS, Spark",Bachelor,1,Finance,2024-01-02,2024-01-18,1652,5.8,Autonomous Tech -AI07456,Principal Data Scientist,103388,CHF,93049,EN,PT,Switzerland,L,Israel,0,"SQL, Mathematics, Spark, TensorFlow",Associate,0,Education,2025-04-26,2025-07-06,1717,5.4,Digital Transformation LLC -AI07457,Autonomous Systems Engineer,216271,USD,216271,EX,FL,Israel,M,Israel,100,"Python, Linux, Java, TensorFlow",Master,14,Energy,2024-10-25,2024-12-10,666,6.3,Future Systems -AI07458,Autonomous Systems Engineer,54685,JPY,6015350,EN,PT,Japan,M,Japan,50,"Python, Linux, Hadoop, Data Visualization",Master,0,Media,2024-08-28,2024-11-03,1196,6.3,Neural Networks Co -AI07459,ML Ops Engineer,101910,USD,101910,SE,FT,South Korea,M,Canada,50,"Tableau, GCP, Azure",Master,6,Real Estate,2025-04-15,2025-06-11,1897,7.4,Algorithmic Solutions -AI07460,Deep Learning Engineer,232335,JPY,25556850,EX,FL,Japan,M,Japan,100,"Scala, Spark, Java, SQL",Master,19,Technology,2024-10-18,2024-12-11,606,9.1,Machine Intelligence Group -AI07461,Machine Learning Engineer,196676,GBP,147507,EX,PT,United Kingdom,S,United Kingdom,50,"Linux, Azure, TensorFlow, Tableau, PyTorch",Associate,18,Technology,2024-02-11,2024-02-29,1568,8.1,AI Innovations -AI07462,Machine Learning Engineer,97001,USD,97001,MI,PT,United States,M,Singapore,100,"PyTorch, Java, Mathematics, Deep Learning",Associate,2,Healthcare,2024-07-30,2024-08-17,1730,8.6,DeepTech Ventures -AI07463,AI Software Engineer,141916,EUR,120629,SE,FL,Germany,L,Germany,100,"Python, TensorFlow, Azure",Master,9,Manufacturing,2024-10-20,2024-11-28,2447,6.7,Advanced Robotics -AI07464,Machine Learning Engineer,58453,USD,58453,EN,FT,United States,S,Malaysia,0,"Linux, Azure, Statistics",PhD,1,Gaming,2024-01-25,2024-02-08,524,9.4,TechCorp Inc -AI07465,AI Architect,65377,EUR,55570,EN,FT,Germany,M,Germany,0,"SQL, Statistics, AWS, Docker",Master,0,Technology,2024-04-17,2024-06-19,1603,5.8,DeepTech Ventures -AI07466,Machine Learning Engineer,84606,SGD,109988,MI,FL,Singapore,S,Singapore,100,"GCP, NLP, Python, Data Visualization, Spark",Master,3,Government,2024-10-21,2024-11-08,2113,9.1,TechCorp Inc -AI07467,ML Ops Engineer,61087,EUR,51924,EN,FT,France,M,France,0,"NLP, R, MLOps",Master,0,Automotive,2025-04-26,2025-06-18,2334,6.1,Quantum Computing Inc -AI07468,NLP Engineer,66540,AUD,89829,EN,FL,Australia,M,China,0,"Spark, Docker, PyTorch, Computer Vision",PhD,0,Healthcare,2024-06-28,2024-08-14,2020,7.2,DeepTech Ventures -AI07469,Machine Learning Researcher,148528,USD,148528,SE,FT,Israel,L,Israel,0,"MLOps, Java, AWS, Deep Learning",Master,9,Telecommunications,2025-01-23,2025-03-09,874,7.4,Smart Analytics -AI07470,Deep Learning Engineer,126440,USD,126440,EX,FT,South Korea,S,South Korea,100,"R, Computer Vision, Scala, Java",Associate,18,Transportation,2024-09-04,2024-09-23,764,5.9,DataVision Ltd -AI07471,Research Scientist,117780,CHF,106002,EN,FT,Switzerland,L,Switzerland,0,"Computer Vision, Data Visualization, Linux, MLOps",Bachelor,1,Finance,2025-04-28,2025-05-21,2477,6.3,DataVision Ltd -AI07472,AI Research Scientist,129661,USD,129661,EX,FT,Finland,M,Ukraine,50,"NLP, MLOps, Python, Spark, Mathematics",Master,10,Real Estate,2024-03-02,2024-04-02,914,6.2,Smart Analytics -AI07473,Robotics Engineer,46753,EUR,39740,EN,PT,Austria,S,Austria,0,"SQL, Hadoop, Statistics, Spark",Associate,0,Manufacturing,2024-05-25,2024-07-06,1228,6.7,TechCorp Inc -AI07474,Computer Vision Engineer,43491,USD,43491,EX,FL,India,S,Vietnam,0,"Azure, TensorFlow, Scala",Bachelor,12,Healthcare,2024-10-16,2024-12-15,1489,7.5,Autonomous Tech -AI07475,AI Architect,120298,SGD,156387,MI,PT,Singapore,L,Singapore,0,"Kubernetes, Git, Spark, Linux, SQL",PhD,3,Gaming,2024-02-25,2024-04-24,890,5.4,DataVision Ltd -AI07476,ML Ops Engineer,260872,USD,260872,EX,FT,Norway,S,Norway,0,"Java, Data Visualization, MLOps",Associate,13,Education,2025-03-23,2025-04-20,1870,5.4,AI Innovations -AI07477,Robotics Engineer,71601,AUD,96661,EN,FT,Australia,S,Australia,50,"Linux, Hadoop, AWS, Python, Deep Learning",Master,0,Education,2025-04-25,2025-06-10,1267,5.9,Algorithmic Solutions -AI07478,Machine Learning Engineer,49525,USD,49525,EX,FL,India,M,Portugal,50,"Docker, Git, GCP, Scala",PhD,15,Manufacturing,2024-04-28,2024-05-20,1446,8.2,AI Innovations -AI07479,AI Research Scientist,82352,USD,82352,EN,FL,Ireland,L,Ireland,50,"GCP, Python, Computer Vision",PhD,1,Healthcare,2024-04-25,2024-05-30,1036,9.6,Neural Networks Co -AI07480,Machine Learning Researcher,238897,USD,238897,EX,CT,Norway,M,Norway,0,"Git, Linux, Statistics",Bachelor,12,Transportation,2024-05-05,2024-06-11,638,7.1,Neural Networks Co -AI07481,AI Research Scientist,64610,USD,64610,EN,CT,Israel,L,Israel,100,"Spark, Kubernetes, Linux, GCP, AWS",PhD,1,Retail,2024-06-04,2024-07-04,552,6.9,Future Systems -AI07482,Principal Data Scientist,121207,USD,121207,EX,FL,Finland,S,Finland,50,"GCP, Git, Statistics",Associate,12,Healthcare,2024-08-10,2024-09-07,1835,8.7,AI Innovations -AI07483,AI Specialist,118359,JPY,13019490,SE,FL,Japan,M,Japan,50,"MLOps, Linux, Java, TensorFlow, Python",Associate,7,Media,2024-11-13,2024-12-24,1107,6.4,Algorithmic Solutions -AI07484,NLP Engineer,176333,CHF,158700,SE,FL,Switzerland,L,Switzerland,0,"Scala, Kubernetes, Deep Learning",Bachelor,8,Education,2024-11-03,2024-11-30,1123,5.5,Cognitive Computing -AI07485,AI Consultant,137799,USD,137799,SE,CT,Ireland,M,Ireland,50,"Spark, Python, Hadoop",Associate,8,Real Estate,2024-06-20,2024-08-31,1243,7.2,Quantum Computing Inc -AI07486,AI Architect,147983,USD,147983,EX,CT,Sweden,S,Russia,50,"SQL, TensorFlow, Tableau, AWS, Mathematics",Master,16,Energy,2025-02-06,2025-04-01,1503,8.1,Quantum Computing Inc -AI07487,AI Research Scientist,44458,USD,44458,EN,FT,Finland,S,Finland,0,"Azure, Scala, Tableau",Bachelor,0,Telecommunications,2024-03-26,2024-06-06,2344,5.6,Algorithmic Solutions -AI07488,ML Ops Engineer,182046,EUR,154739,EX,CT,Netherlands,M,Netherlands,0,"Python, Java, Linux, Statistics, Deep Learning",Bachelor,17,Retail,2024-02-02,2024-04-12,2221,6,DeepTech Ventures -AI07489,Robotics Engineer,89818,SGD,116763,EN,FL,Singapore,L,Singapore,100,"Java, PyTorch, GCP, Tableau",Master,0,Gaming,2024-03-29,2024-05-26,636,5.7,Machine Intelligence Group -AI07490,NLP Engineer,154108,GBP,115581,SE,CT,United Kingdom,M,New Zealand,0,"PyTorch, Kubernetes, Computer Vision",PhD,8,Manufacturing,2025-02-15,2025-04-01,1863,9.1,Machine Intelligence Group -AI07491,Autonomous Systems Engineer,77976,USD,77976,EN,FT,Ireland,M,Ireland,0,"SQL, GCP, Java, Hadoop, Data Visualization",Associate,1,Retail,2024-06-14,2024-07-24,2169,6.7,AI Innovations -AI07492,Computer Vision Engineer,158800,AUD,214380,SE,FT,Australia,L,Australia,100,"Kubernetes, Python, NLP, R",Associate,5,Technology,2024-08-04,2024-09-29,895,5.4,Digital Transformation LLC -AI07493,AI Software Engineer,269552,CHF,242597,EX,FL,Switzerland,L,Switzerland,50,"NLP, Kubernetes, Spark",Associate,16,Retail,2024-09-26,2024-11-21,1202,8.9,Cloud AI Solutions -AI07494,ML Ops Engineer,40777,USD,40777,SE,FT,India,M,India,50,"AWS, MLOps, Java, Scala",Associate,6,Telecommunications,2024-04-21,2024-05-20,1471,9.3,Future Systems -AI07495,Data Scientist,40524,USD,40524,EN,FL,China,L,China,0,"TensorFlow, Azure, MLOps, Linux",Master,1,Government,2024-01-20,2024-03-08,1447,7.8,DeepTech Ventures -AI07496,AI Product Manager,104604,USD,104604,SE,PT,Finland,S,Mexico,100,"NLP, Docker, Data Visualization, Python",Master,8,Retail,2024-03-17,2024-05-24,1519,7.1,Neural Networks Co -AI07497,Research Scientist,108828,GBP,81621,SE,FL,United Kingdom,S,Indonesia,50,"Python, Kubernetes, MLOps, Linux, Mathematics",Bachelor,7,Real Estate,2024-11-22,2024-12-14,2377,5.6,Digital Transformation LLC -AI07498,AI Product Manager,332899,USD,332899,EX,FL,Denmark,L,Denmark,0,"GCP, SQL, PyTorch",PhD,10,Telecommunications,2024-09-23,2024-10-12,786,8.8,Digital Transformation LLC -AI07499,AI Product Manager,282331,USD,282331,EX,FL,United States,M,United States,0,"Statistics, Tableau, Python, Computer Vision, TensorFlow",PhD,17,Media,2024-09-01,2024-10-17,2115,9.5,Predictive Systems -AI07500,Robotics Engineer,50649,USD,50649,MI,FT,China,L,China,0,"Computer Vision, Git, Hadoop",PhD,3,Government,2024-05-04,2024-07-05,754,7.3,Cognitive Computing -AI07501,AI Product Manager,74786,JPY,8226460,EN,FL,Japan,S,Ukraine,100,"AWS, Statistics, R, Hadoop, TensorFlow",Associate,1,Real Estate,2024-01-11,2024-01-30,1792,8,Cognitive Computing -AI07502,Machine Learning Engineer,246647,USD,246647,EX,CT,Denmark,L,Colombia,50,"Git, Linux, Python, Deep Learning, MLOps",Bachelor,11,Telecommunications,2024-05-12,2024-06-24,1926,8.9,Neural Networks Co -AI07503,Machine Learning Engineer,219909,USD,219909,EX,CT,Norway,S,Norway,0,"SQL, Java, Scala, Spark",Bachelor,17,Media,2024-09-06,2024-10-21,798,7.7,Quantum Computing Inc -AI07504,AI Research Scientist,137360,SGD,178568,EX,PT,Singapore,S,Norway,100,"MLOps, Azure, Scala, AWS",Master,13,Media,2025-03-29,2025-05-29,1811,9.3,DeepTech Ventures -AI07505,Data Analyst,80377,USD,80377,EN,CT,Sweden,M,United States,50,"PyTorch, Hadoop, TensorFlow, Computer Vision",Master,1,Healthcare,2024-05-15,2024-06-13,1584,6,Neural Networks Co -AI07506,AI Software Engineer,150710,JPY,16578100,SE,PT,Japan,L,Japan,100,"Mathematics, Spark, Docker, Statistics",PhD,6,Automotive,2024-06-13,2024-08-14,2040,5.4,Cognitive Computing -AI07507,Head of AI,165703,USD,165703,EX,CT,Israel,L,Ireland,50,"Kubernetes, GCP, Computer Vision",Master,16,Transportation,2025-03-29,2025-05-05,1006,6,AI Innovations -AI07508,AI Product Manager,89181,USD,89181,EN,FL,Denmark,S,Singapore,0,"Python, Azure, Mathematics",PhD,0,Energy,2025-02-18,2025-03-20,875,7.7,Smart Analytics -AI07509,Robotics Engineer,179770,CHF,161793,SE,FL,Switzerland,S,Switzerland,0,"NLP, GCP, Docker, Git, Azure",Associate,6,Manufacturing,2024-09-15,2024-10-17,2220,8.3,DataVision Ltd -AI07510,Machine Learning Researcher,148095,USD,148095,SE,FL,Sweden,M,Sweden,0,"Spark, Scala, Deep Learning, Hadoop",Associate,8,Media,2024-06-17,2024-08-16,784,9.3,Predictive Systems -AI07511,AI Software Engineer,86619,USD,86619,MI,PT,United States,S,Sweden,0,"Spark, GCP, Java, R",Bachelor,4,Government,2024-01-19,2024-03-27,1171,7.7,DeepTech Ventures -AI07512,Data Engineer,94298,USD,94298,SE,FL,South Korea,S,South Korea,100,"Scala, Computer Vision, Docker, Java",Associate,6,Energy,2024-11-06,2024-12-28,1362,6.9,Predictive Systems -AI07513,Computer Vision Engineer,196323,USD,196323,SE,CT,Norway,M,Norway,0,"PyTorch, SQL, Spark, TensorFlow",Master,8,Automotive,2024-12-13,2025-01-04,1981,6.6,Predictive Systems -AI07514,Robotics Engineer,21114,USD,21114,EN,CT,India,L,India,100,"Computer Vision, SQL, Tableau",PhD,0,Energy,2025-03-21,2025-04-15,2127,5.5,Autonomous Tech -AI07515,NLP Engineer,149569,EUR,127134,SE,FL,Austria,L,Austria,100,"Kubernetes, Git, SQL",Bachelor,5,Retail,2024-04-30,2024-06-24,2372,8.1,Future Systems -AI07516,Machine Learning Engineer,103038,USD,103038,MI,FL,Sweden,M,Sweden,0,"Computer Vision, Python, Java, Tableau",PhD,2,Energy,2025-03-14,2025-05-03,1504,7.8,Smart Analytics -AI07517,Head of AI,118703,USD,118703,SE,PT,Israel,M,Israel,50,"GCP, PyTorch, Docker",Associate,5,Gaming,2024-10-09,2024-12-04,536,5.4,Smart Analytics -AI07518,AI Consultant,65083,USD,65083,EN,FL,South Korea,L,Vietnam,50,"Linux, Deep Learning, Data Visualization, TensorFlow, Kubernetes",Bachelor,1,Media,2024-05-31,2024-07-21,2356,7.8,Autonomous Tech -AI07519,Data Analyst,143495,USD,143495,SE,PT,Norway,M,Norway,100,"PyTorch, AWS, Scala, Java",PhD,8,Gaming,2024-12-31,2025-01-18,811,7.4,Autonomous Tech -AI07520,Autonomous Systems Engineer,158654,USD,158654,SE,FL,Norway,L,Norway,50,"AWS, Git, Python, GCP, Scala",Bachelor,7,Gaming,2024-10-28,2024-12-21,1527,6.8,Advanced Robotics -AI07521,Head of AI,76071,EUR,64660,MI,FL,Netherlands,S,Netherlands,100,"Kubernetes, Git, Scala, Computer Vision, Python",PhD,2,Education,2024-07-08,2024-08-14,688,8.4,TechCorp Inc -AI07522,Data Analyst,70355,USD,70355,MI,FL,Finland,M,Finland,50,"Java, Spark, Hadoop, Mathematics",Associate,2,Technology,2024-07-25,2024-08-24,2367,5.2,DeepTech Ventures -AI07523,Data Analyst,100575,CAD,125719,MI,CT,Canada,M,Canada,100,"Spark, Tableau, Azure, NLP, Mathematics",PhD,2,Manufacturing,2025-01-04,2025-01-24,1421,6.6,Advanced Robotics -AI07524,Machine Learning Researcher,137502,GBP,103127,SE,FL,United Kingdom,M,United Kingdom,50,"PyTorch, SQL, NLP",PhD,9,Manufacturing,2024-07-24,2024-09-02,1538,5.6,Quantum Computing Inc -AI07525,Data Analyst,76419,AUD,103166,EN,FT,Australia,M,Australia,0,"Python, Deep Learning, Linux, Mathematics, Kubernetes",PhD,0,Education,2024-10-13,2024-12-25,925,9.2,Algorithmic Solutions -AI07526,AI Research Scientist,76902,USD,76902,MI,PT,Finland,M,Finland,50,"TensorFlow, Kubernetes, Spark, Azure, Git",PhD,4,Education,2024-09-20,2024-10-23,2336,8.8,AI Innovations -AI07527,AI Product Manager,89926,USD,89926,EN,CT,Denmark,S,China,50,"Azure, Git, NLP, GCP, Scala",PhD,1,Retail,2024-06-11,2024-07-23,1513,7.4,Future Systems -AI07528,Research Scientist,213625,EUR,181581,EX,FT,Netherlands,S,Philippines,50,"Docker, Java, Data Visualization, TensorFlow, MLOps",Master,14,Manufacturing,2024-09-14,2024-11-13,2394,9.8,Cognitive Computing -AI07529,AI Architect,160222,EUR,136189,EX,FL,Austria,L,Austria,50,"GCP, Linux, Azure, Git",PhD,14,Transportation,2024-01-07,2024-03-03,885,8.1,Smart Analytics -AI07530,Machine Learning Engineer,35947,USD,35947,MI,FL,India,M,Spain,50,"SQL, GCP, Deep Learning",PhD,4,Finance,2024-11-28,2024-12-18,2230,5,Predictive Systems -AI07531,Research Scientist,53653,SGD,69749,EN,CT,Singapore,S,Brazil,0,"Git, Data Visualization, R, Java, GCP",Associate,1,Government,2024-10-16,2024-12-23,2404,6.5,Machine Intelligence Group -AI07532,NLP Engineer,108963,EUR,92619,SE,CT,Netherlands,M,Portugal,0,"Python, TensorFlow, NLP",Associate,7,Telecommunications,2025-01-20,2025-03-09,1210,8.2,Autonomous Tech -AI07533,AI Software Engineer,77378,USD,77378,MI,CT,South Korea,S,Estonia,0,"Spark, Computer Vision, Scala, SQL",PhD,4,Energy,2024-06-16,2024-08-12,1392,5.7,Advanced Robotics -AI07534,Machine Learning Engineer,84375,EUR,71719,MI,CT,Germany,S,Germany,0,"NLP, Data Visualization, Python, Tableau",PhD,4,Healthcare,2025-03-30,2025-05-07,2486,7.8,Advanced Robotics -AI07535,AI Architect,212229,CAD,265286,EX,CT,Canada,L,Canada,0,"NLP, Mathematics, Git, TensorFlow",Bachelor,18,Media,2024-09-30,2024-11-27,1563,8.4,TechCorp Inc -AI07536,Machine Learning Researcher,122917,USD,122917,EX,FT,Israel,S,Israel,0,"Docker, MLOps, TensorFlow, Data Visualization, Linux",PhD,14,Technology,2024-05-31,2024-07-02,1245,8,Advanced Robotics -AI07537,AI Product Manager,75040,EUR,63784,EN,CT,France,L,France,50,"Azure, Python, Linux, Java",Bachelor,0,Technology,2024-01-03,2024-01-24,843,6.2,Autonomous Tech -AI07538,Data Scientist,302015,USD,302015,EX,CT,Denmark,M,Turkey,50,"Computer Vision, GCP, Git, SQL, Hadoop",Master,11,Transportation,2024-08-11,2024-09-09,1447,5.2,TechCorp Inc -AI07539,Data Scientist,100206,EUR,85175,MI,CT,Germany,M,Germany,0,"NLP, Kubernetes, Mathematics",Bachelor,3,Finance,2024-03-24,2024-05-28,1544,6.6,TechCorp Inc -AI07540,Machine Learning Researcher,74112,CAD,92640,EN,FL,Canada,M,Turkey,100,"SQL, PyTorch, AWS, TensorFlow",Master,0,Retail,2024-06-06,2024-07-31,1498,5.6,Digital Transformation LLC -AI07541,Data Engineer,52847,USD,52847,SE,FL,India,L,India,0,"Statistics, Azure, Computer Vision, Deep Learning, SQL",Associate,9,Consulting,2024-04-22,2024-05-15,614,8.4,Future Systems -AI07542,AI Research Scientist,121952,EUR,103659,SE,CT,Austria,M,Austria,0,"Java, Scala, Spark",PhD,9,Retail,2024-02-03,2024-04-08,808,10,Smart Analytics -AI07543,AI Specialist,22932,USD,22932,EN,FT,India,M,India,0,"SQL, Kubernetes, Tableau",Bachelor,1,Technology,2024-06-08,2024-08-12,1556,7.3,Cloud AI Solutions -AI07544,Robotics Engineer,185551,USD,185551,EX,FL,Ireland,L,Sweden,50,"Azure, SQL, Data Visualization, Linux",Bachelor,12,Real Estate,2024-03-13,2024-05-13,608,6.6,Quantum Computing Inc -AI07545,NLP Engineer,144980,USD,144980,EX,FL,South Korea,M,Poland,50,"Python, Linux, AWS, Deep Learning",PhD,12,Manufacturing,2025-04-20,2025-05-24,1125,8.2,Smart Analytics -AI07546,NLP Engineer,137887,USD,137887,MI,CT,United States,L,United States,100,"NLP, Linux, Tableau",Master,4,Government,2024-04-09,2024-05-12,642,10,AI Innovations -AI07547,Principal Data Scientist,26422,USD,26422,EN,FT,China,S,Latvia,100,"Hadoop, Spark, Java, Scala",Master,0,Technology,2025-01-14,2025-01-30,1300,8.4,Future Systems -AI07548,ML Ops Engineer,92812,USD,92812,EN,FL,United States,M,United States,100,"NLP, Computer Vision, Linux",Master,0,Media,2024-12-18,2025-02-20,1521,7.3,TechCorp Inc -AI07549,AI Software Engineer,60930,USD,60930,MI,FT,South Korea,S,South Korea,0,"SQL, TensorFlow, Statistics, Git",Bachelor,3,Healthcare,2024-11-25,2025-01-23,1040,7.5,Autonomous Tech -AI07550,ML Ops Engineer,218956,USD,218956,EX,PT,Finland,M,Finland,50,"SQL, Java, Azure",PhD,18,Education,2024-01-21,2024-03-13,1594,8.8,Digital Transformation LLC -AI07551,Data Scientist,75273,USD,75273,MI,CT,Israel,M,Israel,50,"MLOps, Tableau, Spark",PhD,4,Transportation,2024-09-16,2024-10-18,801,6,Algorithmic Solutions -AI07552,Autonomous Systems Engineer,49221,USD,49221,MI,CT,China,M,China,0,"PyTorch, Hadoop, Python, SQL",Associate,2,Energy,2024-08-28,2024-10-03,1967,5.6,AI Innovations -AI07553,Robotics Engineer,199243,EUR,169357,EX,FT,Germany,L,Indonesia,0,"Docker, TensorFlow, Tableau, SQL",Bachelor,13,Energy,2024-12-31,2025-01-16,1820,9.5,Advanced Robotics -AI07554,NLP Engineer,98108,USD,98108,SE,CT,Ireland,S,Ireland,0,"Tableau, Deep Learning, Git, Python, Scala",PhD,8,Healthcare,2024-10-19,2024-12-17,710,7.6,AI Innovations -AI07555,Principal Data Scientist,251392,EUR,213683,EX,FT,France,L,France,0,"Kubernetes, PyTorch, GCP",PhD,13,Gaming,2025-04-02,2025-06-01,1365,6.9,Smart Analytics -AI07556,Head of AI,102675,SGD,133478,SE,CT,Singapore,S,South Africa,50,"Spark, Hadoop, SQL, Tableau",Associate,8,Automotive,2024-05-30,2024-06-14,2253,8.5,Machine Intelligence Group -AI07557,NLP Engineer,289291,JPY,31822010,EX,PT,Japan,L,Japan,50,"Scala, Kubernetes, R, MLOps",Master,16,Government,2024-12-13,2025-01-18,537,5.7,Quantum Computing Inc -AI07558,AI Consultant,58763,SGD,76392,EN,FT,Singapore,S,Singapore,100,"Scala, PyTorch, AWS",Master,1,Manufacturing,2024-11-21,2024-12-30,1146,8.1,Algorithmic Solutions -AI07559,Machine Learning Engineer,119668,USD,119668,SE,PT,Israel,M,Italy,0,"NLP, Kubernetes, Scala, GCP",Bachelor,8,Finance,2024-09-26,2024-11-12,986,6.9,Machine Intelligence Group -AI07560,Data Scientist,50856,AUD,68656,EN,FT,Australia,S,New Zealand,0,"Azure, NLP, Kubernetes, Scala",Associate,1,Government,2024-11-11,2024-12-02,1490,7.7,Digital Transformation LLC -AI07561,ML Ops Engineer,98859,USD,98859,MI,FT,Norway,S,Norway,50,"Computer Vision, Java, Scala",Master,3,Media,2025-04-26,2025-07-08,932,7,Predictive Systems -AI07562,Principal Data Scientist,276933,USD,276933,EX,FT,Denmark,M,Denmark,50,"Deep Learning, R, MLOps",PhD,14,Manufacturing,2024-09-28,2024-12-03,2353,9.2,Neural Networks Co -AI07563,AI Research Scientist,154287,USD,154287,SE,FT,Norway,S,Norway,0,"Linux, Statistics, NLP",PhD,7,Gaming,2024-02-06,2024-04-09,1675,5.1,Smart Analytics -AI07564,AI Product Manager,185605,EUR,157764,EX,FL,Germany,M,India,0,"SQL, Scala, Kubernetes, MLOps, Spark",Master,11,Healthcare,2024-10-13,2024-11-02,2420,7.4,Autonomous Tech -AI07565,Computer Vision Engineer,147217,AUD,198743,EX,PT,Australia,M,Australia,50,"PyTorch, Scala, Mathematics",Bachelor,13,Real Estate,2024-12-03,2025-01-23,1945,6.1,Cognitive Computing -AI07566,Machine Learning Engineer,84531,USD,84531,MI,PT,Norway,S,Norway,0,"Linux, Python, Scala, Computer Vision",Master,2,Telecommunications,2024-02-13,2024-03-23,967,8.9,Autonomous Tech -AI07567,AI Specialist,188423,GBP,141317,EX,CT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Git, NLP",Bachelor,13,Manufacturing,2024-10-22,2024-11-23,2357,6.3,Advanced Robotics -AI07568,Machine Learning Engineer,93853,USD,93853,EN,PT,United States,L,Norway,50,"Docker, Kubernetes, AWS, Tableau",Associate,1,Real Estate,2025-01-22,2025-03-03,1530,9.7,Smart Analytics -AI07569,AI Software Engineer,173348,USD,173348,EX,FL,South Korea,L,South Korea,100,"NLP, Linux, SQL",Master,13,Gaming,2025-02-23,2025-04-19,786,6.3,TechCorp Inc -AI07570,Computer Vision Engineer,81621,EUR,69378,MI,CT,France,S,Ghana,100,"Java, NLP, R, Docker, Tableau",PhD,4,Technology,2024-08-04,2024-09-11,2069,7.6,DeepTech Ventures -AI07571,Machine Learning Researcher,171427,USD,171427,EX,FL,Finland,S,Chile,0,"Python, Spark, Docker, Computer Vision",Master,12,Retail,2024-08-07,2024-09-19,1068,9.8,Machine Intelligence Group -AI07572,AI Architect,124261,USD,124261,MI,CT,United States,M,United States,100,"Computer Vision, Java, PyTorch, Git, Linux",PhD,4,Technology,2025-03-02,2025-05-12,1411,8.5,TechCorp Inc -AI07573,Autonomous Systems Engineer,78038,GBP,58529,MI,CT,United Kingdom,M,United Kingdom,100,"Mathematics, Hadoop, R",Master,3,Technology,2024-01-16,2024-02-19,1335,9.3,AI Innovations -AI07574,NLP Engineer,84616,JPY,9307760,MI,FL,Japan,S,Japan,50,"Statistics, R, Computer Vision",PhD,2,Automotive,2025-03-09,2025-03-26,757,6.8,AI Innovations -AI07575,Deep Learning Engineer,56130,USD,56130,EN,CT,Ireland,S,Ireland,50,"NLP, Deep Learning, R, SQL, MLOps",PhD,1,Transportation,2025-04-04,2025-06-12,984,7.1,Algorithmic Solutions -AI07576,Principal Data Scientist,180941,EUR,153800,EX,FL,Austria,L,Vietnam,50,"Deep Learning, NLP, Python",Master,15,Education,2024-12-22,2025-01-15,1773,5.9,Smart Analytics -AI07577,Robotics Engineer,36195,USD,36195,MI,PT,India,M,Spain,0,"Kubernetes, Linux, Git, Python",PhD,2,Technology,2024-02-04,2024-02-22,1586,9.2,Quantum Computing Inc -AI07578,Machine Learning Researcher,74934,USD,74934,EN,FT,Denmark,M,Denmark,100,"GCP, PyTorch, Tableau, Deep Learning",Associate,1,Finance,2024-01-30,2024-02-16,2411,6.4,Neural Networks Co -AI07579,Data Analyst,92668,EUR,78768,MI,FL,France,S,France,0,"Python, Hadoop, Data Visualization, Git, Docker",Bachelor,3,Gaming,2024-05-03,2024-06-03,2476,7.3,Digital Transformation LLC -AI07580,ML Ops Engineer,106319,AUD,143531,MI,PT,Australia,M,Australia,0,"SQL, NLP, MLOps, Hadoop",Associate,4,Media,2025-02-19,2025-04-25,655,5.5,Cognitive Computing -AI07581,AI Product Manager,119428,USD,119428,SE,FT,Finland,L,Finland,50,"Java, GCP, Hadoop, Data Visualization, R",Bachelor,5,Technology,2024-01-10,2024-01-24,2417,9.7,Neural Networks Co -AI07582,Research Scientist,148430,JPY,16327300,EX,CT,Japan,S,Japan,100,"Git, Spark, TensorFlow, SQL, Deep Learning",PhD,18,Automotive,2024-04-18,2024-06-23,907,8.3,Neural Networks Co -AI07583,AI Software Engineer,97277,EUR,82685,SE,FT,France,S,India,0,"Mathematics, Kubernetes, Tableau, NLP",Master,5,Technology,2024-07-22,2024-08-26,2242,5.7,Cloud AI Solutions -AI07584,Head of AI,22873,USD,22873,EN,PT,India,S,India,0,"Python, Computer Vision, Git, TensorFlow",Associate,0,Telecommunications,2025-01-15,2025-02-08,1699,8,Digital Transformation LLC -AI07585,Principal Data Scientist,78064,EUR,66354,MI,PT,Germany,M,Germany,100,"Hadoop, Git, Statistics",Master,4,Technology,2025-01-25,2025-02-08,974,8.5,AI Innovations -AI07586,AI Research Scientist,29207,USD,29207,EN,FL,China,S,China,50,"SQL, Kubernetes, MLOps",Associate,1,Energy,2024-02-19,2024-04-11,893,8.4,DeepTech Ventures -AI07587,ML Ops Engineer,171296,EUR,145602,SE,CT,Netherlands,L,Kenya,0,"Hadoop, Spark, Docker, Azure, Scala",Master,7,Automotive,2024-10-22,2024-11-10,1712,6.6,Machine Intelligence Group -AI07588,Data Engineer,60437,USD,60437,EN,CT,Israel,L,Israel,100,"Java, TensorFlow, Docker, Computer Vision",Associate,1,Transportation,2024-03-28,2024-04-18,975,8.4,Algorithmic Solutions -AI07589,AI Specialist,106204,SGD,138065,SE,PT,Singapore,S,Singapore,100,"Python, Kubernetes, AWS",Bachelor,5,Retail,2024-07-01,2024-09-01,1199,7.2,Advanced Robotics -AI07590,NLP Engineer,30321,USD,30321,MI,FT,India,M,India,100,"Data Visualization, Java, Docker, Python",Bachelor,4,Consulting,2024-08-27,2024-09-13,1329,9.5,Cloud AI Solutions -AI07591,Head of AI,189953,EUR,161460,EX,CT,Austria,L,Austria,0,"Spark, SQL, Data Visualization, Deep Learning",Associate,10,Real Estate,2025-01-01,2025-02-04,1500,8.9,Smart Analytics -AI07592,Machine Learning Researcher,54381,EUR,46224,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, Statistics, Azure, Scala",Bachelor,0,Automotive,2024-06-23,2024-08-30,942,5.9,Cognitive Computing -AI07593,Machine Learning Researcher,88330,JPY,9716300,EN,FT,Japan,L,Japan,0,"MLOps, Hadoop, SQL, Git, AWS",Associate,0,Healthcare,2025-03-10,2025-04-29,1145,8.1,Cognitive Computing -AI07594,AI Product Manager,154426,USD,154426,SE,FT,Sweden,L,Thailand,100,"Computer Vision, Tableau, MLOps, SQL",Bachelor,7,Education,2024-02-16,2024-03-09,1855,7.6,Digital Transformation LLC -AI07595,AI Software Engineer,119526,EUR,101597,SE,PT,Netherlands,S,Netherlands,50,"Java, Kubernetes, Spark, Mathematics",Master,6,Media,2025-03-21,2025-04-19,2244,8,Cognitive Computing -AI07596,AI Architect,137197,USD,137197,SE,FT,Denmark,M,Vietnam,0,"Java, Docker, PyTorch, AWS, Hadoop",Associate,6,Healthcare,2024-12-25,2025-02-19,1065,6.7,Smart Analytics -AI07597,Head of AI,117462,USD,117462,SE,CT,Israel,M,Colombia,50,"Data Visualization, PyTorch, NLP, Docker",Associate,8,Transportation,2024-09-27,2024-10-24,2441,6.3,DeepTech Ventures -AI07598,Data Analyst,163257,EUR,138768,SE,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Statistics, Scala",Master,7,Healthcare,2024-11-18,2024-12-09,840,7.3,Neural Networks Co -AI07599,Data Analyst,185659,USD,185659,EX,PT,Israel,L,Israel,50,"Data Visualization, Docker, Computer Vision, NLP",PhD,10,Education,2024-08-29,2024-11-03,1965,7.2,DeepTech Ventures -AI07600,AI Architect,266642,CAD,333303,EX,CT,Canada,L,Germany,0,"PyTorch, GCP, Azure, Mathematics, Statistics",Bachelor,16,Energy,2025-04-16,2025-05-08,1518,5.8,Smart Analytics -AI07601,ML Ops Engineer,73310,USD,73310,EN,FT,Norway,S,Brazil,0,"SQL, Statistics, MLOps, R",Associate,1,Retail,2024-04-26,2024-05-31,530,10,Machine Intelligence Group -AI07602,AI Software Engineer,175822,CHF,158240,MI,FT,Switzerland,L,Portugal,100,"Computer Vision, GCP, Linux, AWS, Tableau",PhD,3,Healthcare,2024-06-05,2024-07-13,1150,5,Neural Networks Co -AI07603,Machine Learning Researcher,82893,USD,82893,EN,FT,Israel,L,Romania,50,"Azure, MLOps, Kubernetes, Docker",PhD,0,Real Estate,2025-02-24,2025-04-14,1318,9.8,Advanced Robotics -AI07604,Computer Vision Engineer,121156,USD,121156,SE,PT,Finland,M,United States,100,"Mathematics, GCP, MLOps, Docker",Associate,7,Technology,2025-04-15,2025-05-01,1153,5.6,Machine Intelligence Group -AI07605,Machine Learning Engineer,85501,USD,85501,MI,CT,Ireland,S,Ireland,100,"Scala, NLP, Java, R",PhD,2,Energy,2024-05-01,2024-06-17,1409,9.7,Cloud AI Solutions -AI07606,Deep Learning Engineer,200592,USD,200592,EX,FL,Sweden,L,Sweden,100,"Scala, PyTorch, Tableau, Mathematics, Kubernetes",PhD,19,Automotive,2024-12-02,2024-12-17,714,6.3,DeepTech Ventures -AI07607,Data Analyst,157367,USD,157367,EX,FL,United States,S,Hungary,50,"MLOps, PyTorch, Kubernetes",PhD,18,Finance,2025-01-09,2025-02-05,1308,8.7,Digital Transformation LLC -AI07608,AI Architect,96408,USD,96408,MI,FL,Norway,S,Norway,50,"R, TensorFlow, SQL, Azure, Spark",Bachelor,4,Automotive,2024-03-23,2024-04-25,574,9,Cloud AI Solutions -AI07609,AI Research Scientist,41086,USD,41086,MI,CT,China,M,China,100,"TensorFlow, Docker, GCP",Bachelor,4,Telecommunications,2025-01-18,2025-03-03,1587,8.9,Quantum Computing Inc -AI07610,AI Architect,87699,EUR,74544,MI,CT,France,L,France,100,"R, PyTorch, Docker, TensorFlow, SQL",Bachelor,2,Government,2024-10-18,2024-11-29,2105,8.6,Predictive Systems -AI07611,AI Architect,173811,CHF,156430,SE,PT,Switzerland,S,Switzerland,0,"Python, PyTorch, Linux",Associate,7,Retail,2025-04-24,2025-05-21,1883,6.7,Cognitive Computing -AI07612,AI Product Manager,126276,EUR,107335,SE,FL,France,S,France,0,"Statistics, GCP, R, Git",Master,5,Government,2024-12-13,2025-01-13,1695,5.4,Quantum Computing Inc -AI07613,Computer Vision Engineer,242933,EUR,206493,EX,FL,Netherlands,M,Finland,100,"Spark, TensorFlow, Linux",PhD,11,Consulting,2024-12-16,2025-01-23,2045,6.3,AI Innovations -AI07614,Robotics Engineer,62515,USD,62515,EN,FL,United States,S,United States,50,"PyTorch, SQL, TensorFlow",Master,1,Media,2025-03-29,2025-04-14,871,7.3,Cognitive Computing -AI07615,AI Software Engineer,96579,USD,96579,SE,FT,Israel,M,Israel,100,"Scala, TensorFlow, Deep Learning",PhD,9,Telecommunications,2024-09-15,2024-11-10,1055,8.3,DataVision Ltd -AI07616,Machine Learning Researcher,66417,USD,66417,EN,FT,Norway,M,Norway,0,"R, NLP, Azure, Git, SQL",Master,0,Consulting,2024-11-07,2024-12-12,795,6.6,TechCorp Inc -AI07617,AI Product Manager,66775,USD,66775,EN,PT,Ireland,M,Mexico,100,"Computer Vision, Git, MLOps, NLP, TensorFlow",Master,0,Education,2024-02-29,2024-04-29,550,9.8,Predictive Systems -AI07618,Autonomous Systems Engineer,112618,SGD,146403,MI,PT,Singapore,L,Singapore,100,"AWS, PyTorch, Docker, TensorFlow, Scala",Associate,4,Finance,2025-02-04,2025-03-31,1936,6.3,Digital Transformation LLC -AI07619,AI Consultant,172134,USD,172134,SE,FT,Norway,M,Brazil,0,"Hadoop, Computer Vision, Python, Docker, GCP",Master,9,Finance,2024-08-12,2024-08-28,2319,6.3,Algorithmic Solutions -AI07620,Research Scientist,89513,EUR,76086,SE,FL,France,S,France,0,"Scala, Git, Python, Azure",Associate,6,Telecommunications,2024-08-08,2024-09-27,2056,6.2,Machine Intelligence Group -AI07621,Head of AI,124617,USD,124617,SE,FL,Denmark,S,Denmark,100,"Azure, NLP, Spark, Hadoop",Associate,9,Gaming,2025-03-19,2025-04-03,1175,7.2,Machine Intelligence Group -AI07622,NLP Engineer,211681,USD,211681,EX,FL,Sweden,S,Colombia,100,"Spark, Tableau, Kubernetes",Bachelor,13,Real Estate,2024-06-25,2024-07-23,2078,6.8,Digital Transformation LLC -AI07623,AI Architect,70756,USD,70756,EN,CT,Sweden,L,Czech Republic,100,"Python, NLP, AWS",PhD,1,Media,2025-03-21,2025-04-29,2181,8.7,Algorithmic Solutions -AI07624,AI Consultant,124712,EUR,106005,SE,PT,Germany,S,Germany,100,"Kubernetes, Tableau, Mathematics, MLOps, Git",Associate,8,Real Estate,2024-01-23,2024-03-07,2333,8,Digital Transformation LLC -AI07625,Research Scientist,81724,USD,81724,EN,FT,Ireland,L,Ireland,0,"Python, Azure, Mathematics, GCP, Statistics",Bachelor,0,Real Estate,2024-10-25,2024-11-21,2292,9.4,TechCorp Inc -AI07626,Data Scientist,98773,USD,98773,MI,FT,Ireland,L,Ireland,50,"TensorFlow, NLP, Git, Hadoop",Bachelor,4,Transportation,2024-04-20,2024-06-29,640,6.3,Future Systems -AI07627,NLP Engineer,123212,SGD,160176,SE,PT,Singapore,S,Singapore,0,"Azure, PyTorch, GCP",PhD,5,Transportation,2024-01-23,2024-03-03,1509,5.9,Future Systems -AI07628,AI Consultant,158235,EUR,134500,EX,CT,France,M,France,100,"Scala, Git, Data Visualization, AWS",PhD,11,Healthcare,2025-04-04,2025-05-28,2070,6.1,Machine Intelligence Group -AI07629,Robotics Engineer,243378,USD,243378,EX,FL,Finland,L,Japan,50,"Linux, Deep Learning, Python, SQL",Master,17,Manufacturing,2024-01-23,2024-03-15,1771,8.9,Smart Analytics -AI07630,Data Engineer,72159,SGD,93807,EN,CT,Singapore,L,Sweden,100,"GCP, Docker, MLOps",Associate,1,Education,2025-04-26,2025-06-29,1183,9,Machine Intelligence Group -AI07631,Computer Vision Engineer,117447,CAD,146809,SE,FT,Canada,M,Canada,50,"Git, Python, TensorFlow",Bachelor,7,Gaming,2025-02-25,2025-04-03,907,6.4,Predictive Systems -AI07632,Data Engineer,93398,EUR,79388,EN,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Data Visualization, Spark",PhD,0,Telecommunications,2024-09-21,2024-10-15,595,6.4,DeepTech Ventures -AI07633,Head of AI,130830,USD,130830,SE,FL,Sweden,L,Latvia,0,"Kubernetes, Python, Hadoop",Associate,5,Technology,2024-04-19,2024-05-25,1607,8.3,Quantum Computing Inc -AI07634,Data Engineer,226889,USD,226889,EX,PT,United States,S,Sweden,50,"GCP, Kubernetes, Data Visualization, Deep Learning, Hadoop",Bachelor,12,Retail,2025-02-02,2025-03-11,792,9,Cognitive Computing -AI07635,Data Engineer,81702,JPY,8987220,EN,FT,Japan,M,Japan,50,"SQL, GCP, Statistics",Associate,0,Consulting,2024-06-12,2024-07-20,504,5.3,Quantum Computing Inc -AI07636,AI Product Manager,111373,EUR,94667,SE,FL,Germany,S,Germany,0,"Mathematics, Python, Tableau, TensorFlow, PyTorch",Bachelor,6,Consulting,2025-01-05,2025-02-08,2037,6.3,Neural Networks Co -AI07637,Robotics Engineer,57310,USD,57310,MI,FL,South Korea,S,Switzerland,50,"Docker, NLP, Python, Kubernetes, Mathematics",Master,4,Telecommunications,2024-05-03,2024-06-27,1556,7.6,Smart Analytics -AI07638,Principal Data Scientist,43322,USD,43322,MI,FL,China,S,China,50,"Spark, Python, TensorFlow, Linux",PhD,3,Real Estate,2024-11-02,2024-12-10,1131,7.2,Predictive Systems -AI07639,Computer Vision Engineer,95292,CHF,85763,EN,PT,Switzerland,L,Switzerland,100,"Git, Hadoop, SQL, Computer Vision",Master,0,Education,2024-02-12,2024-03-25,1940,5.2,DataVision Ltd -AI07640,NLP Engineer,174223,GBP,130667,EX,FT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, Azure",Master,10,Telecommunications,2024-05-26,2024-06-19,981,7.2,DeepTech Ventures -AI07641,Machine Learning Engineer,84562,AUD,114159,MI,FT,Australia,M,Australia,100,"Linux, GCP, TensorFlow, Kubernetes, Statistics",Master,3,Technology,2024-11-09,2024-12-11,1796,5.3,DataVision Ltd -AI07642,Data Analyst,166804,AUD,225185,SE,FL,Australia,L,Philippines,100,"Tableau, Python, TensorFlow, Mathematics",Associate,7,Retail,2024-05-09,2024-07-10,745,5.4,Algorithmic Solutions -AI07643,AI Consultant,32768,USD,32768,EN,PT,China,L,China,50,"Python, SQL, Docker, Mathematics",Bachelor,1,Real Estate,2025-04-30,2025-05-24,1770,7.9,Cognitive Computing -AI07644,Head of AI,217646,EUR,184999,EX,PT,Netherlands,S,Brazil,50,"Spark, TensorFlow, Scala, Hadoop, MLOps",PhD,10,Healthcare,2024-12-10,2025-01-15,2225,8.5,TechCorp Inc -AI07645,Computer Vision Engineer,144258,EUR,122619,SE,FL,Netherlands,S,Netherlands,50,"PyTorch, R, Hadoop",Bachelor,5,Media,2025-01-25,2025-02-18,2300,9.7,DeepTech Ventures -AI07646,AI Architect,104597,USD,104597,SE,FL,South Korea,M,South Korea,100,"GCP, SQL, PyTorch, R",Bachelor,8,Transportation,2024-06-27,2024-07-28,1106,8.2,Neural Networks Co -AI07647,AI Specialist,95849,USD,95849,MI,FL,South Korea,L,South Korea,50,"Tableau, Kubernetes, PyTorch",Bachelor,4,Automotive,2024-11-06,2024-11-22,1076,6,DeepTech Ventures -AI07648,Computer Vision Engineer,265185,EUR,225407,EX,FT,Netherlands,L,Netherlands,50,"Python, PyTorch, Java, Computer Vision",Master,18,Energy,2024-12-14,2025-01-29,674,6.9,Predictive Systems -AI07649,AI Specialist,63417,EUR,53904,EN,CT,Austria,L,South Africa,50,"Linux, Scala, Kubernetes, GCP, Mathematics",PhD,1,Media,2024-10-09,2024-11-20,1572,9.6,Algorithmic Solutions -AI07650,Robotics Engineer,162111,USD,162111,SE,PT,Ireland,L,Thailand,50,"Docker, Statistics, GCP, Mathematics, PyTorch",PhD,8,Real Estate,2024-08-04,2024-10-06,1021,7,AI Innovations -AI07651,AI Architect,51830,USD,51830,EN,CT,South Korea,M,South Korea,0,"GCP, Scala, Tableau, PyTorch, Statistics",Bachelor,1,Energy,2024-08-04,2024-09-22,2067,9.2,Cloud AI Solutions -AI07652,AI Architect,80660,USD,80660,EN,CT,Denmark,L,Denmark,0,"Docker, AWS, MLOps",Bachelor,0,Energy,2024-11-03,2024-12-22,1825,5.3,Cognitive Computing -AI07653,Research Scientist,183478,USD,183478,SE,FT,Denmark,M,New Zealand,0,"Python, TensorFlow, Computer Vision, MLOps",PhD,8,Automotive,2024-02-24,2024-03-11,2350,9.6,Machine Intelligence Group -AI07654,Data Scientist,93839,EUR,79763,EN,FT,Netherlands,L,Netherlands,0,"TensorFlow, Spark, Computer Vision",Associate,1,Manufacturing,2024-01-22,2024-02-08,1415,5.5,Smart Analytics -AI07655,Machine Learning Engineer,63882,JPY,7027020,EN,FT,Japan,L,Japan,0,"Git, AWS, Python, Tableau, Linux",Associate,1,Technology,2024-02-27,2024-04-24,2251,6.2,DeepTech Ventures -AI07656,Data Analyst,126076,GBP,94557,SE,FT,United Kingdom,L,Ghana,50,"Data Visualization, SQL, Azure",Master,6,Finance,2024-02-11,2024-04-05,2026,9.8,DeepTech Ventures -AI07657,Principal Data Scientist,91813,JPY,10099430,MI,FL,Japan,S,Australia,100,"Scala, Data Visualization, Kubernetes, SQL, AWS",Master,3,Education,2024-07-23,2024-08-08,1170,7.6,DataVision Ltd -AI07658,AI Architect,44127,USD,44127,EN,PT,Finland,S,Finland,100,"SQL, Java, Data Visualization",Master,1,Media,2024-05-09,2024-06-05,2336,5,Predictive Systems -AI07659,AI Research Scientist,70724,CAD,88405,EN,FT,Canada,M,Canada,50,"Data Visualization, MLOps, SQL",Associate,0,Automotive,2024-01-20,2024-02-05,541,8,Advanced Robotics -AI07660,Data Analyst,306380,GBP,229785,EX,FT,United Kingdom,L,United Kingdom,50,"PyTorch, TensorFlow, Mathematics, Azure, R",Bachelor,16,Finance,2024-06-16,2024-07-03,1441,9.6,Digital Transformation LLC -AI07661,Data Scientist,59061,EUR,50202,EN,PT,Germany,S,Germany,100,"Scala, SQL, Data Visualization, TensorFlow, Git",Associate,0,Gaming,2024-08-28,2024-10-12,2199,5.2,Future Systems -AI07662,Data Scientist,127372,USD,127372,SE,PT,Denmark,S,Hungary,100,"GCP, AWS, Python, Linux",PhD,6,Telecommunications,2025-04-02,2025-06-10,1330,5.6,DataVision Ltd -AI07663,AI Software Engineer,324728,CHF,292255,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, Python, TensorFlow, Linux",PhD,13,Retail,2024-08-03,2024-09-23,1682,5.2,Smart Analytics -AI07664,AI Consultant,132294,USD,132294,SE,FT,Denmark,S,Denmark,100,"Data Visualization, Python, GCP",Master,7,Manufacturing,2024-01-22,2024-03-09,1383,7.8,AI Innovations -AI07665,Data Engineer,110217,EUR,93684,SE,FL,Germany,S,Germany,50,"R, Tableau, Azure, Python, Hadoop",Associate,7,Finance,2024-08-09,2024-08-29,2475,7.2,Smart Analytics -AI07666,Deep Learning Engineer,108463,USD,108463,MI,FL,Denmark,M,Brazil,50,"Statistics, SQL, Linux, NLP, Hadoop",PhD,4,Consulting,2024-04-24,2024-07-05,1652,8.4,AI Innovations -AI07667,AI Consultant,60083,USD,60083,MI,FL,South Korea,M,Italy,100,"AWS, Scala, Docker, NLP, Linux",PhD,2,Transportation,2025-02-19,2025-03-18,1564,8.2,Machine Intelligence Group -AI07668,NLP Engineer,74921,USD,74921,EX,CT,India,L,India,0,"TensorFlow, NLP, R, Python",PhD,11,Government,2024-02-28,2024-03-26,1818,6.1,Digital Transformation LLC -AI07669,AI Consultant,229930,CHF,206937,EX,FT,Switzerland,S,Kenya,0,"Java, GCP, Statistics, Python, TensorFlow",Associate,13,Retail,2024-05-12,2024-06-24,1945,9.9,Advanced Robotics -AI07670,Research Scientist,134348,CAD,167935,SE,FL,Canada,M,Canada,50,"NLP, Kubernetes, MLOps, Java",Bachelor,9,Transportation,2024-11-21,2025-01-17,2441,6.7,Neural Networks Co -AI07671,AI Research Scientist,84844,GBP,63633,MI,FT,United Kingdom,S,United Kingdom,50,"Scala, Hadoop, Data Visualization, Git, Python",Bachelor,2,Media,2024-12-14,2025-01-13,1273,8.1,Smart Analytics -AI07672,Computer Vision Engineer,75519,CAD,94399,MI,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP",PhD,2,Energy,2024-08-15,2024-09-15,2158,8.4,Machine Intelligence Group -AI07673,AI Specialist,83770,USD,83770,MI,FT,Finland,M,Switzerland,100,"Kubernetes, Scala, Statistics, PyTorch, NLP",PhD,4,Education,2024-12-21,2025-01-11,1827,6,Future Systems -AI07674,Computer Vision Engineer,99649,USD,99649,EN,PT,United States,L,Romania,100,"GCP, R, Data Visualization, SQL, Linux",Associate,1,Energy,2025-04-25,2025-05-14,1620,7.7,DeepTech Ventures -AI07675,Data Engineer,288454,USD,288454,EX,FT,Denmark,M,Denmark,100,"AWS, MLOps, GCP, Scala",Master,18,Consulting,2024-06-27,2024-08-26,1751,5.5,Cognitive Computing -AI07676,Research Scientist,185909,EUR,158023,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, TensorFlow, GCP, Statistics, Java",Associate,15,Telecommunications,2024-11-06,2024-12-19,1477,5.7,Digital Transformation LLC -AI07677,Robotics Engineer,82676,USD,82676,EN,FL,United States,M,United States,100,"AWS, Git, Data Visualization",Associate,0,Automotive,2024-03-03,2024-03-28,2443,6,Cognitive Computing -AI07678,Deep Learning Engineer,180023,USD,180023,EX,FT,South Korea,S,China,0,"Scala, GCP, Deep Learning, Data Visualization, Hadoop",Associate,11,Real Estate,2024-06-08,2024-07-05,2224,10,Quantum Computing Inc -AI07679,AI Consultant,85630,USD,85630,EN,PT,Ireland,L,Ireland,0,"Java, Kubernetes, Scala, Deep Learning, Computer Vision",Bachelor,0,Media,2025-04-02,2025-06-01,1688,9.3,Cognitive Computing -AI07680,AI Research Scientist,91309,EUR,77613,MI,FT,France,L,France,0,"Java, NLP, Linux, TensorFlow",Associate,4,Education,2024-08-20,2024-10-08,1703,7.9,Digital Transformation LLC -AI07681,AI Consultant,73734,EUR,62674,EN,FL,Austria,M,Austria,0,"Python, MLOps, PyTorch, R",PhD,1,Gaming,2024-04-15,2024-05-12,577,7.4,Predictive Systems -AI07682,Research Scientist,180469,USD,180469,EX,FT,Sweden,S,Sweden,50,"SQL, Python, MLOps, AWS",PhD,17,Government,2025-02-24,2025-05-08,2313,5.1,Smart Analytics -AI07683,Machine Learning Researcher,55451,EUR,47133,EN,CT,Austria,L,Austria,50,"Spark, Kubernetes, Statistics, Computer Vision, PyTorch",Master,1,Finance,2025-01-05,2025-02-21,1493,9.2,DeepTech Ventures -AI07684,Deep Learning Engineer,113073,USD,113073,EN,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Data Visualization, Python, R",PhD,0,Automotive,2024-11-28,2025-01-28,2139,9.3,Neural Networks Co -AI07685,Computer Vision Engineer,68363,EUR,58109,EN,FT,France,M,France,50,"Hadoop, Linux, Mathematics, Python",Master,0,Government,2024-08-12,2024-08-29,1755,9.5,Advanced Robotics -AI07686,Robotics Engineer,62860,USD,62860,EX,CT,China,S,China,50,"Hadoop, SQL, NLP",Associate,16,Real Estate,2024-06-30,2024-07-19,540,5.1,Predictive Systems -AI07687,NLP Engineer,176108,USD,176108,EX,PT,Ireland,S,Israel,50,"Python, Hadoop, Kubernetes, Scala, Git",Bachelor,11,Telecommunications,2024-05-30,2024-07-11,1478,5.2,TechCorp Inc -AI07688,AI Software Engineer,86453,EUR,73485,MI,FT,France,L,France,0,"Azure, GCP, Spark, Scala, Hadoop",Master,2,Real Estate,2024-07-20,2024-09-24,1547,8.2,Advanced Robotics -AI07689,Head of AI,170116,EUR,144599,EX,FL,Netherlands,L,Czech Republic,0,"Kubernetes, Java, Git, AWS, Computer Vision",PhD,17,Government,2025-02-23,2025-04-03,1237,5.5,Smart Analytics -AI07690,Principal Data Scientist,79589,EUR,67651,EN,CT,Netherlands,L,Sweden,50,"Python, TensorFlow, SQL, Linux",PhD,1,Government,2025-02-01,2025-02-20,1924,7.6,Cloud AI Solutions -AI07691,AI Architect,190789,USD,190789,EX,PT,Finland,S,Finland,50,"PyTorch, Tableau, SQL, Git",Bachelor,10,Education,2024-04-21,2024-06-12,659,9.9,Smart Analytics -AI07692,Data Engineer,79062,USD,79062,EN,PT,United States,M,United States,0,"Data Visualization, Docker, Mathematics",Bachelor,0,Telecommunications,2024-05-15,2024-07-10,1269,8.7,Algorithmic Solutions -AI07693,Deep Learning Engineer,212322,GBP,159242,EX,FL,United Kingdom,M,United Kingdom,0,"Python, Linux, SQL",Bachelor,14,Retail,2024-11-16,2025-01-19,651,8.2,TechCorp Inc -AI07694,Machine Learning Engineer,126710,CAD,158388,SE,FT,Canada,M,Turkey,0,"Git, Kubernetes, GCP, Spark, NLP",Bachelor,6,Healthcare,2024-03-20,2024-05-14,804,8.2,Autonomous Tech -AI07695,Deep Learning Engineer,135567,SGD,176237,SE,FT,Singapore,S,Singapore,100,"Python, Hadoop, SQL, Data Visualization, NLP",Associate,5,Transportation,2024-08-28,2024-09-22,1554,5.1,AI Innovations -AI07696,Autonomous Systems Engineer,77684,GBP,58263,MI,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, AWS, Azure, R",Associate,2,Finance,2024-02-19,2024-03-31,1848,6.3,Quantum Computing Inc -AI07697,Head of AI,87101,CHF,78391,EN,FT,Switzerland,S,Switzerland,50,"TensorFlow, AWS, Mathematics, NLP",PhD,1,Automotive,2024-04-24,2024-05-21,1700,6.2,Quantum Computing Inc -AI07698,Head of AI,65182,USD,65182,EN,FL,Ireland,L,Ireland,100,"NLP, Statistics, SQL, Data Visualization",Master,0,Manufacturing,2024-05-12,2024-06-23,1768,7.2,Predictive Systems -AI07699,Research Scientist,155741,JPY,17131510,SE,CT,Japan,L,Sweden,50,"SQL, Tableau, NLP, Data Visualization, Azure",Master,8,Automotive,2024-06-02,2024-06-19,590,9.5,Advanced Robotics -AI07700,Computer Vision Engineer,35630,USD,35630,MI,PT,India,M,Russia,100,"Scala, R, Deep Learning, Computer Vision, GCP",PhD,2,Gaming,2024-04-07,2024-05-14,501,7.2,Cognitive Computing -AI07701,Machine Learning Engineer,92685,EUR,78782,EN,PT,Netherlands,L,Philippines,50,"Hadoop, Statistics, Scala, TensorFlow, NLP",Master,0,Automotive,2025-03-28,2025-05-08,1696,9.5,Digital Transformation LLC -AI07702,Machine Learning Engineer,63966,EUR,54371,EN,FT,France,S,France,50,"Spark, Python, Statistics",Associate,0,Government,2024-03-03,2024-03-19,562,6.7,TechCorp Inc -AI07703,Data Scientist,193308,AUD,260966,EX,FL,Australia,L,Italy,50,"Azure, Hadoop, SQL, Python",Associate,19,Media,2024-10-08,2024-11-08,2482,8.6,Quantum Computing Inc -AI07704,AI Architect,68810,JPY,7569100,EN,PT,Japan,M,Japan,50,"Linux, Statistics, Python",Bachelor,0,Technology,2024-01-09,2024-02-05,1000,5.1,DataVision Ltd -AI07705,Head of AI,133424,CHF,120082,MI,PT,Switzerland,S,Switzerland,50,"R, Deep Learning, SQL",Associate,2,Finance,2025-03-19,2025-05-25,2253,8.2,Cloud AI Solutions -AI07706,Head of AI,99725,CHF,89753,MI,PT,Switzerland,S,Switzerland,0,"Python, Statistics, Java, TensorFlow",Associate,3,Telecommunications,2024-03-25,2024-05-07,1474,9,Cognitive Computing -AI07707,Principal Data Scientist,92186,USD,92186,MI,CT,Finland,M,Finland,100,"Mathematics, Python, MLOps, Kubernetes, Linux",Associate,3,Consulting,2025-02-12,2025-02-27,1793,6.8,Advanced Robotics -AI07708,AI Consultant,67420,EUR,57307,MI,CT,France,S,France,0,"Scala, AWS, Tableau",Master,4,Telecommunications,2025-04-17,2025-06-03,1056,7.9,Future Systems -AI07709,ML Ops Engineer,63821,CAD,79776,EN,CT,Canada,L,South Korea,50,"TensorFlow, Tableau, Statistics, Java, Linux",PhD,0,Finance,2025-03-14,2025-04-14,1786,7.2,TechCorp Inc -AI07710,ML Ops Engineer,79858,JPY,8784380,MI,PT,Japan,M,Finland,100,"Tableau, Statistics, Hadoop, Scala, Python",Bachelor,2,Media,2024-08-07,2024-08-22,1849,9.5,AI Innovations -AI07711,Autonomous Systems Engineer,92037,GBP,69028,MI,CT,United Kingdom,S,United Kingdom,50,"Python, MLOps, GCP, TensorFlow, Tableau",PhD,3,Telecommunications,2024-05-26,2024-07-15,1867,7.2,Future Systems -AI07712,Deep Learning Engineer,145429,JPY,15997190,SE,CT,Japan,L,Japan,0,"NLP, PyTorch, SQL, R, Kubernetes",Bachelor,6,Healthcare,2024-04-17,2024-05-27,1406,7.6,DeepTech Ventures -AI07713,ML Ops Engineer,49642,USD,49642,EN,FT,South Korea,M,South Korea,50,"Git, Data Visualization, Scala, Python",Bachelor,1,Healthcare,2024-07-27,2024-09-05,1285,5.5,Quantum Computing Inc -AI07714,NLP Engineer,123567,SGD,160637,SE,FT,Singapore,M,Singapore,0,"Git, Java, Tableau",Associate,9,Transportation,2025-01-07,2025-02-19,2046,8.7,Autonomous Tech -AI07715,AI Architect,110776,CHF,99698,EN,FL,Switzerland,M,Switzerland,50,"SQL, Java, Hadoop, Azure, Python",Associate,1,Transportation,2024-10-17,2024-11-13,1304,8.6,Neural Networks Co -AI07716,Principal Data Scientist,173372,AUD,234052,EX,PT,Australia,M,Australia,50,"Deep Learning, Python, Spark, Hadoop, Mathematics",Bachelor,16,Transportation,2024-11-01,2024-12-28,519,9.9,DataVision Ltd -AI07717,Autonomous Systems Engineer,66211,EUR,56279,EN,CT,Germany,L,Germany,100,"Git, Hadoop, Spark, TensorFlow, Java",PhD,1,Gaming,2024-11-22,2024-12-28,2210,9.7,Cognitive Computing -AI07718,Data Scientist,152011,SGD,197614,SE,FT,Singapore,L,Japan,0,"Docker, Linux, Computer Vision, SQL, PyTorch",PhD,5,Transportation,2024-05-29,2024-06-30,501,5.5,Algorithmic Solutions -AI07719,ML Ops Engineer,227332,SGD,295532,EX,FL,Singapore,S,Singapore,50,"Python, Hadoop, SQL, Azure",Bachelor,19,Education,2025-01-15,2025-03-15,1975,8.9,TechCorp Inc -AI07720,Robotics Engineer,124845,CAD,156056,EX,FT,Canada,S,Romania,100,"SQL, NLP, Azure, Statistics, Python",Associate,15,Retail,2024-03-05,2024-05-14,1059,6.6,Machine Intelligence Group -AI07721,NLP Engineer,88027,SGD,114435,MI,FT,Singapore,M,Singapore,0,"PyTorch, Computer Vision, MLOps, Docker",PhD,3,Real Estate,2024-07-28,2024-09-23,652,8.2,Autonomous Tech -AI07722,Head of AI,160105,USD,160105,SE,PT,Ireland,L,Ireland,50,"Python, Kubernetes, Linux",Master,6,Real Estate,2024-01-31,2024-03-13,1280,9,Machine Intelligence Group -AI07723,AI Research Scientist,45928,USD,45928,SE,FT,India,M,India,0,"Linux, Git, Tableau, Data Visualization",Bachelor,7,Media,2024-10-08,2024-12-05,2291,7.7,Smart Analytics -AI07724,Head of AI,71793,USD,71793,EN,CT,Denmark,M,Denmark,100,"Linux, PyTorch, Computer Vision, Git",Bachelor,1,Automotive,2024-12-08,2024-12-23,1035,6.7,Algorithmic Solutions -AI07725,AI Research Scientist,250916,USD,250916,EX,FT,Norway,L,Norway,0,"Deep Learning, Linux, MLOps, NLP, Tableau",PhD,12,Manufacturing,2024-10-26,2024-11-21,1614,6.4,Future Systems -AI07726,Data Scientist,174103,USD,174103,SE,FL,Denmark,L,Denmark,0,"Git, Linux, NLP, Spark",Associate,6,Manufacturing,2024-04-07,2024-06-14,2322,5.4,Advanced Robotics -AI07727,Principal Data Scientist,109543,GBP,82157,MI,PT,United Kingdom,L,United Kingdom,50,"Azure, Python, GCP, Deep Learning, TensorFlow",Associate,2,Healthcare,2024-10-22,2024-12-07,2284,5.4,TechCorp Inc -AI07728,Robotics Engineer,87605,USD,87605,EN,PT,Ireland,L,Ireland,0,"Azure, Python, Kubernetes, Tableau, TensorFlow",PhD,0,Manufacturing,2024-11-23,2024-12-12,1772,5,Predictive Systems -AI07729,AI Software Engineer,146983,EUR,124936,SE,CT,Germany,M,Germany,0,"Spark, AWS, Git, MLOps",Master,9,Real Estate,2024-04-24,2024-05-16,2162,6.3,Cognitive Computing -AI07730,Deep Learning Engineer,102384,USD,102384,SE,CT,Sweden,M,Brazil,50,"R, Deep Learning, Data Visualization, Hadoop, AWS",Master,8,Technology,2024-06-17,2024-08-22,846,6.4,Predictive Systems -AI07731,AI Research Scientist,261474,JPY,28762140,EX,CT,Japan,L,Japan,50,"Computer Vision, GCP, NLP, Kubernetes, Java",Associate,18,Transportation,2024-04-29,2024-05-21,1030,8.1,Advanced Robotics -AI07732,Data Analyst,74595,CAD,93244,EN,FL,Canada,L,Canada,0,"SQL, Computer Vision, PyTorch, Statistics, Kubernetes",Associate,0,Government,2024-02-17,2024-04-28,736,9,DeepTech Ventures -AI07733,Head of AI,96835,USD,96835,EX,CT,China,L,United Kingdom,0,"Kubernetes, Hadoop, Computer Vision",PhD,18,Government,2024-05-01,2024-06-28,1151,6,Quantum Computing Inc -AI07734,Machine Learning Researcher,136419,USD,136419,MI,PT,Denmark,L,Denmark,0,"Python, Hadoop, Deep Learning, TensorFlow",Master,2,Manufacturing,2024-05-11,2024-06-22,1928,6.7,Digital Transformation LLC -AI07735,Autonomous Systems Engineer,62698,USD,62698,SE,FL,China,L,China,100,"Hadoop, Python, Tableau",Associate,9,Energy,2024-01-01,2024-02-07,512,7,Machine Intelligence Group -AI07736,AI Architect,82570,GBP,61928,MI,PT,United Kingdom,M,Turkey,50,"Scala, Git, Tableau, Computer Vision",Bachelor,4,Retail,2024-04-22,2024-05-06,1986,5.6,Predictive Systems -AI07737,Autonomous Systems Engineer,63993,EUR,54394,EN,FT,France,S,Chile,50,"Scala, SQL, Git, Linux",PhD,1,Energy,2024-04-22,2024-07-02,2119,5.6,Quantum Computing Inc -AI07738,Deep Learning Engineer,117183,USD,117183,MI,FT,Israel,L,Israel,0,"TensorFlow, AWS, PyTorch",Master,4,Technology,2024-03-29,2024-05-15,615,8.3,Smart Analytics -AI07739,NLP Engineer,228120,SGD,296556,EX,CT,Singapore,S,Estonia,50,"Kubernetes, Data Visualization, GCP, Scala, Computer Vision",PhD,18,Media,2024-05-29,2024-07-11,982,6.3,Predictive Systems -AI07740,Autonomous Systems Engineer,168150,USD,168150,EX,FL,Ireland,S,Ireland,100,"SQL, Docker, NLP, Mathematics, Computer Vision",Bachelor,10,Telecommunications,2024-07-10,2024-08-22,2461,7.6,DataVision Ltd -AI07741,Data Engineer,251868,EUR,214088,EX,PT,Netherlands,L,Netherlands,0,"Java, Spark, TensorFlow",PhD,10,Energy,2025-02-27,2025-05-01,2060,6,Future Systems -AI07742,AI Consultant,134610,EUR,114419,SE,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, PyTorch, Linux",Associate,9,Healthcare,2024-01-03,2024-02-22,2155,9.1,DeepTech Ventures -AI07743,Data Scientist,39473,USD,39473,MI,PT,China,M,Poland,0,"Hadoop, Linux, R, Git, SQL",PhD,2,Government,2024-03-09,2024-04-07,1821,7.2,DataVision Ltd -AI07744,Data Engineer,59378,EUR,50471,EN,FT,Germany,S,Germany,50,"Python, AWS, Java",Bachelor,1,Telecommunications,2025-04-22,2025-06-15,1884,5.9,Cognitive Computing -AI07745,AI Research Scientist,126770,EUR,107755,SE,CT,Austria,L,Austria,0,"Docker, Kubernetes, Azure, MLOps",Master,6,Retail,2024-04-12,2024-06-15,1519,5.6,Cloud AI Solutions -AI07746,AI Research Scientist,78592,CAD,98240,MI,CT,Canada,S,Canada,100,"R, TensorFlow, Deep Learning, Git, Docker",Bachelor,2,Retail,2024-11-13,2024-12-29,1997,8,Quantum Computing Inc -AI07747,Deep Learning Engineer,29559,USD,29559,MI,CT,India,L,India,0,"Hadoop, Deep Learning, Java, Tableau",Associate,2,Healthcare,2024-10-04,2024-11-04,754,7,Cloud AI Solutions -AI07748,AI Software Engineer,223895,USD,223895,EX,CT,Sweden,L,Brazil,100,"SQL, AWS, Deep Learning, Statistics, Data Visualization",Master,12,Gaming,2025-01-02,2025-02-11,793,9.4,AI Innovations -AI07749,Principal Data Scientist,170881,AUD,230689,SE,PT,Australia,L,Japan,0,"PyTorch, MLOps, TensorFlow",Bachelor,8,Technology,2024-09-07,2024-10-26,1484,8.9,AI Innovations -AI07750,AI Architect,77100,SGD,100230,MI,FL,Singapore,M,Vietnam,0,"SQL, Git, Data Visualization, PyTorch",Associate,4,Telecommunications,2024-11-01,2024-12-03,1851,8.6,Smart Analytics -AI07751,AI Research Scientist,61337,EUR,52136,EN,PT,France,L,France,0,"Linux, Statistics, Computer Vision",Bachelor,1,Energy,2025-04-29,2025-06-14,1576,9.8,Machine Intelligence Group -AI07752,Data Engineer,90203,AUD,121774,MI,FT,Australia,M,Australia,0,"Linux, Python, Data Visualization, MLOps",Bachelor,2,Manufacturing,2024-07-18,2024-09-13,1980,9.1,Smart Analytics -AI07753,AI Software Engineer,95206,USD,95206,EX,CT,India,L,India,0,"GCP, Scala, Java, Azure",Master,19,Finance,2024-12-17,2025-02-12,1590,8.3,Smart Analytics -AI07754,Machine Learning Engineer,143694,CHF,129325,SE,CT,Switzerland,S,Switzerland,100,"PyTorch, Java, SQL, MLOps, Deep Learning",Associate,7,Transportation,2024-07-13,2024-09-02,1769,5.7,Neural Networks Co -AI07755,AI Software Engineer,205240,CAD,256550,EX,FT,Canada,S,Canada,0,"TensorFlow, Kubernetes, Statistics, R, MLOps",PhD,19,Technology,2024-10-05,2024-11-02,2041,7.4,Future Systems -AI07756,Principal Data Scientist,130858,CAD,163573,SE,FL,Canada,L,Canada,100,"Computer Vision, SQL, PyTorch",Bachelor,5,Consulting,2024-01-14,2024-03-11,835,9.6,DataVision Ltd -AI07757,AI Specialist,109839,USD,109839,MI,PT,Norway,M,Norway,0,"Tableau, AWS, Python",PhD,2,Energy,2025-01-19,2025-03-22,2213,5.6,Digital Transformation LLC -AI07758,AI Architect,234658,EUR,199459,EX,CT,Germany,L,Germany,0,"Computer Vision, GCP, TensorFlow, Deep Learning, Java",Associate,14,Gaming,2025-03-18,2025-05-21,1240,7.2,Cloud AI Solutions -AI07759,Computer Vision Engineer,212824,USD,212824,EX,FL,Israel,S,United States,50,"AWS, GCP, Data Visualization, Computer Vision",Associate,18,Technology,2024-08-27,2024-10-08,1963,9.2,Smart Analytics -AI07760,Computer Vision Engineer,89614,EUR,76172,MI,FT,France,S,France,100,"TensorFlow, Linux, MLOps, R",Master,4,Gaming,2024-09-11,2024-09-26,1242,7.8,DeepTech Ventures -AI07761,AI Research Scientist,230152,EUR,195629,EX,PT,Germany,L,Germany,50,"Python, AWS, Computer Vision, TensorFlow, Mathematics",Bachelor,16,Real Estate,2025-04-05,2025-05-20,2279,5.6,Algorithmic Solutions -AI07762,Machine Learning Engineer,138749,USD,138749,EX,FT,Finland,M,Philippines,0,"Data Visualization, MLOps, Java, R, NLP",Bachelor,17,Retail,2024-06-28,2024-08-19,997,5.1,TechCorp Inc -AI07763,Data Scientist,151433,USD,151433,SE,FL,Denmark,M,Denmark,0,"Linux, Git, AWS, Tableau, SQL",PhD,6,Manufacturing,2024-05-09,2024-07-12,698,7.8,Cognitive Computing -AI07764,Head of AI,113027,USD,113027,MI,FL,United States,M,United States,50,"Scala, Spark, Computer Vision",Master,2,Government,2024-11-12,2025-01-13,522,5.4,Smart Analytics -AI07765,AI Architect,75238,USD,75238,EN,PT,United States,M,Sweden,0,"MLOps, Data Visualization, Statistics, PyTorch",PhD,0,Government,2024-12-04,2024-12-19,2206,6.3,DeepTech Ventures -AI07766,Data Scientist,181300,SGD,235690,EX,CT,Singapore,M,Singapore,0,"Python, GCP, Computer Vision",Bachelor,12,Consulting,2024-04-23,2024-05-28,1081,6.4,DeepTech Ventures -AI07767,Data Analyst,180520,USD,180520,EX,FL,Israel,S,Israel,0,"NLP, Spark, Git",Bachelor,16,Real Estate,2025-03-25,2025-04-14,2169,9.4,Digital Transformation LLC -AI07768,AI Research Scientist,60195,GBP,45146,EN,CT,United Kingdom,S,United Kingdom,100,"R, Python, Tableau, Scala",Bachelor,1,Government,2025-03-01,2025-05-12,2478,7.9,TechCorp Inc -AI07769,Deep Learning Engineer,85237,SGD,110808,EN,FL,Singapore,L,Ghana,50,"Python, Kubernetes, Docker, TensorFlow, SQL",PhD,1,Retail,2024-03-03,2024-05-06,2404,9.4,Advanced Robotics -AI07770,Computer Vision Engineer,120221,USD,120221,SE,FL,Norway,S,New Zealand,100,"Scala, PyTorch, Hadoop, Git, GCP",PhD,8,Government,2024-10-03,2024-12-12,651,7,Cognitive Computing -AI07771,Data Engineer,196214,USD,196214,EX,FT,Finland,M,Finland,50,"Linux, Java, GCP, TensorFlow, NLP",Master,14,Automotive,2024-02-01,2024-03-09,1141,9.8,Advanced Robotics -AI07772,AI Consultant,132988,CAD,166235,SE,FT,Canada,M,Canada,0,"Python, Hadoop, MLOps, TensorFlow, Mathematics",Bachelor,6,Media,2024-06-08,2024-08-09,2131,7.3,Digital Transformation LLC -AI07773,Data Analyst,77664,USD,77664,EN,PT,Ireland,M,Ireland,0,"NLP, Docker, Tableau",PhD,0,Energy,2025-03-06,2025-04-14,2381,6.8,Future Systems -AI07774,Robotics Engineer,148890,CAD,186113,SE,FT,Canada,L,Canada,50,"Scala, Linux, MLOps, Spark, Git",Master,9,Automotive,2025-01-27,2025-03-22,1437,8.6,Machine Intelligence Group -AI07775,Head of AI,95335,USD,95335,MI,PT,Israel,L,China,100,"Python, Hadoop, MLOps",Bachelor,2,Finance,2025-04-12,2025-04-30,2096,9.5,Machine Intelligence Group -AI07776,AI Software Engineer,60390,USD,60390,SE,FT,China,M,China,100,"SQL, GCP, PyTorch, Java",Master,5,Healthcare,2024-02-02,2024-03-19,1377,5.8,TechCorp Inc -AI07777,AI Specialist,113740,CHF,102366,EN,FT,Switzerland,L,Switzerland,50,"Kubernetes, TensorFlow, Python, Linux, Computer Vision",Associate,1,Manufacturing,2024-03-30,2024-05-12,646,7.9,DeepTech Ventures -AI07778,Research Scientist,107116,EUR,91049,SE,PT,France,S,Russia,0,"NLP, PyTorch, AWS, Linux, Computer Vision",Bachelor,5,Automotive,2024-05-31,2024-06-18,1158,9.5,Future Systems -AI07779,Data Scientist,116275,USD,116275,EX,PT,China,L,China,50,"Scala, Java, Spark, Docker",Master,17,Media,2024-03-16,2024-04-07,1611,9,DeepTech Ventures -AI07780,AI Product Manager,75695,EUR,64341,MI,FT,Austria,S,South Korea,50,"Linux, Hadoop, SQL, Spark, Java",Master,4,Education,2024-11-06,2025-01-05,984,5.6,Predictive Systems -AI07781,ML Ops Engineer,123821,EUR,105248,SE,FT,Austria,M,Austria,50,"Kubernetes, Spark, MLOps, NLP",Bachelor,8,Technology,2024-03-08,2024-05-09,2226,8.8,AI Innovations -AI07782,Data Engineer,220673,USD,220673,EX,CT,Ireland,L,Switzerland,50,"Docker, Hadoop, PyTorch, Git",PhD,19,Telecommunications,2024-11-27,2025-02-03,2497,5.6,Smart Analytics -AI07783,ML Ops Engineer,69580,EUR,59143,MI,CT,Netherlands,S,Netherlands,0,"NLP, Git, Kubernetes, Tableau",Master,3,Media,2024-01-10,2024-02-25,752,6.3,Digital Transformation LLC -AI07784,NLP Engineer,64614,USD,64614,EN,CT,Finland,S,Finland,0,"Git, R, Spark, Data Visualization",Master,1,Telecommunications,2024-11-29,2025-01-05,1789,6.1,Cognitive Computing -AI07785,Data Engineer,100944,EUR,85802,SE,CT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch",Master,8,Healthcare,2024-04-10,2024-06-15,1527,6.9,Advanced Robotics -AI07786,Machine Learning Engineer,35266,USD,35266,MI,PT,India,M,India,0,"AWS, SQL, Hadoop, Docker, Computer Vision",PhD,4,Automotive,2024-11-16,2024-11-30,761,7.4,Advanced Robotics -AI07787,AI Software Engineer,79263,AUD,107005,EN,FL,Australia,M,Vietnam,50,"Git, Hadoop, PyTorch",Master,1,Gaming,2024-06-11,2024-07-04,1102,7.8,Smart Analytics -AI07788,Data Scientist,94630,USD,94630,MI,CT,Sweden,S,Sweden,0,"Data Visualization, Azure, Kubernetes, GCP, SQL",PhD,4,Government,2025-02-15,2025-04-03,680,7.7,Neural Networks Co -AI07789,AI Research Scientist,290745,EUR,247133,EX,FT,Netherlands,L,Netherlands,0,"Docker, Linux, AWS",Bachelor,16,Energy,2024-11-05,2024-11-27,2383,7.5,Cloud AI Solutions -AI07790,Computer Vision Engineer,177261,USD,177261,SE,FL,Denmark,M,Vietnam,0,"Azure, PyTorch, SQL, Docker, R",Associate,9,Energy,2024-08-05,2024-10-13,1377,10,Future Systems -AI07791,AI Consultant,79754,SGD,103680,MI,FT,Singapore,S,Singapore,0,"Spark, Computer Vision, Linux, AWS, Statistics",Master,3,Telecommunications,2024-02-15,2024-03-21,970,5.9,AI Innovations -AI07792,AI Specialist,179275,USD,179275,EX,FL,Finland,L,United States,50,"R, AWS, Deep Learning",Master,17,Media,2024-12-11,2025-02-05,2187,5.7,Smart Analytics -AI07793,AI Consultant,120982,CHF,108884,MI,FT,Switzerland,L,Switzerland,0,"Statistics, MLOps, TensorFlow, Java",Master,4,Transportation,2024-01-14,2024-03-19,1448,8,Machine Intelligence Group -AI07794,Data Scientist,56033,USD,56033,EN,FL,Israel,L,Israel,100,"Deep Learning, TensorFlow, Data Visualization, PyTorch",Associate,1,Education,2025-01-20,2025-03-11,1633,8.3,Smart Analytics -AI07795,AI Product Manager,43195,USD,43195,SE,CT,India,L,India,0,"R, Java, Python, Statistics, TensorFlow",Bachelor,6,Technology,2024-06-11,2024-08-05,1479,9.9,Predictive Systems -AI07796,AI Software Engineer,95245,USD,95245,EN,FL,United States,L,Ukraine,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,0,Technology,2024-01-18,2024-03-21,1994,6.3,TechCorp Inc -AI07797,Deep Learning Engineer,68796,USD,68796,MI,PT,South Korea,L,South Korea,0,"Hadoop, Python, Tableau, MLOps, Computer Vision",PhD,4,Education,2024-09-23,2024-10-28,1211,5.1,Future Systems -AI07798,AI Architect,236279,CHF,212651,SE,PT,Switzerland,L,Israel,50,"Kubernetes, SQL, Linux, PyTorch",Master,9,Education,2025-03-05,2025-05-07,1087,6.4,TechCorp Inc -AI07799,Deep Learning Engineer,67944,AUD,91724,EN,CT,Australia,M,Australia,50,"Deep Learning, Kubernetes, Spark, Git",Associate,0,Retail,2025-04-04,2025-05-10,2112,5.6,Predictive Systems -AI07800,Computer Vision Engineer,89810,USD,89810,MI,CT,Denmark,S,Malaysia,100,"Deep Learning, TensorFlow, SQL, Hadoop",Bachelor,4,Media,2024-10-02,2024-11-17,1632,8.6,Machine Intelligence Group -AI07801,Computer Vision Engineer,153315,CAD,191644,EX,FL,Canada,L,Portugal,0,"Java, R, SQL, Deep Learning, Docker",Associate,13,Consulting,2024-11-22,2024-12-17,1764,7.7,TechCorp Inc -AI07802,Machine Learning Researcher,205401,USD,205401,EX,FT,Denmark,M,Denmark,100,"R, TensorFlow, Mathematics",PhD,10,Healthcare,2024-03-18,2024-05-24,1464,8.4,Smart Analytics -AI07803,Robotics Engineer,57780,CAD,72225,EN,PT,Canada,S,Canada,100,"Java, NLP, Mathematics",PhD,1,Retail,2024-10-31,2025-01-10,2381,9.8,TechCorp Inc -AI07804,AI Research Scientist,110762,USD,110762,MI,CT,Norway,L,Sweden,100,"R, Data Visualization, Git, Docker",PhD,2,Real Estate,2024-11-03,2024-12-19,777,6.8,Cognitive Computing -AI07805,Deep Learning Engineer,157791,EUR,134122,SE,FL,France,L,France,50,"Git, Java, GCP, SQL, AWS",PhD,9,Gaming,2024-10-16,2024-11-01,1818,7.8,Cognitive Computing -AI07806,AI Software Engineer,146629,USD,146629,SE,PT,Denmark,S,Denmark,50,"Git, TensorFlow, Deep Learning",Associate,8,Manufacturing,2025-04-25,2025-06-02,1219,8.6,Autonomous Tech -AI07807,AI Consultant,67825,USD,67825,MI,FT,Sweden,S,Poland,100,"Java, Scala, R, SQL, Kubernetes",PhD,3,Education,2025-03-26,2025-06-03,1845,7.4,Autonomous Tech -AI07808,Autonomous Systems Engineer,53522,USD,53522,SE,FL,China,S,China,0,"PyTorch, GCP, Mathematics",Associate,9,Gaming,2025-04-19,2025-05-20,1898,8.6,Future Systems -AI07809,Robotics Engineer,96556,CAD,120695,MI,FT,Canada,L,Portugal,100,"PyTorch, Statistics, Deep Learning",Associate,4,Gaming,2024-10-10,2024-11-19,1150,9.1,DataVision Ltd -AI07810,AI Consultant,161008,USD,161008,SE,CT,Israel,L,Israel,0,"Docker, Deep Learning, Python, Git, Kubernetes",Master,9,Education,2025-03-25,2025-05-08,1648,5.7,Cognitive Computing -AI07811,Head of AI,71917,JPY,7910870,EN,PT,Japan,M,Hungary,100,"Tableau, PyTorch, GCP",Master,1,Media,2024-11-04,2024-12-29,2269,9.6,Neural Networks Co -AI07812,AI Research Scientist,143195,CAD,178994,EX,FL,Canada,S,Canada,50,"Java, Linux, Scala, NLP, Tableau",PhD,13,Healthcare,2025-04-12,2025-06-07,510,5.3,Neural Networks Co -AI07813,Robotics Engineer,135878,SGD,176641,SE,FT,Singapore,S,Singapore,0,"Azure, Kubernetes, Tableau",Bachelor,9,Technology,2024-12-28,2025-02-13,772,8.2,AI Innovations -AI07814,AI Consultant,58123,USD,58123,EN,PT,Finland,L,Finland,50,"Linux, AWS, GCP",Master,1,Manufacturing,2025-01-22,2025-02-10,1596,7.8,Digital Transformation LLC -AI07815,Principal Data Scientist,85459,USD,85459,EX,FT,India,M,Estonia,0,"Scala, Spark, AWS, Statistics",Master,16,Technology,2024-09-10,2024-11-20,1167,7.5,Advanced Robotics -AI07816,AI Consultant,188011,EUR,159809,EX,FL,Germany,S,Germany,0,"SQL, Kubernetes, Tableau",Bachelor,10,Transportation,2024-05-26,2024-07-10,2353,5.7,TechCorp Inc -AI07817,NLP Engineer,76608,USD,76608,EN,CT,United States,M,United States,100,"Hadoop, Spark, Python, GCP, SQL",Associate,1,Transportation,2024-11-19,2025-01-29,617,6.1,AI Innovations -AI07818,Computer Vision Engineer,87288,GBP,65466,MI,PT,United Kingdom,M,Egypt,50,"Statistics, Kubernetes, Tableau, Linux",Master,4,Energy,2024-08-22,2024-09-09,1983,8.5,Cloud AI Solutions -AI07819,AI Specialist,114472,JPY,12591920,SE,CT,Japan,S,France,50,"Mathematics, Hadoop, Spark, Tableau, GCP",Bachelor,5,Education,2024-10-03,2024-11-30,1545,8.3,DeepTech Ventures -AI07820,AI Research Scientist,115293,GBP,86470,MI,CT,United Kingdom,M,Romania,0,"PyTorch, Kubernetes, Deep Learning, Git",Associate,4,Finance,2024-01-17,2024-03-21,1165,6.1,AI Innovations -AI07821,Deep Learning Engineer,85770,USD,85770,SE,PT,South Korea,S,South Korea,50,"GCP, Computer Vision, Hadoop, Azure",PhD,7,Government,2024-08-30,2024-10-31,2128,9.5,Digital Transformation LLC -AI07822,Computer Vision Engineer,153843,EUR,130767,EX,FT,France,M,France,50,"Python, Tableau, SQL, PyTorch, Hadoop",Bachelor,16,Education,2025-02-23,2025-03-23,1151,9.8,DeepTech Ventures -AI07823,NLP Engineer,119824,CHF,107842,MI,FL,Switzerland,M,Switzerland,50,"Linux, Computer Vision, R, Python",PhD,3,Technology,2025-04-25,2025-05-13,2109,8.8,Neural Networks Co -AI07824,Data Engineer,88480,EUR,75208,MI,FL,Germany,M,Finland,100,"PyTorch, Kubernetes, MLOps, Scala, Java",Master,4,Energy,2024-02-16,2024-04-08,1029,9.3,DeepTech Ventures -AI07825,AI Research Scientist,86607,USD,86607,SE,PT,Finland,S,Finland,100,"GCP, AWS, MLOps",PhD,7,Consulting,2024-04-24,2024-05-12,2162,8.8,Digital Transformation LLC -AI07826,AI Research Scientist,185098,EUR,157333,EX,FL,Netherlands,M,Netherlands,50,"Docker, Azure, Git, Deep Learning",Bachelor,18,Gaming,2024-04-11,2024-05-28,902,5.8,AI Innovations -AI07827,AI Specialist,42629,USD,42629,EN,FT,South Korea,S,Sweden,0,"Spark, Hadoop, Tableau",Bachelor,0,Energy,2024-07-06,2024-07-21,1250,5.1,Cloud AI Solutions -AI07828,AI Architect,73796,EUR,62727,EN,FL,France,L,France,100,"Deep Learning, SQL, PyTorch",Bachelor,0,Government,2024-06-09,2024-07-23,2437,5.8,Cognitive Computing -AI07829,AI Consultant,145709,USD,145709,EX,FT,United States,S,Mexico,100,"Python, Azure, Tableau, Statistics",Bachelor,18,Energy,2024-09-11,2024-09-26,1740,7.9,TechCorp Inc -AI07830,Principal Data Scientist,153383,CHF,138045,MI,FT,Switzerland,M,Switzerland,100,"Kubernetes, SQL, Tableau",Associate,4,Consulting,2024-02-21,2024-03-08,686,7.6,Quantum Computing Inc -AI07831,Data Analyst,138997,USD,138997,SE,CT,Israel,L,Israel,50,"Python, Git, Computer Vision, Java, GCP",Bachelor,5,Telecommunications,2024-11-15,2024-12-13,1685,6.3,Algorithmic Solutions -AI07832,ML Ops Engineer,52674,USD,52674,EN,CT,Israel,S,Italy,50,"Git, Tableau, Computer Vision, SQL",Master,0,Gaming,2024-01-12,2024-02-08,1383,7.3,Cloud AI Solutions -AI07833,NLP Engineer,46073,USD,46073,EN,PT,Sweden,S,France,0,"Python, MLOps, R",Bachelor,0,Manufacturing,2024-04-23,2024-06-29,1299,5.1,Advanced Robotics -AI07834,AI Architect,143115,EUR,121648,SE,FT,Austria,M,Austria,50,"Python, Data Visualization, TensorFlow, Statistics",Associate,9,Retail,2024-06-26,2024-08-20,1232,9.1,Smart Analytics -AI07835,Machine Learning Engineer,133093,EUR,113129,EX,CT,Austria,S,Austria,100,"Tableau, Docker, Hadoop, Scala, R",PhD,11,Media,2024-07-25,2024-09-09,1717,5.9,Neural Networks Co -AI07836,Autonomous Systems Engineer,99958,USD,99958,MI,CT,Sweden,M,Romania,50,"Data Visualization, Java, NLP",Associate,2,Retail,2024-10-20,2024-11-14,655,5.9,Autonomous Tech -AI07837,AI Consultant,100906,JPY,11099660,MI,PT,Japan,M,Nigeria,0,"Mathematics, R, Deep Learning",Associate,3,Finance,2024-11-23,2025-01-08,1322,9.6,DeepTech Ventures -AI07838,Principal Data Scientist,73621,USD,73621,EN,PT,Ireland,L,Ireland,0,"Java, Scala, Python",Master,0,Finance,2024-12-14,2025-01-19,1999,7.3,DeepTech Ventures -AI07839,ML Ops Engineer,131785,AUD,177910,SE,CT,Australia,M,Mexico,0,"PyTorch, Linux, Computer Vision, Azure",Master,5,Real Estate,2025-02-03,2025-02-17,785,5.8,Predictive Systems -AI07840,NLP Engineer,302166,USD,302166,EX,FT,United States,L,United States,100,"Python, Linux, Hadoop, MLOps, Azure",PhD,15,Consulting,2024-05-16,2024-07-06,1539,8.4,Cognitive Computing -AI07841,AI Specialist,230443,USD,230443,EX,CT,United States,L,United States,50,"Git, R, AWS, SQL",Associate,11,Gaming,2024-05-24,2024-06-14,589,7.7,Digital Transformation LLC -AI07842,Machine Learning Engineer,52678,USD,52678,EN,PT,Sweden,S,Romania,0,"Kubernetes, SQL, Computer Vision, MLOps, Deep Learning",Master,0,Technology,2025-02-09,2025-04-21,2097,8.8,DataVision Ltd -AI07843,Data Scientist,219188,CHF,197269,EX,PT,Switzerland,M,Switzerland,0,"Kubernetes, Docker, Linux, Azure, Scala",Associate,19,Government,2024-07-05,2024-08-08,1009,8.2,Smart Analytics -AI07844,AI Specialist,63772,USD,63772,SE,PT,China,M,China,0,"PyTorch, Java, GCP, Mathematics",PhD,8,Retail,2024-10-24,2024-12-14,1928,8.2,Advanced Robotics -AI07845,NLP Engineer,63461,EUR,53942,MI,FT,Austria,S,Austria,50,"Computer Vision, Git, Python",Bachelor,2,Telecommunications,2025-01-12,2025-03-25,1638,7.5,Future Systems -AI07846,AI Consultant,125077,USD,125077,MI,PT,Norway,L,Norway,100,"Data Visualization, TensorFlow, Java, Deep Learning",PhD,4,Automotive,2024-02-15,2024-04-06,1340,7.5,Cloud AI Solutions -AI07847,Computer Vision Engineer,157223,EUR,133640,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Scala",Master,7,Manufacturing,2024-03-24,2024-04-12,1193,6.3,AI Innovations -AI07848,Data Scientist,216895,EUR,184361,EX,CT,Netherlands,L,India,100,"Tableau, Scala, AWS",Bachelor,19,Automotive,2024-02-08,2024-02-27,1605,9,Advanced Robotics -AI07849,AI Architect,133507,USD,133507,SE,FT,Sweden,S,Vietnam,50,"TensorFlow, Git, AWS, GCP, Deep Learning",Master,5,Finance,2024-02-28,2024-04-29,1863,6.8,Advanced Robotics -AI07850,Data Engineer,207722,USD,207722,EX,FL,South Korea,L,South Korea,100,"Statistics, Git, Spark, R",Bachelor,17,Media,2024-08-08,2024-09-20,1585,8.9,DataVision Ltd -AI07851,Machine Learning Engineer,91743,EUR,77982,MI,CT,Netherlands,L,Netherlands,50,"Hadoop, Tableau, Scala",Associate,2,Retail,2024-07-16,2024-09-19,1685,7,AI Innovations -AI07852,ML Ops Engineer,87600,USD,87600,MI,FT,Denmark,S,Denmark,100,"GCP, Docker, Python, Spark, NLP",PhD,2,Education,2025-02-18,2025-03-07,881,6.5,Cloud AI Solutions -AI07853,AI Product Manager,78893,USD,78893,MI,PT,South Korea,M,Israel,50,"Docker, PyTorch, Kubernetes, MLOps",PhD,4,Healthcare,2024-09-19,2024-10-29,1284,9.5,Machine Intelligence Group -AI07854,Research Scientist,139691,USD,139691,EX,PT,Israel,S,Israel,100,"Linux, Python, Data Visualization",Master,15,Media,2024-10-24,2024-11-13,800,6.9,Quantum Computing Inc -AI07855,Principal Data Scientist,71086,USD,71086,MI,FL,Finland,S,Finland,0,"Hadoop, Azure, NLP, PyTorch, TensorFlow",Associate,2,Telecommunications,2025-04-12,2025-06-07,2412,6.7,TechCorp Inc -AI07856,AI Consultant,38307,USD,38307,SE,FL,India,M,India,50,"Hadoop, PyTorch, Computer Vision, SQL",Master,7,Education,2024-08-13,2024-10-13,1489,5.8,AI Innovations -AI07857,Principal Data Scientist,236250,USD,236250,EX,FT,Norway,L,Norway,50,"SQL, Mathematics, Java",PhD,15,Automotive,2024-02-24,2024-03-27,1164,7.3,Algorithmic Solutions -AI07858,NLP Engineer,94410,CHF,84969,MI,CT,Switzerland,S,Switzerland,50,"Hadoop, Linux, Computer Vision, Spark, PyTorch",PhD,4,Automotive,2024-03-26,2024-05-03,1633,9.5,Cloud AI Solutions -AI07859,ML Ops Engineer,239612,EUR,203670,EX,PT,Austria,L,Israel,100,"Docker, Scala, Java, Deep Learning, R",Associate,10,Healthcare,2024-05-07,2024-05-29,1636,5.3,Algorithmic Solutions -AI07860,Data Analyst,49846,USD,49846,EN,FT,South Korea,L,South Korea,50,"TensorFlow, SQL, Mathematics",Bachelor,1,Manufacturing,2024-09-12,2024-11-07,602,9.6,Cloud AI Solutions -AI07861,Data Scientist,90589,SGD,117766,MI,CT,Singapore,M,Singapore,50,"Computer Vision, Linux, MLOps, Scala, Kubernetes",Master,3,Real Estate,2024-10-29,2024-11-30,2105,8.8,Cloud AI Solutions -AI07862,Machine Learning Researcher,75857,USD,75857,EN,FT,Denmark,S,Denmark,100,"R, Spark, GCP",Associate,0,Transportation,2025-04-05,2025-06-04,1331,7.5,Future Systems -AI07863,Machine Learning Engineer,229106,USD,229106,EX,PT,United States,S,United States,0,"Python, MLOps, Data Visualization, Deep Learning",Associate,10,Transportation,2024-06-03,2024-06-28,703,8.9,DeepTech Ventures -AI07864,Robotics Engineer,226048,EUR,192141,EX,FT,Germany,M,Germany,100,"Java, PyTorch, TensorFlow, SQL",PhD,15,Media,2025-01-28,2025-02-17,1648,8.8,Cloud AI Solutions -AI07865,Robotics Engineer,74551,EUR,63368,MI,PT,Austria,S,Austria,0,"R, Statistics, Mathematics, Data Visualization",Associate,3,Finance,2024-06-09,2024-08-20,1298,5.1,Autonomous Tech -AI07866,Deep Learning Engineer,209614,EUR,178172,EX,CT,Netherlands,S,Netherlands,100,"Scala, NLP, Kubernetes",Associate,18,Automotive,2024-03-08,2024-04-28,1958,7.1,Algorithmic Solutions -AI07867,Research Scientist,62202,USD,62202,EN,PT,Ireland,S,Hungary,100,"Statistics, Spark, Scala, Linux",Master,1,Technology,2024-09-13,2024-10-19,2499,8.3,Digital Transformation LLC -AI07868,Data Engineer,76226,SGD,99094,EN,CT,Singapore,L,Singapore,100,"Spark, SQL, Python, Scala, Deep Learning",Master,1,Government,2024-10-30,2024-12-11,1269,5.5,DataVision Ltd -AI07869,Principal Data Scientist,186638,CHF,167974,SE,FL,Switzerland,M,Switzerland,100,"Spark, Linux, Python",PhD,9,Consulting,2024-03-01,2024-05-07,1062,8.2,Smart Analytics -AI07870,AI Research Scientist,275375,USD,275375,EX,FT,Ireland,L,Ireland,50,"Mathematics, Azure, Scala",Associate,15,Healthcare,2024-07-29,2024-09-19,1842,6,Autonomous Tech -AI07871,Autonomous Systems Engineer,59693,JPY,6566230,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, SQL, Deep Learning",Associate,1,Finance,2024-11-15,2025-01-22,765,5.1,Cloud AI Solutions -AI07872,Research Scientist,72671,USD,72671,EN,FT,Sweden,L,Sweden,100,"Kubernetes, Scala, Linux, Docker, NLP",Bachelor,1,Retail,2024-10-18,2024-11-25,827,8.9,Cognitive Computing -AI07873,AI Architect,103897,AUD,140261,MI,PT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, SQL, Deep Learning",Master,3,Telecommunications,2024-12-29,2025-03-02,547,9.2,TechCorp Inc -AI07874,Head of AI,101567,AUD,137115,SE,FL,Australia,S,Australia,0,"Linux, Hadoop, MLOps",Master,6,Real Estate,2024-09-11,2024-10-07,1857,9.1,Predictive Systems -AI07875,Head of AI,74940,USD,74940,EN,PT,Sweden,L,Sweden,50,"GCP, Computer Vision, Python",PhD,1,Real Estate,2024-01-16,2024-03-22,2286,6.1,Algorithmic Solutions -AI07876,Machine Learning Researcher,204444,GBP,153333,EX,PT,United Kingdom,M,United Kingdom,50,"MLOps, Azure, TensorFlow, Python",Bachelor,13,Finance,2024-11-19,2024-12-19,1862,7,Autonomous Tech -AI07877,Deep Learning Engineer,264606,CAD,330758,EX,CT,Canada,L,Canada,100,"GCP, SQL, Azure, R",PhD,11,Government,2024-02-07,2024-04-10,2308,6.4,Digital Transformation LLC -AI07878,AI Product Manager,170883,EUR,145251,EX,CT,Germany,S,Germany,50,"Python, Git, Tableau, TensorFlow, Statistics",Master,17,Media,2024-03-23,2024-05-24,1102,7.6,Smart Analytics -AI07879,Data Analyst,152247,USD,152247,MI,FT,Denmark,L,Denmark,100,"SQL, Scala, Statistics",PhD,2,Transportation,2024-05-15,2024-06-06,529,8.5,Machine Intelligence Group -AI07880,AI Specialist,75029,AUD,101289,MI,FT,Australia,M,Australia,100,"Hadoop, MLOps, Tableau, GCP",Bachelor,4,Manufacturing,2024-09-09,2024-10-06,2288,8.7,DeepTech Ventures -AI07881,Machine Learning Engineer,44910,USD,44910,SE,FL,India,M,India,50,"Azure, R, Statistics, NLP",Master,8,Transportation,2024-06-09,2024-07-10,1285,6.9,TechCorp Inc -AI07882,Autonomous Systems Engineer,57794,GBP,43346,EN,FT,United Kingdom,M,United Kingdom,0,"NLP, AWS, R, Python, TensorFlow",Master,0,Finance,2024-03-01,2024-05-11,1515,10,Future Systems -AI07883,AI Research Scientist,155551,USD,155551,SE,FT,Denmark,S,Netherlands,50,"GCP, Linux, MLOps",Master,9,Finance,2024-12-08,2025-01-14,2040,8.3,TechCorp Inc -AI07884,Computer Vision Engineer,185612,USD,185612,EX,FL,Ireland,L,Ireland,50,"Scala, PyTorch, NLP",Master,13,Manufacturing,2025-04-27,2025-06-28,1410,9.3,Cognitive Computing -AI07885,Deep Learning Engineer,69810,JPY,7679100,EN,FL,Japan,M,Japan,50,"Docker, Scala, Python, Statistics, Hadoop",Master,0,Retail,2024-04-20,2024-06-12,874,5.9,Future Systems -AI07886,Machine Learning Engineer,108934,EUR,92594,MI,PT,Netherlands,L,Philippines,0,"Hadoop, Linux, NLP",PhD,3,Real Estate,2024-10-04,2024-10-31,2217,8.1,TechCorp Inc -AI07887,Robotics Engineer,116867,USD,116867,MI,FL,United States,M,United States,100,"Python, Deep Learning, Hadoop, Docker",Bachelor,4,Technology,2024-05-29,2024-07-30,1731,9.8,TechCorp Inc -AI07888,Principal Data Scientist,107417,EUR,91304,MI,FL,Austria,L,Czech Republic,100,"Spark, Computer Vision, Azure, SQL, Scala",Bachelor,2,Manufacturing,2024-12-12,2025-01-29,581,8.2,Quantum Computing Inc -AI07889,Autonomous Systems Engineer,60938,EUR,51797,EN,FT,Austria,S,Austria,50,"Tableau, Python, TensorFlow",Bachelor,1,Telecommunications,2024-04-06,2024-04-24,1259,6.8,AI Innovations -AI07890,Computer Vision Engineer,228287,GBP,171215,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Azure, Scala, SQL, Git",Master,14,Education,2024-04-17,2024-05-28,1740,9.3,DataVision Ltd -AI07891,AI Consultant,149332,USD,149332,SE,PT,Norway,M,Norway,50,"Deep Learning, R, Kubernetes",PhD,7,Energy,2024-07-02,2024-07-31,1673,8.9,Smart Analytics -AI07892,Autonomous Systems Engineer,101212,CAD,126515,SE,PT,Canada,M,Canada,100,"NLP, Scala, Python, PyTorch",Master,6,Media,2024-03-02,2024-03-21,1825,9.5,Algorithmic Solutions -AI07893,AI Architect,136111,USD,136111,MI,PT,Denmark,L,Denmark,0,"Scala, AWS, Hadoop, Python, Git",Associate,2,Automotive,2025-03-24,2025-05-11,1343,5.9,Future Systems -AI07894,Autonomous Systems Engineer,106323,GBP,79742,MI,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, Scala",Bachelor,3,Technology,2024-12-23,2025-02-28,2392,8.7,DeepTech Ventures -AI07895,Computer Vision Engineer,156650,AUD,211478,EX,FT,Australia,M,Netherlands,50,"Data Visualization, Azure, SQL, Hadoop, Java",Master,12,Transportation,2024-08-19,2024-10-15,763,5.7,Algorithmic Solutions -AI07896,Data Scientist,137174,EUR,116598,SE,PT,France,M,Philippines,0,"Java, Python, Data Visualization, AWS",Bachelor,5,Consulting,2025-04-16,2025-05-09,1132,7.2,Cognitive Computing -AI07897,AI Product Manager,106794,USD,106794,MI,CT,Finland,L,South Korea,100,"MLOps, AWS, Tableau, SQL, Python",Associate,2,Retail,2025-04-06,2025-05-12,1189,6.1,Quantum Computing Inc -AI07898,Autonomous Systems Engineer,229594,CAD,286993,EX,PT,Canada,M,Canada,0,"Python, Linux, MLOps",PhD,15,Energy,2024-11-24,2024-12-23,1826,7.1,Quantum Computing Inc -AI07899,Autonomous Systems Engineer,72245,EUR,61408,EN,PT,Netherlands,M,Netherlands,50,"SQL, PyTorch, AWS, Linux",PhD,0,Finance,2024-10-30,2024-12-09,2296,7.6,Autonomous Tech -AI07900,AI Architect,154453,USD,154453,SE,PT,Ireland,L,Ireland,0,"Data Visualization, Linux, R, Python, Azure",Associate,6,Retail,2024-12-25,2025-03-07,1418,8.6,Algorithmic Solutions -AI07901,AI Specialist,64086,EUR,54473,EN,CT,Germany,S,Romania,50,"Java, R, SQL, Git, Deep Learning",Bachelor,1,Technology,2024-07-23,2024-08-17,2472,5.1,Autonomous Tech -AI07902,ML Ops Engineer,101108,EUR,85942,MI,PT,France,L,France,100,"Statistics, Linux, Mathematics",Bachelor,3,Energy,2025-04-03,2025-06-05,2003,6.3,Machine Intelligence Group -AI07903,Head of AI,88469,USD,88469,EN,FL,Denmark,L,Denmark,100,"Python, Linux, MLOps",PhD,1,Gaming,2024-12-01,2025-02-07,626,6,Digital Transformation LLC -AI07904,Data Engineer,111556,USD,111556,EX,CT,China,M,China,50,"SQL, GCP, Kubernetes",Master,15,Telecommunications,2024-11-05,2024-12-19,1737,5.5,Quantum Computing Inc -AI07905,AI Research Scientist,95017,EUR,80764,MI,FT,Netherlands,S,Thailand,100,"Azure, SQL, Computer Vision, R",Bachelor,2,Transportation,2025-03-23,2025-04-09,1717,7.8,Cognitive Computing -AI07906,Data Analyst,98367,AUD,132795,SE,PT,Australia,S,Mexico,50,"Docker, Statistics, Python, NLP, Tableau",PhD,7,Gaming,2024-02-04,2024-04-07,1534,8.7,Smart Analytics -AI07907,AI Product Manager,92735,EUR,78825,EN,PT,Germany,L,Chile,0,"Tableau, SQL, TensorFlow",PhD,0,Finance,2025-04-28,2025-05-30,1976,5.2,TechCorp Inc -AI07908,Principal Data Scientist,135039,USD,135039,SE,FL,Ireland,M,Ireland,0,"Python, Azure, Data Visualization, SQL",Master,7,Media,2024-04-06,2024-05-24,1236,8.6,Machine Intelligence Group -AI07909,Machine Learning Engineer,205457,EUR,174638,EX,FT,Netherlands,M,Netherlands,50,"Git, Kubernetes, Hadoop",Bachelor,10,Technology,2025-03-30,2025-04-17,1285,9.3,Future Systems -AI07910,Deep Learning Engineer,86892,JPY,9558120,MI,FL,Japan,S,Japan,50,"MLOps, Python, Linux, TensorFlow, GCP",PhD,2,Technology,2024-06-24,2024-07-20,1287,5.6,Neural Networks Co -AI07911,AI Product Manager,100067,EUR,85057,MI,FL,Netherlands,L,Netherlands,100,"AWS, Deep Learning, Computer Vision",PhD,4,Healthcare,2024-12-18,2025-02-04,1780,5.7,Advanced Robotics -AI07912,Autonomous Systems Engineer,86435,USD,86435,EN,CT,Sweden,L,Sweden,50,"Kubernetes, NLP, Tableau, Python, Computer Vision",PhD,1,Education,2024-12-18,2025-01-04,2053,6.1,Machine Intelligence Group -AI07913,AI Product Manager,69261,SGD,90039,MI,FL,Singapore,S,Singapore,100,"Python, SQL, Docker",Associate,2,Automotive,2024-05-26,2024-07-27,1673,7,Cloud AI Solutions -AI07914,Computer Vision Engineer,187635,CHF,168872,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, AWS, MLOps, R, GCP",PhD,5,Consulting,2024-06-23,2024-08-21,2261,8.7,Neural Networks Co -AI07915,Data Engineer,150751,CHF,135676,MI,FT,Switzerland,M,Switzerland,50,"Statistics, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2025-02-21,2025-04-12,1563,7.4,Machine Intelligence Group -AI07916,AI Product Manager,117003,AUD,157954,SE,FL,Australia,M,Australia,100,"TensorFlow, AWS, MLOps, Azure, Linux",PhD,8,Manufacturing,2025-02-25,2025-05-09,533,8.4,DataVision Ltd -AI07917,Machine Learning Engineer,81733,EUR,69473,EN,FL,France,L,Belgium,50,"Azure, TensorFlow, Tableau, Python",Associate,0,Real Estate,2024-04-03,2024-05-06,1383,8.5,AI Innovations -AI07918,AI Architect,187345,USD,187345,EX,CT,Ireland,S,Ireland,0,"R, Data Visualization, SQL, Docker",Master,11,Gaming,2024-03-22,2024-05-05,1543,8.3,Cognitive Computing -AI07919,Robotics Engineer,143200,USD,143200,MI,PT,Denmark,L,Denmark,100,"Spark, Computer Vision, Data Visualization, GCP, AWS",PhD,3,Transportation,2025-02-15,2025-03-26,1646,7.2,Smart Analytics -AI07920,AI Product Manager,68868,EUR,58538,EN,FL,Germany,S,Finland,0,"NLP, TensorFlow, Azure",PhD,1,Education,2024-09-02,2024-10-25,571,6.7,Predictive Systems -AI07921,Autonomous Systems Engineer,79844,USD,79844,MI,CT,Sweden,M,Mexico,0,"Kubernetes, AWS, NLP",Master,2,Telecommunications,2024-01-20,2024-02-28,1962,5.4,Smart Analytics -AI07922,Research Scientist,158799,USD,158799,SE,FT,Denmark,L,Denmark,0,"Scala, R, Git",PhD,9,Education,2024-12-30,2025-02-02,1832,6.6,Quantum Computing Inc -AI07923,AI Architect,125614,EUR,106772,SE,FT,Netherlands,L,Argentina,100,"PyTorch, Python, GCP",Bachelor,5,Automotive,2024-05-23,2024-07-05,2140,5.6,Predictive Systems -AI07924,AI Software Engineer,104482,USD,104482,MI,FT,United States,L,United States,0,"Java, SQL, Statistics",PhD,3,Gaming,2024-11-22,2024-12-09,1939,5.3,Neural Networks Co -AI07925,Deep Learning Engineer,196895,EUR,167361,EX,FT,Austria,M,Austria,50,"Scala, Spark, PyTorch",Bachelor,16,Gaming,2024-07-30,2024-10-08,751,6.9,AI Innovations -AI07926,Computer Vision Engineer,133125,EUR,113156,SE,PT,Germany,M,Germany,50,"MLOps, R, Statistics",Master,8,Consulting,2025-03-17,2025-04-28,1400,6.3,DeepTech Ventures -AI07927,AI Specialist,182420,USD,182420,EX,CT,South Korea,L,South Korea,50,"PyTorch, Data Visualization, Spark",Master,17,Energy,2024-07-03,2024-07-26,1745,8.9,Predictive Systems -AI07928,AI Architect,151509,CHF,136358,SE,CT,Switzerland,M,Switzerland,100,"TensorFlow, Python, Kubernetes, AWS",Master,8,Transportation,2024-01-07,2024-02-26,1536,5.8,Advanced Robotics -AI07929,Head of AI,69352,USD,69352,MI,CT,Finland,M,Finland,0,"Data Visualization, TensorFlow, Azure",PhD,3,Manufacturing,2024-12-25,2025-02-02,1882,6.8,Advanced Robotics -AI07930,NLP Engineer,45522,USD,45522,SE,PT,India,S,India,0,"Computer Vision, Hadoop, Git, MLOps",PhD,9,Automotive,2024-04-08,2024-05-06,1194,6.9,Future Systems -AI07931,Data Engineer,43570,USD,43570,SE,PT,India,S,India,100,"MLOps, Hadoop, Spark, NLP, Mathematics",Associate,9,Energy,2024-08-05,2024-09-23,1359,8.8,AI Innovations -AI07932,AI Software Engineer,98915,USD,98915,MI,CT,Israel,M,Israel,0,"Docker, Git, TensorFlow, GCP",Associate,3,Real Estate,2025-03-02,2025-04-18,2083,7.5,Machine Intelligence Group -AI07933,Research Scientist,132893,USD,132893,MI,FT,Norway,M,Thailand,50,"Computer Vision, SQL, Tableau",Bachelor,2,Real Estate,2024-10-23,2024-11-16,1749,6.9,TechCorp Inc -AI07934,ML Ops Engineer,97204,CHF,87484,EN,PT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Docker",Bachelor,1,Finance,2025-03-31,2025-04-29,816,9.8,Predictive Systems -AI07935,Machine Learning Engineer,127523,USD,127523,MI,FL,United States,M,United States,0,"Hadoop, Mathematics, Docker, Data Visualization, Kubernetes",Bachelor,2,Education,2024-04-13,2024-04-27,634,5.7,Quantum Computing Inc -AI07936,AI Product Manager,89735,USD,89735,EN,CT,Norway,L,Norway,50,"Java, Python, Git",Associate,0,Government,2025-03-10,2025-04-14,757,6.2,TechCorp Inc -AI07937,Research Scientist,97385,USD,97385,MI,PT,Norway,S,Norway,0,"Docker, PyTorch, NLP, Python",PhD,4,Education,2024-12-16,2025-02-13,1489,5.8,Autonomous Tech -AI07938,Machine Learning Researcher,52180,USD,52180,EN,CT,Sweden,S,Egypt,100,"PyTorch, Java, Statistics",Associate,0,Finance,2024-12-05,2025-01-07,2313,7.8,DataVision Ltd -AI07939,Robotics Engineer,233176,USD,233176,EX,FT,Denmark,L,Denmark,0,"Hadoop, Python, Azure, TensorFlow",Bachelor,18,Media,2024-07-09,2024-08-04,2378,6.6,Digital Transformation LLC -AI07940,NLP Engineer,151930,AUD,205106,EX,FT,Australia,M,Australia,100,"NLP, Java, PyTorch, TensorFlow",PhD,17,Energy,2024-05-05,2024-07-01,543,9.3,DeepTech Ventures -AI07941,Data Analyst,166632,SGD,216622,EX,PT,Singapore,M,Singapore,100,"Linux, MLOps, Python",Bachelor,15,Media,2025-02-14,2025-03-25,1476,5.7,Cloud AI Solutions -AI07942,Data Analyst,100715,USD,100715,MI,CT,United States,M,United States,0,"SQL, Statistics, Git, Data Visualization, Java",Associate,2,Consulting,2024-06-25,2024-08-27,1320,6,DeepTech Ventures -AI07943,Computer Vision Engineer,74580,JPY,8203800,EN,CT,Japan,S,Japan,0,"Git, Computer Vision, Tableau",Associate,0,Telecommunications,2024-03-02,2024-04-17,616,5.5,DataVision Ltd -AI07944,AI Architect,120355,SGD,156462,SE,FT,Singapore,M,Philippines,50,"Scala, Python, MLOps, SQL",Master,5,Gaming,2024-03-11,2024-03-25,1771,5.8,Neural Networks Co -AI07945,AI Specialist,129835,USD,129835,EX,CT,Ireland,S,Ireland,100,"Deep Learning, Spark, Tableau, Python",Bachelor,11,Media,2025-01-24,2025-03-28,1977,7.4,Cognitive Computing -AI07946,AI Product Manager,143095,EUR,121631,SE,FT,Netherlands,L,Russia,0,"MLOps, Kubernetes, Tableau",Bachelor,5,Media,2024-08-04,2024-10-13,1147,8.4,Predictive Systems -AI07947,AI Consultant,162582,CHF,146324,SE,CT,Switzerland,M,Malaysia,100,"Data Visualization, Docker, Computer Vision, Git",PhD,9,Healthcare,2025-04-30,2025-05-18,558,6.1,Neural Networks Co -AI07948,Deep Learning Engineer,66995,USD,66995,EX,CT,India,M,India,100,"Python, MLOps, TensorFlow",Bachelor,13,Finance,2025-04-30,2025-05-22,1661,6,Cognitive Computing -AI07949,AI Specialist,99477,JPY,10942470,MI,PT,Japan,L,Japan,100,"Hadoop, R, Scala, Azure",Bachelor,2,Government,2024-10-18,2024-12-14,594,8.8,Algorithmic Solutions -AI07950,AI Architect,159574,USD,159574,SE,FT,Denmark,L,Ghana,50,"Python, Data Visualization, Git, PyTorch",Master,9,Finance,2025-04-07,2025-04-29,998,5.3,Predictive Systems -AI07951,AI Product Manager,23228,USD,23228,EN,PT,India,S,India,0,"MLOps, Hadoop, R, TensorFlow, Tableau",Associate,1,Technology,2024-03-01,2024-04-02,1213,7.5,DataVision Ltd -AI07952,AI Architect,173217,USD,173217,SE,CT,United States,M,United States,50,"Statistics, Linux, Docker, Deep Learning",Bachelor,5,Real Estate,2024-02-10,2024-03-18,1019,6.8,DataVision Ltd -AI07953,AI Research Scientist,80075,USD,80075,MI,PT,Finland,L,Finland,100,"SQL, AWS, TensorFlow, Mathematics, Linux",Bachelor,4,Healthcare,2024-05-31,2024-07-03,2425,8.4,Cognitive Computing -AI07954,Data Scientist,55361,JPY,6089710,EN,PT,Japan,S,Japan,100,"SQL, PyTorch, Hadoop, Kubernetes",Bachelor,1,Telecommunications,2024-07-09,2024-09-04,2030,5.8,Quantum Computing Inc -AI07955,Research Scientist,93720,USD,93720,MI,FL,Israel,M,Israel,50,"PyTorch, TensorFlow, MLOps",Master,4,Manufacturing,2024-10-22,2024-11-12,1971,5.9,Future Systems -AI07956,Data Engineer,103590,USD,103590,MI,FT,Finland,M,Ghana,0,"Python, AWS, Azure, Linux",Bachelor,3,Transportation,2024-10-28,2024-11-26,1170,6,Digital Transformation LLC -AI07957,Head of AI,166505,JPY,18315550,EX,PT,Japan,L,Japan,100,"Git, Docker, Python, GCP, Linux",PhD,17,Real Estate,2024-12-13,2025-01-02,858,5.3,Future Systems -AI07958,Deep Learning Engineer,150946,CHF,135851,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, Azure, Deep Learning",Associate,2,Transportation,2024-06-14,2024-08-26,1490,9.1,Cognitive Computing -AI07959,ML Ops Engineer,218604,AUD,295115,EX,PT,Australia,L,Ghana,50,"Tableau, Azure, AWS, Kubernetes, Java",PhD,17,Education,2024-04-17,2024-05-09,1976,5.3,Cognitive Computing -AI07960,Data Analyst,201864,USD,201864,EX,CT,Sweden,S,Sweden,100,"Computer Vision, Java, R",Associate,16,Transportation,2024-09-06,2024-10-26,523,6,Algorithmic Solutions -AI07961,AI Research Scientist,77414,AUD,104509,MI,PT,Australia,M,Argentina,100,"Scala, Java, Tableau",Bachelor,3,Energy,2024-01-13,2024-02-13,1416,5.2,TechCorp Inc -AI07962,Machine Learning Researcher,128494,EUR,109220,EX,FL,Austria,S,Austria,0,"Kubernetes, PyTorch, R",PhD,12,Transportation,2024-05-25,2024-08-04,730,5.5,Cognitive Computing -AI07963,AI Research Scientist,120539,USD,120539,EX,CT,China,L,China,0,"Python, GCP, Docker",Bachelor,10,Real Estate,2025-03-27,2025-06-06,572,8.7,Advanced Robotics -AI07964,AI Software Engineer,60570,USD,60570,EN,PT,Finland,L,Finland,0,"MLOps, Spark, TensorFlow, Kubernetes, SQL",Associate,1,Healthcare,2024-03-25,2024-04-16,1857,5.9,TechCorp Inc -AI07965,Research Scientist,88260,USD,88260,EN,PT,Denmark,S,Philippines,100,"Git, Statistics, Linux, Azure",Bachelor,0,Real Estate,2024-12-09,2025-01-01,1245,8.8,Smart Analytics -AI07966,Deep Learning Engineer,78518,USD,78518,MI,FT,Israel,S,Israel,50,"Hadoop, Kubernetes, Python, Deep Learning, Mathematics",Master,2,Real Estate,2024-09-12,2024-09-27,2279,8.7,TechCorp Inc -AI07967,Machine Learning Engineer,97759,EUR,83095,MI,FT,Netherlands,S,Netherlands,50,"PyTorch, GCP, Statistics, Docker",Master,2,Manufacturing,2025-03-11,2025-05-18,1358,6.1,TechCorp Inc -AI07968,Data Analyst,92686,EUR,78783,MI,FT,Germany,M,Israel,50,"Computer Vision, MLOps, TensorFlow, Python, PyTorch",PhD,2,Gaming,2025-02-10,2025-03-25,1588,9.7,Neural Networks Co -AI07969,Deep Learning Engineer,109730,CHF,98757,EN,CT,Switzerland,M,Switzerland,0,"Python, Spark, Tableau",Master,1,Manufacturing,2024-07-15,2024-09-05,1812,6.5,Neural Networks Co -AI07970,Computer Vision Engineer,61314,USD,61314,EX,FT,India,L,India,100,"Kubernetes, TensorFlow, MLOps",Bachelor,18,Telecommunications,2024-04-01,2024-05-20,953,5.8,Future Systems -AI07971,AI Research Scientist,34450,USD,34450,MI,CT,China,M,Switzerland,0,"Python, TensorFlow, Scala, Kubernetes, Java",Master,3,Retail,2024-07-06,2024-09-15,1840,8,Predictive Systems -AI07972,Deep Learning Engineer,104797,USD,104797,SE,CT,Ireland,S,Ireland,50,"Python, Data Visualization, Spark, SQL, Java",PhD,5,Retail,2025-01-28,2025-02-24,1987,8.8,Cognitive Computing -AI07973,NLP Engineer,143973,AUD,194364,SE,PT,Australia,L,Australia,100,"PyTorch, SQL, Hadoop",Bachelor,7,Education,2024-02-18,2024-04-18,683,9.4,Digital Transformation LLC -AI07974,Data Engineer,60516,USD,60516,EN,FL,Sweden,M,Sweden,50,"Java, PyTorch, Scala, Statistics",Master,0,Automotive,2024-09-13,2024-10-18,818,5.6,Machine Intelligence Group -AI07975,Autonomous Systems Engineer,110800,CHF,99720,MI,PT,Switzerland,M,Switzerland,50,"Python, Computer Vision, Kubernetes, R, TensorFlow",PhD,3,Healthcare,2024-05-13,2024-07-21,1718,5.9,TechCorp Inc -AI07976,Data Scientist,83576,USD,83576,SE,FT,South Korea,S,Norway,0,"Deep Learning, NLP, Data Visualization, Scala, Mathematics",Bachelor,5,Real Estate,2025-02-27,2025-05-03,1461,5.4,Advanced Robotics -AI07977,AI Consultant,150796,USD,150796,SE,CT,Finland,L,Finland,100,"Hadoop, NLP, Linux, Scala, Python",PhD,9,Media,2024-12-03,2024-12-23,766,5.7,Autonomous Tech -AI07978,Head of AI,67072,USD,67072,EN,PT,Israel,L,Israel,0,"Deep Learning, AWS, NLP, Docker, GCP",Associate,1,Telecommunications,2024-03-26,2024-05-01,1888,10,Cloud AI Solutions -AI07979,Robotics Engineer,51985,USD,51985,EN,FT,Sweden,S,Sweden,100,"AWS, R, MLOps, Azure",Master,0,Technology,2024-03-25,2024-05-18,2215,6.4,AI Innovations -AI07980,AI Product Manager,110993,USD,110993,SE,CT,Finland,M,Finland,100,"Linux, Tableau, SQL, Spark, Scala",PhD,5,Education,2024-04-12,2024-04-29,2320,5.5,Cloud AI Solutions -AI07981,Head of AI,94069,USD,94069,EN,FT,Norway,M,Norway,100,"R, TensorFlow, Java, Git, Python",Associate,1,Telecommunications,2024-09-14,2024-10-16,1036,7.7,DeepTech Ventures -AI07982,AI Architect,146889,CHF,132200,MI,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, Mathematics",PhD,4,Telecommunications,2025-03-04,2025-04-15,726,5.8,Advanced Robotics -AI07983,Principal Data Scientist,155346,USD,155346,SE,FL,United States,S,United States,0,"Computer Vision, Java, Git, Docker",Bachelor,9,Telecommunications,2025-01-01,2025-02-27,1994,9.9,TechCorp Inc -AI07984,Data Scientist,124124,EUR,105505,SE,CT,France,S,France,50,"TensorFlow, PyTorch, Tableau, Computer Vision",PhD,6,Gaming,2024-05-28,2024-08-07,1082,9.7,Cloud AI Solutions -AI07985,Deep Learning Engineer,137231,CAD,171539,EX,FT,Canada,S,Canada,100,"Docker, AWS, PyTorch, SQL",Associate,15,Consulting,2024-01-22,2024-03-22,1011,7.7,Advanced Robotics -AI07986,AI Architect,45728,CAD,57160,EN,CT,Canada,S,Canada,0,"MLOps, Docker, SQL",Master,1,Gaming,2024-04-21,2024-07-03,2066,5.7,Advanced Robotics -AI07987,Machine Learning Researcher,61291,EUR,52097,EN,FL,France,L,France,100,"SQL, MLOps, AWS, Hadoop",Bachelor,0,Education,2024-06-27,2024-08-09,1539,8.3,Neural Networks Co -AI07988,AI Architect,64443,EUR,54777,EN,FL,France,M,France,100,"Git, Kubernetes, Computer Vision",PhD,0,Media,2025-02-01,2025-04-11,2228,6.7,Future Systems -AI07989,Deep Learning Engineer,66409,USD,66409,EN,FL,United States,M,Colombia,50,"MLOps, Azure, Python, Kubernetes, Data Visualization",Bachelor,1,Healthcare,2024-11-05,2025-01-09,1753,8.3,Advanced Robotics -AI07990,NLP Engineer,76025,USD,76025,EX,CT,China,S,China,0,"Deep Learning, PyTorch, Linux",Associate,10,Retail,2024-05-14,2024-06-05,1627,5,Cloud AI Solutions -AI07991,Machine Learning Researcher,211009,USD,211009,EX,FL,Ireland,L,Ireland,100,"SQL, Computer Vision, Tableau",Master,10,Manufacturing,2025-04-11,2025-05-31,1249,5.6,Algorithmic Solutions -AI07992,AI Product Manager,154995,EUR,131746,SE,FL,Germany,L,Poland,50,"Scala, NLP, Mathematics, Docker, Java",PhD,6,Government,2025-03-26,2025-05-17,1985,7.3,Cloud AI Solutions -AI07993,AI Consultant,44675,USD,44675,SE,FL,India,L,Singapore,0,"Docker, Scala, MLOps, Linux, SQL",PhD,7,Finance,2024-11-11,2025-01-21,782,8.5,AI Innovations -AI07994,Research Scientist,87124,SGD,113261,EN,PT,Singapore,L,Singapore,0,"Scala, Java, TensorFlow, GCP, Deep Learning",Bachelor,1,Healthcare,2024-03-10,2024-04-25,1861,5.7,Cognitive Computing -AI07995,Robotics Engineer,122808,USD,122808,MI,PT,Sweden,L,Sweden,0,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,4,Consulting,2024-03-23,2024-05-16,1697,9,Predictive Systems -AI07996,Data Engineer,133625,JPY,14698750,SE,PT,Japan,L,Ireland,50,"Azure, Python, Mathematics",Associate,8,Government,2024-11-17,2024-12-03,1052,9.2,AI Innovations -AI07997,Autonomous Systems Engineer,71366,USD,71366,EN,CT,Israel,M,Israel,0,"TensorFlow, NLP, Kubernetes, Data Visualization, AWS",Bachelor,0,Energy,2024-10-28,2024-11-22,2129,7.3,Neural Networks Co -AI07998,AI Consultant,123920,USD,123920,SE,CT,Sweden,S,Brazil,50,"Docker, AWS, Hadoop, Java, Azure",Bachelor,5,Automotive,2025-01-23,2025-03-18,972,8.5,Autonomous Tech -AI07999,AI Product Manager,134233,JPY,14765630,MI,CT,Japan,L,Japan,50,"GCP, SQL, Tableau, Kubernetes",PhD,4,Finance,2024-09-13,2024-11-05,1135,6.4,Machine Intelligence Group -AI08000,Machine Learning Researcher,109561,USD,109561,MI,FT,Sweden,L,Netherlands,0,"Python, Java, NLP, Linux",Bachelor,4,Finance,2024-04-09,2024-06-13,1402,8.9,AI Innovations -AI08001,Data Scientist,71713,SGD,93227,EN,PT,Singapore,L,Thailand,50,"GCP, Statistics, Tableau, Scala",Associate,0,Government,2024-05-02,2024-07-10,2238,5.7,Quantum Computing Inc -AI08002,Robotics Engineer,58752,CAD,73440,EN,PT,Canada,M,Canada,100,"SQL, TensorFlow, Git, AWS",Master,0,Automotive,2024-12-13,2025-01-06,878,8,Digital Transformation LLC -AI08003,Autonomous Systems Engineer,118460,USD,118460,MI,FL,Norway,M,Norway,50,"NLP, Mathematics, Deep Learning, Python",Bachelor,4,Retail,2024-06-25,2024-07-30,1000,8.5,DataVision Ltd -AI08004,Machine Learning Researcher,82449,EUR,70082,EN,FL,Netherlands,M,Norway,0,"NLP, Spark, TensorFlow",Bachelor,0,Telecommunications,2024-05-25,2024-06-19,1871,8,Advanced Robotics -AI08005,Machine Learning Engineer,80025,SGD,104033,MI,FT,Singapore,S,Singapore,100,"Hadoop, Tableau, Spark, GCP",PhD,4,Real Estate,2024-04-18,2024-06-12,1556,8.2,Quantum Computing Inc -AI08006,Robotics Engineer,221861,USD,221861,EX,FL,Ireland,S,Ireland,100,"Kubernetes, GCP, Linux, SQL, Data Visualization",Bachelor,10,Manufacturing,2024-11-13,2025-01-24,818,7.2,TechCorp Inc -AI08007,AI Consultant,284268,USD,284268,EX,FT,Ireland,L,Ireland,50,"Data Visualization, AWS, PyTorch, Spark, Hadoop",Master,18,Technology,2024-05-23,2024-06-07,2236,5.1,Autonomous Tech -AI08008,Deep Learning Engineer,171547,SGD,223011,EX,PT,Singapore,S,Singapore,50,"Linux, Java, Tableau, GCP, Kubernetes",PhD,12,Retail,2025-04-09,2025-04-25,1173,9.2,Cloud AI Solutions -AI08009,AI Software Engineer,323208,CHF,290887,EX,FL,Switzerland,L,Switzerland,100,"Tableau, Deep Learning, Data Visualization, SQL, Linux",Master,14,Energy,2024-05-24,2024-07-04,1871,5.7,Cognitive Computing -AI08010,AI Product Manager,113656,USD,113656,MI,FT,United States,M,Ireland,50,"Statistics, SQL, MLOps",Master,2,Government,2024-10-04,2024-11-20,1427,7,Digital Transformation LLC -AI08011,Principal Data Scientist,77152,USD,77152,MI,FL,Ireland,M,Ireland,50,"AWS, TensorFlow, GCP, Deep Learning, SQL",PhD,4,Technology,2025-02-01,2025-04-01,2268,8.4,Algorithmic Solutions -AI08012,NLP Engineer,222207,SGD,288869,EX,FT,Singapore,L,Singapore,100,"Statistics, Tableau, Scala",Associate,13,Telecommunications,2025-01-18,2025-02-28,1899,6.6,Smart Analytics -AI08013,AI Consultant,196407,USD,196407,EX,PT,Denmark,S,Denmark,100,"Java, SQL, Deep Learning, Computer Vision, Spark",Bachelor,17,Government,2024-11-01,2025-01-03,2236,7.5,Autonomous Tech -AI08014,Research Scientist,27068,USD,27068,MI,PT,India,M,India,100,"Spark, Statistics, PyTorch",Bachelor,4,Retail,2024-08-27,2024-11-08,2145,9.7,Neural Networks Co -AI08015,AI Research Scientist,99789,USD,99789,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Statistics, GCP",PhD,7,Automotive,2025-03-14,2025-05-09,564,6.7,Predictive Systems -AI08016,Research Scientist,157360,CHF,141624,SE,CT,Switzerland,S,Czech Republic,50,"Java, Scala, MLOps, NLP",Bachelor,7,Education,2024-12-28,2025-02-03,2474,5,Algorithmic Solutions -AI08017,Data Engineer,73368,CHF,66031,EN,CT,Switzerland,S,Switzerland,0,"Spark, Linux, Python",Bachelor,1,Healthcare,2024-08-03,2024-09-29,764,6.3,Smart Analytics -AI08018,AI Specialist,130971,CHF,117874,EN,FL,Switzerland,L,Switzerland,0,"TensorFlow, Python, Mathematics",Master,1,Transportation,2024-07-09,2024-09-09,2002,8.4,DataVision Ltd -AI08019,Autonomous Systems Engineer,42371,USD,42371,MI,FT,China,S,China,100,"SQL, Scala, Git",Associate,3,Consulting,2024-02-08,2024-03-16,2063,6.8,Machine Intelligence Group -AI08020,AI Architect,96446,USD,96446,EN,PT,United States,L,Denmark,50,"PyTorch, Linux, Statistics",Master,1,Energy,2024-02-11,2024-03-22,1721,8.2,DeepTech Ventures -AI08021,Data Scientist,253346,USD,253346,EX,FT,United States,M,United States,50,"NLP, Linux, Azure",PhD,15,Manufacturing,2024-11-12,2025-01-14,1765,5.8,Smart Analytics -AI08022,AI Specialist,210688,JPY,23175680,EX,FT,Japan,M,Japan,50,"MLOps, Hadoop, Python",Associate,14,Transportation,2024-01-04,2024-02-16,1448,5.1,Algorithmic Solutions -AI08023,Data Analyst,20088,USD,20088,EN,CT,India,S,India,50,"R, Azure, TensorFlow, Tableau, Git",Master,1,Healthcare,2024-11-06,2024-12-07,1065,6.7,AI Innovations -AI08024,AI Research Scientist,115869,EUR,98489,MI,FT,France,L,France,100,"Kubernetes, Azure, TensorFlow, Java, Scala",Bachelor,4,Gaming,2024-12-01,2025-01-14,890,5.5,Neural Networks Co -AI08025,Computer Vision Engineer,27041,USD,27041,MI,FL,India,M,Argentina,0,"Git, GCP, Scala, Deep Learning, TensorFlow",Associate,2,Manufacturing,2024-05-08,2024-07-11,631,8.4,Future Systems -AI08026,AI Research Scientist,133722,USD,133722,SE,FL,Ireland,S,Ireland,50,"Mathematics, Statistics, Java",Master,8,Government,2025-04-11,2025-05-30,2432,6.4,Advanced Robotics -AI08027,Autonomous Systems Engineer,75208,USD,75208,EN,PT,United States,S,Ukraine,0,"PyTorch, Azure, Java, Spark",PhD,0,Finance,2024-07-15,2024-08-15,980,5.1,Future Systems -AI08028,Machine Learning Researcher,109705,EUR,93249,MI,FT,Germany,M,Russia,0,"Python, Linux, NLP",PhD,4,Real Estate,2024-12-18,2025-01-13,2235,7.4,AI Innovations -AI08029,AI Consultant,55926,USD,55926,EN,FT,South Korea,M,Poland,50,"Python, SQL, MLOps",Master,1,Consulting,2024-05-08,2024-06-17,538,7,Advanced Robotics -AI08030,Data Analyst,154681,USD,154681,SE,PT,Denmark,L,Denmark,50,"Git, Hadoop, Tableau, Data Visualization",Associate,7,Government,2025-02-09,2025-04-17,975,9.4,Digital Transformation LLC -AI08031,NLP Engineer,72975,USD,72975,EX,PT,India,M,India,0,"GCP, Tableau, Scala",PhD,14,Technology,2024-04-10,2024-05-03,556,9.2,Machine Intelligence Group -AI08032,Deep Learning Engineer,122344,USD,122344,SE,CT,Sweden,M,Brazil,50,"Spark, AWS, Git, PyTorch",Bachelor,8,Real Estate,2024-05-16,2024-07-25,1732,7,DeepTech Ventures -AI08033,Machine Learning Researcher,78706,EUR,66900,MI,FT,Germany,M,Germany,0,"Data Visualization, AWS, Python, Spark, TensorFlow",PhD,2,Retail,2024-05-22,2024-07-24,737,9.5,Machine Intelligence Group -AI08034,Data Analyst,87488,EUR,74365,SE,FT,Austria,S,Austria,50,"Kubernetes, PyTorch, TensorFlow, Statistics",Bachelor,8,Automotive,2024-11-30,2024-12-30,2075,6.2,DeepTech Ventures -AI08035,Data Scientist,109945,GBP,82459,SE,PT,United Kingdom,S,Australia,50,"AWS, Data Visualization, Scala, Tableau, MLOps",Associate,5,Telecommunications,2025-02-20,2025-03-10,1706,6.6,Algorithmic Solutions -AI08036,Autonomous Systems Engineer,128555,USD,128555,SE,FT,United States,S,Ireland,0,"SQL, Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,9,Automotive,2024-09-23,2024-11-10,2140,6.4,DataVision Ltd -AI08037,Data Engineer,83558,USD,83558,EX,FL,China,M,Portugal,0,"Java, GCP, Tableau, Deep Learning",Associate,13,Healthcare,2024-11-22,2025-01-12,1439,8.8,Advanced Robotics -AI08038,Autonomous Systems Engineer,59257,USD,59257,SE,CT,China,L,China,50,"R, Mathematics, Tableau",Bachelor,8,Education,2024-02-09,2024-04-11,1925,9.6,DeepTech Ventures -AI08039,Research Scientist,211226,USD,211226,EX,CT,Sweden,L,Sweden,50,"Hadoop, Scala, GCP, Docker, R",PhD,10,Real Estate,2024-10-18,2024-12-08,1516,8.5,Cloud AI Solutions -AI08040,Data Engineer,58429,EUR,49665,EN,FT,Austria,S,Austria,50,"Linux, Python, Computer Vision, AWS",Master,0,Healthcare,2024-05-11,2024-07-10,1024,8.5,AI Innovations -AI08041,AI Specialist,30008,USD,30008,EN,CT,India,L,India,100,"Linux, PyTorch, Git, Computer Vision",Master,1,Real Estate,2024-10-29,2024-11-23,799,6.5,Machine Intelligence Group -AI08042,Principal Data Scientist,63440,USD,63440,EX,PT,India,M,India,0,"Hadoop, Java, SQL, Computer Vision",PhD,18,Energy,2024-10-19,2024-12-06,1042,9.3,DataVision Ltd -AI08043,AI Architect,75902,USD,75902,EN,PT,United States,S,United States,50,"AWS, Data Visualization, Tableau, Scala",Associate,0,Real Estate,2024-02-05,2024-03-03,1077,8.2,Algorithmic Solutions -AI08044,AI Consultant,212552,GBP,159414,EX,FL,United Kingdom,S,Austria,100,"SQL, Spark, MLOps",Associate,11,Finance,2025-03-20,2025-05-02,516,7.9,Neural Networks Co -AI08045,AI Product Manager,105830,EUR,89956,MI,FL,France,L,France,100,"Hadoop, GCP, Scala, Tableau",Bachelor,3,Healthcare,2024-08-16,2024-10-12,878,9.8,Autonomous Tech -AI08046,Head of AI,82250,USD,82250,MI,PT,Sweden,M,Sweden,0,"Azure, MLOps, Statistics, R, GCP",Associate,2,Consulting,2024-07-15,2024-08-29,1795,7.2,DataVision Ltd -AI08047,AI Product Manager,106488,EUR,90515,SE,PT,Germany,M,Germany,0,"PyTorch, Kubernetes, Computer Vision, TensorFlow, Spark",Bachelor,9,Telecommunications,2024-12-20,2025-01-31,960,7.2,Quantum Computing Inc -AI08048,Head of AI,147509,USD,147509,SE,CT,Sweden,L,Sweden,0,"Python, Mathematics, Linux, TensorFlow, Deep Learning",Master,6,Healthcare,2024-12-18,2025-01-25,1965,6,Cognitive Computing -AI08049,AI Specialist,107129,EUR,91060,MI,CT,Netherlands,L,Netherlands,0,"R, PyTorch, GCP, Computer Vision, Git",Bachelor,2,Automotive,2024-04-19,2024-05-30,1355,9.2,Machine Intelligence Group -AI08050,AI Research Scientist,263994,CHF,237595,EX,FT,Switzerland,S,Switzerland,100,"Azure, Python, MLOps, Kubernetes, Hadoop",Bachelor,19,Consulting,2024-12-11,2025-01-16,1088,6.4,Quantum Computing Inc -AI08051,NLP Engineer,115888,SGD,150654,MI,FT,Singapore,L,Australia,50,"Kubernetes, Docker, Spark, Linux, Computer Vision",Associate,2,Energy,2024-05-03,2024-06-29,2345,5.2,Autonomous Tech -AI08052,Research Scientist,183653,SGD,238749,EX,PT,Singapore,M,Singapore,100,"Statistics, Computer Vision, Python",Master,14,Government,2024-10-22,2024-12-06,2176,8.6,DeepTech Ventures -AI08053,Autonomous Systems Engineer,136651,SGD,177646,EX,FT,Singapore,S,Singapore,50,"Statistics, Python, AWS, PyTorch",Master,18,Real Estate,2024-12-20,2025-01-29,1776,8.5,Autonomous Tech -AI08054,AI Product Manager,138663,USD,138663,EX,CT,Finland,M,New Zealand,100,"Git, Python, Mathematics, Linux",Associate,13,Gaming,2024-06-16,2024-08-04,2319,6.5,Future Systems -AI08055,AI Software Engineer,156452,GBP,117339,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, Tableau, Statistics",Bachelor,10,Gaming,2024-03-26,2024-05-10,1929,7.2,Neural Networks Co -AI08056,Computer Vision Engineer,91988,USD,91988,MI,CT,United States,M,United States,50,"Git, Scala, Data Visualization",PhD,4,Healthcare,2024-07-23,2024-10-02,1514,8.5,TechCorp Inc -AI08057,AI Product Manager,170809,GBP,128107,EX,CT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, AWS, Computer Vision",Master,11,Telecommunications,2024-08-23,2024-09-06,1384,9.9,Digital Transformation LLC -AI08058,NLP Engineer,102306,EUR,86960,MI,PT,Netherlands,L,Indonesia,100,"SQL, NLP, Python",Master,4,Automotive,2024-10-19,2024-12-24,1838,8.7,Machine Intelligence Group -AI08059,Computer Vision Engineer,66585,EUR,56597,EN,CT,France,S,France,0,"NLP, PyTorch, MLOps, Kubernetes, TensorFlow",Associate,0,Education,2024-02-03,2024-02-27,1482,7.9,Predictive Systems -AI08060,Machine Learning Researcher,207692,CHF,186923,SE,CT,Switzerland,M,Switzerland,100,"Python, Spark, TensorFlow, Tableau, PyTorch",PhD,5,Transportation,2024-03-28,2024-06-02,1924,9.6,Quantum Computing Inc -AI08061,Data Analyst,129361,USD,129361,SE,CT,Sweden,M,Sweden,100,"PyTorch, Spark, Hadoop",Master,8,Finance,2024-06-01,2024-07-16,1043,10,Algorithmic Solutions -AI08062,Head of AI,97125,USD,97125,EN,CT,Denmark,L,Denmark,100,"Scala, Tableau, Kubernetes",PhD,0,Energy,2024-01-18,2024-03-28,760,9.3,Algorithmic Solutions -AI08063,Principal Data Scientist,97060,USD,97060,MI,PT,Finland,M,Finland,0,"R, AWS, Statistics, Linux, Deep Learning",PhD,3,Transportation,2024-12-16,2025-01-03,1883,9.8,Future Systems -AI08064,AI Software Engineer,69840,USD,69840,SE,FT,China,L,Spain,50,"Java, AWS, Computer Vision, Docker, Deep Learning",Master,9,Energy,2024-03-12,2024-04-04,2372,7.1,Machine Intelligence Group -AI08065,ML Ops Engineer,86753,EUR,73740,MI,PT,France,L,France,0,"Java, Hadoop, Linux",Associate,3,Real Estate,2024-11-28,2024-12-30,1934,6.7,Quantum Computing Inc -AI08066,Research Scientist,120164,USD,120164,EN,PT,Norway,L,Norway,50,"Computer Vision, Scala, SQL",Associate,1,Telecommunications,2024-02-21,2024-04-14,2276,8.7,Digital Transformation LLC -AI08067,Deep Learning Engineer,63400,USD,63400,EN,PT,Finland,M,Finland,100,"GCP, Tableau, PyTorch",Master,0,Telecommunications,2025-02-17,2025-04-30,1004,8.3,Neural Networks Co -AI08068,Deep Learning Engineer,195225,AUD,263554,EX,FL,Australia,L,Hungary,50,"Git, Python, Azure",Master,17,Automotive,2024-03-06,2024-04-24,1304,7.9,Neural Networks Co -AI08069,AI Specialist,121448,USD,121448,SE,PT,South Korea,L,Luxembourg,50,"Hadoop, Linux, Git, Scala, Java",Master,9,Finance,2024-09-22,2024-10-19,1260,5.3,Autonomous Tech -AI08070,Autonomous Systems Engineer,127574,CHF,114817,MI,CT,Switzerland,S,Canada,0,"TensorFlow, Azure, Spark, Kubernetes",Master,4,Finance,2024-09-18,2024-10-23,733,9.1,Quantum Computing Inc -AI08071,NLP Engineer,28917,USD,28917,EN,FL,China,L,China,50,"SQL, PyTorch, Java, Docker, Linux",PhD,1,Finance,2024-11-08,2024-11-29,2062,8.5,Advanced Robotics -AI08072,NLP Engineer,175601,USD,175601,SE,CT,Denmark,S,Denmark,100,"Python, Scala, AWS, Spark",Master,5,Technology,2024-05-27,2024-06-16,1276,8.5,Quantum Computing Inc -AI08073,Principal Data Scientist,110916,JPY,12200760,SE,CT,Japan,S,United States,100,"Python, Linux, SQL, R, Statistics",Master,9,Retail,2024-03-07,2024-03-30,2208,9.7,Algorithmic Solutions -AI08074,Research Scientist,93983,CAD,117479,MI,PT,Canada,L,Canada,0,"Data Visualization, Kubernetes, Mathematics",Bachelor,4,Healthcare,2024-03-17,2024-03-31,2013,5.2,DeepTech Ventures -AI08075,NLP Engineer,323422,USD,323422,EX,PT,Norway,M,Norway,0,"Docker, R, Data Visualization, Deep Learning, Git",Associate,10,Education,2024-09-25,2024-11-06,1045,7.1,Smart Analytics -AI08076,Robotics Engineer,179355,USD,179355,SE,CT,United States,L,United States,50,"NLP, Python, Data Visualization, Azure, Java",PhD,5,Finance,2024-02-20,2024-04-12,2445,9.2,Advanced Robotics -AI08077,AI Product Manager,85532,USD,85532,EN,FT,Denmark,S,Denmark,50,"Docker, Kubernetes, AWS",Master,0,Telecommunications,2024-11-03,2024-12-30,837,5.9,Machine Intelligence Group -AI08078,Autonomous Systems Engineer,44071,USD,44071,MI,FT,India,L,India,0,"Java, PyTorch, NLP, R, TensorFlow",Associate,3,Government,2025-01-18,2025-03-02,974,8.9,Autonomous Tech -AI08079,Robotics Engineer,130737,USD,130737,SE,FL,Ireland,M,Ireland,50,"Linux, PyTorch, Java, Tableau, TensorFlow",Master,9,Automotive,2024-10-18,2024-11-29,1011,6.9,Cognitive Computing -AI08080,Deep Learning Engineer,147663,CHF,132897,MI,CT,Switzerland,L,Switzerland,50,"SQL, Computer Vision, Scala, GCP",Master,4,Energy,2025-02-18,2025-03-29,2092,7.6,AI Innovations -AI08081,Machine Learning Engineer,269175,USD,269175,EX,FL,Denmark,M,Argentina,100,"AWS, Hadoop, Java, Statistics, Deep Learning",Master,18,Real Estate,2024-02-26,2024-04-05,2398,6.5,AI Innovations -AI08082,Computer Vision Engineer,152150,EUR,129328,SE,FT,France,L,France,50,"Linux, Python, Data Visualization, Java",PhD,5,Consulting,2024-04-07,2024-05-17,1392,9.8,Autonomous Tech -AI08083,AI Consultant,18965,USD,18965,EN,FL,India,S,India,50,"Python, GCP, Deep Learning",Master,0,Automotive,2025-03-07,2025-03-28,2011,7.6,Cloud AI Solutions -AI08084,NLP Engineer,293774,USD,293774,EX,FT,Norway,S,Norway,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,14,Media,2024-06-15,2024-07-21,2330,9.2,Cognitive Computing -AI08085,Head of AI,116082,USD,116082,SE,CT,South Korea,M,United Kingdom,50,"Tableau, Deep Learning, SQL",PhD,9,Consulting,2025-03-02,2025-04-03,1469,6.8,Machine Intelligence Group -AI08086,AI Consultant,55542,USD,55542,EN,FT,South Korea,S,Argentina,100,"Kubernetes, Tableau, MLOps",Master,1,Real Estate,2024-02-20,2024-04-13,1159,8,Quantum Computing Inc -AI08087,AI Consultant,136996,USD,136996,SE,CT,Norway,M,Norway,100,"Linux, SQL, Deep Learning, PyTorch, Hadoop",Bachelor,6,Retail,2024-02-21,2024-03-08,2025,9.8,Cloud AI Solutions -AI08088,ML Ops Engineer,79319,EUR,67421,MI,PT,France,L,France,0,"MLOps, SQL, TensorFlow, Hadoop",Bachelor,3,Media,2024-02-05,2024-03-31,1325,9.7,DataVision Ltd -AI08089,Computer Vision Engineer,105493,CAD,131866,SE,CT,Canada,S,Canada,0,"PyTorch, Linux, Python, Statistics, GCP",Master,9,Education,2025-01-02,2025-01-23,902,9.8,Cloud AI Solutions -AI08090,AI Research Scientist,58931,USD,58931,EN,CT,Israel,S,Israel,50,"Computer Vision, R, SQL",Associate,0,Transportation,2024-09-03,2024-09-21,1976,8.9,DataVision Ltd -AI08091,AI Specialist,269865,USD,269865,EX,CT,Ireland,L,Ireland,100,"Linux, Azure, Deep Learning",Bachelor,18,Technology,2025-03-30,2025-06-07,729,5.7,Autonomous Tech -AI08092,Head of AI,94339,USD,94339,MI,CT,Norway,S,Norway,50,"Kubernetes, TensorFlow, Azure, Tableau, MLOps",Associate,3,Government,2024-04-14,2024-05-02,1970,5.9,Autonomous Tech -AI08093,AI Product Manager,295017,JPY,32451870,EX,CT,Japan,L,Estonia,50,"Kubernetes, Java, Git, SQL",Master,14,Media,2024-09-22,2024-11-04,1295,6.3,Digital Transformation LLC -AI08094,Machine Learning Engineer,101293,SGD,131681,MI,CT,Singapore,S,Singapore,100,"NLP, SQL, Azure, Scala",PhD,2,Healthcare,2025-01-20,2025-03-07,2199,7.9,Machine Intelligence Group -AI08095,AI Specialist,32078,USD,32078,EN,FT,India,L,India,100,"Computer Vision, Tableau, GCP",Associate,0,Consulting,2025-04-16,2025-06-14,2105,5.5,Autonomous Tech -AI08096,Head of AI,99238,GBP,74429,MI,FT,United Kingdom,M,United Kingdom,0,"NLP, R, Kubernetes",Associate,3,Healthcare,2024-09-01,2024-09-23,956,8.2,DeepTech Ventures -AI08097,Data Analyst,87032,USD,87032,MI,FL,Finland,S,Finland,100,"Python, Kubernetes, Tableau",Bachelor,4,Consulting,2024-04-22,2024-05-17,1298,8.2,DeepTech Ventures -AI08098,Data Scientist,156773,USD,156773,SE,FT,Israel,L,Israel,100,"Statistics, Kubernetes, NLP, Linux",Master,5,Technology,2024-02-16,2024-04-03,2324,9.8,Smart Analytics -AI08099,AI Research Scientist,61019,AUD,82376,EN,FT,Australia,L,Australia,100,"Statistics, Git, NLP, Python",Bachelor,0,Real Estate,2024-11-10,2024-11-24,1197,8.6,DeepTech Ventures -AI08100,AI Research Scientist,70543,EUR,59962,EN,PT,Germany,M,Malaysia,0,"TensorFlow, Linux, Tableau, Hadoop, Kubernetes",Bachelor,1,Automotive,2025-03-20,2025-05-19,1099,8,Cloud AI Solutions -AI08101,Deep Learning Engineer,65930,AUD,89006,EN,CT,Australia,S,Australia,50,"GCP, NLP, Hadoop",Master,0,Gaming,2025-02-13,2025-03-07,1258,9.7,Digital Transformation LLC -AI08102,Data Scientist,61443,EUR,52227,EN,CT,France,M,France,0,"SQL, Hadoop, MLOps",Master,1,Healthcare,2024-08-06,2024-10-08,793,7,Algorithmic Solutions -AI08103,Deep Learning Engineer,389007,CHF,350106,EX,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, Hadoop, Deep Learning, Spark",PhD,17,Gaming,2025-01-06,2025-02-22,1261,9.2,Smart Analytics -AI08104,Data Engineer,76813,EUR,65291,MI,PT,Germany,S,Germany,50,"Kubernetes, Spark, NLP, Statistics",Associate,2,Energy,2024-04-22,2024-06-14,1138,8.4,Future Systems -AI08105,ML Ops Engineer,98906,EUR,84070,MI,CT,Austria,L,Austria,0,"Computer Vision, Python, NLP, Spark, TensorFlow",Associate,4,Manufacturing,2025-01-23,2025-03-19,1508,7,DeepTech Ventures -AI08106,Data Scientist,74348,GBP,55761,MI,FL,United Kingdom,S,Singapore,100,"MLOps, Kubernetes, Deep Learning",PhD,3,Government,2025-01-30,2025-04-01,860,6,TechCorp Inc -AI08107,Data Analyst,91122,CHF,82010,EN,FL,Switzerland,M,Switzerland,100,"Mathematics, Deep Learning, Computer Vision, PyTorch, Kubernetes",PhD,0,Government,2024-02-12,2024-04-11,1786,8.6,Advanced Robotics -AI08108,Data Scientist,185096,EUR,157332,EX,FT,France,S,France,100,"Git, Azure, Linux",Bachelor,14,Consulting,2024-01-16,2024-03-06,2314,9.5,Quantum Computing Inc -AI08109,NLP Engineer,94648,EUR,80451,MI,FT,France,M,France,50,"GCP, R, Kubernetes",PhD,3,Automotive,2024-04-14,2024-05-28,2479,7.7,Digital Transformation LLC -AI08110,AI Architect,81723,EUR,69465,MI,PT,France,S,France,0,"Java, R, Spark, SQL, MLOps",Master,3,Gaming,2024-03-14,2024-03-28,724,6.2,Autonomous Tech -AI08111,Autonomous Systems Engineer,249442,GBP,187082,EX,FT,United Kingdom,M,United Kingdom,50,"Deep Learning, R, Tableau, GCP",Bachelor,11,Finance,2025-01-28,2025-03-16,1202,9.4,Digital Transformation LLC -AI08112,Robotics Engineer,111472,CAD,139340,SE,PT,Canada,M,Ghana,100,"Scala, Git, Computer Vision, NLP, AWS",PhD,8,Healthcare,2025-01-04,2025-01-26,2448,6.5,Machine Intelligence Group -AI08113,Data Analyst,107982,USD,107982,MI,PT,Norway,S,Norway,100,"Java, R, Azure, Hadoop, Git",Master,2,Finance,2025-04-03,2025-06-02,2009,8.4,Cognitive Computing -AI08114,NLP Engineer,106322,USD,106322,SE,FT,South Korea,L,South Korea,50,"Kubernetes, TensorFlow, Azure",PhD,5,Technology,2024-03-16,2024-04-16,2356,8.8,Cognitive Computing -AI08115,Data Scientist,97096,USD,97096,MI,PT,South Korea,L,Luxembourg,0,"Linux, NLP, Tableau, Scala",Master,2,Automotive,2025-03-13,2025-05-11,2414,6.3,Advanced Robotics -AI08116,Machine Learning Engineer,71329,USD,71329,SE,FL,China,L,China,0,"GCP, PyTorch, TensorFlow, Kubernetes, AWS",Bachelor,7,Education,2024-10-14,2024-10-31,2022,6.6,DataVision Ltd -AI08117,Machine Learning Researcher,204502,USD,204502,EX,FT,Israel,L,Canada,0,"Computer Vision, Deep Learning, SQL, Linux, Python",Associate,17,Automotive,2024-05-22,2024-06-12,636,7.7,Quantum Computing Inc -AI08118,AI Software Engineer,78540,AUD,106029,EN,PT,Australia,L,Canada,0,"Linux, Deep Learning, Spark, Hadoop",PhD,1,Real Estate,2024-06-27,2024-07-17,1984,8.4,Machine Intelligence Group -AI08119,AI Specialist,102696,USD,102696,MI,FL,Norway,M,Norway,50,"GCP, Statistics, Linux, PyTorch",Bachelor,3,Technology,2024-10-01,2024-11-24,2251,8.7,Digital Transformation LLC -AI08120,Machine Learning Engineer,140672,USD,140672,SE,FL,Ireland,M,Ireland,0,"SQL, Kubernetes, Data Visualization",Master,6,Energy,2025-04-16,2025-05-15,1303,5.4,Smart Analytics -AI08121,AI Consultant,306231,JPY,33685410,EX,FT,Japan,L,Japan,50,"SQL, Linux, Spark, Azure, Hadoop",PhD,11,Transportation,2024-11-09,2025-01-13,2186,7.7,DeepTech Ventures -AI08122,Research Scientist,79751,USD,79751,MI,FT,Israel,L,Israel,0,"Linux, PyTorch, R, NLP",Associate,3,Consulting,2025-01-12,2025-02-10,1412,6.5,Future Systems -AI08123,Data Analyst,59536,AUD,80374,EN,PT,Australia,S,Australia,0,"Python, SQL, AWS",Master,1,Real Estate,2024-03-14,2024-04-17,905,7.5,DeepTech Ventures -AI08124,Data Analyst,217273,USD,217273,EX,CT,Sweden,M,Sweden,100,"GCP, Deep Learning, PyTorch",Bachelor,14,Retail,2024-09-05,2024-10-15,1637,8.5,DataVision Ltd -AI08125,AI Software Engineer,61375,USD,61375,EN,CT,Finland,M,Finland,0,"MLOps, Data Visualization, Python",Associate,1,Technology,2024-04-07,2024-05-06,1196,5.2,Cognitive Computing -AI08126,AI Research Scientist,84104,CHF,75694,EN,PT,Switzerland,S,Switzerland,100,"MLOps, Mathematics, Linux",Associate,0,Energy,2024-12-07,2025-01-11,1663,9.1,Predictive Systems -AI08127,Machine Learning Researcher,119885,JPY,13187350,SE,FT,Japan,M,Japan,50,"Hadoop, Statistics, Git",Master,8,Consulting,2024-04-15,2024-05-15,1847,5.7,Advanced Robotics -AI08128,Head of AI,49872,USD,49872,EN,CT,Finland,M,Germany,100,"GCP, Deep Learning, MLOps, Linux, SQL",Bachelor,1,Telecommunications,2024-03-06,2024-03-30,2282,8.6,AI Innovations -AI08129,AI Product Manager,83785,USD,83785,EX,PT,India,L,Hungary,100,"Scala, R, Statistics",Bachelor,16,Real Estate,2024-12-11,2025-01-24,970,5.9,Cloud AI Solutions -AI08130,Principal Data Scientist,47263,AUD,63805,EN,PT,Australia,S,Australia,100,"AWS, Kubernetes, PyTorch",Associate,1,Education,2025-02-23,2025-05-05,2397,9.9,DataVision Ltd -AI08131,Machine Learning Researcher,82949,CAD,103686,EN,FT,Canada,L,Canada,50,"Mathematics, Git, NLP, Python",PhD,1,Media,2025-04-14,2025-06-10,1455,5.5,Smart Analytics -AI08132,AI Architect,85674,USD,85674,MI,FL,Sweden,M,China,0,"SQL, Python, GCP, Azure",Associate,4,Automotive,2025-04-19,2025-06-25,2146,5.6,Predictive Systems -AI08133,Research Scientist,66353,USD,66353,MI,FL,South Korea,S,South Korea,100,"Python, Hadoop, Deep Learning, SQL",PhD,4,Transportation,2024-08-10,2024-10-12,507,5.8,AI Innovations -AI08134,AI Product Manager,169078,USD,169078,EX,FT,Sweden,S,Sweden,100,"GCP, Statistics, Tableau",Bachelor,18,Automotive,2025-03-05,2025-04-16,814,6.9,Cognitive Computing -AI08135,Autonomous Systems Engineer,181932,EUR,154642,EX,CT,Germany,M,Germany,100,"Docker, Spark, Scala",Master,17,Education,2024-01-02,2024-01-28,1918,7.7,Cognitive Computing -AI08136,Autonomous Systems Engineer,93368,EUR,79363,SE,CT,Germany,S,Germany,50,"R, Scala, Data Visualization",Master,6,Healthcare,2024-08-02,2024-09-01,705,5.2,Neural Networks Co -AI08137,AI Specialist,112677,USD,112677,SE,CT,Israel,S,Israel,50,"Data Visualization, Linux, SQL, R",Bachelor,9,Automotive,2025-02-26,2025-04-06,1251,6.3,Digital Transformation LLC -AI08138,Computer Vision Engineer,145606,EUR,123765,EX,CT,Germany,M,Germany,50,"Java, SQL, Hadoop, Kubernetes",PhD,12,Real Estate,2024-09-20,2024-11-09,1136,6.7,Quantum Computing Inc -AI08139,AI Specialist,60885,USD,60885,EN,FL,Ireland,S,Argentina,50,"Python, SQL, Linux",PhD,0,Manufacturing,2025-03-07,2025-05-08,640,7.1,Digital Transformation LLC -AI08140,Robotics Engineer,53376,AUD,72058,EN,FL,Australia,M,China,100,"Deep Learning, GCP, Kubernetes",Bachelor,0,Technology,2024-08-24,2024-09-26,1725,7,Algorithmic Solutions -AI08141,AI Consultant,75818,EUR,64445,EN,CT,Netherlands,L,Netherlands,0,"Python, Spark, Scala, AWS, R",Master,0,Gaming,2024-10-28,2025-01-08,544,8.3,Quantum Computing Inc -AI08142,Principal Data Scientist,99061,EUR,84202,MI,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, Tableau",Associate,3,Gaming,2025-02-19,2025-04-17,1973,7,Quantum Computing Inc -AI08143,Data Analyst,107756,EUR,91593,MI,FT,Germany,L,Germany,50,"Azure, SQL, Java",Associate,4,Healthcare,2024-10-30,2024-12-10,661,8.1,Cognitive Computing -AI08144,Computer Vision Engineer,75125,USD,75125,SE,FL,China,L,China,0,"Tableau, Azure, Kubernetes, Mathematics",PhD,9,Automotive,2024-01-07,2024-02-08,1592,7.2,Smart Analytics -AI08145,Machine Learning Researcher,96840,CHF,87156,EN,CT,Switzerland,S,Switzerland,50,"Python, TensorFlow, PyTorch, Tableau, Mathematics",Bachelor,0,Finance,2024-12-25,2025-02-03,578,9.1,DataVision Ltd -AI08146,NLP Engineer,78676,USD,78676,EN,CT,Sweden,M,Sweden,100,"Mathematics, Hadoop, Python, Spark",PhD,0,Gaming,2024-07-03,2024-08-25,1565,9.9,Autonomous Tech -AI08147,Computer Vision Engineer,206627,CHF,185964,EX,FL,Switzerland,S,South Korea,100,"TensorFlow, Deep Learning, Tableau, Kubernetes, SQL",Bachelor,10,Transportation,2025-04-14,2025-05-26,767,7.4,Predictive Systems -AI08148,Principal Data Scientist,74509,USD,74509,SE,CT,China,L,Vietnam,100,"TensorFlow, Docker, Kubernetes, GCP, Data Visualization",Bachelor,9,Education,2024-07-17,2024-08-22,2330,7.3,Autonomous Tech -AI08149,Data Engineer,147081,EUR,125019,SE,FL,Germany,L,Malaysia,50,"R, SQL, Statistics",PhD,5,Government,2024-11-05,2024-12-17,1029,7.6,Autonomous Tech -AI08150,AI Consultant,148813,CAD,186016,EX,PT,Canada,M,Canada,0,"Tableau, GCP, Scala, NLP",Bachelor,15,Government,2024-08-22,2024-10-21,2385,8.7,Algorithmic Solutions -AI08151,Deep Learning Engineer,194557,AUD,262652,EX,CT,Australia,M,Australia,100,"Mathematics, Hadoop, Data Visualization, AWS",Master,18,Energy,2024-11-09,2025-01-16,1321,6.4,Quantum Computing Inc -AI08152,Data Analyst,220707,EUR,187601,EX,PT,Germany,S,Germany,100,"Mathematics, SQL, AWS, Kubernetes, Linux",PhD,18,Manufacturing,2024-01-08,2024-02-19,1499,6.4,Cognitive Computing -AI08153,AI Architect,83907,EUR,71321,EN,FT,Austria,L,Brazil,0,"R, Deep Learning, Tableau, PyTorch, Mathematics",PhD,0,Automotive,2024-09-29,2024-10-30,1079,8.8,DataVision Ltd -AI08154,NLP Engineer,203429,CHF,183086,SE,CT,Switzerland,M,China,100,"Kubernetes, AWS, GCP",PhD,5,Technology,2024-06-26,2024-07-22,1030,7.1,Advanced Robotics -AI08155,Head of AI,121903,USD,121903,SE,CT,South Korea,M,South Korea,0,"Python, Hadoop, Mathematics, Tableau, Computer Vision",Master,8,Media,2025-02-28,2025-03-18,667,6.9,Advanced Robotics -AI08156,Computer Vision Engineer,97513,CAD,121891,MI,PT,Canada,L,Canada,50,"Docker, Python, Statistics",Master,3,Real Estate,2024-05-11,2024-07-03,2187,7.1,Machine Intelligence Group -AI08157,AI Consultant,229343,CHF,206409,SE,FL,Switzerland,L,Switzerland,100,"PyTorch, Scala, MLOps, Computer Vision",PhD,6,Automotive,2024-06-20,2024-08-17,548,9.6,Autonomous Tech -AI08158,Data Scientist,135831,SGD,176580,SE,CT,Singapore,S,New Zealand,50,"AWS, Docker, Data Visualization, Deep Learning",Master,8,Manufacturing,2024-10-14,2024-11-18,1245,7.3,Algorithmic Solutions -AI08159,AI Specialist,229897,CHF,206907,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Computer Vision, Hadoop",PhD,9,Gaming,2024-07-14,2024-09-23,1540,5.1,Digital Transformation LLC -AI08160,Data Scientist,75572,AUD,102022,MI,FL,Australia,S,Australia,100,"Tableau, Python, Hadoop",Master,4,Healthcare,2024-09-10,2024-10-03,1850,9.3,Neural Networks Co -AI08161,AI Product Manager,160993,JPY,17709230,EX,FL,Japan,S,Japan,0,"Python, Kubernetes, Git, Linux",PhD,15,Real Estate,2024-05-11,2024-06-24,1652,6.6,Algorithmic Solutions -AI08162,Data Engineer,81776,SGD,106309,MI,CT,Singapore,S,Singapore,50,"R, PyTorch, Spark, Statistics",PhD,3,Consulting,2024-02-11,2024-04-17,820,5.6,Machine Intelligence Group -AI08163,Head of AI,81570,USD,81570,EN,PT,Finland,L,Finland,50,"Linux, Data Visualization, Hadoop, Azure, Tableau",Bachelor,0,Energy,2024-05-11,2024-06-12,507,7.4,Smart Analytics -AI08164,Autonomous Systems Engineer,93162,EUR,79188,MI,CT,Germany,S,Germany,100,"Data Visualization, Git, Python, Scala, Computer Vision",Master,4,Energy,2024-02-23,2024-04-27,535,7.2,Predictive Systems -AI08165,Machine Learning Researcher,227631,AUD,307302,EX,FT,Australia,S,Argentina,100,"SQL, GCP, Git",PhD,19,Gaming,2024-07-21,2024-09-26,640,6.2,AI Innovations -AI08166,AI Architect,131380,USD,131380,SE,FL,Sweden,L,Poland,100,"SQL, Deep Learning, Scala, Computer Vision, PyTorch",Bachelor,5,Telecommunications,2025-02-25,2025-05-01,2251,6.9,Algorithmic Solutions -AI08167,Data Analyst,33242,USD,33242,EN,FT,China,L,Estonia,0,"Kubernetes, SQL, Tableau",Associate,0,Healthcare,2024-08-07,2024-08-24,552,8.7,Cloud AI Solutions -AI08168,Data Scientist,336599,USD,336599,EX,FT,Denmark,L,Denmark,50,"PyTorch, Linux, Statistics, GCP, Python",Bachelor,14,Retail,2024-11-14,2025-01-14,1602,7,Smart Analytics -AI08169,AI Software Engineer,132545,SGD,172309,MI,FT,Singapore,L,United Kingdom,0,"AWS, Kubernetes, NLP, Azure",Bachelor,4,Consulting,2025-02-03,2025-02-21,2499,5.5,Smart Analytics -AI08170,AI Specialist,300635,USD,300635,EX,CT,United States,L,United States,100,"PyTorch, Python, Computer Vision, Scala",Associate,10,Energy,2024-06-18,2024-07-24,1527,7.8,Quantum Computing Inc -AI08171,AI Specialist,94953,USD,94953,MI,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Scala, Linux, TensorFlow",Bachelor,2,Healthcare,2024-01-04,2024-02-03,999,7.1,Machine Intelligence Group -AI08172,AI Architect,178775,AUD,241346,EX,FT,Australia,S,Denmark,0,"Java, Tableau, R, Statistics, GCP",Associate,11,Retail,2024-08-21,2024-10-13,1289,5,Machine Intelligence Group -AI08173,Data Analyst,74369,CAD,92961,MI,FT,Canada,S,Canada,100,"Statistics, Data Visualization, GCP, Hadoop",Associate,3,Real Estate,2024-11-10,2024-11-27,1659,7.9,Digital Transformation LLC -AI08174,Computer Vision Engineer,75798,USD,75798,EN,FL,Norway,M,Norway,0,"Statistics, R, Mathematics",Associate,1,Media,2024-04-28,2024-05-25,1617,6.8,DeepTech Ventures -AI08175,Autonomous Systems Engineer,186114,EUR,158197,EX,FL,Austria,L,Austria,100,"NLP, SQL, Data Visualization, Azure",Associate,19,Consulting,2024-12-15,2025-02-19,762,9.2,Cognitive Computing -AI08176,AI Product Manager,95648,USD,95648,MI,CT,Ireland,M,Austria,50,"Linux, Python, Java, Spark",Bachelor,4,Energy,2024-10-04,2024-11-29,1137,6.4,Digital Transformation LLC -AI08177,AI Research Scientist,359202,CHF,323282,EX,CT,Switzerland,M,Switzerland,0,"Python, MLOps, Computer Vision",Associate,13,Finance,2025-01-26,2025-03-29,1430,7.7,DataVision Ltd -AI08178,Head of AI,76073,GBP,57055,MI,FL,United Kingdom,S,United Kingdom,50,"Python, Git, TensorFlow, MLOps",Master,2,Technology,2024-09-17,2024-11-11,1703,7.3,Advanced Robotics -AI08179,NLP Engineer,49705,USD,49705,EN,FT,Finland,M,Indonesia,50,"Spark, Tableau, Azure, GCP",Bachelor,0,Telecommunications,2024-07-25,2024-08-30,1697,5.1,DataVision Ltd -AI08180,AI Consultant,98961,EUR,84117,MI,FL,Netherlands,S,Ireland,100,"R, PyTorch, Docker, Linux",Master,4,Technology,2025-01-16,2025-02-18,1231,6.1,Cloud AI Solutions -AI08181,Data Scientist,73832,USD,73832,EN,FL,United States,M,United States,0,"NLP, Spark, Deep Learning, MLOps",PhD,0,Healthcare,2025-04-28,2025-06-20,1551,5.2,Cloud AI Solutions -AI08182,NLP Engineer,209012,USD,209012,EX,FL,Sweden,M,Sweden,0,"Python, Kubernetes, Spark",Bachelor,16,Government,2024-10-04,2024-11-26,2115,7.8,DataVision Ltd -AI08183,AI Research Scientist,114933,JPY,12642630,MI,CT,Japan,M,Russia,0,"Kubernetes, Git, SQL",Associate,3,Automotive,2024-03-18,2024-05-29,608,6.3,Digital Transformation LLC -AI08184,Data Analyst,127420,CHF,114678,MI,FL,Switzerland,M,Switzerland,0,"Docker, Python, TensorFlow",PhD,3,Consulting,2024-04-30,2024-05-27,987,9.7,Smart Analytics -AI08185,Machine Learning Engineer,144510,EUR,122834,SE,PT,France,L,France,50,"Computer Vision, Hadoop, Mathematics",Master,5,Retail,2025-02-05,2025-02-24,2346,8.4,Digital Transformation LLC -AI08186,Autonomous Systems Engineer,99445,AUD,134251,SE,FT,Australia,S,Australia,50,"MLOps, Tableau, SQL, Data Visualization, R",PhD,9,Consulting,2024-08-30,2024-09-21,1691,8.9,Autonomous Tech -AI08187,AI Research Scientist,101862,EUR,86583,MI,FT,Netherlands,L,Netherlands,50,"Deep Learning, PyTorch, TensorFlow, GCP",Bachelor,4,Automotive,2024-09-04,2024-10-04,2009,7.1,Future Systems -AI08188,Computer Vision Engineer,54758,USD,54758,EN,CT,Israel,S,Ghana,0,"TensorFlow, SQL, MLOps, GCP",Bachelor,0,Transportation,2024-12-08,2025-02-18,1157,8.2,Neural Networks Co -AI08189,Robotics Engineer,93957,EUR,79863,MI,PT,Netherlands,S,Mexico,50,"GCP, SQL, Azure",PhD,4,Energy,2024-11-03,2025-01-03,569,6.7,Quantum Computing Inc -AI08190,Machine Learning Researcher,184257,EUR,156618,EX,PT,Austria,L,Austria,0,"SQL, Docker, Data Visualization",Associate,17,Telecommunications,2025-02-08,2025-04-17,1806,6.3,Cognitive Computing -AI08191,Head of AI,65196,EUR,55417,MI,PT,France,S,France,50,"SQL, TensorFlow, Data Visualization, Linux",PhD,2,Government,2024-09-16,2024-10-20,909,8.6,Future Systems -AI08192,Data Analyst,121164,USD,121164,EX,FL,South Korea,S,South Korea,50,"GCP, Git, Deep Learning, Docker",Bachelor,12,Education,2024-05-09,2024-06-11,1313,5.9,Machine Intelligence Group -AI08193,Machine Learning Engineer,93873,AUD,126729,SE,PT,Australia,S,Australia,50,"Mathematics, Data Visualization, Tableau, Linux, Hadoop",Bachelor,7,Retail,2024-06-04,2024-06-27,1816,9.2,Digital Transformation LLC -AI08194,Computer Vision Engineer,148307,USD,148307,MI,FL,Denmark,L,Denmark,50,"Java, Computer Vision, Python, Tableau, Data Visualization",PhD,3,Healthcare,2024-10-08,2024-11-09,2328,6.2,AI Innovations -AI08195,AI Specialist,145377,GBP,109033,EX,PT,United Kingdom,S,United Kingdom,100,"Git, Deep Learning, Data Visualization",PhD,10,Technology,2024-03-08,2024-05-14,1526,9.6,DataVision Ltd -AI08196,Autonomous Systems Engineer,42525,USD,42525,EN,PT,South Korea,M,Estonia,50,"SQL, Deep Learning, Java, Python",Associate,1,Finance,2024-10-26,2024-11-25,862,9.3,Cognitive Computing -AI08197,AI Software Engineer,282434,USD,282434,EX,CT,Denmark,S,Denmark,100,"Azure, Java, MLOps, SQL, R",PhD,18,Telecommunications,2024-06-07,2024-06-26,1490,8.2,DeepTech Ventures -AI08198,AI Research Scientist,209133,USD,209133,EX,FT,Norway,L,Germany,50,"Scala, Git, Computer Vision, Spark",Associate,15,Energy,2024-01-01,2024-01-26,2279,8.1,Cognitive Computing -AI08199,Principal Data Scientist,250333,GBP,187750,EX,FT,United Kingdom,L,United Kingdom,0,"Linux, Statistics, PyTorch, Mathematics, Tableau",Bachelor,18,Healthcare,2024-01-23,2024-03-22,1827,8,Predictive Systems -AI08200,Research Scientist,174979,USD,174979,EX,FL,Norway,S,Indonesia,100,"Deep Learning, AWS, Computer Vision, Scala",Bachelor,18,Technology,2024-03-16,2024-03-30,2275,7.5,Smart Analytics -AI08201,Data Scientist,101837,USD,101837,SE,CT,Sweden,S,Sweden,100,"Azure, Scala, PyTorch",Bachelor,6,Government,2024-10-03,2024-10-20,600,6.6,Quantum Computing Inc -AI08202,Machine Learning Researcher,109223,USD,109223,SE,FT,Finland,M,Estonia,100,"TensorFlow, Azure, Mathematics, Kubernetes, AWS",Bachelor,5,Gaming,2024-07-28,2024-08-16,1615,8.2,Algorithmic Solutions -AI08203,Machine Learning Researcher,160180,USD,160180,SE,CT,Norway,S,Norway,50,"Linux, Scala, Mathematics, Kubernetes, Tableau",PhD,8,Real Estate,2024-11-06,2025-01-07,1020,6.1,Autonomous Tech -AI08204,Principal Data Scientist,52809,USD,52809,EN,PT,South Korea,L,South Korea,0,"Tableau, PyTorch, Git",Bachelor,1,Retail,2024-05-04,2024-05-30,1410,6.8,Autonomous Tech -AI08205,Computer Vision Engineer,218360,USD,218360,EX,FT,Norway,M,Norway,0,"Kubernetes, R, AWS, Mathematics, Statistics",Bachelor,12,Healthcare,2025-04-06,2025-04-26,2264,9.8,Digital Transformation LLC -AI08206,AI Consultant,99844,EUR,84867,MI,FT,Austria,L,India,0,"Hadoop, TensorFlow, Java, GCP, Docker",Bachelor,2,Retail,2024-07-28,2024-10-05,1801,8.3,Algorithmic Solutions -AI08207,AI Research Scientist,191537,SGD,248998,EX,FL,Singapore,L,Ireland,0,"Data Visualization, Hadoop, Computer Vision",Associate,12,Finance,2024-03-25,2024-04-29,928,6.4,Algorithmic Solutions -AI08208,Machine Learning Researcher,225775,USD,225775,EX,CT,Israel,M,Israel,0,"Python, Java, Hadoop, GCP, NLP",Bachelor,14,Finance,2024-05-13,2024-06-02,1054,5.5,AI Innovations -AI08209,Data Scientist,83618,USD,83618,EN,FL,Finland,L,Finland,0,"TensorFlow, Python, Hadoop, Tableau",Master,0,Automotive,2024-11-14,2025-01-21,1114,8.9,Neural Networks Co -AI08210,ML Ops Engineer,167785,EUR,142617,EX,FT,Germany,S,Germany,100,"Git, Deep Learning, Azure",Master,14,Manufacturing,2024-09-30,2024-10-29,1951,8.1,Machine Intelligence Group -AI08211,AI Research Scientist,25456,USD,25456,EN,CT,India,S,India,0,"AWS, Mathematics, Python",Bachelor,0,Government,2024-10-05,2024-10-19,1184,6.8,Neural Networks Co -AI08212,Data Analyst,109322,USD,109322,SE,CT,South Korea,L,South Korea,50,"Python, SQL, TensorFlow, AWS, Java",PhD,6,Gaming,2024-03-05,2024-05-03,2326,9.2,TechCorp Inc -AI08213,AI Architect,100260,USD,100260,SE,FL,Finland,M,Belgium,50,"PyTorch, Hadoop, Docker, Computer Vision",PhD,9,Manufacturing,2024-09-07,2024-10-14,1995,10,Smart Analytics -AI08214,Data Analyst,111999,USD,111999,SE,PT,Israel,M,Israel,50,"PyTorch, Python, Java, NLP, Hadoop",PhD,5,Automotive,2025-03-02,2025-05-09,833,5,AI Innovations -AI08215,Robotics Engineer,70798,JPY,7787780,EN,FT,Japan,M,Japan,100,"Tableau, TensorFlow, Python",PhD,1,Finance,2024-12-17,2025-01-04,1022,6.7,DataVision Ltd -AI08216,Robotics Engineer,75569,AUD,102018,MI,PT,Australia,S,Australia,50,"AWS, PyTorch, SQL",Bachelor,4,Gaming,2025-03-15,2025-05-06,1557,6.9,Neural Networks Co -AI08217,Autonomous Systems Engineer,173910,USD,173910,EX,PT,Israel,L,Israel,0,"TensorFlow, Deep Learning, Azure",Master,10,Healthcare,2025-01-18,2025-03-06,1685,5.6,Smart Analytics -AI08218,AI Software Engineer,234620,USD,234620,EX,PT,United States,M,United States,50,"Data Visualization, Git, GCP",Master,11,Consulting,2024-03-19,2024-05-30,2246,5.6,TechCorp Inc -AI08219,Data Scientist,54313,EUR,46166,EN,FL,Netherlands,S,Netherlands,50,"Azure, R, Scala, SQL, Git",Associate,1,Transportation,2024-04-04,2024-05-14,626,5.5,Predictive Systems -AI08220,Machine Learning Engineer,223033,GBP,167275,EX,FL,United Kingdom,S,Mexico,50,"Java, Computer Vision, SQL",Bachelor,14,Telecommunications,2024-05-05,2024-06-16,531,9.2,Autonomous Tech -AI08221,ML Ops Engineer,235007,USD,235007,EX,FT,South Korea,L,South Korea,0,"SQL, Kubernetes, NLP",Master,16,Healthcare,2024-10-22,2024-12-18,2222,9.2,TechCorp Inc -AI08222,AI Specialist,68349,EUR,58097,EN,PT,Netherlands,S,Netherlands,100,"Docker, NLP, Data Visualization, Linux",Master,0,Finance,2025-04-19,2025-06-14,2333,8.6,Future Systems -AI08223,AI Consultant,88924,USD,88924,MI,CT,Israel,L,Israel,100,"SQL, PyTorch, Deep Learning, Azure, AWS",Master,4,Real Estate,2024-03-23,2024-05-25,1368,5.8,Predictive Systems -AI08224,AI Specialist,107723,USD,107723,SE,FT,South Korea,L,South Korea,50,"R, Python, Statistics, Spark, GCP",Associate,5,Energy,2025-04-13,2025-06-23,664,8.2,Machine Intelligence Group -AI08225,AI Architect,100120,USD,100120,MI,FL,Denmark,S,Denmark,100,"Python, Git, Spark",Associate,4,Technology,2024-02-17,2024-04-07,2445,5.5,Neural Networks Co -AI08226,AI Specialist,52959,USD,52959,EN,CT,Israel,S,Israel,50,"Python, Tableau, Git",Master,1,Retail,2024-12-09,2025-01-28,645,5.7,DataVision Ltd -AI08227,ML Ops Engineer,88552,EUR,75269,EN,CT,Germany,L,Portugal,50,"MLOps, Tableau, SQL",PhD,0,Consulting,2025-03-02,2025-04-08,1539,5.8,AI Innovations -AI08228,AI Research Scientist,152649,CHF,137384,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, Kubernetes, MLOps",Bachelor,6,Transportation,2025-04-20,2025-06-07,963,5.9,Cloud AI Solutions -AI08229,Computer Vision Engineer,89988,USD,89988,EX,FL,China,L,China,100,"TensorFlow, Spark, Data Visualization, SQL, Docker",Bachelor,19,Healthcare,2024-12-31,2025-01-23,686,6.8,Algorithmic Solutions -AI08230,Principal Data Scientist,91107,USD,91107,MI,PT,United States,S,Japan,0,"R, Data Visualization, Linux",PhD,4,Retail,2025-04-05,2025-04-23,2056,8.4,Digital Transformation LLC -AI08231,AI Software Engineer,144476,USD,144476,MI,FT,United States,L,Mexico,100,"Python, SQL, Tableau, Git, Java",Master,2,Manufacturing,2024-11-04,2024-12-02,1950,6.9,Advanced Robotics -AI08232,Data Engineer,161347,CHF,145212,SE,PT,Switzerland,M,Switzerland,0,"Data Visualization, Spark, PyTorch, Git, Statistics",Bachelor,6,Telecommunications,2024-11-24,2025-01-11,1879,9.9,DataVision Ltd -AI08233,Principal Data Scientist,140235,AUD,189317,EX,FT,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau",Master,11,Energy,2024-05-27,2024-06-13,2013,9.6,Algorithmic Solutions -AI08234,Data Analyst,148219,USD,148219,EX,CT,Sweden,S,Sweden,100,"Java, Azure, Tableau, Python",Associate,16,Manufacturing,2024-10-26,2024-12-31,1949,8.6,Smart Analytics -AI08235,AI Architect,105601,SGD,137281,SE,FT,Singapore,S,France,100,"Git, Python, Hadoop",Master,7,Media,2024-01-23,2024-03-30,2256,5.8,AI Innovations -AI08236,AI Architect,64809,JPY,7128990,EN,CT,Japan,L,Portugal,0,"Docker, R, NLP",Bachelor,1,Technology,2025-01-14,2025-02-15,1701,7.2,Algorithmic Solutions -AI08237,Machine Learning Researcher,78106,EUR,66390,EN,FT,Austria,L,Germany,50,"Spark, PyTorch, R, Computer Vision",Master,1,Consulting,2025-04-25,2025-06-26,2113,9.1,Advanced Robotics -AI08238,Data Analyst,60250,SGD,78325,EN,FL,Singapore,M,Singapore,100,"SQL, Scala, Kubernetes, Deep Learning",PhD,1,Retail,2025-04-01,2025-05-30,1424,7.3,Cloud AI Solutions -AI08239,Machine Learning Researcher,54773,GBP,41080,EN,CT,United Kingdom,S,United Kingdom,100,"SQL, TensorFlow, Computer Vision, Statistics",Bachelor,0,Automotive,2024-02-22,2024-04-25,2397,7.9,TechCorp Inc -AI08240,Machine Learning Researcher,111174,USD,111174,EN,FL,Denmark,L,Japan,50,"Data Visualization, Hadoop, Python, R",Master,0,Automotive,2024-08-12,2024-09-08,1329,5.9,Cognitive Computing -AI08241,AI Software Engineer,67798,CAD,84748,EN,PT,Canada,L,Malaysia,100,"PyTorch, Python, Docker, Mathematics, SQL",Master,1,Finance,2024-03-10,2024-04-20,631,7.1,Autonomous Tech -AI08242,AI Specialist,124429,USD,124429,SE,FT,Sweden,M,Sweden,50,"Python, Data Visualization, SQL, Computer Vision, Hadoop",Associate,5,Finance,2024-11-02,2024-12-03,1318,8.1,DeepTech Ventures -AI08243,Deep Learning Engineer,61446,EUR,52229,EN,PT,Austria,S,Austria,50,"Statistics, Git, MLOps, GCP",PhD,0,Real Estate,2024-09-06,2024-09-24,1899,6.2,AI Innovations -AI08244,Research Scientist,166025,EUR,141121,EX,CT,Germany,S,Germany,0,"Hadoop, Kubernetes, Git, PyTorch, Linux",PhD,14,Finance,2024-08-11,2024-10-17,782,7.7,Cognitive Computing -AI08245,Deep Learning Engineer,200365,AUD,270493,EX,CT,Australia,M,Australia,100,"Java, SQL, Data Visualization",Bachelor,10,Energy,2024-02-02,2024-03-17,1775,5.6,Cognitive Computing -AI08246,AI Consultant,68661,USD,68661,EN,CT,Denmark,M,Denmark,0,"Python, Git, TensorFlow, Computer Vision",Master,0,Education,2025-03-26,2025-04-10,1038,6.4,Cognitive Computing -AI08247,Research Scientist,128591,USD,128591,MI,CT,United States,L,United States,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,2,Government,2024-06-15,2024-08-08,1680,6.5,Predictive Systems -AI08248,Machine Learning Researcher,90540,USD,90540,MI,FT,Norway,S,Chile,100,"Data Visualization, R, Python, TensorFlow",Associate,2,Education,2024-11-11,2024-12-27,2176,9.9,Quantum Computing Inc -AI08249,AI Software Engineer,98359,USD,98359,MI,FL,United States,M,Spain,100,"Git, AWS, Hadoop, R",Associate,2,Real Estate,2024-10-13,2024-12-22,628,7.9,Cognitive Computing -AI08250,Deep Learning Engineer,60172,USD,60172,EN,FT,Finland,M,Finland,50,"Python, Azure, Tableau",Associate,1,Automotive,2024-01-17,2024-02-14,2166,9.6,Cloud AI Solutions -AI08251,Data Engineer,59702,USD,59702,MI,CT,South Korea,S,South Korea,0,"Statistics, Data Visualization, AWS, Mathematics, Python",Bachelor,4,Real Estate,2024-06-30,2024-08-30,2287,8,AI Innovations -AI08252,Research Scientist,231158,USD,231158,EX,CT,United States,M,Belgium,0,"GCP, Java, Hadoop, Scala",Associate,11,Government,2024-09-01,2024-11-09,1335,5.6,Cognitive Computing -AI08253,Principal Data Scientist,56253,EUR,47815,EN,PT,France,S,Sweden,0,"Tableau, Git, PyTorch, TensorFlow",Associate,1,Real Estate,2024-08-26,2024-09-26,1976,6.2,Autonomous Tech -AI08254,AI Product Manager,66100,USD,66100,EN,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Tableau, Hadoop",Master,1,Government,2024-09-23,2024-11-15,1415,9.7,AI Innovations -AI08255,AI Software Engineer,43269,USD,43269,MI,FT,China,M,China,100,"SQL, MLOps, PyTorch, Statistics, Python",Associate,3,Finance,2024-09-20,2024-10-05,2402,8.5,DeepTech Ventures -AI08256,AI Software Engineer,87445,SGD,113679,EN,PT,Singapore,L,Singapore,0,"Scala, Python, TensorFlow, AWS, Mathematics",Associate,0,Consulting,2025-01-13,2025-03-16,2260,6.9,Cloud AI Solutions -AI08257,Deep Learning Engineer,125861,EUR,106982,SE,FL,Netherlands,L,Netherlands,0,"AWS, Java, Python",Bachelor,9,Technology,2025-02-15,2025-03-06,574,7,Machine Intelligence Group -AI08258,AI Specialist,218971,GBP,164228,EX,PT,United Kingdom,S,Ukraine,0,"PyTorch, Hadoop, Kubernetes, Azure",Master,14,Telecommunications,2024-08-27,2024-11-07,2328,5.7,AI Innovations -AI08259,AI Software Engineer,192168,USD,192168,EX,FL,Ireland,L,Ireland,100,"SQL, Azure, Kubernetes, GCP, NLP",Master,13,Finance,2024-08-18,2024-10-01,1469,7.6,Quantum Computing Inc -AI08260,AI Product Manager,159792,EUR,135823,EX,FL,Austria,M,Austria,100,"R, NLP, Data Visualization, Kubernetes",PhD,19,Healthcare,2024-07-01,2024-07-24,576,8.3,AI Innovations -AI08261,Autonomous Systems Engineer,228879,EUR,194547,EX,FT,Germany,L,Australia,100,"Tableau, Java, Python",Master,13,Real Estate,2024-12-20,2025-01-12,1732,7.4,Machine Intelligence Group -AI08262,AI Product Manager,213850,GBP,160388,EX,FT,United Kingdom,S,United Kingdom,50,"Python, Docker, Hadoop, Statistics",Associate,13,Real Estate,2024-12-05,2025-01-07,1984,6.2,Digital Transformation LLC -AI08263,Machine Learning Engineer,161935,USD,161935,EX,CT,Sweden,S,Spain,50,"AWS, Azure, Deep Learning, Python",Bachelor,14,Finance,2025-01-12,2025-02-12,2282,6.1,AI Innovations -AI08264,NLP Engineer,46071,USD,46071,EN,FT,Finland,S,Finland,50,"Python, Kubernetes, R",Associate,1,Finance,2024-09-11,2024-11-23,1573,8.8,AI Innovations -AI08265,Head of AI,138140,SGD,179582,SE,PT,Singapore,M,Singapore,0,"Python, Statistics, Mathematics",Associate,9,Technology,2024-02-11,2024-03-10,1215,5.5,Advanced Robotics -AI08266,NLP Engineer,40218,USD,40218,MI,FT,India,L,India,0,"Deep Learning, Mathematics, Data Visualization",Master,2,Education,2024-01-01,2024-01-23,1620,7.2,Future Systems -AI08267,Robotics Engineer,69695,CAD,87119,EN,CT,Canada,L,Canada,0,"Hadoop, Java, Scala, Azure",Associate,1,Media,2024-06-03,2024-06-22,1729,6.4,Autonomous Tech -AI08268,Machine Learning Researcher,87123,EUR,74055,MI,PT,Germany,L,Germany,100,"Scala, Data Visualization, Statistics",Associate,4,Energy,2025-03-20,2025-05-13,1316,6.3,Cloud AI Solutions -AI08269,Data Engineer,88198,USD,88198,MI,PT,Israel,S,Israel,100,"Spark, PyTorch, Tableau",PhD,3,Energy,2025-01-22,2025-03-21,715,7.3,Smart Analytics -AI08270,AI Product Manager,64179,USD,64179,EN,PT,Sweden,S,Sweden,100,"Java, Git, AWS, Linux, Computer Vision",Associate,0,Consulting,2024-07-13,2024-08-11,1398,9.8,DataVision Ltd -AI08271,ML Ops Engineer,85336,USD,85336,MI,CT,Ireland,M,Ireland,100,"Kubernetes, TensorFlow, Tableau, MLOps, Data Visualization",Master,4,Manufacturing,2024-11-05,2024-12-23,754,6.4,TechCorp Inc -AI08272,Head of AI,83626,AUD,112895,MI,FL,Australia,L,Hungary,0,"Linux, Kubernetes, Scala, Java",PhD,2,Government,2025-03-28,2025-04-18,1439,8.6,Future Systems -AI08273,AI Product Manager,103151,USD,103151,MI,PT,United States,L,United States,50,"Data Visualization, Scala, Tableau",PhD,4,Gaming,2024-11-10,2024-12-04,1252,6.1,Quantum Computing Inc -AI08274,Principal Data Scientist,71248,USD,71248,MI,CT,South Korea,L,South Korea,0,"Data Visualization, Tableau, SQL, NLP, Python",PhD,3,Real Estate,2025-03-01,2025-04-26,1534,10,Advanced Robotics -AI08275,Data Scientist,85197,USD,85197,EN,FL,Ireland,L,Ireland,0,"Docker, Git, Data Visualization",PhD,1,Energy,2024-07-26,2024-09-25,590,6.8,TechCorp Inc -AI08276,AI Consultant,48680,USD,48680,EN,FL,South Korea,S,South Korea,0,"Hadoop, Computer Vision, AWS, PyTorch",Associate,0,Retail,2024-10-05,2024-12-07,1515,9.8,Quantum Computing Inc -AI08277,Head of AI,104442,USD,104442,EN,FL,Norway,M,Norway,50,"Hadoop, R, SQL, MLOps, NLP",PhD,0,Manufacturing,2025-03-21,2025-04-10,1557,8.3,Algorithmic Solutions -AI08278,AI Software Engineer,108808,EUR,92487,SE,FT,Germany,M,Germany,50,"Data Visualization, PyTorch, Scala, AWS",Bachelor,7,Energy,2024-11-29,2025-01-17,851,5.9,DeepTech Ventures -AI08279,Head of AI,222268,EUR,188928,EX,CT,France,L,France,0,"Azure, Kubernetes, Statistics",Associate,12,Automotive,2024-11-20,2024-12-13,1598,8.2,TechCorp Inc -AI08280,AI Research Scientist,69400,USD,69400,MI,CT,Finland,M,Turkey,0,"Deep Learning, Data Visualization, Tableau, Spark, Computer Vision",PhD,2,Real Estate,2024-04-27,2024-06-19,909,6.3,Smart Analytics -AI08281,ML Ops Engineer,146017,JPY,16061870,EX,CT,Japan,S,Colombia,0,"Linux, Deep Learning, SQL",PhD,17,Gaming,2024-02-07,2024-03-10,551,8.4,Advanced Robotics -AI08282,AI Architect,128715,SGD,167330,SE,CT,Singapore,M,Singapore,50,"Python, Deep Learning, Java, SQL",Bachelor,7,Technology,2024-11-05,2024-11-22,1880,6,Smart Analytics -AI08283,Principal Data Scientist,291772,CHF,262595,EX,PT,Switzerland,M,Switzerland,50,"Kubernetes, Docker, SQL, Tableau",Associate,15,Telecommunications,2024-01-02,2024-02-19,1924,6.9,Future Systems -AI08284,Robotics Engineer,88229,USD,88229,SE,FT,South Korea,M,Germany,50,"Docker, Azure, Mathematics, Java",Associate,5,Telecommunications,2024-03-12,2024-04-26,2075,5.3,Cognitive Computing -AI08285,Head of AI,125238,AUD,169071,SE,PT,Australia,S,Japan,0,"Deep Learning, AWS, R, Python",Master,5,Gaming,2024-01-16,2024-02-18,2338,6,Digital Transformation LLC -AI08286,Autonomous Systems Engineer,59375,USD,59375,EN,FL,Finland,S,Finland,0,"R, Tableau, Scala",Bachelor,0,Technology,2024-11-20,2024-12-16,2109,9.5,Advanced Robotics -AI08287,Computer Vision Engineer,200898,USD,200898,EX,FL,Sweden,L,Sweden,100,"MLOps, Git, SQL",Bachelor,16,Automotive,2024-10-11,2024-10-26,2127,9.4,Advanced Robotics -AI08288,AI Architect,70777,USD,70777,EX,CT,India,L,India,0,"Linux, Hadoop, Kubernetes",Associate,18,Retail,2024-10-07,2024-11-10,1846,8.8,DataVision Ltd -AI08289,Head of AI,174280,GBP,130710,EX,PT,United Kingdom,M,Singapore,0,"Git, GCP, MLOps, Python, Azure",PhD,11,Real Estate,2024-10-06,2024-12-05,1269,8.2,DataVision Ltd -AI08290,Autonomous Systems Engineer,83034,CAD,103793,MI,FL,Canada,M,Canada,50,"Azure, PyTorch, Scala, Git, TensorFlow",Bachelor,3,Real Estate,2025-01-07,2025-02-17,2323,7.6,Autonomous Tech -AI08291,Machine Learning Engineer,80523,USD,80523,MI,FT,South Korea,L,South Korea,100,"Statistics, PyTorch, NLP, Azure",Master,3,Real Estate,2025-04-06,2025-05-22,2395,6.7,Quantum Computing Inc -AI08292,Machine Learning Engineer,85363,USD,85363,EN,CT,Sweden,L,Turkey,50,"Python, SQL, Linux, GCP, Hadoop",Bachelor,0,Media,2024-03-19,2024-04-07,601,9.8,Machine Intelligence Group -AI08293,NLP Engineer,84635,USD,84635,EN,CT,Denmark,M,Denmark,0,"Tableau, SQL, Scala",PhD,1,Retail,2024-04-02,2024-04-19,1101,8.4,Machine Intelligence Group -AI08294,AI Research Scientist,92637,EUR,78741,SE,PT,Germany,S,Germany,0,"GCP, Mathematics, Git, SQL",Associate,7,Real Estate,2024-10-31,2024-12-12,716,7.4,AI Innovations -AI08295,AI Research Scientist,135123,SGD,175660,SE,FT,Singapore,S,Singapore,0,"MLOps, Spark, Deep Learning, AWS, R",Associate,7,Telecommunications,2024-08-25,2024-09-10,596,9.9,Future Systems -AI08296,Principal Data Scientist,73693,USD,73693,EX,CT,China,S,China,50,"R, Deep Learning, Statistics, Python, TensorFlow",Associate,13,Healthcare,2024-01-01,2024-02-25,1055,9.1,Cloud AI Solutions -AI08297,AI Specialist,62151,USD,62151,SE,FL,China,M,China,100,"TensorFlow, Python, Java",Bachelor,6,Government,2024-03-16,2024-04-17,1507,7.1,AI Innovations -AI08298,Data Engineer,107829,CHF,97046,MI,FL,Switzerland,S,Switzerland,0,"Spark, TensorFlow, Python, Git",Bachelor,3,Government,2024-07-27,2024-09-17,815,5.8,Cloud AI Solutions -AI08299,Robotics Engineer,149913,GBP,112435,SE,FT,United Kingdom,M,Mexico,100,"Kubernetes, SQL, Statistics, MLOps, Azure",Associate,8,Manufacturing,2024-12-15,2025-01-22,1153,5.7,Neural Networks Co -AI08300,Head of AI,147367,USD,147367,SE,PT,United States,M,Denmark,50,"Data Visualization, Scala, AWS, Computer Vision, SQL",Bachelor,9,Automotive,2025-04-13,2025-06-11,2235,5.2,Cloud AI Solutions -AI08301,Research Scientist,143496,USD,143496,EX,FT,Finland,M,Finland,50,"Linux, Kubernetes, Docker, Tableau",PhD,15,Consulting,2024-01-29,2024-02-23,962,7.3,Machine Intelligence Group -AI08302,AI Architect,265331,USD,265331,EX,FT,Norway,L,Netherlands,50,"Deep Learning, Hadoop, R, SQL, NLP",Master,10,Healthcare,2024-05-25,2024-06-21,605,6.3,Quantum Computing Inc -AI08303,AI Product Manager,72261,EUR,61422,EN,PT,Germany,S,Germany,0,"Data Visualization, Python, Hadoop, Linux, Java",Associate,1,Manufacturing,2024-06-18,2024-08-14,2384,5.7,DataVision Ltd -AI08304,AI Specialist,255237,CHF,229713,EX,CT,Switzerland,S,Mexico,50,"Azure, TensorFlow, Tableau, Data Visualization, GCP",Bachelor,12,Gaming,2024-02-16,2024-03-30,969,7.7,TechCorp Inc -AI08305,AI Specialist,61670,USD,61670,EN,PT,Ireland,M,Ireland,0,"Kubernetes, Python, Spark, Data Visualization",Associate,1,Retail,2024-10-05,2024-12-07,567,8,Smart Analytics -AI08306,AI Product Manager,92113,USD,92113,MI,PT,Ireland,M,Ireland,50,"Azure, Python, Data Visualization, Java, GCP",Master,3,Automotive,2024-05-05,2024-07-02,2339,6.7,Neural Networks Co -AI08307,Head of AI,291884,EUR,248101,EX,PT,Germany,L,Philippines,100,"Data Visualization, Mathematics, SQL",Bachelor,17,Consulting,2025-01-13,2025-02-14,859,7.4,Advanced Robotics -AI08308,Autonomous Systems Engineer,180243,JPY,19826730,EX,PT,Japan,L,Japan,0,"AWS, Hadoop, Java",Bachelor,18,Retail,2025-01-20,2025-03-27,2024,9.9,DeepTech Ventures -AI08309,AI Product Manager,57135,USD,57135,EX,CT,India,M,India,0,"PyTorch, Git, Data Visualization, Scala, Hadoop",Bachelor,10,Automotive,2025-02-07,2025-03-09,1222,8.6,Autonomous Tech -AI08310,Deep Learning Engineer,109488,SGD,142334,SE,FT,Singapore,S,Chile,100,"Linux, SQL, NLP",Bachelor,7,Healthcare,2024-05-13,2024-06-30,1770,5.8,Algorithmic Solutions -AI08311,Head of AI,124520,USD,124520,MI,FT,Denmark,S,Mexico,0,"Git, AWS, Kubernetes",Associate,4,Media,2024-03-09,2024-05-12,922,6.9,DataVision Ltd -AI08312,Deep Learning Engineer,127767,USD,127767,MI,CT,United States,M,United States,50,"Spark, GCP, PyTorch, Mathematics",Associate,4,Transportation,2024-05-01,2024-07-08,1260,7.7,Autonomous Tech -AI08313,Robotics Engineer,80406,USD,80406,MI,FT,Sweden,M,Sweden,0,"MLOps, Azure, Deep Learning",PhD,3,Media,2024-11-01,2024-11-26,1697,6.8,Predictive Systems -AI08314,AI Consultant,82023,CAD,102529,MI,CT,Canada,L,Canada,50,"Linux, Python, TensorFlow, PyTorch",Associate,4,Media,2024-04-14,2024-06-25,1382,9.6,TechCorp Inc -AI08315,Research Scientist,128543,SGD,167106,SE,CT,Singapore,M,Singapore,50,"Python, Spark, PyTorch, Kubernetes",Master,8,Energy,2024-08-05,2024-09-25,514,8,Advanced Robotics -AI08316,Deep Learning Engineer,75558,USD,75558,MI,PT,Sweden,M,Sweden,100,"Spark, Python, SQL, GCP",Associate,2,Transportation,2024-12-21,2025-01-27,1422,6.4,Quantum Computing Inc -AI08317,NLP Engineer,72192,GBP,54144,EN,PT,United Kingdom,M,Poland,50,"Kubernetes, Java, Hadoop",Master,0,Manufacturing,2024-09-08,2024-09-26,501,7.4,Cognitive Computing -AI08318,Data Scientist,68382,EUR,58125,EN,PT,Germany,S,Germany,0,"Deep Learning, Git, Java, SQL",PhD,1,Automotive,2024-03-23,2024-04-26,2001,8.9,Digital Transformation LLC -AI08319,Machine Learning Engineer,37162,USD,37162,SE,FT,India,S,China,100,"Scala, Mathematics, Deep Learning",Master,5,Retail,2024-12-14,2025-02-04,1613,7.5,Algorithmic Solutions -AI08320,Data Engineer,90745,EUR,77133,MI,CT,Netherlands,S,Netherlands,50,"Tableau, SQL, Scala, PyTorch, Python",Master,2,Automotive,2024-08-28,2024-11-03,2203,9.5,AI Innovations -AI08321,Data Engineer,68389,USD,68389,EN,CT,Finland,M,Finland,50,"Hadoop, Python, TensorFlow",Bachelor,1,Automotive,2024-05-27,2024-07-04,1625,8.4,Machine Intelligence Group -AI08322,Deep Learning Engineer,52150,USD,52150,EX,CT,India,S,Japan,50,"PyTorch, MLOps, SQL",Master,16,Telecommunications,2024-02-15,2024-03-10,839,8.4,AI Innovations -AI08323,Machine Learning Engineer,70856,USD,70856,MI,CT,Israel,M,Israel,0,"Kubernetes, Git, Spark, Scala",Bachelor,2,Manufacturing,2024-03-08,2024-05-13,1675,6.1,Cognitive Computing -AI08324,AI Product Manager,70901,USD,70901,EN,FT,Sweden,L,Sweden,0,"AWS, Python, Git, Deep Learning, TensorFlow",Bachelor,0,Education,2024-03-22,2024-04-23,1246,8,Cloud AI Solutions -AI08325,Machine Learning Engineer,18392,USD,18392,EN,CT,India,S,Colombia,100,"Spark, Git, R, Java",PhD,0,Manufacturing,2024-02-18,2024-03-09,1206,9.7,Machine Intelligence Group -AI08326,Machine Learning Engineer,72083,GBP,54062,MI,CT,United Kingdom,S,United Kingdom,100,"Scala, Git, Kubernetes, SQL, AWS",Master,4,Energy,2024-02-27,2024-04-26,1006,9.8,Advanced Robotics -AI08327,Data Engineer,80363,EUR,68309,EN,FL,Netherlands,M,United States,0,"Computer Vision, Spark, Deep Learning, SQL",Bachelor,1,Education,2025-04-30,2025-06-13,2448,8.5,Future Systems -AI08328,Deep Learning Engineer,81508,USD,81508,EX,PT,India,L,India,50,"Hadoop, NLP, Deep Learning, Tableau, Kubernetes",Master,10,Healthcare,2024-07-16,2024-09-17,1183,9.4,Cognitive Computing -AI08329,Computer Vision Engineer,58680,CAD,73350,EN,FT,Canada,M,Ghana,100,"Docker, Scala, SQL, Kubernetes",Bachelor,1,Real Estate,2025-03-24,2025-05-02,1626,5.9,DeepTech Ventures -AI08330,Deep Learning Engineer,127110,EUR,108044,SE,PT,Netherlands,L,Switzerland,100,"NLP, SQL, Linux, Git, GCP",PhD,6,Education,2024-10-21,2024-12-27,1388,9.8,DataVision Ltd -AI08331,Deep Learning Engineer,35777,USD,35777,EN,PT,China,L,China,0,"Hadoop, Java, Data Visualization, NLP",Master,1,Consulting,2024-02-04,2024-03-12,2081,6,Digital Transformation LLC -AI08332,AI Architect,137961,EUR,117267,SE,FL,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Kubernetes",Master,7,Finance,2025-02-23,2025-04-23,1015,8.2,Quantum Computing Inc -AI08333,Data Analyst,93307,CHF,83976,EN,FL,Switzerland,L,Switzerland,50,"SQL, PyTorch, TensorFlow, Linux",Master,0,Manufacturing,2024-03-30,2024-05-22,1208,6.4,Machine Intelligence Group -AI08334,Autonomous Systems Engineer,90828,AUD,122618,EN,FL,Australia,L,Australia,100,"Git, MLOps, Data Visualization",Bachelor,0,Education,2024-02-15,2024-03-30,1635,7.5,Cognitive Computing -AI08335,Data Engineer,42637,USD,42637,SE,PT,India,M,India,0,"SQL, PyTorch, Linux, Scala",PhD,8,Retail,2024-07-27,2024-10-03,1949,7.8,DataVision Ltd -AI08336,Machine Learning Engineer,183463,USD,183463,EX,CT,Denmark,S,Denmark,50,"Python, Computer Vision, Tableau, TensorFlow, Git",Associate,19,Automotive,2024-04-18,2024-05-24,674,5.9,Future Systems -AI08337,Machine Learning Engineer,110858,AUD,149658,MI,CT,Australia,L,Ireland,100,"PyTorch, Java, Tableau, Docker, Statistics",Associate,2,Manufacturing,2025-04-03,2025-05-15,1345,8.7,Cloud AI Solutions -AI08338,AI Consultant,187012,USD,187012,EX,CT,Finland,S,Finland,0,"Git, Azure, Computer Vision, Kubernetes",Master,13,Government,2024-03-21,2024-04-07,640,8.1,Algorithmic Solutions -AI08339,AI Software Engineer,267395,USD,267395,EX,PT,United States,L,United States,0,"Python, TensorFlow, Computer Vision, Statistics",Associate,17,Retail,2024-04-05,2024-05-03,2448,5.1,TechCorp Inc -AI08340,AI Software Engineer,49037,JPY,5394070,EN,PT,Japan,S,Sweden,50,"Computer Vision, Azure, Statistics, SQL, Spark",Bachelor,0,Government,2024-07-25,2024-08-29,2046,8.4,Machine Intelligence Group -AI08341,Deep Learning Engineer,231031,USD,231031,EX,FL,Ireland,L,Ireland,100,"NLP, AWS, SQL, Computer Vision",PhD,16,Automotive,2025-02-18,2025-04-10,1911,8.1,Future Systems -AI08342,AI Specialist,265453,USD,265453,EX,CT,Ireland,L,Ireland,50,"MLOps, AWS, Kubernetes, Scala, Hadoop",Master,14,Automotive,2024-12-24,2025-01-14,1989,7.9,Machine Intelligence Group -AI08343,AI Consultant,82540,USD,82540,MI,CT,Israel,S,Israel,100,"Git, AWS, Python, Computer Vision, Statistics",Bachelor,2,Gaming,2025-02-05,2025-04-01,2265,7.7,Cloud AI Solutions -AI08344,AI Specialist,126029,USD,126029,SE,FL,Israel,S,Israel,50,"Spark, Docker, Computer Vision, Statistics, Python",Master,6,Automotive,2025-02-23,2025-04-07,1666,8.1,Predictive Systems -AI08345,AI Architect,224510,JPY,24696100,EX,PT,Japan,S,Japan,50,"PyTorch, Docker, Git",Bachelor,14,Technology,2025-02-07,2025-04-17,2078,8.4,AI Innovations -AI08346,Research Scientist,76405,USD,76405,EN,FT,Denmark,L,Denmark,0,"Data Visualization, AWS, Spark, Mathematics",Bachelor,1,Gaming,2024-04-13,2024-05-03,1596,7.1,Algorithmic Solutions -AI08347,Machine Learning Researcher,57273,USD,57273,EN,FL,Israel,L,Israel,0,"Kubernetes, SQL, Mathematics",Bachelor,1,Transportation,2025-01-20,2025-03-23,984,7.8,Neural Networks Co -AI08348,Robotics Engineer,78816,USD,78816,MI,FL,South Korea,L,South Korea,50,"Linux, Computer Vision, R, Statistics",Associate,2,Gaming,2024-01-23,2024-02-19,1491,7,DataVision Ltd -AI08349,AI Specialist,129597,USD,129597,EX,FL,Ireland,S,Thailand,50,"Kubernetes, SQL, Statistics, Computer Vision, Java",Master,19,Real Estate,2024-09-25,2024-11-11,1470,7.5,DeepTech Ventures -AI08350,Robotics Engineer,78527,USD,78527,EX,PT,India,L,India,50,"SQL, Tableau, Linux",PhD,16,Energy,2025-01-12,2025-02-13,1545,6.5,Neural Networks Co -AI08351,AI Consultant,147701,GBP,110776,SE,FT,United Kingdom,L,Finland,50,"Computer Vision, Spark, Statistics, Python",Associate,7,Finance,2024-08-08,2024-09-20,623,8,Autonomous Tech -AI08352,Machine Learning Researcher,124500,USD,124500,SE,PT,Israel,L,Israel,100,"Git, Data Visualization, NLP",Associate,6,Consulting,2024-09-22,2024-11-26,2444,7.1,DataVision Ltd -AI08353,Data Engineer,30093,USD,30093,MI,FT,India,L,India,100,"Python, Computer Vision, Statistics",PhD,2,Real Estate,2024-07-08,2024-07-23,1079,5.6,DeepTech Ventures -AI08354,Computer Vision Engineer,95154,USD,95154,MI,CT,Sweden,M,Sweden,100,"Git, NLP, GCP",Bachelor,4,Gaming,2024-03-22,2024-04-23,755,5.8,Future Systems -AI08355,Machine Learning Researcher,125964,USD,125964,EX,FT,Ireland,S,Brazil,0,"SQL, AWS, Mathematics, NLP",Bachelor,14,Media,2025-01-25,2025-02-18,2241,6.7,Cloud AI Solutions -AI08356,Data Engineer,234668,EUR,199468,EX,FL,France,M,China,50,"Linux, NLP, Kubernetes, AWS, Python",PhD,15,Finance,2024-07-17,2024-08-18,1680,9,TechCorp Inc -AI08357,Head of AI,72375,EUR,61519,MI,FL,France,S,Philippines,0,"GCP, Mathematics, SQL, Scala, Deep Learning",Master,4,Consulting,2024-04-07,2024-04-30,759,6.9,DataVision Ltd -AI08358,Data Engineer,199511,USD,199511,EX,CT,Finland,L,Finland,50,"Statistics, NLP, SQL, Kubernetes",Master,15,Consulting,2024-12-19,2025-01-15,523,7.5,AI Innovations -AI08359,AI Specialist,82707,USD,82707,MI,FL,Ireland,S,Ireland,100,"Spark, NLP, Python",Bachelor,4,Manufacturing,2024-07-03,2024-08-19,538,8.9,Predictive Systems -AI08360,AI Architect,49846,USD,49846,EN,CT,Ireland,S,Ireland,50,"Mathematics, Spark, Deep Learning, NLP",Bachelor,0,Transportation,2025-04-03,2025-05-02,1323,5.9,Future Systems -AI08361,AI Research Scientist,231076,SGD,300399,EX,CT,Singapore,S,Singapore,50,"Python, Spark, Statistics, Data Visualization",Bachelor,14,Technology,2024-08-15,2024-09-28,1757,6.8,Neural Networks Co -AI08362,Research Scientist,150796,USD,150796,SE,CT,Denmark,M,Denmark,50,"Python, Mathematics, Kubernetes, Hadoop",Bachelor,7,Telecommunications,2024-05-28,2024-07-20,2287,6.2,Quantum Computing Inc -AI08363,Machine Learning Researcher,116702,USD,116702,SE,CT,Ireland,S,Ireland,50,"NLP, TensorFlow, Java, Linux, R",Bachelor,8,Technology,2025-03-01,2025-03-19,1076,8.3,Advanced Robotics -AI08364,Computer Vision Engineer,127076,CHF,114368,EN,PT,Switzerland,L,Switzerland,0,"NLP, Java, Mathematics, Python",Associate,0,Technology,2024-10-18,2024-12-09,1891,7.8,Quantum Computing Inc -AI08365,Machine Learning Researcher,138133,JPY,15194630,SE,CT,Japan,S,Philippines,100,"MLOps, Python, Data Visualization",PhD,9,Finance,2024-06-12,2024-08-15,1650,8,Cognitive Computing -AI08366,Data Scientist,72519,USD,72519,EN,FT,Finland,M,Switzerland,50,"Java, PyTorch, Spark",Bachelor,1,Manufacturing,2024-11-10,2025-01-22,1763,7.2,Predictive Systems -AI08367,AI Software Engineer,202605,USD,202605,EX,FL,Israel,L,Israel,100,"R, Deep Learning, TensorFlow",Master,19,Energy,2025-04-07,2025-05-04,950,9.1,Neural Networks Co -AI08368,ML Ops Engineer,147327,USD,147327,EX,PT,Finland,L,Vietnam,50,"Scala, GCP, Hadoop, SQL",Associate,12,Transportation,2025-01-07,2025-03-02,1715,5.9,DataVision Ltd -AI08369,AI Specialist,35455,USD,35455,MI,CT,India,M,India,100,"Kubernetes, Deep Learning, Data Visualization, Spark",Associate,4,Media,2025-03-05,2025-05-09,810,8.6,Machine Intelligence Group -AI08370,ML Ops Engineer,85603,USD,85603,MI,FL,Ireland,M,Ireland,100,"Data Visualization, Scala, Spark, Computer Vision",Bachelor,4,Gaming,2025-03-22,2025-05-19,1079,7,Cloud AI Solutions -AI08371,Data Scientist,174323,USD,174323,EX,FL,Israel,M,Spain,100,"Deep Learning, Kubernetes, NLP, Spark",PhD,11,Technology,2025-01-05,2025-01-22,2480,8.9,Autonomous Tech -AI08372,Head of AI,138386,CHF,124547,SE,FL,Switzerland,S,Switzerland,100,"Tableau, Azure, Hadoop, R, NLP",Master,5,Retail,2025-01-21,2025-03-15,2000,8.5,Future Systems -AI08373,AI Specialist,86425,USD,86425,MI,PT,Finland,S,Australia,100,"Python, Statistics, Git",Bachelor,4,Manufacturing,2024-10-24,2024-12-04,1636,9.1,Future Systems -AI08374,AI Architect,79209,EUR,67328,MI,FT,France,M,France,50,"Java, MLOps, TensorFlow",PhD,2,Gaming,2024-05-03,2024-05-22,2438,9.2,Future Systems -AI08375,Robotics Engineer,93206,GBP,69905,MI,PT,United Kingdom,L,United Kingdom,0,"Linux, Mathematics, Deep Learning",Bachelor,2,Consulting,2025-03-19,2025-04-09,692,6.2,Cloud AI Solutions -AI08376,Head of AI,183144,EUR,155672,EX,PT,Germany,S,Germany,50,"Data Visualization, GCP, Spark, TensorFlow",Associate,11,Gaming,2024-04-03,2024-05-12,1696,5.9,Smart Analytics -AI08377,Computer Vision Engineer,115035,USD,115035,MI,FL,United States,L,Poland,50,"Computer Vision, Linux, Mathematics, Git, Kubernetes",PhD,3,Telecommunications,2024-10-05,2024-12-14,1758,8.1,Advanced Robotics -AI08378,Robotics Engineer,52046,USD,52046,EN,PT,Ireland,M,Ireland,0,"Python, Java, Git, Linux, GCP",Master,0,Consulting,2024-04-21,2024-06-18,2451,7.5,Advanced Robotics -AI08379,Data Engineer,27042,USD,27042,MI,FT,India,M,India,0,"Scala, NLP, Java, Hadoop",Associate,3,Retail,2024-08-29,2024-10-21,1230,9.1,Quantum Computing Inc -AI08380,Principal Data Scientist,69140,EUR,58769,MI,FL,Germany,S,Philippines,100,"Java, Computer Vision, R",Associate,4,Education,2024-11-05,2024-11-23,2300,9.2,AI Innovations -AI08381,Principal Data Scientist,54144,USD,54144,SE,FL,China,M,South Korea,50,"Hadoop, Java, AWS, R, MLOps",Bachelor,5,Education,2024-04-07,2024-05-15,1069,8,Digital Transformation LLC -AI08382,Autonomous Systems Engineer,102140,GBP,76605,MI,PT,United Kingdom,M,United Kingdom,50,"Azure, Linux, Deep Learning",PhD,3,Real Estate,2024-09-02,2024-10-26,920,6.4,Smart Analytics -AI08383,Machine Learning Researcher,159981,EUR,135984,SE,PT,Germany,L,Germany,100,"Python, Computer Vision, Deep Learning",Associate,9,Retail,2024-01-16,2024-02-17,1058,7.1,DeepTech Ventures -AI08384,Research Scientist,52315,USD,52315,EN,FT,South Korea,M,South Korea,50,"Hadoop, SQL, Linux, Data Visualization, GCP",PhD,1,Media,2024-05-07,2024-06-17,944,6.2,Quantum Computing Inc -AI08385,AI Research Scientist,174231,AUD,235212,SE,PT,Australia,L,Australia,50,"NLP, Scala, Java, Linux",Associate,7,Manufacturing,2025-02-17,2025-03-14,2270,9.9,Cognitive Computing -AI08386,AI Specialist,97169,GBP,72877,MI,CT,United Kingdom,L,United Kingdom,0,"MLOps, AWS, Java, SQL, Git",Master,3,Government,2024-09-24,2024-10-09,2310,6.1,Predictive Systems -AI08387,Autonomous Systems Engineer,143744,CAD,179680,SE,PT,Canada,M,Poland,0,"Linux, Statistics, Deep Learning, MLOps",Bachelor,9,Energy,2024-12-17,2025-02-03,1811,5.8,Smart Analytics -AI08388,Data Scientist,112243,USD,112243,MI,CT,United States,S,Hungary,100,"Data Visualization, Scala, SQL, AWS",Master,2,Finance,2024-05-28,2024-07-18,978,7.8,Cognitive Computing -AI08389,ML Ops Engineer,127387,USD,127387,MI,FL,Denmark,M,China,0,"Deep Learning, PyTorch, MLOps",Bachelor,3,Technology,2025-04-02,2025-06-08,2393,7.7,Autonomous Tech -AI08390,Machine Learning Researcher,131304,EUR,111608,SE,PT,Austria,M,Austria,0,"SQL, PyTorch, GCP, Hadoop",PhD,6,Consulting,2024-12-16,2025-01-24,1299,8.4,Cognitive Computing -AI08391,Machine Learning Engineer,71777,AUD,96899,EN,FL,Australia,L,Ireland,50,"Java, R, Python, Azure, Mathematics",Master,0,Media,2025-01-03,2025-02-16,1167,8.2,Cognitive Computing -AI08392,Machine Learning Researcher,116676,SGD,151679,SE,PT,Singapore,S,Singapore,100,"Kubernetes, Hadoop, Java",Bachelor,7,Finance,2024-03-06,2024-04-09,764,7.6,AI Innovations -AI08393,AI Consultant,126226,GBP,94670,SE,FL,United Kingdom,S,Mexico,50,"Spark, Java, PyTorch, GCP",Master,6,Technology,2024-10-02,2024-12-11,901,9.1,Advanced Robotics -AI08394,ML Ops Engineer,82894,AUD,111907,MI,CT,Australia,S,Australia,100,"R, GCP, Computer Vision, Spark, SQL",Master,4,Government,2025-02-04,2025-02-18,624,7.8,TechCorp Inc -AI08395,Machine Learning Researcher,38746,USD,38746,EN,FT,China,L,South Korea,0,"Hadoop, Statistics, SQL, Tableau",Bachelor,0,Energy,2025-01-27,2025-02-26,1600,8.4,Quantum Computing Inc -AI08396,AI Consultant,92661,USD,92661,MI,FT,Norway,S,Japan,100,"SQL, Python, Git, Kubernetes",Master,2,Government,2024-04-26,2024-06-25,511,9.4,TechCorp Inc -AI08397,AI Research Scientist,62143,USD,62143,MI,PT,South Korea,M,Czech Republic,100,"Python, TensorFlow, NLP",Associate,4,Media,2025-01-31,2025-02-23,854,5.1,Autonomous Tech -AI08398,AI Software Engineer,176385,GBP,132289,EX,PT,United Kingdom,S,United Kingdom,100,"SQL, Scala, Azure, Computer Vision, GCP",Bachelor,14,Real Estate,2025-02-06,2025-02-21,2442,5.3,Machine Intelligence Group -AI08399,AI Software Engineer,81358,EUR,69154,MI,FL,France,M,France,0,"SQL, Docker, Data Visualization, Hadoop, Deep Learning",Associate,3,Media,2024-04-06,2024-04-28,836,5.3,DeepTech Ventures -AI08400,Robotics Engineer,78489,USD,78489,MI,FL,Israel,M,Israel,0,"Docker, AWS, NLP",PhD,2,Telecommunications,2025-04-02,2025-05-04,712,9,Advanced Robotics -AI08401,Autonomous Systems Engineer,157109,EUR,133543,SE,CT,Germany,L,Portugal,100,"Java, MLOps, R, NLP",PhD,5,Automotive,2025-01-12,2025-01-26,1530,8,Smart Analytics -AI08402,AI Software Engineer,154305,AUD,208312,EX,FL,Australia,S,Ghana,0,"TensorFlow, R, Statistics",Master,17,Telecommunications,2025-01-15,2025-02-19,2485,8,TechCorp Inc -AI08403,Machine Learning Engineer,61309,AUD,82767,EN,PT,Australia,S,India,50,"SQL, Python, Deep Learning, AWS, Statistics",Associate,0,Real Estate,2025-02-06,2025-03-11,820,6.9,DataVision Ltd -AI08404,Data Scientist,189613,AUD,255978,EX,FT,Australia,M,Australia,50,"Java, R, Hadoop",Associate,13,Media,2024-10-29,2024-11-22,1473,9.1,Cloud AI Solutions -AI08405,AI Product Manager,214403,USD,214403,EX,PT,United States,S,United States,0,"Docker, Linux, Azure, Statistics, Tableau",Associate,18,Retail,2025-03-18,2025-04-05,1843,6.3,TechCorp Inc -AI08406,AI Consultant,133222,EUR,113239,SE,PT,Austria,M,Argentina,0,"Scala, PyTorch, GCP, Spark, Computer Vision",Master,7,Transportation,2024-07-03,2024-08-09,1185,8.9,DataVision Ltd -AI08407,Data Engineer,62909,USD,62909,EN,PT,Israel,L,Israel,100,"Tableau, Java, Scala, Data Visualization, TensorFlow",PhD,1,Government,2024-08-19,2024-10-13,2330,5.2,DeepTech Ventures -AI08408,AI Product Manager,19343,USD,19343,EN,FT,India,S,India,50,"GCP, Git, PyTorch",Associate,1,Transportation,2025-01-05,2025-02-08,2174,9.3,Quantum Computing Inc -AI08409,Robotics Engineer,222547,USD,222547,EX,PT,Ireland,S,Ireland,0,"Linux, PyTorch, Data Visualization",Bachelor,14,Manufacturing,2024-02-19,2024-03-09,1579,5.6,Smart Analytics -AI08410,AI Consultant,234130,JPY,25754300,EX,FT,Japan,S,Japan,100,"Linux, Azure, MLOps, Git",Bachelor,11,Real Estate,2025-02-08,2025-02-23,1013,5.8,Cognitive Computing -AI08411,Deep Learning Engineer,215309,USD,215309,EX,CT,Finland,S,Finland,100,"Computer Vision, MLOps, GCP",Master,13,Media,2024-06-30,2024-09-09,1203,7.3,Cognitive Computing -AI08412,AI Product Manager,72372,USD,72372,MI,CT,Israel,S,Chile,50,"Scala, SQL, Spark, GCP",PhD,4,Technology,2024-04-13,2024-05-14,764,8.2,Smart Analytics -AI08413,Deep Learning Engineer,167429,AUD,226029,EX,CT,Australia,L,Austria,100,"SQL, AWS, Scala, GCP, Azure",Bachelor,11,Transportation,2024-04-17,2024-05-05,1020,6.5,Algorithmic Solutions -AI08414,AI Consultant,171432,USD,171432,EX,PT,Israel,L,Israel,50,"Spark, PyTorch, Java, TensorFlow",Bachelor,16,Energy,2024-06-06,2024-07-18,1921,6.1,Predictive Systems -AI08415,AI Research Scientist,162301,USD,162301,SE,FL,Sweden,L,United Kingdom,50,"SQL, Hadoop, Azure",Master,6,Telecommunications,2025-02-03,2025-04-02,1728,6.4,Cognitive Computing -AI08416,Computer Vision Engineer,106745,USD,106745,MI,CT,Sweden,M,Luxembourg,50,"Python, GCP, Azure, SQL, TensorFlow",Bachelor,3,Healthcare,2024-06-27,2024-07-23,2005,9.2,Advanced Robotics -AI08417,AI Specialist,169009,EUR,143658,EX,FL,Netherlands,L,Netherlands,0,"Computer Vision, PyTorch, Tableau",PhD,18,Government,2024-03-24,2024-05-26,1702,6.2,Algorithmic Solutions -AI08418,AI Architect,233941,SGD,304123,EX,PT,Singapore,M,Italy,50,"MLOps, SQL, AWS, NLP, Data Visualization",Bachelor,15,Energy,2024-06-13,2024-07-22,1480,6.3,Machine Intelligence Group -AI08419,AI Software Engineer,179620,EUR,152677,EX,PT,Austria,L,Sweden,50,"Python, Kubernetes, Statistics, AWS",Master,13,Technology,2024-01-28,2024-03-11,1610,9.6,Quantum Computing Inc -AI08420,ML Ops Engineer,128589,JPY,14144790,SE,PT,Japan,S,Japan,50,"PyTorch, TensorFlow, Docker",PhD,6,Gaming,2024-10-13,2024-11-08,2114,9,AI Innovations -AI08421,Deep Learning Engineer,76779,EUR,65262,EN,PT,Netherlands,L,Netherlands,0,"Mathematics, PyTorch, Scala",Associate,1,Retail,2024-12-16,2025-01-12,2438,7,Neural Networks Co -AI08422,AI Specialist,114807,EUR,97586,SE,FL,France,S,Norway,100,"Azure, Java, Git",Master,6,Automotive,2024-06-06,2024-07-31,1526,6.6,DataVision Ltd -AI08423,Autonomous Systems Engineer,126904,AUD,171320,SE,PT,Australia,S,Australia,50,"Scala, Kubernetes, R, GCP, Hadoop",Master,8,Consulting,2024-12-05,2025-01-11,2035,6.8,Neural Networks Co -AI08424,ML Ops Engineer,23823,USD,23823,EN,CT,India,L,India,50,"GCP, Python, TensorFlow, Deep Learning",PhD,0,Media,2024-08-10,2024-09-06,1222,6.2,Cloud AI Solutions -AI08425,Robotics Engineer,91085,USD,91085,MI,FL,United States,S,United States,50,"Computer Vision, Statistics, NLP, Kubernetes",Master,4,Consulting,2025-03-09,2025-05-09,1623,9.9,Cloud AI Solutions -AI08426,AI Software Engineer,123889,EUR,105306,SE,CT,Netherlands,M,Netherlands,0,"Python, Hadoop, R, Linux",Associate,6,Retail,2024-02-10,2024-04-04,1683,8.9,Quantum Computing Inc -AI08427,Machine Learning Engineer,116702,USD,116702,SE,CT,South Korea,M,South Korea,50,"Hadoop, Tableau, AWS, PyTorch",Master,9,Technology,2024-07-14,2024-09-04,1427,6,Predictive Systems -AI08428,Research Scientist,114453,USD,114453,MI,PT,Sweden,L,Argentina,0,"Spark, SQL, Azure, MLOps",PhD,2,Government,2024-06-06,2024-08-04,2473,5.2,TechCorp Inc -AI08429,Data Analyst,127753,GBP,95815,MI,FT,United Kingdom,L,United Kingdom,50,"TensorFlow, Docker, Tableau, Java",Master,4,Technology,2025-01-13,2025-03-14,665,5.1,Smart Analytics -AI08430,AI Research Scientist,279320,SGD,363116,EX,FT,Singapore,L,Turkey,50,"Computer Vision, MLOps, Statistics",Associate,14,Telecommunications,2024-02-28,2024-04-01,1660,8.8,DeepTech Ventures -AI08431,Computer Vision Engineer,193375,EUR,164369,EX,FT,Germany,M,Czech Republic,50,"Tableau, Python, NLP, Spark, Computer Vision",Master,10,Education,2024-06-21,2024-07-06,2499,9.3,Machine Intelligence Group -AI08432,AI Consultant,199737,CHF,179763,SE,FT,Switzerland,M,Switzerland,0,"Java, Scala, MLOps",Master,8,Telecommunications,2025-01-28,2025-02-27,2100,7.8,Cloud AI Solutions -AI08433,AI Software Engineer,53228,USD,53228,EN,CT,Finland,S,Finland,0,"TensorFlow, SQL, Data Visualization, Mathematics",Master,0,Energy,2024-03-06,2024-05-13,1656,9.8,Smart Analytics -AI08434,Autonomous Systems Engineer,124669,EUR,105969,SE,CT,Austria,L,Austria,100,"Deep Learning, Python, Linux",Master,6,Real Estate,2025-02-09,2025-03-21,1166,8.1,Algorithmic Solutions -AI08435,AI Research Scientist,139094,USD,139094,SE,CT,Norway,S,Singapore,50,"SQL, Docker, PyTorch, Hadoop, Scala",Bachelor,5,Education,2024-10-30,2024-11-20,842,9.6,Algorithmic Solutions -AI08436,AI Research Scientist,103028,CHF,92725,EN,FL,Switzerland,L,Portugal,100,"Computer Vision, Tableau, Scala, Deep Learning, Azure",Associate,1,Retail,2024-10-21,2024-11-06,1091,8,Advanced Robotics -AI08437,Data Analyst,140713,USD,140713,SE,PT,Ireland,L,Sweden,50,"Data Visualization, Python, TensorFlow",Associate,5,Automotive,2024-12-10,2025-01-27,2280,9,Cognitive Computing -AI08438,AI Software Engineer,93762,USD,93762,EN,CT,Norway,M,Norway,100,"GCP, Python, Deep Learning, TensorFlow",PhD,1,Education,2025-01-05,2025-03-09,1924,9.2,AI Innovations -AI08439,Machine Learning Engineer,60042,USD,60042,EN,CT,United States,M,United States,50,"Scala, Azure, Tableau",Associate,0,Automotive,2024-06-20,2024-08-16,905,5.2,Neural Networks Co -AI08440,Deep Learning Engineer,125462,USD,125462,SE,FL,Israel,M,Norway,0,"Mathematics, SQL, Data Visualization, Linux",Master,8,Manufacturing,2024-09-18,2024-10-20,1182,9.1,Future Systems -AI08441,Autonomous Systems Engineer,79766,EUR,67801,MI,PT,Germany,M,Germany,0,"Spark, Hadoop, Tableau",Associate,4,Automotive,2025-02-13,2025-03-29,769,7.3,Algorithmic Solutions -AI08442,AI Architect,63995,USD,63995,SE,CT,China,S,China,50,"Java, SQL, Kubernetes, AWS",Associate,9,Energy,2024-05-05,2024-07-09,1467,8,Cognitive Computing -AI08443,Deep Learning Engineer,67575,EUR,57439,EN,CT,France,S,France,0,"R, Scala, GCP, Linux",Bachelor,0,Real Estate,2024-12-28,2025-02-15,2065,9.8,DeepTech Ventures -AI08444,Machine Learning Engineer,180825,GBP,135619,SE,FT,United Kingdom,L,Russia,0,"SQL, Scala, NLP, Statistics, PyTorch",Master,5,Healthcare,2024-02-07,2024-03-17,2210,7.4,Neural Networks Co -AI08445,Autonomous Systems Engineer,46588,USD,46588,SE,CT,China,S,China,0,"Hadoop, Mathematics, NLP, AWS",Bachelor,7,Government,2024-12-04,2025-01-10,1897,8.6,Machine Intelligence Group -AI08446,AI Specialist,70840,USD,70840,EN,FT,Sweden,S,Sweden,0,"SQL, Data Visualization, Linux",Master,0,Telecommunications,2024-06-08,2024-07-21,2485,9,Predictive Systems -AI08447,AI Research Scientist,40656,USD,40656,MI,PT,China,M,China,50,"Python, Mathematics, GCP, AWS",PhD,3,Retail,2025-01-17,2025-03-15,1534,5.3,Advanced Robotics -AI08448,Research Scientist,50149,EUR,42627,EN,PT,Austria,S,Austria,50,"Data Visualization, AWS, SQL, Statistics",Associate,0,Finance,2024-10-15,2024-12-12,1516,6.1,TechCorp Inc -AI08449,Research Scientist,128622,AUD,173640,SE,FL,Australia,M,Australia,100,"Deep Learning, Scala, PyTorch, Mathematics, GCP",Associate,9,Education,2024-12-05,2025-01-22,1434,7.4,Cloud AI Solutions -AI08450,Machine Learning Engineer,100866,GBP,75650,MI,FL,United Kingdom,S,United Kingdom,0,"Java, Scala, Linux, Deep Learning",Bachelor,4,Telecommunications,2024-03-18,2024-04-26,1156,5.5,Quantum Computing Inc -AI08451,AI Architect,98292,GBP,73719,MI,FT,United Kingdom,L,United Kingdom,0,"Scala, Hadoop, Statistics, TensorFlow",Associate,2,Automotive,2024-07-18,2024-09-04,2349,8.4,Quantum Computing Inc -AI08452,Machine Learning Engineer,77362,AUD,104439,MI,FT,Australia,M,Australia,50,"SQL, Linux, Java, PyTorch",Bachelor,4,Gaming,2025-03-18,2025-04-24,834,7.9,DataVision Ltd -AI08453,Data Analyst,78850,AUD,106448,MI,FT,Australia,M,Australia,100,"Tableau, GCP, TensorFlow, PyTorch, Azure",Associate,2,Government,2025-03-06,2025-05-18,1560,5.7,Predictive Systems -AI08454,Computer Vision Engineer,87737,GBP,65803,EN,FT,United Kingdom,L,United Kingdom,0,"R, AWS, NLP, MLOps, Spark",PhD,1,Education,2025-02-09,2025-04-16,552,8.6,Predictive Systems -AI08455,AI Architect,91614,USD,91614,MI,FL,Ireland,L,Ireland,0,"Python, NLP, Kubernetes, Computer Vision",Associate,4,Technology,2024-12-21,2025-02-12,1349,5.5,AI Innovations -AI08456,Computer Vision Engineer,186919,USD,186919,EX,CT,Norway,S,Norway,0,"Java, Linux, SQL, Deep Learning",Bachelor,14,Healthcare,2024-05-16,2024-07-05,1629,9.9,Quantum Computing Inc -AI08457,Data Scientist,70265,CAD,87831,EN,PT,Canada,M,Estonia,50,"Kubernetes, SQL, Tableau, TensorFlow, Mathematics",Bachelor,0,Transportation,2024-07-23,2024-08-07,1608,7.5,AI Innovations -AI08458,Autonomous Systems Engineer,45732,USD,45732,EN,FT,Finland,S,Finland,100,"Kubernetes, SQL, Data Visualization",PhD,1,Energy,2025-02-23,2025-04-05,1157,7.4,DataVision Ltd -AI08459,Machine Learning Researcher,36182,USD,36182,SE,FT,India,M,India,100,"NLP, Data Visualization, PyTorch, MLOps, TensorFlow",Master,6,Automotive,2024-12-03,2025-01-24,2302,7.7,Future Systems -AI08460,AI Software Engineer,64887,EUR,55154,MI,PT,Austria,S,Austria,50,"Linux, Tableau, PyTorch",Associate,4,Consulting,2024-02-26,2024-04-09,1763,7.4,Predictive Systems -AI08461,AI Product Manager,309181,USD,309181,EX,FT,Denmark,L,Estonia,50,"GCP, Python, Spark",Master,15,Government,2025-01-01,2025-02-10,1074,7.6,Smart Analytics -AI08462,Data Analyst,93055,USD,93055,MI,FT,United States,M,United States,100,"Statistics, Kubernetes, Java, GCP, Scala",Master,3,Retail,2024-04-04,2024-05-23,1929,7.2,Cloud AI Solutions -AI08463,Data Analyst,186453,CHF,167808,SE,FL,Switzerland,M,Sweden,100,"Scala, Hadoop, Java, Mathematics, Statistics",Associate,6,Energy,2025-04-06,2025-04-26,567,6.9,DataVision Ltd -AI08464,Computer Vision Engineer,83203,USD,83203,EN,FT,United States,M,United States,100,"SQL, PyTorch, Data Visualization",Associate,0,Gaming,2024-01-27,2024-02-14,1842,6.9,DataVision Ltd -AI08465,Machine Learning Researcher,188584,EUR,160296,EX,FT,Germany,M,Germany,50,"SQL, Kubernetes, Spark, Hadoop",Bachelor,17,Technology,2025-02-16,2025-03-29,1547,9.3,Algorithmic Solutions -AI08466,Data Analyst,121863,USD,121863,MI,FL,Norway,S,Norway,100,"AWS, Linux, Scala",Associate,4,Real Estate,2024-05-16,2024-06-06,2163,9.1,AI Innovations -AI08467,Computer Vision Engineer,53043,CAD,66304,EN,CT,Canada,M,Canada,0,"SQL, Tableau, Java, Kubernetes",PhD,0,Consulting,2024-10-18,2024-11-11,1508,9.8,Predictive Systems -AI08468,Deep Learning Engineer,105766,USD,105766,MI,FL,Norway,S,Norway,50,"TensorFlow, SQL, Scala, Azure",Master,2,Retail,2024-04-03,2024-04-28,1624,9.9,Quantum Computing Inc -AI08469,AI Specialist,127422,EUR,108309,SE,FT,Austria,S,Austria,0,"Statistics, Hadoop, Computer Vision",PhD,6,Healthcare,2024-08-11,2024-10-13,1126,7.4,Future Systems -AI08470,NLP Engineer,274301,CHF,246871,EX,PT,Switzerland,M,Switzerland,0,"Computer Vision, Mathematics, NLP",Bachelor,13,Technology,2024-08-25,2024-09-15,987,5.4,Quantum Computing Inc -AI08471,Machine Learning Engineer,107589,USD,107589,SE,FL,Sweden,S,Sweden,0,"Linux, Docker, Data Visualization, Git",Master,7,Real Estate,2024-07-31,2024-09-23,568,7.7,Quantum Computing Inc -AI08472,ML Ops Engineer,68293,EUR,58049,EN,PT,France,M,France,0,"Git, Scala, Deep Learning, R, Azure",PhD,1,Education,2024-05-15,2024-06-24,2321,7.3,Future Systems -AI08473,Computer Vision Engineer,257050,JPY,28275500,EX,FT,Japan,M,Japan,100,"Deep Learning, Java, Mathematics, Hadoop, PyTorch",Associate,17,Finance,2025-04-27,2025-05-23,2319,9.9,Predictive Systems -AI08474,Deep Learning Engineer,154708,USD,154708,EX,FL,Sweden,M,Hungary,50,"PyTorch, GCP, SQL",Master,13,Healthcare,2024-09-03,2024-09-25,2285,6.8,AI Innovations -AI08475,Machine Learning Researcher,80788,USD,80788,MI,FL,Sweden,S,Sweden,0,"Python, Deep Learning, Docker",PhD,3,Transportation,2024-07-25,2024-09-02,1268,6.9,Digital Transformation LLC -AI08476,Head of AI,117314,USD,117314,SE,FT,Finland,L,Finland,0,"Data Visualization, Python, SQL, Git",Associate,7,Technology,2024-07-05,2024-08-01,1317,5.2,Advanced Robotics -AI08477,Machine Learning Researcher,117690,AUD,158882,SE,CT,Australia,M,Australia,0,"PyTorch, Python, Git",PhD,8,Consulting,2025-04-13,2025-05-08,989,5.6,TechCorp Inc -AI08478,AI Architect,214411,USD,214411,EX,PT,United States,L,United States,50,"NLP, Java, Git, Kubernetes",PhD,11,Finance,2024-11-04,2024-12-13,2395,8.6,Cloud AI Solutions -AI08479,Machine Learning Researcher,155700,USD,155700,SE,PT,United States,S,United States,0,"Python, Statistics, Docker",Bachelor,7,Healthcare,2024-10-15,2024-12-27,1971,9.8,DeepTech Ventures -AI08480,Autonomous Systems Engineer,111686,EUR,94933,SE,CT,Netherlands,M,Colombia,50,"Docker, MLOps, AWS, Deep Learning",Master,7,Finance,2024-08-05,2024-10-04,1018,9.4,Algorithmic Solutions -AI08481,AI Research Scientist,65656,AUD,88636,MI,PT,Australia,S,Malaysia,50,"Computer Vision, SQL, PyTorch, Mathematics, AWS",Master,4,Finance,2024-04-29,2024-07-11,2396,5.1,DataVision Ltd -AI08482,Principal Data Scientist,85926,USD,85926,EX,CT,India,M,India,0,"Data Visualization, R, Java, MLOps",PhD,10,Automotive,2025-02-28,2025-05-12,906,7.2,AI Innovations -AI08483,AI Research Scientist,130166,GBP,97625,EX,FL,United Kingdom,S,United Kingdom,0,"Mathematics, Deep Learning, Hadoop, Docker, Java",Master,11,Education,2024-01-29,2024-03-26,1014,5.4,Machine Intelligence Group -AI08484,Autonomous Systems Engineer,132900,USD,132900,MI,FT,Denmark,L,Denmark,100,"Git, SQL, Python, NLP, Deep Learning",Bachelor,4,Finance,2024-11-06,2024-12-13,660,7.8,DeepTech Ventures -AI08485,Deep Learning Engineer,156100,EUR,132685,SE,PT,Netherlands,L,Netherlands,50,"Python, Java, MLOps",Associate,7,Technology,2024-02-12,2024-03-28,2028,5.2,DataVision Ltd -AI08486,Data Engineer,133627,USD,133627,SE,FT,Norway,M,Norway,100,"Azure, SQL, Kubernetes, Computer Vision, Statistics",Bachelor,9,Education,2024-09-26,2024-11-10,1712,6.4,Cognitive Computing -AI08487,AI Architect,88478,EUR,75206,SE,FT,France,S,France,100,"Hadoop, Linux, AWS, PyTorch, MLOps",Associate,5,Transportation,2024-04-07,2024-06-15,1496,7.5,Smart Analytics -AI08488,Machine Learning Engineer,212608,EUR,180717,EX,PT,Austria,M,Austria,50,"Azure, Computer Vision, Git, AWS, Docker",PhD,12,Telecommunications,2024-07-06,2024-08-09,519,6.5,Quantum Computing Inc -AI08489,AI Architect,58073,USD,58073,EN,FT,Israel,S,Israel,50,"Java, TensorFlow, Mathematics",Master,0,Media,2024-12-23,2025-02-28,903,9.7,DeepTech Ventures -AI08490,AI Consultant,91448,USD,91448,EN,PT,Ireland,L,Czech Republic,50,"PyTorch, MLOps, Spark",PhD,1,Automotive,2025-01-17,2025-02-16,1090,5.6,Digital Transformation LLC -AI08491,Head of AI,95900,USD,95900,MI,PT,Sweden,L,Sweden,0,"TensorFlow, Tableau, R",PhD,4,Transportation,2024-08-14,2024-09-11,647,7.6,Future Systems -AI08492,Principal Data Scientist,179096,AUD,241780,EX,FT,Australia,M,Australia,100,"Spark, SQL, PyTorch, Deep Learning",Associate,18,Transportation,2025-01-25,2025-04-08,1108,6.7,DeepTech Ventures -AI08493,AI Product Manager,59907,USD,59907,EN,FT,Israel,M,Israel,50,"Mathematics, AWS, MLOps, Java",PhD,0,Government,2024-06-23,2024-07-31,1306,9.4,DeepTech Ventures -AI08494,Research Scientist,67233,AUD,90765,EN,FT,Australia,L,Australia,0,"Python, Java, Mathematics, Spark",PhD,1,Automotive,2024-03-15,2024-05-25,943,5.8,Cognitive Computing -AI08495,Data Engineer,203674,CHF,183307,SE,FL,Switzerland,M,Switzerland,50,"Scala, Spark, Azure, Tableau, Kubernetes",Bachelor,9,Real Estate,2024-11-29,2025-01-07,2130,6,Neural Networks Co -AI08496,AI Software Engineer,113013,EUR,96061,SE,FL,Austria,M,Colombia,50,"Python, AWS, Data Visualization, NLP",Bachelor,7,Retail,2025-03-26,2025-05-24,1018,9.9,TechCorp Inc -AI08497,AI Architect,239650,AUD,323528,EX,PT,Australia,M,Australia,50,"Scala, Computer Vision, SQL, Data Visualization",Bachelor,17,Transportation,2024-03-16,2024-05-19,1926,9.1,Neural Networks Co -AI08498,Computer Vision Engineer,237855,CAD,297319,EX,CT,Canada,L,Japan,50,"NLP, Hadoop, MLOps, Scala",PhD,14,Healthcare,2025-01-09,2025-03-17,2032,8.2,DataVision Ltd -AI08499,Machine Learning Researcher,90048,EUR,76541,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Docker, TensorFlow, Scala, AWS",Bachelor,3,Transportation,2025-03-14,2025-05-14,1034,8.4,AI Innovations -AI08500,Robotics Engineer,103593,USD,103593,SE,PT,South Korea,S,South Korea,0,"Spark, Scala, Kubernetes, Hadoop, Java",Master,5,Retail,2024-08-31,2024-09-30,1593,10,Neural Networks Co -AI08501,AI Software Engineer,118005,SGD,153407,SE,PT,Singapore,S,Singapore,0,"Azure, Scala, Deep Learning",Master,9,Media,2024-11-18,2025-01-09,1227,7.1,Predictive Systems -AI08502,Machine Learning Engineer,102645,CHF,92381,EN,FT,Switzerland,M,Switzerland,0,"Hadoop, Kubernetes, Python, Linux",Associate,1,Transportation,2024-09-27,2024-11-30,1269,6,Predictive Systems -AI08503,Research Scientist,213544,AUD,288284,EX,FL,Australia,S,Australia,0,"PyTorch, SQL, MLOps, Spark",Master,16,Telecommunications,2024-05-22,2024-06-21,2216,8.2,Autonomous Tech -AI08504,Autonomous Systems Engineer,99231,EUR,84346,MI,FT,Germany,S,Germany,100,"Azure, SQL, Mathematics, Docker, AWS",Bachelor,2,Finance,2025-03-08,2025-05-04,1765,6.3,Neural Networks Co -AI08505,AI Specialist,189940,CAD,237425,EX,FL,Canada,M,Canada,50,"Azure, Hadoop, SQL, PyTorch",Bachelor,15,Energy,2024-09-09,2024-10-28,949,6.5,Quantum Computing Inc -AI08506,Head of AI,97410,USD,97410,EN,FT,Denmark,M,Denmark,0,"Python, TensorFlow, Linux, PyTorch, Deep Learning",Associate,0,Telecommunications,2025-01-18,2025-02-13,678,8.7,TechCorp Inc -AI08507,AI Specialist,115419,GBP,86564,SE,PT,United Kingdom,M,United Kingdom,0,"Python, Docker, Mathematics",PhD,9,Government,2024-11-06,2024-12-15,2448,9.3,Autonomous Tech -AI08508,Deep Learning Engineer,55421,USD,55421,EN,PT,South Korea,M,South Korea,100,"Python, R, Mathematics, TensorFlow",Bachelor,1,Education,2024-07-09,2024-08-01,2257,8.5,DeepTech Ventures -AI08509,Principal Data Scientist,174114,EUR,147997,SE,FL,Germany,L,Germany,100,"GCP, Python, MLOps",Associate,9,Education,2024-09-02,2024-10-05,1057,7.6,Cloud AI Solutions -AI08510,Data Analyst,223978,USD,223978,EX,PT,Sweden,M,Sweden,0,"R, TensorFlow, Scala, Linux, Mathematics",Master,14,Government,2024-09-15,2024-10-23,1841,7.9,Cloud AI Solutions -AI08511,Principal Data Scientist,239199,GBP,179399,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, Python, Data Visualization",PhD,16,Government,2024-09-24,2024-10-28,2389,6.4,Predictive Systems -AI08512,AI Research Scientist,82844,CHF,74560,EN,FT,Switzerland,M,United Kingdom,0,"Data Visualization, Azure, GCP, Java",PhD,1,Media,2024-06-12,2024-08-18,2214,7.1,Neural Networks Co -AI08513,AI Specialist,122977,USD,122977,SE,PT,Finland,L,Finland,50,"Python, Azure, Spark",Associate,9,Government,2025-02-09,2025-04-12,2372,7.1,Algorithmic Solutions -AI08514,Deep Learning Engineer,113326,USD,113326,MI,PT,Denmark,M,Denmark,50,"Kubernetes, Scala, Git, Azure, AWS",Associate,4,Government,2024-04-16,2024-06-18,850,5,Autonomous Tech -AI08515,Research Scientist,90965,CAD,113706,MI,CT,Canada,S,Turkey,0,"Linux, Kubernetes, Python, TensorFlow, Scala",Associate,3,Education,2025-04-19,2025-05-13,1326,6,Cloud AI Solutions -AI08516,Data Engineer,134158,USD,134158,SE,FL,Finland,L,Finland,50,"Java, SQL, Kubernetes, Hadoop",Associate,5,Media,2024-02-28,2024-04-26,670,5.9,Advanced Robotics -AI08517,Data Engineer,62279,CAD,77849,EN,PT,Canada,M,Canada,50,"Statistics, Python, Computer Vision, Spark, Kubernetes",Master,0,Retail,2024-07-16,2024-08-03,2107,6.4,Neural Networks Co -AI08518,Principal Data Scientist,201716,USD,201716,SE,CT,United States,L,Germany,100,"Spark, NLP, GCP, Tableau",Associate,6,Healthcare,2024-08-06,2024-08-29,572,9.8,AI Innovations -AI08519,AI Software Engineer,165043,USD,165043,EX,PT,Finland,L,Finland,50,"NLP, SQL, Java, GCP",Master,13,Automotive,2024-02-15,2024-03-06,1770,9.4,Predictive Systems -AI08520,NLP Engineer,95834,USD,95834,MI,FT,Denmark,M,Denmark,100,"Python, TensorFlow, Statistics, Azure, GCP",PhD,4,Healthcare,2025-01-03,2025-03-06,1278,7.7,Neural Networks Co -AI08521,AI Architect,131818,USD,131818,SE,FT,South Korea,L,Brazil,0,"Kubernetes, Python, Azure, TensorFlow",Master,5,Energy,2025-03-01,2025-04-03,1547,7,Digital Transformation LLC -AI08522,Robotics Engineer,86510,USD,86510,MI,FT,Denmark,S,South Africa,0,"Deep Learning, Azure, Python",Bachelor,2,Retail,2024-07-23,2024-08-19,2077,6.9,TechCorp Inc -AI08523,AI Software Engineer,83243,USD,83243,EN,PT,Israel,L,United Kingdom,50,"Python, Computer Vision, Linux, TensorFlow, Kubernetes",PhD,1,Gaming,2025-02-25,2025-03-11,1789,5.2,Future Systems -AI08524,AI Software Engineer,76490,CHF,68841,EN,PT,Switzerland,M,United Kingdom,50,"Scala, GCP, Python, Statistics, MLOps",Master,0,Education,2024-01-20,2024-02-08,1601,7.4,Advanced Robotics -AI08525,Head of AI,239503,EUR,203578,EX,CT,Germany,M,Germany,0,"Kubernetes, Hadoop, GCP, TensorFlow, Python",PhD,12,Finance,2025-03-04,2025-03-20,717,9.5,Machine Intelligence Group -AI08526,AI Specialist,159699,AUD,215594,SE,CT,Australia,L,Australia,50,"Scala, Tableau, Azure, Docker",PhD,5,Technology,2024-07-14,2024-08-31,1429,8.8,DeepTech Ventures -AI08527,Machine Learning Engineer,127190,SGD,165347,MI,CT,Singapore,L,Portugal,100,"Linux, NLP, Docker, Hadoop, Computer Vision",Master,2,Technology,2024-06-21,2024-08-27,1630,8.3,Digital Transformation LLC -AI08528,Autonomous Systems Engineer,61030,SGD,79339,EN,FT,Singapore,M,Singapore,50,"Statistics, TensorFlow, Scala, Python",Master,1,Automotive,2024-03-02,2024-04-16,2268,8.9,Future Systems -AI08529,Computer Vision Engineer,30719,USD,30719,MI,FT,India,S,Switzerland,0,"Python, Linux, MLOps, Statistics, Git",Master,2,Healthcare,2024-06-08,2024-06-22,1519,5.4,Neural Networks Co -AI08530,Robotics Engineer,322323,USD,322323,EX,FL,Denmark,M,Denmark,100,"PyTorch, Mathematics, Deep Learning",Bachelor,15,Government,2025-04-11,2025-06-10,1717,7.2,Predictive Systems -AI08531,Data Engineer,239858,CHF,215872,SE,FL,Switzerland,L,Switzerland,0,"TensorFlow, Docker, Linux",PhD,9,Media,2024-01-16,2024-02-12,850,6.6,Smart Analytics -AI08532,AI Specialist,90256,USD,90256,EN,FL,Ireland,L,Norway,100,"TensorFlow, GCP, Statistics, Python",PhD,1,Manufacturing,2025-01-23,2025-02-16,2232,6.8,Quantum Computing Inc -AI08533,Data Scientist,96346,GBP,72260,EN,FT,United Kingdom,L,United Kingdom,50,"MLOps, Spark, GCP",PhD,1,Transportation,2024-11-20,2025-01-15,1593,6.8,Future Systems -AI08534,AI Architect,227082,GBP,170312,EX,FT,United Kingdom,S,United Kingdom,0,"Git, Hadoop, Tableau, AWS",Associate,18,Media,2024-03-18,2024-05-08,1054,8.4,Quantum Computing Inc -AI08535,AI Consultant,174649,USD,174649,EX,FL,Sweden,S,Sweden,100,"PyTorch, GCP, Deep Learning",PhD,19,Telecommunications,2025-01-07,2025-02-01,2161,9.6,Autonomous Tech -AI08536,Principal Data Scientist,244243,EUR,207607,EX,PT,Austria,L,Austria,50,"Mathematics, SQL, Docker, TensorFlow",Master,14,Manufacturing,2025-04-17,2025-05-29,881,5.9,DataVision Ltd -AI08537,AI Software Engineer,140294,GBP,105221,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Scala, MLOps",Master,6,Automotive,2025-01-23,2025-03-30,2467,6.9,AI Innovations -AI08538,AI Consultant,125410,CAD,156763,SE,CT,Canada,L,Ghana,100,"Scala, Hadoop, AWS",Master,5,Real Estate,2024-11-23,2025-01-04,2245,8.1,Cognitive Computing -AI08539,AI Specialist,102002,CAD,127503,MI,CT,Canada,M,Netherlands,0,"Linux, Mathematics, MLOps",Associate,2,Transportation,2024-02-22,2024-04-04,1720,9.7,Autonomous Tech -AI08540,Machine Learning Researcher,70722,AUD,95475,EN,CT,Australia,M,Belgium,100,"Mathematics, Linux, AWS, Docker, SQL",Master,1,Manufacturing,2025-04-25,2025-05-17,1856,8.8,Machine Intelligence Group -AI08541,AI Product Manager,92261,GBP,69196,MI,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, NLP",PhD,3,Government,2024-01-10,2024-01-29,2021,6.4,Quantum Computing Inc -AI08542,AI Architect,84465,CHF,76019,EN,PT,Switzerland,L,Switzerland,100,"Data Visualization, Spark, Deep Learning",Associate,0,Consulting,2025-01-02,2025-02-15,2374,5,Future Systems -AI08543,Machine Learning Engineer,73370,EUR,62365,EN,PT,Germany,M,Germany,50,"Linux, Docker, Kubernetes",PhD,0,Technology,2024-04-21,2024-06-05,2319,6.5,Algorithmic Solutions -AI08544,Data Scientist,125995,EUR,107096,EX,PT,France,S,United Kingdom,0,"SQL, Spark, PyTorch, Hadoop",PhD,12,Transportation,2024-03-21,2024-04-30,1217,9.4,DataVision Ltd -AI08545,Machine Learning Researcher,109740,SGD,142662,MI,CT,Singapore,L,Singapore,100,"Java, Deep Learning, TensorFlow, Statistics",Bachelor,4,Education,2024-02-25,2024-03-14,1024,9.7,Predictive Systems -AI08546,Principal Data Scientist,126186,USD,126186,MI,FL,Norway,S,Norway,50,"Git, Linux, Python, Kubernetes",PhD,3,Energy,2024-04-12,2024-06-04,2446,7.8,DeepTech Ventures -AI08547,AI Product Manager,114618,EUR,97425,SE,FL,Austria,S,Austria,50,"Git, AWS, Azure, Statistics, Scala",Master,8,Manufacturing,2024-11-01,2025-01-09,543,9.3,Advanced Robotics -AI08548,AI Consultant,194158,EUR,165034,EX,PT,France,L,France,100,"Linux, Azure, TensorFlow, Git",PhD,15,Media,2024-09-14,2024-10-18,971,9.5,Future Systems -AI08549,Machine Learning Engineer,68896,USD,68896,EN,CT,Ireland,L,Ireland,0,"TensorFlow, PyTorch, AWS, Statistics",Associate,1,Energy,2024-12-28,2025-01-19,903,6.7,TechCorp Inc -AI08550,AI Product Manager,179602,JPY,19756220,SE,PT,Japan,L,Japan,50,"Docker, Python, NLP, MLOps",Bachelor,8,Gaming,2024-10-22,2024-11-24,2386,7.6,Predictive Systems -AI08551,Machine Learning Engineer,197099,EUR,167534,EX,CT,Netherlands,S,Netherlands,0,"SQL, Spark, Python, R",PhD,17,Finance,2024-10-01,2024-12-09,874,6.6,Autonomous Tech -AI08552,AI Architect,63579,USD,63579,MI,FT,Israel,S,Israel,50,"Hadoop, Linux, GCP, Tableau, Mathematics",Master,3,Gaming,2024-03-16,2024-05-07,2455,7.2,Algorithmic Solutions -AI08553,Machine Learning Researcher,141152,USD,141152,EX,CT,South Korea,S,South Korea,0,"Spark, Linux, Python, Azure",Master,16,Government,2024-10-01,2024-12-12,1492,5.1,Machine Intelligence Group -AI08554,NLP Engineer,96134,SGD,124974,MI,PT,Singapore,M,Singapore,0,"TensorFlow, Mathematics, Data Visualization",Associate,4,Transportation,2024-09-23,2024-11-17,1025,9.4,AI Innovations -AI08555,Research Scientist,127024,GBP,95268,SE,FT,United Kingdom,L,United Kingdom,100,"R, SQL, MLOps, Statistics, Hadoop",Master,9,Energy,2024-05-14,2024-06-30,1870,6.8,Cognitive Computing -AI08556,Machine Learning Researcher,145838,USD,145838,SE,FL,Denmark,M,Denmark,50,"Docker, NLP, Kubernetes, Statistics, Mathematics",Associate,7,Consulting,2024-02-26,2024-03-29,1533,5.2,DataVision Ltd -AI08557,Robotics Engineer,130985,EUR,111337,SE,FL,Germany,M,Germany,50,"Data Visualization, Linux, Python, TensorFlow, AWS",Master,5,Telecommunications,2024-12-29,2025-02-05,2324,6.5,Cloud AI Solutions -AI08558,Robotics Engineer,154058,EUR,130949,SE,PT,France,L,France,0,"Python, TensorFlow, MLOps, Hadoop",PhD,5,Finance,2024-02-08,2024-03-19,2052,5.5,Smart Analytics -AI08559,Machine Learning Researcher,97591,USD,97591,MI,PT,Norway,S,Russia,0,"R, Git, Kubernetes, Computer Vision",Master,2,Government,2025-02-26,2025-04-24,1877,6.9,AI Innovations -AI08560,Machine Learning Engineer,271305,SGD,352697,EX,FL,Singapore,L,New Zealand,100,"Git, PyTorch, AWS, Data Visualization",Associate,19,Transportation,2024-10-04,2024-10-22,638,9.3,Algorithmic Solutions -AI08561,ML Ops Engineer,98409,EUR,83648,MI,CT,Netherlands,L,Netherlands,100,"TensorFlow, MLOps, Scala",PhD,3,Consulting,2024-01-05,2024-02-14,1500,7.7,Machine Intelligence Group -AI08562,AI Research Scientist,148798,JPY,16367780,SE,CT,Japan,L,Japan,100,"Scala, PyTorch, AWS, TensorFlow",Associate,6,Government,2024-11-21,2024-12-31,747,8.3,Cognitive Computing -AI08563,AI Product Manager,279602,GBP,209702,EX,FL,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, Statistics, Docker, Scala",Associate,16,Education,2025-01-23,2025-02-18,1232,7.6,AI Innovations -AI08564,NLP Engineer,95686,SGD,124392,MI,CT,Singapore,S,Luxembourg,50,"Tableau, TensorFlow, Java, Kubernetes",Bachelor,3,Healthcare,2024-11-18,2024-12-10,582,9.9,Future Systems -AI08565,AI Consultant,64322,USD,64322,EN,FT,Israel,M,Israel,0,"NLP, GCP, Docker",PhD,1,Telecommunications,2025-02-16,2025-04-22,2144,5.5,Smart Analytics -AI08566,NLP Engineer,136594,USD,136594,MI,PT,Denmark,M,Nigeria,0,"Java, Computer Vision, Python, AWS, TensorFlow",PhD,2,Energy,2024-05-03,2024-05-29,1479,6.7,AI Innovations -AI08567,Robotics Engineer,82693,EUR,70289,EN,FL,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure",PhD,0,Energy,2025-04-13,2025-05-14,1302,8.8,DataVision Ltd -AI08568,AI Specialist,153976,USD,153976,EX,CT,United States,S,Argentina,50,"Scala, R, Tableau, TensorFlow, Docker",PhD,19,Retail,2024-09-18,2024-10-19,591,6.5,Autonomous Tech -AI08569,Data Scientist,139600,USD,139600,SE,FL,Norway,M,Japan,0,"GCP, Kubernetes, SQL, Computer Vision",Master,6,Media,2024-12-20,2025-02-13,1575,5.5,Cognitive Computing -AI08570,Robotics Engineer,249090,GBP,186818,EX,FT,United Kingdom,L,Poland,50,"Java, Python, Deep Learning",PhD,17,Energy,2024-04-24,2024-06-13,1346,5.6,Cloud AI Solutions -AI08571,Data Analyst,40276,USD,40276,SE,FT,India,S,India,100,"Computer Vision, Linux, GCP, Statistics",Associate,9,Consulting,2024-11-09,2025-01-19,1140,7.5,Digital Transformation LLC -AI08572,Robotics Engineer,72904,USD,72904,MI,FL,Finland,S,Finland,100,"Python, Java, Docker",Master,4,Healthcare,2024-04-10,2024-05-07,920,5,Quantum Computing Inc -AI08573,Research Scientist,64042,SGD,83255,EN,CT,Singapore,S,Singapore,100,"Linux, SQL, Git, MLOps, Hadoop",Bachelor,1,Consulting,2024-10-11,2024-11-12,1592,8.3,DataVision Ltd -AI08574,Machine Learning Researcher,305717,JPY,33628870,EX,PT,Japan,L,Luxembourg,50,"Kubernetes, Git, GCP, NLP, SQL",PhD,15,Technology,2024-08-03,2024-09-04,1529,9.7,DeepTech Ventures -AI08575,Research Scientist,85542,USD,85542,EN,FL,Norway,S,Norway,100,"TensorFlow, Tableau, Python",Bachelor,0,Gaming,2024-07-12,2024-08-11,620,8.6,Digital Transformation LLC -AI08576,Computer Vision Engineer,62229,USD,62229,MI,FL,South Korea,M,Ukraine,100,"Scala, R, NLP, Linux, Deep Learning",Associate,2,Manufacturing,2025-01-20,2025-03-03,2251,6.6,Predictive Systems -AI08577,Data Scientist,183034,CAD,228793,EX,FT,Canada,S,Canada,100,"Azure, SQL, Scala, Data Visualization, Git",Master,15,Technology,2024-04-02,2024-05-25,1927,7.5,AI Innovations -AI08578,Robotics Engineer,77261,CAD,96576,EN,FT,Canada,L,Canada,100,"Hadoop, PyTorch, Java",PhD,0,Technology,2025-02-21,2025-03-10,1539,7.2,Quantum Computing Inc -AI08579,AI Software Engineer,101020,USD,101020,MI,CT,Ireland,L,Thailand,0,"R, Tableau, Azure",Associate,2,Healthcare,2024-09-04,2024-11-16,661,6.9,Predictive Systems -AI08580,AI Consultant,76948,USD,76948,MI,PT,Finland,S,Hungary,100,"Hadoop, Git, PyTorch, AWS, Linux",Bachelor,4,Consulting,2024-02-28,2024-04-01,1102,7.8,Cognitive Computing -AI08581,AI Specialist,81536,USD,81536,EX,FT,China,M,China,0,"Kubernetes, Python, Azure, Spark",Bachelor,13,Gaming,2024-11-02,2024-12-12,2087,5.4,AI Innovations -AI08582,Principal Data Scientist,95198,USD,95198,SE,FL,Finland,S,Finland,0,"Git, R, Tableau",Bachelor,9,Consulting,2024-03-09,2024-04-10,1619,6.4,Predictive Systems -AI08583,AI Consultant,164093,GBP,123070,SE,PT,United Kingdom,L,Ghana,50,"TensorFlow, AWS, Tableau, Kubernetes, NLP",Master,9,Media,2024-04-02,2024-05-23,2074,9.8,DataVision Ltd -AI08584,Research Scientist,140767,USD,140767,SE,CT,United States,L,Hungary,0,"Tableau, Python, TensorFlow, PyTorch",Bachelor,8,Automotive,2024-08-11,2024-10-16,1142,9.1,Algorithmic Solutions -AI08585,Machine Learning Researcher,102336,USD,102336,EX,FL,China,L,China,50,"PyTorch, Hadoop, Git",Master,19,Consulting,2025-04-27,2025-05-11,662,5.8,Advanced Robotics -AI08586,Research Scientist,58994,EUR,50145,EN,FT,Austria,L,Austria,50,"Spark, Linux, Git, Azure",Master,0,Automotive,2025-02-16,2025-03-15,1940,7,DeepTech Ventures -AI08587,NLP Engineer,51117,AUD,69008,EN,FL,Australia,M,Australia,50,"Python, Java, MLOps",Master,0,Real Estate,2024-09-07,2024-11-02,2071,7,Machine Intelligence Group -AI08588,Data Scientist,82013,USD,82013,EN,FT,United States,L,United States,100,"SQL, Statistics, PyTorch, R",PhD,1,Real Estate,2024-06-09,2024-07-24,1950,8.5,AI Innovations -AI08589,AI Product Manager,204881,USD,204881,EX,PT,Finland,S,Finland,50,"Python, Spark, NLP",Master,10,Manufacturing,2024-01-20,2024-02-05,936,8.9,Future Systems -AI08590,AI Software Engineer,78751,USD,78751,EX,CT,India,M,India,100,"NLP, GCP, Spark, Kubernetes",Bachelor,13,Retail,2024-12-20,2025-01-12,1019,6.5,AI Innovations -AI08591,Head of AI,130461,GBP,97846,MI,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Kubernetes, SQL, GCP",PhD,3,Education,2024-08-14,2024-09-10,1707,9,Digital Transformation LLC -AI08592,AI Product Manager,83311,JPY,9164210,MI,PT,Japan,S,Japan,0,"Docker, Spark, Data Visualization, Git, Python",PhD,4,Consulting,2024-01-16,2024-02-17,1419,5.3,AI Innovations -AI08593,AI Research Scientist,57136,GBP,42852,EN,PT,United Kingdom,M,Sweden,100,"AWS, R, SQL, Deep Learning",Associate,0,Retail,2024-02-06,2024-02-25,2040,8.5,TechCorp Inc -AI08594,Head of AI,109478,USD,109478,MI,CT,Sweden,L,Sweden,0,"GCP, Azure, Tableau, Computer Vision, Git",Bachelor,2,Energy,2024-05-12,2024-07-03,1628,9.1,Autonomous Tech -AI08595,NLP Engineer,86990,USD,86990,MI,PT,Israel,L,Romania,0,"TensorFlow, GCP, NLP, Spark, Scala",Associate,3,Consulting,2024-11-05,2024-12-05,2421,6.1,Predictive Systems -AI08596,Machine Learning Engineer,241562,USD,241562,EX,CT,Ireland,M,Ireland,50,"R, Python, Mathematics, NLP",PhD,11,Government,2025-03-21,2025-05-28,1893,5.8,DataVision Ltd -AI08597,Principal Data Scientist,21704,USD,21704,EN,PT,India,M,India,50,"GCP, Deep Learning, Tableau",Associate,1,Telecommunications,2024-10-18,2024-12-25,1489,7.5,Autonomous Tech -AI08598,ML Ops Engineer,88065,EUR,74855,MI,FT,Netherlands,S,Netherlands,50,"Kubernetes, PyTorch, Azure, GCP, MLOps",Bachelor,3,Retail,2025-04-19,2025-05-13,779,5.9,Predictive Systems -AI08599,Research Scientist,52913,USD,52913,MI,PT,China,L,Ghana,0,"Data Visualization, Spark, Kubernetes, Java, Statistics",Associate,2,Education,2024-05-22,2024-06-05,1036,7.7,DataVision Ltd -AI08600,Robotics Engineer,60550,EUR,51468,EN,CT,Netherlands,M,Poland,0,"SQL, Statistics, Spark, Git",Bachelor,1,Energy,2025-03-23,2025-05-17,1973,6.4,Neural Networks Co -AI08601,Computer Vision Engineer,57164,USD,57164,EN,FT,Israel,L,Israel,50,"Azure, Java, Git, Computer Vision, Python",Master,1,Government,2024-05-08,2024-06-05,1916,9.1,DeepTech Ventures -AI08602,Principal Data Scientist,196044,USD,196044,EX,FL,Finland,L,Finland,100,"Java, Python, R, Docker, AWS",Master,19,Automotive,2025-01-13,2025-03-06,1055,6.4,Future Systems -AI08603,Deep Learning Engineer,205349,CAD,256686,EX,CT,Canada,M,Canada,50,"Kubernetes, NLP, Statistics, Deep Learning",Bachelor,10,Finance,2025-02-13,2025-04-19,1523,7.2,Smart Analytics -AI08604,Machine Learning Engineer,141845,CHF,127661,MI,FL,Switzerland,L,Switzerland,50,"AWS, Statistics, Tableau",PhD,2,Real Estate,2024-07-30,2024-09-23,2215,5.3,Quantum Computing Inc -AI08605,AI Specialist,111688,USD,111688,MI,PT,United States,L,Vietnam,50,"Git, Kubernetes, Statistics, Tableau",Bachelor,4,Media,2024-06-12,2024-08-17,1284,6.3,DeepTech Ventures -AI08606,Head of AI,68031,JPY,7483410,EN,FL,Japan,M,Japan,0,"AWS, Linux, Python, TensorFlow, Java",Bachelor,1,Consulting,2024-11-06,2025-01-07,2344,10,Machine Intelligence Group -AI08607,AI Product Manager,107527,CHF,96774,EN,FT,Switzerland,L,Switzerland,100,"Hadoop, MLOps, TensorFlow",PhD,1,Retail,2024-03-14,2024-05-09,2383,6.7,Advanced Robotics -AI08608,AI Consultant,181374,EUR,154168,EX,FL,Germany,M,Germany,50,"Hadoop, GCP, PyTorch, SQL, Linux",Master,13,Energy,2025-03-02,2025-04-14,865,7.3,Algorithmic Solutions -AI08609,Data Engineer,118961,EUR,101117,SE,PT,Germany,S,Portugal,0,"Kubernetes, AWS, R",PhD,8,Retail,2024-09-04,2024-11-16,1248,9.6,Algorithmic Solutions -AI08610,ML Ops Engineer,52835,USD,52835,MI,FT,China,L,China,50,"Spark, Kubernetes, Deep Learning",Bachelor,4,Education,2025-04-14,2025-05-09,1169,8.6,Smart Analytics -AI08611,Machine Learning Engineer,70673,USD,70673,SE,FT,China,M,China,50,"Java, Kubernetes, Tableau",Master,7,Telecommunications,2024-04-28,2024-05-17,1371,9.1,Quantum Computing Inc -AI08612,ML Ops Engineer,94570,AUD,127670,SE,CT,Australia,S,Australia,0,"Python, TensorFlow, Docker, R, Computer Vision",PhD,8,Transportation,2024-09-09,2024-10-10,1297,5.5,Digital Transformation LLC -AI08613,AI Research Scientist,64693,USD,64693,EN,FT,Israel,L,Israel,0,"AWS, MLOps, GCP, Mathematics",Bachelor,0,Consulting,2024-05-17,2024-07-21,2215,6.2,Quantum Computing Inc -AI08614,Head of AI,191853,USD,191853,SE,PT,Denmark,M,Denmark,0,"Scala, Git, Kubernetes, PyTorch, Python",PhD,8,Media,2025-01-30,2025-03-22,900,7.4,Autonomous Tech -AI08615,Data Analyst,114269,SGD,148550,SE,FT,Singapore,M,Singapore,0,"AWS, Statistics, NLP, Tableau",Bachelor,9,Energy,2024-12-16,2025-01-29,2116,9,Machine Intelligence Group -AI08616,Machine Learning Researcher,269818,JPY,29679980,EX,PT,Japan,M,Japan,50,"Computer Vision, PyTorch, Python, Azure, AWS",Bachelor,15,Real Estate,2024-02-05,2024-03-07,935,9.8,TechCorp Inc -AI08617,AI Software Engineer,120069,USD,120069,SE,CT,Norway,S,Norway,50,"AWS, R, Statistics, PyTorch",PhD,5,Manufacturing,2024-07-10,2024-08-18,1887,7.3,Cognitive Computing -AI08618,Data Analyst,86504,USD,86504,MI,FT,South Korea,M,South Korea,0,"Python, Hadoop, Git, TensorFlow",Bachelor,3,Media,2025-01-13,2025-03-02,2433,6.4,Future Systems -AI08619,Machine Learning Researcher,120570,USD,120570,EX,CT,China,L,China,50,"Python, SQL, AWS, Computer Vision",Bachelor,17,Telecommunications,2024-02-11,2024-03-10,1747,5.2,DeepTech Ventures -AI08620,Data Scientist,184942,USD,184942,EX,CT,Ireland,L,Latvia,50,"Computer Vision, Docker, R",Master,17,Automotive,2024-07-09,2024-08-24,600,9.6,AI Innovations -AI08621,Data Scientist,89220,EUR,75837,EN,PT,Germany,L,Germany,50,"Linux, Git, Computer Vision, Hadoop, Java",PhD,0,Real Estate,2024-03-08,2024-04-13,1551,5.3,Future Systems -AI08622,AI Product Manager,134492,JPY,14794120,SE,FL,Japan,M,Japan,100,"R, Statistics, NLP, Spark",Associate,8,Transportation,2024-10-31,2024-12-23,2443,8.6,DeepTech Ventures -AI08623,Machine Learning Researcher,137903,EUR,117218,EX,FL,France,S,France,50,"Java, Hadoop, NLP",Associate,16,Manufacturing,2024-11-10,2024-12-10,796,7.2,Smart Analytics -AI08624,Deep Learning Engineer,139031,GBP,104273,EX,FT,United Kingdom,S,Norway,0,"Linux, Azure, Mathematics, SQL, Hadoop",PhD,16,Energy,2024-12-15,2025-01-03,1916,5.9,Autonomous Tech -AI08625,AI Software Engineer,202153,USD,202153,EX,FT,South Korea,L,South Korea,50,"Scala, Computer Vision, Linux, Python, Kubernetes",Associate,17,Consulting,2025-03-05,2025-04-09,1250,6.2,DeepTech Ventures -AI08626,AI Architect,71668,USD,71668,MI,PT,Israel,S,South Africa,100,"Kubernetes, Git, R, PyTorch",Associate,3,Retail,2025-01-19,2025-04-02,1593,6,Cloud AI Solutions -AI08627,AI Product Manager,89404,USD,89404,EN,CT,Denmark,L,Denmark,0,"PyTorch, Tableau, TensorFlow",Bachelor,0,Finance,2024-11-04,2024-12-09,1637,8,DeepTech Ventures -AI08628,Head of AI,145615,USD,145615,SE,FT,Sweden,M,Sweden,0,"Linux, MLOps, Data Visualization, Python, NLP",Associate,8,Consulting,2024-10-10,2024-11-09,2127,9.5,Cloud AI Solutions -AI08629,Data Analyst,207813,USD,207813,EX,FL,Finland,L,Finland,0,"R, Linux, Deep Learning",Associate,13,Transportation,2024-12-30,2025-02-17,1223,5.3,Cloud AI Solutions -AI08630,AI Architect,142528,EUR,121149,SE,FT,Netherlands,M,Netherlands,50,"Git, Scala, Statistics, MLOps, SQL",Master,8,Technology,2025-03-21,2025-05-22,1866,6.3,Autonomous Tech -AI08631,AI Specialist,68097,USD,68097,MI,FT,Finland,M,Finland,50,"Kubernetes, Python, GCP",Bachelor,3,Manufacturing,2025-03-11,2025-04-08,1548,7.5,Machine Intelligence Group -AI08632,Data Engineer,224311,SGD,291604,EX,CT,Singapore,S,Singapore,50,"Java, Linux, Mathematics, Azure, Scala",Associate,17,Transportation,2025-01-16,2025-01-30,659,8.8,AI Innovations -AI08633,Autonomous Systems Engineer,114501,CAD,143126,SE,FT,Canada,L,Canada,50,"Tableau, PyTorch, Git, Python, Linux",Bachelor,7,Consulting,2024-10-26,2024-11-11,880,6.1,Autonomous Tech -AI08634,NLP Engineer,65825,USD,65825,SE,FL,China,L,China,0,"AWS, Java, Azure",Bachelor,5,Finance,2024-10-04,2024-10-24,1602,9.2,Autonomous Tech -AI08635,AI Specialist,196121,CAD,245151,EX,PT,Canada,S,Canada,0,"Spark, Kubernetes, GCP, Tableau",Associate,18,Education,2025-04-30,2025-06-18,954,7.6,AI Innovations -AI08636,Principal Data Scientist,94824,USD,94824,EN,PT,United States,M,United States,100,"Hadoop, Linux, Kubernetes",Associate,1,Manufacturing,2024-01-02,2024-03-03,922,5,Machine Intelligence Group -AI08637,AI Software Engineer,48808,USD,48808,SE,PT,China,M,China,100,"Linux, Docker, R, Mathematics",Master,8,Government,2024-04-09,2024-06-16,2216,8.1,Autonomous Tech -AI08638,Robotics Engineer,119252,EUR,101364,SE,CT,Netherlands,M,Finland,0,"PyTorch, TensorFlow, Mathematics, Java, Spark",Master,5,Finance,2024-11-28,2025-02-05,1993,7.6,Machine Intelligence Group -AI08639,AI Architect,77771,CHF,69994,EN,FL,Switzerland,M,Switzerland,50,"Scala, Tableau, Deep Learning",Master,0,Education,2024-02-11,2024-03-05,1677,8.1,Future Systems -AI08640,ML Ops Engineer,106474,USD,106474,SE,CT,Ireland,S,Ireland,0,"PyTorch, SQL, AWS, Docker",Master,6,Consulting,2024-09-22,2024-10-06,1764,6.9,Algorithmic Solutions -AI08641,Computer Vision Engineer,233835,AUD,315677,EX,CT,Australia,M,Australia,100,"R, GCP, Mathematics",Associate,17,Government,2024-12-30,2025-02-18,2214,8.9,Future Systems -AI08642,Data Analyst,95754,SGD,124480,MI,CT,Singapore,M,Singapore,100,"Tableau, TensorFlow, NLP, SQL",Bachelor,2,Telecommunications,2024-07-21,2024-09-24,1939,8.9,AI Innovations -AI08643,Data Engineer,111708,CAD,139635,SE,CT,Canada,S,Russia,0,"Python, TensorFlow, Kubernetes, Hadoop, Docker",Bachelor,5,Government,2024-09-08,2024-11-12,2019,5.3,Quantum Computing Inc -AI08644,Principal Data Scientist,263271,JPY,28959810,EX,CT,Japan,M,Kenya,100,"Kubernetes, TensorFlow, Mathematics, AWS, PyTorch",Bachelor,14,Healthcare,2024-01-07,2024-03-11,1071,9.6,Quantum Computing Inc -AI08645,Robotics Engineer,201498,USD,201498,SE,PT,Norway,L,Norway,100,"Spark, Java, Docker, GCP, Statistics",Master,6,Telecommunications,2024-03-04,2024-04-17,1970,8.9,Cognitive Computing -AI08646,Machine Learning Researcher,98345,USD,98345,EN,PT,Norway,M,Norway,100,"R, Linux, Java",Bachelor,0,Automotive,2024-11-01,2024-11-27,1920,5.9,TechCorp Inc -AI08647,Data Engineer,47321,USD,47321,MI,PT,China,M,China,50,"GCP, Java, Tableau, Statistics",Associate,4,Manufacturing,2024-03-11,2024-04-06,1151,8.8,DataVision Ltd -AI08648,Data Analyst,76662,USD,76662,MI,FT,South Korea,S,Romania,100,"Statistics, Python, NLP",Associate,3,Retail,2025-04-06,2025-05-16,1934,9.5,Quantum Computing Inc -AI08649,Data Scientist,135115,USD,135115,SE,CT,Israel,L,Egypt,100,"Docker, Spark, R, MLOps, Azure",Associate,6,Manufacturing,2024-06-24,2024-08-29,1019,5.6,Cloud AI Solutions -AI08650,Computer Vision Engineer,95343,EUR,81042,MI,PT,France,M,France,100,"SQL, GCP, Docker, Computer Vision, Hadoop",Master,4,Technology,2024-07-08,2024-08-12,2321,7.6,TechCorp Inc -AI08651,Principal Data Scientist,19877,USD,19877,EN,FL,India,S,India,0,"R, Python, Computer Vision",PhD,1,Government,2024-10-25,2024-12-23,1853,6.7,Machine Intelligence Group -AI08652,AI Consultant,120340,SGD,156442,SE,FL,Singapore,M,Singapore,50,"Linux, Java, Python, Kubernetes, Deep Learning",Bachelor,8,Automotive,2024-07-20,2024-08-24,2341,9.6,Autonomous Tech -AI08653,Data Analyst,105495,SGD,137144,SE,CT,Singapore,S,Singapore,0,"Java, GCP, AWS",PhD,8,Transportation,2024-03-04,2024-05-16,715,7.8,Machine Intelligence Group -AI08654,Data Scientist,23760,USD,23760,EN,FL,China,S,China,50,"TensorFlow, Linux, Computer Vision",Associate,0,Telecommunications,2024-09-05,2024-10-10,2121,8.5,Neural Networks Co -AI08655,Research Scientist,81420,JPY,8956200,EN,FT,Japan,M,Japan,50,"PyTorch, Tableau, Scala",Bachelor,1,Technology,2024-08-07,2024-10-08,2240,6.8,Autonomous Tech -AI08656,Machine Learning Researcher,117907,SGD,153279,SE,PT,Singapore,M,Singapore,100,"Python, Git, R, TensorFlow, Statistics",Associate,6,Government,2024-02-08,2024-04-14,2148,7.7,Future Systems -AI08657,Machine Learning Engineer,96703,JPY,10637330,MI,FT,Japan,S,Japan,100,"Azure, Java, GCP, TensorFlow, MLOps",Associate,2,Healthcare,2025-04-06,2025-06-15,1390,8.5,Cloud AI Solutions -AI08658,Data Analyst,64544,AUD,87134,EN,CT,Australia,S,Australia,100,"SQL, Java, Mathematics, PyTorch",Bachelor,1,Transportation,2025-03-27,2025-04-17,1219,5.6,TechCorp Inc -AI08659,Principal Data Scientist,113782,JPY,12516020,SE,FL,Japan,M,Japan,100,"Scala, Azure, PyTorch, SQL",Bachelor,5,Media,2024-04-05,2024-05-10,1092,9.9,Predictive Systems -AI08660,Machine Learning Researcher,128270,USD,128270,MI,FT,United States,L,United States,100,"R, Git, Python, NLP, TensorFlow",Master,2,Telecommunications,2025-02-20,2025-03-25,2100,5.6,Machine Intelligence Group -AI08661,Head of AI,65592,USD,65592,MI,FL,Sweden,S,Sweden,100,"Python, Git, Scala",Master,3,Media,2024-03-04,2024-04-14,2111,9.3,Advanced Robotics -AI08662,AI Software Engineer,54617,CAD,68271,EN,FT,Canada,M,Canada,100,"MLOps, Java, Python",Bachelor,0,Manufacturing,2024-02-12,2024-04-24,993,8.7,Predictive Systems -AI08663,AI Consultant,82192,USD,82192,MI,FT,South Korea,M,Italy,50,"Kubernetes, Scala, Spark",Associate,2,Automotive,2024-03-05,2024-04-18,994,6.1,Advanced Robotics -AI08664,Principal Data Scientist,81981,EUR,69684,MI,FT,France,L,France,50,"Python, NLP, TensorFlow, Git, Java",Master,4,Media,2024-07-08,2024-09-08,1850,6.7,Neural Networks Co -AI08665,AI Research Scientist,76034,EUR,64629,MI,PT,Austria,S,Austria,0,"R, Computer Vision, Python, Kubernetes, MLOps",Bachelor,3,Manufacturing,2024-06-06,2024-07-30,1652,8,Future Systems -AI08666,AI Architect,24952,USD,24952,EN,CT,India,M,India,50,"Linux, PyTorch, Python, Hadoop",Bachelor,0,Manufacturing,2025-01-16,2025-03-24,2290,9.1,Cloud AI Solutions -AI08667,Data Engineer,44314,USD,44314,MI,CT,China,S,Switzerland,0,"PyTorch, GCP, SQL, Data Visualization, Tableau",PhD,2,Telecommunications,2024-09-05,2024-11-17,1117,7.4,Predictive Systems -AI08668,AI Product Manager,160046,CAD,200058,EX,CT,Canada,L,Canada,0,"Tableau, R, Git, Data Visualization, Computer Vision",Associate,10,Technology,2025-02-26,2025-04-08,1302,6.3,DataVision Ltd -AI08669,Data Scientist,224937,EUR,191196,EX,FL,Netherlands,M,China,0,"SQL, PyTorch, Mathematics",Master,13,Real Estate,2025-04-27,2025-06-14,2360,7.6,Predictive Systems -AI08670,Deep Learning Engineer,69057,SGD,89774,MI,PT,Singapore,S,Singapore,50,"R, AWS, Azure, Deep Learning",Associate,3,Technology,2024-01-25,2024-02-10,991,6.4,Cognitive Computing -AI08671,AI Consultant,65525,EUR,55696,EN,FL,Germany,M,Germany,100,"Hadoop, SQL, Computer Vision",PhD,0,Technology,2024-12-31,2025-01-27,1022,5.6,AI Innovations -AI08672,Data Engineer,231770,CHF,208593,EX,FT,Switzerland,M,Switzerland,0,"Kubernetes, Spark, GCP",PhD,10,Telecommunications,2024-03-09,2024-03-24,946,6.2,Quantum Computing Inc -AI08673,Autonomous Systems Engineer,189743,GBP,142307,EX,CT,United Kingdom,S,United Kingdom,0,"Python, Linux, TensorFlow, Data Visualization",Bachelor,11,Education,2024-11-11,2025-01-04,1985,7.6,DeepTech Ventures -AI08674,AI Consultant,84046,CAD,105058,MI,CT,Canada,L,Brazil,50,"NLP, GCP, Python, Tableau",Associate,2,Finance,2024-11-03,2025-01-11,1018,5.7,DeepTech Ventures -AI08675,Robotics Engineer,58018,USD,58018,SE,FL,China,M,China,100,"Computer Vision, Hadoop, Python",Associate,7,Media,2024-02-15,2024-03-11,2304,8,Neural Networks Co -AI08676,Head of AI,82096,USD,82096,EX,FT,China,L,Finland,50,"Git, Linux, Hadoop, GCP, Kubernetes",Associate,10,Finance,2025-02-10,2025-03-14,2277,5.1,Advanced Robotics -AI08677,AI Research Scientist,228962,EUR,194618,EX,FL,France,L,France,50,"Hadoop, SQL, Python",PhD,14,Energy,2024-10-15,2024-12-24,601,9.5,Quantum Computing Inc -AI08678,Head of AI,59789,EUR,50821,EN,CT,Netherlands,S,Netherlands,100,"R, Hadoop, Kubernetes, GCP",PhD,0,Finance,2024-10-26,2024-12-13,1908,7.9,Autonomous Tech -AI08679,AI Product Manager,65661,JPY,7222710,EN,CT,Japan,S,Japan,0,"Spark, Linux, PyTorch",Bachelor,0,Education,2024-09-27,2024-11-06,1374,6.3,Advanced Robotics -AI08680,Head of AI,192079,USD,192079,EX,FT,South Korea,L,South Korea,0,"Spark, Java, TensorFlow, Statistics, AWS",PhD,11,Telecommunications,2025-01-02,2025-03-05,2192,5.7,Predictive Systems -AI08681,Computer Vision Engineer,98259,EUR,83520,MI,FL,Germany,S,Germany,100,"Java, Spark, Mathematics, R",Associate,3,Telecommunications,2025-01-14,2025-03-21,639,8.4,Algorithmic Solutions -AI08682,Data Analyst,152980,SGD,198874,EX,FL,Singapore,M,Singapore,100,"R, Tableau, SQL",Associate,18,Transportation,2024-04-16,2024-05-07,1446,7,Autonomous Tech -AI08683,AI Product Manager,52672,EUR,44771,EN,FL,Austria,S,Austria,0,"R, Statistics, Data Visualization",Bachelor,0,Manufacturing,2024-07-12,2024-08-21,2084,9.1,Algorithmic Solutions -AI08684,ML Ops Engineer,22389,USD,22389,EN,FL,India,S,Luxembourg,0,"Mathematics, Tableau, GCP",Bachelor,1,Manufacturing,2024-10-17,2024-11-01,2404,9.6,Quantum Computing Inc -AI08685,ML Ops Engineer,62477,AUD,84344,EN,CT,Australia,M,Australia,0,"Hadoop, Git, Python",Master,1,Manufacturing,2024-02-07,2024-02-25,797,8.8,DataVision Ltd -AI08686,Principal Data Scientist,76545,USD,76545,MI,CT,Ireland,M,Ireland,100,"PyTorch, NLP, Java, Mathematics",Bachelor,3,Healthcare,2024-12-09,2025-02-01,1782,6.9,Cognitive Computing -AI08687,AI Software Engineer,86947,USD,86947,SE,FL,South Korea,M,Canada,100,"Kubernetes, TensorFlow, Python",PhD,6,Energy,2024-08-24,2024-10-19,976,6.5,Cloud AI Solutions -AI08688,Deep Learning Engineer,83441,GBP,62581,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, Python, TensorFlow, Git, PyTorch",Master,4,Media,2024-01-16,2024-03-19,555,7.4,Algorithmic Solutions -AI08689,AI Architect,300340,GBP,225255,EX,FT,United Kingdom,L,United Kingdom,100,"Git, Kubernetes, R, NLP, Deep Learning",Master,11,Real Estate,2025-03-16,2025-04-09,2004,6.7,Predictive Systems -AI08690,AI Research Scientist,149207,USD,149207,SE,CT,United States,S,United States,100,"Statistics, Azure, Computer Vision",Bachelor,6,Consulting,2024-01-12,2024-03-04,656,5.1,AI Innovations -AI08691,Principal Data Scientist,160666,EUR,136566,SE,PT,Netherlands,L,Nigeria,0,"GCP, Scala, Data Visualization, Spark, Mathematics",Master,9,Energy,2025-01-08,2025-01-30,2146,5.6,Algorithmic Solutions -AI08692,Machine Learning Researcher,150614,EUR,128022,SE,FL,Germany,L,Japan,0,"Python, Git, Spark",Master,7,Consulting,2024-07-28,2024-10-03,1729,8,DataVision Ltd -AI08693,AI Consultant,55468,EUR,47148,EN,CT,Germany,S,Germany,50,"Hadoop, Data Visualization, Git",Master,1,Technology,2024-05-18,2024-07-03,1912,9.4,Algorithmic Solutions -AI08694,Autonomous Systems Engineer,106627,USD,106627,MI,FL,Norway,M,Singapore,50,"Linux, Data Visualization, Python, Deep Learning",Associate,4,Automotive,2025-02-17,2025-04-03,2132,8.7,Future Systems -AI08695,Computer Vision Engineer,151032,SGD,196342,SE,CT,Singapore,M,Singapore,0,"Scala, Computer Vision, Linux, Spark",PhD,6,Automotive,2025-02-17,2025-04-16,2187,9.4,Algorithmic Solutions -AI08696,AI Architect,62996,USD,62996,EN,PT,South Korea,M,Mexico,100,"Scala, Data Visualization, Python, Statistics",PhD,0,Manufacturing,2024-12-15,2025-01-11,710,5.4,Quantum Computing Inc -AI08697,ML Ops Engineer,124463,AUD,168025,SE,PT,Australia,S,Ireland,100,"Spark, AWS, R, Computer Vision, PyTorch",PhD,6,Energy,2024-02-21,2024-04-05,2212,5.3,Predictive Systems -AI08698,Data Engineer,84011,EUR,71409,MI,FT,Germany,L,China,50,"SQL, Python, NLP, Statistics, Deep Learning",Bachelor,2,Healthcare,2024-10-16,2024-11-29,2444,8.4,Digital Transformation LLC -AI08699,Machine Learning Engineer,108909,USD,108909,SE,FL,South Korea,M,South Korea,0,"AWS, SQL, MLOps",PhD,6,Technology,2025-04-07,2025-06-06,2373,9.7,Machine Intelligence Group -AI08700,Autonomous Systems Engineer,117099,AUD,158084,SE,PT,Australia,M,Australia,50,"Azure, Tableau, SQL, Git",Bachelor,7,Telecommunications,2024-06-29,2024-07-16,1572,8.5,AI Innovations -AI08701,AI Architect,243649,CHF,219284,SE,CT,Switzerland,L,Switzerland,50,"R, NLP, Python, Azure",Bachelor,6,Telecommunications,2024-11-25,2024-12-22,734,7,Future Systems -AI08702,AI Consultant,85139,USD,85139,MI,CT,Sweden,S,Sweden,0,"Python, SQL, Computer Vision, Statistics",Bachelor,4,Manufacturing,2024-11-10,2024-12-25,746,9.7,Future Systems -AI08703,AI Architect,149890,CHF,134901,SE,PT,Switzerland,S,South Africa,50,"NLP, GCP, Spark, Linux",Associate,9,Retail,2024-10-04,2024-10-19,933,6.5,DeepTech Ventures -AI08704,Head of AI,72866,USD,72866,MI,FL,South Korea,M,South Korea,50,"Python, TensorFlow, NLP, Deep Learning, MLOps",Master,3,Finance,2024-07-12,2024-07-28,2089,9.4,Digital Transformation LLC -AI08705,AI Specialist,26722,USD,26722,EN,CT,India,L,India,50,"Azure, SQL, Java, PyTorch",Bachelor,1,Education,2024-07-12,2024-08-09,1064,6.8,TechCorp Inc -AI08706,AI Specialist,169001,USD,169001,SE,FT,Norway,L,Czech Republic,100,"Python, R, Computer Vision, Hadoop",Master,8,Finance,2024-09-14,2024-10-06,2184,5.4,Advanced Robotics -AI08707,Principal Data Scientist,71514,USD,71514,MI,PT,South Korea,S,South Korea,50,"Scala, Kubernetes, Azure, Deep Learning, SQL",Bachelor,3,Government,2025-01-30,2025-03-01,708,9.3,Algorithmic Solutions -AI08708,Machine Learning Researcher,128232,EUR,108997,SE,FT,Netherlands,M,Japan,50,"Spark, Data Visualization, TensorFlow, Mathematics, Azure",Master,6,Energy,2024-06-07,2024-07-01,883,6.9,Future Systems -AI08709,AI Software Engineer,58091,USD,58091,EN,FL,Israel,M,Austria,0,"Python, Mathematics, NLP, TensorFlow, Spark",Bachelor,1,Consulting,2025-04-07,2025-06-11,674,7.4,DataVision Ltd -AI08710,Deep Learning Engineer,63424,JPY,6976640,EN,CT,Japan,S,Japan,100,"Kubernetes, R, Hadoop, Azure",Associate,0,Real Estate,2024-08-27,2024-10-23,1625,8.8,Smart Analytics -AI08711,Computer Vision Engineer,65363,USD,65363,SE,FL,China,M,South Africa,0,"Hadoop, Tableau, GCP, Java",Associate,5,Telecommunications,2024-02-21,2024-03-19,2347,6.6,Smart Analytics -AI08712,Robotics Engineer,54587,USD,54587,EX,FL,India,M,India,0,"Python, TensorFlow, Docker, Mathematics, Java",Bachelor,18,Automotive,2024-10-04,2024-12-03,1159,6.4,Quantum Computing Inc -AI08713,Data Scientist,248642,CHF,223778,EX,FT,Switzerland,M,Switzerland,0,"AWS, MLOps, Docker",Master,11,Technology,2024-07-27,2024-09-02,1616,8.6,Algorithmic Solutions -AI08714,AI Software Engineer,64401,USD,64401,EX,FL,China,S,China,50,"Deep Learning, Kubernetes, Tableau, Python",PhD,17,Finance,2025-03-28,2025-04-12,1565,7.8,DeepTech Ventures -AI08715,AI Product Manager,92513,USD,92513,SE,PT,Finland,S,Belgium,50,"Kubernetes, TensorFlow, SQL, Deep Learning, Hadoop",Associate,5,Transportation,2024-10-14,2024-11-26,1362,9.3,Advanced Robotics -AI08716,Robotics Engineer,238453,USD,238453,EX,FT,United States,M,United States,0,"Java, Python, TensorFlow",Associate,11,Media,2025-03-27,2025-05-16,1106,7.8,Machine Intelligence Group -AI08717,Data Engineer,99160,AUD,133866,MI,PT,Australia,M,Australia,50,"Java, Scala, Python",PhD,3,Media,2024-11-29,2025-01-25,2447,7.6,Advanced Robotics -AI08718,Data Scientist,248599,USD,248599,EX,PT,Finland,L,Finland,0,"SQL, PyTorch, Tableau, Docker",Bachelor,13,Finance,2024-05-12,2024-06-26,2240,6.5,TechCorp Inc -AI08719,NLP Engineer,236767,USD,236767,EX,CT,Ireland,M,Ireland,100,"GCP, NLP, AWS, SQL, Kubernetes",Associate,13,Transportation,2024-10-12,2024-12-03,1905,5,AI Innovations -AI08720,Deep Learning Engineer,110782,GBP,83087,MI,FL,United Kingdom,L,United Kingdom,0,"GCP, Data Visualization, Linux, Computer Vision, Kubernetes",Associate,2,Gaming,2024-11-09,2024-12-16,609,8.5,Cloud AI Solutions -AI08721,AI Research Scientist,302161,GBP,226621,EX,CT,United Kingdom,L,United Kingdom,100,"Mathematics, Java, Data Visualization, R",PhD,18,Energy,2025-04-05,2025-05-01,2008,9.9,DataVision Ltd -AI08722,AI Architect,146187,SGD,190043,EX,FL,Singapore,S,Thailand,0,"Kubernetes, GCP, MLOps, Statistics, Git",Associate,12,Technology,2025-01-10,2025-03-23,1238,9.7,Advanced Robotics -AI08723,AI Specialist,94634,EUR,80439,MI,CT,France,L,France,0,"R, Scala, Computer Vision, Mathematics, Python",Master,3,Media,2024-08-26,2024-10-05,712,6.2,Neural Networks Co -AI08724,AI Consultant,115988,USD,115988,SE,FL,Finland,M,Finland,50,"Hadoop, SQL, R, NLP, Scala",Associate,8,Retail,2025-01-16,2025-03-25,1191,5.4,Future Systems -AI08725,Autonomous Systems Engineer,192776,EUR,163860,EX,PT,Austria,L,Chile,100,"Computer Vision, Kubernetes, Mathematics",PhD,12,Retail,2025-04-22,2025-06-07,1757,7.2,DataVision Ltd -AI08726,ML Ops Engineer,33869,USD,33869,EN,PT,China,L,China,0,"Computer Vision, Git, Python, Spark",Master,1,Consulting,2024-02-10,2024-03-09,2019,7.9,Cognitive Computing -AI08727,AI Research Scientist,77360,JPY,8509600,EN,PT,Japan,M,Kenya,100,"SQL, Mathematics, MLOps, Statistics, Azure",PhD,0,Media,2025-01-18,2025-02-24,1156,8.5,TechCorp Inc -AI08728,Data Engineer,236119,JPY,25973090,EX,CT,Japan,L,Japan,50,"AWS, Python, TensorFlow, NLP",PhD,13,Consulting,2024-11-22,2024-12-14,602,5.4,Cloud AI Solutions -AI08729,Machine Learning Researcher,99743,USD,99743,EX,FT,China,M,China,100,"Hadoop, Python, Deep Learning, Linux, Mathematics",Master,17,Healthcare,2024-07-03,2024-07-26,1081,5.7,Quantum Computing Inc -AI08730,Data Scientist,92399,USD,92399,EN,FT,Denmark,S,Germany,0,"Spark, Python, MLOps",PhD,1,Education,2025-04-24,2025-06-25,1223,5.8,TechCorp Inc -AI08731,Computer Vision Engineer,110170,USD,110170,MI,CT,Sweden,M,India,100,"Linux, Docker, R, Git, AWS",PhD,4,Gaming,2025-01-06,2025-02-21,2429,7.4,DataVision Ltd -AI08732,Machine Learning Researcher,198925,USD,198925,EX,CT,Ireland,S,Nigeria,0,"Scala, R, SQL",Master,13,Gaming,2024-03-05,2024-05-09,1898,5.9,Algorithmic Solutions -AI08733,Data Engineer,170795,EUR,145176,EX,PT,Austria,M,Austria,50,"Java, SQL, GCP",PhD,17,Gaming,2025-04-29,2025-05-14,2240,8.1,Quantum Computing Inc -AI08734,Machine Learning Researcher,152232,EUR,129397,EX,FL,Netherlands,M,Netherlands,100,"Java, Hadoop, Tableau, Statistics, Spark",Master,19,Telecommunications,2024-12-19,2025-02-23,1989,7.5,AI Innovations -AI08735,AI Architect,308244,USD,308244,EX,FL,Norway,M,Portugal,0,"Spark, Java, PyTorch, Azure, Linux",Associate,10,Energy,2025-04-07,2025-05-19,1331,6.8,DeepTech Ventures -AI08736,AI Product Manager,58771,USD,58771,SE,CT,India,L,India,50,"Deep Learning, Hadoop, Computer Vision",PhD,7,Government,2024-02-05,2024-03-08,1849,6.6,Algorithmic Solutions -AI08737,Machine Learning Engineer,69542,EUR,59111,EN,CT,Netherlands,M,New Zealand,50,"Azure, Java, AWS, Python",Associate,1,Government,2024-06-04,2024-06-27,680,7.1,Advanced Robotics -AI08738,Principal Data Scientist,99141,USD,99141,MI,FL,Ireland,L,Hungary,50,"AWS, Linux, R, NLP, Docker",Bachelor,2,Government,2024-04-22,2024-05-07,1798,7.7,Autonomous Tech -AI08739,Machine Learning Engineer,115731,AUD,156237,MI,CT,Australia,L,Australia,0,"Git, Kubernetes, R, Spark, Deep Learning",PhD,4,Automotive,2025-02-24,2025-03-17,1199,8.8,AI Innovations -AI08740,AI Architect,73001,SGD,94901,EN,FL,Singapore,L,Singapore,50,"PyTorch, Scala, Docker",PhD,0,Technology,2024-06-13,2024-07-21,1492,9.9,Predictive Systems -AI08741,ML Ops Engineer,354384,USD,354384,EX,CT,Denmark,L,Portugal,100,"Deep Learning, Azure, Data Visualization",Associate,17,Media,2024-08-28,2024-09-28,1776,7.6,Machine Intelligence Group -AI08742,AI Software Engineer,89933,JPY,9892630,MI,PT,Japan,M,Japan,100,"Python, Docker, Azure, AWS",PhD,3,Telecommunications,2024-04-09,2024-04-25,1282,8.2,DeepTech Ventures -AI08743,AI Specialist,165985,JPY,18258350,EX,FL,Japan,L,Japan,0,"Git, Scala, Computer Vision, PyTorch",Associate,11,Real Estate,2024-07-31,2024-09-05,2297,8.6,Machine Intelligence Group -AI08744,Machine Learning Engineer,84231,EUR,71596,MI,PT,France,M,Philippines,100,"Scala, Kubernetes, R, Mathematics",Bachelor,4,Automotive,2024-11-24,2025-01-01,663,7.3,Cloud AI Solutions -AI08745,AI Research Scientist,123845,USD,123845,SE,CT,United States,S,New Zealand,50,"AWS, Deep Learning, Git, Docker, Azure",Bachelor,6,Transportation,2024-01-13,2024-02-15,686,6.2,Algorithmic Solutions -AI08746,Data Scientist,272008,USD,272008,EX,FL,Norway,S,Romania,100,"Python, Kubernetes, Tableau, Deep Learning, Docker",Bachelor,19,Retail,2024-09-07,2024-10-12,1953,9.3,Smart Analytics -AI08747,ML Ops Engineer,338395,USD,338395,EX,PT,United States,L,United States,50,"Linux, Python, Spark, Scala, Deep Learning",PhD,15,Technology,2025-03-16,2025-04-19,2070,6.4,Cognitive Computing -AI08748,AI Consultant,104347,EUR,88695,MI,FL,Germany,M,Netherlands,100,"Spark, Mathematics, Deep Learning, Computer Vision, AWS",Associate,4,Manufacturing,2024-02-18,2024-04-02,821,9.4,Machine Intelligence Group -AI08749,ML Ops Engineer,129907,JPY,14289770,SE,PT,Japan,S,Japan,100,"Data Visualization, Java, Tableau, TensorFlow, GCP",PhD,8,Real Estate,2024-12-04,2025-01-17,2013,5.7,Machine Intelligence Group -AI08750,Robotics Engineer,75071,EUR,63810,EN,CT,Austria,L,Austria,50,"Tableau, Mathematics, Python, TensorFlow, Deep Learning",PhD,1,Finance,2024-03-17,2024-05-28,2359,7.6,TechCorp Inc -AI08751,Data Scientist,89718,USD,89718,EN,FL,Ireland,L,Ireland,0,"SQL, Python, PyTorch",PhD,1,Healthcare,2024-12-28,2025-01-13,883,6.6,Predictive Systems -AI08752,Head of AI,123663,JPY,13602930,SE,CT,Japan,S,Japan,50,"Kubernetes, AWS, Statistics, Computer Vision",Associate,6,Education,2024-03-31,2024-05-07,522,6.3,DataVision Ltd -AI08753,AI Architect,232491,EUR,197617,EX,CT,France,M,France,50,"GCP, AWS, Hadoop, Tableau, Statistics",Bachelor,18,Healthcare,2024-03-27,2024-05-09,1496,9.3,Machine Intelligence Group -AI08754,Machine Learning Researcher,54167,USD,54167,SE,PT,India,L,Norway,0,"Git, Linux, Spark, Mathematics",Master,7,Education,2024-01-31,2024-03-30,2248,8.6,DataVision Ltd -AI08755,AI Product Manager,89079,CAD,111349,MI,CT,Canada,L,Canada,100,"MLOps, SQL, Python",Associate,2,Manufacturing,2024-08-25,2024-09-15,2460,6.6,Smart Analytics -AI08756,Data Scientist,194970,GBP,146228,EX,PT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, R, NLP, Deep Learning",Master,19,Government,2024-10-02,2024-10-16,961,8.8,Smart Analytics -AI08757,ML Ops Engineer,228547,USD,228547,EX,FL,Sweden,S,Sweden,0,"Tableau, Spark, GCP",PhD,13,Government,2025-01-10,2025-02-18,1740,7.2,Digital Transformation LLC -AI08758,Robotics Engineer,52055,USD,52055,SE,FL,India,L,India,50,"Linux, Hadoop, SQL",Bachelor,7,Automotive,2024-03-14,2024-04-05,2193,8.6,Advanced Robotics -AI08759,Head of AI,57328,USD,57328,EX,CT,India,M,India,50,"Python, R, Deep Learning, NLP, AWS",Associate,12,Education,2025-03-02,2025-03-31,1122,8.4,TechCorp Inc -AI08760,Autonomous Systems Engineer,52301,USD,52301,EN,PT,Sweden,S,Sweden,0,"Hadoop, Python, Kubernetes, Computer Vision, TensorFlow",Master,1,Telecommunications,2025-04-04,2025-04-23,1291,7.4,Cloud AI Solutions -AI08761,Robotics Engineer,23552,USD,23552,EN,PT,India,L,India,50,"Azure, Java, NLP, R, Deep Learning",PhD,0,Manufacturing,2025-03-20,2025-04-14,953,9.5,Quantum Computing Inc -AI08762,AI Product Manager,135585,EUR,115247,SE,FT,Netherlands,S,Netherlands,50,"Java, SQL, PyTorch, Deep Learning, Docker",Bachelor,8,Government,2024-10-09,2024-11-29,2293,6.8,Advanced Robotics -AI08763,AI Software Engineer,281620,USD,281620,EX,FT,Ireland,L,Ireland,50,"Git, Kubernetes, Scala, Spark, Computer Vision",Bachelor,13,Gaming,2024-06-15,2024-08-10,770,8.7,Digital Transformation LLC -AI08764,NLP Engineer,158612,SGD,206196,SE,CT,Singapore,M,Singapore,0,"Spark, Data Visualization, Java, MLOps, Linux",Master,5,Retail,2024-07-17,2024-09-15,836,6.9,Advanced Robotics -AI08765,AI Specialist,104480,USD,104480,MI,CT,Ireland,L,Ireland,100,"TensorFlow, Python, Tableau, SQL",PhD,4,Energy,2024-01-29,2024-04-03,734,8.8,Machine Intelligence Group -AI08766,Machine Learning Engineer,50599,EUR,43009,EN,FT,Germany,S,Romania,50,"Python, Hadoop, Data Visualization, Scala",Master,1,Government,2024-09-22,2024-11-07,857,5.1,Future Systems -AI08767,AI Consultant,74316,EUR,63169,MI,FT,Netherlands,S,Netherlands,100,"Linux, Tableau, SQL, Kubernetes",Master,3,Technology,2024-11-05,2024-12-04,763,5.8,Predictive Systems -AI08768,Robotics Engineer,91016,CAD,113770,MI,CT,Canada,L,Switzerland,50,"Hadoop, Spark, Deep Learning, Python",Associate,3,Transportation,2025-04-14,2025-05-10,1257,6.5,Cloud AI Solutions -AI08769,AI Product Manager,83508,USD,83508,MI,FT,Finland,L,Finland,50,"Linux, Git, PyTorch, Hadoop",Bachelor,3,Technology,2024-12-11,2025-01-29,725,7.6,Machine Intelligence Group -AI08770,AI Research Scientist,54579,USD,54579,EN,PT,Israel,S,Luxembourg,100,"Tableau, GCP, Git",Associate,0,Government,2025-04-01,2025-05-12,1489,6.9,Machine Intelligence Group -AI08771,NLP Engineer,147819,EUR,125646,EX,PT,Netherlands,S,Netherlands,50,"Data Visualization, PyTorch, Hadoop",Master,13,Automotive,2025-03-22,2025-04-10,1636,10,Future Systems -AI08772,Autonomous Systems Engineer,85094,USD,85094,MI,FT,Sweden,S,Finland,100,"Scala, Azure, Spark",Master,3,Consulting,2024-10-17,2024-12-04,801,7.3,Digital Transformation LLC -AI08773,AI Product Manager,18730,USD,18730,EN,CT,India,S,India,100,"Data Visualization, R, SQL",Associate,0,Real Estate,2024-08-01,2024-08-18,1893,6,Smart Analytics -AI08774,Deep Learning Engineer,89305,EUR,75909,MI,FT,Netherlands,S,South Korea,100,"AWS, Python, MLOps, TensorFlow, Hadoop",Master,3,Manufacturing,2024-04-16,2024-06-22,659,6.6,Smart Analytics -AI08775,Data Engineer,67597,USD,67597,MI,FT,South Korea,S,South Korea,100,"Deep Learning, Kubernetes, GCP",PhD,2,Telecommunications,2024-11-08,2025-01-03,1645,6.6,Future Systems -AI08776,NLP Engineer,67427,SGD,87655,EN,PT,Singapore,M,Singapore,0,"Linux, Mathematics, Hadoop",Master,0,Automotive,2024-04-20,2024-06-22,563,7.4,Autonomous Tech -AI08777,Machine Learning Engineer,80525,CAD,100656,MI,CT,Canada,S,Canada,0,"Mathematics, Kubernetes, SQL",PhD,3,Technology,2024-04-12,2024-06-24,533,8.2,Cloud AI Solutions -AI08778,Machine Learning Researcher,73119,USD,73119,EN,CT,Israel,M,Australia,100,"R, Kubernetes, Docker",Associate,0,Technology,2024-08-30,2024-11-11,2228,9.9,Smart Analytics -AI08779,Data Engineer,76899,USD,76899,EN,FT,Norway,L,Norway,50,"MLOps, NLP, Docker, Git",PhD,1,Finance,2024-03-06,2024-05-18,728,9.6,Machine Intelligence Group -AI08780,AI Specialist,71826,EUR,61052,EN,CT,Austria,M,Brazil,100,"Docker, Git, Hadoop, SQL, Computer Vision",Master,0,Transportation,2024-11-24,2024-12-20,1285,5.3,Quantum Computing Inc -AI08781,Autonomous Systems Engineer,101327,USD,101327,EN,PT,Norway,M,Norway,50,"Java, GCP, Python",Associate,1,Telecommunications,2024-11-18,2024-12-23,1879,6,Algorithmic Solutions -AI08782,Robotics Engineer,69083,USD,69083,MI,CT,Israel,M,Israel,100,"Python, Kubernetes, Docker",Master,2,Technology,2024-07-22,2024-08-08,1075,5.2,Algorithmic Solutions -AI08783,ML Ops Engineer,90930,EUR,77291,MI,PT,Austria,M,Austria,0,"Scala, TensorFlow, MLOps, Python",Master,2,Media,2024-09-10,2024-09-27,2010,7.2,DeepTech Ventures -AI08784,Autonomous Systems Engineer,124784,USD,124784,SE,PT,South Korea,M,Mexico,100,"Linux, Azure, Python",Bachelor,8,Media,2024-08-10,2024-10-12,632,5.8,DataVision Ltd -AI08785,Deep Learning Engineer,112554,USD,112554,MI,FT,Norway,M,Norway,50,"Python, Computer Vision, TensorFlow, Java, Hadoop",Master,4,Technology,2024-03-26,2024-04-17,644,7.1,Neural Networks Co -AI08786,AI Consultant,138859,EUR,118030,SE,FT,France,M,France,0,"NLP, Git, Azure, R, Python",Master,6,Retail,2024-03-25,2024-05-02,2136,7.2,Future Systems -AI08787,Data Scientist,155807,EUR,132436,EX,CT,France,L,Singapore,100,"AWS, R, Python, Git, Scala",PhD,18,Consulting,2024-11-14,2024-12-10,1084,6.8,Digital Transformation LLC -AI08788,Computer Vision Engineer,70709,EUR,60103,EN,CT,Germany,S,Canada,50,"TensorFlow, SQL, AWS",Master,1,Automotive,2024-05-10,2024-07-16,1987,8.1,Advanced Robotics -AI08789,NLP Engineer,20948,USD,20948,EN,FL,India,S,India,50,"Scala, Spark, Docker",Associate,1,Technology,2025-03-14,2025-05-08,505,9.5,Smart Analytics -AI08790,Head of AI,128719,EUR,109411,SE,PT,Netherlands,M,Turkey,100,"R, GCP, Python, Java, Mathematics",PhD,7,Energy,2024-06-13,2024-08-06,1872,9.6,Neural Networks Co -AI08791,AI Product Manager,73053,USD,73053,EN,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Azure",PhD,1,Telecommunications,2024-07-18,2024-08-03,1480,6.1,DataVision Ltd -AI08792,Research Scientist,127282,USD,127282,MI,PT,Denmark,S,Denmark,50,"Tableau, Spark, Python, Linux",PhD,4,Telecommunications,2024-07-24,2024-09-01,2464,8.9,DeepTech Ventures -AI08793,AI Product Manager,195816,SGD,254561,EX,FT,Singapore,S,Singapore,0,"Git, R, Deep Learning, Mathematics, Java",Master,13,Telecommunications,2024-01-03,2024-02-25,1036,6.2,Autonomous Tech -AI08794,NLP Engineer,169752,USD,169752,EX,CT,United States,M,United States,0,"MLOps, Java, Statistics, Data Visualization",Associate,14,Healthcare,2025-04-23,2025-06-24,956,5.7,Predictive Systems -AI08795,AI Consultant,105502,USD,105502,EX,FT,China,L,China,0,"SQL, Linux, Tableau, Computer Vision",Master,10,Transportation,2025-01-09,2025-02-24,1935,5.5,TechCorp Inc -AI08796,Data Engineer,112014,USD,112014,SE,PT,Ireland,S,Ireland,100,"TensorFlow, Scala, Python, Docker, R",Associate,6,Finance,2025-01-19,2025-03-09,1596,9.5,Machine Intelligence Group -AI08797,Machine Learning Engineer,247688,JPY,27245680,EX,FT,Japan,L,Japan,50,"PyTorch, SQL, Kubernetes, R",Master,18,Real Estate,2025-02-20,2025-05-03,1479,8.2,Autonomous Tech -AI08798,ML Ops Engineer,74961,EUR,63717,EN,PT,France,M,France,0,"TensorFlow, Data Visualization, Linux",PhD,1,Gaming,2024-10-24,2024-12-19,1666,6.3,Neural Networks Co -AI08799,ML Ops Engineer,115927,USD,115927,SE,PT,South Korea,L,Latvia,50,"Kubernetes, Data Visualization, PyTorch, GCP",PhD,8,Real Estate,2024-09-19,2024-10-10,2021,9.5,AI Innovations -AI08800,AI Consultant,60784,EUR,51666,EN,FT,France,S,France,50,"Tableau, NLP, Computer Vision, R",Master,0,Transportation,2025-04-01,2025-05-24,2418,5.9,Advanced Robotics -AI08801,Research Scientist,88808,EUR,75487,MI,FL,Germany,S,Germany,50,"GCP, PyTorch, Computer Vision",Master,2,Telecommunications,2025-04-04,2025-05-14,865,9.4,DeepTech Ventures -AI08802,AI Research Scientist,147363,EUR,125259,SE,CT,Austria,L,Austria,100,"Python, GCP, Computer Vision, TensorFlow, Azure",Associate,6,Manufacturing,2024-10-25,2025-01-02,651,8.3,Digital Transformation LLC -AI08803,AI Specialist,49188,USD,49188,EX,FT,India,S,India,100,"R, Azure, Linux, Computer Vision, Java",Associate,17,Healthcare,2024-07-25,2024-08-18,1743,9.3,Cloud AI Solutions -AI08804,Principal Data Scientist,159673,AUD,215559,EX,PT,Australia,M,Australia,0,"Hadoop, Linux, Java",PhD,18,Transportation,2025-03-01,2025-04-14,594,7.9,Future Systems -AI08805,AI Specialist,113403,EUR,96393,SE,CT,Germany,M,Germany,50,"Spark, Java, Tableau, Python, Statistics",Bachelor,7,Energy,2024-12-18,2025-03-01,2388,7.3,Smart Analytics -AI08806,Deep Learning Engineer,101965,USD,101965,MI,PT,Denmark,M,Denmark,0,"Scala, Python, Spark, Data Visualization",Bachelor,2,Media,2025-02-21,2025-03-26,1964,9.9,Advanced Robotics -AI08807,Head of AI,75727,USD,75727,MI,FL,Ireland,M,Ireland,50,"Data Visualization, Python, Deep Learning",Bachelor,4,Real Estate,2024-04-11,2024-06-07,2012,7.1,Machine Intelligence Group -AI08808,Principal Data Scientist,64011,EUR,54409,MI,CT,France,S,France,0,"R, Scala, NLP",PhD,2,Retail,2024-12-19,2025-01-03,528,5.5,AI Innovations -AI08809,Machine Learning Engineer,108796,JPY,11967560,MI,FL,Japan,L,Brazil,50,"R, Deep Learning, GCP, Computer Vision, Scala",Bachelor,4,Automotive,2024-06-13,2024-08-07,877,7.6,TechCorp Inc -AI08810,Robotics Engineer,235070,JPY,25857700,EX,CT,Japan,L,Japan,100,"Data Visualization, Scala, Linux, Python, Hadoop",Bachelor,11,Technology,2025-04-17,2025-05-07,1540,5.5,AI Innovations -AI08811,Data Engineer,180679,USD,180679,EX,FT,South Korea,M,Netherlands,100,"SQL, Linux, Java, Git",PhD,15,Healthcare,2024-03-17,2024-05-29,2493,8.8,Advanced Robotics -AI08812,Robotics Engineer,151818,EUR,129045,EX,FL,Germany,S,Thailand,0,"SQL, Java, R",PhD,19,Technology,2024-12-21,2025-01-19,887,7.9,Digital Transformation LLC -AI08813,Autonomous Systems Engineer,106856,USD,106856,MI,CT,Israel,L,Portugal,0,"Statistics, R, Tableau",PhD,4,Consulting,2024-02-27,2024-04-09,1290,6.3,Cloud AI Solutions -AI08814,Robotics Engineer,108490,JPY,11933900,MI,PT,Japan,M,Mexico,100,"Azure, Python, Deep Learning",PhD,2,Education,2024-04-06,2024-04-22,1077,6,Smart Analytics -AI08815,ML Ops Engineer,71874,EUR,61093,MI,CT,France,M,France,0,"Kubernetes, Python, SQL, MLOps, Statistics",PhD,3,Real Estate,2024-09-18,2024-11-30,1725,5.5,Quantum Computing Inc -AI08816,AI Consultant,202910,EUR,172474,EX,FL,France,S,Hungary,50,"PyTorch, Tableau, TensorFlow, Computer Vision",Bachelor,19,Real Estate,2025-01-26,2025-03-15,1807,8.3,DataVision Ltd -AI08817,AI Product Manager,118893,EUR,101059,SE,FL,Austria,L,Australia,50,"Deep Learning, Linux, GCP, Mathematics",Master,9,Retail,2024-03-16,2024-04-03,718,5.9,Digital Transformation LLC -AI08818,Data Analyst,90747,USD,90747,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Java, Git",Associate,4,Technology,2024-12-17,2025-02-23,1975,7.1,Digital Transformation LLC -AI08819,AI Software Engineer,55913,USD,55913,EN,FT,Ireland,M,Estonia,50,"Tableau, Spark, PyTorch, SQL, Data Visualization",Master,0,Consulting,2024-01-27,2024-02-27,936,5.8,Future Systems -AI08820,Data Scientist,321130,CHF,289017,EX,PT,Switzerland,S,Finland,100,"AWS, Docker, MLOps, SQL, Kubernetes",Bachelor,16,Telecommunications,2024-01-31,2024-04-03,572,9.1,Cognitive Computing -AI08821,Data Scientist,48284,USD,48284,EN,CT,Finland,S,Finland,50,"Python, Git, Linux, AWS",Master,0,Education,2024-04-26,2024-06-29,1758,7,DataVision Ltd -AI08822,Machine Learning Engineer,93069,USD,93069,EN,PT,Denmark,L,Denmark,0,"Data Visualization, Mathematics, Python, NLP",Bachelor,1,Education,2025-03-20,2025-05-22,1265,9.3,DataVision Ltd -AI08823,AI Architect,154216,USD,154216,SE,CT,Norway,L,Norway,0,"Scala, Git, Mathematics, Spark",Bachelor,5,Finance,2024-09-08,2024-11-01,652,8.7,TechCorp Inc -AI08824,Autonomous Systems Engineer,212745,AUD,287206,EX,PT,Australia,M,Australia,50,"NLP, Data Visualization, Docker, Python, Spark",PhD,10,Automotive,2025-03-11,2025-04-22,1584,9,Cloud AI Solutions -AI08825,ML Ops Engineer,148725,AUD,200779,EX,FT,Australia,M,Australia,50,"Computer Vision, Docker, TensorFlow",PhD,16,Automotive,2025-04-25,2025-05-30,1977,5.7,Predictive Systems -AI08826,Deep Learning Engineer,214868,AUD,290072,EX,CT,Australia,S,South Africa,100,"SQL, Computer Vision, Java, Mathematics, AWS",Master,17,Consulting,2024-12-07,2025-01-17,613,6.9,Neural Networks Co -AI08827,AI Consultant,48192,USD,48192,EN,CT,Sweden,S,Luxembourg,100,"SQL, TensorFlow, Git",Associate,0,Manufacturing,2024-02-11,2024-03-09,1626,7.6,Digital Transformation LLC -AI08828,Autonomous Systems Engineer,53715,USD,53715,EN,FT,Israel,S,Israel,50,"Python, TensorFlow, Linux, AWS, R",Associate,1,Education,2024-07-18,2024-08-02,1454,6.6,AI Innovations -AI08829,Data Engineer,79419,EUR,67506,MI,FL,Netherlands,S,Chile,100,"Python, Java, Computer Vision, AWS",PhD,3,Retail,2024-03-22,2024-05-07,2420,9.3,Quantum Computing Inc -AI08830,ML Ops Engineer,189251,EUR,160863,EX,FL,Austria,M,Austria,100,"Kubernetes, Computer Vision, Python, GCP, Statistics",Bachelor,12,Energy,2024-07-28,2024-08-22,1299,8.1,Cognitive Computing -AI08831,AI Product Manager,82862,USD,82862,MI,FT,United States,S,United States,50,"Tableau, Spark, Python",PhD,2,Technology,2024-03-14,2024-04-21,1366,9.2,TechCorp Inc -AI08832,Research Scientist,312798,CHF,281518,EX,CT,Switzerland,S,Portugal,100,"PyTorch, Mathematics, Deep Learning, TensorFlow",Associate,12,Retail,2024-06-06,2024-06-27,1963,5.8,Cloud AI Solutions -AI08833,ML Ops Engineer,104615,CHF,94154,EN,FL,Switzerland,L,United States,0,"Linux, Spark, Git, SQL, Hadoop",Master,0,Media,2024-06-22,2024-07-29,2231,9.5,Smart Analytics -AI08834,Deep Learning Engineer,42852,USD,42852,MI,FL,China,L,China,50,"R, Java, Azure, Deep Learning, AWS",Bachelor,2,Automotive,2024-05-03,2024-07-04,934,6.3,Smart Analytics -AI08835,Principal Data Scientist,83129,CAD,103911,MI,FT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Linux",Bachelor,3,Real Estate,2024-04-15,2024-05-03,810,5.5,Digital Transformation LLC -AI08836,Robotics Engineer,64763,SGD,84192,EN,PT,Singapore,S,Singapore,50,"R, SQL, Deep Learning",PhD,0,Government,2024-04-30,2024-07-10,1126,9.1,Neural Networks Co -AI08837,Data Scientist,140525,SGD,182683,SE,PT,Singapore,L,China,0,"Docker, Spark, Python, AWS",Associate,6,Automotive,2024-05-15,2024-07-25,816,8.2,TechCorp Inc -AI08838,AI Software Engineer,164731,AUD,222387,SE,FT,Australia,L,Australia,0,"Linux, PyTorch, Data Visualization, SQL",Bachelor,8,Automotive,2024-11-18,2024-12-17,1758,6.2,DataVision Ltd -AI08839,Machine Learning Researcher,58860,USD,58860,MI,CT,China,L,China,100,"Python, R, TensorFlow",PhD,4,Transportation,2024-10-13,2024-12-15,1321,9.7,Cloud AI Solutions -AI08840,AI Specialist,117441,USD,117441,MI,CT,Norway,M,Norway,100,"Mathematics, Kubernetes, NLP, Computer Vision, Linux",Master,4,Automotive,2025-03-10,2025-05-04,1794,8.9,DataVision Ltd -AI08841,Computer Vision Engineer,72350,EUR,61498,EN,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, PyTorch, Tableau",Bachelor,1,Energy,2024-06-22,2024-07-12,504,6.1,TechCorp Inc -AI08842,Deep Learning Engineer,92337,AUD,124655,SE,PT,Australia,S,South Africa,100,"AWS, Spark, Computer Vision, Docker, Mathematics",Bachelor,7,Healthcare,2024-07-16,2024-08-26,1201,5.5,Advanced Robotics -AI08843,Autonomous Systems Engineer,53864,EUR,45784,EN,CT,Austria,M,Mexico,0,"Deep Learning, Hadoop, Linux",PhD,0,Transportation,2024-10-12,2024-12-11,2012,7.7,Machine Intelligence Group -AI08844,AI Architect,33665,USD,33665,MI,CT,India,L,India,0,"Mathematics, Kubernetes, Docker, Scala",Associate,4,Finance,2024-03-13,2024-04-13,1806,9.4,Advanced Robotics -AI08845,Machine Learning Researcher,182110,EUR,154794,EX,PT,France,M,France,50,"Python, Git, Tableau, NLP",Associate,13,Energy,2025-03-18,2025-04-08,1774,9.6,Future Systems -AI08846,Head of AI,115234,SGD,149804,MI,FL,Singapore,L,Singapore,0,"Kubernetes, Computer Vision, Azure",Master,4,Energy,2024-01-16,2024-02-03,2189,8.7,Neural Networks Co -AI08847,Data Analyst,163943,SGD,213126,EX,FL,Singapore,M,Singapore,100,"MLOps, Linux, NLP",PhD,12,Energy,2024-04-04,2024-06-05,843,8,DeepTech Ventures -AI08848,Autonomous Systems Engineer,153511,JPY,16886210,SE,PT,Japan,M,Argentina,50,"Spark, Git, Python, TensorFlow",PhD,9,Education,2024-12-30,2025-02-12,1650,6.8,DataVision Ltd -AI08849,NLP Engineer,110442,SGD,143575,MI,FT,Singapore,L,Singapore,100,"Spark, Python, TensorFlow, R",Master,4,Healthcare,2025-03-17,2025-05-20,894,5.7,TechCorp Inc -AI08850,Research Scientist,136904,USD,136904,EX,FL,Israel,M,Israel,0,"Spark, Linux, Kubernetes",Master,14,Technology,2024-10-31,2024-12-17,2225,9.7,Future Systems -AI08851,ML Ops Engineer,83201,USD,83201,EN,FT,Finland,L,Thailand,50,"Hadoop, NLP, Python",Master,1,Real Estate,2025-02-21,2025-03-27,543,7.2,Predictive Systems -AI08852,Robotics Engineer,134018,CAD,167523,SE,PT,Canada,L,Thailand,50,"Python, Java, Data Visualization",Associate,6,Media,2024-01-08,2024-03-14,889,6.6,Predictive Systems -AI08853,Principal Data Scientist,88509,EUR,75233,MI,PT,France,M,France,100,"PyTorch, R, Computer Vision, Scala",Associate,2,Healthcare,2024-01-14,2024-03-05,2308,8.5,Digital Transformation LLC -AI08854,Research Scientist,126724,USD,126724,MI,PT,Denmark,L,Denmark,100,"Git, Python, TensorFlow, PyTorch",PhD,2,Technology,2024-05-19,2024-06-12,1390,7.3,Future Systems -AI08855,Principal Data Scientist,281410,EUR,239199,EX,FL,Netherlands,L,Egypt,0,"Statistics, Mathematics, NLP, Docker, Computer Vision",Master,15,Government,2024-04-19,2024-05-12,1403,5.5,Digital Transformation LLC -AI08856,Head of AI,162401,CAD,203001,EX,PT,Canada,M,Ghana,0,"PyTorch, Mathematics, MLOps, TensorFlow, NLP",Associate,17,Healthcare,2025-04-20,2025-06-18,1233,7.2,Autonomous Tech -AI08857,Machine Learning Engineer,180046,CHF,162041,SE,FT,Switzerland,M,Ghana,0,"Statistics, R, Java",Associate,8,Consulting,2024-07-23,2024-09-21,740,6.3,Neural Networks Co -AI08858,Data Scientist,73927,USD,73927,MI,CT,Sweden,S,Mexico,0,"Hadoop, MLOps, Linux, Spark, Git",Associate,2,Healthcare,2024-07-31,2024-09-05,2041,5.5,TechCorp Inc -AI08859,Data Engineer,109990,EUR,93492,MI,FL,Germany,M,United States,50,"Python, Java, Hadoop, Statistics, Computer Vision",Master,3,Real Estate,2024-06-28,2024-08-22,2199,5.8,Machine Intelligence Group -AI08860,Data Scientist,126474,USD,126474,SE,CT,Israel,L,Russia,100,"Tableau, Java, Kubernetes",Master,6,Consulting,2025-02-20,2025-04-07,1834,5.9,AI Innovations -AI08861,AI Research Scientist,160685,EUR,136582,EX,PT,Netherlands,M,Netherlands,0,"R, GCP, Git, Spark",PhD,13,Media,2024-05-28,2024-06-13,2083,6,Machine Intelligence Group -AI08862,Deep Learning Engineer,317312,CHF,285581,EX,CT,Switzerland,S,United Kingdom,50,"Git, R, GCP, Kubernetes, Java",Bachelor,16,Technology,2024-09-15,2024-11-12,1711,7.7,Advanced Robotics -AI08863,AI Consultant,85129,USD,85129,EN,PT,Denmark,L,Denmark,0,"NLP, PyTorch, TensorFlow",Bachelor,0,Energy,2024-09-29,2024-12-06,1340,8.8,Quantum Computing Inc -AI08864,AI Consultant,162063,USD,162063,EX,FL,Finland,L,Poland,50,"Deep Learning, Docker, AWS, SQL",Bachelor,16,Gaming,2024-05-05,2024-06-11,1974,8.3,Machine Intelligence Group -AI08865,Computer Vision Engineer,50185,USD,50185,EN,CT,Finland,M,India,50,"AWS, R, Deep Learning",Master,1,Education,2024-06-16,2024-07-02,1048,7.8,AI Innovations -AI08866,Autonomous Systems Engineer,212146,EUR,180324,EX,FT,Austria,L,Austria,50,"Java, TensorFlow, Mathematics, Tableau",Master,12,Technology,2025-03-07,2025-04-18,1448,5.2,DataVision Ltd -AI08867,AI Specialist,205751,JPY,22632610,EX,PT,Japan,M,Norway,50,"TensorFlow, Azure, Scala",Associate,19,Education,2024-04-13,2024-05-12,1542,7.7,DataVision Ltd -AI08868,AI Software Engineer,144178,USD,144178,SE,CT,Sweden,L,Indonesia,50,"PyTorch, GCP, Spark",Associate,5,Energy,2024-01-24,2024-02-18,2406,5.2,Quantum Computing Inc -AI08869,Machine Learning Researcher,154217,CHF,138795,SE,CT,Switzerland,M,Switzerland,0,"Scala, Computer Vision, Kubernetes, Deep Learning, Docker",Master,5,Gaming,2024-10-30,2024-12-09,2011,8.5,Cognitive Computing -AI08870,Data Analyst,118300,USD,118300,SE,FL,Israel,L,Israel,0,"Statistics, MLOps, Spark, Computer Vision, TensorFlow",Associate,6,Retail,2024-03-22,2024-04-14,1823,6.4,Cognitive Computing -AI08871,Data Analyst,164623,USD,164623,SE,CT,Norway,L,Norway,0,"Python, SQL, Computer Vision, Mathematics, TensorFlow",Master,5,Education,2024-12-11,2025-01-19,2283,7.2,Advanced Robotics -AI08872,Data Engineer,209872,USD,209872,EX,PT,Denmark,M,Denmark,0,"Kubernetes, Azure, Tableau, R, NLP",PhD,12,Energy,2025-04-03,2025-05-14,1604,9.2,Quantum Computing Inc -AI08873,Deep Learning Engineer,140537,EUR,119456,SE,CT,France,L,France,100,"Linux, MLOps, TensorFlow, PyTorch, Mathematics",Master,6,Finance,2024-06-08,2024-07-29,1729,5.8,Neural Networks Co -AI08874,Principal Data Scientist,72674,USD,72674,MI,FT,Israel,S,Vietnam,0,"Linux, Java, SQL, Kubernetes, PyTorch",PhD,2,Consulting,2025-04-10,2025-06-22,1258,7.7,TechCorp Inc -AI08875,AI Product Manager,96117,EUR,81699,MI,FT,France,L,Australia,100,"Linux, Java, Scala",Master,2,Education,2025-04-21,2025-06-20,1684,7.7,AI Innovations -AI08876,Data Scientist,132251,EUR,112413,SE,FL,Netherlands,L,Canada,0,"SQL, Kubernetes, Azure, Computer Vision",Master,7,Gaming,2024-08-03,2024-08-22,1336,9.3,Advanced Robotics -AI08877,Robotics Engineer,180163,SGD,234212,SE,PT,Singapore,L,Singapore,100,"Kubernetes, SQL, Linux",Associate,9,Technology,2024-09-26,2024-10-14,2472,6,Machine Intelligence Group -AI08878,AI Software Engineer,64220,GBP,48165,EN,FL,United Kingdom,S,United Kingdom,0,"Data Visualization, Azure, NLP",Associate,0,Media,2024-10-13,2024-11-25,947,8.6,Digital Transformation LLC -AI08879,Computer Vision Engineer,70080,AUD,94608,EN,CT,Australia,L,Australia,0,"Scala, PyTorch, TensorFlow, Tableau, Deep Learning",PhD,1,Real Estate,2025-01-18,2025-03-27,2308,8.5,Algorithmic Solutions -AI08880,Head of AI,72201,USD,72201,MI,PT,Finland,M,Israel,50,"NLP, Deep Learning, MLOps, PyTorch",PhD,3,Manufacturing,2025-03-31,2025-04-16,1516,9.5,Advanced Robotics -AI08881,AI Research Scientist,150170,CAD,187713,EX,FL,Canada,S,Canada,50,"Computer Vision, Java, TensorFlow",PhD,11,Government,2025-02-27,2025-03-29,2288,9,Digital Transformation LLC -AI08882,NLP Engineer,68586,USD,68586,EN,FL,Sweden,M,Estonia,50,"Deep Learning, Spark, GCP",Bachelor,1,Telecommunications,2024-03-21,2024-04-21,2215,9.5,Future Systems -AI08883,AI Specialist,58484,EUR,49711,EN,PT,France,L,France,0,"Docker, Python, Spark, Hadoop",Master,1,Automotive,2024-01-31,2024-04-01,1875,5.3,AI Innovations -AI08884,Data Analyst,53494,USD,53494,EN,FL,South Korea,S,South Korea,0,"MLOps, Docker, Linux, Computer Vision",Master,0,Telecommunications,2024-09-20,2024-11-04,1820,9.5,Smart Analytics -AI08885,AI Software Engineer,175512,USD,175512,SE,FL,Norway,L,Norway,0,"Linux, Computer Vision, PyTorch, Azure, TensorFlow",Associate,7,Automotive,2025-02-11,2025-03-26,2244,9.9,Cloud AI Solutions -AI08886,AI Product Manager,124719,USD,124719,MI,PT,Norway,M,Argentina,100,"Python, Kubernetes, PyTorch",Associate,2,Automotive,2025-01-27,2025-02-27,2326,6.6,Autonomous Tech -AI08887,Machine Learning Researcher,65569,USD,65569,EN,CT,Israel,S,Israel,0,"AWS, Tableau, Mathematics",Bachelor,0,Gaming,2025-02-14,2025-03-04,2433,6.3,AI Innovations -AI08888,AI Software Engineer,184461,USD,184461,EX,CT,Denmark,M,Israel,0,"Python, R, Data Visualization",Associate,13,Education,2024-06-25,2024-08-11,2438,5.9,Neural Networks Co -AI08889,AI Software Engineer,176661,CHF,158995,SE,FL,Switzerland,L,Finland,0,"PyTorch, Mathematics, AWS, Azure, Deep Learning",Associate,8,Media,2024-04-15,2024-05-08,1040,6.3,Algorithmic Solutions -AI08890,Research Scientist,113468,GBP,85101,MI,FT,United Kingdom,L,United Kingdom,50,"Python, Computer Vision, Statistics, Tableau",Associate,3,Transportation,2024-11-24,2025-01-22,1859,7.7,Cognitive Computing -AI08891,Robotics Engineer,94278,EUR,80136,MI,FL,France,M,Belgium,50,"Git, Kubernetes, Computer Vision, Python",PhD,3,Automotive,2024-07-25,2024-08-31,2395,8.6,Quantum Computing Inc -AI08892,AI Research Scientist,124121,EUR,105503,MI,FT,Netherlands,L,Netherlands,0,"Git, PyTorch, TensorFlow",PhD,3,Manufacturing,2025-01-15,2025-02-07,1523,5.8,Smart Analytics -AI08893,ML Ops Engineer,118336,EUR,100586,SE,FL,Netherlands,S,Netherlands,0,"Computer Vision, Git, Docker, Azure, TensorFlow",Bachelor,7,Manufacturing,2024-07-04,2024-08-11,1467,6.5,Algorithmic Solutions -AI08894,AI Consultant,63446,JPY,6979060,EN,CT,Japan,M,Japan,100,"PyTorch, Docker, GCP",Associate,1,Education,2024-08-14,2024-09-07,2327,8.5,Smart Analytics -AI08895,Data Analyst,88302,GBP,66227,MI,CT,United Kingdom,M,United Kingdom,100,"SQL, Git, Docker, Deep Learning",Master,4,Energy,2025-04-18,2025-05-12,1494,7.8,Smart Analytics -AI08896,Data Engineer,69937,CAD,87421,EN,CT,Canada,L,South Korea,0,"Tableau, Git, Java, NLP, Mathematics",PhD,1,Healthcare,2024-07-08,2024-09-03,1246,6.4,Cloud AI Solutions -AI08897,Data Scientist,76500,USD,76500,MI,PT,South Korea,S,South Korea,50,"Python, Kubernetes, Azure",Associate,3,Manufacturing,2025-03-21,2025-05-09,1141,5.4,TechCorp Inc -AI08898,Data Analyst,133991,USD,133991,MI,PT,Denmark,L,Spain,100,"Deep Learning, SQL, TensorFlow, Computer Vision",PhD,2,Automotive,2025-02-27,2025-04-30,1018,7.6,DeepTech Ventures -AI08899,Research Scientist,37472,USD,37472,EN,CT,China,M,China,0,"SQL, Mathematics, Docker, Python, Linux",Master,1,Media,2024-07-30,2024-08-23,597,7.8,Neural Networks Co -AI08900,NLP Engineer,55334,GBP,41501,EN,PT,United Kingdom,S,United Kingdom,50,"SQL, Docker, Hadoop, GCP, Azure",Master,0,Retail,2024-11-01,2024-12-28,1928,8.9,Digital Transformation LLC -AI08901,Data Engineer,118965,CHF,107069,MI,FT,Switzerland,M,Switzerland,0,"SQL, Scala, PyTorch, TensorFlow",Master,4,Finance,2024-11-08,2024-12-10,1082,5.3,TechCorp Inc -AI08902,ML Ops Engineer,59325,EUR,50426,EN,PT,France,M,France,0,"Data Visualization, Git, Computer Vision",Bachelor,0,Retail,2024-03-24,2024-04-26,2308,8.2,DataVision Ltd -AI08903,AI Research Scientist,79037,EUR,67181,MI,FT,Austria,M,United Kingdom,0,"Tableau, R, Deep Learning, Computer Vision, Azure",PhD,3,Healthcare,2025-03-29,2025-05-20,566,8.8,Digital Transformation LLC -AI08904,Computer Vision Engineer,149385,EUR,126977,EX,FT,Austria,L,Belgium,50,"Python, TensorFlow, Git, Spark",Bachelor,15,Real Estate,2024-06-18,2024-07-05,586,6.5,Neural Networks Co -AI08905,AI Product Manager,76318,EUR,64870,MI,CT,Austria,M,Austria,100,"Python, Computer Vision, Linux",PhD,2,Government,2024-03-15,2024-05-03,1441,6.9,DeepTech Ventures -AI08906,Research Scientist,189385,AUD,255670,EX,FT,Australia,M,Australia,50,"Hadoop, GCP, Tableau, Java, Azure",Master,18,Transportation,2024-04-17,2024-05-05,1029,6.1,Cognitive Computing -AI08907,Autonomous Systems Engineer,130219,EUR,110686,SE,CT,Germany,M,Germany,100,"Python, SQL, Java",PhD,9,Government,2024-09-01,2024-11-04,1562,5.4,Smart Analytics -AI08908,NLP Engineer,150596,JPY,16565560,EX,CT,Japan,S,Japan,0,"TensorFlow, Hadoop, SQL, Scala, Python",Associate,16,Education,2024-03-14,2024-05-07,1265,8.4,Digital Transformation LLC -AI08909,Head of AI,144363,USD,144363,EX,PT,Sweden,S,Kenya,0,"Mathematics, Deep Learning, R, SQL, Linux",Master,14,Media,2024-05-19,2024-06-29,1823,7.6,Digital Transformation LLC -AI08910,AI Software Engineer,21072,USD,21072,EN,FT,India,L,India,100,"Kubernetes, GCP, NLP, MLOps",Bachelor,1,Technology,2024-12-15,2025-01-26,905,6.9,Future Systems -AI08911,ML Ops Engineer,186827,USD,186827,EX,FT,Israel,S,Israel,0,"Java, TensorFlow, NLP, Mathematics, PyTorch",Associate,14,Retail,2024-05-12,2024-06-03,1583,6.1,Machine Intelligence Group -AI08912,Principal Data Scientist,143167,USD,143167,SE,PT,South Korea,L,South Korea,100,"PyTorch, Python, NLP",Associate,9,Education,2025-01-19,2025-02-13,1955,8.8,Quantum Computing Inc -AI08913,ML Ops Engineer,128988,USD,128988,SE,CT,Israel,M,Estonia,100,"PyTorch, Data Visualization, Linux, MLOps",PhD,6,Government,2024-09-08,2024-11-01,960,6.1,Quantum Computing Inc -AI08914,Deep Learning Engineer,276188,EUR,234760,EX,FL,Germany,L,Germany,50,"GCP, Git, Data Visualization",Associate,13,Finance,2024-08-23,2024-10-28,1647,8.1,Digital Transformation LLC -AI08915,Autonomous Systems Engineer,41148,USD,41148,MI,PT,India,L,Portugal,100,"SQL, Hadoop, PyTorch, Docker, Git",Master,2,Consulting,2024-10-21,2024-12-28,2149,9.3,TechCorp Inc -AI08916,AI Consultant,79365,USD,79365,EX,FT,India,M,Czech Republic,0,"Data Visualization, Git, R",Master,10,Media,2025-03-02,2025-05-09,2308,5.8,TechCorp Inc -AI08917,Data Scientist,60786,USD,60786,EX,FL,India,M,India,100,"TensorFlow, PyTorch, Linux, Statistics",PhD,17,Manufacturing,2024-06-09,2024-07-14,1544,9.1,Cloud AI Solutions -AI08918,ML Ops Engineer,85296,USD,85296,MI,CT,Finland,S,India,100,"Deep Learning, Data Visualization, Python, Hadoop",PhD,3,Finance,2024-11-10,2024-12-17,2034,7.6,Future Systems -AI08919,Computer Vision Engineer,111246,SGD,144620,MI,FT,Singapore,L,Singapore,50,"Docker, Java, Data Visualization, Azure",Master,2,Consulting,2024-12-09,2025-01-03,1316,9.1,Cognitive Computing -AI08920,Robotics Engineer,89925,USD,89925,MI,PT,Ireland,L,Ireland,100,"Tableau, MLOps, Kubernetes, Hadoop, Computer Vision",PhD,2,Gaming,2024-12-27,2025-01-10,2334,6.3,AI Innovations -AI08921,Computer Vision Engineer,90696,USD,90696,MI,PT,United States,M,Israel,100,"Deep Learning, Statistics, Git, Kubernetes, NLP",Associate,2,Media,2024-08-23,2024-09-27,2447,6.3,Smart Analytics -AI08922,Robotics Engineer,131512,AUD,177541,SE,PT,Australia,S,Australia,0,"PyTorch, Scala, Spark, Deep Learning, Azure",Associate,8,Technology,2024-07-25,2024-09-13,1710,9.6,Cloud AI Solutions -AI08923,AI Product Manager,198409,AUD,267852,EX,CT,Australia,S,Australia,50,"PyTorch, GCP, MLOps, Spark",PhD,15,Healthcare,2025-04-26,2025-06-15,710,9.5,Autonomous Tech -AI08924,Data Analyst,157473,USD,157473,SE,FT,Sweden,L,Sweden,0,"Deep Learning, Tableau, R, NLP",Master,6,Finance,2024-10-24,2024-12-04,1694,7.5,Algorithmic Solutions -AI08925,NLP Engineer,126003,EUR,107103,SE,FL,France,M,France,0,"Java, Statistics, Spark, Computer Vision, TensorFlow",Bachelor,7,Energy,2024-08-04,2024-09-21,703,5.6,DeepTech Ventures -AI08926,AI Research Scientist,119850,USD,119850,SE,FT,South Korea,M,South Korea,0,"MLOps, Linux, Scala",Associate,5,Education,2024-03-29,2024-05-03,2346,9.8,DataVision Ltd -AI08927,AI Specialist,95591,CHF,86032,EN,FL,Switzerland,M,Ireland,100,"TensorFlow, PyTorch, Docker",Bachelor,1,Healthcare,2024-05-18,2024-06-03,618,8.3,TechCorp Inc -AI08928,Data Scientist,73865,GBP,55399,EN,PT,United Kingdom,M,United Kingdom,100,"Java, R, Kubernetes, Git",PhD,0,Transportation,2024-06-13,2024-07-26,2249,5.5,DeepTech Ventures -AI08929,Principal Data Scientist,71155,GBP,53366,EN,CT,United Kingdom,S,United Kingdom,0,"Java, PyTorch, NLP",PhD,0,Education,2025-01-05,2025-01-21,2184,8.6,DeepTech Ventures -AI08930,Robotics Engineer,69945,SGD,90929,MI,FL,Singapore,S,Singapore,50,"Scala, Kubernetes, Docker, Java",Associate,2,Real Estate,2024-08-15,2024-10-07,1353,9.3,Cognitive Computing -AI08931,Computer Vision Engineer,24897,USD,24897,EN,CT,China,M,China,100,"GCP, Azure, AWS",Master,0,Manufacturing,2025-04-01,2025-05-01,1147,5.1,DataVision Ltd -AI08932,Research Scientist,67162,AUD,90669,EN,FL,Australia,L,Australia,100,"Scala, Statistics, Java",Associate,0,Government,2024-08-29,2024-10-24,1973,9.2,Cloud AI Solutions -AI08933,Principal Data Scientist,57928,GBP,43446,EN,PT,United Kingdom,S,United Kingdom,50,"Java, Git, Python",PhD,1,Manufacturing,2024-02-27,2024-04-21,526,7.1,Machine Intelligence Group -AI08934,Autonomous Systems Engineer,153211,CHF,137890,MI,PT,Switzerland,M,Switzerland,50,"TensorFlow, Linux, Mathematics, Kubernetes",Bachelor,4,Transportation,2024-04-30,2024-06-21,891,8.8,Future Systems -AI08935,AI Software Engineer,111274,USD,111274,MI,CT,Denmark,S,Denmark,100,"AWS, Hadoop, Scala",Associate,2,Automotive,2024-09-20,2024-11-19,2435,8.2,Smart Analytics -AI08936,AI Specialist,119212,USD,119212,SE,CT,Israel,M,Kenya,50,"Kubernetes, Azure, Scala, SQL",Associate,5,Telecommunications,2025-03-24,2025-05-03,952,5.4,Neural Networks Co -AI08937,AI Software Engineer,167862,USD,167862,EX,FL,Israel,S,Israel,50,"Mathematics, Spark, NLP, R, Python",Bachelor,15,Automotive,2024-05-17,2024-06-03,622,9.8,Neural Networks Co -AI08938,AI Research Scientist,73151,EUR,62178,MI,PT,Germany,M,Finland,100,"Deep Learning, SQL, PyTorch, AWS",Master,4,Retail,2024-10-06,2024-10-26,1228,9.5,Cloud AI Solutions -AI08939,Research Scientist,159226,CHF,143303,MI,FT,Switzerland,L,China,0,"Linux, MLOps, Data Visualization",Master,4,Gaming,2024-05-26,2024-07-29,794,8.2,Future Systems -AI08940,AI Software Engineer,62380,USD,62380,EN,PT,Ireland,M,Romania,0,"Scala, Kubernetes, SQL, MLOps, Spark",PhD,1,Healthcare,2025-03-02,2025-03-28,1960,6.9,AI Innovations -AI08941,AI Product Manager,113996,JPY,12539560,SE,FL,Japan,M,Japan,50,"AWS, Linux, Java, Hadoop",Master,9,Consulting,2025-01-10,2025-03-06,2463,8.9,DeepTech Ventures -AI08942,NLP Engineer,51094,USD,51094,EN,CT,Ireland,M,Ireland,0,"NLP, MLOps, Statistics",Bachelor,1,Gaming,2025-04-21,2025-05-29,2239,9,TechCorp Inc -AI08943,AI Specialist,69394,USD,69394,EN,FT,Israel,L,Israel,100,"Kubernetes, Python, MLOps, Azure",PhD,1,Automotive,2025-01-08,2025-02-09,571,5.3,Future Systems -AI08944,AI Specialist,105999,CHF,95399,EN,PT,Switzerland,L,Ghana,50,"R, GCP, Hadoop, Kubernetes",Master,0,Consulting,2024-12-04,2025-02-09,1844,8,DeepTech Ventures -AI08945,ML Ops Engineer,99978,EUR,84981,SE,CT,Austria,M,Italy,0,"Kubernetes, NLP, Git, Mathematics, Hadoop",Associate,8,Energy,2025-04-29,2025-05-26,2222,8.3,DeepTech Ventures -AI08946,Data Scientist,52184,USD,52184,EN,FL,South Korea,L,South Korea,50,"SQL, Hadoop, GCP",Bachelor,0,Retail,2024-05-22,2024-06-15,1923,8.4,Digital Transformation LLC -AI08947,Data Scientist,76210,EUR,64779,MI,FL,Germany,M,Germany,50,"Java, Kubernetes, Data Visualization, NLP",PhD,2,Transportation,2024-02-02,2024-03-29,977,5.7,Predictive Systems -AI08948,AI Product Manager,67505,USD,67505,MI,FT,Israel,S,Israel,0,"PyTorch, TensorFlow, Data Visualization, Kubernetes, AWS",Bachelor,4,Consulting,2024-11-02,2024-12-17,1324,9.8,Digital Transformation LLC -AI08949,Robotics Engineer,70420,USD,70420,MI,PT,Israel,S,India,100,"Python, Scala, MLOps, AWS, NLP",PhD,4,Manufacturing,2025-01-22,2025-03-06,1191,8,Machine Intelligence Group -AI08950,AI Consultant,23683,USD,23683,EN,CT,India,L,India,50,"R, Kubernetes, Git",Master,0,Education,2024-08-04,2024-10-12,1085,8.9,Quantum Computing Inc -AI08951,Computer Vision Engineer,120220,USD,120220,MI,PT,United States,M,United States,0,"Python, Scala, Computer Vision, SQL",PhD,3,Telecommunications,2024-09-26,2024-12-01,785,5.1,Advanced Robotics -AI08952,AI Software Engineer,185311,USD,185311,EX,PT,Finland,M,Finland,50,"Hadoop, GCP, NLP, AWS, Tableau",PhD,15,Gaming,2024-09-07,2024-10-11,1773,8.5,Smart Analytics -AI08953,Robotics Engineer,140225,EUR,119191,SE,CT,Netherlands,S,Netherlands,0,"SQL, Kubernetes, Mathematics, Linux, Deep Learning",Associate,6,Real Estate,2024-04-23,2024-06-01,755,8,TechCorp Inc -AI08954,AI Specialist,126983,USD,126983,SE,FL,Israel,L,Israel,0,"Kubernetes, SQL, PyTorch, Git",PhD,9,Telecommunications,2024-12-09,2025-02-12,2196,5.3,AI Innovations -AI08955,Head of AI,198792,USD,198792,EX,FL,Finland,L,Thailand,50,"Git, PyTorch, R",Associate,11,Manufacturing,2024-05-09,2024-07-02,1864,8.1,Autonomous Tech -AI08956,AI Consultant,84341,EUR,71690,MI,FL,Austria,L,Austria,50,"Spark, Hadoop, Azure, Tableau",Bachelor,3,Finance,2024-09-29,2024-12-05,1673,6.8,Advanced Robotics -AI08957,Principal Data Scientist,59341,EUR,50440,EN,FT,Netherlands,M,Netherlands,50,"MLOps, Java, R",Associate,1,Healthcare,2024-04-22,2024-06-02,2363,7.2,Digital Transformation LLC -AI08958,Machine Learning Engineer,26028,USD,26028,MI,FT,India,M,India,0,"R, MLOps, SQL",Bachelor,3,Finance,2024-01-06,2024-02-17,991,6.9,TechCorp Inc -AI08959,AI Architect,146559,JPY,16121490,SE,PT,Japan,L,Denmark,100,"Azure, Hadoop, Python",Bachelor,9,Real Estate,2025-04-18,2025-05-11,550,9.9,Future Systems -AI08960,NLP Engineer,258425,USD,258425,EX,FT,Denmark,M,Mexico,100,"SQL, Deep Learning, AWS, Kubernetes, Mathematics",Master,12,Education,2024-07-28,2024-08-17,964,8.4,Neural Networks Co -AI08961,AI Research Scientist,158120,EUR,134402,SE,FT,Netherlands,L,South Korea,50,"Data Visualization, PyTorch, Kubernetes, Statistics",PhD,7,Real Estate,2024-09-22,2024-11-04,953,7.7,Algorithmic Solutions -AI08962,AI Specialist,77719,USD,77719,EN,CT,United States,M,United States,0,"Azure, Spark, Tableau, NLP",Master,0,Media,2024-07-29,2024-08-27,2030,6.2,Cognitive Computing -AI08963,AI Specialist,28039,USD,28039,EN,PT,China,S,China,0,"AWS, Tableau, Computer Vision, Hadoop, NLP",Master,0,Automotive,2024-08-24,2024-10-09,636,8.7,TechCorp Inc -AI08964,Robotics Engineer,96472,SGD,125414,MI,FT,Singapore,M,Ireland,50,"Python, SQL, GCP",Master,2,Government,2024-06-12,2024-07-20,724,8,Cloud AI Solutions -AI08965,Principal Data Scientist,89844,USD,89844,SE,PT,South Korea,M,Singapore,0,"Computer Vision, Hadoop, AWS, Scala, Spark",Bachelor,5,Finance,2024-02-05,2024-04-16,1977,7.1,Quantum Computing Inc -AI08966,AI Research Scientist,79472,SGD,103314,EN,PT,Singapore,L,Nigeria,0,"Scala, Kubernetes, MLOps, NLP, Mathematics",Bachelor,0,Gaming,2025-02-12,2025-02-28,1571,7,Predictive Systems -AI08967,AI Product Manager,92695,USD,92695,MI,PT,South Korea,L,South Korea,100,"Python, Docker, GCP, TensorFlow",Master,3,Government,2025-04-29,2025-06-19,802,5.6,Quantum Computing Inc -AI08968,NLP Engineer,105477,JPY,11602470,MI,PT,Japan,M,South Africa,0,"Spark, Deep Learning, Mathematics",PhD,2,Finance,2025-03-28,2025-04-16,1334,5.1,Algorithmic Solutions -AI08969,AI Consultant,59744,USD,59744,EN,FT,Finland,S,Finland,100,"Mathematics, Data Visualization, PyTorch, MLOps",Master,0,Consulting,2025-01-11,2025-03-23,1224,6.8,Neural Networks Co -AI08970,NLP Engineer,75054,JPY,8255940,EN,PT,Japan,M,Israel,0,"Data Visualization, Git, R, Scala",Master,0,Technology,2024-01-07,2024-01-26,1701,6.7,Smart Analytics -AI08971,AI Product Manager,75503,USD,75503,MI,FT,South Korea,M,South Korea,100,"Scala, Java, Data Visualization, Git",Associate,4,Education,2024-10-01,2024-10-25,1856,5.5,Cognitive Computing -AI08972,AI Specialist,86929,USD,86929,MI,FT,Israel,L,Israel,100,"R, Deep Learning, Spark",PhD,4,Technology,2024-03-16,2024-04-11,918,8.8,Predictive Systems -AI08973,Data Scientist,80667,EUR,68567,MI,FL,France,L,France,0,"TensorFlow, AWS, Statistics, Mathematics, Spark",Bachelor,4,Real Estate,2024-09-17,2024-10-20,1916,5.3,Predictive Systems -AI08974,Robotics Engineer,142450,USD,142450,EX,FT,South Korea,S,South Korea,50,"R, Scala, Python",Master,11,Education,2025-01-19,2025-03-27,2181,9,DataVision Ltd -AI08975,AI Software Engineer,145577,USD,145577,EX,FL,Ireland,S,Ireland,50,"Scala, Tableau, Spark, Statistics",Bachelor,11,Telecommunications,2024-07-19,2024-08-19,1784,7.6,Machine Intelligence Group -AI08976,Principal Data Scientist,138782,CHF,124904,MI,FT,Switzerland,L,Switzerland,100,"PyTorch, Git, GCP",Associate,2,Government,2024-04-10,2024-06-14,1512,5.7,Digital Transformation LLC -AI08977,Data Scientist,148776,AUD,200848,SE,FL,Australia,M,Australia,100,"R, Tableau, Python, Statistics",PhD,8,Gaming,2025-01-15,2025-03-21,1573,9.5,DeepTech Ventures -AI08978,Data Engineer,150654,USD,150654,MI,PT,Norway,L,Thailand,100,"AWS, Computer Vision, Data Visualization, R",Bachelor,4,Consulting,2024-02-29,2024-03-27,760,7.4,Advanced Robotics -AI08979,AI Consultant,262984,USD,262984,EX,CT,Ireland,L,Ireland,0,"Linux, Java, Spark, Scala, Computer Vision",Bachelor,11,Transportation,2024-12-06,2025-01-22,2032,5.7,Neural Networks Co -AI08980,AI Specialist,82698,GBP,62024,MI,CT,United Kingdom,S,United Kingdom,50,"Docker, Data Visualization, Spark",Master,2,Consulting,2025-03-22,2025-05-04,1128,5.7,Neural Networks Co -AI08981,Robotics Engineer,78355,GBP,58766,MI,FT,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, Statistics, Computer Vision",Master,3,Automotive,2024-02-22,2024-04-23,1032,7,Machine Intelligence Group -AI08982,AI Product Manager,83880,EUR,71298,MI,FL,France,L,France,100,"Hadoop, PyTorch, Tableau, TensorFlow, NLP",PhD,2,Technology,2024-08-08,2024-09-19,1316,9.3,Cloud AI Solutions -AI08983,Data Analyst,67262,GBP,50447,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Scala, R",Master,0,Automotive,2024-06-07,2024-07-05,1330,7.3,Predictive Systems -AI08984,Computer Vision Engineer,65253,USD,65253,SE,FT,China,M,China,0,"NLP, TensorFlow, Spark",Bachelor,5,Consulting,2025-03-22,2025-05-21,882,7.4,AI Innovations -AI08985,ML Ops Engineer,100727,USD,100727,SE,PT,Israel,S,Israel,0,"Tableau, TensorFlow, GCP, Statistics",Master,5,Automotive,2024-01-23,2024-02-23,2081,6,Cloud AI Solutions -AI08986,Principal Data Scientist,201256,CAD,251570,EX,CT,Canada,S,Italy,0,"Azure, Python, Computer Vision",Master,17,Media,2025-03-15,2025-05-14,999,6.2,DataVision Ltd -AI08987,Deep Learning Engineer,98333,CHF,88500,EN,CT,Switzerland,S,Poland,100,"GCP, R, SQL, Statistics, Data Visualization",Bachelor,1,Healthcare,2024-10-04,2024-10-27,1743,6.8,Cognitive Computing -AI08988,AI Product Manager,238048,GBP,178536,EX,CT,United Kingdom,S,Switzerland,100,"Scala, R, Computer Vision, Kubernetes",PhD,19,Automotive,2024-11-09,2024-12-01,696,8,Algorithmic Solutions -AI08989,Computer Vision Engineer,111723,USD,111723,SE,PT,South Korea,S,Ukraine,0,"R, Statistics, Computer Vision, GCP",PhD,6,Transportation,2024-06-15,2024-08-23,909,9.7,Autonomous Tech -AI08990,ML Ops Engineer,62271,EUR,52930,EN,FL,Germany,S,Germany,50,"Linux, R, Git, Hadoop, Docker",Associate,0,Manufacturing,2024-08-25,2024-11-02,1742,7.1,TechCorp Inc -AI08991,Machine Learning Researcher,186844,CAD,233555,EX,FL,Canada,L,Canada,100,"Kubernetes, Statistics, Mathematics, Linux, Java",Associate,18,Retail,2024-08-26,2024-10-11,1541,9.1,Machine Intelligence Group -AI08992,AI Software Engineer,151803,USD,151803,SE,FL,United States,S,United States,0,"Computer Vision, Data Visualization, R, NLP, Deep Learning",Master,9,Manufacturing,2024-07-07,2024-07-25,2344,8,Neural Networks Co -AI08993,AI Product Manager,86780,USD,86780,MI,FL,Norway,S,Estonia,50,"Kubernetes, NLP, SQL",Associate,3,Telecommunications,2024-05-26,2024-06-22,2178,9,Quantum Computing Inc -AI08994,Deep Learning Engineer,92335,USD,92335,EN,FT,Ireland,L,Ireland,100,"AWS, Kubernetes, SQL, Scala",Bachelor,0,Retail,2024-09-08,2024-10-31,1318,8,Algorithmic Solutions -AI08995,Data Analyst,79908,USD,79908,MI,CT,South Korea,L,South Korea,100,"Hadoop, GCP, Computer Vision, Mathematics",Master,4,Technology,2024-06-21,2024-07-17,597,5.5,Autonomous Tech -AI08996,AI Consultant,139660,USD,139660,MI,CT,Denmark,L,Denmark,100,"Deep Learning, Python, MLOps",Master,4,Government,2025-02-01,2025-04-13,2451,6.1,Cognitive Computing -AI08997,Head of AI,55908,CAD,69885,EN,FL,Canada,S,Canada,50,"Linux, SQL, MLOps, Mathematics, Spark",PhD,0,Technology,2025-01-31,2025-03-22,1148,6.3,Cognitive Computing -AI08998,Data Engineer,88659,EUR,75360,MI,CT,Austria,L,Austria,100,"AWS, R, NLP, Data Visualization, Tableau",Bachelor,4,Telecommunications,2024-03-05,2024-04-16,2403,7.5,Neural Networks Co -AI08999,Machine Learning Engineer,205613,USD,205613,SE,PT,Norway,L,Australia,100,"Deep Learning, TensorFlow, R",Bachelor,8,Real Estate,2024-10-01,2024-11-06,1407,5.6,Digital Transformation LLC -AI09000,AI Software Engineer,90371,EUR,76815,EN,FT,Germany,L,Germany,100,"Kubernetes, Java, Mathematics, Scala, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-12-06,1818,7.1,DeepTech Ventures -AI09001,Data Analyst,88134,USD,88134,EN,FT,Sweden,L,Sweden,100,"Hadoop, Git, Computer Vision",Associate,0,Automotive,2025-02-11,2025-03-15,587,7.3,Autonomous Tech -AI09002,Computer Vision Engineer,42049,USD,42049,EN,FT,South Korea,M,South Korea,50,"TensorFlow, Statistics, SQL, Git",Associate,1,Government,2024-08-30,2024-11-05,2280,9.8,Cognitive Computing -AI09003,AI Consultant,53035,USD,53035,SE,PT,India,M,India,50,"SQL, Computer Vision, Tableau",PhD,8,Media,2024-03-28,2024-06-01,2121,9.3,Advanced Robotics -AI09004,Autonomous Systems Engineer,24765,USD,24765,EN,FL,India,S,India,100,"Docker, Python, Mathematics, Kubernetes",PhD,1,Energy,2024-12-11,2024-12-28,1299,10,Quantum Computing Inc -AI09005,Data Analyst,162474,USD,162474,SE,FT,Denmark,S,Colombia,100,"Computer Vision, R, Scala",Master,5,Transportation,2024-04-30,2024-06-30,1769,6.3,Predictive Systems -AI09006,Computer Vision Engineer,156947,USD,156947,EX,FT,Finland,M,Finland,100,"Mathematics, AWS, Deep Learning, Computer Vision",PhD,15,Transportation,2024-07-29,2024-10-05,820,7.6,Neural Networks Co -AI09007,Deep Learning Engineer,174776,USD,174776,EX,CT,Ireland,M,Ireland,50,"Computer Vision, GCP, Scala, Linux, PyTorch",Master,13,Real Estate,2024-08-16,2024-09-27,652,6.6,Future Systems -AI09008,AI Architect,70304,USD,70304,MI,FT,South Korea,L,South Korea,0,"Java, AWS, Tableau",Associate,3,Technology,2024-09-26,2024-11-04,610,9.5,Quantum Computing Inc -AI09009,ML Ops Engineer,172841,USD,172841,EX,PT,Israel,S,Israel,100,"Spark, PyTorch, Git",Master,16,Government,2024-06-24,2024-08-07,2356,8.7,Autonomous Tech -AI09010,AI Software Engineer,130736,EUR,111126,SE,FL,Austria,L,Austria,100,"Spark, R, Hadoop, Statistics, SQL",Master,6,Education,2024-04-28,2024-06-21,1538,9.1,Machine Intelligence Group -AI09011,AI Research Scientist,250854,EUR,213226,EX,PT,Austria,L,Austria,0,"Deep Learning, Kubernetes, Python, Git",PhD,17,Manufacturing,2025-03-10,2025-04-15,2094,6.8,TechCorp Inc -AI09012,AI Consultant,143001,SGD,185901,SE,PT,Singapore,L,Singapore,100,"MLOps, Java, Python, Computer Vision, Docker",Master,7,Healthcare,2024-02-08,2024-03-15,935,6.8,Future Systems -AI09013,AI Product Manager,248777,USD,248777,EX,FL,Sweden,M,Sweden,100,"Tableau, PyTorch, Docker, GCP, TensorFlow",Associate,11,Finance,2024-03-09,2024-04-05,1927,9.3,Future Systems -AI09014,AI Software Engineer,287219,SGD,373385,EX,FL,Singapore,L,Netherlands,50,"AWS, Scala, Mathematics, GCP, Docker",Bachelor,11,Transportation,2024-03-18,2024-05-26,1759,5.1,Autonomous Tech -AI09015,NLP Engineer,116645,USD,116645,MI,CT,Norway,S,Norway,100,"NLP, SQL, Tableau, AWS",Associate,2,Telecommunications,2024-09-28,2024-11-28,1035,10,Future Systems -AI09016,AI Product Manager,52061,USD,52061,EN,FL,South Korea,L,South Korea,100,"Computer Vision, SQL, Kubernetes, Git",PhD,0,Gaming,2024-05-10,2024-07-21,1489,7.8,Cloud AI Solutions -AI09017,AI Architect,104358,EUR,88704,SE,PT,France,S,Philippines,100,"Linux, R, Spark",Associate,5,Media,2024-12-07,2025-02-14,2437,6.8,DeepTech Ventures -AI09018,Machine Learning Engineer,64123,USD,64123,SE,PT,China,S,United States,50,"Computer Vision, Spark, Tableau",Master,7,Real Estate,2024-06-28,2024-08-14,715,7.3,Advanced Robotics -AI09019,AI Specialist,149941,USD,149941,SE,FT,Sweden,L,Ukraine,100,"Hadoop, SQL, TensorFlow, Spark",PhD,6,Gaming,2024-11-13,2024-12-14,1278,5.6,TechCorp Inc -AI09020,Deep Learning Engineer,56400,CAD,70500,EN,FL,Canada,M,Canada,50,"Tableau, NLP, PyTorch, Kubernetes",PhD,0,Technology,2024-01-08,2024-03-12,1632,8.3,DataVision Ltd -AI09021,AI Research Scientist,95750,USD,95750,SE,CT,Ireland,S,Thailand,0,"Docker, Python, Kubernetes, MLOps, Mathematics",Bachelor,6,Real Estate,2024-12-21,2025-01-08,2016,9.2,Predictive Systems -AI09022,AI Research Scientist,64039,EUR,54433,EN,FL,Germany,M,Germany,100,"SQL, Deep Learning, Git, PyTorch",PhD,0,Government,2025-03-24,2025-05-01,778,7.7,Cognitive Computing -AI09023,Data Engineer,56110,EUR,47694,EN,FL,Germany,M,Ireland,50,"Azure, Tableau, TensorFlow, Data Visualization, Deep Learning",PhD,1,Telecommunications,2024-12-23,2025-02-01,1111,7,Future Systems -AI09024,AI Specialist,124462,USD,124462,MI,PT,Denmark,S,Denmark,50,"NLP, AWS, Computer Vision, Python",Associate,4,Energy,2025-03-29,2025-05-26,1940,7.4,Neural Networks Co -AI09025,AI Consultant,190189,EUR,161661,EX,PT,Austria,M,Brazil,50,"Scala, Hadoop, Java, Linux",Master,11,Government,2024-02-21,2024-03-29,1380,9.4,Neural Networks Co -AI09026,AI Research Scientist,110339,USD,110339,SE,FL,United States,S,United States,100,"Kubernetes, PyTorch, TensorFlow, Python",Associate,9,Retail,2024-08-29,2024-10-12,1207,6.2,Quantum Computing Inc -AI09027,Data Engineer,198685,USD,198685,EX,CT,Israel,M,Israel,0,"MLOps, TensorFlow, Kubernetes",PhD,18,Retail,2024-09-11,2024-10-07,2290,8.6,Algorithmic Solutions -AI09028,Robotics Engineer,118424,USD,118424,MI,CT,United States,M,Egypt,100,"Statistics, NLP, Deep Learning",Master,4,Healthcare,2024-04-11,2024-05-28,1308,9.3,TechCorp Inc -AI09029,Research Scientist,77664,CHF,69898,EN,PT,Switzerland,M,Canada,50,"Azure, Spark, Python, MLOps, Computer Vision",Associate,0,Consulting,2024-09-09,2024-11-21,2200,5.3,Future Systems -AI09030,Research Scientist,60040,USD,60040,EN,FL,Israel,M,Israel,0,"Docker, Python, Azure, Hadoop, Deep Learning",Master,1,Education,2024-12-03,2025-01-08,1776,6.9,Machine Intelligence Group -AI09031,NLP Engineer,79791,USD,79791,EN,FL,Denmark,L,Denmark,100,"TensorFlow, Java, Scala, Statistics",Associate,0,Retail,2024-11-20,2024-12-10,1808,9.2,DeepTech Ventures -AI09032,AI Product Manager,124008,USD,124008,MI,FT,Denmark,L,Denmark,50,"GCP, Java, TensorFlow, Deep Learning, Computer Vision",Associate,2,Gaming,2024-02-13,2024-04-16,741,7.2,Cognitive Computing -AI09033,AI Consultant,35031,USD,35031,MI,FT,India,S,India,50,"Java, Mathematics, Deep Learning, Data Visualization, TensorFlow",Associate,4,Energy,2024-12-23,2025-02-18,699,7.6,AI Innovations -AI09034,Head of AI,67240,USD,67240,EN,FL,Norway,S,Norway,0,"AWS, Scala, Data Visualization",Bachelor,0,Education,2024-06-23,2024-08-27,1817,9.8,Quantum Computing Inc -AI09035,AI Specialist,94732,USD,94732,SE,PT,South Korea,M,South Korea,100,"Statistics, R, Deep Learning",PhD,8,Energy,2024-05-05,2024-05-21,1209,9.9,Advanced Robotics -AI09036,Autonomous Systems Engineer,129130,CHF,116217,MI,FT,Switzerland,L,Belgium,0,"Kubernetes, Java, AWS, Azure",Associate,3,Energy,2025-03-16,2025-05-07,1250,5.6,DataVision Ltd -AI09037,Data Analyst,228742,EUR,194431,EX,CT,Austria,L,Chile,50,"PyTorch, SQL, Java",PhD,19,Transportation,2025-04-19,2025-05-31,1839,5.5,DataVision Ltd -AI09038,Machine Learning Engineer,96859,SGD,125917,MI,FL,Singapore,M,Singapore,100,"Kubernetes, SQL, Deep Learning, Hadoop, PyTorch",Master,4,Education,2024-08-17,2024-10-14,2037,9,Machine Intelligence Group -AI09039,AI Software Engineer,86548,JPY,9520280,EN,FL,Japan,L,Japan,0,"TensorFlow, Spark, NLP, PyTorch, Data Visualization",Associate,1,Education,2024-04-29,2024-05-30,2115,5.4,DataVision Ltd -AI09040,Deep Learning Engineer,145427,EUR,123613,SE,CT,France,L,France,0,"Git, Spark, Computer Vision",Associate,9,Telecommunications,2024-01-10,2024-01-30,1730,7.9,AI Innovations -AI09041,Head of AI,144726,USD,144726,SE,FL,South Korea,L,South Korea,0,"Computer Vision, AWS, Docker, PyTorch, Hadoop",Associate,7,Healthcare,2024-04-17,2024-06-28,2490,6.8,Neural Networks Co -AI09042,Data Scientist,118275,USD,118275,MI,FL,Finland,L,France,100,"R, Linux, Computer Vision",Master,2,Real Estate,2024-09-11,2024-11-04,556,7.7,Algorithmic Solutions -AI09043,Head of AI,90563,CHF,81507,EN,FL,Switzerland,L,Switzerland,100,"Git, Linux, AWS, Statistics, Hadoop",Bachelor,0,Healthcare,2024-09-14,2024-11-16,1631,7.9,Quantum Computing Inc -AI09044,Head of AI,107754,USD,107754,SE,PT,South Korea,S,South Korea,100,"Python, Scala, Linux",Master,9,Energy,2024-08-20,2024-09-20,1052,8.4,Cognitive Computing -AI09045,AI Research Scientist,63613,USD,63613,EN,FT,Sweden,S,Sweden,50,"Linux, PyTorch, TensorFlow",Bachelor,1,Finance,2024-04-23,2024-06-13,2070,5.3,Neural Networks Co -AI09046,Research Scientist,185435,USD,185435,EX,CT,Ireland,M,Canada,0,"Spark, Docker, Python",Bachelor,15,Technology,2024-09-11,2024-10-08,1991,8.2,Advanced Robotics -AI09047,Autonomous Systems Engineer,46410,USD,46410,SE,PT,India,M,India,0,"Scala, Spark, Git, Azure",Associate,9,Energy,2024-08-19,2024-09-09,1622,6.3,Smart Analytics -AI09048,ML Ops Engineer,143416,USD,143416,EX,PT,Sweden,S,Sweden,100,"MLOps, R, Computer Vision",PhD,18,Real Estate,2024-11-09,2024-12-08,2151,5.3,Digital Transformation LLC -AI09049,AI Consultant,76825,USD,76825,EN,CT,Norway,S,Norway,100,"Computer Vision, R, SQL, Linux, Docker",Associate,0,Real Estate,2024-04-05,2024-06-02,1986,5.8,Digital Transformation LLC -AI09050,NLP Engineer,198466,CHF,178619,SE,FL,Switzerland,M,Switzerland,0,"SQL, Tableau, Computer Vision, MLOps",Bachelor,7,Government,2024-04-26,2024-07-05,716,9.7,Future Systems -AI09051,Data Analyst,130066,CHF,117059,MI,CT,Switzerland,S,Switzerland,50,"Mathematics, Hadoop, Python",Master,2,Education,2024-06-02,2024-07-05,916,7.7,Advanced Robotics -AI09052,AI Specialist,112733,EUR,95823,MI,FL,Germany,L,Germany,50,"AWS, Git, PyTorch",PhD,4,Government,2024-03-13,2024-05-14,2111,6.3,Quantum Computing Inc -AI09053,Data Scientist,46914,USD,46914,EN,PT,Finland,S,United States,100,"Python, Linux, Spark, Deep Learning",Master,1,Finance,2024-02-26,2024-03-27,2063,5.8,Smart Analytics -AI09054,AI Specialist,275297,USD,275297,EX,FL,Israel,L,Vietnam,50,"Tableau, Python, Kubernetes, Computer Vision",Associate,19,Transportation,2025-01-22,2025-04-03,2364,7.2,Cloud AI Solutions -AI09055,AI Product Manager,161001,GBP,120751,EX,PT,United Kingdom,S,United Kingdom,50,"Deep Learning, Azure, Kubernetes, Java, SQL",Bachelor,10,Technology,2024-03-16,2024-04-11,1985,9.6,Algorithmic Solutions -AI09056,Data Analyst,73717,SGD,95832,EN,PT,Singapore,M,Ukraine,0,"Python, Hadoop, Data Visualization",Master,0,Government,2025-03-05,2025-03-22,2321,8.3,Cognitive Computing -AI09057,Data Engineer,173430,AUD,234131,EX,FL,Australia,S,Indonesia,100,"Azure, Spark, Computer Vision",Associate,16,Media,2024-11-01,2024-12-24,1601,6.3,TechCorp Inc -AI09058,Data Analyst,289418,USD,289418,EX,FT,Sweden,L,Sweden,50,"Hadoop, Spark, TensorFlow, Linux",Associate,10,Healthcare,2024-07-13,2024-08-25,1193,5.4,AI Innovations -AI09059,Autonomous Systems Engineer,25689,USD,25689,MI,FL,India,M,India,0,"Scala, GCP, Tableau, Kubernetes, Java",Associate,4,Automotive,2024-05-19,2024-06-18,1208,9.6,TechCorp Inc -AI09060,Data Engineer,60503,USD,60503,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, Computer Vision, R, SQL",PhD,1,Transportation,2024-02-25,2024-03-17,2322,9.1,DataVision Ltd -AI09061,AI Architect,278853,USD,278853,EX,PT,Sweden,L,Sweden,50,"Python, Tableau, SQL",Associate,16,Manufacturing,2025-03-05,2025-05-04,1316,9.2,Machine Intelligence Group -AI09062,NLP Engineer,84797,EUR,72077,MI,CT,France,L,France,50,"TensorFlow, Python, Hadoop, Kubernetes",Bachelor,4,Real Estate,2025-04-08,2025-05-29,1787,5.1,TechCorp Inc -AI09063,Data Engineer,112505,EUR,95629,SE,FT,France,S,France,50,"Data Visualization, Scala, AWS, TensorFlow, Kubernetes",Associate,5,Healthcare,2024-05-19,2024-06-28,2296,6.5,DeepTech Ventures -AI09064,Autonomous Systems Engineer,322176,USD,322176,EX,FL,United States,L,United States,100,"Python, Hadoop, SQL",PhD,19,Finance,2024-09-04,2024-09-23,2234,9.4,Smart Analytics -AI09065,Machine Learning Engineer,153151,USD,153151,SE,PT,Sweden,L,Sweden,100,"SQL, Spark, MLOps, Data Visualization",Associate,9,Manufacturing,2024-08-26,2024-10-02,2125,7.7,Advanced Robotics -AI09066,AI Software Engineer,89864,USD,89864,EN,CT,Norway,L,Hungary,100,"Python, Docker, Tableau, AWS",PhD,0,Technology,2025-04-02,2025-04-19,2399,9.8,Digital Transformation LLC -AI09067,Data Scientist,103238,SGD,134209,MI,PT,Singapore,M,Japan,100,"Azure, Statistics, Hadoop, R",Master,3,Consulting,2025-01-26,2025-04-06,924,5.3,Autonomous Tech -AI09068,AI Specialist,62237,USD,62237,MI,FT,South Korea,S,Hungary,100,"Statistics, Tableau, SQL, Spark, Data Visualization",Master,4,Energy,2025-03-10,2025-04-13,1059,9.5,Autonomous Tech -AI09069,ML Ops Engineer,250692,EUR,213088,EX,FL,Netherlands,M,Netherlands,50,"Linux, GCP, Python, Mathematics, Azure",PhD,11,Healthcare,2024-12-11,2024-12-28,1030,8,Machine Intelligence Group -AI09070,ML Ops Engineer,75599,USD,75599,MI,PT,Ireland,M,South Africa,0,"Java, Kubernetes, Mathematics, SQL",Master,2,Consulting,2024-05-01,2024-07-12,1978,8.9,Advanced Robotics -AI09071,AI Product Manager,170126,CHF,153113,SE,FT,Switzerland,M,Switzerland,0,"Data Visualization, Statistics, NLP, MLOps",Associate,9,Healthcare,2024-03-14,2024-05-15,1405,5.6,Digital Transformation LLC -AI09072,Machine Learning Engineer,112438,EUR,95572,MI,CT,France,L,France,100,"Python, Statistics, AWS, Kubernetes, NLP",Master,4,Government,2024-04-26,2024-06-06,1829,9.3,DataVision Ltd -AI09073,AI Specialist,202327,USD,202327,EX,PT,Israel,M,Israel,0,"PyTorch, Linux, R",Associate,17,Retail,2024-05-20,2024-06-24,520,7.9,Quantum Computing Inc -AI09074,Head of AI,49609,EUR,42168,EN,CT,France,S,France,100,"Python, Java, NLP",Associate,1,Retail,2024-01-11,2024-03-08,1480,6.9,Machine Intelligence Group -AI09075,Data Analyst,101267,USD,101267,EX,FL,South Korea,S,Indonesia,100,"GCP, Azure, NLP, SQL, R",Bachelor,12,Retail,2024-05-01,2024-06-13,1534,8.8,DataVision Ltd -AI09076,Data Engineer,175412,EUR,149100,EX,FT,Germany,S,Germany,100,"Statistics, MLOps, Java",Associate,17,Manufacturing,2025-03-25,2025-05-04,2138,7.7,Cloud AI Solutions -AI09077,Robotics Engineer,132763,SGD,172592,SE,CT,Singapore,S,Singapore,50,"Hadoop, Tableau, R, Deep Learning",Associate,6,Manufacturing,2024-03-19,2024-05-10,1912,7.5,DeepTech Ventures -AI09078,Head of AI,146012,EUR,124110,EX,CT,Austria,S,United States,50,"Tableau, Linux, Java, R",Master,19,Retail,2025-02-15,2025-04-14,955,9.4,TechCorp Inc -AI09079,AI Architect,128830,USD,128830,SE,PT,Finland,S,Finland,0,"Python, TensorFlow, GCP, Java",Bachelor,9,Consulting,2024-01-15,2024-03-10,2249,6.9,AI Innovations -AI09080,Data Analyst,73935,EUR,62845,MI,PT,Germany,S,Germany,50,"PyTorch, Scala, MLOps",Master,2,Technology,2024-09-13,2024-11-07,1797,8.9,Cognitive Computing -AI09081,Machine Learning Researcher,20704,USD,20704,EN,FL,India,S,India,100,"Hadoop, Linux, GCP, Statistics",Master,0,Education,2024-02-22,2024-03-18,1935,5.9,Digital Transformation LLC -AI09082,AI Software Engineer,106038,USD,106038,EN,PT,United States,L,United States,50,"Spark, R, Deep Learning",Bachelor,1,Telecommunications,2024-03-24,2024-04-15,1621,5.5,Smart Analytics -AI09083,Machine Learning Researcher,256638,USD,256638,EX,FT,United States,L,United States,0,"Docker, Scala, Statistics, Data Visualization",Associate,18,Transportation,2024-04-13,2024-05-09,1801,9.7,DeepTech Ventures -AI09084,ML Ops Engineer,160139,CHF,144125,MI,FL,Switzerland,L,Japan,0,"Azure, Scala, NLP, Deep Learning, Git",Master,4,Automotive,2024-07-12,2024-09-06,1577,7.8,Smart Analytics -AI09085,Data Engineer,125643,USD,125643,MI,CT,United States,L,United States,100,"Linux, Mathematics, Deep Learning, Python, Statistics",Master,2,Media,2024-12-12,2025-02-05,2246,9.7,Machine Intelligence Group -AI09086,Research Scientist,33763,USD,33763,EN,FT,China,M,South Africa,50,"Java, Tableau, AWS, Scala, Linux",Associate,1,Automotive,2024-08-19,2024-09-26,1405,7.1,TechCorp Inc -AI09087,Computer Vision Engineer,51407,USD,51407,EN,PT,Sweden,M,Sweden,100,"Linux, Mathematics, SQL, MLOps",Associate,0,Gaming,2024-07-22,2024-09-28,1140,8.2,Autonomous Tech -AI09088,Data Scientist,93819,USD,93819,SE,FL,Finland,S,Finland,50,"Kubernetes, Java, MLOps, Scala, GCP",Bachelor,9,Manufacturing,2024-06-01,2024-06-18,1272,8.9,DataVision Ltd -AI09089,Data Engineer,108668,USD,108668,MI,PT,United States,S,United States,100,"Kubernetes, TensorFlow, GCP",Associate,3,Energy,2024-06-12,2024-08-13,2463,9,Predictive Systems -AI09090,AI Consultant,128578,AUD,173580,EX,PT,Australia,S,Australia,0,"Kubernetes, SQL, NLP",PhD,19,Technology,2024-11-24,2024-12-16,853,9.9,Predictive Systems -AI09091,AI Specialist,34167,USD,34167,MI,FL,China,M,China,50,"Linux, Scala, Spark, Git",PhD,2,Automotive,2024-09-11,2024-11-02,1155,6.7,Smart Analytics -AI09092,Deep Learning Engineer,82557,JPY,9081270,MI,FL,Japan,S,Colombia,50,"MLOps, NLP, R",Master,3,Manufacturing,2024-01-02,2024-02-29,1336,5.5,Cloud AI Solutions -AI09093,Machine Learning Engineer,73184,EUR,62206,EN,FL,Austria,M,Austria,100,"Python, SQL, GCP",Master,0,Automotive,2024-10-20,2024-12-10,2376,7.1,Predictive Systems -AI09094,Research Scientist,185487,EUR,157664,EX,PT,France,L,France,50,"Python, Deep Learning, Data Visualization, Java",PhD,10,Gaming,2024-07-21,2024-08-18,2304,8.6,TechCorp Inc -AI09095,Computer Vision Engineer,184041,JPY,20244510,EX,PT,Japan,M,Sweden,0,"TensorFlow, Java, Linux",PhD,13,Energy,2024-10-28,2024-12-13,1131,6.9,Machine Intelligence Group -AI09096,Data Analyst,63990,USD,63990,EN,PT,South Korea,L,Czech Republic,0,"Linux, Mathematics, Tableau, MLOps",PhD,0,Real Estate,2024-07-18,2024-09-08,1360,8.4,Autonomous Tech -AI09097,Deep Learning Engineer,77439,USD,77439,EN,FT,Denmark,L,Denmark,100,"Tableau, Git, Linux",PhD,1,Technology,2024-08-13,2024-09-08,526,10,Predictive Systems -AI09098,Machine Learning Researcher,54169,CAD,67711,EN,PT,Canada,S,Switzerland,100,"Spark, Azure, SQL, Hadoop, Statistics",PhD,0,Gaming,2024-08-28,2024-10-20,1818,7.1,Predictive Systems -AI09099,Deep Learning Engineer,97993,EUR,83294,SE,PT,Germany,S,Germany,0,"Kubernetes, Python, TensorFlow, Statistics",Master,6,Government,2024-09-24,2024-11-25,1849,6.6,Cognitive Computing -AI09100,Data Scientist,79820,JPY,8780200,EN,PT,Japan,L,Japan,100,"Azure, Git, R, Java, Scala",Master,1,Technology,2024-10-12,2024-12-04,1735,6.9,DataVision Ltd -AI09101,Principal Data Scientist,104484,USD,104484,EN,FT,United States,L,United States,0,"PyTorch, TensorFlow, R, Scala",Master,1,Automotive,2024-03-14,2024-03-29,1370,5.8,Smart Analytics -AI09102,Machine Learning Researcher,103925,USD,103925,MI,FL,Sweden,M,United Kingdom,0,"R, PyTorch, Mathematics",Master,3,Telecommunications,2024-06-17,2024-08-25,1236,8.4,TechCorp Inc -AI09103,AI Architect,99884,EUR,84901,SE,FL,Germany,S,Germany,0,"Spark, Azure, NLP, Mathematics, SQL",Associate,9,Manufacturing,2025-03-13,2025-05-11,2448,7.6,TechCorp Inc -AI09104,Machine Learning Researcher,153139,JPY,16845290,SE,FL,Japan,L,Japan,0,"Linux, Python, Deep Learning, Statistics, Computer Vision",Associate,5,Technology,2025-04-25,2025-06-21,2037,7.4,Future Systems -AI09105,ML Ops Engineer,61944,EUR,52652,EN,FL,France,L,France,50,"Deep Learning, Hadoop, PyTorch, NLP",Master,0,Retail,2024-09-28,2024-10-18,2126,6.7,TechCorp Inc -AI09106,Data Engineer,65282,EUR,55490,EN,PT,Austria,M,Austria,50,"Docker, Tableau, NLP",Master,1,Automotive,2024-05-21,2024-08-02,837,8.6,Quantum Computing Inc -AI09107,NLP Engineer,96292,EUR,81848,SE,CT,Germany,S,Germany,100,"NLP, Deep Learning, Scala",Bachelor,9,Consulting,2024-05-18,2024-07-17,1311,6.3,Algorithmic Solutions -AI09108,ML Ops Engineer,157918,CHF,142126,MI,CT,Switzerland,L,Switzerland,100,"Docker, Git, Mathematics",PhD,4,Technology,2024-07-16,2024-08-28,1630,5.3,Cloud AI Solutions -AI09109,Robotics Engineer,68722,AUD,92775,EN,FT,Australia,M,Australia,100,"Python, Spark, Java",Master,0,Education,2024-04-17,2024-05-18,2294,7,Neural Networks Co -AI09110,Computer Vision Engineer,34572,USD,34572,MI,FT,India,S,Austria,50,"Statistics, Python, TensorFlow",PhD,4,Manufacturing,2025-04-13,2025-05-02,1135,5.9,Predictive Systems -AI09111,AI Research Scientist,46646,USD,46646,MI,CT,China,L,China,50,"Deep Learning, MLOps, GCP, NLP",PhD,4,Telecommunications,2025-04-10,2025-05-23,1392,5.4,TechCorp Inc -AI09112,AI Architect,235688,EUR,200335,EX,PT,France,M,Argentina,0,"AWS, Git, Data Visualization, Statistics",Master,15,Transportation,2025-03-24,2025-05-18,2377,6.6,Autonomous Tech -AI09113,NLP Engineer,273202,USD,273202,EX,FT,Israel,L,Russia,100,"Scala, R, Azure, SQL",PhD,17,Transportation,2024-04-04,2024-05-13,717,5.6,DataVision Ltd -AI09114,Principal Data Scientist,191484,CAD,239355,EX,FT,Canada,S,Canada,0,"NLP, Spark, Scala, TensorFlow, Deep Learning",Associate,11,Manufacturing,2025-03-03,2025-04-29,674,9.1,AI Innovations -AI09115,AI Research Scientist,59597,USD,59597,EX,CT,India,M,Israel,0,"MLOps, Scala, TensorFlow",Bachelor,12,Manufacturing,2024-04-19,2024-06-24,1996,7,Smart Analytics -AI09116,Autonomous Systems Engineer,152712,USD,152712,EX,FL,Ireland,S,Ireland,50,"Deep Learning, Python, Data Visualization, Git, R",Master,12,Transportation,2024-05-13,2024-07-23,2066,7.7,DataVision Ltd -AI09117,Machine Learning Engineer,260073,EUR,221062,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, TensorFlow, Computer Vision, Data Visualization",Associate,14,Government,2024-04-27,2024-06-16,2072,9.8,Digital Transformation LLC -AI09118,Principal Data Scientist,21379,USD,21379,EN,PT,India,M,India,50,"Computer Vision, GCP, Hadoop, Python, Data Visualization",PhD,1,Healthcare,2024-06-02,2024-07-05,785,5.4,Machine Intelligence Group -AI09119,Machine Learning Researcher,39561,USD,39561,MI,FT,China,L,China,100,"Computer Vision, TensorFlow, Hadoop",Bachelor,4,Retail,2024-09-21,2024-11-03,930,8.7,Smart Analytics -AI09120,AI Software Engineer,126547,EUR,107565,MI,CT,Germany,L,Germany,50,"Linux, Docker, PyTorch",Bachelor,4,Telecommunications,2025-04-24,2025-07-06,1681,7,Algorithmic Solutions -AI09121,Autonomous Systems Engineer,187489,USD,187489,EX,PT,South Korea,S,South Korea,50,"Java, Kubernetes, Tableau",PhD,17,Energy,2024-08-20,2024-10-06,2373,10,TechCorp Inc -AI09122,NLP Engineer,131267,USD,131267,SE,FL,United States,M,United States,0,"SQL, R, Linux, GCP",Bachelor,8,Finance,2024-01-24,2024-03-11,1746,9,Autonomous Tech -AI09123,AI Architect,77519,USD,77519,EN,FL,Finland,L,Finland,0,"Azure, Kubernetes, Scala",Associate,0,Finance,2025-03-21,2025-05-12,1803,6.2,DeepTech Ventures -AI09124,ML Ops Engineer,108940,AUD,147069,MI,PT,Australia,L,Kenya,100,"Hadoop, Java, Tableau",Bachelor,2,Government,2024-02-24,2024-04-24,2250,8.3,DataVision Ltd -AI09125,Machine Learning Researcher,151325,GBP,113494,EX,FL,United Kingdom,M,Ukraine,0,"Hadoop, PyTorch, Deep Learning",PhD,12,Real Estate,2025-01-05,2025-02-23,2290,8.5,TechCorp Inc -AI09126,Head of AI,164274,USD,164274,EX,FL,Ireland,L,Finland,50,"Python, TensorFlow, PyTorch, Deep Learning",Master,13,Automotive,2024-11-15,2024-12-17,930,6.2,Future Systems -AI09127,Principal Data Scientist,96078,AUD,129705,MI,CT,Australia,S,Australia,0,"Scala, AWS, Azure, R",Master,2,Telecommunications,2024-02-19,2024-03-15,2296,6.6,TechCorp Inc -AI09128,Principal Data Scientist,234097,EUR,198982,EX,FT,Netherlands,S,Luxembourg,100,"Hadoop, Scala, Deep Learning, R, AWS",PhD,17,Manufacturing,2024-09-16,2024-11-26,1852,5.8,Advanced Robotics -AI09129,Research Scientist,285597,USD,285597,EX,CT,Norway,M,Mexico,50,"Kubernetes, Deep Learning, TensorFlow, Scala",Associate,17,Energy,2024-04-09,2024-06-11,1210,7.6,Future Systems -AI09130,Autonomous Systems Engineer,273922,USD,273922,EX,FT,Norway,L,Norway,100,"Python, Docker, Hadoop, Deep Learning, Mathematics",Associate,16,Energy,2024-04-13,2024-05-11,1232,5.6,Quantum Computing Inc -AI09131,AI Software Engineer,61758,EUR,52494,MI,PT,Austria,S,Austria,50,"MLOps, Deep Learning, PyTorch, GCP",PhD,4,Energy,2025-03-06,2025-05-03,2361,7.4,Predictive Systems -AI09132,Autonomous Systems Engineer,216376,EUR,183920,EX,PT,Austria,L,Austria,100,"SQL, Azure, Kubernetes, Docker",Master,15,Transportation,2024-05-28,2024-07-21,2425,6.2,Autonomous Tech -AI09133,Data Engineer,137572,USD,137572,SE,PT,Denmark,S,Kenya,50,"Data Visualization, Azure, Python",Bachelor,7,Education,2025-04-29,2025-07-11,1115,8.3,Neural Networks Co -AI09134,Machine Learning Researcher,206544,JPY,22719840,EX,CT,Japan,S,Japan,50,"MLOps, SQL, TensorFlow, Data Visualization, Statistics",Master,16,Gaming,2024-06-13,2024-07-10,2087,6.2,DataVision Ltd -AI09135,ML Ops Engineer,141517,USD,141517,SE,FT,South Korea,L,Colombia,0,"Kubernetes, Python, AWS",Associate,6,Gaming,2024-04-07,2024-06-11,822,6.1,DeepTech Ventures -AI09136,Research Scientist,87198,EUR,74118,MI,PT,Austria,L,Austria,50,"Kubernetes, Spark, SQL, NLP",Master,4,Automotive,2025-04-11,2025-05-31,1541,9.8,Predictive Systems -AI09137,Machine Learning Researcher,87108,EUR,74042,EN,PT,Netherlands,L,Netherlands,0,"PyTorch, Java, Scala, Docker, TensorFlow",Bachelor,0,Gaming,2024-09-06,2024-11-16,2018,7.6,TechCorp Inc -AI09138,Robotics Engineer,214335,EUR,182185,EX,CT,Austria,S,Denmark,0,"Hadoop, AWS, SQL",Associate,15,Education,2024-10-30,2024-12-27,1232,9.5,Machine Intelligence Group -AI09139,AI Specialist,153507,CAD,191884,EX,FT,Canada,S,Canada,100,"SQL, Docker, Data Visualization, MLOps",PhD,15,Consulting,2024-09-04,2024-11-09,2064,8.6,Cloud AI Solutions -AI09140,Data Analyst,73451,EUR,62433,MI,PT,Austria,S,Austria,0,"Git, Python, Data Visualization, Azure, Tableau",PhD,2,Energy,2024-11-23,2024-12-26,2401,7.7,DeepTech Ventures -AI09141,Robotics Engineer,141812,SGD,184356,SE,PT,Singapore,M,Singapore,0,"Mathematics, Spark, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-02-17,2364,8.8,Future Systems -AI09142,AI Software Engineer,185928,USD,185928,EX,PT,South Korea,M,China,50,"Spark, Scala, Statistics, Hadoop",Master,11,Consulting,2024-05-08,2024-07-17,1047,8.2,Algorithmic Solutions -AI09143,Machine Learning Engineer,114515,USD,114515,SE,PT,Israel,S,Israel,50,"Tableau, NLP, GCP, Computer Vision",Bachelor,7,Education,2024-02-02,2024-03-01,961,7.9,AI Innovations -AI09144,Data Analyst,175467,EUR,149147,EX,CT,Germany,S,Germany,0,"Git, Statistics, Tableau, TensorFlow",Master,15,Retail,2025-02-10,2025-03-05,2273,6.5,DeepTech Ventures -AI09145,Head of AI,88766,EUR,75451,MI,CT,Netherlands,L,Netherlands,0,"R, AWS, Data Visualization",Associate,2,Transportation,2024-10-14,2024-11-16,850,9,Digital Transformation LLC -AI09146,Computer Vision Engineer,111355,JPY,12249050,MI,FL,Japan,M,Poland,0,"Python, PyTorch, Deep Learning, GCP",PhD,4,Telecommunications,2025-01-16,2025-02-20,2186,7.2,Future Systems -AI09147,Machine Learning Engineer,128271,CAD,160339,SE,FT,Canada,S,Canada,100,"Data Visualization, NLP, Tableau",Bachelor,5,Government,2024-11-15,2024-12-07,837,7.7,Advanced Robotics -AI09148,Machine Learning Engineer,123580,EUR,105043,SE,FT,France,M,France,0,"NLP, Spark, Deep Learning",Master,9,Education,2025-03-13,2025-05-21,1067,8.3,AI Innovations -AI09149,ML Ops Engineer,77084,AUD,104063,EN,CT,Australia,L,Australia,0,"Data Visualization, NLP, TensorFlow, Azure",Bachelor,1,Consulting,2024-07-02,2024-07-20,1859,7.6,DataVision Ltd -AI09150,AI Specialist,46762,USD,46762,EN,PT,Ireland,S,Ireland,100,"PyTorch, SQL, Deep Learning, Scala, Tableau",Associate,1,Government,2025-03-26,2025-05-25,1596,9.3,Machine Intelligence Group -AI09151,AI Consultant,218952,USD,218952,EX,PT,Ireland,M,Ireland,50,"MLOps, AWS, SQL, Mathematics, Azure",Bachelor,13,Government,2025-01-30,2025-03-21,628,7.9,Advanced Robotics -AI09152,AI Product Manager,61455,SGD,79892,EN,FT,Singapore,S,Australia,50,"Hadoop, Tableau, Spark, Linux, Computer Vision",Bachelor,1,Finance,2024-04-19,2024-06-14,1344,5.6,Predictive Systems -AI09153,Machine Learning Engineer,66187,USD,66187,EX,PT,China,M,China,100,"Azure, Git, Tableau, SQL",Bachelor,17,Finance,2024-11-22,2024-12-11,1180,6.7,Cloud AI Solutions -AI09154,NLP Engineer,130172,SGD,169224,SE,FT,Singapore,S,Japan,50,"GCP, Java, MLOps, Computer Vision",PhD,8,Automotive,2025-03-01,2025-05-09,1102,9.1,TechCorp Inc -AI09155,Machine Learning Engineer,77763,JPY,8553930,EN,FT,Japan,L,Japan,100,"SQL, PyTorch, Mathematics, Docker",Associate,1,Real Estate,2025-03-15,2025-05-08,648,5.8,Autonomous Tech -AI09156,Research Scientist,100848,USD,100848,MI,CT,Norway,M,Norway,100,"Docker, Git, AWS",PhD,2,Energy,2024-08-19,2024-09-28,752,6.5,Smart Analytics -AI09157,Machine Learning Engineer,144916,JPY,15940760,EX,FT,Japan,S,Japan,50,"PyTorch, Scala, Python",PhD,18,Retail,2025-02-06,2025-03-23,1976,5.7,Quantum Computing Inc -AI09158,Autonomous Systems Engineer,241167,SGD,313517,EX,PT,Singapore,S,Israel,100,"Spark, Statistics, Computer Vision, Git",Associate,17,Technology,2024-06-11,2024-07-22,2278,8.5,Algorithmic Solutions -AI09159,Head of AI,122631,GBP,91973,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, SQL, Deep Learning, MLOps",Associate,3,Healthcare,2025-03-21,2025-05-10,1649,7.5,AI Innovations -AI09160,ML Ops Engineer,52113,USD,52113,SE,FL,India,M,India,50,"Computer Vision, GCP, Tableau, NLP",Master,9,Telecommunications,2024-05-01,2024-05-19,1707,5.2,Digital Transformation LLC -AI09161,AI Specialist,131239,AUD,177173,SE,PT,Australia,S,Latvia,0,"Spark, Hadoop, TensorFlow, MLOps",Associate,8,Consulting,2024-12-07,2025-02-16,1374,6.6,Autonomous Tech -AI09162,AI Architect,39306,USD,39306,SE,CT,India,S,India,100,"Linux, MLOps, Tableau, AWS, Git",PhD,7,Automotive,2025-04-23,2025-05-24,703,6.6,Smart Analytics -AI09163,Machine Learning Engineer,55092,EUR,46828,EN,FT,Austria,M,Austria,100,"Python, GCP, Mathematics, MLOps",Bachelor,0,Automotive,2024-07-24,2024-09-15,1765,7.5,Quantum Computing Inc -AI09164,Research Scientist,155977,AUD,210569,SE,CT,Australia,L,Australia,50,"Azure, Mathematics, Data Visualization",PhD,7,Real Estate,2024-12-22,2025-02-15,564,9.6,AI Innovations -AI09165,AI Architect,92563,USD,92563,EN,FL,United States,M,United States,100,"Python, Kubernetes, Computer Vision, NLP",Associate,0,Education,2024-09-29,2024-10-17,2497,9.7,Cloud AI Solutions -AI09166,Data Scientist,56883,USD,56883,EN,FL,Finland,M,Finland,50,"Tableau, Hadoop, Python",PhD,1,Energy,2024-08-25,2024-10-24,2304,5.1,Advanced Robotics -AI09167,AI Research Scientist,63119,USD,63119,EN,FT,Norway,S,Norway,0,"Docker, MLOps, Scala, Computer Vision, Azure",Associate,1,Finance,2024-04-17,2024-05-28,1624,9.1,Algorithmic Solutions -AI09168,Robotics Engineer,124054,USD,124054,SE,CT,Finland,S,Argentina,0,"Python, GCP, Computer Vision",Bachelor,7,Energy,2024-09-10,2024-10-17,1475,8.2,DataVision Ltd -AI09169,Head of AI,70626,AUD,95345,EN,CT,Australia,S,Australia,100,"GCP, TensorFlow, MLOps, Python",Master,0,Government,2025-03-21,2025-04-13,2467,9.3,DataVision Ltd -AI09170,AI Consultant,95105,EUR,80839,MI,PT,Germany,M,China,50,"Spark, SQL, MLOps, Hadoop, Statistics",Master,3,Gaming,2024-02-26,2024-03-18,1527,5.9,Smart Analytics -AI09171,AI Architect,142966,GBP,107225,SE,FL,United Kingdom,M,Canada,0,"Computer Vision, SQL, Deep Learning, Git, Hadoop",Bachelor,6,Energy,2024-02-27,2024-04-18,1558,8.4,Machine Intelligence Group -AI09172,Autonomous Systems Engineer,30269,USD,30269,EN,FL,India,L,Israel,50,"NLP, Kubernetes, TensorFlow, MLOps, Git",Master,1,Retail,2024-12-02,2024-12-23,1413,6.7,Future Systems -AI09173,Computer Vision Engineer,172669,USD,172669,SE,FL,Norway,M,Norway,0,"Docker, PyTorch, Java, Python, Scala",Bachelor,8,Real Estate,2024-07-22,2024-08-16,1753,9.4,Future Systems -AI09174,Robotics Engineer,129725,USD,129725,EX,PT,Ireland,S,Ireland,50,"Scala, Azure, Tableau, NLP",Master,14,Media,2024-06-24,2024-09-02,1349,8.5,Digital Transformation LLC -AI09175,Computer Vision Engineer,63167,SGD,82117,EN,CT,Singapore,S,Singapore,100,"NLP, GCP, Deep Learning, Python, Hadoop",Master,0,Retail,2024-09-27,2024-12-09,686,8.7,Neural Networks Co -AI09176,AI Specialist,258786,USD,258786,EX,FL,Norway,S,Norway,50,"Linux, Kubernetes, PyTorch",Master,10,Technology,2024-04-22,2024-05-08,1899,5.4,Cognitive Computing -AI09177,AI Research Scientist,44253,USD,44253,MI,CT,China,S,Finland,50,"Hadoop, Python, Azure, Kubernetes, Scala",Bachelor,2,Energy,2025-01-02,2025-02-15,1158,8.5,Quantum Computing Inc -AI09178,AI Consultant,130321,GBP,97741,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, MLOps, SQL",Master,7,Technology,2024-04-29,2024-05-18,2064,8.7,Advanced Robotics -AI09179,Research Scientist,163239,EUR,138753,EX,FT,France,M,France,0,"Linux, Git, Data Visualization, Deep Learning",Master,13,Healthcare,2024-09-06,2024-11-17,766,9,Smart Analytics -AI09180,Research Scientist,88353,CAD,110441,MI,FL,Canada,S,Philippines,100,"R, Linux, SQL, Git, AWS",Bachelor,4,Manufacturing,2024-05-06,2024-05-31,1684,7.6,Algorithmic Solutions -AI09181,Machine Learning Engineer,99421,CAD,124276,MI,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Tableau",Master,4,Retail,2024-04-20,2024-05-16,1672,6.4,Machine Intelligence Group -AI09182,Deep Learning Engineer,92458,EUR,78589,SE,FL,Germany,S,Germany,0,"Scala, PyTorch, Hadoop",PhD,7,Transportation,2024-05-10,2024-07-15,1982,9.8,Cloud AI Solutions -AI09183,Autonomous Systems Engineer,176930,JPY,19462300,SE,FL,Japan,L,Japan,50,"Kubernetes, Deep Learning, MLOps, Azure",Master,7,Healthcare,2024-03-24,2024-04-25,1765,6.9,DeepTech Ventures -AI09184,Machine Learning Engineer,87956,USD,87956,MI,CT,Israel,S,Israel,50,"Spark, Python, Data Visualization",Master,4,Telecommunications,2024-01-16,2024-02-22,1350,9.5,Algorithmic Solutions -AI09185,Data Scientist,178060,USD,178060,SE,FT,Norway,L,Norway,100,"Spark, Git, NLP, Statistics",Master,7,Energy,2025-01-28,2025-04-11,2470,7.7,Algorithmic Solutions -AI09186,Robotics Engineer,274887,USD,274887,EX,FT,Finland,L,Finland,50,"Python, TensorFlow, Git, Linux, Azure",Bachelor,18,Media,2025-03-19,2025-05-06,524,5.2,Quantum Computing Inc -AI09187,AI Software Engineer,111752,USD,111752,MI,PT,Ireland,L,Ireland,100,"Docker, Spark, NLP, Kubernetes, Computer Vision",Bachelor,4,Gaming,2024-01-05,2024-01-20,1344,8.3,Cloud AI Solutions -AI09188,AI Specialist,58945,CAD,73681,EN,FL,Canada,L,South Africa,100,"R, SQL, Linux",Master,0,Education,2024-12-30,2025-02-24,1925,8.9,Machine Intelligence Group -AI09189,AI Specialist,192129,USD,192129,SE,FL,Denmark,L,Denmark,50,"Linux, Python, Tableau",Master,6,Education,2024-03-30,2024-06-03,1867,9.3,TechCorp Inc -AI09190,Data Analyst,111169,AUD,150078,SE,PT,Australia,M,Canada,50,"PyTorch, Linux, MLOps",Master,8,Education,2024-10-10,2024-10-26,726,6.8,DataVision Ltd -AI09191,Machine Learning Researcher,92985,GBP,69739,MI,PT,United Kingdom,L,United Kingdom,50,"AWS, TensorFlow, SQL, Azure",Master,3,Gaming,2024-07-23,2024-08-21,1875,6.4,Machine Intelligence Group -AI09192,AI Consultant,96505,CHF,86855,EN,PT,Switzerland,S,Switzerland,50,"SQL, TensorFlow, NLP, AWS, Tableau",Bachelor,0,Manufacturing,2024-02-29,2024-04-30,2394,7,Cognitive Computing -AI09193,AI Software Engineer,158342,USD,158342,EX,FT,South Korea,L,South Korea,0,"GCP, TensorFlow, NLP, Statistics, Computer Vision",Master,12,Consulting,2025-03-12,2025-04-27,1649,6.4,Cognitive Computing -AI09194,AI Specialist,93578,JPY,10293580,EN,CT,Japan,L,Japan,0,"Java, TensorFlow, Azure, Tableau, Kubernetes",Associate,1,Gaming,2024-10-26,2024-11-30,2036,9.3,Smart Analytics -AI09195,Data Engineer,214274,USD,214274,EX,CT,United States,M,Czech Republic,100,"Java, Data Visualization, PyTorch",Master,13,Technology,2024-11-12,2024-12-31,743,8,Digital Transformation LLC -AI09196,AI Consultant,178303,CAD,222879,EX,CT,Canada,M,Canada,50,"Mathematics, Computer Vision, Spark, Hadoop, SQL",Associate,17,Government,2025-03-03,2025-04-19,1070,8.9,Advanced Robotics -AI09197,Head of AI,36007,USD,36007,SE,FT,India,M,India,50,"AWS, Tableau, TensorFlow, Git",Associate,7,Finance,2024-02-07,2024-03-03,730,6,Advanced Robotics -AI09198,Deep Learning Engineer,171051,EUR,145393,EX,PT,Austria,S,Canada,50,"Python, AWS, TensorFlow",Bachelor,13,Consulting,2024-05-21,2024-07-03,1012,8.5,Algorithmic Solutions -AI09199,Head of AI,198950,EUR,169108,EX,FT,Austria,S,Austria,50,"Spark, SQL, Statistics",Associate,14,Government,2025-03-12,2025-04-20,2381,9.2,DeepTech Ventures -AI09200,Robotics Engineer,124387,EUR,105729,SE,FT,France,M,France,100,"PyTorch, TensorFlow, Deep Learning, Scala, Java",Associate,8,Gaming,2024-10-15,2024-12-06,911,5,Neural Networks Co -AI09201,Computer Vision Engineer,106704,USD,106704,MI,FL,Ireland,L,Ireland,100,"R, Git, Azure, Scala, Python",PhD,3,Telecommunications,2024-01-15,2024-02-03,1956,5.7,DeepTech Ventures -AI09202,Research Scientist,149562,USD,149562,EX,FL,Finland,L,Finland,0,"Scala, Tableau, Python, SQL, Kubernetes",Associate,16,Education,2024-10-12,2024-12-08,1386,7.2,Cloud AI Solutions -AI09203,AI Software Engineer,112666,USD,112666,SE,FL,Finland,L,Japan,50,"Azure, Java, Computer Vision",PhD,8,Telecommunications,2024-04-27,2024-06-01,1069,7.2,Cloud AI Solutions -AI09204,Data Analyst,102655,USD,102655,MI,CT,Norway,S,Norway,100,"PyTorch, Computer Vision, Git",Master,2,Telecommunications,2024-12-02,2025-02-12,721,5.4,TechCorp Inc -AI09205,Research Scientist,60391,CAD,75489,EN,FT,Canada,M,Canada,50,"SQL, Spark, PyTorch",PhD,1,Manufacturing,2024-01-31,2024-04-13,1304,6.9,DeepTech Ventures -AI09206,Data Analyst,93418,USD,93418,SE,PT,South Korea,S,Estonia,0,"Git, SQL, Hadoop, Mathematics, Scala",Associate,9,Education,2024-04-04,2024-06-10,2248,9.4,Cloud AI Solutions -AI09207,AI Architect,64099,EUR,54484,MI,PT,France,S,Japan,100,"Scala, Spark, Java, Computer Vision, Docker",Associate,4,Education,2024-11-15,2024-12-08,2247,5.1,Cognitive Computing -AI09208,Head of AI,170894,JPY,18798340,SE,FL,Japan,L,Japan,0,"Data Visualization, PyTorch, SQL",Bachelor,8,Real Estate,2024-03-13,2024-05-15,2021,6.9,Algorithmic Solutions -AI09209,Autonomous Systems Engineer,26067,USD,26067,EN,CT,India,M,Russia,100,"Hadoop, Python, TensorFlow, Git",Bachelor,0,Consulting,2024-01-23,2024-03-07,892,7.1,Advanced Robotics -AI09210,AI Specialist,87803,EUR,74633,EN,PT,Germany,L,Germany,100,"TensorFlow, Python, GCP",Master,1,Media,2024-11-08,2024-12-04,822,8.7,Algorithmic Solutions -AI09211,AI Consultant,73822,CAD,92278,EN,FL,Canada,M,Netherlands,0,"Tableau, TensorFlow, Scala, Statistics",Master,1,Technology,2024-10-03,2024-10-20,1230,5.2,Predictive Systems -AI09212,Machine Learning Engineer,92932,CHF,83639,EN,FT,Switzerland,M,Switzerland,100,"AWS, NLP, SQL",Bachelor,0,Education,2024-07-23,2024-09-05,608,6.4,Neural Networks Co -AI09213,AI Consultant,68084,EUR,57871,EN,PT,Netherlands,L,France,100,"Linux, Tableau, Spark, AWS, Azure",PhD,0,Technology,2025-02-23,2025-04-28,1068,8.9,Cloud AI Solutions -AI09214,AI Specialist,207439,SGD,269671,EX,FL,Singapore,M,Singapore,100,"Java, Spark, NLP",Associate,18,Media,2024-03-19,2024-04-21,1904,5.8,Machine Intelligence Group -AI09215,Data Analyst,96026,USD,96026,EX,FL,China,S,China,100,"SQL, PyTorch, Data Visualization, MLOps",Bachelor,10,Telecommunications,2025-04-16,2025-05-31,868,9.4,Digital Transformation LLC -AI09216,Research Scientist,59680,EUR,50728,EN,FT,France,M,France,0,"Hadoop, MLOps, TensorFlow, Mathematics",Associate,1,Retail,2025-03-12,2025-05-20,2217,6.3,DataVision Ltd -AI09217,AI Specialist,56599,USD,56599,EN,CT,Israel,M,Israel,50,"Azure, AWS, Docker",Master,1,Retail,2025-03-09,2025-04-18,2056,7.5,Future Systems -AI09218,Principal Data Scientist,76244,USD,76244,EN,PT,United States,M,Nigeria,50,"PyTorch, Statistics, TensorFlow",Bachelor,1,Government,2024-09-24,2024-11-27,2133,5.8,Cloud AI Solutions -AI09219,Research Scientist,79160,EUR,67286,MI,FT,France,S,France,100,"Kubernetes, PyTorch, MLOps, SQL",Associate,4,Consulting,2024-11-09,2024-12-14,1801,9.4,Quantum Computing Inc -AI09220,Data Scientist,60957,USD,60957,EN,CT,Ireland,L,Ireland,50,"Git, Python, GCP",PhD,0,Gaming,2025-03-31,2025-05-04,1384,8.1,Future Systems -AI09221,Autonomous Systems Engineer,155548,USD,155548,SE,FL,Israel,L,India,100,"MLOps, Python, TensorFlow, PyTorch, Data Visualization",Master,5,Consulting,2024-08-12,2024-09-22,1725,6.7,Algorithmic Solutions -AI09222,AI Product Manager,123088,JPY,13539680,MI,PT,Japan,L,Japan,0,"Statistics, Scala, Python, GCP, R",Master,2,Manufacturing,2024-05-23,2024-06-09,1989,9,Algorithmic Solutions -AI09223,Research Scientist,121682,USD,121682,MI,FL,Norway,L,Vietnam,100,"Hadoop, Tableau, Spark, Mathematics, Scala",Associate,4,Finance,2024-12-25,2025-02-05,1174,5.7,Cognitive Computing -AI09224,AI Consultant,169915,EUR,144428,EX,PT,Germany,L,Germany,0,"GCP, Hadoop, Git, Computer Vision, R",Associate,14,Media,2025-01-19,2025-02-24,852,5.2,Autonomous Tech -AI09225,AI Specialist,119381,CAD,149226,MI,PT,Canada,L,Canada,100,"Java, MLOps, AWS",PhD,4,Manufacturing,2024-09-22,2024-11-04,2129,8.6,Digital Transformation LLC -AI09226,Deep Learning Engineer,133384,GBP,100038,SE,PT,United Kingdom,M,United Kingdom,0,"SQL, TensorFlow, AWS",Associate,6,Government,2024-04-07,2024-05-07,575,9.1,Machine Intelligence Group -AI09227,AI Architect,122154,USD,122154,SE,FT,United States,S,Colombia,100,"Python, Spark, Mathematics",Master,8,Technology,2024-07-25,2024-09-20,2343,6.7,DeepTech Ventures -AI09228,AI Specialist,66659,EUR,56660,EN,FL,Netherlands,S,Netherlands,100,"Kubernetes, PyTorch, TensorFlow, Spark, Computer Vision",PhD,1,Finance,2024-03-02,2024-04-15,2386,6.7,Cloud AI Solutions -AI09229,Data Analyst,92410,EUR,78549,MI,PT,Germany,L,Germany,100,"Hadoop, SQL, AWS",Bachelor,2,Technology,2024-03-28,2024-05-25,2078,8.7,Algorithmic Solutions -AI09230,Principal Data Scientist,81950,USD,81950,SE,FT,South Korea,S,South Korea,50,"Azure, SQL, Python, TensorFlow",Associate,9,Real Estate,2025-01-27,2025-03-31,1513,6.6,Predictive Systems -AI09231,AI Research Scientist,192330,EUR,163481,EX,CT,Netherlands,L,Netherlands,100,"GCP, Spark, Data Visualization, SQL",Bachelor,19,Government,2025-04-30,2025-05-28,1050,6.7,Cloud AI Solutions -AI09232,AI Specialist,194139,CHF,174725,SE,CT,Switzerland,M,Romania,50,"Deep Learning, Java, MLOps, Kubernetes, AWS",Associate,7,Retail,2024-06-18,2024-07-23,2017,9.3,Cognitive Computing -AI09233,Machine Learning Researcher,287100,USD,287100,EX,PT,Denmark,S,Denmark,0,"R, Python, Spark",Master,14,Technology,2025-03-18,2025-04-23,505,7,DataVision Ltd -AI09234,AI Consultant,192660,USD,192660,EX,FT,Finland,S,Finland,50,"GCP, PyTorch, TensorFlow, SQL",Associate,18,Healthcare,2024-06-29,2024-08-24,1758,7,AI Innovations -AI09235,AI Specialist,79472,USD,79472,MI,CT,Israel,M,Kenya,0,"Python, Spark, Kubernetes, PyTorch, Tableau",Master,3,Technology,2024-07-21,2024-09-07,1228,5.5,Advanced Robotics -AI09236,Autonomous Systems Engineer,118867,USD,118867,MI,FL,Norway,L,Norway,0,"MLOps, TensorFlow, Python",PhD,2,Telecommunications,2024-10-11,2024-12-13,2362,9.9,Algorithmic Solutions -AI09237,Research Scientist,123406,USD,123406,SE,PT,South Korea,L,Colombia,100,"SQL, PyTorch, AWS, Kubernetes",Associate,7,Automotive,2024-12-14,2025-02-20,1950,9.1,AI Innovations -AI09238,NLP Engineer,122245,USD,122245,SE,PT,Denmark,S,Denmark,100,"Git, Data Visualization, AWS",Master,5,Gaming,2024-10-30,2024-11-15,1775,9.5,Machine Intelligence Group -AI09239,ML Ops Engineer,191922,EUR,163134,EX,PT,France,S,France,0,"MLOps, Java, Docker, Scala",Associate,14,Gaming,2024-12-15,2025-01-12,2390,6,Cognitive Computing -AI09240,Data Engineer,68565,SGD,89135,EN,PT,Singapore,L,Singapore,50,"Kubernetes, Statistics, Data Visualization, Azure, Computer Vision",Master,0,Retail,2024-03-05,2024-04-21,2290,6.2,Quantum Computing Inc -AI09241,ML Ops Engineer,102495,JPY,11274450,MI,PT,Japan,S,Estonia,0,"Linux, Scala, Java, Azure",PhD,3,Manufacturing,2024-12-06,2025-01-21,1059,9.7,Predictive Systems -AI09242,Research Scientist,69321,SGD,90117,EN,CT,Singapore,L,Singapore,50,"AWS, Scala, Statistics, R",Master,0,Telecommunications,2024-08-31,2024-11-01,1292,8,Autonomous Tech -AI09243,Autonomous Systems Engineer,100703,AUD,135949,MI,FT,Australia,L,Australia,100,"Kubernetes, Tableau, Docker",PhD,4,Education,2024-07-05,2024-09-04,2102,7.8,Cognitive Computing -AI09244,AI Product Manager,87600,AUD,118260,EN,FT,Australia,L,Norway,0,"R, Mathematics, PyTorch, Deep Learning",Associate,1,Gaming,2024-01-06,2024-02-17,2084,7.9,Cloud AI Solutions -AI09245,AI Product Manager,104439,USD,104439,EN,FT,Denmark,M,Denmark,100,"Data Visualization, Linux, Computer Vision, Kubernetes, Mathematics",PhD,1,Real Estate,2024-03-19,2024-04-02,765,5.1,Smart Analytics -AI09246,Machine Learning Engineer,114869,CHF,103382,MI,CT,Switzerland,M,Switzerland,50,"GCP, Python, SQL, Kubernetes, Docker",Bachelor,4,Healthcare,2024-02-02,2024-04-04,1465,6.6,Machine Intelligence Group -AI09247,AI Consultant,77038,USD,77038,MI,CT,South Korea,S,South Korea,50,"Deep Learning, Kubernetes, Tableau, NLP",Master,4,Consulting,2024-03-17,2024-05-05,590,9.9,Autonomous Tech -AI09248,Machine Learning Engineer,115588,USD,115588,SE,FL,Sweden,S,New Zealand,50,"Docker, Mathematics, Tableau, GCP",Associate,7,Gaming,2025-02-23,2025-03-10,1018,7.5,DataVision Ltd -AI09249,Computer Vision Engineer,124933,CAD,156166,SE,FL,Canada,S,Canada,0,"GCP, Python, Data Visualization, Computer Vision, Deep Learning",Associate,8,Gaming,2024-07-16,2024-09-02,2228,6.4,Smart Analytics -AI09250,Robotics Engineer,105467,EUR,89647,MI,FT,Germany,L,Germany,0,"TensorFlow, Computer Vision, PyTorch, Deep Learning, Statistics",Associate,2,Healthcare,2024-11-03,2024-12-29,743,9.4,TechCorp Inc -AI09251,Research Scientist,108242,USD,108242,MI,FT,Ireland,L,Germany,100,"Computer Vision, GCP, Git, Tableau",Master,2,Manufacturing,2024-09-10,2024-09-26,682,9.8,Advanced Robotics -AI09252,AI Architect,92353,AUD,124677,SE,CT,Australia,S,Australia,100,"Mathematics, Azure, Tableau, TensorFlow, Java",Bachelor,6,Consulting,2024-02-04,2024-04-17,1028,9.1,Cloud AI Solutions -AI09253,Head of AI,137894,USD,137894,SE,PT,South Korea,L,Argentina,100,"Mathematics, Docker, GCP, Spark",Bachelor,5,Healthcare,2025-01-25,2025-02-22,1638,8.3,Autonomous Tech -AI09254,AI Specialist,80356,SGD,104463,EN,FL,Singapore,L,India,0,"Python, GCP, Kubernetes, Scala, Linux",Associate,0,Telecommunications,2024-04-19,2024-06-05,512,5.1,Smart Analytics -AI09255,Data Analyst,97471,USD,97471,MI,PT,Ireland,L,New Zealand,0,"Linux, AWS, Hadoop",Bachelor,3,Manufacturing,2024-01-25,2024-03-27,610,9.8,Future Systems -AI09256,Data Scientist,157922,USD,157922,EX,CT,Finland,M,Singapore,50,"R, Python, Statistics, Docker, Deep Learning",Associate,13,Consulting,2024-10-26,2024-12-05,2233,5.2,Cognitive Computing -AI09257,NLP Engineer,86054,CAD,107568,MI,FL,Canada,L,India,0,"Kubernetes, Python, Azure, TensorFlow, PyTorch",Bachelor,3,Real Estate,2024-07-08,2024-08-17,680,5.3,Cognitive Computing -AI09258,Data Scientist,133023,JPY,14632530,SE,FL,Japan,L,Colombia,50,"Azure, Docker, Deep Learning, SQL, MLOps",PhD,8,Real Estate,2025-03-03,2025-04-23,936,7.5,Algorithmic Solutions -AI09259,NLP Engineer,96262,GBP,72197,EN,CT,United Kingdom,L,United Kingdom,0,"Scala, Kubernetes, Git, GCP, Hadoop",PhD,0,Consulting,2024-12-03,2025-01-25,1844,6.4,Digital Transformation LLC -AI09260,Machine Learning Engineer,33333,USD,33333,MI,PT,India,L,India,50,"Hadoop, Scala, Java",Master,4,Technology,2024-05-26,2024-07-21,1580,8.4,DataVision Ltd -AI09261,Deep Learning Engineer,87092,USD,87092,MI,CT,Ireland,L,Ireland,50,"Hadoop, Git, R, GCP",Bachelor,4,Consulting,2025-02-27,2025-03-31,1789,9,Digital Transformation LLC -AI09262,Research Scientist,146551,USD,146551,EX,FL,Ireland,M,Ireland,0,"AWS, Hadoop, R",Master,16,Energy,2024-10-11,2024-12-16,2266,7,Digital Transformation LLC -AI09263,Robotics Engineer,66231,CAD,82789,EN,PT,Canada,L,Canada,0,"Deep Learning, Spark, TensorFlow",Master,1,Energy,2025-02-03,2025-04-13,1660,5.5,Autonomous Tech -AI09264,Robotics Engineer,145114,AUD,195904,SE,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, NLP",Associate,5,Telecommunications,2024-12-01,2025-02-09,1103,9.5,Autonomous Tech -AI09265,Autonomous Systems Engineer,146269,USD,146269,SE,PT,Sweden,M,Malaysia,0,"NLP, Hadoop, MLOps",Master,7,Finance,2024-12-01,2025-02-05,683,5.6,Quantum Computing Inc -AI09266,Research Scientist,125674,CAD,157093,SE,CT,Canada,L,Ukraine,50,"MLOps, TensorFlow, Mathematics, AWS",Bachelor,9,Government,2025-03-24,2025-05-16,871,8.6,Neural Networks Co -AI09267,Machine Learning Engineer,127447,JPY,14019170,SE,PT,Japan,S,Japan,100,"Java, Kubernetes, SQL",Associate,8,Transportation,2024-02-26,2024-03-27,1801,7.2,Advanced Robotics -AI09268,NLP Engineer,61294,EUR,52100,EN,CT,France,M,France,0,"SQL, Hadoop, Scala, Data Visualization",Bachelor,0,Energy,2024-09-29,2024-10-28,1878,7.2,Cloud AI Solutions -AI09269,ML Ops Engineer,135156,USD,135156,SE,FL,Sweden,S,Sweden,50,"AWS, Linux, SQL",PhD,6,Education,2024-11-09,2024-12-20,1976,8.2,DeepTech Ventures -AI09270,Autonomous Systems Engineer,67394,EUR,57285,EN,FL,Austria,L,Portugal,50,"GCP, PyTorch, SQL",PhD,1,Consulting,2024-06-24,2024-07-31,1455,5.6,DeepTech Ventures -AI09271,Data Scientist,90125,EUR,76606,MI,FL,Germany,M,Germany,0,"Deep Learning, Computer Vision, Linux, SQL",PhD,3,Manufacturing,2024-02-27,2024-03-27,2164,6.7,Machine Intelligence Group -AI09272,Data Engineer,136268,USD,136268,SE,CT,Ireland,L,Ireland,50,"Kubernetes, PyTorch, SQL",PhD,5,Healthcare,2024-04-09,2024-05-26,521,8.3,DataVision Ltd -AI09273,Data Scientist,69814,USD,69814,MI,FL,Finland,M,Portugal,100,"Kubernetes, Linux, Azure, Scala, PyTorch",PhD,2,Healthcare,2024-08-16,2024-10-14,2026,7,TechCorp Inc -AI09274,Robotics Engineer,295783,USD,295783,EX,FT,Denmark,S,Germany,50,"Spark, NLP, Java, PyTorch",Associate,12,Energy,2024-06-03,2024-07-17,2053,10,Cloud AI Solutions -AI09275,Head of AI,85810,JPY,9439100,MI,FL,Japan,M,Japan,100,"Data Visualization, Azure, Python, Kubernetes, Linux",Associate,4,Automotive,2024-10-27,2024-11-23,2108,7.2,Cognitive Computing -AI09276,AI Research Scientist,197095,USD,197095,EX,FL,Finland,S,Finland,0,"R, Statistics, Java",PhD,10,Technology,2025-03-19,2025-04-05,1049,6.7,Advanced Robotics -AI09277,Head of AI,122788,USD,122788,SE,CT,Ireland,S,China,100,"Python, Scala, GCP, TensorFlow",PhD,7,Retail,2024-04-19,2024-06-19,2250,9.2,Algorithmic Solutions -AI09278,Research Scientist,124194,USD,124194,SE,PT,Sweden,S,Sweden,0,"Scala, Git, Docker, Data Visualization, NLP",Master,8,Gaming,2024-01-05,2024-02-24,1663,7.6,DataVision Ltd -AI09279,AI Consultant,58846,USD,58846,MI,CT,South Korea,S,New Zealand,100,"PyTorch, Kubernetes, Linux",PhD,3,Technology,2024-09-02,2024-10-29,1711,5.3,DataVision Ltd -AI09280,Data Engineer,106557,CHF,95901,MI,PT,Switzerland,M,Switzerland,100,"GCP, TensorFlow, Java",Bachelor,3,Telecommunications,2024-11-22,2024-12-10,2401,7.1,Autonomous Tech -AI09281,Research Scientist,128421,EUR,109158,SE,FL,France,S,Germany,0,"PyTorch, Linux, Tableau",Bachelor,9,Gaming,2025-02-26,2025-04-03,2027,7.1,Predictive Systems -AI09282,AI Product Manager,117576,EUR,99940,SE,FL,France,L,Philippines,0,"Python, Deep Learning, Tableau, Kubernetes, GCP",Associate,8,Energy,2024-09-30,2024-11-13,636,9.7,Future Systems -AI09283,AI Specialist,57593,USD,57593,EN,CT,Israel,L,Ukraine,100,"Python, Kubernetes, AWS",Bachelor,0,Real Estate,2024-09-14,2024-09-30,912,6.9,Algorithmic Solutions -AI09284,AI Software Engineer,212215,USD,212215,EX,FL,United States,S,United States,50,"Azure, Git, Hadoop, Spark",Bachelor,16,Finance,2024-10-06,2024-10-21,2111,8.6,TechCorp Inc -AI09285,AI Consultant,135399,CHF,121859,MI,CT,Switzerland,L,Switzerland,100,"Spark, TensorFlow, NLP, Kubernetes",PhD,3,Consulting,2024-04-04,2024-05-28,1618,9.2,Future Systems -AI09286,Machine Learning Researcher,166176,USD,166176,EX,FL,South Korea,L,South Korea,0,"Git, Python, Azure",Associate,15,Gaming,2024-08-08,2024-10-06,1302,7.1,DeepTech Ventures -AI09287,Machine Learning Engineer,144034,GBP,108026,SE,CT,United Kingdom,S,United Kingdom,0,"Git, Docker, R, Statistics",Associate,9,Finance,2024-06-15,2024-07-19,1279,9.7,Neural Networks Co -AI09288,Head of AI,61774,USD,61774,SE,FL,India,L,India,100,"R, Hadoop, Tableau, Java",Master,6,Real Estate,2024-12-05,2025-02-15,2230,7.1,Autonomous Tech -AI09289,Deep Learning Engineer,103881,EUR,88299,SE,FT,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,5,Consulting,2024-07-07,2024-07-27,893,5.4,TechCorp Inc -AI09290,Data Analyst,59689,EUR,50736,EN,CT,France,L,France,100,"Git, R, MLOps, Python",Associate,0,Retail,2024-11-04,2024-11-26,1476,6.6,DeepTech Ventures -AI09291,AI Architect,191160,SGD,248508,EX,FL,Singapore,S,Singapore,50,"R, TensorFlow, Spark, Git",PhD,12,Retail,2024-07-27,2024-09-14,928,6.8,Digital Transformation LLC -AI09292,Data Engineer,89134,USD,89134,MI,CT,United States,S,Netherlands,50,"PyTorch, NLP, Kubernetes, Deep Learning, GCP",Bachelor,3,Technology,2024-10-06,2024-12-08,2234,5.7,Future Systems -AI09293,AI Software Engineer,142040,CAD,177550,EX,CT,Canada,M,Canada,50,"Mathematics, R, Data Visualization, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-04-18,2024-05-31,1401,6.1,Digital Transformation LLC -AI09294,Computer Vision Engineer,67255,USD,67255,MI,PT,Sweden,S,Sweden,100,"Hadoop, Docker, Java, Tableau",PhD,2,Media,2025-04-24,2025-06-12,1670,6.1,Digital Transformation LLC -AI09295,Deep Learning Engineer,186135,USD,186135,EX,FT,Israel,M,Singapore,50,"Hadoop, R, Python, TensorFlow, PyTorch",Master,14,Retail,2024-03-17,2024-04-16,1967,9.8,DeepTech Ventures -AI09296,Machine Learning Engineer,53611,USD,53611,EN,FT,Finland,M,United States,0,"Scala, Python, Deep Learning, Spark, Git",Bachelor,0,Automotive,2024-07-22,2024-08-24,1846,6,Predictive Systems -AI09297,Deep Learning Engineer,94103,USD,94103,MI,FL,Sweden,M,Sweden,100,"Scala, SQL, MLOps, Data Visualization",PhD,3,Gaming,2025-04-20,2025-05-23,1959,8.2,AI Innovations -AI09298,AI Specialist,87733,SGD,114053,EN,FT,Singapore,L,Singapore,100,"Spark, Linux, SQL",Associate,0,Finance,2024-01-02,2024-02-29,632,5.9,Algorithmic Solutions -AI09299,Data Engineer,128376,USD,128376,MI,PT,Denmark,M,Denmark,100,"Python, SQL, PyTorch",Master,2,Healthcare,2024-01-22,2024-03-01,985,8.7,Machine Intelligence Group -AI09300,Head of AI,85553,EUR,72720,MI,FL,Germany,L,Germany,0,"Spark, TensorFlow, Tableau",Master,2,Media,2025-04-23,2025-05-27,934,6.8,DeepTech Ventures -AI09301,Robotics Engineer,165398,EUR,140588,EX,PT,Germany,S,Germany,0,"GCP, Kubernetes, SQL, Deep Learning",Master,10,Real Estate,2025-04-05,2025-05-31,2215,9.7,Autonomous Tech -AI09302,AI Product Manager,111102,GBP,83327,SE,FT,United Kingdom,S,United Kingdom,50,"GCP, Scala, Linux",Bachelor,9,Finance,2024-12-25,2025-01-18,2257,5.5,Cloud AI Solutions -AI09303,Machine Learning Researcher,259032,EUR,220177,EX,FT,Netherlands,L,Netherlands,50,"Python, SQL, R",Associate,18,Government,2025-04-20,2025-07-01,2247,9.6,TechCorp Inc -AI09304,Machine Learning Researcher,64774,EUR,55058,MI,FL,Austria,S,Austria,0,"PyTorch, Hadoop, Computer Vision",PhD,3,Education,2025-02-25,2025-05-06,1421,7.3,Neural Networks Co -AI09305,Data Engineer,221161,EUR,187987,EX,FT,Germany,M,Australia,50,"Computer Vision, TensorFlow, Kubernetes",Bachelor,19,Healthcare,2024-12-24,2025-01-19,725,6.8,Cognitive Computing -AI09306,Deep Learning Engineer,240461,AUD,324622,EX,FT,Australia,L,Australia,50,"Git, SQL, Statistics, Linux",Bachelor,18,Healthcare,2025-03-13,2025-05-14,1914,9,Smart Analytics -AI09307,Data Scientist,95043,SGD,123556,MI,FL,Singapore,S,Singapore,50,"Python, TensorFlow, Tableau",PhD,2,Manufacturing,2024-08-02,2024-10-14,2189,9.3,Advanced Robotics -AI09308,AI Consultant,39308,USD,39308,EN,PT,South Korea,S,Poland,0,"Kubernetes, Git, Deep Learning, TensorFlow, Spark",Associate,1,Transportation,2024-05-06,2024-06-20,1885,7.6,Predictive Systems -AI09309,Machine Learning Engineer,118281,USD,118281,SE,FT,South Korea,L,South Korea,100,"Docker, R, Statistics, Hadoop, GCP",Associate,9,Real Estate,2024-06-06,2024-08-05,2323,7.8,DataVision Ltd -AI09310,Data Analyst,107506,EUR,91380,MI,FT,Netherlands,M,Ireland,100,"Docker, Python, Data Visualization",PhD,3,Education,2024-07-29,2024-09-08,2123,5.7,Smart Analytics -AI09311,AI Architect,161533,USD,161533,EX,FL,Ireland,L,Ireland,100,"Data Visualization, TensorFlow, Git, Deep Learning",Bachelor,14,Energy,2024-08-20,2024-09-29,2120,8,Smart Analytics -AI09312,Machine Learning Researcher,106952,EUR,90909,MI,FL,Germany,M,Germany,0,"Tableau, TensorFlow, Git, Kubernetes, Docker",Bachelor,4,Technology,2025-04-07,2025-05-12,1647,5,TechCorp Inc -AI09313,Machine Learning Researcher,117619,JPY,12938090,MI,PT,Japan,L,Japan,100,"NLP, Python, GCP, Deep Learning, MLOps",Associate,3,Manufacturing,2024-04-17,2024-06-20,1171,7.2,Predictive Systems -AI09314,AI Research Scientist,164714,USD,164714,SE,FT,United States,L,United States,50,"Tableau, Java, Kubernetes",Bachelor,7,Real Estate,2024-07-06,2024-08-17,511,8.5,Machine Intelligence Group -AI09315,AI Software Engineer,55967,USD,55967,EN,FT,South Korea,M,South Korea,50,"Python, NLP, Mathematics",Associate,1,Media,2025-04-21,2025-05-15,2102,5.3,Autonomous Tech -AI09316,Research Scientist,48225,EUR,40991,EN,FT,Germany,S,Germany,100,"Azure, AWS, GCP, Git",PhD,1,Transportation,2024-04-11,2024-05-03,1919,5.3,Machine Intelligence Group -AI09317,Machine Learning Researcher,99314,USD,99314,MI,CT,United States,S,United States,50,"Statistics, Git, Kubernetes",Master,2,Automotive,2024-08-26,2024-10-06,1365,7,Quantum Computing Inc -AI09318,Research Scientist,61925,CAD,77406,MI,FT,Canada,S,Canada,50,"Git, Azure, Tableau, MLOps",Master,4,Finance,2024-08-06,2024-09-29,2038,9.6,Future Systems -AI09319,AI Research Scientist,64161,SGD,83409,EN,CT,Singapore,M,Singapore,100,"GCP, Hadoop, Docker, Computer Vision",Bachelor,0,Government,2024-09-17,2024-10-15,1222,7.1,Machine Intelligence Group -AI09320,Machine Learning Engineer,59904,USD,59904,SE,CT,China,L,China,100,"Kubernetes, Scala, Tableau",Bachelor,8,Manufacturing,2024-12-26,2025-02-28,942,9.9,Digital Transformation LLC -AI09321,AI Architect,84843,EUR,72117,MI,CT,Austria,L,Austria,50,"PyTorch, Git, Scala",Master,2,Media,2024-02-17,2024-03-11,1296,7.5,Autonomous Tech -AI09322,NLP Engineer,116882,EUR,99350,MI,FL,Netherlands,M,Ukraine,100,"Java, Kubernetes, Azure, Computer Vision",Associate,2,Transportation,2024-03-22,2024-05-14,893,7.7,Autonomous Tech -AI09323,Robotics Engineer,41992,USD,41992,MI,FT,India,L,India,0,"PyTorch, Deep Learning, Mathematics, Spark",Bachelor,4,Finance,2024-11-26,2025-01-09,556,6.6,Algorithmic Solutions -AI09324,Data Scientist,83559,USD,83559,MI,FT,Ireland,L,Singapore,100,"TensorFlow, SQL, Mathematics, Tableau, AWS",Bachelor,3,Government,2025-01-06,2025-02-19,1509,8.9,Advanced Robotics -AI09325,Machine Learning Engineer,165796,USD,165796,EX,FL,Ireland,L,Ireland,100,"Kubernetes, Docker, R, Tableau",Master,15,Government,2025-04-02,2025-04-28,1526,6.8,Quantum Computing Inc -AI09326,Data Scientist,27209,USD,27209,MI,PT,India,S,India,50,"Python, Computer Vision, Data Visualization, TensorFlow, Docker",PhD,2,Transportation,2024-06-06,2024-07-31,627,6.7,Neural Networks Co -AI09327,AI Specialist,238785,EUR,202967,EX,FT,France,L,Ghana,50,"Azure, Python, TensorFlow, MLOps, Computer Vision",PhD,19,Automotive,2024-05-14,2024-06-21,1303,9.7,Predictive Systems -AI09328,AI Specialist,36971,USD,36971,SE,PT,India,S,Argentina,0,"AWS, Tableau, Spark, Mathematics, Computer Vision",PhD,5,Education,2024-03-14,2024-04-06,1849,5.7,Cloud AI Solutions -AI09329,Deep Learning Engineer,281022,USD,281022,EX,FT,Norway,S,Netherlands,100,"Python, Data Visualization, Spark",PhD,12,Retail,2025-04-18,2025-06-15,1583,7,Predictive Systems -AI09330,AI Architect,69740,JPY,7671400,EN,CT,Japan,S,Japan,0,"NLP, GCP, Mathematics, Kubernetes",PhD,1,Education,2024-02-13,2024-04-14,1821,9.8,Algorithmic Solutions -AI09331,AI Architect,117773,USD,117773,MI,FT,United States,M,United States,100,"Hadoop, PyTorch, GCP, AWS",PhD,4,Real Estate,2025-02-28,2025-03-25,1720,6.3,Machine Intelligence Group -AI09332,Research Scientist,149573,USD,149573,EX,FT,Israel,S,Israel,0,"Python, GCP, Hadoop",Master,17,Government,2024-08-06,2024-10-03,1603,8,DeepTech Ventures -AI09333,Machine Learning Researcher,115785,GBP,86839,MI,CT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, Kubernetes, Scala, Hadoop",PhD,4,Automotive,2024-09-18,2024-10-09,1354,5,Predictive Systems -AI09334,Head of AI,155051,JPY,17055610,EX,FT,Japan,S,Estonia,0,"Hadoop, GCP, Linux",Bachelor,14,Technology,2025-04-04,2025-06-02,2362,8,Autonomous Tech -AI09335,AI Software Engineer,69683,SGD,90588,EN,CT,Singapore,M,Singapore,50,"NLP, SQL, Kubernetes",Bachelor,0,Gaming,2024-05-20,2024-06-10,860,5.3,Autonomous Tech -AI09336,Machine Learning Engineer,63898,USD,63898,EN,CT,Ireland,S,Ireland,100,"Mathematics, MLOps, GCP",Associate,0,Technology,2024-07-13,2024-08-04,1335,6.3,Digital Transformation LLC -AI09337,NLP Engineer,91901,USD,91901,MI,FL,Sweden,M,Sweden,0,"PyTorch, Mathematics, Kubernetes",PhD,4,Finance,2024-06-28,2024-09-07,641,7.8,Autonomous Tech -AI09338,AI Consultant,59695,EUR,50741,EN,FT,France,S,Ghana,100,"R, GCP, PyTorch, AWS",Master,1,Automotive,2024-10-04,2024-10-29,1315,7,Future Systems -AI09339,Data Engineer,65038,GBP,48779,EN,PT,United Kingdom,S,United Kingdom,50,"Docker, Python, Computer Vision, R",Master,0,Real Estate,2024-06-03,2024-08-10,1902,8.5,AI Innovations -AI09340,AI Consultant,86847,USD,86847,MI,FT,Finland,M,Finland,100,"Scala, MLOps, Java",Bachelor,2,Real Estate,2025-03-20,2025-05-08,2066,9,Advanced Robotics -AI09341,Deep Learning Engineer,34236,USD,34236,MI,FT,China,M,China,0,"TensorFlow, R, Linux",Associate,4,Telecommunications,2024-04-18,2024-06-01,2369,5.6,AI Innovations -AI09342,AI Consultant,160503,EUR,136428,SE,FL,France,L,Australia,50,"AWS, Python, Data Visualization",Bachelor,8,Government,2024-12-05,2025-01-07,1991,7,Algorithmic Solutions -AI09343,Machine Learning Engineer,120317,USD,120317,SE,FT,Israel,M,Israel,50,"SQL, Docker, TensorFlow, Linux, Tableau",Bachelor,6,Education,2025-01-05,2025-02-20,1725,9.6,Neural Networks Co -AI09344,Principal Data Scientist,79295,EUR,67401,EN,PT,France,L,France,100,"GCP, SQL, Scala, Python",Master,0,Real Estate,2024-04-13,2024-06-15,2373,6.9,Quantum Computing Inc -AI09345,Principal Data Scientist,57136,EUR,48566,EN,PT,Austria,M,United States,50,"Linux, Scala, TensorFlow",Master,0,Real Estate,2024-02-23,2024-04-03,1669,6.7,Autonomous Tech -AI09346,Research Scientist,109133,USD,109133,SE,PT,Israel,M,Israel,0,"Java, R, Statistics, SQL",PhD,8,Telecommunications,2025-03-17,2025-05-02,2042,8.7,Smart Analytics -AI09347,Machine Learning Engineer,226278,CHF,203650,EX,FT,Switzerland,M,Switzerland,50,"Mathematics, Scala, Azure",PhD,15,Media,2025-01-20,2025-03-29,1514,9.2,Autonomous Tech -AI09348,ML Ops Engineer,67762,USD,67762,EN,FT,Finland,S,Finland,100,"Kubernetes, Data Visualization, MLOps, Python",Associate,0,Gaming,2024-11-21,2024-12-10,1779,8.1,DeepTech Ventures -AI09349,Research Scientist,158626,USD,158626,SE,FT,Norway,S,Norway,0,"Python, Scala, Java, TensorFlow",PhD,9,Government,2024-06-23,2024-07-12,1918,5.6,Smart Analytics -AI09350,Research Scientist,35902,USD,35902,MI,FT,India,M,Philippines,0,"Linux, Spark, Data Visualization, Java, Mathematics",Bachelor,2,Finance,2024-05-30,2024-08-04,2143,6.3,Future Systems -AI09351,AI Specialist,199630,EUR,169686,EX,FL,France,S,France,100,"Linux, Hadoop, Data Visualization, MLOps",Associate,19,Retail,2024-03-14,2024-04-28,2431,6.4,Cognitive Computing -AI09352,ML Ops Engineer,34288,USD,34288,MI,PT,India,L,Austria,0,"Python, AWS, SQL, Data Visualization",Associate,3,Telecommunications,2024-12-29,2025-02-20,688,8.8,Autonomous Tech -AI09353,AI Consultant,64165,USD,64165,EN,PT,Finland,L,Finland,100,"Kubernetes, Deep Learning, Data Visualization, Python",Master,0,Healthcare,2024-02-23,2024-04-20,2185,5.9,Quantum Computing Inc -AI09354,AI Architect,68161,CAD,85201,EN,CT,Canada,L,Canada,100,"Scala, Azure, Statistics, Linux, PyTorch",PhD,1,Transportation,2024-08-25,2024-10-29,1318,5.2,Machine Intelligence Group -AI09355,Deep Learning Engineer,190540,AUD,257229,EX,PT,Australia,S,Australia,100,"SQL, Azure, Scala, Tableau, Spark",Associate,17,Automotive,2025-01-23,2025-02-11,1879,5.1,Digital Transformation LLC -AI09356,AI Consultant,145966,USD,145966,EX,FT,South Korea,S,South Korea,50,"PyTorch, TensorFlow, Python",Bachelor,13,Media,2024-10-09,2024-12-02,2054,8.6,Autonomous Tech -AI09357,AI Research Scientist,64339,USD,64339,MI,PT,South Korea,S,Belgium,0,"Java, R, Python, AWS",Associate,2,Consulting,2024-07-13,2024-08-18,632,6.7,Advanced Robotics -AI09358,Computer Vision Engineer,72089,GBP,54067,EN,FT,United Kingdom,L,Ireland,50,"Deep Learning, Scala, Statistics, Computer Vision, Docker",PhD,0,Finance,2025-02-18,2025-04-30,2314,6.2,TechCorp Inc -AI09359,Data Scientist,121917,USD,121917,MI,PT,Sweden,L,China,100,"PyTorch, Hadoop, Java, Kubernetes, MLOps",PhD,4,Finance,2024-01-15,2024-02-28,794,9.3,Advanced Robotics -AI09360,Computer Vision Engineer,62465,EUR,53095,EN,CT,Netherlands,M,Japan,0,"Python, AWS, Mathematics, SQL, Java",Associate,1,Energy,2024-01-29,2024-03-21,595,8.6,Autonomous Tech -AI09361,AI Consultant,120168,JPY,13218480,SE,PT,Japan,S,Japan,50,"Statistics, Computer Vision, Kubernetes, TensorFlow",Associate,9,Healthcare,2025-02-18,2025-04-10,781,9.7,Predictive Systems -AI09362,Data Scientist,74225,EUR,63091,MI,FL,France,S,France,100,"R, Git, Scala, Kubernetes",PhD,4,Manufacturing,2024-12-20,2025-02-05,524,7,DeepTech Ventures -AI09363,Head of AI,86630,USD,86630,SE,CT,Israel,S,Czech Republic,100,"Statistics, R, Kubernetes, Computer Vision, SQL",Bachelor,8,Education,2024-09-16,2024-11-19,2024,5.3,AI Innovations -AI09364,Data Analyst,45119,USD,45119,MI,FT,China,S,New Zealand,100,"Kubernetes, Python, Statistics, GCP",Master,4,Gaming,2024-09-15,2024-11-23,2360,5.9,DataVision Ltd -AI09365,Data Analyst,70424,USD,70424,SE,FL,China,M,China,100,"AWS, Docker, GCP, Python",Master,6,Manufacturing,2024-08-11,2024-09-30,1551,5.1,DeepTech Ventures -AI09366,Data Scientist,124107,EUR,105491,SE,PT,France,S,France,0,"Spark, Java, NLP, Computer Vision",Bachelor,7,Finance,2024-02-14,2024-03-08,1939,6.9,Machine Intelligence Group -AI09367,Machine Learning Researcher,104599,CHF,94139,MI,FL,Switzerland,S,Israel,0,"Hadoop, Scala, Deep Learning, NLP, TensorFlow",Master,2,Government,2024-07-05,2024-08-23,1948,9,TechCorp Inc -AI09368,AI Product Manager,130443,SGD,169576,SE,PT,Singapore,M,Singapore,50,"Deep Learning, MLOps, Git, SQL, Kubernetes",Bachelor,7,Finance,2024-09-18,2024-10-02,947,8.5,Cognitive Computing -AI09369,Machine Learning Engineer,51380,USD,51380,SE,PT,China,M,Turkey,100,"Linux, Spark, Kubernetes",Bachelor,7,Manufacturing,2024-04-27,2024-06-30,1994,7.2,Algorithmic Solutions -AI09370,ML Ops Engineer,55972,EUR,47576,EN,PT,France,S,Egypt,100,"Linux, Python, Deep Learning, AWS",Associate,0,Telecommunications,2024-01-13,2024-03-01,1786,6.9,Machine Intelligence Group -AI09371,AI Specialist,140112,EUR,119095,EX,PT,Austria,M,Kenya,100,"Linux, R, Data Visualization",PhD,10,Real Estate,2024-07-03,2024-08-18,991,6.3,DeepTech Ventures -AI09372,Research Scientist,77842,EUR,66166,EN,FL,Netherlands,M,Netherlands,100,"Statistics, Hadoop, Python",Master,1,Healthcare,2024-05-09,2024-07-14,1380,5,Cloud AI Solutions -AI09373,Data Analyst,143720,USD,143720,EX,FL,South Korea,M,Ukraine,50,"Scala, AWS, Azure, Computer Vision, Statistics",Associate,16,Technology,2024-06-09,2024-07-23,566,6.9,Cognitive Computing -AI09374,Machine Learning Engineer,93910,USD,93910,MI,CT,South Korea,L,Netherlands,100,"GCP, NLP, Data Visualization, Python, Linux",Master,2,Consulting,2024-12-31,2025-02-27,748,9.8,Autonomous Tech -AI09375,NLP Engineer,92622,JPY,10188420,MI,CT,Japan,M,Estonia,50,"Statistics, Kubernetes, R, Scala",Associate,2,Healthcare,2024-05-09,2024-06-26,508,8.6,Cognitive Computing -AI09376,Data Analyst,207950,USD,207950,EX,FL,Ireland,S,Portugal,0,"Hadoop, GCP, Statistics, Deep Learning",Bachelor,16,Gaming,2024-05-17,2024-06-21,823,5.1,Cognitive Computing -AI09377,AI Research Scientist,52390,CAD,65488,EN,FT,Canada,S,Ireland,50,"Deep Learning, Python, Docker",Master,0,Finance,2024-06-29,2024-08-19,818,8.7,Smart Analytics -AI09378,NLP Engineer,72765,EUR,61850,MI,FT,Germany,S,Germany,50,"AWS, Kubernetes, GCP, NLP",PhD,4,Telecommunications,2024-06-13,2024-08-25,604,9.9,Quantum Computing Inc -AI09379,Robotics Engineer,95125,EUR,80856,SE,PT,France,S,Turkey,0,"Python, Java, Kubernetes, TensorFlow, Docker",Master,7,Media,2024-09-06,2024-11-12,1188,6.3,DataVision Ltd -AI09380,Data Analyst,86783,USD,86783,EX,CT,China,S,China,50,"Kubernetes, Java, MLOps",Associate,10,Real Estate,2025-01-16,2025-02-23,1979,5.6,Predictive Systems -AI09381,Principal Data Scientist,195942,SGD,254725,EX,CT,Singapore,S,Singapore,50,"PyTorch, Python, Linux, Mathematics",Bachelor,18,Automotive,2024-02-24,2024-05-05,2119,9.8,Algorithmic Solutions -AI09382,AI Architect,88045,USD,88045,SE,PT,Finland,S,Finland,0,"AWS, Kubernetes, Java, GCP, Azure",Master,8,Media,2024-05-24,2024-06-10,1613,6.5,DataVision Ltd -AI09383,ML Ops Engineer,34080,USD,34080,EN,PT,China,S,China,100,"Python, Tableau, Statistics, Deep Learning",Associate,0,Telecommunications,2024-08-15,2024-08-30,858,6.4,Algorithmic Solutions -AI09384,Machine Learning Researcher,159791,AUD,215718,SE,CT,Australia,L,Australia,0,"TensorFlow, Mathematics, Data Visualization, Linux",Associate,9,Media,2024-11-05,2025-01-12,1415,5.4,Smart Analytics -AI09385,Computer Vision Engineer,82207,EUR,69876,MI,CT,Germany,M,Germany,100,"Kubernetes, Java, Docker, R, Statistics",Master,2,Telecommunications,2024-08-18,2024-10-28,2049,6.4,DataVision Ltd -AI09386,Computer Vision Engineer,121634,USD,121634,SE,CT,South Korea,M,Argentina,50,"R, SQL, Data Visualization",Master,6,Healthcare,2025-02-04,2025-03-25,1979,8.6,Smart Analytics -AI09387,AI Research Scientist,29142,USD,29142,EN,CT,India,L,India,0,"Linux, Hadoop, Data Visualization, Spark",Bachelor,1,Technology,2024-10-18,2024-11-13,2226,5.3,Advanced Robotics -AI09388,AI Software Engineer,62502,JPY,6875220,EN,PT,Japan,L,Japan,100,"Kubernetes, Python, Spark, Docker, Git",Bachelor,0,Gaming,2025-01-22,2025-03-06,1769,6.4,DeepTech Ventures -AI09389,NLP Engineer,106016,USD,106016,EX,PT,South Korea,S,South Korea,100,"Mathematics, Python, Statistics, Git, TensorFlow",Master,18,Energy,2025-03-19,2025-05-26,658,9,Algorithmic Solutions -AI09390,Machine Learning Engineer,223388,USD,223388,EX,FT,United States,S,United States,0,"Python, Spark, TensorFlow, GCP, PyTorch",Bachelor,13,Retail,2024-04-13,2024-05-02,776,7.7,Autonomous Tech -AI09391,AI Product Manager,260456,JPY,28650160,EX,CT,Japan,L,Poland,50,"Hadoop, Deep Learning, Tableau",Bachelor,13,Manufacturing,2024-04-11,2024-05-12,1344,6.3,Advanced Robotics -AI09392,Deep Learning Engineer,122043,AUD,164758,SE,FL,Australia,S,Malaysia,100,"SQL, R, Python, Statistics",PhD,9,Government,2025-04-14,2025-05-26,528,8.4,Autonomous Tech -AI09393,AI Software Engineer,79246,EUR,67359,MI,CT,Germany,S,Germany,50,"Kubernetes, Deep Learning, Java, Azure, R",Associate,4,Media,2025-01-18,2025-03-04,1975,8.8,AI Innovations -AI09394,AI Specialist,200872,GBP,150654,EX,PT,United Kingdom,L,Sweden,100,"Computer Vision, Statistics, Docker",Associate,14,Technology,2024-06-26,2024-09-05,2354,5.4,TechCorp Inc -AI09395,Head of AI,103261,AUD,139402,SE,FL,Australia,M,Australia,0,"Docker, SQL, Azure, AWS",Bachelor,5,Gaming,2025-03-11,2025-04-08,1989,10,Cloud AI Solutions -AI09396,AI Software Engineer,56852,USD,56852,EN,FT,Sweden,S,Sweden,50,"Git, Computer Vision, Data Visualization",Associate,1,Consulting,2024-02-26,2024-04-12,1249,8,Digital Transformation LLC -AI09397,Data Engineer,87803,AUD,118534,MI,CT,Australia,L,Australia,100,"PyTorch, GCP, Java, Docker, Tableau",Associate,4,Automotive,2024-10-23,2024-12-02,1156,7.5,TechCorp Inc -AI09398,ML Ops Engineer,63510,USD,63510,EN,FL,Israel,L,Israel,50,"SQL, Azure, TensorFlow, Computer Vision, R",Associate,1,Consulting,2025-04-14,2025-04-28,1830,7.1,DataVision Ltd -AI09399,Deep Learning Engineer,92068,USD,92068,EN,PT,United States,M,United States,50,"MLOps, Kubernetes, Python",Associate,1,Telecommunications,2024-10-03,2024-11-21,2475,6.3,Algorithmic Solutions -AI09400,NLP Engineer,75818,GBP,56864,MI,FL,United Kingdom,S,United States,100,"PyTorch, Java, AWS, GCP, TensorFlow",Associate,4,Technology,2025-01-17,2025-03-13,2063,6.9,Autonomous Tech -AI09401,Deep Learning Engineer,120141,USD,120141,SE,PT,Ireland,S,Malaysia,0,"Java, GCP, Python, Linux, MLOps",PhD,6,Media,2024-04-14,2024-06-16,2469,7.6,Quantum Computing Inc -AI09402,Principal Data Scientist,77151,USD,77151,MI,PT,Sweden,S,Sweden,50,"Linux, Statistics, Java",PhD,2,Automotive,2025-03-17,2025-05-05,1385,5.3,AI Innovations -AI09403,Principal Data Scientist,69108,USD,69108,MI,CT,South Korea,S,Turkey,0,"Python, GCP, TensorFlow, Data Visualization",Master,4,Consulting,2024-04-28,2024-05-23,2108,6.2,Quantum Computing Inc -AI09404,Machine Learning Researcher,209966,EUR,178471,EX,PT,France,L,Finland,100,"Linux, Azure, Kubernetes, Docker, Git",PhD,19,Real Estate,2024-06-30,2024-08-14,937,9,Algorithmic Solutions -AI09405,Robotics Engineer,75780,USD,75780,EN,PT,Ireland,M,Ireland,0,"MLOps, PyTorch, Mathematics, Kubernetes",Associate,1,Retail,2024-03-28,2024-05-03,1240,9.9,Future Systems -AI09406,AI Product Manager,59033,AUD,79695,EN,PT,Australia,L,Egypt,50,"Python, NLP, Tableau, TensorFlow",Master,0,Gaming,2025-02-01,2025-03-29,1668,8.1,Future Systems -AI09407,Data Engineer,173659,USD,173659,EX,CT,Ireland,M,Ireland,100,"Hadoop, Statistics, TensorFlow, Spark",PhD,15,Technology,2024-11-21,2025-01-29,1737,7.4,DataVision Ltd -AI09408,AI Architect,218617,USD,218617,EX,FT,Ireland,S,Ireland,50,"MLOps, Git, AWS, Docker",Bachelor,18,Consulting,2025-04-13,2025-06-08,878,6.9,AI Innovations -AI09409,AI Consultant,51900,USD,51900,SE,PT,India,M,South Africa,100,"Git, Python, MLOps",Bachelor,6,Gaming,2024-04-11,2024-06-06,1782,8.4,Digital Transformation LLC -AI09410,Autonomous Systems Engineer,83722,EUR,71164,MI,FT,Germany,S,Germany,100,"Git, Linux, Data Visualization",PhD,4,Real Estate,2025-04-14,2025-06-16,1176,9.3,TechCorp Inc -AI09411,ML Ops Engineer,64831,CAD,81039,EN,FL,Canada,S,Kenya,50,"NLP, Python, SQL, Linux, GCP",Master,1,Transportation,2024-05-16,2024-07-20,1981,5.5,Algorithmic Solutions -AI09412,AI Research Scientist,80478,JPY,8852580,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, GCP, Java, PyTorch",Master,1,Telecommunications,2024-06-15,2024-08-12,1157,9.6,AI Innovations -AI09413,Machine Learning Engineer,152682,CHF,137414,MI,FL,Switzerland,M,Switzerland,100,"Linux, Docker, R",Bachelor,2,Education,2025-01-22,2025-02-08,2221,7.8,Neural Networks Co -AI09414,Research Scientist,73388,USD,73388,EN,FT,Israel,M,Israel,0,"Hadoop, GCP, Data Visualization, Java, MLOps",Bachelor,0,Education,2025-01-22,2025-03-13,998,7.2,Advanced Robotics -AI09415,Head of AI,191472,AUD,258487,EX,FL,Australia,S,Belgium,0,"Azure, Java, TensorFlow, Linux, Git",Master,18,Automotive,2024-12-07,2025-02-06,654,9.3,Cognitive Computing -AI09416,AI Architect,111011,USD,111011,SE,FT,South Korea,M,South Korea,0,"Data Visualization, Linux, Python, Statistics, Mathematics",Master,5,Energy,2025-03-16,2025-05-28,2347,6.7,Digital Transformation LLC -AI09417,Machine Learning Researcher,61781,JPY,6795910,EN,FT,Japan,M,Singapore,100,"Linux, GCP, MLOps",Bachelor,0,Retail,2025-04-08,2025-05-21,548,8.5,DataVision Ltd -AI09418,NLP Engineer,194729,EUR,165520,EX,FT,France,M,France,50,"Mathematics, Java, Data Visualization",Master,13,Consulting,2024-08-04,2024-09-18,510,8.4,Quantum Computing Inc -AI09419,AI Product Manager,100526,EUR,85447,MI,CT,Netherlands,S,Netherlands,100,"Scala, Docker, Data Visualization",Master,3,Media,2024-06-04,2024-07-03,1421,7.6,DataVision Ltd -AI09420,Data Analyst,92755,USD,92755,MI,CT,Israel,L,Israel,0,"SQL, PyTorch, Azure, Git, R",Master,4,Finance,2024-08-15,2024-10-19,2437,9.7,Cloud AI Solutions -AI09421,Robotics Engineer,97289,GBP,72967,SE,PT,United Kingdom,S,United Kingdom,50,"NLP, AWS, Java",Bachelor,8,Automotive,2024-09-12,2024-09-30,1299,5.1,Autonomous Tech -AI09422,Machine Learning Engineer,153741,USD,153741,EX,FL,South Korea,L,South Korea,100,"Java, Deep Learning, Data Visualization",Bachelor,10,Retail,2024-09-19,2024-10-23,1707,6.7,DeepTech Ventures -AI09423,Head of AI,157987,SGD,205383,EX,CT,Singapore,M,Singapore,50,"Azure, Docker, Tableau",Bachelor,18,Healthcare,2024-02-18,2024-03-14,2161,9.1,Advanced Robotics -AI09424,AI Architect,120516,CHF,108464,MI,PT,Switzerland,M,Norway,50,"Linux, SQL, Computer Vision, Kubernetes",Master,3,Telecommunications,2024-08-26,2024-09-20,657,5.5,DataVision Ltd -AI09425,AI Specialist,203853,EUR,173275,EX,PT,Netherlands,L,Netherlands,50,"Spark, Scala, GCP",PhD,18,Real Estate,2024-03-20,2024-04-27,1169,7.2,Future Systems -AI09426,Data Scientist,142413,USD,142413,SE,CT,Finland,M,Finland,100,"TensorFlow, Python, Scala, Azure, MLOps",Associate,7,Retail,2024-12-04,2025-01-10,1806,8.3,Neural Networks Co -AI09427,Head of AI,173201,CHF,155881,SE,FL,Switzerland,S,Switzerland,100,"Computer Vision, Hadoop, Python",PhD,6,Finance,2024-07-02,2024-07-28,1290,8.9,Machine Intelligence Group -AI09428,Autonomous Systems Engineer,204387,CAD,255484,EX,FL,Canada,S,Thailand,50,"Computer Vision, TensorFlow, NLP, Python, Data Visualization",Associate,13,Government,2025-01-08,2025-02-03,1275,5.7,Algorithmic Solutions -AI09429,AI Specialist,24626,USD,24626,EN,PT,India,S,India,50,"Azure, Spark, SQL, Docker, Hadoop",Bachelor,0,Energy,2024-10-25,2024-12-14,2213,6.7,Cognitive Computing -AI09430,Data Engineer,30632,USD,30632,MI,FL,China,S,United States,100,"Docker, Python, GCP, TensorFlow, AWS",Bachelor,3,Technology,2025-02-03,2025-03-09,2442,7.1,Cognitive Computing -AI09431,Data Scientist,51880,CAD,64850,EN,FT,Canada,S,Canada,0,"R, PyTorch, Hadoop",PhD,1,Government,2024-11-23,2025-01-16,1334,8.9,Quantum Computing Inc -AI09432,Autonomous Systems Engineer,105546,USD,105546,SE,CT,Ireland,M,Ireland,0,"Data Visualization, Mathematics, Java, Computer Vision, Scala",Bachelor,5,Manufacturing,2024-07-06,2024-08-07,1958,9.4,TechCorp Inc -AI09433,AI Product Manager,156352,EUR,132899,EX,FT,France,S,France,100,"R, Scala, Computer Vision",Associate,18,Consulting,2024-09-17,2024-10-20,1481,7.5,TechCorp Inc -AI09434,Autonomous Systems Engineer,82869,USD,82869,MI,PT,Sweden,S,Sweden,0,"Hadoop, MLOps, Git",Master,4,Gaming,2024-04-10,2024-06-07,2048,5.3,AI Innovations -AI09435,Robotics Engineer,249284,EUR,211891,EX,PT,Germany,L,Finland,50,"Data Visualization, Hadoop, Statistics",Master,10,Education,2025-02-17,2025-04-19,1549,6.4,DeepTech Ventures -AI09436,AI Consultant,143332,EUR,121832,EX,FT,France,S,South Africa,50,"TensorFlow, Computer Vision, MLOps, Tableau, Kubernetes",Master,12,Telecommunications,2024-03-27,2024-05-14,1786,5.1,Cognitive Computing -AI09437,Data Analyst,102445,USD,102445,MI,CT,Denmark,S,Denmark,50,"SQL, Scala, AWS",Master,3,Consulting,2024-12-01,2025-02-06,1144,8.9,Predictive Systems -AI09438,Computer Vision Engineer,95141,CAD,118926,SE,PT,Canada,S,Netherlands,0,"SQL, PyTorch, R, Mathematics",Bachelor,5,Gaming,2024-07-05,2024-08-10,1531,9.4,Autonomous Tech -AI09439,Computer Vision Engineer,85527,EUR,72698,MI,FL,France,S,France,0,"Linux, R, Statistics, Kubernetes",Bachelor,2,Healthcare,2024-02-19,2024-04-28,543,9.9,DataVision Ltd -AI09440,Autonomous Systems Engineer,84275,EUR,71634,MI,CT,Austria,L,Austria,100,"Git, Linux, Python",Master,4,Healthcare,2024-11-01,2024-11-23,1865,6.5,Digital Transformation LLC -AI09441,Data Analyst,171765,USD,171765,EX,FL,Finland,S,Finland,100,"Tableau, NLP, Hadoop, Python",Master,10,Manufacturing,2024-07-29,2024-08-21,2398,6.2,Cognitive Computing -AI09442,Robotics Engineer,47657,USD,47657,MI,FT,China,L,China,0,"Computer Vision, Kubernetes, Java",Bachelor,4,Transportation,2025-04-26,2025-07-06,1427,6.5,Cloud AI Solutions -AI09443,Robotics Engineer,54748,USD,54748,EN,PT,Israel,S,Israel,50,"PyTorch, AWS, Data Visualization, GCP",Master,0,Education,2024-05-28,2024-07-31,2405,7.4,Future Systems -AI09444,Data Scientist,47134,AUD,63631,EN,FL,Australia,S,United Kingdom,50,"NLP, Statistics, Kubernetes, Python, GCP",PhD,0,Healthcare,2024-06-28,2024-08-26,613,6.1,DataVision Ltd -AI09445,ML Ops Engineer,84635,AUD,114257,MI,CT,Australia,L,Australia,100,"Kubernetes, SQL, Java, Git",PhD,3,Technology,2024-03-25,2024-05-30,1487,5.6,Future Systems -AI09446,ML Ops Engineer,84203,EUR,71573,MI,FL,France,L,France,100,"PyTorch, Mathematics, Scala",PhD,3,Real Estate,2025-02-26,2025-04-17,2353,6.5,Predictive Systems -AI09447,AI Product Manager,105870,EUR,89990,MI,PT,Netherlands,L,Netherlands,100,"Python, Linux, TensorFlow, Hadoop, PyTorch",Bachelor,4,Automotive,2024-07-29,2024-10-04,1615,5.4,DataVision Ltd -AI09448,AI Architect,66252,USD,66252,EX,CT,China,M,Russia,0,"Statistics, PyTorch, Tableau",Master,16,Healthcare,2024-11-30,2024-12-26,897,9.8,Neural Networks Co -AI09449,Data Engineer,91263,USD,91263,MI,FT,Finland,M,Finland,0,"GCP, PyTorch, Deep Learning, Mathematics, Computer Vision",Master,4,Finance,2024-10-01,2024-11-09,1366,7.7,Digital Transformation LLC -AI09450,Machine Learning Researcher,69243,USD,69243,EN,FT,Israel,M,Israel,50,"Azure, Python, SQL, Tableau, TensorFlow",Master,0,Manufacturing,2024-10-10,2024-12-16,689,6.2,TechCorp Inc -AI09451,Principal Data Scientist,137522,USD,137522,SE,PT,Ireland,M,France,100,"AWS, Tableau, Python",Bachelor,7,Government,2024-07-07,2024-07-28,709,6.8,Digital Transformation LLC -AI09452,NLP Engineer,266422,GBP,199817,EX,FT,United Kingdom,L,United Kingdom,50,"R, AWS, Data Visualization",PhD,11,Gaming,2024-03-29,2024-05-03,817,7.1,DeepTech Ventures -AI09453,Machine Learning Researcher,199823,EUR,169850,EX,PT,France,S,France,50,"Java, MLOps, GCP, AWS, PyTorch",Associate,12,Media,2024-02-25,2024-03-31,2329,6.6,Machine Intelligence Group -AI09454,NLP Engineer,69686,USD,69686,EN,CT,Ireland,M,Ireland,100,"Data Visualization, SQL, NLP, Kubernetes, Python",Associate,0,Real Estate,2025-01-25,2025-02-15,1109,7,Autonomous Tech -AI09455,Principal Data Scientist,173317,USD,173317,EX,FT,Denmark,S,Denmark,50,"TensorFlow, Scala, Statistics",PhD,18,Technology,2024-12-17,2025-02-23,1801,8.7,Future Systems -AI09456,Robotics Engineer,181014,EUR,153862,EX,FT,Austria,S,Austria,0,"Kubernetes, GCP, Python, Mathematics",PhD,18,Retail,2024-11-16,2025-01-05,1255,6,Predictive Systems -AI09457,AI Research Scientist,262405,USD,262405,EX,PT,Finland,L,Finland,0,"Deep Learning, Python, Azure, SQL",Master,19,Finance,2024-03-31,2024-05-27,2116,8.8,Machine Intelligence Group -AI09458,Data Engineer,109773,JPY,12075030,MI,FT,Japan,M,Vietnam,50,"Python, Tableau, Computer Vision",Bachelor,2,Gaming,2025-01-06,2025-02-25,2433,5.7,TechCorp Inc -AI09459,Data Scientist,81338,CAD,101673,EN,FL,Canada,L,Canada,0,"MLOps, Data Visualization, AWS, Python, TensorFlow",Bachelor,1,Healthcare,2025-01-23,2025-03-30,550,7.2,DataVision Ltd -AI09460,AI Research Scientist,147302,SGD,191493,SE,PT,Singapore,M,Singapore,0,"SQL, AWS, Kubernetes, Hadoop",Associate,5,Education,2024-05-27,2024-07-17,1214,7.5,Advanced Robotics -AI09461,Data Scientist,89314,CAD,111643,MI,PT,Canada,L,Romania,0,"Python, TensorFlow, Data Visualization, Git, Statistics",PhD,3,Technology,2024-01-25,2024-03-12,590,9.3,DataVision Ltd -AI09462,Head of AI,131205,USD,131205,SE,CT,Ireland,L,Ireland,0,"R, Python, TensorFlow, Java",Associate,8,Finance,2024-10-17,2024-12-12,1799,7.1,Cognitive Computing -AI09463,ML Ops Engineer,236960,EUR,201416,EX,FT,Netherlands,S,Netherlands,50,"Data Visualization, R, Linux, Tableau",Associate,12,Media,2024-05-12,2024-07-10,1716,9.1,Neural Networks Co -AI09464,Research Scientist,70521,EUR,59943,EN,FL,Netherlands,M,Nigeria,50,"Git, Python, TensorFlow",Bachelor,1,Telecommunications,2024-09-23,2024-11-21,2406,9.2,Advanced Robotics -AI09465,NLP Engineer,22718,USD,22718,EN,CT,India,M,India,100,"Computer Vision, SQL, Python",PhD,1,Consulting,2025-04-28,2025-06-01,2464,6.6,AI Innovations -AI09466,Autonomous Systems Engineer,302715,USD,302715,EX,PT,Norway,L,New Zealand,0,"Tableau, Python, NLP, Git, MLOps",PhD,12,Technology,2025-01-28,2025-02-21,655,8.2,Future Systems -AI09467,Data Engineer,148771,USD,148771,SE,FL,Finland,L,Finland,100,"PyTorch, GCP, TensorFlow, AWS, Deep Learning",Master,8,Education,2024-12-09,2025-01-28,1688,9.1,Autonomous Tech -AI09468,Principal Data Scientist,168216,USD,168216,SE,CT,United States,M,United States,50,"GCP, Linux, Docker, Hadoop",Bachelor,6,Telecommunications,2024-12-07,2024-12-27,1732,8.8,DataVision Ltd -AI09469,AI Architect,83184,USD,83184,MI,FL,Sweden,L,Sweden,0,"MLOps, Data Visualization, Hadoop, Java, TensorFlow",Master,4,Real Estate,2024-06-03,2024-08-08,1248,8.2,Cloud AI Solutions -AI09470,Machine Learning Researcher,98439,USD,98439,SE,CT,South Korea,L,South Korea,100,"Python, Git, Computer Vision, NLP, R",Associate,8,Manufacturing,2024-07-25,2024-09-29,1463,7.7,TechCorp Inc -AI09471,ML Ops Engineer,164239,USD,164239,MI,PT,Denmark,L,Denmark,0,"Spark, Computer Vision, Kubernetes, Python, Linux",Bachelor,4,Gaming,2024-06-04,2024-07-26,802,8.3,Digital Transformation LLC -AI09472,AI Product Manager,96933,USD,96933,EN,PT,Norway,L,Nigeria,50,"Data Visualization, AWS, Hadoop, Computer Vision",Bachelor,1,Government,2025-04-21,2025-05-19,1741,8.3,Advanced Robotics -AI09473,Data Analyst,108451,USD,108451,EN,CT,Denmark,L,Denmark,0,"Python, Tableau, Azure",Bachelor,0,Retail,2024-03-30,2024-06-03,620,9,TechCorp Inc -AI09474,Robotics Engineer,63644,AUD,85919,EN,PT,Australia,S,Australia,100,"Docker, Azure, GCP, Python",Master,0,Manufacturing,2024-12-29,2025-02-06,886,6.7,DeepTech Ventures -AI09475,AI Specialist,199800,USD,199800,SE,PT,Norway,L,Norway,100,"GCP, Git, Java",PhD,8,Technology,2024-04-09,2024-05-30,716,6.2,AI Innovations -AI09476,Robotics Engineer,158584,USD,158584,SE,FL,Denmark,L,Denmark,100,"PyTorch, GCP, Scala, Linux, Deep Learning",Associate,8,Real Estate,2024-10-11,2024-11-13,1060,8.8,Future Systems -AI09477,Head of AI,200639,USD,200639,EX,FT,Israel,M,Israel,50,"Docker, Tableau, Python, GCP, Azure",Bachelor,17,Energy,2024-02-10,2024-04-03,2424,6.2,Quantum Computing Inc -AI09478,Research Scientist,76094,USD,76094,EX,FT,China,M,China,50,"GCP, R, NLP, Deep Learning",PhD,19,Automotive,2025-03-28,2025-06-06,612,9.8,Cloud AI Solutions -AI09479,AI Research Scientist,24147,USD,24147,MI,FT,India,S,India,50,"GCP, Computer Vision, Kubernetes, Linux, Data Visualization",Bachelor,3,Retail,2024-10-31,2024-12-02,950,9.5,Machine Intelligence Group -AI09480,AI Research Scientist,50123,EUR,42605,EN,PT,France,M,France,50,"Python, Spark, NLP, R",PhD,1,Manufacturing,2024-01-06,2024-03-10,540,5.5,Smart Analytics -AI09481,Robotics Engineer,110573,USD,110573,SE,CT,South Korea,L,South Korea,0,"NLP, GCP, Hadoop",Associate,7,Retail,2024-07-27,2024-09-07,798,5.2,DeepTech Ventures -AI09482,NLP Engineer,108897,USD,108897,MI,CT,Sweden,M,Norway,0,"Kubernetes, Python, TensorFlow, Docker, PyTorch",PhD,4,Automotive,2024-03-10,2024-05-06,715,8.6,Advanced Robotics -AI09483,Principal Data Scientist,330519,USD,330519,EX,PT,Norway,L,Norway,50,"Statistics, Azure, PyTorch, MLOps, SQL",Master,11,Consulting,2025-02-04,2025-03-03,544,5.8,Cloud AI Solutions -AI09484,Deep Learning Engineer,64196,JPY,7061560,EN,FL,Japan,S,Egypt,0,"Statistics, SQL, Data Visualization",Associate,0,Media,2025-03-23,2025-05-14,911,8,Machine Intelligence Group -AI09485,Data Analyst,112869,USD,112869,EX,FT,China,M,Latvia,50,"Scala, Python, NLP",PhD,19,Media,2025-04-28,2025-06-13,588,5.9,Quantum Computing Inc -AI09486,AI Software Engineer,64664,EUR,54964,EN,FL,Germany,M,Germany,100,"SQL, Hadoop, Kubernetes, PyTorch, AWS",Bachelor,0,Automotive,2024-11-30,2025-01-27,1161,7.8,Algorithmic Solutions -AI09487,AI Consultant,175674,JPY,19324140,SE,PT,Japan,L,Japan,0,"Hadoop, Java, PyTorch",Associate,7,Manufacturing,2024-01-31,2024-03-23,723,6.4,AI Innovations -AI09488,Data Analyst,95581,SGD,124255,MI,CT,Singapore,L,Hungary,0,"Git, Azure, Statistics, TensorFlow, Kubernetes",Associate,2,Manufacturing,2024-08-06,2024-09-03,1006,9.8,Advanced Robotics -AI09489,AI Software Engineer,158682,EUR,134880,SE,CT,Austria,L,Romania,50,"Data Visualization, Spark, Hadoop, MLOps, Scala",Associate,7,Telecommunications,2025-04-09,2025-05-22,2434,6.5,Advanced Robotics -AI09490,NLP Engineer,145879,SGD,189643,SE,PT,Singapore,M,Singapore,0,"Statistics, GCP, Azure",Associate,9,Energy,2024-06-29,2024-07-16,1866,6.5,Predictive Systems -AI09491,AI Specialist,196139,USD,196139,EX,CT,Israel,S,Denmark,50,"R, Mathematics, PyTorch, Kubernetes, Azure",PhD,11,Consulting,2024-11-13,2024-12-27,1979,9.4,AI Innovations -AI09492,Deep Learning Engineer,334470,USD,334470,EX,FL,Denmark,L,Denmark,100,"Git, Computer Vision, Deep Learning, Python, TensorFlow",PhD,13,Media,2025-01-26,2025-02-10,1594,7.8,Machine Intelligence Group -AI09493,Computer Vision Engineer,87626,USD,87626,MI,FT,Ireland,S,Ireland,100,"Java, Data Visualization, Hadoop, R",PhD,3,Technology,2024-12-15,2025-02-15,2127,6.5,Algorithmic Solutions -AI09494,Research Scientist,98110,USD,98110,EX,PT,China,S,China,0,"Azure, Python, Deep Learning",Associate,18,Healthcare,2024-06-23,2024-07-27,774,9.5,Predictive Systems -AI09495,AI Research Scientist,125951,CAD,157439,SE,PT,Canada,S,Brazil,100,"Linux, PyTorch, Kubernetes, Tableau, Git",Bachelor,9,Education,2024-05-31,2024-07-27,2495,7.2,DeepTech Ventures -AI09496,Data Analyst,86390,USD,86390,SE,FL,South Korea,M,Philippines,0,"Kubernetes, Mathematics, Scala, Docker",Bachelor,6,Healthcare,2024-06-06,2024-08-03,1154,7.5,Smart Analytics -AI09497,Data Engineer,28282,USD,28282,EN,FT,India,M,India,0,"R, Statistics, SQL, Azure",Associate,0,Technology,2025-04-05,2025-05-29,1646,5.6,Smart Analytics -AI09498,Data Scientist,145712,CHF,131141,MI,CT,Switzerland,M,South Africa,50,"Scala, Docker, NLP",Bachelor,2,Media,2024-11-01,2024-12-13,1336,6.5,Cognitive Computing -AI09499,Machine Learning Engineer,90645,EUR,77048,MI,CT,Germany,L,Germany,50,"Docker, SQL, GCP, TensorFlow",PhD,4,Healthcare,2025-02-08,2025-03-28,2137,8.3,Autonomous Tech -AI09500,Head of AI,82283,SGD,106968,EN,CT,Singapore,M,Singapore,0,"Spark, Hadoop, AWS, Data Visualization, Java",Associate,1,Gaming,2024-11-27,2024-12-20,1536,7.8,Algorithmic Solutions -AI09501,AI Architect,71045,USD,71045,EX,CT,India,M,India,100,"SQL, TensorFlow, MLOps, Docker, Python",Master,19,Manufacturing,2024-01-20,2024-03-20,717,5.9,Smart Analytics -AI09502,Data Scientist,62430,USD,62430,SE,CT,China,L,China,0,"Scala, Statistics, Python",Master,6,Technology,2024-10-23,2025-01-02,1617,9.3,Algorithmic Solutions -AI09503,Principal Data Scientist,106555,USD,106555,SE,FL,Finland,S,Finland,0,"R, Python, Hadoop",PhD,9,Finance,2024-04-07,2024-04-26,2418,7.8,DeepTech Ventures -AI09504,AI Software Engineer,71729,USD,71729,EN,PT,Finland,L,Finland,100,"SQL, Python, Azure",Master,0,Real Estate,2024-10-03,2024-11-30,1129,7.5,Autonomous Tech -AI09505,AI Architect,50504,EUR,42928,EN,FT,France,S,France,100,"TensorFlow, Statistics, MLOps, Tableau, Linux",Master,0,Telecommunications,2024-01-16,2024-03-05,808,9.4,Neural Networks Co -AI09506,Data Scientist,113850,AUD,153698,SE,CT,Australia,M,Australia,50,"SQL, Hadoop, Data Visualization",Master,9,Manufacturing,2024-11-18,2025-01-26,2066,9.5,TechCorp Inc -AI09507,NLP Engineer,315569,USD,315569,EX,PT,United States,L,United States,50,"Tableau, Scala, R, Statistics, TensorFlow",Associate,14,Technology,2024-04-22,2024-05-08,644,8,Future Systems -AI09508,Machine Learning Engineer,235397,GBP,176548,EX,FT,United Kingdom,L,Israel,0,"Java, SQL, Mathematics, Kubernetes",Master,15,Telecommunications,2025-02-05,2025-04-14,503,8.8,Cloud AI Solutions -AI09509,Machine Learning Engineer,126375,USD,126375,MI,FT,Denmark,L,Argentina,50,"Java, Kubernetes, TensorFlow, NLP",Master,4,Telecommunications,2024-03-02,2024-04-10,1297,9.7,DeepTech Ventures -AI09510,Research Scientist,64708,SGD,84120,EN,CT,Singapore,M,Switzerland,0,"Python, TensorFlow, Mathematics",Master,0,Education,2024-12-29,2025-03-06,2203,8.8,TechCorp Inc -AI09511,Research Scientist,128518,GBP,96389,SE,PT,United Kingdom,M,United Kingdom,100,"Hadoop, Data Visualization, Kubernetes, MLOps, AWS",Bachelor,7,Manufacturing,2024-10-15,2024-11-20,2401,7.7,Neural Networks Co -AI09512,Machine Learning Researcher,103052,USD,103052,SE,FL,South Korea,M,Vietnam,0,"Computer Vision, Spark, Tableau, Python",Associate,9,Telecommunications,2024-10-19,2024-12-15,1990,5.6,Future Systems -AI09513,Data Engineer,98700,EUR,83895,SE,FL,Netherlands,S,Finland,0,"Python, TensorFlow, Azure, Kubernetes",Master,8,Transportation,2024-01-29,2024-03-26,663,8.9,TechCorp Inc -AI09514,Principal Data Scientist,36797,USD,36797,MI,CT,India,L,Philippines,100,"AWS, Python, Kubernetes, Mathematics, Deep Learning",Bachelor,4,Energy,2024-11-23,2025-01-13,1780,8.4,Algorithmic Solutions -AI09515,Head of AI,171574,USD,171574,EX,PT,South Korea,S,South Korea,50,"NLP, Python, Spark, Linux, Java",Master,10,Finance,2024-04-17,2024-06-01,1404,8.9,DataVision Ltd -AI09516,Autonomous Systems Engineer,156283,JPY,17191130,SE,FT,Japan,M,Japan,50,"Data Visualization, R, PyTorch",Master,8,Real Estate,2024-11-29,2025-01-15,939,7.9,TechCorp Inc -AI09517,Robotics Engineer,66972,JPY,7366920,EN,FT,Japan,L,Argentina,50,"Scala, Git, Python, Mathematics, Azure",Associate,0,Consulting,2025-03-20,2025-04-27,769,8.7,Smart Analytics -AI09518,Computer Vision Engineer,122877,CHF,110589,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, MLOps, SQL, Java, PyTorch",PhD,2,Real Estate,2024-08-12,2024-10-19,1550,5.4,Neural Networks Co -AI09519,Data Analyst,245072,USD,245072,EX,FL,United States,L,United States,100,"Mathematics, R, Scala, Hadoop",Master,15,Technology,2024-12-27,2025-02-16,1935,7.8,Quantum Computing Inc -AI09520,Data Engineer,43038,USD,43038,MI,FT,China,S,China,100,"Spark, SQL, MLOps",PhD,2,Telecommunications,2024-04-08,2024-05-23,1670,8.3,Future Systems -AI09521,Autonomous Systems Engineer,111598,EUR,94858,MI,CT,France,L,France,0,"Computer Vision, Linux, SQL",Associate,4,Consulting,2025-02-18,2025-04-11,2363,8.2,Predictive Systems -AI09522,NLP Engineer,251849,JPY,27703390,EX,PT,Japan,L,Japan,0,"Scala, Docker, GCP",PhD,15,Transportation,2024-04-06,2024-05-17,2248,6.3,Digital Transformation LLC -AI09523,Data Analyst,110989,USD,110989,MI,CT,Norway,M,Hungary,0,"Mathematics, Azure, SQL",PhD,3,Government,2024-06-23,2024-08-23,1859,7.8,Autonomous Tech -AI09524,Data Engineer,127024,USD,127024,SE,CT,United States,S,Chile,0,"Java, MLOps, Spark",PhD,8,Gaming,2024-06-21,2024-08-02,1861,7.6,Quantum Computing Inc -AI09525,Research Scientist,332546,USD,332546,EX,FL,Denmark,L,Denmark,100,"MLOps, Azure, Tableau, Python, TensorFlow",Bachelor,14,Energy,2024-01-11,2024-03-04,1609,8.8,Future Systems -AI09526,Head of AI,133295,AUD,179948,SE,CT,Australia,M,Australia,0,"Python, AWS, NLP",Master,5,Consulting,2024-03-09,2024-05-05,2345,7.6,AI Innovations -AI09527,AI Research Scientist,86259,CAD,107824,MI,PT,Canada,L,Canada,50,"Tableau, Computer Vision, PyTorch",Associate,3,Education,2024-04-23,2024-06-08,1409,6.3,Predictive Systems -AI09528,Research Scientist,110503,USD,110503,MI,FL,Norway,M,Norway,0,"AWS, SQL, Tableau",Associate,3,Real Estate,2025-03-27,2025-04-11,1252,9,Algorithmic Solutions -AI09529,AI Architect,108797,EUR,92477,MI,CT,Netherlands,M,Netherlands,50,"AWS, Docker, Mathematics",Bachelor,4,Transportation,2024-08-13,2024-10-08,1802,8.4,Autonomous Tech -AI09530,Data Analyst,184018,USD,184018,EX,PT,South Korea,L,South Korea,0,"Statistics, Data Visualization, Azure, Linux",Master,17,Real Estate,2024-04-13,2024-05-21,1346,6.3,Digital Transformation LLC -AI09531,AI Software Engineer,147794,SGD,192132,SE,PT,Singapore,M,Singapore,100,"Python, TensorFlow, Kubernetes, Hadoop",Associate,6,Government,2024-08-27,2024-09-29,815,9.6,Future Systems -AI09532,Autonomous Systems Engineer,71774,JPY,7895140,MI,FL,Japan,S,Japan,50,"SQL, Git, Tableau",PhD,3,Manufacturing,2024-01-28,2024-03-05,1074,5.2,Cognitive Computing -AI09533,Data Scientist,219834,EUR,186859,EX,PT,Austria,M,Austria,0,"Linux, Statistics, MLOps",Master,18,Retail,2025-04-22,2025-05-12,1865,6.1,AI Innovations -AI09534,ML Ops Engineer,186565,USD,186565,EX,FL,South Korea,M,South Korea,100,"MLOps, Statistics, Python",PhD,17,Manufacturing,2024-07-10,2024-09-19,538,5.1,Digital Transformation LLC -AI09535,Data Analyst,27602,USD,27602,EN,FT,China,M,China,0,"R, Scala, SQL, PyTorch",Bachelor,1,Real Estate,2024-08-26,2024-09-10,885,6.1,Cognitive Computing -AI09536,Robotics Engineer,57129,USD,57129,EN,PT,Israel,S,Israel,50,"Spark, Python, SQL, Azure",PhD,1,Manufacturing,2025-03-20,2025-05-21,1666,8.3,Predictive Systems -AI09537,AI Consultant,22217,USD,22217,EN,FT,India,S,India,100,"SQL, GCP, Statistics, Mathematics, PyTorch",Master,0,Real Estate,2024-12-05,2025-01-06,1760,9.9,AI Innovations -AI09538,Head of AI,67864,USD,67864,EX,PT,China,S,Turkey,0,"Hadoop, Deep Learning, Docker, Mathematics, Scala",Associate,19,Retail,2024-04-21,2024-06-06,501,7.2,Autonomous Tech -AI09539,AI Research Scientist,84278,EUR,71636,EN,FT,Germany,L,Germany,50,"Git, Data Visualization, Scala, Azure, Statistics",PhD,0,Media,2024-08-12,2024-10-18,1838,9.5,Advanced Robotics -AI09540,Machine Learning Researcher,116369,USD,116369,SE,FL,South Korea,M,South Korea,0,"Docker, Linux, Spark, Mathematics, NLP",Associate,5,Technology,2024-11-02,2024-12-15,2197,7.7,Machine Intelligence Group -AI09541,AI Specialist,110779,USD,110779,SE,FT,Israel,M,Israel,0,"PyTorch, NLP, Java, R, Computer Vision",Associate,7,Government,2025-02-15,2025-04-23,1776,6.2,Neural Networks Co -AI09542,Data Scientist,285402,USD,285402,EX,FL,Denmark,S,Denmark,50,"TensorFlow, R, Docker, Mathematics, Data Visualization",Bachelor,11,Real Estate,2024-12-30,2025-01-13,1349,6,Quantum Computing Inc -AI09543,NLP Engineer,169619,USD,169619,SE,FT,Norway,M,Norway,100,"GCP, Linux, Docker, Python",PhD,9,Consulting,2024-03-19,2024-05-03,1063,9.2,Quantum Computing Inc -AI09544,Data Scientist,119460,USD,119460,EX,CT,South Korea,S,South Korea,50,"Scala, Kubernetes, Hadoop, Git, Computer Vision",Master,16,Government,2025-02-05,2025-03-06,1333,8.1,Quantum Computing Inc -AI09545,Data Engineer,141162,USD,141162,MI,CT,Denmark,M,Kenya,0,"MLOps, Python, TensorFlow, Kubernetes",PhD,2,Technology,2024-04-21,2024-06-06,947,8.8,Future Systems -AI09546,AI Specialist,125984,USD,125984,SE,PT,Israel,S,Israel,0,"Scala, Tableau, Mathematics, Azure",Associate,9,Gaming,2025-03-20,2025-05-22,1335,8,Future Systems -AI09547,Robotics Engineer,121116,EUR,102949,SE,FL,France,L,France,50,"GCP, Scala, MLOps",Bachelor,8,Media,2025-02-02,2025-03-16,2159,8.7,Cognitive Computing -AI09548,Robotics Engineer,116096,SGD,150925,MI,CT,Singapore,L,Malaysia,100,"Tableau, Python, Linux, Hadoop, TensorFlow",Associate,3,Energy,2024-03-28,2024-05-08,1044,5,Autonomous Tech -AI09549,AI Architect,120313,USD,120313,SE,PT,Ireland,M,Ireland,50,"Python, Docker, Data Visualization",PhD,6,Consulting,2024-06-23,2024-07-22,1587,8.8,TechCorp Inc -AI09550,AI Software Engineer,136464,USD,136464,SE,FT,Ireland,L,Ireland,100,"Tableau, Linux, TensorFlow",Master,9,Transportation,2024-10-11,2024-12-03,1255,9.4,Digital Transformation LLC -AI09551,AI Research Scientist,95934,USD,95934,MI,FT,Israel,M,Israel,50,"Python, Data Visualization, Java, Azure",Bachelor,2,Government,2024-12-20,2025-01-10,2205,9.7,Autonomous Tech -AI09552,AI Software Engineer,85570,CHF,77013,EN,FT,Switzerland,S,Switzerland,50,"Kubernetes, Computer Vision, Scala, Python",Master,0,Finance,2024-06-16,2024-07-11,2114,6.6,Autonomous Tech -AI09553,AI Research Scientist,61645,AUD,83221,EN,CT,Australia,L,Singapore,50,"Kubernetes, Python, Scala, Computer Vision, TensorFlow",Bachelor,1,Gaming,2024-11-06,2024-11-22,2038,5.6,Algorithmic Solutions -AI09554,NLP Engineer,83872,EUR,71291,MI,FL,Austria,S,Austria,100,"GCP, Scala, Deep Learning, SQL, Computer Vision",Associate,4,Consulting,2024-12-21,2025-01-07,1490,8.8,Quantum Computing Inc -AI09555,Computer Vision Engineer,102899,EUR,87464,MI,FL,Austria,L,Austria,50,"Spark, Scala, Deep Learning, Data Visualization, TensorFlow",PhD,3,Real Estate,2024-11-08,2024-11-30,2454,5.4,Algorithmic Solutions -AI09556,Data Engineer,71513,SGD,92967,EN,FL,Singapore,S,United Kingdom,100,"Scala, Linux, Computer Vision, Kubernetes, Git",Master,0,Manufacturing,2024-10-29,2024-12-10,1345,8.4,Predictive Systems -AI09557,Machine Learning Engineer,115012,USD,115012,SE,FT,South Korea,M,China,0,"Java, R, Kubernetes, Docker",Associate,9,Technology,2024-09-26,2024-11-16,984,5.2,Neural Networks Co -AI09558,Machine Learning Engineer,47215,CAD,59019,EN,PT,Canada,S,Canada,100,"Kubernetes, TensorFlow, Docker",Bachelor,0,Technology,2024-06-11,2024-08-20,1165,6.6,AI Innovations -AI09559,AI Specialist,118372,EUR,100616,SE,FL,France,L,Belgium,100,"Linux, Spark, AWS, Deep Learning",PhD,8,Energy,2025-04-08,2025-05-18,1304,5,Cloud AI Solutions -AI09560,Computer Vision Engineer,147836,AUD,199579,SE,CT,Australia,L,Australia,50,"Git, Kubernetes, SQL, GCP, Azure",Bachelor,8,Manufacturing,2024-04-16,2024-05-11,1611,5.6,DataVision Ltd -AI09561,Data Analyst,224535,EUR,190855,EX,FT,Germany,M,Germany,0,"Statistics, SQL, Azure, Python",Associate,15,Education,2025-02-06,2025-03-10,1882,6.8,Predictive Systems -AI09562,AI Software Engineer,138016,USD,138016,SE,CT,Denmark,M,Denmark,50,"Python, Scala, NLP, Git",Associate,8,Government,2024-08-27,2024-10-11,2108,9.4,Future Systems -AI09563,AI Consultant,93538,USD,93538,EN,PT,Norway,S,Norway,0,"Kubernetes, PyTorch, Statistics",PhD,0,Manufacturing,2024-10-26,2024-12-02,2026,9.3,TechCorp Inc -AI09564,Computer Vision Engineer,120674,USD,120674,SE,PT,United States,S,United States,50,"NLP, Docker, Git",PhD,9,Transportation,2024-10-26,2024-12-23,634,6.2,Autonomous Tech -AI09565,AI Architect,299206,CHF,269285,EX,CT,Switzerland,S,Chile,50,"PyTorch, Linux, MLOps, TensorFlow",PhD,11,Telecommunications,2025-04-22,2025-06-13,1150,8.1,Future Systems -AI09566,AI Specialist,128478,AUD,173445,SE,CT,Australia,L,Australia,50,"Python, TensorFlow, Azure",Master,6,Government,2024-04-17,2024-05-17,1949,7.9,Digital Transformation LLC -AI09567,Machine Learning Researcher,60265,AUD,81358,EN,PT,Australia,M,Australia,50,"Computer Vision, Java, MLOps",Master,1,Gaming,2024-03-16,2024-05-17,773,6.6,Autonomous Tech -AI09568,Computer Vision Engineer,279290,USD,279290,EX,PT,Denmark,S,Hungary,50,"Git, R, Scala, Docker, MLOps",Master,16,Government,2024-06-24,2024-07-23,1099,7.6,DataVision Ltd -AI09569,Computer Vision Engineer,110511,CAD,138139,SE,FT,Canada,L,Estonia,0,"Python, TensorFlow, Linux",Associate,9,Telecommunications,2025-01-08,2025-01-30,2403,9.4,Smart Analytics -AI09570,Data Analyst,108968,USD,108968,SE,CT,South Korea,S,South Korea,100,"PyTorch, Spark, Git, Kubernetes",Associate,8,Technology,2025-04-02,2025-04-22,1818,6.1,Machine Intelligence Group -AI09571,Data Engineer,81290,GBP,60968,MI,FT,United Kingdom,S,Switzerland,0,"Kubernetes, R, PyTorch",Bachelor,3,Consulting,2025-02-27,2025-04-14,1907,6.4,Predictive Systems -AI09572,Robotics Engineer,191881,CHF,172693,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, MLOps, Python, Spark",Bachelor,5,Transportation,2024-12-16,2025-01-19,1266,5.1,Predictive Systems -AI09573,Robotics Engineer,106589,CHF,95930,MI,FT,Switzerland,M,Switzerland,100,"Mathematics, AWS, Computer Vision, TensorFlow",Master,2,Manufacturing,2024-09-28,2024-10-21,1384,6.9,Cognitive Computing -AI09574,Machine Learning Engineer,97626,USD,97626,MI,PT,Ireland,L,Austria,100,"Scala, PyTorch, MLOps",Bachelor,3,Telecommunications,2024-10-04,2024-11-26,2239,8.1,Autonomous Tech -AI09575,AI Architect,141618,USD,141618,MI,FT,Denmark,L,Italy,0,"Data Visualization, Scala, Docker, Python, TensorFlow",Master,2,Government,2024-02-18,2024-04-10,1654,5.2,Digital Transformation LLC -AI09576,Autonomous Systems Engineer,95458,EUR,81139,MI,FL,Netherlands,L,Argentina,0,"Linux, SQL, Java",Bachelor,4,Education,2025-03-25,2025-04-22,2104,6.8,AI Innovations -AI09577,Robotics Engineer,105315,CHF,94784,MI,FL,Switzerland,S,Vietnam,100,"Azure, Python, Linux",PhD,3,Technology,2025-03-22,2025-04-23,507,6.3,DataVision Ltd -AI09578,AI Specialist,71116,EUR,60449,MI,PT,Austria,S,Austria,50,"Mathematics, TensorFlow, Python, Computer Vision, Azure",Master,3,Finance,2025-01-11,2025-03-22,2210,6.9,DeepTech Ventures -AI09579,Autonomous Systems Engineer,82679,EUR,70277,EN,FT,Netherlands,L,China,0,"Scala, NLP, GCP",Associate,0,Automotive,2024-03-14,2024-04-12,1625,8.7,Algorithmic Solutions -AI09580,Machine Learning Engineer,177922,EUR,151234,EX,FT,Germany,S,Germany,0,"Data Visualization, Git, TensorFlow",Associate,12,Healthcare,2024-12-05,2025-01-23,1334,9.3,DeepTech Ventures -AI09581,Data Scientist,31465,USD,31465,EN,FT,India,L,India,0,"Scala, Linux, SQL, PyTorch",Master,1,Transportation,2024-05-23,2024-06-11,1808,6.1,DeepTech Ventures -AI09582,AI Specialist,114364,USD,114364,EN,FL,Denmark,L,Denmark,0,"AWS, NLP, Tableau, Docker",Bachelor,1,Finance,2024-08-24,2024-10-02,582,7.7,DeepTech Ventures -AI09583,Data Scientist,206549,USD,206549,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, MLOps",Associate,15,Gaming,2024-05-04,2024-06-07,2093,8,Neural Networks Co -AI09584,Computer Vision Engineer,112749,EUR,95837,SE,FL,Germany,M,Turkey,100,"Hadoop, Git, Computer Vision, R, Java",PhD,6,Education,2024-09-09,2024-11-10,2317,7.4,DataVision Ltd -AI09585,Machine Learning Researcher,97146,EUR,82574,MI,CT,France,M,France,50,"PyTorch, AWS, Hadoop, Azure, Deep Learning",PhD,2,Real Estate,2025-01-13,2025-01-27,1832,7.3,DeepTech Ventures -AI09586,Research Scientist,35698,USD,35698,SE,FL,India,S,India,0,"Linux, GCP, PyTorch, NLP, Scala",Associate,5,Media,2024-02-02,2024-04-10,2048,5.7,Future Systems -AI09587,AI Research Scientist,64209,USD,64209,EN,CT,Israel,M,Israel,100,"Tableau, GCP, Java",Master,1,Telecommunications,2024-07-22,2024-09-02,1711,6.1,Advanced Robotics -AI09588,Robotics Engineer,108749,USD,108749,EN,FT,United States,L,United States,100,"Mathematics, Python, TensorFlow, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-11-09,1228,7.8,DeepTech Ventures -AI09589,AI Research Scientist,78664,USD,78664,MI,CT,Sweden,M,Australia,50,"TensorFlow, Python, GCP, Deep Learning, NLP",Associate,4,Finance,2024-11-26,2024-12-31,1225,9.1,Predictive Systems -AI09590,Autonomous Systems Engineer,72106,SGD,93738,MI,CT,Singapore,S,Singapore,0,"Data Visualization, Python, AWS, GCP, TensorFlow",Associate,4,Government,2024-01-04,2024-03-10,2323,9.6,TechCorp Inc -AI09591,Deep Learning Engineer,41945,USD,41945,MI,FL,China,S,China,0,"TensorFlow, Deep Learning, Data Visualization, Hadoop",PhD,2,Technology,2024-11-01,2025-01-07,2002,5.6,DataVision Ltd -AI09592,AI Consultant,135711,USD,135711,SE,FL,Sweden,S,Sweden,100,"Docker, Tableau, GCP, PyTorch, Statistics",Master,8,Government,2024-11-23,2024-12-07,2244,7.9,Advanced Robotics -AI09593,NLP Engineer,311228,USD,311228,EX,FL,United States,L,United States,50,"Python, Computer Vision, Linux, Spark, TensorFlow",Bachelor,17,Gaming,2024-05-19,2024-06-25,1679,5.7,Neural Networks Co -AI09594,Deep Learning Engineer,80311,USD,80311,EN,FL,Denmark,S,Denmark,50,"TensorFlow, Kubernetes, Git",Master,1,Telecommunications,2024-07-30,2024-09-14,663,6.3,Advanced Robotics -AI09595,Computer Vision Engineer,140434,USD,140434,EX,CT,Finland,M,Finland,100,"Azure, Python, Docker",Associate,17,Real Estate,2024-04-03,2024-05-17,1737,8.8,Autonomous Tech -AI09596,AI Architect,242982,USD,242982,EX,FT,Norway,S,Norway,100,"Spark, NLP, Python, TensorFlow",Associate,10,Retail,2024-03-31,2024-06-11,2335,6.4,Digital Transformation LLC -AI09597,Deep Learning Engineer,71755,USD,71755,EN,PT,Finland,L,Finland,100,"Tableau, PyTorch, Deep Learning, Git, TensorFlow",PhD,1,Retail,2024-08-04,2024-10-03,2271,8.7,DeepTech Ventures -AI09598,AI Software Engineer,31328,USD,31328,MI,CT,India,L,India,100,"Git, Scala, Computer Vision",Master,2,Telecommunications,2024-09-25,2024-11-07,1426,6,TechCorp Inc -AI09599,Data Engineer,108210,USD,108210,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Deep Learning, Spark",Bachelor,9,Energy,2024-04-26,2024-06-04,925,8.1,AI Innovations -AI09600,NLP Engineer,127242,GBP,95432,SE,PT,United Kingdom,M,United Kingdom,100,"SQL, Kubernetes, Scala, AWS",Associate,9,Healthcare,2025-01-21,2025-04-03,1609,9.1,Algorithmic Solutions -AI09601,AI Software Engineer,122440,USD,122440,SE,CT,Finland,L,Finland,100,"Kubernetes, Spark, Hadoop, Git",Bachelor,7,Finance,2024-05-25,2024-06-20,1905,9.4,Smart Analytics -AI09602,Data Analyst,163000,USD,163000,EX,FT,Ireland,M,Belgium,100,"Scala, Linux, MLOps",Associate,17,Gaming,2025-01-09,2025-02-02,502,7.4,DataVision Ltd -AI09603,Machine Learning Researcher,238582,JPY,26244020,EX,FL,Japan,M,Japan,0,"Azure, Scala, Hadoop, Git",Master,12,Finance,2025-01-08,2025-02-10,773,7.3,AI Innovations -AI09604,ML Ops Engineer,56341,USD,56341,EN,PT,South Korea,M,South Korea,0,"SQL, Tableau, PyTorch",Bachelor,1,Media,2024-10-31,2024-12-01,815,7.9,TechCorp Inc -AI09605,ML Ops Engineer,82286,GBP,61715,EN,FL,United Kingdom,L,United Kingdom,50,"Java, Computer Vision, SQL, Deep Learning, PyTorch",Associate,1,Telecommunications,2025-02-24,2025-04-02,1160,7.2,TechCorp Inc -AI09606,ML Ops Engineer,206792,USD,206792,EX,FL,Norway,M,Norway,0,"Scala, GCP, PyTorch",Associate,10,Manufacturing,2024-08-27,2024-10-21,550,7.3,Smart Analytics -AI09607,Data Engineer,111725,EUR,94966,MI,PT,France,L,Russia,100,"Mathematics, MLOps, Data Visualization, Kubernetes",PhD,4,Real Estate,2024-07-24,2024-08-15,1981,5.9,Cloud AI Solutions -AI09608,Principal Data Scientist,256576,USD,256576,EX,FL,Finland,L,Ukraine,0,"Git, R, Computer Vision",Master,14,Finance,2024-04-28,2024-05-29,2329,8.6,Machine Intelligence Group -AI09609,NLP Engineer,157172,EUR,133596,EX,CT,France,S,France,100,"TensorFlow, Docker, Git",PhD,10,Manufacturing,2024-12-17,2025-02-24,703,7.4,AI Innovations -AI09610,Data Analyst,38565,USD,38565,MI,CT,India,L,India,50,"AWS, Computer Vision, SQL",Associate,3,Transportation,2024-09-16,2024-11-19,551,10,Cloud AI Solutions -AI09611,Principal Data Scientist,93643,CHF,84279,EN,FT,Switzerland,S,Egypt,0,"Python, Git, Computer Vision, Deep Learning, Linux",Associate,1,Healthcare,2024-11-15,2025-01-01,651,8.2,Cognitive Computing -AI09612,AI Product Manager,349386,CHF,314447,EX,PT,Switzerland,L,Switzerland,100,"Git, Tableau, TensorFlow",Associate,11,Retail,2024-10-02,2024-12-13,2214,9.4,Cloud AI Solutions -AI09613,ML Ops Engineer,135479,EUR,115157,EX,FT,Austria,S,Austria,50,"SQL, TensorFlow, Tableau, Hadoop, Spark",Bachelor,19,Telecommunications,2025-02-12,2025-04-19,2223,6.1,TechCorp Inc -AI09614,AI Architect,18474,USD,18474,EN,FL,India,S,Netherlands,50,"Git, Deep Learning, Scala, Java, Tableau",Master,1,Technology,2024-03-21,2024-05-07,1106,6.3,Quantum Computing Inc -AI09615,Deep Learning Engineer,84485,USD,84485,SE,FT,South Korea,M,South Korea,50,"TensorFlow, Python, Spark, SQL, AWS",Master,9,Telecommunications,2024-06-08,2024-06-25,1760,8.1,TechCorp Inc -AI09616,Data Engineer,108371,USD,108371,EN,PT,Denmark,L,Denmark,0,"AWS, Tableau, Hadoop",Bachelor,1,Energy,2024-07-29,2024-10-04,710,9.1,Algorithmic Solutions -AI09617,Data Analyst,115972,EUR,98576,SE,FL,Austria,L,Austria,0,"Deep Learning, GCP, Data Visualization, MLOps, NLP",Master,7,Government,2024-09-09,2024-10-17,1584,9.2,Quantum Computing Inc -AI09618,Computer Vision Engineer,107070,USD,107070,MI,CT,Norway,M,Norway,100,"Python, Docker, Azure, Spark",Bachelor,3,Retail,2024-02-09,2024-03-11,642,9.4,DataVision Ltd -AI09619,AI Consultant,63084,USD,63084,EN,FT,Sweden,L,Sweden,50,"Hadoop, Azure, Data Visualization, NLP",Master,0,Automotive,2024-06-20,2024-07-22,1427,5,Digital Transformation LLC -AI09620,Head of AI,152429,USD,152429,MI,CT,Denmark,L,Denmark,0,"TensorFlow, Mathematics, Azure, SQL",Associate,3,Retail,2024-09-18,2024-11-01,2456,9.6,Quantum Computing Inc -AI09621,Computer Vision Engineer,61740,USD,61740,SE,FT,India,L,Estonia,0,"Azure, Java, Deep Learning",PhD,6,Education,2024-05-26,2024-07-17,1435,7.1,Neural Networks Co -AI09622,Autonomous Systems Engineer,135651,USD,135651,SE,CT,Sweden,S,Sweden,50,"Mathematics, Python, TensorFlow, Tableau",Bachelor,5,Retail,2025-04-29,2025-06-07,626,7,Autonomous Tech -AI09623,Computer Vision Engineer,91734,USD,91734,MI,FT,Israel,L,Israel,50,"Scala, SQL, PyTorch, Spark",Associate,3,Transportation,2024-03-07,2024-04-03,2414,7.9,Digital Transformation LLC -AI09624,ML Ops Engineer,178754,USD,178754,SE,PT,United States,L,United States,0,"Python, Kubernetes, Spark, TensorFlow",Associate,7,Gaming,2024-03-28,2024-04-15,2228,9.3,DataVision Ltd -AI09625,Data Analyst,141292,USD,141292,SE,FL,Denmark,S,Denmark,50,"AWS, SQL, Data Visualization, Statistics, Git",Master,5,Energy,2024-12-03,2025-01-22,1969,7.3,Cloud AI Solutions -AI09626,Data Scientist,63976,CAD,79970,EN,FT,Canada,S,Egypt,0,"Spark, PyTorch, Statistics, Data Visualization, R",Associate,1,Technology,2024-08-20,2024-09-20,1847,6.2,Machine Intelligence Group -AI09627,Principal Data Scientist,172992,USD,172992,SE,FT,United States,L,United States,100,"TensorFlow, Python, Deep Learning",Bachelor,6,Healthcare,2024-01-05,2024-02-22,802,7,DeepTech Ventures -AI09628,Data Engineer,274237,USD,274237,EX,PT,Ireland,L,Ireland,50,"Docker, AWS, PyTorch, GCP",Master,12,Gaming,2024-08-27,2024-10-15,1234,8.1,AI Innovations -AI09629,Deep Learning Engineer,191469,USD,191469,EX,FT,Israel,M,Israel,50,"Python, Azure, Data Visualization, TensorFlow",PhD,13,Retail,2025-01-29,2025-02-12,543,6.7,Predictive Systems -AI09630,Research Scientist,203503,EUR,172978,EX,FT,Netherlands,L,Netherlands,50,"Python, AWS, Computer Vision, Linux, TensorFlow",Bachelor,19,Consulting,2025-02-27,2025-05-04,552,7.5,Digital Transformation LLC -AI09631,NLP Engineer,101614,EUR,86372,SE,PT,Austria,S,Austria,100,"Hadoop, Java, NLP, Deep Learning",PhD,6,Retail,2025-04-24,2025-06-07,1662,7.3,TechCorp Inc -AI09632,Machine Learning Engineer,72890,SGD,94757,EN,PT,Singapore,M,Chile,100,"TensorFlow, Kubernetes, Git",Master,0,Retail,2024-02-06,2024-04-12,2204,9.7,Smart Analytics -AI09633,Deep Learning Engineer,241369,USD,241369,EX,CT,Israel,L,Israel,50,"Computer Vision, Git, Mathematics",Master,11,Technology,2024-05-25,2024-08-03,1757,9.2,Algorithmic Solutions -AI09634,Data Analyst,80985,JPY,8908350,EN,PT,Japan,M,Japan,50,"Python, PyTorch, Spark, Mathematics, AWS",PhD,0,Technology,2024-03-16,2024-04-12,749,6.3,Machine Intelligence Group -AI09635,Computer Vision Engineer,48693,USD,48693,SE,FL,China,S,China,0,"Git, Python, NLP, Data Visualization",PhD,6,Healthcare,2024-02-09,2024-04-17,2083,8.9,Predictive Systems -AI09636,AI Software Engineer,120364,USD,120364,SE,FT,Ireland,M,Ireland,100,"Python, Tableau, MLOps, Azure, Computer Vision",PhD,6,Telecommunications,2024-08-20,2024-09-28,632,6.3,Cognitive Computing -AI09637,Data Analyst,119327,EUR,101428,SE,FL,France,M,Nigeria,100,"Mathematics, AWS, Tableau",Master,9,Education,2025-02-17,2025-04-26,1137,7.8,Autonomous Tech -AI09638,ML Ops Engineer,52959,USD,52959,EN,FL,Finland,S,Finland,0,"Java, MLOps, Python, Linux",Associate,1,Telecommunications,2024-11-07,2024-11-23,2153,9.6,DataVision Ltd -AI09639,Principal Data Scientist,44848,USD,44848,EN,PT,South Korea,S,South Korea,0,"Python, TensorFlow, Deep Learning, Linux, Computer Vision",Bachelor,1,Real Estate,2025-03-10,2025-05-20,615,8.8,Future Systems -AI09640,AI Software Engineer,279410,JPY,30735100,EX,CT,Japan,L,Japan,0,"R, Tableau, SQL, Computer Vision, Linux",Master,19,Healthcare,2024-09-30,2024-11-15,898,9.2,Neural Networks Co -AI09641,AI Product Manager,276943,USD,276943,EX,FL,Norway,S,Norway,0,"PyTorch, GCP, Statistics, Tableau",PhD,18,Automotive,2024-12-21,2025-02-03,1529,8.8,Future Systems -AI09642,Autonomous Systems Engineer,190274,USD,190274,SE,FT,Denmark,M,Denmark,0,"AWS, SQL, Kubernetes",Associate,9,Telecommunications,2024-01-12,2024-01-27,1114,9.4,AI Innovations -AI09643,Data Scientist,98262,JPY,10808820,EN,FL,Japan,L,France,0,"Python, SQL, Hadoop, Statistics",PhD,1,Manufacturing,2024-04-03,2024-04-28,1441,5.3,Future Systems -AI09644,AI Research Scientist,70103,USD,70103,EN,PT,South Korea,L,South Korea,100,"Mathematics, Computer Vision, Spark",Bachelor,1,Automotive,2024-02-20,2024-03-20,2351,5.5,Digital Transformation LLC -AI09645,Deep Learning Engineer,244222,USD,244222,EX,CT,Sweden,M,Israel,100,"PyTorch, TensorFlow, Deep Learning, Data Visualization, SQL",PhD,14,Energy,2024-03-18,2024-05-15,909,6.5,DataVision Ltd -AI09646,AI Software Engineer,98207,USD,98207,MI,FL,Sweden,S,Sweden,50,"R, Hadoop, Tableau, SQL, GCP",Associate,4,Real Estate,2024-09-26,2024-11-20,2490,8.4,Predictive Systems -AI09647,Machine Learning Engineer,74097,USD,74097,MI,CT,Finland,S,Brazil,50,"Hadoop, Python, MLOps",Master,4,Healthcare,2024-04-21,2024-05-11,2339,9.1,Quantum Computing Inc -AI09648,AI Specialist,57153,JPY,6286830,EN,CT,Japan,M,Japan,100,"TensorFlow, Scala, Docker, Hadoop",Master,1,Telecommunications,2024-09-12,2024-10-21,2307,8.8,DeepTech Ventures -AI09649,Research Scientist,99157,EUR,84283,MI,CT,France,M,Switzerland,0,"SQL, Hadoop, PyTorch",Master,3,Education,2024-04-23,2024-06-29,1974,9.2,Cloud AI Solutions -AI09650,AI Product Manager,104851,USD,104851,SE,CT,Israel,S,Israel,50,"Git, R, Python, Deep Learning, Java",Master,8,Automotive,2024-02-15,2024-04-26,2450,5.3,Quantum Computing Inc -AI09651,AI Specialist,70704,USD,70704,EN,CT,United States,M,United States,50,"Data Visualization, MLOps, Scala, Statistics, R",Master,1,Real Estate,2024-10-06,2024-12-11,513,5.8,Autonomous Tech -AI09652,AI Research Scientist,86595,AUD,116903,MI,FT,Australia,M,Australia,100,"Spark, TensorFlow, NLP",Master,4,Transportation,2025-01-04,2025-03-02,1800,5.7,Cognitive Computing -AI09653,Autonomous Systems Engineer,139992,USD,139992,SE,PT,Ireland,M,Egypt,0,"Mathematics, Python, Kubernetes",Master,5,Telecommunications,2024-04-30,2024-06-11,1651,8.9,Machine Intelligence Group -AI09654,AI Consultant,69365,EUR,58960,MI,CT,Germany,S,Germany,100,"Scala, Deep Learning, MLOps, Hadoop",PhD,2,Government,2024-01-25,2024-03-31,2284,7.6,Future Systems -AI09655,Data Engineer,98050,USD,98050,MI,FT,Finland,L,Finland,0,"Kubernetes, R, MLOps, Deep Learning, Scala",PhD,2,Telecommunications,2024-06-10,2024-07-19,1741,7,Smart Analytics -AI09656,AI Architect,20880,USD,20880,EN,CT,India,M,India,50,"Spark, Git, Kubernetes, Python",Bachelor,1,Finance,2024-05-11,2024-07-15,603,6.6,Cloud AI Solutions -AI09657,AI Research Scientist,80608,SGD,104790,EN,CT,Singapore,L,Singapore,0,"Scala, R, Hadoop, Deep Learning",PhD,0,Government,2025-04-04,2025-06-08,1483,5.4,Algorithmic Solutions -AI09658,Research Scientist,121634,CHF,109471,EN,PT,Switzerland,L,Czech Republic,50,"Python, Hadoop, AWS",Associate,1,Gaming,2024-03-08,2024-05-19,2259,8.4,Advanced Robotics -AI09659,Principal Data Scientist,200363,EUR,170309,EX,CT,Austria,L,Austria,100,"Tableau, Statistics, TensorFlow, Python",Bachelor,19,Technology,2025-01-07,2025-01-26,2480,7.7,Smart Analytics -AI09660,Machine Learning Researcher,65086,USD,65086,EN,FL,United States,S,United States,0,"Python, Linux, Tableau",PhD,1,Technology,2024-10-04,2024-11-23,2294,6.6,Predictive Systems -AI09661,Machine Learning Engineer,76722,USD,76722,EN,FT,Norway,S,Argentina,50,"Computer Vision, Spark, R, Hadoop, Docker",PhD,0,Government,2024-02-28,2024-05-05,1503,9.2,DataVision Ltd -AI09662,Data Engineer,136698,EUR,116193,SE,FL,Germany,M,Australia,0,"Statistics, Scala, SQL, Hadoop",Master,5,Healthcare,2024-07-28,2024-09-29,1467,8.3,TechCorp Inc -AI09663,Head of AI,89233,AUD,120465,MI,FT,Australia,S,Australia,100,"Azure, Statistics, Python, Data Visualization",Bachelor,3,Automotive,2025-01-11,2025-02-05,1410,9.4,Algorithmic Solutions -AI09664,AI Specialist,51178,AUD,69090,EN,FL,Australia,S,Egypt,50,"PyTorch, GCP, TensorFlow",Associate,1,Manufacturing,2024-01-25,2024-02-19,1458,9.7,Advanced Robotics -AI09665,AI Software Engineer,66263,EUR,56324,EN,FL,Germany,M,Argentina,0,"R, Tableau, Java",Associate,0,Transportation,2024-07-23,2024-09-13,558,9.3,Machine Intelligence Group -AI09666,Data Engineer,173476,USD,173476,EX,FL,Finland,S,Finland,100,"Linux, Kubernetes, Deep Learning, SQL, Git",Master,17,Government,2025-04-07,2025-04-30,2135,6.3,Machine Intelligence Group -AI09667,AI Software Engineer,161253,SGD,209629,EX,PT,Singapore,S,Singapore,100,"NLP, SQL, Statistics, Tableau",PhD,15,Real Estate,2024-03-21,2024-05-18,2353,9,AI Innovations -AI09668,AI Consultant,261254,EUR,222066,EX,PT,Germany,L,Germany,100,"Hadoop, Python, Kubernetes, Statistics, TensorFlow",Associate,12,Education,2025-04-26,2025-07-02,739,5.5,Advanced Robotics -AI09669,ML Ops Engineer,199726,USD,199726,EX,FT,Finland,M,Canada,0,"R, GCP, Deep Learning",Master,14,Technology,2024-09-05,2024-11-06,654,6.1,Smart Analytics -AI09670,Computer Vision Engineer,155809,AUD,210342,SE,PT,Australia,L,Australia,50,"PyTorch, Git, GCP",Master,8,Automotive,2024-04-25,2024-06-11,1358,5.6,Future Systems -AI09671,AI Specialist,27270,USD,27270,EN,FT,China,M,Vietnam,100,"Scala, Git, Azure",Associate,1,Transportation,2025-01-07,2025-02-06,2070,9.8,Smart Analytics -AI09672,NLP Engineer,123021,JPY,13532310,SE,CT,Japan,S,Japan,0,"Python, Scala, NLP, Docker, Kubernetes",Master,5,Finance,2024-10-29,2024-11-24,825,7.1,Neural Networks Co -AI09673,Robotics Engineer,218828,USD,218828,EX,FL,Ireland,S,Ireland,100,"PyTorch, TensorFlow, Azure, Kubernetes, Git",PhD,13,Telecommunications,2025-02-27,2025-05-08,1379,9.3,DeepTech Ventures -AI09674,Data Scientist,96009,USD,96009,EN,PT,Denmark,M,Denmark,100,"Spark, Statistics, SQL, Git",PhD,1,Real Estate,2024-04-02,2024-06-01,1154,7.4,Cloud AI Solutions -AI09675,AI Research Scientist,105293,USD,105293,EX,FT,China,L,China,100,"Tableau, Computer Vision, PyTorch, Linux, Mathematics",Associate,11,Automotive,2024-04-09,2024-06-02,1914,8,AI Innovations -AI09676,Machine Learning Researcher,140098,SGD,182127,SE,CT,Singapore,S,Singapore,50,"PyTorch, Java, GCP",Associate,6,Finance,2025-01-29,2025-03-07,951,6.5,Future Systems -AI09677,AI Product Manager,109453,CHF,98508,EN,FL,Switzerland,L,Switzerland,50,"Python, Scala, TensorFlow, Statistics, Computer Vision",Bachelor,1,Real Estate,2024-09-14,2024-10-27,2333,9.4,Cognitive Computing -AI09678,Data Engineer,135675,USD,135675,SE,FT,Ireland,S,Ghana,0,"Scala, GCP, Python",Associate,5,Real Estate,2025-03-27,2025-04-28,513,5.8,Cognitive Computing -AI09679,Data Analyst,55854,USD,55854,EN,FL,South Korea,S,South Korea,50,"Scala, TensorFlow, NLP",Bachelor,1,Government,2025-01-10,2025-03-03,2440,8.4,Quantum Computing Inc -AI09680,Data Analyst,95094,EUR,80830,SE,FT,Austria,S,Brazil,50,"Kubernetes, Python, Azure",Associate,5,Real Estate,2024-06-14,2024-08-02,2045,10,Smart Analytics -AI09681,Autonomous Systems Engineer,218586,USD,218586,EX,CT,Finland,L,Finland,0,"Linux, Hadoop, GCP, Tableau, Computer Vision",Bachelor,12,Media,2024-11-24,2025-01-25,1646,5.6,Quantum Computing Inc -AI09682,AI Specialist,49538,USD,49538,EN,CT,Finland,S,Finland,0,"Linux, Computer Vision, Docker, SQL",Master,1,Finance,2024-08-01,2024-09-10,1675,8.2,Cognitive Computing -AI09683,AI Software Engineer,133909,EUR,113823,EX,FT,France,S,Spain,50,"Data Visualization, GCP, MLOps, NLP",Associate,15,Manufacturing,2024-03-26,2024-04-24,1593,7.6,Cognitive Computing -AI09684,Principal Data Scientist,48444,EUR,41177,EN,CT,France,M,Hungary,100,"Azure, Scala, Python",Bachelor,1,Transportation,2024-02-02,2024-04-02,561,5.1,TechCorp Inc -AI09685,AI Research Scientist,256902,EUR,218367,EX,CT,Netherlands,M,Netherlands,100,"PyTorch, Tableau, Hadoop",Master,17,Gaming,2024-10-12,2024-11-27,1394,8.3,Autonomous Tech -AI09686,AI Architect,57022,USD,57022,SE,CT,China,M,China,0,"MLOps, Python, Docker",Master,9,Education,2024-05-16,2024-06-16,1314,9.5,Cognitive Computing -AI09687,AI Specialist,26272,USD,26272,EN,FL,India,M,Argentina,100,"Kubernetes, Tableau, Scala",Bachelor,1,Energy,2025-03-18,2025-04-08,1146,7.7,Advanced Robotics -AI09688,Deep Learning Engineer,191403,GBP,143552,EX,FL,United Kingdom,S,Philippines,50,"Tableau, Data Visualization, Computer Vision",PhD,13,Technology,2024-02-27,2024-05-05,2261,6.8,Cognitive Computing -AI09689,Machine Learning Researcher,102609,USD,102609,MI,CT,Ireland,M,Ireland,0,"Python, Linux, TensorFlow, Hadoop, Azure",PhD,3,Government,2024-04-25,2024-06-18,1130,9.7,Future Systems -AI09690,Machine Learning Engineer,86953,USD,86953,MI,PT,South Korea,M,Brazil,100,"R, SQL, TensorFlow, GCP, Computer Vision",Master,2,Energy,2024-01-07,2024-01-25,1942,9.5,DeepTech Ventures -AI09691,AI Architect,220260,EUR,187221,EX,FL,France,M,France,0,"Docker, Azure, Computer Vision, AWS, GCP",Bachelor,19,Automotive,2024-10-27,2025-01-01,2461,9.6,Autonomous Tech -AI09692,Robotics Engineer,129728,SGD,168646,SE,PT,Singapore,S,Singapore,100,"SQL, NLP, Hadoop",Bachelor,7,Gaming,2024-12-01,2025-01-12,2243,9.7,Cloud AI Solutions -AI09693,Principal Data Scientist,140854,USD,140854,SE,FL,Ireland,L,Ireland,0,"Python, Spark, Data Visualization",Bachelor,5,Transportation,2024-07-03,2024-09-14,1262,6.5,Cognitive Computing -AI09694,Data Analyst,247679,JPY,27244690,EX,FL,Japan,L,Japan,100,"PyTorch, NLP, Computer Vision, Java",Associate,19,Healthcare,2024-04-26,2024-06-02,1484,5.7,Predictive Systems -AI09695,Machine Learning Researcher,159898,JPY,17588780,SE,FL,Japan,M,Japan,50,"Spark, PyTorch, Tableau",PhD,9,Education,2024-11-30,2025-01-18,1577,7.7,Future Systems -AI09696,Data Engineer,119549,EUR,101617,SE,FT,Austria,M,Austria,0,"GCP, Docker, Tableau, Git",Bachelor,7,Telecommunications,2024-06-11,2024-08-11,1379,7.3,Cognitive Computing -AI09697,Data Scientist,141626,USD,141626,SE,PT,Finland,L,Finland,100,"MLOps, Docker, Kubernetes, R",PhD,9,Retail,2024-08-31,2024-10-31,688,8.3,Advanced Robotics -AI09698,Machine Learning Engineer,83010,EUR,70559,EN,CT,Germany,L,Malaysia,100,"Hadoop, SQL, Java",Bachelor,0,Retail,2024-12-21,2025-02-03,2456,9.9,Smart Analytics -AI09699,Machine Learning Engineer,102708,JPY,11297880,MI,CT,Japan,L,Japan,100,"TensorFlow, Linux, Tableau, SQL",Associate,2,Gaming,2024-03-24,2024-04-11,1512,7.6,Digital Transformation LLC -AI09700,NLP Engineer,108628,JPY,11949080,MI,FT,Japan,L,Japan,0,"NLP, Hadoop, GCP",Bachelor,3,Energy,2024-01-18,2024-02-26,667,9.1,Algorithmic Solutions -AI09701,Data Analyst,74902,JPY,8239220,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, NLP, GCP, Scala",Associate,0,Manufacturing,2024-07-01,2024-09-12,2409,8,Quantum Computing Inc -AI09702,Data Engineer,87428,CHF,78685,EN,FT,Switzerland,S,Switzerland,0,"Python, AWS, Deep Learning",Bachelor,0,Transportation,2024-03-27,2024-05-09,1937,6,Machine Intelligence Group -AI09703,Robotics Engineer,76047,AUD,102663,MI,PT,Australia,M,Australia,0,"R, AWS, MLOps, Scala, Deep Learning",PhD,3,Energy,2024-08-21,2024-09-08,1513,6.2,TechCorp Inc -AI09704,Deep Learning Engineer,260148,USD,260148,EX,FT,United States,S,Turkey,50,"Git, Scala, Data Visualization",Bachelor,18,Telecommunications,2025-01-10,2025-02-12,2240,8,Digital Transformation LLC -AI09705,Robotics Engineer,74496,USD,74496,MI,CT,Sweden,S,Sweden,0,"Java, Spark, TensorFlow",PhD,2,Energy,2025-04-23,2025-06-29,1834,6.9,Predictive Systems -AI09706,NLP Engineer,79118,EUR,67250,MI,PT,Germany,S,United States,0,"Azure, Tableau, Git",PhD,3,Manufacturing,2024-04-06,2024-05-11,1883,8.8,Advanced Robotics -AI09707,ML Ops Engineer,115756,EUR,98393,SE,FL,Germany,S,Germany,50,"Git, SQL, Kubernetes, Deep Learning, Hadoop",Bachelor,5,Transportation,2025-04-19,2025-05-27,1471,7.4,AI Innovations -AI09708,AI Software Engineer,86602,EUR,73612,SE,PT,France,S,Brazil,0,"SQL, Data Visualization, Scala, Azure",Associate,6,Education,2025-02-22,2025-03-18,1378,9.6,Machine Intelligence Group -AI09709,Principal Data Scientist,125719,AUD,169721,SE,CT,Australia,M,Australia,100,"Scala, Kubernetes, Docker",Master,6,Consulting,2024-03-02,2024-04-01,1265,7.2,Cloud AI Solutions -AI09710,NLP Engineer,18481,USD,18481,EN,CT,India,S,India,50,"Python, TensorFlow, Scala, PyTorch",Associate,0,Automotive,2024-05-11,2024-05-31,2012,6.4,Predictive Systems -AI09711,ML Ops Engineer,88351,USD,88351,SE,CT,Finland,S,Ghana,100,"SQL, Statistics, GCP, Hadoop, Deep Learning",Associate,6,Manufacturing,2024-07-10,2024-07-30,2256,5.5,Quantum Computing Inc -AI09712,AI Consultant,40280,USD,40280,MI,PT,India,L,India,50,"Statistics, PyTorch, Hadoop, Scala, AWS",Master,3,Automotive,2024-08-23,2024-09-27,1701,5.9,AI Innovations -AI09713,Deep Learning Engineer,87759,USD,87759,MI,FL,Ireland,L,Russia,100,"Hadoop, R, Tableau, GCP, Kubernetes",Bachelor,3,Finance,2024-05-29,2024-07-25,1034,6.2,Algorithmic Solutions -AI09714,AI Consultant,140279,USD,140279,SE,FT,Israel,L,Israel,100,"Data Visualization, SQL, Docker, TensorFlow",Bachelor,7,Media,2024-03-27,2024-05-16,725,9.6,Cognitive Computing -AI09715,Data Engineer,113020,EUR,96067,SE,CT,Austria,L,Austria,0,"Data Visualization, Kubernetes, Deep Learning",Associate,5,Consulting,2024-12-27,2025-01-23,753,9.3,Machine Intelligence Group -AI09716,Machine Learning Engineer,213625,USD,213625,EX,FT,Norway,M,Norway,100,"AWS, SQL, Git, Kubernetes",Master,15,Finance,2024-01-08,2024-03-09,562,7.3,Machine Intelligence Group -AI09717,Autonomous Systems Engineer,127115,EUR,108048,SE,FT,Austria,L,Brazil,100,"Spark, MLOps, Python, Tableau",PhD,5,Finance,2024-12-02,2025-02-07,1020,9,Advanced Robotics -AI09718,AI Software Engineer,53464,SGD,69503,EN,PT,Singapore,S,Colombia,0,"Hadoop, Statistics, Mathematics, Docker, AWS",Associate,1,Automotive,2025-04-18,2025-05-21,1121,5.5,Machine Intelligence Group -AI09719,Research Scientist,105947,USD,105947,EN,FT,Denmark,L,Denmark,50,"Kubernetes, Scala, Git",Bachelor,1,Consulting,2024-07-06,2024-08-05,1834,7.7,Cloud AI Solutions -AI09720,AI Research Scientist,389066,CHF,350159,EX,FT,Switzerland,L,Switzerland,0,"Hadoop, SQL, Docker",PhD,10,Finance,2024-08-13,2024-10-19,1479,6.6,Autonomous Tech -AI09721,AI Architect,162534,EUR,138154,EX,FT,Netherlands,S,Chile,100,"Scala, Tableau, Data Visualization, Deep Learning",Bachelor,13,Manufacturing,2024-01-07,2024-02-12,2180,6.9,Neural Networks Co -AI09722,Deep Learning Engineer,67954,EUR,57761,EN,CT,Austria,M,Austria,100,"Mathematics, TensorFlow, MLOps, NLP",Master,1,Transportation,2024-02-23,2024-04-27,2132,9.3,Predictive Systems -AI09723,Machine Learning Researcher,236172,AUD,318832,EX,PT,Australia,M,Australia,0,"SQL, Python, Deep Learning, NLP, Spark",Associate,16,Technology,2025-03-10,2025-04-22,1099,6.6,Cloud AI Solutions -AI09724,AI Architect,235127,EUR,199858,EX,CT,France,L,France,100,"Scala, R, Data Visualization, Azure",Associate,11,Finance,2024-02-14,2024-04-16,1353,7.4,Digital Transformation LLC -AI09725,Robotics Engineer,122654,EUR,104256,MI,FT,Netherlands,L,Netherlands,0,"Azure, Git, GCP, TensorFlow",Master,3,Transportation,2024-03-01,2024-04-29,1111,7.1,Advanced Robotics -AI09726,AI Research Scientist,205223,AUD,277051,EX,FT,Australia,S,Egypt,50,"Deep Learning, Kubernetes, Computer Vision, Hadoop, Data Visualization",Master,15,Transportation,2024-08-03,2024-10-12,2209,5.5,Advanced Robotics -AI09727,Robotics Engineer,148358,SGD,192865,SE,PT,Singapore,M,Egypt,100,"Scala, Statistics, AWS, TensorFlow",Bachelor,6,Healthcare,2024-05-10,2024-06-18,1848,6.6,Quantum Computing Inc -AI09728,Data Scientist,220353,USD,220353,EX,FL,Norway,L,Norway,100,"Python, Azure, Docker",Master,10,Finance,2025-02-25,2025-03-20,648,6.8,Algorithmic Solutions -AI09729,Deep Learning Engineer,189506,EUR,161080,EX,CT,Netherlands,L,Netherlands,50,"Python, MLOps, TensorFlow, AWS, Deep Learning",Associate,17,Healthcare,2024-10-04,2024-10-30,1498,7,Smart Analytics -AI09730,AI Software Engineer,69812,JPY,7679320,EN,FT,Japan,M,Brazil,50,"R, Java, Docker",Master,0,Gaming,2024-06-25,2024-09-04,1792,8.4,Machine Intelligence Group -AI09731,Data Scientist,61754,USD,61754,SE,PT,India,L,India,100,"R, PyTorch, Tableau, Computer Vision",Bachelor,5,Energy,2024-10-30,2025-01-09,993,9.9,Digital Transformation LLC -AI09732,Data Engineer,87674,USD,87674,MI,PT,Finland,S,Finland,0,"Tableau, TensorFlow, Linux, AWS, Computer Vision",Bachelor,3,Automotive,2024-01-27,2024-03-08,1229,8.2,Cloud AI Solutions -AI09733,AI Research Scientist,100642,USD,100642,MI,CT,Norway,S,Vietnam,100,"Scala, SQL, MLOps",PhD,4,Media,2024-08-01,2024-09-25,1487,7.8,Smart Analytics -AI09734,ML Ops Engineer,179394,AUD,242182,EX,FT,Australia,S,Australia,50,"Python, TensorFlow, Statistics",Associate,19,Real Estate,2024-03-19,2024-04-21,1973,7.1,Cognitive Computing -AI09735,AI Consultant,177616,USD,177616,SE,FL,United States,L,United States,50,"Scala, R, Data Visualization",Master,6,Transportation,2024-06-14,2024-08-07,1656,7.7,Cognitive Computing -AI09736,Deep Learning Engineer,31495,USD,31495,EN,CT,China,L,China,100,"NLP, Python, Statistics, SQL",PhD,1,Government,2024-06-21,2024-08-15,1654,6,Predictive Systems -AI09737,AI Consultant,44106,USD,44106,SE,PT,China,S,Nigeria,100,"Computer Vision, PyTorch, Git",Bachelor,9,Government,2024-10-06,2024-10-31,2386,7.4,Neural Networks Co -AI09738,Computer Vision Engineer,60523,EUR,51445,EN,CT,Netherlands,S,Netherlands,100,"SQL, PyTorch, Spark, TensorFlow, Tableau",PhD,0,Manufacturing,2025-02-15,2025-03-29,2025,7.3,Neural Networks Co -AI09739,Deep Learning Engineer,149499,SGD,194349,SE,FT,Singapore,M,Estonia,100,"MLOps, NLP, Tableau, TensorFlow, Java",Bachelor,5,Gaming,2024-09-21,2024-11-16,730,9,Machine Intelligence Group -AI09740,AI Architect,99163,USD,99163,SE,CT,South Korea,L,South Korea,50,"TensorFlow, SQL, Statistics",Bachelor,8,Energy,2024-12-22,2025-02-22,1266,9.5,Predictive Systems -AI09741,Computer Vision Engineer,295991,USD,295991,EX,CT,United States,L,Luxembourg,100,"Spark, TensorFlow, R",PhD,19,Education,2024-05-01,2024-07-04,1775,6.2,Cognitive Computing -AI09742,AI Architect,136129,USD,136129,MI,FL,Norway,L,Norway,100,"PyTorch, Hadoop, Statistics, Git, Deep Learning",PhD,2,Finance,2024-11-04,2024-11-19,1746,5.3,Smart Analytics -AI09743,Deep Learning Engineer,113701,EUR,96646,SE,FT,Austria,S,Austria,100,"R, Linux, Java",Master,5,Automotive,2024-04-06,2024-05-14,1949,7.4,Future Systems -AI09744,AI Architect,81106,CHF,72995,EN,PT,Switzerland,S,Switzerland,0,"Python, Spark, Statistics, Linux",PhD,1,Gaming,2025-02-11,2025-02-25,629,5.7,Advanced Robotics -AI09745,Data Analyst,69980,USD,69980,EX,FL,India,M,India,0,"PyTorch, TensorFlow, Docker, SQL, Statistics",Associate,14,Retail,2025-03-18,2025-04-23,1445,7.7,Digital Transformation LLC -AI09746,ML Ops Engineer,326836,USD,326836,EX,FT,Norway,M,Norway,0,"TensorFlow, SQL, Data Visualization",Bachelor,12,Finance,2024-09-14,2024-11-19,840,6.8,Algorithmic Solutions -AI09747,Data Engineer,99357,EUR,84453,SE,FL,Austria,M,Austria,50,"Python, Java, Azure, AWS",Bachelor,7,Automotive,2024-10-08,2024-11-16,560,6.6,DataVision Ltd -AI09748,Machine Learning Researcher,147291,USD,147291,EX,PT,Israel,L,Israel,50,"PyTorch, Spark, R, Git, Tableau",PhD,16,Manufacturing,2024-11-06,2024-11-27,1962,9.5,Digital Transformation LLC -AI09749,AI Research Scientist,241227,USD,241227,EX,FT,Norway,S,Norway,100,"Python, Spark, Tableau, TensorFlow, Deep Learning",Master,12,Media,2025-04-01,2025-05-12,667,7.5,TechCorp Inc -AI09750,Research Scientist,75529,USD,75529,EN,FL,Finland,L,Argentina,50,"Java, PyTorch, NLP, SQL, Scala",Bachelor,0,Manufacturing,2024-07-30,2024-08-24,1470,9.2,Future Systems -AI09751,Machine Learning Engineer,68543,USD,68543,EN,CT,Norway,S,Norway,100,"MLOps, Deep Learning, Data Visualization",Master,1,Telecommunications,2024-03-08,2024-04-16,2407,8.8,Cognitive Computing -AI09752,Principal Data Scientist,69686,USD,69686,EN,CT,United States,S,Czech Republic,100,"PyTorch, SQL, Data Visualization, Deep Learning",Bachelor,0,Telecommunications,2024-03-26,2024-05-18,1978,6.3,Advanced Robotics -AI09753,AI Architect,240290,EUR,204247,EX,CT,Netherlands,M,Netherlands,0,"Scala, Python, Azure",PhD,18,Retail,2024-04-14,2024-06-26,1249,8.2,Neural Networks Co -AI09754,Robotics Engineer,152827,CHF,137544,MI,CT,Switzerland,M,Poland,100,"Kubernetes, Docker, Mathematics",PhD,4,Automotive,2025-04-09,2025-05-17,2154,9.7,DeepTech Ventures -AI09755,AI Software Engineer,124396,EUR,105737,EX,CT,Germany,S,Germany,0,"PyTorch, Deep Learning, Hadoop, Computer Vision, Linux",PhD,15,Retail,2024-08-18,2024-10-09,708,6.3,Smart Analytics -AI09756,Machine Learning Engineer,246978,EUR,209931,EX,FL,Netherlands,M,Netherlands,100,"Azure, Java, PyTorch, Deep Learning, AWS",Bachelor,13,Transportation,2024-04-17,2024-05-26,605,8.1,TechCorp Inc -AI09757,Research Scientist,102797,JPY,11307670,MI,CT,Japan,M,Japan,0,"PyTorch, TensorFlow, Kubernetes",Associate,3,Manufacturing,2024-02-10,2024-04-23,522,7,Machine Intelligence Group -AI09758,Head of AI,67987,SGD,88383,EN,FL,Singapore,S,Singapore,0,"Python, Hadoop, SQL, Git, AWS",Bachelor,1,Consulting,2024-02-27,2024-05-01,761,7.4,Advanced Robotics -AI09759,Data Analyst,283056,USD,283056,EX,FL,Norway,L,Colombia,100,"Hadoop, Tableau, Python, Kubernetes, Mathematics",Master,15,Gaming,2024-10-17,2024-12-10,1021,7.7,Cloud AI Solutions -AI09760,Principal Data Scientist,362848,USD,362848,EX,CT,Norway,L,Norway,100,"GCP, Statistics, MLOps",Associate,13,Media,2025-01-08,2025-02-20,697,5.8,Predictive Systems -AI09761,Data Engineer,63275,SGD,82258,EN,PT,Singapore,M,Singapore,0,"Linux, Kubernetes, Hadoop, Docker, R",Associate,1,Media,2025-01-26,2025-02-13,1719,9.9,Cognitive Computing -AI09762,Data Scientist,61622,GBP,46217,EN,CT,United Kingdom,S,United Kingdom,50,"R, NLP, SQL",PhD,1,Telecommunications,2024-01-28,2024-03-25,1936,9.8,Predictive Systems -AI09763,Principal Data Scientist,82457,CHF,74211,EN,FL,Switzerland,M,Norway,0,"Python, Git, Computer Vision, TensorFlow",PhD,1,Automotive,2024-01-12,2024-02-13,1591,9,Neural Networks Co -AI09764,Head of AI,71625,EUR,60881,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch, Data Visualization, Azure",Associate,4,Gaming,2024-10-08,2024-12-10,1383,8.7,Advanced Robotics -AI09765,NLP Engineer,119422,EUR,101509,MI,FL,Germany,L,Ukraine,50,"PyTorch, TensorFlow, AWS",PhD,3,Media,2024-09-06,2024-10-02,2426,9.7,Quantum Computing Inc -AI09766,Deep Learning Engineer,54944,EUR,46702,EN,CT,Austria,S,Austria,50,"Python, SQL, Mathematics, Java",Associate,1,Finance,2024-10-17,2024-11-24,722,5,Quantum Computing Inc -AI09767,Robotics Engineer,52068,EUR,44258,EN,CT,France,M,France,100,"Python, SQL, Mathematics",Bachelor,1,Technology,2024-11-23,2025-01-20,908,6.3,Neural Networks Co -AI09768,Data Analyst,34503,USD,34503,EN,PT,China,L,Norway,50,"Statistics, Python, TensorFlow, PyTorch",Associate,0,Education,2025-04-01,2025-05-19,2330,7.6,TechCorp Inc -AI09769,Deep Learning Engineer,95396,USD,95396,SE,CT,Sweden,S,Sweden,100,"TensorFlow, SQL, Docker, Statistics",Bachelor,5,Telecommunications,2024-05-06,2024-06-09,1419,5.9,DeepTech Ventures -AI09770,AI Specialist,143291,EUR,121797,EX,CT,France,S,France,50,"PyTorch, R, TensorFlow, Computer Vision, GCP",PhD,14,Education,2025-02-27,2025-04-06,751,9.6,Cognitive Computing -AI09771,NLP Engineer,66180,USD,66180,EN,PT,Sweden,M,South Korea,50,"PyTorch, Git, Tableau",Bachelor,1,Government,2024-03-25,2024-05-15,1216,6.1,Digital Transformation LLC -AI09772,AI Product Manager,142280,USD,142280,SE,CT,Finland,M,Finland,0,"Python, Scala, Computer Vision, Tableau",Bachelor,9,Education,2024-11-23,2024-12-14,947,9.6,Cognitive Computing -AI09773,Principal Data Scientist,72824,USD,72824,MI,FT,South Korea,S,South Korea,50,"Computer Vision, GCP, Linux",Bachelor,3,Automotive,2024-09-14,2024-10-31,1124,6.5,Quantum Computing Inc -AI09774,AI Software Engineer,91337,JPY,10047070,MI,FT,Japan,M,Japan,0,"PyTorch, Docker, SQL, Deep Learning",PhD,3,Government,2024-07-15,2024-09-01,653,6.4,Quantum Computing Inc -AI09775,Machine Learning Researcher,59812,USD,59812,EN,FT,Israel,S,Hungary,0,"Python, Kubernetes, TensorFlow",PhD,1,Transportation,2024-10-02,2024-12-10,2279,9.5,Machine Intelligence Group -AI09776,Machine Learning Engineer,94416,CAD,118020,MI,PT,Canada,M,Canada,100,"Linux, Spark, Scala, Python",Associate,4,Retail,2024-01-31,2024-04-05,1742,5.1,TechCorp Inc -AI09777,Principal Data Scientist,162702,CHF,146432,MI,FL,Switzerland,L,China,100,"Computer Vision, Java, MLOps, Spark",Bachelor,4,Transportation,2024-08-24,2024-09-15,1799,5.4,Future Systems -AI09778,ML Ops Engineer,208539,CAD,260674,EX,FL,Canada,L,Canada,0,"SQL, Python, Git",PhD,16,Consulting,2024-07-13,2024-08-02,1191,5.7,Neural Networks Co -AI09779,Data Engineer,293805,USD,293805,EX,PT,Norway,L,Norway,100,"Java, Linux, Kubernetes, Deep Learning, Git",Master,13,Retail,2025-03-18,2025-05-24,1990,7.4,Digital Transformation LLC -AI09780,Robotics Engineer,109663,USD,109663,MI,FT,Norway,L,Norway,100,"NLP, Hadoop, Spark, PyTorch",Bachelor,4,Consulting,2024-04-05,2024-06-15,1177,6.5,Smart Analytics -AI09781,AI Product Manager,62003,USD,62003,EX,PT,India,M,Belgium,50,"Kubernetes, Data Visualization, Linux, Python, Scala",PhD,10,Government,2025-04-28,2025-07-07,1364,8.1,TechCorp Inc -AI09782,Deep Learning Engineer,110601,USD,110601,MI,PT,Denmark,S,Denmark,100,"MLOps, Docker, Kubernetes, Tableau, PyTorch",Master,4,Transportation,2024-07-21,2024-08-27,1275,6.7,AI Innovations -AI09783,Machine Learning Engineer,97802,USD,97802,SE,FL,Finland,S,Finland,100,"PyTorch, SQL, GCP, Docker",Master,7,Technology,2025-01-05,2025-03-01,1277,8.1,Future Systems -AI09784,AI Research Scientist,31409,USD,31409,EN,FL,China,S,China,100,"Scala, MLOps, SQL, Hadoop",Bachelor,0,Manufacturing,2024-02-28,2024-04-05,987,7,DataVision Ltd -AI09785,Data Analyst,217049,USD,217049,EX,CT,Ireland,S,Ireland,100,"Scala, Spark, Computer Vision, AWS",Bachelor,15,Energy,2025-01-02,2025-02-14,527,5.7,Future Systems -AI09786,AI Consultant,113873,USD,113873,SE,FL,Finland,L,Finland,0,"Statistics, MLOps, Python, Hadoop",Bachelor,5,Gaming,2024-02-15,2024-04-22,929,6.8,AI Innovations -AI09787,Data Scientist,154501,CHF,139051,MI,CT,Switzerland,M,France,50,"Python, TensorFlow, Linux, PyTorch, Scala",Associate,4,Technology,2024-07-05,2024-08-07,2288,8.3,Cloud AI Solutions -AI09788,Data Analyst,65431,CAD,81789,EN,PT,Canada,S,Belgium,100,"AWS, NLP, Git",Bachelor,1,Finance,2024-11-24,2024-12-11,2365,7.8,Cognitive Computing -AI09789,AI Consultant,182995,CAD,228744,EX,FL,Canada,S,Canada,0,"PyTorch, Hadoop, Mathematics, NLP",Bachelor,14,Transportation,2024-07-11,2024-09-11,1806,8.5,DataVision Ltd -AI09790,Data Engineer,69850,JPY,7683500,EN,FL,Japan,S,Japan,100,"SQL, NLP, Docker",PhD,1,Transportation,2025-01-26,2025-03-23,736,6.1,Neural Networks Co -AI09791,Data Engineer,204758,EUR,174044,EX,FL,Germany,S,Romania,100,"Scala, Kubernetes, Deep Learning",Associate,14,Gaming,2024-01-24,2024-02-07,2040,7.5,DataVision Ltd -AI09792,Robotics Engineer,118924,USD,118924,SE,CT,South Korea,M,South Korea,50,"Kubernetes, Git, TensorFlow",Master,9,Manufacturing,2025-02-14,2025-04-06,2190,8,Algorithmic Solutions -AI09793,AI Specialist,140720,GBP,105540,SE,CT,United Kingdom,M,Austria,50,"Spark, Hadoop, Linux, Scala",Bachelor,7,Technology,2024-10-21,2024-11-09,899,8.4,Cognitive Computing -AI09794,AI Consultant,83079,EUR,70617,MI,FT,Germany,S,Germany,100,"R, SQL, Statistics",Associate,4,Manufacturing,2025-04-08,2025-05-28,2250,9.7,DataVision Ltd -AI09795,Head of AI,160182,SGD,208237,SE,CT,Singapore,L,Canada,50,"Git, NLP, AWS",Bachelor,7,Consulting,2024-10-21,2024-11-07,2076,8.2,Predictive Systems -AI09796,AI Consultant,64536,USD,64536,EN,FL,Ireland,M,Ireland,0,"SQL, Hadoop, Mathematics",Bachelor,0,Healthcare,2024-01-22,2024-03-28,2158,9.8,Neural Networks Co -AI09797,Machine Learning Engineer,250363,AUD,337990,EX,FT,Australia,L,Australia,50,"MLOps, SQL, TensorFlow, R",Master,18,Consulting,2024-02-12,2024-04-03,1816,9.1,Quantum Computing Inc -AI09798,Data Engineer,45433,USD,45433,SE,PT,India,L,India,100,"Computer Vision, Spark, Statistics",Bachelor,7,Education,2024-08-28,2024-10-05,1982,7.3,Advanced Robotics -AI09799,Data Analyst,63135,CAD,78919,EN,FT,Canada,L,Sweden,0,"SQL, MLOps, Scala, TensorFlow",Associate,1,Manufacturing,2025-04-28,2025-07-10,2401,5.4,Neural Networks Co -AI09800,Data Scientist,72576,USD,72576,EX,FL,China,S,Italy,50,"Git, AWS, Scala, Data Visualization",Associate,10,Real Estate,2024-03-25,2024-05-12,678,8.2,DeepTech Ventures -AI09801,Research Scientist,137937,USD,137937,EX,CT,South Korea,M,South Korea,100,"Python, Statistics, Spark",Master,18,Energy,2024-07-11,2024-08-15,1878,8.4,Algorithmic Solutions -AI09802,Autonomous Systems Engineer,137663,EUR,117014,SE,CT,France,L,France,50,"Java, Spark, Mathematics, PyTorch",Bachelor,6,Consulting,2025-02-11,2025-03-12,1432,7,Machine Intelligence Group -AI09803,AI Consultant,201971,USD,201971,EX,FL,Sweden,L,Sweden,50,"Python, Data Visualization, Linux, GCP",Associate,19,Energy,2024-03-02,2024-04-18,1265,7.5,Digital Transformation LLC -AI09804,Data Scientist,49095,USD,49095,MI,CT,China,M,Egypt,0,"Tableau, Java, Azure, NLP, Python",PhD,4,Media,2024-10-20,2024-11-24,1490,6.8,Cognitive Computing -AI09805,Research Scientist,210286,USD,210286,EX,FT,United States,L,Czech Republic,0,"Spark, Linux, Scala",PhD,17,Transportation,2024-11-16,2024-12-02,2014,8.8,TechCorp Inc -AI09806,AI Specialist,196218,USD,196218,SE,PT,Denmark,M,Ghana,50,"Hadoop, Docker, Deep Learning, GCP, SQL",Associate,8,Energy,2024-08-22,2024-10-07,2279,8.6,Future Systems -AI09807,Machine Learning Engineer,18616,USD,18616,EN,FT,India,S,India,50,"Git, Tableau, Kubernetes, Data Visualization",Associate,0,Media,2024-07-20,2024-09-07,894,5.4,Machine Intelligence Group -AI09808,Autonomous Systems Engineer,118826,USD,118826,MI,FT,Finland,L,Finland,0,"Kubernetes, Docker, R",Associate,4,Education,2024-05-17,2024-06-12,1146,8.2,DataVision Ltd -AI09809,Computer Vision Engineer,277649,USD,277649,EX,FT,United States,L,Japan,100,"Statistics, SQL, Deep Learning",Associate,15,Media,2024-10-15,2024-12-11,2120,9.6,Advanced Robotics -AI09810,AI Research Scientist,67075,EUR,57014,MI,PT,France,S,France,50,"Linux, Scala, Computer Vision, PyTorch",Associate,2,Manufacturing,2024-08-24,2024-09-26,669,6.5,Autonomous Tech -AI09811,Machine Learning Engineer,62913,JPY,6920430,EN,FT,Japan,L,Japan,100,"SQL, Java, Mathematics",Bachelor,0,Media,2025-03-09,2025-03-25,1843,5.3,TechCorp Inc -AI09812,AI Software Engineer,95618,CHF,86056,MI,CT,Switzerland,S,India,50,"Computer Vision, Statistics, Kubernetes, Java",PhD,4,Education,2024-03-27,2024-06-01,1596,5.5,Future Systems -AI09813,Head of AI,219644,USD,219644,SE,PT,Norway,L,United States,100,"Git, Deep Learning, Python, Computer Vision",Bachelor,9,Education,2025-02-01,2025-03-18,1841,8.8,Quantum Computing Inc -AI09814,AI Research Scientist,183702,CHF,165332,SE,FT,Switzerland,L,Switzerland,50,"Computer Vision, Tableau, Git, MLOps, NLP",PhD,8,Telecommunications,2024-08-06,2024-08-28,1473,9.6,DeepTech Ventures -AI09815,Computer Vision Engineer,68877,AUD,92984,EN,PT,Australia,S,Australia,100,"SQL, PyTorch, Git, AWS, TensorFlow",Bachelor,1,Telecommunications,2025-03-03,2025-04-29,2430,5.8,Machine Intelligence Group -AI09816,AI Specialist,130605,EUR,111014,EX,CT,Austria,M,Austria,100,"Spark, R, Kubernetes",PhD,13,Consulting,2024-04-21,2024-05-18,1198,5.8,Advanced Robotics -AI09817,Machine Learning Researcher,204630,AUD,276251,EX,FT,Australia,S,Australia,50,"Azure, PyTorch, Linux",Associate,17,Consulting,2024-03-23,2024-05-13,1441,6.7,TechCorp Inc -AI09818,Machine Learning Researcher,52908,USD,52908,SE,PT,China,S,Ghana,0,"Python, Azure, Deep Learning, NLP",PhD,9,Manufacturing,2024-11-07,2024-12-03,1769,5.9,Predictive Systems -AI09819,AI Consultant,94508,CHF,85057,EN,FT,Switzerland,L,Russia,50,"Computer Vision, MLOps, Tableau",PhD,0,Retail,2024-04-23,2024-06-11,970,8.7,Machine Intelligence Group -AI09820,AI Consultant,129697,GBP,97273,SE,PT,United Kingdom,L,Denmark,50,"Hadoop, PyTorch, AWS, Linux, NLP",Associate,6,Consulting,2025-03-07,2025-03-30,895,8.6,Future Systems -AI09821,Computer Vision Engineer,114261,EUR,97122,SE,FT,France,S,France,0,"Computer Vision, Python, Mathematics",Bachelor,8,Retail,2024-10-15,2024-12-24,1576,7.1,Cloud AI Solutions -AI09822,Principal Data Scientist,66838,AUD,90231,EN,CT,Australia,L,Ukraine,50,"Azure, Linux, MLOps, Scala",Master,1,Transportation,2024-04-06,2024-06-15,2404,8,DeepTech Ventures -AI09823,Data Engineer,74558,CHF,67102,EN,CT,Switzerland,S,Switzerland,0,"Mathematics, GCP, Docker, AWS",Bachelor,0,Healthcare,2024-06-05,2024-08-15,1416,8.9,Autonomous Tech -AI09824,Autonomous Systems Engineer,77135,JPY,8484850,EN,FT,Japan,L,Japan,100,"Kubernetes, Statistics, PyTorch",Associate,1,Healthcare,2024-11-19,2025-01-27,805,6.4,Cognitive Computing -AI09825,AI Architect,186851,USD,186851,EX,FL,Norway,M,Norway,50,"Mathematics, R, Spark, Computer Vision",Bachelor,12,Media,2025-03-31,2025-05-03,804,9.9,Machine Intelligence Group -AI09826,AI Product Manager,77859,USD,77859,EN,FT,Sweden,M,Sweden,100,"Spark, Java, Statistics, Mathematics",Master,1,Government,2024-02-14,2024-03-12,1780,9.3,Cognitive Computing -AI09827,Deep Learning Engineer,90139,USD,90139,EN,FT,Denmark,M,Turkey,0,"TensorFlow, SQL, Python, NLP, AWS",Associate,0,Healthcare,2024-09-11,2024-10-03,852,8.2,Cognitive Computing -AI09828,AI Specialist,149714,USD,149714,MI,CT,Denmark,L,Denmark,0,"Python, SQL, NLP, Hadoop",Bachelor,2,Government,2025-04-05,2025-06-09,1519,8.6,Cloud AI Solutions -AI09829,Autonomous Systems Engineer,176198,EUR,149768,EX,CT,Austria,M,Latvia,50,"Deep Learning, Spark, Java, Computer Vision",Master,19,Government,2024-03-12,2024-05-07,1526,8.8,DeepTech Ventures -AI09830,AI Consultant,228336,CHF,205502,EX,FT,Switzerland,M,South Africa,0,"Java, Spark, Azure, Linux",Bachelor,19,Real Estate,2024-08-31,2024-09-16,805,5.5,Digital Transformation LLC -AI09831,Computer Vision Engineer,17942,USD,17942,EN,FL,India,S,South Korea,50,"Data Visualization, PyTorch, TensorFlow, SQL",PhD,1,Technology,2024-08-22,2024-10-28,1023,8.8,DataVision Ltd -AI09832,Autonomous Systems Engineer,140214,USD,140214,SE,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch, Azure",Bachelor,5,Real Estate,2024-09-22,2024-11-15,609,9.5,DeepTech Ventures -AI09833,AI Specialist,234802,USD,234802,EX,CT,Ireland,M,Ireland,0,"Spark, Kubernetes, Tableau, R, Linux",Master,12,Healthcare,2024-05-15,2024-07-25,906,8.3,Cognitive Computing -AI09834,AI Architect,54715,SGD,71130,EN,FL,Singapore,M,Singapore,50,"Data Visualization, Scala, NLP, Python, Mathematics",Master,1,Government,2025-01-29,2025-04-03,2046,6,Algorithmic Solutions -AI09835,AI Architect,288436,USD,288436,EX,FL,Norway,L,Singapore,100,"Java, Computer Vision, PyTorch, TensorFlow",Master,17,Healthcare,2025-01-21,2025-04-01,1751,8.3,Future Systems -AI09836,Robotics Engineer,77512,EUR,65885,MI,PT,Germany,S,Brazil,0,"Scala, R, Kubernetes",Master,3,Finance,2024-01-25,2024-02-29,704,5.5,DataVision Ltd -AI09837,Research Scientist,230817,GBP,173113,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, Hadoop, Spark",Bachelor,16,Healthcare,2025-01-14,2025-03-08,1547,8.9,Smart Analytics -AI09838,Data Analyst,126549,EUR,107567,SE,PT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, MLOps, AWS, Azure",Associate,7,Media,2025-03-07,2025-05-03,634,6.9,Digital Transformation LLC -AI09839,AI Specialist,55058,JPY,6056380,EN,CT,Japan,S,Japan,100,"Python, Mathematics, TensorFlow",Bachelor,0,Consulting,2024-06-15,2024-08-19,1925,6.1,Future Systems -AI09840,Data Engineer,123391,USD,123391,EX,PT,Israel,S,Mexico,50,"Java, Kubernetes, Tableau",Associate,11,Healthcare,2024-06-07,2024-06-23,2028,8.8,Autonomous Tech -AI09841,NLP Engineer,322051,USD,322051,EX,PT,Norway,L,Norway,100,"Git, R, Python, Computer Vision",Associate,11,Healthcare,2024-12-14,2025-01-08,2432,9.6,Quantum Computing Inc -AI09842,Research Scientist,37366,USD,37366,EN,FL,China,L,United Kingdom,0,"Git, SQL, NLP, PyTorch, Computer Vision",Master,0,Consulting,2024-01-24,2024-03-07,979,7.4,Autonomous Tech -AI09843,NLP Engineer,243682,EUR,207130,EX,FT,Netherlands,M,Netherlands,0,"Git, Python, TensorFlow",PhD,11,Manufacturing,2024-05-07,2024-06-26,1216,7.7,Predictive Systems -AI09844,Robotics Engineer,159124,CHF,143212,MI,FT,Switzerland,L,Switzerland,50,"Linux, GCP, Data Visualization",PhD,3,Media,2024-06-20,2024-07-07,2172,8,Algorithmic Solutions -AI09845,Computer Vision Engineer,49586,SGD,64462,EN,FT,Singapore,S,South Africa,0,"AWS, Git, PyTorch, Deep Learning",Associate,1,Finance,2024-02-20,2024-04-16,2441,9.9,Advanced Robotics -AI09846,Research Scientist,307401,USD,307401,EX,FL,United States,L,United States,50,"AWS, MLOps, Azure",PhD,10,Energy,2024-06-07,2024-07-08,1586,7.7,Neural Networks Co -AI09847,Robotics Engineer,173982,USD,173982,EX,CT,South Korea,S,South Korea,100,"Scala, Computer Vision, Python, Git, NLP",Associate,13,Manufacturing,2025-02-12,2025-03-20,725,7.4,Smart Analytics -AI09848,AI Product Manager,143207,USD,143207,SE,CT,Israel,M,Germany,0,"Python, NLP, TensorFlow",PhD,7,Telecommunications,2024-11-05,2024-11-25,1967,8.9,Algorithmic Solutions -AI09849,AI Research Scientist,144621,SGD,188007,EX,CT,Singapore,S,Singapore,0,"Linux, GCP, Scala",Associate,12,Healthcare,2024-05-31,2024-07-01,1397,6.9,Autonomous Tech -AI09850,AI Consultant,80428,EUR,68364,EN,FT,Germany,M,India,0,"SQL, Tableau, Scala, Git",PhD,0,Manufacturing,2024-11-19,2025-01-19,1987,8.8,Autonomous Tech -AI09851,ML Ops Engineer,306456,SGD,398393,EX,FL,Singapore,L,France,0,"Tableau, AWS, TensorFlow, Python, SQL",PhD,17,Manufacturing,2024-02-27,2024-03-27,2234,9.5,TechCorp Inc -AI09852,Data Scientist,123489,USD,123489,MI,PT,Denmark,M,Sweden,0,"Hadoop, Python, Data Visualization, Kubernetes",Associate,3,Gaming,2025-03-05,2025-04-21,761,8.1,Predictive Systems -AI09853,Machine Learning Researcher,131962,USD,131962,EX,CT,China,L,China,100,"Hadoop, SQL, Data Visualization",Bachelor,18,Retail,2024-01-03,2024-03-12,1973,8.6,Predictive Systems -AI09854,Principal Data Scientist,115511,CAD,144389,SE,FT,Canada,L,Canada,0,"Linux, Kubernetes, GCP, NLP",PhD,6,Technology,2024-06-30,2024-08-27,2363,6.6,Cloud AI Solutions -AI09855,Data Analyst,144101,EUR,122486,SE,PT,Netherlands,M,Netherlands,100,"R, Git, SQL, Java, Data Visualization",Master,9,Healthcare,2024-09-29,2024-10-14,961,5.2,Future Systems -AI09856,Data Engineer,187329,GBP,140497,EX,FT,United Kingdom,L,Russia,0,"Python, Java, Tableau, TensorFlow",Master,10,Energy,2024-12-03,2025-02-09,2026,9.2,Algorithmic Solutions -AI09857,Autonomous Systems Engineer,113840,CAD,142300,SE,CT,Canada,S,Canada,50,"Linux, Python, Tableau, Data Visualization",PhD,7,Technology,2024-11-20,2025-01-01,926,9.2,Digital Transformation LLC -AI09858,Principal Data Scientist,246771,USD,246771,EX,CT,Norway,M,Ghana,100,"R, Deep Learning, Azure, Linux, Kubernetes",Bachelor,19,Government,2024-04-29,2024-07-07,1293,7.2,Advanced Robotics -AI09859,AI Software Engineer,126469,SGD,164410,MI,PT,Singapore,L,Singapore,0,"Azure, R, Java, Python, SQL",Associate,4,Education,2024-01-22,2024-04-04,1395,8.6,Machine Intelligence Group -AI09860,Data Scientist,23821,USD,23821,MI,FL,India,S,India,100,"Git, Java, R",Bachelor,4,Gaming,2024-04-07,2024-06-03,1821,9.8,Cloud AI Solutions -AI09861,Research Scientist,165461,EUR,140642,SE,FT,Netherlands,L,Netherlands,100,"Mathematics, Data Visualization, Linux",Associate,8,Media,2024-11-25,2024-12-14,2016,9.1,Machine Intelligence Group -AI09862,AI Consultant,24465,USD,24465,EN,CT,India,L,India,50,"SQL, Scala, Deep Learning",Bachelor,1,Media,2024-12-15,2025-01-16,1653,7,DeepTech Ventures -AI09863,Machine Learning Researcher,83518,EUR,70990,MI,FT,Germany,M,Germany,100,"Python, NLP, Git, Kubernetes",Associate,4,Healthcare,2024-06-10,2024-07-29,1380,5.1,Neural Networks Co -AI09864,AI Software Engineer,172981,USD,172981,EX,PT,Sweden,S,Luxembourg,50,"Git, Linux, Computer Vision",Associate,16,Retail,2024-02-11,2024-04-13,673,7,Smart Analytics -AI09865,AI Specialist,68862,EUR,58533,MI,CT,Austria,M,Austria,0,"Linux, SQL, Tableau",Master,4,Technology,2024-09-03,2024-11-08,1318,6,Cognitive Computing -AI09866,Computer Vision Engineer,126859,USD,126859,SE,PT,Israel,S,Israel,50,"AWS, Git, Java",Master,7,Consulting,2024-09-13,2024-10-13,626,8.2,Smart Analytics -AI09867,Robotics Engineer,71219,CHF,64097,EN,FT,Switzerland,S,Switzerland,100,"SQL, Scala, Data Visualization, Linux, TensorFlow",PhD,0,Transportation,2024-09-07,2024-10-11,1446,7.2,Quantum Computing Inc -AI09868,AI Consultant,125998,EUR,107098,SE,CT,Austria,L,Austria,50,"SQL, Git, R, PyTorch, Computer Vision",Master,6,Media,2024-10-09,2024-11-27,2170,9.9,Cognitive Computing -AI09869,Head of AI,178944,USD,178944,SE,CT,Denmark,M,Denmark,50,"Kubernetes, Hadoop, MLOps",Bachelor,7,Real Estate,2024-02-29,2024-04-12,1915,7.6,Algorithmic Solutions -AI09870,Deep Learning Engineer,147376,USD,147376,EX,PT,Ireland,M,Ireland,0,"Java, Computer Vision, NLP, PyTorch, Statistics",Bachelor,17,Manufacturing,2024-05-03,2024-06-08,947,9,Predictive Systems -AI09871,Data Analyst,76399,USD,76399,MI,FL,Israel,S,Ukraine,50,"R, Azure, SQL, Computer Vision",Master,2,Manufacturing,2024-04-20,2024-05-31,1191,9.2,Machine Intelligence Group -AI09872,AI Research Scientist,136519,EUR,116041,EX,PT,Germany,M,Austria,100,"Scala, Java, Python, Mathematics, AWS",PhD,19,Manufacturing,2024-08-11,2024-10-16,1833,5.1,DataVision Ltd -AI09873,Deep Learning Engineer,116176,EUR,98750,MI,FL,Austria,L,Austria,50,"Spark, Azure, R, AWS",Master,4,Media,2025-04-06,2025-05-30,2202,5.3,Neural Networks Co -AI09874,AI Research Scientist,114218,AUD,154194,MI,CT,Australia,L,Australia,50,"Hadoop, Kubernetes, SQL",Bachelor,4,Gaming,2025-04-27,2025-05-22,1916,7.5,Digital Transformation LLC -AI09875,Data Analyst,79786,USD,79786,EN,PT,Israel,L,Israel,50,"Spark, Data Visualization, MLOps, Kubernetes, Scala",Bachelor,1,Transportation,2024-03-04,2024-04-12,1711,8.5,TechCorp Inc -AI09876,NLP Engineer,102654,USD,102654,MI,FL,United States,S,United States,50,"PyTorch, MLOps, Deep Learning",Bachelor,3,Telecommunications,2024-10-29,2024-12-28,1731,6.8,Cloud AI Solutions -AI09877,AI Consultant,110047,JPY,12105170,MI,FT,Japan,L,Japan,0,"Scala, Azure, Deep Learning, Linux",PhD,3,Education,2024-08-23,2024-10-11,2493,7.8,TechCorp Inc -AI09878,Robotics Engineer,43437,USD,43437,SE,FT,China,S,China,50,"Java, R, Azure, Data Visualization",PhD,9,Consulting,2024-01-24,2024-02-23,1497,8.3,Digital Transformation LLC -AI09879,AI Architect,197171,CHF,177454,SE,FT,Switzerland,M,Switzerland,100,"AWS, R, Tableau, Mathematics",Bachelor,6,Media,2024-02-18,2024-03-16,1025,5.1,DeepTech Ventures -AI09880,AI Software Engineer,174106,USD,174106,EX,FT,Ireland,L,Ireland,100,"Kubernetes, NLP, TensorFlow, GCP, AWS",PhD,12,Technology,2024-07-15,2024-08-17,1972,9.7,Smart Analytics -AI09881,NLP Engineer,88358,USD,88358,MI,CT,Finland,M,Finland,50,"Docker, MLOps, Python, Mathematics, R",PhD,4,Healthcare,2024-09-27,2024-10-14,2123,7.1,Algorithmic Solutions -AI09882,Head of AI,93787,USD,93787,SE,PT,South Korea,M,India,50,"Computer Vision, PyTorch, Data Visualization",Master,5,Manufacturing,2025-03-02,2025-04-09,1784,6.5,DataVision Ltd -AI09883,Research Scientist,116502,USD,116502,MI,FT,United States,L,United States,100,"NLP, Azure, Data Visualization",PhD,3,Education,2024-02-09,2024-03-30,2387,9.2,Algorithmic Solutions -AI09884,AI Consultant,35301,USD,35301,MI,FT,China,S,Italy,0,"GCP, Deep Learning, Tableau, AWS",PhD,2,Finance,2024-10-18,2024-11-18,820,6.5,DeepTech Ventures -AI09885,Computer Vision Engineer,130851,USD,130851,SE,PT,Denmark,S,Ukraine,0,"TensorFlow, Hadoop, Linux, Kubernetes",Bachelor,5,Retail,2025-03-18,2025-04-05,649,8.2,Digital Transformation LLC -AI09886,AI Research Scientist,122176,USD,122176,SE,FL,Sweden,M,Sweden,100,"Python, Git, Scala, TensorFlow",PhD,9,Government,2024-09-15,2024-10-31,2241,9.2,Future Systems -AI09887,AI Specialist,175333,SGD,227933,SE,FL,Singapore,L,Singapore,50,"Spark, Python, TensorFlow, Tableau",Associate,6,Education,2024-11-19,2025-01-16,826,9,TechCorp Inc -AI09888,Data Scientist,113930,USD,113930,SE,CT,Israel,M,Israel,0,"MLOps, Linux, AWS, Deep Learning, PyTorch",PhD,9,Transportation,2024-03-02,2024-04-27,1764,8.6,Autonomous Tech -AI09889,Data Engineer,122929,USD,122929,MI,FL,Ireland,L,Ireland,100,"PyTorch, R, Java, Python, Spark",Bachelor,2,Automotive,2024-07-09,2024-09-15,1307,8.3,Algorithmic Solutions -AI09890,Research Scientist,188908,EUR,160572,EX,FL,Netherlands,M,Netherlands,100,"Docker, Tableau, Python",PhD,16,Retail,2024-01-20,2024-02-11,1747,7.4,TechCorp Inc -AI09891,AI Architect,66033,USD,66033,EN,PT,South Korea,L,South Korea,50,"Deep Learning, SQL, Mathematics, AWS",PhD,1,Media,2024-06-27,2024-07-20,1478,9.1,Machine Intelligence Group -AI09892,Deep Learning Engineer,148648,AUD,200675,SE,PT,Australia,M,Australia,0,"R, SQL, TensorFlow, Azure, Tableau",Associate,6,Government,2024-08-31,2024-09-28,754,8.7,Smart Analytics -AI09893,Research Scientist,142225,EUR,120891,SE,PT,Germany,M,Germany,50,"Kubernetes, Git, NLP, Mathematics, GCP",Bachelor,9,Transportation,2025-03-03,2025-04-09,1697,9.9,Smart Analytics -AI09894,AI Product Manager,163931,USD,163931,EX,FL,Finland,M,Finland,50,"SQL, Kubernetes, Python, Spark, R",Master,13,Real Estate,2024-11-08,2025-01-08,1318,8.9,DataVision Ltd -AI09895,Autonomous Systems Engineer,71392,EUR,60683,EN,FT,Austria,M,Austria,50,"GCP, Java, Kubernetes, Spark",PhD,1,Finance,2024-02-23,2024-04-28,1661,5.7,Neural Networks Co -AI09896,Machine Learning Researcher,111415,JPY,12255650,SE,FL,Japan,S,Sweden,100,"Deep Learning, Kubernetes, R, TensorFlow, Java",Bachelor,6,Retail,2024-04-04,2024-05-16,742,8,Algorithmic Solutions -AI09897,NLP Engineer,67040,CAD,83800,EN,FL,Canada,M,Canada,0,"MLOps, Linux, Docker, Kubernetes",Master,1,Media,2024-10-25,2025-01-05,1056,8.1,Smart Analytics -AI09898,Research Scientist,336020,USD,336020,EX,CT,Denmark,L,Denmark,0,"Java, Git, PyTorch, AWS, Kubernetes",Master,16,Media,2024-01-25,2024-03-09,1964,6.8,DataVision Ltd -AI09899,AI Consultant,194195,USD,194195,SE,FL,Norway,L,Israel,50,"Scala, Python, NLP",Master,6,Retail,2025-02-12,2025-03-31,2305,7.2,DataVision Ltd -AI09900,AI Software Engineer,110004,EUR,93503,MI,FT,Germany,L,Germany,0,"AWS, Computer Vision, Kubernetes, Java, Spark",Bachelor,2,Consulting,2024-08-08,2024-09-03,1401,5.7,Cognitive Computing -AI09901,NLP Engineer,65717,USD,65717,EN,PT,Finland,S,Finland,0,"Data Visualization, Deep Learning, Spark, AWS",Master,1,Telecommunications,2024-10-08,2024-11-06,2155,8.5,Predictive Systems -AI09902,Data Engineer,80715,GBP,60536,EN,CT,United Kingdom,L,United Kingdom,100,"Azure, NLP, SQL, GCP, Docker",Bachelor,1,Healthcare,2025-01-04,2025-02-25,806,7.6,DataVision Ltd -AI09903,Data Scientist,225112,USD,225112,EX,PT,Ireland,M,Canada,100,"Git, Python, AWS, GCP",Master,19,Retail,2025-03-19,2025-05-21,2392,6,Neural Networks Co -AI09904,Data Engineer,206433,EUR,175468,EX,FL,France,L,Nigeria,50,"Mathematics, Linux, Tableau, Azure",Bachelor,16,Transportation,2025-02-13,2025-02-28,2389,8.6,Algorithmic Solutions -AI09905,Research Scientist,163201,USD,163201,SE,CT,Denmark,S,Denmark,0,"Statistics, NLP, SQL, PyTorch",PhD,8,Automotive,2025-03-20,2025-05-25,1445,9.2,Future Systems -AI09906,Robotics Engineer,210688,EUR,179085,EX,CT,Austria,S,Austria,50,"Java, SQL, Linux, AWS",Bachelor,17,Healthcare,2024-11-03,2024-12-21,1482,6,Algorithmic Solutions -AI09907,AI Specialist,135482,USD,135482,SE,CT,Denmark,S,Denmark,0,"Java, Kubernetes, Hadoop",Master,5,Healthcare,2024-09-03,2024-09-17,1042,5.9,Cloud AI Solutions -AI09908,ML Ops Engineer,80264,SGD,104343,EN,FT,Singapore,M,Netherlands,0,"Azure, GCP, SQL, TensorFlow, Data Visualization",PhD,0,Transportation,2025-01-23,2025-04-03,690,9.9,Smart Analytics -AI09909,AI Consultant,121140,USD,121140,SE,PT,Finland,M,Finland,50,"Mathematics, MLOps, Azure, Linux, SQL",Master,8,Technology,2024-06-30,2024-07-16,689,5.9,Machine Intelligence Group -AI09910,Data Scientist,210071,EUR,178560,EX,PT,Germany,M,Germany,0,"Spark, Statistics, PyTorch, Azure, Mathematics",Bachelor,13,Healthcare,2024-06-21,2024-08-24,1513,5.3,Future Systems -AI09911,Autonomous Systems Engineer,252427,EUR,214563,EX,CT,France,L,Thailand,50,"Python, Linux, TensorFlow",Bachelor,10,Manufacturing,2024-09-26,2024-11-01,2275,7.6,Neural Networks Co -AI09912,AI Architect,211690,USD,211690,EX,PT,Israel,M,Israel,100,"Tableau, Computer Vision, Python, AWS",Associate,11,Real Estate,2024-11-26,2025-01-19,1954,9.6,Advanced Robotics -AI09913,Principal Data Scientist,89052,USD,89052,MI,PT,Ireland,M,Japan,50,"NLP, PyTorch, TensorFlow",Master,2,Media,2025-02-10,2025-04-23,1301,6.4,Machine Intelligence Group -AI09914,Autonomous Systems Engineer,105815,USD,105815,MI,FT,Norway,M,Indonesia,50,"Linux, PyTorch, Kubernetes",Associate,2,Government,2025-02-17,2025-04-07,1594,6.6,DeepTech Ventures -AI09915,AI Research Scientist,107540,USD,107540,SE,FT,Israel,S,Israel,50,"NLP, Hadoop, Kubernetes",Bachelor,7,Manufacturing,2025-02-23,2025-04-09,2336,9.3,DeepTech Ventures -AI09916,ML Ops Engineer,95240,USD,95240,EN,FL,Denmark,M,Denmark,0,"SQL, Data Visualization, PyTorch, Linux",PhD,0,Gaming,2024-06-09,2024-07-06,2323,7.3,DeepTech Ventures -AI09917,Research Scientist,191684,USD,191684,EX,FL,Sweden,S,Sweden,100,"Java, Computer Vision, Git",Master,11,Transportation,2024-02-06,2024-03-04,1230,8.8,Advanced Robotics -AI09918,Principal Data Scientist,59242,USD,59242,EN,FT,South Korea,M,South Korea,50,"Spark, Hadoop, Mathematics, TensorFlow",Associate,1,Consulting,2024-04-08,2024-06-12,1353,6.7,Predictive Systems -AI09919,Machine Learning Researcher,83529,USD,83529,MI,FT,Finland,S,Finland,0,"TensorFlow, Docker, MLOps, Git, GCP",PhD,2,Government,2025-01-20,2025-03-02,1757,6.5,Advanced Robotics -AI09920,Machine Learning Engineer,139067,USD,139067,SE,FT,Finland,M,Finland,50,"Hadoop, Git, Kubernetes, AWS, Python",PhD,9,Technology,2024-03-08,2024-04-13,1871,8.2,Cloud AI Solutions -AI09921,AI Architect,49440,SGD,64272,EN,FT,Singapore,S,Turkey,50,"Data Visualization, NLP, Java, SQL, TensorFlow",Associate,0,Media,2025-04-10,2025-04-26,2447,7.1,Future Systems -AI09922,AI Software Engineer,18220,USD,18220,EN,FT,India,M,India,50,"SQL, TensorFlow, Python, R, Data Visualization",Master,0,Education,2024-04-06,2024-06-15,1271,5.5,Algorithmic Solutions -AI09923,NLP Engineer,65418,USD,65418,EN,FT,Israel,M,Israel,50,"Git, Mathematics, Linux",Bachelor,0,Finance,2024-11-02,2025-01-04,1374,5.7,Cloud AI Solutions -AI09924,Data Analyst,157206,USD,157206,EX,FT,Sweden,M,Sweden,0,"Python, NLP, Mathematics, Spark",Master,14,Automotive,2024-07-16,2024-07-31,2023,9.7,DeepTech Ventures -AI09925,AI Consultant,125227,CHF,112704,EN,PT,Switzerland,L,Switzerland,0,"Docker, Python, Computer Vision, SQL, Linux",Master,1,Manufacturing,2024-02-27,2024-04-03,536,8.5,AI Innovations -AI09926,Data Scientist,99081,USD,99081,SE,FT,Israel,M,Israel,100,"Java, Computer Vision, Kubernetes, Spark",PhD,8,Retail,2024-03-02,2024-04-20,1832,8.1,Neural Networks Co -AI09927,AI Architect,137965,USD,137965,SE,CT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, SQL, Docker, Linux",PhD,7,Retail,2024-09-26,2024-10-26,938,6.3,Cloud AI Solutions -AI09928,AI Product Manager,79335,USD,79335,EN,FT,Sweden,L,Indonesia,100,"MLOps, SQL, Azure, PyTorch",Bachelor,0,Energy,2024-03-04,2024-05-13,2184,7.5,Neural Networks Co -AI09929,Computer Vision Engineer,88458,USD,88458,EX,PT,China,S,China,50,"AWS, R, Tableau, Hadoop",Bachelor,16,Real Estate,2024-12-17,2025-02-24,1991,6.2,Neural Networks Co -AI09930,NLP Engineer,122917,USD,122917,SE,PT,Sweden,S,Sweden,100,"Python, R, GCP, MLOps, Deep Learning",Master,6,Manufacturing,2025-01-18,2025-03-15,763,8.6,Advanced Robotics -AI09931,Autonomous Systems Engineer,51646,JPY,5681060,EN,FT,Japan,S,Poland,0,"Spark, GCP, Docker, R, Kubernetes",Master,1,Transportation,2024-08-09,2024-09-20,1648,6.9,Smart Analytics -AI09932,AI Product Manager,105874,USD,105874,SE,FT,South Korea,S,South Korea,50,"Tableau, Linux, GCP, TensorFlow, Spark",Master,7,Transportation,2024-08-16,2024-09-28,1716,5.8,Machine Intelligence Group -AI09933,AI Specialist,52597,USD,52597,SE,PT,China,S,China,100,"AWS, R, Deep Learning, Computer Vision",Master,8,Telecommunications,2024-12-18,2025-02-25,1975,7.7,Algorithmic Solutions -AI09934,Data Scientist,90978,GBP,68234,MI,PT,United Kingdom,S,United Kingdom,100,"Scala, MLOps, TensorFlow",PhD,4,Healthcare,2024-01-09,2024-01-25,1444,6.4,Algorithmic Solutions -AI09935,Data Analyst,170390,USD,170390,EX,CT,Finland,M,Singapore,0,"Tableau, Azure, SQL, Statistics, AWS",Bachelor,18,Technology,2024-07-20,2024-08-26,650,6.9,Cloud AI Solutions -AI09936,Research Scientist,104491,EUR,88817,MI,CT,Germany,M,Germany,0,"Deep Learning, Linux, Computer Vision, GCP, Docker",PhD,2,Consulting,2024-01-17,2024-02-10,832,8,DeepTech Ventures -AI09937,AI Product Manager,89899,USD,89899,EX,FT,China,M,China,50,"R, AWS, Azure, Deep Learning, Python",Master,12,Real Estate,2025-02-28,2025-04-20,1332,5.4,Neural Networks Co -AI09938,Data Scientist,81953,EUR,69660,EN,PT,Germany,L,Germany,50,"Hadoop, Python, GCP, Deep Learning",Bachelor,0,Manufacturing,2024-12-21,2025-01-18,967,7.3,Neural Networks Co -AI09939,AI Product Manager,63919,GBP,47939,EN,FL,United Kingdom,S,United Kingdom,50,"Docker, SQL, AWS, Mathematics",PhD,0,Finance,2024-05-29,2024-07-25,2267,7,Cognitive Computing -AI09940,AI Software Engineer,251077,USD,251077,EX,PT,Sweden,L,Sweden,50,"Python, GCP, Mathematics, AWS",Bachelor,16,Retail,2024-04-16,2024-05-30,1188,7.2,Future Systems -AI09941,Research Scientist,154431,EUR,131266,EX,CT,Netherlands,M,Israel,0,"Scala, Tableau, Hadoop, Linux",Associate,11,Transportation,2024-09-10,2024-10-31,690,7.3,Machine Intelligence Group -AI09942,Data Scientist,84206,CAD,105258,MI,PT,Canada,S,Canada,0,"Hadoop, Java, SQL, Computer Vision, Azure",Bachelor,3,Real Estate,2024-12-02,2024-12-22,2097,6.3,AI Innovations -AI09943,AI Research Scientist,94103,USD,94103,EX,CT,India,L,Hungary,0,"Hadoop, SQL, Kubernetes",Master,10,Consulting,2024-04-30,2024-06-14,1596,8.2,Quantum Computing Inc -AI09944,Robotics Engineer,172742,EUR,146831,EX,FL,Netherlands,M,Netherlands,100,"Data Visualization, GCP, PyTorch, AWS",Associate,14,Media,2024-05-01,2024-06-22,1002,5.4,DeepTech Ventures -AI09945,AI Consultant,202350,AUD,273173,EX,FL,Australia,S,Australia,0,"Hadoop, Kubernetes, GCP",PhD,18,Media,2024-08-30,2024-10-09,2174,8.1,Predictive Systems -AI09946,AI Product Manager,220924,JPY,24301640,EX,PT,Japan,M,Japan,50,"TensorFlow, Deep Learning, Data Visualization",Associate,18,Government,2025-02-24,2025-04-14,717,6.1,Machine Intelligence Group -AI09947,Machine Learning Engineer,202063,EUR,171754,EX,FL,Germany,L,Germany,100,"Python, TensorFlow, SQL, Linux, Hadoop",Associate,16,Consulting,2024-05-29,2024-08-09,2230,8.7,Digital Transformation LLC -AI09948,NLP Engineer,156925,SGD,204003,SE,PT,Singapore,L,New Zealand,50,"Azure, Spark, Hadoop, Linux, SQL",Bachelor,8,Energy,2025-04-13,2025-05-26,679,8.6,DeepTech Ventures -AI09949,Machine Learning Researcher,127958,USD,127958,SE,FT,United States,S,United States,0,"AWS, SQL, Azure",PhD,6,Consulting,2024-11-25,2025-01-14,2152,9.7,Autonomous Tech -AI09950,AI Architect,88010,USD,88010,MI,PT,Finland,M,Finland,50,"SQL, Data Visualization, Spark, MLOps, Statistics",Bachelor,4,Education,2024-03-04,2024-05-05,2274,9.1,Predictive Systems -AI09951,Data Engineer,73299,USD,73299,EX,CT,India,S,India,0,"Python, Spark, SQL, Deep Learning, Linux",Associate,11,Media,2024-04-15,2024-06-03,668,7.4,Machine Intelligence Group -AI09952,Data Analyst,38886,USD,38886,MI,FT,India,L,India,0,"R, Python, Git, Statistics, Azure",Associate,3,Media,2025-01-14,2025-03-03,2418,5.1,Advanced Robotics -AI09953,Research Scientist,87404,EUR,74293,EN,CT,Netherlands,L,Norway,100,"TensorFlow, GCP, Python, Linux",Bachelor,0,Manufacturing,2024-12-19,2025-02-02,1258,8.5,Future Systems -AI09954,AI Product Manager,50608,EUR,43017,EN,FL,Netherlands,S,Denmark,100,"Spark, MLOps, Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-01-19,2024-03-04,2364,5.5,Advanced Robotics -AI09955,Data Analyst,87958,USD,87958,MI,FL,Sweden,S,Sweden,0,"Java, AWS, Mathematics, Deep Learning",Bachelor,4,Transportation,2024-07-12,2024-09-13,1500,7.9,Cloud AI Solutions -AI09956,NLP Engineer,65492,USD,65492,MI,CT,South Korea,M,Russia,100,"Deep Learning, Python, TensorFlow",Bachelor,2,Gaming,2024-07-06,2024-09-01,1987,9.6,Advanced Robotics -AI09957,Research Scientist,260160,USD,260160,EX,FL,Norway,M,Norway,0,"Linux, Computer Vision, R",Master,17,Finance,2024-03-14,2024-04-12,1484,9.1,AI Innovations -AI09958,Research Scientist,70254,GBP,52691,EN,CT,United Kingdom,M,United Kingdom,0,"Statistics, Tableau, GCP",Master,0,Healthcare,2024-08-06,2024-08-24,1063,7.7,Cognitive Computing -AI09959,NLP Engineer,159037,AUD,214700,EX,FT,Australia,L,Australia,50,"Kubernetes, Docker, Spark",PhD,19,Finance,2025-02-18,2025-03-16,858,6.7,Future Systems -AI09960,Data Scientist,117550,EUR,99918,SE,CT,France,S,France,100,"Computer Vision, Data Visualization, Kubernetes, Scala, Tableau",Master,9,Media,2024-04-08,2024-06-13,1552,7.1,Cognitive Computing -AI09961,Machine Learning Researcher,138817,USD,138817,MI,PT,United States,L,Estonia,50,"R, Deep Learning, TensorFlow, Docker",Master,2,Finance,2025-01-09,2025-03-13,1358,9.7,Neural Networks Co -AI09962,Machine Learning Researcher,233912,AUD,315781,EX,CT,Australia,L,Australia,50,"Hadoop, Linux, Docker",PhD,16,Real Estate,2024-09-26,2024-11-26,1830,8.5,AI Innovations -AI09963,AI Architect,83523,JPY,9187530,EN,FT,Japan,M,Japan,50,"AWS, Docker, Java, R",Associate,1,Transportation,2024-05-26,2024-07-09,1334,8.7,Digital Transformation LLC -AI09964,AI Consultant,49711,USD,49711,SE,CT,India,M,India,0,"PyTorch, Computer Vision, Linux",Bachelor,8,Education,2025-01-13,2025-02-22,1029,7.5,Advanced Robotics -AI09965,AI Product Manager,116921,CAD,146151,SE,FL,Canada,L,Canada,100,"Java, MLOps, SQL",Bachelor,6,Manufacturing,2024-05-09,2024-07-19,2433,8.1,Machine Intelligence Group -AI09966,Data Analyst,213255,CHF,191930,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Linux, Computer Vision, Python, Spark",Associate,8,Healthcare,2024-03-12,2024-04-16,749,7.6,DeepTech Ventures -AI09967,Principal Data Scientist,102306,USD,102306,MI,FL,United States,S,Denmark,0,"Python, NLP, Statistics, Spark, Mathematics",PhD,2,Manufacturing,2024-05-02,2024-05-23,2478,6,Digital Transformation LLC -AI09968,ML Ops Engineer,86619,CAD,108274,MI,CT,Canada,L,Canada,100,"Python, Java, Spark, Computer Vision, TensorFlow",Master,2,Retail,2024-02-08,2024-03-06,1030,7.9,AI Innovations -AI09969,ML Ops Engineer,66607,EUR,56616,EN,FL,Germany,M,Czech Republic,100,"PyTorch, Tableau, Python, Docker, AWS",Bachelor,1,Media,2024-02-14,2024-03-11,2276,9.9,Digital Transformation LLC -AI09970,Head of AI,103856,USD,103856,MI,CT,Ireland,M,Ireland,50,"Computer Vision, Azure, Python, Linux",PhD,3,Retail,2024-10-25,2024-12-04,928,6.4,Digital Transformation LLC -AI09971,AI Consultant,128302,GBP,96227,MI,FT,United Kingdom,L,United Kingdom,100,"Spark, GCP, Deep Learning, Python",Bachelor,2,Transportation,2024-06-22,2024-08-20,648,9.9,Quantum Computing Inc -AI09972,ML Ops Engineer,99518,EUR,84590,MI,PT,Germany,L,Germany,0,"Statistics, MLOps, AWS",Associate,4,Transportation,2024-06-04,2024-06-18,2181,5.9,Cognitive Computing -AI09973,Research Scientist,225083,USD,225083,EX,CT,United States,M,Malaysia,0,"Scala, TensorFlow, Tableau, R",PhD,19,Real Estate,2025-01-09,2025-01-30,1316,7,Quantum Computing Inc -AI09974,Data Scientist,76078,EUR,64666,MI,FL,Austria,S,Austria,100,"R, Java, Linux",Associate,2,Manufacturing,2024-11-29,2024-12-23,871,6,Future Systems -AI09975,Data Analyst,208198,USD,208198,EX,FL,United States,L,China,100,"GCP, R, Spark, SQL",PhD,17,Energy,2024-11-26,2024-12-10,2426,6.8,Machine Intelligence Group -AI09976,Machine Learning Researcher,115497,SGD,150146,SE,FL,Singapore,S,France,50,"Python, Git, Computer Vision, Tableau",Associate,6,Manufacturing,2024-03-23,2024-05-27,1337,7,Advanced Robotics -AI09977,Data Analyst,30191,USD,30191,EN,FL,China,S,South Africa,50,"Python, Computer Vision, Docker, Kubernetes, Git",Master,0,Automotive,2024-06-28,2024-08-09,1509,6.8,Cloud AI Solutions -AI09978,Robotics Engineer,122452,USD,122452,MI,CT,Norway,S,Norway,0,"Spark, PyTorch, Kubernetes, Deep Learning, Tableau",Master,2,Telecommunications,2024-09-10,2024-11-17,1088,7,AI Innovations -AI09979,Robotics Engineer,80064,JPY,8807040,EN,CT,Japan,M,New Zealand,100,"Scala, SQL, Kubernetes, Tableau",Associate,1,Media,2024-12-28,2025-01-16,2318,7.6,Smart Analytics -AI09980,AI Architect,156844,USD,156844,SE,FL,United States,S,United States,50,"Docker, Spark, NLP, SQL, R",Master,8,Telecommunications,2024-01-05,2024-02-18,1084,5.8,Digital Transformation LLC -AI09981,AI Consultant,204204,CHF,183784,SE,CT,Switzerland,L,Switzerland,50,"Spark, AWS, Python",Master,8,Technology,2025-02-24,2025-05-02,1083,6.1,Cloud AI Solutions -AI09982,Principal Data Scientist,33152,USD,33152,MI,PT,India,L,India,100,"Deep Learning, Azure, Scala",Associate,3,Real Estate,2025-02-27,2025-03-31,1465,9.2,TechCorp Inc -AI09983,Data Engineer,65768,USD,65768,SE,FL,China,M,France,100,"R, Statistics, Scala, AWS, Azure",PhD,9,Gaming,2024-12-04,2024-12-25,2408,6.3,Machine Intelligence Group -AI09984,Data Scientist,73194,USD,73194,MI,PT,Sweden,M,Sweden,100,"Docker, Data Visualization, Linux",Associate,3,Retail,2024-08-23,2024-09-08,1618,8.2,AI Innovations -AI09985,AI Architect,55370,SGD,71981,EN,FL,Singapore,S,Singapore,50,"Mathematics, AWS, Hadoop",Associate,0,Retail,2024-11-08,2024-12-07,2104,8.3,Advanced Robotics -AI09986,Deep Learning Engineer,210307,GBP,157730,EX,FT,United Kingdom,M,United Kingdom,0,"GCP, Linux, Computer Vision, Java, Deep Learning",PhD,18,Retail,2024-04-30,2024-06-16,1090,5.3,Digital Transformation LLC -AI09987,AI Research Scientist,84436,USD,84436,EN,FT,United States,M,United States,100,"Java, NLP, GCP, Kubernetes",Master,1,Consulting,2024-04-24,2024-05-12,1654,7.3,Cognitive Computing -AI09988,ML Ops Engineer,54161,AUD,73117,EN,FT,Australia,S,Australia,0,"Azure, Scala, Java",PhD,1,Healthcare,2024-10-22,2024-11-13,1338,8.3,Neural Networks Co -AI09989,AI Software Engineer,205169,USD,205169,EX,CT,United States,M,United States,100,"Python, Tableau, NLP, Computer Vision",Master,12,Transportation,2024-09-27,2024-11-13,2197,5.7,DeepTech Ventures -AI09990,Data Engineer,38591,USD,38591,MI,PT,China,M,Colombia,50,"Python, Statistics, MLOps, TensorFlow, Computer Vision",Master,4,Transportation,2025-01-01,2025-02-12,1506,9.6,Neural Networks Co -AI09991,Research Scientist,68630,EUR,58336,EN,FT,France,L,United Kingdom,50,"R, Python, NLP, Data Visualization",PhD,0,Finance,2025-04-30,2025-06-24,2243,6.6,DeepTech Ventures -AI09992,Autonomous Systems Engineer,43605,USD,43605,SE,CT,China,S,China,0,"PyTorch, Deep Learning, TensorFlow",Bachelor,9,Consulting,2025-03-28,2025-05-18,969,7,Advanced Robotics -AI09993,ML Ops Engineer,161575,USD,161575,EX,CT,Finland,M,Finland,0,"Docker, Scala, Hadoop, TensorFlow, NLP",Master,16,Consulting,2024-11-16,2024-12-06,2224,9.9,Cognitive Computing -AI09994,Autonomous Systems Engineer,45084,USD,45084,MI,FL,China,M,China,50,"Linux, SQL, GCP",Bachelor,3,Telecommunications,2024-05-10,2024-05-29,1998,8.6,Neural Networks Co -AI09995,AI Product Manager,88847,USD,88847,SE,CT,South Korea,S,South Korea,100,"Hadoop, Scala, Tableau",Associate,5,Media,2024-07-09,2024-09-19,1406,5.1,Smart Analytics -AI09996,Data Analyst,273652,USD,273652,EX,PT,Norway,L,Norway,50,"Docker, Statistics, Linux, Python",Master,12,Real Estate,2024-04-28,2024-06-03,1723,8.9,Cognitive Computing -AI09997,AI Specialist,77815,JPY,8559650,EN,CT,Japan,M,Japan,50,"Python, SQL, Data Visualization, MLOps",Bachelor,1,Technology,2024-10-14,2024-12-14,1183,8.1,Cognitive Computing -AI09998,Head of AI,71265,USD,71265,MI,CT,Sweden,S,Ireland,100,"PyTorch, GCP, Kubernetes",Associate,2,Transportation,2024-08-02,2024-09-08,937,7.6,Algorithmic Solutions -AI09999,ML Ops Engineer,206399,USD,206399,EX,CT,United States,L,United States,0,"PyTorch, R, Tableau",Master,18,Automotive,2024-12-04,2024-12-27,1313,9,Neural Networks Co -AI10000,AI Consultant,199903,JPY,21989330,EX,FL,Japan,L,France,0,"Git, Python, Docker",PhD,16,Education,2025-04-27,2025-05-11,2171,7.3,Advanced Robotics -AI10001,AI Specialist,167578,USD,167578,SE,FT,Denmark,S,Denmark,100,"Linux, Python, Hadoop",PhD,6,Healthcare,2024-08-07,2024-09-16,996,9.6,Autonomous Tech -AI10002,AI Architect,154721,CHF,139249,SE,CT,Switzerland,M,Sweden,0,"Python, TensorFlow, MLOps, Azure",Bachelor,6,Government,2024-09-15,2024-10-05,1917,8.6,Future Systems -AI10003,AI Consultant,122754,EUR,104341,SE,FT,Netherlands,S,Czech Republic,100,"Spark, MLOps, TensorFlow, NLP, Mathematics",Master,7,Transportation,2025-01-20,2025-03-05,1738,5.5,Autonomous Tech -AI10004,Data Analyst,68729,USD,68729,EN,FL,Israel,M,Israel,0,"Computer Vision, Statistics, SQL, Python",Master,0,Automotive,2025-03-07,2025-04-07,1313,5.1,Cognitive Computing -AI10005,AI Software Engineer,85966,SGD,111756,EN,FT,Singapore,L,Singapore,100,"Hadoop, Docker, Data Visualization, Python",Associate,0,Education,2025-04-01,2025-04-22,1119,9.4,DataVision Ltd -AI10006,Data Analyst,131244,JPY,14436840,SE,FL,Japan,L,Japan,50,"Git, Scala, Java, Computer Vision",Master,8,Media,2024-03-24,2024-04-26,960,8.3,Autonomous Tech -AI10007,Computer Vision Engineer,122218,USD,122218,SE,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Hadoop, MLOps",Associate,7,Automotive,2024-05-12,2024-07-18,2497,8.8,Quantum Computing Inc -AI10008,Research Scientist,79816,USD,79816,EN,PT,Norway,S,Canada,0,"Python, GCP, AWS",Bachelor,1,Manufacturing,2024-04-19,2024-06-25,546,6.3,Cognitive Computing -AI10009,Machine Learning Engineer,76709,EUR,65203,MI,PT,Netherlands,S,Netherlands,0,"TensorFlow, Azure, Kubernetes, Python, MLOps",Bachelor,2,Media,2024-04-28,2024-06-14,531,8.4,DeepTech Ventures -AI10010,Data Analyst,53982,USD,53982,EN,FT,Ireland,S,South Africa,0,"SQL, Scala, Tableau",Bachelor,0,Government,2024-06-29,2024-09-01,1371,8.3,Future Systems -AI10011,ML Ops Engineer,192615,EUR,163723,EX,FL,France,M,France,0,"Kubernetes, Tableau, Python",PhD,11,Energy,2025-01-29,2025-03-17,505,9.4,DataVision Ltd -AI10012,AI Architect,145605,JPY,16016550,SE,PT,Japan,L,Japan,100,"R, GCP, Java",Bachelor,8,Technology,2025-03-10,2025-04-10,2336,7.4,Neural Networks Co -AI10013,Autonomous Systems Engineer,97274,USD,97274,MI,PT,Denmark,S,Denmark,50,"PyTorch, Azure, Git",Bachelor,2,Technology,2024-10-18,2024-11-27,1260,9,TechCorp Inc -AI10014,AI Specialist,244858,USD,244858,EX,FL,Norway,S,Norway,100,"PyTorch, R, SQL, Statistics",Associate,15,Media,2024-03-14,2024-05-20,1932,7.1,Autonomous Tech -AI10015,Data Engineer,104413,EUR,88751,MI,PT,Netherlands,L,Netherlands,0,"GCP, MLOps, Scala, Kubernetes",Associate,4,Healthcare,2025-03-26,2025-05-18,1269,6.8,AI Innovations -AI10016,AI Specialist,213972,USD,213972,SE,CT,Norway,L,Norway,100,"AWS, Docker, Data Visualization, Deep Learning",Bachelor,6,Education,2024-05-04,2024-07-09,2063,5.1,Advanced Robotics -AI10017,Machine Learning Engineer,163739,USD,163739,EX,CT,Finland,S,Finland,0,"AWS, Kubernetes, Statistics, R",Associate,18,Real Estate,2024-12-11,2025-01-28,1031,8.2,Quantum Computing Inc -AI10018,Head of AI,54758,USD,54758,EN,CT,South Korea,S,Chile,0,"Tableau, Linux, AWS, TensorFlow, Deep Learning",Master,0,Technology,2024-12-13,2025-02-18,1502,6.9,DataVision Ltd -AI10019,Principal Data Scientist,90479,EUR,76907,MI,PT,France,M,Ireland,100,"Docker, R, MLOps, Kubernetes",Associate,4,Telecommunications,2024-03-19,2024-05-02,1148,9.7,Future Systems -AI10020,Deep Learning Engineer,159487,USD,159487,SE,PT,Norway,L,Singapore,100,"Docker, MLOps, Tableau, Python, Kubernetes",PhD,7,Real Estate,2024-09-25,2024-11-25,2469,6.3,Future Systems -AI10021,Computer Vision Engineer,64591,EUR,54902,EN,FT,Netherlands,L,Netherlands,0,"Scala, AWS, SQL, Python",Bachelor,1,Finance,2024-03-15,2024-04-23,2168,6.5,Neural Networks Co -AI10022,AI Product Manager,186453,GBP,139840,EX,CT,United Kingdom,M,Philippines,100,"TensorFlow, Hadoop, AWS, Java, Deep Learning",Bachelor,19,Technology,2024-09-17,2024-11-04,1428,5.1,DataVision Ltd -AI10023,Principal Data Scientist,367782,USD,367782,EX,FT,Denmark,L,Switzerland,0,"Data Visualization, Python, Git",Bachelor,16,Finance,2024-08-20,2024-10-12,1285,8.6,Future Systems -AI10024,Data Scientist,122924,AUD,165947,MI,FL,Australia,L,Spain,0,"Java, Linux, TensorFlow, SQL, MLOps",Master,4,Healthcare,2024-09-05,2024-09-19,797,7.6,Neural Networks Co -AI10025,Autonomous Systems Engineer,243749,AUD,329061,EX,PT,Australia,L,Australia,100,"GCP, Data Visualization, Linux, Computer Vision, SQL",PhD,19,Retail,2025-02-08,2025-03-22,2447,6.4,AI Innovations -AI10026,Computer Vision Engineer,78463,JPY,8630930,MI,CT,Japan,S,Japan,50,"Scala, Data Visualization, Git",Associate,3,Manufacturing,2024-04-17,2024-06-10,2462,9.4,TechCorp Inc -AI10027,Machine Learning Engineer,177410,USD,177410,SE,FT,Norway,M,Norway,0,"Linux, Python, PyTorch, Scala, AWS",Master,6,Consulting,2024-06-25,2024-08-15,1228,9.4,Machine Intelligence Group -AI10028,Robotics Engineer,85282,USD,85282,MI,FL,Israel,M,Israel,0,"Scala, Linux, TensorFlow, GCP, Statistics",PhD,2,Manufacturing,2024-07-04,2024-07-20,607,5.8,Digital Transformation LLC -AI10029,AI Consultant,54574,USD,54574,EN,CT,United States,S,United States,100,"Scala, Docker, Computer Vision, SQL",Master,1,Technology,2024-07-18,2024-08-21,1471,9.1,Algorithmic Solutions -AI10030,AI Architect,99684,JPY,10965240,MI,FL,Japan,M,Malaysia,100,"R, SQL, Kubernetes",Master,4,Transportation,2024-12-14,2025-02-25,1017,7,AI Innovations -AI10031,Autonomous Systems Engineer,107913,EUR,91726,SE,FT,France,S,France,100,"Spark, TensorFlow, Kubernetes",PhD,9,Government,2024-04-05,2024-06-09,769,9.3,Quantum Computing Inc -AI10032,Deep Learning Engineer,110437,SGD,143568,MI,FL,Singapore,L,Singapore,100,"Docker, MLOps, GCP, Python",Associate,2,Technology,2024-03-16,2024-05-18,1027,5.6,Cognitive Computing -AI10033,Data Scientist,32139,USD,32139,MI,FL,China,S,China,0,"Git, Python, Mathematics",Bachelor,2,Real Estate,2024-06-18,2024-07-31,1820,7.2,TechCorp Inc -AI10034,Research Scientist,78757,USD,78757,MI,FL,Ireland,M,Thailand,0,"Python, Tableau, NLP, MLOps",PhD,3,Government,2024-06-24,2024-08-26,1381,9.5,Algorithmic Solutions -AI10035,AI Architect,264042,AUD,356457,EX,FT,Australia,L,Australia,0,"Kubernetes, Statistics, MLOps, R",Associate,12,Telecommunications,2024-02-29,2024-05-01,2038,9.1,Autonomous Tech -AI10036,Data Engineer,208291,USD,208291,EX,PT,Ireland,L,Ireland,50,"Linux, AWS, Python, TensorFlow, Deep Learning",Master,11,Retail,2024-03-06,2024-05-15,1662,7.2,Cloud AI Solutions -AI10037,AI Architect,100038,USD,100038,MI,CT,Denmark,M,Egypt,100,"Kubernetes, Computer Vision, Git, NLP, Deep Learning",PhD,4,Retail,2024-01-23,2024-02-06,2234,6.8,DataVision Ltd -AI10038,NLP Engineer,77060,USD,77060,EN,PT,Norway,L,Israel,0,"Kubernetes, PyTorch, Mathematics",Associate,0,Government,2024-12-25,2025-01-08,1416,6.7,DeepTech Ventures -AI10039,Autonomous Systems Engineer,222150,USD,222150,EX,PT,Denmark,L,Switzerland,50,"Statistics, R, Python, Mathematics, Data Visualization",PhD,16,Gaming,2024-07-07,2024-09-10,1253,6.1,DataVision Ltd -AI10040,Robotics Engineer,163117,USD,163117,EX,CT,Israel,S,France,100,"SQL, Mathematics, Java",Bachelor,15,Education,2025-02-09,2025-04-20,584,6.3,Future Systems -AI10041,Research Scientist,221296,JPY,24342560,EX,PT,Japan,S,Austria,50,"AWS, Scala, GCP",PhD,10,Government,2024-02-06,2024-02-25,616,7.2,Advanced Robotics -AI10042,NLP Engineer,75240,USD,75240,MI,PT,Sweden,M,Sweden,50,"MLOps, NLP, TensorFlow",Bachelor,3,Technology,2024-01-03,2024-01-27,2150,9.7,Algorithmic Solutions -AI10043,AI Specialist,190468,GBP,142851,EX,PT,United Kingdom,S,United Kingdom,100,"R, Azure, Tableau, SQL",Associate,10,Gaming,2024-04-07,2024-05-11,2175,6,AI Innovations -AI10044,Machine Learning Engineer,229205,USD,229205,EX,FL,Norway,L,Norway,0,"Mathematics, PyTorch, Docker",Master,19,Government,2024-07-30,2024-08-27,702,5.6,Machine Intelligence Group -AI10045,AI Product Manager,158082,JPY,17389020,EX,FL,Japan,S,Japan,100,"Linux, Data Visualization, Spark",Bachelor,17,Retail,2024-04-13,2024-06-02,1116,6.2,Neural Networks Co -AI10046,Autonomous Systems Engineer,158388,EUR,134630,SE,PT,Austria,L,Austria,50,"MLOps, Azure, Tableau, Data Visualization",PhD,7,Transportation,2024-09-03,2024-11-15,1409,9.8,DataVision Ltd -AI10047,Deep Learning Engineer,270701,USD,270701,EX,CT,Norway,M,Norway,0,"GCP, Kubernetes, Python",Bachelor,10,Technology,2024-04-22,2024-06-02,673,9.5,AI Innovations -AI10048,AI Specialist,106640,EUR,90644,MI,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Statistics, Docker",PhD,4,Education,2024-12-18,2025-02-15,1432,8.5,TechCorp Inc -AI10049,AI Research Scientist,69424,EUR,59010,MI,FT,France,M,France,50,"GCP, AWS, Docker, Computer Vision, Python",Associate,2,Government,2024-05-11,2024-07-08,848,7,Cloud AI Solutions -AI10050,AI Research Scientist,93528,USD,93528,EN,FT,United States,L,United States,50,"Kubernetes, Docker, Statistics, Scala, Mathematics",Master,0,Transportation,2025-03-09,2025-05-15,1627,6,Autonomous Tech -AI10051,AI Software Engineer,114025,SGD,148233,MI,CT,Singapore,L,Singapore,50,"Scala, Python, Git, GCP, Computer Vision",Bachelor,3,Energy,2025-01-12,2025-02-16,2470,8.2,Cognitive Computing -AI10052,Machine Learning Engineer,91997,EUR,78197,MI,FL,France,S,France,100,"Python, Spark, Git, TensorFlow, Java",Associate,4,Transportation,2025-01-24,2025-02-13,505,8.6,DataVision Ltd -AI10053,Deep Learning Engineer,120244,SGD,156317,SE,PT,Singapore,S,Argentina,0,"Mathematics, Python, Hadoop, Tableau",Master,7,Gaming,2024-04-17,2024-05-07,721,7.3,DataVision Ltd -AI10054,Data Analyst,132194,USD,132194,EX,CT,China,L,China,50,"SQL, PyTorch, MLOps, TensorFlow",PhD,18,Telecommunications,2024-04-22,2024-06-24,1300,5.8,DataVision Ltd -AI10055,AI Specialist,108571,USD,108571,EX,CT,China,M,Kenya,100,"SQL, Linux, TensorFlow, Deep Learning",Bachelor,11,Media,2024-04-30,2024-05-17,1016,7.8,Predictive Systems -AI10056,Autonomous Systems Engineer,75698,USD,75698,EN,FL,Israel,M,Israel,100,"SQL, AWS, Hadoop, Python",Master,1,Technology,2025-03-25,2025-05-09,1791,8.2,AI Innovations -AI10057,Principal Data Scientist,39365,USD,39365,MI,CT,China,L,China,100,"Statistics, Git, GCP, Azure",Associate,3,Transportation,2024-01-19,2024-03-24,2176,8.1,Advanced Robotics -AI10058,Robotics Engineer,183526,EUR,155997,EX,PT,Germany,L,Germany,0,"NLP, Git, Java",Bachelor,10,Automotive,2024-10-10,2024-11-28,974,7.4,DataVision Ltd -AI10059,AI Consultant,143337,EUR,121836,EX,PT,Germany,M,Poland,100,"Data Visualization, SQL, PyTorch",Master,14,Technology,2024-06-16,2024-07-05,1608,5.2,DeepTech Ventures -AI10060,AI Software Engineer,63211,GBP,47408,EN,FL,United Kingdom,M,United Kingdom,50,"NLP, Git, MLOps",Associate,1,Gaming,2024-07-29,2024-09-17,2029,6.6,TechCorp Inc -AI10061,AI Architect,60718,GBP,45539,EN,FL,United Kingdom,S,United Kingdom,0,"GCP, Tableau, Scala, Java, AWS",Associate,0,Consulting,2024-03-05,2024-04-25,1108,9.2,DeepTech Ventures -AI10062,Robotics Engineer,93597,USD,93597,MI,FL,Finland,L,Poland,100,"Python, Scala, Tableau, MLOps, Azure",Bachelor,2,Government,2024-02-26,2024-03-16,1084,9.8,Quantum Computing Inc -AI10063,Deep Learning Engineer,92670,USD,92670,SE,FL,Israel,S,Israel,0,"Spark, Statistics, Linux, Mathematics",Master,9,Energy,2024-02-20,2024-04-18,674,5.5,Digital Transformation LLC -AI10064,Principal Data Scientist,52329,AUD,70644,EN,FL,Australia,M,Australia,100,"Linux, TensorFlow, Azure",Bachelor,1,Gaming,2025-02-07,2025-03-14,648,9.2,Autonomous Tech -AI10065,Autonomous Systems Engineer,110402,CHF,99362,MI,FT,Switzerland,M,Switzerland,100,"SQL, PyTorch, Azure",Bachelor,4,Finance,2024-02-11,2024-03-08,1722,5.9,Digital Transformation LLC -AI10066,Head of AI,79269,EUR,67379,EN,CT,France,L,France,100,"Python, TensorFlow, AWS",PhD,0,Transportation,2024-08-18,2024-10-10,1318,9.9,Cloud AI Solutions -AI10067,Deep Learning Engineer,147090,AUD,198572,SE,CT,Australia,L,Australia,0,"Statistics, GCP, NLP, MLOps",Bachelor,8,Media,2024-08-23,2024-10-13,1890,7.2,Digital Transformation LLC -AI10068,Research Scientist,95456,CAD,119320,SE,CT,Canada,S,Canada,0,"Scala, R, Hadoop, GCP",PhD,7,Technology,2024-01-06,2024-01-26,2009,9.3,Digital Transformation LLC -AI10069,AI Software Engineer,86713,GBP,65035,MI,CT,United Kingdom,S,United Kingdom,0,"R, Data Visualization, PyTorch, Java, Statistics",Associate,2,Real Estate,2024-06-09,2024-07-18,795,9.6,Cloud AI Solutions -AI10070,Robotics Engineer,267784,EUR,227616,EX,PT,Germany,L,Germany,0,"SQL, Java, Statistics, Computer Vision, GCP",PhD,17,Real Estate,2024-01-04,2024-02-25,2268,9,AI Innovations -AI10071,Autonomous Systems Engineer,107929,EUR,91740,MI,FL,Germany,M,Israel,0,"SQL, R, Data Visualization",PhD,4,Healthcare,2025-01-30,2025-03-16,608,9.1,Algorithmic Solutions -AI10072,Data Engineer,187961,USD,187961,SE,FT,Denmark,M,Denmark,50,"Mathematics, Java, Scala",PhD,5,Healthcare,2024-10-26,2024-11-17,887,8.6,Future Systems -AI10073,Research Scientist,79425,USD,79425,EN,CT,United States,S,Portugal,0,"Spark, R, Scala",Bachelor,0,Retail,2024-04-16,2024-05-04,2159,6.3,Machine Intelligence Group -AI10074,Autonomous Systems Engineer,69795,EUR,59326,MI,FL,France,M,France,50,"Java, Mathematics, Kubernetes, TensorFlow",Master,4,Finance,2025-02-19,2025-03-21,1831,9.8,Algorithmic Solutions -AI10075,NLP Engineer,91415,SGD,118840,MI,FT,Singapore,S,Singapore,0,"Computer Vision, Linux, Statistics",Associate,3,Media,2024-06-17,2024-08-24,607,6,Algorithmic Solutions -AI10076,AI Software Engineer,69308,EUR,58912,EN,PT,France,L,France,100,"R, PyTorch, Statistics, Git",Bachelor,0,Healthcare,2024-09-21,2024-11-28,1355,9.4,TechCorp Inc -AI10077,AI Software Engineer,262289,GBP,196717,EX,FT,United Kingdom,L,United Kingdom,100,"Computer Vision, Deep Learning, Data Visualization",Bachelor,12,Government,2025-03-26,2025-05-15,1644,9,Future Systems -AI10078,Research Scientist,117333,USD,117333,MI,PT,Ireland,L,Ireland,50,"Hadoop, Tableau, Java, Deep Learning",PhD,3,Education,2024-03-06,2024-05-10,1796,8,Digital Transformation LLC -AI10079,AI Architect,109771,USD,109771,MI,FT,United States,M,United States,100,"Linux, R, Kubernetes, Deep Learning",Associate,2,Finance,2024-01-09,2024-03-21,2490,5,Algorithmic Solutions -AI10080,NLP Engineer,150367,USD,150367,MI,FT,Norway,L,Romania,50,"SQL, TensorFlow, Computer Vision, AWS, Tableau",Associate,3,Technology,2024-05-15,2024-06-27,1894,5.2,AI Innovations -AI10081,Deep Learning Engineer,88240,EUR,75004,MI,PT,France,M,United Kingdom,100,"Data Visualization, TensorFlow, Docker, GCP, Deep Learning",Bachelor,2,Government,2025-03-26,2025-05-09,2369,9.8,Autonomous Tech -AI10082,NLP Engineer,158509,JPY,17435990,EX,FL,Japan,M,Japan,0,"PyTorch, Git, Scala, GCP",Master,19,Healthcare,2024-08-08,2024-09-13,2335,7.4,Digital Transformation LLC -AI10083,Computer Vision Engineer,95690,CHF,86121,EN,PT,Switzerland,M,Switzerland,100,"NLP, Spark, Python, Mathematics",Associate,0,Healthcare,2024-11-22,2025-01-23,2223,9.4,Digital Transformation LLC -AI10084,Research Scientist,65431,GBP,49073,EN,FL,United Kingdom,S,United Kingdom,100,"Docker, Tableau, Linux, Kubernetes",Associate,0,Transportation,2025-04-16,2025-05-05,1112,8,Cloud AI Solutions -AI10085,Research Scientist,41112,USD,41112,MI,FT,India,L,India,100,"Hadoop, Kubernetes, Python",PhD,4,Media,2024-05-12,2024-06-04,2195,8.7,Cognitive Computing -AI10086,AI Software Engineer,59137,EUR,50266,EN,FT,Netherlands,M,Netherlands,100,"Hadoop, Java, Azure",PhD,0,Transportation,2024-06-10,2024-08-02,514,9.7,Smart Analytics -AI10087,Autonomous Systems Engineer,78995,EUR,67146,MI,FT,Germany,S,Colombia,50,"Scala, Java, AWS",Bachelor,4,Real Estate,2024-06-15,2024-08-07,1977,5.2,DataVision Ltd -AI10088,Computer Vision Engineer,48283,USD,48283,SE,FL,China,S,Austria,0,"AWS, Deep Learning, Spark, SQL, Scala",Master,7,Technology,2024-05-10,2024-06-15,1845,5.8,Algorithmic Solutions -AI10089,Autonomous Systems Engineer,151012,USD,151012,SE,CT,Denmark,S,Australia,50,"Java, Kubernetes, Linux",Master,6,Healthcare,2025-01-29,2025-04-04,621,9.2,Neural Networks Co -AI10090,Deep Learning Engineer,225202,USD,225202,EX,FL,Norway,S,New Zealand,0,"R, Docker, Deep Learning",Associate,10,Technology,2024-01-15,2024-03-12,2018,7,Predictive Systems -AI10091,Computer Vision Engineer,172242,USD,172242,EX,FT,Denmark,S,Denmark,50,"MLOps, NLP, Spark",Associate,18,Telecommunications,2024-08-15,2024-10-24,500,6.8,Algorithmic Solutions -AI10092,AI Consultant,99624,JPY,10958640,MI,PT,Japan,S,Colombia,100,"R, GCP, Computer Vision, Data Visualization, Hadoop",PhD,3,Technology,2025-03-12,2025-04-17,2365,7.9,Neural Networks Co -AI10093,AI Software Engineer,116417,EUR,98954,SE,CT,Netherlands,M,Netherlands,100,"Kubernetes, GCP, AWS, Tableau",Associate,7,Automotive,2024-12-20,2025-02-26,1379,6.9,DeepTech Ventures -AI10094,Deep Learning Engineer,181783,EUR,154516,EX,PT,France,S,Romania,100,"Python, Mathematics, Hadoop, Java",PhD,19,Education,2024-05-01,2024-06-29,557,5.8,DataVision Ltd -AI10095,AI Research Scientist,150971,AUD,203811,SE,CT,Australia,L,Australia,50,"SQL, Hadoop, Mathematics, Git, Docker",Associate,7,Real Estate,2025-01-16,2025-02-04,2333,7.3,Autonomous Tech -AI10096,ML Ops Engineer,94318,USD,94318,MI,PT,Norway,S,Mexico,50,"Scala, GCP, Java, Git",Bachelor,2,Automotive,2024-03-02,2024-05-07,1541,7.2,Algorithmic Solutions -AI10097,AI Research Scientist,95368,GBP,71526,MI,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, AWS, Docker",Bachelor,2,Finance,2025-04-19,2025-05-17,2341,7,TechCorp Inc -AI10098,AI Product Manager,190518,AUD,257199,EX,FT,Australia,M,Australia,100,"Hadoop, Spark, PyTorch",Associate,15,Energy,2024-01-19,2024-02-10,880,9.8,Machine Intelligence Group -AI10099,Computer Vision Engineer,55407,USD,55407,SE,CT,China,L,China,100,"Statistics, NLP, Scala",Master,5,Government,2024-03-02,2024-03-19,2404,7.2,Neural Networks Co -AI10100,ML Ops Engineer,21909,USD,21909,EN,FL,India,S,India,100,"Spark, Kubernetes, Tableau, Linux, Scala",Master,1,Healthcare,2024-07-27,2024-09-24,2258,6.6,Quantum Computing Inc -AI10101,AI Product Manager,92434,EUR,78569,MI,FL,France,M,South Africa,50,"Spark, SQL, Kubernetes, Deep Learning, Mathematics",PhD,3,Retail,2024-02-18,2024-04-04,562,9.3,Advanced Robotics -AI10102,Data Engineer,161210,USD,161210,SE,PT,Denmark,S,Denmark,100,"SQL, GCP, Statistics, Docker",Associate,6,Manufacturing,2024-02-09,2024-03-15,1008,5.9,Future Systems -AI10103,Head of AI,67818,USD,67818,SE,PT,China,L,Belgium,100,"Git, PyTorch, Tableau, R",Bachelor,5,Education,2024-12-28,2025-03-04,972,6.6,Machine Intelligence Group -AI10104,Computer Vision Engineer,93012,EUR,79060,MI,CT,Netherlands,M,Netherlands,0,"MLOps, Scala, Statistics",PhD,3,Finance,2024-03-20,2024-05-18,1313,5.2,Quantum Computing Inc -AI10105,Data Scientist,44243,USD,44243,MI,FL,China,L,China,100,"Python, Spark, MLOps",Associate,4,Education,2025-04-03,2025-06-01,1470,7.3,Algorithmic Solutions -AI10106,Deep Learning Engineer,73792,CAD,92240,EN,CT,Canada,L,South Korea,50,"MLOps, TensorFlow, Scala, Hadoop",PhD,0,Healthcare,2024-07-27,2024-09-16,1612,7.8,TechCorp Inc -AI10107,Deep Learning Engineer,82816,USD,82816,EX,FL,China,L,China,0,"Java, AWS, Azure, Python",Master,17,Energy,2024-04-16,2024-06-26,1824,5.1,DeepTech Ventures -AI10108,Robotics Engineer,153795,EUR,130726,SE,FT,Netherlands,L,Austria,50,"MLOps, TensorFlow, Docker",PhD,5,Technology,2025-04-25,2025-05-26,1033,5.1,TechCorp Inc -AI10109,Machine Learning Researcher,86614,USD,86614,MI,FT,Finland,L,Finland,0,"Python, TensorFlow, AWS",PhD,3,Education,2025-01-09,2025-02-10,827,8.6,Cloud AI Solutions -AI10110,Autonomous Systems Engineer,75523,EUR,64195,EN,FT,France,L,Russia,100,"R, SQL, Docker, MLOps, PyTorch",Master,1,Transportation,2024-06-18,2024-08-12,1776,6.4,Advanced Robotics -AI10111,Principal Data Scientist,105311,USD,105311,SE,PT,Israel,M,Israel,0,"Java, PyTorch, Statistics",PhD,5,Media,2024-07-16,2024-08-13,1714,8.6,Autonomous Tech -AI10112,Machine Learning Engineer,49131,JPY,5404410,EN,CT,Japan,S,Belgium,50,"Hadoop, GCP, Scala, TensorFlow",Master,1,Healthcare,2024-07-30,2024-09-22,1387,6.7,Machine Intelligence Group -AI10113,Head of AI,26483,USD,26483,EN,FL,China,S,China,50,"Java, Computer Vision, Data Visualization, GCP, PyTorch",PhD,1,Consulting,2024-08-06,2024-10-05,1235,8.1,TechCorp Inc -AI10114,Data Engineer,107269,USD,107269,SE,FT,Israel,S,Australia,100,"PyTorch, Spark, SQL, Linux",Associate,9,Energy,2024-10-02,2024-11-22,1007,6,Future Systems -AI10115,AI Product Manager,78026,USD,78026,EN,FL,Denmark,S,Denmark,100,"Git, Python, Linux, Azure",Bachelor,1,Retail,2024-05-22,2024-07-07,2242,6.5,TechCorp Inc -AI10116,ML Ops Engineer,98849,USD,98849,MI,PT,United States,L,Poland,100,"PyTorch, SQL, Data Visualization, Computer Vision",Associate,4,Consulting,2024-11-04,2024-12-28,540,5.1,DataVision Ltd -AI10117,Machine Learning Engineer,246511,USD,246511,EX,PT,Denmark,S,Russia,50,"Hadoop, Python, Tableau",Master,16,Real Estate,2024-02-18,2024-03-26,812,8.6,Algorithmic Solutions -AI10118,Head of AI,108146,CHF,97331,EN,FL,Switzerland,M,Switzerland,0,"Python, AWS, TensorFlow",PhD,0,Telecommunications,2024-03-07,2024-04-06,794,8.1,Algorithmic Solutions -AI10119,Machine Learning Researcher,66740,JPY,7341400,EN,CT,Japan,M,Canada,50,"Tableau, Linux, Kubernetes, PyTorch, Mathematics",Associate,1,Government,2024-04-25,2024-07-03,1062,5,Machine Intelligence Group -AI10120,Machine Learning Engineer,253573,USD,253573,EX,FT,Norway,L,Norway,50,"PyTorch, Python, Java, Tableau, R",Bachelor,17,Government,2024-05-05,2024-06-14,1950,9.2,Cloud AI Solutions -AI10121,Data Engineer,79168,AUD,106877,MI,FL,Australia,S,Australia,100,"Mathematics, Python, R, Git, TensorFlow",PhD,2,Telecommunications,2024-08-05,2024-09-19,993,6.4,Autonomous Tech -AI10122,Data Analyst,139622,EUR,118679,SE,PT,Netherlands,L,Netherlands,50,"Deep Learning, Mathematics, Hadoop, PyTorch",Master,9,Consulting,2025-04-03,2025-06-01,2392,6.5,Cognitive Computing -AI10123,Machine Learning Engineer,43943,USD,43943,SE,FT,India,S,India,50,"SQL, Scala, Python",PhD,9,Telecommunications,2024-04-13,2024-05-31,1723,7.5,TechCorp Inc -AI10124,AI Research Scientist,162422,GBP,121817,EX,FT,United Kingdom,S,United Kingdom,0,"Git, SQL, NLP, Azure, Linux",Master,17,Education,2024-05-16,2024-07-05,1442,5.3,Advanced Robotics -AI10125,ML Ops Engineer,43406,USD,43406,EN,CT,South Korea,S,Mexico,50,"Kubernetes, Java, R, SQL",Bachelor,0,Consulting,2024-09-10,2024-10-02,2472,9.5,Cloud AI Solutions -AI10126,Data Analyst,95920,JPY,10551200,MI,FT,Japan,L,Japan,100,"Python, TensorFlow, Mathematics",Master,2,Transportation,2024-12-02,2025-01-08,2081,9.2,Neural Networks Co -AI10127,AI Consultant,197698,EUR,168043,EX,FT,Germany,S,Germany,100,"GCP, Azure, Python, PyTorch, Java",Master,13,Finance,2024-10-22,2024-12-02,718,5.8,Future Systems -AI10128,AI Specialist,173515,AUD,234245,EX,FT,Australia,L,Nigeria,0,"Python, Scala, AWS, TensorFlow, Linux",Bachelor,16,Finance,2024-02-11,2024-03-27,1432,5.6,AI Innovations -AI10129,AI Specialist,192426,AUD,259775,EX,FL,Australia,L,Philippines,50,"Statistics, Hadoop, SQL",PhD,11,Gaming,2024-04-02,2024-05-30,1928,8.3,Cognitive Computing -AI10130,Research Scientist,212764,USD,212764,SE,CT,Denmark,L,Denmark,50,"Linux, Kubernetes, Data Visualization",Bachelor,8,Technology,2024-09-05,2024-10-01,2235,8.8,Machine Intelligence Group -AI10131,Autonomous Systems Engineer,50136,USD,50136,EN,PT,Finland,M,Finland,0,"AWS, Git, SQL, Azure, Linux",Master,0,Education,2024-10-12,2024-11-30,1646,5.1,Algorithmic Solutions -AI10132,AI Consultant,199327,EUR,169428,EX,FL,Austria,S,Latvia,50,"Python, SQL, Mathematics, Deep Learning",Bachelor,14,Real Estate,2024-04-05,2024-05-26,1617,5.3,AI Innovations -AI10133,AI Architect,104098,CHF,93688,EN,FL,Switzerland,L,Indonesia,100,"Git, Java, Python, TensorFlow, Mathematics",Associate,0,Manufacturing,2024-03-05,2024-04-23,1488,7.5,Quantum Computing Inc -AI10134,Research Scientist,89534,USD,89534,MI,FT,Finland,S,Finland,0,"Kubernetes, Docker, R, Hadoop, PyTorch",PhD,2,Finance,2024-07-07,2024-09-10,2258,8.5,Cloud AI Solutions -AI10135,NLP Engineer,72126,CAD,90158,EN,CT,Canada,L,Canada,0,"Spark, Git, Computer Vision, PyTorch, Kubernetes",PhD,0,Education,2024-09-06,2024-11-11,679,9.5,DataVision Ltd -AI10136,Autonomous Systems Engineer,120139,USD,120139,SE,FL,Sweden,S,Netherlands,100,"Mathematics, Python, Linux, SQL",Master,6,Healthcare,2024-03-05,2024-03-22,1834,8.2,Smart Analytics -AI10137,NLP Engineer,209827,CHF,188844,EX,CT,Switzerland,M,Switzerland,0,"Python, Tableau, Data Visualization, NLP",Master,17,Government,2024-01-31,2024-03-24,1007,5.5,Machine Intelligence Group -AI10138,NLP Engineer,63620,JPY,6998200,EN,FL,Japan,M,Japan,50,"Computer Vision, R, MLOps, SQL, PyTorch",Master,0,Healthcare,2025-04-13,2025-06-21,696,8.1,Autonomous Tech -AI10139,Robotics Engineer,43464,USD,43464,EN,CT,China,L,China,0,"PyTorch, AWS, Hadoop, NLP, Spark",PhD,0,Retail,2025-02-06,2025-04-15,1875,8.6,DeepTech Ventures -AI10140,Machine Learning Researcher,81847,USD,81847,SE,PT,China,L,Czech Republic,0,"MLOps, Data Visualization, AWS, Scala",PhD,9,Technology,2024-05-22,2024-08-01,799,8.2,Neural Networks Co -AI10141,ML Ops Engineer,125011,GBP,93758,SE,CT,United Kingdom,S,Germany,50,"Linux, Azure, Git, Computer Vision, TensorFlow",Master,9,Gaming,2024-09-08,2024-09-25,977,7,Algorithmic Solutions -AI10142,Deep Learning Engineer,253282,CAD,316603,EX,FT,Canada,L,Kenya,0,"Python, Git, TensorFlow, Azure, PyTorch",Associate,18,Finance,2024-10-09,2024-12-10,1585,6.8,DataVision Ltd -AI10143,Data Analyst,163715,USD,163715,EX,FL,Finland,S,Finland,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Media,2025-01-19,2025-02-05,1900,8.5,Advanced Robotics -AI10144,Head of AI,71407,EUR,60696,EN,FL,Germany,S,Indonesia,50,"SQL, Tableau, PyTorch",Master,0,Energy,2024-12-08,2025-02-12,1897,6.3,Quantum Computing Inc -AI10145,Deep Learning Engineer,66634,USD,66634,EN,PT,Ireland,L,Ireland,100,"AWS, Deep Learning, SQL, Azure, PyTorch",Associate,0,Media,2024-02-24,2024-03-23,1775,9.5,Digital Transformation LLC -AI10146,Autonomous Systems Engineer,160350,EUR,136298,EX,PT,Germany,M,Germany,50,"Spark, Kubernetes, MLOps, Python, Computer Vision",Associate,10,Energy,2025-04-20,2025-05-08,681,7.6,AI Innovations -AI10147,Deep Learning Engineer,119141,EUR,101270,SE,FT,Netherlands,M,Chile,50,"Hadoop, Azure, Git, Computer Vision, Scala",PhD,7,Finance,2024-04-04,2024-05-30,923,7.7,AI Innovations -AI10148,Machine Learning Engineer,92580,USD,92580,MI,FL,Israel,L,Israel,100,"GCP, Kubernetes, Computer Vision",Associate,4,Education,2024-07-19,2024-09-18,2309,9.4,Autonomous Tech -AI10149,Data Engineer,145627,AUD,196596,SE,PT,Australia,L,Australia,50,"Scala, Deep Learning, Computer Vision",PhD,5,Government,2024-08-16,2024-10-08,530,5.3,Algorithmic Solutions -AI10150,AI Specialist,213045,EUR,181088,EX,PT,Germany,M,Thailand,50,"Docker, MLOps, Kubernetes",Bachelor,12,Manufacturing,2025-03-18,2025-05-01,1675,7.7,Cognitive Computing -AI10151,Computer Vision Engineer,297403,SGD,386624,EX,FT,Singapore,L,Singapore,50,"Computer Vision, Python, Azure, Data Visualization",Bachelor,14,Finance,2024-05-18,2024-06-13,964,5.2,TechCorp Inc -AI10152,Data Analyst,69197,EUR,58817,MI,FT,France,S,France,0,"TensorFlow, MLOps, Java",Master,3,Gaming,2024-11-24,2024-12-30,2362,7.6,Smart Analytics -AI10153,Data Analyst,132689,USD,132689,SE,FT,Israel,L,Israel,100,"Computer Vision, Spark, Python, Mathematics, MLOps",Bachelor,7,Gaming,2024-04-14,2024-05-01,1072,6,Neural Networks Co -AI10154,Computer Vision Engineer,83336,GBP,62502,MI,FL,United Kingdom,S,Italy,50,"PyTorch, MLOps, SQL, Spark",PhD,2,Real Estate,2024-12-17,2025-01-23,2268,5.4,Predictive Systems -AI10155,AI Consultant,172090,JPY,18929900,SE,FT,Japan,L,Japan,0,"NLP, SQL, TensorFlow, Spark",Associate,5,Media,2024-10-30,2024-11-30,1316,8.8,DeepTech Ventures -AI10156,AI Product Manager,24926,USD,24926,EN,PT,China,M,China,0,"Mathematics, NLP, Data Visualization, Deep Learning, Hadoop",Associate,0,Healthcare,2025-04-13,2025-06-19,853,9.2,Advanced Robotics -AI10157,Data Analyst,211550,EUR,179818,EX,FL,Austria,L,Austria,100,"AWS, Kubernetes, NLP",Bachelor,17,Gaming,2025-01-31,2025-04-07,1102,5.6,Digital Transformation LLC -AI10158,NLP Engineer,104635,USD,104635,SE,PT,Finland,S,Finland,100,"Deep Learning, Scala, Tableau",Master,6,Real Estate,2024-10-17,2024-12-18,623,6.9,Digital Transformation LLC -AI10159,Data Scientist,67458,USD,67458,EN,FT,Finland,S,Finland,50,"Python, Azure, Tableau, Java",Master,1,Government,2024-03-05,2024-04-03,2364,5.5,Predictive Systems -AI10160,Research Scientist,137160,USD,137160,SE,CT,Sweden,L,Sweden,100,"Docker, Tableau, GCP, R",Associate,8,Retail,2024-01-04,2024-03-13,839,7.5,Cloud AI Solutions -AI10161,Head of AI,68285,USD,68285,EN,PT,Norway,S,Norway,50,"Java, Azure, AWS, Statistics, Computer Vision",Bachelor,0,Automotive,2025-03-24,2025-04-15,1170,9.8,Quantum Computing Inc -AI10162,Machine Learning Researcher,74005,CHF,66605,EN,FT,Switzerland,S,Philippines,100,"Hadoop, R, NLP",Associate,0,Manufacturing,2024-03-18,2024-04-09,1639,6.8,Cognitive Computing -AI10163,AI Architect,127491,JPY,14024010,SE,PT,Japan,M,Czech Republic,0,"SQL, Docker, Data Visualization, Mathematics",Associate,5,Real Estate,2024-08-26,2024-09-24,990,7.8,DeepTech Ventures -AI10164,Principal Data Scientist,64002,USD,64002,EX,FL,China,S,China,0,"Python, GCP, Data Visualization, MLOps",Master,14,Real Estate,2024-04-29,2024-05-31,1479,9.6,Advanced Robotics -AI10165,Data Analyst,87641,USD,87641,MI,FT,South Korea,L,South Korea,100,"SQL, NLP, Statistics, GCP, Java",PhD,4,Media,2024-03-28,2024-06-03,2285,8.9,DataVision Ltd -AI10166,Autonomous Systems Engineer,54064,JPY,5947040,EN,PT,Japan,S,Poland,0,"PyTorch, Docker, R, Deep Learning, Java",Master,0,Retail,2025-01-02,2025-03-06,1094,6.7,Machine Intelligence Group -AI10167,Research Scientist,92164,USD,92164,MI,CT,Denmark,S,Denmark,100,"Azure, NLP, Python, Statistics, Scala",PhD,4,Real Estate,2024-03-28,2024-06-01,2147,9.1,Autonomous Tech -AI10168,AI Product Manager,303272,USD,303272,EX,FT,Norway,L,Norway,0,"SQL, Spark, Tableau, PyTorch, Hadoop",PhD,11,Real Estate,2025-04-02,2025-04-20,1007,8.3,Cognitive Computing -AI10169,Data Analyst,125114,USD,125114,EX,FT,Sweden,S,Sweden,50,"Kubernetes, Git, Deep Learning, Computer Vision, Scala",Bachelor,12,Technology,2024-08-12,2024-09-08,2065,9.5,AI Innovations -AI10170,Deep Learning Engineer,54317,USD,54317,EN,CT,Ireland,M,Egypt,50,"Deep Learning, Spark, TensorFlow, PyTorch, Azure",Bachelor,1,Education,2025-03-20,2025-05-11,1082,6.1,DataVision Ltd -AI10171,Principal Data Scientist,75401,GBP,56551,MI,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, Data Visualization, Java",Bachelor,4,Healthcare,2024-08-02,2024-09-25,1106,8.8,DeepTech Ventures -AI10172,ML Ops Engineer,125780,USD,125780,SE,FL,Ireland,L,Ireland,0,"TensorFlow, Python, Computer Vision, SQL, Scala",Master,5,Real Estate,2024-08-25,2024-09-09,1249,8.9,Quantum Computing Inc -AI10173,Machine Learning Researcher,92433,USD,92433,EN,PT,Denmark,M,Denmark,0,"Python, TensorFlow, Azure, Computer Vision",Associate,0,Finance,2025-03-31,2025-05-24,2132,5.2,Cloud AI Solutions -AI10174,AI Specialist,64856,GBP,48642,EN,CT,United Kingdom,L,Ukraine,50,"Java, R, Tableau",PhD,1,Gaming,2024-07-14,2024-08-09,1592,6.5,TechCorp Inc -AI10175,Autonomous Systems Engineer,403493,CHF,363144,EX,FL,Switzerland,L,Switzerland,100,"Git, SQL, Spark, PyTorch",PhD,14,Gaming,2025-03-15,2025-05-05,1045,5.5,Cognitive Computing -AI10176,NLP Engineer,68862,USD,68862,EX,CT,India,L,India,100,"PyTorch, SQL, Tableau",PhD,17,Manufacturing,2024-10-20,2024-11-11,988,5.2,Machine Intelligence Group -AI10177,AI Consultant,210010,GBP,157508,EX,CT,United Kingdom,S,United Kingdom,0,"Spark, GCP, Linux",Bachelor,18,Media,2025-04-16,2025-06-14,1217,7.5,Neural Networks Co -AI10178,Machine Learning Researcher,123778,AUD,167100,SE,FT,Australia,L,Turkey,0,"Linux, Python, Tableau, Mathematics",Bachelor,5,Healthcare,2024-03-26,2024-06-04,1700,10,Cognitive Computing -AI10179,Machine Learning Researcher,70793,SGD,92031,MI,FT,Singapore,S,Singapore,100,"R, SQL, Azure",Associate,2,Gaming,2025-02-04,2025-03-15,739,8,DataVision Ltd -AI10180,Autonomous Systems Engineer,135779,EUR,115412,EX,PT,Germany,S,Indonesia,50,"Deep Learning, Git, Spark, GCP, Azure",Master,18,Telecommunications,2024-05-03,2024-07-09,1937,5.3,AI Innovations -AI10181,AI Specialist,70351,USD,70351,MI,CT,Finland,S,Finland,100,"SQL, NLP, TensorFlow",Master,4,Healthcare,2024-03-07,2024-03-25,1223,7.8,AI Innovations -AI10182,AI Architect,168478,CHF,151630,MI,FL,Switzerland,L,Switzerland,50,"Git, Kubernetes, PyTorch, R, SQL",Master,2,Education,2024-06-03,2024-08-06,1027,8,DeepTech Ventures -AI10183,Robotics Engineer,132893,USD,132893,EX,FT,Israel,S,Israel,0,"Computer Vision, Python, TensorFlow, Mathematics, Linux",Bachelor,17,Real Estate,2024-11-17,2024-12-02,2289,9.3,Future Systems -AI10184,Data Engineer,277707,GBP,208280,EX,FT,United Kingdom,L,United Kingdom,50,"Git, R, Statistics, Data Visualization",Associate,13,Retail,2024-12-21,2025-01-09,1010,7.9,DataVision Ltd -AI10185,NLP Engineer,131380,USD,131380,MI,FT,United States,L,United States,100,"PyTorch, TensorFlow, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-02-17,2024-04-04,604,10,TechCorp Inc -AI10186,AI Specialist,104109,USD,104109,SE,FT,South Korea,S,Brazil,100,"Deep Learning, AWS, Kubernetes, SQL, PyTorch",Associate,7,Real Estate,2024-04-29,2024-07-08,1705,6.8,Cloud AI Solutions -AI10187,Autonomous Systems Engineer,144897,EUR,123162,SE,PT,Netherlands,L,Netherlands,100,"Spark, Computer Vision, Hadoop",Associate,7,Manufacturing,2024-10-07,2024-11-07,1202,5.7,DataVision Ltd -AI10188,Machine Learning Engineer,234506,SGD,304858,EX,FL,Singapore,S,Singapore,100,"Python, Kubernetes, Spark, Mathematics",Associate,12,Education,2024-12-28,2025-03-08,1410,6.5,Future Systems -AI10189,NLP Engineer,138684,USD,138684,MI,PT,Denmark,M,Denmark,50,"Python, Tableau, Azure, PyTorch",Master,4,Manufacturing,2024-07-25,2024-08-28,1314,7.5,Cloud AI Solutions -AI10190,Machine Learning Engineer,91626,USD,91626,MI,FL,Ireland,S,Ireland,0,"Data Visualization, Deep Learning, MLOps, Spark",Associate,3,Government,2024-06-30,2024-08-10,1506,6.3,Smart Analytics -AI10191,AI Consultant,227796,USD,227796,EX,FT,United States,S,Germany,100,"R, Hadoop, Docker",Master,11,Finance,2024-10-07,2024-10-22,728,6.8,Quantum Computing Inc -AI10192,Machine Learning Engineer,237622,EUR,201979,EX,FT,Germany,M,Germany,100,"TensorFlow, Python, Scala",Associate,11,Technology,2024-06-30,2024-07-27,788,9.8,Digital Transformation LLC -AI10193,Autonomous Systems Engineer,59553,JPY,6550830,EN,CT,Japan,M,Japan,100,"SQL, GCP, PyTorch, Java",Associate,1,Government,2024-11-02,2024-11-25,2408,5.6,Machine Intelligence Group -AI10194,Data Engineer,75248,EUR,63961,MI,FT,Austria,S,Austria,50,"Spark, TensorFlow, Linux",Bachelor,4,Finance,2024-02-08,2024-04-17,1561,6.8,Cloud AI Solutions -AI10195,AI Product Manager,44563,USD,44563,SE,FT,India,M,Hungary,0,"Java, Linux, Python, Spark",Master,5,Automotive,2024-12-17,2025-02-25,1663,7.9,Quantum Computing Inc -AI10196,AI Consultant,186290,CHF,167661,SE,CT,Switzerland,M,Switzerland,0,"Tableau, Kubernetes, Git",Master,8,Real Estate,2025-04-30,2025-05-31,1747,5.6,DataVision Ltd -AI10197,AI Consultant,130662,EUR,111063,EX,CT,France,S,France,100,"Python, Azure, Tableau, Linux",Master,13,Technology,2024-09-06,2024-10-29,2453,6.7,DeepTech Ventures -AI10198,Principal Data Scientist,202772,USD,202772,EX,CT,Ireland,S,Ireland,100,"Computer Vision, Docker, Statistics",Associate,11,Telecommunications,2025-02-06,2025-04-08,514,5.3,Digital Transformation LLC -AI10199,AI Product Manager,190276,USD,190276,EX,CT,Sweden,L,Sweden,50,"Kubernetes, Docker, Python",Master,18,Gaming,2025-04-02,2025-04-25,1339,5.8,Smart Analytics -AI10200,AI Architect,99498,EUR,84573,SE,CT,Netherlands,S,Switzerland,100,"Mathematics, Tableau, R, Java",Associate,6,Automotive,2024-04-03,2024-04-23,1999,9.7,Cognitive Computing -AI10201,AI Product Manager,190361,AUD,256987,EX,FT,Australia,M,Australia,0,"GCP, Deep Learning, Python, Linux",Master,15,Gaming,2024-12-24,2025-02-04,1361,7.6,Autonomous Tech -AI10202,Head of AI,62384,USD,62384,EN,FT,United States,M,United States,0,"Git, Azure, Deep Learning",Master,1,Energy,2024-09-14,2024-11-17,541,8,Smart Analytics -AI10203,AI Research Scientist,139626,USD,139626,SE,FT,Norway,M,Norway,100,"Scala, Python, NLP, Docker, AWS",Associate,8,Media,2024-12-04,2025-01-11,1764,8.7,AI Innovations -AI10204,AI Software Engineer,76788,USD,76788,EX,FL,India,S,India,50,"NLP, Kubernetes, GCP, Python, Java",Master,17,Manufacturing,2024-08-19,2024-09-07,2043,6.8,TechCorp Inc -AI10205,Robotics Engineer,177449,USD,177449,SE,CT,Norway,L,Norway,0,"Docker, Statistics, Python, Tableau",Bachelor,8,Healthcare,2024-06-08,2024-07-10,2020,8.5,AI Innovations -AI10206,Data Analyst,61915,USD,61915,EN,FL,Finland,L,Finland,0,"Mathematics, R, NLP",PhD,0,Energy,2025-02-24,2025-04-05,2439,7.3,Machine Intelligence Group -AI10207,Research Scientist,59769,SGD,77700,EN,CT,Singapore,S,Singapore,0,"R, AWS, Linux",Bachelor,0,Transportation,2024-09-05,2024-09-26,796,8.3,Cognitive Computing -AI10208,Autonomous Systems Engineer,102469,CHF,92222,MI,CT,Switzerland,M,Germany,0,"PyTorch, Kubernetes, Docker, SQL",PhD,2,Transportation,2024-10-17,2024-11-14,1833,6.8,TechCorp Inc -AI10209,Autonomous Systems Engineer,144818,USD,144818,MI,CT,Denmark,L,Denmark,0,"R, Hadoop, Scala, PyTorch",PhD,2,Technology,2024-09-03,2024-10-10,812,6.3,Digital Transformation LLC -AI10210,Principal Data Scientist,151885,CAD,189856,SE,PT,Canada,L,Canada,50,"Docker, Tableau, Data Visualization",Associate,7,Media,2025-03-27,2025-05-17,1140,9.6,Smart Analytics -AI10211,AI Consultant,76782,USD,76782,EN,PT,United States,L,United States,0,"GCP, Mathematics, AWS",PhD,1,Education,2024-04-03,2024-04-25,1697,5.3,Algorithmic Solutions -AI10212,Head of AI,76167,USD,76167,MI,CT,Sweden,M,Sweden,0,"Spark, Scala, SQL",Bachelor,3,Government,2024-08-09,2024-10-19,1139,7.8,Quantum Computing Inc -AI10213,Research Scientist,109222,SGD,141989,MI,PT,Singapore,M,Singapore,0,"Python, TensorFlow, Java",PhD,3,Automotive,2024-09-26,2024-11-13,1852,8.3,Algorithmic Solutions -AI10214,Robotics Engineer,112535,CAD,140669,SE,FT,Canada,L,Vietnam,50,"Kubernetes, GCP, Data Visualization, SQL",PhD,7,Transportation,2025-03-16,2025-05-24,1174,8.7,Quantum Computing Inc -AI10215,Principal Data Scientist,283415,USD,283415,EX,FT,Sweden,L,Japan,50,"Computer Vision, Statistics, Docker",PhD,19,Automotive,2024-10-10,2024-12-22,1359,5.2,Algorithmic Solutions -AI10216,Data Scientist,75965,EUR,64570,MI,FT,Germany,M,Germany,50,"AWS, Linux, Hadoop, R, MLOps",PhD,4,Government,2024-10-16,2024-11-12,2301,8.4,Machine Intelligence Group -AI10217,NLP Engineer,91675,EUR,77924,MI,FL,Austria,M,Austria,0,"TensorFlow, AWS, Statistics",Bachelor,4,Consulting,2024-12-24,2025-02-16,515,8.9,Quantum Computing Inc -AI10218,Data Scientist,142668,CAD,178335,EX,PT,Canada,S,Canada,0,"Python, Java, Git, Spark, Azure",Associate,15,Consulting,2024-11-03,2024-11-27,2152,6.1,AI Innovations -AI10219,AI Specialist,65229,CAD,81536,EN,FL,Canada,S,Russia,100,"Python, Kubernetes, TensorFlow, Hadoop",Associate,1,Media,2024-01-02,2024-02-16,1513,7.5,Machine Intelligence Group -AI10220,Machine Learning Engineer,80835,CAD,101044,MI,FL,Canada,S,Singapore,100,"Data Visualization, Scala, Kubernetes, Deep Learning, GCP",PhD,2,Healthcare,2024-11-28,2025-01-01,1934,5.8,Autonomous Tech -AI10221,Deep Learning Engineer,250293,SGD,325381,EX,FL,Singapore,M,Singapore,100,"Kubernetes, Java, SQL, PyTorch, Azure",Associate,13,Finance,2024-03-10,2024-04-25,2222,7.5,Algorithmic Solutions -AI10222,AI Architect,162995,CHF,146696,MI,FT,Switzerland,L,Switzerland,0,"Git, Java, Spark, Python, GCP",Master,2,Retail,2025-01-07,2025-02-23,2411,9.5,DataVision Ltd -AI10223,AI Consultant,247822,USD,247822,EX,FL,Norway,M,Norway,100,"Git, Tableau, Deep Learning, Docker",Bachelor,19,Gaming,2024-02-26,2024-04-14,573,8.5,Cloud AI Solutions -AI10224,Machine Learning Engineer,168577,AUD,227579,SE,FL,Australia,L,Indonesia,100,"Hadoop, Kubernetes, Scala, Azure",Bachelor,6,Transportation,2024-06-01,2024-06-22,1731,6.2,Cognitive Computing -AI10225,Deep Learning Engineer,86183,USD,86183,EN,PT,Ireland,L,Ireland,100,"Data Visualization, Linux, PyTorch, TensorFlow",Associate,1,Government,2024-03-24,2024-04-13,929,6.4,Machine Intelligence Group -AI10226,AI Product Manager,95435,USD,95435,EN,FT,Norway,M,Ukraine,50,"SQL, Tableau, AWS, Java, R",PhD,0,Government,2024-09-16,2024-10-25,882,9.1,Advanced Robotics -AI10227,Robotics Engineer,86159,JPY,9477490,MI,FL,Japan,S,Japan,50,"GCP, NLP, PyTorch, Python",Bachelor,4,Education,2024-03-31,2024-05-05,1672,5.1,Advanced Robotics -AI10228,Deep Learning Engineer,30009,USD,30009,EN,CT,China,L,China,100,"Java, Linux, NLP, Git, Spark",Bachelor,0,Retail,2025-01-06,2025-02-09,1576,9.5,Advanced Robotics -AI10229,Robotics Engineer,65632,USD,65632,EN,PT,Finland,S,Finland,100,"Git, Python, SQL, GCP",Bachelor,1,Government,2025-03-24,2025-06-04,911,5.5,Cloud AI Solutions -AI10230,Data Engineer,161846,USD,161846,SE,PT,Israel,L,Israel,50,"GCP, Spark, Linux",PhD,6,Healthcare,2024-11-20,2024-12-15,2142,6.7,Quantum Computing Inc -AI10231,AI Research Scientist,67413,EUR,57301,EN,CT,Netherlands,S,Netherlands,0,"Azure, SQL, Data Visualization",PhD,1,Automotive,2024-06-26,2024-08-10,624,5.2,Digital Transformation LLC -AI10232,AI Architect,95990,USD,95990,SE,FL,Finland,S,Finland,0,"Tableau, TensorFlow, Kubernetes, SQL, GCP",PhD,9,Consulting,2024-02-15,2024-04-20,1850,9.3,TechCorp Inc -AI10233,Research Scientist,80350,CAD,100438,MI,CT,Canada,S,Canada,100,"NLP, SQL, PyTorch, Deep Learning, MLOps",Associate,4,Gaming,2024-10-15,2024-12-27,2154,6.5,Advanced Robotics -AI10234,Robotics Engineer,135564,USD,135564,EX,PT,China,L,China,50,"PyTorch, Kubernetes, TensorFlow, Linux",Master,16,Healthcare,2024-12-06,2025-02-01,586,8.8,Smart Analytics -AI10235,AI Software Engineer,218274,JPY,24010140,EX,PT,Japan,L,Japan,0,"GCP, Spark, Data Visualization",Bachelor,12,Healthcare,2024-12-04,2025-01-27,1162,5.3,Cognitive Computing -AI10236,NLP Engineer,79956,USD,79956,MI,FT,Israel,L,Israel,50,"SQL, Statistics, AWS, Docker",Associate,3,Manufacturing,2024-05-16,2024-07-06,2101,5.8,DeepTech Ventures -AI10237,AI Product Manager,210360,USD,210360,EX,PT,Ireland,L,Hungary,50,"Python, Computer Vision, Mathematics",Master,11,Government,2024-10-08,2024-12-06,1305,7.1,DeepTech Ventures -AI10238,AI Software Engineer,203510,USD,203510,EX,PT,Finland,M,France,50,"Python, Hadoop, Linux",Associate,14,Finance,2024-06-29,2024-08-26,1073,7.3,TechCorp Inc -AI10239,Principal Data Scientist,54946,USD,54946,MI,FL,China,L,Norway,0,"Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,2,Energy,2024-04-27,2024-06-21,761,6.2,TechCorp Inc -AI10240,Deep Learning Engineer,301525,USD,301525,EX,FT,Norway,M,Norway,0,"Tableau, Kubernetes, Linux, AWS",PhD,15,Media,2024-10-16,2024-12-26,1359,9,TechCorp Inc -AI10241,Data Engineer,54730,AUD,73886,EN,CT,Australia,M,Australia,50,"Scala, Kubernetes, Deep Learning, GCP, SQL",Bachelor,0,Automotive,2024-09-07,2024-10-31,641,6.1,TechCorp Inc -AI10242,Data Engineer,70076,USD,70076,MI,CT,South Korea,M,South Korea,0,"Git, Hadoop, GCP",Bachelor,3,Transportation,2024-03-25,2024-05-26,1249,7,Predictive Systems -AI10243,Robotics Engineer,140236,USD,140236,EX,FL,South Korea,M,South Korea,0,"Spark, R, Java, Data Visualization, Tableau",Associate,14,Energy,2025-04-14,2025-06-15,1958,9.3,Machine Intelligence Group -AI10244,AI Consultant,76319,CHF,68687,EN,CT,Switzerland,S,South Africa,0,"Spark, Git, SQL",Associate,1,Gaming,2024-02-18,2024-03-10,1721,7.5,Quantum Computing Inc -AI10245,Principal Data Scientist,117897,USD,117897,EN,PT,Denmark,L,Philippines,0,"Spark, Tableau, Java",Bachelor,1,Retail,2024-12-02,2025-01-09,1874,6,AI Innovations -AI10246,Principal Data Scientist,67144,USD,67144,EX,FT,India,M,India,0,"Git, Python, NLP, Deep Learning, R",Associate,18,Finance,2024-02-13,2024-02-27,849,5.1,Predictive Systems -AI10247,Computer Vision Engineer,77616,EUR,65974,EN,CT,France,L,France,50,"AWS, Computer Vision, Data Visualization, MLOps, Statistics",Bachelor,0,Government,2024-04-04,2024-06-02,1095,6.9,Machine Intelligence Group -AI10248,Research Scientist,141826,USD,141826,MI,CT,Norway,L,Norway,0,"Python, Kubernetes, SQL, Linux, Hadoop",Associate,3,Real Estate,2024-11-12,2025-01-11,2171,5.3,DeepTech Ventures -AI10249,Data Engineer,73463,JPY,8080930,EN,FT,Japan,S,Japan,100,"Python, Git, NLP, GCP, Hadoop",Bachelor,1,Manufacturing,2024-07-11,2024-08-05,1343,6.1,Machine Intelligence Group -AI10250,AI Research Scientist,109715,USD,109715,MI,CT,Denmark,M,Denmark,0,"Docker, SQL, PyTorch, Spark",Bachelor,4,Finance,2024-02-05,2024-03-04,2237,7,DeepTech Ventures -AI10251,Robotics Engineer,69994,EUR,59495,MI,FT,Austria,M,Austria,0,"Statistics, Azure, Python",Bachelor,2,Manufacturing,2025-04-15,2025-05-07,1393,5.8,Predictive Systems -AI10252,NLP Engineer,117074,CHF,105367,MI,CT,Switzerland,S,Colombia,100,"GCP, Azure, NLP, TensorFlow",Master,4,Manufacturing,2025-02-13,2025-03-17,1001,6.5,DataVision Ltd -AI10253,Computer Vision Engineer,105296,GBP,78972,MI,FL,United Kingdom,S,United Kingdom,100,"Scala, Computer Vision, GCP, NLP, Git",Associate,3,Gaming,2024-05-09,2024-07-20,1754,8.6,DeepTech Ventures -AI10254,Head of AI,165753,CHF,149178,SE,FL,Switzerland,S,Netherlands,50,"Deep Learning, Hadoop, Java",Associate,9,Real Estate,2024-07-11,2024-08-17,1737,9.4,Cloud AI Solutions -AI10255,Deep Learning Engineer,136546,SGD,177510,SE,CT,Singapore,L,Japan,50,"SQL, R, NLP",Associate,5,Finance,2024-10-14,2024-11-05,1371,6.2,Cloud AI Solutions -AI10256,ML Ops Engineer,61219,USD,61219,EN,CT,Israel,M,Indonesia,0,"Kubernetes, MLOps, Scala",Master,0,Consulting,2025-01-01,2025-03-09,1568,8.3,DeepTech Ventures -AI10257,Head of AI,86631,EUR,73636,MI,FT,Austria,M,Austria,0,"Docker, SQL, Mathematics",PhD,2,Manufacturing,2024-01-20,2024-03-17,1632,7,Autonomous Tech -AI10258,AI Consultant,226414,USD,226414,EX,PT,Ireland,M,Ireland,100,"NLP, Azure, Deep Learning",Associate,13,Education,2024-07-26,2024-09-18,666,9.4,Neural Networks Co -AI10259,AI Research Scientist,113616,EUR,96574,SE,FT,Netherlands,S,Netherlands,50,"Scala, Hadoop, Computer Vision, Deep Learning",Master,7,Retail,2025-04-09,2025-06-14,1885,6,Smart Analytics -AI10260,Principal Data Scientist,191958,USD,191958,SE,FL,Norway,L,Norway,0,"Mathematics, Computer Vision, Kubernetes",Bachelor,6,Healthcare,2025-04-12,2025-05-03,1954,8.1,AI Innovations -AI10261,AI Research Scientist,50163,CAD,62704,EN,CT,Canada,S,Brazil,50,"Git, PyTorch, TensorFlow",PhD,1,Telecommunications,2025-03-03,2025-03-27,2229,8.6,TechCorp Inc -AI10262,Robotics Engineer,337422,USD,337422,EX,FL,United States,L,Sweden,100,"Linux, NLP, TensorFlow, Docker, Mathematics",PhD,12,Government,2024-04-21,2024-05-20,1783,9.7,Cognitive Computing -AI10263,AI Architect,67566,USD,67566,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Data Visualization, Git",Associate,1,Telecommunications,2024-10-21,2025-01-01,1563,6.5,Cloud AI Solutions -AI10264,AI Specialist,59923,EUR,50935,EN,FL,Netherlands,M,Australia,100,"Docker, Python, Deep Learning, SQL, Statistics",Bachelor,0,Education,2025-03-06,2025-04-26,2410,5.9,DataVision Ltd -AI10265,Data Engineer,238139,EUR,202418,EX,CT,France,M,France,50,"Deep Learning, Hadoop, Python, Docker, Git",Associate,12,Education,2024-01-19,2024-02-27,786,9.9,Advanced Robotics -AI10266,Research Scientist,231140,USD,231140,EX,PT,Israel,L,Israel,100,"SQL, PyTorch, R, Spark",Bachelor,16,Transportation,2024-02-02,2024-04-12,1351,6.2,Neural Networks Co -AI10267,Principal Data Scientist,124660,JPY,13712600,SE,PT,Japan,M,Japan,0,"Scala, Azure, Linux",Bachelor,7,Retail,2024-02-22,2024-05-02,1365,6.9,Cloud AI Solutions -AI10268,AI Product Manager,147934,USD,147934,SE,FL,Sweden,L,Finland,50,"R, SQL, PyTorch, Hadoop, Mathematics",Associate,5,Retail,2024-05-04,2024-07-15,2042,8.7,Digital Transformation LLC -AI10269,NLP Engineer,154109,USD,154109,SE,PT,Sweden,L,Argentina,0,"Python, Kubernetes, MLOps, NLP, TensorFlow",Bachelor,5,Technology,2024-06-14,2024-08-06,652,9.6,Machine Intelligence Group -AI10270,Head of AI,182664,SGD,237463,SE,PT,Singapore,L,Singapore,100,"SQL, PyTorch, NLP, TensorFlow, Statistics",Associate,8,Education,2024-08-08,2024-10-05,1732,5.8,AI Innovations -AI10271,AI Research Scientist,106779,GBP,80084,MI,PT,United Kingdom,L,Thailand,0,"Mathematics, SQL, Git",Associate,2,Retail,2024-03-22,2024-05-25,2379,7.7,TechCorp Inc -AI10272,Principal Data Scientist,76695,SGD,99704,EN,PT,Singapore,S,Indonesia,0,"Data Visualization, TensorFlow, MLOps",Bachelor,0,Manufacturing,2024-08-27,2024-10-30,1852,6.8,Machine Intelligence Group -AI10273,Deep Learning Engineer,33529,USD,33529,EN,CT,China,M,China,50,"Kubernetes, Deep Learning, GCP",PhD,1,Consulting,2024-10-11,2024-11-07,1608,7.6,Advanced Robotics -AI10274,Machine Learning Researcher,92400,EUR,78540,EN,CT,Germany,L,Germany,100,"Linux, Mathematics, Hadoop, Spark, Java",Associate,0,Government,2024-05-15,2024-07-12,1559,8.9,Cognitive Computing -AI10275,Autonomous Systems Engineer,222418,USD,222418,EX,FT,United States,M,United States,100,"Azure, Kubernetes, Deep Learning",Bachelor,17,Media,2025-03-01,2025-04-25,1951,9.3,Quantum Computing Inc -AI10276,AI Product Manager,86393,EUR,73434,EN,CT,Netherlands,L,Ukraine,50,"TensorFlow, Azure, Computer Vision",Associate,1,Automotive,2025-01-02,2025-02-15,1735,5.6,Quantum Computing Inc -AI10277,AI Software Engineer,122637,USD,122637,SE,PT,Norway,S,Norway,100,"NLP, Scala, R, Azure",PhD,8,Automotive,2024-04-15,2024-05-14,1246,9,Algorithmic Solutions -AI10278,ML Ops Engineer,190440,AUD,257094,EX,PT,Australia,L,Brazil,100,"Azure, TensorFlow, Data Visualization",Associate,16,Manufacturing,2024-12-26,2025-03-01,1381,6.6,Neural Networks Co -AI10279,Machine Learning Researcher,72783,CHF,65505,EN,FL,Switzerland,S,Switzerland,50,"AWS, SQL, Hadoop",Bachelor,1,Telecommunications,2024-06-17,2024-07-14,2348,9.5,Predictive Systems -AI10280,AI Software Engineer,191481,EUR,162759,EX,FL,Germany,S,Germany,0,"Docker, Python, Data Visualization",Master,10,Healthcare,2024-05-31,2024-07-08,1695,5.6,Predictive Systems -AI10281,AI Software Engineer,119141,USD,119141,MI,FL,Denmark,S,Denmark,50,"Scala, Python, Deep Learning, Azure, Linux",Bachelor,2,Manufacturing,2024-04-25,2024-06-14,1185,8.7,Neural Networks Co -AI10282,Autonomous Systems Engineer,61294,SGD,79682,EN,FT,Singapore,M,Czech Republic,0,"Docker, Spark, R, Linux",Bachelor,1,Energy,2024-04-16,2024-06-17,1547,8.3,Predictive Systems -AI10283,Machine Learning Researcher,112748,EUR,95836,SE,FT,Austria,L,South Africa,50,"Scala, Python, MLOps",PhD,9,Consulting,2024-01-05,2024-02-24,1639,6.8,Smart Analytics -AI10284,AI Specialist,69817,CAD,87271,MI,FL,Canada,M,Philippines,0,"Git, Statistics, Mathematics, Spark, Azure",Bachelor,2,Technology,2024-04-15,2024-06-11,1463,9.8,Quantum Computing Inc -AI10285,Data Engineer,162528,CAD,203160,EX,PT,Canada,S,Canada,0,"Git, Hadoop, TensorFlow, Scala",Bachelor,16,Energy,2024-09-24,2024-11-22,1815,9.5,Autonomous Tech -AI10286,Principal Data Scientist,80432,USD,80432,EN,PT,Denmark,L,Denmark,0,"Kubernetes, AWS, Java",PhD,1,Telecommunications,2024-11-13,2024-12-01,2443,6.2,DeepTech Ventures -AI10287,Robotics Engineer,263161,CHF,236845,EX,CT,Switzerland,L,Switzerland,0,"Kubernetes, Python, Computer Vision, TensorFlow",Bachelor,15,Government,2025-01-04,2025-02-06,1699,6.4,Predictive Systems -AI10288,AI Research Scientist,70408,CAD,88010,EN,CT,Canada,L,Canada,100,"PyTorch, Computer Vision, Statistics",PhD,0,Gaming,2024-03-29,2024-05-25,643,9.9,AI Innovations -AI10289,Machine Learning Researcher,84533,EUR,71853,MI,FL,France,S,Latvia,100,"Scala, Linux, Kubernetes",Associate,3,Automotive,2024-04-10,2024-04-28,2027,6.5,Quantum Computing Inc -AI10290,Machine Learning Researcher,94145,USD,94145,MI,CT,South Korea,L,South Korea,0,"Java, GCP, R",PhD,4,Energy,2024-04-20,2024-05-26,1087,7.6,Autonomous Tech -AI10291,Research Scientist,52193,USD,52193,EN,PT,Finland,M,Finland,100,"Azure, Spark, Git",Bachelor,0,Telecommunications,2024-12-31,2025-03-12,2340,8.1,Predictive Systems -AI10292,AI Consultant,153253,USD,153253,EX,CT,Ireland,M,Ireland,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,10,Media,2024-01-18,2024-03-30,1495,9.8,Smart Analytics -AI10293,Machine Learning Engineer,87192,USD,87192,MI,CT,Israel,L,Australia,100,"Computer Vision, R, Tableau, Data Visualization",Bachelor,4,Retail,2024-08-20,2024-10-04,1220,9.7,DeepTech Ventures -AI10294,AI Specialist,214211,CHF,192790,EX,PT,Switzerland,S,Turkey,100,"Java, AWS, Statistics, Hadoop",PhD,19,Gaming,2024-01-10,2024-02-05,746,5.5,Algorithmic Solutions -AI10295,AI Product Manager,203264,JPY,22359040,EX,CT,Japan,M,Poland,50,"SQL, Hadoop, Git, Linux",Bachelor,16,Finance,2025-01-19,2025-03-14,1961,5.2,Predictive Systems -AI10296,Autonomous Systems Engineer,172259,JPY,18948490,EX,PT,Japan,M,Russia,100,"Deep Learning, MLOps, Python, Tableau, Scala",Associate,16,Gaming,2024-02-03,2024-03-02,1017,7.4,Algorithmic Solutions -AI10297,Research Scientist,109363,SGD,142172,SE,CT,Singapore,S,Singapore,100,"Deep Learning, Java, Python",Associate,6,Energy,2024-11-02,2024-12-08,1270,7.9,Predictive Systems -AI10298,AI Software Engineer,50885,USD,50885,EX,FL,India,S,India,100,"AWS, Python, Git, Statistics, TensorFlow",Bachelor,17,Government,2025-04-08,2025-05-19,1119,9.6,Algorithmic Solutions -AI10299,ML Ops Engineer,108450,USD,108450,MI,FL,Norway,L,Norway,100,"Linux, PyTorch, TensorFlow, Docker, Mathematics",Associate,2,Media,2025-04-24,2025-07-04,1495,7,Digital Transformation LLC -AI10300,AI Specialist,57880,USD,57880,MI,FL,China,L,China,100,"Python, Spark, Tableau, Scala, Mathematics",Master,3,Transportation,2024-05-27,2024-07-02,2363,9.2,Neural Networks Co -AI10301,AI Software Engineer,113212,USD,113212,SE,FT,South Korea,S,South Korea,100,"GCP, Spark, NLP, TensorFlow, MLOps",PhD,7,Consulting,2024-01-04,2024-02-11,1158,8.9,Advanced Robotics -AI10302,AI Architect,161719,USD,161719,SE,PT,Norway,L,Norway,0,"R, Git, Kubernetes",Associate,8,Finance,2024-05-18,2024-07-18,653,7.1,Digital Transformation LLC -AI10303,Data Engineer,71629,USD,71629,EN,PT,South Korea,L,China,0,"Tableau, GCP, Linux",Bachelor,1,Telecommunications,2024-09-26,2024-11-24,1646,5.5,Smart Analytics -AI10304,Deep Learning Engineer,257527,USD,257527,EX,FL,Ireland,L,Ireland,50,"Linux, Deep Learning, MLOps, PyTorch",Master,10,Technology,2024-03-26,2024-05-21,1258,9.4,Cognitive Computing -AI10305,Computer Vision Engineer,174720,USD,174720,EX,FT,United States,M,Ireland,0,"Kubernetes, Spark, Computer Vision, TensorFlow, Scala",Associate,15,Finance,2024-03-19,2024-04-13,722,6.4,AI Innovations -AI10306,AI Software Engineer,163238,USD,163238,SE,FL,Ireland,L,Ireland,50,"Python, AWS, Scala",Master,7,Healthcare,2024-12-14,2025-01-11,1790,9.2,Algorithmic Solutions -AI10307,AI Consultant,212985,EUR,181037,EX,PT,Netherlands,M,Netherlands,50,"Spark, Deep Learning, Data Visualization",PhD,10,Energy,2024-07-06,2024-07-23,1464,8.8,Predictive Systems -AI10308,AI Specialist,115588,AUD,156044,SE,PT,Australia,S,Australia,0,"PyTorch, Mathematics, NLP, Kubernetes",PhD,8,Education,2025-03-03,2025-03-25,581,7.5,DeepTech Ventures -AI10309,AI Architect,76351,USD,76351,EN,FL,Ireland,L,Ireland,50,"SQL, Python, Tableau, Scala, Statistics",PhD,1,Gaming,2024-06-13,2024-08-05,1297,7.4,Machine Intelligence Group -AI10310,Robotics Engineer,127693,CAD,159616,EX,FL,Canada,S,Canada,100,"Python, TensorFlow, Mathematics, Azure, PyTorch",Associate,16,Gaming,2025-03-14,2025-03-31,1790,7.1,TechCorp Inc -AI10311,Autonomous Systems Engineer,199789,USD,199789,EX,CT,Sweden,L,Chile,50,"Linux, Java, R",Master,10,Government,2024-12-17,2025-01-16,2344,7.5,Neural Networks Co -AI10312,AI Specialist,60987,USD,60987,EN,PT,Ireland,M,Mexico,100,"Deep Learning, Data Visualization, Scala, AWS, Linux",PhD,1,Consulting,2024-07-17,2024-08-05,2185,9.7,Autonomous Tech -AI10313,AI Product Manager,86536,USD,86536,MI,CT,Finland,M,Finland,0,"Scala, R, AWS",Associate,4,Telecommunications,2024-01-06,2024-01-27,1328,9.6,Predictive Systems -AI10314,Data Analyst,96169,EUR,81744,MI,CT,Austria,L,Austria,100,"Scala, Hadoop, Docker, Deep Learning",Bachelor,3,Government,2024-03-16,2024-05-04,1754,8.9,DataVision Ltd -AI10315,Autonomous Systems Engineer,192529,CAD,240661,EX,FT,Canada,M,Canada,50,"AWS, Kubernetes, R, Computer Vision, Statistics",PhD,16,Automotive,2024-01-15,2024-02-16,1373,6.7,DeepTech Ventures -AI10316,Data Analyst,100410,USD,100410,EX,CT,India,L,India,50,"MLOps, Data Visualization, Mathematics, Azure, Java",PhD,19,Manufacturing,2024-11-18,2025-01-04,1798,9.5,Quantum Computing Inc -AI10317,Machine Learning Researcher,52644,USD,52644,EN,PT,Sweden,M,Sweden,0,"SQL, Git, R, Deep Learning",Associate,1,Transportation,2024-04-04,2024-06-08,1491,6.1,Digital Transformation LLC -AI10318,AI Consultant,141234,USD,141234,SE,FT,United States,S,United States,0,"SQL, Kubernetes, GCP",Bachelor,5,Government,2024-11-18,2024-12-08,1135,5.6,Advanced Robotics -AI10319,AI Research Scientist,110559,USD,110559,MI,FL,Denmark,M,Spain,0,"Hadoop, Docker, MLOps, Linux, Data Visualization",Associate,4,Consulting,2024-11-07,2025-01-17,1542,9,DataVision Ltd -AI10320,AI Consultant,217485,USD,217485,EX,PT,Ireland,L,Luxembourg,0,"Scala, Statistics, Python, Mathematics",PhD,11,Government,2024-03-12,2024-04-19,1730,5.2,Predictive Systems -AI10321,Research Scientist,71252,USD,71252,EN,CT,Norway,M,Norway,0,"R, TensorFlow, PyTorch, Spark",Master,0,Retail,2024-12-09,2025-01-19,2090,6.6,DeepTech Ventures -AI10322,Data Scientist,53971,EUR,45875,EN,FL,France,S,France,0,"TensorFlow, Python, Git, Computer Vision, AWS",Master,0,Technology,2025-01-01,2025-02-12,523,7.5,Algorithmic Solutions -AI10323,Machine Learning Engineer,220263,AUD,297355,EX,CT,Australia,L,Australia,0,"NLP, Data Visualization, TensorFlow, Hadoop",Associate,11,Media,2025-03-10,2025-03-27,1532,5.9,Cloud AI Solutions -AI10324,ML Ops Engineer,277182,USD,277182,EX,FL,Norway,M,Norway,50,"Azure, Linux, NLP, GCP",Bachelor,15,Technology,2024-11-16,2025-01-10,652,7.6,Advanced Robotics -AI10325,Computer Vision Engineer,66175,USD,66175,EN,FT,Finland,M,Turkey,0,"Kubernetes, Statistics, Docker, Spark",Bachelor,1,Gaming,2024-07-09,2024-09-19,1983,5.4,DeepTech Ventures -AI10326,Principal Data Scientist,87331,USD,87331,EN,FT,Norway,L,Norway,100,"Hadoop, SQL, MLOps, Statistics, PyTorch",PhD,0,Retail,2024-07-06,2024-08-26,1817,7.5,Neural Networks Co -AI10327,ML Ops Engineer,139322,USD,139322,MI,CT,Norway,M,Norway,100,"Git, MLOps, Java, GCP",Master,4,Manufacturing,2024-10-17,2024-11-29,1376,9.3,Cloud AI Solutions -AI10328,Autonomous Systems Engineer,111301,EUR,94606,SE,FT,Germany,M,Germany,0,"TensorFlow, R, GCP",Master,5,Transportation,2024-08-09,2024-10-07,1598,6.4,TechCorp Inc -AI10329,AI Architect,132825,GBP,99619,EX,FT,United Kingdom,S,United Kingdom,0,"Statistics, R, AWS, PyTorch, TensorFlow",PhD,17,Gaming,2024-12-16,2025-02-20,708,5.1,AI Innovations -AI10330,AI Consultant,169505,AUD,228832,EX,CT,Australia,M,Australia,0,"SQL, Hadoop, PyTorch, Scala, Kubernetes",PhD,14,Media,2024-02-25,2024-04-17,790,8.8,Machine Intelligence Group -AI10331,Machine Learning Researcher,88530,AUD,119516,MI,CT,Australia,L,Australia,0,"SQL, Scala, Docker, Azure, Mathematics",Master,4,Transportation,2024-04-05,2024-05-26,1421,9.5,Cognitive Computing -AI10332,Machine Learning Researcher,127006,EUR,107955,SE,FT,Austria,S,Austria,50,"GCP, Data Visualization, PyTorch, Computer Vision, Deep Learning",Bachelor,6,Energy,2025-01-02,2025-03-03,2400,6.2,Digital Transformation LLC -AI10333,Computer Vision Engineer,244361,AUD,329887,EX,FT,Australia,M,Australia,100,"Java, Deep Learning, Hadoop",Associate,10,Automotive,2025-03-25,2025-06-03,1476,6.4,Cloud AI Solutions -AI10334,Computer Vision Engineer,74201,CAD,92751,EN,PT,Canada,L,Canada,0,"PyTorch, Python, GCP, TensorFlow, Hadoop",Associate,1,Gaming,2024-11-23,2025-01-20,661,6.4,Machine Intelligence Group -AI10335,Robotics Engineer,166881,USD,166881,SE,PT,Norway,S,United Kingdom,0,"Java, PyTorch, Tableau, TensorFlow, Deep Learning",PhD,8,Healthcare,2024-11-09,2024-11-27,2036,5.9,TechCorp Inc -AI10336,Research Scientist,28173,USD,28173,EN,CT,India,L,India,50,"Python, NLP, Hadoop, Computer Vision",Bachelor,1,Real Estate,2024-08-03,2024-09-17,1891,5.5,Autonomous Tech -AI10337,AI Software Engineer,73010,USD,73010,EN,CT,United States,L,United States,100,"Docker, Tableau, Data Visualization, Azure",PhD,1,Government,2025-02-04,2025-04-15,2119,8,Future Systems -AI10338,Computer Vision Engineer,102446,EUR,87079,MI,CT,Austria,L,Argentina,100,"NLP, MLOps, SQL",Master,3,Telecommunications,2024-10-06,2024-11-16,1801,9.8,Predictive Systems -AI10339,Principal Data Scientist,89214,USD,89214,SE,CT,Finland,S,Finland,0,"Statistics, Azure, Python, SQL",Master,8,Education,2024-12-08,2025-01-30,1097,5.2,Autonomous Tech -AI10340,NLP Engineer,203849,USD,203849,EX,FT,South Korea,L,South Korea,0,"Scala, PyTorch, Git, Linux",Master,12,Finance,2024-07-13,2024-09-04,645,6.1,Future Systems -AI10341,AI Consultant,231925,EUR,197136,EX,CT,Austria,L,Austria,100,"TensorFlow, R, Linux, Hadoop",Associate,16,Transportation,2025-04-01,2025-06-12,2122,9.3,TechCorp Inc -AI10342,Principal Data Scientist,135857,CAD,169821,SE,PT,Canada,L,Czech Republic,50,"Mathematics, Spark, Data Visualization",Bachelor,7,Automotive,2025-04-02,2025-05-23,1584,6.5,Cloud AI Solutions -AI10343,AI Research Scientist,135341,SGD,175943,SE,FL,Singapore,L,Singapore,0,"GCP, Linux, Deep Learning",Bachelor,7,Finance,2024-03-20,2024-04-07,1590,7.7,Quantum Computing Inc -AI10344,AI Architect,131968,EUR,112173,SE,CT,France,L,France,0,"Python, Computer Vision, R, Deep Learning",Master,9,Technology,2025-04-03,2025-05-27,1288,9.7,Predictive Systems -AI10345,AI Software Engineer,123858,GBP,92894,SE,FL,United Kingdom,S,Ukraine,0,"Linux, GCP, R, AWS",Bachelor,5,Media,2025-03-02,2025-04-10,2322,5.5,Cognitive Computing -AI10346,NLP Engineer,348262,CHF,313436,EX,CT,Switzerland,M,Ireland,100,"AWS, Python, Kubernetes",Associate,16,Retail,2024-06-26,2024-08-22,720,6.2,Algorithmic Solutions -AI10347,AI Product Manager,139444,USD,139444,SE,CT,Sweden,L,Sweden,50,"Python, Docker, Data Visualization, MLOps, Statistics",Associate,8,Manufacturing,2024-07-20,2024-09-20,1968,5.5,DataVision Ltd -AI10348,Machine Learning Engineer,149870,USD,149870,SE,FL,Denmark,S,Denmark,50,"SQL, Data Visualization, Tableau, Spark, Java",Master,9,Healthcare,2024-01-26,2024-03-10,763,9.5,Machine Intelligence Group -AI10349,Computer Vision Engineer,71964,USD,71964,EN,PT,Sweden,S,Sweden,50,"NLP, MLOps, Python, Scala, Docker",Master,1,Finance,2024-05-07,2024-07-08,1882,9.7,Advanced Robotics -AI10350,Robotics Engineer,27319,USD,27319,EN,FL,India,L,India,0,"Linux, Scala, Python, PyTorch",Associate,0,Automotive,2024-11-16,2025-01-10,1675,7,Algorithmic Solutions -AI10351,Deep Learning Engineer,150456,GBP,112842,EX,FT,United Kingdom,M,United Kingdom,0,"Kubernetes, R, Statistics, Tableau, MLOps",Associate,12,Telecommunications,2025-03-27,2025-04-16,1274,9,AI Innovations -AI10352,AI Specialist,305568,USD,305568,EX,FL,Norway,L,Norway,50,"SQL, PyTorch, Java, Computer Vision, Deep Learning",PhD,12,Transportation,2024-10-01,2024-11-28,1211,9.1,Digital Transformation LLC -AI10353,Data Scientist,181656,EUR,154408,EX,PT,Austria,S,Austria,100,"SQL, Spark, PyTorch",Bachelor,11,Healthcare,2024-01-25,2024-04-04,2218,5,Smart Analytics -AI10354,AI Specialist,83544,CAD,104430,MI,FT,Canada,L,Canada,0,"TensorFlow, Linux, Git, Kubernetes, Mathematics",PhD,4,Energy,2024-05-10,2024-05-27,1605,5.3,Machine Intelligence Group -AI10355,Data Scientist,85383,SGD,110998,EN,CT,Singapore,L,Singapore,0,"MLOps, Statistics, AWS",Master,1,Telecommunications,2024-05-01,2024-07-06,920,8,Cognitive Computing -AI10356,Data Analyst,118808,USD,118808,MI,FL,Israel,L,Portugal,50,"MLOps, TensorFlow, Scala",Master,3,Transportation,2024-05-31,2024-08-06,837,7.5,Smart Analytics -AI10357,Research Scientist,110158,GBP,82619,MI,CT,United Kingdom,M,Belgium,100,"Java, Computer Vision, Data Visualization, MLOps",PhD,3,Finance,2025-03-28,2025-05-05,1881,9.2,AI Innovations -AI10358,Principal Data Scientist,68395,AUD,92333,EN,FT,Australia,M,Australia,50,"AWS, Python, Docker, Deep Learning, Hadoop",Associate,0,Automotive,2024-10-18,2024-11-04,985,9.6,Digital Transformation LLC -AI10359,AI Consultant,83740,EUR,71179,MI,FL,Austria,L,Austria,0,"Hadoop, Linux, Python, Deep Learning",Associate,2,Transportation,2025-03-21,2025-05-24,655,5.2,Cloud AI Solutions -AI10360,Data Scientist,52109,USD,52109,EX,PT,India,S,India,0,"Python, Kubernetes, Tableau, TensorFlow",Bachelor,15,Education,2025-02-03,2025-04-09,1995,6.1,DeepTech Ventures -AI10361,Machine Learning Researcher,103993,AUD,140391,SE,FT,Australia,S,Sweden,100,"Tableau, Java, Python, SQL, AWS",PhD,9,Education,2024-06-14,2024-07-17,1523,9.9,Predictive Systems -AI10362,Machine Learning Researcher,183121,GBP,137341,EX,FT,United Kingdom,L,United Kingdom,50,"Linux, Kubernetes, R, AWS",Bachelor,11,Telecommunications,2024-03-05,2024-03-28,1413,8.2,Advanced Robotics -AI10363,Data Scientist,76735,USD,76735,SE,PT,South Korea,S,New Zealand,0,"NLP, Kubernetes, AWS, SQL",PhD,8,Energy,2024-08-25,2024-09-23,1994,9.6,Future Systems -AI10364,NLP Engineer,206350,GBP,154763,EX,PT,United Kingdom,L,United Kingdom,100,"Tableau, SQL, Spark, Computer Vision",PhD,18,Telecommunications,2024-06-23,2024-08-09,2468,7.2,TechCorp Inc -AI10365,Autonomous Systems Engineer,105977,GBP,79483,MI,PT,United Kingdom,M,United Kingdom,50,"NLP, Java, TensorFlow",PhD,4,Media,2024-05-20,2024-07-02,2109,5.6,Cloud AI Solutions -AI10366,NLP Engineer,216215,JPY,23783650,EX,CT,Japan,L,Japan,100,"NLP, Hadoop, Kubernetes",Bachelor,19,Retail,2024-06-28,2024-07-30,1784,8,Predictive Systems -AI10367,NLP Engineer,75477,EUR,64155,MI,CT,Germany,M,Germany,0,"NLP, Scala, Spark, PyTorch, Linux",Associate,2,Media,2024-03-21,2024-05-21,1501,6.6,Smart Analytics -AI10368,Principal Data Scientist,48875,USD,48875,SE,FT,China,M,China,100,"Linux, Java, Computer Vision, Kubernetes, Mathematics",Associate,5,Healthcare,2024-12-11,2024-12-27,1022,9.1,Neural Networks Co -AI10369,Principal Data Scientist,104599,CHF,94139,EN,PT,Switzerland,M,Switzerland,50,"Python, Git, Linux, TensorFlow, R",Bachelor,1,Consulting,2025-04-10,2025-04-25,991,9.1,Future Systems -AI10370,Machine Learning Engineer,48610,GBP,36458,EN,PT,United Kingdom,S,United Kingdom,100,"MLOps, SQL, Azure, TensorFlow, GCP",Master,0,Education,2024-09-30,2024-11-05,527,8.4,DataVision Ltd -AI10371,Autonomous Systems Engineer,63371,USD,63371,EN,FT,Ireland,M,Ireland,0,"Docker, Tableau, Data Visualization, Python, Statistics",Associate,1,Finance,2024-12-26,2025-01-24,2265,6.7,AI Innovations -AI10372,Head of AI,62938,EUR,53497,EN,FL,Germany,S,Germany,0,"Java, Hadoop, R",PhD,0,Media,2025-01-17,2025-02-08,1240,6.9,Neural Networks Co -AI10373,AI Specialist,90753,EUR,77140,MI,CT,France,M,New Zealand,100,"Linux, Hadoop, Tableau",Master,4,Manufacturing,2024-12-15,2025-01-24,2436,6.4,Future Systems -AI10374,AI Specialist,82651,USD,82651,MI,FL,South Korea,M,South Korea,100,"Python, TensorFlow, Computer Vision, AWS, Java",Master,3,Education,2024-08-29,2024-10-04,794,5.4,DataVision Ltd -AI10375,Principal Data Scientist,76895,EUR,65361,MI,FT,Netherlands,S,Netherlands,0,"Azure, NLP, Python, Computer Vision, Docker",PhD,2,Finance,2024-02-29,2024-05-08,2416,7.8,AI Innovations -AI10376,NLP Engineer,180262,CAD,225328,EX,CT,Canada,L,Canada,100,"MLOps, Spark, Data Visualization, R",Bachelor,13,Government,2025-02-08,2025-04-19,2351,9.9,TechCorp Inc -AI10377,Head of AI,113460,USD,113460,SE,CT,Finland,S,Kenya,100,"Hadoop, Linux, PyTorch",Bachelor,7,Gaming,2024-06-03,2024-08-03,1972,5.3,DataVision Ltd -AI10378,NLP Engineer,153403,USD,153403,SE,PT,Sweden,L,Sweden,50,"GCP, Azure, Mathematics",Bachelor,7,Healthcare,2024-07-23,2024-09-05,2006,5.7,Autonomous Tech -AI10379,Data Engineer,84780,CAD,105975,MI,PT,Canada,S,Canada,100,"Kubernetes, Docker, Tableau, Azure, Git",PhD,4,Education,2024-08-25,2024-10-21,1131,5.2,AI Innovations -AI10380,AI Consultant,157851,JPY,17363610,EX,CT,Japan,M,Belgium,100,"Scala, TensorFlow, Kubernetes, SQL, PyTorch",Bachelor,12,Telecommunications,2024-12-25,2025-01-19,1496,6,DeepTech Ventures -AI10381,ML Ops Engineer,161328,JPY,17746080,EX,PT,Japan,S,Japan,50,"R, Scala, Mathematics, Deep Learning",Associate,12,Automotive,2024-01-01,2024-03-12,1229,7.1,Machine Intelligence Group -AI10382,AI Research Scientist,180015,CAD,225019,EX,FL,Canada,S,Canada,0,"Deep Learning, Statistics, Scala, Azure",Associate,15,Government,2024-06-11,2024-07-21,856,10,Cloud AI Solutions -AI10383,Machine Learning Researcher,169051,USD,169051,SE,PT,United States,L,United States,50,"R, Java, Deep Learning",PhD,6,Retail,2024-11-02,2025-01-01,2205,7.5,Cloud AI Solutions -AI10384,Robotics Engineer,47369,USD,47369,SE,PT,India,L,India,50,"Linux, Docker, AWS, R",Bachelor,7,Energy,2024-09-12,2024-09-30,2206,9.3,Future Systems -AI10385,Computer Vision Engineer,59893,EUR,50909,EN,FT,Austria,L,Luxembourg,50,"Docker, TensorFlow, NLP, GCP",Bachelor,1,Gaming,2025-01-17,2025-03-08,630,7.8,Cognitive Computing -AI10386,AI Research Scientist,77568,JPY,8532480,EN,FT,Japan,M,Japan,0,"Linux, Python, Deep Learning, TensorFlow, Git",PhD,0,Energy,2024-03-12,2024-05-03,2286,7.8,Advanced Robotics -AI10387,Robotics Engineer,65205,USD,65205,SE,PT,China,M,Kenya,100,"PyTorch, TensorFlow, Deep Learning",PhD,9,Finance,2024-03-10,2024-04-06,766,9.5,DataVision Ltd -AI10388,Robotics Engineer,123050,CHF,110745,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Hadoop, MLOps, SQL",Master,0,Transportation,2024-02-18,2024-03-24,961,9.9,Algorithmic Solutions -AI10389,AI Specialist,59751,USD,59751,EN,FL,Finland,M,Finland,50,"Kubernetes, Linux, GCP, Spark",PhD,0,Gaming,2024-01-08,2024-01-27,2237,7.2,TechCorp Inc -AI10390,AI Product Manager,158205,USD,158205,EX,PT,South Korea,S,South Korea,100,"Kubernetes, Spark, Python, Git, AWS",Master,12,Finance,2024-05-12,2024-06-04,1898,5.2,Future Systems -AI10391,Data Scientist,104978,USD,104978,MI,CT,Ireland,M,Netherlands,50,"AWS, Tableau, Java, Azure, Python",Associate,4,Technology,2024-02-14,2024-03-25,1561,5.3,Predictive Systems -AI10392,AI Product Manager,51383,JPY,5652130,EN,FL,Japan,S,Japan,50,"SQL, Kubernetes, Deep Learning, NLP",PhD,1,Gaming,2024-07-26,2024-08-17,1313,5.5,Quantum Computing Inc -AI10393,Head of AI,133639,CHF,120275,MI,FT,Switzerland,L,Switzerland,0,"Linux, AWS, Deep Learning",PhD,2,Education,2025-01-28,2025-03-05,1763,6.2,Predictive Systems -AI10394,NLP Engineer,70113,JPY,7712430,EN,FL,Japan,M,Japan,0,"Deep Learning, GCP, Scala",PhD,0,Gaming,2024-02-20,2024-04-30,2186,6.7,Quantum Computing Inc -AI10395,AI Product Manager,104072,EUR,88461,MI,FL,Germany,M,Germany,50,"Deep Learning, Python, TensorFlow, Mathematics, PyTorch",Bachelor,4,Retail,2024-05-30,2024-08-08,1966,9.8,TechCorp Inc -AI10396,AI Specialist,71642,AUD,96717,EN,PT,Australia,S,Australia,0,"SQL, Scala, Computer Vision, PyTorch, TensorFlow",Bachelor,0,Gaming,2024-10-08,2024-10-30,1976,6.4,DeepTech Ventures -AI10397,Deep Learning Engineer,140288,USD,140288,SE,FT,Sweden,L,Sweden,50,"Python, Mathematics, TensorFlow",Bachelor,8,Government,2024-06-28,2024-09-07,1002,7,Machine Intelligence Group -AI10398,Data Scientist,134675,EUR,114474,SE,CT,Netherlands,S,Argentina,100,"Python, Git, Statistics",Bachelor,8,Technology,2024-03-11,2024-03-27,1466,7.1,Neural Networks Co -AI10399,AI Consultant,22938,USD,22938,EN,FT,India,M,India,100,"GCP, Tableau, Azure, Mathematics, Spark",Associate,0,Education,2024-05-07,2024-06-09,1943,8.4,Cloud AI Solutions -AI10400,Deep Learning Engineer,141684,EUR,120431,SE,FT,France,L,France,0,"AWS, R, PyTorch, Docker, Tableau",Master,7,Retail,2024-05-11,2024-07-20,2266,5.2,AI Innovations -AI10401,Principal Data Scientist,83033,USD,83033,SE,FL,South Korea,S,South Korea,100,"NLP, Python, TensorFlow, Hadoop, Spark",Bachelor,8,Education,2024-10-28,2024-12-03,2458,6.5,Future Systems -AI10402,Data Engineer,222353,EUR,189000,EX,FT,Netherlands,M,Netherlands,50,"R, Tableau, NLP, MLOps, Docker",Bachelor,18,Telecommunications,2025-01-26,2025-04-09,2350,8.2,TechCorp Inc -AI10403,AI Specialist,89362,EUR,75958,MI,PT,Netherlands,L,Netherlands,0,"TensorFlow, PyTorch, Deep Learning",Master,4,Retail,2024-01-19,2024-03-03,906,9.7,AI Innovations -AI10404,AI Specialist,199765,USD,199765,EX,FL,South Korea,M,South Korea,100,"Python, Git, Docker, GCP, Tableau",Master,19,Real Estate,2024-09-30,2024-11-01,2156,8.1,Future Systems -AI10405,Head of AI,102081,AUD,137809,SE,PT,Australia,M,Australia,50,"Mathematics, Scala, R, Kubernetes",Master,9,Retail,2024-07-07,2024-08-26,2167,8.5,Cloud AI Solutions -AI10406,AI Research Scientist,221776,USD,221776,EX,FL,Norway,S,Norway,0,"SQL, Python, NLP",Bachelor,10,Finance,2024-03-30,2024-05-01,801,5.5,Cloud AI Solutions -AI10407,Deep Learning Engineer,95606,USD,95606,EX,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, GCP, Statistics",Associate,14,Retail,2025-04-12,2025-05-04,609,8.6,Advanced Robotics -AI10408,Data Scientist,102808,EUR,87387,MI,PT,Austria,M,Austria,100,"SQL, Linux, NLP, Scala",PhD,4,Real Estate,2024-07-06,2024-08-14,1703,5.2,Digital Transformation LLC -AI10409,ML Ops Engineer,104905,USD,104905,MI,CT,Norway,S,Norway,50,"Spark, AWS, Statistics",Master,4,Healthcare,2024-08-18,2024-10-02,1678,7.7,DataVision Ltd -AI10410,Computer Vision Engineer,133598,CHF,120238,MI,FT,Switzerland,S,Switzerland,0,"Spark, Kubernetes, Data Visualization",Bachelor,3,Energy,2024-10-11,2024-12-05,2492,6.9,Machine Intelligence Group -AI10411,Autonomous Systems Engineer,282463,JPY,31070930,EX,CT,Japan,L,Japan,0,"MLOps, Java, Python",Associate,19,Education,2024-12-22,2025-01-08,1949,9.9,Cloud AI Solutions -AI10412,Data Engineer,146803,EUR,124783,EX,PT,Germany,M,Germany,100,"SQL, Git, Computer Vision, AWS",Master,13,Finance,2025-02-09,2025-04-21,2291,6.2,Predictive Systems -AI10413,AI Product Manager,226731,USD,226731,EX,FT,Ireland,L,Ireland,0,"Linux, Computer Vision, R, Python",Associate,17,Consulting,2024-05-01,2024-06-25,2395,10,Predictive Systems -AI10414,Data Scientist,85796,EUR,72927,MI,FT,France,L,France,0,"Python, TensorFlow, Mathematics",Associate,3,Transportation,2024-06-16,2024-08-01,2131,9.4,Machine Intelligence Group -AI10415,Head of AI,67219,AUD,90746,EN,FT,Australia,L,Australia,50,"MLOps, Deep Learning, TensorFlow, Python, Computer Vision",PhD,0,Telecommunications,2025-03-29,2025-05-16,2183,5.8,Digital Transformation LLC -AI10416,Deep Learning Engineer,19495,USD,19495,EN,CT,India,M,India,50,"Azure, Python, Linux",Associate,1,Manufacturing,2024-11-20,2025-01-18,1129,6.5,Predictive Systems -AI10417,Machine Learning Engineer,143665,USD,143665,SE,CT,Sweden,M,Sweden,0,"Git, Deep Learning, MLOps, PyTorch",Bachelor,8,Manufacturing,2024-08-21,2024-09-04,951,6.9,DeepTech Ventures -AI10418,Computer Vision Engineer,54072,AUD,72997,EN,PT,Australia,S,Germany,100,"SQL, Tableau, PyTorch, AWS, MLOps",Master,0,Media,2024-09-01,2024-11-02,1394,7.4,DataVision Ltd -AI10419,Data Scientist,93668,EUR,79618,SE,FT,Austria,S,Austria,100,"Mathematics, Git, MLOps, Kubernetes",Bachelor,6,Finance,2024-04-26,2024-05-11,2402,5,Predictive Systems -AI10420,ML Ops Engineer,238158,USD,238158,EX,PT,Norway,L,Norway,50,"Git, SQL, Python, GCP",Master,19,Real Estate,2024-06-15,2024-07-29,1932,8.7,Quantum Computing Inc -AI10421,Computer Vision Engineer,71023,GBP,53267,EN,CT,United Kingdom,S,South Africa,100,"Hadoop, Git, R, Java",Master,1,Real Estate,2024-06-14,2024-07-12,1434,9.5,Digital Transformation LLC -AI10422,AI Specialist,86841,EUR,73815,MI,CT,Germany,L,Australia,100,"PyTorch, TensorFlow, MLOps",PhD,2,Media,2024-01-19,2024-03-24,806,9.9,Cognitive Computing -AI10423,ML Ops Engineer,154195,CAD,192744,EX,PT,Canada,S,Belgium,50,"NLP, PyTorch, R, Java",Master,15,Consulting,2024-10-09,2024-10-31,695,5.8,Future Systems -AI10424,Robotics Engineer,92933,SGD,120813,MI,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Scala",PhD,3,Education,2024-06-03,2024-07-30,1876,7.2,DataVision Ltd -AI10425,Deep Learning Engineer,122175,SGD,158828,SE,PT,Singapore,S,Nigeria,50,"NLP, Scala, Statistics, Deep Learning",Master,8,Technology,2024-05-18,2024-07-22,2133,5.2,Smart Analytics -AI10426,AI Software Engineer,123306,EUR,104810,EX,CT,France,S,France,100,"Python, TensorFlow, GCP",PhD,15,Education,2024-11-15,2025-01-06,1729,6.4,AI Innovations -AI10427,AI Research Scientist,103528,EUR,87999,MI,PT,Austria,L,Austria,100,"GCP, AWS, MLOps",Bachelor,4,Government,2024-08-05,2024-09-24,926,5.8,DataVision Ltd -AI10428,AI Specialist,98123,EUR,83405,SE,FT,Netherlands,S,Netherlands,0,"PyTorch, NLP, Docker, AWS",Associate,6,Telecommunications,2024-08-22,2024-10-12,1172,6.8,Predictive Systems -AI10429,AI Research Scientist,75392,USD,75392,EN,FL,South Korea,L,South Korea,0,"Python, Java, Azure, Kubernetes, Git",Bachelor,1,Finance,2024-02-08,2024-03-21,1380,8.2,Future Systems -AI10430,AI Architect,47588,CAD,59485,EN,FL,Canada,S,Canada,50,"Kubernetes, Git, Tableau",PhD,0,Real Estate,2024-08-23,2024-10-20,2296,6.1,Future Systems -AI10431,Data Engineer,64925,JPY,7141750,EN,CT,Japan,S,Estonia,50,"Scala, Mathematics, SQL, Azure, Data Visualization",Bachelor,1,Manufacturing,2024-10-13,2024-12-11,1706,8.8,DeepTech Ventures -AI10432,AI Consultant,59060,USD,59060,MI,CT,China,L,China,0,"Computer Vision, Java, PyTorch",Master,3,Government,2024-03-23,2024-05-12,2496,6.8,Quantum Computing Inc -AI10433,Machine Learning Researcher,206097,USD,206097,SE,CT,Denmark,L,Denmark,100,"Python, Data Visualization, Spark",Master,8,Energy,2024-10-08,2024-11-26,2416,8.5,AI Innovations -AI10434,Data Engineer,61098,USD,61098,EN,FL,South Korea,M,Indonesia,0,"Statistics, PyTorch, MLOps",Master,1,Telecommunications,2024-05-20,2024-06-27,1175,8,Quantum Computing Inc -AI10435,Data Scientist,63567,USD,63567,EN,CT,Ireland,M,Ireland,0,"AWS, R, Data Visualization",Bachelor,0,Gaming,2024-07-12,2024-07-31,2154,9.2,Quantum Computing Inc -AI10436,Machine Learning Engineer,247728,CHF,222955,SE,FL,Switzerland,L,Indonesia,0,"Hadoop, Kubernetes, NLP",Associate,9,Telecommunications,2024-08-22,2024-09-21,1912,5.7,TechCorp Inc -AI10437,Research Scientist,125206,GBP,93905,SE,CT,United Kingdom,M,Indonesia,50,"Deep Learning, Tableau, Kubernetes, Git",Master,7,Media,2024-09-26,2024-10-16,1042,8.2,Digital Transformation LLC -AI10438,Robotics Engineer,72094,EUR,61280,EN,PT,France,M,France,100,"Linux, Java, Mathematics, Computer Vision, PyTorch",Associate,1,Healthcare,2025-03-31,2025-05-23,2433,5.9,TechCorp Inc -AI10439,AI Research Scientist,85942,CAD,107428,EN,PT,Canada,L,Canada,100,"Linux, Kubernetes, Hadoop, Statistics",Associate,0,Consulting,2024-05-09,2024-06-25,2072,7.1,TechCorp Inc -AI10440,ML Ops Engineer,191299,USD,191299,EX,CT,Ireland,M,Spain,100,"Azure, SQL, PyTorch",Bachelor,17,Telecommunications,2024-05-14,2024-06-24,1221,5.6,Autonomous Tech -AI10441,Computer Vision Engineer,145582,USD,145582,SE,CT,Israel,L,Israel,50,"Deep Learning, Kubernetes, R",Associate,5,Technology,2024-08-24,2024-10-21,1743,7.9,AI Innovations -AI10442,AI Architect,91181,AUD,123094,MI,PT,Australia,S,Australia,100,"Git, Docker, SQL, Kubernetes",Master,4,Media,2024-12-18,2025-02-24,1535,5.8,Smart Analytics -AI10443,NLP Engineer,100215,USD,100215,EX,CT,China,S,Indonesia,0,"Docker, R, Java",Bachelor,11,Manufacturing,2024-03-11,2024-05-09,2088,9.3,Quantum Computing Inc -AI10444,AI Consultant,47259,USD,47259,EX,FT,India,S,India,100,"TensorFlow, Spark, NLP",PhD,14,Energy,2024-11-15,2024-12-28,1642,6.1,Quantum Computing Inc -AI10445,AI Architect,244995,USD,244995,EX,CT,Norway,M,Norway,0,"TensorFlow, Docker, R",PhD,14,Education,2024-09-19,2024-11-18,1936,9.3,TechCorp Inc -AI10446,Data Analyst,131732,AUD,177838,SE,CT,Australia,L,Australia,50,"TensorFlow, Java, Deep Learning, Linux",Associate,7,Government,2024-06-16,2024-08-09,943,6.1,Quantum Computing Inc -AI10447,Autonomous Systems Engineer,142453,SGD,185189,SE,CT,Singapore,M,Singapore,100,"Mathematics, Docker, Python, Scala, Computer Vision",Master,8,Transportation,2024-12-23,2025-02-02,846,6.6,DataVision Ltd -AI10448,Data Scientist,114905,EUR,97669,MI,FL,France,L,France,100,"Python, GCP, Spark",Bachelor,4,Real Estate,2024-03-30,2024-05-07,972,5.5,Smart Analytics -AI10449,Machine Learning Engineer,94309,USD,94309,MI,CT,Sweden,L,Sweden,0,"Python, Git, TensorFlow, Docker, PyTorch",Associate,2,Retail,2024-09-24,2024-12-03,1036,7.7,DeepTech Ventures -AI10450,AI Consultant,269435,CHF,242492,EX,PT,Switzerland,M,Switzerland,100,"MLOps, Java, Azure",Bachelor,18,Manufacturing,2025-02-26,2025-04-08,1393,9.2,Advanced Robotics -AI10451,Machine Learning Engineer,64365,EUR,54710,EN,FL,Germany,S,Germany,0,"Spark, GCP, Mathematics",Associate,1,Gaming,2024-04-26,2024-07-01,1828,10,TechCorp Inc -AI10452,AI Specialist,105348,USD,105348,EN,PT,Norway,L,Norway,100,"NLP, Python, Kubernetes, AWS",Master,0,Technology,2024-12-18,2025-01-13,1099,9.1,Cloud AI Solutions -AI10453,Machine Learning Engineer,157110,GBP,117833,SE,FL,United Kingdom,L,United Kingdom,50,"Scala, Deep Learning, MLOps, Data Visualization",Bachelor,6,Technology,2024-03-26,2024-05-22,1108,9.9,Autonomous Tech -AI10454,Computer Vision Engineer,312583,USD,312583,EX,FL,Denmark,L,United States,0,"SQL, Deep Learning, NLP",Master,19,Manufacturing,2024-08-16,2024-09-16,536,8.6,Digital Transformation LLC -AI10455,Autonomous Systems Engineer,74526,USD,74526,EX,FT,China,M,Canada,0,"TensorFlow, R, Data Visualization",Master,12,Education,2024-07-22,2024-09-24,1101,10,Cognitive Computing -AI10456,Robotics Engineer,172413,JPY,18965430,SE,FL,Japan,L,Japan,100,"Python, Docker, TensorFlow, SQL, AWS",Associate,5,Media,2025-03-02,2025-03-30,1199,5.3,TechCorp Inc -AI10457,Machine Learning Researcher,163535,EUR,139005,SE,PT,Austria,L,Austria,50,"Statistics, Spark, Tableau",Master,8,Government,2024-08-19,2024-10-10,1823,9,TechCorp Inc -AI10458,Data Analyst,132082,USD,132082,EX,FL,South Korea,M,South Korea,50,"SQL, NLP, Azure, Scala, Python",Master,17,Media,2024-06-13,2024-08-15,1298,9.2,Digital Transformation LLC -AI10459,Research Scientist,261749,USD,261749,EX,CT,Norway,S,Finland,100,"Computer Vision, Statistics, PyTorch, Java",PhD,12,Government,2024-02-19,2024-03-06,1489,8.4,Cognitive Computing -AI10460,Head of AI,68534,USD,68534,SE,FL,China,M,China,50,"Deep Learning, GCP, Computer Vision",Master,8,Media,2024-03-08,2024-03-26,1951,6.7,Machine Intelligence Group -AI10461,AI Consultant,95396,EUR,81087,MI,CT,Germany,M,Germany,100,"Linux, SQL, Kubernetes, GCP",Bachelor,4,Retail,2024-06-11,2024-07-03,1007,7.8,Predictive Systems -AI10462,Data Scientist,74131,AUD,100077,EN,CT,Australia,M,Australia,50,"Spark, Hadoop, Tableau, Mathematics",Master,1,Transportation,2024-01-15,2024-03-05,951,8.9,Neural Networks Co -AI10463,Computer Vision Engineer,115232,USD,115232,MI,CT,Denmark,M,Denmark,50,"Tableau, NLP, Scala, Deep Learning, PyTorch",Master,3,Technology,2024-12-25,2025-02-25,667,6.9,Digital Transformation LLC -AI10464,Machine Learning Engineer,58227,SGD,75695,EN,FL,Singapore,S,Singapore,100,"Kubernetes, Deep Learning, NLP, TensorFlow",Bachelor,1,Healthcare,2024-01-03,2024-01-19,2113,9.1,Machine Intelligence Group -AI10465,Data Analyst,188430,CHF,169587,SE,FT,Switzerland,L,Switzerland,100,"Python, Scala, Hadoop, Docker, TensorFlow",Associate,6,Technology,2025-03-01,2025-03-25,955,6.4,Quantum Computing Inc -AI10466,Head of AI,72415,SGD,94140,EN,PT,Singapore,M,Singapore,0,"Git, Scala, Linux, SQL",Associate,0,Retail,2024-05-12,2024-06-18,2310,7.2,DeepTech Ventures -AI10467,AI Consultant,49041,GBP,36781,EN,FT,United Kingdom,S,United Kingdom,100,"Docker, Spark, Deep Learning, TensorFlow, PyTorch",Master,1,Manufacturing,2024-10-28,2024-11-18,660,8.4,Neural Networks Co -AI10468,Research Scientist,78075,USD,78075,MI,FL,Finland,M,Finland,0,"Statistics, Hadoop, Tableau, Kubernetes",Master,3,Automotive,2025-03-27,2025-05-28,657,9,Neural Networks Co -AI10469,Autonomous Systems Engineer,96725,USD,96725,EN,PT,Denmark,L,Denmark,100,"Git, PyTorch, Scala, Azure",Associate,1,Technology,2025-01-26,2025-02-20,1553,5.6,Cloud AI Solutions -AI10470,AI Architect,116451,CAD,145564,MI,FL,Canada,L,Canada,0,"Kubernetes, Azure, SQL, Java, Spark",Bachelor,3,Automotive,2024-06-17,2024-08-24,883,9.6,Autonomous Tech -AI10471,AI Research Scientist,96459,SGD,125397,EN,FT,Singapore,L,Austria,100,"Data Visualization, Azure, Mathematics, PyTorch",PhD,0,Manufacturing,2024-03-26,2024-06-04,1160,7.4,DataVision Ltd -AI10472,AI Research Scientist,254343,CHF,228909,EX,FT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Hadoop, Statistics",Associate,18,Real Estate,2024-02-28,2024-04-15,1326,8.1,Autonomous Tech -AI10473,Autonomous Systems Engineer,131234,EUR,111549,SE,FL,Germany,S,Germany,100,"Java, Spark, Statistics, Mathematics",PhD,6,Manufacturing,2024-08-13,2024-09-24,701,9.5,Future Systems -AI10474,Autonomous Systems Engineer,53585,USD,53585,EN,CT,South Korea,S,South Korea,100,"Tableau, NLP, MLOps, Data Visualization",PhD,0,Media,2025-01-01,2025-03-09,1610,6.6,Future Systems -AI10475,AI Consultant,156371,USD,156371,SE,PT,Denmark,M,Denmark,0,"NLP, Hadoop, GCP, Azure, Java",Bachelor,8,Telecommunications,2025-01-21,2025-02-24,686,6.6,DataVision Ltd -AI10476,NLP Engineer,166022,GBP,124517,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, Docker",PhD,19,Consulting,2024-10-31,2024-12-31,2259,9.8,Predictive Systems -AI10477,AI Software Engineer,87583,SGD,113858,MI,FL,Singapore,M,Belgium,100,"Data Visualization, Docker, Kubernetes, Scala",Bachelor,2,Manufacturing,2024-08-12,2024-09-07,1779,9.8,Predictive Systems -AI10478,Robotics Engineer,131350,USD,131350,SE,FL,Ireland,M,Ireland,100,"NLP, Java, Kubernetes",Bachelor,7,Education,2024-10-07,2024-11-16,1324,5.1,Algorithmic Solutions -AI10479,Robotics Engineer,25847,USD,25847,EN,FL,China,M,China,100,"R, TensorFlow, Docker, Data Visualization",Master,1,Manufacturing,2024-05-13,2024-07-19,567,7.3,Smart Analytics -AI10480,Data Scientist,70279,USD,70279,EN,CT,Sweden,M,Sweden,0,"Docker, Kubernetes, AWS, Tableau, Git",Master,0,Transportation,2025-04-16,2025-05-18,2431,5.9,Quantum Computing Inc -AI10481,Principal Data Scientist,83967,USD,83967,MI,FL,Sweden,L,Sweden,50,"Data Visualization, Git, Scala",Associate,4,Consulting,2024-06-26,2024-07-30,533,5.8,Advanced Robotics -AI10482,Data Analyst,117772,USD,117772,SE,FT,Israel,S,Israel,50,"AWS, GCP, Statistics, Java",PhD,5,Government,2025-04-30,2025-07-02,1085,7,Predictive Systems -AI10483,Data Engineer,77901,USD,77901,MI,PT,Finland,S,Finland,100,"Scala, Spark, AWS, PyTorch, Linux",PhD,4,Government,2024-02-16,2024-04-19,2164,9.6,Digital Transformation LLC -AI10484,Robotics Engineer,251299,USD,251299,EX,FT,Israel,L,Israel,100,"Kubernetes, Scala, GCP",PhD,17,Retail,2024-02-17,2024-03-10,2304,9.5,Quantum Computing Inc -AI10485,ML Ops Engineer,56632,CAD,70790,EN,FL,Canada,S,Canada,0,"Computer Vision, AWS, NLP",Master,1,Media,2025-04-10,2025-06-08,1669,8.2,Cloud AI Solutions -AI10486,Data Scientist,89248,EUR,75861,SE,FT,Austria,S,Austria,0,"PyTorch, MLOps, Python, R",Master,6,Technology,2025-04-03,2025-06-01,819,6.8,Machine Intelligence Group -AI10487,ML Ops Engineer,159129,CHF,143216,SE,FL,Switzerland,S,Switzerland,0,"TensorFlow, SQL, R",Associate,8,Government,2024-09-09,2024-10-10,2320,5.5,Cognitive Computing -AI10488,Deep Learning Engineer,121563,USD,121563,SE,CT,Finland,S,Norway,100,"Python, GCP, Git, TensorFlow, Statistics",Associate,9,Government,2024-11-11,2024-12-16,1300,5.6,Future Systems -AI10489,Computer Vision Engineer,60861,EUR,51732,EN,CT,Austria,L,Austria,0,"Azure, PyTorch, Mathematics, Python",Bachelor,0,Telecommunications,2024-03-13,2024-05-24,1422,8.3,DeepTech Ventures -AI10490,Research Scientist,118967,CHF,107070,MI,CT,Switzerland,L,Canada,50,"Java, MLOps, Python, R",PhD,4,Technology,2024-08-31,2024-10-28,1605,9.3,DataVision Ltd -AI10491,AI Research Scientist,233392,EUR,198383,EX,FT,Germany,L,Germany,100,"Statistics, Java, PyTorch, Deep Learning",Bachelor,16,Government,2024-02-29,2024-05-07,2030,7.7,AI Innovations -AI10492,Data Analyst,132254,EUR,112416,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, Computer Vision, Tableau",Master,9,Education,2024-06-18,2024-07-04,2009,7.7,DataVision Ltd -AI10493,Data Analyst,64661,USD,64661,EN,FL,Finland,L,Finland,100,"Statistics, TensorFlow, Hadoop, GCP, Deep Learning",PhD,1,Finance,2024-09-08,2024-10-18,621,8.1,Smart Analytics -AI10494,Head of AI,113314,USD,113314,MI,CT,United States,M,Australia,50,"Python, SQL, Linux, GCP, Scala",Master,4,Media,2024-06-26,2024-08-09,936,9.4,AI Innovations -AI10495,Autonomous Systems Engineer,114505,SGD,148857,SE,CT,Singapore,S,Singapore,100,"Java, R, GCP, Mathematics, Hadoop",Associate,8,Media,2024-03-25,2024-04-16,1103,9.3,Smart Analytics -AI10496,AI Software Engineer,176423,EUR,149960,EX,CT,Austria,L,Ghana,100,"PyTorch, Hadoop, Linux, Azure, Scala",PhD,17,Government,2024-11-18,2024-12-08,2133,6.2,Smart Analytics -AI10497,Deep Learning Engineer,47416,EUR,40304,EN,PT,Austria,S,Austria,0,"Linux, AWS, Computer Vision",Associate,0,Telecommunications,2024-10-10,2024-12-09,1205,5.9,DeepTech Ventures -AI10498,Data Scientist,273664,GBP,205248,EX,FL,United Kingdom,L,United Kingdom,100,"Azure, Python, GCP",Bachelor,18,Technology,2024-08-21,2024-10-14,1518,6.8,Predictive Systems -AI10499,AI Product Manager,158106,SGD,205538,SE,PT,Singapore,L,Singapore,100,"Python, Kubernetes, Computer Vision, Hadoop",Bachelor,9,Telecommunications,2024-06-16,2024-07-05,576,8.1,Autonomous Tech -AI10500,Deep Learning Engineer,134252,EUR,114114,SE,CT,Austria,M,Austria,50,"Azure, Scala, AWS",Associate,7,Education,2025-04-01,2025-04-28,821,9.3,Smart Analytics -AI10501,Research Scientist,39883,USD,39883,EN,CT,South Korea,S,Australia,100,"Tableau, PyTorch, AWS, Statistics, Git",Bachelor,0,Real Estate,2024-09-18,2024-11-19,2465,6.2,Quantum Computing Inc -AI10502,AI Architect,86586,USD,86586,MI,FL,Ireland,S,Ireland,100,"SQL, Scala, Statistics, Kubernetes, GCP",Bachelor,4,Transportation,2024-11-26,2024-12-16,1516,8.2,Cognitive Computing -AI10503,NLP Engineer,158006,JPY,17380660,SE,PT,Japan,L,Switzerland,50,"Kubernetes, Spark, R, Deep Learning",Bachelor,9,Finance,2024-09-02,2024-11-12,2181,9.5,Quantum Computing Inc -AI10504,Research Scientist,160380,USD,160380,EX,FL,Israel,L,Israel,50,"Python, Azure, NLP, TensorFlow, AWS",Master,18,Government,2024-10-19,2024-11-29,2304,5.4,Advanced Robotics -AI10505,NLP Engineer,178755,USD,178755,SE,CT,Norway,L,Norway,100,"Hadoop, Spark, Computer Vision",PhD,6,Energy,2025-01-29,2025-02-20,1020,6.4,Predictive Systems -AI10506,Principal Data Scientist,99536,USD,99536,MI,CT,United States,M,United States,100,"Linux, PyTorch, SQL, Statistics, MLOps",Bachelor,2,Manufacturing,2025-04-07,2025-06-13,1184,6.2,Predictive Systems -AI10507,AI Research Scientist,124279,AUD,167777,MI,FT,Australia,L,Australia,50,"Java, PyTorch, R, Tableau",Bachelor,2,Retail,2025-04-27,2025-06-06,862,5.8,DeepTech Ventures -AI10508,Machine Learning Engineer,64888,EUR,55155,EN,FL,Germany,L,Germany,50,"Spark, Linux, PyTorch, Java",Associate,1,Technology,2025-02-11,2025-03-06,1392,5.1,Cloud AI Solutions -AI10509,AI Product Manager,102390,EUR,87032,SE,FL,Germany,S,Germany,0,"GCP, Deep Learning, R, TensorFlow",PhD,9,Gaming,2024-06-27,2024-08-12,1601,5.7,Future Systems -AI10510,Research Scientist,43363,USD,43363,MI,PT,China,L,China,100,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Master,3,Government,2024-05-10,2024-07-19,1250,9.1,Algorithmic Solutions -AI10511,Machine Learning Engineer,82118,AUD,110859,EN,CT,Australia,L,Australia,50,"Deep Learning, Mathematics, Data Visualization",PhD,0,Transportation,2024-05-22,2024-07-11,2347,9,Machine Intelligence Group -AI10512,Deep Learning Engineer,138768,USD,138768,SE,FL,Ireland,L,Ireland,50,"Hadoop, Kubernetes, Data Visualization, NLP, Spark",Associate,7,Media,2024-08-09,2024-09-26,2439,6.6,Neural Networks Co -AI10513,Computer Vision Engineer,48876,AUD,65983,EN,FL,Australia,S,Australia,50,"NLP, GCP, Tableau, Azure, Docker",Master,1,Gaming,2024-06-01,2024-07-29,1711,7.9,DataVision Ltd -AI10514,Machine Learning Researcher,72281,USD,72281,EN,FT,Ireland,S,Ireland,0,"SQL, Hadoop, Data Visualization",Bachelor,0,Consulting,2024-09-22,2024-10-09,1577,8.4,Neural Networks Co -AI10515,AI Research Scientist,136114,AUD,183754,SE,PT,Australia,S,Australia,100,"Python, Scala, Java, Deep Learning",Bachelor,8,Consulting,2024-01-04,2024-02-22,901,5.5,Predictive Systems -AI10516,Data Analyst,47355,USD,47355,SE,FL,India,S,Israel,100,"Tableau, Spark, AWS, Scala, SQL",Bachelor,6,Gaming,2024-11-09,2024-11-24,1396,6.4,Autonomous Tech -AI10517,AI Architect,116538,USD,116538,MI,FT,Israel,L,Israel,0,"Statistics, Spark, Mathematics",Bachelor,2,Finance,2024-09-06,2024-10-24,1791,9.1,Machine Intelligence Group -AI10518,Data Engineer,101215,USD,101215,MI,CT,Ireland,M,Ireland,0,"Git, Python, NLP, Statistics, Kubernetes",PhD,4,Energy,2024-06-25,2024-08-08,1775,9.3,Smart Analytics -AI10519,Computer Vision Engineer,120939,CHF,108845,MI,CT,Switzerland,L,Switzerland,0,"Git, Java, SQL, Azure",Associate,3,Media,2024-12-16,2025-02-17,1891,8,Smart Analytics -AI10520,AI Consultant,53345,JPY,5867950,EN,PT,Japan,S,Netherlands,50,"Python, TensorFlow, Kubernetes, Linux, MLOps",Master,1,Telecommunications,2024-05-28,2024-07-13,605,7.9,Quantum Computing Inc -AI10521,Machine Learning Researcher,49297,USD,49297,EN,FT,Israel,M,Israel,0,"Kubernetes, PyTorch, GCP",Master,0,Manufacturing,2024-06-15,2024-07-19,2343,8.2,Predictive Systems -AI10522,Data Engineer,85313,SGD,110907,EN,FL,Singapore,M,Singapore,100,"SQL, PyTorch, NLP, Hadoop, MLOps",PhD,1,Gaming,2024-02-03,2024-02-17,960,6.9,Future Systems -AI10523,Computer Vision Engineer,165378,CAD,206723,EX,FT,Canada,S,Canada,50,"Java, Git, Tableau, GCP",Bachelor,18,Real Estate,2024-01-26,2024-03-25,1637,9.5,Algorithmic Solutions -AI10524,AI Product Manager,78358,USD,78358,EN,PT,Israel,L,Israel,0,"Java, SQL, Computer Vision, R",Bachelor,0,Government,2024-01-24,2024-03-07,723,6.1,DeepTech Ventures -AI10525,NLP Engineer,23160,USD,23160,EN,FL,India,S,India,100,"Docker, Git, Statistics, R",Bachelor,1,Manufacturing,2024-05-09,2024-06-14,936,9.7,Quantum Computing Inc -AI10526,Research Scientist,85575,USD,85575,MI,PT,Israel,M,Israel,0,"Python, Kubernetes, Linux, NLP, PyTorch",Bachelor,2,Education,2025-03-28,2025-06-04,2322,7.1,TechCorp Inc -AI10527,AI Specialist,188461,JPY,20730710,EX,FL,Japan,S,Japan,50,"Scala, Spark, Tableau, MLOps",Master,18,Consulting,2025-01-19,2025-03-26,988,5.7,Digital Transformation LLC -AI10528,Autonomous Systems Engineer,16621,USD,16621,EN,CT,India,S,India,0,"Kubernetes, Python, AWS",Master,0,Manufacturing,2025-02-24,2025-04-29,1724,7.9,Advanced Robotics -AI10529,Machine Learning Researcher,154393,CAD,192991,SE,FL,Canada,L,Canada,100,"Kubernetes, Python, TensorFlow, Java",Master,7,Retail,2024-10-23,2024-11-26,2475,6.9,Quantum Computing Inc -AI10530,Machine Learning Researcher,115524,USD,115524,SE,FT,Finland,S,Finland,50,"R, SQL, Data Visualization, Linux, Deep Learning",Associate,6,Education,2024-01-27,2024-03-29,1229,6.9,Advanced Robotics -AI10531,AI Software Engineer,20633,USD,20633,EN,PT,India,S,India,100,"SQL, GCP, Azure",PhD,1,Real Estate,2024-03-02,2024-04-17,1824,6.9,Cognitive Computing -AI10532,Robotics Engineer,190066,GBP,142550,EX,FL,United Kingdom,S,Romania,50,"PyTorch, Docker, AWS, Deep Learning",Associate,11,Government,2024-08-17,2024-10-08,1342,9.3,Quantum Computing Inc -AI10533,Head of AI,296126,JPY,32573860,EX,FT,Japan,L,Japan,0,"PyTorch, Statistics, TensorFlow, NLP, Deep Learning",Associate,18,Gaming,2024-07-21,2024-09-18,775,9.6,Predictive Systems -AI10534,Autonomous Systems Engineer,187800,USD,187800,SE,FL,Norway,L,Norway,100,"Tableau, Git, Deep Learning, Python, SQL",PhD,7,Real Estate,2024-12-30,2025-03-13,1720,9.5,Autonomous Tech -AI10535,Data Scientist,206562,USD,206562,EX,CT,Ireland,S,Ireland,100,"GCP, Java, NLP, Data Visualization",Associate,17,Gaming,2024-06-10,2024-07-15,1196,7.1,Algorithmic Solutions -AI10536,AI Specialist,188230,JPY,20705300,EX,FL,Japan,S,Japan,0,"Python, Computer Vision, Tableau, Linux",PhD,11,Manufacturing,2024-08-20,2024-10-17,1097,7.5,TechCorp Inc -AI10537,Machine Learning Engineer,151183,USD,151183,SE,FT,Norway,S,Norway,50,"Hadoop, SQL, TensorFlow, NLP",PhD,5,Retail,2024-12-27,2025-01-31,1674,6,DeepTech Ventures -AI10538,Principal Data Scientist,84340,JPY,9277400,EN,PT,Japan,L,Japan,0,"MLOps, Git, Java, Kubernetes",Bachelor,1,Transportation,2024-06-05,2024-08-03,1477,7.1,Machine Intelligence Group -AI10539,Head of AI,130206,SGD,169268,SE,CT,Singapore,S,Singapore,100,"R, Scala, SQL, Data Visualization",Bachelor,7,Media,2024-10-05,2024-11-13,566,6,TechCorp Inc -AI10540,Machine Learning Researcher,59063,AUD,79735,EN,CT,Australia,M,Australia,0,"Azure, Python, GCP, Scala",Bachelor,0,Gaming,2024-06-07,2024-07-23,696,8.6,Cloud AI Solutions -AI10541,Data Engineer,105416,CHF,94874,EN,CT,Switzerland,M,Switzerland,50,"R, Python, Data Visualization, TensorFlow, Git",PhD,1,Consulting,2024-01-28,2024-03-11,2392,6.7,DeepTech Ventures -AI10542,Head of AI,116299,USD,116299,EX,PT,China,M,China,100,"Hadoop, Linux, SQL",Bachelor,17,Transportation,2025-01-03,2025-03-15,615,5.2,AI Innovations -AI10543,Data Analyst,123542,USD,123542,SE,FT,Sweden,M,Sweden,50,"Git, Python, AWS",Bachelor,8,Healthcare,2024-03-27,2024-05-07,2113,5.1,Cloud AI Solutions -AI10544,Computer Vision Engineer,268891,CHF,242002,EX,FL,Switzerland,L,Switzerland,50,"Statistics, R, Tableau",Master,19,Consulting,2024-10-05,2024-12-05,1722,5.8,Digital Transformation LLC -AI10545,Robotics Engineer,184006,USD,184006,EX,PT,South Korea,M,France,0,"Spark, Deep Learning, Computer Vision, Python",Bachelor,11,Telecommunications,2024-10-01,2024-11-25,1949,9.3,Future Systems -AI10546,Head of AI,253222,JPY,27854420,EX,CT,Japan,L,Japan,0,"PyTorch, Data Visualization, TensorFlow, GCP, Python",Master,17,Energy,2024-05-03,2024-06-01,1021,8.7,TechCorp Inc -AI10547,AI Software Engineer,117179,USD,117179,EN,PT,Norway,L,Thailand,100,"Data Visualization, Linux, Python",Master,1,Real Estate,2024-05-10,2024-07-06,2212,6.9,Digital Transformation LLC -AI10548,Machine Learning Engineer,267272,GBP,200454,EX,FT,United Kingdom,L,Portugal,0,"Git, Data Visualization, Java, NLP",PhD,10,Real Estate,2024-02-01,2024-03-15,503,8.8,DataVision Ltd -AI10549,Deep Learning Engineer,58015,EUR,49313,EN,FL,France,M,France,50,"Linux, NLP, Mathematics",PhD,0,Retail,2025-03-13,2025-05-25,2176,9,Smart Analytics -AI10550,Computer Vision Engineer,134945,EUR,114703,SE,FL,France,M,Philippines,100,"MLOps, Python, Hadoop, TensorFlow, Git",Master,5,Government,2024-05-20,2024-07-23,935,7.1,Machine Intelligence Group -AI10551,Data Analyst,171640,GBP,128730,SE,CT,United Kingdom,L,United Kingdom,100,"TensorFlow, Linux, Hadoop",PhD,7,Government,2024-03-26,2024-04-22,2475,9.2,Advanced Robotics -AI10552,NLP Engineer,188053,USD,188053,EX,PT,Sweden,S,Sweden,50,"Scala, Deep Learning, Java, PyTorch",Associate,18,Retail,2024-02-24,2024-03-21,2223,6.9,Machine Intelligence Group -AI10553,Research Scientist,174050,EUR,147943,SE,PT,Netherlands,L,Netherlands,100,"Linux, Statistics, Spark",Bachelor,5,Gaming,2024-07-08,2024-09-19,712,8.2,Digital Transformation LLC -AI10554,Machine Learning Researcher,162350,USD,162350,EX,CT,South Korea,S,South Korea,100,"SQL, AWS, MLOps, Azure",Master,15,Consulting,2024-06-01,2024-08-11,1094,7.6,Digital Transformation LLC -AI10555,NLP Engineer,48857,USD,48857,EN,FL,Sweden,S,Singapore,0,"Scala, Java, Computer Vision, Python, TensorFlow",Bachelor,1,Technology,2025-01-17,2025-03-10,2343,9.3,Neural Networks Co -AI10556,Autonomous Systems Engineer,81741,SGD,106263,EN,FT,Singapore,M,Singapore,100,"Mathematics, Git, NLP, SQL",Associate,0,Healthcare,2025-01-16,2025-03-25,2261,6.9,Cognitive Computing -AI10557,Data Scientist,93881,EUR,79799,MI,FT,Austria,M,Austria,100,"Scala, MLOps, Java, TensorFlow",Bachelor,3,Healthcare,2024-07-16,2024-08-24,1606,7.5,Machine Intelligence Group -AI10558,AI Research Scientist,52800,USD,52800,EN,FL,Finland,S,Finland,0,"MLOps, Docker, Data Visualization, R",PhD,0,Finance,2024-08-14,2024-10-18,551,6.8,Predictive Systems -AI10559,AI Consultant,164719,CHF,148247,MI,FL,Switzerland,L,Switzerland,100,"Hadoop, Data Visualization, Scala, Docker",Associate,4,Consulting,2024-06-24,2024-08-24,1239,5.3,Autonomous Tech -AI10560,Research Scientist,89861,GBP,67396,MI,CT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Python, Tableau",Master,2,Education,2024-07-03,2024-07-19,1058,6.4,AI Innovations -AI10561,Autonomous Systems Engineer,182265,USD,182265,EX,FL,Israel,S,Israel,100,"Kubernetes, TensorFlow, Mathematics, AWS",Bachelor,19,Manufacturing,2024-10-28,2025-01-04,1922,7.1,Quantum Computing Inc -AI10562,Head of AI,119526,USD,119526,SE,PT,Israel,M,Austria,100,"Spark, Mathematics, Python",Bachelor,6,Technology,2025-03-05,2025-04-23,1562,7,Cognitive Computing -AI10563,Deep Learning Engineer,167797,USD,167797,EX,FL,Sweden,S,United Kingdom,100,"Computer Vision, NLP, Statistics",Master,19,Healthcare,2024-12-19,2025-02-14,1184,7.9,Algorithmic Solutions -AI10564,Machine Learning Researcher,338875,USD,338875,EX,FT,United States,L,United States,100,"Statistics, PyTorch, Deep Learning, TensorFlow",Master,16,Automotive,2024-07-24,2024-08-10,2085,7.1,Smart Analytics -AI10565,NLP Engineer,191360,EUR,162656,EX,FT,Austria,S,Austria,50,"Mathematics, Hadoop, Git, Computer Vision, Data Visualization",Bachelor,16,Telecommunications,2025-04-06,2025-06-01,2448,6.5,Future Systems -AI10566,Machine Learning Researcher,134565,USD,134565,SE,FL,United States,S,United States,0,"Statistics, Linux, Python, Git, Tableau",PhD,6,Real Estate,2024-09-04,2024-10-21,653,9.5,TechCorp Inc -AI10567,AI Consultant,75173,JPY,8269030,EN,FL,Japan,S,Belgium,100,"Python, TensorFlow, Mathematics, Git",Associate,0,Real Estate,2024-11-01,2024-12-04,2083,5.4,Cloud AI Solutions -AI10568,Machine Learning Engineer,123862,EUR,105283,SE,FL,France,S,France,0,"NLP, Tableau, Computer Vision",PhD,7,Finance,2024-02-29,2024-03-18,1232,5.4,Algorithmic Solutions -AI10569,Research Scientist,118839,AUD,160433,MI,FL,Australia,L,Australia,50,"PyTorch, TensorFlow, GCP, Spark",Master,4,Automotive,2024-04-22,2024-05-25,963,8,TechCorp Inc -AI10570,Robotics Engineer,72716,EUR,61809,EN,FL,Germany,L,Germany,100,"GCP, Python, Data Visualization, TensorFlow, Computer Vision",Bachelor,0,Transportation,2024-07-03,2024-07-27,501,7.8,Smart Analytics -AI10571,Data Scientist,126408,USD,126408,MI,FT,United States,L,Nigeria,0,"R, Python, NLP, Hadoop, Deep Learning",Master,4,Retail,2024-08-10,2024-10-13,1126,5.1,Neural Networks Co -AI10572,AI Research Scientist,116295,EUR,98851,MI,CT,Netherlands,M,Netherlands,100,"SQL, Deep Learning, PyTorch, Git, GCP",Bachelor,4,Telecommunications,2024-06-04,2024-07-25,991,7.3,Digital Transformation LLC -AI10573,AI Architect,104716,EUR,89009,MI,CT,Germany,L,New Zealand,50,"Kubernetes, Docker, Git",Master,3,Media,2025-02-07,2025-04-15,688,7.5,Advanced Robotics -AI10574,AI Product Manager,130494,JPY,14354340,MI,FT,Japan,L,Japan,0,"Kubernetes, TensorFlow, Python",Bachelor,4,Technology,2025-01-27,2025-04-06,1863,7.8,Quantum Computing Inc -AI10575,ML Ops Engineer,150085,AUD,202615,SE,CT,Australia,L,Australia,100,"AWS, Azure, Python, Java, MLOps",Master,5,Automotive,2024-05-03,2024-07-07,523,8.6,DataVision Ltd -AI10576,Deep Learning Engineer,45879,USD,45879,SE,PT,India,S,Latvia,50,"R, GCP, PyTorch, Computer Vision, Statistics",Bachelor,6,Government,2024-01-29,2024-02-25,2273,7.7,Cloud AI Solutions -AI10577,Data Scientist,108528,USD,108528,MI,CT,Denmark,L,Latvia,50,"Git, Kubernetes, Java",PhD,3,Consulting,2024-10-30,2025-01-04,1012,10,DeepTech Ventures -AI10578,Autonomous Systems Engineer,191897,EUR,163112,EX,FL,Austria,L,China,100,"R, SQL, Deep Learning",PhD,19,Automotive,2025-02-18,2025-04-19,1240,5.1,Algorithmic Solutions -AI10579,AI Software Engineer,93358,USD,93358,MI,PT,Norway,S,Norway,50,"Statistics, Kubernetes, NLP, GCP",Associate,4,Technology,2024-04-08,2024-05-16,909,6.4,Predictive Systems -AI10580,Data Engineer,31111,USD,31111,MI,CT,India,M,Argentina,100,"Spark, Kubernetes, Mathematics",PhD,3,Gaming,2024-09-21,2024-11-08,2004,5.8,Predictive Systems -AI10581,NLP Engineer,275338,AUD,371706,EX,CT,Australia,L,Australia,50,"Docker, Data Visualization, Java, Spark",PhD,19,Media,2024-06-14,2024-08-08,784,8.5,AI Innovations -AI10582,AI Consultant,147650,USD,147650,SE,FL,Ireland,L,Ireland,100,"GCP, Kubernetes, PyTorch, Scala, Deep Learning",Master,8,Automotive,2024-09-15,2024-10-03,1084,5.9,Predictive Systems -AI10583,Data Scientist,204393,GBP,153295,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, GCP, Data Visualization",Bachelor,18,Gaming,2025-01-17,2025-02-02,1818,5.9,Cognitive Computing -AI10584,Data Engineer,63051,USD,63051,EN,CT,South Korea,M,South Korea,0,"Git, Java, NLP",Master,1,Energy,2024-10-26,2024-11-24,509,6.6,Smart Analytics -AI10585,Computer Vision Engineer,68170,JPY,7498700,EN,FT,Japan,M,Singapore,0,"Kubernetes, TensorFlow, GCP",Associate,1,Telecommunications,2025-01-08,2025-03-12,2423,6.7,Future Systems -AI10586,Principal Data Scientist,63760,GBP,47820,EN,PT,United Kingdom,L,United Kingdom,0,"Python, Kubernetes, TensorFlow, Scala",Associate,0,Technology,2024-02-04,2024-03-05,1911,6.2,Future Systems -AI10587,Machine Learning Engineer,93851,USD,93851,MI,FL,United States,S,Switzerland,0,"TensorFlow, Scala, GCP, SQL",Master,3,Gaming,2025-04-23,2025-06-22,2028,8.4,Smart Analytics -AI10588,Data Scientist,125553,USD,125553,SE,PT,United States,S,United States,50,"Java, GCP, Azure",Master,6,Education,2024-10-31,2024-11-29,1036,8.1,AI Innovations -AI10589,Computer Vision Engineer,56723,CAD,70904,EN,FT,Canada,L,Canada,100,"Tableau, Python, Kubernetes, Scala",Associate,1,Gaming,2024-11-08,2024-11-25,1997,6.6,Digital Transformation LLC -AI10590,AI Product Manager,78007,USD,78007,EN,CT,United States,S,United States,50,"Azure, Spark, MLOps, Tableau",Bachelor,1,Finance,2024-03-01,2024-03-17,2122,9.3,Advanced Robotics -AI10591,Data Scientist,230768,USD,230768,EX,CT,Finland,L,Spain,50,"MLOps, Scala, TensorFlow, Mathematics",PhD,17,Media,2024-06-26,2024-07-29,1798,8.4,Cognitive Computing -AI10592,Data Scientist,61453,USD,61453,EN,CT,Israel,S,Israel,100,"Java, Python, Git",Bachelor,0,Energy,2024-07-09,2024-08-07,671,9.4,Predictive Systems -AI10593,Robotics Engineer,86143,CAD,107679,MI,PT,Canada,S,Canada,50,"Hadoop, NLP, Scala",Master,2,Manufacturing,2025-01-03,2025-03-05,1242,6.6,TechCorp Inc -AI10594,Head of AI,60433,CAD,75541,EN,FT,Canada,L,Brazil,50,"Java, Kubernetes, MLOps, Computer Vision",Associate,0,Education,2024-08-29,2024-09-21,613,5.9,Quantum Computing Inc -AI10595,AI Architect,71504,EUR,60778,MI,FL,Austria,M,Austria,50,"PyTorch, Git, Kubernetes, Deep Learning, Scala",Bachelor,2,Finance,2024-11-17,2025-01-23,1193,5.3,Autonomous Tech -AI10596,Deep Learning Engineer,141331,CAD,176664,SE,FT,Canada,M,Canada,0,"SQL, Python, GCP, Java, TensorFlow",PhD,9,Consulting,2024-08-25,2024-11-06,2124,5.7,Machine Intelligence Group -AI10597,Data Scientist,182504,JPY,20075440,SE,PT,Japan,L,Finland,100,"Spark, Tableau, Deep Learning, SQL",Associate,5,Finance,2024-09-24,2024-11-09,2236,8.1,Advanced Robotics -AI10598,Data Analyst,32356,USD,32356,MI,FT,China,S,China,50,"NLP, SQL, Scala",PhD,2,Retail,2024-06-06,2024-06-24,1316,8,Neural Networks Co -AI10599,AI Specialist,212698,AUD,287142,EX,FL,Australia,S,Australia,50,"Scala, Git, SQL",Associate,16,Gaming,2024-06-28,2024-08-26,1759,5.3,Future Systems -AI10600,AI Software Engineer,159697,EUR,135742,EX,PT,France,M,France,0,"Linux, Python, R",Bachelor,11,Media,2024-06-17,2024-08-23,2236,9.1,Predictive Systems -AI10601,Principal Data Scientist,104312,USD,104312,EN,CT,United States,L,Australia,0,"Docker, Linux, PyTorch, Data Visualization",Associate,1,Education,2024-09-07,2024-10-06,1298,7.9,Smart Analytics -AI10602,Machine Learning Researcher,80606,USD,80606,EN,FL,Sweden,M,Sweden,50,"Scala, Git, Data Visualization, Mathematics, SQL",PhD,1,Energy,2024-08-06,2024-09-03,721,6.8,Digital Transformation LLC -AI10603,AI Specialist,123309,EUR,104813,SE,FT,Germany,M,United Kingdom,0,"Java, Docker, GCP",Master,7,Media,2024-11-26,2025-01-27,1603,9.3,Future Systems -AI10604,AI Architect,278484,AUD,375953,EX,FL,Australia,L,Norway,0,"Linux, Scala, Git, Python, TensorFlow",Bachelor,14,Education,2025-04-29,2025-05-24,605,8.6,DataVision Ltd -AI10605,NLP Engineer,88219,USD,88219,MI,FT,Ireland,L,Ireland,50,"Python, Linux, Kubernetes",PhD,2,Education,2025-03-04,2025-04-25,963,9.6,Cloud AI Solutions -AI10606,ML Ops Engineer,85752,CHF,77177,EN,FL,Switzerland,S,Canada,100,"Python, TensorFlow, Git, PyTorch, NLP",Master,1,Retail,2024-04-26,2024-06-06,1245,7.8,AI Innovations -AI10607,ML Ops Engineer,152528,USD,152528,SE,FT,Sweden,M,Argentina,100,"NLP, Azure, Java",Associate,5,Healthcare,2024-11-28,2024-12-19,1606,9.8,Advanced Robotics -AI10608,Principal Data Scientist,79883,EUR,67901,MI,PT,Austria,S,Austria,0,"Python, MLOps, TensorFlow, Computer Vision, Statistics",PhD,3,Real Estate,2024-01-25,2024-03-31,635,6.9,Future Systems -AI10609,Data Analyst,71938,USD,71938,MI,PT,Israel,M,United Kingdom,100,"Azure, Spark, Scala, Mathematics, Python",Bachelor,4,Media,2025-02-15,2025-03-31,1038,5.6,Smart Analytics -AI10610,AI Architect,187859,USD,187859,EX,PT,South Korea,M,South Korea,100,"Hadoop, R, PyTorch, SQL",PhD,13,Government,2025-03-13,2025-04-30,991,8.2,TechCorp Inc -AI10611,Research Scientist,80473,USD,80473,SE,FL,South Korea,S,South Korea,100,"NLP, AWS, Java, Computer Vision, Python",Bachelor,6,Consulting,2024-04-15,2024-05-04,2365,7.2,DataVision Ltd -AI10612,Machine Learning Engineer,150968,EUR,128323,SE,FL,Germany,L,Turkey,100,"Python, Scala, TensorFlow, Deep Learning, Java",Master,8,Gaming,2024-03-14,2024-05-18,953,6,Cognitive Computing -AI10613,AI Software Engineer,117941,USD,117941,MI,CT,Finland,L,Denmark,100,"R, Spark, Data Visualization, Deep Learning, Azure",PhD,4,Energy,2024-04-10,2024-06-03,786,9.1,Autonomous Tech -AI10614,AI Software Engineer,67317,USD,67317,EN,CT,Denmark,S,Russia,50,"Docker, Spark, R, GCP",Bachelor,0,Healthcare,2024-01-02,2024-03-04,2454,7.2,AI Innovations -AI10615,Data Engineer,120964,EUR,102819,SE,PT,Netherlands,M,Luxembourg,0,"R, Java, SQL",PhD,8,Healthcare,2024-01-24,2024-02-29,1395,8.5,TechCorp Inc -AI10616,Head of AI,147747,CHF,132972,MI,CT,Switzerland,L,Switzerland,50,"Scala, Spark, Data Visualization",Master,4,Transportation,2024-03-04,2024-03-26,1292,5.9,Algorithmic Solutions -AI10617,Computer Vision Engineer,144492,AUD,195064,SE,PT,Australia,L,Australia,50,"Java, Spark, TensorFlow, Hadoop, Scala",Associate,9,Manufacturing,2025-04-06,2025-06-12,2186,5.3,Algorithmic Solutions -AI10618,Machine Learning Engineer,245526,USD,245526,EX,FT,United States,S,Israel,100,"Python, Git, Kubernetes",Bachelor,12,Manufacturing,2025-02-28,2025-03-19,1919,5.4,Autonomous Tech -AI10619,Machine Learning Researcher,118930,GBP,89198,SE,FL,United Kingdom,S,United Kingdom,100,"GCP, NLP, Hadoop, Python, Scala",Master,8,Technology,2024-02-06,2024-03-12,2485,6.4,Autonomous Tech -AI10620,Data Scientist,173914,USD,173914,SE,PT,United States,L,United States,100,"Scala, Java, NLP, PyTorch, SQL",Bachelor,9,Telecommunications,2024-01-06,2024-02-15,1015,8.9,AI Innovations -AI10621,AI Architect,46392,EUR,39433,EN,FT,Germany,S,Latvia,100,"NLP, Azure, Linux, Kubernetes, Data Visualization",PhD,1,Finance,2024-06-08,2024-06-27,2495,7.9,DeepTech Ventures -AI10622,AI Product Manager,97856,USD,97856,SE,FT,Ireland,S,Ireland,50,"Python, Scala, Spark, GCP, Linux",Bachelor,8,Gaming,2024-06-17,2024-07-05,938,9.4,DeepTech Ventures -AI10623,Machine Learning Engineer,118261,EUR,100522,SE,FT,Germany,S,Germany,0,"MLOps, Git, Kubernetes, NLP",Master,6,Energy,2024-04-25,2024-05-24,1937,8.4,AI Innovations -AI10624,Deep Learning Engineer,85135,EUR,72365,MI,PT,France,M,France,50,"Scala, Spark, Git",Bachelor,3,Technology,2024-07-10,2024-08-30,967,7.4,Cognitive Computing -AI10625,Machine Learning Researcher,178627,AUD,241146,EX,FL,Australia,L,Austria,0,"Python, Deep Learning, Tableau",Bachelor,12,Transportation,2025-02-27,2025-04-23,1070,7.9,Quantum Computing Inc -AI10626,AI Specialist,95464,USD,95464,MI,FL,Sweden,S,Germany,100,"Scala, Java, AWS",Bachelor,3,Finance,2024-12-19,2025-02-11,629,9.5,Predictive Systems -AI10627,Deep Learning Engineer,91229,AUD,123159,EN,PT,Australia,L,Australia,0,"Azure, SQL, Tableau",Associate,0,Energy,2024-08-15,2024-09-26,1126,9.2,Cloud AI Solutions -AI10628,Research Scientist,192344,USD,192344,EX,FL,Sweden,S,Sweden,100,"TensorFlow, GCP, SQL, Docker, Git",Master,14,Automotive,2024-02-19,2024-03-10,2148,9.4,Predictive Systems -AI10629,Data Analyst,47789,USD,47789,EN,CT,Israel,S,Israel,100,"SQL, Linux, PyTorch, Git",Associate,0,Finance,2025-01-05,2025-01-26,1422,6,Predictive Systems -AI10630,Machine Learning Engineer,129729,EUR,110270,SE,FT,Germany,M,Germany,50,"Docker, Linux, Spark, Python",Associate,8,Technology,2024-02-05,2024-03-31,1715,7.5,TechCorp Inc -AI10631,AI Software Engineer,72974,USD,72974,MI,FT,South Korea,S,Canada,50,"Linux, Spark, Python, NLP, TensorFlow",PhD,2,Transportation,2024-03-07,2024-04-28,2093,9.4,Advanced Robotics -AI10632,Computer Vision Engineer,140615,EUR,119523,SE,FT,France,L,France,50,"PyTorch, Computer Vision, R, Scala, AWS",Bachelor,8,Manufacturing,2025-01-30,2025-02-27,876,5.4,Autonomous Tech -AI10633,Data Engineer,111490,SGD,144937,MI,FL,Singapore,M,Singapore,0,"Python, NLP, TensorFlow",PhD,4,Retail,2024-08-30,2024-10-18,1663,6.3,Predictive Systems -AI10634,Deep Learning Engineer,61103,GBP,45827,EN,FL,United Kingdom,S,United Kingdom,50,"Spark, Docker, Python, Deep Learning",PhD,1,Media,2025-01-23,2025-02-23,1769,5.6,Algorithmic Solutions -AI10635,AI Product Manager,116733,USD,116733,EX,CT,Israel,S,Israel,100,"Azure, Scala, MLOps, Python",Master,18,Media,2025-04-25,2025-05-14,1365,6.7,Machine Intelligence Group -AI10636,AI Specialist,283444,USD,283444,EX,PT,Ireland,L,Latvia,0,"SQL, Scala, R, Docker, Deep Learning",Associate,12,Government,2025-04-11,2025-05-02,2143,7.8,AI Innovations -AI10637,AI Architect,107069,EUR,91009,MI,FT,Netherlands,M,South Korea,100,"Python, TensorFlow, GCP",Master,2,Energy,2025-03-05,2025-04-09,1179,8.7,TechCorp Inc -AI10638,AI Consultant,73972,USD,73972,EN,PT,Israel,M,Israel,100,"Docker, MLOps, Mathematics, Linux",Master,0,Media,2024-06-10,2024-07-28,1551,9.9,DataVision Ltd -AI10639,AI Product Manager,52290,JPY,5751900,EN,PT,Japan,S,Japan,0,"NLP, Azure, Mathematics",Bachelor,1,Energy,2024-07-09,2024-09-10,1815,5.8,Advanced Robotics -AI10640,AI Product Manager,204367,CAD,255459,EX,CT,Canada,M,Canada,100,"AWS, Java, Azure, TensorFlow, Linux",Bachelor,15,Healthcare,2024-10-25,2024-11-23,1798,5.2,Smart Analytics -AI10641,Autonomous Systems Engineer,91739,JPY,10091290,MI,CT,Japan,M,Japan,50,"Statistics, R, Python, MLOps, GCP",Bachelor,3,Gaming,2025-01-25,2025-03-08,902,5.1,Autonomous Tech -AI10642,AI Specialist,52164,SGD,67813,EN,PT,Singapore,S,Singapore,100,"R, GCP, Computer Vision",Master,1,Retail,2024-10-23,2024-11-22,2141,5.9,Cognitive Computing -AI10643,Data Analyst,135990,EUR,115592,SE,FL,France,L,France,0,"Tableau, Java, SQL, Azure",Associate,7,Government,2024-10-23,2024-12-17,1398,8.2,Cloud AI Solutions -AI10644,Autonomous Systems Engineer,180546,GBP,135410,SE,CT,United Kingdom,L,United Kingdom,0,"Hadoop, SQL, Spark, Kubernetes",Bachelor,9,Gaming,2025-02-18,2025-03-06,1432,8.4,TechCorp Inc -AI10645,Data Analyst,173391,EUR,147382,EX,PT,France,S,Luxembourg,100,"Java, Python, Mathematics, GCP, Linux",Associate,16,Government,2024-08-24,2024-11-02,2082,8.5,Digital Transformation LLC -AI10646,AI Consultant,131162,JPY,14427820,SE,CT,Japan,S,India,100,"GCP, Azure, Spark, Data Visualization",PhD,5,Technology,2024-05-01,2024-07-03,2200,5.5,DeepTech Ventures -AI10647,Autonomous Systems Engineer,83876,USD,83876,EN,CT,Israel,L,Israel,100,"Python, GCP, Deep Learning, TensorFlow, Data Visualization",Master,1,Consulting,2024-12-27,2025-02-21,524,9.9,DeepTech Ventures -AI10648,AI Product Manager,120528,USD,120528,SE,CT,Denmark,S,Ghana,0,"Java, Python, Linux",Bachelor,5,Consulting,2024-09-05,2024-10-28,675,8.1,Advanced Robotics -AI10649,Head of AI,20105,USD,20105,EN,PT,India,S,India,100,"Java, PyTorch, MLOps, Data Visualization, Linux",Associate,1,Energy,2025-01-08,2025-01-28,926,9.6,Autonomous Tech -AI10650,Computer Vision Engineer,99524,EUR,84595,MI,PT,Austria,M,Austria,0,"GCP, SQL, Tableau, PyTorch",Master,2,Government,2025-01-24,2025-02-08,2434,9.2,Algorithmic Solutions -AI10651,Research Scientist,97168,EUR,82593,EN,FT,Netherlands,L,Australia,0,"Python, TensorFlow, Docker, Statistics, SQL",Bachelor,1,Manufacturing,2025-02-22,2025-04-26,1604,9.4,Advanced Robotics -AI10652,Machine Learning Researcher,79501,AUD,107326,MI,PT,Australia,S,Austria,0,"R, Hadoop, AWS, Docker",Master,3,Energy,2024-05-09,2024-05-23,1453,8.1,DeepTech Ventures -AI10653,NLP Engineer,80406,GBP,60305,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Python",Associate,0,Technology,2025-02-15,2025-04-28,1482,6,DataVision Ltd -AI10654,Principal Data Scientist,179168,SGD,232918,SE,FL,Singapore,L,Singapore,50,"SQL, PyTorch, Java, GCP",Master,5,Manufacturing,2024-07-30,2024-09-23,2303,5.6,Smart Analytics -AI10655,Machine Learning Researcher,117302,USD,117302,SE,FT,United States,S,United States,50,"Docker, Deep Learning, Kubernetes, R, SQL",Bachelor,7,Finance,2025-04-07,2025-06-05,1833,8.9,Predictive Systems -AI10656,Machine Learning Researcher,24496,USD,24496,EN,CT,China,S,Netherlands,0,"Java, Computer Vision, Kubernetes",Associate,1,Telecommunications,2024-04-07,2024-06-16,1991,9.8,Advanced Robotics -AI10657,AI Consultant,136071,GBP,102053,EX,CT,United Kingdom,S,United Kingdom,100,"Python, SQL, GCP, Hadoop, Spark",Associate,16,Real Estate,2025-03-27,2025-04-18,965,7.4,Cognitive Computing -AI10658,Robotics Engineer,238120,USD,238120,EX,PT,Sweden,L,Sweden,50,"Java, Docker, Mathematics, Git, Data Visualization",Master,16,Education,2024-02-25,2024-03-13,1211,8,DeepTech Ventures -AI10659,ML Ops Engineer,156352,JPY,17198720,SE,CT,Japan,M,Belgium,100,"Java, Kubernetes, GCP, Mathematics, TensorFlow",Associate,7,Finance,2024-12-10,2025-01-30,1328,7.7,Cognitive Computing -AI10660,Computer Vision Engineer,36448,USD,36448,EN,FL,China,L,China,0,"TensorFlow, Git, Python, GCP, SQL",Master,0,Healthcare,2024-02-06,2024-04-06,501,7.3,Smart Analytics -AI10661,ML Ops Engineer,225966,USD,225966,EX,FL,South Korea,L,South Korea,50,"R, Git, Tableau",Associate,14,Media,2024-09-11,2024-11-14,661,7,Quantum Computing Inc -AI10662,AI Specialist,30284,USD,30284,MI,CT,India,M,India,0,"Hadoop, Spark, MLOps, Git, Linux",PhD,3,Healthcare,2024-09-21,2024-11-24,2167,8.6,Autonomous Tech -AI10663,Research Scientist,202712,USD,202712,EX,FL,Denmark,S,Chile,100,"GCP, Kubernetes, AWS, R, Spark",Bachelor,12,Automotive,2024-08-20,2024-10-13,1609,5.7,TechCorp Inc -AI10664,AI Research Scientist,166959,USD,166959,EX,FT,Finland,M,Canada,50,"PyTorch, AWS, Azure",Associate,10,Finance,2024-12-21,2025-02-20,850,5.5,Quantum Computing Inc -AI10665,AI Consultant,122284,EUR,103941,SE,PT,France,S,South Africa,100,"MLOps, Python, TensorFlow",PhD,6,Telecommunications,2024-09-30,2024-11-21,1211,8.9,Algorithmic Solutions -AI10666,Head of AI,116235,USD,116235,SE,CT,Ireland,S,Brazil,100,"R, Java, Tableau, MLOps",Master,8,Healthcare,2024-10-27,2024-11-16,973,8.6,Advanced Robotics -AI10667,Head of AI,202957,USD,202957,EX,PT,Sweden,M,Sweden,0,"Git, Docker, Deep Learning, TensorFlow",PhD,19,Energy,2024-08-13,2024-09-02,2052,5.2,Algorithmic Solutions -AI10668,AI Consultant,79718,JPY,8768980,MI,FT,Japan,S,Portugal,100,"Tableau, Spark, Hadoop",Master,3,Real Estate,2024-11-22,2025-01-06,1868,5.3,Cognitive Computing -AI10669,Robotics Engineer,125746,GBP,94310,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, PyTorch, Mathematics",Master,9,Real Estate,2024-02-26,2024-03-16,919,7,Neural Networks Co -AI10670,AI Specialist,154306,GBP,115730,SE,FT,United Kingdom,M,United Kingdom,0,"Docker, MLOps, PyTorch, Spark",Bachelor,9,Transportation,2024-08-31,2024-09-17,987,9.6,Cloud AI Solutions -AI10671,AI Consultant,86374,EUR,73418,MI,CT,Netherlands,M,Norway,100,"MLOps, Git, GCP",Bachelor,4,Finance,2024-10-01,2024-11-08,558,6.8,DataVision Ltd -AI10672,ML Ops Engineer,113235,USD,113235,SE,FT,Finland,M,Switzerland,0,"GCP, Mathematics, Computer Vision",Master,8,Manufacturing,2024-03-08,2024-05-01,1365,7.5,Digital Transformation LLC -AI10673,Data Analyst,266149,USD,266149,EX,FT,Denmark,S,Denmark,100,"Data Visualization, Spark, NLP, Hadoop, Deep Learning",Master,16,Telecommunications,2024-02-10,2024-03-25,595,6.4,Algorithmic Solutions -AI10674,Head of AI,77319,JPY,8505090,MI,FL,Japan,S,Japan,0,"Git, MLOps, TensorFlow, Kubernetes",PhD,3,Transportation,2024-06-20,2024-07-17,1217,7.9,Algorithmic Solutions -AI10675,Data Engineer,74543,USD,74543,MI,FT,South Korea,M,South Korea,0,"Java, Python, Tableau, Azure, Hadoop",Bachelor,4,Finance,2024-11-18,2025-01-30,1362,9.3,TechCorp Inc -AI10676,AI Specialist,51768,SGD,67298,EN,FL,Singapore,S,Singapore,100,"Docker, AWS, Kubernetes, Tableau",PhD,0,Energy,2025-04-30,2025-06-05,1526,9.2,AI Innovations -AI10677,Autonomous Systems Engineer,213531,USD,213531,EX,PT,Norway,S,Norway,50,"AWS, Data Visualization, Docker, GCP, Python",Master,18,Consulting,2024-05-30,2024-07-20,885,8.5,AI Innovations -AI10678,AI Research Scientist,195386,GBP,146540,EX,FT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, SQL, Linux",Bachelor,14,Telecommunications,2025-01-05,2025-03-05,2185,5.4,Machine Intelligence Group -AI10679,Data Engineer,91835,USD,91835,EX,CT,China,L,China,50,"Linux, Mathematics, NLP, Python",PhD,19,Gaming,2024-10-21,2024-12-01,985,6.2,Cloud AI Solutions -AI10680,AI Research Scientist,95351,EUR,81048,SE,PT,Germany,S,Germany,50,"Spark, SQL, Deep Learning, NLP",Associate,9,Healthcare,2024-08-05,2024-10-13,2260,5,DataVision Ltd -AI10681,Robotics Engineer,89630,USD,89630,MI,CT,Finland,L,Finland,0,"Deep Learning, SQL, Computer Vision",PhD,2,Government,2024-07-21,2024-08-27,1413,9.3,Future Systems -AI10682,Computer Vision Engineer,70678,EUR,60076,MI,PT,Germany,S,Germany,0,"TensorFlow, AWS, Linux, MLOps, Azure",Associate,3,Automotive,2024-04-30,2024-06-18,2104,8,DataVision Ltd -AI10683,Computer Vision Engineer,134959,JPY,14845490,SE,CT,Japan,M,Kenya,100,"GCP, Java, Linux",Bachelor,9,Finance,2024-10-29,2025-01-07,1173,6,Advanced Robotics -AI10684,Head of AI,38645,USD,38645,SE,FL,India,S,India,100,"TensorFlow, Docker, SQL, MLOps",PhD,7,Transportation,2025-01-25,2025-03-26,2358,6.5,DataVision Ltd -AI10685,Machine Learning Engineer,156721,JPY,17239310,EX,FT,Japan,M,Japan,50,"NLP, Git, Deep Learning, Python",PhD,18,Education,2024-03-30,2024-06-10,1357,7.7,Machine Intelligence Group -AI10686,Computer Vision Engineer,60173,USD,60173,EN,PT,Sweden,S,Sweden,50,"TensorFlow, Scala, Java, Statistics",Master,1,Government,2024-06-25,2024-07-26,2352,8.5,AI Innovations -AI10687,Machine Learning Researcher,61314,USD,61314,MI,FT,South Korea,S,South Korea,50,"Python, Docker, Tableau",PhD,2,Manufacturing,2024-02-18,2024-04-27,1801,9.7,Cloud AI Solutions -AI10688,Autonomous Systems Engineer,151060,USD,151060,EX,CT,Israel,S,Israel,100,"Azure, Docker, Python",Master,13,Technology,2025-03-28,2025-05-27,2382,9,Quantum Computing Inc -AI10689,Robotics Engineer,78798,SGD,102437,MI,FL,Singapore,M,Singapore,50,"Data Visualization, PyTorch, Git, Docker",Associate,2,Government,2024-10-22,2024-12-02,2429,7.9,Predictive Systems -AI10690,Principal Data Scientist,28501,USD,28501,MI,FL,India,M,India,100,"Data Visualization, TensorFlow, Python, Scala",Bachelor,3,Gaming,2024-09-26,2024-10-16,2203,7.1,Advanced Robotics -AI10691,Data Scientist,147112,USD,147112,SE,FL,Denmark,M,Denmark,0,"SQL, GCP, Java, Statistics",Associate,7,Retail,2024-02-24,2024-03-23,2407,5.9,Future Systems -AI10692,Machine Learning Engineer,57860,EUR,49181,EN,FT,Austria,L,Finland,50,"Data Visualization, Tableau, Spark, Python, Hadoop",Master,0,Transportation,2024-03-13,2024-04-01,2104,5.7,Neural Networks Co -AI10693,Autonomous Systems Engineer,124336,JPY,13676960,SE,CT,Japan,L,Norway,100,"Docker, GCP, MLOps",Bachelor,6,Transportation,2024-04-02,2024-05-23,1518,6.2,AI Innovations -AI10694,Machine Learning Researcher,52712,EUR,44805,EN,FT,France,M,France,50,"Scala, Hadoop, Statistics, Azure, PyTorch",PhD,0,Energy,2024-08-21,2024-11-01,1117,5.2,TechCorp Inc -AI10695,NLP Engineer,151816,CHF,136634,SE,FL,Switzerland,S,Switzerland,100,"R, Scala, Statistics",PhD,8,Automotive,2024-12-18,2025-02-09,680,7.8,Autonomous Tech -AI10696,Data Engineer,136528,USD,136528,EX,PT,China,L,China,0,"Kubernetes, Java, MLOps",Associate,14,Transportation,2024-05-12,2024-06-17,2317,7.3,Advanced Robotics -AI10697,AI Software Engineer,117912,EUR,100225,SE,PT,France,L,France,50,"SQL, Docker, NLP, Statistics",Bachelor,6,Finance,2025-02-02,2025-04-04,2357,8.2,Machine Intelligence Group -AI10698,AI Consultant,152584,EUR,129696,EX,FT,Austria,S,Austria,0,"PyTorch, Docker, Data Visualization, AWS",PhD,16,Technology,2024-09-16,2024-10-23,1903,6.7,Neural Networks Co -AI10699,AI Software Engineer,148386,USD,148386,MI,FL,United States,L,Kenya,50,"AWS, Python, Statistics",PhD,4,Government,2025-03-01,2025-05-06,832,9.3,Neural Networks Co -AI10700,NLP Engineer,170113,USD,170113,SE,FT,United States,M,United States,100,"Data Visualization, Azure, Java, NLP, Hadoop",PhD,5,Automotive,2024-04-09,2024-05-30,2437,9.4,Algorithmic Solutions -AI10701,Data Engineer,76774,EUR,65258,MI,FL,Germany,M,Hungary,0,"Kubernetes, Statistics, Azure, Deep Learning, SQL",Associate,4,Healthcare,2025-03-29,2025-04-20,876,8.2,DeepTech Ventures -AI10702,AI Software Engineer,104215,USD,104215,EN,FT,Norway,L,Norway,50,"PyTorch, TensorFlow, Tableau, Java, Mathematics",Master,1,Government,2024-05-17,2024-06-26,869,9,Cognitive Computing -AI10703,NLP Engineer,214317,USD,214317,EX,FL,Denmark,S,Russia,50,"Statistics, Scala, Kubernetes, GCP",Bachelor,19,Transportation,2025-04-04,2025-06-10,1517,6.9,DeepTech Ventures -AI10704,Data Scientist,134618,EUR,114425,SE,PT,Austria,M,Austria,0,"Mathematics, GCP, PyTorch, TensorFlow",Master,5,Energy,2025-03-25,2025-05-15,1450,9.9,AI Innovations -AI10705,AI Software Engineer,73195,USD,73195,EN,CT,Ireland,L,Vietnam,100,"GCP, Scala, Mathematics",Associate,1,Finance,2024-08-03,2024-10-09,1283,8,Digital Transformation LLC -AI10706,Computer Vision Engineer,116013,USD,116013,SE,PT,Sweden,S,Austria,0,"Spark, PyTorch, NLP, Java",Bachelor,6,Gaming,2024-02-09,2024-03-20,2305,9.4,TechCorp Inc -AI10707,AI Specialist,129732,JPY,14270520,SE,PT,Japan,L,Japan,50,"Computer Vision, Deep Learning, Linux",Master,8,Real Estate,2024-06-01,2024-06-15,2326,6,Cloud AI Solutions -AI10708,AI Specialist,250954,GBP,188216,EX,FT,United Kingdom,L,United Kingdom,100,"Scala, MLOps, Linux, Kubernetes",Master,19,Media,2025-04-23,2025-05-11,1862,5.9,Autonomous Tech -AI10709,Data Scientist,64591,CAD,80739,EN,CT,Canada,L,Canada,100,"Azure, Scala, R",Bachelor,1,Retail,2024-01-21,2024-02-15,2126,9,Autonomous Tech -AI10710,Data Engineer,117699,USD,117699,SE,FT,Ireland,M,Ireland,100,"Docker, Python, SQL",Associate,7,Retail,2024-08-08,2024-10-07,1819,9.9,Future Systems -AI10711,NLP Engineer,111868,USD,111868,EX,FT,China,L,China,50,"Linux, Git, R, Docker",Master,13,Gaming,2024-06-05,2024-07-18,1727,5.4,Autonomous Tech -AI10712,Research Scientist,143592,USD,143592,SE,PT,United States,S,United States,50,"Computer Vision, Hadoop, Tableau",PhD,5,Finance,2024-01-10,2024-03-23,2454,7.9,Autonomous Tech -AI10713,AI Specialist,112805,EUR,95884,MI,FL,Austria,L,Austria,100,"Python, Hadoop, AWS, Statistics",PhD,4,Education,2024-01-04,2024-01-30,2148,8.7,TechCorp Inc -AI10714,AI Architect,161399,USD,161399,EX,FT,Israel,L,Israel,0,"Java, NLP, SQL",PhD,10,Manufacturing,2024-09-19,2024-11-24,1789,7.8,Autonomous Tech -AI10715,AI Architect,243356,USD,243356,EX,FL,Norway,S,Norway,0,"NLP, Scala, R",Master,14,Transportation,2024-05-12,2024-06-12,1489,5.6,Cognitive Computing -AI10716,Principal Data Scientist,91224,USD,91224,MI,CT,Israel,L,Canada,50,"PyTorch, GCP, AWS",Bachelor,2,Manufacturing,2024-07-30,2024-10-10,1336,8.1,Neural Networks Co -AI10717,Data Engineer,42308,USD,42308,MI,FL,China,M,China,50,"Java, SQL, Docker",PhD,2,Gaming,2024-11-19,2025-01-08,764,7.9,AI Innovations -AI10718,AI Research Scientist,44344,USD,44344,MI,PT,China,L,China,100,"Scala, Mathematics, Deep Learning, Data Visualization, PyTorch",Associate,2,Transportation,2025-01-27,2025-03-06,1050,7.7,Quantum Computing Inc -AI10719,AI Consultant,176796,EUR,150277,EX,FT,France,M,France,50,"Python, Docker, Deep Learning, TensorFlow, NLP",Associate,12,Manufacturing,2024-02-26,2024-04-14,1400,9.1,Neural Networks Co -AI10720,Data Analyst,128958,JPY,14185380,SE,CT,Japan,L,Ireland,100,"Python, Git, Docker, Mathematics, Tableau",PhD,5,Retail,2024-06-05,2024-07-24,1906,5.9,Predictive Systems -AI10721,AI Research Scientist,38734,USD,38734,SE,CT,India,S,India,50,"Azure, MLOps, Statistics, Docker",PhD,9,Retail,2024-09-11,2024-09-25,698,9.4,AI Innovations -AI10722,Robotics Engineer,139670,GBP,104753,SE,CT,United Kingdom,M,Canada,0,"Python, Scala, MLOps, AWS",PhD,6,Media,2024-06-22,2024-07-07,1717,6.3,Algorithmic Solutions -AI10723,Principal Data Scientist,151422,EUR,128709,EX,CT,Germany,S,Germany,0,"PyTorch, TensorFlow, R, Linux, Mathematics",PhD,14,Automotive,2025-02-08,2025-03-20,590,7.3,Digital Transformation LLC -AI10724,Computer Vision Engineer,59521,EUR,50593,EN,CT,Netherlands,S,Netherlands,50,"Scala, R, NLP, MLOps",Bachelor,0,Real Estate,2024-09-08,2024-09-26,1095,7.3,DeepTech Ventures -AI10725,ML Ops Engineer,71064,USD,71064,MI,FT,South Korea,M,South Korea,50,"Java, Python, R, Mathematics, PyTorch",PhD,2,Consulting,2024-06-22,2024-08-18,1716,8.6,Future Systems -AI10726,Data Scientist,226728,EUR,192719,EX,CT,France,L,France,100,"Java, MLOps, TensorFlow, Computer Vision",Associate,16,Transportation,2024-06-02,2024-06-18,971,7.2,Cognitive Computing -AI10727,Machine Learning Researcher,112137,CAD,140171,MI,FL,Canada,L,Canada,50,"TensorFlow, Linux, Computer Vision, Git, Java",Associate,4,Retail,2025-04-21,2025-05-21,2367,7.8,AI Innovations -AI10728,Machine Learning Engineer,127819,CAD,159774,SE,CT,Canada,L,Germany,100,"Python, SQL, Scala, Computer Vision",PhD,5,Healthcare,2025-04-05,2025-05-31,2077,9.2,DataVision Ltd -AI10729,Data Analyst,96910,JPY,10660100,MI,FL,Japan,M,Japan,0,"SQL, AWS, GCP",Associate,2,Consulting,2024-02-23,2024-04-02,1569,7.9,Machine Intelligence Group -AI10730,Autonomous Systems Engineer,80604,USD,80604,EX,CT,India,L,Singapore,50,"Python, Mathematics, Tableau",Associate,11,Media,2024-04-19,2024-06-17,897,5.4,DataVision Ltd -AI10731,Head of AI,104712,USD,104712,SE,CT,Ireland,S,Argentina,0,"Kubernetes, Python, AWS, Deep Learning",PhD,9,Real Estate,2024-12-10,2024-12-31,643,6.7,Neural Networks Co -AI10732,Data Engineer,76848,CAD,96060,MI,FT,Canada,M,Canada,0,"Kubernetes, Tableau, Hadoop",Bachelor,4,Energy,2024-09-23,2024-11-14,1993,7.5,Cognitive Computing -AI10733,Deep Learning Engineer,155320,AUD,209682,EX,CT,Australia,M,Australia,0,"SQL, Scala, Computer Vision, Tableau, Linux",Master,14,Government,2025-01-05,2025-02-21,1624,6.7,DataVision Ltd -AI10734,AI Consultant,197617,GBP,148213,EX,PT,United Kingdom,S,United Kingdom,50,"AWS, PyTorch, Deep Learning",Associate,18,Finance,2024-11-11,2024-12-24,1858,7.2,Future Systems -AI10735,AI Research Scientist,49891,EUR,42407,EN,FT,Netherlands,S,Netherlands,0,"NLP, R, Computer Vision, Azure",Associate,0,Media,2024-03-30,2024-05-03,1695,9.3,DataVision Ltd -AI10736,Principal Data Scientist,117730,EUR,100071,SE,FL,Germany,L,Germany,0,"AWS, MLOps, Mathematics, Tableau",Master,5,Automotive,2024-12-21,2025-02-13,1009,5.6,Cognitive Computing -AI10737,AI Architect,115851,USD,115851,SE,PT,South Korea,M,South Korea,100,"Git, Python, Kubernetes, Statistics, Data Visualization",Associate,8,Media,2024-10-08,2024-11-09,990,7,Cloud AI Solutions -AI10738,Machine Learning Engineer,73670,CAD,92088,EN,CT,Canada,M,Egypt,100,"Linux, PyTorch, SQL, Java, Statistics",Associate,0,Government,2024-09-01,2024-10-17,1315,7.8,Predictive Systems -AI10739,AI Software Engineer,214568,CHF,193111,SE,FL,Switzerland,M,Switzerland,50,"AWS, Linux, Computer Vision",Master,7,Retail,2024-08-10,2024-09-15,937,6.8,Algorithmic Solutions -AI10740,AI Architect,258181,USD,258181,EX,CT,United States,L,Mexico,0,"MLOps, Spark, Data Visualization, GCP, Computer Vision",PhD,19,Retail,2024-05-24,2024-07-22,1825,7.1,AI Innovations -AI10741,Deep Learning Engineer,39478,USD,39478,EN,FL,South Korea,S,South Korea,50,"Git, Deep Learning, Spark, Java",Master,0,Automotive,2024-07-01,2024-08-10,922,7.9,DataVision Ltd -AI10742,Robotics Engineer,54274,USD,54274,MI,FT,China,L,China,0,"R, Java, AWS",Master,4,Manufacturing,2024-06-25,2024-07-15,723,7.2,Machine Intelligence Group -AI10743,Data Analyst,48788,USD,48788,SE,FT,China,S,China,0,"SQL, Deep Learning, Java, Computer Vision",Master,5,Healthcare,2025-01-09,2025-01-31,1444,7.1,Algorithmic Solutions -AI10744,NLP Engineer,232286,CHF,209057,SE,PT,Switzerland,L,Switzerland,50,"AWS, Python, GCP",Associate,8,Healthcare,2024-08-26,2024-09-19,637,9.9,Neural Networks Co -AI10745,AI Specialist,251960,USD,251960,EX,FT,United States,S,United States,100,"SQL, Scala, Python, MLOps, R",Master,13,Gaming,2024-04-11,2024-06-03,2323,6.1,Digital Transformation LLC -AI10746,Data Engineer,100923,CHF,90831,MI,FL,Switzerland,S,Malaysia,100,"Kubernetes, Scala, Azure, TensorFlow, SQL",Master,4,Healthcare,2024-07-01,2024-09-09,2073,5.9,Cognitive Computing -AI10747,Robotics Engineer,101479,AUD,136997,MI,CT,Australia,M,Australia,100,"Spark, Git, Computer Vision, AWS",PhD,4,Government,2025-04-16,2025-06-08,867,5.2,Quantum Computing Inc -AI10748,AI Software Engineer,238738,USD,238738,EX,FT,Israel,L,Israel,50,"Python, TensorFlow, Tableau",Associate,18,Retail,2024-09-22,2024-11-14,851,6.6,TechCorp Inc -AI10749,ML Ops Engineer,63999,EUR,54399,EN,CT,Netherlands,L,Kenya,100,"SQL, Python, Kubernetes, Data Visualization",Associate,0,Media,2024-11-25,2025-01-13,2084,7.3,Algorithmic Solutions -AI10750,Deep Learning Engineer,89374,USD,89374,MI,PT,Ireland,M,Ireland,0,"SQL, Spark, Scala, Python, Data Visualization",Master,4,Gaming,2025-04-20,2025-05-06,2047,9.6,AI Innovations -AI10751,NLP Engineer,71485,USD,71485,MI,FL,Sweden,S,France,50,"R, Scala, Data Visualization",Bachelor,4,Gaming,2024-08-21,2024-09-14,979,7.1,AI Innovations -AI10752,AI Software Engineer,173599,CAD,216999,EX,FL,Canada,M,Canada,50,"Deep Learning, SQL, PyTorch",PhD,13,Media,2025-04-16,2025-06-19,876,8.2,Cognitive Computing -AI10753,AI Product Manager,44067,USD,44067,EX,FT,India,S,India,50,"Statistics, NLP, Hadoop, Linux, Deep Learning",Bachelor,11,Consulting,2024-08-13,2024-09-30,778,9.1,Cloud AI Solutions -AI10754,AI Software Engineer,103357,EUR,87853,MI,FT,Netherlands,L,Netherlands,100,"AWS, Linux, Mathematics",PhD,3,Education,2024-08-11,2024-08-31,600,8.9,DataVision Ltd -AI10755,Data Scientist,95805,EUR,81434,MI,FL,Netherlands,M,Netherlands,50,"Linux, Hadoop, Deep Learning",PhD,2,Energy,2025-04-17,2025-06-13,2304,5,Machine Intelligence Group -AI10756,Data Scientist,286492,USD,286492,EX,FT,Norway,M,Norway,0,"R, NLP, Python, Docker",Bachelor,10,Energy,2024-06-02,2024-06-22,746,8.7,Machine Intelligence Group -AI10757,Head of AI,64481,EUR,54809,EN,FL,France,S,Italy,50,"Spark, Linux, Deep Learning, MLOps, PyTorch",Master,0,Energy,2024-03-15,2024-05-16,2443,8.7,Cloud AI Solutions -AI10758,Autonomous Systems Engineer,206801,USD,206801,EX,CT,Israel,M,Israel,100,"NLP, AWS, Scala, Azure, Python",Bachelor,18,Gaming,2024-04-28,2024-06-10,747,8.5,Autonomous Tech -AI10759,AI Specialist,161515,JPY,17766650,SE,FT,Japan,M,Canada,100,"Data Visualization, R, Scala, MLOps",Bachelor,5,Media,2024-03-20,2024-05-15,1508,9.6,Cognitive Computing -AI10760,Machine Learning Engineer,129002,USD,129002,EX,FL,Israel,S,Israel,100,"Statistics, R, Git",PhD,13,Retail,2024-09-03,2024-09-20,1993,7.1,AI Innovations -AI10761,Computer Vision Engineer,77898,CAD,97373,MI,FL,Canada,M,Canada,100,"Azure, Spark, Scala, Java, Git",Associate,2,Automotive,2024-06-21,2024-07-22,984,7.4,Quantum Computing Inc -AI10762,Data Engineer,117229,EUR,99645,SE,FL,Netherlands,S,Norway,100,"Spark, Mathematics, Linux",Master,9,Automotive,2025-04-13,2025-05-18,1881,8.1,Autonomous Tech -AI10763,Machine Learning Researcher,81371,EUR,69165,MI,FL,Netherlands,S,Netherlands,0,"SQL, R, Java, Kubernetes, Git",Associate,3,Manufacturing,2024-01-28,2024-03-02,1429,8.7,Algorithmic Solutions -AI10764,Data Engineer,72322,USD,72322,EN,PT,South Korea,L,South Korea,0,"MLOps, Azure, Python",Bachelor,1,Automotive,2024-09-06,2024-11-18,2024,7.9,Cloud AI Solutions -AI10765,ML Ops Engineer,94388,USD,94388,EX,FT,India,L,India,0,"Azure, SQL, Spark, Statistics, R",Master,12,Media,2024-06-24,2024-08-24,1661,7.3,Advanced Robotics -AI10766,ML Ops Engineer,202122,USD,202122,EX,CT,Denmark,M,Australia,50,"GCP, R, Git, TensorFlow",PhD,16,Energy,2024-09-23,2024-12-01,1479,9.8,Smart Analytics -AI10767,AI Software Engineer,86254,CAD,107818,MI,FL,Canada,L,Canada,50,"TensorFlow, NLP, Linux",PhD,4,Government,2025-04-06,2025-06-05,2494,9.7,Quantum Computing Inc -AI10768,Machine Learning Researcher,83507,SGD,108559,MI,CT,Singapore,S,Singapore,100,"Tableau, Computer Vision, GCP",Bachelor,2,Education,2024-08-19,2024-10-16,2354,6.4,Quantum Computing Inc -AI10769,Research Scientist,173027,EUR,147073,SE,CT,Germany,L,Brazil,100,"Tableau, Git, Hadoop, Spark, PyTorch",PhD,8,Education,2024-12-05,2024-12-21,690,5.5,Advanced Robotics -AI10770,Data Engineer,116393,EUR,98934,SE,FT,Germany,M,Germany,100,"MLOps, Scala, Azure, GCP, Kubernetes",Associate,8,Finance,2024-08-03,2024-09-12,2354,6.9,Cloud AI Solutions -AI10771,AI Software Engineer,99131,CHF,89218,MI,PT,Switzerland,S,Switzerland,100,"Kubernetes, Docker, Tableau, Hadoop, Java",Associate,3,Government,2024-05-07,2024-06-19,2068,6.1,Digital Transformation LLC -AI10772,Autonomous Systems Engineer,50959,USD,50959,EN,PT,Israel,M,Israel,100,"Hadoop, Kubernetes, SQL, Java, R",Bachelor,0,Consulting,2024-04-29,2024-06-16,2134,8.9,AI Innovations -AI10773,Data Analyst,107661,USD,107661,MI,CT,Denmark,S,Denmark,100,"Docker, Hadoop, Kubernetes, Python",Master,2,Finance,2025-01-03,2025-03-15,922,7.6,Cognitive Computing -AI10774,AI Specialist,174458,EUR,148289,EX,CT,Netherlands,M,Netherlands,100,"Python, Git, Kubernetes, Tableau",Bachelor,15,Media,2024-10-04,2024-11-05,1151,9,DataVision Ltd -AI10775,AI Specialist,126182,SGD,164037,SE,FT,Singapore,L,Singapore,0,"Linux, Python, Java, Git",PhD,7,Gaming,2024-03-23,2024-06-04,2236,9.7,Machine Intelligence Group -AI10776,Computer Vision Engineer,293038,CHF,263734,EX,CT,Switzerland,L,Switzerland,100,"Python, TensorFlow, R, Java, Computer Vision",PhD,13,Education,2024-05-12,2024-07-04,872,7.7,Future Systems -AI10777,AI Consultant,171137,EUR,145466,EX,CT,Austria,L,Austria,0,"Statistics, Linux, Scala",PhD,19,Gaming,2024-09-18,2024-10-26,1784,8.5,Smart Analytics -AI10778,AI Architect,106675,CHF,96008,MI,FT,Switzerland,S,Switzerland,0,"MLOps, Git, Deep Learning, Mathematics",PhD,3,Energy,2025-01-19,2025-03-01,1725,8.7,Quantum Computing Inc -AI10779,ML Ops Engineer,266812,USD,266812,EX,CT,Denmark,S,Denmark,100,"Python, NLP, Mathematics, TensorFlow",Bachelor,11,Retail,2024-09-23,2024-12-03,675,5.9,AI Innovations -AI10780,Data Scientist,85605,USD,85605,MI,FT,Finland,M,Estonia,100,"Kubernetes, Python, Computer Vision",Associate,3,Healthcare,2024-04-30,2024-06-10,2427,7.2,Smart Analytics -AI10781,NLP Engineer,201964,USD,201964,EX,CT,Israel,L,Czech Republic,0,"Scala, Python, Kubernetes, Computer Vision, SQL",Bachelor,13,Government,2024-01-29,2024-02-22,1295,7,Smart Analytics -AI10782,AI Specialist,137083,USD,137083,SE,FT,Israel,L,Israel,50,"AWS, Hadoop, Python, Scala, Spark",Bachelor,8,Gaming,2025-04-28,2025-05-18,1859,9,Neural Networks Co -AI10783,Data Analyst,75000,EUR,63750,EN,FL,Netherlands,S,Mexico,100,"R, Hadoop, Deep Learning, Java",Master,0,Finance,2024-02-24,2024-03-16,1353,7.8,AI Innovations -AI10784,Principal Data Scientist,200686,USD,200686,EX,CT,Sweden,L,Sweden,0,"Tableau, Python, NLP, TensorFlow, Scala",Associate,16,Telecommunications,2024-11-02,2024-12-31,1499,9.9,Predictive Systems -AI10785,Principal Data Scientist,129291,JPY,14222010,SE,FL,Japan,L,Japan,50,"R, Computer Vision, Azure, GCP",Associate,8,Transportation,2024-10-01,2024-10-19,1209,6.7,DeepTech Ventures -AI10786,Data Engineer,86101,EUR,73186,MI,PT,France,S,France,50,"SQL, Scala, Hadoop",PhD,4,Gaming,2024-02-20,2024-04-17,1586,5.3,Digital Transformation LLC -AI10787,AI Architect,61948,USD,61948,EN,PT,Sweden,L,Sweden,100,"SQL, PyTorch, Java, Azure",Associate,0,Education,2025-03-18,2025-05-18,1004,9.5,DeepTech Ventures -AI10788,Machine Learning Researcher,53377,USD,53377,MI,PT,China,L,China,0,"Python, Java, TensorFlow",Associate,2,Consulting,2025-01-16,2025-03-02,633,6.6,Digital Transformation LLC -AI10789,Robotics Engineer,125096,CHF,112586,MI,PT,Switzerland,S,Brazil,50,"Kubernetes, Git, Data Visualization, Python, Linux",Bachelor,3,Education,2025-01-05,2025-02-12,567,5.3,Future Systems -AI10790,AI Specialist,303813,CHF,273432,EX,FT,Switzerland,S,Switzerland,100,"SQL, Tableau, NLP, PyTorch, Mathematics",Associate,14,Government,2024-09-14,2024-09-28,1178,8.9,Quantum Computing Inc -AI10791,Machine Learning Researcher,52898,USD,52898,EN,CT,South Korea,M,South Korea,0,"Tableau, Kubernetes, Computer Vision",Bachelor,0,Healthcare,2024-11-19,2024-12-27,1927,6.2,DeepTech Ventures -AI10792,Data Scientist,91033,JPY,10013630,MI,PT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization",PhD,3,Energy,2024-07-25,2024-09-30,1290,6.4,Quantum Computing Inc -AI10793,AI Architect,87585,USD,87585,EN,FL,United States,L,United States,100,"Hadoop, NLP, Linux, GCP, SQL",Bachelor,0,Energy,2025-02-01,2025-04-12,2491,6.7,AI Innovations -AI10794,AI Architect,136182,GBP,102137,SE,FT,United Kingdom,S,United Kingdom,100,"Computer Vision, NLP, Tableau, GCP",Bachelor,9,Automotive,2024-10-18,2024-11-20,1243,5.5,Quantum Computing Inc -AI10795,Data Engineer,132993,EUR,113044,SE,FT,Germany,M,Nigeria,100,"Python, TensorFlow, PyTorch, Spark, Kubernetes",Bachelor,7,Retail,2024-10-21,2024-11-06,2207,5.7,Digital Transformation LLC -AI10796,Autonomous Systems Engineer,165196,EUR,140417,EX,FT,Austria,S,Austria,100,"Python, TensorFlow, Kubernetes, Spark, AWS",Master,13,Education,2024-01-18,2024-02-19,551,9.2,Neural Networks Co -AI10797,AI Research Scientist,171750,GBP,128813,SE,CT,United Kingdom,L,United Kingdom,0,"Spark, NLP, Kubernetes, Data Visualization, Computer Vision",Master,5,Real Estate,2024-02-01,2024-04-04,1748,6.4,Smart Analytics -AI10798,AI Research Scientist,117335,EUR,99735,SE,FT,France,M,France,100,"Linux, GCP, Spark, MLOps",Associate,7,Real Estate,2024-05-23,2024-06-19,1923,8,Neural Networks Co -AI10799,Data Scientist,137278,GBP,102959,SE,PT,United Kingdom,S,United Kingdom,0,"R, SQL, Java, Kubernetes",Bachelor,9,Gaming,2025-01-19,2025-03-29,1473,6.4,Quantum Computing Inc -AI10800,Machine Learning Engineer,147147,USD,147147,EX,CT,Sweden,M,Sweden,100,"TensorFlow, Hadoop, Tableau, Docker, GCP",Master,14,Consulting,2024-08-29,2024-10-19,1580,7.2,Machine Intelligence Group -AI10801,Data Engineer,71205,EUR,60524,MI,FT,Austria,M,China,100,"NLP, SQL, PyTorch",Master,3,Retail,2024-07-10,2024-09-12,1566,8,Smart Analytics -AI10802,Machine Learning Researcher,134161,CAD,167701,SE,PT,Canada,M,Canada,0,"Linux, Hadoop, Kubernetes, Python",Master,6,Automotive,2024-12-15,2025-01-31,2485,5.4,Algorithmic Solutions -AI10803,Autonomous Systems Engineer,82237,USD,82237,MI,PT,Sweden,S,Australia,50,"Python, TensorFlow, Statistics",PhD,4,Retail,2024-10-19,2024-11-27,1074,5.8,Predictive Systems -AI10804,Autonomous Systems Engineer,38622,USD,38622,MI,FT,India,M,India,100,"Git, Linux, AWS, TensorFlow",Associate,3,Technology,2024-05-02,2024-05-22,2055,6.7,Cloud AI Solutions -AI10805,Robotics Engineer,55769,USD,55769,EN,FL,Sweden,M,India,100,"Scala, NLP, Computer Vision",Master,1,Retail,2024-12-22,2025-02-05,2420,7.4,TechCorp Inc -AI10806,ML Ops Engineer,67249,CHF,60524,EN,FL,Switzerland,S,Switzerland,100,"Scala, Java, Deep Learning",Associate,0,Automotive,2024-02-29,2024-04-04,523,7.5,Cloud AI Solutions -AI10807,AI Specialist,42394,USD,42394,MI,CT,China,M,China,0,"MLOps, Kubernetes, Git",Associate,3,Consulting,2024-08-17,2024-09-15,2406,7.8,AI Innovations -AI10808,AI Product Manager,22136,USD,22136,EN,FL,China,S,China,100,"SQL, Mathematics, Tableau, MLOps",Bachelor,1,Consulting,2024-11-10,2025-01-08,1809,8.3,Machine Intelligence Group -AI10809,Computer Vision Engineer,134580,SGD,174954,SE,CT,Singapore,S,Turkey,0,"MLOps, Computer Vision, Python, TensorFlow, Git",Associate,7,Retail,2024-12-27,2025-03-06,1655,6.9,Machine Intelligence Group -AI10810,AI Architect,65961,CAD,82451,EN,CT,Canada,M,Canada,0,"GCP, Spark, Scala, Kubernetes",PhD,1,Education,2024-12-29,2025-03-01,1771,6.4,Neural Networks Co -AI10811,AI Product Manager,117629,USD,117629,MI,CT,Norway,M,Norway,0,"Python, Deep Learning, Computer Vision, R",Associate,4,Transportation,2024-02-08,2024-02-22,795,8.7,Future Systems -AI10812,Machine Learning Researcher,87716,EUR,74559,MI,FT,Germany,S,Finland,50,"Linux, Mathematics, GCP",PhD,3,Energy,2025-01-27,2025-03-06,986,9.1,DeepTech Ventures -AI10813,AI Research Scientist,18861,USD,18861,EN,CT,India,M,India,50,"R, Linux, SQL",Bachelor,0,Manufacturing,2025-04-07,2025-06-04,1425,7.6,Autonomous Tech -AI10814,Robotics Engineer,122512,USD,122512,MI,FT,Norway,M,Norway,0,"PyTorch, R, Linux, Hadoop",Bachelor,2,Consulting,2024-10-09,2024-10-26,2292,6.8,Autonomous Tech -AI10815,Deep Learning Engineer,180159,CAD,225199,EX,FT,Canada,L,Canada,50,"Statistics, Azure, Python, Tableau, Scala",PhD,16,Manufacturing,2024-12-09,2025-01-12,2370,5.4,Neural Networks Co -AI10816,AI Architect,168620,EUR,143327,EX,CT,Austria,L,Austria,100,"Git, PyTorch, NLP, GCP",PhD,15,Real Estate,2025-03-21,2025-05-17,658,6.1,Cloud AI Solutions -AI10817,NLP Engineer,72274,USD,72274,SE,FT,China,L,China,0,"Mathematics, Computer Vision, Statistics, SQL, Spark",PhD,5,Telecommunications,2025-04-12,2025-05-03,1316,6.9,Future Systems -AI10818,Autonomous Systems Engineer,67126,USD,67126,EN,CT,Israel,L,Israel,100,"Mathematics, Kubernetes, Azure, Java",Associate,1,Manufacturing,2024-10-13,2024-12-03,2387,6.5,Advanced Robotics -AI10819,NLP Engineer,94449,EUR,80282,MI,PT,France,L,France,50,"Azure, Scala, Linux",PhD,4,Gaming,2024-06-15,2024-08-26,2175,7.3,Autonomous Tech -AI10820,Machine Learning Engineer,112859,EUR,95930,SE,PT,France,L,France,50,"NLP, SQL, PyTorch, Data Visualization",Master,5,Energy,2024-06-22,2024-08-28,2162,8.8,Advanced Robotics -AI10821,Data Engineer,144547,SGD,187911,SE,FT,Singapore,M,Switzerland,0,"NLP, SQL, PyTorch, AWS",PhD,6,Manufacturing,2024-07-15,2024-09-15,1374,7.1,Digital Transformation LLC -AI10822,Machine Learning Researcher,80627,EUR,68533,MI,FL,Austria,M,Austria,100,"Scala, Python, Docker, Kubernetes, TensorFlow",PhD,3,Education,2024-07-23,2024-08-25,2061,6.9,DataVision Ltd -AI10823,Deep Learning Engineer,151439,EUR,128723,EX,FT,Austria,L,Austria,50,"TensorFlow, Azure, Java, Docker, Git",PhD,11,Education,2024-09-13,2024-11-11,782,9.8,Machine Intelligence Group -AI10824,ML Ops Engineer,43069,USD,43069,MI,FT,China,M,China,50,"PyTorch, Spark, SQL, GCP, AWS",Bachelor,4,Technology,2024-01-03,2024-02-16,2356,6.4,Cognitive Computing -AI10825,AI Specialist,137861,USD,137861,EX,CT,Finland,M,China,0,"NLP, Scala, SQL, PyTorch",PhD,14,Government,2024-11-04,2025-01-13,703,9,Quantum Computing Inc -AI10826,AI Product Manager,192829,USD,192829,EX,CT,Denmark,S,Denmark,0,"Java, Mathematics, Git",Bachelor,10,Real Estate,2024-08-11,2024-09-17,971,7.4,AI Innovations -AI10827,AI Specialist,108163,EUR,91939,SE,FT,Austria,M,Austria,0,"Computer Vision, Linux, PyTorch, SQL, TensorFlow",Associate,7,Gaming,2024-09-16,2024-10-10,1127,7.5,Cognitive Computing -AI10828,ML Ops Engineer,65216,EUR,55434,MI,PT,Austria,S,Colombia,50,"SQL, Linux, Azure, NLP, Git",Master,3,Education,2024-01-08,2024-02-14,2280,9.4,Future Systems -AI10829,Machine Learning Researcher,80149,CAD,100186,MI,PT,Canada,M,Canada,0,"Python, Data Visualization, Docker, Hadoop",PhD,4,Retail,2025-03-26,2025-06-05,1233,5.3,TechCorp Inc -AI10830,ML Ops Engineer,205835,SGD,267586,EX,FT,Singapore,S,Singapore,50,"TensorFlow, Git, Hadoop",Master,12,Technology,2025-04-23,2025-06-15,2294,9.8,Autonomous Tech -AI10831,Head of AI,105584,USD,105584,EN,FT,Norway,L,Norway,100,"Git, Computer Vision, Python",Bachelor,0,Finance,2024-10-21,2024-12-10,2375,8.7,Neural Networks Co -AI10832,Data Scientist,134679,USD,134679,SE,FT,South Korea,L,South Korea,100,"Spark, Data Visualization, Deep Learning, NLP, Scala",PhD,7,Transportation,2025-04-12,2025-05-02,1266,6.8,Future Systems -AI10833,Data Analyst,63653,GBP,47740,EN,FT,United Kingdom,M,China,50,"Scala, Deep Learning, NLP, PyTorch",PhD,0,Government,2024-10-06,2024-11-21,1421,7.2,Digital Transformation LLC -AI10834,AI Architect,116733,EUR,99223,MI,FT,Germany,L,Germany,100,"Hadoop, SQL, Python",Associate,3,Real Estate,2025-04-13,2025-06-15,1457,5.1,Digital Transformation LLC -AI10835,Computer Vision Engineer,171496,USD,171496,EX,FL,Norway,S,Norway,50,"Mathematics, TensorFlow, Statistics, Linux, GCP",Master,18,Finance,2024-04-22,2024-06-09,897,9.1,Quantum Computing Inc -AI10836,Machine Learning Engineer,179259,SGD,233037,EX,FT,Singapore,L,Singapore,0,"PyTorch, Java, R, Statistics, Linux",Associate,16,Technology,2024-03-23,2024-05-04,1256,7.5,Cognitive Computing -AI10837,Data Scientist,222335,USD,222335,SE,FL,Denmark,L,Denmark,0,"PyTorch, AWS, NLP, Linux",Bachelor,8,Telecommunications,2024-11-25,2024-12-14,2295,6.2,Predictive Systems -AI10838,Head of AI,182726,USD,182726,EX,CT,Norway,M,Norway,0,"TensorFlow, Hadoop, PyTorch, Data Visualization, Spark",Bachelor,17,Telecommunications,2024-06-04,2024-07-28,2321,9.9,DeepTech Ventures -AI10839,Data Scientist,59545,USD,59545,SE,CT,China,L,China,100,"R, NLP, Kubernetes, Python, Docker",PhD,5,Education,2024-12-10,2025-01-26,1221,8.6,Algorithmic Solutions -AI10840,Autonomous Systems Engineer,159516,USD,159516,MI,CT,Norway,L,Philippines,0,"Hadoop, Kubernetes, Docker",Associate,3,Gaming,2024-03-30,2024-05-29,1823,7,Machine Intelligence Group -AI10841,Robotics Engineer,61743,USD,61743,EN,CT,Ireland,S,Ireland,0,"NLP, Azure, Spark, Deep Learning, GCP",PhD,1,Education,2024-10-04,2024-12-10,1963,6.5,Quantum Computing Inc -AI10842,Head of AI,68105,USD,68105,MI,FT,Finland,M,Ireland,50,"Python, Docker, Azure",Master,2,Retail,2025-01-08,2025-03-17,1930,6.6,Digital Transformation LLC -AI10843,Data Scientist,199352,EUR,169449,EX,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure, PyTorch",Associate,11,Real Estate,2024-06-17,2024-07-25,621,5.7,Algorithmic Solutions -AI10844,AI Specialist,177487,USD,177487,EX,CT,Denmark,M,Denmark,0,"Scala, Kubernetes, R",Bachelor,10,Manufacturing,2025-04-03,2025-06-14,878,8.6,Digital Transformation LLC -AI10845,Robotics Engineer,62199,EUR,52869,EN,CT,Germany,S,Russia,50,"Data Visualization, Python, Deep Learning, Computer Vision",Bachelor,0,Retail,2025-02-26,2025-05-02,1586,5.9,DataVision Ltd -AI10846,Head of AI,89631,USD,89631,EN,FL,Ireland,L,Ireland,0,"Git, R, Tableau, PyTorch",Associate,1,Education,2025-02-13,2025-04-16,1377,6.1,DataVision Ltd -AI10847,Data Engineer,73376,CAD,91720,MI,PT,Canada,S,Canada,100,"R, PyTorch, NLP",Associate,4,Media,2024-03-22,2024-05-16,1147,5.2,DeepTech Ventures -AI10848,Research Scientist,94533,USD,94533,MI,FT,Denmark,S,Denmark,50,"Linux, Scala, TensorFlow, Data Visualization, Python",Master,2,Finance,2024-01-12,2024-02-16,1115,8.8,Predictive Systems -AI10849,AI Software Engineer,193687,EUR,164634,EX,PT,Austria,M,Austria,100,"AWS, Scala, R, Tableau",Master,18,Retail,2024-04-19,2024-06-20,901,9.5,Smart Analytics -AI10850,Robotics Engineer,53931,USD,53931,SE,FL,India,L,Kenya,0,"MLOps, Python, Data Visualization, Azure",Associate,9,Retail,2024-12-30,2025-01-21,2014,8.9,TechCorp Inc -AI10851,Machine Learning Engineer,116512,USD,116512,EX,PT,China,M,China,100,"TensorFlow, SQL, MLOps, Deep Learning",PhD,19,Healthcare,2025-03-17,2025-04-24,1614,7.3,Predictive Systems -AI10852,ML Ops Engineer,99823,USD,99823,MI,PT,Denmark,S,Denmark,0,"Git, MLOps, SQL",Associate,2,Telecommunications,2024-03-29,2024-05-25,593,6.8,Future Systems -AI10853,AI Research Scientist,87180,CAD,108975,EN,FL,Canada,L,Canada,100,"GCP, Tableau, Data Visualization, PyTorch",Master,0,Real Estate,2024-04-18,2024-05-08,1341,8.3,Smart Analytics -AI10854,Data Analyst,47973,USD,47973,MI,FL,China,M,China,50,"Hadoop, PyTorch, GCP, Computer Vision",PhD,2,Telecommunications,2024-06-11,2024-08-06,776,8,Quantum Computing Inc -AI10855,Head of AI,313259,USD,313259,EX,FT,Denmark,M,Romania,100,"Python, R, Spark, Linux",Associate,10,Finance,2024-09-23,2024-11-28,2488,6.8,Predictive Systems -AI10856,AI Specialist,199489,USD,199489,SE,FT,Denmark,L,Denmark,50,"SQL, MLOps, Python, Data Visualization, Azure",Associate,8,Government,2024-02-16,2024-03-21,2398,5.9,DeepTech Ventures -AI10857,Autonomous Systems Engineer,32228,USD,32228,EN,CT,China,S,China,50,"Statistics, GCP, SQL, Python, Azure",PhD,1,Gaming,2024-02-17,2024-03-18,1063,6.4,Cloud AI Solutions -AI10858,Principal Data Scientist,113385,USD,113385,MI,PT,Denmark,M,Egypt,50,"GCP, Kubernetes, Tableau",Associate,2,Technology,2024-09-21,2024-11-22,1831,9.4,DataVision Ltd -AI10859,AI Specialist,252641,USD,252641,EX,FT,Ireland,L,Ireland,100,"Tableau, Scala, NLP, Python, Java",Master,17,Transportation,2024-08-30,2024-10-14,2301,7.9,TechCorp Inc -AI10860,Data Engineer,90555,USD,90555,MI,FT,Denmark,S,Denmark,50,"PyTorch, TensorFlow, Linux",Bachelor,4,Finance,2024-03-05,2024-04-18,1969,8.3,Algorithmic Solutions -AI10861,Research Scientist,77655,USD,77655,EN,FT,Norway,M,Norway,50,"Deep Learning, Linux, GCP, Python",Master,1,Manufacturing,2024-03-17,2024-04-15,2224,8.3,Neural Networks Co -AI10862,Data Engineer,141801,USD,141801,MI,FL,Norway,L,Thailand,0,"Spark, Git, Data Visualization, Azure",Bachelor,2,Consulting,2024-06-09,2024-08-15,937,5.9,Future Systems -AI10863,NLP Engineer,163767,USD,163767,SE,FT,Denmark,S,Denmark,100,"SQL, Hadoop, AWS",Bachelor,9,Healthcare,2024-06-13,2024-07-29,1267,6.5,TechCorp Inc -AI10864,Principal Data Scientist,59859,USD,59859,EN,FL,South Korea,L,South Korea,0,"Docker, SQL, Deep Learning, NLP",Associate,1,Healthcare,2025-02-19,2025-03-18,2208,6.4,Quantum Computing Inc -AI10865,Principal Data Scientist,90290,USD,90290,MI,PT,Israel,L,Israel,0,"Python, NLP, Kubernetes, Docker",PhD,3,Media,2024-07-02,2024-09-08,886,6.5,Cognitive Computing -AI10866,Research Scientist,114206,EUR,97075,SE,FT,France,L,France,100,"Python, Docker, Computer Vision, SQL, Kubernetes",PhD,6,Gaming,2025-01-07,2025-03-20,1772,9.1,Smart Analytics -AI10867,Head of AI,99967,USD,99967,SE,PT,Sweden,S,Sweden,50,"R, Java, AWS",Associate,6,Media,2024-12-31,2025-03-06,516,8.1,Neural Networks Co -AI10868,ML Ops Engineer,208430,USD,208430,EX,CT,Sweden,M,Sweden,100,"Azure, Data Visualization, Tableau, Git",PhD,16,Manufacturing,2025-02-18,2025-03-09,883,8.8,Neural Networks Co -AI10869,ML Ops Engineer,88936,GBP,66702,MI,CT,United Kingdom,S,United Kingdom,0,"NLP, Deep Learning, Spark, Git",Master,2,Manufacturing,2024-01-21,2024-04-02,882,7.3,Predictive Systems -AI10870,AI Specialist,172753,USD,172753,SE,CT,Norway,S,Norway,100,"Python, R, GCP, Scala, TensorFlow",Bachelor,6,Gaming,2024-06-04,2024-06-30,892,7.1,Autonomous Tech -AI10871,Robotics Engineer,172661,USD,172661,EX,CT,Finland,L,Finland,50,"SQL, Kubernetes, MLOps, Deep Learning",PhD,10,Telecommunications,2025-02-17,2025-03-03,795,9.9,TechCorp Inc -AI10872,Robotics Engineer,61484,EUR,52261,EN,FL,France,L,France,50,"Docker, SQL, AWS",Bachelor,1,Healthcare,2024-02-23,2024-04-08,2272,6.2,TechCorp Inc -AI10873,Robotics Engineer,71875,EUR,61094,EN,FT,Germany,S,Ukraine,0,"Mathematics, Tableau, Hadoop, Java",PhD,0,Telecommunications,2024-05-18,2024-06-13,1647,6.7,Cloud AI Solutions -AI10874,Data Engineer,79797,USD,79797,MI,FL,Sweden,S,Sweden,50,"Kubernetes, Python, TensorFlow, AWS, NLP",Bachelor,3,Telecommunications,2025-03-21,2025-05-08,527,9.2,Advanced Robotics -AI10875,AI Consultant,91965,USD,91965,EX,FT,India,L,India,50,"Computer Vision, Docker, Python, GCP, Linux",Bachelor,15,Manufacturing,2024-10-03,2024-11-10,1418,7.3,Smart Analytics -AI10876,Robotics Engineer,128584,EUR,109296,SE,FL,Austria,S,Austria,100,"Git, Data Visualization, SQL, Computer Vision",Master,5,Energy,2024-04-07,2024-06-11,2097,6.6,Machine Intelligence Group -AI10877,AI Product Manager,92990,USD,92990,EN,CT,United States,M,United States,100,"Kubernetes, R, GCP, Statistics",Master,0,Telecommunications,2024-12-07,2025-02-18,2231,9.9,DeepTech Ventures -AI10878,AI Architect,85862,USD,85862,EN,FT,Norway,M,Norway,0,"Hadoop, Docker, AWS, Data Visualization",PhD,1,Manufacturing,2024-05-19,2024-07-01,1306,8.6,Cloud AI Solutions -AI10879,AI Product Manager,96557,CAD,120696,MI,CT,Canada,M,Portugal,100,"Git, NLP, Tableau, Data Visualization",Bachelor,3,Telecommunications,2024-01-13,2024-03-13,1805,6.4,Digital Transformation LLC -AI10880,AI Research Scientist,136056,USD,136056,SE,CT,Sweden,S,Austria,50,"AWS, Computer Vision, Mathematics, R",Associate,8,Retail,2024-04-08,2024-05-16,884,9.7,Digital Transformation LLC -AI10881,Principal Data Scientist,191877,EUR,163095,EX,FT,Austria,L,Austria,0,"Spark, GCP, Deep Learning, Scala",Bachelor,15,Transportation,2024-07-08,2024-07-29,2481,7.8,DeepTech Ventures -AI10882,Deep Learning Engineer,58995,USD,58995,EN,CT,Sweden,L,Portugal,0,"Linux, Spark, R",Associate,1,Telecommunications,2025-03-01,2025-03-26,1543,9.8,Smart Analytics -AI10883,Robotics Engineer,171771,USD,171771,SE,FL,Denmark,L,Denmark,50,"AWS, Computer Vision, SQL, Spark",Master,7,Finance,2024-09-14,2024-10-08,1457,9.4,Cognitive Computing -AI10884,AI Software Engineer,124350,USD,124350,SE,PT,United States,M,Netherlands,100,"SQL, Deep Learning, NLP",Master,7,Media,2024-04-04,2024-05-14,1461,9,Autonomous Tech -AI10885,Autonomous Systems Engineer,264027,USD,264027,EX,FT,United States,S,Indonesia,50,"Scala, R, Data Visualization, Python, TensorFlow",Associate,13,Transportation,2024-08-31,2024-09-20,1916,6.7,Future Systems -AI10886,Machine Learning Engineer,254261,EUR,216122,EX,PT,Austria,L,Belgium,50,"Git, TensorFlow, Mathematics",Associate,18,Manufacturing,2024-03-12,2024-05-19,965,5.7,Algorithmic Solutions -AI10887,Head of AI,95509,GBP,71632,MI,FL,United Kingdom,L,United Kingdom,0,"Hadoop, GCP, Data Visualization, Statistics, MLOps",Master,4,Real Estate,2024-11-03,2024-11-24,1264,7.5,DataVision Ltd -AI10888,ML Ops Engineer,144757,CAD,180946,SE,FT,Canada,L,Canada,100,"Hadoop, TensorFlow, NLP",PhD,9,Government,2024-07-08,2024-08-09,1528,5.7,Quantum Computing Inc -AI10889,AI Specialist,80856,USD,80856,EN,FL,Norway,S,Norway,50,"NLP, Scala, Java",Bachelor,0,Energy,2024-11-29,2025-01-14,2142,8.8,DeepTech Ventures -AI10890,Data Engineer,170023,SGD,221030,EX,CT,Singapore,S,Singapore,50,"Mathematics, NLP, Git, Computer Vision, Deep Learning",Bachelor,14,Technology,2024-03-18,2024-05-29,1846,9.5,DataVision Ltd -AI10891,Data Scientist,67573,USD,67573,MI,PT,Israel,S,Kenya,100,"Python, SQL, Java, MLOps",Master,2,Transportation,2024-01-08,2024-03-12,1770,8.9,Cognitive Computing -AI10892,Deep Learning Engineer,43295,USD,43295,MI,FL,India,L,India,0,"Kubernetes, Azure, SQL, Computer Vision",Master,4,Finance,2024-07-25,2024-09-01,1342,7.4,DataVision Ltd -AI10893,Principal Data Scientist,138506,CAD,173133,SE,CT,Canada,L,Canada,0,"Java, Git, Tableau, Kubernetes, R",Bachelor,5,Consulting,2024-08-01,2024-09-17,971,9.6,Cognitive Computing -AI10894,AI Specialist,83927,SGD,109105,EN,FL,Singapore,L,Mexico,0,"Tableau, Kubernetes, Linux",PhD,0,Manufacturing,2024-08-25,2024-11-01,2240,9.8,Cloud AI Solutions -AI10895,AI Product Manager,77484,GBP,58113,EN,FT,United Kingdom,M,United Kingdom,50,"Spark, GCP, Scala, Docker, Hadoop",Bachelor,1,Retail,2025-04-29,2025-05-22,1818,8.7,DeepTech Ventures -AI10896,Deep Learning Engineer,149388,USD,149388,SE,FL,Ireland,M,Ireland,100,"Tableau, Azure, PyTorch, NLP, SQL",PhD,6,Government,2024-06-07,2024-07-30,855,9.9,Autonomous Tech -AI10897,AI Specialist,220434,EUR,187369,EX,PT,Netherlands,S,Netherlands,50,"Kubernetes, Git, Data Visualization, Python",PhD,14,Retail,2024-04-25,2024-05-14,1114,8.6,DataVision Ltd -AI10898,Head of AI,79212,GBP,59409,EN,FL,United Kingdom,M,Romania,100,"AWS, Data Visualization, Git",Associate,1,Finance,2025-03-13,2025-05-04,1636,5.9,Algorithmic Solutions -AI10899,Machine Learning Researcher,169031,EUR,143676,SE,FL,Germany,L,Germany,50,"Linux, Python, NLP, Java",Bachelor,7,Automotive,2024-10-07,2024-11-23,2421,9.2,Advanced Robotics -AI10900,AI Product Manager,165582,USD,165582,SE,CT,Norway,L,Norway,50,"Scala, Data Visualization, Python",PhD,8,Education,2024-02-12,2024-03-04,1890,6.5,Digital Transformation LLC -AI10901,NLP Engineer,323522,CHF,291170,EX,FL,Switzerland,L,Switzerland,100,"Docker, MLOps, Kubernetes, GCP",Bachelor,18,Energy,2025-04-27,2025-05-15,1564,10,Cognitive Computing -AI10902,ML Ops Engineer,89783,USD,89783,EN,FL,United States,L,United States,100,"Azure, MLOps, Statistics",Master,1,Gaming,2024-07-29,2024-10-08,1060,6.7,Advanced Robotics -AI10903,Head of AI,172737,USD,172737,EX,PT,Denmark,S,Denmark,50,"AWS, Linux, Mathematics, Data Visualization, NLP",Master,13,Telecommunications,2025-01-29,2025-03-10,1381,8.9,Algorithmic Solutions -AI10904,Data Scientist,118389,USD,118389,SE,FT,Ireland,M,Ireland,50,"GCP, Linux, SQL, Kubernetes",Associate,5,Consulting,2025-03-18,2025-05-12,1971,6.7,Algorithmic Solutions -AI10905,AI Research Scientist,77597,GBP,58198,EN,FL,United Kingdom,M,United Kingdom,100,"Java, Deep Learning, R, Docker",Associate,0,Gaming,2024-08-11,2024-09-03,2061,9.5,Advanced Robotics -AI10906,Data Scientist,139624,SGD,181511,SE,PT,Singapore,S,Singapore,50,"Python, TensorFlow, Statistics",Associate,7,Media,2024-10-02,2024-11-07,1774,9.6,Smart Analytics -AI10907,Data Scientist,118666,SGD,154266,SE,PT,Singapore,M,Singapore,100,"Linux, Scala, Data Visualization, Kubernetes",Master,5,Media,2025-01-14,2025-01-28,964,5.3,Autonomous Tech -AI10908,Data Scientist,74287,EUR,63144,EN,CT,Netherlands,S,Russia,100,"SQL, Kubernetes, Data Visualization, Deep Learning",PhD,1,Education,2024-04-04,2024-05-24,1947,7.1,DataVision Ltd -AI10909,AI Product Manager,208649,GBP,156487,EX,CT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Java",Associate,13,Finance,2024-12-13,2025-01-16,1064,8.1,Machine Intelligence Group -AI10910,Data Analyst,123996,EUR,105397,SE,FL,France,L,United Kingdom,0,"Kubernetes, Scala, Spark, PyTorch, Java",Bachelor,8,Healthcare,2024-04-07,2024-05-19,1805,8,Quantum Computing Inc -AI10911,Data Analyst,229871,EUR,195390,EX,PT,Germany,L,Germany,50,"PyTorch, Deep Learning, Computer Vision",PhD,15,Healthcare,2025-03-02,2025-04-05,2477,9.5,Cloud AI Solutions -AI10912,Machine Learning Engineer,92771,SGD,120602,MI,FL,Singapore,S,Singapore,50,"Docker, SQL, Azure, TensorFlow",Associate,2,Automotive,2024-08-02,2024-10-14,910,7.1,Autonomous Tech -AI10913,Data Scientist,31230,USD,31230,EN,FL,China,M,Vietnam,100,"Azure, Python, Data Visualization, R, Statistics",Bachelor,1,Consulting,2025-03-26,2025-05-15,1660,8.5,TechCorp Inc -AI10914,AI Specialist,120411,USD,120411,SE,CT,Israel,S,Turkey,50,"Python, AWS, Linux, Git",Associate,7,Energy,2025-02-02,2025-03-25,2299,6.3,Autonomous Tech -AI10915,Computer Vision Engineer,219663,EUR,186714,EX,FT,Germany,S,Germany,100,"Python, R, TensorFlow, Docker",Bachelor,16,Automotive,2024-01-05,2024-02-25,1906,7.1,DeepTech Ventures -AI10916,Research Scientist,62748,EUR,53336,MI,FT,Austria,S,Austria,50,"Tableau, Mathematics, Python, SQL, AWS",Master,3,Real Estate,2024-07-16,2024-08-12,1479,5.8,TechCorp Inc -AI10917,AI Software Engineer,60299,GBP,45224,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Data Visualization, PyTorch",Master,1,Education,2024-12-06,2025-02-05,1779,7.8,Smart Analytics -AI10918,Head of AI,266091,EUR,226177,EX,PT,Netherlands,M,Netherlands,50,"NLP, Kubernetes, Scala, Statistics, TensorFlow",Associate,13,Media,2025-04-02,2025-04-27,990,5.7,Algorithmic Solutions -AI10919,AI Specialist,252940,AUD,341469,EX,FT,Australia,L,Austria,0,"SQL, GCP, Python, Hadoop",PhD,16,Healthcare,2025-03-07,2025-04-07,2229,8.7,Algorithmic Solutions -AI10920,Principal Data Scientist,100217,JPY,11023870,MI,FT,Japan,L,New Zealand,50,"Scala, SQL, Git, Deep Learning",Associate,3,Gaming,2025-04-25,2025-06-30,1851,6.8,Neural Networks Co -AI10921,Deep Learning Engineer,197325,USD,197325,EX,FL,United States,S,United States,100,"Scala, Java, R",PhD,14,Manufacturing,2024-03-26,2024-06-06,1769,5,Cognitive Computing -AI10922,Head of AI,23752,USD,23752,EN,FT,India,M,India,0,"SQL, Linux, MLOps, GCP",Master,0,Technology,2024-10-22,2024-12-11,1459,6.8,Machine Intelligence Group -AI10923,Machine Learning Researcher,61586,GBP,46190,EN,FL,United Kingdom,S,United Kingdom,50,"Kubernetes, Tableau, Python, Docker, Java",Associate,0,Telecommunications,2024-10-21,2024-11-22,970,9.3,TechCorp Inc -AI10924,AI Software Engineer,32487,USD,32487,MI,FL,India,S,Latvia,100,"SQL, Git, R",Associate,2,Energy,2024-07-23,2024-09-21,2404,7,DataVision Ltd -AI10925,Deep Learning Engineer,71388,USD,71388,EN,FT,Ireland,S,Ireland,100,"SQL, Scala, Statistics, NLP",Associate,1,Transportation,2024-03-15,2024-04-02,2180,8,DataVision Ltd -AI10926,NLP Engineer,218351,CHF,196516,SE,FL,Switzerland,L,Switzerland,50,"SQL, Hadoop, Deep Learning",Bachelor,8,Government,2024-08-26,2024-09-23,1062,9.4,DataVision Ltd -AI10927,AI Specialist,166329,GBP,124747,EX,PT,United Kingdom,L,United Kingdom,100,"Statistics, Git, PyTorch",Master,14,Retail,2024-05-06,2024-06-02,1104,9.6,AI Innovations -AI10928,AI Software Engineer,75044,GBP,56283,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Java, MLOps, Scala",Master,0,Gaming,2024-12-01,2024-12-15,933,8.6,Cloud AI Solutions -AI10929,AI Consultant,206933,SGD,269013,EX,CT,Singapore,L,Switzerland,0,"Docker, Python, GCP",Bachelor,19,Real Estate,2025-03-11,2025-04-07,1194,7.7,Smart Analytics -AI10930,Machine Learning Engineer,195026,EUR,165772,EX,CT,Germany,M,Germany,100,"SQL, Spark, AWS",Master,10,Media,2025-03-18,2025-05-15,1217,7.7,Machine Intelligence Group -AI10931,Head of AI,104858,USD,104858,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, AWS, PyTorch",PhD,8,Transportation,2024-07-30,2024-09-27,1048,7.3,Future Systems -AI10932,Autonomous Systems Engineer,118890,USD,118890,SE,CT,Israel,S,Israel,0,"Scala, MLOps, Tableau, Kubernetes, Mathematics",Bachelor,6,Retail,2024-08-31,2024-10-02,1165,8.9,Quantum Computing Inc -AI10933,Deep Learning Engineer,87321,EUR,74223,MI,CT,Germany,L,Germany,50,"Git, Computer Vision, Java",PhD,3,Healthcare,2024-01-11,2024-03-01,2443,10,Smart Analytics -AI10934,AI Product Manager,104724,USD,104724,SE,CT,Ireland,S,Ireland,100,"Linux, Data Visualization, Tableau, MLOps, Kubernetes",PhD,9,Gaming,2024-06-02,2024-06-24,1259,8.3,Cloud AI Solutions -AI10935,AI Research Scientist,65970,EUR,56075,MI,FL,Austria,S,Austria,50,"PyTorch, Python, Linux, Scala",PhD,3,Energy,2024-07-01,2024-09-10,2200,5.2,AI Innovations -AI10936,AI Specialist,102652,USD,102652,SE,CT,South Korea,M,South Korea,100,"Data Visualization, Mathematics, GCP",Bachelor,5,Consulting,2024-04-02,2024-04-17,927,6.8,Quantum Computing Inc -AI10937,Data Scientist,120871,EUR,102740,SE,PT,Netherlands,M,Netherlands,100,"Linux, Hadoop, AWS, Data Visualization, GCP",Associate,6,Healthcare,2024-07-24,2024-10-01,1764,7.3,DataVision Ltd -AI10938,NLP Engineer,91506,JPY,10065660,EN,FT,Japan,L,Japan,100,"SQL, Linux, Mathematics",PhD,1,Energy,2025-03-16,2025-04-29,1817,7,Future Systems -AI10939,Data Scientist,156607,CAD,195759,EX,PT,Canada,L,Canada,0,"Spark, Python, Docker",PhD,12,Energy,2024-04-24,2024-06-02,1016,6.4,Autonomous Tech -AI10940,Computer Vision Engineer,114380,USD,114380,MI,FT,Israel,L,Israel,100,"R, GCP, PyTorch",Associate,4,Retail,2025-01-01,2025-02-01,646,7.1,Smart Analytics -AI10941,NLP Engineer,47258,EUR,40169,EN,FT,Austria,S,Austria,0,"Python, Scala, Computer Vision",Associate,1,Gaming,2024-10-28,2024-12-15,1295,6.9,Smart Analytics -AI10942,Computer Vision Engineer,63033,SGD,81943,EN,PT,Singapore,S,Singapore,100,"Python, GCP, Computer Vision, Azure",Associate,1,Retail,2024-11-23,2025-01-01,961,9.4,Machine Intelligence Group -AI10943,Data Analyst,51890,USD,51890,EX,CT,India,S,India,50,"Scala, Computer Vision, Kubernetes, GCP",Master,18,Finance,2025-01-31,2025-04-02,1200,9.1,Advanced Robotics -AI10944,NLP Engineer,114029,EUR,96925,MI,FL,France,L,Philippines,100,"GCP, Java, NLP",PhD,4,Technology,2025-02-07,2025-04-13,2083,5.4,Autonomous Tech -AI10945,Data Engineer,97612,USD,97612,MI,PT,Ireland,L,Ireland,100,"PyTorch, Kubernetes, GCP, NLP",PhD,4,Retail,2024-12-29,2025-01-20,912,6.7,TechCorp Inc -AI10946,Research Scientist,99042,EUR,84186,MI,PT,France,M,France,100,"Docker, Hadoop, Computer Vision",Bachelor,4,Government,2024-01-17,2024-03-19,1864,6,Predictive Systems -AI10947,Deep Learning Engineer,143114,EUR,121647,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Kubernetes",Master,8,Government,2024-08-07,2024-09-02,592,9.3,TechCorp Inc -AI10948,AI Consultant,246283,USD,246283,EX,CT,Norway,S,Norway,0,"R, PyTorch, Mathematics, TensorFlow",Bachelor,13,Healthcare,2025-01-06,2025-02-26,1469,7.7,Algorithmic Solutions -AI10949,NLP Engineer,83037,JPY,9134070,MI,PT,Japan,M,Germany,50,"Python, Data Visualization, TensorFlow, Hadoop",Associate,3,Government,2024-05-28,2024-07-26,1776,8.6,Digital Transformation LLC -AI10950,NLP Engineer,64015,USD,64015,EN,PT,Sweden,L,Sweden,0,"Python, Kubernetes, Docker",Bachelor,1,Technology,2024-10-01,2024-10-20,1023,7.3,AI Innovations -AI10951,Data Scientist,121642,USD,121642,EX,CT,Finland,S,Finland,0,"Kubernetes, NLP, Python, Mathematics",Associate,17,Education,2024-03-26,2024-05-23,549,10,Autonomous Tech -AI10952,AI Software Engineer,76327,GBP,57245,EN,PT,United Kingdom,S,Indonesia,50,"Tableau, GCP, Git, Azure, Kubernetes",Associate,0,Energy,2024-05-17,2024-07-19,1246,8.7,DeepTech Ventures -AI10953,Robotics Engineer,165749,EUR,140887,EX,CT,Austria,S,Austria,0,"Hadoop, Python, TensorFlow",Bachelor,16,Technology,2024-01-19,2024-02-07,1686,6.2,Cloud AI Solutions -AI10954,Data Analyst,137659,USD,137659,SE,FL,Sweden,L,Sweden,100,"Statistics, Docker, TensorFlow",PhD,7,Energy,2025-04-18,2025-06-08,1577,7.6,Machine Intelligence Group -AI10955,AI Specialist,105624,GBP,79218,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, R, Azure, Linux",Master,4,Healthcare,2024-08-18,2024-10-30,641,8.8,TechCorp Inc -AI10956,Autonomous Systems Engineer,146967,USD,146967,MI,CT,Norway,L,Norway,100,"Spark, GCP, Hadoop",Bachelor,4,Technology,2024-04-11,2024-05-09,2256,8.4,Smart Analytics -AI10957,Machine Learning Engineer,76091,USD,76091,EN,PT,Ireland,L,Ireland,100,"Docker, Computer Vision, Git, R, GCP",Bachelor,1,Government,2024-02-08,2024-04-05,1762,5.2,Machine Intelligence Group -AI10958,Machine Learning Researcher,79160,USD,79160,EN,FT,Denmark,M,Luxembourg,50,"Kubernetes, Python, TensorFlow",Bachelor,0,Transportation,2024-01-18,2024-03-14,2020,7.1,Cloud AI Solutions -AI10959,Robotics Engineer,176142,CHF,158528,MI,FT,Switzerland,L,Luxembourg,0,"AWS, R, Data Visualization",PhD,3,Education,2024-03-24,2024-04-10,1000,6.3,Cloud AI Solutions -AI10960,Computer Vision Engineer,85509,EUR,72683,MI,PT,Germany,S,Germany,100,"Data Visualization, MLOps, Kubernetes, SQL, Python",Associate,3,Education,2024-11-01,2025-01-06,610,9.4,Cloud AI Solutions -AI10961,Data Analyst,66853,USD,66853,MI,FL,Finland,S,Finland,100,"R, Mathematics, Linux",PhD,4,Finance,2024-08-02,2024-08-21,1589,5.9,Machine Intelligence Group -AI10962,Research Scientist,26651,USD,26651,MI,FL,India,S,India,100,"Java, SQL, Azure, Git, GCP",Bachelor,4,Transportation,2024-01-18,2024-02-23,1808,8.2,Digital Transformation LLC -AI10963,Machine Learning Engineer,60811,USD,60811,EN,FT,United States,M,United States,0,"MLOps, Tableau, Scala, Hadoop, AWS",Bachelor,0,Gaming,2024-02-14,2024-03-30,997,8.2,Future Systems -AI10964,Data Engineer,65850,USD,65850,EN,CT,South Korea,M,South Korea,0,"Hadoop, GCP, Tableau",Associate,0,Retail,2024-12-05,2025-02-09,580,5.1,Future Systems -AI10965,Deep Learning Engineer,159852,EUR,135874,EX,FL,France,M,France,100,"Kubernetes, Hadoop, Python, AWS",Bachelor,12,Technology,2024-02-26,2024-04-15,694,9,Cloud AI Solutions -AI10966,AI Software Engineer,117072,CHF,105365,MI,CT,Switzerland,M,Luxembourg,100,"Data Visualization, TensorFlow, Python",Master,4,Education,2024-02-01,2024-04-06,1043,9,TechCorp Inc -AI10967,Head of AI,73513,USD,73513,EX,FT,India,S,India,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Consulting,2024-12-31,2025-03-03,2106,5.9,AI Innovations -AI10968,AI Specialist,158422,EUR,134659,EX,PT,Germany,M,Germany,50,"Python, Mathematics, TensorFlow",PhD,19,Consulting,2024-06-19,2024-08-12,732,7.7,Quantum Computing Inc -AI10969,AI Consultant,52063,USD,52063,EN,PT,South Korea,M,South Korea,0,"Computer Vision, MLOps, Mathematics, Docker",PhD,1,Finance,2025-04-04,2025-05-02,2052,5.9,TechCorp Inc -AI10970,AI Architect,87999,USD,87999,EN,PT,Norway,L,Norway,50,"Azure, Python, Computer Vision",PhD,0,Consulting,2025-01-25,2025-03-04,2011,9.3,Cognitive Computing -AI10971,Robotics Engineer,65735,AUD,88742,EN,FL,Australia,S,Vietnam,100,"Scala, Git, Statistics",Associate,1,Real Estate,2025-02-02,2025-03-04,776,9.9,AI Innovations -AI10972,Machine Learning Researcher,79748,USD,79748,EX,FT,India,M,India,100,"NLP, Python, Mathematics, GCP",Master,17,Education,2025-02-02,2025-03-10,998,9.9,DeepTech Ventures -AI10973,Machine Learning Engineer,153047,CHF,137742,MI,FT,Switzerland,L,New Zealand,0,"SQL, Python, R",Master,3,Retail,2024-07-25,2024-09-26,1468,5.9,Future Systems -AI10974,Data Analyst,82660,GBP,61995,EN,PT,United Kingdom,L,United Kingdom,100,"Java, R, Mathematics",Bachelor,1,Retail,2024-09-09,2024-10-07,599,9.5,Smart Analytics -AI10975,Computer Vision Engineer,245036,USD,245036,EX,CT,United States,S,United States,100,"Git, Linux, Kubernetes, Deep Learning, NLP",Bachelor,17,Technology,2024-05-15,2024-07-22,804,9.9,Smart Analytics -AI10976,AI Research Scientist,223802,AUD,302133,EX,PT,Australia,S,Australia,100,"AWS, Kubernetes, Computer Vision",Bachelor,11,Energy,2024-11-04,2025-01-10,964,7.1,Cloud AI Solutions -AI10977,Machine Learning Researcher,83891,AUD,113253,MI,FL,Australia,M,Australia,50,"Git, MLOps, Scala, GCP, Spark",Master,3,Real Estate,2025-02-23,2025-04-21,852,6.8,Advanced Robotics -AI10978,Machine Learning Researcher,98442,GBP,73832,SE,PT,United Kingdom,S,United Kingdom,50,"SQL, Git, TensorFlow, Python",PhD,5,Education,2024-03-31,2024-04-21,1604,9.9,Advanced Robotics -AI10979,NLP Engineer,128077,JPY,14088470,SE,FL,Japan,M,Japan,100,"TensorFlow, Python, MLOps, Git",Associate,6,Energy,2024-03-06,2024-04-22,1539,5.5,TechCorp Inc -AI10980,Data Scientist,186264,USD,186264,EX,FT,Sweden,M,Sweden,0,"SQL, Computer Vision, Scala",Bachelor,15,Finance,2024-07-16,2024-09-10,612,7.4,Advanced Robotics -AI10981,AI Research Scientist,110728,USD,110728,MI,CT,Norway,M,Norway,0,"TensorFlow, Python, Kubernetes, R",PhD,3,Technology,2025-03-23,2025-04-11,1637,8.5,Algorithmic Solutions -AI10982,Robotics Engineer,215988,USD,215988,EX,PT,Denmark,M,Denmark,0,"PyTorch, Deep Learning, NLP, Git",Associate,15,Manufacturing,2024-06-09,2024-06-23,508,9.8,Cognitive Computing -AI10983,Autonomous Systems Engineer,125459,USD,125459,SE,CT,Israel,S,Indonesia,50,"Python, Scala, Kubernetes, Deep Learning, AWS",PhD,6,Automotive,2024-03-23,2024-05-26,1423,7.2,AI Innovations -AI10984,ML Ops Engineer,247115,USD,247115,EX,FL,United States,L,United States,0,"TensorFlow, R, Deep Learning, GCP, Git",Associate,19,Consulting,2024-12-03,2025-01-24,1894,5.5,Digital Transformation LLC -AI10985,Machine Learning Engineer,311593,USD,311593,EX,FL,Norway,L,Norway,0,"Linux, Python, TensorFlow",Master,16,Finance,2025-01-23,2025-03-08,1712,7.9,Future Systems -AI10986,Data Analyst,129554,USD,129554,EX,FT,China,L,China,0,"Data Visualization, Kubernetes, Java",Associate,18,Consulting,2025-03-23,2025-05-28,705,9.2,Cloud AI Solutions -AI10987,Deep Learning Engineer,284164,USD,284164,EX,PT,Norway,L,Norway,100,"R, Statistics, SQL, Python, Linux",Master,14,Telecommunications,2024-02-03,2024-02-28,2259,6.5,Cognitive Computing -AI10988,Deep Learning Engineer,144657,EUR,122958,SE,FT,Netherlands,L,Netherlands,0,"SQL, Statistics, Linux",Master,5,Government,2025-02-23,2025-04-30,586,5.7,Predictive Systems -AI10989,Computer Vision Engineer,178156,CAD,222695,EX,FT,Canada,M,Canada,0,"Kubernetes, SQL, Azure, Hadoop",PhD,19,Automotive,2025-02-03,2025-03-22,1702,7.2,Neural Networks Co -AI10990,Data Scientist,86173,CAD,107716,MI,FL,Canada,M,Canada,100,"MLOps, Git, PyTorch, Mathematics",Associate,2,Healthcare,2024-08-09,2024-10-03,1035,8.4,Cloud AI Solutions -AI10991,Data Scientist,106280,SGD,138164,MI,PT,Singapore,L,Czech Republic,100,"Java, SQL, Kubernetes, AWS",Associate,2,Energy,2024-11-26,2025-01-07,779,5.8,TechCorp Inc -AI10992,Data Scientist,80053,AUD,108072,MI,FL,Australia,M,Australia,50,"Deep Learning, Linux, MLOps, SQL, Kubernetes",Master,4,Healthcare,2025-03-05,2025-03-20,1525,9.8,TechCorp Inc -AI10993,AI Architect,91642,CAD,114553,MI,CT,Canada,M,Canada,50,"Git, Docker, Spark, R, Mathematics",Master,2,Real Estate,2024-11-17,2024-12-09,1599,5.7,AI Innovations -AI10994,Data Analyst,72487,EUR,61614,EN,FL,Germany,S,Netherlands,0,"PyTorch, Tableau, Mathematics, MLOps",PhD,1,Education,2025-02-01,2025-02-19,2284,6,Future Systems -AI10995,Data Analyst,40355,USD,40355,EN,FT,China,L,Denmark,0,"Python, TensorFlow, PyTorch, AWS",PhD,0,Gaming,2024-12-21,2025-01-26,1733,5.1,Cognitive Computing -AI10996,AI Architect,185648,USD,185648,EX,FL,Denmark,M,Denmark,50,"Tableau, TensorFlow, Git, Statistics",PhD,18,Education,2024-11-08,2025-01-11,711,7.2,Quantum Computing Inc -AI10997,NLP Engineer,177709,USD,177709,EX,PT,Ireland,M,Ireland,100,"AWS, MLOps, Deep Learning",Master,13,Real Estate,2024-04-13,2024-06-02,1165,6.5,Predictive Systems -AI10998,Computer Vision Engineer,60113,EUR,51096,EN,CT,Netherlands,S,Netherlands,100,"AWS, Data Visualization, Linux, TensorFlow",Associate,0,Consulting,2024-12-01,2025-01-06,1214,6.7,AI Innovations -AI10999,Data Engineer,170719,USD,170719,EX,FL,Norway,S,Norway,100,"Hadoop, Python, TensorFlow",PhD,13,Consulting,2025-01-31,2025-04-04,2355,6.2,AI Innovations -AI11000,Principal Data Scientist,94395,USD,94395,MI,CT,South Korea,L,South Korea,0,"R, SQL, Kubernetes",PhD,4,Telecommunications,2024-11-11,2024-12-13,1904,6.7,Digital Transformation LLC -AI11001,Robotics Engineer,170094,EUR,144580,EX,FL,Netherlands,L,Netherlands,50,"Kubernetes, Git, PyTorch, SQL, Deep Learning",Associate,12,Automotive,2025-02-25,2025-04-07,1931,9,Predictive Systems -AI11002,Robotics Engineer,44187,USD,44187,MI,FT,China,S,China,100,"TensorFlow, Docker, Scala",Associate,4,Manufacturing,2025-04-07,2025-05-06,1790,5.4,Predictive Systems -AI11003,NLP Engineer,199463,USD,199463,EX,FT,Ireland,S,Chile,0,"Tableau, TensorFlow, Linux, Python",Bachelor,16,Manufacturing,2024-10-06,2024-11-13,833,6.1,TechCorp Inc -AI11004,Machine Learning Researcher,103266,CAD,129083,SE,PT,Canada,M,Canada,100,"Python, Kubernetes, Docker",Master,9,Education,2024-10-12,2024-12-17,1567,8.5,Quantum Computing Inc -AI11005,Head of AI,74247,EUR,63110,MI,PT,Austria,M,Poland,100,"SQL, Deep Learning, Python, Hadoop",PhD,2,Finance,2025-03-10,2025-04-26,1921,7.6,DeepTech Ventures -AI11006,Robotics Engineer,267617,GBP,200713,EX,FL,United Kingdom,M,Egypt,100,"Python, TensorFlow, PyTorch, Tableau, Docker",Associate,12,Technology,2024-02-04,2024-04-16,1058,8.6,Future Systems -AI11007,AI Product Manager,170750,EUR,145138,SE,PT,Netherlands,L,Hungary,0,"Python, Data Visualization, MLOps, Hadoop, AWS",Associate,5,Finance,2024-07-14,2024-08-11,1811,7.5,Predictive Systems -AI11008,AI Architect,151644,EUR,128897,EX,FT,Germany,S,Germany,0,"TensorFlow, Tableau, GCP, PyTorch, Statistics",Associate,10,Automotive,2025-02-22,2025-04-29,1657,6.4,DeepTech Ventures -AI11009,Head of AI,19668,USD,19668,EN,CT,India,M,India,50,"MLOps, Scala, GCP, AWS, Kubernetes",Bachelor,0,Real Estate,2024-08-28,2024-09-13,1898,7.2,Advanced Robotics -AI11010,AI Specialist,133233,USD,133233,SE,FT,Sweden,M,Sweden,50,"SQL, PyTorch, Linux, Deep Learning",Master,8,Manufacturing,2024-08-20,2024-10-19,1836,6.2,Advanced Robotics -AI11011,AI Consultant,62844,USD,62844,EN,PT,Ireland,S,Ireland,50,"Git, PyTorch, TensorFlow, Docker",Bachelor,1,Media,2024-03-26,2024-05-17,987,8.8,Machine Intelligence Group -AI11012,Data Scientist,144621,USD,144621,SE,FL,Norway,S,Norway,50,"Spark, Kubernetes, Computer Vision, AWS",Associate,6,Transportation,2024-10-31,2024-11-29,2429,5.4,Digital Transformation LLC -AI11013,AI Product Manager,121548,USD,121548,SE,FT,United States,M,United States,50,"Hadoop, Deep Learning, Kubernetes, Spark, Python",Master,6,Real Estate,2024-11-28,2025-01-20,959,6.8,Algorithmic Solutions -AI11014,ML Ops Engineer,355399,CHF,319859,EX,FT,Switzerland,M,Switzerland,0,"GCP, Git, Computer Vision",Bachelor,14,Technology,2024-07-25,2024-08-29,1808,8.8,Digital Transformation LLC -AI11015,AI Research Scientist,261652,USD,261652,EX,PT,Norway,S,Norway,0,"SQL, AWS, GCP",Bachelor,10,Transportation,2024-12-24,2025-02-12,536,6,Quantum Computing Inc -AI11016,Principal Data Scientist,135239,USD,135239,SE,FL,United States,M,United States,0,"Python, Data Visualization, Hadoop, Scala",Bachelor,9,Automotive,2024-10-13,2024-11-21,941,5.3,AI Innovations -AI11017,AI Research Scientist,136136,USD,136136,SE,FL,United States,M,United States,0,"GCP, Data Visualization, PyTorch, R, Spark",Master,7,Real Estate,2024-02-17,2024-03-04,2020,9.3,Predictive Systems -AI11018,Computer Vision Engineer,162399,USD,162399,EX,FT,Ireland,S,Ireland,100,"R, GCP, MLOps, Python",Associate,16,Media,2025-04-10,2025-05-26,1549,5.8,DataVision Ltd -AI11019,Data Scientist,250763,GBP,188072,EX,FL,United Kingdom,L,Czech Republic,100,"Data Visualization, TensorFlow, NLP, Statistics",Associate,12,Transportation,2024-09-21,2024-10-27,1830,7.4,Cognitive Computing -AI11020,Deep Learning Engineer,63767,EUR,54202,EN,PT,Germany,S,Germany,50,"Hadoop, Data Visualization, GCP",Master,1,Consulting,2025-04-17,2025-05-08,1518,9.1,Cloud AI Solutions -AI11021,Research Scientist,74764,EUR,63549,MI,FL,Austria,M,Austria,50,"Python, TensorFlow, NLP",Master,2,Telecommunications,2024-12-05,2025-02-06,2011,5.2,Quantum Computing Inc -AI11022,Research Scientist,46031,USD,46031,EN,FT,Israel,S,Hungary,50,"Kubernetes, Java, Scala",PhD,1,Transportation,2024-10-28,2024-12-28,648,8.6,Cognitive Computing -AI11023,AI Consultant,52060,EUR,44251,EN,FL,Austria,M,Austria,50,"R, Hadoop, SQL",PhD,0,Automotive,2024-12-10,2025-01-19,1945,5.2,DataVision Ltd -AI11024,Autonomous Systems Engineer,138305,EUR,117559,SE,CT,France,M,France,50,"Java, Hadoop, NLP, Computer Vision",PhD,8,Consulting,2025-01-09,2025-02-16,1084,5.7,AI Innovations -AI11025,AI Product Manager,82393,USD,82393,MI,PT,United States,S,United States,100,"Docker, PyTorch, R, Azure",Bachelor,2,Government,2025-04-07,2025-05-14,2069,8.7,Quantum Computing Inc -AI11026,AI Product Manager,174517,USD,174517,EX,CT,Sweden,L,Sweden,100,"TensorFlow, Docker, R",PhD,16,Telecommunications,2024-10-06,2024-11-22,1820,9.2,TechCorp Inc -AI11027,Robotics Engineer,133855,USD,133855,MI,PT,Norway,L,Norway,0,"SQL, MLOps, Data Visualization",Bachelor,4,Automotive,2024-12-12,2024-12-30,1909,8.8,Future Systems -AI11028,Data Analyst,114683,EUR,97481,SE,FL,Austria,L,Ukraine,50,"Git, Hadoop, Java",PhD,7,Consulting,2025-03-06,2025-04-15,1203,8.5,Cloud AI Solutions -AI11029,Data Analyst,144927,CHF,130434,MI,FL,Switzerland,M,Ghana,50,"R, SQL, Java, Hadoop, Git",Master,3,Government,2025-02-18,2025-04-26,1093,5.9,Smart Analytics -AI11030,AI Software Engineer,125273,AUD,169119,SE,CT,Australia,S,Australia,100,"AWS, Python, GCP, Spark, TensorFlow",PhD,7,Finance,2024-04-14,2024-05-01,2128,9.5,Predictive Systems -AI11031,AI Consultant,147687,EUR,125534,SE,PT,Netherlands,L,Ireland,0,"Hadoop, Spark, PyTorch, Scala",Associate,5,Education,2024-10-21,2024-11-04,2008,7.1,Future Systems -AI11032,Data Scientist,50116,USD,50116,EN,CT,Finland,M,Vietnam,0,"Java, Kubernetes, Data Visualization, GCP, NLP",Bachelor,1,Education,2024-12-25,2025-01-26,1419,7.3,Algorithmic Solutions -AI11033,Data Analyst,104932,EUR,89192,MI,PT,Netherlands,S,Netherlands,100,"Linux, Scala, MLOps",Associate,2,Consulting,2024-12-16,2025-01-17,2408,7.1,Predictive Systems -AI11034,Machine Learning Engineer,109091,CAD,136364,SE,FL,Canada,M,Canada,0,"PyTorch, R, GCP, Tableau",PhD,8,Government,2024-08-31,2024-09-19,1227,7.5,Advanced Robotics -AI11035,Machine Learning Engineer,108563,GBP,81422,MI,CT,United Kingdom,L,Japan,50,"Python, PyTorch, Scala, SQL",Associate,4,Finance,2024-08-20,2024-10-19,663,6.6,Digital Transformation LLC -AI11036,AI Research Scientist,69383,SGD,90198,EN,FT,Singapore,M,Singapore,100,"Kubernetes, Statistics, GCP",Associate,0,Media,2024-04-15,2024-05-30,643,5.7,AI Innovations -AI11037,Principal Data Scientist,83302,JPY,9163220,MI,FL,Japan,S,Japan,0,"Java, MLOps, Tableau",Master,2,Automotive,2024-03-01,2024-04-30,1368,5.8,Algorithmic Solutions -AI11038,NLP Engineer,253256,EUR,215268,EX,FL,Netherlands,M,Netherlands,50,"Scala, Docker, Computer Vision, Python, Mathematics",Associate,14,Education,2024-12-01,2025-01-10,2350,9.3,DeepTech Ventures -AI11039,Autonomous Systems Engineer,247403,USD,247403,EX,PT,United States,M,United States,50,"Tableau, Docker, Python, Git",Bachelor,19,Education,2024-10-06,2024-12-04,2319,6.1,Smart Analytics -AI11040,Computer Vision Engineer,75025,USD,75025,MI,FL,Ireland,S,Canada,0,"PyTorch, R, Spark, MLOps, Git",Associate,2,Transportation,2024-10-06,2024-11-29,1591,8,TechCorp Inc -AI11041,AI Consultant,60929,USD,60929,EN,FT,Israel,M,Israel,0,"Hadoop, Git, Data Visualization",PhD,1,Retail,2025-03-20,2025-04-13,1691,9.7,Algorithmic Solutions -AI11042,AI Consultant,55166,GBP,41375,EN,FT,United Kingdom,M,United Kingdom,50,"Kubernetes, Statistics, Deep Learning, Tableau, MLOps",PhD,0,Media,2024-01-16,2024-03-22,1296,6,Cognitive Computing -AI11043,Data Engineer,70004,USD,70004,EN,PT,Sweden,M,Sweden,0,"R, Git, Java, Linux",Associate,0,Healthcare,2024-05-30,2024-08-02,2277,8.2,Future Systems -AI11044,AI Specialist,275697,USD,275697,EX,CT,Norway,L,Norway,0,"AWS, PyTorch, SQL, TensorFlow",Master,19,Government,2025-02-28,2025-05-04,951,8.6,Smart Analytics -AI11045,Principal Data Scientist,52725,EUR,44816,EN,PT,Germany,M,Ukraine,100,"Python, Computer Vision, Azure",Bachelor,0,Media,2024-08-11,2024-09-10,1030,5.1,Quantum Computing Inc -AI11046,Computer Vision Engineer,268365,USD,268365,EX,FL,Norway,M,United States,0,"Python, Azure, Data Visualization",Associate,11,Gaming,2025-03-04,2025-04-12,1695,9.3,DataVision Ltd -AI11047,Principal Data Scientist,76596,JPY,8425560,MI,PT,Japan,M,China,50,"Java, Linux, Python",Associate,2,Retail,2024-11-08,2024-12-05,623,7.5,Smart Analytics -AI11048,Computer Vision Engineer,285551,AUD,385494,EX,FL,Australia,L,Australia,50,"Python, NLP, Mathematics, PyTorch, Spark",Bachelor,12,Automotive,2024-02-28,2024-03-21,570,5.4,TechCorp Inc -AI11049,Robotics Engineer,118954,CAD,148693,SE,PT,Canada,L,Canada,100,"Python, PyTorch, Statistics",PhD,5,Government,2025-04-25,2025-05-15,2402,8.9,Cloud AI Solutions -AI11050,ML Ops Engineer,153938,CAD,192423,EX,CT,Canada,S,Canada,0,"PyTorch, Kubernetes, Scala, R, Data Visualization",Associate,16,Real Estate,2024-11-11,2024-12-29,1553,8.6,Advanced Robotics -AI11051,Deep Learning Engineer,131972,GBP,98979,MI,PT,United Kingdom,L,United Kingdom,100,"NLP, GCP, Python, Linux, Azure",Master,2,Manufacturing,2024-11-18,2024-12-21,2189,5.1,Advanced Robotics -AI11052,AI Product Manager,123154,USD,123154,EX,PT,Israel,S,Israel,50,"Data Visualization, Linux, Java",Bachelor,18,Energy,2024-07-29,2024-09-27,1275,7.4,Future Systems -AI11053,ML Ops Engineer,84249,JPY,9267390,MI,FL,Japan,M,Italy,50,"Java, NLP, Azure",Associate,4,Education,2024-04-25,2024-06-22,857,6.5,Smart Analytics -AI11054,Principal Data Scientist,93431,USD,93431,MI,PT,Sweden,S,Vietnam,50,"GCP, Tableau, Computer Vision, Linux",Associate,2,Finance,2025-02-04,2025-02-18,939,5,DataVision Ltd -AI11055,Computer Vision Engineer,135625,EUR,115281,EX,FL,France,M,France,0,"MLOps, Scala, NLP, PyTorch",Master,17,Gaming,2024-07-04,2024-08-28,1870,9.5,TechCorp Inc -AI11056,AI Product Manager,218295,EUR,185551,EX,PT,Austria,L,Austria,50,"SQL, Kubernetes, Docker, Tableau",Master,14,Gaming,2024-06-29,2024-08-03,1091,9.3,Predictive Systems -AI11057,ML Ops Engineer,99582,USD,99582,EN,FL,Denmark,L,Netherlands,100,"Linux, Data Visualization, PyTorch",Associate,1,Consulting,2025-03-29,2025-04-25,1168,9.6,Autonomous Tech -AI11058,Robotics Engineer,262079,GBP,196559,EX,FL,United Kingdom,L,United Kingdom,100,"Python, Java, Spark",Master,15,Technology,2024-02-06,2024-03-22,811,9.7,Smart Analytics -AI11059,AI Research Scientist,124785,USD,124785,SE,FT,Israel,M,Israel,50,"GCP, Scala, NLP, Kubernetes",Bachelor,7,Government,2024-12-19,2025-01-07,820,5.3,Cognitive Computing -AI11060,Autonomous Systems Engineer,78762,USD,78762,MI,FT,South Korea,S,South Korea,100,"TensorFlow, Python, Docker",Associate,3,Transportation,2024-01-05,2024-01-28,1893,8.9,Autonomous Tech -AI11061,Computer Vision Engineer,116968,JPY,12866480,MI,PT,Japan,M,Japan,50,"Java, R, Mathematics, Data Visualization, NLP",Bachelor,4,Manufacturing,2024-09-14,2024-10-25,2019,6.7,Machine Intelligence Group -AI11062,Machine Learning Researcher,82720,EUR,70312,MI,FT,Netherlands,M,Netherlands,0,"Data Visualization, Kubernetes, Azure",PhD,2,Telecommunications,2024-12-30,2025-03-08,812,9.1,DeepTech Ventures -AI11063,Data Analyst,105375,USD,105375,MI,FL,United States,M,United States,50,"TensorFlow, GCP, Azure, Hadoop",Master,3,Retail,2024-06-04,2024-07-24,1249,6.6,Algorithmic Solutions -AI11064,Computer Vision Engineer,123190,EUR,104712,EX,PT,Austria,S,Austria,50,"Data Visualization, AWS, Linux, Computer Vision, Statistics",Master,10,Real Estate,2024-07-11,2024-08-26,1042,9.7,DataVision Ltd -AI11065,ML Ops Engineer,277393,EUR,235784,EX,FL,Germany,L,Germany,0,"Kubernetes, Computer Vision, Git, Mathematics",Bachelor,17,Finance,2024-09-07,2024-11-01,996,5.5,DataVision Ltd -AI11066,Robotics Engineer,106542,EUR,90561,SE,FL,Germany,S,Germany,100,"Tableau, Java, Computer Vision",Bachelor,6,Media,2024-07-24,2024-09-12,547,8.7,DataVision Ltd -AI11067,NLP Engineer,94499,EUR,80324,MI,FL,France,L,Kenya,50,"Git, Java, MLOps, Computer Vision",Bachelor,2,Gaming,2024-02-12,2024-04-15,821,7.8,Quantum Computing Inc -AI11068,Autonomous Systems Engineer,189283,CHF,170355,SE,PT,Switzerland,M,Latvia,0,"Scala, GCP, Deep Learning",Master,8,Education,2024-06-16,2024-07-24,1321,9.7,Cloud AI Solutions -AI11069,Computer Vision Engineer,157133,EUR,133563,SE,FL,Germany,L,Germany,100,"Python, Git, Kubernetes, Deep Learning, R",Master,9,Finance,2024-08-07,2024-09-30,913,6.6,Algorithmic Solutions -AI11070,Robotics Engineer,258931,USD,258931,EX,FT,Denmark,S,Argentina,100,"Python, AWS, Docker",Associate,15,Government,2024-06-22,2024-07-31,1270,5.5,AI Innovations -AI11071,AI Specialist,94485,CAD,118106,MI,CT,Canada,M,Canada,50,"Java, Hadoop, SQL, Mathematics, GCP",Bachelor,3,Technology,2025-02-28,2025-03-23,1538,8.3,DataVision Ltd -AI11072,AI Architect,53437,USD,53437,EN,PT,Sweden,S,Sweden,50,"SQL, Hadoop, Linux",Bachelor,1,Government,2024-01-07,2024-02-08,980,9.9,Predictive Systems -AI11073,Computer Vision Engineer,81989,EUR,69691,MI,FT,France,S,Russia,100,"TensorFlow, Tableau, Mathematics, Java",Associate,2,Automotive,2024-03-08,2024-04-05,1163,7.1,Quantum Computing Inc -AI11074,AI Software Engineer,53872,GBP,40404,EN,PT,United Kingdom,S,Vietnam,100,"Python, SQL, Hadoop",PhD,1,Real Estate,2024-08-01,2024-09-27,1286,5.1,Predictive Systems -AI11075,AI Product Manager,112299,USD,112299,MI,PT,Finland,L,Finland,100,"Python, TensorFlow, Docker, PyTorch, Scala",Bachelor,4,Manufacturing,2024-05-06,2024-06-02,2011,8.1,AI Innovations -AI11076,Head of AI,148344,EUR,126092,EX,PT,Austria,M,Nigeria,50,"Git, Kubernetes, GCP, Tableau, MLOps",Associate,17,Education,2024-09-28,2024-11-09,1791,6.3,Future Systems -AI11077,AI Consultant,149732,AUD,202138,EX,PT,Australia,M,Australia,50,"Python, Git, NLP, Scala",PhD,19,Retail,2024-03-31,2024-04-28,1510,9.2,Cloud AI Solutions -AI11078,Research Scientist,86366,USD,86366,MI,FL,United States,S,United States,0,"Git, Scala, MLOps, R",PhD,4,Manufacturing,2025-04-23,2025-05-07,2253,7.7,Digital Transformation LLC -AI11079,AI Specialist,126508,USD,126508,MI,FL,Norway,S,Malaysia,0,"GCP, AWS, Data Visualization, Python, TensorFlow",Bachelor,3,Finance,2024-01-17,2024-03-07,1652,9.3,AI Innovations -AI11080,Data Scientist,88565,USD,88565,MI,FT,Israel,M,Malaysia,0,"MLOps, Mathematics, TensorFlow, GCP, AWS",Master,3,Media,2024-01-27,2024-02-19,1483,9.6,Future Systems -AI11081,AI Software Engineer,67656,USD,67656,EN,FT,Ireland,L,Czech Republic,0,"Python, Azure, Kubernetes",Associate,0,Retail,2024-06-20,2024-08-08,2044,6.3,Neural Networks Co -AI11082,AI Architect,112374,EUR,95518,MI,FT,Netherlands,L,Netherlands,50,"Scala, R, Spark",Associate,4,Retail,2025-01-11,2025-02-20,1000,6.6,DeepTech Ventures -AI11083,AI Research Scientist,117883,JPY,12967130,MI,PT,Japan,L,Japan,0,"Data Visualization, Hadoop, Linux",Master,3,Transportation,2024-01-15,2024-01-29,727,9.2,Autonomous Tech -AI11084,AI Software Engineer,121000,USD,121000,SE,FL,United States,M,China,100,"Java, Deep Learning, MLOps, Git",Bachelor,5,Media,2025-04-16,2025-05-28,2140,6.8,DeepTech Ventures -AI11085,Data Engineer,207170,CAD,258963,EX,FL,Canada,L,Canada,0,"TensorFlow, Statistics, Spark, SQL",Master,17,Healthcare,2024-10-28,2024-12-06,766,9.4,Smart Analytics -AI11086,AI Architect,116459,USD,116459,SE,FT,South Korea,L,South Korea,50,"Tableau, Azure, Java, NLP, R",Associate,5,Education,2025-04-25,2025-05-31,502,9.5,Predictive Systems -AI11087,Autonomous Systems Engineer,122703,CHF,110433,MI,FL,Switzerland,L,Switzerland,0,"Linux, Azure, Mathematics",PhD,2,Government,2024-12-26,2025-03-03,2270,8.4,Future Systems -AI11088,Computer Vision Engineer,97199,USD,97199,EN,CT,Norway,L,Norway,50,"Deep Learning, TensorFlow, Scala, Computer Vision, Linux",Bachelor,0,Gaming,2024-06-12,2024-07-22,2472,9,Future Systems -AI11089,Principal Data Scientist,290472,GBP,217854,EX,FT,United Kingdom,L,Italy,100,"Tableau, AWS, TensorFlow",Master,16,Media,2024-09-15,2024-10-23,1094,7.3,TechCorp Inc -AI11090,AI Specialist,81583,EUR,69346,EN,FL,France,L,France,100,"Spark, MLOps, Linux",Bachelor,1,Manufacturing,2024-04-08,2024-06-20,1025,9.5,Neural Networks Co -AI11091,Robotics Engineer,96594,USD,96594,MI,FT,Finland,L,Finland,50,"Linux, GCP, Tableau",Master,4,Media,2024-11-23,2025-01-26,1434,5.8,Algorithmic Solutions -AI11092,AI Consultant,64211,USD,64211,SE,FT,China,S,China,100,"R, Kubernetes, Tableau, Computer Vision, Azure",Master,7,Transportation,2024-01-19,2024-03-19,629,7,Future Systems -AI11093,Data Analyst,155715,EUR,132358,EX,CT,France,L,France,100,"Statistics, Mathematics, Data Visualization, Hadoop, Python",Master,18,Government,2024-04-25,2024-07-07,749,9.6,TechCorp Inc -AI11094,NLP Engineer,114469,USD,114469,MI,FT,Ireland,L,Switzerland,50,"Docker, Kubernetes, GCP",Associate,4,Media,2024-06-23,2024-07-09,556,8.2,Smart Analytics -AI11095,Autonomous Systems Engineer,90803,USD,90803,MI,FT,Ireland,S,India,100,"R, GCP, Computer Vision, Statistics",Bachelor,2,Gaming,2024-10-05,2024-10-29,983,7.6,Machine Intelligence Group -AI11096,Autonomous Systems Engineer,52790,USD,52790,EN,PT,Finland,S,Finland,0,"Kubernetes, R, Computer Vision, Java, Git",Associate,1,Gaming,2024-02-20,2024-04-06,637,9.2,Quantum Computing Inc -AI11097,AI Product Manager,123158,EUR,104684,SE,FL,Germany,S,Germany,50,"Linux, Tableau, Docker, Deep Learning",Bachelor,9,Gaming,2024-09-26,2024-11-06,1797,9.5,Predictive Systems -AI11098,NLP Engineer,136173,USD,136173,EX,FL,Ireland,M,Ireland,0,"Mathematics, Git, Scala",Bachelor,15,Finance,2024-03-06,2024-03-22,1892,9.9,AI Innovations -AI11099,AI Product Manager,33349,USD,33349,EN,FT,China,S,China,50,"AWS, Hadoop, MLOps, TensorFlow",PhD,1,Education,2025-02-15,2025-04-19,1995,9.9,Advanced Robotics -AI11100,Robotics Engineer,109691,USD,109691,EX,FL,China,L,China,100,"Git, PyTorch, SQL",PhD,12,Retail,2024-12-10,2025-01-27,542,8.7,Advanced Robotics -AI11101,AI Software Engineer,154172,USD,154172,SE,PT,Sweden,L,Sweden,50,"Scala, Deep Learning, Data Visualization, Tableau, Docker",Master,7,Real Estate,2024-12-03,2025-02-02,870,8.2,Quantum Computing Inc -AI11102,NLP Engineer,62316,AUD,84127,EN,FT,Australia,S,United States,100,"Python, AWS, Deep Learning, Kubernetes, Statistics",Associate,1,Finance,2024-09-14,2024-10-28,1518,7.6,Digital Transformation LLC -AI11103,Data Scientist,100179,USD,100179,SE,FT,Sweden,S,Finland,100,"Computer Vision, Mathematics, Linux, AWS",PhD,7,Transportation,2024-12-15,2025-01-25,722,9.9,Cognitive Computing -AI11104,Research Scientist,165296,SGD,214885,EX,FT,Singapore,S,Singapore,0,"NLP, SQL, Java, PyTorch",PhD,10,Consulting,2024-10-06,2024-11-08,1218,8.4,Predictive Systems -AI11105,Research Scientist,199699,AUD,269594,EX,FL,Australia,S,Australia,100,"Data Visualization, Python, Kubernetes, Deep Learning, Tableau",Associate,11,Technology,2024-11-10,2024-11-28,1954,8.6,Digital Transformation LLC -AI11106,Autonomous Systems Engineer,199230,USD,199230,SE,FL,Norway,L,Norway,0,"Azure, TensorFlow, Scala, Python, Java",Associate,8,Media,2025-04-19,2025-05-28,1359,8.2,Quantum Computing Inc -AI11107,Data Analyst,60772,AUD,82042,EN,PT,Australia,L,Australia,50,"Deep Learning, Linux, Data Visualization",Associate,0,Real Estate,2024-04-25,2024-06-22,2427,5.6,Machine Intelligence Group -AI11108,Head of AI,35534,USD,35534,MI,CT,China,S,China,50,"Python, TensorFlow, NLP, Scala",Bachelor,3,Finance,2024-01-16,2024-03-12,1054,7.2,Neural Networks Co -AI11109,Principal Data Scientist,127355,EUR,108252,SE,CT,France,S,Colombia,50,"GCP, Java, Scala, Data Visualization, Computer Vision",Associate,7,Healthcare,2025-02-09,2025-04-11,1012,7.9,Smart Analytics -AI11110,AI Research Scientist,150163,USD,150163,SE,PT,Sweden,M,Sweden,100,"Docker, Azure, Data Visualization, Spark, Kubernetes",Bachelor,8,Media,2025-03-16,2025-04-23,1933,6.9,Cognitive Computing -AI11111,Deep Learning Engineer,34278,USD,34278,SE,CT,India,S,India,0,"Data Visualization, Kubernetes, Scala, Statistics",Associate,8,Real Estate,2024-05-23,2024-06-29,550,8.4,Autonomous Tech -AI11112,Robotics Engineer,50385,JPY,5542350,EN,PT,Japan,S,Japan,0,"GCP, Kubernetes, Java, Spark",Bachelor,1,Energy,2024-01-17,2024-02-08,851,8.2,AI Innovations -AI11113,AI Software Engineer,127626,USD,127626,MI,FL,Norway,S,Nigeria,0,"Python, TensorFlow, Data Visualization",Bachelor,2,Technology,2024-09-05,2024-10-01,782,5.9,Predictive Systems -AI11114,Robotics Engineer,87121,USD,87121,EN,FL,Ireland,L,Ireland,0,"Python, Java, AWS, MLOps, Statistics",Master,0,Transportation,2024-07-14,2024-09-22,1394,6.5,AI Innovations -AI11115,Computer Vision Engineer,242532,EUR,206152,EX,FL,Austria,L,Czech Republic,50,"TensorFlow, GCP, Statistics, AWS",PhD,19,Transportation,2024-02-22,2024-04-09,2387,6.6,DataVision Ltd -AI11116,Autonomous Systems Engineer,42882,USD,42882,EN,PT,South Korea,S,Chile,50,"Data Visualization, Docker, Computer Vision, Hadoop",Master,0,Energy,2024-01-31,2024-03-28,2147,8.2,TechCorp Inc -AI11117,AI Software Engineer,63065,USD,63065,MI,CT,South Korea,S,Portugal,50,"SQL, Scala, Mathematics, R",PhD,2,Energy,2024-12-28,2025-02-24,1177,7.8,Smart Analytics -AI11118,Autonomous Systems Engineer,54039,USD,54039,SE,FL,China,S,China,100,"Spark, TensorFlow, Data Visualization",Associate,8,Healthcare,2025-02-05,2025-04-18,1353,5.6,Cognitive Computing -AI11119,Robotics Engineer,184798,JPY,20327780,EX,PT,Japan,L,South Africa,0,"Mathematics, Statistics, Python",Associate,18,Telecommunications,2025-02-07,2025-02-27,1660,9.1,TechCorp Inc -AI11120,Research Scientist,238260,USD,238260,EX,PT,Sweden,L,Sweden,100,"Python, TensorFlow, R, Computer Vision",Associate,12,Media,2025-04-16,2025-06-01,1703,5.3,Quantum Computing Inc -AI11121,Autonomous Systems Engineer,261853,USD,261853,EX,FL,Denmark,S,Denmark,100,"Docker, Linux, PyTorch",PhD,19,Finance,2024-01-28,2024-03-08,1113,8.7,Predictive Systems -AI11122,Data Engineer,239826,SGD,311774,EX,PT,Singapore,S,Singapore,0,"PyTorch, Linux, TensorFlow, SQL",Associate,16,Technology,2025-02-04,2025-02-18,2109,7.7,Predictive Systems -AI11123,Research Scientist,201246,EUR,171059,EX,CT,Germany,M,Germany,50,"Docker, Azure, Data Visualization",Associate,10,Transportation,2025-04-15,2025-05-27,2412,9.3,Machine Intelligence Group -AI11124,Data Engineer,109684,USD,109684,SE,CT,Finland,M,Finland,100,"Hadoop, R, Linux, Java, SQL",Associate,8,Manufacturing,2024-07-18,2024-09-07,876,5.8,Smart Analytics -AI11125,Data Analyst,83819,EUR,71246,MI,FT,Germany,L,Czech Republic,50,"R, Java, MLOps, Kubernetes",Master,2,Gaming,2024-02-25,2024-04-24,988,9.9,Cloud AI Solutions -AI11126,AI Software Engineer,61837,GBP,46378,EN,FT,United Kingdom,S,United Kingdom,50,"Python, GCP, Tableau, R",Bachelor,0,Telecommunications,2024-07-12,2024-09-14,2451,8,TechCorp Inc -AI11127,AI Architect,75517,GBP,56638,EN,FT,United Kingdom,S,Finland,50,"Data Visualization, TensorFlow, MLOps, Python",Bachelor,1,Retail,2024-11-24,2025-01-21,1177,7.3,AI Innovations -AI11128,NLP Engineer,131115,USD,131115,SE,CT,United States,S,United States,0,"TensorFlow, Python, PyTorch",Master,7,Energy,2024-11-27,2025-02-01,673,9.3,DataVision Ltd -AI11129,Data Engineer,169966,EUR,144471,EX,FL,France,S,Poland,50,"Hadoop, PyTorch, Statistics, Mathematics, Deep Learning",Bachelor,15,Consulting,2024-01-20,2024-02-27,529,6.3,DeepTech Ventures -AI11130,Head of AI,79201,USD,79201,EX,FT,India,S,India,50,"Docker, Python, Data Visualization, Scala",Master,10,Finance,2025-02-08,2025-03-08,2200,10,Predictive Systems -AI11131,AI Consultant,71991,EUR,61192,EN,FL,France,L,Israel,50,"Mathematics, GCP, Deep Learning",Bachelor,0,Transportation,2024-03-03,2024-04-05,2377,9.1,Cloud AI Solutions -AI11132,Data Engineer,211340,GBP,158505,EX,CT,United Kingdom,S,Nigeria,50,"NLP, Java, Kubernetes, Git",PhD,11,Automotive,2025-02-17,2025-04-27,921,9.3,TechCorp Inc -AI11133,Machine Learning Engineer,121942,USD,121942,SE,PT,Israel,S,Israel,100,"Kubernetes, GCP, SQL, Git",Associate,5,Healthcare,2024-06-08,2024-07-29,859,8.9,DataVision Ltd -AI11134,Principal Data Scientist,133708,CAD,167135,SE,FL,Canada,M,Canada,50,"Tableau, PyTorch, NLP",Associate,5,Education,2025-03-01,2025-04-24,1145,9.5,Advanced Robotics -AI11135,Data Scientist,128594,GBP,96446,MI,FT,United Kingdom,L,United Kingdom,0,"Statistics, R, PyTorch, TensorFlow",Associate,2,Automotive,2024-11-03,2024-11-19,895,9.7,Digital Transformation LLC -AI11136,Machine Learning Researcher,90783,EUR,77166,MI,PT,France,L,France,100,"R, Scala, NLP",Associate,4,Retail,2024-09-19,2024-11-13,1985,9.1,Neural Networks Co -AI11137,AI Product Manager,241386,GBP,181040,EX,CT,United Kingdom,S,United Kingdom,50,"Scala, Java, R",PhD,13,Technology,2024-03-19,2024-05-02,1706,6.4,Advanced Robotics -AI11138,Data Scientist,50199,USD,50199,EN,FL,South Korea,M,South Korea,50,"Azure, Hadoop, SQL",Master,0,Automotive,2025-03-05,2025-05-12,1284,9.4,TechCorp Inc -AI11139,Head of AI,69589,AUD,93945,EN,FL,Australia,S,Australia,0,"R, SQL, Data Visualization, Git",Bachelor,1,Transportation,2024-02-04,2024-04-10,2397,7.6,Autonomous Tech -AI11140,Data Analyst,249049,USD,249049,EX,FT,United States,L,United States,50,"Azure, Python, Tableau",Bachelor,19,Finance,2024-10-02,2024-11-20,708,5,Neural Networks Co -AI11141,Data Engineer,74973,USD,74973,EN,FT,United States,M,United States,0,"SQL, Kubernetes, AWS",PhD,1,Technology,2025-02-05,2025-03-23,2354,5.3,DeepTech Ventures -AI11142,AI Specialist,86870,USD,86870,MI,FL,Denmark,S,Australia,100,"NLP, SQL, R",PhD,4,Finance,2024-06-22,2024-08-11,1019,7.6,Cloud AI Solutions -AI11143,Robotics Engineer,132380,USD,132380,SE,FL,Israel,M,Israel,0,"Data Visualization, MLOps, SQL, R",Master,5,Energy,2024-08-18,2024-09-03,883,8.3,DeepTech Ventures -AI11144,AI Specialist,134074,EUR,113963,SE,FT,Germany,M,Germany,100,"Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,7,Manufacturing,2024-05-13,2024-06-13,1001,9.2,TechCorp Inc -AI11145,Autonomous Systems Engineer,29783,USD,29783,MI,PT,India,M,Australia,50,"Java, TensorFlow, AWS, Linux",Bachelor,2,Government,2024-11-25,2024-12-21,567,8.8,Neural Networks Co -AI11146,Autonomous Systems Engineer,129656,JPY,14262160,SE,FT,Japan,M,Japan,50,"Python, Kubernetes, Mathematics, MLOps",Associate,8,Media,2024-02-25,2024-05-03,1544,9.7,Smart Analytics -AI11147,AI Research Scientist,101315,USD,101315,SE,CT,Sweden,S,Sweden,50,"R, PyTorch, Azure, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-03-22,1720,8.1,Cognitive Computing -AI11148,Head of AI,154178,USD,154178,EX,FT,Israel,M,Austria,50,"Hadoop, Java, Mathematics",Bachelor,18,Government,2025-01-13,2025-03-16,2287,6.1,Cloud AI Solutions -AI11149,Data Scientist,71943,EUR,61152,EN,PT,Austria,L,Austria,50,"Docker, SQL, Python, AWS",Bachelor,0,Automotive,2024-03-13,2024-05-12,2360,5.5,Predictive Systems -AI11150,AI Research Scientist,187201,USD,187201,EX,FL,South Korea,M,Netherlands,50,"GCP, NLP, AWS",PhD,17,Gaming,2025-03-02,2025-05-12,1532,8.8,Machine Intelligence Group -AI11151,AI Software Engineer,69671,AUD,94056,MI,CT,Australia,S,Australia,100,"Python, Tableau, TensorFlow",Master,3,Healthcare,2024-08-18,2024-10-12,2262,6.6,Algorithmic Solutions -AI11152,Deep Learning Engineer,119940,AUD,161919,SE,CT,Australia,M,Australia,50,"SQL, PyTorch, TensorFlow, Deep Learning, Statistics",PhD,7,Gaming,2024-01-03,2024-03-14,1693,6.3,Future Systems -AI11153,Principal Data Scientist,102411,CHF,92170,MI,FL,Switzerland,S,Mexico,100,"Java, Hadoop, SQL, Computer Vision, Mathematics",Master,3,Healthcare,2024-08-23,2024-09-13,762,9.4,Neural Networks Co -AI11154,ML Ops Engineer,94579,CAD,118224,MI,FL,Canada,L,Canada,50,"PyTorch, GCP, Scala, Hadoop",Associate,4,Real Estate,2024-10-21,2024-12-09,813,8.3,Advanced Robotics -AI11155,Head of AI,93077,GBP,69808,EN,CT,United Kingdom,L,United Kingdom,100,"R, Deep Learning, Python, Statistics, Computer Vision",Associate,1,Finance,2024-06-19,2024-07-08,1504,5.2,Digital Transformation LLC -AI11156,AI Architect,215780,USD,215780,EX,FL,Denmark,L,Denmark,0,"Linux, Computer Vision, GCP, Azure",Master,15,Energy,2024-07-20,2024-09-13,2054,7.2,DataVision Ltd -AI11157,Machine Learning Researcher,123240,EUR,104754,SE,PT,Austria,M,Austria,0,"Kubernetes, Deep Learning, Docker, Statistics, Java",Bachelor,5,Education,2024-09-13,2024-10-09,1895,6.2,Predictive Systems -AI11158,Head of AI,172179,USD,172179,SE,PT,Denmark,M,Egypt,50,"GCP, R, MLOps, TensorFlow",Bachelor,6,Consulting,2024-08-30,2024-10-12,987,8.1,Digital Transformation LLC -AI11159,AI Software Engineer,211756,USD,211756,EX,PT,Sweden,L,Sweden,0,"Data Visualization, NLP, GCP",Master,10,Manufacturing,2024-07-04,2024-07-30,1708,7.2,Neural Networks Co -AI11160,Machine Learning Researcher,68820,USD,68820,MI,FL,South Korea,S,South Korea,50,"NLP, GCP, R, Data Visualization, Computer Vision",Master,4,Automotive,2025-01-03,2025-03-10,1419,9.4,Algorithmic Solutions -AI11161,Machine Learning Researcher,40630,USD,40630,EN,CT,South Korea,S,South Korea,0,"Git, Kubernetes, Hadoop, Java",PhD,1,Gaming,2025-02-28,2025-03-28,692,9.2,TechCorp Inc -AI11162,AI Product Manager,79533,EUR,67603,MI,FL,Austria,S,Israel,0,"NLP, SQL, PyTorch, Tableau, Docker",Associate,4,Manufacturing,2025-03-18,2025-05-02,1282,6.9,AI Innovations -AI11163,Data Engineer,85375,CHF,76838,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Scala, Linux, Docker, MLOps",PhD,0,Transportation,2024-09-14,2024-11-21,2017,7.8,DataVision Ltd -AI11164,Machine Learning Researcher,34517,USD,34517,MI,CT,China,S,China,50,"PyTorch, TensorFlow, MLOps, Java, R",Associate,3,Transportation,2024-02-18,2024-04-19,2242,9.2,AI Innovations -AI11165,Robotics Engineer,169364,USD,169364,EX,PT,Sweden,M,Sweden,0,"Data Visualization, PyTorch, TensorFlow, Statistics, Azure",Master,14,Real Estate,2025-01-06,2025-03-01,1951,9.6,Cognitive Computing -AI11166,AI Architect,118975,CAD,148719,SE,CT,Canada,L,Canada,50,"Python, Mathematics, Git, Computer Vision",PhD,6,Telecommunications,2024-11-26,2025-01-13,1063,7,Machine Intelligence Group -AI11167,AI Specialist,53965,USD,53965,SE,FL,India,L,India,100,"SQL, Java, PyTorch",Bachelor,5,Consulting,2024-01-13,2024-02-21,581,7.6,Neural Networks Co -AI11168,Principal Data Scientist,163916,USD,163916,EX,CT,Sweden,L,Sweden,0,"Data Visualization, Java, Tableau",Associate,19,Education,2024-03-01,2024-03-30,1789,8.4,Machine Intelligence Group -AI11169,Deep Learning Engineer,82346,USD,82346,MI,FT,Israel,M,New Zealand,0,"Azure, GCP, Deep Learning, Scala",Bachelor,2,Transportation,2024-03-31,2024-05-30,522,8.2,TechCorp Inc -AI11170,AI Specialist,124224,JPY,13664640,SE,FT,Japan,S,Japan,50,"Computer Vision, Python, Azure",Associate,8,Manufacturing,2024-01-18,2024-03-08,965,7.5,DataVision Ltd -AI11171,AI Consultant,141596,USD,141596,SE,CT,Finland,M,Denmark,100,"MLOps, Linux, Kubernetes, Python, Statistics",Bachelor,8,Healthcare,2025-04-29,2025-07-09,1133,8.3,Algorithmic Solutions -AI11172,AI Research Scientist,36117,USD,36117,MI,PT,India,L,Colombia,50,"Mathematics, Git, Python",Bachelor,2,Manufacturing,2024-04-04,2024-05-22,684,5.2,Smart Analytics -AI11173,Data Engineer,72859,USD,72859,MI,FT,Ireland,S,Thailand,100,"Deep Learning, TensorFlow, Git, SQL, Java",Bachelor,4,Real Estate,2024-06-19,2024-08-27,1261,7.3,Autonomous Tech -AI11174,AI Software Engineer,145568,GBP,109176,SE,FT,United Kingdom,S,Estonia,50,"AWS, Python, Tableau, Git",Associate,9,Finance,2024-05-03,2024-05-28,595,6.6,Predictive Systems -AI11175,NLP Engineer,81162,GBP,60872,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, Statistics, NLP, R",Master,4,Transportation,2024-01-29,2024-03-10,1900,7,Quantum Computing Inc -AI11176,NLP Engineer,222942,EUR,189501,EX,PT,Netherlands,M,Netherlands,100,"Docker, Scala, Computer Vision, Linux",Associate,13,Manufacturing,2024-09-15,2024-10-15,1315,8.7,Digital Transformation LLC -AI11177,Computer Vision Engineer,241236,AUD,325669,EX,FL,Australia,M,India,50,"Statistics, Python, R, Linux, SQL",Bachelor,11,Transportation,2024-09-22,2024-11-29,1590,9.6,Autonomous Tech -AI11178,Data Analyst,79043,CAD,98804,EN,FL,Canada,L,Canada,0,"R, Linux, Python, Java",Associate,1,Healthcare,2025-04-10,2025-05-19,556,6.3,Neural Networks Co -AI11179,AI Specialist,118334,USD,118334,MI,PT,United States,M,Chile,50,"GCP, MLOps, Scala, Python",Bachelor,4,Gaming,2024-12-23,2025-01-25,616,9.6,Autonomous Tech -AI11180,Head of AI,90117,USD,90117,SE,PT,Israel,S,Israel,0,"Linux, NLP, PyTorch, Git",PhD,7,Government,2024-08-16,2024-09-24,971,9.9,Neural Networks Co -AI11181,AI Software Engineer,174435,USD,174435,SE,PT,Denmark,L,Denmark,0,"Computer Vision, Kubernetes, Tableau, Linux, Mathematics",PhD,7,Retail,2025-03-17,2025-05-07,2391,6.2,Machine Intelligence Group -AI11182,Machine Learning Researcher,118598,USD,118598,SE,PT,Sweden,L,Sweden,100,"Azure, Python, Mathematics, Kubernetes, AWS",PhD,6,Manufacturing,2024-05-11,2024-07-23,2052,9,Quantum Computing Inc -AI11183,Robotics Engineer,37061,USD,37061,MI,PT,China,S,Argentina,0,"SQL, Docker, Kubernetes, MLOps",PhD,4,Transportation,2025-01-28,2025-02-19,2380,6,Algorithmic Solutions -AI11184,AI Product Manager,229849,EUR,195372,EX,FT,Netherlands,S,Netherlands,100,"Kubernetes, SQL, Computer Vision, Mathematics",Master,17,Technology,2024-10-03,2024-11-08,1912,6.5,Cloud AI Solutions -AI11185,AI Research Scientist,178162,CHF,160346,MI,PT,Switzerland,L,Switzerland,50,"Python, Kubernetes, TensorFlow",Bachelor,4,Education,2024-12-15,2025-01-26,1263,7.9,Advanced Robotics -AI11186,Data Engineer,175805,GBP,131854,EX,CT,United Kingdom,L,Canada,100,"Spark, AWS, Azure, GCP",Bachelor,10,Healthcare,2025-04-22,2025-06-03,984,7.2,DeepTech Ventures -AI11187,Autonomous Systems Engineer,105402,USD,105402,MI,FT,Sweden,L,New Zealand,50,"Computer Vision, Data Visualization, Java",Bachelor,3,Finance,2024-05-11,2024-07-02,2493,9.7,DeepTech Ventures -AI11188,AI Software Engineer,33884,USD,33884,MI,PT,India,M,Luxembourg,50,"PyTorch, GCP, TensorFlow, Scala, Kubernetes",PhD,2,Retail,2024-09-03,2024-11-12,1283,9.6,Machine Intelligence Group -AI11189,Computer Vision Engineer,60249,USD,60249,EN,FL,Ireland,M,Ireland,50,"Data Visualization, Azure, Tableau, TensorFlow, Statistics",Master,0,Education,2024-01-02,2024-02-24,1904,6.3,Digital Transformation LLC -AI11190,NLP Engineer,81942,USD,81942,MI,FT,Finland,M,Finland,100,"Data Visualization, Hadoop, Scala, Tableau",PhD,2,Finance,2025-01-25,2025-03-18,1325,8.5,Smart Analytics -AI11191,ML Ops Engineer,76583,AUD,103387,EN,FT,Australia,M,Belgium,0,"Docker, Spark, TensorFlow, AWS, Computer Vision",Master,1,Government,2024-06-22,2024-08-06,2483,8.6,Algorithmic Solutions -AI11192,AI Specialist,61080,USD,61080,SE,PT,India,L,India,50,"Java, MLOps, Data Visualization, Spark, Statistics",PhD,5,Consulting,2024-03-22,2024-05-14,2326,9.5,Cloud AI Solutions -AI11193,Data Engineer,129718,GBP,97289,SE,CT,United Kingdom,S,United Kingdom,0,"Python, TensorFlow, Docker",Associate,9,Consulting,2024-04-30,2024-07-07,1768,5.2,Cloud AI Solutions -AI11194,AI Specialist,89873,GBP,67405,MI,CT,United Kingdom,S,United Kingdom,100,"Azure, Linux, Tableau, Docker",Master,3,Consulting,2025-03-05,2025-04-11,692,5.9,Neural Networks Co -AI11195,Data Scientist,203419,USD,203419,EX,PT,Finland,S,Finland,100,"Python, Kubernetes, TensorFlow, MLOps, Tableau",Master,10,Manufacturing,2025-04-27,2025-05-27,1819,9.1,Machine Intelligence Group -AI11196,Machine Learning Engineer,154964,CHF,139468,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, Git, Computer Vision, TensorFlow",Bachelor,7,Manufacturing,2024-12-01,2025-01-13,1378,9.5,Autonomous Tech -AI11197,ML Ops Engineer,127404,USD,127404,EX,CT,Israel,S,Austria,100,"TensorFlow, Git, Python, Java",Bachelor,16,Transportation,2024-07-24,2024-09-08,2469,5.1,AI Innovations -AI11198,Head of AI,112946,EUR,96004,MI,PT,Austria,L,Austria,100,"Kubernetes, Linux, Scala, Java, Mathematics",Master,2,Real Estate,2024-10-23,2024-11-15,1555,5.3,AI Innovations -AI11199,Head of AI,166982,CHF,150284,SE,FL,Switzerland,L,Switzerland,0,"GCP, Kubernetes, Mathematics, AWS, Statistics",Master,5,Consulting,2024-04-18,2024-06-19,1128,7,Future Systems -AI11200,AI Architect,79897,USD,79897,EN,FT,Ireland,L,Ireland,0,"Java, Python, R, Kubernetes",Associate,1,Technology,2024-04-11,2024-04-29,1307,6,Algorithmic Solutions -AI11201,Machine Learning Researcher,199034,CHF,179131,EX,CT,Switzerland,S,Switzerland,0,"Linux, Deep Learning, Computer Vision, GCP, Git",PhD,13,Energy,2024-05-27,2024-06-14,2002,7.9,Advanced Robotics -AI11202,Robotics Engineer,121505,USD,121505,MI,CT,United States,L,Mexico,0,"Deep Learning, PyTorch, Kubernetes, Docker, TensorFlow",Bachelor,3,Transportation,2024-12-20,2025-02-22,505,9.6,Neural Networks Co -AI11203,AI Specialist,98949,EUR,84107,SE,FT,Austria,S,Austria,0,"SQL, Git, Docker, TensorFlow, NLP",Bachelor,9,Media,2024-03-12,2024-05-14,2235,7.3,Predictive Systems -AI11204,Autonomous Systems Engineer,175782,USD,175782,EX,PT,Sweden,S,Sweden,50,"Hadoop, GCP, NLP",Master,10,Automotive,2025-03-12,2025-05-08,909,7.6,Cloud AI Solutions -AI11205,Data Engineer,204328,EUR,173679,EX,CT,Netherlands,L,Russia,50,"Linux, R, Azure, Deep Learning",Associate,13,Automotive,2024-08-26,2024-10-17,747,7.8,Quantum Computing Inc -AI11206,Machine Learning Researcher,47111,USD,47111,EN,PT,Ireland,S,Ireland,50,"Python, Git, Hadoop, GCP, Deep Learning",Master,0,Transportation,2024-04-08,2024-05-01,2498,7.9,Smart Analytics -AI11207,Data Analyst,97477,GBP,73108,MI,PT,United Kingdom,S,United Kingdom,100,"Python, Docker, TensorFlow, Statistics, Java",Associate,3,Real Estate,2024-08-05,2024-09-09,1609,5.2,DeepTech Ventures -AI11208,ML Ops Engineer,45439,USD,45439,SE,CT,India,S,India,0,"Mathematics, SQL, Deep Learning, PyTorch",Associate,5,Manufacturing,2024-11-16,2024-12-24,1674,9.8,Quantum Computing Inc -AI11209,ML Ops Engineer,268419,GBP,201314,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, Spark, Python",Master,11,Technology,2024-07-12,2024-08-31,2445,5.6,DeepTech Ventures -AI11210,Head of AI,42030,USD,42030,MI,FT,India,L,Germany,50,"Git, Statistics, Data Visualization, Python, Deep Learning",Bachelor,2,Real Estate,2025-04-11,2025-06-18,1712,6.3,Quantum Computing Inc -AI11211,Research Scientist,134524,USD,134524,SE,FT,Finland,M,Finland,100,"PyTorch, MLOps, Deep Learning",Master,9,Real Estate,2024-03-21,2024-05-13,2193,9,Future Systems -AI11212,AI Research Scientist,178034,USD,178034,EX,FT,Israel,M,Chile,0,"PyTorch, Deep Learning, MLOps, Hadoop, Linux",Bachelor,19,Healthcare,2024-01-17,2024-03-28,2436,9.8,DeepTech Ventures -AI11213,AI Product Manager,79119,USD,79119,MI,PT,Sweden,S,Sweden,100,"Spark, Git, Statistics, Deep Learning, PyTorch",Associate,4,Manufacturing,2024-03-20,2024-05-11,1637,7.7,TechCorp Inc -AI11214,AI Product Manager,168770,USD,168770,EX,PT,Ireland,L,India,50,"PyTorch, TensorFlow, Docker, Mathematics",Associate,15,Transportation,2024-11-09,2024-12-28,1740,6.8,Cognitive Computing -AI11215,Machine Learning Researcher,65252,AUD,88090,EN,FT,Australia,M,Australia,100,"Computer Vision, Mathematics, NLP, Git, MLOps",Bachelor,1,Education,2025-01-15,2025-02-26,1035,6.7,DataVision Ltd -AI11216,Autonomous Systems Engineer,163792,GBP,122844,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, SQL, TensorFlow, Azure, Statistics",Associate,14,Retail,2024-07-25,2024-08-25,664,8.4,Cognitive Computing -AI11217,Machine Learning Engineer,196273,USD,196273,SE,FT,Norway,M,Thailand,0,"Mathematics, PyTorch, Scala, Azure",Master,5,Consulting,2024-09-30,2024-10-16,1052,7,Advanced Robotics -AI11218,Machine Learning Researcher,50242,EUR,42706,EN,CT,France,M,Australia,50,"Python, Java, NLP",Associate,0,Government,2025-03-31,2025-04-29,690,7.3,DeepTech Ventures -AI11219,Machine Learning Engineer,262801,USD,262801,EX,FL,Sweden,L,Sweden,50,"Data Visualization, SQL, Hadoop, MLOps",Associate,19,Transportation,2024-05-07,2024-06-14,1769,6.1,Advanced Robotics -AI11220,Data Analyst,61263,EUR,52074,EN,FL,Germany,L,Singapore,0,"Spark, Hadoop, Statistics, Linux, Python",PhD,0,Real Estate,2024-09-20,2024-10-22,892,9.5,Autonomous Tech -AI11221,ML Ops Engineer,146528,CHF,131875,MI,PT,Switzerland,M,Switzerland,50,"Azure, Python, TensorFlow, Docker",Associate,3,Consulting,2025-02-07,2025-03-22,2279,9.9,Predictive Systems -AI11222,AI Product Manager,163758,USD,163758,SE,FT,Norway,S,Norway,50,"Kubernetes, MLOps, Scala, AWS",Master,9,Media,2024-11-19,2024-12-18,1651,7.6,Algorithmic Solutions -AI11223,AI Research Scientist,166269,JPY,18289590,EX,CT,Japan,L,Japan,0,"Git, Python, Hadoop",Associate,16,Manufacturing,2024-04-18,2024-06-11,2443,8.9,Machine Intelligence Group -AI11224,Autonomous Systems Engineer,233000,EUR,198050,EX,CT,France,M,France,50,"Mathematics, Docker, Kubernetes",PhD,10,Healthcare,2025-01-02,2025-01-17,778,8,DeepTech Ventures -AI11225,AI Research Scientist,91649,USD,91649,MI,PT,United States,S,Ireland,50,"Java, Statistics, Data Visualization, Git, SQL",Associate,4,Media,2024-02-06,2024-03-14,1886,9.4,TechCorp Inc -AI11226,Machine Learning Researcher,152617,CHF,137355,SE,CT,Switzerland,M,Denmark,50,"Java, Mathematics, Kubernetes, Python, Scala",Bachelor,5,Transportation,2024-03-01,2024-04-18,2489,9,Autonomous Tech -AI11227,Deep Learning Engineer,111739,USD,111739,SE,FT,Finland,S,Finland,0,"TensorFlow, Tableau, Spark, GCP, SQL",Bachelor,5,Healthcare,2024-04-14,2024-05-19,2451,7.4,Algorithmic Solutions -AI11228,NLP Engineer,66659,EUR,56660,EN,PT,France,M,Mexico,50,"Tableau, Python, Scala",Bachelor,0,Automotive,2024-01-07,2024-01-22,1040,7.9,Cognitive Computing -AI11229,Machine Learning Engineer,186273,AUD,251469,EX,CT,Australia,L,Australia,50,"Data Visualization, Docker, Tableau, Java",Bachelor,14,Consulting,2024-05-25,2024-07-13,1691,5.6,Algorithmic Solutions -AI11230,AI Specialist,165955,USD,165955,EX,CT,Finland,L,India,100,"TensorFlow, Data Visualization, Tableau, Statistics, AWS",Bachelor,15,Education,2024-10-23,2024-11-29,603,8.8,AI Innovations -AI11231,Data Scientist,206355,EUR,175402,EX,CT,Germany,M,Germany,50,"Linux, Computer Vision, PyTorch, TensorFlow",PhD,14,Government,2024-09-09,2024-10-19,1908,5.4,Digital Transformation LLC -AI11232,Data Analyst,28132,USD,28132,EN,CT,India,M,Argentina,100,"Computer Vision, PyTorch, Spark",Bachelor,1,Energy,2025-01-05,2025-03-18,1774,7.4,Cloud AI Solutions -AI11233,Research Scientist,105432,USD,105432,EX,CT,China,M,China,0,"Spark, Kubernetes, Java, Statistics, TensorFlow",Bachelor,17,Energy,2024-07-19,2024-08-24,2474,7.7,Digital Transformation LLC -AI11234,Machine Learning Engineer,84482,USD,84482,EN,CT,United States,S,Malaysia,100,"Docker, Scala, NLP, AWS",Associate,1,Media,2024-06-27,2024-07-17,2399,5.2,Advanced Robotics -AI11235,Data Analyst,207967,USD,207967,EX,PT,Finland,S,Estonia,0,"Statistics, Mathematics, PyTorch",Master,11,Telecommunications,2024-02-17,2024-04-04,586,7.5,Machine Intelligence Group -AI11236,AI Product Manager,105835,USD,105835,MI,FT,Ireland,M,Ireland,0,"Azure, GCP, Git, AWS",PhD,4,Energy,2024-05-14,2024-07-20,1077,5.6,Predictive Systems -AI11237,Data Scientist,90084,USD,90084,MI,CT,Ireland,L,Japan,50,"R, SQL, Python, Spark, Deep Learning",Associate,3,Transportation,2025-03-24,2025-05-04,1376,5.1,Machine Intelligence Group -AI11238,AI Architect,70560,AUD,95256,EN,FT,Australia,M,Australia,50,"Python, TensorFlow, Java, Spark",Bachelor,0,Finance,2024-01-11,2024-03-09,1687,7.2,Neural Networks Co -AI11239,Data Scientist,119651,EUR,101703,SE,FL,France,S,France,0,"Linux, Python, Statistics, Kubernetes",Master,5,Media,2024-12-29,2025-03-11,1854,7.6,Digital Transformation LLC -AI11240,Deep Learning Engineer,81359,EUR,69155,EN,PT,Netherlands,L,Estonia,100,"Linux, Python, Spark, Computer Vision, Statistics",Bachelor,1,Consulting,2025-03-24,2025-05-11,607,8,Neural Networks Co -AI11241,Head of AI,94506,USD,94506,MI,CT,Ireland,M,Spain,0,"PyTorch, Deep Learning, MLOps",Master,3,Manufacturing,2024-02-08,2024-02-24,854,8.2,Digital Transformation LLC -AI11242,AI Consultant,57555,CAD,71944,EN,FT,Canada,S,Canada,0,"Git, Java, SQL",Bachelor,1,Gaming,2025-01-14,2025-03-01,993,8.6,TechCorp Inc -AI11243,AI Architect,58309,USD,58309,MI,FL,China,L,China,50,"Java, Linux, Tableau, Mathematics",Bachelor,4,Healthcare,2024-07-20,2024-09-03,671,7.1,Cognitive Computing -AI11244,Data Analyst,104581,USD,104581,MI,FT,United States,L,United States,100,"Python, Tableau, AWS",Associate,3,Retail,2024-02-07,2024-03-08,1281,9.1,Smart Analytics -AI11245,AI Architect,51087,USD,51087,SE,FT,China,M,China,50,"Data Visualization, Git, Kubernetes, Spark, R",PhD,8,Government,2024-01-22,2024-02-24,1657,7.2,Autonomous Tech -AI11246,Robotics Engineer,163866,CHF,147479,MI,FT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Deep Learning, AWS, Linux",PhD,3,Media,2024-04-01,2024-05-04,1667,5.9,DataVision Ltd -AI11247,Data Analyst,48310,USD,48310,EN,CT,Finland,M,Finland,50,"Data Visualization, Kubernetes, Scala",Associate,1,Transportation,2025-04-24,2025-05-29,1452,8.1,Digital Transformation LLC -AI11248,Machine Learning Engineer,189402,USD,189402,SE,FT,Denmark,L,Denmark,100,"Hadoop, GCP, Tableau, Computer Vision",Associate,8,Automotive,2025-03-05,2025-03-30,1720,6.8,Smart Analytics -AI11249,Robotics Engineer,30514,USD,30514,MI,FT,India,L,Czech Republic,0,"Python, Git, TensorFlow, Deep Learning, PyTorch",Bachelor,4,Media,2025-03-30,2025-04-13,1193,5.6,Predictive Systems -AI11250,AI Consultant,69642,GBP,52232,EN,PT,United Kingdom,L,Kenya,50,"Spark, Python, Computer Vision, Data Visualization, TensorFlow",Bachelor,0,Telecommunications,2024-09-17,2024-11-25,1878,10,Future Systems -AI11251,Head of AI,117224,JPY,12894640,SE,FT,Japan,S,South Africa,100,"AWS, R, PyTorch, Java, SQL",Bachelor,5,Media,2024-05-22,2024-06-16,2113,7.6,Digital Transformation LLC -AI11252,Computer Vision Engineer,100484,CAD,125605,MI,FL,Canada,L,Canada,50,"Java, Hadoop, PyTorch, AWS, TensorFlow",PhD,3,Consulting,2024-02-20,2024-04-02,2263,6.1,DeepTech Ventures -AI11253,AI Software Engineer,124618,CHF,112156,EN,PT,Switzerland,L,Switzerland,50,"Git, Python, R, Statistics",PhD,0,Transportation,2024-09-14,2024-10-05,1843,9.9,Future Systems -AI11254,AI Product Manager,191724,USD,191724,EX,FL,Ireland,S,Ireland,50,"Python, Hadoop, Spark, Docker",PhD,18,Education,2024-03-26,2024-06-01,2039,9.3,Machine Intelligence Group -AI11255,ML Ops Engineer,97569,USD,97569,EN,CT,Denmark,M,Denmark,100,"NLP, Statistics, SQL, PyTorch, Linux",Master,0,Education,2024-02-12,2024-03-25,2263,9.5,TechCorp Inc -AI11256,Computer Vision Engineer,118684,USD,118684,SE,CT,Finland,L,Finland,100,"Scala, Python, Statistics, Linux",PhD,9,Manufacturing,2024-08-29,2024-10-17,1785,6,DeepTech Ventures -AI11257,Deep Learning Engineer,80305,CHF,72275,EN,FL,Switzerland,S,Switzerland,50,"Git, GCP, SQL, Spark, Docker",PhD,1,Healthcare,2024-10-22,2024-12-02,1862,6.3,Machine Intelligence Group -AI11258,Principal Data Scientist,214921,USD,214921,EX,CT,Sweden,S,India,100,"Kubernetes, AWS, GCP, Git, Spark",PhD,17,Retail,2024-02-01,2024-03-15,1894,6,Predictive Systems -AI11259,AI Architect,178983,CHF,161085,SE,PT,Switzerland,L,Germany,100,"Java, TensorFlow, Hadoop",Associate,9,Transportation,2024-11-26,2024-12-30,1204,9.5,Algorithmic Solutions -AI11260,AI Product Manager,78327,USD,78327,MI,PT,Finland,L,Finland,50,"Spark, AWS, SQL, Tableau",Associate,4,Finance,2025-02-14,2025-03-28,2387,6.1,Predictive Systems -AI11261,Robotics Engineer,85793,USD,85793,EN,FL,Denmark,S,Denmark,0,"AWS, Java, GCP, PyTorch",Associate,0,Telecommunications,2024-07-25,2024-09-09,866,7.7,Predictive Systems -AI11262,AI Specialist,80644,EUR,68547,EN,FT,Netherlands,L,Netherlands,50,"Git, GCP, Java, Python, Computer Vision",Master,1,Energy,2025-04-08,2025-05-24,2017,6,DataVision Ltd -AI11263,AI Specialist,123929,SGD,161108,MI,CT,Singapore,L,Singapore,50,"PyTorch, TensorFlow, Mathematics, Deep Learning, Git",Bachelor,2,Automotive,2024-05-08,2024-06-25,1499,8.7,Algorithmic Solutions -AI11264,AI Research Scientist,108923,USD,108923,MI,FT,Finland,L,New Zealand,0,"Linux, Docker, Deep Learning, PyTorch",Master,4,Media,2024-09-28,2024-11-21,2273,9.3,AI Innovations -AI11265,Machine Learning Engineer,140940,USD,140940,SE,FL,South Korea,L,South Korea,50,"R, PyTorch, Computer Vision",Bachelor,9,Media,2024-10-03,2024-11-11,1587,8.4,Cognitive Computing -AI11266,NLP Engineer,315420,CHF,283878,EX,PT,Switzerland,L,Switzerland,100,"MLOps, SQL, PyTorch, Linux",PhD,13,Education,2024-10-14,2024-12-14,1791,9.4,TechCorp Inc -AI11267,Head of AI,71258,CAD,89073,EN,FL,Canada,M,Thailand,50,"GCP, Spark, Azure, PyTorch",Master,1,Technology,2024-05-29,2024-07-22,2017,5.9,Digital Transformation LLC -AI11268,Data Engineer,105428,JPY,11597080,MI,PT,Japan,L,Japan,0,"SQL, Python, Java, Tableau, TensorFlow",Associate,4,Technology,2025-03-29,2025-04-29,1302,5.6,Future Systems -AI11269,Data Scientist,167067,EUR,142007,EX,PT,France,L,Hungary,50,"Linux, PyTorch, Git, AWS, Java",Associate,12,Retail,2025-03-24,2025-04-15,1311,9.3,DeepTech Ventures -AI11270,Computer Vision Engineer,75062,USD,75062,EN,FT,Denmark,S,Denmark,50,"AWS, TensorFlow, Computer Vision, NLP",PhD,0,Gaming,2024-04-26,2024-06-17,2110,7,Cognitive Computing -AI11271,Computer Vision Engineer,54168,USD,54168,EX,FL,India,M,India,100,"Scala, PyTorch, Computer Vision, TensorFlow",PhD,10,Education,2024-04-09,2024-05-17,1658,7.9,Cognitive Computing -AI11272,Data Analyst,61930,SGD,80509,EN,PT,Singapore,M,Singapore,0,"Git, Computer Vision, SQL, Python, MLOps",Master,0,Consulting,2024-11-25,2025-01-08,1655,7.3,AI Innovations -AI11273,AI Product Manager,148519,EUR,126241,EX,PT,Austria,M,Austria,100,"Computer Vision, Data Visualization, Python",Master,11,Gaming,2025-04-27,2025-05-21,669,7.5,Smart Analytics -AI11274,Deep Learning Engineer,199528,USD,199528,EX,PT,Norway,S,Norway,100,"Python, Git, Computer Vision, TensorFlow",PhD,12,Finance,2024-02-08,2024-03-17,544,6.2,Quantum Computing Inc -AI11275,AI Architect,53596,USD,53596,EX,FL,India,S,India,50,"Azure, MLOps, Statistics, PyTorch, Computer Vision",Associate,11,Gaming,2024-11-09,2024-12-30,2407,9.4,Autonomous Tech -AI11276,Head of AI,97034,USD,97034,EN,CT,Denmark,M,Denmark,50,"PyTorch, Kubernetes, Deep Learning, Linux, Azure",Master,0,Media,2024-05-24,2024-07-01,1585,5.5,Cognitive Computing -AI11277,ML Ops Engineer,102547,AUD,138438,SE,FT,Australia,S,Australia,100,"Deep Learning, Python, Hadoop",Bachelor,5,Telecommunications,2024-05-07,2024-07-10,1872,7.2,Smart Analytics -AI11278,Machine Learning Engineer,63599,SGD,82679,EN,FT,Singapore,M,Singapore,50,"NLP, SQL, MLOps",Bachelor,1,Manufacturing,2024-10-17,2024-12-12,1319,6.6,Cloud AI Solutions -AI11279,Computer Vision Engineer,93730,EUR,79671,MI,FL,Austria,L,Austria,100,"Scala, Python, Mathematics, Kubernetes, Spark",Bachelor,4,Automotive,2024-11-08,2024-12-08,1254,6.8,DataVision Ltd -AI11280,AI Architect,205424,USD,205424,SE,FL,United States,L,Austria,100,"Data Visualization, Hadoop, Scala, PyTorch, Spark",Associate,7,Gaming,2024-04-03,2024-05-20,2330,8.7,Cognitive Computing -AI11281,Computer Vision Engineer,88065,USD,88065,EN,FL,Denmark,S,Denmark,100,"Linux, R, PyTorch, TensorFlow, Spark",Bachelor,1,Gaming,2025-03-23,2025-04-28,2085,5.6,Cloud AI Solutions -AI11282,ML Ops Engineer,115890,USD,115890,SE,FL,Israel,M,Israel,50,"PyTorch, GCP, Git",Master,9,Transportation,2024-11-04,2024-12-13,1762,7.5,AI Innovations -AI11283,Data Analyst,233264,SGD,303243,EX,CT,Singapore,S,Singapore,100,"Kubernetes, Scala, Tableau, Deep Learning",Associate,11,Telecommunications,2024-06-15,2024-08-03,814,6.1,Digital Transformation LLC -AI11284,AI Consultant,85232,EUR,72447,MI,FT,France,M,France,100,"Linux, Scala, Statistics, Python",PhD,3,Energy,2024-10-01,2024-11-26,2152,9.3,Predictive Systems -AI11285,AI Product Manager,125339,CHF,112805,MI,CT,Switzerland,M,Switzerland,0,"Python, Mathematics, Docker",PhD,2,Retail,2025-02-19,2025-05-02,1397,9.6,DataVision Ltd -AI11286,Research Scientist,185360,USD,185360,EX,CT,Ireland,L,Ireland,50,"NLP, Kubernetes, Docker, Python",Master,16,Retail,2024-01-23,2024-02-18,1618,7.8,Neural Networks Co -AI11287,Head of AI,106629,EUR,90635,MI,CT,France,L,France,0,"Data Visualization, Python, Azure, Scala",Bachelor,3,Retail,2025-02-06,2025-04-10,1496,8.7,Cloud AI Solutions -AI11288,Computer Vision Engineer,97894,USD,97894,EX,PT,India,L,India,0,"Scala, Java, Linux, R, SQL",PhD,13,Gaming,2025-01-01,2025-01-26,1062,9.3,Digital Transformation LLC -AI11289,Research Scientist,79189,USD,79189,EX,PT,India,M,Canada,50,"Java, Kubernetes, Scala",Master,12,Consulting,2024-05-06,2024-07-03,2204,9,Advanced Robotics -AI11290,AI Consultant,89489,JPY,9843790,MI,CT,Japan,L,Japan,50,"Docker, SQL, PyTorch",PhD,3,Retail,2024-11-24,2025-01-17,1809,6.4,AI Innovations -AI11291,Head of AI,119280,USD,119280,MI,CT,Israel,L,Netherlands,0,"Docker, Spark, Kubernetes, Scala, Mathematics",PhD,2,Manufacturing,2024-02-28,2024-05-05,716,7.1,DeepTech Ventures -AI11292,Robotics Engineer,219065,EUR,186205,EX,FT,Germany,S,Germany,0,"Python, Spark, Tableau",Associate,16,Manufacturing,2024-02-21,2024-03-13,800,7.6,TechCorp Inc -AI11293,Head of AI,218346,SGD,283850,EX,PT,Singapore,S,Singapore,50,"TensorFlow, Linux, GCP, Computer Vision, Deep Learning",Master,15,Finance,2024-05-22,2024-07-24,1652,9.7,Algorithmic Solutions -AI11294,AI Specialist,154420,SGD,200746,SE,CT,Singapore,M,Singapore,100,"Python, Git, Spark, Scala, Azure",Associate,7,Technology,2024-04-21,2024-06-29,645,8.8,Neural Networks Co -AI11295,AI Specialist,126566,USD,126566,SE,PT,Denmark,S,Norway,50,"Python, Data Visualization, Statistics",Bachelor,6,Consulting,2025-01-05,2025-01-28,1877,6.3,Cognitive Computing -AI11296,NLP Engineer,67525,AUD,91159,EN,FT,Australia,S,Australia,100,"Python, TensorFlow, Linux, AWS",Master,0,Gaming,2024-02-07,2024-04-03,1711,9.2,Digital Transformation LLC -AI11297,Research Scientist,130551,SGD,169716,SE,PT,Singapore,M,Singapore,0,"SQL, Kubernetes, Python, MLOps, Scala",Master,8,Telecommunications,2025-02-03,2025-03-04,890,7.7,Machine Intelligence Group -AI11298,Robotics Engineer,67815,USD,67815,EN,FL,Sweden,L,Sweden,0,"GCP, Scala, Kubernetes, Deep Learning",Master,1,Real Estate,2024-06-15,2024-07-30,2103,9.3,TechCorp Inc -AI11299,Data Scientist,26237,USD,26237,MI,CT,India,S,India,50,"MLOps, Git, SQL, Azure, Statistics",PhD,3,Transportation,2024-09-28,2024-11-27,850,5.9,Machine Intelligence Group -AI11300,Data Scientist,285608,SGD,371290,EX,PT,Singapore,L,Singapore,0,"PyTorch, Statistics, Computer Vision, GCP, Mathematics",PhD,10,Media,2025-01-09,2025-02-21,953,5.4,Autonomous Tech -AI11301,Machine Learning Engineer,73386,USD,73386,EN,FT,South Korea,L,South Korea,0,"Scala, Python, TensorFlow, Git, Hadoop",Associate,0,Manufacturing,2024-05-15,2024-07-03,1736,9.8,Autonomous Tech -AI11302,AI Specialist,24994,USD,24994,EN,CT,China,S,China,0,"Java, Kubernetes, GCP, Docker",Bachelor,0,Media,2024-04-08,2024-05-15,1010,7.6,Advanced Robotics -AI11303,Machine Learning Researcher,84205,AUD,113677,MI,FL,Australia,M,Australia,100,"Hadoop, MLOps, PyTorch, Scala, Kubernetes",Master,3,Energy,2024-06-17,2024-07-02,2481,9,Smart Analytics -AI11304,Deep Learning Engineer,167419,USD,167419,EX,FL,Israel,S,Australia,100,"AWS, Mathematics, Scala",Bachelor,11,Consulting,2024-08-10,2024-09-19,2109,6.1,Neural Networks Co -AI11305,Data Engineer,83819,EUR,71246,EN,CT,Austria,L,Austria,50,"Spark, Deep Learning, TensorFlow, Python, Git",Bachelor,1,Telecommunications,2025-04-05,2025-06-08,2018,7.8,Autonomous Tech -AI11306,Data Scientist,71467,USD,71467,EX,CT,China,M,China,100,"Python, Kubernetes, Tableau, Computer Vision",Master,11,Telecommunications,2024-09-05,2024-09-23,1673,5.8,Predictive Systems -AI11307,AI Specialist,150771,EUR,128155,SE,PT,Netherlands,L,Finland,0,"PyTorch, Kubernetes, Mathematics, Git",Master,5,Media,2025-02-08,2025-02-24,835,7.9,Cloud AI Solutions -AI11308,Autonomous Systems Engineer,187205,USD,187205,EX,FT,Finland,S,Finland,0,"Python, Scala, Git",Bachelor,15,Manufacturing,2024-05-09,2024-05-31,1333,9.2,Quantum Computing Inc -AI11309,AI Architect,25891,USD,25891,EN,FT,China,M,China,50,"SQL, Scala, Deep Learning",PhD,1,Automotive,2024-10-04,2024-12-05,2089,5.4,Cloud AI Solutions -AI11310,Machine Learning Researcher,62044,USD,62044,SE,CT,China,M,France,0,"Deep Learning, Statistics, SQL",Bachelor,5,Automotive,2025-02-13,2025-03-18,2477,6.4,DeepTech Ventures -AI11311,Data Scientist,155807,USD,155807,SE,CT,Israel,L,Israel,100,"Computer Vision, MLOps, Linux, TensorFlow",PhD,6,Real Estate,2024-07-22,2024-09-07,1354,9.4,Advanced Robotics -AI11312,Autonomous Systems Engineer,75916,EUR,64529,EN,FL,Netherlands,S,Netherlands,50,"TensorFlow, Mathematics, Java, MLOps, SQL",Associate,1,Gaming,2024-01-30,2024-03-29,708,7.8,Machine Intelligence Group -AI11313,Autonomous Systems Engineer,93324,SGD,121321,EN,FL,Singapore,L,Singapore,50,"Azure, GCP, Computer Vision, Deep Learning",PhD,1,Manufacturing,2024-04-18,2024-05-19,1592,9.6,Digital Transformation LLC -AI11314,Research Scientist,176161,EUR,149737,EX,FL,France,M,France,50,"Scala, Computer Vision, Azure",Bachelor,11,Real Estate,2024-12-10,2025-02-04,1294,9.5,Autonomous Tech -AI11315,ML Ops Engineer,135633,CAD,169541,SE,CT,Canada,L,Canada,100,"Python, GCP, TensorFlow",PhD,9,Manufacturing,2025-04-11,2025-05-30,2051,8,Future Systems -AI11316,Computer Vision Engineer,96084,USD,96084,MI,FT,Ireland,S,Thailand,50,"Kubernetes, Java, R, Deep Learning",Master,4,Real Estate,2024-06-19,2024-07-20,2346,9.6,AI Innovations -AI11317,AI Product Manager,229922,CHF,206930,EX,FT,Switzerland,M,Switzerland,50,"Python, TensorFlow, Scala, Kubernetes",Associate,15,Transportation,2025-01-14,2025-02-24,1777,7.5,Neural Networks Co -AI11318,AI Research Scientist,92771,USD,92771,EN,CT,Denmark,L,Denmark,50,"Git, Kubernetes, Python",Bachelor,1,Transportation,2024-09-10,2024-10-17,1267,9.4,Predictive Systems -AI11319,Machine Learning Engineer,137444,JPY,15118840,SE,FL,Japan,L,Japan,100,"Docker, Linux, Tableau, NLP, Mathematics",Associate,6,Energy,2024-01-14,2024-03-05,2117,5.1,Neural Networks Co -AI11320,Research Scientist,72988,CAD,91235,EN,FL,Canada,L,Canada,100,"Git, Python, Java, AWS, Scala",Associate,0,Automotive,2024-05-16,2024-06-12,1189,7.7,Smart Analytics -AI11321,Autonomous Systems Engineer,129227,USD,129227,SE,PT,Denmark,S,Denmark,0,"Python, TensorFlow, Git, Deep Learning",Bachelor,8,Automotive,2024-09-05,2024-10-31,1294,6.7,Future Systems -AI11322,ML Ops Engineer,84467,USD,84467,EN,FT,Ireland,L,Ireland,0,"SQL, Docker, Computer Vision",Master,0,Transportation,2025-01-15,2025-03-20,1191,9.7,Predictive Systems -AI11323,Data Analyst,98088,GBP,73566,MI,FL,United Kingdom,L,United Kingdom,0,"PyTorch, Mathematics, Git, Kubernetes, Python",Master,3,Government,2024-05-09,2024-07-11,988,7.3,Cloud AI Solutions -AI11324,Research Scientist,119116,USD,119116,SE,PT,Sweden,S,Sweden,100,"Docker, Linux, Mathematics, Deep Learning",PhD,9,Consulting,2024-03-26,2024-04-21,1723,6.2,Predictive Systems -AI11325,Autonomous Systems Engineer,181037,USD,181037,EX,FL,Ireland,M,Ireland,100,"Linux, Spark, NLP",PhD,18,Energy,2024-09-11,2024-11-23,1753,5.3,Digital Transformation LLC -AI11326,AI Consultant,79650,JPY,8761500,EN,FT,Japan,M,Thailand,50,"Tableau, GCP, PyTorch, MLOps, TensorFlow",PhD,1,Telecommunications,2025-04-06,2025-06-07,1950,9.7,Cognitive Computing -AI11327,Robotics Engineer,81235,CHF,73112,EN,FL,Switzerland,M,Switzerland,50,"R, Spark, Python, Azure",Bachelor,0,Government,2024-04-01,2024-06-08,1105,7.9,Neural Networks Co -AI11328,AI Architect,71268,EUR,60578,EN,CT,Netherlands,M,Netherlands,50,"Tableau, MLOps, Kubernetes, Scala, Mathematics",PhD,1,Telecommunications,2025-03-14,2025-04-10,630,5.3,Autonomous Tech -AI11329,AI Product Manager,227826,CAD,284783,EX,PT,Canada,M,Canada,50,"R, Scala, PyTorch, Python, Linux",Master,13,Technology,2024-08-30,2024-10-07,1875,6.1,Future Systems -AI11330,Robotics Engineer,96577,USD,96577,MI,PT,Ireland,L,Romania,50,"Deep Learning, Spark, Computer Vision, Scala",PhD,3,Energy,2025-04-18,2025-06-01,1204,7.4,Cognitive Computing -AI11331,Data Analyst,32109,USD,32109,EN,CT,China,L,China,0,"Git, NLP, Data Visualization, Mathematics, Linux",Associate,1,Transportation,2024-02-12,2024-03-10,2181,7.1,Smart Analytics -AI11332,AI Architect,125192,USD,125192,EX,PT,China,L,China,0,"MLOps, Deep Learning, R, SQL",Master,14,Manufacturing,2025-03-17,2025-04-21,1763,9.2,Quantum Computing Inc -AI11333,Machine Learning Researcher,70652,JPY,7771720,EN,FL,Japan,L,Japan,100,"Computer Vision, SQL, Linux, Tableau, Git",Bachelor,1,Transportation,2024-12-25,2025-01-15,2207,6,Quantum Computing Inc -AI11334,NLP Engineer,114477,USD,114477,SE,FT,South Korea,L,South Korea,100,"MLOps, Data Visualization, Azure, Docker",Master,7,Gaming,2024-07-12,2024-09-13,2184,7.6,TechCorp Inc -AI11335,Robotics Engineer,46341,USD,46341,EN,CT,South Korea,S,South Korea,100,"Kubernetes, Tableau, NLP, Spark, Linux",Associate,1,Technology,2024-04-05,2024-05-09,2226,7.3,Cognitive Computing -AI11336,Research Scientist,68397,USD,68397,MI,PT,Israel,M,Israel,50,"Tableau, Scala, GCP",Master,4,Automotive,2024-05-05,2024-06-27,1629,7.2,AI Innovations -AI11337,Machine Learning Researcher,87051,USD,87051,MI,FL,Finland,S,Finland,100,"Linux, Java, Data Visualization, Computer Vision",PhD,4,Government,2025-03-20,2025-04-11,1691,9.9,AI Innovations -AI11338,AI Architect,79887,USD,79887,EN,FT,United States,L,United States,0,"Computer Vision, SQL, R",Bachelor,0,Automotive,2025-02-24,2025-04-28,1084,8.7,Smart Analytics -AI11339,Deep Learning Engineer,134547,EUR,114365,EX,FT,France,S,Turkey,50,"Computer Vision, Python, Tableau, TensorFlow, Statistics",Associate,19,Consulting,2024-05-13,2024-07-07,2369,9.9,Algorithmic Solutions -AI11340,Deep Learning Engineer,108427,EUR,92163,MI,FL,Austria,L,Austria,0,"Tableau, GCP, Linux",Associate,2,Real Estate,2024-01-16,2024-02-05,2062,8.8,Smart Analytics -AI11341,Research Scientist,45769,EUR,38904,EN,FL,Austria,S,Canada,50,"Data Visualization, Hadoop, Mathematics, Kubernetes",Bachelor,1,Technology,2024-07-09,2024-08-09,2381,5.1,Digital Transformation LLC -AI11342,Research Scientist,65686,EUR,55833,EN,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, Git, Scala, MLOps",PhD,1,Telecommunications,2024-10-01,2024-12-09,1542,7.1,Future Systems -AI11343,AI Research Scientist,134629,USD,134629,EX,PT,Israel,M,Israel,0,"R, GCP, Docker, Kubernetes",Bachelor,16,Consulting,2025-04-07,2025-05-25,1542,8.7,Quantum Computing Inc -AI11344,Machine Learning Engineer,105266,USD,105266,EN,FT,Norway,L,Romania,100,"Python, TensorFlow, Kubernetes, PyTorch",Bachelor,0,Government,2024-10-01,2024-11-13,1447,8.2,AI Innovations -AI11345,ML Ops Engineer,111826,CAD,139783,SE,CT,Canada,L,New Zealand,0,"Linux, Python, AWS, SQL",Associate,9,Automotive,2025-02-26,2025-04-29,949,8.1,Advanced Robotics -AI11346,Robotics Engineer,97870,USD,97870,SE,FL,Sweden,S,Norway,0,"Spark, Deep Learning, R",Associate,8,Energy,2024-01-26,2024-03-14,582,9.6,Future Systems -AI11347,NLP Engineer,56233,USD,56233,SE,CT,China,S,China,50,"Tableau, SQL, PyTorch, MLOps, Docker",PhD,9,Manufacturing,2024-05-14,2024-07-03,710,6,TechCorp Inc -AI11348,Data Scientist,136380,AUD,184113,SE,CT,Australia,M,Australia,100,"Hadoop, Docker, Scala",Bachelor,5,Real Estate,2025-02-05,2025-03-17,711,8.6,Cloud AI Solutions -AI11349,Machine Learning Engineer,129432,USD,129432,SE,PT,Sweden,M,Sweden,0,"Linux, Azure, NLP, Statistics, AWS",Associate,7,Gaming,2025-04-13,2025-05-13,2032,8.1,AI Innovations -AI11350,Deep Learning Engineer,274081,USD,274081,EX,FT,Denmark,S,Luxembourg,0,"SQL, Spark, Statistics, Git, Python",Associate,17,Real Estate,2024-12-26,2025-02-23,1154,8.8,DataVision Ltd -AI11351,Data Engineer,70458,USD,70458,MI,PT,Finland,S,Finland,50,"Scala, SQL, Python, Spark, GCP",Bachelor,3,Telecommunications,2024-12-28,2025-01-25,1865,7.4,DataVision Ltd -AI11352,Deep Learning Engineer,54782,CAD,68478,EN,FT,Canada,S,Canada,50,"Hadoop, Data Visualization, AWS, TensorFlow",PhD,0,Government,2024-07-12,2024-08-29,2043,9.8,Advanced Robotics -AI11353,AI Research Scientist,64330,EUR,54681,EN,FT,Austria,M,Austria,100,"Deep Learning, Tableau, Python, Azure",Bachelor,0,Media,2024-03-05,2024-03-25,1355,7.6,Digital Transformation LLC -AI11354,Head of AI,253257,USD,253257,EX,PT,United States,L,United States,100,"GCP, Python, AWS",PhD,12,Transportation,2025-03-31,2025-05-04,950,7.9,Future Systems -AI11355,AI Research Scientist,72157,JPY,7937270,EN,CT,Japan,S,Japan,50,"Azure, Linux, R, Tableau",Associate,1,Gaming,2025-03-29,2025-04-21,1647,6.3,Digital Transformation LLC -AI11356,AI Specialist,79437,EUR,67521,EN,PT,Netherlands,M,Netherlands,100,"Tableau, Hadoop, Java",Master,0,Finance,2025-03-12,2025-03-29,566,6.8,Cognitive Computing -AI11357,AI Research Scientist,89807,USD,89807,EN,PT,Norway,S,Norway,100,"Docker, Spark, MLOps, Scala",Bachelor,0,Consulting,2024-02-28,2024-04-21,987,7.5,TechCorp Inc -AI11358,Data Engineer,223811,USD,223811,EX,FL,Norway,L,Norway,100,"Deep Learning, TensorFlow, NLP, Hadoop",Associate,13,Government,2025-02-10,2025-03-06,1630,6.3,Cloud AI Solutions -AI11359,Principal Data Scientist,43079,USD,43079,SE,CT,India,M,India,100,"MLOps, GCP, Java, PyTorch, Azure",Bachelor,7,Energy,2024-08-23,2024-10-24,781,9.2,Autonomous Tech -AI11360,Data Engineer,171228,SGD,222596,SE,FL,Singapore,L,Singapore,0,"Data Visualization, Hadoop, Python",Bachelor,7,Automotive,2024-12-23,2025-01-25,1585,7.1,DataVision Ltd -AI11361,AI Software Engineer,320305,USD,320305,EX,FT,United States,L,United States,50,"Scala, Hadoop, Tableau, MLOps, Spark",Associate,11,Healthcare,2025-03-05,2025-04-07,2126,9.8,Advanced Robotics -AI11362,AI Specialist,265506,CAD,331883,EX,FT,Canada,L,Canada,100,"AWS, Data Visualization, GCP, Linux",Bachelor,16,Retail,2025-03-18,2025-05-28,1455,7.6,Machine Intelligence Group -AI11363,AI Product Manager,191096,CHF,171986,SE,CT,Switzerland,S,Switzerland,100,"AWS, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-04-21,2025-06-06,1793,9.5,Machine Intelligence Group -AI11364,Computer Vision Engineer,46630,USD,46630,MI,PT,China,L,China,100,"Computer Vision, Mathematics, TensorFlow, Python",PhD,4,Healthcare,2024-01-19,2024-03-24,531,5.1,Cloud AI Solutions -AI11365,AI Specialist,97986,USD,97986,SE,FL,Ireland,S,Russia,100,"Python, GCP, TensorFlow, Java",PhD,5,Healthcare,2025-02-26,2025-03-27,686,8,AI Innovations -AI11366,ML Ops Engineer,136685,USD,136685,SE,PT,South Korea,L,South Korea,0,"PyTorch, AWS, Linux",Bachelor,5,Technology,2024-10-14,2024-11-27,784,6.5,Cloud AI Solutions -AI11367,ML Ops Engineer,90657,CAD,113321,MI,PT,Canada,M,Canada,0,"PyTorch, SQL, Mathematics",Bachelor,2,Automotive,2024-10-09,2024-12-10,991,9.8,AI Innovations -AI11368,Research Scientist,170307,USD,170307,SE,FT,United States,L,United States,100,"Azure, Git, AWS",PhD,9,Technology,2025-01-02,2025-03-08,2456,9,Advanced Robotics -AI11369,Deep Learning Engineer,137251,USD,137251,MI,CT,Denmark,L,Denmark,0,"Java, SQL, PyTorch, AWS",Bachelor,2,Telecommunications,2025-02-12,2025-03-07,2401,9.2,Future Systems -AI11370,Data Scientist,175338,USD,175338,EX,PT,Finland,L,Finland,100,"TensorFlow, R, Mathematics, GCP, Deep Learning",Associate,10,Government,2025-02-19,2025-03-09,602,9.1,Digital Transformation LLC -AI11371,Deep Learning Engineer,81903,JPY,9009330,EN,PT,Japan,L,Japan,100,"Scala, Java, GCP",PhD,1,Energy,2024-11-10,2024-11-27,2492,8.8,Predictive Systems -AI11372,Data Engineer,119281,SGD,155065,SE,FT,Singapore,S,Singapore,0,"SQL, Python, Tableau, Deep Learning, AWS",Bachelor,7,Transportation,2024-05-06,2024-07-01,579,6.1,Machine Intelligence Group -AI11373,Machine Learning Researcher,59467,USD,59467,EN,FT,South Korea,L,South Korea,100,"SQL, Git, PyTorch, Kubernetes, Java",PhD,1,Finance,2024-12-08,2025-01-06,1293,9.8,Neural Networks Co -AI11374,Head of AI,136127,EUR,115708,SE,FT,Germany,M,Germany,100,"Git, Computer Vision, Spark",Associate,8,Healthcare,2024-04-18,2024-06-18,1980,7.5,Algorithmic Solutions -AI11375,Deep Learning Engineer,150034,USD,150034,EX,FT,Israel,S,Israel,100,"AWS, Git, Python, TensorFlow, R",Master,19,Government,2025-02-12,2025-04-21,1236,8.8,Autonomous Tech -AI11376,Research Scientist,293963,EUR,249869,EX,FT,Netherlands,L,Netherlands,50,"Scala, NLP, AWS, Azure, Git",Bachelor,12,Manufacturing,2024-06-26,2024-07-24,1473,8,Cognitive Computing -AI11377,NLP Engineer,93910,USD,93910,EN,PT,Norway,M,South Korea,50,"R, Deep Learning, Git, Python, Docker",PhD,1,Energy,2024-11-19,2025-01-20,782,7.6,Predictive Systems -AI11378,AI Specialist,106154,CAD,132693,SE,FL,Canada,S,Canada,100,"Mathematics, Python, Statistics",PhD,9,Retail,2024-09-22,2024-11-24,869,7.9,AI Innovations -AI11379,Principal Data Scientist,83026,EUR,70572,EN,CT,Germany,L,Germany,100,"Java, R, Hadoop, Scala",Associate,1,Education,2025-02-15,2025-04-11,924,6.6,AI Innovations -AI11380,AI Consultant,62488,USD,62488,EX,FL,India,S,India,0,"Git, NLP, Kubernetes, AWS, Computer Vision",Master,10,Healthcare,2024-05-21,2024-07-22,1404,6.3,Cognitive Computing -AI11381,Data Engineer,82469,JPY,9071590,EN,FL,Japan,L,Japan,100,"PyTorch, TensorFlow, Mathematics, Deep Learning, Data Visualization",Associate,0,Telecommunications,2024-07-21,2024-09-18,1642,5.3,DeepTech Ventures -AI11382,AI Research Scientist,37153,USD,37153,MI,FL,India,M,India,100,"Java, R, GCP, MLOps, Docker",PhD,4,Energy,2024-02-14,2024-04-04,2213,8.1,Cloud AI Solutions -AI11383,Head of AI,100902,USD,100902,SE,PT,South Korea,L,South Korea,50,"Python, Java, Linux, TensorFlow",PhD,8,Education,2024-05-27,2024-07-13,1402,9.1,Predictive Systems -AI11384,Data Engineer,61167,SGD,79517,EN,FT,Singapore,S,Singapore,0,"Python, Java, SQL, Linux, NLP",Associate,1,Real Estate,2024-07-25,2024-09-17,1081,8,Advanced Robotics -AI11385,NLP Engineer,72149,USD,72149,EX,PT,India,L,Ukraine,100,"Python, GCP, Tableau",PhD,16,Education,2024-09-13,2024-11-18,917,8.4,Future Systems -AI11386,Machine Learning Engineer,145674,USD,145674,SE,FL,Finland,L,Finland,0,"Python, Docker, Hadoop",PhD,9,Finance,2025-03-06,2025-04-14,1983,9.4,Neural Networks Co -AI11387,NLP Engineer,121414,CAD,151768,SE,FL,Canada,M,Canada,50,"Linux, Hadoop, Tableau, SQL, Python",Bachelor,7,Education,2024-08-23,2024-10-12,890,6.6,Digital Transformation LLC -AI11388,ML Ops Engineer,78140,EUR,66419,EN,PT,France,L,France,100,"SQL, Git, Scala, Hadoop, NLP",Associate,1,Automotive,2024-12-14,2025-02-06,826,8.9,Digital Transformation LLC -AI11389,Head of AI,141442,USD,141442,SE,FL,United States,M,United States,50,"Kubernetes, AWS, Data Visualization",PhD,9,Real Estate,2025-03-26,2025-05-28,1718,8.5,Smart Analytics -AI11390,Machine Learning Researcher,96067,USD,96067,MI,CT,Israel,L,Israel,50,"Tableau, Spark, Hadoop",PhD,2,Healthcare,2025-04-20,2025-06-26,1870,7.7,Cloud AI Solutions -AI11391,Data Scientist,388535,CHF,349682,EX,CT,Switzerland,L,Egypt,50,"MLOps, Azure, Data Visualization, Scala, SQL",Master,16,Transportation,2024-06-20,2024-07-06,929,9.4,Predictive Systems -AI11392,Deep Learning Engineer,132494,CAD,165618,SE,FL,Canada,L,Canada,100,"Python, Kubernetes, Azure",PhD,6,Transportation,2024-01-25,2024-03-10,1687,8.1,Smart Analytics -AI11393,Machine Learning Engineer,66690,EUR,56687,MI,FT,Austria,S,New Zealand,50,"Docker, Statistics, Deep Learning, Azure, Scala",Bachelor,3,Automotive,2024-02-09,2024-03-23,868,9.6,DataVision Ltd -AI11394,Data Scientist,122287,GBP,91715,MI,PT,United Kingdom,L,United Kingdom,100,"AWS, Python, Spark",Bachelor,2,Retail,2024-09-12,2024-10-29,1159,6,Quantum Computing Inc -AI11395,Machine Learning Engineer,81923,USD,81923,EN,CT,Ireland,L,Ireland,0,"Python, TensorFlow, Git, Docker",Master,0,Real Estate,2025-03-05,2025-05-10,2422,7.5,Future Systems -AI11396,ML Ops Engineer,317576,USD,317576,EX,FL,Denmark,L,United States,100,"NLP, Tableau, SQL",Associate,16,Media,2024-10-17,2024-11-26,1252,8.1,TechCorp Inc -AI11397,AI Architect,111218,EUR,94535,SE,FT,Austria,S,Austria,0,"Mathematics, R, Computer Vision",Bachelor,6,Technology,2025-03-05,2025-03-20,2285,9,AI Innovations -AI11398,Data Engineer,137824,AUD,186062,EX,PT,Australia,S,Australia,0,"Java, SQL, Deep Learning, Azure, Computer Vision",Associate,13,Consulting,2025-02-14,2025-03-07,1942,6.7,Digital Transformation LLC -AI11399,Computer Vision Engineer,124975,EUR,106229,MI,PT,Netherlands,L,Netherlands,0,"Python, Linux, Scala, Data Visualization",Master,3,Automotive,2025-01-04,2025-02-02,1299,6,Digital Transformation LLC -AI11400,AI Product Manager,202807,SGD,263649,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Tableau",Bachelor,10,Finance,2024-05-11,2024-07-05,1842,7.1,Cognitive Computing -AI11401,AI Product Manager,225578,CHF,203020,EX,CT,Switzerland,S,Switzerland,50,"Docker, Azure, Python",Master,12,Technology,2025-01-06,2025-02-02,2234,5.7,Quantum Computing Inc -AI11402,Data Analyst,67004,EUR,56953,EN,CT,Austria,M,South Africa,0,"R, SQL, GCP, Computer Vision",Associate,1,Retail,2024-05-07,2024-06-07,1313,5.1,Smart Analytics -AI11403,NLP Engineer,91436,USD,91436,MI,PT,Finland,M,Ireland,0,"Data Visualization, Spark, SQL",PhD,4,Telecommunications,2024-12-14,2025-02-10,889,7.2,Machine Intelligence Group -AI11404,Data Engineer,190150,USD,190150,SE,CT,Denmark,M,Denmark,100,"Git, SQL, Tableau",Bachelor,5,Telecommunications,2024-10-10,2024-12-19,1116,6,AI Innovations -AI11405,Research Scientist,190516,AUD,257197,EX,CT,Australia,L,Australia,50,"AWS, SQL, Kubernetes, Python",Master,17,Healthcare,2024-01-22,2024-03-25,1876,8.5,Predictive Systems -AI11406,Machine Learning Engineer,113403,EUR,96393,MI,CT,Netherlands,L,Netherlands,100,"GCP, Computer Vision, Mathematics, SQL, Scala",Bachelor,3,Real Estate,2024-05-05,2024-07-10,2473,9.6,Smart Analytics -AI11407,AI Product Manager,206127,USD,206127,EX,FL,United States,M,Sweden,0,"Java, R, Computer Vision, Git",Master,16,Energy,2025-02-09,2025-03-15,1636,5.7,Predictive Systems -AI11408,Machine Learning Engineer,164366,USD,164366,SE,CT,Sweden,L,Sweden,100,"Scala, Data Visualization, Spark",Bachelor,8,Telecommunications,2024-09-16,2024-11-23,2292,5.6,TechCorp Inc -AI11409,Machine Learning Engineer,135548,CAD,169435,EX,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, GCP, Data Visualization",PhD,14,Automotive,2024-08-21,2024-10-29,731,8.5,Neural Networks Co -AI11410,Robotics Engineer,81926,EUR,69637,EN,CT,Netherlands,L,Singapore,0,"Data Visualization, Scala, AWS, Linux",Associate,1,Retail,2024-08-05,2024-10-07,1080,8.9,DeepTech Ventures -AI11411,NLP Engineer,61432,CAD,76790,MI,FT,Canada,S,Canada,0,"Python, NLP, Linux",Bachelor,4,Retail,2025-01-25,2025-03-22,1959,5.6,Quantum Computing Inc -AI11412,Data Engineer,82350,SGD,107055,EN,CT,Singapore,M,Austria,50,"Hadoop, Deep Learning, Kubernetes, Spark, NLP",PhD,1,Gaming,2024-03-29,2024-04-20,1918,8.6,Machine Intelligence Group -AI11413,Robotics Engineer,91758,USD,91758,EN,PT,Norway,L,Norway,0,"GCP, Docker, R",PhD,1,Media,2025-01-23,2025-02-24,1382,8.3,DataVision Ltd -AI11414,Head of AI,26320,USD,26320,MI,PT,India,M,India,100,"Scala, Python, Mathematics, SQL",Associate,4,Automotive,2024-11-16,2024-12-11,678,8.9,Digital Transformation LLC -AI11415,AI Research Scientist,181477,GBP,136108,SE,CT,United Kingdom,L,United Kingdom,100,"NLP, Python, Linux, Deep Learning, Scala",PhD,5,Finance,2024-07-14,2024-09-10,1750,9.9,DeepTech Ventures -AI11416,AI Product Manager,119031,CAD,148789,SE,FT,Canada,S,Canada,100,"R, PyTorch, Python, MLOps",Bachelor,7,Technology,2024-04-08,2024-05-15,1777,9,Advanced Robotics -AI11417,AI Consultant,199896,JPY,21988560,EX,CT,Japan,S,Japan,100,"Tableau, Computer Vision, Statistics",Associate,10,Healthcare,2024-06-16,2024-08-02,1371,8,Advanced Robotics -AI11418,Machine Learning Researcher,143700,CAD,179625,EX,FL,Canada,M,Norway,100,"Docker, MLOps, GCP, R",PhD,11,Technology,2025-04-17,2025-05-28,2111,5.4,Advanced Robotics -AI11419,Machine Learning Engineer,257865,GBP,193399,EX,CT,United Kingdom,M,United Kingdom,50,"AWS, Spark, TensorFlow, Docker",Bachelor,18,Retail,2025-03-28,2025-06-01,2455,6.7,DeepTech Ventures -AI11420,Data Engineer,88557,SGD,115124,MI,FL,Singapore,S,New Zealand,0,"Kubernetes, Git, Data Visualization",PhD,3,Finance,2024-09-11,2024-10-26,520,6.5,TechCorp Inc -AI11421,Computer Vision Engineer,170140,CAD,212675,EX,FT,Canada,S,Canada,0,"Tableau, PyTorch, Kubernetes, R, Linux",PhD,11,Healthcare,2024-09-27,2024-11-25,1734,5.4,DeepTech Ventures -AI11422,Data Engineer,78293,CAD,97866,MI,FL,Canada,L,Canada,100,"Python, SQL, Statistics, Docker, Java",Associate,2,Healthcare,2024-05-04,2024-06-06,2239,5.1,Machine Intelligence Group -AI11423,AI Product Manager,95607,USD,95607,EN,CT,Norway,M,Norway,0,"GCP, Git, Java, Azure",Bachelor,0,Consulting,2024-07-28,2024-08-16,1686,8.9,Smart Analytics -AI11424,Data Analyst,75288,USD,75288,EN,FT,United States,L,Ghana,50,"Git, Hadoop, Tableau, Linux",Master,1,Healthcare,2024-05-05,2024-06-29,1636,7.1,Advanced Robotics -AI11425,Data Engineer,99770,CHF,89793,MI,FT,Switzerland,S,Switzerland,100,"Tableau, Docker, Deep Learning, Python, Hadoop",Master,2,Retail,2024-08-13,2024-09-16,2414,6.4,Predictive Systems -AI11426,AI Product Manager,107307,EUR,91211,SE,PT,Germany,S,Germany,0,"Tableau, Hadoop, NLP, GCP",Associate,5,Government,2024-03-01,2024-04-25,1825,8.6,DataVision Ltd -AI11427,NLP Engineer,80388,CAD,100485,MI,PT,Canada,S,Australia,0,"Java, SQL, AWS",Master,4,Automotive,2024-03-17,2024-05-17,2261,5.8,AI Innovations -AI11428,AI Consultant,43320,USD,43320,MI,FL,India,L,India,0,"Java, SQL, Scala, Statistics, AWS",Associate,3,Gaming,2024-02-01,2024-04-05,1139,6.7,Digital Transformation LLC -AI11429,AI Product Manager,49686,USD,49686,EX,FL,India,S,India,0,"Spark, Mathematics, Linux, Python",Associate,14,Media,2024-07-22,2024-09-30,1729,5.2,Smart Analytics -AI11430,AI Consultant,41656,USD,41656,MI,FT,China,S,Romania,100,"Python, Java, MLOps, Git",Bachelor,4,Gaming,2024-02-09,2024-03-01,1449,9.6,DataVision Ltd -AI11431,Data Engineer,149191,USD,149191,EX,FT,South Korea,S,South Korea,50,"SQL, Mathematics, MLOps",Bachelor,13,Real Estate,2025-02-25,2025-04-05,2473,6.1,DataVision Ltd -AI11432,Data Analyst,70858,USD,70858,MI,FL,South Korea,S,Canada,100,"Python, PyTorch, Statistics, Data Visualization",Bachelor,4,Government,2024-02-23,2024-05-02,1997,7,TechCorp Inc -AI11433,AI Software Engineer,112994,EUR,96045,SE,FT,France,S,France,100,"TensorFlow, NLP, SQL, Hadoop, Spark",Bachelor,8,Technology,2024-06-16,2024-08-08,1673,5.6,Neural Networks Co -AI11434,NLP Engineer,81456,USD,81456,MI,FL,South Korea,L,South Korea,100,"Tableau, TensorFlow, PyTorch",Bachelor,2,Finance,2024-11-08,2024-11-22,515,5.2,TechCorp Inc -AI11435,Head of AI,54011,EUR,45909,EN,CT,Austria,M,Austria,0,"Deep Learning, PyTorch, Statistics, Computer Vision, R",Master,1,Consulting,2024-10-20,2024-11-08,1295,7.9,Algorithmic Solutions -AI11436,AI Specialist,85091,USD,85091,EN,PT,Denmark,M,Denmark,100,"Mathematics, Spark, Kubernetes",Associate,1,Energy,2024-02-15,2024-04-03,780,6.5,TechCorp Inc -AI11437,AI Software Engineer,115899,USD,115899,EN,PT,Norway,L,Norway,50,"PyTorch, Mathematics, Tableau, Spark",PhD,0,Media,2025-01-11,2025-03-10,2231,6,AI Innovations -AI11438,Research Scientist,89371,JPY,9830810,MI,FL,Japan,M,Japan,0,"GCP, Azure, Tableau, MLOps",PhD,2,Manufacturing,2025-02-13,2025-03-21,1803,8.4,Future Systems -AI11439,Principal Data Scientist,125683,EUR,106831,SE,FT,Netherlands,M,Netherlands,50,"SQL, Java, Python, Azure, R",PhD,9,Education,2025-02-08,2025-03-27,1423,8.8,AI Innovations -AI11440,AI Research Scientist,349284,CHF,314356,EX,PT,Switzerland,L,Switzerland,100,"Python, TensorFlow, Docker, Deep Learning",Bachelor,13,Retail,2025-04-05,2025-04-25,1937,5.4,Cognitive Computing -AI11441,Data Scientist,140809,EUR,119688,EX,PT,Netherlands,S,Denmark,0,"Python, TensorFlow, MLOps, Scala, Java",Associate,18,Government,2024-03-19,2024-05-05,1264,6.7,Algorithmic Solutions -AI11442,Machine Learning Engineer,69956,USD,69956,MI,CT,Finland,S,Finland,100,"R, PyTorch, NLP, Scala",Master,4,Media,2024-03-14,2024-05-13,841,9.4,Digital Transformation LLC -AI11443,Autonomous Systems Engineer,71681,EUR,60929,EN,FL,France,M,Belgium,0,"Deep Learning, Computer Vision, Tableau, Python, Azure",PhD,0,Transportation,2025-04-18,2025-05-09,1084,7.6,AI Innovations -AI11444,NLP Engineer,215291,CAD,269114,EX,FL,Canada,L,Canada,50,"R, SQL, Computer Vision, GCP, Kubernetes",Associate,15,Technology,2024-08-14,2024-09-27,2204,9.3,DataVision Ltd -AI11445,Computer Vision Engineer,22321,USD,22321,EN,FL,India,S,India,0,"Deep Learning, Java, Statistics, Hadoop, Scala",PhD,1,Gaming,2024-09-09,2024-11-01,1646,9.2,TechCorp Inc -AI11446,Machine Learning Researcher,107424,USD,107424,MI,FT,United States,S,United States,100,"Git, Docker, Python, Azure, Computer Vision",PhD,2,Finance,2025-01-17,2025-02-01,759,7.8,Digital Transformation LLC -AI11447,AI Product Manager,97858,AUD,132108,MI,FT,Australia,S,Sweden,100,"Git, Kubernetes, MLOps, Tableau, GCP",PhD,2,Telecommunications,2024-11-12,2024-12-27,948,5.5,DeepTech Ventures -AI11448,Head of AI,131805,USD,131805,SE,PT,Finland,L,Finland,100,"Kubernetes, MLOps, Azure, Deep Learning, Scala",Master,9,Manufacturing,2024-11-12,2024-12-13,1137,7.9,Cloud AI Solutions -AI11449,AI Product Manager,168977,EUR,143630,SE,FL,Germany,L,Norway,0,"Data Visualization, MLOps, PyTorch, Deep Learning",PhD,5,Media,2024-08-24,2024-10-29,1876,6.1,DeepTech Ventures -AI11450,Computer Vision Engineer,112692,USD,112692,SE,CT,Israel,M,Israel,100,"Scala, Kubernetes, Azure",Associate,5,Energy,2024-06-25,2024-08-20,2010,7.9,DataVision Ltd -AI11451,NLP Engineer,24819,USD,24819,EN,FL,India,S,India,100,"Spark, Deep Learning, Tableau",Bachelor,0,Retail,2024-10-01,2024-11-24,916,6.4,Cognitive Computing -AI11452,Autonomous Systems Engineer,50429,USD,50429,MI,CT,China,M,China,0,"AWS, Azure, R, Computer Vision",PhD,4,Transportation,2024-05-08,2024-07-17,2418,7.6,Algorithmic Solutions -AI11453,AI Product Manager,92616,CAD,115770,MI,PT,Canada,L,Canada,100,"TensorFlow, Mathematics, Tableau",PhD,4,Energy,2024-08-22,2024-09-17,1475,6.8,Predictive Systems -AI11454,AI Architect,149371,USD,149371,MI,PT,United States,L,Spain,100,"PyTorch, Azure, Kubernetes, TensorFlow",Bachelor,3,Healthcare,2025-01-02,2025-02-23,2177,6.7,Autonomous Tech -AI11455,Machine Learning Engineer,235873,CHF,212286,EX,PT,Switzerland,S,Brazil,100,"Java, Git, Docker, MLOps",Master,10,Consulting,2024-06-26,2024-09-03,1795,8.8,Smart Analytics -AI11456,AI Consultant,46440,USD,46440,EN,FT,South Korea,S,South Korea,0,"Kubernetes, Spark, NLP, Git, Python",Associate,0,Transportation,2024-05-04,2024-05-27,536,5.3,Neural Networks Co -AI11457,Computer Vision Engineer,227078,EUR,193016,EX,PT,Netherlands,M,Romania,0,"R, Spark, Scala, Python",PhD,14,Media,2024-12-27,2025-01-28,937,7.2,Autonomous Tech -AI11458,Robotics Engineer,63953,EUR,54360,EN,FL,Netherlands,M,Netherlands,100,"AWS, Python, Tableau, TensorFlow",Associate,0,Manufacturing,2024-11-13,2024-12-05,662,5.3,Cloud AI Solutions -AI11459,AI Software Engineer,77328,EUR,65729,MI,FL,Germany,S,Germany,0,"Spark, Scala, PyTorch, Linux",Bachelor,2,Technology,2024-05-01,2024-05-22,2423,7.8,Neural Networks Co -AI11460,AI Product Manager,64672,USD,64672,EN,CT,Sweden,L,Latvia,50,"TensorFlow, R, Spark, Python, Azure",PhD,0,Real Estate,2024-11-21,2024-12-14,1484,7.3,Digital Transformation LLC -AI11461,AI Product Manager,103343,GBP,77507,MI,CT,United Kingdom,S,Switzerland,100,"TensorFlow, Data Visualization, Linux, Mathematics, Kubernetes",PhD,3,Finance,2024-03-05,2024-05-08,1183,8.8,Quantum Computing Inc -AI11462,NLP Engineer,99987,EUR,84989,MI,CT,Netherlands,S,Netherlands,50,"Spark, Linux, Data Visualization, Python",Master,3,Education,2025-01-12,2025-01-26,2303,6.5,Machine Intelligence Group -AI11463,NLP Engineer,37144,USD,37144,MI,PT,China,M,China,0,"Mathematics, Scala, SQL, Python",Master,3,Media,2024-04-01,2024-05-23,2408,5.5,Predictive Systems -AI11464,Head of AI,239050,JPY,26295500,EX,FL,Japan,M,Japan,50,"Azure, SQL, Hadoop",Master,17,Government,2024-11-03,2024-12-21,1181,6.4,DataVision Ltd -AI11465,Research Scientist,63804,USD,63804,EN,FL,Ireland,M,Ireland,50,"MLOps, Mathematics, Statistics, AWS",Bachelor,1,Finance,2024-10-02,2024-10-22,1980,8,Predictive Systems -AI11466,AI Research Scientist,121719,USD,121719,MI,PT,Sweden,L,Germany,50,"Statistics, Hadoop, Deep Learning, R",Master,2,Automotive,2024-11-23,2024-12-15,1865,5.7,DataVision Ltd -AI11467,Robotics Engineer,318346,USD,318346,EX,FL,Norway,M,Norway,50,"Python, TensorFlow, Java",Associate,10,Telecommunications,2024-04-10,2024-06-17,1715,9.3,AI Innovations -AI11468,NLP Engineer,113713,JPY,12508430,SE,PT,Japan,M,Philippines,0,"Java, SQL, Python, TensorFlow, PyTorch",Associate,9,Technology,2024-07-22,2024-09-19,2127,9.1,TechCorp Inc -AI11469,Research Scientist,129110,CAD,161388,SE,FL,Canada,M,Canada,100,"Scala, AWS, Computer Vision, Statistics, Mathematics",Associate,6,Real Estate,2024-04-24,2024-06-15,1850,8.8,Quantum Computing Inc -AI11470,Research Scientist,76550,USD,76550,EN,FT,United States,S,France,0,"SQL, Statistics, R",Associate,1,Telecommunications,2024-03-21,2024-05-01,972,7.6,Neural Networks Co -AI11471,AI Software Engineer,160981,JPY,17707910,EX,CT,Japan,S,Japan,100,"Kubernetes, Computer Vision, NLP",Associate,19,Retail,2024-09-04,2024-10-19,2152,9.3,Cloud AI Solutions -AI11472,AI Software Engineer,249798,CHF,224818,EX,FL,Switzerland,L,Switzerland,100,"Azure, Deep Learning, Spark, Linux, NLP",PhD,13,Real Estate,2024-08-29,2024-10-23,854,7.2,Cloud AI Solutions -AI11473,AI Specialist,110277,USD,110277,MI,CT,Ireland,L,Ireland,0,"Python, Java, Tableau, Spark",PhD,4,Telecommunications,2024-09-11,2024-10-19,1386,5.6,Quantum Computing Inc -AI11474,AI Architect,314219,USD,314219,EX,CT,Denmark,M,Denmark,100,"Python, Azure, Scala",Bachelor,19,Transportation,2025-02-02,2025-03-29,1389,7.3,Quantum Computing Inc -AI11475,Data Analyst,335263,CHF,301737,EX,FL,Switzerland,L,Switzerland,100,"Statistics, SQL, GCP",Master,14,Consulting,2024-09-25,2024-11-23,1870,7.4,Quantum Computing Inc -AI11476,Machine Learning Engineer,124417,CHF,111975,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, SQL, MLOps, Linux",PhD,2,Gaming,2024-04-26,2024-05-25,2021,8.9,DataVision Ltd -AI11477,AI Research Scientist,124130,USD,124130,SE,FL,Finland,M,Finland,0,"Scala, Hadoop, R, Linux, NLP",Associate,8,Education,2024-06-03,2024-07-07,1239,6.5,Machine Intelligence Group -AI11478,Machine Learning Researcher,80925,USD,80925,EN,FL,United States,S,Netherlands,50,"Python, Kubernetes, Data Visualization, Azure",Master,0,Finance,2024-10-06,2024-11-03,1923,8.3,Quantum Computing Inc -AI11479,Head of AI,79342,USD,79342,MI,CT,Ireland,M,Colombia,100,"Linux, Java, Scala",Master,3,Healthcare,2024-03-18,2024-05-25,1291,9.5,Digital Transformation LLC -AI11480,Autonomous Systems Engineer,97152,USD,97152,EN,CT,United States,L,United States,0,"PyTorch, Scala, Tableau",Bachelor,0,Technology,2025-02-08,2025-04-13,2187,7,Machine Intelligence Group -AI11481,Machine Learning Engineer,142004,EUR,120703,SE,FT,France,L,France,0,"SQL, Computer Vision, AWS",Associate,6,Automotive,2024-02-25,2024-05-05,731,8.5,Future Systems -AI11482,Computer Vision Engineer,147965,USD,147965,SE,PT,United States,M,United States,50,"Azure, Java, GCP",PhD,7,Consulting,2024-03-21,2024-05-08,2334,7.9,Predictive Systems -AI11483,Deep Learning Engineer,192037,USD,192037,EX,CT,Ireland,L,Ireland,50,"Java, Docker, NLP",Bachelor,10,Real Estate,2024-01-11,2024-02-08,1028,5.9,DeepTech Ventures -AI11484,Data Scientist,127383,EUR,108276,SE,FL,France,M,South Korea,0,"Kubernetes, Hadoop, Linux, GCP",PhD,9,Finance,2024-10-29,2024-12-30,1853,8.4,DeepTech Ventures -AI11485,Principal Data Scientist,85256,EUR,72468,MI,CT,Netherlands,S,Netherlands,50,"Scala, Mathematics, Python, Spark, GCP",PhD,3,Healthcare,2024-05-31,2024-08-06,899,5.5,Cloud AI Solutions -AI11486,Data Analyst,191885,USD,191885,SE,CT,Norway,L,Norway,50,"PyTorch, Python, Data Visualization",Bachelor,7,Consulting,2024-04-19,2024-06-15,2006,8.6,DataVision Ltd -AI11487,Data Engineer,106706,USD,106706,SE,FL,Israel,S,Israel,100,"Docker, Git, NLP, MLOps",Bachelor,6,Gaming,2025-03-24,2025-05-22,1323,7.6,Advanced Robotics -AI11488,AI Product Manager,144625,USD,144625,SE,FT,Ireland,L,Ireland,50,"Scala, Python, SQL, Mathematics",Bachelor,6,Government,2025-02-07,2025-04-08,2418,6.6,Machine Intelligence Group -AI11489,NLP Engineer,89096,GBP,66822,MI,CT,United Kingdom,L,United Kingdom,0,"R, SQL, Tableau, Statistics, Azure",PhD,4,Government,2025-02-17,2025-04-27,944,8.8,Predictive Systems -AI11490,AI Product Manager,113094,USD,113094,MI,FL,Denmark,M,Denmark,50,"Java, R, Statistics",Master,3,Real Estate,2024-03-15,2024-05-22,1878,7.7,DeepTech Ventures -AI11491,Machine Learning Researcher,44438,USD,44438,EN,FL,South Korea,S,South Korea,50,"Hadoop, Tableau, GCP, MLOps",PhD,0,Government,2024-03-11,2024-03-25,2149,8.8,Advanced Robotics -AI11492,AI Research Scientist,74828,EUR,63604,EN,CT,Netherlands,S,Netherlands,0,"Computer Vision, Python, Kubernetes, SQL",Master,1,Manufacturing,2024-09-12,2024-10-21,1386,6.3,Quantum Computing Inc -AI11493,Principal Data Scientist,79856,AUD,107806,MI,PT,Australia,M,Australia,0,"Hadoop, Scala, Git, Deep Learning, Java",PhD,2,Retail,2024-05-22,2024-07-24,1575,6.9,Quantum Computing Inc -AI11494,AI Specialist,155247,USD,155247,EX,FT,Ireland,M,Ireland,100,"Python, Mathematics, Git, Hadoop, Computer Vision",Master,17,Consulting,2025-02-04,2025-02-18,1759,9.4,Algorithmic Solutions -AI11495,AI Research Scientist,86084,EUR,73171,EN,PT,France,L,Poland,100,"Java, GCP, Data Visualization, Kubernetes, Python",Bachelor,1,Healthcare,2025-02-05,2025-04-03,1866,5.1,AI Innovations -AI11496,AI Specialist,121255,USD,121255,MI,PT,Norway,L,Norway,0,"SQL, Scala, AWS, GCP",PhD,4,Telecommunications,2024-03-28,2024-06-03,2180,8.1,TechCorp Inc -AI11497,AI Consultant,120964,USD,120964,SE,CT,Denmark,S,Nigeria,50,"Spark, SQL, Deep Learning",Associate,9,Healthcare,2024-05-10,2024-07-02,511,9.3,TechCorp Inc -AI11498,Autonomous Systems Engineer,170957,GBP,128218,SE,FL,United Kingdom,L,United Kingdom,100,"Azure, Hadoop, Python",Associate,6,Retail,2024-11-16,2024-12-12,1965,8.5,DataVision Ltd -AI11499,Machine Learning Engineer,80134,JPY,8814740,MI,FL,Japan,M,Ireland,0,"Java, AWS, TensorFlow, Spark, Tableau",Associate,2,Manufacturing,2024-04-11,2024-06-07,936,6.7,Smart Analytics -AI11500,AI Consultant,139486,JPY,15343460,EX,FT,Japan,S,Canada,50,"NLP, Python, Data Visualization",Associate,13,Finance,2024-09-07,2024-11-17,1203,6.6,Neural Networks Co -AI11501,Deep Learning Engineer,65381,SGD,84995,EN,FT,Singapore,L,Singapore,50,"Linux, R, Docker, Python",Bachelor,0,Education,2024-11-21,2025-01-17,1622,6.9,TechCorp Inc -AI11502,Data Engineer,171324,USD,171324,EX,CT,Norway,S,Norway,0,"Statistics, SQL, Scala, Kubernetes, Data Visualization",Bachelor,15,Education,2024-07-02,2024-08-11,1183,7.5,Advanced Robotics -AI11503,AI Specialist,87775,USD,87775,SE,FL,South Korea,M,South Korea,100,"MLOps, SQL, Python, Scala, Git",Master,6,Media,2024-07-07,2024-08-04,2349,6.3,Cognitive Computing -AI11504,Deep Learning Engineer,172632,EUR,146737,EX,FL,Austria,S,Austria,0,"Tableau, Kubernetes, AWS",Master,11,Manufacturing,2024-11-10,2024-12-30,2272,5.6,Neural Networks Co -AI11505,Data Analyst,88588,USD,88588,MI,PT,Denmark,S,Denmark,50,"Hadoop, Docker, Mathematics",Bachelor,4,Real Estate,2024-10-02,2024-10-18,572,6.8,DeepTech Ventures -AI11506,Data Scientist,168771,EUR,143455,EX,FT,Netherlands,M,Netherlands,0,"TensorFlow, NLP, Python, GCP",Associate,15,Retail,2025-03-16,2025-05-06,1787,5.7,DeepTech Ventures -AI11507,AI Product Manager,90000,USD,90000,MI,FT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, Data Visualization, SQL",Associate,4,Real Estate,2024-04-12,2024-04-29,1336,5.1,Quantum Computing Inc -AI11508,NLP Engineer,38919,USD,38919,MI,PT,China,M,Belgium,0,"R, Hadoop, NLP",Bachelor,3,Finance,2025-03-02,2025-03-24,1440,7.8,Predictive Systems -AI11509,Deep Learning Engineer,63396,EUR,53887,EN,CT,France,M,France,50,"Hadoop, GCP, AWS, Scala, Azure",Bachelor,0,Government,2024-07-03,2024-08-24,1182,5.9,DataVision Ltd -AI11510,AI Software Engineer,127703,USD,127703,EX,FL,South Korea,S,Indonesia,50,"Hadoop, Scala, TensorFlow, GCP",PhD,14,Retail,2024-11-18,2025-01-03,1976,6.3,Algorithmic Solutions -AI11511,Research Scientist,136930,USD,136930,MI,FT,Norway,M,Norway,50,"Azure, SQL, Computer Vision, Spark, Statistics",PhD,2,Manufacturing,2024-02-05,2024-03-06,2481,9.8,Cognitive Computing -AI11512,Machine Learning Researcher,62653,EUR,53255,EN,FL,Austria,S,Austria,0,"SQL, Scala, GCP",Bachelor,0,Media,2024-02-07,2024-04-07,1111,5.1,Smart Analytics -AI11513,AI Consultant,238158,USD,238158,EX,FL,Sweden,L,Sweden,0,"Mathematics, Data Visualization, GCP, Python, Git",PhD,19,Telecommunications,2025-02-03,2025-02-26,2232,7.3,Advanced Robotics -AI11514,AI Specialist,67273,AUD,90819,MI,FL,Australia,S,Australia,100,"AWS, Computer Vision, Linux, NLP",Bachelor,2,Telecommunications,2024-12-05,2024-12-25,1782,8.6,Cloud AI Solutions -AI11515,AI Software Engineer,296408,USD,296408,EX,FL,Denmark,L,Denmark,50,"Azure, Git, Statistics",PhD,12,Real Estate,2024-01-07,2024-02-03,1976,8.8,DeepTech Ventures -AI11516,Deep Learning Engineer,82078,EUR,69766,MI,FT,Netherlands,S,Netherlands,100,"AWS, Statistics, Tableau",Associate,3,Media,2025-03-27,2025-05-19,2475,9.3,Algorithmic Solutions -AI11517,Data Analyst,62170,EUR,52845,MI,CT,France,S,Australia,0,"AWS, Git, Python, GCP",PhD,2,Telecommunications,2025-04-17,2025-05-30,2294,6.8,AI Innovations -AI11518,Principal Data Scientist,156317,GBP,117238,SE,FL,United Kingdom,L,Thailand,100,"SQL, Scala, Kubernetes, Git",Bachelor,8,Government,2025-02-15,2025-03-20,2149,5.3,Algorithmic Solutions -AI11519,Principal Data Scientist,222260,CHF,200034,EX,FL,Switzerland,S,Switzerland,0,"SQL, PyTorch, Linux",Bachelor,11,Transportation,2024-08-15,2024-09-29,1557,8.8,Machine Intelligence Group -AI11520,Deep Learning Engineer,37876,USD,37876,SE,FL,India,S,India,0,"Data Visualization, Scala, R",Associate,5,Manufacturing,2024-09-05,2024-11-03,1333,8.7,Smart Analytics -AI11521,AI Consultant,78486,USD,78486,MI,PT,Sweden,M,Sweden,50,"Java, PyTorch, Linux",Associate,4,Energy,2024-10-03,2024-12-07,2117,9.1,DataVision Ltd -AI11522,Deep Learning Engineer,192938,EUR,163997,EX,CT,Netherlands,S,Kenya,100,"AWS, Scala, Deep Learning",Master,14,Transportation,2024-10-18,2024-12-29,1316,9.7,Predictive Systems -AI11523,Principal Data Scientist,43359,USD,43359,SE,PT,India,L,India,50,"Statistics, MLOps, Mathematics, Data Visualization",PhD,8,Healthcare,2025-01-27,2025-02-27,2445,8.8,Cognitive Computing -AI11524,Principal Data Scientist,118994,EUR,101145,SE,PT,Germany,M,Germany,100,"Spark, GCP, TensorFlow",Associate,9,Technology,2024-08-25,2024-10-07,1049,5.6,Neural Networks Co -AI11525,NLP Engineer,97478,CHF,87730,MI,FL,Switzerland,S,Switzerland,0,"Hadoop, SQL, Scala, Data Visualization, AWS",PhD,4,Telecommunications,2025-03-30,2025-05-01,1307,9.6,Digital Transformation LLC -AI11526,Head of AI,88392,EUR,75133,MI,FT,France,S,France,50,"Data Visualization, R, GCP, SQL",PhD,2,Energy,2024-11-28,2024-12-26,1526,5.8,Smart Analytics -AI11527,Machine Learning Researcher,134966,USD,134966,SE,FL,Sweden,S,Austria,50,"Kubernetes, Hadoop, PyTorch, Data Visualization, Computer Vision",Associate,6,Energy,2024-05-24,2024-06-14,1182,6,Cognitive Computing -AI11528,AI Specialist,106203,AUD,143374,MI,FL,Australia,M,Australia,0,"Azure, Computer Vision, SQL, Kubernetes, Statistics",Master,3,Telecommunications,2024-02-03,2024-02-24,1658,9.8,Predictive Systems -AI11529,AI Software Engineer,202928,USD,202928,EX,CT,Ireland,S,Ireland,0,"R, PyTorch, Git, Java",Bachelor,18,Gaming,2024-06-26,2024-07-24,2250,6.3,TechCorp Inc -AI11530,NLP Engineer,127991,USD,127991,MI,FT,Norway,S,Norway,100,"Mathematics, Data Visualization, R, Computer Vision",Bachelor,3,Real Estate,2024-11-18,2025-01-25,1062,8,AI Innovations -AI11531,AI Architect,92358,EUR,78504,SE,FL,Austria,S,Finland,50,"GCP, Kubernetes, AWS, Computer Vision",Associate,8,Manufacturing,2024-10-03,2024-12-02,2090,9,DataVision Ltd -AI11532,Data Engineer,272629,USD,272629,EX,FL,Norway,S,Russia,50,"MLOps, Docker, Java, Mathematics, PyTorch",Master,19,Retail,2025-02-17,2025-03-27,1463,8.6,Future Systems -AI11533,AI Architect,221472,JPY,24361920,EX,PT,Japan,S,Japan,50,"Tableau, Java, Docker, Scala",PhD,10,Media,2024-09-28,2024-10-19,1044,8.7,Neural Networks Co -AI11534,Autonomous Systems Engineer,73577,CAD,91971,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, MLOps, Java, PyTorch",PhD,1,Automotive,2024-03-30,2024-05-03,1561,7.1,DeepTech Ventures -AI11535,ML Ops Engineer,58063,EUR,49354,EN,CT,Germany,M,Germany,0,"Data Visualization, Scala, Linux, NLP",Master,0,Consulting,2024-09-04,2024-11-05,2249,9.1,DeepTech Ventures -AI11536,Computer Vision Engineer,219400,AUD,296190,EX,FL,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau, Azure, GCP",PhD,17,Transportation,2024-04-27,2024-07-03,1931,5.6,DeepTech Ventures -AI11537,Machine Learning Engineer,103961,GBP,77971,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Docker, Hadoop, Mathematics",Associate,2,Real Estate,2024-10-26,2024-12-20,1011,9.3,Algorithmic Solutions -AI11538,Data Scientist,82413,USD,82413,EX,PT,India,M,India,0,"Python, Spark, TensorFlow, GCP, PyTorch",Master,13,Finance,2024-03-18,2024-05-21,1591,8.7,Machine Intelligence Group -AI11539,Computer Vision Engineer,172900,CHF,155610,SE,FL,Switzerland,L,Switzerland,50,"SQL, Deep Learning, Tableau, TensorFlow, Statistics",Master,6,Media,2024-05-28,2024-06-15,2243,7.4,Quantum Computing Inc -AI11540,Research Scientist,189271,EUR,160880,EX,CT,Netherlands,M,Netherlands,0,"TensorFlow, GCP, Mathematics, Docker",Bachelor,10,Transportation,2024-10-02,2024-11-15,1545,5.3,Advanced Robotics -AI11541,AI Product Manager,111442,EUR,94726,MI,CT,France,L,France,100,"Python, Statistics, NLP",Bachelor,3,Government,2024-05-07,2024-07-01,1973,7.6,Predictive Systems -AI11542,NLP Engineer,67863,GBP,50897,EN,PT,United Kingdom,S,United Kingdom,100,"GCP, Deep Learning, NLP",Bachelor,0,Automotive,2024-07-06,2024-08-11,751,8.8,Cognitive Computing -AI11543,NLP Engineer,37216,USD,37216,MI,FT,India,M,India,100,"Scala, Spark, Tableau, Mathematics, Python",Associate,2,Consulting,2025-01-12,2025-02-18,1396,8.8,Autonomous Tech -AI11544,ML Ops Engineer,146138,USD,146138,SE,FT,Ireland,M,Ireland,0,"Deep Learning, Scala, Tableau, SQL, Computer Vision",Master,9,Media,2024-10-06,2024-11-11,1436,8.5,Cognitive Computing -AI11545,Data Scientist,45328,CAD,56660,EN,PT,Canada,S,Hungary,50,"Deep Learning, R, MLOps, SQL, Spark",Bachelor,0,Automotive,2024-10-18,2024-11-19,2424,8.9,TechCorp Inc -AI11546,Data Scientist,100310,USD,100310,MI,PT,Israel,L,Estonia,50,"Linux, Kubernetes, Scala, Python",PhD,4,Consulting,2024-04-22,2024-05-30,1423,7.2,Quantum Computing Inc -AI11547,Principal Data Scientist,147245,EUR,125158,SE,CT,France,L,France,50,"MLOps, Linux, Data Visualization, Spark",Associate,6,Media,2024-10-23,2024-11-18,729,6.4,Autonomous Tech -AI11548,Autonomous Systems Engineer,88089,EUR,74876,MI,FT,Germany,S,Germany,0,"Git, Azure, Python, Hadoop",PhD,3,Automotive,2024-01-17,2024-02-18,2100,7.4,Digital Transformation LLC -AI11549,Principal Data Scientist,72575,USD,72575,EN,CT,South Korea,L,South Korea,50,"TensorFlow, AWS, Deep Learning, Python, MLOps",Bachelor,0,Media,2024-11-06,2025-01-17,753,9.5,DeepTech Ventures -AI11550,AI Research Scientist,85617,USD,85617,MI,FL,Finland,S,Finland,50,"SQL, GCP, PyTorch, AWS",Bachelor,4,Healthcare,2025-04-26,2025-07-02,911,5.5,Cloud AI Solutions -AI11551,AI Consultant,89607,CAD,112009,MI,PT,Canada,S,Canada,50,"Computer Vision, AWS, SQL",Associate,2,Government,2024-10-17,2024-12-10,851,5.1,AI Innovations -AI11552,Robotics Engineer,51322,EUR,43624,EN,FL,Austria,S,Austria,50,"Git, Hadoop, SQL, NLP",PhD,1,Transportation,2025-01-05,2025-02-16,1864,7.7,Cognitive Computing -AI11553,Computer Vision Engineer,93109,EUR,79143,SE,PT,France,S,France,0,"Docker, Hadoop, Tableau, Statistics, GCP",Bachelor,9,Real Estate,2024-05-09,2024-06-23,1392,5.4,DeepTech Ventures -AI11554,Robotics Engineer,39952,USD,39952,MI,PT,China,S,China,100,"Statistics, R, Docker, Deep Learning",Master,4,Manufacturing,2024-12-22,2025-01-12,2188,7.8,TechCorp Inc -AI11555,Head of AI,53528,USD,53528,SE,CT,China,M,China,100,"TensorFlow, Python, Data Visualization",Bachelor,6,Media,2024-08-30,2024-10-28,1322,5.8,Predictive Systems -AI11556,Data Engineer,87394,EUR,74285,MI,FL,Netherlands,M,Netherlands,0,"Mathematics, GCP, Scala, NLP",Master,3,Healthcare,2024-03-12,2024-05-19,2338,9.7,Smart Analytics -AI11557,Deep Learning Engineer,172148,EUR,146326,EX,PT,Netherlands,S,Netherlands,50,"SQL, Python, Git",Bachelor,19,Manufacturing,2024-07-31,2024-08-24,712,5.6,TechCorp Inc -AI11558,AI Research Scientist,63353,EUR,53850,EN,FT,France,S,France,50,"Linux, PyTorch, R, MLOps, Statistics",Associate,1,Finance,2025-04-04,2025-04-23,1231,7.1,TechCorp Inc -AI11559,Machine Learning Researcher,65724,USD,65724,EN,FL,South Korea,L,South Korea,50,"Git, MLOps, GCP",Bachelor,0,Transportation,2024-02-04,2024-03-14,1883,7.4,Machine Intelligence Group -AI11560,ML Ops Engineer,114291,EUR,97147,SE,PT,Austria,S,Austria,100,"SQL, Kubernetes, Tableau, Linux",Associate,8,Education,2024-09-27,2024-11-09,666,8.2,DataVision Ltd -AI11561,Machine Learning Engineer,85594,USD,85594,EN,PT,Ireland,L,Ireland,50,"Git, Data Visualization, Hadoop, NLP, Deep Learning",Bachelor,0,Automotive,2024-04-04,2024-05-15,2034,7.9,DataVision Ltd -AI11562,AI Specialist,123737,JPY,13611070,SE,PT,Japan,M,Japan,50,"Python, AWS, Computer Vision, TensorFlow",Bachelor,5,Education,2024-09-01,2024-09-25,2237,5,Predictive Systems -AI11563,Deep Learning Engineer,240031,EUR,204026,EX,PT,Germany,M,Germany,0,"Java, Mathematics, TensorFlow",Master,11,Technology,2024-09-07,2024-10-18,683,8.7,Autonomous Tech -AI11564,Research Scientist,31490,USD,31490,MI,PT,India,M,Sweden,100,"Linux, SQL, Computer Vision, Data Visualization",Master,2,Telecommunications,2025-01-14,2025-02-12,1008,7.5,TechCorp Inc -AI11565,AI Specialist,60618,EUR,51525,EN,CT,Germany,L,South Korea,0,"R, Tableau, Deep Learning, Kubernetes",Master,0,Retail,2024-10-29,2024-12-02,1489,7.3,Predictive Systems -AI11566,AI Architect,78418,USD,78418,EN,CT,Israel,L,Israel,100,"Python, NLP, MLOps",Associate,0,Manufacturing,2024-09-05,2024-09-30,846,9.3,AI Innovations -AI11567,Data Scientist,269385,JPY,29632350,EX,CT,Japan,M,Japan,50,"NLP, Kubernetes, Spark, Mathematics, Python",Associate,13,Automotive,2025-01-31,2025-04-09,1439,8,Autonomous Tech -AI11568,Autonomous Systems Engineer,97601,USD,97601,MI,PT,United States,S,Ireland,100,"PyTorch, Azure, Linux, GCP",Bachelor,2,Finance,2024-09-08,2024-10-29,1430,6.3,AI Innovations -AI11569,AI Software Engineer,195834,USD,195834,EX,FL,Finland,S,Argentina,50,"TensorFlow, GCP, SQL",Associate,15,Consulting,2024-09-22,2024-11-15,987,9.9,Cognitive Computing -AI11570,AI Consultant,136182,USD,136182,EX,CT,South Korea,M,South Korea,100,"Scala, Deep Learning, Azure, Statistics, Data Visualization",Master,18,Transportation,2025-02-06,2025-03-05,1479,6.8,Smart Analytics -AI11571,AI Software Engineer,210024,CAD,262530,EX,FT,Canada,S,Switzerland,50,"Scala, Python, Hadoop, Git",Bachelor,11,Healthcare,2025-02-21,2025-03-22,1133,9.1,DeepTech Ventures -AI11572,Principal Data Scientist,54381,USD,54381,EN,FT,Israel,S,Israel,0,"Spark, PyTorch, Azure, R, Scala",Associate,1,Manufacturing,2024-12-06,2024-12-22,1312,5.1,DataVision Ltd -AI11573,AI Product Manager,190082,USD,190082,SE,CT,Denmark,M,Denmark,0,"Docker, GCP, Java, PyTorch, Deep Learning",Bachelor,9,Manufacturing,2024-08-23,2024-10-19,945,6.2,Cloud AI Solutions -AI11574,AI Software Engineer,84428,JPY,9287080,MI,FT,Japan,S,Japan,50,"Hadoop, TensorFlow, GCP",Associate,2,Media,2024-03-14,2024-04-14,1969,6.7,Cognitive Computing -AI11575,Robotics Engineer,111780,SGD,145314,SE,CT,Singapore,S,Singapore,0,"Python, GCP, AWS, Mathematics, TensorFlow",PhD,5,Transportation,2025-03-13,2025-03-30,746,5.1,Machine Intelligence Group -AI11576,Principal Data Scientist,103260,USD,103260,EN,FT,Norway,M,Norway,0,"R, Python, Spark, Java, GCP",Bachelor,0,Education,2024-12-21,2025-02-17,714,8.4,Digital Transformation LLC -AI11577,AI Specialist,129654,USD,129654,MI,CT,Denmark,L,France,50,"Docker, SQL, Data Visualization",Master,2,Gaming,2024-04-03,2024-06-07,815,6.6,Neural Networks Co -AI11578,AI Product Manager,37250,USD,37250,EN,PT,China,M,Indonesia,50,"Python, Scala, TensorFlow, Tableau",Associate,0,Telecommunications,2024-06-22,2024-09-03,1594,5.3,Advanced Robotics -AI11579,Data Scientist,287770,USD,287770,EX,PT,Ireland,L,Ireland,50,"Hadoop, PyTorch, Kubernetes",Master,13,Energy,2025-01-10,2025-03-14,761,5.5,Digital Transformation LLC -AI11580,Data Scientist,65359,JPY,7189490,EN,PT,Japan,M,Colombia,100,"Data Visualization, Git, Scala, Computer Vision",PhD,0,Gaming,2025-03-25,2025-04-14,1483,8.7,Smart Analytics -AI11581,NLP Engineer,122773,USD,122773,SE,FT,Ireland,M,Ireland,100,"SQL, Tableau, Spark",Associate,8,Government,2024-03-14,2024-04-05,1698,9.2,DataVision Ltd -AI11582,Data Engineer,60408,USD,60408,EN,PT,Finland,L,Finland,100,"Git, PyTorch, GCP, Spark, Tableau",Bachelor,1,Manufacturing,2024-08-13,2024-10-01,1351,6.5,TechCorp Inc -AI11583,AI Software Engineer,150096,USD,150096,SE,FT,Sweden,L,Sweden,50,"Python, TensorFlow, Spark",Associate,6,Telecommunications,2024-02-05,2024-04-08,1653,7.2,Future Systems -AI11584,Data Scientist,205206,EUR,174425,EX,FL,France,L,France,100,"SQL, Kubernetes, PyTorch",Bachelor,17,Gaming,2024-05-19,2024-06-11,1708,5.6,TechCorp Inc -AI11585,Data Scientist,26000,USD,26000,MI,FT,India,M,India,100,"PyTorch, Azure, NLP",PhD,4,Consulting,2024-10-17,2024-12-02,1250,9.1,Advanced Robotics -AI11586,Data Engineer,65860,USD,65860,EN,CT,South Korea,L,South Korea,100,"Mathematics, Scala, Python, Git, Computer Vision",Associate,0,Manufacturing,2024-09-19,2024-11-09,1493,7.8,Future Systems -AI11587,Computer Vision Engineer,94548,GBP,70911,MI,FT,United Kingdom,L,United Kingdom,50,"Hadoop, Tableau, Computer Vision",PhD,2,Telecommunications,2024-09-22,2024-11-27,848,9.5,Cognitive Computing -AI11588,Robotics Engineer,139420,USD,139420,SE,CT,Finland,L,Kenya,0,"GCP, Computer Vision, NLP",PhD,6,Automotive,2024-02-08,2024-03-11,1488,7.9,Neural Networks Co -AI11589,AI Consultant,96731,USD,96731,EN,FL,United States,L,United States,50,"Java, R, SQL, Docker",Associate,0,Real Estate,2024-07-19,2024-08-13,2423,5.2,Algorithmic Solutions -AI11590,Data Engineer,166302,EUR,141357,SE,FT,Netherlands,L,Switzerland,50,"Hadoop, Computer Vision, Python, Java, Kubernetes",Bachelor,6,Real Estate,2024-09-08,2024-09-25,622,6.3,Autonomous Tech -AI11591,AI Research Scientist,169852,USD,169852,EX,PT,South Korea,M,South Korea,100,"SQL, Git, Docker, PyTorch",Bachelor,19,Automotive,2024-05-04,2024-06-04,2138,5.4,Future Systems -AI11592,Autonomous Systems Engineer,50112,USD,50112,EN,PT,Ireland,S,Ireland,50,"Data Visualization, Computer Vision, SQL, Hadoop",PhD,0,Energy,2024-10-13,2024-12-03,1750,9.7,Autonomous Tech -AI11593,Data Engineer,25790,USD,25790,EN,FT,India,L,Romania,50,"TensorFlow, SQL, Hadoop, Tableau",Master,0,Media,2024-07-29,2024-08-27,1971,8,Cognitive Computing -AI11594,Robotics Engineer,111118,SGD,144453,SE,PT,Singapore,M,Singapore,50,"AWS, Docker, NLP, Kubernetes, Azure",Associate,7,Telecommunications,2025-03-23,2025-05-02,960,8.7,Cloud AI Solutions -AI11595,Data Engineer,63655,GBP,47741,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, Python, R, TensorFlow",PhD,0,Consulting,2024-03-16,2024-04-29,2498,6.2,Algorithmic Solutions -AI11596,AI Product Manager,180875,USD,180875,EX,CT,Ireland,L,Sweden,0,"Scala, Kubernetes, Python",Master,11,Finance,2024-11-07,2024-12-25,649,8.2,Algorithmic Solutions -AI11597,AI Software Engineer,59927,EUR,50938,EN,CT,France,S,Czech Republic,50,"Mathematics, Computer Vision, Data Visualization",Bachelor,0,Real Estate,2024-03-06,2024-05-12,794,9.5,Machine Intelligence Group -AI11598,AI Research Scientist,254962,EUR,216718,EX,FT,France,L,France,0,"SQL, NLP, Docker",Bachelor,15,Finance,2024-11-30,2025-01-07,1476,9.7,Autonomous Tech -AI11599,Machine Learning Researcher,173503,CHF,156153,SE,CT,Switzerland,S,Kenya,50,"Mathematics, Computer Vision, AWS",Associate,5,Retail,2024-06-02,2024-07-05,2001,7.4,Neural Networks Co -AI11600,Data Engineer,33680,USD,33680,EN,FL,China,M,China,100,"Statistics, AWS, PyTorch, Kubernetes, TensorFlow",Associate,0,Gaming,2024-10-14,2024-11-16,555,6.4,TechCorp Inc -AI11601,Machine Learning Researcher,115942,USD,115942,MI,FL,United States,L,United States,0,"Scala, AWS, Data Visualization, Computer Vision",Bachelor,3,Finance,2024-07-20,2024-09-09,1811,7.7,AI Innovations -AI11602,AI Architect,77384,AUD,104468,EN,FL,Australia,L,Australia,0,"R, Tableau, Linux, GCP",PhD,1,Real Estate,2025-02-28,2025-04-10,593,5.3,DeepTech Ventures -AI11603,Data Analyst,331419,CHF,298277,EX,FT,Switzerland,M,Switzerland,0,"Git, NLP, R",Associate,18,Manufacturing,2024-05-05,2024-06-17,2175,5.8,DeepTech Ventures -AI11604,Data Scientist,131344,USD,131344,SE,CT,Sweden,L,Australia,100,"Statistics, MLOps, Hadoop, Kubernetes, Docker",PhD,6,Government,2025-01-23,2025-03-23,2206,6.1,Advanced Robotics -AI11605,Autonomous Systems Engineer,81352,USD,81352,EX,PT,India,M,Kenya,50,"Python, TensorFlow, Deep Learning, Hadoop, Linux",Master,11,Telecommunications,2024-01-27,2024-03-15,1582,6.7,Quantum Computing Inc -AI11606,NLP Engineer,75140,EUR,63869,EN,FT,Netherlands,S,Netherlands,100,"Java, Spark, Kubernetes",Associate,0,Real Estate,2025-04-26,2025-05-23,2246,9.4,Cloud AI Solutions -AI11607,AI Specialist,57023,USD,57023,EN,FL,Ireland,M,United Kingdom,100,"NLP, Statistics, AWS, Kubernetes",Bachelor,0,Education,2024-03-23,2024-04-25,1207,8,Future Systems -AI11608,Principal Data Scientist,76910,JPY,8460100,EN,FL,Japan,S,Japan,50,"Python, Azure, Tableau, SQL, Deep Learning",Associate,1,Transportation,2025-02-24,2025-04-05,1100,5.5,Machine Intelligence Group -AI11609,Data Engineer,86816,USD,86816,EN,FT,Norway,S,Norway,50,"Hadoop, Python, MLOps, Docker, Tableau",Bachelor,1,Automotive,2024-12-28,2025-02-16,1200,7.4,Predictive Systems -AI11610,Head of AI,177419,EUR,150806,EX,FL,Austria,L,Austria,50,"PyTorch, Hadoop, Kubernetes, TensorFlow, Java",Master,14,Telecommunications,2024-11-19,2025-01-27,1430,7.7,DataVision Ltd -AI11611,Principal Data Scientist,143077,USD,143077,EX,FT,Israel,M,Italy,50,"R, Spark, AWS, Scala, NLP",Master,12,Real Estate,2024-12-05,2025-02-02,2272,5.8,Cognitive Computing -AI11612,Robotics Engineer,55124,SGD,71661,EN,FT,Singapore,S,United Kingdom,50,"Statistics, Scala, Hadoop, Spark",Associate,1,Government,2024-03-23,2024-05-01,792,7,Digital Transformation LLC -AI11613,Data Analyst,202411,USD,202411,EX,FL,Sweden,S,Sweden,100,"SQL, R, Tableau, PyTorch, Java",PhD,16,Healthcare,2024-09-05,2024-10-26,2074,6.4,AI Innovations -AI11614,Deep Learning Engineer,84402,EUR,71742,MI,PT,Austria,S,Belgium,50,"AWS, Git, TensorFlow, R",PhD,2,Healthcare,2024-04-20,2024-05-29,1385,10,Autonomous Tech -AI11615,Machine Learning Engineer,194046,GBP,145535,EX,PT,United Kingdom,L,United Kingdom,100,"Linux, Azure, Statistics, PyTorch",PhD,12,Manufacturing,2024-12-10,2024-12-26,2089,9.9,Smart Analytics -AI11616,Research Scientist,59744,AUD,80654,EN,PT,Australia,S,Australia,100,"MLOps, Computer Vision, Deep Learning, R",Associate,0,Healthcare,2024-04-18,2024-05-12,1076,7.2,Future Systems -AI11617,ML Ops Engineer,102625,USD,102625,SE,FL,Israel,M,Israel,50,"Azure, SQL, GCP",Master,5,Government,2024-01-27,2024-03-18,751,7.9,Neural Networks Co -AI11618,Computer Vision Engineer,56790,EUR,48272,EN,FT,France,S,South Korea,100,"Git, GCP, Java",Master,1,Manufacturing,2024-01-28,2024-04-05,1966,5.2,Autonomous Tech -AI11619,AI Specialist,56948,USD,56948,EN,PT,Ireland,M,Ireland,50,"SQL, Mathematics, TensorFlow, AWS",Master,0,Transportation,2024-01-25,2024-04-04,1345,6.9,Quantum Computing Inc -AI11620,AI Product Manager,124698,USD,124698,MI,FT,United States,M,Chile,50,"Java, R, Scala, Linux",PhD,3,Gaming,2024-10-11,2024-11-24,600,5.1,AI Innovations -AI11621,Principal Data Scientist,158637,USD,158637,SE,PT,Norway,L,Indonesia,50,"Data Visualization, Docker, Azure, R, PyTorch",Associate,6,Real Estate,2024-02-22,2024-04-23,1254,7.8,Quantum Computing Inc -AI11622,AI Product Manager,104750,USD,104750,MI,CT,Israel,L,Switzerland,100,"PyTorch, Spark, Tableau, Computer Vision, Azure",Associate,4,Technology,2024-12-11,2025-01-23,2141,6.4,Autonomous Tech -AI11623,AI Software Engineer,149617,JPY,16457870,EX,CT,Japan,S,Japan,50,"Kubernetes, Scala, Java",PhD,13,Consulting,2024-03-03,2024-03-20,523,6.7,DataVision Ltd -AI11624,Data Analyst,54122,SGD,70359,EN,CT,Singapore,M,Singapore,100,"Spark, PyTorch, Statistics, Docker, Mathematics",Bachelor,1,Real Estate,2024-04-30,2024-07-11,851,7.3,Smart Analytics -AI11625,Deep Learning Engineer,103462,JPY,11380820,MI,PT,Japan,S,Germany,100,"SQL, Kubernetes, Computer Vision, Java",Bachelor,3,Gaming,2024-05-07,2024-05-24,1539,5.1,Future Systems -AI11626,Data Analyst,200620,USD,200620,EX,PT,Denmark,S,Denmark,100,"TensorFlow, NLP, GCP, AWS, PyTorch",PhD,10,Energy,2024-09-26,2024-11-05,1152,9.5,Digital Transformation LLC -AI11627,Deep Learning Engineer,63203,GBP,47402,EN,FT,United Kingdom,S,Israel,0,"NLP, Python, AWS",Bachelor,1,Technology,2024-09-21,2024-10-21,1794,5.4,Advanced Robotics -AI11628,Machine Learning Researcher,92506,EUR,78630,EN,FL,Netherlands,L,Netherlands,50,"Scala, Python, Mathematics",Bachelor,0,Manufacturing,2024-09-26,2024-10-10,565,6.2,Predictive Systems -AI11629,AI Research Scientist,78404,USD,78404,MI,FT,South Korea,S,South Korea,50,"Mathematics, TensorFlow, Tableau, MLOps, Kubernetes",PhD,4,Real Estate,2025-01-19,2025-02-25,2407,9.3,Future Systems -AI11630,AI Product Manager,155868,EUR,132488,SE,FT,Netherlands,L,Netherlands,0,"Hadoop, TensorFlow, NLP",Master,6,Technology,2024-12-05,2025-01-17,2008,5.3,Predictive Systems -AI11631,AI Research Scientist,156517,USD,156517,SE,FL,United States,M,United States,50,"SQL, Linux, Data Visualization",PhD,8,Healthcare,2024-10-11,2024-12-17,1487,6.4,Algorithmic Solutions -AI11632,Data Analyst,212507,USD,212507,EX,FT,United States,S,Estonia,100,"AWS, Scala, Java, Statistics",Associate,12,Finance,2025-03-30,2025-05-04,1171,9.9,Advanced Robotics -AI11633,Machine Learning Researcher,171831,JPY,18901410,SE,CT,Japan,L,Japan,0,"TensorFlow, Hadoop, NLP",Bachelor,5,Technology,2024-03-30,2024-05-12,1514,6.1,AI Innovations -AI11634,Computer Vision Engineer,208009,USD,208009,EX,FT,United States,S,Chile,50,"Spark, PyTorch, SQL",Bachelor,14,Transportation,2024-07-28,2024-10-06,2490,5.8,Quantum Computing Inc -AI11635,Data Scientist,193197,EUR,164217,EX,FL,Germany,L,Germany,50,"Tableau, Python, Spark, Mathematics",Associate,19,Telecommunications,2024-05-18,2024-06-24,1462,5.7,Smart Analytics -AI11636,AI Architect,105371,USD,105371,MI,FT,Norway,S,Colombia,100,"R, MLOps, Spark, PyTorch, GCP",Bachelor,4,Finance,2024-10-16,2024-11-21,797,9.7,Algorithmic Solutions -AI11637,Deep Learning Engineer,166349,CAD,207936,EX,CT,Canada,L,Canada,0,"Spark, NLP, Scala",Bachelor,14,Telecommunications,2024-04-13,2024-06-17,1478,7.6,Autonomous Tech -AI11638,Research Scientist,141464,USD,141464,SE,FT,Denmark,M,Denmark,100,"MLOps, Git, Scala, GCP",Bachelor,6,Manufacturing,2024-12-27,2025-02-09,1520,7.4,Cognitive Computing -AI11639,AI Consultant,28009,USD,28009,EN,CT,China,M,China,100,"Linux, SQL, MLOps",Master,1,Telecommunications,2024-03-04,2024-03-26,2322,5.1,Digital Transformation LLC -AI11640,Head of AI,173041,USD,173041,EX,FL,Finland,S,Finland,100,"NLP, Kubernetes, Deep Learning, Git",Master,10,Government,2024-01-14,2024-02-17,730,8,Autonomous Tech -AI11641,Robotics Engineer,239925,USD,239925,EX,CT,Finland,L,Finland,100,"Python, Linux, Data Visualization, Scala, Mathematics",PhD,10,Manufacturing,2024-08-23,2024-10-29,2431,7.9,TechCorp Inc -AI11642,Deep Learning Engineer,36984,USD,36984,EN,FT,China,L,China,0,"Hadoop, Java, R, Data Visualization, Kubernetes",Associate,0,Government,2024-06-13,2024-07-21,1370,8.3,Predictive Systems -AI11643,AI Consultant,251261,USD,251261,EX,PT,Denmark,L,Poland,100,"Azure, Git, Linux",Bachelor,18,Real Estate,2024-12-13,2025-02-11,593,7.8,Neural Networks Co -AI11644,AI Consultant,139815,USD,139815,EX,PT,South Korea,L,Turkey,0,"NLP, SQL, Java, Deep Learning",Bachelor,13,Gaming,2024-09-26,2024-11-25,969,8.3,DataVision Ltd -AI11645,Deep Learning Engineer,51437,EUR,43721,EN,PT,France,M,France,50,"MLOps, AWS, Python, Hadoop, Statistics",Master,0,Media,2025-01-11,2025-03-08,830,8.6,Quantum Computing Inc -AI11646,AI Software Engineer,89863,USD,89863,SE,CT,South Korea,S,South Korea,50,"Git, Hadoop, Python, Linux, Kubernetes",Master,6,Healthcare,2024-02-06,2024-03-30,1952,8.7,Cloud AI Solutions -AI11647,Machine Learning Researcher,65048,USD,65048,EN,PT,Denmark,S,Denmark,50,"Computer Vision, Scala, R, Mathematics, Azure",PhD,0,Healthcare,2024-12-12,2025-01-30,1762,7,AI Innovations -AI11648,Machine Learning Researcher,136806,USD,136806,SE,PT,Sweden,L,Sweden,100,"TensorFlow, R, NLP",Associate,6,Media,2024-04-21,2024-05-06,952,9,Future Systems -AI11649,Deep Learning Engineer,104749,SGD,136174,SE,FT,Singapore,S,Singapore,0,"GCP, TensorFlow, Deep Learning, Python, Git",Associate,7,Retail,2024-02-29,2024-03-17,1742,6.4,Machine Intelligence Group -AI11650,Robotics Engineer,96999,USD,96999,MI,PT,South Korea,L,South Korea,0,"Python, Deep Learning, NLP",Associate,4,Finance,2024-06-25,2024-08-18,1657,5.2,Advanced Robotics -AI11651,Principal Data Scientist,243815,USD,243815,EX,FL,Norway,S,Ukraine,100,"Scala, Java, AWS, R, NLP",Master,18,Healthcare,2024-08-06,2024-09-04,1774,9.8,Neural Networks Co -AI11652,AI Product Manager,76637,GBP,57478,MI,FL,United Kingdom,S,Australia,100,"R, PyTorch, Mathematics, Kubernetes",PhD,4,Education,2025-03-08,2025-05-18,2173,7.5,Digital Transformation LLC -AI11653,ML Ops Engineer,85502,USD,85502,EN,PT,Denmark,L,Denmark,100,"PyTorch, Data Visualization, Spark, Scala, Deep Learning",Bachelor,1,Education,2025-04-12,2025-06-06,2375,6.9,Advanced Robotics -AI11654,Research Scientist,120897,JPY,13298670,SE,CT,Japan,M,Japan,50,"Python, Java, Mathematics",Master,6,Consulting,2024-11-25,2024-12-11,2364,8.5,Machine Intelligence Group -AI11655,Robotics Engineer,91013,USD,91013,EN,FL,Denmark,M,Denmark,0,"Python, Docker, Linux, Git, Scala",Bachelor,0,Media,2024-01-15,2024-01-29,2453,9.9,Predictive Systems -AI11656,Data Engineer,85335,EUR,72535,MI,FL,Austria,S,Austria,50,"Git, PyTorch, MLOps, Computer Vision",PhD,3,Energy,2024-09-09,2024-11-16,1556,5.4,Cognitive Computing -AI11657,AI Consultant,163644,USD,163644,SE,FL,Ireland,L,Ireland,0,"Git, GCP, Deep Learning, Python",Master,7,Finance,2024-10-14,2024-12-16,2454,7.4,Digital Transformation LLC -AI11658,Autonomous Systems Engineer,95444,USD,95444,EN,FT,Norway,M,Luxembourg,0,"Hadoop, PyTorch, TensorFlow",PhD,0,Media,2025-03-31,2025-05-28,1706,8.3,Neural Networks Co -AI11659,Computer Vision Engineer,246523,EUR,209545,EX,PT,Netherlands,M,Netherlands,0,"Scala, PyTorch, Statistics, SQL, Spark",Associate,11,Healthcare,2024-09-23,2024-11-08,1759,6.4,DataVision Ltd -AI11660,Research Scientist,65060,USD,65060,EN,CT,Finland,S,Finland,50,"Data Visualization, Hadoop, Azure",Master,1,Healthcare,2025-01-24,2025-02-24,2176,5.5,Cloud AI Solutions -AI11661,Principal Data Scientist,78657,GBP,58993,EN,PT,United Kingdom,M,United Kingdom,50,"Docker, Tableau, R",Bachelor,1,Gaming,2025-02-25,2025-04-10,545,6.9,Predictive Systems -AI11662,AI Specialist,138491,JPY,15234010,EX,PT,Japan,S,Denmark,0,"Hadoop, Azure, Python",Master,17,Telecommunications,2024-11-01,2024-12-04,749,8.7,Autonomous Tech -AI11663,AI Research Scientist,78736,SGD,102357,EN,PT,Singapore,L,Singapore,0,"Computer Vision, Data Visualization, Scala",PhD,1,Transportation,2024-09-20,2024-11-22,1390,8.7,Autonomous Tech -AI11664,Research Scientist,72680,EUR,61778,EN,PT,France,L,France,0,"Tableau, Git, Computer Vision, TensorFlow",Master,1,Automotive,2024-08-22,2024-10-16,1594,5.2,Cloud AI Solutions -AI11665,Data Scientist,46963,CAD,58704,EN,FL,Canada,S,Canada,100,"NLP, Python, Azure, TensorFlow, PyTorch",PhD,0,Finance,2024-05-26,2024-07-23,2231,6.8,Algorithmic Solutions -AI11666,AI Software Engineer,196455,AUD,265214,EX,PT,Australia,M,Egypt,0,"TensorFlow, Mathematics, Kubernetes",Master,16,Healthcare,2024-04-15,2024-06-10,714,7.7,Smart Analytics -AI11667,Data Scientist,150699,GBP,113024,SE,FT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Scala",PhD,7,Consulting,2024-05-07,2024-07-14,1491,8.2,Neural Networks Co -AI11668,Robotics Engineer,225713,EUR,191856,EX,PT,Netherlands,M,Netherlands,100,"Tableau, Kubernetes, Mathematics",Master,18,Real Estate,2024-02-23,2024-03-09,764,7.6,Predictive Systems -AI11669,Robotics Engineer,89546,USD,89546,EX,PT,India,M,Indonesia,100,"Java, NLP, Hadoop, SQL, Mathematics",Associate,10,Energy,2024-06-28,2024-08-30,2223,7.3,Autonomous Tech -AI11670,Data Scientist,38039,USD,38039,SE,PT,India,M,India,100,"Deep Learning, Git, Kubernetes, GCP",PhD,6,Media,2024-06-30,2024-07-23,1391,6.2,Machine Intelligence Group -AI11671,Data Analyst,157935,CHF,142142,SE,PT,Switzerland,M,Switzerland,50,"Docker, Statistics, NLP, Scala, Python",PhD,6,Consulting,2024-05-13,2024-07-05,2149,8.2,Cognitive Computing -AI11672,Data Analyst,87759,SGD,114087,MI,PT,Singapore,S,Singapore,100,"Git, AWS, Docker, SQL",Bachelor,3,Telecommunications,2024-01-09,2024-03-10,1228,6.9,Advanced Robotics -AI11673,AI Architect,155389,GBP,116542,SE,FL,United Kingdom,L,United Kingdom,0,"Tableau, Hadoop, PyTorch, NLP, Mathematics",Master,7,Manufacturing,2024-05-22,2024-07-04,1487,9.3,Predictive Systems -AI11674,Machine Learning Engineer,73343,EUR,62342,EN,CT,France,M,France,50,"Java, Deep Learning, NLP, SQL, Python",PhD,1,Automotive,2024-08-11,2024-10-04,2451,8.6,Autonomous Tech -AI11675,NLP Engineer,24357,USD,24357,EN,FT,India,L,India,50,"Deep Learning, Hadoop, Kubernetes, Java",Master,1,Automotive,2024-06-03,2024-06-18,950,7.8,Future Systems -AI11676,Autonomous Systems Engineer,69149,USD,69149,EN,FL,Israel,M,Israel,50,"Data Visualization, Java, SQL",PhD,1,Retail,2024-07-30,2024-09-10,2197,8.5,DeepTech Ventures -AI11677,AI Specialist,65314,EUR,55517,EN,PT,France,S,France,50,"Linux, R, PyTorch, GCP, Git",Associate,1,Media,2024-06-20,2024-07-27,1963,5.8,AI Innovations -AI11678,Deep Learning Engineer,133224,USD,133224,SE,PT,Sweden,L,Sweden,50,"TensorFlow, Git, Python, Deep Learning",Master,7,Gaming,2024-07-18,2024-08-18,2306,6.3,Cloud AI Solutions -AI11679,Head of AI,38105,USD,38105,EN,CT,South Korea,S,Italy,0,"AWS, Python, Statistics, TensorFlow",Associate,1,Real Estate,2025-03-17,2025-04-03,563,7.8,Cloud AI Solutions -AI11680,Deep Learning Engineer,63981,USD,63981,EN,FL,Israel,L,Israel,0,"SQL, NLP, Tableau, Computer Vision",PhD,1,Retail,2024-01-09,2024-02-14,1632,8.7,Cognitive Computing -AI11681,AI Software Engineer,231463,GBP,173597,EX,PT,United Kingdom,L,United Kingdom,50,"Data Visualization, Scala, R",Master,12,Education,2024-04-17,2024-06-04,1661,7.4,DataVision Ltd -AI11682,Data Engineer,303234,USD,303234,EX,FL,United States,L,United States,0,"Python, MLOps, Java, TensorFlow, Git",Bachelor,10,Finance,2024-03-14,2024-04-19,2490,6.8,Cognitive Computing -AI11683,Data Analyst,57839,USD,57839,EN,FT,Ireland,S,Ireland,100,"Git, Python, Java, Computer Vision, Scala",PhD,1,Manufacturing,2024-07-04,2024-09-15,746,5.9,DeepTech Ventures -AI11684,Head of AI,105737,USD,105737,MI,FL,Norway,M,Norway,100,"Computer Vision, Kubernetes, TensorFlow, Hadoop, Statistics",Associate,4,Education,2024-11-10,2024-12-31,746,7.9,TechCorp Inc -AI11685,NLP Engineer,83703,GBP,62777,EN,CT,United Kingdom,M,United Kingdom,0,"NLP, Deep Learning, Spark",PhD,1,Technology,2025-01-14,2025-03-14,1926,7,Quantum Computing Inc -AI11686,Research Scientist,374078,USD,374078,EX,FL,Denmark,L,Denmark,100,"Docker, Kubernetes, Deep Learning",PhD,18,Media,2024-04-04,2024-04-27,617,8.4,Predictive Systems -AI11687,AI Consultant,73845,USD,73845,MI,PT,Sweden,S,Sweden,50,"Mathematics, R, AWS",Associate,3,Transportation,2025-03-13,2025-05-22,1960,8.4,Predictive Systems -AI11688,Autonomous Systems Engineer,199570,USD,199570,EX,PT,South Korea,M,South Korea,0,"MLOps, Java, AWS",Master,18,Real Estate,2024-10-29,2024-11-24,1566,5.8,Predictive Systems -AI11689,ML Ops Engineer,59456,USD,59456,EN,FL,Ireland,S,Ireland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Retail,2024-06-23,2024-09-01,765,5.6,Cloud AI Solutions -AI11690,Principal Data Scientist,46874,USD,46874,MI,CT,China,M,China,50,"PyTorch, GCP, Computer Vision, NLP, AWS",Associate,2,Education,2024-06-09,2024-08-11,730,9.2,Quantum Computing Inc -AI11691,Machine Learning Researcher,264204,USD,264204,EX,PT,United States,M,United States,100,"Kubernetes, Hadoop, NLP",Master,12,Education,2025-04-19,2025-05-21,1029,5.7,Advanced Robotics -AI11692,Autonomous Systems Engineer,92702,USD,92702,MI,CT,Denmark,S,Denmark,100,"Linux, MLOps, Deep Learning, Hadoop",Bachelor,4,Energy,2024-04-13,2024-05-31,803,6,Digital Transformation LLC -AI11693,Machine Learning Engineer,127152,USD,127152,SE,FT,Ireland,M,Ireland,100,"Kubernetes, PyTorch, Git, Hadoop",Master,9,Media,2024-03-11,2024-04-17,821,8.2,Future Systems -AI11694,AI Product Manager,97952,USD,97952,EX,FL,India,L,India,0,"Linux, Data Visualization, Git, Deep Learning",Master,15,Finance,2024-07-17,2024-09-18,957,5.7,Algorithmic Solutions -AI11695,Deep Learning Engineer,119734,EUR,101774,SE,CT,Austria,L,Australia,100,"Scala, Python, NLP, Azure",Master,6,Gaming,2025-02-21,2025-05-03,2012,5.1,Neural Networks Co -AI11696,Head of AI,52313,USD,52313,SE,FL,India,L,India,100,"GCP, NLP, Git, Azure, MLOps",PhD,8,Education,2025-04-03,2025-05-24,2225,6,Algorithmic Solutions -AI11697,Principal Data Scientist,150527,USD,150527,SE,PT,Norway,S,Norway,100,"Tableau, Python, TensorFlow, Spark, Scala",PhD,6,Energy,2025-04-10,2025-05-09,1649,6.3,TechCorp Inc -AI11698,Research Scientist,102071,EUR,86760,SE,CT,Austria,M,Austria,100,"Data Visualization, PyTorch, Tableau, Spark",Bachelor,8,Transportation,2024-09-29,2024-10-24,750,6.4,Digital Transformation LLC -AI11699,AI Specialist,120049,JPY,13205390,SE,FL,Japan,M,Australia,100,"Python, GCP, TensorFlow, Docker, Mathematics",Master,8,Healthcare,2024-09-12,2024-10-31,2407,6.7,Advanced Robotics -AI11700,Data Scientist,57666,USD,57666,EN,FT,United States,S,Germany,0,"Python, TensorFlow, MLOps",Master,1,Telecommunications,2025-02-12,2025-03-09,664,6.4,AI Innovations -AI11701,Research Scientist,48186,USD,48186,EN,FT,South Korea,M,Egypt,0,"Data Visualization, Tableau, Linux, MLOps",Associate,1,Technology,2024-01-18,2024-02-28,1545,7.3,Advanced Robotics -AI11702,Research Scientist,105485,EUR,89662,SE,PT,Germany,S,Germany,0,"Statistics, Azure, Python",PhD,7,Manufacturing,2024-10-31,2025-01-10,2359,8.1,Cloud AI Solutions -AI11703,NLP Engineer,131219,SGD,170585,SE,PT,Singapore,S,Singapore,50,"Azure, NLP, Scala",Bachelor,7,Media,2025-03-22,2025-04-18,1790,9.4,Advanced Robotics -AI11704,Robotics Engineer,51061,AUD,68932,EN,CT,Australia,M,Switzerland,50,"Java, Linux, PyTorch, Azure, Spark",Bachelor,1,Retail,2025-03-07,2025-05-16,900,8.2,Digital Transformation LLC -AI11705,AI Research Scientist,118577,USD,118577,MI,PT,Israel,L,Singapore,0,"Hadoop, Spark, TensorFlow, Mathematics, NLP",Master,3,Telecommunications,2024-11-17,2024-12-08,915,9.3,TechCorp Inc -AI11706,Robotics Engineer,123562,JPY,13591820,MI,PT,Japan,L,Canada,0,"NLP, Computer Vision, Linux",Bachelor,4,Healthcare,2024-01-08,2024-02-17,2221,8.1,Advanced Robotics -AI11707,AI Research Scientist,51487,GBP,38615,EN,FT,United Kingdom,S,United Kingdom,50,"Tableau, Docker, MLOps, R, Kubernetes",Associate,0,Education,2024-05-08,2024-05-29,1828,6.3,Advanced Robotics -AI11708,AI Research Scientist,48045,EUR,40838,EN,CT,Austria,M,South Africa,0,"NLP, Git, PyTorch",PhD,1,Healthcare,2025-01-04,2025-01-22,2067,6.2,Quantum Computing Inc -AI11709,Principal Data Scientist,107844,USD,107844,SE,FT,Sweden,M,India,0,"Hadoop, Linux, Data Visualization",PhD,5,Telecommunications,2024-02-19,2024-03-09,2493,6.6,TechCorp Inc -AI11710,Machine Learning Engineer,39178,USD,39178,EN,FT,South Korea,S,India,50,"R, SQL, MLOps, Statistics, GCP",Bachelor,1,Consulting,2024-02-25,2024-04-07,2194,8.4,Machine Intelligence Group -AI11711,AI Architect,222589,SGD,289366,EX,FL,Singapore,S,Singapore,100,"Scala, R, MLOps, AWS, Tableau",Associate,19,Technology,2025-04-01,2025-04-19,1448,7.8,AI Innovations -AI11712,AI Software Engineer,103634,EUR,88089,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, Data Visualization, Tableau, TensorFlow, Docker",PhD,2,Education,2024-03-26,2024-04-13,1772,6.2,Smart Analytics -AI11713,AI Consultant,144301,SGD,187591,SE,FT,Singapore,M,Singapore,0,"Spark, R, TensorFlow, Computer Vision",Bachelor,6,Healthcare,2024-12-17,2025-02-21,2482,8.9,Predictive Systems -AI11714,AI Specialist,99374,EUR,84468,SE,PT,Austria,M,Austria,0,"Git, Scala, Java",Associate,7,Transportation,2024-04-05,2024-04-22,2414,6.5,Quantum Computing Inc -AI11715,AI Software Engineer,182255,USD,182255,EX,FL,Sweden,M,Sweden,0,"Data Visualization, Spark, Python, TensorFlow",Associate,18,Manufacturing,2024-10-22,2024-11-13,846,8,TechCorp Inc -AI11716,Data Engineer,64006,USD,64006,MI,CT,Finland,S,Finland,100,"Java, Kubernetes, Data Visualization, Scala, AWS",PhD,2,Retail,2025-04-12,2025-06-07,1653,6.9,Autonomous Tech -AI11717,Autonomous Systems Engineer,240322,CHF,216290,SE,FL,Switzerland,L,Switzerland,100,"Docker, Mathematics, PyTorch",Bachelor,7,Government,2024-06-28,2024-08-10,2379,7.5,AI Innovations -AI11718,Computer Vision Engineer,90893,USD,90893,MI,PT,Ireland,M,Ireland,50,"MLOps, Python, Azure, Statistics",Bachelor,4,Automotive,2025-04-26,2025-07-07,1506,5.3,Cognitive Computing -AI11719,AI Research Scientist,126730,GBP,95048,SE,PT,United Kingdom,M,United Kingdom,50,"Java, Python, R, TensorFlow, Kubernetes",Associate,6,Automotive,2024-01-27,2024-03-25,760,8.2,TechCorp Inc -AI11720,Deep Learning Engineer,90617,USD,90617,MI,FT,Ireland,S,Ireland,50,"Deep Learning, Git, Java",PhD,4,Media,2024-12-31,2025-02-16,2047,8.8,DataVision Ltd -AI11721,Head of AI,67532,CAD,84415,EN,FT,Canada,M,Luxembourg,100,"Computer Vision, Git, R, Kubernetes",Associate,0,Education,2024-05-11,2024-07-04,1673,5.8,Cloud AI Solutions -AI11722,AI Product Manager,81482,USD,81482,EN,CT,United States,M,United States,50,"AWS, Scala, Kubernetes, NLP",Associate,0,Finance,2024-12-16,2025-02-01,1186,7.6,Advanced Robotics -AI11723,Data Engineer,100637,JPY,11070070,MI,CT,Japan,M,Japan,0,"Java, Scala, Tableau",Master,2,Manufacturing,2024-06-07,2024-08-09,2037,8.2,Smart Analytics -AI11724,Autonomous Systems Engineer,182186,USD,182186,SE,CT,United States,L,United States,50,"Linux, AWS, NLP, TensorFlow",Master,7,Media,2024-06-11,2024-07-20,1317,6.9,Autonomous Tech -AI11725,Research Scientist,124119,USD,124119,MI,CT,Denmark,S,Belgium,0,"Java, Data Visualization, Scala, TensorFlow",Master,2,Government,2024-12-04,2025-01-23,1255,9.6,Advanced Robotics -AI11726,Robotics Engineer,75711,EUR,64354,EN,FL,France,M,South Korea,0,"R, Scala, GCP",PhD,0,Government,2024-04-26,2024-05-29,1596,7.8,DataVision Ltd -AI11727,AI Specialist,105178,USD,105178,EX,CT,China,L,Indonesia,50,"AWS, Azure, Tableau, SQL",Master,17,Consulting,2024-02-21,2024-05-02,1551,8.1,Advanced Robotics -AI11728,Data Engineer,245876,USD,245876,EX,FL,United States,M,United States,0,"Hadoop, Data Visualization, SQL, AWS",Associate,13,Government,2024-02-17,2024-04-20,1530,5.7,Cognitive Computing -AI11729,Principal Data Scientist,60817,USD,60817,SE,PT,China,M,New Zealand,0,"Kubernetes, PyTorch, Java, Spark, Computer Vision",Bachelor,6,Energy,2025-04-04,2025-06-08,2238,5.3,AI Innovations -AI11730,Autonomous Systems Engineer,159519,AUD,215351,EX,CT,Australia,S,Australia,100,"Linux, Java, Spark",Bachelor,13,Finance,2025-04-30,2025-07-09,686,8.6,TechCorp Inc -AI11731,AI Software Engineer,62606,USD,62606,EN,FL,Norway,S,Norway,100,"Tableau, TensorFlow, Git, Python",PhD,1,Real Estate,2024-09-27,2024-10-24,2295,7.1,TechCorp Inc -AI11732,ML Ops Engineer,87179,USD,87179,MI,FL,Sweden,S,Denmark,50,"Python, GCP, PyTorch, MLOps, AWS",Associate,4,Education,2024-07-30,2024-09-02,2230,5.6,Neural Networks Co -AI11733,Autonomous Systems Engineer,248988,GBP,186741,EX,PT,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, AWS, SQL",PhD,18,Healthcare,2024-01-30,2024-02-15,2260,8.5,DeepTech Ventures -AI11734,Research Scientist,85390,EUR,72582,EN,CT,Austria,L,Austria,50,"Linux, Hadoop, Docker, Python, Kubernetes",Master,0,Manufacturing,2025-03-19,2025-04-19,1718,7.1,Machine Intelligence Group -AI11735,Machine Learning Researcher,85050,USD,85050,EN,FT,Norway,L,Ukraine,0,"TensorFlow, Java, AWS",PhD,0,Healthcare,2024-03-08,2024-05-10,1927,5.7,Machine Intelligence Group -AI11736,Machine Learning Researcher,162248,USD,162248,SE,FL,Denmark,M,China,50,"Python, NLP, TensorFlow",Master,7,Media,2024-11-27,2025-01-11,1029,5.6,Autonomous Tech -AI11737,Machine Learning Engineer,89020,USD,89020,MI,FT,Ireland,M,Ireland,50,"Kubernetes, Data Visualization, Computer Vision, MLOps, NLP",Master,3,Energy,2024-12-05,2024-12-24,1355,7.9,Cloud AI Solutions -AI11738,Head of AI,197899,EUR,168214,EX,FL,Netherlands,L,Netherlands,0,"MLOps, Hadoop, AWS, Scala, TensorFlow",Bachelor,17,Consulting,2024-08-06,2024-10-06,1178,7.4,DataVision Ltd -AI11739,AI Software Engineer,300946,USD,300946,EX,CT,Denmark,L,Denmark,50,"MLOps, Azure, SQL, Kubernetes",Master,11,Gaming,2024-01-05,2024-03-13,949,6.2,Cloud AI Solutions -AI11740,ML Ops Engineer,128716,AUD,173767,SE,FT,Australia,L,Chile,100,"Azure, Scala, SQL, Spark",Associate,6,Technology,2025-01-16,2025-02-04,704,7.8,Autonomous Tech -AI11741,Machine Learning Researcher,69635,USD,69635,MI,FL,Ireland,S,Austria,50,"Mathematics, TensorFlow, Hadoop",Master,4,Energy,2024-04-17,2024-06-02,2256,10,DataVision Ltd -AI11742,Robotics Engineer,75013,USD,75013,EN,FL,Sweden,M,Latvia,0,"Kubernetes, Docker, Hadoop, MLOps",Bachelor,1,Government,2024-01-20,2024-03-25,2410,6.2,Cognitive Computing -AI11743,Head of AI,55579,USD,55579,EX,CT,India,L,India,100,"Spark, Git, R, Computer Vision",PhD,15,Finance,2024-10-15,2024-11-28,2417,8.1,Autonomous Tech -AI11744,Data Engineer,296991,EUR,252442,EX,PT,Netherlands,L,Netherlands,0,"Computer Vision, Python, TensorFlow, Mathematics, GCP",PhD,14,Retail,2024-01-02,2024-02-13,2415,8.6,Algorithmic Solutions -AI11745,Autonomous Systems Engineer,112545,JPY,12379950,MI,PT,Japan,M,Japan,0,"Python, NLP, SQL",PhD,3,Retail,2025-01-21,2025-03-06,1781,7.6,Quantum Computing Inc -AI11746,Computer Vision Engineer,69324,USD,69324,EX,PT,China,M,Colombia,0,"NLP, SQL, Java, R, Tableau",PhD,14,Education,2024-10-24,2024-12-23,519,7.5,DeepTech Ventures -AI11747,AI Research Scientist,98287,USD,98287,SE,FT,South Korea,S,South Korea,100,"R, Hadoop, Java, GCP, NLP",Bachelor,8,Retail,2024-12-05,2024-12-27,2317,7.2,DataVision Ltd -AI11748,AI Research Scientist,115628,SGD,150316,MI,CT,Singapore,L,Singapore,100,"Computer Vision, Python, GCP",Bachelor,2,Energy,2025-04-23,2025-07-03,2069,6.6,TechCorp Inc -AI11749,AI Research Scientist,61446,USD,61446,EN,PT,Finland,L,Finland,50,"Docker, Linux, Tableau",Master,0,Education,2025-02-08,2025-02-26,1567,8.6,Neural Networks Co -AI11750,AI Consultant,120919,USD,120919,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, AWS",Associate,3,Healthcare,2025-03-20,2025-04-13,1792,8.8,Cloud AI Solutions -AI11751,Research Scientist,145685,SGD,189391,SE,FL,Singapore,L,Chile,50,"AWS, Hadoop, NLP",Bachelor,5,Education,2024-11-30,2025-01-18,1182,7.2,DataVision Ltd -AI11752,Autonomous Systems Engineer,67265,USD,67265,EN,FL,South Korea,L,South Africa,100,"SQL, Kubernetes, Mathematics, PyTorch",Master,0,Transportation,2024-03-06,2024-04-05,927,9.6,DeepTech Ventures -AI11753,Principal Data Scientist,93562,CAD,116953,MI,CT,Canada,S,Canada,100,"Tableau, Linux, Kubernetes, GCP, Spark",Bachelor,4,Government,2024-02-26,2024-04-26,1548,5.6,DataVision Ltd -AI11754,AI Software Engineer,128363,EUR,109109,SE,CT,Germany,L,Germany,0,"Azure, Linux, Python, SQL",PhD,9,Media,2024-09-28,2024-12-10,591,5.6,Cognitive Computing -AI11755,Data Scientist,142169,EUR,120844,SE,FL,Netherlands,M,Netherlands,50,"Tableau, NLP, Scala, Java",Master,9,Transportation,2024-10-01,2024-12-03,1840,8.7,Autonomous Tech -AI11756,Data Analyst,82106,EUR,69790,MI,FL,Germany,M,Germany,0,"Java, Git, Computer Vision, Statistics, Data Visualization",PhD,4,Consulting,2024-02-01,2024-04-04,1738,5.8,Cognitive Computing -AI11757,AI Software Engineer,349865,CHF,314879,EX,FL,Switzerland,M,Switzerland,50,"Mathematics, Hadoop, Data Visualization",Associate,17,Automotive,2024-03-27,2024-06-06,661,9.9,Algorithmic Solutions -AI11758,Data Engineer,105787,USD,105787,SE,FL,South Korea,M,South Korea,100,"R, SQL, PyTorch, Mathematics",PhD,5,Telecommunications,2024-12-23,2025-01-18,2347,9.8,Smart Analytics -AI11759,Data Scientist,123402,USD,123402,MI,CT,Sweden,L,Ukraine,100,"NLP, AWS, PyTorch",Master,3,Gaming,2024-11-27,2024-12-22,592,7.6,Autonomous Tech -AI11760,Machine Learning Researcher,239675,USD,239675,EX,FT,Israel,M,Malaysia,100,"Tableau, MLOps, SQL, Mathematics, Git",Associate,12,Transportation,2024-01-13,2024-02-09,1523,8.8,Advanced Robotics -AI11761,Principal Data Scientist,241965,AUD,326653,EX,FT,Australia,L,Australia,100,"Hadoop, Data Visualization, Tableau, Deep Learning, Python",Bachelor,19,Telecommunications,2024-11-07,2024-11-24,853,8.5,Smart Analytics -AI11762,Machine Learning Engineer,76847,USD,76847,MI,FT,Sweden,M,Sweden,50,"MLOps, Computer Vision, SQL, Mathematics",Bachelor,4,Transportation,2024-07-17,2024-09-23,1659,7.9,Cloud AI Solutions -AI11763,Computer Vision Engineer,200851,USD,200851,SE,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Python, Azure",PhD,7,Gaming,2024-11-29,2025-01-11,2272,7.8,Cognitive Computing -AI11764,Research Scientist,130522,USD,130522,MI,FL,Denmark,L,Denmark,50,"Linux, Data Visualization, Hadoop, Git",Associate,3,Automotive,2024-11-22,2025-02-03,1442,5.3,DataVision Ltd -AI11765,AI Research Scientist,68149,USD,68149,EN,PT,South Korea,L,Thailand,50,"GCP, Linux, Spark, Computer Vision, Mathematics",Master,0,Manufacturing,2024-05-29,2024-07-05,673,6.1,Future Systems -AI11766,Principal Data Scientist,61452,EUR,52234,EN,FL,Netherlands,M,Singapore,0,"Python, AWS, Data Visualization, PyTorch, Kubernetes",Associate,0,Education,2025-01-15,2025-03-07,1472,9.6,Neural Networks Co -AI11767,Head of AI,86593,SGD,112571,MI,FL,Singapore,S,Singapore,100,"Mathematics, Computer Vision, Tableau, MLOps, Hadoop",Master,2,Transportation,2024-06-17,2024-08-04,766,9.4,Smart Analytics -AI11768,AI Consultant,62600,USD,62600,EN,FL,Norway,S,Norway,0,"AWS, R, MLOps, SQL",Master,1,Education,2025-03-29,2025-04-29,851,8,TechCorp Inc -AI11769,Machine Learning Researcher,77533,USD,77533,EN,FT,Denmark,M,Denmark,0,"Statistics, SQL, Python",Master,0,Telecommunications,2025-04-18,2025-05-20,2403,6.5,Autonomous Tech -AI11770,Deep Learning Engineer,212689,EUR,180786,EX,PT,Austria,L,Norway,50,"SQL, Git, Hadoop, Docker, GCP",Master,13,Telecommunications,2024-05-17,2024-06-20,2432,9.3,Advanced Robotics -AI11771,Data Scientist,118889,USD,118889,MI,FL,Israel,L,Netherlands,50,"Hadoop, SQL, Scala",PhD,2,Media,2024-08-18,2024-10-17,669,5.3,Advanced Robotics -AI11772,AI Software Engineer,145546,GBP,109160,SE,FT,United Kingdom,M,United Kingdom,100,"Statistics, Python, NLP, Deep Learning, R",Master,7,Telecommunications,2024-09-06,2024-11-05,1299,7.1,Quantum Computing Inc -AI11773,Deep Learning Engineer,91754,EUR,77991,MI,FL,Netherlands,S,Netherlands,100,"Hadoop, TensorFlow, PyTorch",Associate,3,Transportation,2024-07-27,2024-08-18,745,6.8,Autonomous Tech -AI11774,Research Scientist,144229,GBP,108172,EX,FL,United Kingdom,M,Germany,100,"Kubernetes, GCP, SQL",PhD,18,Real Estate,2024-02-16,2024-03-10,1543,8,Neural Networks Co -AI11775,Robotics Engineer,109199,EUR,92819,SE,PT,Austria,S,Austria,0,"Kubernetes, Statistics, Scala, PyTorch",Master,7,Automotive,2025-02-03,2025-03-08,2168,8.3,Quantum Computing Inc -AI11776,Head of AI,56909,USD,56909,EN,CT,Finland,M,Finland,100,"SQL, Scala, PyTorch, GCP, Java",PhD,1,Real Estate,2024-04-16,2024-05-27,1343,7,Algorithmic Solutions -AI11777,AI Consultant,117496,USD,117496,EX,PT,China,M,China,100,"Deep Learning, Docker, Data Visualization, Tableau, R",Associate,19,Transportation,2024-01-09,2024-02-01,1773,6.1,Predictive Systems -AI11778,Machine Learning Researcher,115487,USD,115487,MI,FL,Denmark,L,Denmark,100,"Kubernetes, PyTorch, Azure, Spark",Associate,4,Telecommunications,2024-01-02,2024-03-15,980,7.2,Cognitive Computing -AI11779,Computer Vision Engineer,115188,EUR,97910,MI,FT,Netherlands,M,India,0,"Data Visualization, NLP, SQL",PhD,4,Telecommunications,2024-08-07,2024-09-06,609,6.4,Cognitive Computing -AI11780,ML Ops Engineer,192782,USD,192782,EX,FL,Ireland,M,Ireland,50,"MLOps, Statistics, Mathematics, Scala, Data Visualization",Associate,16,Media,2025-03-21,2025-04-24,648,9.1,DeepTech Ventures -AI11781,Principal Data Scientist,158600,EUR,134810,EX,CT,Netherlands,S,Netherlands,100,"Python, Linux, Deep Learning",PhD,14,Automotive,2024-09-23,2024-11-18,582,5.5,Smart Analytics -AI11782,Robotics Engineer,64447,GBP,48335,EN,CT,United Kingdom,M,United Kingdom,100,"Computer Vision, Git, Tableau",Master,0,Finance,2024-07-25,2024-09-05,1713,6.5,Future Systems -AI11783,Research Scientist,189773,CHF,170796,SE,FL,Switzerland,M,Ukraine,100,"Computer Vision, Python, TensorFlow",Associate,8,Transportation,2024-05-28,2024-07-24,1824,6.1,Predictive Systems -AI11784,ML Ops Engineer,136525,CAD,170656,SE,CT,Canada,L,Canada,100,"Docker, Azure, Mathematics",Bachelor,9,Healthcare,2024-09-22,2024-11-21,1768,5.3,Algorithmic Solutions -AI11785,Head of AI,108746,USD,108746,EX,FT,South Korea,S,South Korea,50,"Azure, R, Scala, Tableau, Statistics",Master,16,Technology,2025-03-14,2025-05-24,2133,6.3,TechCorp Inc -AI11786,Robotics Engineer,79890,USD,79890,EX,PT,China,S,United States,50,"Computer Vision, Hadoop, GCP, Statistics",PhD,15,Automotive,2024-11-29,2024-12-20,1445,5.3,Predictive Systems -AI11787,AI Architect,128508,USD,128508,EX,FT,Finland,S,Nigeria,50,"Kubernetes, Docker, Spark",Master,16,Technology,2024-11-28,2025-01-05,1335,10,Algorithmic Solutions -AI11788,Computer Vision Engineer,149717,EUR,127259,SE,FT,Netherlands,M,Netherlands,0,"Mathematics, GCP, SQL",Master,6,Consulting,2024-05-22,2024-07-12,893,5.5,Cognitive Computing -AI11789,ML Ops Engineer,74780,CHF,67302,EN,CT,Switzerland,M,Italy,100,"Computer Vision, Mathematics, Tableau, Data Visualization",Master,0,Automotive,2025-03-26,2025-04-11,846,8.7,Autonomous Tech -AI11790,Data Analyst,86855,EUR,73827,EN,FT,France,L,France,50,"PyTorch, Deep Learning, NLP, R, AWS",Associate,1,Gaming,2024-03-06,2024-04-30,577,9.1,Cloud AI Solutions -AI11791,AI Research Scientist,153299,AUD,206954,SE,CT,Australia,L,Egypt,0,"TensorFlow, Python, Deep Learning",Master,9,Energy,2024-04-26,2024-05-11,1120,5.6,DeepTech Ventures -AI11792,Head of AI,53256,USD,53256,EN,PT,Ireland,S,Ireland,100,"GCP, R, Data Visualization, Hadoop, Kubernetes",Associate,1,Gaming,2024-03-29,2024-04-27,1989,7.5,Digital Transformation LLC -AI11793,ML Ops Engineer,104761,USD,104761,EN,CT,Norway,L,Norway,0,"Computer Vision, Git, GCP, Data Visualization",Associate,1,Automotive,2024-09-08,2024-11-13,1927,5.5,DeepTech Ventures -AI11794,AI Product Manager,257772,JPY,28354920,EX,CT,Japan,L,United States,0,"Java, R, Linux, SQL, NLP",Bachelor,11,Education,2024-02-19,2024-04-22,1495,7.6,Smart Analytics -AI11795,Data Analyst,113051,USD,113051,SE,FL,Israel,M,Thailand,50,"Mathematics, Deep Learning, Data Visualization",Master,5,Telecommunications,2024-01-04,2024-03-06,728,5.4,AI Innovations -AI11796,AI Architect,184356,JPY,20279160,SE,PT,Japan,L,Japan,100,"AWS, Tableau, Python",Bachelor,9,Consulting,2024-04-03,2024-04-24,1525,6.7,DeepTech Ventures -AI11797,AI Research Scientist,48522,CAD,60653,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, Tableau",Bachelor,1,Education,2024-05-25,2024-07-20,1523,6.9,Machine Intelligence Group -AI11798,Data Engineer,57358,SGD,74565,EN,CT,Singapore,M,Singapore,100,"Kubernetes, Docker, MLOps, Scala, Mathematics",Associate,0,Education,2025-04-18,2025-05-03,1292,8.7,Future Systems -AI11799,AI Architect,92877,CAD,116096,SE,FT,Canada,S,Canada,0,"Statistics, AWS, Deep Learning",Associate,8,Manufacturing,2024-01-06,2024-03-13,2113,9.1,Cloud AI Solutions -AI11800,Data Engineer,64999,USD,64999,MI,FT,Israel,S,Israel,0,"GCP, Mathematics, Data Visualization, Python",Associate,3,Transportation,2024-03-22,2024-04-16,2159,9.7,Neural Networks Co -AI11801,Deep Learning Engineer,216255,EUR,183817,EX,PT,Germany,L,Germany,50,"SQL, AWS, Tableau",Bachelor,14,Technology,2024-05-01,2024-07-07,742,8.8,DataVision Ltd -AI11802,AI Software Engineer,139600,CAD,174500,SE,FT,Canada,L,Canada,50,"PyTorch, Kubernetes, Computer Vision, Python, Tableau",PhD,9,Gaming,2024-05-08,2024-07-01,1981,9.8,Machine Intelligence Group -AI11803,AI Specialist,214259,USD,214259,SE,FT,Norway,L,Norway,50,"Python, Docker, Azure, Mathematics, Java",PhD,9,Automotive,2025-04-27,2025-05-11,2008,5.9,Predictive Systems -AI11804,Machine Learning Engineer,90613,USD,90613,EX,FL,India,L,India,0,"SQL, Git, Deep Learning, AWS",PhD,12,Education,2024-07-17,2024-09-06,1898,5.4,Future Systems -AI11805,AI Software Engineer,237611,AUD,320775,EX,PT,Australia,M,Australia,0,"Java, Computer Vision, Python, Mathematics",Associate,18,Automotive,2024-09-15,2024-11-23,2125,7.3,Quantum Computing Inc -AI11806,AI Specialist,85520,USD,85520,MI,CT,Israel,L,Israel,50,"Linux, SQL, Python, Scala",Master,2,Technology,2025-02-25,2025-03-11,1858,8.4,Digital Transformation LLC -AI11807,Computer Vision Engineer,120980,CAD,151225,EX,CT,Canada,S,Ukraine,0,"Computer Vision, Azure, Spark",Bachelor,10,Healthcare,2024-04-19,2024-05-31,940,7,Cognitive Computing -AI11808,Autonomous Systems Engineer,91834,EUR,78059,MI,PT,Austria,S,Portugal,50,"PyTorch, Scala, Data Visualization",Master,4,Government,2024-02-27,2024-04-21,516,7.9,DeepTech Ventures -AI11809,Computer Vision Engineer,197241,USD,197241,EX,FT,United States,M,Nigeria,0,"Deep Learning, TensorFlow, Hadoop, GCP",Bachelor,19,Education,2024-11-07,2024-12-28,652,7.3,Predictive Systems -AI11810,Machine Learning Researcher,26172,USD,26172,MI,FL,India,S,India,100,"Linux, NLP, Scala, Statistics",PhD,2,Consulting,2025-02-09,2025-03-14,603,5,Smart Analytics -AI11811,ML Ops Engineer,95730,USD,95730,SE,FT,Israel,S,Israel,0,"Tableau, Kubernetes, TensorFlow, Data Visualization, NLP",Master,5,Consulting,2024-02-26,2024-04-07,1257,6.2,Quantum Computing Inc -AI11812,Machine Learning Engineer,269491,USD,269491,EX,FT,United States,S,United States,50,"Tableau, R, Azure",Associate,15,Consulting,2024-11-04,2024-11-29,2469,8.9,Digital Transformation LLC -AI11813,Research Scientist,103816,CHF,93434,EN,FL,Switzerland,M,Switzerland,0,"GCP, R, Mathematics",Master,1,Government,2025-01-21,2025-02-25,1061,9.4,DataVision Ltd -AI11814,Data Analyst,120743,USD,120743,SE,PT,South Korea,M,Nigeria,100,"PyTorch, Java, Data Visualization",Bachelor,8,Education,2024-08-20,2024-10-07,2458,8.4,TechCorp Inc -AI11815,Data Scientist,23025,USD,23025,MI,FT,India,S,Denmark,100,"Linux, Hadoop, Python, Computer Vision",Associate,4,Consulting,2024-04-04,2024-05-15,1444,5.5,Machine Intelligence Group -AI11816,Autonomous Systems Engineer,44505,USD,44505,SE,FT,India,L,Romania,50,"Hadoop, Data Visualization, Git",Associate,6,Telecommunications,2024-10-04,2024-11-23,2406,8.7,Cognitive Computing -AI11817,Head of AI,105183,JPY,11570130,MI,PT,Japan,L,South Korea,100,"GCP, Spark, Deep Learning",PhD,3,Gaming,2024-09-03,2024-09-30,633,5.8,Autonomous Tech -AI11818,Machine Learning Engineer,137294,USD,137294,EX,PT,Israel,S,Mexico,0,"R, Scala, Docker, GCP",Master,12,Finance,2024-02-03,2024-03-05,1274,8.3,DeepTech Ventures -AI11819,ML Ops Engineer,101696,GBP,76272,SE,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Azure, PyTorch, Statistics, Mathematics",Associate,6,Telecommunications,2024-04-08,2024-06-15,766,7.1,Autonomous Tech -AI11820,Data Analyst,64069,EUR,54459,MI,PT,Austria,S,Austria,50,"Docker, NLP, Mathematics, Data Visualization",Bachelor,3,Energy,2024-02-28,2024-03-14,748,5.4,TechCorp Inc -AI11821,AI Product Manager,111264,USD,111264,SE,PT,South Korea,M,South Korea,100,"Data Visualization, Linux, SQL, R, Deep Learning",PhD,6,Media,2024-09-16,2024-10-28,2399,8.8,Smart Analytics -AI11822,Principal Data Scientist,109807,USD,109807,MI,PT,Denmark,M,Denmark,50,"Python, Spark, Deep Learning",Associate,4,Telecommunications,2024-10-04,2024-11-24,1800,7.9,Cloud AI Solutions -AI11823,AI Research Scientist,92835,EUR,78910,MI,CT,Netherlands,M,Netherlands,100,"Spark, Computer Vision, PyTorch, Tableau",Associate,3,Retail,2025-02-04,2025-03-07,2441,6.1,Neural Networks Co -AI11824,AI Product Manager,203369,EUR,172864,EX,CT,France,M,France,0,"PyTorch, Docker, Deep Learning",Bachelor,13,Retail,2024-09-09,2024-10-29,1041,7.4,Future Systems -AI11825,Head of AI,177370,USD,177370,EX,CT,Israel,S,Israel,100,"Git, AWS, Python, TensorFlow",Master,17,Telecommunications,2024-10-29,2024-12-16,1070,9.3,Quantum Computing Inc -AI11826,AI Software Engineer,244805,CHF,220325,EX,PT,Switzerland,L,Switzerland,100,"Docker, Python, Data Visualization, TensorFlow",PhD,18,Retail,2024-05-25,2024-07-11,1889,8.5,Algorithmic Solutions -AI11827,AI Product Manager,35462,USD,35462,MI,FT,India,L,India,100,"Tableau, AWS, Mathematics, Linux",Bachelor,3,Healthcare,2024-11-22,2024-12-07,1136,9.7,Future Systems -AI11828,Data Scientist,68404,CAD,85505,EN,FL,Canada,L,Romania,100,"Azure, Scala, SQL, PyTorch, Spark",Associate,0,Real Estate,2024-07-18,2024-09-20,2166,6.5,Cognitive Computing -AI11829,Autonomous Systems Engineer,128996,AUD,174145,SE,FT,Australia,L,Ukraine,100,"GCP, Spark, MLOps, NLP, SQL",Bachelor,7,Healthcare,2024-10-08,2024-12-04,1539,5,Machine Intelligence Group -AI11830,Data Analyst,72807,EUR,61886,EN,FT,Austria,M,Austria,100,"Git, R, Scala, Deep Learning, SQL",PhD,0,Energy,2024-03-02,2024-04-10,2177,7.5,Autonomous Tech -AI11831,Deep Learning Engineer,107118,USD,107118,MI,CT,Denmark,M,Denmark,100,"PyTorch, Data Visualization, GCP, TensorFlow, Linux",Bachelor,4,Automotive,2025-04-11,2025-05-01,2040,8.1,Cognitive Computing -AI11832,Principal Data Scientist,27731,USD,27731,MI,FT,India,M,India,0,"Python, Linux, TensorFlow",Master,4,Consulting,2024-09-04,2024-10-14,976,8.5,Autonomous Tech -AI11833,AI Research Scientist,74228,USD,74228,EN,PT,Norway,M,Norway,100,"Mathematics, Kubernetes, R, Spark, Scala",PhD,0,Automotive,2025-03-29,2025-05-21,2187,9.4,Digital Transformation LLC -AI11834,AI Consultant,77712,USD,77712,EN,FL,Sweden,M,Sweden,0,"Hadoop, PyTorch, Git, Computer Vision",Associate,1,Manufacturing,2024-02-25,2024-05-01,826,6.1,AI Innovations -AI11835,AI Specialist,94668,USD,94668,EX,PT,China,S,China,50,"SQL, NLP, Kubernetes, PyTorch, GCP",PhD,19,Consulting,2024-03-18,2024-04-22,1984,5.4,Cloud AI Solutions -AI11836,AI Architect,212705,USD,212705,EX,FT,South Korea,L,Luxembourg,100,"R, GCP, Tableau",Master,16,Manufacturing,2024-01-15,2024-03-28,2206,6.1,Quantum Computing Inc -AI11837,AI Research Scientist,200761,CHF,180685,EX,PT,Switzerland,S,Switzerland,50,"Kubernetes, SQL, PyTorch, R",Master,11,Real Estate,2024-05-02,2024-06-07,1090,7.1,DeepTech Ventures -AI11838,Machine Learning Engineer,85039,AUD,114803,MI,CT,Australia,M,Australia,100,"Statistics, Tableau, MLOps, Java",Bachelor,2,Manufacturing,2024-08-10,2024-09-22,1756,9.5,Predictive Systems -AI11839,AI Product Manager,62080,USD,62080,EX,CT,India,L,India,50,"Scala, Git, Tableau, Kubernetes, Azure",Bachelor,12,Real Estate,2024-10-03,2024-10-30,987,5.1,Cognitive Computing -AI11840,AI Architect,196292,USD,196292,EX,CT,Sweden,M,Argentina,100,"R, SQL, Deep Learning",Associate,18,Education,2024-03-22,2024-04-29,1280,9.4,Quantum Computing Inc -AI11841,AI Specialist,158220,USD,158220,EX,CT,Sweden,M,Sweden,0,"SQL, TensorFlow, Deep Learning",PhD,19,Gaming,2024-03-13,2024-04-13,1358,7.8,Cognitive Computing -AI11842,AI Architect,29068,USD,29068,MI,FT,India,M,Indonesia,100,"Computer Vision, Hadoop, Linux",Master,4,Gaming,2024-09-14,2024-10-28,913,7.7,DataVision Ltd -AI11843,Data Scientist,61344,GBP,46008,EN,CT,United Kingdom,M,France,0,"TensorFlow, Java, Mathematics, GCP",PhD,1,Transportation,2024-06-15,2024-08-16,1521,7.4,Smart Analytics -AI11844,AI Architect,192580,CHF,173322,SE,FL,Switzerland,M,Switzerland,50,"TensorFlow, NLP, Linux",PhD,5,Technology,2024-01-20,2024-02-12,1743,9.7,Predictive Systems -AI11845,Data Engineer,69295,SGD,90084,EN,PT,Singapore,L,Singapore,100,"SQL, GCP, Computer Vision",Master,0,Retail,2024-09-16,2024-11-18,2296,8.5,TechCorp Inc -AI11846,Computer Vision Engineer,132554,EUR,112671,SE,CT,France,M,France,50,"Kubernetes, Scala, Computer Vision, Java, Docker",Associate,7,Real Estate,2024-05-10,2024-07-04,826,8.8,Quantum Computing Inc -AI11847,AI Consultant,172103,EUR,146288,EX,FL,France,S,Czech Republic,0,"R, SQL, Statistics, Azure, Computer Vision",Master,14,Manufacturing,2024-02-10,2024-03-01,1648,7.4,DeepTech Ventures -AI11848,AI Specialist,113947,GBP,85460,SE,FT,United Kingdom,M,United Kingdom,50,"Git, Deep Learning, R",Bachelor,8,Energy,2025-04-13,2025-05-21,1447,9.4,Cognitive Computing -AI11849,AI Consultant,38972,USD,38972,MI,CT,China,M,China,50,"Tableau, Hadoop, Deep Learning, Spark, GCP",Associate,2,Retail,2024-07-28,2024-08-19,2480,9.4,Future Systems -AI11850,Robotics Engineer,129198,EUR,109818,SE,PT,Austria,L,Canada,100,"SQL, Git, NLP, Python, Kubernetes",Associate,9,Healthcare,2024-11-20,2025-01-20,2336,7.3,DataVision Ltd -AI11851,Machine Learning Researcher,85968,USD,85968,EN,FL,Sweden,L,Sweden,0,"R, Azure, NLP, SQL, Data Visualization",Bachelor,1,Government,2024-03-21,2024-04-10,2330,5.2,Cognitive Computing -AI11852,AI Specialist,89602,USD,89602,EN,PT,Denmark,M,Portugal,50,"Computer Vision, Java, Python, Scala",PhD,1,Finance,2024-11-17,2025-01-06,2474,5.5,Digital Transformation LLC -AI11853,AI Software Engineer,75324,USD,75324,EN,PT,United States,S,United States,50,"GCP, Scala, Data Visualization, Spark",PhD,1,Real Estate,2025-02-06,2025-02-26,830,9.3,AI Innovations -AI11854,AI Consultant,89924,USD,89924,MI,CT,Finland,S,Finland,0,"Azure, Docker, Deep Learning",Master,3,Media,2024-11-17,2025-01-10,844,9.8,Digital Transformation LLC -AI11855,Machine Learning Engineer,65329,USD,65329,EN,PT,South Korea,M,Switzerland,100,"R, Hadoop, Spark, Mathematics, Computer Vision",Bachelor,0,Healthcare,2024-04-30,2024-05-28,547,5.2,DataVision Ltd -AI11856,AI Software Engineer,93470,AUD,126185,MI,CT,Australia,M,Australia,0,"MLOps, R, Tableau",Master,4,Media,2024-11-29,2024-12-22,1805,8.1,Digital Transformation LLC -AI11857,Research Scientist,95936,JPY,10552960,EN,PT,Japan,L,Japan,100,"Git, Python, MLOps",Master,0,Finance,2024-08-17,2024-10-26,1297,8.2,Predictive Systems -AI11858,Machine Learning Researcher,112418,SGD,146143,MI,PT,Singapore,M,Singapore,0,"Linux, R, Hadoop, Statistics, MLOps",Associate,4,Consulting,2024-08-31,2024-09-30,1676,9.9,AI Innovations -AI11859,AI Architect,210662,USD,210662,EX,CT,Sweden,S,Sweden,0,"SQL, Hadoop, TensorFlow, Spark",Bachelor,16,Gaming,2024-09-10,2024-10-07,1986,7.4,DataVision Ltd -AI11860,Machine Learning Engineer,55827,USD,55827,EN,FT,South Korea,M,South Korea,0,"SQL, Docker, MLOps, Azure",Associate,1,Real Estate,2024-07-09,2024-08-20,2250,5.2,Neural Networks Co -AI11861,Deep Learning Engineer,174827,USD,174827,SE,PT,Denmark,M,Denmark,50,"Computer Vision, SQL, Kubernetes, Mathematics",Bachelor,5,Healthcare,2024-07-18,2024-09-25,1268,5.9,Machine Intelligence Group -AI11862,Head of AI,222968,USD,222968,EX,FT,South Korea,L,Nigeria,100,"PyTorch, Hadoop, TensorFlow",PhD,17,Energy,2024-10-30,2024-12-18,1644,6,Autonomous Tech -AI11863,Data Analyst,250630,USD,250630,EX,FL,Denmark,L,Estonia,50,"Python, Docker, MLOps, Azure",Bachelor,15,Telecommunications,2024-07-29,2024-09-02,606,6.1,Cloud AI Solutions -AI11864,AI Product Manager,188795,CHF,169916,SE,FT,Switzerland,M,Switzerland,0,"R, Docker, Tableau, Azure, PyTorch",Associate,5,Technology,2025-01-24,2025-02-22,1357,7.6,AI Innovations -AI11865,Data Scientist,116184,EUR,98756,SE,FT,France,S,Italy,50,"Linux, Java, Scala, Kubernetes, MLOps",PhD,5,Automotive,2025-02-15,2025-03-26,2428,5.5,Digital Transformation LLC -AI11866,Deep Learning Engineer,85463,USD,85463,EN,FL,Israel,L,Switzerland,100,"Deep Learning, MLOps, Statistics, NLP",Associate,1,Government,2024-04-16,2024-05-04,2237,6.5,Smart Analytics -AI11867,Robotics Engineer,62097,EUR,52782,EN,PT,Netherlands,S,Netherlands,0,"Hadoop, Kubernetes, Python",Associate,1,Energy,2024-11-30,2025-02-04,1363,9.3,Cognitive Computing -AI11868,Data Scientist,77625,USD,77625,EN,FL,Israel,L,Israel,50,"AWS, Kubernetes, PyTorch, Docker",Bachelor,1,Technology,2025-01-14,2025-03-07,1422,5.7,Digital Transformation LLC -AI11869,Data Engineer,89334,JPY,9826740,MI,CT,Japan,M,Canada,100,"Linux, GCP, Statistics, AWS, Hadoop",Bachelor,2,Manufacturing,2024-09-21,2024-10-19,733,9.5,Neural Networks Co -AI11870,Deep Learning Engineer,115065,EUR,97805,SE,CT,Austria,M,Austria,0,"SQL, Git, Tableau, Linux",Master,7,Consulting,2024-02-05,2024-03-02,1057,6.6,Quantum Computing Inc -AI11871,NLP Engineer,29565,USD,29565,MI,CT,India,M,India,100,"Python, Linux, Tableau, TensorFlow",PhD,2,Manufacturing,2025-03-21,2025-05-10,2038,8.4,Neural Networks Co -AI11872,Autonomous Systems Engineer,151856,USD,151856,SE,FL,Denmark,M,Denmark,0,"PyTorch, Docker, Tableau, Spark, GCP",PhD,6,Real Estate,2024-01-03,2024-03-04,795,6.1,Algorithmic Solutions -AI11873,Principal Data Scientist,59832,USD,59832,EN,FL,Israel,L,Australia,100,"Git, TensorFlow, SQL, NLP",Associate,1,Government,2024-03-07,2024-04-25,2026,9.5,Cloud AI Solutions -AI11874,Data Scientist,100061,USD,100061,SE,FT,Finland,S,Finland,0,"Docker, Python, TensorFlow, Tableau, Kubernetes",Bachelor,7,Gaming,2024-09-16,2024-11-15,2469,8.8,Autonomous Tech -AI11875,Computer Vision Engineer,55729,EUR,47370,EN,FL,France,S,France,50,"Docker, R, GCP, SQL",PhD,0,Education,2024-02-06,2024-02-29,1845,7.7,Quantum Computing Inc -AI11876,Machine Learning Researcher,47262,EUR,40173,EN,FT,France,S,France,50,"Python, TensorFlow, MLOps, Deep Learning, Java",Master,1,Education,2025-03-20,2025-05-04,1036,9,AI Innovations -AI11877,AI Product Manager,126583,USD,126583,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Linux, Java",Master,19,Automotive,2025-04-04,2025-06-11,1998,8.7,Autonomous Tech -AI11878,NLP Engineer,46601,EUR,39611,EN,PT,France,S,France,50,"Scala, Statistics, Linux, TensorFlow, MLOps",Master,0,Consulting,2024-05-26,2024-06-17,1646,7.1,AI Innovations -AI11879,AI Research Scientist,53772,GBP,40329,EN,PT,United Kingdom,S,United Kingdom,100,"Tableau, Git, Computer Vision",PhD,1,Technology,2025-03-20,2025-05-25,1581,5.1,Smart Analytics -AI11880,Data Scientist,203974,USD,203974,EX,FL,Ireland,L,Ireland,100,"Git, Python, Scala",Bachelor,17,Consulting,2024-09-04,2024-10-29,2278,7.8,AI Innovations -AI11881,AI Product Manager,23558,USD,23558,EN,FT,China,S,China,100,"Linux, Scala, Mathematics, Computer Vision",PhD,0,Gaming,2025-01-23,2025-04-01,1696,9.1,Smart Analytics -AI11882,Head of AI,195265,USD,195265,EX,FT,Finland,M,Finland,0,"Kubernetes, PyTorch, Scala, Git, AWS",Bachelor,12,Media,2025-03-21,2025-04-29,2425,9.6,Quantum Computing Inc -AI11883,AI Consultant,125170,USD,125170,MI,PT,United States,L,United States,0,"Tableau, Hadoop, PyTorch",Master,2,Energy,2025-03-05,2025-04-29,574,5.3,Autonomous Tech -AI11884,Machine Learning Researcher,154524,USD,154524,MI,PT,Norway,L,Norway,0,"Python, Scala, GCP, Computer Vision, AWS",Master,4,Gaming,2024-12-19,2025-02-23,1061,6.8,Future Systems -AI11885,Principal Data Scientist,78129,EUR,66410,MI,FT,Germany,M,Switzerland,100,"Mathematics, TensorFlow, Kubernetes",Master,4,Education,2024-12-15,2025-02-02,1911,6.1,AI Innovations -AI11886,AI Specialist,82474,USD,82474,EN,FL,Denmark,L,Denmark,100,"AWS, Linux, Tableau",Master,0,Government,2024-10-31,2024-11-29,1015,6.7,Digital Transformation LLC -AI11887,Data Analyst,60195,USD,60195,EN,CT,Ireland,S,Ireland,50,"Hadoop, NLP, Scala, Azure, Spark",Associate,0,Manufacturing,2025-03-11,2025-04-08,535,7.4,TechCorp Inc -AI11888,Computer Vision Engineer,85391,JPY,9393010,EN,FL,Japan,M,Japan,50,"Scala, Python, Mathematics, GCP",Master,0,Consulting,2025-02-05,2025-02-24,2183,8.4,DeepTech Ventures -AI11889,AI Product Manager,138187,GBP,103640,SE,PT,United Kingdom,M,United Kingdom,0,"NLP, PyTorch, SQL",Associate,7,Government,2025-04-01,2025-05-16,1041,7.6,Future Systems -AI11890,AI Research Scientist,90522,USD,90522,MI,CT,United States,S,Brazil,50,"SQL, Docker, PyTorch",PhD,4,Consulting,2025-02-18,2025-04-13,1067,8.7,TechCorp Inc -AI11891,Data Scientist,118016,EUR,100314,SE,FL,France,S,France,100,"Deep Learning, Spark, Python, Computer Vision, Linux",Bachelor,5,Media,2024-05-20,2024-06-20,2461,7.7,Quantum Computing Inc -AI11892,Principal Data Scientist,45677,USD,45677,MI,FT,China,L,China,50,"TensorFlow, Statistics, Git, MLOps",Master,2,Real Estate,2024-04-06,2024-05-06,1862,7.3,DataVision Ltd -AI11893,AI Specialist,80735,USD,80735,MI,PT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, SQL, MLOps",Associate,3,Energy,2024-10-09,2024-11-16,2497,6.8,Smart Analytics -AI11894,Data Engineer,174749,EUR,148537,SE,FT,Netherlands,L,Nigeria,50,"Kubernetes, SQL, Python",Master,6,Media,2024-01-28,2024-03-02,2235,5.5,DataVision Ltd -AI11895,Autonomous Systems Engineer,153986,USD,153986,EX,FL,South Korea,S,South Korea,50,"GCP, Python, Data Visualization",Master,19,Government,2024-07-05,2024-09-07,1093,6.4,Digital Transformation LLC -AI11896,AI Consultant,239879,GBP,179909,EX,PT,United Kingdom,S,United Kingdom,100,"Java, TensorFlow, Docker, SQL, AWS",Associate,10,Gaming,2025-01-25,2025-02-15,814,7.5,Algorithmic Solutions -AI11897,AI Product Manager,113202,JPY,12452220,MI,PT,Japan,L,Japan,0,"NLP, Spark, Python, TensorFlow, Git",Bachelor,3,Government,2024-05-24,2024-06-15,618,5.6,Quantum Computing Inc -AI11898,Deep Learning Engineer,176289,USD,176289,EX,FT,Sweden,M,Sweden,0,"Data Visualization, GCP, Linux",Associate,19,Real Estate,2024-08-14,2024-10-16,1171,7.7,Quantum Computing Inc -AI11899,AI Specialist,74877,CAD,93596,EN,FL,Canada,M,Romania,100,"Hadoop, Data Visualization, AWS, Java",Master,0,Transportation,2024-04-05,2024-05-19,1958,5.7,Autonomous Tech -AI11900,Deep Learning Engineer,121054,USD,121054,SE,PT,Israel,M,South Africa,50,"GCP, AWS, Mathematics, Tableau",Bachelor,9,Manufacturing,2024-11-17,2025-01-18,2146,7.1,Predictive Systems -AI11901,Head of AI,121862,CAD,152328,SE,FL,Canada,M,Chile,0,"Git, GCP, Spark, R, AWS",Bachelor,8,Finance,2025-04-11,2025-05-05,2480,8.7,Neural Networks Co -AI11902,AI Product Manager,68676,USD,68676,MI,PT,South Korea,L,South Korea,50,"Tableau, Kubernetes, Python",PhD,3,Manufacturing,2024-04-05,2024-05-28,951,7.4,Cognitive Computing -AI11903,AI Specialist,140355,CAD,175444,SE,CT,Canada,L,Canada,100,"Spark, SQL, Computer Vision",Bachelor,7,Automotive,2024-06-20,2024-07-21,738,5.6,Neural Networks Co -AI11904,Data Scientist,107343,EUR,91242,SE,CT,Austria,S,United States,100,"Linux, R, SQL, Spark, GCP",Master,6,Retail,2025-01-17,2025-02-24,1393,5.6,Advanced Robotics -AI11905,Data Analyst,124289,USD,124289,SE,PT,Ireland,M,Ireland,100,"Statistics, Tableau, SQL, Data Visualization, Python",Master,6,Telecommunications,2024-01-19,2024-03-30,1647,7.1,Cloud AI Solutions -AI11906,Deep Learning Engineer,111588,USD,111588,MI,FL,Ireland,L,Ireland,50,"Mathematics, TensorFlow, Tableau, Computer Vision",Associate,2,Consulting,2024-04-17,2024-06-23,2381,5.5,Advanced Robotics -AI11907,NLP Engineer,140602,AUD,189813,SE,PT,Australia,M,Australia,50,"SQL, Azure, AWS",Master,7,Technology,2024-05-08,2024-07-12,583,6.9,Autonomous Tech -AI11908,Deep Learning Engineer,220576,USD,220576,SE,PT,Norway,L,Norway,0,"Deep Learning, Data Visualization, Java, GCP",Master,6,Real Estate,2024-09-12,2024-10-13,1736,5.6,Neural Networks Co -AI11909,Data Scientist,63791,USD,63791,EX,FT,India,L,India,50,"Java, Spark, GCP, Tableau, Computer Vision",PhD,16,Retail,2025-01-06,2025-02-17,1610,9.6,Predictive Systems -AI11910,Robotics Engineer,115544,EUR,98212,SE,FT,Austria,S,Italy,100,"PyTorch, TensorFlow, Computer Vision, GCP, Spark",PhD,5,Gaming,2024-11-21,2024-12-28,2140,6.8,Digital Transformation LLC -AI11911,Computer Vision Engineer,141470,USD,141470,SE,FL,Finland,L,Canada,50,"Java, Python, Kubernetes",Bachelor,7,Transportation,2024-04-17,2024-05-11,1095,5.5,Machine Intelligence Group -AI11912,Robotics Engineer,119546,USD,119546,SE,FL,Sweden,M,Switzerland,100,"Kubernetes, AWS, Computer Vision",Associate,8,Energy,2024-09-13,2024-11-23,1690,7.2,TechCorp Inc -AI11913,Robotics Engineer,70709,SGD,91922,EN,PT,Singapore,L,Singapore,0,"Spark, Linux, Scala, Docker",PhD,0,Technology,2024-05-01,2024-06-11,984,8.9,Cognitive Computing -AI11914,Autonomous Systems Engineer,139969,AUD,188958,SE,FT,Australia,M,Australia,100,"Python, Spark, TensorFlow, MLOps, AWS",Bachelor,7,Gaming,2025-03-01,2025-03-18,1633,6,Machine Intelligence Group -AI11915,Computer Vision Engineer,249239,USD,249239,EX,CT,United States,M,United States,100,"Data Visualization, AWS, TensorFlow",Bachelor,19,Healthcare,2024-11-12,2024-12-16,1154,6.6,DataVision Ltd -AI11916,Data Scientist,72005,EUR,61204,EN,FL,France,M,France,0,"PyTorch, Scala, Data Visualization, Statistics, AWS",Master,1,Real Estate,2024-05-07,2024-05-25,1077,7.7,Digital Transformation LLC -AI11917,Head of AI,82315,USD,82315,MI,FL,Finland,M,Finland,0,"Java, Computer Vision, Tableau, Python",PhD,2,Media,2025-01-19,2025-03-24,653,5.4,DataVision Ltd -AI11918,AI Product Manager,172045,USD,172045,SE,PT,Sweden,L,Sweden,100,"GCP, Linux, Deep Learning, Scala, MLOps",Associate,6,Consulting,2024-12-20,2025-02-20,1852,8.2,Quantum Computing Inc -AI11919,Data Engineer,227310,EUR,193214,EX,CT,Germany,M,Germany,100,"Data Visualization, Python, R",PhD,19,Technology,2025-02-23,2025-04-07,560,9,AI Innovations -AI11920,Head of AI,84752,GBP,63564,MI,FL,United Kingdom,M,United Kingdom,50,"Azure, Tableau, Linux",Bachelor,3,Energy,2024-04-16,2024-06-06,789,5.7,Autonomous Tech -AI11921,Principal Data Scientist,141732,USD,141732,SE,FL,Finland,L,Brazil,50,"MLOps, Scala, TensorFlow, Deep Learning, GCP",PhD,7,Transportation,2024-12-08,2025-01-04,734,9.6,Autonomous Tech -AI11922,AI Architect,169211,USD,169211,SE,PT,Denmark,S,Argentina,100,"Java, Python, MLOps, TensorFlow, Kubernetes",Bachelor,8,Transportation,2025-03-07,2025-04-21,1516,9.5,Machine Intelligence Group -AI11923,Research Scientist,247914,GBP,185936,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, Python, GCP, R, Hadoop",Master,17,Automotive,2024-02-19,2024-03-13,849,7.8,TechCorp Inc -AI11924,Deep Learning Engineer,66536,CAD,83170,EN,FT,Canada,S,Malaysia,0,"PyTorch, Azure, MLOps",PhD,1,Energy,2024-05-29,2024-06-13,1642,5.4,DeepTech Ventures -AI11925,Robotics Engineer,133785,CHF,120407,MI,FL,Switzerland,M,Switzerland,50,"Spark, MLOps, GCP, Docker, Java",PhD,4,Finance,2025-02-01,2025-04-14,1364,5.8,Digital Transformation LLC -AI11926,Data Analyst,65022,GBP,48767,EN,CT,United Kingdom,L,United Kingdom,100,"Spark, GCP, SQL, NLP",Master,1,Real Estate,2025-04-21,2025-05-22,1446,6.4,Cognitive Computing -AI11927,NLP Engineer,247285,USD,247285,EX,FL,Norway,M,Norway,50,"NLP, SQL, Azure",Master,11,Government,2025-01-11,2025-03-04,767,9.8,Neural Networks Co -AI11928,NLP Engineer,51541,USD,51541,EN,FL,Finland,M,Finland,0,"Java, Kubernetes, Data Visualization, Docker",PhD,0,Manufacturing,2024-01-27,2024-02-26,1836,8.4,Digital Transformation LLC -AI11929,AI Consultant,186164,GBP,139623,SE,PT,United Kingdom,L,New Zealand,0,"Linux, Scala, Mathematics, R, Azure",Master,6,Telecommunications,2024-09-01,2024-11-09,2042,7.3,Quantum Computing Inc -AI11930,NLP Engineer,80116,USD,80116,MI,CT,Ireland,S,Ireland,0,"Python, Hadoop, GCP, TensorFlow",PhD,4,Media,2025-01-02,2025-01-21,1716,5.6,Neural Networks Co -AI11931,AI Consultant,62190,EUR,52862,EN,CT,Austria,M,Netherlands,100,"Hadoop, Git, NLP, TensorFlow",PhD,0,Gaming,2024-04-08,2024-04-25,1587,5.8,Cognitive Computing -AI11932,Principal Data Scientist,99982,USD,99982,MI,PT,Sweden,M,Italy,50,"Git, Azure, Kubernetes",Bachelor,3,Finance,2024-03-18,2024-05-28,2079,6.7,Smart Analytics -AI11933,AI Architect,126992,CAD,158740,SE,PT,Canada,L,Austria,100,"Git, Scala, Data Visualization, Python",PhD,5,Consulting,2024-11-05,2024-12-12,1638,6.9,Quantum Computing Inc -AI11934,NLP Engineer,283236,USD,283236,EX,FL,Denmark,M,Denmark,0,"Mathematics, Linux, Git",PhD,12,Real Estate,2024-10-07,2024-11-14,1479,8.2,AI Innovations -AI11935,Machine Learning Engineer,211425,CHF,190283,SE,PT,Switzerland,L,Singapore,100,"Linux, Data Visualization, Hadoop",PhD,8,Manufacturing,2024-07-10,2024-09-08,2048,7.7,Cloud AI Solutions -AI11936,Data Scientist,44730,CAD,55913,EN,PT,Canada,S,Israel,0,"Linux, GCP, R, Hadoop, SQL",Associate,0,Retail,2024-10-24,2024-12-23,1274,8.7,Digital Transformation LLC -AI11937,Data Analyst,34838,USD,34838,MI,PT,China,S,China,50,"Scala, AWS, Docker",Associate,4,Finance,2024-02-18,2024-03-21,2184,6.9,Smart Analytics -AI11938,AI Software Engineer,225196,USD,225196,EX,FL,United States,S,United States,0,"Java, R, Hadoop, Kubernetes, PyTorch",PhD,12,Transportation,2024-03-07,2024-04-13,1541,7.1,Neural Networks Co -AI11939,Head of AI,122390,USD,122390,MI,FT,United States,M,United States,0,"PyTorch, TensorFlow, Computer Vision, Docker, Mathematics",Associate,2,Media,2024-09-02,2024-10-09,1198,6.3,TechCorp Inc -AI11940,Deep Learning Engineer,134314,USD,134314,SE,FL,Finland,M,Finland,100,"AWS, SQL, PyTorch",Master,9,Government,2024-05-03,2024-05-19,2257,9.4,Machine Intelligence Group -AI11941,Autonomous Systems Engineer,63509,USD,63509,EN,PT,Israel,M,Israel,100,"Hadoop, Deep Learning, Scala, Python",Master,1,Transportation,2024-08-10,2024-09-13,1368,6.5,Algorithmic Solutions -AI11942,AI Software Engineer,179124,JPY,19703640,SE,CT,Japan,L,Japan,50,"Spark, SQL, R, Scala",Bachelor,6,Gaming,2024-10-09,2024-12-13,2235,7.7,DataVision Ltd -AI11943,AI Architect,128394,GBP,96296,MI,PT,United Kingdom,L,Poland,100,"SQL, Tableau, Mathematics, Data Visualization",PhD,3,Manufacturing,2024-12-16,2025-02-07,1582,6.4,TechCorp Inc -AI11944,Deep Learning Engineer,126623,CHF,113961,MI,FL,Switzerland,L,Brazil,0,"SQL, Scala, MLOps, R, Git",PhD,3,Energy,2024-05-23,2024-07-18,2276,6.4,Algorithmic Solutions -AI11945,AI Architect,113817,EUR,96744,SE,PT,Germany,M,Germany,50,"TensorFlow, Docker, Kubernetes",Master,8,Finance,2024-02-03,2024-02-24,1339,8,Quantum Computing Inc -AI11946,AI Architect,139320,USD,139320,EX,CT,South Korea,L,South Korea,100,"MLOps, Scala, Linux, Deep Learning, Computer Vision",Master,16,Technology,2025-04-05,2025-06-13,2440,7.6,Advanced Robotics -AI11947,AI Product Manager,123195,EUR,104716,SE,FL,Germany,S,Germany,100,"Python, MLOps, Tableau, TensorFlow, GCP",Master,6,Transportation,2024-01-02,2024-03-03,1983,8.6,Quantum Computing Inc -AI11948,AI Architect,59966,CAD,74958,EN,PT,Canada,M,Ireland,0,"Computer Vision, NLP, GCP, Linux, Azure",PhD,0,Finance,2024-01-24,2024-02-14,1953,5.8,Digital Transformation LLC -AI11949,AI Research Scientist,32241,USD,32241,EN,CT,India,L,India,100,"Kubernetes, Data Visualization, Azure",Bachelor,1,Energy,2024-12-07,2025-02-02,1441,6.2,Cognitive Computing -AI11950,Autonomous Systems Engineer,125879,CAD,157349,EX,FT,Canada,S,Canada,0,"Git, GCP, MLOps",Bachelor,13,Retail,2024-04-20,2024-05-25,1270,8.7,Quantum Computing Inc -AI11951,Head of AI,63170,USD,63170,MI,FL,Israel,S,Israel,0,"SQL, PyTorch, Azure, MLOps, Git",Bachelor,2,Media,2025-03-23,2025-04-21,1528,5.1,Digital Transformation LLC -AI11952,NLP Engineer,155126,JPY,17063860,EX,CT,Japan,M,New Zealand,50,"Python, TensorFlow, NLP",Associate,16,Real Estate,2024-09-30,2024-12-04,2446,10,Neural Networks Co -AI11953,AI Architect,86565,CAD,108206,MI,CT,Canada,M,Canada,100,"SQL, Python, Spark, Scala",Bachelor,2,Manufacturing,2024-03-29,2024-05-19,1589,6.7,Quantum Computing Inc -AI11954,Principal Data Scientist,103951,EUR,88358,MI,CT,Germany,L,Germany,100,"TensorFlow, Data Visualization, Python, Mathematics, Kubernetes",PhD,4,Retail,2024-04-23,2024-05-07,955,9.4,Algorithmic Solutions -AI11955,Data Engineer,121572,USD,121572,SE,FL,Ireland,L,Ireland,100,"Linux, TensorFlow, Docker",Associate,8,Real Estate,2024-07-01,2024-08-10,1827,8.3,TechCorp Inc -AI11956,Deep Learning Engineer,80289,USD,80289,EN,CT,Denmark,M,Denmark,50,"R, Azure, AWS",Associate,0,Transportation,2024-11-04,2025-01-06,1019,9.5,Smart Analytics -AI11957,Head of AI,142312,USD,142312,SE,FL,United States,L,United States,100,"NLP, Hadoop, Scala, Tableau",Bachelor,9,Media,2024-08-18,2024-10-13,1326,7.4,Future Systems -AI11958,ML Ops Engineer,45228,USD,45228,MI,PT,China,L,China,100,"Deep Learning, Kubernetes, Spark, NLP",Associate,3,Government,2025-01-01,2025-03-10,994,5.3,Algorithmic Solutions -AI11959,AI Architect,105421,SGD,137047,MI,FL,Singapore,M,Singapore,50,"NLP, TensorFlow, Tableau",Associate,3,Transportation,2025-03-20,2025-04-19,1425,7,Cognitive Computing -AI11960,Autonomous Systems Engineer,253979,CHF,228581,EX,FL,Switzerland,M,Thailand,100,"Hadoop, Scala, PyTorch, AWS, Data Visualization",Associate,11,Government,2025-04-18,2025-05-21,1367,7.3,Neural Networks Co -AI11961,Autonomous Systems Engineer,80682,EUR,68580,MI,PT,Netherlands,S,Chile,50,"NLP, Git, Spark, AWS, Hadoop",Bachelor,4,Education,2025-04-09,2025-05-09,1274,6.8,Machine Intelligence Group -AI11962,Machine Learning Engineer,58564,USD,58564,SE,PT,China,L,China,0,"Java, GCP, Deep Learning",Master,5,Energy,2024-08-17,2024-09-08,1669,7.7,Future Systems -AI11963,ML Ops Engineer,165885,EUR,141002,EX,FL,France,M,France,0,"Python, Deep Learning, Data Visualization",PhD,19,Media,2024-08-07,2024-09-19,783,10,Digital Transformation LLC -AI11964,Data Engineer,190838,USD,190838,SE,PT,Denmark,M,Austria,100,"Deep Learning, AWS, Statistics",Bachelor,6,Telecommunications,2024-02-14,2024-04-06,2414,9.6,Predictive Systems -AI11965,AI Specialist,55369,USD,55369,EX,FL,India,M,India,0,"Docker, GCP, Data Visualization, Mathematics, Tableau",Associate,17,Automotive,2024-01-09,2024-02-27,1164,10,AI Innovations -AI11966,Data Scientist,71105,EUR,60439,EN,FL,Netherlands,L,Netherlands,0,"Spark, PyTorch, Mathematics",Master,0,Telecommunications,2024-03-25,2024-05-30,1018,7.5,Quantum Computing Inc -AI11967,Deep Learning Engineer,75264,USD,75264,EN,FL,Sweden,M,Sweden,0,"GCP, Tableau, Python, Data Visualization, TensorFlow",Associate,0,Retail,2024-07-03,2024-07-22,1393,6.1,Smart Analytics -AI11968,Autonomous Systems Engineer,164799,USD,164799,SE,FT,Norway,M,Norway,100,"Hadoop, Kubernetes, Python, R, SQL",Master,9,Gaming,2024-05-10,2024-06-23,518,6.2,Neural Networks Co -AI11969,Machine Learning Engineer,76924,EUR,65385,MI,FT,Austria,M,Portugal,50,"Spark, Azure, Kubernetes",PhD,3,Telecommunications,2024-11-09,2024-12-18,913,6.5,Cognitive Computing -AI11970,Principal Data Scientist,43350,USD,43350,MI,PT,India,L,Ireland,50,"Git, Azure, Hadoop",Associate,3,Healthcare,2025-04-15,2025-06-19,1003,9.3,Predictive Systems -AI11971,AI Product Manager,61506,EUR,52280,EN,FL,Austria,S,Austria,0,"Kubernetes, Hadoop, PyTorch, Git, Data Visualization",Associate,0,Education,2025-03-18,2025-05-22,1927,6.3,Cognitive Computing -AI11972,AI Architect,102342,AUD,138162,MI,PT,Australia,M,Australia,100,"Python, SQL, Hadoop",PhD,4,Consulting,2024-04-13,2024-05-08,1056,9.6,Digital Transformation LLC -AI11973,AI Product Manager,167315,CHF,150584,SE,CT,Switzerland,L,Switzerland,50,"Scala, Computer Vision, SQL, GCP, MLOps",PhD,8,Transportation,2024-12-07,2025-01-08,1876,6.2,Quantum Computing Inc -AI11974,AI Consultant,128451,EUR,109183,EX,PT,France,M,France,0,"Spark, Python, Statistics, Java, TensorFlow",Master,19,Real Estate,2024-08-06,2024-09-04,2292,9.4,Autonomous Tech -AI11975,Robotics Engineer,71957,GBP,53968,EN,FT,United Kingdom,S,United Kingdom,0,"Scala, GCP, Computer Vision, Docker",Master,0,Healthcare,2024-04-15,2024-05-17,529,6.3,DataVision Ltd -AI11976,ML Ops Engineer,117836,AUD,159079,SE,PT,Australia,L,Argentina,50,"Python, PyTorch, Git, Computer Vision, Statistics",PhD,6,Education,2024-06-29,2024-07-16,2090,5.9,Algorithmic Solutions -AI11977,Data Engineer,121319,SGD,157715,MI,PT,Singapore,L,New Zealand,50,"GCP, Git, Mathematics, Computer Vision, TensorFlow",Bachelor,4,Real Estate,2024-05-16,2024-07-28,1785,8.7,TechCorp Inc -AI11978,Machine Learning Researcher,118151,EUR,100428,EX,FL,France,S,France,100,"TensorFlow, SQL, MLOps",Associate,13,Retail,2025-04-12,2025-06-22,1142,6.1,Cognitive Computing -AI11979,AI Software Engineer,82974,GBP,62231,MI,FL,United Kingdom,S,United Kingdom,0,"Linux, AWS, Deep Learning, Scala",Bachelor,3,Telecommunications,2024-01-09,2024-02-03,662,7.9,Future Systems -AI11980,Data Analyst,91372,USD,91372,EN,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-10-03,2024-10-26,2231,9.5,Predictive Systems -AI11981,AI Product Manager,33654,USD,33654,EN,FL,China,M,China,0,"Spark, SQL, Linux, Hadoop",Associate,0,Healthcare,2025-03-07,2025-05-19,1924,5.9,Neural Networks Co -AI11982,Head of AI,156264,EUR,132824,SE,FL,France,L,South Africa,50,"Kubernetes, SQL, PyTorch, Data Visualization, Computer Vision",PhD,8,Education,2024-11-24,2025-01-21,1009,7.4,Cognitive Computing -AI11983,Data Analyst,84928,CAD,106160,MI,FL,Canada,M,Canada,50,"PyTorch, Spark, Data Visualization, SQL, Docker",Master,4,Technology,2024-11-12,2024-12-15,574,9.6,DataVision Ltd -AI11984,Research Scientist,129254,CAD,161568,SE,PT,Canada,M,Canada,0,"Python, Azure, Statistics, Java, Computer Vision",Master,9,Consulting,2024-12-28,2025-02-11,2081,9.1,Autonomous Tech -AI11985,AI Consultant,206297,USD,206297,EX,CT,Finland,M,Finland,50,"AWS, Spark, Mathematics, Hadoop, GCP",Master,10,Real Estate,2024-06-25,2024-08-25,2117,6.1,Algorithmic Solutions -AI11986,Data Analyst,105092,EUR,89328,MI,CT,Austria,L,Austria,0,"Linux, TensorFlow, Scala, Azure",Master,3,Government,2024-04-25,2024-05-27,2118,6.5,DataVision Ltd -AI11987,Deep Learning Engineer,216314,USD,216314,EX,PT,Denmark,L,Denmark,0,"TensorFlow, Scala, GCP, R, Tableau",PhD,19,Media,2025-03-05,2025-04-18,2302,8.6,Quantum Computing Inc -AI11988,AI Software Engineer,114139,EUR,97018,SE,FT,France,S,France,0,"Java, NLP, Git, Statistics",Master,6,Gaming,2024-11-06,2025-01-18,2402,8.2,DataVision Ltd -AI11989,Autonomous Systems Engineer,253207,GBP,189905,EX,FT,United Kingdom,L,United Kingdom,0,"R, Mathematics, SQL, Java",Bachelor,12,Manufacturing,2024-11-08,2024-12-27,534,9.6,Cloud AI Solutions -AI11990,Data Engineer,117195,CHF,105476,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Docker, NLP, PyTorch",PhD,4,Technology,2024-03-28,2024-04-27,998,5.9,Quantum Computing Inc -AI11991,AI Research Scientist,75215,USD,75215,EN,FT,United States,S,United States,100,"TensorFlow, GCP, Java, Scala, Python",Master,1,Energy,2025-03-13,2025-03-30,2257,8.4,AI Innovations -AI11992,Data Scientist,91308,USD,91308,MI,CT,Ireland,S,Ireland,100,"Azure, Linux, Scala",PhD,2,Telecommunications,2024-05-29,2024-07-03,1125,9.7,Cloud AI Solutions -AI11993,NLP Engineer,101994,USD,101994,MI,FT,United States,L,United States,50,"Python, R, PyTorch, Deep Learning",Master,3,Healthcare,2025-03-09,2025-04-03,1316,7.3,Digital Transformation LLC -AI11994,AI Consultant,63814,SGD,82958,EN,FT,Singapore,M,Singapore,0,"Java, AWS, PyTorch",PhD,1,Gaming,2024-12-23,2025-02-07,1775,5.5,Predictive Systems -AI11995,AI Software Engineer,82096,CHF,73886,EN,FL,Switzerland,M,Switzerland,50,"SQL, Tableau, TensorFlow, Docker",PhD,1,Manufacturing,2024-01-26,2024-03-03,2046,7.2,Future Systems -AI11996,Data Analyst,139446,USD,139446,SE,FL,United States,L,United States,0,"Python, Data Visualization, Kubernetes",Associate,8,Consulting,2025-04-27,2025-05-31,1178,5.2,Cognitive Computing -AI11997,AI Consultant,50489,CAD,63111,EN,PT,Canada,S,Canada,0,"Mathematics, SQL, AWS, Deep Learning",Master,1,Healthcare,2024-07-07,2024-08-30,1144,8.2,Autonomous Tech -AI11998,AI Architect,202463,EUR,172094,EX,CT,France,L,France,50,"R, Statistics, Tableau",Associate,18,Retail,2024-05-07,2024-06-08,2361,5.1,TechCorp Inc -AI11999,AI Consultant,257007,USD,257007,EX,FL,Israel,L,Israel,0,"SQL, Git, Spark",Associate,16,Healthcare,2025-03-29,2025-06-02,2113,8.4,Future Systems -AI12000,Data Analyst,165859,JPY,18244490,SE,FL,Japan,L,Japan,50,"Kubernetes, Mathematics, MLOps",PhD,5,Education,2024-11-04,2025-01-12,1168,5.2,Quantum Computing Inc -AI12001,NLP Engineer,269890,USD,269890,EX,FL,Norway,S,Norway,0,"PyTorch, Python, Git, Kubernetes",Associate,19,Technology,2024-03-09,2024-03-25,1218,5.8,Algorithmic Solutions -AI12002,AI Product Manager,249468,EUR,212048,EX,FL,Netherlands,M,Netherlands,100,"Azure, Tableau, Statistics",PhD,16,Telecommunications,2024-06-14,2024-07-15,534,5,Cognitive Computing -AI12003,Robotics Engineer,146512,SGD,190466,SE,FT,Singapore,M,Singapore,100,"Python, Deep Learning, Computer Vision, Scala",Master,7,Manufacturing,2024-12-29,2025-01-27,728,5.8,Smart Analytics -AI12004,Robotics Engineer,74373,EUR,63217,MI,CT,Austria,S,Austria,0,"NLP, Docker, PyTorch, Azure, Mathematics",Master,4,Gaming,2024-11-09,2025-01-16,1187,8.1,Cognitive Computing -AI12005,AI Consultant,191280,USD,191280,EX,CT,Israel,M,Ukraine,100,"SQL, R, MLOps, Docker",Associate,18,Gaming,2024-03-28,2024-05-16,789,5.7,Algorithmic Solutions -AI12006,Machine Learning Engineer,122748,EUR,104336,SE,CT,Germany,M,Germany,100,"Java, R, NLP, Computer Vision, Azure",Bachelor,8,Healthcare,2024-11-22,2025-02-03,1419,5.3,Autonomous Tech -AI12007,Deep Learning Engineer,40909,USD,40909,SE,PT,India,M,India,50,"NLP, Hadoop, MLOps",Associate,7,Government,2024-08-07,2024-09-08,2498,9.3,TechCorp Inc -AI12008,Principal Data Scientist,51031,USD,51031,EX,CT,India,M,India,0,"Kubernetes, Docker, Azure",PhD,12,Telecommunications,2025-01-21,2025-02-12,1890,10,Advanced Robotics -AI12009,Deep Learning Engineer,111269,CHF,100142,MI,PT,Switzerland,M,Switzerland,0,"Java, TensorFlow, Linux",Associate,4,Automotive,2024-09-13,2024-10-07,1949,6.5,Machine Intelligence Group -AI12010,AI Architect,68234,EUR,57999,EN,FT,Austria,L,Switzerland,100,"Scala, Python, Docker, SQL, Statistics",Associate,1,Transportation,2024-12-05,2025-02-01,2202,5.9,Cognitive Computing -AI12011,Deep Learning Engineer,138852,USD,138852,MI,FT,Denmark,L,Romania,50,"Deep Learning, Python, Scala, GCP, SQL",Bachelor,2,Retail,2024-03-29,2024-05-12,2392,8.3,TechCorp Inc -AI12012,AI Research Scientist,112322,USD,112322,SE,PT,Israel,M,Israel,0,"Java, Git, Mathematics, Statistics",Bachelor,8,Government,2024-03-31,2024-04-21,1766,5.1,Autonomous Tech -AI12013,AI Consultant,172547,AUD,232938,EX,PT,Australia,L,Australia,0,"Python, PyTorch, Mathematics, Java, Tableau",Bachelor,19,Energy,2025-01-13,2025-02-03,1606,5.6,TechCorp Inc -AI12014,Machine Learning Engineer,210775,CHF,189698,SE,CT,Switzerland,M,Switzerland,50,"Docker, R, Computer Vision, Hadoop, MLOps",Associate,7,Education,2025-02-25,2025-03-24,891,6.1,Cognitive Computing -AI12015,ML Ops Engineer,42437,USD,42437,SE,CT,India,M,India,0,"Hadoop, R, Statistics, Git, Docker",Master,5,Education,2025-02-20,2025-03-15,1846,7.9,Predictive Systems -AI12016,Research Scientist,75457,USD,75457,MI,FT,South Korea,M,South Korea,0,"Docker, Tableau, Computer Vision, Java, Hadoop",Master,2,Technology,2024-01-16,2024-03-09,510,5.1,Cognitive Computing -AI12017,AI Architect,81055,AUD,109424,MI,FT,Australia,S,Israel,0,"Data Visualization, TensorFlow, Tableau",Associate,3,Manufacturing,2025-03-19,2025-04-30,1842,8.3,Autonomous Tech -AI12018,Data Analyst,158028,GBP,118521,EX,CT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Mathematics, Hadoop, MLOps",Associate,13,Telecommunications,2024-11-20,2025-01-02,2151,6.6,Quantum Computing Inc -AI12019,Computer Vision Engineer,85667,EUR,72817,MI,FT,Austria,L,Austria,100,"Scala, Mathematics, MLOps, Java",Associate,3,Automotive,2025-03-06,2025-04-14,1455,7.1,Neural Networks Co -AI12020,AI Consultant,92565,USD,92565,MI,FL,South Korea,L,South Korea,100,"Mathematics, AWS, MLOps, R, Java",Bachelor,2,Media,2024-02-15,2024-04-03,2106,7.6,Cloud AI Solutions -AI12021,Data Scientist,218585,USD,218585,EX,FL,United States,S,United States,0,"Azure, SQL, Linux",Master,19,Technology,2025-02-21,2025-04-29,1692,7.1,Smart Analytics -AI12022,Machine Learning Engineer,135669,CHF,122102,MI,FT,Switzerland,S,Switzerland,100,"Kubernetes, SQL, Computer Vision, PyTorch",Bachelor,4,Transportation,2024-06-19,2024-07-10,1965,5.8,Autonomous Tech -AI12023,Machine Learning Engineer,161267,SGD,209647,SE,FT,Singapore,M,Canada,50,"Scala, Python, Docker, Kubernetes, Tableau",Associate,5,Consulting,2024-08-07,2024-09-11,1851,5.4,Digital Transformation LLC -AI12024,Machine Learning Researcher,161659,EUR,137410,EX,PT,Austria,L,Austria,100,"Python, AWS, Azure, Deep Learning, R",Associate,12,Finance,2024-01-06,2024-02-24,730,5.1,Digital Transformation LLC -AI12025,ML Ops Engineer,84538,GBP,63404,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Java, Tableau, Statistics",Bachelor,0,Media,2024-02-18,2024-03-04,1481,8.2,Cloud AI Solutions -AI12026,AI Consultant,123396,EUR,104887,SE,CT,Germany,S,Poland,100,"Git, SQL, Kubernetes",Master,7,Finance,2025-03-17,2025-05-03,1628,9.6,Cognitive Computing -AI12027,NLP Engineer,94740,USD,94740,SE,FT,Sweden,S,Sweden,50,"SQL, NLP, Azure, Mathematics, Python",Bachelor,7,Automotive,2024-09-21,2024-11-21,1527,9.1,DataVision Ltd -AI12028,Machine Learning Engineer,237856,USD,237856,EX,PT,Denmark,M,Denmark,100,"Scala, NLP, Java, Data Visualization",Master,11,Technology,2024-10-29,2024-12-31,1067,9.5,Digital Transformation LLC -AI12029,Computer Vision Engineer,144410,USD,144410,EX,PT,South Korea,L,South Korea,100,"Data Visualization, Python, Tableau, Docker, Deep Learning",PhD,11,Technology,2024-08-16,2024-10-08,1659,7.5,TechCorp Inc -AI12030,Autonomous Systems Engineer,62979,EUR,53532,EN,FL,Netherlands,S,Latvia,50,"R, Deep Learning, Tableau",Bachelor,0,Gaming,2024-12-04,2024-12-27,1609,6.9,Smart Analytics -AI12031,AI Consultant,134825,CHF,121343,MI,FL,Switzerland,L,Argentina,50,"PyTorch, Computer Vision, TensorFlow",Master,4,Gaming,2024-01-15,2024-03-22,853,7.2,Machine Intelligence Group -AI12032,Deep Learning Engineer,115226,USD,115226,MI,PT,Ireland,L,Ireland,50,"Docker, Tableau, Statistics, GCP, Deep Learning",Master,4,Media,2024-02-19,2024-03-12,1816,5.4,Smart Analytics -AI12033,AI Consultant,128090,JPY,14089900,MI,FL,Japan,L,Japan,100,"Statistics, Spark, PyTorch, Data Visualization",Master,3,Education,2024-10-11,2024-12-12,2013,5.1,TechCorp Inc -AI12034,Machine Learning Engineer,148729,USD,148729,EX,FT,Sweden,S,Sweden,100,"Data Visualization, Git, PyTorch, Hadoop",Master,11,Media,2024-02-10,2024-03-19,1419,5.6,Smart Analytics -AI12035,AI Research Scientist,42922,USD,42922,MI,FL,China,L,China,100,"Computer Vision, Tableau, GCP, Spark, PyTorch",Bachelor,3,Telecommunications,2024-01-25,2024-03-15,582,6,Algorithmic Solutions -AI12036,Robotics Engineer,97362,USD,97362,EN,CT,Norway,L,Norway,100,"Computer Vision, Data Visualization, MLOps, Tableau, NLP",Associate,0,Healthcare,2024-09-09,2024-09-29,1851,9.7,DeepTech Ventures -AI12037,Machine Learning Researcher,59118,USD,59118,SE,CT,China,M,China,0,"Hadoop, Linux, SQL",Bachelor,7,Consulting,2024-07-02,2024-08-19,871,7.8,Advanced Robotics -AI12038,Computer Vision Engineer,73489,CAD,91861,EN,PT,Canada,M,Israel,50,"AWS, Azure, SQL, PyTorch, NLP",PhD,0,Gaming,2024-01-07,2024-02-24,2056,5.3,Smart Analytics -AI12039,Deep Learning Engineer,111684,CAD,139605,SE,PT,Canada,L,Brazil,50,"Linux, Hadoop, Data Visualization, Kubernetes",PhD,7,Automotive,2024-04-02,2024-05-09,957,7.3,Cloud AI Solutions -AI12040,AI Research Scientist,64479,EUR,54807,EN,FT,France,S,Switzerland,100,"PyTorch, NLP, Deep Learning",PhD,0,Energy,2025-02-25,2025-04-11,1960,5.1,Predictive Systems -AI12041,AI Specialist,175295,USD,175295,SE,CT,United States,M,United States,0,"Hadoop, Tableau, Linux, Scala, Python",Master,8,Technology,2024-09-16,2024-11-24,2420,5.5,Neural Networks Co -AI12042,Deep Learning Engineer,29310,USD,29310,EN,FL,China,L,China,100,"Java, R, NLP, GCP, Tableau",Associate,0,Real Estate,2024-08-06,2024-10-11,1524,7.3,DataVision Ltd -AI12043,Data Engineer,109138,EUR,92767,MI,FL,Germany,M,Canada,50,"Data Visualization, TensorFlow, PyTorch",Bachelor,3,Technology,2024-07-28,2024-09-08,1065,6.9,Future Systems -AI12044,AI Software Engineer,74590,USD,74590,EX,FT,India,L,India,0,"GCP, Java, Linux",Master,11,Manufacturing,2024-10-05,2024-12-16,1788,8.5,Neural Networks Co -AI12045,AI Consultant,137100,USD,137100,MI,CT,United States,L,Egypt,100,"Tableau, Java, Mathematics, SQL, R",Associate,3,Media,2024-05-21,2024-07-26,1922,7.8,Advanced Robotics -AI12046,AI Research Scientist,169631,USD,169631,EX,FL,Ireland,L,Ireland,50,"SQL, Git, Mathematics, AWS",Master,15,Manufacturing,2024-05-25,2024-07-31,2372,5.4,Digital Transformation LLC -AI12047,Machine Learning Engineer,182100,USD,182100,SE,PT,Norway,L,Norway,0,"TensorFlow, SQL, Java, Computer Vision, Git",Master,6,Retail,2025-03-10,2025-04-11,1534,6.7,Neural Networks Co -AI12048,Robotics Engineer,30598,USD,30598,EN,FT,India,L,India,50,"Data Visualization, Kubernetes, Scala",Associate,0,Consulting,2025-04-20,2025-05-24,707,5.7,Smart Analytics -AI12049,AI Research Scientist,59506,EUR,50580,EN,CT,France,S,France,50,"Computer Vision, NLP, Git, Kubernetes",Bachelor,0,Healthcare,2025-02-24,2025-05-06,2354,5.9,Machine Intelligence Group -AI12050,AI Consultant,176984,CAD,221230,EX,FT,Canada,S,Belgium,50,"Computer Vision, Java, Spark, Statistics, Deep Learning",Bachelor,19,Transportation,2025-04-06,2025-05-11,753,5.1,Machine Intelligence Group -AI12051,Head of AI,76635,USD,76635,MI,FL,Finland,M,Argentina,0,"PyTorch, Python, MLOps",PhD,3,Transportation,2024-10-21,2024-11-09,2223,5.7,Cognitive Computing -AI12052,ML Ops Engineer,142757,USD,142757,SE,CT,Israel,M,Israel,0,"Tableau, NLP, Mathematics",PhD,6,Gaming,2024-10-27,2024-11-28,2278,9.3,Cloud AI Solutions -AI12053,Machine Learning Engineer,157767,AUD,212985,SE,FL,Australia,L,Australia,100,"NLP, Linux, Mathematics",Associate,5,Transportation,2025-01-19,2025-03-14,1357,10,Smart Analytics -AI12054,Data Scientist,155133,JPY,17064630,SE,FL,Japan,M,Japan,50,"MLOps, AWS, R",Associate,8,Education,2024-04-22,2024-05-14,679,8.7,Machine Intelligence Group -AI12055,AI Consultant,103814,USD,103814,MI,FL,Finland,M,Indonesia,50,"Mathematics, AWS, Linux",Associate,3,Finance,2024-02-21,2024-05-04,619,7.6,Smart Analytics -AI12056,NLP Engineer,126742,CHF,114068,MI,PT,Switzerland,M,Switzerland,0,"AWS, Kubernetes, Tableau",Associate,3,Real Estate,2024-09-05,2024-10-20,1227,7.1,Advanced Robotics -AI12057,Machine Learning Engineer,149642,SGD,194535,EX,PT,Singapore,S,Singapore,0,"Python, NLP, SQL, AWS, TensorFlow",Associate,14,Telecommunications,2024-04-11,2024-06-04,599,5.6,Quantum Computing Inc -AI12058,Machine Learning Engineer,119639,GBP,89729,SE,PT,United Kingdom,S,United Kingdom,50,"Tableau, Python, Data Visualization",Bachelor,9,Retail,2025-01-06,2025-02-27,1845,5.5,Quantum Computing Inc -AI12059,AI Architect,94779,CAD,118474,SE,FT,Canada,S,Canada,100,"Scala, Java, Docker, Kubernetes, Data Visualization",Master,7,Media,2024-05-15,2024-07-19,2195,7.1,Advanced Robotics -AI12060,Data Scientist,289132,USD,289132,EX,FT,Norway,S,Norway,100,"TensorFlow, R, NLP",Associate,12,Automotive,2025-01-12,2025-02-15,1149,7.1,Cloud AI Solutions -AI12061,NLP Engineer,81914,EUR,69627,EN,CT,Germany,L,Germany,0,"Linux, Git, SQL",Master,1,Government,2024-08-06,2024-10-05,2272,6.8,DataVision Ltd -AI12062,Autonomous Systems Engineer,143423,EUR,121910,SE,FT,Austria,L,Austria,100,"Python, Java, Deep Learning",Associate,5,Healthcare,2024-03-01,2024-04-12,2001,7.8,Predictive Systems -AI12063,Autonomous Systems Engineer,67712,EUR,57555,EN,CT,Austria,S,Austria,0,"Scala, Linux, Python, AWS, Docker",Bachelor,0,Government,2025-01-18,2025-03-03,2191,5.6,Autonomous Tech -AI12064,Robotics Engineer,119637,GBP,89728,SE,FT,United Kingdom,S,Spain,50,"Python, AWS, Data Visualization",PhD,9,Education,2024-04-23,2024-06-03,787,5.7,Digital Transformation LLC -AI12065,Computer Vision Engineer,95673,EUR,81322,MI,FL,Netherlands,L,South Korea,0,"Tableau, TensorFlow, Python, Linux",PhD,3,Finance,2024-08-30,2024-10-22,1692,6.9,Predictive Systems -AI12066,ML Ops Engineer,206540,EUR,175559,EX,FT,Germany,M,Germany,50,"R, Mathematics, TensorFlow",PhD,11,Media,2025-02-23,2025-04-21,1614,9.8,TechCorp Inc -AI12067,ML Ops Engineer,251443,USD,251443,EX,FT,United States,S,United States,0,"Python, Scala, Docker, Deep Learning, NLP",Associate,10,Automotive,2024-03-08,2024-04-10,620,7.3,DataVision Ltd -AI12068,Data Engineer,116790,CAD,145988,SE,CT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Computer Vision, R",Associate,7,Education,2025-01-18,2025-03-12,1376,5.8,Algorithmic Solutions -AI12069,Computer Vision Engineer,113165,EUR,96190,SE,FT,Germany,S,Portugal,0,"Docker, Python, NLP, Computer Vision",Master,6,Consulting,2024-09-18,2024-11-17,1378,5.3,Digital Transformation LLC -AI12070,AI Research Scientist,117256,CHF,105530,MI,PT,Switzerland,S,Switzerland,100,"AWS, Scala, Computer Vision",PhD,3,Healthcare,2024-06-12,2024-07-14,1082,8.6,Algorithmic Solutions -AI12071,AI Specialist,300778,USD,300778,EX,PT,Norway,M,Norway,0,"Java, Python, GCP, Spark, TensorFlow",Bachelor,12,Technology,2025-02-04,2025-04-13,867,7.6,Predictive Systems -AI12072,Robotics Engineer,141137,SGD,183478,SE,CT,Singapore,L,Singapore,100,"Git, Linux, GCP, Spark",Associate,6,Finance,2024-02-12,2024-03-12,975,6.3,Advanced Robotics -AI12073,Robotics Engineer,46660,USD,46660,MI,CT,China,S,China,0,"AWS, Kubernetes, Docker",Bachelor,4,Consulting,2024-06-19,2024-08-01,2391,8.2,Autonomous Tech -AI12074,Principal Data Scientist,167557,USD,167557,EX,PT,Israel,L,Israel,0,"Azure, SQL, Data Visualization, Deep Learning",Associate,10,Consulting,2024-06-19,2024-08-16,820,5,Digital Transformation LLC -AI12075,Data Engineer,152794,USD,152794,SE,PT,United States,L,United States,100,"Scala, GCP, Docker",Associate,9,Automotive,2024-05-24,2024-06-07,1160,7.9,Neural Networks Co -AI12076,AI Consultant,96217,USD,96217,EX,FL,China,L,Romania,100,"R, SQL, Linux, Docker",Master,18,Healthcare,2024-12-25,2025-02-03,1390,8.2,Digital Transformation LLC -AI12077,AI Architect,93192,CHF,83873,EN,CT,Switzerland,L,Switzerland,50,"Azure, Python, MLOps, Scala, R",Master,0,Education,2024-03-12,2024-04-16,2202,6.2,Autonomous Tech -AI12078,Robotics Engineer,104902,USD,104902,MI,FL,Ireland,L,Ireland,0,"Azure, NLP, Spark, AWS",Master,4,Real Estate,2024-01-09,2024-03-22,1676,9.4,Future Systems -AI12079,AI Software Engineer,77869,USD,77869,MI,PT,South Korea,S,South Korea,100,"GCP, Kubernetes, Tableau, Mathematics, SQL",Associate,4,Finance,2024-05-23,2024-06-22,2322,9.6,DataVision Ltd -AI12080,AI Software Engineer,61860,USD,61860,SE,FT,China,M,China,100,"Kubernetes, Python, Computer Vision, TensorFlow, Linux",Master,6,Transportation,2024-10-05,2024-11-14,2429,6.5,Predictive Systems -AI12081,ML Ops Engineer,149417,USD,149417,SE,FT,Ireland,L,Ireland,0,"Docker, Azure, Linux, GCP, Java",PhD,9,Government,2024-11-12,2024-12-01,1510,7.5,Smart Analytics -AI12082,Head of AI,46702,USD,46702,MI,PT,China,M,China,100,"Kubernetes, R, SQL",Bachelor,2,Media,2024-11-09,2024-12-11,850,9.8,Quantum Computing Inc -AI12083,Data Scientist,65493,USD,65493,EN,PT,Ireland,L,Ireland,50,"Data Visualization, Linux, Mathematics, Python, Computer Vision",Associate,0,Finance,2024-09-02,2024-10-04,1196,9.4,DeepTech Ventures -AI12084,Head of AI,84582,JPY,9304020,MI,FL,Japan,M,Japan,100,"Scala, Spark, TensorFlow, AWS",Associate,4,Government,2024-07-14,2024-08-05,922,9.1,Smart Analytics -AI12085,AI Software Engineer,168343,JPY,18517730,SE,FT,Japan,L,Japan,0,"Git, Scala, Statistics, Mathematics",Associate,7,Education,2024-02-01,2024-04-04,1613,5.8,DataVision Ltd -AI12086,Machine Learning Researcher,122314,USD,122314,EX,FT,South Korea,S,Portugal,50,"R, Java, AWS, Deep Learning",PhD,10,Manufacturing,2025-04-18,2025-06-13,1322,7.9,DeepTech Ventures -AI12087,Autonomous Systems Engineer,177998,USD,177998,SE,CT,United States,L,United States,50,"Deep Learning, Mathematics, NLP",PhD,9,Energy,2024-12-30,2025-03-07,1399,5.9,Digital Transformation LLC -AI12088,Data Analyst,53354,USD,53354,EN,PT,South Korea,S,South Korea,100,"TensorFlow, Python, MLOps",Associate,0,Real Estate,2024-05-15,2024-07-05,1721,7.6,Digital Transformation LLC -AI12089,Head of AI,160257,USD,160257,MI,CT,Norway,L,Italy,100,"PyTorch, AWS, Mathematics, Docker",Master,4,Retail,2024-02-05,2024-03-04,2077,6.3,Future Systems -AI12090,Robotics Engineer,47255,USD,47255,EN,CT,South Korea,S,Poland,100,"R, Docker, Statistics, GCP, Git",Bachelor,1,Media,2024-12-07,2025-02-05,1532,7.3,Advanced Robotics -AI12091,AI Research Scientist,244976,SGD,318469,EX,CT,Singapore,M,Singapore,100,"Java, AWS, MLOps, Computer Vision",Associate,15,Gaming,2024-01-12,2024-02-17,730,6.1,TechCorp Inc -AI12092,Principal Data Scientist,18580,USD,18580,EN,FL,India,S,India,50,"Spark, NLP, Statistics, Linux, Python",Master,0,Real Estate,2025-02-24,2025-03-10,1215,9.6,Digital Transformation LLC -AI12093,Robotics Engineer,92541,GBP,69406,EN,FT,United Kingdom,L,Spain,50,"NLP, GCP, MLOps",Bachelor,1,Finance,2024-09-11,2024-10-10,1775,7.6,Predictive Systems -AI12094,AI Software Engineer,136851,USD,136851,SE,FT,United States,S,United States,100,"R, GCP, Scala",Bachelor,5,Finance,2024-07-29,2024-09-06,1209,5.3,Machine Intelligence Group -AI12095,AI Specialist,74577,GBP,55933,EN,FL,United Kingdom,L,Russia,0,"Git, Spark, Computer Vision, Hadoop, AWS",PhD,1,Education,2025-02-16,2025-03-16,1122,8,Machine Intelligence Group -AI12096,Data Engineer,130249,SGD,169324,MI,PT,Singapore,L,Hungary,0,"Mathematics, Statistics, Tableau, Spark",PhD,3,Consulting,2024-12-27,2025-02-11,1095,9.4,Autonomous Tech -AI12097,Machine Learning Researcher,279715,USD,279715,EX,FL,Denmark,S,Singapore,50,"Docker, SQL, Hadoop, AWS",Master,10,Telecommunications,2024-01-12,2024-01-28,2016,9.8,Digital Transformation LLC -AI12098,Data Analyst,25917,USD,25917,MI,CT,India,S,India,0,"SQL, GCP, MLOps",Associate,2,Retail,2024-05-29,2024-06-28,2476,5.5,Cognitive Computing -AI12099,Deep Learning Engineer,192954,EUR,164011,EX,CT,Netherlands,S,Netherlands,50,"AWS, Kubernetes, Scala",Bachelor,10,Retail,2024-06-16,2024-07-23,1690,6.4,DeepTech Ventures -AI12100,Machine Learning Engineer,151696,USD,151696,EX,FT,United States,S,United States,0,"Python, Computer Vision, Git",Master,19,Education,2024-05-28,2024-06-27,1075,5.5,AI Innovations -AI12101,Computer Vision Engineer,181487,USD,181487,EX,CT,United States,M,United States,100,"Python, TensorFlow, Tableau",PhD,15,Manufacturing,2024-09-05,2024-10-20,729,9.3,Neural Networks Co -AI12102,Machine Learning Engineer,290032,CHF,261029,EX,FL,Switzerland,S,Switzerland,100,"AWS, Spark, R, Statistics, Mathematics",Master,18,Gaming,2024-12-07,2025-01-10,1549,5.5,Algorithmic Solutions -AI12103,Principal Data Scientist,88078,USD,88078,MI,PT,Israel,L,Israel,100,"Kubernetes, TensorFlow, SQL, Spark",Bachelor,2,Automotive,2024-03-31,2024-04-24,1515,8.7,Machine Intelligence Group -AI12104,Robotics Engineer,120897,USD,120897,MI,FT,Ireland,L,Ireland,100,"SQL, Java, PyTorch",PhD,3,Gaming,2024-05-11,2024-06-25,830,5.6,Neural Networks Co -AI12105,Head of AI,99552,GBP,74664,MI,CT,United Kingdom,L,United Kingdom,100,"Azure, TensorFlow, GCP, Kubernetes, Computer Vision",PhD,3,Manufacturing,2024-06-16,2024-07-10,1141,7.8,Predictive Systems -AI12106,AI Architect,229166,EUR,194791,EX,FT,Germany,S,Canada,50,"Scala, Linux, PyTorch",Master,15,Healthcare,2025-02-12,2025-03-20,1754,5.9,DataVision Ltd -AI12107,Data Engineer,65688,EUR,55835,EN,CT,Netherlands,S,Netherlands,0,"SQL, PyTorch, Azure, Computer Vision",Bachelor,0,Healthcare,2024-10-29,2024-12-09,586,9.5,Digital Transformation LLC -AI12108,Data Analyst,94258,GBP,70694,MI,FT,United Kingdom,S,Vietnam,100,"Java, Deep Learning, R",Bachelor,4,Manufacturing,2024-05-15,2024-06-18,2486,7.2,Autonomous Tech -AI12109,Machine Learning Researcher,61046,EUR,51889,EN,CT,France,S,South Korea,50,"Spark, Tableau, R, AWS",Associate,0,Real Estate,2024-08-25,2024-10-20,2285,8.2,Future Systems -AI12110,AI Research Scientist,200891,AUD,271203,EX,FT,Australia,S,Estonia,50,"Spark, TensorFlow, PyTorch, Computer Vision, Docker",PhD,12,Gaming,2024-12-01,2025-01-01,2100,7.9,Algorithmic Solutions -AI12111,AI Software Engineer,135505,JPY,14905550,SE,FL,Japan,L,Japan,0,"AWS, MLOps, Tableau, Statistics, Computer Vision",Bachelor,7,Education,2025-03-20,2025-05-29,664,8.6,Predictive Systems -AI12112,Computer Vision Engineer,98227,USD,98227,MI,CT,Norway,S,Switzerland,0,"Python, Git, Tableau, Computer Vision",Associate,3,Retail,2024-07-31,2024-10-10,1973,7.5,TechCorp Inc -AI12113,Principal Data Scientist,156496,USD,156496,EX,PT,South Korea,M,South Korea,0,"AWS, R, Python, Statistics",PhD,15,Retail,2024-05-28,2024-08-01,1858,7.7,Future Systems -AI12114,Machine Learning Researcher,102263,AUD,138055,MI,FL,Australia,M,Australia,0,"AWS, Tableau, Hadoop, TensorFlow, Azure",Associate,4,Retail,2024-06-28,2024-07-23,1553,6.3,Algorithmic Solutions -AI12115,Data Scientist,82355,GBP,61766,MI,FL,United Kingdom,S,United Kingdom,50,"Scala, Kubernetes, MLOps, SQL",Associate,4,Government,2024-11-04,2024-12-31,1044,7.3,Algorithmic Solutions -AI12116,AI Software Engineer,102312,USD,102312,EX,CT,China,M,China,100,"AWS, Scala, PyTorch",Master,14,Government,2025-03-24,2025-05-07,1376,9.9,DataVision Ltd -AI12117,Machine Learning Engineer,213639,USD,213639,EX,FL,Sweden,S,Hungary,50,"R, SQL, Docker, Computer Vision",Associate,14,Transportation,2024-12-04,2025-01-07,2256,7.8,Algorithmic Solutions -AI12118,Autonomous Systems Engineer,79347,USD,79347,EN,FT,Denmark,M,Denmark,0,"Python, Mathematics, Spark",Master,1,Healthcare,2024-11-12,2024-12-03,2385,9.2,Cloud AI Solutions -AI12119,Machine Learning Engineer,378082,USD,378082,EX,PT,Denmark,L,Denmark,100,"Scala, Statistics, R, Linux",PhD,14,Transportation,2024-12-21,2025-01-17,1551,8.5,DataVision Ltd -AI12120,AI Specialist,90690,USD,90690,MI,FL,Israel,M,Netherlands,0,"R, SQL, Python, TensorFlow",Bachelor,3,Telecommunications,2024-01-27,2024-03-19,2135,8.9,Advanced Robotics -AI12121,AI Software Engineer,183050,USD,183050,EX,CT,Israel,L,Philippines,50,"Deep Learning, NLP, PyTorch, GCP",Master,19,Retail,2024-09-11,2024-11-03,562,7.9,Autonomous Tech -AI12122,AI Research Scientist,106292,EUR,90348,MI,FT,France,L,France,0,"GCP, Python, PyTorch, Tableau",Associate,2,Gaming,2025-02-13,2025-03-12,2000,7.8,DataVision Ltd -AI12123,Data Engineer,281331,CHF,253198,EX,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Mathematics",Associate,19,Automotive,2025-04-15,2025-05-08,1116,5.1,Advanced Robotics -AI12124,Deep Learning Engineer,269789,JPY,29676790,EX,PT,Japan,M,Brazil,50,"SQL, Python, Kubernetes, Computer Vision, Data Visualization",PhD,18,Transportation,2025-01-03,2025-02-14,1006,9.3,DataVision Ltd -AI12125,Principal Data Scientist,55691,EUR,47337,EN,PT,Germany,M,Germany,0,"Azure, Tableau, Spark, Git",Bachelor,1,Energy,2024-06-14,2024-07-04,1510,5.8,Predictive Systems -AI12126,AI Research Scientist,162401,EUR,138041,EX,FL,Netherlands,M,Netherlands,50,"Deep Learning, Linux, SQL, MLOps",PhD,19,Education,2024-04-29,2024-06-03,2255,5.9,Cognitive Computing -AI12127,Robotics Engineer,185193,CHF,166674,SE,FT,Switzerland,S,Switzerland,50,"Data Visualization, Spark, SQL, Java, Deep Learning",Associate,8,Government,2024-04-05,2024-05-31,1191,5.6,Quantum Computing Inc -AI12128,AI Product Manager,288184,EUR,244956,EX,FT,Germany,L,Germany,100,"Docker, MLOps, R, Hadoop",Bachelor,13,Manufacturing,2024-11-25,2024-12-20,1153,5.8,Algorithmic Solutions -AI12129,Machine Learning Researcher,124643,CAD,155804,SE,CT,Canada,L,Ghana,0,"MLOps, Scala, Java",PhD,9,Automotive,2025-04-30,2025-05-21,1770,9.9,Neural Networks Co -AI12130,AI Software Engineer,43362,USD,43362,EN,FT,Israel,S,Israel,0,"GCP, PyTorch, Kubernetes, AWS, Docker",Master,0,Consulting,2025-02-13,2025-04-10,597,5,DataVision Ltd -AI12131,ML Ops Engineer,79374,USD,79374,SE,PT,South Korea,S,South Korea,50,"GCP, Mathematics, TensorFlow, Python",Bachelor,5,Telecommunications,2024-12-21,2025-01-14,1133,8.1,Neural Networks Co -AI12132,AI Consultant,316394,CHF,284755,EX,FT,Switzerland,S,Switzerland,50,"Azure, SQL, Git",Bachelor,10,Finance,2024-07-24,2024-10-04,891,5.4,Advanced Robotics -AI12133,Autonomous Systems Engineer,96744,EUR,82232,SE,PT,Germany,S,Germany,50,"AWS, Docker, GCP, Tableau, PyTorch",Master,8,Real Estate,2024-11-05,2024-12-12,1905,9,Cloud AI Solutions -AI12134,Head of AI,95183,SGD,123738,EN,FT,Singapore,L,Singapore,0,"PyTorch, Kubernetes, GCP",PhD,1,Finance,2024-11-17,2025-01-08,1001,8,Algorithmic Solutions -AI12135,Machine Learning Researcher,121586,USD,121586,SE,PT,United States,M,United States,100,"Scala, PyTorch, Mathematics, MLOps, Git",Bachelor,9,Consulting,2024-06-23,2024-07-25,1663,9.6,DeepTech Ventures -AI12136,Machine Learning Researcher,64380,SGD,83694,EN,FL,Singapore,M,Singapore,50,"Spark, Data Visualization, Java, TensorFlow",Bachelor,1,Healthcare,2024-11-11,2024-12-27,579,5.6,Predictive Systems -AI12137,Computer Vision Engineer,142065,GBP,106549,SE,PT,United Kingdom,S,United Kingdom,0,"R, Computer Vision, Data Visualization, NLP",PhD,9,Transportation,2024-09-14,2024-11-07,1555,5.9,Quantum Computing Inc -AI12138,Autonomous Systems Engineer,30742,USD,30742,EN,FT,China,S,China,0,"Azure, TensorFlow, GCP, Deep Learning",Bachelor,0,Media,2025-04-19,2025-05-17,1319,7.5,Smart Analytics -AI12139,Head of AI,207496,CHF,186746,SE,FL,Switzerland,L,Switzerland,50,"Git, Scala, Docker, Tableau",Master,5,Consulting,2024-03-27,2024-04-18,1801,6.2,Advanced Robotics -AI12140,AI Research Scientist,89982,USD,89982,MI,CT,Israel,S,Brazil,0,"Deep Learning, Kubernetes, Scala",Associate,4,Transportation,2025-03-29,2025-06-04,2083,5.7,Machine Intelligence Group -AI12141,Deep Learning Engineer,116355,USD,116355,SE,FT,Ireland,S,Luxembourg,50,"Python, TensorFlow, MLOps, Deep Learning",Bachelor,9,Gaming,2024-07-26,2024-08-23,2384,8.5,Advanced Robotics -AI12142,AI Architect,87703,USD,87703,MI,FT,Israel,L,Israel,0,"Docker, Tableau, R",Master,4,Manufacturing,2025-02-15,2025-03-14,1525,5.7,Cognitive Computing -AI12143,Data Scientist,75219,CHF,67697,EN,FT,Switzerland,M,Switzerland,100,"Git, R, Tableau, NLP",Associate,0,Government,2024-07-03,2024-07-20,1775,9.1,Future Systems -AI12144,Deep Learning Engineer,71478,EUR,60756,EN,FT,France,L,France,0,"Docker, PyTorch, Spark",PhD,0,Education,2024-09-11,2024-11-12,622,7.3,Digital Transformation LLC -AI12145,AI Research Scientist,132922,GBP,99692,SE,FL,United Kingdom,L,United Kingdom,0,"Linux, Spark, MLOps, Mathematics, Python",Bachelor,9,Automotive,2025-03-13,2025-05-04,721,9.8,Machine Intelligence Group -AI12146,Robotics Engineer,155903,CAD,194879,SE,PT,Canada,L,Canada,100,"Scala, MLOps, Data Visualization",Bachelor,5,Finance,2025-01-05,2025-02-28,1869,5.4,DeepTech Ventures -AI12147,AI Research Scientist,176781,USD,176781,EX,FL,South Korea,S,Singapore,0,"PyTorch, Statistics, Java, GCP",Bachelor,16,Manufacturing,2024-04-05,2024-05-08,2499,8.8,Cloud AI Solutions -AI12148,ML Ops Engineer,125692,AUD,169684,SE,FT,Australia,S,Australia,50,"SQL, Python, Git, Deep Learning",Associate,8,Consulting,2024-11-23,2025-01-19,2471,9.8,Cognitive Computing -AI12149,AI Product Manager,118577,USD,118577,EX,PT,South Korea,M,South Korea,50,"SQL, AWS, Java, Azure, R",PhD,10,Media,2024-10-24,2024-11-14,1747,9.7,AI Innovations -AI12150,AI Product Manager,56555,USD,56555,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Java, Data Visualization",Associate,1,Real Estate,2024-12-30,2025-01-13,2499,7.3,DeepTech Ventures -AI12151,Research Scientist,60065,USD,60065,EN,FT,Finland,L,Finland,0,"Mathematics, PyTorch, Spark",PhD,0,Manufacturing,2024-12-26,2025-02-14,859,9.9,Future Systems -AI12152,Research Scientist,139198,USD,139198,SE,CT,Sweden,L,France,0,"Spark, Hadoop, GCP, Java, Mathematics",Associate,6,Gaming,2024-07-26,2024-09-19,879,8.4,Algorithmic Solutions -AI12153,Machine Learning Researcher,143607,USD,143607,SE,FT,Ireland,M,Ireland,0,"Azure, Hadoop, Python, GCP",Associate,6,Retail,2025-03-20,2025-04-04,1532,10,Digital Transformation LLC -AI12154,Data Analyst,176811,USD,176811,EX,CT,South Korea,L,South Korea,50,"Kubernetes, Scala, Git, Java, GCP",Associate,16,Consulting,2024-11-04,2025-01-09,1133,10,Advanced Robotics -AI12155,Principal Data Scientist,166590,EUR,141602,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Docker, Azure, Scala, Python",Bachelor,5,Media,2024-07-20,2024-09-09,2307,7,Quantum Computing Inc -AI12156,Computer Vision Engineer,34463,USD,34463,MI,FL,India,M,India,100,"PyTorch, Python, Kubernetes, AWS",PhD,2,Technology,2024-07-20,2024-08-26,2225,6.4,Neural Networks Co -AI12157,AI Software Engineer,195880,USD,195880,EX,FL,Finland,S,Finland,0,"Hadoop, Python, TensorFlow, GCP, R",PhD,18,Retail,2024-01-17,2024-03-05,1179,5.6,Neural Networks Co -AI12158,Research Scientist,41697,USD,41697,MI,PT,China,M,China,50,"Azure, Python, TensorFlow",PhD,3,Manufacturing,2024-12-11,2025-02-07,1376,5.2,AI Innovations -AI12159,Research Scientist,61900,USD,61900,EN,CT,Norway,S,Norway,50,"TensorFlow, Scala, Deep Learning",Master,1,Healthcare,2024-11-20,2024-12-30,665,6.2,DataVision Ltd -AI12160,AI Consultant,32827,USD,32827,MI,FL,China,S,China,100,"Python, Kubernetes, SQL, Linux, Docker",Associate,2,Manufacturing,2024-11-03,2024-12-09,2369,7,DataVision Ltd -AI12161,Research Scientist,71766,CAD,89708,EN,FL,Canada,L,Canada,50,"Spark, Java, Mathematics, PyTorch, Computer Vision",Bachelor,1,Technology,2024-06-17,2024-07-07,1130,8.3,DeepTech Ventures -AI12162,ML Ops Engineer,221363,EUR,188159,EX,CT,Austria,M,Austria,0,"PyTorch, TensorFlow, Spark, Hadoop, Azure",Associate,16,Telecommunications,2024-04-08,2024-05-14,2389,5.5,Machine Intelligence Group -AI12163,Autonomous Systems Engineer,125926,AUD,170000,MI,FT,Australia,L,Australia,50,"Spark, Python, Mathematics, TensorFlow, Data Visualization",PhD,2,Gaming,2025-03-11,2025-04-16,1021,8.7,Autonomous Tech -AI12164,Deep Learning Engineer,121421,USD,121421,MI,FL,Denmark,M,Denmark,0,"Docker, AWS, Azure, Tableau, Spark",PhD,3,Telecommunications,2024-06-25,2024-07-18,824,9.4,Quantum Computing Inc -AI12165,Machine Learning Engineer,252757,AUD,341222,EX,FL,Australia,L,Australia,50,"Deep Learning, Scala, PyTorch, GCP, Azure",Associate,15,Automotive,2024-08-13,2024-09-04,2321,6.6,Autonomous Tech -AI12166,Data Scientist,132931,USD,132931,SE,PT,United States,S,United States,50,"Azure, Deep Learning, SQL",Associate,7,Finance,2024-09-07,2024-11-12,792,9.2,Autonomous Tech -AI12167,NLP Engineer,76358,GBP,57269,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, SQL, Computer Vision",Bachelor,1,Telecommunications,2024-12-28,2025-02-05,2476,7.7,Advanced Robotics -AI12168,Research Scientist,243166,AUD,328274,EX,CT,Australia,M,Estonia,0,"PyTorch, Mathematics, NLP, Computer Vision, TensorFlow",Bachelor,17,Automotive,2024-08-22,2024-11-01,2356,6.4,Smart Analytics -AI12169,Principal Data Scientist,101437,USD,101437,EN,CT,Norway,L,Israel,100,"SQL, Docker, Scala",Bachelor,0,Automotive,2024-07-28,2024-09-09,2330,9,Machine Intelligence Group -AI12170,Deep Learning Engineer,99518,USD,99518,MI,CT,United States,L,Luxembourg,100,"Python, TensorFlow, Git, Tableau",PhD,3,Retail,2024-06-25,2024-07-30,600,5.5,Advanced Robotics -AI12171,Deep Learning Engineer,240736,USD,240736,EX,PT,South Korea,L,Vietnam,100,"Scala, Kubernetes, Computer Vision",PhD,17,Telecommunications,2024-02-15,2024-04-24,1757,9.6,Future Systems -AI12172,Data Scientist,296026,SGD,384834,EX,FT,Singapore,L,India,100,"AWS, Scala, Data Visualization, MLOps",Master,12,Transportation,2025-02-05,2025-02-26,1392,5.6,Neural Networks Co -AI12173,Data Engineer,229184,JPY,25210240,EX,FT,Japan,L,Japan,0,"Java, SQL, GCP, NLP",Associate,17,Real Estate,2025-04-24,2025-06-01,1733,9.9,Smart Analytics -AI12174,ML Ops Engineer,151494,USD,151494,SE,FL,Ireland,M,Brazil,0,"Git, Python, MLOps, Java",Associate,7,Automotive,2024-12-04,2025-01-06,1744,6.3,Cloud AI Solutions -AI12175,NLP Engineer,237805,USD,237805,EX,CT,Sweden,L,Sweden,100,"PyTorch, Scala, Git, Mathematics",Master,10,Government,2024-08-03,2024-10-13,1883,5.1,Digital Transformation LLC -AI12176,Autonomous Systems Engineer,71970,AUD,97160,EN,FT,Australia,S,Australia,100,"R, Hadoop, NLP, SQL, Java",Master,0,Consulting,2025-03-22,2025-05-05,1066,6.9,Future Systems -AI12177,AI Architect,142468,SGD,185208,SE,CT,Singapore,S,Singapore,100,"PyTorch, Hadoop, AWS, R, Statistics",PhD,9,Automotive,2024-09-18,2024-10-09,2447,7.8,Predictive Systems -AI12178,NLP Engineer,88665,GBP,66499,MI,FT,United Kingdom,L,Kenya,100,"TensorFlow, Computer Vision, Scala, Tableau, Linux",Bachelor,4,Education,2024-04-12,2024-04-28,2448,7.7,Quantum Computing Inc -AI12179,AI Research Scientist,30066,USD,30066,EN,FL,China,L,China,50,"Azure, Python, Kubernetes, Deep Learning",Associate,1,Finance,2024-04-18,2024-05-10,2492,8.4,Predictive Systems -AI12180,AI Product Manager,90082,EUR,76570,MI,FL,France,S,France,0,"Linux, Docker, Statistics",Bachelor,4,Finance,2025-01-19,2025-02-12,1737,5.8,TechCorp Inc -AI12181,Research Scientist,101851,SGD,132406,MI,CT,Singapore,S,Singapore,0,"Kubernetes, SQL, PyTorch, MLOps",Bachelor,2,Automotive,2024-10-19,2024-12-14,1603,5.2,DeepTech Ventures -AI12182,ML Ops Engineer,246833,USD,246833,EX,FL,United States,S,United States,0,"Spark, AWS, MLOps",Associate,11,Government,2024-01-14,2024-01-28,1238,7.5,DataVision Ltd -AI12183,AI Software Engineer,89470,CHF,80523,EN,PT,Switzerland,S,Switzerland,0,"AWS, Python, GCP, Hadoop",PhD,1,Retail,2024-03-07,2024-05-02,2108,9.5,AI Innovations -AI12184,Deep Learning Engineer,71297,CAD,89121,EN,FT,Canada,M,Luxembourg,0,"SQL, Data Visualization, R",Bachelor,1,Finance,2024-06-28,2024-07-17,1898,9.1,Future Systems -AI12185,Data Scientist,86039,GBP,64529,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Scala, NLP, Computer Vision, Deep Learning",Master,2,Education,2024-05-30,2024-07-07,1586,9.9,Future Systems -AI12186,Data Scientist,34424,USD,34424,MI,CT,India,L,India,50,"GCP, Linux, Statistics",PhD,3,Technology,2024-08-22,2024-10-29,521,9.1,Predictive Systems -AI12187,Machine Learning Researcher,29840,USD,29840,MI,FT,India,M,India,0,"Python, Scala, Tableau, GCP",Master,4,Education,2025-03-20,2025-05-26,1867,8.5,Advanced Robotics -AI12188,Machine Learning Researcher,82805,AUD,111787,MI,PT,Australia,M,Ukraine,100,"TensorFlow, AWS, MLOps",Master,4,Government,2024-07-09,2024-08-15,1520,9.1,Neural Networks Co -AI12189,AI Specialist,90863,USD,90863,MI,CT,Ireland,M,Ireland,100,"Scala, R, Data Visualization",Bachelor,3,Telecommunications,2025-02-05,2025-02-19,928,7.1,Cloud AI Solutions -AI12190,AI Software Engineer,75880,USD,75880,EN,FL,Finland,L,Finland,100,"NLP, TensorFlow, AWS, Tableau, Java",PhD,1,Government,2025-01-11,2025-02-01,2354,8.3,DeepTech Ventures -AI12191,AI Specialist,90998,USD,90998,MI,CT,Norway,S,Norway,100,"Linux, Python, Kubernetes, Spark, Hadoop",PhD,2,Real Estate,2024-10-01,2024-10-15,1560,8.3,AI Innovations -AI12192,AI Product Manager,83633,EUR,71088,MI,CT,Netherlands,S,Netherlands,0,"PyTorch, GCP, Mathematics, Linux",Associate,2,Real Estate,2024-05-25,2024-07-09,2074,5.8,Algorithmic Solutions -AI12193,Deep Learning Engineer,64326,USD,64326,EN,FL,Israel,M,Israel,100,"Computer Vision, Linux, GCP",PhD,0,Finance,2024-07-02,2024-08-21,2230,8.7,Smart Analytics -AI12194,Computer Vision Engineer,111239,CHF,100115,MI,CT,Switzerland,S,Switzerland,50,"PyTorch, SQL, Computer Vision, Java",Bachelor,4,Real Estate,2024-07-08,2024-08-11,2220,7.8,Cognitive Computing -AI12195,AI Product Manager,193976,USD,193976,EX,FL,Norway,M,Belgium,100,"Mathematics, Python, SQL, GCP",PhD,17,Healthcare,2024-12-01,2025-02-03,636,5.3,Smart Analytics -AI12196,AI Architect,252737,USD,252737,EX,CT,Sweden,L,Sweden,0,"Java, Scala, MLOps, Python, Computer Vision",Master,11,Media,2024-08-30,2024-10-12,729,6.4,Quantum Computing Inc -AI12197,AI Specialist,83997,EUR,71397,MI,FL,France,M,France,0,"Kubernetes, Spark, PyTorch",Master,3,Real Estate,2025-02-25,2025-03-30,1849,7.4,Autonomous Tech -AI12198,AI Research Scientist,243739,EUR,207178,EX,PT,Germany,M,Germany,0,"Tableau, Mathematics, MLOps, Hadoop, Python",PhD,16,Technology,2024-07-27,2024-09-28,1990,9.4,Smart Analytics -AI12199,AI Consultant,169734,USD,169734,EX,FL,South Korea,M,South Korea,0,"Scala, Mathematics, Docker, Kubernetes",PhD,17,Energy,2024-12-07,2025-02-15,829,6.6,Algorithmic Solutions -AI12200,Machine Learning Researcher,59827,EUR,50853,EN,FL,Netherlands,S,China,0,"Git, Java, PyTorch, MLOps",Master,0,Finance,2024-04-20,2024-07-02,1072,5.9,Cloud AI Solutions -AI12201,Machine Learning Engineer,107719,SGD,140035,MI,PT,Singapore,L,Singapore,100,"AWS, Deep Learning, Hadoop, Linux",Master,4,Media,2024-04-16,2024-06-15,1335,8.5,AI Innovations -AI12202,AI Software Engineer,75575,JPY,8313250,EN,FT,Japan,M,Japan,50,"Computer Vision, Tableau, Deep Learning, MLOps",PhD,0,Media,2024-12-18,2025-02-17,1152,9.3,Autonomous Tech -AI12203,Autonomous Systems Engineer,281411,GBP,211058,EX,PT,United Kingdom,L,Russia,0,"Git, Spark, TensorFlow, Docker",Bachelor,13,Technology,2024-06-06,2024-07-22,1091,8.9,Cognitive Computing -AI12204,Deep Learning Engineer,88523,USD,88523,MI,FT,Ireland,L,Ireland,50,"Java, Python, Mathematics, Azure, Deep Learning",Bachelor,3,Automotive,2025-04-08,2025-06-13,1762,6.7,Digital Transformation LLC -AI12205,Deep Learning Engineer,61599,USD,61599,EN,PT,South Korea,L,South Korea,0,"Java, Spark, Tableau, Mathematics",Master,1,Government,2024-03-21,2024-05-06,794,7.6,Neural Networks Co -AI12206,Robotics Engineer,74511,SGD,96864,EN,CT,Singapore,L,Singapore,50,"NLP, Statistics, Python",Bachelor,1,Telecommunications,2024-09-22,2024-10-29,2068,6.3,DeepTech Ventures -AI12207,AI Research Scientist,23318,USD,23318,MI,FL,India,S,Thailand,50,"Scala, GCP, Python",Master,3,Government,2025-01-04,2025-02-14,1584,6.2,Quantum Computing Inc -AI12208,Computer Vision Engineer,136734,USD,136734,SE,CT,Finland,L,Finland,100,"Java, Scala, GCP, Kubernetes",Master,7,Telecommunications,2024-06-16,2024-07-24,1494,8,Predictive Systems -AI12209,Deep Learning Engineer,21533,USD,21533,EN,FL,India,L,India,100,"TensorFlow, Python, Data Visualization, Azure",Master,0,Transportation,2024-06-20,2024-07-27,759,9.6,Predictive Systems -AI12210,AI Consultant,69344,EUR,58942,EN,PT,France,M,France,50,"Kubernetes, AWS, Deep Learning",PhD,1,Automotive,2024-11-21,2024-12-21,760,6.5,Quantum Computing Inc -AI12211,Data Engineer,77016,USD,77016,EN,CT,Denmark,M,Thailand,50,"R, GCP, Kubernetes",PhD,0,Consulting,2024-12-05,2024-12-21,1323,7.8,Advanced Robotics -AI12212,AI Product Manager,79033,AUD,106695,MI,FT,Australia,M,Australia,50,"NLP, GCP, Spark",PhD,3,Manufacturing,2024-12-07,2025-01-30,1300,7.2,Future Systems -AI12213,AI Research Scientist,98816,CHF,88934,EN,FT,Switzerland,M,Switzerland,100,"Spark, Statistics, TensorFlow, Tableau",Master,1,Telecommunications,2024-06-05,2024-08-08,1929,7.3,Digital Transformation LLC -AI12214,Robotics Engineer,149985,USD,149985,SE,PT,Israel,L,Hungary,0,"TensorFlow, SQL, GCP, NLP, AWS",Master,6,Government,2024-08-14,2024-09-22,658,5.7,DataVision Ltd -AI12215,Data Scientist,129162,EUR,109788,SE,CT,Netherlands,S,Netherlands,0,"Mathematics, Git, R, SQL",Master,8,Retail,2024-03-24,2024-06-04,1376,8.6,Quantum Computing Inc -AI12216,Robotics Engineer,162024,CAD,202530,EX,CT,Canada,M,Canada,0,"Spark, SQL, Mathematics, PyTorch",Bachelor,14,Healthcare,2024-09-24,2024-11-28,2158,7.9,Algorithmic Solutions -AI12217,AI Consultant,72727,USD,72727,MI,PT,South Korea,S,South Korea,50,"MLOps, GCP, Scala, Computer Vision",Associate,4,Healthcare,2024-11-19,2025-01-02,914,5.4,Machine Intelligence Group -AI12218,Machine Learning Researcher,74894,USD,74894,EN,FL,Ireland,L,Ireland,100,"Kubernetes, MLOps, Linux, PyTorch, Git",PhD,0,Transportation,2025-02-13,2025-04-20,619,6.5,Advanced Robotics -AI12219,AI Specialist,106226,CAD,132783,SE,CT,Canada,M,Canada,100,"Scala, PyTorch, Docker",Associate,5,Energy,2024-12-02,2025-01-14,1075,9.4,Future Systems -AI12220,Computer Vision Engineer,103330,USD,103330,SE,FT,South Korea,L,South Korea,0,"NLP, AWS, Python",Associate,7,Finance,2024-01-07,2024-02-22,1951,6.2,Smart Analytics -AI12221,AI Software Engineer,228843,GBP,171632,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, Python, Computer Vision",Bachelor,18,Manufacturing,2024-10-31,2024-12-16,2231,7.7,Neural Networks Co -AI12222,Deep Learning Engineer,129776,USD,129776,MI,FT,Denmark,M,Vietnam,50,"Hadoop, Linux, SQL",Associate,3,Healthcare,2025-01-30,2025-03-07,1368,8.4,Quantum Computing Inc -AI12223,Research Scientist,146735,USD,146735,SE,FL,Norway,S,United States,50,"Computer Vision, TensorFlow, GCP",Associate,6,Automotive,2024-05-05,2024-05-20,623,8,DeepTech Ventures -AI12224,AI Research Scientist,128592,USD,128592,MI,CT,Denmark,S,Poland,50,"Hadoop, Deep Learning, Spark, AWS",Associate,4,Automotive,2024-06-11,2024-06-26,1115,6.1,TechCorp Inc -AI12225,AI Architect,166057,USD,166057,SE,PT,United States,L,United States,50,"R, MLOps, PyTorch, TensorFlow, Azure",PhD,9,Real Estate,2025-02-05,2025-03-11,2164,6.4,TechCorp Inc -AI12226,Principal Data Scientist,183692,CHF,165323,EX,FT,Switzerland,S,Switzerland,0,"R, Statistics, Git, Mathematics, GCP",Associate,10,Energy,2024-10-19,2024-11-15,2045,7,Machine Intelligence Group -AI12227,AI Software Engineer,43783,USD,43783,EN,FT,South Korea,M,South Korea,50,"SQL, Kubernetes, AWS, R",PhD,0,Education,2024-03-23,2024-04-12,2327,6.8,Quantum Computing Inc -AI12228,Data Scientist,131756,SGD,171283,SE,CT,Singapore,S,Singapore,100,"Mathematics, Deep Learning, Python, Java",Associate,7,Media,2024-01-01,2024-01-27,967,5.1,DeepTech Ventures -AI12229,AI Product Manager,93277,EUR,79285,MI,CT,Germany,S,Nigeria,100,"SQL, Azure, Computer Vision, Scala",PhD,4,Automotive,2024-03-16,2024-03-31,764,5.9,Machine Intelligence Group -AI12230,NLP Engineer,75614,SGD,98298,MI,FT,Singapore,S,Singapore,50,"Kubernetes, R, GCP, MLOps, Docker",Master,2,Government,2024-12-02,2025-01-19,2241,9.1,Cognitive Computing -AI12231,AI Consultant,247382,USD,247382,EX,FT,Ireland,M,Ireland,50,"TensorFlow, Docker, Deep Learning, Python",Master,15,Consulting,2024-10-29,2024-12-25,2013,6,Cloud AI Solutions -AI12232,AI Architect,106997,SGD,139096,MI,CT,Singapore,M,Singapore,50,"MLOps, Data Visualization, R",PhD,2,Healthcare,2024-11-27,2025-01-31,2177,8.8,Cognitive Computing -AI12233,Data Scientist,138109,GBP,103582,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Hadoop, Docker",Bachelor,6,Manufacturing,2024-02-24,2024-04-07,1495,6.9,Machine Intelligence Group -AI12234,Computer Vision Engineer,138794,USD,138794,EX,FT,Ireland,M,Ireland,100,"Statistics, Computer Vision, PyTorch, Azure, Deep Learning",Master,16,Media,2024-02-04,2024-04-09,2355,7.7,DataVision Ltd -AI12235,Autonomous Systems Engineer,168757,USD,168757,EX,CT,South Korea,L,Mexico,0,"TensorFlow, Hadoop, Linux, Docker",Master,11,Media,2024-06-03,2024-07-19,2255,9.6,Digital Transformation LLC -AI12236,AI Consultant,124514,USD,124514,MI,FT,Sweden,L,Spain,0,"Linux, R, Spark, Python, GCP",Associate,4,Government,2024-08-28,2024-10-03,587,9.7,Advanced Robotics -AI12237,Head of AI,59609,GBP,44707,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Computer Vision",Master,0,Retail,2024-05-19,2024-06-03,1917,7.4,Autonomous Tech -AI12238,Computer Vision Engineer,96741,JPY,10641510,MI,PT,Japan,S,Japan,0,"Computer Vision, Azure, Git, TensorFlow, Mathematics",Associate,4,Energy,2024-02-11,2024-04-18,2132,6.9,Quantum Computing Inc -AI12239,Data Analyst,263387,EUR,223879,EX,FL,Netherlands,L,Czech Republic,0,"Statistics, PyTorch, Java, MLOps, Deep Learning",PhD,16,Education,2024-08-08,2024-10-12,2083,6.1,TechCorp Inc -AI12240,Computer Vision Engineer,98959,GBP,74219,MI,PT,United Kingdom,S,United Kingdom,50,"Computer Vision, Hadoop, R, Scala",Bachelor,2,Healthcare,2025-02-15,2025-03-20,1818,7.3,Future Systems -AI12241,Data Scientist,120653,USD,120653,MI,FL,United States,L,United States,100,"Mathematics, Python, Tableau, Data Visualization",Associate,3,Government,2025-04-28,2025-05-19,2337,7.3,DeepTech Ventures -AI12242,AI Architect,157279,AUD,212327,EX,PT,Australia,S,India,100,"Scala, Python, Computer Vision",PhD,18,Real Estate,2024-08-03,2024-09-05,2318,7.4,Cloud AI Solutions -AI12243,AI Specialist,252708,EUR,214802,EX,PT,France,L,France,100,"GCP, Azure, Scala, Data Visualization",Master,18,Government,2024-07-16,2024-09-12,1823,5.1,Advanced Robotics -AI12244,Computer Vision Engineer,98348,USD,98348,EN,FT,Denmark,M,Denmark,0,"NLP, MLOps, Git",PhD,1,Retail,2024-11-22,2024-12-13,1969,7,Smart Analytics -AI12245,AI Architect,195438,USD,195438,EX,FT,Denmark,M,Denmark,50,"Scala, Kubernetes, NLP, Statistics, Python",Associate,11,Gaming,2024-11-18,2024-12-13,1555,9.1,TechCorp Inc -AI12246,Deep Learning Engineer,118243,USD,118243,SE,FT,Israel,M,Luxembourg,50,"Git, MLOps, R, Data Visualization",Master,8,Automotive,2024-09-19,2024-10-11,1355,8.2,Digital Transformation LLC -AI12247,Principal Data Scientist,70867,SGD,92127,MI,CT,Singapore,S,Estonia,100,"R, SQL, Deep Learning",Associate,4,Real Estate,2024-11-03,2024-12-09,715,5.6,Advanced Robotics -AI12248,Data Scientist,108015,USD,108015,SE,PT,South Korea,L,Spain,50,"Hadoop, Python, GCP",PhD,7,Manufacturing,2024-02-22,2024-03-07,2082,5.4,AI Innovations -AI12249,Computer Vision Engineer,68609,USD,68609,MI,FT,South Korea,S,South Korea,50,"Kubernetes, Linux, Docker",Master,3,Transportation,2024-02-01,2024-03-29,652,7.1,Smart Analytics -AI12250,Research Scientist,138450,USD,138450,SE,FL,Norway,M,France,100,"Azure, Java, MLOps, Computer Vision",Bachelor,7,Healthcare,2024-06-18,2024-08-17,1731,5.6,Neural Networks Co -AI12251,Autonomous Systems Engineer,129185,USD,129185,SE,PT,Israel,L,Israel,0,"GCP, Python, Git, Java",PhD,8,Telecommunications,2024-05-18,2024-07-11,2162,8.2,Cognitive Computing -AI12252,Data Engineer,62912,EUR,53475,EN,PT,Austria,L,Austria,50,"SQL, Docker, Linux",PhD,0,Transportation,2024-08-06,2024-09-25,926,6.4,Machine Intelligence Group -AI12253,Machine Learning Engineer,185718,USD,185718,EX,PT,Israel,L,Israel,50,"Python, Mathematics, MLOps, TensorFlow, Deep Learning",Bachelor,11,Manufacturing,2024-02-08,2024-04-04,2195,5.2,DataVision Ltd -AI12254,Machine Learning Engineer,159827,USD,159827,EX,FL,Israel,M,Israel,100,"Python, GCP, Linux, Statistics, Hadoop",Master,19,Finance,2024-12-09,2024-12-28,963,5.4,Autonomous Tech -AI12255,Computer Vision Engineer,93928,SGD,122106,MI,FT,Singapore,M,China,0,"Computer Vision, Python, TensorFlow, Docker, Statistics",Master,3,Media,2024-11-11,2024-11-30,870,6.1,Digital Transformation LLC -AI12256,Research Scientist,75790,GBP,56843,EN,FL,United Kingdom,S,Japan,0,"Java, Scala, GCP, Spark",Bachelor,1,Energy,2024-01-24,2024-03-03,1431,6.5,Neural Networks Co -AI12257,AI Consultant,34200,USD,34200,EN,FT,China,L,China,0,"NLP, Mathematics, Tableau, R, MLOps",Associate,0,Media,2024-04-13,2024-06-24,912,8.4,AI Innovations -AI12258,AI Software Engineer,90286,USD,90286,EN,FT,Denmark,M,Denmark,50,"Deep Learning, Spark, Azure, Tableau, AWS",Master,0,Telecommunications,2024-08-27,2024-10-29,1571,5.3,Digital Transformation LLC -AI12259,Robotics Engineer,146547,CAD,183184,EX,FL,Canada,S,Canada,100,"Kubernetes, Spark, Deep Learning, Statistics, PyTorch",PhD,17,Automotive,2025-03-30,2025-06-01,1978,8.4,TechCorp Inc -AI12260,Computer Vision Engineer,31797,USD,31797,MI,FT,India,M,Belgium,50,"Linux, Kubernetes, Statistics, Deep Learning, R",Associate,3,Gaming,2024-07-10,2024-09-18,923,8.9,Predictive Systems -AI12261,Machine Learning Engineer,54017,CAD,67521,EN,FT,Canada,M,Canada,50,"Git, Python, Spark, Scala",Associate,0,Transportation,2024-09-12,2024-10-08,513,9.2,Quantum Computing Inc -AI12262,Head of AI,272906,EUR,231970,EX,FT,Netherlands,L,India,50,"Python, Spark, Java, Data Visualization",Associate,16,Automotive,2025-03-10,2025-04-11,1833,7.6,Smart Analytics -AI12263,Machine Learning Engineer,43901,CAD,54876,EN,FT,Canada,S,Romania,100,"Deep Learning, AWS, Docker",Master,1,Energy,2024-01-11,2024-03-13,1700,6.7,Advanced Robotics -AI12264,Data Engineer,127644,AUD,172319,SE,FT,Australia,L,India,50,"Mathematics, Python, Computer Vision",Master,8,Finance,2024-07-14,2024-08-25,1260,5.1,Cognitive Computing -AI12265,AI Product Manager,128688,USD,128688,MI,PT,Denmark,L,Ireland,0,"R, Azure, Statistics",Master,4,Automotive,2024-06-28,2024-08-30,2202,9.9,Cognitive Computing -AI12266,AI Product Manager,94657,USD,94657,SE,FT,South Korea,S,South Korea,100,"SQL, TensorFlow, Deep Learning, Hadoop",PhD,8,Government,2025-04-09,2025-05-28,1489,8.8,TechCorp Inc -AI12267,AI Architect,109965,USD,109965,EN,PT,Denmark,L,Mexico,50,"Java, PyTorch, Docker, TensorFlow",Master,1,Gaming,2024-03-07,2024-04-29,752,7,Future Systems -AI12268,Head of AI,206612,USD,206612,EX,CT,Denmark,S,Denmark,0,"Java, R, SQL",Associate,17,Finance,2024-11-19,2025-01-18,1979,9.5,Autonomous Tech -AI12269,Data Engineer,181402,USD,181402,EX,FL,Sweden,S,China,100,"Statistics, SQL, Linux, Spark, Computer Vision",Associate,10,Transportation,2024-09-09,2024-11-09,1526,5,DataVision Ltd -AI12270,Machine Learning Engineer,193935,CHF,174542,SE,FT,Switzerland,L,Switzerland,100,"Git, Docker, Python",Associate,8,Finance,2024-12-22,2025-02-01,671,8.6,Advanced Robotics -AI12271,AI Architect,59622,USD,59622,SE,FT,China,L,China,100,"PyTorch, GCP, Scala",Master,8,Retail,2024-08-19,2024-09-10,616,6.9,DeepTech Ventures -AI12272,Data Engineer,82962,EUR,70518,MI,FL,Netherlands,S,Luxembourg,50,"Hadoop, AWS, NLP",Associate,4,Telecommunications,2024-03-05,2024-05-03,2217,6.5,AI Innovations -AI12273,AI Research Scientist,179005,USD,179005,EX,PT,Sweden,S,New Zealand,50,"Python, TensorFlow, Deep Learning, AWS, Statistics",Master,13,Consulting,2024-02-09,2024-03-09,1916,9.8,Cloud AI Solutions -AI12274,NLP Engineer,45061,USD,45061,EN,FL,South Korea,M,South Korea,50,"Java, SQL, GCP, Deep Learning",PhD,1,Gaming,2024-02-07,2024-02-24,2265,7.7,Future Systems -AI12275,Robotics Engineer,183033,USD,183033,EX,PT,Israel,L,Israel,100,"Git, GCP, MLOps, Computer Vision",PhD,18,Healthcare,2024-10-31,2025-01-03,1456,6.2,DataVision Ltd -AI12276,AI Architect,85926,USD,85926,EN,FL,United States,L,United States,50,"Linux, R, Mathematics, SQL",PhD,0,Technology,2024-02-14,2024-03-31,724,7.7,Cognitive Computing -AI12277,AI Specialist,90585,EUR,76997,SE,FL,Austria,S,United Kingdom,0,"Python, Azure, TensorFlow, Statistics",Bachelor,8,Finance,2024-12-16,2025-01-28,694,7.3,Cognitive Computing -AI12278,ML Ops Engineer,175783,CHF,158205,SE,CT,Switzerland,L,Austria,100,"Docker, Tableau, NLP, Linux, AWS",Associate,7,Gaming,2025-02-12,2025-03-25,1058,8.5,Machine Intelligence Group -AI12279,AI Consultant,136939,USD,136939,SE,FT,Denmark,M,Denmark,0,"Java, GCP, Python, R, Computer Vision",Master,5,Education,2024-12-16,2025-02-04,2284,6.8,Autonomous Tech -AI12280,Computer Vision Engineer,91436,USD,91436,MI,FL,Israel,M,Denmark,50,"Kubernetes, Spark, Tableau",Bachelor,3,Telecommunications,2024-12-28,2025-03-06,596,7.2,TechCorp Inc -AI12281,Computer Vision Engineer,149033,CHF,134130,MI,FT,Switzerland,M,Switzerland,0,"Git, TensorFlow, Data Visualization, Computer Vision, Docker",PhD,4,Media,2024-02-01,2024-04-01,1269,9.8,Advanced Robotics -AI12282,Machine Learning Engineer,66306,USD,66306,EN,CT,Denmark,M,Denmark,100,"SQL, TensorFlow, NLP, Linux",Master,0,Consulting,2024-02-25,2024-05-01,939,5.2,DataVision Ltd -AI12283,AI Software Engineer,59399,USD,59399,SE,CT,China,M,China,100,"Python, TensorFlow, Deep Learning, Git",PhD,5,Healthcare,2024-06-27,2024-08-24,2474,6.1,TechCorp Inc -AI12284,Data Analyst,99702,USD,99702,SE,CT,Sweden,S,Sweden,100,"Python, TensorFlow, Data Visualization",Bachelor,7,Transportation,2025-04-01,2025-05-15,874,9.5,TechCorp Inc -AI12285,AI Architect,100196,USD,100196,SE,CT,South Korea,S,South Korea,50,"Docker, Scala, Python",Master,6,Healthcare,2024-04-04,2024-05-03,600,9.7,Machine Intelligence Group -AI12286,AI Architect,247639,CAD,309549,EX,CT,Canada,L,Spain,100,"R, GCP, Python, Mathematics",Master,10,Media,2024-11-25,2024-12-11,1628,9.1,Digital Transformation LLC -AI12287,Autonomous Systems Engineer,98862,USD,98862,MI,FT,Norway,S,Chile,50,"Python, Computer Vision, GCP, Java, MLOps",Master,4,Manufacturing,2024-05-22,2024-07-16,1346,9.2,Cloud AI Solutions -AI12288,AI Software Engineer,100088,EUR,85075,MI,FL,Netherlands,S,Colombia,100,"Java, Azure, GCP, R",Associate,4,Gaming,2025-01-31,2025-03-12,677,9,Digital Transformation LLC -AI12289,ML Ops Engineer,67854,USD,67854,MI,FL,Israel,S,Israel,50,"Data Visualization, Computer Vision, PyTorch, Spark, GCP",Bachelor,2,Finance,2024-03-28,2024-06-07,1834,7.5,AI Innovations -AI12290,Research Scientist,133071,USD,133071,SE,CT,Finland,M,Finland,0,"Python, Linux, MLOps, Statistics",PhD,8,Healthcare,2024-03-17,2024-05-18,859,8.6,AI Innovations -AI12291,AI Research Scientist,94334,SGD,122634,MI,FL,Singapore,L,Singapore,0,"NLP, Docker, Mathematics, Hadoop",Bachelor,3,Healthcare,2024-12-19,2025-01-24,871,6,Digital Transformation LLC -AI12292,AI Research Scientist,79114,USD,79114,EX,PT,China,L,China,50,"NLP, SQL, Python, Kubernetes",Bachelor,14,Real Estate,2024-08-07,2024-09-27,1681,9.1,Machine Intelligence Group -AI12293,Autonomous Systems Engineer,140641,USD,140641,SE,FL,Sweden,M,Sweden,50,"Python, Kubernetes, GCP, Statistics, Tableau",Master,7,Telecommunications,2024-05-01,2024-05-21,2152,9.2,DeepTech Ventures -AI12294,Computer Vision Engineer,108378,CHF,97540,MI,FT,Switzerland,S,Switzerland,0,"R, Azure, MLOps, Spark, Python",Master,2,Gaming,2024-05-13,2024-06-08,2394,8.6,Autonomous Tech -AI12295,Deep Learning Engineer,66720,USD,66720,EN,FL,Denmark,M,Thailand,0,"Python, TensorFlow, MLOps",Bachelor,0,Technology,2024-04-28,2024-06-22,2040,6.9,Algorithmic Solutions -AI12296,AI Architect,103843,EUR,88267,MI,PT,Germany,L,Germany,100,"Linux, R, Azure, Python",PhD,3,Healthcare,2025-04-03,2025-05-26,789,8.4,Predictive Systems -AI12297,Principal Data Scientist,180949,USD,180949,SE,FL,Norway,M,Norway,0,"SQL, Java, Spark",Associate,7,Real Estate,2024-04-29,2024-06-17,740,8.6,TechCorp Inc -AI12298,Robotics Engineer,320986,USD,320986,EX,CT,United States,L,United States,100,"NLP, Azure, Scala",Bachelor,11,Media,2025-02-28,2025-03-15,1339,8.7,Neural Networks Co -AI12299,AI Product Manager,164065,SGD,213285,SE,PT,Singapore,L,Singapore,100,"Statistics, GCP, Linux, Hadoop",Bachelor,9,Technology,2024-09-19,2024-11-02,1815,8.8,TechCorp Inc -AI12300,Data Analyst,84134,USD,84134,MI,FT,Sweden,S,Sweden,0,"Python, Java, Tableau",PhD,3,Healthcare,2024-01-29,2024-02-19,2364,8.2,Algorithmic Solutions -AI12301,AI Product Manager,59000,USD,59000,EN,FT,Ireland,L,Ireland,0,"Spark, Mathematics, R",Master,0,Energy,2024-11-17,2025-01-16,975,6.3,AI Innovations -AI12302,Data Analyst,184365,USD,184365,EX,FL,Sweden,M,Sweden,50,"SQL, Python, Linux, Docker, Java",Bachelor,17,Automotive,2024-03-21,2024-04-05,2378,5.9,Cognitive Computing -AI12303,AI Architect,74246,CAD,92808,MI,PT,Canada,S,Thailand,100,"PyTorch, SQL, Docker, Computer Vision, R",Master,2,Automotive,2024-08-11,2024-10-22,819,5.2,Cloud AI Solutions -AI12304,Machine Learning Researcher,116928,USD,116928,SE,PT,Ireland,S,Ireland,0,"Docker, MLOps, Scala, Python, AWS",PhD,7,Finance,2024-03-31,2024-04-22,1068,5.2,AI Innovations -AI12305,Principal Data Scientist,64457,USD,64457,SE,FT,China,L,China,50,"Statistics, Scala, Kubernetes",PhD,7,Finance,2024-03-27,2024-05-17,915,9.4,Autonomous Tech -AI12306,AI Architect,34017,USD,34017,EN,CT,China,S,China,50,"Git, Docker, Azure, Tableau, Python",Associate,1,Government,2025-03-01,2025-04-15,1811,8.1,Cognitive Computing -AI12307,Principal Data Scientist,86245,USD,86245,EN,FL,Ireland,L,Ireland,0,"Deep Learning, R, SQL, PyTorch",Master,1,Technology,2024-05-14,2024-06-24,1477,6.9,Predictive Systems -AI12308,Data Analyst,304034,USD,304034,EX,CT,Denmark,M,Denmark,50,"MLOps, Linux, Hadoop, PyTorch",Master,11,Retail,2024-01-06,2024-01-23,683,9,Machine Intelligence Group -AI12309,Machine Learning Researcher,207016,USD,207016,EX,FT,Finland,S,Finland,100,"Hadoop, R, PyTorch, Java, Docker",Associate,11,Media,2024-12-11,2025-01-06,593,5.3,AI Innovations -AI12310,AI Research Scientist,192387,GBP,144290,EX,FL,United Kingdom,M,Singapore,50,"Java, Python, R",PhD,17,Consulting,2024-09-18,2024-11-22,2353,8.6,Future Systems -AI12311,Data Analyst,23733,USD,23733,MI,FT,India,S,Switzerland,100,"Git, Python, MLOps, Tableau",Master,3,Gaming,2024-08-25,2024-09-15,628,8.6,Advanced Robotics -AI12312,AI Architect,154274,USD,154274,SE,PT,Denmark,L,United States,0,"Deep Learning, Mathematics, Scala, AWS",PhD,9,Retail,2024-02-13,2024-03-27,1673,6,DeepTech Ventures -AI12313,NLP Engineer,43529,USD,43529,MI,CT,China,S,Colombia,50,"Scala, Kubernetes, R, Computer Vision",Master,4,Education,2025-01-04,2025-02-27,855,8.4,Future Systems -AI12314,AI Product Manager,214849,EUR,182622,EX,FL,Austria,M,Austria,50,"Git, Hadoop, Mathematics, PyTorch, Statistics",Bachelor,11,Government,2024-10-25,2024-11-09,2133,8.4,Algorithmic Solutions -AI12315,AI Research Scientist,49530,USD,49530,MI,PT,China,M,China,50,"Kubernetes, GCP, Python",PhD,3,Transportation,2024-12-16,2025-02-12,1247,5.3,Algorithmic Solutions -AI12316,AI Product Manager,90866,USD,90866,EN,FL,Denmark,S,Denmark,0,"Tableau, TensorFlow, Linux, Java",PhD,1,Education,2024-09-04,2024-11-03,2019,9.6,Neural Networks Co -AI12317,Principal Data Scientist,38519,USD,38519,EN,CT,South Korea,S,South Korea,0,"Tableau, AWS, SQL, Computer Vision",PhD,1,Healthcare,2024-07-04,2024-09-02,1845,5.3,DeepTech Ventures -AI12318,Principal Data Scientist,190560,SGD,247728,EX,PT,Singapore,L,Singapore,50,"Kubernetes, Spark, TensorFlow, Data Visualization, Mathematics",PhD,14,Automotive,2024-01-07,2024-03-06,1253,8.5,Future Systems -AI12319,Data Scientist,111397,USD,111397,SE,FL,Sweden,M,Sweden,0,"NLP, Java, Git, SQL",Bachelor,9,Healthcare,2024-04-21,2024-05-27,2032,9.6,DeepTech Ventures -AI12320,Head of AI,100635,USD,100635,MI,CT,Finland,M,Finland,0,"Linux, Java, SQL, Mathematics",PhD,2,Automotive,2025-04-28,2025-05-20,2219,9,Quantum Computing Inc -AI12321,Robotics Engineer,108577,USD,108577,SE,FT,Finland,M,Finland,100,"Statistics, GCP, Docker, Git, Computer Vision",Associate,7,Healthcare,2024-07-23,2024-09-11,641,5,TechCorp Inc -AI12322,AI Product Manager,34193,USD,34193,MI,PT,India,L,India,0,"Scala, GCP, Linux, SQL, Hadoop",Bachelor,3,Healthcare,2024-06-08,2024-07-20,679,6.1,Quantum Computing Inc -AI12323,AI Software Engineer,110241,EUR,93705,SE,PT,Austria,M,Indonesia,50,"GCP, Computer Vision, TensorFlow, Tableau",Bachelor,6,Real Estate,2024-06-06,2024-07-21,1072,8.8,DeepTech Ventures -AI12324,Data Scientist,184497,USD,184497,EX,PT,Denmark,S,Denmark,50,"Tableau, Azure, Java, Kubernetes, MLOps",Master,16,Real Estate,2024-07-24,2024-09-07,1516,5.3,DeepTech Ventures -AI12325,AI Architect,84774,USD,84774,EN,FL,Finland,L,Finland,50,"Hadoop, PyTorch, Git, Azure, TensorFlow",Bachelor,0,Manufacturing,2024-09-12,2024-11-17,1470,6.4,Cloud AI Solutions -AI12326,Robotics Engineer,235792,USD,235792,EX,CT,United States,L,Philippines,0,"MLOps, Java, Docker",Bachelor,14,Finance,2024-10-20,2024-11-03,1360,6,Advanced Robotics -AI12327,Autonomous Systems Engineer,54131,USD,54131,EX,FL,India,M,India,0,"Computer Vision, GCP, Scala, Git",Master,15,Government,2024-07-09,2024-07-25,1390,7,Cognitive Computing -AI12328,Research Scientist,154810,CAD,193513,EX,FT,Canada,L,Canada,100,"Computer Vision, Kubernetes, NLP, R, Scala",Bachelor,15,Media,2024-09-03,2024-10-30,1652,6,DataVision Ltd -AI12329,AI Software Engineer,86911,EUR,73874,EN,PT,Netherlands,L,Netherlands,0,"Python, Spark, GCP, AWS, Azure",PhD,0,Telecommunications,2024-03-02,2024-05-11,2154,5.1,Digital Transformation LLC -AI12330,Machine Learning Engineer,83432,JPY,9177520,MI,CT,Japan,S,Austria,0,"Kubernetes, Git, MLOps, GCP",PhD,3,Media,2024-11-03,2024-12-08,1132,8.1,AI Innovations -AI12331,Data Analyst,104994,USD,104994,EX,CT,China,M,China,100,"Deep Learning, PyTorch, Data Visualization, TensorFlow, MLOps",PhD,11,Healthcare,2025-02-05,2025-03-22,1601,9.4,Cloud AI Solutions -AI12332,Principal Data Scientist,114869,EUR,97639,SE,PT,France,L,France,50,"Scala, Git, PyTorch",PhD,6,Consulting,2024-06-12,2024-07-28,1537,6.3,Predictive Systems -AI12333,AI Consultant,108366,USD,108366,SE,FT,South Korea,M,South Korea,100,"Azure, AWS, Data Visualization, Git, Computer Vision",Associate,7,Transportation,2024-04-07,2024-06-17,1379,8.2,Future Systems -AI12334,Machine Learning Engineer,112203,USD,112203,MI,FL,Ireland,L,Ireland,50,"SQL, R, Python, AWS",PhD,2,Media,2024-12-04,2025-01-07,1218,8.6,Smart Analytics -AI12335,Data Analyst,152809,EUR,129888,EX,FL,France,S,France,100,"Spark, Python, Tableau, Statistics",Master,19,Retail,2024-05-07,2024-06-07,1099,6.6,Autonomous Tech -AI12336,AI Consultant,55945,USD,55945,MI,CT,China,L,Finland,0,"Azure, Scala, Python, Statistics, Mathematics",Bachelor,4,Gaming,2024-01-01,2024-01-23,2346,6.7,Machine Intelligence Group -AI12337,Research Scientist,139128,USD,139128,SE,PT,Finland,L,Finland,100,"Hadoop, Scala, Computer Vision, TensorFlow, Docker",PhD,8,Media,2024-09-19,2024-10-07,761,6.9,Quantum Computing Inc -AI12338,NLP Engineer,74433,USD,74433,MI,PT,Ireland,S,Ireland,50,"R, GCP, Hadoop",Master,2,Real Estate,2024-05-15,2024-07-04,888,6.7,Predictive Systems -AI12339,Deep Learning Engineer,62585,USD,62585,EN,PT,Finland,L,Russia,100,"GCP, SQL, NLP, Statistics",PhD,1,Real Estate,2024-03-14,2024-04-09,1943,8.9,Cognitive Computing -AI12340,Deep Learning Engineer,64130,JPY,7054300,EN,PT,Japan,S,Japan,50,"Hadoop, Tableau, AWS, Java, Data Visualization",PhD,1,Telecommunications,2025-01-16,2025-01-31,2403,8.8,DataVision Ltd -AI12341,Head of AI,24000,USD,24000,EN,FL,India,M,India,50,"Spark, Hadoop, Statistics, Python",PhD,1,Retail,2024-06-20,2024-08-19,1168,9.5,Advanced Robotics -AI12342,ML Ops Engineer,63740,EUR,54179,EN,FL,France,L,Belgium,100,"Computer Vision, MLOps, Deep Learning, Python",Associate,0,Telecommunications,2024-12-15,2025-01-26,2452,5,Cognitive Computing -AI12343,AI Architect,75688,EUR,64335,EN,FT,Netherlands,M,Netherlands,100,"TensorFlow, Spark, Tableau, Data Visualization, Scala",PhD,0,Retail,2024-12-01,2025-02-10,1406,6.3,Smart Analytics -AI12344,Autonomous Systems Engineer,91038,USD,91038,EN,CT,Sweden,L,Sweden,0,"Python, Java, AWS, Mathematics",Associate,1,Consulting,2024-02-05,2024-03-18,908,5.5,Predictive Systems -AI12345,Autonomous Systems Engineer,171871,USD,171871,EX,FT,Israel,M,Malaysia,50,"PyTorch, R, Mathematics, MLOps",Associate,10,Real Estate,2024-06-03,2024-07-14,2018,8.2,Predictive Systems -AI12346,ML Ops Engineer,92855,USD,92855,EN,FL,Norway,S,Ukraine,0,"Python, Data Visualization, TensorFlow, Spark, Hadoop",Associate,1,Education,2024-08-01,2024-09-11,1286,9.5,Future Systems -AI12347,AI Specialist,138709,USD,138709,MI,PT,Norway,M,Norway,100,"Scala, MLOps, TensorFlow, Hadoop",Master,2,Government,2025-04-27,2025-06-27,1095,7.7,Predictive Systems -AI12348,AI Product Manager,89902,USD,89902,EX,CT,India,L,India,50,"Java, Statistics, Tableau, NLP, PyTorch",Bachelor,12,Telecommunications,2024-03-08,2024-04-04,791,9.8,TechCorp Inc -AI12349,Machine Learning Engineer,172633,USD,172633,SE,CT,United States,M,Poland,50,"Python, R, Git, GCP, Deep Learning",Associate,8,Retail,2024-10-08,2024-12-08,645,6.9,TechCorp Inc -AI12350,Robotics Engineer,113910,USD,113910,SE,FT,Israel,M,Israel,0,"Azure, Scala, Data Visualization, Java, Spark",Bachelor,5,Retail,2024-08-20,2024-10-17,1576,5.7,Neural Networks Co -AI12351,Robotics Engineer,145181,USD,145181,SE,FT,United States,S,United Kingdom,50,"Spark, Tableau, MLOps, R, Computer Vision",Associate,8,Gaming,2024-06-23,2024-07-19,1128,5.5,Smart Analytics -AI12352,Data Scientist,126932,CAD,158665,SE,FL,Canada,S,Canada,0,"Computer Vision, Scala, Azure, SQL, Hadoop",PhD,7,Education,2024-11-02,2025-01-14,1822,6.6,Algorithmic Solutions -AI12353,Data Engineer,237969,EUR,202274,EX,FT,Austria,L,Austria,100,"Computer Vision, Azure, Hadoop, Git",Bachelor,13,Manufacturing,2024-03-22,2024-04-19,1312,9.3,Cloud AI Solutions -AI12354,ML Ops Engineer,70164,USD,70164,EX,CT,China,S,China,50,"Kubernetes, Scala, GCP",PhD,12,Energy,2024-02-05,2024-02-25,1714,6.4,Algorithmic Solutions -AI12355,Principal Data Scientist,91580,USD,91580,MI,PT,Sweden,L,Sweden,50,"Java, TensorFlow, NLP, R, Linux",Associate,2,Retail,2025-04-17,2025-05-30,1576,8.7,Algorithmic Solutions -AI12356,Data Scientist,210798,SGD,274037,EX,CT,Singapore,L,Czech Republic,50,"Azure, Python, TensorFlow",Bachelor,16,Automotive,2025-04-27,2025-06-03,1488,5.4,Advanced Robotics -AI12357,Data Scientist,172275,SGD,223958,EX,FL,Singapore,S,Norway,100,"PyTorch, MLOps, Scala, Mathematics, Computer Vision",Associate,11,Telecommunications,2024-01-22,2024-03-26,1642,5.1,DeepTech Ventures -AI12358,Data Scientist,181539,GBP,136154,SE,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, AWS",Bachelor,5,Gaming,2024-03-29,2024-04-30,849,9.6,AI Innovations -AI12359,Principal Data Scientist,83912,JPY,9230320,EN,FT,Japan,L,Japan,100,"Docker, Data Visualization, Computer Vision",Master,0,Automotive,2024-09-05,2024-10-07,1372,5.8,Predictive Systems -AI12360,AI Product Manager,126540,USD,126540,MI,PT,Sweden,L,Sweden,0,"Deep Learning, Kubernetes, Python, Git",Bachelor,3,Government,2024-11-17,2024-12-20,747,8.2,Future Systems -AI12361,Machine Learning Researcher,136341,USD,136341,MI,FL,Denmark,L,South Africa,100,"SQL, NLP, MLOps",Master,2,Finance,2024-08-19,2024-10-08,2113,7.4,Machine Intelligence Group -AI12362,Principal Data Scientist,134759,EUR,114545,SE,FT,Germany,S,Germany,50,"NLP, Spark, Azure, Python",Bachelor,6,Energy,2024-08-24,2024-10-23,901,5.4,Digital Transformation LLC -AI12363,AI Research Scientist,71946,EUR,61154,MI,FT,Netherlands,S,Turkey,100,"Spark, Hadoop, TensorFlow, MLOps",Master,3,Healthcare,2024-08-14,2024-10-03,1113,7.5,Quantum Computing Inc -AI12364,NLP Engineer,93601,EUR,79561,MI,PT,France,L,France,50,"Python, GCP, Kubernetes, TensorFlow, Git",Master,2,Telecommunications,2025-01-18,2025-02-19,986,5.6,Predictive Systems -AI12365,Autonomous Systems Engineer,96130,CAD,120163,SE,FL,Canada,M,Canada,50,"Scala, AWS, Tableau, TensorFlow, Spark",Bachelor,7,Transportation,2024-08-16,2024-09-13,547,5.1,Neural Networks Co -AI12366,AI Consultant,62895,CAD,78619,EN,FT,Canada,L,Canada,0,"Hadoop, SQL, TensorFlow, Python",Associate,0,Telecommunications,2025-04-07,2025-05-17,903,7.6,Predictive Systems -AI12367,ML Ops Engineer,71053,USD,71053,EN,FT,Finland,M,Finland,50,"Scala, Java, GCP, Spark",Bachelor,1,Finance,2024-04-25,2024-05-17,626,5.2,Algorithmic Solutions -AI12368,Data Scientist,235335,USD,235335,EX,CT,Ireland,M,Ireland,100,"Scala, R, NLP",PhD,10,Finance,2024-12-12,2025-01-02,826,7.7,Neural Networks Co -AI12369,Data Analyst,189502,EUR,161077,EX,CT,Austria,S,Australia,50,"Hadoop, PyTorch, SQL, GCP",Bachelor,15,Finance,2025-02-24,2025-04-25,2412,8.9,Algorithmic Solutions -AI12370,Deep Learning Engineer,60818,USD,60818,SE,FT,China,M,China,50,"Scala, Data Visualization, SQL, TensorFlow",PhD,7,Education,2024-11-13,2024-12-05,1109,6.7,Quantum Computing Inc -AI12371,Data Analyst,139977,EUR,118980,SE,CT,Netherlands,L,Norway,50,"Java, GCP, Azure, Tableau, AWS",PhD,5,Energy,2024-02-25,2024-03-24,1555,6,DeepTech Ventures -AI12372,Autonomous Systems Engineer,305019,GBP,228764,EX,FT,United Kingdom,L,United Kingdom,0,"Kubernetes, Spark, Python, Java",PhD,19,Gaming,2024-08-06,2024-08-24,907,6.5,Autonomous Tech -AI12373,AI Architect,74292,EUR,63148,MI,FT,Austria,M,Philippines,0,"Python, Mathematics, PyTorch, SQL, Deep Learning",Associate,3,Finance,2025-02-24,2025-04-25,2408,8.3,Cloud AI Solutions -AI12374,ML Ops Engineer,65497,USD,65497,EN,FL,Finland,L,Finland,0,"Linux, Deep Learning, Python, Mathematics, Git",PhD,1,Media,2024-11-18,2025-01-05,1132,9.1,Advanced Robotics -AI12375,Principal Data Scientist,17450,USD,17450,EN,FT,India,S,India,50,"MLOps, Azure, Git",Bachelor,0,Real Estate,2024-12-03,2025-02-13,517,6.4,Neural Networks Co -AI12376,Machine Learning Engineer,56393,CAD,70491,EN,FL,Canada,S,Canada,100,"R, Tableau, Docker",Bachelor,0,Real Estate,2024-08-28,2024-10-25,2498,6.7,Algorithmic Solutions -AI12377,Machine Learning Researcher,28903,USD,28903,EN,FT,India,L,India,0,"Python, Deep Learning, Computer Vision",Associate,0,Finance,2025-03-14,2025-05-09,2425,5.8,Cognitive Computing -AI12378,Machine Learning Researcher,204225,JPY,22464750,EX,FL,Japan,M,Japan,100,"NLP, SQL, PyTorch",Bachelor,14,Manufacturing,2025-02-25,2025-03-16,735,9.2,Neural Networks Co -AI12379,Head of AI,182487,EUR,155114,EX,CT,Austria,M,Italy,100,"Python, PyTorch, Linux, Java, GCP",Associate,13,Consulting,2024-03-12,2024-04-02,891,6.2,AI Innovations -AI12380,Robotics Engineer,122104,USD,122104,SE,PT,United States,M,South Africa,50,"R, Data Visualization, Linux",PhD,8,Transportation,2024-05-09,2024-05-30,933,5.6,Neural Networks Co -AI12381,Data Engineer,107231,USD,107231,SE,CT,Sweden,S,Sweden,100,"Git, Kubernetes, PyTorch",Bachelor,9,Telecommunications,2024-06-15,2024-08-14,643,9.2,Quantum Computing Inc -AI12382,Deep Learning Engineer,37458,USD,37458,MI,PT,India,M,Czech Republic,50,"Tableau, Hadoop, Java, Azure",Bachelor,4,Consulting,2024-12-02,2024-12-22,1953,5.2,AI Innovations -AI12383,AI Architect,145761,USD,145761,EX,CT,Israel,S,Israel,100,"Java, Statistics, Python, Tableau",Master,13,Media,2024-06-05,2024-07-08,2475,9.1,Predictive Systems -AI12384,Data Engineer,200170,CHF,180153,EX,FL,Switzerland,S,Switzerland,0,"Git, PyTorch, Tableau, Data Visualization, Docker",Master,13,Manufacturing,2025-04-24,2025-06-27,780,5.6,Future Systems -AI12385,ML Ops Engineer,82455,CAD,103069,MI,PT,Canada,S,Canada,50,"Deep Learning, Git, MLOps",Bachelor,4,Retail,2024-01-29,2024-04-09,1588,6,AI Innovations -AI12386,Principal Data Scientist,77760,AUD,104976,EN,PT,Australia,M,Australia,50,"Hadoop, Mathematics, TensorFlow, R",PhD,1,Government,2024-05-01,2024-06-01,1392,8.5,Algorithmic Solutions -AI12387,AI Architect,142182,USD,142182,SE,FT,Finland,M,Finland,100,"Statistics, Kubernetes, Python, Computer Vision, TensorFlow",Associate,5,Government,2024-04-24,2024-05-10,853,9.9,Cloud AI Solutions -AI12388,Robotics Engineer,132350,USD,132350,SE,CT,Ireland,L,Ireland,100,"Data Visualization, Scala, Python, Azure",Associate,9,Real Estate,2025-01-28,2025-02-21,2147,8.2,Advanced Robotics -AI12389,Data Engineer,141077,USD,141077,SE,FL,South Korea,L,South Korea,100,"Docker, Linux, Spark, Deep Learning",Master,7,Government,2025-01-14,2025-02-13,1331,7.2,DeepTech Ventures -AI12390,Research Scientist,237360,CHF,213624,EX,FT,Switzerland,M,Switzerland,100,"MLOps, Statistics, Hadoop",Bachelor,13,Real Estate,2024-12-24,2025-01-21,1615,8.4,Future Systems -AI12391,Data Engineer,138254,JPY,15207940,EX,CT,Japan,S,Japan,50,"Spark, Kubernetes, Data Visualization, SQL",PhD,15,Healthcare,2024-11-01,2025-01-07,1803,9.5,TechCorp Inc -AI12392,AI Consultant,181342,EUR,154141,EX,FL,Netherlands,S,Netherlands,50,"Mathematics, PyTorch, Data Visualization, Scala, Spark",PhD,16,Technology,2025-03-11,2025-05-20,2346,6.8,Autonomous Tech -AI12393,Deep Learning Engineer,154049,JPY,16945390,SE,PT,Japan,M,Japan,100,"Git, Hadoop, Tableau",PhD,8,Healthcare,2024-04-27,2024-05-25,830,6.3,Advanced Robotics -AI12394,Machine Learning Researcher,57960,EUR,49266,EN,FT,Netherlands,S,Netherlands,0,"Python, Azure, Scala, Linux",Master,1,Education,2024-06-01,2024-07-07,1746,5.7,Machine Intelligence Group -AI12395,Principal Data Scientist,281214,USD,281214,EX,CT,Sweden,L,Russia,50,"Data Visualization, Tableau, Python",Bachelor,11,Manufacturing,2024-12-13,2025-01-05,775,8,Autonomous Tech -AI12396,ML Ops Engineer,78328,EUR,66579,EN,CT,Austria,L,Italy,100,"Linux, Scala, Azure, Statistics, Kubernetes",Associate,0,Transportation,2024-03-20,2024-04-12,662,6,Cloud AI Solutions -AI12397,Deep Learning Engineer,253374,CAD,316718,EX,FT,Canada,L,Canada,50,"SQL, Spark, Hadoop",Bachelor,16,Energy,2024-09-16,2024-10-24,1534,8.8,Algorithmic Solutions -AI12398,Autonomous Systems Engineer,168477,USD,168477,SE,CT,Norway,M,Norway,0,"Spark, Linux, PyTorch, SQL",Master,8,Gaming,2024-07-30,2024-08-24,1899,9.6,Autonomous Tech -AI12399,Machine Learning Engineer,87035,USD,87035,MI,FT,United States,S,United States,0,"Data Visualization, Computer Vision, Java, Spark, Statistics",PhD,3,Healthcare,2025-04-22,2025-06-14,2493,8.2,Future Systems -AI12400,AI Specialist,152751,SGD,198576,EX,FL,Singapore,S,Australia,50,"Azure, Scala, Python, TensorFlow, Spark",Associate,16,Energy,2024-02-06,2024-02-21,1240,8,DeepTech Ventures -AI12401,Data Engineer,92050,USD,92050,MI,FT,Sweden,S,Sweden,0,"Docker, MLOps, Python, R, Statistics",Bachelor,4,Automotive,2025-01-28,2025-02-16,1432,6.2,Autonomous Tech -AI12402,Data Scientist,55016,EUR,46764,EN,FT,France,M,Indonesia,0,"Statistics, Python, PyTorch",Associate,1,Retail,2024-06-07,2024-06-21,1512,9.1,Autonomous Tech -AI12403,Computer Vision Engineer,135145,GBP,101359,SE,PT,United Kingdom,M,United Kingdom,100,"AWS, Linux, TensorFlow",Associate,9,Consulting,2024-05-16,2024-06-04,711,10,DeepTech Ventures -AI12404,Head of AI,118429,GBP,88822,SE,CT,United Kingdom,S,Egypt,100,"Spark, Mathematics, Linux, Deep Learning, TensorFlow",Master,7,Consulting,2025-01-19,2025-03-13,995,8.6,Autonomous Tech -AI12405,NLP Engineer,57898,GBP,43424,EN,FL,United Kingdom,M,United Kingdom,50,"Java, Spark, Tableau, MLOps",Master,0,Energy,2024-02-16,2024-03-25,717,7.3,Quantum Computing Inc -AI12406,AI Architect,51180,EUR,43503,EN,CT,Austria,S,Italy,0,"Python, NLP, Data Visualization",Associate,0,Media,2024-11-22,2024-12-06,698,5.5,Quantum Computing Inc -AI12407,Data Scientist,103458,USD,103458,EX,PT,India,L,India,0,"AWS, Docker, Spark, Java, Tableau",Master,19,Media,2024-06-16,2024-08-12,2212,5.5,Future Systems -AI12408,Data Scientist,102748,USD,102748,EX,CT,China,L,China,0,"AWS, Azure, PyTorch, Scala",Bachelor,10,Finance,2025-02-08,2025-04-08,1986,8.1,Smart Analytics -AI12409,Data Analyst,151467,USD,151467,SE,PT,Ireland,M,Ireland,0,"Statistics, TensorFlow, NLP, Mathematics, Java",Bachelor,8,Real Estate,2024-03-12,2024-04-02,1772,9.7,Cognitive Computing -AI12410,Data Scientist,74836,USD,74836,MI,PT,South Korea,M,Singapore,100,"Statistics, NLP, GCP",Associate,2,Telecommunications,2024-08-19,2024-09-23,571,8.7,Neural Networks Co -AI12411,Machine Learning Engineer,169620,EUR,144177,EX,CT,Netherlands,S,Hungary,100,"Java, Git, Hadoop, Docker",PhD,14,Education,2024-10-07,2024-12-17,2161,6,Cognitive Computing -AI12412,AI Software Engineer,113721,CHF,102349,EN,CT,Switzerland,L,Russia,100,"Java, Python, Statistics, Azure",PhD,1,Automotive,2025-03-08,2025-04-10,2083,8.3,Cognitive Computing -AI12413,Head of AI,127743,CHF,114969,MI,FT,Switzerland,S,Austria,0,"SQL, Mathematics, NLP, Spark, Python",PhD,4,Consulting,2024-11-21,2024-12-07,527,8.6,Quantum Computing Inc -AI12414,Principal Data Scientist,305463,USD,305463,EX,FL,Norway,M,Belgium,50,"Scala, Linux, Computer Vision, Tableau, Java",PhD,13,Media,2024-11-13,2024-12-16,1809,5.9,DataVision Ltd -AI12415,AI Specialist,75828,USD,75828,SE,FT,South Korea,S,Indonesia,100,"Scala, GCP, Spark, Java, Mathematics",PhD,6,Education,2024-03-12,2024-04-26,909,8.5,DeepTech Ventures -AI12416,Data Scientist,116542,GBP,87407,SE,FT,United Kingdom,S,United Kingdom,0,"Docker, Linux, AWS, GCP",Master,7,Technology,2024-05-31,2024-07-31,749,5.4,Machine Intelligence Group -AI12417,Deep Learning Engineer,53985,USD,53985,EN,CT,Finland,M,Finland,0,"Java, Tableau, SQL, GCP",Master,0,Retail,2024-05-19,2024-07-09,1864,5.6,Machine Intelligence Group -AI12418,Computer Vision Engineer,60582,EUR,51495,EN,FT,Netherlands,S,Netherlands,100,"Python, Kubernetes, PyTorch, MLOps",Associate,1,Media,2024-04-10,2024-05-02,2394,6.1,Cognitive Computing -AI12419,Machine Learning Engineer,135425,USD,135425,SE,FL,Norway,S,Norway,100,"PyTorch, Linux, Java, R, Git",Associate,6,Energy,2024-07-24,2024-10-04,1969,5.9,Neural Networks Co -AI12420,AI Specialist,62590,JPY,6884900,EN,CT,Japan,L,Japan,100,"Kubernetes, Java, Hadoop",Bachelor,0,Technology,2024-01-07,2024-02-26,2155,9.5,Smart Analytics -AI12421,AI Architect,231935,GBP,173951,EX,PT,United Kingdom,S,United Kingdom,0,"Scala, Spark, R",Bachelor,11,Retail,2024-03-18,2024-05-29,1567,8.6,Neural Networks Co -AI12422,Machine Learning Researcher,71430,USD,71430,EN,FL,Norway,S,Singapore,0,"Python, Statistics, Data Visualization, AWS",Associate,0,Education,2024-03-30,2024-06-01,1777,6.7,Advanced Robotics -AI12423,Computer Vision Engineer,220600,EUR,187510,EX,FT,France,L,France,0,"Java, TensorFlow, Statistics, Computer Vision",PhD,10,Healthcare,2024-10-19,2024-12-04,1423,9.7,Predictive Systems -AI12424,Head of AI,82694,USD,82694,EN,FT,Norway,S,Norway,50,"Python, Mathematics, Azure",Bachelor,1,Gaming,2024-04-06,2024-05-10,1192,9.6,DeepTech Ventures -AI12425,Robotics Engineer,123932,USD,123932,MI,PT,Sweden,L,Belgium,100,"Python, PyTorch, GCP",Master,3,Education,2024-10-30,2024-12-07,1401,6.8,Smart Analytics -AI12426,AI Consultant,137592,EUR,116953,SE,FT,Germany,M,Germany,100,"Kubernetes, AWS, Data Visualization",Associate,7,Automotive,2025-01-18,2025-03-07,1087,9.8,Predictive Systems -AI12427,Machine Learning Engineer,57950,USD,57950,EN,FL,South Korea,S,South Korea,100,"Tableau, Scala, Python, Deep Learning",PhD,1,Energy,2025-03-05,2025-04-08,2003,8.6,Neural Networks Co -AI12428,AI Architect,126435,USD,126435,SE,FT,Israel,S,Israel,0,"PyTorch, SQL, Linux",Bachelor,5,Real Estate,2024-12-21,2025-02-08,2132,5.6,Algorithmic Solutions -AI12429,Machine Learning Researcher,128267,JPY,14109370,SE,CT,Japan,M,Japan,50,"PyTorch, GCP, TensorFlow, Azure, Python",Bachelor,8,Transportation,2025-04-10,2025-05-17,2324,5.4,Autonomous Tech -AI12430,AI Research Scientist,309048,SGD,401762,EX,PT,Singapore,L,Singapore,50,"MLOps, Data Visualization, Java, Linux, R",PhD,12,Finance,2025-04-07,2025-05-31,1545,8.1,Neural Networks Co -AI12431,Data Analyst,134105,JPY,14751550,SE,FL,Japan,L,Japan,0,"Python, MLOps, Spark, NLP, Kubernetes",Bachelor,6,Education,2024-03-17,2024-05-23,2363,10,DeepTech Ventures -AI12432,AI Software Engineer,84521,USD,84521,MI,FT,Israel,S,Israel,0,"GCP, AWS, NLP, Python, Spark",PhD,4,Retail,2024-02-20,2024-04-29,1050,8.6,Smart Analytics -AI12433,Research Scientist,61395,SGD,79814,EN,CT,Singapore,M,Singapore,50,"Statistics, Tableau, NLP",Master,1,Real Estate,2024-04-29,2024-07-05,1577,9.7,Machine Intelligence Group -AI12434,NLP Engineer,152906,USD,152906,SE,CT,Norway,S,Norway,50,"R, GCP, Computer Vision, Linux",Master,6,Technology,2025-04-27,2025-06-19,2345,6.9,TechCorp Inc -AI12435,AI Research Scientist,150492,USD,150492,EX,FT,Israel,S,Switzerland,50,"Linux, TensorFlow, SQL, Deep Learning",Bachelor,18,Transportation,2024-10-24,2024-11-26,2445,5.1,DataVision Ltd -AI12436,Head of AI,261388,SGD,339804,EX,FT,Singapore,M,Singapore,0,"Java, Python, NLP, Docker",Master,10,Healthcare,2025-02-23,2025-04-23,1326,8.3,AI Innovations -AI12437,AI Software Engineer,181176,USD,181176,EX,CT,Finland,S,South Africa,50,"Computer Vision, Linux, Hadoop, Kubernetes, Scala",Bachelor,11,Real Estate,2024-11-22,2025-01-08,1295,6.7,Cognitive Computing -AI12438,Robotics Engineer,185060,EUR,157301,EX,FT,Germany,M,Germany,100,"R, Spark, SQL, Mathematics, Java",Bachelor,12,Media,2024-07-13,2024-08-14,1670,7.3,Neural Networks Co -AI12439,Data Scientist,128763,SGD,167392,SE,PT,Singapore,L,Singapore,100,"Python, Statistics, PyTorch, Spark",Associate,5,Education,2024-11-10,2024-12-24,1042,9,Cloud AI Solutions -AI12440,AI Software Engineer,125753,USD,125753,MI,FL,Denmark,M,Malaysia,50,"Scala, R, Kubernetes, Git, Python",Master,3,Education,2024-11-24,2024-12-11,2160,6.6,Neural Networks Co -AI12441,Data Scientist,121075,USD,121075,SE,FT,Israel,S,Israel,0,"PyTorch, Scala, Deep Learning, MLOps",PhD,6,Consulting,2024-12-24,2025-01-29,1737,5.8,Autonomous Tech -AI12442,ML Ops Engineer,27334,USD,27334,EN,CT,India,M,India,0,"Kubernetes, PyTorch, Statistics, Computer Vision, TensorFlow",PhD,1,Education,2025-04-01,2025-06-09,1734,8.9,Quantum Computing Inc -AI12443,Computer Vision Engineer,234245,CHF,210821,SE,FT,Switzerland,L,Egypt,50,"PyTorch, SQL, Git, Statistics, GCP",Associate,5,Media,2024-02-08,2024-04-13,2405,9.8,DataVision Ltd -AI12444,AI Software Engineer,79787,USD,79787,EN,FT,Norway,S,Norway,50,"TensorFlow, Tableau, AWS, MLOps",Associate,0,Government,2025-04-27,2025-06-17,695,6.3,Algorithmic Solutions -AI12445,Head of AI,46395,USD,46395,EN,FT,Sweden,S,Sweden,100,"PyTorch, Java, Git, Azure",Bachelor,0,Manufacturing,2024-10-19,2024-12-23,1792,5.6,Cognitive Computing -AI12446,AI Consultant,82377,EUR,70020,EN,CT,Austria,L,Poland,50,"TensorFlow, Python, Tableau",Bachelor,0,Healthcare,2024-02-20,2024-05-02,1384,7.5,Smart Analytics -AI12447,Machine Learning Engineer,63540,CAD,79425,EN,CT,Canada,M,Canada,0,"SQL, NLP, Kubernetes, Git",Associate,0,Energy,2024-12-19,2025-01-08,1756,6.7,Advanced Robotics -AI12448,NLP Engineer,90047,USD,90047,EX,PT,China,M,China,100,"SQL, Deep Learning, Spark, R, Tableau",Bachelor,18,Telecommunications,2025-04-22,2025-06-01,1548,9.9,Predictive Systems -AI12449,Head of AI,108278,USD,108278,SE,PT,Sweden,M,Sweden,50,"PyTorch, Git, Mathematics, Scala",Bachelor,5,Manufacturing,2024-05-13,2024-05-31,1662,8.1,Cognitive Computing -AI12450,Machine Learning Engineer,255205,JPY,28072550,EX,CT,Japan,L,Japan,100,"R, Mathematics, Linux",Bachelor,17,Technology,2024-09-12,2024-10-16,1755,5.2,Algorithmic Solutions -AI12451,Machine Learning Engineer,63780,USD,63780,SE,PT,China,M,China,100,"PyTorch, Computer Vision, Tableau",Associate,8,Energy,2024-08-13,2024-10-04,1419,6.3,Predictive Systems -AI12452,Machine Learning Researcher,57335,GBP,43001,EN,FT,United Kingdom,S,Belgium,50,"Git, Mathematics, MLOps, Deep Learning, R",PhD,0,Retail,2024-01-31,2024-03-11,814,10,Neural Networks Co -AI12453,AI Consultant,68846,USD,68846,EN,PT,Finland,M,Finland,50,"Scala, Tableau, Deep Learning",PhD,1,Gaming,2025-02-18,2025-03-12,2445,7.5,DataVision Ltd -AI12454,Autonomous Systems Engineer,127642,EUR,108496,SE,CT,Netherlands,L,India,50,"MLOps, TensorFlow, AWS, Hadoop",Master,6,Technology,2025-04-24,2025-07-04,1015,7.5,Machine Intelligence Group -AI12455,Data Engineer,119425,USD,119425,SE,PT,Ireland,M,Nigeria,0,"Hadoop, Python, MLOps",Associate,9,Education,2025-04-15,2025-05-14,1732,5.9,Advanced Robotics -AI12456,Data Scientist,29224,USD,29224,EN,PT,China,S,China,0,"Data Visualization, Scala, Kubernetes, SQL, R",Associate,0,Finance,2024-12-08,2024-12-28,2189,9.1,Predictive Systems -AI12457,Computer Vision Engineer,198486,EUR,168713,EX,PT,Austria,M,Austria,100,"TensorFlow, Azure, NLP, Computer Vision",Associate,13,Telecommunications,2024-07-25,2024-09-25,1275,8.2,Advanced Robotics -AI12458,Machine Learning Engineer,203533,CHF,183180,EX,FT,Switzerland,S,Switzerland,0,"GCP, SQL, PyTorch, Kubernetes, Statistics",Bachelor,14,Technology,2025-04-24,2025-05-20,696,6.6,TechCorp Inc -AI12459,AI Product Manager,194939,EUR,165698,EX,FL,France,L,France,50,"Linux, Mathematics, NLP, PyTorch",Bachelor,10,Telecommunications,2024-03-26,2024-05-07,1719,6.7,Algorithmic Solutions -AI12460,Data Analyst,61708,EUR,52452,EN,PT,Germany,S,Germany,50,"Hadoop, Python, Git",Bachelor,1,Manufacturing,2024-05-22,2024-06-14,629,7.5,DataVision Ltd -AI12461,AI Research Scientist,100793,USD,100793,MI,FL,Ireland,L,Ireland,50,"Linux, Hadoop, R, Computer Vision, Statistics",Master,4,Gaming,2024-05-29,2024-08-09,2070,9,Advanced Robotics -AI12462,AI Architect,75694,GBP,56771,EN,PT,United Kingdom,M,Austria,0,"Statistics, PyTorch, Docker, Azure, SQL",Associate,0,Manufacturing,2025-01-06,2025-02-11,2171,8.3,Cognitive Computing -AI12463,Data Scientist,115446,EUR,98129,MI,FL,Netherlands,L,Netherlands,50,"Docker, Python, Deep Learning, Spark",Associate,2,Transportation,2024-07-21,2024-08-23,2121,7.9,Smart Analytics -AI12464,Research Scientist,49167,EUR,41792,EN,FT,Austria,S,Austria,100,"R, Mathematics, Hadoop",Associate,0,Automotive,2024-07-10,2024-08-10,614,8.4,DataVision Ltd -AI12465,AI Product Manager,70180,USD,70180,EN,FL,Sweden,S,Sweden,0,"Docker, R, Deep Learning, SQL",Master,1,Government,2024-03-23,2024-05-12,580,7.5,DeepTech Ventures -AI12466,Data Analyst,19503,USD,19503,EN,CT,India,S,India,0,"PyTorch, Azure, R, SQL",Bachelor,0,Education,2025-03-12,2025-03-26,2448,5.9,Digital Transformation LLC -AI12467,Data Engineer,92958,USD,92958,SE,FT,South Korea,M,South Korea,0,"Azure, SQL, Kubernetes, Spark, Linux",Associate,7,Government,2024-03-19,2024-04-03,1193,6.8,AI Innovations -AI12468,ML Ops Engineer,46075,USD,46075,EX,CT,India,S,India,50,"Scala, NLP, Git",Bachelor,17,Media,2024-10-06,2024-11-30,1655,10,Algorithmic Solutions -AI12469,Data Engineer,31356,USD,31356,MI,FT,China,S,China,0,"Mathematics, Python, Tableau, Computer Vision, SQL",Bachelor,4,Real Estate,2025-03-05,2025-04-06,857,7.5,AI Innovations -AI12470,Data Engineer,169277,EUR,143885,EX,FL,Austria,M,Vietnam,0,"SQL, Git, PyTorch, NLP",Master,12,Media,2024-08-17,2024-10-27,664,7.8,Smart Analytics -AI12471,Machine Learning Engineer,34533,USD,34533,MI,CT,China,M,China,100,"AWS, Tableau, TensorFlow, Spark",PhD,3,Government,2024-04-18,2024-05-15,1855,8.2,DataVision Ltd -AI12472,Deep Learning Engineer,72285,JPY,7951350,EN,FL,Japan,S,Japan,50,"Linux, MLOps, Git, Java",PhD,0,Healthcare,2024-09-24,2024-10-28,1564,7.9,Machine Intelligence Group -AI12473,Machine Learning Researcher,212718,USD,212718,EX,CT,Finland,S,Finland,50,"SQL, Python, Hadoop, Mathematics, Computer Vision",PhD,17,Education,2025-04-05,2025-06-06,2270,8.6,Machine Intelligence Group -AI12474,Machine Learning Engineer,202624,EUR,172230,EX,CT,France,S,France,50,"PyTorch, Hadoop, TensorFlow, SQL",PhD,16,Finance,2024-12-30,2025-01-13,1686,7.2,Machine Intelligence Group -AI12475,ML Ops Engineer,71740,USD,71740,MI,CT,South Korea,L,South Korea,50,"SQL, AWS, Computer Vision, Spark, Linux",Associate,3,Automotive,2025-04-06,2025-05-13,756,9.9,Cloud AI Solutions -AI12476,Autonomous Systems Engineer,232339,CHF,209105,EX,CT,Switzerland,L,Switzerland,0,"AWS, Python, Kubernetes",Master,18,Retail,2024-12-07,2025-01-25,1266,7.2,AI Innovations -AI12477,Machine Learning Engineer,147817,USD,147817,EX,CT,Israel,S,India,0,"Scala, R, SQL",Bachelor,15,Telecommunications,2024-12-13,2025-01-18,1399,6.3,Future Systems -AI12478,Data Engineer,73011,EUR,62059,MI,PT,Germany,S,Germany,50,"SQL, Scala, Tableau",Associate,3,Education,2024-11-22,2024-12-16,1245,7.3,Cognitive Computing -AI12479,ML Ops Engineer,69151,USD,69151,EN,CT,Israel,M,Israel,100,"PyTorch, Python, Statistics",PhD,0,Technology,2024-06-09,2024-08-07,1621,6.5,Digital Transformation LLC -AI12480,Machine Learning Engineer,200050,CHF,180045,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Data Visualization, Statistics, Git",Associate,5,Transportation,2024-05-24,2024-07-16,982,5.5,Autonomous Tech -AI12481,Data Engineer,68571,AUD,92571,MI,FL,Australia,S,Romania,0,"MLOps, Azure, Tableau",Bachelor,3,Consulting,2025-04-10,2025-05-15,578,9.6,DataVision Ltd -AI12482,AI Specialist,27494,USD,27494,EN,FL,China,S,Brazil,50,"Python, Azure, Git, R, Computer Vision",PhD,0,Finance,2024-10-05,2024-11-07,1180,9.1,Cloud AI Solutions -AI12483,AI Research Scientist,54178,USD,54178,SE,CT,China,M,United States,100,"Linux, Scala, PyTorch",PhD,5,Healthcare,2025-04-02,2025-05-31,1625,7.5,Advanced Robotics -AI12484,Robotics Engineer,147943,USD,147943,SE,CT,Denmark,M,Denmark,0,"GCP, Python, Mathematics, Linux",Bachelor,9,Finance,2025-03-19,2025-04-15,1829,6.6,Cloud AI Solutions -AI12485,Research Scientist,246165,CHF,221549,SE,FT,Switzerland,L,Switzerland,50,"Deep Learning, Data Visualization, Docker",Associate,8,Transportation,2024-08-13,2024-09-19,1412,6.4,DataVision Ltd -AI12486,Autonomous Systems Engineer,31203,USD,31203,MI,FT,India,M,India,50,"Data Visualization, SQL, Scala, Tableau, Git",Bachelor,2,Energy,2024-02-27,2024-04-03,1073,5.4,Digital Transformation LLC -AI12487,Head of AI,109051,USD,109051,SE,PT,South Korea,S,South Korea,100,"Scala, AWS, Python",Master,7,Technology,2024-11-09,2024-12-11,1828,7.7,DataVision Ltd -AI12488,AI Consultant,76767,EUR,65252,EN,FL,Netherlands,M,Romania,100,"Tableau, Scala, Docker",Associate,0,Transportation,2024-08-22,2024-10-22,1011,5.9,TechCorp Inc -AI12489,Computer Vision Engineer,64846,GBP,48635,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Scala, TensorFlow",Master,0,Gaming,2024-10-08,2024-12-06,621,6.9,TechCorp Inc -AI12490,Data Engineer,126205,AUD,170377,SE,FT,Australia,L,Australia,100,"Spark, Linux, GCP",Associate,7,Real Estate,2024-01-19,2024-03-08,2036,6.5,Future Systems -AI12491,Data Engineer,162483,USD,162483,MI,PT,Norway,L,Norway,100,"Java, Statistics, R, Docker, Scala",Master,3,Consulting,2024-12-17,2025-02-02,1825,8.3,DeepTech Ventures -AI12492,Machine Learning Engineer,77554,USD,77554,MI,CT,Israel,S,Israel,50,"Azure, AWS, TensorFlow, Linux, Mathematics",Master,3,Education,2024-10-26,2024-11-30,807,5.5,Algorithmic Solutions -AI12493,AI Product Manager,216415,JPY,23805650,EX,FT,Japan,L,Japan,0,"Scala, Python, Hadoop, Git",Master,14,Transportation,2024-01-20,2024-02-15,1804,7.5,Future Systems -AI12494,AI Architect,130182,EUR,110655,SE,FL,Germany,S,Germany,50,"SQL, TensorFlow, GCP",Bachelor,9,Education,2025-03-27,2025-05-17,662,5.9,Machine Intelligence Group -AI12495,Data Scientist,187797,SGD,244136,EX,FL,Singapore,S,Singapore,100,"R, MLOps, Kubernetes, Statistics, Deep Learning",PhD,18,Healthcare,2024-06-30,2024-09-03,799,5.2,Advanced Robotics -AI12496,AI Software Engineer,123365,USD,123365,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Mathematics, TensorFlow, AWS",Associate,4,Manufacturing,2025-01-20,2025-03-24,1723,5.6,Quantum Computing Inc -AI12497,Data Analyst,69926,EUR,59437,EN,FT,Austria,L,Austria,50,"GCP, MLOps, Statistics",Master,1,Real Estate,2024-04-23,2024-06-20,2381,7.5,Cognitive Computing -AI12498,AI Architect,80574,GBP,60431,EN,FT,United Kingdom,M,Poland,50,"Python, Deep Learning, Kubernetes",Associate,0,Finance,2024-07-31,2024-08-23,2300,6.7,Neural Networks Co -AI12499,Computer Vision Engineer,80148,USD,80148,EN,CT,United States,S,United States,50,"Kubernetes, TensorFlow, Computer Vision, Hadoop, Linux",PhD,1,Transportation,2024-10-28,2024-12-23,1220,6.7,DataVision Ltd -AI12500,Machine Learning Engineer,270850,EUR,230223,EX,CT,Germany,L,Indonesia,100,"Statistics, Python, Data Visualization, Scala",Associate,11,Gaming,2025-02-04,2025-03-09,1919,9.5,Neural Networks Co -AI12501,Deep Learning Engineer,160933,CHF,144840,SE,CT,Switzerland,M,Switzerland,100,"Docker, R, Mathematics, Spark, Azure",PhD,7,Energy,2024-03-19,2024-04-19,2404,8,DataVision Ltd -AI12502,Machine Learning Researcher,165119,USD,165119,EX,FT,Ireland,M,Ireland,0,"Data Visualization, Hadoop, Python, Linux",Bachelor,16,Energy,2024-02-05,2024-02-27,709,5.5,Cognitive Computing -AI12503,Deep Learning Engineer,145099,EUR,123334,SE,PT,Germany,L,Germany,50,"GCP, Linux, Tableau, Spark, Data Visualization",Master,7,Media,2025-03-11,2025-05-07,717,6.9,Smart Analytics -AI12504,NLP Engineer,51742,JPY,5691620,EN,FL,Japan,S,Japan,100,"Kubernetes, Python, Data Visualization, Git",PhD,1,Education,2024-02-28,2024-03-19,1536,8.3,Autonomous Tech -AI12505,AI Software Engineer,109327,USD,109327,SE,CT,Sweden,M,Sweden,50,"Docker, MLOps, AWS",PhD,9,Consulting,2024-07-03,2024-07-24,1297,9,DataVision Ltd -AI12506,AI Specialist,151570,CHF,136413,MI,PT,Switzerland,M,Switzerland,100,"Tableau, Kubernetes, TensorFlow, Spark",Master,2,Government,2024-05-27,2024-07-18,2059,7.2,Advanced Robotics -AI12507,Deep Learning Engineer,214037,USD,214037,EX,PT,Sweden,S,Sweden,0,"Mathematics, Computer Vision, Linux",Master,19,Government,2024-03-18,2024-04-11,1865,9.1,Advanced Robotics -AI12508,AI Product Manager,238972,USD,238972,EX,CT,Finland,L,Finland,0,"GCP, Hadoop, Tableau, Deep Learning",Master,18,Healthcare,2024-01-10,2024-02-29,1350,9.8,Predictive Systems -AI12509,Data Analyst,120788,EUR,102670,SE,PT,Germany,L,Germany,50,"Spark, Linux, Deep Learning, Git, TensorFlow",Associate,7,Retail,2024-07-24,2024-09-15,606,8.3,Cognitive Computing -AI12510,AI Product Manager,161084,USD,161084,SE,FT,United States,L,Spain,0,"Linux, Tableau, Data Visualization, Hadoop",Bachelor,7,Telecommunications,2024-01-23,2024-03-16,1681,8,Future Systems -AI12511,AI Specialist,224471,CAD,280589,EX,PT,Canada,M,Canada,100,"SQL, NLP, Azure",Master,17,Government,2024-12-04,2025-02-02,2031,5.4,Neural Networks Co -AI12512,Robotics Engineer,162992,AUD,220039,SE,CT,Australia,L,South Korea,100,"R, NLP, Linux, SQL",Bachelor,8,Government,2024-08-22,2024-09-27,746,6.8,Future Systems -AI12513,Data Analyst,30696,USD,30696,EN,CT,China,S,Portugal,0,"GCP, NLP, Linux, R",Master,0,Media,2024-10-08,2024-11-14,1377,9.1,Algorithmic Solutions -AI12514,Research Scientist,98339,EUR,83588,SE,CT,Austria,M,Austria,0,"PyTorch, R, TensorFlow",Associate,5,Retail,2025-03-28,2025-06-07,1314,5.7,Neural Networks Co -AI12515,Research Scientist,129262,EUR,109873,SE,CT,Austria,M,Austria,0,"Python, Azure, Docker, R, Git",PhD,7,Energy,2024-01-08,2024-02-05,2298,8.5,Autonomous Tech -AI12516,Machine Learning Engineer,112931,CAD,141164,SE,PT,Canada,L,Canada,0,"Python, Tableau, Docker",Associate,8,Consulting,2024-12-14,2025-01-25,2110,6.5,Cognitive Computing -AI12517,AI Product Manager,109950,USD,109950,MI,FT,Ireland,L,Estonia,0,"Azure, AWS, Linux, Docker",Associate,3,Media,2024-07-25,2024-09-12,1158,8.2,Autonomous Tech -AI12518,Computer Vision Engineer,84503,EUR,71828,EN,FT,Germany,L,Germany,0,"R, Linux, NLP",PhD,1,Gaming,2024-04-19,2024-06-20,1765,5.6,Smart Analytics -AI12519,Principal Data Scientist,89243,USD,89243,MI,FL,Sweden,M,South Africa,100,"Azure, Data Visualization, Kubernetes, Docker",PhD,3,Retail,2024-11-09,2024-12-14,592,8,Predictive Systems -AI12520,Data Analyst,194683,CHF,175215,SE,FL,Switzerland,M,Switzerland,100,"Hadoop, SQL, Linux, Scala",PhD,8,Real Estate,2024-03-03,2024-05-11,2107,7.7,Autonomous Tech -AI12521,Data Scientist,34111,USD,34111,MI,PT,China,S,China,50,"Statistics, AWS, R",Master,2,Telecommunications,2024-08-10,2024-09-03,870,6.5,AI Innovations -AI12522,NLP Engineer,104286,SGD,135572,MI,PT,Singapore,L,Singapore,100,"MLOps, Docker, Java, Spark",PhD,4,Finance,2024-04-19,2024-06-07,2023,8.2,Cognitive Computing -AI12523,Research Scientist,87236,EUR,74151,MI,FL,Germany,M,Germany,100,"Java, Hadoop, Python, Spark, TensorFlow",Associate,3,Technology,2024-02-23,2024-04-13,1927,9.6,DataVision Ltd -AI12524,Head of AI,61002,EUR,51852,EN,PT,Germany,L,Germany,50,"Computer Vision, Kubernetes, Hadoop",Master,1,Media,2024-07-14,2024-07-31,2002,5.9,Advanced Robotics -AI12525,Autonomous Systems Engineer,131108,GBP,98331,MI,FL,United Kingdom,L,United Kingdom,100,"AWS, MLOps, Tableau",PhD,3,Government,2024-02-18,2024-04-21,1902,5.8,TechCorp Inc -AI12526,NLP Engineer,109470,GBP,82103,MI,PT,United Kingdom,L,Egypt,100,"Python, TensorFlow, Statistics",Master,3,Media,2025-03-03,2025-05-01,1242,6.5,Autonomous Tech -AI12527,AI Consultant,63355,GBP,47516,EN,FT,United Kingdom,S,United Kingdom,50,"PyTorch, Linux, Python, Scala",Bachelor,0,Healthcare,2024-07-12,2024-09-09,1354,9.1,DataVision Ltd -AI12528,Data Engineer,199949,EUR,169957,EX,PT,Austria,M,Austria,50,"Git, Spark, GCP",Master,17,Retail,2024-08-30,2024-11-10,1410,8.9,TechCorp Inc -AI12529,Principal Data Scientist,59401,CAD,74251,EN,FL,Canada,S,Portugal,50,"Git, SQL, Scala",PhD,0,Energy,2024-04-27,2024-05-16,2043,9.9,Algorithmic Solutions -AI12530,Head of AI,100922,USD,100922,MI,PT,South Korea,L,South Korea,100,"Python, Git, SQL, Java, Computer Vision",PhD,3,Real Estate,2024-12-21,2025-02-20,2101,8,Machine Intelligence Group -AI12531,Data Analyst,64014,USD,64014,EN,FT,Israel,M,Israel,50,"SQL, PyTorch, Computer Vision, Git",Master,1,Finance,2024-08-01,2024-08-16,2168,8.9,Predictive Systems -AI12532,AI Consultant,164409,AUD,221952,SE,CT,Australia,L,Canada,0,"Kubernetes, PyTorch, Mathematics, SQL, Tableau",Master,6,Gaming,2024-08-30,2024-11-01,2111,7.2,Digital Transformation LLC -AI12533,NLP Engineer,214487,EUR,182314,EX,FL,France,M,France,100,"Kubernetes, SQL, PyTorch",Master,11,Government,2024-09-29,2024-11-04,1748,8.5,Cloud AI Solutions -AI12534,Autonomous Systems Engineer,133642,USD,133642,MI,PT,Norway,L,Norway,100,"Scala, Statistics, Spark",Master,4,Manufacturing,2024-05-25,2024-07-13,850,7.5,Predictive Systems -AI12535,AI Software Engineer,93357,USD,93357,EN,CT,United States,L,United States,0,"Computer Vision, NLP, Tableau, Python",PhD,1,Healthcare,2024-06-28,2024-08-07,1914,7.6,TechCorp Inc -AI12536,Robotics Engineer,68512,USD,68512,SE,FL,China,M,China,0,"Linux, MLOps, AWS, Statistics",PhD,9,Technology,2024-12-11,2025-01-29,1339,8,Algorithmic Solutions -AI12537,AI Specialist,134492,USD,134492,MI,PT,Denmark,M,Denmark,50,"MLOps, GCP, Java, Hadoop",Master,4,Retail,2024-02-21,2024-03-23,2035,5.2,AI Innovations -AI12538,Autonomous Systems Engineer,131311,JPY,14444210,SE,CT,Japan,M,Vietnam,0,"Scala, R, Azure, Git, Kubernetes",Associate,5,Manufacturing,2024-08-10,2024-09-23,1940,8.9,DeepTech Ventures -AI12539,Principal Data Scientist,255914,GBP,191936,EX,PT,United Kingdom,M,South Korea,0,"Git, Kubernetes, NLP",PhD,15,Gaming,2025-01-29,2025-03-25,1748,7.6,Machine Intelligence Group -AI12540,ML Ops Engineer,49654,USD,49654,EN,FT,Ireland,S,Ireland,100,"Scala, Linux, SQL, Statistics",PhD,0,Real Estate,2024-04-14,2024-06-16,2019,7.4,Predictive Systems -AI12541,AI Architect,47136,USD,47136,EN,CT,Israel,S,Israel,0,"PyTorch, SQL, Docker, AWS, Linux",PhD,1,Technology,2024-05-06,2024-06-21,721,9,Quantum Computing Inc -AI12542,AI Research Scientist,42011,USD,42011,MI,FT,India,L,India,50,"Computer Vision, Java, Python, Azure, Git",Master,3,Real Estate,2024-01-15,2024-02-12,1652,8.1,DataVision Ltd -AI12543,AI Consultant,119147,USD,119147,MI,FL,Finland,L,Russia,100,"Java, PyTorch, MLOps, Hadoop, NLP",Associate,4,Consulting,2024-04-21,2024-05-23,1670,7.3,DeepTech Ventures -AI12544,ML Ops Engineer,98976,USD,98976,MI,CT,United States,S,Mexico,50,"Computer Vision, TensorFlow, Python, Git, R",Bachelor,2,Consulting,2024-10-22,2024-12-31,613,6.7,Smart Analytics -AI12545,Autonomous Systems Engineer,50267,EUR,42727,EN,FT,Germany,S,Philippines,100,"Spark, TensorFlow, Kubernetes, Java, Mathematics",Master,1,Real Estate,2025-04-25,2025-05-25,1081,8.6,Machine Intelligence Group -AI12546,Robotics Engineer,26722,USD,26722,EN,FT,China,S,China,0,"Git, SQL, R, GCP",Bachelor,0,Consulting,2024-10-13,2024-11-11,2251,6.1,Digital Transformation LLC -AI12547,ML Ops Engineer,131283,GBP,98462,SE,CT,United Kingdom,M,Thailand,50,"Tableau, TensorFlow, Docker, GCP, Scala",Bachelor,6,Telecommunications,2024-04-07,2024-05-30,2032,8.5,Cognitive Computing -AI12548,AI Product Manager,117952,SGD,153338,SE,FL,Singapore,M,France,50,"MLOps, SQL, Python, Computer Vision",PhD,5,Technology,2024-04-25,2024-06-10,2174,5.7,AI Innovations -AI12549,Deep Learning Engineer,25607,USD,25607,MI,PT,India,M,Ukraine,100,"PyTorch, Linux, Tableau, GCP",Bachelor,2,Media,2024-12-30,2025-01-17,518,6.9,Digital Transformation LLC -AI12550,Deep Learning Engineer,233172,USD,233172,EX,PT,United States,M,Netherlands,50,"SQL, Tableau, Deep Learning, Java",PhD,18,Telecommunications,2024-04-30,2024-06-19,802,6,TechCorp Inc -AI12551,Data Analyst,74780,AUD,100953,EN,PT,Australia,L,Australia,100,"AWS, GCP, Kubernetes",Bachelor,1,Consulting,2025-03-04,2025-03-24,1215,8.9,Quantum Computing Inc -AI12552,AI Research Scientist,166556,CHF,149900,SE,FT,Switzerland,L,Australia,0,"NLP, R, Scala",Bachelor,7,Finance,2024-09-15,2024-10-14,911,7.1,Advanced Robotics -AI12553,AI Research Scientist,332451,USD,332451,EX,CT,United States,L,United States,50,"Spark, Hadoop, PyTorch",Associate,17,Technology,2024-12-15,2025-01-03,1752,8.2,Advanced Robotics -AI12554,Research Scientist,226551,CHF,203896,SE,FL,Switzerland,L,Switzerland,0,"R, Python, Tableau, Deep Learning",Bachelor,9,Retail,2024-02-08,2024-03-21,1144,9,Advanced Robotics -AI12555,AI Consultant,182206,USD,182206,EX,PT,Sweden,M,Sweden,50,"SQL, Java, Tableau, Statistics, PyTorch",Master,18,Media,2024-09-21,2024-11-02,1591,7.5,Machine Intelligence Group -AI12556,AI Consultant,155691,EUR,132337,SE,CT,Austria,L,Brazil,100,"Hadoop, TensorFlow, GCP, Spark",PhD,6,Telecommunications,2025-01-12,2025-02-16,568,7.4,Smart Analytics -AI12557,Machine Learning Researcher,69981,USD,69981,EN,PT,Sweden,S,Sweden,50,"Python, Deep Learning, TensorFlow, Scala",Master,0,Technology,2024-03-27,2024-06-04,809,5.3,Cognitive Computing -AI12558,Computer Vision Engineer,115602,USD,115602,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Git, Tableau, Statistics, Scala",Associate,2,Consulting,2024-07-31,2024-09-20,2388,7.9,Autonomous Tech -AI12559,Data Analyst,65661,GBP,49246,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, NLP, Kubernetes",Associate,1,Automotive,2024-03-10,2024-04-01,2178,6.6,Future Systems -AI12560,ML Ops Engineer,54988,EUR,46740,EN,FL,France,M,France,100,"Hadoop, SQL, Deep Learning",Bachelor,1,Energy,2024-06-20,2024-08-16,904,5.6,Machine Intelligence Group -AI12561,Deep Learning Engineer,255127,GBP,191345,EX,FT,United Kingdom,L,United Kingdom,0,"Git, PyTorch, Java",Associate,13,Healthcare,2024-01-15,2024-03-25,2312,7.5,Quantum Computing Inc -AI12562,NLP Engineer,60129,USD,60129,EN,CT,Finland,L,Finland,50,"AWS, PyTorch, TensorFlow",Associate,0,Real Estate,2024-01-12,2024-03-12,1811,6.7,Smart Analytics -AI12563,NLP Engineer,151050,USD,151050,EX,FT,Finland,M,Romania,100,"Git, PyTorch, Statistics, R",Bachelor,13,Technology,2024-07-08,2024-09-04,1605,7.8,Smart Analytics -AI12564,NLP Engineer,102467,EUR,87097,MI,FL,France,L,France,0,"PyTorch, Hadoop, Deep Learning, Statistics",PhD,3,Healthcare,2024-05-19,2024-07-26,2339,8.1,Future Systems -AI12565,AI Software Engineer,91655,USD,91655,MI,FL,Sweden,M,Sweden,50,"R, Linux, Spark, Scala, Python",Associate,3,Gaming,2024-09-13,2024-11-11,598,9.4,Digital Transformation LLC -AI12566,Machine Learning Engineer,114161,EUR,97037,MI,FT,France,L,France,50,"Java, Python, Spark",Master,2,Government,2024-11-30,2025-01-30,521,9.2,DeepTech Ventures -AI12567,Data Analyst,73257,EUR,62268,MI,CT,Austria,M,Austria,100,"AWS, PyTorch, Spark, Statistics",Bachelor,2,Education,2024-05-28,2024-07-25,1845,9.4,AI Innovations -AI12568,Computer Vision Engineer,108618,USD,108618,MI,FL,Israel,L,Israel,0,"Java, Docker, GCP, R",PhD,3,Finance,2024-01-18,2024-02-22,581,7.5,Predictive Systems -AI12569,AI Specialist,62843,USD,62843,EN,FL,Denmark,S,Denmark,50,"AWS, Azure, Mathematics, Docker, Kubernetes",Bachelor,1,Education,2024-02-23,2024-04-25,2065,6.3,Quantum Computing Inc -AI12570,Research Scientist,178712,EUR,151905,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, NLP, Docker, Spark",Bachelor,8,Finance,2025-02-22,2025-03-23,1151,8.8,Cloud AI Solutions -AI12571,Machine Learning Researcher,66399,USD,66399,EN,FT,Sweden,M,Sweden,0,"Deep Learning, Python, SQL, GCP, Hadoop",Bachelor,0,Consulting,2024-05-05,2024-06-23,1774,6.6,Algorithmic Solutions -AI12572,Deep Learning Engineer,26206,USD,26206,MI,PT,India,S,Australia,50,"PyTorch, Scala, Git, Data Visualization, Spark",Master,4,Gaming,2024-05-02,2024-06-25,2135,9.7,Smart Analytics -AI12573,Autonomous Systems Engineer,132926,CAD,166158,SE,CT,Canada,M,Canada,100,"R, Deep Learning, Hadoop",Bachelor,9,Healthcare,2024-12-05,2025-01-30,779,6.3,Advanced Robotics -AI12574,Machine Learning Researcher,212788,USD,212788,SE,FT,Norway,L,Spain,100,"Python, Statistics, TensorFlow, Tableau",PhD,9,Consulting,2025-02-24,2025-04-01,743,5.6,Algorithmic Solutions -AI12575,AI Specialist,38991,USD,38991,EN,FL,South Korea,S,South Korea,100,"Docker, Python, TensorFlow",Master,1,Telecommunications,2024-07-02,2024-08-15,955,9.8,Machine Intelligence Group -AI12576,AI Product Manager,50232,USD,50232,EN,PT,Israel,S,Israel,100,"Statistics, R, Data Visualization, Tableau, Deep Learning",PhD,1,Manufacturing,2025-01-07,2025-02-06,2141,7.2,Algorithmic Solutions -AI12577,AI Software Engineer,134499,USD,134499,EX,PT,Finland,M,Finland,50,"SQL, NLP, Spark, Python",PhD,13,Real Estate,2024-11-15,2024-12-05,1800,7.2,DataVision Ltd -AI12578,Research Scientist,148779,USD,148779,EX,PT,South Korea,L,South Korea,100,"R, Azure, Tableau, Docker",Associate,17,Telecommunications,2025-04-24,2025-05-20,2101,9.9,Future Systems -AI12579,Principal Data Scientist,70847,USD,70847,EN,FL,Norway,S,Norway,100,"R, Data Visualization, GCP",Associate,1,Energy,2024-10-23,2024-11-13,1102,9.5,Autonomous Tech -AI12580,AI Software Engineer,62204,USD,62204,EN,FT,Ireland,L,New Zealand,0,"AWS, NLP, Kubernetes, R",Associate,0,Manufacturing,2024-10-06,2024-12-09,1579,5.9,Algorithmic Solutions -AI12581,AI Software Engineer,129841,SGD,168793,EX,FT,Singapore,S,Singapore,100,"R, SQL, NLP, Azure, Python",Master,17,Finance,2024-01-01,2024-03-14,591,9.3,DataVision Ltd -AI12582,Data Analyst,155034,EUR,131779,SE,FT,Netherlands,M,Mexico,50,"TensorFlow, Python, MLOps, PyTorch, Tableau",Master,9,Healthcare,2024-11-14,2024-12-31,2353,9.2,Cognitive Computing -AI12583,AI Software Engineer,187509,JPY,20625990,EX,FL,Japan,S,Israel,100,"R, MLOps, Java, Statistics, TensorFlow",Master,15,Automotive,2024-05-13,2024-05-31,2287,9.4,Algorithmic Solutions -AI12584,AI Consultant,177222,EUR,150639,EX,FL,France,M,Colombia,50,"AWS, Git, NLP, Linux",Bachelor,10,Automotive,2025-02-25,2025-04-07,1455,7.7,DataVision Ltd -AI12585,ML Ops Engineer,333553,USD,333553,EX,FL,Norway,L,Norway,100,"TensorFlow, Python, MLOps, Java, R",PhD,17,Healthcare,2025-04-16,2025-06-27,638,9,Predictive Systems -AI12586,AI Product Manager,51703,EUR,43948,EN,PT,Germany,S,Luxembourg,100,"Linux, Docker, Git, R",Associate,1,Retail,2025-02-26,2025-04-15,914,6.4,Future Systems -AI12587,Data Analyst,161634,USD,161634,SE,FL,Israel,L,Israel,50,"Python, Azure, Mathematics",Bachelor,7,Retail,2025-02-22,2025-03-31,2194,7,AI Innovations -AI12588,AI Product Manager,166572,JPY,18322920,SE,FL,Japan,L,Japan,100,"Docker, Java, R, SQL, AWS",PhD,8,Retail,2024-09-17,2024-10-27,2063,9.2,Predictive Systems -AI12589,NLP Engineer,208798,USD,208798,EX,CT,Sweden,L,Indonesia,50,"Kubernetes, Data Visualization, TensorFlow",Master,19,Automotive,2024-12-02,2025-01-28,1995,5.2,AI Innovations -AI12590,Data Analyst,86613,USD,86613,MI,FL,Finland,L,Finland,100,"Git, GCP, Computer Vision, AWS, Hadoop",PhD,2,Manufacturing,2024-11-16,2024-12-04,1178,6.7,Neural Networks Co -AI12591,Machine Learning Engineer,117597,CHF,105837,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, Docker, Java",Bachelor,4,Automotive,2024-03-30,2024-04-20,2021,5.2,Machine Intelligence Group -AI12592,Data Analyst,22513,USD,22513,EN,CT,India,L,India,0,"Deep Learning, GCP, Mathematics, R",Associate,0,Telecommunications,2024-05-05,2024-06-20,1160,7.9,Future Systems -AI12593,Machine Learning Engineer,105654,SGD,137350,MI,CT,Singapore,L,Singapore,0,"Mathematics, Git, Scala, Linux",Bachelor,4,Education,2025-01-15,2025-02-03,938,9.7,Quantum Computing Inc -AI12594,AI Consultant,224641,SGD,292033,EX,FT,Singapore,L,Israel,100,"Linux, Java, Mathematics, Hadoop, SQL",Associate,12,Education,2024-09-20,2024-10-09,1957,6.6,Autonomous Tech -AI12595,Computer Vision Engineer,92817,USD,92817,MI,CT,Denmark,S,Denmark,100,"PyTorch, Linux, TensorFlow, R, Mathematics",Associate,4,Finance,2024-06-05,2024-06-23,1419,8.8,Neural Networks Co -AI12596,Deep Learning Engineer,87012,EUR,73960,EN,PT,Austria,L,Austria,100,"Linux, PyTorch, Computer Vision",Bachelor,1,Retail,2025-01-26,2025-02-20,2106,9.6,Autonomous Tech -AI12597,AI Product Manager,176978,USD,176978,EX,PT,Finland,S,New Zealand,100,"Hadoop, Docker, Linux",PhD,19,Automotive,2024-07-11,2024-08-06,776,8.9,Digital Transformation LLC -AI12598,AI Software Engineer,31871,USD,31871,MI,CT,India,L,India,0,"Statistics, Mathematics, TensorFlow",Associate,4,Transportation,2024-04-08,2024-06-08,905,7.7,Future Systems -AI12599,Data Engineer,111513,USD,111513,MI,FL,United States,S,Finland,0,"Kubernetes, Azure, Deep Learning, Data Visualization, SQL",Associate,3,Healthcare,2024-06-09,2024-06-23,901,7.5,AI Innovations -AI12600,Data Scientist,124502,EUR,105827,SE,CT,Austria,M,Austria,100,"Linux, Tableau, Python, Computer Vision, TensorFlow",Master,7,Retail,2024-03-07,2024-03-30,1777,6,DeepTech Ventures -AI12601,AI Architect,143750,EUR,122188,SE,CT,France,M,Brazil,50,"Java, AWS, Git",PhD,9,Finance,2024-06-10,2024-07-15,1569,9.6,Predictive Systems -AI12602,Deep Learning Engineer,107546,EUR,91414,SE,PT,Germany,M,Czech Republic,0,"Tableau, Python, PyTorch",Master,9,Finance,2025-02-20,2025-04-09,641,8.7,Quantum Computing Inc -AI12603,Research Scientist,208493,EUR,177219,EX,FL,Germany,L,Germany,100,"R, SQL, PyTorch",PhD,19,Manufacturing,2024-10-07,2024-11-03,615,6.4,AI Innovations -AI12604,Computer Vision Engineer,290203,USD,290203,EX,CT,Norway,M,Norway,100,"GCP, Python, SQL",Bachelor,18,Real Estate,2024-10-06,2024-11-20,1734,5.3,Autonomous Tech -AI12605,AI Product Manager,79948,USD,79948,MI,CT,Ireland,S,Israel,100,"Scala, Kubernetes, Computer Vision, Tableau, Docker",Bachelor,4,Healthcare,2025-02-15,2025-03-30,1869,9,AI Innovations -AI12606,AI Research Scientist,139049,CHF,125144,MI,FL,Switzerland,M,Canada,50,"Scala, Java, TensorFlow, Tableau",Master,3,Healthcare,2024-02-23,2024-04-12,1656,6.1,DeepTech Ventures -AI12607,NLP Engineer,123828,USD,123828,MI,FL,United States,L,Belgium,100,"Spark, Azure, MLOps, R, GCP",Bachelor,4,Automotive,2025-04-13,2025-05-20,1675,5.3,Quantum Computing Inc -AI12608,Research Scientist,125635,USD,125635,MI,PT,Norway,L,Norway,100,"PyTorch, Tableau, SQL, NLP",Master,4,Government,2024-07-30,2024-08-27,681,7.2,Neural Networks Co -AI12609,Data Scientist,102852,USD,102852,MI,PT,United States,S,United States,100,"Scala, Linux, Python, AWS",Associate,2,Automotive,2024-06-14,2024-07-13,1842,9.2,Smart Analytics -AI12610,Autonomous Systems Engineer,126788,EUR,107770,SE,CT,France,S,France,100,"Tableau, Computer Vision, Kubernetes, R",Bachelor,9,Government,2024-03-12,2024-04-21,1769,9,Smart Analytics -AI12611,Research Scientist,140019,GBP,105014,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, TensorFlow, Hadoop",PhD,15,Consulting,2024-04-05,2024-06-17,1104,7.8,Cloud AI Solutions -AI12612,ML Ops Engineer,225786,JPY,24836460,EX,FL,Japan,M,Japan,100,"Git, Kubernetes, Computer Vision, Python, Deep Learning",Master,13,Gaming,2024-09-03,2024-11-04,859,9.1,Algorithmic Solutions -AI12613,Principal Data Scientist,126761,EUR,107747,SE,FL,Austria,S,Austria,0,"Java, Kubernetes, Python, Computer Vision, TensorFlow",Associate,9,Energy,2024-08-23,2024-09-20,1014,8.6,DeepTech Ventures -AI12614,AI Specialist,97895,USD,97895,SE,FT,Israel,S,Israel,0,"Python, Scala, Docker, Azure, Deep Learning",Master,6,Transportation,2024-05-06,2024-06-24,1202,5.6,Neural Networks Co -AI12615,AI Architect,234625,EUR,199431,EX,PT,Netherlands,L,Norway,50,"Git, Python, NLP, TensorFlow, AWS",Bachelor,15,Healthcare,2024-09-17,2024-11-25,1955,6.4,Quantum Computing Inc -AI12616,Data Engineer,118185,GBP,88639,SE,PT,United Kingdom,M,Germany,100,"Computer Vision, Git, Hadoop, Java",Associate,8,Gaming,2025-01-17,2025-02-13,1198,9.1,Advanced Robotics -AI12617,Deep Learning Engineer,66948,USD,66948,EN,FL,Denmark,S,Denmark,100,"Deep Learning, Scala, Data Visualization",Master,0,Healthcare,2024-09-27,2024-11-26,1683,5.1,Digital Transformation LLC -AI12618,Autonomous Systems Engineer,64481,EUR,54809,EN,FL,France,S,Mexico,100,"Python, Hadoop, GCP",PhD,1,Consulting,2024-05-02,2024-05-22,1179,6.6,Future Systems -AI12619,Research Scientist,153732,CHF,138359,MI,FT,Switzerland,L,Switzerland,0,"MLOps, Spark, Scala, Java, Azure",PhD,3,Consulting,2025-03-10,2025-05-03,789,6.4,Algorithmic Solutions -AI12620,Computer Vision Engineer,130492,USD,130492,SE,FT,Ireland,S,Egypt,50,"Python, Data Visualization, Kubernetes",Associate,8,Education,2024-02-16,2024-03-26,1900,7.4,Neural Networks Co -AI12621,NLP Engineer,116529,USD,116529,MI,FT,Sweden,L,Sweden,50,"SQL, MLOps, Computer Vision, Data Visualization",Bachelor,2,Gaming,2024-12-12,2025-01-19,926,6.1,Algorithmic Solutions -AI12622,Autonomous Systems Engineer,125193,AUD,169011,SE,FT,Australia,L,Australia,100,"AWS, Java, Docker",Bachelor,6,Government,2025-03-21,2025-05-16,1239,7.8,Smart Analytics -AI12623,ML Ops Engineer,153136,EUR,130166,SE,PT,Netherlands,L,Netherlands,0,"Python, Kubernetes, Mathematics, Data Visualization, AWS",Associate,9,Media,2024-08-28,2024-11-01,1464,7.7,Advanced Robotics -AI12624,Data Analyst,174479,USD,174479,EX,FT,United States,S,United States,50,"Python, Hadoop, Linux, Tableau, Computer Vision",Bachelor,12,Government,2024-01-24,2024-03-18,2121,7.5,Machine Intelligence Group -AI12625,Machine Learning Researcher,137316,AUD,185377,SE,PT,Australia,M,Austria,50,"Deep Learning, Spark, AWS, Azure",Bachelor,8,Gaming,2024-05-04,2024-06-13,2081,9.3,DeepTech Ventures -AI12626,Deep Learning Engineer,160330,USD,160330,SE,FL,Norway,S,Norway,100,"R, Statistics, Scala, AWS, Computer Vision",Bachelor,7,Government,2024-04-05,2024-05-14,1371,5.6,TechCorp Inc -AI12627,AI Architect,41342,USD,41342,MI,FL,China,L,Denmark,100,"Python, Git, Scala, GCP, Kubernetes",Bachelor,3,Education,2025-03-18,2025-05-15,1068,6.3,DataVision Ltd -AI12628,Autonomous Systems Engineer,31869,USD,31869,EN,CT,China,S,China,100,"SQL, Linux, PyTorch, GCP, R",Associate,1,Education,2024-11-11,2025-01-20,2218,5.2,Cloud AI Solutions -AI12629,Autonomous Systems Engineer,190329,USD,190329,SE,FL,United States,L,Ghana,0,"R, Python, Docker, SQL",PhD,5,Media,2024-05-18,2024-06-04,615,8,DataVision Ltd -AI12630,Research Scientist,80831,USD,80831,EN,FT,Finland,L,Finland,50,"Git, R, MLOps",Bachelor,1,Gaming,2024-07-01,2024-07-20,1907,7.2,Cloud AI Solutions -AI12631,AI Product Manager,102054,USD,102054,SE,FT,Sweden,S,Sweden,100,"Docker, Linux, MLOps, SQL, Deep Learning",Bachelor,7,Media,2025-03-22,2025-04-19,1223,9.2,Future Systems -AI12632,Computer Vision Engineer,198047,USD,198047,EX,PT,South Korea,M,South Korea,100,"Kubernetes, Tableau, Python",Bachelor,12,Healthcare,2024-05-27,2024-07-15,1391,6.6,Predictive Systems -AI12633,NLP Engineer,70324,USD,70324,EN,CT,United States,M,United States,0,"Linux, Docker, PyTorch, Spark",Master,0,Education,2024-03-24,2024-06-02,578,9.9,Future Systems -AI12634,AI Consultant,61593,USD,61593,EN,FL,Ireland,M,Ireland,0,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-07-15,2024-08-30,2459,7.4,Smart Analytics -AI12635,NLP Engineer,225178,EUR,191401,EX,FL,Austria,M,Austria,100,"Python, Data Visualization, Tableau, Java",Master,17,Healthcare,2024-07-10,2024-08-13,1008,7.2,Algorithmic Solutions -AI12636,Machine Learning Engineer,119102,CAD,148878,SE,FL,Canada,M,Canada,50,"Statistics, Linux, Python, Java, Scala",PhD,9,Telecommunications,2025-03-13,2025-05-11,687,8.1,Smart Analytics -AI12637,AI Architect,188552,USD,188552,EX,CT,Finland,S,Finland,0,"Docker, Computer Vision, Python",Associate,10,Automotive,2025-04-16,2025-05-28,1801,7.3,Algorithmic Solutions -AI12638,Head of AI,226063,CHF,203457,SE,CT,Switzerland,L,Romania,0,"Scala, Hadoop, Deep Learning",Master,5,Technology,2025-02-23,2025-04-07,1020,5.1,DataVision Ltd -AI12639,AI Product Manager,62015,USD,62015,MI,CT,Israel,S,Israel,50,"Python, Scala, PyTorch, Statistics",PhD,3,Technology,2024-11-08,2024-12-28,1879,9.2,Cognitive Computing -AI12640,Computer Vision Engineer,93014,CAD,116268,MI,FT,Canada,M,Canada,0,"MLOps, SQL, PyTorch, Mathematics",PhD,3,Energy,2024-10-12,2024-11-05,1673,8.5,Cloud AI Solutions -AI12641,Machine Learning Researcher,128718,SGD,167333,SE,PT,Singapore,M,Singapore,50,"Mathematics, Hadoop, AWS, Statistics",Associate,7,Manufacturing,2024-12-15,2025-02-03,669,9.6,Autonomous Tech -AI12642,Data Engineer,66805,EUR,56784,EN,CT,Austria,M,Italy,0,"Spark, Git, Deep Learning, Statistics",Associate,1,Real Estate,2024-01-23,2024-02-23,554,5.2,Autonomous Tech -AI12643,ML Ops Engineer,90978,USD,90978,EN,FT,Norway,S,Norway,50,"Python, AWS, Data Visualization, Spark, MLOps",Bachelor,1,Finance,2024-06-14,2024-08-04,2462,8.6,Advanced Robotics -AI12644,Data Scientist,139567,USD,139567,SE,PT,Ireland,L,Ireland,0,"PyTorch, Azure, Docker, GCP",Associate,5,Healthcare,2024-11-17,2024-12-05,1020,9.1,Neural Networks Co -AI12645,Machine Learning Engineer,133001,USD,133001,MI,FL,Denmark,M,Denmark,100,"Git, Linux, Python",Master,3,Healthcare,2024-04-02,2024-06-01,731,7.5,Advanced Robotics -AI12646,AI Product Manager,117366,EUR,99761,SE,FT,Netherlands,S,Netherlands,100,"Statistics, TensorFlow, AWS",Bachelor,5,Retail,2025-02-07,2025-03-23,1523,8.1,Quantum Computing Inc -AI12647,Machine Learning Engineer,56948,USD,56948,EN,PT,South Korea,S,South Korea,100,"Statistics, SQL, Scala, PyTorch, Git",Associate,1,Retail,2025-04-04,2025-05-18,2302,7.3,Digital Transformation LLC -AI12648,AI Product Manager,271210,SGD,352573,EX,PT,Singapore,L,Switzerland,100,"Computer Vision, Scala, SQL, PyTorch, R",Master,11,Media,2024-06-23,2024-07-15,583,9.2,Cloud AI Solutions -AI12649,NLP Engineer,108474,EUR,92203,MI,CT,France,L,Australia,0,"Git, SQL, Tableau, Deep Learning",Master,3,Government,2024-10-09,2024-11-12,966,7.2,TechCorp Inc -AI12650,Data Engineer,74225,USD,74225,MI,PT,Ireland,M,Ireland,0,"PyTorch, Statistics, Docker, Kubernetes",Associate,2,Education,2024-08-21,2024-10-13,1353,8.7,DataVision Ltd -AI12651,AI Research Scientist,97911,CAD,122389,SE,PT,Canada,S,Canada,0,"SQL, R, Tableau, Kubernetes",Master,9,Education,2024-02-28,2024-03-31,2122,9.1,Cognitive Computing -AI12652,Deep Learning Engineer,87471,USD,87471,MI,PT,Finland,L,Finland,50,"Git, Azure, Statistics",Master,3,Technology,2024-06-05,2024-06-19,831,5.3,Digital Transformation LLC -AI12653,AI Consultant,66358,USD,66358,MI,FL,South Korea,M,Poland,0,"Kubernetes, Deep Learning, Python, Data Visualization, Mathematics",Master,3,Transportation,2024-05-18,2024-07-25,1793,8.5,Predictive Systems -AI12654,AI Research Scientist,67502,USD,67502,EN,CT,Ireland,L,Ireland,50,"Statistics, Docker, Python, Hadoop, Git",Associate,0,Healthcare,2024-01-09,2024-01-30,2491,7,Cognitive Computing -AI12655,AI Architect,84581,USD,84581,MI,FL,Ireland,M,Ireland,50,"Linux, Java, R",PhD,2,Energy,2024-10-10,2024-12-21,1998,10,Machine Intelligence Group -AI12656,Autonomous Systems Engineer,94615,USD,94615,EN,FT,United States,M,United States,0,"PyTorch, Scala, Linux",Associate,0,Consulting,2024-09-20,2024-11-27,2355,5.3,Algorithmic Solutions -AI12657,Computer Vision Engineer,126277,EUR,107335,SE,FL,Netherlands,S,Philippines,100,"Python, TensorFlow, Tableau, Azure, Statistics",Master,9,Manufacturing,2025-03-28,2025-05-13,1919,6.5,Smart Analytics -AI12658,Autonomous Systems Engineer,108046,EUR,91839,MI,FT,Netherlands,M,Netherlands,100,"Deep Learning, AWS, Hadoop",Master,4,Consulting,2024-10-22,2024-12-19,2301,9.5,Predictive Systems -AI12659,Machine Learning Researcher,214302,EUR,182157,EX,FT,Netherlands,S,Netherlands,50,"Spark, Docker, Data Visualization, NLP",Associate,16,Retail,2025-04-23,2025-05-19,1213,8.9,Predictive Systems -AI12660,Head of AI,60614,USD,60614,EN,FL,Finland,S,Portugal,100,"Linux, Docker, MLOps",PhD,0,Education,2024-02-24,2024-04-28,2024,7,Advanced Robotics -AI12661,Robotics Engineer,126247,SGD,164121,SE,FT,Singapore,S,Singapore,100,"PyTorch, Python, Docker",Master,8,Finance,2024-10-11,2024-11-08,1708,6.3,Smart Analytics -AI12662,Research Scientist,153207,USD,153207,SE,CT,Denmark,S,Denmark,0,"Python, Java, Git",Bachelor,9,Transportation,2024-11-07,2025-01-02,1270,5.6,DataVision Ltd -AI12663,NLP Engineer,91093,EUR,77429,MI,CT,Austria,M,Austria,0,"Deep Learning, Mathematics, Java, Spark, NLP",PhD,4,Technology,2024-06-13,2024-08-02,1465,7.1,Advanced Robotics -AI12664,Data Analyst,177639,USD,177639,EX,FL,Denmark,S,Denmark,100,"Deep Learning, Linux, Kubernetes",PhD,13,Real Estate,2024-11-11,2024-12-28,1835,7.9,Neural Networks Co -AI12665,AI Architect,72729,EUR,61820,EN,PT,Netherlands,M,Netherlands,50,"Docker, Kubernetes, Scala, Git, Mathematics",Bachelor,1,Real Estate,2024-08-17,2024-09-07,1687,5.5,Predictive Systems -AI12666,ML Ops Engineer,231764,EUR,196999,EX,PT,Netherlands,S,South Korea,50,"Kubernetes, Spark, Scala, Data Visualization",Master,14,Manufacturing,2024-07-28,2024-08-25,1535,7.3,Cloud AI Solutions -AI12667,Robotics Engineer,91852,USD,91852,MI,FT,Israel,M,South Korea,50,"Deep Learning, TensorFlow, Azure",Bachelor,2,Energy,2024-02-09,2024-02-27,876,6.7,Smart Analytics -AI12668,Data Scientist,108220,USD,108220,EN,CT,Denmark,L,Ukraine,50,"Tableau, Computer Vision, AWS, Git",PhD,1,Finance,2024-12-09,2025-02-12,2251,8.5,Smart Analytics -AI12669,NLP Engineer,44513,USD,44513,EN,FL,Israel,S,Israel,100,"Scala, Azure, Statistics",Master,0,Education,2024-01-27,2024-02-16,1799,6.1,Quantum Computing Inc -AI12670,Autonomous Systems Engineer,115978,USD,115978,MI,PT,Finland,L,Germany,50,"Azure, Spark, Mathematics, Java",PhD,4,Government,2024-08-19,2024-10-25,2133,8,DeepTech Ventures -AI12671,AI Architect,60623,USD,60623,EN,FT,Ireland,L,Ireland,0,"Git, Python, TensorFlow, GCP, Linux",Associate,0,Manufacturing,2024-05-10,2024-06-12,1778,8.5,AI Innovations -AI12672,Machine Learning Researcher,193676,USD,193676,SE,FT,Denmark,M,Denmark,100,"Docker, Mathematics, Python",Associate,6,Technology,2024-03-05,2024-05-13,1107,6.2,Cloud AI Solutions -AI12673,Computer Vision Engineer,101827,USD,101827,MI,CT,Norway,S,Norway,100,"Kubernetes, Git, Deep Learning, Python",Bachelor,2,Real Estate,2025-03-06,2025-05-05,1206,9.4,Autonomous Tech -AI12674,AI Consultant,90586,SGD,117762,EN,FT,Singapore,L,Hungary,0,"Statistics, AWS, Python",PhD,0,Real Estate,2024-01-22,2024-03-16,1090,5.1,Cognitive Computing -AI12675,AI Specialist,194601,CAD,243251,EX,PT,Canada,M,Canada,50,"SQL, Kubernetes, GCP",PhD,11,Transportation,2024-09-21,2024-10-16,1795,5.7,Future Systems -AI12676,Data Engineer,382222,CHF,344000,EX,FL,Switzerland,L,Thailand,50,"R, PyTorch, Java, GCP, Deep Learning",Associate,15,Government,2024-05-24,2024-08-04,674,9.9,Algorithmic Solutions -AI12677,AI Specialist,111690,CAD,139613,SE,CT,Canada,L,Canada,100,"Git, Python, Spark",Master,5,Transportation,2024-04-04,2024-05-23,1034,6.3,Future Systems -AI12678,Machine Learning Researcher,74807,EUR,63586,MI,CT,France,S,France,100,"Scala, Python, Mathematics, GCP, Linux",Bachelor,3,Automotive,2024-09-19,2024-11-05,2286,8.2,Predictive Systems -AI12679,Machine Learning Researcher,68533,AUD,92520,EN,FT,Australia,S,Colombia,100,"GCP, R, Linux, Mathematics, Java",PhD,0,Gaming,2024-08-14,2024-10-10,1038,7.9,Quantum Computing Inc -AI12680,Robotics Engineer,130226,EUR,110692,SE,CT,Netherlands,L,Netherlands,100,"PyTorch, Docker, TensorFlow, Java, AWS",Bachelor,5,Healthcare,2024-05-24,2024-06-22,513,5.1,Future Systems -AI12681,AI Specialist,112790,GBP,84593,MI,PT,United Kingdom,L,United Kingdom,50,"TensorFlow, Java, Tableau, Computer Vision, R",Associate,4,Manufacturing,2025-02-28,2025-04-25,1695,6,Cloud AI Solutions -AI12682,Data Scientist,189996,CAD,237495,EX,PT,Canada,L,France,100,"Python, Azure, Scala, Statistics, PyTorch",Associate,11,Retail,2024-12-15,2025-01-28,1151,9.4,DataVision Ltd -AI12683,AI Research Scientist,114387,USD,114387,MI,CT,Norway,M,Norway,50,"Tableau, Spark, Linux, Python",PhD,4,Media,2024-06-10,2024-07-15,640,6.5,Autonomous Tech -AI12684,Machine Learning Engineer,185728,CHF,167155,SE,FL,Switzerland,S,Switzerland,50,"Spark, Java, Scala, AWS",PhD,7,Technology,2024-01-25,2024-02-08,2147,8.7,AI Innovations -AI12685,Computer Vision Engineer,142898,EUR,121463,EX,PT,France,M,France,50,"SQL, Hadoop, Scala",PhD,16,Real Estate,2024-07-13,2024-08-14,1190,9.6,TechCorp Inc -AI12686,Autonomous Systems Engineer,84890,USD,84890,EN,FT,Finland,L,Finland,100,"Kubernetes, Python, Git",Associate,1,Retail,2024-08-01,2024-09-07,772,8.7,AI Innovations -AI12687,Machine Learning Researcher,95220,JPY,10474200,EN,CT,Japan,L,Luxembourg,0,"Scala, Spark, NLP, Tableau",Associate,1,Technology,2025-03-11,2025-04-23,536,9.8,Neural Networks Co -AI12688,Machine Learning Engineer,73529,USD,73529,EN,FT,Norway,M,Russia,0,"Linux, Data Visualization, Spark, SQL",Bachelor,0,Consulting,2024-12-10,2025-01-27,979,9,Advanced Robotics -AI12689,AI Specialist,96565,EUR,82080,MI,FT,Netherlands,S,Netherlands,100,"Python, SQL, PyTorch, Deep Learning",Bachelor,4,Technology,2025-04-05,2025-05-14,713,9.1,Quantum Computing Inc -AI12690,AI Research Scientist,81266,USD,81266,EN,PT,Israel,L,Israel,100,"GCP, Kubernetes, Java, Python, SQL",Master,1,Consulting,2024-01-20,2024-03-02,2055,7.2,Cloud AI Solutions -AI12691,Deep Learning Engineer,120489,CAD,150611,SE,FL,Canada,L,Canada,100,"GCP, Linux, R, SQL",Master,8,Retail,2024-07-17,2024-09-15,1009,9.3,TechCorp Inc -AI12692,ML Ops Engineer,160293,SGD,208381,SE,CT,Singapore,L,Chile,100,"Docker, Deep Learning, NLP, PyTorch, Scala",Associate,7,Transportation,2024-04-29,2024-07-11,2163,6.5,DataVision Ltd -AI12693,Research Scientist,259694,CAD,324618,EX,FL,Canada,L,Canada,100,"R, Deep Learning, Mathematics, Statistics",Bachelor,16,Healthcare,2025-02-20,2025-04-04,2352,6.2,TechCorp Inc -AI12694,NLP Engineer,134216,AUD,181192,SE,PT,Australia,M,Ghana,50,"Linux, Spark, MLOps, PyTorch",Associate,7,Government,2025-01-05,2025-03-15,1073,5.1,DeepTech Ventures -AI12695,Machine Learning Engineer,70756,USD,70756,MI,FL,South Korea,M,South Korea,50,"Linux, Scala, Mathematics",PhD,3,Healthcare,2024-06-09,2024-08-01,1480,8.6,DataVision Ltd -AI12696,AI Software Engineer,74648,USD,74648,MI,CT,Israel,M,Israel,50,"Scala, Tableau, R, SQL",Associate,2,Healthcare,2024-08-05,2024-09-18,581,5.5,TechCorp Inc -AI12697,Deep Learning Engineer,62208,EUR,52877,EN,FT,France,M,Singapore,100,"Java, Scala, MLOps, NLP, TensorFlow",Bachelor,0,Technology,2024-02-06,2024-04-03,1324,9.7,Cognitive Computing -AI12698,AI Research Scientist,127798,USD,127798,SE,PT,Ireland,M,Ireland,0,"Kubernetes, Scala, MLOps",Associate,6,Government,2024-12-16,2025-02-18,2486,9.1,Machine Intelligence Group -AI12699,Research Scientist,44314,USD,44314,MI,FT,China,L,China,0,"Statistics, R, Git, Computer Vision",Bachelor,3,Transportation,2024-03-22,2024-04-18,2342,5.3,Autonomous Tech -AI12700,Machine Learning Researcher,112441,USD,112441,SE,FT,Sweden,S,Sweden,100,"Scala, Azure, NLP, Deep Learning",Master,5,Finance,2025-01-16,2025-02-24,1319,9.8,Cloud AI Solutions -AI12701,AI Architect,67815,EUR,57643,EN,PT,Netherlands,S,United States,0,"Statistics, Docker, R, GCP",Associate,0,Technology,2024-01-16,2024-02-19,1170,9.4,Advanced Robotics -AI12702,AI Software Engineer,116101,USD,116101,MI,FT,Norway,L,Norway,50,"MLOps, Python, Data Visualization, NLP, TensorFlow",Master,4,Manufacturing,2024-07-11,2024-08-14,527,6.6,DeepTech Ventures -AI12703,AI Software Engineer,142224,EUR,120890,EX,PT,Germany,M,Germany,50,"Data Visualization, MLOps, R, Spark",Associate,15,Transportation,2024-08-17,2024-09-12,1792,5.2,Cloud AI Solutions -AI12704,Data Engineer,122247,USD,122247,SE,PT,United States,M,United States,50,"SQL, PyTorch, MLOps, Java, TensorFlow",Master,5,Healthcare,2024-02-18,2024-04-16,507,6.7,Algorithmic Solutions -AI12705,Data Analyst,68996,USD,68996,SE,PT,China,L,China,100,"SQL, Linux, GCP",Bachelor,5,Energy,2024-06-10,2024-07-22,1239,5.9,Cloud AI Solutions -AI12706,AI Research Scientist,58278,GBP,43709,EN,CT,United Kingdom,S,Norway,100,"TensorFlow, Kubernetes, Linux, Tableau",Associate,1,Retail,2024-08-16,2024-09-16,1495,8.6,Digital Transformation LLC -AI12707,AI Product Manager,161500,AUD,218025,SE,CT,Australia,L,Colombia,100,"Kubernetes, R, SQL",Associate,8,Technology,2024-11-14,2025-01-07,1847,8.2,TechCorp Inc -AI12708,Data Analyst,97036,USD,97036,EN,PT,Denmark,L,United Kingdom,0,"Python, NLP, Docker",PhD,0,Transportation,2024-12-20,2025-02-20,1466,6.7,Smart Analytics -AI12709,AI Product Manager,97890,USD,97890,MI,PT,Finland,L,Finland,100,"Statistics, Mathematics, Deep Learning, Linux",PhD,2,Media,2024-09-14,2024-10-07,1422,9.9,DataVision Ltd -AI12710,AI Product Manager,192865,EUR,163935,EX,CT,France,L,France,0,"SQL, Statistics, Mathematics, NLP",Associate,11,Manufacturing,2024-07-12,2024-09-07,1150,9.7,DeepTech Ventures -AI12711,Computer Vision Engineer,19662,USD,19662,EN,FL,India,M,India,0,"Linux, AWS, SQL, Data Visualization",Master,1,Manufacturing,2024-01-08,2024-02-15,2190,8.7,Algorithmic Solutions -AI12712,Research Scientist,95674,USD,95674,SE,CT,Sweden,S,Czech Republic,0,"NLP, Git, Kubernetes, Azure, AWS",PhD,7,Finance,2024-08-24,2024-09-16,855,8.1,Autonomous Tech -AI12713,Head of AI,83952,EUR,71359,EN,CT,Netherlands,L,Netherlands,50,"Statistics, R, Azure, GCP",Bachelor,1,Healthcare,2025-01-22,2025-03-12,798,8.3,Neural Networks Co -AI12714,Autonomous Systems Engineer,70247,USD,70247,EN,PT,Ireland,S,Ireland,0,"Spark, Tableau, Azure",Associate,1,Gaming,2025-02-10,2025-04-16,2099,7.3,Cloud AI Solutions -AI12715,Computer Vision Engineer,194385,GBP,145789,EX,FL,United Kingdom,S,Poland,50,"Python, Tableau, AWS, Azure",Bachelor,14,Transportation,2025-04-07,2025-05-11,1896,8.8,Autonomous Tech -AI12716,Machine Learning Researcher,50464,USD,50464,MI,FT,China,M,China,100,"NLP, Python, Kubernetes, Docker",Associate,2,Telecommunications,2024-11-11,2024-12-17,792,5.9,Neural Networks Co -AI12717,AI Architect,71270,EUR,60580,EN,FL,Netherlands,S,Netherlands,0,"GCP, Linux, MLOps",Bachelor,0,Energy,2024-03-05,2024-03-28,2402,6.4,Autonomous Tech -AI12718,AI Specialist,243177,AUD,328289,EX,FT,Australia,M,Australia,50,"Mathematics, Python, SQL",Bachelor,12,Automotive,2024-11-04,2024-11-26,1744,9.4,Cloud AI Solutions -AI12719,Data Scientist,239543,EUR,203612,EX,FL,Austria,M,India,0,"MLOps, SQL, Deep Learning, Kubernetes",Bachelor,15,Manufacturing,2025-01-08,2025-03-18,2258,6.6,Cognitive Computing -AI12720,Machine Learning Engineer,53499,USD,53499,EN,PT,South Korea,S,South Korea,0,"Data Visualization, AWS, Mathematics, Tableau, Deep Learning",Master,1,Energy,2025-04-03,2025-05-08,1026,5.8,Advanced Robotics -AI12721,Computer Vision Engineer,150607,USD,150607,EX,FT,Israel,M,Israel,50,"R, SQL, PyTorch",Associate,18,Government,2024-01-27,2024-04-08,2485,5.7,Cognitive Computing -AI12722,AI Specialist,79623,USD,79623,EN,FL,United States,L,Australia,0,"Computer Vision, Tableau, Kubernetes, Linux",Master,1,Transportation,2024-06-12,2024-08-09,1144,7.7,Autonomous Tech -AI12723,AI Architect,81308,USD,81308,EN,PT,United States,L,United States,50,"R, Python, Tableau",Associate,0,Media,2025-02-23,2025-03-09,749,6.6,Cloud AI Solutions -AI12724,Head of AI,123946,AUD,167327,SE,FT,Australia,S,Australia,100,"Tableau, Data Visualization, Mathematics",PhD,9,Government,2024-01-19,2024-03-29,2481,8.6,Digital Transformation LLC -AI12725,ML Ops Engineer,42381,USD,42381,SE,CT,India,S,Romania,0,"Python, NLP, Azure, TensorFlow",Associate,9,Retail,2025-01-24,2025-03-22,1466,5.4,Autonomous Tech -AI12726,Data Analyst,35803,USD,35803,MI,CT,China,S,China,0,"Git, TensorFlow, Python, AWS, Kubernetes",Associate,4,Education,2024-06-04,2024-07-16,2091,6.4,Algorithmic Solutions -AI12727,Data Analyst,126100,EUR,107185,SE,FT,Netherlands,L,Netherlands,50,"PyTorch, Tableau, Hadoop, Kubernetes",Bachelor,7,Government,2024-04-10,2024-05-24,2184,7.4,Digital Transformation LLC -AI12728,NLP Engineer,138184,USD,138184,SE,FT,Norway,M,Norway,100,"PyTorch, Hadoop, MLOps, Azure",Master,9,Gaming,2025-03-30,2025-04-25,516,5.2,Algorithmic Solutions -AI12729,AI Architect,38303,USD,38303,MI,FT,India,M,India,50,"Python, TensorFlow, Docker, Mathematics, Hadoop",Master,3,Telecommunications,2024-07-21,2024-08-27,1857,7.1,Neural Networks Co -AI12730,Autonomous Systems Engineer,41682,USD,41682,MI,PT,India,L,India,0,"Python, SQL, Mathematics",Bachelor,4,Manufacturing,2024-08-04,2024-10-16,2045,6.4,Algorithmic Solutions -AI12731,AI Specialist,255802,USD,255802,EX,PT,Israel,L,Romania,100,"Hadoop, Git, GCP, Computer Vision",Associate,12,Telecommunications,2024-04-20,2024-05-05,1123,9.5,Cloud AI Solutions -AI12732,Machine Learning Researcher,80108,CAD,100135,MI,PT,Canada,L,Canada,0,"Kubernetes, Docker, R, Linux, Statistics",Master,3,Telecommunications,2025-03-07,2025-04-06,1393,6.1,Quantum Computing Inc -AI12733,Autonomous Systems Engineer,60460,CAD,75575,EN,PT,Canada,M,Canada,100,"Java, Kubernetes, Data Visualization",PhD,1,Energy,2024-09-25,2024-12-03,1853,10,DataVision Ltd -AI12734,Principal Data Scientist,110481,USD,110481,SE,PT,Sweden,S,Sweden,100,"Kubernetes, Hadoop, Data Visualization, Scala, Java",Bachelor,6,Technology,2024-01-30,2024-03-10,1762,9.4,Digital Transformation LLC -AI12735,AI Research Scientist,181707,EUR,154451,EX,PT,Germany,L,Germany,50,"MLOps, Linux, Hadoop",Bachelor,17,Automotive,2024-07-29,2024-08-19,500,9.7,Autonomous Tech -AI12736,AI Architect,171315,CAD,214144,EX,CT,Canada,S,Colombia,100,"SQL, Java, PyTorch",Bachelor,18,Consulting,2025-01-14,2025-02-22,2115,6,AI Innovations -AI12737,Machine Learning Researcher,186907,EUR,158871,EX,PT,France,S,France,0,"NLP, Hadoop, SQL, Statistics, R",Master,12,Real Estate,2025-04-10,2025-05-12,952,9.4,Cloud AI Solutions -AI12738,Computer Vision Engineer,197246,GBP,147935,EX,FL,United Kingdom,S,United Kingdom,50,"SQL, TensorFlow, Linux, Java",PhD,12,Technology,2024-12-10,2024-12-31,2123,6.2,Future Systems -AI12739,AI Research Scientist,62903,AUD,84919,EN,FL,Australia,M,Australia,0,"Python, Tableau, Scala",Bachelor,0,Media,2024-10-09,2024-12-06,834,6.6,Autonomous Tech -AI12740,Robotics Engineer,168184,CAD,210230,EX,PT,Canada,L,Canada,0,"Hadoop, Mathematics, Spark, Computer Vision, Python",Bachelor,10,Finance,2024-04-05,2024-05-31,2000,5.3,Smart Analytics -AI12741,AI Software Engineer,147859,CAD,184824,EX,FL,Canada,M,Germany,100,"SQL, Tableau, Statistics, Linux, Mathematics",Master,10,Gaming,2024-11-02,2025-01-09,858,8.9,Neural Networks Co -AI12742,Machine Learning Researcher,87226,EUR,74142,MI,FT,Netherlands,S,Romania,50,"Azure, R, SQL, AWS",PhD,2,Education,2024-08-09,2024-09-21,1357,5.7,Predictive Systems -AI12743,Machine Learning Engineer,138319,EUR,117571,SE,FL,France,L,France,0,"Computer Vision, Python, TensorFlow",PhD,9,Manufacturing,2024-11-03,2025-01-06,824,9.1,Future Systems -AI12744,Autonomous Systems Engineer,103507,GBP,77630,MI,CT,United Kingdom,M,Luxembourg,0,"Azure, Data Visualization, Python",PhD,4,Media,2024-04-16,2024-05-29,2078,8,Advanced Robotics -AI12745,Data Engineer,223904,EUR,190318,EX,FT,France,M,France,100,"Azure, PyTorch, Hadoop, Kubernetes, Spark",Associate,11,Transportation,2024-04-12,2024-05-29,581,6.1,Neural Networks Co -AI12746,ML Ops Engineer,142980,USD,142980,EX,FL,Finland,M,Austria,100,"R, SQL, Scala, AWS",Bachelor,15,Telecommunications,2024-10-10,2024-11-15,1600,7.9,DataVision Ltd -AI12747,Head of AI,64103,EUR,54488,EN,FL,Austria,M,Austria,100,"Scala, NLP, Java, GCP, Azure",Master,1,Technology,2025-01-14,2025-02-12,1817,6,Algorithmic Solutions -AI12748,Autonomous Systems Engineer,91062,EUR,77403,MI,PT,Austria,S,Austria,100,"Statistics, PyTorch, Spark, Git, Data Visualization",Master,4,Healthcare,2024-02-14,2024-04-27,1057,9.1,DataVision Ltd -AI12749,Robotics Engineer,78579,EUR,66792,EN,CT,Netherlands,L,Germany,100,"Python, Azure, Scala, Tableau",Bachelor,1,Telecommunications,2024-04-29,2024-05-16,1050,5,Advanced Robotics -AI12750,Deep Learning Engineer,115061,EUR,97802,MI,FL,France,L,France,50,"Linux, Java, R, Mathematics, Kubernetes",Bachelor,4,Manufacturing,2024-02-20,2024-03-05,1225,8.8,Cognitive Computing -AI12751,AI Software Engineer,61569,SGD,80040,EN,PT,Singapore,S,Colombia,0,"Azure, NLP, GCP, Java, Mathematics",PhD,0,Retail,2025-03-05,2025-05-06,1412,5.4,Machine Intelligence Group -AI12752,Principal Data Scientist,106803,SGD,138844,SE,CT,Singapore,S,Singapore,100,"Mathematics, Spark, Java, PyTorch",Associate,7,Finance,2024-09-24,2024-10-27,2223,7.5,Neural Networks Co -AI12753,Data Scientist,88775,USD,88775,MI,FT,Ireland,M,Ireland,50,"Python, Scala, NLP, Kubernetes, TensorFlow",Bachelor,4,Manufacturing,2024-07-23,2024-08-08,677,9.9,Cognitive Computing -AI12754,Principal Data Scientist,143329,CAD,179161,EX,FT,Canada,M,Indonesia,100,"Kubernetes, SQL, PyTorch",Associate,16,Consulting,2024-12-06,2025-01-24,1069,8,Machine Intelligence Group -AI12755,Machine Learning Researcher,83311,CHF,74980,EN,CT,Switzerland,S,China,50,"Git, Mathematics, SQL, PyTorch, Azure",Bachelor,0,Consulting,2025-02-01,2025-02-22,1003,8.6,Algorithmic Solutions -AI12756,Machine Learning Engineer,200496,GBP,150372,EX,FT,United Kingdom,S,United Kingdom,50,"R, Java, Computer Vision, Kubernetes",Associate,18,Finance,2024-04-07,2024-05-03,2129,5.8,Future Systems -AI12757,Principal Data Scientist,60235,SGD,78306,EN,CT,Singapore,S,Singapore,100,"Spark, SQL, R, Scala",Master,1,Media,2024-10-15,2024-12-08,963,6.9,Future Systems -AI12758,Head of AI,74675,USD,74675,EN,FT,Sweden,L,Netherlands,50,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-10-02,2024-11-06,1444,5.8,Cloud AI Solutions -AI12759,AI Consultant,61377,EUR,52170,EN,FT,Austria,S,Austria,100,"SQL, NLP, Spark, MLOps",Associate,1,Transportation,2024-08-06,2024-10-02,1373,6.2,AI Innovations -AI12760,AI Specialist,23390,USD,23390,MI,PT,India,S,India,100,"Linux, R, SQL, Data Visualization, NLP",Associate,2,Telecommunications,2025-02-05,2025-03-01,882,7,TechCorp Inc -AI12761,Machine Learning Researcher,91528,EUR,77799,EN,CT,Netherlands,L,Netherlands,100,"Spark, Python, R, Linux",Master,1,Real Estate,2024-08-22,2024-09-25,2097,7.1,DataVision Ltd -AI12762,Robotics Engineer,146429,USD,146429,SE,PT,Denmark,S,Portugal,50,"Docker, AWS, Tableau, Computer Vision, Kubernetes",Associate,6,Retail,2025-02-08,2025-03-12,1796,5.6,DeepTech Ventures -AI12763,Machine Learning Engineer,44242,USD,44242,SE,FT,India,L,New Zealand,50,"Python, Hadoop, AWS, Statistics",Associate,6,Telecommunications,2025-01-07,2025-01-25,1911,6.5,Quantum Computing Inc -AI12764,Principal Data Scientist,141895,USD,141895,MI,PT,United States,L,United States,50,"Statistics, MLOps, Python",PhD,4,Finance,2025-04-15,2025-06-22,1539,6.5,DataVision Ltd -AI12765,Head of AI,172701,EUR,146796,EX,FT,France,L,Estonia,100,"TensorFlow, Git, Computer Vision, Tableau",Bachelor,16,Media,2024-11-21,2024-12-13,1649,6.9,Machine Intelligence Group -AI12766,AI Research Scientist,122947,JPY,13524170,SE,CT,Japan,S,Switzerland,50,"GCP, Git, Statistics",Master,6,Education,2024-11-02,2024-12-17,1589,8.2,Future Systems -AI12767,Data Analyst,76332,EUR,64882,EN,PT,Netherlands,M,Japan,50,"Java, Docker, PyTorch, Computer Vision, Azure",PhD,1,Energy,2024-09-19,2024-11-09,572,5.1,Predictive Systems -AI12768,ML Ops Engineer,165380,EUR,140573,EX,PT,Austria,S,China,100,"Kubernetes, NLP, GCP, Computer Vision",Associate,17,Education,2024-11-17,2024-12-18,551,5.7,Smart Analytics -AI12769,Head of AI,142751,EUR,121338,EX,FT,Austria,M,Austria,0,"Data Visualization, PyTorch, Tableau, Kubernetes",Bachelor,15,Technology,2024-06-24,2024-08-10,848,9.7,Algorithmic Solutions -AI12770,AI Architect,62156,USD,62156,EX,FL,India,M,India,100,"Java, R, NLP, Computer Vision, Kubernetes",Bachelor,14,Gaming,2024-10-21,2024-12-30,539,5.8,Smart Analytics -AI12771,AI Product Manager,152270,USD,152270,SE,FT,United States,M,United States,50,"Linux, AWS, Data Visualization",Associate,5,Media,2025-03-15,2025-04-17,1162,7.3,Autonomous Tech -AI12772,AI Software Engineer,86405,EUR,73444,MI,CT,Netherlands,M,Denmark,0,"NLP, Mathematics, SQL",Master,2,Automotive,2024-06-04,2024-06-27,1890,10,Cloud AI Solutions -AI12773,Machine Learning Engineer,82630,JPY,9089300,MI,FL,Japan,M,Japan,50,"Python, GCP, Data Visualization",PhD,3,Government,2024-10-04,2024-11-27,1829,7.5,Autonomous Tech -AI12774,AI Specialist,57873,USD,57873,EX,CT,China,S,Malaysia,100,"AWS, Azure, Mathematics",Associate,13,Telecommunications,2024-06-07,2024-07-12,1519,6.3,Digital Transformation LLC -AI12775,Robotics Engineer,28348,USD,28348,EN,FL,India,M,India,0,"Statistics, Spark, Python, Computer Vision, Git",PhD,0,Technology,2024-09-22,2024-11-17,723,8.3,Cognitive Computing -AI12776,Computer Vision Engineer,87180,SGD,113334,MI,FT,Singapore,M,Czech Republic,100,"Linux, Data Visualization, GCP, TensorFlow",PhD,2,Consulting,2024-07-15,2024-09-09,1059,9.7,Cloud AI Solutions -AI12777,Head of AI,91044,GBP,68283,EN,PT,United Kingdom,L,United Kingdom,0,"R, PyTorch, Spark, Git, SQL",Master,0,Retail,2025-03-04,2025-04-03,596,5.4,Digital Transformation LLC -AI12778,NLP Engineer,76331,USD,76331,MI,FT,South Korea,L,South Korea,100,"GCP, Kubernetes, Mathematics, Python",PhD,4,Retail,2025-02-17,2025-03-29,1303,5.6,Digital Transformation LLC -AI12779,Robotics Engineer,118613,EUR,100821,SE,CT,France,L,France,0,"Linux, AWS, Deep Learning",Bachelor,8,Telecommunications,2025-01-19,2025-03-09,615,5.2,DataVision Ltd -AI12780,Machine Learning Researcher,92441,GBP,69331,EN,FL,United Kingdom,L,United Kingdom,50,"R, Computer Vision, Linux, Hadoop, SQL",Associate,0,Retail,2024-01-28,2024-03-27,1260,8.2,Advanced Robotics -AI12781,Data Analyst,268946,CHF,242051,EX,CT,Switzerland,M,Switzerland,50,"Data Visualization, Linux, R, Tableau, NLP",Associate,11,Gaming,2024-05-10,2024-07-03,1285,6.6,Quantum Computing Inc -AI12782,Robotics Engineer,32200,USD,32200,EN,FT,China,S,Estonia,100,"SQL, Git, Azure",Bachelor,1,Finance,2024-10-15,2024-12-11,1756,8.6,AI Innovations -AI12783,Robotics Engineer,138675,GBP,104006,SE,FL,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes",PhD,8,Energy,2024-12-09,2025-02-01,1248,8.5,TechCorp Inc -AI12784,Robotics Engineer,68778,EUR,58461,EN,PT,Germany,L,Germany,100,"TensorFlow, Scala, PyTorch, MLOps",PhD,0,Automotive,2025-02-04,2025-03-16,693,6.4,Future Systems -AI12785,Machine Learning Engineer,209006,CHF,188105,SE,CT,Switzerland,M,Switzerland,100,"PyTorch, Python, NLP, Azure",Associate,9,Transportation,2024-06-10,2024-07-04,2219,8.9,Smart Analytics -AI12786,Machine Learning Engineer,131992,CAD,164990,EX,PT,Canada,M,Canada,0,"Python, NLP, Linux, MLOps, AWS",Associate,15,Gaming,2024-09-22,2024-11-16,1295,6.1,Cognitive Computing -AI12787,Data Engineer,94712,USD,94712,MI,FL,Sweden,L,Sweden,50,"Mathematics, PyTorch, Tableau",PhD,2,Technology,2024-03-28,2024-06-07,1216,8.4,Advanced Robotics -AI12788,NLP Engineer,134256,USD,134256,SE,FL,Sweden,S,Sweden,100,"Kubernetes, TensorFlow, GCP",PhD,5,Media,2025-04-24,2025-06-26,1279,7.7,AI Innovations -AI12789,Deep Learning Engineer,103820,USD,103820,MI,PT,Israel,M,Israel,50,"Python, Tableau, Statistics, TensorFlow, Spark",Bachelor,2,Real Estate,2025-03-01,2025-04-10,1980,6.8,Smart Analytics -AI12790,Research Scientist,90645,USD,90645,MI,PT,United States,M,Portugal,0,"PyTorch, Statistics, Kubernetes, NLP",Master,3,Media,2024-05-09,2024-07-02,585,8.9,Smart Analytics -AI12791,ML Ops Engineer,119424,USD,119424,MI,PT,Finland,L,Canada,100,"SQL, Deep Learning, AWS, PyTorch, Spark",PhD,2,Retail,2024-11-11,2024-12-03,2449,5.3,DeepTech Ventures -AI12792,AI Specialist,100887,USD,100887,MI,FL,Ireland,M,Ireland,100,"Git, GCP, Scala, Linux, PyTorch",Master,3,Manufacturing,2024-07-28,2024-09-22,2297,6.9,Quantum Computing Inc -AI12793,NLP Engineer,99370,USD,99370,EX,FT,China,S,China,0,"Python, Java, AWS",PhD,19,Education,2024-04-06,2024-05-03,1851,7.8,Advanced Robotics -AI12794,Deep Learning Engineer,136900,AUD,184815,EX,FT,Australia,M,Australia,100,"MLOps, Kubernetes, Scala",PhD,19,Finance,2024-11-07,2025-01-14,2396,7.5,Cognitive Computing -AI12795,Autonomous Systems Engineer,46438,USD,46438,EN,PT,South Korea,M,South Korea,0,"Kubernetes, SQL, Hadoop, GCP, Computer Vision",Bachelor,1,Manufacturing,2024-02-01,2024-03-09,2305,5.7,Predictive Systems -AI12796,Machine Learning Engineer,49841,USD,49841,MI,FL,China,M,China,0,"Scala, Git, Spark, SQL, Data Visualization",Associate,2,Gaming,2024-07-09,2024-08-19,2197,8.9,DataVision Ltd -AI12797,AI Research Scientist,87830,USD,87830,EX,FL,China,M,China,0,"Spark, Statistics, Python, Docker, Scala",Associate,12,Education,2024-04-02,2024-06-02,2416,9.3,Neural Networks Co -AI12798,Autonomous Systems Engineer,78608,EUR,66817,MI,CT,Austria,M,Austria,0,"R, Scala, TensorFlow, Java",PhD,3,Education,2024-02-26,2024-03-20,2454,5.2,TechCorp Inc -AI12799,Principal Data Scientist,76299,USD,76299,EN,FL,South Korea,L,Estonia,100,"Scala, Java, GCP",Master,0,Media,2024-07-24,2024-09-17,1410,6.9,TechCorp Inc -AI12800,Machine Learning Engineer,70823,USD,70823,MI,FT,Sweden,S,Sweden,100,"SQL, Hadoop, Git",Master,2,Transportation,2024-04-28,2024-06-09,1116,9,Neural Networks Co -AI12801,Head of AI,161626,USD,161626,SE,PT,Norway,L,Norway,50,"PyTorch, SQL, TensorFlow, Python, Deep Learning",Bachelor,7,Finance,2024-11-10,2024-12-06,2400,5.1,Quantum Computing Inc -AI12802,AI Specialist,94357,GBP,70768,MI,PT,United Kingdom,L,United Kingdom,0,"Scala, Spark, Mathematics, Git",PhD,3,Energy,2024-01-11,2024-03-21,1784,8.3,Future Systems -AI12803,AI Architect,154775,USD,154775,EX,CT,Sweden,M,Sweden,50,"Python, Hadoop, Mathematics",Master,15,Telecommunications,2024-04-16,2024-05-30,2227,8.8,Predictive Systems -AI12804,AI Software Engineer,81393,EUR,69184,MI,PT,France,M,France,100,"Deep Learning, SQL, Azure",Associate,4,Consulting,2025-02-09,2025-03-25,1445,6.4,DeepTech Ventures -AI12805,AI Software Engineer,64623,USD,64623,EN,PT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",Master,1,Energy,2024-06-21,2024-08-28,1928,5.5,DeepTech Ventures -AI12806,Autonomous Systems Engineer,53147,USD,53147,EN,CT,Finland,S,Egypt,100,"AWS, Python, Statistics, Tableau, Hadoop",PhD,1,Technology,2024-08-03,2024-10-07,1518,6.8,DeepTech Ventures -AI12807,Data Scientist,95590,USD,95590,SE,PT,Israel,S,Israel,100,"MLOps, AWS, GCP, NLP, Azure",Bachelor,5,Telecommunications,2024-07-03,2024-08-05,1154,6,Machine Intelligence Group -AI12808,Robotics Engineer,72897,USD,72897,EN,CT,Norway,S,Norway,0,"Spark, MLOps, Kubernetes, Linux, TensorFlow",Associate,1,Telecommunications,2024-06-07,2024-07-16,2207,6.8,Neural Networks Co -AI12809,AI Consultant,150728,USD,150728,EX,PT,United States,S,India,100,"Docker, Java, Statistics, SQL, Hadoop",Associate,14,Government,2024-08-13,2024-09-23,2349,8.2,Cognitive Computing -AI12810,ML Ops Engineer,117055,USD,117055,MI,CT,Norway,M,Norway,100,"Git, Docker, Python, Tableau, Azure",PhD,4,Manufacturing,2024-10-09,2024-12-19,794,5.6,Algorithmic Solutions -AI12811,Machine Learning Researcher,87825,EUR,74651,MI,FL,Austria,M,Austria,50,"SQL, Hadoop, TensorFlow, AWS",Bachelor,2,Media,2024-01-07,2024-02-23,2030,9.6,Algorithmic Solutions -AI12812,Data Analyst,199854,AUD,269803,EX,PT,Australia,S,United States,100,"Tableau, Hadoop, SQL, Data Visualization",Bachelor,13,Media,2024-08-28,2024-10-20,1378,6.7,Quantum Computing Inc -AI12813,Deep Learning Engineer,159183,EUR,135306,SE,FL,Netherlands,L,Netherlands,0,"Docker, Python, Tableau",Master,6,Transportation,2024-11-30,2025-01-19,1835,8,Digital Transformation LLC -AI12814,AI Specialist,64547,GBP,48410,EN,PT,United Kingdom,S,United Kingdom,100,"TensorFlow, SQL, Deep Learning, Docker, NLP",Master,0,Energy,2024-08-12,2024-10-21,666,5.8,Autonomous Tech -AI12815,Data Analyst,95432,CHF,85889,EN,FL,Switzerland,S,Switzerland,100,"Linux, SQL, Azure, Hadoop",Associate,0,Education,2024-08-22,2024-10-27,2451,7.1,Cloud AI Solutions -AI12816,AI Research Scientist,38213,USD,38213,MI,FT,India,M,India,50,"Hadoop, Python, Java",Master,2,Finance,2024-10-09,2024-11-24,2359,5.3,Cloud AI Solutions -AI12817,Computer Vision Engineer,122719,USD,122719,SE,PT,Finland,L,Finland,0,"Python, Data Visualization, Kubernetes, Docker, Linux",Bachelor,7,Gaming,2024-09-18,2024-11-22,1724,7.1,DeepTech Ventures -AI12818,Computer Vision Engineer,126604,CHF,113944,MI,PT,Switzerland,L,Switzerland,0,"AWS, Spark, Statistics, SQL, R",Associate,2,Consulting,2024-10-26,2024-11-29,605,8.4,Neural Networks Co -AI12819,Autonomous Systems Engineer,27641,USD,27641,MI,FT,India,S,India,50,"Git, TensorFlow, AWS",PhD,3,Education,2024-05-21,2024-07-16,1784,7.8,Predictive Systems -AI12820,Data Analyst,106504,USD,106504,EN,CT,Denmark,L,Denmark,0,"TensorFlow, Git, Statistics, Tableau, MLOps",Master,1,Finance,2025-04-29,2025-07-02,2091,8.6,TechCorp Inc -AI12821,AI Product Manager,211310,EUR,179614,EX,PT,Netherlands,M,Netherlands,50,"Git, NLP, AWS, Hadoop",Associate,13,Energy,2024-11-07,2024-11-24,1971,6.2,DeepTech Ventures -AI12822,Autonomous Systems Engineer,55929,USD,55929,MI,CT,China,L,China,0,"Java, Linux, Python, GCP",Associate,3,Telecommunications,2024-03-26,2024-05-25,2125,8.5,Cognitive Computing -AI12823,Principal Data Scientist,189125,GBP,141844,EX,FT,United Kingdom,L,Singapore,0,"AWS, PyTorch, Java, TensorFlow, Statistics",Master,16,Education,2024-06-21,2024-07-30,2004,5.9,TechCorp Inc -AI12824,AI Product Manager,232230,JPY,25545300,EX,FT,Japan,L,Japan,50,"Scala, Docker, Linux, Azure",PhD,14,Consulting,2024-02-10,2024-03-25,719,7.2,Cloud AI Solutions -AI12825,AI Architect,92533,AUD,124920,MI,FT,Australia,M,Australia,100,"Kubernetes, SQL, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-30,1982,5.1,Advanced Robotics -AI12826,Head of AI,170727,USD,170727,EX,CT,South Korea,S,France,0,"TensorFlow, Java, Computer Vision",Associate,15,Real Estate,2024-09-04,2024-11-03,829,5.8,DeepTech Ventures -AI12827,Machine Learning Researcher,64528,USD,64528,EN,CT,Finland,M,Finland,0,"Git, Java, Statistics",Bachelor,0,Consulting,2025-03-14,2025-04-02,1203,9.1,Quantum Computing Inc -AI12828,Robotics Engineer,86994,GBP,65246,EN,PT,United Kingdom,L,Malaysia,50,"Azure, AWS, GCP, Linux",Master,1,Automotive,2025-04-13,2025-05-02,1858,8.6,Cloud AI Solutions -AI12829,AI Architect,195324,USD,195324,EX,FL,Israel,L,Canada,50,"GCP, Spark, SQL, PyTorch, Computer Vision",Master,11,Technology,2024-06-13,2024-07-28,511,9.3,Digital Transformation LLC -AI12830,AI Architect,107212,EUR,91130,SE,CT,Netherlands,S,Germany,50,"Docker, Java, Mathematics",Associate,9,Education,2025-04-30,2025-05-28,1555,7.1,DataVision Ltd -AI12831,Data Scientist,63595,USD,63595,EN,CT,Ireland,M,Ireland,50,"Scala, Python, TensorFlow, Mathematics",Bachelor,0,Gaming,2024-01-14,2024-03-16,2066,7.9,Algorithmic Solutions -AI12832,Data Engineer,146168,USD,146168,SE,PT,United States,M,United States,50,"Tableau, Java, Azure, SQL, PyTorch",Associate,7,Media,2025-04-18,2025-05-15,1733,8.2,Smart Analytics -AI12833,AI Product Manager,23158,USD,23158,EN,FT,China,S,China,0,"Git, NLP, SQL",Master,1,Government,2024-03-17,2024-04-18,1055,8.3,Digital Transformation LLC -AI12834,Data Engineer,74146,EUR,63024,EN,FT,Austria,M,Austria,0,"Linux, Tableau, Git, R, Statistics",Bachelor,1,Media,2024-11-16,2024-12-24,2186,9.8,Future Systems -AI12835,NLP Engineer,244490,SGD,317837,EX,FL,Singapore,M,Vietnam,50,"Python, TensorFlow, AWS, Scala, PyTorch",Master,16,Consulting,2024-08-20,2024-09-05,1520,7.4,DeepTech Ventures -AI12836,Data Analyst,135650,USD,135650,MI,FT,United States,L,Czech Republic,0,"Scala, Azure, PyTorch, Deep Learning, Tableau",Master,2,Technology,2025-02-25,2025-03-23,1602,6.2,Machine Intelligence Group -AI12837,AI Product Manager,161057,EUR,136898,SE,PT,France,L,France,0,"Deep Learning, NLP, MLOps, Scala, TensorFlow",Associate,8,Retail,2025-02-26,2025-04-30,873,5.7,Future Systems -AI12838,AI Research Scientist,95999,SGD,124799,MI,FL,Singapore,L,Australia,50,"SQL, R, MLOps, NLP",Associate,4,Transportation,2024-03-27,2024-06-02,897,5.7,AI Innovations -AI12839,Autonomous Systems Engineer,75071,USD,75071,EN,CT,Sweden,L,Sweden,50,"Tableau, TensorFlow, PyTorch",Associate,0,Manufacturing,2025-04-25,2025-06-11,2289,8,Cloud AI Solutions -AI12840,AI Research Scientist,80156,USD,80156,EN,CT,Sweden,L,Sweden,100,"Scala, SQL, MLOps",Bachelor,0,Manufacturing,2024-04-21,2024-06-27,2425,5.1,Algorithmic Solutions -AI12841,NLP Engineer,77757,CHF,69981,EN,FL,Switzerland,M,Switzerland,0,"SQL, Kubernetes, TensorFlow, Git",PhD,0,Media,2024-01-07,2024-03-20,964,8.7,AI Innovations -AI12842,Machine Learning Engineer,56236,USD,56236,EN,PT,South Korea,M,South Korea,50,"Python, R, Data Visualization, Java, MLOps",Bachelor,1,Consulting,2025-03-15,2025-05-07,2054,9.7,Machine Intelligence Group -AI12843,Computer Vision Engineer,240245,JPY,26426950,EX,CT,Japan,M,Japan,100,"Scala, Java, R, Computer Vision, Git",PhD,14,Technology,2025-01-31,2025-04-01,1258,8.5,Future Systems -AI12844,Data Analyst,275028,USD,275028,EX,PT,Ireland,L,Ireland,100,"Deep Learning, Azure, GCP",Master,12,Manufacturing,2024-02-22,2024-04-02,1031,6.5,Digital Transformation LLC -AI12845,AI Consultant,186213,EUR,158281,EX,CT,Austria,L,Austria,100,"Data Visualization, Linux, SQL, Deep Learning",Bachelor,18,Media,2024-01-25,2024-03-19,2022,7.2,Algorithmic Solutions -AI12846,Data Engineer,287124,USD,287124,EX,FT,Norway,S,Norway,50,"Linux, Tableau, Hadoop, Computer Vision",Bachelor,15,Transportation,2025-02-11,2025-04-13,2175,6.8,Digital Transformation LLC -AI12847,Data Scientist,135404,CHF,121864,MI,PT,Switzerland,M,Switzerland,100,"SQL, Kubernetes, Tableau, Linux",Master,3,Transportation,2025-02-14,2025-04-05,2281,8.1,Quantum Computing Inc -AI12848,Principal Data Scientist,159276,EUR,135385,SE,PT,France,L,France,50,"Hadoop, Docker, Kubernetes, MLOps",PhD,8,Consulting,2024-11-12,2025-01-08,673,8.6,AI Innovations -AI12849,Data Engineer,93350,USD,93350,SE,FL,Sweden,S,Sweden,100,"Linux, Data Visualization, Python",Associate,8,Government,2025-01-28,2025-04-02,533,6.7,AI Innovations -AI12850,AI Product Manager,264276,USD,264276,EX,PT,Ireland,L,Nigeria,50,"Java, SQL, Deep Learning, Hadoop, Spark",Associate,10,Consulting,2025-01-09,2025-02-28,2452,7.7,Machine Intelligence Group -AI12851,ML Ops Engineer,31006,USD,31006,MI,CT,India,S,India,50,"Deep Learning, Python, AWS, Tableau, Spark",Bachelor,4,Manufacturing,2025-04-17,2025-05-19,1090,7.9,Advanced Robotics -AI12852,AI Architect,132059,USD,132059,SE,FT,Israel,M,Israel,50,"Spark, SQL, MLOps",PhD,8,Automotive,2025-01-23,2025-02-12,1688,7,Cloud AI Solutions -AI12853,NLP Engineer,85658,AUD,115638,MI,FL,Australia,L,Japan,50,"Python, NLP, Computer Vision, Git",Bachelor,2,Manufacturing,2024-04-03,2024-05-21,1069,8.1,Neural Networks Co -AI12854,Data Scientist,107273,EUR,91182,SE,PT,Germany,S,Germany,0,"Python, Git, Hadoop",Bachelor,6,Government,2024-07-11,2024-08-21,1704,8.7,Algorithmic Solutions -AI12855,Data Scientist,120446,EUR,102379,SE,CT,Netherlands,S,Netherlands,0,"Linux, Java, Git, Tableau",Bachelor,7,Manufacturing,2024-02-22,2024-04-23,1512,5.8,Future Systems -AI12856,Principal Data Scientist,92064,USD,92064,MI,FL,Israel,L,Israel,100,"Python, GCP, Computer Vision, TensorFlow",Bachelor,2,Real Estate,2025-04-30,2025-05-29,779,7.7,AI Innovations -AI12857,ML Ops Engineer,170651,USD,170651,EX,PT,Finland,S,Brazil,100,"AWS, Azure, Python, TensorFlow",Associate,17,Gaming,2024-05-08,2024-05-29,1131,8.1,DeepTech Ventures -AI12858,Principal Data Scientist,209732,USD,209732,EX,FL,United States,L,United States,0,"Python, Docker, Data Visualization, Azure",PhD,13,Healthcare,2024-09-09,2024-10-09,1392,8.9,Autonomous Tech -AI12859,Data Scientist,90595,EUR,77006,MI,FL,France,M,France,100,"Data Visualization, Docker, Tableau, SQL",Bachelor,2,Retail,2025-04-17,2025-05-23,1909,9.4,Cognitive Computing -AI12860,ML Ops Engineer,134103,GBP,100577,SE,PT,United Kingdom,L,United Kingdom,0,"GCP, Spark, Tableau",Associate,6,Telecommunications,2024-09-05,2024-10-15,2247,5.8,Predictive Systems -AI12861,AI Software Engineer,328767,USD,328767,EX,CT,Norway,M,Norway,50,"Git, Mathematics, Deep Learning, PyTorch",PhD,14,Gaming,2024-03-27,2024-04-23,813,8.1,TechCorp Inc -AI12862,Head of AI,201006,USD,201006,EX,CT,Israel,M,Denmark,0,"TensorFlow, Python, Docker",PhD,14,Transportation,2025-02-28,2025-04-20,999,5.7,DataVision Ltd -AI12863,Research Scientist,127726,JPY,14049860,SE,PT,Japan,S,Japan,50,"Mathematics, AWS, PyTorch, Deep Learning, Java",PhD,8,Gaming,2025-04-10,2025-04-30,742,6.3,Predictive Systems -AI12864,Computer Vision Engineer,269096,USD,269096,EX,FL,United States,L,United States,50,"TensorFlow, MLOps, Tableau",Associate,17,Education,2024-10-04,2024-11-24,1224,7.5,Cognitive Computing -AI12865,Data Engineer,149753,EUR,127290,SE,FT,Austria,L,China,100,"GCP, Spark, Scala, Data Visualization, Python",Master,7,Education,2024-11-28,2025-01-08,637,5.5,Future Systems -AI12866,ML Ops Engineer,145711,SGD,189424,SE,PT,Singapore,M,Singapore,100,"Scala, Docker, Statistics, Deep Learning, Computer Vision",Bachelor,5,Real Estate,2025-02-18,2025-04-01,2320,9.4,Predictive Systems -AI12867,AI Consultant,20533,USD,20533,EN,FT,India,S,India,100,"Scala, Kubernetes, Hadoop",Associate,0,Technology,2025-01-16,2025-02-02,1142,9.7,Future Systems -AI12868,NLP Engineer,80896,USD,80896,EN,CT,United States,L,United States,0,"Python, TensorFlow, Azure, Java, Tableau",PhD,0,Telecommunications,2024-02-09,2024-04-07,1088,6.5,Digital Transformation LLC -AI12869,Autonomous Systems Engineer,128356,EUR,109103,SE,FT,Netherlands,L,Netherlands,0,"NLP, TensorFlow, R, Computer Vision, Scala",Bachelor,5,Consulting,2024-12-27,2025-02-25,520,9.3,Cloud AI Solutions -AI12870,Data Engineer,118886,USD,118886,SE,FL,United States,S,Kenya,50,"Java, MLOps, Computer Vision, AWS, Azure",PhD,7,Education,2024-03-06,2024-03-26,1504,8.8,Future Systems -AI12871,AI Architect,115314,USD,115314,MI,FT,Denmark,S,Denmark,100,"Linux, Python, NLP, Git",Associate,2,Consulting,2024-11-16,2024-12-24,777,6,Quantum Computing Inc -AI12872,Data Scientist,132602,CHF,119342,MI,CT,Switzerland,S,Switzerland,100,"Python, Spark, Deep Learning",PhD,2,Consulting,2024-07-23,2024-08-12,2381,9.1,Advanced Robotics -AI12873,AI Software Engineer,145255,GBP,108941,EX,CT,United Kingdom,S,United Kingdom,50,"MLOps, Mathematics, Docker, PyTorch, TensorFlow",Associate,17,Automotive,2024-10-21,2024-11-20,2468,5.5,Cloud AI Solutions -AI12874,ML Ops Engineer,139099,USD,139099,SE,PT,South Korea,L,South Korea,0,"Spark, Azure, Data Visualization, GCP",Bachelor,8,Transportation,2025-03-16,2025-04-18,2132,7.1,Machine Intelligence Group -AI12875,AI Architect,112407,CHF,101166,MI,FL,Switzerland,M,Netherlands,100,"Hadoop, NLP, Tableau",Bachelor,3,Government,2025-01-10,2025-02-26,1032,8,Advanced Robotics -AI12876,Data Scientist,113716,USD,113716,MI,FL,Ireland,L,Ireland,100,"PyTorch, GCP, Statistics",Associate,4,Real Estate,2024-11-24,2024-12-16,2045,5.2,Machine Intelligence Group -AI12877,Data Scientist,45202,USD,45202,EN,FT,South Korea,S,South Korea,50,"Tableau, Java, Kubernetes, Azure, Scala",Master,0,Education,2024-02-17,2024-03-13,1242,6.1,Cloud AI Solutions -AI12878,Autonomous Systems Engineer,131630,USD,131630,EX,PT,Israel,M,Israel,50,"Git, Java, Linux, TensorFlow, Deep Learning",Master,13,Automotive,2025-01-24,2025-03-21,1311,5,TechCorp Inc -AI12879,Computer Vision Engineer,130641,JPY,14370510,MI,FT,Japan,L,Japan,50,"Python, Spark, Scala, Data Visualization, SQL",Associate,3,Real Estate,2024-12-18,2025-01-23,2057,6.3,TechCorp Inc -AI12880,Deep Learning Engineer,270691,GBP,203018,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Azure, Java, SQL, Computer Vision",Master,16,Education,2025-03-14,2025-04-22,1824,6.9,Neural Networks Co -AI12881,AI Product Manager,90830,USD,90830,MI,PT,United States,M,United States,100,"MLOps, Data Visualization, Python, SQL, GCP",Master,3,Education,2025-01-14,2025-02-11,1273,6.8,Smart Analytics -AI12882,AI Architect,155288,USD,155288,EX,CT,South Korea,S,Canada,50,"Python, Deep Learning, TensorFlow, Java, Statistics",PhD,18,Manufacturing,2025-01-27,2025-03-23,1295,7.8,Algorithmic Solutions -AI12883,NLP Engineer,55458,USD,55458,EN,CT,Finland,M,Finland,0,"Python, TensorFlow, Statistics",Associate,0,Healthcare,2024-02-11,2024-02-25,1132,6.2,Cloud AI Solutions -AI12884,Research Scientist,142729,USD,142729,MI,FL,Norway,M,Norway,100,"Kubernetes, MLOps, Scala, Computer Vision",Master,2,Transportation,2024-03-24,2024-05-13,2222,6.5,Smart Analytics -AI12885,Data Engineer,72858,USD,72858,EN,CT,Denmark,M,Switzerland,100,"SQL, R, Tableau, AWS, Computer Vision",Bachelor,0,Retail,2025-01-12,2025-02-06,1491,5.6,Future Systems -AI12886,Robotics Engineer,107428,AUD,145028,MI,FT,Australia,L,Australia,0,"Computer Vision, Python, Git, Kubernetes, Docker",Associate,3,Telecommunications,2024-06-09,2024-07-13,1024,9.4,Machine Intelligence Group -AI12887,Data Scientist,86669,EUR,73669,MI,FT,Netherlands,M,Netherlands,0,"Docker, Hadoop, MLOps, Git",Bachelor,3,Finance,2025-02-07,2025-03-21,1124,9.1,Digital Transformation LLC -AI12888,Research Scientist,128076,CAD,160095,EX,CT,Canada,M,Singapore,50,"Deep Learning, NLP, Data Visualization, Kubernetes",PhD,13,Media,2025-01-16,2025-03-10,923,9.5,DeepTech Ventures -AI12889,Machine Learning Engineer,106104,USD,106104,SE,PT,Israel,M,Israel,0,"Azure, SQL, Data Visualization, Python",Associate,5,Transportation,2024-03-23,2024-04-15,1567,9.3,Algorithmic Solutions -AI12890,Deep Learning Engineer,68721,USD,68721,MI,FL,Sweden,S,South Korea,50,"Scala, Spark, MLOps",Master,2,Energy,2024-05-15,2024-07-17,771,6.1,Future Systems -AI12891,NLP Engineer,86559,CAD,108199,MI,CT,Canada,M,Canada,50,"SQL, Kubernetes, Mathematics, Computer Vision, Azure",Associate,4,Gaming,2024-04-18,2024-06-28,2191,5,DeepTech Ventures -AI12892,ML Ops Engineer,61330,USD,61330,EN,FL,Israel,S,Israel,100,"NLP, PyTorch, Tableau, Scala, Java",PhD,1,Government,2024-03-06,2024-04-27,2174,5.7,Algorithmic Solutions -AI12893,Research Scientist,119858,AUD,161808,MI,PT,Australia,L,China,50,"Tableau, Statistics, Azure",Master,3,Media,2024-10-30,2024-11-13,1341,8.4,Quantum Computing Inc -AI12894,Robotics Engineer,118666,USD,118666,EN,FL,Norway,L,United States,0,"Scala, GCP, MLOps",PhD,1,Real Estate,2024-05-18,2024-07-03,1551,7.1,Digital Transformation LLC -AI12895,Autonomous Systems Engineer,25726,USD,25726,EN,FL,China,S,China,50,"TensorFlow, Linux, MLOps, R",Master,0,Transportation,2025-03-03,2025-03-22,2314,7.6,Machine Intelligence Group -AI12896,AI Specialist,29930,USD,29930,EN,CT,India,L,India,50,"Linux, Python, Tableau",Bachelor,0,Gaming,2024-04-21,2024-06-12,2416,7.5,DeepTech Ventures -AI12897,AI Architect,37505,USD,37505,MI,PT,India,M,India,0,"Mathematics, MLOps, Data Visualization",Bachelor,2,Media,2024-01-01,2024-01-22,1487,6.2,Predictive Systems -AI12898,Head of AI,116283,USD,116283,MI,CT,United States,S,Nigeria,0,"Git, Computer Vision, PyTorch, Hadoop",PhD,2,Automotive,2024-10-10,2024-12-09,1497,9.3,Neural Networks Co -AI12899,AI Product Manager,45147,USD,45147,SE,CT,India,S,India,0,"Python, TensorFlow, GCP",Associate,5,Real Estate,2024-05-06,2024-07-13,1498,5.7,Machine Intelligence Group -AI12900,Principal Data Scientist,66746,USD,66746,EN,CT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",PhD,0,Technology,2025-02-23,2025-04-21,1410,9.4,AI Innovations -AI12901,Data Analyst,61929,CAD,77411,EN,CT,Canada,M,Canada,100,"Git, Computer Vision, Statistics, Data Visualization, Java",Master,1,Retail,2024-06-06,2024-07-29,1877,6.8,Quantum Computing Inc -AI12902,Head of AI,210982,USD,210982,EX,FT,Sweden,M,Sweden,50,"Data Visualization, Tableau, Linux, TensorFlow, Java",Associate,11,Media,2024-03-04,2024-05-01,2082,9.4,Smart Analytics -AI12903,NLP Engineer,82621,SGD,107407,EN,FL,Singapore,L,Germany,100,"Tableau, PyTorch, TensorFlow, Python",Associate,1,Telecommunications,2025-03-15,2025-04-29,1755,7.7,AI Innovations -AI12904,Machine Learning Engineer,227131,EUR,193061,EX,FT,Germany,L,Germany,50,"Spark, PyTorch, Azure",Master,16,Automotive,2024-12-17,2025-01-21,640,7,Digital Transformation LLC -AI12905,Machine Learning Researcher,113462,USD,113462,MI,FL,United States,S,United States,0,"Azure, Tableau, Scala",Associate,2,Technology,2024-11-30,2024-12-19,2147,6,Algorithmic Solutions -AI12906,Machine Learning Researcher,146522,USD,146522,SE,PT,Denmark,M,Denmark,50,"Data Visualization, MLOps, Docker, Scala, R",Bachelor,7,Consulting,2024-12-31,2025-01-22,2267,8.2,Cloud AI Solutions -AI12907,AI Architect,310444,USD,310444,EX,FL,Denmark,M,Denmark,0,"NLP, TensorFlow, Java",PhD,17,Gaming,2025-02-07,2025-03-14,1768,5.4,Future Systems -AI12908,Machine Learning Engineer,212270,CAD,265338,EX,FL,Canada,S,Canada,50,"Scala, AWS, Computer Vision",PhD,10,Consulting,2024-12-01,2024-12-15,821,9.7,Autonomous Tech -AI12909,Principal Data Scientist,55426,USD,55426,MI,PT,South Korea,S,South Korea,0,"NLP, TensorFlow, PyTorch, Linux",Master,3,Technology,2025-01-25,2025-03-15,2111,9.6,Autonomous Tech -AI12910,NLP Engineer,284645,USD,284645,EX,PT,Denmark,M,Denmark,0,"SQL, Hadoop, Mathematics, MLOps, AWS",Bachelor,17,Automotive,2025-04-30,2025-05-15,1964,5.2,Advanced Robotics -AI12911,Machine Learning Engineer,91905,EUR,78119,MI,PT,France,M,France,100,"Kubernetes, MLOps, Linux, Java",Associate,3,Real Estate,2024-09-04,2024-10-07,1258,8.4,Neural Networks Co -AI12912,AI Consultant,46252,USD,46252,EN,FT,South Korea,S,South Korea,100,"Mathematics, Spark, MLOps, Computer Vision",Associate,1,Education,2024-07-15,2024-08-06,596,5.6,Digital Transformation LLC -AI12913,Data Engineer,140999,EUR,119849,SE,CT,Germany,L,Germany,0,"TensorFlow, Python, Hadoop",Master,6,Government,2024-04-19,2024-05-24,969,5.3,DataVision Ltd -AI12914,AI Architect,61460,USD,61460,EN,FT,Ireland,L,Philippines,100,"MLOps, Python, TensorFlow",PhD,0,Transportation,2024-12-28,2025-02-06,1746,8.3,TechCorp Inc -AI12915,AI Product Manager,107693,USD,107693,EN,FT,United States,L,United States,0,"Data Visualization, Kubernetes, NLP, AWS",Master,1,Telecommunications,2024-01-18,2024-02-22,1186,5.5,DataVision Ltd -AI12916,Deep Learning Engineer,202576,CAD,253220,EX,FT,Canada,L,Canada,100,"Azure, Deep Learning, GCP, Docker",Associate,15,Telecommunications,2024-09-09,2024-10-15,1817,9.4,DataVision Ltd -AI12917,AI Architect,61666,USD,61666,EN,FT,Israel,S,Israel,0,"Hadoop, R, Mathematics",Associate,1,Energy,2024-08-31,2024-09-15,2378,8.5,Cloud AI Solutions -AI12918,Data Scientist,40597,USD,40597,MI,FT,China,M,China,0,"R, MLOps, PyTorch",Master,4,Real Estate,2024-12-25,2025-03-01,1634,6.4,Cloud AI Solutions -AI12919,AI Research Scientist,136441,SGD,177373,SE,FL,Singapore,L,Singapore,0,"Docker, GCP, MLOps",Master,8,Automotive,2024-02-03,2024-04-05,1625,5.8,Predictive Systems -AI12920,Principal Data Scientist,64127,USD,64127,SE,PT,China,L,China,50,"Scala, TensorFlow, Kubernetes",Master,8,Gaming,2024-09-04,2024-10-11,581,7.2,Machine Intelligence Group -AI12921,ML Ops Engineer,104753,AUD,141417,SE,FL,Australia,M,Turkey,0,"GCP, Spark, Statistics",Bachelor,5,Gaming,2024-07-07,2024-08-15,1289,9.6,Quantum Computing Inc -AI12922,Principal Data Scientist,122222,USD,122222,MI,PT,Denmark,M,United Kingdom,50,"Docker, Deep Learning, Scala",Bachelor,2,Education,2024-07-30,2024-09-01,584,9.3,Predictive Systems -AI12923,NLP Engineer,101788,EUR,86520,SE,FL,France,M,France,50,"Data Visualization, Python, SQL, R, Java",Bachelor,9,Consulting,2024-08-30,2024-10-18,2421,9.7,AI Innovations -AI12924,Autonomous Systems Engineer,341521,CHF,307369,EX,FT,Switzerland,L,Australia,50,"Linux, Docker, SQL, GCP",Bachelor,11,Consulting,2024-11-01,2024-11-24,736,5.9,Cloud AI Solutions -AI12925,AI Specialist,63658,USD,63658,EN,PT,Israel,M,Israel,0,"Data Visualization, MLOps, Python, Java",PhD,0,Education,2024-04-18,2024-05-13,1176,9,Neural Networks Co -AI12926,Data Engineer,172241,USD,172241,EX,PT,Finland,M,Finland,50,"Scala, Hadoop, Data Visualization, NLP",Bachelor,11,Energy,2025-03-25,2025-04-20,1125,7.9,Algorithmic Solutions -AI12927,Data Engineer,80284,EUR,68241,MI,CT,Netherlands,M,Netherlands,100,"Linux, PyTorch, SQL",PhD,3,Energy,2024-11-19,2025-01-10,2146,8.8,Autonomous Tech -AI12928,Head of AI,82705,USD,82705,EN,FT,Sweden,L,Sweden,0,"Mathematics, Tableau, Hadoop, PyTorch",PhD,0,Finance,2024-03-09,2024-04-10,1351,8.1,Neural Networks Co -AI12929,ML Ops Engineer,82163,USD,82163,EN,PT,Finland,L,Finland,0,"Docker, MLOps, Deep Learning, Kubernetes, GCP",Associate,1,Manufacturing,2025-04-24,2025-06-19,1669,8.8,Algorithmic Solutions -AI12930,Principal Data Scientist,134609,USD,134609,SE,FT,Ireland,S,Ireland,100,"R, TensorFlow, Hadoop",Associate,9,Transportation,2025-02-10,2025-03-15,2238,7.6,Future Systems -AI12931,Machine Learning Researcher,50356,EUR,42803,EN,PT,Germany,S,Germany,0,"Git, TensorFlow, Data Visualization",Bachelor,1,Education,2025-04-13,2025-06-15,777,6.3,Digital Transformation LLC -AI12932,Robotics Engineer,100882,USD,100882,MI,CT,United States,S,United States,100,"Hadoop, Tableau, Git",Associate,3,Media,2024-11-07,2025-01-13,1996,6,Cloud AI Solutions -AI12933,AI Software Engineer,97133,USD,97133,SE,CT,Finland,M,Finland,100,"Computer Vision, Python, SQL, Docker",Associate,6,Education,2024-04-20,2024-05-18,2044,7.9,Cognitive Computing -AI12934,Data Engineer,169587,USD,169587,SE,PT,United States,L,United States,50,"R, GCP, SQL",Bachelor,6,Retail,2025-04-07,2025-05-13,612,7.6,Neural Networks Co -AI12935,AI Consultant,218131,EUR,185411,EX,CT,France,M,Turkey,0,"Hadoop, SQL, GCP, Git",Bachelor,10,Education,2025-02-18,2025-03-22,2034,8.5,Machine Intelligence Group -AI12936,NLP Engineer,103226,USD,103226,MI,CT,United States,M,Turkey,0,"Python, Hadoop, MLOps, Data Visualization, PyTorch",Bachelor,4,Retail,2024-09-23,2024-10-30,1512,6.2,AI Innovations -AI12937,Principal Data Scientist,100052,USD,100052,EN,PT,United States,L,United States,50,"PyTorch, R, Linux, Kubernetes, Scala",PhD,0,Consulting,2025-01-27,2025-04-08,1611,6.2,Algorithmic Solutions -AI12938,Deep Learning Engineer,166634,USD,166634,SE,FL,Norway,M,United States,0,"GCP, Python, Scala, Docker",Bachelor,8,Real Estate,2024-02-04,2024-02-29,673,9.3,Future Systems -AI12939,AI Consultant,116226,USD,116226,SE,FT,Sweden,M,Sweden,50,"PyTorch, Java, TensorFlow",Bachelor,6,Finance,2024-05-14,2024-07-11,1881,6.1,DeepTech Ventures -AI12940,NLP Engineer,95173,EUR,80897,SE,FL,Germany,S,Canada,0,"Scala, Java, Mathematics, Linux, Git",Master,6,Gaming,2024-08-21,2024-10-31,1306,9.8,Future Systems -AI12941,Data Scientist,164965,EUR,140220,EX,CT,Germany,S,Germany,0,"TensorFlow, Docker, Deep Learning, Python, Git",Bachelor,17,Consulting,2025-02-06,2025-03-09,1669,7.8,AI Innovations -AI12942,AI Architect,110208,CHF,99187,MI,CT,Switzerland,S,Switzerland,0,"SQL, Hadoop, R",PhD,4,Technology,2024-05-28,2024-07-06,712,9.8,AI Innovations -AI12943,AI Consultant,66541,USD,66541,EN,FT,United States,S,Brazil,100,"Kubernetes, Mathematics, NLP, SQL, Tableau",Bachelor,0,Consulting,2025-04-07,2025-05-14,2176,8.2,Digital Transformation LLC -AI12944,Computer Vision Engineer,349894,USD,349894,EX,FT,Norway,L,Norway,100,"SQL, Python, MLOps, Statistics",Master,14,Technology,2025-02-07,2025-03-15,1449,8.7,AI Innovations -AI12945,Machine Learning Engineer,186739,CHF,168065,SE,FT,Switzerland,S,Switzerland,0,"Deep Learning, Git, Java",PhD,9,Manufacturing,2024-05-22,2024-07-01,1850,7.5,Digital Transformation LLC -AI12946,Machine Learning Researcher,239337,SGD,311138,EX,FT,Singapore,S,Singapore,50,"Tableau, Java, NLP",Master,19,Education,2024-04-03,2024-04-29,2231,9.4,Algorithmic Solutions -AI12947,Machine Learning Researcher,36462,USD,36462,MI,FL,India,M,India,100,"TensorFlow, PyTorch, MLOps, GCP",PhD,4,Finance,2024-05-15,2024-07-10,2444,5.7,Machine Intelligence Group -AI12948,Data Analyst,91501,USD,91501,EN,CT,Denmark,M,Denmark,0,"Mathematics, R, Python",Master,1,Real Estate,2024-09-28,2024-10-18,747,5.5,DataVision Ltd -AI12949,Head of AI,112775,USD,112775,SE,CT,South Korea,L,Austria,0,"SQL, Computer Vision, Linux",Bachelor,5,Manufacturing,2024-10-03,2024-11-23,1899,8.5,Machine Intelligence Group -AI12950,Principal Data Scientist,114451,CAD,143064,SE,PT,Canada,L,Denmark,50,"Java, Hadoop, Tableau, Computer Vision, Statistics",PhD,9,Consulting,2024-02-04,2024-02-24,1992,8.1,Predictive Systems -AI12951,AI Specialist,106509,SGD,138462,SE,PT,Singapore,S,Singapore,0,"Kubernetes, SQL, Azure, PyTorch, TensorFlow",Associate,5,Consulting,2024-03-26,2024-05-09,2482,5.1,Future Systems -AI12952,AI Research Scientist,122296,JPY,13452560,SE,FL,Japan,S,Japan,50,"Kubernetes, SQL, Git, Data Visualization, NLP",Master,7,Retail,2024-06-17,2024-08-08,1647,9.2,DeepTech Ventures -AI12953,ML Ops Engineer,105130,USD,105130,EX,FL,South Korea,S,Egypt,0,"PyTorch, NLP, Python, Hadoop, GCP",Associate,18,Finance,2025-02-07,2025-04-21,1519,6,Advanced Robotics -AI12954,AI Consultant,54001,USD,54001,EN,PT,Israel,S,Israel,0,"SQL, Mathematics, TensorFlow, Python, Kubernetes",PhD,0,Gaming,2024-08-06,2024-09-01,2349,9.3,Digital Transformation LLC -AI12955,Data Scientist,48008,USD,48008,EN,FL,Finland,M,Singapore,50,"Data Visualization, Linux, Deep Learning, MLOps",Bachelor,1,Government,2024-02-20,2024-04-03,1739,8.7,Future Systems -AI12956,AI Software Engineer,48486,CAD,60608,EN,FT,Canada,S,Canada,0,"Spark, TensorFlow, SQL, Data Visualization, Kubernetes",Bachelor,1,Media,2025-01-18,2025-02-09,1337,10,Smart Analytics -AI12957,Machine Learning Researcher,270112,EUR,229595,EX,CT,Germany,L,Germany,0,"AWS, Python, Computer Vision",PhD,14,Manufacturing,2024-05-16,2024-07-01,855,7.7,DataVision Ltd -AI12958,AI Research Scientist,90538,EUR,76957,MI,FL,Germany,S,India,100,"Kubernetes, Hadoop, TensorFlow, Computer Vision",PhD,2,Real Estate,2024-02-03,2024-02-29,1388,9.1,Advanced Robotics -AI12959,Principal Data Scientist,151418,USD,151418,SE,FL,Israel,L,Israel,100,"Computer Vision, SQL, Scala, GCP, Spark",Master,8,Telecommunications,2024-06-07,2024-08-17,2032,10,Quantum Computing Inc -AI12960,Data Engineer,198647,CHF,178782,EX,FT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, Hadoop, SQL, AWS",PhD,10,Telecommunications,2025-02-12,2025-03-07,909,8.2,Autonomous Tech -AI12961,Deep Learning Engineer,156122,CAD,195153,SE,FT,Canada,L,Canada,100,"Spark, Tableau, Java, Data Visualization",Bachelor,5,Automotive,2025-01-16,2025-02-09,585,9.2,Predictive Systems -AI12962,ML Ops Engineer,164345,USD,164345,EX,PT,Israel,S,Israel,100,"Git, Kubernetes, Statistics",Associate,14,Education,2025-01-23,2025-02-09,2343,6.5,DataVision Ltd -AI12963,Computer Vision Engineer,156737,USD,156737,MI,CT,Denmark,L,Denmark,50,"Spark, R, SQL, Java, Mathematics",Master,2,Gaming,2024-10-24,2024-11-12,860,9.5,Quantum Computing Inc -AI12964,Research Scientist,134102,EUR,113987,SE,PT,Netherlands,M,Netherlands,50,"Data Visualization, Computer Vision, AWS, GCP, Statistics",Bachelor,9,Government,2024-10-06,2024-12-18,847,8.9,Future Systems -AI12965,Head of AI,112325,USD,112325,SE,FL,Israel,M,Israel,50,"Tableau, Azure, Python, Hadoop, Docker",PhD,9,Automotive,2025-02-07,2025-04-12,1786,5.7,Predictive Systems -AI12966,ML Ops Engineer,92446,USD,92446,EX,FT,China,S,New Zealand,50,"Spark, Python, Tableau, TensorFlow, GCP",Master,12,Technology,2025-03-05,2025-03-27,996,5.8,Cloud AI Solutions -AI12967,AI Research Scientist,262159,USD,262159,EX,FT,Ireland,L,Ireland,0,"Python, Spark, TensorFlow",Bachelor,18,Media,2025-04-27,2025-05-12,639,8.4,Predictive Systems -AI12968,Data Engineer,44890,USD,44890,MI,FL,China,M,China,0,"Hadoop, Data Visualization, MLOps, Deep Learning",PhD,4,Finance,2024-09-04,2024-11-04,1790,8.9,DeepTech Ventures -AI12969,AI Product Manager,217707,USD,217707,EX,PT,Ireland,S,Belgium,100,"Docker, Python, AWS, TensorFlow",Master,12,Telecommunications,2024-03-22,2024-04-05,1857,8.4,Autonomous Tech -AI12970,AI Product Manager,154903,USD,154903,EX,FT,Sweden,M,Brazil,50,"Scala, PyTorch, Spark, MLOps, Git",Bachelor,17,Energy,2025-02-03,2025-04-11,1604,7.5,Digital Transformation LLC -AI12971,Computer Vision Engineer,224171,USD,224171,EX,FL,United States,L,United States,50,"Deep Learning, Linux, Java, Python, SQL",Master,16,Education,2024-02-11,2024-04-24,1888,7.7,Autonomous Tech -AI12972,Principal Data Scientist,193696,USD,193696,EX,FL,Norway,M,Norway,100,"Mathematics, Deep Learning, Git, Spark",Associate,10,Manufacturing,2024-09-22,2024-11-11,1564,8.1,Cognitive Computing -AI12973,Robotics Engineer,75949,EUR,64557,EN,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, Docker",Master,0,Education,2024-07-07,2024-08-17,743,9.4,Cloud AI Solutions -AI12974,Data Scientist,54686,USD,54686,EN,FL,Ireland,S,Netherlands,50,"Scala, AWS, Python",Bachelor,1,Healthcare,2024-08-16,2024-10-05,1467,6.8,Machine Intelligence Group -AI12975,Principal Data Scientist,103836,EUR,88261,MI,CT,France,M,Argentina,0,"Azure, Python, Deep Learning",Bachelor,3,Manufacturing,2025-03-15,2025-04-14,2314,9.8,Machine Intelligence Group -AI12976,Machine Learning Researcher,80675,USD,80675,MI,FT,Ireland,S,Ireland,50,"Scala, Java, Kubernetes, Spark, Statistics",Bachelor,4,Retail,2024-05-18,2024-06-01,1182,6.5,DeepTech Ventures -AI12977,Computer Vision Engineer,96576,USD,96576,MI,FT,United States,S,Argentina,50,"GCP, Hadoop, SQL",PhD,4,Government,2024-09-16,2024-10-05,1345,7,Machine Intelligence Group -AI12978,AI Architect,186491,CAD,233114,EX,CT,Canada,L,Canada,0,"NLP, Docker, Tableau, Computer Vision",Associate,19,Consulting,2024-08-15,2024-10-07,912,9.7,DataVision Ltd -AI12979,ML Ops Engineer,112803,CHF,101523,EN,FL,Switzerland,M,Switzerland,0,"R, Tableau, Scala",Associate,1,Transportation,2025-04-13,2025-05-17,1292,5.9,Smart Analytics -AI12980,Data Scientist,66258,CAD,82823,EN,FL,Canada,S,Canada,50,"Scala, Python, Statistics",PhD,1,Manufacturing,2025-04-02,2025-06-01,1933,7.8,Smart Analytics -AI12981,AI Architect,122843,GBP,92132,MI,FL,United Kingdom,L,Ukraine,0,"SQL, Java, Python",PhD,4,Media,2024-01-28,2024-02-12,786,5.7,Autonomous Tech -AI12982,AI Research Scientist,70436,USD,70436,EX,PT,India,M,India,100,"NLP, PyTorch, Statistics, Linux",PhD,12,Finance,2024-10-06,2024-11-30,1345,6.4,Digital Transformation LLC -AI12983,Head of AI,111112,USD,111112,MI,FL,Sweden,L,United States,100,"Python, Tableau, SQL",Bachelor,2,Education,2024-08-27,2024-10-01,1822,8.5,Digital Transformation LLC -AI12984,NLP Engineer,62688,USD,62688,EN,FT,Ireland,S,Mexico,100,"Java, Docker, Statistics, Linux",Bachelor,0,Technology,2025-03-11,2025-03-31,1549,7.4,TechCorp Inc -AI12985,Principal Data Scientist,109993,AUD,148491,MI,FT,Australia,M,Australia,50,"MLOps, Git, NLP, Computer Vision",PhD,3,Energy,2024-01-04,2024-02-26,891,9,Quantum Computing Inc -AI12986,Robotics Engineer,90739,AUD,122498,MI,PT,Australia,M,Malaysia,100,"Computer Vision, NLP, MLOps, PyTorch, Docker",PhD,2,Retail,2024-09-13,2024-10-23,1603,8,TechCorp Inc -AI12987,NLP Engineer,116788,EUR,99270,SE,FL,France,M,France,50,"R, Kubernetes, Computer Vision, Hadoop, Docker",Associate,5,Education,2025-02-14,2025-03-14,2471,9.7,Quantum Computing Inc -AI12988,Data Scientist,89119,EUR,75751,MI,FL,Germany,M,Germany,100,"Hadoop, Linux, Tableau, Docker, Kubernetes",Bachelor,4,Telecommunications,2024-09-23,2024-11-23,2175,6.7,TechCorp Inc -AI12989,Machine Learning Engineer,80678,SGD,104881,MI,FT,Singapore,S,Singapore,100,"Git, SQL, Azure",Master,3,Real Estate,2025-04-23,2025-05-12,1070,9.1,Future Systems -AI12990,Head of AI,146187,EUR,124259,SE,PT,Austria,L,Austria,100,"SQL, MLOps, R",Associate,5,Education,2025-02-17,2025-04-21,1463,8.1,DataVision Ltd -AI12991,Machine Learning Engineer,77845,USD,77845,EX,CT,India,S,India,0,"GCP, Java, Data Visualization",PhD,12,Transportation,2024-02-29,2024-04-30,720,8.2,AI Innovations -AI12992,Autonomous Systems Engineer,73922,USD,73922,EN,FT,United States,M,United Kingdom,50,"TensorFlow, Python, Computer Vision, R, Hadoop",Bachelor,0,Healthcare,2024-01-13,2024-02-19,1487,5.1,Cloud AI Solutions -AI12993,Data Scientist,103867,EUR,88287,MI,PT,Netherlands,S,Netherlands,100,"Linux, Java, R",Master,2,Gaming,2024-06-24,2024-08-24,1252,5.4,DeepTech Ventures -AI12994,AI Research Scientist,125902,EUR,107017,EX,PT,France,S,France,50,"SQL, MLOps, Kubernetes, Mathematics, Computer Vision",PhD,13,Transportation,2025-02-07,2025-04-18,593,9.1,TechCorp Inc -AI12995,AI Architect,29129,USD,29129,MI,FT,India,M,India,0,"Spark, R, Hadoop",Associate,4,Automotive,2025-03-13,2025-04-11,1097,9.8,Digital Transformation LLC -AI12996,AI Software Engineer,43029,USD,43029,EN,PT,South Korea,S,South Korea,100,"Docker, Tableau, SQL",Bachelor,0,Healthcare,2024-02-03,2024-03-06,610,7.4,DeepTech Ventures -AI12997,Machine Learning Engineer,79088,USD,79088,EN,FT,Sweden,L,Sweden,0,"Data Visualization, Tableau, SQL, Mathematics",Bachelor,0,Media,2024-02-17,2024-04-13,1246,8.9,Advanced Robotics -AI12998,AI Specialist,49171,USD,49171,EN,FT,Sweden,S,Turkey,50,"Computer Vision, Python, MLOps",Bachelor,0,Automotive,2024-08-19,2024-09-27,1611,5.5,Digital Transformation LLC -AI12999,Data Analyst,62847,SGD,81701,EN,CT,Singapore,L,Singapore,100,"Git, TensorFlow, Tableau, Scala",PhD,1,Transportation,2024-01-01,2024-02-24,1985,7,Cognitive Computing -AI13000,AI Specialist,80522,USD,80522,SE,CT,South Korea,S,Ghana,100,"PyTorch, Docker, Azure, TensorFlow",Associate,6,Gaming,2025-03-11,2025-03-28,978,8.9,Quantum Computing Inc -AI13001,AI Consultant,64623,EUR,54930,EN,PT,Netherlands,S,Netherlands,50,"Mathematics, AWS, Docker, Statistics",PhD,0,Telecommunications,2024-04-15,2024-06-18,764,9.8,Quantum Computing Inc -AI13002,Machine Learning Engineer,138114,USD,138114,SE,CT,United States,S,United States,0,"MLOps, Linux, Kubernetes",PhD,8,Telecommunications,2024-07-17,2024-09-09,1795,5.7,Digital Transformation LLC -AI13003,AI Consultant,175938,AUD,237516,EX,FL,Australia,L,Australia,100,"Linux, Tableau, Git",Bachelor,12,Gaming,2024-05-23,2024-06-12,1700,9.3,Algorithmic Solutions -AI13004,Data Engineer,58622,USD,58622,EX,PT,China,S,Indonesia,0,"Hadoop, SQL, Computer Vision",Bachelor,17,Automotive,2025-04-30,2025-06-14,807,7.7,Future Systems -AI13005,Data Engineer,79766,GBP,59825,MI,FT,United Kingdom,M,United Kingdom,50,"Statistics, Java, TensorFlow, PyTorch, Computer Vision",PhD,4,Manufacturing,2024-05-13,2024-06-04,905,5.8,AI Innovations -AI13006,Machine Learning Researcher,89995,USD,89995,MI,CT,Norway,S,Norway,0,"TensorFlow, Statistics, R, Docker, Java",Bachelor,2,Government,2024-04-21,2024-06-17,641,5.6,Neural Networks Co -AI13007,NLP Engineer,160586,USD,160586,SE,FL,Ireland,L,Portugal,0,"Git, AWS, Mathematics",Master,7,Transportation,2024-06-17,2024-08-09,2063,6.9,Smart Analytics -AI13008,AI Specialist,109290,USD,109290,EX,FL,China,M,Switzerland,0,"Java, Python, Statistics, GCP, NLP",Master,11,Energy,2025-04-23,2025-05-13,2189,9.8,Cognitive Computing -AI13009,Robotics Engineer,222632,EUR,189237,EX,FL,Netherlands,M,Netherlands,0,"Azure, Kubernetes, GCP, SQL, Hadoop",Master,19,Finance,2024-11-13,2024-12-28,881,5.7,AI Innovations -AI13010,Research Scientist,154841,CHF,139357,MI,CT,Switzerland,L,Australia,0,"Hadoop, MLOps, Kubernetes, Java",Bachelor,4,Automotive,2024-06-24,2024-07-10,1923,6.5,Predictive Systems -AI13011,Machine Learning Engineer,350148,CHF,315133,EX,CT,Switzerland,M,Switzerland,0,"Java, Git, Azure",Associate,15,Finance,2024-08-24,2024-10-06,691,7.7,Smart Analytics -AI13012,AI Research Scientist,85240,USD,85240,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Hadoop, Mathematics",Bachelor,2,Finance,2025-01-09,2025-02-16,731,9.7,Future Systems -AI13013,Robotics Engineer,129453,GBP,97090,SE,FT,United Kingdom,M,United Kingdom,0,"MLOps, Git, Mathematics, Spark",Bachelor,7,Retail,2024-01-19,2024-03-26,2363,6.9,Predictive Systems -AI13014,Data Engineer,269378,SGD,350191,EX,FT,Singapore,M,Singapore,0,"NLP, Python, SQL, Data Visualization",Master,15,Energy,2024-07-27,2024-08-19,2033,8.8,AI Innovations -AI13015,Deep Learning Engineer,280599,USD,280599,EX,PT,Ireland,L,Ireland,0,"Linux, SQL, NLP, GCP",Master,16,Retail,2024-04-22,2024-07-02,893,7.5,DataVision Ltd -AI13016,Machine Learning Engineer,71137,EUR,60466,MI,FL,Netherlands,S,Netherlands,50,"Kubernetes, Computer Vision, SQL, Deep Learning, PyTorch",PhD,3,Education,2024-02-20,2024-03-14,676,9.4,Advanced Robotics -AI13017,Data Scientist,174913,EUR,148676,EX,CT,Netherlands,M,France,0,"NLP, Statistics, Hadoop",Bachelor,19,Manufacturing,2024-08-10,2024-09-04,840,5.5,Digital Transformation LLC -AI13018,Deep Learning Engineer,115630,USD,115630,SE,PT,Israel,S,Estonia,50,"Java, Data Visualization, Scala, Azure, GCP",Master,9,Gaming,2024-09-15,2024-10-26,2138,9.3,DataVision Ltd -AI13019,Robotics Engineer,70395,SGD,91514,EN,PT,Singapore,M,Singapore,100,"SQL, TensorFlow, Java, MLOps",Bachelor,0,Real Estate,2024-12-30,2025-01-20,1089,5.6,DeepTech Ventures -AI13020,Deep Learning Engineer,53458,EUR,45439,EN,FT,Austria,S,Austria,50,"TensorFlow, Python, MLOps, Statistics",Associate,0,Retail,2024-06-19,2024-07-15,1120,8.6,Smart Analytics -AI13021,AI Architect,28054,USD,28054,MI,FT,India,S,Nigeria,0,"Python, Java, TensorFlow",PhD,2,Technology,2024-04-12,2024-05-27,530,6.3,Machine Intelligence Group -AI13022,Head of AI,162934,EUR,138494,SE,CT,Germany,L,Philippines,0,"SQL, Data Visualization, Python, Azure",Master,7,Transportation,2024-09-18,2024-10-30,2064,7.5,Neural Networks Co -AI13023,NLP Engineer,111667,USD,111667,MI,FL,Norway,L,Norway,0,"NLP, Tableau, Azure, Git, Linux",Associate,3,Transportation,2025-01-06,2025-02-25,1817,9.1,Smart Analytics -AI13024,ML Ops Engineer,219405,EUR,186494,EX,FL,Netherlands,L,Netherlands,0,"Java, MLOps, TensorFlow, NLP, SQL",Master,14,Automotive,2024-03-05,2024-04-28,1117,6.1,Future Systems -AI13025,ML Ops Engineer,111552,USD,111552,MI,FL,Sweden,L,Sweden,50,"Scala, Python, GCP",Bachelor,2,Automotive,2024-05-15,2024-06-11,841,6.9,Advanced Robotics -AI13026,AI Consultant,123560,USD,123560,MI,PT,Norway,L,Norway,100,"Spark, Data Visualization, Azure, Java, Docker",Associate,2,Media,2024-04-24,2024-05-09,2045,7.7,Algorithmic Solutions -AI13027,AI Specialist,304170,USD,304170,EX,CT,Norway,M,Spain,50,"Python, Data Visualization, AWS, Docker, TensorFlow",Associate,17,Manufacturing,2024-04-28,2024-06-17,1464,8.9,Digital Transformation LLC -AI13028,AI Software Engineer,151323,USD,151323,EX,FL,South Korea,L,South Korea,0,"Python, TensorFlow, Data Visualization, Scala, AWS",PhD,10,Media,2024-11-14,2025-01-13,1035,5.6,Algorithmic Solutions -AI13029,Head of AI,57091,USD,57091,EN,FT,United States,S,United States,50,"R, Linux, Tableau, Git",PhD,1,Gaming,2024-03-13,2024-05-21,2015,7.2,Algorithmic Solutions -AI13030,Research Scientist,160113,USD,160113,SE,FL,Finland,L,Finland,0,"Kubernetes, Tableau, Computer Vision",Associate,6,Education,2024-09-02,2024-09-25,1518,5.5,Predictive Systems -AI13031,AI Consultant,69137,JPY,7605070,EN,PT,Japan,L,Japan,50,"Git, MLOps, Data Visualization, PyTorch, Azure",PhD,0,Consulting,2024-03-07,2024-05-15,1334,5.5,Future Systems -AI13032,Computer Vision Engineer,52465,AUD,70828,EN,FL,Australia,S,Canada,100,"Scala, Linux, AWS",PhD,0,Transportation,2025-02-12,2025-03-07,1863,7.9,TechCorp Inc -AI13033,Machine Learning Researcher,74221,JPY,8164310,MI,FT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization, Computer Vision",Associate,4,Retail,2025-02-17,2025-04-02,1139,5.2,AI Innovations -AI13034,Robotics Engineer,73237,USD,73237,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2024-02-22,2024-04-08,644,5.8,Quantum Computing Inc -AI13035,Data Scientist,116610,USD,116610,MI,FT,Finland,L,Finland,50,"Hadoop, SQL, Mathematics",PhD,2,Consulting,2024-06-17,2024-08-10,2042,5.3,Autonomous Tech -AI13036,AI Product Manager,155471,CAD,194339,SE,PT,Canada,L,Canada,50,"GCP, PyTorch, Java",Bachelor,8,Energy,2024-12-25,2025-01-17,1576,5.5,AI Innovations -AI13037,Robotics Engineer,53502,USD,53502,SE,CT,India,M,Finland,0,"PyTorch, TensorFlow, Tableau, AWS, Linux",Master,6,Government,2025-02-14,2025-04-24,2130,9.6,Machine Intelligence Group -AI13038,Autonomous Systems Engineer,174189,USD,174189,EX,PT,Ireland,L,United States,50,"R, Mathematics, Hadoop",PhD,16,Consulting,2024-10-05,2024-11-02,1656,8.7,Advanced Robotics -AI13039,Machine Learning Engineer,140960,SGD,183248,SE,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning, Java, R",PhD,9,Finance,2025-01-28,2025-03-07,2233,7.5,Smart Analytics -AI13040,Deep Learning Engineer,65603,SGD,85284,EN,PT,Singapore,S,Singapore,50,"Linux, AWS, Python",Associate,0,Finance,2024-08-01,2024-08-21,1584,5.1,Smart Analytics -AI13041,AI Specialist,280472,EUR,238401,EX,CT,Netherlands,L,Thailand,50,"R, NLP, Java, Data Visualization, Scala",PhD,17,Consulting,2024-07-30,2024-09-25,1827,6.7,Autonomous Tech -AI13042,Research Scientist,194338,EUR,165187,EX,CT,Germany,L,Philippines,100,"SQL, Hadoop, Kubernetes, Java, NLP",Master,17,Manufacturing,2025-01-31,2025-03-20,2167,5.9,Future Systems -AI13043,Autonomous Systems Engineer,162690,USD,162690,MI,FL,Norway,L,Norway,50,"Git, Linux, Docker",Associate,3,Real Estate,2025-04-08,2025-06-18,2084,6.3,TechCorp Inc -AI13044,Machine Learning Researcher,178197,USD,178197,SE,PT,Denmark,M,Colombia,0,"MLOps, Python, TensorFlow",Master,7,Media,2024-05-29,2024-07-07,2093,8.1,Cognitive Computing -AI13045,Machine Learning Researcher,75976,USD,75976,EX,FL,China,S,China,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,15,Transportation,2024-05-16,2024-07-28,1108,6,DeepTech Ventures -AI13046,Machine Learning Engineer,129457,JPY,14240270,SE,CT,Japan,S,Luxembourg,0,"Linux, Python, Git",Associate,8,Education,2024-01-04,2024-01-26,1084,9.9,Advanced Robotics -AI13047,Data Analyst,116495,CAD,145619,EX,FL,Canada,S,Canada,50,"Git, Python, SQL, Data Visualization, Spark",Bachelor,16,Consulting,2025-02-08,2025-03-31,1552,9.2,Neural Networks Co -AI13048,Head of AI,148839,USD,148839,EX,PT,Sweden,S,Sweden,0,"Hadoop, Spark, Deep Learning",Bachelor,17,Media,2024-03-17,2024-04-03,1358,5.5,DataVision Ltd -AI13049,AI Architect,123589,CHF,111230,MI,CT,Switzerland,M,Ireland,50,"Linux, Mathematics, Data Visualization, Docker, PyTorch",PhD,3,Government,2024-06-25,2024-08-22,1871,9.7,Advanced Robotics -AI13050,Deep Learning Engineer,83978,EUR,71381,EN,FT,France,L,France,50,"Python, Mathematics, Scala, Java, TensorFlow",PhD,1,Real Estate,2024-11-18,2024-12-21,1434,9.3,Algorithmic Solutions -AI13051,Principal Data Scientist,66441,EUR,56475,EN,PT,Germany,L,Germany,50,"Spark, Java, Statistics, R",PhD,0,Gaming,2024-08-28,2024-10-13,1565,6.3,TechCorp Inc -AI13052,Machine Learning Researcher,282786,EUR,240368,EX,PT,Netherlands,L,Netherlands,50,"Git, Python, TensorFlow",Master,14,Retail,2024-01-24,2024-03-14,1684,9.8,Predictive Systems -AI13053,Robotics Engineer,102501,CHF,92251,EN,FL,Switzerland,M,Switzerland,0,"SQL, GCP, Data Visualization, PyTorch, R",Master,1,Gaming,2024-09-07,2024-10-01,975,7.9,Cognitive Computing -AI13054,AI Software Engineer,71975,USD,71975,EN,FT,United States,M,Turkey,50,"AWS, Mathematics, Scala, Hadoop",Bachelor,1,Real Estate,2025-03-11,2025-04-05,2168,9.1,Smart Analytics -AI13055,Robotics Engineer,66498,USD,66498,MI,CT,South Korea,M,South Korea,0,"MLOps, PyTorch, Spark, NLP",PhD,3,Manufacturing,2024-07-07,2024-07-22,1418,7.1,Predictive Systems -AI13056,Research Scientist,88009,EUR,74808,EN,FT,Germany,L,Germany,0,"R, SQL, Azure",PhD,1,Technology,2025-03-09,2025-04-20,2288,5.1,DeepTech Ventures -AI13057,AI Consultant,163347,USD,163347,MI,CT,Norway,L,Ireland,100,"GCP, Python, Java, Docker",Master,4,Energy,2024-11-02,2024-11-25,984,8.5,Advanced Robotics -AI13058,Principal Data Scientist,80967,GBP,60725,EN,CT,United Kingdom,L,Luxembourg,100,"Deep Learning, Linux, Python, Hadoop",Associate,1,Technology,2024-11-01,2024-12-16,2453,5,Advanced Robotics -AI13059,AI Architect,108015,EUR,91813,MI,FL,Germany,M,Hungary,0,"Kubernetes, SQL, MLOps, Docker",Associate,4,Telecommunications,2024-08-15,2024-10-11,549,10,Future Systems -AI13060,AI Research Scientist,237965,USD,237965,EX,FT,Norway,L,Norway,100,"Tableau, MLOps, SQL, Linux, Java",Associate,12,Automotive,2024-09-18,2024-10-30,760,9.4,DeepTech Ventures -AI13061,Computer Vision Engineer,48996,USD,48996,MI,FL,China,L,China,100,"Java, Linux, Python",Associate,3,Manufacturing,2024-12-13,2025-01-22,2075,6.9,DeepTech Ventures -AI13062,Machine Learning Engineer,293914,CHF,264523,EX,CT,Switzerland,L,Estonia,50,"Statistics, Python, Linux",Bachelor,16,Manufacturing,2025-03-04,2025-04-15,1936,8.8,Algorithmic Solutions -AI13063,Research Scientist,68050,USD,68050,EN,FT,Ireland,M,Ireland,0,"Statistics, GCP, Deep Learning, Java, Python",Master,1,Healthcare,2024-12-29,2025-01-13,620,7,Digital Transformation LLC -AI13064,Machine Learning Researcher,66356,USD,66356,EN,PT,Ireland,M,Ireland,100,"Data Visualization, Docker, Python",Associate,0,Real Estate,2024-03-31,2024-05-26,1050,6.3,Cognitive Computing -AI13065,Data Analyst,68146,USD,68146,EN,FL,Finland,L,Thailand,0,"Python, Scala, Tableau",Associate,1,Real Estate,2024-09-20,2024-11-21,733,5.9,TechCorp Inc -AI13066,Data Scientist,133642,CAD,167053,SE,PT,Canada,L,Canada,50,"PyTorch, Statistics, Azure, Python",Bachelor,8,Technology,2025-04-27,2025-05-15,1623,5.8,Machine Intelligence Group -AI13067,AI Software Engineer,53834,USD,53834,SE,FT,China,M,China,0,"Git, GCP, Docker",Master,9,Government,2025-04-01,2025-06-03,2469,7.3,Cloud AI Solutions -AI13068,Head of AI,38246,USD,38246,EN,CT,South Korea,S,Turkey,100,"Git, Docker, SQL, Deep Learning, GCP",Master,1,Automotive,2024-06-15,2024-07-29,2133,7.9,Future Systems -AI13069,NLP Engineer,87601,JPY,9636110,EN,FL,Japan,L,Malaysia,0,"Spark, Git, Kubernetes",Master,1,Retail,2024-02-26,2024-04-05,521,6.7,AI Innovations -AI13070,AI Research Scientist,83658,AUD,112938,MI,FT,Australia,L,Australia,0,"Linux, TensorFlow, Hadoop, PyTorch",Associate,3,Healthcare,2024-06-30,2024-08-28,2162,5.8,Predictive Systems -AI13071,Robotics Engineer,109147,AUD,147348,SE,CT,Australia,S,Australia,0,"Mathematics, Git, Deep Learning, Spark, Linux",Associate,9,Transportation,2024-09-15,2024-10-26,1351,5.6,AI Innovations -AI13072,AI Specialist,61946,USD,61946,EN,PT,Israel,L,Vietnam,100,"Linux, Kubernetes, PyTorch",Associate,1,Technology,2025-04-19,2025-05-16,1210,6.7,AI Innovations -AI13073,Data Scientist,343823,CHF,309441,EX,CT,Switzerland,L,United Kingdom,0,"SQL, Docker, TensorFlow",PhD,16,Manufacturing,2024-07-14,2024-09-24,1773,6.3,Future Systems -AI13074,Data Analyst,109859,USD,109859,MI,PT,Norway,L,Denmark,50,"GCP, Docker, Computer Vision, Kubernetes, Linux",Master,4,Automotive,2024-05-04,2024-06-20,1533,7.7,Machine Intelligence Group -AI13075,Machine Learning Researcher,186936,EUR,158896,EX,CT,Germany,S,Germany,100,"GCP, AWS, MLOps, TensorFlow, Deep Learning",Bachelor,14,Automotive,2024-06-01,2024-06-16,1693,6,Quantum Computing Inc -AI13076,AI Specialist,56525,EUR,48046,EN,PT,France,M,France,50,"GCP, SQL, Data Visualization, Hadoop",Associate,1,Real Estate,2024-09-21,2024-10-26,715,5.9,Neural Networks Co -AI13077,Data Scientist,65610,CAD,82013,EN,FT,Canada,S,Canada,100,"Azure, Kubernetes, SQL, Docker",PhD,1,Education,2025-01-22,2025-02-18,642,6.6,Advanced Robotics -AI13078,Research Scientist,66543,USD,66543,EN,CT,Sweden,L,Sweden,50,"Data Visualization, Spark, TensorFlow, Java",Master,1,Education,2025-02-12,2025-03-17,1971,5.9,Cloud AI Solutions -AI13079,Head of AI,95195,GBP,71396,EN,CT,United Kingdom,L,Switzerland,50,"Statistics, PyTorch, SQL, GCP, Docker",Master,1,Education,2024-07-27,2024-08-27,1362,8.4,Predictive Systems -AI13080,Data Engineer,88191,USD,88191,MI,CT,Norway,S,Norway,0,"Java, Deep Learning, Python",PhD,2,Telecommunications,2024-09-30,2024-12-08,788,7.8,Machine Intelligence Group -AI13081,AI Software Engineer,85673,USD,85673,MI,FL,Finland,S,Finland,0,"Python, Hadoop, TensorFlow, Linux",PhD,4,Healthcare,2024-10-02,2024-10-17,917,5.6,Advanced Robotics -AI13082,Computer Vision Engineer,250835,USD,250835,EX,FT,Finland,L,Finland,0,"Hadoop, MLOps, R, Python",Master,14,Retail,2025-04-22,2025-07-03,918,9.8,Machine Intelligence Group -AI13083,Machine Learning Engineer,65750,EUR,55888,MI,FT,Austria,S,Austria,50,"Tableau, TensorFlow, Python, NLP, R",PhD,3,Automotive,2025-04-03,2025-05-27,2456,8.9,Future Systems -AI13084,Principal Data Scientist,96483,USD,96483,MI,PT,Norway,M,Norway,0,"Python, Kubernetes, Azure, Statistics, Linux",PhD,2,Media,2024-02-05,2024-02-28,605,8.1,TechCorp Inc -AI13085,Principal Data Scientist,111619,EUR,94876,MI,PT,Germany,L,Japan,0,"Computer Vision, PyTorch, NLP, TensorFlow, Kubernetes",Associate,3,Consulting,2025-03-10,2025-04-05,967,5.3,Machine Intelligence Group -AI13086,Data Analyst,68910,USD,68910,MI,FT,Sweden,S,France,100,"SQL, GCP, Tableau, TensorFlow",Associate,2,Technology,2024-04-12,2024-05-02,2143,6.5,Quantum Computing Inc -AI13087,Research Scientist,32232,USD,32232,MI,FL,India,M,Finland,0,"Linux, AWS, Hadoop, SQL",Master,4,Energy,2024-08-15,2024-10-12,1713,8.9,Digital Transformation LLC -AI13088,AI Product Manager,85895,USD,85895,MI,PT,South Korea,L,South Korea,100,"MLOps, Scala, Docker, AWS, Spark",Associate,4,Gaming,2024-07-16,2024-09-18,1126,5,Machine Intelligence Group -AI13089,AI Research Scientist,151896,EUR,129112,EX,PT,Netherlands,S,United Kingdom,100,"Kubernetes, Java, Scala",Associate,18,Media,2024-07-14,2024-09-15,2330,6.7,Advanced Robotics -AI13090,Computer Vision Engineer,282442,USD,282442,EX,CT,United States,M,United States,100,"SQL, Spark, Python, Docker",Master,15,Technology,2024-02-23,2024-03-25,1246,9.6,Autonomous Tech -AI13091,Data Analyst,132020,USD,132020,SE,PT,United States,M,United States,100,"SQL, Java, AWS, Spark",PhD,9,Transportation,2024-10-22,2024-12-30,1902,8.7,TechCorp Inc -AI13092,AI Research Scientist,118211,EUR,100479,SE,PT,Austria,S,Austria,50,"Hadoop, Mathematics, Python, Scala, TensorFlow",Associate,7,Government,2024-11-04,2024-12-26,1773,8.1,Neural Networks Co -AI13093,Machine Learning Engineer,95484,USD,95484,MI,FT,Sweden,L,Sweden,50,"Linux, Azure, Kubernetes, AWS, SQL",PhD,3,Media,2024-12-31,2025-02-19,2495,8,Cloud AI Solutions -AI13094,Deep Learning Engineer,211850,SGD,275405,EX,PT,Singapore,M,Singapore,50,"Tableau, Python, Linux, Computer Vision, TensorFlow",Master,11,Technology,2024-05-22,2024-06-19,1157,5.6,Advanced Robotics -AI13095,Research Scientist,120477,USD,120477,MI,PT,Denmark,S,Canada,0,"GCP, Kubernetes, TensorFlow, Spark, Data Visualization",PhD,4,Telecommunications,2024-11-21,2024-12-15,701,7.1,Predictive Systems -AI13096,NLP Engineer,218123,USD,218123,EX,FT,Ireland,M,Vietnam,0,"GCP, Azure, Python",Bachelor,17,Energy,2025-03-17,2025-04-24,1056,5.3,Advanced Robotics -AI13097,AI Software Engineer,98570,USD,98570,MI,FT,Sweden,M,Russia,100,"Scala, Computer Vision, Azure, Mathematics, Data Visualization",Master,2,Technology,2024-06-21,2024-08-03,672,8.2,Autonomous Tech -AI13098,AI Architect,81790,USD,81790,MI,FL,Israel,L,Thailand,50,"SQL, Kubernetes, Hadoop, PyTorch, GCP",Bachelor,4,Media,2024-06-30,2024-08-17,830,7.7,Digital Transformation LLC -AI13099,NLP Engineer,91536,CAD,114420,MI,FT,Canada,L,Canada,100,"Spark, Linux, TensorFlow, MLOps, Java",PhD,2,Real Estate,2024-04-11,2024-05-08,1728,9.3,Cognitive Computing -AI13100,AI Specialist,116205,EUR,98774,SE,PT,Austria,M,Austria,0,"Java, SQL, Data Visualization",Bachelor,8,Media,2025-01-23,2025-03-26,2388,9.5,Predictive Systems -AI13101,Principal Data Scientist,58576,EUR,49790,EN,CT,France,M,Hungary,100,"Docker, Linux, Data Visualization, GCP",PhD,0,Transportation,2024-09-13,2024-10-14,2244,7.6,Advanced Robotics -AI13102,AI Software Engineer,106840,CHF,96156,MI,PT,Switzerland,S,Switzerland,0,"Spark, Scala, SQL, Statistics, Deep Learning",Bachelor,4,Transportation,2024-10-09,2024-12-14,862,9.3,Future Systems -AI13103,Computer Vision Engineer,123259,CAD,154074,SE,FL,Canada,L,Canada,50,"Data Visualization, NLP, R",Associate,9,Automotive,2024-07-12,2024-08-10,1202,9.9,Predictive Systems -AI13104,Deep Learning Engineer,88273,JPY,9710030,MI,PT,Japan,M,Australia,50,"NLP, Docker, Computer Vision, SQL",Master,2,Real Estate,2024-04-08,2024-05-04,775,8.3,Cloud AI Solutions -AI13105,AI Specialist,133522,USD,133522,SE,PT,Denmark,M,Turkey,100,"Mathematics, R, Linux, Java",Associate,9,Finance,2024-12-28,2025-02-08,1878,6.2,Predictive Systems -AI13106,AI Consultant,159549,USD,159549,EX,FL,Finland,L,Finland,100,"Linux, PyTorch, MLOps, Java, Kubernetes",PhD,13,Media,2024-03-04,2024-04-15,1430,8.6,Machine Intelligence Group -AI13107,ML Ops Engineer,106103,CAD,132629,SE,FT,Canada,M,Canada,50,"Hadoop, PyTorch, MLOps",PhD,5,Automotive,2024-10-23,2024-12-21,1229,7.9,TechCorp Inc -AI13108,AI Consultant,98258,EUR,83519,SE,FL,France,M,France,50,"Docker, AWS, Tableau, Git",Associate,5,Telecommunications,2024-03-24,2024-05-25,2457,5.9,Cognitive Computing -AI13109,Autonomous Systems Engineer,125492,USD,125492,EX,FT,Ireland,S,Ireland,100,"Spark, Scala, MLOps, Linux",PhD,14,Retail,2025-03-27,2025-05-12,1351,8.2,Predictive Systems -AI13110,AI Research Scientist,166393,EUR,141434,EX,PT,Austria,S,Egypt,100,"AWS, Kubernetes, MLOps",Associate,15,Finance,2025-02-09,2025-04-20,1894,5.5,Neural Networks Co -AI13111,ML Ops Engineer,86105,EUR,73189,MI,FT,Austria,M,Austria,0,"Linux, Java, R, GCP",Bachelor,4,Healthcare,2024-08-27,2024-10-28,2399,7.6,Cloud AI Solutions -AI13112,Data Engineer,125111,USD,125111,SE,FT,Finland,S,Finland,0,"Scala, SQL, Mathematics, Statistics, Linux",Associate,5,Manufacturing,2024-01-14,2024-03-27,1070,5,DataVision Ltd -AI13113,ML Ops Engineer,103754,USD,103754,MI,FT,Sweden,M,Egypt,100,"Docker, Deep Learning, Python, Computer Vision, Git",Associate,2,Consulting,2025-04-22,2025-05-20,731,5.5,Machine Intelligence Group -AI13114,Research Scientist,65132,USD,65132,EN,PT,Sweden,M,Mexico,100,"Docker, Statistics, R, PyTorch, TensorFlow",Bachelor,1,Education,2025-04-16,2025-05-22,1489,9.5,DataVision Ltd -AI13115,AI Architect,195654,CHF,176089,EX,FT,Switzerland,S,Switzerland,100,"SQL, MLOps, Scala",Bachelor,11,Consulting,2024-06-08,2024-07-12,658,6.5,Autonomous Tech -AI13116,Data Engineer,65035,EUR,55280,EN,FL,Austria,S,Philippines,0,"TensorFlow, Data Visualization, Tableau, Scala",Associate,0,Energy,2024-11-12,2025-01-23,1952,9.1,Cognitive Computing -AI13117,AI Product Manager,248091,EUR,210877,EX,CT,France,L,France,50,"Statistics, Spark, SQL, Hadoop",PhD,15,Energy,2024-10-10,2024-12-10,860,5.9,Autonomous Tech -AI13118,Robotics Engineer,141327,EUR,120128,SE,FL,Austria,M,Philippines,0,"GCP, PyTorch, TensorFlow",Bachelor,9,Media,2024-07-29,2024-08-29,1588,7.3,Cloud AI Solutions -AI13119,Data Engineer,343050,USD,343050,EX,PT,Denmark,L,Denmark,100,"MLOps, Kubernetes, SQL",Associate,13,Media,2024-10-26,2024-11-26,1308,5.8,Cloud AI Solutions -AI13120,NLP Engineer,169592,USD,169592,SE,FL,Norway,M,Estonia,0,"Spark, SQL, Data Visualization, Deep Learning",Master,6,Education,2024-12-23,2025-01-27,1423,8.5,Quantum Computing Inc -AI13121,Computer Vision Engineer,73049,EUR,62092,EN,PT,Germany,M,Canada,0,"Mathematics, AWS, SQL",Master,0,Transportation,2024-09-25,2024-11-30,1971,5.8,Quantum Computing Inc -AI13122,Data Analyst,107795,USD,107795,MI,FT,United States,L,United States,0,"R, SQL, AWS",PhD,3,Education,2024-11-18,2024-12-29,1861,9.3,DataVision Ltd -AI13123,Principal Data Scientist,103946,AUD,140327,SE,FT,Australia,M,Australia,100,"Tableau, Python, Statistics",Master,6,Education,2024-10-15,2024-11-09,645,6.3,AI Innovations -AI13124,AI Specialist,141419,JPY,15556090,SE,PT,Japan,S,Japan,100,"Python, MLOps, TensorFlow, Kubernetes, Docker",Master,5,Finance,2024-09-20,2024-10-14,1712,5.6,Neural Networks Co -AI13125,Robotics Engineer,56273,USD,56273,SE,FT,China,S,China,0,"Linux, Python, TensorFlow, Computer Vision",Associate,8,Healthcare,2024-03-03,2024-03-21,1241,8.3,Cloud AI Solutions -AI13126,ML Ops Engineer,225699,AUD,304694,EX,FL,Australia,S,Australia,50,"Linux, Spark, Git, Mathematics, Python",Bachelor,18,Transportation,2024-06-09,2024-07-01,834,7.2,Cognitive Computing -AI13127,Autonomous Systems Engineer,191962,USD,191962,EX,FT,Israel,S,Israel,100,"Tableau, AWS, Statistics",Master,12,Technology,2025-03-15,2025-05-19,1939,9.3,DataVision Ltd -AI13128,Robotics Engineer,65172,EUR,55396,EN,PT,Austria,L,Austria,100,"Docker, Kubernetes, Java, R, Hadoop",PhD,0,Consulting,2024-05-13,2024-07-13,2202,6.3,DataVision Ltd -AI13129,Data Engineer,152054,AUD,205273,SE,FL,Australia,L,Australia,50,"Python, Kubernetes, R, Mathematics",Bachelor,8,Finance,2024-06-24,2024-08-02,685,10,Smart Analytics -AI13130,AI Product Manager,27800,USD,27800,EN,FT,India,M,Kenya,100,"AWS, Git, Python, SQL, Statistics",PhD,1,Media,2024-06-19,2024-08-28,2359,5.1,DataVision Ltd -AI13131,ML Ops Engineer,87373,AUD,117954,MI,PT,Australia,S,Australia,0,"Linux, Git, Scala, R",Master,3,Education,2024-03-01,2024-04-23,1287,9.8,DataVision Ltd -AI13132,AI Product Manager,121517,USD,121517,EX,FL,China,L,China,50,"Computer Vision, Git, MLOps, Tableau",Bachelor,17,Retail,2024-01-02,2024-01-26,714,5.2,Neural Networks Co -AI13133,Principal Data Scientist,95651,USD,95651,MI,FL,Sweden,S,Turkey,100,"GCP, Tableau, Spark",Master,4,Retail,2024-05-05,2024-06-09,1097,6.3,Quantum Computing Inc -AI13134,NLP Engineer,135229,EUR,114945,SE,CT,Germany,S,Singapore,0,"GCP, Docker, Tableau, Linux",Associate,5,Finance,2024-03-03,2024-04-19,1628,7.6,Predictive Systems -AI13135,Machine Learning Researcher,59742,USD,59742,EN,CT,South Korea,L,Italy,0,"Docker, Python, NLP, Kubernetes, Data Visualization",Associate,1,Automotive,2025-03-08,2025-05-01,2448,6.7,Predictive Systems -AI13136,Head of AI,285325,AUD,385189,EX,CT,Australia,L,Ireland,100,"Scala, Spark, GCP, Deep Learning, MLOps",Associate,14,Finance,2024-02-01,2024-03-18,1668,5.3,Cognitive Computing -AI13137,Machine Learning Engineer,177700,GBP,133275,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Python",PhD,14,Retail,2024-03-13,2024-05-11,504,8.2,Quantum Computing Inc -AI13138,AI Architect,129173,USD,129173,MI,PT,United States,L,United States,50,"Scala, MLOps, Spark, NLP",PhD,2,Technology,2024-08-20,2024-10-29,1608,6,Predictive Systems -AI13139,AI Product Manager,124365,EUR,105710,SE,FL,Germany,L,Germany,100,"Statistics, AWS, Java",Master,5,Real Estate,2025-03-21,2025-05-30,2132,9.4,Digital Transformation LLC -AI13140,Data Scientist,28510,USD,28510,EN,CT,India,L,India,100,"TensorFlow, Scala, Java, Python",Associate,0,Manufacturing,2024-01-19,2024-04-01,514,7.1,Future Systems -AI13141,Autonomous Systems Engineer,147366,AUD,198944,SE,CT,Australia,L,India,50,"PyTorch, AWS, TensorFlow, SQL",Master,8,Government,2024-05-16,2024-06-30,2032,9.6,Smart Analytics -AI13142,Data Engineer,54967,EUR,46722,EN,PT,Netherlands,S,Netherlands,0,"Linux, SQL, TensorFlow, Deep Learning, AWS",Master,1,Education,2024-03-17,2024-04-05,1683,6.5,AI Innovations -AI13143,Machine Learning Researcher,56049,EUR,47642,EN,PT,France,S,France,50,"Kubernetes, Linux, Git, Azure, Mathematics",Bachelor,0,Government,2024-09-14,2024-10-18,1354,8.9,Machine Intelligence Group -AI13144,Data Scientist,50627,USD,50627,EN,CT,Ireland,S,Ireland,100,"AWS, Git, Python",Bachelor,0,Finance,2024-09-29,2024-10-22,767,7,Quantum Computing Inc -AI13145,Principal Data Scientist,129562,JPY,14251820,SE,PT,Japan,L,Japan,100,"Deep Learning, Azure, NLP, Python",PhD,7,Media,2024-12-02,2024-12-22,1863,7.5,Smart Analytics -AI13146,Autonomous Systems Engineer,86193,USD,86193,MI,FL,Finland,M,Finland,50,"Kubernetes, Statistics, Python",Bachelor,2,Automotive,2024-03-16,2024-04-19,855,8.9,Quantum Computing Inc -AI13147,AI Research Scientist,242707,CAD,303384,EX,PT,Canada,L,Canada,50,"Python, Spark, PyTorch, R",Associate,13,Telecommunications,2025-02-19,2025-03-22,1183,5.7,Quantum Computing Inc -AI13148,Data Engineer,22180,USD,22180,EN,FL,China,S,China,100,"Statistics, Data Visualization, Git, Linux",Bachelor,1,Energy,2024-05-22,2024-08-01,2339,8.8,Digital Transformation LLC -AI13149,Computer Vision Engineer,144736,CHF,130262,MI,CT,Switzerland,L,Switzerland,50,"Git, Docker, Azure",Associate,2,Telecommunications,2024-10-23,2024-12-31,2474,8.9,Predictive Systems -AI13150,Data Scientist,89075,EUR,75714,MI,FT,Netherlands,M,Brazil,100,"Mathematics, SQL, NLP, Computer Vision",Associate,4,Telecommunications,2024-02-06,2024-04-17,1369,8.4,Algorithmic Solutions -AI13151,Research Scientist,146125,JPY,16073750,SE,CT,Japan,M,Vietnam,100,"Scala, Statistics, Azure",Bachelor,5,Manufacturing,2024-01-11,2024-02-22,1903,8.1,Quantum Computing Inc -AI13152,Data Analyst,57872,EUR,49191,EN,FT,France,S,Czech Republic,50,"Scala, Docker, Statistics, Spark",Master,1,Healthcare,2024-12-22,2025-01-06,1208,9.7,Cognitive Computing -AI13153,Machine Learning Researcher,49720,USD,49720,EX,PT,India,M,Finland,100,"Deep Learning, Python, Tableau",Master,16,Retail,2024-10-19,2024-11-05,1858,8.1,AI Innovations -AI13154,AI Architect,94893,USD,94893,EX,FL,China,S,Germany,50,"Docker, Python, AWS, TensorFlow",Master,11,Manufacturing,2024-08-29,2024-11-07,1073,6.1,AI Innovations -AI13155,NLP Engineer,124615,EUR,105923,SE,PT,Austria,S,Austria,100,"Git, SQL, Java",Bachelor,6,Retail,2025-01-30,2025-04-03,911,5.3,DeepTech Ventures -AI13156,Data Analyst,136314,CHF,122683,SE,CT,Switzerland,S,Switzerland,50,"Docker, R, AWS",PhD,7,Telecommunications,2024-04-19,2024-06-25,1481,6,Advanced Robotics -AI13157,Deep Learning Engineer,60206,EUR,51175,EN,FL,France,S,Philippines,50,"Data Visualization, Linux, Tableau",Associate,0,Consulting,2024-12-01,2025-01-06,912,8.4,DataVision Ltd -AI13158,AI Product Manager,99753,USD,99753,MI,FT,Ireland,M,Denmark,100,"SQL, Scala, Linux",Associate,2,Consulting,2025-04-13,2025-05-07,1352,9.4,DataVision Ltd -AI13159,Machine Learning Engineer,93871,AUD,126726,SE,FL,Australia,S,Australia,100,"Scala, Java, AWS",Bachelor,5,Finance,2025-04-15,2025-05-10,2344,9.1,Cognitive Computing -AI13160,Data Scientist,116623,EUR,99130,EX,PT,France,S,India,100,"AWS, NLP, MLOps, Linux, GCP",Bachelor,14,Retail,2024-07-12,2024-08-02,825,8.8,Quantum Computing Inc -AI13161,Robotics Engineer,102693,SGD,133501,SE,CT,Singapore,S,Singapore,100,"Tableau, R, Linux, Java, PyTorch",Master,5,Automotive,2024-05-27,2024-06-21,1700,8,Predictive Systems -AI13162,Head of AI,62122,USD,62122,EN,PT,Finland,M,Finland,100,"Spark, Scala, Azure, Statistics, MLOps",Bachelor,1,Gaming,2024-04-08,2024-06-05,854,8.2,Autonomous Tech -AI13163,NLP Engineer,58719,USD,58719,SE,CT,China,L,China,100,"Python, MLOps, Scala, Computer Vision, Statistics",Master,8,Real Estate,2025-03-01,2025-05-03,2172,9.7,Machine Intelligence Group -AI13164,AI Software Engineer,59864,USD,59864,EN,CT,Sweden,M,Mexico,50,"Deep Learning, SQL, Data Visualization, MLOps, PyTorch",PhD,1,Real Estate,2024-09-30,2024-10-16,906,9.1,DataVision Ltd -AI13165,Data Engineer,248769,CHF,223892,EX,CT,Switzerland,L,Switzerland,50,"Python, TensorFlow, SQL, Docker, AWS",Associate,12,Real Estate,2025-04-23,2025-05-09,1869,9.4,Algorithmic Solutions -AI13166,Head of AI,100787,USD,100787,MI,FL,Israel,L,Colombia,0,"Hadoop, Kubernetes, SQL, Computer Vision",Master,2,Media,2024-03-18,2024-04-12,878,9.6,Predictive Systems -AI13167,Deep Learning Engineer,90501,EUR,76926,MI,PT,Germany,L,Germany,50,"GCP, MLOps, Azure",Associate,4,Finance,2025-03-13,2025-04-12,1900,7.7,Advanced Robotics -AI13168,AI Product Manager,98721,USD,98721,MI,FT,Sweden,M,Belgium,50,"Data Visualization, PyTorch, NLP",Associate,3,Automotive,2024-09-17,2024-10-20,1279,6.1,Quantum Computing Inc -AI13169,ML Ops Engineer,216873,USD,216873,EX,FT,Sweden,L,Sweden,0,"TensorFlow, Linux, MLOps, Computer Vision",PhD,11,Automotive,2024-04-17,2024-06-14,500,9.5,Quantum Computing Inc -AI13170,AI Consultant,51793,EUR,44024,EN,PT,Austria,S,South Africa,50,"Statistics, Mathematics, GCP, Spark",Bachelor,1,Healthcare,2024-10-12,2024-11-27,625,9.8,Quantum Computing Inc -AI13171,Machine Learning Engineer,89005,EUR,75654,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Mathematics, NLP",Master,3,Telecommunications,2025-04-02,2025-04-29,1954,5.2,DeepTech Ventures -AI13172,Data Analyst,112200,USD,112200,SE,FL,Israel,M,Israel,100,"TensorFlow, Scala, Mathematics",Associate,9,Consulting,2025-01-13,2025-03-09,1087,5.2,TechCorp Inc -AI13173,AI Product Manager,93493,USD,93493,MI,FL,Ireland,S,Switzerland,50,"TensorFlow, Python, Tableau, Deep Learning",Bachelor,4,Technology,2024-09-14,2024-09-29,1688,5.5,TechCorp Inc -AI13174,Machine Learning Researcher,150175,AUD,202736,EX,PT,Australia,M,Australia,100,"Java, R, SQL",Master,17,Government,2024-12-20,2025-02-24,2485,8.3,TechCorp Inc -AI13175,AI Research Scientist,66666,CAD,83333,EN,CT,Canada,L,China,100,"Linux, TensorFlow, Deep Learning, Python",Associate,0,Finance,2024-07-05,2024-09-02,1773,6.9,Future Systems -AI13176,Robotics Engineer,101266,USD,101266,MI,FT,Finland,L,Finland,100,"MLOps, Git, Python, Statistics, Linux",PhD,4,Education,2024-09-13,2024-10-30,1769,5.8,Digital Transformation LLC -AI13177,Autonomous Systems Engineer,76613,USD,76613,EN,FT,United States,M,United States,50,"Linux, Java, TensorFlow, MLOps",Master,1,Telecommunications,2024-08-02,2024-09-02,1973,8.5,Digital Transformation LLC -AI13178,Machine Learning Researcher,49536,USD,49536,EX,PT,India,S,Austria,50,"Spark, Docker, R, Deep Learning",PhD,18,Real Estate,2024-11-24,2024-12-24,2071,8.5,Digital Transformation LLC -AI13179,Deep Learning Engineer,61260,USD,61260,SE,CT,China,L,China,0,"Scala, R, Python",Master,9,Automotive,2025-01-07,2025-03-04,859,6.5,Cognitive Computing -AI13180,AI Specialist,149430,USD,149430,EX,PT,Finland,L,Argentina,100,"R, Python, Java, PyTorch, Tableau",Associate,14,Media,2024-12-09,2024-12-29,1331,7.2,Neural Networks Co -AI13181,Data Scientist,123078,EUR,104616,SE,FT,Austria,L,Austria,0,"Docker, Git, Deep Learning, Statistics, Hadoop",Bachelor,6,Education,2024-08-21,2024-10-24,1714,9.4,Advanced Robotics -AI13182,Machine Learning Engineer,70132,EUR,59612,MI,FL,Austria,S,Thailand,0,"Computer Vision, NLP, Python",Bachelor,2,Automotive,2025-04-22,2025-05-12,1803,9.6,Future Systems -AI13183,Data Analyst,141806,USD,141806,MI,PT,United States,L,United States,100,"MLOps, Kubernetes, GCP, R",Associate,2,Energy,2025-01-03,2025-03-08,818,5.4,Smart Analytics -AI13184,AI Specialist,111124,USD,111124,EX,PT,China,M,Germany,50,"Python, Data Visualization, TensorFlow, Java",Associate,10,Consulting,2024-04-15,2024-05-07,1584,5.1,Predictive Systems -AI13185,Deep Learning Engineer,152448,EUR,129581,EX,FL,Germany,S,Germany,100,"GCP, Hadoop, NLP, Tableau, Computer Vision",PhD,10,Gaming,2024-06-20,2024-08-06,1048,6.7,Cloud AI Solutions -AI13186,ML Ops Engineer,147859,EUR,125680,EX,FL,Germany,S,Germany,0,"Kubernetes, Tableau, AWS, Computer Vision",PhD,13,Energy,2024-03-20,2024-04-04,1994,5.9,AI Innovations -AI13187,AI Architect,71833,CAD,89791,MI,FT,Canada,M,Belgium,100,"Java, SQL, Spark",Master,4,Telecommunications,2024-09-15,2024-11-25,2415,8.3,Predictive Systems -AI13188,Autonomous Systems Engineer,265945,USD,265945,EX,CT,Denmark,L,Denmark,0,"Data Visualization, AWS, Tableau",PhD,13,Real Estate,2024-02-05,2024-04-10,1051,8.5,Smart Analytics -AI13189,Deep Learning Engineer,182312,EUR,154965,EX,PT,Austria,L,Austria,100,"Python, Data Visualization, Statistics, MLOps",PhD,18,Telecommunications,2024-11-19,2024-12-11,1525,7.7,Smart Analytics -AI13190,Robotics Engineer,81783,USD,81783,MI,FL,Ireland,M,Israel,0,"Hadoop, Mathematics, MLOps",Master,2,Energy,2024-11-18,2025-01-03,1787,5.5,Cognitive Computing -AI13191,Computer Vision Engineer,283095,JPY,31140450,EX,PT,Japan,L,Japan,50,"Computer Vision, Python, MLOps, PyTorch",Bachelor,12,Manufacturing,2024-08-02,2024-08-28,2074,5.4,Future Systems -AI13192,AI Research Scientist,140169,EUR,119144,SE,CT,Austria,M,Austria,100,"PyTorch, Data Visualization, SQL",PhD,5,Retail,2025-01-20,2025-02-22,1103,7.7,Cognitive Computing -AI13193,Deep Learning Engineer,55566,EUR,47231,EN,CT,France,S,France,50,"Hadoop, Scala, Java",PhD,0,Energy,2024-06-03,2024-07-12,2240,7.9,Advanced Robotics -AI13194,ML Ops Engineer,312518,CHF,281266,EX,PT,Switzerland,L,New Zealand,50,"Python, GCP, NLP, SQL",Master,17,Finance,2024-09-23,2024-12-01,2430,5.9,Cloud AI Solutions -AI13195,Data Analyst,42317,USD,42317,EN,PT,South Korea,S,Russia,0,"GCP, Python, Git",Associate,0,Education,2025-02-05,2025-03-17,1394,10,Smart Analytics -AI13196,Autonomous Systems Engineer,115876,USD,115876,SE,CT,Finland,S,United States,0,"Git, Data Visualization, Deep Learning, MLOps",Bachelor,9,Energy,2025-03-20,2025-05-19,925,6,Cloud AI Solutions -AI13197,AI Software Engineer,59246,AUD,79982,EN,FT,Australia,L,Australia,0,"Docker, Spark, Data Visualization",PhD,0,Healthcare,2024-07-11,2024-08-30,830,9,Machine Intelligence Group -AI13198,Data Scientist,138647,GBP,103985,SE,PT,United Kingdom,M,Poland,50,"NLP, Docker, Kubernetes, Statistics",Master,7,Telecommunications,2024-03-21,2024-05-27,1264,6.5,Cloud AI Solutions -AI13199,AI Consultant,28360,USD,28360,EN,FL,China,M,Luxembourg,0,"Python, TensorFlow, PyTorch",Associate,0,Retail,2024-04-14,2024-05-08,1103,9.6,Cognitive Computing -AI13200,Autonomous Systems Engineer,197908,JPY,21769880,EX,FL,Japan,M,Japan,50,"Git, Linux, Azure, Data Visualization",Associate,16,Real Estate,2025-02-18,2025-04-15,1951,6.4,AI Innovations -AI13201,AI Software Engineer,181959,AUD,245645,EX,CT,Australia,S,Australia,50,"SQL, GCP, Azure, NLP, Spark",Associate,17,Consulting,2024-11-09,2024-12-19,1213,8.5,Machine Intelligence Group -AI13202,ML Ops Engineer,27691,USD,27691,EN,FL,India,M,India,100,"Kubernetes, TensorFlow, GCP, Statistics, Azure",Associate,1,Healthcare,2025-03-15,2025-04-13,1099,7.8,Quantum Computing Inc -AI13203,Research Scientist,142866,JPY,15715260,SE,CT,Japan,M,Japan,50,"Azure, AWS, Statistics, Scala",PhD,9,Government,2025-01-08,2025-01-24,2332,7.9,Smart Analytics -AI13204,Data Engineer,79744,CAD,99680,MI,PT,Canada,L,Japan,100,"Python, R, GCP, Azure, Spark",Bachelor,4,Real Estate,2024-01-13,2024-02-03,574,8.8,Autonomous Tech -AI13205,AI Architect,198736,USD,198736,EX,PT,United States,S,United States,0,"Linux, Mathematics, Git, NLP, Spark",Associate,18,Government,2024-09-01,2024-10-20,1551,7.1,Digital Transformation LLC -AI13206,Research Scientist,104891,USD,104891,MI,CT,Denmark,M,South Korea,100,"Data Visualization, Azure, GCP, SQL",Associate,2,Retail,2024-05-08,2024-07-17,1911,8.8,Machine Intelligence Group -AI13207,Data Scientist,61269,USD,61269,SE,FL,India,L,India,100,"PyTorch, TensorFlow, GCP",Bachelor,6,Real Estate,2024-01-08,2024-03-12,1695,6.8,AI Innovations -AI13208,Research Scientist,25071,USD,25071,MI,CT,India,S,India,50,"Linux, Deep Learning, Spark",Associate,2,Technology,2025-01-13,2025-03-08,1449,7.7,DeepTech Ventures -AI13209,Data Engineer,84490,CHF,76041,EN,FT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Tableau",PhD,0,Transportation,2024-06-22,2024-08-22,1823,7.3,Algorithmic Solutions -AI13210,AI Architect,58087,USD,58087,MI,PT,South Korea,S,Luxembourg,50,"NLP, Statistics, AWS, Kubernetes",Bachelor,2,Real Estate,2024-08-19,2024-09-29,2017,8.8,Future Systems -AI13211,Autonomous Systems Engineer,50417,EUR,42854,EN,CT,Austria,M,Austria,0,"Azure, Java, Data Visualization",PhD,0,Manufacturing,2024-05-04,2024-06-09,1748,7.7,Cloud AI Solutions -AI13212,AI Software Engineer,149113,SGD,193847,SE,CT,Singapore,M,Singapore,0,"Java, Docker, NLP, Statistics, Scala",Associate,7,Education,2025-01-17,2025-02-18,1353,8.8,Cognitive Computing -AI13213,AI Consultant,94092,EUR,79978,SE,PT,Austria,S,Austria,100,"Hadoop, Tableau, Computer Vision, Python",Bachelor,9,Finance,2024-07-03,2024-08-25,1449,8.6,TechCorp Inc -AI13214,Head of AI,185420,USD,185420,SE,PT,United States,L,Mexico,0,"SQL, Scala, Data Visualization",Associate,6,Consulting,2024-04-25,2024-07-03,1896,9.4,Autonomous Tech -AI13215,Data Analyst,93085,EUR,79122,MI,PT,Netherlands,M,Ghana,100,"Statistics, MLOps, Computer Vision, Java, AWS",Associate,3,Government,2025-01-13,2025-02-28,2006,10,Cognitive Computing -AI13216,NLP Engineer,102367,GBP,76775,MI,FL,United Kingdom,M,United Kingdom,0,"Azure, Spark, Docker",Master,3,Healthcare,2025-02-11,2025-04-14,2318,9.9,Advanced Robotics -AI13217,Machine Learning Engineer,213126,AUD,287720,EX,FT,Australia,L,Australia,100,"Python, Data Visualization, SQL, AWS",Master,18,Gaming,2025-02-17,2025-03-10,1670,5.7,Cognitive Computing -AI13218,Data Engineer,70624,USD,70624,MI,PT,South Korea,S,South Korea,100,"Linux, TensorFlow, Data Visualization",Associate,3,Transportation,2024-07-08,2024-09-13,511,7.5,Cognitive Computing -AI13219,Machine Learning Engineer,48905,EUR,41569,EN,FL,Netherlands,S,Vietnam,0,"Docker, Tableau, PyTorch, TensorFlow, NLP",Associate,1,Real Estate,2024-01-25,2024-03-01,847,9.9,Advanced Robotics -AI13220,Research Scientist,98101,JPY,10791110,SE,FL,Japan,S,Portugal,50,"SQL, Linux, R",PhD,8,Consulting,2024-05-23,2024-06-22,1283,7.4,Neural Networks Co -AI13221,AI Consultant,141464,EUR,120244,SE,PT,Austria,M,Austria,50,"MLOps, Data Visualization, Python, TensorFlow, Docker",Master,9,Automotive,2024-02-13,2024-04-10,1489,8.7,DeepTech Ventures -AI13222,AI Specialist,140338,USD,140338,SE,CT,United States,S,Colombia,0,"Hadoop, Kubernetes, MLOps, SQL",Bachelor,6,Education,2024-12-05,2025-01-05,1117,8,Quantum Computing Inc -AI13223,AI Research Scientist,102674,JPY,11294140,SE,FT,Japan,S,Japan,50,"Python, AWS, R",PhD,5,Automotive,2024-07-31,2024-10-02,503,9.4,Smart Analytics -AI13224,AI Consultant,50281,CAD,62851,EN,FL,Canada,M,Czech Republic,100,"Spark, TensorFlow, Python",PhD,1,Media,2024-05-19,2024-06-23,2064,6.4,AI Innovations -AI13225,ML Ops Engineer,126345,SGD,164249,SE,CT,Singapore,L,Singapore,0,"Python, Linux, Git, Computer Vision",Associate,6,Consulting,2025-01-09,2025-03-04,1300,6.5,Algorithmic Solutions -AI13226,Head of AI,310457,USD,310457,EX,FL,Denmark,M,Denmark,100,"Linux, Kubernetes, PyTorch, Hadoop, Azure",Bachelor,19,Energy,2024-08-04,2024-09-29,693,8,DataVision Ltd -AI13227,AI Architect,133886,USD,133886,SE,CT,Denmark,M,Mexico,100,"Python, NLP, Scala, Computer Vision",Associate,7,Real Estate,2024-07-06,2024-08-23,796,8.3,Cognitive Computing -AI13228,Research Scientist,266548,USD,266548,EX,FL,Finland,L,Finland,100,"Kubernetes, Azure, SQL, AWS",PhD,14,Real Estate,2024-03-04,2024-03-20,1603,5.2,Machine Intelligence Group -AI13229,ML Ops Engineer,45522,USD,45522,MI,FT,China,L,China,50,"Scala, Statistics, Data Visualization, Java, Mathematics",Bachelor,2,Telecommunications,2024-07-29,2024-09-04,534,9.7,Predictive Systems -AI13230,Principal Data Scientist,110658,GBP,82994,MI,PT,United Kingdom,L,United Kingdom,100,"Scala, Kubernetes, Spark, Docker",Associate,4,Transportation,2024-03-24,2024-06-01,2049,8.3,Digital Transformation LLC -AI13231,Research Scientist,80074,USD,80074,EN,FL,Denmark,L,Denmark,50,"Data Visualization, Linux, SQL",Bachelor,1,Manufacturing,2025-02-08,2025-03-10,1335,8,Machine Intelligence Group -AI13232,AI Architect,135856,USD,135856,SE,FL,Sweden,S,Sweden,100,"Azure, R, PyTorch, AWS",Associate,9,Government,2024-09-18,2024-10-02,2285,7.6,DeepTech Ventures -AI13233,Principal Data Scientist,116833,CAD,146041,SE,CT,Canada,S,Canada,50,"Tableau, Linux, AWS, MLOps",Bachelor,8,Consulting,2025-03-02,2025-05-07,1983,9.1,Quantum Computing Inc -AI13234,AI Architect,134634,USD,134634,MI,CT,United States,L,United States,0,"Kubernetes, Statistics, Spark",Master,2,Healthcare,2024-04-03,2024-05-07,1639,9.1,Cognitive Computing -AI13235,ML Ops Engineer,129280,CHF,116352,MI,FL,Switzerland,L,Switzerland,100,"Computer Vision, Tableau, TensorFlow, Python, Statistics",Master,4,Automotive,2024-06-19,2024-08-16,1739,9,AI Innovations -AI13236,Data Engineer,246914,USD,246914,EX,FL,Denmark,L,Thailand,50,"Java, PyTorch, Mathematics, NLP",Bachelor,17,Consulting,2024-11-09,2024-12-15,2011,5.5,Future Systems -AI13237,Research Scientist,94188,JPY,10360680,MI,FL,Japan,M,Turkey,100,"Linux, Python, MLOps, Hadoop, TensorFlow",PhD,4,Gaming,2024-03-17,2024-04-04,2004,6.4,Autonomous Tech -AI13238,Deep Learning Engineer,114774,AUD,154945,MI,FT,Australia,L,Australia,100,"Python, TensorFlow, NLP, Hadoop",Associate,4,Technology,2024-05-31,2024-08-05,1786,5.2,Smart Analytics -AI13239,ML Ops Engineer,59249,USD,59249,EN,CT,Ireland,L,Ireland,0,"SQL, R, Kubernetes",Master,1,Retail,2024-08-14,2024-08-28,516,8.2,DataVision Ltd -AI13240,Principal Data Scientist,81389,USD,81389,MI,PT,South Korea,L,Turkey,0,"SQL, Hadoop, Tableau, Data Visualization",Associate,2,Technology,2024-03-02,2024-05-04,892,7.9,DataVision Ltd -AI13241,Deep Learning Engineer,60315,USD,60315,EN,PT,United States,S,China,50,"Git, PyTorch, Kubernetes",Bachelor,1,Healthcare,2024-02-27,2024-03-25,902,7.3,Algorithmic Solutions -AI13242,Research Scientist,187520,SGD,243776,EX,PT,Singapore,M,Ghana,100,"Azure, Docker, SQL, Python",PhD,17,Finance,2025-04-09,2025-06-03,1424,6.4,AI Innovations -AI13243,Data Analyst,137040,USD,137040,MI,CT,Denmark,M,Denmark,0,"NLP, TensorFlow, Docker, GCP, Python",Master,3,Consulting,2024-08-30,2024-10-22,1172,5.7,DataVision Ltd -AI13244,Computer Vision Engineer,180365,SGD,234475,SE,FL,Singapore,L,Spain,0,"SQL, PyTorch, Tableau, MLOps",PhD,5,Healthcare,2024-08-04,2024-10-12,1304,6.4,AI Innovations -AI13245,AI Research Scientist,40180,USD,40180,EN,PT,China,L,China,50,"GCP, TensorFlow, Hadoop, Python, Kubernetes",Bachelor,1,Real Estate,2024-08-09,2024-09-10,1172,7.6,DeepTech Ventures -AI13246,AI Research Scientist,93313,JPY,10264430,MI,FL,Japan,S,Japan,50,"Python, Spark, Statistics, AWS, Mathematics",Master,2,Telecommunications,2025-01-12,2025-03-03,1062,6.3,Algorithmic Solutions -AI13247,Machine Learning Engineer,106766,SGD,138796,MI,FT,Singapore,M,Singapore,50,"Kubernetes, R, Docker, PyTorch, Git",Associate,3,Government,2024-01-27,2024-03-06,2237,6.4,Algorithmic Solutions -AI13248,Machine Learning Engineer,210437,USD,210437,EX,PT,Israel,L,Israel,100,"Tableau, Kubernetes, Java, Python",Bachelor,14,Telecommunications,2024-05-29,2024-07-18,2171,8,Cognitive Computing -AI13249,AI Product Manager,75988,JPY,8358680,MI,FT,Japan,S,Japan,100,"Kubernetes, NLP, Tableau, Data Visualization",PhD,2,Telecommunications,2024-03-05,2024-04-02,1882,5.4,Cognitive Computing -AI13250,Computer Vision Engineer,144385,JPY,15882350,SE,PT,Japan,S,Japan,50,"Deep Learning, Docker, Tableau, Kubernetes, Spark",Associate,6,Manufacturing,2024-09-04,2024-11-14,1730,7.3,Quantum Computing Inc -AI13251,NLP Engineer,90091,USD,90091,SE,CT,Israel,S,Japan,100,"TensorFlow, MLOps, AWS, Java",Bachelor,8,Finance,2024-06-28,2024-07-24,1937,5.9,Digital Transformation LLC -AI13252,Deep Learning Engineer,105779,USD,105779,SE,PT,Sweden,S,Sweden,0,"Azure, AWS, Computer Vision, Python, Docker",Bachelor,6,Transportation,2025-02-16,2025-04-04,2095,5.7,Quantum Computing Inc -AI13253,NLP Engineer,306666,USD,306666,EX,PT,Norway,L,Belgium,100,"Git, Mathematics, Spark, PyTorch, Statistics",PhD,15,Manufacturing,2024-12-16,2025-01-07,2167,6.7,DeepTech Ventures -AI13254,Machine Learning Researcher,53085,USD,53085,EN,PT,Finland,S,Finland,50,"Java, Tableau, Kubernetes",PhD,1,Telecommunications,2024-07-23,2024-09-23,1112,9.7,Future Systems -AI13255,AI Research Scientist,100104,EUR,85088,SE,FL,Austria,M,Denmark,0,"Python, Statistics, Hadoop",Master,5,Energy,2024-03-23,2024-04-24,1623,7,Predictive Systems -AI13256,NLP Engineer,271861,USD,271861,EX,FL,Norway,L,Norway,50,"Azure, Python, Java",Bachelor,15,Technology,2024-12-06,2025-02-01,2332,9.2,DeepTech Ventures -AI13257,Data Engineer,49399,USD,49399,EN,FT,South Korea,M,South Korea,50,"MLOps, Python, Tableau, AWS, Java",Associate,1,Energy,2024-06-19,2024-08-18,675,8.6,Smart Analytics -AI13258,Data Analyst,103468,JPY,11381480,SE,FT,Japan,S,Japan,100,"Hadoop, R, Scala",Associate,5,Technology,2024-08-24,2024-09-23,1561,9.3,Quantum Computing Inc -AI13259,Machine Learning Engineer,93578,USD,93578,MI,CT,United States,M,United States,50,"TensorFlow, AWS, Spark, Kubernetes, SQL",Associate,3,Retail,2024-11-07,2024-12-18,1889,9.3,Quantum Computing Inc -AI13260,Machine Learning Engineer,84233,EUR,71598,EN,CT,France,L,France,0,"Python, TensorFlow, Deep Learning, Statistics",PhD,1,Media,2024-07-11,2024-07-25,742,5.7,Cloud AI Solutions -AI13261,AI Consultant,112337,USD,112337,EN,CT,Denmark,L,Denmark,0,"Tableau, Linux, Kubernetes",PhD,1,Government,2024-07-11,2024-09-02,1248,9,Advanced Robotics -AI13262,AI Consultant,239391,USD,239391,EX,FT,Denmark,M,Sweden,50,"Hadoop, Scala, MLOps, R, Git",Bachelor,12,Energy,2025-04-29,2025-06-29,2480,5,DataVision Ltd -AI13263,Computer Vision Engineer,45215,USD,45215,EN,PT,South Korea,S,South Korea,0,"GCP, Linux, NLP, Hadoop",PhD,0,Media,2024-07-13,2024-09-13,1982,5.5,Neural Networks Co -AI13264,Machine Learning Researcher,48795,EUR,41476,EN,FT,France,S,Romania,50,"TensorFlow, Python, SQL, Kubernetes",Bachelor,1,Real Estate,2025-01-23,2025-03-11,1982,8.7,DataVision Ltd -AI13265,AI Consultant,119095,CHF,107186,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, Hadoop, GCP, Computer Vision, Azure",PhD,2,Telecommunications,2024-04-13,2024-05-30,958,8.9,Smart Analytics -AI13266,ML Ops Engineer,98669,GBP,74002,SE,CT,United Kingdom,S,United Kingdom,100,"MLOps, Python, Data Visualization",Master,9,Automotive,2024-05-10,2024-07-06,1095,8.3,TechCorp Inc -AI13267,AI Architect,128617,SGD,167202,SE,CT,Singapore,M,Netherlands,100,"Computer Vision, SQL, Data Visualization, Kubernetes, Docker",PhD,6,Retail,2024-08-17,2024-09-09,2213,8.5,DataVision Ltd -AI13268,Robotics Engineer,95556,USD,95556,MI,FT,Sweden,M,Sweden,0,"Kubernetes, Deep Learning, Linux",PhD,2,Manufacturing,2024-12-13,2025-01-31,1250,6.2,Advanced Robotics -AI13269,Machine Learning Engineer,200162,SGD,260211,EX,FL,Singapore,L,Singapore,50,"R, Spark, MLOps, Mathematics",PhD,11,Manufacturing,2025-01-23,2025-02-09,840,8.3,Autonomous Tech -AI13270,Principal Data Scientist,109357,EUR,92953,MI,PT,Netherlands,L,Norway,0,"NLP, Git, Java, MLOps",Associate,4,Government,2025-02-01,2025-03-30,2304,6.7,Quantum Computing Inc -AI13271,Head of AI,122021,USD,122021,MI,FT,Norway,M,United Kingdom,0,"Kubernetes, Python, Tableau",Master,2,Manufacturing,2024-08-19,2024-10-07,669,5.3,DataVision Ltd -AI13272,Head of AI,325087,CHF,292578,EX,PT,Switzerland,L,Ghana,100,"Python, Git, Tableau",Associate,11,Retail,2025-03-25,2025-05-21,2055,5.5,DataVision Ltd -AI13273,Machine Learning Engineer,168996,JPY,18589560,EX,FT,Japan,M,Chile,0,"Deep Learning, Scala, Spark, Python",Associate,16,Healthcare,2024-01-30,2024-03-25,1234,6.2,Digital Transformation LLC -AI13274,ML Ops Engineer,43570,USD,43570,EN,FT,South Korea,S,South Korea,50,"Java, SQL, Git, Data Visualization, Python",Master,0,Manufacturing,2024-03-31,2024-05-26,1032,6.9,Algorithmic Solutions -AI13275,AI Architect,149909,USD,149909,SE,PT,United States,L,United States,50,"GCP, Python, TensorFlow, Deep Learning, Tableau",PhD,9,Gaming,2025-03-25,2025-05-05,1503,5.8,Future Systems -AI13276,Computer Vision Engineer,82164,USD,82164,EN,FL,United States,S,Sweden,50,"TensorFlow, NLP, Linux, Statistics, Deep Learning",Bachelor,1,Transportation,2024-01-04,2024-01-27,1031,6,Digital Transformation LLC -AI13277,AI Consultant,92430,USD,92430,MI,CT,Israel,S,Brazil,100,"Data Visualization, Tableau, PyTorch, Python, Mathematics",Associate,4,Real Estate,2025-01-29,2025-02-12,1295,8.4,Autonomous Tech -AI13278,AI Specialist,49758,USD,49758,EN,FT,South Korea,S,South Korea,100,"R, Statistics, Hadoop, Git",Master,0,Healthcare,2024-11-03,2025-01-07,2206,7.6,Neural Networks Co -AI13279,AI Product Manager,74628,GBP,55971,EN,CT,United Kingdom,L,Russia,100,"Git, Hadoop, MLOps",PhD,1,Healthcare,2024-02-16,2024-03-14,1505,5.7,Cloud AI Solutions -AI13280,Robotics Engineer,128025,GBP,96019,MI,FT,United Kingdom,L,South Africa,50,"Python, Linux, Azure, Deep Learning",Master,2,Education,2024-03-30,2024-04-23,2160,7.1,Cognitive Computing -AI13281,Data Engineer,100244,EUR,85207,SE,CT,Germany,S,Netherlands,50,"R, SQL, Scala, Python",Master,8,Education,2024-08-14,2024-09-05,865,7,Future Systems -AI13282,Autonomous Systems Engineer,34992,USD,34992,MI,FL,India,S,Belgium,100,"PyTorch, Java, NLP",Associate,3,Retail,2024-02-17,2024-04-08,1855,9.9,DataVision Ltd -AI13283,AI Research Scientist,94904,EUR,80668,MI,CT,France,L,Israel,100,"GCP, Linux, Hadoop, Java",PhD,2,Healthcare,2024-05-04,2024-06-17,1361,9.8,Digital Transformation LLC -AI13284,Data Analyst,134647,JPY,14811170,EX,CT,Japan,S,Japan,0,"Kubernetes, Python, TensorFlow, Deep Learning",Associate,19,Automotive,2025-01-31,2025-03-28,1051,8.8,DataVision Ltd -AI13285,AI Consultant,47733,USD,47733,EN,FL,Finland,S,Argentina,50,"NLP, Python, Java, R, GCP",PhD,1,Transportation,2024-11-14,2024-12-17,2101,5.6,Neural Networks Co -AI13286,AI Research Scientist,126186,GBP,94640,SE,FT,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Deep Learning, Python, NLP",PhD,8,Manufacturing,2024-04-25,2024-06-21,706,5.2,Cloud AI Solutions -AI13287,Robotics Engineer,178018,USD,178018,EX,FL,Finland,M,Finland,50,"GCP, NLP, Scala, Java",Master,11,Education,2024-05-21,2024-06-30,600,6.7,AI Innovations -AI13288,Computer Vision Engineer,58807,EUR,49986,EN,FL,France,L,France,100,"Computer Vision, R, Python, Kubernetes, MLOps",Associate,1,Media,2024-06-09,2024-07-29,713,6.8,Cognitive Computing -AI13289,ML Ops Engineer,78517,EUR,66739,EN,FT,France,L,France,100,"GCP, Deep Learning, Linux",Master,0,Technology,2024-12-31,2025-02-15,692,9.8,Machine Intelligence Group -AI13290,Computer Vision Engineer,152471,EUR,129600,SE,FT,Germany,L,Germany,0,"Git, Statistics, Kubernetes, Linux, PyTorch",PhD,9,Automotive,2024-05-12,2024-05-28,632,6.8,DataVision Ltd -AI13291,AI Research Scientist,83053,USD,83053,EN,FT,Ireland,L,Ireland,0,"Kubernetes, Python, AWS, TensorFlow, Data Visualization",PhD,1,Transportation,2024-12-18,2025-02-03,1920,7.4,TechCorp Inc -AI13292,Deep Learning Engineer,55419,EUR,47106,EN,FL,Austria,S,Czech Republic,100,"Data Visualization, GCP, Kubernetes, R",Master,1,Real Estate,2025-01-19,2025-02-18,2179,8.7,Machine Intelligence Group -AI13293,Data Analyst,226088,CAD,282610,EX,CT,Canada,M,Latvia,0,"Tableau, Hadoop, Kubernetes, Mathematics, Scala",PhD,13,Retail,2024-02-24,2024-03-19,777,9.9,Cognitive Computing -AI13294,Machine Learning Researcher,140926,GBP,105695,SE,FT,United Kingdom,S,United Kingdom,100,"MLOps, PyTorch, Docker, Mathematics",Bachelor,5,Consulting,2024-03-17,2024-04-10,566,7.9,DataVision Ltd -AI13295,Machine Learning Researcher,97767,EUR,83102,SE,FT,Netherlands,S,Netherlands,50,"Linux, Git, MLOps, Computer Vision, Python",Associate,9,Automotive,2024-01-07,2024-02-23,1471,5.5,Neural Networks Co -AI13296,Data Scientist,100990,GBP,75743,SE,FL,United Kingdom,S,United Kingdom,100,"Python, Deep Learning, SQL, GCP",Associate,8,Technology,2024-10-31,2024-11-22,904,8.7,DeepTech Ventures -AI13297,Data Analyst,136795,GBP,102596,SE,PT,United Kingdom,M,United Kingdom,100,"MLOps, Hadoop, Scala, Linux, Java",Master,7,Telecommunications,2024-06-13,2024-06-29,2464,6.1,AI Innovations -AI13298,AI Architect,76815,USD,76815,MI,FT,Sweden,S,Sweden,100,"Mathematics, AWS, Hadoop, Deep Learning",Bachelor,3,Manufacturing,2024-09-24,2024-10-11,1123,5.5,Smart Analytics -AI13299,Head of AI,80644,USD,80644,EN,PT,United States,M,United States,50,"Python, TensorFlow, Tableau",PhD,1,Gaming,2024-08-17,2024-09-20,1924,10,TechCorp Inc -AI13300,Deep Learning Engineer,90240,JPY,9926400,MI,FL,Japan,S,Japan,50,"SQL, PyTorch, MLOps",Associate,3,Government,2024-09-16,2024-11-26,591,9.1,Machine Intelligence Group -AI13301,Machine Learning Engineer,199372,USD,199372,EX,PT,Norway,S,Luxembourg,0,"Python, Scala, NLP, Azure, Kubernetes",PhD,17,Technology,2024-07-05,2024-09-07,1177,8.6,Quantum Computing Inc -AI13302,Robotics Engineer,232839,EUR,197913,EX,CT,France,M,France,100,"Linux, GCP, R, Spark, Python",Master,10,Media,2024-12-12,2025-02-11,1555,6.9,Cloud AI Solutions -AI13303,AI Research Scientist,120541,USD,120541,MI,CT,Denmark,M,Denmark,100,"PyTorch, Kubernetes, Hadoop, NLP, GCP",Master,2,Consulting,2025-01-02,2025-01-30,2358,6.2,Predictive Systems -AI13304,ML Ops Engineer,94694,USD,94694,EN,CT,Norway,M,Romania,0,"Spark, Computer Vision, SQL",Associate,1,Gaming,2024-02-19,2024-05-02,1701,8.5,TechCorp Inc -AI13305,NLP Engineer,69183,AUD,93397,EN,PT,Australia,M,Japan,50,"Azure, Linux, PyTorch",Master,0,Finance,2024-08-25,2024-11-03,657,7.3,AI Innovations -AI13306,AI Software Engineer,101698,EUR,86443,SE,FT,Austria,M,China,100,"Linux, Python, Azure, TensorFlow, AWS",Master,6,Real Estate,2024-05-15,2024-06-20,976,7.9,Quantum Computing Inc -AI13307,Head of AI,131365,USD,131365,SE,FL,Israel,M,Israel,50,"Data Visualization, Spark, GCP, Docker",PhD,7,Gaming,2024-02-14,2024-04-15,1663,6.3,Quantum Computing Inc -AI13308,AI Consultant,130237,GBP,97678,SE,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, R, AWS",PhD,8,Finance,2024-01-14,2024-03-15,1184,10,TechCorp Inc -AI13309,AI Architect,171976,USD,171976,SE,FT,Ireland,L,Ireland,100,"Deep Learning, Azure, Spark",Associate,6,Energy,2024-04-23,2024-05-26,811,6.3,Quantum Computing Inc -AI13310,AI Product Manager,219348,USD,219348,EX,FT,Denmark,L,Denmark,50,"Python, TensorFlow, PyTorch, Docker, Statistics",Associate,18,Telecommunications,2024-02-28,2024-04-28,629,5.6,Autonomous Tech -AI13311,AI Research Scientist,215507,USD,215507,EX,FL,Israel,M,Israel,100,"Scala, TensorFlow, Azure, Python, PyTorch",PhD,19,Education,2024-07-10,2024-08-07,2042,7.6,Digital Transformation LLC -AI13312,Data Analyst,168512,USD,168512,SE,FL,Sweden,L,Canada,100,"GCP, Data Visualization, Python",PhD,7,Transportation,2024-04-23,2024-06-29,1881,9.1,Algorithmic Solutions -AI13313,AI Research Scientist,121328,JPY,13346080,SE,FL,Japan,S,Japan,0,"SQL, PyTorch, GCP, Tableau",Master,8,Real Estate,2024-04-18,2024-05-21,733,7.3,Machine Intelligence Group -AI13314,AI Software Engineer,289498,USD,289498,EX,PT,Denmark,M,Denmark,0,"Scala, GCP, Deep Learning, R",Associate,10,Healthcare,2024-12-23,2025-01-15,670,9.1,Digital Transformation LLC -AI13315,AI Research Scientist,109391,AUD,147678,SE,CT,Australia,S,Australia,50,"AWS, Kubernetes, Mathematics, Java",Bachelor,5,Technology,2024-07-09,2024-09-04,571,8.7,Neural Networks Co -AI13316,Head of AI,92796,USD,92796,MI,PT,South Korea,L,South Korea,100,"Data Visualization, TensorFlow, NLP, Kubernetes",Associate,4,Telecommunications,2024-02-15,2024-04-14,1608,9.6,Future Systems -AI13317,Computer Vision Engineer,254375,SGD,330688,EX,FT,Singapore,M,Singapore,0,"GCP, Scala, Git, R",Associate,19,Education,2024-05-08,2024-05-29,1024,6.5,Smart Analytics -AI13318,Machine Learning Researcher,64737,CAD,80921,MI,FL,Canada,S,Canada,0,"Git, Tableau, Python, Data Visualization, TensorFlow",Bachelor,2,Gaming,2024-01-31,2024-04-05,1165,6.2,Future Systems -AI13319,Robotics Engineer,101753,EUR,86490,SE,PT,Netherlands,S,Netherlands,50,"Kubernetes, NLP, Data Visualization, GCP, Linux",PhD,9,Real Estate,2025-04-07,2025-05-07,1334,7.5,Predictive Systems -AI13320,Autonomous Systems Engineer,208375,EUR,177119,EX,FT,Netherlands,M,Netherlands,100,"Git, Mathematics, Computer Vision",Bachelor,11,Education,2025-04-21,2025-06-24,977,9.1,Quantum Computing Inc -AI13321,Autonomous Systems Engineer,127596,AUD,172255,SE,FL,Australia,S,Netherlands,50,"SQL, PyTorch, Java",Master,6,Healthcare,2024-09-01,2024-11-02,2402,6.6,Digital Transformation LLC -AI13322,Data Analyst,231910,EUR,197124,EX,FL,France,L,France,50,"MLOps, PyTorch, Hadoop",Associate,12,Automotive,2024-09-29,2024-11-15,1309,9.4,Neural Networks Co -AI13323,ML Ops Engineer,40030,USD,40030,SE,FL,India,M,India,0,"GCP, Deep Learning, Kubernetes",Bachelor,5,Transportation,2024-11-08,2024-12-02,1632,5.6,Cloud AI Solutions -AI13324,AI Architect,108886,USD,108886,EX,FT,China,L,China,100,"NLP, Scala, SQL",Master,11,Technology,2024-03-22,2024-04-27,1355,6,DeepTech Ventures -AI13325,Data Scientist,25902,USD,25902,EN,PT,China,M,Romania,50,"TensorFlow, Linux, Hadoop",Bachelor,0,Technology,2024-12-03,2025-01-12,1563,6,Algorithmic Solutions -AI13326,AI Research Scientist,86757,AUD,117122,MI,CT,Australia,L,Australia,100,"Kubernetes, GCP, Data Visualization, Mathematics, SQL",Bachelor,3,Retail,2025-01-15,2025-03-04,1437,7,Smart Analytics -AI13327,Data Analyst,38963,USD,38963,MI,FT,China,M,China,0,"Kubernetes, Spark, Python, Linux, Mathematics",Associate,3,Automotive,2024-11-17,2024-12-02,1495,6.7,Machine Intelligence Group -AI13328,AI Architect,308292,CHF,277463,EX,FL,Switzerland,L,Switzerland,100,"Kubernetes, Spark, Tableau, Hadoop, Git",PhD,11,Education,2024-06-07,2024-07-04,1113,7.9,DeepTech Ventures -AI13329,AI Software Engineer,194259,CHF,174833,SE,FL,Switzerland,L,Ukraine,50,"Kubernetes, Scala, Statistics, Tableau, Spark",Associate,7,Gaming,2024-06-11,2024-07-30,2266,7.6,Algorithmic Solutions -AI13330,Machine Learning Researcher,90499,AUD,122174,EN,CT,Australia,L,Kenya,100,"Linux, Python, Mathematics, Kubernetes, Hadoop",PhD,0,Government,2025-02-01,2025-03-16,1479,7.1,Cognitive Computing -AI13331,AI Research Scientist,152866,EUR,129936,EX,FT,Netherlands,S,Nigeria,0,"Git, Linux, Kubernetes, Python",PhD,14,Consulting,2024-02-13,2024-04-24,1604,5.9,Future Systems -AI13332,AI Consultant,207262,USD,207262,EX,FT,Norway,M,United States,0,"PyTorch, TensorFlow, Spark, Python, Hadoop",Master,19,Media,2025-04-07,2025-06-18,1968,9,Quantum Computing Inc -AI13333,Autonomous Systems Engineer,97380,CAD,121725,MI,FT,Canada,L,Russia,100,"R, MLOps, Data Visualization, SQL, Mathematics",Bachelor,4,Consulting,2024-06-21,2024-07-13,2191,5.9,Algorithmic Solutions -AI13334,AI Software Engineer,163759,USD,163759,SE,PT,Denmark,L,Denmark,0,"Kubernetes, Docker, Scala, Hadoop, Statistics",Associate,5,Real Estate,2024-03-04,2024-04-02,2380,6.1,Digital Transformation LLC -AI13335,Machine Learning Researcher,121421,EUR,103208,SE,FL,France,S,France,0,"Java, Linux, Tableau, MLOps, Statistics",Associate,6,Telecommunications,2025-04-01,2025-05-06,595,7.4,Future Systems -AI13336,Data Engineer,43568,EUR,37033,EN,PT,France,S,China,50,"Statistics, GCP, Data Visualization, Java",Bachelor,0,Technology,2024-04-02,2024-06-09,880,9.1,Machine Intelligence Group -AI13337,Research Scientist,119350,USD,119350,EX,FT,China,L,China,0,"Java, NLP, Python, Kubernetes",Associate,10,Healthcare,2024-02-11,2024-03-29,1105,9.2,Predictive Systems -AI13338,Computer Vision Engineer,95494,USD,95494,SE,PT,South Korea,S,South Korea,50,"Python, TensorFlow, Java",Associate,6,Energy,2024-04-16,2024-05-16,2058,6,Predictive Systems -AI13339,Deep Learning Engineer,62202,EUR,52872,EN,CT,Germany,S,Germany,50,"Scala, SQL, Python, Java, NLP",Master,1,Media,2025-04-17,2025-06-22,997,6.6,TechCorp Inc -AI13340,AI Consultant,88967,USD,88967,EN,PT,Sweden,L,Turkey,50,"TensorFlow, Azure, Deep Learning, Computer Vision, Linux",PhD,1,Real Estate,2024-12-20,2025-02-09,2438,7.1,Autonomous Tech -AI13341,Robotics Engineer,63313,CAD,79141,EN,FT,Canada,M,Canada,100,"Kubernetes, PyTorch, Mathematics, Computer Vision, GCP",Bachelor,1,Telecommunications,2024-12-24,2025-02-28,1312,7.3,Quantum Computing Inc -AI13342,Autonomous Systems Engineer,59228,CAD,74035,EN,PT,Canada,S,Canada,0,"TensorFlow, Python, Java, Spark, Kubernetes",Associate,0,Retail,2024-07-23,2024-09-19,924,8.8,Algorithmic Solutions -AI13343,Autonomous Systems Engineer,125001,USD,125001,SE,CT,Israel,S,Israel,100,"AWS, Spark, Data Visualization, Git",Associate,8,Energy,2024-08-01,2024-09-07,1524,6.6,TechCorp Inc -AI13344,Principal Data Scientist,36642,USD,36642,EN,PT,China,L,China,100,"Python, Scala, Java",Master,0,Telecommunications,2024-10-28,2024-12-27,1096,5.9,Neural Networks Co -AI13345,Principal Data Scientist,113963,USD,113963,MI,PT,Denmark,M,Denmark,100,"Python, Data Visualization, AWS, Spark",PhD,2,Energy,2024-07-20,2024-09-26,1472,8.2,Autonomous Tech -AI13346,Machine Learning Engineer,135609,USD,135609,SE,FT,Denmark,M,Luxembourg,100,"R, Tableau, Statistics, NLP",Master,8,Healthcare,2024-01-29,2024-03-21,1855,8.7,AI Innovations -AI13347,Deep Learning Engineer,129508,GBP,97131,SE,FT,United Kingdom,M,United Kingdom,0,"Linux, Docker, PyTorch, R",Master,9,Transportation,2024-09-28,2024-11-13,1340,9,AI Innovations -AI13348,Head of AI,222566,JPY,24482260,EX,PT,Japan,S,Japan,0,"Docker, Deep Learning, SQL, MLOps",PhD,11,Gaming,2024-05-13,2024-07-15,766,6.3,Machine Intelligence Group -AI13349,AI Architect,263402,JPY,28974220,EX,PT,Japan,L,Japan,0,"Kubernetes, Java, R, Statistics",Associate,11,Education,2024-09-18,2024-10-15,2271,6.6,AI Innovations -AI13350,Computer Vision Engineer,60120,GBP,45090,EN,FL,United Kingdom,S,Ukraine,0,"MLOps, Computer Vision, GCP, Kubernetes",PhD,1,Telecommunications,2025-03-03,2025-05-10,1798,6.9,Autonomous Tech -AI13351,Machine Learning Engineer,76589,USD,76589,MI,FT,Finland,S,Finland,100,"Kubernetes, Git, SQL",Associate,2,Real Estate,2024-08-18,2024-10-29,2474,9.2,Algorithmic Solutions -AI13352,Deep Learning Engineer,73963,USD,73963,EN,FL,United States,L,United States,50,"Python, TensorFlow, Azure, Spark, PyTorch",Master,1,Finance,2024-09-24,2024-10-19,714,9.9,Quantum Computing Inc -AI13353,Machine Learning Researcher,320290,USD,320290,EX,FT,Denmark,L,Denmark,100,"Hadoop, Python, Scala, AWS",Bachelor,13,Media,2024-11-02,2024-12-29,1220,5.6,DeepTech Ventures -AI13354,Deep Learning Engineer,148841,JPY,16372510,SE,FL,Japan,L,Russia,0,"Kubernetes, Scala, Java, Spark, R",Associate,8,Real Estate,2024-07-22,2024-08-20,828,6.6,Neural Networks Co -AI13355,Head of AI,111086,USD,111086,EN,FL,Denmark,L,Denmark,100,"Computer Vision, Azure, Python, TensorFlow, GCP",Master,1,Automotive,2024-06-01,2024-07-19,2404,7,AI Innovations -AI13356,Computer Vision Engineer,259096,USD,259096,EX,FL,United States,M,United States,50,"Spark, Statistics, NLP, Python",Bachelor,17,Telecommunications,2024-07-23,2024-08-08,1084,7,Quantum Computing Inc -AI13357,Computer Vision Engineer,90325,CAD,112906,MI,PT,Canada,L,New Zealand,100,"Kubernetes, Deep Learning, Python, Data Visualization",Bachelor,4,Healthcare,2024-09-05,2024-10-04,1127,5.4,TechCorp Inc -AI13358,AI Product Manager,92718,SGD,120533,MI,CT,Singapore,L,Singapore,0,"Python, MLOps, Tableau, TensorFlow",Associate,2,Manufacturing,2024-07-11,2024-09-07,893,9.6,DeepTech Ventures -AI13359,Deep Learning Engineer,124245,USD,124245,SE,PT,Israel,M,Israel,0,"PyTorch, TensorFlow, Mathematics",Bachelor,6,Energy,2025-01-10,2025-02-16,2472,5,Cloud AI Solutions -AI13360,Data Scientist,235413,GBP,176560,EX,FT,United Kingdom,S,United Kingdom,0,"Java, Hadoop, Tableau",Bachelor,12,Education,2025-02-11,2025-03-15,1436,8,Quantum Computing Inc -AI13361,Machine Learning Engineer,137922,EUR,117234,SE,PT,France,L,France,0,"AWS, Kubernetes, MLOps, Scala, Python",Bachelor,9,Telecommunications,2024-09-11,2024-11-20,2186,9.5,Future Systems -AI13362,Data Scientist,123420,USD,123420,MI,FT,United States,M,United States,100,"Mathematics, SQL, PyTorch, GCP",Bachelor,3,Energy,2024-10-30,2024-12-31,855,8.3,Advanced Robotics -AI13363,AI Software Engineer,234411,USD,234411,EX,PT,Israel,L,Russia,50,"Spark, Computer Vision, Docker, Data Visualization, R",Bachelor,16,Manufacturing,2024-08-28,2024-09-24,2452,6.8,DataVision Ltd -AI13364,Deep Learning Engineer,28209,USD,28209,MI,PT,India,S,India,100,"Azure, Scala, Mathematics, Linux, SQL",Master,3,Transportation,2025-02-06,2025-03-31,1105,9.3,Future Systems -AI13365,Machine Learning Engineer,77044,USD,77044,EN,FL,Norway,S,France,100,"Azure, AWS, Git",PhD,1,Transportation,2025-01-31,2025-03-24,852,5.4,Autonomous Tech -AI13366,Principal Data Scientist,126485,JPY,13913350,SE,FT,Japan,M,Japan,50,"SQL, Kubernetes, PyTorch, Tableau, Deep Learning",Associate,8,Technology,2024-10-05,2024-12-04,2474,5.5,Neural Networks Co -AI13367,NLP Engineer,75977,USD,75977,EN,FL,Ireland,L,Ireland,50,"R, Git, TensorFlow, Computer Vision, Spark",PhD,1,Media,2024-10-09,2024-12-10,1540,7.5,AI Innovations -AI13368,Data Engineer,53042,EUR,45086,EN,CT,Austria,M,Mexico,0,"Python, TensorFlow, Scala, Azure",Associate,0,Education,2024-01-28,2024-03-09,1094,8.1,Digital Transformation LLC -AI13369,AI Product Manager,88798,EUR,75478,MI,FL,Netherlands,M,Nigeria,0,"Deep Learning, Azure, MLOps",Bachelor,3,Technology,2024-07-01,2024-07-26,2121,5.7,Cloud AI Solutions -AI13370,Autonomous Systems Engineer,133645,EUR,113598,EX,PT,Austria,S,Austria,0,"Spark, Python, TensorFlow",Bachelor,18,Retail,2024-06-05,2024-06-24,2153,9.9,Cloud AI Solutions -AI13371,Machine Learning Engineer,123940,USD,123940,SE,CT,Sweden,L,Sweden,50,"Computer Vision, NLP, Scala, Python, Kubernetes",Associate,8,Transportation,2024-03-08,2024-03-25,2348,8.9,Smart Analytics -AI13372,AI Product Manager,250927,USD,250927,EX,FL,Finland,L,Finland,50,"Python, Kubernetes, Tableau, Hadoop, Data Visualization",Master,11,Healthcare,2025-02-12,2025-03-07,1895,7.2,Algorithmic Solutions -AI13373,AI Research Scientist,68177,SGD,88630,EN,FL,Singapore,S,Singapore,0,"Tableau, SQL, Statistics, TensorFlow, Docker",Bachelor,0,Finance,2024-05-18,2024-07-12,1152,7.8,TechCorp Inc -AI13374,AI Software Engineer,92501,USD,92501,MI,FL,Israel,L,Israel,100,"Python, TensorFlow, Scala, Hadoop",Associate,2,Real Estate,2025-02-24,2025-04-21,535,7.1,Neural Networks Co -AI13375,Computer Vision Engineer,117573,EUR,99937,SE,CT,Netherlands,M,Indonesia,50,"Azure, GCP, Scala, Mathematics, Spark",Master,5,Real Estate,2024-09-24,2024-10-13,1801,7.8,Autonomous Tech -AI13376,AI Software Engineer,48867,USD,48867,EN,FL,South Korea,M,South Korea,100,"Data Visualization, Linux, AWS, PyTorch, Java",Master,1,Gaming,2024-04-10,2024-05-06,1455,8.8,Quantum Computing Inc -AI13377,AI Product Manager,65451,AUD,88359,EN,CT,Australia,S,Australia,50,"Hadoop, Data Visualization, TensorFlow, Mathematics, Azure",Associate,1,Transportation,2025-02-28,2025-04-18,973,8.5,Smart Analytics -AI13378,NLP Engineer,96257,EUR,81818,SE,CT,Austria,M,Thailand,100,"Scala, Linux, Tableau, Data Visualization",Bachelor,9,Technology,2024-11-22,2025-01-31,2016,9.9,DeepTech Ventures -AI13379,Computer Vision Engineer,64758,USD,64758,MI,FL,Israel,S,Israel,50,"Tableau, Spark, GCP, PyTorch, Data Visualization",Associate,4,Telecommunications,2024-07-17,2024-08-06,1475,9.7,Cognitive Computing -AI13380,AI Architect,76008,EUR,64607,EN,CT,Germany,M,Hungary,50,"Tableau, Kubernetes, Data Visualization",PhD,0,Manufacturing,2024-02-26,2024-04-03,2311,7.7,Future Systems -AI13381,ML Ops Engineer,61682,EUR,52430,EN,CT,Netherlands,S,Netherlands,50,"Python, Docker, Hadoop",PhD,0,Energy,2024-02-28,2024-03-27,1643,9.9,Cloud AI Solutions -AI13382,AI Specialist,193425,USD,193425,EX,FL,Ireland,S,Ireland,0,"NLP, PyTorch, Statistics, Spark, Mathematics",Bachelor,19,Media,2024-11-23,2024-12-24,1129,9.6,Advanced Robotics -AI13383,Computer Vision Engineer,96082,EUR,81670,SE,FL,France,M,France,0,"PyTorch, Mathematics, Python",Master,9,Energy,2024-08-15,2024-10-24,2178,6.7,Cloud AI Solutions -AI13384,AI Research Scientist,118266,CHF,106439,MI,CT,Switzerland,M,Turkey,50,"SQL, Mathematics, Spark, Kubernetes",Bachelor,3,Finance,2024-07-29,2024-09-22,1546,10,TechCorp Inc -AI13385,Head of AI,92143,AUD,124393,EN,FT,Australia,L,Australia,100,"Git, Docker, Kubernetes, Spark, GCP",Associate,1,Government,2024-03-27,2024-04-11,1750,5.5,Neural Networks Co -AI13386,Computer Vision Engineer,53657,SGD,69754,EN,FL,Singapore,S,Singapore,100,"PyTorch, GCP, Python",PhD,1,Gaming,2024-10-03,2024-11-27,1961,6.1,Predictive Systems -AI13387,AI Software Engineer,219960,USD,219960,EX,FT,United States,M,United States,100,"SQL, PyTorch, Kubernetes",Bachelor,17,Automotive,2024-03-14,2024-04-01,1905,8.2,Digital Transformation LLC -AI13388,AI Software Engineer,227427,USD,227427,EX,FT,Ireland,S,Ireland,0,"Scala, Git, Hadoop",Bachelor,15,Finance,2025-03-05,2025-03-23,1930,7.2,Machine Intelligence Group -AI13389,AI Research Scientist,140704,USD,140704,EX,PT,South Korea,L,South Korea,100,"SQL, Python, PyTorch, Azure, Mathematics",Bachelor,19,Retail,2024-10-08,2024-11-30,1659,6,Predictive Systems -AI13390,AI Architect,90170,USD,90170,EN,FL,Denmark,S,Norway,0,"R, Hadoop, Mathematics",PhD,1,Automotive,2025-01-27,2025-02-18,1589,7.9,Smart Analytics -AI13391,AI Architect,75174,AUD,101485,MI,FT,Australia,S,Australia,100,"GCP, Python, Tableau, MLOps",Associate,2,Consulting,2024-06-18,2024-07-25,2007,7.6,Digital Transformation LLC -AI13392,Data Scientist,98977,EUR,84130,MI,CT,Germany,S,Germany,100,"Deep Learning, Spark, Python",Associate,2,Retail,2025-02-10,2025-04-06,760,6.2,Advanced Robotics -AI13393,Data Engineer,92614,USD,92614,EN,PT,Norway,L,Norway,100,"SQL, Linux, MLOps, Python, GCP",Bachelor,1,Real Estate,2024-04-27,2024-06-06,2066,8,Advanced Robotics -AI13394,Research Scientist,24682,USD,24682,EN,CT,China,S,China,0,"AWS, Linux, TensorFlow",Bachelor,0,Government,2024-07-20,2024-09-27,1943,8.2,Neural Networks Co -AI13395,Head of AI,169552,USD,169552,EX,FT,Finland,S,Finland,100,"TensorFlow, Python, Tableau",Bachelor,11,Finance,2024-08-15,2024-10-27,1956,7.4,Digital Transformation LLC -AI13396,ML Ops Engineer,152388,EUR,129530,EX,PT,Germany,M,Germany,0,"PyTorch, GCP, Azure, SQL, Mathematics",Bachelor,14,Government,2024-05-28,2024-06-13,1778,7.6,Cognitive Computing -AI13397,Research Scientist,56108,EUR,47692,EN,FL,Netherlands,S,Netherlands,50,"NLP, Python, Java",Master,0,Automotive,2025-02-17,2025-04-14,576,5.4,Machine Intelligence Group -AI13398,AI Consultant,185781,USD,185781,SE,CT,Norway,M,Norway,100,"Computer Vision, Kubernetes, NLP, Java, TensorFlow",Bachelor,6,Real Estate,2024-03-26,2024-05-19,1329,9.7,AI Innovations -AI13399,ML Ops Engineer,175075,SGD,227598,EX,PT,Singapore,S,Singapore,0,"Spark, PyTorch, Docker, SQL",Associate,18,Telecommunications,2025-03-27,2025-05-23,588,6.2,DataVision Ltd -AI13400,AI Specialist,69174,USD,69174,EN,PT,United States,M,United States,100,"Kubernetes, Spark, Python, Java",PhD,0,Telecommunications,2024-03-20,2024-04-08,1954,9.9,Cognitive Computing -AI13401,Data Engineer,114304,CHF,102874,EN,FT,Switzerland,L,Switzerland,50,"R, Python, Mathematics, Java",Associate,0,Energy,2024-06-02,2024-06-16,634,7.5,Neural Networks Co -AI13402,AI Specialist,205622,EUR,174779,EX,FL,Netherlands,M,Netherlands,100,"Mathematics, SQL, Data Visualization",PhD,18,Healthcare,2025-04-11,2025-05-27,501,8,Quantum Computing Inc -AI13403,Computer Vision Engineer,162908,EUR,138472,SE,FT,France,L,Argentina,100,"Scala, Docker, Statistics",PhD,7,Consulting,2024-07-19,2024-09-19,2059,7,Autonomous Tech -AI13404,Principal Data Scientist,357781,USD,357781,EX,PT,Denmark,L,Denmark,100,"Python, TensorFlow, AWS, Computer Vision, Statistics",Associate,10,Government,2025-03-02,2025-03-25,994,10,DeepTech Ventures -AI13405,ML Ops Engineer,204495,USD,204495,EX,CT,Sweden,M,Sweden,0,"Python, Docker, Data Visualization",PhD,10,Telecommunications,2024-06-16,2024-07-08,2403,9.1,DeepTech Ventures -AI13406,AI Software Engineer,70678,GBP,53009,EN,FL,United Kingdom,M,United Kingdom,100,"Python, Hadoop, Git, TensorFlow, Statistics",Associate,0,Automotive,2025-04-30,2025-06-01,1363,7.6,Machine Intelligence Group -AI13407,Machine Learning Engineer,114963,EUR,97719,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Data Visualization, SQL, TensorFlow, Java",Master,4,Telecommunications,2024-09-17,2024-10-16,905,6.7,Future Systems -AI13408,Research Scientist,67163,USD,67163,EX,FL,India,S,India,100,"TensorFlow, Deep Learning, Tableau",Bachelor,17,Education,2025-04-03,2025-05-16,1435,8.1,Autonomous Tech -AI13409,Machine Learning Engineer,211419,SGD,274845,EX,FL,Singapore,S,Switzerland,100,"Hadoop, Java, NLP, TensorFlow, Kubernetes",PhD,12,Technology,2024-12-17,2025-01-05,1204,9.8,DataVision Ltd -AI13410,AI Software Engineer,134096,USD,134096,SE,FT,Sweden,L,Sweden,50,"Deep Learning, Docker, GCP, Data Visualization, AWS",Bachelor,6,Gaming,2025-01-27,2025-03-15,2282,5.1,Autonomous Tech -AI13411,AI Architect,146850,USD,146850,SE,PT,Finland,L,Finland,100,"Mathematics, PyTorch, Hadoop, Spark, TensorFlow",Master,8,Automotive,2024-04-28,2024-05-15,1904,7.5,Autonomous Tech -AI13412,Robotics Engineer,67285,JPY,7401350,EN,CT,Japan,M,Egypt,100,"NLP, Deep Learning, Hadoop, Computer Vision",Associate,0,Energy,2024-06-10,2024-07-11,1776,9.8,Future Systems -AI13413,Data Scientist,287563,USD,287563,EX,FL,United States,M,Spain,50,"Python, TensorFlow, Git, Hadoop",PhD,10,Energy,2024-10-21,2024-12-06,1959,5.3,DataVision Ltd -AI13414,Data Analyst,86376,USD,86376,MI,FT,Israel,L,Israel,50,"TensorFlow, Data Visualization, Statistics",Associate,3,Telecommunications,2024-04-21,2024-06-24,821,5.2,Digital Transformation LLC -AI13415,Data Engineer,78208,USD,78208,SE,FL,South Korea,S,South Korea,50,"GCP, PyTorch, NLP, MLOps, Java",Bachelor,7,Government,2024-06-13,2024-08-21,2037,6.7,Predictive Systems -AI13416,AI Research Scientist,83692,USD,83692,MI,CT,United States,S,Poland,100,"Git, Tableau, Data Visualization, Kubernetes",Master,2,Real Estate,2024-03-31,2024-05-15,1315,8.6,Autonomous Tech -AI13417,Robotics Engineer,143315,USD,143315,EX,FT,Ireland,M,Ireland,100,"Linux, Data Visualization, Docker",Associate,16,Healthcare,2024-10-09,2024-10-29,1430,8.1,Cognitive Computing -AI13418,AI Architect,75949,AUD,102531,EN,FL,Australia,L,Australia,0,"R, PyTorch, Docker",Bachelor,0,Technology,2024-11-21,2025-01-14,1323,5.7,Smart Analytics -AI13419,AI Architect,124751,EUR,106038,SE,FL,France,M,France,50,"Python, TensorFlow, Data Visualization, Hadoop",PhD,7,Healthcare,2024-10-23,2024-12-08,866,5.4,AI Innovations -AI13420,NLP Engineer,189998,EUR,161498,EX,FT,Netherlands,L,Ghana,50,"Kubernetes, SQL, Data Visualization, MLOps, PyTorch",Associate,17,Real Estate,2024-08-31,2024-09-23,1284,6.9,Advanced Robotics -AI13421,Data Engineer,193193,EUR,164214,EX,CT,France,L,France,50,"Linux, Azure, SQL, R, Java",Associate,14,Healthcare,2024-06-21,2024-07-10,1148,8.1,Digital Transformation LLC -AI13422,AI Consultant,180069,SGD,234090,EX,PT,Singapore,L,Singapore,50,"PyTorch, GCP, Hadoop",Master,11,Consulting,2024-09-29,2024-11-16,2011,7.2,Digital Transformation LLC -AI13423,Deep Learning Engineer,202205,USD,202205,EX,FT,Israel,L,Israel,0,"PyTorch, Spark, Python",PhD,14,Energy,2024-12-20,2025-01-21,1805,8.6,Advanced Robotics -AI13424,NLP Engineer,84851,USD,84851,EN,FL,Sweden,L,Sweden,50,"Kubernetes, Tableau, TensorFlow, GCP, Python",PhD,1,Gaming,2024-01-23,2024-02-26,691,7.6,Quantum Computing Inc -AI13425,Autonomous Systems Engineer,100135,GBP,75101,MI,FL,United Kingdom,S,United Kingdom,0,"Computer Vision, Scala, PyTorch, Linux",Associate,4,Retail,2024-06-22,2024-07-08,942,5.8,Smart Analytics -AI13426,Principal Data Scientist,149157,EUR,126783,SE,FT,Netherlands,L,Netherlands,0,"GCP, Docker, Data Visualization, Scala",Associate,9,Energy,2024-07-08,2024-09-14,2036,5.2,Quantum Computing Inc -AI13427,Data Engineer,255277,CAD,319096,EX,CT,Canada,L,Canada,50,"Kubernetes, NLP, R, Deep Learning",Bachelor,17,Retail,2024-08-22,2024-09-28,530,5,Advanced Robotics -AI13428,NLP Engineer,118601,CHF,106741,EN,CT,Switzerland,L,Switzerland,50,"Kubernetes, Git, SQL, TensorFlow",Master,1,Government,2024-07-25,2024-09-22,2069,5.3,TechCorp Inc -AI13429,AI Specialist,204430,AUD,275981,EX,FL,Australia,M,South Africa,0,"TensorFlow, Python, NLP, AWS, Git",Bachelor,16,Gaming,2024-05-25,2024-07-13,2183,8.1,Neural Networks Co -AI13430,AI Specialist,148777,USD,148777,SE,FT,Norway,S,India,0,"Java, Linux, PyTorch, NLP, Kubernetes",Master,5,Telecommunications,2025-04-24,2025-06-11,1673,8.5,Digital Transformation LLC -AI13431,AI Software Engineer,280124,USD,280124,EX,PT,Norway,L,Turkey,50,"Tableau, Data Visualization, Java, TensorFlow",PhD,19,Automotive,2024-12-15,2025-01-22,617,5.6,Advanced Robotics -AI13432,AI Software Engineer,68849,EUR,58522,EN,PT,Germany,L,Germany,100,"MLOps, Hadoop, Spark",Master,1,Energy,2025-03-14,2025-04-03,2099,8.6,Machine Intelligence Group -AI13433,AI Research Scientist,29926,USD,29926,MI,FT,India,L,India,50,"Statistics, Azure, Spark, PyTorch, Deep Learning",Master,4,Education,2024-05-06,2024-07-01,1172,7.6,Future Systems -AI13434,ML Ops Engineer,70863,USD,70863,EN,FT,Israel,L,Israel,50,"R, MLOps, SQL",PhD,0,Manufacturing,2025-02-23,2025-04-18,1950,7.9,Quantum Computing Inc -AI13435,Research Scientist,63834,USD,63834,EN,CT,Israel,M,Israel,0,"Java, GCP, MLOps, Deep Learning",Master,0,Transportation,2024-04-30,2024-07-09,922,9.3,Digital Transformation LLC -AI13436,Deep Learning Engineer,332210,CHF,298989,EX,FT,Switzerland,M,South Africa,100,"GCP, Deep Learning, Git",PhD,15,Energy,2025-02-03,2025-03-22,2134,10,Quantum Computing Inc -AI13437,AI Product Manager,67710,USD,67710,EN,PT,Denmark,S,Sweden,0,"Statistics, Linux, Data Visualization",Master,0,Manufacturing,2024-12-29,2025-02-24,1974,9.9,Future Systems -AI13438,Data Scientist,129621,EUR,110178,EX,CT,Austria,M,Argentina,0,"Git, Docker, Java, R, Hadoop",Bachelor,15,Real Estate,2024-01-25,2024-03-27,2066,9.4,Advanced Robotics -AI13439,Research Scientist,84399,USD,84399,MI,FL,Ireland,L,Switzerland,0,"AWS, MLOps, Python",Bachelor,4,Energy,2024-05-01,2024-07-01,1456,8.2,Machine Intelligence Group -AI13440,Research Scientist,140977,GBP,105733,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, PyTorch, Java",PhD,9,Media,2024-07-26,2024-10-04,1604,7.4,TechCorp Inc -AI13441,Research Scientist,130649,CHF,117584,EN,CT,Switzerland,L,Switzerland,0,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Retail,2024-04-03,2024-05-07,1426,5.7,Machine Intelligence Group -AI13442,AI Product Manager,94972,EUR,80726,MI,PT,France,L,New Zealand,100,"SQL, MLOps, Computer Vision, Linux, GCP",Bachelor,4,Consulting,2024-05-18,2024-06-12,1705,7.4,Predictive Systems -AI13443,AI Specialist,176030,EUR,149626,EX,PT,Austria,S,Finland,50,"Git, Scala, AWS",Master,18,Real Estate,2024-04-14,2024-06-13,1595,7.6,DeepTech Ventures -AI13444,Research Scientist,101314,USD,101314,SE,PT,Israel,M,Israel,100,"Linux, Spark, Computer Vision, MLOps, Python",PhD,9,Telecommunications,2024-10-10,2024-11-28,1405,6,Cloud AI Solutions -AI13445,AI Consultant,59806,EUR,50835,EN,PT,Germany,S,Germany,0,"Docker, Scala, Statistics",Associate,1,Consulting,2025-01-08,2025-01-24,965,6.3,Neural Networks Co -AI13446,Data Analyst,106748,USD,106748,SE,PT,Israel,S,Netherlands,100,"Scala, Python, Computer Vision, Tableau",Bachelor,5,Education,2024-04-23,2024-06-05,1187,7.4,TechCorp Inc -AI13447,Autonomous Systems Engineer,49405,CAD,61756,EN,PT,Canada,M,Canada,0,"Linux, Python, Tableau",PhD,0,Automotive,2025-01-10,2025-02-22,2350,5,Digital Transformation LLC -AI13448,Data Scientist,230116,SGD,299151,EX,PT,Singapore,L,Turkey,100,"Python, Java, Computer Vision, TensorFlow, GCP",Bachelor,18,Energy,2024-12-25,2025-02-15,1605,8,Autonomous Tech -AI13449,AI Specialist,155786,EUR,132418,SE,FL,Netherlands,M,United States,50,"NLP, SQL, MLOps",Bachelor,8,Education,2024-01-02,2024-01-26,1425,8.5,AI Innovations -AI13450,Data Scientist,78295,EUR,66551,MI,PT,Germany,M,Germany,0,"Scala, Python, Tableau, NLP, MLOps",Master,4,Technology,2024-08-02,2024-08-31,2422,6.2,Machine Intelligence Group -AI13451,ML Ops Engineer,116184,USD,116184,MI,CT,Ireland,L,Czech Republic,0,"SQL, MLOps, TensorFlow, Git, Data Visualization",PhD,4,Gaming,2024-03-22,2024-05-06,1048,8.4,DeepTech Ventures -AI13452,Machine Learning Engineer,70480,USD,70480,EN,FT,United States,S,United States,50,"Mathematics, Statistics, TensorFlow, PyTorch",Master,1,Media,2024-02-26,2024-03-24,1238,9.2,Quantum Computing Inc -AI13453,Machine Learning Engineer,257142,EUR,218571,EX,FL,France,L,South Korea,50,"Python, Kubernetes, GCP, R",PhD,10,Retail,2024-04-19,2024-05-06,2218,9.8,Advanced Robotics -AI13454,Head of AI,75895,CHF,68306,EN,PT,Switzerland,M,Spain,0,"Hadoop, AWS, Tableau",PhD,0,Energy,2024-10-11,2024-11-27,1842,7.3,DataVision Ltd -AI13455,Autonomous Systems Engineer,130146,JPY,14316060,MI,FL,Japan,L,Japan,0,"GCP, Docker, MLOps, Tableau, Hadoop",Bachelor,2,Telecommunications,2024-09-28,2024-10-18,2259,6.4,Quantum Computing Inc -AI13456,Head of AI,62607,USD,62607,SE,PT,China,S,China,0,"Spark, R, Linux, SQL",Bachelor,9,Media,2024-08-08,2024-10-04,2050,5.1,DataVision Ltd -AI13457,AI Specialist,213739,USD,213739,SE,CT,Denmark,L,Denmark,50,"SQL, Scala, Data Visualization, Linux, AWS",Associate,5,Energy,2024-03-28,2024-06-04,561,5.3,AI Innovations -AI13458,Research Scientist,239862,AUD,323814,EX,CT,Australia,L,Australia,50,"GCP, Hadoop, R",Bachelor,18,Government,2024-06-03,2024-07-22,713,5.4,AI Innovations -AI13459,Deep Learning Engineer,85775,EUR,72909,EN,FT,Austria,L,Colombia,50,"Spark, Data Visualization, Hadoop, Docker",Master,0,Retail,2024-06-15,2024-07-07,1378,6.3,Cognitive Computing -AI13460,Head of AI,52732,CAD,65915,EN,FL,Canada,M,Canada,100,"GCP, TensorFlow, Python, NLP",Bachelor,1,Finance,2025-02-04,2025-03-01,2406,6.5,AI Innovations -AI13461,Data Scientist,134420,SGD,174746,SE,FT,Singapore,M,Singapore,100,"Hadoop, SQL, Kubernetes",Bachelor,8,Education,2025-01-17,2025-03-06,1438,8.8,Quantum Computing Inc -AI13462,Robotics Engineer,261477,CHF,235329,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Python, GCP",Associate,12,Retail,2024-10-29,2024-12-02,1127,7,Cognitive Computing -AI13463,AI Consultant,163591,CHF,147232,SE,CT,Switzerland,M,Switzerland,100,"SQL, Hadoop, Scala, Deep Learning",Bachelor,9,Telecommunications,2024-09-24,2024-10-20,1728,8.4,Quantum Computing Inc -AI13464,AI Architect,140181,AUD,189244,SE,PT,Australia,M,Chile,0,"Azure, Tableau, Linux, Docker",Bachelor,9,Media,2024-03-23,2024-05-13,2319,6.6,Autonomous Tech -AI13465,Deep Learning Engineer,142202,AUD,191973,SE,PT,Australia,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, Statistics",Master,6,Real Estate,2024-03-20,2024-05-09,1741,9.8,Predictive Systems -AI13466,Research Scientist,157835,GBP,118376,EX,CT,United Kingdom,S,Italy,50,"GCP, AWS, Linux, Deep Learning, SQL",Master,16,Consulting,2024-02-25,2024-04-11,620,9.3,Cognitive Computing -AI13467,Deep Learning Engineer,186913,USD,186913,SE,FL,United States,L,United States,50,"TensorFlow, GCP, Deep Learning",Associate,8,Government,2024-02-04,2024-04-08,1879,9.4,Predictive Systems -AI13468,Machine Learning Engineer,133440,USD,133440,SE,FT,Sweden,S,Sweden,0,"Hadoop, Scala, Kubernetes, Mathematics, Python",Bachelor,9,Telecommunications,2025-03-15,2025-04-21,1873,5.5,DeepTech Ventures -AI13469,Robotics Engineer,138149,USD,138149,EX,CT,Ireland,S,New Zealand,50,"Deep Learning, Kubernetes, Computer Vision",PhD,10,Technology,2024-03-27,2024-05-11,617,6.3,AI Innovations -AI13470,Principal Data Scientist,130691,EUR,111087,SE,FL,Austria,L,Austria,0,"Kubernetes, Deep Learning, Java, AWS, Computer Vision",PhD,9,Media,2024-09-13,2024-10-24,1605,5.8,Machine Intelligence Group -AI13471,AI Research Scientist,87469,USD,87469,MI,PT,Israel,M,Israel,100,"Hadoop, SQL, Tableau, Azure, Kubernetes",Master,3,Government,2024-10-23,2024-11-28,2305,9.2,TechCorp Inc -AI13472,AI Specialist,106777,GBP,80083,MI,FL,United Kingdom,L,United Kingdom,0,"Deep Learning, SQL, Spark",PhD,3,Finance,2024-12-08,2024-12-26,1723,10,Neural Networks Co -AI13473,NLP Engineer,50461,USD,50461,SE,PT,China,M,China,100,"Data Visualization, Hadoop, Computer Vision",Associate,7,Finance,2024-04-01,2024-05-03,2354,5.8,Algorithmic Solutions -AI13474,Computer Vision Engineer,159609,EUR,135668,EX,FL,Austria,M,Indonesia,0,"Python, Git, TensorFlow",Associate,11,Consulting,2024-03-14,2024-03-29,1071,8.5,Predictive Systems -AI13475,Machine Learning Researcher,154149,EUR,131027,EX,PT,France,M,France,0,"Python, SQL, Linux, GCP",Master,18,Manufacturing,2024-07-14,2024-09-09,1775,8.5,Autonomous Tech -AI13476,AI Software Engineer,64819,GBP,48614,EN,FL,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Azure",Associate,1,Consulting,2024-05-16,2024-07-22,2036,5.7,TechCorp Inc -AI13477,Principal Data Scientist,125314,SGD,162908,MI,FL,Singapore,L,Singapore,100,"AWS, Azure, Spark, Computer Vision",Bachelor,2,Manufacturing,2024-11-03,2024-11-17,2038,9.1,Algorithmic Solutions -AI13478,AI Specialist,55051,USD,55051,EN,PT,Israel,S,Australia,100,"Scala, SQL, Azure",PhD,0,Technology,2024-11-01,2024-12-01,1137,7.1,Algorithmic Solutions -AI13479,AI Specialist,32595,USD,32595,MI,FT,India,L,India,100,"Hadoop, Java, NLP",Associate,4,Media,2024-04-13,2024-05-19,548,9.6,Digital Transformation LLC -AI13480,AI Architect,71110,EUR,60444,MI,FL,Netherlands,S,Belgium,100,"Git, R, TensorFlow",PhD,2,Finance,2024-06-25,2024-09-04,2334,7.8,Cognitive Computing -AI13481,AI Software Engineer,169547,JPY,18650170,EX,PT,Japan,S,Japan,100,"NLP, GCP, Tableau, PyTorch",Master,18,Finance,2024-03-09,2024-05-04,848,5.8,Algorithmic Solutions -AI13482,ML Ops Engineer,178084,CHF,160276,SE,CT,Switzerland,S,Switzerland,100,"Python, TensorFlow, AWS",Master,8,Real Estate,2025-03-29,2025-05-13,1319,8.4,Autonomous Tech -AI13483,AI Architect,62829,GBP,47122,EN,FL,United Kingdom,S,Romania,50,"NLP, Hadoop, Scala, SQL, GCP",PhD,1,Finance,2025-01-03,2025-01-24,1496,5.4,Neural Networks Co -AI13484,AI Research Scientist,159514,USD,159514,EX,CT,South Korea,M,South Korea,50,"Python, NLP, Mathematics, Git",Associate,17,Healthcare,2025-02-06,2025-04-13,2270,6.4,AI Innovations -AI13485,AI Architect,127374,USD,127374,MI,PT,Norway,S,Chile,50,"Python, MLOps, NLP, Linux, AWS",PhD,2,Finance,2024-04-24,2024-05-13,2290,6.2,Quantum Computing Inc -AI13486,ML Ops Engineer,123377,USD,123377,MI,FT,Sweden,L,Ireland,100,"Hadoop, Scala, Mathematics, Linux",Master,2,Automotive,2024-10-31,2024-12-05,603,5.5,TechCorp Inc -AI13487,AI Product Manager,131293,JPY,14442230,SE,CT,Japan,M,Japan,0,"Deep Learning, AWS, Python, Mathematics, Hadoop",Master,5,Retail,2024-06-16,2024-08-22,760,8,AI Innovations -AI13488,Data Engineer,69197,EUR,58817,EN,PT,Germany,M,Germany,50,"SQL, Docker, MLOps, Hadoop",Associate,0,Energy,2025-02-20,2025-03-25,1451,7.2,Advanced Robotics -AI13489,ML Ops Engineer,96379,EUR,81922,MI,FL,France,M,Argentina,100,"Tableau, Computer Vision, Docker",Associate,3,Transportation,2024-04-06,2024-06-07,557,7.9,Autonomous Tech -AI13490,Robotics Engineer,57105,USD,57105,EN,CT,Israel,L,Spain,50,"R, Tableau, SQL, Deep Learning",Associate,1,Media,2024-10-16,2024-12-07,2426,6.8,Machine Intelligence Group -AI13491,AI Consultant,41328,USD,41328,MI,FL,China,M,New Zealand,50,"Docker, SQL, Azure, Python, Mathematics",Master,2,Government,2024-02-10,2024-02-27,576,9.9,Machine Intelligence Group -AI13492,Data Scientist,119623,USD,119623,MI,CT,Denmark,L,Denmark,0,"Python, TensorFlow, Deep Learning, SQL",Bachelor,2,Technology,2025-04-29,2025-06-22,1740,6.8,DataVision Ltd -AI13493,Robotics Engineer,158417,USD,158417,EX,PT,Ireland,M,Ireland,50,"Python, Azure, TensorFlow",Associate,10,Technology,2025-01-18,2025-03-01,2083,8,Autonomous Tech -AI13494,Data Scientist,82345,AUD,111166,MI,FT,Australia,S,Australia,100,"Deep Learning, Tableau, Statistics",Bachelor,4,Gaming,2025-04-15,2025-05-22,2475,5.6,DataVision Ltd -AI13495,Computer Vision Engineer,28336,USD,28336,EN,CT,India,M,India,50,"Statistics, Mathematics, AWS",Bachelor,0,Telecommunications,2024-12-21,2025-02-04,2180,6.9,TechCorp Inc -AI13496,Computer Vision Engineer,176246,USD,176246,EX,FT,South Korea,S,South Korea,50,"Docker, Kubernetes, MLOps, Deep Learning",Bachelor,15,Retail,2025-01-16,2025-03-29,1879,5.4,Smart Analytics -AI13497,NLP Engineer,47000,USD,47000,SE,FL,India,S,India,100,"Python, NLP, TensorFlow, GCP",Master,7,Transportation,2025-03-26,2025-04-12,1770,8.1,AI Innovations -AI13498,ML Ops Engineer,47164,USD,47164,EN,FL,South Korea,M,South Korea,50,"Computer Vision, Deep Learning, Scala, Python",PhD,1,Media,2025-04-08,2025-05-29,2331,5.5,DataVision Ltd -AI13499,Principal Data Scientist,132818,SGD,172663,SE,CT,Singapore,M,Singapore,0,"Linux, MLOps, Scala, Data Visualization",PhD,5,Real Estate,2024-12-06,2025-01-29,1896,8.9,Neural Networks Co -AI13500,AI Specialist,85866,EUR,72986,MI,CT,Germany,L,Germany,100,"PyTorch, Deep Learning, Kubernetes, AWS, Computer Vision",PhD,3,Media,2024-11-23,2025-01-19,2172,8,Neural Networks Co -AI13501,NLP Engineer,92368,EUR,78513,SE,FL,Germany,S,Germany,100,"AWS, Linux, Spark",Master,8,Automotive,2024-06-05,2024-06-25,1291,6.5,Autonomous Tech -AI13502,Computer Vision Engineer,100531,USD,100531,SE,PT,South Korea,L,South Korea,0,"SQL, Docker, Python, MLOps",Associate,6,Consulting,2024-07-17,2024-08-12,988,6.4,Algorithmic Solutions -AI13503,Data Analyst,87818,USD,87818,MI,PT,Finland,S,Argentina,50,"Kubernetes, Azure, Java, Data Visualization, GCP",Associate,3,Energy,2025-04-15,2025-06-10,1287,9.1,Digital Transformation LLC -AI13504,Robotics Engineer,214112,AUD,289051,EX,CT,Australia,S,Australia,100,"Python, Mathematics, Hadoop, Scala, Azure",PhD,16,Telecommunications,2025-03-02,2025-03-24,1204,7.7,Future Systems -AI13505,Data Engineer,137081,JPY,15078910,SE,FL,Japan,L,Switzerland,100,"Tableau, Python, Scala, Spark",Bachelor,7,Automotive,2024-01-28,2024-03-22,1876,5.3,DataVision Ltd -AI13506,Data Analyst,53421,USD,53421,SE,PT,India,M,India,0,"Kubernetes, Git, NLP, TensorFlow, PyTorch",Associate,8,Healthcare,2024-08-02,2024-09-04,931,5.6,Autonomous Tech -AI13507,AI Architect,75794,GBP,56846,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Docker, Spark, Computer Vision, PyTorch",Associate,0,Gaming,2025-03-24,2025-04-24,1153,6.2,Cognitive Computing -AI13508,NLP Engineer,175103,EUR,148838,EX,CT,Austria,L,Austria,50,"Java, Scala, GCP",PhD,17,Telecommunications,2024-06-03,2024-07-02,1294,5.3,Neural Networks Co -AI13509,ML Ops Engineer,175669,CHF,158102,SE,FL,Switzerland,S,Switzerland,100,"TensorFlow, Git, SQL",PhD,6,Media,2024-08-29,2024-09-28,1991,7.7,Autonomous Tech -AI13510,AI Architect,152942,USD,152942,EX,CT,Israel,L,Israel,0,"Kubernetes, Java, Git",PhD,14,Transportation,2024-10-04,2024-10-25,2411,8.4,Future Systems -AI13511,AI Architect,115652,USD,115652,MI,PT,Finland,L,Finland,100,"Linux, SQL, PyTorch, GCP, TensorFlow",Master,4,Gaming,2025-04-16,2025-05-09,691,5.9,Cognitive Computing -AI13512,AI Product Manager,254643,EUR,216447,EX,CT,Netherlands,L,Netherlands,0,"Hadoop, Statistics, Linux, Data Visualization",Associate,17,Gaming,2024-03-05,2024-05-17,1152,6.3,Autonomous Tech -AI13513,Machine Learning Researcher,113576,EUR,96540,MI,PT,Germany,L,Latvia,0,"SQL, Linux, R, Hadoop, Computer Vision",Master,4,Media,2024-10-20,2024-11-21,1737,7.2,Smart Analytics -AI13514,Data Engineer,82775,USD,82775,EN,FL,Norway,M,Norway,100,"Mathematics, R, Docker, Spark, SQL",PhD,1,Telecommunications,2024-02-14,2024-03-18,1834,9.4,Quantum Computing Inc -AI13515,AI Architect,166158,USD,166158,SE,PT,Norway,S,Norway,100,"Java, MLOps, NLP, Git, Mathematics",PhD,5,Transportation,2024-11-05,2024-12-28,604,9.8,AI Innovations -AI13516,Computer Vision Engineer,128965,USD,128965,MI,FT,United States,L,United States,0,"GCP, TensorFlow, Mathematics, Computer Vision, AWS",PhD,4,Consulting,2024-10-04,2024-11-27,871,8,Autonomous Tech -AI13517,Data Scientist,117391,USD,117391,SE,CT,South Korea,M,South Korea,50,"Spark, TensorFlow, GCP",Associate,9,Telecommunications,2024-11-06,2025-01-14,1903,8.8,Autonomous Tech -AI13518,Data Analyst,270558,USD,270558,EX,FL,Norway,S,Norway,0,"GCP, Python, MLOps, Tableau, Kubernetes",Master,17,Media,2025-01-07,2025-03-07,2124,9.3,Neural Networks Co -AI13519,Data Engineer,190549,CAD,238186,EX,FL,Canada,S,Spain,50,"Python, Git, MLOps",Bachelor,10,Education,2024-08-18,2024-10-22,1395,6.6,AI Innovations -AI13520,Computer Vision Engineer,53483,USD,53483,EN,CT,South Korea,S,Thailand,0,"Python, Deep Learning, SQL",Bachelor,1,Gaming,2024-04-20,2024-06-01,1095,6.2,DataVision Ltd -AI13521,Computer Vision Engineer,119338,USD,119338,SE,FT,United States,S,Kenya,50,"TensorFlow, R, MLOps, Java, AWS",PhD,6,Gaming,2024-09-06,2024-11-05,2370,6.9,Cloud AI Solutions -AI13522,AI Architect,66333,USD,66333,MI,PT,South Korea,S,Thailand,100,"Statistics, Hadoop, Tableau, GCP",PhD,4,Education,2024-10-09,2024-11-12,1271,7.9,Predictive Systems -AI13523,Machine Learning Researcher,102503,GBP,76877,MI,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Scala, Docker, Java, Deep Learning",Master,4,Media,2024-01-23,2024-03-11,1799,6.3,Cloud AI Solutions -AI13524,AI Architect,135092,USD,135092,SE,CT,Finland,M,Finland,0,"Scala, SQL, PyTorch, Spark",Bachelor,8,Healthcare,2024-11-29,2024-12-25,2206,5.5,Cloud AI Solutions -AI13525,Machine Learning Engineer,102919,USD,102919,SE,CT,South Korea,S,South Korea,100,"GCP, Python, Java, Docker",PhD,5,Government,2024-06-09,2024-08-01,897,9.4,Cognitive Computing -AI13526,Principal Data Scientist,135359,SGD,175967,SE,CT,Singapore,M,Singapore,100,"TensorFlow, SQL, GCP, Java, Statistics",Bachelor,9,Transportation,2024-12-16,2025-02-11,1370,6.7,AI Innovations -AI13527,Machine Learning Engineer,125939,USD,125939,MI,CT,Norway,L,Norway,50,"Mathematics, Linux, Hadoop, TensorFlow",PhD,2,Retail,2025-01-19,2025-03-22,674,6.3,Autonomous Tech -AI13528,Research Scientist,187712,CHF,168941,SE,CT,Switzerland,S,Switzerland,0,"MLOps, R, Azure",Associate,8,Retail,2024-10-31,2024-12-06,1040,8,Advanced Robotics -AI13529,AI Research Scientist,243121,SGD,316057,EX,PT,Singapore,M,Singapore,50,"Java, SQL, Data Visualization",Associate,11,Transportation,2024-01-06,2024-03-04,716,5.8,AI Innovations -AI13530,AI Software Engineer,53273,USD,53273,SE,FT,India,M,India,50,"Python, Statistics, Hadoop, TensorFlow",PhD,6,Government,2024-12-27,2025-02-09,2149,7.2,Neural Networks Co -AI13531,Data Analyst,34231,USD,34231,EN,PT,China,L,China,0,"Kubernetes, Python, Git",Master,0,Education,2024-01-25,2024-03-09,2443,8.8,Algorithmic Solutions -AI13532,Research Scientist,64663,GBP,48497,EN,FT,United Kingdom,S,United Kingdom,0,"MLOps, Azure, TensorFlow, Deep Learning, Python",PhD,1,Manufacturing,2024-12-11,2025-02-16,2320,7.7,Cognitive Computing -AI13533,Robotics Engineer,145887,CHF,131298,SE,FL,Switzerland,S,Switzerland,50,"Deep Learning, SQL, PyTorch, Linux",Associate,7,Manufacturing,2024-12-23,2025-01-08,2106,6,Quantum Computing Inc -AI13534,Robotics Engineer,225404,GBP,169053,EX,FL,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning",Master,16,Technology,2025-03-07,2025-03-31,1137,8.3,Future Systems -AI13535,Machine Learning Researcher,118211,USD,118211,SE,FL,South Korea,M,South Korea,0,"Spark, GCP, SQL, MLOps",Master,5,Healthcare,2024-04-01,2024-05-24,817,8,DeepTech Ventures -AI13536,AI Product Manager,121319,USD,121319,MI,CT,Norway,M,Romania,50,"R, Tableau, Java, Git, Computer Vision",Associate,4,Consulting,2024-03-10,2024-05-14,737,7.2,Autonomous Tech -AI13537,Robotics Engineer,83754,JPY,9212940,MI,FL,Japan,S,Denmark,50,"Computer Vision, Kubernetes, Deep Learning",Bachelor,4,Manufacturing,2024-08-23,2024-10-25,2217,8.4,Neural Networks Co -AI13538,Head of AI,41420,USD,41420,SE,CT,India,M,India,100,"Java, Azure, MLOps, Hadoop, Spark",PhD,7,Retail,2024-03-24,2024-04-13,511,8.4,Advanced Robotics -AI13539,ML Ops Engineer,167184,USD,167184,SE,CT,Denmark,L,Nigeria,50,"Computer Vision, SQL, Python, Azure",Associate,7,Energy,2025-04-05,2025-05-14,1470,5.7,TechCorp Inc -AI13540,Data Engineer,79973,USD,79973,EN,FL,Norway,S,Norway,0,"Scala, Kubernetes, PyTorch",Associate,0,Retail,2024-02-29,2024-04-20,1710,7.4,DataVision Ltd -AI13541,Machine Learning Engineer,215068,USD,215068,SE,CT,Norway,L,Norway,50,"Python, TensorFlow, Computer Vision, Git, Linux",Master,5,Manufacturing,2024-07-15,2024-09-14,1303,9.2,Cloud AI Solutions -AI13542,AI Research Scientist,61811,USD,61811,EN,FT,Israel,S,Estonia,0,"Python, Tableau, Kubernetes",Master,0,Media,2025-02-18,2025-04-21,1234,8.9,DeepTech Ventures -AI13543,AI Architect,105290,SGD,136877,SE,FL,Singapore,S,Singapore,0,"SQL, Spark, Scala, Git, Azure",Associate,6,Telecommunications,2025-03-12,2025-05-21,1211,5.4,Quantum Computing Inc -AI13544,AI Consultant,87480,SGD,113724,MI,FL,Singapore,M,Singapore,100,"SQL, Tableau, Spark, PyTorch",Associate,3,Education,2024-12-24,2025-01-25,1963,7.2,Advanced Robotics -AI13545,Computer Vision Engineer,100005,CAD,125006,MI,FL,Canada,M,Romania,0,"Computer Vision, R, Linux, PyTorch, Git",PhD,3,Education,2024-11-14,2024-12-19,1834,6.6,Cognitive Computing -AI13546,Robotics Engineer,162358,CHF,146122,MI,CT,Switzerland,L,Switzerland,50,"SQL, Python, Tableau, MLOps, Spark",Bachelor,3,Finance,2024-01-23,2024-03-14,504,9.3,AI Innovations -AI13547,Machine Learning Researcher,158769,USD,158769,EX,FL,South Korea,S,Ireland,0,"MLOps, NLP, R, Python, Tableau",Associate,10,Government,2025-02-24,2025-03-31,1856,9,Cognitive Computing -AI13548,Machine Learning Engineer,231743,EUR,196982,EX,CT,Netherlands,S,Netherlands,100,"SQL, Scala, Docker, Mathematics, Computer Vision",Associate,12,Healthcare,2025-04-04,2025-05-12,1675,8.3,Advanced Robotics -AI13549,Robotics Engineer,198048,EUR,168341,EX,FL,Germany,L,Germany,100,"Java, MLOps, Git, Spark, Scala",PhD,14,Retail,2025-02-17,2025-04-30,2389,7.9,Neural Networks Co -AI13550,Computer Vision Engineer,170409,USD,170409,SE,FT,Norway,M,Norway,50,"Python, Data Visualization, PyTorch, Tableau, AWS",Bachelor,8,Technology,2024-03-22,2024-05-18,1565,8.9,Predictive Systems -AI13551,Data Scientist,137317,JPY,15104870,SE,FT,Japan,M,Japan,100,"Kubernetes, Spark, GCP, Python, Mathematics",Master,7,Real Estate,2025-04-16,2025-06-17,506,9.5,TechCorp Inc -AI13552,Data Analyst,215252,USD,215252,EX,FT,Norway,L,Norway,50,"Spark, Python, Data Visualization",PhD,16,Government,2025-03-02,2025-05-08,1376,7.6,DeepTech Ventures -AI13553,NLP Engineer,115357,AUD,155732,SE,PT,Australia,S,Colombia,100,"R, Kubernetes, SQL, Hadoop, Statistics",Master,6,Education,2025-02-13,2025-03-17,737,7.6,Smart Analytics -AI13554,NLP Engineer,78765,EUR,66950,MI,CT,Netherlands,M,Netherlands,100,"TensorFlow, Hadoop, Scala",Associate,2,Gaming,2025-01-01,2025-03-11,1847,6.3,Autonomous Tech -AI13555,Deep Learning Engineer,111065,CHF,99959,EN,CT,Switzerland,M,Switzerland,50,"Git, NLP, Scala, Computer Vision",Bachelor,0,Gaming,2024-02-06,2024-03-28,1593,7.4,Machine Intelligence Group -AI13556,Data Scientist,79550,USD,79550,SE,PT,China,L,China,100,"Tableau, Data Visualization, AWS",Associate,8,Government,2024-05-13,2024-07-24,2221,5.3,TechCorp Inc -AI13557,Data Analyst,155394,USD,155394,EX,PT,South Korea,S,New Zealand,50,"R, Tableau, Computer Vision",Associate,12,Healthcare,2025-01-03,2025-02-28,2068,7.5,Advanced Robotics -AI13558,Deep Learning Engineer,92899,USD,92899,MI,FL,Israel,L,Israel,100,"Java, MLOps, AWS",Bachelor,4,Manufacturing,2024-09-14,2024-10-24,1009,9.6,Digital Transformation LLC -AI13559,Data Engineer,94215,GBP,70661,MI,CT,United Kingdom,S,Argentina,50,"NLP, Mathematics, Kubernetes, MLOps",Bachelor,3,Technology,2024-12-30,2025-03-07,1513,8.3,Quantum Computing Inc -AI13560,Robotics Engineer,80817,AUD,109103,MI,PT,Australia,M,Nigeria,50,"Computer Vision, Linux, MLOps",PhD,3,Gaming,2024-09-29,2024-10-14,1084,8.4,DeepTech Ventures -AI13561,Machine Learning Researcher,142421,EUR,121058,EX,FT,Austria,S,Austria,100,"Spark, Scala, Deep Learning, TensorFlow, Azure",Associate,16,Healthcare,2024-07-13,2024-09-16,1113,5.2,Neural Networks Co -AI13562,AI Software Engineer,162016,SGD,210621,EX,FL,Singapore,M,France,50,"NLP, Python, TensorFlow, Spark",Bachelor,10,Gaming,2025-02-15,2025-03-29,2037,9,Quantum Computing Inc -AI13563,AI Specialist,240723,USD,240723,EX,CT,Ireland,M,Ireland,100,"Computer Vision, AWS, Kubernetes, Data Visualization, Git",PhD,17,Consulting,2024-02-07,2024-04-13,624,7.6,Cloud AI Solutions -AI13564,Computer Vision Engineer,177202,USD,177202,EX,FT,Denmark,M,United States,0,"Kubernetes, R, SQL, Java",Associate,11,Telecommunications,2025-01-09,2025-02-20,713,9.7,Digital Transformation LLC -AI13565,AI Software Engineer,19994,USD,19994,EN,PT,India,S,India,0,"Deep Learning, Mathematics, Scala",Associate,1,Consulting,2024-12-07,2025-01-07,1936,6.2,AI Innovations -AI13566,Research Scientist,87827,GBP,65870,MI,CT,United Kingdom,M,China,100,"Scala, R, AWS",Bachelor,4,Government,2025-03-13,2025-05-19,859,5.3,Digital Transformation LLC -AI13567,Data Engineer,246485,SGD,320431,EX,CT,Singapore,L,Singapore,50,"Kubernetes, Azure, Deep Learning, R",PhD,17,Real Estate,2025-01-02,2025-03-16,561,9,TechCorp Inc -AI13568,AI Architect,185718,JPY,20428980,EX,FL,Japan,S,Japan,50,"Scala, R, SQL, GCP, Mathematics",Associate,12,Technology,2024-01-31,2024-02-25,2094,7.8,Digital Transformation LLC -AI13569,AI Consultant,80076,USD,80076,SE,FT,China,L,Portugal,100,"Docker, Java, Statistics, Git",PhD,9,Manufacturing,2024-01-15,2024-02-12,1429,8.4,Advanced Robotics -AI13570,AI Software Engineer,184303,GBP,138227,SE,FL,United Kingdom,L,Mexico,0,"Python, Deep Learning, TensorFlow, Computer Vision, Kubernetes",Associate,5,Gaming,2024-10-28,2025-01-07,1685,6.5,TechCorp Inc -AI13571,Computer Vision Engineer,144334,CAD,180418,EX,CT,Canada,S,Canada,50,"Data Visualization, Java, Deep Learning",Associate,10,Government,2024-08-16,2024-10-01,1155,5.5,DeepTech Ventures -AI13572,Principal Data Scientist,136225,EUR,115791,SE,CT,Austria,L,Austria,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,9,Energy,2025-01-05,2025-03-08,1676,8.4,Smart Analytics -AI13573,Machine Learning Researcher,132186,USD,132186,SE,CT,Finland,M,Finland,100,"Java, NLP, AWS, Statistics",Associate,7,Manufacturing,2025-01-30,2025-03-03,1939,5.3,Advanced Robotics -AI13574,Deep Learning Engineer,125855,USD,125855,MI,CT,Sweden,L,Sweden,50,"R, TensorFlow, Kubernetes",Bachelor,3,Media,2024-12-21,2025-01-05,1426,9.5,Machine Intelligence Group -AI13575,Head of AI,56288,USD,56288,EN,FT,South Korea,S,South Korea,100,"Data Visualization, Java, Scala, Python, TensorFlow",PhD,0,Retail,2024-10-27,2024-12-20,2134,9.3,DataVision Ltd -AI13576,Data Scientist,249001,EUR,211651,EX,CT,Austria,L,Austria,0,"Tableau, Kubernetes, TensorFlow, Scala, AWS",Master,12,Telecommunications,2024-09-17,2024-11-26,1570,6.3,Predictive Systems -AI13577,Principal Data Scientist,132994,EUR,113045,EX,PT,Netherlands,S,Netherlands,100,"R, Computer Vision, NLP",Master,13,Healthcare,2025-04-22,2025-07-02,2196,8.9,TechCorp Inc -AI13578,AI Architect,108206,AUD,146078,MI,PT,Australia,M,Australia,50,"Tableau, Mathematics, Data Visualization, Python, Spark",Associate,2,Consulting,2024-06-30,2024-07-18,579,8.4,Quantum Computing Inc -AI13579,AI Consultant,55261,GBP,41446,EN,CT,United Kingdom,M,United Kingdom,100,"Python, Java, PyTorch",PhD,1,Telecommunications,2024-11-09,2024-12-14,831,5.7,Smart Analytics -AI13580,Head of AI,212757,EUR,180843,EX,FL,France,S,France,50,"Spark, Tableau, Scala, Linux",Master,10,Manufacturing,2024-05-19,2024-07-09,2126,7.6,Machine Intelligence Group -AI13581,Principal Data Scientist,115527,USD,115527,MI,PT,Denmark,S,United States,50,"SQL, Git, NLP, GCP, PyTorch",Associate,4,Education,2024-03-10,2024-05-20,785,5.8,Digital Transformation LLC -AI13582,Research Scientist,90576,USD,90576,EX,FT,China,S,Spain,50,"Linux, Hadoop, GCP",Associate,17,Telecommunications,2024-04-29,2024-07-01,652,5.8,Autonomous Tech -AI13583,NLP Engineer,68314,EUR,58067,EN,FL,Austria,S,Austria,50,"SQL, Linux, Computer Vision, Scala",Bachelor,0,Consulting,2024-02-02,2024-03-24,1389,9.8,Future Systems -AI13584,Data Analyst,80632,USD,80632,EN,FT,Norway,S,Norway,100,"Tableau, GCP, Linux",PhD,1,Media,2024-01-09,2024-02-12,845,9.2,Advanced Robotics -AI13585,Head of AI,85732,USD,85732,MI,PT,South Korea,L,South Korea,0,"Scala, MLOps, Tableau, SQL",Associate,4,Education,2024-03-17,2024-05-11,888,6.3,Digital Transformation LLC -AI13586,Machine Learning Engineer,89212,USD,89212,EN,CT,Denmark,M,Denmark,0,"TensorFlow, Data Visualization, Linux, PyTorch",Bachelor,1,Healthcare,2024-01-12,2024-02-27,2145,5.6,AI Innovations -AI13587,AI Product Manager,58528,USD,58528,SE,FL,India,L,India,50,"Hadoop, Git, PyTorch, Azure",PhD,5,Consulting,2024-10-31,2024-12-19,2079,9.9,Advanced Robotics -AI13588,Data Engineer,111013,EUR,94361,SE,PT,Netherlands,M,Mexico,100,"Scala, AWS, Java, Kubernetes, Deep Learning",Associate,5,Transportation,2025-03-11,2025-03-28,2267,9.5,Advanced Robotics -AI13589,ML Ops Engineer,161974,EUR,137678,SE,PT,France,L,Austria,0,"Statistics, R, Tableau",Bachelor,9,Finance,2024-02-26,2024-03-31,1545,6.2,Quantum Computing Inc -AI13590,AI Consultant,100290,USD,100290,MI,FT,Denmark,S,Denmark,0,"Kubernetes, Hadoop, PyTorch",Bachelor,2,Consulting,2024-04-13,2024-05-20,1342,5.8,Digital Transformation LLC -AI13591,Machine Learning Engineer,66642,USD,66642,EN,FL,Norway,M,Germany,50,"SQL, Hadoop, Tableau, Git, Scala",Associate,1,Finance,2025-02-23,2025-05-04,2080,5.4,Neural Networks Co -AI13592,Head of AI,162695,USD,162695,EX,PT,South Korea,M,Finland,0,"R, NLP, SQL",Associate,12,Government,2024-10-29,2024-12-06,2391,9.4,Smart Analytics -AI13593,AI Specialist,137077,EUR,116515,SE,FL,Austria,M,Austria,0,"Statistics, SQL, PyTorch, Deep Learning, Python",Associate,5,Transportation,2024-01-06,2024-03-17,1084,6.5,Advanced Robotics -AI13594,AI Software Engineer,132459,GBP,99344,SE,FL,United Kingdom,S,France,50,"Linux, Computer Vision, Deep Learning",Associate,8,Transportation,2024-08-25,2024-09-29,1483,5.4,AI Innovations -AI13595,Computer Vision Engineer,19457,USD,19457,EN,CT,India,S,India,0,"Scala, Kubernetes, Azure",PhD,0,Gaming,2025-04-09,2025-05-29,2272,8.1,TechCorp Inc -AI13596,Machine Learning Researcher,38912,USD,38912,MI,PT,India,L,India,50,"Mathematics, PyTorch, Python, Java, TensorFlow",PhD,2,Media,2024-10-30,2024-12-19,505,9.7,Advanced Robotics -AI13597,Data Scientist,111322,CAD,139153,MI,CT,Canada,L,Canada,100,"Docker, PyTorch, Computer Vision, AWS",Bachelor,4,Healthcare,2024-03-06,2024-05-02,1667,6.7,Machine Intelligence Group -AI13598,NLP Engineer,39729,USD,39729,MI,FL,China,S,China,100,"Python, Java, Docker",Bachelor,4,Education,2024-01-16,2024-02-08,820,7.6,Quantum Computing Inc -AI13599,Data Analyst,64601,USD,64601,EN,CT,Sweden,M,Sweden,100,"Java, MLOps, Kubernetes, Mathematics",Bachelor,1,Media,2024-09-14,2024-10-21,1542,5.8,Algorithmic Solutions -AI13600,Head of AI,199532,USD,199532,EX,PT,Ireland,S,Ireland,100,"Statistics, Hadoop, Spark",Associate,17,Finance,2024-10-17,2024-12-20,1422,9.4,Cloud AI Solutions -AI13601,ML Ops Engineer,204827,USD,204827,EX,PT,Norway,M,Malaysia,100,"MLOps, Mathematics, SQL",PhD,13,Education,2024-06-13,2024-08-11,1453,5.2,Algorithmic Solutions -AI13602,AI Software Engineer,131492,USD,131492,MI,CT,Norway,L,Norway,100,"Python, Linux, Docker, Git",PhD,3,Automotive,2025-01-26,2025-03-11,1257,5.2,Machine Intelligence Group -AI13603,Head of AI,200548,USD,200548,EX,CT,Ireland,M,Thailand,100,"SQL, NLP, PyTorch",PhD,17,Media,2024-05-22,2024-06-30,657,9,DeepTech Ventures -AI13604,Research Scientist,109537,SGD,142398,MI,PT,Singapore,L,Philippines,100,"PyTorch, Scala, NLP, Tableau",Master,3,Real Estate,2024-06-20,2024-07-08,1744,8.9,Autonomous Tech -AI13605,Deep Learning Engineer,169432,USD,169432,SE,PT,Ireland,L,Ireland,50,"Kubernetes, Python, Computer Vision",Master,6,Automotive,2024-09-12,2024-10-19,1222,6.2,Future Systems -AI13606,NLP Engineer,166233,USD,166233,EX,PT,United States,M,United States,0,"GCP, Azure, Computer Vision",Master,12,Government,2025-01-20,2025-02-05,1119,7.8,Machine Intelligence Group -AI13607,AI Consultant,67397,AUD,90986,MI,FT,Australia,S,Australia,50,"Scala, PyTorch, SQL",PhD,2,Technology,2025-03-16,2025-04-30,2214,8.1,DataVision Ltd -AI13608,AI Consultant,56703,USD,56703,SE,FT,China,S,China,0,"Git, R, Computer Vision",Bachelor,8,Manufacturing,2024-11-11,2024-12-21,2219,8.7,DeepTech Ventures -AI13609,Research Scientist,26374,USD,26374,EN,CT,China,S,China,0,"Kubernetes, Python, Scala, Deep Learning, Computer Vision",Associate,1,Government,2024-10-18,2024-11-24,575,9.3,Digital Transformation LLC -AI13610,AI Architect,45657,USD,45657,SE,CT,India,L,India,0,"Computer Vision, Deep Learning, R",Bachelor,9,Gaming,2024-01-16,2024-03-03,624,7.4,Digital Transformation LLC -AI13611,Computer Vision Engineer,39452,USD,39452,EN,CT,South Korea,S,Norway,50,"Git, NLP, Python",Associate,0,Education,2025-01-25,2025-02-28,1967,7.1,Machine Intelligence Group -AI13612,Data Analyst,123631,USD,123631,SE,PT,Sweden,S,Sweden,100,"TensorFlow, Mathematics, GCP",Bachelor,9,Healthcare,2024-02-25,2024-04-28,1819,7.7,DataVision Ltd -AI13613,ML Ops Engineer,102463,SGD,133202,MI,CT,Singapore,S,Singapore,100,"MLOps, Statistics, Scala, Data Visualization",Associate,2,Healthcare,2024-08-21,2024-09-15,799,7.2,Neural Networks Co -AI13614,Data Engineer,38458,USD,38458,MI,FT,China,M,China,100,"Azure, Computer Vision, Docker, PyTorch",Master,3,Manufacturing,2025-04-05,2025-05-30,2158,6,Autonomous Tech -AI13615,AI Software Engineer,50577,EUR,42990,EN,PT,Germany,S,Germany,50,"TensorFlow, R, Azure, AWS, NLP",Associate,0,Technology,2024-10-21,2024-12-28,1836,8.4,DeepTech Ventures -AI13616,Machine Learning Engineer,91272,AUD,123217,EN,FL,Australia,L,Malaysia,50,"Python, TensorFlow, Data Visualization",Master,0,Real Estate,2025-03-05,2025-04-03,1752,8.1,Quantum Computing Inc -AI13617,AI Software Engineer,92478,USD,92478,EN,CT,United States,L,United States,100,"Computer Vision, Statistics, MLOps",PhD,0,Automotive,2024-05-03,2024-06-24,1054,5.5,Cloud AI Solutions -AI13618,NLP Engineer,213025,USD,213025,EX,CT,Sweden,S,Sweden,100,"Python, Linux, GCP, Hadoop, PyTorch",Bachelor,10,Government,2025-02-15,2025-03-14,534,6.2,Algorithmic Solutions -AI13619,Autonomous Systems Engineer,240149,USD,240149,EX,FT,United States,L,United States,100,"SQL, GCP, Azure, NLP",PhD,15,Government,2024-10-28,2024-12-15,1242,5.9,Machine Intelligence Group -AI13620,Data Analyst,97727,EUR,83068,MI,PT,Austria,L,Austria,50,"Deep Learning, SQL, Data Visualization, PyTorch",Associate,3,Gaming,2025-04-25,2025-06-22,1949,9.7,Autonomous Tech -AI13621,Robotics Engineer,81590,CAD,101988,MI,CT,Canada,S,Netherlands,50,"Hadoop, Kubernetes, Mathematics",Associate,3,Government,2024-09-05,2024-11-03,1546,7.3,Cloud AI Solutions -AI13622,NLP Engineer,80741,AUD,109000,MI,FT,Australia,M,Colombia,100,"SQL, Python, MLOps",Bachelor,2,Technology,2024-08-29,2024-11-08,2250,7.9,DeepTech Ventures -AI13623,Head of AI,207242,USD,207242,EX,PT,Israel,S,Argentina,50,"Linux, Hadoop, Tableau",Associate,14,Manufacturing,2024-11-11,2024-12-18,2227,5.1,Cloud AI Solutions -AI13624,Principal Data Scientist,162118,USD,162118,EX,FL,Israel,S,Israel,100,"AWS, Docker, Mathematics",Associate,13,Telecommunications,2024-03-18,2024-05-07,1676,8.7,Autonomous Tech -AI13625,AI Software Engineer,95549,USD,95549,MI,FL,Israel,L,Israel,0,"Java, AWS, NLP, Tableau, Azure",Master,2,Gaming,2025-04-05,2025-06-14,1519,6.8,Advanced Robotics -AI13626,Autonomous Systems Engineer,22852,USD,22852,EN,PT,China,S,China,50,"Java, Spark, TensorFlow, Kubernetes",Master,0,Transportation,2024-11-11,2024-12-15,2127,7.1,Digital Transformation LLC -AI13627,Robotics Engineer,99707,USD,99707,EN,FT,United States,L,United States,0,"NLP, GCP, AWS, Git, Hadoop",Bachelor,1,Transportation,2024-03-02,2024-04-20,1827,5.9,Smart Analytics -AI13628,Autonomous Systems Engineer,82711,USD,82711,EN,FL,Finland,L,Finland,100,"Kubernetes, Python, Statistics, GCP, Java",Associate,1,Telecommunications,2024-03-23,2024-05-25,832,5.9,Autonomous Tech -AI13629,Data Analyst,114447,USD,114447,MI,PT,Norway,M,Norway,100,"Tableau, Linux, AWS",Associate,3,Transportation,2024-01-24,2024-02-27,2294,6.1,Predictive Systems -AI13630,Principal Data Scientist,80841,CAD,101051,MI,FL,Canada,S,Canada,50,"Hadoop, Git, MLOps, Statistics",Bachelor,3,Gaming,2025-01-10,2025-02-08,1943,7.7,DataVision Ltd -AI13631,Data Scientist,75011,USD,75011,EN,PT,Israel,L,Israel,100,"Tableau, Statistics, Computer Vision",Master,0,Transportation,2025-02-10,2025-03-21,1721,8.4,Neural Networks Co -AI13632,AI Specialist,48013,USD,48013,EX,PT,India,S,India,0,"TensorFlow, Scala, PyTorch, Statistics, Data Visualization",Bachelor,10,Healthcare,2024-03-05,2024-05-06,965,6.6,Cloud AI Solutions -AI13633,Head of AI,210553,EUR,178970,EX,CT,Germany,L,Germany,50,"Kubernetes, Scala, Data Visualization, Hadoop",Master,19,Consulting,2025-04-13,2025-05-07,956,7,Cloud AI Solutions -AI13634,Principal Data Scientist,68238,EUR,58002,EN,FT,Germany,S,Austria,100,"Kubernetes, Hadoop, PyTorch, AWS",Associate,0,Finance,2024-11-05,2025-01-16,1327,7.8,TechCorp Inc -AI13635,Autonomous Systems Engineer,211620,CHF,190458,SE,CT,Switzerland,M,Switzerland,50,"Java, Scala, SQL, Git",Bachelor,6,Telecommunications,2025-02-22,2025-04-19,709,8.4,Cloud AI Solutions -AI13636,AI Research Scientist,200684,USD,200684,EX,PT,Sweden,M,Sweden,50,"SQL, AWS, Hadoop",Associate,19,Telecommunications,2025-04-06,2025-06-08,1175,7.6,AI Innovations -AI13637,AI Software Engineer,91715,USD,91715,SE,PT,South Korea,S,Netherlands,100,"Tableau, Deep Learning, R, Python, TensorFlow",PhD,7,Education,2025-01-23,2025-02-06,1869,8.6,Neural Networks Co -AI13638,Principal Data Scientist,93185,JPY,10250350,EN,FL,Japan,L,Japan,50,"Python, AWS, Azure",Master,0,Technology,2025-04-13,2025-05-20,1885,9,AI Innovations -AI13639,Machine Learning Researcher,87268,USD,87268,EN,FT,Denmark,M,Denmark,100,"Azure, Java, SQL",Associate,1,Education,2025-01-31,2025-02-22,2387,6.9,Algorithmic Solutions -AI13640,Data Scientist,267540,CHF,240786,EX,PT,Switzerland,S,Switzerland,50,"MLOps, Tableau, Scala",Master,11,Telecommunications,2024-11-06,2024-11-29,2360,7.7,Autonomous Tech -AI13641,Data Engineer,126759,USD,126759,SE,FL,Sweden,M,Sweden,50,"Python, Docker, Data Visualization, PyTorch",Bachelor,7,Media,2024-02-08,2024-03-09,1723,6,Cognitive Computing -AI13642,Data Scientist,129742,USD,129742,SE,FT,Ireland,L,Ireland,50,"Linux, Mathematics, MLOps",Bachelor,9,Healthcare,2024-07-20,2024-08-23,1374,7.2,Digital Transformation LLC -AI13643,NLP Engineer,78149,GBP,58612,EN,FL,United Kingdom,M,United Kingdom,0,"R, AWS, TensorFlow, Mathematics",Master,0,Gaming,2024-04-24,2024-05-13,897,7.2,Cloud AI Solutions -AI13644,AI Consultant,84880,USD,84880,MI,FL,Norway,S,Norway,50,"SQL, GCP, NLP",Master,3,Finance,2024-03-22,2024-04-08,1412,8.2,Neural Networks Co -AI13645,Data Scientist,106468,USD,106468,EX,CT,China,L,China,50,"Linux, Docker, Tableau, Scala, GCP",Master,17,Finance,2024-03-09,2024-04-05,1740,9.2,DataVision Ltd -AI13646,AI Specialist,77051,USD,77051,EN,PT,Denmark,L,Mexico,50,"Hadoop, Docker, Kubernetes",PhD,1,Telecommunications,2024-12-28,2025-02-07,2495,6.8,TechCorp Inc -AI13647,AI Consultant,54386,AUD,73421,EN,FT,Australia,M,Australia,0,"PyTorch, TensorFlow, Git",Bachelor,1,Technology,2024-12-10,2025-01-19,561,9.2,Neural Networks Co -AI13648,Research Scientist,241352,SGD,313758,EX,CT,Singapore,L,Singapore,50,"Mathematics, Azure, Hadoop",Associate,12,Healthcare,2024-10-10,2024-11-02,1924,8.7,Algorithmic Solutions -AI13649,Computer Vision Engineer,122023,USD,122023,MI,CT,Denmark,S,Denmark,100,"Kubernetes, NLP, R, PyTorch, Docker",PhD,3,Finance,2024-10-11,2024-11-08,955,5.7,Neural Networks Co -AI13650,Computer Vision Engineer,69776,SGD,90709,MI,FT,Singapore,S,Ireland,0,"Java, Tableau, Hadoop, Scala, AWS",Master,4,Energy,2024-01-09,2024-03-11,602,8.3,DeepTech Ventures -AI13651,ML Ops Engineer,150163,USD,150163,SE,FL,Ireland,L,Ireland,100,"Kubernetes, Deep Learning, Azure",PhD,5,Transportation,2024-10-16,2024-12-22,868,7.7,Autonomous Tech -AI13652,Data Analyst,46451,CAD,58064,EN,CT,Canada,S,Canada,50,"NLP, Kubernetes, R, Java",Master,0,Manufacturing,2024-10-29,2024-11-15,718,8.2,Cognitive Computing -AI13653,Data Scientist,78071,AUD,105396,MI,PT,Australia,S,Australia,50,"Spark, Tableau, Java, Python",Associate,4,Consulting,2025-02-15,2025-04-21,648,9.9,Advanced Robotics -AI13654,Machine Learning Engineer,141974,USD,141974,SE,FL,South Korea,L,South Korea,100,"Spark, Tableau, PyTorch, Deep Learning, GCP",Associate,8,Finance,2024-03-15,2024-04-14,2050,8.6,Digital Transformation LLC -AI13655,Robotics Engineer,101301,JPY,11143110,MI,FT,Japan,L,Japan,50,"Tableau, SQL, GCP, Java",Bachelor,2,Automotive,2024-02-08,2024-02-27,1956,9.6,Cloud AI Solutions -AI13656,AI Architect,147615,USD,147615,SE,FL,Israel,L,Israel,100,"Docker, SQL, Kubernetes",Master,7,Healthcare,2024-12-01,2025-01-24,2115,5.3,Algorithmic Solutions -AI13657,Robotics Engineer,59247,USD,59247,EX,FT,India,M,Italy,100,"TensorFlow, PyTorch, Deep Learning",Associate,12,Gaming,2024-01-27,2024-03-09,1303,8.7,Digital Transformation LLC -AI13658,Computer Vision Engineer,68387,AUD,92322,EN,CT,Australia,S,Australia,0,"Scala, Git, SQL, Python, R",Associate,1,Real Estate,2025-03-29,2025-05-15,2393,9.4,Cognitive Computing -AI13659,Machine Learning Engineer,94339,SGD,122641,EN,FL,Singapore,L,Malaysia,50,"Git, SQL, GCP, Mathematics",Bachelor,1,Education,2024-02-27,2024-04-21,1382,6.9,Machine Intelligence Group -AI13660,Machine Learning Engineer,246518,SGD,320473,EX,FL,Singapore,L,Mexico,0,"Python, Kubernetes, Azure",Master,18,Consulting,2024-03-31,2024-05-07,594,8.7,TechCorp Inc -AI13661,Data Analyst,102322,USD,102322,MI,FT,Finland,M,Finland,100,"R, PyTorch, TensorFlow, Git",Master,2,Transportation,2024-03-19,2024-04-17,1537,9,Algorithmic Solutions -AI13662,Autonomous Systems Engineer,209756,USD,209756,EX,FT,United States,M,United States,100,"Tableau, Java, Kubernetes",PhD,10,Healthcare,2025-03-31,2025-05-19,1441,6.2,Advanced Robotics -AI13663,Data Scientist,130034,SGD,169044,SE,FT,Singapore,M,South Korea,100,"SQL, Linux, Git, Deep Learning, Statistics",Master,6,Gaming,2024-12-19,2025-02-15,1705,6.3,Predictive Systems -AI13664,AI Specialist,112402,EUR,95542,SE,PT,Germany,M,Germany,0,"Git, Python, Scala",Associate,7,Gaming,2024-12-30,2025-02-04,1356,5.6,AI Innovations -AI13665,Data Analyst,111935,USD,111935,SE,FL,Sweden,M,Sweden,50,"Deep Learning, Linux, Data Visualization, Statistics, Tableau",Bachelor,7,Real Estate,2024-10-26,2024-12-26,1616,7.5,AI Innovations -AI13666,ML Ops Engineer,210290,USD,210290,EX,PT,Finland,S,Finland,0,"Hadoop, Scala, Spark, Computer Vision",Bachelor,17,Real Estate,2024-04-15,2024-05-27,1321,6.2,Future Systems -AI13667,Data Engineer,156011,USD,156011,SE,PT,Norway,S,Norway,0,"Spark, Linux, Computer Vision, Python, Azure",Associate,9,Manufacturing,2024-09-28,2024-11-18,1382,8.2,AI Innovations -AI13668,Machine Learning Researcher,72835,USD,72835,EN,PT,United States,S,Italy,50,"Java, Scala, Deep Learning, Docker",Master,1,Healthcare,2024-01-03,2024-03-10,1536,9,Advanced Robotics -AI13669,Data Analyst,182390,USD,182390,SE,FL,Norway,M,Japan,50,"Tableau, Data Visualization, Azure, Docker",Associate,7,Real Estate,2024-04-23,2024-06-03,1277,5.7,Predictive Systems -AI13670,Machine Learning Researcher,69023,CAD,86279,EN,FL,Canada,M,Canada,50,"Scala, Python, Azure",Bachelor,1,Energy,2024-10-10,2024-11-03,2005,9.1,Cloud AI Solutions -AI13671,NLP Engineer,92468,GBP,69351,MI,FL,United Kingdom,M,United Kingdom,50,"Spark, Java, Data Visualization, GCP",PhD,3,Automotive,2024-06-13,2024-06-28,1890,8.1,Smart Analytics -AI13672,Research Scientist,65251,USD,65251,EN,CT,Israel,L,Israel,50,"PyTorch, Deep Learning, Spark",Master,0,Real Estate,2025-01-07,2025-02-15,651,5.6,Cognitive Computing -AI13673,AI Specialist,217187,USD,217187,EX,FL,Ireland,M,Ireland,100,"R, PyTorch, Data Visualization",Associate,15,Education,2024-03-17,2024-04-08,1446,8.3,Smart Analytics -AI13674,Autonomous Systems Engineer,54380,EUR,46223,EN,PT,Germany,S,Germany,0,"Linux, Python, Git, Statistics",Master,0,Finance,2025-01-01,2025-02-03,1960,9.6,DataVision Ltd -AI13675,AI Consultant,295717,EUR,251359,EX,CT,Netherlands,L,Netherlands,100,"Java, Data Visualization, Spark",Master,11,Finance,2024-12-19,2025-01-16,1535,9,Algorithmic Solutions -AI13676,NLP Engineer,122502,AUD,165378,SE,FT,Australia,M,Hungary,100,"NLP, TensorFlow, Hadoop",Associate,6,Consulting,2025-04-24,2025-05-09,2498,6.8,Algorithmic Solutions -AI13677,Deep Learning Engineer,109823,USD,109823,MI,CT,Sweden,L,Sweden,100,"Hadoop, AWS, Java, Statistics, Azure",Bachelor,3,Energy,2024-05-16,2024-07-01,976,8.4,Smart Analytics -AI13678,Autonomous Systems Engineer,82666,USD,82666,EN,FT,Finland,L,Finland,100,"Spark, Python, Azure, Java",PhD,0,Automotive,2025-04-08,2025-05-07,1809,7.3,Machine Intelligence Group -AI13679,Robotics Engineer,69269,GBP,51952,EN,FT,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python, Data Visualization",Master,1,Retail,2024-10-19,2024-12-20,1443,7.5,Smart Analytics -AI13680,AI Specialist,193819,USD,193819,EX,PT,Sweden,S,Sweden,50,"Linux, TensorFlow, Git, Kubernetes",PhD,11,Finance,2025-04-28,2025-05-28,630,7.4,Machine Intelligence Group -AI13681,Head of AI,104297,SGD,135586,MI,PT,Singapore,M,Singapore,100,"Java, R, AWS, Computer Vision, Statistics",PhD,4,Manufacturing,2025-02-23,2025-03-28,1501,8.7,Algorithmic Solutions -AI13682,NLP Engineer,64787,EUR,55069,EN,FL,France,S,France,0,"Hadoop, MLOps, Docker, Linux, TensorFlow",PhD,1,Energy,2025-02-08,2025-04-20,2254,7.7,DeepTech Ventures -AI13683,AI Architect,321641,USD,321641,EX,FT,Norway,M,Norway,100,"Git, TensorFlow, Scala",Bachelor,11,Education,2025-04-14,2025-06-22,1672,7.7,AI Innovations -AI13684,Computer Vision Engineer,55628,SGD,72316,EN,CT,Singapore,M,Turkey,100,"Azure, Java, R, Computer Vision, Hadoop",PhD,1,Healthcare,2025-04-18,2025-06-28,1517,5.8,Future Systems -AI13685,AI Architect,45870,USD,45870,MI,FT,China,S,Colombia,100,"AWS, Java, R, MLOps, SQL",Associate,3,Finance,2024-09-25,2024-11-27,530,5.4,Quantum Computing Inc -AI13686,AI Architect,152656,USD,152656,MI,FT,Denmark,L,Denmark,100,"MLOps, Kubernetes, PyTorch",Bachelor,3,Education,2024-03-03,2024-05-07,1022,7.1,Future Systems -AI13687,AI Software Engineer,26656,USD,26656,MI,FT,India,M,India,100,"Java, R, Data Visualization, Scala",Master,2,Retail,2025-01-27,2025-03-22,717,9.5,Advanced Robotics -AI13688,Data Analyst,146759,USD,146759,SE,PT,United States,L,United Kingdom,50,"R, Spark, Kubernetes, Python, AWS",Associate,7,Government,2024-08-10,2024-09-20,1615,8.4,TechCorp Inc -AI13689,AI Specialist,44241,CAD,55301,EN,FL,Canada,S,Canada,0,"Python, TensorFlow, PyTorch",Master,0,Finance,2025-01-01,2025-02-28,1287,6.1,TechCorp Inc -AI13690,Principal Data Scientist,124494,CHF,112045,EN,CT,Switzerland,L,Switzerland,50,"Linux, Hadoop, SQL, PyTorch, GCP",Bachelor,1,Media,2024-02-14,2024-03-12,1057,7.4,Cognitive Computing -AI13691,AI Specialist,83827,USD,83827,EX,PT,India,M,India,100,"Azure, Linux, Java, SQL",Bachelor,18,Automotive,2024-11-17,2024-12-01,1223,6.5,Advanced Robotics -AI13692,Machine Learning Researcher,133335,EUR,113335,SE,FL,Germany,M,Germany,100,"MLOps, Kubernetes, PyTorch, Statistics, SQL",PhD,8,Real Estate,2024-08-10,2024-09-29,1968,8.7,Future Systems -AI13693,Autonomous Systems Engineer,161531,EUR,137301,SE,FL,France,L,France,0,"Hadoop, Python, SQL, NLP",PhD,7,Retail,2024-12-06,2025-01-24,2300,5.5,Future Systems -AI13694,Deep Learning Engineer,80194,USD,80194,EN,FT,Ireland,M,Ireland,0,"SQL, R, Data Visualization",Master,0,Consulting,2024-12-28,2025-02-11,924,5.9,DataVision Ltd -AI13695,Data Scientist,181350,GBP,136013,EX,PT,United Kingdom,M,United Kingdom,0,"Tableau, Scala, NLP, TensorFlow",Bachelor,18,Consulting,2024-11-25,2025-01-11,2264,6.7,Predictive Systems -AI13696,AI Software Engineer,102985,USD,102985,MI,FT,Finland,M,Finland,50,"SQL, NLP, Git",PhD,3,Transportation,2025-02-20,2025-03-30,1591,8.7,Quantum Computing Inc -AI13697,AI Consultant,70147,USD,70147,EN,FT,Norway,M,Norway,0,"SQL, Scala, Git",Master,0,Education,2024-03-25,2024-04-30,598,9.5,Algorithmic Solutions -AI13698,Machine Learning Researcher,95188,SGD,123744,MI,PT,Singapore,L,Singapore,0,"Azure, PyTorch, Statistics, Hadoop, Java",Associate,3,Media,2024-12-04,2024-12-22,1227,9.4,Quantum Computing Inc -AI13699,Robotics Engineer,274623,USD,274623,EX,FL,United States,L,United States,50,"Python, PyTorch, Git, Azure, Java",Associate,14,Government,2024-02-08,2024-03-11,2135,6.4,Quantum Computing Inc -AI13700,Robotics Engineer,79001,EUR,67151,EN,CT,Germany,L,Germany,50,"Python, TensorFlow, NLP, Java",Master,1,Real Estate,2024-06-01,2024-07-07,1648,7.8,Digital Transformation LLC -AI13701,Autonomous Systems Engineer,133645,AUD,180421,SE,FL,Australia,M,Estonia,50,"Tableau, AWS, NLP, Docker",Bachelor,8,Education,2025-03-18,2025-05-26,706,9.9,AI Innovations -AI13702,Machine Learning Researcher,63052,USD,63052,SE,CT,China,S,China,0,"Computer Vision, Tableau, Data Visualization, NLP",Associate,5,Manufacturing,2024-08-12,2024-08-29,1774,6.5,Quantum Computing Inc -AI13703,AI Research Scientist,150556,AUD,203251,SE,PT,Australia,M,Australia,100,"SQL, Hadoop, Computer Vision, R",Associate,6,Technology,2024-11-02,2024-12-24,1164,8.4,Advanced Robotics -AI13704,AI Specialist,44619,USD,44619,SE,FL,China,S,China,50,"Java, TensorFlow, Git, AWS",PhD,6,Automotive,2025-04-15,2025-05-09,1572,7.6,AI Innovations -AI13705,Autonomous Systems Engineer,243017,USD,243017,EX,CT,Israel,L,Israel,0,"Scala, Data Visualization, Kubernetes, Computer Vision, Spark",Associate,12,Gaming,2024-03-09,2024-03-28,2181,8.1,Predictive Systems -AI13706,AI Specialist,201305,EUR,171109,EX,FT,Germany,L,Germany,0,"GCP, Git, PyTorch, SQL, Mathematics",Master,15,Automotive,2024-04-26,2024-06-08,1686,9.2,Quantum Computing Inc -AI13707,AI Research Scientist,94123,SGD,122360,EN,FL,Singapore,L,Singapore,50,"Java, SQL, Azure, MLOps, PyTorch",Master,0,Media,2024-01-05,2024-03-12,1613,5.4,Digital Transformation LLC -AI13708,Data Engineer,52016,GBP,39012,EN,FT,United Kingdom,S,Switzerland,100,"Azure, Kubernetes, Docker, AWS, Scala",PhD,0,Manufacturing,2024-10-14,2024-11-09,2014,6.2,Predictive Systems -AI13709,Computer Vision Engineer,48238,EUR,41002,EN,PT,France,S,Ireland,100,"Java, PyTorch, GCP",Master,0,Manufacturing,2024-03-23,2024-05-24,710,5.1,DataVision Ltd -AI13710,Data Analyst,189852,USD,189852,EX,CT,Ireland,M,Ireland,100,"Azure, Spark, SQL, Python",Master,12,Automotive,2024-07-21,2024-09-03,2343,8.2,AI Innovations -AI13711,Autonomous Systems Engineer,71233,CAD,89041,MI,FT,Canada,M,Vietnam,0,"Kubernetes, Computer Vision, Data Visualization, Azure, R",PhD,4,Transportation,2024-03-05,2024-05-04,979,8,Digital Transformation LLC -AI13712,Research Scientist,152809,EUR,129888,SE,PT,Germany,M,Germany,50,"Git, Java, R, NLP, Kubernetes",Associate,8,Real Estate,2025-01-17,2025-02-07,855,9.3,DataVision Ltd -AI13713,Principal Data Scientist,79844,USD,79844,MI,FL,Sweden,M,Sweden,50,"GCP, TensorFlow, Data Visualization, PyTorch, MLOps",Master,4,Retail,2024-11-04,2024-12-22,2002,5.7,DeepTech Ventures -AI13714,AI Specialist,90766,USD,90766,EN,CT,Sweden,L,Sweden,0,"Hadoop, Git, Spark, TensorFlow, GCP",PhD,1,Retail,2024-02-19,2024-04-22,2059,7.7,Neural Networks Co -AI13715,AI Specialist,94607,EUR,80416,MI,CT,France,M,France,50,"Linux, Spark, Azure",Associate,3,Education,2024-10-22,2024-12-14,1778,8.7,Smart Analytics -AI13716,Machine Learning Engineer,155537,JPY,17109070,SE,FT,Japan,L,Ireland,50,"Spark, Kubernetes, SQL, NLP",PhD,7,Gaming,2024-01-26,2024-02-14,1465,9.6,Algorithmic Solutions -AI13717,Principal Data Scientist,84059,GBP,63044,MI,FL,United Kingdom,M,Indonesia,0,"Spark, Python, TensorFlow, Hadoop",Bachelor,3,Media,2024-10-18,2024-12-03,1930,6.4,Smart Analytics -AI13718,Head of AI,214035,USD,214035,EX,FL,Israel,S,Israel,50,"Linux, MLOps, Hadoop, GCP, Python",PhD,12,Retail,2024-02-02,2024-02-22,1111,10,AI Innovations -AI13719,Machine Learning Engineer,62794,USD,62794,SE,FT,China,M,China,100,"Hadoop, Git, Docker, NLP",Associate,9,Telecommunications,2024-09-09,2024-09-24,858,10,Autonomous Tech -AI13720,Principal Data Scientist,78666,USD,78666,MI,FT,Sweden,S,Sweden,0,"Git, SQL, Python, R",Master,4,Automotive,2025-04-16,2025-05-18,1482,8.3,TechCorp Inc -AI13721,Head of AI,73536,JPY,8088960,EN,FT,Japan,M,Turkey,100,"Scala, Kubernetes, Java, PyTorch",PhD,0,Media,2024-08-15,2024-09-25,1805,8.9,Cloud AI Solutions -AI13722,Research Scientist,35544,USD,35544,MI,PT,China,M,Luxembourg,50,"Deep Learning, PyTorch, Java",Master,4,Education,2024-08-11,2024-10-22,1603,5.9,DeepTech Ventures -AI13723,AI Research Scientist,49579,USD,49579,EN,PT,South Korea,L,South Korea,50,"AWS, PyTorch, Scala, Linux",Associate,1,Automotive,2024-06-14,2024-08-20,2298,8.8,Digital Transformation LLC -AI13724,Data Engineer,37102,USD,37102,SE,PT,India,M,India,100,"Spark, Java, Git, Data Visualization, R",PhD,7,Finance,2024-07-23,2024-10-01,1467,5.6,Machine Intelligence Group -AI13725,Data Engineer,151791,CHF,136612,SE,FL,Switzerland,S,Switzerland,0,"Kubernetes, Mathematics, PyTorch, Spark",PhD,7,Media,2025-02-09,2025-04-23,1366,6.5,Cognitive Computing -AI13726,Head of AI,114945,USD,114945,SE,FT,Sweden,M,Sweden,100,"Computer Vision, Mathematics, NLP, PyTorch",Associate,7,Automotive,2025-02-01,2025-03-28,2374,9.5,AI Innovations -AI13727,Machine Learning Engineer,74998,CAD,93748,EN,FT,Canada,M,Canada,100,"Scala, Java, Docker",Associate,0,Transportation,2024-03-22,2024-05-02,1851,8.3,Digital Transformation LLC -AI13728,AI Software Engineer,119208,USD,119208,SE,FT,Israel,S,Israel,0,"Python, TensorFlow, Git",PhD,5,Gaming,2024-09-10,2024-11-12,762,6.6,Digital Transformation LLC -AI13729,Data Engineer,215124,USD,215124,EX,FL,Finland,M,Canada,100,"Data Visualization, Scala, AWS",Master,16,Manufacturing,2024-02-06,2024-02-26,626,8,Quantum Computing Inc -AI13730,Data Engineer,111381,JPY,12251910,SE,PT,Japan,M,Japan,50,"Scala, GCP, TensorFlow",PhD,6,Government,2024-01-05,2024-02-28,545,8.7,Future Systems -AI13731,AI Specialist,62659,EUR,53260,EN,FL,Germany,M,Germany,100,"Linux, Hadoop, Data Visualization, Python",PhD,0,Healthcare,2024-08-05,2024-09-19,1980,9.3,DeepTech Ventures -AI13732,Data Scientist,174509,EUR,148333,EX,PT,Austria,M,Austria,0,"Deep Learning, Hadoop, SQL",Associate,10,Manufacturing,2025-03-12,2025-04-12,1714,6.1,Cloud AI Solutions -AI13733,Principal Data Scientist,76295,USD,76295,SE,PT,China,L,China,0,"Python, SQL, AWS, Computer Vision",PhD,6,Real Estate,2024-09-30,2024-10-15,1025,6.9,TechCorp Inc -AI13734,Computer Vision Engineer,82190,CHF,73971,EN,CT,Switzerland,M,Malaysia,50,"Scala, Tableau, Python, Linux",Bachelor,1,Transportation,2024-06-27,2024-08-18,2364,5.3,Future Systems -AI13735,Data Scientist,60176,USD,60176,SE,FT,China,S,China,50,"R, Git, SQL",Bachelor,6,Finance,2024-07-30,2024-08-19,1300,9.1,Smart Analytics -AI13736,Computer Vision Engineer,91041,USD,91041,SE,FL,South Korea,S,Ukraine,100,"Computer Vision, Kubernetes, Git, Scala, Azure",Bachelor,8,Consulting,2024-10-06,2024-11-24,913,6.3,Quantum Computing Inc -AI13737,Robotics Engineer,51392,USD,51392,MI,FT,China,L,China,100,"Deep Learning, Hadoop, GCP",Master,2,Government,2024-01-03,2024-03-04,1175,8.8,Algorithmic Solutions -AI13738,Autonomous Systems Engineer,291795,USD,291795,EX,PT,Denmark,M,Denmark,50,"Scala, Statistics, AWS",Associate,13,Education,2025-03-18,2025-04-02,1768,7.8,Smart Analytics -AI13739,Head of AI,95963,USD,95963,EX,FL,India,L,India,0,"Kubernetes, Tableau, Hadoop",Bachelor,16,Energy,2024-10-21,2025-01-02,652,6.2,DeepTech Ventures -AI13740,AI Product Manager,48317,USD,48317,EN,FT,Ireland,S,Indonesia,50,"Python, TensorFlow, Mathematics",PhD,1,Media,2025-02-22,2025-04-20,1696,9.4,Quantum Computing Inc -AI13741,Machine Learning Researcher,66508,USD,66508,EN,FL,United States,S,Australia,100,"Docker, Python, PyTorch, Linux",PhD,1,Manufacturing,2025-02-04,2025-03-17,1858,6.4,Future Systems -AI13742,AI Architect,160872,EUR,136741,SE,FT,Germany,L,Israel,0,"AWS, Scala, SQL",Bachelor,5,Manufacturing,2024-02-02,2024-04-14,769,9.8,Cognitive Computing -AI13743,Autonomous Systems Engineer,170265,EUR,144725,EX,CT,Netherlands,S,Netherlands,0,"PyTorch, R, Deep Learning, Mathematics, NLP",PhD,14,Healthcare,2024-05-10,2024-07-21,2311,8.8,Algorithmic Solutions -AI13744,Computer Vision Engineer,67378,AUD,90960,EN,FT,Australia,M,Portugal,100,"Mathematics, PyTorch, Deep Learning, Data Visualization",Associate,0,Healthcare,2024-05-19,2024-07-26,2047,6.8,Digital Transformation LLC -AI13745,AI Consultant,201053,EUR,170895,EX,FL,Germany,L,Germany,0,"TensorFlow, Scala, SQL",Master,14,Gaming,2024-02-13,2024-04-08,793,5.1,Quantum Computing Inc -AI13746,Autonomous Systems Engineer,61127,EUR,51958,EN,FT,Germany,M,Germany,100,"Python, Azure, Tableau, MLOps, Computer Vision",Bachelor,0,Media,2025-04-04,2025-05-20,736,8.2,Predictive Systems -AI13747,Head of AI,132422,USD,132422,SE,CT,Ireland,M,Ireland,50,"Data Visualization, Python, Azure, Linux, R",Associate,7,Manufacturing,2024-12-16,2025-01-23,1166,9.4,Autonomous Tech -AI13748,Computer Vision Engineer,99521,EUR,84593,MI,CT,Netherlands,L,Netherlands,0,"Spark, SQL, Tableau, NLP, GCP",Master,3,Retail,2024-03-01,2024-04-05,1557,5.4,Advanced Robotics -AI13749,Data Engineer,187640,EUR,159494,EX,FT,France,M,United States,0,"MLOps, AWS, R",Associate,12,Manufacturing,2025-02-14,2025-03-09,1734,8.2,Cognitive Computing -AI13750,ML Ops Engineer,79512,CHF,71561,EN,FT,Switzerland,M,Switzerland,50,"SQL, GCP, Mathematics",Bachelor,1,Gaming,2024-11-03,2025-01-04,1933,6.2,Machine Intelligence Group -AI13751,ML Ops Engineer,76070,USD,76070,EN,FT,United States,M,United States,50,"SQL, Statistics, PyTorch, Spark, Kubernetes",Master,0,Energy,2025-04-30,2025-07-09,502,9.2,TechCorp Inc -AI13752,Research Scientist,214448,CHF,193003,SE,PT,Switzerland,M,Germany,0,"MLOps, PyTorch, TensorFlow, Docker",Master,6,Retail,2024-04-27,2024-06-01,1168,8.2,Smart Analytics -AI13753,ML Ops Engineer,197364,SGD,256573,EX,PT,Singapore,S,Singapore,100,"Linux, Docker, GCP, Hadoop, R",Master,13,Retail,2024-05-20,2024-07-04,689,9.1,Autonomous Tech -AI13754,Deep Learning Engineer,106426,EUR,90462,SE,CT,Netherlands,S,Kenya,100,"AWS, Kubernetes, Computer Vision, Python, Data Visualization",Associate,6,Energy,2024-08-26,2024-09-29,978,5.9,Cognitive Computing -AI13755,Computer Vision Engineer,64010,EUR,54409,MI,PT,France,S,France,100,"Data Visualization, PyTorch, Python, Azure, Docker",Master,3,Energy,2024-07-03,2024-09-10,1583,7.7,Predictive Systems -AI13756,AI Software Engineer,208320,USD,208320,EX,PT,Israel,L,Vietnam,50,"Kubernetes, Linux, TensorFlow",Bachelor,19,Energy,2024-10-06,2024-11-06,1807,6,Future Systems -AI13757,AI Product Manager,93335,USD,93335,MI,PT,Ireland,S,Ireland,0,"PyTorch, Kubernetes, Java, Deep Learning, Spark",Bachelor,4,Gaming,2025-04-08,2025-05-03,1110,5.6,Digital Transformation LLC -AI13758,AI Consultant,102368,USD,102368,SE,FT,Israel,S,Israel,0,"TensorFlow, Python, Data Visualization, Git, Hadoop",PhD,7,Gaming,2024-02-18,2024-04-18,1249,7.6,AI Innovations -AI13759,AI Product Manager,64929,EUR,55190,EN,PT,Netherlands,S,Netherlands,50,"Git, Java, Hadoop, SQL, Spark",Associate,0,Consulting,2025-01-18,2025-03-09,1113,5.9,AI Innovations -AI13760,AI Software Engineer,206784,USD,206784,EX,FL,Sweden,M,Sweden,100,"AWS, Linux, Scala, Statistics",Bachelor,17,Transportation,2024-04-06,2024-06-03,2115,6.2,DataVision Ltd -AI13761,Research Scientist,203979,USD,203979,EX,FT,South Korea,L,Latvia,100,"Git, Spark, MLOps, Docker",PhD,14,Real Estate,2024-03-30,2024-05-25,1655,7,Digital Transformation LLC -AI13762,Research Scientist,124710,CHF,112239,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, PyTorch, SQL, Deep Learning",PhD,2,Technology,2024-01-03,2024-02-05,1509,5.3,Cloud AI Solutions -AI13763,AI Software Engineer,60824,USD,60824,EN,FT,South Korea,L,Mexico,0,"PyTorch, Tableau, Deep Learning",Master,1,Automotive,2025-04-06,2025-06-12,1468,7,AI Innovations -AI13764,Robotics Engineer,133068,EUR,113108,EX,FT,France,S,France,0,"Hadoop, NLP, Mathematics, GCP",Associate,13,Finance,2024-08-25,2024-09-28,1755,7,Quantum Computing Inc -AI13765,Data Scientist,122346,USD,122346,SE,PT,Denmark,S,Chile,0,"Java, Kubernetes, GCP, SQL",Master,6,Gaming,2025-04-23,2025-06-25,1865,9.7,Future Systems -AI13766,Principal Data Scientist,180133,EUR,153113,EX,FT,Netherlands,L,Netherlands,100,"Python, Git, Kubernetes",Bachelor,14,Technology,2024-01-11,2024-03-01,1372,5.9,AI Innovations -AI13767,AI Product Manager,79220,USD,79220,MI,FT,Israel,L,Spain,0,"Mathematics, Kubernetes, Scala, Spark, TensorFlow",Associate,3,Transportation,2024-02-20,2024-03-12,2424,7.9,Algorithmic Solutions -AI13768,AI Research Scientist,129587,USD,129587,SE,FT,Israel,L,Israel,0,"AWS, Java, TensorFlow",Master,5,Consulting,2024-11-02,2025-01-11,2071,6.8,Cognitive Computing -AI13769,NLP Engineer,58088,USD,58088,EN,FT,South Korea,S,South Korea,0,"Hadoop, Computer Vision, Azure",Master,1,Transportation,2024-06-26,2024-07-22,1400,8.5,Machine Intelligence Group -AI13770,Computer Vision Engineer,202346,USD,202346,EX,CT,Norway,M,Spain,0,"Linux, NLP, Mathematics, Tableau, Spark",Bachelor,12,Technology,2024-03-18,2024-04-29,2120,8.8,Autonomous Tech -AI13771,Data Scientist,242484,USD,242484,EX,PT,Israel,L,Israel,100,"Computer Vision, PyTorch, Deep Learning, TensorFlow, MLOps",PhD,19,Government,2024-06-12,2024-07-02,938,9.3,AI Innovations -AI13772,AI Consultant,89975,GBP,67481,EN,FL,United Kingdom,L,United Kingdom,0,"SQL, Kubernetes, TensorFlow",Bachelor,1,Gaming,2024-11-05,2025-01-16,2206,8.6,TechCorp Inc -AI13773,NLP Engineer,89837,GBP,67378,MI,FL,United Kingdom,M,Finland,100,"NLP, Java, Data Visualization, Python, Deep Learning",Master,3,Energy,2024-10-08,2024-11-25,1152,8.9,Quantum Computing Inc -AI13774,NLP Engineer,218325,EUR,185576,EX,FT,Germany,M,Germany,100,"NLP, Scala, Git",Master,15,Manufacturing,2024-04-01,2024-06-11,2033,5.6,TechCorp Inc -AI13775,Robotics Engineer,75754,EUR,64391,EN,PT,Germany,M,Germany,100,"Git, Docker, Azure, GCP, Java",Bachelor,1,Government,2024-05-24,2024-08-03,1675,8.8,Future Systems -AI13776,Machine Learning Engineer,117509,EUR,99883,MI,FL,Austria,L,Australia,100,"Java, R, MLOps, Linux",Associate,4,Education,2024-04-20,2024-06-04,1885,7.8,Cloud AI Solutions -AI13777,Data Scientist,84791,USD,84791,EX,FT,India,M,Poland,0,"Python, Java, NLP, GCP",Bachelor,13,Retail,2024-07-03,2024-08-18,925,9.1,Predictive Systems -AI13778,Machine Learning Engineer,55644,USD,55644,EN,FL,South Korea,M,South Korea,100,"Statistics, Kubernetes, R, Linux",PhD,0,Education,2024-01-17,2024-03-23,800,7.5,Advanced Robotics -AI13779,Data Scientist,32651,USD,32651,MI,PT,India,L,India,50,"Computer Vision, NLP, Data Visualization, Python",Bachelor,3,Technology,2024-10-25,2024-12-28,1578,5.3,Neural Networks Co -AI13780,AI Software Engineer,207687,EUR,176534,EX,FT,Germany,M,Israel,50,"Python, Mathematics, Kubernetes",Bachelor,17,Finance,2024-04-19,2024-06-03,707,6.2,Cognitive Computing -AI13781,Machine Learning Engineer,251818,GBP,188864,EX,FT,United Kingdom,L,Latvia,100,"Deep Learning, Linux, Tableau, AWS",PhD,12,Telecommunications,2025-03-18,2025-05-13,775,6.7,Cognitive Computing -AI13782,Computer Vision Engineer,117307,USD,117307,MI,FL,Denmark,S,Denmark,0,"Git, Data Visualization, PyTorch, NLP, Java",PhD,4,Media,2024-08-30,2024-09-29,1371,7.6,Cloud AI Solutions -AI13783,Data Analyst,67912,JPY,7470320,EN,FT,Japan,S,Japan,0,"Scala, SQL, AWS, Docker",Master,0,Technology,2025-04-10,2025-05-14,2390,6,DataVision Ltd -AI13784,Data Engineer,221812,JPY,24399320,EX,FT,Japan,M,Japan,50,"Python, PyTorch, R, Mathematics",Bachelor,19,Gaming,2025-01-21,2025-03-24,1380,7.3,Autonomous Tech -AI13785,NLP Engineer,67496,USD,67496,SE,FT,China,M,Malaysia,100,"R, Hadoop, Computer Vision, Python, Scala",PhD,6,Transportation,2024-11-19,2024-12-15,862,8.1,Cognitive Computing -AI13786,Robotics Engineer,75744,CAD,94680,EN,CT,Canada,M,Canada,0,"Java, Linux, Mathematics",PhD,1,Energy,2024-07-28,2024-09-08,1383,9.6,AI Innovations -AI13787,Deep Learning Engineer,78980,SGD,102674,MI,CT,Singapore,S,Singapore,0,"SQL, PyTorch, Azure, R",PhD,4,Finance,2025-03-17,2025-04-15,1515,7.6,Neural Networks Co -AI13788,AI Consultant,138142,EUR,117421,SE,FL,Netherlands,S,South Africa,0,"Java, MLOps, Scala",PhD,6,Healthcare,2025-04-13,2025-06-14,1676,7.4,Smart Analytics -AI13789,ML Ops Engineer,183795,USD,183795,EX,CT,Sweden,M,Sweden,50,"Spark, Python, Tableau, Azure, GCP",Master,16,Energy,2024-06-20,2024-08-15,858,5.3,Digital Transformation LLC -AI13790,Autonomous Systems Engineer,181750,JPY,19992500,SE,FL,Japan,L,Japan,0,"GCP, Linux, Kubernetes, Scala",PhD,6,Consulting,2024-07-23,2024-09-07,1634,6.1,TechCorp Inc -AI13791,Autonomous Systems Engineer,122129,AUD,164874,SE,FT,Australia,S,Romania,100,"Spark, Kubernetes, MLOps",Master,6,Healthcare,2024-03-14,2024-04-03,685,5.9,Machine Intelligence Group -AI13792,Data Engineer,227275,CHF,204548,EX,CT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Deep Learning, Scala",Bachelor,16,Government,2024-04-10,2024-06-22,768,7.7,Neural Networks Co -AI13793,Machine Learning Engineer,164834,USD,164834,SE,FT,Denmark,S,Czech Republic,50,"SQL, Scala, Hadoop",PhD,9,Education,2024-01-01,2024-01-16,1996,7.8,Cognitive Computing -AI13794,Data Scientist,86870,CHF,78183,EN,FT,Switzerland,M,Brazil,50,"Java, Kubernetes, NLP",PhD,1,Consulting,2024-11-12,2025-01-21,983,5.4,Algorithmic Solutions -AI13795,ML Ops Engineer,75356,USD,75356,EN,FL,Sweden,L,Sweden,50,"Docker, PyTorch, Data Visualization, Azure",Associate,1,Consulting,2024-05-20,2024-07-06,845,9.2,Autonomous Tech -AI13796,AI Research Scientist,70888,USD,70888,MI,FT,Finland,M,Finland,100,"Spark, Mathematics, SQL, AWS",Bachelor,4,Healthcare,2024-11-22,2024-12-10,2303,5.4,DataVision Ltd -AI13797,Research Scientist,85683,AUD,115672,MI,FL,Australia,L,Philippines,100,"Scala, Python, Java, Docker, Data Visualization",Associate,3,Finance,2024-09-13,2024-11-22,1167,9.8,Future Systems -AI13798,Robotics Engineer,136342,EUR,115891,SE,CT,Austria,M,Australia,100,"TensorFlow, Java, MLOps",Bachelor,5,Energy,2024-06-07,2024-07-11,922,8.1,AI Innovations -AI13799,Deep Learning Engineer,308880,CHF,277992,EX,FT,Switzerland,S,Switzerland,0,"Deep Learning, Docker, AWS, Mathematics, Statistics",Associate,15,Automotive,2024-05-29,2024-07-01,1649,9.1,Smart Analytics -AI13800,Machine Learning Engineer,163206,USD,163206,EX,PT,United States,S,United States,50,"PyTorch, Linux, Azure, Hadoop, Kubernetes",Bachelor,19,Energy,2024-02-20,2024-04-18,2044,6.7,Cloud AI Solutions -AI13801,Data Engineer,268727,AUD,362781,EX,FT,Australia,L,Australia,100,"Kubernetes, SQL, Data Visualization, Tableau, Spark",Bachelor,13,Technology,2025-04-26,2025-06-21,1933,6.1,DeepTech Ventures -AI13802,AI Consultant,158218,CAD,197773,EX,PT,Canada,L,Canada,50,"GCP, Python, Computer Vision, Kubernetes, MLOps",Master,19,Technology,2024-03-23,2024-04-08,1759,7,AI Innovations -AI13803,Robotics Engineer,90014,GBP,67511,MI,FT,United Kingdom,S,United Kingdom,0,"Hadoop, Deep Learning, Linux, Java",PhD,3,Real Estate,2024-03-17,2024-04-30,2183,8.9,Cloud AI Solutions -AI13804,Deep Learning Engineer,350601,CHF,315541,EX,FL,Switzerland,M,Switzerland,50,"R, Computer Vision, Hadoop",Bachelor,17,Finance,2024-10-24,2025-01-05,674,7.5,Autonomous Tech -AI13805,Machine Learning Researcher,162040,USD,162040,EX,PT,Denmark,S,Denmark,0,"Statistics, Linux, Deep Learning",Bachelor,11,Government,2024-07-06,2024-08-25,808,6.6,Autonomous Tech -AI13806,AI Research Scientist,195569,CAD,244461,EX,FT,Canada,L,Canada,0,"Scala, TensorFlow, Java, Docker, SQL",Bachelor,14,Telecommunications,2024-01-26,2024-02-21,1230,5,DataVision Ltd -AI13807,AI Consultant,65095,USD,65095,EX,PT,China,S,China,50,"GCP, Mathematics, Python",Associate,14,Consulting,2024-08-05,2024-10-06,1770,5.3,Cognitive Computing -AI13808,Principal Data Scientist,135374,AUD,182755,SE,PT,Australia,S,Estonia,0,"Git, NLP, Linux, Hadoop",Master,6,Manufacturing,2025-02-14,2025-04-10,1991,6.5,Neural Networks Co -AI13809,Machine Learning Engineer,114011,USD,114011,SE,CT,South Korea,M,South Korea,0,"Kubernetes, Python, Linux, NLP",Associate,7,Gaming,2024-11-07,2024-12-28,1423,8.7,Machine Intelligence Group -AI13810,Data Engineer,67057,EUR,56998,MI,FT,Austria,S,Mexico,100,"NLP, Python, Hadoop, Linux, Azure",Associate,2,Education,2024-06-16,2024-08-01,1249,9.3,DeepTech Ventures -AI13811,AI Specialist,59067,EUR,50207,EN,FL,France,L,France,50,"Linux, MLOps, Spark, Python, Git",Bachelor,1,Retail,2024-10-07,2024-10-31,1401,9.7,Quantum Computing Inc -AI13812,AI Architect,178851,USD,178851,SE,FL,United States,L,United States,0,"Python, TensorFlow, GCP, Tableau",Associate,8,Consulting,2024-09-14,2024-11-01,2079,5.4,Neural Networks Co -AI13813,Robotics Engineer,91673,USD,91673,EX,FL,China,S,Spain,0,"Docker, Java, Linux",Master,12,Automotive,2025-03-26,2025-05-18,896,9.3,Machine Intelligence Group -AI13814,Machine Learning Researcher,176800,USD,176800,SE,FL,Norway,M,Austria,100,"Linux, NLP, Scala, Java",Bachelor,6,Manufacturing,2024-06-17,2024-08-03,807,8.2,Cognitive Computing -AI13815,AI Product Manager,56994,GBP,42746,EN,FL,United Kingdom,S,Spain,50,"Docker, Statistics, Scala, Java",Associate,1,Technology,2024-07-07,2024-08-16,1916,5.5,DeepTech Ventures -AI13816,AI Consultant,152056,EUR,129248,SE,CT,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Linux, GCP",Bachelor,7,Automotive,2024-03-08,2024-03-23,711,6.9,Predictive Systems -AI13817,Principal Data Scientist,77428,SGD,100656,MI,PT,Singapore,S,Singapore,100,"PyTorch, Linux, SQL, Data Visualization",Master,4,Government,2024-09-09,2024-10-03,994,9.7,Machine Intelligence Group -AI13818,Computer Vision Engineer,232854,AUD,314353,EX,PT,Australia,M,Turkey,50,"TensorFlow, AWS, Python, NLP",Master,14,Gaming,2024-03-27,2024-05-23,2158,5.8,Autonomous Tech -AI13819,AI Software Engineer,198603,CHF,178743,SE,FL,Switzerland,L,Turkey,100,"Spark, Git, Docker",Master,7,Technology,2025-01-28,2025-04-07,1864,8.2,Cognitive Computing -AI13820,AI Specialist,119402,USD,119402,SE,CT,Finland,L,Finland,100,"GCP, Scala, SQL, Tableau",Master,7,Telecommunications,2024-10-25,2024-12-17,742,8.4,Future Systems -AI13821,Machine Learning Engineer,62647,AUD,84573,EN,FL,Australia,M,Australia,50,"Azure, Git, Computer Vision, Tableau, Docker",Associate,1,Transportation,2024-03-19,2024-04-06,2182,5.9,TechCorp Inc -AI13822,AI Software Engineer,226045,USD,226045,EX,FL,Denmark,S,Latvia,100,"Hadoop, Scala, PyTorch",Associate,17,Education,2024-05-28,2024-07-25,664,7.2,Neural Networks Co -AI13823,Head of AI,220671,AUD,297906,EX,FL,Australia,L,Australia,0,"Kubernetes, MLOps, Mathematics, SQL",Bachelor,10,Energy,2024-10-29,2024-12-11,900,6,TechCorp Inc -AI13824,Principal Data Scientist,88695,CHF,79826,EN,PT,Switzerland,S,Switzerland,50,"NLP, SQL, R, Computer Vision, Docker",Associate,0,Real Estate,2024-07-31,2024-09-18,1805,5.8,DataVision Ltd -AI13825,NLP Engineer,55419,USD,55419,SE,PT,India,L,India,0,"Kubernetes, Computer Vision, Spark, Python, Docker",PhD,9,Energy,2024-04-17,2024-06-28,2238,9.1,AI Innovations -AI13826,AI Architect,121382,USD,121382,MI,FT,Norway,M,Finland,100,"SQL, Scala, Git, Computer Vision",Associate,4,Technology,2024-02-20,2024-03-05,1592,9.6,Digital Transformation LLC -AI13827,AI Research Scientist,80405,EUR,68344,EN,FL,Austria,L,Finland,0,"Azure, Git, Tableau, TensorFlow",Master,1,Education,2024-12-16,2025-01-09,2261,7.1,Predictive Systems -AI13828,NLP Engineer,234097,EUR,198982,EX,CT,France,L,Turkey,0,"Spark, Hadoop, SQL",Master,13,Gaming,2024-05-04,2024-06-14,1819,5.9,Future Systems -AI13829,Robotics Engineer,122139,USD,122139,SE,PT,Finland,M,Turkey,100,"GCP, Kubernetes, Hadoop, MLOps, Scala",Bachelor,8,Consulting,2024-09-08,2024-11-16,1113,9.6,Smart Analytics -AI13830,Autonomous Systems Engineer,61146,EUR,51974,EN,PT,Germany,L,Italy,100,"Computer Vision, Hadoop, Linux, SQL, Statistics",Bachelor,1,Education,2024-12-22,2025-03-03,2096,8.7,Autonomous Tech -AI13831,AI Research Scientist,72035,USD,72035,EN,FL,United States,S,United States,100,"Python, NLP, Docker, Kubernetes, Git",Associate,0,Gaming,2025-02-14,2025-04-22,2448,7,DeepTech Ventures -AI13832,Computer Vision Engineer,224347,USD,224347,EX,FT,Sweden,M,Belgium,50,"TensorFlow, GCP, Scala, R",Associate,19,Government,2025-04-03,2025-06-15,1747,8,Predictive Systems -AI13833,Principal Data Scientist,54240,USD,54240,SE,CT,China,S,Canada,100,"Spark, Python, PyTorch, SQL",Bachelor,5,Telecommunications,2024-08-16,2024-10-22,1611,7.8,Machine Intelligence Group -AI13834,Principal Data Scientist,153995,USD,153995,SE,FL,Denmark,M,Denmark,0,"GCP, Data Visualization, R",Associate,5,Retail,2024-09-07,2024-10-26,1386,9.7,Predictive Systems -AI13835,Autonomous Systems Engineer,196504,USD,196504,SE,FT,United States,L,United Kingdom,0,"Hadoop, Docker, TensorFlow, Mathematics, Git",Associate,6,Real Estate,2024-09-22,2024-10-06,2223,8.4,Predictive Systems -AI13836,Deep Learning Engineer,164839,GBP,123629,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, MLOps, R, GCP",Bachelor,10,Government,2024-12-24,2025-01-08,2256,10,AI Innovations -AI13837,NLP Engineer,57984,USD,57984,EN,PT,South Korea,M,South Korea,50,"Python, Mathematics, TensorFlow",Bachelor,0,Energy,2025-02-20,2025-05-03,2117,7.1,Advanced Robotics -AI13838,AI Architect,269893,EUR,229409,EX,PT,Netherlands,L,Germany,100,"Azure, Data Visualization, Git",PhD,13,Education,2025-03-24,2025-04-08,2342,5.2,Cloud AI Solutions -AI13839,Data Analyst,72103,EUR,61288,EN,FT,Netherlands,S,Netherlands,100,"Mathematics, Computer Vision, SQL, Kubernetes",Bachelor,1,Education,2025-02-13,2025-04-19,1864,5.7,Neural Networks Co -AI13840,Principal Data Scientist,130093,JPY,14310230,SE,PT,Japan,S,Japan,50,"Data Visualization, Git, Mathematics, Deep Learning, NLP",Master,7,Media,2024-12-05,2025-01-30,1903,8.2,Algorithmic Solutions -AI13841,AI Specialist,68572,USD,68572,EN,FT,Ireland,L,Ireland,100,"Kubernetes, Java, GCP, Mathematics, Scala",Associate,0,Technology,2024-12-15,2024-12-31,663,7.8,Cloud AI Solutions -AI13842,AI Architect,55431,EUR,47116,EN,FT,Germany,M,Germany,0,"PyTorch, Java, Statistics",Bachelor,1,Gaming,2024-05-01,2024-05-27,585,5.5,Future Systems -AI13843,AI Consultant,104409,AUD,140952,MI,FT,Australia,L,Hungary,100,"R, Python, GCP",Master,2,Finance,2024-07-06,2024-08-17,1477,6.3,Smart Analytics -AI13844,AI Product Manager,98179,USD,98179,MI,CT,Norway,S,Norway,100,"PyTorch, TensorFlow, Java, Hadoop",PhD,2,Technology,2024-10-30,2024-12-28,1392,9.2,Smart Analytics -AI13845,AI Product Manager,138780,USD,138780,EX,FT,Finland,S,New Zealand,0,"Deep Learning, Data Visualization, Python",PhD,11,Retail,2024-03-19,2024-05-12,2161,5.6,AI Innovations -AI13846,Principal Data Scientist,222699,CHF,200429,SE,PT,Switzerland,L,Switzerland,50,"Python, Linux, SQL",Bachelor,9,Retail,2025-01-22,2025-03-10,849,6.4,DeepTech Ventures -AI13847,AI Architect,50170,USD,50170,EN,PT,South Korea,L,South Korea,0,"PyTorch, Python, MLOps",Master,1,Retail,2025-04-16,2025-05-10,2460,7.6,Advanced Robotics -AI13848,Research Scientist,38746,USD,38746,MI,FT,China,S,Philippines,0,"R, Git, Tableau, Scala, Docker",PhD,4,Manufacturing,2025-03-10,2025-05-08,2240,5.9,Predictive Systems -AI13849,Principal Data Scientist,74319,USD,74319,EN,PT,Israel,M,Canada,100,"Python, Scala, AWS",Associate,0,Education,2025-02-20,2025-03-06,1598,9.8,Cognitive Computing -AI13850,Data Engineer,273668,JPY,30103480,EX,PT,Japan,L,Ghana,100,"Tableau, Spark, Deep Learning, GCP, Python",Bachelor,10,Education,2024-08-18,2024-09-08,2356,7.9,Cloud AI Solutions -AI13851,Data Engineer,66041,USD,66041,EN,PT,Denmark,M,Ukraine,100,"Mathematics, TensorFlow, Git, Python, Linux",Master,0,Telecommunications,2024-11-18,2024-12-30,1290,5.5,Advanced Robotics -AI13852,AI Product Manager,75268,EUR,63978,EN,PT,Germany,M,Germany,100,"Data Visualization, Scala, Statistics, NLP",Bachelor,1,Transportation,2024-12-18,2025-01-24,1933,7.4,Future Systems -AI13853,Robotics Engineer,177163,EUR,150589,EX,CT,Germany,M,Russia,100,"Java, Spark, Computer Vision, Docker",Master,13,Retail,2025-01-01,2025-02-11,1434,9.5,Advanced Robotics -AI13854,AI Software Engineer,169340,JPY,18627400,EX,CT,Japan,L,Japan,50,"Kubernetes, Computer Vision, Python, Scala",Master,16,Retail,2024-12-16,2025-02-18,903,9,DeepTech Ventures -AI13855,Research Scientist,150295,SGD,195384,SE,FT,Singapore,M,Malaysia,50,"R, Python, Data Visualization",Associate,5,Real Estate,2024-02-24,2024-04-01,1181,5.5,Neural Networks Co -AI13856,AI Product Manager,154260,CHF,138834,SE,FL,Switzerland,M,Germany,50,"GCP, Python, Tableau, Statistics, Mathematics",Associate,6,Gaming,2024-06-26,2024-07-13,1751,7.1,Predictive Systems -AI13857,AI Specialist,100497,CAD,125621,MI,CT,Canada,M,Canada,50,"TensorFlow, Python, Java",PhD,2,Retail,2024-12-24,2025-02-12,2099,6.5,DeepTech Ventures -AI13858,Machine Learning Engineer,193134,USD,193134,EX,FL,Sweden,L,South Korea,50,"Kubernetes, GCP, Python",Associate,14,Consulting,2024-08-13,2024-10-23,786,6.8,Algorithmic Solutions -AI13859,ML Ops Engineer,170026,CHF,153023,MI,FL,Switzerland,L,Switzerland,50,"Hadoop, Azure, Tableau, Data Visualization, Git",Bachelor,3,Automotive,2024-09-18,2024-11-07,2419,7.7,AI Innovations -AI13860,Data Analyst,237130,USD,237130,EX,FL,Finland,M,Hungary,50,"AWS, Hadoop, Tableau, Git",Associate,13,Technology,2024-01-23,2024-03-02,1588,7.8,Algorithmic Solutions -AI13861,Principal Data Scientist,122855,CHF,110570,MI,CT,Switzerland,S,Switzerland,100,"AWS, R, Git",PhD,4,Healthcare,2024-09-08,2024-11-18,1670,8.5,Smart Analytics -AI13862,AI Consultant,73055,CHF,65750,EN,FL,Switzerland,S,Egypt,50,"TensorFlow, Python, Docker, Statistics",PhD,0,Media,2024-08-22,2024-10-22,1510,8.9,Future Systems -AI13863,Research Scientist,38444,USD,38444,SE,CT,India,S,India,100,"PyTorch, Linux, TensorFlow, Data Visualization",Associate,9,Transportation,2024-06-14,2024-07-23,1791,9.6,Machine Intelligence Group -AI13864,Data Scientist,174441,USD,174441,EX,PT,Ireland,M,Romania,50,"Data Visualization, Azure, Python",Bachelor,11,Real Estate,2025-02-26,2025-03-27,1148,9.5,Future Systems -AI13865,AI Research Scientist,120189,USD,120189,SE,FL,Denmark,S,Denmark,0,"Python, SQL, Scala, TensorFlow, AWS",Master,5,Telecommunications,2025-04-06,2025-06-12,953,9.9,Future Systems -AI13866,Principal Data Scientist,112460,USD,112460,SE,PT,Ireland,S,Ireland,100,"Azure, Python, GCP, Scala, Mathematics",Associate,8,Technology,2024-08-17,2024-09-22,2399,9.8,Autonomous Tech -AI13867,AI Architect,230551,AUD,311244,EX,CT,Australia,M,Australia,100,"Spark, Statistics, Scala, Computer Vision, SQL",Bachelor,17,Education,2024-03-28,2024-05-17,1060,5.4,Neural Networks Co -AI13868,AI Research Scientist,143999,EUR,122399,SE,FL,Netherlands,L,Netherlands,0,"Deep Learning, Python, NLP, Hadoop, Java",PhD,6,Consulting,2024-05-05,2024-06-29,2418,8.8,Quantum Computing Inc -AI13869,AI Specialist,181922,CHF,163730,SE,CT,Switzerland,L,Hungary,50,"AWS, Git, Java",PhD,7,Transportation,2025-04-08,2025-06-03,1333,9.8,Cloud AI Solutions -AI13870,Autonomous Systems Engineer,121801,USD,121801,SE,FL,South Korea,L,France,0,"Python, TensorFlow, Computer Vision",Bachelor,8,Telecommunications,2024-04-09,2024-04-25,739,10,AI Innovations -AI13871,Research Scientist,158462,GBP,118847,SE,PT,United Kingdom,M,United Kingdom,0,"R, Python, PyTorch, Git, SQL",Master,9,Manufacturing,2024-04-12,2024-05-03,2349,9.4,Future Systems -AI13872,NLP Engineer,113678,USD,113678,SE,CT,Finland,L,Finland,0,"Python, Computer Vision, Linux, Azure",Bachelor,7,Education,2024-12-07,2025-02-04,1789,9.6,Future Systems -AI13873,ML Ops Engineer,151647,GBP,113735,SE,CT,United Kingdom,M,United Kingdom,50,"Git, R, Java",Bachelor,7,Telecommunications,2024-08-05,2024-09-18,1696,8.9,Quantum Computing Inc -AI13874,AI Software Engineer,111894,USD,111894,SE,FL,United States,S,United States,0,"Deep Learning, Kubernetes, Scala",PhD,8,Energy,2024-04-04,2024-04-22,1512,7.9,Advanced Robotics -AI13875,Autonomous Systems Engineer,99898,USD,99898,MI,PT,Sweden,M,Sweden,100,"Linux, Python, TensorFlow, Scala",PhD,3,Gaming,2024-08-24,2024-10-23,2166,7.9,TechCorp Inc -AI13876,Computer Vision Engineer,88708,USD,88708,MI,PT,Sweden,M,Egypt,50,"Computer Vision, MLOps, Java, Kubernetes, Docker",Master,2,Retail,2025-01-23,2025-04-02,788,8.2,Quantum Computing Inc -AI13877,AI Specialist,101550,JPY,11170500,MI,CT,Japan,M,Russia,0,"AWS, R, Deep Learning, Python",Master,4,Transportation,2024-05-27,2024-07-19,2250,7.9,TechCorp Inc -AI13878,ML Ops Engineer,69360,CAD,86700,EN,CT,Canada,L,Canada,100,"Kubernetes, Scala, Computer Vision",PhD,1,Retail,2024-05-19,2024-06-15,540,7.1,TechCorp Inc -AI13879,Robotics Engineer,124351,SGD,161656,SE,PT,Singapore,S,Singapore,100,"MLOps, SQL, Data Visualization, TensorFlow",Bachelor,6,Healthcare,2024-05-22,2024-06-11,2292,7.5,Quantum Computing Inc -AI13880,AI Specialist,174613,GBP,130960,EX,CT,United Kingdom,S,Finland,100,"SQL, Azure, NLP, Hadoop",Bachelor,17,Healthcare,2024-09-26,2024-10-15,2365,5.6,Machine Intelligence Group -AI13881,AI Software Engineer,164314,GBP,123236,SE,FT,United Kingdom,L,United Kingdom,0,"Git, Deep Learning, MLOps, Java",Bachelor,7,Healthcare,2025-01-11,2025-03-25,1645,8.6,TechCorp Inc -AI13882,NLP Engineer,33496,USD,33496,MI,FT,India,M,India,100,"PyTorch, Kubernetes, Deep Learning, MLOps, GCP",Associate,4,Telecommunications,2024-04-21,2024-07-01,1093,8,Advanced Robotics -AI13883,NLP Engineer,90700,USD,90700,EN,CT,United States,M,United States,50,"Tableau, Data Visualization, SQL, Python, GCP",Master,0,Government,2024-11-18,2025-01-20,1192,9.6,Neural Networks Co -AI13884,Machine Learning Researcher,43580,USD,43580,SE,PT,India,L,India,0,"Python, Computer Vision, Data Visualization",Associate,6,Healthcare,2025-01-19,2025-02-10,725,9.1,Future Systems -AI13885,Autonomous Systems Engineer,134932,USD,134932,SE,PT,United States,S,United States,0,"GCP, Python, PyTorch, Computer Vision, Hadoop",Master,8,Media,2024-04-05,2024-04-24,1152,5.6,TechCorp Inc -AI13886,Machine Learning Researcher,97649,USD,97649,MI,PT,Denmark,S,Denmark,100,"Python, Azure, GCP, Scala, Docker",Associate,2,Transportation,2024-02-26,2024-04-26,1846,9.1,Algorithmic Solutions -AI13887,Data Scientist,150764,EUR,128149,EX,FT,Germany,S,Ukraine,100,"Azure, Data Visualization, AWS, Python, Computer Vision",Bachelor,15,Healthcare,2024-10-24,2024-12-25,1536,9.2,Machine Intelligence Group -AI13888,Machine Learning Engineer,136387,GBP,102290,SE,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Statistics",PhD,9,Gaming,2025-01-20,2025-02-10,2089,9.9,Advanced Robotics -AI13889,AI Research Scientist,99958,USD,99958,MI,CT,United States,M,United States,100,"Linux, Kubernetes, Java, Computer Vision, NLP",Master,3,Government,2024-06-03,2024-07-14,1509,5.7,Neural Networks Co -AI13890,Autonomous Systems Engineer,98300,CAD,122875,SE,PT,Canada,S,Canada,0,"Python, Data Visualization, TensorFlow",Associate,7,Technology,2025-01-04,2025-03-07,566,5.5,Advanced Robotics -AI13891,Machine Learning Researcher,22579,USD,22579,EN,FT,India,S,India,100,"TensorFlow, SQL, Azure",Associate,0,Telecommunications,2024-05-19,2024-06-05,548,5.6,Future Systems -AI13892,Data Engineer,159778,USD,159778,SE,CT,Ireland,L,Romania,100,"Spark, Kubernetes, SQL, PyTorch",Bachelor,8,Manufacturing,2024-12-02,2025-02-11,1797,9.3,Autonomous Tech -AI13893,Autonomous Systems Engineer,52353,USD,52353,EX,CT,India,M,India,50,"R, Computer Vision, MLOps, Spark",Master,19,Government,2024-05-01,2024-06-16,2384,6.8,TechCorp Inc -AI13894,Data Scientist,82987,EUR,70539,MI,FT,Netherlands,M,Netherlands,0,"PyTorch, TensorFlow, NLP, R, Python",Master,2,Automotive,2025-02-09,2025-03-28,2186,9.1,Cognitive Computing -AI13895,Machine Learning Engineer,76339,USD,76339,SE,FL,South Korea,S,South Korea,50,"Python, GCP, Computer Vision",Associate,5,Healthcare,2025-02-19,2025-04-15,521,7.2,DeepTech Ventures -AI13896,Research Scientist,100750,USD,100750,EN,FL,Norway,L,Norway,50,"Azure, R, Docker",Master,1,Gaming,2024-09-26,2024-11-10,1045,7.3,Quantum Computing Inc -AI13897,Principal Data Scientist,73199,SGD,95159,EN,FT,Singapore,S,Singapore,50,"Python, PyTorch, Hadoop, Java",PhD,1,Government,2024-09-24,2024-11-02,668,5.6,Algorithmic Solutions -AI13898,Computer Vision Engineer,76495,USD,76495,EN,FT,United States,M,United States,100,"R, Docker, Data Visualization, NLP, PyTorch",Master,1,Automotive,2025-01-19,2025-03-12,1924,7.5,Algorithmic Solutions -AI13899,Machine Learning Researcher,101641,USD,101641,EN,FT,Norway,M,Norway,100,"Azure, NLP, SQL, Computer Vision, PyTorch",Bachelor,0,Technology,2024-01-03,2024-01-18,1481,5.7,Advanced Robotics -AI13900,Head of AI,66025,EUR,56121,EN,PT,Germany,M,Germany,50,"Python, R, TensorFlow, Statistics, AWS",Bachelor,1,Transportation,2024-07-20,2024-08-03,908,9,Machine Intelligence Group -AI13901,AI Product Manager,55150,USD,55150,SE,FT,India,L,India,100,"Hadoop, Tableau, Scala",Master,6,Energy,2025-02-20,2025-04-07,2055,9.2,DeepTech Ventures -AI13902,Data Engineer,132349,GBP,99262,EX,FT,United Kingdom,S,United Kingdom,50,"Spark, Tableau, AWS, Java",Master,17,Healthcare,2024-08-31,2024-10-30,750,5.6,Algorithmic Solutions -AI13903,AI Software Engineer,84903,EUR,72168,MI,PT,Netherlands,M,Netherlands,0,"Kubernetes, PyTorch, Data Visualization, Computer Vision",Bachelor,3,Manufacturing,2024-02-06,2024-04-15,761,5.5,Autonomous Tech -AI13904,Robotics Engineer,172144,JPY,18935840,SE,FT,Japan,L,Kenya,50,"Git, PyTorch, Java, Spark",Master,9,Telecommunications,2025-01-04,2025-02-06,710,6.3,TechCorp Inc -AI13905,AI Software Engineer,83302,SGD,108293,EN,PT,Singapore,M,Singapore,50,"Mathematics, Deep Learning, Python, Kubernetes, Azure",Bachelor,1,Media,2025-04-10,2025-05-09,2257,7.8,Cloud AI Solutions -AI13906,NLP Engineer,109085,CHF,98177,MI,CT,Switzerland,S,Australia,50,"SQL, Data Visualization, AWS, MLOps",Bachelor,3,Retail,2024-01-01,2024-02-09,1601,7.5,Neural Networks Co -AI13907,Machine Learning Engineer,354720,CHF,319248,EX,FT,Switzerland,M,Denmark,100,"SQL, Java, Linux",Master,17,Finance,2024-06-27,2024-07-19,1806,5.9,DeepTech Ventures -AI13908,Data Engineer,106171,EUR,90245,SE,PT,France,M,Ukraine,0,"Scala, Deep Learning, Computer Vision",Bachelor,5,Finance,2024-08-13,2024-09-08,1723,8.6,Cloud AI Solutions -AI13909,AI Specialist,86810,USD,86810,EX,PT,India,M,Germany,50,"Spark, PyTorch, Git, Data Visualization",Master,15,Energy,2024-05-29,2024-07-01,1002,8.6,Algorithmic Solutions -AI13910,Machine Learning Engineer,131624,USD,131624,SE,CT,Sweden,M,Ireland,50,"Docker, Linux, Kubernetes, NLP",PhD,8,Transportation,2024-02-11,2024-04-22,1531,9,DeepTech Ventures -AI13911,AI Research Scientist,68905,SGD,89577,EN,FL,Singapore,S,Singapore,50,"Kubernetes, R, TensorFlow, Statistics, Hadoop",Bachelor,0,Government,2024-03-06,2024-04-17,775,6.6,Predictive Systems -AI13912,Machine Learning Engineer,134463,GBP,100847,SE,FL,United Kingdom,M,Netherlands,0,"Spark, Linux, TensorFlow, Java",Bachelor,5,Manufacturing,2025-04-11,2025-05-04,1935,5.3,Quantum Computing Inc -AI13913,Principal Data Scientist,98904,USD,98904,EX,FL,India,L,India,0,"Git, GCP, Tableau, Spark, Scala",Master,14,Energy,2024-02-25,2024-04-09,1310,9.9,Digital Transformation LLC -AI13914,Data Engineer,257480,USD,257480,EX,FT,Norway,S,Japan,0,"GCP, Statistics, Linux, Scala, R",Master,13,Energy,2024-11-24,2025-01-09,890,5.5,Digital Transformation LLC -AI13915,AI Architect,117881,SGD,153245,SE,FL,Singapore,S,Singapore,0,"SQL, Git, Data Visualization, PyTorch, MLOps",Master,7,Government,2025-04-03,2025-06-01,680,9.4,Future Systems -AI13916,ML Ops Engineer,131840,EUR,112064,EX,CT,France,M,France,50,"Kubernetes, Java, Azure, Python, TensorFlow",PhD,13,Consulting,2024-07-24,2024-08-17,1098,8.7,AI Innovations -AI13917,Machine Learning Researcher,235864,SGD,306623,EX,PT,Singapore,S,Romania,0,"R, Data Visualization, GCP, Tableau",PhD,12,Technology,2024-12-30,2025-02-10,1394,8.7,DataVision Ltd -AI13918,Robotics Engineer,151764,EUR,128999,SE,FL,Germany,M,Germany,100,"Python, TensorFlow, Java, PyTorch, Mathematics",Associate,6,Media,2024-12-08,2025-01-21,2196,7.8,Future Systems -AI13919,AI Consultant,120897,USD,120897,MI,CT,Norway,L,Turkey,0,"GCP, Spark, Deep Learning",PhD,3,Retail,2025-03-16,2025-05-03,1528,5.6,DataVision Ltd -AI13920,Deep Learning Engineer,319778,USD,319778,EX,CT,Denmark,M,Denmark,0,"MLOps, Tableau, Linux, Git",Bachelor,18,Energy,2024-10-18,2024-11-05,1330,7.2,Cloud AI Solutions -AI13921,Data Engineer,213125,EUR,181156,EX,CT,Germany,M,Philippines,100,"TensorFlow, MLOps, GCP, Java",PhD,16,Energy,2025-01-11,2025-03-14,1895,8.2,TechCorp Inc -AI13922,AI Specialist,99994,EUR,84995,MI,PT,Netherlands,L,Czech Republic,50,"Computer Vision, AWS, TensorFlow, Python, R",Bachelor,2,Retail,2025-04-14,2025-06-13,1090,5.2,Algorithmic Solutions -AI13923,Deep Learning Engineer,42397,USD,42397,EN,FT,China,L,China,0,"TensorFlow, AWS, Azure, PyTorch",Master,1,Gaming,2024-03-01,2024-04-13,2322,6.3,AI Innovations -AI13924,Data Engineer,268816,GBP,201612,EX,CT,United Kingdom,M,United Kingdom,50,"Tableau, SQL, R, Docker, Kubernetes",Master,11,Telecommunications,2025-01-07,2025-03-02,1846,7.4,Cloud AI Solutions -AI13925,Machine Learning Engineer,146336,USD,146336,MI,CT,Denmark,L,United States,0,"PyTorch, R, Mathematics",Bachelor,4,Automotive,2024-11-15,2024-12-13,1227,8.2,Digital Transformation LLC -AI13926,ML Ops Engineer,163963,EUR,139369,EX,PT,Germany,M,Israel,100,"SQL, Data Visualization, Hadoop",PhD,15,Government,2024-08-13,2024-10-15,916,6.7,Predictive Systems -AI13927,Research Scientist,50533,USD,50533,SE,PT,India,M,India,0,"Statistics, R, Computer Vision, Hadoop, Git",Bachelor,5,Energy,2024-03-31,2024-05-29,1703,5.5,Smart Analytics -AI13928,AI Architect,82127,SGD,106765,EN,FT,Singapore,L,Colombia,50,"AWS, Spark, Linux, TensorFlow, Python",Master,0,Energy,2024-12-25,2025-01-23,2258,5.2,Cloud AI Solutions -AI13929,AI Consultant,116006,GBP,87005,SE,FT,United Kingdom,S,United Kingdom,50,"Python, PyTorch, Tableau, Mathematics, MLOps",Master,9,Education,2024-08-12,2024-10-10,1582,8,Algorithmic Solutions -AI13930,Robotics Engineer,126184,USD,126184,MI,PT,Norway,M,Norway,100,"Java, Linux, TensorFlow, R, Data Visualization",Master,4,Transportation,2024-11-14,2024-12-31,1710,5.6,Predictive Systems -AI13931,Machine Learning Researcher,160147,EUR,136125,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, TensorFlow, NLP, Statistics, Data Visualization",Master,7,Manufacturing,2024-04-13,2024-06-12,1699,5.9,Predictive Systems -AI13932,AI Product Manager,107865,SGD,140225,MI,CT,Singapore,M,Vietnam,100,"Python, Data Visualization, TensorFlow, PyTorch",Master,4,Gaming,2025-01-11,2025-02-26,1084,9.1,DeepTech Ventures -AI13933,AI Architect,187028,CHF,168325,SE,FT,Switzerland,S,Switzerland,0,"Python, Docker, Hadoop, Azure",Master,7,Transportation,2024-04-15,2024-06-12,1931,9,Machine Intelligence Group -AI13934,ML Ops Engineer,110875,CHF,99788,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, Python, Data Visualization",Master,3,Education,2024-12-13,2025-01-14,1288,7.1,Autonomous Tech -AI13935,Data Engineer,206757,USD,206757,EX,FL,United States,S,Ghana,0,"Scala, PyTorch, Data Visualization, GCP",PhD,13,Technology,2024-11-09,2024-12-02,1852,8.6,Advanced Robotics -AI13936,Machine Learning Engineer,56474,USD,56474,EN,FT,Ireland,M,Ireland,50,"Python, R, PyTorch",Bachelor,0,Government,2024-08-11,2024-09-09,1099,8.2,Cognitive Computing -AI13937,AI Specialist,85570,USD,85570,EX,FL,India,M,Italy,0,"PyTorch, TensorFlow, Linux, NLP",Bachelor,15,Automotive,2024-02-19,2024-04-21,689,7.9,Digital Transformation LLC -AI13938,Autonomous Systems Engineer,212458,CHF,191212,SE,FL,Switzerland,L,Switzerland,100,"Scala, Python, TensorFlow",Bachelor,6,Manufacturing,2024-06-06,2024-07-22,889,9.5,Advanced Robotics -AI13939,AI Architect,70580,SGD,91754,EN,PT,Singapore,S,Chile,100,"Azure, GCP, Python",Associate,1,Media,2024-01-16,2024-02-12,1169,9.8,AI Innovations -AI13940,Data Engineer,36309,USD,36309,SE,CT,India,S,Norway,100,"Linux, Git, Kubernetes, PyTorch, SQL",Master,9,Consulting,2024-05-21,2024-07-06,747,6.6,DeepTech Ventures -AI13941,Deep Learning Engineer,64560,USD,64560,EN,FT,Israel,M,Turkey,50,"Python, Data Visualization, Linux, Kubernetes, Computer Vision",Bachelor,0,Technology,2024-12-18,2025-02-16,1314,6,Smart Analytics -AI13942,Deep Learning Engineer,94949,EUR,80707,MI,CT,France,L,France,100,"R, Computer Vision, Data Visualization, Java",Bachelor,4,Transportation,2024-08-19,2024-09-25,979,6,Cloud AI Solutions -AI13943,Research Scientist,74347,USD,74347,MI,PT,South Korea,M,South Korea,50,"PyTorch, GCP, Scala, Java",Bachelor,3,Media,2024-10-04,2024-12-01,1926,7.9,AI Innovations -AI13944,AI Product Manager,321456,USD,321456,EX,FL,United States,L,United States,100,"Docker, GCP, Statistics",Master,15,Automotive,2024-10-25,2024-12-06,1311,8.6,Quantum Computing Inc -AI13945,Head of AI,72159,EUR,61335,EN,FT,Germany,L,Germany,0,"R, Spark, Mathematics",PhD,0,Retail,2024-04-16,2024-06-08,1412,8.4,Advanced Robotics -AI13946,Machine Learning Researcher,185190,USD,185190,EX,PT,Finland,S,Finland,100,"GCP, Scala, MLOps, Python, Azure",Bachelor,12,Automotive,2024-07-10,2024-09-20,977,8.5,Autonomous Tech -AI13947,AI Product Manager,150333,EUR,127783,SE,FT,Germany,L,Poland,0,"R, Azure, Git, Python",PhD,9,Automotive,2025-01-18,2025-02-24,1452,9.1,Quantum Computing Inc -AI13948,Research Scientist,265558,AUD,358503,EX,PT,Australia,L,Australia,0,"Java, Deep Learning, NLP",Master,12,Education,2024-06-07,2024-07-09,874,9.9,Cognitive Computing -AI13949,Machine Learning Researcher,82299,EUR,69954,MI,FT,Austria,L,Kenya,0,"Data Visualization, Deep Learning, Java",Master,2,Consulting,2024-11-14,2024-12-25,981,8.1,Cloud AI Solutions -AI13950,AI Specialist,148281,JPY,16310910,SE,FL,Japan,L,Japan,50,"Linux, Java, R, Kubernetes",PhD,5,Healthcare,2025-03-02,2025-03-17,892,7.8,Cognitive Computing -AI13951,AI Product Manager,33202,USD,33202,MI,FT,China,S,China,0,"Java, Python, Data Visualization, TensorFlow, Git",Bachelor,2,Education,2024-05-18,2024-07-19,821,8.5,Algorithmic Solutions -AI13952,AI Software Engineer,67300,USD,67300,EN,CT,Israel,M,Israel,0,"TensorFlow, Python, Linux, Statistics",Bachelor,0,Finance,2024-05-23,2024-06-25,2327,7.1,Cloud AI Solutions -AI13953,AI Product Manager,120081,USD,120081,MI,FL,Ireland,L,Ireland,100,"Data Visualization, R, Azure",Master,4,Real Estate,2024-01-15,2024-02-21,2086,7.6,Cognitive Computing -AI13954,Machine Learning Engineer,73036,EUR,62081,MI,CT,France,S,France,0,"Python, MLOps, Tableau",PhD,2,Technology,2025-04-08,2025-05-05,1365,9.2,AI Innovations -AI13955,Robotics Engineer,87908,USD,87908,EN,FT,Norway,S,Norway,100,"Kubernetes, Data Visualization, NLP, R, TensorFlow",Associate,0,Consulting,2024-11-29,2025-01-21,609,8.3,Quantum Computing Inc -AI13956,Machine Learning Researcher,70146,USD,70146,EX,PT,India,S,India,0,"Git, Python, Data Visualization, Linux, Scala",Bachelor,14,Education,2024-05-14,2024-07-25,669,5.5,DeepTech Ventures -AI13957,Principal Data Scientist,32133,USD,32133,MI,FL,India,S,India,100,"Azure, Python, Tableau, GCP",Bachelor,3,Media,2024-10-21,2024-12-25,1969,8.9,Algorithmic Solutions -AI13958,Data Scientist,108840,JPY,11972400,SE,CT,Japan,S,Japan,50,"TensorFlow, Kubernetes, GCP, Spark",Associate,8,Consulting,2024-06-17,2024-07-06,1758,7.5,Neural Networks Co -AI13959,Machine Learning Researcher,122926,EUR,104487,SE,PT,Netherlands,M,United States,0,"Kubernetes, Scala, Tableau",Master,9,Retail,2024-03-17,2024-04-03,1477,8.5,Autonomous Tech -AI13960,AI Product Manager,287863,CHF,259077,EX,PT,Switzerland,M,Norway,50,"Scala, Deep Learning, Hadoop",PhD,19,Automotive,2024-04-07,2024-05-24,1944,6.5,Predictive Systems -AI13961,Machine Learning Engineer,99266,USD,99266,SE,FT,Ireland,S,Ireland,50,"MLOps, Spark, PyTorch",Associate,7,Finance,2024-07-15,2024-08-10,2461,5.3,Neural Networks Co -AI13962,NLP Engineer,228899,JPY,25178890,EX,FT,Japan,M,China,50,"MLOps, Docker, Kubernetes, Python, AWS",PhD,18,Real Estate,2024-06-05,2024-07-28,2258,8.4,Advanced Robotics -AI13963,Data Scientist,162574,USD,162574,EX,PT,Ireland,M,Ireland,100,"Kubernetes, Spark, Tableau, Deep Learning",Bachelor,16,Real Estate,2024-10-29,2024-12-21,2146,6.7,AI Innovations -AI13964,Data Engineer,225255,USD,225255,EX,PT,Finland,L,Finland,100,"Deep Learning, Computer Vision, Tableau, Azure, Docker",PhD,13,Manufacturing,2024-06-12,2024-08-12,632,5.5,Autonomous Tech -AI13965,Head of AI,132938,CHF,119644,MI,FL,Switzerland,S,Switzerland,0,"Git, Azure, MLOps, Linux, R",PhD,2,Education,2025-02-04,2025-03-01,551,9.9,Smart Analytics -AI13966,AI Consultant,90671,USD,90671,SE,FT,Israel,S,Poland,50,"PyTorch, Kubernetes, TensorFlow, SQL",PhD,7,Finance,2025-02-08,2025-02-25,2316,9.8,Algorithmic Solutions -AI13967,AI Architect,179691,SGD,233598,EX,CT,Singapore,L,Singapore,0,"Scala, MLOps, Python",Bachelor,13,Telecommunications,2024-10-13,2024-12-18,1094,7.5,Cognitive Computing -AI13968,AI Specialist,80674,USD,80674,EX,FL,India,L,India,0,"Git, PyTorch, Hadoop",PhD,13,Real Estate,2024-06-30,2024-07-27,1834,9.6,Quantum Computing Inc -AI13969,Research Scientist,96450,CAD,120563,SE,PT,Canada,S,Canada,50,"Hadoop, Python, TensorFlow, Computer Vision",Master,9,Transportation,2024-03-17,2024-05-05,1744,5.3,TechCorp Inc -AI13970,AI Research Scientist,132495,USD,132495,SE,FL,Sweden,L,Sweden,50,"Kubernetes, Docker, NLP",Bachelor,9,Automotive,2024-10-12,2024-12-04,1918,8.9,Cloud AI Solutions -AI13971,Machine Learning Engineer,70645,CAD,88306,EN,CT,Canada,L,Canada,50,"Linux, Tableau, Python, PyTorch",Associate,1,Media,2025-03-27,2025-05-11,1527,9.3,Machine Intelligence Group -AI13972,Robotics Engineer,24476,USD,24476,EN,PT,China,S,China,50,"Statistics, Scala, Java, MLOps, Deep Learning",Associate,1,Telecommunications,2024-12-18,2025-01-21,996,7.5,Neural Networks Co -AI13973,Machine Learning Engineer,219297,SGD,285086,EX,FL,Singapore,L,Singapore,50,"Kubernetes, Scala, Spark, Deep Learning, Statistics",Associate,15,Automotive,2024-06-27,2024-07-25,705,6.6,Machine Intelligence Group -AI13974,Computer Vision Engineer,139564,GBP,104673,EX,PT,United Kingdom,S,United Kingdom,100,"Linux, GCP, Scala",PhD,15,Telecommunications,2025-03-10,2025-04-17,1455,9.2,Machine Intelligence Group -AI13975,NLP Engineer,232693,USD,232693,EX,FT,United States,S,United States,50,"Computer Vision, Python, TensorFlow, Java, R",PhD,14,Gaming,2024-06-29,2024-08-03,2116,7.7,AI Innovations -AI13976,Machine Learning Engineer,97324,USD,97324,MI,PT,Ireland,S,Sweden,50,"AWS, Linux, NLP, Kubernetes",PhD,3,Energy,2024-01-31,2024-04-01,970,6.7,Autonomous Tech -AI13977,AI Specialist,83572,USD,83572,MI,FT,South Korea,L,Italy,0,"Docker, Hadoop, Kubernetes, Statistics, R",Bachelor,3,Real Estate,2024-01-03,2024-03-13,2121,8.2,Cloud AI Solutions -AI13978,Computer Vision Engineer,119106,USD,119106,MI,FL,United States,M,Nigeria,100,"Tableau, Java, Python",Bachelor,2,Government,2025-04-19,2025-06-14,1345,7.8,Machine Intelligence Group -AI13979,Deep Learning Engineer,107752,SGD,140078,MI,PT,Singapore,L,Singapore,100,"AWS, Docker, Data Visualization, GCP, Kubernetes",Master,2,Energy,2024-06-08,2024-06-28,2045,5.3,Cloud AI Solutions -AI13980,AI Consultant,62312,SGD,81006,EN,FL,Singapore,M,Singapore,0,"Deep Learning, Data Visualization, Python, Tableau, MLOps",PhD,1,Education,2024-05-02,2024-05-26,1829,7.8,Neural Networks Co -AI13981,Principal Data Scientist,118029,USD,118029,SE,FT,Ireland,L,Ireland,0,"TensorFlow, SQL, Tableau",PhD,7,Retail,2024-05-14,2024-07-25,1262,7.4,TechCorp Inc -AI13982,Computer Vision Engineer,204810,AUD,276494,EX,FL,Australia,S,Australia,0,"AWS, Data Visualization, R, NLP",Master,18,Retail,2024-01-28,2024-03-03,727,6.1,Neural Networks Co -AI13983,Research Scientist,79470,EUR,67550,MI,FT,Netherlands,M,Portugal,100,"Deep Learning, Mathematics, MLOps, Java, GCP",Associate,3,Finance,2024-09-06,2024-10-18,2268,9.1,Future Systems -AI13984,Data Analyst,86228,AUD,116408,MI,CT,Australia,M,Switzerland,100,"Statistics, Spark, GCP, Git",PhD,2,Real Estate,2024-06-17,2024-07-02,1626,6.6,Neural Networks Co -AI13985,Data Engineer,118142,CAD,147678,MI,FT,Canada,L,Canada,100,"NLP, Python, Tableau",PhD,3,Retail,2024-02-16,2024-03-02,984,5.8,Smart Analytics -AI13986,Principal Data Scientist,149989,USD,149989,EX,CT,Israel,S,Israel,100,"AWS, PyTorch, Deep Learning, Mathematics",Bachelor,11,Energy,2024-09-14,2024-10-04,1455,6.8,TechCorp Inc -AI13987,Data Scientist,59094,USD,59094,EN,CT,South Korea,M,United States,0,"Kubernetes, Data Visualization, Git",Master,1,Retail,2024-07-09,2024-07-29,1869,8,Cognitive Computing -AI13988,Machine Learning Engineer,177285,USD,177285,SE,FL,Norway,L,Norway,0,"Scala, MLOps, Tableau, Data Visualization, R",Associate,8,Government,2024-03-30,2024-04-29,1226,8.2,Quantum Computing Inc -AI13989,Autonomous Systems Engineer,86720,USD,86720,EN,PT,Denmark,M,Denmark,0,"Computer Vision, Tableau, Scala",Master,1,Education,2024-04-01,2024-06-07,1124,6.8,Advanced Robotics -AI13990,Data Scientist,86353,USD,86353,EX,CT,China,L,China,0,"Computer Vision, Statistics, NLP, Tableau, Scala",Associate,17,Real Estate,2024-11-30,2025-01-08,1182,9.3,Cognitive Computing -AI13991,AI Specialist,43936,USD,43936,SE,PT,India,M,India,50,"Data Visualization, PyTorch, Docker, Hadoop, AWS",PhD,8,Real Estate,2025-03-07,2025-05-17,1226,6.7,Neural Networks Co -AI13992,Computer Vision Engineer,143556,USD,143556,EX,FT,Finland,M,Spain,100,"Data Visualization, Statistics, Python, Git",Master,16,Education,2025-03-05,2025-04-16,2169,8.9,Predictive Systems -AI13993,Robotics Engineer,78380,USD,78380,EX,PT,India,M,China,50,"Python, Java, PyTorch, Mathematics",PhD,18,Government,2024-12-24,2025-01-20,768,5.9,Predictive Systems -AI13994,AI Consultant,72730,EUR,61821,MI,FL,Austria,S,Austria,100,"GCP, SQL, Kubernetes, Data Visualization",Bachelor,2,Energy,2024-08-03,2024-09-03,519,7.1,Digital Transformation LLC -AI13995,Head of AI,290341,USD,290341,EX,CT,Sweden,L,Sweden,0,"Computer Vision, Python, MLOps",Associate,16,Retail,2024-06-15,2024-08-25,618,5.1,DataVision Ltd -AI13996,Data Engineer,217967,USD,217967,EX,CT,Ireland,S,Brazil,50,"PyTorch, AWS, TensorFlow",Master,17,Media,2024-09-18,2024-11-03,1350,8.7,Digital Transformation LLC -AI13997,Data Engineer,102309,USD,102309,EX,FL,India,L,India,100,"SQL, Python, Computer Vision, Mathematics",Bachelor,11,Technology,2024-05-17,2024-06-25,1370,8.2,Neural Networks Co -AI13998,Research Scientist,80525,EUR,68446,MI,FT,Netherlands,M,Indonesia,0,"Java, R, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-09,2180,7.3,Advanced Robotics -AI13999,Data Scientist,202160,USD,202160,SE,FT,United States,L,United States,100,"MLOps, Git, Tableau, Scala",Bachelor,6,Transportation,2025-04-12,2025-06-24,1769,7,Algorithmic Solutions -AI14000,Head of AI,220964,USD,220964,EX,FT,Sweden,S,Sweden,100,"PyTorch, Computer Vision, Hadoop, Python, Spark",PhD,19,Automotive,2024-11-14,2025-01-15,2217,8.3,Quantum Computing Inc -AI14001,AI Specialist,56149,USD,56149,EN,PT,Israel,L,Israel,100,"TensorFlow, NLP, Data Visualization, Scala",Master,0,Technology,2025-03-06,2025-04-20,2102,8.5,Algorithmic Solutions -AI14002,Principal Data Scientist,145157,CAD,181446,SE,FT,Canada,L,Canada,100,"Azure, Data Visualization, AWS, Kubernetes",PhD,9,Education,2025-01-16,2025-02-09,2214,5.6,Neural Networks Co -AI14003,Data Engineer,172667,USD,172667,SE,PT,Sweden,L,Mexico,0,"SQL, GCP, Java, Deep Learning",Bachelor,6,Education,2024-12-28,2025-01-17,1466,5.4,AI Innovations -AI14004,NLP Engineer,138247,AUD,186633,EX,FL,Australia,M,Chile,100,"SQL, Python, Computer Vision, NLP, Spark",Master,12,Consulting,2024-12-28,2025-02-25,1737,6,Machine Intelligence Group -AI14005,Robotics Engineer,129293,USD,129293,MI,PT,Norway,M,South Africa,0,"Mathematics, Linux, MLOps",Master,4,Media,2024-04-10,2024-05-06,1752,7,TechCorp Inc -AI14006,AI Specialist,106869,CAD,133586,SE,FT,Canada,M,New Zealand,100,"SQL, Python, Statistics, GCP, Kubernetes",Master,7,Media,2024-08-21,2024-10-15,1926,5.1,Machine Intelligence Group -AI14007,NLP Engineer,57671,EUR,49020,EN,FT,France,L,France,50,"Azure, Git, Hadoop",Associate,1,Healthcare,2025-04-02,2025-05-01,1741,6.8,DataVision Ltd -AI14008,AI Product Manager,279242,GBP,209432,EX,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Linux, Computer Vision",Master,12,Transportation,2024-10-21,2024-11-15,1138,6.9,Machine Intelligence Group -AI14009,Data Scientist,204632,JPY,22509520,EX,FT,Japan,L,Japan,100,"Scala, Spark, Deep Learning, Git, PyTorch",Associate,14,Retail,2025-02-27,2025-04-07,1462,9.9,AI Innovations -AI14010,Data Engineer,203509,EUR,172983,EX,FT,Germany,M,Germany,100,"Python, MLOps, Data Visualization, Scala, Tableau",Associate,11,Real Estate,2024-03-29,2024-05-25,1317,6.1,Machine Intelligence Group -AI14011,AI Research Scientist,76433,EUR,64968,EN,CT,Netherlands,S,Netherlands,50,"Python, Data Visualization, Hadoop, GCP",Associate,1,Technology,2025-04-23,2025-06-06,1324,7.1,TechCorp Inc -AI14012,Machine Learning Engineer,143395,CAD,179244,EX,FL,Canada,M,Singapore,0,"NLP, Data Visualization, Python",Associate,15,Energy,2025-01-28,2025-03-27,1767,7.8,AI Innovations -AI14013,Data Scientist,190317,USD,190317,EX,PT,United States,M,United States,0,"Tableau, Spark, R",PhD,13,Gaming,2024-10-23,2024-11-17,1196,6.9,Machine Intelligence Group -AI14014,Deep Learning Engineer,18052,USD,18052,EN,FL,India,M,Russia,50,"AWS, SQL, Computer Vision, NLP, Azure",Associate,0,Finance,2024-09-24,2024-11-05,1104,5,Machine Intelligence Group -AI14015,Data Analyst,157903,EUR,134218,SE,FL,Germany,L,Germany,50,"Hadoop, Linux, R",Associate,7,Energy,2024-02-29,2024-04-23,766,5.4,DataVision Ltd -AI14016,Deep Learning Engineer,208955,USD,208955,EX,FL,United States,L,United States,100,"Computer Vision, PyTorch, Git",Master,19,Consulting,2024-04-18,2024-06-22,2055,8.9,Autonomous Tech -AI14017,Research Scientist,34807,USD,34807,EN,CT,China,L,China,100,"Linux, R, Statistics, Kubernetes",Bachelor,1,Education,2025-02-23,2025-04-28,1827,7.1,Future Systems -AI14018,Research Scientist,81021,AUD,109378,MI,FT,Australia,S,Australia,100,"Linux, GCP, Mathematics, NLP",PhD,2,Energy,2024-12-18,2025-01-16,1620,9.9,Machine Intelligence Group -AI14019,Data Analyst,64631,EUR,54936,EN,CT,France,L,France,50,"Azure, Deep Learning, Scala, Computer Vision",Master,1,Healthcare,2024-07-28,2024-09-18,665,9.9,Smart Analytics -AI14020,AI Specialist,92162,USD,92162,EN,FT,Denmark,S,Denmark,0,"GCP, Data Visualization, Spark",PhD,0,Gaming,2024-06-16,2024-08-26,1011,9.5,Future Systems -AI14021,AI Product Manager,110327,USD,110327,MI,FT,Ireland,M,Ireland,100,"Tableau, Hadoop, Java, Spark, Deep Learning",Bachelor,2,Consulting,2024-09-18,2024-10-29,1272,7.4,Quantum Computing Inc -AI14022,Robotics Engineer,102765,USD,102765,MI,FL,Denmark,S,Denmark,0,"Linux, Git, Tableau",Bachelor,3,Technology,2025-02-10,2025-03-29,1076,8.5,DataVision Ltd -AI14023,Deep Learning Engineer,91759,USD,91759,EN,CT,United States,M,South Africa,100,"R, SQL, Hadoop",PhD,0,Automotive,2024-01-09,2024-03-01,2033,5,Digital Transformation LLC -AI14024,AI Product Manager,159836,USD,159836,EX,CT,Ireland,L,United States,50,"GCP, SQL, Hadoop",PhD,17,Consulting,2024-09-19,2024-11-09,2184,5.4,DataVision Ltd -AI14025,AI Software Engineer,120984,CHF,108886,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Kubernetes, AWS, MLOps, SQL",Associate,1,Real Estate,2024-12-20,2025-02-11,658,5.3,Predictive Systems -AI14026,Data Scientist,159881,USD,159881,SE,PT,Ireland,L,Ireland,0,"Scala, PyTorch, Azure, AWS, Statistics",Bachelor,5,Telecommunications,2025-04-07,2025-05-31,2464,6.7,Digital Transformation LLC -AI14027,NLP Engineer,89150,JPY,9806500,EN,FL,Japan,L,Japan,0,"Git, GCP, Mathematics, PyTorch, TensorFlow",Master,1,Gaming,2024-02-13,2024-04-24,691,5.7,Autonomous Tech -AI14028,AI Consultant,67892,EUR,57708,MI,CT,France,S,France,100,"Kubernetes, Docker, Java",Master,3,Finance,2025-03-14,2025-04-01,1181,5.6,Quantum Computing Inc -AI14029,ML Ops Engineer,92548,GBP,69411,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Mathematics, Computer Vision, R",Master,1,Transportation,2024-09-14,2024-11-16,1462,5.9,Neural Networks Co -AI14030,Head of AI,53496,USD,53496,EN,FT,South Korea,S,Israel,0,"Deep Learning, Python, Tableau",Master,1,Energy,2024-11-03,2024-11-21,1703,9,Cognitive Computing -AI14031,Computer Vision Engineer,70599,EUR,60009,MI,FL,Austria,S,Colombia,50,"Java, Scala, Azure",Associate,3,Gaming,2025-02-16,2025-04-22,661,6.9,Quantum Computing Inc -AI14032,ML Ops Engineer,61691,EUR,52437,MI,CT,Austria,S,Austria,100,"Kubernetes, Computer Vision, Java",Master,4,Finance,2024-06-22,2024-08-10,1223,9,TechCorp Inc -AI14033,Data Analyst,128526,USD,128526,SE,FL,Ireland,L,Ireland,50,"AWS, SQL, GCP, Java",Master,9,Gaming,2024-01-21,2024-02-16,2257,5.5,Smart Analytics -AI14034,Autonomous Systems Engineer,211888,JPY,23307680,EX,FT,Japan,M,Japan,50,"Linux, MLOps, Azure, Hadoop, Spark",Associate,14,Energy,2024-09-08,2024-10-15,2247,6.9,Predictive Systems -AI14035,Robotics Engineer,111691,CAD,139614,SE,FL,Canada,S,Canada,50,"Scala, Git, R, AWS",Bachelor,6,Telecommunications,2025-03-28,2025-05-12,1360,10,AI Innovations -AI14036,Data Scientist,38446,USD,38446,SE,PT,India,S,India,100,"Docker, Python, TensorFlow, GCP",Associate,9,Government,2024-10-08,2024-11-18,1097,5.3,TechCorp Inc -AI14037,NLP Engineer,90939,CAD,113674,MI,CT,Canada,L,Canada,50,"SQL, Data Visualization, MLOps, Git, Kubernetes",Master,4,Finance,2024-05-03,2024-06-16,592,9.7,Neural Networks Co -AI14038,AI Software Engineer,89119,CAD,111399,MI,FL,Canada,S,Canada,100,"R, Data Visualization, Statistics, Scala",Master,2,Real Estate,2024-03-15,2024-05-22,805,6.7,AI Innovations -AI14039,Principal Data Scientist,334067,USD,334067,EX,FT,Norway,L,Norway,50,"Python, Statistics, Git",Master,11,Media,2025-02-20,2025-03-12,929,9.1,Digital Transformation LLC -AI14040,Head of AI,168122,USD,168122,EX,FT,South Korea,S,South Korea,0,"Mathematics, Linux, Scala, Statistics, SQL",PhD,12,Manufacturing,2025-01-15,2025-03-21,2195,6.3,Neural Networks Co -AI14041,ML Ops Engineer,130674,CHF,117607,SE,PT,Switzerland,S,Switzerland,0,"Azure, Python, Tableau, GCP",Associate,9,Telecommunications,2025-01-05,2025-02-15,2192,5.3,TechCorp Inc -AI14042,Research Scientist,147848,EUR,125671,EX,CT,Austria,S,Austria,50,"Java, Azure, GCP",PhD,19,Automotive,2024-01-23,2024-02-11,1992,9.4,Neural Networks Co -AI14043,Data Engineer,206878,CHF,186190,EX,PT,Switzerland,M,United States,50,"Linux, TensorFlow, Python, Deep Learning",PhD,10,Telecommunications,2024-02-25,2024-03-27,2374,9.9,Neural Networks Co -AI14044,ML Ops Engineer,120770,USD,120770,MI,FT,Denmark,S,Denmark,0,"Statistics, Python, Computer Vision, PyTorch",Bachelor,4,Manufacturing,2025-02-20,2025-03-08,1180,7.4,Cloud AI Solutions -AI14045,ML Ops Engineer,209060,CAD,261325,EX,CT,Canada,S,Canada,50,"TensorFlow, Kubernetes, Scala",Associate,17,Technology,2024-12-02,2025-01-27,600,9.1,Predictive Systems -AI14046,Robotics Engineer,55846,USD,55846,EN,PT,Ireland,S,Ireland,0,"Deep Learning, Data Visualization, Tableau, Mathematics",Associate,1,Consulting,2024-12-05,2025-01-12,1994,6.8,TechCorp Inc -AI14047,Autonomous Systems Engineer,96258,USD,96258,MI,FL,Ireland,M,Ireland,50,"Scala, Data Visualization, Azure, NLP, Git",Associate,3,Manufacturing,2025-01-12,2025-01-28,1073,8,Machine Intelligence Group -AI14048,Principal Data Scientist,76228,AUD,102908,EN,CT,Australia,L,Australia,100,"SQL, Git, PyTorch, Tableau, Kubernetes",Bachelor,1,Government,2024-05-08,2024-06-03,1156,7.1,Autonomous Tech -AI14049,AI Research Scientist,202209,USD,202209,SE,PT,Norway,L,Estonia,100,"TensorFlow, Computer Vision, SQL, Java, Linux",Bachelor,6,Gaming,2025-04-17,2025-06-21,1599,6.4,TechCorp Inc -AI14050,Autonomous Systems Engineer,106972,CHF,96275,MI,PT,Switzerland,S,Egypt,100,"MLOps, Linux, Tableau, PyTorch, Hadoop",PhD,4,Finance,2024-01-09,2024-03-09,636,7.1,Advanced Robotics -AI14051,Computer Vision Engineer,79068,USD,79068,EX,FT,China,S,China,50,"Tableau, Deep Learning, PyTorch",PhD,16,Energy,2024-01-06,2024-02-04,1101,9.8,Quantum Computing Inc -AI14052,Autonomous Systems Engineer,101691,CHF,91522,MI,PT,Switzerland,S,Switzerland,50,"Java, Scala, Git, Statistics",Bachelor,2,Transportation,2024-09-01,2024-10-13,1488,5.8,Autonomous Tech -AI14053,AI Software Engineer,113366,SGD,147376,MI,PT,Singapore,L,Singapore,100,"Java, NLP, Spark, TensorFlow, Azure",Master,4,Manufacturing,2024-11-11,2024-12-04,772,8.5,Quantum Computing Inc -AI14054,ML Ops Engineer,309967,GBP,232475,EX,FL,United Kingdom,L,United Kingdom,50,"SQL, Java, Data Visualization, Hadoop, Computer Vision",Bachelor,18,Technology,2025-01-08,2025-02-20,830,6.8,Quantum Computing Inc -AI14055,AI Research Scientist,137461,EUR,116842,SE,CT,Netherlands,S,Luxembourg,50,"GCP, Python, TensorFlow, R",Associate,9,Healthcare,2025-01-06,2025-03-09,1144,8.2,AI Innovations -AI14056,AI Software Engineer,87443,USD,87443,EN,CT,United States,L,United States,0,"Computer Vision, Hadoop, Python, Kubernetes, Docker",Associate,0,Finance,2024-11-12,2024-12-06,2171,8.1,Digital Transformation LLC -AI14057,ML Ops Engineer,116059,SGD,150877,MI,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Azure, Computer Vision, Git",PhD,4,Retail,2024-07-05,2024-08-28,810,9.1,Advanced Robotics -AI14058,Principal Data Scientist,82475,USD,82475,EN,CT,Denmark,S,Netherlands,0,"GCP, SQL, Spark, Java, Mathematics",Associate,1,Retail,2025-02-19,2025-03-24,1099,9.4,Neural Networks Co -AI14059,Machine Learning Researcher,134959,USD,134959,SE,PT,Ireland,M,Ireland,50,"Git, Azure, MLOps, Linux",Bachelor,8,Finance,2024-02-26,2024-04-03,1639,9.7,AI Innovations -AI14060,NLP Engineer,295543,USD,295543,EX,FL,United States,L,Portugal,0,"SQL, Scala, Mathematics, Azure, Hadoop",Associate,14,Manufacturing,2024-03-10,2024-04-19,739,8.7,Smart Analytics -AI14061,Head of AI,69846,USD,69846,EN,FL,United States,M,Estonia,100,"Java, PyTorch, Scala, SQL",Associate,1,Finance,2024-11-09,2024-12-29,2048,8.7,DataVision Ltd -AI14062,Data Analyst,129073,JPY,14198030,SE,CT,Japan,L,Japan,100,"Linux, Data Visualization, Kubernetes, NLP, R",Bachelor,6,Transportation,2024-03-12,2024-04-27,1605,8.8,Machine Intelligence Group -AI14063,Principal Data Scientist,60030,EUR,51026,EN,CT,France,L,France,0,"Python, Java, Azure",PhD,1,Healthcare,2024-02-09,2024-04-13,810,5.2,Smart Analytics -AI14064,Machine Learning Engineer,90890,CAD,113613,MI,FL,Canada,L,Romania,50,"Statistics, Kubernetes, Python, TensorFlow",Master,2,Real Estate,2024-04-19,2024-06-12,1477,5.8,Neural Networks Co -AI14065,AI Architect,166381,USD,166381,SE,PT,Ireland,L,Germany,100,"Java, Data Visualization, AWS, Docker, Computer Vision",Bachelor,7,Media,2024-08-24,2024-09-19,2450,7.8,Smart Analytics -AI14066,AI Product Manager,281704,USD,281704,EX,FL,Ireland,L,New Zealand,100,"Computer Vision, Azure, Spark, AWS",Master,17,Energy,2024-09-24,2024-11-10,2033,9.6,DeepTech Ventures -AI14067,Computer Vision Engineer,132917,USD,132917,SE,FT,Ireland,S,Ireland,50,"SQL, Git, Python",Associate,7,Real Estate,2024-10-05,2024-11-07,980,5.5,AI Innovations -AI14068,AI Product Manager,29350,USD,29350,MI,FL,India,S,India,100,"Kubernetes, PyTorch, Hadoop, MLOps, Spark",Master,3,Education,2024-07-19,2024-09-18,1755,8.1,Quantum Computing Inc -AI14069,Data Analyst,72631,USD,72631,EN,FL,Norway,S,Norway,0,"Mathematics, Statistics, Kubernetes, Azure",PhD,0,Energy,2025-03-23,2025-04-09,1392,6.1,DataVision Ltd -AI14070,AI Research Scientist,57268,USD,57268,SE,FT,China,M,China,50,"TensorFlow, SQL, Data Visualization, GCP, Azure",Master,5,Retail,2024-02-18,2024-04-01,1414,7.5,Autonomous Tech -AI14071,AI Research Scientist,83126,CHF,74813,EN,FL,Switzerland,L,Sweden,0,"Python, TensorFlow, Scala, Kubernetes, Computer Vision",PhD,1,Transportation,2024-09-19,2024-10-28,1399,7.1,Advanced Robotics -AI14072,AI Product Manager,114645,USD,114645,MI,FL,Norway,M,Norway,0,"Git, SQL, MLOps",Master,4,Transportation,2024-11-23,2024-12-10,2416,6,DeepTech Ventures -AI14073,ML Ops Engineer,63688,USD,63688,EN,FT,Israel,S,Israel,50,"Data Visualization, Git, Computer Vision",PhD,1,Real Estate,2024-03-03,2024-04-06,1831,8.3,Advanced Robotics -AI14074,Research Scientist,122807,EUR,104386,SE,FT,Germany,S,Switzerland,0,"GCP, Docker, Statistics",Master,8,Healthcare,2025-02-26,2025-04-20,1672,6.2,Quantum Computing Inc -AI14075,Deep Learning Engineer,102173,USD,102173,SE,PT,Ireland,S,Ireland,100,"Azure, Linux, Git, Java, TensorFlow",Associate,7,Automotive,2024-07-29,2024-09-13,795,8.7,Quantum Computing Inc -AI14076,Computer Vision Engineer,139906,GBP,104930,SE,FT,United Kingdom,S,United Kingdom,0,"Git, Data Visualization, AWS, Computer Vision",PhD,8,Transportation,2024-12-23,2025-02-17,1359,8.9,DeepTech Ventures -AI14077,AI Architect,161399,JPY,17753890,EX,PT,Japan,S,Japan,100,"PyTorch, R, Kubernetes",Associate,15,Transportation,2024-12-26,2025-02-07,945,8.9,Advanced Robotics -AI14078,Principal Data Scientist,104420,EUR,88757,SE,PT,Austria,S,Netherlands,50,"Data Visualization, Statistics, Tableau",PhD,9,Healthcare,2025-04-11,2025-04-30,624,7.7,Quantum Computing Inc -AI14079,AI Software Engineer,88018,EUR,74815,MI,FT,Austria,L,Austria,100,"Spark, GCP, Scala",Bachelor,4,Gaming,2024-08-17,2024-09-12,1130,5.3,Smart Analytics -AI14080,AI Consultant,65855,USD,65855,SE,PT,China,M,China,0,"Java, Linux, MLOps",Associate,6,Automotive,2024-10-08,2024-11-26,2119,8.8,Cognitive Computing -AI14081,AI Software Engineer,153926,JPY,16931860,SE,PT,Japan,L,Japan,0,"Java, GCP, Mathematics, Docker, Python",Bachelor,7,Gaming,2024-02-27,2024-03-31,1128,8.4,Cloud AI Solutions -AI14082,Autonomous Systems Engineer,133543,SGD,173606,MI,FT,Singapore,L,Singapore,0,"NLP, GCP, Azure, Scala, Statistics",Bachelor,3,Real Estate,2024-10-18,2024-12-25,653,7.3,Machine Intelligence Group -AI14083,Machine Learning Researcher,132804,USD,132804,SE,PT,United States,M,United States,50,"Linux, Python, SQL, NLP, Computer Vision",Master,8,Transportation,2024-11-19,2024-12-14,965,8.5,Cloud AI Solutions -AI14084,Head of AI,185999,SGD,241799,EX,FT,Singapore,M,Singapore,0,"Git, Python, Statistics",Associate,11,Consulting,2024-03-07,2024-05-07,1393,8.7,Quantum Computing Inc -AI14085,Data Scientist,160037,USD,160037,SE,FT,Denmark,M,Denmark,100,"Java, Spark, Computer Vision",Bachelor,5,Real Estate,2024-06-11,2024-07-20,2246,5.4,Algorithmic Solutions -AI14086,Data Scientist,71318,SGD,92713,MI,FT,Singapore,S,Singapore,50,"Spark, Linux, NLP, AWS",Master,2,Energy,2024-10-28,2024-11-21,1534,9.5,Cloud AI Solutions -AI14087,Data Analyst,210874,GBP,158156,EX,CT,United Kingdom,L,United Kingdom,100,"SQL, PyTorch, Azure, Scala, Java",Bachelor,14,Manufacturing,2024-05-18,2024-07-18,551,9.9,Quantum Computing Inc -AI14088,Head of AI,171409,EUR,145698,SE,FT,Netherlands,L,Netherlands,0,"Tableau, Git, Kubernetes, AWS, GCP",Bachelor,7,Gaming,2025-01-28,2025-03-20,2499,7,Advanced Robotics -AI14089,Deep Learning Engineer,41300,USD,41300,EN,FL,South Korea,S,Chile,100,"Scala, Hadoop, Data Visualization, Spark",Associate,0,Automotive,2024-02-10,2024-03-28,1754,8.5,DeepTech Ventures -AI14090,NLP Engineer,61734,USD,61734,SE,FT,China,M,China,50,"Kubernetes, Scala, AWS",Associate,6,Automotive,2024-12-19,2025-01-07,2073,7.4,Smart Analytics -AI14091,Machine Learning Engineer,171718,CAD,214648,EX,FL,Canada,L,Romania,0,"GCP, PyTorch, Statistics, Spark",PhD,19,Media,2024-03-27,2024-04-11,1548,6.2,Advanced Robotics -AI14092,Research Scientist,72603,JPY,7986330,EN,FT,Japan,S,Japan,100,"NLP, Kubernetes, Data Visualization",Master,1,Telecommunications,2024-02-27,2024-04-23,1185,8.5,TechCorp Inc -AI14093,AI Research Scientist,147559,SGD,191827,SE,FT,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization, MLOps, NLP",PhD,7,Telecommunications,2025-03-05,2025-04-17,2433,6.6,Advanced Robotics -AI14094,Principal Data Scientist,117163,JPY,12887930,MI,PT,Japan,L,Spain,50,"SQL, Python, Data Visualization",Bachelor,4,Gaming,2024-01-27,2024-02-15,2052,7.4,Quantum Computing Inc -AI14095,Research Scientist,112263,EUR,95424,MI,FL,Netherlands,M,Netherlands,0,"Hadoop, R, TensorFlow",PhD,2,Energy,2024-12-21,2025-02-02,2463,9.3,Cloud AI Solutions -AI14096,AI Software Engineer,29429,USD,29429,EN,FL,China,M,China,0,"GCP, R, Statistics, Spark",Bachelor,1,Gaming,2024-12-16,2025-01-21,1928,8.6,Cloud AI Solutions -AI14097,Head of AI,125096,USD,125096,MI,FL,United States,L,United States,50,"Tableau, Scala, Kubernetes",PhD,4,Healthcare,2025-04-16,2025-06-12,896,6.1,Digital Transformation LLC -AI14098,Autonomous Systems Engineer,290902,JPY,31999220,EX,FT,Japan,L,Japan,50,"Hadoop, Java, R, Kubernetes",Bachelor,12,Education,2024-06-04,2024-07-30,2175,5.4,Neural Networks Co -AI14099,Deep Learning Engineer,139674,USD,139674,SE,FL,Sweden,M,Egypt,100,"TensorFlow, PyTorch, Tableau, Statistics, Mathematics",PhD,8,Transportation,2024-05-19,2024-07-31,978,5.3,Digital Transformation LLC -AI14100,Data Engineer,112288,USD,112288,SE,FT,Ireland,S,Singapore,50,"Linux, Deep Learning, Kubernetes",PhD,7,Manufacturing,2024-12-20,2025-01-27,544,8.8,Machine Intelligence Group -AI14101,AI Specialist,55248,USD,55248,EX,CT,India,M,Mexico,50,"Tableau, Python, TensorFlow, AWS",PhD,16,Technology,2025-02-12,2025-03-02,1131,7,Smart Analytics -AI14102,Data Engineer,222488,USD,222488,SE,PT,Norway,L,Norway,0,"Scala, Computer Vision, Mathematics, R, NLP",Master,5,Technology,2025-02-12,2025-04-21,854,5.3,Quantum Computing Inc -AI14103,AI Software Engineer,186626,USD,186626,SE,PT,Norway,L,Denmark,100,"MLOps, SQL, Kubernetes",Associate,9,Education,2024-03-30,2024-05-07,1277,8.1,Quantum Computing Inc -AI14104,Deep Learning Engineer,262649,JPY,28891390,EX,FT,Japan,L,Japan,0,"Python, Kubernetes, Docker, TensorFlow",Master,17,Gaming,2024-10-01,2024-11-01,773,7.2,Machine Intelligence Group -AI14105,ML Ops Engineer,103455,USD,103455,MI,CT,United States,S,United States,50,"Azure, GCP, Statistics, MLOps, Python",Bachelor,3,Education,2024-07-06,2024-09-16,2487,6.3,DataVision Ltd -AI14106,Data Scientist,122416,USD,122416,MI,FL,Norway,M,Norway,0,"Kubernetes, Java, PyTorch, SQL, Spark",Bachelor,3,Education,2024-12-12,2025-01-02,1535,9.5,Autonomous Tech -AI14107,AI Product Manager,126398,SGD,164317,SE,FT,Singapore,L,Belgium,50,"GCP, Statistics, Hadoop, TensorFlow",Associate,9,Real Estate,2024-06-13,2024-07-11,2140,6.6,Machine Intelligence Group -AI14108,Deep Learning Engineer,104577,USD,104577,EN,PT,Denmark,L,Denmark,0,"SQL, Docker, Azure, R",Bachelor,0,Transportation,2025-02-06,2025-02-24,2202,8.4,Future Systems -AI14109,Machine Learning Researcher,222225,GBP,166669,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, PyTorch, Scala, Kubernetes",PhD,12,Automotive,2024-11-03,2025-01-11,2381,8.1,DataVision Ltd -AI14110,Head of AI,153799,EUR,130729,EX,CT,Netherlands,S,Netherlands,100,"AWS, Spark, Kubernetes, SQL, Linux",Associate,12,Consulting,2025-03-24,2025-05-08,508,7.2,Predictive Systems -AI14111,Machine Learning Engineer,77712,GBP,58284,EN,CT,United Kingdom,L,Hungary,0,"Python, Kubernetes, Computer Vision, Deep Learning, Tableau",Bachelor,1,Automotive,2024-01-31,2024-04-08,938,7.4,Cognitive Computing -AI14112,Data Analyst,68332,USD,68332,EN,CT,Finland,M,Indonesia,0,"Docker, PyTorch, Data Visualization, Linux, Git",Associate,1,Government,2024-03-11,2024-03-25,1373,9.4,Digital Transformation LLC -AI14113,AI Consultant,81904,USD,81904,SE,FT,China,L,China,50,"GCP, Git, Mathematics, Data Visualization",Master,7,Technology,2024-11-08,2024-11-26,832,8.5,Machine Intelligence Group -AI14114,ML Ops Engineer,67175,GBP,50381,EN,PT,United Kingdom,M,United Kingdom,50,"Python, Kubernetes, SQL",Associate,1,Gaming,2024-10-29,2024-12-24,2341,6.8,Machine Intelligence Group -AI14115,Computer Vision Engineer,71427,USD,71427,EN,PT,Finland,L,South Africa,0,"Azure, PyTorch, Tableau",PhD,0,Healthcare,2024-01-21,2024-03-15,1801,7.8,Cloud AI Solutions -AI14116,Principal Data Scientist,163454,AUD,220663,EX,PT,Australia,S,Thailand,50,"Python, GCP, NLP",PhD,10,Automotive,2024-03-24,2024-05-30,2143,9.6,Algorithmic Solutions -AI14117,Robotics Engineer,70727,EUR,60118,MI,FL,Germany,S,Germany,0,"Linux, Computer Vision, Tableau, Azure, Python",PhD,4,Manufacturing,2025-04-21,2025-06-28,1474,8.3,Cognitive Computing -AI14118,Machine Learning Researcher,136745,SGD,177769,EX,PT,Singapore,S,Singapore,0,"Scala, Hadoop, Python, TensorFlow",PhD,14,Telecommunications,2024-01-26,2024-03-28,1093,5.3,DeepTech Ventures -AI14119,Autonomous Systems Engineer,122312,USD,122312,SE,PT,United States,M,Canada,50,"SQL, Git, AWS, GCP",Master,8,Manufacturing,2024-02-11,2024-04-21,2457,9.7,Quantum Computing Inc -AI14120,ML Ops Engineer,88018,SGD,114423,EN,CT,Singapore,L,Singapore,50,"Mathematics, Deep Learning, Java, Python, AWS",PhD,1,Education,2024-08-14,2024-10-25,2109,8.2,Predictive Systems -AI14121,AI Architect,107618,EUR,91475,SE,FT,France,S,France,0,"SQL, PyTorch, Tableau, Hadoop, Azure",PhD,8,Healthcare,2024-08-30,2024-10-27,2427,5.6,Advanced Robotics -AI14122,NLP Engineer,82542,GBP,61907,EN,PT,United Kingdom,L,United Kingdom,50,"Linux, Java, Scala, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-02,954,5.8,Future Systems -AI14123,NLP Engineer,37476,USD,37476,EN,PT,China,L,China,50,"Java, PyTorch, TensorFlow, Deep Learning",Associate,1,Consulting,2024-08-13,2024-09-10,2224,9.9,DeepTech Ventures -AI14124,Principal Data Scientist,24095,USD,24095,EN,PT,India,M,India,100,"Kubernetes, PyTorch, TensorFlow, Mathematics",Master,1,Healthcare,2024-05-30,2024-07-16,2200,6.9,Cognitive Computing -AI14125,Research Scientist,295505,GBP,221629,EX,FL,United Kingdom,L,Italy,50,"Python, Deep Learning, Java, Azure, GCP",Bachelor,19,Automotive,2024-08-27,2024-09-17,1366,7,Autonomous Tech -AI14126,Deep Learning Engineer,85346,JPY,9388060,EN,PT,Japan,L,Japan,100,"Scala, Java, Python, MLOps, TensorFlow",Associate,1,Manufacturing,2024-09-14,2024-11-16,1248,8.7,DeepTech Ventures -AI14127,Principal Data Scientist,142448,USD,142448,SE,PT,Finland,L,Finland,50,"Kubernetes, SQL, AWS, Git",Bachelor,7,Consulting,2024-08-21,2024-09-18,559,7.9,Predictive Systems -AI14128,ML Ops Engineer,60149,USD,60149,EN,CT,Sweden,L,Sweden,100,"Azure, SQL, TensorFlow",Associate,1,Government,2024-08-19,2024-10-11,2102,6,Future Systems -AI14129,Principal Data Scientist,92230,USD,92230,MI,FL,Israel,M,Israel,100,"Azure, Python, Java, Computer Vision",PhD,3,Gaming,2024-11-15,2024-12-01,1355,5.7,Smart Analytics -AI14130,Data Engineer,93635,EUR,79590,SE,CT,Austria,S,Austria,100,"Scala, GCP, Hadoop, Statistics",Associate,9,Consulting,2024-11-01,2024-11-26,568,7.3,Advanced Robotics -AI14131,NLP Engineer,109810,GBP,82358,SE,FT,United Kingdom,M,United Kingdom,50,"Mathematics, AWS, NLP",Master,9,Transportation,2024-09-29,2024-10-15,1683,9.8,Algorithmic Solutions -AI14132,Data Scientist,268003,EUR,227803,EX,CT,Austria,L,Austria,0,"R, Hadoop, Scala",PhD,14,Media,2024-04-12,2024-06-15,1657,6.2,Quantum Computing Inc -AI14133,AI Consultant,241976,EUR,205680,EX,FT,France,L,France,100,"Kubernetes, SQL, NLP, Java, Hadoop",Master,11,Gaming,2025-02-01,2025-03-26,2290,6.1,Predictive Systems -AI14134,Data Scientist,60314,GBP,45236,EN,PT,United Kingdom,M,Ireland,50,"Kubernetes, Git, Computer Vision, Hadoop",Master,0,Telecommunications,2024-10-28,2024-12-16,2263,8.5,Cloud AI Solutions -AI14135,Autonomous Systems Engineer,34598,USD,34598,MI,FT,China,M,Russia,100,"Linux, Mathematics, Java",Bachelor,2,Consulting,2025-03-08,2025-04-17,1270,6.7,Quantum Computing Inc -AI14136,Data Analyst,174612,USD,174612,EX,CT,Israel,M,Israel,100,"R, Git, Scala, Python, Mathematics",Associate,17,Healthcare,2024-04-20,2024-06-14,1197,9.4,Neural Networks Co -AI14137,AI Research Scientist,119374,USD,119374,SE,CT,Denmark,S,India,50,"Java, R, Data Visualization, Azure",Master,9,Transportation,2024-09-25,2024-10-15,1604,6.3,Smart Analytics -AI14138,Research Scientist,121158,GBP,90869,SE,PT,United Kingdom,M,Kenya,0,"PyTorch, TensorFlow, Computer Vision, Azure, Git",PhD,9,Manufacturing,2025-03-19,2025-05-25,1718,8.2,AI Innovations -AI14139,Robotics Engineer,126193,USD,126193,SE,FL,Ireland,M,Kenya,50,"TensorFlow, Linux, Java",Bachelor,5,Consulting,2024-10-05,2024-11-22,530,9.7,Predictive Systems -AI14140,ML Ops Engineer,41111,USD,41111,MI,FT,China,M,China,100,"SQL, Java, Git, Kubernetes, PyTorch",PhD,2,Consulting,2024-01-17,2024-03-01,2487,9.7,DataVision Ltd -AI14141,Autonomous Systems Engineer,22562,USD,22562,EN,CT,India,S,India,0,"Tableau, TensorFlow, Kubernetes",Bachelor,0,Retail,2024-12-16,2025-01-11,1698,7.5,TechCorp Inc -AI14142,Data Scientist,219263,USD,219263,EX,FT,Sweden,S,Sweden,50,"Azure, Mathematics, Data Visualization, Git",Master,14,Manufacturing,2024-11-06,2024-12-18,1340,5.1,TechCorp Inc -AI14143,Data Analyst,96400,SGD,125320,MI,CT,Singapore,S,Singapore,0,"Tableau, Scala, Python, TensorFlow",Bachelor,4,Telecommunications,2024-12-06,2024-12-29,927,6,Autonomous Tech -AI14144,Autonomous Systems Engineer,128818,USD,128818,SE,PT,Ireland,M,Norway,0,"GCP, Data Visualization, Computer Vision",Master,7,Telecommunications,2024-02-07,2024-03-05,1702,7.8,Neural Networks Co -AI14145,NLP Engineer,216334,USD,216334,EX,PT,Israel,M,Israel,50,"PyTorch, SQL, MLOps, TensorFlow, AWS",Bachelor,12,Real Estate,2024-02-04,2024-02-19,1082,6.2,Quantum Computing Inc -AI14146,Machine Learning Researcher,94530,USD,94530,MI,FT,United States,S,United States,100,"Git, Docker, Data Visualization",Bachelor,2,Manufacturing,2025-04-23,2025-06-24,2094,6.1,AI Innovations -AI14147,Head of AI,89370,EUR,75965,MI,FL,Germany,M,Germany,0,"TensorFlow, Java, Mathematics",PhD,3,Retail,2024-11-14,2025-01-26,650,8.2,Cloud AI Solutions -AI14148,Data Engineer,127066,AUD,171539,SE,FL,Australia,M,Kenya,50,"Python, AWS, Scala, TensorFlow, Git",PhD,6,Transportation,2025-01-12,2025-03-13,1023,7.8,Cognitive Computing -AI14149,Principal Data Scientist,110035,EUR,93530,MI,FT,Netherlands,L,Netherlands,100,"SQL, Python, Scala",Associate,4,Automotive,2024-09-15,2024-11-14,1887,7.8,TechCorp Inc -AI14150,Machine Learning Researcher,139926,USD,139926,EX,FT,South Korea,M,South Korea,100,"PyTorch, Git, TensorFlow, R, Computer Vision",Master,12,Education,2024-01-04,2024-02-04,1739,6.9,Smart Analytics -AI14151,Machine Learning Engineer,77667,USD,77667,MI,FL,Finland,S,Finland,0,"Statistics, GCP, NLP",Associate,4,Gaming,2024-08-16,2024-10-20,1023,8.6,Algorithmic Solutions -AI14152,Deep Learning Engineer,178132,USD,178132,EX,FT,Finland,M,United States,50,"Linux, Data Visualization, Kubernetes, TensorFlow, Python",Associate,16,Finance,2024-01-04,2024-01-27,505,5.8,Autonomous Tech -AI14153,AI Research Scientist,86792,EUR,73773,MI,PT,Austria,S,Austria,0,"Data Visualization, PyTorch, Spark, Kubernetes",Associate,3,Telecommunications,2025-02-25,2025-04-13,1744,7.6,Advanced Robotics -AI14154,Autonomous Systems Engineer,316782,CHF,285104,EX,FT,Switzerland,L,Argentina,50,"MLOps, Linux, Java",Associate,16,Real Estate,2024-06-11,2024-08-12,579,5.9,Predictive Systems -AI14155,Machine Learning Engineer,96906,USD,96906,MI,FT,Ireland,L,Ireland,50,"Linux, GCP, Kubernetes, AWS",Master,4,Real Estate,2024-09-21,2024-11-23,2050,7.7,Predictive Systems -AI14156,Computer Vision Engineer,69233,SGD,90003,EN,PT,Singapore,M,Singapore,50,"Linux, Docker, Tableau",Master,0,Gaming,2024-02-26,2024-04-03,1093,6.5,Future Systems -AI14157,Data Engineer,108244,EUR,92007,SE,FT,Netherlands,S,Netherlands,50,"R, NLP, Azure",Bachelor,8,Telecommunications,2024-03-02,2024-03-29,1838,7.9,Digital Transformation LLC -AI14158,Deep Learning Engineer,93348,EUR,79346,MI,FT,Austria,L,Austria,100,"Linux, Java, Spark, Python",Bachelor,2,Finance,2024-03-20,2024-04-12,1098,8.3,Autonomous Tech -AI14159,AI Product Manager,79789,USD,79789,EN,CT,United States,M,India,0,"Spark, Linux, Tableau, Computer Vision",Associate,1,Healthcare,2024-07-17,2024-09-15,618,8.8,Cloud AI Solutions -AI14160,Machine Learning Engineer,69277,JPY,7620470,EN,PT,Japan,L,Hungary,100,"Kubernetes, Scala, Spark",Master,1,Automotive,2024-04-20,2024-06-03,1022,7,Predictive Systems -AI14161,AI Research Scientist,182548,USD,182548,EX,PT,Norway,S,Vietnam,0,"Python, GCP, MLOps, Scala, Hadoop",Master,17,Telecommunications,2024-08-07,2024-09-01,1375,5.5,Autonomous Tech -AI14162,Head of AI,80971,EUR,68825,MI,CT,Netherlands,S,Norway,100,"GCP, Mathematics, Azure, Linux, NLP",Associate,2,Automotive,2025-03-11,2025-04-24,554,9.9,Quantum Computing Inc -AI14163,Deep Learning Engineer,84774,USD,84774,EN,FT,Norway,S,Spain,0,"MLOps, Python, SQL, Statistics, Azure",PhD,1,Real Estate,2024-07-25,2024-09-06,1881,5.2,DataVision Ltd -AI14164,ML Ops Engineer,88260,EUR,75021,MI,PT,Austria,M,Austria,100,"Docker, Mathematics, Scala, Statistics, Linux",Master,3,Consulting,2024-06-15,2024-08-14,2124,8.7,Future Systems -AI14165,Research Scientist,105933,USD,105933,EN,FL,Norway,L,Norway,100,"Git, Mathematics, Data Visualization, AWS",PhD,0,Technology,2025-03-14,2025-05-15,2088,6.2,Algorithmic Solutions -AI14166,AI Product Manager,252207,USD,252207,EX,FT,Norway,M,Norway,0,"Kubernetes, Azure, MLOps, Computer Vision, NLP",Master,15,Automotive,2025-02-08,2025-02-22,1166,8.9,Algorithmic Solutions -AI14167,AI Consultant,24594,USD,24594,EN,PT,India,L,India,0,"Python, AWS, SQL",Master,0,Transportation,2024-05-11,2024-07-01,1973,8.1,AI Innovations -AI14168,Head of AI,133353,SGD,173359,MI,FT,Singapore,L,Singapore,50,"Mathematics, Computer Vision, NLP, Tableau, Python",Master,2,Media,2024-06-25,2024-07-29,1940,8.6,Machine Intelligence Group -AI14169,ML Ops Engineer,116932,USD,116932,SE,FT,Israel,M,Israel,100,"Tableau, TensorFlow, Computer Vision, Spark, Statistics",Bachelor,6,Gaming,2025-02-03,2025-03-05,898,6.2,Algorithmic Solutions -AI14170,AI Research Scientist,169884,USD,169884,EX,FL,South Korea,L,South Korea,0,"Kubernetes, R, Python",PhD,16,Technology,2024-07-12,2024-07-30,1070,7.1,Machine Intelligence Group -AI14171,AI Specialist,171722,JPY,18889420,EX,PT,Japan,M,Estonia,50,"Kubernetes, Git, Computer Vision, Deep Learning, Spark",Associate,12,Education,2024-02-26,2024-04-11,2486,9.9,Cloud AI Solutions -AI14172,AI Consultant,303831,USD,303831,EX,FL,Norway,M,Norway,0,"AWS, MLOps, R",Bachelor,18,Automotive,2025-03-30,2025-06-04,1522,8.3,Cognitive Computing -AI14173,NLP Engineer,28602,USD,28602,EN,FL,China,S,China,100,"Python, Spark, Docker",Associate,1,Gaming,2024-08-01,2024-09-28,1209,5.2,Autonomous Tech -AI14174,AI Specialist,267508,EUR,227382,EX,FL,Netherlands,M,Netherlands,100,"Kubernetes, Scala, Statistics, Azure, Tableau",Master,16,Retail,2025-03-05,2025-03-23,1209,9.6,Future Systems -AI14175,ML Ops Engineer,115925,EUR,98536,SE,FL,Austria,L,Russia,100,"Python, TensorFlow, Mathematics, PyTorch, Spark",Bachelor,8,Consulting,2024-02-12,2024-03-26,1614,9.3,Future Systems -AI14176,Data Analyst,80656,USD,80656,MI,PT,Finland,S,Kenya,100,"Python, Deep Learning, Azure, SQL, Git",PhD,2,Real Estate,2024-02-22,2024-04-10,1277,8.1,Future Systems -AI14177,Machine Learning Engineer,27562,USD,27562,EN,FL,India,M,India,0,"TensorFlow, Deep Learning, Tableau, Kubernetes",Master,1,Manufacturing,2024-07-29,2024-08-22,1304,6.8,Advanced Robotics -AI14178,Principal Data Scientist,192999,EUR,164049,EX,PT,Austria,S,Austria,50,"MLOps, NLP, Linux, TensorFlow",PhD,19,Gaming,2024-12-18,2025-02-07,701,8.5,Advanced Robotics -AI14179,AI Consultant,254016,JPY,27941760,EX,FT,Japan,M,Japan,0,"Python, Kubernetes, Mathematics, Deep Learning",Bachelor,17,Energy,2024-03-14,2024-05-22,1852,9.1,Future Systems -AI14180,Data Analyst,63794,EUR,54225,EN,FT,Austria,S,Austria,50,"PyTorch, R, NLP, Python",Master,1,Healthcare,2024-08-25,2024-10-24,1738,8.1,Autonomous Tech -AI14181,Machine Learning Engineer,82068,GBP,61551,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, PyTorch, Spark, Deep Learning, Computer Vision",PhD,1,Consulting,2024-09-09,2024-10-21,1023,6.7,Autonomous Tech -AI14182,AI Product Manager,68103,CAD,85129,EN,CT,Canada,S,Canada,50,"Data Visualization, Docker, Python, Computer Vision, Hadoop",Bachelor,1,Automotive,2024-01-07,2024-02-29,2000,6.3,DataVision Ltd -AI14183,NLP Engineer,108322,USD,108322,SE,FT,Israel,S,Israel,100,"Python, TensorFlow, MLOps",Associate,5,Government,2024-02-23,2024-04-06,1554,8.9,Predictive Systems -AI14184,Principal Data Scientist,80835,USD,80835,EN,FT,Norway,M,Norway,0,"Statistics, Scala, Linux",Bachelor,0,Automotive,2024-07-20,2024-08-17,1986,5.4,AI Innovations -AI14185,Head of AI,114660,USD,114660,SE,CT,Ireland,S,Ireland,50,"R, Git, Deep Learning, SQL",Associate,8,Automotive,2025-02-08,2025-03-25,2061,9.5,TechCorp Inc -AI14186,AI Consultant,106582,GBP,79937,MI,CT,United Kingdom,L,Ukraine,100,"Hadoop, Scala, Computer Vision, Python",Master,3,Consulting,2024-09-12,2024-11-02,2032,8.1,Digital Transformation LLC -AI14187,Machine Learning Engineer,96014,EUR,81612,MI,CT,Germany,S,Germany,50,"Scala, Java, TensorFlow, Statistics, Deep Learning",PhD,4,Media,2024-09-16,2024-11-02,1645,8.4,Predictive Systems -AI14188,Robotics Engineer,91689,USD,91689,MI,CT,Ireland,M,Ireland,100,"PyTorch, TensorFlow, Mathematics, Statistics",Master,3,Technology,2024-02-18,2024-04-18,996,7,Future Systems -AI14189,Machine Learning Researcher,64501,SGD,83851,EN,FT,Singapore,S,Singapore,0,"Linux, Deep Learning, PyTorch, Mathematics, NLP",PhD,1,Real Estate,2024-05-01,2024-06-12,1800,9.5,DataVision Ltd -AI14190,NLP Engineer,75701,CAD,94626,EN,PT,Canada,L,Canada,50,"AWS, Git, Statistics",PhD,0,Finance,2024-04-19,2024-05-03,1321,5.8,Neural Networks Co -AI14191,Head of AI,45437,USD,45437,EN,PT,Israel,S,Israel,50,"Git, Deep Learning, Kubernetes",PhD,0,Automotive,2025-04-27,2025-06-06,1697,6.6,Cloud AI Solutions -AI14192,Machine Learning Researcher,74737,USD,74737,EN,PT,Finland,M,Germany,0,"GCP, Java, R, Docker",PhD,0,Media,2024-05-13,2024-07-15,2338,9.9,DataVision Ltd -AI14193,Computer Vision Engineer,57174,USD,57174,EN,FL,Finland,L,Finland,0,"NLP, SQL, Java, AWS",Master,1,Retail,2024-05-01,2024-07-06,1347,6.9,Cloud AI Solutions -AI14194,Research Scientist,152694,USD,152694,EX,PT,Sweden,M,Sweden,0,"Data Visualization, AWS, Java, SQL",Associate,14,Healthcare,2024-03-28,2024-05-23,776,9.2,Algorithmic Solutions -AI14195,Head of AI,118599,EUR,100809,SE,PT,France,L,Philippines,100,"Kubernetes, Scala, Tableau, GCP, Data Visualization",Bachelor,9,Automotive,2024-10-30,2024-11-20,1006,5.2,TechCorp Inc -AI14196,Research Scientist,87706,CHF,78935,EN,FL,Switzerland,S,Switzerland,0,"Kubernetes, NLP, GCP, Linux, Computer Vision",Associate,0,Energy,2025-02-11,2025-03-29,1980,6,Quantum Computing Inc -AI14197,Machine Learning Researcher,88238,EUR,75002,MI,FT,France,M,France,0,"Azure, PyTorch, AWS, GCP",Associate,3,Telecommunications,2024-11-27,2024-12-19,1198,8.9,Future Systems -AI14198,AI Specialist,92582,USD,92582,SE,FT,South Korea,S,South Korea,0,"NLP, Statistics, Hadoop",PhD,5,Healthcare,2025-03-16,2025-04-14,1582,9.9,Algorithmic Solutions -AI14199,Data Analyst,38341,USD,38341,MI,FT,China,M,China,100,"Kubernetes, Python, Deep Learning, MLOps",Associate,3,Automotive,2024-10-29,2024-12-08,2212,7.7,Cloud AI Solutions -AI14200,AI Architect,40454,USD,40454,SE,FT,India,M,India,0,"R, Azure, Java",PhD,9,Automotive,2025-04-20,2025-06-07,1755,6.9,Future Systems -AI14201,Robotics Engineer,67022,SGD,87129,EN,CT,Singapore,M,Singapore,50,"SQL, Java, AWS",Master,1,Healthcare,2025-02-09,2025-03-16,1201,8.7,Quantum Computing Inc -AI14202,Research Scientist,46195,USD,46195,EN,CT,South Korea,S,Norway,50,"Python, Linux, Java, Docker",PhD,0,Real Estate,2024-01-31,2024-03-23,1062,9.5,Neural Networks Co -AI14203,Machine Learning Engineer,184717,USD,184717,EX,FT,Sweden,L,Sweden,100,"Java, R, SQL, Spark, Mathematics",Master,16,Consulting,2024-11-13,2024-12-11,1866,7.5,Predictive Systems -AI14204,Machine Learning Researcher,84313,SGD,109607,EN,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Linux, Azure",Bachelor,0,Government,2024-11-20,2025-01-22,1994,7.4,Machine Intelligence Group -AI14205,Research Scientist,171948,JPY,18914280,EX,PT,Japan,M,China,0,"GCP, Spark, Docker, NLP, PyTorch",Bachelor,17,Telecommunications,2024-08-12,2024-10-04,938,7.8,Quantum Computing Inc -AI14206,Data Scientist,65079,EUR,55317,EN,PT,Netherlands,L,Sweden,50,"Scala, SQL, PyTorch, Hadoop, Azure",Bachelor,0,Consulting,2025-03-01,2025-05-02,507,6.6,TechCorp Inc -AI14207,Machine Learning Researcher,257240,USD,257240,EX,CT,United States,S,United States,100,"PyTorch, MLOps, NLP, Python",Master,15,Media,2025-04-29,2025-06-28,2003,5.1,Algorithmic Solutions -AI14208,Deep Learning Engineer,71462,AUD,96474,EN,PT,Australia,M,Colombia,100,"SQL, Linux, Mathematics",PhD,0,Healthcare,2024-04-23,2024-05-26,859,8.6,Digital Transformation LLC -AI14209,NLP Engineer,123699,USD,123699,MI,PT,United States,M,Ghana,100,"Git, PyTorch, TensorFlow, Kubernetes",Bachelor,3,Retail,2024-06-19,2024-08-02,1773,5.6,Autonomous Tech -AI14210,AI Architect,72589,USD,72589,EN,FL,Finland,M,Finland,100,"Linux, Python, Hadoop, TensorFlow",Associate,1,Energy,2024-02-29,2024-05-01,596,7,Quantum Computing Inc -AI14211,Data Engineer,128822,AUD,173910,SE,PT,Australia,S,Australia,50,"Data Visualization, Python, Git",Master,5,Manufacturing,2025-03-12,2025-04-02,1922,9.9,Algorithmic Solutions -AI14212,AI Consultant,76617,USD,76617,EN,FL,Sweden,M,Sweden,0,"Mathematics, Linux, Computer Vision, PyTorch",Associate,1,Automotive,2024-08-12,2024-09-19,1012,5.6,TechCorp Inc -AI14213,AI Specialist,93353,USD,93353,EN,PT,Norway,S,Norway,100,"Linux, Kubernetes, Scala",Associate,0,Retail,2025-02-09,2025-04-04,537,5.6,Autonomous Tech -AI14214,Deep Learning Engineer,128582,CHF,115724,MI,FT,Switzerland,L,Switzerland,50,"GCP, Python, Mathematics",Master,4,Transportation,2024-03-02,2024-05-14,1475,8,Machine Intelligence Group -AI14215,Data Analyst,105420,USD,105420,SE,CT,Israel,S,Israel,50,"Python, Kubernetes, Deep Learning, AWS, R",Master,8,Energy,2024-10-22,2024-12-12,1192,8.9,AI Innovations -AI14216,AI Specialist,158281,JPY,17410910,SE,FL,Japan,L,Japan,0,"Linux, AWS, GCP, Mathematics, Docker",Bachelor,5,Real Estate,2024-06-21,2024-08-03,2371,5.4,Neural Networks Co -AI14217,Robotics Engineer,90700,USD,90700,EN,PT,United States,M,United States,50,"PyTorch, TensorFlow, Computer Vision",PhD,1,Energy,2024-03-06,2024-03-27,1800,8.6,Quantum Computing Inc -AI14218,NLP Engineer,163549,USD,163549,SE,FL,Israel,L,Israel,100,"Java, MLOps, GCP",Master,9,Technology,2024-07-16,2024-09-05,1715,6.7,Machine Intelligence Group -AI14219,AI Architect,91126,USD,91126,EN,FL,Denmark,M,Denmark,50,"GCP, Kubernetes, Linux, Computer Vision, Python",PhD,0,Transportation,2024-05-01,2024-05-21,1952,5.9,Cognitive Computing -AI14220,AI Specialist,197097,USD,197097,SE,FL,Norway,L,Norway,0,"Java, Hadoop, TensorFlow",Associate,5,Healthcare,2024-05-28,2024-06-12,2047,5.8,Future Systems -AI14221,AI Architect,130848,USD,130848,SE,PT,Ireland,S,Ireland,50,"Python, Mathematics, Computer Vision, NLP, TensorFlow",PhD,7,Education,2024-09-10,2024-11-02,1856,9.1,DataVision Ltd -AI14222,Machine Learning Engineer,115185,EUR,97907,SE,PT,France,L,Switzerland,100,"Data Visualization, Python, TensorFlow, PyTorch",Bachelor,7,Education,2025-03-14,2025-03-31,1921,9.2,DeepTech Ventures -AI14223,AI Specialist,74184,USD,74184,MI,FT,Finland,S,Philippines,50,"Hadoop, Linux, Git, SQL, Java",PhD,2,Education,2025-03-27,2025-06-05,1287,7.9,AI Innovations -AI14224,Machine Learning Engineer,85351,EUR,72548,EN,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, GCP, NLP, Git",Bachelor,1,Real Estate,2024-12-04,2024-12-22,761,8.2,DataVision Ltd -AI14225,Autonomous Systems Engineer,65593,USD,65593,EN,PT,United States,S,United States,50,"Computer Vision, Azure, Data Visualization",Master,1,Media,2024-09-12,2024-10-22,2483,6,Predictive Systems -AI14226,Robotics Engineer,123894,USD,123894,SE,CT,Ireland,S,Ireland,50,"Spark, Azure, Tableau, SQL, PyTorch",Master,6,Government,2024-02-12,2024-02-27,1054,5.9,DataVision Ltd -AI14227,AI Architect,152751,USD,152751,MI,PT,Denmark,L,Denmark,100,"Scala, Computer Vision, SQL, Git, PyTorch",PhD,2,Energy,2024-04-14,2024-05-04,1986,9.9,Cloud AI Solutions -AI14228,AI Software Engineer,94949,USD,94949,MI,CT,Norway,S,Norway,0,"Python, MLOps, Spark, Scala, TensorFlow",Associate,3,Gaming,2024-01-03,2024-01-18,1610,9.6,Neural Networks Co -AI14229,Machine Learning Researcher,199664,USD,199664,EX,FL,South Korea,L,South Korea,0,"Kubernetes, Python, Linux",Associate,18,Healthcare,2024-10-11,2024-11-15,538,6.3,Future Systems -AI14230,Research Scientist,51090,USD,51090,EN,PT,South Korea,L,South Korea,50,"Git, Scala, Kubernetes, Statistics",Master,1,Manufacturing,2024-06-29,2024-08-26,1607,7.1,Predictive Systems -AI14231,Head of AI,80797,EUR,68677,MI,FL,Germany,S,Germany,100,"PyTorch, Azure, Hadoop, Tableau",Associate,4,Telecommunications,2024-01-20,2024-03-22,1039,9.1,Cognitive Computing -AI14232,AI Product Manager,148078,EUR,125866,SE,PT,France,L,India,100,"Data Visualization, Tableau, Azure, Python, GCP",Associate,5,Government,2024-09-27,2024-11-01,1476,5,DataVision Ltd -AI14233,Research Scientist,241116,EUR,204949,EX,CT,Netherlands,L,Netherlands,50,"Hadoop, Python, Spark, Kubernetes",Bachelor,15,Technology,2024-12-27,2025-02-03,1545,9.9,Cloud AI Solutions -AI14234,AI Specialist,71525,CAD,89406,MI,FL,Canada,M,Canada,100,"GCP, Azure, R, Data Visualization",Bachelor,4,Transportation,2024-01-05,2024-03-13,852,8.8,Cognitive Computing -AI14235,Machine Learning Researcher,228052,USD,228052,EX,FL,Denmark,S,Denmark,0,"Hadoop, Python, Computer Vision, Git, Scala",Bachelor,13,Real Estate,2025-02-07,2025-04-06,1439,7,TechCorp Inc -AI14236,Deep Learning Engineer,92722,SGD,120539,MI,FL,Singapore,L,Singapore,100,"MLOps, Spark, Data Visualization",Bachelor,3,Consulting,2024-03-20,2024-05-18,1536,9.8,Future Systems -AI14237,Principal Data Scientist,177606,JPY,19536660,SE,FL,Japan,L,Japan,50,"Scala, Spark, PyTorch, TensorFlow",Master,5,Government,2024-04-05,2024-05-02,2385,7.5,DataVision Ltd -AI14238,Deep Learning Engineer,65911,USD,65911,EN,CT,South Korea,L,South Korea,50,"PyTorch, Tableau, TensorFlow",PhD,1,Energy,2024-02-19,2024-03-30,1306,9.3,Autonomous Tech -AI14239,Machine Learning Engineer,91391,GBP,68543,MI,FT,United Kingdom,S,Mexico,0,"Scala, Python, MLOps, Kubernetes, TensorFlow",Bachelor,2,Healthcare,2024-01-11,2024-02-05,1946,9.2,Algorithmic Solutions -AI14240,Machine Learning Researcher,201317,USD,201317,EX,FT,Israel,M,Israel,50,"Hadoop, PyTorch, R, Tableau",Master,17,Gaming,2024-08-13,2024-10-07,2364,6.2,Neural Networks Co -AI14241,AI Research Scientist,63528,EUR,53999,EN,FT,France,M,France,50,"Scala, Python, PyTorch",PhD,1,Gaming,2025-01-11,2025-03-08,1363,8.2,Smart Analytics -AI14242,AI Consultant,74903,EUR,63668,EN,PT,Austria,L,Austria,0,"Git, Tableau, Python",Master,1,Education,2024-02-15,2024-04-27,1458,9.9,Algorithmic Solutions -AI14243,Computer Vision Engineer,33431,USD,33431,EN,PT,China,S,Latvia,0,"SQL, Spark, PyTorch, Deep Learning, Git",Associate,0,Automotive,2024-04-14,2024-05-30,1801,8.1,DataVision Ltd -AI14244,AI Software Engineer,58058,AUD,78378,EN,PT,Australia,S,Australia,50,"Git, TensorFlow, Deep Learning, MLOps, Scala",Bachelor,1,Energy,2025-03-09,2025-04-04,2334,5,Neural Networks Co -AI14245,NLP Engineer,125186,USD,125186,SE,FL,Ireland,L,Colombia,100,"R, Java, TensorFlow, Computer Vision, Hadoop",PhD,5,Manufacturing,2024-11-02,2025-01-13,2404,5.2,Neural Networks Co -AI14246,AI Research Scientist,157137,USD,157137,SE,CT,Denmark,L,Singapore,100,"Computer Vision, Linux, SQL",Associate,7,Automotive,2024-03-14,2024-03-30,644,6,Quantum Computing Inc -AI14247,Data Scientist,32212,USD,32212,MI,PT,India,M,India,0,"Scala, PyTorch, Azure, Hadoop, Linux",Bachelor,3,Energy,2024-05-04,2024-06-08,2216,6.5,Future Systems -AI14248,Head of AI,96262,USD,96262,MI,CT,Finland,L,Romania,0,"Spark, SQL, Kubernetes, Git, AWS",Bachelor,2,Manufacturing,2025-04-19,2025-06-02,749,8.3,DeepTech Ventures -AI14249,AI Specialist,87709,USD,87709,SE,CT,South Korea,M,Vietnam,100,"PyTorch, Kubernetes, Hadoop, AWS, SQL",Associate,7,Media,2024-07-24,2024-08-10,1821,6.8,Predictive Systems -AI14250,Robotics Engineer,150226,JPY,16524860,EX,FL,Japan,M,Japan,100,"Git, NLP, Data Visualization",Master,17,Government,2024-02-05,2024-03-15,642,9.7,Algorithmic Solutions -AI14251,AI Product Manager,68640,USD,68640,EN,PT,South Korea,L,South Korea,100,"Spark, Python, Tableau, MLOps, TensorFlow",PhD,0,Technology,2024-01-03,2024-03-07,1794,8.8,TechCorp Inc -AI14252,Data Analyst,54111,EUR,45994,EN,PT,France,M,Germany,0,"GCP, Data Visualization, Java, Computer Vision",PhD,0,Energy,2025-03-16,2025-04-30,2028,6.2,AI Innovations -AI14253,Computer Vision Engineer,144317,SGD,187612,EX,FT,Singapore,S,Ghana,50,"GCP, Git, Kubernetes, AWS",Associate,15,Gaming,2024-08-07,2024-10-10,969,6.8,Smart Analytics -AI14254,Principal Data Scientist,136724,AUD,184577,SE,FL,Australia,L,Australia,50,"Linux, Data Visualization, Python, Scala",Associate,8,Gaming,2024-11-08,2024-12-07,1981,9.5,Cognitive Computing -AI14255,Robotics Engineer,100385,EUR,85327,MI,CT,Austria,L,Russia,50,"Docker, Python, MLOps, TensorFlow, SQL",Bachelor,4,Technology,2024-02-10,2024-04-12,811,6.8,Autonomous Tech -AI14256,AI Specialist,90275,EUR,76734,EN,PT,Germany,L,Italy,100,"Git, Linux, TensorFlow, R, Computer Vision",Bachelor,0,Education,2025-01-08,2025-03-22,1806,6,DataVision Ltd -AI14257,Principal Data Scientist,180652,EUR,153554,EX,PT,Netherlands,S,Poland,100,"Deep Learning, AWS, Data Visualization, TensorFlow",Master,17,Real Estate,2024-07-31,2024-09-30,2331,7.9,Neural Networks Co -AI14258,Research Scientist,51128,EUR,43459,EN,FT,Germany,M,Germany,0,"SQL, Kubernetes, MLOps, GCP, Azure",Bachelor,0,Government,2024-09-23,2024-11-20,1099,6.9,Digital Transformation LLC -AI14259,Computer Vision Engineer,129737,EUR,110276,SE,FL,Austria,L,Austria,50,"Scala, Git, Kubernetes, TensorFlow, Python",PhD,9,Healthcare,2025-01-09,2025-02-11,1980,8.9,Autonomous Tech -AI14260,Machine Learning Researcher,81423,SGD,105850,EN,CT,Singapore,L,Canada,100,"Python, Kubernetes, Deep Learning, Docker",Associate,1,Healthcare,2024-11-20,2025-01-16,2142,5.5,Autonomous Tech -AI14261,Data Engineer,171399,CHF,154259,MI,FL,Switzerland,L,Poland,0,"PyTorch, SQL, TensorFlow, Tableau, Computer Vision",Master,2,Energy,2024-08-30,2024-11-02,1386,7.1,Algorithmic Solutions -AI14262,Principal Data Scientist,299540,USD,299540,EX,CT,Norway,L,Norway,100,"Spark, Linux, Data Visualization, Scala, PyTorch",PhD,16,Media,2024-07-29,2024-09-12,971,6.9,Machine Intelligence Group -AI14263,ML Ops Engineer,23079,USD,23079,MI,FL,India,S,India,50,"TensorFlow, Tableau, PyTorch",Associate,2,Real Estate,2024-12-15,2025-01-01,1015,6.9,Predictive Systems -AI14264,AI Software Engineer,160236,USD,160236,MI,PT,Norway,L,Mexico,0,"Deep Learning, Git, Kubernetes, Azure, Java",Associate,2,Gaming,2024-08-23,2024-10-26,2377,6.8,Machine Intelligence Group -AI14265,Machine Learning Researcher,75808,USD,75808,EN,FT,Sweden,L,Sweden,100,"Tableau, MLOps, Kubernetes, Hadoop, Azure",Associate,1,Media,2024-03-28,2024-05-31,1175,8.2,Future Systems -AI14266,Machine Learning Engineer,109582,USD,109582,MI,PT,Finland,L,Russia,50,"Computer Vision, Python, Java, R",PhD,3,Consulting,2025-01-10,2025-02-28,1714,8.8,Smart Analytics -AI14267,Robotics Engineer,85941,CAD,107426,MI,PT,Canada,M,Canada,0,"Scala, R, Data Visualization, Linux",Associate,2,Automotive,2025-01-17,2025-02-16,1525,7.9,DeepTech Ventures -AI14268,Computer Vision Engineer,160982,SGD,209277,SE,CT,Singapore,L,Turkey,100,"SQL, Azure, Statistics",Associate,5,Healthcare,2025-04-10,2025-05-05,642,9.5,Cognitive Computing -AI14269,AI Specialist,111319,GBP,83489,SE,CT,United Kingdom,S,United Kingdom,0,"Java, Azure, AWS, Spark, TensorFlow",Bachelor,7,Healthcare,2024-12-20,2025-02-26,913,8.1,TechCorp Inc -AI14270,NLP Engineer,99974,EUR,84978,SE,FT,France,M,France,0,"Python, Computer Vision, Tableau, Scala, Azure",Master,9,Finance,2024-01-11,2024-03-02,1351,8.9,TechCorp Inc -AI14271,AI Research Scientist,103001,CAD,128751,MI,PT,Canada,M,Finland,50,"Java, Kubernetes, PyTorch",Bachelor,4,Retail,2024-12-17,2025-01-01,963,9.7,Neural Networks Co -AI14272,AI Software Engineer,207251,EUR,176163,EX,PT,Austria,S,United States,100,"PyTorch, Computer Vision, Python, TensorFlow",Master,11,Technology,2024-08-17,2024-10-18,1504,9.1,Cloud AI Solutions -AI14273,ML Ops Engineer,65060,USD,65060,EN,FT,Finland,L,Finland,0,"AWS, Data Visualization, Hadoop",Master,1,Media,2025-03-15,2025-04-09,1904,7.6,TechCorp Inc -AI14274,AI Consultant,90343,EUR,76792,MI,CT,Austria,M,Austria,50,"Python, TensorFlow, Git",Master,3,Gaming,2024-05-26,2024-07-10,1702,6.8,Neural Networks Co -AI14275,AI Specialist,99304,USD,99304,SE,PT,Israel,M,Poland,50,"PyTorch, Git, Kubernetes",Bachelor,7,Manufacturing,2025-03-15,2025-04-23,1905,6.7,Machine Intelligence Group -AI14276,Robotics Engineer,79942,USD,79942,EN,PT,Sweden,M,Sweden,50,"Computer Vision, SQL, Kubernetes, Docker",PhD,1,Education,2024-10-29,2025-01-07,1330,9.8,Smart Analytics -AI14277,Computer Vision Engineer,105304,GBP,78978,SE,PT,United Kingdom,S,United Kingdom,50,"Azure, Linux, Hadoop, Mathematics, Kubernetes",Associate,8,Manufacturing,2025-01-18,2025-02-23,619,8.7,Future Systems -AI14278,Data Engineer,118101,USD,118101,SE,FL,Finland,M,Denmark,50,"TensorFlow, Spark, Statistics, Linux, AWS",Associate,7,Gaming,2024-11-06,2025-01-06,1101,5,Cloud AI Solutions -AI14279,AI Product Manager,64827,USD,64827,SE,FL,China,L,China,0,"Scala, Python, MLOps, Hadoop",Master,8,Finance,2025-02-11,2025-03-16,855,9.2,Algorithmic Solutions -AI14280,Head of AI,136792,USD,136792,MI,FL,Norway,L,United Kingdom,0,"Hadoop, Azure, Statistics",Master,4,Education,2024-11-15,2025-01-23,2468,8.3,Smart Analytics -AI14281,Deep Learning Engineer,125716,EUR,106859,SE,FL,France,L,France,0,"SQL, Python, Java, NLP, Spark",PhD,8,Education,2024-12-05,2025-01-07,1744,7.8,Algorithmic Solutions -AI14282,ML Ops Engineer,74299,USD,74299,EN,CT,Sweden,M,Sweden,0,"Java, Python, NLP",PhD,0,Consulting,2024-02-26,2024-05-05,2071,9.9,Digital Transformation LLC -AI14283,Machine Learning Engineer,279034,USD,279034,EX,FL,United States,L,Egypt,0,"Computer Vision, GCP, MLOps, NLP",Associate,19,Consulting,2024-09-05,2024-10-30,1323,6.5,Digital Transformation LLC -AI14284,Data Scientist,84474,GBP,63356,EN,FL,United Kingdom,M,United Kingdom,0,"Spark, NLP, TensorFlow",Associate,1,Education,2024-01-08,2024-02-02,1232,5.6,Neural Networks Co -AI14285,NLP Engineer,105225,USD,105225,EX,FL,China,L,Mexico,0,"MLOps, Azure, Kubernetes, NLP",Bachelor,17,Media,2024-02-17,2024-04-30,2011,9.9,Algorithmic Solutions -AI14286,Machine Learning Researcher,140938,USD,140938,SE,PT,South Korea,L,Romania,0,"Docker, Linux, Hadoop, NLP, R",PhD,6,Healthcare,2025-03-26,2025-05-04,804,7.2,TechCorp Inc -AI14287,Autonomous Systems Engineer,51274,USD,51274,EN,FT,South Korea,L,South Korea,50,"GCP, Azure, AWS, Deep Learning, Mathematics",Master,1,Technology,2024-10-08,2024-11-14,1708,9.1,DeepTech Ventures -AI14288,Data Scientist,78815,JPY,8669650,MI,PT,Japan,S,Japan,100,"Computer Vision, Java, NLP, Mathematics, Linux",PhD,3,Telecommunications,2024-04-07,2024-05-18,2219,9.4,Cloud AI Solutions -AI14289,Robotics Engineer,62675,USD,62675,EN,PT,Israel,L,Israel,50,"MLOps, Git, GCP",Associate,1,Healthcare,2025-01-10,2025-02-13,767,5.8,DeepTech Ventures -AI14290,Head of AI,44043,USD,44043,SE,FL,India,S,India,50,"Kubernetes, Scala, GCP, Python",Master,8,Media,2025-02-10,2025-04-17,1249,9.5,DataVision Ltd -AI14291,Machine Learning Engineer,91908,GBP,68931,MI,PT,United Kingdom,S,United Kingdom,100,"Data Visualization, Kubernetes, GCP, Scala",PhD,2,Real Estate,2024-06-08,2024-07-23,1802,9.7,DataVision Ltd -AI14292,Machine Learning Researcher,161960,EUR,137666,EX,CT,Austria,M,Austria,0,"Docker, Java, MLOps",PhD,14,Telecommunications,2024-10-31,2024-11-15,633,9.2,Future Systems -AI14293,AI Product Manager,59982,USD,59982,EN,FL,Israel,S,Indonesia,0,"AWS, Kubernetes, SQL, GCP, Data Visualization",PhD,0,Energy,2024-11-03,2024-12-06,1024,5.5,Neural Networks Co -AI14294,Data Analyst,73332,USD,73332,MI,FT,Israel,S,Malaysia,100,"Data Visualization, Statistics, Spark, Tableau",Associate,3,Energy,2024-01-17,2024-03-26,1881,6.4,Advanced Robotics -AI14295,Machine Learning Engineer,235865,USD,235865,EX,FT,Israel,M,Israel,0,"Hadoop, Linux, Kubernetes",PhD,17,Telecommunications,2024-12-15,2025-02-16,1931,7.2,DeepTech Ventures -AI14296,Computer Vision Engineer,62646,EUR,53249,EN,CT,France,L,Japan,50,"Hadoop, Statistics, Git",Bachelor,0,Government,2024-05-03,2024-05-21,2160,8.5,Autonomous Tech -AI14297,ML Ops Engineer,81857,USD,81857,MI,PT,United States,S,Finland,0,"TensorFlow, Linux, Python, Hadoop",Associate,2,Government,2025-03-31,2025-05-26,2393,9.2,Quantum Computing Inc -AI14298,Computer Vision Engineer,98405,AUD,132847,MI,PT,Australia,S,Denmark,0,"PyTorch, Computer Vision, Kubernetes, GCP, AWS",Master,4,Telecommunications,2025-02-17,2025-03-20,2240,8,Cognitive Computing -AI14299,Principal Data Scientist,52393,USD,52393,EN,FL,Sweden,S,Thailand,0,"Python, Kubernetes, TensorFlow",PhD,0,Transportation,2024-10-06,2024-11-27,969,9.3,Neural Networks Co -AI14300,Computer Vision Engineer,51076,USD,51076,EN,FL,Ireland,S,Ireland,0,"PyTorch, Deep Learning, SQL, GCP",Associate,0,Retail,2025-03-16,2025-05-19,1948,5.6,Quantum Computing Inc -AI14301,Data Engineer,109859,CHF,98873,EN,FT,Switzerland,L,Switzerland,0,"Mathematics, Scala, Tableau",Bachelor,0,Energy,2024-07-10,2024-09-16,620,7.6,DataVision Ltd -AI14302,Machine Learning Researcher,140133,SGD,182173,SE,PT,Singapore,S,Poland,50,"Scala, Java, Docker",Master,9,Healthcare,2024-05-15,2024-06-10,1824,8.6,Autonomous Tech -AI14303,Head of AI,233979,USD,233979,EX,FT,United States,S,United States,50,"MLOps, R, GCP, Linux",Bachelor,19,Gaming,2024-08-06,2024-10-18,1936,7.7,Quantum Computing Inc -AI14304,AI Architect,61640,EUR,52394,EN,FL,France,S,France,100,"Java, PyTorch, Azure",Associate,1,Manufacturing,2025-01-26,2025-03-09,1512,7.2,Advanced Robotics -AI14305,NLP Engineer,162855,EUR,138427,SE,PT,Germany,L,Germany,100,"Python, Spark, TensorFlow, Statistics, Git",Master,8,Healthcare,2024-11-29,2025-01-24,1320,5.5,Quantum Computing Inc -AI14306,Autonomous Systems Engineer,102016,EUR,86714,MI,FT,Austria,L,Austria,0,"Azure, Git, Python, Linux",Bachelor,2,Consulting,2024-04-10,2024-05-10,1178,7.1,AI Innovations -AI14307,Data Scientist,65504,CAD,81880,EN,PT,Canada,L,Canada,100,"Docker, Data Visualization, Tableau, TensorFlow, Mathematics",Associate,0,Technology,2024-12-08,2025-02-10,678,5.2,Digital Transformation LLC -AI14308,AI Product Manager,75588,USD,75588,MI,FT,South Korea,S,South Korea,0,"GCP, R, NLP",Bachelor,4,Technology,2024-04-17,2024-05-28,1720,8,TechCorp Inc -AI14309,AI Architect,112458,CAD,140573,SE,FL,Canada,M,Canada,50,"Docker, Computer Vision, PyTorch",Associate,6,Education,2024-01-23,2024-03-11,1021,8.7,Cloud AI Solutions -AI14310,Computer Vision Engineer,124536,EUR,105856,EX,PT,Austria,S,Denmark,100,"TensorFlow, Deep Learning, Data Visualization, Computer Vision, Java",PhD,10,Media,2024-10-01,2024-11-07,550,9.6,Cognitive Computing -AI14311,Head of AI,175373,EUR,149067,EX,FL,Germany,L,Germany,50,"Statistics, PyTorch, Deep Learning",Master,17,Transportation,2024-07-03,2024-08-29,1193,10,Neural Networks Co -AI14312,AI Architect,116773,USD,116773,MI,CT,Ireland,L,Argentina,100,"Java, Hadoop, MLOps",PhD,3,Finance,2024-11-21,2024-12-26,502,6.2,Smart Analytics -AI14313,Machine Learning Engineer,81273,EUR,69082,EN,CT,Netherlands,M,Japan,0,"R, SQL, NLP, Git, GCP",Master,0,Media,2024-07-06,2024-08-16,862,9.9,Predictive Systems -AI14314,Machine Learning Engineer,90934,USD,90934,MI,PT,United States,S,United States,50,"Linux, GCP, Statistics, Deep Learning",Master,2,Manufacturing,2024-09-10,2024-10-19,2041,6.1,DataVision Ltd -AI14315,Computer Vision Engineer,141213,SGD,183577,SE,FL,Singapore,S,Philippines,100,"AWS, Python, Statistics, TensorFlow",PhD,9,Telecommunications,2024-07-23,2024-08-26,661,6.1,Cognitive Computing -AI14316,Head of AI,275394,SGD,358012,EX,FL,Singapore,L,Romania,100,"Python, Spark, Git, TensorFlow",Bachelor,18,Healthcare,2024-05-24,2024-07-29,874,6.6,Digital Transformation LLC -AI14317,Principal Data Scientist,107900,CAD,134875,SE,PT,Canada,S,Canada,0,"PyTorch, Azure, Spark",Bachelor,6,Government,2025-01-04,2025-01-19,1643,6,Future Systems -AI14318,Research Scientist,94985,JPY,10448350,EN,FT,Japan,L,Germany,100,"Python, Git, Deep Learning, PyTorch",PhD,1,Transportation,2024-03-03,2024-03-23,675,7.4,Autonomous Tech -AI14319,Computer Vision Engineer,123657,JPY,13602270,SE,FL,Japan,M,Italy,0,"Git, PyTorch, TensorFlow",PhD,8,Transportation,2024-06-07,2024-07-05,1062,8.8,Cloud AI Solutions -AI14320,AI Specialist,18446,USD,18446,EN,FL,India,S,India,100,"PyTorch, Scala, Git, NLP",Master,1,Transportation,2024-01-03,2024-02-01,2179,7.4,TechCorp Inc -AI14321,Robotics Engineer,125558,USD,125558,EX,FL,China,L,Romania,50,"Spark, MLOps, SQL, Hadoop",Bachelor,14,Technology,2024-04-09,2024-04-23,1998,7,DataVision Ltd -AI14322,Data Engineer,55209,EUR,46928,EN,FT,France,L,France,0,"Deep Learning, Kubernetes, Git, Statistics",Bachelor,1,Media,2024-12-14,2025-01-29,1887,6.6,Algorithmic Solutions -AI14323,AI Research Scientist,233676,EUR,198625,EX,FL,France,L,France,50,"SQL, Hadoop, PyTorch, Tableau",PhD,11,Manufacturing,2024-04-26,2024-07-01,2101,6.6,Cognitive Computing -AI14324,Principal Data Scientist,30081,USD,30081,MI,FT,India,L,India,0,"SQL, Git, Docker",PhD,2,Education,2024-09-03,2024-10-21,2325,5.8,Autonomous Tech -AI14325,Robotics Engineer,155252,EUR,131964,EX,CT,Austria,M,Austria,50,"Kubernetes, Hadoop, Spark, Docker, Git",Associate,11,Real Estate,2024-01-24,2024-03-31,1042,9.8,Predictive Systems -AI14326,Machine Learning Researcher,132368,CAD,165460,SE,FT,Canada,M,Canada,100,"SQL, Git, Data Visualization, Java, Spark",Master,7,Finance,2025-02-24,2025-04-04,1828,5.2,DeepTech Ventures -AI14327,Computer Vision Engineer,84373,USD,84373,MI,CT,South Korea,M,South Korea,0,"SQL, Computer Vision, Kubernetes, MLOps, Python",PhD,2,Telecommunications,2024-07-26,2024-10-07,2348,6.8,Digital Transformation LLC -AI14328,AI Architect,264528,USD,264528,EX,CT,Denmark,M,Denmark,100,"GCP, Linux, Computer Vision",Associate,11,Gaming,2024-09-15,2024-11-27,2001,7.5,AI Innovations -AI14329,Data Engineer,29715,USD,29715,EN,CT,India,L,India,0,"Mathematics, Scala, Python, AWS, Data Visualization",PhD,0,Automotive,2025-04-06,2025-06-07,2490,9.3,Advanced Robotics -AI14330,AI Specialist,164165,EUR,139540,SE,CT,Germany,L,Germany,50,"Java, MLOps, Linux, Deep Learning",Bachelor,9,Consulting,2024-01-14,2024-02-05,1341,9.4,TechCorp Inc -AI14331,Research Scientist,223621,USD,223621,EX,FL,Denmark,L,Czech Republic,0,"Scala, Tableau, Kubernetes, R",PhD,11,Manufacturing,2024-12-14,2025-02-06,705,6,Neural Networks Co -AI14332,AI Architect,226374,SGD,294286,EX,FL,Singapore,S,Singapore,100,"Kubernetes, Python, Data Visualization",Bachelor,16,Finance,2024-01-11,2024-03-22,1812,8.8,AI Innovations -AI14333,Machine Learning Engineer,76615,USD,76615,EN,FT,Sweden,M,Norway,50,"Scala, Tableau, R, Azure, Linux",Master,0,Gaming,2024-08-01,2024-08-20,1375,5.9,Algorithmic Solutions -AI14334,AI Consultant,85551,CHF,76996,EN,PT,Switzerland,L,Switzerland,100,"PyTorch, Linux, TensorFlow",Master,0,Telecommunications,2024-12-19,2025-01-18,2033,8.9,TechCorp Inc -AI14335,AI Consultant,156675,GBP,117506,EX,FT,United Kingdom,M,France,50,"Hadoop, Scala, Linux, Computer Vision",Master,18,Finance,2024-09-03,2024-10-07,1584,9,Predictive Systems -AI14336,Principal Data Scientist,55271,EUR,46980,EN,FL,France,M,France,50,"Git, TensorFlow, PyTorch, Scala",Bachelor,0,Finance,2024-05-15,2024-06-11,1717,8.4,Cloud AI Solutions -AI14337,AI Software Engineer,166389,USD,166389,EX,FL,Finland,M,Ghana,50,"R, Python, Hadoop",Bachelor,12,Retail,2025-03-11,2025-04-15,2042,7.1,Predictive Systems -AI14338,NLP Engineer,82549,SGD,107314,EN,FL,Singapore,L,United States,0,"MLOps, Azure, Kubernetes, Tableau, Docker",Master,1,Consulting,2025-01-21,2025-03-24,1901,6.8,Smart Analytics -AI14339,Principal Data Scientist,76753,GBP,57565,EN,CT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, PyTorch",Master,1,Real Estate,2024-02-20,2024-04-02,975,9.2,Neural Networks Co -AI14340,AI Research Scientist,73157,EUR,62183,MI,PT,Netherlands,S,Netherlands,50,"Scala, SQL, Data Visualization, GCP, PyTorch",PhD,4,Finance,2025-01-21,2025-03-29,678,8,Cognitive Computing -AI14341,Data Analyst,116897,USD,116897,SE,FL,South Korea,M,Belgium,100,"PyTorch, TensorFlow, Git, GCP, Linux",PhD,6,Retail,2024-11-19,2025-01-26,1136,6.6,Future Systems -AI14342,AI Software Engineer,130794,USD,130794,SE,FL,Finland,L,Vietnam,0,"Python, AWS, Statistics, Computer Vision",PhD,9,Media,2024-08-25,2024-10-23,1247,8.4,DataVision Ltd -AI14343,Deep Learning Engineer,102032,JPY,11223520,MI,FL,Japan,M,Japan,100,"Kubernetes, Computer Vision, AWS, Azure",Associate,4,Healthcare,2025-01-30,2025-03-25,2399,8.4,AI Innovations -AI14344,AI Product Manager,142857,EUR,121428,SE,FT,Austria,L,South Africa,50,"SQL, Python, AWS, Java, TensorFlow",PhD,7,Consulting,2024-03-29,2024-05-11,2479,9.5,Cognitive Computing -AI14345,AI Research Scientist,187842,SGD,244195,EX,PT,Singapore,M,Singapore,50,"Hadoop, TensorFlow, Computer Vision, MLOps",PhD,14,Media,2025-01-24,2025-02-10,1075,7.9,Neural Networks Co -AI14346,AI Research Scientist,157194,SGD,204352,EX,FL,Singapore,S,Poland,100,"Python, Java, SQL",Bachelor,17,Automotive,2025-01-20,2025-02-05,2120,5.7,Cloud AI Solutions -AI14347,Deep Learning Engineer,104641,EUR,88945,MI,CT,Netherlands,S,Belgium,0,"SQL, Git, Kubernetes",Master,4,Transportation,2025-03-17,2025-04-25,2022,9.4,Advanced Robotics -AI14348,Machine Learning Engineer,70047,USD,70047,EN,CT,United States,S,Indonesia,100,"Deep Learning, Scala, AWS",Master,1,Manufacturing,2024-07-12,2024-08-14,1560,6.3,Algorithmic Solutions -AI14349,AI Consultant,174437,USD,174437,SE,CT,Norway,S,Egypt,0,"AWS, Docker, SQL, Git, Scala",Associate,5,Energy,2024-02-12,2024-04-05,1526,8.2,Algorithmic Solutions -AI14350,Head of AI,291903,AUD,394069,EX,FT,Australia,L,Australia,50,"Statistics, Scala, Deep Learning, Data Visualization, Mathematics",Bachelor,17,Government,2024-10-26,2024-11-10,2021,8.3,Machine Intelligence Group -AI14351,Data Engineer,257612,USD,257612,EX,CT,United States,S,Japan,50,"R, Deep Learning, Azure",Associate,19,Telecommunications,2024-04-01,2024-05-13,1277,9.2,Cloud AI Solutions -AI14352,ML Ops Engineer,138666,USD,138666,MI,FT,Norway,M,India,50,"Linux, Data Visualization, TensorFlow, Mathematics",Master,2,Telecommunications,2024-12-07,2025-02-04,1782,6.3,Cognitive Computing -AI14353,Autonomous Systems Engineer,139390,SGD,181207,SE,PT,Singapore,M,Singapore,50,"Python, TensorFlow, PyTorch, Azure, Linux",PhD,9,Retail,2025-01-21,2025-04-03,2156,9,Cloud AI Solutions -AI14354,Data Engineer,137009,EUR,116458,SE,CT,Austria,L,Austria,100,"Java, Spark, Computer Vision",Associate,9,Gaming,2024-03-21,2024-04-25,1105,9.6,Advanced Robotics -AI14355,AI Architect,154759,USD,154759,EX,FL,Ireland,M,Ireland,100,"SQL, PyTorch, GCP",Bachelor,17,Automotive,2024-04-06,2024-05-03,1786,7.4,Cognitive Computing -AI14356,Data Engineer,132746,SGD,172570,SE,CT,Singapore,M,Sweden,100,"Python, NLP, TensorFlow, PyTorch, Git",PhD,6,Technology,2024-02-14,2024-03-01,2443,7.7,Neural Networks Co -AI14357,Data Engineer,100856,GBP,75642,MI,FT,United Kingdom,L,United Kingdom,100,"SQL, Kubernetes, Deep Learning, Python",PhD,3,Government,2024-02-16,2024-04-09,763,8,AI Innovations -AI14358,Machine Learning Engineer,49761,GBP,37321,EN,FL,United Kingdom,S,Romania,50,"R, Tableau, SQL",Master,0,Education,2024-02-02,2024-02-23,1476,5.9,DeepTech Ventures -AI14359,Research Scientist,77665,GBP,58249,EN,CT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning, Hadoop",PhD,0,Education,2024-01-08,2024-02-20,654,7.7,Digital Transformation LLC -AI14360,Data Scientist,71610,USD,71610,EN,FT,Ireland,L,Italy,0,"Spark, AWS, SQL",PhD,0,Finance,2024-09-20,2024-10-13,1560,5.9,Cloud AI Solutions -AI14361,Head of AI,57686,CAD,72108,EN,FT,Canada,M,Canada,100,"Git, Mathematics, SQL, TensorFlow, Computer Vision",Master,1,Energy,2024-06-11,2024-08-06,2351,8.3,Smart Analytics -AI14362,Machine Learning Researcher,131219,EUR,111536,SE,CT,Netherlands,M,Netherlands,50,"Docker, PyTorch, Azure, Hadoop, TensorFlow",Master,6,Transportation,2024-06-12,2024-07-12,1918,7.8,Cognitive Computing -AI14363,Robotics Engineer,104036,AUD,140449,MI,FT,Australia,M,Australia,100,"Kubernetes, Computer Vision, NLP",Bachelor,3,Media,2024-12-11,2025-02-06,1735,7.2,Smart Analytics -AI14364,NLP Engineer,154548,USD,154548,EX,FT,Finland,L,India,50,"PyTorch, TensorFlow, Java",Master,18,Retail,2024-02-04,2024-03-05,1766,8.9,Autonomous Tech -AI14365,ML Ops Engineer,189083,USD,189083,EX,PT,Sweden,L,Sweden,50,"SQL, Linux, Statistics, Hadoop",PhD,19,Healthcare,2024-10-27,2024-11-11,1412,7.5,TechCorp Inc -AI14366,Head of AI,107559,USD,107559,SE,PT,Sweden,S,Sweden,0,"Azure, Kubernetes, Mathematics, Docker",Associate,6,Energy,2024-03-13,2024-05-05,1206,8.8,Quantum Computing Inc -AI14367,Machine Learning Engineer,197070,CAD,246338,EX,FT,Canada,S,Canada,100,"PyTorch, Hadoop, Python, Git",Bachelor,10,Government,2024-07-20,2024-09-10,1688,10,Digital Transformation LLC -AI14368,Data Analyst,158181,CAD,197726,SE,PT,Canada,L,Egypt,0,"Linux, R, MLOps",Bachelor,8,Telecommunications,2024-04-26,2024-06-18,799,6.6,Cloud AI Solutions -AI14369,Data Analyst,118102,EUR,100387,SE,FL,France,S,France,100,"R, Mathematics, Scala, Statistics",Bachelor,9,Healthcare,2024-04-13,2024-05-05,1809,6.9,AI Innovations -AI14370,Data Engineer,112990,USD,112990,MI,CT,Norway,S,Norway,0,"Linux, Java, PyTorch, Git, MLOps",Master,4,Transportation,2025-04-02,2025-04-26,2482,6.6,AI Innovations -AI14371,ML Ops Engineer,147657,JPY,16242270,EX,PT,Japan,M,Japan,50,"Spark, MLOps, Azure, SQL, Docker",Master,11,Education,2024-05-16,2024-06-25,1666,5.6,Machine Intelligence Group -AI14372,Machine Learning Engineer,145533,EUR,123703,SE,PT,Netherlands,M,China,100,"Python, TensorFlow, Docker",Associate,6,Education,2024-01-10,2024-02-28,730,7.6,Cognitive Computing -AI14373,Data Scientist,128282,USD,128282,MI,CT,Denmark,M,Russia,0,"Python, Scala, SQL",Bachelor,2,Retail,2024-10-04,2024-10-24,1809,8.2,DataVision Ltd -AI14374,Principal Data Scientist,118956,EUR,101113,SE,PT,Germany,L,Germany,50,"NLP, Deep Learning, Kubernetes",PhD,9,Consulting,2024-12-07,2024-12-30,1671,7.2,Future Systems -AI14375,AI Consultant,64457,USD,64457,EX,FT,China,M,China,50,"R, Python, Linux, Docker, MLOps",Bachelor,12,Finance,2024-08-06,2024-09-15,2061,6.6,DeepTech Ventures -AI14376,ML Ops Engineer,75849,EUR,64472,EN,CT,Netherlands,M,Netherlands,100,"Data Visualization, TensorFlow, Deep Learning, Tableau, Hadoop",Master,0,Automotive,2024-03-01,2024-03-23,1079,5.1,Neural Networks Co -AI14377,Data Engineer,137657,USD,137657,EX,FT,China,L,New Zealand,0,"Docker, Data Visualization, Tableau, R",Bachelor,18,Media,2024-10-31,2024-12-05,1668,7.7,Predictive Systems -AI14378,Robotics Engineer,144216,USD,144216,SE,PT,Sweden,M,Sweden,0,"Git, GCP, Tableau, PyTorch, Java",Bachelor,6,Consulting,2024-11-17,2025-01-07,2242,7.7,Cognitive Computing -AI14379,AI Consultant,113094,SGD,147022,SE,PT,Singapore,M,Singapore,0,"NLP, Kubernetes, GCP",Bachelor,5,Gaming,2024-07-30,2024-10-11,2205,5.1,Future Systems -AI14380,Data Engineer,138816,GBP,104112,SE,FT,United Kingdom,S,United Kingdom,100,"Data Visualization, R, Python",Bachelor,7,Gaming,2024-12-11,2025-02-10,1227,9.5,Cloud AI Solutions -AI14381,AI Research Scientist,105524,EUR,89695,SE,FT,France,S,France,50,"Python, Data Visualization, GCP, Mathematics",Bachelor,5,Telecommunications,2024-06-11,2024-08-17,1248,6.9,Future Systems -AI14382,Machine Learning Engineer,235370,JPY,25890700,EX,CT,Japan,L,Estonia,50,"Python, Azure, SQL, Spark, AWS",Master,19,Automotive,2024-02-07,2024-03-18,960,8.3,DataVision Ltd -AI14383,Machine Learning Engineer,53545,USD,53545,EN,FT,Finland,M,Finland,0,"Docker, Linux, Computer Vision",Master,0,Retail,2025-01-24,2025-03-25,520,9.6,Quantum Computing Inc -AI14384,Principal Data Scientist,246044,AUD,332159,EX,FL,Australia,L,Australia,50,"Statistics, R, Kubernetes, PyTorch",Master,10,Transportation,2024-04-06,2024-05-07,1758,5.3,TechCorp Inc -AI14385,Machine Learning Engineer,79749,EUR,67787,MI,FL,Austria,S,Austria,100,"Deep Learning, Data Visualization, Java, Tableau",Bachelor,3,Healthcare,2025-04-16,2025-06-05,2163,7.1,Digital Transformation LLC -AI14386,AI Product Manager,45513,USD,45513,MI,FL,China,S,China,50,"GCP, Spark, PyTorch, MLOps",PhD,2,Education,2024-11-09,2024-12-03,1131,9.9,Machine Intelligence Group -AI14387,ML Ops Engineer,147346,SGD,191550,SE,FT,Singapore,L,Singapore,50,"Kubernetes, Azure, Linux, Statistics, Spark",Associate,8,Telecommunications,2024-04-09,2024-05-03,1332,9.2,Advanced Robotics -AI14388,Autonomous Systems Engineer,96801,EUR,82281,MI,FL,Austria,M,Romania,50,"Statistics, PyTorch, Azure, Spark",Master,4,Government,2024-03-22,2024-05-26,616,7.2,Cognitive Computing -AI14389,Data Scientist,112083,USD,112083,MI,CT,Ireland,L,Ireland,50,"Tableau, SQL, Kubernetes, PyTorch",Bachelor,3,Transportation,2024-07-26,2024-09-25,1774,5.2,Advanced Robotics -AI14390,Computer Vision Engineer,119874,AUD,161830,MI,PT,Australia,L,Australia,50,"Git, PyTorch, Tableau, AWS",Bachelor,2,Healthcare,2025-04-12,2025-05-20,681,5.9,Advanced Robotics -AI14391,AI Product Manager,37440,USD,37440,SE,FT,India,M,India,0,"SQL, PyTorch, R, Statistics",Bachelor,5,Consulting,2024-07-03,2024-08-02,1668,8.8,Cognitive Computing -AI14392,AI Software Engineer,156018,USD,156018,SE,PT,United States,S,United States,100,"Spark, TensorFlow, Computer Vision",Master,7,Education,2024-01-01,2024-02-28,1438,8.6,Future Systems -AI14393,AI Architect,77323,USD,77323,MI,FT,Finland,S,Finland,100,"MLOps, AWS, GCP, Spark, Tableau",Master,3,Consulting,2024-03-05,2024-04-12,2405,7,Predictive Systems -AI14394,Machine Learning Researcher,157671,USD,157671,EX,PT,South Korea,S,South Korea,0,"GCP, R, Kubernetes",Master,11,Real Estate,2024-10-13,2024-11-17,1026,7.5,Digital Transformation LLC -AI14395,Deep Learning Engineer,107434,SGD,139664,MI,FT,Singapore,M,Singapore,50,"Hadoop, Docker, AWS, PyTorch",PhD,3,Energy,2024-07-25,2024-09-19,2130,7.5,Cloud AI Solutions -AI14396,Robotics Engineer,69805,EUR,59334,MI,FT,France,M,France,50,"SQL, Data Visualization, Azure, Spark",PhD,2,Media,2024-10-02,2024-10-16,1607,9.8,Advanced Robotics -AI14397,AI Research Scientist,80668,EUR,68568,MI,FL,Austria,L,Austria,100,"Hadoop, Tableau, SQL, NLP",PhD,4,Consulting,2025-02-06,2025-04-05,594,6,Digital Transformation LLC -AI14398,Head of AI,140967,EUR,119822,EX,FT,Germany,M,Philippines,100,"Data Visualization, R, SQL",Master,11,Finance,2024-04-10,2024-04-29,1541,6.4,Algorithmic Solutions -AI14399,Principal Data Scientist,112216,USD,112216,SE,PT,Sweden,M,Belgium,0,"Python, TensorFlow, Docker",Master,7,Real Estate,2024-08-12,2024-09-20,1853,7.9,TechCorp Inc -AI14400,Autonomous Systems Engineer,210828,JPY,23191080,EX,PT,Japan,S,Japan,50,"SQL, Python, R",Bachelor,19,Healthcare,2025-04-16,2025-06-28,2384,6.5,TechCorp Inc -AI14401,Principal Data Scientist,44332,USD,44332,SE,FL,India,S,India,0,"Git, MLOps, Tableau, Kubernetes, Computer Vision",Master,9,Manufacturing,2024-08-28,2024-09-21,942,9.8,AI Innovations -AI14402,Data Engineer,68896,EUR,58562,EN,FL,France,M,France,50,"Computer Vision, SQL, Kubernetes, Linux",Bachelor,1,Education,2024-09-01,2024-11-04,847,8,Future Systems -AI14403,Data Scientist,165554,CHF,148999,MI,FL,Switzerland,L,Netherlands,50,"SQL, Kubernetes, MLOps, Hadoop",Bachelor,4,Consulting,2024-06-05,2024-06-19,1740,8.3,Digital Transformation LLC -AI14404,AI Architect,114670,USD,114670,MI,PT,Denmark,S,Denmark,100,"Python, TensorFlow, MLOps, Docker",PhD,4,Government,2024-05-19,2024-06-09,1820,9.2,Algorithmic Solutions -AI14405,Data Analyst,97405,JPY,10714550,EN,PT,Japan,L,Ireland,50,"Spark, Linux, Data Visualization, Git",Master,1,Energy,2024-05-02,2024-06-27,2381,7.8,DataVision Ltd -AI14406,AI Specialist,92003,EUR,78203,SE,PT,France,S,Hungary,0,"SQL, Linux, Scala, Docker, Kubernetes",Master,8,Consulting,2024-07-03,2024-07-28,1265,6.2,Digital Transformation LLC -AI14407,Principal Data Scientist,85732,USD,85732,EN,FT,Denmark,S,Denmark,0,"Scala, Computer Vision, R, SQL",Master,0,Healthcare,2024-07-01,2024-08-01,2168,9,DataVision Ltd -AI14408,Data Analyst,158515,EUR,134738,EX,FT,Netherlands,M,Netherlands,50,"Java, Spark, Data Visualization, MLOps, Mathematics",PhD,16,Consulting,2024-08-10,2024-09-21,1073,8.2,Predictive Systems -AI14409,AI Specialist,119601,USD,119601,SE,CT,Sweden,M,Sweden,50,"Python, Hadoop, Data Visualization, Docker, Computer Vision",Associate,9,Consulting,2025-03-05,2025-05-04,1855,5.6,Machine Intelligence Group -AI14410,NLP Engineer,72330,EUR,61481,EN,PT,France,M,France,0,"Computer Vision, GCP, Docker",Bachelor,0,Transportation,2024-02-22,2024-04-01,1518,5.4,Machine Intelligence Group -AI14411,AI Specialist,109208,GBP,81906,SE,PT,United Kingdom,M,United Kingdom,100,"Tableau, Git, GCP, PyTorch",PhD,7,Energy,2024-02-01,2024-02-26,1993,7,Predictive Systems -AI14412,Computer Vision Engineer,59992,USD,59992,EX,PT,India,M,Turkey,100,"NLP, PyTorch, AWS, GCP, Java",Master,11,Consulting,2025-03-26,2025-05-29,901,8,Cognitive Computing -AI14413,Data Scientist,81724,USD,81724,EN,FL,Sweden,L,Sweden,0,"Java, Hadoop, Azure, Computer Vision, Git",PhD,1,Manufacturing,2024-05-20,2024-07-27,1347,8.9,TechCorp Inc -AI14414,Autonomous Systems Engineer,152556,USD,152556,SE,PT,Norway,S,Norway,0,"Deep Learning, SQL, Computer Vision, Scala, Azure",Master,5,Automotive,2025-02-27,2025-03-17,563,5.3,Advanced Robotics -AI14415,AI Consultant,93627,SGD,121715,MI,CT,Singapore,M,Singapore,50,"Data Visualization, TensorFlow, Scala",Bachelor,2,Media,2024-12-22,2025-01-18,2345,6.4,Predictive Systems -AI14416,AI Consultant,368934,USD,368934,EX,PT,Norway,L,Norway,0,"TensorFlow, Azure, PyTorch, Tableau, Python",Associate,12,Energy,2024-11-07,2025-01-03,594,8.8,Smart Analytics -AI14417,ML Ops Engineer,62871,USD,62871,EN,FT,Ireland,M,Thailand,100,"AWS, SQL, Python",Master,1,Media,2025-04-02,2025-04-24,2391,6.5,Machine Intelligence Group -AI14418,AI Software Engineer,163945,SGD,213129,EX,FT,Singapore,M,Germany,100,"GCP, Data Visualization, AWS",Associate,13,Technology,2024-01-10,2024-03-02,2184,8.1,Predictive Systems -AI14419,AI Software Engineer,282346,CHF,254111,EX,PT,Switzerland,S,Ireland,0,"Scala, TensorFlow, AWS, R",Bachelor,18,Finance,2025-02-06,2025-04-10,949,7.3,Neural Networks Co -AI14420,AI Architect,198337,USD,198337,EX,FT,Finland,L,Israel,100,"Kubernetes, Azure, Statistics, Git",Bachelor,17,Real Estate,2024-03-03,2024-03-25,2005,6.5,AI Innovations -AI14421,Data Analyst,75384,USD,75384,SE,FT,China,L,Turkey,50,"Kubernetes, Linux, Data Visualization",Master,9,Consulting,2024-10-06,2024-11-05,1413,9.4,Cloud AI Solutions -AI14422,NLP Engineer,209294,EUR,177900,EX,PT,Germany,M,Germany,100,"R, Python, AWS",Master,17,Energy,2024-10-27,2024-11-25,1635,8.9,Neural Networks Co -AI14423,Robotics Engineer,61021,USD,61021,EN,PT,Israel,M,Israel,100,"Tableau, Azure, Spark, Java",PhD,1,Telecommunications,2025-03-09,2025-04-03,715,6.4,Neural Networks Co -AI14424,AI Software Engineer,132259,GBP,99194,SE,FT,United Kingdom,S,United Kingdom,0,"Python, AWS, Data Visualization, Linux, GCP",Bachelor,8,Media,2024-06-09,2024-07-27,711,9.2,TechCorp Inc -AI14425,AI Specialist,131957,USD,131957,SE,PT,Sweden,S,Sweden,100,"Python, AWS, TensorFlow",PhD,9,Media,2024-09-19,2024-10-08,694,5.3,Machine Intelligence Group -AI14426,Deep Learning Engineer,87003,USD,87003,EN,PT,United States,L,United States,100,"Tableau, Docker, Hadoop, PyTorch, R",Bachelor,0,Education,2024-07-07,2024-08-17,1928,5.9,Smart Analytics -AI14427,AI Product Manager,220540,EUR,187459,EX,CT,Netherlands,S,Netherlands,50,"AWS, Linux, Kubernetes, Statistics, Mathematics",Associate,11,Education,2024-08-16,2024-09-06,1340,10,Algorithmic Solutions -AI14428,Data Analyst,167769,CHF,150992,SE,PT,Switzerland,L,Switzerland,50,"Hadoop, Java, NLP, Mathematics, Deep Learning",Associate,7,Government,2024-01-26,2024-03-16,1036,5.7,Machine Intelligence Group -AI14429,Head of AI,187950,USD,187950,EX,FL,South Korea,S,China,50,"Data Visualization, AWS, TensorFlow, Hadoop, Azure",Associate,19,Gaming,2024-12-24,2025-02-17,920,5.7,DeepTech Ventures -AI14430,ML Ops Engineer,58695,EUR,49891,EN,FT,Germany,S,Singapore,0,"Linux, Kubernetes, NLP, Mathematics",Master,0,Automotive,2024-02-21,2024-03-29,588,7.4,DeepTech Ventures -AI14431,Machine Learning Engineer,265749,USD,265749,EX,CT,Ireland,L,Ireland,0,"PyTorch, Java, MLOps, Scala, Azure",Bachelor,11,Gaming,2024-10-23,2024-11-23,697,8.8,DataVision Ltd -AI14432,Research Scientist,110493,EUR,93919,SE,PT,Germany,S,Germany,100,"R, NLP, Python",PhD,7,Healthcare,2025-01-11,2025-03-17,2345,6.9,Quantum Computing Inc -AI14433,Computer Vision Engineer,20337,USD,20337,EN,FT,India,S,Switzerland,0,"GCP, SQL, PyTorch",PhD,0,Consulting,2025-04-08,2025-05-31,1553,9.3,Algorithmic Solutions -AI14434,Computer Vision Engineer,123983,JPY,13638130,MI,CT,Japan,L,Japan,100,"Python, Kubernetes, Spark, Data Visualization",Associate,2,Gaming,2025-01-20,2025-02-19,830,9.8,Machine Intelligence Group -AI14435,AI Software Engineer,206076,USD,206076,EX,FL,United States,L,United States,0,"GCP, Scala, R",Master,14,Transportation,2025-01-22,2025-02-27,1893,5.4,Predictive Systems -AI14436,Computer Vision Engineer,76678,CAD,95848,MI,FT,Canada,S,Canada,100,"Linux, Deep Learning, Docker, TensorFlow",PhD,4,Media,2024-05-27,2024-07-02,1571,6.1,Autonomous Tech -AI14437,AI Specialist,108696,USD,108696,EX,CT,China,L,China,50,"SQL, Python, Git, Tableau",Associate,13,Education,2024-04-14,2024-05-10,1504,9.3,DataVision Ltd -AI14438,NLP Engineer,124557,CAD,155696,SE,FT,Canada,S,Canada,100,"Scala, PyTorch, SQL, Data Visualization",Associate,9,Technology,2024-10-08,2024-10-26,2225,9.7,Cloud AI Solutions -AI14439,Research Scientist,95689,EUR,81336,MI,PT,Germany,S,South Africa,0,"GCP, Azure, PyTorch, TensorFlow, AWS",Bachelor,4,Transportation,2024-05-16,2024-07-15,1331,7.1,Autonomous Tech -AI14440,AI Specialist,295651,SGD,384346,EX,FT,Singapore,L,Vietnam,0,"Python, GCP, Tableau, TensorFlow, Spark",PhD,15,Telecommunications,2024-10-10,2024-11-30,1805,6.3,DataVision Ltd -AI14441,AI Software Engineer,219218,CAD,274023,EX,PT,Canada,L,Canada,100,"Data Visualization, Scala, Mathematics, Java, AWS",Associate,10,Energy,2025-03-13,2025-04-26,2212,5.1,Predictive Systems -AI14442,Machine Learning Engineer,125323,CAD,156654,SE,CT,Canada,M,Canada,50,"PyTorch, TensorFlow, Scala, AWS, Java",Master,5,Telecommunications,2025-01-23,2025-03-22,1414,6,Smart Analytics -AI14443,Data Scientist,62189,EUR,52861,EN,CT,France,L,Ghana,0,"Python, TensorFlow, Linux, Azure",PhD,0,Healthcare,2025-03-02,2025-03-20,779,9.4,Cognitive Computing -AI14444,Research Scientist,82731,USD,82731,EN,FT,United States,M,Argentina,50,"Spark, MLOps, Scala",Master,1,Finance,2025-02-14,2025-03-10,2269,9.3,Digital Transformation LLC -AI14445,Data Engineer,104548,SGD,135912,SE,CT,Singapore,S,Singapore,100,"Python, TensorFlow, Deep Learning, MLOps",Associate,9,Real Estate,2024-02-06,2024-03-11,1024,6.9,Smart Analytics -AI14446,AI Research Scientist,186864,SGD,242923,EX,CT,Singapore,S,China,0,"Python, TensorFlow, Data Visualization, R",Associate,10,Retail,2024-12-30,2025-02-12,1927,8.8,Advanced Robotics -AI14447,Computer Vision Engineer,90839,CHF,81755,EN,PT,Switzerland,M,Switzerland,50,"Java, Azure, Deep Learning, Scala",PhD,0,Real Estate,2025-03-31,2025-05-22,1877,9,Advanced Robotics -AI14448,AI Consultant,70876,USD,70876,SE,CT,China,L,China,0,"Python, GCP, Git, Deep Learning",PhD,8,Retail,2024-09-18,2024-11-18,1534,8.4,AI Innovations -AI14449,Robotics Engineer,124242,EUR,105606,EX,FT,France,S,Spain,0,"Spark, Git, Python",Associate,13,Consulting,2025-02-17,2025-03-16,919,5.2,Autonomous Tech -AI14450,Deep Learning Engineer,82268,USD,82268,MI,PT,United States,S,United States,100,"R, MLOps, Hadoop, GCP",Master,4,Retail,2025-01-16,2025-03-19,2139,6.8,Cognitive Computing -AI14451,Data Scientist,108994,EUR,92645,MI,FL,Germany,L,Germany,100,"Deep Learning, NLP, Python",Bachelor,4,Media,2024-05-24,2024-06-12,777,5.2,Algorithmic Solutions -AI14452,Principal Data Scientist,88271,USD,88271,MI,FL,Israel,M,Israel,50,"SQL, R, Linux, Docker",Associate,3,Government,2024-12-21,2025-02-05,1348,5.6,Advanced Robotics -AI14453,Deep Learning Engineer,141697,GBP,106273,SE,FL,United Kingdom,M,United Kingdom,0,"Java, AWS, MLOps, Python, Computer Vision",PhD,8,Transportation,2024-10-20,2024-12-04,1060,6,Advanced Robotics -AI14454,AI Software Engineer,77206,CAD,96508,MI,FL,Canada,M,Canada,100,"Spark, Hadoop, Kubernetes, SQL",Master,2,Transportation,2024-03-17,2024-04-28,1765,6,DataVision Ltd -AI14455,Deep Learning Engineer,63781,USD,63781,EN,FT,Ireland,M,Ireland,0,"Scala, GCP, MLOps, Computer Vision, Linux",PhD,1,Consulting,2024-09-06,2024-09-22,2327,7.3,DataVision Ltd -AI14456,Autonomous Systems Engineer,107579,GBP,80684,MI,CT,United Kingdom,L,United Kingdom,0,"Linux, NLP, Spark, Python",Associate,2,Technology,2024-11-08,2024-12-27,654,6.3,DeepTech Ventures -AI14457,AI Architect,210771,CHF,189694,SE,FT,Switzerland,M,Switzerland,50,"Scala, Hadoop, Docker, Computer Vision, Spark",PhD,8,Technology,2024-02-17,2024-04-09,1854,8,Digital Transformation LLC -AI14458,Principal Data Scientist,71437,JPY,7858070,MI,CT,Japan,S,Poland,100,"Kubernetes, Scala, Docker",PhD,4,Healthcare,2024-06-23,2024-08-29,1933,5.2,Machine Intelligence Group -AI14459,Computer Vision Engineer,57340,USD,57340,EN,CT,Sweden,S,Sweden,0,"PyTorch, Python, Mathematics",Associate,1,Manufacturing,2025-03-10,2025-04-22,2221,6.5,TechCorp Inc -AI14460,Robotics Engineer,89880,CAD,112350,MI,CT,Canada,L,Japan,0,"GCP, Hadoop, Git, Tableau, PyTorch",Master,2,Technology,2024-09-28,2024-11-06,1323,8.9,AI Innovations -AI14461,ML Ops Engineer,68307,USD,68307,MI,CT,Israel,S,Israel,100,"AWS, Python, TensorFlow, PyTorch",PhD,4,Real Estate,2025-02-06,2025-03-01,2079,7.2,Cloud AI Solutions -AI14462,Autonomous Systems Engineer,149703,CAD,187129,EX,PT,Canada,S,Canada,0,"Hadoop, Java, Linux",Associate,15,Automotive,2024-05-15,2024-07-27,2181,6.4,AI Innovations -AI14463,ML Ops Engineer,31779,USD,31779,EN,CT,India,L,India,0,"Scala, Azure, Statistics, Python",Associate,1,Automotive,2024-12-22,2025-02-13,533,9.4,TechCorp Inc -AI14464,AI Product Manager,131531,GBP,98648,MI,PT,United Kingdom,L,United Kingdom,50,"Git, Data Visualization, Hadoop",PhD,4,Education,2024-03-01,2024-04-14,1022,5.8,Smart Analytics -AI14465,AI Product Manager,200424,CAD,250530,EX,PT,Canada,M,Canada,0,"MLOps, Python, Kubernetes, TensorFlow, Java",Master,17,Transportation,2024-11-15,2024-12-29,2202,6.9,Quantum Computing Inc -AI14466,Robotics Engineer,129718,GBP,97289,MI,FL,United Kingdom,L,Ukraine,100,"Statistics, SQL, MLOps, Hadoop, Scala",PhD,3,Retail,2024-06-15,2024-07-12,1936,6.9,Cloud AI Solutions -AI14467,AI Software Engineer,84762,USD,84762,MI,FL,Finland,S,Hungary,100,"Python, Computer Vision, Java, Deep Learning",Bachelor,3,Gaming,2024-03-06,2024-05-06,1062,6.3,Digital Transformation LLC -AI14468,Data Analyst,143526,CAD,179408,SE,FL,Canada,L,Austria,100,"Java, Kubernetes, AWS, PyTorch",Master,9,Education,2024-06-19,2024-07-05,1739,8.8,Algorithmic Solutions -AI14469,AI Consultant,134652,USD,134652,EX,PT,Finland,S,Finland,50,"MLOps, AWS, Git, SQL",Associate,18,Media,2024-03-21,2024-04-10,2226,7.2,AI Innovations -AI14470,Principal Data Scientist,72770,USD,72770,EN,FL,Finland,M,Finland,50,"SQL, PyTorch, Deep Learning, GCP, Mathematics",Master,1,Telecommunications,2025-02-01,2025-03-28,2147,8.6,Cloud AI Solutions -AI14471,Data Scientist,165036,CHF,148532,SE,FT,Switzerland,S,Switzerland,50,"Azure, Git, Data Visualization, TensorFlow, Kubernetes",Associate,9,Finance,2024-03-14,2024-04-18,973,8.5,Machine Intelligence Group -AI14472,Machine Learning Researcher,277879,USD,277879,EX,PT,Denmark,L,Denmark,50,"Data Visualization, Azure, R, SQL",Bachelor,10,Energy,2024-01-25,2024-03-31,2242,7.7,Cloud AI Solutions -AI14473,AI Specialist,292246,USD,292246,EX,FL,Ireland,L,Ireland,100,"AWS, Scala, Mathematics, MLOps",PhD,16,Consulting,2024-07-01,2024-08-04,1417,8.9,Machine Intelligence Group -AI14474,AI Software Engineer,122288,EUR,103945,MI,PT,Netherlands,L,Netherlands,50,"TensorFlow, Kubernetes, Scala",PhD,4,Consulting,2024-08-16,2024-09-22,1424,7,Autonomous Tech -AI14475,AI Architect,185384,USD,185384,EX,CT,Denmark,M,Denmark,100,"Spark, Deep Learning, Python",Associate,18,Telecommunications,2024-12-22,2025-01-09,734,9.1,AI Innovations -AI14476,AI Architect,204233,EUR,173598,EX,FL,Austria,S,Austria,0,"Git, Computer Vision, Tableau",Master,14,Finance,2024-03-22,2024-04-16,1045,7.6,Cognitive Computing -AI14477,AI Consultant,57991,CAD,72489,EN,CT,Canada,L,Austria,50,"Computer Vision, Python, Data Visualization",Bachelor,1,Telecommunications,2024-02-09,2024-04-01,2183,8.7,Advanced Robotics -AI14478,Autonomous Systems Engineer,235868,USD,235868,EX,FL,Finland,L,Finland,100,"Deep Learning, Scala, SQL",PhD,11,Technology,2025-01-30,2025-02-15,1745,5.8,Cognitive Computing -AI14479,Research Scientist,150822,EUR,128199,SE,FT,Netherlands,L,Netherlands,50,"Kubernetes, Scala, MLOps, Mathematics, Statistics",Master,7,Government,2024-05-20,2024-06-18,526,8.5,Machine Intelligence Group -AI14480,Machine Learning Researcher,112953,USD,112953,EN,FL,Denmark,L,Denmark,50,"Tableau, Statistics, Spark, MLOps, Git",Bachelor,0,Manufacturing,2024-01-25,2024-02-19,876,8.4,Algorithmic Solutions -AI14481,ML Ops Engineer,201083,AUD,271462,EX,PT,Australia,S,Colombia,0,"Java, Hadoop, SQL, Git, Docker",Associate,14,Real Estate,2024-07-03,2024-08-11,1486,7.3,Future Systems -AI14482,Machine Learning Engineer,63962,CAD,79953,MI,CT,Canada,S,Canada,50,"Azure, PyTorch, SQL, Computer Vision, Mathematics",Bachelor,2,Consulting,2025-02-08,2025-04-02,1369,8.1,Cognitive Computing -AI14483,AI Consultant,124552,CHF,112097,MI,CT,Switzerland,M,Switzerland,100,"SQL, Azure, Scala, Python",PhD,4,Telecommunications,2025-01-26,2025-03-02,1392,9,Predictive Systems -AI14484,Data Analyst,65428,USD,65428,EN,FL,Israel,M,Chile,50,"SQL, Hadoop, Mathematics, Computer Vision, Deep Learning",Associate,0,Real Estate,2025-04-06,2025-06-14,1254,6.9,DeepTech Ventures -AI14485,Computer Vision Engineer,122062,CHF,109856,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, TensorFlow, Statistics, R, Deep Learning",Bachelor,2,Telecommunications,2024-05-11,2024-06-15,2116,7.8,Smart Analytics -AI14486,AI Research Scientist,111469,AUD,150483,SE,FL,Australia,S,Brazil,0,"MLOps, Git, Kubernetes, NLP",PhD,8,Media,2025-03-25,2025-05-16,581,5.9,Machine Intelligence Group -AI14487,Deep Learning Engineer,181761,USD,181761,EX,FT,South Korea,M,South Korea,50,"Tableau, Computer Vision, Kubernetes",PhD,10,Government,2025-01-17,2025-02-08,1234,9.5,Cloud AI Solutions -AI14488,Data Analyst,116229,GBP,87172,SE,PT,United Kingdom,M,Latvia,100,"Kubernetes, Docker, MLOps, Git",Bachelor,8,Finance,2025-01-03,2025-02-16,1852,9.8,DataVision Ltd -AI14489,Data Scientist,82622,USD,82622,EN,CT,Finland,L,Finland,100,"SQL, Kubernetes, Statistics, Deep Learning, PyTorch",Master,0,Gaming,2025-01-20,2025-03-16,1749,8.5,Autonomous Tech -AI14490,AI Research Scientist,96369,USD,96369,EN,FL,Norway,L,Norway,50,"MLOps, Git, Python",PhD,0,Consulting,2024-01-30,2024-03-08,1367,9.4,Cognitive Computing -AI14491,Research Scientist,53103,USD,53103,EN,CT,Israel,M,Israel,0,"Tableau, Kubernetes, Scala, R, Mathematics",Bachelor,1,Consulting,2024-04-27,2024-07-04,1971,9.2,Algorithmic Solutions -AI14492,NLP Engineer,57126,EUR,48557,EN,PT,France,S,United Kingdom,50,"Python, Spark, NLP",Master,0,Media,2024-08-11,2024-10-23,1473,7.3,Machine Intelligence Group -AI14493,Machine Learning Engineer,94857,JPY,10434270,EN,PT,Japan,L,Japan,0,"AWS, Java, Scala, Spark",Bachelor,0,Automotive,2025-03-30,2025-05-04,1942,8.4,Advanced Robotics -AI14494,Research Scientist,99850,EUR,84873,SE,PT,Austria,S,Germany,100,"NLP, Java, Tableau, GCP",Master,7,Automotive,2024-10-14,2024-12-12,1764,9.5,Autonomous Tech -AI14495,Machine Learning Researcher,26941,USD,26941,EN,FT,India,L,India,50,"Kubernetes, Docker, Data Visualization, GCP",Bachelor,1,Healthcare,2024-01-29,2024-03-18,929,5.2,Autonomous Tech -AI14496,Principal Data Scientist,37543,USD,37543,MI,FT,India,L,Romania,100,"Data Visualization, Hadoop, TensorFlow",PhD,4,Manufacturing,2025-02-09,2025-03-27,1623,9.6,Cognitive Computing -AI14497,Head of AI,145765,USD,145765,SE,PT,Israel,L,Israel,50,"Python, TensorFlow, PyTorch",Associate,9,Energy,2024-07-07,2024-08-09,1970,7.4,Machine Intelligence Group -AI14498,Data Analyst,109358,USD,109358,SE,FT,Sweden,M,Ukraine,100,"Data Visualization, SQL, Kubernetes",Associate,6,Education,2025-03-23,2025-05-26,1121,6,Quantum Computing Inc -AI14499,Computer Vision Engineer,85375,USD,85375,EX,CT,China,M,Vietnam,0,"Hadoop, Java, Azure, GCP, Scala",Associate,16,Energy,2024-02-13,2024-04-14,1288,9.6,Autonomous Tech -AI14500,AI Research Scientist,34369,USD,34369,MI,FT,China,S,China,50,"Java, Kubernetes, Hadoop, Statistics",Associate,2,Finance,2024-10-24,2024-12-15,2200,8.1,Smart Analytics -AI14501,Head of AI,101172,USD,101172,MI,FT,United States,S,United States,100,"Python, NLP, TensorFlow, GCP",PhD,3,Finance,2024-10-26,2024-12-02,1033,5.6,AI Innovations -AI14502,Robotics Engineer,100350,USD,100350,EN,FT,Denmark,L,Denmark,50,"SQL, AWS, GCP",Bachelor,0,Manufacturing,2024-12-20,2025-03-03,1176,7.2,Cloud AI Solutions -AI14503,Computer Vision Engineer,53409,SGD,69432,EN,FL,Singapore,S,Singapore,50,"Hadoop, Java, PyTorch",PhD,1,Media,2024-06-25,2024-09-03,2077,7.7,Future Systems -AI14504,Head of AI,109264,USD,109264,MI,PT,Finland,L,Czech Republic,0,"Java, Linux, AWS",Bachelor,3,Finance,2024-03-29,2024-06-06,677,6.5,Digital Transformation LLC -AI14505,Research Scientist,67190,USD,67190,EN,FL,United States,M,United States,0,"SQL, Spark, Computer Vision",Master,0,Energy,2024-06-12,2024-07-13,1965,8.4,TechCorp Inc -AI14506,AI Architect,68547,JPY,7540170,EN,FT,Japan,S,Argentina,0,"Mathematics, PyTorch, Computer Vision",PhD,0,Automotive,2025-02-05,2025-03-18,1778,5.3,Cloud AI Solutions -AI14507,Machine Learning Researcher,86075,USD,86075,MI,PT,Israel,S,Israel,50,"Hadoop, Java, Mathematics",Master,2,Gaming,2024-05-15,2024-06-18,1624,9.5,Advanced Robotics -AI14508,ML Ops Engineer,71794,USD,71794,SE,FL,China,M,China,50,"GCP, Java, Python, Git, NLP",Master,8,Telecommunications,2024-07-21,2024-08-14,1256,8.3,Quantum Computing Inc -AI14509,AI Product Manager,89033,EUR,75678,MI,CT,Netherlands,S,Netherlands,0,"Data Visualization, R, SQL, Computer Vision",Bachelor,2,Media,2024-09-30,2024-10-17,1062,5.3,Digital Transformation LLC -AI14510,Principal Data Scientist,241780,GBP,181335,EX,FT,United Kingdom,S,United Kingdom,50,"SQL, Java, GCP, PyTorch",Associate,13,Gaming,2025-03-26,2025-06-02,1804,5.4,Advanced Robotics -AI14511,Head of AI,90029,GBP,67522,MI,PT,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, TensorFlow, Kubernetes",Associate,2,Media,2024-07-29,2024-08-25,1922,8.2,Machine Intelligence Group -AI14512,NLP Engineer,125238,USD,125238,SE,FL,Israel,S,Israel,0,"Hadoop, Spark, Kubernetes",Bachelor,9,Retail,2024-07-16,2024-09-27,764,8.6,AI Innovations -AI14513,ML Ops Engineer,60541,USD,60541,MI,FL,South Korea,S,South Korea,50,"Git, Linux, NLP",Bachelor,2,Automotive,2024-08-17,2024-09-17,1236,8.7,DataVision Ltd -AI14514,AI Specialist,45630,EUR,38786,EN,FT,France,S,France,0,"TensorFlow, GCP, Linux",Associate,1,Healthcare,2024-07-04,2024-07-29,676,6.1,Smart Analytics -AI14515,AI Consultant,159534,CHF,143581,SE,FL,Switzerland,M,Switzerland,0,"Deep Learning, GCP, R",Bachelor,6,Finance,2024-11-09,2025-01-21,1441,7.5,Algorithmic Solutions -AI14516,Data Analyst,68523,USD,68523,EN,FL,Ireland,M,Ireland,0,"Kubernetes, Deep Learning, Hadoop, Statistics",Bachelor,0,Energy,2024-11-15,2025-01-23,836,6.5,TechCorp Inc -AI14517,Computer Vision Engineer,93997,EUR,79897,MI,FT,Austria,M,Austria,50,"GCP, PyTorch, Data Visualization, SQL",Master,3,Transportation,2025-01-27,2025-03-02,1646,6.8,DeepTech Ventures -AI14518,Robotics Engineer,61638,EUR,52392,MI,FL,France,S,United Kingdom,100,"Java, Mathematics, AWS, Computer Vision",PhD,3,Automotive,2025-02-07,2025-03-14,2027,6.3,DeepTech Ventures -AI14519,Data Engineer,111944,USD,111944,SE,FL,Finland,L,Finland,100,"Hadoop, Spark, Java, Linux, MLOps",Associate,9,Consulting,2024-02-19,2024-04-24,1783,9.6,DataVision Ltd -AI14520,Computer Vision Engineer,99102,JPY,10901220,SE,FL,Japan,S,Japan,100,"Hadoop, MLOps, Git, Statistics",Associate,6,Government,2024-06-26,2024-08-05,2283,9.9,Smart Analytics -AI14521,AI Product Manager,66373,USD,66373,EN,FL,Ireland,S,Ireland,0,"Python, Docker, Git",Bachelor,0,Gaming,2024-12-27,2025-02-22,2425,6.7,DataVision Ltd -AI14522,Machine Learning Engineer,286837,USD,286837,EX,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Linux, PyTorch, GCP",Bachelor,10,Government,2024-01-06,2024-03-19,737,6.3,AI Innovations -AI14523,Computer Vision Engineer,163282,EUR,138790,EX,CT,France,M,France,100,"Scala, Python, Deep Learning, TensorFlow, AWS",PhD,12,Consulting,2025-01-27,2025-02-16,1004,6.4,Machine Intelligence Group -AI14524,Machine Learning Engineer,116441,USD,116441,SE,FT,South Korea,M,South Korea,100,"TensorFlow, Azure, Data Visualization",Master,9,Manufacturing,2025-02-28,2025-03-30,1732,5.6,Future Systems -AI14525,AI Software Engineer,72672,CAD,90840,EN,FT,Canada,M,China,0,"Scala, AWS, Computer Vision",Master,1,Media,2024-09-13,2024-10-15,789,5.4,Cloud AI Solutions -AI14526,Principal Data Scientist,125105,USD,125105,SE,FT,Sweden,S,Sweden,0,"R, Kubernetes, MLOps",PhD,8,Healthcare,2024-09-01,2024-10-22,623,5.4,Future Systems -AI14527,AI Architect,160966,SGD,209256,SE,CT,Singapore,L,Singapore,50,"Data Visualization, Docker, Statistics, Azure, MLOps",Bachelor,5,Manufacturing,2024-08-09,2024-10-12,1920,7.8,Cloud AI Solutions -AI14528,NLP Engineer,87326,CAD,109158,MI,CT,Canada,S,Canada,50,"Kubernetes, TensorFlow, SQL",PhD,4,Energy,2024-05-15,2024-06-07,754,7,Smart Analytics -AI14529,AI Product Manager,135601,USD,135601,SE,PT,Ireland,M,China,50,"Linux, Python, Statistics, AWS",Master,8,Gaming,2024-03-17,2024-04-17,1413,6.1,Algorithmic Solutions -AI14530,Principal Data Scientist,217533,CHF,195780,EX,PT,Switzerland,M,Romania,0,"GCP, Docker, SQL",Master,17,Finance,2025-03-26,2025-06-01,633,8.2,Cloud AI Solutions -AI14531,Head of AI,98113,EUR,83396,MI,FL,Austria,M,France,50,"Python, Tableau, Kubernetes, Linux, Java",Associate,3,Automotive,2024-10-30,2024-11-16,2184,8.1,DeepTech Ventures -AI14532,Autonomous Systems Engineer,81244,USD,81244,EN,PT,Israel,L,Hungary,50,"Spark, PyTorch, R, AWS, MLOps",Associate,1,Gaming,2024-02-01,2024-03-22,628,6.4,Autonomous Tech -AI14533,AI Architect,89895,EUR,76411,EN,CT,Netherlands,L,Italy,100,"Scala, Statistics, Java, Azure",PhD,0,Healthcare,2024-06-24,2024-08-11,1131,8,Autonomous Tech -AI14534,Research Scientist,171139,USD,171139,EX,FL,Sweden,M,Latvia,100,"TensorFlow, Git, SQL, Java, Python",Master,15,Technology,2024-06-10,2024-07-11,1799,9.7,Neural Networks Co -AI14535,Robotics Engineer,62756,SGD,81583,EN,FL,Singapore,M,Singapore,50,"Tableau, PyTorch, MLOps, TensorFlow, Linux",Master,0,Education,2024-06-04,2024-07-10,918,7.3,Smart Analytics -AI14536,Deep Learning Engineer,335964,CHF,302368,EX,CT,Switzerland,M,Switzerland,50,"R, Hadoop, Azure, GCP",PhD,11,Consulting,2025-02-20,2025-05-03,707,7.6,DataVision Ltd -AI14537,Data Scientist,106920,EUR,90882,MI,FT,Germany,M,United Kingdom,50,"Linux, AWS, Mathematics",Master,3,Healthcare,2024-09-17,2024-11-29,2132,7.3,Digital Transformation LLC -AI14538,Deep Learning Engineer,119575,EUR,101639,MI,CT,Austria,L,Austria,100,"Kubernetes, Java, Python, NLP, Spark",Bachelor,4,Energy,2024-12-04,2024-12-24,2163,6.1,AI Innovations -AI14539,Computer Vision Engineer,84559,USD,84559,EX,FT,China,M,China,50,"TensorFlow, SQL, Mathematics",PhD,10,Gaming,2025-04-15,2025-05-18,1877,8.6,Predictive Systems -AI14540,Head of AI,101252,USD,101252,MI,FL,Norway,M,Norway,100,"NLP, SQL, R, Docker",Associate,2,Media,2024-01-05,2024-03-01,1702,9.2,Digital Transformation LLC -AI14541,Deep Learning Engineer,236723,CHF,213051,EX,FL,Switzerland,L,Switzerland,0,"SQL, Scala, TensorFlow, GCP, Git",Master,17,Real Estate,2024-10-13,2024-11-13,2464,9.2,Machine Intelligence Group -AI14542,Data Analyst,244256,USD,244256,EX,FL,United States,S,United States,0,"Tableau, PyTorch, R",Bachelor,16,Finance,2024-07-03,2024-07-20,2238,5.9,Machine Intelligence Group -AI14543,Machine Learning Engineer,158103,EUR,134388,EX,FT,Germany,M,Denmark,50,"Hadoop, SQL, Java, GCP, PyTorch",PhD,11,Transportation,2025-01-30,2025-02-26,955,5.6,AI Innovations -AI14544,Head of AI,130549,EUR,110967,SE,CT,Germany,S,Germany,50,"R, GCP, Scala",Bachelor,5,Manufacturing,2025-03-06,2025-04-19,2156,7,TechCorp Inc -AI14545,AI Product Manager,175962,USD,175962,SE,FT,Denmark,M,Denmark,100,"Data Visualization, Docker, AWS, SQL, Linux",Master,7,Education,2025-03-23,2025-05-10,2102,5.9,Future Systems -AI14546,Head of AI,140334,USD,140334,EX,PT,Ireland,M,Ireland,100,"TensorFlow, Linux, Azure",PhD,13,Healthcare,2025-01-26,2025-03-27,1612,5.6,Cloud AI Solutions -AI14547,Machine Learning Engineer,83160,CHF,74844,EN,PT,Switzerland,M,Switzerland,50,"Docker, Linux, Deep Learning, TensorFlow, Git",Associate,0,Consulting,2024-12-10,2025-01-21,1282,9,Algorithmic Solutions -AI14548,Computer Vision Engineer,195354,AUD,263728,EX,CT,Australia,L,Indonesia,100,"Kubernetes, Scala, NLP, GCP, Tableau",Associate,19,Education,2025-04-21,2025-05-31,2365,9.6,AI Innovations -AI14549,AI Product Manager,62596,AUD,84505,EN,FL,Australia,L,Canada,100,"Python, Scala, Statistics",Bachelor,1,Consulting,2024-10-21,2024-12-22,1983,5.5,Algorithmic Solutions -AI14550,Machine Learning Engineer,246772,EUR,209756,EX,PT,Austria,L,Austria,100,"Deep Learning, Git, Scala, Java, Computer Vision",Associate,13,Energy,2024-10-24,2024-11-28,770,9.6,Cognitive Computing -AI14551,Data Engineer,59096,USD,59096,EN,CT,South Korea,S,South Korea,100,"Java, Hadoop, Data Visualization, Linux, Tableau",Master,1,Energy,2024-06-14,2024-08-19,2494,8,Predictive Systems -AI14552,Principal Data Scientist,144657,USD,144657,EX,FT,Sweden,S,Portugal,50,"NLP, Deep Learning, Data Visualization, Hadoop, SQL",Bachelor,12,Gaming,2024-02-12,2024-03-29,2372,9.8,AI Innovations -AI14553,Research Scientist,98312,USD,98312,EX,FT,China,L,China,100,"Scala, Python, NLP, R",Associate,17,Retail,2024-10-08,2024-11-24,574,9.4,Advanced Robotics -AI14554,Machine Learning Researcher,268721,EUR,228413,EX,CT,Germany,L,Germany,100,"Python, SQL, AWS",Master,10,Transportation,2024-12-16,2025-01-21,2163,5.8,Machine Intelligence Group -AI14555,Robotics Engineer,24804,USD,24804,EN,CT,China,S,Ukraine,50,"Python, Azure, TensorFlow, R",PhD,1,Real Estate,2024-06-09,2024-07-22,563,6.5,Cognitive Computing -AI14556,Robotics Engineer,116955,AUD,157889,SE,FT,Australia,S,Australia,100,"Python, Kubernetes, Data Visualization",Associate,8,Automotive,2025-03-15,2025-05-19,1300,9.5,Digital Transformation LLC -AI14557,Computer Vision Engineer,102088,EUR,86775,MI,CT,France,L,France,100,"Azure, GCP, SQL, Deep Learning, PyTorch",Associate,3,Healthcare,2025-04-02,2025-06-03,1698,6.4,Advanced Robotics -AI14558,Autonomous Systems Engineer,150619,EUR,128026,SE,CT,Germany,L,Germany,50,"Scala, Python, Mathematics, Deep Learning",Associate,7,Technology,2025-02-28,2025-03-30,1410,8.2,Neural Networks Co -AI14559,AI Specialist,110839,CAD,138549,MI,PT,Canada,L,Malaysia,50,"SQL, NLP, Kubernetes, Mathematics",Bachelor,4,Gaming,2025-04-15,2025-05-02,1293,6,Cloud AI Solutions -AI14560,Computer Vision Engineer,201264,CHF,181138,EX,PT,Switzerland,M,Germany,0,"GCP, Scala, SQL, Computer Vision",Master,15,Manufacturing,2024-11-01,2024-12-17,2398,9.8,Cloud AI Solutions -AI14561,Autonomous Systems Engineer,87432,USD,87432,EN,PT,United States,M,United States,100,"TensorFlow, GCP, MLOps",Master,0,Transportation,2024-09-30,2024-12-02,1262,5.5,Future Systems -AI14562,AI Software Engineer,63493,EUR,53969,EN,PT,Netherlands,L,Netherlands,50,"NLP, SQL, Linux",Associate,0,Real Estate,2024-10-14,2024-12-24,2168,9.5,Digital Transformation LLC -AI14563,Research Scientist,184467,JPY,20291370,EX,FL,Japan,L,Japan,50,"Mathematics, Kubernetes, Azure, Deep Learning",PhD,18,Government,2024-05-23,2024-06-11,872,5.7,Advanced Robotics -AI14564,AI Research Scientist,209096,EUR,177732,EX,FT,Germany,M,Germany,100,"Kubernetes, Azure, Spark, GCP, Java",PhD,19,Real Estate,2024-02-29,2024-04-25,1107,8.6,Algorithmic Solutions -AI14565,Research Scientist,98677,SGD,128280,MI,PT,Singapore,S,Singapore,100,"NLP, AWS, Kubernetes, SQL, GCP",Associate,2,Retail,2024-02-23,2024-03-20,741,5.5,Advanced Robotics -AI14566,ML Ops Engineer,99800,CAD,124750,SE,FL,Canada,M,Canada,50,"PyTorch, Spark, TensorFlow, Kubernetes",PhD,5,Real Estate,2024-11-10,2025-01-21,1041,9.6,Digital Transformation LLC -AI14567,AI Research Scientist,109379,USD,109379,MI,CT,Finland,L,Finland,100,"Java, SQL, Linux",PhD,3,Transportation,2025-01-01,2025-03-06,1690,6.2,TechCorp Inc -AI14568,Data Analyst,68608,USD,68608,SE,CT,China,L,China,0,"Hadoop, Python, TensorFlow",Associate,5,Telecommunications,2024-08-01,2024-09-10,2444,8.5,TechCorp Inc -AI14569,Head of AI,70451,USD,70451,EX,CT,India,S,India,100,"Linux, Azure, Deep Learning, GCP",Bachelor,19,Consulting,2024-02-28,2024-03-21,985,8.7,DataVision Ltd -AI14570,NLP Engineer,127444,USD,127444,SE,FT,Norway,S,Norway,0,"Python, TensorFlow, Mathematics, AWS",Bachelor,6,Healthcare,2024-10-08,2024-11-11,1031,9.7,Neural Networks Co -AI14571,AI Research Scientist,59585,GBP,44689,EN,CT,United Kingdom,M,Spain,0,"Linux, PyTorch, Statistics, Scala",Associate,1,Transportation,2024-10-02,2024-12-05,2342,7.6,TechCorp Inc -AI14572,Principal Data Scientist,129467,GBP,97100,MI,CT,United Kingdom,L,New Zealand,50,"R, Computer Vision, Mathematics, SQL",Bachelor,2,Technology,2024-12-27,2025-02-02,983,5.9,Machine Intelligence Group -AI14573,AI Architect,89818,CHF,80836,EN,FL,Switzerland,S,Romania,50,"Git, Python, AWS, Deep Learning",PhD,1,Energy,2024-04-01,2024-06-03,1846,5.6,Algorithmic Solutions -AI14574,AI Specialist,168508,USD,168508,EX,FL,Israel,S,Kenya,50,"Hadoop, PyTorch, SQL",Associate,18,Telecommunications,2024-07-26,2024-09-09,2122,5.1,Autonomous Tech -AI14575,Machine Learning Researcher,139480,GBP,104610,SE,PT,United Kingdom,L,Colombia,100,"Azure, Scala, NLP, Mathematics, PyTorch",Master,8,Healthcare,2024-01-04,2024-02-01,2378,8.2,TechCorp Inc -AI14576,Machine Learning Researcher,192002,EUR,163202,EX,FL,Austria,L,Austria,50,"GCP, TensorFlow, Deep Learning, Data Visualization, SQL",Bachelor,18,Education,2024-07-12,2024-08-08,559,7.7,Autonomous Tech -AI14577,NLP Engineer,58121,USD,58121,MI,CT,China,L,China,0,"Mathematics, R, Tableau, SQL",PhD,2,Healthcare,2025-01-12,2025-02-15,1764,8,DeepTech Ventures -AI14578,Research Scientist,134623,EUR,114430,EX,FL,France,S,France,0,"NLP, Data Visualization, Java, R",Associate,15,Education,2025-04-08,2025-05-05,1864,9.3,TechCorp Inc -AI14579,AI Architect,97785,USD,97785,MI,CT,Norway,S,Norway,0,"Java, PyTorch, TensorFlow, Python",PhD,4,Gaming,2024-03-28,2024-05-26,807,7.5,AI Innovations -AI14580,Principal Data Scientist,219292,AUD,296044,EX,FL,Australia,L,Australia,100,"SQL, Mathematics, GCP",Master,11,Real Estate,2024-01-16,2024-03-12,974,6.3,DeepTech Ventures -AI14581,Principal Data Scientist,52713,USD,52713,MI,CT,China,L,China,100,"MLOps, Python, Spark, Scala",Bachelor,2,Telecommunications,2024-05-13,2024-07-10,1083,9.5,Autonomous Tech -AI14582,AI Architect,318665,USD,318665,EX,FT,Denmark,M,Denmark,50,"AWS, PyTorch, Deep Learning",Bachelor,13,Healthcare,2024-11-02,2024-11-19,1618,8.7,Digital Transformation LLC -AI14583,Data Analyst,150768,CHF,135691,MI,FL,Switzerland,M,Switzerland,50,"Statistics, Scala, R, Kubernetes, Python",Master,4,Telecommunications,2024-09-28,2024-11-19,1321,9.3,Predictive Systems -AI14584,Robotics Engineer,130419,USD,130419,MI,CT,Denmark,M,Denmark,50,"Spark, Scala, Deep Learning, TensorFlow, NLP",PhD,2,Manufacturing,2024-11-10,2024-12-18,1361,5.6,Autonomous Tech -AI14585,Machine Learning Researcher,134257,USD,134257,MI,FL,Denmark,L,Sweden,50,"Python, AWS, Computer Vision, Azure",Associate,2,Telecommunications,2025-03-12,2025-05-06,1297,8.8,Digital Transformation LLC -AI14586,Robotics Engineer,88859,GBP,66644,MI,PT,United Kingdom,L,Latvia,50,"Java, R, MLOps, GCP, Scala",PhD,2,Finance,2024-09-12,2024-10-09,1916,6.4,Machine Intelligence Group -AI14587,Head of AI,124958,USD,124958,SE,FT,South Korea,M,South Korea,50,"Python, Scala, AWS, TensorFlow, Java",Master,8,Telecommunications,2024-09-10,2024-10-13,2029,9.9,Smart Analytics -AI14588,Data Engineer,173410,GBP,130058,SE,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,9,Healthcare,2024-02-11,2024-03-13,2108,8.5,Neural Networks Co -AI14589,AI Specialist,119770,EUR,101805,SE,PT,France,M,France,50,"Python, Mathematics, Azure, TensorFlow",Associate,7,Automotive,2025-04-17,2025-06-29,648,7.8,DeepTech Ventures -AI14590,Data Scientist,57438,EUR,48822,EN,FT,Netherlands,M,Netherlands,50,"Kubernetes, Deep Learning, Computer Vision, GCP",Master,1,Transportation,2024-08-16,2024-10-23,717,8.2,Digital Transformation LLC -AI14591,Machine Learning Engineer,168237,CAD,210296,EX,PT,Canada,S,Canada,100,"AWS, Java, R, Data Visualization",Associate,10,Government,2024-03-14,2024-05-09,2119,9.1,DeepTech Ventures -AI14592,Principal Data Scientist,198127,USD,198127,EX,FT,Sweden,M,Ireland,100,"Linux, Git, MLOps, Tableau, Computer Vision",PhD,19,Retail,2025-04-26,2025-05-10,2065,6.7,Advanced Robotics -AI14593,AI Software Engineer,91754,USD,91754,SE,FT,South Korea,S,South Korea,0,"Computer Vision, Tableau, AWS, Data Visualization, Python",Bachelor,5,Education,2024-10-23,2024-12-28,2354,9.8,Autonomous Tech -AI14594,AI Research Scientist,59433,CAD,74291,EN,FL,Canada,L,Romania,0,"Linux, Data Visualization, Deep Learning",PhD,1,Media,2025-01-12,2025-01-30,1618,9,Quantum Computing Inc -AI14595,AI Consultant,128719,EUR,109411,SE,CT,Germany,M,Germany,100,"Scala, SQL, Linux, Azure",Master,5,Consulting,2025-03-18,2025-05-26,1435,8.1,DataVision Ltd -AI14596,NLP Engineer,225590,CHF,203031,EX,FT,Switzerland,M,Switzerland,50,"Data Visualization, Statistics, SQL, Deep Learning, Mathematics",PhD,10,Healthcare,2024-08-17,2024-10-03,832,9.9,Machine Intelligence Group -AI14597,Data Engineer,327266,USD,327266,EX,FL,Norway,M,Norway,0,"Deep Learning, Python, Java, Computer Vision, SQL",Master,19,Consulting,2024-06-19,2024-08-03,1607,9.6,Quantum Computing Inc -AI14598,Computer Vision Engineer,77377,USD,77377,MI,FL,Ireland,M,Italy,100,"TensorFlow, Scala, Mathematics",Master,3,Manufacturing,2024-09-09,2024-11-13,1176,9.6,Autonomous Tech -AI14599,Research Scientist,172505,USD,172505,SE,FL,Norway,M,Norway,0,"Linux, Azure, Deep Learning, Python",Master,5,Automotive,2025-03-18,2025-04-29,789,5.2,Advanced Robotics -AI14600,Head of AI,97488,GBP,73116,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, Java, Kubernetes, TensorFlow",Master,4,Healthcare,2024-02-23,2024-04-12,506,9.9,Future Systems -AI14601,Head of AI,71688,USD,71688,EN,CT,Ireland,M,Ireland,100,"Data Visualization, Python, SQL, TensorFlow",Master,0,Telecommunications,2024-08-13,2024-09-13,518,9,Autonomous Tech -AI14602,Machine Learning Researcher,177939,USD,177939,EX,PT,Finland,L,United Kingdom,50,"Java, Hadoop, Computer Vision",Master,15,Government,2024-07-13,2024-08-31,2444,8.5,DeepTech Ventures -AI14603,Deep Learning Engineer,176846,CHF,159161,EX,CT,Switzerland,S,Switzerland,100,"Computer Vision, Docker, Data Visualization, Linux, Statistics",PhD,16,Consulting,2024-04-01,2024-06-05,1132,8.3,DataVision Ltd -AI14604,AI Consultant,75786,EUR,64418,MI,FL,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP, Java, Scala",PhD,2,Consulting,2024-12-22,2025-02-12,517,8.1,Algorithmic Solutions -AI14605,AI Consultant,57729,USD,57729,EN,CT,Finland,L,Finland,50,"Scala, Hadoop, Git, Data Visualization",Bachelor,1,Gaming,2024-01-05,2024-02-26,1690,5.2,Cloud AI Solutions -AI14606,Head of AI,103984,USD,103984,SE,FT,South Korea,S,South Africa,50,"Tableau, Azure, SQL, Java, Spark",Associate,8,Government,2024-11-24,2024-12-08,1783,9.7,Cognitive Computing -AI14607,NLP Engineer,109857,GBP,82393,SE,FL,United Kingdom,M,United Kingdom,50,"Kubernetes, Java, NLP",Master,8,Telecommunications,2024-02-25,2024-04-07,814,6,Cloud AI Solutions -AI14608,Data Analyst,211073,USD,211073,EX,CT,Ireland,S,Ireland,0,"GCP, Git, MLOps",PhD,11,Technology,2024-10-18,2024-11-02,674,9,Quantum Computing Inc -AI14609,Data Engineer,134522,USD,134522,SE,CT,Sweden,L,Sweden,0,"AWS, Hadoop, MLOps, Python",Master,5,Education,2025-03-14,2025-04-04,1612,5.7,Predictive Systems -AI14610,AI Architect,161100,CHF,144990,SE,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, AWS, MLOps, Scala",Associate,6,Transportation,2025-01-31,2025-03-14,1781,8,DeepTech Ventures -AI14611,Autonomous Systems Engineer,122301,EUR,103956,SE,FL,Germany,M,Germany,50,"Kubernetes, Python, Computer Vision",Associate,6,Government,2024-09-07,2024-10-23,2201,5.8,Autonomous Tech -AI14612,NLP Engineer,85699,EUR,72844,MI,FT,Germany,S,Mexico,50,"Kubernetes, Java, R, Docker, Statistics",PhD,2,Healthcare,2024-06-12,2024-07-09,1286,9.8,Quantum Computing Inc -AI14613,AI Consultant,70435,CAD,88044,EN,FL,Canada,M,India,0,"Linux, PyTorch, MLOps, R",Associate,1,Consulting,2025-02-02,2025-03-08,889,8.9,DeepTech Ventures -AI14614,Machine Learning Researcher,83577,EUR,71040,MI,FT,Austria,L,Austria,0,"Scala, Tableau, Python",PhD,2,Transportation,2024-05-12,2024-07-13,880,10,Digital Transformation LLC -AI14615,Machine Learning Researcher,224546,USD,224546,EX,CT,Denmark,L,Denmark,100,"PyTorch, AWS, TensorFlow",Associate,18,Real Estate,2024-11-18,2024-12-17,1647,5.1,Advanced Robotics -AI14616,AI Consultant,164191,JPY,18061010,SE,CT,Japan,L,Japan,100,"R, Linux, SQL, PyTorch, AWS",Bachelor,7,Technology,2024-01-02,2024-03-03,1513,7.5,DataVision Ltd -AI14617,AI Architect,234520,SGD,304876,EX,CT,Singapore,S,Singapore,0,"Tableau, Hadoop, Kubernetes, SQL, NLP",Master,14,Manufacturing,2024-03-23,2024-04-26,2487,8.6,Cloud AI Solutions -AI14618,Deep Learning Engineer,50375,USD,50375,SE,CT,China,S,China,100,"Python, Docker, Linux, Mathematics, Kubernetes",Bachelor,8,Technology,2024-08-29,2024-09-29,1638,9.7,Digital Transformation LLC -AI14619,Research Scientist,60031,EUR,51026,EN,CT,France,L,Vietnam,50,"Tableau, Data Visualization, AWS, Azure",Associate,1,Finance,2025-03-17,2025-05-24,1254,9.6,Quantum Computing Inc -AI14620,Computer Vision Engineer,38594,USD,38594,MI,FL,China,M,Hungary,100,"AWS, PyTorch, MLOps, NLP, Kubernetes",PhD,4,Automotive,2025-04-19,2025-06-06,2450,8.4,DeepTech Ventures -AI14621,AI Architect,115790,EUR,98422,SE,PT,Germany,M,Germany,0,"Scala, Python, AWS",Master,5,Gaming,2024-10-12,2024-12-11,2193,7.6,Advanced Robotics -AI14622,AI Product Manager,134490,USD,134490,SE,PT,Denmark,M,Denmark,50,"Python, Mathematics, Deep Learning, Git",PhD,7,Manufacturing,2024-02-22,2024-03-21,1593,7,Future Systems -AI14623,ML Ops Engineer,80936,USD,80936,MI,CT,United States,S,United States,100,"Docker, Python, AWS",PhD,3,Gaming,2024-11-01,2024-12-27,1341,8.3,TechCorp Inc -AI14624,Computer Vision Engineer,142227,USD,142227,SE,CT,Finland,M,Finland,0,"Spark, Tableau, Linux",PhD,5,Retail,2024-04-03,2024-05-13,2195,6.1,Quantum Computing Inc -AI14625,Data Analyst,301196,USD,301196,EX,FT,Norway,M,Australia,100,"Spark, TensorFlow, Azure, Docker, Tableau",Master,11,Education,2025-04-09,2025-05-24,664,7.3,Digital Transformation LLC -AI14626,AI Specialist,42683,USD,42683,SE,FL,India,M,India,0,"Mathematics, Kubernetes, Python",PhD,5,Telecommunications,2025-03-12,2025-05-06,527,9.5,TechCorp Inc -AI14627,Data Scientist,104271,USD,104271,SE,FT,South Korea,L,Chile,50,"R, Tableau, Scala, Deep Learning",PhD,9,Automotive,2024-10-09,2024-10-28,2307,7.7,Machine Intelligence Group -AI14628,Deep Learning Engineer,53911,USD,53911,SE,FT,India,L,India,50,"Java, Scala, Statistics, Azure, Python",PhD,9,Healthcare,2024-02-10,2024-04-15,1406,6.8,Advanced Robotics -AI14629,Data Scientist,119029,GBP,89272,MI,CT,United Kingdom,L,United Kingdom,50,"Java, PyTorch, Tableau, Deep Learning",Bachelor,3,Transportation,2024-10-27,2024-11-21,1815,8,Advanced Robotics -AI14630,Data Engineer,213288,EUR,181295,EX,CT,Germany,S,Germany,50,"SQL, Docker, GCP, AWS, R",Master,10,Government,2024-02-28,2024-04-02,879,8.5,Autonomous Tech -AI14631,AI Product Manager,109524,USD,109524,MI,PT,Denmark,S,Canada,50,"SQL, Docker, Statistics, Python",Master,3,Manufacturing,2024-05-03,2024-07-06,1628,6.9,Algorithmic Solutions -AI14632,AI Product Manager,58198,USD,58198,MI,CT,China,L,China,50,"Scala, Hadoop, Computer Vision, Java, Python",PhD,4,Automotive,2024-04-13,2024-06-11,1765,6.8,Quantum Computing Inc -AI14633,AI Research Scientist,113671,USD,113671,MI,CT,United States,L,Mexico,100,"Python, PyTorch, GCP, R",Master,3,Technology,2024-06-26,2024-09-05,1239,7.3,Digital Transformation LLC -AI14634,Head of AI,49824,USD,49824,SE,CT,India,M,India,0,"TensorFlow, GCP, SQL, Scala",Bachelor,6,Government,2024-12-28,2025-01-28,2279,9.9,Cloud AI Solutions -AI14635,Autonomous Systems Engineer,89500,EUR,76075,EN,PT,Netherlands,L,Netherlands,100,"Docker, Scala, Tableau",PhD,0,Gaming,2024-09-30,2024-11-12,935,5.9,Smart Analytics -AI14636,AI Research Scientist,224343,USD,224343,EX,FT,South Korea,L,South Korea,0,"Mathematics, AWS, Python, Deep Learning, Azure",Master,13,Technology,2024-11-12,2024-12-16,572,7.9,AI Innovations -AI14637,AI Consultant,175920,SGD,228696,EX,FT,Singapore,M,Singapore,50,"PyTorch, Azure, Mathematics, GCP",Master,14,Retail,2024-07-05,2024-07-25,956,8.7,Digital Transformation LLC -AI14638,Data Engineer,158352,AUD,213775,SE,FL,Australia,L,Australia,50,"TensorFlow, Python, Statistics, Git, Computer Vision",PhD,8,Gaming,2025-01-21,2025-03-21,1254,9,Cognitive Computing -AI14639,NLP Engineer,99340,USD,99340,EX,FT,China,S,China,0,"Computer Vision, Mathematics, PyTorch, TensorFlow",Master,19,Healthcare,2024-09-11,2024-10-11,535,7.4,Autonomous Tech -AI14640,Research Scientist,62050,JPY,6825500,EN,CT,Japan,M,Japan,50,"MLOps, PyTorch, Data Visualization, Docker",Bachelor,0,Education,2025-04-19,2025-06-13,2134,5.1,Machine Intelligence Group -AI14641,Head of AI,73299,USD,73299,EN,CT,United States,L,Argentina,100,"Python, Docker, SQL, Statistics",Master,1,Finance,2024-05-02,2024-06-12,2290,6.4,DeepTech Ventures -AI14642,AI Research Scientist,127142,EUR,108071,SE,CT,Austria,L,Austria,50,"Kubernetes, Java, Python, AWS",Bachelor,6,Transportation,2024-08-13,2024-10-23,1104,8.6,Predictive Systems -AI14643,AI Research Scientist,103463,USD,103463,SE,CT,Israel,S,Israel,100,"R, AWS, Computer Vision",Bachelor,6,Media,2024-03-16,2024-04-23,1690,6,Cloud AI Solutions -AI14644,Research Scientist,81210,USD,81210,MI,CT,South Korea,S,South Korea,100,"Kubernetes, Linux, Data Visualization",Associate,3,Telecommunications,2024-07-10,2024-07-27,1925,9,AI Innovations -AI14645,Data Engineer,26249,USD,26249,EN,CT,India,M,India,50,"R, SQL, Computer Vision, Hadoop, PyTorch",PhD,0,Finance,2025-01-09,2025-02-05,2316,9.9,DataVision Ltd -AI14646,Research Scientist,92398,AUD,124737,MI,CT,Australia,L,Australia,0,"Kubernetes, Spark, TensorFlow",Bachelor,4,Gaming,2024-06-09,2024-06-26,1440,5.3,Cognitive Computing -AI14647,Deep Learning Engineer,81062,GBP,60797,EN,FL,United Kingdom,L,United Kingdom,50,"Kubernetes, Azure, MLOps, Git, Statistics",Bachelor,1,Technology,2025-03-10,2025-05-05,2360,7.4,AI Innovations -AI14648,AI Software Engineer,194332,CHF,174899,SE,FT,Switzerland,L,Switzerland,50,"Python, Git, TensorFlow, SQL",Bachelor,9,Government,2024-06-15,2024-07-09,2134,9.5,TechCorp Inc -AI14649,AI Research Scientist,166789,JPY,18346790,SE,FL,Japan,L,United Kingdom,0,"Python, Scala, Statistics, GCP, Computer Vision",Bachelor,5,Telecommunications,2024-06-11,2024-07-08,989,8.4,Neural Networks Co -AI14650,AI Product Manager,271121,USD,271121,EX,FL,United States,L,United States,50,"Azure, Mathematics, NLP, Spark",Bachelor,19,Government,2024-11-10,2025-01-15,2193,9.6,DeepTech Ventures -AI14651,Principal Data Scientist,121488,EUR,103265,SE,FL,Germany,S,Germany,100,"Python, Kubernetes, Git, Deep Learning",PhD,6,Automotive,2024-07-31,2024-10-07,799,8,Smart Analytics -AI14652,Machine Learning Engineer,146495,AUD,197768,EX,CT,Australia,S,Australia,0,"GCP, Deep Learning, SQL, Kubernetes, Linux",Associate,13,Consulting,2024-12-08,2025-01-19,1963,5.9,Quantum Computing Inc -AI14653,AI Consultant,113007,USD,113007,MI,CT,Denmark,S,Estonia,100,"Python, Tableau, SQL",Bachelor,2,Media,2025-01-11,2025-03-12,1510,5.2,DataVision Ltd -AI14654,AI Research Scientist,79500,USD,79500,EN,CT,United States,L,Luxembourg,100,"SQL, Scala, Hadoop, Deep Learning",PhD,0,Government,2024-04-12,2024-05-16,1217,6.4,Autonomous Tech -AI14655,Autonomous Systems Engineer,84593,SGD,109971,MI,PT,Singapore,M,Singapore,0,"Linux, Git, SQL",Associate,2,Transportation,2024-12-03,2025-02-08,2411,7.9,TechCorp Inc -AI14656,Head of AI,87458,EUR,74339,MI,FL,France,L,France,50,"Deep Learning, Linux, NLP, Computer Vision, SQL",Master,3,Automotive,2024-06-16,2024-08-05,2258,8.2,DataVision Ltd -AI14657,AI Specialist,207998,USD,207998,EX,CT,Norway,L,Norway,100,"Kubernetes, MLOps, Python, Data Visualization, Docker",Bachelor,19,Media,2025-04-26,2025-07-01,2207,7.6,Machine Intelligence Group -AI14658,ML Ops Engineer,53800,GBP,40350,EN,FL,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, MLOps, NLP",PhD,1,Telecommunications,2024-10-05,2024-11-01,1568,9.7,Smart Analytics -AI14659,Machine Learning Researcher,56084,EUR,47671,EN,CT,Netherlands,M,Netherlands,50,"Tableau, Linux, Statistics",PhD,0,Media,2024-05-21,2024-07-31,1910,6.7,Digital Transformation LLC -AI14660,Robotics Engineer,92516,USD,92516,EN,FT,Norway,S,Norway,0,"Python, Kubernetes, MLOps, GCP, Spark",Bachelor,0,Retail,2025-02-16,2025-03-04,1766,9.7,Predictive Systems -AI14661,AI Product Manager,119724,USD,119724,EX,FL,China,M,China,0,"Docker, Python, MLOps",Associate,14,Telecommunications,2024-04-04,2024-05-04,1543,6.6,Cognitive Computing -AI14662,Machine Learning Researcher,104136,USD,104136,EX,FL,China,S,China,100,"Java, Computer Vision, NLP, R, MLOps",Bachelor,13,Manufacturing,2024-11-14,2025-01-02,647,8.6,Neural Networks Co -AI14663,Machine Learning Researcher,96383,USD,96383,MI,FT,Sweden,M,Sweden,0,"Spark, Git, Deep Learning, Computer Vision, Python",Associate,2,Media,2024-07-18,2024-09-26,543,8.5,Future Systems -AI14664,Robotics Engineer,75403,USD,75403,EN,FL,United States,L,United States,0,"Python, Data Visualization, TensorFlow, Computer Vision, Deep Learning",Bachelor,0,Transportation,2024-04-25,2024-05-26,2493,7.1,DataVision Ltd -AI14665,Machine Learning Researcher,100534,USD,100534,EN,FL,Denmark,M,Mexico,0,"Tableau, Git, Data Visualization",Master,1,Manufacturing,2024-09-15,2024-11-09,2459,7.8,Machine Intelligence Group -AI14666,Research Scientist,97918,USD,97918,MI,CT,Norway,S,Norway,0,"PyTorch, Python, Statistics, Git, Tableau",Associate,3,Government,2025-03-16,2025-04-15,1112,5.9,Machine Intelligence Group -AI14667,Principal Data Scientist,46643,USD,46643,EN,FL,Finland,S,Finland,50,"Data Visualization, Kubernetes, Python, Spark, NLP",Bachelor,1,Manufacturing,2024-08-22,2024-10-02,1297,9.3,DeepTech Ventures -AI14668,AI Product Manager,161683,EUR,137431,EX,FT,Germany,L,Germany,50,"Hadoop, SQL, Python, TensorFlow, MLOps",PhD,19,Energy,2024-04-30,2024-06-28,819,9.5,Cognitive Computing -AI14669,Data Scientist,78579,USD,78579,MI,CT,Israel,S,Israel,0,"Java, Data Visualization, MLOps, R, AWS",Associate,2,Telecommunications,2024-02-15,2024-04-20,1410,8.9,Predictive Systems -AI14670,AI Architect,98927,EUR,84088,MI,FT,Netherlands,S,Netherlands,0,"Tableau, GCP, Azure, Hadoop, Scala",Associate,3,Government,2024-01-29,2024-03-14,1021,8.2,Future Systems -AI14671,Computer Vision Engineer,74384,JPY,8182240,EN,FL,Japan,M,Japan,50,"Data Visualization, PyTorch, Deep Learning, NLP",Associate,1,Manufacturing,2024-08-08,2024-08-31,1730,8.2,Advanced Robotics -AI14672,AI Product Manager,203594,AUD,274852,EX,FT,Australia,L,Australia,0,"Java, Data Visualization, MLOps, SQL",Master,17,Technology,2024-01-13,2024-03-17,2249,9.3,TechCorp Inc -AI14673,Head of AI,304108,SGD,395340,EX,CT,Singapore,L,Singapore,0,"Python, TensorFlow, Kubernetes, Spark, Statistics",Bachelor,11,Retail,2024-12-25,2025-03-02,2030,7.1,Cloud AI Solutions -AI14674,AI Architect,128907,CAD,161134,SE,CT,Canada,M,Canada,0,"SQL, Azure, Python",Master,8,Energy,2025-02-19,2025-03-08,1987,6.9,DeepTech Ventures -AI14675,Machine Learning Researcher,103434,EUR,87919,MI,PT,Austria,M,Austria,100,"TensorFlow, Mathematics, Linux, SQL",PhD,2,Finance,2024-04-19,2024-05-27,1328,5.4,Digital Transformation LLC -AI14676,AI Specialist,126930,USD,126930,MI,FL,Norway,S,Norway,0,"Linux, Python, Computer Vision",Bachelor,2,Media,2025-02-11,2025-04-05,1625,7.2,Machine Intelligence Group -AI14677,Research Scientist,150089,EUR,127576,EX,FL,Germany,M,Germany,100,"Python, R, Java, Git, Tableau",Bachelor,19,Transportation,2025-02-22,2025-04-15,1964,7.4,Machine Intelligence Group -AI14678,Machine Learning Engineer,84084,CAD,105105,MI,FL,Canada,M,Singapore,0,"Java, PyTorch, Kubernetes, Azure, R",PhD,4,Media,2024-06-30,2024-09-01,1516,9.8,Algorithmic Solutions -AI14679,NLP Engineer,137388,USD,137388,SE,CT,South Korea,L,South Korea,100,"Docker, PyTorch, Kubernetes",Bachelor,8,Technology,2024-07-18,2024-09-02,2379,6.2,Advanced Robotics -AI14680,AI Consultant,70308,USD,70308,MI,PT,Finland,M,Finland,100,"SQL, Scala, Git, PyTorch",PhD,4,Real Estate,2024-07-21,2024-09-02,1317,8,TechCorp Inc -AI14681,AI Product Manager,121990,SGD,158587,MI,PT,Singapore,L,Ireland,50,"SQL, Linux, TensorFlow",Master,2,Technology,2024-03-06,2024-04-16,926,9,DataVision Ltd -AI14682,ML Ops Engineer,69409,USD,69409,EN,CT,Sweden,L,Sweden,0,"AWS, Mathematics, GCP, Azure",Master,1,Consulting,2024-06-09,2024-08-19,594,5.5,Future Systems -AI14683,AI Research Scientist,89827,USD,89827,EN,CT,Denmark,M,Denmark,0,"Tableau, Java, Data Visualization, Python",Master,1,Consulting,2024-10-17,2024-11-20,1703,9.2,Smart Analytics -AI14684,Head of AI,48806,USD,48806,SE,PT,China,S,China,50,"Python, Computer Vision, Hadoop, Scala, Git",Bachelor,6,Retail,2024-10-27,2024-12-17,1758,6.4,AI Innovations -AI14685,Head of AI,94120,CAD,117650,SE,FT,Canada,S,Canada,0,"PyTorch, SQL, NLP",Associate,6,Finance,2024-11-13,2025-01-19,2290,5.4,Quantum Computing Inc -AI14686,Data Analyst,175493,USD,175493,SE,FL,United States,L,United States,100,"Kubernetes, NLP, Scala, MLOps, Spark",PhD,5,Media,2024-05-26,2024-06-28,2336,5.7,Predictive Systems -AI14687,Data Scientist,257356,EUR,218753,EX,CT,Austria,L,Austria,50,"Python, Spark, Mathematics, Git",Master,16,Energy,2024-01-20,2024-02-12,2229,8.3,TechCorp Inc -AI14688,Computer Vision Engineer,200799,CAD,250999,EX,FL,Canada,M,Canada,50,"Linux, Tableau, Docker",Bachelor,15,Healthcare,2024-06-14,2024-07-05,1406,6.5,AI Innovations -AI14689,Data Scientist,210158,EUR,178634,EX,PT,Austria,M,Czech Republic,0,"SQL, PyTorch, Mathematics",Bachelor,15,Transportation,2024-11-22,2025-01-24,1727,8.6,Smart Analytics -AI14690,Autonomous Systems Engineer,46770,USD,46770,EN,FL,Sweden,S,Switzerland,0,"AWS, Kubernetes, Tableau, GCP, Linux",Associate,0,Healthcare,2024-11-28,2025-01-25,1620,5.6,TechCorp Inc -AI14691,Data Engineer,114132,CHF,102719,MI,CT,Switzerland,M,Switzerland,50,"Java, TensorFlow, SQL, Deep Learning",Associate,4,Real Estate,2024-05-24,2024-06-30,2162,7.2,AI Innovations -AI14692,Computer Vision Engineer,71064,USD,71064,EN,FT,Ireland,S,Ireland,0,"Docker, Python, TensorFlow, R",Master,1,Automotive,2024-06-11,2024-08-15,2497,5.7,Cloud AI Solutions -AI14693,Data Scientist,181541,SGD,236003,SE,FT,Singapore,L,Singapore,50,"Tableau, Hadoop, SQL, MLOps, Git",Master,5,Finance,2024-04-19,2024-05-06,1193,8.1,Future Systems -AI14694,Research Scientist,24046,USD,24046,EN,PT,China,S,China,100,"SQL, Python, Java, GCP, Computer Vision",PhD,0,Automotive,2025-02-24,2025-04-05,2443,7.6,Neural Networks Co -AI14695,AI Specialist,107262,USD,107262,SE,CT,South Korea,M,South Korea,50,"Java, Computer Vision, Mathematics",PhD,5,Government,2024-12-02,2024-12-30,2342,9.6,Neural Networks Co -AI14696,Head of AI,120857,USD,120857,SE,FL,South Korea,L,South Korea,50,"Python, TensorFlow, Deep Learning",PhD,9,Finance,2024-06-05,2024-07-05,1291,5.6,Algorithmic Solutions -AI14697,Head of AI,71387,CAD,89234,EN,CT,Canada,M,Canada,0,"Docker, Git, Python",Master,0,Finance,2024-02-11,2024-03-29,2059,5.9,Neural Networks Co -AI14698,Data Engineer,64859,USD,64859,MI,PT,South Korea,S,South Korea,0,"MLOps, Git, Python",PhD,4,Energy,2025-04-24,2025-06-14,2136,5.9,Neural Networks Co -AI14699,AI Consultant,69368,JPY,7630480,EN,FT,Japan,M,Japan,0,"Kubernetes, Computer Vision, Git",PhD,0,Consulting,2024-03-16,2024-04-22,550,8,Advanced Robotics -AI14700,AI Product Manager,57640,EUR,48994,EN,PT,Netherlands,M,Netherlands,50,"Java, Linux, Spark, Azure",Bachelor,0,Real Estate,2024-07-20,2024-08-11,2226,8,Cloud AI Solutions -AI14701,Research Scientist,100171,CAD,125214,SE,FT,Canada,S,Canada,0,"Git, MLOps, Linux, Data Visualization, Azure",Bachelor,5,Transportation,2024-02-08,2024-03-07,1994,5,Advanced Robotics -AI14702,Deep Learning Engineer,66219,SGD,86085,EN,CT,Singapore,S,Singapore,100,"GCP, Data Visualization, Azure, AWS",PhD,0,Retail,2024-12-23,2025-02-25,1170,6.5,Cognitive Computing -AI14703,Deep Learning Engineer,133384,EUR,113376,EX,PT,Austria,S,Austria,0,"Python, TensorFlow, Tableau",Master,11,Real Estate,2024-01-07,2024-03-03,1888,8.8,TechCorp Inc -AI14704,Machine Learning Researcher,133208,EUR,113227,SE,FL,Netherlands,L,Japan,100,"Git, Data Visualization, SQL",Bachelor,8,Media,2024-06-06,2024-08-17,640,7.6,Advanced Robotics -AI14705,AI Consultant,179309,USD,179309,EX,FT,Ireland,S,Ireland,0,"Data Visualization, R, Linux",Associate,15,Telecommunications,2024-01-18,2024-02-18,1899,8,DeepTech Ventures -AI14706,Principal Data Scientist,85394,JPY,9393340,MI,FL,Japan,S,Japan,0,"Azure, Scala, Deep Learning, GCP, AWS",PhD,4,Transportation,2024-09-29,2024-11-01,557,7.1,Digital Transformation LLC -AI14707,NLP Engineer,150883,AUD,203692,SE,FT,Australia,L,Australia,0,"Hadoop, Git, Spark, SQL, Python",PhD,5,Education,2024-12-26,2025-01-16,2237,7.9,Autonomous Tech -AI14708,Research Scientist,140306,JPY,15433660,EX,FL,Japan,S,Turkey,100,"Kubernetes, PyTorch, Data Visualization, Hadoop, Docker",Master,15,Finance,2025-03-04,2025-04-07,2469,8.7,Quantum Computing Inc -AI14709,ML Ops Engineer,132345,USD,132345,MI,CT,Norway,L,Switzerland,100,"MLOps, PyTorch, Data Visualization, Scala",Associate,3,Retail,2025-01-29,2025-03-14,1930,7.7,DataVision Ltd -AI14710,AI Specialist,81632,EUR,69387,EN,CT,Germany,L,Netherlands,0,"Scala, Python, NLP, Tableau, Git",PhD,0,Healthcare,2024-04-09,2024-04-26,1361,7.6,Future Systems -AI14711,Robotics Engineer,145334,SGD,188934,SE,FT,Singapore,M,Singapore,0,"NLP, Java, Python, Statistics, Deep Learning",PhD,9,Energy,2025-03-28,2025-05-21,2432,8.3,AI Innovations -AI14712,AI Product Manager,103134,CHF,92821,EN,CT,Switzerland,M,Switzerland,100,"Spark, R, GCP, TensorFlow, PyTorch",Master,0,Media,2024-09-14,2024-11-23,679,6.6,Digital Transformation LLC -AI14713,Machine Learning Engineer,73844,USD,73844,EN,PT,Denmark,M,Denmark,50,"SQL, Statistics, MLOps, Mathematics",Associate,0,Transportation,2024-04-03,2024-05-20,1162,7,DataVision Ltd -AI14714,NLP Engineer,53224,USD,53224,EN,PT,Israel,S,Israel,50,"Python, Mathematics, Kubernetes",Associate,0,Telecommunications,2024-11-29,2025-01-30,1152,7.7,TechCorp Inc -AI14715,NLP Engineer,96148,USD,96148,EN,FL,Norway,L,Norway,50,"SQL, GCP, Kubernetes, PyTorch",Associate,0,Transportation,2025-02-18,2025-05-02,1244,9.6,Advanced Robotics -AI14716,AI Research Scientist,61479,USD,61479,MI,FL,South Korea,M,South Korea,50,"Docker, Hadoop, TensorFlow, Spark",Master,3,Finance,2024-06-19,2024-07-15,1985,6,Predictive Systems -AI14717,AI Product Manager,89485,CHF,80537,EN,FL,Switzerland,L,Switzerland,50,"Scala, GCP, Statistics, Python",Master,1,Automotive,2025-03-13,2025-05-08,660,5.9,TechCorp Inc -AI14718,AI Specialist,119054,AUD,160723,MI,FT,Australia,L,Australia,100,"Git, Python, R",PhD,2,Manufacturing,2024-10-02,2024-11-15,1819,8.1,Neural Networks Co -AI14719,Data Scientist,39720,USD,39720,SE,FT,India,S,India,0,"R, Kubernetes, Python",Bachelor,9,Automotive,2024-01-14,2024-03-07,580,7.3,DeepTech Ventures -AI14720,Deep Learning Engineer,148540,GBP,111405,SE,FT,United Kingdom,L,United Kingdom,100,"Hadoop, Computer Vision, Git, Azure, Tableau",Master,5,Retail,2025-04-11,2025-05-09,643,6.5,Advanced Robotics -AI14721,AI Architect,67388,USD,67388,EN,PT,Ireland,S,Ireland,0,"MLOps, SQL, Linux, Git",Master,1,Media,2024-04-11,2024-05-19,835,5.6,Advanced Robotics -AI14722,Machine Learning Researcher,71198,USD,71198,MI,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, AWS",PhD,3,Government,2024-09-26,2024-10-28,2030,5.2,TechCorp Inc -AI14723,Computer Vision Engineer,114413,USD,114413,MI,PT,United States,L,United States,0,"MLOps, PyTorch, Kubernetes, TensorFlow, AWS",PhD,4,Real Estate,2024-07-12,2024-09-12,1436,7.9,Digital Transformation LLC -AI14724,AI Research Scientist,75404,USD,75404,EN,PT,United States,M,United States,50,"Python, Hadoop, Java, TensorFlow, Computer Vision",Associate,0,Transportation,2024-10-17,2024-11-16,2155,5.8,Quantum Computing Inc -AI14725,Data Scientist,72723,USD,72723,MI,FL,South Korea,M,South Korea,0,"Computer Vision, Python, SQL, R",Bachelor,3,Technology,2024-01-18,2024-02-13,2430,9.7,Predictive Systems -AI14726,Data Analyst,87914,USD,87914,EX,CT,China,M,China,100,"Spark, Python, Git, Docker",PhD,14,Technology,2024-08-22,2024-09-13,1342,6.6,Smart Analytics -AI14727,Machine Learning Engineer,121462,EUR,103243,SE,CT,Germany,L,Germany,0,"Kubernetes, Java, Computer Vision",Associate,7,Healthcare,2024-03-08,2024-04-08,1728,8.5,Future Systems -AI14728,AI Specialist,28481,USD,28481,EN,FL,China,S,China,50,"Scala, Spark, Git",Associate,0,Energy,2025-01-04,2025-02-12,2191,7.9,Advanced Robotics -AI14729,AI Consultant,168933,SGD,219613,EX,CT,Singapore,L,Singapore,0,"Linux, MLOps, Python, TensorFlow, NLP",Bachelor,11,Automotive,2024-05-22,2024-07-08,2084,9.9,Neural Networks Co -AI14730,AI Consultant,116189,USD,116189,MI,CT,Sweden,L,Sweden,50,"Python, GCP, Tableau, Deep Learning",PhD,3,Education,2024-05-04,2024-06-15,1686,6.9,Neural Networks Co -AI14731,Autonomous Systems Engineer,162901,USD,162901,EX,FL,Norway,S,Nigeria,0,"Scala, Kubernetes, Linux, NLP",PhD,12,Retail,2024-04-21,2024-05-14,1580,7.4,AI Innovations -AI14732,Data Scientist,312986,USD,312986,EX,CT,Norway,M,Norway,0,"Git, Docker, Deep Learning, Hadoop",Associate,17,Technology,2024-05-23,2024-07-21,2326,6.7,Autonomous Tech -AI14733,Data Engineer,118449,EUR,100682,SE,PT,France,L,France,100,"Python, TensorFlow, Azure, Computer Vision",Associate,8,Manufacturing,2024-02-27,2024-05-07,2232,6.7,DataVision Ltd -AI14734,AI Research Scientist,105386,EUR,89578,MI,PT,Germany,M,Germany,0,"Java, Mathematics, Kubernetes",Bachelor,2,Finance,2024-06-08,2024-08-14,1140,8.7,TechCorp Inc -AI14735,AI Specialist,79025,EUR,67171,MI,FL,Netherlands,S,Netherlands,50,"Python, MLOps, Git, TensorFlow",Bachelor,3,Technology,2024-02-05,2024-04-09,686,5.1,Predictive Systems -AI14736,Research Scientist,102196,USD,102196,MI,PT,Sweden,M,Russia,100,"Python, Spark, Hadoop, Statistics",Master,2,Gaming,2024-01-15,2024-03-10,1781,6.5,DeepTech Ventures -AI14737,NLP Engineer,67175,EUR,57099,EN,FL,Austria,S,Austria,50,"Deep Learning, PyTorch, Linux, Java, AWS",Bachelor,1,Retail,2024-08-25,2024-10-23,782,9.3,Machine Intelligence Group -AI14738,ML Ops Engineer,59042,AUD,79707,EN,CT,Australia,S,Australia,0,"Data Visualization, SQL, Statistics, MLOps, Spark",PhD,1,Manufacturing,2024-06-19,2024-08-02,1419,6.6,Machine Intelligence Group -AI14739,AI Consultant,245998,CHF,221398,EX,PT,Switzerland,S,Russia,100,"Python, Mathematics, Scala, GCP",Associate,15,Consulting,2024-04-12,2024-05-24,1628,9.4,Future Systems -AI14740,AI Specialist,48852,SGD,63508,EN,CT,Singapore,S,Singapore,0,"Docker, TensorFlow, Git, GCP, AWS",Master,0,Finance,2025-01-18,2025-02-25,2134,8.4,Digital Transformation LLC -AI14741,AI Software Engineer,133871,EUR,113790,SE,CT,Netherlands,S,Netherlands,100,"Python, TensorFlow, Statistics, PyTorch, Git",Master,9,Technology,2024-03-13,2024-05-22,736,5.1,Quantum Computing Inc -AI14742,Machine Learning Researcher,210751,CHF,189676,EX,FT,Switzerland,S,Switzerland,100,"SQL, GCP, Spark",Associate,16,Government,2024-09-12,2024-09-29,506,5,Cognitive Computing -AI14743,Machine Learning Researcher,178193,CHF,160374,SE,PT,Switzerland,S,South Africa,0,"Python, SQL, Azure, TensorFlow, Git",Associate,5,Consulting,2024-11-29,2025-01-11,2214,5.5,TechCorp Inc -AI14744,Robotics Engineer,119308,USD,119308,SE,FL,Sweden,M,Sweden,100,"Scala, R, Azure",Master,5,Manufacturing,2024-01-20,2024-02-26,857,7.9,Future Systems -AI14745,Robotics Engineer,153010,EUR,130059,EX,FT,Austria,L,Austria,50,"Python, SQL, Java, Docker",Master,17,Consulting,2024-07-12,2024-08-24,2272,9.5,Neural Networks Co -AI14746,Principal Data Scientist,52312,AUD,70621,EN,FL,Australia,S,Australia,50,"SQL, Kubernetes, Docker",Master,1,Transportation,2024-06-28,2024-08-29,1897,9.4,Quantum Computing Inc -AI14747,NLP Engineer,240647,AUD,324873,EX,FL,Australia,M,Sweden,0,"Docker, NLP, Linux, Python",Bachelor,17,Government,2025-03-06,2025-05-05,1227,9,Digital Transformation LLC -AI14748,Autonomous Systems Engineer,68811,EUR,58489,EN,FT,Germany,M,Germany,0,"Spark, Linux, GCP, Scala",Associate,1,Energy,2025-02-18,2025-03-05,791,9.9,Digital Transformation LLC -AI14749,Data Engineer,133800,SGD,173940,MI,FT,Singapore,L,Belgium,100,"SQL, Docker, Java, R",Bachelor,2,Manufacturing,2024-05-08,2024-06-23,944,5.6,DeepTech Ventures -AI14750,AI Research Scientist,110037,AUD,148550,MI,PT,Australia,L,Australia,50,"SQL, Kubernetes, Tableau, Hadoop",Associate,2,Telecommunications,2025-04-13,2025-05-29,1320,6,Autonomous Tech -AI14751,Machine Learning Researcher,43790,USD,43790,SE,PT,India,L,Chile,50,"R, SQL, GCP",Associate,6,Education,2024-05-16,2024-07-25,850,10,Cloud AI Solutions -AI14752,AI Specialist,101457,USD,101457,MI,CT,Ireland,M,Argentina,50,"Python, SQL, Azure",PhD,4,Education,2024-05-12,2024-06-29,2256,7.5,DataVision Ltd -AI14753,AI Specialist,82442,SGD,107175,MI,FL,Singapore,S,Singapore,100,"AWS, TensorFlow, Git",Associate,3,Transportation,2024-02-28,2024-03-16,2365,8.8,Machine Intelligence Group -AI14754,AI Product Manager,76359,USD,76359,EN,CT,Israel,L,Israel,0,"Hadoop, MLOps, Java, Computer Vision, Mathematics",PhD,0,Education,2024-01-31,2024-03-19,1856,9.6,Advanced Robotics -AI14755,AI Specialist,166212,USD,166212,SE,PT,Sweden,L,Sweden,100,"Linux, Spark, Computer Vision, Data Visualization, Python",PhD,7,Manufacturing,2024-04-24,2024-06-27,1511,7.3,Future Systems -AI14756,Head of AI,74070,EUR,62960,MI,FL,Austria,M,Austria,0,"Python, Statistics, Computer Vision",Master,4,Media,2024-01-01,2024-02-25,708,9.8,Cognitive Computing -AI14757,Machine Learning Researcher,23662,USD,23662,EN,FT,India,S,India,0,"SQL, Data Visualization, PyTorch",PhD,0,Real Estate,2024-10-02,2024-10-25,2397,7.1,Machine Intelligence Group -AI14758,Data Scientist,68764,EUR,58449,EN,FL,France,M,Estonia,0,"GCP, TensorFlow, Azure",Bachelor,1,Consulting,2024-09-09,2024-10-14,1164,7,Quantum Computing Inc -AI14759,Research Scientist,55947,USD,55947,EN,CT,Sweden,M,Sweden,100,"Mathematics, Java, PyTorch, Azure",Associate,0,Real Estate,2025-04-21,2025-05-19,806,9,Future Systems -AI14760,AI Product Manager,174977,CHF,157479,SE,PT,Switzerland,L,Switzerland,50,"Tableau, Computer Vision, Spark, Azure, SQL",Master,7,Automotive,2024-08-21,2024-10-11,1609,9.6,Predictive Systems -AI14761,Principal Data Scientist,141796,SGD,184335,SE,PT,Singapore,S,Singapore,50,"Scala, Spark, Python, TensorFlow, Computer Vision",Bachelor,8,Government,2024-04-05,2024-05-09,1338,8.1,AI Innovations -AI14762,Machine Learning Researcher,72370,USD,72370,EX,FL,China,S,China,0,"SQL, Python, Spark, Deep Learning, MLOps",Associate,11,Technology,2024-07-26,2024-08-23,1131,6.9,Autonomous Tech -AI14763,NLP Engineer,90342,EUR,76791,EN,FL,Germany,L,Argentina,50,"Kubernetes, NLP, SQL, PyTorch, R",Associate,0,Manufacturing,2024-08-19,2024-09-03,810,7.3,TechCorp Inc -AI14764,AI Software Engineer,65389,AUD,88275,EN,CT,Australia,S,Poland,0,"Java, Spark, Python, Azure, AWS",PhD,1,Energy,2024-03-02,2024-04-13,848,6.3,TechCorp Inc -AI14765,Robotics Engineer,191753,AUD,258867,EX,FT,Australia,S,Argentina,50,"R, Kubernetes, Scala, Deep Learning, Mathematics",Associate,18,Government,2024-05-06,2024-06-07,1998,5.8,Machine Intelligence Group -AI14766,Computer Vision Engineer,87202,GBP,65402,MI,FT,United Kingdom,S,United Kingdom,50,"Docker, SQL, Java, TensorFlow",Associate,4,Education,2024-04-20,2024-06-22,726,6.4,DeepTech Ventures -AI14767,Research Scientist,78313,USD,78313,MI,FL,Finland,M,Finland,50,"SQL, Data Visualization, Java",Associate,4,Education,2024-09-19,2024-11-04,1662,6.6,Neural Networks Co -AI14768,Principal Data Scientist,65799,USD,65799,EN,FT,United States,M,United States,0,"NLP, R, Kubernetes",PhD,0,Real Estate,2025-01-10,2025-03-14,1239,9.1,Advanced Robotics -AI14769,Research Scientist,29517,USD,29517,EN,CT,China,M,Mexico,50,"GCP, SQL, MLOps, NLP",Associate,0,Technology,2024-08-26,2024-11-05,2343,8.9,Digital Transformation LLC -AI14770,AI Product Manager,81826,USD,81826,EX,CT,India,L,India,0,"PyTorch, SQL, Kubernetes, Statistics",Associate,13,Transportation,2025-02-11,2025-04-07,1718,5.1,DeepTech Ventures -AI14771,Principal Data Scientist,117961,AUD,159247,MI,CT,Australia,L,Australia,100,"Data Visualization, GCP, Hadoop, MLOps",Bachelor,4,Education,2024-12-18,2025-01-01,1811,6.5,DeepTech Ventures -AI14772,AI Specialist,120810,USD,120810,EX,CT,China,L,Japan,100,"Mathematics, Python, Tableau",Bachelor,17,Automotive,2025-01-13,2025-01-27,2403,8.4,Cognitive Computing -AI14773,Data Analyst,43667,USD,43667,MI,FT,China,M,Israel,50,"Spark, Python, Docker, Git",Master,4,Education,2024-05-17,2024-06-22,1403,8.6,Predictive Systems -AI14774,Head of AI,128893,USD,128893,SE,FT,Finland,M,Finland,50,"Java, Linux, Deep Learning, Spark, Mathematics",Master,6,Transportation,2024-06-26,2024-07-13,1199,6.7,Quantum Computing Inc -AI14775,ML Ops Engineer,119069,CAD,148836,SE,FT,Canada,M,Canada,50,"PyTorch, GCP, TensorFlow",Bachelor,8,Energy,2024-07-24,2024-09-30,2205,7.6,Machine Intelligence Group -AI14776,NLP Engineer,66333,AUD,89550,EN,FL,Australia,M,Australia,100,"SQL, Kubernetes, Hadoop",Bachelor,1,Retail,2024-09-30,2024-10-21,2227,6.8,Algorithmic Solutions -AI14777,Machine Learning Researcher,89432,USD,89432,MI,FT,South Korea,L,South Korea,0,"GCP, Data Visualization, Kubernetes, Docker",Associate,2,Education,2025-02-28,2025-04-17,1204,8.6,Predictive Systems -AI14778,AI Consultant,56324,EUR,47875,EN,FL,Netherlands,S,Latvia,100,"Git, Mathematics, R",Associate,1,Retail,2024-01-18,2024-03-15,853,9.1,Machine Intelligence Group -AI14779,Research Scientist,145285,USD,145285,MI,FT,United States,L,United States,100,"R, Mathematics, Kubernetes, NLP",Associate,3,Gaming,2024-04-04,2024-05-07,1091,6.9,Future Systems -AI14780,AI Product Manager,227003,USD,227003,EX,FL,Israel,L,China,50,"SQL, AWS, GCP, Kubernetes",Associate,19,Education,2024-01-21,2024-03-23,858,5,Cloud AI Solutions -AI14781,Deep Learning Engineer,123976,EUR,105380,EX,CT,Germany,S,Germany,0,"Linux, Hadoop, Spark, Python",Bachelor,12,Education,2024-09-08,2024-11-08,742,7.2,Quantum Computing Inc -AI14782,Principal Data Scientist,63982,USD,63982,EN,PT,Sweden,S,Sweden,100,"Scala, TensorFlow, MLOps, Git, Computer Vision",Associate,1,Telecommunications,2024-07-08,2024-08-23,1255,8.9,TechCorp Inc -AI14783,Data Scientist,26617,USD,26617,EN,CT,India,M,India,0,"GCP, Kubernetes, Mathematics, NLP",Associate,0,Gaming,2025-04-21,2025-05-16,1994,8.2,Autonomous Tech -AI14784,Data Scientist,213307,CHF,191976,EX,FT,Switzerland,S,Switzerland,50,"Computer Vision, Python, TensorFlow, Linux",Bachelor,19,Education,2024-12-12,2025-02-21,2249,6.8,Cognitive Computing -AI14785,Machine Learning Engineer,68856,USD,68856,MI,CT,Finland,M,Finland,0,"GCP, Python, Spark",Associate,4,Government,2024-10-16,2024-10-31,1095,9.7,Autonomous Tech -AI14786,Head of AI,75179,USD,75179,EN,FT,United States,S,United States,0,"Kubernetes, Python, Linux, AWS, Deep Learning",PhD,0,Healthcare,2024-12-03,2025-01-22,1923,8.3,Autonomous Tech -AI14787,ML Ops Engineer,164858,AUD,222558,SE,FT,Australia,L,Australia,0,"AWS, Azure, PyTorch, Data Visualization",Bachelor,6,Gaming,2024-08-26,2024-10-31,1342,8.6,Autonomous Tech -AI14788,AI Software Engineer,70806,USD,70806,SE,FL,China,M,Germany,50,"Tableau, Spark, Scala",PhD,6,Manufacturing,2024-06-24,2024-08-16,1063,8.6,Digital Transformation LLC -AI14789,ML Ops Engineer,118788,USD,118788,SE,FT,Finland,L,Mexico,50,"Hadoop, Python, SQL",Master,7,Education,2025-04-29,2025-05-26,1420,9.1,Neural Networks Co -AI14790,AI Software Engineer,60352,AUD,81475,EN,FT,Australia,M,New Zealand,50,"Kubernetes, Java, MLOps, Azure",PhD,1,Energy,2024-01-29,2024-02-22,808,9.6,Digital Transformation LLC -AI14791,AI Software Engineer,87016,CAD,108770,MI,PT,Canada,L,South Korea,50,"Tableau, Docker, Java, GCP",Master,4,Healthcare,2024-02-16,2024-04-13,1869,6,Quantum Computing Inc -AI14792,Principal Data Scientist,192474,AUD,259840,EX,FL,Australia,M,Turkey,50,"Linux, R, Tableau",PhD,11,Finance,2024-01-21,2024-04-01,1558,7.5,Cloud AI Solutions -AI14793,Head of AI,83774,JPY,9215140,MI,FT,Japan,S,Japan,0,"NLP, TensorFlow, Scala, Docker",Associate,3,Energy,2024-10-06,2024-11-18,1800,6.6,Machine Intelligence Group -AI14794,Data Scientist,177589,CHF,159830,SE,CT,Switzerland,S,Switzerland,50,"Kubernetes, Python, TensorFlow, PyTorch, R",Associate,7,Education,2024-01-28,2024-04-03,1582,5.6,DeepTech Ventures -AI14795,Computer Vision Engineer,63063,USD,63063,EN,FT,Sweden,L,Argentina,50,"R, Hadoop, Linux, Statistics, Spark",PhD,1,Healthcare,2025-04-02,2025-04-24,557,7.9,Cognitive Computing -AI14796,AI Specialist,32842,USD,32842,MI,FT,India,L,Romania,100,"Python, Git, Data Visualization, Java, Statistics",Master,3,Telecommunications,2024-07-20,2024-08-26,2406,5.8,Cognitive Computing -AI14797,Robotics Engineer,307133,USD,307133,EX,FT,Norway,M,Norway,0,"PyTorch, Hadoop, Scala",Master,18,Manufacturing,2025-03-06,2025-05-11,1874,5.8,Neural Networks Co -AI14798,Deep Learning Engineer,260543,JPY,28659730,EX,CT,Japan,M,Latvia,100,"R, Mathematics, Deep Learning",PhD,17,Manufacturing,2025-01-16,2025-03-29,1213,5.5,Quantum Computing Inc -AI14799,AI Specialist,44958,USD,44958,SE,PT,China,S,China,0,"GCP, Azure, NLP",Associate,9,Gaming,2024-11-22,2025-01-17,684,6.2,Smart Analytics -AI14800,Head of AI,131487,AUD,177507,SE,CT,Australia,S,Australia,50,"Python, R, TensorFlow, Deep Learning",PhD,8,Real Estate,2025-04-24,2025-06-18,1130,7.6,Advanced Robotics -AI14801,AI Architect,59373,EUR,50467,EN,PT,Netherlands,M,Netherlands,100,"Python, Mathematics, TensorFlow, Kubernetes",Master,0,Consulting,2024-11-30,2025-01-05,1456,8.2,Smart Analytics -AI14802,Machine Learning Engineer,142471,USD,142471,SE,FT,Finland,M,Finland,50,"TensorFlow, Hadoop, Data Visualization, NLP",Associate,9,Technology,2024-11-18,2024-12-24,1489,6.2,Digital Transformation LLC -AI14803,AI Specialist,33282,USD,33282,MI,PT,India,L,India,50,"SQL, Azure, Kubernetes, Deep Learning",PhD,3,Energy,2024-12-21,2025-01-30,2210,6.1,Autonomous Tech -AI14804,AI Architect,70038,EUR,59532,MI,FL,Austria,M,Austria,50,"Git, PyTorch, Deep Learning",Associate,3,Finance,2024-03-12,2024-03-28,1625,8.5,Machine Intelligence Group -AI14805,Machine Learning Engineer,74946,USD,74946,EN,CT,Denmark,M,Austria,100,"SQL, Java, Azure",Bachelor,0,Government,2024-12-16,2025-02-02,2150,9.3,Algorithmic Solutions -AI14806,Data Scientist,45967,USD,45967,MI,FL,China,S,Ghana,50,"SQL, Computer Vision, AWS",PhD,3,Gaming,2024-11-19,2024-12-21,1627,7.2,Future Systems -AI14807,Principal Data Scientist,292646,SGD,380440,EX,PT,Singapore,L,Singapore,50,"GCP, Git, Azure",PhD,14,Energy,2024-04-23,2024-05-11,846,7.6,Neural Networks Co -AI14808,Data Scientist,133770,USD,133770,MI,PT,United States,L,United States,100,"Java, Mathematics, SQL, PyTorch, Docker",Bachelor,2,Retail,2024-05-19,2024-07-15,2117,7.4,Predictive Systems -AI14809,Principal Data Scientist,103086,USD,103086,MI,CT,Sweden,M,Sweden,0,"Mathematics, SQL, Tableau",Associate,3,Consulting,2024-03-10,2024-04-13,2029,5.9,Cognitive Computing -AI14810,Data Scientist,151977,USD,151977,EX,FT,Israel,S,Israel,100,"Java, PyTorch, Mathematics, Docker, Spark",Bachelor,18,Energy,2024-10-02,2024-10-24,792,7.3,Autonomous Tech -AI14811,AI Software Engineer,42791,USD,42791,MI,FL,India,L,Singapore,100,"Statistics, SQL, PyTorch, AWS",Master,2,Automotive,2024-06-29,2024-08-01,1814,6.1,Cognitive Computing -AI14812,Robotics Engineer,145130,USD,145130,EX,CT,Finland,M,Finland,50,"Java, Linux, Git, AWS",Associate,16,Transportation,2024-03-15,2024-04-30,1409,8.8,DataVision Ltd -AI14813,AI Specialist,50395,USD,50395,EN,CT,Finland,M,Thailand,0,"Git, NLP, Java, Python",PhD,1,Media,2024-12-28,2025-01-12,2037,9.8,TechCorp Inc -AI14814,Deep Learning Engineer,164649,EUR,139952,EX,FL,France,M,France,100,"Git, Python, Spark, Deep Learning",Associate,18,Energy,2025-03-20,2025-04-23,2316,9.6,Quantum Computing Inc -AI14815,Deep Learning Engineer,269435,EUR,229020,EX,PT,Netherlands,L,Netherlands,100,"Git, TensorFlow, Data Visualization",Associate,13,Real Estate,2024-10-23,2024-12-26,2295,9.9,Advanced Robotics -AI14816,Data Engineer,224881,USD,224881,SE,CT,Denmark,L,Denmark,0,"PyTorch, R, Docker, Statistics, Computer Vision",Bachelor,5,Technology,2024-05-16,2024-07-16,1110,9.6,AI Innovations -AI14817,Research Scientist,75931,JPY,8352410,EN,CT,Japan,S,Japan,50,"Azure, PyTorch, Mathematics, SQL, Python",Bachelor,1,Healthcare,2025-04-29,2025-07-02,1616,6.2,Algorithmic Solutions -AI14818,Machine Learning Researcher,138815,EUR,117993,SE,FT,Germany,M,Germany,100,"Statistics, Git, Data Visualization",Master,8,Energy,2025-04-13,2025-05-30,589,7.8,DataVision Ltd -AI14819,Head of AI,302646,CHF,272381,EX,PT,Switzerland,L,Switzerland,100,"Git, R, Hadoop",Associate,13,Finance,2024-03-08,2024-04-17,1931,7.7,Neural Networks Co -AI14820,Data Analyst,84254,AUD,113743,MI,PT,Australia,S,Australia,0,"Git, PyTorch, SQL",Bachelor,2,Education,2024-03-20,2024-05-22,1957,7,Cloud AI Solutions -AI14821,Robotics Engineer,91671,GBP,68753,MI,CT,United Kingdom,L,United Kingdom,100,"Spark, Tableau, Git, GCP",Associate,3,Retail,2024-08-29,2024-10-06,2086,5.6,AI Innovations -AI14822,NLP Engineer,140621,JPY,15468310,SE,PT,Japan,L,Japan,100,"Data Visualization, Python, Java, Statistics",Bachelor,8,Energy,2024-12-04,2025-01-11,1005,5.2,Neural Networks Co -AI14823,Robotics Engineer,93091,USD,93091,MI,PT,Israel,S,Israel,50,"Scala, AWS, Azure, Python",PhD,4,Telecommunications,2024-11-29,2024-12-20,2271,8,Cognitive Computing -AI14824,AI Architect,69964,USD,69964,MI,PT,Israel,S,Malaysia,100,"MLOps, PyTorch, Kubernetes, NLP, Mathematics",Bachelor,2,Consulting,2024-11-15,2025-01-24,2121,6.5,AI Innovations -AI14825,Deep Learning Engineer,235481,GBP,176611,EX,FL,United Kingdom,S,France,100,"Tableau, Linux, MLOps, Python",Master,14,Telecommunications,2024-02-01,2024-04-10,1339,7.5,Algorithmic Solutions -AI14826,Principal Data Scientist,104957,GBP,78718,MI,PT,United Kingdom,M,United Kingdom,0,"Computer Vision, PyTorch, SQL",PhD,3,Manufacturing,2024-06-09,2024-06-23,1178,7.2,Algorithmic Solutions -AI14827,AI Product Manager,70827,EUR,60203,EN,CT,Netherlands,L,Netherlands,0,"Scala, Hadoop, Python",Master,1,Gaming,2024-10-20,2024-12-06,1126,7.9,TechCorp Inc -AI14828,Data Engineer,125048,CAD,156310,SE,FL,Canada,M,Canada,0,"Python, Java, Docker",Master,8,Media,2025-04-26,2025-06-12,2044,7.3,DeepTech Ventures -AI14829,Research Scientist,212816,CAD,266020,EX,CT,Canada,M,Canada,50,"PyTorch, Python, Data Visualization, Kubernetes",Associate,15,Real Estate,2024-08-12,2024-09-29,658,6.7,Predictive Systems -AI14830,Head of AI,58316,USD,58316,EN,FT,Sweden,S,Germany,50,"Spark, Scala, GCP, Java, SQL",PhD,0,Gaming,2024-05-17,2024-07-18,2200,6.5,Future Systems -AI14831,NLP Engineer,100481,EUR,85409,MI,PT,Netherlands,L,Netherlands,100,"TensorFlow, Kubernetes, Spark",Associate,4,Manufacturing,2024-03-04,2024-04-20,2061,6.4,Cognitive Computing -AI14832,Head of AI,49599,USD,49599,MI,PT,China,L,China,100,"SQL, Kubernetes, GCP, Statistics, Hadoop",Master,2,Real Estate,2024-10-31,2024-12-15,708,5.8,DeepTech Ventures -AI14833,Data Analyst,79810,USD,79810,EN,PT,United States,S,Italy,50,"Python, Linux, NLP, TensorFlow, Hadoop",PhD,1,Healthcare,2025-03-24,2025-05-08,2386,6.8,DataVision Ltd -AI14834,AI Architect,57873,USD,57873,SE,FT,China,L,Luxembourg,50,"Kubernetes, Data Visualization, Java, PyTorch, NLP",Associate,9,Government,2024-07-13,2024-08-26,2487,5.4,Digital Transformation LLC -AI14835,Autonomous Systems Engineer,135214,SGD,175778,SE,CT,Singapore,S,Singapore,50,"R, SQL, Computer Vision, Java, Deep Learning",PhD,9,Education,2024-01-28,2024-03-01,2415,8.2,DataVision Ltd -AI14836,Principal Data Scientist,44068,USD,44068,EN,FL,South Korea,S,South Korea,50,"Git, Azure, Computer Vision",Associate,0,Energy,2024-05-30,2024-07-18,1291,6.8,Cloud AI Solutions -AI14837,ML Ops Engineer,218509,USD,218509,EX,CT,United States,S,Malaysia,100,"GCP, TensorFlow, Hadoop, Mathematics, SQL",PhD,19,Finance,2024-08-15,2024-09-04,2459,5.5,Autonomous Tech -AI14838,NLP Engineer,210813,CHF,189732,EX,CT,Switzerland,S,Switzerland,100,"NLP, Git, Data Visualization",Associate,10,Telecommunications,2024-03-25,2024-04-18,857,7.3,Digital Transformation LLC -AI14839,AI Architect,55157,SGD,71704,EN,FL,Singapore,S,Singapore,0,"Python, TensorFlow, Azure, Computer Vision",PhD,0,Finance,2024-06-01,2024-07-01,1582,9.5,Smart Analytics -AI14840,Deep Learning Engineer,70464,EUR,59894,EN,CT,France,M,France,0,"Mathematics, SQL, Tableau, PyTorch",Bachelor,1,Telecommunications,2025-04-27,2025-05-21,643,5.5,Smart Analytics -AI14841,Head of AI,55034,GBP,41276,EN,FL,United Kingdom,M,Sweden,100,"PyTorch, Docker, Data Visualization, Java, Spark",Bachelor,1,Government,2024-09-09,2024-10-05,1608,7,Digital Transformation LLC -AI14842,Machine Learning Engineer,278029,CHF,250226,EX,CT,Switzerland,M,Switzerland,100,"GCP, NLP, SQL, Python, Hadoop",Bachelor,10,Technology,2024-07-17,2024-08-17,1027,9,Smart Analytics -AI14843,ML Ops Engineer,100795,EUR,85676,SE,FT,Austria,S,France,100,"Python, SQL, NLP, Linux",Associate,7,Automotive,2025-04-26,2025-06-28,1660,5.5,AI Innovations -AI14844,Machine Learning Researcher,75234,USD,75234,MI,FL,South Korea,S,Malaysia,50,"Computer Vision, Python, Hadoop, AWS",PhD,3,Telecommunications,2024-05-28,2024-07-27,1864,5.6,DeepTech Ventures -AI14845,Machine Learning Researcher,149192,USD,149192,EX,FL,Sweden,S,Sweden,100,"Linux, Python, Data Visualization, TensorFlow",Master,16,Real Estate,2024-07-27,2024-09-08,646,5.8,Autonomous Tech -AI14846,AI Consultant,182753,USD,182753,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, AWS",Master,11,Real Estate,2025-02-27,2025-04-10,2315,10,DeepTech Ventures -AI14847,Principal Data Scientist,134537,EUR,114356,SE,PT,Austria,M,Austria,0,"Python, Tableau, Java, GCP, TensorFlow",Associate,7,Government,2025-04-03,2025-05-05,965,8.4,Predictive Systems -AI14848,ML Ops Engineer,97397,EUR,82787,MI,FT,Netherlands,L,Netherlands,0,"SQL, Kubernetes, Git",Associate,4,Transportation,2025-01-22,2025-03-29,549,10,AI Innovations -AI14849,AI Product Manager,37126,USD,37126,MI,PT,India,M,India,50,"R, Python, Statistics, Docker",PhD,2,Education,2024-05-30,2024-08-08,1709,8.7,Neural Networks Co -AI14850,AI Research Scientist,67086,USD,67086,MI,FT,South Korea,S,Egypt,50,"Computer Vision, Scala, NLP",Bachelor,3,Education,2024-02-27,2024-04-30,821,5.6,Future Systems -AI14851,AI Specialist,62522,USD,62522,EX,FT,India,S,Germany,100,"Spark, AWS, Scala",Associate,14,Consulting,2025-03-11,2025-04-27,1422,9.7,Future Systems -AI14852,AI Product Manager,107430,AUD,145031,SE,FT,Australia,S,Australia,0,"Git, NLP, Docker, Scala",Master,7,Healthcare,2024-09-02,2024-10-12,1641,9.6,Advanced Robotics -AI14853,AI Architect,115217,CAD,144021,SE,FT,Canada,S,Canada,0,"Kubernetes, SQL, Docker",Bachelor,7,Manufacturing,2024-10-18,2024-11-20,753,9.3,Digital Transformation LLC -AI14854,Head of AI,142120,USD,142120,SE,FT,Denmark,S,Denmark,0,"Scala, Python, AWS, TensorFlow",Associate,6,Healthcare,2024-09-29,2024-10-31,2135,5.2,Cognitive Computing -AI14855,AI Consultant,92445,CAD,115556,MI,FT,Canada,M,Canada,0,"R, TensorFlow, Scala, Git, Computer Vision",Master,4,Real Estate,2024-11-29,2025-01-06,2134,8.9,Digital Transformation LLC -AI14856,Data Scientist,41824,USD,41824,SE,CT,India,L,New Zealand,50,"MLOps, GCP, R, Azure",Associate,6,Retail,2024-05-17,2024-07-21,994,8.6,Autonomous Tech -AI14857,ML Ops Engineer,51207,CAD,64009,EN,FL,Canada,M,Canada,50,"SQL, PyTorch, Git, AWS",PhD,0,Healthcare,2025-01-10,2025-02-06,745,6.5,Cognitive Computing -AI14858,AI Software Engineer,96900,CHF,87210,MI,PT,Switzerland,S,Switzerland,100,"TensorFlow, Mathematics, Hadoop, Data Visualization",PhD,3,Consulting,2024-07-17,2024-08-28,2381,9.4,Smart Analytics -AI14859,Machine Learning Engineer,139440,EUR,118524,SE,FT,Austria,L,Portugal,50,"SQL, Deep Learning, Tableau, GCP",PhD,7,Education,2024-10-01,2024-11-07,898,8,AI Innovations -AI14860,Data Engineer,149725,USD,149725,SE,FT,Finland,L,Finland,100,"MLOps, Computer Vision, SQL, Mathematics, Data Visualization",Bachelor,5,Healthcare,2024-11-12,2025-01-01,1796,8.6,Quantum Computing Inc -AI14861,AI Software Engineer,95613,CHF,86052,EN,FL,Switzerland,S,Switzerland,100,"SQL, PyTorch, Data Visualization, Deep Learning",PhD,0,Manufacturing,2024-01-14,2024-02-05,2410,8.1,Machine Intelligence Group -AI14862,Deep Learning Engineer,84360,EUR,71706,MI,PT,Austria,M,Austria,50,"TensorFlow, Scala, Statistics",Bachelor,2,Media,2025-04-23,2025-05-31,1028,5,TechCorp Inc -AI14863,Principal Data Scientist,109354,EUR,92951,MI,CT,Austria,L,Austria,100,"Statistics, PyTorch, NLP, AWS, Linux",Master,3,Finance,2025-01-13,2025-02-17,1507,6.5,Predictive Systems -AI14864,AI Product Manager,49153,USD,49153,EN,FL,South Korea,M,South Korea,0,"TensorFlow, Deep Learning, Docker",Bachelor,0,Automotive,2024-02-26,2024-03-16,1274,6.4,Predictive Systems -AI14865,AI Specialist,79494,USD,79494,MI,FT,South Korea,M,Vietnam,100,"Kubernetes, SQL, Data Visualization, Mathematics",Bachelor,4,Government,2024-05-30,2024-08-05,1674,5.1,Future Systems -AI14866,AI Architect,99985,JPY,10998350,MI,PT,Japan,L,Japan,100,"Git, SQL, Hadoop",PhD,3,Real Estate,2024-09-14,2024-11-16,2196,8.1,Autonomous Tech -AI14867,Data Scientist,82532,JPY,9078520,EN,PT,Japan,L,Japan,50,"Hadoop, Python, Docker, Mathematics",Bachelor,0,Healthcare,2024-07-11,2024-08-09,1231,9.1,Autonomous Tech -AI14868,Autonomous Systems Engineer,295948,USD,295948,EX,FT,Norway,M,Romania,50,"SQL, Scala, Python",PhD,12,Healthcare,2024-05-01,2024-06-05,630,9.7,Quantum Computing Inc -AI14869,AI Architect,62843,USD,62843,MI,CT,Finland,S,Finland,50,"R, SQL, TensorFlow, AWS, Python",PhD,3,Manufacturing,2024-07-16,2024-07-30,2195,9.7,Predictive Systems -AI14870,Data Scientist,209564,CHF,188608,EX,FT,Switzerland,M,Switzerland,100,"TensorFlow, Git, Scala",Associate,17,Manufacturing,2024-08-23,2024-09-11,1446,5.4,Algorithmic Solutions -AI14871,NLP Engineer,152425,USD,152425,MI,FT,Denmark,L,Denmark,50,"Spark, R, SQL, Python",Bachelor,4,Manufacturing,2024-09-18,2024-11-29,911,5.9,Machine Intelligence Group -AI14872,Robotics Engineer,84147,USD,84147,MI,CT,South Korea,L,South Korea,50,"SQL, Python, Java, Git",PhD,4,Education,2024-10-08,2024-11-09,2252,8.4,Autonomous Tech -AI14873,Data Scientist,119112,USD,119112,MI,CT,Ireland,L,Ireland,100,"Scala, TensorFlow, Mathematics, Java",Associate,2,Consulting,2024-01-24,2024-03-24,945,8.6,Machine Intelligence Group -AI14874,Data Engineer,49882,USD,49882,SE,PT,China,S,China,50,"Java, PyTorch, Kubernetes",Master,8,Manufacturing,2024-06-02,2024-07-18,966,5.4,DeepTech Ventures -AI14875,Data Scientist,223969,USD,223969,EX,CT,Denmark,S,Russia,100,"SQL, Kubernetes, TensorFlow",Master,18,Real Estate,2024-08-30,2024-10-28,1774,6.1,Advanced Robotics -AI14876,Head of AI,118219,USD,118219,MI,PT,Norway,L,Norway,50,"Mathematics, Tableau, Python, Deep Learning, Kubernetes",PhD,2,Telecommunications,2024-07-14,2024-08-15,819,8.8,DataVision Ltd -AI14877,Research Scientist,53669,EUR,45619,EN,CT,Netherlands,S,Netherlands,100,"Scala, Mathematics, MLOps, Java",Master,1,Education,2025-01-28,2025-03-30,820,9.6,Machine Intelligence Group -AI14878,Research Scientist,103628,USD,103628,MI,FT,Ireland,L,Japan,50,"PyTorch, Mathematics, Spark, TensorFlow",Associate,4,Media,2024-12-27,2025-02-16,1923,5.3,Predictive Systems -AI14879,AI Specialist,56178,CAD,70223,EN,FT,Canada,S,Canada,0,"Linux, MLOps, Hadoop, PyTorch",Bachelor,0,Telecommunications,2024-05-02,2024-06-04,2267,9.5,Machine Intelligence Group -AI14880,AI Software Engineer,146442,USD,146442,SE,PT,United States,L,United States,50,"Spark, TensorFlow, Mathematics, MLOps, Data Visualization",Bachelor,9,Healthcare,2024-05-01,2024-06-12,2052,6.5,Cognitive Computing -AI14881,Computer Vision Engineer,63769,GBP,47827,EN,CT,United Kingdom,L,Norway,50,"PyTorch, Python, Data Visualization, SQL, Docker",Associate,1,Gaming,2024-01-30,2024-03-23,1175,8.2,Smart Analytics -AI14882,AI Software Engineer,24026,USD,24026,EN,FT,India,L,India,50,"Java, SQL, Hadoop, GCP",Master,0,Energy,2024-11-20,2025-01-31,1643,7.3,Cloud AI Solutions -AI14883,Deep Learning Engineer,128886,EUR,109553,SE,FL,France,S,France,0,"Kubernetes, Scala, Linux",Master,7,Healthcare,2025-02-11,2025-03-04,559,9.1,Future Systems -AI14884,Data Engineer,86675,EUR,73674,EN,CT,Netherlands,L,Ukraine,50,"Python, TensorFlow, MLOps, PyTorch, Spark",Master,0,Media,2025-03-19,2025-05-12,954,7.9,Smart Analytics -AI14885,Principal Data Scientist,112837,USD,112837,SE,FT,Finland,L,Ukraine,100,"Python, Java, Scala, AWS",Master,7,Government,2025-02-26,2025-03-25,1527,7.3,AI Innovations -AI14886,AI Specialist,79915,CAD,99894,MI,CT,Canada,L,Ireland,100,"PyTorch, Spark, Scala, SQL, TensorFlow",PhD,3,Government,2024-06-15,2024-07-24,1978,9.8,Algorithmic Solutions -AI14887,Principal Data Scientist,55583,EUR,47246,EN,CT,Germany,S,Germany,0,"SQL, Java, Statistics",Master,0,Government,2025-02-14,2025-03-04,1427,8.5,Quantum Computing Inc -AI14888,AI Consultant,102567,EUR,87182,MI,FL,France,L,France,0,"Scala, Mathematics, R, Hadoop, Computer Vision",PhD,2,Consulting,2024-01-15,2024-03-07,1168,7.6,Autonomous Tech -AI14889,Data Scientist,63765,EUR,54200,EN,FL,Austria,S,Austria,50,"Scala, Linux, NLP, Tableau",Associate,1,Healthcare,2024-11-23,2024-12-22,926,9.6,Quantum Computing Inc -AI14890,Research Scientist,109816,JPY,12079760,SE,PT,Japan,M,Japan,100,"Tableau, Python, Kubernetes, NLP",Bachelor,7,Gaming,2024-04-24,2024-06-23,2297,9.3,Predictive Systems -AI14891,Machine Learning Engineer,147705,EUR,125549,SE,FT,Austria,L,Turkey,100,"Spark, Kubernetes, Data Visualization",Associate,7,Telecommunications,2024-01-08,2024-02-19,1790,5.3,Machine Intelligence Group -AI14892,NLP Engineer,180262,USD,180262,EX,CT,South Korea,L,South Korea,100,"SQL, PyTorch, AWS, Deep Learning, TensorFlow",Master,14,Healthcare,2024-04-04,2024-05-06,984,8.7,Digital Transformation LLC -AI14893,Research Scientist,26108,USD,26108,MI,CT,India,M,Nigeria,50,"MLOps, Python, PyTorch, Java, SQL",Master,3,Retail,2024-01-12,2024-03-18,2323,7.5,TechCorp Inc -AI14894,Data Scientist,85429,AUD,115329,MI,FL,Australia,S,Portugal,50,"Computer Vision, TensorFlow, Python",Associate,2,Finance,2024-02-07,2024-03-04,1715,8.6,Digital Transformation LLC -AI14895,Data Scientist,85824,GBP,64368,EN,PT,United Kingdom,L,Sweden,0,"SQL, Spark, PyTorch, Mathematics",Associate,1,Healthcare,2024-01-15,2024-03-12,1941,7.1,Advanced Robotics -AI14896,Deep Learning Engineer,36761,USD,36761,MI,PT,China,S,China,0,"Python, Scala, Git",PhD,4,Government,2025-03-03,2025-03-22,1141,6.6,DeepTech Ventures -AI14897,Machine Learning Researcher,178346,USD,178346,SE,FL,United States,M,United States,50,"Java, NLP, MLOps",PhD,8,Technology,2025-01-22,2025-02-28,1669,10,Quantum Computing Inc -AI14898,Principal Data Scientist,210345,USD,210345,EX,FT,Denmark,L,Norway,0,"Mathematics, Hadoop, Kubernetes, Linux, Azure",PhD,19,Finance,2024-02-22,2024-05-01,1614,7,DeepTech Ventures -AI14899,AI Product Manager,219044,CAD,273805,EX,CT,Canada,L,Belgium,50,"Hadoop, R, Scala, Data Visualization",Master,18,Education,2024-01-26,2024-03-29,1456,7.7,Quantum Computing Inc -AI14900,Principal Data Scientist,64885,CAD,81106,EN,CT,Canada,L,South Africa,0,"AWS, Hadoop, R, Kubernetes",Associate,1,Retail,2024-06-10,2024-07-13,1036,8.2,Neural Networks Co -AI14901,Machine Learning Researcher,98266,JPY,10809260,EN,FT,Japan,L,Russia,0,"Linux, Statistics, Mathematics, Hadoop, PyTorch",PhD,0,Real Estate,2025-01-27,2025-04-05,1598,5.5,Advanced Robotics -AI14902,Head of AI,104995,USD,104995,SE,PT,Ireland,S,Ireland,50,"Scala, MLOps, Azure, Git, Computer Vision",PhD,6,Government,2025-04-04,2025-05-30,1420,9.8,Machine Intelligence Group -AI14903,Head of AI,150009,USD,150009,SE,PT,United States,S,United States,0,"Java, Deep Learning, TensorFlow",Associate,8,Gaming,2024-05-20,2024-07-31,1122,5.1,Autonomous Tech -AI14904,AI Architect,213345,USD,213345,SE,FL,Denmark,L,Ghana,50,"Python, Tableau, Azure, Spark, Kubernetes",Master,8,Telecommunications,2024-08-09,2024-09-30,1207,8.6,Neural Networks Co -AI14905,Machine Learning Engineer,105646,EUR,89799,MI,PT,Germany,M,Kenya,50,"Scala, Hadoop, AWS, Python, Statistics",Master,2,Consulting,2025-03-17,2025-04-19,884,8.6,Neural Networks Co -AI14906,Deep Learning Engineer,155943,EUR,132552,SE,PT,Germany,L,Germany,50,"Deep Learning, Spark, Git, Kubernetes",PhD,9,Gaming,2024-02-19,2024-03-20,1251,9.1,Future Systems -AI14907,Autonomous Systems Engineer,108937,EUR,92596,SE,FL,Germany,M,Ghana,0,"Python, TensorFlow, Kubernetes, Data Visualization, Computer Vision",Bachelor,7,Real Estate,2024-11-11,2024-11-29,2247,9.5,Predictive Systems -AI14908,Computer Vision Engineer,107249,CHF,96524,EN,PT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, SQL, Java, Scala",PhD,0,Consulting,2025-02-19,2025-04-02,2331,7.7,Neural Networks Co -AI14909,Machine Learning Engineer,92023,USD,92023,MI,FL,Ireland,S,Ireland,50,"TensorFlow, Java, SQL, R",PhD,3,Education,2025-03-06,2025-04-02,1052,5.7,DeepTech Ventures -AI14910,AI Architect,67935,USD,67935,MI,FT,Finland,S,Canada,100,"SQL, PyTorch, GCP",PhD,3,Energy,2024-01-06,2024-02-15,1292,5.1,Cognitive Computing -AI14911,AI Architect,35800,USD,35800,MI,CT,India,L,India,100,"TensorFlow, Mathematics, Azure, Scala, Java",Master,4,Technology,2024-10-26,2024-12-10,2131,9.1,DataVision Ltd -AI14912,Computer Vision Engineer,35601,USD,35601,SE,PT,India,S,India,50,"Python, MLOps, R, Statistics, Hadoop",Bachelor,6,Technology,2024-05-31,2024-07-15,729,7.6,AI Innovations -AI14913,Data Scientist,122019,EUR,103716,SE,PT,Netherlands,M,Netherlands,0,"Spark, PyTorch, GCP, Azure, Statistics",Master,7,Manufacturing,2024-05-13,2024-06-20,770,8.6,DataVision Ltd -AI14914,Data Analyst,65215,AUD,88040,EN,PT,Australia,S,Australia,50,"SQL, Scala, Computer Vision, Deep Learning",PhD,0,Manufacturing,2024-07-17,2024-08-19,1315,7.7,Future Systems -AI14915,Robotics Engineer,151010,USD,151010,SE,CT,Norway,S,Norway,50,"Hadoop, Spark, Data Visualization, SQL",Bachelor,9,Finance,2024-01-24,2024-02-22,2036,7.2,AI Innovations -AI14916,NLP Engineer,90626,USD,90626,MI,FT,Israel,L,Israel,0,"PyTorch, Docker, Deep Learning, GCP",Bachelor,4,Gaming,2024-10-06,2024-10-20,2024,7.5,Predictive Systems -AI14917,AI Research Scientist,114235,EUR,97100,MI,FT,Austria,L,Austria,100,"Hadoop, Python, NLP",Master,2,Transportation,2024-11-06,2024-12-21,1677,7.6,Advanced Robotics -AI14918,AI Consultant,99643,USD,99643,EN,FT,Norway,M,Norway,0,"TensorFlow, Kubernetes, GCP, Linux",Bachelor,0,Media,2024-08-02,2024-08-29,1430,5.1,TechCorp Inc -AI14919,Machine Learning Researcher,114099,USD,114099,SE,FT,United States,S,United States,0,"Hadoop, MLOps, SQL, Data Visualization",Bachelor,9,Automotive,2024-12-05,2025-02-11,589,5,Cloud AI Solutions -AI14920,Robotics Engineer,187262,SGD,243441,EX,FL,Singapore,M,Singapore,100,"Kubernetes, AWS, Git, Data Visualization",PhD,14,Automotive,2025-01-09,2025-03-14,1439,7.9,Advanced Robotics -AI14921,Data Scientist,41245,USD,41245,SE,FL,India,M,India,0,"GCP, Spark, Java, Data Visualization",Bachelor,8,Finance,2024-10-22,2024-12-30,2167,6.3,Algorithmic Solutions -AI14922,Autonomous Systems Engineer,60902,USD,60902,EN,FL,Denmark,S,Denmark,100,"GCP, SQL, Azure, Mathematics",PhD,1,Technology,2025-04-10,2025-05-31,1742,5.4,TechCorp Inc -AI14923,Data Engineer,57892,EUR,49208,EN,PT,France,M,France,0,"GCP, Spark, Git",Bachelor,1,Automotive,2024-11-18,2025-01-18,2050,7.4,Quantum Computing Inc -AI14924,AI Consultant,127852,CAD,159815,EX,PT,Canada,S,Ghana,100,"Azure, AWS, NLP, Computer Vision, TensorFlow",Associate,18,Transportation,2024-02-03,2024-03-01,1403,8.6,DataVision Ltd -AI14925,Data Analyst,214783,JPY,23626130,EX,CT,Japan,S,Japan,50,"R, Linux, Mathematics, MLOps, SQL",Master,12,Energy,2024-02-26,2024-04-23,2345,6.1,Predictive Systems -AI14926,Data Engineer,87394,EUR,74285,MI,PT,France,S,France,0,"Python, NLP, Deep Learning, Hadoop, Computer Vision",Associate,2,Automotive,2024-09-10,2024-11-05,1737,7.3,Autonomous Tech -AI14927,Autonomous Systems Engineer,98451,USD,98451,EN,FT,Norway,M,Norway,0,"SQL, Linux, Kubernetes, Azure, NLP",Associate,0,Real Estate,2024-10-04,2024-10-18,2299,6,Digital Transformation LLC -AI14928,NLP Engineer,74127,GBP,55595,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Hadoop, Data Visualization, NLP",Bachelor,0,Automotive,2024-12-18,2025-01-04,2454,7.4,Quantum Computing Inc -AI14929,Machine Learning Researcher,51492,USD,51492,EX,PT,India,S,India,50,"Docker, GCP, Computer Vision, Kubernetes",Bachelor,10,Media,2024-07-28,2024-10-06,2116,5.7,Advanced Robotics -AI14930,Head of AI,168869,SGD,219530,EX,PT,Singapore,S,Singapore,0,"Deep Learning, Docker, PyTorch, AWS",Associate,11,Automotive,2024-01-20,2024-02-28,956,8.3,AI Innovations -AI14931,AI Software Engineer,104543,JPY,11499730,SE,CT,Japan,S,Japan,0,"R, Azure, TensorFlow, MLOps",Master,9,Transportation,2024-09-20,2024-10-22,1456,6.1,Digital Transformation LLC -AI14932,AI Product Manager,88186,SGD,114642,MI,PT,Singapore,M,Mexico,50,"Java, Computer Vision, Linux, Data Visualization, PyTorch",Associate,4,Transportation,2024-06-11,2024-07-09,1523,9.3,Advanced Robotics -AI14933,Data Scientist,135656,USD,135656,EX,FT,Finland,S,Latvia,0,"Linux, SQL, Git, Python",PhD,12,Telecommunications,2024-08-17,2024-09-18,1864,5.9,AI Innovations -AI14934,AI Software Engineer,124876,EUR,106145,EX,FT,Germany,S,Germany,0,"Statistics, MLOps, AWS, Computer Vision, Linux",PhD,12,Government,2024-04-22,2024-06-29,540,5.8,Smart Analytics -AI14935,Data Engineer,75356,CAD,94195,EN,FT,Canada,M,Canada,100,"PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2025-04-25,2025-06-14,1057,9.3,Algorithmic Solutions -AI14936,Data Engineer,95193,EUR,80914,SE,CT,France,S,France,0,"Linux, Computer Vision, Git, Spark, TensorFlow",Associate,5,Technology,2025-03-22,2025-05-31,2416,9.1,Cloud AI Solutions -AI14937,Autonomous Systems Engineer,203347,SGD,264351,EX,PT,Singapore,L,Singapore,50,"Data Visualization, Python, Git, NLP",PhD,16,Energy,2024-08-31,2024-10-13,2016,5.3,Predictive Systems -AI14938,Machine Learning Researcher,95262,GBP,71447,MI,PT,United Kingdom,M,South Africa,100,"Kubernetes, Data Visualization, Spark",Associate,2,Retail,2024-02-01,2024-04-01,1027,8.3,Machine Intelligence Group -AI14939,Computer Vision Engineer,162617,USD,162617,MI,PT,Denmark,L,Denmark,50,"Hadoop, Kubernetes, Linux, Scala, Azure",Associate,2,Automotive,2024-12-05,2024-12-27,2086,5.3,Autonomous Tech -AI14940,AI Research Scientist,119770,GBP,89828,SE,FL,United Kingdom,S,Malaysia,100,"Java, Azure, AWS, Hadoop",Associate,9,Technology,2025-01-27,2025-04-02,2470,7.5,Autonomous Tech -AI14941,Data Scientist,220001,CAD,275001,EX,PT,Canada,L,Canada,100,"Java, Scala, MLOps, Kubernetes",Bachelor,19,Telecommunications,2024-06-15,2024-08-07,757,5.3,AI Innovations -AI14942,AI Consultant,64943,EUR,55202,EN,FL,France,S,France,100,"PyTorch, AWS, MLOps, Tableau",Master,1,Manufacturing,2024-08-11,2024-10-11,1367,8.7,Machine Intelligence Group -AI14943,Data Scientist,218883,EUR,186051,EX,FL,Netherlands,S,Netherlands,0,"Hadoop, Docker, Spark, Deep Learning",Master,10,Energy,2024-04-06,2024-05-03,1713,9.4,Autonomous Tech -AI14944,AI Research Scientist,86404,USD,86404,MI,FL,Israel,M,Switzerland,50,"Computer Vision, Docker, Python",Master,2,Manufacturing,2024-02-14,2024-03-16,2410,7.7,Quantum Computing Inc -AI14945,AI Architect,175545,SGD,228209,EX,PT,Singapore,S,Singapore,100,"Git, Statistics, Python, Mathematics, Scala",Master,13,Automotive,2024-07-30,2024-09-12,571,9.1,Autonomous Tech -AI14946,AI Product Manager,148458,USD,148458,MI,FL,Norway,L,Norway,100,"Azure, Python, Statistics",Master,4,Gaming,2024-06-10,2024-08-06,1292,6,Advanced Robotics -AI14947,Deep Learning Engineer,104899,EUR,89164,MI,CT,Austria,L,Austria,50,"Computer Vision, Python, Spark, R",Associate,2,Healthcare,2024-01-12,2024-03-25,1839,5.6,Future Systems -AI14948,Data Engineer,101094,USD,101094,SE,FL,Finland,S,Finland,0,"Spark, SQL, Linux",Master,5,Finance,2025-04-12,2025-05-06,723,6.3,Predictive Systems -AI14949,AI Product Manager,125424,USD,125424,SE,FL,Finland,M,Finland,50,"Linux, SQL, Python, Git",PhD,7,Consulting,2024-10-27,2025-01-02,2396,6.3,Advanced Robotics -AI14950,Autonomous Systems Engineer,82744,JPY,9101840,MI,PT,Japan,M,South Africa,0,"GCP, Docker, Java, SQL",PhD,4,Gaming,2024-01-23,2024-02-19,1773,7.4,Machine Intelligence Group -AI14951,Computer Vision Engineer,117343,USD,117343,MI,PT,Norway,L,Norway,100,"Docker, Computer Vision, MLOps",Associate,2,Energy,2024-04-02,2024-06-01,515,6.7,AI Innovations -AI14952,ML Ops Engineer,118354,USD,118354,MI,CT,Sweden,L,Sweden,0,"Python, TensorFlow, R",Master,2,Education,2024-11-27,2025-01-31,1583,5.6,Predictive Systems -AI14953,Autonomous Systems Engineer,124093,USD,124093,EX,CT,South Korea,S,South Korea,100,"SQL, TensorFlow, Data Visualization",Bachelor,14,Real Estate,2024-09-28,2024-11-21,1677,6.8,DeepTech Ventures -AI14954,Deep Learning Engineer,63367,SGD,82377,EN,CT,Singapore,S,Singapore,0,"Data Visualization, GCP, Mathematics, Statistics, Scala",Bachelor,0,Retail,2025-04-29,2025-06-07,2329,5.4,Future Systems -AI14955,Machine Learning Researcher,161652,USD,161652,SE,FL,Norway,M,France,50,"MLOps, Deep Learning, NLP, PyTorch",Bachelor,5,Healthcare,2024-03-02,2024-05-07,1578,8.2,Cloud AI Solutions -AI14956,AI Research Scientist,104435,USD,104435,SE,FT,South Korea,M,South Korea,50,"Python, TensorFlow, AWS, PyTorch, SQL",PhD,5,Education,2024-11-17,2025-01-21,1555,7.3,Future Systems -AI14957,Data Scientist,140824,EUR,119700,SE,CT,Netherlands,S,Australia,50,"Statistics, Mathematics, Python",Bachelor,7,Government,2025-01-24,2025-03-17,2252,5.9,Future Systems -AI14958,NLP Engineer,33429,USD,33429,MI,PT,China,S,China,0,"SQL, MLOps, Mathematics, TensorFlow, GCP",Master,4,Education,2025-04-20,2025-05-06,628,9.8,Cloud AI Solutions -AI14959,Data Engineer,56924,USD,56924,EX,FL,India,L,India,100,"Kubernetes, Scala, Mathematics, TensorFlow, Linux",Master,12,Media,2025-02-13,2025-02-27,632,8.4,Cognitive Computing -AI14960,AI Specialist,108996,USD,108996,EN,FT,Norway,L,India,50,"GCP, Spark, Python",PhD,1,Government,2024-07-04,2024-08-23,1049,6.1,Future Systems -AI14961,AI Specialist,159001,USD,159001,SE,FL,United States,M,United States,50,"Data Visualization, NLP, AWS, R",Master,9,Transportation,2024-02-25,2024-04-03,1217,7.9,AI Innovations -AI14962,Machine Learning Researcher,186143,USD,186143,EX,FL,Norway,S,Norway,50,"Linux, Spark, Data Visualization",Associate,10,Healthcare,2024-07-18,2024-08-29,1432,8.4,Machine Intelligence Group -AI14963,AI Specialist,67937,USD,67937,SE,CT,China,L,China,0,"GCP, NLP, Scala, R, Java",PhD,6,Healthcare,2024-03-11,2024-04-02,2287,7.1,Cognitive Computing -AI14964,Machine Learning Engineer,62318,USD,62318,EN,PT,South Korea,L,South Korea,0,"Linux, TensorFlow, Deep Learning, Scala",PhD,1,Energy,2024-07-06,2024-08-10,1687,8.4,TechCorp Inc -AI14965,Deep Learning Engineer,92518,USD,92518,MI,FL,Israel,M,Israel,50,"Python, Data Visualization, Linux, Azure",Bachelor,2,Gaming,2024-11-17,2024-12-04,1191,6.2,Cognitive Computing -AI14966,Research Scientist,212794,AUD,287272,EX,FL,Australia,M,Australia,50,"Tableau, Kubernetes, TensorFlow, Mathematics",Bachelor,11,Consulting,2024-12-25,2025-02-26,1380,9.5,Neural Networks Co -AI14967,Research Scientist,116954,USD,116954,EX,FL,South Korea,M,Czech Republic,0,"SQL, Python, Docker",Master,12,Finance,2024-06-11,2024-07-26,1484,7.9,Quantum Computing Inc -AI14968,AI Specialist,146064,USD,146064,SE,PT,Sweden,L,Sweden,0,"Kubernetes, SQL, Linux",Associate,8,Healthcare,2024-12-29,2025-02-06,1882,6.3,DeepTech Ventures -AI14969,Principal Data Scientist,105890,SGD,137657,MI,FL,Singapore,L,Luxembourg,100,"Python, Computer Vision, Tableau",PhD,4,Real Estate,2024-05-10,2024-06-04,2107,7.7,Neural Networks Co -AI14970,Data Analyst,62944,AUD,84974,EN,FL,Australia,S,Malaysia,100,"Docker, TensorFlow, Mathematics, AWS, SQL",Master,0,Automotive,2024-04-01,2024-06-12,1846,6.4,Machine Intelligence Group -AI14971,AI Research Scientist,142892,USD,142892,MI,FL,Denmark,L,Denmark,0,"Data Visualization, Scala, SQL, Kubernetes",Bachelor,4,Automotive,2024-09-20,2024-10-18,770,5.7,Neural Networks Co -AI14972,Data Engineer,182144,USD,182144,EX,FL,Denmark,M,Nigeria,100,"Python, NLP, TensorFlow, Docker",Associate,17,Telecommunications,2024-11-20,2025-01-24,1514,6.3,DataVision Ltd -AI14973,Computer Vision Engineer,184474,USD,184474,EX,PT,Finland,S,Finland,0,"Java, GCP, SQL, Docker, PyTorch",PhD,11,Real Estate,2024-03-31,2024-05-20,921,6.9,Cloud AI Solutions -AI14974,AI Architect,105686,USD,105686,SE,CT,South Korea,L,Japan,0,"Data Visualization, Docker, Spark",PhD,8,Technology,2024-09-07,2024-11-01,2269,6.3,Cloud AI Solutions -AI14975,Computer Vision Engineer,40256,USD,40256,EN,FL,South Korea,S,South Korea,100,"Tableau, Linux, PyTorch, GCP, Python",Master,1,Consulting,2024-11-26,2024-12-18,2172,9.6,Quantum Computing Inc -AI14976,AI Specialist,116503,USD,116503,MI,FL,Sweden,L,Sweden,0,"Kubernetes, Hadoop, GCP, Spark, Java",PhD,3,Government,2024-09-11,2024-11-05,2035,9.7,Cognitive Computing -AI14977,AI Specialist,161707,CAD,202134,EX,PT,Canada,L,Estonia,0,"MLOps, Java, Linux",Master,18,Consulting,2024-05-03,2024-06-26,1766,9,Smart Analytics -AI14978,AI Architect,176965,USD,176965,SE,FL,Denmark,M,Denmark,50,"Python, GCP, Hadoop, Statistics",Master,6,Healthcare,2024-03-20,2024-05-22,1431,5.3,Future Systems -AI14979,Data Analyst,165811,USD,165811,EX,FT,Ireland,M,Ireland,50,"Python, SQL, GCP",Associate,18,Telecommunications,2024-06-25,2024-07-21,840,6.7,TechCorp Inc -AI14980,Deep Learning Engineer,64531,JPY,7098410,EN,FT,Japan,M,United States,100,"PyTorch, TensorFlow, GCP",PhD,0,Healthcare,2024-11-30,2024-12-31,1047,9.2,Predictive Systems -AI14981,Data Scientist,102580,CHF,92322,EN,FT,Switzerland,S,Switzerland,50,"Java, AWS, Data Visualization, Statistics",Master,0,Education,2025-04-07,2025-06-04,2165,5.9,Predictive Systems -AI14982,NLP Engineer,203175,USD,203175,EX,PT,Israel,S,Israel,0,"Spark, Docker, PyTorch, Kubernetes",PhD,14,Automotive,2025-03-20,2025-05-13,1966,6,Predictive Systems -AI14983,Data Scientist,49068,USD,49068,EN,PT,Israel,M,Israel,0,"Kubernetes, GCP, Linux",PhD,0,Healthcare,2024-02-04,2024-04-08,1800,6,Algorithmic Solutions -AI14984,Research Scientist,224701,USD,224701,SE,FT,Denmark,L,Denmark,0,"PyTorch, Data Visualization, NLP, Statistics",Master,5,Gaming,2024-06-27,2024-08-24,2392,7.9,Predictive Systems -AI14985,Computer Vision Engineer,74923,USD,74923,MI,PT,Ireland,M,Ireland,100,"PyTorch, Linux, TensorFlow, GCP, Java",PhD,4,Manufacturing,2024-03-19,2024-05-19,1755,8.2,Digital Transformation LLC -AI14986,Computer Vision Engineer,87266,GBP,65450,EN,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, Computer Vision, MLOps, Azure",PhD,0,Telecommunications,2024-11-19,2024-12-24,2402,5.1,DataVision Ltd -AI14987,ML Ops Engineer,200074,EUR,170063,EX,CT,Austria,M,Austria,50,"MLOps, Kubernetes, Mathematics",Associate,18,Energy,2024-07-26,2024-08-16,2163,6.5,Cognitive Computing -AI14988,Data Analyst,108520,JPY,11937200,MI,FT,Japan,M,Japan,100,"SQL, Hadoop, Scala, Kubernetes, Mathematics",Associate,3,Education,2025-03-19,2025-05-16,914,8.3,Neural Networks Co -AI14989,Autonomous Systems Engineer,104423,SGD,135750,MI,FT,Singapore,M,Singapore,100,"Docker, Kubernetes, Azure, TensorFlow, Deep Learning",Bachelor,2,Technology,2024-07-14,2024-08-04,844,5.3,Cloud AI Solutions -AI14990,ML Ops Engineer,68334,EUR,58084,EN,FT,Germany,L,Australia,100,"Scala, SQL, Java, R",Bachelor,0,Gaming,2024-04-22,2024-06-19,1506,9.2,Smart Analytics -AI14991,AI Product Manager,58388,SGD,75904,EN,FT,Singapore,M,Singapore,50,"Deep Learning, Git, Data Visualization, Tableau",PhD,0,Real Estate,2024-11-17,2025-01-23,2186,5.5,Neural Networks Co -AI14992,AI Research Scientist,40912,USD,40912,EN,FT,South Korea,S,South Korea,100,"Mathematics, AWS, Computer Vision, Docker, Hadoop",Bachelor,0,Energy,2025-02-05,2025-02-26,2027,6.6,DeepTech Ventures -AI14993,Machine Learning Researcher,93530,EUR,79501,MI,PT,Netherlands,S,Netherlands,50,"Tableau, Docker, Java, Deep Learning",PhD,3,Telecommunications,2024-09-27,2024-10-14,1825,6.1,Future Systems -AI14994,Deep Learning Engineer,54536,CAD,68170,EN,FL,Canada,M,Canada,0,"Linux, Kubernetes, Python, TensorFlow",Bachelor,1,Government,2024-08-18,2024-10-16,1547,7.9,Advanced Robotics -AI14995,AI Research Scientist,151756,USD,151756,SE,FT,United States,M,United States,0,"Mathematics, Python, Tableau",Bachelor,7,Gaming,2025-03-19,2025-04-09,837,9.3,Cognitive Computing -AI14996,AI Product Manager,39171,USD,39171,MI,CT,China,M,China,50,"Azure, R, NLP, Docker, Computer Vision",PhD,4,Consulting,2025-01-07,2025-02-07,1107,5.2,Smart Analytics -AI14997,AI Product Manager,77555,EUR,65922,EN,CT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Mathematics, AWS, Computer Vision",PhD,0,Energy,2024-12-22,2025-02-12,1870,9.7,Autonomous Tech -AI14998,Data Engineer,28380,USD,28380,EN,FL,India,M,India,50,"Azure, Kubernetes, Spark, Statistics, MLOps",Associate,1,Government,2024-05-04,2024-05-21,1558,9,Digital Transformation LLC -AI14999,AI Specialist,58764,EUR,49949,EN,PT,France,M,France,100,"MLOps, Statistics, Data Visualization, R, Python",Master,0,Real Estate,2024-05-08,2024-06-22,546,8.4,Machine Intelligence Group -AI15000,Principal Data Scientist,58623,USD,58623,SE,FT,China,M,China,0,"AWS, Spark, Computer Vision, Data Visualization, Tableau",PhD,6,Transportation,2024-11-23,2024-12-15,1034,9.7,Quantum Computing Inc \ No newline at end of file diff --git a/first_project_data.ipynb b/first_project_data.ipynb deleted file mode 100644 index 59f36b53..00000000 --- a/first_project_data.ipynb +++ /dev/null @@ -1,666 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "b80b6ec1-6064-4376-bd7b-10b625628a3f", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "\n", - "df = pd.read_csv(\"ai_job_dataset1.csv\") # Added the missing period between pd and read_csv" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "85c9a635-fc58-4d18-981e-0b68bdeed25e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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job_idjob_titlesalary_usdsalary_currencysalary_localexperience_levelemployment_typecompany_locationcompany_sizeemployee_residenceremote_ratiorequired_skillseducation_requiredyears_experienceindustryposting_dateapplication_deadlinejob_description_lengthbenefits_scorecompany_name
0AI00001Data Scientist219728USD219728EXPTSwedenMSweden0Python, Computer Vision, R, DockerAssociate13Transportation2024-09-232024-10-3111326.6TechCorp Inc
1AI00002Head of AI230237JPY25326070EXPTJapanLJapan50Kubernetes, MLOps, Tableau, PythonBachelor10Transportation2024-07-262024-09-1222998.5Cloud AI Solutions
2AI00003Data Engineer128890EUR109557EXCTGermanySGermany100Spark, Scala, Hadoop, PyTorch, GCPBachelor12Automotive2025-01-192025-03-2813295.5Quantum Computing Inc
3AI00004Computer Vision Engineer96349USD96349MIFLFinlandLFinland50MLOps, Linux, Tableau, PythonPhD2Automotive2024-07-202024-09-0611326.8Cognitive Computing
4AI00005Robotics Engineer63065EUR53605ENFTFranceSFrance100R, Scala, SQL, GCP, PythonAssociate0Finance2025-03-162025-05-0920119.3Advanced Robotics
...............................................................
14995AI14996AI Product Manager39171USD39171MICTChinaMChina50Azure, R, NLP, Docker, Computer VisionPhD4Consulting2025-01-072025-02-0711075.2Smart Analytics
14996AI14997AI Product Manager77555EUR65922ENCTNetherlandsMNetherlands50Python, TensorFlow, Mathematics, AWS, Computer...PhD0Energy2024-12-222025-02-1218709.7Autonomous Tech
14997AI14998Data Engineer28380USD28380ENFLIndiaMIndia50Azure, Kubernetes, Spark, Statistics, MLOpsAssociate1Government2024-05-042024-05-2115589.0Digital Transformation LLC
14998AI14999AI Specialist58764EUR49949ENPTFranceMFrance100MLOps, Statistics, Data Visualization, R, PythonMaster0Real Estate2024-05-082024-06-225468.4Machine Intelligence Group
14999AI15000Principal Data Scientist58623USD58623SEFTChinaMChina0AWS, Spark, Computer Vision, Data Visualizatio...PhD6Transportation2024-11-232024-12-1510349.7Quantum Computing Inc
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salary_usdsalary_localremote_ratioyears_experiencejob_description_lengthbenefits_score
count15000.0000001.500000e+0415000.00000015000.00000015000.00000015000.000000
mean121991.9382678.292366e+0550.1966676.3656671500.8526007.499540
std63968.3618463.425325e+0640.8440845.598551574.7246471.444202
min16621.0000001.662100e+040.0000000.000000500.0000005.000000
25%74978.5000007.383075e+040.0000002.000000998.7500006.300000
50%107261.5000001.090355e+0550.0000005.0000001512.0000007.500000
75%155752.2500001.673278e+05100.00000010.0000001994.0000008.800000
max410273.0000003.368541e+07100.00000019.0000002499.00000010.000000
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" - ], - "text/plain": [ - " salary_usd salary_local remote_ratio years_experience \\\n", - "count 15000.000000 1.500000e+04 15000.000000 15000.000000 \n", - "mean 121991.938267 8.292366e+05 50.196667 6.365667 \n", - "std 63968.361846 3.425325e+06 40.844084 5.598551 \n", - "min 16621.000000 1.662100e+04 0.000000 0.000000 \n", - "25% 74978.500000 7.383075e+04 0.000000 2.000000 \n", - "50% 107261.500000 1.090355e+05 50.000000 5.000000 \n", - "75% 155752.250000 1.673278e+05 100.000000 10.000000 \n", - "max 410273.000000 3.368541e+07 100.000000 19.000000 \n", - "\n", - " job_description_length benefits_score \n", - "count 15000.000000 15000.000000 \n", - "mean 1500.852600 7.499540 \n", - "std 574.724647 1.444202 \n", - "min 500.000000 5.000000 \n", - "25% 998.750000 6.300000 \n", - "50% 1512.000000 7.500000 \n", - "75% 1994.000000 8.800000 \n", - "max 2499.000000 10.000000 " - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "625648e0-a076-4b14-ac67-aaba0e612b30", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "job_id 15000\n", - "job_title 20\n", - "salary_usd 14359\n", - "salary_currency 8\n", - "salary_local 14458\n", - "experience_level 4\n", - "employment_type 4\n", - "company_location 20\n", - "company_size 3\n", - "employee_residence 50\n", - "remote_ratio 3\n", - "required_skills 13651\n", - "education_required 4\n", - "years_experience 20\n", - "industry 15\n", - "posting_date 486\n", - "application_deadline 543\n", - "job_description_length 2000\n", - "benefits_score 51\n", - "company_name 16\n", - "dtype: int64" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.nunique() " - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "948f2f5b-4c92-42a0-8c97-fee1f38c987c", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "industry\n", - "Government 1035\n", - "Manufacturing 1035\n", - "Consulting 1021\n", - "Finance 1018\n", - "Automotive 1015\n", - "Technology 1011\n", - "Real Estate 1005\n", - "Gaming 999\n", - "Telecommunications 995\n", - "Education 992\n", - "Energy 989\n", - "Healthcare 984\n", - "Retail 978\n", - "Media 972\n", - "Transportation 951\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df.industry.value_counts() " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e86704c7-13d2-4cf2-a11d-96542a5432df", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:base] *", - "language": "python", - "name": "conda-base-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/ai_job_dataset1.csv b/notebooks/ai_job_dataset1.csv deleted file mode 100644 index 5c9e5669..00000000 --- a/notebooks/ai_job_dataset1.csv +++ /dev/null @@ -1,15001 +0,0 @@ -job_id,job_title,salary_usd,salary_currency,salary_local,experience_level,employment_type,company_location,company_size,employee_residence,remote_ratio,required_skills,education_required,years_experience,industry,posting_date,application_deadline,job_description_length,benefits_score,company_name -AI00001,Data Scientist,219728,USD,219728,EX,PT,Sweden,M,Sweden,0,"Python, Computer Vision, R, Docker",Associate,13,Transportation,2024-09-23,2024-10-31,1132,6.6,TechCorp Inc -AI00002,Head of AI,230237,JPY,25326070,EX,PT,Japan,L,Japan,50,"Kubernetes, MLOps, Tableau, Python",Bachelor,10,Transportation,2024-07-26,2024-09-12,2299,8.5,Cloud AI Solutions -AI00003,Data Engineer,128890,EUR,109557,EX,CT,Germany,S,Germany,100,"Spark, Scala, Hadoop, PyTorch, GCP",Bachelor,12,Automotive,2025-01-19,2025-03-28,1329,5.5,Quantum Computing Inc -AI00004,Computer Vision Engineer,96349,USD,96349,MI,FL,Finland,L,Finland,50,"MLOps, Linux, Tableau, Python",PhD,2,Automotive,2024-07-20,2024-09-06,1132,6.8,Cognitive Computing -AI00005,Robotics Engineer,63065,EUR,53605,EN,FT,France,S,France,100,"R, Scala, SQL, GCP, Python",Associate,0,Finance,2025-03-16,2025-05-09,2011,9.3,Advanced Robotics -AI00006,Data Scientist,111794,SGD,145332,SE,CT,Singapore,S,Norway,50,"NLP, MLOps, TensorFlow",Master,7,Technology,2024-11-10,2025-01-20,1021,5.1,Cloud AI Solutions -AI00007,AI Consultant,113897,CAD,142371,SE,PT,Canada,L,Poland,50,"PyTorch, Linux, NLP",Associate,9,Gaming,2024-02-29,2024-04-21,2268,7.4,AI Innovations -AI00008,Head of AI,168639,AUD,227663,SE,FT,Australia,L,Vietnam,100,"Spark, SQL, Tableau, Computer Vision, Linux",Associate,9,Consulting,2024-02-26,2024-03-17,1497,5.5,TechCorp Inc -AI00009,Data Scientist,92624,JPY,10188640,MI,FT,Japan,L,Japan,50,"Kubernetes, SQL, Docker, Deep Learning",Bachelor,4,Government,2024-08-18,2024-10-03,1724,9.5,DataVision Ltd -AI00010,Machine Learning Engineer,215627,GBP,161720,EX,FT,United Kingdom,M,United Kingdom,50,"Git, Scala, GCP",PhD,10,Government,2025-01-18,2025-03-20,902,7.8,DeepTech Ventures -AI00011,Data Engineer,129706,USD,129706,MI,CT,Denmark,L,Denmark,0,"SQL, PyTorch, Statistics, TensorFlow, NLP",Bachelor,3,Consulting,2024-03-10,2024-05-17,2247,5.2,Cloud AI Solutions -AI00012,Deep Learning Engineer,76559,USD,76559,EN,FL,United States,S,United States,100,"Data Visualization, Mathematics, PyTorch, GCP",Bachelor,1,Government,2025-02-09,2025-04-14,694,8.3,Machine Intelligence Group -AI00013,Principal Data Scientist,185834,USD,185834,EX,CT,United States,L,United States,100,"Linux, Data Visualization, Python, TensorFlow",Associate,14,Telecommunications,2024-03-27,2024-06-03,1710,8.9,Autonomous Tech -AI00014,Principal Data Scientist,89801,USD,89801,MI,PT,Sweden,M,Belgium,100,"Linux, MLOps, Deep Learning",Master,3,Healthcare,2024-10-30,2025-01-06,1361,8.7,Cloud AI Solutions -AI00015,Principal Data Scientist,252601,USD,252601,EX,PT,Norway,L,Norway,100,"Kubernetes, SQL, AWS, Git, Computer Vision",Master,19,Gaming,2024-07-24,2024-08-14,572,5.1,TechCorp Inc -AI00016,AI Product Manager,20520,USD,20520,EN,FT,India,S,India,0,"Hadoop, Git, Computer Vision, Kubernetes, Data Visualization",Master,0,Gaming,2024-08-22,2024-10-05,2455,7.5,Predictive Systems -AI00017,Robotics Engineer,192789,CHF,173510,SE,PT,Switzerland,S,Switzerland,100,"Tableau, Git, Python, Java",Master,5,Healthcare,2024-03-27,2024-06-08,524,5.9,Quantum Computing Inc -AI00018,Machine Learning Researcher,107184,SGD,139339,SE,FL,Singapore,S,Singapore,50,"Azure, GCP, Computer Vision",Master,7,Automotive,2024-05-07,2024-05-28,2111,9.2,DeepTech Ventures -AI00019,Robotics Engineer,141909,EUR,120623,SE,FT,Netherlands,M,Netherlands,0,"Git, Kubernetes, MLOps, Spark",Associate,6,Healthcare,2024-12-22,2025-01-20,1601,7.8,Cloud AI Solutions -AI00020,Data Engineer,118238,USD,118238,SE,FL,Ireland,M,Ireland,100,"AWS, Python, Azure, SQL, Computer Vision",Associate,7,Education,2024-11-07,2025-01-02,2431,8.2,TechCorp Inc -AI00021,Data Scientist,155210,AUD,209534,SE,PT,Australia,L,Argentina,0,"Spark, NLP, AWS",Master,7,Energy,2025-01-24,2025-03-18,595,9.7,Neural Networks Co -AI00022,Data Engineer,96699,AUD,130544,SE,FT,Australia,S,Australia,0,"GCP, Linux, Mathematics",PhD,5,Technology,2025-03-29,2025-04-13,582,9.7,TechCorp Inc -AI00023,AI Software Engineer,161477,EUR,137255,SE,FT,France,L,France,50,"Mathematics, Spark, Linux",Bachelor,8,Real Estate,2025-02-04,2025-03-03,1861,9.5,DataVision Ltd -AI00024,AI Software Engineer,316709,USD,316709,EX,CT,Denmark,L,Denmark,50,"Data Visualization, Azure, Statistics",PhD,18,Transportation,2025-04-29,2025-06-21,1284,7.6,Autonomous Tech -AI00025,ML Ops Engineer,62089,CAD,77611,MI,CT,Canada,S,Singapore,50,"Python, GCP, Linux, SQL, Deep Learning",PhD,3,Media,2024-03-18,2024-04-25,2264,9.7,Predictive Systems -AI00026,Principal Data Scientist,77985,USD,77985,EN,CT,Denmark,S,Denmark,0,"SQL, TensorFlow, Computer Vision, Kubernetes",Associate,0,Automotive,2025-03-07,2025-04-03,655,9.4,Neural Networks Co -AI00027,Robotics Engineer,55315,EUR,47018,EN,PT,Austria,S,Austria,0,"Spark, Deep Learning, SQL, NLP, Python",PhD,0,Media,2025-01-09,2025-03-22,1107,9.5,Future Systems -AI00028,AI Architect,246647,SGD,320641,EX,PT,Singapore,M,Singapore,50,"Scala, Mathematics, SQL",Master,16,Telecommunications,2024-08-08,2024-08-26,2347,6.6,DeepTech Ventures -AI00029,Deep Learning Engineer,29050,USD,29050,EN,FT,China,S,Germany,0,"PyTorch, Kubernetes, Deep Learning, Hadoop",Associate,1,Consulting,2025-02-06,2025-03-19,555,5.2,AI Innovations -AI00030,Head of AI,120599,GBP,90449,MI,CT,United Kingdom,L,United Kingdom,50,"Linux, AWS, Python",Master,4,Energy,2024-09-21,2024-11-07,699,6.4,Quantum Computing Inc -AI00031,AI Specialist,277727,SGD,361045,EX,PT,Singapore,L,Singapore,50,"Python, Git, TensorFlow",Associate,13,Healthcare,2024-10-04,2024-11-05,529,9,Future Systems -AI00032,Data Engineer,158734,CAD,198418,EX,PT,Canada,S,South Korea,50,"Data Visualization, NLP, Computer Vision",Master,16,Retail,2024-05-20,2024-07-29,1607,6.2,Future Systems -AI00033,Data Engineer,139438,JPY,15338180,SE,FL,Japan,L,Japan,0,"Python, Spark, Git, Data Visualization, Docker",PhD,9,Retail,2025-03-16,2025-05-12,1826,9.9,Cognitive Computing -AI00034,Head of AI,131432,SGD,170862,SE,PT,Singapore,M,Sweden,50,"Kubernetes, Data Visualization, Deep Learning, Azure, Computer Vision",Master,5,Manufacturing,2024-05-03,2024-07-15,1134,5.3,Cognitive Computing -AI00035,Data Analyst,140290,USD,140290,MI,PT,Denmark,L,Denmark,50,"PyTorch, SQL, R, Azure",Associate,4,Real Estate,2024-07-18,2024-09-26,2437,5.7,DeepTech Ventures -AI00036,Research Scientist,90858,EUR,77229,MI,CT,France,L,France,50,"Scala, PyTorch, Deep Learning, Kubernetes, Java",Bachelor,2,Real Estate,2024-08-13,2024-09-13,1793,7.1,DataVision Ltd -AI00037,Autonomous Systems Engineer,126597,GBP,94948,SE,FL,United Kingdom,L,Singapore,50,"PyTorch, Java, TensorFlow, Computer Vision, SQL",Master,6,Government,2024-03-30,2024-04-13,2236,7.8,Machine Intelligence Group -AI00038,AI Architect,53274,USD,53274,EN,FL,Finland,M,Finland,100,"Spark, Python, Statistics, Hadoop, TensorFlow",Associate,0,Automotive,2025-03-22,2025-04-12,1444,6,Autonomous Tech -AI00039,Machine Learning Researcher,155357,USD,155357,EX,FL,Sweden,S,France,100,"TensorFlow, SQL, Computer Vision, Kubernetes",Bachelor,17,Real Estate,2024-12-11,2025-01-01,830,5.2,Cloud AI Solutions -AI00040,Principal Data Scientist,116292,EUR,98848,MI,FL,Netherlands,M,Hungary,50,"Java, Docker, Python",Bachelor,4,Gaming,2024-07-28,2024-09-06,2404,7.9,Quantum Computing Inc -AI00041,Computer Vision Engineer,140363,EUR,119309,SE,CT,Austria,L,Austria,100,"MLOps, Hadoop, TensorFlow, Kubernetes",Master,6,Manufacturing,2025-01-31,2025-04-06,1852,9.8,TechCorp Inc -AI00042,Research Scientist,162306,USD,162306,SE,CT,Israel,L,Luxembourg,0,"Statistics, SQL, Tableau, Hadoop, R",Master,9,Energy,2024-11-12,2024-12-08,1066,5.6,Neural Networks Co -AI00043,Data Analyst,134224,USD,134224,EX,FT,China,L,China,0,"Python, SQL, Git",Master,16,Technology,2024-10-13,2024-11-15,1743,6.6,Quantum Computing Inc -AI00044,Research Scientist,77500,GBP,58125,MI,CT,United Kingdom,S,Norway,0,"Mathematics, Hadoop, TensorFlow",PhD,3,Technology,2024-08-20,2024-10-29,811,10,Machine Intelligence Group -AI00045,Computer Vision Engineer,154083,USD,154083,SE,PT,Ireland,L,Ireland,50,"Hadoop, Python, Deep Learning",Associate,7,Manufacturing,2024-01-09,2024-02-16,1969,7.7,Neural Networks Co -AI00046,Machine Learning Engineer,79445,USD,79445,MI,FL,Ireland,M,Ireland,50,"Python, Statistics, TensorFlow, Computer Vision",Bachelor,4,Real Estate,2024-09-28,2024-10-16,511,7.2,Cloud AI Solutions -AI00047,Head of AI,157466,CHF,141719,SE,FL,Switzerland,M,Switzerland,100,"Git, Data Visualization, Spark, Computer Vision, Azure",Associate,8,Automotive,2024-01-21,2024-03-03,547,5.2,Future Systems -AI00048,Head of AI,38972,USD,38972,MI,FT,India,L,India,0,"Kubernetes, Mathematics, TensorFlow, MLOps",PhD,4,Real Estate,2024-01-28,2024-03-09,2163,7.1,AI Innovations -AI00049,Deep Learning Engineer,66090,CAD,82613,MI,PT,Canada,S,Canada,0,"AWS, SQL, R, Scala",PhD,3,Technology,2025-04-10,2025-04-29,1901,5.3,DeepTech Ventures -AI00050,Data Analyst,47943,USD,47943,MI,PT,China,L,China,50,"TensorFlow, Mathematics, NLP, Docker",PhD,2,Finance,2024-11-23,2025-01-13,2483,6.2,Smart Analytics -AI00051,ML Ops Engineer,217318,USD,217318,EX,PT,Ireland,M,Malaysia,100,"SQL, PyTorch, Hadoop",Bachelor,17,Finance,2024-11-14,2024-12-22,1647,7.8,Cognitive Computing -AI00052,AI Architect,84705,USD,84705,MI,CT,Norway,S,Norway,50,"Scala, Spark, PyTorch",PhD,3,Government,2024-12-19,2025-01-11,879,6.6,Autonomous Tech -AI00053,NLP Engineer,36076,USD,36076,SE,FT,India,M,India,50,"Python, TensorFlow, Data Visualization",Master,7,Media,2024-08-14,2024-09-23,580,7.5,Cognitive Computing -AI00054,AI Consultant,160216,USD,160216,EX,FT,Israel,L,Israel,100,"Deep Learning, Linux, Python, SQL",Master,15,Education,2024-05-09,2024-05-29,941,6,Predictive Systems -AI00055,Deep Learning Engineer,60826,GBP,45620,EN,FT,United Kingdom,S,United Kingdom,0,"SQL, Kubernetes, Azure",Bachelor,0,Energy,2024-11-02,2024-11-30,1731,6.3,Autonomous Tech -AI00056,Deep Learning Engineer,237320,GBP,177990,EX,PT,United Kingdom,M,United Kingdom,0,"Kubernetes, MLOps, Scala",Bachelor,16,Real Estate,2024-11-12,2024-12-28,991,7.7,DataVision Ltd -AI00057,Robotics Engineer,60243,EUR,51207,EN,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Linux, Mathematics",Master,1,Healthcare,2024-12-05,2024-12-20,1661,8.8,Future Systems -AI00058,Head of AI,74091,JPY,8150010,EN,PT,Japan,M,Japan,50,"Deep Learning, NLP, R, Linux, SQL",Bachelor,1,Consulting,2025-01-18,2025-03-23,1295,7.2,Quantum Computing Inc -AI00059,AI Specialist,68535,EUR,58255,EN,FT,France,L,France,100,"SQL, Scala, PyTorch",Associate,1,Media,2024-05-01,2024-06-17,1943,5.5,Machine Intelligence Group -AI00060,Robotics Engineer,99401,USD,99401,MI,FL,Norway,S,Norway,50,"Hadoop, Kubernetes, Data Visualization, Python, Linux",Bachelor,3,Healthcare,2024-03-20,2024-04-20,1371,9.4,Quantum Computing Inc -AI00061,Machine Learning Researcher,67632,USD,67632,EN,FT,Ireland,L,Ireland,0,"Linux, GCP, Deep Learning",Master,0,Government,2024-07-13,2024-08-10,2133,8.9,Advanced Robotics -AI00062,ML Ops Engineer,133163,EUR,113189,SE,CT,Netherlands,M,Netherlands,0,"SQL, Statistics, MLOps, PyTorch, Kubernetes",Associate,6,Media,2025-01-03,2025-01-21,2141,7.9,Neural Networks Co -AI00063,Robotics Engineer,125752,USD,125752,MI,FT,Norway,S,Norway,0,"NLP, Statistics, Scala",Master,4,Automotive,2024-05-17,2024-06-24,2390,6,Machine Intelligence Group -AI00064,AI Product Manager,70927,JPY,7801970,EN,CT,Japan,M,Japan,0,"Git, Computer Vision, Docker, SQL, Hadoop",Associate,1,Technology,2024-03-07,2024-04-05,1847,9.3,Quantum Computing Inc -AI00065,Data Engineer,80810,GBP,60608,EN,PT,United Kingdom,L,United Kingdom,0,"Azure, MLOps, Python, Linux, TensorFlow",Master,1,Energy,2024-10-30,2025-01-01,1476,5.4,Algorithmic Solutions -AI00066,Machine Learning Engineer,59614,SGD,77498,EN,CT,Singapore,S,Singapore,100,"Java, Kubernetes, GCP, Linux, Data Visualization",Associate,1,Healthcare,2024-11-07,2024-12-19,1581,7.3,Quantum Computing Inc -AI00067,Robotics Engineer,151907,EUR,129121,EX,FT,Germany,S,Ghana,50,"Python, R, MLOps",Associate,16,Media,2024-09-21,2024-10-16,1433,6.1,Quantum Computing Inc -AI00068,Data Scientist,76317,USD,76317,EX,CT,India,M,India,0,"TensorFlow, Deep Learning, Spark",Bachelor,14,Energy,2024-06-19,2024-07-15,1228,9.1,DataVision Ltd -AI00069,AI Research Scientist,160534,USD,160534,SE,FL,Denmark,M,Denmark,100,"GCP, SQL, MLOps",Master,9,Gaming,2024-06-10,2024-07-07,1651,8.3,Advanced Robotics -AI00070,AI Consultant,40687,USD,40687,MI,FT,India,L,India,50,"SQL, R, GCP, PyTorch, AWS",Master,3,Transportation,2024-07-16,2024-08-25,804,7.3,Algorithmic Solutions -AI00071,Computer Vision Engineer,129265,AUD,174508,SE,FL,Australia,S,Australia,0,"Java, Scala, TensorFlow",Master,5,Consulting,2025-04-06,2025-05-07,2410,6.9,DataVision Ltd -AI00072,NLP Engineer,94396,USD,94396,EX,PT,China,M,China,100,"Scala, Python, Tableau, Mathematics",Master,18,Government,2024-07-30,2024-08-18,1033,9.5,Advanced Robotics -AI00073,NLP Engineer,158237,USD,158237,EX,CT,South Korea,L,South Korea,0,"Python, NLP, GCP",Master,11,Finance,2025-01-24,2025-03-29,1676,6,Quantum Computing Inc -AI00074,Robotics Engineer,239068,USD,239068,EX,PT,Denmark,L,Denmark,50,"TensorFlow, Java, NLP, Hadoop, GCP",PhD,18,Media,2024-08-26,2024-10-30,1321,6.8,Autonomous Tech -AI00075,Robotics Engineer,81401,USD,81401,MI,FL,Finland,M,Belgium,0,"Java, Spark, Data Visualization, AWS, Git",Associate,2,Retail,2025-02-07,2025-04-11,1930,6.3,Future Systems -AI00076,AI Specialist,144229,CHF,129806,MI,FT,Switzerland,M,Japan,0,"Python, TensorFlow, MLOps, PyTorch",PhD,2,Media,2024-01-02,2024-03-02,1213,9.5,DeepTech Ventures -AI00077,AI Consultant,78936,EUR,67096,MI,FL,Germany,S,Germany,0,"Mathematics, Tableau, R, NLP, SQL",Bachelor,4,Consulting,2024-11-30,2025-01-03,697,6.9,Cloud AI Solutions -AI00078,AI Consultant,101054,USD,101054,SE,PT,South Korea,L,United Kingdom,0,"PyTorch, Python, TensorFlow",Bachelor,6,Healthcare,2025-02-04,2025-03-20,2396,8.8,DeepTech Ventures -AI00079,AI Specialist,91807,EUR,78036,SE,FT,Austria,S,Austria,50,"Linux, Azure, Scala, Python",Master,9,Education,2024-07-21,2024-09-13,1519,8.3,TechCorp Inc -AI00080,Machine Learning Engineer,49858,EUR,42379,EN,CT,Austria,S,Singapore,100,"PyTorch, Spark, Linux",Bachelor,1,Healthcare,2024-01-25,2024-04-02,1215,9.2,AI Innovations -AI00081,Robotics Engineer,80596,EUR,68507,EN,FT,Austria,L,Switzerland,0,"Kubernetes, Scala, PyTorch, Mathematics",Master,1,Education,2024-06-27,2024-08-26,1512,6.8,Digital Transformation LLC -AI00082,Head of AI,76026,USD,76026,MI,FT,Sweden,M,Sweden,50,"Tableau, SQL, R, Scala",PhD,4,Healthcare,2025-02-12,2025-03-24,1079,8,Predictive Systems -AI00083,Deep Learning Engineer,84841,USD,84841,MI,CT,Sweden,L,Sweden,0,"Azure, Linux, TensorFlow, GCP",Associate,4,Transportation,2024-11-18,2025-01-05,2456,5.7,Cognitive Computing -AI00084,Data Scientist,158900,CHF,143010,SE,FL,Switzerland,M,Switzerland,50,"Python, Statistics, Mathematics, Docker, TensorFlow",Associate,8,Finance,2024-06-14,2024-07-05,2367,6,Quantum Computing Inc -AI00085,Autonomous Systems Engineer,153858,EUR,130779,EX,CT,Germany,S,Germany,50,"MLOps, Azure, Java",Master,13,Gaming,2025-04-29,2025-06-21,2133,5.1,Cloud AI Solutions -AI00086,Data Scientist,115314,USD,115314,MI,CT,Denmark,M,Finland,0,"Java, Git, R, Azure",Bachelor,3,Real Estate,2024-06-01,2024-06-27,1783,7.9,Smart Analytics -AI00087,Machine Learning Engineer,181068,USD,181068,EX,FT,Israel,S,Israel,100,"R, Java, Hadoop, Mathematics",PhD,13,Transportation,2024-01-26,2024-03-25,1322,8.5,Machine Intelligence Group -AI00088,AI Software Engineer,119021,USD,119021,EN,FT,Denmark,L,Portugal,0,"Computer Vision, Docker, Linux, GCP",PhD,1,Transportation,2025-03-07,2025-05-10,1461,7.3,DataVision Ltd -AI00089,Data Analyst,219746,USD,219746,EX,FL,Israel,M,Czech Republic,100,"R, Python, Scala, TensorFlow",PhD,15,Finance,2024-07-02,2024-09-12,1485,7,Smart Analytics -AI00090,AI Consultant,115774,USD,115774,EX,FL,China,L,China,50,"Hadoop, Scala, NLP, PyTorch, SQL",Associate,10,Real Estate,2024-02-04,2024-03-09,1618,5.3,DataVision Ltd -AI00091,AI Consultant,130984,CHF,117886,EN,PT,Switzerland,L,Philippines,50,"MLOps, Deep Learning, Kubernetes, Azure, GCP",Bachelor,1,Retail,2024-01-08,2024-03-20,1774,5.3,DataVision Ltd -AI00092,ML Ops Engineer,191223,CHF,172101,EX,FT,Switzerland,S,Germany,0,"NLP, Azure, SQL",PhD,18,Healthcare,2024-04-07,2024-06-07,1926,6.8,Neural Networks Co -AI00093,AI Consultant,155502,USD,155502,SE,FT,Norway,M,Italy,50,"Python, NLP, AWS, Spark",PhD,9,Consulting,2025-01-29,2025-02-22,2449,7.6,Future Systems -AI00094,AI Specialist,86140,EUR,73219,MI,PT,Germany,L,South Korea,50,"Scala, Kubernetes, Deep Learning, AWS",Master,4,Real Estate,2025-03-11,2025-04-12,1816,7.3,Predictive Systems -AI00095,AI Architect,96028,GBP,72021,MI,FL,United Kingdom,L,Australia,0,"Data Visualization, MLOps, GCP, PyTorch",Bachelor,4,Healthcare,2025-03-09,2025-03-28,1878,6.6,Future Systems -AI00096,Principal Data Scientist,134920,USD,134920,SE,PT,United States,S,United States,0,"SQL, Mathematics, Data Visualization, Kubernetes",Associate,7,Consulting,2025-04-03,2025-05-12,1930,6.7,Predictive Systems -AI00097,Research Scientist,107694,USD,107694,SE,FL,Ireland,M,Estonia,50,"Spark, Linux, MLOps, R",Associate,5,Retail,2024-03-20,2024-04-22,2292,5.1,Future Systems -AI00098,Deep Learning Engineer,114301,USD,114301,MI,FT,Finland,L,Finland,0,"Tableau, MLOps, Python",Bachelor,4,Real Estate,2025-02-08,2025-03-05,1506,7.5,Digital Transformation LLC -AI00099,Machine Learning Researcher,92728,GBP,69546,MI,FT,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes, Azure",Bachelor,4,Transportation,2024-12-25,2025-02-05,1948,9.3,Cognitive Computing -AI00100,NLP Engineer,76826,SGD,99874,EN,PT,Singapore,M,Singapore,50,"Git, R, Statistics, PyTorch, Deep Learning",Bachelor,1,Government,2025-04-08,2025-05-10,804,7.4,Predictive Systems -AI00101,AI Consultant,48870,USD,48870,SE,PT,India,L,India,0,"Hadoop, Java, Azure, Spark, Statistics",Associate,7,Healthcare,2025-03-26,2025-05-16,1108,5.6,Cognitive Computing -AI00102,Data Scientist,89527,AUD,120861,MI,FT,Australia,L,United States,50,"Linux, Azure, SQL, R, Java",Master,4,Finance,2024-12-09,2024-12-30,1299,5.8,Predictive Systems -AI00103,Autonomous Systems Engineer,81103,AUD,109489,EN,CT,Australia,L,Australia,0,"Mathematics, SQL, Kubernetes",Master,0,Media,2024-05-26,2024-08-07,2055,7,Digital Transformation LLC -AI00104,Machine Learning Engineer,283428,USD,283428,EX,CT,Denmark,L,Denmark,0,"Python, TensorFlow, MLOps, Data Visualization",Associate,13,Healthcare,2025-03-10,2025-05-11,1275,5.1,Smart Analytics -AI00105,AI Product Manager,104906,USD,104906,MI,FL,United States,S,Portugal,50,"PyTorch, Java, Spark, Statistics",Bachelor,3,Technology,2025-01-26,2025-03-28,2101,8,Cognitive Computing -AI00106,AI Software Engineer,231496,USD,231496,EX,PT,Finland,L,Finland,50,"Tableau, R, Kubernetes",Master,18,Automotive,2025-02-13,2025-04-10,895,5.5,DataVision Ltd -AI00107,Robotics Engineer,147402,JPY,16214220,SE,FT,Japan,L,Japan,100,"Azure, GCP, Scala, R, Python",Bachelor,8,Automotive,2024-12-11,2025-02-01,593,7,Algorithmic Solutions -AI00108,Data Scientist,69331,EUR,58931,EN,FT,Austria,L,Austria,100,"AWS, Git, NLP, Java, Computer Vision",Master,1,Healthcare,2025-04-11,2025-05-21,639,8.8,AI Innovations -AI00109,AI Consultant,215842,EUR,183466,EX,CT,France,S,France,0,"Deep Learning, TensorFlow, Spark, Python",Bachelor,12,Healthcare,2024-12-19,2025-01-28,2098,6.7,Machine Intelligence Group -AI00110,Data Scientist,79833,USD,79833,SE,PT,South Korea,S,South Korea,0,"Java, SQL, PyTorch, TensorFlow, AWS",PhD,6,Healthcare,2024-01-04,2024-01-18,1284,5.7,Predictive Systems -AI00111,Data Scientist,304859,USD,304859,EX,FT,Norway,L,Norway,100,"Linux, SQL, Mathematics",Bachelor,15,Media,2025-03-22,2025-05-05,2460,6,Advanced Robotics -AI00112,Research Scientist,112217,EUR,95384,SE,CT,Germany,S,Israel,0,"Spark, Scala, Azure",Associate,8,Technology,2025-03-07,2025-04-23,1679,10,Digital Transformation LLC -AI00113,Head of AI,45738,USD,45738,EN,FL,South Korea,M,South Korea,100,"TensorFlow, Hadoop, Spark",Associate,0,Manufacturing,2024-03-17,2024-04-05,1481,9.5,DeepTech Ventures -AI00114,Machine Learning Researcher,195309,EUR,166013,EX,PT,Germany,S,Germany,50,"SQL, Tableau, PyTorch, NLP",Bachelor,18,Consulting,2024-12-14,2025-02-23,1277,5.3,DeepTech Ventures -AI00115,Data Scientist,141439,USD,141439,SE,FL,United States,L,United States,50,"Kubernetes, GCP, Git, SQL",PhD,9,Retail,2024-06-24,2024-07-13,1021,6.3,Digital Transformation LLC -AI00116,AI Consultant,125836,USD,125836,MI,FT,Norway,L,Norway,100,"Statistics, Kubernetes, Spark, GCP",Master,2,Transportation,2024-12-27,2025-02-22,1650,10,Predictive Systems -AI00117,Machine Learning Researcher,58213,USD,58213,EN,FT,Israel,S,Thailand,50,"Azure, Linux, Kubernetes",PhD,0,Telecommunications,2025-04-13,2025-06-08,1087,5.5,Cloud AI Solutions -AI00118,ML Ops Engineer,82191,EUR,69862,MI,CT,Germany,M,Germany,0,"Spark, GCP, Hadoop",Bachelor,2,Media,2024-08-05,2024-10-16,1906,9.5,Quantum Computing Inc -AI00119,Machine Learning Researcher,207975,AUD,280766,EX,CT,Australia,S,Colombia,0,"SQL, Azure, Computer Vision",Master,13,Telecommunications,2025-02-21,2025-04-07,1475,9.9,Future Systems -AI00120,Computer Vision Engineer,115664,USD,115664,SE,PT,Ireland,M,Ireland,0,"TensorFlow, R, Data Visualization",Bachelor,7,Automotive,2024-03-27,2024-05-15,1449,7.8,Smart Analytics -AI00121,AI Software Engineer,109337,USD,109337,SE,PT,Ireland,M,Ireland,50,"Data Visualization, PyTorch, Python, Mathematics, Git",Associate,9,Government,2025-04-26,2025-05-13,901,8.1,Predictive Systems -AI00122,Data Analyst,115386,USD,115386,SE,PT,Finland,M,Finland,100,"MLOps, Statistics, Hadoop, SQL",Associate,7,Energy,2024-09-02,2024-11-03,2387,6.7,Smart Analytics -AI00123,Autonomous Systems Engineer,64431,GBP,48323,EN,FT,United Kingdom,L,United Kingdom,50,"Git, Deep Learning, Python, Statistics, TensorFlow",Bachelor,1,Automotive,2025-01-25,2025-02-25,825,9,DeepTech Ventures -AI00124,Data Engineer,108088,USD,108088,SE,FL,United States,S,United States,100,"Tableau, Python, Docker, Azure",Bachelor,9,Consulting,2024-10-07,2024-12-15,1769,8,Smart Analytics -AI00125,ML Ops Engineer,228314,GBP,171236,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Hadoop, SQL, Statistics, TensorFlow",Master,16,Telecommunications,2024-10-18,2024-12-04,1005,6.5,Cognitive Computing -AI00126,Data Scientist,153260,AUD,206901,SE,CT,Australia,L,Australia,0,"MLOps, Java, NLP",Master,9,Education,2025-04-02,2025-05-04,1768,9.7,DataVision Ltd -AI00127,Data Scientist,63667,USD,63667,MI,CT,Israel,S,Norway,100,"R, Data Visualization, SQL, NLP",PhD,4,Energy,2025-03-20,2025-05-12,1336,7.9,Algorithmic Solutions -AI00128,Research Scientist,31185,USD,31185,MI,FL,China,S,Colombia,100,"AWS, GCP, NLP, SQL, Statistics",Associate,3,Healthcare,2025-03-11,2025-04-07,1510,9.2,Neural Networks Co -AI00129,Machine Learning Engineer,132167,EUR,112342,SE,PT,Germany,M,Germany,50,"MLOps, Docker, Linux, Computer Vision",Bachelor,9,Education,2024-08-04,2024-10-12,1110,6.2,Quantum Computing Inc -AI00130,AI Research Scientist,223349,JPY,24568390,EX,FL,Japan,L,Japan,100,"PyTorch, Mathematics, TensorFlow",Bachelor,11,Gaming,2024-07-31,2024-09-27,1489,5.9,Smart Analytics -AI00131,AI Architect,26957,USD,26957,EN,CT,India,M,India,100,"Azure, Computer Vision, Statistics",Bachelor,1,Transportation,2025-03-23,2025-04-17,2335,9.5,DataVision Ltd -AI00132,AI Software Engineer,93564,USD,93564,MI,CT,Sweden,S,Sweden,0,"PyTorch, Docker, Data Visualization, Scala, Computer Vision",Associate,2,Transportation,2025-03-25,2025-04-13,515,9.7,Advanced Robotics -AI00133,Computer Vision Engineer,113846,EUR,96769,SE,PT,France,S,France,100,"SQL, Git, R, Hadoop, Docker",Associate,6,Energy,2024-09-02,2024-10-30,2447,7.8,DataVision Ltd -AI00134,AI Specialist,147580,EUR,125443,EX,FL,France,M,France,0,"Linux, Deep Learning, Hadoop, Kubernetes, Docker",PhD,17,Telecommunications,2024-11-13,2025-01-10,2416,5.9,Cloud AI Solutions -AI00135,Data Engineer,50514,CAD,63143,EN,PT,Canada,M,Philippines,100,"SQL, PyTorch, Tableau, NLP",PhD,1,Automotive,2024-08-04,2024-08-28,2384,9,Cognitive Computing -AI00136,AI Product Manager,94158,EUR,80034,MI,FL,Germany,M,Vietnam,100,"PyTorch, R, Scala",Master,2,Education,2024-09-01,2024-10-10,867,5.5,Future Systems -AI00137,Principal Data Scientist,161009,EUR,136858,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, AWS, GCP",Associate,19,Transportation,2024-02-17,2024-03-17,1247,7.1,Cognitive Computing -AI00138,Data Analyst,91911,USD,91911,EX,FT,India,L,India,100,"PyTorch, SQL, Azure, Docker",Associate,15,Technology,2024-06-15,2024-08-15,2149,5.9,Cloud AI Solutions -AI00139,AI Specialist,248071,EUR,210860,EX,FL,Germany,M,Czech Republic,50,"Kubernetes, R, GCP",Bachelor,15,Consulting,2025-04-13,2025-04-29,616,7.6,Future Systems -AI00140,Autonomous Systems Engineer,150204,EUR,127673,SE,PT,Germany,M,Germany,50,"Docker, Linux, Kubernetes, Data Visualization",Bachelor,9,Transportation,2025-03-18,2025-04-12,1478,6.3,Neural Networks Co -AI00141,AI Product Manager,181517,EUR,154289,SE,CT,Netherlands,L,Netherlands,50,"SQL, Kubernetes, NLP, MLOps",PhD,9,Government,2024-08-13,2024-09-05,981,8.9,TechCorp Inc -AI00142,Data Analyst,64573,EUR,54887,EN,PT,France,L,France,100,"Kubernetes, GCP, Mathematics, Python",Master,1,Government,2024-07-19,2024-09-30,1495,9.2,AI Innovations -AI00143,ML Ops Engineer,89332,USD,89332,MI,CT,United States,S,United States,100,"Python, TensorFlow, Deep Learning, Docker, PyTorch",Bachelor,4,Finance,2024-08-20,2024-10-23,2011,6,Predictive Systems -AI00144,Machine Learning Engineer,118239,USD,118239,SE,FL,Sweden,S,Indonesia,50,"AWS, Hadoop, PyTorch, Statistics, Azure",PhD,9,Energy,2024-08-03,2024-09-22,576,8.1,Future Systems -AI00145,AI Specialist,103715,JPY,11408650,MI,FT,Japan,S,Japan,50,"Python, Azure, Statistics",Bachelor,4,Automotive,2024-12-11,2025-01-20,2224,9.3,Neural Networks Co -AI00146,AI Consultant,151680,AUD,204768,EX,FL,Australia,S,Australia,100,"Computer Vision, AWS, Kubernetes",Associate,14,Manufacturing,2024-06-20,2024-07-31,2439,6.9,Cognitive Computing -AI00147,Data Analyst,142589,EUR,121201,SE,FT,Netherlands,L,Netherlands,0,"Docker, Tableau, Kubernetes, Data Visualization, GCP",Master,8,Government,2024-10-25,2024-11-11,2431,6,Predictive Systems -AI00148,Research Scientist,63062,USD,63062,EN,PT,Sweden,L,Sweden,50,"PyTorch, R, Mathematics, Kubernetes",Associate,1,Real Estate,2024-09-05,2024-10-18,1558,6.7,Smart Analytics -AI00149,Data Engineer,80691,JPY,8876010,EN,CT,Japan,L,Japan,100,"Deep Learning, Computer Vision, PyTorch, Statistics, Spark",Master,1,Retail,2024-12-21,2025-01-04,624,8.1,DataVision Ltd -AI00150,Data Analyst,171580,JPY,18873800,SE,PT,Japan,L,Kenya,100,"SQL, Spark, MLOps",PhD,7,Manufacturing,2024-10-14,2024-12-09,1931,6.7,Predictive Systems -AI00151,Autonomous Systems Engineer,58331,USD,58331,SE,PT,China,M,Chile,0,"Hadoop, Java, NLP, Mathematics, Python",Master,5,Transportation,2024-11-23,2025-01-24,2002,6.1,Cognitive Computing -AI00152,Head of AI,85620,CAD,107025,MI,FT,Canada,L,Canada,100,"TensorFlow, GCP, MLOps, NLP",Associate,4,Healthcare,2025-01-22,2025-02-23,848,5.8,Quantum Computing Inc -AI00153,AI Consultant,220871,EUR,187740,EX,FT,Austria,M,Austria,0,"Linux, Tableau, Spark, Scala",Associate,14,Automotive,2024-06-28,2024-07-31,821,5.2,DeepTech Ventures -AI00154,ML Ops Engineer,93007,EUR,79056,MI,CT,France,M,France,50,"Docker, SQL, MLOps, GCP, Hadoop",Bachelor,4,Energy,2024-06-05,2024-07-23,1595,6.4,Cognitive Computing -AI00155,AI Specialist,191783,SGD,249318,EX,FT,Singapore,S,Singapore,100,"Java, GCP, PyTorch",PhD,14,Healthcare,2024-10-04,2024-10-27,2352,5.6,Advanced Robotics -AI00156,Head of AI,83683,USD,83683,MI,FL,Israel,S,Czech Republic,50,"Mathematics, Computer Vision, MLOps, Git, Deep Learning",Bachelor,3,Education,2024-05-15,2024-06-07,818,5.3,Smart Analytics -AI00157,Research Scientist,107869,USD,107869,SE,FL,Ireland,S,Ireland,50,"SQL, Linux, GCP",Associate,8,Finance,2024-02-17,2024-04-01,2148,7.3,Predictive Systems -AI00158,Autonomous Systems Engineer,73528,USD,73528,MI,PT,Sweden,S,Poland,0,"NLP, R, Git, MLOps",Associate,2,Finance,2024-03-01,2024-05-05,557,8,Algorithmic Solutions -AI00159,NLP Engineer,47642,USD,47642,MI,FL,China,L,Sweden,100,"Python, TensorFlow, NLP",PhD,3,Telecommunications,2024-11-22,2025-01-13,2171,8,DeepTech Ventures -AI00160,AI Software Engineer,179937,EUR,152946,SE,PT,Netherlands,L,Netherlands,50,"Python, TensorFlow, NLP, Kubernetes",Associate,6,Real Estate,2024-06-01,2024-07-29,774,8.1,Machine Intelligence Group -AI00161,Data Engineer,157066,CHF,141359,MI,PT,Switzerland,L,Sweden,0,"GCP, Docker, NLP, Data Visualization",PhD,2,Transportation,2024-05-01,2024-05-26,887,9,Neural Networks Co -AI00162,Data Scientist,57299,USD,57299,EN,CT,Israel,M,Israel,0,"PyTorch, Spark, TensorFlow",Bachelor,1,Retail,2024-01-17,2024-02-19,794,7.8,DataVision Ltd -AI00163,Data Engineer,176844,CAD,221055,EX,FL,Canada,L,France,50,"Linux, Scala, Tableau",PhD,10,Telecommunications,2024-06-08,2024-07-19,577,5.4,Digital Transformation LLC -AI00164,AI Research Scientist,64892,CAD,81115,EN,CT,Canada,M,Canada,50,"Kubernetes, Scala, Azure, Computer Vision",Associate,1,Transportation,2024-11-05,2025-01-03,1645,5.7,Algorithmic Solutions -AI00165,AI Specialist,63024,EUR,53570,EN,CT,Austria,L,Austria,0,"Git, Statistics, Data Visualization",Bachelor,1,Gaming,2024-04-04,2024-05-05,1745,9.2,Algorithmic Solutions -AI00166,Principal Data Scientist,136695,CHF,123026,MI,FL,Switzerland,S,Switzerland,50,"Linux, GCP, Tableau, Java",Bachelor,2,Gaming,2024-12-10,2024-12-27,1424,5.9,Algorithmic Solutions -AI00167,Data Scientist,69744,USD,69744,EN,PT,South Korea,L,South Korea,50,"Python, Docker, Tableau",Associate,1,Telecommunications,2024-12-30,2025-01-22,1077,8.4,Autonomous Tech -AI00168,AI Specialist,135137,EUR,114866,EX,FL,Austria,M,Austria,0,"Kubernetes, GCP, Data Visualization",PhD,18,Finance,2024-04-06,2024-05-17,1590,5.4,TechCorp Inc -AI00169,Computer Vision Engineer,143037,USD,143037,EX,FL,Sweden,S,Sweden,0,"Data Visualization, Linux, Azure, Java",PhD,13,Manufacturing,2024-05-24,2024-07-07,775,9.5,Autonomous Tech -AI00170,Machine Learning Engineer,113068,GBP,84801,SE,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, Java, Data Visualization, Kubernetes",Master,9,Gaming,2024-06-10,2024-07-05,1805,6.6,Machine Intelligence Group -AI00171,AI Software Engineer,113917,GBP,85438,SE,PT,United Kingdom,S,Russia,0,"SQL, Kubernetes, GCP",Master,9,Government,2024-10-07,2024-10-26,1720,7.3,Future Systems -AI00172,Head of AI,80311,USD,80311,EX,PT,India,M,India,50,"Git, GCP, Computer Vision, Kubernetes, Docker",Bachelor,13,Finance,2025-01-17,2025-03-11,1052,5,Smart Analytics -AI00173,Autonomous Systems Engineer,160261,EUR,136222,SE,CT,Germany,L,Germany,50,"AWS, Linux, Scala, GCP, Python",Associate,6,Education,2024-02-26,2024-04-16,748,9.9,Smart Analytics -AI00174,Research Scientist,152241,CHF,137017,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, SQL, Git, PyTorch, Computer Vision",Bachelor,8,Gaming,2024-04-05,2024-06-05,1807,5.9,AI Innovations -AI00175,Research Scientist,74172,USD,74172,MI,CT,Israel,M,Israel,100,"Statistics, Kubernetes, GCP, Spark",PhD,2,Government,2024-01-24,2024-03-22,1780,7.5,Algorithmic Solutions -AI00176,Computer Vision Engineer,105632,USD,105632,MI,FL,Finland,L,Norway,100,"AWS, R, MLOps",Bachelor,3,Government,2025-01-03,2025-01-30,2376,9.4,Machine Intelligence Group -AI00177,Principal Data Scientist,89515,SGD,116370,MI,CT,Singapore,L,South Africa,100,"PyTorch, NLP, Computer Vision",Associate,4,Gaming,2025-01-17,2025-03-29,2328,7.4,DataVision Ltd -AI00178,AI Software Engineer,102319,USD,102319,MI,FL,Denmark,M,Colombia,50,"Deep Learning, Mathematics, Data Visualization, NLP",Associate,4,Energy,2024-07-14,2024-08-01,1939,6.2,Cognitive Computing -AI00179,AI Software Engineer,110536,USD,110536,MI,CT,Denmark,M,France,50,"SQL, Spark, Mathematics, Linux, TensorFlow",Associate,2,Real Estate,2024-05-01,2024-06-22,1559,5.4,DeepTech Ventures -AI00180,NLP Engineer,176372,USD,176372,SE,FL,Denmark,S,Denmark,0,"SQL, AWS, Computer Vision",Bachelor,5,Technology,2024-05-02,2024-07-05,729,8,AI Innovations -AI00181,AI Software Engineer,58111,EUR,49394,EN,FT,Austria,S,Austria,100,"Docker, Linux, Java",Bachelor,0,Finance,2024-01-20,2024-02-17,889,5.6,Digital Transformation LLC -AI00182,AI Product Manager,39802,USD,39802,SE,PT,India,M,Spain,100,"Git, Hadoop, Linux",Associate,8,Consulting,2024-02-05,2024-03-06,2046,8.3,Digital Transformation LLC -AI00183,Head of AI,147385,EUR,125277,SE,FL,France,L,Denmark,50,"Java, Statistics, AWS, Scala",Master,9,Consulting,2024-03-08,2024-03-25,1576,8.6,Cloud AI Solutions -AI00184,Research Scientist,118122,USD,118122,EN,FT,Denmark,L,Denmark,0,"Git, Scala, MLOps, Docker, Hadoop",Associate,0,Automotive,2024-07-20,2024-09-06,2018,9.3,Cloud AI Solutions -AI00185,AI Architect,75225,AUD,101554,EN,FT,Australia,L,Russia,100,"Deep Learning, MLOps, Linux",Master,0,Real Estate,2024-10-10,2024-11-26,2399,7.5,Machine Intelligence Group -AI00186,AI Research Scientist,48325,CAD,60406,EN,FL,Canada,M,Canada,100,"Spark, TensorFlow, Hadoop",Associate,0,Manufacturing,2025-03-26,2025-06-07,1523,6.2,Algorithmic Solutions -AI00187,Data Scientist,64973,USD,64973,EN,CT,Sweden,L,Sweden,0,"Git, Spark, NLP, MLOps",Master,0,Energy,2024-03-08,2024-04-24,1016,6.4,AI Innovations -AI00188,Computer Vision Engineer,78182,AUD,105546,MI,PT,Australia,M,Australia,50,"Hadoop, Docker, Computer Vision, Linux",Associate,4,Retail,2024-03-22,2024-05-22,1582,7.9,Cloud AI Solutions -AI00189,Data Analyst,357875,USD,357875,EX,PT,Norway,L,Norway,50,"Git, AWS, Linux, Tableau, Java",Associate,10,Retail,2024-01-19,2024-02-27,1044,8,Advanced Robotics -AI00190,AI Software Engineer,61953,USD,61953,SE,FT,India,L,India,50,"AWS, NLP, Tableau, SQL, PyTorch",Associate,8,Finance,2024-08-20,2024-10-14,1469,6.3,Advanced Robotics -AI00191,AI Product Manager,236982,USD,236982,EX,FL,Denmark,L,Poland,0,"AWS, Kubernetes, Tableau",Master,10,Gaming,2025-03-20,2025-04-03,597,5.1,Smart Analytics -AI00192,Principal Data Scientist,90203,EUR,76673,MI,PT,Austria,S,Austria,50,"Python, R, MLOps, GCP",PhD,3,Finance,2025-03-08,2025-05-12,1774,7.5,Autonomous Tech -AI00193,NLP Engineer,109984,JPY,12098240,SE,CT,Japan,S,Switzerland,0,"Data Visualization, Linux, SQL",Associate,7,Energy,2024-08-07,2024-08-31,1535,8,DeepTech Ventures -AI00194,AI Specialist,146371,CAD,182964,EX,PT,Canada,S,Ireland,100,"MLOps, Python, Scala, Docker",PhD,14,Healthcare,2024-11-15,2024-12-17,2313,5.4,Machine Intelligence Group -AI00195,Deep Learning Engineer,268088,EUR,227875,EX,PT,Netherlands,M,Netherlands,0,"NLP, AWS, Tableau, Scala, Computer Vision",Associate,10,Finance,2024-11-04,2024-12-21,1385,9.5,Predictive Systems -AI00196,Data Engineer,97647,GBP,73235,MI,CT,United Kingdom,S,Norway,50,"Java, Data Visualization, Scala, R",PhD,4,Government,2024-02-27,2024-04-08,1305,6.2,DeepTech Ventures -AI00197,Principal Data Scientist,221711,EUR,188454,EX,FT,Germany,S,Turkey,0,"TensorFlow, Kubernetes, NLP, PyTorch",Bachelor,17,Gaming,2025-01-14,2025-03-16,1652,8.9,Machine Intelligence Group -AI00198,Data Scientist,78716,EUR,66909,EN,PT,Germany,L,Germany,100,"Azure, Statistics, Kubernetes, Java",Bachelor,0,Automotive,2024-07-12,2024-08-13,2401,8.2,DataVision Ltd -AI00199,Principal Data Scientist,169717,CHF,152745,SE,CT,Switzerland,S,Switzerland,50,"Spark, Scala, PyTorch, Statistics",Master,5,Education,2024-03-07,2024-04-03,1003,9.5,DeepTech Ventures -AI00200,Data Analyst,92798,EUR,78878,MI,CT,Austria,L,Austria,50,"Linux, Kubernetes, SQL, Git",PhD,4,Consulting,2024-09-07,2024-11-12,1685,6.4,Neural Networks Co -AI00201,AI Product Manager,37177,USD,37177,MI,FL,China,S,China,0,"R, AWS, Hadoop, Spark",Associate,2,Automotive,2024-06-13,2024-08-25,869,6.1,Digital Transformation LLC -AI00202,Data Analyst,85505,USD,85505,MI,CT,Israel,S,Israel,50,"Java, Linux, R",Bachelor,4,Gaming,2025-01-21,2025-03-28,1983,5.1,Future Systems -AI00203,Robotics Engineer,113625,EUR,96581,MI,FT,France,L,France,100,"R, Python, Data Visualization, Scala",Associate,3,Automotive,2024-12-13,2025-01-02,2036,5.8,Advanced Robotics -AI00204,ML Ops Engineer,121846,AUD,164492,SE,PT,Australia,L,Australia,50,"NLP, AWS, Docker, Python",Master,6,Retail,2025-02-06,2025-04-20,2213,7.4,DeepTech Ventures -AI00205,Robotics Engineer,115136,JPY,12664960,MI,FT,Japan,M,Japan,50,"Scala, Python, Mathematics",Bachelor,3,Finance,2024-08-09,2024-09-03,1542,6.3,Neural Networks Co -AI00206,Data Scientist,265646,EUR,225799,EX,FT,France,L,Canada,0,"PyTorch, Computer Vision, SQL, AWS",Bachelor,16,Healthcare,2024-12-28,2025-01-11,1473,9.4,Predictive Systems -AI00207,AI Consultant,92726,CHF,83453,EN,FT,Switzerland,L,Switzerland,0,"Kubernetes, R, GCP, MLOps, Mathematics",Bachelor,0,Telecommunications,2024-09-22,2024-11-17,2013,9.8,AI Innovations -AI00208,Research Scientist,50607,USD,50607,EN,FL,Israel,S,Israel,100,"Azure, Tableau, Kubernetes, Deep Learning, Computer Vision",Bachelor,0,Telecommunications,2024-06-10,2024-08-05,1801,8.6,Autonomous Tech -AI00209,Machine Learning Researcher,219875,USD,219875,EX,PT,Sweden,L,Sweden,50,"NLP, Kubernetes, Tableau, Linux, R",Master,15,Automotive,2024-09-12,2024-11-15,1609,8.4,TechCorp Inc -AI00210,Robotics Engineer,93342,USD,93342,EX,CT,China,M,China,100,"Spark, Python, Azure",Master,11,Transportation,2025-02-15,2025-04-02,1345,7.2,AI Innovations -AI00211,Data Scientist,99132,EUR,84262,MI,FL,Netherlands,L,Netherlands,50,"Python, Linux, R",PhD,3,Government,2024-05-17,2024-06-15,2121,9.7,Advanced Robotics -AI00212,Data Analyst,148775,SGD,193408,SE,CT,Singapore,L,France,0,"Java, PyTorch, Scala",Associate,5,Real Estate,2024-01-07,2024-01-26,1222,6.3,Smart Analytics -AI00213,Data Scientist,63090,USD,63090,EN,CT,Denmark,S,Denmark,100,"AWS, MLOps, Python, Tableau, Azure",Master,0,Retail,2024-01-25,2024-03-18,1913,5.4,Neural Networks Co -AI00214,Robotics Engineer,39782,USD,39782,EN,CT,China,L,China,0,"Data Visualization, NLP, Python, R, Computer Vision",Bachelor,1,Transportation,2024-10-30,2025-01-04,2183,8.9,Quantum Computing Inc -AI00215,AI Architect,240915,CAD,301144,EX,PT,Canada,L,Canada,0,"TensorFlow, Java, MLOps",Master,14,Energy,2024-02-23,2024-04-17,1222,7.3,Advanced Robotics -AI00216,Robotics Engineer,69061,SGD,89779,MI,FL,Singapore,S,France,100,"Data Visualization, Linux, Tableau, Mathematics, Kubernetes",Master,4,Real Estate,2024-12-17,2025-02-01,1319,6.9,Future Systems -AI00217,Machine Learning Engineer,146403,EUR,124443,SE,PT,Netherlands,L,Netherlands,100,"Python, Scala, Java, Computer Vision, Azure",PhD,5,Gaming,2024-01-04,2024-02-07,1031,8.4,Algorithmic Solutions -AI00218,AI Consultant,56884,USD,56884,EN,CT,Finland,M,Finland,100,"Python, Mathematics, Tableau, Kubernetes",Bachelor,1,Government,2024-08-08,2024-08-24,532,9.1,Autonomous Tech -AI00219,AI Consultant,172277,CHF,155049,SE,PT,Switzerland,L,Switzerland,0,"Hadoop, Spark, Kubernetes, PyTorch, Azure",Bachelor,9,Technology,2024-08-09,2024-08-26,1725,9.7,Quantum Computing Inc -AI00220,Data Engineer,254054,EUR,215946,EX,CT,Austria,L,Austria,100,"R, Tableau, Data Visualization, Spark",Bachelor,17,Education,2024-09-26,2024-11-08,1518,9.8,Digital Transformation LLC -AI00221,Machine Learning Researcher,97442,EUR,82826,SE,FT,Germany,S,Germany,50,"Computer Vision, Linux, TensorFlow",PhD,5,Retail,2024-07-07,2024-08-01,1164,5.5,DataVision Ltd -AI00222,NLP Engineer,84037,USD,84037,EX,PT,China,S,China,50,"Computer Vision, NLP, GCP",Bachelor,19,Retail,2024-01-24,2024-02-12,2292,6,Autonomous Tech -AI00223,Principal Data Scientist,104614,EUR,88922,MI,CT,Netherlands,S,Netherlands,50,"SQL, Python, Linux, Computer Vision, Hadoop",Bachelor,4,Telecommunications,2024-10-10,2024-12-09,1895,7.9,Digital Transformation LLC -AI00224,Data Scientist,103566,USD,103566,SE,CT,Finland,S,Finland,100,"Git, Linux, Java, Statistics",Bachelor,7,Manufacturing,2024-01-09,2024-03-04,1777,8,Predictive Systems -AI00225,Autonomous Systems Engineer,69417,USD,69417,EN,CT,Ireland,L,Canada,50,"Data Visualization, Java, Docker, Kubernetes",Master,0,Energy,2024-04-22,2024-05-12,1887,9.4,Cloud AI Solutions -AI00226,AI Product Manager,27748,USD,27748,EN,FT,China,S,Israel,100,"NLP, Java, TensorFlow",Master,0,Automotive,2024-12-09,2025-02-03,1984,5.8,Autonomous Tech -AI00227,NLP Engineer,245370,USD,245370,EX,FL,Sweden,M,Sweden,100,"Tableau, Java, TensorFlow",Master,14,Real Estate,2024-03-17,2024-04-03,2030,8.4,Cognitive Computing -AI00228,AI Software Engineer,86794,JPY,9547340,MI,FL,Japan,S,Japan,50,"Scala, SQL, Hadoop, Statistics, GCP",Bachelor,4,Finance,2025-02-25,2025-04-25,1875,8.2,Cloud AI Solutions -AI00229,Computer Vision Engineer,58554,USD,58554,EN,FT,Ireland,S,Ireland,0,"Linux, Java, R, SQL, Mathematics",Master,1,Healthcare,2024-11-20,2024-12-22,2448,9.3,Cognitive Computing -AI00230,AI Specialist,152077,GBP,114058,SE,FT,United Kingdom,L,Canada,50,"Kubernetes, Git, Statistics",PhD,6,Automotive,2024-01-30,2024-03-20,2336,9.6,Cognitive Computing -AI00231,Data Scientist,152349,JPY,16758390,EX,FT,Japan,S,Japan,50,"MLOps, Scala, Java",Associate,10,Healthcare,2024-08-04,2024-09-30,1703,5.5,Quantum Computing Inc -AI00232,Deep Learning Engineer,155935,USD,155935,EX,FL,Israel,S,Ghana,50,"Python, Hadoop, Git",Associate,17,Retail,2025-03-25,2025-04-27,661,8.8,Predictive Systems -AI00233,Deep Learning Engineer,299354,CHF,269419,EX,FL,Switzerland,S,Switzerland,100,"MLOps, Scala, Docker",Bachelor,14,Retail,2024-06-16,2024-07-31,572,6.8,Advanced Robotics -AI00234,Autonomous Systems Engineer,112130,JPY,12334300,SE,FT,Japan,M,Japan,100,"SQL, Azure, Deep Learning",Associate,5,Energy,2024-03-14,2024-05-14,2021,9.4,Cognitive Computing -AI00235,AI Product Manager,299005,GBP,224254,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, MLOps, Statistics, Computer Vision",Master,16,Transportation,2024-06-17,2024-08-17,687,9.5,Cloud AI Solutions -AI00236,AI Product Manager,57697,JPY,6346670,EN,FL,Japan,M,Japan,100,"Python, TensorFlow, Deep Learning, MLOps",PhD,1,Energy,2024-03-23,2024-05-01,1370,9.7,DataVision Ltd -AI00237,Deep Learning Engineer,140199,SGD,182259,EX,FT,Singapore,S,Singapore,0,"Docker, Data Visualization, Python",Associate,18,Manufacturing,2025-03-26,2025-04-22,568,6.7,Predictive Systems -AI00238,Computer Vision Engineer,107028,USD,107028,EX,CT,China,M,Ghana,50,"Git, Linux, Statistics, Mathematics",PhD,11,Education,2024-10-29,2025-01-01,1172,5.8,Future Systems -AI00239,Data Analyst,48978,USD,48978,EN,FL,South Korea,M,Switzerland,50,"Computer Vision, Kubernetes, Git",Associate,1,Gaming,2024-02-21,2024-04-21,647,7.3,Future Systems -AI00240,Principal Data Scientist,101366,EUR,86161,MI,FL,France,M,France,100,"Python, Data Visualization, Linux, Azure",Master,3,Manufacturing,2025-01-04,2025-01-20,1292,6.7,DataVision Ltd -AI00241,AI Research Scientist,79125,EUR,67256,MI,CT,Netherlands,S,Netherlands,100,"Computer Vision, GCP, NLP, Statistics",PhD,4,Media,2024-03-05,2024-05-14,510,7.8,Smart Analytics -AI00242,Machine Learning Engineer,51110,USD,51110,SE,FL,China,S,China,50,"TensorFlow, Mathematics, Deep Learning, Computer Vision, R",Master,6,Automotive,2024-03-22,2024-05-06,1861,9.8,Cloud AI Solutions -AI00243,Data Scientist,96374,EUR,81918,MI,PT,Germany,S,Germany,0,"Deep Learning, SQL, Git, PyTorch",Associate,3,Retail,2024-05-08,2024-06-08,744,8.8,TechCorp Inc -AI00244,Autonomous Systems Engineer,92286,SGD,119972,EN,PT,Singapore,L,Singapore,100,"AWS, Java, Python, Mathematics",PhD,0,Energy,2025-02-04,2025-04-05,830,8.3,Advanced Robotics -AI00245,Data Scientist,102456,USD,102456,SE,FL,Sweden,S,Sweden,100,"PyTorch, Git, R, Azure",PhD,7,Education,2024-08-31,2024-11-12,552,6.9,Algorithmic Solutions -AI00246,ML Ops Engineer,138420,USD,138420,EX,CT,Sweden,M,Sweden,50,"PyTorch, Docker, Data Visualization, GCP, TensorFlow",PhD,17,Transportation,2024-02-13,2024-03-21,1582,5.3,DataVision Ltd -AI00247,AI Software Engineer,203654,CAD,254568,EX,PT,Canada,L,Canada,100,"SQL, Kubernetes, Computer Vision, GCP",PhD,12,Retail,2024-01-19,2024-03-23,1049,8.1,Advanced Robotics -AI00248,Robotics Engineer,121706,EUR,103450,SE,FT,Austria,L,Austria,50,"Hadoop, Data Visualization, Python, TensorFlow, Mathematics",PhD,8,Real Estate,2024-12-31,2025-02-23,2066,9.1,Neural Networks Co -AI00249,AI Software Engineer,112939,SGD,146821,SE,CT,Singapore,S,Netherlands,0,"R, Azure, Computer Vision, Deep Learning",PhD,9,Consulting,2024-10-30,2024-11-21,2008,10,Smart Analytics -AI00250,AI Software Engineer,223145,EUR,189673,EX,CT,Germany,L,Brazil,50,"Kubernetes, Scala, MLOps, Statistics",Bachelor,19,Energy,2024-01-02,2024-01-26,2356,7.1,AI Innovations -AI00251,Data Engineer,198959,AUD,268595,EX,FT,Australia,M,Australia,0,"Spark, Python, Deep Learning, TensorFlow, Mathematics",Master,11,Telecommunications,2025-03-11,2025-04-04,1821,7.1,Neural Networks Co -AI00252,Machine Learning Engineer,249841,USD,249841,EX,CT,United States,M,United States,100,"Scala, Linux, Java, Data Visualization",Associate,14,Healthcare,2024-01-08,2024-01-29,2130,7,Machine Intelligence Group -AI00253,AI Architect,81300,CHF,73170,EN,CT,Switzerland,S,Switzerland,0,"SQL, Python, Scala",Master,0,Energy,2024-04-26,2024-06-02,1225,9,AI Innovations -AI00254,Machine Learning Engineer,89201,USD,89201,EX,CT,China,L,Colombia,0,"Kubernetes, Mathematics, Data Visualization, SQL",Master,16,Gaming,2025-02-15,2025-03-15,1146,5.7,TechCorp Inc -AI00255,Robotics Engineer,123827,CHF,111444,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, GCP, AWS, SQL, NLP",Master,4,Telecommunications,2025-01-14,2025-03-11,543,8.3,Quantum Computing Inc -AI00256,AI Product Manager,321014,USD,321014,EX,FL,Denmark,M,Denmark,100,"Hadoop, Scala, MLOps",Master,16,Finance,2024-04-02,2024-06-13,1990,5.3,Neural Networks Co -AI00257,ML Ops Engineer,195690,USD,195690,EX,PT,Ireland,L,Ireland,100,"Azure, Kubernetes, PyTorch",Associate,11,Education,2024-01-15,2024-03-12,1481,6.2,Neural Networks Co -AI00258,AI Software Engineer,88109,SGD,114542,MI,FL,Singapore,M,South Korea,100,"SQL, Hadoop, Tableau, Spark",Bachelor,2,Government,2025-03-24,2025-06-01,2164,9.9,AI Innovations -AI00259,Deep Learning Engineer,93310,EUR,79314,SE,PT,Germany,S,Germany,0,"TensorFlow, Statistics, Mathematics",Associate,8,Retail,2024-08-24,2024-10-22,1732,5.5,Smart Analytics -AI00260,Deep Learning Engineer,180162,EUR,153138,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, Java, Spark, NLP",Associate,12,Technology,2024-03-06,2024-04-29,2049,9.7,Autonomous Tech -AI00261,Deep Learning Engineer,324764,CHF,292288,EX,PT,Switzerland,M,Switzerland,0,"TensorFlow, Kubernetes, Docker, Tableau, Scala",Associate,14,Manufacturing,2024-08-05,2024-10-03,1915,8.2,Quantum Computing Inc -AI00262,AI Consultant,57105,SGD,74237,EN,FT,Singapore,M,India,0,"Scala, Data Visualization, Python, GCP",Associate,1,Telecommunications,2024-05-26,2024-08-01,2453,6.9,DataVision Ltd -AI00263,Research Scientist,131121,USD,131121,EX,PT,Finland,M,South Africa,100,"Data Visualization, R, Kubernetes",Bachelor,11,Education,2024-10-02,2024-12-04,1707,7.3,Digital Transformation LLC -AI00264,NLP Engineer,87993,USD,87993,SE,FL,Israel,S,Netherlands,50,"MLOps, Deep Learning, Azure, Kubernetes",Associate,6,Real Estate,2024-11-10,2025-01-04,1598,9.4,Cognitive Computing -AI00265,Data Analyst,77654,EUR,66006,EN,CT,Austria,L,Austria,50,"PyTorch, Hadoop, Tableau, Docker",Associate,1,Retail,2024-10-11,2024-12-03,1681,7.7,Neural Networks Co -AI00266,Machine Learning Engineer,47769,AUD,64488,EN,PT,Australia,S,Australia,50,"Java, Python, Data Visualization, Docker",Master,1,Transportation,2024-02-24,2024-04-01,2173,5.2,Neural Networks Co -AI00267,NLP Engineer,112750,GBP,84563,SE,PT,United Kingdom,S,United Kingdom,100,"Git, Statistics, Spark",Master,8,Real Estate,2024-04-14,2024-05-15,529,5.5,Predictive Systems -AI00268,AI Architect,63413,USD,63413,EN,PT,Denmark,S,Denmark,0,"Tableau, Hadoop, Statistics, MLOps",Associate,0,Gaming,2024-06-11,2024-08-09,2014,7.5,DataVision Ltd -AI00269,Robotics Engineer,96518,EUR,82040,SE,FT,Austria,S,Norway,0,"GCP, Deep Learning, Java, Statistics, Spark",Bachelor,5,Automotive,2024-02-20,2024-04-23,702,8.4,TechCorp Inc -AI00270,AI Research Scientist,136768,USD,136768,MI,PT,Norway,M,Norway,50,"Python, Java, SQL",Bachelor,4,Healthcare,2025-03-08,2025-04-01,2160,9.5,Smart Analytics -AI00271,Research Scientist,143660,CAD,179575,SE,FL,Canada,L,Canada,100,"Statistics, Java, Data Visualization, Azure",Master,8,Education,2024-01-22,2024-03-07,1728,6.7,Algorithmic Solutions -AI00272,Data Engineer,122612,SGD,159396,SE,FT,Singapore,S,Singapore,50,"GCP, Azure, Tableau, Computer Vision, Scala",Associate,9,Media,2024-10-26,2024-11-12,1794,5.8,TechCorp Inc -AI00273,Principal Data Scientist,224629,AUD,303249,EX,FL,Australia,S,Australia,100,"R, SQL, Kubernetes, Statistics, Linux",Master,15,Healthcare,2024-07-14,2024-07-31,2418,9.6,Cognitive Computing -AI00274,Computer Vision Engineer,110517,EUR,93939,SE,FT,France,L,France,50,"Python, TensorFlow, Hadoop, R",PhD,7,Manufacturing,2024-10-17,2024-11-27,2208,8.2,Advanced Robotics -AI00275,Robotics Engineer,78533,SGD,102093,EN,CT,Singapore,M,Singapore,100,"Deep Learning, Spark, Git",Bachelor,0,Government,2024-10-22,2024-12-24,1972,5.7,Future Systems -AI00276,Head of AI,282152,CHF,253937,EX,CT,Switzerland,S,United Kingdom,50,"Spark, Kubernetes, SQL",PhD,15,Energy,2024-03-23,2024-06-03,678,7,DeepTech Ventures -AI00277,Data Scientist,240352,CHF,216317,EX,CT,Switzerland,M,Switzerland,50,"TensorFlow, Spark, Computer Vision",PhD,18,Automotive,2024-06-24,2024-08-02,886,6.8,Cognitive Computing -AI00278,Computer Vision Engineer,87353,CHF,78618,EN,FL,Switzerland,M,Switzerland,50,"Java, Git, AWS",Associate,0,Technology,2025-03-17,2025-04-01,2072,7.5,DataVision Ltd -AI00279,Research Scientist,201368,EUR,171163,EX,FL,Austria,M,Austria,100,"Git, PyTorch, NLP",Associate,10,Transportation,2024-02-16,2024-03-15,2032,6.4,Cognitive Computing -AI00280,AI Consultant,102371,USD,102371,MI,FT,Sweden,M,Sweden,50,"Scala, Java, Linux, AWS",Associate,3,Telecommunications,2024-12-29,2025-02-22,2442,6.5,Cloud AI Solutions -AI00281,Machine Learning Engineer,160729,USD,160729,MI,FT,Denmark,L,Denmark,50,"Python, TensorFlow, Kubernetes, Mathematics, MLOps",PhD,3,Government,2024-03-22,2024-04-12,660,7.8,Cognitive Computing -AI00282,Data Analyst,127341,USD,127341,SE,CT,Ireland,L,Finland,0,"Python, Linux, TensorFlow, Java",Associate,8,Manufacturing,2025-01-07,2025-01-28,1241,6.4,Cognitive Computing -AI00283,AI Product Manager,132125,EUR,112306,SE,FT,Netherlands,L,Netherlands,50,"Deep Learning, Computer Vision, Tableau",Associate,6,Manufacturing,2024-06-13,2024-08-11,1042,7,Advanced Robotics -AI00284,Data Scientist,106892,CAD,133615,MI,PT,Canada,L,Canada,100,"MLOps, Python, Computer Vision, AWS",PhD,2,Gaming,2025-01-18,2025-03-19,2323,5.5,Digital Transformation LLC -AI00285,Machine Learning Researcher,101740,EUR,86479,MI,CT,Germany,L,Germany,100,"Scala, Python, Tableau",Master,3,Finance,2024-08-22,2024-09-18,1429,8.8,DeepTech Ventures -AI00286,Machine Learning Researcher,48965,USD,48965,MI,PT,China,M,China,0,"Python, TensorFlow, Spark, GCP",Bachelor,2,Automotive,2024-11-01,2024-12-26,1541,5.9,Future Systems -AI00287,Autonomous Systems Engineer,53173,USD,53173,EN,FL,Sweden,S,Sweden,50,"TensorFlow, Kubernetes, Python, Data Visualization, GCP",Master,0,Telecommunications,2024-02-09,2024-04-20,1299,8.3,Machine Intelligence Group -AI00288,Computer Vision Engineer,201645,EUR,171398,EX,PT,Netherlands,S,Netherlands,100,"Scala, Kubernetes, Data Visualization",Associate,17,Real Estate,2024-12-11,2025-01-11,1871,9.2,DataVision Ltd -AI00289,Robotics Engineer,47718,USD,47718,MI,FT,China,L,China,100,"R, Kubernetes, AWS, SQL, TensorFlow",Master,3,Retail,2025-01-03,2025-02-09,649,6.2,Neural Networks Co -AI00290,AI Architect,358613,USD,358613,EX,FL,Norway,L,Norway,0,"AWS, Java, Statistics",PhD,16,Telecommunications,2024-08-06,2024-09-17,1555,9.6,Autonomous Tech -AI00291,AI Product Manager,96280,USD,96280,EN,FL,United States,L,United States,50,"Spark, MLOps, SQL, PyTorch, Computer Vision",Bachelor,0,Technology,2024-10-13,2024-12-15,2353,6.2,Digital Transformation LLC -AI00292,ML Ops Engineer,87032,USD,87032,SE,PT,South Korea,S,Netherlands,50,"PyTorch, Linux, Deep Learning",Master,7,Manufacturing,2024-11-13,2025-01-02,1397,5.5,Algorithmic Solutions -AI00293,AI Architect,112059,JPY,12326490,SE,FT,Japan,S,Japan,50,"Docker, Python, Kubernetes, GCP, TensorFlow",Bachelor,9,Education,2024-06-21,2024-08-23,1799,7.3,Machine Intelligence Group -AI00294,AI Specialist,115102,EUR,97837,SE,FT,Austria,L,Austria,100,"Python, Linux, Kubernetes, Hadoop",PhD,7,Automotive,2024-05-10,2024-07-19,2334,9.2,DeepTech Ventures -AI00295,AI Specialist,271779,USD,271779,EX,CT,Ireland,L,Ireland,50,"Computer Vision, Azure, Data Visualization, NLP",Master,11,Automotive,2025-02-06,2025-03-23,1247,9,Cloud AI Solutions -AI00296,AI Research Scientist,66364,CAD,82955,MI,PT,Canada,S,Colombia,50,"Python, SQL, NLP",Bachelor,3,Gaming,2024-08-18,2024-09-01,1891,6.6,AI Innovations -AI00297,Deep Learning Engineer,131466,USD,131466,MI,PT,Norway,L,Norway,50,"R, AWS, Hadoop, NLP, Spark",PhD,2,Automotive,2024-01-02,2024-01-25,1013,7.9,TechCorp Inc -AI00298,Head of AI,42235,USD,42235,EN,FT,South Korea,S,Ghana,100,"Python, Data Visualization, Kubernetes",PhD,1,Government,2024-04-19,2024-06-27,2078,6.4,DeepTech Ventures -AI00299,Deep Learning Engineer,55844,EUR,47467,EN,FL,Netherlands,M,Estonia,50,"Java, NLP, Python, Deep Learning, Computer Vision",PhD,1,Transportation,2024-05-04,2024-07-10,976,7.9,Quantum Computing Inc -AI00300,Machine Learning Researcher,75499,USD,75499,EN,FT,Sweden,L,Sweden,0,"GCP, Linux, Deep Learning, Java, Kubernetes",PhD,1,Education,2024-10-02,2024-10-27,2054,9.6,Future Systems -AI00301,AI Architect,84962,SGD,110451,EN,CT,Singapore,L,Israel,50,"GCP, Data Visualization, Azure",Associate,1,Finance,2024-05-15,2024-06-29,1804,6.2,TechCorp Inc -AI00302,Data Analyst,144336,CHF,129902,MI,CT,Switzerland,M,Switzerland,0,"Data Visualization, Java, Mathematics, AWS",Bachelor,3,Gaming,2025-02-06,2025-03-30,1336,7.8,Machine Intelligence Group -AI00303,AI Consultant,52300,USD,52300,SE,PT,China,S,China,100,"Docker, TensorFlow, GCP",Bachelor,8,Consulting,2024-03-10,2024-04-19,800,9.1,DataVision Ltd -AI00304,Data Engineer,157426,EUR,133812,EX,PT,Austria,S,Turkey,100,"Scala, Tableau, Java",PhD,13,Manufacturing,2025-04-07,2025-05-16,1741,6.2,Cloud AI Solutions -AI00305,Deep Learning Engineer,174692,USD,174692,EX,CT,South Korea,M,Portugal,100,"Linux, Python, TensorFlow",PhD,12,Automotive,2025-04-20,2025-06-27,731,7.9,Autonomous Tech -AI00306,NLP Engineer,142293,USD,142293,MI,PT,Norway,L,Sweden,50,"Git, Java, Deep Learning, Linux, Mathematics",Master,2,Energy,2025-04-05,2025-06-01,1398,7.1,Quantum Computing Inc -AI00307,AI Architect,109818,USD,109818,SE,FL,South Korea,S,South Korea,0,"GCP, Git, Statistics",PhD,9,Consulting,2024-01-04,2024-02-02,2344,5,Advanced Robotics -AI00308,AI Research Scientist,69642,USD,69642,EN,FT,Norway,M,Norway,0,"Java, SQL, Scala, PyTorch, NLP",Master,0,Automotive,2024-01-19,2024-03-31,583,7.9,AI Innovations -AI00309,Principal Data Scientist,70652,EUR,60054,MI,FL,Netherlands,S,Netherlands,50,"Computer Vision, Scala, Mathematics",Master,2,Media,2024-10-30,2024-12-30,1086,9.1,Advanced Robotics -AI00310,Data Analyst,242235,GBP,181676,EX,FL,United Kingdom,L,United Kingdom,100,"R, PyTorch, Docker",Master,12,Education,2024-12-18,2025-03-01,2038,6,Machine Intelligence Group -AI00311,AI Architect,211982,SGD,275577,EX,FT,Singapore,S,Singapore,50,"Hadoop, AWS, Docker",PhD,19,Manufacturing,2024-01-12,2024-02-18,1352,6.8,Machine Intelligence Group -AI00312,Principal Data Scientist,88077,EUR,74865,EN,FL,Germany,L,Germany,100,"Python, GCP, TensorFlow, Mathematics, PyTorch",Bachelor,1,Transportation,2024-02-20,2024-04-18,986,8.2,Machine Intelligence Group -AI00313,Robotics Engineer,107261,EUR,91172,MI,CT,Germany,L,Germany,50,"Hadoop, Tableau, Java, Git",Associate,3,Manufacturing,2024-10-19,2024-11-04,1617,9.7,AI Innovations -AI00314,Computer Vision Engineer,284132,USD,284132,EX,FT,United States,M,United States,0,"Deep Learning, Docker, Hadoop, Data Visualization",Master,10,Government,2025-04-24,2025-07-06,1832,5.1,Autonomous Tech -AI00315,AI Software Engineer,105482,USD,105482,SE,CT,South Korea,M,South Korea,100,"SQL, Git, AWS",PhD,5,Consulting,2025-02-13,2025-04-25,1845,5.9,Cognitive Computing -AI00316,AI Architect,161728,GBP,121296,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, PyTorch",PhD,15,Finance,2025-03-03,2025-04-19,1932,8.6,DataVision Ltd -AI00317,Data Engineer,131352,USD,131352,SE,PT,Norway,S,Sweden,0,"Scala, MLOps, GCP, Java",Bachelor,9,Retail,2024-11-02,2024-12-13,1802,5.8,Machine Intelligence Group -AI00318,Data Analyst,161727,EUR,137468,SE,FT,Austria,L,Finland,100,"Docker, GCP, SQL",PhD,6,Technology,2025-01-26,2025-04-04,1940,5.9,Cognitive Computing -AI00319,Data Analyst,151527,USD,151527,SE,FL,United States,L,Romania,0,"Java, SQL, Kubernetes, Git",PhD,7,Retail,2024-07-18,2024-09-02,845,7.1,Machine Intelligence Group -AI00320,Machine Learning Researcher,112476,USD,112476,SE,FT,Israel,L,Israel,50,"Hadoop, Git, Statistics",Master,6,Consulting,2024-04-20,2024-05-10,2413,8.7,TechCorp Inc -AI00321,ML Ops Engineer,72913,CAD,91141,MI,FT,Canada,M,Canada,0,"R, SQL, Mathematics",PhD,3,Telecommunications,2025-04-01,2025-05-31,941,7,Cognitive Computing -AI00322,Data Analyst,68734,CAD,85918,EN,FT,Canada,L,Malaysia,100,"Computer Vision, Python, TensorFlow, Docker",PhD,1,Finance,2024-08-28,2024-10-24,805,8.5,Algorithmic Solutions -AI00323,NLP Engineer,179564,EUR,152629,EX,FL,Netherlands,S,Netherlands,50,"Python, AWS, Git",Bachelor,11,Government,2024-01-24,2024-03-17,654,9.1,Quantum Computing Inc -AI00324,Data Scientist,71265,GBP,53449,EN,PT,United Kingdom,S,United Kingdom,0,"PyTorch, TensorFlow, Azure, Computer Vision, Java",Bachelor,1,Automotive,2024-03-27,2024-05-12,2172,9.5,DeepTech Ventures -AI00325,Deep Learning Engineer,143064,USD,143064,SE,FL,South Korea,L,Denmark,100,"Scala, Python, TensorFlow",Master,8,Telecommunications,2024-02-26,2024-04-13,1887,7.2,DataVision Ltd -AI00326,Deep Learning Engineer,196042,EUR,166636,EX,CT,Austria,L,Italy,0,"Kubernetes, PyTorch, Tableau, Docker, Computer Vision",PhD,14,Consulting,2025-02-14,2025-03-20,911,7.3,Advanced Robotics -AI00327,Data Engineer,101946,USD,101946,SE,FL,Ireland,S,Ireland,0,"SQL, PyTorch, Data Visualization, Computer Vision",Bachelor,7,Finance,2025-02-14,2025-04-20,1521,7.1,Digital Transformation LLC -AI00328,Autonomous Systems Engineer,89020,GBP,66765,MI,FL,United Kingdom,S,Brazil,50,"Kubernetes, R, Git, AWS",PhD,4,Media,2024-09-06,2024-10-27,1497,9.2,Algorithmic Solutions -AI00329,Autonomous Systems Engineer,134011,JPY,14741210,SE,PT,Japan,S,Israel,100,"Deep Learning, Statistics, Spark",PhD,9,Energy,2024-08-10,2024-09-15,2405,8.8,TechCorp Inc -AI00330,Data Analyst,97657,SGD,126954,MI,CT,Singapore,M,Singapore,100,"Scala, Git, MLOps",Master,2,Gaming,2024-08-28,2024-09-15,2240,8.9,Predictive Systems -AI00331,Deep Learning Engineer,153990,USD,153990,EX,PT,South Korea,M,Luxembourg,50,"Scala, Git, Deep Learning, SQL, Kubernetes",Bachelor,14,Consulting,2024-06-29,2024-08-12,1020,5.7,Algorithmic Solutions -AI00332,Robotics Engineer,124696,EUR,105992,SE,FT,Netherlands,S,Argentina,100,"PyTorch, Python, Computer Vision",PhD,6,Automotive,2024-05-17,2024-07-09,1117,5.5,TechCorp Inc -AI00333,Robotics Engineer,94884,USD,94884,MI,PT,Ireland,S,Ireland,0,"Linux, Hadoop, GCP",Bachelor,2,Retail,2024-11-06,2024-12-19,961,9.2,Cognitive Computing -AI00334,AI Architect,101192,CHF,91073,EN,FT,Switzerland,M,Switzerland,50,"R, Scala, Kubernetes, Git",PhD,0,Transportation,2024-12-28,2025-01-28,1793,5.8,DeepTech Ventures -AI00335,AI Product Manager,106624,USD,106624,SE,FT,Ireland,M,Ireland,100,"Git, Statistics, Azure",Associate,6,Telecommunications,2025-02-02,2025-02-25,2175,5.2,Cognitive Computing -AI00336,Data Scientist,187401,GBP,140551,EX,FT,United Kingdom,M,Germany,100,"TensorFlow, Docker, Spark, Python",Bachelor,12,Energy,2024-10-24,2024-11-11,1400,9.5,TechCorp Inc -AI00337,Data Analyst,165694,USD,165694,EX,FL,United States,M,United States,100,"Python, Kubernetes, MLOps",Associate,15,Retail,2024-01-04,2024-03-15,2434,8.8,DataVision Ltd -AI00338,Machine Learning Engineer,122206,USD,122206,SE,FL,United States,M,United States,50,"Spark, AWS, Linux, SQL, PyTorch",Bachelor,6,Healthcare,2024-01-31,2024-03-06,2282,9.2,Algorithmic Solutions -AI00339,Data Engineer,91226,SGD,118594,MI,PT,Singapore,L,India,0,"Python, TensorFlow, PyTorch, SQL",Bachelor,2,Transportation,2024-12-06,2025-01-16,519,7.7,Autonomous Tech -AI00340,AI Product Manager,110449,CHF,99404,MI,FL,Switzerland,S,Switzerland,100,"Mathematics, Linux, NLP",Bachelor,3,Energy,2025-02-01,2025-02-19,1970,5.9,Algorithmic Solutions -AI00341,AI Architect,275705,EUR,234349,EX,FT,Netherlands,L,Netherlands,100,"MLOps, SQL, Kubernetes, Spark, Java",Bachelor,16,Finance,2024-04-25,2024-05-29,2299,5.4,Future Systems -AI00342,ML Ops Engineer,161670,USD,161670,EX,PT,Finland,M,Brazil,0,"MLOps, Python, TensorFlow, GCP",Associate,11,Technology,2024-08-13,2024-09-18,1061,5.9,Machine Intelligence Group -AI00343,Computer Vision Engineer,95328,GBP,71496,MI,PT,United Kingdom,S,United Kingdom,50,"MLOps, Spark, Git, Deep Learning",PhD,3,Technology,2025-03-25,2025-04-26,734,8.5,Smart Analytics -AI00344,AI Consultant,68548,EUR,58266,EN,PT,Germany,M,Germany,0,"Hadoop, Spark, Statistics, Tableau",Associate,1,Transportation,2025-02-24,2025-03-26,1762,7.8,Digital Transformation LLC -AI00345,AI Consultant,378502,USD,378502,EX,FT,Denmark,L,Denmark,0,"SQL, Mathematics, Scala, Hadoop",Bachelor,12,Consulting,2024-09-29,2024-12-01,2234,8.4,Future Systems -AI00346,NLP Engineer,76682,USD,76682,SE,CT,South Korea,S,South Korea,0,"PyTorch, Kubernetes, Azure, GCP",Master,7,Gaming,2024-09-25,2024-11-12,643,10,Machine Intelligence Group -AI00347,Deep Learning Engineer,108478,USD,108478,MI,CT,Sweden,L,Sweden,0,"Hadoop, Java, Docker, Deep Learning",Master,2,Transportation,2024-04-24,2024-05-10,1436,9.4,Cognitive Computing -AI00348,Research Scientist,114526,JPY,12597860,MI,FL,Japan,M,Belgium,0,"Python, TensorFlow, SQL, NLP",Associate,3,Real Estate,2024-02-16,2024-03-05,1095,5.8,Future Systems -AI00349,AI Specialist,75609,USD,75609,EN,PT,Norway,S,Norway,0,"AWS, Python, Git, Statistics",PhD,0,Government,2024-09-19,2024-11-30,2109,9.9,Algorithmic Solutions -AI00350,Data Analyst,214389,USD,214389,SE,FL,Denmark,L,Denmark,100,"Java, Kubernetes, Python, SQL",Associate,6,Retail,2025-04-29,2025-06-13,2348,8.8,Smart Analytics -AI00351,NLP Engineer,104396,USD,104396,SE,CT,Finland,S,Finland,100,"SQL, Azure, Data Visualization, NLP",Master,7,Telecommunications,2024-08-13,2024-10-15,1398,5.3,Quantum Computing Inc -AI00352,Principal Data Scientist,53469,EUR,45449,EN,PT,France,M,United Kingdom,50,"Docker, Statistics, Data Visualization",PhD,0,Government,2024-01-10,2024-02-20,1249,6,Smart Analytics -AI00353,Head of AI,327929,USD,327929,EX,FL,Denmark,L,Denmark,0,"TensorFlow, Python, Data Visualization, NLP, Tableau",PhD,14,Transportation,2024-02-19,2024-04-14,1000,6.5,Smart Analytics -AI00354,Data Scientist,87984,JPY,9678240,MI,PT,Japan,S,Japan,100,"Computer Vision, Git, Tableau, Data Visualization",Bachelor,2,Consulting,2024-01-08,2024-02-19,560,7.4,Algorithmic Solutions -AI00355,AI Architect,127823,JPY,14060530,SE,CT,Japan,S,Japan,0,"Linux, MLOps, Tableau",Associate,8,Automotive,2025-04-17,2025-05-24,1762,7.3,Future Systems -AI00356,Machine Learning Researcher,93295,AUD,125948,MI,FL,Australia,M,Australia,0,"Spark, Mathematics, Linux",Associate,4,Education,2024-02-10,2024-04-04,582,5.1,Algorithmic Solutions -AI00357,NLP Engineer,25560,USD,25560,MI,PT,India,M,India,50,"Kubernetes, Linux, Tableau, Mathematics",Master,2,Transportation,2024-02-29,2024-04-02,1775,7.5,Cognitive Computing -AI00358,Deep Learning Engineer,110777,GBP,83083,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, Python, GCP",PhD,3,Transportation,2024-07-10,2024-08-31,1446,8.5,Quantum Computing Inc -AI00359,AI Specialist,253223,EUR,215240,EX,FL,Germany,M,Germany,0,"Scala, Kubernetes, SQL, Hadoop, Docker",Bachelor,17,Retail,2024-07-24,2024-08-27,1970,5,Algorithmic Solutions -AI00360,ML Ops Engineer,234867,EUR,199637,EX,PT,Netherlands,M,Israel,0,"Spark, Statistics, MLOps, R",PhD,10,Automotive,2024-11-18,2024-12-27,826,5.1,Digital Transformation LLC -AI00361,AI Consultant,49385,USD,49385,EN,FT,Finland,S,Finland,50,"NLP, Statistics, Hadoop",Master,0,Media,2025-03-28,2025-04-13,1111,6.6,Advanced Robotics -AI00362,Data Scientist,59557,USD,59557,SE,CT,China,L,Denmark,100,"PyTorch, GCP, NLP, Spark",Bachelor,8,Telecommunications,2024-03-26,2024-06-06,977,6.3,TechCorp Inc -AI00363,AI Product Manager,95864,EUR,81484,SE,PT,France,S,France,0,"SQL, Hadoop, Tableau, Data Visualization",Master,6,Energy,2024-01-22,2024-03-27,1764,7.6,Predictive Systems -AI00364,AI Product Manager,217693,USD,217693,EX,PT,Israel,L,Israel,0,"GCP, MLOps, Scala, Kubernetes, Docker",Associate,18,Transportation,2024-04-15,2024-05-19,1099,9.7,Digital Transformation LLC -AI00365,ML Ops Engineer,108994,EUR,92645,MI,FL,France,L,France,100,"Kubernetes, Mathematics, Scala",Associate,2,Energy,2024-07-24,2024-08-31,1864,9.9,AI Innovations -AI00366,AI Software Engineer,75633,USD,75633,MI,FT,South Korea,S,Ghana,100,"Scala, Linux, NLP, R, Computer Vision",Associate,4,Gaming,2024-06-07,2024-06-27,1965,8.1,Advanced Robotics -AI00367,AI Research Scientist,62810,EUR,53389,EN,FL,Germany,S,Germany,100,"Deep Learning, Python, Tableau, Computer Vision, Statistics",Associate,0,Automotive,2025-02-13,2025-04-05,1004,9.7,Predictive Systems -AI00368,Data Engineer,151628,EUR,128884,EX,FT,France,S,France,100,"Python, TensorFlow, Java",Bachelor,15,Real Estate,2024-08-02,2024-09-30,539,8.3,AI Innovations -AI00369,AI Research Scientist,125355,SGD,162962,SE,FL,Singapore,M,Singapore,100,"Docker, NLP, AWS",Master,9,Transportation,2025-02-27,2025-05-07,2194,9.7,Quantum Computing Inc -AI00370,Principal Data Scientist,136102,USD,136102,SE,PT,Denmark,M,Denmark,100,"Linux, PyTorch, Tableau, Mathematics",PhD,7,Telecommunications,2024-03-08,2024-04-08,1973,5.1,Machine Intelligence Group -AI00371,Deep Learning Engineer,56934,EUR,48394,EN,PT,France,L,France,0,"Git, SQL, NLP, PyTorch",PhD,0,Automotive,2024-02-07,2024-03-26,1672,6.9,Advanced Robotics -AI00372,ML Ops Engineer,67190,EUR,57112,MI,FL,France,S,Italy,50,"Scala, Tableau, Python, Docker, Hadoop",Master,4,Gaming,2024-02-18,2024-04-06,1470,8.3,AI Innovations -AI00373,AI Software Engineer,125164,EUR,106389,SE,FL,Austria,L,Austria,50,"Azure, Deep Learning, MLOps, Linux",PhD,9,Transportation,2024-06-26,2024-08-24,2025,5.1,TechCorp Inc -AI00374,NLP Engineer,85407,SGD,111029,EN,PT,Singapore,L,Singapore,50,"Statistics, GCP, AWS, SQL",Master,1,Media,2024-07-08,2024-09-17,646,8.2,Autonomous Tech -AI00375,ML Ops Engineer,112057,JPY,12326270,SE,FL,Japan,S,Japan,0,"Python, TensorFlow, PyTorch, SQL, Deep Learning",Master,7,Manufacturing,2025-03-13,2025-04-03,789,8.5,Neural Networks Co -AI00376,ML Ops Engineer,95078,USD,95078,MI,CT,Denmark,M,Denmark,0,"SQL, MLOps, Scala",Bachelor,3,Automotive,2025-02-26,2025-04-21,1839,5.7,Quantum Computing Inc -AI00377,AI Product Manager,198651,USD,198651,EX,CT,Norway,M,Norway,100,"SQL, Spark, TensorFlow, Deep Learning, Kubernetes",Bachelor,18,Retail,2024-05-08,2024-05-27,2463,5.7,DeepTech Ventures -AI00378,AI Software Engineer,220998,JPY,24309780,EX,CT,Japan,S,India,50,"SQL, Linux, Tableau, Azure, Scala",Bachelor,12,Education,2024-05-04,2024-06-16,731,7.3,Cloud AI Solutions -AI00379,NLP Engineer,74126,USD,74126,EX,FT,India,S,India,100,"Scala, PyTorch, Docker, Deep Learning, SQL",PhD,12,Government,2024-09-22,2024-10-29,1926,7.5,Predictive Systems -AI00380,Machine Learning Engineer,75172,EUR,63896,MI,CT,Austria,S,Austria,100,"SQL, Kubernetes, Docker, NLP",Associate,4,Media,2024-09-09,2024-11-15,2261,8.5,Cognitive Computing -AI00381,Deep Learning Engineer,60975,EUR,51829,EN,FT,Austria,L,Austria,100,"SQL, Hadoop, Tableau, Kubernetes",Master,1,Transportation,2024-11-21,2025-01-29,620,9.6,Cloud AI Solutions -AI00382,Principal Data Scientist,89175,EUR,75799,MI,FT,Germany,L,Singapore,0,"Computer Vision, AWS, GCP, Deep Learning, Spark",PhD,2,Manufacturing,2024-01-11,2024-02-21,2215,8.9,Digital Transformation LLC -AI00383,Computer Vision Engineer,149285,EUR,126892,SE,FL,Netherlands,L,Netherlands,50,"Python, Mathematics, Kubernetes",PhD,5,Education,2025-01-06,2025-03-02,1359,5.4,Predictive Systems -AI00384,AI Product Manager,192204,EUR,163373,EX,FT,Germany,M,Germany,0,"Mathematics, Linux, SQL",Bachelor,13,Media,2025-02-01,2025-03-10,1161,6.7,Future Systems -AI00385,NLP Engineer,94197,CHF,84777,MI,PT,Switzerland,S,Norway,100,"Spark, TensorFlow, Deep Learning, GCP",Associate,4,Finance,2024-09-28,2024-10-28,1172,5.3,Future Systems -AI00386,Autonomous Systems Engineer,90408,EUR,76847,EN,FL,Germany,L,Czech Republic,100,"Linux, SQL, Git",PhD,1,Technology,2024-01-25,2024-03-10,892,7.1,Autonomous Tech -AI00387,ML Ops Engineer,72940,USD,72940,MI,FT,Ireland,S,Czech Republic,0,"GCP, Hadoop, Java",PhD,3,Technology,2024-03-24,2024-05-07,1913,8.1,DeepTech Ventures -AI00388,Machine Learning Engineer,140696,JPY,15476560,SE,PT,Japan,S,Japan,0,"AWS, Java, GCP",Master,9,Real Estate,2024-04-03,2024-04-25,1774,5.6,Neural Networks Co -AI00389,Robotics Engineer,210902,CHF,189812,EX,FT,Switzerland,S,Switzerland,0,"Java, NLP, TensorFlow, PyTorch, Git",Bachelor,12,Real Estate,2024-09-25,2024-11-28,982,9.8,Cognitive Computing -AI00390,Computer Vision Engineer,78559,SGD,102127,EN,FL,Singapore,M,Singapore,100,"Python, PyTorch, Computer Vision",Bachelor,0,Automotive,2024-12-03,2025-01-13,586,5,AI Innovations -AI00391,AI Consultant,32923,USD,32923,MI,FT,India,M,India,50,"Kubernetes, MLOps, PyTorch, Linux, AWS",Master,4,Gaming,2024-01-20,2024-03-26,1442,9.2,AI Innovations -AI00392,Research Scientist,112363,JPY,12359930,SE,FL,Japan,S,Ukraine,0,"Python, TensorFlow, Azure, NLP, Data Visualization",Bachelor,9,Finance,2024-04-26,2024-05-12,843,9.4,Autonomous Tech -AI00393,AI Consultant,188028,USD,188028,EX,CT,United States,L,United States,50,"Scala, SQL, NLP",Associate,11,Retail,2025-04-25,2025-06-22,852,8.9,Quantum Computing Inc -AI00394,AI Product Manager,165794,USD,165794,EX,FT,Norway,S,United States,100,"Python, Azure, R, Kubernetes",Bachelor,16,Gaming,2025-01-26,2025-03-16,903,8.6,Advanced Robotics -AI00395,ML Ops Engineer,109778,EUR,93311,MI,FL,Netherlands,L,Netherlands,50,"Scala, GCP, Mathematics",PhD,3,Media,2024-02-11,2024-02-28,2366,8.9,Smart Analytics -AI00396,Head of AI,162918,USD,162918,EX,FL,Ireland,L,Ireland,0,"Hadoop, AWS, Scala",Bachelor,17,Consulting,2024-10-16,2024-12-12,721,5.5,TechCorp Inc -AI00397,Autonomous Systems Engineer,219603,USD,219603,EX,PT,United States,M,United States,0,"Python, Mathematics, Data Visualization",PhD,12,Transportation,2024-05-06,2024-06-16,894,8.5,DeepTech Ventures -AI00398,Head of AI,304991,CHF,274492,EX,FT,Switzerland,L,Switzerland,100,"Azure, PyTorch, Kubernetes, NLP, Java",Associate,17,Manufacturing,2024-03-08,2024-04-15,2314,6.5,Algorithmic Solutions -AI00399,AI Research Scientist,99431,AUD,134232,SE,FL,Australia,S,Estonia,50,"Kubernetes, TensorFlow, SQL",Associate,5,Retail,2024-04-09,2024-05-19,1227,6.7,DeepTech Ventures -AI00400,Data Scientist,92131,USD,92131,MI,CT,Sweden,L,Sweden,0,"SQL, Git, Statistics",Bachelor,3,Retail,2024-04-29,2024-07-01,1590,6.2,Digital Transformation LLC -AI00401,Research Scientist,111236,JPY,12235960,MI,FL,Japan,M,Japan,100,"Python, Spark, Linux, TensorFlow, Java",Master,3,Media,2025-03-05,2025-04-08,1407,6.1,Cloud AI Solutions -AI00402,AI Research Scientist,263705,USD,263705,EX,CT,Norway,M,Norway,0,"SQL, Scala, Linux",Bachelor,10,Technology,2024-12-16,2025-01-24,870,6.3,Cognitive Computing -AI00403,Head of AI,37401,USD,37401,MI,CT,China,S,Colombia,0,"Linux, Deep Learning, Statistics",Bachelor,2,Real Estate,2025-03-27,2025-06-04,728,8.3,Smart Analytics -AI00404,ML Ops Engineer,122481,GBP,91861,MI,FT,United Kingdom,L,Mexico,50,"MLOps, Tableau, Hadoop, AWS",Bachelor,3,Healthcare,2025-02-03,2025-03-11,1575,8,DeepTech Ventures -AI00405,Deep Learning Engineer,29050,USD,29050,EN,FL,India,L,India,50,"Spark, Azure, TensorFlow, Mathematics",Master,0,Real Estate,2024-05-24,2024-06-10,1106,6.7,Neural Networks Co -AI00406,Principal Data Scientist,142280,GBP,106710,SE,FT,United Kingdom,L,United Kingdom,100,"NLP, SQL, GCP, Kubernetes",Bachelor,9,Transportation,2024-08-30,2024-10-04,1311,9.9,TechCorp Inc -AI00407,AI Consultant,75989,USD,75989,EN,PT,United States,L,United States,0,"SQL, Java, TensorFlow, MLOps",PhD,0,Healthcare,2024-09-25,2024-11-19,2338,6.3,TechCorp Inc -AI00408,Computer Vision Engineer,103477,SGD,134520,SE,PT,Singapore,S,Singapore,100,"Scala, Data Visualization, TensorFlow, Azure, Statistics",Associate,6,Gaming,2024-02-11,2024-03-28,2343,8.9,Advanced Robotics -AI00409,ML Ops Engineer,111121,USD,111121,MI,FT,United States,S,United States,100,"Docker, Scala, Git, R",Associate,3,Healthcare,2024-03-05,2024-03-22,1349,7.6,Algorithmic Solutions -AI00410,Data Engineer,357359,CHF,321623,EX,CT,Switzerland,M,Switzerland,100,"PyTorch, MLOps, R, Scala, Tableau",PhD,19,Consulting,2024-06-28,2024-08-06,1855,7.3,Machine Intelligence Group -AI00411,ML Ops Engineer,107663,CAD,134579,MI,FT,Canada,L,Canada,100,"Docker, SQL, AWS, Computer Vision, Deep Learning",Bachelor,2,Education,2024-08-06,2024-09-10,683,5.3,Algorithmic Solutions -AI00412,Data Scientist,83352,GBP,62514,MI,PT,United Kingdom,S,United Kingdom,0,"PyTorch, SQL, GCP, AWS, TensorFlow",Bachelor,2,Education,2024-10-12,2024-11-07,1599,6.6,Future Systems -AI00413,Deep Learning Engineer,55431,GBP,41573,EN,CT,United Kingdom,S,United Kingdom,100,"Data Visualization, Git, Computer Vision, Kubernetes",Master,0,Retail,2024-03-08,2024-04-26,721,9.9,Cognitive Computing -AI00414,Data Scientist,149644,EUR,127197,SE,CT,Germany,M,Germany,100,"Git, Kubernetes, Linux",Associate,9,Education,2024-03-19,2024-04-18,825,7.7,Algorithmic Solutions -AI00415,AI Software Engineer,94453,USD,94453,MI,FT,Ireland,S,Ireland,50,"Computer Vision, Spark, SQL, GCP",PhD,2,Gaming,2025-04-05,2025-06-01,1352,5.2,Machine Intelligence Group -AI00416,Robotics Engineer,40773,USD,40773,MI,FT,China,M,China,0,"Python, Kubernetes, Docker, GCP",Bachelor,2,Finance,2024-05-26,2024-06-14,2359,6,Neural Networks Co -AI00417,AI Consultant,94832,CAD,118540,MI,CT,Canada,L,Australia,50,"GCP, TensorFlow, Linux",PhD,2,Education,2025-03-21,2025-05-18,1023,8.7,Advanced Robotics -AI00418,AI Specialist,66884,EUR,56851,EN,CT,Austria,L,Austria,100,"TensorFlow, AWS, Python, Mathematics, Deep Learning",Master,1,Transportation,2024-10-28,2024-12-18,1927,7.9,Quantum Computing Inc -AI00419,ML Ops Engineer,222209,USD,222209,SE,FL,Norway,L,Norway,50,"TensorFlow, SQL, Deep Learning",PhD,7,Finance,2024-03-15,2024-05-07,1846,6.3,Autonomous Tech -AI00420,Robotics Engineer,181591,JPY,19975010,EX,FL,Japan,S,Romania,50,"Python, TensorFlow, Java, Linux",Associate,15,Real Estate,2024-06-06,2024-07-19,2025,7.4,Cognitive Computing -AI00421,AI Research Scientist,70146,USD,70146,EN,PT,Sweden,M,Sweden,0,"Python, Azure, Deep Learning, TensorFlow, Data Visualization",Bachelor,1,Healthcare,2025-03-29,2025-05-17,1790,7,Quantum Computing Inc -AI00422,AI Software Engineer,77528,USD,77528,MI,CT,Ireland,M,Ireland,100,"Python, Spark, TensorFlow, Statistics, Java",Bachelor,2,Gaming,2024-01-12,2024-03-05,950,6.7,Future Systems -AI00423,AI Software Engineer,133696,CAD,167120,EX,FL,Canada,M,Canada,50,"AWS, Deep Learning, R, Computer Vision",Master,15,Government,2024-09-21,2024-11-28,2050,6.5,Neural Networks Co -AI00424,Deep Learning Engineer,266317,USD,266317,EX,FL,Norway,M,Norway,0,"R, GCP, MLOps, Azure, Python",Associate,19,Technology,2024-05-16,2024-07-07,970,5.3,Predictive Systems -AI00425,Head of AI,171903,USD,171903,EX,CT,Israel,L,India,100,"Kubernetes, Spark, Docker, Scala, Hadoop",Master,19,Healthcare,2024-07-27,2024-09-03,2156,9.3,Advanced Robotics -AI00426,Research Scientist,134807,CAD,168509,EX,FL,Canada,M,Denmark,0,"GCP, Kubernetes, SQL, Azure, Computer Vision",Bachelor,17,Manufacturing,2024-08-22,2024-09-05,1624,8.8,Digital Transformation LLC -AI00427,AI Product Manager,123091,EUR,104627,SE,FL,France,S,France,0,"Scala, TensorFlow, Spark, SQL",Bachelor,6,Consulting,2025-02-13,2025-03-31,2071,6,Digital Transformation LLC -AI00428,Data Engineer,55885,USD,55885,SE,FT,China,S,China,50,"Python, R, MLOps, Kubernetes",Bachelor,9,Education,2024-08-30,2024-09-19,875,8,Neural Networks Co -AI00429,Robotics Engineer,190416,USD,190416,EX,PT,Israel,S,Israel,100,"Linux, Hadoop, Kubernetes, Computer Vision, Deep Learning",Master,11,Finance,2024-10-11,2024-11-20,1500,9.8,Quantum Computing Inc -AI00430,Deep Learning Engineer,155137,USD,155137,SE,FL,Norway,S,Argentina,100,"Git, PyTorch, TensorFlow, SQL, Python",Master,6,Real Estate,2025-02-20,2025-03-22,2010,6.3,Predictive Systems -AI00431,Deep Learning Engineer,233502,SGD,303553,EX,FL,Singapore,L,Singapore,0,"Azure, Hadoop, R",Bachelor,14,Gaming,2025-02-13,2025-02-27,1261,9.1,Neural Networks Co -AI00432,Autonomous Systems Engineer,106241,USD,106241,SE,FT,South Korea,L,South Korea,100,"SQL, NLP, Python, Java",Associate,7,Consulting,2024-04-19,2024-06-12,1827,8.3,Advanced Robotics -AI00433,Principal Data Scientist,170331,JPY,18736410,EX,PT,Japan,L,China,100,"Kubernetes, Python, Computer Vision, Deep Learning",Master,17,Transportation,2025-01-11,2025-02-01,602,5.6,Autonomous Tech -AI00434,Machine Learning Researcher,190752,USD,190752,SE,PT,Denmark,M,Denmark,100,"TensorFlow, Spark, Deep Learning",Master,9,Gaming,2025-01-05,2025-02-01,1336,7.6,DeepTech Ventures -AI00435,Machine Learning Engineer,57858,JPY,6364380,EN,FL,Japan,S,Japan,0,"SQL, Hadoop, AWS, Mathematics",Bachelor,0,Consulting,2024-10-15,2024-11-10,1143,8.3,DataVision Ltd -AI00436,AI Consultant,60290,EUR,51247,EN,FT,Germany,M,Germany,50,"Computer Vision, MLOps, R",Associate,0,Real Estate,2024-09-01,2024-09-22,1266,9.6,Autonomous Tech -AI00437,Machine Learning Researcher,78662,USD,78662,MI,CT,South Korea,L,Norway,0,"Spark, Computer Vision, Mathematics",PhD,2,Technology,2024-02-09,2024-04-12,1998,9.9,Cloud AI Solutions -AI00438,Deep Learning Engineer,68057,USD,68057,EN,CT,Denmark,S,Denmark,0,"R, MLOps, AWS, Python",Master,1,Real Estate,2024-03-15,2024-05-12,2060,6.3,Cognitive Computing -AI00439,Data Engineer,152822,USD,152822,SE,CT,United States,M,India,50,"Git, Mathematics, Docker",Master,5,Healthcare,2025-03-29,2025-04-14,1541,5.8,Advanced Robotics -AI00440,Head of AI,168351,USD,168351,SE,FL,Sweden,L,Sweden,100,"Docker, Spark, Data Visualization, GCP",Bachelor,7,Energy,2025-03-03,2025-03-17,1746,9.3,TechCorp Inc -AI00441,Machine Learning Researcher,280392,USD,280392,EX,FT,United States,M,United States,0,"Docker, Hadoop, Azure, Python, Scala",Associate,15,Government,2024-10-17,2024-12-06,1427,5.8,Neural Networks Co -AI00442,AI Specialist,165716,USD,165716,EX,FL,Finland,L,Norway,50,"Data Visualization, R, Java",PhD,18,Media,2025-04-18,2025-05-22,2251,6.2,Quantum Computing Inc -AI00443,Computer Vision Engineer,187794,USD,187794,EX,FT,Finland,M,Finland,0,"Git, AWS, SQL, Kubernetes",PhD,11,Energy,2024-09-17,2024-10-02,1284,9,Quantum Computing Inc -AI00444,NLP Engineer,245697,EUR,208842,EX,FT,Germany,L,Germany,0,"GCP, Python, Mathematics",PhD,10,Healthcare,2024-08-22,2024-09-07,2112,9,Cognitive Computing -AI00445,Data Analyst,79411,CAD,99264,MI,CT,Canada,S,Canada,0,"SQL, Linux, Git, PyTorch, NLP",Master,3,Retail,2025-01-16,2025-02-27,2121,7.8,DeepTech Ventures -AI00446,AI Software Engineer,117847,USD,117847,SE,FT,South Korea,L,South Korea,100,"Scala, Python, Hadoop, Docker",Associate,7,Finance,2024-12-03,2024-12-17,1511,5.3,Cloud AI Solutions -AI00447,Principal Data Scientist,112962,GBP,84722,SE,FT,United Kingdom,M,Canada,100,"SQL, Python, Kubernetes, TensorFlow, Docker",Associate,9,Media,2024-06-04,2024-06-29,905,6.9,Machine Intelligence Group -AI00448,AI Product Manager,166397,AUD,224636,SE,FT,Australia,L,Australia,100,"Git, NLP, GCP, TensorFlow, Python",Master,7,Real Estate,2024-11-10,2024-12-01,2239,5,DeepTech Ventures -AI00449,Machine Learning Engineer,135988,USD,135988,SE,PT,Denmark,M,Israel,100,"Azure, Scala, GCP, MLOps",Bachelor,5,Media,2024-01-09,2024-03-08,1645,9.9,Neural Networks Co -AI00450,AI Specialist,30929,USD,30929,MI,FT,India,M,India,100,"Git, Azure, Kubernetes, R, SQL",PhD,2,Consulting,2024-04-14,2024-05-07,1963,9.6,DataVision Ltd -AI00451,Machine Learning Engineer,112165,EUR,95340,SE,FL,Germany,M,Germany,50,"Azure, AWS, Spark",Master,5,Technology,2024-02-11,2024-03-05,2021,8.9,Smart Analytics -AI00452,Data Scientist,100758,EUR,85644,MI,FL,Germany,M,Germany,100,"Python, Scala, NLP, Spark",Associate,4,Telecommunications,2024-04-21,2024-05-24,1162,9.1,Predictive Systems -AI00453,Principal Data Scientist,83754,USD,83754,EN,PT,Norway,L,United Kingdom,100,"Mathematics, Computer Vision, Git",Master,0,Finance,2025-01-15,2025-02-06,2164,7.8,Cloud AI Solutions -AI00454,Head of AI,109895,CHF,98906,MI,PT,Switzerland,S,Switzerland,100,"Tableau, Scala, Python",Associate,4,Consulting,2024-03-08,2024-04-25,2487,8.9,AI Innovations -AI00455,Machine Learning Engineer,160760,EUR,136646,EX,FT,Netherlands,M,Netherlands,50,"NLP, Linux, TensorFlow, Data Visualization",Bachelor,11,Energy,2024-02-23,2024-04-19,1258,7.1,Algorithmic Solutions -AI00456,Machine Learning Engineer,167415,AUD,226010,SE,PT,Australia,L,Australia,100,"Linux, Python, TensorFlow",Bachelor,5,Energy,2024-11-15,2024-12-04,2488,6.7,DataVision Ltd -AI00457,Data Scientist,58948,AUD,79580,EN,CT,Australia,L,Australia,100,"Azure, NLP, PyTorch",Master,1,Healthcare,2024-07-13,2024-09-09,515,7.4,Cloud AI Solutions -AI00458,ML Ops Engineer,73406,USD,73406,MI,CT,South Korea,L,South Korea,0,"Mathematics, Java, R",Bachelor,3,Retail,2024-12-28,2025-01-15,677,6,DeepTech Ventures -AI00459,AI Software Engineer,153534,EUR,130504,EX,FT,Austria,L,Austria,100,"MLOps, Linux, Docker, PyTorch",Associate,19,Gaming,2024-06-04,2024-07-16,1625,7.5,Predictive Systems -AI00460,Data Scientist,81787,JPY,8996570,MI,PT,Japan,M,Japan,50,"Java, Spark, AWS, Linux, MLOps",PhD,4,Manufacturing,2025-03-08,2025-05-11,577,5.9,Predictive Systems -AI00461,Computer Vision Engineer,121967,USD,121967,MI,PT,Ireland,L,Ireland,0,"AWS, TensorFlow, Statistics, Mathematics",Master,4,Finance,2024-06-30,2024-08-19,914,6.5,Algorithmic Solutions -AI00462,Data Analyst,181438,JPY,19958180,EX,CT,Japan,S,Japan,50,"Java, Spark, TensorFlow",Associate,14,Real Estate,2025-01-25,2025-03-04,2075,5.5,Quantum Computing Inc -AI00463,Autonomous Systems Engineer,60296,USD,60296,EN,PT,Ireland,L,Ireland,50,"Spark, Azure, PyTorch, Python, TensorFlow",Master,1,Retail,2025-01-21,2025-02-26,635,7.3,Algorithmic Solutions -AI00464,AI Specialist,64191,USD,64191,EN,PT,Sweden,M,Vietnam,50,"Kubernetes, Linux, Data Visualization, PyTorch",Master,1,Healthcare,2024-11-26,2024-12-11,2243,5.6,Future Systems -AI00465,AI Research Scientist,96896,CHF,87206,EN,FL,Switzerland,S,Italy,50,"Python, Scala, Azure, Hadoop",PhD,0,Gaming,2024-09-25,2024-12-05,1137,7.4,Algorithmic Solutions -AI00466,Principal Data Scientist,78105,USD,78105,MI,PT,South Korea,M,South Korea,50,"Scala, SQL, Data Visualization",Bachelor,2,Healthcare,2025-02-14,2025-03-24,2258,5.2,Predictive Systems -AI00467,Robotics Engineer,71686,EUR,60933,EN,PT,Germany,S,Germany,50,"Kubernetes, PyTorch, Linux",Master,0,Retail,2024-09-21,2024-10-20,1282,8,Cognitive Computing -AI00468,AI Research Scientist,148827,EUR,126503,SE,PT,Germany,M,Australia,0,"Python, Spark, NLP, R",Associate,9,Finance,2024-11-27,2025-01-31,1119,5,Neural Networks Co -AI00469,Data Analyst,92179,CAD,115224,SE,FL,Canada,S,Canada,100,"Python, Tableau, TensorFlow, GCP",Associate,8,Transportation,2025-03-01,2025-05-01,2487,8.2,Cognitive Computing -AI00470,Computer Vision Engineer,75460,EUR,64141,MI,FL,Austria,M,Austria,50,"Computer Vision, NLP, Kubernetes",Bachelor,3,Retail,2024-09-27,2024-11-17,1175,6.1,Advanced Robotics -AI00471,AI Architect,146580,EUR,124593,EX,PT,Netherlands,M,Netherlands,50,"Git, Docker, Mathematics, SQL",Associate,17,Education,2024-10-23,2024-12-20,1494,9.8,DataVision Ltd -AI00472,Data Analyst,68722,USD,68722,EN,FL,United States,S,Finland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Technology,2025-01-11,2025-03-06,1575,6.3,Neural Networks Co -AI00473,ML Ops Engineer,60841,USD,60841,EN,CT,United States,S,United States,50,"NLP, Scala, AWS, SQL, Hadoop",PhD,1,Automotive,2025-03-22,2025-05-27,2340,5.4,Machine Intelligence Group -AI00474,Deep Learning Engineer,49130,USD,49130,EN,FL,Sweden,S,Luxembourg,50,"TensorFlow, Python, Data Visualization, Deep Learning, AWS",Master,0,Education,2025-04-12,2025-05-16,2022,9.1,Advanced Robotics -AI00475,AI Product Manager,162683,USD,162683,SE,FT,Finland,L,Finland,50,"Python, TensorFlow, NLP, Kubernetes, Statistics",Master,9,Consulting,2024-12-30,2025-03-07,1100,9.1,Algorithmic Solutions -AI00476,Data Analyst,151676,EUR,128925,SE,PT,Germany,M,Germany,50,"Java, Hadoop, Data Visualization, MLOps, TensorFlow",Master,8,Government,2024-12-07,2025-01-15,1822,8.9,Advanced Robotics -AI00477,Head of AI,140928,USD,140928,MI,CT,Norway,M,Philippines,50,"Linux, TensorFlow, Hadoop, Docker",Master,4,Education,2024-04-10,2024-06-22,1543,8.9,DeepTech Ventures -AI00478,AI Specialist,140382,AUD,189516,SE,FL,Australia,M,Colombia,100,"Mathematics, GCP, Python, TensorFlow, NLP",Associate,8,Finance,2024-09-26,2024-11-22,2458,6.8,Cloud AI Solutions -AI00479,Machine Learning Engineer,179691,USD,179691,EX,CT,Ireland,S,Egypt,0,"TensorFlow, PyTorch, Scala, AWS",Bachelor,18,Energy,2024-09-29,2024-10-26,2128,6.7,Predictive Systems -AI00480,Principal Data Scientist,132280,EUR,112438,SE,FL,France,L,France,100,"Docker, Linux, Tableau, Git",PhD,8,Retail,2024-10-24,2024-12-14,599,8.1,Future Systems -AI00481,Computer Vision Engineer,90861,USD,90861,MI,FL,Norway,S,Norway,0,"Linux, SQL, R, Git, AWS",Associate,4,Telecommunications,2024-05-23,2024-07-14,783,7.9,Predictive Systems -AI00482,Data Engineer,102239,USD,102239,EX,PT,China,L,China,50,"Hadoop, Linux, R",Master,11,Technology,2025-04-16,2025-05-04,1574,9.5,Predictive Systems -AI00483,Machine Learning Engineer,71795,EUR,61026,EN,CT,Germany,M,Germany,0,"Python, Computer Vision, Hadoop, GCP, SQL",Master,1,Energy,2024-06-17,2024-08-13,2350,5.4,AI Innovations -AI00484,NLP Engineer,55230,EUR,46946,EN,FL,France,L,France,0,"Tableau, Data Visualization, Git, Linux, Hadoop",PhD,1,Media,2024-03-17,2024-04-02,840,9,Cognitive Computing -AI00485,AI Consultant,56030,EUR,47626,EN,PT,Germany,M,United States,50,"Docker, Deep Learning, Kubernetes, Spark",Bachelor,1,Government,2024-07-22,2024-08-20,1612,7.1,Autonomous Tech -AI00486,Head of AI,99246,USD,99246,EX,PT,India,L,India,100,"Spark, SQL, PyTorch, Java",Associate,17,Real Estate,2024-09-15,2024-11-02,1339,7.8,Predictive Systems -AI00487,AI Product Manager,130136,CAD,162670,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, TensorFlow, Computer Vision, Hadoop",PhD,11,Consulting,2025-01-05,2025-01-31,2026,6.3,DeepTech Ventures -AI00488,AI Research Scientist,51311,JPY,5644210,EN,FL,Japan,S,Japan,100,"Tableau, Linux, TensorFlow, Data Visualization",PhD,1,Telecommunications,2025-01-15,2025-03-09,856,6.7,Digital Transformation LLC -AI00489,Machine Learning Engineer,59010,USD,59010,EN,FL,South Korea,S,South Korea,100,"Hadoop, Computer Vision, Mathematics, GCP, Git",Associate,1,Real Estate,2024-12-27,2025-02-09,1203,9.1,Quantum Computing Inc -AI00490,AI Research Scientist,139257,USD,139257,SE,CT,United States,L,United States,50,"Azure, TensorFlow, Kubernetes, Computer Vision, Hadoop",Master,5,Manufacturing,2024-02-27,2024-03-25,1275,7.4,DataVision Ltd -AI00491,Data Analyst,50920,USD,50920,EN,FL,Finland,S,Finland,0,"Git, Scala, SQL",Master,0,Manufacturing,2024-11-05,2024-12-13,2039,8.6,Smart Analytics -AI00492,AI Specialist,116377,CHF,104739,EN,CT,Switzerland,L,Indonesia,100,"Azure, Scala, Deep Learning, Computer Vision, Statistics",Associate,0,Finance,2025-01-16,2025-02-01,1586,7,DeepTech Ventures -AI00493,Principal Data Scientist,101911,CHF,91720,EN,FT,Switzerland,M,France,0,"Linux, GCP, NLP",Associate,0,Education,2024-11-06,2024-12-23,1975,7.1,Cognitive Computing -AI00494,Data Analyst,92714,EUR,78807,EN,PT,Netherlands,L,Portugal,50,"Java, Mathematics, Tableau, Spark, PyTorch",Master,1,Technology,2024-03-17,2024-03-31,1305,9.3,Neural Networks Co -AI00495,Head of AI,83757,GBP,62818,EN,CT,United Kingdom,L,United Kingdom,0,"Statistics, Mathematics, Data Visualization",Bachelor,0,Media,2024-08-09,2024-09-20,1023,5,Advanced Robotics -AI00496,AI Specialist,88018,CAD,110023,MI,PT,Canada,L,Canada,50,"MLOps, NLP, SQL, Data Visualization",Master,2,Energy,2025-04-03,2025-04-29,1955,5.2,DataVision Ltd -AI00497,Data Scientist,51864,USD,51864,EN,FT,Finland,S,Finland,100,"Computer Vision, Scala, Data Visualization",Master,1,Transportation,2024-03-05,2024-05-02,2470,6.3,Cloud AI Solutions -AI00498,Head of AI,96976,SGD,126069,MI,CT,Singapore,L,Indonesia,50,"Spark, Hadoop, Scala, Linux",Associate,4,Manufacturing,2024-06-03,2024-07-08,1038,9.4,Predictive Systems -AI00499,Computer Vision Engineer,120263,USD,120263,EX,FT,South Korea,M,Chile,100,"Python, GCP, Spark",Bachelor,13,Retail,2024-10-23,2024-12-08,2046,6.7,Predictive Systems -AI00500,Data Scientist,178114,CHF,160303,SE,PT,Switzerland,S,Colombia,0,"AWS, Java, GCP",PhD,9,Consulting,2024-11-17,2024-12-31,1369,5.7,Cognitive Computing -AI00501,AI Research Scientist,94379,AUD,127412,MI,CT,Australia,L,Australia,50,"TensorFlow, GCP, PyTorch",Master,3,Finance,2025-01-05,2025-01-28,784,7.9,DeepTech Ventures -AI00502,AI Software Engineer,268149,USD,268149,EX,FT,Norway,M,Norway,0,"Git, Python, Azure, Statistics, AWS",PhD,17,Media,2024-02-03,2024-03-15,1961,5.6,Machine Intelligence Group -AI00503,NLP Engineer,90472,CAD,113090,MI,CT,Canada,L,Canada,0,"Mathematics, AWS, Git, Kubernetes, SQL",Master,3,Finance,2024-10-07,2024-11-18,1473,8.7,Quantum Computing Inc -AI00504,AI Product Manager,86547,USD,86547,SE,FT,Israel,S,Israel,0,"Git, Computer Vision, NLP, R",PhD,7,Healthcare,2024-11-08,2025-01-02,1978,8.8,Machine Intelligence Group -AI00505,AI Consultant,150700,EUR,128095,SE,CT,France,L,India,0,"Computer Vision, Azure, Data Visualization, Scala",PhD,6,Retail,2024-06-08,2024-07-06,2425,8.1,Predictive Systems -AI00506,AI Specialist,216740,USD,216740,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Azure, Python, Linux, Docker",Bachelor,14,Healthcare,2025-04-14,2025-05-01,1701,5.3,TechCorp Inc -AI00507,AI Software Engineer,59227,EUR,50343,EN,FL,Netherlands,M,Netherlands,0,"Docker, Tableau, Kubernetes",PhD,1,Healthcare,2025-01-22,2025-02-19,624,9.7,TechCorp Inc -AI00508,AI Software Engineer,163281,CAD,204101,SE,PT,Canada,L,Canada,0,"Git, TensorFlow, Tableau",PhD,5,Transportation,2025-01-20,2025-02-18,2007,7.3,Advanced Robotics -AI00509,Data Engineer,66305,USD,66305,EN,FT,United States,S,Estonia,100,"GCP, Java, AWS, Data Visualization",PhD,1,Transportation,2024-11-09,2024-12-30,1348,6.9,Smart Analytics -AI00510,AI Consultant,126408,CAD,158010,SE,PT,Canada,L,Canada,100,"Spark, Python, GCP, SQL",Bachelor,6,Automotive,2024-08-11,2024-09-18,1300,6.6,Machine Intelligence Group -AI00511,NLP Engineer,144024,EUR,122420,SE,FL,Netherlands,L,Netherlands,100,"AWS, R, Deep Learning, Kubernetes",Associate,7,Automotive,2024-07-03,2024-08-09,1552,9.6,Smart Analytics -AI00512,AI Software Engineer,108805,USD,108805,SE,FT,South Korea,M,South Korea,0,"AWS, Azure, Linux, Mathematics",Master,6,Transportation,2024-12-25,2025-02-08,2105,8.1,Cognitive Computing -AI00513,Data Analyst,79093,EUR,67229,MI,PT,France,M,Ireland,50,"Linux, Java, Tableau",PhD,3,Energy,2024-08-11,2024-09-03,837,8.9,Cloud AI Solutions -AI00514,Machine Learning Engineer,295893,USD,295893,EX,PT,Denmark,S,Denmark,50,"Spark, Python, Java, NLP, TensorFlow",Bachelor,15,Retail,2024-04-13,2024-06-18,1210,7.9,Algorithmic Solutions -AI00515,AI Specialist,83000,JPY,9130000,MI,FT,Japan,M,Japan,50,"TensorFlow, Hadoop, Data Visualization",PhD,2,Education,2024-12-12,2025-01-23,1006,5.2,Quantum Computing Inc -AI00516,AI Software Engineer,80124,USD,80124,EN,CT,United States,M,United States,0,"R, AWS, Hadoop, Kubernetes",Master,0,Education,2024-11-07,2024-12-14,665,9.8,Autonomous Tech -AI00517,Data Engineer,69336,EUR,58936,EN,FL,Germany,L,Vietnam,0,"Mathematics, Spark, Python",Bachelor,1,Gaming,2024-12-28,2025-01-30,1975,9.8,Autonomous Tech -AI00518,Data Engineer,42380,USD,42380,SE,FL,India,L,United States,0,"Azure, Docker, Java, MLOps",Master,5,Telecommunications,2024-08-02,2024-09-18,1526,6.9,TechCorp Inc -AI00519,Data Scientist,149450,EUR,127033,EX,PT,Germany,M,Philippines,0,"Mathematics, Spark, Docker, Hadoop",Bachelor,18,Telecommunications,2024-09-10,2024-11-01,1201,7.7,Smart Analytics -AI00520,AI Software Engineer,285891,CHF,257302,EX,FT,Switzerland,S,Singapore,50,"Java, Python, MLOps, Linux, Azure",Master,16,Consulting,2024-08-22,2024-09-29,1105,5.8,Neural Networks Co -AI00521,Computer Vision Engineer,75240,USD,75240,EN,CT,South Korea,L,South Korea,100,"Mathematics, Hadoop, Docker",PhD,1,Telecommunications,2024-01-20,2024-02-03,1921,9.3,Algorithmic Solutions -AI00522,Data Scientist,124786,JPY,13726460,SE,FL,Japan,M,Japan,0,"NLP, AWS, Data Visualization, MLOps",Bachelor,7,Education,2024-03-20,2024-05-24,1442,8.3,Algorithmic Solutions -AI00523,Machine Learning Researcher,109043,CHF,98139,MI,FL,Switzerland,S,Switzerland,0,"GCP, Azure, Linux",Associate,3,Government,2025-03-08,2025-05-15,1570,5.6,Machine Intelligence Group -AI00524,Machine Learning Engineer,89035,USD,89035,SE,CT,Finland,S,Ireland,50,"SQL, Docker, NLP, Python",Associate,5,Telecommunications,2024-08-29,2024-09-20,864,6.6,Quantum Computing Inc -AI00525,Machine Learning Engineer,190529,USD,190529,EX,FL,Finland,M,Finland,50,"Linux, Spark, Tableau, Mathematics, Azure",Bachelor,19,Technology,2024-10-11,2024-11-03,1090,10,Neural Networks Co -AI00526,Machine Learning Engineer,169009,USD,169009,SE,PT,United States,M,Finland,100,"Docker, Kubernetes, Azure",Master,9,Healthcare,2024-11-21,2025-01-25,1366,9.7,TechCorp Inc -AI00527,Autonomous Systems Engineer,48714,USD,48714,EN,FT,Israel,S,Israel,100,"Git, R, Python, Mathematics",Master,1,Energy,2025-03-15,2025-04-01,530,8.6,Advanced Robotics -AI00528,ML Ops Engineer,97541,EUR,82910,SE,FT,Netherlands,S,Netherlands,0,"MLOps, Python, Kubernetes, TensorFlow",PhD,5,Manufacturing,2024-12-16,2025-01-21,1792,9.2,Predictive Systems -AI00529,Robotics Engineer,144493,EUR,122819,SE,CT,Germany,M,Germany,0,"Spark, Java, Deep Learning, R",PhD,5,Education,2025-04-18,2025-05-26,2224,7.1,TechCorp Inc -AI00530,Computer Vision Engineer,185421,USD,185421,EX,CT,Denmark,S,Nigeria,0,"PyTorch, SQL, Docker, TensorFlow",Associate,11,Media,2024-06-18,2024-08-03,1524,9.7,DeepTech Ventures -AI00531,Principal Data Scientist,287164,USD,287164,EX,FL,Sweden,L,Sweden,0,"Azure, TensorFlow, Statistics, PyTorch, R",Bachelor,18,Consulting,2024-08-31,2024-10-03,1681,8.4,AI Innovations -AI00532,AI Consultant,120968,JPY,13306480,SE,PT,Japan,S,Japan,0,"Azure, Hadoop, Scala, Computer Vision, Python",PhD,8,Healthcare,2024-10-25,2024-11-30,952,7.3,Advanced Robotics -AI00533,AI Research Scientist,135171,USD,135171,EX,CT,Sweden,S,Sweden,50,"Azure, Deep Learning, GCP, TensorFlow",Associate,14,Healthcare,2024-05-14,2024-05-31,1460,6.7,Cognitive Computing -AI00534,AI Architect,129545,CHF,116591,EN,PT,Switzerland,L,Finland,100,"Scala, Python, Computer Vision, Deep Learning",Master,1,Government,2024-03-14,2024-04-20,561,9.3,TechCorp Inc -AI00535,Data Analyst,97794,SGD,127132,MI,CT,Singapore,L,Singapore,50,"PyTorch, R, Data Visualization",PhD,2,Gaming,2024-04-04,2024-06-12,984,6.1,Autonomous Tech -AI00536,Deep Learning Engineer,145395,CAD,181744,EX,FL,Canada,M,Brazil,100,"Computer Vision, Data Visualization, Python, Spark, TensorFlow",PhD,18,Automotive,2024-07-27,2024-09-08,1959,7.5,TechCorp Inc -AI00537,Computer Vision Engineer,204217,USD,204217,EX,CT,Sweden,M,Kenya,50,"GCP, Deep Learning, R",Associate,11,Education,2024-09-28,2024-11-16,1581,7.2,Future Systems -AI00538,Autonomous Systems Engineer,98702,USD,98702,EN,FT,Denmark,L,Denmark,0,"Statistics, Kubernetes, R, SQL",Bachelor,0,Telecommunications,2025-02-17,2025-03-11,1517,9.4,Machine Intelligence Group -AI00539,Deep Learning Engineer,99895,GBP,74921,MI,CT,United Kingdom,S,New Zealand,0,"R, PyTorch, GCP, NLP, Git",Bachelor,3,Finance,2025-01-27,2025-03-20,2257,10,Machine Intelligence Group -AI00540,NLP Engineer,135571,EUR,115235,SE,FL,Netherlands,S,Netherlands,100,"Git, Spark, R, SQL, Tableau",PhD,8,Telecommunications,2024-07-13,2024-09-01,2391,8.7,Advanced Robotics -AI00541,AI Specialist,119266,USD,119266,SE,PT,Ireland,L,Ireland,50,"SQL, Python, Data Visualization",PhD,6,Government,2024-04-04,2024-05-21,1518,9.2,Digital Transformation LLC -AI00542,Research Scientist,110844,EUR,94217,SE,CT,Austria,L,Austria,50,"Scala, Statistics, MLOps, Deep Learning",Associate,8,Transportation,2025-02-07,2025-03-09,1353,9.6,DeepTech Ventures -AI00543,NLP Engineer,145736,EUR,123876,SE,FT,Netherlands,L,Ghana,50,"Linux, Python, NLP, TensorFlow",Master,9,Transportation,2025-01-16,2025-03-05,2348,6.1,Cloud AI Solutions -AI00544,AI Software Engineer,232735,EUR,197825,EX,PT,France,M,France,0,"Spark, PyTorch, TensorFlow, Deep Learning, Azure",Bachelor,11,Manufacturing,2025-04-15,2025-06-25,1449,9.7,Future Systems -AI00545,Machine Learning Researcher,56990,USD,56990,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Hadoop",PhD,1,Telecommunications,2024-02-17,2024-03-25,2274,6.2,Algorithmic Solutions -AI00546,AI Software Engineer,169605,USD,169605,EX,FT,Israel,M,Israel,0,"Data Visualization, AWS, TensorFlow, R, Linux",PhD,15,Real Estate,2024-05-17,2024-06-16,1672,6,Digital Transformation LLC -AI00547,Machine Learning Engineer,145138,USD,145138,SE,PT,Finland,L,United Kingdom,0,"PyTorch, Git, Python, AWS",PhD,8,Real Estate,2024-12-25,2025-02-16,793,5.2,AI Innovations -AI00548,Data Scientist,139121,EUR,118253,SE,FL,Germany,L,Germany,50,"Git, Kubernetes, Python, Linux",Bachelor,5,Finance,2024-10-20,2024-11-17,587,9.2,Cloud AI Solutions -AI00549,AI Product Manager,178631,USD,178631,EX,PT,Israel,S,Malaysia,100,"TensorFlow, Spark, Computer Vision, NLP",Bachelor,13,Automotive,2024-09-28,2024-11-18,1081,6.8,Machine Intelligence Group -AI00550,NLP Engineer,90723,SGD,117940,MI,PT,Singapore,S,New Zealand,0,"Linux, Scala, Git",Bachelor,4,Retail,2024-12-28,2025-01-20,2414,7.3,DataVision Ltd -AI00551,ML Ops Engineer,49069,USD,49069,MI,CT,China,M,China,100,"Python, Docker, TensorFlow",PhD,4,Automotive,2024-11-26,2025-02-06,1659,7.2,Autonomous Tech -AI00552,Deep Learning Engineer,68202,JPY,7502220,EN,FL,Japan,L,Japan,50,"TensorFlow, Java, AWS, R",Master,0,Automotive,2025-04-08,2025-05-08,1446,5.6,Cloud AI Solutions -AI00553,Data Analyst,116676,EUR,99175,MI,FL,Germany,L,Germany,0,"R, TensorFlow, Kubernetes, Scala, Statistics",Associate,3,Media,2024-03-25,2024-04-26,1460,5.8,Smart Analytics -AI00554,AI Specialist,153139,USD,153139,SE,FT,Finland,L,Finland,100,"Python, Spark, Scala, Deep Learning, Mathematics",PhD,7,Real Estate,2025-04-28,2025-05-21,609,6.8,Autonomous Tech -AI00555,Computer Vision Engineer,131402,EUR,111692,EX,FL,Netherlands,S,Netherlands,50,"MLOps, Tableau, SQL",Master,13,Media,2024-12-31,2025-03-14,1147,5.1,DeepTech Ventures -AI00556,Machine Learning Engineer,54607,EUR,46416,EN,CT,Austria,M,Austria,50,"Git, Java, Hadoop",Associate,1,Real Estate,2024-08-11,2024-10-18,1342,6.4,Advanced Robotics -AI00557,Autonomous Systems Engineer,71774,JPY,7895140,MI,CT,Japan,S,Egypt,100,"Java, Data Visualization, Deep Learning, MLOps, Spark",PhD,4,Government,2024-02-04,2024-03-17,2022,9.7,DataVision Ltd -AI00558,Data Engineer,110765,EUR,94150,SE,FL,Germany,S,China,0,"PyTorch, GCP, TensorFlow",PhD,6,Technology,2024-03-02,2024-03-21,721,5.4,AI Innovations -AI00559,Data Analyst,265991,USD,265991,EX,PT,United States,L,Vietnam,100,"AWS, Git, Docker, Azure, Computer Vision",Master,13,Finance,2024-07-24,2024-09-24,1528,7.7,DataVision Ltd -AI00560,AI Research Scientist,83839,USD,83839,MI,FL,Israel,L,Israel,50,"Scala, Spark, GCP, Azure, NLP",Bachelor,4,Real Estate,2024-03-09,2024-03-29,1589,7.2,DataVision Ltd -AI00561,Machine Learning Engineer,236251,SGD,307126,EX,PT,Singapore,L,Singapore,100,"Tableau, Mathematics, AWS, NLP, Deep Learning",Bachelor,13,Healthcare,2024-09-04,2024-10-08,678,8,Future Systems -AI00562,AI Research Scientist,241129,AUD,325524,EX,FT,Australia,M,Australia,100,"Python, Computer Vision, Git, Scala",Bachelor,16,Manufacturing,2025-02-27,2025-03-15,962,7.5,Cloud AI Solutions -AI00563,Machine Learning Researcher,159083,USD,159083,SE,PT,Israel,L,Israel,100,"Linux, Computer Vision, Data Visualization",Bachelor,7,Education,2024-11-27,2024-12-25,1205,6.5,Quantum Computing Inc -AI00564,Computer Vision Engineer,103506,USD,103506,SE,FL,South Korea,L,South Korea,0,"Tableau, Azure, AWS",Master,8,Healthcare,2024-09-05,2024-11-10,1490,9.1,Future Systems -AI00565,Principal Data Scientist,232495,USD,232495,EX,PT,Denmark,M,Denmark,0,"Deep Learning, AWS, Azure",Master,10,Real Estate,2025-02-01,2025-04-11,2289,8.2,Future Systems -AI00566,AI Research Scientist,112744,CHF,101470,EN,CT,Switzerland,L,Switzerland,50,"AWS, Kubernetes, Hadoop, Spark",Associate,1,Gaming,2025-01-20,2025-03-28,779,5.1,Cloud AI Solutions -AI00567,Autonomous Systems Engineer,129622,USD,129622,SE,PT,South Korea,L,South Korea,0,"GCP, R, Computer Vision, PyTorch, Git",PhD,5,Energy,2024-05-21,2024-07-30,1268,5.7,TechCorp Inc -AI00568,Machine Learning Engineer,100903,EUR,85768,SE,CT,Austria,S,Austria,0,"Docker, Python, AWS, Spark, TensorFlow",Bachelor,5,Education,2024-06-21,2024-08-28,683,8.2,Future Systems -AI00569,Principal Data Scientist,238019,EUR,202316,EX,FL,Austria,M,Estonia,0,"Python, Kubernetes, TensorFlow, Azure",Bachelor,11,Telecommunications,2025-02-18,2025-03-12,1577,9.7,Future Systems -AI00570,Machine Learning Engineer,41302,USD,41302,EN,PT,China,L,China,100,"GCP, Azure, NLP",Bachelor,0,Manufacturing,2024-02-09,2024-02-29,991,8,DataVision Ltd -AI00571,Deep Learning Engineer,128647,USD,128647,EX,CT,Ireland,S,Ireland,100,"SQL, Computer Vision, Python, AWS, Java",Associate,17,Real Estate,2025-01-16,2025-02-23,1579,7.8,Advanced Robotics -AI00572,AI Software Engineer,52696,EUR,44792,EN,FL,France,S,France,50,"Docker, Kubernetes, Python, GCP",PhD,0,Government,2024-06-06,2024-06-20,1102,5.6,Machine Intelligence Group -AI00573,Principal Data Scientist,229071,GBP,171803,EX,FT,United Kingdom,L,United Kingdom,0,"Java, Python, Data Visualization, MLOps",Associate,19,Education,2024-07-16,2024-08-19,629,8.8,Quantum Computing Inc -AI00574,Autonomous Systems Engineer,215282,USD,215282,EX,FL,Denmark,M,Denmark,50,"MLOps, NLP, Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-06-17,2024-08-13,528,7.8,Algorithmic Solutions -AI00575,Principal Data Scientist,199110,EUR,169244,EX,FT,France,S,Ukraine,0,"TensorFlow, Hadoop, Kubernetes, SQL",Master,10,Finance,2024-05-01,2024-06-16,908,5.5,Future Systems -AI00576,NLP Engineer,75004,USD,75004,EN,FT,United States,L,United States,50,"Computer Vision, Linux, Spark, Hadoop",Bachelor,1,Technology,2024-08-30,2024-09-27,786,8.5,Smart Analytics -AI00577,Research Scientist,149575,USD,149575,SE,PT,Israel,L,Israel,50,"Linux, PyTorch, Git, R",Master,6,Transportation,2024-03-11,2024-04-21,821,9.5,Cloud AI Solutions -AI00578,Deep Learning Engineer,138904,USD,138904,EX,CT,Israel,S,Israel,50,"Scala, Python, Deep Learning",Master,15,Telecommunications,2025-04-06,2025-05-31,1452,5.4,Autonomous Tech -AI00579,Computer Vision Engineer,133658,SGD,173755,SE,FL,Singapore,L,Singapore,50,"Kubernetes, R, Mathematics",Master,7,Telecommunications,2025-01-30,2025-04-09,1637,8.8,Cognitive Computing -AI00580,Research Scientist,148968,EUR,126623,EX,FT,Austria,S,Mexico,0,"Spark, Scala, Hadoop, Computer Vision",PhD,10,Education,2024-12-01,2025-01-28,2122,5.7,Neural Networks Co -AI00581,AI Product Manager,87661,JPY,9642710,MI,PT,Japan,S,Japan,100,"Data Visualization, Hadoop, PyTorch, NLP",Master,3,Finance,2024-04-30,2024-05-25,885,5.9,Cognitive Computing -AI00582,Data Analyst,235575,CAD,294469,EX,PT,Canada,L,Japan,0,"Scala, Tableau, Linux, PyTorch, Spark",Master,12,Technology,2024-02-13,2024-03-13,2033,6.8,Machine Intelligence Group -AI00583,Computer Vision Engineer,195175,USD,195175,EX,PT,Israel,S,Israel,100,"AWS, Spark, PyTorch, Kubernetes, Tableau",Master,14,Real Estate,2025-02-19,2025-03-28,1435,7.1,AI Innovations -AI00584,Data Engineer,143318,CAD,179148,SE,PT,Canada,M,Canada,100,"GCP, PyTorch, Tableau, Git",Master,8,Energy,2024-07-18,2024-08-01,2002,9.3,AI Innovations -AI00585,Machine Learning Engineer,102959,CHF,92663,EN,FL,Switzerland,L,Switzerland,100,"Scala, Hadoop, Docker",Master,1,Finance,2024-07-15,2024-08-26,1849,7.7,Advanced Robotics -AI00586,ML Ops Engineer,90379,AUD,122012,MI,FL,Australia,S,Italy,100,"Data Visualization, Docker, Python, TensorFlow",Master,4,Finance,2025-04-20,2025-07-02,1029,7.5,Predictive Systems -AI00587,Principal Data Scientist,71203,CAD,89004,EN,FT,Canada,M,Canada,100,"TensorFlow, Git, SQL, Kubernetes, Java",Associate,0,Energy,2025-03-24,2025-04-27,1537,6.2,Advanced Robotics -AI00588,AI Consultant,177188,EUR,150610,EX,FL,Netherlands,S,Netherlands,100,"Scala, AWS, Git",Bachelor,13,Manufacturing,2025-01-06,2025-01-23,1619,8.6,Machine Intelligence Group -AI00589,Machine Learning Engineer,95416,USD,95416,MI,CT,Sweden,M,Brazil,100,"Java, Docker, Computer Vision, Linux, Mathematics",Master,2,Technology,2024-05-24,2024-06-09,938,5.6,Cognitive Computing -AI00590,Head of AI,89044,USD,89044,EN,CT,Norway,L,Czech Republic,50,"SQL, PyTorch, Tableau",PhD,1,Government,2024-04-11,2024-06-19,1762,7.2,Quantum Computing Inc -AI00591,NLP Engineer,78263,EUR,66524,EN,PT,Netherlands,M,Ireland,100,"Python, TensorFlow, GCP",PhD,0,Energy,2024-07-10,2024-09-21,1563,6.9,Predictive Systems -AI00592,ML Ops Engineer,231654,JPY,25481940,EX,PT,Japan,M,Japan,0,"Python, Mathematics, GCP, Computer Vision, AWS",PhD,11,Finance,2024-09-08,2024-09-28,1880,10,Digital Transformation LLC -AI00593,NLP Engineer,149046,USD,149046,SE,PT,Sweden,L,Sweden,0,"Python, Kubernetes, TensorFlow, Computer Vision, PyTorch",Associate,9,Technology,2024-08-19,2024-09-30,2359,5.5,Predictive Systems -AI00594,Machine Learning Researcher,84232,CAD,105290,MI,CT,Canada,S,Canada,100,"GCP, Scala, Azure, Statistics",Master,4,Gaming,2024-12-23,2025-01-29,537,7,Machine Intelligence Group -AI00595,ML Ops Engineer,94348,CAD,117935,SE,FT,Canada,S,Canada,50,"GCP, SQL, Spark, Linux",Master,7,Energy,2024-03-02,2024-04-12,527,7.4,DataVision Ltd -AI00596,Data Engineer,128839,USD,128839,SE,FL,Finland,M,Finland,50,"Mathematics, Statistics, Deep Learning, Java, Kubernetes",PhD,6,Retail,2024-11-05,2025-01-13,2263,8.5,Algorithmic Solutions -AI00597,AI Architect,166829,EUR,141805,SE,FL,Netherlands,L,Netherlands,100,"AWS, Kubernetes, Deep Learning",Associate,5,Consulting,2024-11-02,2024-11-30,2187,9.3,Cloud AI Solutions -AI00598,AI Software Engineer,67959,GBP,50969,EN,FT,United Kingdom,M,United Kingdom,100,"Docker, Scala, NLP, TensorFlow, Spark",PhD,1,Real Estate,2024-01-02,2024-01-20,599,7.4,Machine Intelligence Group -AI00599,AI Architect,80303,AUD,108409,MI,FT,Australia,M,Australia,50,"Python, GCP, Git, Java, Mathematics",Bachelor,4,Healthcare,2024-08-09,2024-10-07,812,9.3,Smart Analytics -AI00600,Data Engineer,104350,EUR,88698,MI,FL,Netherlands,S,Netherlands,50,"MLOps, Mathematics, Git",Bachelor,2,Transportation,2024-02-04,2024-04-04,2112,7.4,Algorithmic Solutions -AI00601,AI Consultant,146664,EUR,124664,SE,PT,Netherlands,L,Netherlands,50,"Python, SQL, Computer Vision, Java",PhD,8,Automotive,2024-04-04,2024-05-29,589,8.1,Machine Intelligence Group -AI00602,AI Software Engineer,119423,EUR,101510,SE,PT,Germany,M,Germany,50,"GCP, TensorFlow, Computer Vision, AWS",Master,9,Gaming,2024-11-19,2024-12-31,1840,9,Algorithmic Solutions -AI00603,AI Consultant,31988,USD,31988,EN,PT,China,M,China,50,"Docker, Mathematics, Scala",PhD,0,Automotive,2024-01-14,2024-02-20,2450,6.1,Future Systems -AI00604,AI Architect,94563,GBP,70922,EN,FT,United Kingdom,L,United Kingdom,50,"Git, TensorFlow, Deep Learning, Azure, Computer Vision",Bachelor,1,Finance,2024-01-05,2024-03-01,1461,9.7,DeepTech Ventures -AI00605,Autonomous Systems Engineer,85269,USD,85269,EN,FL,Ireland,L,Ireland,50,"MLOps, Deep Learning, PyTorch",Bachelor,0,Technology,2024-02-11,2024-03-30,953,7.9,DeepTech Ventures -AI00606,AI Architect,87092,USD,87092,EN,PT,Israel,L,Israel,50,"Kubernetes, Statistics, Scala",PhD,0,Healthcare,2024-02-25,2024-04-14,1931,9.9,Predictive Systems -AI00607,Machine Learning Researcher,75721,USD,75721,EN,FT,Finland,L,China,100,"Docker, Git, Python, Mathematics",PhD,1,Manufacturing,2024-07-05,2024-09-12,2487,5.1,DeepTech Ventures -AI00608,Research Scientist,158003,USD,158003,SE,FT,Sweden,L,Sweden,0,"Python, SQL, Tableau, Data Visualization",Master,7,Government,2025-04-20,2025-06-22,634,5.9,Future Systems -AI00609,Autonomous Systems Engineer,189198,JPY,20811780,EX,FL,Japan,M,Japan,0,"Computer Vision, Spark, Data Visualization, Java",Associate,18,Finance,2024-03-27,2024-06-01,2153,6.9,AI Innovations -AI00610,Research Scientist,57287,EUR,48694,EN,FL,France,M,France,100,"AWS, PyTorch, Computer Vision, GCP, Scala",Associate,1,Technology,2024-10-15,2024-12-08,1413,7.1,Machine Intelligence Group -AI00611,AI Specialist,116891,GBP,87668,MI,FT,United Kingdom,L,Japan,0,"TensorFlow, PyTorch, GCP, NLP",Bachelor,2,Education,2024-12-31,2025-03-11,865,8.1,Autonomous Tech -AI00612,Autonomous Systems Engineer,86678,USD,86678,MI,FT,Sweden,S,Hungary,50,"AWS, Mathematics, GCP, Git",Associate,4,Telecommunications,2025-04-08,2025-05-19,1812,6.6,Autonomous Tech -AI00613,Research Scientist,237261,EUR,201672,EX,PT,Germany,L,Germany,50,"Mathematics, Scala, PyTorch",Bachelor,16,Government,2024-06-04,2024-07-26,686,7.1,Neural Networks Co -AI00614,Data Engineer,340350,CHF,306315,EX,FT,Switzerland,L,France,0,"Python, Spark, Deep Learning, Azure, TensorFlow",PhD,17,Gaming,2024-07-14,2024-08-13,2373,7.2,Algorithmic Solutions -AI00615,Data Scientist,143376,USD,143376,SE,FL,Norway,S,Norway,50,"PyTorch, Mathematics, Deep Learning, Linux, AWS",Associate,8,Transportation,2025-04-06,2025-05-25,1159,7.7,Advanced Robotics -AI00616,Robotics Engineer,212213,CHF,190992,SE,FL,Switzerland,M,Switzerland,0,"Azure, SQL, Kubernetes, NLP",Associate,9,Consulting,2024-03-19,2024-04-30,1213,6.8,Autonomous Tech -AI00617,Principal Data Scientist,147392,SGD,191610,SE,CT,Singapore,L,Finland,100,"NLP, MLOps, SQL, Linux",Associate,5,Automotive,2025-03-03,2025-03-23,1701,5.8,AI Innovations -AI00618,Machine Learning Engineer,93630,USD,93630,SE,PT,Finland,S,Finland,50,"Kubernetes, SQL, PyTorch",Master,6,Energy,2025-02-27,2025-03-24,1022,6.5,Neural Networks Co -AI00619,AI Software Engineer,99867,CHF,89880,EN,FT,Switzerland,M,Switzerland,0,"Python, Git, TensorFlow",Master,0,Healthcare,2024-06-27,2024-08-09,1864,6.4,Advanced Robotics -AI00620,NLP Engineer,167900,CHF,151110,MI,FL,Switzerland,L,India,100,"Python, AWS, TensorFlow, Data Visualization, Computer Vision",Bachelor,3,Automotive,2025-03-25,2025-05-22,2095,5,DeepTech Ventures -AI00621,Computer Vision Engineer,113585,USD,113585,MI,FL,Norway,S,Egypt,50,"Computer Vision, Python, Statistics, TensorFlow",Associate,4,Government,2024-12-12,2025-01-27,1077,8.5,Digital Transformation LLC -AI00622,AI Software Engineer,88040,GBP,66030,MI,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, AWS, PyTorch, Deep Learning, Data Visualization",PhD,2,Finance,2024-08-03,2024-10-04,1715,8.2,Quantum Computing Inc -AI00623,Autonomous Systems Engineer,234891,USD,234891,EX,CT,South Korea,L,South Korea,0,"Spark, Scala, Statistics, Computer Vision",Master,19,Retail,2024-08-26,2024-09-22,2055,7,Future Systems -AI00624,Machine Learning Researcher,55689,EUR,47336,EN,PT,Austria,L,Austria,50,"Python, Mathematics, Deep Learning, Linux, GCP",Master,1,Government,2024-11-28,2025-01-27,1296,7.5,Predictive Systems -AI00625,Deep Learning Engineer,192002,EUR,163202,EX,FT,France,S,Japan,50,"MLOps, Java, Linux, Hadoop, PyTorch",PhD,15,Education,2024-08-21,2024-09-19,1600,8.8,DataVision Ltd -AI00626,Research Scientist,88478,USD,88478,EX,CT,India,L,India,100,"R, AWS, Mathematics",Bachelor,12,Education,2024-02-05,2024-03-18,703,6.5,Neural Networks Co -AI00627,ML Ops Engineer,233768,EUR,198703,EX,FT,Austria,M,Austria,50,"Python, Azure, Scala, AWS",Master,13,Manufacturing,2024-10-06,2024-11-12,2390,5.4,Autonomous Tech -AI00628,Autonomous Systems Engineer,394510,CHF,355059,EX,PT,Switzerland,L,Switzerland,0,"MLOps, Java, Statistics, Deep Learning, SQL",Master,18,Finance,2024-02-15,2024-04-28,1628,9.6,Smart Analytics -AI00629,AI Research Scientist,96275,CHF,86648,EN,FT,Switzerland,S,Switzerland,0,"Python, NLP, GCP, Docker, Java",PhD,0,Gaming,2024-01-09,2024-02-16,2313,7.4,Neural Networks Co -AI00630,Data Scientist,67084,USD,67084,SE,PT,China,M,Japan,100,"SQL, MLOps, Java",Associate,5,Government,2024-06-21,2024-07-18,852,8.7,AI Innovations -AI00631,Head of AI,87326,USD,87326,MI,PT,South Korea,M,South Africa,100,"PyTorch, NLP, MLOps",PhD,3,Retail,2024-06-17,2024-07-21,1777,7,Future Systems -AI00632,Research Scientist,88829,USD,88829,MI,PT,Finland,M,Belgium,50,"SQL, Linux, Deep Learning, Scala",Master,3,Consulting,2024-04-23,2024-07-05,1733,7.3,Cognitive Computing -AI00633,Autonomous Systems Engineer,110532,USD,110532,MI,FL,Denmark,M,Denmark,50,"Computer Vision, Mathematics, NLP",PhD,3,Manufacturing,2024-09-27,2024-11-05,2039,8.5,Future Systems -AI00634,AI Product Manager,60357,USD,60357,EN,CT,South Korea,L,Belgium,0,"Azure, TensorFlow, NLP, Python, PyTorch",Associate,0,Media,2024-03-06,2024-04-05,562,9.6,DataVision Ltd -AI00635,AI Research Scientist,315064,CHF,283558,EX,FL,Switzerland,S,Switzerland,0,"NLP, Git, Scala, Hadoop, Docker",Bachelor,18,Real Estate,2024-04-15,2024-05-18,1191,9.6,Cognitive Computing -AI00636,AI Software Engineer,70097,USD,70097,EN,PT,Denmark,S,Denmark,100,"Git, Python, TensorFlow",PhD,0,Finance,2025-04-13,2025-06-10,2054,5.4,Quantum Computing Inc -AI00637,Principal Data Scientist,117235,USD,117235,SE,FL,Ireland,M,Ireland,50,"Scala, Git, Azure",PhD,6,Government,2025-01-24,2025-03-30,1962,7.4,Autonomous Tech -AI00638,Principal Data Scientist,65851,USD,65851,EN,FT,Sweden,S,Turkey,100,"Hadoop, Python, Statistics, Scala",Associate,0,Energy,2025-01-03,2025-03-06,692,8.3,Quantum Computing Inc -AI00639,Computer Vision Engineer,84191,JPY,9261010,MI,FL,Japan,M,Japan,100,"R, Docker, Git, GCP, Statistics",Master,2,Consulting,2024-07-20,2024-09-06,1495,8.2,TechCorp Inc -AI00640,NLP Engineer,134590,USD,134590,MI,FT,Norway,M,Norway,0,"Python, SQL, Docker, TensorFlow, Tableau",PhD,2,Manufacturing,2024-04-12,2024-06-07,1564,8.4,AI Innovations -AI00641,AI Product Manager,139686,AUD,188576,SE,FL,Australia,M,Australia,100,"NLP, SQL, GCP, Tableau",Master,6,Education,2024-03-25,2024-04-28,2364,8.3,Smart Analytics -AI00642,AI Software Engineer,115226,USD,115226,SE,PT,South Korea,L,South Korea,0,"Python, Kubernetes, TensorFlow",Bachelor,5,Telecommunications,2025-04-19,2025-05-03,1761,5.9,Quantum Computing Inc -AI00643,Deep Learning Engineer,262115,EUR,222798,EX,PT,Netherlands,L,Netherlands,0,"Java, GCP, Computer Vision",Associate,12,Consulting,2024-05-08,2024-07-07,736,9.2,Algorithmic Solutions -AI00644,Data Scientist,111532,EUR,94802,SE,FL,Austria,S,Austria,50,"NLP, Java, Computer Vision, R, Deep Learning",Master,6,Gaming,2024-07-03,2024-07-17,517,5.4,Algorithmic Solutions -AI00645,Research Scientist,267795,SGD,348134,EX,CT,Singapore,M,Egypt,50,"Java, Azure, Kubernetes, PyTorch, Docker",Associate,11,Transportation,2024-10-07,2024-11-10,1026,5.4,DeepTech Ventures -AI00646,AI Software Engineer,63052,EUR,53594,EN,FT,France,M,United Kingdom,100,"Scala, Python, MLOps",Master,0,Retail,2024-02-05,2024-03-22,1183,6.6,Cognitive Computing -AI00647,AI Architect,54424,USD,54424,EN,FL,United States,S,Austria,0,"R, Kubernetes, Mathematics, Hadoop, SQL",PhD,1,Energy,2024-01-02,2024-01-21,1220,9.2,DeepTech Ventures -AI00648,AI Software Engineer,67908,USD,67908,SE,FT,China,M,Colombia,100,"Git, Spark, AWS, Scala",Bachelor,6,Gaming,2024-01-21,2024-02-28,2163,9.4,Smart Analytics -AI00649,ML Ops Engineer,115395,GBP,86546,SE,FL,United Kingdom,S,United Kingdom,100,"R, Kubernetes, Data Visualization",Bachelor,6,Government,2024-10-28,2024-12-30,1312,7.8,Predictive Systems -AI00650,Data Scientist,122516,AUD,165397,SE,FT,Australia,S,South Africa,100,"Deep Learning, Python, Git, Kubernetes, GCP",Master,9,Transportation,2024-07-23,2024-10-03,2397,8.7,AI Innovations -AI00651,Machine Learning Researcher,118846,EUR,101019,SE,FL,France,S,France,50,"SQL, AWS, NLP, PyTorch, Computer Vision",PhD,5,Manufacturing,2024-10-06,2024-11-11,1725,9.3,Machine Intelligence Group -AI00652,Machine Learning Engineer,98835,USD,98835,MI,FT,Sweden,M,Sweden,0,"AWS, Deep Learning, TensorFlow",Bachelor,2,Consulting,2024-02-06,2024-03-15,705,9.3,Neural Networks Co -AI00653,Data Engineer,295640,USD,295640,EX,FT,United States,M,United States,0,"AWS, GCP, Git, SQL",Master,11,Media,2024-01-08,2024-02-14,1782,8.3,Machine Intelligence Group -AI00654,Machine Learning Engineer,136359,SGD,177267,SE,CT,Singapore,M,Singapore,50,"R, Deep Learning, MLOps",Bachelor,9,Telecommunications,2024-08-30,2024-09-28,769,9.6,TechCorp Inc -AI00655,Principal Data Scientist,187425,USD,187425,EX,CT,Sweden,L,Sweden,0,"SQL, TensorFlow, Docker, Python, GCP",PhD,13,Consulting,2025-02-05,2025-02-25,1415,9.3,Cognitive Computing -AI00656,Machine Learning Engineer,91932,USD,91932,MI,FL,Sweden,M,Sweden,50,"MLOps, Kubernetes, Tableau, Scala",PhD,2,Manufacturing,2024-09-06,2024-10-18,1272,6.8,TechCorp Inc -AI00657,AI Software Engineer,71409,USD,71409,EN,FT,United States,L,United States,0,"Git, Linux, Data Visualization, Deep Learning",PhD,0,Telecommunications,2024-01-23,2024-03-17,1482,9.7,Neural Networks Co -AI00658,Machine Learning Engineer,48739,USD,48739,EN,FL,Ireland,S,Latvia,50,"Python, TensorFlow, Linux, PyTorch",PhD,0,Retail,2024-03-28,2024-05-11,1628,5.1,Predictive Systems -AI00659,AI Architect,61632,EUR,52387,EN,CT,Germany,S,Colombia,50,"Spark, Kubernetes, Data Visualization, Hadoop",Bachelor,1,Real Estate,2025-02-05,2025-02-19,910,6.1,Cloud AI Solutions -AI00660,Machine Learning Researcher,98216,JPY,10803760,MI,CT,Japan,S,New Zealand,0,"Spark, Deep Learning, NLP, PyTorch, Data Visualization",PhD,4,Energy,2024-04-16,2024-06-22,1612,6.4,DataVision Ltd -AI00661,AI Product Manager,104633,EUR,88938,SE,FL,Germany,S,Germany,100,"PyTorch, Spark, Tableau, Data Visualization",Master,6,Education,2024-08-06,2024-10-17,1922,7.3,Digital Transformation LLC -AI00662,AI Software Engineer,41990,USD,41990,MI,CT,China,L,India,100,"Scala, Azure, Deep Learning, Spark, Git",Associate,2,Government,2024-07-30,2024-09-24,1928,9.8,Autonomous Tech -AI00663,Data Analyst,238728,SGD,310346,EX,CT,Singapore,S,Singapore,0,"Python, MLOps, TensorFlow, NLP, Tableau",Master,12,Gaming,2024-08-25,2024-10-04,2000,7.7,Algorithmic Solutions -AI00664,AI Consultant,329444,CHF,296500,EX,FL,Switzerland,M,Switzerland,100,"Hadoop, Scala, Linux, Python",Bachelor,14,Real Estate,2024-12-27,2025-02-10,1268,8,Smart Analytics -AI00665,Research Scientist,70081,USD,70081,EN,FT,Israel,L,Israel,100,"Hadoop, R, Tableau, Python",Bachelor,1,Government,2024-04-20,2024-06-20,1280,7.4,AI Innovations -AI00666,Head of AI,288084,USD,288084,EX,FT,Denmark,L,Denmark,0,"Docker, Hadoop, Linux",Associate,15,Education,2024-10-06,2024-12-15,1022,7.1,Autonomous Tech -AI00667,AI Consultant,65282,USD,65282,MI,FL,Israel,S,Israel,100,"Scala, Tableau, NLP",Associate,2,Consulting,2024-03-22,2024-05-19,2126,5.5,TechCorp Inc -AI00668,Machine Learning Engineer,126052,SGD,163868,SE,PT,Singapore,S,Singapore,50,"Java, Scala, MLOps, R, Linux",PhD,6,Consulting,2024-07-23,2024-09-18,1915,7.4,DataVision Ltd -AI00669,Data Scientist,247685,USD,247685,EX,PT,Ireland,M,South Africa,100,"Data Visualization, SQL, Linux, Scala",PhD,12,Automotive,2025-03-28,2025-05-31,1375,7.5,Cognitive Computing -AI00670,AI Software Engineer,80022,GBP,60017,MI,FL,United Kingdom,M,United Kingdom,0,"Linux, PyTorch, Python, Statistics, Deep Learning",Master,3,Energy,2024-03-11,2024-04-21,603,5.5,Smart Analytics -AI00671,Data Analyst,96062,SGD,124881,EN,CT,Singapore,L,Singapore,0,"SQL, Scala, Data Visualization",Associate,1,Finance,2024-09-11,2024-11-08,2460,8.6,Algorithmic Solutions -AI00672,Principal Data Scientist,174460,USD,174460,SE,FL,Denmark,L,Denmark,100,"R, Mathematics, Python, Data Visualization, Docker",Master,9,Media,2025-02-27,2025-04-16,960,8.7,Smart Analytics -AI00673,AI Software Engineer,183335,EUR,155835,EX,PT,Austria,M,Austria,100,"NLP, PyTorch, Hadoop, Tableau, SQL",PhD,12,Education,2024-04-24,2024-05-30,897,8.4,Neural Networks Co -AI00674,Data Engineer,223437,USD,223437,EX,FL,Sweden,M,Sweden,100,"Linux, R, SQL, AWS",Bachelor,18,Gaming,2025-02-14,2025-03-24,2274,6.2,Neural Networks Co -AI00675,AI Specialist,177360,USD,177360,SE,PT,Denmark,L,Turkey,50,"Azure, TensorFlow, SQL",Bachelor,6,Consulting,2024-07-23,2024-09-18,1564,7.1,AI Innovations -AI00676,AI Consultant,206532,JPY,22718520,EX,FT,Japan,M,Canada,100,"SQL, Deep Learning, MLOps, Linux",Bachelor,10,Technology,2024-02-22,2024-03-09,1130,6.4,Cloud AI Solutions -AI00677,Robotics Engineer,112216,EUR,95384,MI,CT,Austria,L,Austria,100,"Deep Learning, TensorFlow, Kubernetes",PhD,4,Energy,2024-12-10,2024-12-25,715,6.3,Algorithmic Solutions -AI00678,AI Software Engineer,55817,CAD,69771,EN,PT,Canada,S,Canada,100,"Python, Azure, Deep Learning, SQL",Associate,0,Technology,2025-01-24,2025-03-23,1550,6.1,Autonomous Tech -AI00679,AI Specialist,324267,USD,324267,EX,CT,Norway,L,Norway,50,"Scala, Java, Mathematics",PhD,11,Finance,2024-04-05,2024-06-05,1346,6.5,Predictive Systems -AI00680,NLP Engineer,76065,JPY,8367150,MI,FT,Japan,S,Japan,50,"R, SQL, Kubernetes, Java",PhD,4,Education,2025-02-21,2025-04-10,1473,5.6,Predictive Systems -AI00681,Machine Learning Researcher,146849,CHF,132164,SE,PT,Switzerland,M,Spain,0,"Azure, SQL, MLOps",PhD,8,Education,2024-07-17,2024-08-17,1337,7.4,Predictive Systems -AI00682,Head of AI,81041,SGD,105353,EN,FL,Singapore,M,India,50,"Kubernetes, SQL, PyTorch",PhD,0,Healthcare,2025-02-12,2025-04-21,722,5.5,Advanced Robotics -AI00683,Computer Vision Engineer,106945,USD,106945,EN,PT,United States,L,Malaysia,100,"Tableau, Java, AWS, Data Visualization, Scala",PhD,0,Government,2024-02-11,2024-04-01,615,9.4,Quantum Computing Inc -AI00684,Robotics Engineer,329543,USD,329543,EX,PT,Denmark,L,Singapore,100,"Data Visualization, Scala, Statistics, NLP, Hadoop",Associate,18,Technology,2024-08-01,2024-09-21,553,8.4,Neural Networks Co -AI00685,Machine Learning Engineer,92316,USD,92316,SE,CT,Israel,S,United States,100,"Kubernetes, Deep Learning, Scala, PyTorch, R",Associate,6,Transportation,2024-12-27,2025-03-08,834,7.2,Cognitive Computing -AI00686,AI Research Scientist,209495,JPY,23044450,EX,FL,Japan,S,Japan,100,"TensorFlow, AWS, Kubernetes",PhD,19,Government,2025-03-15,2025-05-18,1511,6.9,AI Innovations -AI00687,Data Analyst,201545,USD,201545,EX,CT,Ireland,L,Australia,0,"Scala, Mathematics, Spark, Kubernetes",PhD,17,Telecommunications,2024-09-16,2024-11-23,1552,6.7,Cloud AI Solutions -AI00688,Principal Data Scientist,122321,CAD,152901,SE,PT,Canada,S,Canada,0,"Hadoop, Python, Deep Learning",Master,6,Consulting,2024-09-28,2024-12-05,2048,6.1,Cloud AI Solutions -AI00689,Machine Learning Researcher,120647,CHF,108582,EN,CT,Switzerland,L,Switzerland,50,"Tableau, MLOps, Data Visualization",Bachelor,0,Manufacturing,2024-07-26,2024-10-04,1544,9.1,Algorithmic Solutions -AI00690,Data Analyst,56584,USD,56584,EN,FL,South Korea,S,Sweden,100,"Tableau, Mathematics, Kubernetes, Git",Bachelor,0,Consulting,2024-02-10,2024-04-17,1670,5.3,AI Innovations -AI00691,AI Architect,143314,CHF,128983,SE,CT,Switzerland,S,Australia,50,"Hadoop, Java, GCP",Bachelor,8,Finance,2024-09-02,2024-10-31,2319,8,Autonomous Tech -AI00692,NLP Engineer,130879,JPY,14396690,SE,PT,Japan,M,Japan,0,"Python, Azure, MLOps",Master,6,Real Estate,2024-04-12,2024-06-19,2280,5.4,Cloud AI Solutions -AI00693,Machine Learning Engineer,79223,AUD,106951,MI,FL,Australia,S,Egypt,100,"Java, Kubernetes, R, Azure",Associate,4,Government,2024-11-15,2024-12-29,1232,5.5,Quantum Computing Inc -AI00694,Deep Learning Engineer,145545,USD,145545,SE,FL,Norway,M,Norway,100,"Docker, Tableau, Hadoop, Computer Vision",Bachelor,5,Retail,2025-01-21,2025-03-14,1802,8.8,TechCorp Inc -AI00695,Computer Vision Engineer,100393,JPY,11043230,MI,PT,Japan,L,Japan,50,"Java, Spark, AWS",Master,3,Education,2024-09-07,2024-10-21,947,9.2,Neural Networks Co -AI00696,AI Software Engineer,197280,USD,197280,EX,FT,Ireland,S,Ireland,100,"TensorFlow, Kubernetes, Linux, NLP",Master,16,Telecommunications,2024-08-05,2024-09-08,777,6,Autonomous Tech -AI00697,Computer Vision Engineer,88090,USD,88090,MI,FT,South Korea,M,South Korea,100,"Python, Computer Vision, Scala, Spark, TensorFlow",Associate,3,Retail,2025-01-02,2025-02-08,1674,10,AI Innovations -AI00698,Computer Vision Engineer,69911,USD,69911,MI,FT,South Korea,S,South Korea,100,"Kubernetes, TensorFlow, GCP",Master,3,Automotive,2024-09-12,2024-11-16,582,7.3,DataVision Ltd -AI00699,ML Ops Engineer,218971,CHF,197074,EX,FL,Switzerland,M,Switzerland,0,"Mathematics, Python, Tableau, AWS",Associate,18,Telecommunications,2025-03-22,2025-04-06,1989,6.5,Digital Transformation LLC -AI00700,AI Product Manager,79860,EUR,67881,EN,FT,Austria,L,Austria,50,"Mathematics, NLP, Tableau, Java",Bachelor,0,Government,2025-04-26,2025-05-23,2214,7.6,TechCorp Inc -AI00701,AI Architect,118343,CAD,147929,SE,CT,Canada,M,Indonesia,100,"GCP, PyTorch, AWS, Tableau, Kubernetes",Master,9,Automotive,2024-11-03,2024-11-29,2230,5.7,Advanced Robotics -AI00702,Research Scientist,142832,USD,142832,SE,FL,Finland,L,Finland,100,"Spark, Deep Learning, Python, AWS",Bachelor,6,Consulting,2024-12-14,2025-02-24,2222,6,Neural Networks Co -AI00703,Computer Vision Engineer,103304,EUR,87808,SE,CT,France,S,South Korea,0,"Deep Learning, SQL, Mathematics, Kubernetes, Tableau",Master,9,Media,2024-08-06,2024-09-15,1382,9.6,Neural Networks Co -AI00704,NLP Engineer,51555,USD,51555,SE,FT,India,M,India,50,"Java, R, NLP",PhD,6,Technology,2024-12-15,2025-01-17,1452,8,AI Innovations -AI00705,Robotics Engineer,33564,USD,33564,MI,FT,India,L,Israel,0,"Scala, Tableau, Kubernetes, Deep Learning",Associate,4,Media,2024-03-30,2024-05-06,562,5.8,DataVision Ltd -AI00706,AI Specialist,46733,USD,46733,MI,FT,China,S,Ireland,50,"Scala, PyTorch, Data Visualization, SQL, Java",Associate,3,Media,2024-12-20,2025-02-09,777,9.4,Digital Transformation LLC -AI00707,AI Architect,163489,EUR,138966,SE,FL,Germany,L,Germany,50,"Spark, Python, TensorFlow, NLP",Bachelor,8,Technology,2024-11-16,2025-01-24,1573,9.4,Machine Intelligence Group -AI00708,AI Consultant,127499,SGD,165749,SE,CT,Singapore,M,Singapore,100,"Docker, R, GCP, Scala, Hadoop",Master,9,Government,2024-11-29,2025-01-22,830,9.8,AI Innovations -AI00709,Head of AI,169543,EUR,144112,SE,FT,Germany,L,Germany,50,"Statistics, Git, Linux, Hadoop, Kubernetes",PhD,8,Energy,2024-09-24,2024-10-28,1703,5.1,DeepTech Ventures -AI00710,AI Specialist,252321,EUR,214473,EX,FT,France,L,France,100,"Statistics, AWS, Azure",Bachelor,14,Education,2024-04-05,2024-05-07,966,9.9,Smart Analytics -AI00711,Robotics Engineer,83888,GBP,62916,MI,FT,United Kingdom,M,United Kingdom,100,"MLOps, Deep Learning, Docker, Spark",Master,2,Technology,2025-03-04,2025-04-02,1553,6.1,Quantum Computing Inc -AI00712,NLP Engineer,117983,AUD,159277,SE,FT,Australia,M,Finland,50,"Computer Vision, Data Visualization, Java",Associate,5,Media,2024-03-08,2024-04-07,2450,7.8,DeepTech Ventures -AI00713,Research Scientist,153305,SGD,199297,EX,FL,Singapore,M,Singapore,100,"R, Docker, Scala, Mathematics, PyTorch",PhD,19,Education,2025-03-03,2025-03-22,824,7.7,Smart Analytics -AI00714,Deep Learning Engineer,112643,JPY,12390730,SE,FT,Japan,S,Japan,50,"PyTorch, Python, TensorFlow, Mathematics, AWS",Associate,9,Gaming,2024-12-31,2025-03-13,1976,6.1,Predictive Systems -AI00715,AI Product Manager,64605,USD,64605,EN,FT,Norway,S,Norway,50,"Deep Learning, MLOps, Python",Associate,1,Gaming,2025-02-26,2025-03-14,875,8.6,Cloud AI Solutions -AI00716,Autonomous Systems Engineer,62679,EUR,53277,MI,CT,France,S,Ireland,50,"R, SQL, Kubernetes, Azure, TensorFlow",PhD,3,Consulting,2024-08-13,2024-09-08,819,7,Cognitive Computing -AI00717,AI Consultant,161602,EUR,137362,EX,PT,France,L,France,100,"Hadoop, Kubernetes, Git, Docker",Associate,11,Automotive,2024-02-20,2024-03-20,2361,9,Advanced Robotics -AI00718,Computer Vision Engineer,124703,GBP,93527,SE,PT,United Kingdom,M,Latvia,0,"AWS, PyTorch, Tableau",Bachelor,6,Healthcare,2024-09-30,2024-11-13,1138,8.4,Cognitive Computing -AI00719,Head of AI,200853,USD,200853,EX,FT,Israel,M,Israel,50,"R, Statistics, SQL, Deep Learning",Master,13,Technology,2024-11-11,2025-01-17,1274,7.5,Algorithmic Solutions -AI00720,ML Ops Engineer,34021,USD,34021,MI,PT,India,S,India,50,"Git, Python, GCP, SQL, Java",PhD,2,Energy,2024-02-15,2024-03-25,2324,5.3,Cognitive Computing -AI00721,Robotics Engineer,90355,EUR,76802,MI,CT,Germany,M,Germany,50,"Deep Learning, Data Visualization, NLP, R",Bachelor,2,Energy,2024-11-17,2024-12-20,2458,9.4,Future Systems -AI00722,Machine Learning Engineer,63360,USD,63360,EN,FL,Ireland,M,Ireland,100,"Computer Vision, MLOps, SQL, Docker, PyTorch",Master,1,Telecommunications,2024-10-22,2024-11-19,1383,5.1,DataVision Ltd -AI00723,Data Analyst,185352,USD,185352,EX,PT,Ireland,S,New Zealand,0,"Scala, MLOps, Data Visualization",Bachelor,10,Government,2024-09-27,2024-11-06,1306,6.1,Advanced Robotics -AI00724,AI Software Engineer,85462,SGD,111101,EN,FT,Singapore,L,Switzerland,50,"NLP, Kubernetes, Git",Master,1,Transportation,2024-05-11,2024-06-27,591,9.9,Predictive Systems -AI00725,AI Product Manager,119183,EUR,101306,SE,PT,Austria,L,Austria,100,"Git, MLOps, Spark, Linux, Hadoop",Associate,9,Telecommunications,2025-01-16,2025-02-23,2480,9.5,Digital Transformation LLC -AI00726,Machine Learning Engineer,116244,EUR,98807,SE,CT,Austria,M,Austria,50,"R, Kubernetes, Spark",Bachelor,6,Technology,2024-02-02,2024-03-04,1029,6.1,Algorithmic Solutions -AI00727,Machine Learning Researcher,287291,USD,287291,EX,FT,Norway,S,Norway,50,"Scala, R, Tableau",Master,19,Manufacturing,2024-08-27,2024-10-31,1944,9.3,Quantum Computing Inc -AI00728,Data Engineer,160191,EUR,136162,EX,FL,Germany,S,Germany,50,"Linux, Git, Statistics, Deep Learning, Java",PhD,17,Automotive,2024-11-28,2025-01-24,688,9.9,TechCorp Inc -AI00729,AI Architect,207916,USD,207916,EX,FL,South Korea,M,South Korea,100,"Kubernetes, Mathematics, Hadoop, Deep Learning",Master,15,Retail,2024-10-17,2024-11-25,1085,8.7,Algorithmic Solutions -AI00730,Deep Learning Engineer,215737,USD,215737,EX,CT,Israel,S,Israel,50,"Linux, Scala, Git, SQL",PhD,15,Manufacturing,2024-06-29,2024-08-27,1269,5.2,Neural Networks Co -AI00731,Principal Data Scientist,89008,USD,89008,EN,CT,Denmark,L,New Zealand,0,"PyTorch, AWS, MLOps",Master,0,Telecommunications,2024-01-04,2024-02-12,1540,8.3,Future Systems -AI00732,Principal Data Scientist,122155,GBP,91616,SE,PT,United Kingdom,S,United Kingdom,100,"PyTorch, Hadoop, Computer Vision",Bachelor,9,Media,2024-02-16,2024-03-27,1762,5.3,TechCorp Inc -AI00733,Data Scientist,40715,USD,40715,EN,FL,China,L,South Korea,0,"Python, NLP, Hadoop, Docker, Tableau",PhD,1,Technology,2024-07-06,2024-08-10,1018,7.9,Cloud AI Solutions -AI00734,Robotics Engineer,188499,CHF,169649,SE,PT,Switzerland,S,India,0,"Git, Data Visualization, Hadoop",Bachelor,9,Finance,2024-10-31,2024-11-18,870,6.6,Digital Transformation LLC -AI00735,AI Specialist,181167,GBP,135875,EX,PT,United Kingdom,M,Thailand,100,"Azure, MLOps, Mathematics, Docker",Bachelor,16,Transportation,2024-11-30,2025-01-25,1237,9.7,DataVision Ltd -AI00736,AI Software Engineer,137580,USD,137580,SE,CT,Denmark,M,Denmark,50,"Deep Learning, Kubernetes, AWS, Mathematics, GCP",PhD,7,Healthcare,2024-07-02,2024-09-06,1646,7.9,Neural Networks Co -AI00737,Autonomous Systems Engineer,81092,CAD,101365,EN,CT,Canada,L,India,0,"NLP, SQL, Statistics, Data Visualization, Scala",PhD,0,Finance,2025-04-27,2025-05-23,623,8.2,Digital Transformation LLC -AI00738,Principal Data Scientist,167011,EUR,141959,EX,PT,Germany,M,Russia,0,"Azure, MLOps, Python, Data Visualization, Mathematics",Master,16,Healthcare,2024-05-15,2024-06-12,2468,7.6,DeepTech Ventures -AI00739,Data Analyst,115690,SGD,150397,MI,CT,Singapore,M,Singapore,50,"Python, MLOps, Git",Master,2,Consulting,2024-11-25,2024-12-20,1357,6.2,Future Systems -AI00740,Head of AI,85081,JPY,9358910,MI,CT,Japan,M,Japan,100,"Docker, Git, Hadoop",Associate,3,Energy,2024-11-15,2024-11-29,1877,9.6,Smart Analytics -AI00741,AI Product Manager,204925,USD,204925,EX,CT,Norway,S,New Zealand,100,"TensorFlow, Azure, Scala, Kubernetes, Spark",PhD,13,Manufacturing,2025-03-10,2025-04-18,2392,5.3,Autonomous Tech -AI00742,NLP Engineer,71330,USD,71330,EN,FT,Ireland,M,Ireland,100,"Statistics, Kubernetes, Deep Learning, Scala, AWS",Master,1,Finance,2025-01-12,2025-02-03,1304,5.3,Smart Analytics -AI00743,ML Ops Engineer,147961,CHF,133165,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, Git, SQL",PhD,2,Gaming,2024-11-18,2025-01-27,2488,7,Digital Transformation LLC -AI00744,AI Architect,81537,EUR,69306,MI,PT,Germany,M,France,100,"GCP, Linux, Kubernetes",Associate,2,Media,2025-02-21,2025-03-08,1123,8.1,Quantum Computing Inc -AI00745,Autonomous Systems Engineer,169303,EUR,143908,EX,FL,Germany,M,Germany,0,"Linux, Kubernetes, AWS, Data Visualization",PhD,14,Transportation,2024-05-08,2024-07-09,1444,7,Machine Intelligence Group -AI00746,Autonomous Systems Engineer,79345,USD,79345,EN,FL,United States,L,United States,100,"Spark, Kubernetes, SQL, AWS",Associate,1,Gaming,2024-01-01,2024-03-03,2459,7.1,Cognitive Computing -AI00747,NLP Engineer,141710,EUR,120454,EX,FT,Austria,S,Argentina,100,"Azure, Python, Git, Docker",Master,12,Real Estate,2025-04-28,2025-06-20,975,7.4,AI Innovations -AI00748,Research Scientist,176540,USD,176540,EX,FT,Sweden,S,United States,0,"TensorFlow, Kubernetes, Git, Java, Docker",Master,16,Healthcare,2024-09-17,2024-11-19,738,5.5,Algorithmic Solutions -AI00749,Deep Learning Engineer,75872,SGD,98634,EN,FT,Singapore,S,Netherlands,0,"Hadoop, MLOps, Python, Computer Vision, Docker",Associate,0,Retail,2025-01-06,2025-01-30,1818,8.4,Digital Transformation LLC -AI00750,Machine Learning Researcher,39100,USD,39100,MI,CT,China,M,Netherlands,100,"SQL, Docker, Python, Mathematics",PhD,3,Energy,2025-04-08,2025-04-22,1101,5.7,DeepTech Ventures -AI00751,Data Analyst,60610,USD,60610,MI,PT,South Korea,S,South Korea,50,"PyTorch, Computer Vision, Mathematics, R",Associate,3,Finance,2025-03-23,2025-05-24,748,5.4,Digital Transformation LLC -AI00752,NLP Engineer,64997,USD,64997,EN,CT,Finland,L,Finland,50,"Computer Vision, TensorFlow, Java",PhD,0,Automotive,2024-12-01,2025-01-01,1749,7.9,Autonomous Tech -AI00753,Principal Data Scientist,79831,USD,79831,MI,FT,Finland,S,Finland,0,"Scala, Java, Kubernetes, Data Visualization, Git",Bachelor,4,Retail,2024-05-09,2024-06-22,1863,9.6,Autonomous Tech -AI00754,Data Analyst,75434,JPY,8297740,EN,FT,Japan,L,Austria,100,"Computer Vision, SQL, Linux, AWS, Mathematics",PhD,1,Technology,2025-04-23,2025-05-12,2180,7.3,DataVision Ltd -AI00755,NLP Engineer,135956,USD,135956,SE,PT,Israel,M,Israel,100,"Kubernetes, Scala, Computer Vision",Master,8,Transportation,2024-02-11,2024-04-20,1899,5.7,TechCorp Inc -AI00756,Machine Learning Engineer,91194,CAD,113993,MI,PT,Canada,S,Canada,0,"Azure, Spark, Linux, Scala, SQL",PhD,3,Media,2024-08-13,2024-09-20,689,9.9,Neural Networks Co -AI00757,Research Scientist,182045,USD,182045,EX,CT,Israel,S,India,100,"Computer Vision, Hadoop, Kubernetes, Spark, Statistics",PhD,10,Technology,2024-11-25,2025-01-26,1620,10,Digital Transformation LLC -AI00758,Data Engineer,143858,USD,143858,EX,FT,Israel,M,Israel,50,"Deep Learning, Kubernetes, Hadoop, Linux",Associate,10,Automotive,2025-01-03,2025-02-05,1182,7.8,Digital Transformation LLC -AI00759,Data Analyst,135781,USD,135781,SE,FT,Finland,M,Finland,100,"Linux, R, Hadoop, Computer Vision, Python",Master,7,Retail,2024-11-26,2025-02-03,1587,6.2,Cloud AI Solutions -AI00760,AI Product Manager,151948,USD,151948,MI,FL,Denmark,L,Germany,100,"Statistics, Computer Vision, NLP, Python, TensorFlow",Bachelor,3,Manufacturing,2024-11-11,2024-12-10,1738,6.3,Predictive Systems -AI00761,AI Research Scientist,97414,CAD,121768,SE,FL,Canada,S,Canada,0,"Tableau, R, SQL, GCP, Docker",Master,6,Healthcare,2024-08-04,2024-08-30,748,9.3,Autonomous Tech -AI00762,Autonomous Systems Engineer,44257,USD,44257,MI,PT,China,M,China,50,"Kubernetes, Hadoop, GCP, Scala, Azure",PhD,4,Manufacturing,2024-11-28,2024-12-23,1984,6.4,Autonomous Tech -AI00763,Machine Learning Researcher,183099,USD,183099,SE,FT,Denmark,M,Denmark,100,"GCP, Docker, MLOps, Tableau, PyTorch",Master,9,Manufacturing,2025-01-21,2025-02-11,542,8.9,Cloud AI Solutions -AI00764,AI Product Manager,66978,EUR,56931,EN,FT,France,M,France,50,"Azure, Linux, Statistics, NLP",Associate,0,Gaming,2025-04-06,2025-05-07,721,9.4,Cloud AI Solutions -AI00765,Computer Vision Engineer,58844,USD,58844,EN,PT,United States,S,Kenya,100,"SQL, Python, Mathematics",PhD,1,Technology,2024-03-15,2024-04-20,874,7.2,Digital Transformation LLC -AI00766,Data Scientist,86679,EUR,73677,EN,PT,France,L,France,50,"Scala, Docker, Spark, MLOps, NLP",PhD,1,Gaming,2024-04-09,2024-04-24,865,5.7,Cognitive Computing -AI00767,Research Scientist,102607,EUR,87216,MI,FL,Austria,L,Austria,50,"Scala, Python, Tableau, Statistics",Associate,4,Telecommunications,2025-04-16,2025-05-16,2191,8.4,Autonomous Tech -AI00768,AI Research Scientist,117860,USD,117860,MI,FL,Norway,S,Norway,0,"Linux, Python, Scala",Master,3,Consulting,2024-02-21,2024-03-23,1949,9.6,Cloud AI Solutions -AI00769,Data Engineer,53776,AUD,72598,EN,PT,Australia,M,Mexico,50,"PyTorch, Spark, TensorFlow",PhD,1,Energy,2025-03-31,2025-05-21,1959,10,Advanced Robotics -AI00770,Autonomous Systems Engineer,22245,USD,22245,EN,FL,India,S,India,100,"R, AWS, Mathematics, Deep Learning, MLOps",Bachelor,1,Automotive,2025-03-07,2025-04-27,2075,7.7,TechCorp Inc -AI00771,Deep Learning Engineer,86753,USD,86753,EN,CT,Denmark,S,Hungary,50,"Kubernetes, MLOps, SQL, Python",Bachelor,0,Consulting,2025-01-27,2025-03-19,527,8.3,Quantum Computing Inc -AI00772,Data Scientist,59445,CAD,74306,EN,PT,Canada,S,Canada,50,"Kubernetes, GCP, Java, Deep Learning, Statistics",Associate,0,Finance,2024-02-26,2024-03-21,1565,6.9,Autonomous Tech -AI00773,Machine Learning Researcher,181623,USD,181623,SE,FL,Norway,L,Norway,100,"Azure, Scala, Python, Git",Bachelor,7,Telecommunications,2024-02-14,2024-03-10,2148,9.1,Neural Networks Co -AI00774,Machine Learning Engineer,23848,USD,23848,EN,FL,China,S,Poland,0,"TensorFlow, Spark, NLP, Mathematics",Associate,1,Real Estate,2024-02-29,2024-04-17,1126,8.6,Machine Intelligence Group -AI00775,Head of AI,67555,USD,67555,SE,PT,China,L,China,100,"Mathematics, Scala, Java",PhD,5,Education,2024-11-30,2025-01-08,1445,8.8,Future Systems -AI00776,Autonomous Systems Engineer,156672,USD,156672,EX,FL,Sweden,L,Sweden,0,"Statistics, SQL, Python, AWS, Computer Vision",Associate,19,Real Estate,2025-03-23,2025-05-11,2253,7,AI Innovations -AI00777,Data Analyst,99310,USD,99310,EX,FT,China,S,Vietnam,50,"Scala, Java, Deep Learning",Associate,14,Transportation,2024-04-28,2024-05-28,1790,5.8,TechCorp Inc -AI00778,Data Scientist,106468,USD,106468,SE,FL,South Korea,S,Singapore,0,"Kubernetes, PyTorch, SQL, Computer Vision, Tableau",PhD,5,Energy,2025-02-07,2025-03-21,735,8.3,DataVision Ltd -AI00779,NLP Engineer,133549,JPY,14690390,SE,PT,Japan,L,Portugal,50,"Statistics, Docker, TensorFlow",Master,8,Government,2024-02-03,2024-03-05,762,7.5,Autonomous Tech -AI00780,AI Consultant,101850,USD,101850,EN,FL,Norway,L,Norway,50,"Mathematics, NLP, MLOps, Linux",PhD,1,Healthcare,2025-04-04,2025-04-24,1992,7.7,TechCorp Inc -AI00781,Data Analyst,135555,USD,135555,EX,FL,China,L,China,50,"Deep Learning, Scala, Python",Associate,18,Real Estate,2025-01-14,2025-02-16,1694,6.9,Advanced Robotics -AI00782,Data Scientist,194650,USD,194650,EX,CT,Norway,M,Norway,0,"GCP, Scala, PyTorch, SQL",Master,13,Automotive,2025-01-01,2025-01-16,1290,9.4,Cognitive Computing -AI00783,NLP Engineer,48184,USD,48184,SE,FT,India,S,India,50,"Kubernetes, Docker, Python, TensorFlow",PhD,8,Real Estate,2024-06-02,2024-07-06,526,7.4,Digital Transformation LLC -AI00784,NLP Engineer,102143,EUR,86822,MI,PT,Netherlands,S,Austria,100,"Docker, Git, Scala, Mathematics",Master,2,Technology,2024-10-02,2024-10-16,883,8.9,Cognitive Computing -AI00785,Data Engineer,130584,USD,130584,SE,FT,Finland,L,Hungary,0,"Kubernetes, Azure, Spark",PhD,6,Gaming,2024-05-29,2024-06-27,1303,8,Predictive Systems -AI00786,ML Ops Engineer,197290,USD,197290,SE,FL,Denmark,M,Nigeria,50,"Python, TensorFlow, Statistics, PyTorch, Deep Learning",Bachelor,5,Education,2024-08-30,2024-09-15,1376,8.8,TechCorp Inc -AI00787,AI Architect,57552,EUR,48919,EN,FL,Germany,M,Germany,50,"Hadoop, TensorFlow, Tableau",PhD,0,Retail,2024-04-21,2024-05-15,2185,5.4,Algorithmic Solutions -AI00788,AI Specialist,138325,USD,138325,SE,CT,Sweden,M,Sweden,0,"Azure, Spark, Data Visualization, R, Python",Master,7,Transportation,2024-10-25,2024-11-17,1112,5.6,Machine Intelligence Group -AI00789,AI Product Manager,62787,USD,62787,EN,FL,Norway,S,Singapore,0,"Hadoop, Scala, R, Python",Associate,1,Automotive,2024-09-11,2024-10-10,1204,5.1,Cloud AI Solutions -AI00790,AI Research Scientist,96898,EUR,82363,SE,FL,Austria,M,Austria,50,"Docker, Tableau, SQL, Deep Learning, MLOps",Bachelor,8,Healthcare,2024-09-15,2024-10-22,1719,6.3,Future Systems -AI00791,AI Software Engineer,101690,USD,101690,MI,CT,Norway,S,Norway,100,"Scala, Deep Learning, Git, TensorFlow",Bachelor,4,Telecommunications,2025-03-21,2025-05-01,2046,9.9,Predictive Systems -AI00792,Data Scientist,104342,USD,104342,MI,CT,United States,L,United States,50,"Azure, SQL, Python, AWS",Bachelor,2,Technology,2024-08-23,2024-09-21,2196,7.8,Future Systems -AI00793,Principal Data Scientist,182831,EUR,155406,EX,PT,Austria,S,Chile,100,"Kubernetes, Linux, Scala, Deep Learning, Azure",Master,18,Transportation,2024-12-22,2025-01-27,1334,5.8,Quantum Computing Inc -AI00794,AI Specialist,65362,EUR,55558,EN,PT,France,L,Japan,0,"TensorFlow, AWS, NLP, Data Visualization",Bachelor,1,Government,2024-09-12,2024-10-12,1819,5.2,Predictive Systems -AI00795,AI Software Engineer,116249,EUR,98812,SE,FL,France,M,France,50,"Scala, Java, MLOps, Azure",PhD,8,Finance,2024-05-02,2024-06-10,1595,8.6,Digital Transformation LLC -AI00796,Machine Learning Researcher,181065,USD,181065,EX,FL,Norway,S,Norway,0,"Java, R, Statistics, Linux, Mathematics",Master,19,Healthcare,2024-10-18,2024-11-03,2202,8,Machine Intelligence Group -AI00797,Data Engineer,110326,EUR,93777,SE,PT,France,S,France,0,"PyTorch, Hadoop, AWS, Python",Associate,8,Technology,2024-11-08,2024-12-14,739,9.3,Quantum Computing Inc -AI00798,AI Research Scientist,113275,EUR,96284,SE,FT,Netherlands,M,Netherlands,0,"Docker, Java, Tableau, Hadoop",Master,6,Consulting,2024-03-08,2024-04-17,1264,8,Quantum Computing Inc -AI00799,Autonomous Systems Engineer,86720,CAD,108400,SE,CT,Canada,S,Canada,0,"Spark, Kubernetes, SQL, Data Visualization",Bachelor,7,Consulting,2024-03-21,2024-05-18,821,6.7,Smart Analytics -AI00800,Deep Learning Engineer,88527,USD,88527,SE,CT,South Korea,M,South Korea,100,"Python, Docker, Linux, Spark, Scala",Master,8,Technology,2024-02-14,2024-04-27,1973,6.3,TechCorp Inc -AI00801,AI Software Engineer,75281,USD,75281,EN,FL,Finland,M,Finland,100,"Git, Python, Tableau, Spark",Associate,0,Technology,2024-07-12,2024-08-01,1666,8.4,Advanced Robotics -AI00802,Principal Data Scientist,63784,AUD,86108,EN,FL,Australia,L,Australia,100,"SQL, Deep Learning, Data Visualization, TensorFlow",Master,0,Healthcare,2025-02-14,2025-03-01,668,10,Quantum Computing Inc -AI00803,AI Product Manager,140500,SGD,182650,SE,CT,Singapore,L,Malaysia,0,"Kubernetes, Data Visualization, MLOps, Python, GCP",PhD,7,Energy,2024-12-15,2025-02-10,1733,8.6,Predictive Systems -AI00804,Deep Learning Engineer,30726,USD,30726,EN,FT,India,L,India,100,"Spark, Kubernetes, MLOps, Git",PhD,1,Telecommunications,2024-10-02,2024-10-18,782,7.9,Predictive Systems -AI00805,AI Specialist,242789,SGD,315626,EX,PT,Singapore,M,Singapore,50,"Data Visualization, Hadoop, MLOps, SQL",Associate,15,Manufacturing,2024-06-10,2024-07-03,592,8.7,DeepTech Ventures -AI00806,ML Ops Engineer,126827,USD,126827,EX,FT,South Korea,S,South Korea,0,"Python, Git, R, NLP, PyTorch",Master,17,Real Estate,2024-05-24,2024-06-19,2410,9.6,Digital Transformation LLC -AI00807,Robotics Engineer,77753,JPY,8552830,MI,CT,Japan,M,Japan,100,"Linux, Python, Java, Azure, Git",PhD,2,Automotive,2025-04-09,2025-06-19,845,9.4,Neural Networks Co -AI00808,Autonomous Systems Engineer,204502,USD,204502,EX,PT,United States,S,United States,100,"NLP, Linux, PyTorch",Master,13,Consulting,2024-11-23,2024-12-14,1899,9.7,Machine Intelligence Group -AI00809,Machine Learning Engineer,76869,EUR,65339,MI,PT,France,S,France,50,"SQL, Git, TensorFlow, Statistics",Bachelor,4,Healthcare,2025-03-11,2025-04-24,1199,7.6,AI Innovations -AI00810,Computer Vision Engineer,128192,USD,128192,SE,FT,Ireland,S,India,0,"R, SQL, PyTorch, Docker, Deep Learning",Bachelor,5,Energy,2024-11-01,2024-12-12,2010,5.4,Cognitive Computing -AI00811,Machine Learning Engineer,234782,CHF,211304,EX,PT,Switzerland,M,Switzerland,0,"Mathematics, SQL, MLOps, TensorFlow, Kubernetes",Associate,19,Education,2024-02-05,2024-03-25,1540,7.4,Quantum Computing Inc -AI00812,Robotics Engineer,243016,USD,243016,EX,CT,Norway,S,Norway,0,"SQL, Deep Learning, Data Visualization",PhD,14,Consulting,2024-04-20,2024-06-27,2207,5.9,Machine Intelligence Group -AI00813,ML Ops Engineer,232932,GBP,174699,EX,CT,United Kingdom,L,United Kingdom,50,"Statistics, Spark, Python, AWS, Azure",Bachelor,19,Education,2024-05-27,2024-07-02,2321,7.9,DeepTech Ventures -AI00814,AI Software Engineer,157713,EUR,134056,EX,FT,France,L,France,100,"Statistics, Azure, NLP, Data Visualization, Deep Learning",Associate,11,Real Estate,2024-03-29,2024-04-18,1275,7.3,Quantum Computing Inc -AI00815,Computer Vision Engineer,78731,GBP,59048,MI,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, PyTorch, SQL, Mathematics, Scala",Bachelor,4,Retail,2025-01-12,2025-01-26,893,9.7,DataVision Ltd -AI00816,Machine Learning Engineer,118802,CAD,148503,SE,PT,Canada,L,Canada,50,"GCP, Docker, Azure, Tableau, PyTorch",PhD,5,Telecommunications,2025-01-18,2025-02-08,2228,9.6,Digital Transformation LLC -AI00817,AI Software Engineer,86119,CHF,77507,EN,PT,Switzerland,M,Switzerland,50,"MLOps, Scala, Azure",Master,1,Retail,2025-03-14,2025-04-18,1655,7.2,Future Systems -AI00818,Head of AI,148519,GBP,111389,EX,CT,United Kingdom,M,United Kingdom,50,"MLOps, Java, Scala, R",PhD,19,Retail,2025-02-11,2025-02-26,1578,5.8,Neural Networks Co -AI00819,AI Research Scientist,48058,USD,48058,EN,PT,South Korea,S,South Korea,100,"Spark, Hadoop, TensorFlow, Data Visualization, Computer Vision",Associate,1,Manufacturing,2024-08-26,2024-11-06,1378,5.2,Future Systems -AI00820,AI Architect,68183,EUR,57956,EN,FT,France,M,France,0,"Mathematics, SQL, Spark, Kubernetes, PyTorch",PhD,0,Retail,2024-12-08,2025-02-11,1399,5.9,Algorithmic Solutions -AI00821,Principal Data Scientist,237151,GBP,177863,EX,FT,United Kingdom,S,United Kingdom,100,"Git, Computer Vision, Tableau, Azure",PhD,15,Energy,2025-04-02,2025-05-20,2094,9.5,Algorithmic Solutions -AI00822,Data Engineer,95252,USD,95252,MI,PT,Ireland,S,Ireland,50,"Scala, MLOps, SQL",Bachelor,4,Real Estate,2024-11-05,2024-12-17,1479,9.9,AI Innovations -AI00823,NLP Engineer,142166,JPY,15638260,SE,CT,Japan,L,Japan,50,"Python, TensorFlow, Computer Vision, AWS, Statistics",Master,5,Transportation,2024-11-02,2024-12-20,1946,6.1,DeepTech Ventures -AI00824,Machine Learning Engineer,107965,USD,107965,SE,CT,Sweden,S,Romania,100,"SQL, Kubernetes, MLOps, NLP, GCP",Bachelor,9,Healthcare,2024-08-16,2024-08-31,1211,7.3,Advanced Robotics -AI00825,ML Ops Engineer,239943,EUR,203952,EX,FT,Netherlands,L,Netherlands,50,"Azure, MLOps, R, Python, TensorFlow",Bachelor,12,Real Estate,2024-05-16,2024-07-11,602,9.1,Machine Intelligence Group -AI00826,Robotics Engineer,287023,USD,287023,EX,PT,Ireland,L,Ireland,100,"Computer Vision, Linux, GCP, Scala",Master,10,Education,2025-03-31,2025-04-29,543,7.4,Cloud AI Solutions -AI00827,AI Architect,108794,USD,108794,MI,FL,Norway,L,Ukraine,0,"Hadoop, Kubernetes, Docker, Statistics, SQL",Associate,4,Government,2024-09-27,2024-11-26,1050,5.9,Advanced Robotics -AI00828,AI Specialist,91776,USD,91776,EN,FT,United States,M,Germany,0,"Docker, Computer Vision, AWS, Python, TensorFlow",PhD,1,Technology,2024-03-19,2024-04-25,2314,6.1,Predictive Systems -AI00829,Robotics Engineer,61890,USD,61890,EN,PT,South Korea,L,Italy,0,"Java, R, SQL",Bachelor,1,Consulting,2024-12-20,2025-01-15,709,5.4,Advanced Robotics -AI00830,Data Analyst,345294,USD,345294,EX,FT,Norway,L,Norway,100,"Kubernetes, TensorFlow, GCP",PhD,11,Telecommunications,2025-02-03,2025-04-06,1012,6.6,DataVision Ltd -AI00831,AI Product Manager,78569,USD,78569,MI,CT,Israel,L,Israel,0,"Spark, PyTorch, MLOps, NLP, Kubernetes",Master,4,Healthcare,2024-11-20,2024-12-05,2033,7.4,DataVision Ltd -AI00832,Autonomous Systems Engineer,66673,EUR,56672,EN,PT,France,M,France,100,"Git, Scala, Python",Master,0,Telecommunications,2024-11-27,2024-12-14,1825,8.6,Future Systems -AI00833,Machine Learning Researcher,183500,CHF,165150,SE,CT,Switzerland,M,Switzerland,50,"TensorFlow, Python, Computer Vision, Statistics, Scala",PhD,8,Transportation,2025-01-24,2025-03-08,686,9.1,Digital Transformation LLC -AI00834,ML Ops Engineer,165234,SGD,214804,EX,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Python, NLP",Associate,10,Manufacturing,2024-05-07,2024-05-22,913,6,Future Systems -AI00835,Principal Data Scientist,119549,SGD,155414,MI,FT,Singapore,L,Singapore,100,"Kubernetes, NLP, MLOps",Master,2,Consulting,2024-11-05,2024-12-12,1344,5.7,Digital Transformation LLC -AI00836,NLP Engineer,325936,USD,325936,EX,PT,Norway,L,Norway,100,"Scala, Spark, Deep Learning",Bachelor,19,Government,2024-09-01,2024-11-04,1066,8.3,Cognitive Computing -AI00837,ML Ops Engineer,157221,SGD,204387,SE,FT,Singapore,L,Singapore,0,"PyTorch, Java, GCP, Python, Hadoop",Associate,7,Gaming,2025-02-24,2025-03-23,908,8.5,Future Systems -AI00838,Machine Learning Engineer,98221,USD,98221,SE,PT,South Korea,L,South Korea,0,"Python, Deep Learning, AWS, Statistics",Bachelor,6,Finance,2024-05-04,2024-06-10,1650,6.7,Algorithmic Solutions -AI00839,Autonomous Systems Engineer,155502,GBP,116627,EX,CT,United Kingdom,M,India,50,"Kubernetes, Java, Docker, Hadoop",Master,11,Healthcare,2025-03-18,2025-05-10,503,9.5,DeepTech Ventures -AI00840,Principal Data Scientist,276679,USD,276679,EX,FT,Denmark,L,Denmark,0,"PyTorch, GCP, MLOps, AWS, Mathematics",Master,11,Telecommunications,2024-07-11,2024-09-21,1457,8.7,Predictive Systems -AI00841,AI Product Manager,187955,EUR,159762,EX,CT,Germany,S,Turkey,0,"Docker, Git, Linux",Master,19,Manufacturing,2025-02-01,2025-04-04,2439,7.9,Smart Analytics -AI00842,Data Engineer,135585,USD,135585,MI,FT,Denmark,L,Denmark,100,"AWS, Python, GCP",Associate,4,Real Estate,2024-06-02,2024-08-11,2302,5.1,Cloud AI Solutions -AI00843,Machine Learning Researcher,138945,USD,138945,SE,PT,United States,L,Kenya,50,"Java, Azure, Data Visualization, NLP",Master,5,Transportation,2024-07-08,2024-08-01,1468,7.3,TechCorp Inc -AI00844,Autonomous Systems Engineer,89723,EUR,76265,MI,FL,Netherlands,S,Netherlands,50,"Python, PyTorch, Spark, TensorFlow",Associate,3,Education,2024-06-17,2024-08-12,914,5.3,Advanced Robotics -AI00845,Computer Vision Engineer,74250,USD,74250,EN,FL,United States,L,Colombia,100,"NLP, R, TensorFlow",Associate,0,Consulting,2024-09-22,2024-10-07,2179,5.3,Predictive Systems -AI00846,Machine Learning Researcher,209546,USD,209546,EX,FT,Norway,M,Norway,100,"NLP, SQL, PyTorch, Git, Spark",Associate,11,Telecommunications,2025-01-24,2025-02-23,2485,7.7,Smart Analytics -AI00847,AI Product Manager,137463,JPY,15120930,EX,FL,Japan,S,Japan,0,"AWS, Git, Python, NLP, Scala",Associate,13,Healthcare,2024-05-28,2024-06-11,1088,7.9,Autonomous Tech -AI00848,Head of AI,83657,USD,83657,EN,FT,Ireland,L,Ireland,0,"Python, MLOps, Data Visualization, Spark",Master,0,Government,2024-06-25,2024-08-14,1808,6.4,Predictive Systems -AI00849,Data Engineer,120560,USD,120560,MI,FT,United States,M,Vietnam,0,"Hadoop, MLOps, Spark, Kubernetes",Bachelor,3,Retail,2024-08-18,2024-09-15,1128,7.5,AI Innovations -AI00850,AI Architect,87119,USD,87119,SE,PT,Israel,S,Denmark,100,"Scala, Statistics, Java",Associate,7,Media,2025-04-05,2025-05-17,1585,8.6,AI Innovations -AI00851,Principal Data Scientist,71418,USD,71418,MI,FL,South Korea,L,South Korea,100,"AWS, Linux, R",Master,4,Government,2024-10-17,2024-12-22,1154,8.8,Predictive Systems -AI00852,AI Consultant,46727,USD,46727,EX,FT,India,S,India,50,"SQL, Docker, Python",Bachelor,19,Automotive,2024-08-31,2024-10-20,1896,6.9,Advanced Robotics -AI00853,Data Scientist,164321,USD,164321,EX,PT,Sweden,S,Netherlands,50,"Kubernetes, GCP, PyTorch",Master,16,Energy,2024-08-01,2024-09-10,2008,6.4,Predictive Systems -AI00854,AI Product Manager,80460,JPY,8850600,EN,FL,Japan,M,Indonesia,0,"Python, Scala, TensorFlow",Bachelor,1,Energy,2025-01-17,2025-03-02,2267,9.9,Quantum Computing Inc -AI00855,Robotics Engineer,99510,EUR,84584,SE,CT,France,S,France,50,"Deep Learning, SQL, PyTorch",Associate,8,Technology,2025-04-26,2025-06-26,2131,9.8,Neural Networks Co -AI00856,Head of AI,145409,CHF,130868,MI,PT,Switzerland,M,Switzerland,100,"Git, NLP, Tableau, Python",Associate,2,Energy,2024-06-03,2024-08-04,1347,8.8,Cognitive Computing -AI00857,Data Analyst,289465,USD,289465,EX,PT,United States,M,United States,50,"Docker, MLOps, Python, Statistics, SQL",Bachelor,13,Retail,2025-04-08,2025-05-20,1420,9.2,Digital Transformation LLC -AI00858,ML Ops Engineer,85216,JPY,9373760,EN,FT,Japan,M,Japan,0,"AWS, Data Visualization, Python",Bachelor,1,Telecommunications,2024-09-17,2024-10-23,797,8.8,Cognitive Computing -AI00859,AI Software Engineer,88921,CAD,111151,MI,CT,Canada,S,Canada,100,"SQL, Kubernetes, Azure, Hadoop",PhD,3,Technology,2024-09-01,2024-09-21,1630,8.8,Advanced Robotics -AI00860,NLP Engineer,65144,USD,65144,EN,FL,Sweden,L,Argentina,100,"Hadoop, MLOps, Docker, Deep Learning, Statistics",Associate,0,Retail,2024-09-16,2024-11-25,1121,5.5,Quantum Computing Inc -AI00861,Data Analyst,103403,USD,103403,MI,CT,Israel,M,Israel,50,"Tableau, SQL, Linux, NLP, Kubernetes",Bachelor,3,Technology,2024-01-14,2024-02-11,2139,6.6,Smart Analytics -AI00862,Deep Learning Engineer,121368,USD,121368,SE,FL,Israel,M,Israel,50,"Spark, Python, Data Visualization",PhD,8,Energy,2024-04-01,2024-05-29,1567,5.2,Predictive Systems -AI00863,Head of AI,168109,AUD,226947,SE,CT,Australia,L,Australia,50,"Data Visualization, GCP, SQL",Bachelor,7,Gaming,2025-01-25,2025-03-22,2457,9.6,Cognitive Computing -AI00864,Robotics Engineer,40616,USD,40616,MI,CT,China,S,Canada,0,"TensorFlow, Git, Python, Hadoop",Associate,2,Finance,2024-07-31,2024-08-27,2010,5.9,Neural Networks Co -AI00865,NLP Engineer,176886,CHF,159197,EX,CT,Switzerland,S,Switzerland,0,"PyTorch, Scala, Deep Learning, Computer Vision",Master,16,Real Estate,2024-02-18,2024-04-22,1045,9.8,DataVision Ltd -AI00866,Autonomous Systems Engineer,107548,EUR,91416,MI,CT,Germany,M,Germany,0,"Linux, Python, TensorFlow",Master,2,Consulting,2024-08-16,2024-10-17,1812,9.7,AI Innovations -AI00867,AI Software Engineer,313203,CHF,281883,EX,FL,Switzerland,S,Switzerland,50,"Kubernetes, Python, Mathematics, Java",Master,15,Finance,2025-04-02,2025-06-14,1078,6,Algorithmic Solutions -AI00868,AI Consultant,147571,EUR,125435,EX,FT,France,M,United States,0,"R, GCP, Git",Associate,12,Consulting,2024-12-14,2025-02-12,679,5,Advanced Robotics -AI00869,Deep Learning Engineer,239432,EUR,203517,EX,PT,France,M,France,100,"R, NLP, Java, Hadoop",Associate,19,Automotive,2024-06-03,2024-08-02,1371,8,Machine Intelligence Group -AI00870,Machine Learning Researcher,119559,USD,119559,MI,CT,United States,L,United States,0,"PyTorch, Linux, NLP, MLOps, Java",Bachelor,2,Real Estate,2025-03-31,2025-05-15,546,5.9,Quantum Computing Inc -AI00871,AI Consultant,72051,SGD,93666,EN,FT,Singapore,S,Singapore,100,"AWS, Kubernetes, Tableau, Azure, Java",Master,0,Education,2024-09-11,2024-10-07,2394,6,Future Systems -AI00872,Machine Learning Engineer,80766,AUD,109034,EN,FT,Australia,L,India,100,"Java, R, NLP, Azure",PhD,1,Media,2025-02-03,2025-02-18,845,7.2,Future Systems -AI00873,Computer Vision Engineer,75201,CHF,67681,EN,PT,Switzerland,M,Switzerland,100,"Data Visualization, SQL, Scala, Deep Learning, Hadoop",Associate,0,Telecommunications,2024-08-11,2024-10-21,505,6.5,Cloud AI Solutions -AI00874,Machine Learning Engineer,367330,CHF,330597,EX,PT,Switzerland,L,Belgium,100,"Kubernetes, SQL, Mathematics, Deep Learning, Computer Vision",Master,12,Finance,2025-01-25,2025-02-26,1732,6.1,Cloud AI Solutions -AI00875,AI Specialist,99824,CHF,89842,EN,FL,Switzerland,S,Switzerland,100,"Tableau, Linux, AWS, Python, Mathematics",Master,1,Manufacturing,2025-01-30,2025-03-15,1530,9.4,DataVision Ltd -AI00876,Computer Vision Engineer,183643,GBP,137732,EX,FL,United Kingdom,L,United Kingdom,50,"Git, Python, NLP",Bachelor,16,Transportation,2024-09-30,2024-10-22,1295,9.9,DataVision Ltd -AI00877,Research Scientist,86875,CAD,108594,MI,FL,Canada,L,Canada,0,"Kubernetes, NLP, SQL",Bachelor,2,Education,2025-01-27,2025-03-10,2499,8.1,DataVision Ltd -AI00878,AI Architect,92050,USD,92050,EN,PT,Denmark,S,Denmark,100,"Spark, Docker, Computer Vision, NLP, Data Visualization",PhD,0,Healthcare,2025-02-04,2025-03-26,1907,5,DataVision Ltd -AI00879,Machine Learning Engineer,188547,EUR,160265,EX,CT,Germany,S,Indonesia,100,"Hadoop, SQL, Computer Vision, PyTorch, Docker",Bachelor,10,Transportation,2024-07-01,2024-08-17,1395,7.2,Cloud AI Solutions -AI00880,Data Scientist,93400,USD,93400,MI,FT,Ireland,S,Ireland,0,"Scala, Azure, Data Visualization, PyTorch, Git",Bachelor,4,Government,2024-11-09,2025-01-08,1829,5.7,Machine Intelligence Group -AI00881,Data Scientist,121492,EUR,103268,SE,PT,Germany,M,Germany,50,"AWS, Tableau, Kubernetes, Python",Associate,5,Technology,2025-04-11,2025-06-15,799,6.4,Future Systems -AI00882,AI Software Engineer,214716,CAD,268395,EX,CT,Canada,M,Canada,100,"SQL, Java, Git, Scala, Spark",Bachelor,13,Transportation,2024-01-29,2024-04-02,1629,7.4,Smart Analytics -AI00883,Machine Learning Engineer,96552,USD,96552,MI,PT,Denmark,S,Chile,0,"Spark, Git, Data Visualization, Kubernetes, SQL",Bachelor,3,Transportation,2025-03-01,2025-04-25,1746,6.7,DataVision Ltd -AI00884,Research Scientist,82126,EUR,69807,MI,CT,France,M,France,50,"Tableau, Hadoop, Python, AWS",PhD,4,Energy,2024-06-20,2024-08-31,1435,6.3,AI Innovations -AI00885,ML Ops Engineer,101793,EUR,86524,MI,FT,France,L,France,50,"TensorFlow, Azure, Python, Deep Learning",PhD,3,Education,2024-07-14,2024-07-31,926,5.5,Future Systems -AI00886,AI Research Scientist,119593,CAD,149491,MI,PT,Canada,L,Canada,100,"Data Visualization, Python, Tableau",Master,3,Government,2024-02-17,2024-04-23,908,6.3,Autonomous Tech -AI00887,AI Software Engineer,83380,USD,83380,EX,FL,China,M,China,0,"R, Scala, AWS, Data Visualization",PhD,18,Education,2024-08-19,2024-09-06,848,9.6,Advanced Robotics -AI00888,NLP Engineer,104077,EUR,88465,MI,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, Docker, Azure",Associate,3,Transportation,2025-03-29,2025-05-19,821,6.8,Smart Analytics -AI00889,Research Scientist,107155,EUR,91082,SE,PT,France,M,France,100,"Scala, SQL, GCP, Git, Linux",Associate,5,Real Estate,2024-09-29,2024-11-03,2162,6.2,Autonomous Tech -AI00890,AI Architect,95613,USD,95613,EN,FL,Denmark,M,Denmark,50,"Hadoop, Docker, Scala",Associate,0,Consulting,2024-11-08,2024-12-06,1404,8.3,TechCorp Inc -AI00891,AI Research Scientist,79915,USD,79915,MI,CT,Israel,S,Israel,0,"PyTorch, Hadoop, TensorFlow",Master,2,Consulting,2024-01-08,2024-01-29,2279,9.7,Advanced Robotics -AI00892,ML Ops Engineer,152836,USD,152836,SE,FT,Israel,L,Israel,100,"Statistics, PyTorch, NLP, Git",Associate,9,Education,2024-01-25,2024-02-24,2225,5.8,Predictive Systems -AI00893,AI Research Scientist,201144,SGD,261487,EX,FT,Singapore,M,Singapore,50,"Linux, AWS, R, Deep Learning, Docker",Associate,10,Government,2024-11-09,2025-01-10,1814,7.9,TechCorp Inc -AI00894,Machine Learning Researcher,74068,USD,74068,MI,FT,Israel,S,Israel,100,"SQL, PyTorch, Linux",PhD,4,Healthcare,2024-11-11,2024-12-06,1384,5.9,Digital Transformation LLC -AI00895,Principal Data Scientist,94861,EUR,80632,MI,FT,Netherlands,S,Netherlands,50,"Git, Scala, Tableau, Spark",Master,2,Government,2024-06-01,2024-07-10,1711,5.7,Autonomous Tech -AI00896,Head of AI,89534,USD,89534,MI,FL,South Korea,M,Romania,100,"Azure, AWS, GCP, Git, Kubernetes",PhD,4,Consulting,2024-02-21,2024-04-30,1229,7.5,AI Innovations -AI00897,Research Scientist,121009,USD,121009,MI,PT,Denmark,L,Switzerland,50,"R, Scala, Computer Vision, Azure",Associate,2,Government,2024-10-17,2024-12-20,2092,7.5,Autonomous Tech -AI00898,AI Software Engineer,98503,USD,98503,MI,FT,Denmark,M,United Kingdom,100,"Kubernetes, Linux, Hadoop",Bachelor,3,Energy,2025-01-24,2025-03-07,2120,7.1,Algorithmic Solutions -AI00899,Autonomous Systems Engineer,92133,USD,92133,MI,FL,Finland,L,Finland,100,"R, Scala, GCP",Bachelor,2,Automotive,2024-08-24,2024-10-18,2014,6.8,Predictive Systems -AI00900,Research Scientist,108765,USD,108765,MI,PT,United States,M,United States,0,"Spark, TensorFlow, Java, Azure",Bachelor,4,Automotive,2024-06-24,2024-07-28,1043,8.9,Autonomous Tech -AI00901,Machine Learning Engineer,93440,CHF,84096,EN,CT,Switzerland,M,Switzerland,0,"Statistics, Git, Kubernetes, Python, Azure",Bachelor,0,Retail,2024-10-17,2024-11-20,659,6.1,Cloud AI Solutions -AI00902,AI Architect,88745,SGD,115369,MI,FT,Singapore,S,Singapore,100,"SQL, Deep Learning, GCP, MLOps, Spark",Associate,4,Finance,2025-03-02,2025-03-22,1741,9.5,Algorithmic Solutions -AI00903,Research Scientist,105976,USD,105976,SE,PT,Ireland,M,Ireland,100,"SQL, Hadoop, Kubernetes",Associate,7,Transportation,2024-03-16,2024-05-20,1015,7.6,Digital Transformation LLC -AI00904,NLP Engineer,59221,USD,59221,MI,PT,South Korea,S,South Korea,0,"Statistics, Spark, Tableau, Java",Associate,3,Media,2024-09-09,2024-10-19,1905,5.3,Quantum Computing Inc -AI00905,NLP Engineer,61996,USD,61996,EN,FT,Sweden,L,United States,100,"Scala, Kubernetes, Computer Vision, SQL",PhD,0,Gaming,2024-02-25,2024-03-23,2259,7.8,Quantum Computing Inc -AI00906,ML Ops Engineer,90426,EUR,76862,MI,FT,France,S,France,50,"Git, Data Visualization, Spark",Master,3,Real Estate,2025-04-02,2025-04-28,1535,6.2,Autonomous Tech -AI00907,AI Consultant,60924,EUR,51785,EN,PT,France,S,France,0,"Scala, Hadoop, Java",Associate,0,Healthcare,2024-08-09,2024-09-03,2378,7.5,Advanced Robotics -AI00908,Data Engineer,243192,CAD,303990,EX,CT,Canada,L,Canada,0,"Scala, Azure, Kubernetes, Java, Statistics",Bachelor,16,Automotive,2024-03-07,2024-05-19,1815,9,Machine Intelligence Group -AI00909,Deep Learning Engineer,166087,EUR,141174,EX,FT,France,L,France,0,"Mathematics, Git, Data Visualization, Scala",Associate,10,Finance,2024-01-20,2024-02-14,2264,9.3,Smart Analytics -AI00910,Research Scientist,85173,USD,85173,EN,CT,Finland,L,Finland,0,"Statistics, Java, NLP, Git",Bachelor,0,Real Estate,2024-07-18,2024-09-06,2477,5.6,Machine Intelligence Group -AI00911,AI Specialist,309247,CHF,278322,EX,CT,Switzerland,L,Switzerland,100,"Computer Vision, GCP, Statistics, Azure, TensorFlow",Associate,10,Telecommunications,2024-02-18,2024-03-26,749,5.1,Digital Transformation LLC -AI00912,Computer Vision Engineer,121556,EUR,103323,MI,FL,Germany,L,Germany,0,"Data Visualization, Scala, PyTorch",PhD,3,Gaming,2025-04-17,2025-05-04,1461,5.2,Neural Networks Co -AI00913,AI Consultant,89998,JPY,9899780,EN,CT,Japan,L,Japan,50,"Scala, TensorFlow, Linux",PhD,1,Technology,2024-06-11,2024-07-20,617,8,Cognitive Computing -AI00914,AI Architect,63415,EUR,53903,MI,FT,France,S,France,100,"Kubernetes, Scala, Hadoop, Java, NLP",Master,3,Energy,2025-02-19,2025-04-13,1601,5.4,Future Systems -AI00915,Data Scientist,132964,USD,132964,MI,PT,Denmark,M,Denmark,0,"Scala, Python, MLOps",Master,2,Energy,2024-04-01,2024-06-11,1070,6.9,Machine Intelligence Group -AI00916,ML Ops Engineer,65099,SGD,84629,EN,PT,Singapore,S,Singapore,50,"Linux, PyTorch, SQL",Associate,0,Transportation,2024-02-03,2024-02-21,2192,5.1,DataVision Ltd -AI00917,AI Product Manager,170410,USD,170410,EX,FT,South Korea,L,South Korea,100,"MLOps, PyTorch, Tableau, SQL",Associate,16,Healthcare,2024-01-25,2024-02-18,1497,9.6,DataVision Ltd -AI00918,Data Engineer,25440,USD,25440,EN,CT,India,M,India,0,"Kubernetes, Scala, AWS",Master,1,Gaming,2024-10-28,2024-11-12,987,6.4,Advanced Robotics -AI00919,Research Scientist,173489,JPY,19083790,SE,FT,Japan,L,France,50,"Git, SQL, Kubernetes, Mathematics, PyTorch",Bachelor,8,Energy,2025-01-12,2025-01-29,647,5,Cloud AI Solutions -AI00920,Computer Vision Engineer,216939,USD,216939,EX,FT,United States,L,United States,100,"GCP, Git, MLOps, Mathematics, Scala",Master,13,Real Estate,2024-02-18,2024-04-25,1487,5.8,Algorithmic Solutions -AI00921,Autonomous Systems Engineer,117695,USD,117695,SE,FL,United States,S,Austria,50,"Hadoop, Azure, Java, Linux, Deep Learning",Bachelor,9,Gaming,2024-04-30,2024-06-10,894,9.4,Neural Networks Co -AI00922,AI Specialist,78936,AUD,106564,MI,CT,Australia,M,Australia,100,"Python, Git, TensorFlow, Deep Learning",Associate,4,Telecommunications,2024-09-07,2024-11-13,1081,9,Cloud AI Solutions -AI00923,NLP Engineer,113661,USD,113661,EN,FT,Norway,L,Norway,50,"Python, PyTorch, Git, Linux",Associate,0,Manufacturing,2025-02-16,2025-04-25,1471,5.9,Quantum Computing Inc -AI00924,Computer Vision Engineer,226030,JPY,24863300,EX,FT,Japan,S,Japan,50,"Git, SQL, Spark",Bachelor,17,Energy,2025-01-04,2025-02-16,744,9.8,AI Innovations -AI00925,Machine Learning Researcher,162220,USD,162220,EX,CT,Finland,S,Russia,50,"Spark, Data Visualization, PyTorch",Master,17,Transportation,2024-01-27,2024-03-12,862,5.5,Future Systems -AI00926,Deep Learning Engineer,165689,USD,165689,EX,FT,Ireland,S,Ireland,0,"R, TensorFlow, GCP, Linux, Statistics",PhD,19,Automotive,2024-11-13,2024-11-29,567,9.5,Cognitive Computing -AI00927,Principal Data Scientist,319536,CHF,287582,EX,FT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Java, Tableau",PhD,16,Technology,2024-01-22,2024-02-17,1950,6,DeepTech Ventures -AI00928,Data Scientist,97294,USD,97294,SE,CT,Israel,M,Israel,50,"Azure, Java, Spark, Linux, R",PhD,7,Manufacturing,2024-07-17,2024-08-21,985,7.9,Quantum Computing Inc -AI00929,Machine Learning Researcher,94506,USD,94506,EN,FT,Denmark,L,Denmark,50,"Docker, Scala, Azure, Mathematics, MLOps",Associate,1,Consulting,2024-09-29,2024-11-06,2181,9.4,Quantum Computing Inc -AI00930,Data Engineer,122519,USD,122519,SE,PT,Israel,M,Israel,50,"Data Visualization, MLOps, Hadoop, Docker",Bachelor,8,Manufacturing,2024-07-19,2024-08-09,644,7.3,Machine Intelligence Group -AI00931,Autonomous Systems Engineer,61916,USD,61916,MI,FT,South Korea,S,South Korea,100,"Java, Statistics, GCP, Kubernetes, NLP",Associate,2,Energy,2024-10-16,2024-11-03,1639,5.1,Autonomous Tech -AI00932,Principal Data Scientist,78823,USD,78823,MI,FL,Israel,M,India,50,"Python, GCP, TensorFlow, Mathematics",Associate,4,Technology,2024-09-07,2024-09-26,756,5.2,Machine Intelligence Group -AI00933,Data Engineer,111124,USD,111124,EN,CT,Denmark,L,China,0,"Spark, GCP, Data Visualization",Master,0,Technology,2024-04-23,2024-07-01,1021,8.5,Neural Networks Co -AI00934,Robotics Engineer,91289,EUR,77596,EN,FL,Netherlands,L,Netherlands,0,"PyTorch, Spark, Azure, Kubernetes, Java",Master,0,Education,2024-02-06,2024-03-10,972,8.5,DataVision Ltd -AI00935,AI Specialist,195659,USD,195659,SE,PT,Norway,L,Norway,50,"Python, Hadoop, TensorFlow, Computer Vision",PhD,6,Media,2024-02-08,2024-03-18,1789,7,Future Systems -AI00936,Data Engineer,199412,EUR,169500,EX,PT,Germany,S,Norway,50,"Java, Scala, Docker",Bachelor,17,Government,2024-02-05,2024-03-08,1254,8.1,Smart Analytics -AI00937,Data Engineer,202421,USD,202421,EX,FL,Norway,L,Norway,100,"Kubernetes, Git, PyTorch",Master,19,Manufacturing,2024-11-22,2025-01-28,2135,6.4,Machine Intelligence Group -AI00938,Data Scientist,133682,GBP,100262,MI,FL,United Kingdom,L,United Kingdom,100,"Hadoop, Spark, MLOps, GCP, R",Associate,3,Manufacturing,2025-03-20,2025-05-05,2382,8,Autonomous Tech -AI00939,Data Analyst,205143,GBP,153857,EX,PT,United Kingdom,L,South Africa,0,"TensorFlow, Azure, NLP",Associate,11,Finance,2024-08-28,2024-10-29,2193,9.1,Future Systems -AI00940,Head of AI,27765,USD,27765,EN,CT,China,S,China,0,"MLOps, Deep Learning, Python, Tableau",Bachelor,1,Consulting,2025-01-15,2025-02-12,968,9.3,Cloud AI Solutions -AI00941,NLP Engineer,170181,USD,170181,EX,PT,Ireland,M,Ireland,100,"Deep Learning, Python, Azure, TensorFlow",Bachelor,11,Gaming,2024-12-26,2025-01-24,2089,8,DataVision Ltd -AI00942,ML Ops Engineer,103167,USD,103167,MI,CT,United States,M,United States,100,"AWS, Kubernetes, MLOps",Associate,2,Healthcare,2024-04-05,2024-04-21,1873,8,Predictive Systems -AI00943,ML Ops Engineer,194546,USD,194546,EX,PT,Sweden,L,Sweden,0,"TensorFlow, Docker, Python, Hadoop",Master,16,Retail,2025-01-07,2025-03-05,1532,7.2,Digital Transformation LLC -AI00944,Research Scientist,130072,USD,130072,EX,CT,Israel,S,Israel,100,"R, Data Visualization, Java",Master,13,Government,2024-10-14,2024-11-20,2006,5.4,Cloud AI Solutions -AI00945,AI Specialist,39197,USD,39197,EN,PT,China,L,Australia,0,"Kubernetes, Java, SQL, NLP",Associate,1,Energy,2024-05-17,2024-07-08,1770,6.7,Quantum Computing Inc -AI00946,Autonomous Systems Engineer,204421,EUR,173758,EX,FL,Austria,L,Austria,50,"PyTorch, Data Visualization, Azure",Master,14,Energy,2024-07-30,2024-09-05,2389,8.5,Neural Networks Co -AI00947,Head of AI,112925,CHF,101633,EN,FT,Switzerland,L,Switzerland,100,"SQL, GCP, Spark, Azure, Linux",Bachelor,0,Government,2024-11-07,2024-11-26,1221,5.7,DataVision Ltd -AI00948,Data Scientist,265788,SGD,345524,EX,FT,Singapore,M,Turkey,0,"MLOps, Data Visualization, Scala, Python, AWS",Associate,18,Technology,2025-01-26,2025-04-07,2270,5.4,Smart Analytics -AI00949,Machine Learning Researcher,98150,USD,98150,EN,FL,Denmark,L,Denmark,0,"Data Visualization, Java, Hadoop",PhD,1,Energy,2025-03-11,2025-04-27,1648,7.6,Autonomous Tech -AI00950,Data Engineer,126741,USD,126741,SE,FL,United States,S,Romania,50,"PyTorch, Data Visualization, Azure, Computer Vision",Master,9,Finance,2024-05-29,2024-07-20,1974,5.9,Predictive Systems -AI00951,ML Ops Engineer,75006,USD,75006,EN,FL,Israel,M,Austria,100,"MLOps, TensorFlow, Scala",Associate,1,Finance,2024-02-15,2024-03-01,1642,7.3,DeepTech Ventures -AI00952,AI Research Scientist,84346,EUR,71694,MI,FT,Austria,S,France,0,"Statistics, Spark, GCP",Associate,4,Manufacturing,2024-09-20,2024-10-27,2188,7.5,DataVision Ltd -AI00953,Autonomous Systems Engineer,48241,USD,48241,SE,PT,India,M,India,50,"SQL, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-03-16,2025-05-06,2398,9.9,Neural Networks Co -AI00954,Research Scientist,162681,EUR,138279,EX,CT,Germany,L,Germany,50,"Python, Scala, Data Visualization",Associate,18,Telecommunications,2025-02-21,2025-03-09,2201,9.8,Advanced Robotics -AI00955,Deep Learning Engineer,125204,JPY,13772440,SE,CT,Japan,S,Vietnam,100,"Data Visualization, Kubernetes, Scala, NLP",Master,7,Retail,2024-04-30,2024-05-20,2284,5.9,Cloud AI Solutions -AI00956,Machine Learning Engineer,140001,EUR,119001,SE,FT,Netherlands,M,Luxembourg,50,"Python, TensorFlow, GCP, Computer Vision, Java",Bachelor,8,Manufacturing,2024-12-14,2025-02-06,1825,6.5,Autonomous Tech -AI00957,AI Software Engineer,162125,AUD,218869,SE,FT,Australia,L,Austria,100,"Computer Vision, Docker, TensorFlow",Bachelor,8,Consulting,2024-12-10,2025-02-07,565,5.4,Predictive Systems -AI00958,Deep Learning Engineer,128132,SGD,166572,SE,FL,Singapore,S,Japan,100,"Python, NLP, TensorFlow",PhD,7,Technology,2024-08-10,2024-09-24,1112,6.2,Cognitive Computing -AI00959,NLP Engineer,225554,USD,225554,SE,FT,Denmark,L,Latvia,50,"PyTorch, R, Docker",Bachelor,8,Technology,2024-09-12,2024-11-17,1301,9.3,Cloud AI Solutions -AI00960,ML Ops Engineer,130639,EUR,111043,SE,FT,Germany,M,Germany,0,"Python, Hadoop, PyTorch, Git, TensorFlow",PhD,7,Healthcare,2024-09-12,2024-11-12,1996,6.9,TechCorp Inc -AI00961,Data Analyst,66422,USD,66422,EN,FT,United States,S,United States,0,"Python, Hadoop, Kubernetes",Associate,0,Retail,2024-05-13,2024-07-18,1765,5.4,Autonomous Tech -AI00962,AI Architect,54625,CAD,68281,EN,CT,Canada,S,Ireland,0,"Scala, SQL, GCP, Computer Vision, Mathematics",Bachelor,0,Technology,2024-05-01,2024-07-08,1946,5.7,Cloud AI Solutions -AI00963,ML Ops Engineer,135145,USD,135145,MI,PT,Norway,M,Norway,50,"SQL, Docker, PyTorch, GCP, Kubernetes",Bachelor,3,Automotive,2025-04-27,2025-05-15,998,7.5,Smart Analytics -AI00964,ML Ops Engineer,61177,CAD,76471,EN,FL,Canada,S,Canada,100,"Spark, R, AWS, GCP, MLOps",Bachelor,0,Consulting,2025-04-04,2025-05-30,1465,6.8,Cognitive Computing -AI00965,AI Product Manager,74961,USD,74961,EX,FT,China,L,China,100,"Kubernetes, Git, Java, Azure, Tableau",PhD,16,Consulting,2024-07-17,2024-09-05,954,6.8,Smart Analytics -AI00966,NLP Engineer,47280,USD,47280,MI,PT,China,M,China,100,"Computer Vision, TensorFlow, Statistics, Python",PhD,2,Finance,2025-03-30,2025-06-05,985,9.4,Algorithmic Solutions -AI00967,Research Scientist,141577,USD,141577,EX,PT,Finland,S,Finland,50,"AWS, SQL, Python",Associate,13,Transportation,2024-09-16,2024-10-16,1955,6.1,TechCorp Inc -AI00968,NLP Engineer,130504,CHF,117454,EN,FT,Switzerland,L,Philippines,100,"Spark, MLOps, Tableau, Git",Bachelor,0,Media,2025-02-11,2025-02-26,691,8.4,Neural Networks Co -AI00969,Research Scientist,107421,USD,107421,MI,CT,Norway,S,Norway,50,"Git, Docker, Tableau, PyTorch",Bachelor,2,Consulting,2024-08-02,2024-09-23,1782,8.9,DataVision Ltd -AI00970,Data Analyst,93042,USD,93042,MI,PT,United States,S,United States,50,"Statistics, Linux, Git, Hadoop, Mathematics",Master,2,Finance,2024-10-14,2024-11-02,803,5.2,DataVision Ltd -AI00971,AI Consultant,168047,USD,168047,EX,FL,Ireland,L,Ireland,0,"Data Visualization, Linux, Docker, Python, GCP",Master,11,Government,2024-06-25,2024-08-04,1693,9.7,Predictive Systems -AI00972,AI Specialist,27281,USD,27281,EN,PT,China,S,Latvia,100,"Java, SQL, Tableau, GCP",PhD,1,Telecommunications,2025-01-04,2025-03-01,1739,7.1,Advanced Robotics -AI00973,Research Scientist,99145,USD,99145,MI,FL,United States,M,United States,100,"Kubernetes, Mathematics, Data Visualization, MLOps, Hadoop",Master,4,Media,2025-01-20,2025-03-09,954,9.2,Advanced Robotics -AI00974,Deep Learning Engineer,121002,USD,121002,SE,PT,Finland,S,Finland,100,"AWS, NLP, Kubernetes",Master,8,Consulting,2024-03-07,2024-05-12,1557,8.6,Cognitive Computing -AI00975,Data Scientist,259814,USD,259814,EX,PT,Norway,M,Vietnam,50,"PyTorch, R, TensorFlow, AWS, Statistics",Associate,12,Automotive,2024-04-15,2024-05-07,1416,5,DeepTech Ventures -AI00976,Computer Vision Engineer,209072,EUR,177711,EX,CT,France,L,France,100,"TensorFlow, PyTorch, SQL, AWS",Bachelor,15,Transportation,2024-03-23,2024-05-16,1826,7,Predictive Systems -AI00977,AI Software Engineer,50802,USD,50802,SE,CT,China,M,Russia,50,"MLOps, Computer Vision, Data Visualization, Java",PhD,5,Energy,2024-10-13,2024-11-20,501,6.5,Cognitive Computing -AI00978,NLP Engineer,112292,JPY,12352120,MI,PT,Japan,M,Japan,100,"Docker, Hadoop, Kubernetes, AWS",Bachelor,2,Gaming,2024-09-04,2024-10-30,875,8.7,TechCorp Inc -AI00979,Machine Learning Engineer,255076,USD,255076,EX,PT,Ireland,L,Finland,0,"Azure, Docker, Scala",PhD,15,Finance,2024-12-15,2025-02-21,1651,6.2,Digital Transformation LLC -AI00980,Head of AI,75393,EUR,64084,MI,FL,Netherlands,S,Finland,50,"Scala, Hadoop, Linux, GCP",Master,2,Consulting,2024-12-15,2025-01-30,1146,5.1,Quantum Computing Inc -AI00981,Head of AI,96519,USD,96519,EN,FL,United States,L,United States,100,"TensorFlow, Tableau, Git, Scala",Master,1,Finance,2024-07-24,2024-09-08,984,9.6,Autonomous Tech -AI00982,Deep Learning Engineer,135767,USD,135767,SE,FL,Sweden,L,Ukraine,50,"Scala, Azure, Git, Python, R",Associate,7,Gaming,2024-09-05,2024-10-13,736,8.7,DataVision Ltd -AI00983,AI Research Scientist,169082,USD,169082,EX,FT,Finland,L,Finland,50,"GCP, Hadoop, Python, Tableau, Mathematics",Master,17,Finance,2024-02-10,2024-03-22,914,6.9,Quantum Computing Inc -AI00984,AI Software Engineer,91630,EUR,77886,MI,FL,Germany,L,United States,50,"SQL, Linux, Data Visualization, NLP",Bachelor,3,Finance,2024-12-31,2025-03-04,2243,5.6,Machine Intelligence Group -AI00985,Research Scientist,172863,USD,172863,EX,CT,United States,M,United States,100,"SQL, Scala, Kubernetes",Bachelor,13,Transportation,2024-10-24,2024-11-08,2023,8.9,DataVision Ltd -AI00986,Head of AI,103897,USD,103897,MI,FL,Finland,L,Finland,100,"Scala, Java, Git, Azure, R",Associate,3,Retail,2025-04-06,2025-05-02,1242,8.9,Future Systems -AI00987,Computer Vision Engineer,93834,CAD,117293,MI,PT,Canada,L,Canada,100,"TensorFlow, PyTorch, AWS",Associate,2,Gaming,2024-09-01,2024-10-21,1303,5.8,Smart Analytics -AI00988,Autonomous Systems Engineer,53634,GBP,40226,EN,CT,United Kingdom,S,United Kingdom,0,"SQL, Hadoop, Kubernetes",PhD,0,Telecommunications,2025-04-16,2025-06-15,1608,7.3,Machine Intelligence Group -AI00989,AI Research Scientist,127594,USD,127594,SE,FT,Finland,L,Finland,0,"Python, TensorFlow, Hadoop, PyTorch",Bachelor,8,Automotive,2024-12-19,2025-02-24,926,6.4,Future Systems -AI00990,AI Product Manager,292915,CHF,263624,EX,FT,Switzerland,L,Thailand,100,"Data Visualization, Python, R, Azure",Bachelor,16,Media,2025-01-14,2025-02-25,2345,8.2,Future Systems -AI00991,Data Scientist,174020,USD,174020,EX,FT,Israel,S,Israel,100,"TensorFlow, PyTorch, MLOps, Computer Vision",Bachelor,18,Media,2025-01-25,2025-04-08,2090,6.6,Cloud AI Solutions -AI00992,ML Ops Engineer,88526,EUR,75247,MI,CT,Germany,S,Egypt,100,"Python, Git, MLOps, NLP, Spark",Master,4,Real Estate,2025-03-05,2025-05-17,1279,7.6,Cognitive Computing -AI00993,AI Software Engineer,74475,AUD,100541,EN,PT,Australia,M,Australia,0,"TensorFlow, Data Visualization, R",Associate,1,Transportation,2024-09-09,2024-10-10,734,9.8,Neural Networks Co -AI00994,Deep Learning Engineer,96427,USD,96427,EX,CT,China,S,China,100,"Computer Vision, Hadoop, Statistics, Deep Learning",PhD,18,Automotive,2024-10-10,2024-11-10,1393,7.3,Cognitive Computing -AI00995,ML Ops Engineer,225810,SGD,293553,EX,FT,Singapore,S,India,100,"Data Visualization, Spark, Kubernetes",PhD,19,Gaming,2025-02-19,2025-04-15,1937,8.2,Cloud AI Solutions -AI00996,AI Research Scientist,168512,EUR,143235,EX,CT,Netherlands,S,Hungary,0,"Java, Linux, MLOps, Tableau",Bachelor,10,Consulting,2024-10-15,2024-11-29,929,6.5,Cognitive Computing -AI00997,Head of AI,168159,GBP,126119,EX,CT,United Kingdom,M,United Kingdom,50,"Azure, PyTorch, GCP, Deep Learning, Kubernetes",PhD,14,Finance,2024-05-26,2024-06-27,1479,5.4,Cognitive Computing -AI00998,Research Scientist,59148,CAD,73935,EN,CT,Canada,L,Canada,0,"AWS, R, PyTorch",PhD,1,Government,2024-11-07,2024-12-12,1951,7.1,Predictive Systems -AI00999,Data Analyst,65802,GBP,49352,EN,PT,United Kingdom,L,Ghana,100,"Azure, Hadoop, Git",PhD,0,Telecommunications,2024-03-20,2024-05-18,1364,6.8,DataVision Ltd -AI01000,AI Architect,110206,EUR,93675,MI,CT,France,L,France,100,"Git, R, Python, Azure, Tableau",PhD,4,Finance,2024-11-29,2025-01-07,903,6.5,Autonomous Tech -AI01001,Data Analyst,149976,EUR,127480,SE,FL,France,L,France,100,"GCP, Git, Data Visualization, PyTorch",Bachelor,9,Energy,2024-05-31,2024-08-07,1685,7.2,TechCorp Inc -AI01002,Principal Data Scientist,179731,AUD,242637,EX,CT,Australia,M,Australia,50,"Python, GCP, Kubernetes, Deep Learning",Bachelor,18,Education,2024-03-29,2024-05-12,2328,7.2,Algorithmic Solutions -AI01003,Research Scientist,148216,USD,148216,EX,FL,Israel,S,Israel,100,"Kubernetes, Python, Scala, Computer Vision",PhD,10,Telecommunications,2024-12-13,2025-02-14,1572,6.3,Machine Intelligence Group -AI01004,AI Research Scientist,69697,CAD,87121,MI,FL,Canada,S,Canada,0,"GCP, AWS, Hadoop, Statistics, Docker",PhD,4,Automotive,2025-01-05,2025-03-09,1809,6.1,Future Systems -AI01005,Autonomous Systems Engineer,193479,CHF,174131,SE,CT,Switzerland,S,Switzerland,50,"Computer Vision, Linux, Tableau, NLP",Associate,6,Manufacturing,2025-02-01,2025-04-12,1620,9,Predictive Systems -AI01006,Data Engineer,27327,USD,27327,EN,CT,India,M,India,100,"Hadoop, Python, SQL, Azure, Kubernetes",PhD,1,Gaming,2024-03-10,2024-04-08,858,8.8,AI Innovations -AI01007,Deep Learning Engineer,175817,USD,175817,SE,PT,Denmark,L,Denmark,50,"SQL, Python, GCP, Computer Vision",PhD,9,Automotive,2024-12-14,2025-02-05,2179,10,Future Systems -AI01008,AI Software Engineer,79605,EUR,67664,MI,FT,France,S,France,50,"Mathematics, SQL, Computer Vision",PhD,2,Technology,2024-05-03,2024-07-10,1656,9.9,Smart Analytics -AI01009,AI Specialist,136610,USD,136610,SE,FL,Denmark,M,Denmark,100,"NLP, Azure, Data Visualization, Kubernetes",Bachelor,6,Education,2024-10-29,2025-01-06,1763,9.8,TechCorp Inc -AI01010,Data Scientist,54165,EUR,46040,EN,CT,France,S,France,100,"PyTorch, Git, Mathematics, SQL",PhD,1,Healthcare,2024-12-17,2025-01-12,1474,7,DataVision Ltd -AI01011,AI Consultant,82548,USD,82548,EN,FL,Denmark,S,Malaysia,50,"R, Tableau, Kubernetes",Associate,1,Real Estate,2025-02-20,2025-03-18,1171,6.9,AI Innovations -AI01012,Research Scientist,149033,USD,149033,EX,FL,South Korea,M,South Korea,100,"SQL, R, Docker, Data Visualization",Bachelor,17,Technology,2024-06-15,2024-08-13,1619,9.1,Machine Intelligence Group -AI01013,Machine Learning Engineer,26672,USD,26672,MI,PT,India,M,India,50,"AWS, PyTorch, MLOps, Deep Learning",PhD,2,Real Estate,2024-11-21,2025-01-10,1601,9.1,Algorithmic Solutions -AI01014,AI Consultant,103610,USD,103610,MI,FT,Sweden,L,Sweden,50,"Mathematics, Python, TensorFlow, Scala",Associate,3,Government,2024-07-02,2024-08-27,859,6.4,Predictive Systems -AI01015,Principal Data Scientist,59901,GBP,44926,EN,CT,United Kingdom,M,Colombia,100,"R, Hadoop, Python, Computer Vision",Bachelor,1,Finance,2024-03-20,2024-05-27,2189,8.2,Cognitive Computing -AI01016,Machine Learning Engineer,84403,USD,84403,MI,FT,Finland,M,India,0,"Tableau, Spark, Python",PhD,4,Finance,2024-09-10,2024-11-05,2085,5.6,Neural Networks Co -AI01017,AI Product Manager,235236,EUR,199951,EX,FL,France,M,South Africa,50,"GCP, Python, Data Visualization, MLOps, TensorFlow",Associate,10,Healthcare,2024-09-01,2024-10-11,2164,7.5,Machine Intelligence Group -AI01018,AI Research Scientist,140841,USD,140841,SE,FL,United States,S,United States,100,"Python, TensorFlow, Kubernetes",PhD,9,Finance,2024-10-17,2024-11-29,1005,5.2,Future Systems -AI01019,Deep Learning Engineer,64188,EUR,54560,EN,PT,Austria,M,Austria,0,"Kubernetes, Scala, Mathematics, SQL",Bachelor,1,Media,2025-01-16,2025-02-01,2217,5.6,Digital Transformation LLC -AI01020,Principal Data Scientist,140677,CHF,126609,SE,FL,Switzerland,S,Switzerland,100,"Python, TensorFlow, GCP, PyTorch",PhD,6,Retail,2024-05-22,2024-06-14,1249,5.2,Machine Intelligence Group -AI01021,Research Scientist,275555,USD,275555,EX,FT,Ireland,L,Egypt,0,"R, Linux, Scala",Associate,15,Retail,2024-12-16,2025-01-14,801,6.9,TechCorp Inc -AI01022,AI Specialist,174133,CHF,156720,SE,FT,Switzerland,M,Switzerland,0,"R, Deep Learning, TensorFlow",Associate,8,Real Estate,2025-01-23,2025-02-18,1540,9.6,Smart Analytics -AI01023,Machine Learning Engineer,49918,USD,49918,EN,CT,South Korea,M,South Korea,0,"Git, Python, SQL",PhD,0,Manufacturing,2025-04-17,2025-05-07,1226,8.1,AI Innovations -AI01024,Computer Vision Engineer,211602,USD,211602,EX,FL,Norway,L,Turkey,50,"AWS, Hadoop, NLP, Computer Vision, Statistics",Master,16,Real Estate,2025-03-27,2025-04-30,1244,7.3,Neural Networks Co -AI01025,AI Software Engineer,192792,USD,192792,EX,FT,Israel,L,Ireland,50,"Scala, NLP, SQL, Linux, Docker",PhD,15,Technology,2024-06-12,2024-08-11,2314,6.2,Digital Transformation LLC -AI01026,AI Specialist,70846,EUR,60219,MI,CT,Austria,S,Turkey,100,"TensorFlow, Java, R",Associate,4,Gaming,2024-02-11,2024-04-07,1268,9.4,Digital Transformation LLC -AI01027,AI Architect,93783,USD,93783,EN,PT,United States,M,United States,100,"MLOps, Java, Azure, Mathematics, PyTorch",Bachelor,1,Finance,2024-05-19,2024-06-10,1828,10,Neural Networks Co -AI01028,AI Architect,41072,USD,41072,MI,FT,China,S,China,0,"R, Docker, MLOps",Associate,3,Telecommunications,2024-04-11,2024-05-24,2158,6.6,Advanced Robotics -AI01029,AI Architect,102805,CAD,128506,MI,PT,Canada,M,Switzerland,100,"Azure, TensorFlow, Data Visualization, NLP",Master,3,Education,2024-12-16,2025-02-02,1000,9.9,Autonomous Tech -AI01030,AI Product Manager,113537,USD,113537,MI,FT,Ireland,L,Ireland,0,"GCP, Scala, Hadoop",PhD,4,Media,2024-01-20,2024-03-21,1063,8.1,DeepTech Ventures -AI01031,Research Scientist,73590,USD,73590,EN,FL,Denmark,M,Denmark,100,"Python, Git, Tableau, R",Master,1,Retail,2024-11-01,2024-12-27,1490,9.2,Digital Transformation LLC -AI01032,Computer Vision Engineer,96582,USD,96582,EN,CT,Denmark,L,Denmark,100,"Java, Computer Vision, GCP",PhD,0,Real Estate,2024-08-27,2024-09-29,649,9.1,DataVision Ltd -AI01033,AI Research Scientist,62705,USD,62705,EN,PT,Israel,M,India,0,"Java, GCP, Linux, Spark, Python",Bachelor,0,Gaming,2024-10-19,2024-12-08,723,5.1,Smart Analytics -AI01034,AI Product Manager,77955,GBP,58466,EN,FT,United Kingdom,M,United Kingdom,50,"Data Visualization, Computer Vision, Scala",Master,0,Education,2024-06-07,2024-07-04,2444,7,Autonomous Tech -AI01035,Data Analyst,129874,AUD,175330,EX,FT,Australia,S,Australia,0,"Linux, Statistics, Computer Vision",PhD,15,Education,2024-11-16,2024-12-05,2443,7.5,Quantum Computing Inc -AI01036,AI Architect,106907,GBP,80180,MI,CT,United Kingdom,L,United Kingdom,100,"NLP, Java, SQL, Spark, Mathematics",Associate,4,Gaming,2024-12-08,2025-02-16,1589,7.3,Algorithmic Solutions -AI01037,AI Consultant,110152,USD,110152,MI,CT,United States,L,United States,0,"Tableau, Azure, R, NLP",Bachelor,4,Gaming,2024-02-24,2024-03-27,976,8.9,Cognitive Computing -AI01038,AI Research Scientist,49922,USD,49922,MI,FT,China,L,China,50,"Azure, Spark, Scala, SQL, Deep Learning",Bachelor,4,Government,2024-07-26,2024-09-14,1580,8.8,DataVision Ltd -AI01039,AI Software Engineer,84890,USD,84890,EN,CT,Ireland,L,Ireland,100,"GCP, Hadoop, Azure, Scala",PhD,0,Gaming,2024-05-28,2024-07-01,2159,9.2,Cloud AI Solutions -AI01040,Data Scientist,73564,EUR,62529,MI,PT,France,M,Singapore,50,"Scala, Tableau, Docker, SQL, Mathematics",Associate,4,Consulting,2024-04-05,2024-05-26,1702,7.5,Cognitive Computing -AI01041,Autonomous Systems Engineer,196201,USD,196201,SE,PT,United States,L,Philippines,0,"Git, Python, Java",Master,5,Consulting,2025-02-15,2025-04-07,1756,8.8,Cloud AI Solutions -AI01042,NLP Engineer,164425,USD,164425,SE,CT,Finland,L,Italy,0,"GCP, Docker, R, Git",Master,9,Education,2024-07-17,2024-09-02,1881,5.6,Autonomous Tech -AI01043,ML Ops Engineer,158518,JPY,17436980,SE,FT,Japan,L,United Kingdom,0,"GCP, NLP, Deep Learning, Docker, R",Bachelor,6,Healthcare,2025-02-06,2025-02-25,2218,7.2,Quantum Computing Inc -AI01044,Autonomous Systems Engineer,137246,USD,137246,MI,PT,Norway,M,Norway,100,"TensorFlow, Kubernetes, AWS, Linux, Docker",Bachelor,4,Consulting,2024-04-12,2024-05-14,609,8.4,Machine Intelligence Group -AI01045,NLP Engineer,222330,EUR,188981,EX,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Scala",Associate,15,Automotive,2025-04-08,2025-05-12,1335,9.6,Autonomous Tech -AI01046,ML Ops Engineer,73721,USD,73721,MI,FL,Israel,S,Sweden,100,"Java, Tableau, MLOps",Master,2,Real Estate,2025-03-06,2025-04-14,1797,5.2,Predictive Systems -AI01047,AI Software Engineer,125284,CHF,112756,MI,CT,Switzerland,M,Switzerland,0,"Mathematics, SQL, Hadoop, Spark, Deep Learning",Associate,3,Healthcare,2024-02-01,2024-02-15,553,9.4,DeepTech Ventures -AI01048,AI Software Engineer,266424,USD,266424,EX,PT,Ireland,L,Ireland,50,"Azure, Scala, R, Tableau",PhD,17,Education,2024-04-19,2024-06-26,515,5.2,DataVision Ltd -AI01049,AI Consultant,158788,EUR,134970,EX,FL,France,S,France,50,"Linux, Mathematics, SQL",Associate,14,Automotive,2025-03-07,2025-04-12,559,7,Advanced Robotics -AI01050,Autonomous Systems Engineer,99628,SGD,129516,MI,FL,Singapore,S,Singapore,100,"PyTorch, AWS, Azure, Kubernetes, MLOps",Associate,3,Government,2024-07-22,2024-08-27,799,5.1,Smart Analytics -AI01051,AI Architect,52727,GBP,39545,EN,FT,United Kingdom,S,Austria,100,"Java, SQL, Linux",Bachelor,1,Energy,2025-03-17,2025-05-24,1166,9,Neural Networks Co -AI01052,AI Specialist,38473,USD,38473,MI,PT,India,L,India,100,"Tableau, Spark, Scala, NLP",Master,4,Manufacturing,2024-10-05,2024-11-03,2320,7.9,Smart Analytics -AI01053,Machine Learning Researcher,64133,USD,64133,EN,PT,United States,M,Sweden,0,"Azure, AWS, TensorFlow, Hadoop",Master,1,Real Estate,2024-09-24,2024-12-03,955,7.8,DataVision Ltd -AI01054,Data Analyst,47110,CAD,58888,EN,CT,Canada,S,Canada,50,"Java, Linux, Kubernetes, Azure",Bachelor,1,Media,2024-11-26,2025-01-06,844,8.4,Quantum Computing Inc -AI01055,Machine Learning Engineer,71783,EUR,61016,EN,CT,France,L,France,50,"Mathematics, SQL, Computer Vision",Associate,1,Media,2024-07-31,2024-10-07,524,8.8,Cognitive Computing -AI01056,AI Software Engineer,83829,USD,83829,EN,FL,Norway,S,India,50,"PyTorch, TensorFlow, Statistics, Hadoop, Python",Bachelor,0,Finance,2024-06-18,2024-08-29,1929,8.3,TechCorp Inc -AI01057,Robotics Engineer,91511,USD,91511,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, Mathematics, Spark",PhD,4,Technology,2024-11-17,2024-12-09,1221,5.7,Quantum Computing Inc -AI01058,ML Ops Engineer,198095,EUR,168381,EX,PT,France,S,France,50,"Git, R, Python, Scala",PhD,14,Education,2024-07-01,2024-08-27,1815,9.5,Machine Intelligence Group -AI01059,AI Product Manager,119407,USD,119407,SE,PT,Norway,S,Norway,0,"Git, Java, Tableau, Linux, Deep Learning",PhD,7,Manufacturing,2025-02-15,2025-03-24,2040,6.2,Algorithmic Solutions -AI01060,Data Engineer,87493,USD,87493,MI,FL,Denmark,S,Denmark,100,"MLOps, Hadoop, Linux, Scala",PhD,4,Energy,2024-12-04,2025-01-21,2032,6.5,Advanced Robotics -AI01061,Data Engineer,121335,USD,121335,SE,PT,Norway,S,Norway,50,"Python, Spark, Mathematics, SQL",Associate,7,Automotive,2024-12-06,2025-01-11,1573,7.9,DeepTech Ventures -AI01062,AI Architect,289174,SGD,375926,EX,FL,Singapore,L,Singapore,0,"Hadoop, SQL, Data Visualization, Deep Learning",Master,13,Retail,2025-02-04,2025-03-26,2451,8.5,Cognitive Computing -AI01063,Deep Learning Engineer,154280,USD,154280,SE,CT,Finland,L,Finland,0,"Data Visualization, Python, AWS",Bachelor,5,Education,2024-01-28,2024-03-21,547,9.6,Autonomous Tech -AI01064,Head of AI,62297,CAD,77871,EN,PT,Canada,S,Canada,100,"Mathematics, Hadoop, MLOps, Linux",Associate,0,Healthcare,2024-09-26,2024-11-02,2467,7.4,AI Innovations -AI01065,AI Software Engineer,114311,CAD,142889,MI,FL,Canada,L,Canada,50,"Mathematics, Computer Vision, Python",PhD,2,Telecommunications,2024-04-10,2024-04-27,1979,8.8,TechCorp Inc -AI01066,AI Research Scientist,163458,CAD,204323,SE,CT,Canada,L,Canada,50,"Azure, Python, Deep Learning, Spark",Master,7,Real Estate,2024-07-30,2024-10-05,1096,7.4,Cloud AI Solutions -AI01067,AI Software Engineer,107211,EUR,91129,MI,CT,France,L,Singapore,0,"Statistics, R, Computer Vision",Master,4,Government,2024-10-18,2024-11-13,678,8.4,Machine Intelligence Group -AI01068,Deep Learning Engineer,136382,USD,136382,MI,FL,Denmark,M,Spain,50,"AWS, Mathematics, NLP",PhD,2,Transportation,2024-10-03,2024-12-06,1219,6.1,AI Innovations -AI01069,Head of AI,249477,CHF,224529,EX,CT,Switzerland,S,Switzerland,50,"NLP, Hadoop, Python, Data Visualization, R",Associate,11,Government,2024-01-31,2024-03-01,1495,7.3,Predictive Systems -AI01070,Data Analyst,177617,EUR,150974,EX,PT,France,M,France,0,"AWS, TensorFlow, Data Visualization, Deep Learning",Master,11,Gaming,2024-12-13,2025-01-06,1493,8,Predictive Systems -AI01071,Computer Vision Engineer,66870,EUR,56840,EN,FL,Austria,M,Austria,0,"Azure, Deep Learning, Python, Git, Docker",Associate,1,Technology,2024-06-09,2024-07-08,2209,9.8,TechCorp Inc -AI01072,AI Software Engineer,79882,EUR,67900,MI,PT,Netherlands,M,Netherlands,0,"Spark, Hadoop, Git, Python, R",Associate,3,Education,2024-10-14,2024-11-16,1560,6.2,AI Innovations -AI01073,AI Research Scientist,114997,EUR,97747,MI,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Python",Bachelor,4,Telecommunications,2024-03-10,2024-03-25,1176,8.2,Predictive Systems -AI01074,Principal Data Scientist,67556,CHF,60800,EN,FT,Switzerland,S,Switzerland,100,"MLOps, Python, Hadoop, Kubernetes, Deep Learning",Master,1,Finance,2024-10-19,2024-12-07,885,6.6,Algorithmic Solutions -AI01075,Deep Learning Engineer,50726,USD,50726,SE,FT,India,M,Australia,0,"Java, AWS, R, Computer Vision, Git",Master,9,Telecommunications,2024-05-02,2024-05-18,556,8.3,Neural Networks Co -AI01076,Data Scientist,45956,EUR,39063,EN,FT,France,S,Italy,0,"Data Visualization, MLOps, AWS",PhD,1,Consulting,2024-11-12,2024-12-14,2065,6.6,Smart Analytics -AI01077,Data Engineer,29934,USD,29934,MI,FT,India,S,India,50,"SQL, Kubernetes, MLOps, Scala, Linux",Bachelor,2,Technology,2024-07-10,2024-08-01,2366,7,DataVision Ltd -AI01078,Deep Learning Engineer,89070,USD,89070,EX,PT,India,M,United Kingdom,0,"Python, Scala, Linux, GCP, Deep Learning",Associate,14,Technology,2025-02-23,2025-04-20,1673,8.1,Autonomous Tech -AI01079,AI Consultant,123195,EUR,104716,SE,FT,Germany,L,Chile,100,"GCP, SQL, Tableau, Spark, Mathematics",Bachelor,6,Finance,2024-12-16,2025-01-21,1581,8.6,Digital Transformation LLC -AI01080,Research Scientist,83392,USD,83392,MI,PT,South Korea,L,Singapore,100,"R, PyTorch, Tableau, Deep Learning, GCP",Associate,3,Automotive,2024-03-27,2024-06-05,1328,7.3,Digital Transformation LLC -AI01081,Principal Data Scientist,241040,USD,241040,EX,FT,Norway,S,Norway,100,"Azure, Linux, Data Visualization",PhD,18,Retail,2024-04-15,2024-06-08,2485,6.9,Cloud AI Solutions -AI01082,AI Consultant,226924,GBP,170193,EX,FL,United Kingdom,S,United Kingdom,100,"AWS, Docker, Kubernetes, Deep Learning, Tableau",Bachelor,17,Government,2024-08-30,2024-10-29,860,8.1,Neural Networks Co -AI01083,Data Analyst,28173,USD,28173,EN,FL,India,M,Singapore,100,"R, SQL, AWS",PhD,1,Gaming,2024-03-17,2024-04-23,2356,8.7,Predictive Systems -AI01084,Autonomous Systems Engineer,96863,EUR,82334,MI,PT,France,M,France,0,"Python, TensorFlow, Tableau",PhD,3,Government,2024-08-18,2024-10-19,1317,7.6,Future Systems -AI01085,ML Ops Engineer,126853,USD,126853,EX,FT,China,L,China,100,"AWS, Spark, NLP, Azure",PhD,13,Real Estate,2025-04-18,2025-05-12,2007,7.3,Algorithmic Solutions -AI01086,Principal Data Scientist,143421,USD,143421,SE,CT,United States,M,United States,100,"Azure, MLOps, Hadoop",Bachelor,6,Telecommunications,2024-11-07,2024-12-28,1193,9.5,DeepTech Ventures -AI01087,AI Consultant,20785,USD,20785,EN,PT,India,S,India,0,"Kubernetes, Spark, Azure, PyTorch",Master,1,Manufacturing,2024-12-24,2025-01-22,642,6.2,Cognitive Computing -AI01088,AI Research Scientist,67394,EUR,57285,EN,FT,Austria,M,Austria,100,"Tableau, Java, Python, Azure, R",PhD,0,Education,2024-11-07,2024-12-23,989,9.1,Algorithmic Solutions -AI01089,Data Engineer,93436,AUD,126139,MI,CT,Australia,L,Hungary,50,"Tableau, PyTorch, Scala, Azure",Master,3,Gaming,2024-01-21,2024-03-09,1503,6.1,Digital Transformation LLC -AI01090,ML Ops Engineer,95063,EUR,80804,MI,PT,France,M,France,100,"Kubernetes, Spark, Scala",Associate,2,Government,2024-09-08,2024-10-22,2378,9.6,Machine Intelligence Group -AI01091,Computer Vision Engineer,167478,USD,167478,EX,PT,United States,M,United States,100,"Statistics, Git, Docker",Bachelor,18,Healthcare,2024-03-16,2024-04-13,626,7.2,Machine Intelligence Group -AI01092,Autonomous Systems Engineer,139198,CHF,125278,SE,CT,Switzerland,S,Switzerland,100,"Java, Linux, Python, Hadoop, Azure",Master,5,Automotive,2024-02-27,2024-04-05,2301,9.1,Digital Transformation LLC -AI01093,Computer Vision Engineer,215699,USD,215699,EX,PT,Ireland,L,Ireland,0,"Computer Vision, Java, MLOps, AWS",Master,19,Automotive,2024-06-03,2024-06-30,2486,8.5,Advanced Robotics -AI01094,Research Scientist,138827,AUD,187416,EX,CT,Australia,S,Australia,100,"Docker, Data Visualization, Tableau, TensorFlow, AWS",Master,15,Manufacturing,2025-04-28,2025-05-28,1069,9.4,Machine Intelligence Group -AI01095,AI Consultant,79327,JPY,8725970,EN,PT,Japan,M,Japan,100,"AWS, TensorFlow, SQL, Computer Vision",Master,0,Real Estate,2025-02-26,2025-04-20,1008,7.3,Machine Intelligence Group -AI01096,AI Research Scientist,70002,USD,70002,EN,FT,Finland,L,Finland,50,"Mathematics, SQL, Data Visualization, MLOps",Master,1,Gaming,2024-12-31,2025-02-10,2355,9,Cognitive Computing -AI01097,AI Research Scientist,85342,EUR,72541,EN,FL,Netherlands,L,Netherlands,50,"Java, SQL, Spark",Associate,1,Energy,2024-11-25,2025-01-20,1783,6.7,TechCorp Inc -AI01098,AI Architect,116683,SGD,151688,SE,FT,Singapore,M,Singapore,100,"AWS, PyTorch, Python, Spark",Master,5,Automotive,2024-03-27,2024-05-12,2269,5.3,Cloud AI Solutions -AI01099,Head of AI,127338,EUR,108237,EX,CT,France,S,Estonia,50,"Scala, Spark, TensorFlow",Associate,19,Gaming,2024-03-09,2024-04-29,2085,5.1,Cloud AI Solutions -AI01100,Research Scientist,80026,USD,80026,SE,FT,South Korea,S,South Korea,100,"R, Java, Linux, GCP",Master,9,Healthcare,2024-04-24,2024-06-06,1833,6.7,Neural Networks Co -AI01101,Deep Learning Engineer,119475,CHF,107528,EN,PT,Switzerland,L,Switzerland,0,"Spark, Azure, Python",PhD,1,Gaming,2024-05-03,2024-07-14,2219,5.9,Predictive Systems -AI01102,ML Ops Engineer,254552,AUD,343645,EX,CT,Australia,L,Egypt,0,"Deep Learning, Python, Java, GCP, TensorFlow",Associate,12,Transportation,2024-04-23,2024-05-13,1757,5.6,Cognitive Computing -AI01103,Head of AI,118245,USD,118245,SE,PT,Ireland,M,Canada,0,"Mathematics, AWS, Data Visualization, Computer Vision",Master,6,Consulting,2024-08-16,2024-10-08,1898,9.3,Neural Networks Co -AI01104,AI Software Engineer,117254,EUR,99666,SE,FL,Austria,M,Austria,0,"SQL, Data Visualization, R, Spark, GCP",PhD,7,Government,2024-12-26,2025-02-18,2230,9.3,Autonomous Tech -AI01105,Data Scientist,256695,USD,256695,EX,FL,Ireland,L,Ireland,50,"MLOps, Scala, AWS",Bachelor,14,Automotive,2024-06-11,2024-07-26,617,9.1,Autonomous Tech -AI01106,Computer Vision Engineer,188203,USD,188203,EX,FL,Finland,M,Finland,0,"Hadoop, R, Python, Git",Bachelor,15,Real Estate,2024-08-12,2024-09-07,1201,9.4,Advanced Robotics -AI01107,Computer Vision Engineer,191049,USD,191049,EX,FL,United States,S,United States,0,"AWS, Linux, Azure",Bachelor,17,Education,2024-06-02,2024-07-06,887,7.7,AI Innovations -AI01108,AI Product Manager,75973,EUR,64577,EN,FT,Germany,M,Thailand,50,"SQL, NLP, Tableau",Master,1,Automotive,2024-08-16,2024-09-27,646,7.7,DataVision Ltd -AI01109,Machine Learning Researcher,205143,SGD,266686,EX,FT,Singapore,M,Singapore,100,"Scala, Docker, MLOps",PhD,14,Transportation,2024-08-04,2024-08-28,2458,9,Machine Intelligence Group -AI01110,AI Specialist,92600,USD,92600,SE,FT,Ireland,S,Ireland,0,"SQL, Java, Computer Vision",PhD,8,Healthcare,2024-03-03,2024-04-03,1281,6.1,Predictive Systems -AI01111,Research Scientist,307696,USD,307696,EX,CT,Denmark,L,Czech Republic,100,"Data Visualization, TensorFlow, Python, MLOps, Deep Learning",Bachelor,12,Government,2024-09-25,2024-10-17,526,7.3,Advanced Robotics -AI01112,Machine Learning Engineer,289667,USD,289667,EX,FL,United States,L,United States,0,"Mathematics, Scala, PyTorch",Master,15,Automotive,2024-10-26,2024-12-20,2369,6.6,Cognitive Computing -AI01113,AI Product Manager,104108,USD,104108,SE,FT,Sweden,S,Sweden,50,"Spark, Java, R, TensorFlow, SQL",PhD,9,Automotive,2025-01-02,2025-02-26,1083,6.1,Predictive Systems -AI01114,NLP Engineer,85459,USD,85459,EN,FT,Denmark,M,Denmark,50,"Statistics, Spark, PyTorch",Bachelor,1,Retail,2024-07-18,2024-08-13,2416,6.6,DataVision Ltd -AI01115,Computer Vision Engineer,48088,EUR,40875,EN,FT,France,M,France,0,"NLP, Scala, Java",Bachelor,0,Finance,2024-04-08,2024-05-19,1362,9.7,Smart Analytics -AI01116,AI Architect,103764,USD,103764,SE,PT,Sweden,S,Sweden,50,"SQL, Docker, AWS",Associate,9,Manufacturing,2024-11-15,2025-01-01,1227,9.4,Future Systems -AI01117,Deep Learning Engineer,135128,SGD,175666,SE,PT,Singapore,M,Singapore,100,"NLP, R, Azure, SQL, Java",Master,9,Government,2024-05-15,2024-07-11,693,6.1,Machine Intelligence Group -AI01118,NLP Engineer,78044,JPY,8584840,MI,PT,Japan,S,Japan,0,"TensorFlow, Azure, Python, Tableau",Bachelor,4,Gaming,2024-11-08,2024-12-12,1943,7.9,Autonomous Tech -AI01119,Research Scientist,77226,SGD,100394,MI,FT,Singapore,M,Singapore,0,"Scala, Spark, Computer Vision, Python, Tableau",PhD,3,Telecommunications,2024-07-16,2024-08-29,1506,6.6,Predictive Systems -AI01120,Machine Learning Engineer,149651,CAD,187064,EX,CT,Canada,M,Canada,100,"TensorFlow, Python, Kubernetes, MLOps, AWS",Associate,11,Gaming,2024-09-18,2024-11-15,943,7.9,DeepTech Ventures -AI01121,Machine Learning Engineer,183833,EUR,156258,EX,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, R",Associate,10,Healthcare,2025-03-24,2025-05-29,2012,9.6,Future Systems -AI01122,Computer Vision Engineer,104425,EUR,88761,MI,PT,Germany,L,China,0,"MLOps, Java, Python, Kubernetes, Computer Vision",Bachelor,4,Transportation,2024-07-30,2024-08-24,532,5.7,Quantum Computing Inc -AI01123,AI Consultant,163323,USD,163323,EX,CT,Sweden,S,Sweden,0,"NLP, Data Visualization, AWS, Python, TensorFlow",Bachelor,10,Gaming,2024-10-14,2024-11-11,1137,6.6,Autonomous Tech -AI01124,Data Engineer,136850,EUR,116323,EX,FT,Germany,S,Norway,0,"Tableau, Python, TensorFlow, Computer Vision, GCP",PhD,11,Healthcare,2024-08-14,2024-09-02,831,7.2,Cloud AI Solutions -AI01125,AI Consultant,133658,GBP,100244,SE,FL,United Kingdom,S,United Kingdom,100,"Kubernetes, SQL, GCP",PhD,8,Manufacturing,2024-05-17,2024-06-24,1514,6,Smart Analytics -AI01126,AI Specialist,168161,JPY,18497710,SE,FT,Japan,L,Japan,0,"Python, GCP, TensorFlow, Computer Vision, Hadoop",PhD,6,Government,2025-02-06,2025-03-12,2290,5.8,Cloud AI Solutions -AI01127,AI Research Scientist,87945,JPY,9673950,MI,FT,Japan,M,Japan,0,"Computer Vision, PyTorch, Data Visualization",Associate,2,Consulting,2025-04-30,2025-06-13,1525,6.3,Autonomous Tech -AI01128,Data Analyst,150603,USD,150603,SE,FL,Norway,M,Norway,50,"GCP, R, Computer Vision, Linux, SQL",Master,9,Healthcare,2024-05-14,2024-07-09,2451,9.6,Cloud AI Solutions -AI01129,Research Scientist,41667,USD,41667,MI,CT,China,M,China,100,"Data Visualization, Kubernetes, MLOps, TensorFlow",Master,3,Finance,2024-06-03,2024-08-12,1963,9,Cognitive Computing -AI01130,Machine Learning Researcher,270857,USD,270857,EX,FT,Denmark,L,Denmark,0,"Spark, PyTorch, Hadoop",Associate,14,Healthcare,2025-01-09,2025-02-17,1836,7.5,Machine Intelligence Group -AI01131,AI Product Manager,70021,JPY,7702310,EN,FL,Japan,M,South Korea,100,"SQL, Git, Python",Master,1,Automotive,2024-09-30,2024-11-08,2044,9,Machine Intelligence Group -AI01132,Deep Learning Engineer,180120,USD,180120,EX,FL,Finland,S,Finland,50,"PyTorch, R, Java, SQL",Bachelor,19,Gaming,2025-03-21,2025-04-27,2134,9.4,TechCorp Inc -AI01133,Data Analyst,109592,CAD,136990,SE,FT,Canada,S,Kenya,50,"GCP, Spark, AWS, Python, Mathematics",Master,8,Gaming,2024-04-30,2024-06-13,1754,8.9,TechCorp Inc -AI01134,NLP Engineer,248395,EUR,211136,EX,FL,Germany,M,Germany,100,"Kubernetes, Data Visualization, Java, Scala, MLOps",Master,11,Energy,2024-06-19,2024-08-31,2176,7.6,Digital Transformation LLC -AI01135,ML Ops Engineer,166428,EUR,141464,EX,FL,France,S,Luxembourg,50,"Linux, AWS, Deep Learning, Computer Vision",Bachelor,12,Real Estate,2024-10-28,2024-12-07,2272,9.4,DataVision Ltd -AI01136,AI Product Manager,64110,SGD,83343,EN,FL,Singapore,S,Ukraine,50,"Kubernetes, Statistics, Scala, Deep Learning",Master,1,Manufacturing,2024-02-23,2024-03-17,1013,7.7,Autonomous Tech -AI01137,NLP Engineer,89254,USD,89254,MI,CT,Israel,M,Israel,50,"Azure, PyTorch, Data Visualization, Computer Vision, Mathematics",Bachelor,2,Real Estate,2025-02-03,2025-03-03,736,5.6,Neural Networks Co -AI01138,ML Ops Engineer,89632,CAD,112040,SE,FT,Canada,S,Brazil,50,"PyTorch, Git, Python",Master,7,Technology,2024-09-11,2024-10-26,1963,8.9,Digital Transformation LLC -AI01139,Research Scientist,94147,JPY,10356170,MI,FL,Japan,S,Austria,100,"NLP, Python, GCP, Mathematics",Associate,4,Telecommunications,2024-07-04,2024-08-12,2179,9.7,DeepTech Ventures -AI01140,Data Scientist,95536,USD,95536,EX,PT,China,M,Poland,50,"PyTorch, TensorFlow, GCP, NLP",Bachelor,12,Consulting,2024-07-13,2024-08-13,2028,5.3,DataVision Ltd -AI01141,AI Specialist,128104,USD,128104,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, Git, Data Visualization",Master,6,Manufacturing,2024-03-16,2024-04-12,1759,6.7,DeepTech Ventures -AI01142,Data Analyst,224736,USD,224736,EX,FL,Denmark,S,South Africa,100,"Python, TensorFlow, SQL, Kubernetes, AWS",Associate,15,Manufacturing,2024-01-18,2024-02-12,617,6.5,Machine Intelligence Group -AI01143,Principal Data Scientist,132221,JPY,14544310,MI,FT,Japan,L,Japan,0,"Python, Git, GCP, NLP, Hadoop",PhD,4,Consulting,2024-09-26,2024-10-22,1834,9.4,Cloud AI Solutions -AI01144,AI Consultant,107463,EUR,91344,SE,FT,Austria,M,Ireland,0,"Data Visualization, PyTorch, Git, Computer Vision",PhD,7,Media,2025-03-17,2025-04-19,1360,6.3,DataVision Ltd -AI01145,Machine Learning Researcher,200093,CAD,250116,EX,FL,Canada,M,India,50,"Statistics, R, Tableau, Hadoop",Bachelor,18,Real Estate,2024-09-22,2024-11-06,1322,8.4,Advanced Robotics -AI01146,Machine Learning Engineer,168952,AUD,228085,SE,PT,Australia,L,Australia,100,"SQL, R, Hadoop, Docker",Master,7,Finance,2024-02-11,2024-02-25,1398,5.9,Digital Transformation LLC -AI01147,Deep Learning Engineer,223789,JPY,24616790,EX,FT,Japan,S,Japan,100,"Hadoop, SQL, Linux",Bachelor,10,Technology,2024-05-22,2024-06-16,1821,5.2,Machine Intelligence Group -AI01148,Data Engineer,121814,USD,121814,SE,CT,South Korea,L,South Korea,0,"Spark, Linux, Hadoop",PhD,7,Telecommunications,2024-04-11,2024-05-26,808,9.6,Predictive Systems -AI01149,NLP Engineer,188710,USD,188710,EX,PT,Finland,S,Finland,0,"SQL, Hadoop, Tableau",Associate,19,Transportation,2024-05-31,2024-07-28,2221,5.7,Smart Analytics -AI01150,AI Consultant,73645,AUD,99421,MI,PT,Australia,S,Australia,50,"Python, Spark, Data Visualization, NLP",Bachelor,3,Government,2024-03-23,2024-04-22,1750,9.6,Advanced Robotics -AI01151,ML Ops Engineer,167924,GBP,125943,EX,FL,United Kingdom,S,Ghana,0,"Hadoop, SQL, GCP, Scala, Computer Vision",Master,13,Education,2025-03-24,2025-05-11,2123,10,Future Systems -AI01152,NLP Engineer,104995,USD,104995,MI,FT,Sweden,L,Sweden,50,"Tableau, GCP, Mathematics",Bachelor,3,Media,2024-02-10,2024-02-29,2335,5.9,Algorithmic Solutions -AI01153,NLP Engineer,319365,CHF,287429,EX,FT,Switzerland,M,Switzerland,100,"Python, Linux, TensorFlow, AWS",Associate,15,Telecommunications,2024-08-01,2024-08-31,2420,7.4,Advanced Robotics -AI01154,Data Engineer,120902,USD,120902,SE,FL,South Korea,L,South Korea,0,"Linux, Python, MLOps, Spark, Mathematics",PhD,6,Healthcare,2024-12-15,2025-02-07,592,7.2,DataVision Ltd -AI01155,AI Research Scientist,93958,EUR,79864,MI,CT,Germany,M,Latvia,50,"SQL, Data Visualization, Scala",Master,3,Real Estate,2024-11-25,2025-02-04,2028,7.9,Advanced Robotics -AI01156,Machine Learning Researcher,204959,USD,204959,EX,CT,Denmark,L,Denmark,50,"TensorFlow, Python, GCP, R",Bachelor,10,Manufacturing,2025-03-27,2025-04-30,2354,6.1,Digital Transformation LLC -AI01157,Computer Vision Engineer,45750,USD,45750,MI,FL,China,M,Denmark,0,"Statistics, PyTorch, TensorFlow, Computer Vision, Deep Learning",PhD,2,Energy,2025-03-09,2025-03-24,972,7.4,TechCorp Inc -AI01158,Data Engineer,191169,EUR,162494,EX,CT,Germany,M,Egypt,100,"Scala, Java, Computer Vision, AWS",Associate,13,Gaming,2025-03-19,2025-04-03,2281,5.6,Algorithmic Solutions -AI01159,Robotics Engineer,187320,JPY,20605200,EX,PT,Japan,L,Spain,100,"Java, TensorFlow, Data Visualization",PhD,16,Education,2024-09-23,2024-11-10,701,8.8,Cloud AI Solutions -AI01160,AI Architect,45995,USD,45995,SE,FL,China,S,China,0,"Python, TensorFlow, Linux, Statistics",Bachelor,8,Telecommunications,2024-12-03,2024-12-22,1433,8.3,AI Innovations -AI01161,Principal Data Scientist,189388,EUR,160980,EX,FL,France,S,France,50,"TensorFlow, Python, PyTorch, AWS, R",Associate,10,Healthcare,2024-11-23,2025-01-20,2162,9.9,Digital Transformation LLC -AI01162,AI Research Scientist,77764,CHF,69988,EN,PT,Switzerland,M,Ghana,100,"Kubernetes, SQL, Data Visualization",Master,0,Finance,2024-11-28,2024-12-21,1143,8,Cognitive Computing -AI01163,Data Engineer,70260,EUR,59721,EN,FL,Germany,L,Germany,0,"Linux, Data Visualization, MLOps, Git",Master,1,Education,2024-12-05,2025-01-03,604,8,Cloud AI Solutions -AI01164,Autonomous Systems Engineer,59125,EUR,50256,EN,PT,Germany,S,Germany,50,"Scala, Python, Tableau, Computer Vision",PhD,1,Gaming,2024-10-22,2024-12-14,706,7.7,Smart Analytics -AI01165,Head of AI,85915,CHF,77324,EN,FL,Switzerland,S,Switzerland,0,"Python, Tableau, Java, AWS, Statistics",Associate,1,Telecommunications,2025-04-15,2025-05-29,1359,8.5,Cognitive Computing -AI01166,AI Software Engineer,161147,USD,161147,SE,FL,Israel,L,Israel,50,"Spark, Linux, Kubernetes, Hadoop, Python",Associate,9,Energy,2024-09-05,2024-11-03,1023,6.3,Cognitive Computing -AI01167,AI Consultant,145874,USD,145874,EX,PT,Israel,M,Israel,50,"GCP, Statistics, MLOps, Python, AWS",PhD,16,Education,2024-08-23,2024-11-01,1826,9.6,Smart Analytics -AI01168,Research Scientist,41928,USD,41928,MI,PT,India,L,India,50,"AWS, MLOps, NLP",Associate,3,Telecommunications,2024-07-06,2024-09-04,1539,7.1,Quantum Computing Inc -AI01169,NLP Engineer,244108,USD,244108,EX,CT,Denmark,S,Denmark,0,"Hadoop, Python, SQL",Associate,14,Transportation,2024-05-21,2024-06-29,974,8.9,AI Innovations -AI01170,NLP Engineer,74765,CHF,67289,EN,FT,Switzerland,M,Vietnam,50,"Tableau, Deep Learning, Kubernetes, AWS",Master,0,Retail,2025-04-20,2025-06-25,861,6.6,Quantum Computing Inc -AI01171,AI Software Engineer,111797,USD,111797,SE,CT,Finland,S,Finland,50,"Python, MLOps, Linux",Bachelor,8,Finance,2024-07-14,2024-09-06,778,7.1,Cognitive Computing -AI01172,AI Product Manager,129173,AUD,174384,SE,FL,Australia,M,Australia,100,"Scala, Spark, MLOps, Mathematics, Linux",PhD,8,Automotive,2024-08-12,2024-10-10,1154,9.1,Neural Networks Co -AI01173,Robotics Engineer,109849,USD,109849,SE,FL,Ireland,S,Ireland,0,"SQL, TensorFlow, MLOps",Master,5,Transportation,2024-11-08,2024-11-27,1872,9.3,Smart Analytics -AI01174,NLP Engineer,86314,CHF,77683,EN,FL,Switzerland,L,Switzerland,0,"Scala, Python, TensorFlow, Computer Vision",Bachelor,0,Retail,2025-01-30,2025-03-15,2197,9.2,Cognitive Computing -AI01175,AI Product Manager,134718,CHF,121246,MI,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Linux, R",Bachelor,4,Finance,2024-10-09,2024-11-11,2272,6.1,TechCorp Inc -AI01176,Machine Learning Researcher,146659,USD,146659,SE,CT,Sweden,M,Sweden,100,"TensorFlow, PyTorch, Kubernetes",Associate,6,Government,2025-01-24,2025-02-15,2107,8.3,DeepTech Ventures -AI01177,NLP Engineer,207301,GBP,155476,EX,FL,United Kingdom,M,United Kingdom,100,"Java, SQL, Spark, TensorFlow",Master,15,Real Estate,2024-01-06,2024-02-17,1385,6.5,DeepTech Ventures -AI01178,Data Scientist,86551,EUR,73568,MI,CT,Netherlands,S,Netherlands,100,"Scala, Statistics, SQL",PhD,2,Finance,2024-01-18,2024-02-14,752,8.8,Neural Networks Co -AI01179,AI Consultant,101086,SGD,131412,MI,FL,Singapore,L,Latvia,0,"Tableau, AWS, Hadoop, Kubernetes, SQL",Bachelor,2,Automotive,2024-11-02,2024-12-18,1462,10,Autonomous Tech -AI01180,Computer Vision Engineer,243742,USD,243742,EX,FL,Ireland,M,Ireland,100,"Linux, GCP, AWS",Master,16,Automotive,2024-10-18,2024-11-12,972,8.4,Future Systems -AI01181,AI Software Engineer,45910,EUR,39024,EN,FL,Austria,S,Austria,100,"Linux, Data Visualization, Git, Scala",Master,0,Automotive,2024-09-17,2024-10-25,1021,9.7,Machine Intelligence Group -AI01182,Principal Data Scientist,165181,EUR,140404,EX,CT,France,L,France,100,"TensorFlow, NLP, Hadoop, Kubernetes, Python",Bachelor,14,Finance,2024-01-07,2024-02-25,1029,6.7,Quantum Computing Inc -AI01183,Machine Learning Researcher,47299,AUD,63854,EN,PT,Australia,S,Australia,100,"SQL, Linux, Git, Tableau",Master,1,Telecommunications,2024-06-17,2024-07-23,2432,6.8,DeepTech Ventures -AI01184,AI Specialist,69234,CAD,86543,EN,FT,Canada,M,Ireland,100,"Computer Vision, Java, Data Visualization",PhD,0,Retail,2024-01-15,2024-02-13,1184,5,AI Innovations -AI01185,AI Product Manager,95021,SGD,123527,MI,FL,Singapore,L,Belgium,50,"MLOps, Tableau, Python, Docker",Bachelor,3,Telecommunications,2024-10-12,2024-10-26,2138,5.7,Future Systems -AI01186,Machine Learning Engineer,27279,USD,27279,EN,CT,India,L,India,0,"Statistics, Mathematics, Tableau",Associate,0,Real Estate,2024-02-27,2024-03-25,1258,6.5,TechCorp Inc -AI01187,Machine Learning Researcher,74665,SGD,97065,EN,FL,Singapore,S,Singapore,100,"R, Azure, PyTorch",PhD,0,Retail,2024-01-14,2024-03-05,1743,7.5,Advanced Robotics -AI01188,AI Consultant,105569,USD,105569,SE,CT,South Korea,M,France,0,"Python, Java, Data Visualization, Deep Learning",Associate,7,Manufacturing,2024-06-07,2024-07-06,765,6.9,Future Systems -AI01189,Principal Data Scientist,75073,USD,75073,EN,FL,Sweden,M,Sweden,0,"Python, R, Tableau, Data Visualization, AWS",Associate,1,Retail,2024-11-20,2025-01-28,1316,5.8,Future Systems -AI01190,AI Software Engineer,185794,USD,185794,EX,FT,Denmark,M,Singapore,100,"R, MLOps, Computer Vision, Git",PhD,18,Energy,2025-01-27,2025-02-13,691,7.1,DeepTech Ventures -AI01191,AI Specialist,222006,USD,222006,EX,FL,United States,S,New Zealand,100,"Hadoop, Spark, Mathematics",Bachelor,19,Energy,2025-02-19,2025-03-27,987,9.1,TechCorp Inc -AI01192,Robotics Engineer,95988,USD,95988,MI,PT,Ireland,M,Switzerland,0,"PyTorch, Linux, Scala, Mathematics, GCP",Master,2,Real Estate,2025-02-21,2025-03-18,1899,9.6,Autonomous Tech -AI01193,Autonomous Systems Engineer,75420,GBP,56565,EN,CT,United Kingdom,M,Israel,50,"Linux, Spark, TensorFlow, Python",Associate,1,Media,2024-07-03,2024-09-02,1590,5.9,Quantum Computing Inc -AI01194,AI Consultant,56066,CAD,70083,EN,FL,Canada,S,Japan,0,"Spark, Kubernetes, TensorFlow",PhD,0,Technology,2024-09-28,2024-10-28,1278,9.1,Neural Networks Co -AI01195,ML Ops Engineer,34199,USD,34199,MI,CT,India,S,India,100,"Java, Kubernetes, Azure, GCP",Associate,3,Energy,2025-02-11,2025-04-09,1150,6.6,DeepTech Ventures -AI01196,Robotics Engineer,123046,USD,123046,SE,PT,Israel,M,Israel,50,"Python, Docker, Data Visualization, MLOps, Deep Learning",Master,9,Media,2024-09-13,2024-10-08,1501,6.8,Predictive Systems -AI01197,Research Scientist,155715,EUR,132358,SE,CT,Austria,L,Brazil,100,"Java, Kubernetes, Docker",Associate,8,Manufacturing,2024-09-01,2024-10-31,1240,6.6,Cloud AI Solutions -AI01198,AI Architect,135052,CHF,121547,MI,CT,Switzerland,M,New Zealand,100,"GCP, Python, Git, Java, Computer Vision",PhD,4,Finance,2024-07-08,2024-09-15,1191,6.2,Smart Analytics -AI01199,AI Research Scientist,139723,GBP,104792,SE,PT,United Kingdom,L,Canada,100,"Kubernetes, Spark, MLOps",Associate,5,Finance,2024-06-27,2024-07-23,1731,9.7,Cloud AI Solutions -AI01200,AI Software Engineer,126789,USD,126789,SE,CT,Israel,S,Israel,50,"Hadoop, Git, Statistics",Bachelor,6,Healthcare,2024-07-31,2024-08-14,2157,5.9,DeepTech Ventures -AI01201,Data Analyst,51041,SGD,66353,EN,FT,Singapore,S,Singapore,100,"Statistics, AWS, Scala, PyTorch",PhD,1,Healthcare,2024-01-30,2024-02-19,1755,6.8,Cloud AI Solutions -AI01202,Machine Learning Engineer,66473,AUD,89739,EN,FT,Australia,M,Australia,100,"Docker, Kubernetes, Statistics, Spark",Master,0,Energy,2025-02-04,2025-02-20,2260,7.9,Future Systems -AI01203,AI Consultant,82798,JPY,9107780,EN,FT,Japan,L,Japan,50,"Azure, SQL, AWS",Master,0,Real Estate,2025-01-10,2025-03-06,1844,8.2,Quantum Computing Inc -AI01204,Machine Learning Researcher,208808,USD,208808,EX,CT,Ireland,M,Estonia,100,"Java, Python, PyTorch, SQL",Associate,16,Healthcare,2024-01-16,2024-02-29,2313,5.3,Autonomous Tech -AI01205,Principal Data Scientist,85454,USD,85454,EN,FT,Denmark,M,Denmark,100,"SQL, Scala, Kubernetes",PhD,0,Government,2024-12-20,2025-02-05,1407,7.8,Cloud AI Solutions -AI01206,Principal Data Scientist,312926,CHF,281633,EX,FT,Switzerland,S,Switzerland,100,"Kubernetes, Git, Mathematics, Hadoop, PyTorch",Bachelor,17,Media,2024-08-07,2024-10-14,1468,6.5,Predictive Systems -AI01207,Computer Vision Engineer,112468,USD,112468,EN,FT,Denmark,L,Italy,100,"R, Java, Linux",Master,0,Manufacturing,2024-11-13,2024-11-30,1081,9.1,Neural Networks Co -AI01208,Data Analyst,184835,USD,184835,EX,PT,Sweden,L,Sweden,100,"GCP, Python, TensorFlow, SQL",Bachelor,12,Consulting,2024-09-22,2024-10-31,570,6.7,Algorithmic Solutions -AI01209,Robotics Engineer,114775,EUR,97559,SE,PT,France,L,France,100,"Python, Git, TensorFlow, Data Visualization, Linux",Bachelor,7,Education,2024-06-20,2024-08-10,1743,9.4,Neural Networks Co -AI01210,Deep Learning Engineer,87755,CAD,109694,MI,PT,Canada,L,Portugal,100,"Deep Learning, Scala, Data Visualization, TensorFlow",Bachelor,3,Energy,2024-11-03,2024-12-15,1436,6.4,Predictive Systems -AI01211,AI Consultant,226988,SGD,295084,EX,CT,Singapore,S,Singapore,0,"Statistics, NLP, Linux",Master,12,Manufacturing,2024-05-03,2024-06-13,2480,5.1,Advanced Robotics -AI01212,Data Scientist,109751,CAD,137189,SE,PT,Canada,S,Denmark,100,"Azure, Kubernetes, Spark, Computer Vision",PhD,9,Energy,2024-09-01,2024-10-13,2171,7.1,Future Systems -AI01213,NLP Engineer,110714,USD,110714,EX,FL,China,M,China,100,"NLP, Scala, Kubernetes, Python",Master,15,Finance,2024-06-01,2024-08-13,835,7.9,TechCorp Inc -AI01214,AI Architect,243320,USD,243320,EX,CT,Israel,L,Israel,0,"NLP, Scala, Python, Computer Vision",PhD,16,Telecommunications,2024-09-17,2024-11-17,2026,5.8,DataVision Ltd -AI01215,Machine Learning Researcher,137660,USD,137660,SE,FT,Sweden,M,India,100,"Tableau, Kubernetes, SQL, Java",Associate,6,Technology,2024-07-19,2024-09-02,964,8.2,Future Systems -AI01216,Deep Learning Engineer,101137,USD,101137,MI,CT,Denmark,M,Belgium,50,"R, Azure, Deep Learning, SQL, Java",Master,2,Telecommunications,2025-01-02,2025-02-06,2016,10,DataVision Ltd -AI01217,Data Analyst,76750,EUR,65238,EN,FT,Netherlands,M,Netherlands,0,"Java, Git, Data Visualization",Bachelor,0,Gaming,2024-07-20,2024-09-01,723,6.9,Cognitive Computing -AI01218,Machine Learning Researcher,225610,USD,225610,EX,PT,Denmark,M,Denmark,50,"PyTorch, Deep Learning, TensorFlow",Associate,14,Telecommunications,2024-06-21,2024-08-10,810,7.1,Predictive Systems -AI01219,AI Consultant,250681,USD,250681,EX,FL,Denmark,S,Denmark,0,"TensorFlow, R, Spark, Python",PhD,15,Retail,2024-07-17,2024-09-22,818,6.3,Smart Analytics -AI01220,Deep Learning Engineer,68073,USD,68073,EN,PT,United States,M,United States,50,"MLOps, AWS, SQL, NLP, Statistics",Master,0,Technology,2024-03-11,2024-04-05,1104,5.4,TechCorp Inc -AI01221,Data Scientist,83363,EUR,70859,MI,FL,Germany,S,Germany,100,"Git, Linux, MLOps, Mathematics",Bachelor,2,Energy,2024-08-01,2024-09-15,2321,6.2,Cognitive Computing -AI01222,AI Architect,82241,USD,82241,EN,FL,United States,L,United States,0,"Spark, R, Deep Learning, Java, Git",Master,0,Education,2024-03-04,2024-05-09,515,9.9,Neural Networks Co -AI01223,AI Research Scientist,70446,USD,70446,EN,PT,South Korea,L,South Korea,0,"Python, Git, TensorFlow, GCP, PyTorch",Master,1,Energy,2024-11-08,2024-11-27,688,8.3,Digital Transformation LLC -AI01224,Machine Learning Researcher,91327,USD,91327,EN,PT,United States,M,United States,0,"Hadoop, Scala, Statistics, Git",Bachelor,0,Technology,2024-06-20,2024-07-15,703,5.6,Advanced Robotics -AI01225,Data Scientist,39389,USD,39389,MI,CT,India,L,India,0,"Data Visualization, SQL, Hadoop",Associate,4,Media,2024-10-03,2024-11-12,1197,9.6,Neural Networks Co -AI01226,Robotics Engineer,81525,EUR,69296,EN,CT,Netherlands,L,Netherlands,0,"AWS, Data Visualization, PyTorch",PhD,0,Finance,2025-04-03,2025-06-04,2353,5.8,DeepTech Ventures -AI01227,Data Analyst,64441,EUR,54775,EN,PT,Germany,S,Germany,50,"PyTorch, TensorFlow, Tableau, GCP",Associate,1,Retail,2024-10-15,2024-11-18,604,5.3,Cloud AI Solutions -AI01228,Data Scientist,154936,CAD,193670,SE,FL,Canada,L,Spain,0,"Data Visualization, Python, Scala, TensorFlow, Statistics",Master,7,Energy,2024-01-23,2024-03-19,1911,5.5,Autonomous Tech -AI01229,Machine Learning Engineer,252651,USD,252651,EX,CT,Finland,L,Finland,0,"Python, Java, MLOps, Computer Vision, Deep Learning",Associate,11,Media,2024-07-25,2024-09-09,1989,9.7,AI Innovations -AI01230,AI Research Scientist,85211,GBP,63908,MI,PT,United Kingdom,M,United Kingdom,0,"AWS, MLOps, Deep Learning, SQL",Bachelor,2,Energy,2024-08-28,2024-09-20,1984,6.7,Advanced Robotics -AI01231,Head of AI,75989,USD,75989,MI,CT,South Korea,S,South Korea,0,"PyTorch, TensorFlow, Docker, Hadoop",Associate,2,Telecommunications,2024-11-22,2025-01-08,1985,5.6,Algorithmic Solutions -AI01232,NLP Engineer,81874,USD,81874,MI,CT,Ireland,M,Ireland,50,"Azure, GCP, Statistics, PyTorch",Bachelor,2,Real Estate,2024-10-16,2024-12-09,1992,8.5,Autonomous Tech -AI01233,Robotics Engineer,159436,USD,159436,SE,CT,Israel,L,Australia,50,"TensorFlow, Data Visualization, Java, Azure",Associate,7,Telecommunications,2024-02-02,2024-03-12,1302,10,DeepTech Ventures -AI01234,AI Research Scientist,116597,USD,116597,SE,FT,Finland,M,Switzerland,50,"Deep Learning, Statistics, AWS",Associate,5,Media,2024-12-12,2025-01-11,762,8.9,Future Systems -AI01235,ML Ops Engineer,123943,JPY,13633730,SE,CT,Japan,M,Japan,50,"Python, TensorFlow, GCP, SQL, Git",PhD,9,Consulting,2024-08-04,2024-08-31,2347,8.3,DataVision Ltd -AI01236,Principal Data Scientist,142168,EUR,120843,SE,PT,France,M,France,50,"Mathematics, TensorFlow, Docker, NLP",Associate,9,Gaming,2024-05-21,2024-06-07,1546,7.3,TechCorp Inc -AI01237,Machine Learning Engineer,145212,USD,145212,MI,FT,United States,L,United Kingdom,50,"Linux, R, Deep Learning",Master,3,Finance,2024-01-14,2024-03-20,1063,7.7,Neural Networks Co -AI01238,Data Engineer,150880,JPY,16596800,SE,FT,Japan,L,Japan,100,"Mathematics, R, Data Visualization",Associate,6,Gaming,2024-12-11,2025-01-15,2362,6,Neural Networks Co -AI01239,ML Ops Engineer,78416,USD,78416,MI,FL,Israel,M,Israel,0,"Kubernetes, Python, Data Visualization, TensorFlow, AWS",PhD,4,Technology,2024-12-29,2025-03-11,521,8.6,Machine Intelligence Group -AI01240,Robotics Engineer,167446,EUR,142329,EX,CT,Netherlands,L,Netherlands,0,"Git, Azure, PyTorch, Deep Learning",Associate,13,Education,2025-04-28,2025-05-26,2462,5.7,DataVision Ltd -AI01241,AI Architect,136891,USD,136891,EX,FT,South Korea,S,South Korea,50,"Data Visualization, Java, Linux, AWS",Associate,13,Manufacturing,2024-11-09,2025-01-06,2072,6.3,Cloud AI Solutions -AI01242,AI Product Manager,56186,CAD,70233,EN,CT,Canada,L,Sweden,0,"Tableau, Deep Learning, Spark, TensorFlow, Hadoop",Bachelor,0,Retail,2024-02-09,2024-03-02,1179,7.5,Future Systems -AI01243,Data Scientist,89015,CAD,111269,MI,FL,Canada,L,India,100,"Kubernetes, Python, Azure",PhD,3,Transportation,2025-02-25,2025-03-24,1473,8.2,Cloud AI Solutions -AI01244,Principal Data Scientist,101256,GBP,75942,MI,CT,United Kingdom,L,Brazil,0,"PyTorch, Linux, Spark",PhD,4,Manufacturing,2024-10-28,2024-11-12,635,6.8,Digital Transformation LLC -AI01245,Machine Learning Engineer,223846,EUR,190269,EX,FL,Austria,M,Austria,50,"Hadoop, TensorFlow, Python",PhD,10,Finance,2024-11-02,2024-12-03,1775,8.2,Algorithmic Solutions -AI01246,Data Analyst,89705,CAD,112131,MI,PT,Canada,L,Canada,0,"Scala, Python, Kubernetes",Associate,4,Gaming,2024-11-23,2025-01-08,1486,8.3,DataVision Ltd -AI01247,Head of AI,173178,USD,173178,EX,FL,South Korea,L,South Korea,0,"Python, AWS, Statistics, Computer Vision, SQL",Associate,17,Real Estate,2025-03-10,2025-04-07,2301,6.6,TechCorp Inc -AI01248,Deep Learning Engineer,119123,USD,119123,SE,PT,Norway,S,Portugal,100,"Data Visualization, Python, TensorFlow",Associate,9,Automotive,2024-11-16,2025-01-05,2295,9.7,Autonomous Tech -AI01249,Robotics Engineer,205428,USD,205428,EX,FL,United States,L,United States,0,"R, Spark, Mathematics, TensorFlow, Deep Learning",Associate,10,Finance,2024-06-30,2024-08-22,1349,8.2,TechCorp Inc -AI01250,Deep Learning Engineer,107614,USD,107614,SE,FT,Israel,M,Switzerland,0,"Statistics, NLP, GCP, Python, PyTorch",Bachelor,5,Gaming,2024-04-02,2024-06-11,2346,7.6,Advanced Robotics -AI01251,AI Architect,96395,USD,96395,SE,FT,Israel,M,Israel,50,"Git, PyTorch, Statistics",PhD,5,Energy,2024-10-21,2024-11-27,824,5.4,Quantum Computing Inc -AI01252,Deep Learning Engineer,113420,USD,113420,EN,CT,Norway,L,Norway,50,"Spark, Hadoop, PyTorch, TensorFlow, NLP",Master,1,Technology,2024-07-10,2024-09-11,1658,7.3,DataVision Ltd -AI01253,Machine Learning Engineer,186496,USD,186496,EX,FL,Israel,L,Israel,100,"Azure, AWS, Computer Vision, Java",Bachelor,19,Finance,2024-04-02,2024-05-14,1245,9.2,Smart Analytics -AI01254,Research Scientist,212359,USD,212359,EX,FL,Finland,M,Finland,0,"PyTorch, NLP, Hadoop",Associate,13,Technology,2024-08-01,2024-08-31,508,8.3,TechCorp Inc -AI01255,Head of AI,48963,USD,48963,SE,CT,India,L,India,100,"Python, Computer Vision, TensorFlow",Associate,9,Telecommunications,2025-04-15,2025-05-27,1577,5.6,Quantum Computing Inc -AI01256,Principal Data Scientist,84644,EUR,71947,MI,FL,France,L,France,100,"NLP, Kubernetes, Python",Bachelor,4,Healthcare,2025-02-25,2025-04-03,1615,5.7,Quantum Computing Inc -AI01257,Robotics Engineer,129200,USD,129200,MI,CT,Denmark,L,Denmark,100,"Java, SQL, Kubernetes, Computer Vision",Associate,4,Manufacturing,2025-03-06,2025-05-16,1076,9.3,Neural Networks Co -AI01258,AI Research Scientist,131449,JPY,14459390,SE,FT,Japan,M,Japan,50,"SQL, Hadoop, NLP, Deep Learning, GCP",Associate,9,Retail,2025-02-25,2025-05-08,2118,7.4,Digital Transformation LLC -AI01259,Computer Vision Engineer,37726,USD,37726,EN,CT,China,L,United States,0,"Git, Python, PyTorch, GCP, AWS",PhD,1,Media,2024-03-18,2024-04-03,2339,9.5,Machine Intelligence Group -AI01260,Robotics Engineer,147408,USD,147408,SE,CT,United States,L,United States,0,"Scala, Python, AWS",Master,6,Media,2024-09-26,2024-11-18,652,6.5,DeepTech Ventures -AI01261,Autonomous Systems Engineer,68165,USD,68165,EN,PT,United States,S,Netherlands,0,"Azure, Linux, Computer Vision, R, Java",Bachelor,1,Finance,2024-07-30,2024-10-07,1978,8.5,Quantum Computing Inc -AI01262,Head of AI,153774,USD,153774,EX,FL,Finland,M,Finland,100,"Azure, Hadoop, AWS, Docker",Master,15,Automotive,2024-06-30,2024-08-18,1117,6.7,Quantum Computing Inc -AI01263,AI Consultant,139995,EUR,118996,EX,PT,Austria,S,Colombia,50,"Mathematics, Computer Vision, Linux, Scala, PyTorch",Associate,13,Government,2024-02-13,2024-04-18,546,9,Machine Intelligence Group -AI01264,Computer Vision Engineer,126306,CAD,157883,SE,CT,Canada,S,Vietnam,0,"Azure, R, TensorFlow, AWS, Deep Learning",Associate,6,Transportation,2024-04-20,2024-06-17,2177,8.8,Algorithmic Solutions -AI01265,Principal Data Scientist,142937,USD,142937,SE,FL,United States,S,United States,50,"Git, Python, R, MLOps, Statistics",Bachelor,5,Healthcare,2024-03-12,2024-05-15,1101,5.8,Cloud AI Solutions -AI01266,Data Analyst,157493,USD,157493,SE,FL,Norway,L,Norway,0,"PyTorch, Hadoop, TensorFlow",PhD,8,Media,2024-04-01,2024-04-30,1738,5.9,Algorithmic Solutions -AI01267,Research Scientist,81840,USD,81840,EN,FT,Denmark,S,Denmark,50,"Python, Docker, Deep Learning, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-07,558,8.5,Neural Networks Co -AI01268,AI Product Manager,120340,USD,120340,MI,CT,Norway,S,Norway,0,"Spark, TensorFlow, Python",Associate,2,Transportation,2024-12-18,2025-02-20,2435,9.3,Algorithmic Solutions -AI01269,Deep Learning Engineer,133498,GBP,100124,MI,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,3,Gaming,2024-04-02,2024-05-04,2347,9.6,Autonomous Tech -AI01270,Autonomous Systems Engineer,168321,EUR,143073,EX,PT,Netherlands,M,Netherlands,100,"Mathematics, R, NLP, Deep Learning",Master,18,Automotive,2025-02-13,2025-04-27,1845,7.9,Future Systems -AI01271,Machine Learning Engineer,128450,CAD,160563,SE,PT,Canada,M,Canada,50,"SQL, Hadoop, Git, AWS",Bachelor,7,Healthcare,2024-03-29,2024-05-23,552,6.2,DeepTech Ventures -AI01272,Robotics Engineer,71869,SGD,93430,EN,FT,Singapore,M,Luxembourg,100,"Tableau, Azure, Scala, Computer Vision",Associate,0,Energy,2024-10-23,2024-12-19,1601,7.9,Advanced Robotics -AI01273,AI Architect,86340,USD,86340,MI,FL,Sweden,M,Sweden,0,"AWS, Scala, Hadoop",Master,2,Consulting,2024-12-17,2025-02-05,1229,5,Smart Analytics -AI01274,AI Product Manager,73047,CAD,91309,EN,PT,Canada,M,Australia,100,"NLP, Computer Vision, Python, Hadoop, TensorFlow",Associate,1,Finance,2024-01-17,2024-02-04,1706,8.6,Predictive Systems -AI01275,Principal Data Scientist,125916,AUD,169987,MI,PT,Australia,L,Australia,50,"Tableau, Python, SQL",Master,3,Real Estate,2024-10-25,2024-12-04,1314,9.1,Autonomous Tech -AI01276,AI Software Engineer,107722,USD,107722,SE,PT,Finland,M,Finland,0,"GCP, R, Docker, SQL",PhD,6,Media,2024-08-04,2024-09-20,2439,5.2,DeepTech Ventures -AI01277,AI Architect,100220,USD,100220,MI,PT,Ireland,M,Ukraine,100,"Java, Azure, Spark, Mathematics",Associate,3,Real Estate,2025-04-12,2025-06-17,1841,9.7,DataVision Ltd -AI01278,Machine Learning Researcher,141420,USD,141420,EX,FL,Finland,S,Finland,50,"Linux, PyTorch, Hadoop",Associate,15,Telecommunications,2024-07-26,2024-10-07,877,9.3,Cognitive Computing -AI01279,ML Ops Engineer,43276,USD,43276,SE,FT,China,S,China,0,"AWS, Docker, Computer Vision, PyTorch, SQL",Bachelor,7,Finance,2025-01-26,2025-02-22,2494,6.5,Machine Intelligence Group -AI01280,ML Ops Engineer,101313,EUR,86116,SE,FT,Germany,S,Germany,50,"Statistics, Spark, Data Visualization",Associate,6,Government,2025-03-28,2025-05-08,937,9.9,DataVision Ltd -AI01281,Data Analyst,238881,EUR,203049,EX,FT,Austria,L,Austria,0,"PyTorch, NLP, Scala, Linux",PhD,13,Technology,2024-05-03,2024-07-09,897,7.5,Future Systems -AI01282,Data Scientist,144471,SGD,187812,SE,FL,Singapore,M,Singapore,100,"Java, Deep Learning, Azure",Associate,8,Real Estate,2024-04-01,2024-05-09,984,6,Neural Networks Co -AI01283,Head of AI,71781,EUR,61014,MI,CT,Austria,M,Estonia,100,"Docker, R, Linux, SQL",Bachelor,4,Education,2024-05-05,2024-06-15,2151,5.9,Quantum Computing Inc -AI01284,AI Architect,34334,USD,34334,MI,FT,India,M,Norway,50,"Hadoop, GCP, PyTorch, MLOps, TensorFlow",PhD,3,Government,2024-07-20,2024-08-07,1662,5.8,Neural Networks Co -AI01285,AI Research Scientist,59699,USD,59699,EN,PT,Sweden,L,Sweden,0,"Tableau, MLOps, Scala, Java, NLP",Master,1,Telecommunications,2024-03-09,2024-04-17,526,9.8,Autonomous Tech -AI01286,AI Specialist,74398,SGD,96717,EN,PT,Singapore,L,Denmark,50,"GCP, Kubernetes, Data Visualization, Deep Learning",PhD,1,Gaming,2024-07-05,2024-08-04,560,6.5,Smart Analytics -AI01287,Data Scientist,114132,USD,114132,MI,CT,Israel,L,Israel,100,"R, Spark, NLP, Hadoop",PhD,4,Real Estate,2024-04-02,2024-06-01,1575,7.8,Quantum Computing Inc -AI01288,AI Specialist,82988,USD,82988,EN,FL,Israel,L,United Kingdom,50,"NLP, TensorFlow, PyTorch, Deep Learning, AWS",PhD,1,Gaming,2024-11-05,2024-11-20,1031,5.3,Algorithmic Solutions -AI01289,Data Engineer,129184,USD,129184,MI,FT,Denmark,M,Denmark,100,"Scala, Java, Computer Vision, R, Tableau",Associate,4,Transportation,2024-06-19,2024-08-22,2210,8.1,Autonomous Tech -AI01290,Head of AI,122761,USD,122761,SE,PT,Sweden,S,Sweden,100,"Java, Scala, Mathematics",Master,7,Automotive,2024-07-17,2024-09-06,1608,9.1,TechCorp Inc -AI01291,Machine Learning Engineer,176080,USD,176080,EX,PT,South Korea,S,South Korea,50,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,10,Manufacturing,2024-08-08,2024-09-14,2453,7.3,Cognitive Computing -AI01292,AI Software Engineer,132322,USD,132322,MI,CT,Denmark,L,Denmark,0,"PyTorch, MLOps, Scala, Computer Vision",PhD,3,Healthcare,2024-09-08,2024-11-11,2323,6.5,Machine Intelligence Group -AI01293,Head of AI,220734,EUR,187624,EX,CT,Netherlands,S,Netherlands,50,"TensorFlow, Azure, Scala, Statistics",Associate,19,Media,2024-04-24,2024-05-20,1183,8.8,Advanced Robotics -AI01294,Deep Learning Engineer,210396,USD,210396,EX,PT,Ireland,S,Ireland,0,"Git, MLOps, Kubernetes, Java, Azure",PhD,10,Energy,2025-03-19,2025-04-05,1745,5.2,Future Systems -AI01295,Research Scientist,178095,USD,178095,SE,CT,Norway,L,New Zealand,100,"Python, Tableau, Azure, Statistics",Bachelor,9,Healthcare,2024-09-16,2024-10-12,1142,5.7,Machine Intelligence Group -AI01296,AI Consultant,130897,EUR,111262,EX,FL,France,S,France,50,"GCP, Linux, Data Visualization",Associate,11,Real Estate,2024-03-05,2024-03-30,1235,5.1,Advanced Robotics -AI01297,Computer Vision Engineer,278652,EUR,236854,EX,FL,Netherlands,L,Netherlands,100,"R, Kubernetes, NLP",PhD,14,Real Estate,2025-04-19,2025-05-29,1960,5.7,Cognitive Computing -AI01298,ML Ops Engineer,241681,USD,241681,EX,FL,Finland,L,Finland,0,"Kubernetes, Azure, AWS",Associate,10,Gaming,2024-10-25,2024-12-05,2150,6.3,TechCorp Inc -AI01299,Data Scientist,108165,USD,108165,MI,FL,Norway,S,Poland,50,"Data Visualization, Linux, MLOps, R, NLP",PhD,2,Media,2025-03-09,2025-05-16,962,7.7,Smart Analytics -AI01300,AI Research Scientist,37809,USD,37809,SE,CT,India,M,Estonia,0,"Hadoop, Data Visualization, NLP, Python, Docker",Bachelor,7,Government,2024-05-24,2024-06-13,1144,9.4,DeepTech Ventures -AI01301,Machine Learning Engineer,59161,USD,59161,SE,CT,China,L,China,100,"SQL, Tableau, Scala, Data Visualization",Bachelor,6,Consulting,2024-10-03,2024-11-01,848,9.8,Neural Networks Co -AI01302,Deep Learning Engineer,65717,AUD,88718,EN,FL,Australia,M,Australia,50,"Scala, Git, TensorFlow, Linux",PhD,1,Gaming,2024-08-25,2024-10-20,2168,8.9,Neural Networks Co -AI01303,Machine Learning Engineer,131415,USD,131415,EX,FL,South Korea,M,Czech Republic,0,"TensorFlow, Scala, Computer Vision",Master,14,Finance,2025-04-27,2025-06-20,686,9.2,DataVision Ltd -AI01304,NLP Engineer,165177,CHF,148659,SE,FL,Switzerland,S,Switzerland,0,"Azure, Kubernetes, NLP, AWS",PhD,6,Energy,2024-07-07,2024-09-09,2397,8.6,Algorithmic Solutions -AI01305,Machine Learning Researcher,134710,USD,134710,SE,PT,Finland,L,Finland,50,"Python, Hadoop, NLP",Associate,9,Automotive,2025-01-27,2025-03-22,898,5.9,Smart Analytics -AI01306,AI Specialist,132331,EUR,112481,SE,CT,France,L,France,100,"NLP, Scala, Kubernetes",Master,6,Automotive,2025-02-14,2025-03-17,1623,6,Quantum Computing Inc -AI01307,Machine Learning Researcher,25085,USD,25085,EN,CT,China,S,China,100,"TensorFlow, Scala, PyTorch, GCP, Git",Associate,1,Manufacturing,2024-07-31,2024-09-25,2291,5.2,DataVision Ltd -AI01308,AI Architect,81436,USD,81436,EN,FL,United States,M,United States,50,"Java, Docker, Tableau, Linux, Deep Learning",Associate,0,Technology,2024-11-25,2025-01-31,1081,8.4,Autonomous Tech -AI01309,Robotics Engineer,121581,JPY,13373910,SE,FT,Japan,M,Japan,100,"GCP, Kubernetes, AWS, Docker",Associate,8,Technology,2024-12-10,2025-01-31,1652,9.7,Quantum Computing Inc -AI01310,NLP Engineer,85043,USD,85043,MI,CT,South Korea,M,South Korea,100,"Kubernetes, PyTorch, Computer Vision, GCP, Git",Master,3,Telecommunications,2024-08-20,2024-10-26,1219,8,DeepTech Ventures -AI01311,Principal Data Scientist,77847,EUR,66170,EN,PT,Netherlands,L,Netherlands,50,"Mathematics, Linux, Scala, GCP, Kubernetes",Bachelor,0,Consulting,2024-07-31,2024-09-24,2283,7.1,Cloud AI Solutions -AI01312,Research Scientist,112294,EUR,95450,SE,FT,France,M,France,50,"Python, Java, Hadoop, Deep Learning",PhD,6,Government,2024-09-17,2024-11-16,2496,7.4,Smart Analytics -AI01313,Autonomous Systems Engineer,118482,USD,118482,SE,FT,Finland,M,Portugal,50,"Kubernetes, Docker, NLP, Python, Deep Learning",Master,7,Finance,2024-02-01,2024-02-20,1250,7.6,Neural Networks Co -AI01314,NLP Engineer,76423,USD,76423,EN,PT,United States,M,United States,0,"SQL, Data Visualization, Scala, GCP",Associate,1,Consulting,2024-05-27,2024-07-17,2180,8.7,Autonomous Tech -AI01315,Computer Vision Engineer,66969,EUR,56924,MI,CT,Austria,S,Israel,0,"Python, TensorFlow, Spark, Deep Learning",Associate,2,Government,2024-06-29,2024-08-20,2048,8.5,Predictive Systems -AI01316,AI Architect,88996,USD,88996,MI,FL,Ireland,L,Ireland,100,"SQL, Mathematics, Python",Bachelor,4,Finance,2024-01-12,2024-02-03,2325,8.4,Smart Analytics -AI01317,AI Architect,67741,GBP,50806,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Spark, Computer Vision, PyTorch, Linux",Master,0,Manufacturing,2024-07-24,2024-08-18,808,8.6,Smart Analytics -AI01318,AI Architect,104123,CHF,93711,EN,FL,Switzerland,M,Switzerland,0,"TensorFlow, Computer Vision, NLP",Master,0,Automotive,2024-09-16,2024-10-12,1848,5.4,TechCorp Inc -AI01319,AI Specialist,52117,SGD,67752,EN,FL,Singapore,S,Singapore,50,"Kubernetes, GCP, Linux",PhD,1,Government,2025-03-20,2025-05-17,1881,8.5,Cognitive Computing -AI01320,AI Specialist,107002,USD,107002,EN,CT,Denmark,L,South Korea,100,"GCP, R, Tableau, Statistics, Data Visualization",Bachelor,1,Retail,2024-03-12,2024-04-20,2188,9.9,Algorithmic Solutions -AI01321,Head of AI,171421,JPY,18856310,EX,FT,Japan,S,Japan,0,"Scala, Computer Vision, Tableau, Statistics",Bachelor,12,Education,2025-02-26,2025-04-27,867,7.3,Quantum Computing Inc -AI01322,Principal Data Scientist,102160,USD,102160,SE,FL,Finland,M,Norway,50,"Kubernetes, Scala, Tableau, MLOps",Associate,5,Transportation,2024-12-16,2025-02-04,1617,9.4,Advanced Robotics -AI01323,Robotics Engineer,78797,GBP,59098,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, TensorFlow, R",Associate,0,Automotive,2024-10-11,2024-12-01,708,9.2,DeepTech Ventures -AI01324,Machine Learning Researcher,143483,CAD,179354,SE,CT,Canada,M,Malaysia,0,"Linux, Deep Learning, PyTorch, Mathematics",PhD,8,Education,2025-03-18,2025-04-08,2064,6.2,Machine Intelligence Group -AI01325,Autonomous Systems Engineer,224567,USD,224567,SE,FL,Denmark,L,India,0,"Spark, Linux, Tableau, Data Visualization",Bachelor,7,Automotive,2025-02-03,2025-03-24,1751,7,Smart Analytics -AI01326,Autonomous Systems Engineer,141545,AUD,191086,SE,FL,Australia,L,Australia,0,"Computer Vision, Mathematics, Spark",Bachelor,8,Automotive,2024-10-16,2024-11-09,2451,7.8,Digital Transformation LLC -AI01327,Data Engineer,56427,USD,56427,EN,FT,Israel,M,Hungary,0,"Kubernetes, Tableau, SQL",Bachelor,1,Transportation,2025-01-26,2025-04-07,838,6.1,Future Systems -AI01328,Robotics Engineer,90510,USD,90510,MI,CT,Norway,S,China,100,"SQL, Spark, Mathematics",Bachelor,4,Retail,2024-03-05,2024-04-01,2031,7.2,Future Systems -AI01329,Research Scientist,158669,USD,158669,EX,PT,Israel,S,Israel,100,"SQL, Computer Vision, Docker, AWS, PyTorch",Associate,19,Manufacturing,2024-08-12,2024-08-28,1226,7.8,Digital Transformation LLC -AI01330,AI Software Engineer,74539,JPY,8199290,EN,FT,Japan,S,South Korea,50,"GCP, Java, SQL, R, AWS",PhD,1,Media,2024-12-11,2024-12-30,746,5.1,Neural Networks Co -AI01331,Computer Vision Engineer,124395,EUR,105736,SE,FL,Netherlands,S,Russia,0,"Spark, Git, SQL, Python, TensorFlow",Master,9,Energy,2025-04-15,2025-06-10,2301,9.2,DataVision Ltd -AI01332,AI Research Scientist,174114,USD,174114,EX,PT,United States,M,United States,0,"Data Visualization, MLOps, Tableau, Python, Kubernetes",Master,10,Real Estate,2024-05-15,2024-06-13,2132,7,Digital Transformation LLC -AI01333,Autonomous Systems Engineer,321202,CHF,289082,EX,CT,Switzerland,M,Switzerland,0,"Scala, Linux, Computer Vision",Master,19,Telecommunications,2024-01-14,2024-03-27,1102,9.8,Advanced Robotics -AI01334,NLP Engineer,73469,USD,73469,MI,FL,Sweden,S,Sweden,0,"Python, Hadoop, TensorFlow",Associate,3,Media,2024-02-02,2024-04-08,1664,8.2,DataVision Ltd -AI01335,ML Ops Engineer,142197,USD,142197,SE,PT,Sweden,L,Finland,50,"R, PyTorch, NLP, GCP",PhD,8,Media,2025-03-31,2025-05-14,1349,7.3,Digital Transformation LLC -AI01336,Machine Learning Researcher,157699,EUR,134044,EX,PT,France,S,France,50,"Python, GCP, Scala",Bachelor,19,Consulting,2024-11-05,2024-12-03,1625,7.9,Cognitive Computing -AI01337,Research Scientist,101213,USD,101213,SE,CT,Finland,S,Finland,100,"SQL, Scala, Statistics, Git",Associate,9,Real Estate,2025-04-06,2025-04-28,801,5.1,Predictive Systems -AI01338,AI Architect,84729,USD,84729,MI,CT,Sweden,S,New Zealand,100,"Scala, Spark, Hadoop, Python",Master,3,Automotive,2024-04-07,2024-05-31,1053,9.3,TechCorp Inc -AI01339,Robotics Engineer,87739,CHF,78965,EN,CT,Switzerland,M,Switzerland,0,"R, SQL, Java, Statistics, Linux",Master,0,Finance,2024-10-09,2024-10-28,2211,10,AI Innovations -AI01340,Autonomous Systems Engineer,30121,USD,30121,EN,FL,China,M,Spain,50,"R, Docker, PyTorch",PhD,0,Manufacturing,2024-04-08,2024-06-19,1586,8.1,Digital Transformation LLC -AI01341,Machine Learning Engineer,100916,JPY,11100760,MI,CT,Japan,S,Japan,50,"Scala, Python, MLOps",Bachelor,2,Real Estate,2024-03-17,2024-05-15,2096,5.6,DeepTech Ventures -AI01342,Computer Vision Engineer,55277,USD,55277,EN,FL,Israel,S,Israel,50,"Git, GCP, Kubernetes, Computer Vision, R",Bachelor,0,Finance,2024-08-28,2024-09-24,1348,6.9,DeepTech Ventures -AI01343,ML Ops Engineer,113420,USD,113420,MI,PT,Ireland,L,Romania,0,"Python, TensorFlow, Tableau, MLOps",Master,4,Manufacturing,2025-02-04,2025-03-31,858,7.3,Digital Transformation LLC -AI01344,Machine Learning Engineer,50194,USD,50194,EN,FL,Finland,M,Finland,0,"SQL, Java, Python, Scala, Deep Learning",Bachelor,1,Automotive,2025-02-08,2025-04-11,664,8.1,DataVision Ltd -AI01345,Head of AI,98859,USD,98859,EX,CT,India,L,India,50,"Azure, Python, Kubernetes, Statistics, Deep Learning",Associate,14,Consulting,2024-04-25,2024-06-20,1997,9.2,Predictive Systems -AI01346,Deep Learning Engineer,195373,CHF,175836,SE,FL,Switzerland,M,Switzerland,100,"PyTorch, Git, Tableau",Associate,7,Finance,2025-02-21,2025-03-21,555,7.2,Cloud AI Solutions -AI01347,AI Software Engineer,150038,AUD,202551,SE,CT,Australia,M,Australia,100,"SQL, TensorFlow, Mathematics, Python",Master,8,Automotive,2024-04-26,2024-05-21,2430,5.8,Autonomous Tech -AI01348,AI Software Engineer,46960,USD,46960,EN,PT,South Korea,S,Chile,100,"NLP, Azure, Data Visualization",PhD,1,Government,2024-05-21,2024-07-18,2271,9.1,Autonomous Tech -AI01349,Research Scientist,256508,EUR,218032,EX,FL,Germany,L,Germany,0,"R, Data Visualization, Docker, Scala, Deep Learning",Associate,14,Government,2024-07-04,2024-08-28,1511,7,DeepTech Ventures -AI01350,Principal Data Scientist,123766,GBP,92825,MI,CT,United Kingdom,L,United Kingdom,50,"Python, TensorFlow, R, Computer Vision, PyTorch",Bachelor,4,Retail,2024-06-14,2024-07-20,868,5.9,Neural Networks Co -AI01351,Data Analyst,138655,EUR,117857,SE,PT,Germany,L,Germany,50,"Deep Learning, NLP, Kubernetes, Hadoop",Master,9,Technology,2024-03-10,2024-04-09,1039,6.2,Digital Transformation LLC -AI01352,AI Software Engineer,112307,EUR,95461,MI,FT,Netherlands,M,Vietnam,0,"Python, Azure, Linux, TensorFlow, Java",Associate,3,Government,2024-05-04,2024-06-30,1320,9.4,Future Systems -AI01353,AI Product Manager,75008,USD,75008,EX,FT,India,L,New Zealand,50,"PyTorch, TensorFlow, Spark, Tableau, Scala",Bachelor,15,Retail,2024-09-23,2024-10-29,1493,8,Algorithmic Solutions -AI01354,Robotics Engineer,72038,USD,72038,MI,CT,South Korea,S,South Korea,50,"Python, Docker, AWS, GCP",PhD,3,Energy,2024-05-01,2024-06-26,2322,5.3,DeepTech Ventures -AI01355,AI Software Engineer,141038,USD,141038,SE,CT,Finland,M,Finland,100,"Statistics, MLOps, Python, Linux, Deep Learning",Bachelor,6,Transportation,2025-04-06,2025-04-25,1720,7.3,Algorithmic Solutions -AI01356,AI Research Scientist,113496,USD,113496,SE,CT,Israel,S,Israel,50,"R, Spark, TensorFlow",PhD,9,Real Estate,2024-10-29,2024-11-13,542,8.3,Neural Networks Co -AI01357,Computer Vision Engineer,100144,EUR,85122,SE,FL,France,S,France,0,"Tableau, PyTorch, TensorFlow",PhD,8,Healthcare,2024-09-18,2024-10-22,1494,5.8,Cloud AI Solutions -AI01358,AI Research Scientist,210470,SGD,273611,EX,PT,Singapore,M,Singapore,0,"PyTorch, Azure, Hadoop, Java",Bachelor,12,Real Estate,2024-07-05,2024-07-25,1609,8.3,Autonomous Tech -AI01359,Head of AI,66974,CAD,83718,MI,FT,Canada,S,Canada,100,"Python, Docker, TensorFlow, PyTorch",Master,3,Media,2024-07-03,2024-08-14,2141,7.4,Future Systems -AI01360,Autonomous Systems Engineer,137007,EUR,116456,SE,FT,Netherlands,L,Malaysia,100,"Scala, Computer Vision, SQL, PyTorch, Azure",Associate,8,Government,2025-03-10,2025-05-02,1033,6.7,Cognitive Computing -AI01361,Machine Learning Engineer,80135,USD,80135,MI,CT,Ireland,S,Ireland,50,"Data Visualization, GCP, AWS, SQL, NLP",PhD,4,Government,2024-07-23,2024-10-01,2267,8.8,Smart Analytics -AI01362,Research Scientist,158546,EUR,134764,SE,FT,Netherlands,M,Netherlands,50,"SQL, Hadoop, R, Computer Vision, Docker",Associate,9,Manufacturing,2024-02-03,2024-04-09,2352,9.9,Algorithmic Solutions -AI01363,Deep Learning Engineer,194317,USD,194317,EX,FT,Denmark,M,Denmark,100,"Git, GCP, Tableau, Kubernetes",Bachelor,19,Energy,2024-03-31,2024-06-02,1493,7.2,Digital Transformation LLC -AI01364,Head of AI,83493,EUR,70969,MI,CT,Netherlands,M,Netherlands,50,"Java, Spark, GCP",Master,2,Automotive,2024-05-26,2024-06-10,2305,6.9,Predictive Systems -AI01365,Data Analyst,104222,USD,104222,EN,FT,United States,L,Malaysia,100,"Spark, SQL, Azure, Git, Hadoop",PhD,1,Government,2024-12-06,2025-01-01,1541,5.3,AI Innovations -AI01366,Autonomous Systems Engineer,49854,USD,49854,MI,CT,China,L,China,100,"Python, Hadoop, Computer Vision, Spark, Kubernetes",Master,4,Automotive,2025-01-06,2025-01-28,2345,6.9,Cloud AI Solutions -AI01367,Autonomous Systems Engineer,158519,CAD,198149,EX,CT,Canada,M,Canada,50,"SQL, PyTorch, Mathematics, Hadoop, AWS",Bachelor,14,Government,2025-03-07,2025-04-26,2403,9.8,TechCorp Inc -AI01368,Autonomous Systems Engineer,180734,USD,180734,SE,PT,United States,L,United States,50,"Java, Python, Linux",Master,6,Technology,2024-02-12,2024-04-09,2239,6.3,Machine Intelligence Group -AI01369,ML Ops Engineer,261993,USD,261993,EX,PT,Ireland,L,Russia,0,"SQL, GCP, Mathematics, NLP",Master,11,Telecommunications,2025-04-11,2025-05-10,2341,5.4,Cognitive Computing -AI01370,Robotics Engineer,98054,USD,98054,SE,FT,Finland,M,Finland,0,"PyTorch, SQL, Git, MLOps, AWS",Associate,9,Gaming,2024-01-08,2024-03-04,950,9.8,DataVision Ltd -AI01371,AI Product Manager,82903,USD,82903,MI,PT,South Korea,M,South Korea,50,"Mathematics, Docker, NLP",Bachelor,4,Gaming,2024-12-24,2025-03-05,2095,8.2,Algorithmic Solutions -AI01372,AI Software Engineer,121557,USD,121557,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Scala, Statistics, GCP",PhD,4,Education,2024-08-27,2024-10-09,1642,8.2,Cognitive Computing -AI01373,Data Analyst,172640,USD,172640,SE,FT,Norway,S,Norway,50,"Linux, Kubernetes, SQL",PhD,6,Manufacturing,2024-11-08,2024-12-31,1912,6.7,DataVision Ltd -AI01374,AI Product Manager,122704,EUR,104298,SE,FT,France,M,France,50,"Azure, Tableau, SQL, GCP, Git",PhD,9,Retail,2024-05-24,2024-07-10,1627,9.2,Future Systems -AI01375,Deep Learning Engineer,60832,JPY,6691520,EN,CT,Japan,S,Japan,0,"Tableau, Java, Python, Azure",Bachelor,1,Transportation,2024-06-07,2024-08-17,2416,5.8,AI Innovations -AI01376,AI Research Scientist,134265,USD,134265,EX,FL,South Korea,L,South Korea,0,"Kubernetes, GCP, Mathematics, AWS",Associate,19,Media,2024-09-27,2024-11-06,635,7.2,Cloud AI Solutions -AI01377,Machine Learning Engineer,65618,USD,65618,EN,FT,Denmark,S,Thailand,100,"R, Linux, Hadoop, Git, Computer Vision",Bachelor,1,Gaming,2025-03-15,2025-04-08,508,5.4,Neural Networks Co -AI01378,NLP Engineer,104745,GBP,78559,SE,FL,United Kingdom,S,Denmark,100,"Docker, Linux, Data Visualization, R",Bachelor,7,Government,2025-02-01,2025-03-13,1749,9.3,DataVision Ltd -AI01379,AI Software Engineer,53253,GBP,39940,EN,FL,United Kingdom,S,United Kingdom,50,"PyTorch, Spark, TensorFlow, Azure, Hadoop",Master,0,Technology,2025-04-11,2025-06-03,652,9,Cloud AI Solutions -AI01380,Computer Vision Engineer,166691,JPY,18336010,EX,PT,Japan,S,Japan,100,"Mathematics, Deep Learning, Scala, R, PyTorch",Master,14,Automotive,2024-05-17,2024-06-10,1849,7,DeepTech Ventures -AI01381,Computer Vision Engineer,146267,CAD,182834,EX,PT,Canada,M,Canada,0,"Scala, R, Docker",PhD,10,Gaming,2025-01-10,2025-02-13,2428,7,DeepTech Ventures -AI01382,AI Consultant,97969,USD,97969,SE,FT,Finland,M,Finland,0,"Spark, PyTorch, MLOps, Tableau",PhD,9,Energy,2024-06-09,2024-07-07,530,9.7,Advanced Robotics -AI01383,Principal Data Scientist,206614,CAD,258268,EX,PT,Canada,M,Ireland,100,"Hadoop, R, Kubernetes",Bachelor,14,Government,2024-02-11,2024-03-20,874,6.2,Machine Intelligence Group -AI01384,Data Analyst,78327,EUR,66578,MI,FT,Austria,M,Austria,0,"Data Visualization, NLP, Mathematics",PhD,3,Consulting,2024-06-29,2024-08-23,2076,5.7,AI Innovations -AI01385,Robotics Engineer,70510,EUR,59934,EN,PT,Austria,L,Turkey,0,"R, Python, TensorFlow, Tableau, Statistics",Bachelor,0,Gaming,2024-08-28,2024-09-29,912,7.1,DataVision Ltd -AI01386,Data Analyst,41791,USD,41791,SE,FT,India,M,India,100,"Linux, SQL, Mathematics, Hadoop",Bachelor,7,Media,2024-12-02,2025-01-11,2227,9.7,Algorithmic Solutions -AI01387,AI Consultant,115800,EUR,98430,MI,FL,Austria,L,Luxembourg,50,"Python, TensorFlow, Spark, PyTorch",Bachelor,3,Media,2025-02-02,2025-03-29,1284,7.9,Digital Transformation LLC -AI01388,Machine Learning Engineer,113860,USD,113860,SE,PT,Finland,L,Sweden,100,"SQL, PyTorch, Python, Docker",Associate,6,Healthcare,2024-05-02,2024-07-11,1096,8.5,AI Innovations -AI01389,Data Analyst,181595,USD,181595,SE,FT,United States,L,United States,100,"Docker, PyTorch, Data Visualization, Hadoop, Spark",Master,7,Automotive,2024-12-31,2025-03-10,1181,8.7,Digital Transformation LLC -AI01390,AI Product Manager,157567,EUR,133932,EX,FT,Austria,L,Israel,50,"Azure, Hadoop, Java, Deep Learning",Associate,18,Finance,2024-01-14,2024-02-22,2191,5.6,Quantum Computing Inc -AI01391,Autonomous Systems Engineer,124885,EUR,106152,MI,FL,Netherlands,L,Netherlands,0,"Linux, AWS, Spark, SQL, PyTorch",PhD,4,Automotive,2024-12-11,2025-01-11,1416,9.2,Smart Analytics -AI01392,NLP Engineer,123910,USD,123910,EX,FL,Ireland,S,Ireland,50,"PyTorch, Tableau, Computer Vision, Git",Bachelor,16,Transportation,2024-09-22,2024-11-24,1656,8,Neural Networks Co -AI01393,AI Specialist,137838,USD,137838,SE,FL,Sweden,L,Belgium,0,"Mathematics, MLOps, Tableau, Kubernetes, Python",PhD,8,Gaming,2024-07-12,2024-08-07,732,7.8,Cloud AI Solutions -AI01394,Data Engineer,313735,USD,313735,EX,FT,Denmark,M,Denmark,0,"NLP, Linux, Kubernetes",Associate,12,Healthcare,2024-12-16,2025-01-06,1940,6.7,Neural Networks Co -AI01395,Computer Vision Engineer,96380,USD,96380,EN,PT,Denmark,M,Ireland,50,"Kubernetes, Python, Statistics",Bachelor,0,Media,2024-10-12,2024-11-30,1399,9,Digital Transformation LLC -AI01396,Data Engineer,63171,EUR,53695,EN,CT,Netherlands,M,Netherlands,100,"Scala, Hadoop, AWS",Bachelor,0,Automotive,2024-12-24,2025-03-03,561,8.8,AI Innovations -AI01397,AI Specialist,123969,USD,123969,SE,FT,Sweden,S,Sweden,0,"SQL, PyTorch, GCP",Bachelor,9,Energy,2025-04-01,2025-04-22,1527,9.8,Quantum Computing Inc -AI01398,Data Analyst,54611,EUR,46419,EN,CT,France,M,France,0,"Python, Linux, TensorFlow, Computer Vision, PyTorch",PhD,0,Technology,2024-12-11,2024-12-26,865,9,Machine Intelligence Group -AI01399,Machine Learning Engineer,119705,USD,119705,MI,PT,Denmark,L,Switzerland,0,"MLOps, Python, R, AWS, Docker",Bachelor,3,Education,2024-03-23,2024-06-02,1556,7.2,Quantum Computing Inc -AI01400,Autonomous Systems Engineer,173697,CHF,156327,SE,FL,Switzerland,S,China,50,"Python, AWS, Scala",Associate,9,Media,2025-01-09,2025-03-23,927,8.2,Algorithmic Solutions -AI01401,Data Scientist,144553,AUD,195147,SE,CT,Australia,L,South Korea,0,"Data Visualization, R, Linux, MLOps",PhD,6,Telecommunications,2024-07-22,2024-09-21,1806,5.8,AI Innovations -AI01402,Research Scientist,76409,GBP,57307,MI,FL,United Kingdom,S,Brazil,50,"AWS, Hadoop, PyTorch",Master,2,Government,2024-10-29,2024-11-12,2125,8.3,DataVision Ltd -AI01403,NLP Engineer,105022,AUD,141780,SE,FT,Australia,M,Japan,0,"Mathematics, Python, Data Visualization, Deep Learning, GCP",PhD,8,Government,2024-01-11,2024-03-12,1947,8.4,Cognitive Computing -AI01404,Data Engineer,147919,AUD,199691,SE,PT,Australia,L,Australia,0,"TensorFlow, Linux, Azure, Mathematics",Bachelor,8,Manufacturing,2024-05-20,2024-07-28,1479,7.6,Neural Networks Co -AI01405,Data Engineer,105054,CHF,94549,EN,CT,Switzerland,L,Switzerland,100,"Azure, Java, Data Visualization",Master,0,Technology,2024-03-06,2024-04-21,740,5.3,Advanced Robotics -AI01406,AI Architect,168883,USD,168883,EX,PT,South Korea,S,South Korea,50,"PyTorch, Spark, R, TensorFlow",Bachelor,17,Government,2024-04-02,2024-04-28,1976,5.5,TechCorp Inc -AI01407,AI Architect,54905,USD,54905,EN,PT,Finland,S,Malaysia,50,"SQL, Python, Azure, Hadoop, Mathematics",PhD,0,Government,2025-02-24,2025-03-31,1770,6.6,Machine Intelligence Group -AI01408,Data Scientist,73214,USD,73214,EX,CT,China,M,China,50,"SQL, Statistics, PyTorch, AWS",Bachelor,19,Government,2024-01-14,2024-03-03,1326,8.6,Future Systems -AI01409,Computer Vision Engineer,75589,USD,75589,MI,PT,South Korea,S,South Korea,50,"Python, Statistics, Computer Vision, Linux",Bachelor,4,Automotive,2024-02-11,2024-04-16,2026,7.2,Digital Transformation LLC -AI01410,Robotics Engineer,104795,CHF,94316,EN,CT,Switzerland,M,Japan,50,"Deep Learning, TensorFlow, Python, Linux, Java",Master,1,Telecommunications,2025-04-06,2025-05-28,1865,6.6,Future Systems -AI01411,AI Architect,19456,USD,19456,EN,CT,India,S,India,0,"Java, GCP, AWS, Deep Learning, Spark",Associate,1,Automotive,2024-02-24,2024-03-11,1072,9.7,Autonomous Tech -AI01412,Data Engineer,212599,EUR,180709,EX,FT,Austria,S,Austria,50,"Python, Docker, SQL, Linux",Master,13,Automotive,2024-07-11,2024-07-27,1697,10,DeepTech Ventures -AI01413,AI Research Scientist,63226,JPY,6954860,EN,CT,Japan,M,Japan,0,"Hadoop, Python, TensorFlow, Deep Learning",Bachelor,1,Government,2024-10-04,2024-12-07,963,6.7,Cloud AI Solutions -AI01414,AI Architect,188891,USD,188891,SE,PT,United States,L,Portugal,0,"Python, SQL, Linux",Master,5,Automotive,2024-01-16,2024-03-01,2133,5.8,DeepTech Ventures -AI01415,Head of AI,45335,USD,45335,EN,FT,South Korea,S,South Korea,100,"NLP, SQL, Java, MLOps, Kubernetes",Bachelor,0,Manufacturing,2024-06-01,2024-06-17,1381,6.3,Predictive Systems -AI01416,NLP Engineer,114078,GBP,85559,MI,CT,United Kingdom,M,United Kingdom,50,"Java, TensorFlow, GCP",PhD,4,Technology,2024-05-01,2024-05-26,1203,6.5,Digital Transformation LLC -AI01417,AI Software Engineer,221905,USD,221905,EX,FL,Norway,L,Norway,0,"Hadoop, Scala, SQL",Bachelor,16,Gaming,2024-11-19,2024-12-05,1585,5.9,Algorithmic Solutions -AI01418,Principal Data Scientist,34898,USD,34898,MI,FL,China,M,China,100,"Kubernetes, Linux, Git, SQL, R",PhD,4,Retail,2025-01-17,2025-02-14,1878,7.1,AI Innovations -AI01419,Autonomous Systems Engineer,288283,USD,288283,EX,FL,Ireland,L,Vietnam,50,"Tableau, Statistics, Spark, Kubernetes, Git",Master,17,Consulting,2024-01-31,2024-03-21,882,7.1,Cloud AI Solutions -AI01420,Robotics Engineer,75188,USD,75188,MI,FT,Ireland,M,Ukraine,50,"Python, Git, Azure",Associate,3,Government,2025-04-11,2025-05-26,1123,9,TechCorp Inc -AI01421,Principal Data Scientist,87149,USD,87149,EN,FL,Denmark,S,Italy,50,"Azure, Kubernetes, Docker, SQL, Data Visualization",Associate,1,Real Estate,2024-11-02,2024-11-18,1009,7.4,TechCorp Inc -AI01422,Robotics Engineer,91150,USD,91150,MI,CT,Norway,S,Norway,50,"Java, Python, Computer Vision",PhD,4,Retail,2024-06-05,2024-08-04,2308,7,Quantum Computing Inc -AI01423,Research Scientist,126040,AUD,170154,SE,FL,Australia,S,Australia,50,"Docker, SQL, Mathematics, Spark",Master,9,Manufacturing,2024-05-07,2024-06-21,2052,9.9,DeepTech Ventures -AI01424,AI Research Scientist,187737,USD,187737,EX,FT,Sweden,L,Sweden,0,"Java, R, Mathematics, Computer Vision",PhD,15,Government,2024-03-30,2024-04-25,1706,7,Machine Intelligence Group -AI01425,AI Product Manager,125535,USD,125535,MI,PT,United States,M,United States,0,"Hadoop, PyTorch, Scala, GCP",Bachelor,3,Retail,2024-06-17,2024-07-16,2147,7.7,TechCorp Inc -AI01426,AI Product Manager,373536,USD,373536,EX,FL,Norway,L,Norway,100,"NLP, Kubernetes, Spark",Master,10,Technology,2025-03-20,2025-05-22,730,9.4,DeepTech Ventures -AI01427,Deep Learning Engineer,100732,CHF,90659,EN,FT,Switzerland,M,Switzerland,100,"Tableau, Python, Hadoop, Kubernetes",PhD,1,Media,2024-06-16,2024-07-30,1200,10,Predictive Systems -AI01428,Data Engineer,212371,GBP,159278,EX,FT,United Kingdom,L,United Kingdom,50,"Java, Kubernetes, Tableau, Hadoop, Scala",Bachelor,15,Consulting,2025-03-06,2025-03-20,615,9.5,Autonomous Tech -AI01429,AI Software Engineer,65466,EUR,55646,EN,PT,Germany,L,Germany,0,"Mathematics, PyTorch, Statistics",Master,1,Finance,2024-03-25,2024-05-04,1943,8.2,Quantum Computing Inc -AI01430,Computer Vision Engineer,109204,SGD,141965,MI,PT,Singapore,M,Nigeria,50,"Mathematics, Data Visualization, MLOps, Tableau",Associate,3,Retail,2024-09-15,2024-11-16,1841,5.3,AI Innovations -AI01431,Data Engineer,72736,JPY,8000960,MI,CT,Japan,S,Germany,50,"R, Python, Data Visualization, PyTorch",Associate,2,Telecommunications,2025-02-13,2025-03-21,1794,8.9,AI Innovations -AI01432,Autonomous Systems Engineer,20520,USD,20520,EN,FL,India,M,Israel,100,"R, Spark, Hadoop, Kubernetes, GCP",Associate,0,Gaming,2024-07-21,2024-08-07,2201,8.9,Cloud AI Solutions -AI01433,AI Architect,158930,USD,158930,EX,PT,Ireland,M,Ireland,100,"Spark, PyTorch, Mathematics",PhD,19,Transportation,2025-01-29,2025-03-23,965,7.9,DeepTech Ventures -AI01434,Principal Data Scientist,76074,CHF,68467,EN,FT,Switzerland,M,Switzerland,100,"Scala, Spark, MLOps",Master,0,Gaming,2024-06-14,2024-07-22,2169,6,Cognitive Computing -AI01435,Machine Learning Researcher,59343,EUR,50442,EN,FT,France,S,France,0,"NLP, Mathematics, Kubernetes, Computer Vision, Tableau",Bachelor,1,Government,2024-03-29,2024-05-11,690,8.2,Advanced Robotics -AI01436,Data Scientist,104447,USD,104447,MI,CT,United States,S,United States,100,"Deep Learning, Data Visualization, AWS, TensorFlow, Scala",Bachelor,2,Technology,2024-12-10,2025-02-15,1675,8.4,Neural Networks Co -AI01437,AI Software Engineer,43120,USD,43120,MI,PT,China,M,China,50,"AWS, Docker, NLP",Bachelor,4,Automotive,2024-03-04,2024-04-21,1871,8.9,DataVision Ltd -AI01438,Machine Learning Engineer,219852,EUR,186874,EX,FL,Austria,L,Austria,100,"Hadoop, Kubernetes, TensorFlow, GCP",Associate,14,Healthcare,2024-01-11,2024-03-11,1760,6.6,DataVision Ltd -AI01439,Data Engineer,40164,USD,40164,SE,CT,India,S,India,0,"Scala, Kubernetes, Git, Docker",Bachelor,7,Telecommunications,2024-11-21,2025-01-23,2230,5.9,Digital Transformation LLC -AI01440,Data Analyst,164110,SGD,213343,EX,FT,Singapore,S,Singapore,50,"SQL, Git, GCP",Associate,15,Gaming,2025-01-04,2025-02-01,1042,7.8,Future Systems -AI01441,Machine Learning Researcher,33846,USD,33846,MI,PT,China,S,China,100,"PyTorch, Hadoop, Statistics, AWS, Computer Vision",Bachelor,2,Transportation,2024-03-06,2024-03-22,804,6.8,Digital Transformation LLC -AI01442,Data Engineer,126266,USD,126266,MI,PT,Sweden,L,Sweden,100,"PyTorch, Spark, TensorFlow",Master,4,Energy,2024-06-28,2024-07-28,1765,6.6,Machine Intelligence Group -AI01443,Head of AI,98327,USD,98327,MI,PT,United States,L,United States,50,"R, Data Visualization, Mathematics",Associate,4,Education,2024-09-12,2024-10-04,1849,5.1,Neural Networks Co -AI01444,Data Scientist,77366,GBP,58025,MI,PT,United Kingdom,S,Japan,50,"Python, TensorFlow, NLP, Azure, AWS",PhD,3,Automotive,2024-06-19,2024-08-04,2357,5.6,Cognitive Computing -AI01445,ML Ops Engineer,76129,USD,76129,EN,FL,Denmark,S,Indonesia,50,"Hadoop, PyTorch, MLOps",Master,0,Education,2024-12-01,2024-12-15,788,7.8,Cloud AI Solutions -AI01446,AI Product Manager,134331,CHF,120898,MI,PT,Switzerland,L,Switzerland,100,"Java, Mathematics, TensorFlow",Associate,2,Energy,2024-01-11,2024-02-19,842,10,DeepTech Ventures -AI01447,Data Engineer,56083,EUR,47671,EN,FL,Austria,M,Austria,0,"Python, Statistics, SQL, R, Linux",Master,1,Transportation,2024-07-24,2024-08-16,1613,6.4,AI Innovations -AI01448,Robotics Engineer,147444,USD,147444,EX,CT,Finland,S,Finland,0,"Scala, Spark, Java",PhD,15,Technology,2025-04-18,2025-06-06,2271,5.6,Cloud AI Solutions -AI01449,AI Product Manager,92983,USD,92983,EN,CT,Norway,S,Ghana,50,"TensorFlow, Scala, GCP, Git",PhD,0,Education,2025-01-04,2025-01-26,1036,7.8,Neural Networks Co -AI01450,ML Ops Engineer,83859,EUR,71280,EN,FL,Austria,L,Austria,50,"Tableau, Hadoop, PyTorch",Bachelor,1,Real Estate,2025-01-18,2025-03-31,2435,8.2,Predictive Systems -AI01451,NLP Engineer,84786,EUR,72068,MI,FL,Germany,M,Ukraine,0,"Java, Linux, Statistics, Git",Master,2,Transportation,2025-02-04,2025-03-18,1912,9.2,Digital Transformation LLC -AI01452,Computer Vision Engineer,154829,EUR,131605,EX,CT,Germany,S,Kenya,100,"Tableau, AWS, Hadoop, Kubernetes, Git",Bachelor,11,Energy,2024-08-21,2024-10-30,2309,5.4,DataVision Ltd -AI01453,Machine Learning Engineer,216967,GBP,162725,EX,FT,United Kingdom,S,Chile,0,"R, Scala, NLP, Git, Docker",Bachelor,12,Education,2024-07-18,2024-09-29,1500,8.6,Future Systems -AI01454,Computer Vision Engineer,90170,USD,90170,MI,PT,Ireland,L,Ireland,100,"Git, TensorFlow, Deep Learning",Bachelor,3,Transportation,2024-04-12,2024-05-08,2067,5.6,TechCorp Inc -AI01455,AI Software Engineer,59279,SGD,77063,EN,PT,Singapore,M,Singapore,0,"Python, TensorFlow, PyTorch, Linux",Associate,1,Education,2025-02-22,2025-04-02,2481,9.2,Cloud AI Solutions -AI01456,AI Specialist,85165,USD,85165,EX,FL,China,L,China,100,"MLOps, Spark, Azure, TensorFlow",Bachelor,19,Automotive,2025-03-11,2025-04-29,1813,6.6,Digital Transformation LLC -AI01457,Machine Learning Researcher,58417,EUR,49654,EN,PT,Netherlands,S,United States,100,"Spark, Docker, GCP, Statistics, Python",PhD,1,Technology,2024-07-22,2024-09-17,1842,8.4,Smart Analytics -AI01458,Research Scientist,160456,EUR,136388,EX,CT,Netherlands,M,Netherlands,100,"Python, TensorFlow, MLOps, Spark, R",Master,11,Manufacturing,2024-04-08,2024-05-27,1814,5.4,Autonomous Tech -AI01459,Robotics Engineer,29590,USD,29590,EN,FT,China,S,South Korea,0,"Linux, Data Visualization, Java, Hadoop, NLP",Bachelor,1,Retail,2024-06-10,2024-08-07,1355,5.4,TechCorp Inc -AI01460,Deep Learning Engineer,242489,GBP,181867,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, Hadoop, Python, Mathematics, Docker",Bachelor,19,Telecommunications,2024-08-14,2024-09-04,985,5.8,Algorithmic Solutions -AI01461,ML Ops Engineer,136042,GBP,102032,SE,FT,United Kingdom,S,Austria,0,"Scala, Kubernetes, Linux, AWS",Bachelor,8,Gaming,2024-07-19,2024-09-08,2139,8.7,Future Systems -AI01462,AI Software Engineer,104200,CAD,130250,SE,FT,Canada,M,Canada,100,"Linux, Kubernetes, Scala",Master,9,Gaming,2025-03-26,2025-05-11,2429,6.3,Advanced Robotics -AI01463,Principal Data Scientist,137878,EUR,117196,SE,CT,Germany,L,Latvia,50,"R, SQL, Tableau, MLOps, Kubernetes",Master,7,Manufacturing,2025-03-10,2025-03-31,640,7.2,Cognitive Computing -AI01464,ML Ops Engineer,187710,USD,187710,SE,PT,Denmark,M,Denmark,50,"Git, NLP, SQL",Bachelor,8,Consulting,2025-02-15,2025-03-25,1597,7.4,Algorithmic Solutions -AI01465,AI Software Engineer,50439,USD,50439,SE,CT,India,M,India,100,"Spark, Python, TensorFlow, Statistics, Java",Master,7,Telecommunications,2024-01-08,2024-03-03,2331,7.7,Algorithmic Solutions -AI01466,AI Architect,29300,USD,29300,EN,FT,India,L,India,50,"Tableau, R, MLOps",PhD,1,Media,2024-11-03,2025-01-01,2378,8.5,Algorithmic Solutions -AI01467,Machine Learning Engineer,93689,USD,93689,EX,FT,China,S,China,0,"Python, TensorFlow, Mathematics, Kubernetes, Docker",Associate,18,Real Estate,2024-04-02,2024-05-26,2251,8.3,Smart Analytics -AI01468,Data Analyst,182500,USD,182500,EX,FL,United States,M,United States,0,"Mathematics, MLOps, Azure",Associate,16,Automotive,2024-11-22,2024-12-29,1397,9.6,Neural Networks Co -AI01469,Robotics Engineer,149041,AUD,201205,SE,FL,Australia,L,Australia,0,"PyTorch, TensorFlow, Scala, Git",PhD,8,Education,2025-03-10,2025-04-23,851,7.2,Digital Transformation LLC -AI01470,Computer Vision Engineer,43748,EUR,37186,EN,PT,France,S,Mexico,50,"Deep Learning, Java, SQL, Git, Docker",PhD,0,Education,2024-12-18,2025-01-30,692,9.5,AI Innovations -AI01471,Principal Data Scientist,54185,EUR,46057,EN,FT,Germany,S,India,0,"Computer Vision, PyTorch, Scala, GCP",Master,0,Telecommunications,2025-03-18,2025-05-29,755,6.8,TechCorp Inc -AI01472,NLP Engineer,69436,USD,69436,EX,PT,India,M,India,100,"Data Visualization, Kubernetes, Python",Associate,19,Automotive,2024-11-10,2024-12-04,748,8.4,Neural Networks Co -AI01473,Data Analyst,103188,USD,103188,EN,PT,United States,L,United States,0,"Git, Spark, Python, Java, GCP",PhD,1,Transportation,2024-03-24,2024-04-24,1596,5.6,Smart Analytics -AI01474,AI Research Scientist,116739,CHF,105065,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Java, Hadoop",Bachelor,0,Education,2025-01-21,2025-02-11,2191,6.3,Future Systems -AI01475,Deep Learning Engineer,73367,EUR,62362,EN,FL,Austria,M,Austria,0,"AWS, SQL, Tableau, PyTorch",Bachelor,1,Gaming,2024-11-30,2024-12-30,521,6.3,Predictive Systems -AI01476,Data Engineer,72979,JPY,8027690,EN,CT,Japan,S,Japan,50,"PyTorch, R, Docker, GCP, Azure",Associate,1,Retail,2025-02-21,2025-03-27,2262,6.5,Neural Networks Co -AI01477,Data Engineer,193939,USD,193939,EX,PT,Israel,M,Israel,100,"TensorFlow, Python, Hadoop, Tableau, Data Visualization",Bachelor,12,Technology,2025-01-28,2025-03-24,1382,8.6,DeepTech Ventures -AI01478,Research Scientist,151333,USD,151333,EX,FL,Ireland,M,Ireland,50,"Kubernetes, R, Statistics, GCP, Scala",Master,19,Gaming,2025-03-04,2025-05-04,503,5.8,Cognitive Computing -AI01479,Data Scientist,63229,USD,63229,SE,CT,China,S,China,100,"Scala, Java, Statistics, AWS, Kubernetes",Associate,6,Education,2024-12-17,2025-01-21,2342,9.8,Cognitive Computing -AI01480,Principal Data Scientist,188397,CHF,169557,SE,FT,Switzerland,S,Netherlands,50,"Git, PyTorch, AWS, Docker, GCP",Master,7,Healthcare,2024-09-02,2024-10-31,1198,9.6,AI Innovations -AI01481,Robotics Engineer,102987,USD,102987,MI,FT,Denmark,M,Denmark,0,"Python, GCP, MLOps, Azure, Hadoop",PhD,4,Retail,2024-07-28,2024-10-05,1017,6.5,DataVision Ltd -AI01482,AI Specialist,226210,USD,226210,SE,FT,Denmark,L,Denmark,50,"PyTorch, Scala, TensorFlow, AWS, Deep Learning",PhD,9,Manufacturing,2024-02-15,2024-03-29,2494,5.6,Future Systems -AI01483,AI Architect,18309,USD,18309,EN,FL,India,S,India,100,"PyTorch, Deep Learning, TensorFlow",Associate,0,Media,2024-10-14,2024-12-12,1247,7.6,DeepTech Ventures -AI01484,AI Software Engineer,210459,USD,210459,EX,CT,Israel,S,Israel,0,"Python, Computer Vision, NLP, Azure, Java",Master,17,Government,2025-02-19,2025-04-26,898,6.9,Advanced Robotics -AI01485,Robotics Engineer,70962,USD,70962,SE,CT,China,M,China,0,"Computer Vision, SQL, Linux",Associate,6,Consulting,2025-02-10,2025-03-22,1509,5.3,Machine Intelligence Group -AI01486,AI Research Scientist,71103,EUR,60438,MI,PT,Netherlands,S,New Zealand,0,"R, AWS, Kubernetes, Linux, Mathematics",Bachelor,3,Healthcare,2024-06-04,2024-08-16,1863,8.7,Predictive Systems -AI01487,Computer Vision Engineer,94344,USD,94344,EN,FT,Denmark,M,Argentina,50,"AWS, Tableau, SQL, PyTorch",Master,0,Education,2024-08-31,2024-09-27,1961,8.1,Predictive Systems -AI01488,Autonomous Systems Engineer,31310,USD,31310,EN,FT,China,M,China,100,"Tableau, Kubernetes, Scala",Bachelor,0,Healthcare,2025-03-16,2025-04-20,712,6.8,DataVision Ltd -AI01489,AI Product Manager,186865,USD,186865,EX,PT,Ireland,L,Ireland,100,"Data Visualization, Python, TensorFlow, AWS",PhD,17,Technology,2024-06-07,2024-08-14,1906,8,Cognitive Computing -AI01490,AI Product Manager,22689,USD,22689,EN,CT,India,S,India,50,"Deep Learning, SQL, MLOps, Data Visualization, Git",Bachelor,0,Finance,2024-08-20,2024-09-29,835,5.1,DataVision Ltd -AI01491,AI Product Manager,71875,USD,71875,EX,FT,China,M,China,50,"Hadoop, SQL, Data Visualization, TensorFlow",PhD,17,Healthcare,2024-01-30,2024-03-22,2427,8.7,DataVision Ltd -AI01492,AI Specialist,91093,USD,91093,EN,FT,Denmark,M,Denmark,50,"Tableau, SQL, Python",Master,1,Finance,2024-07-07,2024-07-22,1322,7.4,Cloud AI Solutions -AI01493,NLP Engineer,59983,USD,59983,MI,CT,South Korea,S,Colombia,50,"SQL, PyTorch, Tableau, Kubernetes",Master,3,Finance,2025-02-22,2025-04-04,1654,9.6,Smart Analytics -AI01494,AI Specialist,315917,CHF,284325,EX,FL,Switzerland,M,Switzerland,50,"Statistics, SQL, Tableau, Computer Vision, Docker",PhD,13,Media,2024-01-21,2024-03-01,870,7.4,Predictive Systems -AI01495,Robotics Engineer,49015,USD,49015,EN,FT,Ireland,S,Ireland,100,"Scala, Data Visualization, SQL, MLOps",Bachelor,1,Healthcare,2024-11-30,2025-01-28,920,5.1,Predictive Systems -AI01496,NLP Engineer,45174,USD,45174,EN,CT,South Korea,M,South Korea,50,"Python, Scala, SQL",Associate,0,Consulting,2024-07-27,2024-08-17,857,5.7,Quantum Computing Inc -AI01497,Head of AI,124375,USD,124375,MI,FL,Norway,L,Norway,0,"SQL, Computer Vision, Git, GCP, PyTorch",Master,3,Transportation,2024-10-22,2025-01-01,2017,6.1,TechCorp Inc -AI01498,Principal Data Scientist,24919,USD,24919,EN,CT,India,M,Indonesia,0,"TensorFlow, Tableau, GCP",Associate,0,Gaming,2024-07-25,2024-08-18,2434,7.3,Predictive Systems -AI01499,AI Architect,103196,EUR,87717,SE,FL,Austria,M,Austria,50,"SQL, Java, Kubernetes, Deep Learning",Master,9,Automotive,2025-04-08,2025-06-02,2102,8,DataVision Ltd -AI01500,Computer Vision Engineer,101200,USD,101200,EN,FL,Norway,M,Norway,100,"SQL, Computer Vision, PyTorch, Git, Tableau",Bachelor,1,Government,2024-11-04,2024-11-21,2344,6.9,Advanced Robotics -AI01501,Data Scientist,146547,USD,146547,SE,FT,Finland,L,Canada,100,"TensorFlow, NLP, Mathematics, Tableau, Kubernetes",Bachelor,9,Automotive,2024-10-30,2024-12-27,669,6.9,Machine Intelligence Group -AI01502,Autonomous Systems Engineer,72296,USD,72296,SE,CT,China,L,China,50,"Scala, AWS, NLP, Git, Python",Associate,8,Automotive,2025-03-21,2025-05-14,1029,9.8,Algorithmic Solutions -AI01503,ML Ops Engineer,63430,USD,63430,EN,FL,United States,S,Thailand,50,"GCP, Deep Learning, PyTorch, AWS",PhD,0,Automotive,2024-11-14,2025-01-08,2301,6.9,Machine Intelligence Group -AI01504,Computer Vision Engineer,266480,USD,266480,EX,FT,Israel,L,Israel,100,"SQL, Python, Tableau, Statistics",Bachelor,16,Consulting,2024-12-02,2025-01-20,1350,6.4,Predictive Systems -AI01505,Computer Vision Engineer,115622,EUR,98279,SE,CT,Austria,S,Austria,0,"Spark, Hadoop, Data Visualization, MLOps, Azure",Master,6,Transportation,2024-07-26,2024-08-18,589,7.9,DataVision Ltd -AI01506,NLP Engineer,59313,USD,59313,SE,FT,India,L,Philippines,0,"Data Visualization, GCP, Linux, Computer Vision",Master,7,Manufacturing,2024-12-26,2025-02-16,901,7.3,AI Innovations -AI01507,Research Scientist,106901,EUR,90866,MI,FL,Germany,L,Germany,50,"TensorFlow, Python, Statistics",PhD,3,Manufacturing,2025-04-14,2025-06-23,746,5.8,Smart Analytics -AI01508,NLP Engineer,179377,EUR,152470,EX,CT,Netherlands,S,Nigeria,0,"Data Visualization, GCP, Scala, R, AWS",Associate,11,Technology,2024-09-21,2024-10-23,1996,6.3,Algorithmic Solutions -AI01509,Data Engineer,98356,USD,98356,MI,CT,Sweden,M,Sweden,0,"NLP, PyTorch, Scala, Deep Learning",Associate,2,Technology,2024-12-12,2025-01-17,1771,6,Autonomous Tech -AI01510,Data Analyst,143818,SGD,186963,SE,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, TensorFlow, Statistics",Bachelor,8,Manufacturing,2024-05-16,2024-07-14,807,8,DeepTech Ventures -AI01511,AI Research Scientist,148765,CAD,185956,SE,PT,Canada,L,Canada,50,"Computer Vision, PyTorch, SQL",Associate,6,Gaming,2025-04-28,2025-07-10,1542,6.4,Quantum Computing Inc -AI01512,Research Scientist,88116,USD,88116,EN,FT,Norway,S,Singapore,0,"R, NLP, GCP",PhD,1,Telecommunications,2025-03-14,2025-03-29,2478,6.7,Predictive Systems -AI01513,Robotics Engineer,49914,USD,49914,EN,FL,South Korea,S,South Korea,50,"Hadoop, Python, Computer Vision",PhD,0,Telecommunications,2024-01-30,2024-04-11,1057,6.9,Quantum Computing Inc -AI01514,Autonomous Systems Engineer,39015,USD,39015,EN,PT,China,L,China,0,"R, Linux, SQL, PyTorch",PhD,0,Automotive,2024-10-27,2024-12-10,1371,6.3,Digital Transformation LLC -AI01515,AI Architect,88810,GBP,66608,MI,FL,United Kingdom,L,Russia,0,"Tableau, Scala, Spark",PhD,4,Finance,2024-07-25,2024-09-25,963,9.9,Predictive Systems -AI01516,Machine Learning Engineer,224663,USD,224663,EX,FL,United States,L,United States,50,"TensorFlow, Deep Learning, Computer Vision",Associate,19,Automotive,2024-11-28,2025-01-18,1986,9.9,DeepTech Ventures -AI01517,Data Scientist,63881,AUD,86239,EN,CT,Australia,L,Australia,0,"PyTorch, GCP, Computer Vision, AWS",Associate,0,Transportation,2024-10-24,2024-11-10,1505,9.4,Digital Transformation LLC -AI01518,Machine Learning Researcher,95307,USD,95307,SE,CT,South Korea,M,South Korea,0,"Hadoop, AWS, Scala, TensorFlow",Master,6,Energy,2024-09-22,2024-10-21,1156,8.5,DeepTech Ventures -AI01519,AI Software Engineer,102086,USD,102086,EN,PT,Norway,L,Norway,100,"Mathematics, Git, Java",PhD,0,Education,2024-01-16,2024-02-10,1340,8.2,Autonomous Tech -AI01520,Deep Learning Engineer,97103,AUD,131089,MI,PT,Australia,M,Australia,100,"Statistics, Tableau, Data Visualization",PhD,2,Technology,2024-12-31,2025-01-23,1745,8.3,Future Systems -AI01521,Data Scientist,174876,CHF,157388,SE,PT,Switzerland,M,Switzerland,100,"SQL, Spark, GCP, PyTorch, Azure",Bachelor,7,Retail,2024-05-23,2024-07-07,2247,7.3,Autonomous Tech -AI01522,Machine Learning Researcher,77585,EUR,65947,MI,FT,France,M,France,50,"GCP, Scala, Deep Learning",Associate,2,Gaming,2024-08-13,2024-10-15,2332,5.5,Machine Intelligence Group -AI01523,Robotics Engineer,83753,USD,83753,EN,PT,Denmark,M,Denmark,0,"Tableau, Spark, Python, MLOps",Master,0,Retail,2024-05-26,2024-07-02,1715,5.8,Algorithmic Solutions -AI01524,Deep Learning Engineer,191492,JPY,21064120,EX,FT,Japan,S,Japan,0,"Python, MLOps, Mathematics",Bachelor,11,Healthcare,2024-05-21,2024-07-26,1072,7.3,TechCorp Inc -AI01525,AI Consultant,71219,USD,71219,EN,FL,Israel,M,Israel,0,"PyTorch, SQL, TensorFlow, Scala, Python",PhD,0,Healthcare,2024-04-03,2024-05-25,1209,9.4,TechCorp Inc -AI01526,Computer Vision Engineer,143605,AUD,193867,SE,PT,Australia,L,Australia,50,"Git, TensorFlow, Computer Vision, MLOps, Deep Learning",Bachelor,9,Media,2024-03-27,2024-04-16,1914,6.8,Digital Transformation LLC -AI01527,Data Analyst,261388,USD,261388,EX,FL,Norway,L,Norway,100,"Tableau, Mathematics, Scala, Java, Computer Vision",Bachelor,11,Finance,2024-10-20,2024-12-27,688,10,DeepTech Ventures -AI01528,Data Engineer,115250,GBP,86438,MI,FT,United Kingdom,L,United Kingdom,0,"Java, Tableau, PyTorch, Statistics, Azure",Bachelor,3,Retail,2024-07-01,2024-08-03,1696,8.9,Algorithmic Solutions -AI01529,AI Research Scientist,214259,USD,214259,EX,FT,Ireland,M,Ireland,0,"Tableau, Linux, PyTorch, Docker, Deep Learning",Associate,16,Education,2024-10-07,2024-10-31,609,6.8,Algorithmic Solutions -AI01530,Machine Learning Researcher,50907,USD,50907,SE,FT,China,S,Poland,0,"Statistics, Scala, Deep Learning, NLP",Bachelor,6,Telecommunications,2024-04-23,2024-05-18,1329,6.2,DataVision Ltd -AI01531,NLP Engineer,157211,USD,157211,EX,CT,Israel,S,Israel,0,"Java, GCP, Computer Vision, Git, Hadoop",Master,11,Education,2024-11-10,2024-12-02,1072,8.1,Machine Intelligence Group -AI01532,ML Ops Engineer,110447,EUR,93880,MI,FT,Germany,M,Germany,50,"Java, Python, Git, SQL, Computer Vision",Bachelor,4,Gaming,2024-08-18,2024-10-19,666,6.9,Cognitive Computing -AI01533,ML Ops Engineer,108700,SGD,141310,MI,CT,Singapore,L,Singapore,0,"Git, NLP, Kubernetes, Statistics",Bachelor,4,Education,2024-09-23,2024-10-28,1849,8.3,Digital Transformation LLC -AI01534,Head of AI,67170,EUR,57095,EN,CT,France,L,Australia,100,"AWS, R, SQL, Mathematics",Master,1,Finance,2025-01-07,2025-03-07,832,6.6,Machine Intelligence Group -AI01535,Computer Vision Engineer,45079,USD,45079,SE,FL,China,S,China,0,"Data Visualization, Spark, Linux",Master,6,Energy,2024-09-15,2024-11-17,1064,6,Advanced Robotics -AI01536,AI Architect,97906,AUD,132173,MI,PT,Australia,S,Australia,100,"Linux, SQL, R, Computer Vision, Spark",Bachelor,3,Government,2024-04-28,2024-06-05,2486,5.6,TechCorp Inc -AI01537,Principal Data Scientist,88189,USD,88189,SE,PT,South Korea,S,South Korea,100,"Scala, Hadoop, Tableau, Git",Associate,8,Retail,2025-03-02,2025-04-20,1536,7.3,Machine Intelligence Group -AI01538,Robotics Engineer,103595,CAD,129494,MI,FT,Canada,M,Canada,0,"TensorFlow, Computer Vision, Python, MLOps",Associate,2,Consulting,2024-04-04,2024-05-20,657,6.9,Smart Analytics -AI01539,Data Analyst,113624,USD,113624,SE,CT,Finland,S,Sweden,50,"SQL, GCP, Linux, Tableau, Hadoop",Bachelor,8,Technology,2024-05-24,2024-06-23,2433,7.2,Smart Analytics -AI01540,Autonomous Systems Engineer,134364,SGD,174673,SE,CT,Singapore,M,Singapore,100,"Mathematics, NLP, Docker, Tableau, Git",Master,8,Healthcare,2024-12-22,2025-01-18,1559,7.7,Smart Analytics -AI01541,AI Product Manager,143237,AUD,193370,EX,FT,Australia,S,Australia,100,"Docker, Python, Kubernetes",PhD,12,Real Estate,2025-02-13,2025-03-31,723,6.6,Predictive Systems -AI01542,ML Ops Engineer,61187,CAD,76484,EN,FT,Canada,L,Canada,100,"TensorFlow, Computer Vision, SQL, Scala, Hadoop",Associate,0,Telecommunications,2024-08-21,2024-09-21,1196,7.9,Machine Intelligence Group -AI01543,Autonomous Systems Engineer,64608,USD,64608,EN,FT,South Korea,M,Colombia,50,"GCP, Python, Hadoop, TensorFlow",PhD,0,Government,2025-03-21,2025-05-16,2441,8.1,Smart Analytics -AI01544,Principal Data Scientist,311834,CHF,280651,EX,FT,Switzerland,L,Switzerland,0,"Kubernetes, Hadoop, Python, Data Visualization, Mathematics",Bachelor,14,Transportation,2024-02-29,2024-04-11,1088,7.6,DataVision Ltd -AI01545,Deep Learning Engineer,127894,USD,127894,MI,CT,Denmark,M,Denmark,50,"TensorFlow, Azure, GCP, Java",Master,4,Finance,2024-07-17,2024-09-04,538,8.3,Machine Intelligence Group -AI01546,Data Scientist,75336,GBP,56502,EN,FL,United Kingdom,S,United Kingdom,0,"NLP, Java, MLOps, Kubernetes",Bachelor,0,Telecommunications,2024-09-12,2024-10-21,2367,9.7,AI Innovations -AI01547,Research Scientist,66416,USD,66416,EN,FL,Ireland,S,Ireland,50,"R, SQL, Linux, Mathematics",Associate,1,Telecommunications,2024-04-05,2024-06-09,1592,8.4,AI Innovations -AI01548,AI Architect,49315,USD,49315,EN,FT,Israel,S,Israel,50,"GCP, Git, Data Visualization, Tableau, MLOps",Bachelor,0,Government,2024-11-05,2024-12-08,1778,6.7,Neural Networks Co -AI01549,AI Architect,130837,EUR,111211,SE,FT,Germany,S,Germany,100,"Python, TensorFlow, Deep Learning, Scala, Computer Vision",Master,9,Automotive,2024-02-03,2024-03-18,1032,7.6,DataVision Ltd -AI01550,Head of AI,93179,CAD,116474,SE,PT,Canada,S,Canada,0,"Kubernetes, NLP, MLOps, Spark, Hadoop",Associate,5,Gaming,2024-08-28,2024-10-20,2076,5.8,Future Systems -AI01551,Machine Learning Researcher,88696,EUR,75392,EN,PT,Netherlands,L,Netherlands,50,"Java, Mathematics, GCP",Bachelor,1,Consulting,2025-03-23,2025-04-11,896,5.3,Smart Analytics -AI01552,AI Specialist,125978,GBP,94484,SE,PT,United Kingdom,S,United Kingdom,100,"Azure, TensorFlow, Scala",Bachelor,8,Energy,2025-03-01,2025-05-12,1769,9.5,Predictive Systems -AI01553,Robotics Engineer,73015,EUR,62063,EN,CT,Netherlands,M,Netherlands,50,"Git, GCP, Tableau, MLOps",Bachelor,1,Gaming,2024-02-19,2024-04-26,647,5.7,Machine Intelligence Group -AI01554,Data Analyst,89921,EUR,76433,MI,CT,Austria,S,Austria,100,"R, NLP, Python",Bachelor,2,Finance,2024-12-07,2025-01-20,1779,5.3,Digital Transformation LLC -AI01555,AI Specialist,145615,USD,145615,SE,FL,Denmark,S,Denmark,50,"Deep Learning, MLOps, PyTorch, Git, Statistics",Master,8,Automotive,2024-08-16,2024-10-28,2383,5.3,Quantum Computing Inc -AI01556,Machine Learning Researcher,72798,EUR,61878,EN,PT,France,L,France,0,"Deep Learning, SQL, Tableau, Python",PhD,1,Finance,2024-02-26,2024-04-20,976,8.1,Algorithmic Solutions -AI01557,AI Architect,202771,EUR,172355,EX,FL,France,S,Estonia,0,"Linux, Spark, Computer Vision",Master,19,Gaming,2024-04-30,2024-06-04,1300,8.1,Machine Intelligence Group -AI01558,Computer Vision Engineer,101963,SGD,132552,MI,FL,Singapore,S,Singapore,50,"Data Visualization, Scala, Tableau, Java, Mathematics",PhD,2,Telecommunications,2025-01-27,2025-03-04,2401,8.7,Cloud AI Solutions -AI01559,Principal Data Scientist,131393,EUR,111684,SE,FL,Netherlands,L,Egypt,0,"Python, Data Visualization, TensorFlow",Associate,6,Gaming,2024-06-30,2024-09-04,1399,7.3,Predictive Systems -AI01560,Data Engineer,216001,USD,216001,SE,PT,Denmark,L,Philippines,100,"Java, GCP, Deep Learning, Docker, Spark",Associate,7,Education,2024-11-17,2024-12-05,2098,7.9,Machine Intelligence Group -AI01561,AI Research Scientist,165488,USD,165488,EX,FT,South Korea,S,Egypt,100,"Tableau, Computer Vision, Docker, Python",Associate,17,Finance,2024-01-01,2024-03-12,732,5,Smart Analytics -AI01562,AI Consultant,279330,SGD,363129,EX,FT,Singapore,L,Nigeria,100,"PyTorch, Mathematics, Docker, Statistics, R",Associate,11,Media,2024-08-26,2024-09-25,1724,5.4,Algorithmic Solutions -AI01563,Head of AI,120176,EUR,102150,SE,CT,Austria,M,Austria,0,"Computer Vision, AWS, Data Visualization, Linux, R",PhD,9,Retail,2024-04-16,2024-06-07,922,8.9,Advanced Robotics -AI01564,AI Architect,242800,EUR,206380,EX,FL,Netherlands,M,Netherlands,50,"Docker, Git, Data Visualization, MLOps",PhD,14,Finance,2024-07-09,2024-08-10,1726,8.7,Algorithmic Solutions -AI01565,Autonomous Systems Engineer,135978,AUD,183570,SE,FT,Australia,S,Romania,0,"Azure, GCP, Linux, Python",Associate,7,Gaming,2025-04-19,2025-05-08,1352,9.8,Machine Intelligence Group -AI01566,Computer Vision Engineer,233643,CHF,210279,SE,PT,Switzerland,L,Switzerland,100,"Linux, GCP, TensorFlow, Docker, Python",Master,6,Education,2024-03-30,2024-06-10,1082,9.4,Neural Networks Co -AI01567,AI Architect,63249,USD,63249,MI,FT,South Korea,M,South Korea,100,"Spark, Data Visualization, Kubernetes, Python, Docker",Associate,2,Education,2024-08-12,2024-09-15,839,6,TechCorp Inc -AI01568,Data Engineer,89516,USD,89516,EX,PT,India,L,India,0,"Java, R, MLOps, Spark",Master,11,Real Estate,2024-03-12,2024-05-08,1876,9.7,Algorithmic Solutions -AI01569,Principal Data Scientist,176954,EUR,150411,EX,FT,France,M,Australia,50,"SQL, Python, MLOps",Master,15,Transportation,2024-08-18,2024-09-20,1122,6,Cloud AI Solutions -AI01570,Head of AI,55961,USD,55961,MI,PT,China,L,China,50,"Spark, Kubernetes, MLOps, Azure, Data Visualization",Associate,3,Education,2024-10-01,2024-12-03,1474,8.7,Smart Analytics -AI01571,Head of AI,132864,GBP,99648,SE,FT,United Kingdom,M,United Kingdom,100,"Scala, Python, Tableau",Bachelor,6,Finance,2025-03-18,2025-04-08,616,5.8,DataVision Ltd -AI01572,Research Scientist,104418,AUD,140964,MI,CT,Australia,M,Austria,50,"R, Git, MLOps, Spark",Associate,4,Manufacturing,2025-02-20,2025-04-03,2135,5.3,Algorithmic Solutions -AI01573,Deep Learning Engineer,80490,AUD,108662,EN,FL,Australia,M,South Africa,0,"TensorFlow, Java, Git",Bachelor,0,Healthcare,2024-06-15,2024-07-11,1830,9.8,Cognitive Computing -AI01574,Head of AI,85744,USD,85744,MI,FT,Israel,L,Israel,50,"R, GCP, Mathematics",Bachelor,3,Automotive,2024-12-04,2025-01-09,1123,7.8,DeepTech Ventures -AI01575,Principal Data Scientist,101111,EUR,85944,SE,FL,Austria,S,Netherlands,100,"Docker, Mathematics, Tableau, Linux",Master,9,Education,2025-02-09,2025-02-24,1304,8.8,Future Systems -AI01576,Machine Learning Engineer,195573,CAD,244466,EX,FT,Canada,L,Canada,100,"Mathematics, GCP, Kubernetes",Master,18,Telecommunications,2024-03-07,2024-04-23,1002,6.4,DataVision Ltd -AI01577,Robotics Engineer,136148,AUD,183800,SE,FL,Australia,M,Indonesia,0,"Azure, Java, SQL, Python, Computer Vision",PhD,9,Retail,2024-06-14,2024-07-02,1581,8.4,Quantum Computing Inc -AI01578,AI Architect,108512,SGD,141066,MI,FT,Singapore,L,Denmark,50,"Computer Vision, Linux, Data Visualization, Java, Azure",Master,4,Government,2024-03-23,2024-04-10,2122,9.3,Machine Intelligence Group -AI01579,Data Engineer,216695,EUR,184191,EX,FL,Germany,S,Germany,0,"Java, Tableau, Python, Deep Learning",Master,16,Education,2024-08-11,2024-09-07,646,7,Digital Transformation LLC -AI01580,NLP Engineer,169781,CHF,152803,SE,CT,Switzerland,S,Switzerland,50,"Python, Hadoop, Linux",PhD,5,Telecommunications,2024-08-20,2024-10-18,2253,8.6,Cloud AI Solutions -AI01581,Robotics Engineer,306082,CHF,275474,EX,PT,Switzerland,L,Switzerland,0,"Spark, AWS, Statistics",PhD,19,Telecommunications,2025-03-12,2025-05-16,1909,8.5,AI Innovations -AI01582,AI Research Scientist,82438,CHF,74194,EN,CT,Switzerland,S,Switzerland,0,"PyTorch, Java, MLOps",Associate,0,Finance,2024-10-20,2024-12-26,1139,5.2,DataVision Ltd -AI01583,NLP Engineer,57552,USD,57552,EN,FT,Ireland,M,India,0,"R, SQL, Deep Learning, PyTorch, Git",Associate,0,Finance,2024-03-10,2024-05-05,2293,7.6,Predictive Systems -AI01584,Head of AI,54111,CAD,67639,EN,CT,Canada,M,Canada,50,"Statistics, Spark, TensorFlow, Scala, GCP",PhD,1,Technology,2025-03-11,2025-04-13,1725,9.3,TechCorp Inc -AI01585,AI Product Manager,139157,EUR,118283,SE,PT,Germany,M,Germany,0,"Java, Azure, Python, MLOps",Bachelor,7,Media,2025-03-06,2025-05-13,1081,9.7,Cognitive Computing -AI01586,Deep Learning Engineer,84808,EUR,72087,MI,FT,Austria,M,Austria,100,"Git, Linux, Hadoop, GCP, Python",PhD,4,Telecommunications,2024-04-25,2024-05-18,764,5.7,TechCorp Inc -AI01587,AI Software Engineer,141179,EUR,120002,SE,CT,Austria,M,Austria,100,"Java, Python, TensorFlow",Associate,7,Transportation,2024-04-07,2024-06-03,1342,6.3,Advanced Robotics -AI01588,Computer Vision Engineer,318090,USD,318090,EX,PT,United States,L,United States,0,"PyTorch, MLOps, Hadoop",Bachelor,14,Technology,2024-04-04,2024-04-23,1247,6,DeepTech Ventures -AI01589,Data Analyst,130980,EUR,111333,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, R, Linux",PhD,3,Healthcare,2024-07-04,2024-09-04,1109,10,DataVision Ltd -AI01590,Robotics Engineer,134292,USD,134292,EX,FT,Israel,S,Israel,0,"NLP, Git, Tableau, GCP",Bachelor,13,Government,2024-11-14,2025-01-17,696,8.4,Cognitive Computing -AI01591,AI Architect,137679,AUD,185867,EX,PT,Australia,M,Australia,50,"R, Linux, Python, Deep Learning",Associate,11,Gaming,2024-09-19,2024-10-31,1964,8.3,Autonomous Tech -AI01592,AI Product Manager,179453,EUR,152535,EX,FT,France,M,France,0,"SQL, Tableau, Azure, Kubernetes, Python",Bachelor,12,Technology,2024-02-27,2024-04-12,996,8.9,Digital Transformation LLC -AI01593,ML Ops Engineer,118618,USD,118618,SE,FL,Ireland,M,Ireland,50,"Python, Java, Git, Hadoop, Statistics",Associate,8,Healthcare,2025-03-29,2025-05-21,1265,7.8,Advanced Robotics -AI01594,Data Analyst,154250,USD,154250,SE,PT,Finland,L,Finland,0,"AWS, Mathematics, PyTorch, TensorFlow",Associate,7,Education,2024-11-15,2024-12-14,2495,9,DataVision Ltd -AI01595,Machine Learning Researcher,63563,USD,63563,MI,FT,South Korea,M,Romania,50,"Java, Data Visualization, SQL, MLOps, Python",PhD,4,Manufacturing,2025-03-13,2025-04-22,1537,5.7,Predictive Systems -AI01596,Head of AI,199854,GBP,149891,EX,FT,United Kingdom,S,United Kingdom,100,"NLP, Hadoop, Kubernetes, Docker",Master,18,Consulting,2024-10-21,2024-12-22,660,5.3,Smart Analytics -AI01597,ML Ops Engineer,123361,EUR,104857,SE,FL,Germany,L,Germany,0,"NLP, Spark, Hadoop, Python",Master,6,Media,2024-09-27,2024-10-14,1538,8.9,TechCorp Inc -AI01598,AI Consultant,103643,USD,103643,SE,CT,Finland,S,Portugal,0,"Linux, Azure, Python",Master,6,Manufacturing,2024-12-11,2025-02-19,858,8.8,Cognitive Computing -AI01599,Data Scientist,61632,USD,61632,MI,CT,South Korea,M,United Kingdom,0,"R, Git, Scala",Bachelor,4,Real Estate,2024-01-06,2024-02-16,607,6.5,DataVision Ltd -AI01600,Data Engineer,64782,USD,64782,EN,CT,South Korea,M,South Korea,50,"GCP, Azure, Data Visualization, Git",Master,0,Automotive,2025-02-04,2025-03-03,942,8.1,AI Innovations -AI01601,Machine Learning Engineer,160583,USD,160583,SE,FL,Norway,L,France,100,"Data Visualization, Spark, Kubernetes",Master,7,Healthcare,2024-01-24,2024-03-28,1801,8,Advanced Robotics -AI01602,NLP Engineer,259300,SGD,337090,EX,CT,Singapore,M,Singapore,100,"Spark, GCP, Azure, Python, Tableau",Master,16,Healthcare,2025-03-10,2025-05-12,1482,5.3,DeepTech Ventures -AI01603,AI Architect,99029,EUR,84175,MI,PT,Netherlands,M,Netherlands,100,"Hadoop, Azure, Python, TensorFlow, Git",Master,2,Healthcare,2024-08-18,2024-10-04,1003,9.3,Future Systems -AI01604,Principal Data Scientist,84037,USD,84037,EN,CT,Ireland,L,Ireland,100,"TensorFlow, PyTorch, SQL, Spark, Docker",Associate,1,Energy,2024-11-20,2024-12-31,1267,6.6,Smart Analytics -AI01605,Computer Vision Engineer,70093,USD,70093,MI,FT,South Korea,L,Egypt,0,"R, Azure, PyTorch",PhD,2,Consulting,2024-11-23,2025-01-06,945,9.4,Future Systems -AI01606,Head of AI,133209,EUR,113228,SE,FT,Germany,M,Malaysia,0,"Hadoop, Python, Linux, TensorFlow, Java",PhD,9,Healthcare,2025-02-14,2025-03-15,1859,6.7,Autonomous Tech -AI01607,Head of AI,116248,USD,116248,SE,FL,Sweden,M,Sweden,100,"Python, TensorFlow, PyTorch",Associate,9,Transportation,2024-08-10,2024-10-21,1971,5.7,AI Innovations -AI01608,Machine Learning Researcher,62383,CAD,77979,EN,PT,Canada,M,Canada,100,"Data Visualization, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Media,2024-06-18,2024-08-10,1148,9.2,Quantum Computing Inc -AI01609,AI Consultant,192600,CHF,173340,EX,CT,Switzerland,S,Switzerland,100,"Linux, MLOps, GCP, TensorFlow",Associate,12,Transportation,2024-06-09,2024-08-05,1620,8,Neural Networks Co -AI01610,Research Scientist,91590,CAD,114488,MI,PT,Canada,M,Canada,0,"Statistics, SQL, AWS, Mathematics, Azure",Associate,2,Telecommunications,2024-11-18,2025-01-06,770,7.2,Algorithmic Solutions -AI01611,AI Consultant,102798,USD,102798,SE,FL,South Korea,L,South Korea,50,"Spark, SQL, Statistics",Bachelor,7,Real Estate,2025-03-15,2025-04-07,1954,8.6,AI Innovations -AI01612,AI Architect,103697,EUR,88142,MI,FT,Germany,M,Germany,0,"SQL, Python, Hadoop, Computer Vision, GCP",Associate,2,Media,2024-05-18,2024-07-01,1173,9.2,Quantum Computing Inc -AI01613,Machine Learning Engineer,28499,USD,28499,MI,CT,India,S,Brazil,0,"Tableau, SQL, Scala, AWS, GCP",Master,2,Manufacturing,2024-01-26,2024-03-20,2350,8.9,DeepTech Ventures -AI01614,Research Scientist,69768,USD,69768,MI,PT,South Korea,L,Mexico,0,"Kubernetes, Docker, AWS, SQL, Python",Bachelor,3,Automotive,2024-10-03,2024-11-24,2257,7,Predictive Systems -AI01615,Research Scientist,71036,AUD,95899,MI,FT,Australia,S,Australia,100,"Azure, Scala, MLOps, Computer Vision, Data Visualization",PhD,4,Real Estate,2024-05-08,2024-06-04,1216,7.4,Advanced Robotics -AI01616,Data Scientist,121894,GBP,91421,SE,CT,United Kingdom,S,United Kingdom,50,"Linux, Python, Kubernetes, TensorFlow, Git",Master,7,Transportation,2024-04-12,2024-05-29,1233,5.3,Cognitive Computing -AI01617,AI Software Engineer,60930,EUR,51791,EN,FL,Austria,S,Austria,50,"Tableau, PyTorch, Scala, GCP",Master,0,Consulting,2024-05-14,2024-06-16,1096,9.8,TechCorp Inc -AI01618,Principal Data Scientist,124442,USD,124442,SE,CT,Finland,M,Finland,0,"Computer Vision, Docker, SQL, Mathematics, Hadoop",PhD,7,Consulting,2025-04-02,2025-06-08,970,8.2,Advanced Robotics -AI01619,Computer Vision Engineer,88420,USD,88420,MI,CT,Sweden,L,Sweden,50,"Git, Hadoop, Java",Bachelor,2,Manufacturing,2024-08-11,2024-09-04,2056,5.9,Future Systems -AI01620,AI Consultant,84817,USD,84817,EN,CT,Ireland,L,Ireland,100,"Python, GCP, SQL",Bachelor,0,Telecommunications,2024-12-12,2025-02-01,1659,5.3,Smart Analytics -AI01621,AI Consultant,155811,SGD,202554,SE,CT,Singapore,M,Singapore,0,"Tableau, Git, SQL, Statistics",Master,6,Education,2024-10-09,2024-12-10,1916,5.3,TechCorp Inc -AI01622,AI Product Manager,95395,USD,95395,MI,PT,Israel,M,Japan,0,"TensorFlow, Deep Learning, Python, Computer Vision, PyTorch",Master,3,Media,2024-11-14,2025-01-12,908,8.2,DataVision Ltd -AI01623,NLP Engineer,82987,EUR,70539,MI,FT,Germany,S,Germany,0,"Python, NLP, AWS, Computer Vision, R",Bachelor,2,Real Estate,2024-10-30,2024-11-24,2035,5.8,Cloud AI Solutions -AI01624,Data Scientist,161403,USD,161403,EX,FL,Finland,M,Finland,50,"SQL, Statistics, PyTorch, Deep Learning",PhD,15,Finance,2024-05-16,2024-07-15,1635,9.8,DataVision Ltd -AI01625,Robotics Engineer,151191,USD,151191,SE,FT,Denmark,S,Denmark,0,"NLP, Tableau, Scala, GCP",PhD,8,Energy,2025-04-01,2025-04-24,890,6.7,Digital Transformation LLC -AI01626,Machine Learning Researcher,92075,EUR,78264,SE,CT,France,S,France,100,"GCP, Java, R",Bachelor,6,Government,2024-11-02,2024-12-05,2261,7.7,Cloud AI Solutions -AI01627,Autonomous Systems Engineer,43996,USD,43996,MI,FL,China,S,China,100,"Python, Azure, TensorFlow, Hadoop",Master,2,Manufacturing,2024-02-22,2024-03-16,2422,7.2,DataVision Ltd -AI01628,AI Research Scientist,25803,USD,25803,EN,PT,India,M,India,50,"Kubernetes, MLOps, Azure, Linux, Computer Vision",Master,0,Technology,2024-12-30,2025-03-04,1599,7.1,DataVision Ltd -AI01629,Machine Learning Engineer,99682,USD,99682,EN,FL,United States,L,Ukraine,0,"SQL, Scala, Git",Associate,0,Technology,2025-03-12,2025-04-19,2193,5.3,AI Innovations -AI01630,Autonomous Systems Engineer,108655,USD,108655,EX,PT,China,L,China,0,"PyTorch, Mathematics, Spark, Java, Hadoop",Associate,17,Gaming,2024-05-11,2024-06-25,1410,7.9,Algorithmic Solutions -AI01631,Machine Learning Researcher,79605,AUD,107467,MI,PT,Australia,M,Australia,50,"GCP, Tableau, Data Visualization, MLOps, Python",Master,3,Real Estate,2024-05-29,2024-07-25,789,7,DeepTech Ventures -AI01632,AI Specialist,68143,EUR,57922,EN,PT,Netherlands,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2024-01-25,2024-02-23,1355,5.5,Future Systems -AI01633,ML Ops Engineer,177618,SGD,230903,EX,PT,Singapore,S,Singapore,0,"Hadoop, SQL, NLP",Bachelor,18,Energy,2024-02-08,2024-03-19,957,8.1,Neural Networks Co -AI01634,Robotics Engineer,220052,CAD,275065,EX,CT,Canada,L,Ghana,50,"Hadoop, Scala, Tableau",Master,17,Media,2025-01-02,2025-01-26,1422,9.1,DeepTech Ventures -AI01635,AI Software Engineer,83629,GBP,62722,MI,PT,United Kingdom,M,Denmark,100,"Python, Tableau, Deep Learning, Data Visualization, Hadoop",PhD,2,Gaming,2024-04-12,2024-05-24,2018,6.2,Autonomous Tech -AI01636,AI Software Engineer,162381,EUR,138024,SE,FT,Netherlands,L,Netherlands,0,"Scala, Python, GCP",Bachelor,6,Gaming,2024-09-19,2024-11-27,1315,5.4,DataVision Ltd -AI01637,Machine Learning Researcher,124109,USD,124109,SE,FT,Sweden,M,Sweden,0,"Python, Hadoop, Git, GCP",Bachelor,8,Transportation,2024-01-31,2024-03-22,1835,5.9,Predictive Systems -AI01638,AI Product Manager,59192,AUD,79909,EN,CT,Australia,M,Indonesia,0,"Linux, TensorFlow, PyTorch, Java, AWS",Associate,1,Media,2024-03-28,2024-04-15,1675,6.3,Smart Analytics -AI01639,AI Research Scientist,49329,USD,49329,SE,PT,India,M,India,0,"Hadoop, Tableau, Kubernetes, PyTorch, Computer Vision",Associate,7,Energy,2025-01-25,2025-03-17,1500,5.9,DataVision Ltd -AI01640,Autonomous Systems Engineer,76915,USD,76915,EX,FT,India,M,India,100,"Statistics, Python, TensorFlow, GCP",Associate,13,Government,2024-10-14,2024-12-13,1541,5.4,Quantum Computing Inc -AI01641,AI Product Manager,101027,USD,101027,EX,FT,China,M,China,100,"Java, Deep Learning, Python",Master,11,Media,2024-01-28,2024-03-06,882,8.8,Predictive Systems -AI01642,Machine Learning Engineer,238301,USD,238301,EX,FT,Norway,S,Norway,100,"Linux, SQL, PyTorch, AWS, Hadoop",PhD,13,Transportation,2024-10-08,2024-11-25,2043,5.7,Quantum Computing Inc -AI01643,Data Scientist,143521,USD,143521,SE,PT,Ireland,L,Luxembourg,50,"SQL, Docker, Azure, MLOps",Associate,5,Retail,2024-04-26,2024-05-23,2414,8.2,Neural Networks Co -AI01644,AI Research Scientist,139551,JPY,15350610,SE,FL,Japan,L,Luxembourg,100,"MLOps, TensorFlow, SQL, Linux",Bachelor,7,Education,2025-01-18,2025-03-10,1243,7,AI Innovations -AI01645,Autonomous Systems Engineer,85768,EUR,72903,EN,FL,Austria,L,Austria,50,"Hadoop, Statistics, NLP, Python",Master,1,Manufacturing,2025-04-09,2025-06-11,1439,9,Cloud AI Solutions -AI01646,Data Engineer,252548,USD,252548,EX,FL,United States,L,United States,50,"Kubernetes, Python, AWS, GCP",PhD,13,Consulting,2024-09-12,2024-10-12,2479,6.3,DeepTech Ventures -AI01647,AI Architect,116048,EUR,98641,MI,CT,Austria,L,Austria,0,"SQL, Azure, Computer Vision, Statistics",Bachelor,4,Government,2024-06-11,2024-07-18,526,9.6,Machine Intelligence Group -AI01648,Head of AI,29834,USD,29834,EN,PT,China,L,China,0,"SQL, Docker, NLP",Bachelor,0,Gaming,2024-05-01,2024-05-22,1564,9,DataVision Ltd -AI01649,Machine Learning Engineer,120609,CAD,150761,SE,FT,Canada,S,Canada,0,"Spark, PyTorch, Statistics",Bachelor,5,Energy,2024-06-11,2024-08-09,844,6.4,Algorithmic Solutions -AI01650,Robotics Engineer,79431,EUR,67516,MI,PT,Austria,L,Austria,0,"R, Hadoop, Azure, Java, Docker",Master,2,Real Estate,2024-04-04,2024-05-09,1677,5.6,Algorithmic Solutions -AI01651,Research Scientist,194187,CAD,242734,EX,CT,Canada,S,Canada,100,"Python, Computer Vision, Spark",Master,14,Telecommunications,2024-12-14,2024-12-29,2369,8.9,Machine Intelligence Group -AI01652,Principal Data Scientist,177785,USD,177785,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Python, Scala, Linux",Master,7,Energy,2024-05-16,2024-06-17,1684,9.6,AI Innovations -AI01653,Computer Vision Engineer,231560,USD,231560,EX,CT,Israel,L,Israel,100,"Spark, Git, SQL, TensorFlow, Azure",Associate,14,Media,2024-01-04,2024-02-03,881,7.6,Smart Analytics -AI01654,AI Software Engineer,114280,CHF,102852,MI,FT,Switzerland,M,Switzerland,0,"Statistics, Kubernetes, Tableau, Docker, Scala",PhD,4,Healthcare,2024-08-31,2024-10-05,695,6.9,Predictive Systems -AI01655,Deep Learning Engineer,75014,EUR,63762,EN,PT,Netherlands,S,Indonesia,100,"Python, Tableau, Azure",Bachelor,1,Finance,2024-11-23,2025-01-21,1349,7.1,TechCorp Inc -AI01656,Data Engineer,32244,USD,32244,EN,CT,India,L,India,100,"SQL, Docker, GCP, Computer Vision",Associate,0,Automotive,2024-05-23,2024-07-29,915,6.3,Cognitive Computing -AI01657,Data Engineer,130809,USD,130809,SE,CT,Sweden,L,Sweden,100,"Python, Git, Kubernetes, GCP",PhD,9,Real Estate,2025-04-30,2025-06-29,696,8.1,Advanced Robotics -AI01658,Data Scientist,194628,CAD,243285,EX,CT,Canada,M,Canada,0,"Git, SQL, Data Visualization, PyTorch, Azure",Associate,19,Real Estate,2024-03-03,2024-04-07,1807,8.9,Digital Transformation LLC -AI01659,Deep Learning Engineer,31750,USD,31750,EN,FL,China,M,Italy,100,"PyTorch, SQL, AWS",Bachelor,1,Energy,2024-11-23,2024-12-27,1036,5.4,Predictive Systems -AI01660,Autonomous Systems Engineer,72863,USD,72863,MI,CT,Israel,S,Netherlands,0,"Git, MLOps, Java, Mathematics",Bachelor,2,Healthcare,2024-04-12,2024-06-02,2466,5.9,Smart Analytics -AI01661,AI Architect,158698,EUR,134893,EX,CT,France,M,France,100,"SQL, Kubernetes, R",Bachelor,11,Manufacturing,2025-04-19,2025-06-10,1473,5.6,Neural Networks Co -AI01662,AI Consultant,70435,USD,70435,EN,CT,United States,L,Germany,0,"Computer Vision, Azure, MLOps, NLP, Git",PhD,0,Real Estate,2024-02-10,2024-04-19,1111,8.5,Smart Analytics -AI01663,Robotics Engineer,70871,USD,70871,MI,FT,Israel,M,Israel,100,"Computer Vision, Kubernetes, Git, PyTorch",Bachelor,2,Consulting,2024-10-18,2024-11-07,2450,7.5,Cloud AI Solutions -AI01664,AI Research Scientist,69256,USD,69256,EN,FT,Finland,L,Hungary,50,"Docker, Tableau, Kubernetes",Master,0,Retail,2025-01-01,2025-03-07,1772,8.3,Cloud AI Solutions -AI01665,Computer Vision Engineer,172569,EUR,146684,EX,CT,Germany,M,Germany,100,"Kubernetes, Spark, PyTorch, GCP",Bachelor,14,Consulting,2025-01-08,2025-02-02,2081,6,Predictive Systems -AI01666,Data Engineer,105421,USD,105421,MI,PT,Ireland,M,Netherlands,50,"R, SQL, Statistics, Java, Data Visualization",Master,4,Manufacturing,2024-10-18,2024-12-20,1129,5,Advanced Robotics -AI01667,Research Scientist,280936,USD,280936,EX,PT,Ireland,L,Ireland,0,"Spark, Python, TensorFlow, SQL, Linux",Bachelor,13,Finance,2024-01-27,2024-03-16,2149,7.9,AI Innovations -AI01668,AI Research Scientist,244804,USD,244804,EX,FT,Denmark,S,Denmark,100,"Azure, Computer Vision, TensorFlow, Python, GCP",PhD,12,Real Estate,2025-01-24,2025-03-17,2021,9.3,Advanced Robotics -AI01669,AI Architect,116583,USD,116583,MI,PT,United States,S,Colombia,100,"SQL, Computer Vision, Kubernetes, AWS, R",Bachelor,2,Transportation,2024-01-17,2024-01-31,2075,9.1,Digital Transformation LLC -AI01670,Computer Vision Engineer,44363,USD,44363,SE,CT,India,M,India,50,"Hadoop, Tableau, R, MLOps, AWS",PhD,9,Government,2024-10-25,2024-12-03,1663,6.6,Algorithmic Solutions -AI01671,Robotics Engineer,103234,GBP,77426,MI,FT,United Kingdom,S,Nigeria,50,"GCP, MLOps, Scala",Associate,4,Media,2024-06-25,2024-08-29,1363,8.2,Machine Intelligence Group -AI01672,AI Research Scientist,241862,USD,241862,EX,FL,Norway,M,France,0,"Scala, PyTorch, Docker, Mathematics, SQL",Master,17,Retail,2025-02-21,2025-04-22,1897,5.9,Machine Intelligence Group -AI01673,Data Scientist,61352,USD,61352,EX,PT,India,L,Argentina,100,"Python, SQL, MLOps",Master,19,Consulting,2025-01-31,2025-04-11,901,9.7,DataVision Ltd -AI01674,Principal Data Scientist,247449,USD,247449,EX,FT,Ireland,M,Ireland,50,"SQL, Mathematics, AWS, Linux, R",Bachelor,16,Manufacturing,2025-04-11,2025-05-19,1591,6.1,Smart Analytics -AI01675,NLP Engineer,91517,USD,91517,MI,CT,Denmark,S,Denmark,100,"Linux, PyTorch, Tableau",Bachelor,4,Energy,2025-01-05,2025-01-24,1982,6.5,Predictive Systems -AI01676,Deep Learning Engineer,231797,EUR,197027,EX,PT,Netherlands,L,Israel,100,"SQL, Java, Deep Learning, MLOps",Bachelor,13,Retail,2024-11-02,2024-11-18,1062,7.4,Cloud AI Solutions -AI01677,AI Software Engineer,29053,USD,29053,EN,FT,China,L,China,100,"Scala, GCP, NLP, PyTorch",Associate,1,Finance,2024-05-17,2024-06-15,503,5.3,Smart Analytics -AI01678,Data Scientist,38480,USD,38480,MI,FT,India,L,India,50,"Scala, Spark, PyTorch, AWS",Bachelor,2,Consulting,2025-03-25,2025-05-06,2254,5.6,Autonomous Tech -AI01679,Data Scientist,49357,USD,49357,EN,FT,Finland,S,Finland,0,"Java, Mathematics, Tableau, NLP, Deep Learning",Bachelor,1,Transportation,2024-07-02,2024-07-31,2422,5.9,DeepTech Ventures -AI01680,Data Analyst,100391,CAD,125489,SE,FT,Canada,M,Nigeria,50,"Hadoop, Linux, SQL",Bachelor,9,Government,2024-10-05,2024-12-02,1941,5.7,Algorithmic Solutions -AI01681,ML Ops Engineer,72840,CHF,65556,EN,FL,Switzerland,S,Switzerland,50,"Python, Git, Java, Docker",Associate,0,Gaming,2024-02-28,2024-03-19,2048,5,Autonomous Tech -AI01682,Data Scientist,265397,EUR,225587,EX,FL,Germany,L,Germany,100,"Scala, AWS, NLP, Statistics",Master,16,Retail,2024-07-24,2024-08-21,1192,5.9,Predictive Systems -AI01683,NLP Engineer,92492,AUD,124864,EN,FL,Australia,L,Australia,100,"Tableau, SQL, Git, Python",PhD,0,Consulting,2024-05-26,2024-07-24,1700,9.4,TechCorp Inc -AI01684,AI Specialist,110408,USD,110408,SE,CT,Sweden,S,Sweden,0,"Python, Linux, R, Computer Vision",Associate,7,Technology,2024-09-25,2024-12-01,2267,10,Quantum Computing Inc -AI01685,NLP Engineer,139699,EUR,118744,EX,FT,Germany,M,Ireland,50,"Azure, Deep Learning, Scala, Mathematics",Associate,19,Finance,2024-07-25,2024-08-31,582,9.1,Advanced Robotics -AI01686,ML Ops Engineer,80747,EUR,68635,MI,CT,Netherlands,S,Netherlands,50,"NLP, Data Visualization, Python, TensorFlow, Linux",Master,3,Telecommunications,2024-02-22,2024-03-09,1345,7.1,Cognitive Computing -AI01687,Data Scientist,86520,EUR,73542,MI,FL,Austria,S,Nigeria,100,"Python, Git, TensorFlow",Bachelor,4,Finance,2024-07-08,2024-09-05,1578,6.4,Machine Intelligence Group -AI01688,AI Specialist,55997,USD,55997,EX,CT,India,M,Israel,50,"NLP, Azure, Python",PhD,12,Manufacturing,2025-03-25,2025-05-28,1550,5.4,AI Innovations -AI01689,AI Software Engineer,107119,SGD,139255,MI,PT,Singapore,M,Singapore,100,"Kubernetes, MLOps, Java, TensorFlow",Bachelor,3,Transportation,2024-04-22,2024-06-21,2417,5.3,Advanced Robotics -AI01690,Research Scientist,117336,EUR,99736,SE,FT,Austria,S,Malaysia,0,"NLP, Scala, Python",Bachelor,9,Consulting,2024-08-23,2024-09-10,1052,6.3,DeepTech Ventures -AI01691,Head of AI,164003,EUR,139403,EX,PT,Austria,S,Vietnam,0,"NLP, Java, PyTorch, GCP",PhD,16,Education,2024-03-09,2024-03-25,645,6,TechCorp Inc -AI01692,Computer Vision Engineer,109093,USD,109093,MI,FL,Ireland,L,Ireland,50,"Statistics, Azure, Scala, GCP, NLP",Master,4,Manufacturing,2025-04-26,2025-06-12,2262,8.6,AI Innovations -AI01693,Machine Learning Researcher,60847,USD,60847,EN,FL,Ireland,M,Ireland,50,"Azure, Mathematics, Python",Associate,0,Manufacturing,2024-12-19,2025-02-26,1775,7.8,DeepTech Ventures -AI01694,AI Product Manager,64394,USD,64394,MI,FT,South Korea,S,South Africa,0,"Azure, Deep Learning, GCP, Spark, R",Bachelor,4,Gaming,2024-01-24,2024-02-20,1682,9.2,Digital Transformation LLC -AI01695,Principal Data Scientist,56336,USD,56336,EN,FT,Sweden,M,Sweden,100,"Python, MLOps, Git",Bachelor,1,Transportation,2024-12-15,2025-01-23,1402,9.9,Predictive Systems -AI01696,AI Consultant,151360,JPY,16649600,EX,PT,Japan,M,Japan,50,"Scala, Kubernetes, Computer Vision, NLP, Git",PhD,11,Transportation,2024-05-26,2024-07-29,2089,5.4,Digital Transformation LLC -AI01697,Head of AI,108867,EUR,92537,SE,FL,Netherlands,M,Netherlands,50,"Mathematics, Java, Spark",PhD,7,Automotive,2024-07-15,2024-09-15,1367,6.6,Cognitive Computing -AI01698,AI Consultant,163581,EUR,139044,SE,CT,Germany,L,Germany,50,"GCP, Computer Vision, Hadoop",PhD,8,Automotive,2024-10-15,2024-12-01,1213,8.5,Machine Intelligence Group -AI01699,AI Product Manager,111866,JPY,12305260,MI,FT,Japan,M,Japan,0,"Java, Kubernetes, SQL, Mathematics",Bachelor,2,Media,2024-11-04,2024-12-30,1683,9.3,Cloud AI Solutions -AI01700,NLP Engineer,56511,USD,56511,EN,CT,South Korea,L,Israel,50,"Kubernetes, Java, Deep Learning, Mathematics, Computer Vision",PhD,0,Media,2024-10-29,2024-11-30,2130,7.1,Future Systems -AI01701,NLP Engineer,40401,USD,40401,MI,CT,China,L,China,100,"TensorFlow, SQL, Mathematics, Linux",PhD,4,Healthcare,2024-05-11,2024-06-10,2122,9.1,TechCorp Inc -AI01702,Research Scientist,130250,CHF,117225,MI,FL,Switzerland,L,Hungary,0,"Data Visualization, GCP, Scala, Docker",PhD,2,Media,2024-03-30,2024-05-22,2139,5,Algorithmic Solutions -AI01703,Computer Vision Engineer,41173,USD,41173,MI,CT,China,S,Austria,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2025-04-29,2025-06-23,1174,6.2,Smart Analytics -AI01704,Data Engineer,69187,USD,69187,EN,FL,United States,S,United States,50,"Kubernetes, Spark, Java",Associate,0,Media,2024-01-31,2024-04-04,1954,9.2,Quantum Computing Inc -AI01705,NLP Engineer,80973,USD,80973,EX,FT,India,S,Australia,100,"Linux, Python, Tableau, Kubernetes, SQL",Associate,11,Energy,2024-04-07,2024-05-31,1601,7.7,Quantum Computing Inc -AI01706,AI Software Engineer,117099,USD,117099,SE,PT,Ireland,M,Ireland,50,"Spark, Java, Computer Vision, Tableau",Bachelor,7,Real Estate,2024-10-03,2024-10-20,672,6.3,DeepTech Ventures -AI01707,AI Architect,62738,USD,62738,EN,FL,Finland,S,Canada,0,"Git, SQL, GCP",Associate,1,Consulting,2024-02-06,2024-03-01,1244,9.7,Neural Networks Co -AI01708,AI Product Manager,120017,EUR,102014,MI,FT,Germany,L,Germany,100,"Java, Kubernetes, Deep Learning",Bachelor,4,Education,2025-02-03,2025-03-17,588,8.6,Digital Transformation LLC -AI01709,AI Architect,146456,USD,146456,MI,FL,United States,L,United States,0,"SQL, Spark, Linux",PhD,2,Real Estate,2024-08-20,2024-10-17,1112,5.3,Autonomous Tech -AI01710,Data Engineer,116585,AUD,157390,SE,FL,Australia,M,Australia,0,"Mathematics, Computer Vision, Linux, Kubernetes",Master,8,Energy,2024-02-26,2024-04-21,1405,8.2,DeepTech Ventures -AI01711,AI Architect,48908,EUR,41572,EN,FT,France,M,France,100,"Spark, TensorFlow, Python, NLP, Statistics",Master,1,Healthcare,2024-12-28,2025-03-06,739,7.1,Machine Intelligence Group -AI01712,Head of AI,140368,USD,140368,MI,FT,Norway,M,Norway,0,"Java, Linux, Statistics, GCP",Master,2,Manufacturing,2024-06-25,2024-08-09,1177,8.6,Future Systems -AI01713,Deep Learning Engineer,117338,JPY,12907180,MI,FL,Japan,L,Brazil,100,"PyTorch, SQL, Hadoop, Deep Learning, Kubernetes",Associate,3,Manufacturing,2024-12-07,2025-01-22,1586,6.8,Quantum Computing Inc -AI01714,Head of AI,25199,USD,25199,EN,PT,China,M,Germany,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Media,2024-04-18,2024-06-22,849,9.8,Machine Intelligence Group -AI01715,AI Architect,101321,EUR,86123,MI,FT,France,M,France,50,"Python, Statistics, Tableau",PhD,3,Gaming,2025-03-24,2025-04-20,2449,7.7,Predictive Systems -AI01716,Machine Learning Engineer,86336,USD,86336,MI,FT,Ireland,S,Ghana,0,"Deep Learning, SQL, Data Visualization, PyTorch",Master,4,Retail,2025-03-09,2025-05-21,1028,8.6,TechCorp Inc -AI01717,Machine Learning Researcher,104654,JPY,11511940,MI,FL,Japan,L,Japan,100,"Azure, Deep Learning, R",Master,2,Energy,2024-02-24,2024-04-20,739,8.1,Cognitive Computing -AI01718,AI Specialist,93107,USD,93107,MI,FT,Ireland,L,Mexico,0,"PyTorch, GCP, Tableau",Associate,3,Gaming,2024-03-18,2024-04-05,2334,9.5,Smart Analytics -AI01719,AI Consultant,113304,USD,113304,MI,CT,Norway,S,Norway,0,"SQL, Azure, PyTorch",Bachelor,3,Healthcare,2024-04-24,2024-05-19,517,6.1,Algorithmic Solutions -AI01720,Deep Learning Engineer,159382,USD,159382,EX,CT,Ireland,M,Ireland,100,"Java, Python, Computer Vision, R",Master,12,Transportation,2024-07-03,2024-07-18,617,8.7,Future Systems -AI01721,AI Specialist,112099,USD,112099,SE,FL,South Korea,M,South Korea,50,"Azure, Python, Computer Vision",Bachelor,9,Media,2024-07-03,2024-07-17,1317,8,Advanced Robotics -AI01722,Head of AI,106493,USD,106493,MI,PT,Norway,M,Norway,0,"Linux, Scala, PyTorch, MLOps, Tableau",Master,4,Real Estate,2025-03-27,2025-05-18,1839,7.1,AI Innovations -AI01723,AI Architect,76693,SGD,99701,EN,FT,Singapore,M,Singapore,100,"Mathematics, Statistics, PyTorch",PhD,1,Real Estate,2025-04-14,2025-05-02,740,8.4,Neural Networks Co -AI01724,NLP Engineer,145475,USD,145475,SE,CT,Finland,L,Latvia,100,"Spark, Java, Deep Learning, AWS",Associate,9,Energy,2025-02-11,2025-03-14,1076,8.5,DataVision Ltd -AI01725,Data Analyst,79166,GBP,59375,EN,FT,United Kingdom,L,United Kingdom,50,"Scala, Kubernetes, MLOps, Azure, AWS",PhD,0,Finance,2024-09-24,2024-10-08,1643,9.6,DeepTech Ventures -AI01726,AI Architect,187864,USD,187864,EX,FL,Sweden,M,Sweden,0,"Git, PyTorch, SQL, Scala",Associate,16,Gaming,2024-12-06,2025-01-07,921,6.1,Future Systems -AI01727,AI Consultant,50080,USD,50080,EN,CT,Israel,S,Israel,100,"Deep Learning, Python, Mathematics",Bachelor,1,Technology,2025-01-27,2025-04-06,2110,6.6,Autonomous Tech -AI01728,Autonomous Systems Engineer,103470,JPY,11381700,MI,CT,Japan,L,Japan,100,"Computer Vision, R, Kubernetes, Tableau",Master,2,Technology,2024-11-14,2024-12-09,1694,6.9,Predictive Systems -AI01729,Machine Learning Engineer,84323,USD,84323,MI,FT,Sweden,M,Sweden,50,"Kubernetes, Git, Statistics",Bachelor,3,Real Estate,2024-11-25,2025-01-08,1134,8,DeepTech Ventures -AI01730,Robotics Engineer,71020,CAD,88775,MI,PT,Canada,S,Czech Republic,100,"Java, Tableau, PyTorch, NLP, SQL",Bachelor,3,Manufacturing,2024-02-21,2024-04-23,1253,9.7,Future Systems -AI01731,NLP Engineer,74489,USD,74489,EX,FL,China,M,Austria,50,"Linux, Docker, SQL",PhD,11,Healthcare,2024-06-03,2024-07-24,1437,9.7,TechCorp Inc -AI01732,AI Product Manager,55564,AUD,75011,EN,FT,Australia,M,Australia,50,"SQL, PyTorch, Git, Azure, AWS",Bachelor,0,Transportation,2025-03-22,2025-06-02,2036,6.3,Predictive Systems -AI01733,AI Consultant,84737,USD,84737,EN,CT,United States,S,United States,0,"Spark, Data Visualization, Computer Vision",Bachelor,1,Telecommunications,2025-01-06,2025-02-02,1139,6.8,DeepTech Ventures -AI01734,AI Software Engineer,125029,EUR,106275,SE,FL,France,M,France,50,"SQL, Azure, Java, Spark, AWS",Master,5,Healthcare,2025-01-19,2025-03-23,1740,5.6,DataVision Ltd -AI01735,Robotics Engineer,93053,EUR,79095,MI,FL,France,S,France,0,"Spark, R, Data Visualization",PhD,3,Education,2025-01-06,2025-02-15,629,5.1,DeepTech Ventures -AI01736,AI Architect,116161,USD,116161,MI,FT,United States,S,United States,50,"SQL, PyTorch, GCP, Linux",PhD,2,Technology,2025-01-07,2025-02-22,1201,7.2,Predictive Systems -AI01737,AI Software Engineer,96819,USD,96819,MI,FT,United States,S,United States,0,"Spark, Python, Tableau, Kubernetes",PhD,3,Finance,2024-11-18,2025-01-12,1105,7.7,TechCorp Inc -AI01738,Computer Vision Engineer,21074,USD,21074,EN,CT,India,M,India,50,"Git, Azure, Data Visualization",Associate,0,Retail,2024-06-29,2024-07-30,1551,7.4,Algorithmic Solutions -AI01739,Data Scientist,131324,USD,131324,MI,PT,Denmark,M,Denmark,100,"Tableau, Deep Learning, GCP, Java",PhD,2,Transportation,2024-12-14,2025-02-16,2003,6,Digital Transformation LLC -AI01740,Principal Data Scientist,58660,USD,58660,EN,CT,Finland,M,Finland,50,"Hadoop, Spark, Tableau",PhD,1,Finance,2024-10-09,2024-11-22,1205,9.9,Digital Transformation LLC -AI01741,Machine Learning Engineer,132875,EUR,112944,MI,PT,Netherlands,L,Malaysia,50,"GCP, Python, Mathematics, Linux, SQL",PhD,4,Consulting,2024-08-28,2024-10-31,1392,6.1,Quantum Computing Inc -AI01742,Computer Vision Engineer,74316,USD,74316,MI,FT,South Korea,S,South Korea,50,"TensorFlow, GCP, Azure",Bachelor,3,Energy,2024-11-17,2025-01-04,1075,9.4,Advanced Robotics -AI01743,Data Engineer,65320,EUR,55522,EN,FT,France,S,France,100,"Java, Python, Git",Bachelor,1,Media,2024-04-01,2024-05-18,915,8.7,Digital Transformation LLC -AI01744,Autonomous Systems Engineer,128941,USD,128941,SE,CT,Finland,L,Finland,50,"TensorFlow, Spark, PyTorch",Master,7,Manufacturing,2025-01-26,2025-03-07,2349,7.6,Cognitive Computing -AI01745,Principal Data Scientist,42409,USD,42409,MI,CT,China,M,South Korea,100,"PyTorch, TensorFlow, NLP",Bachelor,2,Media,2024-04-16,2024-05-09,2188,9.6,Algorithmic Solutions -AI01746,NLP Engineer,76564,GBP,57423,EN,FT,United Kingdom,S,United Kingdom,100,"Deep Learning, Azure, Scala",PhD,0,Government,2024-03-03,2024-04-13,1639,9.4,Neural Networks Co -AI01747,NLP Engineer,289808,EUR,246337,EX,FT,Netherlands,L,Luxembourg,100,"Statistics, TensorFlow, PyTorch, Data Visualization, Hadoop",PhD,17,Automotive,2025-03-17,2025-04-28,2224,6.3,Neural Networks Co -AI01748,Data Analyst,62042,CAD,77553,EN,FL,Canada,M,Kenya,50,"Python, Azure, Tableau",Bachelor,1,Government,2024-02-15,2024-03-21,1611,6.1,TechCorp Inc -AI01749,AI Product Manager,98976,EUR,84130,MI,FT,Netherlands,M,Netherlands,100,"Statistics, Python, Mathematics, Linux, Hadoop",PhD,4,Manufacturing,2024-11-08,2024-12-24,2377,6.9,Autonomous Tech -AI01750,AI Architect,122469,USD,122469,EX,FL,South Korea,M,South Korea,50,"Linux, Scala, Java, Deep Learning, Spark",Bachelor,19,Education,2024-09-05,2024-10-17,1048,7.1,Future Systems -AI01751,NLP Engineer,187847,USD,187847,EX,FT,Ireland,M,Ireland,50,"PyTorch, TensorFlow, SQL, R",PhD,16,Transportation,2024-01-27,2024-02-16,2318,10,DeepTech Ventures -AI01752,AI Consultant,157782,JPY,17356020,EX,FT,Japan,S,Japan,0,"Spark, NLP, GCP",Master,13,Transportation,2024-11-25,2025-01-06,670,9.1,Cognitive Computing -AI01753,Research Scientist,128659,USD,128659,MI,FL,Denmark,S,Mexico,50,"Python, Linux, Scala, TensorFlow",Bachelor,2,Gaming,2024-03-04,2024-05-03,1580,5.7,Algorithmic Solutions -AI01754,AI Architect,61499,USD,61499,EN,FL,Finland,M,Ukraine,100,"Scala, Data Visualization, SQL, Tableau, MLOps",PhD,0,Government,2024-08-12,2024-10-13,1241,6.6,Neural Networks Co -AI01755,Deep Learning Engineer,66190,USD,66190,EN,FL,Ireland,L,Ireland,50,"Computer Vision, Git, Tableau, Linux, Python",PhD,1,Telecommunications,2024-10-18,2024-11-22,642,9.5,Digital Transformation LLC -AI01756,Machine Learning Engineer,29153,USD,29153,EN,FL,China,M,China,0,"Hadoop, Linux, Deep Learning, Mathematics, Git",PhD,0,Media,2024-01-16,2024-02-14,1718,9.1,Predictive Systems -AI01757,Deep Learning Engineer,64431,JPY,7087410,EN,FT,Japan,S,Japan,0,"Java, Tableau, MLOps",Master,1,Gaming,2024-03-06,2024-04-13,1972,9.2,Machine Intelligence Group -AI01758,Data Analyst,330366,USD,330366,EX,FL,Denmark,L,Denmark,0,"NLP, SQL, Tableau, Docker",Bachelor,17,Gaming,2024-03-14,2024-04-20,736,7.9,DataVision Ltd -AI01759,Machine Learning Engineer,128575,USD,128575,MI,PT,United States,M,United States,0,"Linux, Kubernetes, Spark",Bachelor,3,Automotive,2025-04-26,2025-05-21,518,9.4,Cloud AI Solutions -AI01760,AI Software Engineer,150066,GBP,112550,SE,PT,United Kingdom,M,United Kingdom,100,"Java, NLP, AWS, R, SQL",Associate,9,Media,2024-04-28,2024-07-10,1608,9.3,Predictive Systems -AI01761,Data Engineer,147214,SGD,191378,SE,CT,Singapore,L,Singapore,0,"Azure, Tableau, Scala, NLP, SQL",Associate,6,Gaming,2024-06-12,2024-07-31,1222,7.4,Cognitive Computing -AI01762,Computer Vision Engineer,35538,USD,35538,EN,FT,China,M,New Zealand,100,"AWS, Git, PyTorch, Java",Bachelor,0,Consulting,2024-11-03,2024-11-17,1062,9.5,DeepTech Ventures -AI01763,ML Ops Engineer,131200,EUR,111520,SE,FL,Germany,S,Germany,100,"GCP, Scala, NLP, Computer Vision, AWS",PhD,7,Government,2024-10-23,2024-12-30,1286,6.9,DeepTech Ventures -AI01764,Computer Vision Engineer,65465,USD,65465,EN,FT,South Korea,M,Switzerland,100,"Java, Linux, Scala",Associate,1,Consulting,2024-08-08,2024-09-29,728,8.9,TechCorp Inc -AI01765,AI Software Engineer,239103,GBP,179327,EX,CT,United Kingdom,M,United Kingdom,50,"R, Python, TensorFlow, Computer Vision",Associate,12,Automotive,2024-07-04,2024-07-25,1486,9.7,AI Innovations -AI01766,Robotics Engineer,107447,EUR,91330,SE,FL,Germany,S,France,50,"Data Visualization, Spark, R",Master,8,Technology,2024-07-13,2024-07-31,633,8.4,AI Innovations -AI01767,Machine Learning Researcher,56221,USD,56221,MI,FT,South Korea,S,South Korea,100,"PyTorch, SQL, MLOps, Data Visualization, Statistics",Master,4,Real Estate,2024-10-18,2024-12-08,575,8.1,Predictive Systems -AI01768,Deep Learning Engineer,123027,AUD,166086,MI,CT,Australia,L,Australia,0,"Linux, Kubernetes, Tableau, Java",Associate,4,Technology,2024-07-27,2024-09-03,1040,5.2,Predictive Systems -AI01769,AI Research Scientist,117390,JPY,12912900,SE,FT,Japan,S,Japan,50,"Java, SQL, Scala, Kubernetes",PhD,5,Education,2024-10-23,2024-12-21,2199,7.3,Algorithmic Solutions -AI01770,Autonomous Systems Engineer,89124,EUR,75755,MI,PT,France,L,France,100,"Kubernetes, TensorFlow, AWS, Linux, Azure",Master,4,Finance,2025-04-15,2025-05-02,1308,9.1,DataVision Ltd -AI01771,AI Product Manager,251508,EUR,213782,EX,PT,France,L,France,0,"GCP, R, Tableau, Spark",Associate,15,Finance,2024-09-05,2024-11-07,2493,9,Future Systems -AI01772,AI Software Engineer,100520,USD,100520,EX,CT,China,L,China,100,"Azure, Python, SQL",Associate,15,Media,2024-07-27,2024-09-29,1705,6.9,DeepTech Ventures -AI01773,Data Scientist,348466,CHF,313619,EX,PT,Switzerland,M,Switzerland,100,"GCP, SQL, Tableau, Data Visualization",Bachelor,13,Energy,2024-02-28,2024-04-19,1875,7.4,TechCorp Inc -AI01774,Autonomous Systems Engineer,132749,USD,132749,SE,FL,Norway,S,Latvia,0,"Linux, Computer Vision, SQL",Bachelor,5,Government,2024-03-22,2024-05-26,2272,7.5,Digital Transformation LLC -AI01775,AI Specialist,63454,USD,63454,EN,FT,Sweden,M,Colombia,50,"Azure, NLP, Deep Learning",PhD,1,Government,2024-12-30,2025-01-26,1742,5.1,Advanced Robotics -AI01776,ML Ops Engineer,102787,EUR,87369,SE,CT,Germany,M,Egypt,100,"Data Visualization, SQL, Python, Computer Vision",Bachelor,5,Transportation,2024-08-21,2024-10-01,1436,7.7,AI Innovations -AI01777,NLP Engineer,19313,USD,19313,EN,FT,India,M,Australia,50,"Python, MLOps, Linux, Deep Learning, Computer Vision",Associate,1,Finance,2024-10-07,2024-10-30,1240,9.1,DeepTech Ventures -AI01778,Machine Learning Researcher,129410,USD,129410,SE,FL,Ireland,M,Ireland,100,"Hadoop, Spark, Python, Kubernetes",Master,5,Automotive,2025-04-23,2025-07-04,1559,6.1,DataVision Ltd -AI01779,NLP Engineer,172013,JPY,18921430,EX,FT,Japan,L,Japan,0,"TensorFlow, Tableau, Azure",Master,11,Manufacturing,2025-01-13,2025-02-08,597,8.1,Machine Intelligence Group -AI01780,Autonomous Systems Engineer,158074,USD,158074,EX,CT,South Korea,S,Estonia,50,"SQL, PyTorch, Deep Learning, Tableau",PhD,14,Government,2024-03-08,2024-04-08,2054,9.4,Smart Analytics -AI01781,Data Engineer,70476,SGD,91619,MI,FL,Singapore,S,Poland,50,"AWS, Deep Learning, Python, SQL",Associate,4,Telecommunications,2024-12-20,2025-01-07,2322,6.3,TechCorp Inc -AI01782,Principal Data Scientist,90948,USD,90948,MI,CT,Israel,L,Canada,100,"Linux, GCP, Tableau, Deep Learning",Master,3,Manufacturing,2024-10-25,2024-12-10,1802,5.7,Quantum Computing Inc -AI01783,Machine Learning Researcher,238184,EUR,202456,EX,CT,Netherlands,M,Romania,50,"Python, Java, GCP, TensorFlow",Bachelor,10,Technology,2024-07-08,2024-07-25,715,6,Machine Intelligence Group -AI01784,Computer Vision Engineer,142525,USD,142525,EX,CT,Finland,M,Finland,0,"PyTorch, Kubernetes, NLP, Java",Bachelor,14,Gaming,2024-03-08,2024-04-04,647,6.7,DeepTech Ventures -AI01785,Deep Learning Engineer,210001,EUR,178501,EX,FL,Netherlands,S,Romania,50,"Python, Spark, NLP, Mathematics, Deep Learning",Bachelor,12,Consulting,2024-01-20,2024-03-21,1318,6.8,Cloud AI Solutions -AI01786,Data Analyst,124024,USD,124024,MI,FL,Denmark,L,Indonesia,0,"Spark, Python, Hadoop",Master,4,Manufacturing,2024-07-27,2024-08-24,973,6,Advanced Robotics -AI01787,AI Product Manager,269130,USD,269130,EX,PT,Denmark,M,Denmark,0,"Spark, Tableau, GCP",Associate,17,Manufacturing,2025-04-28,2025-07-10,1322,6.4,Autonomous Tech -AI01788,AI Specialist,44705,USD,44705,SE,CT,India,M,China,100,"Hadoop, Statistics, Scala, Mathematics, Kubernetes",Bachelor,8,Energy,2024-06-02,2024-07-04,1945,9.4,Digital Transformation LLC -AI01789,Data Analyst,79352,EUR,67449,EN,PT,Netherlands,M,Netherlands,100,"MLOps, Java, Python",Bachelor,0,Finance,2025-03-19,2025-05-10,2050,9.5,Cloud AI Solutions -AI01790,AI Consultant,143377,JPY,15771470,SE,FL,Japan,M,Japan,50,"TensorFlow, Computer Vision, MLOps, Data Visualization, Python",PhD,7,Real Estate,2024-01-27,2024-02-19,786,5.3,Machine Intelligence Group -AI01791,Machine Learning Engineer,40231,USD,40231,MI,FL,China,M,Malaysia,100,"Tableau, TensorFlow, Scala, Python, Mathematics",Bachelor,4,Retail,2024-01-27,2024-02-12,967,7.5,Advanced Robotics -AI01792,Robotics Engineer,79846,GBP,59885,MI,PT,United Kingdom,M,Ukraine,50,"PyTorch, Kubernetes, Computer Vision, GCP, Linux",PhD,2,Energy,2024-05-28,2024-07-03,668,5.9,Advanced Robotics -AI01793,Research Scientist,138782,USD,138782,EX,FL,Ireland,S,Malaysia,0,"Azure, Spark, R, Statistics, SQL",PhD,12,Manufacturing,2025-01-29,2025-03-13,1957,9.3,DeepTech Ventures -AI01794,ML Ops Engineer,199769,EUR,169804,EX,CT,Austria,S,Portugal,0,"AWS, Python, PyTorch",Associate,18,Transportation,2024-06-13,2024-08-19,580,7.9,Machine Intelligence Group -AI01795,AI Research Scientist,305289,USD,305289,EX,FL,Denmark,L,France,100,"Docker, MLOps, Data Visualization",Associate,17,Technology,2025-04-11,2025-06-08,1208,9.1,Algorithmic Solutions -AI01796,AI Product Manager,230691,EUR,196087,EX,FT,Austria,M,Estonia,0,"Git, Python, Linux, Kubernetes, AWS",Master,17,Consulting,2025-02-22,2025-03-10,1625,8.6,Future Systems -AI01797,AI Product Manager,238615,JPY,26247650,EX,CT,Japan,L,Austria,0,"Kubernetes, Git, Java, GCP, SQL",Bachelor,19,Manufacturing,2024-07-04,2024-08-11,1578,8.1,Neural Networks Co -AI01798,Machine Learning Engineer,98044,USD,98044,SE,FT,Sweden,S,Sweden,100,"Scala, R, TensorFlow",Associate,7,Telecommunications,2024-02-06,2024-03-31,1120,5.1,Cloud AI Solutions -AI01799,AI Research Scientist,69231,AUD,93462,MI,PT,Australia,S,Australia,100,"Scala, Java, R, Deep Learning, SQL",Associate,3,Gaming,2024-08-19,2024-10-02,2261,9.7,Machine Intelligence Group -AI01800,NLP Engineer,233794,AUD,315622,EX,FT,Australia,L,Australia,50,"Azure, Spark, SQL, Mathematics",Master,19,Transportation,2024-01-14,2024-02-18,902,6.8,Neural Networks Co -AI01801,Computer Vision Engineer,145411,EUR,123599,SE,FT,Netherlands,S,Netherlands,50,"TensorFlow, SQL, Deep Learning, R",PhD,8,Manufacturing,2025-03-20,2025-05-19,1854,6.4,Advanced Robotics -AI01802,ML Ops Engineer,119952,USD,119952,SE,FT,United States,S,Russia,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,9,Finance,2024-10-14,2024-11-06,1828,8.2,Neural Networks Co -AI01803,AI Architect,152045,USD,152045,EX,PT,United States,S,United States,50,"Mathematics, Docker, Tableau",Associate,17,Retail,2024-10-22,2024-12-23,2178,7.6,Predictive Systems -AI01804,AI Software Engineer,60657,USD,60657,SE,FT,China,L,China,0,"Java, Data Visualization, Git, Statistics",Master,8,Government,2025-02-06,2025-03-10,2006,5.1,DeepTech Ventures -AI01805,AI Specialist,157794,USD,157794,EX,PT,South Korea,L,Argentina,50,"Java, Spark, MLOps, Statistics, Python",Associate,13,Media,2025-03-04,2025-04-16,2398,8.4,DataVision Ltd -AI01806,Data Engineer,37836,USD,37836,MI,FT,India,L,Sweden,50,"GCP, Mathematics, Hadoop",Bachelor,2,Finance,2025-04-23,2025-07-05,1374,7.8,Neural Networks Co -AI01807,AI Research Scientist,68797,USD,68797,MI,FL,Israel,S,United Kingdom,100,"TensorFlow, Docker, Git, R",Bachelor,2,Manufacturing,2024-04-02,2024-05-05,2438,5.1,Autonomous Tech -AI01808,Data Scientist,144648,EUR,122951,SE,FL,France,L,France,50,"GCP, Kubernetes, Docker, Spark, Azure",Associate,6,Government,2024-04-22,2024-05-29,1741,5.8,Cloud AI Solutions -AI01809,AI Architect,88724,USD,88724,EN,FT,Ireland,L,Ireland,0,"Scala, Python, Data Visualization",Bachelor,1,Telecommunications,2024-01-26,2024-03-12,2198,9.9,Digital Transformation LLC -AI01810,Data Engineer,186244,CHF,167620,SE,PT,Switzerland,S,Switzerland,50,"Python, Scala, Computer Vision, MLOps, Linux",Master,5,Media,2025-02-14,2025-04-13,2167,5,Neural Networks Co -AI01811,Deep Learning Engineer,88469,USD,88469,SE,FL,South Korea,S,Czech Republic,0,"Spark, R, Scala, Java",Master,6,Education,2025-02-26,2025-04-02,1641,5.2,Machine Intelligence Group -AI01812,Principal Data Scientist,310111,USD,310111,EX,CT,Norway,L,Norway,0,"Statistics, Computer Vision, NLP, Linux",Bachelor,19,Retail,2024-08-08,2024-10-02,1834,6.2,AI Innovations -AI01813,AI Consultant,98560,SGD,128128,SE,CT,Singapore,S,Switzerland,100,"Statistics, MLOps, Mathematics, GCP",PhD,5,Education,2024-11-25,2024-12-09,1838,9.6,AI Innovations -AI01814,AI Specialist,159392,USD,159392,SE,FT,Norway,M,Poland,0,"Java, R, PyTorch",Bachelor,6,Media,2024-10-13,2024-11-27,1842,8,Autonomous Tech -AI01815,Data Engineer,109927,USD,109927,MI,FT,Norway,S,Norway,0,"PyTorch, Kubernetes, TensorFlow, Git",Associate,2,Manufacturing,2025-03-20,2025-05-04,1979,5,Autonomous Tech -AI01816,AI Consultant,135881,EUR,115499,SE,PT,Germany,S,Germany,100,"PyTorch, SQL, NLP",Bachelor,9,Transportation,2025-03-17,2025-04-30,1232,8.4,TechCorp Inc -AI01817,Data Engineer,170048,USD,170048,EX,CT,United States,S,Israel,100,"Statistics, Linux, Tableau, R",PhD,16,Automotive,2024-02-20,2024-03-28,1561,9.8,Machine Intelligence Group -AI01818,Computer Vision Engineer,86374,USD,86374,EX,CT,India,M,India,50,"TensorFlow, Statistics, Scala, Python",PhD,12,Healthcare,2025-01-01,2025-02-09,1201,9.7,Advanced Robotics -AI01819,Computer Vision Engineer,79277,CAD,99096,MI,FT,Canada,S,Canada,100,"PyTorch, R, GCP, Java, Linux",Master,2,Real Estate,2024-05-10,2024-06-02,1121,9.6,AI Innovations -AI01820,Data Scientist,73902,USD,73902,MI,FT,Finland,S,Turkey,100,"Deep Learning, Scala, TensorFlow, MLOps",Master,2,Gaming,2024-02-03,2024-04-03,1351,9,Cognitive Computing -AI01821,Principal Data Scientist,61896,USD,61896,EN,FL,Ireland,M,Ghana,0,"Kubernetes, Azure, SQL, R, Docker",Associate,1,Automotive,2024-01-13,2024-02-12,1699,5.2,DeepTech Ventures -AI01822,AI Product Manager,57201,CAD,71501,EN,PT,Canada,L,Canada,100,"Linux, Tableau, MLOps, Azure",Bachelor,1,Healthcare,2024-12-08,2025-01-30,1408,6.3,AI Innovations -AI01823,Principal Data Scientist,72205,USD,72205,EN,CT,Sweden,M,Brazil,100,"Tableau, Docker, Spark, Kubernetes",Bachelor,0,Transportation,2024-03-31,2024-05-22,943,9.2,Quantum Computing Inc -AI01824,AI Specialist,45721,USD,45721,EN,FL,Israel,S,Singapore,0,"Azure, AWS, Docker",Master,1,Retail,2024-01-16,2024-02-09,2151,7.9,Quantum Computing Inc -AI01825,AI Research Scientist,76605,USD,76605,EN,CT,Denmark,M,Denmark,100,"Spark, Java, Deep Learning, Kubernetes, AWS",Master,1,Healthcare,2024-12-31,2025-03-06,1455,9.9,TechCorp Inc -AI01826,Data Engineer,90927,EUR,77288,MI,FL,Netherlands,L,Netherlands,0,"R, Git, Deep Learning",PhD,2,Automotive,2024-03-05,2024-04-25,777,6.5,Digital Transformation LLC -AI01827,ML Ops Engineer,129674,CAD,162093,SE,CT,Canada,L,Canada,50,"MLOps, Python, NLP, Linux, Hadoop",Master,5,Energy,2025-02-14,2025-04-20,1628,9.7,Smart Analytics -AI01828,Autonomous Systems Engineer,79647,USD,79647,EN,CT,Israel,L,Brazil,100,"Azure, Tableau, Spark",PhD,0,Automotive,2024-06-28,2024-09-03,1836,5.4,DeepTech Ventures -AI01829,Autonomous Systems Engineer,143268,USD,143268,SE,CT,United States,L,United States,100,"Scala, Docker, SQL, Git, MLOps",Bachelor,6,Finance,2024-04-22,2024-06-02,2000,7.5,Neural Networks Co -AI01830,Principal Data Scientist,55944,USD,55944,EN,CT,United States,S,United States,0,"Python, Scala, GCP",Master,1,Consulting,2024-04-21,2024-06-22,2218,8.8,Cloud AI Solutions -AI01831,Head of AI,147714,USD,147714,SE,PT,Denmark,M,Denmark,50,"R, Hadoop, Scala",PhD,7,Gaming,2024-03-05,2024-03-23,1834,5.2,Neural Networks Co -AI01832,AI Product Manager,62923,GBP,47192,EN,FL,United Kingdom,L,United Kingdom,100,"SQL, Statistics, MLOps",Master,0,Automotive,2024-05-17,2024-06-02,2457,5.2,Predictive Systems -AI01833,Deep Learning Engineer,195780,USD,195780,EX,FT,Denmark,S,Japan,100,"Java, PyTorch, Spark",PhD,13,Automotive,2024-04-24,2024-06-03,943,6.5,Machine Intelligence Group -AI01834,Data Analyst,127106,USD,127106,SE,CT,United States,S,Estonia,50,"Python, R, NLP, MLOps, Java",Bachelor,8,Automotive,2025-04-12,2025-06-06,935,5.4,Advanced Robotics -AI01835,Deep Learning Engineer,57038,USD,57038,EN,FT,South Korea,L,South Korea,100,"Data Visualization, R, Hadoop, PyTorch",Master,1,Media,2024-01-06,2024-02-01,2304,5.1,Predictive Systems -AI01836,AI Software Engineer,130998,USD,130998,SE,CT,South Korea,L,South Korea,100,"Data Visualization, PyTorch, Tableau, Git",Bachelor,8,Real Estate,2024-08-01,2024-09-15,1062,5.7,DeepTech Ventures -AI01837,Autonomous Systems Engineer,66589,EUR,56601,EN,FT,Austria,S,Austria,50,"Azure, NLP, GCP, PyTorch",Associate,1,Transportation,2024-11-03,2025-01-07,2290,5.9,AI Innovations -AI01838,Computer Vision Engineer,194996,EUR,165747,EX,CT,Netherlands,L,Malaysia,100,"Data Visualization, Docker, Git, PyTorch, Java",Associate,12,Gaming,2024-10-23,2024-12-10,1664,9.5,Cognitive Computing -AI01839,Data Engineer,152454,EUR,129586,SE,FT,Austria,L,Finland,0,"Statistics, Docker, Hadoop, R",Master,7,Real Estate,2024-08-03,2024-09-01,1068,8.1,DeepTech Ventures -AI01840,Data Analyst,72614,EUR,61722,EN,CT,Germany,S,Germany,50,"Tableau, GCP, MLOps, PyTorch, Git",Associate,0,Real Estate,2024-05-24,2024-07-09,1330,6.5,Predictive Systems -AI01841,Machine Learning Researcher,69406,EUR,58995,EN,CT,Netherlands,L,Netherlands,50,"Hadoop, PyTorch, Data Visualization, TensorFlow, Scala",Associate,1,Education,2024-08-26,2024-09-24,1163,6,Future Systems -AI01842,Machine Learning Engineer,109931,CHF,98938,MI,FL,Switzerland,S,Mexico,50,"TensorFlow, Git, Computer Vision",Master,4,Technology,2025-03-12,2025-05-04,1832,7.5,Future Systems -AI01843,AI Software Engineer,37793,USD,37793,EN,CT,China,M,China,50,"Python, TensorFlow, MLOps, Statistics, Scala",Bachelor,1,Retail,2024-02-05,2024-02-27,2034,8.8,DataVision Ltd -AI01844,Autonomous Systems Engineer,273120,USD,273120,EX,FL,Ireland,L,Ireland,100,"Mathematics, Linux, TensorFlow",Bachelor,15,Retail,2025-04-16,2025-06-27,910,8,Neural Networks Co -AI01845,ML Ops Engineer,105016,CHF,94514,MI,CT,Switzerland,M,Switzerland,100,"Scala, Mathematics, SQL",Master,3,Retail,2025-02-17,2025-04-13,1877,6.2,Cognitive Computing -AI01846,Machine Learning Engineer,231563,CAD,289454,EX,CT,Canada,M,Canada,0,"PyTorch, Hadoop, Kubernetes",Bachelor,10,Education,2024-05-05,2024-06-11,1289,7.7,Neural Networks Co -AI01847,NLP Engineer,120136,USD,120136,SE,CT,Finland,M,Finland,50,"Hadoop, Docker, SQL, TensorFlow, Tableau",Associate,5,Real Estate,2024-07-20,2024-09-19,1156,9.1,Quantum Computing Inc -AI01848,Robotics Engineer,25404,USD,25404,EN,FT,India,L,India,100,"Python, Azure, TensorFlow, GCP",Associate,0,Retail,2024-03-27,2024-04-13,650,8.1,Digital Transformation LLC -AI01849,Data Analyst,58557,JPY,6441270,EN,PT,Japan,M,Japan,100,"R, Docker, Computer Vision, Deep Learning, Hadoop",Associate,1,Government,2025-01-26,2025-02-21,1676,6.7,Predictive Systems -AI01850,AI Software Engineer,78957,EUR,67113,EN,PT,Netherlands,L,Netherlands,100,"Kubernetes, Linux, Java",Master,1,Telecommunications,2024-02-26,2024-04-12,540,8.2,Neural Networks Co -AI01851,NLP Engineer,22675,USD,22675,EN,FL,India,L,India,50,"GCP, R, Data Visualization",PhD,0,Transportation,2024-01-15,2024-03-27,2064,8.5,DataVision Ltd -AI01852,NLP Engineer,147152,USD,147152,SE,FT,Norway,S,Norway,0,"Scala, SQL, PyTorch, Computer Vision, Deep Learning",PhD,9,Finance,2024-10-11,2024-12-08,660,6.2,Cognitive Computing -AI01853,AI Architect,103466,EUR,87946,SE,FL,Austria,M,Austria,100,"Hadoop, Spark, PyTorch",Bachelor,9,Technology,2024-11-28,2024-12-31,1886,6.3,Machine Intelligence Group -AI01854,Machine Learning Researcher,78287,USD,78287,EN,FL,Ireland,M,Ireland,0,"Spark, AWS, Hadoop, Java",PhD,1,Real Estate,2025-02-21,2025-05-04,2397,9.4,Autonomous Tech -AI01855,AI Consultant,142221,EUR,120888,SE,CT,Germany,M,Germany,50,"Git, Kubernetes, Python, TensorFlow, Hadoop",Associate,9,Gaming,2024-07-21,2024-09-26,1266,9.3,Future Systems -AI01856,Machine Learning Engineer,82950,USD,82950,EN,FT,Norway,L,Germany,50,"Kubernetes, Data Visualization, SQL, Mathematics, GCP",Master,0,Gaming,2024-07-21,2024-08-24,800,6.1,Cognitive Computing -AI01857,AI Product Manager,124220,USD,124220,MI,CT,Ireland,L,Ireland,0,"Linux, Computer Vision, Tableau, Kubernetes",Associate,3,Government,2024-08-16,2024-10-11,2005,9.7,Cloud AI Solutions -AI01858,NLP Engineer,78087,CAD,97609,EN,FT,Canada,L,Belgium,50,"MLOps, R, Computer Vision",Bachelor,1,Technology,2024-02-09,2024-03-26,760,9.2,AI Innovations -AI01859,Machine Learning Researcher,50319,GBP,37739,EN,FT,United Kingdom,S,United Kingdom,50,"Deep Learning, MLOps, Java, Git",Bachelor,0,Government,2024-03-29,2024-05-17,2216,10,Smart Analytics -AI01860,Data Analyst,82880,EUR,70448,MI,PT,Netherlands,S,Turkey,0,"TensorFlow, Python, Spark, MLOps",Bachelor,3,Education,2024-05-31,2024-07-19,1846,7.1,Algorithmic Solutions -AI01861,AI Specialist,119491,USD,119491,MI,FT,Ireland,L,Ireland,50,"R, AWS, Spark, Linux, Computer Vision",Master,3,Automotive,2024-04-30,2024-06-27,1982,7.5,Future Systems -AI01862,AI Specialist,202791,USD,202791,SE,FT,United States,L,United States,0,"Kubernetes, Tableau, GCP",Bachelor,8,Technology,2025-02-27,2025-05-03,1627,5.7,DeepTech Ventures -AI01863,Autonomous Systems Engineer,203607,EUR,173066,EX,FL,France,M,Czech Republic,0,"Linux, Data Visualization, NLP",Bachelor,13,Automotive,2024-06-13,2024-08-25,615,8.8,AI Innovations -AI01864,ML Ops Engineer,76776,SGD,99809,EN,FT,Singapore,L,Singapore,0,"Computer Vision, R, Tableau, Linux",PhD,1,Gaming,2024-09-02,2024-10-02,2193,6.9,Neural Networks Co -AI01865,Data Analyst,66728,USD,66728,EN,FL,Sweden,S,Indonesia,100,"Scala, Kubernetes, Computer Vision, TensorFlow",PhD,1,Education,2024-08-17,2024-09-16,679,6.9,Autonomous Tech -AI01866,AI Software Engineer,135400,USD,135400,SE,FL,United States,S,Luxembourg,0,"Hadoop, Python, TensorFlow",Bachelor,5,Consulting,2024-11-09,2024-12-12,856,5.6,Cloud AI Solutions -AI01867,Research Scientist,123743,CAD,154679,SE,FT,Canada,S,Austria,50,"R, Java, Statistics, GCP, Git",Associate,7,Consulting,2024-07-21,2024-09-13,1360,5.3,Cloud AI Solutions -AI01868,Deep Learning Engineer,109631,USD,109631,MI,FL,Norway,S,Germany,50,"AWS, Computer Vision, Data Visualization, NLP",Master,3,Manufacturing,2025-04-05,2025-06-09,2205,6.4,Future Systems -AI01869,Principal Data Scientist,153283,USD,153283,SE,FL,Norway,L,Israel,100,"Python, NLP, Kubernetes, Mathematics",Associate,6,Automotive,2024-04-19,2024-06-02,2060,8.2,Algorithmic Solutions -AI01870,AI Consultant,96402,USD,96402,MI,CT,Norway,M,Norway,0,"Statistics, Scala, Tableau, Computer Vision",PhD,4,Healthcare,2024-07-15,2024-09-25,2089,9.6,Neural Networks Co -AI01871,Research Scientist,158028,USD,158028,SE,FT,Denmark,L,Denmark,100,"Hadoop, Python, TensorFlow",PhD,9,Retail,2024-02-25,2024-04-03,1515,7.3,Predictive Systems -AI01872,NLP Engineer,45538,USD,45538,SE,FL,India,S,India,50,"Git, TensorFlow, Java",Bachelor,8,Gaming,2024-02-06,2024-02-26,1204,9.4,TechCorp Inc -AI01873,AI Architect,115560,USD,115560,MI,FT,Finland,L,Finland,100,"Data Visualization, Linux, AWS, MLOps, Kubernetes",Master,3,Government,2024-03-24,2024-05-02,1753,9,TechCorp Inc -AI01874,AI Consultant,136534,EUR,116054,SE,PT,Germany,M,Germany,100,"Python, TensorFlow, Scala, Java",Master,6,Education,2024-12-19,2025-02-05,1155,7.6,TechCorp Inc -AI01875,AI Research Scientist,211480,USD,211480,EX,CT,Ireland,S,Philippines,50,"Git, TensorFlow, Data Visualization, Computer Vision, Kubernetes",Master,16,Education,2024-05-16,2024-07-17,847,6.5,Cognitive Computing -AI01876,Deep Learning Engineer,112194,USD,112194,SE,FL,Ireland,S,Ireland,50,"Git, Docker, Kubernetes, GCP, Tableau",Bachelor,7,Government,2024-01-27,2024-03-13,1418,8.8,Cloud AI Solutions -AI01877,Autonomous Systems Engineer,150077,USD,150077,EX,FT,Sweden,M,Italy,100,"R, GCP, Linux, Data Visualization, Azure",Bachelor,14,Manufacturing,2024-01-18,2024-03-02,1325,8.6,AI Innovations -AI01878,AI Consultant,125806,USD,125806,SE,CT,Sweden,S,Sweden,50,"Mathematics, Kubernetes, Computer Vision, R",Master,6,Technology,2024-01-01,2024-01-30,1313,5.8,Future Systems -AI01879,Head of AI,66045,USD,66045,EN,CT,Israel,S,Israel,0,"Java, Docker, Computer Vision, Linux, PyTorch",Bachelor,0,Energy,2024-02-17,2024-03-11,1759,9.8,Digital Transformation LLC -AI01880,AI Research Scientist,174743,USD,174743,SE,FT,Norway,S,Poland,0,"SQL, Python, AWS, Java",Bachelor,8,Automotive,2024-09-16,2024-10-31,2102,7.6,AI Innovations -AI01881,AI Product Manager,96725,EUR,82216,EN,CT,Netherlands,L,Romania,0,"Scala, Hadoop, Data Visualization, Azure",Bachelor,1,Consulting,2024-03-22,2024-04-24,2067,6.5,Smart Analytics -AI01882,Data Analyst,61494,USD,61494,EX,PT,India,S,India,50,"Scala, SQL, PyTorch, Statistics",Master,15,Gaming,2024-05-31,2024-06-28,700,9.2,Algorithmic Solutions -AI01883,Autonomous Systems Engineer,51504,CAD,64380,EN,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, Kubernetes",Bachelor,0,Finance,2024-02-16,2024-04-20,725,10,Future Systems -AI01884,Research Scientist,84676,USD,84676,EN,FL,Norway,L,Norway,50,"Hadoop, Git, Data Visualization, PyTorch",Bachelor,1,Automotive,2024-02-13,2024-03-08,2299,5.6,Neural Networks Co -AI01885,Data Engineer,116829,USD,116829,MI,FT,United States,S,United States,100,"GCP, MLOps, AWS",Bachelor,2,Manufacturing,2024-02-02,2024-02-23,2179,5.6,Algorithmic Solutions -AI01886,Machine Learning Researcher,253322,USD,253322,EX,FT,Norway,M,Norway,0,"PyTorch, SQL, MLOps, TensorFlow, Computer Vision",Associate,17,Consulting,2025-01-02,2025-01-29,928,6.3,AI Innovations -AI01887,Machine Learning Researcher,307829,CHF,277046,EX,CT,Switzerland,L,Switzerland,50,"Python, R, Computer Vision, Hadoop, NLP",Master,18,Healthcare,2024-07-09,2024-07-25,2073,9.3,Digital Transformation LLC -AI01888,Head of AI,74701,USD,74701,EN,PT,United States,L,United States,50,"SQL, Git, Java, Mathematics",Master,0,Telecommunications,2024-12-25,2025-02-10,2396,6.5,Cloud AI Solutions -AI01889,Machine Learning Researcher,77814,CAD,97268,MI,PT,Canada,S,Canada,100,"Python, MLOps, Git, Java",PhD,3,Technology,2024-03-23,2024-04-28,2111,5.3,Predictive Systems -AI01890,Head of AI,153857,USD,153857,SE,FL,Ireland,L,Ireland,50,"NLP, Linux, Scala",Master,5,Finance,2024-11-14,2024-12-18,2443,8.8,Autonomous Tech -AI01891,Head of AI,53752,EUR,45689,EN,FL,Netherlands,S,Netherlands,50,"R, Mathematics, SQL",PhD,0,Government,2024-02-26,2024-05-06,1201,5.2,Advanced Robotics -AI01892,Head of AI,67828,USD,67828,EN,PT,Denmark,S,Denmark,0,"PyTorch, Scala, TensorFlow",PhD,0,Government,2025-04-23,2025-07-01,2053,9,Cognitive Computing -AI01893,Machine Learning Engineer,98247,USD,98247,MI,PT,Ireland,S,Vietnam,50,"SQL, TensorFlow, Python, Computer Vision",Bachelor,2,Telecommunications,2025-03-30,2025-04-19,993,7,Digital Transformation LLC -AI01894,AI Product Manager,171970,USD,171970,SE,FL,United States,M,United States,100,"NLP, Linux, MLOps, TensorFlow, Python",PhD,5,Finance,2024-05-17,2024-07-16,698,9.9,Autonomous Tech -AI01895,Machine Learning Engineer,143515,JPY,15786650,SE,FL,Japan,S,Japan,50,"PyTorch, Linux, Tableau, Kubernetes, Spark",Bachelor,9,Consulting,2024-04-24,2024-07-02,2340,7.8,DeepTech Ventures -AI01896,Head of AI,39901,USD,39901,SE,CT,India,S,India,50,"Spark, AWS, Python, Deep Learning",Bachelor,6,Retail,2024-07-11,2024-09-12,685,6.5,Smart Analytics -AI01897,Autonomous Systems Engineer,117566,JPY,12932260,SE,FT,Japan,S,Ukraine,50,"Kubernetes, Python, NLP, Deep Learning, Mathematics",Master,8,Transportation,2025-03-31,2025-05-30,2123,5.2,Smart Analytics -AI01898,Head of AI,113872,CHF,102485,EN,FL,Switzerland,M,Switzerland,50,"SQL, AWS, Statistics, PyTorch",PhD,1,Retail,2024-12-17,2025-01-14,2123,8.5,AI Innovations -AI01899,Machine Learning Engineer,68525,USD,68525,EN,CT,Finland,L,Finland,100,"Mathematics, Kubernetes, R",Master,1,Telecommunications,2024-09-01,2024-09-30,1605,7.2,Advanced Robotics -AI01900,Data Analyst,143796,GBP,107847,SE,FT,United Kingdom,L,Belgium,50,"R, Scala, PyTorch, Git, Python",Master,7,Manufacturing,2024-08-19,2024-10-08,1811,5.6,Predictive Systems -AI01901,NLP Engineer,267822,GBP,200867,EX,CT,United Kingdom,M,Canada,100,"Tableau, Docker, AWS, NLP",Associate,16,Automotive,2024-08-19,2024-09-30,997,9.7,Digital Transformation LLC -AI01902,AI Research Scientist,92727,USD,92727,SE,FL,South Korea,M,Denmark,100,"MLOps, Data Visualization, Java",PhD,8,Retail,2024-01-05,2024-02-07,2179,8.6,Cloud AI Solutions -AI01903,AI Research Scientist,87977,EUR,74780,MI,FT,France,L,France,0,"Hadoop, Linux, Java",Master,3,Real Estate,2024-04-14,2024-05-07,1923,10,Future Systems -AI01904,Autonomous Systems Engineer,71922,EUR,61134,MI,PT,Germany,S,Germany,0,"AWS, Spark, Data Visualization, Git, Scala",PhD,3,Manufacturing,2025-03-07,2025-03-20,1861,9.3,Cognitive Computing -AI01905,Principal Data Scientist,31507,USD,31507,EN,FT,China,L,China,100,"Tableau, Linux, Python, Statistics, R",PhD,0,Gaming,2025-01-26,2025-04-02,1263,8.9,TechCorp Inc -AI01906,Principal Data Scientist,30492,USD,30492,EN,FL,China,M,China,100,"SQL, PyTorch, Tableau, Statistics",PhD,0,Healthcare,2024-10-04,2024-11-19,748,5.1,Advanced Robotics -AI01907,AI Research Scientist,116151,EUR,98728,MI,PT,Netherlands,M,Netherlands,50,"Azure, Linux, Computer Vision, Tableau",Master,3,Automotive,2025-04-16,2025-05-12,1794,9.6,Quantum Computing Inc -AI01908,Machine Learning Researcher,71966,CAD,89958,MI,FL,Canada,M,Canada,50,"Tableau, Python, TensorFlow, Computer Vision, Azure",Associate,2,Finance,2024-03-04,2024-05-05,779,6.1,Autonomous Tech -AI01909,Computer Vision Engineer,163401,GBP,122551,SE,FT,United Kingdom,L,United Kingdom,50,"Python, SQL, Linux",Master,6,Automotive,2024-09-18,2024-11-11,744,6.7,Quantum Computing Inc -AI01910,Robotics Engineer,61330,EUR,52131,EN,CT,France,M,Denmark,0,"Hadoop, Scala, Linux",PhD,1,Consulting,2024-08-09,2024-10-03,1120,9.6,TechCorp Inc -AI01911,Data Engineer,214921,USD,214921,EX,PT,Ireland,S,Ireland,0,"R, MLOps, SQL, Computer Vision, Docker",PhD,16,Media,2025-02-21,2025-04-17,793,8,Algorithmic Solutions -AI01912,AI Product Manager,76932,EUR,65392,EN,FL,Germany,M,Germany,100,"Tableau, TensorFlow, Docker, Spark, SQL",PhD,1,Government,2024-04-29,2024-06-29,614,6.6,Future Systems -AI01913,Research Scientist,169028,CAD,211285,EX,FT,Canada,S,Canada,0,"Java, Deep Learning, Computer Vision, Hadoop",Master,11,Gaming,2024-07-17,2024-09-24,1655,6.5,Smart Analytics -AI01914,Autonomous Systems Engineer,118035,AUD,159347,SE,PT,Australia,L,Australia,0,"Mathematics, Linux, Kubernetes, Python",Associate,9,Automotive,2024-04-18,2024-06-29,1343,8.9,DeepTech Ventures -AI01915,AI Product Manager,113938,USD,113938,MI,PT,Denmark,M,Denmark,100,"Data Visualization, GCP, TensorFlow",Associate,3,Finance,2024-12-02,2025-01-19,863,5.5,Smart Analytics -AI01916,Autonomous Systems Engineer,109615,CAD,137019,SE,FL,Canada,S,Canada,100,"Hadoop, Kubernetes, Scala, Statistics, GCP",PhD,7,Media,2025-03-26,2025-04-22,2420,9.6,Smart Analytics -AI01917,Data Analyst,27659,USD,27659,MI,PT,India,M,India,100,"NLP, Data Visualization, MLOps, Hadoop",Master,2,Healthcare,2024-10-03,2024-10-26,2282,6.1,Neural Networks Co -AI01918,AI Product Manager,67740,USD,67740,EN,PT,United States,S,Austria,100,"Python, Scala, Linux",PhD,0,Real Estate,2025-03-14,2025-05-16,1682,9.8,DeepTech Ventures -AI01919,Machine Learning Researcher,174654,USD,174654,SE,CT,Sweden,L,South Korea,50,"Scala, R, Hadoop, AWS, Python",Master,6,Energy,2024-02-21,2024-03-26,502,5.4,DeepTech Ventures -AI01920,Data Analyst,232730,CAD,290913,EX,FT,Canada,M,India,50,"Hadoop, Kubernetes, Data Visualization, Mathematics, Tableau",PhD,15,Technology,2024-03-11,2024-05-19,1522,5.4,Cognitive Computing -AI01921,Data Analyst,63711,EUR,54154,MI,PT,Austria,S,Austria,50,"Computer Vision, Data Visualization, Python, NLP, AWS",PhD,3,Energy,2025-02-02,2025-02-22,1411,7.5,DataVision Ltd -AI01922,Principal Data Scientist,116990,USD,116990,SE,CT,South Korea,M,South Korea,100,"Computer Vision, R, Scala, GCP, SQL",Associate,8,Media,2024-01-08,2024-03-05,731,6.6,Autonomous Tech -AI01923,AI Architect,105481,USD,105481,MI,CT,Israel,L,Israel,0,"PyTorch, SQL, Computer Vision, NLP, TensorFlow",Master,3,Manufacturing,2024-03-15,2024-04-23,2371,5.2,DeepTech Ventures -AI01924,Data Analyst,161259,EUR,137070,EX,CT,Netherlands,M,Netherlands,0,"Spark, SQL, MLOps",Associate,11,Education,2024-10-15,2024-12-05,1598,9.3,Advanced Robotics -AI01925,Research Scientist,121460,USD,121460,SE,FT,Ireland,L,Ireland,50,"Java, AWS, Mathematics",Bachelor,8,Healthcare,2024-08-28,2024-10-21,848,6.3,Digital Transformation LLC -AI01926,Data Engineer,70644,USD,70644,EN,FL,Sweden,M,Sweden,100,"Python, TensorFlow, Deep Learning",Master,1,Consulting,2025-03-14,2025-04-20,2323,7.4,Future Systems -AI01927,NLP Engineer,109579,GBP,82184,SE,CT,United Kingdom,M,United Kingdom,100,"Python, Docker, Mathematics, Linux, Hadoop",Bachelor,7,Real Estate,2024-10-12,2024-12-04,2482,8.3,Cognitive Computing -AI01928,Head of AI,90547,CAD,113184,MI,CT,Canada,S,United Kingdom,100,"Kubernetes, Docker, Tableau, Azure",PhD,4,Consulting,2024-10-26,2024-12-15,2228,6,Predictive Systems -AI01929,Machine Learning Researcher,218360,USD,218360,EX,PT,South Korea,L,South Korea,0,"GCP, PyTorch, Linux, Azure",Bachelor,18,Healthcare,2024-03-27,2024-04-11,960,6.4,Predictive Systems -AI01930,Robotics Engineer,140380,EUR,119323,SE,PT,Austria,M,Austria,100,"Kubernetes, Scala, R, Computer Vision",PhD,6,Media,2025-04-02,2025-05-10,2084,9.7,Neural Networks Co -AI01931,Computer Vision Engineer,119973,USD,119973,SE,FT,South Korea,L,South Korea,50,"Azure, Python, TensorFlow",Bachelor,7,Transportation,2024-02-18,2024-04-20,2141,6.7,TechCorp Inc -AI01932,NLP Engineer,102535,USD,102535,MI,CT,United States,S,United States,100,"Scala, Python, Linux, Tableau, Computer Vision",Bachelor,4,Energy,2024-01-04,2024-03-09,2029,7.7,DeepTech Ventures -AI01933,Machine Learning Researcher,106806,AUD,144188,MI,FT,Australia,L,Australia,50,"SQL, Java, Docker",Bachelor,2,Manufacturing,2025-03-02,2025-04-09,1517,8.7,Predictive Systems -AI01934,Deep Learning Engineer,54346,CAD,67933,EN,CT,Canada,S,Canada,100,"MLOps, TensorFlow, SQL, Scala",Associate,1,Media,2025-02-27,2025-03-22,1549,8.5,Future Systems -AI01935,AI Consultant,70194,USD,70194,SE,CT,China,L,China,0,"Linux, PyTorch, TensorFlow, AWS",PhD,6,Automotive,2024-07-08,2024-08-24,1557,6.3,Cloud AI Solutions -AI01936,Computer Vision Engineer,94729,EUR,80520,MI,FL,Netherlands,S,Argentina,100,"Data Visualization, Spark, Mathematics",PhD,3,Transportation,2025-03-21,2025-04-18,770,6.5,Neural Networks Co -AI01937,NLP Engineer,46286,USD,46286,EN,FT,Finland,S,Finland,100,"Python, Git, Kubernetes",Master,0,Transportation,2024-09-18,2024-11-20,2261,9.6,Algorithmic Solutions -AI01938,Machine Learning Engineer,166362,USD,166362,SE,CT,Norway,L,Denmark,50,"Data Visualization, PyTorch, Hadoop, Linux",Associate,9,Technology,2025-03-14,2025-04-03,884,6.9,Smart Analytics -AI01939,AI Software Engineer,185959,GBP,139469,EX,CT,United Kingdom,S,United Kingdom,100,"AWS, SQL, Data Visualization, Computer Vision",Master,12,Manufacturing,2024-04-21,2024-06-15,2359,6.1,Advanced Robotics -AI01940,AI Software Engineer,124415,USD,124415,SE,PT,South Korea,M,South Korea,50,"SQL, Spark, R",Associate,9,Media,2024-04-15,2024-05-30,2248,6.3,Advanced Robotics -AI01941,AI Architect,69802,USD,69802,EN,CT,Ireland,S,Netherlands,50,"Linux, Kubernetes, Python, TensorFlow, Data Visualization",Master,0,Transportation,2025-04-10,2025-05-24,1731,7.8,Machine Intelligence Group -AI01942,NLP Engineer,220589,USD,220589,EX,FL,United States,S,United States,50,"Scala, Spark, Linux, TensorFlow",Master,18,Telecommunications,2024-02-11,2024-03-30,1595,5.7,Autonomous Tech -AI01943,AI Specialist,80123,AUD,108166,MI,PT,Australia,S,Australia,0,"TensorFlow, Kubernetes, NLP, Linux",PhD,4,Manufacturing,2025-01-17,2025-02-27,1255,9.2,AI Innovations -AI01944,Data Scientist,116909,USD,116909,MI,FL,United States,S,Brazil,100,"MLOps, Linux, SQL, NLP",Bachelor,2,Telecommunications,2024-07-28,2024-10-08,2205,9.1,DataVision Ltd -AI01945,Machine Learning Engineer,43728,EUR,37169,EN,PT,Austria,S,Austria,0,"Java, Python, Azure, NLP",Bachelor,1,Government,2024-10-28,2025-01-06,2246,5.4,DataVision Ltd -AI01946,Autonomous Systems Engineer,64573,EUR,54887,EN,FT,Austria,L,Austria,50,"AWS, Java, NLP",PhD,0,Finance,2025-04-26,2025-06-30,2310,9,Future Systems -AI01947,NLP Engineer,117914,CHF,106123,MI,FL,Switzerland,S,Switzerland,100,"Hadoop, NLP, R",Bachelor,2,Transportation,2024-07-29,2024-10-10,1827,6.1,Autonomous Tech -AI01948,Autonomous Systems Engineer,152384,USD,152384,EX,CT,South Korea,L,Ukraine,100,"Kubernetes, R, Tableau",Bachelor,16,Real Estate,2025-01-19,2025-02-16,1687,6.3,Digital Transformation LLC -AI01949,AI Software Engineer,68312,EUR,58065,MI,FL,Austria,M,Austria,100,"Python, Deep Learning, Computer Vision, Spark, TensorFlow",PhD,3,Telecommunications,2025-03-31,2025-04-19,509,5.2,DataVision Ltd -AI01950,AI Specialist,85129,CAD,106411,MI,PT,Canada,M,Canada,100,"SQL, Kubernetes, Git, Statistics, Docker",Master,4,Real Estate,2024-01-01,2024-01-17,1017,8.8,Advanced Robotics -AI01951,AI Software Engineer,146496,CHF,131846,SE,CT,Switzerland,S,Switzerland,0,"R, Hadoop, Mathematics, Tableau",Bachelor,7,Consulting,2025-03-06,2025-04-12,1644,6.6,Autonomous Tech -AI01952,Research Scientist,120458,USD,120458,MI,FT,Norway,M,Norway,0,"SQL, PyTorch, AWS, Linux, Computer Vision",Master,4,Retail,2025-02-28,2025-03-31,650,5.8,AI Innovations -AI01953,AI Architect,306393,USD,306393,EX,PT,Denmark,M,United Kingdom,100,"Python, Scala, Computer Vision, Mathematics, TensorFlow",Master,12,Retail,2024-04-29,2024-05-27,2084,6.5,Quantum Computing Inc -AI01954,Data Analyst,119182,USD,119182,SE,FT,Ireland,M,Ireland,0,"Mathematics, Azure, Kubernetes, Git",Associate,6,Gaming,2024-08-02,2024-10-10,1648,5.6,Neural Networks Co -AI01955,AI Product Manager,190595,CHF,171536,EX,PT,Switzerland,S,Switzerland,100,"R, PyTorch, GCP, Tableau, Java",PhD,18,Automotive,2024-10-12,2024-11-06,668,5.2,Future Systems -AI01956,AI Product Manager,133627,AUD,180396,SE,PT,Australia,M,Indonesia,100,"Data Visualization, PyTorch, Spark, GCP",PhD,9,Transportation,2024-08-04,2024-10-13,1422,7.2,AI Innovations -AI01957,AI Specialist,102896,USD,102896,MI,FL,Norway,S,Israel,100,"TensorFlow, Azure, MLOps",Bachelor,2,Energy,2024-04-21,2024-05-05,1871,6.3,Machine Intelligence Group -AI01958,AI Consultant,53828,EUR,45754,EN,CT,France,S,France,100,"Hadoop, TensorFlow, Spark, Computer Vision, SQL",PhD,0,Technology,2024-03-17,2024-04-07,1829,6.3,DataVision Ltd -AI01959,Robotics Engineer,229532,EUR,195102,EX,FT,Netherlands,L,Austria,100,"PyTorch, Tableau, Linux, Python",Master,19,Finance,2025-01-02,2025-03-15,548,7.8,Cognitive Computing -AI01960,Machine Learning Researcher,50929,USD,50929,SE,FL,India,L,India,100,"Spark, Kubernetes, Azure, Deep Learning",Associate,7,Healthcare,2024-12-31,2025-01-30,1837,7.8,Machine Intelligence Group -AI01961,Autonomous Systems Engineer,119585,EUR,101647,SE,PT,Germany,S,Germany,50,"R, Kubernetes, Git",Master,5,Media,2025-02-27,2025-04-28,1402,6,Future Systems -AI01962,Deep Learning Engineer,94488,USD,94488,EN,FT,Denmark,M,New Zealand,0,"Linux, TensorFlow, SQL",Associate,0,Manufacturing,2025-03-24,2025-04-20,2344,7.6,Autonomous Tech -AI01963,Data Analyst,62316,EUR,52969,MI,PT,Austria,S,Austria,50,"Statistics, Python, Deep Learning, Git, TensorFlow",PhD,2,Manufacturing,2024-03-24,2024-04-07,602,6.4,Quantum Computing Inc -AI01964,ML Ops Engineer,108014,USD,108014,EN,PT,Denmark,L,Denmark,50,"MLOps, Spark, SQL, NLP",Bachelor,1,Real Estate,2024-05-07,2024-06-02,1694,8.3,Machine Intelligence Group -AI01965,Deep Learning Engineer,137340,EUR,116739,SE,CT,Netherlands,M,Netherlands,50,"Git, MLOps, Java",Associate,5,Automotive,2024-07-31,2024-09-16,776,9.1,DeepTech Ventures -AI01966,AI Consultant,51851,AUD,69999,EN,FL,Australia,M,Australia,50,"MLOps, Scala, Kubernetes, Python, TensorFlow",PhD,0,Education,2024-05-17,2024-07-20,2465,6.1,TechCorp Inc -AI01967,Machine Learning Engineer,158813,USD,158813,SE,PT,Norway,S,Norway,100,"Tableau, Git, Azure, Scala, GCP",Associate,7,Telecommunications,2024-05-17,2024-06-27,2495,6.8,TechCorp Inc -AI01968,NLP Engineer,272366,USD,272366,EX,CT,Norway,M,Norway,100,"Mathematics, TensorFlow, Tableau, Linux, R",Bachelor,11,Consulting,2025-02-25,2025-03-15,1869,5.8,Cloud AI Solutions -AI01969,AI Research Scientist,66656,USD,66656,EN,PT,Finland,S,France,0,"Kubernetes, PyTorch, Java, AWS, Deep Learning",Bachelor,0,Media,2025-02-16,2025-04-20,559,9.2,Neural Networks Co -AI01970,Computer Vision Engineer,97650,EUR,83003,MI,CT,Austria,M,Austria,100,"MLOps, Data Visualization, TensorFlow, Tableau, SQL",PhD,4,Healthcare,2024-08-31,2024-09-14,1105,5.2,Future Systems -AI01971,Data Scientist,198520,USD,198520,EX,FT,Sweden,L,Sweden,50,"Hadoop, PyTorch, Deep Learning, TensorFlow",Bachelor,15,Retail,2025-02-24,2025-03-24,1825,9.4,Machine Intelligence Group -AI01972,Computer Vision Engineer,113590,CHF,102231,MI,FL,Switzerland,M,France,0,"Git, Computer Vision, PyTorch",Bachelor,4,Gaming,2025-01-17,2025-03-20,2437,5.8,AI Innovations -AI01973,Data Scientist,153445,EUR,130428,EX,CT,France,S,France,0,"Python, Data Visualization, TensorFlow, Deep Learning",Master,10,Manufacturing,2025-03-25,2025-04-12,2026,7,Digital Transformation LLC -AI01974,Robotics Engineer,97324,SGD,126521,EN,FL,Singapore,L,Singapore,50,"Java, Tableau, Kubernetes",Bachelor,0,Manufacturing,2024-07-27,2024-09-23,1832,8.8,Algorithmic Solutions -AI01975,Research Scientist,44666,USD,44666,EN,PT,South Korea,S,South Korea,50,"Kubernetes, Python, AWS",Associate,0,Education,2024-11-06,2024-11-30,2233,6.3,Machine Intelligence Group -AI01976,Deep Learning Engineer,296548,USD,296548,EX,PT,United States,M,United States,100,"Tableau, Azure, Java",Bachelor,18,Technology,2024-06-15,2024-08-13,768,9.8,AI Innovations -AI01977,AI Architect,89790,EUR,76322,EN,CT,Netherlands,L,Netherlands,100,"SQL, Git, MLOps",PhD,0,Government,2024-06-11,2024-08-04,1109,9.6,Cognitive Computing -AI01978,ML Ops Engineer,146337,SGD,190238,SE,PT,Singapore,M,Portugal,0,"R, Data Visualization, Java, GCP, Python",Bachelor,9,Consulting,2024-07-09,2024-07-23,1346,5.6,Neural Networks Co -AI01979,Machine Learning Engineer,99555,CHF,89600,MI,PT,Switzerland,S,South Africa,100,"NLP, Docker, PyTorch",Master,4,Energy,2024-02-13,2024-03-05,1281,8.8,Future Systems -AI01980,NLP Engineer,153992,JPY,16939120,EX,FT,Japan,M,Japan,100,"Linux, GCP, MLOps, Data Visualization, Git",PhD,10,Media,2024-07-05,2024-07-27,1340,8.2,Algorithmic Solutions -AI01981,Deep Learning Engineer,103750,EUR,88188,MI,FT,Netherlands,S,Netherlands,100,"Python, Statistics, Mathematics, TensorFlow, Java",Bachelor,4,Government,2025-02-25,2025-04-05,1399,9.5,DataVision Ltd -AI01982,Principal Data Scientist,88704,USD,88704,MI,PT,Ireland,L,Ghana,0,"Linux, Hadoop, R, Mathematics, Kubernetes",Master,2,Real Estate,2024-01-31,2024-03-25,1929,5.3,Cloud AI Solutions -AI01983,Data Analyst,118310,JPY,13014100,MI,PT,Japan,L,Japan,100,"TensorFlow, Data Visualization, Statistics",Master,3,Telecommunications,2024-06-10,2024-08-06,1801,7.4,Smart Analytics -AI01984,Deep Learning Engineer,171397,EUR,145687,EX,FT,Germany,S,Germany,100,"Azure, Linux, Deep Learning",Master,17,Healthcare,2025-03-22,2025-05-23,1983,5.5,Future Systems -AI01985,AI Research Scientist,80403,CAD,100504,MI,CT,Canada,M,Canada,50,"Scala, Java, Deep Learning",Associate,3,Automotive,2025-02-09,2025-03-12,681,9.5,Algorithmic Solutions -AI01986,Robotics Engineer,118077,USD,118077,SE,FL,United States,S,Norway,50,"Statistics, Azure, TensorFlow",Master,6,Manufacturing,2024-05-24,2024-08-01,1654,5.7,TechCorp Inc -AI01987,Head of AI,103534,USD,103534,SE,FL,Sweden,M,Sweden,100,"SQL, Tableau, PyTorch",Associate,9,Technology,2024-12-04,2025-01-26,2035,7.6,Predictive Systems -AI01988,Computer Vision Engineer,101905,EUR,86619,MI,FT,Austria,M,Switzerland,100,"TensorFlow, Python, GCP",Associate,2,Consulting,2024-04-11,2024-05-22,1083,6.1,AI Innovations -AI01989,AI Research Scientist,182075,USD,182075,EX,CT,South Korea,L,Estonia,0,"Kubernetes, Mathematics, Tableau",PhD,18,Finance,2024-03-12,2024-04-19,979,7.8,DeepTech Ventures -AI01990,AI Research Scientist,230990,SGD,300287,EX,FL,Singapore,M,Singapore,0,"SQL, PyTorch, Computer Vision",Master,16,Government,2024-03-13,2024-04-04,574,8.7,Digital Transformation LLC -AI01991,Computer Vision Engineer,215816,EUR,183444,EX,PT,Germany,S,Germany,100,"Mathematics, PyTorch, NLP",PhD,19,Retail,2024-01-15,2024-02-23,2001,8.2,Cognitive Computing -AI01992,Research Scientist,83946,EUR,71354,EN,FL,Germany,L,Germany,50,"R, Spark, Statistics",PhD,1,Energy,2025-04-30,2025-05-30,726,5.2,DeepTech Ventures -AI01993,ML Ops Engineer,96785,USD,96785,MI,PT,Ireland,S,United Kingdom,0,"TensorFlow, R, SQL, Data Visualization, AWS",Bachelor,2,Telecommunications,2024-03-29,2024-05-27,712,5.5,TechCorp Inc -AI01994,Data Scientist,82495,EUR,70121,MI,PT,Netherlands,M,Malaysia,100,"Linux, Git, MLOps",PhD,3,Gaming,2025-03-10,2025-04-05,856,5.8,Neural Networks Co -AI01995,Machine Learning Engineer,131731,GBP,98798,MI,CT,United Kingdom,L,United Kingdom,0,"TensorFlow, AWS, Linux",PhD,3,Technology,2024-11-08,2024-12-31,814,8.2,Digital Transformation LLC -AI01996,Head of AI,56604,USD,56604,EN,CT,Israel,M,Israel,100,"Kubernetes, PyTorch, Statistics, NLP, TensorFlow",PhD,1,Retail,2024-11-17,2025-01-12,1845,7.4,Cognitive Computing -AI01997,Data Analyst,63776,USD,63776,EN,FL,Ireland,S,Ireland,100,"Spark, Mathematics, Java, Statistics, Python",Bachelor,1,Retail,2024-12-04,2025-01-15,2083,7.1,Digital Transformation LLC -AI01998,AI Architect,68800,CAD,86000,MI,CT,Canada,M,Canada,100,"PyTorch, R, Tableau, Deep Learning",Associate,4,Government,2024-08-15,2024-08-29,868,6.4,Smart Analytics -AI01999,AI Architect,45902,USD,45902,MI,CT,China,S,China,100,"SQL, Scala, Tableau, R",Associate,3,Transportation,2024-04-10,2024-06-17,2292,9,Autonomous Tech -AI02000,Data Scientist,87974,SGD,114366,MI,CT,Singapore,S,Singapore,100,"Mathematics, R, TensorFlow, Hadoop",PhD,4,Retail,2024-11-20,2025-01-31,1465,6.4,Quantum Computing Inc -AI02001,AI Architect,141156,USD,141156,SE,CT,Sweden,M,Sweden,100,"Azure, R, Deep Learning, Scala, Java",PhD,8,Manufacturing,2024-09-19,2024-10-03,928,6.4,Machine Intelligence Group -AI02002,Autonomous Systems Engineer,72809,CHF,65528,EN,CT,Switzerland,M,Switzerland,100,"Linux, Hadoop, Deep Learning, PyTorch, Computer Vision",PhD,1,Telecommunications,2024-05-09,2024-06-18,924,9,Advanced Robotics -AI02003,Autonomous Systems Engineer,74905,CHF,67415,EN,PT,Switzerland,M,South Korea,100,"Statistics, SQL, PyTorch, Deep Learning, Azure",Bachelor,1,Healthcare,2024-12-17,2025-02-06,1485,7.6,Neural Networks Co -AI02004,Deep Learning Engineer,83543,CAD,104429,MI,FL,Canada,L,Portugal,50,"Data Visualization, SQL, MLOps, PyTorch",PhD,4,Transportation,2024-09-28,2024-11-16,1281,5.5,AI Innovations -AI02005,ML Ops Engineer,74348,EUR,63196,EN,FL,France,L,France,0,"Kubernetes, Deep Learning, SQL, Python, NLP",PhD,0,Gaming,2024-02-12,2024-03-05,1746,8.1,DeepTech Ventures -AI02006,AI Product Manager,221177,USD,221177,EX,PT,Israel,M,Russia,50,"Python, Git, Data Visualization, Mathematics, GCP",Associate,10,Manufacturing,2024-08-12,2024-09-04,1529,9,DeepTech Ventures -AI02007,Machine Learning Engineer,188560,USD,188560,EX,FT,Israel,S,Israel,100,"Python, Kubernetes, NLP, Linux",PhD,14,Finance,2024-07-20,2024-08-06,1635,6.9,Cloud AI Solutions -AI02008,Principal Data Scientist,63698,JPY,7006780,EN,FL,Japan,M,Japan,0,"Computer Vision, Java, R",PhD,0,Media,2024-12-28,2025-03-02,1197,5.2,Neural Networks Co -AI02009,AI Architect,80238,USD,80238,EN,CT,Norway,L,Norway,50,"MLOps, Docker, GCP, Scala, PyTorch",Bachelor,0,Manufacturing,2024-12-29,2025-02-27,2410,5.4,Quantum Computing Inc -AI02010,Autonomous Systems Engineer,161051,EUR,136893,EX,PT,Austria,L,Austria,50,"Linux, Python, Scala",Bachelor,15,Education,2024-12-18,2025-01-22,1314,5.2,Smart Analytics -AI02011,NLP Engineer,130144,EUR,110622,SE,FT,Germany,S,Argentina,0,"GCP, PyTorch, TensorFlow, Python, Data Visualization",Bachelor,8,Finance,2024-02-04,2024-02-27,2268,5.5,Autonomous Tech -AI02012,AI Research Scientist,50319,USD,50319,EN,PT,Israel,S,Israel,0,"PyTorch, Java, Python, Mathematics, SQL",Bachelor,1,Media,2024-05-12,2024-05-30,782,7.7,DeepTech Ventures -AI02013,Machine Learning Researcher,256545,USD,256545,EX,CT,Sweden,L,Sweden,100,"PyTorch, SQL, Computer Vision, Spark, Azure",Bachelor,18,Healthcare,2025-02-02,2025-02-20,2493,6.9,Autonomous Tech -AI02014,AI Research Scientist,138961,USD,138961,SE,FT,South Korea,L,South Korea,0,"TensorFlow, Docker, SQL",Associate,6,Government,2024-04-11,2024-06-13,1018,8.6,TechCorp Inc -AI02015,Machine Learning Engineer,60037,EUR,51031,EN,CT,Germany,L,United Kingdom,0,"Mathematics, Scala, Data Visualization",Bachelor,0,Education,2024-07-25,2024-08-31,2188,6.3,AI Innovations -AI02016,AI Software Engineer,102110,USD,102110,MI,PT,Norway,M,Norway,0,"Git, Python, Java",Master,3,Retail,2024-11-17,2025-01-17,1311,8.1,AI Innovations -AI02017,Research Scientist,159317,EUR,135419,SE,FL,Germany,L,Germany,50,"Java, TensorFlow, PyTorch, Azure, GCP",PhD,9,Automotive,2025-02-25,2025-03-16,2179,5.8,Machine Intelligence Group -AI02018,Data Analyst,113026,EUR,96072,SE,PT,Netherlands,S,Netherlands,0,"R, GCP, Kubernetes, Spark, Linux",Bachelor,6,Technology,2024-12-19,2025-03-01,1999,9.2,Machine Intelligence Group -AI02019,Data Engineer,175703,USD,175703,SE,FL,Denmark,S,Denmark,50,"Deep Learning, Azure, Hadoop, SQL, Git",Bachelor,8,Telecommunications,2024-03-07,2024-04-19,1080,7,Autonomous Tech -AI02020,Deep Learning Engineer,79945,USD,79945,MI,CT,United States,S,Luxembourg,0,"Git, Statistics, Azure",Master,2,Retail,2024-02-21,2024-04-19,1292,7.3,Machine Intelligence Group -AI02021,Data Analyst,78895,AUD,106508,EN,FL,Australia,L,Australia,0,"MLOps, Kubernetes, TensorFlow, Python",PhD,1,Gaming,2024-03-03,2024-04-22,655,8.2,Neural Networks Co -AI02022,Head of AI,65331,USD,65331,EN,FT,Ireland,S,Ireland,50,"Azure, Kubernetes, AWS, MLOps, TensorFlow",PhD,0,Consulting,2024-06-29,2024-07-23,629,5.2,Advanced Robotics -AI02023,AI Software Engineer,88502,USD,88502,EN,PT,Denmark,L,Denmark,100,"Linux, Git, Deep Learning, SQL, Azure",PhD,0,Gaming,2024-03-06,2024-04-23,2419,8.8,Neural Networks Co -AI02024,AI Research Scientist,218753,SGD,284379,EX,FL,Singapore,M,Norway,0,"Git, Python, Mathematics",Bachelor,17,Media,2024-08-06,2024-09-06,1029,8.6,Cloud AI Solutions -AI02025,Machine Learning Researcher,286960,SGD,373048,EX,FL,Singapore,L,Singapore,50,"Scala, Mathematics, Data Visualization, Git, Python",PhD,13,Energy,2024-07-02,2024-07-19,1324,7.9,Future Systems -AI02026,Autonomous Systems Engineer,54703,USD,54703,EN,FL,Sweden,M,Sweden,0,"Hadoop, Git, Tableau, Scala",PhD,0,Gaming,2024-04-19,2024-06-07,2069,6.4,Advanced Robotics -AI02027,Machine Learning Engineer,119409,USD,119409,SE,PT,Finland,L,Belgium,0,"AWS, MLOps, Kubernetes, Azure, Spark",Bachelor,5,Technology,2024-07-27,2024-09-03,2467,6.3,Autonomous Tech -AI02028,AI Software Engineer,169745,CAD,212181,EX,CT,Canada,M,Canada,50,"Java, SQL, PyTorch",Master,16,Real Estate,2024-03-20,2024-05-06,2094,5.4,Digital Transformation LLC -AI02029,AI Product Manager,117185,EUR,99607,MI,FT,Austria,L,Brazil,50,"Java, Kubernetes, Scala, Computer Vision, Git",Associate,2,Gaming,2025-01-13,2025-02-04,1341,7.6,Quantum Computing Inc -AI02030,AI Specialist,67488,EUR,57365,EN,PT,Germany,L,Italy,0,"SQL, Azure, PyTorch, Docker, TensorFlow",Master,0,Education,2024-10-02,2024-11-21,1857,7.4,Algorithmic Solutions -AI02031,Data Analyst,237063,AUD,320035,EX,FT,Australia,L,Australia,0,"Azure, Java, NLP, Hadoop",Bachelor,12,Technology,2024-07-17,2024-09-09,2126,9.3,Future Systems -AI02032,Data Engineer,121918,EUR,103630,MI,FL,Germany,L,Germany,50,"Kubernetes, Statistics, Tableau",Associate,2,Gaming,2024-07-09,2024-08-08,1044,5.7,Autonomous Tech -AI02033,Deep Learning Engineer,147358,USD,147358,EX,CT,Ireland,S,Argentina,0,"AWS, Python, Kubernetes, TensorFlow, Docker",Master,19,Transportation,2025-02-22,2025-04-06,932,6.2,DeepTech Ventures -AI02034,Data Analyst,159954,SGD,207940,SE,CT,Singapore,M,Singapore,50,"R, Kubernetes, MLOps, AWS, PyTorch",Master,8,Energy,2024-10-10,2024-11-04,886,7.5,Future Systems -AI02035,Data Analyst,112591,USD,112591,SE,FL,South Korea,M,Thailand,0,"Azure, Scala, Data Visualization, Mathematics",Bachelor,5,Government,2024-04-21,2024-05-07,758,5.4,TechCorp Inc -AI02036,AI Consultant,51670,EUR,43920,EN,CT,France,M,France,50,"R, MLOps, TensorFlow, Hadoop",Bachelor,1,Energy,2024-03-25,2024-04-26,1983,9.2,Predictive Systems -AI02037,Data Analyst,54739,USD,54739,EN,CT,Finland,S,Finland,50,"Statistics, MLOps, Tableau, SQL, Linux",PhD,1,Consulting,2024-09-20,2024-11-06,2488,6.7,Future Systems -AI02038,Principal Data Scientist,93238,EUR,79252,SE,CT,France,S,France,0,"NLP, Docker, Python, AWS",Bachelor,5,Education,2024-07-13,2024-08-24,1683,6,DeepTech Ventures -AI02039,AI Research Scientist,84825,USD,84825,MI,FL,Ireland,L,Malaysia,100,"Kubernetes, Mathematics, Tableau, MLOps",Associate,2,Technology,2024-05-16,2024-07-20,1709,6.7,TechCorp Inc -AI02040,AI Software Engineer,78450,USD,78450,MI,FT,Sweden,S,Sweden,100,"Computer Vision, Python, Git, TensorFlow",Bachelor,4,Energy,2024-12-18,2025-01-01,505,5.5,AI Innovations -AI02041,Head of AI,66222,USD,66222,EN,FL,South Korea,L,South Korea,50,"SQL, Deep Learning, NLP, Python",PhD,1,Technology,2024-09-04,2024-10-10,692,9.7,Algorithmic Solutions -AI02042,ML Ops Engineer,87393,USD,87393,MI,FL,United States,S,China,100,"Docker, Kubernetes, Data Visualization, Mathematics, Hadoop",Associate,2,Automotive,2025-01-14,2025-02-13,703,9.5,Smart Analytics -AI02043,Data Scientist,293844,GBP,220383,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Git, Tableau",Master,13,Healthcare,2024-02-11,2024-03-20,905,5.1,Neural Networks Co -AI02044,NLP Engineer,89635,USD,89635,EX,CT,China,S,China,50,"NLP, Scala, SQL, Deep Learning, Azure",Master,17,Manufacturing,2024-02-02,2024-04-05,1941,6.3,Quantum Computing Inc -AI02045,Data Analyst,40827,USD,40827,SE,CT,India,M,Argentina,100,"Deep Learning, PyTorch, Scala, Computer Vision",Associate,8,Consulting,2024-01-21,2024-03-11,867,6.1,DataVision Ltd -AI02046,AI Architect,53958,USD,53958,MI,PT,China,L,New Zealand,50,"SQL, Docker, Tableau",Bachelor,2,Real Estate,2024-05-12,2024-07-15,2051,7.5,DeepTech Ventures -AI02047,Autonomous Systems Engineer,209986,EUR,178488,EX,PT,France,S,France,50,"Scala, Kubernetes, Data Visualization, SQL, R",Associate,15,Real Estate,2024-04-12,2024-05-11,1552,5.3,Smart Analytics -AI02048,Data Engineer,48509,USD,48509,EN,FL,Finland,S,Finland,0,"Git, Mathematics, Hadoop, AWS, Azure",Bachelor,1,Education,2025-03-30,2025-05-03,2109,9.7,TechCorp Inc -AI02049,Autonomous Systems Engineer,256412,USD,256412,EX,CT,Denmark,L,Germany,0,"Java, TensorFlow, Spark, AWS",PhD,18,Real Estate,2025-04-10,2025-05-21,2390,5.7,TechCorp Inc -AI02050,Research Scientist,54244,USD,54244,EN,FL,South Korea,M,South Korea,100,"Python, Java, Tableau, TensorFlow",Master,0,Manufacturing,2024-05-29,2024-06-30,896,5.3,Cloud AI Solutions -AI02051,AI Architect,58064,USD,58064,EN,FT,Sweden,S,Denmark,100,"Kubernetes, MLOps, Statistics",Bachelor,0,Real Estate,2025-03-11,2025-04-30,1851,6.3,Predictive Systems -AI02052,Data Analyst,89637,USD,89637,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, MLOps, Hadoop",Bachelor,8,Gaming,2025-01-01,2025-02-15,795,7.4,Quantum Computing Inc -AI02053,Autonomous Systems Engineer,74071,USD,74071,EN,FL,Denmark,S,Vietnam,100,"R, Computer Vision, PyTorch, GCP",Bachelor,1,Technology,2024-04-11,2024-04-30,1809,7.5,Algorithmic Solutions -AI02054,AI Consultant,89562,EUR,76128,MI,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, Python, SQL, TensorFlow",PhD,4,Retail,2024-10-02,2024-10-16,750,9.4,Neural Networks Co -AI02055,Research Scientist,199418,CHF,179476,SE,FT,Switzerland,L,Switzerland,0,"Python, R, GCP, Spark",PhD,9,Government,2024-03-01,2024-05-01,1597,9.1,Advanced Robotics -AI02056,Robotics Engineer,128887,EUR,109554,EX,PT,France,M,France,50,"Azure, AWS, Tableau",Bachelor,13,Consulting,2024-03-19,2024-04-26,963,8.3,AI Innovations -AI02057,Data Analyst,72518,EUR,61640,EN,PT,Germany,S,Germany,50,"Python, SQL, Tableau",Bachelor,1,Finance,2024-05-30,2024-07-16,506,6.3,DataVision Ltd -AI02058,Autonomous Systems Engineer,63237,EUR,53751,MI,CT,France,S,France,0,"NLP, Kubernetes, Scala, Git, Tableau",PhD,4,Automotive,2024-01-17,2024-02-19,737,6.6,DeepTech Ventures -AI02059,Deep Learning Engineer,135732,GBP,101799,SE,PT,United Kingdom,S,Switzerland,100,"Python, SQL, Java, Computer Vision",Bachelor,5,Government,2024-05-01,2024-07-03,1777,5.8,Cognitive Computing -AI02060,AI Software Engineer,99662,USD,99662,EX,CT,China,M,China,100,"Kubernetes, Azure, Python, Hadoop",Bachelor,12,Transportation,2024-02-04,2024-03-14,1974,5,TechCorp Inc -AI02061,AI Consultant,282892,USD,282892,EX,FL,Ireland,L,Israel,100,"Scala, Java, Kubernetes",Master,14,Real Estate,2024-01-23,2024-02-14,2335,9.5,TechCorp Inc -AI02062,Computer Vision Engineer,126107,USD,126107,MI,CT,Denmark,L,Denmark,100,"Azure, Scala, Kubernetes",PhD,4,Retail,2024-08-23,2024-10-30,1170,9.4,Quantum Computing Inc -AI02063,Research Scientist,157203,USD,157203,SE,FL,United States,M,United States,0,"Git, Python, Computer Vision, Mathematics, AWS",PhD,5,Technology,2024-10-21,2024-12-01,1718,6.6,TechCorp Inc -AI02064,AI Specialist,91180,USD,91180,EN,CT,Norway,M,Norway,0,"Java, GCP, AWS, Hadoop",Master,0,Consulting,2024-12-09,2025-01-23,1561,5.4,Digital Transformation LLC -AI02065,Data Scientist,102489,USD,102489,EX,CT,China,M,China,50,"Tableau, Git, Kubernetes, MLOps, Computer Vision",PhD,19,Retail,2024-08-04,2024-09-15,1000,5.7,Smart Analytics -AI02066,AI Architect,220299,USD,220299,EX,FT,Finland,L,Finland,100,"NLP, Scala, Data Visualization",Associate,18,Retail,2025-04-18,2025-06-27,994,9.8,Smart Analytics -AI02067,AI Specialist,83499,USD,83499,MI,FL,Israel,M,Israel,50,"Data Visualization, Linux, Python, TensorFlow, PyTorch",Master,4,Manufacturing,2025-01-03,2025-02-28,1120,8.5,Cloud AI Solutions -AI02068,AI Research Scientist,72075,EUR,61264,EN,FT,Germany,M,Germany,50,"MLOps, Azure, AWS, Deep Learning, R",Associate,1,Government,2024-08-02,2024-10-03,1635,6.1,Advanced Robotics -AI02069,Deep Learning Engineer,87037,EUR,73981,MI,CT,Netherlands,M,Netherlands,0,"Deep Learning, Docker, NLP, Hadoop",Master,2,Automotive,2024-10-06,2024-11-02,967,5.4,Smart Analytics -AI02070,AI Research Scientist,123099,USD,123099,MI,FT,Denmark,S,Denmark,0,"PyTorch, AWS, MLOps, Python",PhD,2,Consulting,2025-02-22,2025-05-04,1204,7.5,Autonomous Tech -AI02071,Machine Learning Engineer,104913,EUR,89176,SE,CT,Germany,S,China,0,"Kubernetes, Scala, NLP, Mathematics, TensorFlow",Associate,5,Technology,2024-08-13,2024-10-24,2478,7.5,Machine Intelligence Group -AI02072,Deep Learning Engineer,221690,EUR,188437,EX,CT,Austria,L,Mexico,50,"PyTorch, Python, Git, Spark, Azure",Bachelor,19,Telecommunications,2024-08-05,2024-08-29,1602,7.3,Digital Transformation LLC -AI02073,Data Scientist,113653,EUR,96605,SE,FL,Germany,S,Germany,0,"Data Visualization, Kubernetes, Mathematics",Master,8,Real Estate,2024-01-06,2024-03-09,2077,8.6,DataVision Ltd -AI02074,Computer Vision Engineer,250419,USD,250419,EX,PT,United States,L,United States,100,"Data Visualization, Python, Azure, Scala, GCP",Bachelor,18,Retail,2024-05-17,2024-06-08,2362,7.2,Algorithmic Solutions -AI02075,AI Consultant,108412,EUR,92150,SE,CT,France,S,France,100,"Java, Python, Data Visualization, Linux",Associate,8,Gaming,2024-09-14,2024-10-16,1441,8.1,Algorithmic Solutions -AI02076,AI Specialist,186753,EUR,158740,EX,FL,Netherlands,S,Netherlands,100,"Mathematics, SQL, PyTorch",Associate,16,Technology,2025-04-05,2025-06-01,2436,8.9,Advanced Robotics -AI02077,AI Product Manager,134362,GBP,100772,MI,FT,United Kingdom,L,Finland,100,"Tableau, Hadoop, R, Docker",Associate,3,Consulting,2024-04-04,2024-05-15,2222,7.5,Smart Analytics -AI02078,Data Scientist,157702,USD,157702,EX,CT,Sweden,S,Vietnam,0,"Python, TensorFlow, Data Visualization, PyTorch, Hadoop",PhD,19,Real Estate,2024-04-25,2024-07-07,2122,8,Algorithmic Solutions -AI02079,Data Scientist,69203,USD,69203,EN,FL,Israel,M,Israel,0,"Spark, Scala, Python, Kubernetes, Docker",Master,0,Manufacturing,2024-02-16,2024-04-03,1738,9.9,Advanced Robotics -AI02080,AI Product Manager,97206,GBP,72905,MI,FL,United Kingdom,M,New Zealand,0,"TensorFlow, Scala, Deep Learning, Statistics, AWS",PhD,2,Consulting,2024-03-04,2024-03-18,1813,9.6,Quantum Computing Inc -AI02081,Data Scientist,82737,USD,82737,SE,CT,China,L,Japan,50,"Python, R, TensorFlow",Bachelor,9,Government,2024-06-06,2024-08-17,2069,9.9,DeepTech Ventures -AI02082,Machine Learning Engineer,99693,USD,99693,SE,PT,Sweden,S,Sweden,0,"Docker, Scala, Git, AWS",PhD,7,Telecommunications,2024-08-29,2024-10-20,1189,8.3,Autonomous Tech -AI02083,Autonomous Systems Engineer,82795,USD,82795,EN,PT,Finland,L,Finland,0,"SQL, Git, PyTorch, Spark, GCP",Associate,1,Transportation,2024-08-22,2024-09-13,1102,9.8,AI Innovations -AI02084,AI Research Scientist,174298,USD,174298,EX,FL,Finland,M,United States,50,"TensorFlow, Kubernetes, Statistics, SQL, AWS",Bachelor,13,Technology,2024-09-06,2024-09-28,721,7,Advanced Robotics -AI02085,Machine Learning Researcher,270830,CHF,243747,EX,PT,Switzerland,M,Switzerland,100,"PyTorch, Kubernetes, Tableau, SQL, Spark",Bachelor,11,Consulting,2024-11-10,2024-12-22,1174,7.1,Predictive Systems -AI02086,Machine Learning Researcher,68593,USD,68593,MI,PT,Israel,M,Israel,50,"Docker, Tableau, GCP",Master,3,Transportation,2024-10-05,2024-12-07,1095,9.1,Cloud AI Solutions -AI02087,Machine Learning Engineer,67495,EUR,57371,EN,PT,Netherlands,S,Netherlands,50,"Python, Kubernetes, Computer Vision",Bachelor,1,Transportation,2025-01-18,2025-03-19,2058,6.2,Smart Analytics -AI02088,AI Product Manager,114616,GBP,85962,MI,FL,United Kingdom,M,United Kingdom,50,"Statistics, Kubernetes, GCP, NLP, TensorFlow",Master,3,Energy,2024-03-25,2024-04-15,869,5.6,Neural Networks Co -AI02089,Data Engineer,213578,USD,213578,EX,CT,Sweden,M,Japan,50,"PyTorch, Kubernetes, Hadoop, R",Associate,15,Energy,2025-04-14,2025-05-03,1459,8.6,Algorithmic Solutions -AI02090,AI Product Manager,212620,USD,212620,EX,CT,Denmark,L,Denmark,0,"GCP, PyTorch, Data Visualization, Computer Vision",Bachelor,16,Education,2024-09-10,2024-11-10,905,9.1,Cloud AI Solutions -AI02091,Computer Vision Engineer,56144,USD,56144,SE,CT,China,M,China,100,"SQL, Docker, PyTorch, Kubernetes",Master,6,Real Estate,2024-02-08,2024-03-04,2052,7.4,AI Innovations -AI02092,Research Scientist,81572,EUR,69336,MI,FL,Austria,L,Luxembourg,0,"Computer Vision, Linux, PyTorch, Scala",Master,2,Healthcare,2024-09-25,2024-10-31,2115,8,AI Innovations -AI02093,Head of AI,69805,EUR,59334,EN,FL,Germany,S,South Korea,100,"SQL, Linux, Java, TensorFlow",PhD,1,Government,2024-07-09,2024-07-27,1396,6.2,Autonomous Tech -AI02094,ML Ops Engineer,134815,EUR,114593,SE,CT,Netherlands,S,Vietnam,100,"Docker, Tableau, Git, Kubernetes",PhD,7,Transportation,2024-07-14,2024-08-13,1842,9.6,TechCorp Inc -AI02095,NLP Engineer,201072,EUR,170911,EX,PT,Germany,S,Norway,100,"Linux, PyTorch, Git, Mathematics, Statistics",Bachelor,12,Education,2025-02-09,2025-03-21,965,6.2,Autonomous Tech -AI02096,AI Research Scientist,295447,JPY,32499170,EX,FL,Japan,L,Japan,50,"Spark, Linux, Statistics, PyTorch",Master,13,Finance,2024-01-31,2024-03-26,2060,5.6,Neural Networks Co -AI02097,Deep Learning Engineer,76720,USD,76720,EX,FL,China,M,China,50,"SQL, Kubernetes, TensorFlow, Scala",Associate,14,Gaming,2025-02-25,2025-04-02,970,7.9,Neural Networks Co -AI02098,Machine Learning Engineer,125533,USD,125533,SE,FL,Denmark,S,Denmark,0,"Deep Learning, Java, Scala",PhD,8,Automotive,2024-10-11,2024-12-01,1268,9.5,Digital Transformation LLC -AI02099,Robotics Engineer,253018,CAD,316273,EX,FT,Canada,L,Nigeria,50,"R, PyTorch, SQL, Scala",Associate,17,Government,2024-12-31,2025-03-06,1852,7.6,Cognitive Computing -AI02100,AI Product Manager,133162,GBP,99872,SE,FT,United Kingdom,S,United Kingdom,50,"Python, NLP, SQL, Linux, Kubernetes",Bachelor,7,Gaming,2025-04-14,2025-05-17,779,7.6,Digital Transformation LLC -AI02101,AI Architect,91600,USD,91600,MI,FL,South Korea,L,South Korea,100,"Python, GCP, Scala, Docker, Computer Vision",PhD,4,Finance,2024-04-26,2024-05-30,621,7.1,DataVision Ltd -AI02102,AI Product Manager,157559,EUR,133925,EX,CT,Austria,L,Austria,0,"Azure, MLOps, Scala, Computer Vision",Bachelor,19,Telecommunications,2025-03-13,2025-05-23,873,7.5,DeepTech Ventures -AI02103,Data Scientist,171584,USD,171584,EX,CT,Finland,M,Finland,100,"PyTorch, Python, Statistics",PhD,13,Education,2024-08-28,2024-09-24,1690,6.8,Autonomous Tech -AI02104,ML Ops Engineer,156785,CAD,195981,EX,FT,Canada,M,Canada,50,"SQL, PyTorch, Linux, Tableau",Bachelor,16,Media,2024-03-31,2024-04-20,2139,6.3,DataVision Ltd -AI02105,Machine Learning Engineer,293023,USD,293023,EX,CT,Denmark,M,Australia,100,"Docker, Computer Vision, Python, NLP, Deep Learning",Master,12,Manufacturing,2024-08-10,2024-10-10,1377,8.6,Smart Analytics -AI02106,Principal Data Scientist,86508,JPY,9515880,EN,FT,Japan,L,Japan,0,"Computer Vision, TensorFlow, GCP",Master,0,Technology,2025-03-28,2025-06-09,1511,8.8,Cloud AI Solutions -AI02107,AI Software Engineer,81412,USD,81412,EX,FT,China,S,Philippines,0,"Tableau, Linux, MLOps, Spark, Mathematics",Master,18,Media,2024-06-10,2024-07-22,1689,8.6,Advanced Robotics -AI02108,NLP Engineer,186673,EUR,158672,EX,FT,Austria,S,Austria,50,"Docker, Linux, SQL",Associate,10,Healthcare,2024-07-12,2024-08-22,1860,10,Advanced Robotics -AI02109,Principal Data Scientist,112912,USD,112912,MI,PT,United States,L,United States,100,"SQL, Spark, Git",Bachelor,4,Education,2024-09-19,2024-10-15,631,8.3,Cloud AI Solutions -AI02110,Principal Data Scientist,51942,USD,51942,EN,PT,Sweden,M,Japan,0,"R, Linux, Git, GCP, Deep Learning",PhD,0,Energy,2024-01-24,2024-02-27,828,6,Quantum Computing Inc -AI02111,Research Scientist,127418,USD,127418,MI,FT,Norway,M,Norway,0,"Hadoop, Java, Data Visualization",Associate,3,Automotive,2025-03-05,2025-04-16,1167,6.1,Machine Intelligence Group -AI02112,Research Scientist,96844,USD,96844,EN,CT,Denmark,L,Denmark,50,"MLOps, Kubernetes, Python, TensorFlow, PyTorch",Bachelor,0,Finance,2025-01-23,2025-03-03,2403,7.9,Autonomous Tech -AI02113,Principal Data Scientist,205497,USD,205497,EX,PT,Norway,M,Belgium,100,"Spark, TensorFlow, Data Visualization",Master,13,Automotive,2024-03-12,2024-04-14,990,5.2,Future Systems -AI02114,Machine Learning Researcher,36123,USD,36123,MI,FT,China,S,China,50,"R, SQL, Git, PyTorch",Associate,3,Manufacturing,2025-01-10,2025-02-18,812,9.3,Quantum Computing Inc -AI02115,Data Engineer,26530,USD,26530,EN,PT,China,S,China,0,"Scala, MLOps, SQL",Master,0,Automotive,2025-03-26,2025-04-25,2428,7.5,DataVision Ltd -AI02116,Deep Learning Engineer,118399,CAD,147999,SE,FL,Canada,L,Canada,50,"PyTorch, Scala, R",Master,9,Technology,2024-09-27,2024-11-05,2031,6.9,Cloud AI Solutions -AI02117,Data Analyst,100255,GBP,75191,MI,FT,United Kingdom,M,India,100,"Git, SQL, TensorFlow",Bachelor,2,Consulting,2025-04-25,2025-05-14,1999,8.9,Smart Analytics -AI02118,Research Scientist,129800,SGD,168740,SE,FT,Singapore,L,Singapore,100,"SQL, Computer Vision, Tableau, Python",Associate,6,Consulting,2025-03-18,2025-05-11,1202,8.2,DataVision Ltd -AI02119,Data Engineer,165833,AUD,223875,SE,PT,Australia,L,Australia,100,"NLP, Hadoop, Tableau, TensorFlow, SQL",Associate,8,Consulting,2024-12-31,2025-03-13,604,8.2,DataVision Ltd -AI02120,Computer Vision Engineer,84617,EUR,71924,MI,FL,France,L,France,50,"Azure, Java, Statistics",Master,3,Healthcare,2024-06-24,2024-07-15,1313,8.4,DeepTech Ventures -AI02121,AI Product Manager,228358,USD,228358,EX,FL,Sweden,M,Sweden,50,"TensorFlow, SQL, Python, GCP",Master,19,Transportation,2024-10-01,2024-11-15,849,5.3,Predictive Systems -AI02122,Deep Learning Engineer,89402,CHF,80462,EN,FT,Switzerland,S,Ireland,100,"Java, Git, Kubernetes, Scala, Mathematics",Associate,0,Real Estate,2024-03-28,2024-05-18,1854,8.7,Digital Transformation LLC -AI02123,AI Software Engineer,251892,USD,251892,EX,FT,Finland,L,Finland,100,"Spark, Python, Computer Vision, Data Visualization",Master,14,Technology,2024-07-22,2024-08-20,1045,7.9,Algorithmic Solutions -AI02124,NLP Engineer,91223,USD,91223,MI,PT,Ireland,L,Ireland,100,"Python, R, Statistics, GCP",Associate,4,Energy,2024-06-14,2024-08-24,1730,5.3,Algorithmic Solutions -AI02125,Robotics Engineer,178163,EUR,151439,EX,FL,France,L,France,100,"Linux, Hadoop, NLP, Kubernetes",Bachelor,18,Media,2024-07-07,2024-08-30,610,7.8,Cognitive Computing -AI02126,Machine Learning Researcher,110328,USD,110328,MI,FL,Denmark,M,Denmark,50,"AWS, Data Visualization, Tableau, TensorFlow",Bachelor,2,Energy,2024-11-04,2025-01-02,2362,5.9,DeepTech Ventures -AI02127,Research Scientist,80058,USD,80058,EN,CT,Norway,L,Norway,0,"SQL, PyTorch, Statistics, NLP",Master,0,Consulting,2025-04-13,2025-05-08,2081,8.4,AI Innovations -AI02128,Machine Learning Researcher,81768,USD,81768,SE,CT,China,L,China,100,"Git, R, Computer Vision",Master,7,Consulting,2025-03-10,2025-04-23,1020,5.1,Digital Transformation LLC -AI02129,Computer Vision Engineer,273957,EUR,232863,EX,FT,Netherlands,L,Netherlands,100,"Kubernetes, Azure, Spark, GCP",PhD,13,Government,2024-07-10,2024-08-28,589,7,Advanced Robotics -AI02130,Principal Data Scientist,71171,JPY,7828810,MI,CT,Japan,S,Japan,100,"Python, Statistics, Scala, Git",Master,2,Gaming,2025-03-24,2025-04-30,2269,8.9,AI Innovations -AI02131,Research Scientist,262050,EUR,222743,EX,CT,Netherlands,M,China,50,"Python, R, Tableau, Mathematics, GCP",Bachelor,19,Real Estate,2024-05-09,2024-06-14,2049,6.9,Digital Transformation LLC -AI02132,Principal Data Scientist,74346,JPY,8178060,EN,FL,Japan,S,Japan,50,"Git, MLOps, Python, Scala, Computer Vision",Associate,0,Technology,2024-07-31,2024-08-26,1392,5.6,Cognitive Computing -AI02133,AI Architect,26055,USD,26055,EN,FT,India,M,United States,100,"Python, AWS, Data Visualization, NLP",Master,1,Manufacturing,2025-02-04,2025-04-14,2432,5.8,Smart Analytics -AI02134,Autonomous Systems Engineer,113953,USD,113953,MI,FT,Israel,L,Israel,50,"GCP, PyTorch, Tableau",Bachelor,2,Healthcare,2024-07-07,2024-09-05,1361,9.1,Cloud AI Solutions -AI02135,Data Engineer,176525,GBP,132394,SE,CT,United Kingdom,L,United Kingdom,0,"R, Scala, Data Visualization, Linux, PyTorch",Associate,7,Manufacturing,2024-03-15,2024-04-28,2353,9.3,Advanced Robotics -AI02136,Robotics Engineer,137979,CHF,124181,SE,CT,Switzerland,S,Netherlands,0,"Linux, Python, TensorFlow",Bachelor,6,Gaming,2024-10-26,2024-12-29,1773,9.3,Cloud AI Solutions -AI02137,Data Engineer,232117,GBP,174088,EX,PT,United Kingdom,M,United Kingdom,100,"Computer Vision, SQL, Java",Master,15,Government,2024-11-21,2024-12-16,945,6.7,Cognitive Computing -AI02138,Data Analyst,130819,USD,130819,EX,FT,Finland,M,Finland,100,"Java, R, Mathematics",PhD,15,Telecommunications,2024-09-08,2024-10-04,1792,8.5,Neural Networks Co -AI02139,Machine Learning Engineer,245291,GBP,183968,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Python, Docker, Linux, NLP",Master,17,Telecommunications,2024-11-21,2025-01-19,1549,9.1,Future Systems -AI02140,NLP Engineer,121783,EUR,103516,SE,CT,France,M,Colombia,0,"Mathematics, PyTorch, SQL, Linux",PhD,5,Energy,2024-03-19,2024-04-09,2367,9.4,Cloud AI Solutions -AI02141,Machine Learning Engineer,145307,SGD,188899,SE,PT,Singapore,S,Chile,0,"Scala, Hadoop, MLOps, NLP, Java",Bachelor,5,Gaming,2024-05-17,2024-07-17,1974,8.5,Future Systems -AI02142,Robotics Engineer,77107,USD,77107,EN,FL,Norway,M,Norway,50,"Tableau, Kubernetes, Data Visualization",Bachelor,0,Consulting,2024-08-12,2024-08-30,527,5.8,Digital Transformation LLC -AI02143,AI Architect,67501,CAD,84376,EN,CT,Canada,S,Canada,0,"NLP, Tableau, Scala, PyTorch, SQL",PhD,1,Technology,2024-12-23,2025-02-20,720,6.4,Algorithmic Solutions -AI02144,Robotics Engineer,67669,USD,67669,EX,CT,China,M,China,100,"Deep Learning, Docker, Tableau",Bachelor,14,Gaming,2024-04-28,2024-06-09,1412,9.3,Cognitive Computing -AI02145,Head of AI,100999,EUR,85849,MI,FL,France,L,France,0,"MLOps, PyTorch, Kubernetes, Azure",Associate,2,Energy,2024-02-09,2024-04-02,2384,6.4,Algorithmic Solutions -AI02146,AI Consultant,57275,USD,57275,SE,CT,China,L,China,0,"Python, R, Azure",Associate,7,Real Estate,2025-01-23,2025-04-01,1686,9.4,Quantum Computing Inc -AI02147,Data Analyst,116317,USD,116317,EX,FT,Finland,S,Finland,0,"Data Visualization, Hadoop, Spark, Azure",Master,19,Energy,2024-01-24,2024-03-13,2115,5.8,Algorithmic Solutions -AI02148,Autonomous Systems Engineer,72220,USD,72220,EN,FT,United States,S,Argentina,50,"Statistics, Kubernetes, Mathematics",Bachelor,1,Education,2024-04-01,2024-05-18,1403,9.8,Autonomous Tech -AI02149,Computer Vision Engineer,48520,USD,48520,MI,CT,China,L,China,0,"Data Visualization, Python, TensorFlow, GCP, PyTorch",Associate,4,Transportation,2024-08-17,2024-09-03,1182,8.9,Predictive Systems -AI02150,AI Architect,91794,SGD,119332,MI,FT,Singapore,S,Russia,100,"Docker, Python, TensorFlow",Associate,4,Government,2024-10-23,2024-11-18,1817,9.2,Machine Intelligence Group -AI02151,Head of AI,148235,EUR,126000,SE,FL,Netherlands,L,Ireland,100,"Data Visualization, TensorFlow, Docker, Git",Associate,7,Manufacturing,2024-08-20,2024-09-07,2094,6.2,Neural Networks Co -AI02152,AI Software Engineer,63004,EUR,53553,EN,FL,Germany,S,Germany,100,"Azure, PyTorch, Docker, Kubernetes",PhD,1,Healthcare,2025-03-17,2025-04-28,1850,8.4,Future Systems -AI02153,Principal Data Scientist,256279,USD,256279,EX,PT,Finland,L,Finland,0,"Kubernetes, Python, Java, Linux",Master,13,Healthcare,2024-11-17,2025-01-25,573,6.5,Cognitive Computing -AI02154,Machine Learning Engineer,100220,USD,100220,MI,PT,United States,M,United States,100,"Kubernetes, Git, Scala, Statistics, GCP",Bachelor,2,Automotive,2025-03-09,2025-04-19,1993,9.5,Advanced Robotics -AI02155,Deep Learning Engineer,97614,CAD,122018,SE,CT,Canada,S,Canada,50,"Azure, Scala, SQL, Git",Master,7,Healthcare,2024-06-05,2024-06-25,1140,9.9,Cognitive Computing -AI02156,Data Engineer,128100,USD,128100,SE,FL,Sweden,S,Switzerland,100,"Python, AWS, Git, MLOps",PhD,7,Consulting,2024-09-05,2024-09-24,1215,10,Cloud AI Solutions -AI02157,AI Specialist,78590,USD,78590,EN,FL,Denmark,M,Denmark,50,"Python, Data Visualization, TensorFlow",Bachelor,0,Transportation,2025-03-11,2025-04-11,1220,8.7,DataVision Ltd -AI02158,Research Scientist,56489,USD,56489,EN,CT,United States,S,India,0,"Hadoop, Scala, Tableau, GCP",Master,0,Consulting,2024-08-10,2024-09-05,501,8.1,Predictive Systems -AI02159,Head of AI,145462,GBP,109097,SE,PT,United Kingdom,S,United Kingdom,100,"Git, NLP, Azure",PhD,9,Energy,2025-03-15,2025-05-09,2279,5.1,Quantum Computing Inc -AI02160,Robotics Engineer,114141,USD,114141,SE,FT,South Korea,M,South Korea,100,"Git, Java, Deep Learning, Scala, Mathematics",Master,9,Transportation,2024-03-30,2024-04-17,1412,8.6,Digital Transformation LLC -AI02161,Data Scientist,122099,USD,122099,SE,PT,Israel,S,Israel,100,"Azure, GCP, Python, TensorFlow",Bachelor,9,Media,2024-04-29,2024-06-30,1064,5.2,Digital Transformation LLC -AI02162,Data Engineer,109552,SGD,142418,SE,PT,Singapore,M,Singapore,0,"Linux, SQL, Kubernetes, Azure, Python",Master,7,Telecommunications,2024-08-28,2024-10-17,897,5.1,DeepTech Ventures -AI02163,AI Product Manager,57229,EUR,48645,EN,FT,Germany,S,Germany,0,"Kubernetes, Spark, Computer Vision, PyTorch",Associate,1,Manufacturing,2024-08-22,2024-10-10,831,6.6,Quantum Computing Inc -AI02164,NLP Engineer,174350,EUR,148198,EX,FL,France,M,France,100,"Kubernetes, SQL, Docker, Spark, R",Master,12,Technology,2024-08-14,2024-08-29,2021,6.8,Cognitive Computing -AI02165,AI Consultant,131413,USD,131413,SE,FL,Finland,L,Finland,0,"Java, GCP, Kubernetes",Master,6,Media,2024-05-26,2024-07-15,2012,5.7,Algorithmic Solutions -AI02166,NLP Engineer,109502,CAD,136878,SE,FT,Canada,S,Canada,100,"Data Visualization, SQL, R, PyTorch",Associate,7,Education,2025-04-21,2025-06-27,1888,7.3,DataVision Ltd -AI02167,Autonomous Systems Engineer,29846,USD,29846,MI,FL,India,S,India,50,"Spark, Deep Learning, Computer Vision",Master,4,Finance,2024-08-31,2024-10-06,2061,7.4,Future Systems -AI02168,Computer Vision Engineer,155786,USD,155786,SE,FT,Denmark,M,Portugal,0,"R, Computer Vision, Linux, Deep Learning",Master,8,Transportation,2025-04-12,2025-05-06,2317,5.1,Algorithmic Solutions -AI02169,Data Scientist,84770,USD,84770,EX,FT,India,M,India,100,"AWS, Tableau, Git, Deep Learning",Bachelor,17,Finance,2024-11-25,2024-12-28,1787,7.4,Algorithmic Solutions -AI02170,Computer Vision Engineer,89112,USD,89112,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Java, Python",PhD,2,Technology,2024-07-22,2024-08-06,669,6.1,DeepTech Ventures -AI02171,AI Specialist,104744,USD,104744,EN,FT,Denmark,L,United States,0,"Docker, Python, Scala",Master,1,Technology,2025-01-27,2025-04-03,2167,8,Predictive Systems -AI02172,Data Analyst,199544,USD,199544,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Docker, Hadoop, GCP, Linux",Bachelor,11,Education,2025-03-11,2025-04-01,2130,9.5,Quantum Computing Inc -AI02173,Machine Learning Engineer,93564,EUR,79529,MI,CT,France,S,Hungary,100,"SQL, Azure, Tableau, Java, Statistics",Bachelor,3,Energy,2024-01-05,2024-02-03,1181,6,AI Innovations -AI02174,AI Specialist,109257,AUD,147497,MI,PT,Australia,M,Australia,100,"Linux, Git, Statistics, R",PhD,2,Energy,2024-09-15,2024-11-10,1854,8.5,Advanced Robotics -AI02175,AI Product Manager,233827,EUR,198753,EX,FT,Austria,L,Sweden,100,"Kubernetes, R, SQL, AWS",Associate,19,Retail,2024-04-17,2024-05-09,2089,8.7,Algorithmic Solutions -AI02176,AI Specialist,199622,USD,199622,SE,CT,United States,L,United States,0,"TensorFlow, Deep Learning, MLOps, Git, Kubernetes",PhD,8,Consulting,2024-11-04,2024-11-25,1993,10,Cognitive Computing -AI02177,Data Analyst,158846,USD,158846,EX,PT,Sweden,S,Ukraine,50,"Python, Git, Scala, NLP",Bachelor,10,Technology,2025-03-29,2025-04-20,1386,9.9,Neural Networks Co -AI02178,AI Software Engineer,43785,USD,43785,EN,PT,Israel,S,Israel,100,"Statistics, SQL, Spark, Tableau",Bachelor,0,Telecommunications,2024-05-23,2024-07-07,2022,8.6,Neural Networks Co -AI02179,AI Architect,101184,USD,101184,EX,PT,China,S,Estonia,100,"Data Visualization, Docker, Python, Kubernetes",Master,10,Healthcare,2025-03-16,2025-04-20,513,8.3,Machine Intelligence Group -AI02180,Principal Data Scientist,89965,USD,89965,EX,FT,India,L,India,0,"Python, SQL, Computer Vision, Docker, Java",Associate,16,Manufacturing,2025-02-21,2025-03-20,2467,7.2,AI Innovations -AI02181,Principal Data Scientist,73352,SGD,95358,EN,PT,Singapore,L,Brazil,50,"Docker, Data Visualization, Python, Mathematics, R",Bachelor,0,Finance,2025-02-14,2025-04-08,954,7,Digital Transformation LLC -AI02182,Head of AI,199823,USD,199823,EX,CT,Finland,L,India,0,"Azure, Computer Vision, TensorFlow",Bachelor,11,Transportation,2024-07-22,2024-08-20,2424,5.4,Neural Networks Co -AI02183,ML Ops Engineer,77392,GBP,58044,EN,FL,United Kingdom,M,Latvia,50,"Python, Azure, TensorFlow, Statistics, AWS",PhD,1,Technology,2024-02-26,2024-04-01,841,6.5,Algorithmic Solutions -AI02184,Machine Learning Researcher,75898,CAD,94873,EN,FT,Canada,M,Portugal,0,"Git, PyTorch, SQL, Python",PhD,0,Education,2024-02-03,2024-03-26,1178,8.2,AI Innovations -AI02185,Data Analyst,76715,USD,76715,EN,PT,Israel,L,Israel,50,"Tableau, Hadoop, Deep Learning",PhD,0,Energy,2025-03-24,2025-05-12,756,6.7,DataVision Ltd -AI02186,Machine Learning Engineer,99717,JPY,10968870,MI,PT,Japan,M,Japan,50,"GCP, Azure, Linux, Scala",Master,3,Media,2024-02-18,2024-04-11,1134,7.3,Neural Networks Co -AI02187,AI Research Scientist,181613,USD,181613,EX,FL,Israel,L,Israel,50,"Scala, Linux, Java",Bachelor,11,Consulting,2024-08-02,2024-09-21,514,7.4,Cloud AI Solutions -AI02188,Autonomous Systems Engineer,109710,EUR,93254,MI,PT,Netherlands,L,Australia,100,"SQL, Linux, PyTorch, NLP",Bachelor,2,Energy,2024-04-06,2024-04-27,2356,6.3,Digital Transformation LLC -AI02189,AI Product Manager,195849,JPY,21543390,EX,PT,Japan,L,Japan,0,"Scala, Statistics, NLP",PhD,11,Finance,2024-03-18,2024-05-17,1271,6.8,Future Systems -AI02190,Data Scientist,125807,USD,125807,SE,FT,Sweden,L,Indonesia,0,"Python, Data Visualization, Docker, NLP",PhD,8,Media,2024-05-05,2024-05-31,1151,5.8,Digital Transformation LLC -AI02191,Research Scientist,104357,CHF,93921,MI,PT,Switzerland,M,Switzerland,100,"Java, AWS, Mathematics, Hadoop",Master,3,Government,2025-01-23,2025-02-10,1996,9.6,Smart Analytics -AI02192,Data Scientist,176952,EUR,150409,EX,CT,Netherlands,S,Netherlands,50,"Java, MLOps, R, Linux, NLP",Master,12,Transportation,2025-02-24,2025-03-12,2382,9.7,Smart Analytics -AI02193,Head of AI,57405,EUR,48794,EN,FL,France,M,France,100,"PyTorch, Computer Vision, Git, Azure, Scala",Master,1,Technology,2024-08-31,2024-09-26,605,7,Quantum Computing Inc -AI02194,Data Analyst,130621,EUR,111028,EX,FL,France,S,France,0,"Linux, Hadoop, Python, Computer Vision, Git",PhD,16,Real Estate,2024-05-13,2024-07-22,1072,8.9,Smart Analytics -AI02195,Research Scientist,78485,CAD,98106,EN,PT,Canada,L,Canada,0,"Scala, SQL, Statistics, Hadoop",PhD,0,Retail,2024-07-27,2024-09-20,1057,8,AI Innovations -AI02196,AI Consultant,200595,CHF,180536,SE,CT,Switzerland,M,South Africa,50,"Hadoop, Python, Deep Learning, Azure",Master,5,Media,2024-05-20,2024-07-12,2146,9.2,DeepTech Ventures -AI02197,AI Architect,50119,EUR,42601,EN,FL,France,M,France,0,"Docker, Azure, Computer Vision",PhD,1,Energy,2025-01-03,2025-03-01,2042,5.7,Smart Analytics -AI02198,Computer Vision Engineer,78348,EUR,66596,EN,FL,Germany,L,Czech Republic,0,"Tableau, Java, Kubernetes",Master,1,Finance,2024-08-22,2024-09-09,867,7.6,TechCorp Inc -AI02199,AI Software Engineer,158752,USD,158752,MI,FL,Norway,L,China,0,"Python, GCP, TensorFlow, Computer Vision, PyTorch",PhD,2,Energy,2024-02-19,2024-04-02,751,8.1,Smart Analytics -AI02200,Data Scientist,35696,USD,35696,MI,CT,India,L,India,100,"Scala, TensorFlow, Python, Computer Vision, Kubernetes",PhD,3,Transportation,2024-12-22,2025-02-17,2146,9.8,DataVision Ltd -AI02201,AI Architect,81558,AUD,110103,MI,PT,Australia,S,Portugal,50,"Python, Kubernetes, Deep Learning, AWS, MLOps",Master,4,Media,2024-06-03,2024-07-17,1216,9.3,Cognitive Computing -AI02202,AI Architect,240445,JPY,26448950,EX,PT,Japan,L,Japan,0,"Data Visualization, NLP, Python",PhD,12,Finance,2024-10-11,2024-12-10,2060,5.2,Predictive Systems -AI02203,Research Scientist,60197,USD,60197,SE,FT,China,M,Indonesia,100,"PyTorch, NLP, Hadoop, Statistics, Kubernetes",Master,5,Energy,2024-04-26,2024-07-06,2308,5.2,Machine Intelligence Group -AI02204,Deep Learning Engineer,67887,USD,67887,EN,FT,Norway,M,Norway,0,"PyTorch, Java, Spark, Hadoop, GCP",Bachelor,1,Transportation,2024-11-20,2025-01-22,1444,7.6,Autonomous Tech -AI02205,AI Research Scientist,251281,CAD,314101,EX,FL,Canada,L,Canada,50,"Data Visualization, Python, Azure, Scala, Spark",PhD,11,Transportation,2024-09-16,2024-11-14,1947,8.9,AI Innovations -AI02206,Data Engineer,266985,CHF,240287,EX,CT,Switzerland,L,New Zealand,50,"Tableau, PyTorch, Statistics",PhD,19,Automotive,2025-04-11,2025-04-25,889,7.1,Machine Intelligence Group -AI02207,AI Consultant,129783,EUR,110316,MI,FL,Netherlands,L,Netherlands,0,"Spark, Git, Statistics, PyTorch",Associate,4,Education,2024-01-11,2024-03-22,1435,6.1,Neural Networks Co -AI02208,Data Analyst,79996,GBP,59997,EN,FL,United Kingdom,L,United Kingdom,100,"Azure, GCP, Data Visualization",PhD,1,Healthcare,2024-08-22,2024-10-25,2334,8.6,Autonomous Tech -AI02209,Data Engineer,86496,CAD,108120,MI,FT,Canada,S,Canada,100,"Scala, Java, Mathematics, AWS, TensorFlow",PhD,2,Government,2025-01-17,2025-02-19,777,8.7,Advanced Robotics -AI02210,ML Ops Engineer,114996,USD,114996,MI,FT,Israel,L,Israel,50,"Scala, NLP, Hadoop",Master,4,Technology,2024-10-05,2024-11-13,820,5.7,Predictive Systems -AI02211,AI Architect,124110,USD,124110,SE,FL,Israel,L,Israel,0,"GCP, R, Tableau, Data Visualization, Scala",Bachelor,8,Media,2025-01-09,2025-03-08,975,5.6,Autonomous Tech -AI02212,AI Software Engineer,99108,USD,99108,SE,FT,South Korea,S,South Korea,100,"TensorFlow, Azure, Java, PyTorch, Computer Vision",Bachelor,5,Finance,2024-11-07,2024-12-28,895,6.2,Future Systems -AI02213,AI Product Manager,141155,CHF,127040,MI,PT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Tableau",PhD,3,Real Estate,2024-01-09,2024-02-05,1858,6.8,Future Systems -AI02214,AI Product Manager,71602,USD,71602,EN,FT,Ireland,M,Ireland,100,"Git, Computer Vision, Python, TensorFlow, NLP",Associate,1,Manufacturing,2024-06-14,2024-07-14,1203,7.7,Algorithmic Solutions -AI02215,Machine Learning Researcher,99305,USD,99305,EN,FT,Norway,L,Norway,100,"Kubernetes, SQL, NLP, Statistics",Master,1,Finance,2024-03-17,2024-05-29,1286,7.3,Digital Transformation LLC -AI02216,Machine Learning Engineer,268561,EUR,228277,EX,FT,France,L,India,0,"Git, Python, TensorFlow, Linux",PhD,17,Gaming,2025-02-19,2025-03-12,2172,6.4,AI Innovations -AI02217,AI Software Engineer,101510,CHF,91359,EN,CT,Switzerland,L,Austria,100,"SQL, Hadoop, PyTorch, Deep Learning",PhD,0,Gaming,2024-02-10,2024-03-04,1555,7,Machine Intelligence Group -AI02218,Principal Data Scientist,270963,USD,270963,EX,CT,Denmark,L,Austria,0,"MLOps, Statistics, GCP, PyTorch, Scala",PhD,13,Transportation,2024-10-20,2024-12-23,2253,6.3,Autonomous Tech -AI02219,AI Specialist,79001,USD,79001,MI,CT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker",PhD,4,Retail,2024-10-15,2024-12-18,1577,8.2,Machine Intelligence Group -AI02220,Principal Data Scientist,51039,GBP,38279,EN,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, R, Computer Vision",Master,0,Energy,2024-07-10,2024-08-23,527,5.9,Digital Transformation LLC -AI02221,ML Ops Engineer,86750,EUR,73738,EN,PT,Netherlands,L,Austria,50,"Java, Linux, Azure, GCP",Master,1,Energy,2025-04-21,2025-06-24,2026,8.5,DeepTech Ventures -AI02222,Research Scientist,52962,CAD,66203,EN,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Data Visualization, Python, Spark",Associate,1,Telecommunications,2024-07-20,2024-09-30,1427,6.8,Smart Analytics -AI02223,AI Software Engineer,253468,USD,253468,EX,CT,Sweden,M,Sweden,100,"Scala, R, Data Visualization, NLP, Python",Bachelor,19,Gaming,2024-08-12,2024-10-03,2402,7.5,TechCorp Inc -AI02224,AI Specialist,122016,EUR,103714,SE,PT,Germany,L,Australia,50,"Kubernetes, Hadoop, Tableau, PyTorch",Bachelor,7,Education,2024-11-10,2024-11-24,2156,9.1,Smart Analytics -AI02225,Research Scientist,51691,AUD,69783,EN,FT,Australia,S,Malaysia,50,"PyTorch, Linux, Git, TensorFlow, Deep Learning",PhD,1,Manufacturing,2024-03-11,2024-04-11,2158,9.4,DeepTech Ventures -AI02226,Principal Data Scientist,119127,USD,119127,EX,FT,Israel,S,Israel,0,"SQL, Tableau, MLOps",PhD,13,Finance,2025-02-01,2025-04-03,2048,6.3,Autonomous Tech -AI02227,Computer Vision Engineer,190161,USD,190161,EX,FL,Israel,S,Israel,100,"Azure, AWS, Statistics, GCP, Tableau",Associate,15,Technology,2024-05-12,2024-06-23,741,7.6,Smart Analytics -AI02228,Computer Vision Engineer,241186,USD,241186,EX,FT,Denmark,S,Denmark,0,"SQL, TensorFlow, Mathematics",PhD,14,Telecommunications,2024-09-23,2024-11-03,2069,6.3,Advanced Robotics -AI02229,Research Scientist,103949,CAD,129936,SE,CT,Canada,M,Czech Republic,50,"Kubernetes, Java, Data Visualization, MLOps",Associate,8,Education,2024-09-05,2024-10-20,1017,7.6,Smart Analytics -AI02230,Deep Learning Engineer,199232,USD,199232,EX,FT,Sweden,M,Sweden,100,"PyTorch, Data Visualization, Deep Learning",Bachelor,14,Government,2024-06-01,2024-06-18,1509,7.4,Advanced Robotics -AI02231,AI Research Scientist,157050,USD,157050,EX,PT,Sweden,S,Finland,0,"Tableau, Hadoop, R, Linux",PhD,17,Retail,2024-08-19,2024-09-18,852,7.4,Predictive Systems -AI02232,Computer Vision Engineer,84353,USD,84353,MI,PT,Israel,S,Luxembourg,0,"Azure, AWS, Computer Vision",Bachelor,2,Media,2024-08-26,2024-10-07,1724,7.8,Machine Intelligence Group -AI02233,Robotics Engineer,192697,USD,192697,EX,CT,Denmark,S,Denmark,50,"Java, PyTorch, Mathematics, Data Visualization, SQL",Master,12,Healthcare,2025-02-14,2025-03-09,2434,8.7,DeepTech Ventures -AI02234,NLP Engineer,154367,CAD,192959,SE,FT,Canada,L,Mexico,100,"Git, SQL, GCP, Tableau",PhD,5,Transportation,2024-12-12,2025-01-18,1287,5.1,Neural Networks Co -AI02235,Principal Data Scientist,305641,CHF,275077,EX,PT,Switzerland,S,Switzerland,0,"R, NLP, MLOps, Scala, Docker",Master,19,Transportation,2024-12-26,2025-03-08,674,7.7,Neural Networks Co -AI02236,Computer Vision Engineer,337542,CHF,303788,EX,FL,Switzerland,L,Netherlands,50,"Python, NLP, Tableau",PhD,15,Real Estate,2024-10-26,2025-01-07,1813,6.9,Machine Intelligence Group -AI02237,AI Software Engineer,82530,USD,82530,MI,CT,Finland,M,Germany,100,"Java, GCP, Kubernetes, MLOps",Bachelor,2,Technology,2024-08-13,2024-08-27,1062,5.3,Future Systems -AI02238,AI Specialist,183461,USD,183461,EX,CT,South Korea,L,South Korea,100,"Hadoop, Deep Learning, Data Visualization, Java",PhD,10,Telecommunications,2024-07-15,2024-09-08,2037,7.7,Digital Transformation LLC -AI02239,ML Ops Engineer,112033,USD,112033,SE,CT,Israel,M,Israel,50,"GCP, SQL, Data Visualization, Linux, Scala",Bachelor,9,Transportation,2024-01-29,2024-02-19,775,9.4,Cognitive Computing -AI02240,Deep Learning Engineer,121109,EUR,102943,MI,FL,Germany,L,India,100,"PyTorch, Tableau, MLOps, Linux",PhD,3,Healthcare,2024-07-13,2024-09-06,1184,6.8,Digital Transformation LLC -AI02241,NLP Engineer,208944,EUR,177602,EX,FT,Austria,S,Austria,100,"Data Visualization, R, AWS, Azure",Bachelor,16,Technology,2024-09-27,2024-10-27,924,5.5,AI Innovations -AI02242,AI Product Manager,60646,CAD,75808,EN,PT,Canada,L,Canada,50,"TensorFlow, MLOps, Python, AWS",Master,1,Gaming,2024-01-17,2024-03-29,1189,6.8,Neural Networks Co -AI02243,AI Architect,83782,EUR,71215,MI,FT,Germany,M,Germany,100,"Kubernetes, Statistics, MLOps",Associate,2,Transportation,2024-07-14,2024-07-31,1645,7,Algorithmic Solutions -AI02244,Research Scientist,130792,USD,130792,EX,FL,Finland,S,United Kingdom,0,"Spark, Kubernetes, Data Visualization, Python, Linux",Associate,14,Gaming,2025-04-11,2025-04-26,697,8.4,AI Innovations -AI02245,Head of AI,98316,USD,98316,SE,FL,South Korea,M,South Korea,50,"Linux, Hadoop, SQL",Associate,9,Education,2025-02-16,2025-03-14,1669,7.8,Digital Transformation LLC -AI02246,AI Software Engineer,157782,EUR,134115,SE,PT,Netherlands,M,Netherlands,100,"Git, Python, SQL, Deep Learning, Spark",Bachelor,9,Retail,2025-01-01,2025-02-27,709,5.6,Smart Analytics -AI02247,Computer Vision Engineer,54428,USD,54428,EN,PT,South Korea,M,Netherlands,50,"TensorFlow, Mathematics, Tableau, Kubernetes, Linux",Master,0,Manufacturing,2024-10-26,2024-11-19,1158,5.2,DeepTech Ventures -AI02248,Autonomous Systems Engineer,90867,EUR,77237,MI,FT,Germany,L,Germany,50,"Azure, Git, Hadoop",PhD,2,Education,2025-04-16,2025-06-04,634,9.7,Advanced Robotics -AI02249,Machine Learning Researcher,67221,EUR,57138,EN,FT,Austria,S,Austria,50,"Scala, Hadoop, Computer Vision, GCP",Master,1,Technology,2024-05-05,2024-05-29,2072,7.1,Digital Transformation LLC -AI02250,Principal Data Scientist,154303,EUR,131158,EX,FL,France,M,France,100,"Linux, Git, Tableau",Master,17,Manufacturing,2024-05-23,2024-06-22,2153,7.8,Cloud AI Solutions -AI02251,Data Engineer,100244,CHF,90220,EN,FT,Switzerland,S,Russia,0,"Kubernetes, Java, Docker",Associate,1,Healthcare,2025-03-16,2025-05-11,1905,9.8,Machine Intelligence Group -AI02252,Principal Data Scientist,135424,USD,135424,SE,PT,Denmark,S,New Zealand,100,"Tableau, Azure, Git",PhD,5,Automotive,2024-07-08,2024-08-16,562,7,Quantum Computing Inc -AI02253,AI Research Scientist,61375,EUR,52169,EN,PT,France,S,France,100,"Computer Vision, Python, TensorFlow",Bachelor,0,Automotive,2024-12-20,2025-02-24,1802,9.5,Algorithmic Solutions -AI02254,AI Consultant,113261,USD,113261,MI,PT,Sweden,L,Sweden,0,"Tableau, Python, GCP, TensorFlow",PhD,4,Real Estate,2024-12-04,2025-01-12,1918,8.7,Autonomous Tech -AI02255,AI Product Manager,114736,EUR,97526,SE,PT,Austria,S,Mexico,0,"Python, Computer Vision, GCP, MLOps, Data Visualization",Master,9,Government,2024-04-21,2024-05-08,2032,5.1,Machine Intelligence Group -AI02256,NLP Engineer,48296,USD,48296,MI,PT,China,M,Chile,50,"SQL, Java, Python",Associate,2,Government,2024-08-27,2024-11-01,1041,6.4,Cognitive Computing -AI02257,AI Software Engineer,205168,USD,205168,EX,CT,Sweden,L,Sweden,100,"Spark, TensorFlow, NLP, Computer Vision",Associate,10,Real Estate,2024-10-27,2024-11-15,2325,7.7,Cognitive Computing -AI02258,Data Engineer,44379,USD,44379,SE,FL,China,S,China,0,"Python, Docker, Tableau, Kubernetes",Bachelor,7,Energy,2024-03-28,2024-05-16,2495,6.4,Neural Networks Co -AI02259,Head of AI,89555,AUD,120899,EN,FL,Australia,L,Austria,100,"Azure, Git, Computer Vision, SQL, Scala",Master,1,Telecommunications,2025-01-28,2025-02-28,608,8.8,Cloud AI Solutions -AI02260,Head of AI,186544,CAD,233180,EX,FL,Canada,L,South Africa,0,"AWS, Spark, PyTorch, Linux",Master,15,Automotive,2024-08-14,2024-09-08,990,9.5,Autonomous Tech -AI02261,Deep Learning Engineer,130260,USD,130260,MI,FL,Norway,M,Norway,50,"AWS, Deep Learning, Java, Linux",Associate,3,Finance,2024-04-28,2024-06-13,543,5.1,TechCorp Inc -AI02262,AI Specialist,61880,USD,61880,EX,FT,India,S,India,100,"Spark, Git, Scala",Bachelor,14,Media,2025-01-05,2025-03-18,2089,6.2,Smart Analytics -AI02263,Robotics Engineer,185105,EUR,157339,EX,FT,France,M,France,50,"TensorFlow, Data Visualization, Spark",PhD,11,Real Estate,2024-11-11,2024-12-16,944,6,Neural Networks Co -AI02264,AI Consultant,60068,EUR,51058,EN,CT,Netherlands,M,Netherlands,0,"Docker, Git, R, Linux, Scala",Bachelor,1,Technology,2024-03-07,2024-03-23,1856,5.8,Quantum Computing Inc -AI02265,AI Product Manager,152832,JPY,16811520,SE,FL,Japan,L,Japan,100,"Linux, PyTorch, TensorFlow",Master,9,Consulting,2025-02-01,2025-03-15,2241,7.9,TechCorp Inc -AI02266,AI Consultant,163684,AUD,220973,SE,CT,Australia,L,Belgium,0,"TensorFlow, Python, Spark, Java",Associate,5,Automotive,2024-05-01,2024-07-04,2186,9.7,Future Systems -AI02267,Machine Learning Engineer,51675,AUD,69761,EN,PT,Australia,M,Australia,50,"Git, Scala, Computer Vision, Java, Deep Learning",Bachelor,0,Healthcare,2025-01-08,2025-02-02,1966,5.3,Cloud AI Solutions -AI02268,Principal Data Scientist,270523,USD,270523,EX,PT,Norway,S,Thailand,100,"SQL, MLOps, PyTorch, TensorFlow, Tableau",Associate,12,Gaming,2024-06-16,2024-07-30,1569,9.7,TechCorp Inc -AI02269,Principal Data Scientist,138679,EUR,117877,SE,PT,France,M,Finland,100,"Statistics, Tableau, Linux",Master,8,Retail,2024-11-10,2024-12-30,681,6.2,Autonomous Tech -AI02270,Data Scientist,153448,GBP,115086,EX,PT,United Kingdom,S,United Kingdom,100,"PyTorch, TensorFlow, Hadoop, Kubernetes, R",Bachelor,16,Manufacturing,2024-11-26,2024-12-10,2074,9.7,Quantum Computing Inc -AI02271,Autonomous Systems Engineer,99198,CHF,89278,EN,FL,Switzerland,M,Malaysia,100,"PyTorch, NLP, Git, Azure, Mathematics",PhD,0,Education,2024-01-27,2024-03-20,916,6.3,DeepTech Ventures -AI02272,AI Architect,108736,EUR,92426,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, TensorFlow, Java, SQL, Azure",Associate,6,Automotive,2024-11-28,2024-12-21,1268,7.8,AI Innovations -AI02273,AI Product Manager,108349,EUR,92097,SE,PT,Netherlands,S,Netherlands,0,"Linux, MLOps, NLP",Bachelor,8,Education,2025-02-14,2025-04-25,944,5.1,Cloud AI Solutions -AI02274,AI Consultant,97976,USD,97976,SE,FL,Finland,M,Finland,100,"TensorFlow, Kubernetes, Deep Learning, Scala, Azure",Associate,9,Telecommunications,2024-01-05,2024-02-12,1332,5.6,TechCorp Inc -AI02275,Data Engineer,106852,USD,106852,MI,FT,Sweden,L,United States,50,"Kubernetes, SQL, GCP, Computer Vision",PhD,2,Automotive,2024-07-21,2024-09-01,2193,9.1,Algorithmic Solutions -AI02276,AI Research Scientist,157337,CHF,141603,SE,CT,Switzerland,S,Italy,100,"Scala, PyTorch, MLOps, SQL",Bachelor,5,Retail,2024-06-24,2024-07-30,1623,6.4,Digital Transformation LLC -AI02277,Data Engineer,119797,CHF,107817,EN,FT,Switzerland,L,Switzerland,50,"Python, Linux, Deep Learning",Associate,0,Telecommunications,2024-06-27,2024-07-27,624,6.4,Neural Networks Co -AI02278,Machine Learning Researcher,69161,USD,69161,EX,FL,India,M,India,100,"Deep Learning, TensorFlow, Kubernetes, Statistics",Master,15,Healthcare,2024-07-31,2024-09-18,997,5.6,Machine Intelligence Group -AI02279,Data Engineer,138491,AUD,186963,EX,FL,Australia,M,Australia,50,"Deep Learning, TensorFlow, Linux",Bachelor,18,Government,2024-12-19,2025-01-26,839,5.6,Autonomous Tech -AI02280,AI Product Manager,103654,GBP,77741,MI,FL,United Kingdom,M,United Kingdom,0,"GCP, Python, Docker",Associate,2,Real Estate,2025-04-05,2025-04-26,591,9.9,TechCorp Inc -AI02281,Deep Learning Engineer,61991,USD,61991,EN,CT,Ireland,S,Ireland,50,"Mathematics, Python, AWS, TensorFlow, Scala",Bachelor,0,Retail,2024-11-06,2025-01-11,2413,7.5,Autonomous Tech -AI02282,AI Research Scientist,81076,EUR,68915,EN,CT,Austria,L,Austria,100,"Python, Linux, MLOps, TensorFlow, Azure",Master,0,Consulting,2025-03-28,2025-06-09,927,7.4,Digital Transformation LLC -AI02283,Data Engineer,84481,USD,84481,MI,CT,Israel,S,Israel,100,"Mathematics, Data Visualization, TensorFlow",Master,4,Government,2024-06-24,2024-08-08,1198,8.5,Autonomous Tech -AI02284,Machine Learning Engineer,31910,USD,31910,MI,FL,China,S,Singapore,0,"TensorFlow, SQL, Mathematics, NLP",Bachelor,2,Technology,2024-04-05,2024-06-06,1846,7.7,Cognitive Computing -AI02285,Principal Data Scientist,103659,AUD,139940,MI,PT,Australia,L,Australia,50,"Docker, SQL, NLP, GCP, MLOps",Bachelor,2,Media,2024-03-02,2024-04-08,2362,9.8,Predictive Systems -AI02286,Machine Learning Researcher,241811,AUD,326445,EX,CT,Australia,L,Romania,0,"PyTorch, GCP, Python, Spark, MLOps",PhD,19,Government,2024-06-11,2024-08-06,2082,8.8,Smart Analytics -AI02287,Principal Data Scientist,85528,EUR,72699,MI,PT,Netherlands,M,Netherlands,50,"NLP, Mathematics, Java, R",Associate,3,Technology,2024-12-18,2025-01-21,927,8.4,Algorithmic Solutions -AI02288,Research Scientist,233646,SGD,303740,EX,CT,Singapore,M,Singapore,0,"Statistics, SQL, Computer Vision, Linux, Deep Learning",Bachelor,12,Real Estate,2024-06-23,2024-08-03,2210,5.6,Digital Transformation LLC -AI02289,AI Specialist,180558,USD,180558,EX,PT,Denmark,M,Denmark,100,"GCP, Computer Vision, Java",PhD,10,Finance,2025-04-24,2025-05-31,1812,6.5,DeepTech Ventures -AI02290,Data Scientist,94791,EUR,80572,MI,CT,Germany,L,Germany,100,"TensorFlow, Statistics, Kubernetes, PyTorch, R",Master,3,Government,2024-04-08,2024-05-05,1246,6.5,Machine Intelligence Group -AI02291,Robotics Engineer,189914,USD,189914,EX,FT,United States,M,United States,0,"TensorFlow, Hadoop, Linux, Scala",Bachelor,17,Energy,2025-04-27,2025-06-30,2134,7.6,TechCorp Inc -AI02292,Machine Learning Researcher,96777,GBP,72583,MI,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, PyTorch, Java",Associate,3,Education,2024-07-05,2024-07-19,2490,5.5,Quantum Computing Inc -AI02293,AI Architect,29644,USD,29644,MI,PT,India,L,Norway,100,"Hadoop, Python, SQL, Deep Learning, Azure",Associate,4,Gaming,2024-03-20,2024-04-26,825,8.1,Future Systems -AI02294,Autonomous Systems Engineer,191246,USD,191246,EX,CT,United States,L,Kenya,50,"TensorFlow, Python, AWS, R, PyTorch",Bachelor,16,Technology,2025-02-23,2025-05-06,2386,5.7,AI Innovations -AI02295,Data Analyst,74691,USD,74691,MI,CT,South Korea,L,South Korea,50,"MLOps, Tableau, AWS, Linux",Associate,4,Telecommunications,2024-01-09,2024-03-01,1718,7.9,Autonomous Tech -AI02296,NLP Engineer,94955,JPY,10445050,EN,PT,Japan,L,Japan,0,"Spark, R, MLOps, Kubernetes, Azure",Bachelor,1,Automotive,2024-12-19,2025-01-14,2392,9.9,Smart Analytics -AI02297,Robotics Engineer,174201,USD,174201,SE,PT,Norway,M,Norway,50,"Java, Docker, Tableau, Statistics, MLOps",Bachelor,9,Real Estate,2025-02-05,2025-03-14,1951,7.3,DataVision Ltd -AI02298,Machine Learning Researcher,110906,CHF,99815,MI,FL,Switzerland,M,Switzerland,100,"Linux, Spark, Hadoop",PhD,3,Energy,2024-10-05,2024-12-01,2406,9.8,Cloud AI Solutions -AI02299,Research Scientist,129560,SGD,168428,SE,CT,Singapore,S,Singapore,100,"Scala, Java, MLOps",Master,9,Government,2024-08-05,2024-10-02,2483,9.5,Quantum Computing Inc -AI02300,Deep Learning Engineer,56552,AUD,76345,EN,PT,Australia,M,Australia,0,"MLOps, Python, GCP, SQL, Linux",Master,1,Retail,2024-09-01,2024-10-01,1431,8,Machine Intelligence Group -AI02301,AI Product Manager,82665,USD,82665,SE,FT,China,L,Finland,100,"Kubernetes, R, Java, SQL, NLP",Master,6,Gaming,2024-01-26,2024-02-13,1960,7,DataVision Ltd -AI02302,AI Specialist,57257,USD,57257,EN,CT,Ireland,S,Ireland,50,"Deep Learning, MLOps, Hadoop, GCP",Bachelor,0,Healthcare,2024-04-12,2024-04-27,1328,9.7,Machine Intelligence Group -AI02303,Deep Learning Engineer,156738,USD,156738,SE,FT,United States,S,United States,50,"Spark, Scala, Mathematics",PhD,8,Transportation,2024-07-31,2024-08-22,1295,6.4,Cognitive Computing -AI02304,Data Analyst,105347,EUR,89545,SE,CT,Netherlands,S,Netherlands,0,"Linux, R, MLOps",Bachelor,6,Consulting,2024-01-27,2024-03-05,2296,9.4,Advanced Robotics -AI02305,AI Product Manager,223454,JPY,24579940,EX,FT,Japan,S,Japan,100,"Computer Vision, R, PyTorch, GCP",Associate,19,Retail,2025-02-25,2025-03-17,510,5.4,DeepTech Ventures -AI02306,Machine Learning Engineer,72740,USD,72740,MI,PT,Finland,M,Netherlands,0,"GCP, Linux, MLOps, Tableau",Bachelor,3,Media,2025-01-08,2025-02-14,2001,5.1,Autonomous Tech -AI02307,Research Scientist,107622,USD,107622,MI,PT,Ireland,L,Ireland,50,"Git, SQL, PyTorch",Associate,4,Telecommunications,2024-03-06,2024-04-05,602,5.9,TechCorp Inc -AI02308,Principal Data Scientist,150523,EUR,127945,EX,CT,France,S,France,100,"Java, NLP, AWS",Master,18,Education,2024-11-20,2024-12-30,1927,6.8,Neural Networks Co -AI02309,Data Scientist,134704,EUR,114498,SE,FT,Austria,L,Malaysia,0,"Statistics, SQL, GCP, NLP",PhD,5,Manufacturing,2024-08-02,2024-08-27,2230,9.1,AI Innovations -AI02310,Research Scientist,51843,USD,51843,EN,CT,Finland,S,Sweden,0,"Kubernetes, Hadoop, Java, Computer Vision, Tableau",Master,1,Technology,2024-08-25,2024-10-16,797,7.3,TechCorp Inc -AI02311,AI Research Scientist,81429,EUR,69215,MI,FL,Germany,M,Germany,50,"Linux, Git, GCP, AWS, Spark",Master,3,Healthcare,2025-02-14,2025-03-02,2079,5.8,AI Innovations -AI02312,Deep Learning Engineer,208862,CAD,261078,EX,FL,Canada,L,Canada,50,"MLOps, Tableau, Git, Python, Scala",Associate,13,Gaming,2024-06-20,2024-07-25,1901,5.6,Neural Networks Co -AI02313,Machine Learning Engineer,90374,USD,90374,SE,FT,Israel,S,Israel,50,"R, Tableau, Azure, SQL",Master,7,Media,2024-07-10,2024-09-17,1887,9.5,Algorithmic Solutions -AI02314,AI Consultant,61463,EUR,52244,MI,PT,France,S,France,100,"Scala, Azure, MLOps, Python",Associate,3,Finance,2024-11-24,2025-01-11,2182,6,Machine Intelligence Group -AI02315,Deep Learning Engineer,109194,USD,109194,SE,CT,Finland,M,Finland,50,"R, Computer Vision, GCP",Associate,7,Technology,2024-04-01,2024-06-05,1756,7.6,Quantum Computing Inc -AI02316,AI Software Engineer,170066,USD,170066,EX,CT,South Korea,S,Thailand,0,"Data Visualization, Python, PyTorch",Associate,18,Education,2024-05-31,2024-07-18,835,6.1,Quantum Computing Inc -AI02317,Machine Learning Engineer,130203,USD,130203,SE,FL,Sweden,M,Sweden,100,"SQL, Statistics, R, MLOps, Hadoop",Bachelor,5,Education,2024-04-27,2024-06-22,1041,8.1,Algorithmic Solutions -AI02318,Robotics Engineer,92631,USD,92631,MI,CT,United States,M,United States,50,"AWS, Java, Python, GCP, Tableau",Associate,2,Transportation,2024-12-12,2025-01-11,2185,7,Cloud AI Solutions -AI02319,Data Analyst,124406,EUR,105745,SE,CT,France,S,France,50,"Computer Vision, PyTorch, Linux, AWS, SQL",PhD,6,Transportation,2024-01-15,2024-02-21,1041,9.3,Quantum Computing Inc -AI02320,Machine Learning Researcher,81253,USD,81253,MI,FL,Israel,M,Israel,0,"Azure, Git, NLP, Deep Learning, TensorFlow",Bachelor,4,Retail,2024-11-18,2025-01-13,2045,7.4,DeepTech Ventures -AI02321,Data Analyst,94671,EUR,80470,MI,CT,Germany,M,Germany,0,"PyTorch, Kubernetes, Mathematics",Associate,4,Automotive,2024-07-01,2024-08-11,1911,8.4,Smart Analytics -AI02322,Data Scientist,104689,USD,104689,MI,FL,Ireland,M,Ireland,50,"Tableau, Python, TensorFlow, Hadoop",Bachelor,2,Gaming,2024-01-02,2024-03-05,1563,5.7,DeepTech Ventures -AI02323,Research Scientist,124477,EUR,105805,SE,PT,Netherlands,L,Netherlands,100,"Java, R, SQL, Git",Associate,7,Government,2024-02-22,2024-03-17,655,8.5,Future Systems -AI02324,Machine Learning Engineer,225013,EUR,191261,EX,PT,Netherlands,S,Argentina,0,"SQL, Python, Java",PhD,17,Transportation,2024-08-18,2024-09-09,1668,7,Future Systems -AI02325,AI Specialist,57156,USD,57156,EN,PT,Finland,M,Finland,100,"GCP, MLOps, PyTorch",PhD,0,Technology,2024-10-24,2024-12-09,1115,8.4,Machine Intelligence Group -AI02326,Robotics Engineer,75630,USD,75630,MI,PT,Israel,S,Israel,100,"NLP, Mathematics, MLOps, Docker",Associate,2,Finance,2024-11-30,2025-02-07,1371,5.3,Cognitive Computing -AI02327,Data Scientist,193038,USD,193038,EX,CT,Israel,M,Israel,50,"GCP, Linux, MLOps, Mathematics, AWS",PhD,12,Automotive,2024-08-30,2024-10-30,2331,8.4,Predictive Systems -AI02328,ML Ops Engineer,354091,USD,354091,EX,FT,Norway,L,Thailand,0,"Java, Scala, GCP, Mathematics, MLOps",Master,15,Gaming,2024-05-26,2024-06-24,2237,9.6,Autonomous Tech -AI02329,Computer Vision Engineer,116471,CAD,145589,MI,FL,Canada,L,Canada,50,"Statistics, Linux, Azure, Kubernetes, Computer Vision",Master,4,Real Estate,2025-03-04,2025-05-13,1445,6,Neural Networks Co -AI02330,Computer Vision Engineer,52386,EUR,44528,EN,PT,France,M,Thailand,100,"Python, Kubernetes, Data Visualization, TensorFlow",Master,1,Manufacturing,2025-04-27,2025-06-09,1561,8.3,Cloud AI Solutions -AI02331,AI Specialist,23595,USD,23595,EN,CT,China,S,China,100,"NLP, Python, TensorFlow",Associate,1,Retail,2024-08-13,2024-10-13,1556,7.7,Predictive Systems -AI02332,AI Research Scientist,123617,AUD,166883,EX,FL,Australia,S,Australia,0,"MLOps, Mathematics, Python, TensorFlow, Git",Associate,17,Transportation,2024-07-07,2024-09-07,838,5.6,Quantum Computing Inc -AI02333,Robotics Engineer,294173,USD,294173,EX,FT,United States,L,Switzerland,0,"SQL, GCP, Tableau, TensorFlow, Python",Master,16,Media,2025-01-25,2025-02-22,1739,5.6,DeepTech Ventures -AI02334,Data Engineer,158889,USD,158889,SE,FT,United States,L,Netherlands,100,"AWS, Hadoop, Deep Learning, Mathematics, SQL",Master,9,Technology,2024-01-20,2024-03-27,1615,6.4,Future Systems -AI02335,Research Scientist,92187,USD,92187,SE,PT,Israel,S,Spain,0,"Data Visualization, Computer Vision, GCP, Scala, NLP",PhD,8,Telecommunications,2024-08-25,2024-09-22,1474,5.5,Quantum Computing Inc -AI02336,ML Ops Engineer,266476,EUR,226505,EX,PT,France,L,France,0,"Azure, Hadoop, Data Visualization, Spark",Bachelor,18,Gaming,2024-02-22,2024-04-22,886,8.2,Autonomous Tech -AI02337,Data Scientist,64951,EUR,55208,EN,FL,Netherlands,S,Austria,0,"PyTorch, Kubernetes, Java, Azure, MLOps",Master,1,Media,2024-03-15,2024-04-23,1222,9.2,DeepTech Ventures -AI02338,AI Research Scientist,173215,EUR,147233,EX,CT,Netherlands,M,Netherlands,50,"Computer Vision, AWS, Python, TensorFlow, Data Visualization",PhD,19,Telecommunications,2024-02-15,2024-03-15,733,5.1,TechCorp Inc -AI02339,Machine Learning Researcher,114900,USD,114900,MI,PT,Denmark,M,Indonesia,0,"Python, Kubernetes, Git",Bachelor,3,Retail,2024-12-17,2025-02-27,1669,9.5,Future Systems -AI02340,AI Consultant,65123,USD,65123,MI,FT,Finland,S,Finland,0,"SQL, R, AWS, Python",PhD,3,Manufacturing,2025-02-10,2025-03-22,1882,9.2,Smart Analytics -AI02341,AI Consultant,176135,EUR,149715,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Deep Learning, SQL, NLP",Bachelor,17,Automotive,2024-02-18,2024-03-21,512,9.6,Neural Networks Co -AI02342,AI Specialist,128894,USD,128894,EX,FL,South Korea,M,South Korea,100,"Scala, AWS, MLOps, Data Visualization, Statistics",Bachelor,15,Telecommunications,2024-01-24,2024-03-25,2001,8.2,TechCorp Inc -AI02343,AI Specialist,140129,CAD,175161,EX,CT,Canada,M,Canada,0,"Java, Python, GCP",Bachelor,15,Finance,2024-03-19,2024-05-25,1796,6.1,AI Innovations -AI02344,Head of AI,211366,EUR,179661,EX,CT,Austria,S,Austria,100,"R, SQL, Kubernetes, Git, Tableau",Associate,17,Consulting,2025-03-30,2025-04-14,1025,6.6,Future Systems -AI02345,Data Scientist,89067,GBP,66800,MI,FT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Tableau, Git",Master,2,Government,2024-03-23,2024-06-03,1133,8,Predictive Systems -AI02346,Deep Learning Engineer,120608,AUD,162821,SE,FL,Australia,S,Spain,100,"Python, TensorFlow, Data Visualization",Master,9,Healthcare,2024-10-23,2024-11-26,2358,5.9,Advanced Robotics -AI02347,AI Research Scientist,173641,CAD,217051,EX,FL,Canada,S,Canada,0,"Python, Linux, Scala, TensorFlow, R",Bachelor,11,Healthcare,2025-01-20,2025-02-28,2102,5.6,DeepTech Ventures -AI02348,AI Research Scientist,93978,JPY,10337580,MI,PT,Japan,L,Austria,50,"Python, Git, Kubernetes, TensorFlow, Scala",PhD,2,Manufacturing,2025-02-06,2025-03-13,1541,5,Cognitive Computing -AI02349,Data Analyst,291451,CHF,262306,EX,PT,Switzerland,S,Switzerland,100,"Python, TensorFlow, PyTorch, SQL, Hadoop",Associate,18,Education,2024-10-05,2024-12-14,2356,5.5,Cognitive Computing -AI02350,Data Engineer,115058,USD,115058,MI,FL,Denmark,L,Denmark,100,"Scala, NLP, Python, Deep Learning",Master,4,Consulting,2024-03-26,2024-05-10,2092,7.1,Predictive Systems -AI02351,Head of AI,121394,USD,121394,MI,PT,Norway,M,Norway,100,"Linux, Kubernetes, MLOps, PyTorch",PhD,4,Gaming,2024-10-18,2024-12-23,1538,6.8,DeepTech Ventures -AI02352,AI Specialist,51431,USD,51431,MI,CT,China,L,China,50,"Deep Learning, Git, Mathematics, Data Visualization, R",Bachelor,4,Manufacturing,2024-05-31,2024-06-17,2302,7.1,Smart Analytics -AI02353,Robotics Engineer,90064,USD,90064,MI,FT,United States,M,United States,0,"Python, TensorFlow, Computer Vision, Kubernetes",Associate,3,Real Estate,2025-01-29,2025-03-28,1740,8.5,Future Systems -AI02354,Data Scientist,120867,JPY,13295370,SE,PT,Japan,S,Australia,50,"Java, R, Tableau",Associate,6,Retail,2024-03-31,2024-04-29,2008,5.7,Cloud AI Solutions -AI02355,Data Engineer,51975,EUR,44179,EN,FT,Netherlands,S,South Africa,100,"Git, Docker, MLOps",PhD,0,Retail,2024-03-21,2024-04-29,1266,5.5,Cognitive Computing -AI02356,AI Product Manager,125213,EUR,106431,SE,FL,Netherlands,S,Netherlands,50,"R, AWS, Azure",Associate,7,Manufacturing,2024-07-26,2024-09-20,1233,9.9,Machine Intelligence Group -AI02357,AI Specialist,73632,EUR,62587,EN,FL,Netherlands,L,Netherlands,100,"Git, Kubernetes, Spark",Master,0,Automotive,2024-09-23,2024-10-10,2163,7.7,DeepTech Ventures -AI02358,AI Consultant,147336,USD,147336,SE,CT,Israel,L,Israel,50,"Hadoop, Scala, PyTorch, TensorFlow, Python",Master,9,Healthcare,2024-03-12,2024-05-03,2452,8.1,Cloud AI Solutions -AI02359,Data Engineer,113940,JPY,12533400,SE,FL,Japan,S,France,0,"Java, AWS, Linux, GCP, Docker",Associate,7,Transportation,2024-01-28,2024-03-21,1981,6.4,TechCorp Inc -AI02360,Robotics Engineer,115793,EUR,98424,SE,PT,Netherlands,M,Austria,0,"GCP, Statistics, Hadoop",Associate,5,Retail,2025-04-16,2025-06-07,2490,6.9,Digital Transformation LLC -AI02361,Research Scientist,385250,CHF,346725,EX,CT,Switzerland,L,China,0,"Kubernetes, SQL, Docker, Java, Python",Associate,19,Retail,2024-12-31,2025-02-20,2183,6.5,Smart Analytics -AI02362,ML Ops Engineer,97449,EUR,82832,EN,FT,Netherlands,L,Belgium,50,"Linux, Tableau, Python, Deep Learning, TensorFlow",Associate,0,Manufacturing,2024-02-11,2024-03-10,665,5.2,Machine Intelligence Group -AI02363,Autonomous Systems Engineer,158205,EUR,134474,EX,CT,France,L,Mexico,100,"Scala, Linux, Docker, Statistics",Associate,12,Healthcare,2024-08-12,2024-08-27,656,8.8,Predictive Systems -AI02364,Machine Learning Researcher,227940,SGD,296322,EX,FL,Singapore,L,Finland,0,"GCP, Java, SQL",Associate,11,Consulting,2024-09-27,2024-11-13,1038,9.3,Smart Analytics -AI02365,AI Specialist,82774,USD,82774,MI,PT,Israel,L,Sweden,50,"TensorFlow, Java, Deep Learning, Spark",Associate,3,Technology,2024-02-27,2024-04-01,1190,7.9,TechCorp Inc -AI02366,Data Engineer,151102,CHF,135992,SE,CT,Switzerland,S,China,0,"SQL, TensorFlow, AWS, NLP",Associate,6,Real Estate,2024-12-19,2025-01-24,1992,8.7,Advanced Robotics -AI02367,Computer Vision Engineer,135010,USD,135010,MI,CT,Norway,M,Ireland,50,"Statistics, AWS, PyTorch, Data Visualization, Spark",PhD,4,Retail,2025-01-01,2025-02-03,589,6.2,Algorithmic Solutions -AI02368,Head of AI,99493,JPY,10944230,MI,FL,Japan,S,Japan,100,"Deep Learning, Tableau, SQL",PhD,2,Energy,2024-06-25,2024-07-22,2338,8.6,TechCorp Inc -AI02369,AI Product Manager,104842,GBP,78632,MI,CT,United Kingdom,L,Australia,50,"Azure, Scala, AWS, TensorFlow, Statistics",Master,2,Healthcare,2025-03-15,2025-05-26,1211,8.6,Cloud AI Solutions -AI02370,Head of AI,77587,USD,77587,EN,FT,Sweden,L,Estonia,100,"TensorFlow, Linux, R",Master,0,Manufacturing,2024-05-06,2024-06-05,2238,8,Smart Analytics -AI02371,ML Ops Engineer,94792,SGD,123230,MI,FL,Singapore,L,Singapore,50,"AWS, MLOps, Python, TensorFlow",Master,4,Transportation,2024-03-06,2024-05-11,695,6.8,Autonomous Tech -AI02372,AI Consultant,170382,EUR,144825,SE,PT,Netherlands,L,Netherlands,0,"Statistics, Scala, Java",PhD,6,Manufacturing,2024-12-09,2025-01-30,1927,7.3,Autonomous Tech -AI02373,AI Consultant,69714,USD,69714,EN,PT,Finland,M,Switzerland,100,"Scala, Linux, Python",Associate,0,Manufacturing,2024-04-15,2024-06-03,1972,5.9,Quantum Computing Inc -AI02374,AI Specialist,61848,USD,61848,EN,FT,Ireland,L,Ireland,100,"Hadoop, Data Visualization, Python, PyTorch, Deep Learning",PhD,0,Real Estate,2025-01-10,2025-03-05,651,8,Quantum Computing Inc -AI02375,Computer Vision Engineer,65280,EUR,55488,EN,CT,Netherlands,M,Netherlands,100,"Azure, PyTorch, Spark, SQL",PhD,0,Retail,2024-11-04,2024-12-08,1890,6.5,Neural Networks Co -AI02376,Deep Learning Engineer,67421,USD,67421,EN,PT,United States,S,Sweden,50,"Docker, Tableau, Kubernetes, SQL, GCP",PhD,0,Real Estate,2025-02-15,2025-04-10,2051,8.7,Advanced Robotics -AI02377,Data Engineer,276843,USD,276843,EX,FL,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, GCP",PhD,11,Retail,2024-08-10,2024-09-09,740,6.2,Cognitive Computing -AI02378,Computer Vision Engineer,86366,USD,86366,MI,CT,Norway,S,Norway,0,"Statistics, AWS, Kubernetes, Computer Vision, GCP",PhD,4,Education,2024-01-16,2024-03-28,1664,7.7,DataVision Ltd -AI02379,AI Specialist,113593,SGD,147671,SE,PT,Singapore,M,Singapore,100,"SQL, Data Visualization, Tableau, TensorFlow",PhD,9,Real Estate,2024-04-06,2024-06-16,1375,6,Neural Networks Co -AI02380,Autonomous Systems Engineer,248477,USD,248477,EX,CT,United States,L,Austria,100,"Git, TensorFlow, Linux, NLP, Docker",Associate,17,Telecommunications,2024-08-08,2024-08-28,2245,7.4,Machine Intelligence Group -AI02381,Head of AI,140516,USD,140516,SE,FL,Israel,M,Israel,0,"Python, Kubernetes, Tableau, AWS, Computer Vision",Bachelor,5,Real Estate,2024-02-06,2024-04-01,2138,5.8,Algorithmic Solutions -AI02382,ML Ops Engineer,101660,USD,101660,MI,CT,Israel,M,Israel,50,"Tableau, GCP, Hadoop",Master,4,Telecommunications,2025-01-08,2025-02-01,1455,5.1,AI Innovations -AI02383,NLP Engineer,59401,AUD,80191,EN,PT,Australia,S,Australia,0,"Statistics, Python, MLOps, Data Visualization",Associate,1,Real Estate,2025-02-22,2025-03-11,2022,6.2,DataVision Ltd -AI02384,Machine Learning Researcher,282872,CHF,254585,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, SQL, Mathematics",Master,16,Consulting,2024-10-20,2024-11-14,1004,7.7,TechCorp Inc -AI02385,AI Consultant,79004,USD,79004,EN,FL,Denmark,S,Denmark,50,"R, PyTorch, Mathematics",Bachelor,1,Government,2024-10-07,2024-11-22,1888,9,Digital Transformation LLC -AI02386,Autonomous Systems Engineer,90214,USD,90214,EX,CT,China,L,China,100,"Java, PyTorch, SQL, NLP",PhD,14,Healthcare,2024-11-23,2024-12-08,1536,6.3,Machine Intelligence Group -AI02387,NLP Engineer,177517,USD,177517,EX,PT,Denmark,S,Denmark,0,"PyTorch, Tableau, Java, GCP, R",PhD,10,Consulting,2024-05-02,2024-06-22,1170,9.2,TechCorp Inc -AI02388,Research Scientist,138067,USD,138067,SE,PT,Denmark,S,Denmark,100,"Linux, GCP, R, Mathematics",PhD,6,Automotive,2024-05-19,2024-07-17,1830,5.3,Predictive Systems -AI02389,AI Product Manager,175216,EUR,148934,SE,FL,Germany,L,Austria,100,"Linux, Statistics, Data Visualization",Bachelor,6,Retail,2024-10-24,2024-12-14,909,7.9,Quantum Computing Inc -AI02390,Machine Learning Engineer,67149,EUR,57077,EN,PT,France,M,France,0,"Data Visualization, Kubernetes, Spark",Master,0,Telecommunications,2024-12-10,2025-02-06,840,8.6,Advanced Robotics -AI02391,AI Consultant,65086,USD,65086,EN,CT,Sweden,L,Sweden,0,"Data Visualization, PyTorch, Kubernetes, Azure",Associate,1,Government,2024-11-10,2025-01-22,1761,8.1,Predictive Systems -AI02392,Principal Data Scientist,97236,USD,97236,MI,PT,Denmark,S,Ireland,0,"Spark, SQL, Computer Vision",PhD,3,Manufacturing,2024-10-15,2024-12-04,2272,6.9,Advanced Robotics -AI02393,Data Analyst,33499,USD,33499,MI,PT,India,L,India,50,"Data Visualization, R, Linux, GCP",Bachelor,2,Energy,2025-04-03,2025-05-15,1644,8.9,Quantum Computing Inc -AI02394,Data Analyst,83973,EUR,71377,MI,FL,France,S,France,0,"GCP, SQL, Git",PhD,2,Energy,2024-04-15,2024-06-18,2438,7.1,Neural Networks Co -AI02395,AI Software Engineer,77052,USD,77052,MI,CT,Ireland,S,Ireland,50,"GCP, Hadoop, TensorFlow, Deep Learning, AWS",Associate,2,Education,2024-10-08,2024-11-07,1146,9.3,Autonomous Tech -AI02396,NLP Engineer,121702,SGD,158213,SE,FT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Kubernetes, Data Visualization, Java",Bachelor,5,Transportation,2024-07-15,2024-08-09,1798,6.5,Advanced Robotics -AI02397,Data Scientist,226834,USD,226834,EX,CT,Norway,L,Norway,0,"PyTorch, SQL, NLP, R",Master,14,Finance,2024-11-19,2025-01-27,1368,8.2,DataVision Ltd -AI02398,AI Specialist,269663,GBP,202247,EX,FL,United Kingdom,L,Singapore,100,"Mathematics, Git, SQL, TensorFlow",Master,13,Government,2024-08-10,2024-09-15,1189,8.7,AI Innovations -AI02399,ML Ops Engineer,121309,USD,121309,SE,FT,Sweden,L,Sweden,100,"SQL, Deep Learning, Tableau",PhD,7,Real Estate,2024-09-11,2024-10-01,1599,7.5,AI Innovations -AI02400,Machine Learning Researcher,81603,USD,81603,MI,FT,South Korea,S,South Korea,100,"Python, Mathematics, Data Visualization, Scala, Azure",Bachelor,2,Consulting,2025-04-19,2025-06-11,927,9.5,Predictive Systems -AI02401,AI Architect,101849,USD,101849,MI,PT,Denmark,S,France,0,"Python, Azure, TensorFlow",PhD,2,Telecommunications,2024-07-16,2024-09-24,546,8.6,Algorithmic Solutions -AI02402,Deep Learning Engineer,184180,JPY,20259800,SE,PT,Japan,L,Ukraine,0,"Tableau, TensorFlow, GCP, Data Visualization",PhD,9,Automotive,2024-11-15,2024-12-28,2001,7.7,Algorithmic Solutions -AI02403,AI Architect,117248,USD,117248,EN,CT,Denmark,L,Denmark,100,"Docker, Kubernetes, Statistics, Tableau, Python",PhD,0,Education,2024-07-20,2024-08-07,624,7.9,Future Systems -AI02404,Machine Learning Researcher,95725,JPY,10529750,MI,CT,Japan,S,Japan,0,"AWS, Linux, Kubernetes, Data Visualization",Bachelor,4,Media,2025-03-27,2025-05-05,720,6.6,Smart Analytics -AI02405,Computer Vision Engineer,101075,EUR,85914,MI,CT,Germany,M,Germany,0,"TensorFlow, Statistics, Spark, Linux",Bachelor,2,Healthcare,2024-05-19,2024-06-18,2308,5.7,Autonomous Tech -AI02406,AI Architect,138619,CAD,173274,SE,PT,Canada,M,Canada,50,"Kubernetes, PyTorch, Linux, AWS",Bachelor,9,Telecommunications,2025-01-01,2025-01-15,690,7.3,Machine Intelligence Group -AI02407,Data Engineer,138645,AUD,187171,SE,CT,Australia,L,Australia,100,"Deep Learning, Mathematics, PyTorch",Bachelor,5,Finance,2024-10-28,2024-12-18,1590,9.7,TechCorp Inc -AI02408,AI Product Manager,55621,EUR,47278,EN,CT,Netherlands,M,Netherlands,50,"R, Python, Computer Vision, Deep Learning",Bachelor,1,Healthcare,2025-02-04,2025-04-04,684,7.8,Quantum Computing Inc -AI02409,Head of AI,135303,EUR,115008,SE,FL,Germany,L,Germany,100,"AWS, Git, SQL, Docker, Statistics",Bachelor,7,Retail,2024-09-14,2024-09-29,2317,7.9,Neural Networks Co -AI02410,Data Scientist,172436,USD,172436,SE,FT,United States,L,United States,50,"Tableau, Hadoop, Python",Associate,6,Real Estate,2025-03-07,2025-03-31,1364,5.4,Neural Networks Co -AI02411,Data Scientist,152590,AUD,205997,EX,PT,Australia,M,Australia,50,"GCP, Python, NLP, Computer Vision, Data Visualization",Bachelor,17,Finance,2024-08-12,2024-09-02,1932,9.5,DataVision Ltd -AI02412,AI Specialist,110412,USD,110412,SE,PT,Finland,L,Austria,50,"Docker, Spark, Hadoop, Git, SQL",Master,5,Healthcare,2024-03-01,2024-03-17,2307,8.4,Autonomous Tech -AI02413,Data Analyst,98339,GBP,73754,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, Python, Java, Linux",Bachelor,8,Retail,2024-05-09,2024-05-30,1819,7.5,Quantum Computing Inc -AI02414,Machine Learning Engineer,68002,USD,68002,EN,FT,Denmark,M,Denmark,0,"Scala, Azure, Computer Vision, Python",Bachelor,0,Consulting,2024-10-04,2024-11-29,1489,5.7,Cloud AI Solutions -AI02415,Data Engineer,187944,JPY,20673840,EX,CT,Japan,S,Germany,50,"Python, SQL, TensorFlow",Associate,10,Retail,2024-08-02,2024-08-29,1862,9.4,Cognitive Computing -AI02416,Autonomous Systems Engineer,50316,USD,50316,EN,CT,Sweden,S,France,100,"Linux, Docker, Data Visualization, PyTorch, Deep Learning",Bachelor,1,Education,2024-02-10,2024-04-07,1983,9.2,Neural Networks Co -AI02417,Data Analyst,104865,USD,104865,MI,FT,Denmark,M,Denmark,100,"NLP, Python, Java, Statistics",Master,2,Gaming,2024-09-02,2024-10-28,608,7.7,Cloud AI Solutions -AI02418,Deep Learning Engineer,79547,EUR,67615,MI,FL,France,S,France,50,"Statistics, Java, Data Visualization, Computer Vision, Linux",Bachelor,4,Government,2024-06-07,2024-08-17,2315,7.9,Future Systems -AI02419,Data Analyst,48817,USD,48817,EN,PT,Israel,S,Singapore,50,"Linux, R, Git, Kubernetes, Statistics",Bachelor,0,Energy,2024-01-02,2024-02-19,2161,8.2,Algorithmic Solutions -AI02420,Deep Learning Engineer,60358,EUR,51304,EN,FT,France,M,France,50,"Git, Scala, Tableau",PhD,1,Government,2025-01-24,2025-03-09,2400,8.9,DeepTech Ventures -AI02421,Data Scientist,36483,USD,36483,EN,CT,China,M,China,100,"AWS, Java, Tableau, Python",Bachelor,1,Real Estate,2024-12-19,2025-02-03,2044,7,Predictive Systems -AI02422,AI Specialist,34602,USD,34602,MI,CT,India,S,India,50,"Scala, TensorFlow, MLOps, Spark, Deep Learning",Bachelor,4,Consulting,2025-02-05,2025-02-21,2409,9.4,Advanced Robotics -AI02423,Data Scientist,183641,CHF,165277,SE,FL,Switzerland,S,Ukraine,50,"Mathematics, PyTorch, Spark, Scala, AWS",Master,8,Government,2025-01-11,2025-02-04,2248,9.1,AI Innovations -AI02424,Principal Data Scientist,137861,USD,137861,MI,CT,Denmark,M,Denmark,0,"Scala, Mathematics, Computer Vision, Deep Learning",Associate,4,Technology,2024-05-27,2024-07-17,988,8,Cloud AI Solutions -AI02425,Data Engineer,55797,EUR,47427,EN,PT,France,S,France,100,"GCP, Scala, Spark, Python",PhD,0,Manufacturing,2024-06-26,2024-08-06,2194,9.5,DeepTech Ventures -AI02426,Principal Data Scientist,60447,CAD,75559,EN,CT,Canada,L,Canada,50,"Scala, Tableau, Azure, Spark, SQL",Master,1,Retail,2024-03-05,2024-04-25,2068,7,DataVision Ltd -AI02427,Head of AI,188935,EUR,160595,EX,FT,Austria,L,Austria,0,"Java, AWS, R",PhD,14,Retail,2025-01-29,2025-03-12,1647,5,AI Innovations -AI02428,Data Engineer,74196,USD,74196,EX,FL,India,L,India,50,"TensorFlow, Python, Git, Hadoop",Associate,19,Education,2024-03-06,2024-04-22,910,8.1,Machine Intelligence Group -AI02429,AI Architect,171635,CHF,154472,SE,FL,Switzerland,S,Switzerland,100,"R, Tableau, Spark, SQL, Computer Vision",Bachelor,9,Gaming,2024-07-23,2024-09-07,2310,6.8,Neural Networks Co -AI02430,AI Architect,71217,EUR,60534,EN,CT,Netherlands,M,Netherlands,0,"Python, NLP, TensorFlow, AWS",Master,0,Government,2024-06-15,2024-07-02,2397,5.9,Quantum Computing Inc -AI02431,Data Scientist,55275,GBP,41456,EN,CT,United Kingdom,S,United Kingdom,0,"PyTorch, NLP, Java, Python, Docker",Bachelor,1,Technology,2025-04-02,2025-06-08,933,6.2,Autonomous Tech -AI02432,Machine Learning Engineer,63318,USD,63318,EN,CT,Ireland,S,Vietnam,50,"SQL, GCP, PyTorch, Kubernetes",Associate,1,Finance,2025-01-26,2025-02-25,937,9.7,Algorithmic Solutions -AI02433,AI Specialist,102417,USD,102417,MI,CT,South Korea,L,South Korea,50,"Linux, SQL, PyTorch",Master,2,Transportation,2024-08-15,2024-09-01,2253,8.2,AI Innovations -AI02434,Deep Learning Engineer,145507,USD,145507,SE,FT,Ireland,L,Ireland,0,"Deep Learning, Python, NLP, GCP, Git",Master,8,Real Estate,2024-07-08,2024-08-04,1577,8,Neural Networks Co -AI02435,Machine Learning Engineer,70110,EUR,59594,EN,FL,Germany,S,Finland,0,"Kubernetes, Python, Data Visualization",Master,1,Education,2025-01-01,2025-02-12,680,5.1,Autonomous Tech -AI02436,AI Research Scientist,171213,USD,171213,EX,CT,South Korea,M,South Korea,0,"Git, Docker, Deep Learning, Kubernetes, Statistics",PhD,10,Retail,2025-01-06,2025-02-28,731,5.8,Autonomous Tech -AI02437,Robotics Engineer,84500,USD,84500,MI,PT,Sweden,M,Turkey,0,"Spark, Python, TensorFlow, SQL",Associate,4,Consulting,2025-01-15,2025-03-22,1603,9.2,Cognitive Computing -AI02438,Machine Learning Researcher,156224,USD,156224,EX,FL,Israel,S,Israel,0,"Data Visualization, NLP, Java, R, Mathematics",Bachelor,15,Telecommunications,2024-07-07,2024-09-17,2135,9.7,Predictive Systems -AI02439,Research Scientist,92098,USD,92098,MI,FL,Sweden,S,Sweden,0,"TensorFlow, Mathematics, MLOps, Computer Vision",Associate,3,Retail,2025-04-23,2025-05-20,825,5.1,Future Systems -AI02440,Principal Data Scientist,167891,USD,167891,EX,FT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, Deep Learning",Master,15,Government,2024-03-16,2024-05-28,2352,7,Cognitive Computing -AI02441,Data Engineer,101538,SGD,131999,MI,CT,Singapore,S,France,0,"Kubernetes, Data Visualization, Python, Statistics, AWS",PhD,4,Telecommunications,2024-08-01,2024-10-07,2037,5.9,Machine Intelligence Group -AI02442,Computer Vision Engineer,156055,CAD,195069,SE,PT,Canada,L,Canada,100,"Python, SQL, TensorFlow, GCP",PhD,9,Consulting,2024-10-23,2024-12-21,865,9.5,DeepTech Ventures -AI02443,Principal Data Scientist,97531,EUR,82901,MI,PT,Germany,S,Malaysia,50,"Git, Scala, Python",PhD,4,Healthcare,2025-02-13,2025-03-29,1379,6.9,AI Innovations -AI02444,Deep Learning Engineer,66041,USD,66041,EN,CT,Sweden,S,Sweden,0,"GCP, Kubernetes, Docker",Associate,0,Telecommunications,2024-08-16,2024-10-25,746,7.9,AI Innovations -AI02445,Principal Data Scientist,78618,EUR,66825,EN,FL,Germany,M,Turkey,50,"Python, Azure, Scala, Hadoop",Master,1,Education,2025-04-25,2025-05-29,633,8.3,Advanced Robotics -AI02446,Data Scientist,63321,JPY,6965310,EN,CT,Japan,S,Japan,0,"Python, TensorFlow, PyTorch",Associate,1,Government,2024-05-03,2024-07-04,2329,8.4,Autonomous Tech -AI02447,Machine Learning Researcher,171661,AUD,231742,EX,CT,Australia,S,Australia,50,"PyTorch, Hadoop, Computer Vision",Bachelor,14,Government,2024-04-17,2024-06-06,2090,5.7,DeepTech Ventures -AI02448,Data Engineer,65836,CAD,82295,EN,CT,Canada,S,Luxembourg,100,"Scala, Statistics, PyTorch",Master,0,Energy,2025-03-21,2025-04-14,2090,5.3,Quantum Computing Inc -AI02449,Machine Learning Engineer,27320,USD,27320,EN,CT,India,L,India,0,"Python, Kubernetes, Tableau, PyTorch",Bachelor,0,Energy,2025-04-07,2025-06-15,1130,7.5,Cognitive Computing -AI02450,AI Specialist,135041,EUR,114785,SE,CT,Germany,S,Germany,100,"SQL, Kubernetes, Statistics, Hadoop",Associate,5,Energy,2024-07-20,2024-08-29,1002,5.8,Autonomous Tech -AI02451,AI Specialist,113501,USD,113501,SE,PT,United States,S,United States,0,"Spark, Docker, Python, Kubernetes",Master,5,Automotive,2024-01-29,2024-02-29,2412,9.8,Smart Analytics -AI02452,NLP Engineer,84009,USD,84009,EN,FT,Denmark,S,Denmark,50,"Kubernetes, R, Azure, AWS",Master,1,Retail,2024-12-07,2025-02-15,1122,6.1,TechCorp Inc -AI02453,Data Scientist,202038,CAD,252548,EX,FT,Canada,S,Canada,0,"Tableau, TensorFlow, Scala",Associate,17,Government,2024-10-08,2024-10-26,2244,7.4,Cloud AI Solutions -AI02454,AI Research Scientist,157447,USD,157447,SE,PT,Norway,M,Nigeria,0,"R, Python, Git, NLP, Java",Master,5,Healthcare,2024-02-18,2024-04-03,2450,8.4,Future Systems -AI02455,Research Scientist,69117,USD,69117,EX,FL,China,S,South Korea,50,"Scala, Docker, Kubernetes",PhD,16,Government,2025-04-12,2025-05-04,517,8.7,Neural Networks Co -AI02456,AI Consultant,85916,SGD,111691,MI,FT,Singapore,S,Ireland,50,"Scala, Python, Data Visualization, NLP",Associate,2,Gaming,2024-12-19,2025-02-21,2108,5.7,Predictive Systems -AI02457,NLP Engineer,208144,EUR,176922,EX,FL,France,S,France,100,"Hadoop, MLOps, Spark, Git",Master,16,Technology,2024-06-01,2024-07-03,922,9.3,Machine Intelligence Group -AI02458,Computer Vision Engineer,201845,CAD,252306,EX,FT,Canada,L,Canada,100,"Data Visualization, Kubernetes, Scala, AWS, TensorFlow",Associate,11,Energy,2024-11-29,2025-02-05,1453,6.8,Neural Networks Co -AI02459,AI Software Engineer,70992,AUD,95839,EN,FL,Australia,S,Austria,0,"R, Data Visualization, AWS, Scala",PhD,0,Media,2024-05-01,2024-05-20,1609,6.8,DeepTech Ventures -AI02460,Computer Vision Engineer,78762,EUR,66948,MI,FL,Netherlands,S,Malaysia,50,"AWS, Azure, Docker, Hadoop, TensorFlow",Associate,4,Gaming,2024-06-08,2024-06-26,1864,7.5,Advanced Robotics -AI02461,Autonomous Systems Engineer,124250,USD,124250,SE,CT,South Korea,M,United Kingdom,0,"Linux, PyTorch, Kubernetes",PhD,9,Finance,2025-04-16,2025-05-27,1031,7.5,Future Systems -AI02462,AI Architect,79482,USD,79482,EN,PT,Norway,M,South Korea,0,"Computer Vision, Spark, Linux, Deep Learning",Associate,0,Healthcare,2024-09-30,2024-10-14,1803,5.6,Neural Networks Co -AI02463,Machine Learning Engineer,139133,EUR,118263,SE,CT,France,M,France,0,"Hadoop, SQL, Computer Vision, PyTorch",Master,6,Energy,2024-09-11,2024-10-28,1604,7.3,Digital Transformation LLC -AI02464,Computer Vision Engineer,220326,USD,220326,EX,FT,Norway,L,Norway,100,"PyTorch, Linux, TensorFlow, Azure, Hadoop",Master,10,Retail,2025-03-12,2025-05-11,1484,5.1,Autonomous Tech -AI02465,Machine Learning Researcher,56936,USD,56936,SE,FT,China,L,China,0,"Spark, Python, Tableau",Associate,7,Automotive,2024-09-14,2024-11-24,2347,6.1,Machine Intelligence Group -AI02466,Data Scientist,186597,SGD,242576,EX,FL,Singapore,M,Singapore,100,"Git, PyTorch, TensorFlow, Hadoop",PhD,12,Manufacturing,2024-09-12,2024-10-28,796,8.1,Quantum Computing Inc -AI02467,Autonomous Systems Engineer,98276,EUR,83535,MI,CT,Netherlands,M,South Korea,100,"Computer Vision, Hadoop, SQL",Associate,4,Finance,2024-09-29,2024-12-04,1681,7.8,Quantum Computing Inc -AI02468,Machine Learning Researcher,265980,EUR,226083,EX,FT,Netherlands,M,Netherlands,0,"Azure, Kubernetes, Tableau, Computer Vision, Statistics",Master,18,Consulting,2025-01-20,2025-02-15,1629,7.3,Neural Networks Co -AI02469,Principal Data Scientist,28831,USD,28831,EN,CT,China,S,Kenya,0,"Computer Vision, SQL, PyTorch, Docker, TensorFlow",Master,1,Energy,2024-09-23,2024-11-10,1887,7,DeepTech Ventures -AI02470,Machine Learning Engineer,41710,USD,41710,SE,FT,India,S,Mexico,100,"Docker, Java, Hadoop",Master,5,Finance,2024-06-11,2024-07-17,1648,9.4,Advanced Robotics -AI02471,AI Software Engineer,183499,JPY,20184890,SE,FT,Japan,L,Japan,0,"NLP, Git, Python, Java",Associate,8,Technology,2024-05-07,2024-06-21,1918,6.6,Cognitive Computing -AI02472,NLP Engineer,106203,CAD,132754,SE,PT,Canada,S,Canada,50,"Scala, Hadoop, Tableau, SQL, Deep Learning",Associate,6,Telecommunications,2024-06-02,2024-06-25,869,8.1,DataVision Ltd -AI02473,AI Architect,165971,USD,165971,EX,FL,Denmark,S,Denmark,0,"Docker, Hadoop, GCP",Associate,16,Consulting,2024-02-24,2024-05-06,584,7.4,Neural Networks Co -AI02474,Deep Learning Engineer,124861,USD,124861,MI,PT,Denmark,L,Denmark,0,"Kubernetes, Deep Learning, Scala, Java",Associate,4,Retail,2025-01-28,2025-04-11,2295,6,Smart Analytics -AI02475,AI Research Scientist,90314,USD,90314,MI,CT,Ireland,S,Ireland,0,"MLOps, NLP, PyTorch, Kubernetes",Associate,2,Education,2024-01-01,2024-01-18,1471,5.2,Cognitive Computing -AI02476,Data Engineer,82549,USD,82549,EN,PT,Denmark,S,Denmark,100,"Tableau, Java, SQL, Computer Vision, Kubernetes",Associate,0,Manufacturing,2024-03-05,2024-04-14,2066,6.2,DataVision Ltd -AI02477,ML Ops Engineer,24960,USD,24960,EN,FT,India,M,Norway,100,"Kubernetes, Hadoop, Java, Mathematics, Deep Learning",Associate,0,Retail,2025-04-16,2025-05-19,1088,7.1,DeepTech Ventures -AI02478,Deep Learning Engineer,106178,AUD,143340,MI,PT,Australia,M,Australia,0,"PyTorch, GCP, Kubernetes, Statistics, Computer Vision",Associate,3,Government,2024-03-30,2024-06-10,1148,5.2,Cognitive Computing -AI02479,Principal Data Scientist,136353,CHF,122718,MI,FT,Switzerland,M,Switzerland,100,"NLP, Azure, Tableau",Bachelor,4,Technology,2024-04-25,2024-06-29,1915,6.1,Algorithmic Solutions -AI02480,Machine Learning Researcher,140620,USD,140620,MI,FT,Denmark,L,Denmark,50,"NLP, Spark, Scala",Master,4,Technology,2025-03-20,2025-04-15,825,5.1,Predictive Systems -AI02481,Machine Learning Researcher,261035,USD,261035,EX,FT,Finland,L,Finland,50,"Python, AWS, Statistics, TensorFlow, NLP",Master,10,Technology,2024-03-14,2024-04-08,1299,8,Algorithmic Solutions -AI02482,Robotics Engineer,119849,SGD,155804,MI,CT,Singapore,L,Singapore,0,"SQL, PyTorch, Computer Vision",Master,3,Government,2024-04-09,2024-05-27,1022,6.5,Smart Analytics -AI02483,AI Consultant,58782,EUR,49965,EN,CT,Germany,S,Germany,50,"Hadoop, Linux, SQL, Computer Vision",Associate,1,Telecommunications,2025-03-24,2025-04-26,1785,7.7,Machine Intelligence Group -AI02484,Autonomous Systems Engineer,77795,GBP,58346,EN,FL,United Kingdom,L,United Kingdom,100,"Tableau, Python, Mathematics, Scala",Master,0,Gaming,2024-12-02,2025-01-30,1815,6.5,AI Innovations -AI02485,Data Analyst,162430,EUR,138066,EX,FT,Austria,M,Austria,0,"SQL, Scala, AWS, MLOps, NLP",Bachelor,15,Retail,2025-02-04,2025-03-07,621,7.6,DeepTech Ventures -AI02486,Robotics Engineer,156099,JPY,17170890,SE,FT,Japan,M,Poland,0,"Deep Learning, PyTorch, R",Associate,7,Gaming,2025-01-07,2025-01-30,2171,6.5,Predictive Systems -AI02487,NLP Engineer,105660,USD,105660,SE,FL,South Korea,M,South Korea,0,"Spark, PyTorch, Tableau, Statistics, AWS",Bachelor,6,Government,2024-11-30,2024-12-28,1284,6.4,TechCorp Inc -AI02488,ML Ops Engineer,100617,USD,100617,MI,PT,Finland,M,Ireland,0,"Docker, Scala, Data Visualization, NLP",Associate,2,Manufacturing,2025-04-04,2025-05-20,871,6.8,Cognitive Computing -AI02489,Deep Learning Engineer,85747,JPY,9432170,EN,PT,Japan,L,Japan,0,"GCP, Linux, SQL",Associate,0,Government,2024-07-26,2024-08-21,1790,8.8,DataVision Ltd -AI02490,AI Product Manager,103946,SGD,135130,MI,CT,Singapore,M,Singapore,0,"SQL, AWS, Tableau, Java, R",Master,3,Finance,2025-01-14,2025-03-22,2223,9.5,Advanced Robotics -AI02491,Deep Learning Engineer,163429,USD,163429,SE,PT,United States,L,Colombia,100,"Statistics, GCP, TensorFlow, Tableau",PhD,6,Real Estate,2025-04-18,2025-06-25,829,9.2,TechCorp Inc -AI02492,NLP Engineer,134989,CHF,121490,SE,CT,Switzerland,S,Ghana,100,"Azure, Deep Learning, Docker",Bachelor,8,Transportation,2024-05-27,2024-07-16,1154,6.9,Digital Transformation LLC -AI02493,AI Architect,232913,USD,232913,EX,PT,Israel,L,Israel,0,"AWS, MLOps, Data Visualization",PhD,14,Consulting,2025-03-19,2025-04-16,955,5.3,Cloud AI Solutions -AI02494,Machine Learning Researcher,72913,CHF,65622,EN,PT,Switzerland,S,Switzerland,0,"Scala, Python, TensorFlow, Spark, Linux",Master,1,Automotive,2024-06-13,2024-08-24,913,5.9,Neural Networks Co -AI02495,NLP Engineer,62004,CAD,77505,EN,CT,Canada,S,Poland,50,"TensorFlow, Statistics, Hadoop",Master,0,Government,2025-03-09,2025-05-19,2303,7.7,TechCorp Inc -AI02496,Head of AI,54572,USD,54572,EN,FL,Israel,S,Finland,100,"NLP, Scala, PyTorch",Bachelor,0,Retail,2025-04-27,2025-07-03,2392,8,Advanced Robotics -AI02497,Data Scientist,304083,CHF,273675,EX,FL,Switzerland,S,Switzerland,100,"Kubernetes, AWS, Python, Git",Master,15,Transportation,2024-06-20,2024-08-18,1922,7,Autonomous Tech -AI02498,Head of AI,263203,AUD,355324,EX,FL,Australia,L,Australia,0,"Java, Kubernetes, Tableau",PhD,18,Automotive,2024-08-26,2024-09-25,1516,8.6,DeepTech Ventures -AI02499,Machine Learning Researcher,78835,EUR,67010,EN,CT,Germany,L,Brazil,0,"Computer Vision, AWS, Data Visualization, Hadoop, PyTorch",Associate,1,Retail,2024-09-28,2024-11-29,2474,9.1,DeepTech Ventures -AI02500,AI Specialist,91165,USD,91165,EX,PT,China,M,China,0,"AWS, Spark, Git",PhD,10,Education,2024-08-02,2024-08-28,700,9,Quantum Computing Inc -AI02501,Robotics Engineer,141371,USD,141371,SE,PT,Finland,M,Turkey,100,"Java, Git, Mathematics, GCP, Hadoop",Bachelor,7,Consulting,2024-10-25,2024-12-27,1708,5.6,Quantum Computing Inc -AI02502,AI Architect,176050,EUR,149643,EX,FL,Austria,S,Austria,0,"Python, MLOps, TensorFlow",Associate,14,Gaming,2024-04-03,2024-05-04,1629,6.5,Advanced Robotics -AI02503,Research Scientist,164808,USD,164808,SE,PT,Norway,S,Norway,50,"Docker, SQL, Kubernetes, Java",Master,6,Real Estate,2024-08-17,2024-09-11,705,6.4,Cognitive Computing -AI02504,Principal Data Scientist,73825,USD,73825,MI,FL,South Korea,S,South Korea,50,"Spark, SQL, Computer Vision",Associate,3,Manufacturing,2025-01-24,2025-02-18,1905,6.6,TechCorp Inc -AI02505,Data Scientist,56305,USD,56305,EN,FT,Finland,M,Finland,100,"Java, Statistics, Git, Hadoop",Bachelor,0,Consulting,2024-06-29,2024-07-22,904,7.7,Advanced Robotics -AI02506,Computer Vision Engineer,95982,SGD,124777,MI,FT,Singapore,S,Singapore,0,"Scala, Spark, Tableau, SQL",Master,4,Telecommunications,2024-04-20,2024-06-29,2187,7.5,Machine Intelligence Group -AI02507,Robotics Engineer,139813,EUR,118841,EX,FL,France,S,France,100,"Python, Linux, Kubernetes",Bachelor,12,Automotive,2024-08-06,2024-08-27,2393,6.7,Quantum Computing Inc -AI02508,AI Architect,103705,CAD,129631,MI,PT,Canada,L,Canada,0,"Docker, Java, PyTorch",Bachelor,2,Finance,2024-01-12,2024-03-12,1589,6.5,TechCorp Inc -AI02509,AI Product Manager,90682,EUR,77080,MI,FT,Austria,M,Austria,100,"Computer Vision, Tableau, GCP",Master,2,Transportation,2025-03-08,2025-04-06,2327,7.9,Algorithmic Solutions -AI02510,Autonomous Systems Engineer,71388,EUR,60680,EN,PT,Netherlands,S,Belgium,50,"Linux, Git, Kubernetes",Associate,1,Manufacturing,2024-09-19,2024-11-16,1567,7,TechCorp Inc -AI02511,Deep Learning Engineer,96336,USD,96336,MI,PT,Israel,M,Vietnam,100,"Java, Linux, Tableau, Scala",Master,2,Transportation,2024-10-28,2024-12-19,2444,9.1,Advanced Robotics -AI02512,Deep Learning Engineer,128679,USD,128679,EX,CT,Finland,M,Finland,0,"R, Python, Linux",Master,10,Transportation,2024-06-29,2024-08-04,1288,8.4,Neural Networks Co -AI02513,Robotics Engineer,109988,EUR,93490,MI,FL,France,L,France,50,"SQL, MLOps, Java, Azure",Master,3,Retail,2025-02-11,2025-04-11,2329,7.8,Autonomous Tech -AI02514,Robotics Engineer,146873,EUR,124842,SE,FT,Netherlands,L,Vietnam,50,"Kubernetes, SQL, AWS, GCP",PhD,9,Real Estate,2025-03-16,2025-04-24,1914,7.5,TechCorp Inc -AI02515,Machine Learning Engineer,165141,USD,165141,EX,PT,South Korea,M,South Korea,0,"Java, Python, Tableau, Linux, Deep Learning",Master,15,Consulting,2024-03-10,2024-04-14,1945,5.9,Autonomous Tech -AI02516,Machine Learning Engineer,77901,AUD,105166,EN,FT,Australia,M,Australia,100,"Python, AWS, Statistics",Associate,0,Energy,2024-10-18,2024-12-03,2251,7.8,Smart Analytics -AI02517,Research Scientist,94620,SGD,123006,EN,PT,Singapore,L,New Zealand,100,"Hadoop, Java, Spark",Associate,1,Automotive,2024-09-22,2024-12-04,1019,8.6,Cloud AI Solutions -AI02518,Principal Data Scientist,162374,GBP,121781,SE,CT,United Kingdom,L,United Kingdom,50,"Git, Azure, Computer Vision, Mathematics, PyTorch",Associate,9,Retail,2024-03-08,2024-04-16,1503,9.9,Smart Analytics -AI02519,Data Engineer,85536,USD,85536,EN,FL,Finland,L,Finland,100,"MLOps, GCP, SQL",PhD,1,Automotive,2025-01-19,2025-03-17,1202,5.8,Future Systems -AI02520,Research Scientist,132794,GBP,99596,SE,PT,United Kingdom,M,United States,100,"NLP, Git, Python, Mathematics",PhD,7,Telecommunications,2024-10-07,2024-12-05,1060,10,Quantum Computing Inc -AI02521,Head of AI,51202,CAD,64003,EN,CT,Canada,S,Canada,50,"Mathematics, Deep Learning, Kubernetes",PhD,0,Transportation,2024-06-09,2024-07-26,2084,9,Machine Intelligence Group -AI02522,Machine Learning Researcher,105407,USD,105407,MI,CT,Ireland,M,Ireland,0,"Git, Hadoop, Scala, Spark",Bachelor,3,Technology,2024-07-15,2024-08-01,515,6.2,Algorithmic Solutions -AI02523,NLP Engineer,94037,USD,94037,MI,CT,Finland,M,Finland,50,"GCP, Kubernetes, R",Associate,3,Automotive,2024-07-15,2024-08-04,2256,7.6,Advanced Robotics -AI02524,Data Engineer,206898,EUR,175863,EX,FT,Austria,S,Austria,100,"Mathematics, Linux, MLOps",Associate,13,Healthcare,2024-01-10,2024-03-14,527,9.1,Digital Transformation LLC -AI02525,Deep Learning Engineer,243562,CHF,219206,EX,PT,Switzerland,M,Switzerland,0,"Git, Java, Data Visualization",Master,19,Telecommunications,2024-02-01,2024-02-15,1421,5,Machine Intelligence Group -AI02526,Data Analyst,51859,USD,51859,EN,PT,Ireland,S,Luxembourg,100,"Git, PyTorch, Statistics, Docker, Python",Master,1,Technology,2025-03-09,2025-03-28,1458,8.8,Quantum Computing Inc -AI02527,ML Ops Engineer,86795,USD,86795,MI,PT,Sweden,S,Sweden,100,"Tableau, GCP, Linux, Computer Vision, Java",Bachelor,4,Retail,2024-08-02,2024-09-20,659,9.1,Digital Transformation LLC -AI02528,AI Research Scientist,81483,EUR,69261,MI,CT,Germany,M,Ireland,50,"Linux, AWS, Python",Bachelor,4,Gaming,2025-03-26,2025-04-13,1391,9.8,AI Innovations -AI02529,ML Ops Engineer,269686,CHF,242717,EX,PT,Switzerland,M,Portugal,50,"Python, NLP, SQL, Linux, Git",PhD,10,Healthcare,2024-09-29,2024-10-17,1421,9.8,AI Innovations -AI02530,AI Architect,55579,USD,55579,EN,PT,South Korea,S,South Korea,50,"MLOps, Python, Deep Learning",Master,0,Education,2024-10-13,2024-11-05,1101,8.8,Predictive Systems -AI02531,AI Software Engineer,60607,USD,60607,EN,FT,Ireland,L,Ireland,0,"Data Visualization, SQL, GCP, Python, Mathematics",PhD,0,Energy,2024-12-16,2025-02-18,2279,5.8,Machine Intelligence Group -AI02532,NLP Engineer,131631,EUR,111886,SE,PT,Germany,M,Germany,50,"AWS, Data Visualization, Azure",Associate,7,Manufacturing,2024-08-12,2024-09-12,697,8.4,DeepTech Ventures -AI02533,Machine Learning Engineer,54944,EUR,46702,EN,FT,Germany,S,Germany,100,"Statistics, SQL, Python",Bachelor,0,Energy,2025-01-21,2025-03-29,975,7,Cognitive Computing -AI02534,AI Software Engineer,191195,CHF,172076,SE,PT,Switzerland,M,Switzerland,100,"PyTorch, Python, Docker, Kubernetes, Hadoop",Master,5,Healthcare,2024-12-02,2024-12-24,2199,5.2,AI Innovations -AI02535,Data Engineer,120333,CAD,150416,EX,FT,Canada,S,Brazil,100,"Java, NLP, MLOps, TensorFlow",Master,13,Government,2024-01-20,2024-02-03,2326,7.2,Smart Analytics -AI02536,Deep Learning Engineer,65699,USD,65699,EX,FT,China,S,China,0,"Statistics, SQL, Docker",Associate,17,Telecommunications,2025-03-21,2025-04-12,2252,6.9,AI Innovations -AI02537,AI Architect,64976,USD,64976,EN,PT,Israel,M,Luxembourg,0,"Tableau, Azure, Linux, Data Visualization",Master,1,Transportation,2024-02-06,2024-03-12,979,8,Cognitive Computing -AI02538,Research Scientist,209582,USD,209582,EX,CT,Denmark,M,Denmark,0,"SQL, Linux, Computer Vision, AWS",Bachelor,10,Government,2025-02-15,2025-04-19,1382,6.4,Smart Analytics -AI02539,Data Scientist,145591,USD,145591,SE,PT,United States,S,Austria,0,"Tableau, Git, PyTorch",Bachelor,7,Healthcare,2024-08-24,2024-10-18,1653,9.9,TechCorp Inc -AI02540,AI Product Manager,291098,USD,291098,EX,FL,Denmark,M,Denmark,100,"AWS, Kubernetes, R, Python, Statistics",Associate,16,Technology,2024-07-26,2024-09-14,2086,8.7,Algorithmic Solutions -AI02541,Autonomous Systems Engineer,196197,USD,196197,EX,FT,Sweden,L,Sweden,50,"Python, SQL, Kubernetes",Associate,11,Telecommunications,2024-05-04,2024-05-18,2425,8.7,Quantum Computing Inc -AI02542,Principal Data Scientist,186336,USD,186336,EX,PT,South Korea,L,France,0,"R, Docker, Java",Bachelor,10,Healthcare,2024-06-20,2024-07-20,1557,5.9,DataVision Ltd -AI02543,Data Scientist,62080,USD,62080,SE,PT,India,L,India,100,"Spark, Statistics, Data Visualization, Azure, Computer Vision",Bachelor,8,Manufacturing,2024-03-05,2024-04-18,774,6.8,Smart Analytics -AI02544,AI Software Engineer,85101,USD,85101,EN,FT,Denmark,S,Ireland,0,"NLP, Deep Learning, Git, Azure, R",Associate,1,Healthcare,2025-04-27,2025-05-12,1077,7.4,Quantum Computing Inc -AI02545,Robotics Engineer,149817,AUD,202253,SE,FT,Australia,M,Australia,0,"PyTorch, Computer Vision, MLOps, Statistics, Mathematics",Bachelor,7,Media,2024-02-07,2024-03-02,964,7.3,Algorithmic Solutions -AI02546,AI Architect,73727,EUR,62668,EN,FL,Austria,L,Austria,50,"GCP, Java, NLP, Computer Vision, Statistics",Associate,0,Retail,2025-03-09,2025-04-04,2292,6.1,Algorithmic Solutions -AI02547,Machine Learning Researcher,95260,USD,95260,EX,FT,China,L,China,100,"Docker, Git, R, SQL",Master,14,Education,2024-09-22,2024-10-16,1846,9.7,AI Innovations -AI02548,AI Specialist,59469,USD,59469,EN,CT,United States,S,United States,0,"R, Mathematics, Data Visualization, Deep Learning",Master,1,Transportation,2024-09-05,2024-10-06,1302,5.1,Digital Transformation LLC -AI02549,Data Engineer,95741,USD,95741,MI,CT,Ireland,S,Ireland,50,"TensorFlow, Spark, R, AWS, Linux",Master,4,Technology,2024-11-08,2024-11-29,836,6.9,Predictive Systems -AI02550,Data Analyst,99330,CHF,89397,EN,FT,Switzerland,S,Vietnam,0,"Kubernetes, Scala, Deep Learning, GCP",Master,1,Telecommunications,2024-01-22,2024-02-21,636,6.5,AI Innovations -AI02551,Data Engineer,169622,USD,169622,EX,PT,United States,M,United States,100,"GCP, Mathematics, Java, PyTorch",Associate,10,Media,2025-04-10,2025-05-02,1878,5.7,Autonomous Tech -AI02552,NLP Engineer,34014,USD,34014,MI,CT,India,L,India,0,"AWS, R, Kubernetes",Master,2,Government,2024-10-16,2024-11-25,2084,5.6,Advanced Robotics -AI02553,Deep Learning Engineer,48009,EUR,40808,EN,CT,France,S,France,100,"Linux, Java, R, Tableau",Associate,1,Automotive,2024-06-20,2024-07-05,1365,8.1,Quantum Computing Inc -AI02554,Machine Learning Researcher,186879,USD,186879,EX,FL,Ireland,M,United States,0,"Tableau, R, Linux",PhD,13,Consulting,2024-10-22,2024-12-05,923,7.4,Machine Intelligence Group -AI02555,Machine Learning Engineer,43587,USD,43587,SE,CT,India,L,Kenya,100,"Mathematics, Tableau, Azure, Linux",Bachelor,6,Government,2024-07-03,2024-07-22,1803,7.8,Algorithmic Solutions -AI02556,AI Product Manager,296908,USD,296908,EX,FT,Denmark,M,Denmark,0,"Scala, PyTorch, AWS, SQL",Associate,17,Education,2024-01-14,2024-02-12,963,8.2,DeepTech Ventures -AI02557,Principal Data Scientist,185850,CHF,167265,SE,FL,Switzerland,L,Switzerland,0,"Linux, Kubernetes, PyTorch, Deep Learning, Docker",Associate,9,Manufacturing,2025-01-19,2025-02-27,1056,9.1,Advanced Robotics -AI02558,AI Specialist,171053,CAD,213816,EX,CT,Canada,M,Canada,50,"GCP, Kubernetes, Data Visualization, Scala",Associate,18,Finance,2024-04-10,2024-05-30,1822,6.7,Quantum Computing Inc -AI02559,ML Ops Engineer,149653,EUR,127205,EX,PT,France,L,France,0,"Computer Vision, Mathematics, Scala, Data Visualization, Python",PhD,13,Transportation,2024-11-02,2024-11-16,1909,5.8,TechCorp Inc -AI02560,AI Specialist,86772,USD,86772,MI,PT,United States,M,United States,0,"TensorFlow, Kubernetes, PyTorch, Azure",PhD,3,Government,2024-06-25,2024-07-14,934,6.9,AI Innovations -AI02561,Machine Learning Researcher,80745,EUR,68633,MI,FL,Austria,L,Austria,100,"Data Visualization, Python, Spark",Master,4,Healthcare,2024-08-07,2024-09-05,2274,7.6,Autonomous Tech -AI02562,Principal Data Scientist,88333,CAD,110416,MI,FT,Canada,L,Canada,100,"MLOps, GCP, Java, Hadoop",Master,3,Transportation,2024-10-31,2025-01-03,1219,7.5,Quantum Computing Inc -AI02563,Data Engineer,294564,CHF,265108,EX,FT,Switzerland,M,United States,0,"Git, Python, TensorFlow",Master,16,Healthcare,2024-02-28,2024-05-10,1523,9,DeepTech Ventures -AI02564,Autonomous Systems Engineer,151837,USD,151837,SE,FL,United States,S,Estonia,100,"SQL, Mathematics, Tableau, Git",Master,6,Automotive,2025-03-24,2025-04-23,1538,6.9,Algorithmic Solutions -AI02565,Deep Learning Engineer,258351,USD,258351,EX,FL,United States,M,United States,50,"Python, TensorFlow, Scala, Deep Learning",Associate,14,Transportation,2024-12-24,2025-02-14,2412,8.3,AI Innovations -AI02566,AI Specialist,93903,CAD,117379,SE,CT,Canada,S,Canada,50,"Java, MLOps, Statistics, Tableau, Linux",PhD,5,Education,2025-02-20,2025-04-17,968,5.6,Cloud AI Solutions -AI02567,AI Product Manager,129113,USD,129113,SE,CT,Israel,S,Israel,0,"Hadoop, Computer Vision, Kubernetes, R, Docker",Bachelor,9,Automotive,2024-09-30,2024-10-16,2205,8.5,Future Systems -AI02568,AI Software Engineer,86397,EUR,73437,EN,PT,Germany,L,Germany,0,"Computer Vision, Git, Kubernetes, PyTorch",Bachelor,1,Automotive,2024-07-19,2024-09-25,1310,6.3,Algorithmic Solutions -AI02569,Autonomous Systems Engineer,124460,USD,124460,SE,CT,Sweden,M,Brazil,100,"SQL, Scala, Python, AWS, Hadoop",Master,9,Healthcare,2024-06-08,2024-07-07,2132,9.4,AI Innovations -AI02570,Data Engineer,149448,EUR,127031,EX,FT,France,M,France,50,"MLOps, Mathematics, Data Visualization",Master,18,Retail,2024-03-30,2024-04-17,1536,9.8,DeepTech Ventures -AI02571,Data Engineer,58804,EUR,49983,EN,PT,Germany,M,Germany,0,"Statistics, Java, Spark",Associate,1,Healthcare,2024-04-24,2024-06-19,609,7,Cloud AI Solutions -AI02572,AI Consultant,79567,CHF,71610,EN,FL,Switzerland,S,United States,100,"TensorFlow, Deep Learning, Computer Vision",PhD,0,Retail,2024-07-18,2024-08-09,1174,7.3,DataVision Ltd -AI02573,AI Specialist,92586,EUR,78698,MI,PT,Austria,M,Austria,50,"Python, Deep Learning, Kubernetes, Computer Vision",Master,4,Energy,2024-10-19,2024-11-02,739,7.1,Neural Networks Co -AI02574,Data Engineer,88553,JPY,9740830,EN,PT,Japan,L,Italy,0,"PyTorch, Computer Vision, Deep Learning",Associate,0,Finance,2025-01-25,2025-03-24,903,7,DeepTech Ventures -AI02575,Deep Learning Engineer,180911,EUR,153774,EX,FT,Netherlands,M,Netherlands,50,"Kubernetes, Statistics, R, Python, Mathematics",Master,13,Retail,2024-09-29,2024-11-13,1874,6.6,TechCorp Inc -AI02576,Computer Vision Engineer,180125,USD,180125,SE,FL,United States,L,United States,100,"TensorFlow, SQL, Git, AWS",Associate,8,Automotive,2024-12-07,2024-12-21,2412,8.4,Machine Intelligence Group -AI02577,Computer Vision Engineer,52185,EUR,44357,EN,FT,France,S,France,50,"R, Spark, TensorFlow, Data Visualization, SQL",Master,1,Retail,2024-06-27,2024-08-22,2119,9.3,Smart Analytics -AI02578,Machine Learning Researcher,246154,EUR,209231,EX,CT,Austria,L,Austria,0,"Deep Learning, Computer Vision, TensorFlow, Scala",Associate,14,Finance,2025-01-05,2025-03-07,1880,9.6,Cognitive Computing -AI02579,AI Specialist,57512,EUR,48885,EN,FL,Netherlands,M,Australia,100,"Statistics, PyTorch, SQL, Scala, Data Visualization",Associate,0,Consulting,2024-03-23,2024-04-19,575,6.8,AI Innovations -AI02580,Head of AI,170182,CHF,153164,MI,FT,Switzerland,L,Switzerland,0,"TensorFlow, Java, GCP",Master,2,Retail,2024-02-07,2024-03-03,1519,6.4,Cloud AI Solutions -AI02581,Data Scientist,40011,USD,40011,MI,CT,China,M,China,100,"Linux, Tableau, Spark, Java",Associate,3,Finance,2024-07-25,2024-08-30,1950,9.5,DeepTech Ventures -AI02582,Machine Learning Engineer,112165,GBP,84124,SE,CT,United Kingdom,M,Japan,100,"GCP, Kubernetes, Java, SQL, Deep Learning",Associate,7,Finance,2024-07-22,2024-09-02,1763,5.6,Smart Analytics -AI02583,Head of AI,118931,USD,118931,SE,CT,Ireland,L,Ireland,100,"Python, GCP, Scala",PhD,8,Government,2024-09-21,2024-10-28,1210,9,Cognitive Computing -AI02584,AI Specialist,163364,USD,163364,SE,FL,Finland,L,Mexico,0,"PyTorch, Spark, TensorFlow",Bachelor,8,Government,2025-01-06,2025-02-18,1293,6.9,Cloud AI Solutions -AI02585,Data Scientist,131301,USD,131301,EX,FL,South Korea,S,South Korea,0,"Linux, Spark, Deep Learning, Kubernetes",PhD,18,Education,2024-04-10,2024-05-02,2382,7.5,Quantum Computing Inc -AI02586,AI Software Engineer,68441,USD,68441,MI,PT,Ireland,S,Ireland,50,"Kubernetes, Statistics, GCP, Tableau",Master,4,Real Estate,2024-10-02,2024-10-20,1488,8.3,DataVision Ltd -AI02587,Robotics Engineer,135907,USD,135907,MI,CT,United States,L,United States,0,"NLP, GCP, Tableau",PhD,2,Energy,2024-09-26,2024-11-28,597,6.5,Machine Intelligence Group -AI02588,AI Architect,99860,EUR,84881,SE,FT,France,M,France,100,"PyTorch, AWS, NLP, Java, Azure",Master,6,Telecommunications,2024-06-19,2024-08-27,654,8.9,Quantum Computing Inc -AI02589,NLP Engineer,91537,USD,91537,MI,FL,South Korea,L,Argentina,100,"PyTorch, Tableau, NLP, TensorFlow",PhD,3,Telecommunications,2025-03-21,2025-05-29,845,6.9,Future Systems -AI02590,AI Specialist,167565,USD,167565,SE,PT,United States,M,France,50,"Hadoop, Azure, Deep Learning",Master,5,Energy,2024-07-10,2024-08-21,916,6.8,Digital Transformation LLC -AI02591,Machine Learning Researcher,102636,SGD,133427,MI,PT,Singapore,L,Singapore,100,"SQL, MLOps, PyTorch, Data Visualization, TensorFlow",Associate,2,Energy,2024-10-20,2024-12-13,663,7.1,Future Systems -AI02592,AI Consultant,116030,EUR,98626,SE,CT,Germany,M,Germany,100,"TensorFlow, Linux, PyTorch, GCP, Azure",PhD,6,Media,2024-04-05,2024-05-13,1375,5.9,Machine Intelligence Group -AI02593,AI Architect,84644,CAD,105805,EN,PT,Canada,L,Canada,100,"Kubernetes, Python, Hadoop",Master,1,Government,2024-12-25,2025-02-16,2101,8.9,Predictive Systems -AI02594,Research Scientist,65082,AUD,87861,EN,CT,Australia,M,Nigeria,50,"Python, Deep Learning, Kubernetes, Linux",PhD,1,Energy,2024-07-17,2024-08-06,1907,8.2,DataVision Ltd -AI02595,AI Software Engineer,62534,AUD,84421,EN,PT,Australia,M,Australia,50,"Python, Git, TensorFlow",Master,0,Telecommunications,2024-11-26,2025-01-12,2305,6.5,DeepTech Ventures -AI02596,AI Specialist,241137,CHF,217023,SE,FT,Switzerland,L,Switzerland,50,"Spark, Kubernetes, Tableau, Python, Statistics",Master,5,Education,2024-12-05,2025-02-04,1926,7.6,Machine Intelligence Group -AI02597,AI Software Engineer,85906,USD,85906,EN,PT,Finland,L,Finland,50,"Statistics, Linux, Scala, Kubernetes",Associate,1,Media,2024-10-21,2024-11-27,1026,7.7,Cognitive Computing -AI02598,Data Scientist,99399,USD,99399,SE,FT,South Korea,S,Singapore,50,"R, Python, Mathematics",Master,9,Real Estate,2024-03-21,2024-04-10,1095,5,Machine Intelligence Group -AI02599,Machine Learning Engineer,69551,USD,69551,EN,FL,Denmark,S,Denmark,0,"Docker, Python, Hadoop, SQL",Associate,0,Transportation,2024-10-24,2024-11-21,1355,6.4,Quantum Computing Inc -AI02600,Autonomous Systems Engineer,98388,USD,98388,MI,FT,South Korea,L,South Korea,0,"Python, Computer Vision, TensorFlow",Bachelor,4,Energy,2024-07-23,2024-09-17,1870,5.8,Machine Intelligence Group -AI02601,NLP Engineer,59613,CAD,74516,EN,CT,Canada,M,Canada,100,"Computer Vision, R, Docker",PhD,1,Retail,2024-02-07,2024-03-06,1939,6.2,Advanced Robotics -AI02602,AI Software Engineer,84934,USD,84934,EN,FL,United States,S,United States,100,"Computer Vision, Deep Learning, Tableau, Linux",Master,0,Telecommunications,2024-08-16,2024-10-18,1161,6.7,Quantum Computing Inc -AI02603,Data Analyst,86399,USD,86399,EX,FT,India,L,India,50,"Docker, R, Linux",Associate,18,Technology,2024-07-23,2024-09-10,1885,7.5,AI Innovations -AI02604,Data Scientist,167659,AUD,226340,SE,FT,Australia,L,Australia,50,"Kubernetes, TensorFlow, Spark, SQL",PhD,8,Education,2024-12-30,2025-01-22,1211,6.1,Digital Transformation LLC -AI02605,Data Engineer,101084,AUD,136463,MI,CT,Australia,L,Australia,100,"Java, TensorFlow, AWS, Computer Vision",Bachelor,2,Manufacturing,2024-08-01,2024-09-11,724,8.4,Neural Networks Co -AI02606,AI Architect,32520,USD,32520,EN,CT,China,M,Romania,50,"GCP, Linux, Statistics",PhD,1,Technology,2025-02-02,2025-03-08,1144,6.9,Smart Analytics -AI02607,Data Scientist,109024,EUR,92670,SE,FT,Germany,S,Germany,100,"Azure, SQL, TensorFlow, Tableau, Deep Learning",Bachelor,6,Real Estate,2024-09-11,2024-11-10,931,7.8,Predictive Systems -AI02608,AI Consultant,130052,USD,130052,SE,CT,Norway,S,Portugal,100,"Python, PyTorch, Data Visualization, Kubernetes",Associate,8,Healthcare,2025-02-22,2025-03-09,1571,5.6,DeepTech Ventures -AI02609,Deep Learning Engineer,118889,EUR,101056,MI,PT,Austria,L,Austria,50,"Tableau, Deep Learning, Kubernetes",PhD,2,Energy,2024-04-11,2024-05-13,2266,9.5,Smart Analytics -AI02610,Robotics Engineer,120628,USD,120628,EX,FT,Finland,S,Egypt,100,"Hadoop, Linux, Azure, MLOps, Kubernetes",Associate,15,Automotive,2024-04-26,2024-06-12,1815,9.4,DataVision Ltd -AI02611,AI Specialist,74800,CAD,93500,EN,FT,Canada,L,Canada,0,"Azure, Hadoop, Kubernetes, TensorFlow, Statistics",PhD,0,Automotive,2024-07-20,2024-09-04,688,5.2,Quantum Computing Inc -AI02612,AI Software Engineer,64207,GBP,48155,EN,PT,United Kingdom,M,Portugal,0,"Docker, GCP, SQL, AWS",Associate,1,Technology,2024-10-24,2025-01-03,2149,8.1,AI Innovations -AI02613,Computer Vision Engineer,133828,CHF,120445,MI,FT,Switzerland,S,Indonesia,100,"Scala, Spark, Data Visualization, R, Git",Associate,2,Automotive,2025-01-26,2025-02-17,1345,8.3,Advanced Robotics -AI02614,AI Product Manager,79575,AUD,107426,EN,FL,Australia,L,Australia,0,"Linux, AWS, Scala, PyTorch, Docker",Bachelor,1,Energy,2024-01-10,2024-03-18,1969,7.7,Advanced Robotics -AI02615,Autonomous Systems Engineer,131921,AUD,178093,SE,CT,Australia,M,Australia,100,"PyTorch, AWS, Tableau",Bachelor,7,Healthcare,2024-04-25,2024-05-22,546,7.1,Predictive Systems -AI02616,Machine Learning Engineer,237422,USD,237422,EX,FL,Denmark,L,Vietnam,100,"Scala, TensorFlow, SQL, NLP",PhD,18,Retail,2024-08-31,2024-10-04,2210,7.3,Cloud AI Solutions -AI02617,Computer Vision Engineer,78318,EUR,66570,MI,FL,Germany,S,Germany,100,"Data Visualization, Python, Java",Bachelor,2,Manufacturing,2025-04-03,2025-06-10,1370,8.5,Cognitive Computing -AI02618,Autonomous Systems Engineer,108458,EUR,92189,MI,FL,Netherlands,L,Netherlands,100,"Docker, Java, Computer Vision",Bachelor,2,Manufacturing,2024-09-26,2024-11-10,524,7,Smart Analytics -AI02619,Data Analyst,263428,GBP,197571,EX,CT,United Kingdom,M,United Kingdom,100,"MLOps, GCP, Python, TensorFlow, Scala",PhD,18,Gaming,2024-04-28,2024-06-10,1293,5.8,Digital Transformation LLC -AI02620,AI Consultant,46582,USD,46582,MI,PT,China,S,China,100,"MLOps, Deep Learning, Python, NLP, Scala",Bachelor,3,Automotive,2024-03-12,2024-05-14,1625,6.3,DeepTech Ventures -AI02621,Robotics Engineer,169033,SGD,219743,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Data Visualization",PhD,17,Healthcare,2025-03-06,2025-03-24,1506,8.4,TechCorp Inc -AI02622,Machine Learning Researcher,59167,USD,59167,MI,FL,South Korea,S,South Korea,0,"Statistics, Git, Linux, GCP, Computer Vision",Bachelor,2,Telecommunications,2024-12-18,2025-02-14,965,7.3,AI Innovations -AI02623,Deep Learning Engineer,76863,SGD,99922,EN,PT,Singapore,S,Singapore,0,"AWS, Hadoop, NLP, Python, Scala",Master,0,Telecommunications,2024-11-17,2024-12-20,1525,6.4,Quantum Computing Inc -AI02624,Research Scientist,54769,USD,54769,EN,FL,South Korea,S,South Korea,0,"Python, Scala, Java",Bachelor,1,Consulting,2024-12-10,2025-02-10,1118,7.9,TechCorp Inc -AI02625,AI Product Manager,227468,USD,227468,EX,FT,United States,M,Colombia,50,"Linux, TensorFlow, Deep Learning",Master,14,Retail,2024-01-03,2024-03-10,1849,7.9,Algorithmic Solutions -AI02626,Deep Learning Engineer,27385,USD,27385,EN,FT,China,S,Malaysia,50,"TensorFlow, Python, R, Statistics, Spark",PhD,0,Consulting,2024-11-22,2025-01-28,1243,5.3,Quantum Computing Inc -AI02627,NLP Engineer,192062,USD,192062,EX,PT,Norway,M,Norway,100,"TensorFlow, SQL, Mathematics",PhD,10,Real Estate,2024-08-07,2024-09-27,1863,5.4,Cloud AI Solutions -AI02628,Data Analyst,84809,USD,84809,MI,FL,Israel,M,Israel,100,"TensorFlow, AWS, Python, Computer Vision, Scala",Associate,4,Automotive,2024-11-27,2024-12-31,519,8.3,Algorithmic Solutions -AI02629,Computer Vision Engineer,129372,USD,129372,SE,CT,Israel,M,Ukraine,50,"Deep Learning, MLOps, Azure, Java",Master,6,Transportation,2024-03-19,2024-04-04,2253,6.9,Neural Networks Co -AI02630,Principal Data Scientist,61768,CAD,77210,EN,FT,Canada,L,Canada,100,"Java, Git, Kubernetes, PyTorch, Data Visualization",Associate,1,Automotive,2024-02-26,2024-03-14,1170,7.5,Cloud AI Solutions -AI02631,AI Product Manager,33922,USD,33922,EN,CT,China,M,China,100,"Spark, Python, Git, Linux",Associate,0,Technology,2024-07-17,2024-08-15,590,7.1,Algorithmic Solutions -AI02632,Research Scientist,127911,USD,127911,SE,PT,Sweden,M,Sweden,100,"AWS, Python, TensorFlow, Statistics, Deep Learning",Bachelor,6,Real Estate,2024-08-14,2024-09-15,847,9.3,Future Systems -AI02633,AI Consultant,132207,EUR,112376,EX,CT,Austria,S,Austria,100,"Hadoop, Python, Statistics",Master,16,Automotive,2024-01-29,2024-03-16,1880,7.1,Cloud AI Solutions -AI02634,AI Specialist,60862,CAD,76078,EN,CT,Canada,S,United Kingdom,0,"SQL, Computer Vision, Tableau, PyTorch, Scala",PhD,1,Healthcare,2024-07-26,2024-09-06,1914,5.5,Autonomous Tech -AI02635,Machine Learning Researcher,30483,USD,30483,MI,FT,India,S,India,100,"Kubernetes, NLP, Linux",PhD,2,Finance,2024-12-21,2025-01-15,2424,9,TechCorp Inc -AI02636,AI Product Manager,99046,USD,99046,MI,FL,Denmark,S,Denmark,0,"MLOps, R, Kubernetes",Associate,4,Healthcare,2024-12-15,2025-01-30,990,8.9,Quantum Computing Inc -AI02637,AI Product Manager,126174,USD,126174,MI,CT,Denmark,S,New Zealand,0,"Data Visualization, Kubernetes, Scala, Python",Associate,3,Healthcare,2024-06-25,2024-08-27,877,6.1,Cognitive Computing -AI02638,Deep Learning Engineer,226713,USD,226713,EX,FT,Denmark,S,South Africa,50,"Python, TensorFlow, Docker, Mathematics",Bachelor,11,Education,2025-03-16,2025-05-04,760,8.7,Advanced Robotics -AI02639,Robotics Engineer,66662,SGD,86661,EN,PT,Singapore,L,Singapore,100,"Data Visualization, Linux, Kubernetes, Spark, SQL",Bachelor,0,Consulting,2024-03-03,2024-03-28,2192,6.7,Autonomous Tech -AI02640,Machine Learning Engineer,156202,USD,156202,EX,CT,Ireland,S,China,0,"TensorFlow, Data Visualization, Python",Bachelor,14,Media,2024-05-14,2024-06-15,1849,6.6,Predictive Systems -AI02641,ML Ops Engineer,106445,USD,106445,SE,CT,South Korea,S,South Korea,50,"Docker, Deep Learning, Python, GCP, Mathematics",Master,9,Technology,2025-02-01,2025-03-31,2203,7.7,Advanced Robotics -AI02642,Research Scientist,57527,USD,57527,SE,CT,China,L,China,50,"R, SQL, Scala, Tableau, AWS",Associate,7,Telecommunications,2024-11-24,2024-12-18,1466,9.9,DataVision Ltd -AI02643,Data Analyst,71613,USD,71613,EN,CT,Ireland,L,Norway,0,"Azure, Python, GCP, TensorFlow, MLOps",Associate,1,Media,2024-05-12,2024-06-06,1682,8.8,Quantum Computing Inc -AI02644,Data Engineer,214057,USD,214057,SE,FT,Norway,L,Norway,0,"Scala, Deep Learning, Computer Vision, Data Visualization, Docker",PhD,9,Education,2024-12-11,2025-02-03,1422,7.3,DeepTech Ventures -AI02645,AI Research Scientist,113033,USD,113033,SE,PT,Finland,L,Finland,50,"MLOps, Spark, Azure",Bachelor,6,Media,2024-10-07,2024-10-21,1899,6.8,Advanced Robotics -AI02646,Computer Vision Engineer,83831,AUD,113172,MI,FT,Australia,L,Philippines,50,"Scala, Hadoop, Linux, SQL",Associate,4,Retail,2025-02-21,2025-03-25,904,5.3,Cloud AI Solutions -AI02647,Deep Learning Engineer,130289,USD,130289,SE,CT,United States,S,United States,0,"Kubernetes, Scala, Deep Learning",Associate,6,Government,2025-03-10,2025-04-15,2201,9.8,Algorithmic Solutions -AI02648,Data Engineer,128723,CAD,160904,SE,CT,Canada,S,Canada,100,"Scala, Tableau, Python",Master,7,Transportation,2024-09-11,2024-11-13,1131,5.8,DeepTech Ventures -AI02649,AI Consultant,197237,AUD,266270,EX,FL,Australia,S,Australia,0,"Hadoop, Python, Tableau, SQL",Associate,10,Telecommunications,2024-10-10,2024-12-10,2281,6.6,Future Systems -AI02650,Machine Learning Engineer,49680,USD,49680,MI,FL,China,L,China,100,"AWS, Spark, Tableau, NLP, Kubernetes",PhD,2,Finance,2024-02-26,2024-03-20,785,9.9,Future Systems -AI02651,Computer Vision Engineer,79494,USD,79494,MI,CT,United States,S,Indonesia,0,"Scala, Spark, Hadoop",Bachelor,3,Finance,2025-01-07,2025-02-24,1427,6.2,Algorithmic Solutions -AI02652,Data Engineer,120305,SGD,156397,MI,PT,Singapore,L,Singapore,0,"Computer Vision, SQL, Docker, Python, Hadoop",Bachelor,3,Education,2024-09-24,2024-10-18,1572,8.5,Algorithmic Solutions -AI02653,Research Scientist,109402,USD,109402,EX,FL,South Korea,S,South Korea,50,"Python, Scala, TensorFlow, Java, AWS",Bachelor,11,Telecommunications,2024-08-30,2024-10-25,2305,9,Machine Intelligence Group -AI02654,Computer Vision Engineer,131199,SGD,170559,MI,CT,Singapore,L,Russia,50,"R, Linux, Statistics, Spark",Bachelor,3,Consulting,2024-01-25,2024-03-19,593,7.2,TechCorp Inc -AI02655,Data Engineer,89303,USD,89303,MI,PT,Israel,L,Israel,0,"PyTorch, Mathematics, SQL, Scala, NLP",Associate,4,Energy,2024-03-25,2024-04-20,1319,8.3,TechCorp Inc -AI02656,AI Consultant,152868,AUD,206372,EX,FL,Australia,S,United States,0,"Hadoop, Java, Git, Statistics, Spark",PhD,13,Telecommunications,2025-02-13,2025-03-16,1303,6.8,Cloud AI Solutions -AI02657,Machine Learning Engineer,77521,USD,77521,MI,CT,South Korea,L,South Korea,50,"Spark, Hadoop, Tableau, MLOps, Linux",Associate,2,Finance,2025-01-25,2025-04-07,2414,8.6,DataVision Ltd -AI02658,ML Ops Engineer,140909,GBP,105682,SE,FT,United Kingdom,S,United Kingdom,100,"AWS, R, SQL",Master,9,Government,2024-01-14,2024-03-24,1248,9,Future Systems -AI02659,Data Engineer,156224,USD,156224,EX,CT,Finland,L,Finland,0,"Azure, Data Visualization, Statistics",PhD,18,Telecommunications,2024-09-21,2024-10-17,1780,9.1,DataVision Ltd -AI02660,AI Software Engineer,98611,SGD,128194,MI,FT,Singapore,M,Chile,100,"MLOps, Git, Kubernetes",Associate,3,Healthcare,2024-09-14,2024-10-16,1867,9.6,Algorithmic Solutions -AI02661,AI Research Scientist,129667,USD,129667,SE,CT,Ireland,M,South Korea,50,"Hadoop, Data Visualization, SQL, MLOps",Bachelor,7,Real Estate,2024-01-26,2024-02-17,2455,5.6,Cognitive Computing -AI02662,AI Research Scientist,143589,EUR,122051,SE,PT,Austria,M,Germany,50,"Scala, GCP, Computer Vision, Statistics, Tableau",PhD,5,Manufacturing,2024-03-04,2024-05-01,1222,6.3,Quantum Computing Inc -AI02663,Deep Learning Engineer,102918,USD,102918,EN,FT,United States,L,Luxembourg,100,"Python, TensorFlow, Deep Learning, R",Master,0,Finance,2025-04-08,2025-05-19,2329,7.7,DataVision Ltd -AI02664,NLP Engineer,233285,EUR,198292,EX,FT,Austria,L,Ukraine,100,"MLOps, R, Computer Vision",Master,10,Finance,2025-01-12,2025-02-20,1375,6.2,Neural Networks Co -AI02665,AI Research Scientist,161043,USD,161043,SE,FL,United States,M,United States,100,"PyTorch, Spark, Mathematics",Master,5,Energy,2024-07-18,2024-09-21,1559,9.8,Advanced Robotics -AI02666,AI Architect,184501,GBP,138376,EX,FL,United Kingdom,L,Russia,100,"Statistics, TensorFlow, Deep Learning",Associate,18,Consulting,2024-12-10,2025-01-13,1574,6.9,Digital Transformation LLC -AI02667,NLP Engineer,77968,USD,77968,EX,PT,India,S,India,50,"Deep Learning, Spark, MLOps, Hadoop, SQL",Bachelor,10,Retail,2024-03-06,2024-05-16,585,6.2,Digital Transformation LLC -AI02668,AI Architect,251626,USD,251626,EX,PT,United States,S,Argentina,50,"Mathematics, Data Visualization, MLOps, Docker",Bachelor,17,Media,2024-12-30,2025-02-08,2096,7.4,Neural Networks Co -AI02669,AI Product Manager,93801,USD,93801,MI,FL,Finland,L,Malaysia,100,"Python, Git, SQL, Docker",PhD,3,Retail,2024-01-24,2024-02-21,1501,8.3,AI Innovations -AI02670,Autonomous Systems Engineer,85270,USD,85270,EN,FL,United States,M,Indonesia,100,"Spark, Scala, AWS, Deep Learning",PhD,0,Government,2024-01-09,2024-01-24,1067,8.8,DataVision Ltd -AI02671,AI Product Manager,116844,USD,116844,EX,PT,South Korea,S,Malaysia,50,"Docker, Spark, Python, Java",Master,12,Transportation,2025-03-17,2025-04-17,2064,9.8,TechCorp Inc -AI02672,AI Consultant,115484,USD,115484,SE,FL,Finland,S,Finland,0,"Kubernetes, Spark, Git, Computer Vision, Java",Master,6,Gaming,2024-09-16,2024-10-28,1669,5.3,Digital Transformation LLC -AI02673,NLP Engineer,215938,USD,215938,EX,CT,Norway,M,Australia,100,"Linux, Kubernetes, Mathematics, SQL",Bachelor,15,Consulting,2024-01-06,2024-01-25,920,8.1,Smart Analytics -AI02674,Head of AI,112832,USD,112832,SE,FT,Ireland,S,Ireland,0,"R, SQL, Tableau, PyTorch, Java",Master,9,Consulting,2024-03-11,2024-05-17,1000,6.1,AI Innovations -AI02675,Principal Data Scientist,375327,CHF,337794,EX,CT,Switzerland,L,South Africa,0,"SQL, Python, Deep Learning, Kubernetes",Bachelor,12,Automotive,2025-02-23,2025-03-23,700,7.9,DeepTech Ventures -AI02676,AI Product Manager,167432,CHF,150689,SE,FL,Switzerland,M,United Kingdom,50,"Statistics, NLP, MLOps, Linux",Master,9,Healthcare,2024-11-02,2024-12-20,1081,7.9,Machine Intelligence Group -AI02677,Autonomous Systems Engineer,117408,CHF,105667,MI,PT,Switzerland,L,Switzerland,50,"Scala, MLOps, Hadoop, SQL",Master,2,Healthcare,2024-01-14,2024-03-16,2132,7.4,Neural Networks Co -AI02678,Research Scientist,76644,USD,76644,MI,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Data Visualization",Bachelor,3,Technology,2024-02-28,2024-04-09,2292,6,TechCorp Inc -AI02679,Autonomous Systems Engineer,80930,USD,80930,EN,FL,Finland,L,Finland,100,"Git, MLOps, Tableau",Associate,1,Consulting,2024-01-14,2024-03-14,1105,9.2,Predictive Systems -AI02680,ML Ops Engineer,96017,EUR,81614,MI,FL,Austria,M,Austria,0,"Python, Git, NLP, Mathematics, TensorFlow",Master,3,Energy,2024-09-23,2024-10-30,1268,9.5,Predictive Systems -AI02681,Deep Learning Engineer,85062,USD,85062,EN,PT,Denmark,L,Denmark,0,"Kubernetes, Statistics, Python, Java",PhD,0,Education,2024-05-05,2024-07-11,1703,6.8,Advanced Robotics -AI02682,Data Analyst,123126,EUR,104657,SE,FT,France,L,Luxembourg,50,"Linux, SQL, R",Bachelor,9,Manufacturing,2024-02-21,2024-03-25,2431,6.2,DataVision Ltd -AI02683,Robotics Engineer,131093,USD,131093,EX,FL,Finland,M,Finland,50,"PyTorch, Mathematics, Git, R",PhD,13,Real Estate,2024-06-10,2024-08-22,1037,9.8,Advanced Robotics -AI02684,Data Scientist,110151,JPY,12116610,MI,FL,Japan,M,Malaysia,0,"Git, AWS, Python, Kubernetes, Docker",Bachelor,2,Real Estate,2024-01-11,2024-02-05,1352,8.1,Algorithmic Solutions -AI02685,NLP Engineer,120418,CHF,108376,MI,FL,Switzerland,M,Switzerland,0,"GCP, Docker, Mathematics",Master,4,Technology,2025-04-25,2025-06-18,1356,8.8,Quantum Computing Inc -AI02686,Data Analyst,135377,USD,135377,EX,FL,South Korea,L,South Korea,100,"Spark, SQL, Linux, Azure, AWS",Master,10,Transportation,2024-09-16,2024-11-10,784,6.7,Autonomous Tech -AI02687,ML Ops Engineer,87833,USD,87833,MI,FT,Ireland,L,Ireland,50,"Git, Azure, MLOps, Python",PhD,3,Technology,2024-01-10,2024-02-21,2222,8,Advanced Robotics -AI02688,AI Architect,227660,EUR,193511,EX,FL,Germany,S,Germany,50,"Computer Vision, Python, Deep Learning",Bachelor,15,Government,2024-10-16,2024-11-03,1915,9.8,DataVision Ltd -AI02689,Deep Learning Engineer,133632,USD,133632,EX,FT,China,L,China,0,"NLP, Python, Mathematics, GCP",Associate,15,Telecommunications,2024-12-31,2025-01-18,850,8.8,AI Innovations -AI02690,AI Software Engineer,78480,USD,78480,EN,FT,Norway,M,Norway,50,"Spark, Git, Deep Learning, Docker",Associate,1,Healthcare,2024-07-22,2024-08-28,1560,7.4,DeepTech Ventures -AI02691,Head of AI,206088,EUR,175175,EX,FT,France,M,China,0,"Statistics, Tableau, SQL, Data Visualization, PyTorch",Associate,14,Healthcare,2024-03-27,2024-05-28,821,9.3,Future Systems -AI02692,Head of AI,153198,CAD,191498,SE,PT,Canada,L,Canada,100,"Linux, Mathematics, Deep Learning, PyTorch, Azure",Master,9,Transportation,2025-02-01,2025-02-21,1912,8.2,Machine Intelligence Group -AI02693,Head of AI,92186,EUR,78358,MI,FT,France,M,France,100,"Deep Learning, Python, Spark",PhD,2,Retail,2024-09-07,2024-09-28,612,7.8,Advanced Robotics -AI02694,Data Engineer,123240,USD,123240,SE,PT,Finland,M,Finland,0,"NLP, GCP, R",PhD,7,Media,2024-11-05,2024-11-25,2331,9.4,Quantum Computing Inc -AI02695,Data Analyst,77013,SGD,100117,MI,PT,Singapore,M,Singapore,50,"Hadoop, AWS, Linux",Bachelor,4,Retail,2024-06-29,2024-08-01,2245,5.3,Autonomous Tech -AI02696,AI Software Engineer,79315,AUD,107075,MI,PT,Australia,S,Australia,50,"Java, Scala, Hadoop",Master,3,Technology,2024-09-24,2024-10-26,928,7,Smart Analytics -AI02697,Autonomous Systems Engineer,82499,USD,82499,MI,PT,Israel,S,Israel,50,"Linux, Git, TensorFlow, PyTorch, R",Master,3,Energy,2024-12-23,2025-02-08,1156,8.6,DeepTech Ventures -AI02698,AI Research Scientist,89597,USD,89597,MI,CT,Ireland,M,Ireland,100,"PyTorch, Git, Tableau",Master,3,Gaming,2025-04-28,2025-06-27,638,9.4,Future Systems -AI02699,AI Consultant,79127,USD,79127,MI,CT,South Korea,L,South Africa,50,"Spark, Kubernetes, PyTorch, Mathematics, TensorFlow",Bachelor,4,Retail,2025-04-18,2025-06-01,660,9.8,Predictive Systems -AI02700,NLP Engineer,181523,EUR,154295,EX,FT,Germany,S,Germany,100,"Java, SQL, Mathematics",PhD,16,Automotive,2025-03-19,2025-04-25,1872,8.7,Smart Analytics -AI02701,Machine Learning Researcher,136263,USD,136263,EX,FT,Sweden,S,Italy,0,"MLOps, Docker, TensorFlow, Statistics",PhD,14,Technology,2024-06-22,2024-08-27,1042,8.8,DataVision Ltd -AI02702,Computer Vision Engineer,83502,JPY,9185220,MI,FL,Japan,M,Japan,0,"Data Visualization, Java, TensorFlow",Master,4,Education,2024-11-02,2024-11-24,1113,8,TechCorp Inc -AI02703,Autonomous Systems Engineer,80445,USD,80445,EN,FL,Israel,L,Vietnam,100,"Spark, Kubernetes, Linux, Deep Learning",Master,0,Automotive,2024-11-29,2025-01-13,1701,5.6,Algorithmic Solutions -AI02704,NLP Engineer,129262,EUR,109873,SE,CT,Germany,M,Germany,100,"Scala, Mathematics, Deep Learning",Bachelor,5,Education,2025-03-31,2025-06-03,1314,5.9,AI Innovations -AI02705,AI Research Scientist,318729,USD,318729,EX,CT,Denmark,L,Denmark,100,"SQL, PyTorch, MLOps, Scala",PhD,15,Transportation,2024-04-20,2024-06-26,1885,5.1,TechCorp Inc -AI02706,Head of AI,42907,USD,42907,SE,CT,India,S,India,50,"AWS, Spark, NLP",PhD,9,Energy,2025-01-08,2025-02-21,1752,6.7,Quantum Computing Inc -AI02707,AI Architect,35590,USD,35590,MI,CT,China,S,China,50,"Deep Learning, AWS, SQL, Kubernetes",PhD,2,Energy,2025-03-11,2025-04-17,2175,7.9,Machine Intelligence Group -AI02708,ML Ops Engineer,201427,USD,201427,EX,PT,Sweden,M,Sweden,0,"Python, SQL, MLOps, Azure",Bachelor,15,Media,2024-01-04,2024-02-17,1405,6.4,Smart Analytics -AI02709,Head of AI,206878,USD,206878,EX,PT,Israel,S,Portugal,100,"Java, R, Computer Vision, Git, GCP",PhD,11,Government,2024-05-17,2024-07-01,2015,7.1,Neural Networks Co -AI02710,Data Engineer,59555,AUD,80399,EN,FL,Australia,L,Sweden,0,"SQL, Deep Learning, Linux, Python, PyTorch",Master,0,Healthcare,2025-04-18,2025-06-12,631,8.4,Neural Networks Co -AI02711,Computer Vision Engineer,40698,USD,40698,MI,FL,China,L,Egypt,100,"R, PyTorch, Tableau, Scala",Associate,2,Healthcare,2025-04-19,2025-06-18,1730,6.9,Future Systems -AI02712,AI Consultant,60205,USD,60205,EN,FT,Ireland,S,Denmark,50,"AWS, Java, Data Visualization",Associate,1,Retail,2024-06-29,2024-07-18,2272,7,Cloud AI Solutions -AI02713,AI Research Scientist,153723,SGD,199840,EX,CT,Singapore,M,Singapore,0,"Deep Learning, Linux, Computer Vision",Associate,16,Transportation,2025-01-28,2025-04-02,743,5.1,DeepTech Ventures -AI02714,AI Architect,185811,USD,185811,EX,PT,Israel,S,Israel,50,"Hadoop, Kubernetes, Tableau, Spark",Associate,12,Government,2025-04-13,2025-05-26,513,6.5,Autonomous Tech -AI02715,AI Product Manager,49147,EUR,41775,EN,FL,Germany,S,Germany,0,"Data Visualization, Docker, Spark, TensorFlow, Statistics",PhD,1,Gaming,2024-02-05,2024-04-08,996,8.1,TechCorp Inc -AI02716,Computer Vision Engineer,102077,USD,102077,MI,PT,Norway,M,Norway,0,"Kubernetes, Java, Statistics, Mathematics",Bachelor,3,Education,2024-05-05,2024-05-26,2332,5.2,Cloud AI Solutions -AI02717,Robotics Engineer,62401,USD,62401,SE,CT,China,M,Kenya,100,"TensorFlow, Java, Azure, Tableau, R",PhD,6,Retail,2024-08-24,2024-09-25,889,5.4,Cloud AI Solutions -AI02718,AI Architect,107823,EUR,91650,SE,CT,Austria,M,Australia,50,"Statistics, PyTorch, Tableau, Scala",Associate,5,Media,2024-11-10,2024-12-26,1821,8.7,DeepTech Ventures -AI02719,AI Consultant,91347,EUR,77645,MI,CT,Austria,S,Austria,100,"AWS, Linux, Docker",PhD,3,Energy,2024-08-10,2024-10-11,539,6.3,DeepTech Ventures -AI02720,AI Specialist,51459,USD,51459,SE,PT,India,L,India,100,"R, Docker, Statistics, SQL",PhD,5,Transportation,2024-04-23,2024-05-30,1996,9,Smart Analytics -AI02721,AI Product Manager,81873,USD,81873,EN,FT,Denmark,M,Denmark,100,"Linux, Computer Vision, Data Visualization, Git",Associate,0,Healthcare,2024-08-19,2024-09-08,1229,9.3,Cloud AI Solutions -AI02722,ML Ops Engineer,83272,USD,83272,MI,CT,United States,S,United States,50,"Kubernetes, SQL, TensorFlow, NLP",Master,2,Real Estate,2024-05-23,2024-07-07,1214,5.3,Smart Analytics -AI02723,Machine Learning Researcher,116075,SGD,150898,SE,CT,Singapore,S,Singapore,50,"Python, Spark, Java, TensorFlow",Bachelor,7,Education,2024-08-23,2024-10-31,781,5.1,AI Innovations -AI02724,Head of AI,89742,USD,89742,SE,PT,Finland,S,Finland,0,"PyTorch, Statistics, Data Visualization, SQL",Bachelor,9,Telecommunications,2024-08-25,2024-09-19,1044,7.7,Smart Analytics -AI02725,Machine Learning Researcher,72250,USD,72250,EN,FL,Ireland,L,Nigeria,0,"MLOps, Git, PyTorch",Associate,1,Education,2024-10-28,2024-12-05,1070,8.1,Cloud AI Solutions -AI02726,AI Product Manager,89161,CHF,80245,EN,CT,Switzerland,M,Switzerland,100,"Kubernetes, Statistics, Tableau, Data Visualization",Master,1,Consulting,2025-03-04,2025-03-25,905,5.5,Digital Transformation LLC -AI02727,AI Software Engineer,248371,SGD,322882,EX,CT,Singapore,M,Singapore,100,"Spark, Python, Data Visualization, Kubernetes, Deep Learning",Master,19,Retail,2025-01-19,2025-03-05,628,9.1,Machine Intelligence Group -AI02728,Head of AI,237882,GBP,178412,EX,FL,United Kingdom,M,United Kingdom,0,"R, Linux, SQL, Mathematics, MLOps",PhD,12,Consulting,2024-11-11,2024-12-17,1603,7.7,Autonomous Tech -AI02729,AI Product Manager,234093,CHF,210684,SE,FT,Switzerland,L,Switzerland,0,"Data Visualization, TensorFlow, Statistics",Bachelor,8,Consulting,2025-03-21,2025-05-19,2420,5.4,Cloud AI Solutions -AI02730,Head of AI,69998,EUR,59498,EN,FT,France,M,France,50,"Azure, Kubernetes, Scala",Associate,1,Government,2024-07-17,2024-08-09,557,8.1,Algorithmic Solutions -AI02731,Principal Data Scientist,92320,EUR,78472,MI,FL,Netherlands,M,Norway,50,"R, SQL, Azure",Master,3,Government,2024-05-01,2024-06-25,2297,9.4,DeepTech Ventures -AI02732,Principal Data Scientist,61179,CAD,76474,EN,FT,Canada,S,Canada,100,"Hadoop, Kubernetes, MLOps, Docker",PhD,0,Media,2024-04-09,2024-05-11,1420,7.8,Autonomous Tech -AI02733,Deep Learning Engineer,61702,EUR,52447,MI,CT,France,S,France,50,"Java, Hadoop, Tableau, Kubernetes, AWS",Bachelor,3,Technology,2025-02-05,2025-02-20,1250,9,Autonomous Tech -AI02734,Autonomous Systems Engineer,85122,USD,85122,EN,FL,Norway,L,Norway,100,"PyTorch, TensorFlow, Azure, Git",Master,1,Energy,2024-03-29,2024-04-27,734,8,Quantum Computing Inc -AI02735,Data Analyst,78254,USD,78254,EN,PT,Denmark,M,Denmark,0,"TensorFlow, AWS, Hadoop",Bachelor,1,Technology,2025-01-25,2025-02-15,1718,8.4,Quantum Computing Inc -AI02736,AI Research Scientist,70895,USD,70895,EN,PT,Sweden,S,Sweden,50,"Scala, PyTorch, MLOps, SQL, Computer Vision",Associate,1,Government,2025-01-11,2025-03-18,1398,5.8,Future Systems -AI02737,Data Engineer,199927,USD,199927,SE,CT,Norway,L,Latvia,50,"SQL, Spark, PyTorch",Associate,6,Healthcare,2024-03-17,2024-04-02,1138,6.9,Cloud AI Solutions -AI02738,Deep Learning Engineer,170229,CAD,212786,EX,CT,Canada,M,United States,50,"Deep Learning, R, Hadoop, Kubernetes, SQL",Master,16,Retail,2024-03-29,2024-04-30,1109,8.8,Smart Analytics -AI02739,Data Engineer,154419,USD,154419,MI,FT,Norway,L,Norway,50,"Tableau, Computer Vision, Python, TensorFlow, Java",Master,4,Technology,2024-08-12,2024-10-08,1099,9.3,DataVision Ltd -AI02740,AI Product Manager,162643,EUR,138247,SE,CT,Netherlands,L,South Africa,100,"Python, TensorFlow, Tableau, PyTorch",PhD,9,Media,2024-03-24,2024-05-21,2247,7.3,Neural Networks Co -AI02741,Computer Vision Engineer,268185,JPY,29500350,EX,CT,Japan,L,Argentina,50,"Data Visualization, Spark, NLP",Bachelor,11,Automotive,2024-12-27,2025-01-16,942,8.7,TechCorp Inc -AI02742,Data Scientist,180863,GBP,135647,SE,PT,United Kingdom,L,United Kingdom,50,"Python, GCP, TensorFlow, NLP, PyTorch",Bachelor,5,Automotive,2024-01-21,2024-02-20,1397,7.6,Cognitive Computing -AI02743,Machine Learning Researcher,34377,USD,34377,EN,CT,China,L,China,0,"PyTorch, TensorFlow, Computer Vision, Mathematics",Bachelor,1,Real Estate,2024-03-01,2024-05-03,1626,5.8,Machine Intelligence Group -AI02744,Deep Learning Engineer,66309,USD,66309,EX,PT,China,M,China,100,"Spark, Tableau, Linux",Associate,12,Real Estate,2025-01-23,2025-04-05,2186,7.5,TechCorp Inc -AI02745,Computer Vision Engineer,151661,SGD,197159,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, NLP, Mathematics",Master,17,Automotive,2025-01-21,2025-03-24,2125,6,Algorithmic Solutions -AI02746,Principal Data Scientist,169405,JPY,18634550,EX,FL,Japan,M,Sweden,100,"R, Hadoop, Linux",Bachelor,10,Consulting,2024-02-12,2024-03-16,2077,9,DeepTech Ventures -AI02747,NLP Engineer,72571,JPY,7982810,EN,CT,Japan,S,Japan,50,"AWS, Hadoop, SQL, PyTorch",Associate,0,Consulting,2024-11-22,2025-01-29,1015,5,Machine Intelligence Group -AI02748,Data Scientist,240989,GBP,180742,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, TensorFlow, NLP, MLOps",PhD,15,Energy,2024-08-22,2024-10-13,2290,8.6,Future Systems -AI02749,Data Analyst,44658,USD,44658,EN,FL,Finland,S,Finland,0,"AWS, PyTorch, Tableau",Bachelor,1,Energy,2024-08-26,2024-10-14,1578,9.3,Smart Analytics -AI02750,Autonomous Systems Engineer,51559,EUR,43825,EN,CT,France,S,France,50,"Scala, Deep Learning, Computer Vision, PyTorch, SQL",PhD,1,Technology,2024-06-24,2024-07-27,2101,9.5,Cognitive Computing -AI02751,NLP Engineer,165686,CHF,149117,MI,CT,Switzerland,L,Switzerland,100,"Docker, Statistics, Python",Bachelor,2,Real Estate,2024-05-23,2024-06-23,1760,7.2,DeepTech Ventures -AI02752,Head of AI,105339,CHF,94805,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Git, Deep Learning, Data Visualization",Master,0,Healthcare,2024-08-02,2024-08-24,876,8,Algorithmic Solutions -AI02753,AI Software Engineer,209800,EUR,178330,EX,CT,Netherlands,M,Netherlands,0,"Kubernetes, Python, SQL",PhD,18,Consulting,2024-11-19,2024-12-05,2126,8.9,Predictive Systems -AI02754,AI Architect,118780,USD,118780,MI,FT,United States,M,United States,0,"SQL, Data Visualization, TensorFlow, MLOps",Associate,3,Consulting,2025-02-06,2025-03-13,933,6.8,Smart Analytics -AI02755,AI Consultant,125984,CAD,157480,SE,FL,Canada,S,Canada,100,"NLP, Java, Computer Vision",Bachelor,6,Finance,2024-10-30,2024-12-23,1473,9.1,Future Systems -AI02756,Research Scientist,121739,SGD,158261,SE,FT,Singapore,M,Singapore,0,"PyTorch, Java, Spark",PhD,6,Technology,2024-08-19,2024-10-25,1712,8.9,Cloud AI Solutions -AI02757,Deep Learning Engineer,141394,EUR,120185,SE,FT,Netherlands,M,Chile,50,"Hadoop, TensorFlow, Python",Bachelor,5,Telecommunications,2024-05-08,2024-06-01,1923,8.8,Cloud AI Solutions -AI02758,Machine Learning Researcher,74325,USD,74325,EN,FL,Norway,S,Norway,0,"Linux, MLOps, SQL, R",Master,0,Technology,2024-06-21,2024-08-02,2350,9.2,DataVision Ltd -AI02759,Head of AI,181015,SGD,235320,SE,PT,Singapore,L,Singapore,100,"Java, SQL, GCP",Master,7,Technology,2025-03-01,2025-03-26,968,6.6,Cognitive Computing -AI02760,NLP Engineer,54802,SGD,71243,EN,FT,Singapore,M,Singapore,0,"Scala, Python, Docker, Computer Vision",Bachelor,0,Healthcare,2025-03-24,2025-05-20,733,6.3,Smart Analytics -AI02761,Data Analyst,113391,JPY,12473010,MI,PT,Japan,M,Japan,100,"Scala, Data Visualization, Git, Spark",Master,3,Automotive,2024-04-11,2024-05-16,865,8.5,Future Systems -AI02762,NLP Engineer,171064,USD,171064,EX,CT,Ireland,L,Ireland,50,"AWS, PyTorch, Computer Vision, Hadoop, SQL",Bachelor,15,Consulting,2024-11-10,2024-12-27,1791,7.2,Cloud AI Solutions -AI02763,Head of AI,122125,USD,122125,MI,FT,Denmark,M,Denmark,100,"Scala, Tableau, Python, Linux",Bachelor,3,Media,2024-10-08,2024-12-18,1199,7.4,Cognitive Computing -AI02764,Machine Learning Engineer,133237,AUD,179870,SE,CT,Australia,S,Australia,50,"Python, Hadoop, Linux, Scala, Computer Vision",Associate,5,Retail,2024-04-22,2024-06-26,1707,8.4,Machine Intelligence Group -AI02765,Deep Learning Engineer,89475,JPY,9842250,EN,PT,Japan,L,Japan,100,"Python, TensorFlow, Git, Mathematics, Spark",PhD,1,Transportation,2025-01-01,2025-02-27,1924,5.1,DeepTech Ventures -AI02766,AI Product Manager,92805,USD,92805,MI,FL,United States,S,New Zealand,50,"Linux, Spark, Scala, MLOps",Associate,2,Government,2024-04-10,2024-06-21,1389,8,Digital Transformation LLC -AI02767,AI Product Manager,277302,AUD,374358,EX,PT,Australia,L,Australia,100,"Git, Statistics, TensorFlow, SQL, Kubernetes",Master,14,Finance,2024-03-27,2024-05-08,1139,5.7,Quantum Computing Inc -AI02768,AI Consultant,157131,USD,157131,SE,FT,Norway,L,Norway,50,"Spark, Tableau, Computer Vision, NLP",PhD,8,Automotive,2024-07-01,2024-08-31,1981,7.3,Cognitive Computing -AI02769,Machine Learning Engineer,124242,EUR,105606,SE,CT,France,S,Singapore,50,"Spark, Mathematics, MLOps",Master,6,Media,2024-04-29,2024-07-09,2466,9.1,Predictive Systems -AI02770,Robotics Engineer,165005,AUD,222757,EX,FL,Australia,L,Austria,0,"Mathematics, Computer Vision, Data Visualization, Statistics",PhD,18,Education,2024-08-08,2024-09-14,1077,7.9,Quantum Computing Inc -AI02771,Data Analyst,55240,EUR,46954,EN,CT,Austria,S,Austria,0,"Kubernetes, Deep Learning, Git",Bachelor,1,Finance,2024-06-24,2024-08-24,1766,9.7,Neural Networks Co -AI02772,Robotics Engineer,39042,USD,39042,SE,PT,India,M,Colombia,0,"Deep Learning, Linux, Java",Bachelor,6,Manufacturing,2025-02-28,2025-04-17,655,8.5,Autonomous Tech -AI02773,Machine Learning Researcher,64577,USD,64577,EX,FL,India,M,India,50,"NLP, SQL, Scala",Bachelor,15,Government,2024-03-01,2024-04-21,1560,6.6,Cognitive Computing -AI02774,Head of AI,50657,USD,50657,EN,CT,Israel,S,Israel,0,"Python, Java, Tableau, TensorFlow, Mathematics",PhD,0,Real Estate,2024-11-23,2024-12-14,1622,9.1,TechCorp Inc -AI02775,Machine Learning Engineer,108147,GBP,81110,SE,FL,United Kingdom,M,Switzerland,100,"MLOps, Kubernetes, R",Associate,6,Finance,2025-02-07,2025-02-25,690,5.1,Future Systems -AI02776,Robotics Engineer,186468,USD,186468,EX,FL,Norway,M,Norway,100,"TensorFlow, AWS, Data Visualization, Python",Master,17,Automotive,2024-09-06,2024-10-09,2476,5.1,Digital Transformation LLC -AI02777,Data Engineer,148941,EUR,126600,SE,PT,Germany,M,Germany,0,"Python, NLP, Docker, GCP",Bachelor,6,Media,2025-04-24,2025-05-18,2164,9.1,Digital Transformation LLC -AI02778,AI Software Engineer,61003,USD,61003,EN,FT,Norway,S,Norway,100,"Statistics, Computer Vision, Data Visualization",PhD,0,Manufacturing,2025-04-09,2025-05-26,847,7.2,Cloud AI Solutions -AI02779,ML Ops Engineer,130513,USD,130513,SE,PT,Ireland,L,Ireland,0,"Linux, Kubernetes, Scala, Java",Bachelor,9,Technology,2024-05-30,2024-06-22,1034,5.3,Future Systems -AI02780,AI Architect,218583,EUR,185796,EX,FT,France,L,France,100,"Hadoop, R, SQL, PyTorch, Git",PhD,18,Gaming,2024-05-06,2024-06-10,1862,9.4,Machine Intelligence Group -AI02781,AI Consultant,57623,USD,57623,EN,FT,Sweden,S,Sweden,50,"Tableau, AWS, Hadoop, Docker, Statistics",Bachelor,0,Media,2024-05-30,2024-06-20,973,9.8,Future Systems -AI02782,AI Product Manager,63893,USD,63893,EN,FL,South Korea,M,Australia,0,"Linux, Deep Learning, Java, SQL, AWS",PhD,1,Finance,2025-01-12,2025-01-27,984,9.8,Smart Analytics -AI02783,AI Consultant,198531,USD,198531,EX,FL,Norway,M,Norway,100,"AWS, Kubernetes, NLP, Statistics",Associate,12,Transportation,2025-04-14,2025-05-14,1650,9.5,Cognitive Computing -AI02784,Machine Learning Researcher,66355,SGD,86262,EN,FT,Singapore,S,Singapore,100,"Kubernetes, Tableau, Hadoop",PhD,1,Finance,2024-03-10,2024-03-28,762,8.1,Cognitive Computing -AI02785,Head of AI,71500,USD,71500,EN,FT,Finland,L,Finland,0,"R, Hadoop, Linux, SQL, Computer Vision",Master,1,Automotive,2025-01-26,2025-04-01,1426,6.3,AI Innovations -AI02786,AI Specialist,99853,USD,99853,MI,FT,Israel,L,Israel,0,"Computer Vision, Kubernetes, SQL, Docker",Master,2,Consulting,2025-01-07,2025-03-21,679,10,AI Innovations -AI02787,Autonomous Systems Engineer,160109,CHF,144098,SE,PT,Switzerland,M,Thailand,100,"MLOps, AWS, Spark, R",Master,5,Consulting,2024-02-18,2024-03-28,914,9,Digital Transformation LLC -AI02788,AI Specialist,126146,USD,126146,SE,CT,Sweden,M,United Kingdom,50,"PyTorch, TensorFlow, R, SQL, Spark",Master,9,Media,2025-03-06,2025-05-10,2264,8.7,Quantum Computing Inc -AI02789,AI Consultant,32128,USD,32128,EN,PT,China,L,China,50,"Python, Spark, MLOps, TensorFlow, Scala",Master,0,Media,2024-04-23,2024-07-02,1091,7.4,Future Systems -AI02790,AI Software Engineer,23707,USD,23707,EN,FL,India,M,Spain,0,"PyTorch, Hadoop, Deep Learning, Linux",Bachelor,1,Healthcare,2024-03-02,2024-04-27,1306,9.8,Predictive Systems -AI02791,Data Scientist,210918,CAD,263648,EX,FT,Canada,L,Japan,50,"Python, R, Docker, Linux",Master,10,Energy,2024-01-03,2024-01-31,881,7.5,Future Systems -AI02792,AI Architect,132476,EUR,112605,SE,CT,France,L,France,50,"PyTorch, Spark, Statistics, Python",PhD,6,Education,2024-10-16,2024-11-05,2332,7.4,Digital Transformation LLC -AI02793,Research Scientist,97049,EUR,82492,SE,FL,France,M,France,100,"Scala, PyTorch, Data Visualization, Git",PhD,5,Telecommunications,2025-01-10,2025-03-02,1819,8.1,Smart Analytics -AI02794,AI Software Engineer,52529,CAD,65661,EN,FT,Canada,M,Ireland,100,"MLOps, Spark, Tableau, Scala, Statistics",Master,0,Manufacturing,2024-03-06,2024-04-27,2052,5.1,Cognitive Computing -AI02795,Principal Data Scientist,204220,EUR,173587,EX,PT,Austria,S,Egypt,50,"Computer Vision, Deep Learning, Linux",Bachelor,12,Automotive,2024-03-24,2024-04-13,607,8.7,TechCorp Inc -AI02796,AI Software Engineer,132720,SGD,172536,SE,FL,Singapore,L,Singapore,50,"R, Hadoop, Tableau",Bachelor,8,Media,2024-08-04,2024-10-16,1384,6.8,Advanced Robotics -AI02797,Autonomous Systems Engineer,81244,USD,81244,MI,CT,Finland,L,Finland,50,"Docker, Hadoop, Statistics, Linux",Master,4,Manufacturing,2024-05-17,2024-06-27,1528,9.8,Machine Intelligence Group -AI02798,Machine Learning Researcher,161739,USD,161739,MI,FL,Norway,L,Norway,100,"NLP, Kubernetes, PyTorch, Docker, SQL",Master,3,Automotive,2024-04-06,2024-06-08,1521,6.4,DataVision Ltd -AI02799,ML Ops Engineer,71582,CAD,89478,MI,CT,Canada,S,Canada,0,"Kubernetes, Scala, AWS, TensorFlow",PhD,4,Manufacturing,2025-01-18,2025-02-05,865,9.2,DataVision Ltd -AI02800,Robotics Engineer,55770,USD,55770,SE,PT,China,S,China,0,"Docker, R, AWS, Python, Kubernetes",Bachelor,6,Manufacturing,2025-02-17,2025-03-12,1015,9.6,Smart Analytics -AI02801,AI Product Manager,176027,USD,176027,SE,CT,Norway,M,Norway,0,"R, SQL, Tableau",Bachelor,7,Government,2024-08-01,2024-10-05,1205,5.3,Machine Intelligence Group -AI02802,AI Product Manager,47687,USD,47687,SE,CT,India,L,Japan,0,"Data Visualization, TensorFlow, Statistics",Associate,9,Telecommunications,2024-07-20,2024-09-18,681,6.2,Advanced Robotics -AI02803,Autonomous Systems Engineer,60812,USD,60812,MI,PT,South Korea,M,South Korea,0,"R, Git, Deep Learning, GCP",Master,4,Finance,2024-07-02,2024-08-07,628,7.4,Predictive Systems -AI02804,Research Scientist,126567,JPY,13922370,MI,PT,Japan,L,Netherlands,50,"PyTorch, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-12-15,2024-12-29,2386,7.1,Cognitive Computing -AI02805,Research Scientist,97033,SGD,126143,MI,CT,Singapore,S,France,0,"Azure, GCP, Spark, Statistics, Computer Vision",Master,2,Real Estate,2025-02-08,2025-04-19,2196,9.6,Future Systems -AI02806,AI Specialist,70605,USD,70605,EN,FL,Norway,S,Norway,0,"Kubernetes, GCP, Spark, Tableau, Python",Bachelor,0,Consulting,2024-08-04,2024-09-14,1382,8.9,Autonomous Tech -AI02807,Deep Learning Engineer,121078,USD,121078,SE,FT,Israel,L,Israel,50,"Computer Vision, Azure, Data Visualization, Java",Bachelor,5,Retail,2024-06-11,2024-07-22,1033,5.9,DeepTech Ventures -AI02808,ML Ops Engineer,255771,USD,255771,EX,FT,Denmark,S,Denmark,0,"Azure, Kubernetes, Tableau, Python, Hadoop",Master,10,Transportation,2024-11-13,2025-01-14,1097,5.4,Machine Intelligence Group -AI02809,Data Engineer,111629,EUR,94885,SE,PT,France,L,France,50,"Tableau, Statistics, Spark",Master,9,Healthcare,2024-02-07,2024-03-13,1123,6.3,DeepTech Ventures -AI02810,Autonomous Systems Engineer,127275,USD,127275,MI,PT,Denmark,S,Denmark,100,"Java, AWS, SQL, NLP, Deep Learning",Associate,3,Automotive,2024-08-07,2024-09-19,2009,7,Smart Analytics -AI02811,Robotics Engineer,226295,USD,226295,EX,FL,Ireland,S,New Zealand,100,"Docker, Python, AWS",Associate,19,Consulting,2025-01-26,2025-02-12,615,7.6,Autonomous Tech -AI02812,AI Consultant,60249,USD,60249,EN,FL,Sweden,M,Sweden,50,"Scala, Mathematics, Tableau, Statistics, MLOps",Associate,0,Real Estate,2024-01-15,2024-03-05,2151,5.3,Quantum Computing Inc -AI02813,Principal Data Scientist,154394,USD,154394,SE,FL,United States,S,United States,0,"Kubernetes, Hadoop, Python, Azure",Master,5,Manufacturing,2024-04-19,2024-06-20,611,9.2,Digital Transformation LLC -AI02814,Deep Learning Engineer,77141,EUR,65570,MI,CT,Netherlands,S,Russia,0,"Kubernetes, Data Visualization, Mathematics",Associate,2,Automotive,2025-03-24,2025-04-09,1999,7.6,DataVision Ltd -AI02815,AI Product Manager,89813,EUR,76341,MI,PT,Austria,M,Austria,100,"GCP, Java, PyTorch",Associate,2,Technology,2024-06-20,2024-08-20,2490,8.9,Algorithmic Solutions -AI02816,Research Scientist,80989,USD,80989,MI,FT,Finland,S,Finland,0,"R, Statistics, Hadoop, Docker",PhD,4,Retail,2025-02-14,2025-04-25,540,8.4,DataVision Ltd -AI02817,Data Engineer,271778,CHF,244600,EX,PT,Switzerland,L,Switzerland,50,"AWS, Scala, Docker",Bachelor,12,Consulting,2024-03-23,2024-05-31,1285,5.1,Algorithmic Solutions -AI02818,AI Research Scientist,46378,USD,46378,SE,FL,India,S,India,100,"SQL, NLP, PyTorch",Associate,9,Finance,2025-01-26,2025-02-11,1773,9.2,Digital Transformation LLC -AI02819,Principal Data Scientist,101913,EUR,86626,MI,FL,Germany,L,Germany,50,"Spark, Java, MLOps, PyTorch",PhD,3,Telecommunications,2025-01-12,2025-03-23,2063,7.4,Quantum Computing Inc -AI02820,Data Analyst,29407,USD,29407,MI,PT,India,M,India,50,"SQL, TensorFlow, Tableau",PhD,4,Retail,2024-04-30,2024-06-23,2053,5.5,Predictive Systems -AI02821,AI Specialist,122457,USD,122457,EX,FL,South Korea,M,South Korea,0,"Scala, Deep Learning, R, Hadoop, Statistics",Master,12,Automotive,2024-03-13,2024-05-23,595,6.7,Machine Intelligence Group -AI02822,AI Research Scientist,121296,EUR,103102,SE,CT,France,M,Philippines,100,"Data Visualization, SQL, PyTorch",PhD,6,Technology,2024-02-12,2024-03-24,602,6.3,Neural Networks Co -AI02823,AI Specialist,154186,USD,154186,SE,CT,Norway,S,Norway,0,"Git, PyTorch, Tableau, MLOps",PhD,6,Gaming,2024-11-07,2024-12-15,1374,9.5,AI Innovations -AI02824,Robotics Engineer,215813,CAD,269766,EX,CT,Canada,S,Canada,0,"Python, Hadoop, SQL",Master,17,Government,2025-01-06,2025-02-04,664,6.1,TechCorp Inc -AI02825,Robotics Engineer,121313,SGD,157707,MI,FT,Singapore,L,Switzerland,50,"Git, NLP, PyTorch, Python",Associate,4,Gaming,2024-10-05,2024-11-20,1250,8,Predictive Systems -AI02826,Machine Learning Researcher,103697,JPY,11406670,MI,CT,Japan,S,Japan,0,"SQL, Scala, Hadoop, Azure",Bachelor,2,Energy,2024-01-30,2024-03-07,657,5.6,Algorithmic Solutions -AI02827,Research Scientist,148481,CHF,133633,MI,FT,Switzerland,M,Switzerland,0,"Python, MLOps, SQL, Java, Kubernetes",Bachelor,3,Manufacturing,2024-07-11,2024-09-16,1271,8.3,Future Systems -AI02828,AI Software Engineer,247799,USD,247799,EX,CT,Norway,S,Norway,50,"PyTorch, SQL, Linux, Hadoop",Associate,18,Media,2024-04-27,2024-06-30,717,7.8,Cognitive Computing -AI02829,Autonomous Systems Engineer,250860,USD,250860,EX,FL,United States,M,United States,50,"SQL, Tableau, Kubernetes, GCP",Associate,10,Transportation,2024-06-25,2024-07-11,891,7.8,Quantum Computing Inc -AI02830,Research Scientist,163167,AUD,220275,EX,CT,Australia,S,Australia,100,"Kubernetes, Java, GCP, SQL, AWS",Bachelor,19,Energy,2024-01-27,2024-04-03,1603,5.9,Autonomous Tech -AI02831,Principal Data Scientist,323671,USD,323671,EX,CT,United States,L,United States,50,"Computer Vision, Hadoop, Deep Learning",PhD,15,Telecommunications,2025-04-28,2025-06-15,1701,8.3,TechCorp Inc -AI02832,Robotics Engineer,70337,USD,70337,EN,FT,Norway,S,Norway,100,"Hadoop, NLP, SQL, Scala",Associate,1,Healthcare,2024-08-27,2024-10-10,888,9.2,Machine Intelligence Group -AI02833,Data Analyst,63357,EUR,53853,EN,FL,Germany,M,Egypt,100,"Mathematics, Data Visualization, Scala, SQL, Tableau",Bachelor,1,Government,2025-02-15,2025-03-29,2153,5.6,Digital Transformation LLC -AI02834,Head of AI,107154,USD,107154,SE,FL,Israel,S,Israel,0,"PyTorch, GCP, NLP, Java",Master,8,Healthcare,2024-06-22,2024-08-26,1412,6.5,TechCorp Inc -AI02835,AI Research Scientist,184525,USD,184525,SE,PT,Norway,M,Norway,0,"SQL, Python, AWS, TensorFlow",Master,5,Retail,2024-01-26,2024-02-09,2036,5.8,Algorithmic Solutions -AI02836,Robotics Engineer,94391,EUR,80232,MI,FL,Austria,L,Austria,100,"Spark, PyTorch, Python, MLOps",Master,3,Media,2025-01-05,2025-01-27,1704,5.7,Smart Analytics -AI02837,NLP Engineer,134275,USD,134275,SE,FL,South Korea,L,South Korea,0,"Spark, Azure, Computer Vision, Data Visualization, SQL",PhD,9,Automotive,2024-08-26,2024-11-05,1728,5.9,Autonomous Tech -AI02838,AI Consultant,211162,USD,211162,EX,FT,United States,M,United States,50,"Spark, Python, Tableau",PhD,19,Technology,2024-04-12,2024-05-17,2411,9.2,DataVision Ltd -AI02839,Computer Vision Engineer,70647,USD,70647,EN,PT,Ireland,L,Ireland,0,"Python, Statistics, Mathematics, Docker, TensorFlow",Bachelor,0,Education,2024-07-17,2024-09-10,1471,9.5,DataVision Ltd -AI02840,Principal Data Scientist,243402,USD,243402,EX,FT,Finland,L,Finland,0,"AWS, NLP, Docker, Linux",Bachelor,11,Consulting,2024-04-28,2024-05-12,2037,8.1,Digital Transformation LLC -AI02841,AI Product Manager,57000,USD,57000,EN,FL,South Korea,S,India,100,"Linux, SQL, Scala",Associate,0,Finance,2024-11-08,2025-01-03,1424,7.6,Smart Analytics -AI02842,Data Analyst,90610,USD,90610,MI,CT,Israel,S,Israel,50,"Kubernetes, Scala, Mathematics",PhD,4,Telecommunications,2025-02-14,2025-03-18,2329,9.1,Future Systems -AI02843,Research Scientist,240830,EUR,204706,EX,FL,Austria,L,Austria,50,"PyTorch, SQL, Java, Linux, Statistics",PhD,16,Manufacturing,2024-03-29,2024-04-13,563,9.3,Smart Analytics -AI02844,Robotics Engineer,205777,EUR,174910,EX,FL,Austria,L,Colombia,0,"GCP, Spark, TensorFlow, Git",Bachelor,11,Healthcare,2025-04-18,2025-05-27,1273,6.4,DataVision Ltd -AI02845,Machine Learning Researcher,52483,USD,52483,EN,FT,Finland,M,Finland,100,"Hadoop, Data Visualization, SQL",Bachelor,0,Manufacturing,2024-08-30,2024-09-21,1921,9.4,Neural Networks Co -AI02846,Principal Data Scientist,35085,USD,35085,MI,PT,India,M,India,50,"Python, TensorFlow, Mathematics, Hadoop",Associate,4,Media,2025-04-17,2025-05-05,525,9.2,Algorithmic Solutions -AI02847,Principal Data Scientist,170138,USD,170138,SE,PT,Ireland,L,Belgium,0,"Linux, Python, TensorFlow, AWS, Tableau",Master,7,Technology,2025-04-08,2025-05-22,1991,7.6,Advanced Robotics -AI02848,AI Software Engineer,86746,USD,86746,MI,FT,Ireland,M,Turkey,100,"Docker, SQL, Computer Vision",Associate,2,Consulting,2024-12-19,2025-02-26,2126,7.6,Predictive Systems -AI02849,Data Analyst,27601,USD,27601,MI,FT,India,S,India,50,"Python, TensorFlow, Mathematics, MLOps, SQL",Bachelor,4,Technology,2024-05-17,2024-07-06,2050,9.4,Future Systems -AI02850,Principal Data Scientist,114696,USD,114696,SE,FT,Sweden,S,Sweden,0,"Computer Vision, Java, Git, TensorFlow",Associate,7,Government,2025-02-28,2025-05-10,736,6,Neural Networks Co -AI02851,Data Analyst,123445,USD,123445,SE,FT,Finland,M,Canada,50,"Kubernetes, Python, AWS, SQL",Master,5,Telecommunications,2025-04-26,2025-06-15,1506,5.1,Quantum Computing Inc -AI02852,Head of AI,70615,USD,70615,EN,CT,South Korea,L,South Korea,50,"PyTorch, GCP, Linux, Spark",Associate,0,Automotive,2025-04-16,2025-06-19,1374,5.4,Neural Networks Co -AI02853,Data Scientist,190307,CAD,237884,EX,CT,Canada,L,Canada,100,"Statistics, Kubernetes, Azure",Master,17,Consulting,2024-03-30,2024-04-16,746,5.6,Cognitive Computing -AI02854,AI Software Engineer,319590,USD,319590,EX,FL,United States,L,United States,100,"PyTorch, MLOps, GCP",Master,19,Government,2024-01-01,2024-03-14,720,6.4,Cloud AI Solutions -AI02855,AI Research Scientist,207479,USD,207479,SE,PT,Norway,L,China,0,"NLP, Python, Computer Vision, Mathematics",Master,7,Technology,2024-06-03,2024-06-17,2025,6.2,Cloud AI Solutions -AI02856,AI Product Manager,131422,USD,131422,MI,FL,United States,L,Vietnam,50,"Java, Computer Vision, AWS",Associate,4,Gaming,2024-05-24,2024-07-17,1676,5.2,Digital Transformation LLC -AI02857,ML Ops Engineer,95848,EUR,81471,MI,PT,Germany,M,Thailand,0,"Linux, Spark, Deep Learning",Associate,4,Consulting,2024-09-08,2024-10-22,919,5.3,Predictive Systems -AI02858,Robotics Engineer,94145,JPY,10355950,MI,FL,Japan,L,Japan,50,"Python, R, Mathematics, Scala, NLP",PhD,4,Real Estate,2024-01-20,2024-03-09,721,7.5,AI Innovations -AI02859,AI Consultant,130395,CAD,162994,SE,CT,Canada,L,Canada,100,"GCP, Python, MLOps, Kubernetes",PhD,9,Real Estate,2024-12-01,2025-02-05,1098,6.4,Neural Networks Co -AI02860,Robotics Engineer,77116,EUR,65549,EN,CT,Germany,M,Germany,100,"Kubernetes, Computer Vision, Hadoop",Associate,0,Education,2024-03-23,2024-05-01,2136,5.7,Algorithmic Solutions -AI02861,Robotics Engineer,21922,USD,21922,EN,PT,India,L,Romania,50,"Spark, Java, GCP",Bachelor,0,Finance,2024-11-06,2025-01-12,624,5.3,TechCorp Inc -AI02862,AI Research Scientist,248823,USD,248823,EX,CT,United States,S,United States,100,"Python, Git, Mathematics, TensorFlow, Statistics",Bachelor,13,Education,2024-10-05,2024-12-01,990,6.8,Advanced Robotics -AI02863,Head of AI,36405,USD,36405,MI,PT,India,M,India,100,"Linux, Deep Learning, Python, NLP",Master,3,Automotive,2024-10-21,2024-11-13,2089,5.7,DataVision Ltd -AI02864,Principal Data Scientist,253609,EUR,215568,EX,CT,France,L,France,50,"Spark, Tableau, Linux, Python, R",PhD,15,Transportation,2024-10-23,2024-11-12,2390,6,Advanced Robotics -AI02865,NLP Engineer,203699,CHF,183329,SE,CT,Switzerland,M,China,0,"Python, Kubernetes, Computer Vision, TensorFlow, Statistics",PhD,5,Media,2025-02-04,2025-02-21,1665,7.3,Autonomous Tech -AI02866,Machine Learning Engineer,141871,CHF,127684,MI,FL,Switzerland,M,Estonia,100,"Scala, SQL, TensorFlow, Java",Bachelor,2,Finance,2024-01-19,2024-03-02,1034,7.5,Machine Intelligence Group -AI02867,AI Consultant,190310,AUD,256919,EX,PT,Australia,S,Australia,50,"Linux, PyTorch, R, Computer Vision, Python",PhD,10,Technology,2024-11-23,2024-12-18,793,9.6,Smart Analytics -AI02868,Data Scientist,68143,USD,68143,MI,CT,South Korea,S,China,50,"Mathematics, TensorFlow, Git, Python",PhD,2,Gaming,2024-12-29,2025-02-07,560,9.2,Autonomous Tech -AI02869,Robotics Engineer,74136,USD,74136,EN,FL,Ireland,L,Ireland,50,"Statistics, SQL, Azure",PhD,1,Automotive,2024-03-27,2024-06-01,886,9.6,DeepTech Ventures -AI02870,NLP Engineer,73619,EUR,62576,EN,CT,France,L,Estonia,0,"Kubernetes, R, MLOps",PhD,0,Telecommunications,2025-01-26,2025-04-04,1664,6.1,Digital Transformation LLC -AI02871,Research Scientist,77655,USD,77655,EN,PT,Denmark,M,Denmark,50,"Python, Spark, NLP, Java, SQL",Master,0,Media,2025-03-02,2025-05-04,859,9.1,Cloud AI Solutions -AI02872,NLP Engineer,123447,EUR,104930,SE,FL,Austria,S,Austria,50,"Python, TensorFlow, MLOps, Computer Vision",Associate,5,Retail,2024-11-21,2025-01-28,2155,9,Neural Networks Co -AI02873,AI Software Engineer,89174,USD,89174,MI,FL,United States,S,United States,50,"Linux, Statistics, SQL",PhD,4,Gaming,2024-04-10,2024-04-27,1358,7.6,Neural Networks Co -AI02874,Data Analyst,59752,USD,59752,SE,FT,India,L,India,100,"Deep Learning, SQL, Data Visualization, PyTorch, Hadoop",Associate,8,Retail,2024-07-17,2024-09-08,1777,6.7,Neural Networks Co -AI02875,AI Research Scientist,82657,USD,82657,EN,FT,United States,M,United States,100,"MLOps, Python, Linux, Deep Learning",Master,0,Consulting,2025-01-17,2025-03-14,1168,7.6,Digital Transformation LLC -AI02876,Data Analyst,60940,GBP,45705,EN,FL,United Kingdom,M,United Kingdom,50,"GCP, Statistics, Tableau, Data Visualization, NLP",Associate,1,Finance,2025-02-28,2025-04-30,1822,9.4,TechCorp Inc -AI02877,AI Specialist,147265,EUR,125175,EX,FT,Germany,M,Indonesia,50,"Kubernetes, Hadoop, PyTorch, Azure, Git",PhD,15,Real Estate,2024-04-11,2024-05-31,1634,7.4,Future Systems -AI02878,AI Research Scientist,87462,USD,87462,MI,PT,United States,M,Turkey,50,"Git, R, Mathematics, Linux",Associate,4,Telecommunications,2024-09-29,2024-11-18,808,5.4,DeepTech Ventures -AI02879,Principal Data Scientist,203296,CAD,254120,EX,FL,Canada,S,Canada,0,"Java, MLOps, R, Scala",Master,14,Telecommunications,2024-03-01,2024-04-12,1334,9.5,Machine Intelligence Group -AI02880,Machine Learning Researcher,102443,USD,102443,EN,FT,United States,L,Turkey,0,"NLP, TensorFlow, Data Visualization",PhD,0,Technology,2024-07-06,2024-08-13,2438,5.9,TechCorp Inc -AI02881,Autonomous Systems Engineer,165965,SGD,215755,EX,FL,Singapore,S,Singapore,50,"PyTorch, TensorFlow, Python, Statistics, Azure",Master,14,Healthcare,2024-03-31,2024-04-24,567,8.1,Algorithmic Solutions -AI02882,Computer Vision Engineer,142165,USD,142165,SE,FT,Israel,M,Thailand,0,"Python, Tableau, TensorFlow, Mathematics, PyTorch",Bachelor,6,Finance,2024-10-08,2024-12-12,544,8.6,DeepTech Ventures -AI02883,ML Ops Engineer,96944,SGD,126027,MI,FL,Singapore,S,Singapore,100,"Data Visualization, Linux, Scala, Azure",Associate,4,Consulting,2024-11-16,2025-01-19,2107,6,Quantum Computing Inc -AI02884,Data Analyst,101791,USD,101791,MI,FT,Norway,S,Norway,50,"R, Python, TensorFlow, Spark, Computer Vision",Bachelor,2,Technology,2024-04-23,2024-06-20,1704,7.1,Predictive Systems -AI02885,Data Engineer,24801,USD,24801,EN,FL,India,L,Estonia,100,"Scala, Spark, Python, Statistics",Bachelor,1,Manufacturing,2024-07-18,2024-08-18,2393,5.5,AI Innovations -AI02886,AI Specialist,76230,USD,76230,MI,CT,South Korea,M,South Korea,0,"GCP, PyTorch, Computer Vision",Master,3,Real Estate,2024-01-22,2024-03-16,1380,8.2,Future Systems -AI02887,AI Research Scientist,63817,CAD,79771,MI,FL,Canada,S,France,100,"PyTorch, Computer Vision, Mathematics",Bachelor,3,Consulting,2024-06-03,2024-08-12,1787,6.4,Algorithmic Solutions -AI02888,AI Specialist,65577,EUR,55740,MI,FL,Austria,S,Austria,0,"Scala, Mathematics, Linux, MLOps",Associate,3,Energy,2024-10-11,2024-11-04,1471,7.3,TechCorp Inc -AI02889,Autonomous Systems Engineer,114972,JPY,12646920,MI,FT,Japan,M,Japan,100,"Docker, Mathematics, Hadoop",PhD,3,Education,2024-01-25,2024-03-24,1490,7.5,Neural Networks Co -AI02890,AI Product Manager,87185,EUR,74107,SE,PT,Austria,S,Austria,100,"Spark, GCP, Git, Python",PhD,9,Consulting,2024-11-04,2024-12-27,2477,8.8,Autonomous Tech -AI02891,Deep Learning Engineer,212207,CHF,190986,SE,CT,Switzerland,M,Switzerland,100,"Tableau, Scala, Java, Spark, Linux",PhD,8,Gaming,2024-07-14,2024-08-24,519,6.9,Future Systems -AI02892,Machine Learning Engineer,90028,USD,90028,EN,PT,Denmark,L,Denmark,50,"R, SQL, PyTorch, Statistics, Kubernetes",Associate,1,Education,2024-12-24,2025-01-19,2044,7.2,DeepTech Ventures -AI02893,AI Product Manager,156876,JPY,17256360,SE,PT,Japan,L,Ireland,100,"Java, AWS, Computer Vision, Deep Learning",PhD,5,Gaming,2024-08-10,2024-08-28,1727,8.8,Neural Networks Co -AI02894,AI Consultant,116522,USD,116522,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Mathematics, Deep Learning",PhD,6,Manufacturing,2024-03-20,2024-05-09,2027,8.7,Neural Networks Co -AI02895,ML Ops Engineer,156992,CAD,196240,SE,FT,Canada,L,Denmark,0,"Data Visualization, Java, R",Associate,6,Technology,2025-01-28,2025-03-05,2468,9.3,Smart Analytics -AI02896,AI Architect,86246,USD,86246,EN,PT,Sweden,L,Denmark,0,"Java, Linux, Computer Vision, Python",PhD,0,Energy,2024-08-30,2024-09-15,1034,5,DeepTech Ventures -AI02897,Research Scientist,71217,EUR,60534,EN,CT,Austria,M,Israel,0,"GCP, Docker, Statistics, Kubernetes",PhD,1,Media,2024-12-13,2025-01-08,2027,7.4,Neural Networks Co -AI02898,AI Consultant,206746,EUR,175734,EX,CT,Netherlands,L,Netherlands,100,"AWS, Spark, Python",Associate,14,Government,2024-05-22,2024-06-24,1248,8.7,Algorithmic Solutions -AI02899,AI Consultant,169673,EUR,144222,EX,FL,Netherlands,S,Hungary,100,"Git, Scala, AWS",PhD,17,Technology,2024-02-11,2024-04-01,749,8.9,Algorithmic Solutions -AI02900,AI Product Manager,144440,GBP,108330,EX,FL,United Kingdom,S,United Kingdom,0,"NLP, Hadoop, Python",Associate,16,Gaming,2024-10-20,2024-11-19,1944,5.2,Cognitive Computing -AI02901,Machine Learning Engineer,153212,EUR,130230,EX,FT,France,L,France,100,"Deep Learning, Tableau, Python, TensorFlow, Data Visualization",PhD,16,Real Estate,2024-11-14,2025-01-01,1882,5.3,Future Systems -AI02902,Head of AI,204044,EUR,173437,EX,FL,France,S,France,0,"Python, Spark, Deep Learning",PhD,10,Education,2024-11-25,2025-01-31,788,9.1,Smart Analytics -AI02903,Autonomous Systems Engineer,151754,EUR,128991,SE,FT,Germany,L,Germany,100,"Scala, R, Tableau, SQL, GCP",Bachelor,7,Media,2025-04-30,2025-07-05,966,7.8,Quantum Computing Inc -AI02904,Computer Vision Engineer,31800,USD,31800,MI,FT,India,M,India,0,"Scala, Java, Statistics, Tableau",Associate,3,Gaming,2024-01-12,2024-02-28,977,8.8,Neural Networks Co -AI02905,Machine Learning Researcher,58310,JPY,6414100,EN,FL,Japan,M,Japan,0,"R, Docker, NLP, AWS, Hadoop",Bachelor,0,Retail,2024-09-22,2024-11-09,2121,9.9,TechCorp Inc -AI02906,Research Scientist,56624,USD,56624,EN,FL,South Korea,L,United Kingdom,100,"Hadoop, MLOps, Statistics, PyTorch",Bachelor,1,Government,2024-12-03,2024-12-27,2253,8.6,Cloud AI Solutions -AI02907,Machine Learning Researcher,150671,JPY,16573810,SE,FT,Japan,L,Denmark,50,"Mathematics, Scala, Git, Data Visualization, SQL",Bachelor,6,Gaming,2024-05-03,2024-07-07,2248,6.4,Quantum Computing Inc -AI02908,Deep Learning Engineer,202936,GBP,152202,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, SQL, Tableau, Computer Vision",Associate,15,Transportation,2025-03-01,2025-03-30,1479,8,AI Innovations -AI02909,Machine Learning Engineer,162469,AUD,219333,SE,FL,Australia,L,Australia,50,"Azure, Hadoop, Kubernetes, Python, TensorFlow",Master,9,Finance,2025-04-01,2025-05-26,2079,5.2,Future Systems -AI02910,Robotics Engineer,212416,USD,212416,EX,CT,Norway,L,Norway,50,"Linux, Azure, SQL, Statistics",PhD,15,Gaming,2024-05-19,2024-06-05,1563,6.3,Future Systems -AI02911,Robotics Engineer,109255,CHF,98330,MI,PT,Switzerland,S,Switzerland,50,"Deep Learning, Git, Statistics, PyTorch, Computer Vision",Master,3,Gaming,2024-11-15,2025-01-03,2497,5.6,Neural Networks Co -AI02912,Head of AI,88844,CAD,111055,MI,FT,Canada,S,Canada,0,"Azure, Spark, Tableau, GCP, AWS",PhD,3,Media,2024-01-26,2024-02-26,2105,6.8,DataVision Ltd -AI02913,Data Engineer,113440,USD,113440,SE,PT,South Korea,M,Luxembourg,50,"AWS, Tableau, Kubernetes, Docker",Bachelor,9,Automotive,2024-08-20,2024-09-14,2313,9.9,Autonomous Tech -AI02914,Data Engineer,98544,USD,98544,MI,PT,Sweden,L,Sweden,0,"Statistics, Azure, Git, AWS",Associate,2,Manufacturing,2024-09-21,2024-11-19,1775,6.1,AI Innovations -AI02915,Principal Data Scientist,216605,USD,216605,EX,FL,Israel,M,Israel,0,"Deep Learning, Python, Data Visualization, Hadoop, TensorFlow",Bachelor,17,Government,2024-01-05,2024-03-14,920,5.1,Digital Transformation LLC -AI02916,Data Analyst,43555,USD,43555,MI,FL,China,M,South Korea,50,"TensorFlow, GCP, Azure, Scala",Bachelor,4,Energy,2024-05-08,2024-07-02,1426,6.8,TechCorp Inc -AI02917,AI Product Manager,216702,USD,216702,EX,FL,Ireland,S,Ireland,50,"Git, Kubernetes, NLP, Hadoop",PhD,11,Education,2025-04-06,2025-06-17,1477,7.8,Smart Analytics -AI02918,NLP Engineer,172329,USD,172329,SE,CT,Norway,L,Norway,100,"Hadoop, Kubernetes, Scala, Java, PyTorch",PhD,7,Technology,2024-06-05,2024-07-23,2023,6.9,Autonomous Tech -AI02919,Data Scientist,162643,USD,162643,EX,CT,Ireland,M,Ireland,100,"R, GCP, SQL, Docker",Bachelor,17,Finance,2024-06-22,2024-07-13,809,5.2,Autonomous Tech -AI02920,Computer Vision Engineer,239531,CHF,215578,EX,FT,Switzerland,M,South Africa,0,"SQL, TensorFlow, Git",Associate,10,Media,2024-06-11,2024-08-16,2292,5.8,Autonomous Tech -AI02921,Deep Learning Engineer,169678,USD,169678,SE,PT,Norway,M,Norway,100,"TensorFlow, Python, Azure, Scala, NLP",Bachelor,8,Manufacturing,2024-06-15,2024-07-24,1276,6.1,Neural Networks Co -AI02922,Autonomous Systems Engineer,119875,USD,119875,MI,CT,Denmark,M,Denmark,50,"Computer Vision, SQL, PyTorch, R",Associate,4,Healthcare,2024-11-20,2025-01-05,2145,9.7,Cloud AI Solutions -AI02923,Machine Learning Researcher,136892,JPY,15058120,SE,FT,Japan,L,Japan,100,"TensorFlow, MLOps, R, AWS",Associate,8,Finance,2025-04-03,2025-05-03,953,5.8,Machine Intelligence Group -AI02924,Principal Data Scientist,213789,GBP,160342,EX,PT,United Kingdom,M,United Kingdom,100,"Data Visualization, Python, Tableau, Spark, Hadoop",Bachelor,15,Manufacturing,2024-10-26,2024-12-13,1726,6.5,Smart Analytics -AI02925,AI Product Manager,145769,GBP,109327,SE,PT,United Kingdom,S,United Kingdom,0,"Scala, Kubernetes, Statistics",Associate,7,Government,2025-01-07,2025-02-03,588,6.1,Algorithmic Solutions -AI02926,Principal Data Scientist,178902,USD,178902,EX,PT,Finland,S,Finland,0,"PyTorch, Python, Data Visualization",Associate,18,Media,2024-02-19,2024-04-24,1082,8.3,Cloud AI Solutions -AI02927,Machine Learning Researcher,57877,USD,57877,SE,PT,China,S,China,50,"MLOps, Linux, Docker, Deep Learning, Computer Vision",PhD,8,Gaming,2024-06-27,2024-07-28,2380,8.4,Algorithmic Solutions -AI02928,Autonomous Systems Engineer,74494,CAD,93118,MI,FT,Canada,S,Canada,100,"MLOps, AWS, Python",Bachelor,2,Retail,2024-11-05,2024-12-15,554,5.4,Algorithmic Solutions -AI02929,Data Analyst,23410,USD,23410,EN,CT,China,S,China,0,"Java, Kubernetes, NLP",PhD,0,Finance,2024-07-23,2024-09-07,1946,6.1,Advanced Robotics -AI02930,AI Specialist,144968,JPY,15946480,SE,PT,Japan,S,Japan,50,"Java, Computer Vision, Python, Data Visualization",Master,6,Consulting,2024-10-12,2024-12-24,1986,7.8,Neural Networks Co -AI02931,ML Ops Engineer,283252,CHF,254927,EX,FT,Switzerland,S,Switzerland,100,"TensorFlow, Azure, Deep Learning, Python, Linux",Master,18,Energy,2024-02-29,2024-04-18,2390,5.5,DeepTech Ventures -AI02932,Computer Vision Engineer,70074,GBP,52556,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, Statistics",Associate,0,Automotive,2025-03-03,2025-05-07,2141,9.7,DeepTech Ventures -AI02933,Autonomous Systems Engineer,111820,SGD,145366,SE,FL,Singapore,M,Mexico,100,"Kubernetes, Scala, PyTorch",Associate,5,Manufacturing,2024-11-01,2025-01-08,533,8.3,DeepTech Ventures -AI02934,ML Ops Engineer,190557,USD,190557,EX,CT,Israel,S,Israel,100,"Scala, Statistics, PyTorch, Docker",Master,12,Retail,2024-12-26,2025-01-13,798,6.9,Machine Intelligence Group -AI02935,Data Scientist,111831,USD,111831,SE,FL,Ireland,S,Ireland,50,"GCP, Tableau, Python",Associate,7,Manufacturing,2024-05-04,2024-06-24,533,8.3,Digital Transformation LLC -AI02936,Machine Learning Engineer,19152,USD,19152,EN,FT,India,M,India,100,"Java, Scala, Tableau, Data Visualization",Master,1,Gaming,2024-03-10,2024-05-01,1579,9.7,Smart Analytics -AI02937,Machine Learning Researcher,193150,USD,193150,EX,FL,Ireland,S,Ireland,100,"Python, TensorFlow, Tableau",PhD,12,Finance,2024-01-07,2024-02-22,911,7.8,Autonomous Tech -AI02938,Machine Learning Researcher,56802,USD,56802,EN,CT,South Korea,M,France,0,"Python, Scala, Statistics, Spark, Docker",Bachelor,1,Gaming,2024-11-17,2025-01-20,1044,8,TechCorp Inc -AI02939,Data Engineer,128940,EUR,109599,SE,CT,Germany,L,Germany,50,"SQL, PyTorch, Mathematics, Azure",Associate,5,Retail,2024-01-22,2024-03-12,2032,6.5,DataVision Ltd -AI02940,NLP Engineer,142396,USD,142396,SE,FL,Ireland,L,Philippines,100,"Tableau, Python, R, Docker",Master,6,Automotive,2024-05-14,2024-07-01,1925,8.3,Cloud AI Solutions -AI02941,Robotics Engineer,47879,USD,47879,SE,PT,China,S,China,100,"TensorFlow, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-09-18,1035,9.3,TechCorp Inc -AI02942,Data Analyst,129487,SGD,168333,SE,FL,Singapore,M,Singapore,0,"Linux, PyTorch, Data Visualization, Kubernetes",Associate,7,Telecommunications,2024-07-20,2024-09-01,803,6,Advanced Robotics -AI02943,Head of AI,272031,EUR,231226,EX,FL,France,L,France,0,"PyTorch, TensorFlow, Data Visualization",PhD,12,Healthcare,2024-05-15,2024-07-08,666,9.6,DataVision Ltd -AI02944,Data Analyst,125924,GBP,94443,SE,PT,United Kingdom,L,Australia,0,"Linux, Statistics, Git",Bachelor,6,Technology,2025-02-07,2025-03-09,780,6.9,Advanced Robotics -AI02945,Principal Data Scientist,24104,USD,24104,EN,FT,India,S,India,50,"Python, TensorFlow, Tableau, PyTorch",Associate,0,Media,2025-04-01,2025-05-31,860,5.2,Smart Analytics -AI02946,Principal Data Scientist,69920,EUR,59432,EN,FT,Germany,M,Germany,0,"SQL, Scala, Git, GCP",Bachelor,1,Telecommunications,2024-09-13,2024-10-25,2048,5.8,Neural Networks Co -AI02947,Data Scientist,99241,EUR,84355,SE,FT,Austria,S,Austria,50,"Kubernetes, Git, Mathematics",Bachelor,5,Manufacturing,2024-06-13,2024-08-06,803,9.8,Predictive Systems -AI02948,Principal Data Scientist,80687,CHF,72618,EN,CT,Switzerland,S,Switzerland,50,"AWS, NLP, Python, Mathematics, Scala",PhD,1,Automotive,2024-06-26,2024-07-26,1786,7.7,Algorithmic Solutions -AI02949,Deep Learning Engineer,45985,USD,45985,MI,FT,China,L,China,50,"Deep Learning, Python, Docker",PhD,2,Transportation,2024-04-28,2024-07-05,1598,8.6,TechCorp Inc -AI02950,NLP Engineer,71121,USD,71121,MI,PT,South Korea,M,Mexico,50,"Tableau, Deep Learning, TensorFlow, Python, Java",Associate,4,Technology,2024-08-20,2024-09-06,905,8.6,Algorithmic Solutions -AI02951,Principal Data Scientist,214331,USD,214331,EX,FL,Finland,L,Finland,50,"GCP, Python, TensorFlow, Docker, Statistics",Bachelor,10,Transportation,2024-03-02,2024-03-23,1877,8.9,Algorithmic Solutions -AI02952,NLP Engineer,179501,EUR,152576,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, Git, AWS, R, Java",Bachelor,9,Consulting,2024-04-13,2024-05-12,1341,8.5,DeepTech Ventures -AI02953,AI Specialist,213182,USD,213182,EX,FL,Denmark,L,United Kingdom,0,"Hadoop, R, GCP, Deep Learning",Bachelor,15,Real Estate,2024-10-26,2024-12-30,2424,9.3,Smart Analytics -AI02954,Data Analyst,257116,USD,257116,EX,CT,United States,M,Ghana,50,"NLP, R, SQL",PhD,16,Healthcare,2024-09-18,2024-10-19,2162,6.3,Autonomous Tech -AI02955,Principal Data Scientist,210838,EUR,179212,EX,FT,France,S,France,50,"SQL, Azure, Git",Associate,13,Government,2024-07-18,2024-09-26,723,8.1,DeepTech Ventures -AI02956,ML Ops Engineer,161032,USD,161032,SE,PT,Norway,S,Norway,0,"SQL, R, Java, AWS",Associate,5,Telecommunications,2024-01-14,2024-02-08,1827,7.6,Autonomous Tech -AI02957,Data Engineer,97860,EUR,83181,MI,FL,Austria,L,Chile,50,"PyTorch, Computer Vision, R",Bachelor,4,Healthcare,2024-09-19,2024-10-07,2445,6.1,Algorithmic Solutions -AI02958,Machine Learning Researcher,76742,GBP,57557,EN,FT,United Kingdom,S,United Kingdom,0,"GCP, Python, TensorFlow, NLP, Computer Vision",PhD,1,Energy,2024-10-26,2024-12-03,2112,5.1,Autonomous Tech -AI02959,AI Architect,124869,USD,124869,EX,CT,Sweden,S,Czech Republic,0,"Mathematics, Hadoop, GCP, Azure",Bachelor,19,Telecommunications,2024-04-11,2024-05-18,718,7.8,Smart Analytics -AI02960,Data Analyst,158246,USD,158246,SE,FT,Norway,L,South Korea,50,"Tableau, Spark, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-08-28,2024-09-28,939,9.5,TechCorp Inc -AI02961,Data Engineer,277909,USD,277909,EX,CT,Sweden,L,Sweden,0,"Python, Hadoop, Scala, TensorFlow",Master,16,Technology,2025-04-06,2025-06-06,1601,6.7,Neural Networks Co -AI02962,Principal Data Scientist,58343,EUR,49592,EN,FT,Germany,S,Germany,50,"SQL, Spark, Data Visualization",Bachelor,0,Education,2024-10-23,2024-12-01,535,6.5,Neural Networks Co -AI02963,AI Product Manager,98072,USD,98072,MI,PT,Sweden,L,Sweden,0,"TensorFlow, R, Statistics",Associate,4,Energy,2024-03-26,2024-05-19,710,7.8,Predictive Systems -AI02964,ML Ops Engineer,58209,USD,58209,SE,CT,India,L,India,50,"Kubernetes, Python, Spark",Bachelor,6,Government,2024-03-10,2024-05-15,621,7.8,Advanced Robotics -AI02965,Principal Data Scientist,101880,EUR,86598,SE,PT,Germany,S,Czech Republic,50,"Spark, Azure, Docker",PhD,7,Retail,2025-02-04,2025-04-03,1759,8.1,Cloud AI Solutions -AI02966,AI Architect,119812,USD,119812,MI,FL,United States,M,Italy,0,"Deep Learning, Git, Data Visualization, Statistics",Bachelor,4,Manufacturing,2024-02-02,2024-02-17,1503,7.7,TechCorp Inc -AI02967,Research Scientist,184524,USD,184524,EX,FL,Finland,S,Finland,100,"SQL, PyTorch, Deep Learning",Bachelor,12,Manufacturing,2024-10-15,2024-10-30,619,9.1,Smart Analytics -AI02968,AI Architect,212494,EUR,180620,EX,CT,Austria,M,Austria,50,"Spark, Mathematics, Java",Bachelor,19,Automotive,2024-01-03,2024-02-15,1929,6,Digital Transformation LLC -AI02969,NLP Engineer,83942,EUR,71351,MI,CT,Netherlands,S,Israel,0,"Linux, SQL, AWS",Bachelor,3,Finance,2025-04-05,2025-05-10,678,9.8,Machine Intelligence Group -AI02970,ML Ops Engineer,92507,GBP,69380,MI,PT,United Kingdom,L,Canada,100,"Git, Data Visualization, AWS, SQL",Master,3,Government,2025-04-01,2025-06-06,2111,7.5,Future Systems -AI02971,Machine Learning Researcher,71494,EUR,60770,MI,PT,France,M,South Africa,50,"R, Kubernetes, AWS, Python, Computer Vision",PhD,4,Education,2025-04-19,2025-05-31,738,8.3,Smart Analytics -AI02972,AI Product Manager,89952,AUD,121435,MI,FT,Australia,S,Australia,50,"Linux, Spark, Deep Learning",Master,2,Government,2024-07-18,2024-08-06,2280,8.2,Digital Transformation LLC -AI02973,AI Product Manager,74909,USD,74909,EX,CT,India,L,Argentina,100,"Statistics, Kubernetes, Git, GCP, Python",Master,17,Media,2024-02-28,2024-03-14,618,9.2,Algorithmic Solutions -AI02974,Data Scientist,121133,AUD,163530,SE,PT,Australia,M,Australia,100,"Python, Kubernetes, MLOps, Azure",Master,6,Manufacturing,2025-01-01,2025-03-13,1194,8.2,Autonomous Tech -AI02975,Head of AI,106190,SGD,138047,MI,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, Tableau",Bachelor,3,Finance,2024-03-05,2024-05-17,1987,7.2,AI Innovations -AI02976,AI Software Engineer,261845,EUR,222568,EX,FL,Netherlands,M,Netherlands,50,"Python, GCP, Hadoop",PhD,19,Automotive,2024-06-14,2024-08-05,1868,5.7,Quantum Computing Inc -AI02977,Robotics Engineer,104354,EUR,88701,MI,CT,Austria,L,Switzerland,100,"Java, Linux, TensorFlow, Hadoop",Associate,4,Transportation,2025-04-06,2025-04-23,611,9,TechCorp Inc -AI02978,AI Architect,86549,USD,86549,EN,FT,Sweden,L,Sweden,100,"Azure, PyTorch, Data Visualization, Kubernetes",Associate,1,Education,2025-01-27,2025-03-07,1075,6.2,DataVision Ltd -AI02979,ML Ops Engineer,170055,USD,170055,SE,FT,Sweden,L,Netherlands,100,"AWS, Linux, Scala, MLOps, Mathematics",Associate,6,Energy,2024-02-12,2024-03-31,2029,5.2,Machine Intelligence Group -AI02980,Computer Vision Engineer,92633,USD,92633,SE,FT,Israel,S,Israel,0,"Spark, Docker, Data Visualization, PyTorch",PhD,9,Real Estate,2024-05-08,2024-06-16,1790,7,DataVision Ltd -AI02981,Deep Learning Engineer,108025,EUR,91821,SE,FL,France,S,Vietnam,100,"Docker, Java, Linux, Statistics, Computer Vision",Bachelor,5,Manufacturing,2024-08-27,2024-10-11,856,8,Algorithmic Solutions -AI02982,NLP Engineer,231357,EUR,196653,EX,FT,France,L,France,100,"TensorFlow, Data Visualization, SQL, Scala",Master,10,Real Estate,2025-02-05,2025-03-18,771,7.4,Autonomous Tech -AI02983,AI Consultant,75714,AUD,102214,MI,PT,Australia,M,Australia,0,"Git, SQL, Computer Vision, Hadoop, Java",Associate,3,Real Estate,2025-04-25,2025-05-18,895,7.1,Neural Networks Co -AI02984,Machine Learning Researcher,48731,EUR,41421,EN,CT,Austria,S,Austria,100,"R, Hadoop, Docker, Computer Vision, Python",PhD,0,Real Estate,2024-10-05,2024-12-15,1480,9.2,Future Systems -AI02985,AI Architect,63620,EUR,54077,EN,FL,Austria,L,Austria,100,"Linux, Spark, NLP, Kubernetes",Master,1,Energy,2024-05-01,2024-06-14,1567,7.5,DataVision Ltd -AI02986,Deep Learning Engineer,146711,USD,146711,SE,FL,United States,S,United States,50,"R, NLP, Kubernetes",Bachelor,8,Retail,2024-04-09,2024-06-02,1302,6.2,Cloud AI Solutions -AI02987,Autonomous Systems Engineer,217093,USD,217093,EX,PT,Finland,M,Finland,0,"Scala, PyTorch, GCP",Associate,15,Government,2024-01-01,2024-03-13,1010,9.5,Predictive Systems -AI02988,Computer Vision Engineer,158838,EUR,135012,SE,FL,Netherlands,L,South Africa,100,"Hadoop, Python, R",Master,7,Media,2024-11-21,2025-01-20,814,6.7,Cloud AI Solutions -AI02989,Machine Learning Engineer,26471,USD,26471,MI,CT,India,S,India,50,"Tableau, Git, Python, Computer Vision",Master,3,Healthcare,2025-04-15,2025-05-24,2355,8.1,Machine Intelligence Group -AI02990,Principal Data Scientist,52315,EUR,44468,EN,FT,Germany,M,Germany,100,"AWS, Python, Tableau",Master,0,Technology,2024-01-02,2024-02-21,1188,9.6,Quantum Computing Inc -AI02991,Research Scientist,155395,USD,155395,SE,PT,Finland,L,Finland,100,"Git, NLP, Scala",Bachelor,7,Consulting,2024-07-05,2024-08-06,1078,6.3,Smart Analytics -AI02992,Deep Learning Engineer,103774,USD,103774,SE,CT,Sweden,M,Sweden,100,"Python, Java, TensorFlow",PhD,5,Manufacturing,2024-02-14,2024-03-18,738,8.7,Machine Intelligence Group -AI02993,AI Specialist,116286,USD,116286,SE,CT,Finland,M,Czech Republic,0,"AWS, Java, Statistics, Mathematics",Associate,7,Media,2025-04-27,2025-06-01,1491,6.7,Cognitive Computing -AI02994,ML Ops Engineer,75877,USD,75877,EN,CT,United States,S,United States,50,"NLP, Python, SQL, Git",Master,0,Healthcare,2025-01-11,2025-02-22,751,9.7,Future Systems -AI02995,Data Analyst,73643,AUD,99418,MI,FT,Australia,S,Indonesia,0,"Azure, Spark, MLOps",Bachelor,2,Consulting,2024-07-04,2024-07-27,1225,9.9,Advanced Robotics -AI02996,AI Specialist,252203,CHF,226983,EX,FL,Switzerland,L,Switzerland,50,"Hadoop, PyTorch, Java, Computer Vision, Mathematics",Bachelor,13,Automotive,2025-04-18,2025-06-12,1635,7.6,Predictive Systems -AI02997,AI Specialist,82912,USD,82912,MI,FT,Israel,M,Indonesia,0,"R, Tableau, Linux",Bachelor,4,Energy,2024-08-03,2024-08-25,2064,7.6,Advanced Robotics -AI02998,AI Specialist,152624,USD,152624,SE,FL,Ireland,L,Ireland,100,"R, Python, Git, GCP, Linux",Master,9,Retail,2024-11-28,2025-01-15,1068,5.4,Future Systems -AI02999,AI Architect,87630,USD,87630,MI,FT,South Korea,L,South Korea,100,"AWS, Linux, Deep Learning, R",Associate,2,Manufacturing,2024-05-01,2024-06-16,945,8.8,Cognitive Computing -AI03000,AI Research Scientist,234953,SGD,305439,EX,FL,Singapore,S,Singapore,50,"Linux, R, TensorFlow, Git, Tableau",PhD,12,Consulting,2024-04-14,2024-05-18,930,9,AI Innovations -AI03001,AI Research Scientist,121264,SGD,157643,SE,FL,Singapore,S,Singapore,0,"Spark, Kubernetes, GCP, TensorFlow",Master,7,Government,2024-01-14,2024-03-21,1534,9.8,Digital Transformation LLC -AI03002,Machine Learning Researcher,158964,USD,158964,MI,PT,Denmark,L,Denmark,0,"Scala, SQL, Java, Docker, PyTorch",Master,4,Education,2024-06-25,2024-07-10,638,7.6,Cloud AI Solutions -AI03003,Computer Vision Engineer,73586,JPY,8094460,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, Docker, Data Visualization",Bachelor,1,Retail,2024-11-26,2025-01-15,1557,7,DeepTech Ventures -AI03004,Machine Learning Engineer,230512,GBP,172884,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Kubernetes, Python",Master,13,Telecommunications,2024-05-26,2024-06-24,827,7,Advanced Robotics -AI03005,Autonomous Systems Engineer,125009,CAD,156261,SE,CT,Canada,S,Czech Republic,50,"Kubernetes, Computer Vision, SQL",PhD,7,Telecommunications,2025-01-28,2025-03-31,1710,5.3,Advanced Robotics -AI03006,AI Architect,262701,USD,262701,EX,PT,Sweden,L,Belgium,50,"Python, AWS, TensorFlow",Bachelor,19,Gaming,2024-12-02,2025-01-07,1868,9.6,Autonomous Tech -AI03007,ML Ops Engineer,266606,USD,266606,EX,CT,Denmark,S,Denmark,50,"Hadoop, Python, Tableau, Deep Learning",PhD,18,Automotive,2025-02-02,2025-03-30,1674,8.3,Smart Analytics -AI03008,NLP Engineer,140178,SGD,182231,SE,FT,Singapore,S,Singapore,100,"Tableau, Deep Learning, Hadoop, MLOps",Bachelor,5,Retail,2025-04-15,2025-06-20,2368,5.3,Future Systems -AI03009,NLP Engineer,187857,CAD,234821,EX,FL,Canada,L,Canada,0,"Deep Learning, Spark, Data Visualization, SQL, Kubernetes",Bachelor,18,Consulting,2024-07-21,2024-09-28,1818,5.9,Cognitive Computing -AI03010,Data Analyst,42710,USD,42710,MI,FT,China,M,Spain,100,"Java, R, Hadoop, Linux",PhD,2,Finance,2024-11-30,2025-01-16,691,9.8,Digital Transformation LLC -AI03011,Data Scientist,84841,EUR,72115,MI,PT,Netherlands,M,Netherlands,50,"Java, R, Tableau, SQL, Scala",Bachelor,4,Transportation,2024-03-02,2024-04-23,2405,7.6,Advanced Robotics -AI03012,AI Consultant,74980,EUR,63733,MI,CT,Austria,S,Austria,0,"SQL, PyTorch, R, Hadoop, Python",Bachelor,3,Telecommunications,2024-06-25,2024-08-19,1005,8.3,TechCorp Inc -AI03013,AI Consultant,84006,EUR,71405,MI,CT,France,M,Brazil,0,"Deep Learning, SQL, Mathematics",Master,3,Real Estate,2024-06-20,2024-08-04,1656,6.9,Digital Transformation LLC -AI03014,AI Consultant,174420,EUR,148257,EX,CT,France,S,Romania,100,"Kubernetes, Scala, Java, Spark",PhD,19,Education,2024-01-16,2024-03-23,1377,9.3,Future Systems -AI03015,Computer Vision Engineer,243382,USD,243382,EX,PT,Sweden,M,Sweden,50,"Linux, Kubernetes, Git, Docker, Python",Associate,19,Gaming,2024-04-22,2024-06-10,1260,8.7,Advanced Robotics -AI03016,AI Consultant,72001,EUR,61201,MI,PT,Austria,S,Austria,0,"Java, Hadoop, Scala, GCP",PhD,4,Government,2024-04-01,2024-05-16,698,9.4,Cloud AI Solutions -AI03017,AI Architect,349094,USD,349094,EX,PT,Denmark,L,Denmark,100,"PyTorch, Scala, NLP, Computer Vision",Bachelor,13,Healthcare,2024-03-04,2024-05-09,2490,8.9,Cloud AI Solutions -AI03018,Machine Learning Engineer,135760,USD,135760,SE,FT,Norway,S,Norway,50,"Azure, Linux, Docker, SQL",Bachelor,5,Consulting,2024-08-28,2024-09-30,1383,7.4,Quantum Computing Inc -AI03019,AI Research Scientist,127359,EUR,108255,SE,CT,France,L,France,50,"Computer Vision, Java, SQL",Master,9,Telecommunications,2024-06-19,2024-08-08,1050,5.7,Smart Analytics -AI03020,Data Engineer,97760,SGD,127088,SE,PT,Singapore,S,Ireland,0,"TensorFlow, GCP, Tableau, Computer Vision",PhD,6,Technology,2024-03-09,2024-04-17,2013,6.9,Machine Intelligence Group -AI03021,AI Software Engineer,217718,JPY,23948980,EX,FT,Japan,M,Japan,100,"MLOps, R, Computer Vision, Scala",Associate,13,Telecommunications,2024-08-08,2024-10-13,1785,9.8,Smart Analytics -AI03022,Deep Learning Engineer,129149,CAD,161436,SE,CT,Canada,S,Canada,100,"R, Kubernetes, Mathematics",Associate,5,Gaming,2025-04-18,2025-06-30,650,6.7,AI Innovations -AI03023,Data Analyst,66925,USD,66925,EN,PT,Ireland,S,Ireland,50,"SQL, Java, PyTorch, Git, Spark",Master,1,Technology,2024-05-26,2024-06-10,783,5.4,Digital Transformation LLC -AI03024,Data Engineer,87198,EUR,74118,MI,PT,Germany,S,Germany,50,"Git, R, Kubernetes, Spark",Bachelor,2,Gaming,2024-12-18,2025-01-25,1440,9.8,Autonomous Tech -AI03025,AI Software Engineer,94601,USD,94601,EN,PT,United States,L,United States,0,"AWS, Java, Deep Learning, Python, TensorFlow",PhD,0,Telecommunications,2025-01-20,2025-03-30,874,9.3,Neural Networks Co -AI03026,Principal Data Scientist,51043,USD,51043,EN,PT,South Korea,M,South Korea,100,"Data Visualization, AWS, TensorFlow, SQL, NLP",Associate,0,Gaming,2024-07-21,2024-08-30,1749,5.9,Smart Analytics -AI03027,Autonomous Systems Engineer,88860,EUR,75531,MI,CT,France,L,France,50,"Hadoop, Computer Vision, Mathematics, MLOps",Bachelor,3,Retail,2024-09-27,2024-12-08,1581,10,Machine Intelligence Group -AI03028,AI Specialist,91219,USD,91219,MI,FT,Sweden,S,Sweden,50,"GCP, Java, SQL, Deep Learning",PhD,4,Transportation,2025-04-16,2025-06-01,1553,5.8,Autonomous Tech -AI03029,AI Product Manager,23010,USD,23010,MI,FL,India,S,India,100,"Python, Computer Vision, Java",Master,4,Gaming,2024-08-24,2024-11-02,1484,7.7,Predictive Systems -AI03030,Autonomous Systems Engineer,84775,USD,84775,MI,PT,Finland,L,Finland,100,"PyTorch, SQL, Computer Vision",PhD,4,Consulting,2024-11-23,2024-12-08,1320,5.7,Neural Networks Co -AI03031,Machine Learning Researcher,182231,USD,182231,EX,FT,Norway,M,Norway,100,"Tableau, Computer Vision, NLP, Python, MLOps",PhD,11,Government,2024-02-16,2024-03-29,2292,8.2,Autonomous Tech -AI03032,Data Engineer,76682,USD,76682,EX,FT,India,M,India,0,"PyTorch, AWS, Data Visualization, Deep Learning",PhD,12,Finance,2025-04-25,2025-06-15,552,8.7,Neural Networks Co -AI03033,NLP Engineer,103728,EUR,88169,SE,CT,Austria,S,Austria,100,"R, Spark, TensorFlow",Master,8,Gaming,2024-05-01,2024-06-01,700,9.8,Digital Transformation LLC -AI03034,Machine Learning Engineer,108739,CHF,97865,EN,FT,Switzerland,L,Switzerland,0,"Scala, Linux, Computer Vision, Java",Associate,0,Telecommunications,2024-04-23,2024-06-11,829,6.3,Neural Networks Co -AI03035,AI Architect,127790,USD,127790,SE,PT,Israel,L,Israel,50,"GCP, R, Tableau",Master,8,Finance,2024-06-07,2024-07-18,880,6.2,Cloud AI Solutions -AI03036,Deep Learning Engineer,113774,USD,113774,MI,CT,United States,L,Belgium,50,"Data Visualization, R, Java, Tableau",Associate,3,Automotive,2024-04-28,2024-05-27,529,9.4,Algorithmic Solutions -AI03037,Research Scientist,119989,USD,119989,EN,FL,Denmark,L,Denmark,100,"Data Visualization, Linux, Tableau",Associate,1,Telecommunications,2024-07-15,2024-08-25,1170,6.1,Advanced Robotics -AI03038,Machine Learning Engineer,75024,USD,75024,MI,PT,Israel,S,Netherlands,100,"Tableau, Azure, AWS, SQL",Associate,4,Government,2025-04-13,2025-05-22,1521,9.3,Advanced Robotics -AI03039,Research Scientist,67687,USD,67687,EN,CT,Ireland,M,Indonesia,0,"R, Deep Learning, SQL, Data Visualization, Kubernetes",PhD,1,Media,2024-08-12,2024-10-08,508,5.4,AI Innovations -AI03040,Data Scientist,82087,USD,82087,MI,FL,United States,S,United States,100,"MLOps, Hadoop, Java, Spark, Tableau",PhD,4,Media,2024-10-11,2024-11-07,1535,6.8,AI Innovations -AI03041,Computer Vision Engineer,240800,USD,240800,EX,FL,Sweden,M,Sweden,50,"Kubernetes, Deep Learning, SQL, PyTorch",Bachelor,15,Consulting,2024-08-27,2024-09-11,2073,8,TechCorp Inc -AI03042,Principal Data Scientist,76214,EUR,64782,MI,PT,Germany,S,Germany,0,"Python, R, SQL, Kubernetes, Mathematics",PhD,3,Media,2025-02-26,2025-04-14,1646,6.7,Autonomous Tech -AI03043,AI Consultant,259438,CHF,233494,EX,PT,Switzerland,L,Switzerland,0,"Git, Scala, Hadoop, SQL",Bachelor,13,Energy,2024-01-19,2024-02-03,2304,5.3,Predictive Systems -AI03044,Data Engineer,245492,USD,245492,EX,FL,Denmark,S,Denmark,100,"Kubernetes, Deep Learning, Mathematics, AWS",Master,17,Manufacturing,2024-07-24,2024-09-30,2187,8.1,Autonomous Tech -AI03045,ML Ops Engineer,102823,CAD,128529,MI,FL,Canada,M,Canada,100,"Linux, R, TensorFlow, Deep Learning, Data Visualization",Master,3,Manufacturing,2025-04-04,2025-04-24,1976,9.7,Digital Transformation LLC -AI03046,Deep Learning Engineer,283410,USD,283410,EX,FT,Ireland,L,Ireland,50,"Docker, Statistics, Deep Learning, R, SQL",Bachelor,18,Telecommunications,2024-01-27,2024-03-15,1313,7.1,Machine Intelligence Group -AI03047,Machine Learning Engineer,208241,USD,208241,EX,FT,Ireland,M,Kenya,50,"Kubernetes, Azure, Data Visualization",Bachelor,18,Automotive,2024-08-18,2024-10-22,2371,8.9,TechCorp Inc -AI03048,ML Ops Engineer,105274,GBP,78956,MI,PT,United Kingdom,S,Brazil,100,"Java, Git, R, Linux, SQL",PhD,3,Government,2025-01-08,2025-02-16,936,7.4,Neural Networks Co -AI03049,Principal Data Scientist,94841,USD,94841,MI,FL,Israel,L,Israel,0,"SQL, Java, Linux, NLP, Tableau",Bachelor,3,Media,2024-09-17,2024-11-12,651,6.1,Future Systems -AI03050,Autonomous Systems Engineer,114463,EUR,97294,MI,FT,Austria,L,Austria,50,"Python, Hadoop, SQL, Docker",Master,2,Consulting,2024-07-28,2024-09-23,2088,6.8,AI Innovations -AI03051,Data Engineer,158187,USD,158187,SE,PT,Denmark,S,Denmark,100,"SQL, R, Data Visualization, Docker",Bachelor,5,Telecommunications,2024-03-20,2024-05-21,835,6,Future Systems -AI03052,Principal Data Scientist,45177,USD,45177,EN,PT,South Korea,S,South Korea,50,"R, Linux, Python, Tableau, Mathematics",PhD,1,Education,2024-01-23,2024-02-06,1425,5.5,Smart Analytics -AI03053,Head of AI,147403,EUR,125293,SE,PT,Germany,L,Germany,50,"Kubernetes, Hadoop, NLP, Statistics, Python",Associate,8,Automotive,2024-04-26,2024-05-31,1232,8.4,Predictive Systems -AI03054,Deep Learning Engineer,103578,USD,103578,SE,FL,Ireland,S,Ireland,50,"TensorFlow, Linux, PyTorch, Tableau",PhD,5,Transportation,2024-10-16,2024-12-06,2330,8.9,Quantum Computing Inc -AI03055,Deep Learning Engineer,90139,AUD,121688,MI,FL,Australia,L,Australia,100,"R, Mathematics, Data Visualization, Linux, Kubernetes",Master,4,Telecommunications,2025-01-10,2025-02-08,1856,7.4,DataVision Ltd -AI03056,AI Product Manager,140051,EUR,119043,SE,FT,France,L,France,100,"Scala, Git, Statistics, Computer Vision, Python",Master,5,Automotive,2024-01-13,2024-03-02,1252,7.4,Quantum Computing Inc -AI03057,Head of AI,55899,USD,55899,EN,FT,Israel,M,Israel,50,"Tableau, Azure, Hadoop",Bachelor,0,Education,2024-06-01,2024-07-03,1765,8.2,Future Systems -AI03058,Machine Learning Engineer,228939,EUR,194598,EX,CT,Germany,M,Mexico,50,"NLP, AWS, Git, GCP, Mathematics",PhD,14,Transportation,2024-09-10,2024-10-20,2130,8.5,Neural Networks Co -AI03059,Computer Vision Engineer,169575,CHF,152618,SE,PT,Switzerland,S,Switzerland,50,"Tableau, Git, Computer Vision, Python, Statistics",Associate,8,Energy,2025-04-09,2025-06-16,1773,5.1,Autonomous Tech -AI03060,AI Specialist,92434,GBP,69326,EN,CT,United Kingdom,L,Vietnam,0,"Data Visualization, Spark, Computer Vision, SQL, PyTorch",Bachelor,0,Gaming,2024-10-27,2024-12-11,1856,7.4,TechCorp Inc -AI03061,NLP Engineer,45214,CAD,56518,EN,CT,Canada,S,Canada,100,"GCP, Computer Vision, Python, R, TensorFlow",PhD,1,Finance,2024-01-25,2024-03-23,2385,7.6,DeepTech Ventures -AI03062,Principal Data Scientist,125545,AUD,169486,MI,FT,Australia,L,Thailand,50,"Python, Git, TensorFlow, NLP",Associate,4,Technology,2024-09-14,2024-10-20,868,8.1,Future Systems -AI03063,AI Research Scientist,63222,USD,63222,EX,FT,India,M,India,100,"MLOps, TensorFlow, Tableau, Linux",PhD,15,Government,2024-03-21,2024-05-29,1313,5.4,Neural Networks Co -AI03064,Deep Learning Engineer,90458,USD,90458,MI,PT,Finland,L,Finland,0,"SQL, Python, NLP, Statistics",Master,2,Transportation,2024-10-26,2024-12-04,834,9.1,DataVision Ltd -AI03065,Data Analyst,53532,USD,53532,EN,PT,Sweden,S,Brazil,0,"Kubernetes, Statistics, Tableau, Mathematics, Java",Bachelor,1,Energy,2025-03-04,2025-04-17,1479,8.4,Algorithmic Solutions -AI03066,Computer Vision Engineer,111068,USD,111068,MI,FL,Norway,M,United States,100,"Data Visualization, Python, TensorFlow, Docker",Master,4,Telecommunications,2025-03-23,2025-04-24,618,8.8,Future Systems -AI03067,AI Research Scientist,51281,CAD,64101,EN,FT,Canada,M,Ireland,50,"SQL, Kubernetes, Scala, Mathematics",Master,0,Government,2025-01-25,2025-02-20,1572,6.7,Neural Networks Co -AI03068,Robotics Engineer,70333,USD,70333,EX,CT,India,S,India,100,"Tableau, Data Visualization, SQL, PyTorch",Bachelor,12,Finance,2024-05-13,2024-06-24,1694,7.8,Neural Networks Co -AI03069,Data Scientist,113289,USD,113289,MI,PT,Norway,M,Italy,50,"Python, Java, Hadoop, AWS, Kubernetes",Bachelor,4,Gaming,2024-09-17,2024-11-26,1355,7.9,Algorithmic Solutions -AI03070,Deep Learning Engineer,76340,USD,76340,EN,FT,Israel,L,Israel,100,"AWS, SQL, Python",Master,0,Retail,2024-07-29,2024-09-19,1293,8,Predictive Systems -AI03071,Deep Learning Engineer,83602,USD,83602,MI,CT,Finland,M,Finland,100,"Data Visualization, R, NLP, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-15,884,5.7,Quantum Computing Inc -AI03072,Machine Learning Researcher,140958,AUD,190293,EX,CT,Australia,M,Thailand,0,"Docker, Hadoop, Mathematics, Kubernetes",Master,15,Consulting,2024-05-31,2024-07-29,1825,7.2,DeepTech Ventures -AI03073,Machine Learning Engineer,224243,USD,224243,EX,FL,United States,L,United States,50,"Java, R, SQL, Data Visualization, Linux",PhD,17,Media,2024-06-25,2024-08-19,1126,7.2,Predictive Systems -AI03074,AI Product Manager,182443,USD,182443,EX,PT,Sweden,L,Sweden,50,"Computer Vision, Python, Tableau, Data Visualization",Bachelor,15,Technology,2024-10-26,2024-12-02,2303,6.3,Autonomous Tech -AI03075,Principal Data Scientist,116360,AUD,157086,SE,CT,Australia,S,Australia,0,"Mathematics, Kubernetes, Data Visualization, GCP, PyTorch",Master,9,Technology,2024-02-03,2024-03-03,1533,6.7,DeepTech Ventures -AI03076,Machine Learning Engineer,59186,SGD,76942,EN,CT,Singapore,S,Singapore,0,"Java, R, Computer Vision, Tableau, Statistics",Master,1,Government,2025-04-16,2025-06-27,1282,6.6,Digital Transformation LLC -AI03077,AI Product Manager,230221,CAD,287776,EX,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Python",Master,11,Manufacturing,2024-02-06,2024-04-07,883,7.7,Cognitive Computing -AI03078,AI Specialist,249223,EUR,211840,EX,FL,Germany,L,Chile,50,"Scala, TensorFlow, SQL, Kubernetes",Master,14,Retail,2025-04-13,2025-05-23,1427,6.4,Cognitive Computing -AI03079,Principal Data Scientist,170776,USD,170776,SE,CT,United States,M,United States,0,"Java, Data Visualization, R, Scala",Master,5,Gaming,2025-01-16,2025-02-03,1122,8.8,DeepTech Ventures -AI03080,Computer Vision Engineer,76117,EUR,64699,EN,FL,Germany,M,Estonia,0,"R, Git, Hadoop",Master,1,Consulting,2024-01-03,2024-02-07,1271,9.4,Algorithmic Solutions -AI03081,AI Research Scientist,65226,AUD,88055,EN,FT,Australia,L,Australia,0,"Kubernetes, PyTorch, Azure, SQL",PhD,0,Finance,2024-10-26,2024-11-28,684,5.5,Machine Intelligence Group -AI03082,Computer Vision Engineer,63087,EUR,53624,EN,PT,Austria,M,Austria,0,"Git, Azure, Statistics, GCP",Associate,1,Telecommunications,2024-12-19,2025-01-26,2458,8.8,Cloud AI Solutions -AI03083,Machine Learning Engineer,44772,USD,44772,MI,FL,China,M,China,50,"R, Java, Data Visualization",Master,4,Transportation,2024-01-01,2024-01-24,1106,9.3,Algorithmic Solutions -AI03084,Data Scientist,204283,AUD,275782,EX,FT,Australia,S,Brazil,100,"Python, Scala, Kubernetes, Docker",Associate,12,Retail,2024-04-21,2024-06-19,1045,8.5,Advanced Robotics -AI03085,Machine Learning Engineer,114299,USD,114299,SE,PT,Ireland,M,Portugal,100,"GCP, Java, MLOps",Bachelor,8,Transportation,2024-10-26,2024-11-22,1175,6.8,Future Systems -AI03086,AI Consultant,298889,USD,298889,EX,FT,Norway,L,Norway,50,"GCP, Statistics, Git, Hadoop",Associate,16,Consulting,2024-02-29,2024-04-06,1175,6.8,Cloud AI Solutions -AI03087,AI Specialist,71400,JPY,7854000,EN,FT,Japan,S,Japan,50,"Azure, Docker, MLOps",Bachelor,0,Manufacturing,2024-02-13,2024-03-13,2014,8.1,TechCorp Inc -AI03088,Research Scientist,69118,USD,69118,EN,FL,United States,S,United States,100,"Spark, TensorFlow, Git, Docker, Java",Associate,0,Telecommunications,2024-12-12,2025-02-16,739,6,DeepTech Ventures -AI03089,Robotics Engineer,47701,USD,47701,MI,PT,China,M,China,0,"Git, Linux, Mathematics, Kubernetes, Spark",Master,3,Education,2024-08-02,2024-08-17,2068,9.5,Advanced Robotics -AI03090,Data Scientist,162815,USD,162815,SE,FL,Norway,L,Norway,50,"Mathematics, Docker, Statistics",Bachelor,9,Gaming,2024-12-13,2025-01-30,1879,7.3,Predictive Systems -AI03091,Deep Learning Engineer,136275,CHF,122648,MI,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Spark",Associate,3,Automotive,2024-07-11,2024-09-07,506,7.9,Future Systems -AI03092,AI Specialist,77774,CAD,97218,MI,PT,Canada,S,Canada,0,"AWS, Deep Learning, Docker",PhD,2,Retail,2025-04-16,2025-06-09,675,6.2,Neural Networks Co -AI03093,Computer Vision Engineer,151655,JPY,16682050,EX,FT,Japan,S,Japan,0,"Scala, SQL, MLOps, Azure, Kubernetes",Bachelor,17,Energy,2025-02-04,2025-02-27,1886,9.8,DataVision Ltd -AI03094,AI Specialist,147631,USD,147631,SE,FT,Finland,L,Finland,50,"Scala, Deep Learning, Java, Azure, PyTorch",PhD,5,Automotive,2024-03-18,2024-04-10,834,7.5,Digital Transformation LLC -AI03095,Robotics Engineer,44181,USD,44181,EX,CT,India,S,India,100,"GCP, Kubernetes, PyTorch",PhD,15,Transportation,2024-03-28,2024-05-15,2429,8.4,Predictive Systems -AI03096,AI Specialist,92006,EUR,78205,MI,FL,Germany,M,Germany,100,"Spark, Linux, NLP, SQL, Python",PhD,2,Real Estate,2024-10-06,2024-11-10,1434,6,DeepTech Ventures -AI03097,Data Analyst,104944,EUR,89202,MI,CT,Germany,L,Germany,0,"Python, Deep Learning, Data Visualization, R",Master,3,Education,2024-03-10,2024-04-04,1885,6.2,Predictive Systems -AI03098,ML Ops Engineer,261580,USD,261580,EX,CT,United States,M,United States,50,"Linux, Docker, Data Visualization, GCP, SQL",Bachelor,10,Transportation,2024-11-29,2024-12-31,1601,5.1,Neural Networks Co -AI03099,AI Software Engineer,32682,USD,32682,MI,FT,India,L,India,0,"GCP, Kubernetes, Azure",Master,4,Real Estate,2024-06-08,2024-07-17,1624,8.3,Algorithmic Solutions -AI03100,Research Scientist,46243,USD,46243,EN,FT,Sweden,S,Sweden,0,"Hadoop, TensorFlow, Git",Bachelor,1,Real Estate,2025-02-09,2025-04-13,1897,8.6,Quantum Computing Inc -AI03101,AI Software Engineer,51801,CAD,64751,EN,CT,Canada,S,Canada,0,"R, SQL, Linux, Kubernetes, Hadoop",PhD,1,Government,2024-03-16,2024-04-13,1014,8.8,Smart Analytics -AI03102,AI Software Engineer,110654,SGD,143850,MI,PT,Singapore,M,Singapore,0,"Hadoop, Mathematics, Kubernetes, PyTorch",Associate,4,Technology,2024-07-31,2024-09-04,1544,7.4,Cognitive Computing -AI03103,Data Scientist,123362,USD,123362,SE,CT,Israel,S,Israel,0,"Linux, AWS, MLOps, Scala, Python",PhD,8,Energy,2024-03-23,2024-05-08,1021,6.9,Future Systems -AI03104,Principal Data Scientist,66961,USD,66961,MI,FT,South Korea,M,South Korea,100,"Hadoop, Computer Vision, Java, Linux, R",PhD,3,Retail,2024-11-23,2025-01-04,960,7.7,Machine Intelligence Group -AI03105,Autonomous Systems Engineer,96935,USD,96935,MI,FL,Denmark,S,South Korea,50,"AWS, Data Visualization, MLOps",PhD,2,Education,2024-04-02,2024-05-17,597,9.4,DeepTech Ventures -AI03106,NLP Engineer,165702,JPY,18227220,EX,PT,Japan,L,Japan,50,"SQL, R, Linux, PyTorch",Master,12,Retail,2024-08-13,2024-09-01,1511,5.4,Autonomous Tech -AI03107,Computer Vision Engineer,102570,CHF,92313,MI,PT,Switzerland,M,Switzerland,0,"R, SQL, Data Visualization, Computer Vision, Java",Master,4,Healthcare,2024-11-15,2024-12-27,2061,7,Cognitive Computing -AI03108,Principal Data Scientist,31054,USD,31054,MI,CT,India,S,India,50,"Azure, Scala, Java, Mathematics",PhD,4,Government,2025-04-06,2025-05-05,716,5.4,Cognitive Computing -AI03109,AI Software Engineer,26978,USD,26978,EN,CT,China,M,China,0,"Kubernetes, Linux, Mathematics, Hadoop, Scala",Bachelor,1,Healthcare,2024-12-22,2025-01-30,2254,5.5,Neural Networks Co -AI03110,Machine Learning Engineer,45155,USD,45155,SE,FT,China,S,China,50,"Computer Vision, Tableau, Azure, Kubernetes, Spark",Master,5,Gaming,2024-04-03,2024-05-07,582,9.2,Smart Analytics -AI03111,Deep Learning Engineer,84059,USD,84059,MI,FL,United States,S,United States,50,"Linux, Docker, TensorFlow",Bachelor,4,Manufacturing,2024-06-23,2024-07-09,1520,9.1,Future Systems -AI03112,AI Product Manager,66866,USD,66866,EX,FT,India,L,India,0,"Spark, TensorFlow, SQL",Master,13,Transportation,2024-08-09,2024-09-29,2158,9.9,Cloud AI Solutions -AI03113,AI Software Engineer,56427,USD,56427,EN,CT,Ireland,M,Belgium,0,"Docker, Mathematics, PyTorch, Scala",Associate,0,Media,2024-12-19,2025-02-05,568,8.4,Autonomous Tech -AI03114,Principal Data Scientist,91432,USD,91432,MI,FL,Israel,L,Chile,50,"Git, Hadoop, Computer Vision",PhD,3,Healthcare,2024-01-09,2024-03-19,958,7.4,AI Innovations -AI03115,ML Ops Engineer,117486,EUR,99863,SE,FL,France,L,France,50,"Python, R, Computer Vision, Data Visualization, Statistics",PhD,9,Automotive,2025-02-18,2025-04-13,1430,6.9,Digital Transformation LLC -AI03116,ML Ops Engineer,85568,USD,85568,MI,CT,Finland,M,Sweden,0,"Kubernetes, Spark, Tableau, Statistics",PhD,2,Finance,2025-04-11,2025-06-17,538,9.7,Cognitive Computing -AI03117,ML Ops Engineer,308132,EUR,261912,EX,FL,Netherlands,L,India,0,"Hadoop, MLOps, Spark, Linux, R",Associate,19,Retail,2025-04-04,2025-05-24,991,7.7,Future Systems -AI03118,Head of AI,262758,SGD,341585,EX,FL,Singapore,M,Singapore,100,"Python, Computer Vision, Scala",Master,19,Transportation,2024-08-31,2024-09-22,1556,7.2,Autonomous Tech -AI03119,Principal Data Scientist,61958,USD,61958,EX,FL,India,M,Canada,50,"Java, Python, Tableau, Kubernetes, Docker",Master,12,Gaming,2024-10-23,2024-12-27,1245,8.3,Digital Transformation LLC -AI03120,Data Engineer,116493,USD,116493,SE,FL,Ireland,M,Brazil,0,"Linux, AWS, SQL, Kubernetes",PhD,8,Transportation,2024-05-30,2024-07-13,2110,5.1,TechCorp Inc -AI03121,Machine Learning Engineer,174253,SGD,226529,EX,FT,Singapore,S,Singapore,100,"Hadoop, Azure, NLP",Bachelor,14,Education,2025-04-02,2025-04-16,783,5.7,Algorithmic Solutions -AI03122,Research Scientist,133772,USD,133772,SE,PT,United States,S,United States,50,"Kubernetes, PyTorch, GCP",Bachelor,7,Media,2024-04-19,2024-05-04,1741,7.8,Smart Analytics -AI03123,Machine Learning Engineer,183867,USD,183867,EX,FT,Israel,L,Israel,0,"Scala, Computer Vision, Tableau, AWS",PhD,15,Manufacturing,2024-10-05,2024-12-08,1829,6.4,Advanced Robotics -AI03124,Data Analyst,100550,JPY,11060500,MI,FL,Japan,L,Japan,100,"Tableau, Hadoop, Azure, PyTorch, TensorFlow",Associate,3,Transportation,2025-02-28,2025-04-15,842,6.9,Digital Transformation LLC -AI03125,Data Engineer,209570,EUR,178135,EX,FT,Austria,M,Austria,100,"SQL, Python, Java",Associate,10,Telecommunications,2025-01-04,2025-03-08,1946,6.3,Cognitive Computing -AI03126,Machine Learning Researcher,27770,USD,27770,EN,CT,India,L,India,50,"Deep Learning, PyTorch, MLOps, TensorFlow",PhD,0,Manufacturing,2025-01-31,2025-03-25,695,6.1,Machine Intelligence Group -AI03127,Head of AI,239820,SGD,311766,EX,PT,Singapore,M,Singapore,100,"Java, Python, NLP",Bachelor,13,Retail,2024-04-12,2024-06-01,1250,8.2,Future Systems -AI03128,Machine Learning Researcher,90202,USD,90202,EN,FL,Ireland,L,Ireland,50,"Kubernetes, MLOps, PyTorch",PhD,0,Consulting,2025-01-15,2025-03-16,1443,8.8,DataVision Ltd -AI03129,Computer Vision Engineer,47313,EUR,40216,EN,FL,Austria,S,Austria,0,"Python, NLP, TensorFlow",Master,0,Consulting,2025-03-22,2025-05-10,1996,7.4,Predictive Systems -AI03130,Data Analyst,57899,USD,57899,EN,CT,Israel,M,Israel,100,"R, Computer Vision, GCP",Bachelor,1,Healthcare,2024-02-18,2024-04-01,1649,7.8,Machine Intelligence Group -AI03131,ML Ops Engineer,181110,GBP,135833,SE,PT,United Kingdom,L,Mexico,0,"SQL, R, Scala",Bachelor,5,Consulting,2025-04-09,2025-04-29,692,7.4,Autonomous Tech -AI03132,Principal Data Scientist,81776,USD,81776,MI,PT,South Korea,L,South Korea,0,"SQL, Java, Docker, Tableau, Computer Vision",PhD,2,Finance,2024-09-28,2024-12-08,1310,8.1,Advanced Robotics -AI03133,ML Ops Engineer,144619,GBP,108464,EX,CT,United Kingdom,S,United Kingdom,0,"MLOps, AWS, Kubernetes",PhD,12,Retail,2025-03-02,2025-05-02,1415,5.4,Digital Transformation LLC -AI03134,AI Specialist,79986,EUR,67988,MI,FL,Germany,S,Germany,50,"Hadoop, Python, MLOps, NLP",Associate,2,Automotive,2024-01-10,2024-03-17,772,6.7,Predictive Systems -AI03135,AI Architect,70655,USD,70655,EN,FT,United States,M,United States,50,"Mathematics, Linux, SQL, AWS, Tableau",Master,1,Healthcare,2024-07-30,2024-09-01,2024,5.8,Future Systems -AI03136,AI Specialist,250855,USD,250855,EX,PT,United States,S,United States,0,"Spark, Git, Data Visualization, MLOps",Master,15,Energy,2024-04-05,2024-05-01,1802,6.1,Advanced Robotics -AI03137,Machine Learning Engineer,91522,GBP,68642,MI,CT,United Kingdom,M,United Kingdom,100,"Tableau, Azure, PyTorch, SQL, Deep Learning",Bachelor,2,Technology,2024-03-27,2024-05-07,1299,7.3,Digital Transformation LLC -AI03138,Principal Data Scientist,124095,CAD,155119,SE,FL,Canada,S,Ghana,50,"SQL, Scala, GCP",Master,9,Media,2024-05-31,2024-06-28,932,8.3,Cloud AI Solutions -AI03139,Computer Vision Engineer,84282,CAD,105353,MI,FT,Canada,M,Indonesia,50,"Scala, Linux, Kubernetes, Python",PhD,2,Energy,2024-07-22,2024-09-15,1571,6.4,Digital Transformation LLC -AI03140,Data Scientist,163240,USD,163240,SE,FL,United States,M,Russia,50,"Scala, SQL, Azure",Master,5,Government,2024-09-23,2024-11-10,896,8.1,Quantum Computing Inc -AI03141,Machine Learning Researcher,168185,USD,168185,SE,CT,Ireland,L,Ireland,50,"Computer Vision, Git, Python, TensorFlow",Bachelor,7,Consulting,2024-11-08,2024-12-06,2288,7.5,DataVision Ltd -AI03142,Robotics Engineer,116627,USD,116627,MI,CT,United States,S,United States,0,"TensorFlow, NLP, Azure, Linux, Mathematics",Master,3,Education,2024-03-07,2024-05-03,1812,9.9,Machine Intelligence Group -AI03143,AI Product Manager,101270,USD,101270,MI,FT,United States,S,United States,50,"Python, Azure, Tableau",Associate,2,Healthcare,2024-01-03,2024-02-12,602,7,Digital Transformation LLC -AI03144,ML Ops Engineer,65343,USD,65343,EN,CT,Sweden,M,Sweden,100,"GCP, SQL, Tableau",Bachelor,1,Media,2025-03-06,2025-05-15,818,9.8,Predictive Systems -AI03145,Computer Vision Engineer,137416,USD,137416,SE,FT,South Korea,L,Colombia,50,"SQL, Python, MLOps",PhD,9,Telecommunications,2024-07-28,2024-09-22,1997,8.8,Machine Intelligence Group -AI03146,Robotics Engineer,295909,EUR,251523,EX,FL,Netherlands,L,Netherlands,100,"Spark, TensorFlow, Tableau, AWS, Python",Bachelor,10,Healthcare,2024-08-09,2024-08-23,1672,9.7,AI Innovations -AI03147,Autonomous Systems Engineer,143218,USD,143218,SE,FL,Ireland,M,Finland,0,"SQL, Scala, Spark, Azure",PhD,8,Technology,2024-02-15,2024-03-01,1730,9.3,Neural Networks Co -AI03148,Head of AI,190216,EUR,161684,EX,FL,Netherlands,L,Netherlands,0,"Python, MLOps, Kubernetes",Associate,18,Manufacturing,2024-04-10,2024-04-27,2389,5.4,Smart Analytics -AI03149,Data Analyst,151114,JPY,16622540,EX,FT,Japan,S,Japan,50,"Spark, Statistics, Docker, Linux, Hadoop",Master,18,Gaming,2025-04-06,2025-05-03,1213,5.7,Algorithmic Solutions -AI03150,Robotics Engineer,77870,USD,77870,EN,CT,Norway,L,Norway,50,"TensorFlow, PyTorch, AWS, Deep Learning",PhD,0,Automotive,2025-01-12,2025-03-11,2177,5.8,Smart Analytics -AI03151,Robotics Engineer,49183,JPY,5410130,EN,FL,Japan,S,Japan,50,"Tableau, Statistics, Python, NLP, Computer Vision",Master,0,Consulting,2025-02-13,2025-02-27,2439,8.5,DeepTech Ventures -AI03152,Autonomous Systems Engineer,62143,USD,62143,EN,PT,Israel,M,Ukraine,100,"Python, GCP, Deep Learning",Associate,1,Education,2025-01-24,2025-02-24,2048,5.3,Quantum Computing Inc -AI03153,AI Software Engineer,121259,AUD,163700,SE,CT,Australia,M,Belgium,0,"Statistics, Git, Deep Learning, Data Visualization, GCP",PhD,5,Real Estate,2025-02-01,2025-03-03,2113,8.3,Advanced Robotics -AI03154,AI Software Engineer,128628,JPY,14149080,SE,PT,Japan,M,Japan,50,"Statistics, Python, Kubernetes, Git, TensorFlow",Bachelor,9,Telecommunications,2024-12-01,2024-12-21,2034,7.3,Cloud AI Solutions -AI03155,Research Scientist,115473,CAD,144341,SE,CT,Canada,M,Ukraine,50,"Python, Kubernetes, Azure, Spark, TensorFlow",Associate,8,Government,2025-01-21,2025-02-25,1666,9.7,Quantum Computing Inc -AI03156,Data Engineer,238600,USD,238600,EX,FT,Israel,M,Israel,0,"PyTorch, NLP, Python, GCP",Master,11,Media,2024-01-26,2024-03-31,1708,9.6,Advanced Robotics -AI03157,AI Product Manager,113103,CHF,101793,EN,PT,Switzerland,L,Switzerland,0,"SQL, Linux, NLP, Azure, PyTorch",Bachelor,1,Real Estate,2025-01-21,2025-03-19,1928,6.4,Advanced Robotics -AI03158,Deep Learning Engineer,47429,USD,47429,SE,PT,India,S,India,50,"R, Git, SQL, Docker",Associate,7,Government,2024-04-28,2024-06-19,1964,6.3,Algorithmic Solutions -AI03159,AI Research Scientist,274181,USD,274181,EX,PT,Israel,L,Philippines,0,"Scala, AWS, SQL, MLOps",Associate,17,Technology,2025-02-18,2025-03-10,780,9.2,Neural Networks Co -AI03160,Principal Data Scientist,139553,CAD,174441,SE,FT,Canada,M,Canada,50,"Kubernetes, Java, Spark",Bachelor,6,Consulting,2024-12-13,2025-02-03,2398,8.9,Digital Transformation LLC -AI03161,AI Product Manager,83557,USD,83557,MI,CT,Finland,S,Singapore,100,"NLP, Kubernetes, Hadoop, R",PhD,3,Consulting,2024-08-25,2024-10-14,2148,5.2,Autonomous Tech -AI03162,AI Consultant,211357,AUD,285332,EX,CT,Australia,S,Turkey,0,"Scala, Git, Spark, Python",Master,15,Transportation,2024-12-16,2025-02-09,2101,8.2,Digital Transformation LLC -AI03163,ML Ops Engineer,181722,CHF,163550,SE,PT,Switzerland,M,Switzerland,100,"Azure, R, GCP",PhD,8,Real Estate,2024-02-11,2024-04-04,1248,7.2,Machine Intelligence Group -AI03164,Computer Vision Engineer,137403,CAD,171754,SE,CT,Canada,M,Indonesia,0,"TensorFlow, Mathematics, Computer Vision, Python, GCP",Bachelor,8,Finance,2024-03-17,2024-04-07,2482,5.8,Quantum Computing Inc -AI03165,Principal Data Scientist,65926,SGD,85704,EN,CT,Singapore,S,Singapore,0,"Python, MLOps, GCP, Mathematics",Master,1,Transportation,2024-10-08,2024-12-03,666,7.8,DeepTech Ventures -AI03166,Head of AI,63867,USD,63867,EN,CT,Sweden,L,Italy,100,"MLOps, Tableau, GCP, PyTorch, TensorFlow",PhD,0,Real Estate,2025-04-01,2025-05-22,1004,9.7,Advanced Robotics -AI03167,Deep Learning Engineer,73754,EUR,62691,EN,CT,Germany,L,Germany,0,"Linux, R, Data Visualization",Associate,0,Real Estate,2024-07-26,2024-08-17,1181,7.4,Predictive Systems -AI03168,Data Analyst,100588,GBP,75441,MI,CT,United Kingdom,S,United Kingdom,0,"Git, AWS, SQL",Master,4,Government,2024-02-23,2024-03-08,722,9.7,AI Innovations -AI03169,Robotics Engineer,215335,USD,215335,EX,PT,Ireland,S,Ireland,100,"NLP, SQL, Tableau",Bachelor,19,Technology,2025-03-17,2025-04-07,1676,7.2,Quantum Computing Inc -AI03170,AI Architect,96892,GBP,72669,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Linux, PyTorch",PhD,1,Real Estate,2024-07-02,2024-09-03,680,7.3,Neural Networks Co -AI03171,Head of AI,203281,USD,203281,SE,CT,Norway,L,Norway,0,"SQL, Docker, Azure",PhD,9,Technology,2024-07-24,2024-09-30,875,8.7,Cloud AI Solutions -AI03172,Deep Learning Engineer,128930,CHF,116037,MI,PT,Switzerland,M,Switzerland,0,"SQL, PyTorch, GCP, Tableau, Deep Learning",Associate,3,Consulting,2024-12-20,2025-02-21,1288,5,Machine Intelligence Group -AI03173,AI Architect,59295,CAD,74119,EN,FL,Canada,S,Canada,50,"MLOps, Linux, SQL, Statistics",Bachelor,0,Consulting,2024-03-22,2024-04-20,1581,5.1,Algorithmic Solutions -AI03174,AI Architect,149462,CAD,186828,EX,CT,Canada,S,Canada,100,"Spark, Computer Vision, R, SQL",PhD,13,Real Estate,2024-05-28,2024-06-30,1196,7.9,Digital Transformation LLC -AI03175,Data Analyst,134389,USD,134389,EX,FL,South Korea,S,South Korea,50,"Python, Java, MLOps, GCP, Deep Learning",PhD,12,Manufacturing,2025-04-30,2025-05-26,2156,8,Quantum Computing Inc -AI03176,Deep Learning Engineer,77125,USD,77125,EN,FT,Sweden,L,Sweden,50,"Azure, SQL, Linux, Data Visualization, Git",Master,1,Telecommunications,2024-10-22,2024-12-11,2144,8.6,Machine Intelligence Group -AI03177,Autonomous Systems Engineer,177796,GBP,133347,EX,PT,United Kingdom,L,United Kingdom,0,"SQL, Tableau, GCP, AWS",Bachelor,12,Real Estate,2024-09-18,2024-10-03,1210,8.5,Algorithmic Solutions -AI03178,Robotics Engineer,146724,USD,146724,SE,CT,Denmark,M,Denmark,100,"Data Visualization, Python, MLOps, Kubernetes",Bachelor,5,Media,2024-09-01,2024-10-05,628,9.4,DeepTech Ventures -AI03179,Data Engineer,170330,USD,170330,SE,CT,Norway,M,Norway,100,"Git, Statistics, Spark, Python, MLOps",Master,6,Manufacturing,2024-05-06,2024-05-29,2072,7.8,Quantum Computing Inc -AI03180,Computer Vision Engineer,79412,USD,79412,MI,CT,South Korea,S,Finland,100,"NLP, Docker, SQL, Python",Master,3,Energy,2024-09-13,2024-10-22,1679,9.2,Future Systems -AI03181,AI Specialist,124306,EUR,105660,SE,FL,Netherlands,L,Netherlands,100,"Python, Azure, GCP, Mathematics, R",Associate,7,Finance,2024-11-02,2024-12-23,1981,6.4,TechCorp Inc -AI03182,Head of AI,119037,EUR,101181,SE,FT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, Tableau, Python, TensorFlow",Bachelor,7,Technology,2024-12-24,2025-01-16,1560,9.9,Algorithmic Solutions -AI03183,NLP Engineer,222977,EUR,189530,EX,FL,Germany,L,Germany,0,"NLP, Computer Vision, Data Visualization, Docker, SQL",PhD,13,Finance,2025-02-21,2025-03-24,869,9,Machine Intelligence Group -AI03184,Data Engineer,136646,CAD,170808,SE,PT,Canada,M,Canada,100,"Python, Docker, Hadoop, Deep Learning",PhD,9,Telecommunications,2024-05-03,2024-06-06,1317,8.4,Algorithmic Solutions -AI03185,AI Specialist,192004,JPY,21120440,EX,FT,Japan,L,France,0,"Kubernetes, AWS, PyTorch",Master,11,Real Estate,2024-05-25,2024-08-03,2244,6.5,Future Systems -AI03186,Research Scientist,270814,GBP,203111,EX,PT,United Kingdom,L,Sweden,0,"Spark, Deep Learning, Azure, Java, Tableau",Bachelor,17,Gaming,2024-05-18,2024-07-25,1890,6.6,Neural Networks Co -AI03187,AI Consultant,125599,USD,125599,SE,FL,Sweden,M,Sweden,0,"Computer Vision, Java, Data Visualization",Associate,8,Technology,2024-03-07,2024-04-17,723,7.7,TechCorp Inc -AI03188,Machine Learning Engineer,102825,USD,102825,MI,PT,Finland,L,United Kingdom,100,"Docker, Tableau, Hadoop, Computer Vision",Associate,3,Technology,2024-02-16,2024-04-02,1608,7.2,Cloud AI Solutions -AI03189,AI Research Scientist,233678,JPY,25704580,EX,FT,Japan,L,Malaysia,100,"MLOps, Azure, Tableau, NLP, PyTorch",Associate,15,Consulting,2024-08-04,2024-09-30,1310,6.8,Predictive Systems -AI03190,AI Consultant,92649,EUR,78752,MI,PT,Netherlands,M,Czech Republic,100,"Spark, Tableau, MLOps",Associate,4,Energy,2024-09-04,2024-09-23,644,9.9,Advanced Robotics -AI03191,AI Research Scientist,102702,EUR,87297,MI,CT,Germany,M,Germany,0,"GCP, Docker, Scala, Python",PhD,4,Automotive,2025-03-05,2025-04-18,765,7,Machine Intelligence Group -AI03192,Autonomous Systems Engineer,220138,SGD,286179,EX,PT,Singapore,S,Singapore,0,"Java, Linux, Scala, Kubernetes",Associate,10,Finance,2024-12-10,2025-01-28,1094,5.1,Machine Intelligence Group -AI03193,NLP Engineer,102269,SGD,132950,MI,PT,Singapore,L,Singapore,50,"SQL, Python, Deep Learning, Linux",Bachelor,3,Energy,2024-08-19,2024-10-31,1527,10,Cognitive Computing -AI03194,AI Software Engineer,164789,USD,164789,EX,FL,Denmark,S,Denmark,100,"Linux, Scala, Docker",Master,15,Retail,2024-02-22,2024-04-09,2219,9.6,DeepTech Ventures -AI03195,AI Software Engineer,37291,USD,37291,MI,FT,India,L,India,50,"PyTorch, TensorFlow, Docker, Hadoop, Linux",Associate,2,Consulting,2024-12-19,2025-01-27,2137,8.6,AI Innovations -AI03196,NLP Engineer,112266,USD,112266,MI,FT,United States,M,United States,50,"Azure, Kubernetes, AWS",Associate,3,Transportation,2025-03-18,2025-05-22,2235,5.7,Cloud AI Solutions -AI03197,NLP Engineer,67601,USD,67601,EN,FL,South Korea,L,Canada,0,"NLP, GCP, Scala",Associate,0,Finance,2024-01-26,2024-03-27,2022,5.7,Cognitive Computing -AI03198,AI Software Engineer,265839,CAD,332299,EX,CT,Canada,L,Canada,0,"Tableau, SQL, Hadoop, Computer Vision, PyTorch",Master,16,Technology,2024-07-12,2024-08-17,1079,9.9,Cloud AI Solutions -AI03199,Autonomous Systems Engineer,127393,CAD,159241,SE,FT,Canada,S,Canada,50,"SQL, Tableau, Docker, PyTorch",PhD,6,Finance,2025-03-02,2025-04-06,961,9.6,Digital Transformation LLC -AI03200,Machine Learning Engineer,79956,USD,79956,MI,FL,Israel,M,Israel,50,"SQL, Scala, Hadoop, Computer Vision, Python",Associate,3,Automotive,2024-05-05,2024-07-16,1366,7,AI Innovations -AI03201,AI Product Manager,64844,USD,64844,EN,PT,Finland,M,Finland,100,"MLOps, Linux, TensorFlow",Associate,0,Manufacturing,2025-03-11,2025-04-05,642,6.3,AI Innovations -AI03202,Data Analyst,255126,GBP,191345,EX,PT,United Kingdom,L,Netherlands,50,"Docker, MLOps, Data Visualization",Master,17,Technology,2024-02-26,2024-03-11,1055,5.4,Cognitive Computing -AI03203,Data Analyst,55235,USD,55235,EN,FL,Sweden,M,Sweden,100,"Scala, Kubernetes, NLP, Azure",Associate,0,Gaming,2025-01-19,2025-03-16,2002,6.9,Cognitive Computing -AI03204,AI Product Manager,179903,EUR,152918,SE,FT,Netherlands,L,Netherlands,0,"Linux, Scala, Java, Docker",Master,7,Media,2024-01-24,2024-03-30,759,6.3,Machine Intelligence Group -AI03205,Deep Learning Engineer,99326,USD,99326,MI,FT,Finland,L,Finland,100,"Tableau, R, Linux, Git, Java",PhD,2,Transportation,2024-11-09,2024-12-01,713,7.9,Algorithmic Solutions -AI03206,NLP Engineer,36397,USD,36397,MI,PT,China,S,China,100,"NLP, Tableau, Docker, MLOps, Data Visualization",Master,4,Gaming,2025-03-20,2025-05-18,863,9.6,Advanced Robotics -AI03207,Head of AI,55499,USD,55499,SE,FT,China,L,China,50,"Spark, R, Hadoop, Kubernetes",PhD,6,Consulting,2024-03-15,2024-04-29,2352,9.4,Future Systems -AI03208,Data Analyst,32595,USD,32595,MI,FT,India,M,Kenya,100,"Python, MLOps, Data Visualization, AWS",Master,3,Government,2024-09-08,2024-10-05,1738,6.4,Advanced Robotics -AI03209,AI Software Engineer,257447,USD,257447,EX,PT,United States,S,United States,0,"Python, PyTorch, TensorFlow, R",Master,19,Consulting,2024-04-07,2024-06-05,2080,6.7,Predictive Systems -AI03210,Research Scientist,92838,EUR,78912,MI,CT,Austria,M,Austria,0,"PyTorch, Azure, MLOps, GCP",Bachelor,2,Real Estate,2024-04-24,2024-05-10,957,7.2,Cloud AI Solutions -AI03211,ML Ops Engineer,90741,EUR,77130,MI,FT,Austria,S,Austria,0,"Tableau, NLP, GCP, Java",PhD,4,Retail,2024-05-05,2024-06-27,2471,7.1,Cloud AI Solutions -AI03212,Computer Vision Engineer,76319,USD,76319,SE,FL,South Korea,S,South Korea,0,"TensorFlow, Python, Docker, Java",Master,6,Media,2024-03-20,2024-05-24,839,6.4,Autonomous Tech -AI03213,AI Specialist,210418,EUR,178855,EX,FT,Austria,L,Austria,100,"Java, Azure, MLOps",Master,11,Government,2024-11-12,2024-12-14,1743,8.4,DataVision Ltd -AI03214,AI Software Engineer,196045,EUR,166638,EX,FL,Germany,M,Romania,0,"Docker, Python, Kubernetes",PhD,10,Education,2024-11-02,2024-11-23,512,5.2,Neural Networks Co -AI03215,Deep Learning Engineer,135969,CHF,122372,SE,FT,Switzerland,S,Belgium,100,"R, Kubernetes, Docker",PhD,8,Technology,2024-09-18,2024-10-09,1530,5.3,Future Systems -AI03216,Head of AI,48643,EUR,41347,EN,FT,Netherlands,S,Netherlands,100,"NLP, Scala, R, Tableau, Python",Bachelor,1,Retail,2024-03-11,2024-04-04,2102,7.5,DeepTech Ventures -AI03217,AI Architect,78066,USD,78066,EN,PT,Finland,L,Egypt,0,"Python, Data Visualization, Kubernetes",Bachelor,0,Real Estate,2025-03-24,2025-05-26,2098,7.9,TechCorp Inc -AI03218,Machine Learning Researcher,41677,USD,41677,EN,CT,South Korea,S,South Korea,100,"MLOps, R, Kubernetes, Deep Learning",Associate,0,Energy,2024-07-09,2024-09-15,1351,6.1,Autonomous Tech -AI03219,Deep Learning Engineer,93162,JPY,10247820,EN,FT,Japan,L,Japan,100,"Python, Deep Learning, Java",Master,0,Manufacturing,2024-09-06,2024-11-10,1406,9.7,Cognitive Computing -AI03220,Research Scientist,64788,EUR,55070,EN,PT,Germany,S,Hungary,50,"PyTorch, Statistics, Spark, SQL, GCP",Associate,0,Media,2024-11-18,2025-01-28,1017,6,Neural Networks Co -AI03221,AI Architect,154205,USD,154205,EX,CT,Ireland,S,Ireland,50,"Azure, AWS, GCP, Spark",Bachelor,19,Media,2024-10-15,2024-10-31,1369,7.8,Algorithmic Solutions -AI03222,Principal Data Scientist,143701,USD,143701,SE,CT,Israel,M,Israel,100,"Tableau, SQL, Scala, Azure",Associate,8,Media,2025-04-04,2025-06-14,557,6.2,DataVision Ltd -AI03223,Data Scientist,164876,CHF,148388,SE,PT,Switzerland,S,Switzerland,0,"Kubernetes, AWS, Scala, GCP",Bachelor,9,Government,2025-01-01,2025-01-16,1603,6.2,Neural Networks Co -AI03224,Autonomous Systems Engineer,35464,USD,35464,EN,FT,China,M,China,0,"Mathematics, Docker, Azure",PhD,1,Education,2024-02-03,2024-02-28,736,9.4,DeepTech Ventures -AI03225,AI Specialist,59626,USD,59626,EN,FL,Ireland,M,Ireland,0,"Linux, Java, Scala",Bachelor,1,Gaming,2025-03-15,2025-04-18,624,5.5,TechCorp Inc -AI03226,AI Specialist,307432,USD,307432,EX,FL,Norway,M,Norway,100,"Linux, Python, NLP",PhD,11,Manufacturing,2025-01-31,2025-03-30,2437,9.6,Digital Transformation LLC -AI03227,AI Architect,176090,USD,176090,SE,FL,Norway,S,Luxembourg,100,"Hadoop, AWS, Spark",Associate,6,Technology,2025-02-27,2025-04-07,2082,9.2,AI Innovations -AI03228,AI Architect,66682,USD,66682,EN,FL,United States,S,United States,0,"Scala, Java, NLP, R",Associate,0,Finance,2024-08-19,2024-09-24,1664,9.8,Digital Transformation LLC -AI03229,Data Analyst,39616,USD,39616,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Scala, Tableau, R, Python",PhD,0,Real Estate,2024-06-13,2024-07-30,550,8,DeepTech Ventures -AI03230,AI Product Manager,122403,CHF,110163,EN,PT,Switzerland,L,Singapore,100,"TensorFlow, Kubernetes, NLP",Associate,0,Finance,2024-01-23,2024-03-02,2351,8.2,Cognitive Computing -AI03231,Deep Learning Engineer,130431,USD,130431,SE,FT,Finland,M,Finland,100,"Linux, R, NLP",PhD,8,Government,2024-08-26,2024-11-07,1081,6.4,Smart Analytics -AI03232,AI Software Engineer,91342,EUR,77641,MI,PT,Germany,S,Germany,100,"Hadoop, SQL, Docker",Bachelor,4,Healthcare,2024-02-05,2024-04-15,524,6.7,TechCorp Inc -AI03233,AI Product Manager,34743,USD,34743,EN,FL,China,M,China,100,"R, Hadoop, PyTorch",Master,0,Real Estate,2024-03-08,2024-05-01,1698,7.9,Future Systems -AI03234,Computer Vision Engineer,75941,EUR,64550,MI,FT,France,S,France,100,"Statistics, R, Python, GCP",Master,3,Telecommunications,2024-06-30,2024-08-12,1131,6.5,Machine Intelligence Group -AI03235,AI Product Manager,53406,USD,53406,EN,CT,South Korea,M,South Korea,100,"NLP, Kubernetes, Python",Associate,0,Manufacturing,2025-03-01,2025-05-12,2231,9.6,Neural Networks Co -AI03236,Autonomous Systems Engineer,280999,CHF,252899,EX,FT,Switzerland,M,Switzerland,100,"Linux, Kubernetes, GCP, Python",Associate,18,Gaming,2024-06-11,2024-08-17,1120,9.3,Predictive Systems -AI03237,Computer Vision Engineer,211482,SGD,274927,EX,PT,Singapore,L,Singapore,50,"Scala, Statistics, Python",Bachelor,17,Education,2024-09-26,2024-11-06,1183,8,DeepTech Ventures -AI03238,AI Architect,188072,CHF,169265,EX,CT,Switzerland,S,Switzerland,100,"SQL, Kubernetes, Azure",Associate,11,Automotive,2025-02-15,2025-03-15,1142,5.9,Predictive Systems -AI03239,NLP Engineer,89391,EUR,75982,MI,FL,Germany,M,Germany,0,"SQL, Hadoop, Java",Bachelor,2,Consulting,2025-04-15,2025-04-29,2251,6.3,DeepTech Ventures -AI03240,Machine Learning Researcher,172617,CHF,155355,SE,FL,Switzerland,L,Switzerland,0,"Data Visualization, NLP, Azure",Associate,7,Real Estate,2024-11-08,2024-12-19,1254,6.3,Digital Transformation LLC -AI03241,Head of AI,247125,SGD,321263,EX,FT,Singapore,L,Singapore,100,"TensorFlow, Git, Java, Azure, NLP",PhD,18,Energy,2025-03-23,2025-04-11,616,6.1,Advanced Robotics -AI03242,AI Architect,58586,EUR,49798,EN,CT,Austria,L,Austria,0,"Python, AWS, Kubernetes, Scala, Statistics",PhD,0,Government,2025-02-10,2025-03-02,1313,8.6,Quantum Computing Inc -AI03243,AI Consultant,66857,USD,66857,EN,FT,United States,M,France,100,"GCP, Scala, Mathematics",Associate,0,Manufacturing,2024-04-16,2024-05-05,1143,8.9,DeepTech Ventures -AI03244,Machine Learning Engineer,61082,USD,61082,EN,FT,Ireland,S,Ireland,0,"MLOps, Data Visualization, PyTorch, Kubernetes, Python",PhD,1,Government,2024-10-19,2024-12-13,1334,6.9,DataVision Ltd -AI03245,Principal Data Scientist,109973,SGD,142965,MI,FL,Singapore,M,Singapore,100,"Kubernetes, MLOps, Spark, R, SQL",Associate,4,Real Estate,2024-03-04,2024-03-29,1826,9.1,Machine Intelligence Group -AI03246,Machine Learning Engineer,96154,GBP,72116,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, Data Visualization, Scala, Tableau",PhD,3,Telecommunications,2024-10-28,2024-12-15,1199,8.5,Smart Analytics -AI03247,Data Engineer,80737,EUR,68626,MI,CT,France,L,France,50,"Java, Python, Docker",PhD,3,Manufacturing,2024-08-25,2024-09-15,1683,7.5,Quantum Computing Inc -AI03248,Data Analyst,60211,USD,60211,EN,PT,Israel,S,Israel,50,"NLP, Deep Learning, PyTorch, Mathematics, Scala",PhD,0,Technology,2025-01-16,2025-03-09,1572,5.4,DataVision Ltd -AI03249,AI Research Scientist,77885,EUR,66202,MI,PT,Austria,M,Austria,50,"Docker, Azure, Kubernetes",Associate,2,Gaming,2024-09-16,2024-10-07,1002,8.5,Algorithmic Solutions -AI03250,Machine Learning Engineer,91640,CAD,114550,MI,PT,Canada,S,China,50,"PyTorch, TensorFlow, Java, MLOps, AWS",Bachelor,4,Education,2025-03-02,2025-04-13,2355,6.5,Digital Transformation LLC -AI03251,Principal Data Scientist,136201,CAD,170251,EX,FT,Canada,S,Canada,100,"Kubernetes, Java, MLOps",Associate,11,Healthcare,2024-09-24,2024-11-22,1786,9.9,Smart Analytics -AI03252,Machine Learning Researcher,100307,SGD,130399,SE,PT,Singapore,S,Singapore,100,"R, SQL, Statistics, PyTorch",Associate,8,Government,2024-04-16,2024-05-10,844,7.7,Cloud AI Solutions -AI03253,AI Specialist,71821,CAD,89776,EN,FT,Canada,L,Canada,0,"Azure, R, NLP, Hadoop, Git",Bachelor,0,Manufacturing,2024-08-27,2024-09-24,1281,7.9,Future Systems -AI03254,AI Software Engineer,92325,USD,92325,MI,CT,Finland,L,Finland,100,"TensorFlow, Python, Java, Linux",Bachelor,2,Telecommunications,2024-07-26,2024-08-28,1168,8.5,Digital Transformation LLC -AI03255,Machine Learning Researcher,128402,EUR,109142,SE,PT,Germany,S,Germany,0,"Spark, SQL, Azure, GCP, Deep Learning",PhD,5,Government,2025-01-18,2025-03-10,2118,6.3,Quantum Computing Inc -AI03256,Data Analyst,49741,USD,49741,EX,CT,India,M,India,0,"Docker, MLOps, Spark",Associate,12,Real Estate,2024-02-11,2024-04-19,1653,8.1,TechCorp Inc -AI03257,AI Software Engineer,189605,CHF,170645,SE,FT,Switzerland,S,Switzerland,0,"TensorFlow, Python, Tableau, Deep Learning",PhD,5,Real Estate,2025-02-06,2025-03-22,1625,6,Cognitive Computing -AI03258,Machine Learning Engineer,91412,SGD,118836,EN,FL,Singapore,L,United States,100,"Deep Learning, SQL, Hadoop",Associate,1,Education,2025-01-25,2025-03-19,966,7.7,Machine Intelligence Group -AI03259,Robotics Engineer,214536,USD,214536,SE,CT,Denmark,L,Poland,50,"SQL, Java, Statistics, Computer Vision, Deep Learning",PhD,8,Healthcare,2024-08-26,2024-10-23,1367,9.8,AI Innovations -AI03260,Machine Learning Researcher,93353,USD,93353,MI,PT,Norway,S,Norway,0,"Computer Vision, SQL, NLP, PyTorch, AWS",Associate,3,Education,2024-06-30,2024-07-30,2332,5.1,Autonomous Tech -AI03261,AI Architect,119157,USD,119157,SE,CT,Finland,L,Finland,100,"Kubernetes, PyTorch, GCP, Azure",Bachelor,7,Government,2024-01-07,2024-01-24,783,5.4,Advanced Robotics -AI03262,AI Specialist,262609,CHF,236348,EX,CT,Switzerland,L,Switzerland,50,"Hadoop, TensorFlow, PyTorch, Azure",Bachelor,16,Education,2024-05-11,2024-07-22,2100,5.6,Cloud AI Solutions -AI03263,AI Product Manager,69585,AUD,93940,EN,PT,Australia,S,Australia,100,"Computer Vision, Mathematics, Azure, R",PhD,0,Real Estate,2024-12-23,2025-01-20,1195,9.8,Machine Intelligence Group -AI03264,AI Product Manager,74761,AUD,100927,EN,PT,Australia,M,Australia,50,"MLOps, GCP, Docker, Python",Bachelor,0,Government,2024-12-07,2025-01-15,1022,6.9,AI Innovations -AI03265,ML Ops Engineer,162450,CHF,146205,SE,PT,Switzerland,M,Switzerland,0,"Spark, Git, Mathematics, Kubernetes, Python",Associate,7,Automotive,2024-07-06,2024-08-05,2224,6.5,Machine Intelligence Group -AI03266,Data Scientist,88851,USD,88851,EN,FL,Norway,S,Norway,100,"Data Visualization, Linux, Hadoop, Tableau",Bachelor,1,Retail,2025-03-30,2025-04-27,776,9.7,Quantum Computing Inc -AI03267,Autonomous Systems Engineer,91547,EUR,77815,EN,CT,Netherlands,L,Denmark,100,"PyTorch, Scala, Spark, SQL",Master,0,Finance,2025-02-22,2025-03-14,1399,6.3,DeepTech Ventures -AI03268,Principal Data Scientist,58081,EUR,49369,EN,FT,Germany,M,Germany,50,"TensorFlow, Kubernetes, Python, R",PhD,0,Technology,2024-12-27,2025-01-16,1995,8.1,Cloud AI Solutions -AI03269,Computer Vision Engineer,103246,EUR,87759,SE,PT,Austria,S,Austria,50,"Docker, Scala, GCP, AWS",Associate,5,Finance,2024-06-29,2024-08-28,1275,5,Quantum Computing Inc -AI03270,AI Research Scientist,32356,USD,32356,EN,CT,China,S,Estonia,100,"MLOps, R, Hadoop, SQL",PhD,0,Government,2025-01-11,2025-02-08,804,5.2,DeepTech Ventures -AI03271,AI Product Manager,48264,USD,48264,SE,FL,China,S,Hungary,0,"MLOps, PyTorch, Tableau, Data Visualization",Associate,7,Education,2024-08-02,2024-09-27,602,7.5,Neural Networks Co -AI03272,Research Scientist,66275,JPY,7290250,EN,PT,Japan,S,Japan,50,"Python, Tableau, SQL, MLOps",Master,1,Manufacturing,2024-10-01,2024-10-28,1057,7.8,Cloud AI Solutions -AI03273,Machine Learning Researcher,177406,JPY,19514660,EX,FT,Japan,L,Mexico,50,"Hadoop, Spark, Kubernetes",Master,14,Consulting,2024-09-12,2024-10-22,1985,8.4,Algorithmic Solutions -AI03274,Deep Learning Engineer,68779,USD,68779,EN,PT,United States,M,Poland,50,"Python, Git, NLP, Mathematics",PhD,0,Automotive,2024-05-24,2024-06-13,1842,9.1,Predictive Systems -AI03275,Robotics Engineer,93037,EUR,79081,MI,CT,France,M,France,0,"Git, Azure, Computer Vision, Python",PhD,2,Finance,2025-02-20,2025-03-23,1043,5.9,Cognitive Computing -AI03276,AI Product Manager,90694,CAD,113368,SE,CT,Canada,S,Canada,50,"R, Hadoop, Computer Vision, TensorFlow",Associate,8,Manufacturing,2024-12-30,2025-03-09,951,6.9,Quantum Computing Inc -AI03277,Autonomous Systems Engineer,197861,USD,197861,EX,FL,Israel,L,Malaysia,50,"Hadoop, MLOps, TensorFlow",Associate,17,Manufacturing,2025-03-25,2025-05-28,2052,7.2,DataVision Ltd -AI03278,AI Research Scientist,68932,USD,68932,MI,PT,South Korea,M,Chile,0,"Azure, Python, Linux",Master,2,Finance,2024-09-10,2024-10-02,2382,9.7,Quantum Computing Inc -AI03279,AI Software Engineer,83285,EUR,70792,MI,CT,France,M,France,100,"Data Visualization, SQL, R, NLP",Master,2,Media,2024-11-07,2024-12-02,886,9.7,Neural Networks Co -AI03280,NLP Engineer,161470,USD,161470,SE,CT,Israel,L,Israel,0,"Data Visualization, Kubernetes, Computer Vision",PhD,6,Retail,2025-01-18,2025-02-27,1896,9.2,Autonomous Tech -AI03281,NLP Engineer,101298,USD,101298,EN,FT,Norway,M,Norway,50,"NLP, GCP, Scala",Master,1,Technology,2024-12-27,2025-02-18,1133,9.3,Machine Intelligence Group -AI03282,AI Software Engineer,98441,USD,98441,MI,PT,United States,M,United States,0,"Mathematics, Java, Scala, Docker",PhD,2,Finance,2024-03-04,2024-05-15,1689,8.7,Digital Transformation LLC -AI03283,Principal Data Scientist,142540,USD,142540,SE,FT,South Korea,L,Czech Republic,0,"R, PyTorch, Linux, Mathematics",Master,6,Telecommunications,2024-07-19,2024-09-29,1555,8.7,Autonomous Tech -AI03284,Machine Learning Researcher,141976,USD,141976,SE,FT,Israel,M,Indonesia,50,"Git, Kubernetes, PyTorch",PhD,9,Telecommunications,2024-09-14,2024-10-29,2038,9.2,DeepTech Ventures -AI03285,Robotics Engineer,56123,USD,56123,EN,PT,Finland,M,Finland,50,"GCP, Python, AWS",Master,1,Manufacturing,2024-02-15,2024-04-28,503,5.1,Algorithmic Solutions -AI03286,NLP Engineer,93288,EUR,79295,MI,PT,Germany,L,Germany,0,"Statistics, Scala, Mathematics, Kubernetes",Bachelor,4,Gaming,2024-07-22,2024-08-28,2014,7.3,Machine Intelligence Group -AI03287,AI Consultant,111008,USD,111008,MI,FT,United States,S,United States,100,"Azure, R, Mathematics, NLP",Master,4,Consulting,2024-10-27,2024-12-20,2364,8.4,Smart Analytics -AI03288,NLP Engineer,188040,SGD,244452,EX,FT,Singapore,S,Singapore,0,"Scala, Git, SQL, Java, Mathematics",Associate,11,Transportation,2024-06-25,2024-08-12,2155,7.7,DataVision Ltd -AI03289,Computer Vision Engineer,37867,USD,37867,MI,PT,China,S,China,0,"Git, Statistics, Scala",PhD,4,Real Estate,2024-01-08,2024-02-04,2351,8.9,Predictive Systems -AI03290,AI Research Scientist,130573,USD,130573,EX,PT,Israel,S,India,100,"SQL, AWS, Python",Master,18,Finance,2024-02-02,2024-03-05,1006,5.4,Advanced Robotics -AI03291,AI Product Manager,84549,EUR,71867,EN,FL,Austria,L,Austria,50,"Linux, Mathematics, MLOps, Java, PyTorch",PhD,0,Transportation,2024-03-08,2024-04-22,1947,9.8,DataVision Ltd -AI03292,AI Specialist,115767,USD,115767,EN,PT,Denmark,L,Denmark,50,"PyTorch, Python, Linux, Mathematics",PhD,1,Gaming,2025-01-23,2025-03-25,2233,5.3,Autonomous Tech -AI03293,AI Consultant,229034,CHF,206131,SE,FL,Switzerland,L,Malaysia,50,"R, Statistics, Data Visualization, Deep Learning",PhD,5,Gaming,2024-02-08,2024-04-08,1422,9.4,DeepTech Ventures -AI03294,AI Research Scientist,128520,SGD,167076,SE,PT,Singapore,S,Singapore,0,"Scala, TensorFlow, Kubernetes, Docker, Mathematics",Master,6,Media,2024-12-27,2025-01-23,1971,6.5,AI Innovations -AI03295,Data Analyst,73935,EUR,62845,EN,FT,Netherlands,S,Netherlands,100,"Spark, PyTorch, Java, GCP",Associate,0,Government,2024-03-18,2024-04-10,806,8.6,Machine Intelligence Group -AI03296,AI Product Manager,113864,USD,113864,SE,FT,Ireland,S,Kenya,50,"R, Hadoop, SQL, Data Visualization",Master,6,Finance,2025-04-21,2025-06-25,859,5.3,Predictive Systems -AI03297,Computer Vision Engineer,98526,SGD,128084,SE,PT,Singapore,S,Singapore,50,"Azure, PyTorch, NLP",Associate,7,Manufacturing,2024-06-20,2024-08-21,974,8,Autonomous Tech -AI03298,Deep Learning Engineer,66726,USD,66726,EN,PT,Finland,M,Finland,100,"Docker, Computer Vision, Python, Spark",Bachelor,0,Real Estate,2024-06-17,2024-07-10,1308,7.8,Cloud AI Solutions -AI03299,Data Analyst,88638,AUD,119661,EN,CT,Australia,L,Sweden,100,"Mathematics, Deep Learning, Python, Java, TensorFlow",Master,1,Healthcare,2025-03-29,2025-06-03,835,7.6,DataVision Ltd -AI03300,Autonomous Systems Engineer,93012,USD,93012,MI,PT,United States,S,United States,50,"Kubernetes, Deep Learning, Git",PhD,3,Finance,2024-12-07,2024-12-21,1664,9.8,Cloud AI Solutions -AI03301,Computer Vision Engineer,78878,USD,78878,EN,FL,Denmark,L,Canada,50,"Scala, GCP, MLOps, Linux, Spark",Associate,0,Consulting,2025-01-17,2025-03-27,1459,9.1,Advanced Robotics -AI03302,NLP Engineer,82710,JPY,9098100,EN,FT,Japan,M,Japan,0,"Linux, Computer Vision, Tableau, NLP",Master,0,Gaming,2024-06-03,2024-07-20,1488,6.3,DeepTech Ventures -AI03303,Machine Learning Engineer,29961,USD,29961,EN,FT,China,S,Canada,100,"Data Visualization, Python, Kubernetes",Bachelor,1,Real Estate,2025-01-20,2025-02-15,1613,6.1,Future Systems -AI03304,NLP Engineer,273589,USD,273589,EX,FL,Denmark,M,Denmark,100,"R, Spark, GCP, Azure",PhD,11,Real Estate,2025-02-21,2025-04-11,763,7.4,Cognitive Computing -AI03305,AI Consultant,73518,JPY,8086980,EN,FL,Japan,M,Japan,0,"Data Visualization, NLP, AWS, Spark, Computer Vision",PhD,1,Real Estate,2024-11-14,2024-11-30,1298,7.4,AI Innovations -AI03306,Autonomous Systems Engineer,62379,JPY,6861690,EN,FT,Japan,L,Japan,50,"Deep Learning, Python, TensorFlow",Bachelor,1,Retail,2024-02-21,2024-03-26,1088,6,Autonomous Tech -AI03307,Data Analyst,73138,USD,73138,EX,CT,India,L,India,100,"PyTorch, GCP, MLOps, R, Deep Learning",Master,19,Real Estate,2024-01-14,2024-02-28,1574,9.4,Cloud AI Solutions -AI03308,Data Engineer,308012,EUR,261810,EX,FT,Netherlands,L,Israel,0,"Statistics, Spark, SQL, PyTorch, GCP",PhD,19,Automotive,2024-10-26,2024-11-29,852,8.5,Predictive Systems -AI03309,Robotics Engineer,72475,USD,72475,EN,FT,Israel,M,Israel,0,"Linux, TensorFlow, Python, Scala",Master,1,Retail,2024-11-04,2025-01-04,2425,8.7,Autonomous Tech -AI03310,Research Scientist,71202,USD,71202,EN,CT,Norway,S,Norway,0,"Hadoop, MLOps, Git, Linux, NLP",Master,0,Automotive,2025-02-02,2025-02-23,2495,7.8,Predictive Systems -AI03311,AI Research Scientist,178194,EUR,151465,EX,FT,Netherlands,M,Netherlands,100,"Deep Learning, Git, R",Associate,15,Retail,2024-07-18,2024-08-21,2376,7.5,DeepTech Ventures -AI03312,AI Consultant,26837,USD,26837,EN,CT,India,M,India,0,"PyTorch, SQL, Scala",Bachelor,0,Healthcare,2024-01-27,2024-03-06,1504,7.4,Advanced Robotics -AI03313,Principal Data Scientist,97019,USD,97019,MI,FL,Finland,M,Estonia,50,"NLP, Spark, Scala, Git",Bachelor,4,Retail,2025-02-11,2025-04-25,1089,6.5,DataVision Ltd -AI03314,Robotics Engineer,118655,EUR,100857,SE,FT,France,L,Czech Republic,0,"Computer Vision, Tableau, Scala",Bachelor,7,Consulting,2025-02-23,2025-03-27,822,7.4,Machine Intelligence Group -AI03315,AI Specialist,84059,JPY,9246490,MI,FT,Japan,S,Japan,100,"SQL, Docker, Mathematics, GCP",PhD,2,Healthcare,2025-04-04,2025-06-06,2331,5.4,Quantum Computing Inc -AI03316,AI Consultant,205243,CAD,256554,EX,FL,Canada,M,Poland,50,"Java, Tableau, Statistics, Mathematics",Master,11,Education,2025-03-12,2025-05-18,1170,8.7,Digital Transformation LLC -AI03317,AI Research Scientist,65453,USD,65453,MI,PT,Israel,S,Romania,50,"Python, PyTorch, GCP, Java, Deep Learning",PhD,4,Transportation,2024-02-06,2024-03-25,818,8.8,Neural Networks Co -AI03318,Computer Vision Engineer,103929,USD,103929,SE,CT,South Korea,M,South Korea,0,"Data Visualization, Python, Linux, Mathematics",Bachelor,9,Transportation,2024-01-12,2024-01-27,996,6.4,Smart Analytics -AI03319,Head of AI,83770,JPY,9214700,MI,PT,Japan,M,Russia,0,"Kubernetes, NLP, PyTorch",Master,3,Telecommunications,2025-01-31,2025-03-12,1521,6.7,AI Innovations -AI03320,AI Software Engineer,71511,EUR,60784,EN,FL,Germany,M,Germany,50,"Mathematics, R, Java, Git, Linux",Bachelor,1,Government,2024-01-24,2024-04-05,2237,5.2,Smart Analytics -AI03321,Robotics Engineer,86602,USD,86602,MI,FT,Sweden,S,Egypt,100,"PyTorch, TensorFlow, Data Visualization",Master,4,Government,2024-06-10,2024-08-21,1231,6.9,TechCorp Inc -AI03322,AI Consultant,57477,SGD,74720,EN,CT,Singapore,S,Singapore,50,"Python, Hadoop, MLOps, Deep Learning",Master,1,Finance,2024-05-20,2024-06-21,665,6.8,Neural Networks Co -AI03323,Machine Learning Engineer,104741,JPY,11521510,MI,FT,Japan,M,Japan,50,"Docker, Python, Computer Vision, Scala",PhD,4,Technology,2024-08-10,2024-09-12,595,6.6,DataVision Ltd -AI03324,Computer Vision Engineer,257714,USD,257714,EX,FT,Denmark,S,Denmark,100,"Python, Docker, Spark, Azure, Linux",Master,12,Finance,2024-07-22,2024-08-20,1875,5.9,Advanced Robotics -AI03325,Data Engineer,67170,JPY,7388700,EN,FL,Japan,S,Japan,100,"Kubernetes, Scala, NLP, Deep Learning",Bachelor,0,Retail,2024-10-22,2024-12-21,2375,6.8,Advanced Robotics -AI03326,Machine Learning Engineer,145681,EUR,123829,SE,PT,Austria,L,Austria,0,"TensorFlow, Computer Vision, Data Visualization",Associate,5,Consulting,2024-01-20,2024-03-29,808,7.1,DeepTech Ventures -AI03327,AI Specialist,118285,EUR,100542,MI,PT,Austria,L,Ireland,50,"Statistics, Scala, Data Visualization, Spark, Java",Bachelor,2,Government,2025-04-14,2025-05-07,1534,5.3,Cognitive Computing -AI03328,Principal Data Scientist,151221,USD,151221,SE,FL,United States,M,United States,0,"PyTorch, Scala, Hadoop, GCP",Master,6,Technology,2024-07-18,2024-08-17,638,8.6,Machine Intelligence Group -AI03329,Robotics Engineer,97110,CHF,87399,EN,FT,Switzerland,L,Switzerland,50,"Python, GCP, Mathematics",PhD,0,Healthcare,2024-04-25,2024-07-04,825,8.7,Cloud AI Solutions -AI03330,Research Scientist,142010,USD,142010,SE,CT,Israel,L,Israel,0,"Spark, Mathematics, Data Visualization, PyTorch, MLOps",Associate,9,Technology,2024-06-01,2024-07-18,590,5.7,Cloud AI Solutions -AI03331,AI Product Manager,221988,EUR,188690,EX,FT,Netherlands,S,Philippines,100,"Kubernetes, Data Visualization, Git, SQL",Associate,13,Technology,2025-02-15,2025-03-07,2002,9.2,DataVision Ltd -AI03332,AI Consultant,171046,USD,171046,EX,CT,United States,S,United States,100,"PyTorch, AWS, MLOps, Docker",PhD,13,Government,2024-10-09,2024-11-06,1843,6.9,Cloud AI Solutions -AI03333,Research Scientist,71257,USD,71257,EN,FT,South Korea,L,Kenya,50,"Data Visualization, AWS, Tableau, SQL",PhD,0,Technology,2025-02-17,2025-03-07,2459,8.3,TechCorp Inc -AI03334,ML Ops Engineer,109428,USD,109428,SE,PT,Ireland,S,Ireland,0,"Scala, SQL, NLP, Mathematics",Bachelor,5,Healthcare,2024-12-13,2024-12-29,2367,6.1,Smart Analytics -AI03335,Autonomous Systems Engineer,221626,AUD,299195,EX,CT,Australia,M,Romania,100,"Kubernetes, GCP, Data Visualization",Bachelor,13,Healthcare,2024-10-18,2024-11-24,1179,7.6,Machine Intelligence Group -AI03336,Deep Learning Engineer,189458,GBP,142094,EX,CT,United Kingdom,S,Portugal,0,"PyTorch, Spark, SQL, Hadoop, Mathematics",Master,10,Energy,2024-04-14,2024-05-09,1518,5.1,Smart Analytics -AI03337,Principal Data Scientist,200620,CHF,180558,EX,PT,Switzerland,M,Australia,50,"Computer Vision, AWS, Python, TensorFlow",PhD,17,Energy,2024-04-30,2024-07-01,1920,5.4,Machine Intelligence Group -AI03338,AI Specialist,205234,CAD,256543,EX,FT,Canada,S,Canada,50,"Hadoop, Azure, NLP",Bachelor,18,Energy,2024-12-23,2025-02-24,809,7.8,Neural Networks Co -AI03339,Research Scientist,247132,USD,247132,EX,PT,Israel,L,Israel,50,"Python, Kubernetes, SQL",PhD,10,Government,2024-04-21,2024-06-01,673,9.4,TechCorp Inc -AI03340,Deep Learning Engineer,97358,USD,97358,EN,CT,Norway,M,Canada,50,"PyTorch, AWS, Azure, Git, TensorFlow",Master,0,Telecommunications,2024-05-14,2024-07-06,1847,7.1,Quantum Computing Inc -AI03341,Head of AI,57152,SGD,74298,EN,FL,Singapore,M,Singapore,0,"Statistics, Git, Data Visualization",Master,0,Automotive,2024-01-15,2024-03-25,1629,9,Smart Analytics -AI03342,Data Engineer,103950,EUR,88358,SE,PT,France,M,France,100,"Spark, Hadoop, NLP",Master,8,Consulting,2024-06-12,2024-07-25,1220,7.7,Future Systems -AI03343,Principal Data Scientist,112737,AUD,152195,SE,FL,Australia,S,Australia,0,"NLP, Scala, Mathematics, Java, SQL",Bachelor,5,Transportation,2024-08-17,2024-10-12,820,9.9,Neural Networks Co -AI03344,AI Product Manager,81647,JPY,8981170,EN,PT,Japan,L,Denmark,50,"GCP, Tableau, SQL, Computer Vision, Azure",Master,1,Media,2025-03-15,2025-05-10,2037,9,Predictive Systems -AI03345,Autonomous Systems Engineer,80194,USD,80194,MI,PT,Finland,M,Finland,100,"Python, GCP, Statistics",Associate,3,Automotive,2024-06-29,2024-08-07,1331,6.4,Algorithmic Solutions -AI03346,Machine Learning Researcher,50217,USD,50217,SE,FT,India,L,India,0,"Scala, TensorFlow, Tableau",Master,7,Energy,2025-01-29,2025-03-25,677,8.8,Neural Networks Co -AI03347,AI Consultant,242187,SGD,314843,EX,FL,Singapore,S,Netherlands,100,"Statistics, Tableau, PyTorch, NLP",Bachelor,10,Healthcare,2025-03-11,2025-04-12,2106,5.2,Autonomous Tech -AI03348,Head of AI,140261,USD,140261,SE,FL,Norway,M,Norway,100,"Linux, TensorFlow, SQL, Deep Learning, Java",Bachelor,6,Manufacturing,2024-09-02,2024-10-27,640,8.4,Advanced Robotics -AI03349,Data Engineer,92105,USD,92105,MI,FT,Finland,S,Austria,50,"AWS, Hadoop, Spark, NLP, Git",PhD,4,Transportation,2024-12-18,2025-02-17,1207,9,Digital Transformation LLC -AI03350,Research Scientist,123667,USD,123667,SE,PT,Ireland,M,China,50,"PyTorch, Statistics, Azure",PhD,6,Energy,2024-05-21,2024-06-13,1651,9.9,Machine Intelligence Group -AI03351,Machine Learning Engineer,93495,USD,93495,MI,PT,United States,S,United States,0,"TensorFlow, Kubernetes, Hadoop, Azure, Scala",Bachelor,3,Telecommunications,2024-11-14,2025-01-18,1663,6.5,Digital Transformation LLC -AI03352,Research Scientist,164403,AUD,221944,EX,FT,Australia,L,Australia,0,"Python, Git, TensorFlow, Hadoop, Mathematics",Bachelor,14,Government,2025-01-26,2025-03-26,1244,6.3,AI Innovations -AI03353,Deep Learning Engineer,161726,GBP,121295,SE,PT,United Kingdom,M,Indonesia,50,"AWS, Python, Tableau, R",Bachelor,8,Manufacturing,2025-03-03,2025-03-26,1141,8.1,Advanced Robotics -AI03354,Data Engineer,65395,AUD,88283,EN,CT,Australia,S,Australia,100,"PyTorch, Statistics, SQL, AWS",Bachelor,0,Transportation,2025-02-12,2025-04-20,2277,5.7,DeepTech Ventures -AI03355,Research Scientist,163112,USD,163112,SE,PT,Finland,L,Finland,50,"Python, Linux, Java, R",PhD,8,Telecommunications,2024-06-08,2024-08-02,1351,5.6,Autonomous Tech -AI03356,NLP Engineer,120372,USD,120372,SE,PT,Sweden,S,Sweden,0,"Spark, MLOps, Deep Learning",Associate,7,Real Estate,2024-12-27,2025-03-07,1014,5.1,Smart Analytics -AI03357,AI Consultant,80130,USD,80130,EN,FT,Denmark,L,Denmark,100,"SQL, PyTorch, R",Associate,1,Gaming,2024-12-27,2025-02-28,2374,7.3,Advanced Robotics -AI03358,Deep Learning Engineer,69483,USD,69483,SE,CT,China,L,China,50,"Python, R, GCP, Docker",Master,6,Technology,2024-07-26,2024-08-19,733,6.5,Digital Transformation LLC -AI03359,AI Specialist,275292,USD,275292,EX,FL,Denmark,M,Denmark,50,"Git, PyTorch, MLOps, Spark, Kubernetes",Master,16,Government,2024-03-12,2024-03-28,572,9.9,Machine Intelligence Group -AI03360,Data Analyst,90173,EUR,76647,MI,CT,Germany,L,Germany,50,"Linux, Scala, Mathematics, AWS, SQL",Bachelor,4,Technology,2024-11-25,2025-01-29,1158,7.8,Quantum Computing Inc -AI03361,AI Consultant,115690,JPY,12725900,MI,CT,Japan,L,Latvia,100,"Spark, Scala, Tableau, SQL",Master,3,Automotive,2024-11-25,2025-02-05,2463,9.8,Neural Networks Co -AI03362,Machine Learning Engineer,52110,USD,52110,EN,CT,Sweden,M,Luxembourg,100,"Mathematics, Scala, Python, Kubernetes",Associate,0,Energy,2024-06-01,2024-08-07,838,5.6,Cloud AI Solutions -AI03363,Deep Learning Engineer,163804,USD,163804,SE,CT,Norway,M,Estonia,100,"R, Java, Azure, Mathematics, NLP",PhD,7,Energy,2024-04-24,2024-06-25,2440,8.9,AI Innovations -AI03364,Machine Learning Researcher,173688,EUR,147635,SE,PT,Netherlands,L,Netherlands,100,"R, Linux, Git",Associate,6,Media,2024-09-05,2024-10-08,2247,8.2,Autonomous Tech -AI03365,Machine Learning Researcher,244135,AUD,329582,EX,PT,Australia,M,Australia,100,"Linux, SQL, Git, Data Visualization",Master,17,Automotive,2024-12-24,2025-01-16,2027,7.7,Machine Intelligence Group -AI03366,Research Scientist,177041,USD,177041,EX,CT,Finland,S,Estonia,100,"Azure, R, Tableau, Hadoop",Associate,12,Transportation,2024-05-06,2024-05-30,959,7.9,Neural Networks Co -AI03367,Head of AI,113070,CHF,101763,MI,FL,Switzerland,M,Poland,0,"R, Kubernetes, Tableau",PhD,4,Technology,2024-09-10,2024-11-15,1787,8.8,DeepTech Ventures -AI03368,Machine Learning Engineer,34381,USD,34381,SE,CT,India,S,India,0,"Hadoop, Python, Statistics, Linux, AWS",PhD,6,Retail,2025-02-28,2025-03-20,2339,5.2,Machine Intelligence Group -AI03369,AI Architect,102804,USD,102804,EX,FL,China,M,China,100,"Computer Vision, Azure, MLOps, NLP",PhD,11,Government,2024-09-17,2024-11-15,1482,5.7,TechCorp Inc -AI03370,AI Architect,124994,EUR,106245,SE,CT,Netherlands,L,Ukraine,50,"Python, Spark, Tableau",Associate,9,Manufacturing,2024-03-11,2024-05-17,867,7.6,Neural Networks Co -AI03371,Autonomous Systems Engineer,48674,USD,48674,SE,FT,India,M,Ukraine,100,"Scala, NLP, TensorFlow, Java, Git",Associate,9,Technology,2025-02-14,2025-03-07,2390,8.8,DataVision Ltd -AI03372,Autonomous Systems Engineer,83060,GBP,62295,EN,FT,United Kingdom,M,United Kingdom,50,"Scala, Hadoop, Azure, Java",Associate,0,Manufacturing,2025-04-08,2025-04-26,920,5.2,Algorithmic Solutions -AI03373,Computer Vision Engineer,116877,SGD,151940,MI,PT,Singapore,L,Singapore,0,"Mathematics, Spark, PyTorch, Java, SQL",Master,2,Healthcare,2024-12-22,2025-02-21,1090,9.4,AI Innovations -AI03374,AI Consultant,49966,USD,49966,SE,CT,India,M,India,100,"AWS, Git, NLP, Spark",Associate,5,Consulting,2024-10-23,2024-12-03,2239,5.7,DataVision Ltd -AI03375,Machine Learning Engineer,109823,USD,109823,SE,CT,Ireland,S,France,0,"Azure, Linux, Data Visualization, Tableau",Associate,7,Real Estate,2024-09-09,2024-09-27,590,6.4,Digital Transformation LLC -AI03376,Computer Vision Engineer,89964,EUR,76469,MI,CT,Netherlands,M,Romania,100,"Java, GCP, Mathematics",Master,2,Energy,2024-03-26,2024-04-28,1914,7.8,Cloud AI Solutions -AI03377,NLP Engineer,99897,CHF,89907,EN,CT,Switzerland,S,Switzerland,0,"Tableau, SQL, Linux",Associate,1,Energy,2025-02-17,2025-04-16,501,5.5,TechCorp Inc -AI03378,AI Product Manager,112037,CHF,100833,EN,FT,Switzerland,M,Switzerland,0,"AWS, SQL, R, Computer Vision",Associate,1,Telecommunications,2024-02-13,2024-04-04,1799,5.3,DataVision Ltd -AI03379,Robotics Engineer,97555,USD,97555,MI,FL,Sweden,S,Ireland,0,"Deep Learning, AWS, Mathematics, Python",Bachelor,3,Education,2024-07-18,2024-08-05,1520,9.7,Autonomous Tech -AI03380,Deep Learning Engineer,51067,USD,51067,MI,FT,China,L,China,0,"AWS, Kubernetes, R",Bachelor,2,Real Estate,2024-09-29,2024-11-29,705,8.4,Quantum Computing Inc -AI03381,AI Software Engineer,74645,AUD,100771,EN,PT,Australia,M,Australia,50,"Kubernetes, Python, Data Visualization, Statistics, Deep Learning",Master,1,Government,2024-03-18,2024-05-12,652,8.5,Predictive Systems -AI03382,ML Ops Engineer,73008,JPY,8030880,MI,CT,Japan,S,Japan,50,"Java, Kubernetes, Azure",Master,3,Finance,2024-10-18,2024-12-14,1485,8.2,AI Innovations -AI03383,Autonomous Systems Engineer,31006,USD,31006,EN,FT,China,S,China,100,"Python, Data Visualization, Linux, MLOps",PhD,0,Government,2024-06-08,2024-07-24,1097,9.2,Machine Intelligence Group -AI03384,Data Scientist,101583,USD,101583,SE,PT,South Korea,S,Canada,0,"Python, Scala, Hadoop, AWS",Master,9,Government,2024-07-29,2024-09-02,1325,6.1,Smart Analytics -AI03385,Computer Vision Engineer,90261,USD,90261,MI,CT,Sweden,M,Romania,0,"Tableau, Kubernetes, Scala, AWS, Git",Associate,4,Retail,2024-07-08,2024-07-23,1414,6.5,Future Systems -AI03386,AI Product Manager,111512,GBP,83634,MI,FL,United Kingdom,M,Latvia,0,"Statistics, NLP, Linux, Kubernetes, Hadoop",Bachelor,2,Media,2024-05-26,2024-06-15,1256,6.6,Smart Analytics -AI03387,AI Software Engineer,135059,JPY,14856490,SE,PT,Japan,M,South Africa,0,"PyTorch, Computer Vision, Scala, Azure, Linux",PhD,8,Telecommunications,2024-06-01,2024-08-02,1857,8.1,DataVision Ltd -AI03388,AI Architect,188799,USD,188799,EX,CT,Denmark,S,Denmark,50,"Tableau, Docker, NLP, Kubernetes",Associate,13,Real Estate,2024-03-28,2024-04-14,953,9.3,Autonomous Tech -AI03389,Data Scientist,133225,USD,133225,SE,FL,Ireland,S,Ireland,50,"PyTorch, Spark, Docker",PhD,5,Telecommunications,2024-08-27,2024-09-18,573,7,Smart Analytics -AI03390,Autonomous Systems Engineer,60400,USD,60400,SE,FL,China,S,China,0,"Computer Vision, Git, Python",Bachelor,5,Healthcare,2024-12-11,2025-01-06,1043,5.6,DeepTech Ventures -AI03391,Data Scientist,114422,USD,114422,SE,FT,Ireland,M,Ireland,100,"Azure, Linux, Mathematics, Data Visualization",Bachelor,7,Real Estate,2024-06-22,2024-08-11,2321,5.9,Cognitive Computing -AI03392,Research Scientist,85322,USD,85322,EN,CT,Denmark,S,Denmark,100,"Kubernetes, Scala, Mathematics, Azure",Bachelor,1,Healthcare,2024-10-28,2024-12-19,2265,5.8,AI Innovations -AI03393,Head of AI,64462,EUR,54793,MI,FL,Austria,S,Colombia,0,"Scala, PyTorch, TensorFlow, NLP",Master,4,Gaming,2024-04-17,2024-05-24,640,7.8,DataVision Ltd -AI03394,Deep Learning Engineer,214640,CAD,268300,EX,CT,Canada,M,Canada,100,"PyTorch, Kubernetes, GCP, Statistics, AWS",Bachelor,13,Media,2025-01-01,2025-02-04,708,8.6,Algorithmic Solutions -AI03395,NLP Engineer,160700,USD,160700,EX,FT,Israel,M,Israel,100,"Spark, GCP, Scala",Bachelor,18,Consulting,2025-04-15,2025-05-22,1966,6.4,Digital Transformation LLC -AI03396,Machine Learning Researcher,114986,CAD,143733,SE,CT,Canada,S,Israel,0,"AWS, Kubernetes, Azure",PhD,9,Automotive,2024-05-31,2024-08-05,1103,9.5,Predictive Systems -AI03397,Robotics Engineer,160285,GBP,120214,SE,PT,United Kingdom,M,Ireland,50,"Kubernetes, Computer Vision, Python, Git, Mathematics",Master,9,Technology,2025-01-12,2025-03-09,1719,5.4,Digital Transformation LLC -AI03398,ML Ops Engineer,184764,AUD,249431,EX,FT,Australia,L,Argentina,100,"Kubernetes, Python, Scala, Git, TensorFlow",Master,17,Media,2024-07-16,2024-08-18,2153,5.3,Advanced Robotics -AI03399,Deep Learning Engineer,168868,CHF,151981,MI,FL,Switzerland,L,Switzerland,50,"Kubernetes, Deep Learning, Data Visualization",Bachelor,3,Technology,2025-04-12,2025-06-17,2054,7.7,Neural Networks Co -AI03400,AI Architect,59852,GBP,44889,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Tableau, Linux, Scala, Deep Learning",PhD,1,Manufacturing,2025-01-21,2025-04-02,1905,8.8,Quantum Computing Inc -AI03401,Computer Vision Engineer,127118,EUR,108050,SE,CT,Austria,S,France,100,"Spark, Statistics, AWS, GCP, Scala",PhD,6,Technology,2024-10-16,2024-11-04,610,6.6,Quantum Computing Inc -AI03402,Machine Learning Engineer,62015,USD,62015,EN,FL,Sweden,L,Sweden,50,"GCP, SQL, Deep Learning, Python",PhD,1,Consulting,2024-04-17,2024-05-12,1071,9.3,Future Systems -AI03403,AI Software Engineer,70434,EUR,59869,EN,FL,Austria,L,Austria,50,"Python, Spark, Git, Deep Learning, Tableau",Master,1,Telecommunications,2024-04-18,2024-05-13,2274,6.7,AI Innovations -AI03404,AI Software Engineer,102013,USD,102013,EX,PT,South Korea,S,South Korea,0,"Linux, AWS, R",Associate,17,Transportation,2025-04-06,2025-06-04,2244,7.6,AI Innovations -AI03405,AI Architect,178561,USD,178561,EX,CT,Finland,L,Philippines,50,"Data Visualization, Linux, Git, PyTorch",PhD,19,Education,2024-01-23,2024-03-13,651,8,DeepTech Ventures -AI03406,Head of AI,63698,USD,63698,EN,FL,South Korea,L,Kenya,100,"Linux, Python, TensorFlow, MLOps",Bachelor,0,Automotive,2024-02-15,2024-04-14,1653,6.8,Smart Analytics -AI03407,NLP Engineer,70117,USD,70117,EN,CT,Sweden,M,Ukraine,50,"SQL, Data Visualization, Scala, Computer Vision, Azure",Master,0,Real Estate,2024-10-05,2024-12-03,2200,6,Quantum Computing Inc -AI03408,AI Specialist,125886,USD,125886,SE,CT,Israel,L,Ukraine,0,"PyTorch, MLOps, TensorFlow, SQL, Computer Vision",Associate,5,Automotive,2024-10-15,2024-10-31,923,5.9,AI Innovations -AI03409,Head of AI,143263,EUR,121774,SE,CT,Germany,L,Germany,100,"Data Visualization, NLP, Java, PyTorch",PhD,9,Gaming,2024-06-28,2024-08-03,1811,8.7,Quantum Computing Inc -AI03410,Autonomous Systems Engineer,61495,USD,61495,MI,CT,South Korea,S,South Korea,100,"AWS, Hadoop, Mathematics",PhD,4,Finance,2024-12-27,2025-02-24,2423,8.6,Machine Intelligence Group -AI03411,Robotics Engineer,275523,USD,275523,EX,CT,Norway,S,Netherlands,0,"NLP, Scala, Hadoop, Data Visualization",PhD,17,Technology,2024-08-19,2024-09-16,891,8.9,AI Innovations -AI03412,Data Engineer,65593,EUR,55754,EN,CT,France,M,France,100,"Deep Learning, Data Visualization, PyTorch, Kubernetes, Tableau",Master,1,Telecommunications,2024-02-29,2024-04-26,1617,6.2,DataVision Ltd -AI03413,Robotics Engineer,63298,USD,63298,EN,FT,United States,S,United States,50,"Hadoop, Python, TensorFlow, PyTorch, Statistics",PhD,0,Manufacturing,2025-04-30,2025-06-25,1610,9.9,Predictive Systems -AI03414,AI Software Engineer,70299,EUR,59754,MI,PT,France,M,France,100,"SQL, PyTorch, TensorFlow",Bachelor,2,Energy,2025-01-19,2025-02-16,2016,8.4,Cloud AI Solutions -AI03415,Machine Learning Engineer,202655,SGD,263452,EX,FL,Singapore,M,Singapore,0,"Linux, Hadoop, Git",Bachelor,12,Energy,2024-02-17,2024-03-27,2364,8,Quantum Computing Inc -AI03416,AI Specialist,256495,USD,256495,EX,PT,Norway,L,Norway,0,"Python, TensorFlow, Hadoop, Java",Bachelor,13,Transportation,2024-03-08,2024-04-05,1154,8.7,Neural Networks Co -AI03417,AI Product Manager,84934,AUD,114661,EN,PT,Australia,L,Australia,100,"Spark, Linux, R",Master,0,Energy,2024-10-06,2024-11-06,1062,8.9,Smart Analytics -AI03418,Research Scientist,83381,EUR,70874,MI,FL,Germany,S,Germany,100,"Git, Python, TensorFlow, NLP",Bachelor,3,Real Estate,2024-04-20,2024-06-07,1342,9.7,Algorithmic Solutions -AI03419,Data Analyst,26293,USD,26293,EN,FT,India,M,India,50,"PyTorch, SQL, AWS",Bachelor,1,Technology,2025-03-19,2025-05-12,2348,6.2,DataVision Ltd -AI03420,Head of AI,114838,USD,114838,SE,CT,Sweden,S,Sweden,50,"NLP, Python, Computer Vision, R, Deep Learning",Associate,9,Automotive,2025-01-11,2025-02-14,1472,7.1,Smart Analytics -AI03421,AI Specialist,130423,AUD,176071,SE,PT,Australia,S,Australia,0,"Python, Git, TensorFlow",PhD,9,Automotive,2024-11-09,2024-12-22,1640,8.3,Smart Analytics -AI03422,Head of AI,73362,USD,73362,MI,CT,Israel,S,Romania,0,"Python, Data Visualization, TensorFlow",Associate,4,Energy,2024-04-11,2024-06-13,1395,9.4,Algorithmic Solutions -AI03423,Research Scientist,55846,USD,55846,MI,FL,China,L,Sweden,100,"Tableau, Python, Statistics",Master,2,Media,2024-08-15,2024-09-01,1702,7.3,TechCorp Inc -AI03424,AI Product Manager,216173,USD,216173,EX,FT,South Korea,L,Hungary,50,"Python, Git, TensorFlow, Linux",Associate,17,Automotive,2024-04-19,2024-06-07,2275,8.4,Autonomous Tech -AI03425,Data Engineer,184151,GBP,138113,EX,FT,United Kingdom,M,United Kingdom,0,"Python, Docker, Tableau, GCP",Associate,12,Energy,2024-05-11,2024-06-28,957,8.4,Smart Analytics -AI03426,AI Product Manager,109524,CAD,136905,MI,FL,Canada,L,Canada,0,"PyTorch, Hadoop, MLOps, Kubernetes, Linux",PhD,4,Telecommunications,2024-03-27,2024-05-01,1174,8,AI Innovations -AI03427,Research Scientist,83789,USD,83789,EN,FT,United States,M,Colombia,0,"Python, MLOps, SQL, NLP",PhD,0,Healthcare,2025-01-15,2025-02-13,2307,6.7,Digital Transformation LLC -AI03428,Computer Vision Engineer,163508,USD,163508,EX,PT,South Korea,S,South Korea,0,"Scala, R, Deep Learning, Azure",PhD,17,Energy,2025-02-22,2025-04-15,1992,7.7,Smart Analytics -AI03429,Principal Data Scientist,159674,CHF,143707,MI,CT,Switzerland,L,Switzerland,100,"Scala, SQL, Python, Tableau",Master,2,Retail,2024-05-08,2024-06-06,888,8.1,Autonomous Tech -AI03430,Machine Learning Engineer,72337,USD,72337,EN,FL,Norway,S,Finland,50,"Git, Spark, Docker, TensorFlow, Linux",Master,0,Technology,2024-08-23,2024-10-25,598,9.8,Smart Analytics -AI03431,AI Research Scientist,168105,EUR,142889,EX,CT,Germany,L,Germany,100,"Kubernetes, Scala, Python",PhD,10,Telecommunications,2024-01-12,2024-01-27,1693,8.2,Algorithmic Solutions -AI03432,Data Scientist,157793,USD,157793,SE,PT,United States,L,India,0,"Docker, SQL, Computer Vision, Java",Bachelor,7,Telecommunications,2024-01-20,2024-03-09,2041,8.3,Quantum Computing Inc -AI03433,Machine Learning Engineer,186928,USD,186928,SE,FL,Norway,L,Chile,100,"Computer Vision, Python, Kubernetes, AWS",Master,9,Retail,2024-11-01,2024-11-24,1184,5.4,AI Innovations -AI03434,AI Specialist,97344,USD,97344,MI,PT,Ireland,S,Philippines,0,"Docker, Python, Computer Vision",Bachelor,2,Finance,2024-12-02,2025-01-18,1143,6.9,Cognitive Computing -AI03435,AI Product Manager,47190,EUR,40112,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, GCP, AWS, Deep Learning",Associate,0,Finance,2024-12-16,2025-01-04,539,9.7,Neural Networks Co -AI03436,Data Scientist,64670,CAD,80838,EN,PT,Canada,M,Canada,50,"Git, Azure, SQL, Mathematics",PhD,1,Consulting,2024-10-04,2024-11-24,1319,6.8,Machine Intelligence Group -AI03437,AI Architect,126076,USD,126076,SE,CT,Finland,S,Finland,50,"Data Visualization, Python, Linux, Statistics, TensorFlow",PhD,8,Media,2024-05-14,2024-07-22,2017,9.8,Predictive Systems -AI03438,Principal Data Scientist,98433,AUD,132885,MI,CT,Australia,M,Australia,50,"Linux, PyTorch, AWS, Deep Learning, MLOps",Master,2,Media,2024-02-10,2024-04-15,2422,9,Machine Intelligence Group -AI03439,Robotics Engineer,31915,USD,31915,EN,CT,China,L,China,100,"Statistics, Spark, Kubernetes, R, SQL",Bachelor,0,Gaming,2024-08-31,2024-10-07,1804,9.6,Neural Networks Co -AI03440,Data Scientist,175657,USD,175657,SE,PT,Norway,S,Norway,100,"Data Visualization, Spark, MLOps",Bachelor,5,Government,2024-10-07,2024-11-29,1903,9.8,Digital Transformation LLC -AI03441,Deep Learning Engineer,200463,USD,200463,EX,FL,Israel,M,Israel,0,"Scala, Hadoop, Deep Learning, AWS",PhD,19,Media,2024-10-17,2024-12-16,885,5,Quantum Computing Inc -AI03442,Robotics Engineer,109629,USD,109629,SE,CT,South Korea,S,Poland,100,"MLOps, Kubernetes, GCP",Associate,6,Finance,2024-04-12,2024-05-19,811,6.7,DataVision Ltd -AI03443,NLP Engineer,80126,USD,80126,EN,FT,Finland,L,Australia,100,"AWS, Tableau, Linux, Data Visualization",Master,0,Automotive,2024-01-31,2024-02-14,1963,6.2,Future Systems -AI03444,Machine Learning Engineer,91862,GBP,68897,EN,FT,United Kingdom,L,Malaysia,100,"TensorFlow, NLP, Git",PhD,0,Healthcare,2024-07-10,2024-09-02,2134,6.2,DeepTech Ventures -AI03445,Data Scientist,102655,JPY,11292050,MI,CT,Japan,L,Canada,50,"Kubernetes, R, PyTorch, GCP, Java",Master,4,Retail,2025-01-12,2025-02-01,864,6.5,Cloud AI Solutions -AI03446,Data Scientist,147186,AUD,198701,SE,CT,Australia,M,Chile,50,"TensorFlow, Mathematics, Kubernetes, SQL, Statistics",PhD,5,Telecommunications,2025-04-26,2025-06-18,983,7.4,DataVision Ltd -AI03447,Research Scientist,184149,USD,184149,EX,FT,Ireland,S,Ireland,0,"GCP, SQL, Data Visualization, Mathematics",Bachelor,14,Automotive,2024-03-31,2024-04-26,645,6.8,Digital Transformation LLC -AI03448,Computer Vision Engineer,273048,USD,273048,EX,FL,Norway,M,Germany,50,"Python, Mathematics, Data Visualization, Computer Vision",Master,16,Energy,2024-12-15,2024-12-30,892,6.2,Cloud AI Solutions -AI03449,NLP Engineer,105192,GBP,78894,MI,PT,United Kingdom,S,United Kingdom,50,"Kubernetes, TensorFlow, Hadoop, Linux",Master,2,Media,2024-05-21,2024-06-27,845,5.2,DataVision Ltd -AI03450,Deep Learning Engineer,37406,USD,37406,MI,PT,India,M,India,0,"Git, Java, Linux, Python",Master,4,Education,2024-01-27,2024-03-01,1756,6.8,DataVision Ltd -AI03451,AI Specialist,27619,USD,27619,EN,FT,India,M,India,0,"Tableau, Python, R, Kubernetes",Bachelor,0,Government,2024-08-10,2024-10-11,570,8.8,Smart Analytics -AI03452,Machine Learning Researcher,94921,USD,94921,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Spark, Docker",PhD,8,Media,2024-04-04,2024-06-12,2257,5.4,Quantum Computing Inc -AI03453,Data Scientist,199186,USD,199186,EX,FT,Israel,M,Israel,0,"Docker, Kubernetes, Hadoop, Java",Master,13,Automotive,2024-05-26,2024-07-02,2222,9.8,Neural Networks Co -AI03454,ML Ops Engineer,118265,SGD,153745,SE,PT,Singapore,M,Belgium,50,"Kubernetes, R, PyTorch, Git",PhD,8,Energy,2024-08-31,2024-11-01,1950,7.6,Advanced Robotics -AI03455,Computer Vision Engineer,75240,SGD,97812,EN,CT,Singapore,L,Kenya,100,"Azure, Kubernetes, NLP, Computer Vision",Bachelor,1,Technology,2024-05-15,2024-06-30,826,9.8,AI Innovations -AI03456,Research Scientist,65569,USD,65569,EN,FL,Israel,M,Switzerland,50,"GCP, Java, MLOps",PhD,1,Gaming,2024-04-16,2024-06-20,2302,6.3,Predictive Systems -AI03457,Data Scientist,205247,USD,205247,EX,FL,Denmark,S,Denmark,0,"Docker, Kubernetes, Git, SQL",PhD,17,Real Estate,2024-01-16,2024-03-22,1888,7.3,Digital Transformation LLC -AI03458,Data Scientist,37999,USD,37999,MI,CT,India,L,India,100,"Statistics, GCP, MLOps",PhD,4,Government,2024-12-20,2025-01-20,1159,6.2,Quantum Computing Inc -AI03459,Data Engineer,136750,JPY,15042500,SE,CT,Japan,M,Japan,100,"Tableau, Linux, TensorFlow, MLOps",Associate,7,Consulting,2024-03-17,2024-04-10,939,6.6,Neural Networks Co -AI03460,AI Product Manager,55482,USD,55482,EN,FL,Finland,M,Finland,100,"Python, Data Visualization, TensorFlow, Deep Learning",Associate,1,Consulting,2025-02-28,2025-04-05,2469,7.1,DeepTech Ventures -AI03461,Principal Data Scientist,126580,AUD,170883,MI,CT,Australia,L,Australia,0,"Data Visualization, GCP, Computer Vision, Kubernetes",Bachelor,2,Consulting,2025-04-24,2025-06-07,1369,5.4,AI Innovations -AI03462,Deep Learning Engineer,45523,USD,45523,MI,PT,China,L,Switzerland,0,"Spark, GCP, Hadoop, SQL",PhD,2,Retail,2024-08-11,2024-10-17,733,7.2,Future Systems -AI03463,Computer Vision Engineer,69117,USD,69117,MI,PT,Finland,S,New Zealand,0,"Deep Learning, AWS, Docker",Master,4,Finance,2025-03-02,2025-03-30,1948,9.6,Algorithmic Solutions -AI03464,Robotics Engineer,147154,USD,147154,MI,PT,United States,L,United States,0,"MLOps, Scala, SQL, PyTorch, NLP",Master,3,Education,2025-03-07,2025-04-23,1786,8.8,Advanced Robotics -AI03465,Computer Vision Engineer,129411,EUR,109999,SE,CT,Germany,M,Germany,0,"Azure, SQL, NLP, Deep Learning",Associate,6,Retail,2024-04-02,2024-04-25,2001,7.2,Cloud AI Solutions -AI03466,NLP Engineer,103365,AUD,139543,SE,CT,Australia,S,Australia,0,"Hadoop, Statistics, GCP, MLOps, Spark",PhD,7,Education,2024-07-17,2024-09-21,1363,7.2,TechCorp Inc -AI03467,Machine Learning Researcher,155656,USD,155656,SE,FL,United States,L,United States,50,"Deep Learning, R, PyTorch, Docker, Linux",Master,8,Transportation,2025-02-23,2025-03-28,2452,7.1,Cloud AI Solutions -AI03468,Deep Learning Engineer,60372,EUR,51316,EN,PT,Netherlands,M,Netherlands,100,"SQL, GCP, Java",Bachelor,1,Gaming,2024-01-14,2024-02-19,1363,7.7,TechCorp Inc -AI03469,Machine Learning Engineer,90624,EUR,77030,SE,FT,Austria,S,Spain,50,"GCP, Hadoop, PyTorch",Associate,8,Retail,2025-02-24,2025-04-08,655,8.9,Autonomous Tech -AI03470,Principal Data Scientist,28839,USD,28839,EN,CT,China,S,Estonia,50,"Scala, Python, SQL",Master,1,Real Estate,2024-08-20,2024-10-18,1826,10,Cognitive Computing -AI03471,Data Analyst,95397,EUR,81087,MI,FT,Germany,S,Germany,50,"Deep Learning, R, Spark",Bachelor,3,Healthcare,2024-02-06,2024-02-21,705,5.3,DataVision Ltd -AI03472,ML Ops Engineer,265922,JPY,29251420,EX,CT,Japan,L,United States,0,"GCP, Tableau, AWS, SQL",Associate,16,Energy,2024-03-16,2024-05-01,1345,5.6,Predictive Systems -AI03473,NLP Engineer,123952,CHF,111557,MI,CT,Switzerland,M,Switzerland,50,"PyTorch, Java, Git, Computer Vision",Bachelor,2,Automotive,2024-05-14,2024-06-20,713,8.8,Cloud AI Solutions -AI03474,Data Scientist,243390,EUR,206882,EX,FT,Germany,M,Indonesia,100,"Linux, PyTorch, Tableau, Java, Git",Bachelor,12,Automotive,2024-12-01,2024-12-31,1715,9,Cognitive Computing -AI03475,Autonomous Systems Engineer,86886,JPY,9557460,MI,FT,Japan,M,Poland,100,"Kubernetes, Tableau, Azure, NLP, Python",Associate,2,Energy,2024-12-23,2025-02-26,1947,8.7,Machine Intelligence Group -AI03476,Machine Learning Researcher,86470,CHF,77823,EN,FT,Switzerland,S,Switzerland,0,"Python, Java, GCP, NLP",PhD,1,Education,2024-11-30,2024-12-14,1713,6.3,Cloud AI Solutions -AI03477,Principal Data Scientist,128696,EUR,109392,SE,PT,France,L,Malaysia,0,"Git, Linux, Data Visualization, PyTorch",Associate,6,Energy,2024-10-05,2024-11-14,1015,6.2,Autonomous Tech -AI03478,Data Analyst,108456,USD,108456,MI,CT,United States,L,United States,0,"TensorFlow, Deep Learning, Kubernetes, Python",Bachelor,2,Retail,2024-05-19,2024-07-04,1400,5.5,Machine Intelligence Group -AI03479,Data Engineer,114242,USD,114242,SE,FT,Ireland,M,Ireland,0,"Statistics, R, Scala",Master,9,Retail,2024-08-03,2024-09-22,2189,6.4,Smart Analytics -AI03480,Data Engineer,94224,USD,94224,MI,CT,Finland,L,Finland,0,"Spark, Scala, Computer Vision, Mathematics",PhD,2,Technology,2024-10-10,2024-12-14,540,9.2,TechCorp Inc -AI03481,Data Engineer,277483,SGD,360728,EX,FL,Singapore,L,Singapore,50,"MLOps, Spark, Data Visualization, Hadoop",Bachelor,19,Finance,2024-07-30,2024-09-09,770,9.7,Cognitive Computing -AI03482,Computer Vision Engineer,40704,USD,40704,MI,FT,China,M,China,50,"NLP, PyTorch, Tableau, Git, Docker",PhD,2,Media,2024-03-06,2024-05-10,795,6.8,TechCorp Inc -AI03483,Machine Learning Engineer,93238,EUR,79252,EN,CT,Netherlands,L,Portugal,100,"AWS, Statistics, Hadoop",PhD,1,Finance,2024-03-20,2024-05-24,2049,7.8,DeepTech Ventures -AI03484,Machine Learning Researcher,196588,CHF,176929,SE,FT,Switzerland,M,Estonia,0,"Data Visualization, Docker, R",Associate,9,Energy,2024-07-03,2024-09-04,1947,7.5,Autonomous Tech -AI03485,AI Software Engineer,90440,GBP,67830,MI,PT,United Kingdom,M,United Kingdom,50,"PyTorch, AWS, Computer Vision, NLP, GCP",Master,2,Energy,2025-03-19,2025-04-30,2326,6.6,Neural Networks Co -AI03486,AI Consultant,150604,USD,150604,MI,FT,Denmark,L,India,100,"Hadoop, Mathematics, GCP, Kubernetes, MLOps",Associate,2,Gaming,2024-09-03,2024-09-26,762,6.4,Advanced Robotics -AI03487,ML Ops Engineer,58876,USD,58876,SE,PT,India,L,India,0,"MLOps, GCP, SQL",Master,8,Government,2024-11-02,2025-01-02,730,6.3,AI Innovations -AI03488,AI Product Manager,28266,USD,28266,MI,CT,India,S,India,100,"NLP, Data Visualization, Tableau, Mathematics, MLOps",Master,2,Telecommunications,2025-01-26,2025-03-18,901,9.2,TechCorp Inc -AI03489,Research Scientist,83652,CAD,104565,MI,FL,Canada,M,Nigeria,100,"Azure, Tableau, Linux, AWS, Docker",Master,3,Energy,2025-02-01,2025-03-14,2027,6,AI Innovations -AI03490,AI Specialist,69368,USD,69368,EN,FT,Norway,S,Israel,50,"Spark, Python, Git, Azure",Associate,1,Manufacturing,2024-05-16,2024-06-08,1302,7.8,Autonomous Tech -AI03491,Head of AI,130656,USD,130656,SE,PT,Israel,L,Israel,50,"SQL, Mathematics, TensorFlow",PhD,9,Government,2025-02-21,2025-04-01,1038,5.4,Autonomous Tech -AI03492,AI Architect,168459,EUR,143190,SE,PT,Germany,L,Germany,0,"Spark, Hadoop, Scala, MLOps, R",Associate,6,Telecommunications,2024-04-07,2024-04-22,2246,7.9,Advanced Robotics -AI03493,Data Scientist,72394,AUD,97732,MI,CT,Australia,S,Ghana,100,"Deep Learning, GCP, SQL, Python",Master,4,Technology,2024-08-06,2024-08-28,882,6.4,Predictive Systems -AI03494,Principal Data Scientist,37641,USD,37641,MI,FL,India,M,India,0,"Python, Hadoop, SQL, Git, AWS",Master,2,Technology,2025-01-16,2025-03-08,897,5.7,Smart Analytics -AI03495,Deep Learning Engineer,109311,USD,109311,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Hadoop, Python, Linux",Bachelor,2,Government,2024-09-13,2024-11-21,2222,6.1,Algorithmic Solutions -AI03496,Machine Learning Engineer,237727,USD,237727,EX,FL,Denmark,M,Austria,50,"Python, NLP, Data Visualization",Bachelor,16,Telecommunications,2024-03-15,2024-05-25,728,7.3,Advanced Robotics -AI03497,AI Consultant,138467,USD,138467,EX,FT,Sweden,M,Sweden,0,"Python, Hadoop, SQL, Computer Vision",Associate,19,Technology,2024-07-21,2024-08-08,612,10,Digital Transformation LLC -AI03498,Head of AI,125705,EUR,106849,SE,FL,France,M,France,100,"PyTorch, Python, Scala",Bachelor,9,Energy,2024-11-06,2024-12-03,2098,8.1,AI Innovations -AI03499,ML Ops Engineer,107784,USD,107784,MI,PT,Norway,L,Norway,0,"SQL, Statistics, Data Visualization, Python, Mathematics",Bachelor,4,Technology,2024-07-07,2024-09-17,1589,5.9,TechCorp Inc -AI03500,Computer Vision Engineer,49527,USD,49527,SE,CT,India,M,India,0,"Python, Scala, AWS",Master,6,Media,2024-11-03,2025-01-11,1906,9.6,Advanced Robotics -AI03501,AI Software Engineer,73779,JPY,8115690,EN,PT,Japan,S,Poland,0,"Python, Azure, Statistics",Bachelor,1,Transportation,2024-07-05,2024-08-26,1183,10,Digital Transformation LLC -AI03502,AI Consultant,98422,USD,98422,MI,FL,United States,L,United States,50,"SQL, GCP, Statistics, Hadoop, Linux",PhD,3,Real Estate,2024-06-18,2024-07-16,2175,5.9,Algorithmic Solutions -AI03503,Principal Data Scientist,110310,SGD,143403,MI,PT,Singapore,L,Singapore,100,"PyTorch, Deep Learning, Spark",Associate,4,Retail,2025-02-28,2025-03-27,1821,6.7,Future Systems -AI03504,ML Ops Engineer,167443,EUR,142327,EX,FL,Austria,M,Austria,50,"R, Scala, NLP",Master,19,Transportation,2024-12-25,2025-01-21,2422,6.3,Cloud AI Solutions -AI03505,Machine Learning Engineer,135296,SGD,175885,SE,FT,Singapore,S,Singapore,0,"Spark, Kubernetes, Computer Vision",Associate,7,Media,2024-02-18,2024-03-07,2274,9.6,TechCorp Inc -AI03506,Data Scientist,101322,SGD,131719,MI,CT,Singapore,L,Singapore,100,"TensorFlow, Data Visualization, Git",Master,4,Technology,2024-10-30,2024-11-16,1477,9,AI Innovations -AI03507,AI Consultant,81204,AUD,109625,MI,FL,Australia,S,Australia,100,"Python, Hadoop, Linux, NLP, Statistics",PhD,2,Education,2024-01-07,2024-01-30,2214,5.5,DataVision Ltd -AI03508,Machine Learning Engineer,216778,USD,216778,EX,CT,United States,M,United States,100,"AWS, Azure, MLOps",Bachelor,12,Consulting,2024-06-22,2024-07-24,2366,6.3,DeepTech Ventures -AI03509,Computer Vision Engineer,176928,AUD,238853,EX,FL,Australia,M,Australia,100,"GCP, Git, Hadoop",PhD,14,Real Estate,2024-11-29,2025-01-15,1015,5.7,Neural Networks Co -AI03510,Research Scientist,76676,USD,76676,SE,PT,South Korea,S,Russia,0,"Java, SQL, MLOps, Mathematics, Hadoop",PhD,7,Retail,2024-05-27,2024-07-09,2390,9.1,Smart Analytics -AI03511,Data Analyst,167099,USD,167099,SE,PT,United States,L,United States,0,"R, Git, MLOps",PhD,7,Energy,2024-07-03,2024-07-30,720,8.7,Cognitive Computing -AI03512,ML Ops Engineer,89898,USD,89898,SE,CT,South Korea,M,South Korea,50,"SQL, Azure, Scala, MLOps, Python",Master,5,Transportation,2025-03-11,2025-03-30,1286,6,Quantum Computing Inc -AI03513,Robotics Engineer,123146,USD,123146,SE,PT,South Korea,M,South Korea,50,"Spark, Python, Linux, Statistics, Tableau",Master,9,Technology,2024-03-25,2024-05-03,1632,8,Predictive Systems -AI03514,ML Ops Engineer,244148,USD,244148,EX,FT,Denmark,L,Australia,50,"AWS, Python, TensorFlow, PyTorch, Scala",PhD,16,Transportation,2024-12-29,2025-01-14,1215,8.8,AI Innovations -AI03515,Machine Learning Researcher,212784,CHF,191506,EX,FT,Switzerland,S,Switzerland,50,"NLP, Linux, Python, R, TensorFlow",Bachelor,14,Manufacturing,2025-02-25,2025-04-06,689,9.1,Predictive Systems -AI03516,Principal Data Scientist,206443,AUD,278698,EX,PT,Australia,M,Australia,0,"Python, Kubernetes, GCP",Master,15,Gaming,2024-04-27,2024-06-19,2094,7.6,Future Systems -AI03517,ML Ops Engineer,55944,JPY,6153840,EN,FT,Japan,M,Japan,50,"MLOps, Java, R",Bachelor,0,Technology,2024-04-28,2024-05-26,1744,9.3,Machine Intelligence Group -AI03518,Autonomous Systems Engineer,71392,USD,71392,EN,FL,Sweden,S,Sweden,50,"Linux, Statistics, SQL, Git, Mathematics",Bachelor,1,Gaming,2024-05-05,2024-06-28,1567,8.5,Cloud AI Solutions -AI03519,Principal Data Scientist,126751,CAD,158439,SE,PT,Canada,M,Latvia,0,"Git, Java, R, GCP, SQL",Master,8,Technology,2025-01-24,2025-02-23,1506,7.2,Predictive Systems -AI03520,AI Specialist,99185,USD,99185,SE,CT,Finland,M,Finland,50,"GCP, Python, Linux, SQL",Bachelor,5,Retail,2024-01-20,2024-03-13,599,9.6,Cognitive Computing -AI03521,Machine Learning Engineer,218350,AUD,294773,EX,CT,Australia,S,Australia,0,"PyTorch, Tableau, TensorFlow",Master,16,Media,2024-10-28,2024-12-03,909,8.7,Algorithmic Solutions -AI03522,Principal Data Scientist,123624,SGD,160711,MI,PT,Singapore,L,Singapore,100,"PyTorch, Scala, Computer Vision, Spark",Associate,3,Automotive,2024-08-25,2024-09-25,1195,9.5,Cloud AI Solutions -AI03523,AI Research Scientist,150816,USD,150816,EX,PT,Ireland,S,Nigeria,50,"Python, AWS, Computer Vision, Docker, Data Visualization",PhD,18,Technology,2024-10-24,2024-12-09,1118,6.4,TechCorp Inc -AI03524,Computer Vision Engineer,248052,CAD,310065,EX,PT,Canada,L,Canada,0,"Docker, Scala, Data Visualization, Azure, Spark",Master,15,Real Estate,2024-08-08,2024-09-20,1640,6,Predictive Systems -AI03525,Research Scientist,174068,SGD,226288,SE,CT,Singapore,L,Singapore,100,"Mathematics, PyTorch, TensorFlow",Associate,9,Transportation,2024-12-06,2024-12-21,1050,8.7,Smart Analytics -AI03526,Data Analyst,202119,USD,202119,EX,CT,South Korea,L,South Korea,50,"NLP, Python, Spark, TensorFlow",Bachelor,13,Transportation,2024-07-08,2024-08-24,1755,6.6,Cloud AI Solutions -AI03527,AI Research Scientist,52293,USD,52293,EX,CT,India,M,India,50,"AWS, Docker, Statistics",Associate,10,Real Estate,2024-05-25,2024-07-01,2424,5.9,Quantum Computing Inc -AI03528,Machine Learning Researcher,127194,EUR,108115,EX,FL,France,S,France,100,"PyTorch, Docker, TensorFlow, Deep Learning",Associate,10,Real Estate,2024-01-05,2024-03-05,853,7.6,Neural Networks Co -AI03529,Machine Learning Researcher,133885,USD,133885,MI,FT,United States,L,United States,100,"Hadoop, Spark, Tableau",PhD,3,Automotive,2025-01-28,2025-02-23,1070,8.6,Digital Transformation LLC -AI03530,AI Software Engineer,134073,EUR,113962,SE,CT,France,M,France,0,"Hadoop, MLOps, Linux, Spark",Associate,9,Automotive,2024-07-17,2024-08-29,2452,8.7,Predictive Systems -AI03531,Data Analyst,128939,CAD,161174,SE,PT,Canada,L,Canada,100,"Data Visualization, Deep Learning, SQL, MLOps, Java",PhD,5,Telecommunications,2024-11-27,2025-01-24,824,5.1,DeepTech Ventures -AI03532,Data Scientist,65196,USD,65196,MI,PT,Ireland,S,Ireland,0,"GCP, Git, NLP, PyTorch, Statistics",PhD,4,Finance,2025-03-23,2025-04-15,1393,7.4,Cloud AI Solutions -AI03533,Deep Learning Engineer,122554,USD,122554,MI,FL,Ireland,L,Ireland,100,"Kubernetes, R, Python, AWS",Associate,2,Real Estate,2024-12-16,2025-02-05,1118,6.5,DeepTech Ventures -AI03534,NLP Engineer,72995,EUR,62046,EN,CT,Netherlands,S,Kenya,100,"Mathematics, R, Python, Docker, PyTorch",Master,1,Consulting,2024-07-24,2024-08-28,1205,8.6,DeepTech Ventures -AI03535,AI Architect,36919,USD,36919,SE,FT,India,M,India,100,"Hadoop, Scala, Python, Docker",PhD,9,Real Estate,2025-01-26,2025-03-26,842,8.7,Smart Analytics -AI03536,Computer Vision Engineer,111161,JPY,12227710,SE,CT,Japan,S,Japan,50,"Git, Linux, GCP, AWS, SQL",Bachelor,5,Technology,2024-03-01,2024-05-03,999,7.6,AI Innovations -AI03537,Principal Data Scientist,226559,USD,226559,EX,PT,South Korea,L,Argentina,50,"R, Python, Azure, SQL",PhD,11,Consulting,2024-01-27,2024-04-06,679,8,Future Systems -AI03538,AI Product Manager,194134,USD,194134,EX,FT,United States,M,United States,0,"Scala, Docker, Data Visualization, Kubernetes, PyTorch",Bachelor,11,Gaming,2024-08-19,2024-10-01,653,7.3,DataVision Ltd -AI03539,Machine Learning Engineer,48340,CAD,60425,EN,CT,Canada,S,Canada,100,"PyTorch, R, Data Visualization",Bachelor,0,Finance,2024-11-06,2024-12-21,2251,8.2,Future Systems -AI03540,ML Ops Engineer,93478,USD,93478,MI,FL,Sweden,S,Sweden,100,"AWS, SQL, Mathematics",PhD,4,Gaming,2024-01-25,2024-03-18,990,8.9,Cognitive Computing -AI03541,AI Specialist,135053,GBP,101290,SE,FT,United Kingdom,L,United Kingdom,0,"Azure, Deep Learning, TensorFlow",Bachelor,9,Education,2024-04-18,2024-06-23,974,5.4,DataVision Ltd -AI03542,AI Specialist,118702,AUD,160248,SE,CT,Australia,M,New Zealand,50,"AWS, MLOps, Hadoop, NLP, R",Master,5,Government,2025-01-21,2025-03-23,2213,8.3,Neural Networks Co -AI03543,Computer Vision Engineer,66189,USD,66189,EN,CT,Ireland,S,Ireland,0,"Scala, Kubernetes, Python",Associate,1,Education,2024-02-09,2024-03-03,1274,7.5,Quantum Computing Inc -AI03544,NLP Engineer,135922,USD,135922,SE,FL,Finland,M,Finland,100,"Hadoop, Statistics, Azure",Bachelor,8,Finance,2024-03-07,2024-04-24,2462,9.3,Autonomous Tech -AI03545,AI Research Scientist,220929,USD,220929,SE,FT,Denmark,L,Denmark,50,"Linux, Azure, Spark",Master,8,Energy,2024-01-17,2024-03-26,2021,5.8,Machine Intelligence Group -AI03546,NLP Engineer,82829,JPY,9111190,MI,FT,Japan,M,Japan,100,"Spark, Kubernetes, NLP, Hadoop",Associate,2,Technology,2025-04-05,2025-04-29,1930,7.3,Smart Analytics -AI03547,NLP Engineer,91897,AUD,124061,MI,PT,Australia,S,Australia,50,"MLOps, PyTorch, TensorFlow",PhD,3,Manufacturing,2024-09-30,2024-10-16,533,5.1,DataVision Ltd -AI03548,Research Scientist,120965,USD,120965,MI,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Kubernetes",Master,4,Media,2024-01-02,2024-02-08,2239,9.6,Advanced Robotics -AI03549,Machine Learning Engineer,310818,CHF,279736,EX,PT,Switzerland,S,Switzerland,100,"SQL, Python, MLOps, Java, Mathematics",Bachelor,18,Technology,2025-01-27,2025-03-30,1771,6.4,Smart Analytics -AI03550,Deep Learning Engineer,73677,EUR,62625,EN,FL,Austria,L,Austria,50,"SQL, Git, Linux, AWS",Bachelor,0,Technology,2024-07-30,2024-08-30,1254,6.4,Quantum Computing Inc -AI03551,Principal Data Scientist,71156,USD,71156,EN,CT,United States,L,India,0,"Azure, Mathematics, Kubernetes, Deep Learning, Data Visualization",Associate,0,Government,2024-02-17,2024-03-16,2491,7.6,Digital Transformation LLC -AI03552,AI Software Engineer,190140,EUR,161619,EX,PT,Germany,M,Germany,100,"MLOps, Data Visualization, Python, TensorFlow, Deep Learning",Master,17,Real Estate,2024-07-04,2024-07-26,1541,7.4,Future Systems -AI03553,ML Ops Engineer,133027,EUR,113073,SE,FT,Austria,L,Austria,50,"Spark, Linux, Java, PyTorch",Master,5,Telecommunications,2024-08-09,2024-08-27,901,6,Smart Analytics -AI03554,Research Scientist,232210,USD,232210,EX,PT,South Korea,L,Spain,50,"Scala, PyTorch, AWS, Spark, SQL",Master,15,Consulting,2024-08-07,2024-09-05,2085,5,Cognitive Computing -AI03555,Data Analyst,113916,GBP,85437,SE,FT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Hadoop, R, AWS",Associate,8,Energy,2024-05-12,2024-07-02,2364,6,AI Innovations -AI03556,Head of AI,228576,SGD,297149,EX,PT,Singapore,M,Singapore,0,"GCP, Java, SQL, Git",Associate,13,Education,2024-07-25,2024-09-03,1965,7.8,Smart Analytics -AI03557,Machine Learning Researcher,25011,USD,25011,EN,CT,China,M,Portugal,0,"SQL, Linux, Hadoop, Mathematics",PhD,1,Manufacturing,2024-09-01,2024-11-03,1692,9.1,Algorithmic Solutions -AI03558,AI Product Manager,139200,USD,139200,SE,PT,Sweden,M,Sweden,0,"Git, Azure, Tableau, MLOps",Master,5,Energy,2024-05-31,2024-07-16,1241,9.1,Machine Intelligence Group -AI03559,Computer Vision Engineer,292522,CHF,263270,EX,FL,Switzerland,S,Switzerland,0,"R, Java, Tableau, MLOps",Associate,15,Consulting,2024-01-01,2024-01-27,824,7,Machine Intelligence Group -AI03560,AI Specialist,159257,USD,159257,SE,FL,Denmark,L,Denmark,100,"R, TensorFlow, Data Visualization, Tableau, NLP",PhD,5,Healthcare,2024-10-03,2024-12-14,1309,9.8,Quantum Computing Inc -AI03561,AI Research Scientist,108189,USD,108189,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, Azure, GCP, Scala",Master,5,Media,2025-02-26,2025-03-30,1421,5.9,Neural Networks Co -AI03562,Robotics Engineer,112943,USD,112943,SE,CT,Sweden,M,Sweden,100,"SQL, Statistics, Tableau",Master,7,Media,2024-01-16,2024-02-02,1584,7.4,AI Innovations -AI03563,Data Engineer,101976,SGD,132569,MI,CT,Singapore,M,Singapore,50,"Python, Computer Vision, Git",Master,2,Technology,2024-08-24,2024-11-02,2384,6.8,Machine Intelligence Group -AI03564,Principal Data Scientist,90165,GBP,67624,EN,CT,United Kingdom,L,United Kingdom,100,"GCP, Hadoop, Statistics, Computer Vision",Bachelor,1,Technology,2024-05-21,2024-06-15,700,6.6,Cloud AI Solutions -AI03565,ML Ops Engineer,179183,JPY,19710130,EX,CT,Japan,S,Japan,100,"Scala, R, Kubernetes, Python, Docker",Master,18,Real Estate,2024-05-30,2024-06-27,1393,7.2,Digital Transformation LLC -AI03566,NLP Engineer,113638,EUR,96592,SE,PT,Netherlands,M,South Africa,50,"SQL, Python, TensorFlow, Statistics, PyTorch",Bachelor,5,Transportation,2025-04-18,2025-05-12,2288,5.5,Predictive Systems -AI03567,Data Analyst,50907,SGD,66179,EN,PT,Singapore,S,Singapore,0,"Hadoop, SQL, Statistics",Bachelor,0,Manufacturing,2025-03-29,2025-04-26,902,7.7,Smart Analytics -AI03568,AI Consultant,167654,EUR,142506,EX,PT,France,M,France,50,"Kubernetes, Mathematics, Linux, SQL",Bachelor,13,Consulting,2025-04-07,2025-05-27,2217,7.5,DeepTech Ventures -AI03569,Machine Learning Researcher,119056,CHF,107150,MI,FL,Switzerland,S,Switzerland,50,"Docker, Python, Tableau",Master,2,Gaming,2024-09-02,2024-11-02,2403,8.9,Autonomous Tech -AI03570,Autonomous Systems Engineer,95121,USD,95121,MI,PT,United States,M,Poland,0,"Python, TensorFlow, Azure, NLP",PhD,2,Retail,2025-01-26,2025-02-24,1927,7.1,Smart Analytics -AI03571,AI Architect,111821,JPY,12300310,MI,FL,Japan,L,Turkey,50,"Linux, AWS, MLOps, SQL",Master,4,Healthcare,2024-03-04,2024-04-30,1694,5.8,Cognitive Computing -AI03572,Principal Data Scientist,183873,GBP,137905,EX,FT,United Kingdom,M,United Kingdom,0,"PyTorch, Git, Computer Vision, Java, MLOps",Associate,18,Education,2024-07-04,2024-08-04,684,6.5,AI Innovations -AI03573,AI Architect,247623,CHF,222861,EX,FL,Switzerland,L,Switzerland,100,"Java, Statistics, R, SQL, MLOps",PhD,15,Retail,2024-12-12,2025-01-15,2363,9,Future Systems -AI03574,AI Product Manager,70419,USD,70419,SE,FL,China,M,China,0,"Hadoop, Scala, Tableau, PyTorch, Mathematics",PhD,5,Manufacturing,2024-02-15,2024-03-04,1299,5.4,Advanced Robotics -AI03575,AI Architect,80822,CAD,101028,MI,CT,Canada,M,Canada,50,"Kubernetes, Git, Python, Docker",Bachelor,2,Real Estate,2024-11-12,2024-12-22,2216,8.2,DataVision Ltd -AI03576,AI Research Scientist,116798,USD,116798,MI,FL,United States,L,United States,100,"Python, AWS, Tableau, Computer Vision",Associate,2,Media,2024-09-08,2024-11-09,1703,9,Advanced Robotics -AI03577,AI Consultant,32773,USD,32773,EN,PT,India,L,India,50,"Python, MLOps, R, Java",Master,1,Transportation,2024-11-20,2024-12-12,1687,5.4,Machine Intelligence Group -AI03578,AI Research Scientist,153325,AUD,206989,EX,PT,Australia,S,Australia,100,"Kubernetes, Deep Learning, Scala, Linux",Bachelor,18,Energy,2025-04-30,2025-07-11,951,9.7,DeepTech Ventures -AI03579,AI Consultant,139637,EUR,118691,SE,FL,Germany,L,Germany,0,"AWS, Hadoop, MLOps",Associate,9,Retail,2025-03-20,2025-04-09,2137,6.9,Neural Networks Co -AI03580,AI Product Manager,228479,CHF,205631,SE,FT,Switzerland,L,Switzerland,0,"Git, Linux, Spark, Python, GCP",Bachelor,6,Real Estate,2025-04-24,2025-05-30,630,7.4,DeepTech Ventures -AI03581,Data Analyst,213432,USD,213432,EX,FL,Denmark,S,Norway,0,"Kubernetes, NLP, Azure",PhD,14,Automotive,2024-11-14,2024-12-30,1371,9.8,TechCorp Inc -AI03582,Data Scientist,120417,USD,120417,SE,FL,Norway,S,Norway,50,"Python, TensorFlow, GCP, Statistics",Master,7,Real Estate,2024-09-01,2024-10-28,1954,8,Autonomous Tech -AI03583,Computer Vision Engineer,128062,USD,128062,MI,FL,Denmark,S,Denmark,50,"R, Spark, Statistics, Deep Learning",Master,3,Transportation,2024-07-19,2024-09-28,2040,8.6,Quantum Computing Inc -AI03584,AI Product Manager,152788,EUR,129870,SE,FT,France,L,France,100,"Statistics, Deep Learning, Java, Docker",Associate,8,Gaming,2024-08-17,2024-10-28,1390,7.1,Smart Analytics -AI03585,Data Engineer,151742,EUR,128981,EX,PT,France,L,France,0,"TensorFlow, Python, NLP",Bachelor,19,Gaming,2024-06-28,2024-07-21,816,8.9,DeepTech Ventures -AI03586,Robotics Engineer,127281,USD,127281,SE,FL,South Korea,L,South Korea,100,"Deep Learning, Kubernetes, Linux, Mathematics, Hadoop",PhD,8,Gaming,2024-12-15,2025-02-23,2078,7.3,Future Systems -AI03587,Autonomous Systems Engineer,95779,CAD,119724,MI,PT,Canada,M,Canada,50,"Python, Computer Vision, SQL",Associate,2,Real Estate,2025-01-07,2025-01-28,1351,6.2,Future Systems -AI03588,AI Software Engineer,127704,AUD,172400,SE,CT,Australia,L,Australia,0,"SQL, Python, Git, Statistics, MLOps",Associate,5,Automotive,2024-01-22,2024-02-17,2062,9.4,TechCorp Inc -AI03589,Computer Vision Engineer,119308,CAD,149135,SE,FL,Canada,S,Canada,50,"Computer Vision, Hadoop, Python, GCP",Bachelor,8,Education,2025-01-01,2025-01-15,564,8,Machine Intelligence Group -AI03590,ML Ops Engineer,62680,AUD,84618,EN,FT,Australia,M,Australia,50,"GCP, Java, SQL, R",Associate,1,Technology,2024-11-07,2024-12-18,2105,6.6,Advanced Robotics -AI03591,Data Scientist,272438,AUD,367791,EX,PT,Australia,L,Norway,50,"AWS, Scala, NLP, PyTorch",PhD,17,Consulting,2024-03-10,2024-04-13,1144,8.1,Cognitive Computing -AI03592,AI Software Engineer,174329,EUR,148180,SE,CT,Netherlands,L,Netherlands,100,"R, NLP, Java",Master,7,Energy,2024-04-30,2024-05-27,1675,7,Smart Analytics -AI03593,Computer Vision Engineer,46653,USD,46653,EN,CT,Israel,S,Israel,0,"Python, GCP, Statistics",Associate,0,Technology,2024-04-20,2024-06-27,2203,5.6,DeepTech Ventures -AI03594,Head of AI,173890,USD,173890,EX,FT,Israel,M,Israel,100,"MLOps, Python, TensorFlow, Data Visualization, GCP",Associate,17,Finance,2024-04-08,2024-05-19,1771,6.1,Cloud AI Solutions -AI03595,Deep Learning Engineer,338945,CHF,305051,EX,FT,Switzerland,M,Switzerland,50,"MLOps, Git, Statistics",Master,14,Government,2024-04-06,2024-06-02,817,9.6,Advanced Robotics -AI03596,AI Architect,140480,USD,140480,SE,PT,South Korea,L,South Korea,50,"Deep Learning, AWS, Tableau, Azure",Master,7,Retail,2024-06-19,2024-08-10,863,5.1,Cognitive Computing -AI03597,Data Engineer,92646,USD,92646,MI,FT,Israel,S,Israel,100,"Spark, R, Statistics",PhD,2,Education,2024-06-07,2024-08-18,832,6.9,Autonomous Tech -AI03598,Data Engineer,54404,USD,54404,EX,PT,India,M,India,0,"PyTorch, MLOps, TensorFlow",PhD,10,Media,2024-05-05,2024-07-17,875,8.9,Machine Intelligence Group -AI03599,AI Specialist,113043,GBP,84782,SE,CT,United Kingdom,M,United Kingdom,0,"Deep Learning, Computer Vision, Tableau, Spark",PhD,8,Consulting,2025-01-30,2025-04-05,1712,8.2,Digital Transformation LLC -AI03600,Data Analyst,159400,EUR,135490,EX,CT,France,S,Turkey,50,"Deep Learning, Mathematics, TensorFlow",Bachelor,14,Real Estate,2025-01-23,2025-02-21,1732,8.4,Machine Intelligence Group -AI03601,Deep Learning Engineer,31170,USD,31170,EN,FL,China,S,South Africa,0,"Kubernetes, TensorFlow, MLOps",PhD,0,Transportation,2024-11-01,2024-12-09,1498,8.8,Advanced Robotics -AI03602,Principal Data Scientist,108438,USD,108438,MI,FL,Sweden,M,Indonesia,0,"Docker, NLP, Python",Bachelor,2,Real Estate,2024-08-02,2024-08-19,1635,8.9,Smart Analytics -AI03603,AI Architect,111346,USD,111346,SE,FT,United States,S,Indonesia,50,"Scala, Python, TensorFlow, Kubernetes, Statistics",Bachelor,7,Retail,2024-11-11,2024-12-01,970,9,Predictive Systems -AI03604,Deep Learning Engineer,223449,USD,223449,EX,FT,Denmark,S,Denmark,0,"Linux, Computer Vision, Git",Associate,16,Real Estate,2024-03-13,2024-04-26,1483,5.9,AI Innovations -AI03605,Computer Vision Engineer,48324,USD,48324,EN,FT,Sweden,S,Poland,50,"Docker, Azure, Tableau, Kubernetes",Bachelor,0,Telecommunications,2024-10-10,2024-11-19,1822,9.4,AI Innovations -AI03606,Autonomous Systems Engineer,66696,AUD,90040,EN,FT,Australia,M,Australia,100,"Docker, Scala, Computer Vision, Git",Bachelor,1,Retail,2024-07-01,2024-07-29,1526,6.5,Smart Analytics -AI03607,AI Research Scientist,210386,USD,210386,EX,CT,Sweden,S,Sweden,50,"Java, Git, GCP",Bachelor,16,Consulting,2024-11-30,2025-02-01,883,8.6,DataVision Ltd -AI03608,Machine Learning Researcher,48698,USD,48698,MI,CT,China,M,China,0,"Python, Java, AWS, NLP",PhD,3,Finance,2024-11-22,2024-12-16,1110,8,Smart Analytics -AI03609,Machine Learning Researcher,60193,EUR,51164,EN,CT,Austria,M,Austria,50,"Python, TensorFlow, Azure, SQL, PyTorch",Bachelor,0,Government,2024-02-12,2024-03-01,526,5.1,Cognitive Computing -AI03610,AI Specialist,60740,USD,60740,EN,PT,United States,M,United States,100,"AWS, R, Deep Learning, Python, Scala",Bachelor,0,Consulting,2024-03-20,2024-05-12,1052,7.3,Future Systems -AI03611,AI Specialist,118920,USD,118920,MI,CT,Norway,S,Canada,0,"Deep Learning, SQL, Statistics, Mathematics, Java",Master,3,Education,2024-08-19,2024-09-15,1491,5.2,Future Systems -AI03612,Principal Data Scientist,87000,AUD,117450,EN,CT,Australia,L,Australia,100,"R, SQL, Tableau",Associate,1,Finance,2024-07-31,2024-09-05,1336,6.9,DataVision Ltd -AI03613,Deep Learning Engineer,204824,USD,204824,EX,CT,Israel,M,Israel,0,"Hadoop, Computer Vision, Python, MLOps, Kubernetes",Bachelor,12,Media,2024-09-20,2024-10-10,1610,8.8,Advanced Robotics -AI03614,Principal Data Scientist,87194,USD,87194,MI,PT,Norway,S,Norway,0,"Computer Vision, Python, Tableau",Associate,2,Technology,2024-07-18,2024-08-07,1333,9.5,Neural Networks Co -AI03615,Autonomous Systems Engineer,232255,USD,232255,EX,CT,Norway,L,Portugal,100,"Deep Learning, Azure, PyTorch",Associate,16,Automotive,2024-05-28,2024-06-28,2132,9,Digital Transformation LLC -AI03616,Data Engineer,101827,USD,101827,MI,FL,Sweden,L,Sweden,50,"Azure, Docker, Git, NLP",Master,4,Telecommunications,2024-10-05,2024-11-08,1136,7.7,Future Systems -AI03617,Head of AI,240245,GBP,180184,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, R, Data Visualization, Computer Vision",PhD,16,Retail,2024-05-06,2024-06-15,1309,8.9,DeepTech Ventures -AI03618,Data Scientist,167576,USD,167576,SE,CT,Sweden,L,Sweden,50,"Tableau, Hadoop, R, Python",Bachelor,9,Energy,2025-03-06,2025-04-25,1628,8.3,Neural Networks Co -AI03619,AI Research Scientist,215103,CAD,268879,EX,CT,Canada,M,Canada,0,"Python, Git, TensorFlow, Docker, Linux",Master,13,Finance,2024-05-31,2024-07-24,1236,8.7,Smart Analytics -AI03620,Machine Learning Engineer,48369,EUR,41114,EN,PT,Austria,S,Austria,0,"GCP, Kubernetes, SQL, Hadoop, Docker",PhD,1,Telecommunications,2024-06-05,2024-07-18,2049,6.2,Quantum Computing Inc -AI03621,Research Scientist,133879,SGD,174043,SE,FT,Singapore,S,Singapore,100,"Docker, Scala, GCP, Deep Learning",Bachelor,9,Automotive,2024-09-25,2024-11-22,1927,5.1,Machine Intelligence Group -AI03622,Machine Learning Researcher,28565,USD,28565,EN,FT,China,L,China,100,"Statistics, Linux, SQL, Scala",Master,0,Healthcare,2025-02-23,2025-03-27,1764,5.4,Cognitive Computing -AI03623,ML Ops Engineer,159550,USD,159550,MI,PT,Denmark,L,Belgium,50,"Tableau, Linux, Kubernetes",PhD,3,Consulting,2024-01-17,2024-03-19,844,9.1,DataVision Ltd -AI03624,ML Ops Engineer,78403,EUR,66643,MI,FL,Netherlands,M,Netherlands,0,"MLOps, GCP, Data Visualization, Git",PhD,2,Automotive,2025-04-11,2025-05-16,1044,6.9,Neural Networks Co -AI03625,Head of AI,87867,USD,87867,EN,CT,Sweden,L,Sweden,50,"Linux, Git, Statistics",Associate,0,Consulting,2025-04-26,2025-07-06,2334,9.2,Algorithmic Solutions -AI03626,Machine Learning Engineer,116358,USD,116358,SE,CT,Israel,L,Norway,50,"NLP, Kubernetes, Docker, Deep Learning, GCP",Bachelor,8,Telecommunications,2025-01-28,2025-03-21,2472,5.1,Future Systems -AI03627,ML Ops Engineer,198454,SGD,257990,EX,PT,Singapore,L,Singapore,50,"Hadoop, Statistics, Mathematics, Kubernetes, R",Bachelor,18,Gaming,2024-02-05,2024-03-06,1969,5.8,AI Innovations -AI03628,Data Analyst,118657,EUR,100858,SE,PT,Germany,M,Germany,100,"MLOps, SQL, Kubernetes, Mathematics",Associate,6,Gaming,2024-12-03,2025-01-19,1755,8.6,DataVision Ltd -AI03629,Research Scientist,86457,USD,86457,EN,CT,Israel,L,Israel,100,"Mathematics, Java, Git, Linux, Computer Vision",Bachelor,1,Media,2024-04-05,2024-05-18,750,8.2,Digital Transformation LLC -AI03630,AI Research Scientist,52898,EUR,44963,EN,PT,France,M,Poland,50,"Scala, Tableau, Computer Vision, Java, Git",PhD,1,Energy,2024-12-15,2025-01-14,1017,7,Machine Intelligence Group -AI03631,Deep Learning Engineer,25159,USD,25159,EN,PT,India,M,India,50,"Data Visualization, Spark, AWS",Master,0,Manufacturing,2024-04-02,2024-06-11,615,5.5,Predictive Systems -AI03632,AI Research Scientist,67708,USD,67708,MI,CT,Ireland,S,Ireland,50,"Python, Java, SQL, Linux",Bachelor,4,Transportation,2024-04-19,2024-05-17,1446,8.5,Smart Analytics -AI03633,Machine Learning Engineer,214023,USD,214023,EX,FL,Denmark,L,South Korea,0,"R, SQL, Tableau, AWS, Java",Bachelor,13,Energy,2025-03-28,2025-04-20,1796,5.7,AI Innovations -AI03634,AI Product Manager,110880,SGD,144144,SE,CT,Singapore,M,Singapore,0,"MLOps, R, Linux, Python",Master,7,Retail,2024-02-15,2024-03-15,843,8.1,Cognitive Computing -AI03635,Data Engineer,49214,USD,49214,EN,CT,South Korea,M,Sweden,50,"AWS, Linux, Kubernetes",PhD,1,Healthcare,2025-01-05,2025-01-21,1103,6.9,Quantum Computing Inc -AI03636,Robotics Engineer,65197,USD,65197,MI,PT,South Korea,S,South Korea,50,"PyTorch, Hadoop, TensorFlow, Java",Associate,4,Technology,2024-12-04,2025-01-15,903,6.8,Quantum Computing Inc -AI03637,AI Consultant,94494,AUD,127567,MI,PT,Australia,S,Spain,50,"Kubernetes, SQL, Tableau",PhD,2,Real Estate,2024-10-10,2024-12-16,1260,6.6,AI Innovations -AI03638,ML Ops Engineer,93560,CHF,84204,EN,FL,Switzerland,M,China,50,"Linux, AWS, Tableau, Spark, Git",Associate,1,Telecommunications,2024-08-20,2024-10-10,1422,7.3,Predictive Systems -AI03639,Deep Learning Engineer,65918,USD,65918,EN,CT,Ireland,S,Ireland,50,"Docker, Python, Mathematics, Kubernetes, Git",Master,1,Retail,2024-11-09,2025-01-18,1621,6,DataVision Ltd -AI03640,AI Product Manager,136380,EUR,115923,SE,FL,Austria,L,Austria,100,"Mathematics, Tableau, Scala",PhD,6,Consulting,2025-01-28,2025-04-04,1271,7.8,DataVision Ltd -AI03641,Computer Vision Engineer,58677,USD,58677,EN,FL,Finland,M,Finland,100,"R, PyTorch, Azure, SQL, Statistics",Master,1,Gaming,2024-06-04,2024-08-02,1115,9.4,Digital Transformation LLC -AI03642,AI Specialist,78838,USD,78838,MI,FT,Israel,M,Israel,0,"Deep Learning, GCP, Git, Python",Bachelor,2,Energy,2024-07-26,2024-09-13,792,8.9,Autonomous Tech -AI03643,AI Architect,269456,USD,269456,EX,CT,Norway,M,Norway,50,"Python, Scala, Azure, Deep Learning, Computer Vision",Bachelor,15,Telecommunications,2024-02-10,2024-04-03,1052,9.8,Cloud AI Solutions -AI03644,AI Research Scientist,134951,USD,134951,SE,FL,Sweden,L,Sweden,100,"Tableau, Deep Learning, GCP, Python, TensorFlow",Bachelor,9,Automotive,2024-01-28,2024-02-13,1296,8.8,Smart Analytics -AI03645,AI Specialist,71037,USD,71037,EN,PT,Ireland,S,Ireland,0,"Hadoop, R, Java",PhD,0,Healthcare,2025-01-27,2025-03-26,2034,8.9,Cognitive Computing -AI03646,Deep Learning Engineer,81347,CHF,73212,EN,FT,Switzerland,M,Finland,0,"Deep Learning, Kubernetes, Linux",PhD,1,Healthcare,2024-12-11,2025-01-15,2320,9,AI Innovations -AI03647,Deep Learning Engineer,42928,USD,42928,MI,PT,China,S,China,0,"Docker, Linux, TensorFlow",Bachelor,3,Government,2024-03-02,2024-05-08,1427,9.3,DeepTech Ventures -AI03648,AI Architect,133466,CAD,166833,SE,PT,Canada,L,Canada,0,"PyTorch, TensorFlow, Azure",Associate,7,Technology,2024-07-25,2024-09-16,1603,5.4,Cloud AI Solutions -AI03649,Robotics Engineer,199990,USD,199990,EX,FT,Norway,M,Norway,100,"Docker, Kubernetes, AWS, Java",Associate,10,Education,2024-11-13,2024-12-07,1983,5.9,Cloud AI Solutions -AI03650,Machine Learning Researcher,146195,USD,146195,EX,FT,Finland,S,Finland,50,"Spark, Statistics, Hadoop",Master,17,Healthcare,2024-10-04,2024-12-07,502,6.8,Digital Transformation LLC -AI03651,NLP Engineer,98140,EUR,83419,EN,FL,Netherlands,L,Netherlands,100,"Kubernetes, R, Tableau, Data Visualization, AWS",Master,1,Finance,2024-01-01,2024-02-06,1249,6,AI Innovations -AI03652,Data Analyst,37739,USD,37739,EN,PT,China,L,China,100,"Linux, Kubernetes, Data Visualization, MLOps",Associate,0,Retail,2024-02-24,2024-03-12,1183,9.1,Neural Networks Co -AI03653,Deep Learning Engineer,76141,USD,76141,MI,CT,Ireland,S,Ireland,50,"Docker, SQL, PyTorch",Associate,4,Manufacturing,2024-02-13,2024-03-10,1482,9.2,Algorithmic Solutions -AI03654,Robotics Engineer,168289,USD,168289,EX,PT,United States,S,United States,50,"Scala, NLP, Git, Kubernetes",Bachelor,15,Transportation,2024-03-11,2024-05-19,924,6,Smart Analytics -AI03655,ML Ops Engineer,35309,USD,35309,MI,CT,India,M,Belgium,0,"Linux, PyTorch, NLP",PhD,4,Government,2025-02-01,2025-03-24,1527,5.1,AI Innovations -AI03656,Head of AI,252143,EUR,214322,EX,CT,Netherlands,M,Netherlands,100,"Docker, Data Visualization, Hadoop, Statistics",Bachelor,13,Automotive,2025-03-08,2025-03-23,1165,5.5,Digital Transformation LLC -AI03657,Robotics Engineer,61954,USD,61954,EN,PT,Sweden,M,Sweden,100,"SQL, MLOps, PyTorch, Hadoop",Master,1,Education,2024-09-16,2024-11-28,1789,9.3,Quantum Computing Inc -AI03658,Deep Learning Engineer,128736,USD,128736,SE,FT,Sweden,S,Turkey,0,"Git, Hadoop, Mathematics, SQL, R",PhD,5,Finance,2024-09-20,2024-11-28,797,6.1,Machine Intelligence Group -AI03659,AI Product Manager,90524,EUR,76945,MI,CT,Germany,L,Philippines,50,"NLP, Java, Deep Learning, Git",Bachelor,3,Consulting,2024-08-02,2024-09-10,2227,5.1,Smart Analytics -AI03660,Machine Learning Researcher,164213,GBP,123160,EX,FT,United Kingdom,M,United Kingdom,0,"Git, Hadoop, MLOps",Associate,19,Retail,2024-07-30,2024-09-22,2447,7.1,Quantum Computing Inc -AI03661,Data Analyst,106152,SGD,137998,MI,FT,Singapore,L,Singapore,0,"R, Git, Linux",Associate,4,Transportation,2025-04-03,2025-06-14,1267,7.2,DeepTech Ventures -AI03662,Robotics Engineer,101811,EUR,86539,SE,CT,France,M,Brazil,50,"Kubernetes, Python, Tableau",Associate,9,Transportation,2024-03-31,2024-05-23,1113,8.1,Neural Networks Co -AI03663,Machine Learning Engineer,130689,JPY,14375790,SE,FT,Japan,M,Argentina,0,"R, Spark, Data Visualization, Statistics, Azure",Master,8,Manufacturing,2024-04-02,2024-05-23,594,9.8,Neural Networks Co -AI03664,NLP Engineer,134597,USD,134597,EX,FL,Finland,S,Finland,0,"GCP, Java, PyTorch",Associate,14,Gaming,2024-03-07,2024-04-01,1997,6.2,TechCorp Inc -AI03665,Data Scientist,127982,USD,127982,SE,PT,South Korea,L,South Korea,50,"Spark, Kubernetes, Git, Tableau, Python",Bachelor,9,Automotive,2024-04-01,2024-06-04,804,9.3,Cognitive Computing -AI03666,AI Software Engineer,76846,USD,76846,EN,PT,United States,L,Sweden,100,"NLP, Deep Learning, Spark, MLOps",Master,0,Manufacturing,2024-04-13,2024-05-17,590,5.2,Cognitive Computing -AI03667,AI Software Engineer,121507,USD,121507,SE,FL,United States,M,United States,100,"Tableau, Kubernetes, AWS, GCP",Associate,7,Telecommunications,2025-02-05,2025-04-09,1356,7.4,Machine Intelligence Group -AI03668,Principal Data Scientist,190021,USD,190021,EX,FL,Norway,S,Norway,100,"Deep Learning, Java, Spark, Git",Associate,15,Transportation,2024-03-23,2024-05-01,789,8.4,Digital Transformation LLC -AI03669,Robotics Engineer,146680,CAD,183350,SE,FT,Canada,L,Spain,50,"Scala, PyTorch, Computer Vision, Hadoop",Master,5,Energy,2024-04-06,2024-05-19,2431,9.9,Autonomous Tech -AI03670,Autonomous Systems Engineer,82088,GBP,61566,EN,CT,United Kingdom,M,United Kingdom,0,"AWS, Linux, MLOps",PhD,1,Manufacturing,2024-01-11,2024-02-08,1485,9.8,Algorithmic Solutions -AI03671,Computer Vision Engineer,142953,USD,142953,SE,CT,Ireland,L,Ireland,50,"Kubernetes, Java, MLOps, GCP, Mathematics",Bachelor,6,Technology,2024-01-16,2024-03-15,1720,8.7,Quantum Computing Inc -AI03672,AI Specialist,178787,USD,178787,EX,PT,Israel,S,Israel,0,"Docker, Data Visualization, NLP",PhD,15,Technology,2025-04-27,2025-06-07,1111,6.5,AI Innovations -AI03673,Data Engineer,216277,EUR,183835,EX,PT,Austria,M,Austria,100,"Git, Java, MLOps",Master,13,Telecommunications,2024-02-23,2024-03-30,1084,8.5,Cognitive Computing -AI03674,Data Scientist,94882,USD,94882,MI,FT,Finland,L,Finland,50,"Data Visualization, Java, Git, Python, SQL",PhD,3,Education,2025-01-15,2025-03-10,985,8.3,Smart Analytics -AI03675,Data Scientist,73031,GBP,54773,EN,PT,United Kingdom,L,United Kingdom,50,"Computer Vision, Tableau, Python, TensorFlow",Associate,1,Education,2024-11-10,2025-01-22,1425,8.3,Smart Analytics -AI03676,Data Engineer,126700,USD,126700,EX,PT,Sweden,S,Sweden,0,"Linux, Hadoop, Python, TensorFlow",Bachelor,17,Manufacturing,2024-05-18,2024-06-18,2292,7,Machine Intelligence Group -AI03677,Head of AI,95630,GBP,71723,MI,FT,United Kingdom,S,United Kingdom,100,"Scala, Mathematics, Java, Spark, AWS",Master,3,Finance,2024-10-28,2025-01-04,2231,7.4,Algorithmic Solutions -AI03678,Deep Learning Engineer,75175,USD,75175,EN,CT,United States,S,United States,100,"NLP, Linux, SQL",Bachelor,1,Transportation,2025-02-10,2025-03-24,807,5.4,DataVision Ltd -AI03679,Machine Learning Engineer,83872,USD,83872,MI,PT,Israel,L,Egypt,0,"Scala, R, Tableau, Mathematics, Linux",PhD,2,Healthcare,2024-07-17,2024-08-22,619,9.7,AI Innovations -AI03680,Data Scientist,156742,USD,156742,SE,FT,Israel,L,Israel,0,"Deep Learning, R, Java",Bachelor,8,Finance,2024-07-07,2024-08-06,857,9.1,Smart Analytics -AI03681,Principal Data Scientist,111290,USD,111290,SE,FT,Finland,M,Finland,50,"R, Kubernetes, Docker, GCP",PhD,6,Telecommunications,2025-01-30,2025-03-02,2301,6.7,Cloud AI Solutions -AI03682,Computer Vision Engineer,83694,GBP,62771,MI,CT,United Kingdom,M,United Kingdom,0,"Scala, SQL, Hadoop",Bachelor,3,Media,2025-03-28,2025-06-04,1440,7.2,AI Innovations -AI03683,Principal Data Scientist,63711,EUR,54154,EN,FT,France,M,France,50,"Scala, SQL, R",PhD,0,Telecommunications,2024-12-14,2025-01-20,1184,6,Algorithmic Solutions -AI03684,Machine Learning Engineer,108037,EUR,91831,MI,FL,Netherlands,M,Netherlands,100,"GCP, SQL, MLOps, Data Visualization",Associate,2,Real Estate,2024-03-29,2024-05-28,929,7.7,Cognitive Computing -AI03685,Machine Learning Engineer,151599,SGD,197079,SE,FL,Singapore,M,Philippines,0,"Hadoop, Scala, SQL, Kubernetes, AWS",Master,5,Healthcare,2025-04-05,2025-05-09,1044,7.1,Quantum Computing Inc -AI03686,AI Architect,113115,EUR,96148,MI,CT,Netherlands,L,Netherlands,50,"Docker, Spark, Hadoop, NLP",Bachelor,3,Energy,2024-04-18,2024-06-23,1096,6.1,Advanced Robotics -AI03687,Head of AI,213162,USD,213162,EX,FL,Israel,M,Israel,0,"Spark, Python, Tableau, Azure",PhD,18,Real Estate,2024-03-20,2024-05-22,744,9.6,Machine Intelligence Group -AI03688,Deep Learning Engineer,172013,AUD,232218,EX,CT,Australia,L,Italy,50,"R, TensorFlow, Linux, Spark, Mathematics",PhD,16,Manufacturing,2024-05-12,2024-06-04,1245,8.3,Cognitive Computing -AI03689,NLP Engineer,81655,USD,81655,EX,PT,China,L,China,0,"Python, Linux, Git, TensorFlow",Bachelor,12,Consulting,2024-12-10,2025-02-02,580,8.6,Advanced Robotics -AI03690,NLP Engineer,70576,EUR,59990,MI,FL,France,S,France,100,"Computer Vision, R, Azure",PhD,2,Energy,2024-07-11,2024-08-19,1274,9.2,Cognitive Computing -AI03691,Machine Learning Engineer,27457,USD,27457,MI,FL,India,M,India,0,"Kubernetes, Java, Azure",Bachelor,4,Education,2025-04-15,2025-06-27,1890,6,Quantum Computing Inc -AI03692,AI Product Manager,115606,SGD,150288,SE,CT,Singapore,M,France,100,"R, SQL, Scala, Mathematics",Associate,9,Retail,2024-11-21,2025-01-17,2279,8.3,Predictive Systems -AI03693,ML Ops Engineer,85378,EUR,72571,EN,PT,Austria,L,Austria,100,"Computer Vision, Git, Kubernetes",Associate,1,Government,2024-07-09,2024-09-08,500,6.6,DeepTech Ventures -AI03694,AI Specialist,305455,CHF,274910,EX,PT,Switzerland,M,Argentina,0,"Git, Azure, Statistics, R",Master,16,Healthcare,2024-03-29,2024-04-12,1280,5.2,DataVision Ltd -AI03695,Robotics Engineer,115424,USD,115424,MI,FT,Finland,L,Finland,0,"Python, Git, Deep Learning, Spark",Bachelor,4,Finance,2024-02-23,2024-03-23,2154,6.3,Autonomous Tech -AI03696,AI Consultant,73524,USD,73524,EN,FL,United States,S,Vietnam,0,"Python, PyTorch, NLP",Bachelor,0,Government,2024-03-05,2024-04-12,757,6.1,AI Innovations -AI03697,AI Research Scientist,164239,EUR,139603,EX,FT,Germany,M,Germany,50,"Python, Computer Vision, Azure, Java",Bachelor,17,Telecommunications,2024-01-09,2024-02-07,542,9.4,Smart Analytics -AI03698,Head of AI,187030,USD,187030,EX,FT,South Korea,S,South Korea,50,"Docker, Python, R, Kubernetes",PhD,17,Retail,2025-01-28,2025-03-06,2173,8.7,Cloud AI Solutions -AI03699,Principal Data Scientist,201791,AUD,272418,EX,CT,Australia,S,Australia,50,"PyTorch, AWS, Python, NLP",Bachelor,12,Automotive,2024-04-06,2024-04-30,1444,9.7,AI Innovations -AI03700,AI Product Manager,189693,USD,189693,EX,FT,Norway,M,Norway,0,"Computer Vision, PyTorch, Spark",Associate,13,Technology,2024-06-30,2024-09-03,2479,7.2,Autonomous Tech -AI03701,Data Engineer,65796,EUR,55927,EN,PT,Austria,L,Austria,0,"Spark, AWS, Linux, TensorFlow, Azure",Associate,1,Real Estate,2025-03-29,2025-06-09,765,9.1,Autonomous Tech -AI03702,Principal Data Scientist,50207,EUR,42676,EN,FT,France,S,France,50,"Docker, Scala, GCP, Mathematics",PhD,0,Gaming,2024-04-03,2024-05-17,2206,8.8,Future Systems -AI03703,Data Scientist,90924,EUR,77285,MI,CT,Germany,M,Germany,0,"Java, R, NLP, GCP, Linux",Bachelor,3,Technology,2024-05-01,2024-05-26,1171,5.2,Future Systems -AI03704,Autonomous Systems Engineer,66161,CAD,82701,MI,FT,Canada,S,Canada,100,"R, Hadoop, TensorFlow, Git, SQL",Associate,4,Education,2024-07-08,2024-08-31,1791,5,Smart Analytics -AI03705,Data Engineer,166384,AUD,224618,EX,CT,Australia,L,Netherlands,100,"NLP, R, Java, Azure",Bachelor,18,Technology,2024-03-24,2024-05-20,2322,9.5,Cognitive Computing -AI03706,Autonomous Systems Engineer,124008,USD,124008,SE,FL,United States,M,United States,50,"Computer Vision, Azure, PyTorch",Master,6,Technology,2024-11-25,2025-02-02,625,8.6,Smart Analytics -AI03707,AI Software Engineer,83812,USD,83812,MI,CT,Ireland,M,Ireland,0,"Kubernetes, SQL, Tableau",PhD,2,Gaming,2024-06-28,2024-09-09,1991,6,Machine Intelligence Group -AI03708,Computer Vision Engineer,142427,SGD,185155,SE,PT,Singapore,S,Singapore,100,"Git, Python, Tableau, Computer Vision",Bachelor,5,Automotive,2024-12-12,2024-12-27,1392,5.8,AI Innovations -AI03709,AI Consultant,186900,USD,186900,SE,PT,Denmark,M,Denmark,100,"PyTorch, Scala, MLOps, Linux",Bachelor,5,Retail,2024-08-17,2024-09-24,1593,7.9,DataVision Ltd -AI03710,AI Specialist,129050,CAD,161313,SE,CT,Canada,M,Canada,0,"SQL, Deep Learning, Kubernetes, Scala",PhD,9,Healthcare,2025-04-18,2025-05-04,835,9.8,Future Systems -AI03711,Machine Learning Engineer,274462,CHF,247016,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Hadoop, Tableau, MLOps",Bachelor,14,Energy,2025-03-17,2025-04-23,2406,6.4,Quantum Computing Inc -AI03712,AI Product Manager,62465,JPY,6871150,EN,CT,Japan,M,Japan,50,"Mathematics, PyTorch, Tableau, Computer Vision, Git",PhD,0,Telecommunications,2024-12-07,2025-01-03,955,7.6,Smart Analytics -AI03713,Principal Data Scientist,73182,USD,73182,MI,PT,Israel,M,Sweden,100,"Linux, TensorFlow, Scala, SQL, Spark",Associate,2,Retail,2025-03-25,2025-04-30,1570,7.7,Neural Networks Co -AI03714,Deep Learning Engineer,184437,GBP,138328,EX,FL,United Kingdom,S,United Kingdom,50,"Linux, Hadoop, Tableau",PhD,17,Consulting,2024-07-07,2024-08-16,1473,5.4,Predictive Systems -AI03715,Robotics Engineer,94373,GBP,70780,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, TensorFlow, Azure",Bachelor,2,Healthcare,2024-06-26,2024-08-01,1713,8.6,DataVision Ltd -AI03716,Autonomous Systems Engineer,222341,EUR,188990,EX,PT,Austria,M,Denmark,100,"Azure, Scala, Data Visualization",Bachelor,16,Media,2025-01-15,2025-03-23,1873,7.3,Machine Intelligence Group -AI03717,Deep Learning Engineer,54047,CAD,67559,EN,PT,Canada,M,Canada,0,"NLP, Deep Learning, Scala, AWS",Bachelor,0,Government,2024-10-26,2025-01-01,804,5.6,Cloud AI Solutions -AI03718,NLP Engineer,127771,USD,127771,SE,CT,Denmark,S,Denmark,50,"SQL, Azure, Linux",Associate,9,Education,2024-07-06,2024-07-21,677,9.1,DataVision Ltd -AI03719,AI Specialist,93985,EUR,79887,MI,CT,France,M,France,50,"Statistics, Kubernetes, MLOps, R",PhD,3,Gaming,2024-02-18,2024-04-07,548,7.2,DataVision Ltd -AI03720,ML Ops Engineer,66798,EUR,56778,MI,PT,Germany,S,Kenya,0,"NLP, SQL, PyTorch, Java, Computer Vision",Associate,4,Technology,2024-06-03,2024-07-24,1988,5.5,AI Innovations -AI03721,Machine Learning Engineer,155058,USD,155058,SE,FL,Sweden,L,Sweden,100,"Statistics, Kubernetes, GCP, AWS",PhD,7,Gaming,2025-03-15,2025-04-15,1894,5.5,Cloud AI Solutions -AI03722,ML Ops Engineer,280160,JPY,30817600,EX,PT,Japan,L,Japan,0,"Mathematics, Tableau, Linux, Data Visualization",PhD,15,Manufacturing,2024-10-02,2024-11-21,2398,5.6,TechCorp Inc -AI03723,Autonomous Systems Engineer,77244,EUR,65657,MI,FL,France,S,France,50,"Spark, Tableau, TensorFlow, Data Visualization",Associate,4,Manufacturing,2024-01-19,2024-03-23,769,8.2,Cloud AI Solutions -AI03724,Autonomous Systems Engineer,216834,USD,216834,EX,FL,Israel,M,Estonia,100,"Kubernetes, Mathematics, Python",PhD,11,Manufacturing,2025-04-20,2025-07-02,1824,6.6,DeepTech Ventures -AI03725,AI Product Manager,110485,USD,110485,MI,FT,United States,L,Norway,50,"Python, TensorFlow, Spark, PyTorch, NLP",Master,2,Transportation,2024-06-16,2024-07-24,2063,8.6,Neural Networks Co -AI03726,Computer Vision Engineer,43499,USD,43499,SE,FT,China,S,China,50,"SQL, Java, Kubernetes, TensorFlow, Tableau",Bachelor,7,Media,2025-03-24,2025-05-27,537,5.1,DeepTech Ventures -AI03727,Computer Vision Engineer,266981,GBP,200236,EX,PT,United Kingdom,L,United Kingdom,0,"Data Visualization, Java, Spark",Bachelor,13,Telecommunications,2024-10-06,2024-11-05,1978,9.5,Algorithmic Solutions -AI03728,Machine Learning Researcher,126042,USD,126042,SE,FT,Finland,M,Finland,50,"Git, Docker, MLOps, Mathematics, Kubernetes",Associate,8,Automotive,2024-08-28,2024-10-08,1314,7.2,Neural Networks Co -AI03729,AI Specialist,173706,CAD,217133,EX,FL,Canada,S,Canada,50,"Kubernetes, Python, Azure, R, Mathematics",Master,10,Media,2025-01-20,2025-02-22,2026,8.8,Cloud AI Solutions -AI03730,AI Architect,75161,AUD,101467,EN,FT,Australia,M,Portugal,0,"GCP, Python, NLP",Associate,0,Real Estate,2025-02-10,2025-04-22,2388,5.6,Cloud AI Solutions -AI03731,Autonomous Systems Engineer,115030,USD,115030,SE,FT,Israel,M,Israel,50,"Git, TensorFlow, Tableau, Docker",Associate,7,Media,2024-09-07,2024-10-15,623,7.8,Machine Intelligence Group -AI03732,AI Product Manager,151796,AUD,204925,SE,FT,Australia,M,Australia,0,"Python, Kubernetes, Tableau, Computer Vision",PhD,8,Real Estate,2025-03-24,2025-05-26,2435,6.3,Algorithmic Solutions -AI03733,AI Research Scientist,59337,USD,59337,SE,FL,China,M,China,100,"GCP, MLOps, Tableau, R, Hadoop",Master,8,Government,2024-12-23,2025-01-22,617,9.7,Advanced Robotics -AI03734,Robotics Engineer,84211,CHF,75790,EN,PT,Switzerland,L,Finland,100,"TensorFlow, Python, Git",Bachelor,0,Real Estate,2025-03-13,2025-05-18,2309,9.8,AI Innovations -AI03735,Data Analyst,121798,CAD,152248,SE,PT,Canada,S,Sweden,50,"Linux, Tableau, AWS",Associate,5,Media,2025-04-13,2025-06-06,2077,9.9,TechCorp Inc -AI03736,Principal Data Scientist,198790,USD,198790,EX,PT,Israel,M,Ireland,50,"Python, Data Visualization, TensorFlow, Deep Learning, AWS",Associate,11,Government,2024-08-12,2024-10-16,2155,7.2,Autonomous Tech -AI03737,Data Engineer,80590,USD,80590,EN,CT,Norway,L,Thailand,0,"SQL, Spark, MLOps, Statistics, Python",Bachelor,1,Gaming,2024-10-07,2024-11-03,865,8.8,Algorithmic Solutions -AI03738,Principal Data Scientist,158320,EUR,134572,EX,CT,Germany,M,Colombia,50,"SQL, Python, MLOps, Deep Learning",Associate,19,Automotive,2024-01-26,2024-03-16,2065,5.4,Machine Intelligence Group -AI03739,AI Software Engineer,28067,USD,28067,MI,CT,India,S,South Africa,0,"Python, Deep Learning, Scala, Azure, Git",Master,3,Real Estate,2024-12-31,2025-01-19,928,8.1,Quantum Computing Inc -AI03740,Machine Learning Researcher,221734,EUR,188474,EX,FL,France,M,France,100,"MLOps, Hadoop, Python",Bachelor,12,Media,2024-11-12,2024-12-30,1964,8.2,Digital Transformation LLC -AI03741,Research Scientist,66023,USD,66023,EN,CT,South Korea,L,South Korea,100,"PyTorch, TensorFlow, R, Git, Data Visualization",Master,1,Energy,2024-06-22,2024-08-07,820,6,Smart Analytics -AI03742,Machine Learning Engineer,79053,EUR,67195,MI,PT,Austria,M,Austria,100,"Statistics, PyTorch, Azure, Linux, TensorFlow",Master,4,Finance,2024-01-26,2024-03-11,1071,7.5,Quantum Computing Inc -AI03743,AI Specialist,90414,USD,90414,SE,CT,South Korea,M,South Korea,100,"Statistics, TensorFlow, Hadoop",Master,9,Healthcare,2024-07-03,2024-07-28,2008,7.4,TechCorp Inc -AI03744,Head of AI,44966,EUR,38221,EN,CT,France,S,France,0,"PyTorch, TensorFlow, Kubernetes, Scala, Java",Bachelor,1,Healthcare,2024-06-16,2024-08-03,1948,7.6,Quantum Computing Inc -AI03745,Principal Data Scientist,135292,USD,135292,SE,FL,United States,M,Egypt,100,"Deep Learning, Kubernetes, AWS, Scala, NLP",Bachelor,6,Transportation,2024-06-25,2024-07-31,846,9.2,Cloud AI Solutions -AI03746,Principal Data Scientist,224798,EUR,191078,EX,PT,France,M,France,0,"Mathematics, Git, Docker",PhD,19,Media,2024-12-04,2024-12-26,802,6.9,Cloud AI Solutions -AI03747,Deep Learning Engineer,169956,AUD,229441,EX,FT,Australia,S,Australia,100,"Spark, Java, Docker, Computer Vision",Bachelor,10,Gaming,2025-01-26,2025-03-06,750,6.9,Predictive Systems -AI03748,Data Scientist,218143,SGD,283586,EX,FT,Singapore,L,Singapore,0,"Spark, Tableau, Python",Master,19,Energy,2024-05-10,2024-07-17,2434,5.6,AI Innovations -AI03749,AI Research Scientist,123186,EUR,104708,SE,PT,Germany,S,United States,0,"Git, Docker, SQL, Kubernetes",Bachelor,5,Consulting,2024-10-14,2024-11-07,1709,8,Digital Transformation LLC -AI03750,Robotics Engineer,69645,CAD,87056,MI,FT,Canada,S,Canada,100,"Git, Scala, Spark",PhD,2,Automotive,2024-09-09,2024-11-06,1857,8.9,Cloud AI Solutions -AI03751,Head of AI,157091,EUR,133527,EX,PT,Austria,L,Austria,0,"Statistics, Tableau, SQL, Hadoop",PhD,16,Telecommunications,2024-12-21,2025-01-24,888,9.3,TechCorp Inc -AI03752,AI Specialist,90830,EUR,77206,MI,CT,Germany,L,China,50,"Azure, PyTorch, NLP",Associate,4,Retail,2025-03-29,2025-05-26,1841,9.2,Advanced Robotics -AI03753,Deep Learning Engineer,249590,EUR,212152,EX,PT,Netherlands,M,Netherlands,0,"Hadoop, Docker, Data Visualization",PhD,17,Transportation,2025-03-10,2025-03-24,2428,6.1,DeepTech Ventures -AI03754,Computer Vision Engineer,123791,USD,123791,SE,PT,Israel,M,Israel,0,"Linux, AWS, MLOps, Azure, Kubernetes",Bachelor,7,Finance,2024-06-17,2024-08-20,1043,7,Machine Intelligence Group -AI03755,Head of AI,117223,USD,117223,SE,PT,Finland,S,Finland,100,"Docker, MLOps, Computer Vision, Statistics",Bachelor,5,Education,2024-10-17,2024-11-06,2009,9.4,Future Systems -AI03756,NLP Engineer,27366,USD,27366,MI,CT,India,S,India,100,"Data Visualization, Scala, R",PhD,3,Energy,2024-06-04,2024-08-09,2448,6.5,Smart Analytics -AI03757,Machine Learning Researcher,182032,EUR,154727,EX,CT,Austria,L,Austria,0,"MLOps, SQL, AWS, NLP, Spark",Master,13,Consulting,2024-07-27,2024-10-02,1455,8.9,Advanced Robotics -AI03758,Data Analyst,31017,USD,31017,MI,FT,India,L,India,0,"Java, SQL, Deep Learning, PyTorch, Azure",Master,2,Gaming,2024-09-14,2024-10-26,669,5.8,Machine Intelligence Group -AI03759,Head of AI,148948,USD,148948,EX,CT,Finland,S,Finland,100,"Spark, R, MLOps",PhD,16,Technology,2024-06-21,2024-08-14,2352,7.5,Predictive Systems -AI03760,Data Engineer,126217,CHF,113595,MI,CT,Switzerland,L,Switzerland,50,"TensorFlow, Kubernetes, NLP, Deep Learning, Statistics",Bachelor,3,Energy,2024-10-30,2024-12-14,1310,8.9,Neural Networks Co -AI03761,AI Research Scientist,85615,EUR,72773,MI,PT,France,M,France,100,"Deep Learning, NLP, MLOps, Statistics, Kubernetes",Master,3,Gaming,2024-10-17,2024-11-24,2387,9.4,Predictive Systems -AI03762,Deep Learning Engineer,224102,USD,224102,EX,CT,Sweden,M,Sweden,100,"Tableau, Computer Vision, R",Bachelor,17,Government,2024-04-24,2024-05-16,1525,10,Smart Analytics -AI03763,Autonomous Systems Engineer,67594,EUR,57455,EN,PT,Germany,M,Germany,0,"Git, Deep Learning, Python, Tableau",Associate,1,Retail,2024-11-03,2024-11-25,2297,9.8,Cloud AI Solutions -AI03764,Autonomous Systems Engineer,172931,EUR,146991,EX,CT,Germany,S,Germany,100,"Java, Scala, Statistics, Data Visualization",Bachelor,19,Real Estate,2024-08-15,2024-09-13,992,5.9,Future Systems -AI03765,AI Research Scientist,109233,SGD,142003,SE,FT,Singapore,S,Singapore,50,"Python, TensorFlow, R, SQL",PhD,9,Healthcare,2024-07-02,2024-09-12,1286,5.7,Quantum Computing Inc -AI03766,AI Architect,240499,SGD,312649,EX,FT,Singapore,L,Singapore,100,"Hadoop, PyTorch, SQL, R, MLOps",Associate,18,Media,2025-04-28,2025-05-27,2292,7.4,Advanced Robotics -AI03767,Autonomous Systems Engineer,92133,USD,92133,EN,PT,Denmark,M,Denmark,100,"Java, Git, Statistics, R",PhD,1,Education,2025-03-09,2025-05-08,1048,7.5,DeepTech Ventures -AI03768,Machine Learning Researcher,76049,USD,76049,EX,PT,India,M,India,50,"NLP, Python, Linux, Data Visualization",Bachelor,12,Telecommunications,2024-01-07,2024-02-06,1742,5.8,TechCorp Inc -AI03769,Machine Learning Researcher,272882,AUD,368391,EX,CT,Australia,L,Australia,50,"R, SQL, Spark",PhD,19,Transportation,2025-01-29,2025-03-22,656,6.3,Quantum Computing Inc -AI03770,AI Specialist,60278,USD,60278,MI,CT,South Korea,S,South Korea,100,"Spark, NLP, Linux, Kubernetes",Associate,2,Manufacturing,2024-08-11,2024-10-18,1855,9.2,Machine Intelligence Group -AI03771,AI Product Manager,232998,USD,232998,EX,FT,Norway,L,South Africa,50,"Git, SQL, Deep Learning, Scala",Associate,17,Government,2024-08-14,2024-10-18,1447,6.5,Quantum Computing Inc -AI03772,AI Software Engineer,125478,SGD,163121,SE,CT,Singapore,S,Singapore,100,"R, Linux, SQL, Statistics, Deep Learning",Master,9,Consulting,2025-03-23,2025-04-09,703,6.9,Smart Analytics -AI03773,AI Consultant,80666,EUR,68566,MI,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, SQL, R, GCP",Associate,3,Healthcare,2024-03-24,2024-05-11,1026,7.3,TechCorp Inc -AI03774,AI Software Engineer,130187,CHF,117168,MI,CT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Linux, SQL",Associate,4,Consulting,2024-11-19,2025-01-06,1055,5.3,Future Systems -AI03775,Data Analyst,112669,USD,112669,MI,FT,Finland,L,Japan,50,"SQL, Git, TensorFlow, NLP, AWS",Associate,4,Gaming,2025-01-02,2025-02-06,1107,8.8,Machine Intelligence Group -AI03776,AI Research Scientist,117310,CAD,146638,MI,FT,Canada,L,Canada,100,"Python, Azure, NLP",PhD,2,Technology,2024-11-27,2024-12-28,1372,7,Predictive Systems -AI03777,Autonomous Systems Engineer,104436,USD,104436,EN,FL,United States,L,United States,100,"Scala, PyTorch, SQL, AWS",Master,1,Consulting,2024-11-09,2024-12-07,2286,9.8,Cognitive Computing -AI03778,Robotics Engineer,151858,USD,151858,SE,FT,Denmark,L,Denmark,50,"GCP, Data Visualization, MLOps, SQL, Linux",Master,7,Education,2024-09-25,2024-10-12,2069,8,Cloud AI Solutions -AI03779,AI Software Engineer,300122,USD,300122,EX,FL,United States,L,United States,100,"Linux, Data Visualization, Kubernetes",Bachelor,11,Manufacturing,2025-04-12,2025-05-24,1771,8.4,Machine Intelligence Group -AI03780,Research Scientist,123704,USD,123704,MI,PT,United States,M,India,100,"Python, GCP, TensorFlow, Linux, PyTorch",PhD,4,Energy,2024-05-11,2024-05-27,1820,5.6,Quantum Computing Inc -AI03781,NLP Engineer,123407,CAD,154259,SE,PT,Canada,M,Canada,100,"Mathematics, Python, MLOps, SQL, Linux",Bachelor,7,Energy,2024-11-04,2024-11-23,2275,5.9,TechCorp Inc -AI03782,AI Research Scientist,113350,SGD,147355,SE,PT,Singapore,S,Singapore,100,"Scala, Mathematics, Data Visualization, Deep Learning, Java",Bachelor,8,Real Estate,2025-03-23,2025-05-19,1968,7.3,AI Innovations -AI03783,Principal Data Scientist,240944,JPY,26503840,EX,CT,Japan,M,Japan,50,"MLOps, Statistics, Linux",PhD,17,Education,2025-03-05,2025-03-23,1690,6.5,Smart Analytics -AI03784,Autonomous Systems Engineer,56468,USD,56468,MI,FT,China,L,China,100,"R, NLP, TensorFlow, Data Visualization",Master,2,Media,2024-09-06,2024-10-30,1620,9.1,Quantum Computing Inc -AI03785,AI Specialist,23467,USD,23467,EN,FL,India,S,India,0,"Azure, Linux, Computer Vision, AWS, Docker",Bachelor,1,Education,2025-03-22,2025-04-08,1780,8.7,Predictive Systems -AI03786,AI Product Manager,41589,USD,41589,SE,FT,India,S,India,100,"Java, GCP, Azure, PyTorch, Mathematics",PhD,5,Manufacturing,2024-05-18,2024-06-25,1576,7.1,TechCorp Inc -AI03787,Autonomous Systems Engineer,56436,USD,56436,SE,FL,India,L,South Korea,50,"Git, PyTorch, Azure, Data Visualization",PhD,6,Telecommunications,2024-03-05,2024-04-02,2128,8.9,Autonomous Tech -AI03788,Deep Learning Engineer,102052,USD,102052,EN,FT,Denmark,M,Denmark,50,"Scala, Computer Vision, GCP, Git",Master,0,Finance,2025-03-07,2025-03-26,2234,9.6,Cognitive Computing -AI03789,Data Engineer,140417,GBP,105313,SE,PT,United Kingdom,M,New Zealand,0,"SQL, MLOps, PyTorch",Bachelor,5,Energy,2024-10-03,2024-12-15,939,6.5,Predictive Systems -AI03790,Head of AI,62079,USD,62079,EN,CT,Finland,L,Finland,100,"Deep Learning, Kubernetes, Python, AWS",Master,0,Media,2024-01-29,2024-04-05,845,8.3,Advanced Robotics -AI03791,Robotics Engineer,181941,GBP,136456,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Hadoop, SQL",Bachelor,9,Transportation,2024-09-15,2024-11-16,1538,7.2,Cloud AI Solutions -AI03792,Deep Learning Engineer,48759,USD,48759,EN,CT,South Korea,S,South Korea,50,"Kubernetes, Deep Learning, Python",PhD,0,Gaming,2024-06-28,2024-07-21,891,6.7,Smart Analytics -AI03793,Data Engineer,94775,EUR,80559,SE,PT,France,S,France,50,"Statistics, AWS, Spark, Deep Learning",PhD,8,Retail,2024-07-01,2024-08-29,1544,6.4,AI Innovations -AI03794,AI Specialist,111479,JPY,12262690,SE,FL,Japan,S,Poland,100,"Git, Java, GCP, Deep Learning",Master,6,Technology,2024-06-18,2024-08-13,568,9.1,Algorithmic Solutions -AI03795,Data Analyst,196602,USD,196602,EX,CT,Finland,M,Philippines,50,"Statistics, PyTorch, Git, Mathematics",Master,15,Manufacturing,2024-05-29,2024-06-12,1304,5.3,Advanced Robotics -AI03796,Principal Data Scientist,264173,EUR,224547,EX,PT,France,L,France,100,"Mathematics, Python, TensorFlow, MLOps, NLP",PhD,15,Technology,2024-12-15,2025-02-17,2407,9.6,DeepTech Ventures -AI03797,Head of AI,69502,SGD,90353,EN,CT,Singapore,M,Singapore,0,"Hadoop, SQL, PyTorch, Scala, R",PhD,1,Education,2024-12-31,2025-01-23,1948,8.8,Smart Analytics -AI03798,ML Ops Engineer,130004,EUR,110503,SE,PT,Germany,S,Italy,50,"MLOps, SQL, Python",PhD,6,Retail,2024-01-06,2024-02-03,1868,9.7,AI Innovations -AI03799,AI Product Manager,225220,USD,225220,EX,CT,Finland,M,Finland,0,"GCP, Python, TensorFlow, Hadoop, Deep Learning",PhD,11,Real Estate,2024-11-18,2025-01-02,699,8.5,AI Innovations -AI03800,Robotics Engineer,96826,SGD,125874,MI,CT,Singapore,M,Singapore,0,"GCP, PyTorch, Azure, R",PhD,3,Finance,2024-04-13,2024-05-26,1526,5.2,Digital Transformation LLC -AI03801,Machine Learning Engineer,56293,EUR,47849,EN,FL,Germany,S,Estonia,50,"SQL, Data Visualization, R, Computer Vision, NLP",PhD,1,Technology,2024-05-16,2024-07-11,1637,5.2,DeepTech Ventures -AI03802,Principal Data Scientist,197669,USD,197669,EX,FT,Denmark,M,Denmark,50,"Kubernetes, PyTorch, SQL, Docker",Bachelor,17,Real Estate,2025-04-11,2025-05-24,909,7.5,TechCorp Inc -AI03803,Machine Learning Engineer,129726,SGD,168644,SE,FL,Singapore,M,Singapore,50,"Python, Scala, GCP, R",Master,8,Government,2024-08-30,2024-10-26,967,5.1,Autonomous Tech -AI03804,AI Product Manager,146815,USD,146815,EX,PT,Sweden,S,Indonesia,0,"Computer Vision, PyTorch, Scala",Master,12,Consulting,2025-03-02,2025-04-17,850,5.4,Machine Intelligence Group -AI03805,Data Scientist,108448,USD,108448,SE,FT,Finland,S,Finland,100,"Python, TensorFlow, AWS, NLP, Computer Vision",Master,5,Real Estate,2024-04-18,2024-05-12,2123,9.9,DataVision Ltd -AI03806,NLP Engineer,56987,GBP,42740,EN,CT,United Kingdom,S,Romania,0,"Linux, Tableau, TensorFlow, Deep Learning, Git",Master,0,Manufacturing,2024-02-05,2024-02-29,579,5.1,DeepTech Ventures -AI03807,Research Scientist,109575,USD,109575,SE,CT,Finland,S,Finland,0,"Hadoop, SQL, Python, Tableau, Deep Learning",Bachelor,6,Automotive,2024-10-19,2024-12-13,2369,9.7,Machine Intelligence Group -AI03808,AI Research Scientist,61632,USD,61632,EN,CT,Israel,L,Israel,50,"GCP, R, Tableau, Data Visualization, PyTorch",Bachelor,1,Real Estate,2024-10-26,2024-12-29,1601,6.6,Cognitive Computing -AI03809,Research Scientist,86859,USD,86859,MI,CT,Sweden,M,Sweden,0,"NLP, R, AWS, Linux, Deep Learning",Master,4,Technology,2024-06-27,2024-08-25,1979,7.7,Predictive Systems -AI03810,Data Analyst,93901,EUR,79816,MI,PT,Austria,M,Austria,100,"Python, Scala, Git",Bachelor,2,Gaming,2024-04-22,2024-05-17,2379,5,DeepTech Ventures -AI03811,Machine Learning Researcher,78383,USD,78383,SE,CT,South Korea,S,Austria,0,"Azure, Python, MLOps, R",Bachelor,9,Government,2024-10-30,2024-12-25,2250,6.8,Algorithmic Solutions -AI03812,Data Scientist,105143,USD,105143,EX,CT,China,L,China,0,"Deep Learning, Tableau, TensorFlow, R",Bachelor,13,Manufacturing,2024-06-08,2024-07-22,1396,9.6,Cognitive Computing -AI03813,AI Product Manager,113830,EUR,96756,SE,PT,France,M,Ukraine,0,"SQL, Hadoop, TensorFlow, Data Visualization, Linux",Associate,5,Healthcare,2024-10-06,2024-11-15,2416,7.3,Cloud AI Solutions -AI03814,Research Scientist,104205,EUR,88574,MI,FT,Netherlands,M,Romania,0,"Python, Docker, Tableau",Bachelor,4,Education,2025-02-10,2025-04-12,1015,6.6,Autonomous Tech -AI03815,Data Scientist,76948,USD,76948,MI,FL,Finland,S,Finland,0,"Deep Learning, Python, GCP, TensorFlow, Linux",Associate,3,Healthcare,2024-07-30,2024-09-14,2006,9.8,DataVision Ltd -AI03816,Data Scientist,158361,CAD,197951,SE,FT,Canada,L,Austria,100,"Spark, Python, Tableau, TensorFlow, GCP",Master,6,Energy,2024-06-26,2024-08-25,950,7.2,Digital Transformation LLC -AI03817,ML Ops Engineer,246286,USD,246286,EX,PT,Sweden,M,Sweden,100,"Scala, Spark, PyTorch, GCP",Associate,15,Gaming,2024-05-17,2024-07-22,1743,9.9,Advanced Robotics -AI03818,AI Architect,29444,USD,29444,MI,PT,India,M,India,50,"Git, Python, MLOps, NLP",Associate,3,Technology,2025-01-21,2025-02-24,1338,5.3,Machine Intelligence Group -AI03819,Data Scientist,65572,USD,65572,EX,PT,India,L,India,100,"NLP, Kubernetes, Data Visualization",PhD,10,Manufacturing,2025-03-06,2025-05-12,1167,8.5,Autonomous Tech -AI03820,AI Research Scientist,89996,EUR,76497,MI,FL,Austria,M,Austria,0,"MLOps, GCP, Python, TensorFlow, Computer Vision",PhD,3,Energy,2024-06-03,2024-07-11,1872,8.5,Neural Networks Co -AI03821,Head of AI,251600,EUR,213860,EX,FL,Germany,M,Germany,50,"PyTorch, Kubernetes, NLP",Associate,16,Energy,2024-07-03,2024-07-22,634,8.1,Advanced Robotics -AI03822,Principal Data Scientist,97239,GBP,72929,EN,FL,United Kingdom,L,United Kingdom,0,"Hadoop, Scala, Spark, TensorFlow, Tableau",Bachelor,0,Transportation,2024-09-19,2024-11-14,1174,7.8,Cloud AI Solutions -AI03823,Research Scientist,117805,JPY,12958550,SE,FL,Japan,S,Japan,100,"Linux, Azure, Python, Computer Vision",Associate,8,Energy,2024-07-31,2024-09-28,1354,7.7,Autonomous Tech -AI03824,Deep Learning Engineer,124143,USD,124143,MI,CT,United States,M,Finland,100,"Scala, Python, Computer Vision",PhD,2,Automotive,2024-03-20,2024-04-26,1879,9.1,Quantum Computing Inc -AI03825,Robotics Engineer,119551,USD,119551,SE,PT,Sweden,S,Sweden,50,"AWS, Azure, Python, TensorFlow, MLOps",PhD,9,Media,2024-03-28,2024-04-22,1443,8.8,DataVision Ltd -AI03826,NLP Engineer,122489,USD,122489,MI,PT,Ireland,L,Mexico,50,"Linux, Git, Tableau",Master,2,Retail,2024-01-20,2024-02-24,2181,8.3,AI Innovations -AI03827,AI Product Manager,297922,USD,297922,EX,CT,Denmark,L,Denmark,0,"Linux, Java, Tableau, Spark",Master,19,Finance,2024-02-01,2024-02-17,868,9.1,Cloud AI Solutions -AI03828,Autonomous Systems Engineer,284790,CHF,256311,EX,FT,Switzerland,M,Switzerland,100,"Tableau, Computer Vision, Git, MLOps, GCP",Associate,12,Real Estate,2024-03-17,2024-05-02,1087,6,DeepTech Ventures -AI03829,Machine Learning Engineer,140500,SGD,182650,SE,FT,Singapore,S,Singapore,100,"Scala, GCP, Data Visualization, Deep Learning, Mathematics",PhD,8,Energy,2024-11-11,2024-12-25,2434,7.7,AI Innovations -AI03830,NLP Engineer,116663,CHF,104997,MI,PT,Switzerland,S,Finland,50,"Kubernetes, Java, Spark",Master,4,Technology,2025-04-06,2025-06-05,899,6.3,Algorithmic Solutions -AI03831,AI Product Manager,136106,USD,136106,SE,FT,Norway,S,Norway,0,"TensorFlow, Statistics, Linux",Bachelor,6,Energy,2024-01-17,2024-02-09,1312,8.2,AI Innovations -AI03832,AI Specialist,120352,AUD,162475,SE,FL,Australia,S,United Kingdom,0,"Python, TensorFlow, Data Visualization",Associate,8,Technology,2025-02-22,2025-04-20,1026,5.1,Algorithmic Solutions -AI03833,Principal Data Scientist,115824,USD,115824,EX,PT,Finland,S,Finland,100,"Azure, Mathematics, GCP",Associate,10,Energy,2024-10-24,2024-12-23,1678,9.8,Advanced Robotics -AI03834,Data Engineer,192495,USD,192495,EX,PT,Israel,S,Israel,100,"SQL, Data Visualization, Spark, PyTorch",Associate,16,Government,2025-02-21,2025-03-13,1136,9.2,Autonomous Tech -AI03835,AI Consultant,70175,USD,70175,EN,CT,Finland,L,Finland,50,"Python, TensorFlow, MLOps, Tableau",Associate,0,Gaming,2024-03-27,2024-05-07,1939,5.9,Digital Transformation LLC -AI03836,Deep Learning Engineer,36741,USD,36741,MI,FL,India,M,India,100,"Azure, AWS, Spark, Hadoop, GCP",PhD,3,Consulting,2024-01-13,2024-02-01,825,8.6,Quantum Computing Inc -AI03837,Research Scientist,60568,USD,60568,EN,CT,Finland,L,Finland,100,"TensorFlow, SQL, Spark, Mathematics",Master,1,Government,2024-03-06,2024-04-17,1308,5.3,DeepTech Ventures -AI03838,Autonomous Systems Engineer,56833,USD,56833,EN,CT,Israel,M,Israel,50,"Statistics, Mathematics, Deep Learning, Python, TensorFlow",Associate,1,Gaming,2025-02-06,2025-03-19,1659,9.3,Machine Intelligence Group -AI03839,AI Research Scientist,138563,SGD,180132,SE,FT,Singapore,S,Singapore,100,"Tableau, SQL, Computer Vision",Associate,5,Consulting,2024-02-17,2024-03-16,1786,6.1,Machine Intelligence Group -AI03840,Autonomous Systems Engineer,69031,EUR,58676,MI,FL,Germany,S,Germany,50,"NLP, TensorFlow, Scala, Mathematics, R",PhD,3,Telecommunications,2024-09-25,2024-11-09,1921,7.4,Future Systems -AI03841,Principal Data Scientist,49258,USD,49258,EN,CT,Sweden,S,Sweden,100,"R, Docker, Python, Scala, Kubernetes",Bachelor,1,Consulting,2025-01-30,2025-04-04,1364,8.6,Advanced Robotics -AI03842,Machine Learning Engineer,177507,USD,177507,EX,FT,Sweden,M,Sweden,50,"Deep Learning, SQL, PyTorch, Git",Master,16,Gaming,2025-03-13,2025-04-11,1788,7,Cloud AI Solutions -AI03843,Robotics Engineer,278819,USD,278819,EX,CT,Denmark,M,Netherlands,100,"Computer Vision, Hadoop, R",Bachelor,12,Finance,2024-01-23,2024-03-02,1360,6.4,Algorithmic Solutions -AI03844,Data Analyst,101827,JPY,11200970,MI,PT,Japan,M,Japan,50,"Azure, PyTorch, MLOps, Python",Bachelor,4,Gaming,2024-06-07,2024-07-20,1347,5.8,Advanced Robotics -AI03845,Data Engineer,84062,SGD,109281,EN,CT,Singapore,L,Singapore,0,"Kubernetes, Deep Learning, PyTorch, TensorFlow",Bachelor,0,Real Estate,2024-04-26,2024-05-27,2252,8.9,Cognitive Computing -AI03846,Deep Learning Engineer,102646,CHF,92381,MI,PT,Switzerland,S,Spain,50,"Hadoop, Linux, SQL, Python, Java",Bachelor,4,Healthcare,2024-12-26,2025-01-15,2383,6.6,AI Innovations -AI03847,AI Architect,95477,USD,95477,MI,CT,Norway,M,Norway,0,"GCP, TensorFlow, MLOps",Master,4,Gaming,2024-05-23,2024-08-01,1534,8.4,DeepTech Ventures -AI03848,Autonomous Systems Engineer,46111,USD,46111,SE,FL,China,S,China,0,"Spark, Kubernetes, Linux, Mathematics",Master,6,Transportation,2025-01-07,2025-01-25,518,5.9,Machine Intelligence Group -AI03849,Machine Learning Researcher,97023,EUR,82470,MI,FL,Netherlands,M,South Korea,50,"Python, TensorFlow, Linux, PyTorch, Mathematics",PhD,3,Retail,2024-07-31,2024-09-17,2239,8.7,DataVision Ltd -AI03850,Robotics Engineer,220428,USD,220428,EX,CT,Finland,M,Russia,100,"PyTorch, NLP, Statistics, TensorFlow",PhD,18,Energy,2025-01-14,2025-02-15,2110,8.2,Future Systems -AI03851,Data Analyst,111944,USD,111944,MI,FT,United States,L,Japan,50,"GCP, Java, Python, Tableau",PhD,4,Energy,2024-01-19,2024-03-13,1258,6.3,Algorithmic Solutions -AI03852,AI Product Manager,186617,GBP,139963,EX,FL,United Kingdom,L,United Kingdom,100,"AWS, Mathematics, Python",Bachelor,18,Government,2024-01-14,2024-03-23,1910,6.5,Smart Analytics -AI03853,Data Analyst,161013,EUR,136861,EX,FL,Netherlands,M,Netherlands,100,"SQL, Spark, NLP",Bachelor,18,Real Estate,2024-07-04,2024-08-13,1215,7.1,Digital Transformation LLC -AI03854,Principal Data Scientist,30458,USD,30458,MI,FL,India,S,India,100,"Kubernetes, NLP, SQL",Master,2,Consulting,2024-07-30,2024-09-27,1135,8.8,Algorithmic Solutions -AI03855,Research Scientist,64590,USD,64590,EN,FL,Israel,S,Israel,100,"Kubernetes, MLOps, Computer Vision, Azure",PhD,0,Technology,2024-01-17,2024-03-23,2116,9.5,Quantum Computing Inc -AI03856,ML Ops Engineer,113088,USD,113088,SE,PT,South Korea,S,Russia,0,"PyTorch, Kubernetes, Scala, Java, AWS",PhD,6,Automotive,2024-06-19,2024-07-07,2410,8.2,Autonomous Tech -AI03857,Research Scientist,110516,EUR,93939,MI,CT,Netherlands,L,Netherlands,0,"Python, SQL, Java, GCP, Docker",Associate,3,Media,2025-04-16,2025-05-10,1068,7.3,Future Systems -AI03858,Data Analyst,33400,USD,33400,EN,PT,China,S,China,0,"Statistics, Docker, PyTorch, AWS, Python",Associate,1,Consulting,2024-08-30,2024-10-12,2143,9.2,DataVision Ltd -AI03859,Research Scientist,57862,CAD,72328,EN,FT,Canada,M,Canada,0,"GCP, Mathematics, Kubernetes, Statistics",Master,1,Gaming,2024-07-12,2024-09-14,1817,6.1,Digital Transformation LLC -AI03860,Machine Learning Engineer,111403,EUR,94693,SE,FL,Germany,M,South Africa,50,"NLP, GCP, AWS, SQL, Python",Associate,5,Retail,2024-09-26,2024-11-15,2297,8.5,Future Systems -AI03861,AI Consultant,51736,EUR,43976,EN,FT,Netherlands,S,Netherlands,50,"Data Visualization, Kubernetes, Docker, Statistics",Bachelor,0,Government,2024-07-08,2024-08-01,982,5.1,Digital Transformation LLC -AI03862,Data Engineer,23717,USD,23717,EN,FL,India,M,India,50,"Tableau, Azure, R",Bachelor,0,Gaming,2024-05-27,2024-06-26,2332,7.6,Advanced Robotics -AI03863,Principal Data Scientist,109386,USD,109386,MI,FL,Ireland,M,Ireland,0,"Computer Vision, PyTorch, Kubernetes",Master,2,Government,2025-03-28,2025-05-26,1823,6.5,Advanced Robotics -AI03864,Deep Learning Engineer,74878,CAD,93598,MI,PT,Canada,M,Canada,50,"Python, Java, GCP",Bachelor,4,Government,2024-03-24,2024-04-15,2256,7.7,Predictive Systems -AI03865,Autonomous Systems Engineer,65141,USD,65141,EX,FT,India,M,India,0,"Java, R, SQL",Associate,16,Gaming,2024-12-07,2025-01-28,1317,9.2,Cloud AI Solutions -AI03866,AI Architect,128867,CHF,115980,MI,PT,Switzerland,M,Switzerland,50,"Spark, TensorFlow, SQL, Python",Bachelor,4,Energy,2024-10-06,2024-12-06,2112,5.2,DeepTech Ventures -AI03867,Data Analyst,90726,CHF,81653,EN,CT,Switzerland,S,Hungary,100,"Computer Vision, Java, Docker",Associate,1,Telecommunications,2024-09-24,2024-11-07,601,7.2,DeepTech Ventures -AI03868,Deep Learning Engineer,194760,USD,194760,EX,FT,Israel,M,Israel,100,"Python, Tableau, Git, TensorFlow",Master,17,Technology,2024-04-17,2024-05-18,2424,5.2,TechCorp Inc -AI03869,Autonomous Systems Engineer,107056,USD,107056,SE,CT,Ireland,S,Switzerland,0,"TensorFlow, Hadoop, PyTorch, Azure, GCP",Bachelor,5,Healthcare,2024-11-13,2024-12-05,1395,7.6,Future Systems -AI03870,Principal Data Scientist,108594,CAD,135743,SE,FT,Canada,M,South Africa,50,"Hadoop, TensorFlow, Kubernetes",Bachelor,9,Automotive,2025-03-02,2025-03-21,1796,9.7,DataVision Ltd -AI03871,Data Engineer,79163,EUR,67289,MI,CT,Germany,S,Germany,50,"Mathematics, Linux, R, Docker",Master,2,Technology,2024-12-24,2025-02-26,948,8.6,Advanced Robotics -AI03872,Principal Data Scientist,32589,USD,32589,EN,FT,China,M,China,100,"Java, Spark, Tableau, Hadoop, R",PhD,0,Finance,2024-09-08,2024-09-28,2482,6.1,Machine Intelligence Group -AI03873,Machine Learning Researcher,151184,USD,151184,SE,PT,United States,L,United States,50,"Python, Statistics, Computer Vision, TensorFlow, Spark",Associate,9,Telecommunications,2024-06-19,2024-08-19,1282,8.1,Autonomous Tech -AI03874,AI Research Scientist,80519,USD,80519,SE,PT,South Korea,S,South Korea,100,"GCP, Python, Docker, Computer Vision",Bachelor,7,Finance,2024-10-27,2024-12-28,1784,8.5,Future Systems -AI03875,Autonomous Systems Engineer,67798,USD,67798,EN,FT,Finland,S,Finland,50,"NLP, Mathematics, Linux",Bachelor,1,Consulting,2024-02-04,2024-04-17,1593,9,Predictive Systems -AI03876,Data Engineer,142055,JPY,15626050,SE,PT,Japan,L,Japan,0,"Python, Deep Learning, MLOps, Scala, Linux",Master,5,Retail,2024-08-09,2024-09-24,2229,6,Smart Analytics -AI03877,Data Scientist,120576,GBP,90432,SE,PT,United Kingdom,M,United Kingdom,50,"AWS, TensorFlow, Scala, Tableau",Associate,5,Finance,2025-01-15,2025-02-08,2007,6.4,Cloud AI Solutions -AI03878,Principal Data Scientist,125509,USD,125509,MI,FT,Norway,M,Norway,0,"MLOps, Statistics, Kubernetes",PhD,3,Transportation,2024-12-23,2025-01-27,2272,8.5,Advanced Robotics -AI03879,Data Analyst,55931,USD,55931,EX,PT,India,M,Vietnam,50,"Linux, Docker, AWS, Python",Associate,13,Finance,2024-03-07,2024-04-22,2317,8,DataVision Ltd -AI03880,Machine Learning Researcher,231123,JPY,25423530,EX,FT,Japan,L,Japan,50,"NLP, R, SQL, Tableau",Bachelor,13,Consulting,2024-07-09,2024-08-06,1704,6.8,DeepTech Ventures -AI03881,AI Product Manager,228322,USD,228322,EX,FT,South Korea,L,South Korea,0,"Kubernetes, Statistics, MLOps, SQL",Bachelor,17,Education,2025-02-25,2025-04-21,1258,9,Machine Intelligence Group -AI03882,Research Scientist,143444,USD,143444,EX,PT,Finland,S,Russia,0,"TensorFlow, Scala, Linux, PyTorch",Bachelor,14,Finance,2024-04-21,2024-05-30,1040,8.8,Future Systems -AI03883,AI Product Manager,72811,AUD,98295,EN,FT,Australia,M,Australia,0,"PyTorch, SQL, Java, Statistics, Azure",Associate,0,Manufacturing,2024-04-23,2024-06-17,1188,9.5,Quantum Computing Inc -AI03884,Research Scientist,53482,USD,53482,SE,FL,China,S,China,0,"Python, Git, Hadoop, Scala",Bachelor,5,Automotive,2024-01-20,2024-03-15,1359,6.2,Quantum Computing Inc -AI03885,Computer Vision Engineer,69221,AUD,93448,EN,PT,Australia,S,Australia,0,"Python, MLOps, Docker",Bachelor,1,Media,2024-01-14,2024-02-20,2077,5.7,TechCorp Inc -AI03886,ML Ops Engineer,171506,USD,171506,SE,CT,Norway,L,Mexico,50,"Data Visualization, Kubernetes, GCP, Scala",Master,5,Transportation,2024-02-24,2024-03-14,2170,7.8,Smart Analytics -AI03887,Data Analyst,149279,EUR,126887,EX,FT,France,S,France,100,"Kubernetes, Hadoop, Computer Vision, Python, Statistics",PhD,18,Technology,2024-10-01,2024-11-09,1669,9.7,DataVision Ltd -AI03888,AI Architect,123862,EUR,105283,SE,FT,France,M,France,50,"TensorFlow, SQL, Deep Learning, MLOps, Spark",PhD,5,Transportation,2024-07-07,2024-09-04,1315,8.1,DataVision Ltd -AI03889,Data Scientist,261986,USD,261986,EX,PT,Israel,L,Israel,50,"Hadoop, Kubernetes, Java, R",PhD,12,Energy,2025-02-11,2025-03-07,2344,8.3,Machine Intelligence Group -AI03890,Principal Data Scientist,158894,AUD,214507,EX,PT,Australia,S,Austria,0,"Kubernetes, SQL, Linux, Java, PyTorch",PhD,15,Media,2024-04-21,2024-06-17,1938,5.8,Digital Transformation LLC -AI03891,Deep Learning Engineer,137974,EUR,117278,SE,CT,Austria,L,Hungary,50,"Docker, Scala, Hadoop, Git",PhD,6,Telecommunications,2024-08-29,2024-11-07,2039,6.1,Digital Transformation LLC -AI03892,Head of AI,90760,JPY,9983600,MI,CT,Japan,L,Japan,100,"Hadoop, Tableau, Docker",PhD,4,Education,2024-12-17,2025-02-13,1338,9.3,DeepTech Ventures -AI03893,Data Engineer,137606,SGD,178888,SE,CT,Singapore,L,Latvia,0,"GCP, Python, Mathematics, MLOps",Associate,6,Telecommunications,2024-08-24,2024-10-18,858,8.8,Future Systems -AI03894,Deep Learning Engineer,133207,EUR,113226,EX,FL,France,S,France,50,"SQL, Python, TensorFlow",Master,19,Government,2024-10-02,2024-11-27,629,8.3,Machine Intelligence Group -AI03895,AI Product Manager,100495,USD,100495,EX,FT,India,L,India,50,"PyTorch, MLOps, Java, NLP, Scala",PhD,10,Media,2025-03-12,2025-05-17,2399,6.6,Digital Transformation LLC -AI03896,AI Product Manager,91306,EUR,77610,MI,CT,Germany,S,Germany,0,"Tableau, Python, Hadoop, Mathematics",Master,2,Energy,2025-01-24,2025-02-15,2200,5.4,TechCorp Inc -AI03897,AI Specialist,331986,USD,331986,EX,PT,United States,L,Indonesia,0,"PyTorch, Mathematics, MLOps, SQL",Bachelor,11,Consulting,2024-11-18,2025-01-19,2486,5,Machine Intelligence Group -AI03898,AI Software Engineer,75194,EUR,63915,MI,CT,Germany,M,India,0,"Python, TensorFlow, Spark, Azure",PhD,4,Real Estate,2024-08-27,2024-10-07,610,8,Advanced Robotics -AI03899,AI Product Manager,89154,USD,89154,EN,PT,Denmark,M,Singapore,100,"Azure, Python, TensorFlow, Computer Vision, Docker",Associate,0,Technology,2024-03-28,2024-05-28,1881,5.9,DataVision Ltd -AI03900,AI Consultant,64299,USD,64299,EN,PT,South Korea,M,South Korea,50,"Git, Data Visualization, TensorFlow",Bachelor,0,Transportation,2024-08-15,2024-09-18,683,7.8,TechCorp Inc -AI03901,AI Specialist,137294,EUR,116700,SE,FT,Germany,L,Germany,100,"GCP, TensorFlow, MLOps, Mathematics, SQL",Bachelor,8,Government,2024-06-10,2024-07-30,1946,6.4,TechCorp Inc -AI03902,Data Scientist,101275,USD,101275,MI,FL,Ireland,M,Ireland,0,"Git, Kubernetes, Computer Vision, Deep Learning",Associate,2,Technology,2025-01-30,2025-03-29,795,8.7,Cloud AI Solutions -AI03903,Autonomous Systems Engineer,139984,USD,139984,MI,PT,United States,L,United States,100,"Spark, SQL, Mathematics, Docker, Deep Learning",PhD,2,Retail,2024-02-09,2024-04-11,930,8.9,Future Systems -AI03904,Deep Learning Engineer,151316,EUR,128619,EX,FL,France,S,United States,100,"Hadoop, SQL, Deep Learning",Master,12,Consulting,2025-01-04,2025-02-25,2299,6.4,Advanced Robotics -AI03905,NLP Engineer,84471,USD,84471,EN,PT,Denmark,M,Ireland,100,"Python, Git, GCP, Spark",Master,1,Finance,2024-05-14,2024-06-24,796,5.6,AI Innovations -AI03906,Data Engineer,104379,GBP,78284,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Statistics, R, PyTorch",Bachelor,5,Transportation,2024-02-03,2024-03-11,2366,6.3,Machine Intelligence Group -AI03907,Principal Data Scientist,252832,USD,252832,EX,PT,Denmark,S,Denmark,50,"Scala, TensorFlow, Tableau",PhD,10,Energy,2024-10-14,2024-12-24,1983,8.7,Cognitive Computing -AI03908,Machine Learning Researcher,214285,EUR,182142,EX,FT,Germany,L,Chile,100,"Git, Azure, Data Visualization, R, Computer Vision",Master,17,Manufacturing,2024-05-17,2024-07-20,1999,9.6,DataVision Ltd -AI03909,Data Engineer,100489,USD,100489,EN,CT,Norway,L,Norway,100,"Kubernetes, MLOps, SQL, TensorFlow, R",Associate,0,Automotive,2024-10-22,2024-11-30,1403,7.7,AI Innovations -AI03910,Research Scientist,116902,AUD,157818,SE,FT,Australia,M,Australia,50,"GCP, Mathematics, Data Visualization",PhD,8,Real Estate,2024-07-04,2024-08-06,739,6,DataVision Ltd -AI03911,Data Scientist,98004,USD,98004,EN,PT,Norway,M,Israel,0,"Git, AWS, GCP, Deep Learning, Docker",Master,1,Telecommunications,2024-07-22,2024-09-24,2303,6.7,Machine Intelligence Group -AI03912,ML Ops Engineer,216802,USD,216802,EX,FL,United States,S,United States,50,"Python, TensorFlow, Tableau, PyTorch, Azure",PhD,15,Education,2025-03-11,2025-04-21,869,6,Smart Analytics -AI03913,Principal Data Scientist,97639,USD,97639,MI,FT,Sweden,M,United States,50,"Python, TensorFlow, Spark",Master,4,Energy,2024-12-15,2025-02-15,1662,8.8,Quantum Computing Inc -AI03914,AI Specialist,112321,USD,112321,MI,CT,Israel,L,Israel,0,"Mathematics, GCP, Computer Vision, TensorFlow, Spark",PhD,4,Gaming,2024-02-11,2024-03-21,2160,6,Predictive Systems -AI03915,Data Engineer,192260,AUD,259551,EX,FT,Australia,S,Finland,0,"Tableau, MLOps, GCP, Scala",Bachelor,18,Automotive,2024-10-04,2024-12-14,1151,9.4,Quantum Computing Inc -AI03916,Head of AI,109993,AUD,148491,MI,PT,Australia,L,Australia,50,"SQL, Linux, AWS",Associate,4,Telecommunications,2024-02-06,2024-04-12,1361,8.9,Autonomous Tech -AI03917,AI Product Manager,65943,USD,65943,MI,FL,Sweden,S,Sweden,50,"Python, Kubernetes, Java, Hadoop",Master,2,Finance,2024-08-26,2024-10-09,861,9.3,DeepTech Ventures -AI03918,AI Software Engineer,90867,SGD,118127,MI,PT,Singapore,M,Singapore,100,"SQL, Scala, GCP, Kubernetes, Tableau",Associate,3,Education,2024-11-22,2024-12-23,1269,9.5,DataVision Ltd -AI03919,ML Ops Engineer,84856,USD,84856,EX,FT,India,M,India,100,"AWS, Azure, Spark, Data Visualization, Deep Learning",Bachelor,13,Automotive,2025-03-16,2025-05-05,1793,9.5,Future Systems -AI03920,Data Analyst,171549,EUR,145817,EX,FT,France,M,South Africa,0,"Spark, Linux, Tableau, TensorFlow, Data Visualization",Bachelor,11,Manufacturing,2024-08-12,2024-09-15,1377,5.2,AI Innovations -AI03921,AI Research Scientist,191772,EUR,163006,EX,FL,Germany,M,Thailand,0,"Docker, Statistics, Scala, Kubernetes",Bachelor,19,Telecommunications,2024-07-22,2024-08-14,1912,8.4,Advanced Robotics -AI03922,Robotics Engineer,111326,USD,111326,SE,FT,Ireland,S,Ireland,100,"Computer Vision, SQL, Git, Deep Learning, GCP",Bachelor,6,Retail,2024-08-17,2024-09-16,565,7.3,Cognitive Computing -AI03923,Robotics Engineer,180543,JPY,19859730,EX,CT,Japan,M,Japan,50,"SQL, Deep Learning, Python, NLP",Associate,16,Transportation,2024-06-26,2024-07-13,1493,7.1,Predictive Systems -AI03924,AI Research Scientist,35560,USD,35560,EN,FT,China,M,China,50,"Kubernetes, Azure, Python, Deep Learning",Bachelor,1,Energy,2024-06-21,2024-08-09,983,5.7,Future Systems -AI03925,AI Software Engineer,80024,USD,80024,SE,PT,China,L,China,0,"Hadoop, Linux, Data Visualization",PhD,8,Manufacturing,2024-06-06,2024-06-23,1425,10,Machine Intelligence Group -AI03926,AI Architect,62790,USD,62790,EN,PT,Finland,M,Norway,100,"Python, TensorFlow, AWS, Docker",Master,1,Healthcare,2024-09-01,2024-11-12,1164,8.4,Advanced Robotics -AI03927,NLP Engineer,172119,USD,172119,SE,FT,Norway,M,Norway,0,"MLOps, Mathematics, Tableau, Docker, Azure",Associate,5,Finance,2024-03-05,2024-03-20,727,5.8,Quantum Computing Inc -AI03928,AI Software Engineer,144594,USD,144594,EX,FT,Finland,S,Finland,100,"PyTorch, Python, Azure",Associate,14,Finance,2025-04-30,2025-06-24,1107,6.8,Algorithmic Solutions -AI03929,Autonomous Systems Engineer,59241,EUR,50355,EN,FL,France,S,France,50,"Git, PyTorch, Hadoop, Azure, Deep Learning",Bachelor,0,Transportation,2024-01-30,2024-03-19,2005,9.1,Neural Networks Co -AI03930,Research Scientist,114166,EUR,97041,SE,CT,Netherlands,M,Netherlands,0,"SQL, GCP, NLP, Statistics",Bachelor,9,Media,2024-03-05,2024-04-15,2009,6.8,Cloud AI Solutions -AI03931,AI Product Manager,32706,USD,32706,EN,CT,China,S,Hungary,0,"Hadoop, R, SQL",PhD,1,Manufacturing,2024-03-07,2024-04-26,1525,8.4,Smart Analytics -AI03932,AI Research Scientist,120324,USD,120324,SE,FL,Sweden,M,Sweden,0,"PyTorch, TensorFlow, Tableau, SQL",PhD,8,Real Estate,2024-08-24,2024-10-08,1364,8.8,Algorithmic Solutions -AI03933,NLP Engineer,59232,CAD,74040,EN,PT,Canada,L,Austria,50,"Java, Computer Vision, Mathematics, Hadoop",Master,0,Manufacturing,2025-01-16,2025-03-22,1616,8.4,Neural Networks Co -AI03934,AI Architect,221142,CHF,199028,EX,PT,Switzerland,M,Switzerland,50,"PyTorch, Statistics, TensorFlow",Associate,18,Real Estate,2025-02-25,2025-03-29,1739,5.6,Neural Networks Co -AI03935,Research Scientist,48487,USD,48487,EN,CT,Israel,S,Israel,50,"Mathematics, AWS, Data Visualization, Azure, Git",Associate,1,Manufacturing,2025-03-07,2025-04-18,1412,7.8,DeepTech Ventures -AI03936,Machine Learning Researcher,145495,SGD,189144,SE,FT,Singapore,M,Singapore,0,"NLP, Hadoop, Linux",Bachelor,8,Healthcare,2024-10-25,2024-12-07,1094,5,Algorithmic Solutions -AI03937,Autonomous Systems Engineer,64092,SGD,83320,EN,FL,Singapore,L,Kenya,50,"Kubernetes, SQL, Spark, Python, Statistics",Associate,0,Consulting,2024-10-11,2024-12-15,779,7.3,Predictive Systems -AI03938,Data Analyst,135974,USD,135974,SE,CT,Denmark,S,Kenya,0,"Hadoop, Tableau, Python, Mathematics",Master,9,Education,2024-11-09,2024-12-31,2321,7.6,Quantum Computing Inc -AI03939,AI Product Manager,215605,USD,215605,EX,FL,Israel,M,Israel,0,"Java, R, SQL",Master,12,Technology,2024-12-16,2025-01-26,1940,5.6,Predictive Systems -AI03940,Principal Data Scientist,109621,USD,109621,MI,PT,United States,L,Singapore,0,"SQL, AWS, Git, MLOps, GCP",Bachelor,2,Energy,2024-12-20,2025-01-05,849,9.8,Future Systems -AI03941,AI Specialist,155788,USD,155788,SE,FT,United States,S,United States,0,"SQL, Data Visualization, Scala, Azure, Linux",Associate,6,Gaming,2024-06-07,2024-07-29,2489,7.7,Autonomous Tech -AI03942,Research Scientist,114493,USD,114493,SE,FT,Israel,L,Luxembourg,0,"Spark, NLP, Python, Deep Learning",Associate,9,Manufacturing,2024-06-22,2024-07-06,1482,6.2,Digital Transformation LLC -AI03943,AI Architect,127669,EUR,108519,SE,FT,Germany,S,Finland,100,"Mathematics, Kubernetes, Statistics, GCP, Tableau",Master,7,Government,2025-04-23,2025-07-03,1199,8.5,TechCorp Inc -AI03944,Machine Learning Engineer,184048,SGD,239262,EX,CT,Singapore,M,Singapore,0,"TensorFlow, R, Azure, GCP, Hadoop",Master,11,Technology,2024-01-24,2024-02-10,924,6.6,Algorithmic Solutions -AI03945,Machine Learning Engineer,62821,USD,62821,MI,FL,Finland,S,Finland,100,"Python, Linux, Scala, Kubernetes, TensorFlow",PhD,2,Transportation,2025-04-04,2025-05-30,1805,7.6,Autonomous Tech -AI03946,Data Analyst,116061,USD,116061,MI,FL,Norway,M,Norway,50,"Scala, Statistics, Python, Git",PhD,2,Gaming,2024-05-07,2024-07-11,1188,9.5,Predictive Systems -AI03947,Deep Learning Engineer,68069,JPY,7487590,EN,CT,Japan,M,Japan,100,"Docker, R, Deep Learning, Statistics, Mathematics",PhD,1,Consulting,2024-10-10,2024-10-31,2039,8.5,Future Systems -AI03948,ML Ops Engineer,55034,USD,55034,EN,FL,South Korea,S,Czech Republic,100,"R, GCP, Statistics, SQL, Tableau",Bachelor,1,Media,2024-09-27,2024-11-07,1092,8.6,Advanced Robotics -AI03949,AI Product Manager,197089,EUR,167526,EX,FT,Germany,M,Germany,100,"Hadoop, TensorFlow, Tableau, Data Visualization, Kubernetes",Bachelor,13,Government,2024-04-28,2024-06-26,1527,9,Quantum Computing Inc -AI03950,Data Analyst,63965,EUR,54370,EN,FL,Austria,S,Austria,100,"SQL, Spark, PyTorch, AWS, Java",Master,1,Consulting,2024-11-17,2024-12-02,1541,9.2,Cognitive Computing -AI03951,Research Scientist,88359,CHF,79523,EN,FT,Switzerland,S,Switzerland,100,"TensorFlow, Python, NLP",Associate,0,Real Estate,2024-11-04,2024-11-19,1376,6.4,Machine Intelligence Group -AI03952,ML Ops Engineer,58746,USD,58746,EN,CT,Ireland,S,Ireland,50,"SQL, Python, NLP, Scala, Git",Associate,1,Retail,2024-10-16,2024-11-21,748,9,Future Systems -AI03953,ML Ops Engineer,84148,USD,84148,EX,FT,China,M,China,50,"Tableau, PyTorch, Azure, Linux, NLP",Bachelor,17,Retail,2024-08-26,2024-11-05,1420,5.2,Neural Networks Co -AI03954,Machine Learning Engineer,106957,CHF,96261,EN,FL,Switzerland,M,Switzerland,50,"R, PyTorch, Computer Vision",Master,1,Healthcare,2024-11-27,2024-12-12,1030,6.4,Future Systems -AI03955,Autonomous Systems Engineer,83304,CAD,104130,MI,PT,Canada,S,Denmark,50,"GCP, Scala, Data Visualization, TensorFlow",PhD,3,Education,2024-03-30,2024-05-01,943,6.3,TechCorp Inc -AI03956,Principal Data Scientist,169228,USD,169228,EX,FL,United States,M,United States,100,"Python, Azure, Mathematics",Bachelor,10,Education,2024-04-02,2024-05-11,1923,9.7,TechCorp Inc -AI03957,Deep Learning Engineer,87246,CAD,109058,MI,CT,Canada,S,Nigeria,50,"Deep Learning, Python, Mathematics, MLOps",Master,3,Gaming,2024-05-01,2024-06-26,916,9.4,DataVision Ltd -AI03958,Research Scientist,71057,GBP,53293,EN,PT,United Kingdom,M,United Kingdom,100,"Python, PyTorch, Kubernetes, Azure, SQL",PhD,0,Retail,2024-03-04,2024-05-13,1746,7.6,AI Innovations -AI03959,Data Engineer,197354,CAD,246693,EX,CT,Canada,M,Mexico,50,"SQL, R, Tableau, Statistics, Scala",Associate,11,Energy,2024-01-30,2024-03-18,2412,8.8,DeepTech Ventures -AI03960,Research Scientist,128498,USD,128498,EX,FL,Israel,S,China,0,"Mathematics, SQL, Linux",Bachelor,15,Technology,2024-04-29,2024-06-08,1531,9,Advanced Robotics -AI03961,AI Architect,186865,USD,186865,SE,CT,Denmark,L,Denmark,0,"TensorFlow, Azure, NLP, Git, SQL",Master,8,Telecommunications,2024-11-07,2024-12-21,1088,5.3,Quantum Computing Inc -AI03962,AI Research Scientist,107253,USD,107253,MI,FT,United States,M,Russia,100,"Linux, Computer Vision, Python, Data Visualization, Git",PhD,2,Automotive,2024-01-25,2024-03-27,2074,9.8,TechCorp Inc -AI03963,NLP Engineer,63687,USD,63687,MI,FL,Israel,S,Israel,50,"Computer Vision, Kubernetes, SQL, Deep Learning",PhD,4,Education,2024-07-18,2024-09-05,1291,9.5,Neural Networks Co -AI03964,Principal Data Scientist,79216,USD,79216,MI,FT,Israel,S,Israel,100,"PyTorch, Linux, Data Visualization",Associate,2,Education,2024-06-12,2024-07-20,1511,6,Autonomous Tech -AI03965,Data Scientist,231383,USD,231383,EX,FT,Israel,L,Israel,0,"GCP, TensorFlow, Scala, Python, Data Visualization",Master,11,Technology,2024-02-21,2024-04-07,2362,8.9,Smart Analytics -AI03966,Data Engineer,43977,USD,43977,SE,PT,India,S,Sweden,100,"Scala, Data Visualization, Tableau, Java",Bachelor,9,Automotive,2025-04-22,2025-05-15,1455,8.7,DeepTech Ventures -AI03967,Principal Data Scientist,58328,USD,58328,SE,FT,China,M,China,50,"Data Visualization, Scala, Linux, Java",Bachelor,8,Telecommunications,2024-10-09,2024-12-13,860,6.6,DataVision Ltd -AI03968,Machine Learning Engineer,26547,USD,26547,EN,PT,India,L,Turkey,0,"Python, Azure, SQL, Computer Vision",Master,1,Finance,2025-04-01,2025-05-25,976,7.8,TechCorp Inc -AI03969,Autonomous Systems Engineer,55423,USD,55423,EN,CT,South Korea,S,Australia,0,"Docker, SQL, Java, PyTorch, Linux",Master,0,Real Estate,2024-12-12,2025-01-12,1325,7,Advanced Robotics -AI03970,Machine Learning Engineer,24833,USD,24833,MI,FT,India,S,Mexico,0,"R, SQL, Data Visualization",Master,3,Media,2024-12-20,2025-03-03,2055,9.3,Advanced Robotics -AI03971,Principal Data Scientist,110197,USD,110197,MI,FL,United States,M,United States,100,"R, PyTorch, Scala",PhD,3,Real Estate,2025-01-02,2025-03-01,1672,8.7,Machine Intelligence Group -AI03972,AI Architect,72964,USD,72964,EN,FL,Israel,M,Ukraine,100,"AWS, Spark, MLOps, Scala",Associate,0,Government,2024-03-07,2024-04-04,2318,9.2,AI Innovations -AI03973,Robotics Engineer,59921,USD,59921,EN,CT,Sweden,M,Spain,50,"Data Visualization, Python, TensorFlow, Docker, Statistics",Bachelor,1,Finance,2024-11-02,2025-01-11,1707,8.4,Smart Analytics -AI03974,AI Software Engineer,56383,EUR,47926,EN,CT,Austria,S,Argentina,100,"Azure, AWS, NLP, Spark",PhD,0,Telecommunications,2024-12-05,2025-02-15,1841,8.8,Digital Transformation LLC -AI03975,AI Specialist,71225,USD,71225,EX,FL,India,S,India,0,"Git, MLOps, Deep Learning, Python",Master,19,Government,2024-10-14,2024-11-01,987,6.9,Cloud AI Solutions -AI03976,AI Consultant,64188,USD,64188,EN,CT,Sweden,M,Sweden,50,"Statistics, Hadoop, R, TensorFlow",Bachelor,1,Consulting,2024-06-04,2024-06-26,1597,7.2,AI Innovations -AI03977,Machine Learning Researcher,111850,USD,111850,MI,FT,Norway,S,Norway,0,"MLOps, Python, TensorFlow",PhD,2,Real Estate,2024-02-25,2024-03-21,2475,6.4,Algorithmic Solutions -AI03978,Machine Learning Engineer,193873,EUR,164792,EX,FT,Netherlands,M,Netherlands,0,"Scala, Kubernetes, Deep Learning, Java",Master,12,Real Estate,2024-11-10,2025-01-11,2444,8.6,Machine Intelligence Group -AI03979,Head of AI,69980,USD,69980,EX,CT,China,M,China,50,"Mathematics, PyTorch, Statistics, Kubernetes, Hadoop",PhD,17,Technology,2024-01-03,2024-02-05,1838,8.5,Future Systems -AI03980,AI Specialist,17744,USD,17744,EN,FT,India,S,Kenya,0,"AWS, Git, NLP",Master,1,Media,2025-03-11,2025-04-09,1086,7.8,DeepTech Ventures -AI03981,Research Scientist,55353,EUR,47050,EN,PT,France,L,France,100,"PyTorch, TensorFlow, Java, SQL, Mathematics",Associate,0,Consulting,2024-10-17,2024-12-10,1210,8.2,Neural Networks Co -AI03982,AI Specialist,29786,USD,29786,EN,PT,China,M,Latvia,50,"Spark, Statistics, Data Visualization",Bachelor,0,Telecommunications,2024-11-17,2025-01-19,2453,7.3,Advanced Robotics -AI03983,Machine Learning Researcher,75425,EUR,64111,MI,FT,France,M,France,100,"Python, Kubernetes, Deep Learning, Hadoop, R",Master,4,Telecommunications,2025-01-06,2025-02-04,1488,9.1,DeepTech Ventures -AI03984,Data Engineer,154886,EUR,131653,EX,FT,Austria,S,Australia,0,"Git, SQL, Python",Master,13,Gaming,2024-03-04,2024-04-17,2028,9.6,Advanced Robotics -AI03985,Data Engineer,99073,CAD,123841,SE,FT,Canada,M,Canada,0,"Git, Kubernetes, SQL, PyTorch, Hadoop",PhD,9,Automotive,2025-03-07,2025-04-25,1381,6.4,Quantum Computing Inc -AI03986,Head of AI,73454,EUR,62436,EN,FT,France,M,France,0,"Azure, Java, Docker",Bachelor,0,Telecommunications,2024-02-04,2024-02-29,2135,8.8,DataVision Ltd -AI03987,AI Consultant,59838,USD,59838,SE,CT,China,S,China,100,"Kubernetes, PyTorch, Linux, Computer Vision, MLOps",Associate,9,Government,2024-10-19,2024-12-31,2206,7.2,TechCorp Inc -AI03988,AI Consultant,87537,USD,87537,MI,FT,Israel,M,South Korea,0,"Java, Scala, Deep Learning, Azure",Master,2,Energy,2025-02-28,2025-04-22,2433,8.3,Predictive Systems -AI03989,AI Architect,26899,USD,26899,EN,CT,India,M,Estonia,0,"Scala, NLP, Docker",Master,0,Healthcare,2024-05-09,2024-07-19,1252,5.6,DataVision Ltd -AI03990,AI Architect,89970,USD,89970,SE,PT,South Korea,S,Germany,0,"R, MLOps, AWS",Bachelor,7,Telecommunications,2024-11-08,2025-01-03,809,5.6,Cognitive Computing -AI03991,Deep Learning Engineer,135427,USD,135427,SE,FL,Finland,L,Finland,50,"Java, GCP, Scala",PhD,6,Government,2025-03-24,2025-05-14,1411,6.9,Machine Intelligence Group -AI03992,NLP Engineer,55414,EUR,47102,EN,PT,Austria,M,Latvia,0,"Hadoop, Python, Spark, TensorFlow",PhD,0,Transportation,2025-01-27,2025-02-21,977,8.9,DataVision Ltd -AI03993,AI Architect,214757,CHF,193281,SE,CT,Switzerland,M,Switzerland,100,"Tableau, TensorFlow, Kubernetes, Azure",PhD,8,Energy,2024-08-26,2024-09-11,2055,8.7,Cloud AI Solutions -AI03994,AI Specialist,165695,USD,165695,SE,FL,United States,M,United States,50,"MLOps, Kubernetes, Deep Learning, Git",Associate,5,Finance,2025-02-24,2025-04-26,1087,7.7,Algorithmic Solutions -AI03995,AI Research Scientist,88990,USD,88990,EN,CT,Denmark,M,Denmark,50,"Python, TensorFlow, AWS",Master,0,Government,2025-02-19,2025-03-07,697,5.4,Advanced Robotics -AI03996,Head of AI,74202,GBP,55652,EN,FT,United Kingdom,M,United Kingdom,0,"Python, Kubernetes, GCP, Spark",Associate,1,Consulting,2025-01-24,2025-03-26,1970,6.7,Cognitive Computing -AI03997,Computer Vision Engineer,127421,USD,127421,EX,FT,Finland,S,Netherlands,100,"SQL, Docker, Tableau, PyTorch",Master,11,Healthcare,2024-04-12,2024-04-29,920,9.1,DeepTech Ventures -AI03998,Computer Vision Engineer,278984,CHF,251086,EX,PT,Switzerland,L,Austria,0,"Python, TensorFlow, MLOps, GCP, Data Visualization",Master,14,Finance,2024-02-11,2024-03-09,595,6.2,Smart Analytics -AI03999,Autonomous Systems Engineer,158896,USD,158896,SE,FT,Norway,S,Norway,0,"Data Visualization, Tableau, Hadoop, MLOps",Master,9,Technology,2024-03-19,2024-05-23,541,5.4,TechCorp Inc -AI04000,Robotics Engineer,135260,USD,135260,MI,FT,United States,L,United States,0,"Scala, Python, Hadoop, TensorFlow",PhD,2,Consulting,2024-01-29,2024-02-19,1479,5.3,TechCorp Inc -AI04001,AI Architect,75021,EUR,63768,MI,FT,Austria,S,Colombia,50,"Java, R, Data Visualization, NLP",Bachelor,2,Government,2024-02-01,2024-03-04,1164,9.1,Machine Intelligence Group -AI04002,Head of AI,154992,EUR,131743,EX,FL,Austria,S,Austria,50,"Linux, Git, Spark",Associate,19,Automotive,2025-03-28,2025-04-22,1595,6.9,DataVision Ltd -AI04003,Robotics Engineer,190121,JPY,20913310,EX,FL,Japan,L,Japan,100,"Git, Linux, Deep Learning",PhD,11,Government,2024-04-16,2024-06-21,1539,7.5,Predictive Systems -AI04004,Machine Learning Engineer,385410,CHF,346869,EX,FL,Switzerland,L,Switzerland,0,"Data Visualization, Java, GCP",Bachelor,16,Real Estate,2024-12-18,2025-01-04,849,5.5,Cognitive Computing -AI04005,Computer Vision Engineer,100524,USD,100524,SE,FT,Israel,S,Chile,50,"TensorFlow, Hadoop, Kubernetes",Master,5,Real Estate,2025-03-09,2025-05-15,1296,7.4,DeepTech Ventures -AI04006,Machine Learning Researcher,277819,USD,277819,EX,PT,Denmark,M,Denmark,100,"Data Visualization, Python, SQL, Hadoop",Master,14,Gaming,2025-03-22,2025-05-02,1616,9.1,Autonomous Tech -AI04007,NLP Engineer,65703,AUD,88699,EN,FL,Australia,S,Australia,50,"Hadoop, TensorFlow, Python, NLP",Associate,1,Finance,2024-01-21,2024-03-02,532,8.9,Machine Intelligence Group -AI04008,Data Scientist,132522,EUR,112644,SE,FT,France,L,France,50,"Scala, PyTorch, Java, Deep Learning, Mathematics",PhD,6,Transportation,2024-04-13,2024-06-10,1844,7.3,TechCorp Inc -AI04009,Autonomous Systems Engineer,165364,EUR,140559,EX,FL,France,S,France,0,"Computer Vision, Tableau, Hadoop, R, Deep Learning",Master,11,Transportation,2025-04-07,2025-06-14,1602,5.7,Digital Transformation LLC -AI04010,Principal Data Scientist,106407,AUD,143649,SE,CT,Australia,S,Australia,0,"PyTorch, Hadoop, SQL, Azure",PhD,9,Technology,2024-08-07,2024-09-11,1007,5.1,Predictive Systems -AI04011,Autonomous Systems Engineer,72285,JPY,7951350,EN,CT,Japan,M,Turkey,50,"Python, Spark, Hadoop, Computer Vision, TensorFlow",Bachelor,0,Education,2024-02-16,2024-03-17,2400,6.7,Algorithmic Solutions -AI04012,Principal Data Scientist,105498,USD,105498,SE,FT,Finland,S,Finland,0,"Linux, R, Statistics, SQL, Java",Associate,8,Telecommunications,2024-03-20,2024-05-17,1901,9.7,DeepTech Ventures -AI04013,Autonomous Systems Engineer,93513,EUR,79486,MI,CT,Netherlands,S,Netherlands,50,"R, Python, Tableau, Git",Bachelor,3,Energy,2024-10-14,2024-11-17,915,7.7,Cognitive Computing -AI04014,Data Scientist,56370,USD,56370,EN,PT,Finland,M,Finland,0,"MLOps, Python, Docker",PhD,0,Real Estate,2024-02-08,2024-03-27,722,7.5,Future Systems -AI04015,Computer Vision Engineer,111901,EUR,95116,MI,FT,France,L,Indonesia,50,"Scala, Linux, Java, Git, Statistics",Associate,2,Healthcare,2025-03-14,2025-04-07,750,9.7,Cognitive Computing -AI04016,AI Product Manager,250059,USD,250059,EX,CT,Denmark,S,Denmark,0,"Python, TensorFlow, Hadoop, Mathematics, Computer Vision",Associate,18,Telecommunications,2024-09-18,2024-10-22,2174,6.3,Neural Networks Co -AI04017,Research Scientist,273161,USD,273161,EX,CT,Denmark,M,Switzerland,50,"PyTorch, Tableau, Deep Learning, Statistics",Bachelor,19,Consulting,2024-11-21,2024-12-06,612,5.3,Quantum Computing Inc -AI04018,Data Engineer,132189,EUR,112361,SE,FL,Germany,S,Estonia,100,"Linux, Data Visualization, Scala",Master,8,Education,2025-01-23,2025-03-28,1573,6.8,Autonomous Tech -AI04019,AI Architect,66589,EUR,56601,EN,PT,Germany,M,Germany,50,"Linux, Java, NLP",Associate,0,Real Estate,2024-04-14,2024-05-18,1587,9.5,Smart Analytics -AI04020,Data Analyst,60676,EUR,51575,EN,FL,France,M,Singapore,0,"Computer Vision, GCP, Python, Spark, TensorFlow",Bachelor,0,Education,2024-05-27,2024-06-23,1379,8.3,Quantum Computing Inc -AI04021,Principal Data Scientist,109570,CAD,136963,SE,CT,Canada,M,Romania,0,"GCP, Azure, Data Visualization, AWS",PhD,9,Government,2024-12-17,2025-01-15,2415,5.9,DeepTech Ventures -AI04022,Machine Learning Engineer,58052,USD,58052,EN,FT,Israel,S,France,50,"Git, Statistics, MLOps, Azure",Associate,1,Consulting,2024-08-18,2024-10-19,1438,7.2,DeepTech Ventures -AI04023,AI Research Scientist,98945,EUR,84103,MI,FL,Austria,M,Austria,0,"MLOps, PyTorch, Git, AWS",Associate,3,Manufacturing,2024-12-06,2025-01-26,1831,9.1,Algorithmic Solutions -AI04024,AI Product Manager,199637,USD,199637,EX,CT,Israel,L,Israel,100,"Java, Linux, Hadoop",Bachelor,12,Consulting,2024-02-08,2024-02-24,2356,9.9,TechCorp Inc -AI04025,AI Software Engineer,78109,USD,78109,MI,PT,Finland,S,Finland,50,"NLP, Git, Hadoop, Docker",Master,4,Consulting,2024-04-07,2024-05-19,1816,8.6,Predictive Systems -AI04026,AI Software Engineer,73974,USD,73974,MI,FL,Israel,M,Malaysia,0,"Python, GCP, Tableau",Associate,4,Automotive,2024-03-20,2024-04-14,1538,6,Cloud AI Solutions -AI04027,AI Software Engineer,134116,EUR,113999,SE,PT,France,M,France,100,"NLP, SQL, MLOps",Bachelor,7,Manufacturing,2024-05-25,2024-06-16,832,5.2,Digital Transformation LLC -AI04028,Deep Learning Engineer,135851,USD,135851,SE,CT,Finland,L,Ghana,100,"Docker, AWS, Tableau, GCP, TensorFlow",Associate,7,Consulting,2024-09-21,2024-10-14,543,8.9,Digital Transformation LLC -AI04029,Deep Learning Engineer,142460,USD,142460,SE,PT,Ireland,M,Thailand,100,"Tableau, Statistics, Linux, Mathematics, Deep Learning",Master,5,Education,2024-04-02,2024-04-20,697,6.5,AI Innovations -AI04030,Head of AI,69316,USD,69316,EN,PT,Denmark,S,Japan,50,"SQL, Spark, GCP",Associate,0,Government,2024-04-05,2024-04-24,862,8.1,DataVision Ltd -AI04031,Deep Learning Engineer,82158,EUR,69834,EN,FT,France,L,France,50,"AWS, MLOps, SQL, PyTorch, Git",Associate,1,Retail,2024-05-17,2024-06-22,1467,5.6,Machine Intelligence Group -AI04032,AI Product Manager,167922,USD,167922,SE,PT,Ireland,L,Ireland,100,"SQL, AWS, MLOps",Master,5,Healthcare,2024-12-03,2024-12-24,824,9.4,Quantum Computing Inc -AI04033,NLP Engineer,142118,EUR,120800,SE,FL,Austria,L,Austria,100,"Python, Git, SQL, AWS",Associate,8,Manufacturing,2024-07-06,2024-08-18,1172,5.8,Cognitive Computing -AI04034,Deep Learning Engineer,215397,USD,215397,EX,FT,Israel,S,Israel,50,"Data Visualization, Statistics, Hadoop, Deep Learning, Docker",Associate,15,Retail,2024-10-07,2024-12-07,2434,7.6,Quantum Computing Inc -AI04035,Research Scientist,294594,CHF,265135,EX,FT,Switzerland,L,China,0,"Data Visualization, AWS, SQL, PyTorch, Java",Associate,10,Manufacturing,2024-06-23,2024-07-07,1111,5.5,TechCorp Inc -AI04036,AI Specialist,63057,USD,63057,EN,CT,United States,M,United States,50,"NLP, Scala, Data Visualization",Associate,1,Energy,2024-07-30,2024-08-27,2384,10,Cloud AI Solutions -AI04037,ML Ops Engineer,217874,EUR,185193,EX,FL,Austria,M,Portugal,100,"Java, Hadoop, Computer Vision, R, Python",Master,19,Education,2024-08-26,2024-10-09,2330,9.6,Smart Analytics -AI04038,Autonomous Systems Engineer,32792,USD,32792,SE,PT,India,S,India,50,"GCP, Python, SQL, R",Associate,8,Gaming,2024-10-05,2024-12-16,2354,7.7,Advanced Robotics -AI04039,ML Ops Engineer,116266,JPY,12789260,SE,CT,Japan,M,Japan,100,"Kubernetes, Linux, Data Visualization, NLP, Docker",PhD,7,Education,2025-02-08,2025-03-07,1459,6,Future Systems -AI04040,AI Research Scientist,70410,EUR,59849,EN,FL,Austria,L,Austria,50,"PyTorch, Kubernetes, Docker, TensorFlow",PhD,1,Technology,2024-11-11,2024-12-14,1600,5.3,DeepTech Ventures -AI04041,Data Analyst,56897,CAD,71121,EN,FL,Canada,L,Canada,100,"Java, MLOps, R",PhD,1,Consulting,2024-09-04,2024-09-27,2164,8.6,Cognitive Computing -AI04042,Autonomous Systems Engineer,135997,CHF,122397,MI,PT,Switzerland,S,Ghana,100,"Linux, Python, Kubernetes, MLOps, Data Visualization",Associate,3,Technology,2024-05-14,2024-07-09,1556,7.9,Cloud AI Solutions -AI04043,Machine Learning Engineer,50494,USD,50494,EN,FT,Israel,S,Israel,100,"Git, Tableau, PyTorch, Kubernetes, Spark",Associate,1,Media,2024-09-07,2024-10-01,2213,6,DataVision Ltd -AI04044,AI Research Scientist,144481,GBP,108361,EX,PT,United Kingdom,S,United Kingdom,0,"Git, Linux, Data Visualization, Azure",Bachelor,13,Retail,2024-10-06,2024-12-06,1779,5.1,DeepTech Ventures -AI04045,Principal Data Scientist,102340,USD,102340,MI,FT,Ireland,M,Ireland,50,"GCP, Computer Vision, Linux, Tableau",PhD,3,Retail,2024-06-04,2024-06-24,807,5.4,TechCorp Inc -AI04046,AI Research Scientist,289309,USD,289309,EX,FL,Denmark,S,Denmark,50,"Python, Azure, Tableau, Mathematics",Associate,19,Finance,2025-03-07,2025-04-25,557,7.2,Machine Intelligence Group -AI04047,AI Specialist,86564,GBP,64923,EN,PT,United Kingdom,L,United Kingdom,0,"Linux, Azure, TensorFlow",Associate,0,Education,2024-05-22,2024-06-30,2341,6.6,Cognitive Computing -AI04048,Computer Vision Engineer,105245,GBP,78934,MI,CT,United Kingdom,L,United Kingdom,0,"Spark, R, Computer Vision, Deep Learning, Python",Master,3,Government,2025-03-07,2025-04-04,2141,7.9,AI Innovations -AI04049,Principal Data Scientist,135249,USD,135249,EX,FT,Sweden,S,Sweden,100,"Mathematics, Git, Spark, SQL, PyTorch",Master,14,Energy,2024-09-23,2024-10-20,1386,8.8,Predictive Systems -AI04050,AI Research Scientist,351014,CHF,315913,EX,FT,Switzerland,L,Egypt,50,"Statistics, MLOps, Python, TensorFlow",Master,10,Consulting,2024-10-25,2024-12-13,922,5.8,Quantum Computing Inc -AI04051,Data Scientist,170313,GBP,127735,SE,PT,United Kingdom,L,United Kingdom,0,"Azure, Scala, Statistics, SQL, Deep Learning",Master,5,Gaming,2024-07-27,2024-08-29,1363,5.6,Algorithmic Solutions -AI04052,Autonomous Systems Engineer,96839,USD,96839,MI,FL,Israel,L,Israel,0,"Scala, Data Visualization, Computer Vision",Associate,3,Automotive,2025-02-16,2025-03-31,2388,9.8,DeepTech Ventures -AI04053,Machine Learning Engineer,112039,USD,112039,EX,CT,South Korea,M,South Korea,0,"TensorFlow, GCP, Scala",Bachelor,16,Finance,2024-10-01,2024-12-06,1359,5.5,Future Systems -AI04054,Autonomous Systems Engineer,161578,GBP,121184,SE,FL,United Kingdom,L,United Kingdom,50,"Python, Linux, Kubernetes, Git, GCP",PhD,9,Energy,2024-03-23,2024-04-19,538,8.7,Quantum Computing Inc -AI04055,Deep Learning Engineer,162342,USD,162342,SE,CT,United States,L,United States,0,"Deep Learning, SQL, Scala",Associate,7,Manufacturing,2025-03-11,2025-05-06,1837,6.3,Autonomous Tech -AI04056,AI Software Engineer,81152,CAD,101440,MI,FL,Canada,M,Indonesia,50,"Mathematics, Hadoop, SQL, Python, Data Visualization",Master,3,Media,2024-01-16,2024-03-15,1532,5.1,DeepTech Ventures -AI04057,Robotics Engineer,146791,EUR,124772,SE,PT,Germany,L,Germany,50,"MLOps, Git, Kubernetes",Bachelor,6,Media,2024-11-07,2024-12-21,661,6.9,Predictive Systems -AI04058,AI Architect,231457,SGD,300894,EX,FL,Singapore,M,Singapore,0,"Computer Vision, TensorFlow, Linux, Tableau",Associate,13,Manufacturing,2024-01-28,2024-03-28,671,6.5,Cognitive Computing -AI04059,Data Scientist,114857,EUR,97628,SE,PT,Austria,S,Argentina,0,"Python, TensorFlow, Tableau, NLP",Associate,7,Manufacturing,2024-06-26,2024-07-27,1809,9.5,Future Systems -AI04060,Computer Vision Engineer,73750,USD,73750,EX,CT,China,L,China,50,"Spark, PyTorch, SQL, Computer Vision",Associate,15,Gaming,2024-07-29,2024-09-12,1258,9.7,TechCorp Inc -AI04061,Data Engineer,87162,SGD,113311,EN,FL,Singapore,L,Singapore,50,"Computer Vision, Spark, Python, Scala",Bachelor,0,Real Estate,2024-10-20,2024-11-29,979,9.8,Autonomous Tech -AI04062,Machine Learning Engineer,85264,USD,85264,EX,CT,China,M,China,50,"Linux, Java, Docker, SQL, Git",Master,17,Education,2025-01-09,2025-02-11,1762,8.9,Digital Transformation LLC -AI04063,Principal Data Scientist,72355,CAD,90444,EN,FL,Canada,M,Canada,0,"Git, MLOps, Kubernetes, Hadoop",Associate,0,Energy,2024-11-15,2025-01-27,1357,5.3,TechCorp Inc -AI04064,ML Ops Engineer,83615,AUD,112880,MI,CT,Australia,S,Australia,50,"Git, Hadoop, Mathematics",Associate,4,Retail,2024-01-09,2024-02-05,2152,9.3,DataVision Ltd -AI04065,Machine Learning Researcher,201139,USD,201139,SE,FT,United States,L,Denmark,0,"Python, Azure, TensorFlow, Hadoop",PhD,8,Energy,2025-03-07,2025-04-17,2236,8.2,Digital Transformation LLC -AI04066,Research Scientist,227744,USD,227744,EX,FT,Denmark,M,Denmark,50,"Docker, Mathematics, R, SQL, Computer Vision",Bachelor,11,Media,2025-02-23,2025-04-26,656,9.3,Predictive Systems -AI04067,Research Scientist,50231,CAD,62789,EN,PT,Canada,M,Canada,100,"Scala, Spark, SQL, Mathematics",Associate,1,Media,2024-07-17,2024-07-31,572,7.1,Machine Intelligence Group -AI04068,Data Analyst,149410,EUR,126999,EX,FT,Austria,M,Austria,50,"Kubernetes, PyTorch, MLOps",PhD,15,Automotive,2024-04-20,2024-06-19,941,9.2,AI Innovations -AI04069,Data Engineer,322650,CHF,290385,EX,FL,Switzerland,S,Switzerland,50,"NLP, Linux, Python",PhD,18,Consulting,2024-07-24,2024-08-24,1900,6.3,Autonomous Tech -AI04070,Head of AI,138075,CAD,172594,SE,FL,Canada,L,Canada,50,"GCP, Kubernetes, Data Visualization, SQL",Bachelor,8,Technology,2025-03-05,2025-04-21,2390,6.1,Cloud AI Solutions -AI04071,Data Engineer,70492,USD,70492,MI,FL,South Korea,L,South Korea,0,"NLP, R, Kubernetes, Linux, TensorFlow",Bachelor,4,Media,2024-09-10,2024-11-05,1832,8.5,DataVision Ltd -AI04072,AI Architect,50946,USD,50946,EN,FT,South Korea,S,South Korea,0,"Deep Learning, Java, Computer Vision, AWS, Kubernetes",Associate,0,Transportation,2024-05-11,2024-07-06,1102,7.1,Autonomous Tech -AI04073,AI Architect,74567,JPY,8202370,EN,FT,Japan,M,Sweden,0,"TensorFlow, Linux, Python, SQL, AWS",Associate,1,Manufacturing,2024-02-19,2024-03-15,514,5.3,Cognitive Computing -AI04074,Machine Learning Engineer,63683,AUD,85972,EN,CT,Australia,L,Australia,100,"Python, NLP, GCP, Mathematics, Git",Associate,0,Government,2024-12-08,2025-01-07,1692,5.7,TechCorp Inc -AI04075,AI Product Manager,93281,USD,93281,EN,FT,United States,L,Ukraine,100,"Hadoop, Python, Azure, Spark, Statistics",Bachelor,1,Technology,2024-08-20,2024-10-15,1066,6.7,Cloud AI Solutions -AI04076,Deep Learning Engineer,86606,CAD,108258,MI,PT,Canada,S,Ireland,0,"Docker, Scala, Linux",Bachelor,3,Media,2024-05-08,2024-06-29,573,6.2,Smart Analytics -AI04077,AI Software Engineer,114314,EUR,97167,SE,CT,France,M,France,100,"Azure, Git, Hadoop, Data Visualization, Mathematics",PhD,7,Media,2024-09-26,2024-11-11,743,5.1,AI Innovations -AI04078,Machine Learning Researcher,44105,USD,44105,SE,PT,India,L,India,0,"Java, Hadoop, MLOps",PhD,6,Retail,2024-07-10,2024-09-01,724,5.7,Future Systems -AI04079,AI Specialist,87807,EUR,74636,MI,FT,Austria,L,Austria,50,"PyTorch, Git, Java, Scala, TensorFlow",Bachelor,3,Automotive,2024-03-30,2024-04-19,2006,7.2,AI Innovations -AI04080,Principal Data Scientist,105998,AUD,143097,MI,FT,Australia,L,Australia,100,"Spark, Tableau, GCP, Linux, Hadoop",Bachelor,4,Energy,2024-09-05,2024-11-16,1627,7.3,Cloud AI Solutions -AI04081,Deep Learning Engineer,205845,CHF,185261,SE,CT,Switzerland,M,Portugal,0,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Associate,9,Telecommunications,2024-03-05,2024-04-06,2211,8.5,Machine Intelligence Group -AI04082,AI Architect,108031,SGD,140440,SE,CT,Singapore,S,Singapore,50,"Mathematics, Azure, PyTorch",Associate,6,Manufacturing,2024-09-20,2024-10-30,1358,9.2,DeepTech Ventures -AI04083,AI Consultant,43599,USD,43599,MI,PT,China,S,China,50,"MLOps, R, TensorFlow, SQL, GCP",Associate,4,Media,2024-02-23,2024-05-01,2059,6.4,Quantum Computing Inc -AI04084,Data Scientist,100782,GBP,75587,MI,FL,United Kingdom,S,United Kingdom,100,"Mathematics, R, SQL, Spark",Bachelor,3,Manufacturing,2025-02-21,2025-04-09,2245,9.9,Algorithmic Solutions -AI04085,Autonomous Systems Engineer,124064,SGD,161283,SE,PT,Singapore,S,Israel,50,"Java, Scala, NLP, Azure",PhD,8,Gaming,2024-12-25,2025-02-16,1257,7.4,DataVision Ltd -AI04086,Head of AI,32020,USD,32020,EN,FL,China,L,China,100,"SQL, Hadoop, PyTorch, Linux",Associate,1,Media,2024-01-09,2024-01-30,878,8.5,Algorithmic Solutions -AI04087,Machine Learning Engineer,88815,USD,88815,MI,FL,Finland,M,Finland,50,"Linux, Java, Git, Mathematics, NLP",Bachelor,3,Finance,2024-08-21,2024-10-25,2150,6.1,Digital Transformation LLC -AI04088,Data Analyst,102567,CHF,92310,MI,FT,Switzerland,M,Switzerland,50,"Hadoop, Python, PyTorch",Master,4,Consulting,2025-01-14,2025-03-03,1066,7.6,Predictive Systems -AI04089,Computer Vision Engineer,72234,USD,72234,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, SQL, Python, Kubernetes",Associate,1,Telecommunications,2024-03-08,2024-05-01,1659,9.1,Algorithmic Solutions -AI04090,NLP Engineer,284726,CHF,256253,EX,FL,Switzerland,M,Italy,0,"Python, PyTorch, TensorFlow",Master,15,Gaming,2025-02-28,2025-05-07,697,6.5,Algorithmic Solutions -AI04091,Principal Data Scientist,103801,EUR,88231,MI,CT,Netherlands,M,Russia,50,"NLP, AWS, Linux, Statistics, Computer Vision",Master,3,Telecommunications,2025-02-22,2025-03-08,1806,5.2,Neural Networks Co -AI04092,AI Specialist,211598,EUR,179858,EX,FT,Germany,L,Israel,50,"TensorFlow, Scala, Hadoop, Deep Learning, PyTorch",Master,10,Manufacturing,2024-11-18,2025-01-20,1067,6.5,Cloud AI Solutions -AI04093,Principal Data Scientist,65479,GBP,49109,EN,CT,United Kingdom,M,Portugal,50,"GCP, Kubernetes, SQL",Associate,1,Manufacturing,2024-08-06,2024-10-05,2120,8.9,DataVision Ltd -AI04094,ML Ops Engineer,55701,CAD,69626,EN,CT,Canada,S,Canada,50,"Azure, PyTorch, Git",Associate,1,Energy,2024-10-09,2024-12-21,1684,9,TechCorp Inc -AI04095,Machine Learning Researcher,265222,CHF,238700,EX,CT,Switzerland,S,Switzerland,0,"Git, Azure, Spark, Mathematics, AWS",Master,14,Gaming,2025-03-09,2025-03-27,1418,9.8,TechCorp Inc -AI04096,NLP Engineer,33734,USD,33734,MI,FT,China,S,China,50,"R, SQL, NLP, Azure",Associate,4,Gaming,2024-04-27,2024-06-29,964,7.2,Smart Analytics -AI04097,AI Software Engineer,69684,USD,69684,MI,FT,South Korea,S,Spain,50,"Git, R, Tableau, SQL",Bachelor,3,Energy,2025-02-01,2025-03-03,850,7.1,Future Systems -AI04098,AI Specialist,96701,AUD,130546,MI,FT,Australia,L,Australia,50,"PyTorch, Hadoop, Git",Master,4,Technology,2024-07-20,2024-09-30,1167,9.2,Predictive Systems -AI04099,Deep Learning Engineer,180946,USD,180946,EX,FL,Ireland,M,Ireland,50,"Scala, AWS, Git, Hadoop",Bachelor,19,Finance,2024-12-14,2025-01-31,1194,8.5,Advanced Robotics -AI04100,Data Analyst,166915,USD,166915,EX,FL,Finland,M,Finland,100,"Java, PyTorch, Kubernetes, Mathematics, Data Visualization",Associate,12,Technology,2025-02-04,2025-04-08,880,5.2,AI Innovations -AI04101,Autonomous Systems Engineer,121685,USD,121685,SE,FL,Sweden,M,Sweden,0,"Data Visualization, Deep Learning, Python, Statistics",Bachelor,9,Consulting,2024-03-13,2024-05-15,1830,5.2,TechCorp Inc -AI04102,Research Scientist,167790,USD,167790,SE,FL,Norway,L,Norway,100,"Linux, NLP, Python",Bachelor,6,Government,2025-02-27,2025-03-16,1947,9.7,DeepTech Ventures -AI04103,Robotics Engineer,80516,EUR,68439,EN,CT,Netherlands,M,Netherlands,0,"Scala, Git, SQL, Python",PhD,1,Media,2024-09-13,2024-10-21,1007,6,Cognitive Computing -AI04104,Data Scientist,100310,GBP,75233,MI,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Docker, GCP",Associate,2,Education,2024-01-18,2024-03-05,1460,7.7,Cognitive Computing -AI04105,Research Scientist,120643,USD,120643,SE,FT,Sweden,M,Sweden,0,"Docker, R, Deep Learning, Java, Computer Vision",Associate,6,Technology,2025-04-21,2025-06-23,817,7.2,Cognitive Computing -AI04106,AI Architect,68168,EUR,57943,MI,PT,Austria,S,Austria,100,"PyTorch, Linux, SQL, GCP, R",Bachelor,3,Telecommunications,2025-01-09,2025-02-22,2194,5.9,TechCorp Inc -AI04107,Data Engineer,103407,USD,103407,EX,FL,India,L,India,0,"Python, NLP, Statistics",Master,17,Government,2024-10-30,2024-12-23,2100,6.4,Cognitive Computing -AI04108,Principal Data Scientist,79353,JPY,8728830,EN,FT,Japan,M,Japan,0,"GCP, PyTorch, NLP",PhD,0,Telecommunications,2024-05-04,2024-06-19,1235,7,AI Innovations -AI04109,Principal Data Scientist,215826,GBP,161870,EX,FT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Azure, R, Statistics",Associate,14,Telecommunications,2024-04-03,2024-05-25,886,8.7,DeepTech Ventures -AI04110,Data Analyst,124330,EUR,105681,MI,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Deep Learning",Master,3,Retail,2024-12-12,2025-02-19,1635,5.3,Advanced Robotics -AI04111,Machine Learning Engineer,53595,EUR,45556,EN,FT,France,M,Luxembourg,100,"NLP, Git, Docker, Hadoop, Spark",Master,0,Consulting,2024-09-19,2024-11-06,1568,5.2,Advanced Robotics -AI04112,AI Research Scientist,141469,EUR,120249,EX,FL,Germany,S,Germany,0,"R, Python, Computer Vision",Master,14,Transportation,2024-06-08,2024-08-02,1693,6.5,Predictive Systems -AI04113,Computer Vision Engineer,115046,USD,115046,MI,FT,Sweden,L,Sweden,100,"Kubernetes, AWS, GCP, Scala",Master,4,Media,2025-03-14,2025-05-23,739,8,Predictive Systems -AI04114,Machine Learning Engineer,147907,CHF,133116,MI,PT,Switzerland,M,Egypt,0,"SQL, AWS, Scala, Tableau",Associate,4,Automotive,2025-03-11,2025-04-01,1372,8.8,Machine Intelligence Group -AI04115,AI Product Manager,50641,USD,50641,EX,FL,India,S,Hungary,50,"Data Visualization, GCP, R, Hadoop",PhD,19,Healthcare,2024-06-19,2024-08-25,1905,9.3,DataVision Ltd -AI04116,AI Product Manager,214441,EUR,182275,EX,FL,Netherlands,M,Philippines,0,"Linux, Scala, Python, NLP, Mathematics",PhD,10,Manufacturing,2024-02-19,2024-03-29,2265,6.3,Future Systems -AI04117,Computer Vision Engineer,114417,GBP,85813,MI,FL,United Kingdom,M,United Kingdom,50,"Python, R, Mathematics",PhD,2,Technology,2024-03-28,2024-05-14,2050,9.9,Digital Transformation LLC -AI04118,AI Consultant,112932,JPY,12422520,MI,FT,Japan,L,Japan,100,"Scala, Computer Vision, NLP, PyTorch, Spark",Bachelor,4,Healthcare,2025-03-03,2025-04-08,2449,9.3,Autonomous Tech -AI04119,ML Ops Engineer,72211,USD,72211,EN,CT,Israel,L,Israel,0,"Git, Scala, SQL, Mathematics",Bachelor,0,Retail,2024-04-16,2024-05-05,2062,9.8,Cognitive Computing -AI04120,Deep Learning Engineer,182222,AUD,246000,EX,CT,Australia,L,Spain,100,"Azure, Deep Learning, Java",Master,18,Energy,2024-10-01,2024-11-06,1155,7.2,AI Innovations -AI04121,Machine Learning Engineer,83596,EUR,71057,EN,FT,Germany,L,Germany,50,"Data Visualization, NLP, Kubernetes, Python",PhD,0,Government,2025-01-04,2025-03-18,1822,5.2,Future Systems -AI04122,NLP Engineer,109011,CHF,98110,EN,FT,Switzerland,L,Switzerland,50,"PyTorch, Computer Vision, Data Visualization, R",Associate,1,Consulting,2024-01-25,2024-03-12,2002,8.6,DataVision Ltd -AI04123,Deep Learning Engineer,74573,AUD,100674,EN,PT,Australia,L,Australia,0,"Git, Python, Mathematics, Tableau, Docker",PhD,0,Retail,2024-10-21,2024-12-26,926,8.1,Cognitive Computing -AI04124,Principal Data Scientist,117158,EUR,99584,MI,PT,Netherlands,L,Philippines,50,"Python, TensorFlow, Git, Computer Vision, Azure",Master,2,Consulting,2024-11-19,2024-12-17,1918,6.4,Future Systems -AI04125,Head of AI,84442,JPY,9288620,MI,FL,Japan,M,Sweden,50,"SQL, TensorFlow, Mathematics",PhD,2,Telecommunications,2024-12-30,2025-02-23,1372,6.8,Cloud AI Solutions -AI04126,Machine Learning Researcher,64765,USD,64765,EX,FL,India,L,Brazil,100,"PyTorch, Scala, Hadoop, Computer Vision",PhD,11,Media,2024-05-14,2024-06-24,1270,5.8,Algorithmic Solutions -AI04127,Data Scientist,161364,USD,161364,SE,FT,Norway,S,Norway,100,"AWS, MLOps, SQL, Azure",Bachelor,9,Real Estate,2024-02-27,2024-04-29,1176,6.5,Algorithmic Solutions -AI04128,Data Scientist,259567,AUD,350415,EX,PT,Australia,L,Australia,0,"GCP, Docker, Python, Azure, Data Visualization",Master,11,Government,2025-03-23,2025-05-11,789,10,Smart Analytics -AI04129,Machine Learning Engineer,58926,USD,58926,MI,FT,South Korea,S,Finland,0,"Statistics, PyTorch, Java, Scala, Azure",Bachelor,3,Education,2024-05-19,2024-07-04,1330,9.8,Smart Analytics -AI04130,Machine Learning Researcher,205317,USD,205317,SE,FL,United States,L,Argentina,100,"Scala, AWS, Tableau",Associate,7,Government,2024-10-25,2024-12-18,2425,7.3,Neural Networks Co -AI04131,Robotics Engineer,142793,CHF,128514,MI,PT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Mathematics, Statistics, GCP",Bachelor,4,Telecommunications,2024-06-19,2024-08-18,1439,7,Algorithmic Solutions -AI04132,AI Architect,48948,USD,48948,SE,FL,India,L,India,50,"Git, GCP, Python, AWS, NLP",Bachelor,5,Technology,2024-08-30,2024-09-19,2439,8.5,Neural Networks Co -AI04133,Machine Learning Engineer,101284,USD,101284,MI,FL,Ireland,M,Ireland,0,"Kubernetes, Docker, R, Azure",Bachelor,2,Finance,2024-05-07,2024-06-14,2361,7.2,Future Systems -AI04134,Autonomous Systems Engineer,94804,USD,94804,MI,CT,South Korea,L,Vietnam,100,"SQL, PyTorch, GCP",Associate,2,Finance,2025-04-20,2025-06-25,1817,8.7,Cognitive Computing -AI04135,AI Consultant,55274,SGD,71856,EN,FT,Singapore,S,Singapore,0,"Python, TensorFlow, Spark, Deep Learning",Associate,1,Real Estate,2024-12-13,2025-02-04,1539,8.1,DataVision Ltd -AI04136,Machine Learning Engineer,46056,EUR,39148,EN,CT,France,S,France,100,"Kubernetes, Scala, GCP",Associate,1,Government,2024-07-03,2024-09-12,2123,7.8,Smart Analytics -AI04137,AI Research Scientist,71471,SGD,92912,EN,CT,Singapore,M,Singapore,100,"Linux, Kubernetes, NLP, Deep Learning, Scala",Master,0,Education,2024-07-31,2024-09-20,989,6.3,Quantum Computing Inc -AI04138,Data Analyst,173574,AUD,234325,EX,CT,Australia,S,Australia,0,"Linux, Hadoop, R",Master,12,Finance,2025-03-07,2025-04-30,832,5.8,AI Innovations -AI04139,AI Software Engineer,228777,CAD,285971,EX,PT,Canada,L,Canada,0,"Scala, Deep Learning, Data Visualization, Kubernetes, Statistics",PhD,18,Energy,2024-10-02,2024-10-24,2368,8.5,Algorithmic Solutions -AI04140,Data Engineer,218206,AUD,294578,EX,FL,Australia,M,Australia,0,"Linux, TensorFlow, Statistics, Python, Computer Vision",PhD,17,Technology,2025-04-27,2025-06-05,2119,5.6,Digital Transformation LLC -AI04141,Autonomous Systems Engineer,218548,EUR,185766,EX,CT,Netherlands,L,Netherlands,100,"Git, Hadoop, Linux",Master,11,Energy,2024-11-08,2025-01-09,1487,9.7,Digital Transformation LLC -AI04142,Data Scientist,137310,EUR,116714,SE,FT,France,M,France,100,"Scala, NLP, Java, Kubernetes, Linux",PhD,5,Government,2024-10-27,2024-12-13,1017,5.8,Advanced Robotics -AI04143,Research Scientist,112353,EUR,95500,MI,CT,Netherlands,L,Netherlands,0,"PyTorch, GCP, Mathematics, Deep Learning",Associate,2,Media,2024-11-18,2025-01-29,1367,9.6,Algorithmic Solutions -AI04144,Data Analyst,217691,EUR,185037,EX,FT,Germany,M,Germany,50,"R, SQL, NLP",PhD,10,Real Estate,2025-01-17,2025-03-04,1455,9.8,Machine Intelligence Group -AI04145,Data Engineer,82416,EUR,70054,MI,FL,France,L,France,100,"Git, Tableau, Hadoop, Java, Linux",PhD,2,Telecommunications,2024-07-25,2024-08-08,1499,9.1,Machine Intelligence Group -AI04146,Data Engineer,271408,USD,271408,EX,CT,Finland,L,Finland,50,"Kubernetes, R, SQL",Associate,19,Real Estate,2025-02-22,2025-05-04,2037,5.3,Neural Networks Co -AI04147,Robotics Engineer,50767,USD,50767,EN,FT,Israel,M,Israel,100,"Kubernetes, Git, Python",Master,0,Government,2024-08-13,2024-10-04,735,9.7,DeepTech Ventures -AI04148,Computer Vision Engineer,110614,EUR,94022,SE,FT,France,L,France,100,"SQL, Python, Kubernetes",Master,6,Real Estate,2024-12-11,2025-01-01,1473,5.7,Autonomous Tech -AI04149,Computer Vision Engineer,92141,EUR,78320,MI,CT,Netherlands,M,Spain,100,"Scala, Python, Statistics, Deep Learning",PhD,3,Technology,2024-04-18,2024-05-15,1681,6.9,DeepTech Ventures -AI04150,Machine Learning Engineer,48318,USD,48318,EN,FL,South Korea,M,South Korea,50,"Spark, Kubernetes, Statistics",PhD,1,Retail,2025-04-08,2025-04-22,871,5.6,Cloud AI Solutions -AI04151,Research Scientist,263753,EUR,224190,EX,FL,Austria,L,Austria,100,"Linux, Python, Git, Spark",Bachelor,11,Automotive,2024-04-23,2024-06-02,850,8.3,Algorithmic Solutions -AI04152,Machine Learning Researcher,273323,CHF,245991,EX,PT,Switzerland,M,Switzerland,50,"SQL, Statistics, Tableau",PhD,12,Automotive,2025-04-10,2025-05-26,991,8.7,Machine Intelligence Group -AI04153,Research Scientist,62268,USD,62268,MI,FT,Finland,S,Vietnam,0,"Docker, SQL, Spark, Linux",Associate,2,Transportation,2025-02-21,2025-04-13,1843,6.9,Cognitive Computing -AI04154,NLP Engineer,116686,USD,116686,MI,FT,Ireland,L,Ireland,50,"Azure, SQL, Data Visualization, Python, Kubernetes",Master,2,Finance,2025-04-16,2025-06-21,2006,9.9,Smart Analytics -AI04155,AI Research Scientist,129353,EUR,109950,SE,FL,Germany,M,Germany,0,"Python, Deep Learning, Java",PhD,9,Finance,2024-12-29,2025-03-08,2476,8.5,Smart Analytics -AI04156,Principal Data Scientist,267772,EUR,227606,EX,FT,Netherlands,L,Netherlands,0,"Python, R, MLOps, GCP, Kubernetes",Master,15,Real Estate,2024-12-28,2025-02-11,1950,7.8,Quantum Computing Inc -AI04157,AI Architect,59923,EUR,50935,EN,CT,Netherlands,M,Netherlands,100,"R, Java, Mathematics, MLOps, NLP",Associate,1,Consulting,2025-02-04,2025-04-06,1615,7.1,AI Innovations -AI04158,Data Analyst,75531,USD,75531,EX,CT,India,L,India,0,"Java, R, Spark, MLOps",PhD,11,Manufacturing,2024-11-09,2025-01-18,1354,9.1,Quantum Computing Inc -AI04159,AI Specialist,71196,USD,71196,EN,FL,Israel,L,Chile,0,"Data Visualization, Deep Learning, Docker",Master,1,Transportation,2024-01-27,2024-03-21,2117,9.2,Neural Networks Co -AI04160,AI Specialist,88243,USD,88243,MI,FL,Sweden,S,Germany,50,"SQL, Java, PyTorch",Master,2,Automotive,2024-10-03,2024-10-24,1074,9,Future Systems -AI04161,Robotics Engineer,105621,JPY,11618310,SE,PT,Japan,S,Japan,100,"Python, R, GCP, MLOps, TensorFlow",Associate,7,Gaming,2024-06-03,2024-07-28,889,5.6,AI Innovations -AI04162,AI Product Manager,98658,CAD,123323,SE,CT,Canada,S,Canada,0,"SQL, Scala, Python",Associate,5,Consulting,2024-02-09,2024-03-23,1266,6.2,Algorithmic Solutions -AI04163,Machine Learning Researcher,61301,USD,61301,EX,FL,India,L,India,100,"Python, TensorFlow, GCP",Associate,10,Education,2024-03-19,2024-05-10,1512,7.6,Cognitive Computing -AI04164,Head of AI,170872,USD,170872,EX,FT,Norway,S,Norway,0,"AWS, Hadoop, Data Visualization",PhD,16,Consulting,2024-06-10,2024-07-06,1985,10,Smart Analytics -AI04165,AI Software Engineer,56083,USD,56083,EN,FT,South Korea,L,Nigeria,0,"Kubernetes, Hadoop, Statistics",Bachelor,1,Education,2024-12-06,2025-02-02,1313,8.6,DeepTech Ventures -AI04166,AI Architect,71351,EUR,60648,EN,FL,Netherlands,S,Netherlands,0,"Python, TensorFlow, Computer Vision, PyTorch, SQL",PhD,1,Finance,2024-11-15,2025-01-20,1598,6.3,Cloud AI Solutions -AI04167,Deep Learning Engineer,131806,AUD,177938,SE,CT,Australia,L,Australia,0,"TensorFlow, Linux, Java",Bachelor,6,Retail,2024-08-13,2024-10-04,2368,6.9,Neural Networks Co -AI04168,Head of AI,85952,USD,85952,EN,CT,Norway,M,Norway,50,"NLP, Data Visualization, TensorFlow, Linux",PhD,1,Automotive,2024-01-07,2024-02-24,1437,7.8,Cloud AI Solutions -AI04169,Head of AI,177858,SGD,231215,SE,FT,Singapore,L,Singapore,0,"TensorFlow, Mathematics, Docker, Tableau, Deep Learning",Associate,8,Education,2024-10-02,2024-10-23,1797,9.6,DeepTech Ventures -AI04170,Head of AI,210574,USD,210574,SE,FL,Denmark,L,Chile,0,"Hadoop, Scala, Python, Computer Vision, Deep Learning",Associate,9,Government,2024-08-24,2024-10-31,874,6.1,TechCorp Inc -AI04171,Computer Vision Engineer,96894,USD,96894,MI,FT,South Korea,L,Vietnam,100,"Scala, Spark, Data Visualization",Master,4,Gaming,2024-11-18,2025-01-25,1945,5.2,AI Innovations -AI04172,AI Research Scientist,137829,AUD,186069,EX,FL,Australia,M,Australia,100,"GCP, Hadoop, PyTorch, Spark, R",Bachelor,16,Energy,2024-11-03,2024-12-28,1831,7.4,Neural Networks Co -AI04173,Data Analyst,99906,USD,99906,MI,CT,Israel,M,Israel,50,"Kubernetes, SQL, Python, Deep Learning",Bachelor,4,Education,2024-05-30,2024-07-27,517,8,DeepTech Ventures -AI04174,AI Consultant,78189,CAD,97736,EN,FT,Canada,L,Canada,50,"Docker, GCP, Java, Mathematics",Bachelor,1,Retail,2024-06-21,2024-07-29,2449,5.3,DeepTech Ventures -AI04175,Head of AI,221259,JPY,24338490,EX,CT,Japan,L,Austria,100,"Python, SQL, Scala, Tableau",PhD,12,Energy,2025-01-22,2025-02-15,1106,8.1,AI Innovations -AI04176,Data Engineer,69907,GBP,52430,EN,CT,United Kingdom,S,United Kingdom,100,"GCP, Git, SQL, NLP",Bachelor,1,Retail,2024-09-15,2024-11-01,531,7,Predictive Systems -AI04177,Computer Vision Engineer,114573,EUR,97387,MI,CT,Germany,L,Germany,0,"Scala, TensorFlow, SQL",Master,4,Manufacturing,2024-02-22,2024-03-24,1045,8.9,Algorithmic Solutions -AI04178,Autonomous Systems Engineer,91770,CAD,114713,SE,PT,Canada,S,Canada,100,"Python, Deep Learning, TensorFlow, Hadoop, GCP",Master,7,Finance,2025-02-08,2025-03-04,1669,9.5,Autonomous Tech -AI04179,AI Research Scientist,97661,EUR,83012,SE,FT,Germany,S,Germany,0,"Scala, Data Visualization, Git, AWS, Hadoop",PhD,5,Healthcare,2024-12-24,2025-02-02,1681,7.9,Cognitive Computing -AI04180,Machine Learning Researcher,93001,USD,93001,SE,FT,Israel,S,Israel,0,"R, Kubernetes, AWS",Master,8,Healthcare,2024-05-23,2024-08-01,2033,7.1,Cloud AI Solutions -AI04181,Machine Learning Researcher,138207,CAD,172759,EX,FL,Canada,S,Canada,50,"AWS, Java, Data Visualization",Bachelor,19,Healthcare,2024-01-30,2024-02-22,1932,5.6,Future Systems -AI04182,ML Ops Engineer,87070,EUR,74010,MI,FT,Austria,L,Ghana,0,"Data Visualization, Kubernetes, SQL, Deep Learning, GCP",Bachelor,4,Real Estate,2024-02-17,2024-03-08,1838,5.7,Future Systems -AI04183,Research Scientist,102685,USD,102685,SE,FT,South Korea,S,Indonesia,0,"NLP, Kubernetes, PyTorch, Azure, Tableau",Bachelor,9,Consulting,2024-10-03,2024-11-26,1996,9,DataVision Ltd -AI04184,AI Consultant,36735,USD,36735,MI,CT,India,M,India,0,"Python, AWS, Data Visualization, TensorFlow, Spark",Associate,2,Media,2025-02-12,2025-03-19,1482,7.2,Cognitive Computing -AI04185,Machine Learning Researcher,141810,EUR,120539,EX,PT,Germany,M,Germany,100,"Kubernetes, Azure, Statistics, R, Tableau",Associate,18,Telecommunications,2024-04-09,2024-06-16,1488,5.2,Algorithmic Solutions -AI04186,Head of AI,44764,USD,44764,EN,FT,South Korea,M,South Korea,50,"Spark, Kubernetes, NLP, Python, Linux",Associate,1,Energy,2025-02-08,2025-02-27,910,9.1,Future Systems -AI04187,Machine Learning Engineer,251178,EUR,213501,EX,FL,Austria,L,Austria,0,"GCP, Scala, SQL, Deep Learning",Associate,15,Government,2024-08-10,2024-09-30,674,5,Digital Transformation LLC -AI04188,Autonomous Systems Engineer,293534,USD,293534,EX,CT,Norway,M,Norway,50,"Java, PyTorch, AWS, R, Hadoop",Associate,19,Healthcare,2025-04-13,2025-05-31,1581,5.8,DataVision Ltd -AI04189,Data Scientist,47064,USD,47064,EN,PT,Ireland,S,Ireland,0,"Python, Linux, Computer Vision, Azure",Master,1,Technology,2024-04-16,2024-05-26,941,9.6,TechCorp Inc -AI04190,NLP Engineer,133682,SGD,173787,SE,PT,Singapore,M,Singapore,100,"Data Visualization, Kubernetes, R, AWS, NLP",Master,6,Technology,2024-12-05,2025-02-11,1401,8.7,TechCorp Inc -AI04191,Machine Learning Researcher,104881,GBP,78661,SE,CT,United Kingdom,S,United Kingdom,0,"R, Scala, Linux",PhD,5,Real Estate,2024-12-20,2025-01-26,2075,7.9,Future Systems -AI04192,Data Scientist,93613,USD,93613,EX,FT,India,L,India,100,"Azure, PyTorch, Hadoop",Bachelor,11,Technology,2025-01-05,2025-02-06,672,5.7,AI Innovations -AI04193,AI Architect,207719,USD,207719,EX,FT,Sweden,S,Sweden,50,"Tableau, AWS, PyTorch",Associate,17,Consulting,2024-10-02,2024-12-12,1642,5.8,Autonomous Tech -AI04194,Data Scientist,169583,JPY,18654130,EX,FT,Japan,S,Japan,100,"Python, Statistics, Azure, Tableau, Scala",Associate,15,Transportation,2024-12-09,2025-02-18,2352,7.7,Digital Transformation LLC -AI04195,Data Scientist,102146,CHF,91931,EN,FT,Switzerland,M,Japan,0,"Python, Deep Learning, R",PhD,1,Technology,2025-01-07,2025-02-20,2109,5.2,Machine Intelligence Group -AI04196,AI Product Manager,171881,AUD,232039,SE,FL,Australia,L,Australia,50,"PyTorch, AWS, Data Visualization, Git, Deep Learning",PhD,6,Consulting,2024-05-12,2024-07-24,1188,8.1,AI Innovations -AI04197,Data Scientist,24066,USD,24066,EN,FT,India,S,France,0,"TensorFlow, Computer Vision, Python",Master,0,Finance,2024-12-26,2025-01-09,838,7.7,Cloud AI Solutions -AI04198,AI Architect,149018,EUR,126665,EX,PT,France,L,France,0,"TensorFlow, Docker, Spark, NLP",Associate,18,Finance,2024-09-03,2024-09-22,2468,7.6,Future Systems -AI04199,Principal Data Scientist,119622,AUD,161490,SE,PT,Australia,S,Australia,100,"AWS, Scala, Kubernetes, Mathematics",Bachelor,5,Consulting,2024-01-01,2024-03-14,1210,6.5,Smart Analytics -AI04200,Machine Learning Researcher,135418,USD,135418,SE,FT,Sweden,M,Sweden,0,"Kubernetes, GCP, Docker",PhD,8,Gaming,2024-02-15,2024-04-09,2215,6.1,Algorithmic Solutions -AI04201,Robotics Engineer,80410,GBP,60308,MI,PT,United Kingdom,M,United Kingdom,100,"Scala, PyTorch, NLP",Bachelor,2,Retail,2024-05-12,2024-07-04,2221,8,Predictive Systems -AI04202,AI Architect,158403,JPY,17424330,SE,PT,Japan,M,Netherlands,0,"R, Kubernetes, Git",PhD,6,Real Estate,2024-03-15,2024-05-05,2333,8.8,Machine Intelligence Group -AI04203,Deep Learning Engineer,143401,EUR,121891,EX,CT,Austria,M,Austria,50,"Git, Computer Vision, Statistics, Kubernetes, Java",PhD,18,Telecommunications,2024-01-26,2024-04-04,2218,9.7,Advanced Robotics -AI04204,NLP Engineer,72505,USD,72505,MI,CT,Israel,S,Israel,0,"SQL, Linux, Scala",Bachelor,2,Gaming,2025-04-26,2025-06-01,2155,6.3,Digital Transformation LLC -AI04205,Principal Data Scientist,101052,EUR,85894,MI,CT,France,L,France,100,"Java, Python, Mathematics, GCP, Spark",Bachelor,3,Real Estate,2024-09-09,2024-11-13,2376,6,Algorithmic Solutions -AI04206,Robotics Engineer,90464,CAD,113080,MI,FT,Canada,S,Canada,50,"Scala, Kubernetes, Mathematics, Tableau, Hadoop",Master,3,Finance,2024-11-29,2025-01-16,1450,5.1,DeepTech Ventures -AI04207,Machine Learning Engineer,155870,USD,155870,EX,CT,Finland,M,Finland,100,"GCP, SQL, PyTorch, Data Visualization",Bachelor,18,Technology,2024-06-03,2024-08-08,2068,8.4,TechCorp Inc -AI04208,Autonomous Systems Engineer,86105,USD,86105,EX,FL,India,M,India,100,"TensorFlow, Linux, Azure, Kubernetes, Spark",Associate,16,Finance,2025-01-30,2025-03-07,2236,7.9,Algorithmic Solutions -AI04209,AI Software Engineer,60304,EUR,51258,EN,PT,Germany,M,Germany,100,"SQL, Scala, Azure",Master,1,Media,2024-09-27,2024-12-04,1530,8.9,Algorithmic Solutions -AI04210,NLP Engineer,158258,USD,158258,SE,CT,Denmark,S,Denmark,50,"NLP, MLOps, Python, Deep Learning",Master,8,Finance,2024-07-18,2024-08-18,1416,9.5,Future Systems -AI04211,Robotics Engineer,139108,USD,139108,SE,FT,Denmark,M,Hungary,50,"GCP, R, Spark, Data Visualization, Docker",PhD,7,Healthcare,2024-05-05,2024-05-19,2202,7.9,Advanced Robotics -AI04212,Robotics Engineer,127647,GBP,95735,SE,FL,United Kingdom,L,United Kingdom,50,"SQL, Kubernetes, TensorFlow, AWS, R",Master,8,Gaming,2024-06-22,2024-07-14,1248,8.1,Smart Analytics -AI04213,NLP Engineer,113026,CAD,141283,SE,FT,Canada,L,Canada,50,"NLP, Linux, Python, Deep Learning, Java",Associate,8,Gaming,2025-01-09,2025-02-21,1025,8.4,AI Innovations -AI04214,NLP Engineer,160446,USD,160446,EX,FT,United States,M,United States,50,"Mathematics, SQL, MLOps, PyTorch",Associate,16,Manufacturing,2024-04-26,2024-07-07,2148,5.5,AI Innovations -AI04215,Research Scientist,170414,USD,170414,SE,FT,Denmark,S,Denmark,50,"Kubernetes, Azure, Computer Vision",Associate,5,Gaming,2024-08-14,2024-09-16,2394,8.1,Predictive Systems -AI04216,Robotics Engineer,153701,USD,153701,EX,FT,Finland,L,France,100,"Spark, Kubernetes, Statistics",PhD,15,Telecommunications,2024-08-04,2024-09-08,641,6.6,Neural Networks Co -AI04217,AI Research Scientist,66536,SGD,86497,EN,FT,Singapore,M,Singapore,50,"Mathematics, SQL, Kubernetes",Bachelor,1,Government,2024-03-17,2024-04-17,952,9.9,Cloud AI Solutions -AI04218,Autonomous Systems Engineer,144573,USD,144573,EX,CT,South Korea,S,South Korea,100,"Linux, Statistics, GCP, Python, Computer Vision",PhD,18,Energy,2024-11-30,2025-02-10,1931,8,Quantum Computing Inc -AI04219,Autonomous Systems Engineer,39124,USD,39124,SE,FT,India,M,India,0,"Deep Learning, MLOps, Statistics, Spark",Master,5,Manufacturing,2024-10-12,2024-11-15,2309,5.7,Quantum Computing Inc -AI04220,Machine Learning Researcher,148877,EUR,126545,SE,FL,Netherlands,L,Netherlands,50,"Hadoop, Docker, NLP",Associate,5,Consulting,2024-06-28,2024-08-17,1349,9.8,Smart Analytics -AI04221,Research Scientist,62439,AUD,84293,EN,FT,Australia,S,Australia,100,"Java, Python, Kubernetes, GCP",Bachelor,1,Technology,2024-06-05,2024-06-29,1944,7.9,DeepTech Ventures -AI04222,Data Analyst,70705,USD,70705,MI,PT,South Korea,M,South Korea,0,"Data Visualization, Hadoop, Tableau, Mathematics, Linux",PhD,4,Healthcare,2025-01-21,2025-03-04,2030,5.6,DataVision Ltd -AI04223,AI Software Engineer,136064,USD,136064,EX,PT,Israel,M,Israel,100,"SQL, Python, Tableau",Master,13,Energy,2024-12-26,2025-01-14,2276,9.4,DataVision Ltd -AI04224,Machine Learning Researcher,114102,GBP,85577,SE,CT,United Kingdom,S,United Kingdom,50,"GCP, AWS, NLP",Bachelor,9,Manufacturing,2025-02-20,2025-03-15,515,9.1,Neural Networks Co -AI04225,ML Ops Engineer,48875,USD,48875,SE,CT,China,S,Germany,0,"Spark, PyTorch, Java, NLP",Associate,7,Education,2024-05-15,2024-06-07,843,10,Neural Networks Co -AI04226,ML Ops Engineer,66920,USD,66920,EN,CT,Denmark,M,Kenya,0,"Deep Learning, Linux, Computer Vision",Bachelor,1,Gaming,2025-02-18,2025-04-04,1486,7,AI Innovations -AI04227,Deep Learning Engineer,60046,USD,60046,EN,FT,United States,S,Australia,0,"Git, Scala, NLP, SQL, Azure",Bachelor,1,Transportation,2025-04-27,2025-06-06,992,7.9,Machine Intelligence Group -AI04228,Machine Learning Engineer,65824,EUR,55950,MI,FL,France,S,France,0,"Azure, GCP, Mathematics, Scala, TensorFlow",Associate,4,Government,2024-03-31,2024-05-26,639,9.4,Predictive Systems -AI04229,Computer Vision Engineer,92205,USD,92205,MI,FL,Finland,M,Finland,0,"Git, Spark, Deep Learning, AWS",Bachelor,4,Transportation,2024-06-18,2024-08-03,1381,5.8,DataVision Ltd -AI04230,Principal Data Scientist,69016,EUR,58664,MI,FL,Germany,S,Germany,50,"Spark, Linux, Kubernetes, Mathematics",Associate,2,Finance,2024-03-20,2024-04-26,954,6,Machine Intelligence Group -AI04231,AI Consultant,71384,USD,71384,EN,FL,Ireland,M,Ireland,100,"Python, Java, Deep Learning",PhD,0,Finance,2024-01-12,2024-02-27,1060,7.8,DataVision Ltd -AI04232,Data Scientist,63659,EUR,54110,EN,PT,Germany,S,United States,100,"GCP, SQL, Tableau, MLOps",Associate,0,Technology,2024-11-29,2025-01-18,1082,9.9,DeepTech Ventures -AI04233,AI Research Scientist,117611,GBP,88208,SE,FL,United Kingdom,M,Vietnam,0,"PyTorch, Tableau, Hadoop, TensorFlow, Statistics",Associate,7,Media,2025-01-05,2025-01-24,1849,6.6,Digital Transformation LLC -AI04234,Deep Learning Engineer,48074,USD,48074,EN,FL,Sweden,S,Sweden,0,"PyTorch, Python, Spark, Azure, SQL",Bachelor,0,Government,2024-12-26,2025-01-23,606,7.4,Future Systems -AI04235,Principal Data Scientist,122232,EUR,103897,SE,CT,Germany,S,Colombia,0,"R, Java, GCP, Python, Hadoop",Associate,8,Automotive,2025-02-27,2025-03-13,1471,5,Digital Transformation LLC -AI04236,Head of AI,197539,EUR,167908,EX,FL,France,L,Turkey,0,"Kubernetes, PyTorch, Docker, TensorFlow, Python",Master,13,Consulting,2025-01-01,2025-02-26,904,7,Cloud AI Solutions -AI04237,AI Specialist,255683,EUR,217331,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Tableau, Azure",Associate,18,Telecommunications,2024-03-15,2024-04-25,1130,9,Cognitive Computing -AI04238,Machine Learning Engineer,77121,USD,77121,EN,FL,Israel,L,Hungary,100,"SQL, Azure, PyTorch",Associate,1,Consulting,2024-10-06,2024-12-18,2312,6.9,Predictive Systems -AI04239,ML Ops Engineer,52575,USD,52575,MI,FL,China,L,South Africa,50,"Hadoop, Git, Python, Kubernetes",Bachelor,4,Finance,2025-01-23,2025-03-16,624,9.7,Machine Intelligence Group -AI04240,Autonomous Systems Engineer,86907,EUR,73871,SE,CT,Austria,S,Austria,100,"Spark, Data Visualization, AWS, R",Associate,6,Retail,2024-01-18,2024-03-11,733,7.3,Advanced Robotics -AI04241,Computer Vision Engineer,148771,EUR,126455,SE,CT,Germany,M,Germany,0,"Spark, Kubernetes, Deep Learning",Associate,6,Retail,2025-02-12,2025-02-26,2370,9.4,Autonomous Tech -AI04242,Deep Learning Engineer,124742,EUR,106031,SE,FL,Netherlands,L,Netherlands,0,"Python, Scala, Linux, Tableau, TensorFlow",Bachelor,7,Media,2024-11-13,2025-01-07,972,5.2,Cognitive Computing -AI04243,AI Specialist,80538,USD,80538,MI,PT,Sweden,M,Sweden,0,"Hadoop, Azure, Computer Vision, SQL, R",Bachelor,3,Manufacturing,2024-05-26,2024-07-25,1372,7.4,TechCorp Inc -AI04244,Deep Learning Engineer,261998,CHF,235798,EX,FT,Switzerland,S,Switzerland,0,"NLP, R, Computer Vision, Python, Azure",Bachelor,13,Energy,2024-01-21,2024-03-29,751,8.6,Future Systems -AI04245,Data Scientist,161380,JPY,17751800,EX,FT,Japan,M,Japan,0,"Python, Scala, Computer Vision, Hadoop",Master,13,Media,2024-05-14,2024-06-26,1306,6.2,Digital Transformation LLC -AI04246,Research Scientist,114449,USD,114449,SE,PT,Ireland,S,Thailand,0,"Scala, Git, SQL, NLP",PhD,8,Telecommunications,2024-04-22,2024-06-30,683,7.6,Autonomous Tech -AI04247,Robotics Engineer,65542,AUD,88482,EN,FT,Australia,M,Malaysia,0,"Java, Deep Learning, PyTorch, Data Visualization, Tableau",Associate,1,Education,2024-06-29,2024-09-01,1053,7,Predictive Systems -AI04248,Machine Learning Researcher,177905,JPY,19569550,EX,CT,Japan,M,Japan,100,"Kubernetes, SQL, Deep Learning",Bachelor,10,Transportation,2024-01-12,2024-03-07,1848,9.9,Cloud AI Solutions -AI04249,NLP Engineer,89958,SGD,116945,EN,FL,Singapore,L,Singapore,0,"Java, Docker, Deep Learning",Bachelor,1,Automotive,2025-01-04,2025-03-08,993,7.6,AI Innovations -AI04250,Data Scientist,50166,USD,50166,EN,CT,South Korea,S,South Korea,100,"Deep Learning, R, MLOps, Tableau, Scala",Associate,0,Automotive,2024-09-20,2024-11-21,1812,6.3,Cognitive Computing -AI04251,Research Scientist,153548,USD,153548,MI,FT,Denmark,L,Denmark,50,"Statistics, Spark, SQL",PhD,3,Manufacturing,2024-12-03,2025-01-01,977,6,Neural Networks Co -AI04252,AI Research Scientist,199709,CHF,179738,SE,CT,Switzerland,M,Switzerland,100,"GCP, R, NLP, Deep Learning",Associate,9,Consulting,2024-09-29,2024-11-07,992,5.7,Digital Transformation LLC -AI04253,Research Scientist,106748,USD,106748,SE,PT,South Korea,M,South Korea,50,"Scala, Kubernetes, SQL, NLP",Associate,5,Finance,2024-08-11,2024-10-05,501,5.7,Predictive Systems -AI04254,AI Consultant,164745,CHF,148271,SE,PT,Switzerland,S,Switzerland,100,"Computer Vision, NLP, Kubernetes, Scala, Java",Associate,6,Consulting,2024-04-08,2024-05-09,2246,7.6,Cloud AI Solutions -AI04255,Principal Data Scientist,74190,EUR,63062,MI,FL,Austria,S,Austria,0,"Java, PyTorch, Docker, Computer Vision, GCP",Associate,4,Energy,2024-06-10,2024-06-28,1983,9.9,Digital Transformation LLC -AI04256,AI Specialist,77889,EUR,66206,EN,FT,Netherlands,L,Netherlands,100,"Linux, Mathematics, MLOps",Associate,1,Transportation,2024-05-29,2024-07-24,517,6.5,Autonomous Tech -AI04257,Autonomous Systems Engineer,172285,EUR,146442,EX,PT,Austria,S,Austria,100,"Python, Java, Git, AWS, TensorFlow",Master,10,Automotive,2024-05-20,2024-07-15,1924,7.6,Machine Intelligence Group -AI04258,Robotics Engineer,192684,JPY,21195240,EX,FL,Japan,S,Japan,100,"Mathematics, TensorFlow, Deep Learning, Git, Spark",Associate,17,Manufacturing,2024-04-02,2024-05-25,509,5.2,Advanced Robotics -AI04259,Machine Learning Engineer,62085,USD,62085,SE,PT,China,L,China,50,"NLP, PyTorch, Kubernetes, Linux, SQL",Bachelor,6,Technology,2024-11-25,2025-01-24,2146,9.1,AI Innovations -AI04260,Autonomous Systems Engineer,70641,USD,70641,SE,FT,China,M,China,50,"Statistics, R, Python, Git",Master,9,Retail,2024-02-10,2024-03-13,960,9.9,Neural Networks Co -AI04261,Deep Learning Engineer,57845,AUD,78091,EN,CT,Australia,S,Australia,50,"Statistics, Python, PyTorch, R, Spark",Associate,1,Technology,2025-04-19,2025-05-15,1260,5.4,Quantum Computing Inc -AI04262,Deep Learning Engineer,70641,USD,70641,EX,PT,India,S,India,0,"Statistics, Tableau, R, Spark, GCP",Associate,18,Government,2024-10-30,2024-11-19,623,9.6,Autonomous Tech -AI04263,NLP Engineer,266056,SGD,345873,EX,FL,Singapore,L,Singapore,50,"SQL, PyTorch, NLP, Python",Associate,13,Transportation,2024-02-02,2024-03-01,1761,9.8,Digital Transformation LLC -AI04264,AI Software Engineer,39810,USD,39810,MI,PT,China,L,India,100,"PyTorch, Spark, Data Visualization, Kubernetes",Master,3,Telecommunications,2024-10-30,2024-12-17,1598,7.4,Algorithmic Solutions -AI04265,ML Ops Engineer,46834,USD,46834,MI,FT,China,L,China,0,"Git, GCP, AWS, Mathematics",Bachelor,3,Media,2024-06-30,2024-08-02,2086,7.2,AI Innovations -AI04266,Autonomous Systems Engineer,151336,GBP,113502,SE,FT,United Kingdom,L,United Kingdom,100,"Kubernetes, Python, Scala, GCP",Bachelor,7,Technology,2025-03-26,2025-04-16,930,7.3,Cloud AI Solutions -AI04267,AI Consultant,76149,EUR,64727,EN,PT,Austria,L,Austria,0,"Linux, Hadoop, Statistics, Scala, Mathematics",PhD,0,Technology,2025-04-08,2025-06-09,2299,9.7,Cognitive Computing -AI04268,AI Specialist,132231,USD,132231,EX,PT,Israel,S,Israel,100,"Tableau, Python, TensorFlow",Master,11,Automotive,2024-09-20,2024-11-24,526,6.7,Cognitive Computing -AI04269,AI Consultant,163387,USD,163387,SE,CT,Denmark,M,Denmark,50,"R, AWS, Git, Data Visualization",Bachelor,7,Transportation,2024-08-19,2024-10-30,635,5.8,DataVision Ltd -AI04270,Deep Learning Engineer,63017,SGD,81922,EN,CT,Singapore,M,Singapore,50,"Spark, Python, Java, Docker, Scala",Associate,1,Media,2024-12-10,2025-02-10,2238,5.3,Predictive Systems -AI04271,NLP Engineer,33704,USD,33704,MI,FT,India,S,Austria,0,"Java, Python, Mathematics, Git",PhD,4,Technology,2024-10-13,2024-12-18,1957,9.6,Smart Analytics -AI04272,NLP Engineer,199909,USD,199909,EX,CT,Finland,M,Finland,100,"Spark, Git, Linux, Statistics",Master,10,Technology,2024-08-31,2024-09-21,2126,7.7,Future Systems -AI04273,AI Specialist,109037,USD,109037,MI,PT,United States,M,United States,0,"Kubernetes, Python, PyTorch",PhD,2,Consulting,2024-04-29,2024-06-25,1905,6.3,Algorithmic Solutions -AI04274,Data Analyst,79918,EUR,67930,EN,FT,France,L,France,50,"Spark, Computer Vision, AWS, SQL",Associate,0,Gaming,2024-03-12,2024-04-05,2142,6.6,DataVision Ltd -AI04275,Data Analyst,140756,EUR,119643,EX,CT,Austria,S,Romania,50,"MLOps, Python, Tableau",PhD,12,Education,2025-03-06,2025-03-28,1437,5.1,Autonomous Tech -AI04276,Research Scientist,193092,CAD,241365,EX,CT,Canada,S,France,0,"Scala, Git, Data Visualization, Mathematics, Tableau",Associate,14,Automotive,2024-10-29,2024-11-12,2415,9.2,Quantum Computing Inc -AI04277,Head of AI,152328,USD,152328,MI,FT,Norway,L,Norway,50,"Java, Python, AWS",Associate,4,Healthcare,2024-10-09,2024-12-07,1932,6.3,Advanced Robotics -AI04278,NLP Engineer,115808,USD,115808,MI,FL,Norway,L,Norway,100,"Python, TensorFlow, Mathematics, Scala",Bachelor,3,Telecommunications,2024-03-27,2024-04-29,1892,7.4,Cognitive Computing -AI04279,Head of AI,123117,EUR,104649,SE,CT,Austria,S,Austria,50,"Git, AWS, Docker",Bachelor,6,Automotive,2025-01-14,2025-03-02,951,6.4,DataVision Ltd -AI04280,AI Architect,48031,USD,48031,EN,CT,Israel,S,New Zealand,100,"PyTorch, Mathematics, MLOps, SQL, Deep Learning",PhD,1,Automotive,2024-05-15,2024-06-08,1171,6.9,DeepTech Ventures -AI04281,Research Scientist,267720,USD,267720,EX,FL,United States,S,United States,100,"Tableau, Scala, Hadoop, SQL, Kubernetes",Master,16,Technology,2024-07-19,2024-08-30,2497,9.6,Neural Networks Co -AI04282,Head of AI,130274,JPY,14330140,SE,FT,Japan,L,Luxembourg,50,"SQL, Docker, PyTorch, Git",Master,5,Government,2025-04-21,2025-06-04,2222,5.6,Neural Networks Co -AI04283,Deep Learning Engineer,217100,USD,217100,SE,CT,Norway,L,Hungary,0,"Java, Computer Vision, SQL, NLP, Linux",Master,9,Retail,2025-03-08,2025-04-15,593,5.2,Autonomous Tech -AI04284,AI Software Engineer,69518,USD,69518,EN,FT,Denmark,S,Denmark,100,"NLP, SQL, Linux, Scala",Bachelor,1,Education,2024-03-09,2024-03-25,1880,7.4,Cognitive Computing -AI04285,AI Specialist,149647,CAD,187059,EX,FL,Canada,S,Canada,0,"Spark, SQL, Python, Computer Vision",Associate,14,Finance,2025-03-12,2025-05-15,2155,9.2,Digital Transformation LLC -AI04286,NLP Engineer,56185,SGD,73041,EN,PT,Singapore,S,New Zealand,50,"Kubernetes, Data Visualization, Python, TensorFlow, GCP",Bachelor,1,Transportation,2025-04-11,2025-06-10,1919,5.2,Future Systems -AI04287,Head of AI,47695,USD,47695,EN,FT,Sweden,S,Sweden,50,"Spark, Kubernetes, NLP, TensorFlow, Deep Learning",PhD,0,Gaming,2024-01-14,2024-02-24,1378,7.9,DeepTech Ventures -AI04288,AI Specialist,100301,EUR,85256,SE,PT,Germany,S,Germany,50,"Hadoop, Kubernetes, Scala, Computer Vision",PhD,7,Retail,2024-07-17,2024-08-31,1403,9.4,Quantum Computing Inc -AI04289,Machine Learning Engineer,66736,USD,66736,MI,FL,South Korea,M,South Korea,100,"Linux, Kubernetes, Data Visualization, Hadoop, Computer Vision",PhD,4,Gaming,2024-08-25,2024-09-20,754,5.8,Future Systems -AI04290,Principal Data Scientist,71795,JPY,7897450,EN,FL,Japan,L,Egypt,50,"SQL, PyTorch, TensorFlow, Azure",PhD,1,Government,2024-03-21,2024-04-26,2175,5.4,Cognitive Computing -AI04291,ML Ops Engineer,40743,USD,40743,MI,FT,China,M,China,50,"SQL, PyTorch, Data Visualization, Scala",PhD,4,Consulting,2024-05-01,2024-06-09,1212,5.2,Quantum Computing Inc -AI04292,Deep Learning Engineer,50361,EUR,42807,EN,FT,France,M,Belgium,100,"Linux, SQL, Hadoop, Python, Computer Vision",Bachelor,1,Media,2024-09-02,2024-09-25,607,7.3,Algorithmic Solutions -AI04293,Computer Vision Engineer,25504,USD,25504,EN,CT,India,S,India,100,"Python, Deep Learning, NLP, Mathematics, Spark",Master,0,Manufacturing,2024-12-01,2025-01-31,1174,6.5,Algorithmic Solutions -AI04294,Robotics Engineer,100549,USD,100549,SE,FT,South Korea,S,Spain,50,"Kubernetes, Statistics, Spark",Master,5,Healthcare,2024-07-23,2024-09-25,1869,8.2,Autonomous Tech -AI04295,Machine Learning Engineer,96451,EUR,81983,SE,PT,Austria,S,Austria,50,"Deep Learning, Git, Python",Master,7,Transportation,2024-12-23,2025-02-16,1078,7.9,Quantum Computing Inc -AI04296,NLP Engineer,94478,USD,94478,SE,FL,Sweden,S,Sweden,0,"Data Visualization, Computer Vision, Kubernetes",Bachelor,9,Media,2024-04-18,2024-06-14,677,8.3,Autonomous Tech -AI04297,Data Analyst,69250,EUR,58863,EN,CT,Netherlands,S,Ukraine,100,"Linux, PyTorch, R, Java, Git",Master,1,Automotive,2025-01-17,2025-03-05,1851,5.7,DataVision Ltd -AI04298,Data Analyst,99816,USD,99816,MI,CT,Ireland,L,Estonia,100,"Docker, Python, MLOps, Linux, TensorFlow",PhD,2,Retail,2024-02-29,2024-04-10,1889,9.9,Advanced Robotics -AI04299,Data Scientist,151190,USD,151190,SE,FL,Sweden,M,Sweden,100,"Kubernetes, Hadoop, Scala",Bachelor,7,Automotive,2024-04-24,2024-05-23,1258,9.2,Algorithmic Solutions -AI04300,Principal Data Scientist,234904,JPY,25839440,EX,PT,Japan,S,Japan,50,"Kubernetes, Data Visualization, Spark, Docker",PhD,15,Manufacturing,2024-08-03,2024-09-25,1974,9.6,Autonomous Tech -AI04301,AI Architect,100583,CHF,90525,EN,CT,Switzerland,L,China,100,"Computer Vision, AWS, Scala",Bachelor,1,Government,2024-05-11,2024-07-03,1471,8,DeepTech Ventures -AI04302,Head of AI,193990,USD,193990,EX,PT,United States,L,Israel,0,"Python, Kubernetes, Tableau",Associate,15,Consulting,2024-12-25,2025-03-03,2132,8.8,Digital Transformation LLC -AI04303,AI Product Manager,138206,EUR,117475,SE,FL,France,L,United Kingdom,100,"Statistics, PyTorch, Computer Vision, Mathematics, TensorFlow",Associate,7,Education,2025-03-24,2025-05-05,2261,8.5,Neural Networks Co -AI04304,Data Analyst,130833,AUD,176625,SE,PT,Australia,M,Austria,50,"Git, Scala, TensorFlow, AWS, R",Associate,6,Telecommunications,2024-12-06,2025-02-08,1325,6.7,DataVision Ltd -AI04305,Data Scientist,178524,USD,178524,SE,PT,Denmark,M,Sweden,50,"Python, Azure, Tableau, Hadoop",PhD,9,Healthcare,2024-01-31,2024-03-14,1457,7,Quantum Computing Inc -AI04306,NLP Engineer,58009,USD,58009,EN,FT,South Korea,S,South Korea,0,"Data Visualization, Git, Hadoop, SQL",PhD,0,Finance,2024-04-12,2024-05-18,650,9.2,Predictive Systems -AI04307,Autonomous Systems Engineer,51134,USD,51134,MI,CT,China,L,China,100,"TensorFlow, Statistics, Deep Learning",Bachelor,2,Education,2024-09-22,2024-11-21,2371,9,Future Systems -AI04308,Data Engineer,121528,EUR,103299,SE,FT,Germany,M,Germany,100,"TensorFlow, Kubernetes, Computer Vision, Tableau, Data Visualization",Associate,7,Energy,2025-04-03,2025-06-07,1250,5.6,Advanced Robotics -AI04309,NLP Engineer,161005,USD,161005,SE,CT,Israel,L,Israel,50,"Spark, PyTorch, Tableau",Bachelor,8,Transportation,2024-09-14,2024-10-22,2281,8.4,DeepTech Ventures -AI04310,Head of AI,172723,GBP,129542,EX,FL,United Kingdom,M,Ireland,50,"SQL, Git, PyTorch, Linux, Data Visualization",Bachelor,11,Media,2024-03-12,2024-05-19,2264,8.2,Advanced Robotics -AI04311,AI Consultant,124515,EUR,105838,EX,CT,Austria,S,Latvia,100,"Docker, Linux, Data Visualization, SQL",PhD,13,Transportation,2025-02-24,2025-05-06,2164,6.2,Cloud AI Solutions -AI04312,AI Research Scientist,80001,CAD,100001,EN,CT,Canada,L,Canada,0,"Docker, Kubernetes, Spark",Bachelor,1,Manufacturing,2024-01-19,2024-02-02,827,6,Neural Networks Co -AI04313,ML Ops Engineer,106148,EUR,90226,SE,CT,Netherlands,S,Ghana,0,"SQL, TensorFlow, Hadoop",Master,8,Education,2024-12-05,2025-02-10,1912,5.4,Cognitive Computing -AI04314,Computer Vision Engineer,88162,EUR,74938,MI,FL,France,M,France,50,"Data Visualization, Scala, GCP, Python, PyTorch",Master,2,Real Estate,2025-04-16,2025-05-29,1187,5.3,DeepTech Ventures -AI04315,Principal Data Scientist,80965,USD,80965,MI,CT,Israel,S,Argentina,0,"Tableau, Linux, Azure",Master,3,Gaming,2025-03-16,2025-04-03,1786,6,Predictive Systems -AI04316,AI Software Engineer,102591,USD,102591,MI,FL,Sweden,L,Sweden,50,"Docker, SQL, Hadoop, PyTorch",Bachelor,3,Real Estate,2024-06-14,2024-07-17,1331,6.2,Autonomous Tech -AI04317,Data Analyst,83458,CAD,104323,EN,FL,Canada,L,Romania,0,"Mathematics, Kubernetes, MLOps, Hadoop",Bachelor,0,Consulting,2024-06-14,2024-08-21,1749,6.3,Quantum Computing Inc -AI04318,Machine Learning Engineer,131559,EUR,111825,SE,CT,Germany,S,Austria,0,"Hadoop, Linux, Docker",PhD,5,Transportation,2024-01-12,2024-02-25,1897,8.8,Predictive Systems -AI04319,Robotics Engineer,103944,USD,103944,MI,FT,Finland,M,Finland,100,"Linux, MLOps, Computer Vision",PhD,2,Government,2024-10-04,2024-12-14,661,5.1,Smart Analytics -AI04320,AI Specialist,92612,USD,92612,EX,FL,China,S,China,0,"Java, Kubernetes, Python, Git",Bachelor,18,Consulting,2024-12-05,2025-02-02,2154,8.7,Autonomous Tech -AI04321,AI Product Manager,91367,USD,91367,SE,PT,South Korea,M,Luxembourg,100,"Azure, TensorFlow, Tableau, Hadoop",Master,5,Healthcare,2024-03-16,2024-05-04,1310,9.8,TechCorp Inc -AI04322,Deep Learning Engineer,102393,CHF,92154,EN,FL,Switzerland,L,Romania,100,"Azure, Deep Learning, Linux, Tableau, SQL",PhD,1,Consulting,2025-04-29,2025-06-12,1531,7.9,Digital Transformation LLC -AI04323,Computer Vision Engineer,126897,EUR,107862,EX,PT,Austria,S,Austria,50,"Python, SQL, Linux",Bachelor,17,Transportation,2024-07-30,2024-08-21,2068,9.9,Future Systems -AI04324,Deep Learning Engineer,49677,USD,49677,EN,FL,Israel,S,Canada,50,"Tableau, Docker, Kubernetes, Scala, Deep Learning",Bachelor,0,Manufacturing,2024-07-04,2024-08-30,2192,9.4,DataVision Ltd -AI04325,Data Scientist,220260,USD,220260,EX,FT,Sweden,S,Sweden,100,"Data Visualization, TensorFlow, Java, Docker",Master,19,Real Estate,2024-06-24,2024-08-24,1627,5.8,Autonomous Tech -AI04326,NLP Engineer,124924,USD,124924,SE,FL,South Korea,M,Singapore,50,"Linux, SQL, PyTorch",Master,6,Consulting,2024-11-13,2024-12-11,2445,8.4,Machine Intelligence Group -AI04327,Autonomous Systems Engineer,221162,USD,221162,SE,FT,Denmark,L,Denmark,100,"PyTorch, Scala, TensorFlow",PhD,8,Government,2024-07-18,2024-09-24,2325,9.6,Predictive Systems -AI04328,Deep Learning Engineer,68143,EUR,57922,EN,FT,France,S,Colombia,100,"Scala, TensorFlow, Azure, Mathematics",PhD,0,Energy,2024-06-07,2024-06-28,504,7.4,DataVision Ltd -AI04329,Machine Learning Engineer,139571,USD,139571,MI,FL,Denmark,L,Germany,0,"Kubernetes, Spark, PyTorch, Docker, AWS",Associate,2,Healthcare,2024-03-23,2024-05-26,2296,8.7,Advanced Robotics -AI04330,Data Analyst,75216,EUR,63934,MI,CT,Austria,M,Austria,50,"Scala, SQL, PyTorch",Associate,4,Education,2024-05-30,2024-08-04,2468,5.5,TechCorp Inc -AI04331,Data Scientist,185001,USD,185001,EX,CT,Denmark,S,Denmark,100,"Mathematics, Python, NLP",Bachelor,16,Gaming,2025-01-16,2025-03-25,1924,8,Smart Analytics -AI04332,AI Software Engineer,92328,JPY,10156080,MI,CT,Japan,L,Japan,50,"Python, GCP, Docker, Data Visualization, Linux",Master,2,Gaming,2024-01-28,2024-04-10,914,8.2,Predictive Systems -AI04333,AI Product Manager,100927,USD,100927,MI,FT,Denmark,S,Canada,50,"Docker, Tableau, Python, Linux, Mathematics",Bachelor,4,Energy,2025-03-20,2025-04-04,787,8.1,AI Innovations -AI04334,Deep Learning Engineer,99845,SGD,129799,MI,CT,Singapore,L,Singapore,0,"Python, Computer Vision, Scala, Docker",PhD,4,Automotive,2024-08-31,2024-10-08,812,8.4,Neural Networks Co -AI04335,Autonomous Systems Engineer,77405,EUR,65794,EN,CT,Germany,L,Austria,0,"Data Visualization, R, Java, Spark, Linux",Bachelor,0,Consulting,2024-05-01,2024-06-13,649,6,Algorithmic Solutions -AI04336,Deep Learning Engineer,60738,GBP,45554,EN,PT,United Kingdom,S,United Kingdom,50,"Python, Docker, AWS, TensorFlow",Master,0,Automotive,2024-03-22,2024-04-26,555,5.7,Digital Transformation LLC -AI04337,AI Software Engineer,105471,JPY,11601810,MI,FL,Japan,L,Japan,0,"Git, Deep Learning, Statistics",Master,4,Energy,2024-06-18,2024-08-02,1116,6.6,Machine Intelligence Group -AI04338,Deep Learning Engineer,159419,USD,159419,EX,FL,Israel,S,Ghana,0,"Deep Learning, SQL, Tableau, Linux",Master,18,Healthcare,2024-01-03,2024-01-28,925,9.1,AI Innovations -AI04339,ML Ops Engineer,90738,SGD,117959,MI,PT,Singapore,M,Singapore,0,"Spark, GCP, Tableau",Bachelor,3,Energy,2024-12-14,2025-01-14,2148,9,Future Systems -AI04340,Machine Learning Engineer,90479,USD,90479,MI,FT,Finland,S,Austria,50,"Java, Python, GCP, Mathematics, TensorFlow",Bachelor,3,Media,2025-02-13,2025-04-22,2020,8.3,Advanced Robotics -AI04341,NLP Engineer,155058,USD,155058,SE,FL,Ireland,L,Ireland,100,"Data Visualization, Python, SQL",Associate,9,Manufacturing,2024-11-21,2024-12-28,1821,8.5,Machine Intelligence Group -AI04342,AI Research Scientist,85529,USD,85529,MI,CT,Israel,S,Israel,50,"Deep Learning, Mathematics, GCP, Kubernetes, Git",Master,2,Consulting,2024-01-12,2024-02-28,1458,7.7,Quantum Computing Inc -AI04343,AI Research Scientist,86082,SGD,111907,MI,FL,Singapore,S,Singapore,100,"Hadoop, Deep Learning, Computer Vision, PyTorch, R",Master,4,Transportation,2025-01-27,2025-03-26,1346,5.7,DataVision Ltd -AI04344,Autonomous Systems Engineer,96560,USD,96560,EN,FT,Norway,L,Norway,50,"R, Spark, SQL, Deep Learning, Python",PhD,1,Automotive,2024-09-22,2024-11-24,1139,8.2,Machine Intelligence Group -AI04345,Research Scientist,83531,EUR,71001,EN,PT,Austria,L,Ghana,100,"TensorFlow, Kubernetes, Mathematics, NLP",Bachelor,0,Gaming,2024-12-04,2025-01-15,1024,5.5,Predictive Systems -AI04346,AI Research Scientist,113892,EUR,96808,SE,FL,Germany,S,Singapore,100,"Data Visualization, Scala, Deep Learning, Docker",Bachelor,8,Automotive,2025-02-16,2025-03-05,863,8,DeepTech Ventures -AI04347,Data Engineer,261519,JPY,28767090,EX,CT,Japan,M,Japan,50,"R, PyTorch, Scala",PhD,18,Media,2024-07-10,2024-08-28,1671,5.4,Neural Networks Co -AI04348,AI Consultant,112036,USD,112036,MI,CT,Israel,L,Israel,50,"Python, MLOps, TensorFlow",PhD,4,Transportation,2025-02-11,2025-04-25,2093,6.4,Autonomous Tech -AI04349,Data Analyst,91847,USD,91847,EN,PT,Sweden,L,Sweden,100,"Deep Learning, Java, Tableau, PyTorch, Git",Associate,0,Government,2024-02-17,2024-03-15,1937,9.1,Cognitive Computing -AI04350,NLP Engineer,58336,USD,58336,EN,FL,Sweden,S,Sweden,0,"TensorFlow, Java, R",Associate,1,Consulting,2025-02-27,2025-05-03,1310,5.9,Digital Transformation LLC -AI04351,AI Research Scientist,66684,USD,66684,EN,CT,Ireland,M,Ireland,0,"SQL, Python, AWS, TensorFlow",Associate,1,Technology,2025-03-07,2025-04-19,533,7.4,Cloud AI Solutions -AI04352,Research Scientist,91813,USD,91813,MI,PT,Ireland,M,Ireland,0,"R, Mathematics, Tableau, NLP, Data Visualization",Bachelor,3,Gaming,2024-12-26,2025-02-18,1649,7.9,TechCorp Inc -AI04353,AI Consultant,138037,USD,138037,SE,CT,United States,M,United States,0,"Azure, TensorFlow, GCP",Master,7,Transportation,2024-03-25,2024-04-27,1243,7.5,Autonomous Tech -AI04354,Data Analyst,118721,USD,118721,EN,CT,Denmark,L,New Zealand,50,"Hadoop, Tableau, Azure, MLOps, PyTorch",Associate,1,Real Estate,2025-03-21,2025-04-15,2159,7.7,Digital Transformation LLC -AI04355,NLP Engineer,70536,USD,70536,EN,FL,Israel,L,Ghana,50,"Azure, Scala, Docker",Master,1,Technology,2024-04-20,2024-06-05,2136,8.6,Future Systems -AI04356,Research Scientist,96320,EUR,81872,MI,PT,France,L,France,0,"Kubernetes, TensorFlow, NLP",Associate,4,Gaming,2024-12-26,2025-02-28,1277,5.5,TechCorp Inc -AI04357,Head of AI,134322,EUR,114174,SE,FT,Austria,L,Austria,100,"GCP, Deep Learning, Git, Python",Bachelor,8,Consulting,2024-02-03,2024-04-13,848,6.9,Autonomous Tech -AI04358,Robotics Engineer,61853,USD,61853,EN,FL,United States,M,United States,100,"Spark, R, Data Visualization",Master,0,Finance,2024-04-10,2024-05-17,1366,7.6,TechCorp Inc -AI04359,Robotics Engineer,118786,EUR,100968,SE,CT,Austria,S,Austria,0,"Scala, SQL, Computer Vision",Bachelor,5,Consulting,2024-07-22,2024-08-19,818,8.3,Cognitive Computing -AI04360,Autonomous Systems Engineer,63582,USD,63582,EN,FL,Ireland,S,Ireland,50,"Spark, AWS, GCP",PhD,1,Media,2024-01-11,2024-03-21,2243,9.4,Cognitive Computing -AI04361,Machine Learning Engineer,120025,AUD,162034,SE,FT,Australia,L,Norway,50,"PyTorch, Kubernetes, Spark, Java, Mathematics",Bachelor,8,Transportation,2025-03-13,2025-04-02,2126,7.5,Quantum Computing Inc -AI04362,Data Analyst,69623,EUR,59180,MI,CT,France,S,France,0,"Python, SQL, Java, R, AWS",PhD,2,Real Estate,2024-12-02,2025-01-02,1244,9.6,Machine Intelligence Group -AI04363,AI Architect,84572,USD,84572,EN,CT,Denmark,M,Denmark,50,"NLP, Computer Vision, Data Visualization, Deep Learning",Master,0,Finance,2024-07-03,2024-08-31,1897,8,Machine Intelligence Group -AI04364,Machine Learning Engineer,75649,USD,75649,SE,CT,China,L,China,100,"TensorFlow, Linux, Spark, Python, Azure",PhD,8,Transportation,2024-07-23,2024-09-19,1102,5.3,Smart Analytics -AI04365,AI Software Engineer,101898,USD,101898,EN,FL,Norway,M,Netherlands,50,"Python, Scala, Docker, Mathematics, AWS",Bachelor,1,Automotive,2024-03-26,2024-04-18,2051,5.1,Smart Analytics -AI04366,AI Product Manager,146918,EUR,124880,SE,FT,Netherlands,M,Kenya,50,"R, MLOps, PyTorch, NLP",Master,6,Energy,2024-02-18,2024-03-08,770,10,Advanced Robotics -AI04367,Principal Data Scientist,48437,USD,48437,SE,PT,India,S,Norway,100,"Hadoop, Linux, Azure, Computer Vision",PhD,6,Government,2024-12-31,2025-01-23,1949,8.8,DeepTech Ventures -AI04368,AI Software Engineer,156021,USD,156021,EX,CT,Israel,L,Ireland,100,"Scala, Python, SQL",Associate,15,Energy,2024-10-16,2024-12-16,2144,9,DataVision Ltd -AI04369,Research Scientist,142101,USD,142101,SE,PT,Sweden,L,Sweden,100,"Kubernetes, Java, Data Visualization",Master,7,Energy,2024-01-16,2024-03-26,623,6.7,Advanced Robotics -AI04370,AI Research Scientist,85556,EUR,72723,MI,PT,Germany,L,Germany,0,"TensorFlow, Tableau, Python, GCP",Associate,4,Telecommunications,2024-11-06,2025-01-04,1206,8.4,Quantum Computing Inc -AI04371,AI Research Scientist,36647,USD,36647,MI,PT,China,S,Turkey,0,"Java, AWS, GCP, Computer Vision",PhD,2,Retail,2025-03-11,2025-04-20,2008,7.2,Digital Transformation LLC -AI04372,Data Scientist,82294,EUR,69950,MI,CT,Austria,L,Denmark,50,"Spark, Mathematics, Deep Learning, Computer Vision",Master,2,Finance,2024-02-01,2024-03-25,1644,7.3,Predictive Systems -AI04373,AI Specialist,91519,AUD,123551,MI,FL,Australia,L,Australia,100,"Data Visualization, GCP, AWS, Docker",Bachelor,2,Real Estate,2025-04-13,2025-06-10,2219,6.2,Digital Transformation LLC -AI04374,Data Analyst,67529,USD,67529,SE,CT,China,L,Kenya,0,"Spark, Linux, Data Visualization, Scala",Master,7,Consulting,2025-01-24,2025-02-13,1676,6,AI Innovations -AI04375,Data Engineer,194639,USD,194639,EX,FT,Ireland,L,Ireland,0,"Tableau, NLP, SQL",Bachelor,13,Manufacturing,2024-05-04,2024-07-13,1333,5.7,Algorithmic Solutions -AI04376,AI Product Manager,194962,USD,194962,EX,FL,South Korea,M,South Korea,0,"Tableau, Azure, PyTorch, AWS",PhD,17,Real Estate,2024-12-12,2025-02-01,513,6.2,TechCorp Inc -AI04377,Machine Learning Engineer,68003,CAD,85004,MI,FL,Canada,M,Canada,0,"PyTorch, Linux, TensorFlow, Spark",PhD,3,Gaming,2024-08-11,2024-08-26,534,6.1,Digital Transformation LLC -AI04378,Data Engineer,160113,USD,160113,SE,FL,United States,L,United States,100,"Python, Scala, Azure, AWS",Master,7,Automotive,2024-10-07,2024-11-30,1941,6.5,DeepTech Ventures -AI04379,Head of AI,51041,USD,51041,EN,FT,Ireland,S,Ireland,50,"Hadoop, Linux, Mathematics",Associate,0,Government,2025-01-06,2025-01-24,1849,7.6,Autonomous Tech -AI04380,Robotics Engineer,123576,USD,123576,MI,CT,Denmark,S,Denmark,0,"Java, R, Tableau, AWS",Bachelor,3,Healthcare,2024-04-11,2024-05-21,1068,8.6,Advanced Robotics -AI04381,Machine Learning Researcher,76765,EUR,65250,MI,FT,Netherlands,M,Australia,100,"R, SQL, Tableau, Docker, Deep Learning",Associate,2,Finance,2024-10-25,2024-12-25,1685,6.4,TechCorp Inc -AI04382,Data Scientist,212410,USD,212410,EX,CT,Israel,L,Israel,100,"Hadoop, Azure, Statistics",Bachelor,17,Retail,2024-09-28,2024-11-01,1414,9.4,Cognitive Computing -AI04383,Computer Vision Engineer,64240,USD,64240,SE,PT,China,M,China,50,"Hadoop, Scala, PyTorch",Bachelor,8,Retail,2024-09-01,2024-10-28,2324,6.4,Neural Networks Co -AI04384,Autonomous Systems Engineer,132240,USD,132240,EX,CT,Finland,M,Spain,0,"Tableau, Python, Spark, Statistics",PhD,16,Real Estate,2024-08-22,2024-10-19,1289,8.4,Quantum Computing Inc -AI04385,Machine Learning Engineer,90724,CAD,113405,MI,PT,Canada,S,Belgium,0,"Python, GCP, TensorFlow, Spark, AWS",Master,3,Telecommunications,2024-06-29,2024-08-26,1928,7.8,Cloud AI Solutions -AI04386,Machine Learning Researcher,210905,USD,210905,EX,FT,Norway,L,Norway,100,"PyTorch, TensorFlow, Tableau, Data Visualization, Python",Master,12,Real Estate,2024-03-24,2024-05-11,1507,8.1,Cloud AI Solutions -AI04387,AI Product Manager,113235,AUD,152867,SE,PT,Australia,S,Argentina,0,"Python, TensorFlow, Azure",Master,7,Gaming,2024-03-03,2024-04-25,617,8,Algorithmic Solutions -AI04388,AI Software Engineer,167568,EUR,142433,EX,PT,France,S,United States,50,"Mathematics, PyTorch, SQL, Git, Docker",PhD,19,Government,2025-04-20,2025-05-13,1087,6.4,Quantum Computing Inc -AI04389,Data Engineer,60687,USD,60687,EN,FL,Finland,M,Finland,0,"AWS, NLP, Statistics, Python, Deep Learning",PhD,1,Consulting,2024-07-28,2024-09-29,1930,5.3,Advanced Robotics -AI04390,Computer Vision Engineer,140330,USD,140330,EX,PT,Finland,S,Belgium,50,"Python, Scala, Hadoop, Computer Vision, TensorFlow",PhD,16,Technology,2024-08-13,2024-10-12,1619,7.5,DeepTech Ventures -AI04391,Machine Learning Researcher,87316,EUR,74219,MI,FL,Netherlands,S,Netherlands,50,"Data Visualization, Azure, Git",Bachelor,2,Automotive,2024-04-25,2024-06-13,558,7,Cloud AI Solutions -AI04392,AI Software Engineer,103223,USD,103223,EN,CT,United States,L,United States,50,"Linux, Docker, NLP, Computer Vision, Kubernetes",Bachelor,0,Real Estate,2024-12-01,2025-02-02,1214,5,Advanced Robotics -AI04393,Head of AI,259484,GBP,194613,EX,FL,United Kingdom,L,United Kingdom,100,"Scala, Hadoop, TensorFlow, GCP",PhD,19,Energy,2025-01-04,2025-03-16,1671,5.7,Predictive Systems -AI04394,Machine Learning Researcher,83379,USD,83379,EN,FL,United States,S,United States,100,"Tableau, Scala, SQL",PhD,1,Energy,2024-04-16,2024-05-07,831,6.5,Predictive Systems -AI04395,ML Ops Engineer,108902,GBP,81677,MI,FT,United Kingdom,M,United Kingdom,0,"Linux, MLOps, Data Visualization",Bachelor,3,Technology,2024-04-27,2024-06-13,1500,9.9,Future Systems -AI04396,Data Engineer,56324,USD,56324,EN,FT,Finland,L,Finland,0,"R, SQL, MLOps, Linux",PhD,1,Gaming,2024-02-29,2024-03-16,1319,9.6,Cognitive Computing -AI04397,Principal Data Scientist,117902,EUR,100217,MI,FL,Netherlands,L,Netherlands,100,"Deep Learning, Python, NLP",Bachelor,4,Technology,2024-09-06,2024-10-22,2283,5.6,Algorithmic Solutions -AI04398,AI Software Engineer,113637,EUR,96591,MI,FT,Netherlands,L,Netherlands,50,"Scala, SQL, Statistics",Master,3,Retail,2025-02-15,2025-03-31,1625,7.6,Neural Networks Co -AI04399,AI Specialist,100672,EUR,85571,MI,PT,Germany,M,Israel,100,"R, SQL, TensorFlow",Associate,3,Retail,2024-12-11,2025-02-16,1012,8.1,Cognitive Computing -AI04400,Robotics Engineer,59217,JPY,6513870,EN,FL,Japan,S,Nigeria,100,"SQL, R, Data Visualization",Bachelor,0,Technology,2024-05-26,2024-07-02,1332,6.2,Cloud AI Solutions -AI04401,AI Specialist,180746,USD,180746,EX,FL,Ireland,L,Ireland,0,"Scala, Azure, NLP",Bachelor,18,Finance,2024-02-29,2024-04-12,778,9,Cognitive Computing -AI04402,NLP Engineer,76000,AUD,102600,EN,FT,Australia,M,Russia,50,"Azure, Hadoop, Tableau",Bachelor,1,Retail,2025-02-21,2025-03-30,1457,9,Digital Transformation LLC -AI04403,AI Consultant,158289,CAD,197861,EX,CT,Canada,S,Canada,50,"Azure, Python, AWS, TensorFlow",Associate,19,Finance,2024-03-29,2024-05-07,904,6.7,Autonomous Tech -AI04404,AI Software Engineer,210409,USD,210409,EX,CT,South Korea,L,Denmark,100,"Git, Statistics, Azure, SQL, Computer Vision",Bachelor,12,Telecommunications,2024-05-24,2024-06-13,1401,9.6,AI Innovations -AI04405,Data Analyst,72009,USD,72009,MI,CT,Ireland,S,Ireland,0,"Kubernetes, Tableau, TensorFlow, MLOps, Python",PhD,2,Healthcare,2025-01-15,2025-02-17,1726,7,AI Innovations -AI04406,Computer Vision Engineer,216981,SGD,282075,EX,FT,Singapore,L,Estonia,0,"SQL, MLOps, Git, Docker",Master,12,Government,2025-02-02,2025-02-20,884,5.1,Cognitive Computing -AI04407,AI Architect,125378,USD,125378,MI,FL,Denmark,M,Denmark,100,"Spark, Computer Vision, NLP, R",Bachelor,4,Consulting,2024-07-28,2024-08-17,1609,8.1,Advanced Robotics -AI04408,Machine Learning Researcher,80879,USD,80879,MI,CT,United States,S,United States,50,"AWS, Tableau, Linux",PhD,3,Automotive,2024-10-17,2024-12-25,1607,8.5,Cloud AI Solutions -AI04409,Data Scientist,304522,SGD,395879,EX,FT,Singapore,L,Vietnam,0,"TensorFlow, Python, Tableau, Docker",Master,10,Consulting,2025-03-09,2025-05-03,2161,9.3,Autonomous Tech -AI04410,Autonomous Systems Engineer,106646,USD,106646,MI,FT,Sweden,M,Sweden,50,"Java, Kubernetes, Tableau, SQL",PhD,3,Automotive,2025-02-15,2025-03-23,2468,7,Neural Networks Co -AI04411,AI Architect,91413,SGD,118837,MI,PT,Singapore,M,Spain,100,"Mathematics, Computer Vision, NLP, TensorFlow",PhD,4,Technology,2024-11-24,2025-01-13,881,9,Neural Networks Co -AI04412,Deep Learning Engineer,224651,USD,224651,EX,FL,Denmark,L,Denmark,100,"Git, Kubernetes, Python",Bachelor,19,Technology,2024-12-11,2025-02-14,1208,9.4,DataVision Ltd -AI04413,AI Architect,130860,USD,130860,EX,PT,South Korea,L,South Korea,50,"TensorFlow, Docker, MLOps, Kubernetes, Data Visualization",PhD,13,Education,2025-03-19,2025-04-27,1934,7.1,Smart Analytics -AI04414,Machine Learning Researcher,46877,USD,46877,EN,CT,Israel,S,Israel,100,"NLP, TensorFlow, Mathematics, MLOps",PhD,0,Consulting,2024-05-28,2024-06-13,2354,7,Digital Transformation LLC -AI04415,Deep Learning Engineer,179047,EUR,152190,EX,PT,France,M,France,0,"NLP, Docker, Mathematics, Computer Vision, PyTorch",Master,18,Media,2024-10-13,2024-10-27,2472,9.9,Machine Intelligence Group -AI04416,Data Engineer,104146,EUR,88524,SE,FL,Austria,M,Turkey,0,"Docker, Python, Mathematics",PhD,8,Technology,2024-03-15,2024-05-04,1388,5,Machine Intelligence Group -AI04417,AI Consultant,31567,USD,31567,MI,FL,India,S,India,0,"Kubernetes, Git, GCP, Linux",Bachelor,2,Manufacturing,2025-01-23,2025-03-27,1204,6.6,DataVision Ltd -AI04418,Principal Data Scientist,97690,USD,97690,SE,FL,South Korea,S,Kenya,100,"Linux, Computer Vision, Deep Learning, Kubernetes",PhD,7,Transportation,2024-08-22,2024-09-17,2486,6.6,Autonomous Tech -AI04419,Head of AI,62371,AUD,84201,EN,FT,Australia,M,Australia,50,"Azure, NLP, SQL",PhD,0,Technology,2024-09-13,2024-10-11,1120,7.4,DeepTech Ventures -AI04420,AI Product Manager,262516,CHF,236264,EX,FL,Switzerland,L,Switzerland,50,"Scala, Spark, Docker, Kubernetes",Bachelor,19,Media,2024-09-02,2024-10-15,614,9.1,Cognitive Computing -AI04421,AI Specialist,75844,CAD,94805,MI,FL,Canada,S,India,100,"TensorFlow, Kubernetes, Tableau",Associate,2,Energy,2024-05-27,2024-07-01,2116,9.7,Future Systems -AI04422,Data Scientist,131997,JPY,14519670,SE,FL,Japan,L,Thailand,0,"Kubernetes, PyTorch, Computer Vision",Master,5,Government,2024-07-10,2024-08-23,1204,6.1,Smart Analytics -AI04423,Principal Data Scientist,103953,EUR,88360,MI,FT,Netherlands,M,Netherlands,0,"SQL, NLP, PyTorch, Computer Vision, Hadoop",Master,3,Transportation,2024-12-25,2025-01-28,1919,5.8,TechCorp Inc -AI04424,AI Specialist,177676,USD,177676,SE,PT,Denmark,L,Denmark,0,"Azure, Java, Python, Linux, Statistics",Bachelor,8,Finance,2024-11-21,2024-12-30,2199,9.3,Algorithmic Solutions -AI04425,AI Product Manager,122946,AUD,165977,SE,PT,Australia,S,Australia,0,"Spark, Kubernetes, Git, Java, GCP",PhD,9,Education,2024-12-26,2025-02-23,835,7.1,TechCorp Inc -AI04426,Head of AI,202266,USD,202266,EX,CT,Israel,S,Israel,50,"GCP, Computer Vision, SQL, Azure",Associate,12,Healthcare,2024-08-02,2024-09-17,1550,5.9,AI Innovations -AI04427,Machine Learning Engineer,42862,USD,42862,SE,FL,India,S,Russia,100,"Git, Java, Kubernetes, R, Mathematics",Bachelor,5,Gaming,2024-11-08,2025-01-17,1330,6.6,DeepTech Ventures -AI04428,Data Scientist,221324,USD,221324,SE,FT,Norway,L,Spain,100,"Spark, R, Tableau, Python, Linux",Bachelor,7,Retail,2025-04-01,2025-04-29,1133,7.6,Predictive Systems -AI04429,Machine Learning Researcher,129064,SGD,167783,MI,CT,Singapore,L,Hungary,100,"Python, Hadoop, Statistics",Bachelor,4,Manufacturing,2024-07-07,2024-09-17,2002,5.8,TechCorp Inc -AI04430,Computer Vision Engineer,116116,CAD,145145,SE,FT,Canada,L,Singapore,100,"AWS, SQL, Deep Learning, Kubernetes",PhD,8,Manufacturing,2024-06-25,2024-07-12,849,8.3,Algorithmic Solutions -AI04431,Data Scientist,204614,AUD,276229,EX,CT,Australia,L,Australia,0,"Linux, MLOps, NLP, PyTorch",Associate,19,Telecommunications,2025-04-07,2025-04-23,1784,9.7,Neural Networks Co -AI04432,Data Engineer,44008,USD,44008,EX,FT,India,S,India,100,"TensorFlow, Python, Java, Scala, Azure",PhD,15,Transportation,2024-03-12,2024-04-08,1391,5.9,Smart Analytics -AI04433,AI Research Scientist,59937,USD,59937,SE,PT,China,M,Indonesia,100,"PyTorch, TensorFlow, Git",Bachelor,9,Technology,2024-08-21,2024-11-02,798,9.2,Predictive Systems -AI04434,AI Product Manager,86443,USD,86443,MI,PT,Israel,S,Belgium,50,"SQL, Java, MLOps",Master,4,Technology,2024-10-15,2024-11-10,1882,5.9,Digital Transformation LLC -AI04435,AI Specialist,104949,SGD,136434,SE,FL,Singapore,S,Singapore,50,"Java, Linux, Spark",Bachelor,6,Manufacturing,2024-06-07,2024-08-15,855,9.8,Digital Transformation LLC -AI04436,Principal Data Scientist,186813,USD,186813,EX,CT,Ireland,S,France,100,"NLP, Linux, Java",Bachelor,17,Healthcare,2024-01-03,2024-03-12,958,8.6,Algorithmic Solutions -AI04437,AI Specialist,211822,JPY,23300420,EX,FL,Japan,L,Indonesia,50,"Computer Vision, Hadoop, Python, SQL",Bachelor,13,Transportation,2024-03-23,2024-05-05,2204,9.4,Cognitive Computing -AI04438,AI Consultant,153646,SGD,199740,EX,FL,Singapore,M,Romania,100,"Mathematics, PyTorch, MLOps",Master,18,Real Estate,2024-01-07,2024-03-14,607,7.6,DeepTech Ventures -AI04439,Data Analyst,117982,USD,117982,SE,PT,Israel,M,Israel,0,"Python, Linux, R, TensorFlow",PhD,5,Gaming,2024-02-18,2024-04-23,752,9.9,Quantum Computing Inc -AI04440,Data Engineer,133740,SGD,173862,SE,FL,Singapore,S,Mexico,0,"Java, SQL, Mathematics, Deep Learning",Associate,9,Government,2025-01-10,2025-01-24,2271,7.8,Algorithmic Solutions -AI04441,Machine Learning Researcher,84175,USD,84175,EN,FL,Denmark,S,Chile,0,"Azure, Mathematics, MLOps, Scala, Git",Bachelor,1,Healthcare,2024-02-17,2024-04-07,2409,6.9,Smart Analytics -AI04442,Computer Vision Engineer,87366,GBP,65525,MI,CT,United Kingdom,S,Vietnam,0,"Azure, Python, Data Visualization, Mathematics, Computer Vision",Bachelor,2,Consulting,2024-11-26,2024-12-11,1180,10,Digital Transformation LLC -AI04443,Autonomous Systems Engineer,110287,USD,110287,MI,CT,Sweden,L,Vietnam,50,"GCP, Spark, Azure, PyTorch",Bachelor,4,Retail,2025-02-14,2025-03-21,674,7.8,Quantum Computing Inc -AI04444,Data Scientist,104258,USD,104258,SE,CT,South Korea,L,South Korea,0,"Statistics, Kubernetes, R, Java",Associate,8,Automotive,2024-10-26,2024-12-01,2028,9.2,Machine Intelligence Group -AI04445,AI Software Engineer,114211,USD,114211,EN,FT,Denmark,L,Ireland,100,"Python, Kubernetes, Docker",PhD,0,Healthcare,2025-01-07,2025-03-10,1349,9,DeepTech Ventures -AI04446,Head of AI,194011,EUR,164909,EX,PT,France,L,France,100,"PyTorch, Python, NLP, Hadoop",Master,18,Healthcare,2025-04-08,2025-06-06,814,8.4,Algorithmic Solutions -AI04447,Principal Data Scientist,293192,USD,293192,EX,FL,Sweden,L,Sweden,50,"Azure, AWS, Linux, Scala, R",Associate,13,Technology,2024-12-07,2025-01-29,2000,8.4,Future Systems -AI04448,Robotics Engineer,53874,EUR,45793,EN,FL,France,S,France,100,"GCP, R, Statistics",PhD,1,Manufacturing,2024-03-15,2024-04-01,503,6.9,TechCorp Inc -AI04449,Robotics Engineer,88454,USD,88454,SE,CT,Finland,S,Finland,0,"Docker, Hadoop, GCP, Java, Scala",PhD,7,Media,2025-04-25,2025-06-28,2354,5.2,Predictive Systems -AI04450,Robotics Engineer,161911,SGD,210484,EX,CT,Singapore,S,Singapore,50,"SQL, Scala, Linux, Azure",Associate,11,Healthcare,2024-11-04,2025-01-11,1397,8.7,DeepTech Ventures -AI04451,AI Consultant,64565,USD,64565,MI,FT,South Korea,S,South Korea,100,"Hadoop, Git, Tableau, NLP, Azure",PhD,4,Gaming,2024-09-13,2024-10-18,2397,8.1,DeepTech Ventures -AI04452,Data Scientist,47708,USD,47708,EN,CT,Israel,S,Philippines,100,"Python, TensorFlow, Azure, Linux",Bachelor,1,Technology,2024-06-13,2024-07-03,1203,9.5,DeepTech Ventures -AI04453,AI Product Manager,140313,SGD,182407,SE,FL,Singapore,M,Singapore,50,"Mathematics, Scala, Deep Learning",Master,6,Energy,2024-08-15,2024-09-27,1946,6.2,Neural Networks Co -AI04454,AI Software Engineer,94235,JPY,10365850,EN,FL,Japan,L,Spain,100,"R, Tableau, Python, Azure, TensorFlow",Associate,1,Consulting,2024-05-05,2024-07-07,2010,9.2,Machine Intelligence Group -AI04455,Data Engineer,57467,USD,57467,MI,CT,South Korea,S,South Korea,0,"Computer Vision, Spark, Docker, Hadoop, Python",PhD,3,Government,2024-07-21,2024-08-18,1968,8,Neural Networks Co -AI04456,AI Research Scientist,129225,SGD,167993,SE,PT,Singapore,M,Finland,0,"Hadoop, Python, PyTorch, Git",Associate,9,Healthcare,2025-03-22,2025-05-16,1335,5.9,DeepTech Ventures -AI04457,Data Scientist,157816,USD,157816,EX,PT,Ireland,M,Ireland,100,"Scala, GCP, AWS",Bachelor,12,Manufacturing,2025-04-22,2025-06-12,733,10,Neural Networks Co -AI04458,Data Engineer,77796,EUR,66127,MI,FL,Austria,S,Austria,50,"Python, TensorFlow, Tableau",Bachelor,2,Automotive,2024-01-09,2024-01-26,832,5.4,Predictive Systems -AI04459,Deep Learning Engineer,202840,EUR,172414,EX,FT,Netherlands,S,Netherlands,0,"Git, Spark, Computer Vision, Tableau, Java",Associate,17,Manufacturing,2025-02-22,2025-03-18,1954,8.6,Smart Analytics -AI04460,Data Scientist,77051,AUD,104019,EN,FL,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch",Master,0,Media,2024-09-30,2024-11-08,2129,5.6,Advanced Robotics -AI04461,AI Specialist,105395,AUD,142283,MI,FT,Australia,L,Australia,50,"Linux, Git, Kubernetes, NLP, Python",Master,2,Transportation,2024-06-25,2024-08-27,1203,7.1,TechCorp Inc -AI04462,AI Research Scientist,83359,EUR,70855,EN,FL,Netherlands,M,Netherlands,100,"Kubernetes, Java, Data Visualization",Bachelor,0,Real Estate,2025-01-21,2025-02-19,1507,5.4,Machine Intelligence Group -AI04463,Machine Learning Engineer,98213,CHF,88392,EN,CT,Switzerland,L,Switzerland,0,"Java, SQL, Kubernetes, PyTorch",Associate,1,Media,2024-12-23,2025-01-23,1844,8.8,Cognitive Computing -AI04464,AI Software Engineer,39868,USD,39868,MI,FL,China,S,China,100,"R, Docker, TensorFlow, Git",Master,2,Automotive,2024-09-25,2024-11-20,526,5.1,Future Systems -AI04465,Computer Vision Engineer,246512,USD,246512,EX,CT,Norway,M,Norway,0,"Data Visualization, Git, Linux",Bachelor,19,Manufacturing,2025-01-24,2025-03-24,2255,10,Quantum Computing Inc -AI04466,AI Software Engineer,77063,USD,77063,EX,CT,India,M,India,50,"MLOps, Git, Kubernetes",Associate,18,Media,2025-03-31,2025-05-21,680,9.8,Advanced Robotics -AI04467,Principal Data Scientist,60066,EUR,51056,EN,PT,Germany,L,Germany,50,"Deep Learning, Scala, Data Visualization",Associate,0,Media,2024-11-03,2024-11-25,1884,9.6,Quantum Computing Inc -AI04468,NLP Engineer,93900,USD,93900,MI,CT,Ireland,L,Ireland,50,"Linux, AWS, NLP, Git",Bachelor,3,Retail,2024-11-04,2024-12-02,918,5.8,DeepTech Ventures -AI04469,Machine Learning Engineer,132017,EUR,112214,SE,PT,Germany,L,China,50,"GCP, Statistics, SQL, TensorFlow",PhD,7,Technology,2025-03-15,2025-05-08,1645,9.5,Cognitive Computing -AI04470,Head of AI,94447,USD,94447,MI,CT,Norway,S,Norway,0,"Kubernetes, SQL, TensorFlow, PyTorch",Master,4,Education,2024-11-14,2025-01-04,1613,7.8,Cognitive Computing -AI04471,AI Software Engineer,65304,USD,65304,EX,FL,India,M,India,50,"MLOps, Python, TensorFlow, Docker",Associate,12,Finance,2024-07-19,2024-08-04,574,5.8,Cognitive Computing -AI04472,AI Software Engineer,172150,EUR,146328,SE,FL,Netherlands,L,Netherlands,100,"Spark, PyTorch, Data Visualization, Computer Vision",Associate,9,Transportation,2024-11-26,2024-12-10,2024,5.7,Digital Transformation LLC -AI04473,NLP Engineer,88827,USD,88827,MI,FT,Ireland,M,Ireland,50,"Computer Vision, R, Azure, Deep Learning, MLOps",Bachelor,4,Retail,2024-07-13,2024-09-06,2422,7.2,Future Systems -AI04474,Data Engineer,144886,AUD,195596,SE,FT,Australia,L,Australia,0,"Git, GCP, Linux, Computer Vision",Master,8,Manufacturing,2024-07-09,2024-09-11,1834,8.3,Future Systems -AI04475,Research Scientist,133043,USD,133043,EX,FL,Israel,S,France,0,"Python, Deep Learning, Java",PhD,16,Transportation,2024-04-05,2024-06-06,2319,8.8,Advanced Robotics -AI04476,AI Software Engineer,127811,EUR,108639,SE,FL,Netherlands,L,Ireland,50,"Scala, Azure, Docker, AWS, Mathematics",Associate,7,Automotive,2024-11-27,2024-12-24,1278,9.6,Quantum Computing Inc -AI04477,Computer Vision Engineer,103521,CAD,129401,SE,CT,Canada,S,Canada,50,"R, Java, Tableau, Docker",Associate,7,Real Estate,2024-01-04,2024-02-16,2044,5.6,Predictive Systems -AI04478,Research Scientist,54480,SGD,70824,EN,FL,Singapore,M,Singapore,50,"Spark, TensorFlow, MLOps, Python",Master,1,Education,2025-01-30,2025-02-17,1495,9.3,Autonomous Tech -AI04479,Principal Data Scientist,74709,EUR,63503,MI,FL,France,M,France,50,"Scala, Git, MLOps, Statistics",Bachelor,4,Technology,2024-09-11,2024-10-15,1967,5.8,Machine Intelligence Group -AI04480,Computer Vision Engineer,59379,USD,59379,EN,FL,Israel,S,Czech Republic,100,"Java, Computer Vision, MLOps",PhD,1,Government,2025-01-18,2025-02-14,2335,8,Advanced Robotics -AI04481,AI Product Manager,61440,USD,61440,SE,FT,China,M,Japan,0,"Scala, Mathematics, Java",PhD,5,Telecommunications,2024-08-17,2024-10-11,1501,8,Neural Networks Co -AI04482,Autonomous Systems Engineer,134360,GBP,100770,EX,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Python, NLP, TensorFlow, Java",Master,17,Gaming,2024-04-11,2024-05-05,2337,7,Autonomous Tech -AI04483,AI Product Manager,225183,JPY,24770130,EX,FL,Japan,S,Japan,50,"Data Visualization, MLOps, TensorFlow",PhD,13,Energy,2024-10-12,2024-12-17,729,8.6,Algorithmic Solutions -AI04484,Principal Data Scientist,262051,CAD,327564,EX,FT,Canada,L,Colombia,100,"R, Tableau, Statistics, Hadoop, SQL",Bachelor,18,Government,2025-01-30,2025-02-20,678,5.4,Digital Transformation LLC -AI04485,ML Ops Engineer,51148,USD,51148,MI,FL,China,L,Norway,50,"Docker, MLOps, Hadoop, R, Azure",Bachelor,3,Energy,2024-11-06,2024-12-17,1629,9.4,Smart Analytics -AI04486,Deep Learning Engineer,50384,USD,50384,SE,CT,India,L,Finland,100,"Azure, NLP, Spark, Tableau",Bachelor,9,Technology,2024-11-21,2024-12-31,1978,7.9,Algorithmic Solutions -AI04487,Autonomous Systems Engineer,45747,CAD,57184,EN,PT,Canada,S,Philippines,0,"Azure, Docker, Deep Learning, Data Visualization, Python",Master,1,Manufacturing,2024-09-27,2024-12-03,2476,8.3,AI Innovations -AI04488,AI Architect,27660,USD,27660,EN,CT,China,M,China,50,"PyTorch, Git, Hadoop",Master,0,Healthcare,2024-09-12,2024-10-31,2159,7.4,Future Systems -AI04489,Machine Learning Researcher,66412,USD,66412,EN,CT,Finland,L,Finland,0,"Python, Linux, Spark, NLP",Associate,1,Gaming,2024-10-27,2024-11-26,1366,7.1,Autonomous Tech -AI04490,Computer Vision Engineer,286005,USD,286005,EX,CT,Ireland,L,Ireland,100,"R, Python, TensorFlow, PyTorch",Associate,15,Telecommunications,2024-03-06,2024-05-04,1637,9.4,Digital Transformation LLC -AI04491,Data Scientist,162115,EUR,137798,EX,PT,Austria,S,South Africa,50,"Hadoop, PyTorch, Git, R",Master,15,Automotive,2024-09-21,2024-10-27,780,6.4,AI Innovations -AI04492,Autonomous Systems Engineer,179992,JPY,19799120,EX,FL,Japan,M,Japan,50,"Scala, Azure, Deep Learning, Data Visualization",Master,10,Media,2025-01-23,2025-02-12,2176,8.4,Future Systems -AI04493,Data Analyst,52604,USD,52604,EN,FL,Sweden,S,Finland,50,"NLP, Scala, Data Visualization, Kubernetes",Bachelor,1,Energy,2025-01-15,2025-02-20,2181,9.8,DataVision Ltd -AI04494,AI Consultant,135693,USD,135693,MI,FL,Norway,L,Switzerland,0,"Kubernetes, PyTorch, GCP, Scala",Bachelor,2,Healthcare,2024-05-16,2024-05-30,1410,7.8,Autonomous Tech -AI04495,Data Scientist,132806,USD,132806,SE,CT,Norway,M,Norway,100,"Java, PyTorch, Data Visualization, Deep Learning, GCP",PhD,5,Government,2024-08-09,2024-09-10,745,10,TechCorp Inc -AI04496,AI Consultant,119154,CHF,107239,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Tableau, PyTorch",PhD,3,Technology,2024-04-25,2024-07-05,1701,5.6,TechCorp Inc -AI04497,NLP Engineer,116153,CHF,104538,EN,FT,Switzerland,L,Switzerland,0,"PyTorch, SQL, Docker, Deep Learning",PhD,1,Telecommunications,2024-05-22,2024-07-08,2130,5.5,DataVision Ltd -AI04498,AI Product Manager,122285,USD,122285,SE,FL,Norway,S,South Africa,50,"Computer Vision, R, Java, Azure",PhD,7,Consulting,2024-08-05,2024-10-07,1831,8.3,Digital Transformation LLC -AI04499,AI Research Scientist,87146,USD,87146,SE,FL,South Korea,M,South Korea,0,"R, Linux, MLOps, Mathematics, Git",Bachelor,7,Retail,2025-01-06,2025-03-05,2199,5.7,AI Innovations -AI04500,Head of AI,101820,AUD,137457,MI,CT,Australia,M,Ukraine,50,"AWS, Statistics, Data Visualization",Associate,4,Technology,2025-03-18,2025-04-17,1073,6.2,AI Innovations -AI04501,AI Research Scientist,76032,EUR,64627,MI,FL,France,M,Netherlands,100,"PyTorch, GCP, TensorFlow, NLP, Python",Bachelor,3,Consulting,2024-09-08,2024-10-08,1911,8.6,Digital Transformation LLC -AI04502,AI Software Engineer,138064,JPY,15187040,SE,FL,Japan,L,Japan,100,"GCP, PyTorch, Spark",Bachelor,5,Government,2024-02-22,2024-03-17,1028,8.1,Smart Analytics -AI04503,Research Scientist,131574,AUD,177625,SE,FL,Australia,L,Philippines,0,"Python, Spark, Azure, Linux",Bachelor,6,Finance,2024-09-30,2024-11-24,1280,6.4,Digital Transformation LLC -AI04504,Head of AI,366922,CHF,330230,EX,FL,Switzerland,L,Malaysia,0,"TensorFlow, Computer Vision, Hadoop, Python, MLOps",Bachelor,14,Real Estate,2024-01-21,2024-02-06,2396,9.3,Quantum Computing Inc -AI04505,AI Consultant,113179,USD,113179,EN,FT,Denmark,L,Denmark,0,"Git, Docker, Hadoop",Bachelor,1,Automotive,2024-06-26,2024-07-25,1016,8.2,DeepTech Ventures -AI04506,Robotics Engineer,249140,AUD,336339,EX,FL,Australia,L,Australia,100,"Scala, Statistics, NLP",PhD,18,Transportation,2024-07-22,2024-08-22,1206,6.1,Algorithmic Solutions -AI04507,Principal Data Scientist,171609,EUR,145868,EX,FT,Netherlands,M,Germany,50,"Spark, SQL, Java, MLOps, Linux",Bachelor,10,Education,2024-04-27,2024-06-17,2287,7.4,Smart Analytics -AI04508,Machine Learning Engineer,105792,EUR,89923,SE,FL,France,S,Portugal,50,"Spark, NLP, Git, Computer Vision",Master,6,Telecommunications,2024-05-31,2024-07-25,2141,5.3,Cognitive Computing -AI04509,Machine Learning Researcher,173700,USD,173700,EX,FT,South Korea,M,Luxembourg,100,"MLOps, Python, Data Visualization, Mathematics, Linux",Bachelor,19,Finance,2024-01-18,2024-03-02,529,6.5,Predictive Systems -AI04510,Data Analyst,97074,EUR,82513,MI,PT,Netherlands,L,Netherlands,100,"Data Visualization, Linux, Python, MLOps, SQL",Associate,4,Automotive,2025-01-16,2025-02-09,1335,8.4,Smart Analytics -AI04511,Machine Learning Researcher,22207,USD,22207,EN,CT,India,M,India,100,"Deep Learning, Git, Mathematics",Master,1,Energy,2024-03-19,2024-05-08,602,9.6,TechCorp Inc -AI04512,Machine Learning Researcher,166711,USD,166711,SE,PT,Ireland,L,Ireland,100,"Spark, PyTorch, NLP, TensorFlow",Bachelor,8,Consulting,2024-12-01,2024-12-17,886,7.1,Advanced Robotics -AI04513,Machine Learning Researcher,91344,EUR,77642,MI,PT,Germany,S,Austria,100,"Spark, Python, Data Visualization",PhD,4,Telecommunications,2024-01-27,2024-03-30,1213,9.8,TechCorp Inc -AI04514,Data Scientist,171048,USD,171048,SE,FT,Denmark,L,Denmark,0,"PyTorch, SQL, Spark, TensorFlow, Data Visualization",PhD,7,Gaming,2024-12-19,2025-01-04,1329,7.1,Algorithmic Solutions -AI04515,AI Software Engineer,129514,USD,129514,EX,PT,Israel,M,Israel,0,"Python, AWS, GCP, R",Bachelor,14,Real Estate,2025-02-14,2025-04-06,2310,6.5,Future Systems -AI04516,AI Research Scientist,70909,USD,70909,MI,FL,Ireland,S,Ireland,100,"AWS, MLOps, PyTorch, TensorFlow",Master,4,Telecommunications,2024-11-09,2024-12-08,926,6.6,AI Innovations -AI04517,Deep Learning Engineer,55311,EUR,47014,EN,FT,France,M,France,0,"Java, MLOps, TensorFlow, Statistics",Master,1,Healthcare,2024-07-29,2024-09-25,1413,5.2,Smart Analytics -AI04518,Deep Learning Engineer,61598,USD,61598,EX,FT,India,M,India,50,"Linux, Deep Learning, NLP",Bachelor,18,Gaming,2024-04-06,2024-06-04,2247,7,Machine Intelligence Group -AI04519,AI Product Manager,129700,USD,129700,MI,CT,Norway,L,South Korea,0,"Tableau, SQL, Docker",Master,2,Consulting,2025-02-13,2025-03-25,1327,8.3,Autonomous Tech -AI04520,AI Specialist,135809,EUR,115438,SE,FT,Netherlands,S,Netherlands,0,"Scala, R, SQL, Data Visualization, Git",Associate,6,Consulting,2025-03-28,2025-04-22,695,7.3,Autonomous Tech -AI04521,Deep Learning Engineer,238500,EUR,202725,EX,FL,Netherlands,S,South Korea,0,"Linux, Computer Vision, Kubernetes",Associate,18,Transportation,2024-04-01,2024-05-27,1845,6,AI Innovations -AI04522,Head of AI,50048,SGD,65062,EN,FT,Singapore,S,Czech Republic,50,"PyTorch, TensorFlow, Docker",Associate,0,Energy,2024-05-14,2024-06-03,680,7.1,Algorithmic Solutions -AI04523,Autonomous Systems Engineer,164914,USD,164914,SE,PT,United States,L,United States,50,"Hadoop, TensorFlow, Linux, MLOps, GCP",Master,8,Consulting,2024-03-04,2024-04-22,917,7.1,Cloud AI Solutions -AI04524,AI Consultant,181134,CAD,226418,EX,CT,Canada,M,Canada,0,"Git, PyTorch, GCP, AWS, Mathematics",Master,19,Healthcare,2024-01-15,2024-02-05,2366,5.9,Machine Intelligence Group -AI04525,AI Specialist,81453,EUR,69235,EN,FL,Netherlands,L,Netherlands,50,"TensorFlow, Java, Deep Learning, Tableau",Associate,1,Education,2025-02-09,2025-03-27,2323,9.2,DataVision Ltd -AI04526,Machine Learning Researcher,52632,USD,52632,EN,FL,Israel,S,Israel,50,"SQL, Spark, Tableau, Scala",PhD,0,Retail,2024-03-15,2024-04-16,585,8.8,Neural Networks Co -AI04527,Data Analyst,77848,USD,77848,EN,FL,Denmark,L,Denmark,50,"SQL, GCP, PyTorch, Java",PhD,0,Government,2025-02-04,2025-03-16,1735,6.9,DataVision Ltd -AI04528,Autonomous Systems Engineer,117315,USD,117315,SE,PT,Sweden,M,Singapore,0,"Computer Vision, Java, MLOps, Kubernetes, Docker",PhD,5,Retail,2024-08-23,2024-10-07,1852,9,DeepTech Ventures -AI04529,AI Architect,166998,USD,166998,SE,CT,Denmark,S,Israel,100,"MLOps, Linux, Data Visualization, Computer Vision",Associate,7,Manufacturing,2025-02-18,2025-04-09,1054,7.3,Neural Networks Co -AI04530,Head of AI,174172,GBP,130629,SE,CT,United Kingdom,L,United Kingdom,50,"TensorFlow, Python, Linux, Hadoop, Statistics",Associate,8,Healthcare,2024-11-09,2024-12-24,574,5.7,Machine Intelligence Group -AI04531,ML Ops Engineer,93049,CAD,116311,MI,CT,Canada,M,Canada,100,"PyTorch, Data Visualization, SQL, Kubernetes",Bachelor,2,Consulting,2025-04-27,2025-05-12,812,7.4,DeepTech Ventures -AI04532,Robotics Engineer,139395,USD,139395,SE,FL,Sweden,L,Sweden,100,"Docker, SQL, Scala, MLOps, Kubernetes",Master,6,Retail,2024-01-08,2024-02-04,1681,6.5,Algorithmic Solutions -AI04533,AI Software Engineer,207936,USD,207936,SE,FT,Norway,L,Norway,100,"Hadoop, Python, AWS, Linux",Bachelor,6,Technology,2024-11-16,2024-12-12,2030,5,Cognitive Computing -AI04534,Machine Learning Engineer,188512,EUR,160235,EX,CT,Austria,M,Austria,50,"Docker, Git, SQL, Spark, Linux",Master,18,Healthcare,2024-04-03,2024-06-09,1323,9.7,Smart Analytics -AI04535,AI Specialist,176564,GBP,132423,EX,FT,United Kingdom,M,Egypt,0,"Azure, Kubernetes, Linux, SQL",PhD,11,Finance,2024-01-11,2024-02-21,631,7.3,Predictive Systems -AI04536,Research Scientist,156332,GBP,117249,SE,CT,United Kingdom,L,Denmark,100,"Kubernetes, Mathematics, Hadoop, MLOps",Bachelor,7,Manufacturing,2025-02-19,2025-04-25,1511,10,Cognitive Computing -AI04537,Data Scientist,113860,USD,113860,MI,FL,United States,M,United States,50,"Tableau, Kubernetes, Java, MLOps",Bachelor,4,Finance,2024-09-16,2024-11-20,1497,9,DeepTech Ventures -AI04538,Data Scientist,95951,USD,95951,MI,FL,Finland,L,Finland,0,"SQL, Mathematics, Kubernetes, Python",Master,2,Media,2024-10-14,2024-12-07,2141,8.2,AI Innovations -AI04539,Data Engineer,177286,CHF,159557,SE,CT,Switzerland,S,Switzerland,50,"Scala, GCP, SQL, MLOps",Associate,7,Manufacturing,2024-04-28,2024-06-22,2473,9.8,Predictive Systems -AI04540,AI Software Engineer,53681,CAD,67101,EN,CT,Canada,M,Canada,50,"Tableau, Azure, Java, Data Visualization",Associate,0,Energy,2024-05-04,2024-05-26,2123,8.3,AI Innovations -AI04541,AI Research Scientist,130939,AUD,176768,SE,FL,Australia,M,Ireland,100,"Data Visualization, GCP, SQL, NLP, Linux",Bachelor,5,Automotive,2024-07-18,2024-09-10,562,6.6,Autonomous Tech -AI04542,Principal Data Scientist,39395,USD,39395,SE,PT,India,M,India,0,"Spark, Data Visualization, Linux, Deep Learning",PhD,7,Transportation,2024-10-05,2024-10-28,1164,8.6,Algorithmic Solutions -AI04543,AI Architect,123582,USD,123582,MI,FL,Norway,M,Norway,0,"Scala, Java, Spark, Mathematics",PhD,3,Manufacturing,2025-03-21,2025-04-10,630,9.6,Predictive Systems -AI04544,AI Research Scientist,136808,EUR,116287,EX,CT,Netherlands,S,Netherlands,0,"Git, TensorFlow, Scala, GCP, Python",PhD,17,Manufacturing,2024-02-20,2024-03-10,2222,8.2,Advanced Robotics -AI04545,Computer Vision Engineer,38736,USD,38736,SE,FT,India,S,India,100,"Python, Java, TensorFlow, Computer Vision, AWS",Bachelor,5,Retail,2025-03-25,2025-04-29,544,9,TechCorp Inc -AI04546,Data Engineer,111692,USD,111692,SE,CT,Ireland,M,Ireland,0,"Python, Scala, Statistics, NLP, Git",Associate,8,Manufacturing,2025-01-27,2025-03-22,2475,5.5,AI Innovations -AI04547,Robotics Engineer,320350,CHF,288315,EX,FT,Switzerland,M,Switzerland,100,"MLOps, PyTorch, Python, Spark",Bachelor,16,Energy,2024-07-25,2024-09-30,2313,6.9,Digital Transformation LLC -AI04548,Data Scientist,148284,EUR,126041,EX,FL,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,14,Consulting,2024-01-26,2024-03-04,1188,5.7,TechCorp Inc -AI04549,AI Research Scientist,164350,USD,164350,EX,FL,Israel,S,Israel,50,"Java, Docker, Azure, Computer Vision, AWS",Master,19,Consulting,2025-04-20,2025-06-23,2272,9.9,Quantum Computing Inc -AI04550,AI Specialist,300752,CHF,270677,EX,FT,Switzerland,L,Switzerland,100,"Mathematics, Hadoop, Data Visualization, R",Associate,14,Retail,2024-08-16,2024-08-30,1923,9.1,Smart Analytics -AI04551,Research Scientist,71687,USD,71687,SE,CT,China,L,Singapore,0,"Docker, AWS, Computer Vision, Java",Associate,7,Education,2024-02-24,2024-04-25,1076,8,Cloud AI Solutions -AI04552,Robotics Engineer,78911,CAD,98639,MI,FL,Canada,S,Canada,100,"Data Visualization, Python, GCP",PhD,4,Government,2024-10-21,2024-11-17,1168,9.7,Machine Intelligence Group -AI04553,Machine Learning Researcher,85224,USD,85224,MI,CT,Israel,L,Israel,50,"NLP, Hadoop, GCP",Bachelor,4,Consulting,2024-12-18,2025-02-27,1115,7,Cloud AI Solutions -AI04554,AI Research Scientist,30653,USD,30653,MI,PT,India,S,India,100,"Java, TensorFlow, R, GCP",Bachelor,2,Media,2025-03-06,2025-04-14,2316,9.7,Neural Networks Co -AI04555,AI Consultant,125667,USD,125667,MI,FT,Sweden,L,Ireland,100,"Java, Computer Vision, MLOps, Tableau",Bachelor,3,Healthcare,2024-08-06,2024-09-08,1356,7.9,Quantum Computing Inc -AI04556,Data Scientist,59008,USD,59008,EN,FT,Finland,M,Argentina,100,"MLOps, Python, Java, AWS, TensorFlow",Bachelor,1,Education,2024-01-03,2024-03-02,816,8.3,Machine Intelligence Group -AI04557,Head of AI,87615,USD,87615,MI,FL,Norway,S,Norway,100,"Linux, Computer Vision, Statistics, Deep Learning",Bachelor,3,Education,2024-03-18,2024-04-27,2060,6.4,Algorithmic Solutions -AI04558,AI Specialist,64656,USD,64656,SE,FL,China,M,China,0,"NLP, SQL, Spark, TensorFlow, MLOps",PhD,7,Government,2024-11-29,2024-12-24,1692,5.7,TechCorp Inc -AI04559,NLP Engineer,236797,JPY,26047670,EX,CT,Japan,S,Turkey,50,"Scala, Java, Python, Kubernetes",Master,17,Automotive,2024-03-20,2024-05-11,1015,8.6,Autonomous Tech -AI04560,AI Research Scientist,69325,EUR,58926,EN,FT,Germany,L,United Kingdom,0,"SQL, MLOps, Spark, Computer Vision",Associate,0,Finance,2024-06-12,2024-08-02,1048,9.9,TechCorp Inc -AI04561,Research Scientist,100014,USD,100014,SE,FL,South Korea,S,South Korea,50,"Scala, Java, Deep Learning, NLP",Associate,7,Finance,2024-02-23,2024-03-14,1690,9.1,AI Innovations -AI04562,ML Ops Engineer,145257,EUR,123468,SE,FT,France,L,France,50,"SQL, MLOps, Python, NLP",Bachelor,5,Transportation,2025-04-21,2025-06-14,1793,7.5,Cloud AI Solutions -AI04563,Robotics Engineer,129098,SGD,167827,SE,CT,Singapore,M,Singapore,100,"AWS, TensorFlow, Python, Tableau, Statistics",Master,9,Real Estate,2024-04-25,2024-05-22,513,6.6,Autonomous Tech -AI04564,AI Research Scientist,58400,USD,58400,EX,FL,India,M,Australia,0,"R, Mathematics, Computer Vision",Master,15,Real Estate,2024-12-04,2025-01-23,1072,6.4,Machine Intelligence Group -AI04565,Data Engineer,146073,USD,146073,EX,CT,Israel,S,Israel,100,"Docker, Kubernetes, GCP",Bachelor,19,Manufacturing,2024-09-01,2024-09-23,2328,5.9,DataVision Ltd -AI04566,ML Ops Engineer,110488,EUR,93915,SE,FL,Germany,M,Germany,100,"MLOps, NLP, SQL",PhD,9,Manufacturing,2025-02-23,2025-05-05,2166,7.7,Cloud AI Solutions -AI04567,Data Analyst,71058,USD,71058,EN,FL,Norway,M,United States,100,"Computer Vision, SQL, NLP",Master,0,Consulting,2024-04-04,2024-06-14,1040,6.3,Cloud AI Solutions -AI04568,Machine Learning Engineer,231110,SGD,300443,EX,FT,Singapore,L,Singapore,100,"Hadoop, Scala, GCP, PyTorch",Associate,17,Energy,2024-12-14,2025-01-17,2122,8.3,TechCorp Inc -AI04569,Data Engineer,138306,EUR,117560,SE,CT,Germany,L,Germany,100,"Java, Kubernetes, AWS",Master,8,Finance,2025-04-27,2025-05-30,1642,9.6,Algorithmic Solutions -AI04570,Principal Data Scientist,187455,CHF,168710,EX,PT,Switzerland,S,Switzerland,50,"Python, TensorFlow, Azure, Deep Learning, Tableau",PhD,12,Energy,2024-04-18,2024-06-05,2092,8.1,Autonomous Tech -AI04571,Autonomous Systems Engineer,94272,CHF,84845,EN,FT,Switzerland,L,Switzerland,100,"Statistics, SQL, Hadoop, Scala, Data Visualization",PhD,1,Government,2024-03-02,2024-04-04,1216,7.8,DeepTech Ventures -AI04572,ML Ops Engineer,136910,EUR,116374,EX,FT,Germany,S,Philippines,100,"Java, AWS, Computer Vision",Bachelor,17,Consulting,2024-10-15,2024-11-27,1487,5.6,Cloud AI Solutions -AI04573,AI Product Manager,155455,CAD,194319,EX,PT,Canada,L,Luxembourg,0,"Java, GCP, Kubernetes, AWS, NLP",Bachelor,16,Transportation,2024-06-01,2024-06-15,625,5.7,Predictive Systems -AI04574,Machine Learning Engineer,218908,JPY,24079880,EX,FT,Japan,S,Japan,100,"Tableau, AWS, MLOps",Associate,14,Finance,2025-01-11,2025-02-25,1370,6.6,Neural Networks Co -AI04575,AI Specialist,58456,EUR,49688,EN,FL,Austria,S,Austria,0,"Scala, Computer Vision, Statistics",Associate,1,Media,2024-12-27,2025-01-16,1460,6.5,Quantum Computing Inc -AI04576,ML Ops Engineer,79370,GBP,59528,EN,CT,United Kingdom,M,Chile,50,"PyTorch, TensorFlow, R",PhD,1,Technology,2025-01-12,2025-03-13,2208,5.9,DeepTech Ventures -AI04577,Head of AI,56598,USD,56598,SE,FT,China,L,China,50,"MLOps, Git, Java, TensorFlow",PhD,8,Retail,2024-02-18,2024-03-28,1009,8.7,DeepTech Ventures -AI04578,Machine Learning Researcher,164862,USD,164862,EX,FL,United States,M,United States,50,"NLP, Linux, Kubernetes, SQL, MLOps",Master,11,Manufacturing,2024-07-28,2024-09-18,1904,6.9,Algorithmic Solutions -AI04579,AI Consultant,78776,USD,78776,MI,PT,South Korea,L,Chile,100,"Data Visualization, MLOps, AWS",Associate,3,Technology,2025-01-11,2025-02-25,2434,7.7,Predictive Systems -AI04580,Principal Data Scientist,107481,GBP,80611,MI,FT,United Kingdom,M,Canada,50,"Linux, R, Python",Master,4,Manufacturing,2024-06-19,2024-08-24,2101,6.1,Cloud AI Solutions -AI04581,AI Specialist,165800,GBP,124350,EX,FL,United Kingdom,M,United Kingdom,50,"Git, Linux, Deep Learning, MLOps, AWS",Associate,11,Energy,2024-09-08,2024-09-26,883,8.3,AI Innovations -AI04582,Data Scientist,114567,EUR,97382,MI,FL,Netherlands,L,Netherlands,100,"Java, Linux, Python, Hadoop, MLOps",Bachelor,4,Technology,2024-10-23,2024-12-23,931,9.8,Digital Transformation LLC -AI04583,Research Scientist,45528,EUR,38699,EN,FL,France,S,France,100,"Python, Azure, Data Visualization, Deep Learning",Bachelor,1,Telecommunications,2024-12-24,2025-02-18,1363,8.7,Neural Networks Co -AI04584,Computer Vision Engineer,156683,GBP,117512,SE,FT,United Kingdom,M,Nigeria,100,"Computer Vision, AWS, Kubernetes, MLOps, Deep Learning",Bachelor,7,Finance,2024-01-22,2024-03-28,1328,8.6,Digital Transformation LLC -AI04585,Machine Learning Engineer,38720,USD,38720,SE,FL,India,S,India,50,"Kubernetes, Linux, Computer Vision, TensorFlow, NLP",PhD,8,Consulting,2024-04-12,2024-04-30,785,8.3,Cognitive Computing -AI04586,ML Ops Engineer,114629,AUD,154749,SE,FL,Australia,M,Australia,0,"R, Azure, SQL",Master,7,Technology,2025-04-19,2025-05-10,1688,5.4,Neural Networks Co -AI04587,Computer Vision Engineer,57392,CAD,71740,EN,FT,Canada,L,Canada,0,"Tableau, SQL, Kubernetes, Hadoop",Associate,1,Gaming,2024-11-30,2025-01-07,1624,6.3,Advanced Robotics -AI04588,Data Scientist,341117,USD,341117,EX,FL,Norway,L,Norway,50,"Linux, Docker, Kubernetes",Bachelor,18,Telecommunications,2024-01-06,2024-01-24,790,8.5,DataVision Ltd -AI04589,ML Ops Engineer,86046,GBP,64535,MI,CT,United Kingdom,S,United Kingdom,0,"Git, R, Spark, Deep Learning, Data Visualization",Bachelor,3,Transportation,2025-01-12,2025-02-21,1892,9.8,Algorithmic Solutions -AI04590,Computer Vision Engineer,149937,USD,149937,EX,PT,South Korea,S,South Korea,50,"Hadoop, Git, SQL",Master,18,Gaming,2024-07-31,2024-10-10,2454,5.1,Machine Intelligence Group -AI04591,Principal Data Scientist,80029,SGD,104038,EN,CT,Singapore,M,Ghana,0,"TensorFlow, MLOps, Data Visualization, Java",Associate,0,Technology,2025-02-26,2025-05-05,2367,9.5,Quantum Computing Inc -AI04592,Machine Learning Engineer,165691,GBP,124268,SE,PT,United Kingdom,L,Ukraine,0,"Scala, Tableau, SQL",Bachelor,9,Healthcare,2024-05-01,2024-06-09,1945,6,Advanced Robotics -AI04593,Autonomous Systems Engineer,141765,EUR,120500,SE,FL,Netherlands,M,Netherlands,0,"Python, PyTorch, Tableau",PhD,7,Telecommunications,2024-06-05,2024-07-31,1988,8.6,Algorithmic Solutions -AI04594,AI Research Scientist,47675,USD,47675,EN,PT,Ireland,S,Ireland,100,"Git, AWS, R, Mathematics, Kubernetes",Master,0,Energy,2024-02-08,2024-03-06,1872,8,Smart Analytics -AI04595,Data Analyst,114484,USD,114484,EX,CT,China,L,China,0,"Spark, PyTorch, Tableau",Bachelor,13,Consulting,2024-12-14,2025-02-08,2154,6.9,Neural Networks Co -AI04596,Machine Learning Engineer,88276,EUR,75035,MI,FT,Austria,S,Norway,100,"TensorFlow, SQL, R, Tableau",Master,4,Healthcare,2024-05-29,2024-06-26,2038,8.3,Cognitive Computing -AI04597,Autonomous Systems Engineer,174969,USD,174969,SE,FT,Sweden,L,Sweden,50,"Java, Azure, R",Associate,8,Telecommunications,2024-11-02,2024-11-18,2445,9.2,Digital Transformation LLC -AI04598,NLP Engineer,193261,USD,193261,EX,FT,South Korea,L,South Korea,50,"Data Visualization, Spark, R, Mathematics, Linux",Associate,10,Education,2024-12-23,2025-03-06,1301,8.7,DataVision Ltd -AI04599,Deep Learning Engineer,58905,USD,58905,EX,CT,India,S,Hungary,100,"SQL, NLP, PyTorch",PhD,12,Automotive,2024-03-26,2024-06-01,1885,5.1,DeepTech Ventures -AI04600,AI Software Engineer,155003,CAD,193754,SE,CT,Canada,L,South Korea,50,"Azure, AWS, Docker",Master,5,Education,2025-04-11,2025-06-16,1609,5.7,Autonomous Tech -AI04601,AI Research Scientist,137955,USD,137955,MI,PT,United States,L,Turkey,50,"TensorFlow, Python, PyTorch, Linux, NLP",PhD,2,Healthcare,2025-04-23,2025-05-24,1334,9.6,AI Innovations -AI04602,NLP Engineer,127644,USD,127644,SE,CT,Finland,M,Finland,100,"MLOps, SQL, Computer Vision",Master,6,Consulting,2024-08-08,2024-10-19,1112,7.2,Future Systems -AI04603,Data Scientist,131769,EUR,112004,SE,FT,France,M,Romania,0,"Python, AWS, MLOps, GCP, SQL",Associate,7,Education,2024-07-11,2024-09-04,1615,9.2,AI Innovations -AI04604,AI Consultant,69280,CAD,86600,MI,FL,Canada,S,Canada,100,"GCP, Azure, Spark",Associate,4,Education,2024-05-26,2024-08-04,2319,8.4,Cloud AI Solutions -AI04605,Computer Vision Engineer,298482,USD,298482,EX,FT,United States,M,United States,0,"Mathematics, Deep Learning, MLOps, PyTorch, AWS",PhD,10,Real Estate,2024-08-11,2024-09-03,2282,9.1,Cognitive Computing -AI04606,Principal Data Scientist,91961,USD,91961,SE,FT,Ireland,S,Ireland,0,"Scala, GCP, Spark, SQL, Mathematics",Master,5,Education,2024-09-08,2024-10-30,781,9,Quantum Computing Inc -AI04607,Research Scientist,108071,EUR,91860,MI,FL,France,L,France,0,"Docker, AWS, GCP, Computer Vision, Azure",Master,4,Education,2024-07-26,2024-09-28,843,8.8,DeepTech Ventures -AI04608,Principal Data Scientist,89067,USD,89067,MI,CT,Denmark,S,India,0,"Python, TensorFlow, AWS, Computer Vision, SQL",PhD,2,Telecommunications,2025-01-06,2025-03-05,1228,8.5,Neural Networks Co -AI04609,Data Engineer,80773,USD,80773,MI,FT,South Korea,S,South Korea,50,"Python, Kubernetes, NLP, Tableau",Master,2,Real Estate,2024-11-01,2024-11-16,1040,5,AI Innovations -AI04610,Machine Learning Researcher,246330,CHF,221697,EX,PT,Switzerland,M,Switzerland,100,"Scala, PyTorch, AWS",Master,17,Government,2025-01-11,2025-03-04,2363,6,Autonomous Tech -AI04611,AI Software Engineer,158632,USD,158632,EX,FL,Sweden,L,Australia,50,"AWS, Kubernetes, TensorFlow, Statistics, SQL",PhD,16,Automotive,2025-03-16,2025-04-19,969,9.8,Quantum Computing Inc -AI04612,Computer Vision Engineer,55191,GBP,41393,EN,FT,United Kingdom,M,United Kingdom,100,"Hadoop, Java, Computer Vision, Spark",Associate,0,Manufacturing,2025-04-03,2025-06-05,2166,6,Autonomous Tech -AI04613,Data Analyst,290447,USD,290447,EX,PT,Norway,L,Norway,100,"R, Mathematics, Scala, PyTorch",Bachelor,17,Energy,2025-03-16,2025-05-13,2278,6.3,Smart Analytics -AI04614,ML Ops Engineer,162470,EUR,138100,EX,PT,Germany,M,Germany,100,"NLP, Docker, GCP",PhD,16,Manufacturing,2024-03-01,2024-05-08,2135,8.3,DeepTech Ventures -AI04615,Data Engineer,237565,USD,237565,EX,CT,Sweden,L,Spain,0,"Spark, Docker, Scala, Computer Vision, Tableau",PhD,13,Energy,2024-09-17,2024-10-29,1692,7.5,Digital Transformation LLC -AI04616,NLP Engineer,74020,USD,74020,MI,FT,Finland,M,Indonesia,100,"SQL, Spark, NLP, Data Visualization, Computer Vision",Master,2,Automotive,2024-03-06,2024-05-13,553,8.5,TechCorp Inc -AI04617,Principal Data Scientist,184394,USD,184394,EX,CT,Sweden,M,Sweden,0,"Spark, Kubernetes, MLOps, NLP, PyTorch",Bachelor,16,Healthcare,2024-04-03,2024-06-08,659,7.3,Autonomous Tech -AI04618,Data Scientist,195735,USD,195735,EX,FT,Norway,M,Norway,0,"Kubernetes, SQL, NLP",Master,14,Real Estate,2024-02-01,2024-03-07,2095,5.8,Cognitive Computing -AI04619,Machine Learning Engineer,321668,USD,321668,EX,FT,Norway,M,Norway,50,"TensorFlow, Git, Python, R",Associate,17,Finance,2024-05-14,2024-06-13,1411,5.6,Quantum Computing Inc -AI04620,Data Analyst,132287,USD,132287,EX,FL,South Korea,L,South Korea,100,"R, Java, NLP",Associate,16,Energy,2025-03-08,2025-04-02,520,7.3,Neural Networks Co -AI04621,AI Architect,70147,CHF,63132,EN,PT,Switzerland,S,China,0,"TensorFlow, NLP, Linux",Master,1,Transportation,2024-05-17,2024-06-18,887,9.1,Autonomous Tech -AI04622,Head of AI,58977,USD,58977,SE,FL,China,L,China,50,"Docker, GCP, Tableau, Computer Vision, Statistics",PhD,7,Consulting,2025-03-15,2025-05-01,1835,6.9,DeepTech Ventures -AI04623,Head of AI,115529,GBP,86647,MI,FT,United Kingdom,M,United Kingdom,50,"Java, Data Visualization, AWS",Master,2,Automotive,2024-05-03,2024-05-30,1604,5.3,Predictive Systems -AI04624,AI Specialist,123402,USD,123402,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Mathematics",Bachelor,5,Gaming,2024-02-15,2024-03-13,697,8.5,DataVision Ltd -AI04625,Robotics Engineer,81236,USD,81236,MI,PT,Sweden,S,Italy,0,"Scala, Deep Learning, Tableau, R, Python",Bachelor,3,Automotive,2024-10-06,2024-11-13,1216,8.6,Predictive Systems -AI04626,Deep Learning Engineer,23762,USD,23762,EN,FT,China,S,China,50,"Computer Vision, Kubernetes, SQL",Associate,1,Automotive,2024-05-10,2024-06-11,1602,8.5,Quantum Computing Inc -AI04627,Head of AI,80966,USD,80966,EN,CT,Norway,M,Norway,0,"Git, Kubernetes, Hadoop",Associate,1,Education,2024-03-20,2024-05-14,2283,6.1,Quantum Computing Inc -AI04628,AI Product Manager,184463,USD,184463,EX,FT,Denmark,M,United Kingdom,0,"Spark, Statistics, Linux, Java, Deep Learning",Master,10,Finance,2024-07-10,2024-08-22,944,9.5,Future Systems -AI04629,Machine Learning Engineer,80922,CHF,72830,EN,FL,Switzerland,S,Switzerland,100,"R, Azure, MLOps, Tableau, AWS",Bachelor,0,Automotive,2024-10-08,2024-11-21,1763,6.1,TechCorp Inc -AI04630,Data Engineer,225786,SGD,293522,EX,FL,Singapore,L,Netherlands,50,"Python, Spark, Deep Learning, Statistics",Bachelor,12,Transportation,2024-11-20,2024-12-20,2261,5.7,Advanced Robotics -AI04631,AI Specialist,174292,USD,174292,EX,FT,Sweden,S,Colombia,50,"Kubernetes, R, Data Visualization",PhD,10,Energy,2024-07-05,2024-08-16,1578,5.5,Future Systems -AI04632,AI Architect,141209,USD,141209,SE,FL,Finland,M,Finland,50,"Java, PyTorch, Tableau",Associate,9,Government,2025-03-15,2025-03-31,1379,5.6,TechCorp Inc -AI04633,AI Architect,33494,USD,33494,EN,FT,China,M,Chile,0,"R, MLOps, SQL, NLP",PhD,1,Gaming,2025-04-18,2025-05-05,2021,8.1,Algorithmic Solutions -AI04634,Head of AI,102081,GBP,76561,MI,FL,United Kingdom,L,Romania,100,"TensorFlow, Git, Spark, Data Visualization",Master,4,Manufacturing,2024-08-05,2024-09-27,1236,5.9,Cloud AI Solutions -AI04635,Computer Vision Engineer,142338,EUR,120987,SE,PT,Netherlands,M,Netherlands,100,"Scala, Kubernetes, Azure, Python",Master,6,Real Estate,2024-04-29,2024-07-02,1165,5.7,Neural Networks Co -AI04636,Robotics Engineer,111416,USD,111416,MI,FL,United States,S,United States,50,"Linux, Java, MLOps, Azure",Bachelor,3,Telecommunications,2024-11-08,2024-12-21,1032,6.8,AI Innovations -AI04637,Data Analyst,171510,USD,171510,EX,CT,Sweden,S,Austria,0,"SQL, Git, PyTorch, TensorFlow, Tableau",Master,14,Gaming,2024-05-10,2024-07-02,845,6.8,Predictive Systems -AI04638,Robotics Engineer,32757,USD,32757,EN,CT,China,S,Philippines,0,"Spark, Linux, PyTorch, Mathematics, Python",PhD,0,Energy,2024-04-27,2024-06-13,1275,9.6,TechCorp Inc -AI04639,Data Analyst,78323,GBP,58742,MI,CT,United Kingdom,S,United States,0,"TensorFlow, GCP, Mathematics, Java, Linux",Bachelor,3,Real Estate,2025-04-17,2025-05-09,942,8.2,DataVision Ltd -AI04640,Robotics Engineer,68649,GBP,51487,EN,FL,United Kingdom,S,Austria,0,"Hadoop, Git, Spark, PyTorch, Linux",PhD,1,Finance,2024-11-02,2024-12-07,1578,9.7,AI Innovations -AI04641,Deep Learning Engineer,82078,AUD,110805,MI,FL,Australia,M,Australia,50,"PyTorch, Java, Scala, Computer Vision, R",Bachelor,2,Energy,2025-03-30,2025-05-07,1484,6.2,Future Systems -AI04642,AI Software Engineer,65931,USD,65931,EN,CT,Denmark,S,Denmark,0,"Kubernetes, PyTorch, Mathematics, Linux, Git",Master,1,Media,2024-06-24,2024-08-13,691,6.8,DataVision Ltd -AI04643,Research Scientist,207846,USD,207846,EX,PT,South Korea,L,South Korea,50,"Linux, MLOps, SQL, Scala",Bachelor,15,Gaming,2024-06-12,2024-07-11,1452,6.7,Autonomous Tech -AI04644,Principal Data Scientist,107642,GBP,80732,MI,PT,United Kingdom,M,United Kingdom,0,"PyTorch, TensorFlow, Python, R, Data Visualization",Bachelor,4,Healthcare,2024-06-30,2024-07-31,2023,5.9,Cloud AI Solutions -AI04645,Head of AI,51450,EUR,43733,EN,PT,Germany,M,Germany,100,"Kubernetes, SQL, Tableau, MLOps, Deep Learning",PhD,0,Finance,2024-08-13,2024-08-31,1211,8.3,DeepTech Ventures -AI04646,Data Scientist,79522,CAD,99403,EN,CT,Canada,L,Germany,100,"Hadoop, Data Visualization, GCP",PhD,0,Gaming,2024-09-24,2024-11-29,802,8.6,Cloud AI Solutions -AI04647,Machine Learning Engineer,100881,USD,100881,MI,FT,Sweden,L,Sweden,100,"R, Azure, Kubernetes, Hadoop",Bachelor,4,Real Estate,2024-03-22,2024-04-21,631,5.3,Advanced Robotics -AI04648,Research Scientist,89648,USD,89648,MI,PT,Ireland,L,Japan,50,"Data Visualization, NLP, Scala, Python",Bachelor,2,Healthcare,2025-03-22,2025-04-18,785,9.6,Neural Networks Co -AI04649,Principal Data Scientist,227077,JPY,24978470,EX,FT,Japan,S,Japan,50,"NLP, PyTorch, GCP, Azure, AWS",Associate,16,Healthcare,2024-06-07,2024-08-15,1178,6.9,Autonomous Tech -AI04650,Data Scientist,141613,EUR,120371,SE,CT,France,L,Mexico,50,"Git, SQL, AWS",Associate,5,Technology,2024-06-13,2024-07-05,1876,9.5,Advanced Robotics -AI04651,AI Specialist,197086,USD,197086,SE,PT,Denmark,L,Denmark,50,"AWS, Linux, PyTorch, Spark",Associate,8,Retail,2024-05-20,2024-06-18,2105,7.5,Smart Analytics -AI04652,Research Scientist,34933,USD,34933,MI,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, Linux, Java",PhD,2,Media,2025-03-20,2025-04-07,683,9.8,AI Innovations -AI04653,AI Consultant,57403,AUD,77494,EN,PT,Australia,M,Australia,0,"Computer Vision, Java, Git, Hadoop",Associate,0,Automotive,2024-09-11,2024-10-22,584,8,TechCorp Inc -AI04654,Robotics Engineer,217171,GBP,162878,EX,FL,United Kingdom,S,United Kingdom,0,"R, Java, Data Visualization, Git, TensorFlow",Master,16,Healthcare,2024-04-24,2024-07-01,836,6.2,AI Innovations -AI04655,Computer Vision Engineer,85086,USD,85086,EX,FL,China,L,China,50,"Tableau, GCP, Python, Azure",Associate,19,Finance,2024-05-03,2024-07-02,1158,9.4,Quantum Computing Inc -AI04656,AI Product Manager,77309,GBP,57982,EN,CT,United Kingdom,L,Netherlands,50,"Python, R, Computer Vision, NLP, Java",Associate,1,Healthcare,2024-07-30,2024-09-21,936,9.9,Advanced Robotics -AI04657,AI Software Engineer,152616,EUR,129724,SE,FT,Netherlands,M,Malaysia,0,"Git, Scala, Deep Learning, Linux, R",Bachelor,5,Education,2024-05-30,2024-07-22,801,9.5,Cloud AI Solutions -AI04658,AI Architect,80354,CAD,100443,MI,FT,Canada,M,Canada,100,"SQL, AWS, MLOps, Linux, Python",Bachelor,3,Government,2025-02-12,2025-03-25,2160,5.3,AI Innovations -AI04659,Principal Data Scientist,130383,USD,130383,SE,FT,Sweden,S,Sweden,0,"SQL, GCP, TensorFlow, Mathematics, Python",PhD,9,Automotive,2024-04-16,2024-06-10,1167,5.6,TechCorp Inc -AI04660,AI Consultant,191150,AUD,258053,EX,PT,Australia,M,India,0,"Kubernetes, Linux, Tableau",Associate,11,Healthcare,2024-12-12,2025-02-09,2246,5,TechCorp Inc -AI04661,AI Specialist,77392,EUR,65783,MI,CT,Germany,S,Germany,50,"TensorFlow, Python, Azure, GCP",Master,4,Telecommunications,2024-05-07,2024-06-23,786,8.2,TechCorp Inc -AI04662,Data Scientist,72963,USD,72963,EN,CT,Israel,L,Israel,50,"Scala, TensorFlow, Deep Learning",Bachelor,0,Energy,2024-09-22,2024-10-31,1307,9.4,Smart Analytics -AI04663,AI Consultant,77791,AUD,105018,EN,FT,Australia,M,Australia,50,"Computer Vision, Git, Azure, Kubernetes, Statistics",Master,0,Real Estate,2024-04-06,2024-04-30,1900,7.2,DataVision Ltd -AI04664,Robotics Engineer,150499,EUR,127924,EX,CT,Austria,L,Russia,100,"Scala, Kubernetes, PyTorch, TensorFlow",Associate,17,Technology,2024-08-04,2024-10-07,1341,9.2,TechCorp Inc -AI04665,Principal Data Scientist,79579,USD,79579,MI,FT,Sweden,M,Sweden,0,"Linux, Python, GCP",PhD,4,Media,2025-01-16,2025-03-01,1594,6.1,DeepTech Ventures -AI04666,AI Software Engineer,251411,EUR,213699,EX,CT,Germany,L,Germany,100,"Python, Kubernetes, TensorFlow, GCP, Scala",Master,11,Retail,2024-02-07,2024-04-13,581,8.3,Autonomous Tech -AI04667,AI Specialist,54870,USD,54870,MI,FT,South Korea,S,South Korea,0,"Python, TensorFlow, Docker, Linux",Master,3,Transportation,2024-05-24,2024-07-18,1639,8.5,Machine Intelligence Group -AI04668,ML Ops Engineer,104878,EUR,89146,SE,FL,France,S,France,0,"PyTorch, Mathematics, Linux, Git, Deep Learning",Master,9,Healthcare,2025-04-15,2025-05-31,597,9.6,Cognitive Computing -AI04669,Data Scientist,76528,USD,76528,MI,FL,South Korea,L,Sweden,50,"TensorFlow, PyTorch, Docker, NLP, Computer Vision",Master,2,Automotive,2024-05-09,2024-06-14,1549,5.7,Cognitive Computing -AI04670,Autonomous Systems Engineer,372494,CHF,335245,EX,FL,Switzerland,L,Switzerland,50,"Kubernetes, Scala, Java, Git, MLOps",Associate,18,Media,2024-01-15,2024-02-24,1253,8.8,Predictive Systems -AI04671,Machine Learning Engineer,135702,USD,135702,SE,PT,Finland,M,Belgium,100,"Scala, Git, Computer Vision",Bachelor,5,Telecommunications,2024-07-23,2024-08-21,563,8.4,Predictive Systems -AI04672,AI Software Engineer,75693,USD,75693,EN,FT,Denmark,S,Denmark,100,"PyTorch, Kubernetes, Azure",Associate,1,Automotive,2025-04-19,2025-06-09,690,9.8,Machine Intelligence Group -AI04673,Data Scientist,104982,USD,104982,EN,FL,Norway,L,Norway,50,"Java, Tableau, Mathematics, Scala",Bachelor,1,Transportation,2025-03-16,2025-04-20,1806,5.6,Advanced Robotics -AI04674,Research Scientist,244711,EUR,208004,EX,FT,Austria,L,Austria,50,"SQL, NLP, MLOps",Master,12,Government,2024-08-29,2024-10-07,2403,8.7,Future Systems -AI04675,Machine Learning Researcher,45500,USD,45500,EN,CT,South Korea,S,South Korea,50,"TensorFlow, Python, AWS",Master,1,Transportation,2024-01-09,2024-02-24,670,6.9,Autonomous Tech -AI04676,Machine Learning Engineer,117161,USD,117161,EX,FL,Israel,S,Russia,100,"R, Hadoop, Python",Bachelor,14,Automotive,2024-08-06,2024-08-26,1132,5.6,TechCorp Inc -AI04677,ML Ops Engineer,69868,CAD,87335,EN,CT,Canada,M,Turkey,100,"TensorFlow, SQL, Azure, AWS",Master,0,Manufacturing,2024-10-06,2024-11-05,1205,7.8,TechCorp Inc -AI04678,Data Engineer,64406,EUR,54745,EN,CT,Austria,M,Austria,50,"Deep Learning, Kubernetes, R",Bachelor,1,Healthcare,2024-09-07,2024-10-23,1125,9.2,Autonomous Tech -AI04679,AI Consultant,237645,EUR,201998,EX,FL,Netherlands,M,Netherlands,100,"Python, TensorFlow, Deep Learning, NLP",Associate,19,Technology,2025-03-22,2025-04-29,1161,5.5,Autonomous Tech -AI04680,AI Product Manager,49582,USD,49582,EN,FL,Finland,S,Finland,100,"GCP, Java, Python",Master,0,Manufacturing,2024-11-10,2024-11-25,1340,7.8,AI Innovations -AI04681,Data Scientist,83059,USD,83059,MI,PT,Ireland,S,Russia,100,"PyTorch, Data Visualization, Scala, GCP, Mathematics",Associate,3,Transportation,2024-01-02,2024-03-08,837,8.6,Cloud AI Solutions -AI04682,AI Specialist,136959,USD,136959,SE,FT,Ireland,L,Ireland,100,"Mathematics, Git, Statistics",Associate,6,Transportation,2024-02-22,2024-04-03,2084,7.6,Predictive Systems -AI04683,Autonomous Systems Engineer,107694,USD,107694,MI,FT,Denmark,S,Italy,0,"SQL, Mathematics, Tableau, Azure, MLOps",PhD,3,Retail,2024-12-24,2025-01-15,1759,8.1,TechCorp Inc -AI04684,AI Architect,179863,SGD,233822,EX,FT,Singapore,S,Singapore,0,"Data Visualization, Python, TensorFlow, Computer Vision",PhD,13,Telecommunications,2024-08-17,2024-10-29,1456,8.9,Future Systems -AI04685,Principal Data Scientist,138581,USD,138581,SE,CT,Sweden,L,Sweden,0,"Java, R, Linux, Git, MLOps",Master,5,Technology,2024-06-18,2024-08-29,602,9.3,Autonomous Tech -AI04686,Robotics Engineer,167250,GBP,125438,SE,FT,United Kingdom,L,Denmark,100,"Linux, Kubernetes, Computer Vision, Deep Learning, Data Visualization",Master,8,Finance,2024-02-26,2024-04-02,1324,6.9,TechCorp Inc -AI04687,ML Ops Engineer,73285,CAD,91606,MI,FL,Canada,S,Canada,0,"Statistics, AWS, SQL, MLOps",Bachelor,4,Telecommunications,2025-02-19,2025-04-19,1577,7.6,Digital Transformation LLC -AI04688,Machine Learning Researcher,90517,USD,90517,MI,PT,Finland,M,Sweden,50,"NLP, AWS, Scala",Master,3,Retail,2024-05-09,2024-07-02,1600,5.8,Future Systems -AI04689,AI Specialist,137917,USD,137917,EX,FT,Ireland,S,Spain,100,"TensorFlow, SQL, Linux, Python",PhD,17,Automotive,2025-01-01,2025-02-04,1945,6,Cloud AI Solutions -AI04690,AI Architect,113385,EUR,96377,MI,FL,Netherlands,M,Netherlands,100,"Data Visualization, SQL, Git",Bachelor,2,Real Estate,2024-08-12,2024-10-10,1861,7.3,Cognitive Computing -AI04691,Research Scientist,91903,USD,91903,MI,FL,South Korea,L,South Korea,0,"GCP, Git, Tableau",Master,4,Manufacturing,2024-10-24,2024-12-09,1403,5.4,Future Systems -AI04692,Autonomous Systems Engineer,62142,USD,62142,EN,FL,Denmark,S,Denmark,100,"SQL, R, Computer Vision, Statistics",Associate,1,Finance,2024-12-25,2025-02-19,897,8.4,Advanced Robotics -AI04693,Head of AI,162597,EUR,138207,EX,CT,Austria,M,Austria,0,"Computer Vision, MLOps, Python",Associate,13,Technology,2024-02-14,2024-04-04,2369,5,Cognitive Computing -AI04694,AI Product Manager,277090,CHF,249381,EX,PT,Switzerland,S,Switzerland,100,"PyTorch, Deep Learning, Azure",Associate,18,Gaming,2024-07-14,2024-08-10,1405,7.3,DeepTech Ventures -AI04695,AI Architect,111361,EUR,94657,SE,PT,Germany,S,Nigeria,100,"Linux, Scala, Statistics, Python, Computer Vision",Bachelor,7,Media,2024-12-28,2025-02-22,566,5.9,Digital Transformation LLC -AI04696,Data Engineer,124750,USD,124750,SE,CT,Sweden,S,Sweden,50,"Hadoop, Python, NLP",Master,9,Government,2024-03-08,2024-04-13,1770,9.3,Smart Analytics -AI04697,AI Architect,59624,USD,59624,MI,FL,South Korea,M,Netherlands,100,"SQL, Data Visualization, Java, Docker, Linux",PhD,3,Transportation,2024-05-13,2024-06-07,776,5.7,Neural Networks Co -AI04698,AI Consultant,176619,USD,176619,SE,FT,Norway,M,Norway,0,"Git, AWS, Kubernetes, Hadoop",PhD,6,Consulting,2024-08-25,2024-10-17,1981,7.1,Predictive Systems -AI04699,Head of AI,60007,USD,60007,EX,CT,China,S,China,0,"Python, Data Visualization, TensorFlow, Java, Mathematics",Master,17,Education,2025-03-16,2025-04-08,1337,8,Cloud AI Solutions -AI04700,Head of AI,76104,EUR,64688,EN,FL,Germany,M,Germany,0,"Spark, NLP, Deep Learning, Hadoop, Kubernetes",Bachelor,0,Government,2024-01-21,2024-02-26,1394,6.7,Algorithmic Solutions -AI04701,NLP Engineer,116281,USD,116281,SE,CT,Ireland,S,Ireland,100,"Data Visualization, Kubernetes, NLP, Python, Deep Learning",PhD,8,Energy,2024-10-26,2024-12-12,1894,7,Advanced Robotics -AI04702,Autonomous Systems Engineer,67934,USD,67934,EN,FL,Ireland,S,Ireland,0,"SQL, Kubernetes, Python",Associate,1,Transportation,2024-08-05,2024-09-09,946,7.4,Digital Transformation LLC -AI04703,Data Analyst,62548,EUR,53166,EN,FL,Netherlands,M,Singapore,100,"Data Visualization, PyTorch, AWS, Python, Hadoop",PhD,1,Government,2024-11-12,2025-01-21,1149,8.5,Cognitive Computing -AI04704,Machine Learning Researcher,32890,USD,32890,EN,CT,China,L,China,100,"Hadoop, Mathematics, Kubernetes",Bachelor,0,Energy,2025-02-15,2025-03-24,802,9,AI Innovations -AI04705,Computer Vision Engineer,82416,USD,82416,MI,PT,Sweden,S,Sweden,0,"Tableau, GCP, Docker, Kubernetes, Statistics",Master,2,Finance,2024-11-05,2025-01-05,1089,6.6,Predictive Systems -AI04706,Machine Learning Engineer,143048,CAD,178810,SE,PT,Canada,M,Nigeria,50,"R, SQL, AWS, GCP, Data Visualization",Associate,8,Manufacturing,2024-09-19,2024-10-29,571,9.8,Quantum Computing Inc -AI04707,Deep Learning Engineer,76432,USD,76432,EX,CT,India,M,India,100,"MLOps, Kubernetes, SQL, R",Bachelor,11,Technology,2024-11-14,2025-01-14,1773,5,Advanced Robotics -AI04708,ML Ops Engineer,91651,EUR,77903,MI,FT,Germany,L,Belgium,50,"Hadoop, Spark, Data Visualization, Statistics",Bachelor,2,Energy,2024-03-13,2024-04-21,2373,5.1,Autonomous Tech -AI04709,Data Engineer,119672,CHF,107705,EN,PT,Switzerland,L,Switzerland,50,"Mathematics, R, NLP",Associate,0,Energy,2025-02-25,2025-04-11,2305,6.2,Quantum Computing Inc -AI04710,AI Consultant,91372,USD,91372,SE,FL,Finland,S,Finland,0,"Python, GCP, Linux, TensorFlow, R",Master,9,Automotive,2024-04-06,2024-05-29,2201,9.8,Smart Analytics -AI04711,AI Specialist,136154,CHF,122539,MI,FT,Switzerland,M,Switzerland,0,"PyTorch, Docker, Kubernetes, SQL",Associate,2,Technology,2024-09-03,2024-11-05,2425,6.2,Autonomous Tech -AI04712,Robotics Engineer,48395,USD,48395,EX,CT,India,S,United Kingdom,50,"Deep Learning, Azure, Spark, Python",Associate,13,Education,2024-11-21,2024-12-20,2192,5.2,Algorithmic Solutions -AI04713,Machine Learning Engineer,105774,USD,105774,EN,FL,United States,L,United States,0,"PyTorch, MLOps, Docker",Associate,1,Automotive,2024-10-31,2025-01-05,2274,7.1,Digital Transformation LLC -AI04714,Data Analyst,160016,USD,160016,SE,FT,Denmark,S,Denmark,50,"Kubernetes, TensorFlow, Docker, Statistics, Computer Vision",Associate,8,Government,2024-01-31,2024-02-17,1543,8.7,Future Systems -AI04715,Autonomous Systems Engineer,206793,CHF,186114,SE,PT,Switzerland,L,Switzerland,50,"SQL, TensorFlow, GCP, Kubernetes",Bachelor,9,Retail,2024-09-04,2024-10-09,1451,7.9,Predictive Systems -AI04716,AI Architect,86168,USD,86168,EX,CT,India,L,India,100,"Mathematics, GCP, Data Visualization, Spark, Java",Bachelor,11,Technology,2024-12-08,2025-02-08,2468,7.7,Cloud AI Solutions -AI04717,AI Consultant,123853,USD,123853,SE,PT,Sweden,L,Sweden,100,"Computer Vision, Python, TensorFlow, Spark, Deep Learning",PhD,7,Retail,2024-04-27,2024-06-29,2048,8,Autonomous Tech -AI04718,AI Specialist,78399,SGD,101919,EN,PT,Singapore,L,Singapore,0,"SQL, GCP, MLOps, Deep Learning",Bachelor,0,Real Estate,2025-03-20,2025-05-19,962,9.3,Predictive Systems -AI04719,Machine Learning Engineer,138128,SGD,179566,SE,FL,Singapore,M,Ukraine,50,"Kubernetes, Deep Learning, TensorFlow",Master,6,Automotive,2025-02-15,2025-03-13,1918,8.5,Algorithmic Solutions -AI04720,Data Engineer,90321,CAD,112901,MI,FL,Canada,S,Canada,50,"Python, Linux, GCP, Hadoop",Master,2,Consulting,2024-06-05,2024-06-26,2352,9.8,Machine Intelligence Group -AI04721,NLP Engineer,90443,CAD,113054,MI,FT,Canada,L,Canada,0,"Git, Hadoop, Azure, Tableau, Java",Associate,2,Retail,2025-04-08,2025-06-15,1599,8.2,Smart Analytics -AI04722,ML Ops Engineer,121587,EUR,103349,SE,PT,Austria,M,Austria,50,"Docker, Python, MLOps, Git",Master,8,Government,2025-02-22,2025-04-16,1807,7.7,Autonomous Tech -AI04723,Principal Data Scientist,226775,CHF,204098,SE,PT,Switzerland,L,Switzerland,0,"Scala, Deep Learning, Statistics",Associate,8,Telecommunications,2024-11-30,2025-01-26,819,5.3,Future Systems -AI04724,AI Research Scientist,97958,USD,97958,SE,PT,Ireland,S,Ireland,50,"Kubernetes, Python, Data Visualization, MLOps",PhD,5,Gaming,2024-12-02,2025-02-11,1617,9.8,Predictive Systems -AI04725,Deep Learning Engineer,59895,SGD,77864,EN,CT,Singapore,S,Singapore,50,"Python, TensorFlow, Computer Vision, Azure",PhD,1,Real Estate,2024-08-03,2024-08-23,1154,6.8,Neural Networks Co -AI04726,Deep Learning Engineer,96051,USD,96051,MI,CT,Norway,S,Norway,50,"GCP, Hadoop, Deep Learning, Computer Vision",Bachelor,3,Telecommunications,2024-04-15,2024-05-15,1776,6.5,TechCorp Inc -AI04727,Data Analyst,194676,USD,194676,EX,FT,United States,S,Russia,100,"GCP, SQL, Statistics, Java",PhD,13,Transportation,2025-04-26,2025-06-26,1204,9.7,Machine Intelligence Group -AI04728,Principal Data Scientist,83606,SGD,108688,EN,CT,Singapore,M,Singapore,100,"Python, Kubernetes, Hadoop",Associate,0,Gaming,2025-02-24,2025-03-29,2429,5.2,Machine Intelligence Group -AI04729,AI Product Manager,35409,USD,35409,EN,FT,China,L,China,0,"Spark, Kubernetes, Deep Learning",Master,0,Technology,2024-06-13,2024-07-04,2134,5.4,Future Systems -AI04730,AI Product Manager,75374,USD,75374,MI,FL,Ireland,S,Kenya,50,"R, NLP, AWS, Java",Bachelor,2,Manufacturing,2025-02-09,2025-04-03,701,7.6,Cognitive Computing -AI04731,Principal Data Scientist,79994,USD,79994,EX,FT,China,L,China,0,"Hadoop, Python, NLP",Master,17,Real Estate,2024-05-02,2024-07-07,597,8,Autonomous Tech -AI04732,Deep Learning Engineer,78389,EUR,66631,MI,CT,France,S,France,50,"R, Java, Deep Learning, Statistics, Docker",Master,4,Energy,2025-04-30,2025-06-14,2477,5.9,DeepTech Ventures -AI04733,Head of AI,295681,USD,295681,EX,FT,Denmark,L,Denmark,100,"Tableau, Linux, Git",Master,10,Healthcare,2024-05-26,2024-06-27,524,9.4,Digital Transformation LLC -AI04734,AI Software Engineer,126906,EUR,107870,SE,PT,Germany,L,South Korea,100,"Spark, SQL, Azure",PhD,5,Real Estate,2025-04-29,2025-06-05,1181,9.6,Advanced Robotics -AI04735,AI Architect,158136,EUR,134416,EX,CT,Germany,M,Germany,50,"Kubernetes, Python, Linux, Docker",PhD,19,Manufacturing,2024-11-21,2024-12-17,1866,10,Advanced Robotics -AI04736,Computer Vision Engineer,147980,USD,147980,SE,FL,Norway,S,Norway,50,"Python, NLP, Azure",Master,9,Government,2024-07-06,2024-08-17,1488,6.4,Predictive Systems -AI04737,Head of AI,90573,USD,90573,MI,CT,Norway,S,Norway,0,"SQL, Kubernetes, Tableau",Associate,2,Gaming,2024-06-18,2024-08-07,883,5.2,Cloud AI Solutions -AI04738,Machine Learning Researcher,287295,USD,287295,EX,FL,Norway,L,Switzerland,100,"Azure, Data Visualization, Python, TensorFlow, AWS",PhD,10,Healthcare,2024-07-23,2024-08-08,1834,6,Cognitive Computing -AI04739,Deep Learning Engineer,206996,EUR,175947,EX,PT,Netherlands,L,Netherlands,50,"Mathematics, Data Visualization, Java, Docker",PhD,18,Real Estate,2024-08-09,2024-09-06,865,8.7,DataVision Ltd -AI04740,Autonomous Systems Engineer,122080,SGD,158704,SE,PT,Singapore,M,Romania,100,"Tableau, Mathematics, GCP",Bachelor,5,Transportation,2024-11-12,2024-11-28,1587,9.6,Digital Transformation LLC -AI04741,Computer Vision Engineer,70756,USD,70756,EN,FT,United States,S,United States,50,"NLP, TensorFlow, Azure",Associate,0,Finance,2024-01-04,2024-02-05,1760,7.6,Neural Networks Co -AI04742,AI Architect,97152,CHF,87437,EN,FT,Switzerland,L,Switzerland,0,"Python, Data Visualization, TensorFlow",Bachelor,0,Automotive,2024-07-27,2024-09-02,1520,6.2,Quantum Computing Inc -AI04743,Machine Learning Engineer,166402,EUR,141442,SE,CT,Netherlands,L,Netherlands,100,"Linux, R, Scala, Azure, SQL",Bachelor,6,Media,2024-08-30,2024-10-23,1184,8.5,AI Innovations -AI04744,AI Research Scientist,67835,JPY,7461850,EN,FT,Japan,L,Japan,0,"Spark, Docker, Python",Associate,1,Automotive,2024-12-22,2025-01-08,620,9.2,Digital Transformation LLC -AI04745,Data Scientist,149496,EUR,127072,EX,PT,Austria,M,Austria,100,"Computer Vision, AWS, Python, TensorFlow",PhD,13,Consulting,2024-09-02,2024-10-14,1813,10,Future Systems -AI04746,AI Software Engineer,261114,USD,261114,EX,FT,Finland,L,Finland,100,"Computer Vision, Python, Docker, Deep Learning, Linux",Bachelor,10,Government,2025-01-27,2025-03-29,573,5.6,AI Innovations -AI04747,Machine Learning Researcher,39992,USD,39992,EN,CT,China,L,China,0,"GCP, Computer Vision, Data Visualization, Python",PhD,1,Manufacturing,2025-02-24,2025-05-05,2160,6.3,Predictive Systems -AI04748,NLP Engineer,127090,JPY,13979900,SE,FT,Japan,M,Japan,100,"Tableau, Hadoop, Computer Vision, Azure, Deep Learning",Master,6,Automotive,2024-05-05,2024-05-20,1570,8.1,Cognitive Computing -AI04749,Data Analyst,25060,USD,25060,EN,FT,India,M,India,100,"Hadoop, Spark, SQL, NLP, Docker",PhD,1,Gaming,2024-04-14,2024-06-13,1845,9.4,Neural Networks Co -AI04750,NLP Engineer,121674,JPY,13384140,SE,CT,Japan,M,Indonesia,50,"Python, Tableau, Hadoop",Master,5,Real Estate,2024-02-03,2024-03-22,1668,8.7,Quantum Computing Inc -AI04751,AI Product Manager,60372,JPY,6640920,EN,FT,Japan,M,Japan,100,"GCP, Git, NLP, Python, SQL",Associate,0,Retail,2025-04-15,2025-05-23,1562,8.1,AI Innovations -AI04752,Data Engineer,277451,USD,277451,EX,FT,Norway,S,China,100,"Docker, SQL, PyTorch",Bachelor,11,Retail,2024-03-25,2024-06-03,2111,7.8,Future Systems -AI04753,Research Scientist,112653,JPY,12391830,MI,FL,Japan,L,Japan,100,"Python, SQL, Java, Spark",Bachelor,2,Energy,2024-12-25,2025-02-06,2007,8.1,Future Systems -AI04754,AI Consultant,65378,EUR,55571,EN,PT,Austria,S,Austria,100,"PyTorch, Git, MLOps, TensorFlow",Bachelor,0,Healthcare,2025-03-15,2025-05-12,990,7.1,Future Systems -AI04755,Data Engineer,70603,USD,70603,EN,FL,Ireland,M,Chile,50,"NLP, Deep Learning, Git, Kubernetes",PhD,1,Media,2025-01-03,2025-02-12,1881,7.6,Smart Analytics -AI04756,Head of AI,190525,USD,190525,EX,FT,Denmark,S,Estonia,0,"Python, Deep Learning, MLOps, Azure",Bachelor,15,Gaming,2025-02-21,2025-03-16,2332,7.2,Smart Analytics -AI04757,Research Scientist,61699,EUR,52444,EN,FT,Netherlands,M,Netherlands,50,"R, Tableau, Kubernetes",Bachelor,1,Automotive,2024-09-03,2024-10-30,594,8.8,Machine Intelligence Group -AI04758,AI Research Scientist,273689,GBP,205267,EX,FT,United Kingdom,L,Czech Republic,100,"Azure, Linux, Hadoop, Java, Python",PhD,10,Manufacturing,2025-02-02,2025-04-14,2382,6.3,DeepTech Ventures -AI04759,Machine Learning Researcher,99938,USD,99938,MI,CT,United States,M,United States,0,"Azure, Kubernetes, Deep Learning",PhD,3,Retail,2024-09-13,2024-11-02,2160,6.9,Future Systems -AI04760,Robotics Engineer,109758,USD,109758,MI,FT,Ireland,M,Ireland,0,"SQL, NLP, Tableau, Computer Vision, PyTorch",Bachelor,4,Retail,2024-08-14,2024-10-01,1696,5.1,Advanced Robotics -AI04761,AI Consultant,107303,USD,107303,MI,CT,Israel,L,Singapore,50,"TensorFlow, SQL, NLP, Git",PhD,3,Energy,2025-02-28,2025-04-29,1075,8.2,Algorithmic Solutions -AI04762,Data Analyst,89290,USD,89290,EN,FT,Ireland,L,Ireland,50,"Scala, Kubernetes, Tableau",PhD,0,Finance,2024-02-15,2024-04-01,2246,7,Autonomous Tech -AI04763,Data Scientist,172273,USD,172273,EX,PT,Israel,S,Israel,0,"Java, Tableau, Docker",Associate,10,Government,2025-01-26,2025-03-28,1270,9.4,Machine Intelligence Group -AI04764,AI Product Manager,98723,AUD,133276,MI,FL,Australia,L,Australia,50,"Data Visualization, GCP, Scala, MLOps",Master,4,Real Estate,2024-05-08,2024-05-22,824,5.3,Cloud AI Solutions -AI04765,Autonomous Systems Engineer,64219,USD,64219,EN,FT,Ireland,S,Ireland,0,"Linux, Spark, Tableau",PhD,1,Government,2024-01-12,2024-02-18,885,9.1,Predictive Systems -AI04766,Principal Data Scientist,163057,JPY,17936270,SE,FT,Japan,L,Japan,100,"Spark, SQL, Docker, Linux",Master,7,Government,2025-04-20,2025-05-09,1937,8.5,Quantum Computing Inc -AI04767,Machine Learning Engineer,175853,EUR,149475,EX,CT,Netherlands,L,Philippines,100,"PyTorch, AWS, SQL, Python",Master,16,Automotive,2024-02-11,2024-04-12,505,7.7,Cognitive Computing -AI04768,Computer Vision Engineer,24322,USD,24322,EN,PT,India,S,Canada,0,"Azure, MLOps, Python",Associate,1,Finance,2024-07-12,2024-08-28,631,10,Predictive Systems -AI04769,Autonomous Systems Engineer,296894,GBP,222671,EX,CT,United Kingdom,L,United Kingdom,0,"MLOps, SQL, Python, Tableau, Git",Associate,12,Education,2024-12-12,2025-01-04,1608,7.2,TechCorp Inc -AI04770,Deep Learning Engineer,102705,AUD,138652,MI,PT,Australia,M,Australia,0,"SQL, Azure, R",Bachelor,4,Government,2025-01-18,2025-03-27,2238,6.7,Advanced Robotics -AI04771,AI Software Engineer,80745,SGD,104969,MI,CT,Singapore,S,Singapore,50,"Kubernetes, Python, TensorFlow, Statistics",Associate,4,Technology,2024-01-28,2024-03-23,1996,6,Digital Transformation LLC -AI04772,AI Specialist,135774,USD,135774,EX,FT,Ireland,S,Ireland,50,"Computer Vision, Kubernetes, Git",PhD,14,Government,2024-02-27,2024-03-15,927,6.8,Predictive Systems -AI04773,AI Architect,66185,GBP,49639,EN,CT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow, PyTorch",PhD,0,Manufacturing,2024-04-03,2024-06-11,2185,7.8,Autonomous Tech -AI04774,Computer Vision Engineer,142177,USD,142177,MI,FL,Denmark,M,Denmark,0,"Kubernetes, TensorFlow, Docker",PhD,2,Telecommunications,2024-10-16,2024-12-09,2400,8.8,DeepTech Ventures -AI04775,Head of AI,85696,USD,85696,MI,CT,Israel,S,Denmark,100,"Data Visualization, Docker, PyTorch, MLOps, AWS",Master,3,Healthcare,2024-09-16,2024-10-25,1250,8.2,Predictive Systems -AI04776,Data Analyst,148270,GBP,111203,SE,FL,United Kingdom,M,United Kingdom,100,"TensorFlow, Hadoop, MLOps, Statistics",Associate,6,Media,2024-03-16,2024-04-12,583,9.5,Cognitive Computing -AI04777,NLP Engineer,133788,USD,133788,SE,FL,Denmark,S,Ukraine,100,"Linux, Azure, Docker, Computer Vision",PhD,8,Gaming,2025-04-15,2025-05-24,2156,6,Machine Intelligence Group -AI04778,AI Specialist,162677,GBP,122008,EX,FL,United Kingdom,S,United Kingdom,50,"R, Python, Linux",Master,17,Healthcare,2025-03-23,2025-04-20,2094,7.5,Advanced Robotics -AI04779,Autonomous Systems Engineer,152781,USD,152781,SE,CT,Finland,L,Egypt,0,"SQL, PyTorch, NLP, Computer Vision, Deep Learning",Master,9,Technology,2024-07-31,2024-08-21,1388,7.3,Neural Networks Co -AI04780,Research Scientist,91758,EUR,77994,EN,CT,Germany,L,Germany,0,"Scala, PyTorch, Spark",Bachelor,1,Telecommunications,2024-06-09,2024-07-29,2194,9.1,Autonomous Tech -AI04781,AI Architect,151164,CHF,136048,MI,FL,Switzerland,M,Switzerland,100,"Python, Linux, Computer Vision, Tableau",Associate,2,Finance,2024-09-17,2024-11-04,1670,7.9,DeepTech Ventures -AI04782,AI Product Manager,71129,GBP,53347,EN,CT,United Kingdom,S,Spain,50,"SQL, R, Kubernetes",Associate,1,Education,2025-04-22,2025-06-19,1826,7.3,Autonomous Tech -AI04783,Data Scientist,133851,GBP,100388,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, AWS, Hadoop",Master,8,Gaming,2024-07-27,2024-08-14,1570,9.4,Neural Networks Co -AI04784,Principal Data Scientist,60769,USD,60769,MI,FT,South Korea,S,Spain,0,"Data Visualization, Deep Learning, TensorFlow, SQL, Git",Associate,2,Retail,2024-10-03,2024-12-13,2176,7.5,DataVision Ltd -AI04785,AI Research Scientist,184176,EUR,156550,EX,CT,Netherlands,L,Netherlands,100,"Git, NLP, Tableau, SQL, Linux",Associate,15,Manufacturing,2024-06-04,2024-07-16,1994,5.6,TechCorp Inc -AI04786,NLP Engineer,225359,USD,225359,EX,FL,Israel,M,Indonesia,100,"R, Git, AWS",Associate,18,Healthcare,2024-10-25,2024-11-28,1608,6.1,AI Innovations -AI04787,Autonomous Systems Engineer,257030,USD,257030,EX,PT,United States,S,Romania,50,"Git, Linux, Python",PhD,18,Manufacturing,2025-01-20,2025-03-15,1880,6.3,Algorithmic Solutions -AI04788,Data Scientist,106616,SGD,138601,SE,FT,Singapore,S,Sweden,0,"Python, Mathematics, Java, Computer Vision",Associate,8,Retail,2024-02-22,2024-04-22,1948,6.5,DeepTech Ventures -AI04789,Machine Learning Engineer,28056,USD,28056,EN,CT,China,S,China,0,"NLP, Kubernetes, Java",Bachelor,0,Gaming,2024-03-29,2024-05-13,2016,7.1,DataVision Ltd -AI04790,AI Consultant,149551,EUR,127118,SE,CT,France,L,France,0,"Spark, R, SQL, Hadoop",Associate,9,Gaming,2025-01-09,2025-03-17,1387,8.7,Digital Transformation LLC -AI04791,Machine Learning Engineer,72604,AUD,98015,EN,PT,Australia,S,Australia,50,"Tableau, Mathematics, MLOps, Python, TensorFlow",Associate,1,Technology,2024-06-12,2024-07-08,1177,5.6,AI Innovations -AI04792,Principal Data Scientist,57678,USD,57678,EN,FT,Finland,L,Finland,0,"Spark, Java, Statistics, Linux",Bachelor,1,Consulting,2024-12-09,2025-02-20,1801,6.7,Machine Intelligence Group -AI04793,Robotics Engineer,56249,USD,56249,EN,FL,Israel,S,Israel,50,"Python, Tableau, TensorFlow, Data Visualization, Mathematics",Bachelor,1,Transportation,2024-03-01,2024-04-21,537,7.6,Machine Intelligence Group -AI04794,ML Ops Engineer,100701,USD,100701,EX,FL,China,L,France,0,"SQL, Git, Spark, Linux",Associate,13,Media,2024-12-18,2025-01-04,2279,9.3,DataVision Ltd -AI04795,Machine Learning Engineer,86400,USD,86400,EN,CT,United States,M,Kenya,100,"Scala, Deep Learning, Java",Master,0,Retail,2024-01-29,2024-02-21,1913,7.1,AI Innovations -AI04796,AI Specialist,161695,JPY,17786450,SE,CT,Japan,L,Japan,0,"NLP, Docker, Tableau, R",Bachelor,6,Finance,2024-10-12,2024-11-10,2341,7.2,Cognitive Computing -AI04797,AI Consultant,101102,JPY,11121220,MI,PT,Japan,L,Japan,100,"Linux, Data Visualization, PyTorch, Statistics",Master,3,Telecommunications,2024-03-14,2024-04-01,1091,8.8,DeepTech Ventures -AI04798,AI Architect,72270,USD,72270,EN,FL,Ireland,M,Ireland,0,"Deep Learning, R, PyTorch",Associate,1,Energy,2025-03-26,2025-04-25,913,7.9,TechCorp Inc -AI04799,Machine Learning Engineer,53789,USD,53789,EN,PT,South Korea,M,South Korea,0,"SQL, Spark, Tableau",Bachelor,0,Energy,2024-11-19,2025-01-20,1724,5.2,Future Systems -AI04800,Computer Vision Engineer,104468,USD,104468,MI,FL,South Korea,L,South Korea,100,"Java, SQL, Hadoop",Master,2,Retail,2024-09-08,2024-10-25,1169,7.9,Future Systems -AI04801,ML Ops Engineer,225913,USD,225913,EX,FT,Ireland,S,Ireland,100,"Azure, SQL, TensorFlow, Python",Associate,17,Energy,2025-01-30,2025-02-24,2216,6.7,Neural Networks Co -AI04802,AI Specialist,178459,USD,178459,SE,FL,Norway,L,France,100,"SQL, AWS, Computer Vision, GCP, Data Visualization",Master,8,Gaming,2024-05-21,2024-06-07,879,7.1,Quantum Computing Inc -AI04803,Principal Data Scientist,168120,USD,168120,EX,FT,United States,S,United States,0,"Computer Vision, Docker, AWS, Python",PhD,19,Education,2024-11-12,2024-12-16,996,6.9,Quantum Computing Inc -AI04804,AI Specialist,66095,USD,66095,EN,PT,United States,S,Egypt,100,"GCP, Git, Hadoop, Tableau, PyTorch",PhD,0,Manufacturing,2024-08-31,2024-10-07,2130,7.6,Predictive Systems -AI04805,AI Architect,288067,USD,288067,EX,PT,United States,L,United States,0,"SQL, MLOps, PyTorch, Azure",Associate,18,Telecommunications,2024-04-01,2024-05-22,1686,7.8,Autonomous Tech -AI04806,Deep Learning Engineer,18634,USD,18634,EN,FL,India,S,Ireland,50,"Java, Docker, GCP",Master,1,Transportation,2024-09-13,2024-11-20,1978,9.2,Advanced Robotics -AI04807,Research Scientist,66098,USD,66098,EX,FT,China,M,China,0,"Python, Azure, MLOps, TensorFlow, Docker",Master,18,Manufacturing,2025-01-09,2025-02-26,639,7.5,Machine Intelligence Group -AI04808,Computer Vision Engineer,43744,EUR,37182,EN,FL,Austria,S,Austria,0,"Azure, Linux, PyTorch",Bachelor,1,Government,2024-08-27,2024-11-05,1325,7.1,Future Systems -AI04809,Computer Vision Engineer,57278,EUR,48686,EN,PT,Netherlands,M,Netherlands,50,"Deep Learning, Hadoop, GCP",Bachelor,0,Transportation,2024-03-30,2024-05-29,1116,6.2,Cloud AI Solutions -AI04810,AI Product Manager,59918,GBP,44939,EN,FT,United Kingdom,S,United Kingdom,50,"Python, Spark, Git, Deep Learning",Associate,0,Real Estate,2024-07-10,2024-09-04,1899,5.1,Advanced Robotics -AI04811,Data Scientist,68180,EUR,57953,EN,FT,Austria,M,Austria,0,"Python, Azure, Scala",Master,1,Manufacturing,2025-04-16,2025-06-15,563,9.4,Neural Networks Co -AI04812,AI Software Engineer,97864,GBP,73398,SE,PT,United Kingdom,S,United Kingdom,100,"Linux, Spark, GCP",Associate,6,Finance,2024-09-25,2024-10-25,2473,5.3,Advanced Robotics -AI04813,Research Scientist,113546,USD,113546,MI,FT,Ireland,L,Ireland,100,"Azure, Kubernetes, Statistics",Master,3,Healthcare,2024-04-27,2024-05-22,2269,5.8,AI Innovations -AI04814,Deep Learning Engineer,237348,JPY,26108280,EX,PT,Japan,S,Japan,50,"MLOps, Java, Spark, Azure",Master,10,Manufacturing,2025-03-13,2025-03-30,803,9.1,TechCorp Inc -AI04815,AI Architect,251015,SGD,326320,EX,FL,Singapore,M,Singapore,0,"PyTorch, Statistics, Azure, SQL",Associate,11,Government,2024-02-03,2024-04-15,1783,6,Cognitive Computing -AI04816,Machine Learning Engineer,78579,CAD,98224,MI,CT,Canada,M,Canada,100,"MLOps, Hadoop, Statistics, PyTorch, Mathematics",Bachelor,4,Government,2024-02-09,2024-03-09,1867,5.4,Future Systems -AI04817,Principal Data Scientist,85161,USD,85161,MI,CT,Ireland,M,Ireland,0,"PyTorch, TensorFlow, Statistics",Master,4,Telecommunications,2025-02-24,2025-03-29,1322,8.9,Future Systems -AI04818,Machine Learning Researcher,190172,EUR,161646,EX,FL,Netherlands,M,Netherlands,0,"Java, Computer Vision, Spark, GCP, Kubernetes",Bachelor,19,Technology,2024-05-02,2024-07-13,1469,9,Cognitive Computing -AI04819,AI Specialist,100405,JPY,11044550,MI,PT,Japan,L,Japan,50,"Python, Git, Tableau",PhD,3,Energy,2024-09-02,2024-11-14,1833,7.2,DataVision Ltd -AI04820,AI Research Scientist,42239,USD,42239,MI,FT,China,L,China,100,"Git, PyTorch, Azure",Bachelor,2,Energy,2024-03-19,2024-05-07,1606,6.7,DataVision Ltd -AI04821,Research Scientist,287260,USD,287260,EX,CT,Ireland,L,Malaysia,50,"Docker, PyTorch, Computer Vision",Master,14,Manufacturing,2024-06-26,2024-07-18,1892,7.2,Future Systems -AI04822,Data Analyst,198733,AUD,268290,EX,FL,Australia,M,Australia,100,"PyTorch, Computer Vision, AWS, Scala, Kubernetes",Associate,11,Media,2024-04-01,2024-04-22,1667,6.9,Future Systems -AI04823,Robotics Engineer,258415,EUR,219653,EX,CT,France,L,France,0,"MLOps, Scala, Spark",Master,17,Gaming,2024-01-21,2024-02-10,1407,5.7,Neural Networks Co -AI04824,AI Specialist,82073,USD,82073,MI,PT,Finland,M,Finland,100,"Python, TensorFlow, MLOps",Bachelor,3,Finance,2024-07-20,2024-08-25,1654,7.1,Cognitive Computing -AI04825,Deep Learning Engineer,111443,USD,111443,SE,FT,Israel,S,Japan,100,"GCP, SQL, Kubernetes, AWS",PhD,8,Consulting,2024-07-26,2024-09-14,500,8.3,Autonomous Tech -AI04826,AI Architect,200094,JPY,22010340,EX,CT,Japan,L,Japan,0,"Java, PyTorch, Azure, SQL",Bachelor,14,Education,2025-04-11,2025-05-19,1610,8.3,Cloud AI Solutions -AI04827,AI Product Manager,248923,EUR,211585,EX,PT,Germany,M,Nigeria,100,"Linux, Deep Learning, Mathematics, Docker",Master,19,Government,2024-07-25,2024-08-18,555,8.8,Cognitive Computing -AI04828,Computer Vision Engineer,72550,GBP,54413,EN,PT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Computer Vision, Git",Bachelor,1,Media,2024-12-22,2025-01-18,702,9.9,Machine Intelligence Group -AI04829,Deep Learning Engineer,206051,EUR,175143,EX,FL,Austria,L,Austria,100,"GCP, Hadoop, Deep Learning",Associate,13,Retail,2024-11-09,2024-12-22,1120,8.1,Advanced Robotics -AI04830,AI Software Engineer,141826,USD,141826,SE,CT,Sweden,M,Sweden,100,"Java, Scala, Mathematics",Bachelor,7,Finance,2024-12-18,2025-02-07,1838,7.2,DataVision Ltd -AI04831,ML Ops Engineer,196522,EUR,167044,EX,FT,France,S,France,100,"Python, Docker, Statistics",Master,18,Finance,2025-01-18,2025-02-25,708,7.9,Neural Networks Co -AI04832,Machine Learning Researcher,104082,SGD,135307,MI,PT,Singapore,M,Portugal,0,"AWS, R, Azure, Python, Git",PhD,2,Automotive,2024-11-26,2024-12-30,765,6.5,TechCorp Inc -AI04833,ML Ops Engineer,256314,USD,256314,EX,FL,United States,S,United States,0,"Mathematics, R, Deep Learning",Bachelor,11,Consulting,2024-05-23,2024-07-23,2116,9.7,Predictive Systems -AI04834,Computer Vision Engineer,62614,USD,62614,EX,PT,India,M,India,100,"TensorFlow, Git, Java, Computer Vision, Scala",Associate,15,Manufacturing,2024-05-14,2024-07-21,1318,7.9,Cloud AI Solutions -AI04835,AI Product Manager,104089,JPY,11449790,MI,PT,Japan,S,Japan,100,"Git, Docker, Data Visualization, Kubernetes, Scala",Associate,3,Government,2024-06-24,2024-08-16,1828,6.6,DeepTech Ventures -AI04836,ML Ops Engineer,52607,USD,52607,SE,FL,China,S,Vietnam,0,"Python, Statistics, Deep Learning, Scala",PhD,7,Telecommunications,2024-08-29,2024-09-18,2113,7.1,TechCorp Inc -AI04837,ML Ops Engineer,131333,USD,131333,SE,FT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Computer Vision",Master,6,Energy,2025-01-09,2025-02-25,1082,7.7,Predictive Systems -AI04838,Data Engineer,369918,CHF,332926,EX,CT,Switzerland,L,Switzerland,0,"Scala, Java, Deep Learning",Associate,18,Finance,2025-03-23,2025-06-03,2322,6,Machine Intelligence Group -AI04839,Computer Vision Engineer,288629,USD,288629,EX,PT,Sweden,L,Sweden,50,"PyTorch, MLOps, GCP",Associate,19,Telecommunications,2024-04-02,2024-05-27,1934,5.5,TechCorp Inc -AI04840,AI Consultant,186990,EUR,158942,EX,CT,Germany,S,Germany,100,"SQL, Data Visualization, Linux, Scala",PhD,16,Automotive,2025-04-02,2025-05-12,1952,9.8,DataVision Ltd -AI04841,AI Specialist,122223,USD,122223,SE,FT,Sweden,S,Sweden,100,"Data Visualization, Linux, PyTorch",PhD,7,Transportation,2025-03-26,2025-05-22,2384,6.8,DataVision Ltd -AI04842,Computer Vision Engineer,116177,USD,116177,SE,PT,Ireland,S,Ireland,100,"Git, Mathematics, Computer Vision, Java, Deep Learning",PhD,8,Consulting,2024-05-28,2024-06-22,939,9.8,Quantum Computing Inc -AI04843,Research Scientist,155331,USD,155331,EX,FT,Israel,M,Israel,0,"Statistics, Computer Vision, NLP, SQL, Data Visualization",Bachelor,15,Consulting,2024-04-17,2024-05-19,1147,5.7,Autonomous Tech -AI04844,Computer Vision Engineer,157720,EUR,134062,EX,PT,Austria,L,United States,50,"Python, GCP, Tableau, TensorFlow",Bachelor,11,Real Estate,2024-10-24,2024-12-27,1805,6.7,Predictive Systems -AI04845,AI Consultant,80697,CHF,72627,EN,PT,Switzerland,M,Switzerland,100,"PyTorch, Azure, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-10-08,2024-12-02,2026,6.8,Machine Intelligence Group -AI04846,Data Analyst,95727,EUR,81368,EN,FT,Netherlands,L,Netherlands,50,"PyTorch, Spark, Computer Vision",PhD,0,Government,2024-01-15,2024-03-03,1960,6.1,DeepTech Ventures -AI04847,NLP Engineer,303364,USD,303364,EX,FL,Norway,L,Norway,50,"Java, R, Spark, Docker, Deep Learning",Bachelor,18,Manufacturing,2024-10-10,2024-11-12,930,5.4,Machine Intelligence Group -AI04848,Robotics Engineer,130193,JPY,14321230,SE,FL,Japan,M,Japan,0,"Spark, Python, R, AWS, Statistics",Bachelor,5,Government,2025-04-16,2025-06-03,1110,8.1,DeepTech Ventures -AI04849,Data Scientist,87100,CAD,108875,MI,PT,Canada,S,Canada,0,"R, GCP, Azure, Linux, Kubernetes",Associate,3,Automotive,2024-05-14,2024-06-03,2350,5.4,Quantum Computing Inc -AI04850,Principal Data Scientist,253609,SGD,329692,EX,CT,Singapore,M,Singapore,100,"Tableau, Deep Learning, Hadoop",PhD,13,Telecommunications,2024-01-09,2024-02-12,723,5.2,TechCorp Inc -AI04851,Deep Learning Engineer,111947,CAD,139934,MI,PT,Canada,L,Canada,0,"Spark, NLP, Python, Kubernetes, Mathematics",PhD,2,Transportation,2024-10-08,2024-12-08,1637,7.6,Advanced Robotics -AI04852,ML Ops Engineer,149929,SGD,194908,SE,FL,Singapore,L,Singapore,50,"Deep Learning, AWS, Mathematics, GCP, Python",Master,8,Media,2025-04-11,2025-05-06,2130,5.6,AI Innovations -AI04853,AI Product Manager,101866,SGD,132426,MI,FT,Singapore,L,Singapore,0,"SQL, NLP, R",PhD,3,Gaming,2024-04-24,2024-05-19,1461,8.5,Algorithmic Solutions -AI04854,Research Scientist,77165,AUD,104173,MI,PT,Australia,S,Australia,100,"Tableau, Git, Docker, PyTorch, Linux",Master,4,Media,2024-12-02,2025-01-21,1863,7.6,Machine Intelligence Group -AI04855,Computer Vision Engineer,121396,EUR,103187,SE,FL,Germany,M,Canada,50,"Data Visualization, PyTorch, TensorFlow, Statistics, Java",Master,7,Gaming,2024-07-01,2024-07-26,1567,8.8,Advanced Robotics -AI04856,Machine Learning Researcher,136213,USD,136213,SE,FT,Ireland,L,Ireland,50,"Deep Learning, TensorFlow, R, MLOps, Git",Associate,5,Retail,2024-06-23,2024-08-25,2377,8.5,Future Systems -AI04857,AI Architect,145362,USD,145362,SE,CT,Sweden,L,Sweden,50,"R, PyTorch, GCP",Associate,5,Manufacturing,2025-03-11,2025-04-21,939,5.6,Autonomous Tech -AI04858,Head of AI,53624,CAD,67030,EN,FL,Canada,S,Canada,100,"Spark, R, Computer Vision, Data Visualization",PhD,0,Energy,2024-06-02,2024-07-21,2033,6.9,Algorithmic Solutions -AI04859,NLP Engineer,85771,EUR,72905,MI,FT,Austria,L,Austria,0,"Kubernetes, Python, AWS, GCP, Linux",Associate,4,Retail,2024-01-09,2024-03-09,1532,5.3,Quantum Computing Inc -AI04860,Data Analyst,181719,EUR,154461,EX,FT,Germany,L,Germany,0,"Spark, NLP, Data Visualization, Statistics, R",PhD,16,Education,2024-01-20,2024-04-02,820,9,Smart Analytics -AI04861,AI Research Scientist,69580,EUR,59143,MI,PT,Austria,S,Austria,0,"Java, Docker, GCP, Computer Vision, Git",Master,2,Consulting,2025-03-31,2025-06-05,1398,9.3,AI Innovations -AI04862,Data Engineer,132740,EUR,112829,SE,FL,Austria,L,Austria,50,"Kubernetes, AWS, GCP, SQL",Bachelor,7,Gaming,2025-01-29,2025-04-09,1832,6.4,Quantum Computing Inc -AI04863,Principal Data Scientist,130258,CAD,162823,SE,CT,Canada,M,Canada,50,"Data Visualization, Python, TensorFlow",Master,7,Telecommunications,2025-04-28,2025-07-01,1257,6.4,Autonomous Tech -AI04864,Computer Vision Engineer,116709,USD,116709,SE,PT,Israel,S,Russia,50,"SQL, Python, R, AWS, Tableau",PhD,9,Manufacturing,2024-06-23,2024-08-31,1408,6.5,Predictive Systems -AI04865,Research Scientist,80310,EUR,68264,MI,CT,Netherlands,M,Netherlands,0,"SQL, Docker, AWS",Associate,3,Automotive,2024-07-07,2024-09-04,1673,7.5,TechCorp Inc -AI04866,Robotics Engineer,185837,EUR,157961,EX,FL,Austria,M,Austria,100,"Scala, Kubernetes, NLP",Associate,13,Media,2024-05-23,2024-07-09,2427,9.4,Machine Intelligence Group -AI04867,Data Engineer,73290,EUR,62297,EN,CT,Netherlands,M,Netherlands,0,"Java, Mathematics, R",Master,0,Media,2024-12-31,2025-02-03,2265,8.4,Advanced Robotics -AI04868,AI Research Scientist,115082,GBP,86312,MI,PT,United Kingdom,M,United Kingdom,100,"R, MLOps, Git, Linux",Bachelor,2,Finance,2024-12-17,2025-02-06,2229,5.5,Digital Transformation LLC -AI04869,Machine Learning Researcher,239030,AUD,322691,EX,PT,Australia,L,Australia,50,"SQL, TensorFlow, PyTorch, Computer Vision, Mathematics",Associate,11,Automotive,2025-04-09,2025-05-09,1765,6.8,Cloud AI Solutions -AI04870,AI Software Engineer,78991,EUR,67142,MI,CT,Austria,L,Austria,50,"Kubernetes, Java, SQL, Statistics",Bachelor,4,Telecommunications,2025-04-15,2025-05-24,1694,5.1,Predictive Systems -AI04871,Head of AI,174805,USD,174805,EX,PT,Sweden,S,Sweden,100,"Spark, Azure, Scala, Deep Learning",Master,19,Media,2025-01-06,2025-02-01,2055,6.3,DataVision Ltd -AI04872,Machine Learning Researcher,181104,CHF,162994,SE,CT,Switzerland,S,Switzerland,50,"Python, Docker, NLP, AWS, Computer Vision",PhD,9,Consulting,2024-08-23,2024-10-25,2359,7.1,Future Systems -AI04873,AI Architect,115681,USD,115681,SE,PT,Finland,L,Ghana,0,"GCP, Scala, Python",Master,9,Consulting,2024-02-18,2024-04-11,1305,6.7,DeepTech Ventures -AI04874,Robotics Engineer,43208,USD,43208,EN,PT,China,L,China,100,"Scala, Python, Kubernetes, Hadoop",PhD,1,Education,2024-10-29,2025-01-08,2363,5.3,Advanced Robotics -AI04875,AI Specialist,94668,USD,94668,MI,PT,Sweden,S,Sweden,100,"Spark, SQL, Python",Bachelor,4,Manufacturing,2024-12-25,2025-03-06,2189,5.5,Advanced Robotics -AI04876,Principal Data Scientist,88758,EUR,75444,EN,FL,Germany,L,Germany,0,"AWS, Computer Vision, Spark, Java",Master,1,Technology,2024-06-08,2024-07-04,1959,9,Future Systems -AI04877,Data Scientist,107851,EUR,91673,SE,FT,Austria,S,Austria,0,"Statistics, PyTorch, Mathematics",Associate,9,Consulting,2025-02-13,2025-03-24,952,8.1,Predictive Systems -AI04878,Research Scientist,77521,USD,77521,EN,PT,Denmark,L,Japan,0,"Hadoop, Git, Mathematics, Computer Vision",Bachelor,0,Manufacturing,2024-08-27,2024-10-18,1875,6.6,Predictive Systems -AI04879,NLP Engineer,48915,USD,48915,EN,FL,Finland,M,Finland,50,"Kubernetes, Docker, Statistics, Azure, SQL",PhD,0,Transportation,2025-01-15,2025-03-21,2032,8.8,TechCorp Inc -AI04880,AI Specialist,144329,USD,144329,EX,FL,Ireland,S,Ireland,50,"Azure, SQL, TensorFlow, R, Statistics",Master,12,Media,2024-05-03,2024-06-11,1802,9,Algorithmic Solutions -AI04881,Deep Learning Engineer,74868,AUD,101072,MI,CT,Australia,S,Australia,50,"Python, TensorFlow, Java, PyTorch",PhD,4,Retail,2025-04-04,2025-06-11,1782,5.1,Smart Analytics -AI04882,AI Consultant,173810,AUD,234644,SE,PT,Australia,L,Australia,50,"TensorFlow, SQL, Linux, Git",Bachelor,7,Government,2024-03-27,2024-05-04,703,9.5,Advanced Robotics -AI04883,Computer Vision Engineer,119626,USD,119626,SE,CT,Israel,S,Ukraine,50,"Kubernetes, Statistics, Scala",Master,5,Finance,2025-04-29,2025-07-07,1482,7.8,Algorithmic Solutions -AI04884,Head of AI,55331,USD,55331,EN,CT,Finland,S,Finland,50,"Git, Spark, Python",Associate,0,Technology,2024-12-23,2025-03-01,853,6.3,Digital Transformation LLC -AI04885,Research Scientist,126364,EUR,107409,MI,FL,Germany,L,Germany,0,"Statistics, Python, Computer Vision",Master,2,Finance,2024-06-22,2024-08-08,1656,5.6,DeepTech Ventures -AI04886,Autonomous Systems Engineer,193012,USD,193012,EX,PT,Sweden,M,Sweden,50,"Spark, Docker, MLOps, GCP, Kubernetes",PhD,12,Energy,2024-07-03,2024-08-30,1282,8.1,DataVision Ltd -AI04887,Machine Learning Engineer,50277,USD,50277,SE,CT,China,M,China,50,"GCP, Tableau, SQL, Git",PhD,7,Media,2024-07-23,2024-09-01,1771,9.9,AI Innovations -AI04888,Computer Vision Engineer,52691,USD,52691,EN,CT,Sweden,S,Italy,0,"PyTorch, Computer Vision, Tableau, TensorFlow",Bachelor,0,Education,2024-10-17,2024-11-05,1506,6.4,Machine Intelligence Group -AI04889,Head of AI,88745,EUR,75433,MI,CT,Austria,M,Austria,50,"AWS, Spark, Hadoop, Azure, Scala",Master,3,Energy,2025-03-19,2025-05-26,1029,8.9,Predictive Systems -AI04890,AI Research Scientist,69741,EUR,59280,EN,FL,France,M,France,0,"PyTorch, TensorFlow, Kubernetes, NLP, GCP",Bachelor,1,Technology,2024-05-15,2024-07-18,1172,6.8,Autonomous Tech -AI04891,Research Scientist,103812,SGD,134956,SE,PT,Singapore,S,Singapore,50,"GCP, Kubernetes, Docker, Mathematics",Bachelor,7,Energy,2024-06-25,2024-08-14,1953,9.6,Predictive Systems -AI04892,AI Product Manager,110207,USD,110207,EN,PT,Denmark,L,Denmark,0,"PyTorch, Hadoop, Data Visualization, AWS, SQL",PhD,1,Finance,2025-03-17,2025-04-11,1555,6.1,Autonomous Tech -AI04893,Data Engineer,90086,USD,90086,EN,CT,United States,L,United States,50,"Python, Data Visualization, Mathematics, TensorFlow",Master,1,Manufacturing,2024-01-30,2024-03-10,1449,5.4,Digital Transformation LLC -AI04894,Computer Vision Engineer,69149,USD,69149,MI,FT,Finland,M,Kenya,100,"Spark, Python, TensorFlow, GCP",Master,4,Telecommunications,2024-04-12,2024-06-21,1681,7.5,Predictive Systems -AI04895,Robotics Engineer,62098,USD,62098,EX,FL,India,M,India,0,"Deep Learning, MLOps, TensorFlow",Associate,16,Energy,2025-04-13,2025-04-28,2374,8.2,Autonomous Tech -AI04896,AI Research Scientist,58340,EUR,49589,EN,PT,Germany,S,Germany,50,"SQL, MLOps, Tableau, AWS, Azure",PhD,0,Automotive,2024-03-20,2024-05-01,1877,5,Advanced Robotics -AI04897,Machine Learning Researcher,27753,USD,27753,EN,FL,China,M,Chile,0,"SQL, Data Visualization, Python, Kubernetes",PhD,1,Telecommunications,2024-07-30,2024-10-05,853,8.1,DataVision Ltd -AI04898,Data Engineer,94238,EUR,80102,MI,FL,France,L,France,100,"Mathematics, Linux, Azure, Python, TensorFlow",Bachelor,2,Transportation,2024-07-19,2024-08-13,1185,6.9,Algorithmic Solutions -AI04899,AI Research Scientist,90515,USD,90515,SE,CT,South Korea,M,South Korea,0,"Python, TensorFlow, Data Visualization",PhD,6,Media,2024-03-04,2024-05-14,1338,9.1,Autonomous Tech -AI04900,Research Scientist,252088,USD,252088,EX,FL,Ireland,M,Ireland,100,"Mathematics, NLP, Scala, PyTorch, Docker",Master,12,Government,2024-03-11,2024-04-30,1589,7.5,DataVision Ltd -AI04901,Computer Vision Engineer,123498,AUD,166722,EX,FT,Australia,S,Australia,50,"Linux, PyTorch, TensorFlow, Data Visualization, SQL",PhD,19,Media,2025-01-02,2025-01-20,2319,7.5,Smart Analytics -AI04902,Machine Learning Engineer,97399,GBP,73049,SE,PT,United Kingdom,S,United Kingdom,0,"Kubernetes, SQL, R",Bachelor,8,Manufacturing,2024-12-24,2025-01-30,1269,7.4,Cognitive Computing -AI04903,AI Product Manager,122301,SGD,158991,MI,FL,Singapore,L,Singapore,100,"Scala, Python, TensorFlow, AWS",PhD,4,Education,2024-04-04,2024-05-22,2205,7.2,Future Systems -AI04904,Computer Vision Engineer,102239,SGD,132911,MI,PT,Singapore,S,Belgium,50,"Mathematics, Docker, AWS",Associate,4,Manufacturing,2024-07-20,2024-09-28,1780,9,AI Innovations -AI04905,Computer Vision Engineer,194401,JPY,21384110,EX,FL,Japan,S,Nigeria,0,"Java, Python, GCP, AWS",PhD,19,Real Estate,2024-10-12,2024-11-20,2140,5.9,AI Innovations -AI04906,Machine Learning Researcher,88107,USD,88107,EN,PT,Denmark,L,France,50,"Hadoop, Scala, Spark",PhD,0,Technology,2024-07-27,2024-09-15,889,6.7,Autonomous Tech -AI04907,AI Software Engineer,147607,USD,147607,SE,FL,Finland,L,Finland,0,"Python, NLP, GCP, Computer Vision",PhD,7,Automotive,2024-05-24,2024-06-26,2274,8.1,Advanced Robotics -AI04908,AI Product Manager,62399,USD,62399,EN,FT,South Korea,L,South Korea,100,"Python, Data Visualization, R",Master,1,Technology,2025-03-08,2025-05-04,1926,9.4,Machine Intelligence Group -AI04909,AI Consultant,178097,CHF,160287,EX,FL,Switzerland,S,Latvia,50,"Git, PyTorch, Hadoop",PhD,16,Education,2024-03-02,2024-03-22,1043,6.6,Digital Transformation LLC -AI04910,Autonomous Systems Engineer,121196,EUR,103017,SE,FL,Netherlands,S,Netherlands,100,"Docker, Linux, Computer Vision",Master,9,Automotive,2025-03-02,2025-04-27,639,6.4,Quantum Computing Inc -AI04911,ML Ops Engineer,196124,USD,196124,EX,CT,Ireland,L,Ireland,0,"PyTorch, R, AWS",Bachelor,11,Retail,2024-11-14,2024-12-18,1350,5.4,TechCorp Inc -AI04912,Deep Learning Engineer,133436,EUR,113421,EX,FL,Germany,S,United States,100,"Computer Vision, Python, Linux",Bachelor,12,Finance,2024-04-23,2024-06-06,708,5.6,Quantum Computing Inc -AI04913,Research Scientist,63143,JPY,6945730,EN,CT,Japan,S,Japan,0,"Git, Hadoop, Data Visualization, GCP",Bachelor,0,Consulting,2024-01-23,2024-02-09,844,9.7,Future Systems -AI04914,Data Engineer,101308,USD,101308,SE,CT,Finland,M,Finland,100,"SQL, NLP, Statistics, Hadoop",Master,9,Transportation,2024-01-28,2024-03-09,1781,9.5,TechCorp Inc -AI04915,Head of AI,129700,USD,129700,EX,PT,Israel,M,Israel,100,"Mathematics, PyTorch, Computer Vision, Azure, NLP",Bachelor,10,Education,2024-12-07,2025-02-11,819,7.3,Future Systems -AI04916,Data Scientist,82759,GBP,62069,MI,FT,United Kingdom,M,Italy,100,"Azure, Kubernetes, Docker",Associate,3,Technology,2024-09-08,2024-10-17,2024,9,AI Innovations -AI04917,Principal Data Scientist,58384,USD,58384,EN,CT,Sweden,S,Sweden,0,"R, MLOps, Hadoop, Computer Vision",PhD,0,Manufacturing,2024-11-21,2025-01-20,1210,9.6,Predictive Systems -AI04918,NLP Engineer,57840,USD,57840,SE,PT,China,M,China,50,"Kubernetes, PyTorch, Statistics, Docker, Azure",Master,7,Telecommunications,2024-08-17,2024-10-13,1991,5,Machine Intelligence Group -AI04919,AI Architect,67529,USD,67529,EN,FL,Ireland,M,Ireland,0,"Linux, GCP, Mathematics, Deep Learning",PhD,0,Energy,2024-09-27,2024-11-19,1391,5.9,Advanced Robotics -AI04920,Autonomous Systems Engineer,103319,EUR,87821,MI,CT,Netherlands,M,Spain,50,"Kubernetes, Tableau, Java, Computer Vision",Associate,2,Gaming,2024-05-04,2024-06-07,744,6.7,Machine Intelligence Group -AI04921,Data Analyst,264281,USD,264281,EX,FL,Israel,L,Israel,100,"Hadoop, Docker, PyTorch, Spark, Tableau",Associate,16,Healthcare,2024-02-19,2024-03-24,2369,8.6,Quantum Computing Inc -AI04922,Robotics Engineer,90375,USD,90375,EN,FT,Norway,S,Hungary,100,"Statistics, TensorFlow, R, MLOps",PhD,1,Energy,2025-03-11,2025-05-09,2386,9.1,Algorithmic Solutions -AI04923,Machine Learning Researcher,168030,CAD,210038,EX,FT,Canada,L,Canada,100,"GCP, Spark, Deep Learning, TensorFlow, Hadoop",PhD,18,Education,2024-08-02,2024-08-17,1548,9.9,Cognitive Computing -AI04924,AI Architect,144693,USD,144693,SE,CT,United States,S,United States,100,"AWS, Azure, PyTorch",PhD,7,Transportation,2025-01-19,2025-02-28,1380,8.6,Algorithmic Solutions -AI04925,NLP Engineer,169169,EUR,143794,EX,FT,Netherlands,S,Netherlands,100,"Scala, AWS, R",Bachelor,17,Government,2024-10-29,2024-12-16,1867,7.8,Cognitive Computing -AI04926,AI Research Scientist,97205,EUR,82624,MI,PT,Austria,L,Austria,100,"MLOps, Hadoop, Java",Bachelor,2,Automotive,2024-12-04,2025-01-05,1638,8.1,DeepTech Ventures -AI04927,AI Consultant,116462,USD,116462,SE,FL,United States,S,United States,100,"Hadoop, Docker, NLP, Kubernetes, Computer Vision",Master,5,Manufacturing,2024-12-17,2025-02-18,936,9.5,Advanced Robotics -AI04928,AI Research Scientist,161251,USD,161251,EX,CT,United States,S,United States,0,"Tableau, Statistics, TensorFlow, Data Visualization, AWS",Associate,13,Transportation,2024-11-04,2025-01-12,2473,10,Cognitive Computing -AI04929,AI Software Engineer,127524,USD,127524,SE,FL,Sweden,M,Sweden,50,"Deep Learning, SQL, MLOps",Bachelor,8,Gaming,2024-11-25,2025-01-10,845,5.6,TechCorp Inc -AI04930,Autonomous Systems Engineer,40391,USD,40391,MI,CT,India,L,Czech Republic,100,"AWS, PyTorch, Linux, Mathematics, Data Visualization",Master,4,Energy,2024-02-05,2024-04-02,1473,9.8,Neural Networks Co -AI04931,Data Engineer,125657,USD,125657,SE,FT,Finland,S,Hungary,50,"Python, Azure, SQL",PhD,9,Automotive,2024-03-11,2024-03-30,1378,9,Neural Networks Co -AI04932,Computer Vision Engineer,220521,GBP,165391,EX,FL,United Kingdom,S,Poland,100,"AWS, Python, TensorFlow, Statistics",PhD,15,Finance,2024-03-01,2024-04-05,1224,7.4,Autonomous Tech -AI04933,AI Software Engineer,75300,GBP,56475,EN,FL,United Kingdom,S,United Kingdom,50,"GCP, R, Mathematics, Hadoop",Bachelor,0,Real Estate,2025-02-13,2025-04-27,1543,7.5,Machine Intelligence Group -AI04934,Data Analyst,89549,USD,89549,MI,PT,Ireland,L,Vietnam,100,"PyTorch, TensorFlow, Mathematics, Docker",Master,3,Consulting,2025-02-01,2025-04-03,1192,6.1,Cognitive Computing -AI04935,AI Research Scientist,230750,GBP,173063,EX,FL,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Git",Master,18,Retail,2024-07-26,2024-08-25,828,5.6,TechCorp Inc -AI04936,Computer Vision Engineer,43742,USD,43742,MI,CT,China,M,China,100,"Kubernetes, GCP, Scala",PhD,4,Finance,2024-02-28,2024-04-03,568,8.1,Advanced Robotics -AI04937,Machine Learning Engineer,73505,USD,73505,EN,FT,Ireland,L,Israel,100,"Kubernetes, GCP, SQL, Azure",Master,1,Energy,2025-02-15,2025-04-19,1617,8.5,AI Innovations -AI04938,ML Ops Engineer,93032,USD,93032,MI,CT,Israel,S,Ireland,100,"SQL, R, Tableau",Bachelor,2,Real Estate,2024-09-23,2024-11-05,697,8.4,Smart Analytics -AI04939,Machine Learning Researcher,310945,CHF,279851,EX,FL,Switzerland,S,Poland,0,"Kubernetes, Scala, Azure",Bachelor,18,Retail,2024-09-03,2024-10-20,1636,7.5,Smart Analytics -AI04940,Principal Data Scientist,91705,USD,91705,MI,FL,Israel,S,Israel,0,"Computer Vision, Kubernetes, GCP, R",PhD,2,Gaming,2024-05-31,2024-08-09,1029,9.7,Cloud AI Solutions -AI04941,AI Consultant,84567,USD,84567,EN,FL,Norway,L,Norway,50,"R, SQL, Azure, Deep Learning, Linux",Associate,0,Education,2024-04-16,2024-06-03,1320,9.6,Digital Transformation LLC -AI04942,AI Architect,77592,EUR,65953,EN,FT,Austria,L,Vietnam,100,"Docker, Hadoop, Tableau",Master,1,Automotive,2024-07-22,2024-09-16,1129,8.7,DeepTech Ventures -AI04943,Head of AI,106660,USD,106660,SE,FL,Sweden,M,Chile,100,"MLOps, Statistics, AWS, NLP, Computer Vision",Associate,9,Retail,2024-06-15,2024-07-05,1054,9.8,AI Innovations -AI04944,Data Engineer,46462,USD,46462,MI,PT,China,L,China,100,"Kubernetes, Git, Statistics",Bachelor,3,Consulting,2024-12-02,2025-01-04,2365,6.6,Neural Networks Co -AI04945,Autonomous Systems Engineer,131368,GBP,98526,SE,PT,United Kingdom,M,Luxembourg,50,"Git, Azure, GCP, Python, AWS",Bachelor,9,Manufacturing,2024-08-10,2024-10-13,503,5,Cognitive Computing -AI04946,Data Scientist,78787,USD,78787,MI,PT,South Korea,S,South Korea,50,"Kubernetes, PyTorch, MLOps, SQL",Master,3,Retail,2024-11-25,2025-01-12,1588,6.4,Cloud AI Solutions -AI04947,ML Ops Engineer,57111,USD,57111,EN,PT,Sweden,M,Sweden,100,"Java, Azure, PyTorch, Scala",Master,1,Automotive,2025-02-24,2025-04-26,931,9,Quantum Computing Inc -AI04948,Deep Learning Engineer,70529,USD,70529,EN,FL,United States,L,United States,100,"Computer Vision, R, SQL",Master,0,Retail,2024-09-17,2024-11-05,1367,8.8,Cognitive Computing -AI04949,Principal Data Scientist,166422,USD,166422,SE,FT,Ireland,L,United States,100,"Spark, Tableau, R, SQL",PhD,6,Transportation,2024-07-20,2024-09-25,1832,5.5,Future Systems -AI04950,Deep Learning Engineer,132627,JPY,14588970,SE,CT,Japan,S,Japan,100,"R, Kubernetes, Python",Bachelor,9,Finance,2025-03-22,2025-05-06,2345,9.9,Advanced Robotics -AI04951,AI Product Manager,79266,USD,79266,EN,PT,Ireland,M,Ireland,0,"Statistics, Kubernetes, Computer Vision, Python, Git",PhD,0,Automotive,2025-04-29,2025-05-15,1442,6.4,AI Innovations -AI04952,Data Analyst,159779,EUR,135812,EX,CT,Germany,L,Portugal,50,"Azure, Python, Docker, Hadoop, Linux",PhD,12,Government,2024-10-14,2024-11-18,975,7.5,Digital Transformation LLC -AI04953,Principal Data Scientist,139290,USD,139290,SE,CT,United States,S,United States,0,"Tableau, SQL, Scala, Computer Vision, Java",Master,8,Education,2024-10-16,2024-11-17,1978,7.6,AI Innovations -AI04954,Robotics Engineer,231125,CHF,208013,EX,CT,Switzerland,S,Romania,100,"SQL, NLP, Tableau",Master,16,Healthcare,2024-05-05,2024-05-26,1244,9.1,Predictive Systems -AI04955,AI Architect,122595,GBP,91946,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Kubernetes, Scala, Deep Learning",Master,3,Energy,2024-09-02,2024-11-04,2102,8,Algorithmic Solutions -AI04956,Data Analyst,68427,USD,68427,EN,CT,Ireland,S,Ireland,0,"AWS, Linux, SQL",Bachelor,1,Retail,2024-07-20,2024-09-11,1893,6.4,Cognitive Computing -AI04957,Head of AI,202722,USD,202722,EX,FL,Finland,L,Finland,100,"AWS, Git, Python, Deep Learning, Spark",Bachelor,16,Healthcare,2024-06-27,2024-08-21,1923,6.2,Neural Networks Co -AI04958,Data Scientist,108147,EUR,91925,SE,FT,Austria,M,Latvia,50,"Data Visualization, PyTorch, MLOps",PhD,7,Finance,2024-09-26,2024-11-15,626,8.1,Machine Intelligence Group -AI04959,ML Ops Engineer,115437,AUD,155840,SE,FT,Australia,S,Australia,100,"TensorFlow, Hadoop, Mathematics, SQL",Master,6,Automotive,2024-12-13,2025-02-08,1204,9.8,Predictive Systems -AI04960,Head of AI,77217,GBP,57913,MI,PT,United Kingdom,S,United Kingdom,50,"Hadoop, Java, SQL, AWS",Bachelor,4,Finance,2024-10-16,2024-11-02,1484,9.7,DeepTech Ventures -AI04961,AI Software Engineer,57529,USD,57529,EN,CT,Israel,L,Kenya,100,"MLOps, TensorFlow, Kubernetes, Data Visualization",PhD,1,Manufacturing,2024-03-15,2024-03-29,928,8.4,Smart Analytics -AI04962,Principal Data Scientist,113427,EUR,96413,MI,PT,France,L,France,100,"SQL, Data Visualization, TensorFlow, Scala, R",Bachelor,4,Transportation,2024-01-13,2024-03-10,794,6.3,TechCorp Inc -AI04963,Autonomous Systems Engineer,71693,USD,71693,EN,PT,Denmark,M,Denmark,50,"Python, Deep Learning, Mathematics, PyTorch, AWS",PhD,0,Gaming,2024-06-08,2024-07-27,2047,7.3,Digital Transformation LLC -AI04964,ML Ops Engineer,151134,EUR,128464,SE,CT,Germany,M,Germany,0,"PyTorch, Git, TensorFlow",PhD,9,Healthcare,2024-12-05,2025-01-31,1045,9.7,DataVision Ltd -AI04965,AI Product Manager,135496,EUR,115172,EX,CT,France,M,France,0,"GCP, Data Visualization, Scala, Git",PhD,18,Consulting,2024-01-23,2024-02-15,938,7.3,Future Systems -AI04966,NLP Engineer,93530,USD,93530,EX,CT,India,L,India,100,"R, Tableau, Data Visualization, Python, PyTorch",Associate,10,Finance,2024-07-13,2024-08-22,1866,8.2,TechCorp Inc -AI04967,AI Research Scientist,194766,JPY,21424260,EX,PT,Japan,L,Japan,50,"Kubernetes, Spark, PyTorch, TensorFlow",PhD,17,Government,2024-02-20,2024-04-03,1832,7,Smart Analytics -AI04968,Data Engineer,214036,JPY,23543960,EX,PT,Japan,M,Netherlands,0,"Deep Learning, SQL, Spark",Associate,15,Healthcare,2025-02-27,2025-04-29,2309,5.8,Neural Networks Co -AI04969,AI Consultant,33244,USD,33244,EN,CT,China,M,China,50,"Deep Learning, Scala, Tableau, Computer Vision",Associate,0,Gaming,2024-08-03,2024-09-29,1665,7.8,Algorithmic Solutions -AI04970,AI Specialist,133388,USD,133388,SE,FL,Denmark,M,Denmark,100,"Computer Vision, Hadoop, Tableau, TensorFlow, Python",Bachelor,6,Telecommunications,2024-02-10,2024-03-09,623,8.1,Algorithmic Solutions -AI04971,Research Scientist,44185,USD,44185,EN,FT,Israel,S,New Zealand,0,"AWS, Scala, Mathematics, TensorFlow, Hadoop",Master,1,Technology,2024-10-07,2024-12-01,781,5.7,Future Systems -AI04972,AI Architect,89882,EUR,76400,SE,CT,Austria,S,Malaysia,50,"AWS, Azure, GCP, Statistics",Master,8,Healthcare,2024-05-14,2024-07-11,1075,8,Smart Analytics -AI04973,Data Engineer,167159,GBP,125369,EX,PT,United Kingdom,L,United Kingdom,100,"Computer Vision, Git, AWS",Associate,10,Telecommunications,2024-12-05,2025-01-08,1609,7.3,Advanced Robotics -AI04974,Autonomous Systems Engineer,110919,USD,110919,SE,FT,South Korea,M,Australia,50,"Scala, Mathematics, Deep Learning, Computer Vision",Associate,9,Technology,2024-08-09,2024-09-17,1747,6.7,Future Systems -AI04975,AI Consultant,153715,USD,153715,SE,FT,Israel,L,Turkey,0,"MLOps, Linux, Kubernetes",Associate,7,Energy,2024-12-09,2025-01-07,2330,6.8,Quantum Computing Inc -AI04976,AI Consultant,132249,USD,132249,SE,CT,Sweden,M,Ireland,50,"Kubernetes, Git, Spark",Associate,6,Retail,2024-06-21,2024-08-01,690,5.4,Smart Analytics -AI04977,NLP Engineer,231132,USD,231132,EX,FT,Denmark,S,Denmark,0,"Python, Git, Docker, Hadoop, Statistics",Bachelor,14,Media,2024-10-18,2024-12-24,1890,6.3,Neural Networks Co -AI04978,AI Consultant,85300,EUR,72505,EN,CT,France,L,France,50,"Java, Data Visualization, PyTorch, AWS",Associate,0,Energy,2024-04-24,2024-05-21,1221,6.4,Machine Intelligence Group -AI04979,AI Product Manager,128111,USD,128111,EX,CT,Sweden,S,Mexico,100,"Java, R, Computer Vision, Statistics, Kubernetes",Associate,15,Education,2025-03-22,2025-05-06,1631,7.6,Future Systems -AI04980,AI Architect,61852,SGD,80408,EN,FT,Singapore,S,Canada,50,"MLOps, SQL, Git, PyTorch",Bachelor,1,Energy,2024-09-11,2024-09-27,2061,5.6,DataVision Ltd -AI04981,Data Scientist,59300,USD,59300,EN,FL,Israel,S,Sweden,0,"PyTorch, Spark, Tableau, MLOps, SQL",Associate,0,Energy,2024-01-08,2024-03-18,1348,9.3,Machine Intelligence Group -AI04982,Machine Learning Researcher,126739,SGD,164761,SE,PT,Singapore,S,Singapore,50,"Git, TensorFlow, SQL",Associate,5,Media,2024-11-29,2025-01-31,554,8.3,Machine Intelligence Group -AI04983,Computer Vision Engineer,80800,USD,80800,EN,CT,Denmark,M,Denmark,50,"Python, Kubernetes, NLP, Statistics",Associate,0,Gaming,2024-03-25,2024-04-28,594,6,Quantum Computing Inc -AI04984,NLP Engineer,85451,AUD,115359,MI,FT,Australia,S,Luxembourg,50,"Kubernetes, Linux, Python",Bachelor,3,Government,2024-06-02,2024-08-05,2249,7.8,DeepTech Ventures -AI04985,AI Product Manager,82153,USD,82153,EN,CT,United States,M,Estonia,50,"Hadoop, TensorFlow, AWS",Associate,0,Telecommunications,2024-03-14,2024-05-17,927,6,DataVision Ltd -AI04986,Machine Learning Researcher,79663,USD,79663,MI,FL,Ireland,S,Ireland,100,"Java, R, MLOps, SQL, Statistics",Associate,2,Energy,2024-08-06,2024-08-21,1985,7.7,Future Systems -AI04987,Robotics Engineer,141209,EUR,120028,SE,PT,Austria,L,Austria,0,"Hadoop, Linux, PyTorch, Java, Mathematics",Master,8,Energy,2025-04-24,2025-05-10,2143,7.8,TechCorp Inc -AI04988,Machine Learning Researcher,47558,USD,47558,EX,FT,India,S,India,0,"NLP, Tableau, Spark, TensorFlow, Statistics",Bachelor,12,Healthcare,2024-02-03,2024-04-05,1793,9,Predictive Systems -AI04989,Machine Learning Researcher,134887,USD,134887,MI,FT,Denmark,L,Denmark,100,"Data Visualization, Scala, Java, R, Computer Vision",PhD,2,Government,2025-03-13,2025-04-23,2069,9.1,Machine Intelligence Group -AI04990,AI Research Scientist,216990,USD,216990,EX,PT,Finland,M,Finland,50,"Hadoop, SQL, Computer Vision, Scala",Master,19,Technology,2024-04-13,2024-05-19,2371,5.6,TechCorp Inc -AI04991,Machine Learning Engineer,270223,EUR,229690,EX,CT,France,L,France,50,"Linux, Python, Deep Learning, Hadoop",Associate,15,Consulting,2024-02-25,2024-05-08,820,8.2,Digital Transformation LLC -AI04992,AI Product Manager,123617,USD,123617,SE,PT,Sweden,S,Indonesia,50,"Python, Hadoop, TensorFlow, PyTorch",Bachelor,8,Technology,2024-11-14,2024-12-13,1367,9,Advanced Robotics -AI04993,Deep Learning Engineer,179200,CHF,161280,SE,CT,Switzerland,M,Switzerland,50,"Python, Linux, Git, R, TensorFlow",Master,6,Media,2024-10-31,2025-01-02,654,9.1,Quantum Computing Inc -AI04994,Robotics Engineer,123515,USD,123515,SE,FL,Finland,M,Finland,0,"Spark, Kubernetes, Scala, Mathematics, Linux",Master,5,Retail,2025-03-29,2025-05-08,736,9.6,Cloud AI Solutions -AI04995,AI Research Scientist,101862,AUD,137514,MI,PT,Australia,L,Ukraine,100,"Git, Python, Computer Vision, TensorFlow, PyTorch",Associate,3,Transportation,2024-04-13,2024-05-22,1831,5.3,Predictive Systems -AI04996,AI Consultant,183450,USD,183450,EX,PT,United States,S,United States,50,"GCP, Computer Vision, SQL",Bachelor,17,Government,2024-06-17,2024-07-12,902,6.3,Neural Networks Co -AI04997,Machine Learning Engineer,81041,SGD,105353,EN,PT,Singapore,L,Singapore,0,"MLOps, PyTorch, Python, TensorFlow",Associate,1,Finance,2024-06-29,2024-08-16,1494,9.3,Autonomous Tech -AI04998,AI Software Engineer,80467,USD,80467,EX,PT,India,S,India,0,"Mathematics, Linux, Git, PyTorch",Master,14,Manufacturing,2024-11-22,2024-12-25,2205,6.8,Predictive Systems -AI04999,AI Software Engineer,88669,AUD,119703,MI,CT,Australia,L,Australia,100,"Python, Hadoop, MLOps",Master,3,Real Estate,2024-05-30,2024-08-10,1427,5.5,DataVision Ltd -AI05000,Machine Learning Researcher,113313,USD,113313,MI,FT,Sweden,L,Sweden,100,"Scala, SQL, PyTorch, R",PhD,3,Education,2024-09-27,2024-11-25,1895,9.5,Digital Transformation LLC -AI05001,Research Scientist,306192,USD,306192,EX,FT,Denmark,L,Denmark,0,"PyTorch, Azure, Tableau, Scala",PhD,11,Automotive,2025-02-25,2025-03-20,2405,5.5,Smart Analytics -AI05002,Head of AI,190624,USD,190624,EX,CT,Denmark,S,Denmark,50,"Kubernetes, Tableau, Python, Hadoop",Bachelor,15,Automotive,2024-10-22,2024-12-06,1947,7.2,Cloud AI Solutions -AI05003,NLP Engineer,68152,SGD,88598,EN,FT,Singapore,L,Egypt,0,"R, Azure, Kubernetes, Linux",PhD,0,Telecommunications,2024-03-20,2024-05-06,1227,9.1,Algorithmic Solutions -AI05004,Principal Data Scientist,91590,USD,91590,EN,CT,United States,L,Kenya,0,"PyTorch, SQL, Kubernetes, Java, AWS",Associate,1,Media,2024-06-27,2024-07-19,578,6.6,Autonomous Tech -AI05005,AI Research Scientist,50730,EUR,43121,EN,FT,Netherlands,S,Netherlands,0,"R, Java, Data Visualization, NLP",PhD,1,Real Estate,2024-04-28,2024-05-15,1020,5.7,TechCorp Inc -AI05006,Robotics Engineer,57915,GBP,43436,EN,FL,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, AWS, Mathematics, Git",Associate,0,Finance,2025-03-02,2025-04-20,2451,8.9,Future Systems -AI05007,AI Architect,74536,AUD,100624,MI,FL,Australia,S,Turkey,0,"Kubernetes, Docker, Data Visualization",PhD,2,Retail,2025-02-19,2025-04-26,1612,9.3,Predictive Systems -AI05008,Data Engineer,179315,USD,179315,SE,FL,Denmark,L,Denmark,0,"Python, TensorFlow, Linux, PyTorch",PhD,8,Education,2024-09-14,2024-10-29,925,5.3,Digital Transformation LLC -AI05009,ML Ops Engineer,19776,USD,19776,EN,FT,India,M,Japan,50,"Docker, Scala, GCP, MLOps",Bachelor,0,Consulting,2024-07-30,2024-09-17,604,8.3,DataVision Ltd -AI05010,Data Analyst,73489,EUR,62466,EN,CT,Netherlands,S,Ireland,0,"Computer Vision, Tableau, Linux, Git, Deep Learning",Master,0,Education,2024-11-23,2025-01-04,1966,9.7,DeepTech Ventures -AI05011,AI Product Manager,67007,JPY,7370770,EN,CT,Japan,S,Japan,100,"SQL, TensorFlow, Data Visualization, NLP, Linux",Bachelor,1,Finance,2024-10-18,2024-12-25,1765,8.2,Advanced Robotics -AI05012,Machine Learning Engineer,26216,USD,26216,EN,PT,China,M,China,50,"Hadoop, Data Visualization, Python, Statistics, Mathematics",Associate,1,Gaming,2024-08-16,2024-10-25,2458,6.5,Cognitive Computing -AI05013,ML Ops Engineer,80593,CAD,100741,MI,CT,Canada,L,Canada,100,"Hadoop, SQL, Java",Associate,3,Government,2024-06-09,2024-07-02,714,5.3,Machine Intelligence Group -AI05014,Principal Data Scientist,251940,AUD,340119,EX,FL,Australia,L,Australia,50,"NLP, R, Statistics, SQL, Data Visualization",Master,12,Manufacturing,2025-01-01,2025-01-21,2150,7.3,Advanced Robotics -AI05015,Data Scientist,271778,USD,271778,EX,FT,Ireland,L,Ukraine,0,"AWS, Linux, Python, TensorFlow, Computer Vision",Bachelor,17,Automotive,2024-05-06,2024-06-18,1477,8.3,Algorithmic Solutions -AI05016,AI Research Scientist,136680,EUR,116178,SE,FT,Austria,M,Austria,100,"Linux, Scala, Mathematics, Hadoop, Java",Associate,7,Energy,2024-06-27,2024-07-24,1821,6.7,Digital Transformation LLC -AI05017,AI Architect,90736,USD,90736,MI,CT,South Korea,M,Colombia,50,"Data Visualization, Git, R",Bachelor,3,Finance,2025-02-04,2025-03-18,1998,7.6,Future Systems -AI05018,Machine Learning Engineer,176612,USD,176612,EX,FT,Norway,M,Norway,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,12,Real Estate,2025-01-06,2025-01-23,1705,9.6,Digital Transformation LLC -AI05019,NLP Engineer,86142,USD,86142,SE,PT,South Korea,M,Czech Republic,100,"Computer Vision, NLP, Tableau, Data Visualization, MLOps",Master,6,Technology,2024-05-29,2024-07-19,2196,5.1,Advanced Robotics -AI05020,AI Research Scientist,71454,SGD,92890,MI,PT,Singapore,S,Singapore,100,"Scala, Linux, Data Visualization",Bachelor,4,Gaming,2024-02-21,2024-03-23,1063,6.1,Advanced Robotics -AI05021,AI Software Engineer,70698,USD,70698,EN,FT,Norway,S,Norway,100,"TensorFlow, Data Visualization, SQL, Hadoop, R",PhD,0,Real Estate,2024-08-07,2024-10-12,515,9.9,Algorithmic Solutions -AI05022,Computer Vision Engineer,70125,EUR,59606,EN,CT,Germany,M,United States,0,"TensorFlow, Tableau, GCP, Spark, Linux",Associate,0,Manufacturing,2025-04-14,2025-06-25,525,7.9,Machine Intelligence Group -AI05023,AI Specialist,164581,AUD,222184,EX,CT,Australia,S,Australia,100,"Tableau, Linux, PyTorch, TensorFlow, Computer Vision",Bachelor,11,Automotive,2025-02-04,2025-03-02,1128,9.7,TechCorp Inc -AI05024,NLP Engineer,125674,GBP,94256,SE,FL,United Kingdom,L,United Kingdom,100,"Computer Vision, MLOps, Git",Bachelor,6,Media,2024-08-16,2024-10-22,1388,8.8,Quantum Computing Inc -AI05025,Robotics Engineer,108470,CHF,97623,EN,FL,Switzerland,L,Switzerland,100,"Spark, Tableau, Docker, Deep Learning, NLP",Master,1,Telecommunications,2024-04-30,2024-07-10,1708,6.5,Quantum Computing Inc -AI05026,AI Architect,68849,USD,68849,EN,PT,United States,S,United States,0,"PyTorch, AWS, Computer Vision",Associate,0,Healthcare,2024-04-12,2024-06-09,1204,10,TechCorp Inc -AI05027,Autonomous Systems Engineer,101825,JPY,11200750,SE,CT,Japan,S,Japan,50,"MLOps, Java, Data Visualization, Linux, Scala",Bachelor,8,Real Estate,2025-02-27,2025-04-05,960,9.7,Future Systems -AI05028,Deep Learning Engineer,351728,USD,351728,EX,CT,Norway,L,Norway,0,"Tableau, Spark, Python, SQL",Bachelor,17,Real Estate,2024-09-22,2024-10-13,1508,5.3,Quantum Computing Inc -AI05029,Machine Learning Researcher,97819,USD,97819,SE,FL,Ireland,S,Ireland,0,"Deep Learning, Git, GCP, Linux",Bachelor,9,Retail,2024-08-28,2024-09-14,1494,7.2,AI Innovations -AI05030,Data Scientist,163331,USD,163331,SE,FL,United States,M,United States,50,"TensorFlow, Git, Data Visualization, Kubernetes",Master,6,Healthcare,2025-04-29,2025-05-21,1419,9.5,Advanced Robotics -AI05031,Head of AI,93720,USD,93720,MI,CT,United States,M,United States,100,"Linux, Spark, SQL, PyTorch",PhD,4,Government,2024-12-19,2025-01-19,1659,9.1,Machine Intelligence Group -AI05032,NLP Engineer,108820,EUR,92497,MI,PT,Netherlands,M,Netherlands,50,"Kubernetes, Computer Vision, R, GCP, Hadoop",Master,2,Gaming,2024-12-14,2025-02-09,2389,9.4,AI Innovations -AI05033,AI Consultant,23491,USD,23491,EN,FL,India,S,India,0,"R, PyTorch, TensorFlow, Statistics",Bachelor,0,Healthcare,2024-02-07,2024-03-31,1921,7,TechCorp Inc -AI05034,Robotics Engineer,38464,USD,38464,SE,CT,India,M,Israel,100,"Python, TensorFlow, Statistics, PyTorch, Mathematics",PhD,6,Real Estate,2024-09-16,2024-10-17,1319,6.5,TechCorp Inc -AI05035,Data Analyst,121725,USD,121725,SE,PT,South Korea,M,South Korea,0,"Linux, TensorFlow, MLOps, Git, NLP",Bachelor,5,Government,2024-11-20,2024-12-23,1624,7.8,TechCorp Inc -AI05036,Computer Vision Engineer,121877,CHF,109689,MI,CT,Switzerland,L,Switzerland,0,"Python, Git, Deep Learning, Data Visualization",Bachelor,3,Finance,2024-03-21,2024-06-01,1183,6.6,Future Systems -AI05037,Machine Learning Researcher,96000,USD,96000,EN,CT,Norway,M,Norway,50,"Scala, Deep Learning, Computer Vision, GCP, Git",Bachelor,0,Retail,2024-01-27,2024-02-24,1635,8,Advanced Robotics -AI05038,Robotics Engineer,46573,USD,46573,SE,FT,China,S,China,100,"AWS, Linux, PyTorch, GCP",PhD,9,Government,2024-03-22,2024-05-09,830,9.9,Predictive Systems -AI05039,AI Architect,203167,EUR,172692,EX,CT,Austria,M,Austria,50,"SQL, PyTorch, Java, Hadoop",Associate,17,Education,2024-09-14,2024-10-09,865,9.6,DeepTech Ventures -AI05040,Data Scientist,177459,CHF,159713,SE,CT,Switzerland,S,Switzerland,50,"Spark, R, Hadoop, Linux, Mathematics",Bachelor,6,Telecommunications,2024-09-15,2024-10-29,740,9.4,Future Systems -AI05041,Machine Learning Engineer,41556,USD,41556,MI,FT,China,S,China,50,"Python, TensorFlow, Azure, Kubernetes",Associate,3,Gaming,2024-01-04,2024-03-05,1652,6.1,Quantum Computing Inc -AI05042,Data Scientist,152796,USD,152796,EX,PT,Sweden,M,Sweden,100,"Linux, Hadoop, Python",Master,10,Automotive,2025-02-17,2025-04-09,2123,8.4,Cognitive Computing -AI05043,Robotics Engineer,70161,JPY,7717710,EN,PT,Japan,L,Japan,0,"Spark, PyTorch, GCP, Scala, Statistics",PhD,0,Manufacturing,2024-01-18,2024-02-05,1333,6.3,DataVision Ltd -AI05044,ML Ops Engineer,66092,CAD,82615,EN,PT,Canada,S,Sweden,100,"SQL, Scala, NLP",PhD,1,Transportation,2024-03-07,2024-03-31,2308,5.6,Future Systems -AI05045,Data Engineer,271475,SGD,352918,EX,FL,Singapore,L,Singapore,0,"Git, Docker, Hadoop",Associate,10,Media,2024-08-25,2024-10-08,1142,7.1,DataVision Ltd -AI05046,AI Architect,71751,JPY,7892610,EN,CT,Japan,L,Japan,0,"Java, MLOps, Git, Computer Vision, Kubernetes",Associate,1,Real Estate,2024-08-08,2024-09-24,1649,8.1,DeepTech Ventures -AI05047,Research Scientist,91975,USD,91975,EX,PT,China,S,China,0,"Azure, Docker, Mathematics, Statistics, GCP",Bachelor,10,Technology,2024-03-28,2024-05-08,735,8.1,Autonomous Tech -AI05048,Machine Learning Researcher,139317,EUR,118419,SE,FL,France,M,France,100,"Python, Kubernetes, Data Visualization",Bachelor,9,Consulting,2024-09-02,2024-10-04,2142,7.9,Future Systems -AI05049,Machine Learning Researcher,56279,EUR,47837,EN,CT,Netherlands,S,Indonesia,0,"Docker, Python, Data Visualization, Deep Learning",Bachelor,1,Technology,2024-05-07,2024-07-06,2433,7.6,Cloud AI Solutions -AI05050,Head of AI,212031,AUD,286242,EX,PT,Australia,M,Australia,100,"AWS, Statistics, Git, SQL",Associate,15,Gaming,2025-03-10,2025-04-16,1142,7.9,Autonomous Tech -AI05051,AI Research Scientist,261631,AUD,353202,EX,FT,Australia,L,New Zealand,50,"Computer Vision, NLP, GCP",Associate,10,Technology,2024-07-31,2024-08-18,982,6.6,Cognitive Computing -AI05052,Machine Learning Researcher,41755,USD,41755,MI,FL,China,M,China,100,"NLP, SQL, TensorFlow, Linux, Computer Vision",Associate,4,Gaming,2024-10-21,2024-11-30,1171,7.6,Advanced Robotics -AI05053,Computer Vision Engineer,78608,EUR,66817,EN,PT,Netherlands,M,Malaysia,50,"Data Visualization, Scala, Java, Computer Vision, Tableau",PhD,0,Energy,2025-01-20,2025-03-10,642,9.9,Digital Transformation LLC -AI05054,Head of AI,37889,USD,37889,SE,FT,India,M,India,100,"Scala, Deep Learning, MLOps, Python",Associate,8,Retail,2024-02-19,2024-04-03,856,8.9,DataVision Ltd -AI05055,Data Scientist,97397,USD,97397,EN,CT,United States,L,Brazil,50,"Git, Deep Learning, TensorFlow",PhD,1,Finance,2025-04-02,2025-05-05,1562,9.5,Cognitive Computing -AI05056,Data Analyst,265023,USD,265023,EX,CT,Denmark,S,Spain,50,"Git, Docker, Statistics",Master,16,Manufacturing,2024-12-15,2025-01-12,1294,7.7,DataVision Ltd -AI05057,Machine Learning Researcher,143323,AUD,193486,SE,FL,Australia,M,Australia,0,"Tableau, Java, Git",Bachelor,5,Energy,2024-10-31,2025-01-06,729,7,Machine Intelligence Group -AI05058,Head of AI,97000,EUR,82450,SE,CT,France,M,France,0,"Java, SQL, Python, Docker",Associate,5,Technology,2024-01-10,2024-02-03,2147,6.5,Neural Networks Co -AI05059,AI Software Engineer,46374,USD,46374,EN,CT,Ireland,S,United States,100,"PyTorch, Kubernetes, Docker",Bachelor,1,Telecommunications,2024-07-03,2024-09-10,2065,8.9,Smart Analytics -AI05060,AI Architect,229381,EUR,194974,EX,CT,France,M,France,50,"Python, TensorFlow, Scala",PhD,19,Technology,2024-10-01,2024-10-23,1365,9,Digital Transformation LLC -AI05061,Computer Vision Engineer,158873,JPY,17476030,SE,FL,Japan,M,Japan,50,"GCP, Java, Azure",Bachelor,6,Education,2024-06-07,2024-07-04,2166,9.1,Future Systems -AI05062,Machine Learning Engineer,69868,USD,69868,EN,PT,Norway,M,India,50,"Kubernetes, AWS, GCP",Associate,0,Education,2024-02-23,2024-03-26,1959,7.7,DeepTech Ventures -AI05063,AI Specialist,101000,CHF,90900,EN,PT,Switzerland,S,Switzerland,0,"PyTorch, TensorFlow, Python, Git",Bachelor,0,Consulting,2024-12-31,2025-02-13,2181,5.7,Digital Transformation LLC -AI05064,Data Engineer,81849,SGD,106404,EN,CT,Singapore,M,Singapore,100,"NLP, PyTorch, Statistics, Hadoop",PhD,1,Automotive,2024-07-21,2024-09-24,1881,7.7,Smart Analytics -AI05065,AI Architect,134380,GBP,100785,SE,CT,United Kingdom,L,United Kingdom,100,"Git, Azure, Statistics, NLP",PhD,5,Telecommunications,2025-03-04,2025-04-12,2293,5.6,TechCorp Inc -AI05066,Data Scientist,167829,CHF,151046,SE,PT,Switzerland,M,Switzerland,50,"Hadoop, PyTorch, Git, Data Visualization, Docker",Master,7,Government,2024-06-17,2024-08-09,1514,6.7,AI Innovations -AI05067,Machine Learning Engineer,24678,USD,24678,EN,PT,China,S,China,0,"Python, SQL, PyTorch",Master,0,Healthcare,2024-03-22,2024-04-05,1955,9,Predictive Systems -AI05068,Autonomous Systems Engineer,54248,SGD,70522,EN,CT,Singapore,S,Singapore,50,"Scala, Docker, MLOps, AWS, SQL",Bachelor,0,Technology,2024-10-14,2024-12-06,1096,5.5,DeepTech Ventures -AI05069,Head of AI,99288,EUR,84395,SE,CT,Austria,S,Austria,100,"Kubernetes, Spark, AWS",PhD,6,Healthcare,2024-04-04,2024-05-22,2422,7.6,Machine Intelligence Group -AI05070,AI Product Manager,189688,USD,189688,EX,FL,United States,S,United States,100,"Scala, TensorFlow, Mathematics, NLP, Linux",Master,11,Consulting,2024-06-01,2024-06-27,1807,9.8,Smart Analytics -AI05071,Machine Learning Engineer,89528,JPY,9848080,MI,CT,Japan,M,Russia,50,"SQL, Python, Tableau, Java, Docker",Bachelor,3,Government,2024-05-19,2024-06-26,1088,5.4,Advanced Robotics -AI05072,AI Consultant,88720,USD,88720,MI,FT,United States,S,United States,0,"Statistics, Python, TensorFlow, PyTorch, Hadoop",PhD,3,Finance,2025-04-27,2025-07-03,2198,5.6,Algorithmic Solutions -AI05073,NLP Engineer,72059,USD,72059,EN,FT,Sweden,S,Sweden,50,"Git, Scala, Tableau, Computer Vision",Associate,0,Technology,2024-04-26,2024-05-15,2043,8,Predictive Systems -AI05074,Machine Learning Researcher,50803,EUR,43183,EN,PT,France,S,France,0,"TensorFlow, Git, Statistics, SQL",Master,0,Finance,2024-02-18,2024-04-15,1539,9.3,Cloud AI Solutions -AI05075,AI Consultant,24223,USD,24223,EN,FL,India,S,India,100,"Statistics, Hadoop, MLOps, Azure",Associate,1,Gaming,2025-04-03,2025-04-29,2463,8,Cognitive Computing -AI05076,Deep Learning Engineer,121910,USD,121910,MI,FL,Denmark,M,Denmark,100,"Data Visualization, PyTorch, Spark, TensorFlow, SQL",PhD,2,Retail,2025-03-05,2025-05-11,1058,5.9,Machine Intelligence Group -AI05077,Autonomous Systems Engineer,27869,USD,27869,MI,FT,India,M,India,100,"NLP, Docker, Python, Azure",Bachelor,2,Retail,2024-12-03,2025-01-15,1498,9.5,Advanced Robotics -AI05078,Data Scientist,79781,USD,79781,SE,FL,China,L,China,100,"PyTorch, NLP, Data Visualization",PhD,7,Government,2024-05-27,2024-07-28,1915,7.4,Smart Analytics -AI05079,Computer Vision Engineer,94380,CAD,117975,MI,PT,Canada,L,Canada,100,"Git, Hadoop, Python",Master,3,Government,2024-11-23,2025-01-23,943,6.6,Neural Networks Co -AI05080,Deep Learning Engineer,57159,GBP,42869,EN,FL,United Kingdom,S,Netherlands,50,"R, Azure, Tableau, NLP, Linux",Master,1,Healthcare,2024-01-08,2024-02-25,766,6.6,Cloud AI Solutions -AI05081,AI Software Engineer,70183,USD,70183,EX,FT,China,S,China,100,"Statistics, NLP, TensorFlow, Git",Associate,18,Technology,2025-02-20,2025-04-14,1019,7.4,Predictive Systems -AI05082,AI Research Scientist,63741,USD,63741,EN,PT,Finland,L,Finland,0,"Java, Python, Hadoop",Bachelor,1,Healthcare,2024-01-27,2024-02-10,2032,6.1,AI Innovations -AI05083,AI Product Manager,125484,AUD,169403,SE,FT,Australia,L,Australia,100,"PyTorch, TensorFlow, NLP, Git, Spark",Master,6,Gaming,2024-11-29,2024-12-26,1576,8.1,TechCorp Inc -AI05084,Head of AI,165739,JPY,18231290,SE,FT,Japan,L,Japan,50,"R, Python, NLP, TensorFlow",Bachelor,5,Energy,2024-12-09,2025-02-16,2291,9.6,Digital Transformation LLC -AI05085,ML Ops Engineer,70983,EUR,60336,EN,PT,Austria,M,Austria,100,"Deep Learning, Python, MLOps, Java, TensorFlow",Associate,0,Finance,2024-04-05,2024-04-26,1418,5.4,Predictive Systems -AI05086,AI Specialist,110016,GBP,82512,MI,PT,United Kingdom,L,United Kingdom,0,"Python, Hadoop, TensorFlow",PhD,4,Real Estate,2025-04-30,2025-05-28,2127,8.4,Algorithmic Solutions -AI05087,Data Engineer,123436,CHF,111092,EN,PT,Switzerland,L,Switzerland,100,"Kubernetes, Java, Statistics, NLP, Docker",PhD,0,Technology,2025-02-26,2025-04-15,1329,9.2,Smart Analytics -AI05088,Deep Learning Engineer,81729,USD,81729,MI,CT,Ireland,M,Thailand,100,"Java, Azure, NLP, SQL, AWS",Associate,3,Technology,2024-03-06,2024-04-25,552,6.2,Machine Intelligence Group -AI05089,Principal Data Scientist,24353,USD,24353,EN,FT,China,S,China,100,"R, SQL, NLP",Bachelor,1,Finance,2024-02-16,2024-04-27,1050,8.8,DeepTech Ventures -AI05090,AI Consultant,48696,USD,48696,EN,CT,South Korea,L,Mexico,50,"Hadoop, Tableau, Spark, MLOps",PhD,1,Consulting,2025-02-26,2025-03-24,1665,7.6,Cloud AI Solutions -AI05091,AI Software Engineer,114364,CHF,102928,EN,PT,Switzerland,L,South Africa,100,"MLOps, PyTorch, NLP, Mathematics",PhD,0,Telecommunications,2024-01-11,2024-03-15,1731,8.4,Advanced Robotics -AI05092,AI Architect,93835,USD,93835,EN,CT,United States,M,Argentina,50,"Docker, MLOps, Git",Bachelor,1,Real Estate,2025-02-05,2025-03-06,1431,6.9,Autonomous Tech -AI05093,AI Architect,170109,USD,170109,SE,FT,Denmark,S,Denmark,100,"TensorFlow, Computer Vision, Tableau, Python, Azure",Associate,8,Consulting,2025-03-14,2025-05-21,1430,8.9,Predictive Systems -AI05094,Principal Data Scientist,89443,JPY,9838730,EN,FT,Japan,L,Romania,0,"Git, AWS, R",PhD,0,Automotive,2025-02-09,2025-02-27,2366,7,Future Systems -AI05095,AI Specialist,252682,CHF,227414,EX,CT,Switzerland,L,Switzerland,50,"Git, SQL, GCP",Bachelor,12,Education,2025-03-28,2025-05-30,969,8.2,Machine Intelligence Group -AI05096,Machine Learning Engineer,133737,JPY,14711070,SE,CT,Japan,M,Japan,0,"Azure, GCP, Spark, MLOps, AWS",PhD,9,Retail,2024-12-23,2025-02-22,1774,6.6,Cognitive Computing -AI05097,NLP Engineer,73390,USD,73390,EN,CT,Israel,L,Brazil,0,"SQL, TensorFlow, Tableau, AWS",PhD,1,Consulting,2024-01-10,2024-03-08,2396,6.3,Algorithmic Solutions -AI05098,Deep Learning Engineer,215737,EUR,183376,EX,FT,Germany,M,Ghana,100,"Computer Vision, PyTorch, Python, AWS",Associate,13,Telecommunications,2024-07-14,2024-08-14,670,6.4,Machine Intelligence Group -AI05099,Data Analyst,154884,CHF,139396,MI,FL,Switzerland,L,Switzerland,100,"Scala, Java, AWS, PyTorch",PhD,3,Technology,2024-05-18,2024-06-26,1197,7.6,Autonomous Tech -AI05100,AI Specialist,63606,EUR,54065,MI,FT,France,S,India,0,"Scala, Spark, Git, Computer Vision",Associate,2,Media,2024-08-18,2024-09-29,1449,5.6,Machine Intelligence Group -AI05101,AI Software Engineer,26739,USD,26739,MI,FL,India,S,India,50,"Python, SQL, Linux",PhD,2,Automotive,2024-09-10,2024-10-28,2446,5.6,Smart Analytics -AI05102,AI Research Scientist,38550,USD,38550,SE,PT,India,S,Argentina,50,"Kubernetes, TensorFlow, Git",Master,7,Energy,2024-07-13,2024-09-09,503,9.6,Advanced Robotics -AI05103,Machine Learning Engineer,74739,USD,74739,MI,FT,South Korea,M,South Korea,0,"AWS, Computer Vision, R",PhD,3,Retail,2024-06-21,2024-08-02,1362,7.5,Digital Transformation LLC -AI05104,AI Architect,160816,CHF,144734,MI,FT,Switzerland,L,Switzerland,50,"Scala, Java, AWS, Computer Vision",PhD,3,Technology,2024-01-11,2024-02-23,1597,8.3,DeepTech Ventures -AI05105,Research Scientist,73482,USD,73482,EN,PT,United States,S,Colombia,100,"Computer Vision, Tableau, TensorFlow, GCP",PhD,0,Government,2024-05-17,2024-06-29,1698,8.2,Smart Analytics -AI05106,Deep Learning Engineer,53504,USD,53504,EN,PT,Finland,S,Finland,100,"Data Visualization, Azure, Tableau, Docker, PyTorch",PhD,1,Manufacturing,2025-03-01,2025-04-05,1171,6.5,Cognitive Computing -AI05107,AI Architect,58640,EUR,49844,EN,FL,Germany,S,Malaysia,50,"Mathematics, Linux, PyTorch",Associate,1,Manufacturing,2025-03-03,2025-04-21,2294,9.3,Advanced Robotics -AI05108,Principal Data Scientist,110169,EUR,93644,SE,CT,France,S,Switzerland,100,"Java, SQL, Mathematics, MLOps, Deep Learning",Bachelor,5,Energy,2024-04-23,2024-06-28,2276,6.2,Cloud AI Solutions -AI05109,Data Engineer,61539,EUR,52308,EN,FT,Netherlands,S,Netherlands,50,"PyTorch, Docker, Tableau, Mathematics, Azure",Master,0,Gaming,2024-12-15,2025-02-10,972,5.9,Advanced Robotics -AI05110,AI Product Manager,33132,USD,33132,EN,FT,China,M,China,0,"Deep Learning, TensorFlow, Linux, MLOps, Python",Master,0,Finance,2024-02-07,2024-04-04,1289,6,Smart Analytics -AI05111,NLP Engineer,50597,USD,50597,EN,FT,Ireland,S,Ireland,100,"Tableau, GCP, Git, MLOps, Java",Master,0,Healthcare,2025-02-25,2025-04-05,1056,8,Smart Analytics -AI05112,AI Product Manager,138723,SGD,180340,SE,CT,Singapore,S,Norway,0,"Spark, PyTorch, Mathematics",Associate,7,Technology,2025-04-16,2025-05-18,1946,5.5,Predictive Systems -AI05113,ML Ops Engineer,96580,USD,96580,EX,PT,China,L,China,50,"Computer Vision, GCP, Hadoop",Associate,17,Real Estate,2025-03-14,2025-05-13,608,5.5,DataVision Ltd -AI05114,Principal Data Scientist,75245,GBP,56434,EN,FL,United Kingdom,M,United Kingdom,100,"Deep Learning, Python, Linux, Kubernetes",Master,0,Finance,2025-02-21,2025-04-07,579,6.3,Cognitive Computing -AI05115,AI Research Scientist,100596,USD,100596,EN,FL,Denmark,L,Switzerland,100,"PyTorch, Java, MLOps",Bachelor,0,Real Estate,2025-02-17,2025-03-26,1945,7.3,DeepTech Ventures -AI05116,Principal Data Scientist,82608,USD,82608,EN,FT,Sweden,L,Sweden,50,"Data Visualization, Docker, Mathematics",Master,0,Healthcare,2024-01-14,2024-02-28,2416,7.5,DataVision Ltd -AI05117,Principal Data Scientist,86868,EUR,73838,MI,PT,Austria,M,Estonia,50,"Python, Deep Learning, Kubernetes, Statistics, Hadoop",PhD,3,Transportation,2024-06-12,2024-07-13,1798,8.4,Smart Analytics -AI05118,Data Engineer,92090,USD,92090,EN,FT,Denmark,M,Denmark,0,"Data Visualization, AWS, Azure",Associate,0,Gaming,2025-02-20,2025-04-19,2090,6.2,DataVision Ltd -AI05119,AI Research Scientist,125783,USD,125783,MI,PT,Denmark,M,Denmark,50,"Spark, TensorFlow, Deep Learning, Tableau",Master,2,Retail,2024-02-14,2024-04-27,2313,8.6,TechCorp Inc -AI05120,Machine Learning Researcher,168390,SGD,218907,EX,FT,Singapore,S,Singapore,50,"TensorFlow, NLP, Git, GCP, Spark",Master,18,Telecommunications,2024-06-25,2024-07-11,635,5.4,Future Systems -AI05121,AI Product Manager,193710,CHF,174339,SE,FT,Switzerland,L,Turkey,0,"Python, Kubernetes, Data Visualization",Bachelor,8,Finance,2024-09-20,2024-10-14,696,5.2,Neural Networks Co -AI05122,Robotics Engineer,86414,USD,86414,MI,CT,Ireland,S,Thailand,50,"Python, Linux, Data Visualization, Deep Learning",PhD,4,Energy,2024-09-09,2024-10-10,644,6.2,AI Innovations -AI05123,AI Software Engineer,136589,CAD,170736,SE,FT,Canada,M,Canada,100,"Java, Scala, MLOps, Statistics",Bachelor,8,Energy,2024-02-18,2024-04-17,2280,6.5,Neural Networks Co -AI05124,Research Scientist,116556,AUD,157351,MI,PT,Australia,L,Australia,0,"Hadoop, AWS, Java, Computer Vision",Bachelor,4,Government,2024-12-10,2025-01-17,1582,8.8,Advanced Robotics -AI05125,AI Research Scientist,147616,EUR,125474,SE,FT,France,L,France,50,"Git, Azure, MLOps, Python",Master,9,Telecommunications,2025-01-16,2025-03-05,1224,6.1,AI Innovations -AI05126,ML Ops Engineer,167103,JPY,18381330,EX,CT,Japan,L,Colombia,100,"PyTorch, Git, NLP",Master,19,Manufacturing,2024-01-10,2024-02-24,918,6.5,Digital Transformation LLC -AI05127,Research Scientist,187756,USD,187756,EX,PT,Norway,M,Norway,0,"Scala, SQL, MLOps, Kubernetes",PhD,13,Government,2025-03-21,2025-04-30,635,9.7,Neural Networks Co -AI05128,ML Ops Engineer,25560,USD,25560,EN,FL,India,S,India,0,"Git, Java, Hadoop, AWS",Bachelor,0,Finance,2024-12-17,2025-02-09,1801,9.3,Predictive Systems -AI05129,Data Analyst,64206,USD,64206,MI,CT,South Korea,S,South Korea,100,"SQL, R, Scala",Bachelor,3,Media,2024-10-15,2024-12-14,1941,9.9,Digital Transformation LLC -AI05130,AI Architect,118221,EUR,100488,MI,PT,Germany,L,Germany,100,"Statistics, GCP, Mathematics, R, NLP",Master,4,Consulting,2024-12-08,2025-01-22,2017,5.7,Digital Transformation LLC -AI05131,Data Analyst,104839,JPY,11532290,MI,CT,Japan,M,Japan,100,"Java, Linux, Data Visualization, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-25,1810,5.9,Autonomous Tech -AI05132,AI Architect,86714,USD,86714,MI,CT,South Korea,L,South Korea,0,"GCP, Linux, Hadoop, TensorFlow, Data Visualization",Master,2,Education,2024-10-25,2024-11-20,1338,6.7,Cloud AI Solutions -AI05133,AI Research Scientist,110353,USD,110353,MI,CT,Norway,S,Norway,50,"PyTorch, AWS, SQL, R, MLOps",Bachelor,4,Retail,2025-04-25,2025-06-10,877,9.9,Predictive Systems -AI05134,Machine Learning Researcher,61142,USD,61142,EN,PT,Finland,M,Germany,50,"Mathematics, Linux, R, Java",Bachelor,1,Consulting,2024-10-04,2024-10-29,933,7.5,DataVision Ltd -AI05135,ML Ops Engineer,155690,USD,155690,SE,CT,Norway,L,Ukraine,0,"R, Git, Data Visualization, Python, Spark",Bachelor,6,Education,2025-01-20,2025-02-16,619,6.5,AI Innovations -AI05136,Research Scientist,117303,USD,117303,EX,FL,China,L,China,0,"Python, Git, Azure, Deep Learning, TensorFlow",Master,17,Energy,2024-06-16,2024-08-14,1415,6.9,Quantum Computing Inc -AI05137,Data Scientist,55265,CAD,69081,EN,CT,Canada,M,Canada,100,"Java, Kubernetes, NLP, Spark",Master,1,Automotive,2024-12-12,2024-12-27,1241,9.6,Algorithmic Solutions -AI05138,Data Analyst,76310,USD,76310,EX,CT,India,L,India,100,"Git, Python, MLOps",Master,19,Telecommunications,2024-11-17,2024-12-27,786,8.4,Cloud AI Solutions -AI05139,Autonomous Systems Engineer,93083,SGD,121008,EN,FT,Singapore,L,Egypt,50,"Azure, AWS, Deep Learning, Git",Master,1,Technology,2024-08-06,2024-09-28,2421,6.5,Machine Intelligence Group -AI05140,Research Scientist,133350,USD,133350,SE,CT,Norway,S,Norway,100,"Computer Vision, Docker, PyTorch",PhD,7,Transportation,2025-02-25,2025-03-26,1457,8.7,Machine Intelligence Group -AI05141,Computer Vision Engineer,86337,USD,86337,MI,CT,Finland,S,United Kingdom,0,"Hadoop, SQL, Data Visualization, PyTorch",Master,2,Telecommunications,2025-01-18,2025-02-18,1291,8.2,DataVision Ltd -AI05142,Data Scientist,86313,USD,86313,MI,CT,Ireland,M,Ireland,100,"Data Visualization, R, GCP, Python, Computer Vision",PhD,2,Retail,2024-05-12,2024-06-19,2120,7.6,Neural Networks Co -AI05143,ML Ops Engineer,57198,USD,57198,SE,CT,China,M,China,0,"Mathematics, Scala, Kubernetes",PhD,7,Education,2024-05-14,2024-06-21,2017,5.4,DataVision Ltd -AI05144,AI Software Engineer,60582,JPY,6664020,EN,FT,Japan,S,Japan,0,"NLP, Deep Learning, Azure, Python",PhD,1,Education,2024-07-16,2024-08-21,1597,9.4,Advanced Robotics -AI05145,Head of AI,55380,EUR,47073,EN,CT,Austria,M,Austria,0,"Git, GCP, AWS, Mathematics",Bachelor,0,Gaming,2025-03-10,2025-03-26,1708,6.8,DeepTech Ventures -AI05146,AI Research Scientist,48341,USD,48341,SE,FL,India,M,India,0,"Kubernetes, GCP, MLOps, Docker",Associate,7,Technology,2024-06-11,2024-07-23,1819,7.5,AI Innovations -AI05147,AI Product Manager,251565,USD,251565,EX,FT,Norway,L,Norway,50,"GCP, Python, Statistics",Master,17,Healthcare,2024-05-10,2024-06-28,1282,8,Advanced Robotics -AI05148,Machine Learning Researcher,236217,CHF,212595,EX,PT,Switzerland,S,Switzerland,50,"Tableau, Kubernetes, AWS, Mathematics, Scala",Bachelor,13,Education,2025-04-16,2025-06-03,1026,9.3,Digital Transformation LLC -AI05149,Autonomous Systems Engineer,91231,USD,91231,SE,CT,South Korea,M,Colombia,100,"Spark, Scala, MLOps",Master,6,Healthcare,2024-02-04,2024-03-04,1711,7,Neural Networks Co -AI05150,Machine Learning Researcher,61130,USD,61130,EN,FL,Israel,S,Nigeria,0,"SQL, MLOps, Computer Vision, Python, GCP",Bachelor,0,Manufacturing,2024-11-24,2025-01-10,1637,9,AI Innovations -AI05151,Computer Vision Engineer,62398,CAD,77998,EN,CT,Canada,L,Canada,50,"Data Visualization, Linux, Spark",Master,1,Healthcare,2024-06-03,2024-07-05,1982,9.2,AI Innovations -AI05152,Research Scientist,176242,EUR,149806,EX,FL,France,M,South Africa,50,"Python, Hadoop, GCP",Bachelor,14,Education,2025-02-04,2025-04-05,1846,8.2,Neural Networks Co -AI05153,Data Analyst,153418,EUR,130405,EX,FL,France,M,France,100,"MLOps, R, Scala",Bachelor,13,Government,2025-03-26,2025-04-15,844,7.6,DeepTech Ventures -AI05154,Data Scientist,81657,CAD,102071,MI,CT,Canada,S,New Zealand,50,"Scala, Git, Python",Master,2,Energy,2024-08-31,2024-10-12,2064,6.7,Algorithmic Solutions -AI05155,Data Analyst,69844,USD,69844,EN,PT,Israel,L,Israel,100,"Java, SQL, PyTorch, Computer Vision, Hadoop",Bachelor,0,Technology,2025-04-16,2025-05-16,910,7.3,TechCorp Inc -AI05156,AI Consultant,91682,EUR,77930,MI,FT,Netherlands,M,Netherlands,50,"NLP, Linux, Azure, Deep Learning",Associate,4,Gaming,2024-10-02,2024-11-27,1604,5.1,Smart Analytics -AI05157,Computer Vision Engineer,69595,AUD,93953,MI,FT,Australia,S,Russia,50,"PyTorch, TensorFlow, Tableau, AWS, Hadoop",Bachelor,3,Transportation,2024-03-19,2024-04-14,774,8.7,Predictive Systems -AI05158,AI Software Engineer,101742,USD,101742,EN,CT,Norway,L,Spain,100,"Linux, SQL, Tableau, Java",Bachelor,0,Retail,2024-10-03,2024-11-20,1067,9.2,Algorithmic Solutions -AI05159,Head of AI,97961,USD,97961,MI,PT,Israel,L,Israel,0,"AWS, Azure, Git, Mathematics",PhD,4,Education,2024-02-14,2024-04-01,1688,8.1,Future Systems -AI05160,AI Consultant,106022,JPY,11662420,MI,FT,Japan,M,Romania,100,"R, SQL, Data Visualization",Master,3,Energy,2024-08-11,2024-09-29,1832,6.4,AI Innovations -AI05161,ML Ops Engineer,46651,USD,46651,MI,PT,China,M,China,50,"Java, Tableau, PyTorch, Computer Vision",Bachelor,2,Telecommunications,2025-03-15,2025-04-17,807,7.3,Algorithmic Solutions -AI05162,Robotics Engineer,124553,CAD,155691,SE,PT,Canada,L,Canada,0,"Mathematics, Linux, Python, Deep Learning, Kubernetes",PhD,9,Manufacturing,2024-06-03,2024-07-31,922,9.8,DeepTech Ventures -AI05163,ML Ops Engineer,104780,EUR,89063,SE,PT,Austria,S,Austria,100,"Git, Python, Spark",Bachelor,8,Education,2024-07-02,2024-09-06,926,6.4,Autonomous Tech -AI05164,AI Specialist,114730,AUD,154886,SE,CT,Australia,S,Brazil,100,"SQL, R, PyTorch",Master,5,Retail,2024-05-13,2024-06-27,787,6.3,Machine Intelligence Group -AI05165,Research Scientist,162856,EUR,138428,SE,CT,France,L,France,0,"Git, Spark, Kubernetes, Statistics, Azure",Bachelor,5,Telecommunications,2024-10-14,2024-11-15,635,9.7,TechCorp Inc -AI05166,Robotics Engineer,125641,USD,125641,SE,FL,Sweden,S,Vietnam,100,"PyTorch, Computer Vision, AWS, SQL, MLOps",Associate,5,Education,2024-11-09,2025-01-20,1422,8,Cognitive Computing -AI05167,Machine Learning Engineer,89881,CHF,80893,EN,CT,Switzerland,L,Australia,0,"Data Visualization, TensorFlow, Azure",Bachelor,1,Telecommunications,2024-12-14,2025-01-22,993,5.3,TechCorp Inc -AI05168,AI Consultant,289064,USD,289064,EX,FL,United States,L,United States,50,"R, SQL, Tableau, MLOps, Docker",Master,17,Education,2024-04-04,2024-05-13,581,6.2,Machine Intelligence Group -AI05169,AI Specialist,226888,USD,226888,EX,FT,Sweden,S,Denmark,0,"Java, SQL, Data Visualization, PyTorch, Computer Vision",Master,13,Technology,2024-09-15,2024-10-27,2487,8.4,Cloud AI Solutions -AI05170,Principal Data Scientist,153723,EUR,130665,EX,CT,Netherlands,M,Netherlands,50,"Statistics, Spark, Python",Associate,13,Retail,2024-12-28,2025-03-05,1731,8.8,DeepTech Ventures -AI05171,AI Research Scientist,220723,SGD,286940,EX,FT,Singapore,S,Canada,50,"Mathematics, Python, Tableau",Associate,13,Media,2024-02-29,2024-04-19,1833,8,Future Systems -AI05172,Data Analyst,93378,EUR,79371,MI,FT,France,L,South Africa,100,"Spark, GCP, Scala, Computer Vision, Deep Learning",Master,3,Gaming,2024-08-06,2024-08-21,1938,6,TechCorp Inc -AI05173,ML Ops Engineer,162034,GBP,121526,SE,FT,United Kingdom,L,United Kingdom,50,"SQL, TensorFlow, Data Visualization",PhD,5,Media,2024-07-28,2024-08-30,1441,10,Cloud AI Solutions -AI05174,Head of AI,117365,USD,117365,SE,PT,Ireland,S,Ireland,100,"Statistics, Data Visualization, Git",Bachelor,5,Retail,2024-07-25,2024-09-04,1472,7.2,Autonomous Tech -AI05175,Machine Learning Engineer,128624,USD,128624,MI,PT,Denmark,M,Denmark,50,"GCP, Java, Azure, Linux",Master,2,Consulting,2025-04-15,2025-05-24,527,8.9,Quantum Computing Inc -AI05176,Head of AI,112504,EUR,95628,SE,PT,France,M,Austria,50,"Deep Learning, Docker, Computer Vision, Azure, Kubernetes",Bachelor,9,Education,2024-02-16,2024-03-28,1791,5.2,Digital Transformation LLC -AI05177,Data Analyst,91750,USD,91750,MI,CT,Norway,S,Norway,0,"Mathematics, TensorFlow, Computer Vision",Master,4,Transportation,2025-02-08,2025-03-09,1374,10,Neural Networks Co -AI05178,Machine Learning Engineer,216192,USD,216192,EX,FT,South Korea,L,South Korea,100,"Hadoop, Spark, NLP, Computer Vision",Bachelor,15,Gaming,2024-03-03,2024-04-12,508,6.2,Advanced Robotics -AI05179,Principal Data Scientist,102086,USD,102086,SE,FT,Israel,S,Israel,50,"Scala, Java, Azure, Data Visualization, TensorFlow",Associate,5,Finance,2024-04-21,2024-06-10,1342,6.2,Machine Intelligence Group -AI05180,Machine Learning Engineer,150372,USD,150372,SE,PT,Israel,L,Israel,0,"Scala, R, Linux, Mathematics",Bachelor,9,Government,2024-07-25,2024-08-12,2306,7,Algorithmic Solutions -AI05181,Data Analyst,132314,USD,132314,MI,FT,Norway,L,Turkey,100,"PyTorch, Scala, GCP, Mathematics",Bachelor,4,Automotive,2024-09-21,2024-10-14,1172,9.6,Cloud AI Solutions -AI05182,Data Analyst,103230,USD,103230,MI,PT,Sweden,M,Sweden,100,"Java, Scala, Kubernetes, NLP",Bachelor,2,Telecommunications,2024-03-27,2024-05-22,1418,9.9,Algorithmic Solutions -AI05183,AI Architect,120695,CAD,150869,SE,FL,Canada,L,Hungary,50,"GCP, NLP, Azure",Associate,8,Government,2024-08-16,2024-09-30,1328,5.8,Advanced Robotics -AI05184,Machine Learning Engineer,182121,USD,182121,EX,FT,Ireland,M,Austria,100,"Data Visualization, PyTorch, TensorFlow",Associate,19,Energy,2025-04-22,2025-05-07,2017,8.9,Neural Networks Co -AI05185,AI Architect,73616,CHF,66254,EN,PT,Switzerland,S,Argentina,100,"PyTorch, TensorFlow, Docker, Hadoop, Mathematics",PhD,0,Automotive,2024-03-06,2024-04-03,1044,9,Future Systems -AI05186,NLP Engineer,80112,USD,80112,EN,FT,Sweden,M,Denmark,50,"SQL, Python, Scala",Master,0,Telecommunications,2024-01-01,2024-02-06,2050,9.3,Algorithmic Solutions -AI05187,Data Scientist,95409,GBP,71557,MI,FL,United Kingdom,S,United Kingdom,100,"SQL, GCP, Computer Vision",Master,2,Automotive,2024-09-26,2024-11-25,1359,7.1,Predictive Systems -AI05188,NLP Engineer,120427,USD,120427,SE,FT,Israel,L,Israel,100,"Kubernetes, Spark, Java, TensorFlow, Statistics",Bachelor,5,Government,2024-08-12,2024-09-08,2168,9.9,Future Systems -AI05189,AI Research Scientist,38463,USD,38463,SE,CT,India,M,India,0,"Docker, Tableau, Java",Master,6,Gaming,2024-03-06,2024-05-09,2482,9.3,Algorithmic Solutions -AI05190,AI Software Engineer,38200,USD,38200,MI,FT,India,L,India,100,"PyTorch, Tableau, GCP",Bachelor,2,Media,2024-10-24,2024-12-03,1106,5.2,Smart Analytics -AI05191,Head of AI,74370,USD,74370,EN,CT,Ireland,M,Ireland,100,"Python, AWS, MLOps",Bachelor,0,Education,2025-01-10,2025-02-27,2007,9.1,Quantum Computing Inc -AI05192,AI Software Engineer,96885,EUR,82352,MI,FL,Germany,M,Germany,0,"R, Deep Learning, SQL, Statistics",Associate,3,Media,2024-01-17,2024-02-26,2017,5.8,Quantum Computing Inc -AI05193,AI Specialist,23564,USD,23564,EN,FL,India,M,Australia,0,"Linux, Python, Tableau, Hadoop",PhD,1,Healthcare,2025-04-19,2025-05-17,514,6.8,Neural Networks Co -AI05194,Machine Learning Engineer,135679,EUR,115327,SE,FL,Austria,M,Austria,50,"Python, Java, Computer Vision",Master,9,Media,2025-04-27,2025-06-17,1647,9.2,DeepTech Ventures -AI05195,ML Ops Engineer,85715,USD,85715,MI,CT,Finland,L,Ghana,100,"MLOps, Deep Learning, R",Master,2,Energy,2025-02-24,2025-05-03,2049,7.3,Digital Transformation LLC -AI05196,Machine Learning Researcher,127789,CAD,159736,SE,CT,Canada,S,Canada,100,"SQL, Python, NLP, Scala",PhD,6,Healthcare,2024-10-10,2024-12-14,1217,7.2,Algorithmic Solutions -AI05197,Data Engineer,186154,CHF,167539,SE,FT,Switzerland,S,Switzerland,100,"Statistics, Kubernetes, Linux",Bachelor,9,Energy,2025-01-08,2025-02-23,1306,7.4,Smart Analytics -AI05198,Research Scientist,202606,USD,202606,EX,CT,United States,L,United States,50,"Mathematics, TensorFlow, Linux, Docker, R",Master,17,Education,2024-10-15,2024-11-25,898,5.2,Machine Intelligence Group -AI05199,Data Engineer,80486,USD,80486,EX,FL,China,L,China,0,"Python, AWS, GCP, Java",Bachelor,13,Automotive,2024-08-24,2024-10-26,2297,8.4,Cloud AI Solutions -AI05200,Principal Data Scientist,23519,USD,23519,EN,FT,India,S,India,0,"Computer Vision, MLOps, Statistics",Bachelor,0,Real Estate,2024-04-23,2024-06-08,1217,7.9,DeepTech Ventures -AI05201,Head of AI,54022,CAD,67528,EN,CT,Canada,S,Colombia,50,"Spark, Tableau, Deep Learning, Python",Associate,0,Finance,2024-08-25,2024-10-09,1620,5.2,Future Systems -AI05202,Deep Learning Engineer,94661,USD,94661,MI,CT,South Korea,L,South Korea,0,"Spark, Python, Java, Linux",Bachelor,3,Transportation,2024-09-26,2024-10-30,1281,8.3,TechCorp Inc -AI05203,AI Architect,92817,JPY,10209870,EN,FL,Japan,L,Finland,50,"Scala, Git, GCP, Hadoop",Associate,0,Education,2024-01-19,2024-03-08,2205,8.7,Algorithmic Solutions -AI05204,AI Product Manager,183387,SGD,238403,EX,FL,Singapore,S,Singapore,50,"NLP, Tableau, Spark",Associate,14,Transportation,2024-04-28,2024-05-30,1925,5.2,Future Systems -AI05205,Research Scientist,39823,USD,39823,MI,FT,China,S,China,0,"R, Python, Kubernetes, GCP",Bachelor,3,Energy,2024-02-22,2024-04-06,1780,6.6,Quantum Computing Inc -AI05206,Principal Data Scientist,204455,USD,204455,EX,CT,Denmark,S,Denmark,50,"Java, Python, Data Visualization, Kubernetes",Associate,16,Gaming,2025-03-04,2025-03-29,1148,5.5,Autonomous Tech -AI05207,ML Ops Engineer,61232,USD,61232,SE,PT,China,L,Australia,100,"Spark, Azure, Computer Vision",Master,8,Education,2024-09-20,2024-11-17,544,7.3,Autonomous Tech -AI05208,Research Scientist,112367,EUR,95512,SE,FT,France,M,France,100,"Hadoop, Python, Linux, NLP",Bachelor,6,Manufacturing,2024-07-02,2024-08-26,547,6.7,Cognitive Computing -AI05209,Data Analyst,73735,EUR,62675,EN,FL,Germany,L,Germany,0,"Python, PyTorch, Java, Computer Vision",Master,1,Education,2024-06-08,2024-08-04,971,8.9,Autonomous Tech -AI05210,Robotics Engineer,294725,USD,294725,EX,FL,United States,M,United States,0,"Spark, PyTorch, NLP",PhD,11,Healthcare,2024-04-20,2024-05-16,1054,7.2,Autonomous Tech -AI05211,Data Analyst,242630,USD,242630,EX,CT,Denmark,M,Denmark,0,"Kubernetes, Python, Statistics, TensorFlow, Data Visualization",Bachelor,15,Consulting,2024-12-01,2024-12-26,2423,9,Quantum Computing Inc -AI05212,Data Engineer,86849,USD,86849,SE,FT,South Korea,S,South Korea,100,"Scala, Hadoop, Kubernetes, SQL",Associate,6,Education,2024-07-05,2024-08-24,1936,6.7,Cloud AI Solutions -AI05213,AI Specialist,48264,USD,48264,SE,FL,India,M,India,0,"Python, Deep Learning, TensorFlow, Docker",Bachelor,7,Media,2024-11-20,2025-01-24,1965,7.5,AI Innovations -AI05214,ML Ops Engineer,66226,JPY,7284860,EN,PT,Japan,S,Finland,0,"Python, Kubernetes, TensorFlow",Associate,1,Retail,2024-08-17,2024-10-28,584,8.5,Neural Networks Co -AI05215,AI Software Engineer,59484,USD,59484,EX,CT,India,S,France,0,"Linux, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-01-28,2024-02-26,528,6.2,TechCorp Inc -AI05216,AI Software Engineer,75033,GBP,56275,MI,FL,United Kingdom,S,United Kingdom,50,"Git, TensorFlow, Deep Learning",PhD,4,Manufacturing,2025-01-18,2025-02-05,1597,7.4,Cognitive Computing -AI05217,Principal Data Scientist,53070,USD,53070,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Java, GCP, Git",Master,1,Retail,2024-04-02,2024-06-14,2279,5.2,Algorithmic Solutions -AI05218,Autonomous Systems Engineer,80312,USD,80312,MI,PT,Ireland,S,Ireland,0,"Statistics, TensorFlow, Deep Learning, Kubernetes, Mathematics",Master,3,Automotive,2024-03-28,2024-05-26,1395,6.1,DataVision Ltd -AI05219,AI Research Scientist,61589,USD,61589,EN,PT,Finland,S,Finland,100,"Linux, Python, Docker, Deep Learning, MLOps",PhD,0,Education,2025-01-28,2025-04-09,682,7.7,DataVision Ltd -AI05220,Machine Learning Researcher,64464,USD,64464,EN,PT,South Korea,L,South Korea,50,"Kubernetes, Scala, Data Visualization",PhD,1,Retail,2024-02-29,2024-04-22,1904,8.9,Algorithmic Solutions -AI05221,Data Engineer,155127,CHF,139614,MI,PT,Switzerland,M,Switzerland,100,"AWS, Python, MLOps, TensorFlow, PyTorch",PhD,3,Transportation,2024-02-07,2024-03-24,644,6.3,DeepTech Ventures -AI05222,Research Scientist,218691,EUR,185887,EX,CT,Germany,S,Germany,100,"Linux, Statistics, Hadoop, Spark, MLOps",PhD,12,Technology,2024-01-23,2024-03-05,795,6,Future Systems -AI05223,Robotics Engineer,204587,CHF,184128,SE,PT,Switzerland,L,Switzerland,0,"Python, Computer Vision, TensorFlow, Linux",PhD,9,Telecommunications,2024-09-30,2024-10-20,1680,6.9,AI Innovations -AI05224,Robotics Engineer,113415,EUR,96403,SE,PT,Austria,S,Austria,0,"Kubernetes, Scala, Tableau, Mathematics, AWS",PhD,9,Telecommunications,2024-01-18,2024-02-22,2041,8.4,Smart Analytics -AI05225,AI Consultant,111108,USD,111108,SE,FT,South Korea,S,South Korea,0,"Linux, GCP, Mathematics, Computer Vision, MLOps",Associate,5,Automotive,2025-03-08,2025-04-14,2348,8.4,Advanced Robotics -AI05226,AI Product Manager,162371,GBP,121778,EX,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Azure, PyTorch",Associate,13,Consulting,2024-09-01,2024-11-13,2361,9.6,Smart Analytics -AI05227,Data Engineer,78542,USD,78542,EN,PT,Sweden,M,Sweden,100,"R, MLOps, SQL",Master,0,Technology,2024-07-25,2024-08-26,1736,9.6,Autonomous Tech -AI05228,Data Analyst,111272,CHF,100145,MI,CT,Switzerland,M,Italy,0,"R, Spark, Statistics, GCP",Master,2,Finance,2024-07-01,2024-08-04,584,6.6,Machine Intelligence Group -AI05229,Machine Learning Researcher,141413,USD,141413,SE,PT,United States,M,Nigeria,50,"PyTorch, NLP, Scala, GCP, Azure",Associate,9,Government,2025-01-01,2025-03-02,2468,8.9,Autonomous Tech -AI05230,Robotics Engineer,153448,USD,153448,MI,CT,Norway,L,Norway,0,"Scala, Java, MLOps",Associate,4,Telecommunications,2024-02-02,2024-02-24,1035,5.9,Predictive Systems -AI05231,AI Consultant,126522,EUR,107544,SE,CT,Austria,L,Austria,0,"Python, AWS, Data Visualization, Docker, Computer Vision",Bachelor,9,Government,2024-06-13,2024-08-08,1749,9.2,Autonomous Tech -AI05232,Data Analyst,75216,USD,75216,MI,PT,Finland,S,India,0,"Kubernetes, SQL, Scala, GCP, TensorFlow",Bachelor,2,Government,2025-03-04,2025-04-29,979,7,TechCorp Inc -AI05233,Data Analyst,157426,JPY,17316860,EX,FT,Japan,M,Ghana,0,"Deep Learning, Azure, Spark",Bachelor,19,Education,2024-05-10,2024-05-30,1193,5,TechCorp Inc -AI05234,Research Scientist,78696,USD,78696,EN,PT,United States,S,Sweden,0,"Azure, R, Git",Bachelor,1,Government,2024-10-04,2024-12-15,898,6.6,Digital Transformation LLC -AI05235,Robotics Engineer,113402,USD,113402,EX,CT,China,M,China,0,"SQL, Python, Git",Associate,18,Gaming,2025-03-27,2025-05-27,2353,6.1,Machine Intelligence Group -AI05236,Machine Learning Researcher,86790,CHF,78111,EN,CT,Switzerland,M,Switzerland,100,"Python, NLP, TensorFlow",Master,1,Real Estate,2024-11-12,2025-01-18,1071,9.3,DeepTech Ventures -AI05237,Machine Learning Researcher,85140,USD,85140,EN,PT,United States,S,Spain,100,"Git, Spark, Java, SQL, GCP",PhD,0,Education,2025-03-29,2025-05-18,2413,9.7,DataVision Ltd -AI05238,Robotics Engineer,80679,EUR,68577,EN,FT,Austria,L,Austria,100,"R, Git, Tableau",Bachelor,1,Telecommunications,2024-06-23,2024-08-14,1374,8.3,Cloud AI Solutions -AI05239,AI Specialist,207222,USD,207222,EX,CT,Ireland,S,Ireland,100,"Spark, GCP, Data Visualization, Kubernetes, Python",PhD,19,Finance,2024-09-07,2024-10-19,1846,5.3,Autonomous Tech -AI05240,Principal Data Scientist,121677,SGD,158180,MI,PT,Singapore,L,Singapore,50,"Python, R, SQL, Linux",Bachelor,3,Education,2024-03-18,2024-05-23,1099,8.9,Cloud AI Solutions -AI05241,AI Research Scientist,190049,USD,190049,EX,PT,Sweden,M,Sweden,100,"Statistics, Mathematics, Tableau",Master,18,Finance,2025-01-29,2025-03-21,1642,8.9,AI Innovations -AI05242,Data Engineer,77584,USD,77584,EN,PT,Norway,S,Malaysia,100,"Python, AWS, MLOps",Master,0,Government,2024-02-08,2024-04-04,2356,6.9,Future Systems -AI05243,AI Software Engineer,120788,USD,120788,EX,FT,Finland,S,Finland,50,"AWS, TensorFlow, Linux",Master,16,Consulting,2024-02-28,2024-05-05,1853,9.4,Autonomous Tech -AI05244,Deep Learning Engineer,46291,USD,46291,SE,CT,India,S,India,0,"Linux, Deep Learning, R",Bachelor,8,Telecommunications,2025-01-17,2025-03-07,1918,9.6,Quantum Computing Inc -AI05245,Computer Vision Engineer,74298,USD,74298,EN,PT,Israel,L,Israel,100,"Python, Computer Vision, TensorFlow, Linux, Statistics",Associate,0,Energy,2024-05-31,2024-07-12,2312,9.2,Cloud AI Solutions -AI05246,Machine Learning Researcher,166410,USD,166410,SE,FL,Denmark,S,Denmark,100,"Computer Vision, GCP, Scala, Statistics",Associate,7,Finance,2025-01-07,2025-03-06,1366,5.5,DeepTech Ventures -AI05247,Data Analyst,30796,USD,30796,EN,FL,China,S,China,0,"PyTorch, Hadoop, TensorFlow, Docker",PhD,0,Manufacturing,2024-09-30,2024-11-23,1747,5.9,Advanced Robotics -AI05248,Machine Learning Researcher,60780,USD,60780,EN,FT,Sweden,S,Sweden,0,"Azure, Tableau, Mathematics, Data Visualization, Python",PhD,1,Real Estate,2024-01-30,2024-03-11,546,7,AI Innovations -AI05249,Data Engineer,59678,USD,59678,EN,CT,South Korea,L,South Korea,0,"Azure, Kubernetes, Spark, Scala",Master,1,Retail,2024-02-03,2024-03-05,644,7.9,Neural Networks Co -AI05250,Principal Data Scientist,253960,USD,253960,EX,PT,Sweden,L,Sweden,100,"Linux, Git, R, SQL",Master,17,Healthcare,2024-10-24,2024-11-30,1172,6.9,DeepTech Ventures -AI05251,AI Specialist,87660,USD,87660,EN,CT,Sweden,L,Sweden,0,"Hadoop, TensorFlow, PyTorch, GCP, Linux",PhD,1,Energy,2024-07-05,2024-08-07,2016,5.3,DeepTech Ventures -AI05252,AI Architect,210655,USD,210655,EX,CT,Sweden,S,Sweden,50,"SQL, Spark, Tableau, AWS, Git",PhD,13,Automotive,2024-11-17,2025-01-18,1041,7.2,Neural Networks Co -AI05253,Principal Data Scientist,144360,USD,144360,SE,FL,Sweden,M,Sweden,50,"Kubernetes, Docker, Java",Master,9,Manufacturing,2024-04-18,2024-05-03,562,6.9,TechCorp Inc -AI05254,Computer Vision Engineer,57145,USD,57145,EN,FL,Israel,M,Austria,50,"Linux, R, SQL, PyTorch, Java",Associate,0,Retail,2024-02-29,2024-03-31,516,8,Cognitive Computing -AI05255,Computer Vision Engineer,196565,USD,196565,EX,FL,Denmark,S,Denmark,0,"Deep Learning, PyTorch, Linux",Associate,18,Government,2024-07-19,2024-09-08,1595,8.9,Cloud AI Solutions -AI05256,Computer Vision Engineer,78696,CHF,70826,EN,FL,Switzerland,S,Kenya,50,"Spark, Azure, Java, TensorFlow, Kubernetes",Bachelor,0,Real Estate,2024-04-13,2024-06-14,842,8.2,Quantum Computing Inc -AI05257,Autonomous Systems Engineer,69517,USD,69517,SE,PT,China,M,Thailand,50,"AWS, R, Tableau, Deep Learning",Bachelor,8,Healthcare,2025-03-26,2025-05-01,1621,9.5,Cognitive Computing -AI05258,Autonomous Systems Engineer,80960,USD,80960,MI,PT,Israel,S,Israel,50,"Kubernetes, Docker, Tableau, Java, NLP",Master,3,Healthcare,2024-12-31,2025-02-18,1893,9.3,Digital Transformation LLC -AI05259,Data Engineer,111422,EUR,94709,MI,CT,Germany,L,Germany,100,"Kubernetes, Docker, Java, R",PhD,2,Manufacturing,2024-06-15,2024-08-19,1824,5.3,DeepTech Ventures -AI05260,Robotics Engineer,112063,USD,112063,SE,CT,Israel,L,Israel,0,"Git, R, Computer Vision",Bachelor,9,Energy,2025-04-19,2025-06-13,1840,8.6,Machine Intelligence Group -AI05261,AI Architect,206889,USD,206889,EX,PT,United States,S,United States,100,"Scala, GCP, NLP, Python, Kubernetes",Bachelor,10,Telecommunications,2024-06-11,2024-08-11,979,6.2,Neural Networks Co -AI05262,Autonomous Systems Engineer,58383,EUR,49626,EN,CT,Austria,L,Austria,100,"Python, TensorFlow, Tableau, Data Visualization",Bachelor,0,Manufacturing,2024-05-11,2024-07-23,879,9.4,Machine Intelligence Group -AI05263,AI Consultant,176960,USD,176960,SE,CT,Denmark,S,Denmark,0,"Scala, Hadoop, SQL, Kubernetes, Azure",Master,7,Manufacturing,2024-06-14,2024-07-12,1584,5.3,Digital Transformation LLC -AI05264,Research Scientist,68995,EUR,58646,MI,FL,Austria,M,Netherlands,100,"R, Linux, Scala, SQL",Associate,4,Consulting,2025-04-24,2025-07-04,2408,9.5,AI Innovations -AI05265,ML Ops Engineer,130169,CAD,162711,SE,CT,Canada,M,Canada,0,"Kubernetes, TensorFlow, Deep Learning",PhD,9,Transportation,2024-06-02,2024-08-02,747,8,DataVision Ltd -AI05266,Data Engineer,51950,USD,51950,SE,CT,China,S,China,0,"Java, Git, Kubernetes, Python",Bachelor,9,Government,2024-12-18,2025-02-26,1106,7.8,DataVision Ltd -AI05267,AI Software Engineer,95065,USD,95065,MI,FL,Norway,S,Norway,100,"Linux, Kubernetes, Scala, GCP, Statistics",Bachelor,2,Automotive,2024-02-12,2024-03-04,967,9.6,Quantum Computing Inc -AI05268,AI Product Manager,78158,USD,78158,EN,PT,Ireland,M,Ireland,50,"R, SQL, Scala, PyTorch",Associate,1,Education,2024-06-11,2024-07-27,571,8.1,Advanced Robotics -AI05269,AI Architect,156925,EUR,133386,EX,PT,Germany,L,Switzerland,0,"Git, Hadoop, SQL, Linux, Azure",Associate,14,Retail,2024-10-13,2024-12-17,1184,6.8,Machine Intelligence Group -AI05270,Machine Learning Engineer,57461,USD,57461,SE,PT,China,S,China,100,"Data Visualization, SQL, Tableau, Java, GCP",Bachelor,6,Real Estate,2024-05-15,2024-06-29,1779,5.4,Quantum Computing Inc -AI05271,AI Architect,178905,CHF,161015,MI,CT,Switzerland,L,Switzerland,100,"Java, Azure, SQL",Master,4,Telecommunications,2024-06-24,2024-08-11,1733,5.8,Cloud AI Solutions -AI05272,Deep Learning Engineer,72036,EUR,61231,MI,PT,France,M,France,50,"R, Scala, Java, Docker, Kubernetes",PhD,4,Government,2024-03-17,2024-04-28,2121,5.1,Cognitive Computing -AI05273,AI Software Engineer,28532,USD,28532,EN,CT,China,S,China,50,"Spark, Data Visualization, SQL",PhD,1,Energy,2025-01-14,2025-02-04,551,6.3,Smart Analytics -AI05274,Research Scientist,102165,USD,102165,MI,FL,Ireland,M,Australia,50,"SQL, Docker, Data Visualization, GCP",PhD,2,Consulting,2024-04-26,2024-07-03,907,6.1,Future Systems -AI05275,AI Specialist,54248,USD,54248,EN,FT,Sweden,M,Sweden,100,"SQL, Scala, Docker, Kubernetes, Computer Vision",PhD,0,Finance,2025-04-27,2025-06-05,1496,7.7,Cognitive Computing -AI05276,AI Architect,133384,USD,133384,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Scala, TensorFlow, Linux, Deep Learning",Associate,8,Automotive,2025-02-16,2025-03-08,1747,5.8,Digital Transformation LLC -AI05277,Head of AI,166944,JPY,18363840,SE,CT,Japan,L,Japan,0,"SQL, Git, Mathematics",PhD,9,Transportation,2024-12-14,2025-02-25,594,5.2,TechCorp Inc -AI05278,Data Engineer,72269,USD,72269,EN,PT,South Korea,L,Mexico,50,"GCP, Spark, Linux, Computer Vision",Bachelor,1,Technology,2024-05-14,2024-07-03,1113,6,Cloud AI Solutions -AI05279,AI Specialist,39537,USD,39537,SE,FT,India,M,Nigeria,50,"Git, AWS, MLOps, Data Visualization",Associate,5,Manufacturing,2024-07-12,2024-08-07,1801,9.6,Autonomous Tech -AI05280,AI Specialist,206054,USD,206054,EX,FT,Ireland,S,Nigeria,50,"Azure, Hadoop, TensorFlow",Bachelor,12,Manufacturing,2024-03-03,2024-03-19,1141,8.2,Cognitive Computing -AI05281,Autonomous Systems Engineer,94121,CAD,117651,SE,FL,Canada,S,Belgium,50,"Deep Learning, Docker, Scala, Tableau, TensorFlow",Associate,7,Transportation,2025-02-10,2025-02-24,2387,7.9,Advanced Robotics -AI05282,Deep Learning Engineer,110533,AUD,149220,SE,PT,Australia,M,Italy,0,"Linux, TensorFlow, Python",Master,7,Government,2025-01-13,2025-03-20,1907,7.1,Machine Intelligence Group -AI05283,Data Scientist,106010,CHF,95409,MI,CT,Switzerland,M,Switzerland,100,"PyTorch, Statistics, SQL, Deep Learning",PhD,3,Automotive,2024-11-22,2024-12-22,1805,8.2,Autonomous Tech -AI05284,AI Software Engineer,213187,EUR,181209,EX,CT,France,L,France,100,"Linux, Spark, MLOps",PhD,18,Real Estate,2025-01-29,2025-04-02,1803,7.3,Cognitive Computing -AI05285,Research Scientist,103681,USD,103681,EX,PT,China,L,China,100,"PyTorch, Hadoop, Scala, GCP",Associate,17,Gaming,2024-08-03,2024-09-04,2335,7.7,Cognitive Computing -AI05286,Deep Learning Engineer,350954,CHF,315859,EX,FT,Switzerland,L,Switzerland,50,"R, Statistics, PyTorch",PhD,18,Education,2024-09-03,2024-09-25,1159,5.3,Neural Networks Co -AI05287,Robotics Engineer,166456,USD,166456,SE,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Data Visualization, SQL, Statistics",Master,6,Government,2025-04-20,2025-05-26,747,8.1,TechCorp Inc -AI05288,Machine Learning Researcher,127694,USD,127694,SE,FT,Israel,M,Israel,100,"Java, Deep Learning, Statistics",Associate,5,Education,2024-07-27,2024-09-01,1919,9.3,TechCorp Inc -AI05289,AI Architect,44798,USD,44798,SE,CT,India,M,Norway,50,"PyTorch, Azure, Tableau, Spark",Bachelor,5,Technology,2025-01-25,2025-04-08,1375,9.5,Quantum Computing Inc -AI05290,Machine Learning Engineer,97713,USD,97713,MI,FL,Sweden,L,Germany,100,"R, Python, Deep Learning, Computer Vision, Mathematics",Bachelor,2,Gaming,2024-04-15,2024-06-18,2136,8.7,Future Systems -AI05291,AI Research Scientist,104377,EUR,88720,MI,CT,Netherlands,S,Vietnam,50,"Python, Data Visualization, TensorFlow",Master,3,Media,2024-10-28,2024-12-08,1813,6.8,Cloud AI Solutions -AI05292,AI Architect,50775,CAD,63469,EN,FL,Canada,S,Canada,50,"Mathematics, PyTorch, GCP",Master,1,Transportation,2025-04-03,2025-05-06,1795,6.7,Quantum Computing Inc -AI05293,NLP Engineer,212513,USD,212513,EX,FL,South Korea,L,India,50,"Python, AWS, Tableau",Associate,10,Technology,2024-06-28,2024-08-27,2002,7.1,DataVision Ltd -AI05294,Robotics Engineer,33907,USD,33907,MI,PT,India,S,Colombia,100,"MLOps, R, Docker",Bachelor,2,Education,2024-10-13,2024-12-02,1146,8.3,Future Systems -AI05295,AI Specialist,130049,AUD,175566,SE,FT,Australia,M,Australia,50,"Mathematics, TensorFlow, PyTorch, AWS",Master,6,Consulting,2024-05-28,2024-07-26,1484,8,TechCorp Inc -AI05296,Research Scientist,214956,USD,214956,EX,FT,Norway,S,Thailand,50,"AWS, PyTorch, GCP, Statistics",Master,13,Energy,2025-01-05,2025-01-26,1776,9.6,Smart Analytics -AI05297,Data Scientist,131854,USD,131854,SE,CT,United States,M,United States,100,"Data Visualization, MLOps, Tableau, PyTorch",Associate,9,Manufacturing,2025-01-27,2025-04-02,533,9.5,DataVision Ltd -AI05298,Computer Vision Engineer,71723,JPY,7889530,EN,FT,Japan,L,Japan,100,"Computer Vision, NLP, Spark, GCP",Master,0,Technology,2024-09-02,2024-09-19,666,5.5,Digital Transformation LLC -AI05299,Principal Data Scientist,96917,USD,96917,SE,FL,Ireland,S,Ireland,0,"Spark, TensorFlow, Git, Hadoop, PyTorch",Master,8,Transportation,2024-12-18,2025-01-28,1627,5.8,DataVision Ltd -AI05300,AI Product Manager,74302,USD,74302,MI,PT,South Korea,L,South Korea,100,"R, Python, Git",PhD,3,Finance,2025-04-24,2025-05-25,752,8.7,Machine Intelligence Group -AI05301,Computer Vision Engineer,284665,USD,284665,EX,CT,Denmark,M,France,50,"Data Visualization, Java, Scala, MLOps",Bachelor,14,Automotive,2024-06-22,2024-07-09,2464,7.9,Neural Networks Co -AI05302,AI Architect,83787,EUR,71219,MI,PT,France,S,France,0,"SQL, R, AWS, Deep Learning, Hadoop",PhD,3,Healthcare,2024-10-12,2024-11-17,2212,8,Future Systems -AI05303,Machine Learning Engineer,85475,GBP,64106,MI,CT,United Kingdom,M,Mexico,100,"Tableau, GCP, NLP, Spark, Java",PhD,2,Healthcare,2024-05-12,2024-07-13,536,8.5,DataVision Ltd -AI05304,Principal Data Scientist,173819,EUR,147746,EX,PT,Austria,S,Austria,100,"Kubernetes, Statistics, PyTorch, GCP, Linux",Master,14,Education,2024-12-08,2025-02-19,2412,9,Quantum Computing Inc -AI05305,Data Scientist,94067,EUR,79957,MI,PT,Germany,M,Germany,50,"NLP, R, Tableau, Docker, AWS",PhD,4,Healthcare,2025-02-13,2025-03-10,1782,6.6,Cognitive Computing -AI05306,AI Consultant,301786,JPY,33196460,EX,FL,Japan,L,Japan,0,"Deep Learning, Git, Scala, Python",PhD,11,Retail,2025-04-03,2025-04-18,902,9.6,Neural Networks Co -AI05307,AI Research Scientist,86235,EUR,73300,EN,CT,Netherlands,L,Netherlands,100,"SQL, Kubernetes, PyTorch",Associate,1,Retail,2024-02-15,2024-03-04,1324,8.2,DeepTech Ventures -AI05308,Head of AI,165965,USD,165965,EX,FT,Israel,S,Israel,0,"TensorFlow, Azure, Linux",Associate,12,Government,2024-03-01,2024-04-19,1525,5.6,Smart Analytics -AI05309,Machine Learning Engineer,85823,USD,85823,EN,CT,Denmark,M,Denmark,100,"PyTorch, Azure, Data Visualization",Associate,1,Education,2024-07-30,2024-10-08,1458,6.7,Smart Analytics -AI05310,AI Software Engineer,85037,USD,85037,EX,FL,China,L,China,0,"Mathematics, Hadoop, Data Visualization",Bachelor,16,Retail,2024-12-03,2025-01-16,1818,7.9,AI Innovations -AI05311,AI Research Scientist,61149,USD,61149,MI,PT,South Korea,M,Germany,0,"SQL, Kubernetes, PyTorch",Bachelor,2,Media,2024-03-25,2024-06-05,1921,9.4,Advanced Robotics -AI05312,AI Specialist,92493,CAD,115616,MI,CT,Canada,L,Canada,50,"Linux, PyTorch, Git",PhD,3,Consulting,2024-08-13,2024-09-12,1208,7.6,AI Innovations -AI05313,Principal Data Scientist,114033,JPY,12543630,MI,FT,Japan,L,Japan,100,"Tableau, R, MLOps",PhD,4,Automotive,2025-01-24,2025-03-31,1016,7.8,Predictive Systems -AI05314,NLP Engineer,53893,EUR,45809,EN,CT,Germany,S,United Kingdom,0,"Python, Spark, Hadoop",Bachelor,1,Gaming,2024-02-20,2024-03-07,2172,7.6,Machine Intelligence Group -AI05315,ML Ops Engineer,84318,USD,84318,EN,PT,Finland,L,Romania,100,"TensorFlow, Computer Vision, Tableau",PhD,1,Automotive,2024-11-02,2024-12-09,785,7.4,TechCorp Inc -AI05316,Deep Learning Engineer,102359,CAD,127949,SE,CT,Canada,S,Canada,50,"GCP, R, Git, Kubernetes",Bachelor,9,Education,2025-04-24,2025-05-27,1201,7.1,Quantum Computing Inc -AI05317,Data Analyst,37425,USD,37425,EN,CT,China,M,China,100,"SQL, R, Tableau, Azure, PyTorch",Master,1,Manufacturing,2024-04-03,2024-06-08,1464,9.5,Advanced Robotics -AI05318,AI Specialist,78231,USD,78231,EN,CT,Denmark,M,Thailand,100,"Deep Learning, GCP, Python, Data Visualization, Docker",Bachelor,0,Manufacturing,2024-06-01,2024-07-06,2337,5.8,Algorithmic Solutions -AI05319,Machine Learning Engineer,62558,EUR,53174,EN,CT,Netherlands,M,Norway,50,"R, SQL, AWS, MLOps, Docker",Master,1,Transportation,2025-03-30,2025-04-20,2055,7.8,Future Systems -AI05320,Deep Learning Engineer,123579,CAD,154474,SE,FL,Canada,L,Canada,0,"Hadoop, Tableau, GCP, Deep Learning",PhD,5,Technology,2024-10-24,2024-12-15,785,9.3,TechCorp Inc -AI05321,Deep Learning Engineer,83741,CAD,104676,MI,FL,Canada,M,Canada,100,"NLP, Docker, Git",Master,3,Automotive,2025-03-04,2025-05-06,2180,5.3,Quantum Computing Inc -AI05322,Principal Data Scientist,103613,USD,103613,SE,PT,Sweden,S,Spain,50,"Linux, TensorFlow, Hadoop, Computer Vision, Tableau",PhD,7,Automotive,2024-01-10,2024-02-11,1225,10,Algorithmic Solutions -AI05323,Deep Learning Engineer,122345,USD,122345,SE,FT,Israel,S,Israel,0,"SQL, Python, TensorFlow, Git, PyTorch",Associate,9,Manufacturing,2024-02-20,2024-04-15,563,8.7,Autonomous Tech -AI05324,AI Software Engineer,125817,CHF,113235,EN,FT,Switzerland,L,Singapore,0,"Tableau, Scala, Python",Associate,0,Finance,2024-06-25,2024-07-12,2037,6.9,Neural Networks Co -AI05325,AI Research Scientist,83848,USD,83848,MI,CT,Sweden,S,Nigeria,50,"Python, Git, TensorFlow, Deep Learning",Bachelor,2,Media,2024-04-21,2024-07-01,1561,8.1,Predictive Systems -AI05326,Data Analyst,126646,EUR,107649,SE,FT,Netherlands,L,Netherlands,100,"Hadoop, Spark, Linux",Associate,5,Manufacturing,2024-03-20,2024-04-09,2308,7.6,DataVision Ltd -AI05327,AI Product Manager,216544,USD,216544,EX,FT,United States,M,United States,100,"Kubernetes, SQL, Azure, Linux, PyTorch",Associate,14,Transportation,2024-07-25,2024-09-23,1367,5.1,Cloud AI Solutions -AI05328,AI Research Scientist,254248,EUR,216111,EX,FL,Austria,L,Austria,50,"R, Docker, Data Visualization, MLOps, Spark",PhD,13,Automotive,2024-11-17,2025-01-29,2380,8,Machine Intelligence Group -AI05329,Deep Learning Engineer,238603,GBP,178952,EX,FT,United Kingdom,L,United Kingdom,0,"R, Hadoop, SQL, Azure, Tableau",Bachelor,16,Energy,2024-05-10,2024-05-25,1566,8.9,Cloud AI Solutions -AI05330,NLP Engineer,71862,USD,71862,EN,FT,Sweden,M,Austria,50,"SQL, PyTorch, MLOps, NLP, GCP",PhD,1,Automotive,2024-12-15,2025-01-10,2276,9.3,Autonomous Tech -AI05331,Autonomous Systems Engineer,43525,USD,43525,SE,CT,China,S,Philippines,50,"Python, SQL, R, Git, TensorFlow",Master,6,Gaming,2024-09-23,2024-10-19,2248,7.1,Smart Analytics -AI05332,Computer Vision Engineer,133643,EUR,113597,SE,FL,Austria,L,Austria,0,"Python, MLOps, Kubernetes",Associate,5,Healthcare,2025-02-05,2025-03-08,1300,7,Digital Transformation LLC -AI05333,Machine Learning Researcher,209974,SGD,272966,EX,PT,Singapore,S,Singapore,0,"Python, GCP, Scala, SQL",Master,18,Consulting,2024-10-27,2024-11-24,2148,10,Quantum Computing Inc -AI05334,AI Consultant,188802,CAD,236003,EX,FT,Canada,L,Austria,50,"Kubernetes, NLP, PyTorch, Git",Bachelor,14,Automotive,2024-02-27,2024-04-15,1309,8.3,Machine Intelligence Group -AI05335,ML Ops Engineer,109423,USD,109423,MI,FT,Norway,S,Czech Republic,0,"Java, Linux, Computer Vision",Associate,4,Telecommunications,2025-01-05,2025-01-19,1573,5.2,Digital Transformation LLC -AI05336,Data Scientist,193402,SGD,251423,EX,CT,Singapore,L,Singapore,0,"Hadoop, Python, Kubernetes",Bachelor,13,Healthcare,2024-08-27,2024-09-23,1658,8.9,TechCorp Inc -AI05337,Deep Learning Engineer,68104,EUR,57888,EN,FL,France,L,France,100,"Scala, Docker, Mathematics, Spark",PhD,0,Real Estate,2025-01-01,2025-02-23,2350,5.2,Future Systems -AI05338,AI Consultant,115997,USD,115997,MI,FT,United States,M,United States,0,"Linux, Scala, Mathematics, GCP, Deep Learning",Bachelor,4,Gaming,2024-06-27,2024-07-13,2145,8.7,DataVision Ltd -AI05339,AI Specialist,87942,USD,87942,MI,FT,South Korea,M,New Zealand,50,"R, MLOps, SQL, AWS, Scala",PhD,4,Education,2024-03-10,2024-03-27,1259,6.9,Autonomous Tech -AI05340,Machine Learning Engineer,303218,USD,303218,EX,CT,Denmark,L,Denmark,50,"R, Git, Scala",PhD,18,Government,2024-12-15,2025-02-02,1087,9.7,DataVision Ltd -AI05341,Research Scientist,63427,USD,63427,MI,CT,South Korea,S,South Korea,100,"Spark, Hadoop, R",Bachelor,2,Finance,2024-04-14,2024-05-25,952,7.2,Machine Intelligence Group -AI05342,Principal Data Scientist,148375,GBP,111281,SE,FT,United Kingdom,L,United Kingdom,0,"Mathematics, Python, Linux, Hadoop, TensorFlow",Bachelor,6,Education,2025-02-24,2025-04-29,609,7.3,Machine Intelligence Group -AI05343,Machine Learning Researcher,91410,CAD,114263,MI,FL,Canada,M,Canada,0,"GCP, Python, Spark",PhD,2,Transportation,2024-02-11,2024-04-24,1107,5.9,AI Innovations -AI05344,Data Engineer,217295,USD,217295,EX,FL,United States,L,United States,50,"TensorFlow, Java, Scala",Associate,14,Education,2024-01-27,2024-02-23,1243,9.1,Future Systems -AI05345,AI Consultant,65815,AUD,88850,EN,PT,Australia,L,Kenya,50,"Scala, AWS, Git, Computer Vision, Azure",Bachelor,0,Consulting,2025-04-07,2025-05-17,2254,5.6,TechCorp Inc -AI05346,Research Scientist,185973,SGD,241765,EX,CT,Singapore,S,Singapore,0,"NLP, Deep Learning, Git",Associate,13,Real Estate,2025-04-29,2025-06-08,940,5.5,DeepTech Ventures -AI05347,Principal Data Scientist,113175,USD,113175,SE,PT,Finland,S,Finland,100,"TensorFlow, Deep Learning, PyTorch, MLOps, Hadoop",Master,7,Government,2024-08-28,2024-10-29,722,8.4,DeepTech Ventures -AI05348,Deep Learning Engineer,198579,USD,198579,EX,FT,Denmark,S,Denmark,50,"Data Visualization, Docker, Spark, Python, Java",Master,14,Healthcare,2025-03-29,2025-06-08,1705,8.2,Smart Analytics -AI05349,Machine Learning Researcher,25817,USD,25817,EN,CT,India,M,India,0,"MLOps, Scala, Linux, Azure",Bachelor,0,Media,2025-04-08,2025-04-23,1618,7.7,DeepTech Ventures -AI05350,Head of AI,81249,USD,81249,MI,CT,Sweden,M,Ukraine,50,"Computer Vision, R, GCP",Associate,3,Manufacturing,2024-04-08,2024-06-07,1936,9.5,Autonomous Tech -AI05351,Data Analyst,107111,AUD,144600,SE,CT,Australia,S,Australia,100,"Python, Docker, Linux, Statistics, GCP",Associate,7,Finance,2024-06-22,2024-09-01,671,5,Digital Transformation LLC -AI05352,AI Software Engineer,158552,USD,158552,SE,CT,Norway,M,United Kingdom,0,"Git, Python, GCP",Bachelor,7,Technology,2024-11-25,2025-01-14,2214,7.6,TechCorp Inc -AI05353,Autonomous Systems Engineer,209929,USD,209929,EX,CT,United States,M,United States,0,"Azure, Python, Spark, GCP",PhD,14,Transportation,2024-11-24,2025-02-01,1931,5.2,DeepTech Ventures -AI05354,AI Research Scientist,288133,GBP,216100,EX,CT,United Kingdom,L,United Kingdom,0,"Scala, Data Visualization, AWS, Computer Vision",Master,13,Real Estate,2025-02-02,2025-03-05,1068,8.8,Advanced Robotics -AI05355,Head of AI,243777,JPY,26815470,EX,FT,Japan,M,Japan,50,"Mathematics, R, NLP, Linux, SQL",Bachelor,13,Gaming,2025-01-29,2025-02-24,2295,7.8,Digital Transformation LLC -AI05356,Data Engineer,54043,AUD,72958,EN,FT,Australia,M,Germany,50,"Kubernetes, Deep Learning, Git, Hadoop",Associate,0,Manufacturing,2024-02-20,2024-03-05,855,9.4,Cognitive Computing -AI05357,Data Analyst,82069,USD,82069,MI,FL,Ireland,M,Ireland,100,"MLOps, PyTorch, TensorFlow",Associate,3,Retail,2025-01-27,2025-02-28,1505,9.7,Advanced Robotics -AI05358,ML Ops Engineer,65179,USD,65179,MI,CT,Ireland,S,Ireland,50,"SQL, Hadoop, Tableau",PhD,3,Telecommunications,2024-03-09,2024-04-08,2284,5.1,Future Systems -AI05359,AI Specialist,162962,USD,162962,SE,PT,Sweden,L,Poland,0,"Spark, Scala, PyTorch, NLP, GCP",Bachelor,8,Healthcare,2025-02-14,2025-04-26,1367,5.9,Smart Analytics -AI05360,AI Specialist,91928,USD,91928,EX,FT,China,L,China,50,"PyTorch, Scala, Tableau, Linux, NLP",Master,10,Government,2025-04-12,2025-05-07,1517,6.3,DeepTech Ventures -AI05361,AI Architect,134846,USD,134846,SE,PT,United States,M,United States,100,"PyTorch, Git, MLOps, SQL, Java",Master,6,Retail,2024-08-29,2024-09-13,1153,9.9,DataVision Ltd -AI05362,Data Analyst,22186,USD,22186,EN,PT,India,L,Spain,0,"Computer Vision, TensorFlow, NLP, SQL, Mathematics",Bachelor,1,Retail,2024-04-13,2024-06-15,512,8,Quantum Computing Inc -AI05363,Research Scientist,61335,USD,61335,SE,PT,China,L,China,0,"Java, PyTorch, Statistics",Associate,9,Retail,2024-03-05,2024-03-26,733,8.9,TechCorp Inc -AI05364,AI Specialist,246778,EUR,209761,EX,FT,Germany,L,New Zealand,100,"Kubernetes, PyTorch, NLP, TensorFlow",Master,15,Gaming,2025-01-20,2025-03-28,506,5.1,Quantum Computing Inc -AI05365,AI Architect,104343,GBP,78257,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Data Visualization, Java, GCP",Master,3,Retail,2024-05-21,2024-08-01,812,7.3,Autonomous Tech -AI05366,AI Architect,130307,USD,130307,MI,PT,Denmark,L,Denmark,50,"Linux, AWS, Java",PhD,2,Telecommunications,2024-08-05,2024-10-08,1924,6.6,DeepTech Ventures -AI05367,Computer Vision Engineer,83046,USD,83046,EN,FL,Norway,S,Norway,50,"SQL, Linux, Git, PyTorch, Deep Learning",Master,0,Retail,2025-03-05,2025-05-15,2443,6.4,Digital Transformation LLC -AI05368,AI Specialist,157446,USD,157446,MI,PT,Norway,L,Norway,100,"MLOps, Python, Tableau, Kubernetes, Data Visualization",Master,3,Healthcare,2024-08-29,2024-10-25,1804,5.7,Cognitive Computing -AI05369,Machine Learning Researcher,297092,JPY,32680120,EX,FL,Japan,L,Japan,0,"Spark, GCP, Python, Mathematics",Associate,16,Finance,2024-08-07,2024-10-07,989,8.6,Future Systems -AI05370,AI Product Manager,68384,USD,68384,MI,CT,Finland,S,Finland,100,"Python, Linux, MLOps, Kubernetes, TensorFlow",Master,2,Transportation,2025-01-17,2025-03-14,1050,6.4,DataVision Ltd -AI05371,ML Ops Engineer,92089,USD,92089,EX,FL,India,L,India,50,"Docker, Hadoop, SQL, Azure, Java",PhD,17,Automotive,2024-08-13,2024-09-04,764,6,Neural Networks Co -AI05372,Deep Learning Engineer,136227,EUR,115793,SE,FT,Netherlands,L,Netherlands,0,"Statistics, Scala, Deep Learning",PhD,6,Healthcare,2024-01-01,2024-02-29,1685,9.2,Neural Networks Co -AI05373,AI Product Manager,129513,USD,129513,SE,PT,Ireland,M,Australia,100,"Python, Docker, Mathematics",PhD,7,Government,2024-10-18,2024-11-29,1009,7.8,Cloud AI Solutions -AI05374,AI Specialist,135626,USD,135626,SE,PT,Israel,M,Vietnam,50,"Scala, Hadoop, Computer Vision, Deep Learning",PhD,7,Manufacturing,2025-03-27,2025-06-08,1852,8,Advanced Robotics -AI05375,AI Specialist,43215,USD,43215,SE,FL,China,S,Hungary,50,"PyTorch, Python, Linux",Master,9,Energy,2024-08-16,2024-10-05,714,8.1,Smart Analytics -AI05376,AI Research Scientist,70887,EUR,60254,MI,FT,Germany,S,Germany,50,"Python, Java, AWS, Scala, SQL",Associate,4,Retail,2025-02-15,2025-04-17,610,5.4,Smart Analytics -AI05377,ML Ops Engineer,288695,CHF,259826,EX,PT,Switzerland,L,Switzerland,0,"Spark, Linux, Statistics, Mathematics",Master,16,Transportation,2024-03-12,2024-05-19,1570,6,TechCorp Inc -AI05378,Data Engineer,85081,CHF,76573,EN,FT,Switzerland,S,Nigeria,50,"Java, PyTorch, AWS",PhD,1,Energy,2025-03-16,2025-05-10,1736,5.3,Advanced Robotics -AI05379,NLP Engineer,111446,USD,111446,MI,CT,Israel,L,Israel,100,"Spark, MLOps, Scala, AWS",Master,4,Energy,2024-06-17,2024-07-13,513,7.5,Predictive Systems -AI05380,Data Analyst,66898,USD,66898,MI,CT,Israel,S,Israel,50,"Git, Spark, R, PyTorch",Master,3,Gaming,2024-12-01,2025-01-02,1269,6.9,Predictive Systems -AI05381,AI Product Manager,37660,USD,37660,EN,FL,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-07-28,2024-09-17,835,8.5,Neural Networks Co -AI05382,Autonomous Systems Engineer,79062,EUR,67203,EN,PT,Netherlands,L,Finland,50,"NLP, SQL, TensorFlow, Scala, PyTorch",Master,0,Healthcare,2024-07-06,2024-08-07,2128,9.7,Predictive Systems -AI05383,Deep Learning Engineer,125125,SGD,162663,MI,PT,Singapore,L,Singapore,0,"Java, Git, Tableau, Scala",PhD,4,Healthcare,2024-03-03,2024-04-17,1935,6,Advanced Robotics -AI05384,Research Scientist,137554,JPY,15130940,SE,FT,Japan,M,Japan,0,"Data Visualization, Kubernetes, Computer Vision",Bachelor,8,Transportation,2024-09-23,2024-11-04,812,6.2,DeepTech Ventures -AI05385,AI Specialist,95923,EUR,81535,MI,FT,France,M,France,0,"NLP, Git, Mathematics",Associate,2,Transportation,2024-11-03,2024-11-21,667,9.2,DeepTech Ventures -AI05386,Autonomous Systems Engineer,126145,GBP,94609,SE,PT,United Kingdom,L,United Kingdom,50,"Git, Mathematics, NLP",PhD,7,Media,2024-01-15,2024-02-29,1112,6.3,Machine Intelligence Group -AI05387,Principal Data Scientist,98692,USD,98692,SE,PT,Ireland,S,Ireland,0,"Deep Learning, Scala, Computer Vision",Bachelor,5,Gaming,2025-02-02,2025-04-09,1354,6.7,Algorithmic Solutions -AI05388,Head of AI,200999,EUR,170849,EX,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Computer Vision, PyTorch, Git",Master,16,Consulting,2025-03-29,2025-04-29,1230,6.6,Future Systems -AI05389,Head of AI,54737,GBP,41053,EN,CT,United Kingdom,M,South Africa,50,"Python, Kubernetes, Scala",Associate,1,Telecommunications,2024-12-10,2025-01-01,2060,9.6,Quantum Computing Inc -AI05390,Machine Learning Engineer,202067,SGD,262687,EX,FT,Singapore,M,Brazil,100,"R, Scala, Python",Associate,18,Technology,2024-09-02,2024-09-17,2350,7.9,Neural Networks Co -AI05391,AI Research Scientist,247645,CAD,309556,EX,PT,Canada,L,Canada,100,"R, Mathematics, Python, Statistics",Associate,12,Gaming,2024-06-08,2024-07-02,935,8,Future Systems -AI05392,Data Engineer,136820,GBP,102615,SE,PT,United Kingdom,L,United Kingdom,100,"TensorFlow, Tableau, Computer Vision, Scala",Master,9,Real Estate,2025-03-27,2025-05-27,1477,6.5,Machine Intelligence Group -AI05393,Robotics Engineer,118345,USD,118345,EX,PT,Israel,S,Israel,0,"MLOps, Data Visualization, Linux, Docker, GCP",Associate,15,Media,2024-02-13,2024-04-18,1177,9.5,Neural Networks Co -AI05394,Computer Vision Engineer,86939,JPY,9563290,EN,CT,Japan,L,Japan,100,"Kubernetes, R, Hadoop, SQL, Deep Learning",PhD,1,Automotive,2024-08-14,2024-09-28,1232,7.2,Digital Transformation LLC -AI05395,Research Scientist,85462,JPY,9400820,EN,PT,Japan,M,Japan,100,"Kubernetes, Docker, NLP, Statistics, GCP",Associate,0,Government,2025-02-25,2025-04-11,1813,6.4,Algorithmic Solutions -AI05396,AI Research Scientist,75148,CHF,67633,EN,FL,Switzerland,M,Colombia,0,"NLP, Java, Kubernetes, Git",Master,1,Gaming,2025-01-14,2025-02-08,1792,10,Machine Intelligence Group -AI05397,Principal Data Scientist,253163,USD,253163,EX,FL,Denmark,L,Denmark,50,"TensorFlow, Git, Data Visualization",PhD,19,Real Estate,2024-06-06,2024-08-16,1330,5.2,TechCorp Inc -AI05398,AI Architect,30114,USD,30114,EN,FL,China,L,Finland,100,"Statistics, PyTorch, Java, Azure, TensorFlow",Master,1,Telecommunications,2024-11-16,2025-01-19,2090,8,Smart Analytics -AI05399,Computer Vision Engineer,176415,USD,176415,EX,CT,Finland,M,Finland,0,"GCP, NLP, Deep Learning, Spark",PhD,12,Telecommunications,2025-02-20,2025-04-21,1544,8.9,TechCorp Inc -AI05400,AI Specialist,73489,EUR,62466,MI,FT,Germany,M,Germany,50,"SQL, Java, Spark, TensorFlow, R",Associate,4,Automotive,2024-06-02,2024-07-03,2185,8.2,TechCorp Inc -AI05401,ML Ops Engineer,115294,USD,115294,SE,FT,Finland,M,Canada,100,"Azure, MLOps, Scala",Master,7,Real Estate,2024-03-21,2024-04-21,1538,7.8,Neural Networks Co -AI05402,Data Engineer,74479,SGD,96823,EN,FL,Singapore,L,Singapore,100,"SQL, Python, Statistics, Git",Associate,0,Gaming,2024-11-10,2024-12-01,1859,7.7,Smart Analytics -AI05403,AI Software Engineer,97495,USD,97495,SE,FT,Sweden,S,Sweden,0,"Spark, Git, Scala, Computer Vision",Associate,8,Government,2024-09-29,2024-11-25,899,6.9,DeepTech Ventures -AI05404,Principal Data Scientist,63891,USD,63891,EN,FL,Norway,S,Norway,100,"MLOps, SQL, Scala, GCP, Python",Associate,0,Manufacturing,2024-05-15,2024-06-09,1557,6.1,Smart Analytics -AI05405,Data Analyst,49339,CAD,61674,EN,PT,Canada,S,Canada,50,"Kubernetes, MLOps, Git, NLP, Scala",Master,1,Transportation,2024-05-21,2024-06-05,1652,6.6,Advanced Robotics -AI05406,Autonomous Systems Engineer,114592,USD,114592,EX,FL,China,L,Estonia,0,"Scala, NLP, Kubernetes",Master,12,Media,2024-04-14,2024-06-26,967,5.2,DataVision Ltd -AI05407,Data Scientist,44734,USD,44734,SE,FT,India,M,India,50,"NLP, MLOps, Scala, Python, Java",Master,6,Media,2024-11-01,2024-12-12,2496,7.7,Predictive Systems -AI05408,AI Architect,191311,USD,191311,EX,FL,Israel,S,Israel,50,"SQL, Kubernetes, GCP",Master,14,Consulting,2025-03-28,2025-04-21,873,8.3,Predictive Systems -AI05409,Data Engineer,198417,USD,198417,EX,FT,Finland,L,Switzerland,0,"Statistics, Kubernetes, Spark, R",Bachelor,16,Consulting,2024-05-20,2024-07-21,2466,9,Quantum Computing Inc -AI05410,AI Specialist,104925,JPY,11541750,SE,PT,Japan,S,Nigeria,0,"Git, MLOps, Scala, Python",Master,6,Media,2024-04-10,2024-05-05,2391,7.8,Neural Networks Co -AI05411,Research Scientist,221209,EUR,188028,EX,FT,Austria,L,Austria,0,"PyTorch, Data Visualization, MLOps",Bachelor,12,Technology,2024-02-28,2024-04-13,1267,8.2,TechCorp Inc -AI05412,NLP Engineer,85694,EUR,72840,MI,FT,Austria,S,Austria,0,"PyTorch, TensorFlow, MLOps, Hadoop, Python",PhD,3,Technology,2025-02-15,2025-04-14,1832,8.5,Neural Networks Co -AI05413,Research Scientist,148534,USD,148534,SE,FT,United States,S,United States,0,"R, Scala, SQL, Azure",PhD,9,Energy,2024-11-06,2025-01-16,1625,5.3,Neural Networks Co -AI05414,Machine Learning Engineer,79799,USD,79799,MI,FT,Israel,L,Israel,0,"Mathematics, AWS, NLP, PyTorch",Master,2,Manufacturing,2024-02-27,2024-04-09,1588,5.1,DataVision Ltd -AI05415,Robotics Engineer,42345,USD,42345,MI,PT,China,S,China,100,"Python, TensorFlow, Deep Learning, Tableau, Azure",Associate,4,Media,2024-06-02,2024-07-11,1265,9.9,Quantum Computing Inc -AI05416,Deep Learning Engineer,120846,CHF,108761,MI,CT,Switzerland,L,Egypt,50,"PyTorch, Java, TensorFlow, Docker",Master,3,Telecommunications,2024-06-09,2024-08-03,1725,6,Algorithmic Solutions -AI05417,AI Specialist,23612,USD,23612,EN,FL,India,S,Thailand,50,"SQL, Kubernetes, Tableau, Git",Associate,1,Gaming,2024-08-18,2024-09-06,2269,8,Autonomous Tech -AI05418,Deep Learning Engineer,166613,GBP,124960,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, Tableau, PyTorch, Data Visualization",Master,12,Technology,2024-06-03,2024-06-28,1513,9.9,Machine Intelligence Group -AI05419,Principal Data Scientist,56615,AUD,76430,EN,CT,Australia,M,Australia,100,"Spark, Statistics, Computer Vision, Python, MLOps",PhD,0,Telecommunications,2025-04-20,2025-06-26,1809,5.8,Algorithmic Solutions -AI05420,AI Specialist,78519,AUD,106001,MI,FT,Australia,M,Australia,100,"TensorFlow, Kubernetes, Computer Vision, Docker",PhD,4,Consulting,2024-04-30,2024-06-08,1672,6,DeepTech Ventures -AI05421,Data Engineer,176102,CAD,220128,EX,FT,Canada,S,Canada,50,"Kubernetes, Docker, AWS",PhD,11,Media,2025-01-11,2025-03-05,2408,9.4,Cognitive Computing -AI05422,AI Product Manager,39202,USD,39202,MI,CT,China,L,China,100,"NLP, Docker, Azure, Hadoop",Bachelor,3,Gaming,2024-09-17,2024-10-20,2380,9.3,Machine Intelligence Group -AI05423,Machine Learning Engineer,52424,USD,52424,EN,CT,Finland,S,Finland,100,"R, Kubernetes, Java, SQL, Docker",Associate,1,Energy,2025-03-03,2025-04-26,1801,6.4,Smart Analytics -AI05424,AI Research Scientist,74687,SGD,97093,EN,PT,Singapore,S,United States,0,"AWS, Tableau, Docker, Computer Vision",PhD,1,Consulting,2025-03-08,2025-04-02,2295,8,Algorithmic Solutions -AI05425,Computer Vision Engineer,231540,CAD,289425,EX,PT,Canada,L,Canada,100,"Java, Kubernetes, Hadoop, Mathematics, Scala",Associate,12,Education,2025-03-21,2025-04-29,2222,7.1,Neural Networks Co -AI05426,Data Analyst,156641,USD,156641,SE,FT,Norway,S,China,50,"Statistics, TensorFlow, Python, GCP",PhD,6,Transportation,2024-12-20,2025-01-20,717,9.2,TechCorp Inc -AI05427,Data Engineer,119985,CAD,149981,SE,FT,Canada,M,Canada,100,"Git, Deep Learning, Hadoop, NLP, Kubernetes",Associate,9,Transportation,2024-09-07,2024-10-07,1933,9.6,Advanced Robotics -AI05428,Autonomous Systems Engineer,131450,AUD,177458,EX,FT,Australia,S,Australia,100,"Hadoop, Linux, Computer Vision, Deep Learning, Kubernetes",PhD,11,Telecommunications,2024-05-02,2024-06-20,962,8.7,Digital Transformation LLC -AI05429,Machine Learning Engineer,179649,CAD,224561,EX,CT,Canada,M,Canada,50,"Linux, Kubernetes, Data Visualization, AWS",PhD,16,Manufacturing,2024-02-14,2024-03-31,1284,6.3,DeepTech Ventures -AI05430,Deep Learning Engineer,113259,EUR,96270,SE,PT,Austria,L,Switzerland,50,"Java, TensorFlow, Azure, Computer Vision",Bachelor,9,Automotive,2024-07-16,2024-09-04,514,8,Predictive Systems -AI05431,Head of AI,90625,CAD,113281,MI,CT,Canada,M,Canada,50,"SQL, Hadoop, R, Java, Python",Bachelor,4,Consulting,2024-04-19,2024-07-01,2289,7.7,Digital Transformation LLC -AI05432,Computer Vision Engineer,115445,USD,115445,MI,FL,Ireland,L,Ireland,100,"AWS, Hadoop, Data Visualization",Bachelor,2,Gaming,2024-09-10,2024-10-03,1925,5.1,Predictive Systems -AI05433,Deep Learning Engineer,82908,EUR,70472,MI,FL,Austria,S,Austria,0,"Python, Spark, SQL, Hadoop, Mathematics",Associate,4,Transportation,2025-02-06,2025-03-17,2093,8.2,Machine Intelligence Group -AI05434,Machine Learning Engineer,104007,CHF,93606,EN,CT,Switzerland,L,India,0,"Python, Scala, Data Visualization, Hadoop, Linux",PhD,0,Finance,2024-09-04,2024-10-11,1160,5.5,Smart Analytics -AI05435,Research Scientist,90940,AUD,122769,MI,PT,Australia,M,Australia,50,"Hadoop, Python, GCP",Bachelor,3,Media,2024-01-04,2024-03-13,2095,5.1,Digital Transformation LLC -AI05436,AI Product Manager,28492,USD,28492,EN,FT,China,L,China,50,"Python, SQL, Statistics",Associate,1,Healthcare,2024-08-08,2024-09-20,2004,7.6,Future Systems -AI05437,ML Ops Engineer,84521,CHF,76069,EN,FL,Switzerland,S,Switzerland,100,"Git, AWS, Kubernetes, MLOps, Tableau",PhD,0,Media,2025-04-01,2025-06-07,740,7.9,Smart Analytics -AI05438,AI Software Engineer,125527,USD,125527,SE,PT,Finland,L,Argentina,0,"PyTorch, Kubernetes, Docker",Associate,6,Gaming,2024-01-20,2024-03-14,1985,8.9,Cognitive Computing -AI05439,Machine Learning Researcher,98155,SGD,127602,MI,FL,Singapore,S,Singapore,0,"Spark, NLP, Python, TensorFlow, Data Visualization",Associate,2,Finance,2025-03-10,2025-04-13,1473,6.1,Smart Analytics -AI05440,Computer Vision Engineer,54723,SGD,71140,EN,FT,Singapore,M,Singapore,0,"SQL, Git, Hadoop, PyTorch, AWS",Master,0,Real Estate,2024-08-14,2024-10-17,1181,6.8,Machine Intelligence Group -AI05441,AI Research Scientist,132179,GBP,99134,SE,FT,United Kingdom,L,United Kingdom,50,"Python, Linux, Deep Learning, Scala",Associate,9,Manufacturing,2025-02-05,2025-03-02,954,7.6,Smart Analytics -AI05442,Data Engineer,99414,JPY,10935540,MI,CT,Japan,S,South Africa,100,"SQL, Kubernetes, Linux, Hadoop",Associate,2,Real Estate,2025-03-25,2025-05-29,1582,6.3,Predictive Systems -AI05443,Computer Vision Engineer,162201,USD,162201,SE,PT,Israel,L,Ireland,50,"NLP, Azure, Hadoop, Python",PhD,6,Finance,2024-02-02,2024-03-30,1047,9.2,Digital Transformation LLC -AI05444,Data Engineer,61351,USD,61351,EN,PT,Israel,L,Israel,50,"AWS, GCP, MLOps, PyTorch, SQL",Master,0,Gaming,2024-09-01,2024-09-15,2430,8.2,Advanced Robotics -AI05445,Machine Learning Engineer,23989,USD,23989,EN,FL,India,S,India,100,"SQL, R, PyTorch, NLP, Computer Vision",Bachelor,1,Automotive,2024-10-13,2024-11-17,1139,9.5,DataVision Ltd -AI05446,Robotics Engineer,65446,USD,65446,MI,CT,Finland,S,Finland,50,"Python, Git, Mathematics",PhD,3,Education,2024-03-30,2024-04-19,879,6,Predictive Systems -AI05447,ML Ops Engineer,160753,USD,160753,MI,FL,Denmark,L,Denmark,100,"Tableau, Docker, Hadoop, MLOps, GCP",Bachelor,2,Telecommunications,2024-07-31,2024-09-15,1572,7.3,Cloud AI Solutions -AI05448,ML Ops Engineer,159740,AUD,215649,SE,CT,Australia,L,Australia,100,"GCP, Spark, PyTorch",Bachelor,5,Telecommunications,2024-05-29,2024-07-11,1719,5.4,Future Systems -AI05449,Research Scientist,86339,EUR,73388,EN,PT,Austria,L,Austria,100,"Data Visualization, Python, Git, TensorFlow",PhD,1,Manufacturing,2024-01-24,2024-04-03,2369,7.3,Machine Intelligence Group -AI05450,Principal Data Scientist,223810,USD,223810,EX,PT,Israel,M,New Zealand,100,"Statistics, Data Visualization, Python",Bachelor,13,Gaming,2024-08-06,2024-10-18,1937,10,Algorithmic Solutions -AI05451,Robotics Engineer,156078,EUR,132666,EX,FT,Austria,M,Austria,0,"Java, Hadoop, R, AWS",Bachelor,13,Finance,2024-08-23,2024-10-31,1683,9.4,Algorithmic Solutions -AI05452,Principal Data Scientist,95770,CHF,86193,EN,PT,Switzerland,M,Switzerland,100,"Kubernetes, Hadoop, Data Visualization",Bachelor,0,Government,2024-05-12,2024-07-06,1591,9.7,Predictive Systems -AI05453,Deep Learning Engineer,94666,JPY,10413260,EN,FT,Japan,L,Japan,50,"Mathematics, Spark, Python, TensorFlow, PyTorch",Bachelor,1,Consulting,2025-03-27,2025-05-14,2335,7.4,Digital Transformation LLC -AI05454,AI Software Engineer,74801,SGD,97241,EN,FL,Singapore,L,Philippines,50,"Git, GCP, Docker, Mathematics",Associate,0,Manufacturing,2025-02-20,2025-04-28,1151,6.9,Digital Transformation LLC -AI05455,Research Scientist,106506,EUR,90530,SE,FT,Austria,S,Austria,0,"Linux, R, Git",PhD,8,Transportation,2024-05-18,2024-07-12,734,9.2,Neural Networks Co -AI05456,Computer Vision Engineer,150029,SGD,195038,SE,FL,Singapore,L,Singapore,100,"GCP, Kubernetes, Java",Associate,7,Manufacturing,2025-01-24,2025-03-15,1856,7.4,Autonomous Tech -AI05457,NLP Engineer,200851,USD,200851,SE,FT,United States,L,Switzerland,50,"GCP, AWS, PyTorch",Bachelor,5,Transportation,2024-12-15,2025-01-10,2386,7,DeepTech Ventures -AI05458,Machine Learning Researcher,99863,GBP,74897,MI,PT,United Kingdom,S,United Kingdom,0,"AWS, Git, Spark",PhD,2,Transportation,2024-11-26,2024-12-29,2303,7.6,Digital Transformation LLC -AI05459,Head of AI,39799,USD,39799,SE,PT,India,S,Kenya,50,"Computer Vision, SQL, Kubernetes, GCP",Associate,5,Manufacturing,2024-07-26,2024-09-30,1362,7,AI Innovations -AI05460,Data Engineer,96455,USD,96455,MI,PT,Denmark,S,Italy,50,"Statistics, Kubernetes, Linux, SQL, Data Visualization",PhD,4,Education,2024-07-24,2024-09-05,1910,6.3,Algorithmic Solutions -AI05461,Data Analyst,158698,USD,158698,EX,PT,South Korea,S,South Korea,50,"Scala, R, MLOps, Spark",Associate,19,Telecommunications,2024-03-25,2024-04-10,1132,6.3,Future Systems -AI05462,Machine Learning Researcher,180104,EUR,153088,EX,FT,Germany,M,Germany,0,"R, GCP, Git, Statistics",PhD,11,Government,2025-01-04,2025-02-09,2103,6.5,Autonomous Tech -AI05463,ML Ops Engineer,60136,EUR,51116,EN,PT,Netherlands,M,Netherlands,50,"SQL, Linux, AWS",PhD,0,Healthcare,2024-05-23,2024-08-01,691,9.7,Advanced Robotics -AI05464,AI Product Manager,183029,USD,183029,EX,FL,Israel,S,Israel,100,"Scala, TensorFlow, Tableau, MLOps, Kubernetes",Bachelor,19,Manufacturing,2024-01-05,2024-01-23,1507,6.7,Machine Intelligence Group -AI05465,AI Product Manager,114370,EUR,97215,MI,FL,Netherlands,M,Romania,50,"Linux, Kubernetes, Statistics, Python",Master,4,Retail,2025-02-19,2025-03-14,1343,8.5,AI Innovations -AI05466,Head of AI,54599,USD,54599,MI,CT,China,L,Netherlands,100,"Statistics, Docker, Python",Bachelor,2,Gaming,2024-04-23,2024-07-02,1436,6.1,Cloud AI Solutions -AI05467,AI Consultant,149215,EUR,126833,EX,CT,Germany,S,Germany,100,"TensorFlow, Deep Learning, Computer Vision, Tableau, SQL",PhD,12,Technology,2024-09-30,2024-11-10,1897,7,AI Innovations -AI05468,Data Analyst,36117,USD,36117,MI,FT,China,S,China,0,"Python, Azure, SQL, R, Mathematics",PhD,2,Consulting,2024-06-03,2024-07-28,1999,5.4,Cognitive Computing -AI05469,NLP Engineer,58126,EUR,49407,EN,PT,Austria,L,Philippines,100,"Python, SQL, Tableau, AWS, Kubernetes",Master,0,Finance,2025-03-17,2025-05-04,1896,5.7,Advanced Robotics -AI05470,AI Specialist,72607,AUD,98019,MI,CT,Australia,M,Australia,0,"Python, TensorFlow, AWS",Master,2,Real Estate,2025-02-11,2025-03-01,1088,7.4,TechCorp Inc -AI05471,Data Analyst,71757,CAD,89696,MI,FL,Canada,S,Kenya,0,"Statistics, PyTorch, Computer Vision, R, Git",Master,2,Media,2024-03-01,2024-04-26,2146,6.5,Future Systems -AI05472,Deep Learning Engineer,105689,EUR,89836,SE,FL,Germany,M,Germany,50,"R, Kubernetes, Mathematics, NLP",Master,9,Real Estate,2024-11-28,2025-01-13,758,5.1,Quantum Computing Inc -AI05473,Head of AI,42540,USD,42540,MI,FL,India,L,Egypt,100,"Python, Data Visualization, R, Spark, Java",PhD,2,Healthcare,2024-03-08,2024-04-06,1622,5.5,Digital Transformation LLC -AI05474,AI Architect,123577,EUR,105040,EX,FT,Austria,S,Portugal,0,"Python, R, NLP",PhD,12,Government,2024-10-17,2024-12-03,1020,6.6,Machine Intelligence Group -AI05475,AI Architect,236155,CAD,295194,EX,FT,Canada,L,Canada,0,"Scala, Spark, SQL",Master,16,Retail,2024-08-16,2024-09-26,1079,5,TechCorp Inc -AI05476,Machine Learning Engineer,70398,EUR,59838,EN,CT,Austria,L,Romania,100,"PyTorch, Spark, SQL, Mathematics",Master,1,Healthcare,2024-09-24,2024-11-20,1778,8,Machine Intelligence Group -AI05477,Data Scientist,146441,USD,146441,EX,FT,Israel,S,Israel,100,"AWS, Scala, Data Visualization, Java",Master,18,Technology,2024-11-13,2024-11-30,551,8.3,Machine Intelligence Group -AI05478,AI Specialist,47127,USD,47127,SE,CT,India,M,India,0,"Statistics, Azure, Git",PhD,6,Finance,2025-01-31,2025-03-17,1325,8,Algorithmic Solutions -AI05479,AI Product Manager,142445,EUR,121078,EX,FT,Austria,M,Austria,0,"Java, Tableau, Docker, Statistics",Master,10,Telecommunications,2024-05-10,2024-06-08,1295,7.5,Advanced Robotics -AI05480,AI Consultant,67586,USD,67586,SE,FL,China,M,China,0,"Mathematics, MLOps, Python, PyTorch, Tableau",PhD,9,Automotive,2025-04-26,2025-06-04,1573,5.5,Smart Analytics -AI05481,Research Scientist,176023,USD,176023,SE,FL,Denmark,S,Denmark,0,"Azure, SQL, Python, Kubernetes, Deep Learning",PhD,6,Real Estate,2024-07-26,2024-09-18,749,6.7,Advanced Robotics -AI05482,Machine Learning Engineer,21634,USD,21634,EN,FT,China,S,China,100,"Azure, SQL, R, Mathematics",Associate,1,Consulting,2024-09-26,2024-12-04,1237,9.1,Digital Transformation LLC -AI05483,ML Ops Engineer,105516,USD,105516,SE,FT,South Korea,S,Malaysia,50,"Azure, SQL, GCP",Associate,9,Technology,2024-07-31,2024-08-27,2063,7.3,Digital Transformation LLC -AI05484,Research Scientist,144381,USD,144381,EX,PT,Ireland,M,Ireland,0,"R, SQL, Docker",PhD,17,Telecommunications,2024-03-27,2024-04-28,1007,9,Advanced Robotics -AI05485,Deep Learning Engineer,76971,USD,76971,MI,FT,Israel,S,Belgium,0,"Python, Scala, Deep Learning",Associate,3,Automotive,2024-07-08,2024-07-26,1221,6.3,DeepTech Ventures -AI05486,AI Research Scientist,69347,USD,69347,SE,FL,China,L,Austria,50,"Data Visualization, Computer Vision, TensorFlow",Associate,6,Retail,2024-09-16,2024-10-29,2123,5.3,Smart Analytics -AI05487,ML Ops Engineer,63587,JPY,6994570,EN,CT,Japan,S,Japan,50,"Computer Vision, PyTorch, Kubernetes, Java, Spark",Master,1,Finance,2025-01-01,2025-03-12,1372,9.2,Advanced Robotics -AI05488,AI Consultant,159882,EUR,135900,SE,CT,Germany,L,Finland,50,"PyTorch, Tableau, R, Data Visualization",Bachelor,9,Media,2024-11-26,2025-01-30,895,6,Predictive Systems -AI05489,Head of AI,63760,USD,63760,EN,FT,Ireland,M,Ireland,100,"Kubernetes, Python, Tableau",Master,0,Telecommunications,2024-12-18,2025-02-06,1750,9.6,Algorithmic Solutions -AI05490,AI Software Engineer,91323,JPY,10045530,MI,CT,Japan,S,Japan,0,"Linux, AWS, Python",Bachelor,3,Healthcare,2025-01-02,2025-03-10,2170,5.1,DataVision Ltd -AI05491,Principal Data Scientist,95852,SGD,124608,MI,CT,Singapore,S,Singapore,100,"TensorFlow, Azure, Git",Associate,2,Media,2024-04-18,2024-06-02,2250,9.5,Autonomous Tech -AI05492,AI Research Scientist,142643,USD,142643,EX,FT,Ireland,M,Germany,50,"Data Visualization, Statistics, Linux",PhD,19,Telecommunications,2024-09-19,2024-11-09,1075,8.6,Advanced Robotics -AI05493,AI Research Scientist,183011,USD,183011,EX,PT,Finland,S,Luxembourg,100,"SQL, MLOps, TensorFlow, AWS",Bachelor,18,Education,2025-01-01,2025-02-23,1368,5.2,Quantum Computing Inc -AI05494,AI Product Manager,60370,USD,60370,EN,PT,United States,S,United States,50,"NLP, R, Linux, SQL",PhD,0,Technology,2024-01-24,2024-03-07,1727,9.5,Future Systems -AI05495,AI Software Engineer,296283,JPY,32591130,EX,CT,Japan,L,Egypt,50,"Git, SQL, Computer Vision, Mathematics",PhD,13,Media,2024-07-26,2024-08-22,947,7.8,Neural Networks Co -AI05496,NLP Engineer,89935,JPY,9892850,EN,CT,Japan,L,Switzerland,100,"MLOps, Python, Computer Vision, Spark",Master,0,Government,2024-10-12,2024-11-04,2250,8.7,Future Systems -AI05497,Data Analyst,94666,CHF,85199,EN,CT,Switzerland,L,Switzerland,50,"Scala, Tableau, AWS, Computer Vision, TensorFlow",PhD,0,Media,2024-04-28,2024-05-24,1878,6.1,Neural Networks Co -AI05498,Machine Learning Engineer,86209,USD,86209,EN,CT,United States,M,United States,0,"Hadoop, Linux, SQL, NLP, Kubernetes",Bachelor,0,Real Estate,2025-01-12,2025-03-01,1116,8,Digital Transformation LLC -AI05499,Machine Learning Engineer,81814,GBP,61361,EN,FT,United Kingdom,M,United Kingdom,0,"Linux, Azure, Scala",Associate,1,Real Estate,2024-11-22,2024-12-06,1079,8.5,Predictive Systems -AI05500,Data Engineer,122880,EUR,104448,SE,FT,Austria,S,Japan,50,"Scala, Python, Data Visualization, Deep Learning, TensorFlow",PhD,5,Transportation,2024-03-02,2024-05-08,907,5.3,Smart Analytics -AI05501,Data Analyst,161377,CHF,145239,SE,PT,Switzerland,M,Switzerland,0,"Linux, Spark, TensorFlow, Python, Tableau",Associate,5,Government,2025-02-20,2025-03-31,900,9.9,Quantum Computing Inc -AI05502,AI Consultant,64242,JPY,7066620,EN,FL,Japan,S,Japan,0,"Computer Vision, Kubernetes, SQL",Bachelor,1,Real Estate,2024-09-25,2024-11-14,526,6,DeepTech Ventures -AI05503,Robotics Engineer,142995,EUR,121546,SE,CT,Netherlands,M,Ukraine,50,"Computer Vision, Statistics, Kubernetes",Bachelor,5,Government,2024-08-26,2024-10-05,1795,7.9,Autonomous Tech -AI05504,Autonomous Systems Engineer,108977,CAD,136221,SE,PT,Canada,S,Chile,50,"Azure, Computer Vision, NLP, SQL, Mathematics",PhD,7,Education,2025-04-17,2025-06-25,1497,5.4,Predictive Systems -AI05505,Deep Learning Engineer,32809,USD,32809,EN,PT,China,M,China,50,"Statistics, Python, Tableau, Docker, AWS",Bachelor,1,Transportation,2025-01-22,2025-03-08,1052,5.1,Machine Intelligence Group -AI05506,Computer Vision Engineer,236299,GBP,177224,EX,PT,United Kingdom,L,United Kingdom,0,"PyTorch, SQL, Data Visualization, Hadoop",Bachelor,13,Automotive,2024-05-20,2024-07-28,1337,9.6,Future Systems -AI05507,Machine Learning Engineer,133957,USD,133957,MI,CT,Norway,M,Norway,100,"Tableau, Kubernetes, Python, Deep Learning, Azure",Bachelor,3,Transportation,2024-04-29,2024-05-29,1599,8.3,AI Innovations -AI05508,Data Scientist,62909,GBP,47182,EN,PT,United Kingdom,L,United Kingdom,0,"Computer Vision, GCP, MLOps, Statistics, Deep Learning",Bachelor,0,Technology,2025-01-19,2025-03-07,928,8.7,Machine Intelligence Group -AI05509,Machine Learning Engineer,147022,SGD,191129,EX,CT,Singapore,S,Singapore,100,"SQL, PyTorch, NLP, Docker",PhD,15,Manufacturing,2024-12-03,2025-01-02,679,8.9,Neural Networks Co -AI05510,Machine Learning Engineer,144913,EUR,123176,SE,FL,France,L,France,50,"Data Visualization, Git, Spark, Computer Vision",Associate,8,Technology,2025-04-19,2025-06-05,578,8.9,Cognitive Computing -AI05511,AI Specialist,45877,USD,45877,SE,FT,India,M,India,0,"Python, Docker, GCP",PhD,7,Automotive,2024-08-28,2024-09-29,1780,9.7,Algorithmic Solutions -AI05512,Principal Data Scientist,33228,USD,33228,EN,FT,China,S,China,100,"Kubernetes, SQL, Git, Statistics",Associate,1,Media,2024-06-09,2024-07-03,642,6.8,Cloud AI Solutions -AI05513,Machine Learning Researcher,87357,USD,87357,MI,FL,South Korea,M,South Korea,0,"MLOps, Hadoop, NLP, Mathematics",Bachelor,2,Retail,2024-07-25,2024-09-09,1707,7.2,TechCorp Inc -AI05514,AI Product Manager,57116,USD,57116,EN,FT,Finland,M,Finland,100,"NLP, Java, Spark, Kubernetes",PhD,0,Real Estate,2024-06-16,2024-08-23,2471,8.4,Smart Analytics -AI05515,Machine Learning Engineer,67628,GBP,50721,EN,CT,United Kingdom,L,Philippines,0,"Kubernetes, Java, R, Deep Learning",PhD,1,Transportation,2024-04-22,2024-06-05,1168,6.2,Smart Analytics -AI05516,AI Specialist,51699,JPY,5686890,EN,PT,Japan,S,Japan,0,"Tableau, R, PyTorch",Master,0,Transportation,2024-12-30,2025-03-06,1456,6.5,Cloud AI Solutions -AI05517,AI Research Scientist,158696,USD,158696,EX,PT,Sweden,S,Singapore,0,"Git, TensorFlow, Computer Vision, Linux, Python",PhD,16,Automotive,2024-08-16,2024-09-28,1409,6.4,Predictive Systems -AI05518,AI Specialist,181010,EUR,153859,EX,CT,Austria,L,Austria,50,"Azure, Tableau, Python",Bachelor,18,Retail,2025-01-13,2025-01-31,1209,9.6,DeepTech Ventures -AI05519,ML Ops Engineer,143355,USD,143355,SE,FL,Ireland,M,United States,100,"Python, Kubernetes, NLP",Bachelor,8,Manufacturing,2025-03-02,2025-04-09,973,8.8,AI Innovations -AI05520,Data Scientist,94621,USD,94621,MI,CT,Israel,M,South Africa,100,"Data Visualization, Git, Linux, AWS",Master,2,Consulting,2024-09-25,2024-11-17,1804,6.1,Machine Intelligence Group -AI05521,Data Engineer,50440,USD,50440,SE,FT,China,M,China,100,"SQL, PyTorch, Mathematics, Git",Associate,6,Real Estate,2024-10-24,2024-11-17,1306,6.9,DeepTech Ventures -AI05522,Autonomous Systems Engineer,39850,USD,39850,MI,CT,China,L,China,50,"SQL, Computer Vision, Statistics",Master,4,Energy,2024-07-16,2024-08-30,1706,6.3,Neural Networks Co -AI05523,Data Analyst,129312,USD,129312,SE,CT,Finland,M,Finland,100,"Docker, MLOps, Python, Java, Tableau",PhD,9,Real Estate,2024-12-07,2025-02-11,2388,6.2,DeepTech Ventures -AI05524,ML Ops Engineer,262770,EUR,223355,EX,FT,France,L,Philippines,100,"Git, MLOps, Tableau, Scala, Kubernetes",Bachelor,11,Real Estate,2025-01-22,2025-03-31,942,9.9,Cognitive Computing -AI05525,Principal Data Scientist,95183,JPY,10470130,MI,FT,Japan,S,Japan,100,"Tableau, Python, AWS, TensorFlow, Deep Learning",Associate,3,Consulting,2024-07-23,2024-09-01,1428,9.6,Smart Analytics -AI05526,Data Analyst,40242,USD,40242,MI,PT,India,L,India,0,"PyTorch, Azure, Tableau, Kubernetes, TensorFlow",PhD,2,Telecommunications,2024-07-02,2024-07-24,1322,6.8,Autonomous Tech -AI05527,Machine Learning Researcher,164259,JPY,18068490,EX,FT,Japan,S,Colombia,100,"Docker, Kubernetes, NLP, PyTorch, TensorFlow",Associate,19,Gaming,2024-11-05,2024-11-27,2246,8.8,Advanced Robotics -AI05528,Machine Learning Engineer,102309,USD,102309,SE,FT,Finland,M,Finland,100,"Data Visualization, NLP, Python, Hadoop",Master,8,Education,2024-03-04,2024-05-11,939,7.1,Predictive Systems -AI05529,Head of AI,53973,USD,53973,EN,FL,Ireland,S,Thailand,0,"Python, TensorFlow, MLOps",PhD,0,Technology,2025-02-03,2025-03-05,611,7.2,Cognitive Computing -AI05530,AI Product Manager,54973,USD,54973,SE,FT,India,L,India,0,"Scala, Data Visualization, Azure, PyTorch",PhD,7,Automotive,2024-11-12,2024-12-08,1043,9.6,Digital Transformation LLC -AI05531,NLP Engineer,187522,USD,187522,EX,CT,Finland,S,Finland,0,"Scala, Linux, Spark, PyTorch, MLOps",Bachelor,10,Media,2024-11-27,2024-12-31,1802,7.4,Future Systems -AI05532,NLP Engineer,57683,EUR,49031,EN,CT,Austria,S,Austria,0,"R, GCP, Mathematics, Deep Learning",Bachelor,0,Finance,2024-04-04,2024-04-30,1641,5.4,Cloud AI Solutions -AI05533,AI Architect,78473,USD,78473,MI,FL,South Korea,L,South Korea,50,"Kubernetes, Deep Learning, R, Tableau",Bachelor,3,Automotive,2024-07-31,2024-10-03,1798,5.2,DataVision Ltd -AI05534,Computer Vision Engineer,55008,SGD,71510,EN,CT,Singapore,S,Portugal,100,"Mathematics, Azure, Computer Vision",Bachelor,1,Technology,2024-12-16,2025-02-20,1194,9.6,TechCorp Inc -AI05535,Computer Vision Engineer,76394,USD,76394,EN,FL,Norway,S,Norway,100,"Python, Computer Vision, SQL, Docker",PhD,0,Government,2024-01-16,2024-03-04,2400,8.2,Smart Analytics -AI05536,AI Research Scientist,102251,USD,102251,SE,CT,Finland,M,France,100,"MLOps, NLP, R, Data Visualization",Associate,6,Government,2025-01-07,2025-02-08,1801,6.7,Quantum Computing Inc -AI05537,Head of AI,225096,USD,225096,EX,FT,Ireland,L,Ireland,50,"PyTorch, AWS, TensorFlow, Mathematics, Scala",Master,15,Education,2024-05-01,2024-07-01,726,5.7,DeepTech Ventures -AI05538,Principal Data Scientist,204843,CHF,184359,SE,PT,Switzerland,L,Brazil,100,"PyTorch, Scala, Java",PhD,6,Finance,2025-01-06,2025-02-14,1120,7.8,TechCorp Inc -AI05539,Principal Data Scientist,138580,USD,138580,SE,CT,Norway,M,Norway,50,"R, SQL, PyTorch",Master,6,Education,2024-08-09,2024-10-11,944,6.5,DeepTech Ventures -AI05540,Head of AI,85499,EUR,72674,EN,FL,Netherlands,L,Netherlands,50,"PyTorch, TensorFlow, Hadoop",Associate,1,Finance,2024-03-02,2024-03-27,767,5.8,Algorithmic Solutions -AI05541,Machine Learning Researcher,83346,SGD,108350,EN,CT,Singapore,M,Singapore,100,"NLP, Kubernetes, TensorFlow, Docker",Master,0,Finance,2024-04-10,2024-05-23,723,9.1,DeepTech Ventures -AI05542,NLP Engineer,115766,USD,115766,MI,PT,Norway,S,Norway,50,"Tableau, SQL, Azure, PyTorch",PhD,2,Consulting,2024-08-11,2024-10-17,1493,7.2,DataVision Ltd -AI05543,Data Analyst,205113,USD,205113,SE,CT,Denmark,L,Denmark,50,"Java, Spark, NLP",PhD,7,Gaming,2025-03-18,2025-04-17,1640,7.7,AI Innovations -AI05544,AI Software Engineer,160912,USD,160912,SE,FT,Sweden,L,Sweden,100,"Git, GCP, Hadoop, Azure, Statistics",PhD,6,Finance,2024-02-27,2024-04-22,856,6,Predictive Systems -AI05545,AI Research Scientist,142229,USD,142229,SE,PT,Finland,L,Finland,50,"Statistics, Tableau, Computer Vision, Java, Python",Bachelor,6,Real Estate,2024-02-07,2024-03-19,1243,6,Predictive Systems -AI05546,Deep Learning Engineer,79913,USD,79913,MI,FT,Finland,S,Finland,0,"SQL, AWS, Scala",Bachelor,2,Gaming,2024-04-21,2024-05-21,1381,5.6,Digital Transformation LLC -AI05547,Data Scientist,105268,USD,105268,MI,CT,Denmark,M,Denmark,100,"Kubernetes, GCP, Mathematics, Computer Vision, Hadoop",Master,3,Telecommunications,2024-10-25,2024-12-11,1041,6.4,Neural Networks Co -AI05548,Research Scientist,222239,SGD,288911,EX,CT,Singapore,S,Singapore,100,"Spark, Python, R, Computer Vision",Master,11,Technology,2025-02-22,2025-03-08,1199,9.6,AI Innovations -AI05549,Computer Vision Engineer,95349,USD,95349,MI,PT,Sweden,S,Sweden,100,"R, Statistics, Hadoop",Master,3,Telecommunications,2024-05-08,2024-06-18,913,7.2,AI Innovations -AI05550,Machine Learning Engineer,276306,USD,276306,EX,CT,United States,L,United States,0,"TensorFlow, R, Azure",Associate,13,Government,2024-07-21,2024-09-08,880,7.6,DataVision Ltd -AI05551,Head of AI,86349,USD,86349,MI,FL,Finland,S,Finland,100,"Git, Java, Computer Vision, Mathematics, Spark",Master,2,Transportation,2024-06-24,2024-08-13,744,6.4,Autonomous Tech -AI05552,AI Product Manager,200534,USD,200534,EX,FT,United States,S,Luxembourg,50,"Linux, Kubernetes, Python, Mathematics",Bachelor,15,Manufacturing,2024-07-22,2024-09-01,1411,7.1,Autonomous Tech -AI05553,ML Ops Engineer,130848,GBP,98136,SE,PT,United Kingdom,M,United Kingdom,50,"Tableau, Spark, Python, Computer Vision",Associate,7,Transportation,2024-11-18,2025-01-19,506,8.6,Neural Networks Co -AI05554,ML Ops Engineer,137574,USD,137574,SE,FL,Denmark,M,Denmark,100,"Python, MLOps, Scala",Master,9,Gaming,2024-02-05,2024-03-25,2456,6,AI Innovations -AI05555,AI Research Scientist,64547,EUR,54865,MI,PT,France,S,France,100,"Data Visualization, SQL, Statistics",Bachelor,4,Real Estate,2024-10-06,2024-11-08,1689,5.6,Cloud AI Solutions -AI05556,AI Specialist,220582,CHF,198524,SE,FL,Switzerland,L,Switzerland,50,"Data Visualization, Python, Hadoop, MLOps, TensorFlow",Master,9,Education,2025-04-29,2025-05-30,1189,7.7,Autonomous Tech -AI05557,Machine Learning Engineer,68236,EUR,58001,EN,CT,France,M,France,100,"Docker, Deep Learning, Java",Associate,1,Manufacturing,2024-03-04,2024-04-25,2050,8.7,DeepTech Ventures -AI05558,Machine Learning Engineer,102411,CHF,92170,MI,FT,Switzerland,S,Switzerland,0,"Python, SQL, Linux, Azure",Bachelor,3,Real Estate,2024-03-20,2024-04-10,2337,8.1,Neural Networks Co -AI05559,Data Analyst,98866,JPY,10875260,MI,FL,Japan,S,Japan,50,"Python, Mathematics, Scala",Master,3,Real Estate,2025-04-23,2025-05-20,1232,8.7,DeepTech Ventures -AI05560,AI Research Scientist,71678,USD,71678,EN,CT,Norway,S,Norway,50,"Java, Kubernetes, TensorFlow, GCP, Spark",Bachelor,0,Education,2025-02-21,2025-03-23,2418,8.2,DeepTech Ventures -AI05561,Principal Data Scientist,38368,USD,38368,MI,PT,India,L,Ghana,50,"PyTorch, Java, Docker, Kubernetes, GCP",Master,4,Finance,2024-02-16,2024-04-22,1578,9.7,DataVision Ltd -AI05562,Autonomous Systems Engineer,53056,EUR,45098,EN,PT,Germany,M,Germany,100,"Python, MLOps, NLP, TensorFlow",Associate,0,Automotive,2024-12-27,2025-02-05,1918,6.2,Predictive Systems -AI05563,Research Scientist,77960,USD,77960,MI,FT,Finland,S,India,50,"NLP, Kubernetes, Git",PhD,3,Media,2024-08-25,2024-09-30,2354,5.9,DataVision Ltd -AI05564,Computer Vision Engineer,137750,USD,137750,EX,FL,Israel,S,Israel,50,"Hadoop, TensorFlow, Data Visualization, MLOps",Bachelor,15,Transportation,2024-12-13,2025-01-07,686,9.3,AI Innovations -AI05565,Deep Learning Engineer,70399,USD,70399,EN,PT,Finland,L,Singapore,0,"Spark, SQL, Kubernetes",Master,0,Media,2024-06-06,2024-07-02,885,5.8,TechCorp Inc -AI05566,Data Scientist,81497,USD,81497,EX,CT,China,L,China,50,"Azure, Java, Computer Vision, Kubernetes, R",Bachelor,16,Gaming,2024-06-17,2024-08-04,897,8.5,Future Systems -AI05567,Autonomous Systems Engineer,97979,USD,97979,SE,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, Statistics",Master,5,Education,2024-03-11,2024-05-04,1745,5.1,Cloud AI Solutions -AI05568,Machine Learning Engineer,74733,CHF,67260,EN,FT,Switzerland,M,Switzerland,0,"Linux, GCP, PyTorch",Bachelor,0,Retail,2025-04-07,2025-06-01,2308,9.4,Neural Networks Co -AI05569,AI Consultant,34474,USD,34474,MI,FL,India,S,India,100,"Scala, NLP, Java, R, Kubernetes",Associate,3,Education,2025-01-15,2025-02-05,2489,7.9,Quantum Computing Inc -AI05570,Machine Learning Researcher,138565,EUR,117780,EX,CT,France,S,Vietnam,0,"NLP, Docker, Java",Bachelor,11,Media,2024-05-07,2024-06-08,2445,7.8,Digital Transformation LLC -AI05571,Head of AI,91979,USD,91979,MI,FL,Finland,M,Finland,100,"SQL, Computer Vision, Git, Python, Azure",Master,4,Automotive,2024-01-31,2024-03-17,1365,6.3,Predictive Systems -AI05572,AI Product Manager,156226,CHF,140603,MI,FL,Switzerland,L,Philippines,50,"SQL, R, Python",PhD,3,Energy,2024-07-14,2024-09-15,563,7.9,DataVision Ltd -AI05573,Robotics Engineer,220616,SGD,286801,EX,FL,Singapore,S,United States,0,"Linux, NLP, Kubernetes, Scala, SQL",Master,18,Consulting,2024-04-03,2024-05-22,793,6.6,Neural Networks Co -AI05574,Data Engineer,125635,CHF,113072,MI,FL,Switzerland,S,Switzerland,100,"NLP, Python, Scala, GCP",Master,2,Technology,2024-04-24,2024-06-25,569,8.4,TechCorp Inc -AI05575,Data Scientist,141071,EUR,119910,SE,FL,France,L,Austria,0,"Spark, Azure, SQL",PhD,5,Education,2024-07-09,2024-08-16,1177,9.1,Advanced Robotics -AI05576,NLP Engineer,77457,USD,77457,EN,CT,Ireland,M,France,0,"Azure, Mathematics, Python",Bachelor,1,Real Estate,2025-02-26,2025-03-26,1430,6.1,Machine Intelligence Group -AI05577,Computer Vision Engineer,81274,EUR,69083,MI,FL,Austria,L,Austria,100,"Docker, AWS, GCP, PyTorch, Scala",Associate,4,Energy,2024-03-25,2024-04-22,1457,6.7,Neural Networks Co -AI05578,Robotics Engineer,123555,USD,123555,SE,FT,Ireland,S,Ireland,50,"TensorFlow, Git, NLP",Bachelor,7,Finance,2024-06-28,2024-08-29,2138,6.9,DeepTech Ventures -AI05579,AI Product Manager,107981,USD,107981,SE,PT,Finland,M,Finland,100,"Data Visualization, Python, GCP, MLOps, Deep Learning",Master,9,Finance,2024-09-21,2024-10-28,910,5.2,AI Innovations -AI05580,Research Scientist,91339,USD,91339,EN,PT,Sweden,L,Luxembourg,50,"Hadoop, Kubernetes, Computer Vision, TensorFlow, GCP",Bachelor,0,Finance,2025-01-25,2025-04-04,1507,7.5,DataVision Ltd -AI05581,Principal Data Scientist,137460,CHF,123714,MI,CT,Switzerland,L,Switzerland,50,"Python, Hadoop, Git, TensorFlow, PyTorch",Master,3,Healthcare,2025-04-19,2025-05-25,1966,7.9,Neural Networks Co -AI05582,Data Scientist,104465,USD,104465,MI,PT,Norway,M,Netherlands,0,"Statistics, Git, SQL",Bachelor,2,Finance,2024-10-03,2024-11-12,820,7.7,Autonomous Tech -AI05583,Robotics Engineer,77385,USD,77385,MI,FL,Sweden,S,Spain,100,"Git, GCP, MLOps, Deep Learning, Kubernetes",Associate,3,Transportation,2024-02-29,2024-04-20,1137,7.6,Advanced Robotics -AI05584,Machine Learning Engineer,26283,USD,26283,EN,FT,China,S,Colombia,50,"Python, TensorFlow, Kubernetes, PyTorch",PhD,0,Energy,2025-03-31,2025-05-10,714,8.6,Predictive Systems -AI05585,Data Scientist,132539,USD,132539,SE,PT,Denmark,M,Denmark,100,"Data Visualization, Kubernetes, Docker",Master,6,Media,2024-11-04,2024-12-05,2172,10,DeepTech Ventures -AI05586,AI Product Manager,59940,EUR,50949,EN,CT,Netherlands,M,Spain,100,"Python, R, Computer Vision, Git, Azure",Bachelor,0,Finance,2025-01-19,2025-03-25,953,6.9,AI Innovations -AI05587,NLP Engineer,308476,USD,308476,EX,FL,Denmark,M,Ukraine,100,"Data Visualization, TensorFlow, Python",Bachelor,13,Education,2024-05-14,2024-06-09,807,6.4,Future Systems -AI05588,Machine Learning Engineer,117756,GBP,88317,SE,FT,United Kingdom,M,United Kingdom,0,"Tableau, Python, Azure, Statistics, Scala",Master,7,Real Estate,2024-12-06,2025-01-28,1370,7.8,TechCorp Inc -AI05589,Robotics Engineer,95582,USD,95582,EN,PT,Norway,M,Norway,50,"TensorFlow, Statistics, Deep Learning",Master,0,Education,2025-01-13,2025-03-11,1148,5,DeepTech Ventures -AI05590,Deep Learning Engineer,152384,USD,152384,MI,CT,Norway,L,Norway,0,"AWS, PyTorch, Linux, GCP, Computer Vision",Associate,4,Energy,2024-08-23,2024-09-30,2279,7.3,Machine Intelligence Group -AI05591,Data Engineer,149481,USD,149481,SE,CT,Denmark,S,Indonesia,0,"MLOps, Tableau, Hadoop, SQL, R",Master,7,Automotive,2024-05-31,2024-08-10,1674,5.9,DataVision Ltd -AI05592,Robotics Engineer,133014,CHF,119713,MI,FT,Switzerland,M,Switzerland,0,"Hadoop, Scala, Data Visualization, PyTorch",Bachelor,4,Media,2024-04-24,2024-05-20,1451,6.1,Autonomous Tech -AI05593,Computer Vision Engineer,80242,SGD,104315,MI,FT,Singapore,M,Singapore,100,"SQL, Linux, Python, AWS",Master,3,Real Estate,2024-04-12,2024-06-01,956,7,Future Systems -AI05594,AI Product Manager,71080,USD,71080,EN,FL,United States,M,United States,100,"AWS, Kubernetes, TensorFlow",Bachelor,1,Energy,2024-03-04,2024-04-18,895,8.4,Neural Networks Co -AI05595,Robotics Engineer,158297,USD,158297,EX,FT,Sweden,M,Sweden,100,"MLOps, R, Python",PhD,16,Finance,2024-04-14,2024-06-08,1393,6.1,DataVision Ltd -AI05596,Computer Vision Engineer,64920,AUD,87642,EN,FL,Australia,M,Australia,50,"Deep Learning, Linux, Spark, GCP",Bachelor,1,Retail,2024-02-24,2024-04-02,1085,8.3,DeepTech Ventures -AI05597,AI Research Scientist,82287,USD,82287,SE,FT,South Korea,S,South Korea,0,"Kubernetes, TensorFlow, Deep Learning",Master,5,Energy,2024-08-23,2024-09-20,1089,9.3,DataVision Ltd -AI05598,Data Analyst,108508,USD,108508,MI,FT,Finland,L,Finland,50,"Python, GCP, NLP, Spark",PhD,2,Energy,2025-04-04,2025-06-09,929,9.3,DeepTech Ventures -AI05599,Data Analyst,86007,AUD,116109,MI,PT,Australia,M,Australia,50,"Spark, Docker, Data Visualization",Associate,3,Media,2024-07-25,2024-09-17,992,9.4,DeepTech Ventures -AI05600,Principal Data Scientist,157752,USD,157752,SE,CT,Denmark,M,Denmark,50,"R, Scala, PyTorch, Mathematics",Master,9,Real Estate,2024-08-09,2024-10-10,1080,5.6,Algorithmic Solutions -AI05601,Autonomous Systems Engineer,91594,USD,91594,MI,FL,Finland,M,Hungary,0,"Git, Hadoop, MLOps",Bachelor,3,Finance,2024-05-10,2024-06-11,1794,6.4,Predictive Systems -AI05602,Autonomous Systems Engineer,74217,USD,74217,MI,FL,Finland,M,India,50,"GCP, Tableau, Hadoop",PhD,2,Manufacturing,2024-02-22,2024-04-09,683,5.6,TechCorp Inc -AI05603,AI Research Scientist,284154,GBP,213116,EX,CT,United Kingdom,L,United Kingdom,50,"Linux, Java, Data Visualization",Bachelor,15,Consulting,2024-11-29,2025-01-28,725,6.4,AI Innovations -AI05604,AI Software Engineer,163958,USD,163958,EX,FT,South Korea,L,South Korea,50,"Scala, PyTorch, Data Visualization, MLOps",PhD,13,Manufacturing,2024-11-03,2024-11-23,596,8,TechCorp Inc -AI05605,ML Ops Engineer,62034,CAD,77543,EN,PT,Canada,S,Canada,0,"Linux, SQL, Docker, PyTorch, Deep Learning",Associate,1,Real Estate,2025-01-27,2025-02-18,1422,9.4,Advanced Robotics -AI05606,AI Software Engineer,166512,CAD,208140,EX,FT,Canada,S,Ireland,0,"Python, Java, Computer Vision",Master,10,Consulting,2024-02-19,2024-04-24,624,8.8,Future Systems -AI05607,AI Product Manager,209138,USD,209138,EX,PT,Ireland,L,Ireland,100,"Python, Spark, MLOps",Associate,10,Telecommunications,2024-12-17,2025-02-05,790,8.5,DataVision Ltd -AI05608,AI Product Manager,149550,USD,149550,SE,PT,United States,S,United States,100,"Computer Vision, PyTorch, Spark",PhD,7,Technology,2024-08-13,2024-09-02,2025,6.8,Machine Intelligence Group -AI05609,ML Ops Engineer,162213,EUR,137881,EX,FT,Germany,M,Germany,50,"R, Kubernetes, Docker, Tableau, TensorFlow",Bachelor,14,Government,2024-06-14,2024-08-01,979,6,Smart Analytics -AI05610,Robotics Engineer,179531,USD,179531,EX,CT,Norway,M,Latvia,50,"Kubernetes, Deep Learning, Computer Vision, Java",Bachelor,14,Manufacturing,2024-06-09,2024-08-15,1650,7.2,Algorithmic Solutions -AI05611,Data Analyst,206536,USD,206536,EX,FL,South Korea,M,South Korea,50,"Linux, Python, Git, TensorFlow",PhD,12,Healthcare,2024-01-21,2024-02-10,1380,5.6,DataVision Ltd -AI05612,AI Specialist,33744,USD,33744,SE,FT,India,S,India,100,"TensorFlow, Deep Learning, Computer Vision",Associate,7,Manufacturing,2024-12-16,2025-02-26,1221,5.4,Algorithmic Solutions -AI05613,AI Consultant,60562,USD,60562,EN,PT,Israel,L,France,0,"SQL, Statistics, PyTorch, Deep Learning, R",PhD,1,Healthcare,2025-01-07,2025-02-07,1322,7.6,Advanced Robotics -AI05614,AI Software Engineer,55911,AUD,75480,EN,FL,Australia,M,Australia,0,"Spark, Kubernetes, Linux, Hadoop",PhD,0,Manufacturing,2024-02-28,2024-03-26,1136,5.1,Neural Networks Co -AI05615,Autonomous Systems Engineer,95326,USD,95326,MI,FL,South Korea,L,South Korea,50,"R, Kubernetes, MLOps",Associate,4,Retail,2024-11-29,2025-01-29,953,7,AI Innovations -AI05616,Machine Learning Engineer,185388,JPY,20392680,EX,CT,Japan,L,Japan,0,"TensorFlow, Python, MLOps, Spark",PhD,17,Manufacturing,2024-07-28,2024-09-26,2466,9.2,Predictive Systems -AI05617,Research Scientist,150527,EUR,127948,SE,CT,Netherlands,M,Switzerland,100,"Linux, AWS, Tableau, Docker, Mathematics",PhD,7,Healthcare,2024-12-20,2025-02-10,545,5.5,Quantum Computing Inc -AI05618,ML Ops Engineer,119633,USD,119633,EX,FL,China,M,China,100,"Java, PyTorch, Hadoop, Git",Master,11,Finance,2024-07-22,2024-08-20,2109,7,TechCorp Inc -AI05619,Data Scientist,227078,USD,227078,SE,FL,Norway,L,Norway,50,"Git, Spark, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-06-21,2024-07-11,1035,8,Cloud AI Solutions -AI05620,AI Product Manager,195528,USD,195528,SE,FL,Denmark,M,Argentina,0,"PyTorch, Python, NLP, Azure, Spark",Associate,7,Media,2024-09-27,2024-10-22,532,8,TechCorp Inc -AI05621,Data Scientist,123024,CAD,153780,SE,FL,Canada,M,Canada,100,"Hadoop, Spark, Python, Git",Master,7,Finance,2024-12-21,2025-02-20,1417,5,Smart Analytics -AI05622,Research Scientist,151053,USD,151053,MI,FT,Denmark,L,Philippines,50,"AWS, Kubernetes, SQL",PhD,2,Technology,2024-06-13,2024-07-09,628,8.1,DataVision Ltd -AI05623,AI Architect,116626,JPY,12828860,SE,PT,Japan,S,Japan,50,"Scala, Kubernetes, NLP, Statistics, R",PhD,7,Telecommunications,2024-11-06,2024-12-30,791,7.1,Advanced Robotics -AI05624,ML Ops Engineer,97656,EUR,83008,MI,FL,Austria,M,Austria,100,"Kubernetes, Java, R",PhD,4,Retail,2025-02-20,2025-03-13,2400,8,Digital Transformation LLC -AI05625,Research Scientist,94494,EUR,80320,EN,PT,Netherlands,L,Netherlands,100,"Scala, Spark, Java, Computer Vision, Git",PhD,1,Consulting,2025-04-24,2025-05-13,1566,9.9,DeepTech Ventures -AI05626,ML Ops Engineer,43321,USD,43321,SE,PT,India,L,India,100,"TensorFlow, Azure, Git",Master,9,Telecommunications,2024-09-06,2024-10-04,1763,8.8,DataVision Ltd -AI05627,AI Software Engineer,58243,EUR,49507,EN,FL,Germany,S,Malaysia,100,"Kubernetes, GCP, Computer Vision, MLOps",PhD,0,Energy,2024-11-02,2024-12-16,535,8.6,TechCorp Inc -AI05628,Machine Learning Engineer,106076,USD,106076,SE,FT,Israel,M,Malaysia,0,"GCP, Azure, SQL, Docker",Associate,6,Government,2024-08-06,2024-10-14,830,7.9,DeepTech Ventures -AI05629,Head of AI,124280,USD,124280,SE,CT,Israel,M,Malaysia,100,"Git, Python, Kubernetes, MLOps",Associate,7,Automotive,2024-08-01,2024-08-16,1666,9.3,Machine Intelligence Group -AI05630,Robotics Engineer,237713,GBP,178285,EX,FT,United Kingdom,M,Denmark,50,"Java, TensorFlow, Tableau, NLP, Mathematics",Bachelor,18,Education,2025-02-05,2025-03-04,861,7.6,Autonomous Tech -AI05631,AI Product Manager,133896,USD,133896,SE,FL,Sweden,S,Sweden,50,"Spark, SQL, TensorFlow, Computer Vision, Python",PhD,5,Technology,2024-11-20,2024-12-16,2374,5.1,Algorithmic Solutions -AI05632,AI Software Engineer,116023,JPY,12762530,SE,PT,Japan,M,Japan,0,"Tableau, Hadoop, Python, TensorFlow, Deep Learning",Associate,7,Finance,2024-11-09,2025-01-15,2298,5.3,Cognitive Computing -AI05633,Computer Vision Engineer,96751,USD,96751,MI,CT,United States,S,Indonesia,50,"Data Visualization, Python, Java",Bachelor,4,Energy,2025-02-07,2025-03-04,1001,9,Digital Transformation LLC -AI05634,Computer Vision Engineer,134644,EUR,114447,SE,PT,Austria,L,Brazil,50,"Kubernetes, Data Visualization, Tableau, MLOps, Deep Learning",PhD,8,Media,2025-04-25,2025-06-22,1118,6.3,Advanced Robotics -AI05635,Principal Data Scientist,102778,JPY,11305580,MI,FT,Japan,M,Kenya,50,"Spark, SQL, TensorFlow, Azure",Bachelor,2,Healthcare,2025-01-07,2025-01-27,1080,6.1,AI Innovations -AI05636,AI Product Manager,103788,USD,103788,EN,FT,Norway,M,Norway,100,"Kubernetes, TensorFlow, Azure, Tableau",PhD,1,Transportation,2024-07-09,2024-09-17,2278,9.7,Quantum Computing Inc -AI05637,Machine Learning Researcher,43133,USD,43133,EN,CT,China,L,China,100,"AWS, Hadoop, Deep Learning, PyTorch",Associate,1,Gaming,2025-03-02,2025-05-04,1800,9.8,Quantum Computing Inc -AI05638,Research Scientist,186168,EUR,158243,EX,PT,Germany,S,Germany,100,"SQL, Python, MLOps",Master,10,Healthcare,2024-07-01,2024-08-26,655,7,Algorithmic Solutions -AI05639,AI Specialist,269018,GBP,201764,EX,FT,United Kingdom,M,United Kingdom,0,"Hadoop, Deep Learning, Azure, Python, NLP",Associate,18,Real Estate,2024-08-08,2024-09-02,2032,9,DataVision Ltd -AI05640,AI Software Engineer,168038,USD,168038,SE,FL,Denmark,L,Denmark,100,"Azure, Deep Learning, Python",PhD,6,Media,2024-08-24,2024-11-03,797,9.9,Smart Analytics -AI05641,Machine Learning Engineer,63639,USD,63639,EN,FL,South Korea,M,South Korea,100,"Python, Hadoop, Linux, Computer Vision",Associate,0,Manufacturing,2024-08-08,2024-09-23,816,9.5,Algorithmic Solutions -AI05642,AI Specialist,204416,USD,204416,EX,PT,Israel,L,Canada,50,"AWS, Java, TensorFlow, Azure, SQL",Bachelor,16,Consulting,2024-02-02,2024-03-17,1641,6.1,DataVision Ltd -AI05643,AI Research Scientist,28315,USD,28315,MI,CT,India,S,India,0,"AWS, Scala, R, Git",Bachelor,3,Transportation,2024-10-31,2024-12-09,2250,6.6,Algorithmic Solutions -AI05644,Autonomous Systems Engineer,69096,USD,69096,EN,FL,United States,L,United States,100,"Git, Mathematics, TensorFlow, Linux",Bachelor,0,Consulting,2024-07-01,2024-07-28,804,5.5,Smart Analytics -AI05645,Data Analyst,72148,USD,72148,MI,FL,South Korea,L,South Korea,100,"Kubernetes, Git, MLOps, R, Computer Vision",Associate,2,Education,2025-04-12,2025-05-02,1906,7.6,Cloud AI Solutions -AI05646,Research Scientist,155411,USD,155411,SE,PT,Norway,M,Norway,100,"TensorFlow, Scala, MLOps",Bachelor,9,Gaming,2025-04-17,2025-06-23,835,5.2,TechCorp Inc -AI05647,Autonomous Systems Engineer,119240,USD,119240,MI,FL,Ireland,L,Indonesia,0,"Computer Vision, Data Visualization, Hadoop, Kubernetes, Deep Learning",Master,4,Technology,2024-01-16,2024-02-11,674,6,Smart Analytics -AI05648,Autonomous Systems Engineer,57600,USD,57600,EX,CT,India,S,Vietnam,100,"Hadoop, PyTorch, Spark",Master,10,Real Estate,2025-01-18,2025-02-19,1769,9.1,DeepTech Ventures -AI05649,Computer Vision Engineer,53542,USD,53542,EN,CT,Ireland,S,Ireland,50,"Scala, Azure, Python",PhD,0,Consulting,2025-03-24,2025-04-19,2480,8.8,Smart Analytics -AI05650,AI Consultant,151442,USD,151442,EX,PT,Finland,L,Chile,0,"Python, Spark, Computer Vision",PhD,15,Technology,2024-12-17,2025-02-25,2014,9.9,Cognitive Computing -AI05651,Data Analyst,113037,USD,113037,SE,CT,South Korea,S,Vietnam,100,"Kubernetes, PyTorch, GCP",Associate,5,Telecommunications,2024-01-26,2024-03-05,1389,7,Smart Analytics -AI05652,AI Consultant,63321,AUD,85483,EN,PT,Australia,M,Australia,50,"Data Visualization, Computer Vision, Docker, R",PhD,0,Energy,2024-03-27,2024-05-19,2054,6.5,Cloud AI Solutions -AI05653,Head of AI,216696,EUR,184192,EX,PT,Netherlands,L,Argentina,100,"R, SQL, Deep Learning, Spark, Linux",Associate,10,Energy,2024-04-11,2024-05-08,2464,5.3,Autonomous Tech -AI05654,AI Consultant,68832,CAD,86040,MI,CT,Canada,S,Canada,0,"Tableau, Linux, TensorFlow, Data Visualization, Hadoop",Bachelor,3,Telecommunications,2024-01-13,2024-01-29,2000,8.1,Predictive Systems -AI05655,AI Product Manager,125853,JPY,13843830,SE,CT,Japan,L,Japan,50,"Scala, R, Docker, Computer Vision",Bachelor,7,Finance,2024-06-17,2024-08-17,645,5.4,Future Systems -AI05656,AI Architect,90307,USD,90307,MI,FL,South Korea,L,South Korea,100,"Git, SQL, GCP, Azure",PhD,2,Telecommunications,2024-03-06,2024-05-15,1785,8.2,Digital Transformation LLC -AI05657,AI Software Engineer,208536,USD,208536,EX,CT,Norway,L,Norway,0,"Computer Vision, MLOps, Git",Bachelor,11,Consulting,2024-11-30,2025-01-27,1876,9.1,Predictive Systems -AI05658,Data Engineer,79479,USD,79479,SE,PT,China,L,Finland,50,"MLOps, PyTorch, Kubernetes",Master,9,Education,2024-02-12,2024-03-25,861,6,Algorithmic Solutions -AI05659,AI Product Manager,145587,JPY,16014570,SE,FL,Japan,S,Japan,50,"SQL, PyTorch, TensorFlow, Hadoop, Tableau",Bachelor,7,Retail,2025-03-07,2025-03-22,1397,9.9,Autonomous Tech -AI05660,Robotics Engineer,237771,USD,237771,EX,PT,South Korea,L,South Korea,50,"Linux, Python, MLOps",Bachelor,15,Education,2025-02-06,2025-04-20,1107,5.9,Quantum Computing Inc -AI05661,AI Specialist,131882,CHF,118694,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Scala, R",Associate,4,Technology,2024-04-21,2024-05-13,1742,7.2,Predictive Systems -AI05662,Principal Data Scientist,194531,USD,194531,SE,PT,Denmark,L,South Korea,100,"PyTorch, Hadoop, Tableau, Azure, TensorFlow",Associate,5,Finance,2024-07-09,2024-08-12,2058,8.9,Smart Analytics -AI05663,Robotics Engineer,170274,CHF,153247,MI,FL,Switzerland,L,Switzerland,0,"SQL, Kubernetes, Scala, Data Visualization, PyTorch",PhD,3,Consulting,2024-04-28,2024-05-22,1146,9.7,DataVision Ltd -AI05664,AI Architect,238256,GBP,178692,EX,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Java, Tableau, Deep Learning",Master,18,Healthcare,2024-01-28,2024-03-03,1005,7.2,Machine Intelligence Group -AI05665,NLP Engineer,98574,USD,98574,MI,FL,United States,S,United States,50,"GCP, Statistics, Hadoop",PhD,4,Finance,2025-03-30,2025-05-12,916,9.1,Machine Intelligence Group -AI05666,Head of AI,84725,EUR,72016,MI,PT,Germany,L,Germany,50,"Java, Scala, Hadoop, Linux, AWS",Master,3,Energy,2024-06-14,2024-07-27,1296,6.4,Quantum Computing Inc -AI05667,AI Consultant,237420,USD,237420,EX,FL,United States,L,United States,50,"PyTorch, NLP, MLOps, Mathematics, Kubernetes",Associate,17,Energy,2025-04-20,2025-06-04,2368,7.6,DataVision Ltd -AI05668,Research Scientist,94852,SGD,123308,MI,CT,Singapore,M,Singapore,0,"TensorFlow, Scala, Kubernetes, NLP, Python",PhD,3,Media,2024-12-25,2025-01-12,1503,9.1,TechCorp Inc -AI05669,NLP Engineer,53187,EUR,45209,EN,PT,Austria,M,Austria,0,"Python, Docker, NLP",Bachelor,1,Government,2024-10-02,2024-11-02,2170,8.4,Cognitive Computing -AI05670,Head of AI,85325,USD,85325,EN,FT,Norway,L,Norway,100,"MLOps, GCP, Kubernetes, Hadoop, SQL",Bachelor,0,Transportation,2024-10-16,2024-11-24,2270,9.4,Autonomous Tech -AI05671,Data Analyst,84861,EUR,72132,MI,PT,France,M,France,100,"Scala, Hadoop, Computer Vision, Data Visualization",Associate,3,Technology,2025-02-26,2025-04-29,1644,8.7,Autonomous Tech -AI05672,Machine Learning Engineer,110677,EUR,94075,MI,CT,Netherlands,M,Netherlands,0,"PyTorch, Docker, Tableau",Master,4,Consulting,2024-06-30,2024-08-16,500,7.2,Digital Transformation LLC -AI05673,Machine Learning Engineer,55583,EUR,47246,EN,FL,France,S,France,0,"Statistics, PyTorch, R",PhD,0,Healthcare,2024-04-19,2024-05-14,602,8.8,Cloud AI Solutions -AI05674,Deep Learning Engineer,103137,SGD,134078,MI,CT,Singapore,S,United Kingdom,100,"R, GCP, SQL",PhD,3,Gaming,2025-03-18,2025-04-20,546,7.8,AI Innovations -AI05675,Autonomous Systems Engineer,94118,SGD,122353,MI,FT,Singapore,M,Singapore,100,"GCP, Docker, PyTorch, SQL",Bachelor,4,Real Estate,2024-05-23,2024-06-13,1065,6.1,Future Systems -AI05676,AI Product Manager,263320,USD,263320,EX,FL,Ireland,L,Ireland,100,"Data Visualization, Azure, Git, Python, Spark",Bachelor,12,Telecommunications,2025-03-11,2025-05-21,1510,8.9,Predictive Systems -AI05677,Principal Data Scientist,81751,USD,81751,EX,FT,China,S,Indonesia,50,"Statistics, Data Visualization, SQL, Python, Tableau",PhD,19,Real Estate,2024-01-16,2024-03-20,2349,9.8,DeepTech Ventures -AI05678,AI Product Manager,69515,USD,69515,EN,PT,Israel,M,Japan,100,"Python, SQL, Tableau, R, AWS",Master,1,Government,2024-05-14,2024-06-03,1662,6,TechCorp Inc -AI05679,AI Consultant,102539,USD,102539,SE,PT,Ireland,M,New Zealand,50,"Linux, TensorFlow, PyTorch, Data Visualization",Associate,7,Technology,2024-06-29,2024-08-26,1816,9.1,Neural Networks Co -AI05680,AI Consultant,83366,EUR,70861,MI,PT,Germany,M,Germany,50,"Python, Computer Vision, AWS",Associate,3,Telecommunications,2024-11-28,2025-01-28,1453,5.1,Digital Transformation LLC -AI05681,Data Analyst,103994,JPY,11439340,MI,CT,Japan,S,Japan,50,"Linux, Scala, R",Bachelor,3,Energy,2025-04-03,2025-05-27,1046,7.6,TechCorp Inc -AI05682,AI Specialist,63790,USD,63790,EN,PT,Ireland,M,Ireland,0,"SQL, Spark, Computer Vision",Associate,1,Technology,2024-05-14,2024-07-11,1573,8,Algorithmic Solutions -AI05683,Computer Vision Engineer,223100,EUR,189635,EX,PT,Netherlands,S,Thailand,100,"AWS, Data Visualization, Tableau, Hadoop, Statistics",Associate,12,Finance,2024-09-23,2024-11-18,698,6.7,Predictive Systems -AI05684,Robotics Engineer,60827,USD,60827,EN,FT,Sweden,S,Sweden,100,"Scala, Spark, Kubernetes, Docker, NLP",Associate,0,Manufacturing,2024-03-04,2024-03-21,1247,7.5,AI Innovations -AI05685,AI Architect,77717,USD,77717,MI,FT,United States,S,Mexico,0,"Hadoop, Scala, TensorFlow",Master,3,Transportation,2024-03-08,2024-05-13,1519,9.4,Machine Intelligence Group -AI05686,Machine Learning Engineer,97963,USD,97963,MI,CT,South Korea,L,Kenya,100,"Git, TensorFlow, Tableau, Data Visualization",Associate,3,Energy,2024-12-13,2025-01-05,2218,5.8,Cognitive Computing -AI05687,Data Engineer,214315,USD,214315,EX,PT,United States,M,United States,0,"PyTorch, Azure, Kubernetes, Deep Learning, TensorFlow",Associate,18,Media,2024-11-08,2024-12-25,1940,6.2,Quantum Computing Inc -AI05688,Autonomous Systems Engineer,71291,USD,71291,EN,FL,Denmark,M,Denmark,100,"Docker, Scala, AWS, Python",Master,0,Consulting,2024-07-27,2024-08-31,1540,9.6,Quantum Computing Inc -AI05689,Data Scientist,87518,USD,87518,EN,CT,United States,L,Vietnam,0,"AWS, PyTorch, Scala, Hadoop",Bachelor,1,Healthcare,2024-12-13,2025-01-04,906,5.9,AI Innovations -AI05690,Machine Learning Researcher,149558,USD,149558,SE,FL,United States,S,United States,0,"Azure, SQL, TensorFlow, Kubernetes",Bachelor,5,Media,2024-07-27,2024-09-12,2478,7.1,AI Innovations -AI05691,AI Consultant,107945,AUD,145726,MI,FT,Australia,M,Australia,0,"Hadoop, Computer Vision, Kubernetes, Tableau, Azure",PhD,2,Manufacturing,2024-04-25,2024-07-02,2267,5.8,Autonomous Tech -AI05692,Machine Learning Engineer,63957,USD,63957,EX,FT,China,S,Australia,50,"Linux, Tableau, TensorFlow, Computer Vision",PhD,12,Education,2024-02-01,2024-03-24,2482,9.6,Autonomous Tech -AI05693,AI Architect,93563,EUR,79529,MI,CT,Germany,S,Germany,0,"Data Visualization, Python, SQL, Kubernetes",Associate,3,Media,2024-06-24,2024-08-24,953,9,Cloud AI Solutions -AI05694,AI Research Scientist,161134,EUR,136964,SE,FT,France,L,France,100,"R, Data Visualization, Python, Docker",PhD,6,Real Estate,2024-08-04,2024-09-01,2303,5.8,Machine Intelligence Group -AI05695,Principal Data Scientist,212931,CAD,266164,EX,FT,Canada,S,New Zealand,0,"SQL, Linux, Python",Master,12,Technology,2024-04-13,2024-05-18,1452,6.8,TechCorp Inc -AI05696,AI Product Manager,119167,USD,119167,MI,CT,Denmark,M,Denmark,100,"Linux, Azure, MLOps, Kubernetes",Master,2,Automotive,2024-04-27,2024-06-12,1621,9.3,DataVision Ltd -AI05697,Head of AI,102382,USD,102382,EN,FT,Denmark,M,Denmark,100,"Tableau, Spark, NLP, PyTorch, Computer Vision",PhD,1,Government,2025-02-21,2025-05-02,1096,5.2,Predictive Systems -AI05698,AI Specialist,69931,USD,69931,MI,PT,Finland,S,Finland,100,"Kubernetes, GCP, Computer Vision, AWS",PhD,4,Transportation,2025-03-25,2025-05-23,1511,5.2,Predictive Systems -AI05699,Autonomous Systems Engineer,61743,SGD,80266,EN,CT,Singapore,M,Singapore,50,"PyTorch, Computer Vision, Tableau",PhD,1,Technology,2024-11-28,2025-01-03,1091,10,Predictive Systems -AI05700,AI Product Manager,70132,AUD,94678,MI,FT,Australia,S,Australia,50,"Scala, Data Visualization, Docker, R",Associate,4,Transportation,2024-01-12,2024-02-23,2242,5.7,Digital Transformation LLC -AI05701,Robotics Engineer,96886,JPY,10657460,MI,FT,Japan,S,Japan,0,"Git, Hadoop, SQL, Python, Kubernetes",Master,3,Consulting,2024-03-13,2024-05-22,1366,8.7,Future Systems -AI05702,AI Research Scientist,200782,EUR,170665,EX,PT,Netherlands,M,Switzerland,50,"Linux, Java, Kubernetes, TensorFlow",PhD,15,Consulting,2025-03-07,2025-05-13,840,5.2,Digital Transformation LLC -AI05703,Data Analyst,23579,USD,23579,EN,FL,India,L,India,50,"Java, PyTorch, Statistics, Deep Learning",Associate,0,Transportation,2025-02-04,2025-03-03,1565,9.2,Cloud AI Solutions -AI05704,NLP Engineer,55614,AUD,75079,EN,PT,Australia,M,Australia,0,"Java, Hadoop, NLP, Linux",Bachelor,1,Consulting,2024-12-16,2025-02-18,2492,8,Algorithmic Solutions -AI05705,AI Product Manager,150781,EUR,128164,SE,FL,Germany,M,Nigeria,100,"Spark, Tableau, Hadoop, Computer Vision",Master,5,Retail,2024-07-22,2024-09-02,1421,5.3,Cognitive Computing -AI05706,AI Specialist,131468,EUR,111748,SE,CT,Austria,L,Luxembourg,0,"Kubernetes, PyTorch, MLOps, GCP, R",Master,8,Technology,2024-12-27,2025-01-31,2220,8.5,Advanced Robotics -AI05707,Deep Learning Engineer,72393,EUR,61534,EN,FT,France,M,France,0,"PyTorch, Kubernetes, SQL, Scala",Bachelor,1,Energy,2024-02-10,2024-03-22,2211,9.4,Cloud AI Solutions -AI05708,NLP Engineer,139017,USD,139017,SE,PT,Sweden,L,Sweden,100,"MLOps, Computer Vision, R, PyTorch",Associate,5,Manufacturing,2025-02-27,2025-05-02,1808,9.8,Autonomous Tech -AI05709,Principal Data Scientist,112229,USD,112229,MI,FL,Denmark,S,Denmark,50,"Scala, GCP, SQL, Hadoop, Data Visualization",Bachelor,4,Technology,2024-03-03,2024-05-13,702,8.6,Digital Transformation LLC -AI05710,ML Ops Engineer,88643,USD,88643,MI,FL,South Korea,M,South Korea,100,"MLOps, Data Visualization, Azure, AWS",Associate,4,Manufacturing,2024-12-20,2025-01-16,2308,7.5,Cognitive Computing -AI05711,Head of AI,119522,USD,119522,MI,CT,Denmark,S,United States,0,"Deep Learning, Docker, Git, Mathematics",Associate,4,Finance,2025-01-09,2025-03-08,1799,5.9,Predictive Systems -AI05712,NLP Engineer,146464,EUR,124494,SE,CT,Netherlands,M,Denmark,100,"MLOps, AWS, SQL",PhD,6,Real Estate,2024-05-24,2024-07-21,2415,9.5,Cloud AI Solutions -AI05713,Data Scientist,98192,CAD,122740,SE,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP, R, Computer Vision",PhD,6,Telecommunications,2024-07-25,2024-08-11,1143,9.1,Cloud AI Solutions -AI05714,Machine Learning Engineer,80479,USD,80479,EN,FT,Norway,L,Norway,100,"Kubernetes, NLP, Spark, Deep Learning",Associate,1,Healthcare,2025-04-26,2025-07-02,1630,8.7,Future Systems -AI05715,Data Engineer,152265,EUR,129425,EX,FT,Netherlands,S,Netherlands,50,"MLOps, Python, Computer Vision, Linux, TensorFlow",Master,12,Media,2025-04-16,2025-05-25,1049,9.7,AI Innovations -AI05716,AI Software Engineer,77835,USD,77835,EN,FT,Norway,S,Norway,0,"Azure, Python, GCP, TensorFlow",PhD,1,Technology,2024-01-10,2024-03-11,1316,5.8,Quantum Computing Inc -AI05717,AI Architect,63922,JPY,7031420,EN,FT,Japan,L,Japan,50,"NLP, Python, TensorFlow, Linux",Master,1,Energy,2025-04-21,2025-05-12,1569,8.7,AI Innovations -AI05718,NLP Engineer,257100,JPY,28281000,EX,FL,Japan,L,Finland,0,"TensorFlow, Tableau, Docker, NLP",Associate,15,Automotive,2025-02-04,2025-04-12,876,9.3,DeepTech Ventures -AI05719,Deep Learning Engineer,88350,USD,88350,MI,FT,Finland,L,China,50,"Python, Linux, Statistics, Computer Vision",Associate,4,Transportation,2024-07-04,2024-08-20,986,7.7,Neural Networks Co -AI05720,AI Specialist,99465,USD,99465,MI,FL,Denmark,S,France,50,"GCP, Data Visualization, Spark, R",Bachelor,4,Government,2025-03-31,2025-05-09,1730,5.3,Algorithmic Solutions -AI05721,NLP Engineer,179088,USD,179088,EX,CT,Norway,S,Romania,50,"Python, SQL, Deep Learning, Git, Docker",Bachelor,14,Media,2024-07-11,2024-07-26,1923,8.1,Predictive Systems -AI05722,Data Engineer,159540,USD,159540,SE,FT,Denmark,L,Denmark,100,"Mathematics, Git, NLP",Associate,6,Energy,2024-10-06,2024-11-16,1350,9,AI Innovations -AI05723,Deep Learning Engineer,37477,USD,37477,MI,FT,India,M,India,50,"Spark, Scala, Linux, Deep Learning, SQL",PhD,2,Automotive,2024-05-24,2024-07-26,2369,9.3,Predictive Systems -AI05724,Research Scientist,133739,SGD,173861,MI,PT,Singapore,L,Russia,0,"Computer Vision, AWS, Kubernetes",Associate,4,Education,2025-02-08,2025-02-28,865,7.1,Advanced Robotics -AI05725,AI Research Scientist,373674,CHF,336307,EX,FT,Switzerland,L,Switzerland,50,"R, Python, Statistics, Scala, Deep Learning",Associate,16,Automotive,2024-04-19,2024-05-21,626,9.6,Cloud AI Solutions -AI05726,Head of AI,57593,USD,57593,MI,PT,South Korea,S,China,100,"Docker, Linux, AWS, Scala",Associate,3,Retail,2024-11-01,2024-12-15,1985,8.3,TechCorp Inc -AI05727,Machine Learning Researcher,62998,USD,62998,SE,FT,China,S,China,0,"Statistics, Scala, NLP, MLOps, Azure",Bachelor,7,Real Estate,2024-12-01,2025-02-01,1256,7.4,Machine Intelligence Group -AI05728,Research Scientist,99028,SGD,128736,SE,CT,Singapore,S,Singapore,100,"Docker, Spark, AWS",PhD,5,Retail,2024-12-26,2025-01-29,1673,9.8,Advanced Robotics -AI05729,Data Analyst,283076,USD,283076,EX,CT,Norway,S,Norway,50,"NLP, Deep Learning, Spark, MLOps",Master,15,Finance,2024-01-19,2024-02-05,1350,7.5,Cloud AI Solutions -AI05730,Data Scientist,77013,USD,77013,MI,FL,South Korea,L,South Korea,0,"Statistics, Mathematics, Java",Master,2,Retail,2024-10-12,2024-11-16,916,7.2,TechCorp Inc -AI05731,Computer Vision Engineer,88457,USD,88457,MI,FT,South Korea,L,South Korea,100,"Python, Kubernetes, Spark, GCP",Master,4,Healthcare,2024-09-01,2024-09-19,2182,5.6,Cognitive Computing -AI05732,Machine Learning Researcher,99330,USD,99330,MI,CT,South Korea,L,South Korea,0,"Computer Vision, GCP, Kubernetes, SQL",Bachelor,4,Government,2024-10-21,2024-11-27,2415,9.3,AI Innovations -AI05733,Data Scientist,65665,USD,65665,EN,CT,Israel,S,Israel,0,"Python, Azure, Statistics",PhD,1,Government,2024-10-29,2024-12-23,1506,7.6,Autonomous Tech -AI05734,AI Architect,92187,USD,92187,MI,FT,Israel,M,Israel,0,"Hadoop, NLP, MLOps",PhD,3,Manufacturing,2024-02-20,2024-04-23,1555,5.9,Smart Analytics -AI05735,ML Ops Engineer,72655,USD,72655,MI,FT,Israel,M,Israel,100,"GCP, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2024-11-02,2024-12-22,1742,6.7,DeepTech Ventures -AI05736,ML Ops Engineer,117047,CAD,146309,SE,FL,Canada,M,Canada,100,"Linux, SQL, Computer Vision, Kubernetes, PyTorch",Bachelor,6,Healthcare,2024-07-03,2024-09-06,2314,9,TechCorp Inc -AI05737,Data Analyst,66295,USD,66295,EN,FT,Israel,L,Israel,50,"GCP, Linux, Spark",Master,1,Media,2025-02-12,2025-04-10,1387,5.2,Neural Networks Co -AI05738,AI Specialist,159977,USD,159977,SE,CT,United States,L,United States,100,"SQL, Docker, Mathematics, Computer Vision, AWS",Associate,9,Finance,2025-04-13,2025-06-13,1434,9,Cognitive Computing -AI05739,ML Ops Engineer,213245,EUR,181258,EX,CT,Netherlands,S,Netherlands,100,"SQL, Hadoop, Tableau",Bachelor,17,Finance,2025-03-21,2025-04-22,1998,9,DeepTech Ventures -AI05740,Head of AI,119945,EUR,101953,EX,CT,Austria,S,United States,50,"Java, SQL, Git, Docker",PhD,10,Transportation,2024-02-13,2024-03-11,1193,6.3,Algorithmic Solutions -AI05741,Robotics Engineer,216153,USD,216153,EX,PT,Finland,L,Nigeria,100,"TensorFlow, Python, Data Visualization, Statistics",Master,10,Retail,2024-07-03,2024-07-22,2438,8.4,Smart Analytics -AI05742,Data Analyst,40020,USD,40020,MI,FT,India,L,India,50,"Python, SQL, Computer Vision, Git, Linux",Master,4,Healthcare,2025-03-14,2025-05-26,666,5.6,Neural Networks Co -AI05743,AI Architect,92086,CAD,115108,MI,CT,Canada,L,Switzerland,0,"NLP, Kubernetes, Python, Git",PhD,2,Consulting,2024-04-28,2024-06-23,1486,8.5,Predictive Systems -AI05744,AI Product Manager,200654,GBP,150491,EX,FT,United Kingdom,M,Luxembourg,100,"Git, Java, Scala",Master,19,Consulting,2024-12-13,2025-02-04,1872,9.7,TechCorp Inc -AI05745,Computer Vision Engineer,68829,USD,68829,EN,CT,United States,S,United States,100,"Scala, Hadoop, TensorFlow",PhD,1,Gaming,2024-10-27,2024-12-04,1492,9.3,Cognitive Computing -AI05746,Head of AI,197686,USD,197686,EX,CT,Norway,M,Norway,50,"Kubernetes, Docker, Data Visualization, Git, Hadoop",PhD,17,Energy,2024-03-03,2024-04-24,2251,5.2,Advanced Robotics -AI05747,AI Product Manager,165557,USD,165557,EX,PT,Finland,M,Finland,0,"TensorFlow, Spark, Tableau, Computer Vision, MLOps",Associate,12,Retail,2025-03-19,2025-05-30,1803,5.4,Smart Analytics -AI05748,AI Architect,66906,USD,66906,EN,CT,Ireland,S,Argentina,100,"Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-12-13,2025-02-19,1384,8.8,TechCorp Inc -AI05749,AI Software Engineer,59768,USD,59768,EX,FT,China,S,China,100,"SQL, Linux, Git, Mathematics",PhD,16,Consulting,2024-07-11,2024-08-27,793,8.3,Cognitive Computing -AI05750,AI Architect,139169,GBP,104377,SE,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, GCP, Computer Vision, Azure, Kubernetes",Associate,7,Transportation,2024-08-22,2024-09-10,1739,10,Future Systems -AI05751,NLP Engineer,177662,JPY,19542820,EX,FL,Japan,L,Japan,50,"MLOps, Statistics, PyTorch, Spark, Java",PhD,14,Transportation,2025-02-13,2025-03-14,1326,8.3,Machine Intelligence Group -AI05752,ML Ops Engineer,81894,JPY,9008340,MI,FL,Japan,S,Turkey,0,"Python, TensorFlow, Docker, Mathematics",PhD,2,Manufacturing,2024-12-30,2025-01-24,808,9.2,AI Innovations -AI05753,Computer Vision Engineer,213516,USD,213516,EX,PT,Israel,L,Japan,50,"AWS, Docker, Mathematics, Python",Associate,10,Automotive,2024-12-03,2025-02-11,907,7.4,Algorithmic Solutions -AI05754,Deep Learning Engineer,231165,EUR,196490,EX,FL,Austria,M,Sweden,0,"Python, SQL, Azure",Master,17,Energy,2025-02-03,2025-03-01,1994,9.8,Machine Intelligence Group -AI05755,AI Specialist,110726,AUD,149480,SE,PT,Australia,S,Estonia,50,"Deep Learning, Java, NLP",PhD,8,Transportation,2024-04-27,2024-05-14,2129,5.1,Neural Networks Co -AI05756,Research Scientist,83571,USD,83571,EX,PT,China,L,China,50,"MLOps, PyTorch, Git, Scala, Linux",Master,18,Finance,2024-02-25,2024-04-13,2311,8,Predictive Systems -AI05757,NLP Engineer,232736,USD,232736,EX,FT,Denmark,M,Denmark,0,"Hadoop, Deep Learning, NLP, Python, TensorFlow",Master,17,Healthcare,2024-10-06,2024-12-08,577,6.9,Neural Networks Co -AI05758,Robotics Engineer,127623,AUD,172291,SE,CT,Australia,S,Australia,50,"Data Visualization, Kubernetes, Java, Deep Learning, Docker",Bachelor,7,Transportation,2024-09-21,2024-11-05,2226,6.7,TechCorp Inc -AI05759,Computer Vision Engineer,120233,USD,120233,MI,CT,United States,M,United States,100,"Python, R, Tableau, AWS, Hadoop",Bachelor,4,Consulting,2025-01-25,2025-03-04,2398,8.8,Neural Networks Co -AI05760,NLP Engineer,138054,CAD,172568,EX,FL,Canada,M,Canada,0,"Spark, TensorFlow, PyTorch, NLP, Docker",Master,11,Manufacturing,2024-11-10,2024-12-08,2103,10,Machine Intelligence Group -AI05761,AI Specialist,217066,USD,217066,EX,FL,United States,M,Ukraine,100,"GCP, Scala, Data Visualization",PhD,14,Gaming,2025-01-09,2025-02-23,1157,8.5,Algorithmic Solutions -AI05762,Data Analyst,210737,USD,210737,EX,CT,Israel,S,Sweden,50,"Statistics, Mathematics, PyTorch, AWS, Computer Vision",PhD,10,Government,2024-01-22,2024-04-03,2498,8,Machine Intelligence Group -AI05763,Research Scientist,69613,SGD,90497,EN,PT,Singapore,L,Singapore,50,"Python, GCP, Azure",Master,1,Automotive,2024-03-22,2024-05-16,1729,8.4,Algorithmic Solutions -AI05764,AI Product Manager,93437,USD,93437,MI,FL,Finland,M,Finland,50,"Kubernetes, Python, Mathematics, Docker",PhD,3,Healthcare,2025-01-03,2025-02-24,1095,9.6,Future Systems -AI05765,AI Architect,111139,CHF,100025,MI,FT,Switzerland,M,Czech Republic,100,"Kubernetes, Azure, Data Visualization, Python",Bachelor,2,Retail,2024-01-28,2024-03-14,690,7.8,TechCorp Inc -AI05766,AI Architect,91789,EUR,78021,SE,CT,France,S,Belgium,50,"NLP, SQL, Python, TensorFlow",PhD,6,Manufacturing,2024-07-01,2024-07-21,2003,7.1,TechCorp Inc -AI05767,Deep Learning Engineer,103244,AUD,139379,SE,CT,Australia,M,Australia,50,"Python, TensorFlow, Spark, GCP",Bachelor,5,Finance,2024-07-21,2024-08-08,601,6.1,Future Systems -AI05768,Data Analyst,134116,USD,134116,SE,CT,South Korea,L,South Korea,50,"GCP, Git, Java",Associate,9,Retail,2024-07-27,2024-09-22,2148,9.4,Autonomous Tech -AI05769,Machine Learning Engineer,97581,USD,97581,EX,FT,China,M,China,50,"Spark, AWS, Deep Learning",Associate,10,Retail,2024-06-18,2024-07-12,1179,8.8,Neural Networks Co -AI05770,Autonomous Systems Engineer,62705,USD,62705,SE,FT,China,M,China,100,"Java, PyTorch, AWS, Spark",Associate,8,Media,2024-05-11,2024-06-07,1072,6.8,Autonomous Tech -AI05771,Principal Data Scientist,101330,EUR,86131,MI,CT,Netherlands,M,Netherlands,100,"Kubernetes, AWS, Spark, Computer Vision",Bachelor,2,Retail,2024-12-07,2025-02-01,2469,8.4,Algorithmic Solutions -AI05772,Deep Learning Engineer,96335,USD,96335,MI,FT,Norway,M,Norway,0,"Linux, AWS, Git, Scala",Associate,4,Gaming,2024-06-16,2024-08-18,1862,6.3,Digital Transformation LLC -AI05773,Research Scientist,139068,USD,139068,MI,CT,Norway,L,Norway,50,"PyTorch, Spark, TensorFlow, Deep Learning",Master,4,Telecommunications,2024-10-10,2024-10-25,1147,9.1,Algorithmic Solutions -AI05774,AI Architect,70157,USD,70157,EN,FL,United States,S,Vietnam,100,"Spark, Python, Docker, Tableau",PhD,0,Media,2024-08-31,2024-11-12,623,9.2,Algorithmic Solutions -AI05775,AI Specialist,74222,EUR,63089,MI,CT,Germany,M,Ireland,50,"Data Visualization, Tableau, Computer Vision",Associate,3,Consulting,2024-03-27,2024-04-20,1609,8.5,Quantum Computing Inc -AI05776,Autonomous Systems Engineer,53889,USD,53889,SE,CT,India,M,India,50,"NLP, Python, PyTorch, AWS",PhD,9,Manufacturing,2024-12-13,2025-02-06,1295,7.1,TechCorp Inc -AI05777,AI Consultant,59745,AUD,80656,EN,PT,Australia,S,Australia,0,"AWS, Data Visualization, Linux",PhD,1,Real Estate,2025-01-21,2025-03-04,2003,6.5,Smart Analytics -AI05778,Machine Learning Engineer,93809,USD,93809,MI,CT,Denmark,M,Denmark,0,"SQL, PyTorch, GCP, R, Linux",Bachelor,4,Government,2024-09-07,2024-10-10,500,8.2,Predictive Systems -AI05779,Research Scientist,56388,EUR,47930,EN,FL,Austria,L,South Korea,100,"Data Visualization, Computer Vision, GCP, TensorFlow, Tableau",Associate,1,Real Estate,2024-05-20,2024-07-16,733,8.8,Smart Analytics -AI05780,Machine Learning Researcher,73376,USD,73376,EX,FT,China,S,China,0,"Computer Vision, Git, Hadoop, NLP, Linux",PhD,16,Energy,2024-06-18,2024-07-02,1032,5.5,Digital Transformation LLC -AI05781,NLP Engineer,246014,USD,246014,EX,PT,Finland,L,Finland,0,"AWS, Kubernetes, Git, Java",Bachelor,11,Education,2024-03-09,2024-04-11,1900,8.7,DataVision Ltd -AI05782,Data Engineer,75181,CAD,93976,MI,FT,Canada,M,Canada,100,"Spark, NLP, Python, TensorFlow",Master,4,Finance,2024-12-06,2025-02-06,936,9.9,Cloud AI Solutions -AI05783,Research Scientist,175703,USD,175703,EX,PT,Israel,M,Thailand,0,"Git, Spark, Data Visualization, SQL",Bachelor,16,Retail,2024-07-18,2024-09-04,1971,8.4,TechCorp Inc -AI05784,Deep Learning Engineer,120364,CAD,150455,SE,FT,Canada,M,Portugal,100,"NLP, TensorFlow, Scala",PhD,7,Technology,2024-08-23,2024-10-24,635,5.7,DeepTech Ventures -AI05785,Computer Vision Engineer,76445,USD,76445,MI,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Hadoop, NLP, Statistics",Bachelor,2,Government,2024-06-30,2024-08-24,787,9.2,Digital Transformation LLC -AI05786,AI Software Engineer,93159,CHF,83843,EN,PT,Switzerland,M,Switzerland,50,"Scala, Azure, GCP, SQL, Mathematics",PhD,0,Government,2024-10-20,2024-12-20,1154,8.3,Advanced Robotics -AI05787,Machine Learning Researcher,157430,EUR,133816,SE,FT,Germany,L,Italy,0,"SQL, Spark, TensorFlow, Linux",PhD,5,Real Estate,2024-07-15,2024-09-09,1632,9.9,Predictive Systems -AI05788,NLP Engineer,97775,EUR,83109,MI,FL,Germany,L,Germany,100,"Spark, Statistics, Git",Associate,2,Education,2025-01-05,2025-03-17,1419,8.2,Quantum Computing Inc -AI05789,NLP Engineer,59315,USD,59315,EN,FT,Sweden,S,Thailand,50,"R, Linux, Tableau, Kubernetes, AWS",Bachelor,0,Education,2024-05-24,2024-08-01,2125,9.9,Neural Networks Co -AI05790,AI Product Manager,135321,EUR,115023,SE,FT,France,L,France,50,"Hadoop, Python, Mathematics, Data Visualization",Bachelor,8,Transportation,2024-04-17,2024-06-01,1089,8.6,Smart Analytics -AI05791,AI Software Engineer,54243,SGD,70516,EN,PT,Singapore,S,Czech Republic,100,"TensorFlow, Tableau, Mathematics",Bachelor,0,Telecommunications,2024-01-17,2024-02-11,1715,9,Algorithmic Solutions -AI05792,AI Architect,66510,SGD,86463,EN,PT,Singapore,L,Singapore,0,"NLP, Linux, Statistics",Bachelor,0,Government,2025-02-10,2025-04-16,890,8.8,Autonomous Tech -AI05793,Data Engineer,290571,USD,290571,EX,CT,Norway,M,Norway,50,"R, TensorFlow, Git",Bachelor,11,Healthcare,2024-07-26,2024-08-12,1050,5.6,Cognitive Computing -AI05794,Machine Learning Researcher,174210,USD,174210,SE,CT,United States,L,United States,50,"Java, GCP, Hadoop, Deep Learning",Associate,6,Telecommunications,2024-11-09,2024-12-17,718,5.2,DataVision Ltd -AI05795,Autonomous Systems Engineer,187877,USD,187877,SE,FL,United States,L,Latvia,100,"Git, Data Visualization, SQL",PhD,8,Technology,2024-06-23,2024-07-29,1005,7.8,Cognitive Computing -AI05796,AI Product Manager,238675,EUR,202874,EX,CT,Netherlands,M,Netherlands,100,"Git, Data Visualization, Spark, R, Computer Vision",PhD,12,Energy,2025-01-09,2025-02-26,1576,7.2,Algorithmic Solutions -AI05797,Machine Learning Researcher,115479,EUR,98157,SE,CT,France,L,France,100,"Deep Learning, Azure, PyTorch, Kubernetes",Associate,8,Government,2025-01-01,2025-01-19,883,8.1,Algorithmic Solutions -AI05798,AI Consultant,89054,USD,89054,MI,CT,United States,S,United States,0,"Git, SQL, PyTorch",Associate,3,Healthcare,2024-10-22,2024-11-23,1689,9.2,AI Innovations -AI05799,Deep Learning Engineer,161406,USD,161406,SE,CT,Israel,L,Israel,0,"AWS, Computer Vision, MLOps, Python, Mathematics",Master,5,Finance,2024-03-30,2024-06-04,911,6.6,Advanced Robotics -AI05800,AI Research Scientist,64215,GBP,48161,EN,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, Mathematics, GCP, Scala, NLP",Bachelor,0,Automotive,2024-03-30,2024-05-26,1193,5.7,Future Systems -AI05801,Autonomous Systems Engineer,64511,USD,64511,MI,FL,South Korea,M,Vietnam,100,"Python, TensorFlow, Spark, PyTorch",Associate,4,Real Estate,2024-02-19,2024-04-30,1416,8.6,Digital Transformation LLC -AI05802,Autonomous Systems Engineer,126060,USD,126060,EX,CT,China,L,China,50,"Scala, Docker, GCP, Git",Associate,18,Real Estate,2024-06-27,2024-09-04,2144,6.8,Algorithmic Solutions -AI05803,Autonomous Systems Engineer,54920,USD,54920,EN,CT,South Korea,S,Norway,0,"Data Visualization, Python, Docker, Java",PhD,1,Real Estate,2024-03-28,2024-04-22,510,9,DeepTech Ventures -AI05804,AI Research Scientist,266720,GBP,200040,EX,CT,United Kingdom,M,Hungary,0,"Kubernetes, SQL, Docker, Tableau",Bachelor,16,Telecommunications,2024-04-08,2024-05-19,1513,7.1,DeepTech Ventures -AI05805,Principal Data Scientist,54944,AUD,74174,EN,FL,Australia,M,Australia,50,"Azure, Spark, TensorFlow, SQL",Bachelor,1,Manufacturing,2024-02-10,2024-03-08,708,6.3,DeepTech Ventures -AI05806,AI Product Manager,152987,USD,152987,SE,FL,Norway,S,Norway,100,"NLP, MLOps, Data Visualization",Associate,6,Government,2024-03-09,2024-04-10,1687,8.5,Quantum Computing Inc -AI05807,AI Consultant,158814,CHF,142933,SE,CT,Switzerland,M,Switzerland,50,"Azure, Kubernetes, Linux, Docker, Mathematics",Bachelor,8,Retail,2024-12-27,2025-03-10,1650,9.7,Advanced Robotics -AI05808,AI Software Engineer,92910,USD,92910,EX,CT,China,S,India,100,"MLOps, Hadoop, Spark, Deep Learning, Python",Bachelor,15,Consulting,2024-03-19,2024-04-26,1516,8.9,Machine Intelligence Group -AI05809,Autonomous Systems Engineer,209901,USD,209901,EX,CT,Denmark,L,Denmark,50,"Scala, Java, Azure, Deep Learning",Associate,13,Manufacturing,2024-01-05,2024-02-27,761,6.8,Smart Analytics -AI05810,Computer Vision Engineer,82999,AUD,112049,EN,FL,Australia,L,Australia,0,"Scala, Statistics, Data Visualization",Master,0,Telecommunications,2024-05-28,2024-06-23,2391,9.1,TechCorp Inc -AI05811,Computer Vision Engineer,28848,USD,28848,EN,CT,China,L,Ukraine,50,"Docker, Scala, Linux, Java",Bachelor,1,Energy,2024-03-13,2024-05-21,2267,6.6,Autonomous Tech -AI05812,Computer Vision Engineer,65556,AUD,88501,EN,PT,Australia,M,Latvia,100,"Kubernetes, Java, NLP, AWS",Master,1,Gaming,2024-03-11,2024-04-18,1984,7.5,DataVision Ltd -AI05813,Autonomous Systems Engineer,130176,USD,130176,SE,PT,United States,M,United States,0,"TensorFlow, Spark, Git, Java, AWS",Associate,6,Government,2025-01-31,2025-03-08,789,6.5,Predictive Systems -AI05814,Principal Data Scientist,101126,USD,101126,SE,FT,Finland,M,Philippines,0,"Kubernetes, Docker, SQL, PyTorch",Associate,9,Automotive,2025-01-29,2025-04-11,2420,8.2,Future Systems -AI05815,NLP Engineer,116327,USD,116327,SE,CT,United States,S,United States,100,"SQL, MLOps, Java, AWS, TensorFlow",Bachelor,7,Telecommunications,2024-03-03,2024-03-31,1709,7.6,Cloud AI Solutions -AI05816,AI Consultant,70463,EUR,59894,MI,PT,Austria,M,Japan,100,"Scala, Hadoop, Git, Azure, MLOps",Bachelor,3,Healthcare,2024-07-27,2024-08-23,1950,8.2,Autonomous Tech -AI05817,Machine Learning Engineer,66266,CAD,82833,EN,CT,Canada,M,Canada,0,"Tableau, Python, Kubernetes, Mathematics",Bachelor,1,Telecommunications,2024-12-16,2025-01-09,986,8.2,Quantum Computing Inc -AI05818,Head of AI,61462,EUR,52243,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Python, Spark",Associate,1,Manufacturing,2024-08-25,2024-10-14,1730,8.2,Digital Transformation LLC -AI05819,ML Ops Engineer,169366,USD,169366,EX,PT,Sweden,S,Brazil,50,"GCP, Spark, Tableau",Associate,18,Automotive,2024-12-15,2025-02-01,1988,9.5,Quantum Computing Inc -AI05820,Computer Vision Engineer,128994,JPY,14189340,SE,FL,Japan,L,Japan,100,"PyTorch, Mathematics, Azure",Associate,9,Technology,2024-09-19,2024-10-30,1049,7.5,Algorithmic Solutions -AI05821,Machine Learning Engineer,93837,USD,93837,EN,FT,Norway,M,Norway,50,"Scala, AWS, MLOps",PhD,0,Transportation,2025-02-16,2025-04-11,1859,8.1,Advanced Robotics -AI05822,Robotics Engineer,199989,AUD,269985,EX,FL,Australia,M,Australia,50,"Tableau, Azure, NLP, Linux, Python",Master,11,Technology,2024-10-20,2024-12-26,1214,9.7,Digital Transformation LLC -AI05823,Research Scientist,120387,EUR,102329,SE,FL,France,M,France,0,"Linux, SQL, NLP, PyTorch, Hadoop",Associate,8,Finance,2025-01-17,2025-03-22,2031,6.2,Algorithmic Solutions -AI05824,AI Consultant,73237,EUR,62251,EN,CT,Netherlands,M,Netherlands,100,"MLOps, Hadoop, Scala, Computer Vision, TensorFlow",PhD,1,Energy,2024-03-06,2024-04-10,898,7.5,Predictive Systems -AI05825,Robotics Engineer,201799,EUR,171529,EX,CT,Germany,M,Germany,0,"AWS, PyTorch, Mathematics, TensorFlow",Bachelor,19,Gaming,2024-07-28,2024-08-14,1838,9.7,AI Innovations -AI05826,Deep Learning Engineer,134094,USD,134094,EX,FL,South Korea,S,South Korea,100,"Spark, Tableau, SQL, PyTorch, Computer Vision",Bachelor,15,Education,2024-01-08,2024-02-16,1396,5.3,Algorithmic Solutions -AI05827,Machine Learning Engineer,93152,CHF,83837,MI,CT,Switzerland,S,Norway,0,"TensorFlow, AWS, Spark, Statistics",Associate,4,Finance,2024-08-30,2024-09-15,1329,7.2,Cognitive Computing -AI05828,AI Consultant,50681,CAD,63351,EN,FL,Canada,S,Canada,50,"MLOps, Deep Learning, Linux, Hadoop",PhD,0,Education,2024-03-18,2024-04-17,640,6.9,Smart Analytics -AI05829,Autonomous Systems Engineer,153066,EUR,130106,SE,CT,Netherlands,L,Netherlands,0,"Docker, Computer Vision, Azure, Tableau",Associate,7,Education,2025-02-06,2025-04-06,2226,7.4,Smart Analytics -AI05830,Data Scientist,113891,USD,113891,MI,FT,Norway,L,Germany,0,"Docker, Statistics, Git, Spark",Master,4,Healthcare,2024-01-30,2024-03-15,1612,9.8,Digital Transformation LLC -AI05831,Machine Learning Engineer,182667,CAD,228334,EX,FL,Canada,S,Canada,50,"Data Visualization, Scala, Python, Tableau",PhD,19,Education,2024-02-06,2024-03-27,693,8.4,DeepTech Ventures -AI05832,Deep Learning Engineer,85673,USD,85673,SE,CT,South Korea,M,Finland,0,"SQL, Linux, Python",Master,9,Energy,2024-10-15,2024-11-22,2316,8.3,Smart Analytics -AI05833,ML Ops Engineer,141382,USD,141382,MI,PT,Norway,M,South Korea,50,"TensorFlow, Azure, Kubernetes, Deep Learning, MLOps",Bachelor,4,Healthcare,2025-01-15,2025-02-23,1098,6.7,DeepTech Ventures -AI05834,Research Scientist,104303,CAD,130379,SE,FL,Canada,S,Canada,100,"Kubernetes, Git, Hadoop, TensorFlow",Associate,5,Gaming,2024-08-13,2024-09-14,2000,7,Algorithmic Solutions -AI05835,AI Consultant,105290,EUR,89497,SE,CT,Netherlands,S,Netherlands,0,"Java, PyTorch, Azure, GCP",PhD,6,Technology,2024-09-09,2024-10-16,2185,8.7,TechCorp Inc -AI05836,ML Ops Engineer,110705,EUR,94099,MI,FT,Netherlands,L,United Kingdom,50,"Docker, Data Visualization, PyTorch",Master,2,Automotive,2024-05-18,2024-07-20,1968,9.5,Digital Transformation LLC -AI05837,Autonomous Systems Engineer,98458,USD,98458,SE,FT,South Korea,S,South Korea,0,"Spark, R, Java, Mathematics, Azure",Associate,5,Real Estate,2024-08-21,2024-10-15,2455,6,AI Innovations -AI05838,Computer Vision Engineer,80189,CHF,72170,EN,CT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Azure, Hadoop",Associate,0,Automotive,2024-08-28,2024-10-11,2452,6.4,Advanced Robotics -AI05839,AI Consultant,152024,EUR,129220,EX,FT,France,L,Thailand,0,"Deep Learning, MLOps, Linux, Kubernetes",Bachelor,12,Finance,2024-01-17,2024-03-13,2051,6.3,Algorithmic Solutions -AI05840,Computer Vision Engineer,144136,USD,144136,EX,PT,Sweden,S,Egypt,0,"Git, Kubernetes, AWS",Master,15,Media,2024-10-17,2024-11-25,756,9.7,DataVision Ltd -AI05841,Head of AI,68248,USD,68248,EN,FT,Ireland,M,Ireland,100,"PyTorch, Scala, Computer Vision, AWS, Deep Learning",Bachelor,0,Technology,2025-02-24,2025-04-09,1649,6.8,Algorithmic Solutions -AI05842,Autonomous Systems Engineer,162400,CAD,203000,EX,CT,Canada,M,Canada,0,"R, Kubernetes, Linux, Tableau, Hadoop",PhD,18,Education,2024-06-05,2024-07-24,1538,7.5,Cloud AI Solutions -AI05843,Computer Vision Engineer,271814,EUR,231042,EX,CT,Austria,L,Austria,0,"MLOps, SQL, Linux",Bachelor,12,Energy,2024-11-30,2025-01-31,1677,5.9,Neural Networks Co -AI05844,Autonomous Systems Engineer,145196,USD,145196,SE,PT,Israel,L,Israel,50,"R, SQL, Java",Bachelor,7,Telecommunications,2024-04-26,2024-06-04,1164,6.3,Predictive Systems -AI05845,Machine Learning Researcher,204480,EUR,173808,EX,FT,Netherlands,S,Ghana,100,"Docker, Kubernetes, Spark",Master,16,Gaming,2024-08-08,2024-09-10,858,9.8,Digital Transformation LLC -AI05846,Head of AI,60712,EUR,51605,EN,CT,France,M,France,50,"MLOps, Python, Docker",Master,1,Government,2024-04-29,2024-06-30,579,6.3,Predictive Systems -AI05847,AI Research Scientist,142958,CAD,178698,SE,CT,Canada,L,Latvia,50,"Java, SQL, Data Visualization, Docker",Master,8,Education,2024-08-30,2024-10-14,649,5.9,Predictive Systems -AI05848,Deep Learning Engineer,73847,USD,73847,MI,FL,Ireland,S,Ireland,50,"Git, Deep Learning, Data Visualization, Computer Vision",Master,3,Energy,2024-01-17,2024-02-07,834,5.7,AI Innovations -AI05849,Deep Learning Engineer,44043,USD,44043,MI,PT,India,L,India,50,"Git, Azure, Spark, Kubernetes",Bachelor,3,Transportation,2024-06-19,2024-07-04,1303,5.9,Neural Networks Co -AI05850,AI Product Manager,230859,CHF,207773,SE,CT,Switzerland,L,Switzerland,50,"Azure, TensorFlow, Data Visualization, NLP",PhD,5,Retail,2025-04-23,2025-06-02,2335,7.8,Algorithmic Solutions -AI05851,Principal Data Scientist,31387,USD,31387,MI,FT,India,M,India,0,"Mathematics, Tableau, MLOps, SQL, Linux",Master,3,Government,2025-03-02,2025-03-28,1711,5.1,Quantum Computing Inc -AI05852,AI Consultant,69067,CAD,86334,EN,PT,Canada,M,Israel,100,"Python, TensorFlow, PyTorch, AWS",Master,0,Gaming,2024-05-02,2024-07-02,1204,8.2,Predictive Systems -AI05853,Principal Data Scientist,131432,USD,131432,SE,FT,Sweden,S,Canada,100,"Linux, PyTorch, Deep Learning, Python",Master,9,Gaming,2024-10-19,2024-12-12,2263,6.5,Autonomous Tech -AI05854,AI Consultant,83942,USD,83942,MI,CT,Ireland,M,Ireland,0,"Python, Docker, Linux, Kubernetes, Git",Master,4,Automotive,2024-11-29,2025-01-05,1333,9.9,Advanced Robotics -AI05855,AI Specialist,261743,JPY,28791730,EX,CT,Japan,M,Japan,0,"NLP, Scala, Linux",Bachelor,14,Transportation,2024-08-17,2024-09-14,1461,6.8,Machine Intelligence Group -AI05856,Autonomous Systems Engineer,81198,USD,81198,EN,FL,Finland,L,Finland,100,"Hadoop, SQL, Data Visualization, Tableau",PhD,0,Media,2024-08-27,2024-09-15,1880,10,Smart Analytics -AI05857,AI Consultant,99681,JPY,10964910,MI,PT,Japan,M,Japan,100,"Linux, PyTorch, SQL, Java",PhD,2,Consulting,2024-10-01,2024-11-26,2486,5.6,Future Systems -AI05858,Principal Data Scientist,116363,EUR,98909,MI,CT,Netherlands,L,Netherlands,100,"Java, Python, Computer Vision",Bachelor,4,Automotive,2025-02-26,2025-04-21,1595,6.8,Machine Intelligence Group -AI05859,AI Architect,167056,USD,167056,SE,CT,Denmark,S,Denmark,100,"Java, SQL, Data Visualization, Git, Deep Learning",Master,5,Consulting,2024-03-25,2024-04-11,2492,9.8,Machine Intelligence Group -AI05860,AI Architect,44476,EUR,37805,EN,FT,Austria,S,Austria,50,"Java, Kubernetes, Scala, Python",Bachelor,1,Government,2025-01-16,2025-03-04,1671,8.9,Quantum Computing Inc -AI05861,Data Scientist,85390,AUD,115277,EN,PT,Australia,L,Australia,0,"SQL, Azure, Mathematics, AWS",Master,0,Consulting,2024-04-28,2024-05-24,1172,5,Quantum Computing Inc -AI05862,NLP Engineer,151511,CHF,136360,SE,PT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Tableau, Docker",Bachelor,5,Manufacturing,2024-04-23,2024-06-24,2354,9.9,Advanced Robotics -AI05863,AI Product Manager,112471,JPY,12371810,MI,FT,Japan,L,Nigeria,100,"NLP, Azure, AWS",Associate,4,Healthcare,2025-03-30,2025-04-14,809,5.1,DataVision Ltd -AI05864,ML Ops Engineer,172627,CHF,155364,SE,CT,Switzerland,M,Switzerland,0,"NLP, Tableau, Mathematics",Associate,8,Telecommunications,2024-12-10,2024-12-27,1336,6,DeepTech Ventures -AI05865,NLP Engineer,233363,USD,233363,EX,FT,Finland,L,Finland,0,"SQL, Computer Vision, TensorFlow",Master,10,Retail,2024-04-08,2024-05-18,2008,6.6,Cognitive Computing -AI05866,Machine Learning Researcher,116985,EUR,99437,SE,PT,Austria,S,United Kingdom,100,"Mathematics, Git, Docker, SQL",Bachelor,5,Finance,2025-01-11,2025-02-19,2373,7.7,Algorithmic Solutions -AI05867,Computer Vision Engineer,184253,GBP,138190,SE,PT,United Kingdom,L,United Kingdom,50,"Kubernetes, Java, Linux",Bachelor,6,Finance,2024-05-01,2024-07-05,2168,7.1,Cloud AI Solutions -AI05868,AI Specialist,118246,USD,118246,MI,FL,Norway,S,Sweden,50,"Linux, SQL, Mathematics",PhD,4,Education,2024-07-12,2024-08-04,1005,7.9,Machine Intelligence Group -AI05869,AI Software Engineer,173631,CHF,156268,SE,FT,Switzerland,L,Austria,100,"MLOps, Git, Azure, NLP, Statistics",Bachelor,5,Real Estate,2025-01-31,2025-03-19,1567,9.5,Digital Transformation LLC -AI05870,Computer Vision Engineer,105596,USD,105596,MI,PT,Finland,L,Finland,0,"Azure, Scala, Java, Kubernetes",Associate,2,Automotive,2024-12-26,2025-01-13,2408,9.6,Autonomous Tech -AI05871,AI Product Manager,239497,USD,239497,EX,CT,Finland,L,Finland,0,"R, Tableau, Kubernetes",PhD,18,Media,2024-04-12,2024-05-03,1848,7.6,Predictive Systems -AI05872,Research Scientist,60880,USD,60880,EN,FT,South Korea,M,Mexico,50,"SQL, Deep Learning, Hadoop, GCP, PyTorch",Master,0,Gaming,2024-02-14,2024-04-08,1842,6.6,Smart Analytics -AI05873,Machine Learning Researcher,192915,CHF,173624,EX,FT,Switzerland,S,Switzerland,50,"MLOps, Azure, Spark, Python, PyTorch",Associate,14,Government,2024-08-06,2024-09-05,1358,9.1,DataVision Ltd -AI05874,NLP Engineer,62398,USD,62398,MI,FT,Israel,S,Israel,0,"AWS, Linux, Deep Learning, R",Bachelor,2,Gaming,2025-03-18,2025-04-08,1025,9.2,Predictive Systems -AI05875,Machine Learning Researcher,87874,USD,87874,MI,CT,Sweden,S,Sweden,0,"Hadoop, NLP, SQL, Kubernetes",Bachelor,2,Healthcare,2024-02-13,2024-03-15,2305,7.8,Future Systems -AI05876,Computer Vision Engineer,76770,GBP,57578,EN,FL,United Kingdom,L,United Kingdom,0,"Python, Azure, SQL",PhD,0,Healthcare,2024-03-21,2024-05-20,669,9.3,Cognitive Computing -AI05877,AI Software Engineer,134200,EUR,114070,SE,CT,France,M,France,0,"Python, TensorFlow, Tableau, SQL",PhD,5,Real Estate,2024-04-15,2024-05-19,1184,8.2,Cloud AI Solutions -AI05878,Machine Learning Engineer,120552,EUR,102469,SE,CT,Netherlands,S,Netherlands,100,"R, Java, AWS, Computer Vision, GCP",Associate,7,Consulting,2024-05-11,2024-06-03,2434,6.5,Smart Analytics -AI05879,AI Specialist,52784,USD,52784,EN,FL,Sweden,S,Sweden,100,"NLP, Kubernetes, SQL, TensorFlow, Tableau",Associate,1,Gaming,2024-07-31,2024-09-23,1275,7.3,Neural Networks Co -AI05880,AI Product Manager,70428,USD,70428,EN,PT,Israel,L,Israel,0,"Hadoop, R, Deep Learning, NLP, GCP",PhD,1,Government,2024-04-25,2024-05-14,1514,8.1,Advanced Robotics -AI05881,Autonomous Systems Engineer,80363,JPY,8839930,MI,CT,Japan,M,France,100,"AWS, Spark, SQL",Associate,3,Transportation,2024-04-04,2024-05-15,1293,5.9,DeepTech Ventures -AI05882,Machine Learning Engineer,168502,CAD,210628,EX,CT,Canada,L,South Africa,0,"Hadoop, Kubernetes, Java, Mathematics",Master,16,Education,2024-08-17,2024-09-23,1036,9.5,Autonomous Tech -AI05883,NLP Engineer,95415,USD,95415,MI,FT,United States,S,United States,50,"Docker, Scala, Git, Tableau, GCP",Associate,2,Technology,2024-08-06,2024-09-26,1802,9.8,TechCorp Inc -AI05884,Principal Data Scientist,57820,GBP,43365,EN,FL,United Kingdom,S,United Kingdom,100,"GCP, SQL, PyTorch",Bachelor,1,Energy,2024-01-18,2024-02-03,1681,9.2,Autonomous Tech -AI05885,AI Consultant,274165,JPY,30158150,EX,FT,Japan,L,Ukraine,100,"Docker, Python, Spark, Git",Master,16,Automotive,2025-01-30,2025-03-16,2388,7.6,Future Systems -AI05886,ML Ops Engineer,242363,USD,242363,EX,FL,Israel,L,Israel,50,"PyTorch, SQL, Linux, Docker, Azure",Bachelor,16,Manufacturing,2024-10-03,2024-10-24,934,8.1,Future Systems -AI05887,AI Consultant,182784,SGD,237619,EX,CT,Singapore,L,Latvia,0,"MLOps, Kubernetes, NLP, Git, Hadoop",Bachelor,18,Media,2024-01-03,2024-02-27,972,5.2,Advanced Robotics -AI05888,AI Architect,76429,SGD,99358,MI,CT,Singapore,S,Singapore,100,"Computer Vision, Hadoop, Tableau, Spark, Data Visualization",Associate,3,Education,2024-05-11,2024-07-12,1395,8.9,Quantum Computing Inc -AI05889,AI Product Manager,66004,USD,66004,SE,FL,China,L,China,50,"Statistics, Python, Data Visualization, MLOps, TensorFlow",Bachelor,7,Media,2024-01-21,2024-02-19,503,6.2,Machine Intelligence Group -AI05890,Principal Data Scientist,151148,GBP,113361,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Docker, Data Visualization, Computer Vision, Azure",Bachelor,7,Manufacturing,2024-10-21,2024-12-30,1588,9.1,Predictive Systems -AI05891,Data Engineer,168460,USD,168460,EX,FT,South Korea,S,Argentina,100,"Docker, Hadoop, Git, PyTorch, Deep Learning",Bachelor,14,Real Estate,2025-01-01,2025-03-05,1317,8.4,Smart Analytics -AI05892,AI Architect,124855,USD,124855,EX,FT,Israel,S,Israel,0,"Git, Python, AWS",Master,16,Education,2024-07-16,2024-09-21,879,6,Machine Intelligence Group -AI05893,Autonomous Systems Engineer,154883,CHF,139395,MI,FT,Switzerland,M,Switzerland,50,"Python, Spark, Kubernetes",PhD,4,Media,2024-10-25,2025-01-05,1623,6.2,Digital Transformation LLC -AI05894,Robotics Engineer,241392,EUR,205183,EX,PT,Austria,L,Austria,50,"Git, GCP, Linux",Associate,18,Gaming,2025-01-11,2025-01-26,2393,7.9,Advanced Robotics -AI05895,AI Specialist,147818,EUR,125645,EX,CT,France,S,Czech Republic,50,"R, Tableau, Kubernetes, SQL, Deep Learning",Bachelor,16,Transportation,2024-05-11,2024-06-26,921,5.9,Quantum Computing Inc -AI05896,Computer Vision Engineer,89182,USD,89182,EN,CT,Ireland,L,Ireland,50,"PyTorch, Hadoop, Python, Deep Learning, MLOps",PhD,0,Media,2025-02-07,2025-03-25,575,6.5,Cognitive Computing -AI05897,Robotics Engineer,48483,USD,48483,EN,FT,South Korea,S,South Korea,50,"Python, Data Visualization, Spark",PhD,1,Automotive,2025-03-07,2025-04-02,1954,6.1,Advanced Robotics -AI05898,Machine Learning Engineer,39290,USD,39290,MI,CT,China,M,Argentina,100,"Scala, Hadoop, NLP",Master,4,Finance,2025-02-08,2025-03-07,2097,9.5,DataVision Ltd -AI05899,Data Analyst,60878,EUR,51746,EN,FT,Austria,L,Austria,50,"Git, Java, TensorFlow, Statistics",Bachelor,1,Energy,2024-09-18,2024-11-01,639,7.1,Autonomous Tech -AI05900,Computer Vision Engineer,232706,JPY,25597660,EX,PT,Japan,S,Japan,50,"Python, TensorFlow, Kubernetes, Azure, Data Visualization",PhD,14,Real Estate,2024-06-23,2024-08-05,1494,6.7,Quantum Computing Inc -AI05901,AI Research Scientist,52076,EUR,44265,EN,PT,Austria,M,Ireland,50,"Statistics, TensorFlow, SQL, MLOps",Bachelor,0,Technology,2024-09-19,2024-10-07,971,8.7,Future Systems -AI05902,Data Engineer,198461,CAD,248076,EX,PT,Canada,M,Canada,50,"Java, Kubernetes, PyTorch, Statistics",Associate,11,Finance,2024-04-16,2024-06-13,580,5.6,Predictive Systems -AI05903,Computer Vision Engineer,37606,USD,37606,EN,PT,China,L,China,100,"AWS, Git, SQL",PhD,0,Telecommunications,2024-04-03,2024-05-26,1982,7.8,Digital Transformation LLC -AI05904,AI Consultant,238598,EUR,202808,EX,FT,France,L,France,100,"Linux, Git, Spark",Master,13,Retail,2025-04-15,2025-05-12,567,9,TechCorp Inc -AI05905,AI Research Scientist,117613,EUR,99971,MI,FL,France,L,France,100,"Azure, Kubernetes, Tableau, Computer Vision, Deep Learning",Master,4,Energy,2024-11-25,2024-12-25,1812,8.4,Quantum Computing Inc -AI05906,AI Product Manager,296254,USD,296254,EX,FT,Norway,S,Norway,0,"Python, TensorFlow, PyTorch, Computer Vision",Bachelor,14,Consulting,2024-09-17,2024-11-04,2170,6.2,Quantum Computing Inc -AI05907,AI Product Manager,118508,EUR,100732,SE,FL,Netherlands,S,Netherlands,50,"Kubernetes, Linux, NLP",Associate,7,Government,2025-03-21,2025-05-21,1770,9.9,Digital Transformation LLC -AI05908,Research Scientist,90559,EUR,76975,MI,FT,Germany,M,Germany,50,"Spark, TensorFlow, Git, Mathematics",Bachelor,3,Telecommunications,2024-11-13,2024-12-23,1180,6.2,Machine Intelligence Group -AI05909,NLP Engineer,194311,JPY,21374210,EX,CT,Japan,M,Japan,0,"MLOps, GCP, AWS, Azure, Git",Associate,11,Retail,2025-02-19,2025-05-01,953,7.7,Advanced Robotics -AI05910,Robotics Engineer,96127,USD,96127,MI,FL,Ireland,S,Ireland,0,"Linux, SQL, Data Visualization, PyTorch",Master,3,Media,2025-01-02,2025-02-18,1209,7.8,Advanced Robotics -AI05911,Research Scientist,237774,AUD,320995,EX,FT,Australia,L,Australia,100,"R, Linux, Mathematics, Java",Bachelor,19,Finance,2025-01-23,2025-02-14,2373,7.3,TechCorp Inc -AI05912,AI Product Manager,114455,JPY,12590050,SE,PT,Japan,S,Russia,50,"GCP, Data Visualization, Scala, PyTorch",Associate,5,Gaming,2024-04-14,2024-06-19,1943,9,Quantum Computing Inc -AI05913,AI Specialist,70786,CHF,63707,EN,CT,Switzerland,S,Switzerland,0,"R, Java, Azure, Computer Vision",PhD,0,Finance,2025-03-20,2025-04-19,699,5.4,Autonomous Tech -AI05914,AI Software Engineer,38502,USD,38502,MI,FL,China,M,China,50,"GCP, PyTorch, Data Visualization, TensorFlow",Associate,3,Manufacturing,2024-07-19,2024-09-11,776,9.1,Neural Networks Co -AI05915,AI Architect,75059,USD,75059,MI,CT,South Korea,S,South Korea,50,"Git, SQL, MLOps, Mathematics",PhD,3,Education,2024-10-14,2024-12-16,988,5.1,Quantum Computing Inc -AI05916,AI Research Scientist,22820,USD,22820,EN,FL,India,M,India,100,"MLOps, PyTorch, Tableau, AWS, Scala",Associate,1,Consulting,2024-01-17,2024-03-15,2336,7.6,Autonomous Tech -AI05917,NLP Engineer,88433,USD,88433,MI,FL,Israel,S,Israel,0,"Computer Vision, Docker, Mathematics, AWS",PhD,4,Gaming,2024-11-30,2025-01-15,1395,5.4,TechCorp Inc -AI05918,AI Product Manager,202400,AUD,273240,EX,PT,Australia,S,Australia,50,"Python, Azure, Deep Learning",Master,14,Telecommunications,2024-12-06,2025-01-03,636,6,TechCorp Inc -AI05919,ML Ops Engineer,158886,EUR,135053,EX,FT,France,S,Chile,50,"Spark, Linux, NLP",Bachelor,15,Gaming,2024-11-08,2025-01-16,1540,9,Autonomous Tech -AI05920,AI Specialist,101963,EUR,86669,MI,CT,Netherlands,L,Netherlands,50,"Data Visualization, SQL, Python, Spark, Deep Learning",Master,2,Education,2025-04-20,2025-05-16,1011,5.9,Advanced Robotics -AI05921,AI Consultant,86650,USD,86650,MI,FT,Finland,M,Finland,50,"Kubernetes, Git, Azure, NLP, Scala",PhD,4,Manufacturing,2024-08-22,2024-10-31,1975,8.3,Smart Analytics -AI05922,AI Software Engineer,263809,AUD,356142,EX,FT,Australia,L,Ghana,50,"Scala, Python, Computer Vision",Master,13,Gaming,2025-04-28,2025-06-15,512,7.1,Algorithmic Solutions -AI05923,AI Architect,92448,USD,92448,MI,CT,United States,M,United States,0,"GCP, R, PyTorch, SQL",Bachelor,4,Gaming,2024-04-06,2024-04-21,501,6.8,Machine Intelligence Group -AI05924,Machine Learning Engineer,209496,JPY,23044560,EX,FL,Japan,S,Japan,100,"TensorFlow, Spark, Computer Vision, Linux",Master,18,Government,2025-02-07,2025-02-25,1382,7.2,Autonomous Tech -AI05925,Robotics Engineer,72371,AUD,97701,MI,CT,Australia,M,Australia,0,"TensorFlow, Docker, Computer Vision, Linux",Master,4,Telecommunications,2024-12-03,2025-01-12,899,6.9,Future Systems -AI05926,AI Consultant,21755,USD,21755,EN,FL,India,S,India,0,"Azure, TensorFlow, Tableau, Mathematics, PyTorch",Associate,0,Finance,2024-11-27,2025-01-21,1420,8.1,Autonomous Tech -AI05927,Data Engineer,92976,USD,92976,MI,PT,Sweden,M,Sweden,0,"Tableau, Mathematics, Scala, Computer Vision",PhD,3,Automotive,2025-03-01,2025-04-16,900,8.9,Algorithmic Solutions -AI05928,Machine Learning Engineer,148362,AUD,200289,SE,CT,Australia,L,Belgium,100,"Python, Deep Learning, Spark, Mathematics",Bachelor,6,Retail,2024-12-27,2025-01-25,841,6.3,DataVision Ltd -AI05929,Data Analyst,50796,AUD,68575,EN,FL,Australia,S,Australia,100,"SQL, Kubernetes, MLOps",PhD,0,Transportation,2025-04-28,2025-06-12,1502,7,Digital Transformation LLC -AI05930,Autonomous Systems Engineer,123224,AUD,166352,SE,CT,Australia,L,Australia,100,"Python, Kubernetes, Data Visualization, Java",PhD,5,Finance,2024-12-08,2025-01-05,2333,8.8,Predictive Systems -AI05931,Principal Data Scientist,230556,JPY,25361160,EX,FT,Japan,M,Japan,100,"Git, SQL, Scala, MLOps",PhD,18,Telecommunications,2025-02-08,2025-03-25,2163,7.1,Autonomous Tech -AI05932,AI Research Scientist,148164,USD,148164,SE,CT,Denmark,M,Denmark,100,"Java, Hadoop, Mathematics",Associate,6,Retail,2025-02-26,2025-03-31,606,8,Advanced Robotics -AI05933,AI Research Scientist,80479,USD,80479,MI,FL,Finland,S,Poland,0,"Linux, Docker, NLP, Kubernetes, Tableau",Master,4,Energy,2024-05-31,2024-07-12,2043,6.1,Machine Intelligence Group -AI05934,Machine Learning Engineer,109612,USD,109612,SE,PT,Sweden,M,Argentina,50,"Python, Data Visualization, Git, Spark, GCP",Bachelor,6,Transportation,2024-06-27,2024-08-13,1783,10,Neural Networks Co -AI05935,Research Scientist,194931,JPY,21442410,EX,FT,Japan,M,Japan,0,"Azure, Python, Computer Vision",Master,10,Media,2024-07-07,2024-09-13,799,5.7,Quantum Computing Inc -AI05936,Head of AI,111273,SGD,144655,SE,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Docker, Data Visualization",Associate,5,Healthcare,2024-10-12,2024-11-19,893,6.7,Cloud AI Solutions -AI05937,Computer Vision Engineer,52668,EUR,44768,EN,FT,Austria,S,Australia,100,"TensorFlow, Kubernetes, GCP",Associate,0,Education,2025-02-17,2025-03-17,2461,7.1,Algorithmic Solutions -AI05938,AI Specialist,190969,EUR,162324,EX,FL,Netherlands,S,Canada,0,"Docker, Java, Mathematics, PyTorch, TensorFlow",Master,14,Media,2024-02-13,2024-03-31,1311,6.6,Advanced Robotics -AI05939,Research Scientist,211110,CHF,189999,EX,FT,Switzerland,S,Switzerland,100,"SQL, Git, Tableau, Statistics",Associate,14,Energy,2025-03-04,2025-05-09,1747,8.1,Cloud AI Solutions -AI05940,Data Scientist,99999,CHF,89999,EN,FL,Switzerland,S,Switzerland,50,"PyTorch, Linux, Hadoop",Associate,0,Real Estate,2025-04-11,2025-05-13,788,9.6,Neural Networks Co -AI05941,AI Software Engineer,108942,USD,108942,MI,CT,Norway,L,Norway,50,"Linux, Kubernetes, Python, TensorFlow",Bachelor,4,Government,2024-12-09,2025-01-16,926,7.4,Neural Networks Co -AI05942,ML Ops Engineer,131962,AUD,178149,SE,CT,Australia,S,Australia,50,"Java, TensorFlow, Docker, GCP",Associate,9,Gaming,2024-03-14,2024-04-20,550,7.8,Predictive Systems -AI05943,Computer Vision Engineer,76651,EUR,65153,MI,FL,Austria,S,Austria,100,"AWS, Tableau, Kubernetes",Associate,2,Consulting,2024-10-07,2024-11-28,2276,9.3,DataVision Ltd -AI05944,Deep Learning Engineer,98325,USD,98325,EN,PT,Norway,L,Sweden,0,"MLOps, GCP, Python, Mathematics, TensorFlow",Master,1,Media,2024-02-23,2024-03-10,534,5.5,Quantum Computing Inc -AI05945,Robotics Engineer,62079,USD,62079,SE,FL,China,M,China,100,"Scala, Git, Kubernetes, SQL",Master,8,Healthcare,2024-03-28,2024-04-23,1221,8.8,Advanced Robotics -AI05946,ML Ops Engineer,95740,USD,95740,EN,CT,Denmark,L,Denmark,0,"NLP, Spark, SQL, Python",Bachelor,1,Gaming,2025-01-20,2025-03-21,1209,6.5,Future Systems -AI05947,AI Product Manager,105725,USD,105725,SE,CT,Finland,S,Norway,100,"Spark, Git, Linux",PhD,6,Telecommunications,2025-02-16,2025-03-11,615,10,Advanced Robotics -AI05948,Robotics Engineer,187160,CHF,168444,SE,PT,Switzerland,M,Sweden,0,"Python, Git, TensorFlow",PhD,9,Gaming,2024-03-19,2024-04-02,2451,8.5,Autonomous Tech -AI05949,Principal Data Scientist,222856,USD,222856,EX,CT,Ireland,M,Ireland,0,"Python, Data Visualization, TensorFlow, Scala",Bachelor,14,Government,2025-04-01,2025-05-13,1792,8.4,AI Innovations -AI05950,Head of AI,73259,USD,73259,MI,FT,South Korea,S,South Korea,0,"Git, Java, Python",Master,2,Finance,2024-04-16,2024-06-28,1797,5.5,DataVision Ltd -AI05951,Data Engineer,117240,USD,117240,SE,PT,Ireland,S,Ireland,50,"GCP, R, Deep Learning, Tableau",Associate,7,Technology,2024-09-19,2024-11-13,2169,6,Algorithmic Solutions -AI05952,AI Product Manager,124299,USD,124299,SE,FT,Finland,M,Finland,50,"TensorFlow, Python, Mathematics, Statistics, AWS",PhD,8,Finance,2024-04-16,2024-05-04,2498,7,Autonomous Tech -AI05953,Robotics Engineer,67930,EUR,57741,EN,PT,Netherlands,S,Netherlands,50,"SQL, AWS, Data Visualization, R",Master,0,Media,2024-11-19,2024-12-12,663,6.2,Machine Intelligence Group -AI05954,NLP Engineer,85388,EUR,72580,EN,FT,Germany,L,Germany,100,"Java, Azure, Hadoop, Spark",Bachelor,1,Finance,2024-03-16,2024-04-17,610,7.8,Advanced Robotics -AI05955,Machine Learning Researcher,42537,USD,42537,EN,CT,South Korea,S,South Korea,50,"GCP, Kubernetes, Python, Azure, Statistics",Bachelor,1,Manufacturing,2025-02-22,2025-04-25,2004,6.3,Neural Networks Co -AI05956,AI Software Engineer,109665,CAD,137081,SE,FT,Canada,M,Canada,100,"Java, Kubernetes, Mathematics",PhD,9,Real Estate,2024-10-03,2024-12-02,2250,7.3,Neural Networks Co -AI05957,Data Scientist,78478,USD,78478,EN,FT,Norway,M,China,50,"Mathematics, Kubernetes, Docker, Azure, Scala",Associate,1,Automotive,2024-06-28,2024-08-16,1775,6,DataVision Ltd -AI05958,Principal Data Scientist,127696,USD,127696,SE,FT,Finland,L,Finland,0,"Azure, Mathematics, Linux, MLOps, Tableau",Master,5,Gaming,2024-08-14,2024-09-26,610,9.3,Neural Networks Co -AI05959,AI Product Manager,75623,USD,75623,MI,PT,South Korea,S,South Korea,0,"Scala, Kubernetes, Git",PhD,3,Transportation,2024-03-03,2024-04-22,2215,9.3,Cognitive Computing -AI05960,Deep Learning Engineer,221113,AUD,298503,EX,FT,Australia,L,Australia,0,"AWS, Spark, MLOps, Python",Master,19,Gaming,2024-11-03,2024-12-24,1616,5.9,TechCorp Inc -AI05961,Deep Learning Engineer,171238,CAD,214048,EX,CT,Canada,L,Canada,50,"PyTorch, Spark, Tableau, MLOps",Bachelor,14,Automotive,2025-02-05,2025-04-08,1948,9.9,Digital Transformation LLC -AI05962,Robotics Engineer,201912,USD,201912,EX,FT,Israel,L,Israel,100,"GCP, R, PyTorch, Spark, Mathematics",PhD,18,Energy,2025-03-11,2025-04-03,1298,5.7,DataVision Ltd -AI05963,AI Research Scientist,205861,USD,205861,EX,FT,Sweden,S,Sweden,0,"Python, TensorFlow, Kubernetes, Azure, Tableau",Bachelor,15,Media,2025-04-16,2025-06-02,1682,7,Cloud AI Solutions -AI05964,Deep Learning Engineer,302543,USD,302543,EX,PT,Norway,L,Norway,0,"Python, Azure, TensorFlow",PhD,12,Automotive,2024-04-26,2024-05-31,582,8.1,Machine Intelligence Group -AI05965,ML Ops Engineer,115521,EUR,98193,MI,PT,Austria,L,Austria,0,"Azure, Git, Scala, Java",PhD,4,Telecommunications,2024-05-11,2024-07-13,2101,9.5,Cognitive Computing -AI05966,Data Engineer,50057,USD,50057,SE,PT,China,M,China,100,"PyTorch, Tableau, TensorFlow, Azure",Bachelor,9,Retail,2024-03-05,2024-05-12,722,9.3,Cloud AI Solutions -AI05967,Computer Vision Engineer,139280,EUR,118388,SE,CT,Austria,M,Austria,0,"GCP, PyTorch, Data Visualization, Statistics, R",Associate,9,Real Estate,2024-07-06,2024-08-12,2434,6.5,Neural Networks Co -AI05968,AI Research Scientist,80202,USD,80202,EN,CT,Denmark,S,Denmark,0,"Spark, SQL, R, Deep Learning",PhD,1,Government,2024-01-15,2024-03-19,1892,8.2,TechCorp Inc -AI05969,Computer Vision Engineer,115152,USD,115152,SE,PT,Ireland,S,Ireland,100,"Spark, Git, NLP",Associate,7,Media,2024-01-15,2024-02-29,1179,7.3,AI Innovations -AI05970,Deep Learning Engineer,104936,SGD,136417,MI,FL,Singapore,M,Singapore,50,"Java, AWS, PyTorch",Associate,3,Automotive,2024-11-07,2025-01-05,1188,6.7,Future Systems -AI05971,Robotics Engineer,292055,USD,292055,EX,PT,Norway,L,Norway,100,"Kubernetes, Git, Computer Vision, Deep Learning, Mathematics",Master,10,Media,2025-01-20,2025-02-08,1589,9.8,Algorithmic Solutions -AI05972,ML Ops Engineer,129611,USD,129611,SE,PT,Sweden,S,Sweden,100,"AWS, Hadoop, NLP",Bachelor,8,Real Estate,2024-03-02,2024-04-23,1529,8.9,Autonomous Tech -AI05973,Computer Vision Engineer,56599,USD,56599,SE,CT,China,L,China,100,"Python, MLOps, Data Visualization, Deep Learning, R",Bachelor,9,Education,2024-11-23,2024-12-13,2269,7.7,Predictive Systems -AI05974,AI Software Engineer,66137,CAD,82671,MI,FL,Canada,S,Italy,0,"Kubernetes, AWS, Azure",PhD,3,Real Estate,2024-02-23,2024-04-28,508,5.8,DeepTech Ventures -AI05975,AI Specialist,83658,CAD,104573,MI,FT,Canada,L,Canada,0,"R, SQL, PyTorch, NLP",PhD,2,Gaming,2025-04-21,2025-05-23,1619,6.4,Autonomous Tech -AI05976,Autonomous Systems Engineer,197361,USD,197361,SE,FL,Denmark,L,Denmark,100,"Statistics, PyTorch, Kubernetes",PhD,7,Finance,2024-02-04,2024-03-26,1427,8.2,TechCorp Inc -AI05977,AI Architect,283431,EUR,240916,EX,PT,Germany,L,Germany,100,"Computer Vision, Kubernetes, R",Associate,19,Technology,2024-01-03,2024-02-29,2104,5,Machine Intelligence Group -AI05978,Head of AI,83530,JPY,9188300,EN,FT,Japan,L,Japan,0,"Spark, Java, Hadoop, Scala",Bachelor,1,Finance,2024-01-02,2024-02-01,629,8,Predictive Systems -AI05979,NLP Engineer,197715,EUR,168058,EX,FL,France,M,France,0,"Python, Linux, Hadoop",Associate,10,Energy,2025-03-05,2025-04-22,2465,8.4,DeepTech Ventures -AI05980,NLP Engineer,88355,EUR,75102,MI,FL,Netherlands,S,Portugal,100,"Data Visualization, Azure, R, MLOps",Master,3,Real Estate,2024-11-27,2024-12-26,2128,7.7,Autonomous Tech -AI05981,Data Analyst,30619,USD,30619,EN,PT,India,L,India,50,"AWS, Linux, Spark, Java",Master,1,Finance,2024-03-27,2024-05-02,1811,9.9,Cloud AI Solutions -AI05982,NLP Engineer,206289,EUR,175346,EX,FL,Austria,S,Netherlands,0,"Scala, MLOps, NLP",Associate,14,Education,2024-09-03,2024-10-03,1611,8.5,Autonomous Tech -AI05983,Head of AI,27137,USD,27137,EN,CT,China,M,Russia,100,"NLP, Git, Hadoop, Computer Vision, Scala",Master,0,Energy,2025-01-14,2025-03-11,1238,5.4,Advanced Robotics -AI05984,Data Engineer,107037,CAD,133796,SE,FL,Canada,M,Canada,0,"GCP, Scala, NLP, Spark",Bachelor,5,Retail,2025-04-30,2025-06-04,2340,6.8,Neural Networks Co -AI05985,NLP Engineer,134388,USD,134388,SE,FL,South Korea,L,Kenya,50,"GCP, Docker, Python",Associate,6,Manufacturing,2024-06-26,2024-08-27,1415,6.3,Cognitive Computing -AI05986,Data Analyst,154970,EUR,131725,SE,PT,Netherlands,M,Netherlands,0,"Tableau, Kubernetes, TensorFlow",Associate,6,Healthcare,2024-02-17,2024-03-25,1795,5.9,Cloud AI Solutions -AI05987,Autonomous Systems Engineer,127560,USD,127560,MI,CT,United States,L,United States,0,"GCP, AWS, Hadoop",Bachelor,4,Healthcare,2024-02-01,2024-02-26,727,6.2,Digital Transformation LLC -AI05988,Head of AI,71171,AUD,96081,EN,FT,Australia,S,Belgium,100,"Git, SQL, Azure, Spark, Scala",PhD,0,Finance,2024-08-20,2024-09-17,608,8.1,Neural Networks Co -AI05989,ML Ops Engineer,249331,USD,249331,EX,FL,United States,M,United States,0,"Scala, Kubernetes, Mathematics, Python",Bachelor,12,Telecommunications,2024-02-20,2024-04-13,1618,8.7,DataVision Ltd -AI05990,Research Scientist,130515,SGD,169670,SE,PT,Singapore,S,Singapore,0,"NLP, Deep Learning, Statistics",Associate,6,Manufacturing,2025-04-01,2025-05-16,2354,7,TechCorp Inc -AI05991,ML Ops Engineer,57678,EUR,49026,EN,FT,Austria,M,Austria,0,"Statistics, TensorFlow, Data Visualization, Mathematics, Computer Vision",Bachelor,1,Government,2024-05-25,2024-07-05,1904,7.2,Cloud AI Solutions -AI05992,AI Product Manager,269938,USD,269938,EX,FL,Denmark,S,Denmark,50,"Python, Kubernetes, MLOps",Master,16,Transportation,2024-02-08,2024-02-28,789,9.6,Algorithmic Solutions -AI05993,Computer Vision Engineer,63932,USD,63932,SE,FL,China,S,China,0,"GCP, MLOps, Hadoop, NLP",Associate,5,Government,2024-09-13,2024-11-14,753,9.6,Smart Analytics -AI05994,Principal Data Scientist,151633,USD,151633,EX,PT,Sweden,S,Philippines,0,"Python, R, Git",PhD,14,Telecommunications,2024-03-24,2024-04-26,1334,6.4,Advanced Robotics -AI05995,AI Research Scientist,149659,EUR,127210,EX,FT,Austria,L,Poland,100,"TensorFlow, Hadoop, Data Visualization, Docker",Master,14,Energy,2024-10-02,2024-12-03,809,9.1,Cloud AI Solutions -AI05996,AI Architect,63919,USD,63919,EX,FL,China,S,Luxembourg,50,"SQL, MLOps, Kubernetes, Azure",PhD,17,Consulting,2025-04-01,2025-05-30,860,5.8,Algorithmic Solutions -AI05997,Head of AI,189843,USD,189843,EX,PT,Denmark,S,Sweden,100,"TensorFlow, Kubernetes, GCP, Statistics, PyTorch",Associate,11,Retail,2024-01-31,2024-03-21,2054,8.8,AI Innovations -AI05998,NLP Engineer,72310,EUR,61464,MI,PT,Germany,M,Philippines,0,"MLOps, SQL, PyTorch, AWS, Linux",Associate,4,Media,2024-04-24,2024-06-16,1435,8.2,Digital Transformation LLC -AI05999,Computer Vision Engineer,90085,GBP,67564,MI,CT,United Kingdom,M,United Kingdom,50,"Linux, Git, R, Python",Associate,3,Government,2024-03-06,2024-04-23,2417,5.2,Cognitive Computing -AI06000,Head of AI,84107,USD,84107,MI,CT,Israel,M,Israel,0,"R, SQL, Computer Vision",Master,3,Retail,2024-05-21,2024-06-30,1588,5.3,Neural Networks Co -AI06001,AI Architect,99493,USD,99493,MI,CT,United States,M,United States,0,"Python, Git, R",PhD,3,Manufacturing,2025-04-12,2025-06-02,1258,6.7,Algorithmic Solutions -AI06002,Computer Vision Engineer,76756,EUR,65243,MI,PT,Netherlands,S,Netherlands,0,"Deep Learning, Python, Linux, SQL",Bachelor,4,Media,2025-01-17,2025-03-16,1000,5.4,Autonomous Tech -AI06003,Robotics Engineer,74296,GBP,55722,EN,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Spark, R, Data Visualization, Git",Master,1,Automotive,2025-03-09,2025-05-16,2465,6.7,Cloud AI Solutions -AI06004,Machine Learning Engineer,139465,JPY,15341150,SE,FT,Japan,L,Japan,100,"Azure, Docker, Java, Computer Vision, AWS",PhD,5,Healthcare,2025-04-02,2025-05-28,1680,5.3,Neural Networks Co -AI06005,Deep Learning Engineer,124464,AUD,168026,MI,CT,Australia,L,Russia,100,"Python, Hadoop, Data Visualization, Scala, Kubernetes",Bachelor,3,Retail,2024-10-20,2024-12-14,2113,8.2,Advanced Robotics -AI06006,NLP Engineer,169364,SGD,220173,SE,FL,Singapore,L,Estonia,0,"PyTorch, SQL, Tableau, TensorFlow, R",Master,7,Consulting,2024-11-08,2025-01-13,2464,6,TechCorp Inc -AI06007,ML Ops Engineer,104092,EUR,88478,MI,FL,France,L,France,50,"NLP, Docker, TensorFlow, Python, Azure",PhD,2,Retail,2025-01-20,2025-03-18,1428,8.3,Algorithmic Solutions -AI06008,AI Architect,236270,SGD,307151,EX,FL,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization",Associate,14,Healthcare,2024-01-02,2024-03-13,1176,6.9,DeepTech Ventures -AI06009,Machine Learning Researcher,127297,EUR,108202,SE,FT,Germany,L,Germany,50,"TensorFlow, Statistics, Computer Vision",Bachelor,8,Healthcare,2024-10-26,2024-12-21,1450,8.5,TechCorp Inc -AI06010,AI Architect,59837,USD,59837,SE,CT,China,S,China,50,"R, Tableau, Python, TensorFlow",PhD,8,Healthcare,2024-12-01,2025-01-26,1409,7.7,Neural Networks Co -AI06011,Head of AI,101553,EUR,86320,MI,PT,Austria,M,Austria,50,"Kubernetes, Linux, Deep Learning, Mathematics, Tableau",PhD,2,Telecommunications,2024-04-20,2024-05-26,1360,8.4,Quantum Computing Inc -AI06012,Data Analyst,308290,USD,308290,EX,PT,United States,L,Singapore,50,"Scala, Linux, SQL, PyTorch",Master,17,Consulting,2025-02-20,2025-03-26,2200,8.4,Smart Analytics -AI06013,Deep Learning Engineer,151359,USD,151359,SE,PT,Sweden,L,Sweden,50,"R, Scala, Statistics, Kubernetes, SQL",Bachelor,5,Retail,2024-10-15,2024-12-18,1006,8.4,Neural Networks Co -AI06014,AI Research Scientist,130025,EUR,110521,SE,FT,Germany,L,Germany,0,"PyTorch, SQL, R, Hadoop, Git",Master,7,Media,2024-02-24,2024-03-09,841,6.9,Future Systems -AI06015,ML Ops Engineer,257725,USD,257725,EX,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Azure",Associate,14,Retail,2024-12-07,2025-01-22,666,5.9,Smart Analytics -AI06016,Data Scientist,71138,USD,71138,EN,FT,Norway,M,Norway,50,"SQL, Python, Data Visualization, Mathematics, Linux",Bachelor,0,Automotive,2024-03-07,2024-04-13,2470,7.2,AI Innovations -AI06017,AI Product Manager,148695,USD,148695,SE,CT,Denmark,S,Denmark,50,"MLOps, AWS, R",Associate,8,Energy,2024-03-12,2024-05-20,705,7.3,Quantum Computing Inc -AI06018,Research Scientist,141557,USD,141557,SE,FL,United States,S,United States,50,"Tableau, MLOps, R, SQL",Associate,8,Automotive,2024-04-22,2024-05-09,1135,6.6,Digital Transformation LLC -AI06019,Data Analyst,38669,USD,38669,SE,CT,India,S,United Kingdom,0,"Tableau, Java, Deep Learning, Python, Mathematics",Bachelor,6,Manufacturing,2024-04-23,2024-05-16,2029,5.5,DeepTech Ventures -AI06020,ML Ops Engineer,68663,USD,68663,MI,PT,Israel,M,Czech Republic,0,"PyTorch, Kubernetes, Git, TensorFlow",Master,4,Finance,2025-04-16,2025-05-28,676,6.5,Digital Transformation LLC -AI06021,AI Specialist,44333,USD,44333,MI,FL,India,L,Canada,50,"Scala, Linux, Python",Master,3,Consulting,2025-02-06,2025-02-27,566,9.2,Cloud AI Solutions -AI06022,AI Architect,142509,USD,142509,SE,CT,Denmark,S,Denmark,100,"Computer Vision, TensorFlow, Mathematics, NLP",Associate,5,Telecommunications,2024-08-23,2024-10-30,1296,6.9,Cloud AI Solutions -AI06023,Robotics Engineer,55014,USD,55014,MI,CT,China,L,Ireland,0,"R, Python, Tableau",PhD,2,Healthcare,2024-08-13,2024-10-02,2362,9.8,Autonomous Tech -AI06024,AI Consultant,195813,JPY,21539430,EX,FL,Japan,M,Turkey,100,"GCP, Python, AWS, SQL, TensorFlow",Associate,14,Automotive,2024-01-05,2024-01-29,2233,8.2,AI Innovations -AI06025,Data Scientist,43954,USD,43954,SE,FL,China,S,Romania,100,"Java, Linux, Mathematics, Data Visualization",PhD,6,Energy,2024-03-29,2024-06-03,1318,7.5,Machine Intelligence Group -AI06026,Autonomous Systems Engineer,99890,CAD,124863,MI,FL,Canada,L,Canada,50,"Git, SQL, Computer Vision",PhD,3,Media,2024-10-13,2024-11-23,1008,6.3,Algorithmic Solutions -AI06027,AI Specialist,178380,JPY,19621800,SE,CT,Japan,L,Japan,0,"Git, MLOps, TensorFlow, Python, Tableau",Bachelor,8,Media,2025-03-26,2025-04-22,1368,6.1,Neural Networks Co -AI06028,Principal Data Scientist,121764,USD,121764,SE,FT,Finland,S,South Africa,100,"GCP, Hadoop, Python, TensorFlow, Kubernetes",Master,8,Media,2024-12-17,2025-01-05,2150,5.6,AI Innovations -AI06029,AI Research Scientist,148778,JPY,16365580,EX,FT,Japan,M,Japan,100,"Linux, Java, Data Visualization, Tableau, Kubernetes",Associate,15,Media,2024-03-28,2024-05-07,966,5.3,Digital Transformation LLC -AI06030,ML Ops Engineer,139963,CHF,125967,SE,PT,Switzerland,S,Portugal,100,"Hadoop, NLP, Java, Computer Vision",Master,9,Real Estate,2024-08-31,2024-10-15,1961,7.4,AI Innovations -AI06031,Deep Learning Engineer,75640,GBP,56730,EN,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, Hadoop, Spark",PhD,1,Finance,2024-09-10,2024-11-13,2183,8,Cloud AI Solutions -AI06032,AI Research Scientist,78384,USD,78384,MI,FL,Ireland,M,Ireland,50,"GCP, Spark, Data Visualization",Associate,3,Transportation,2024-04-30,2024-06-01,712,6.2,DataVision Ltd -AI06033,AI Research Scientist,50999,USD,50999,MI,FL,China,L,China,100,"Python, NLP, Kubernetes",PhD,3,Manufacturing,2024-07-26,2024-08-22,1225,5.9,DeepTech Ventures -AI06034,AI Research Scientist,61119,EUR,51951,EN,FL,Germany,L,South Africa,50,"GCP, Scala, TensorFlow, Python, Mathematics",PhD,0,Media,2025-03-20,2025-04-11,1428,8.5,Neural Networks Co -AI06035,AI Architect,99511,SGD,129364,MI,FT,Singapore,L,Latvia,100,"R, Java, Tableau, Python, Linux",Bachelor,4,Finance,2024-04-19,2024-06-06,2368,6.8,Neural Networks Co -AI06036,Deep Learning Engineer,208119,EUR,176901,EX,PT,Germany,S,Germany,0,"PyTorch, Spark, Scala, Java",Associate,12,Technology,2024-05-13,2024-06-24,2228,7,Predictive Systems -AI06037,NLP Engineer,64737,USD,64737,EN,FL,South Korea,L,Egypt,0,"SQL, NLP, MLOps, GCP, Tableau",Associate,1,Real Estate,2024-09-08,2024-09-24,1189,6.3,Machine Intelligence Group -AI06038,Deep Learning Engineer,85166,USD,85166,EX,PT,China,L,China,0,"Java, PyTorch, Mathematics, AWS",PhD,12,Real Estate,2024-03-16,2024-05-04,1675,6.2,Quantum Computing Inc -AI06039,AI Specialist,132470,EUR,112600,MI,FT,Netherlands,L,Belgium,100,"Deep Learning, Kubernetes, GCP, Statistics, Computer Vision",Bachelor,2,Consulting,2024-10-15,2024-12-27,1763,7,Advanced Robotics -AI06040,AI Product Manager,27118,USD,27118,EN,FL,China,S,China,0,"Data Visualization, Python, TensorFlow, Spark",PhD,1,Consulting,2024-06-20,2024-08-19,2259,8.4,Neural Networks Co -AI06041,Head of AI,189995,EUR,161496,EX,FL,Germany,S,Denmark,100,"Scala, GCP, Java, Linux",PhD,13,Finance,2025-02-25,2025-03-13,2204,9,Machine Intelligence Group -AI06042,NLP Engineer,182291,CAD,227864,EX,FL,Canada,M,Turkey,50,"GCP, Java, SQL, NLP, Docker",PhD,15,Media,2025-04-25,2025-06-06,1075,6.7,DataVision Ltd -AI06043,AI Specialist,58125,AUD,78469,EN,FL,Australia,M,Argentina,100,"Python, Mathematics, TensorFlow, Azure, Linux",Associate,0,Technology,2024-07-24,2024-08-29,751,7.1,DataVision Ltd -AI06044,Deep Learning Engineer,304701,CHF,274231,EX,PT,Switzerland,M,Switzerland,100,"Git, Linux, Tableau",Associate,15,Energy,2024-08-08,2024-10-14,990,7.1,Digital Transformation LLC -AI06045,Machine Learning Engineer,28807,USD,28807,EN,PT,India,L,India,50,"R, Python, Docker",Master,0,Retail,2024-04-06,2024-06-09,2227,8.6,Algorithmic Solutions -AI06046,AI Research Scientist,119295,CHF,107366,MI,FT,Switzerland,S,Switzerland,100,"Mathematics, TensorFlow, NLP, Scala",Master,4,Government,2024-12-20,2025-01-05,1352,6.2,Neural Networks Co -AI06047,Data Engineer,75061,EUR,63802,MI,CT,Germany,S,Germany,100,"Python, Statistics, Linux, Spark, Deep Learning",Master,4,Gaming,2025-03-25,2025-05-31,2222,7.7,DeepTech Ventures -AI06048,Principal Data Scientist,134979,EUR,114732,SE,FL,Austria,M,Netherlands,50,"Mathematics, PyTorch, Tableau, Linux",Master,7,Government,2024-06-11,2024-08-07,1909,8.4,DeepTech Ventures -AI06049,Computer Vision Engineer,138134,GBP,103601,SE,FL,United Kingdom,S,United Kingdom,50,"SQL, Kubernetes, Python",Master,6,Real Estate,2024-02-01,2024-02-28,507,5.4,Smart Analytics -AI06050,Head of AI,71317,USD,71317,EN,PT,Ireland,M,Ireland,100,"Deep Learning, Data Visualization, Linux",Associate,1,Education,2025-04-20,2025-06-20,2132,9.6,AI Innovations -AI06051,Robotics Engineer,238482,JPY,26233020,EX,FL,Japan,S,Japan,100,"Data Visualization, Git, Kubernetes, NLP, Python",Master,17,Manufacturing,2024-02-06,2024-03-01,1858,8.4,Future Systems -AI06052,Computer Vision Engineer,217112,EUR,184545,EX,PT,France,L,France,100,"Mathematics, Python, Azure, Linux",Bachelor,17,Retail,2025-01-11,2025-02-09,2235,7.7,Predictive Systems -AI06053,AI Architect,91189,AUD,123105,MI,FT,Australia,S,Australia,50,"MLOps, Kubernetes, R, SQL",Master,4,Government,2025-03-19,2025-05-24,1179,6,Digital Transformation LLC -AI06054,AI Software Engineer,31432,USD,31432,MI,PT,India,M,India,0,"Python, Statistics, TensorFlow, Kubernetes, Azure",PhD,2,Finance,2025-03-14,2025-04-09,1250,7.7,Future Systems -AI06055,AI Software Engineer,203827,EUR,173253,EX,FL,Austria,L,Austria,100,"PyTorch, Python, TensorFlow, Statistics, Data Visualization",Associate,19,Finance,2024-07-13,2024-09-09,2138,7.5,Predictive Systems -AI06056,Data Engineer,78958,EUR,67114,MI,CT,France,M,Ukraine,50,"Mathematics, Azure, Tableau, NLP",Master,3,Education,2024-07-08,2024-08-17,2012,8.5,TechCorp Inc -AI06057,Robotics Engineer,100020,AUD,135027,SE,FT,Australia,S,Australia,50,"Kubernetes, NLP, R, Computer Vision",PhD,9,Finance,2024-08-15,2024-09-09,1515,8.7,Advanced Robotics -AI06058,AI Consultant,168504,USD,168504,EX,FT,Israel,L,Israel,100,"R, SQL, Hadoop, Docker",Bachelor,17,Government,2024-10-15,2024-11-07,1388,9.3,Machine Intelligence Group -AI06059,Deep Learning Engineer,59253,USD,59253,EN,CT,Finland,S,New Zealand,100,"Kubernetes, Computer Vision, TensorFlow",Bachelor,1,Finance,2024-04-02,2024-06-11,2238,6.6,DataVision Ltd -AI06060,Computer Vision Engineer,74984,USD,74984,EX,FT,China,S,Turkey,50,"Hadoop, Data Visualization, Git",PhD,15,Education,2024-07-14,2024-09-23,1980,8.3,Cloud AI Solutions -AI06061,Robotics Engineer,236625,USD,236625,EX,CT,Finland,M,Portugal,100,"Hadoop, Deep Learning, TensorFlow, SQL",Master,15,Energy,2024-09-07,2024-11-09,1087,6.7,Neural Networks Co -AI06062,AI Product Manager,111066,USD,111066,SE,FT,United States,S,United States,0,"SQL, Scala, MLOps",Master,6,Automotive,2025-03-28,2025-05-29,2442,7.6,Cloud AI Solutions -AI06063,AI Research Scientist,123116,USD,123116,MI,PT,Denmark,M,Denmark,100,"Git, Java, NLP",Master,4,Healthcare,2024-02-03,2024-02-26,694,5.7,Advanced Robotics -AI06064,AI Software Engineer,72971,EUR,62025,EN,CT,Netherlands,S,Finland,50,"Git, AWS, Data Visualization, Java",Bachelor,1,Gaming,2024-11-10,2024-11-28,1884,9,AI Innovations -AI06065,Head of AI,73070,CAD,91338,EN,FL,Canada,L,Canada,100,"Linux, Azure, Python",Bachelor,0,Retail,2024-03-06,2024-05-18,1253,6.3,Advanced Robotics -AI06066,Data Engineer,73301,USD,73301,EN,CT,Israel,M,Ukraine,50,"R, Git, Tableau",PhD,0,Manufacturing,2024-12-07,2025-01-16,1946,9.1,AI Innovations -AI06067,Research Scientist,46090,USD,46090,MI,FT,China,L,China,50,"TensorFlow, Kubernetes, Mathematics, PyTorch, AWS",PhD,3,Media,2024-09-03,2024-10-13,2485,8.4,Digital Transformation LLC -AI06068,Principal Data Scientist,268531,USD,268531,EX,FT,Sweden,L,Sweden,50,"SQL, GCP, Statistics",PhD,11,Media,2025-02-13,2025-04-20,1051,5.8,Autonomous Tech -AI06069,Robotics Engineer,116014,CHF,104413,MI,PT,Switzerland,M,Switzerland,100,"Docker, Hadoop, NLP, Kubernetes, Scala",PhD,3,Manufacturing,2024-08-14,2024-10-07,1865,6.8,Cloud AI Solutions -AI06070,Data Analyst,112161,USD,112161,MI,FT,Sweden,L,Sweden,0,"R, Spark, SQL, GCP",Bachelor,2,Gaming,2024-04-03,2024-05-16,2499,9.1,Predictive Systems -AI06071,AI Specialist,62287,USD,62287,EX,FT,India,L,Luxembourg,100,"Tableau, Computer Vision, GCP, Data Visualization",Associate,17,Automotive,2024-07-12,2024-08-10,2286,6.4,Quantum Computing Inc -AI06072,NLP Engineer,71300,USD,71300,EN,FL,Israel,M,Israel,50,"GCP, Spark, PyTorch",Bachelor,0,Consulting,2024-10-19,2024-11-26,2200,6.2,Future Systems -AI06073,Machine Learning Engineer,65583,USD,65583,MI,PT,Finland,S,Russia,0,"R, Kubernetes, Mathematics",Associate,2,Media,2025-02-21,2025-04-14,733,8.9,Future Systems -AI06074,Autonomous Systems Engineer,175971,EUR,149575,EX,PT,Austria,S,Austria,100,"Kubernetes, Computer Vision, GCP, SQL",Bachelor,11,Retail,2025-03-21,2025-05-23,1930,9.4,DeepTech Ventures -AI06075,Robotics Engineer,29541,USD,29541,MI,PT,India,M,India,0,"Python, Docker, Linux",Master,3,Gaming,2025-04-02,2025-04-20,1449,6.3,Advanced Robotics -AI06076,Computer Vision Engineer,76318,USD,76318,MI,PT,South Korea,M,Norway,0,"PyTorch, Java, TensorFlow",Master,2,Technology,2025-02-08,2025-03-07,1449,7.9,DeepTech Ventures -AI06077,AI Consultant,257587,USD,257587,EX,PT,Denmark,S,Denmark,50,"Hadoop, Linux, Deep Learning, Scala, R",Bachelor,11,Healthcare,2024-02-05,2024-03-09,1770,5.1,Smart Analytics -AI06078,Autonomous Systems Engineer,188465,EUR,160195,EX,CT,Austria,S,Austria,50,"Hadoop, Python, NLP",PhD,12,Healthcare,2024-02-06,2024-03-19,1220,8.7,Cloud AI Solutions -AI06079,Robotics Engineer,106976,USD,106976,MI,CT,Ireland,L,Ireland,50,"Java, Kubernetes, GCP, Deep Learning, MLOps",PhD,4,Consulting,2024-11-30,2025-01-12,1164,8.7,AI Innovations -AI06080,Autonomous Systems Engineer,142983,EUR,121536,EX,CT,Germany,M,Germany,50,"TensorFlow, Mathematics, GCP, Python",Master,13,Technology,2024-06-20,2024-08-16,1906,6.4,Predictive Systems -AI06081,AI Research Scientist,61577,USD,61577,EN,CT,Sweden,S,Israel,100,"Python, Tableau, Kubernetes, Scala",PhD,0,Finance,2025-04-13,2025-05-05,2097,5.8,Autonomous Tech -AI06082,Machine Learning Engineer,89159,AUD,120365,MI,FL,Australia,S,Australia,0,"Git, AWS, Data Visualization, Hadoop, Tableau",PhD,2,Government,2024-02-25,2024-04-05,2019,7.9,Algorithmic Solutions -AI06083,AI Research Scientist,98446,USD,98446,EN,FT,Denmark,M,Denmark,100,"Kubernetes, Linux, Scala, Mathematics, MLOps",Associate,0,Technology,2024-07-13,2024-09-22,2393,6.7,DataVision Ltd -AI06084,Machine Learning Engineer,50109,GBP,37582,EN,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, Kubernetes, NLP",Bachelor,1,Healthcare,2025-01-04,2025-02-18,2307,5.3,Cognitive Computing -AI06085,Machine Learning Researcher,78378,USD,78378,MI,FL,South Korea,S,South Korea,0,"Git, Deep Learning, Kubernetes, SQL",Master,4,Media,2024-06-25,2024-09-06,1328,9.3,DataVision Ltd -AI06086,Deep Learning Engineer,72771,CAD,90964,MI,CT,Canada,S,Canada,50,"PyTorch, TensorFlow, Data Visualization",Associate,4,Automotive,2025-03-24,2025-06-04,2063,6.6,Future Systems -AI06087,Data Engineer,269658,USD,269658,EX,CT,Finland,L,Finland,0,"SQL, Hadoop, R, GCP",Bachelor,18,Consulting,2024-09-14,2024-10-25,2037,5.7,Cognitive Computing -AI06088,ML Ops Engineer,94499,CAD,118124,SE,PT,Canada,S,United Kingdom,50,"Data Visualization, MLOps, Git",PhD,6,Media,2024-06-26,2024-08-21,2299,8.2,TechCorp Inc -AI06089,Autonomous Systems Engineer,98191,EUR,83462,MI,FT,France,M,France,0,"Scala, PyTorch, SQL",Master,2,Gaming,2024-10-23,2024-11-10,1994,6.3,Smart Analytics -AI06090,AI Software Engineer,52424,EUR,44560,EN,FL,France,M,Vietnam,50,"Kubernetes, Docker, Tableau, PyTorch, Java",Bachelor,1,Gaming,2024-02-28,2024-05-08,1715,8.9,DeepTech Ventures -AI06091,AI Consultant,58246,EUR,49509,EN,PT,Germany,M,Belgium,0,"Hadoop, Spark, NLP",Master,1,Transportation,2024-09-06,2024-11-12,859,8.7,Quantum Computing Inc -AI06092,Head of AI,267949,AUD,361731,EX,CT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, Python",Bachelor,10,Telecommunications,2024-03-12,2024-04-30,707,9.7,Machine Intelligence Group -AI06093,Machine Learning Engineer,70389,USD,70389,EN,FT,Sweden,S,Thailand,100,"Hadoop, Computer Vision, NLP, Azure, Spark",Master,0,Media,2025-02-27,2025-04-12,861,6.6,Cloud AI Solutions -AI06094,Computer Vision Engineer,189799,USD,189799,EX,FL,Denmark,M,Denmark,100,"Hadoop, Python, TensorFlow, MLOps",Bachelor,17,Energy,2024-08-16,2024-10-16,1028,8.6,Machine Intelligence Group -AI06095,Deep Learning Engineer,71097,USD,71097,EN,CT,South Korea,L,South Korea,0,"SQL, TensorFlow, GCP",Master,0,Media,2025-04-02,2025-06-13,1765,8.6,Cognitive Computing -AI06096,ML Ops Engineer,129008,GBP,96756,MI,CT,United Kingdom,L,United Kingdom,0,"SQL, Hadoop, MLOps, Git",Master,4,Government,2025-04-15,2025-05-30,1561,10,Algorithmic Solutions -AI06097,Robotics Engineer,75236,EUR,63951,MI,FL,Netherlands,S,Netherlands,0,"MLOps, Spark, Docker",Associate,3,Consulting,2024-08-04,2024-08-30,664,9.2,Machine Intelligence Group -AI06098,Autonomous Systems Engineer,169125,USD,169125,EX,CT,Denmark,S,Denmark,0,"Data Visualization, Spark, PyTorch, Hadoop, Python",Bachelor,11,Education,2025-02-13,2025-04-10,2098,8.5,Neural Networks Co -AI06099,AI Software Engineer,109880,USD,109880,SE,CT,Israel,M,Israel,100,"SQL, Hadoop, NLP, Deep Learning",Bachelor,9,Gaming,2024-10-11,2024-11-07,804,9.5,Smart Analytics -AI06100,NLP Engineer,122068,USD,122068,MI,PT,United States,L,United States,100,"Kubernetes, Tableau, SQL",PhD,3,Consulting,2024-04-07,2024-04-26,1213,7.9,Cognitive Computing -AI06101,AI Specialist,62513,USD,62513,SE,FL,China,S,Romania,0,"Python, Scala, R, Hadoop, SQL",Associate,8,Consulting,2025-02-28,2025-04-09,1022,8.5,Neural Networks Co -AI06102,AI Software Engineer,67497,USD,67497,EN,CT,Denmark,M,Denmark,100,"Scala, Spark, R",Master,1,Energy,2024-07-05,2024-09-03,1542,8,Digital Transformation LLC -AI06103,Robotics Engineer,68328,USD,68328,SE,FL,China,M,China,50,"R, Java, Tableau",Associate,9,Telecommunications,2024-02-06,2024-03-13,630,6.4,DeepTech Ventures -AI06104,Research Scientist,73887,CAD,92359,EN,PT,Canada,M,Canada,0,"NLP, SQL, R, PyTorch",Bachelor,0,Healthcare,2024-03-30,2024-06-03,2057,6.9,DataVision Ltd -AI06105,Deep Learning Engineer,85387,EUR,72579,MI,PT,France,M,France,50,"Azure, Python, Spark",Master,4,Technology,2024-02-27,2024-03-27,541,7.3,Digital Transformation LLC -AI06106,Data Engineer,81892,JPY,9008120,MI,FT,Japan,S,Japan,0,"NLP, Kubernetes, Data Visualization",PhD,3,Consulting,2024-06-30,2024-07-28,1150,7.3,DeepTech Ventures -AI06107,Autonomous Systems Engineer,125416,SGD,163041,SE,FL,Singapore,S,South Korea,0,"SQL, Python, Azure, Deep Learning",PhD,9,Energy,2024-10-23,2024-12-05,1037,5.6,Algorithmic Solutions -AI06108,Research Scientist,362104,USD,362104,EX,FL,Norway,L,Norway,0,"TensorFlow, Docker, PyTorch",Bachelor,14,Finance,2024-05-23,2024-07-24,2245,8.5,Algorithmic Solutions -AI06109,Machine Learning Engineer,109467,EUR,93047,SE,FT,France,S,France,0,"TensorFlow, Docker, Python",Bachelor,5,Government,2025-01-07,2025-03-12,1615,8.2,Neural Networks Co -AI06110,AI Software Engineer,74992,USD,74992,MI,FT,Israel,S,Denmark,100,"R, SQL, MLOps, AWS",Bachelor,2,Education,2024-10-09,2024-12-15,1285,7.3,Machine Intelligence Group -AI06111,AI Research Scientist,83813,USD,83813,EX,CT,China,S,China,50,"Python, Mathematics, TensorFlow, Data Visualization, Computer Vision",Bachelor,15,Education,2024-01-23,2024-03-07,1797,6.7,Quantum Computing Inc -AI06112,Data Scientist,98188,CHF,88369,EN,FT,Switzerland,S,Switzerland,100,"Spark, PyTorch, TensorFlow, Hadoop",Master,0,Gaming,2024-05-16,2024-06-11,1249,8.7,Advanced Robotics -AI06113,AI Architect,120407,USD,120407,EX,FT,Finland,S,Italy,0,"Deep Learning, R, MLOps, Computer Vision, Azure",PhD,17,Education,2024-11-17,2024-12-31,763,8.5,Algorithmic Solutions -AI06114,Deep Learning Engineer,187126,EUR,159057,EX,PT,France,M,France,0,"Linux, Docker, Computer Vision",Bachelor,18,Energy,2024-04-24,2024-06-23,2499,8.6,AI Innovations -AI06115,Autonomous Systems Engineer,55832,USD,55832,SE,FT,China,M,China,100,"Spark, Statistics, MLOps",PhD,9,Media,2025-03-27,2025-05-29,1242,5.5,Cognitive Computing -AI06116,Data Scientist,99693,USD,99693,MI,FL,Norway,S,Denmark,100,"TensorFlow, PyTorch, MLOps, GCP",Bachelor,2,Automotive,2024-03-06,2024-04-27,580,6.6,Smart Analytics -AI06117,Principal Data Scientist,111940,AUD,151119,SE,PT,Australia,M,South Korea,100,"Python, R, GCP, TensorFlow, Linux",Bachelor,8,Energy,2024-05-05,2024-06-15,601,9.9,Neural Networks Co -AI06118,AI Consultant,350058,USD,350058,EX,CT,Norway,L,Malaysia,50,"SQL, TensorFlow, Data Visualization, Hadoop",PhD,19,Healthcare,2024-02-19,2024-04-02,2435,8.6,Predictive Systems -AI06119,AI Product Manager,118196,EUR,100467,SE,PT,Germany,S,Germany,0,"Computer Vision, Tableau, SQL, Deep Learning, Linux",Bachelor,7,Technology,2024-07-15,2024-09-25,960,7.6,Advanced Robotics -AI06120,Data Analyst,149669,USD,149669,EX,FT,South Korea,L,South Korea,0,"AWS, GCP, Git, Computer Vision, Hadoop",Associate,18,Government,2025-01-14,2025-02-27,1730,7.8,Future Systems -AI06121,AI Architect,207625,CHF,186863,EX,PT,Switzerland,S,Switzerland,0,"GCP, Statistics, NLP, Computer Vision, Spark",Master,10,Transportation,2025-03-30,2025-05-02,2116,8.4,DeepTech Ventures -AI06122,AI Specialist,179611,CHF,161650,SE,PT,Switzerland,M,Switzerland,100,"Scala, TensorFlow, GCP",Associate,5,Media,2025-03-08,2025-04-07,1131,8.8,TechCorp Inc -AI06123,Deep Learning Engineer,72594,USD,72594,MI,FT,Israel,S,Israel,100,"PyTorch, Computer Vision, Tableau, AWS, SQL",Bachelor,4,Education,2024-04-01,2024-05-30,1372,7.6,TechCorp Inc -AI06124,Data Engineer,74990,USD,74990,MI,FL,Ireland,S,Ireland,100,"Spark, Statistics, Data Visualization, Linux",Associate,4,Transportation,2025-01-06,2025-03-19,1208,8.6,Digital Transformation LLC -AI06125,Principal Data Scientist,128233,USD,128233,SE,PT,United States,S,New Zealand,100,"AWS, MLOps, Mathematics",Bachelor,9,Automotive,2024-12-17,2025-01-26,505,9.1,DataVision Ltd -AI06126,AI Specialist,211020,USD,211020,EX,FT,Denmark,S,Denmark,100,"Git, Python, Deep Learning, Computer Vision",Bachelor,19,Technology,2024-08-17,2024-10-08,717,8.6,Quantum Computing Inc -AI06127,Data Engineer,81260,USD,81260,MI,FL,Sweden,S,Sweden,100,"Hadoop, Azure, Mathematics, TensorFlow, MLOps",Master,4,Gaming,2025-02-15,2025-03-05,733,9.9,DataVision Ltd -AI06128,Data Analyst,119633,EUR,101688,SE,PT,France,M,Thailand,50,"SQL, Kubernetes, Linux",Bachelor,7,Government,2024-01-18,2024-03-20,1998,7.5,Cognitive Computing -AI06129,Machine Learning Engineer,73814,USD,73814,MI,PT,Finland,M,Finland,100,"Python, Spark, TensorFlow, Data Visualization, AWS",PhD,4,Technology,2024-02-19,2024-04-20,1409,8.1,DataVision Ltd -AI06130,AI Specialist,288274,EUR,245033,EX,FT,Germany,L,Indonesia,0,"GCP, SQL, AWS",Associate,13,Automotive,2024-09-29,2024-11-30,1683,9.7,Cloud AI Solutions -AI06131,AI Architect,194644,USD,194644,EX,PT,United States,M,United States,100,"Python, Spark, R, Data Visualization, Scala",Master,19,Energy,2024-04-27,2024-06-20,585,9.8,Neural Networks Co -AI06132,AI Software Engineer,116370,JPY,12800700,MI,FL,Japan,M,Japan,100,"AWS, Scala, GCP",Master,4,Gaming,2025-04-07,2025-05-27,1512,9.3,AI Innovations -AI06133,Robotics Engineer,58648,USD,58648,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Mathematics, Spark",PhD,0,Retail,2024-09-14,2024-10-31,2333,7.3,Smart Analytics -AI06134,Head of AI,94136,EUR,80016,MI,FT,France,L,France,0,"SQL, PyTorch, Docker, Statistics",Associate,2,Technology,2024-08-17,2024-10-02,1740,5.9,Neural Networks Co -AI06135,ML Ops Engineer,60881,JPY,6696910,EN,FT,Japan,S,Japan,50,"SQL, AWS, Tableau, R, NLP",Associate,1,Retail,2024-05-13,2024-07-08,2420,9.3,Advanced Robotics -AI06136,NLP Engineer,134266,USD,134266,SE,CT,United States,S,United States,0,"Tableau, GCP, TensorFlow, Docker",PhD,6,Media,2024-04-22,2024-05-09,2340,9.2,Advanced Robotics -AI06137,Head of AI,61969,USD,61969,SE,PT,China,S,China,50,"Kubernetes, SQL, Deep Learning, Statistics, MLOps",Master,7,Energy,2024-08-05,2024-09-14,903,7,Algorithmic Solutions -AI06138,Machine Learning Engineer,122843,CAD,153554,SE,FT,Canada,S,Canada,0,"R, Java, Data Visualization, Python, AWS",Bachelor,9,Healthcare,2025-01-07,2025-02-14,1013,5.8,Quantum Computing Inc -AI06139,AI Specialist,127779,USD,127779,SE,CT,Finland,L,Finland,50,"Docker, Data Visualization, Python",Bachelor,8,Consulting,2025-03-06,2025-04-27,2111,5.8,Machine Intelligence Group -AI06140,AI Architect,27705,USD,27705,MI,FT,India,M,Spain,50,"Linux, Tableau, NLP, Azure",Master,2,Retail,2024-02-21,2024-04-12,1650,6.3,Digital Transformation LLC -AI06141,AI Architect,31007,USD,31007,MI,PT,India,S,India,50,"Python, Docker, Deep Learning, Java, NLP",Bachelor,3,Finance,2025-04-23,2025-05-30,1414,9.3,Cognitive Computing -AI06142,Head of AI,159103,USD,159103,SE,CT,Denmark,L,China,0,"GCP, Hadoop, SQL",PhD,9,Manufacturing,2024-08-25,2024-09-13,1683,6.3,Quantum Computing Inc -AI06143,AI Specialist,81172,USD,81172,MI,FT,Ireland,M,Ireland,50,"Python, Docker, Deep Learning, Azure, GCP",Associate,3,Consulting,2024-05-24,2024-07-10,710,8,TechCorp Inc -AI06144,Deep Learning Engineer,38128,USD,38128,EN,PT,China,L,Canada,100,"Docker, TensorFlow, Hadoop",Associate,0,Media,2024-04-09,2024-06-19,1299,6,AI Innovations -AI06145,Data Engineer,128255,EUR,109017,SE,FT,Germany,S,India,100,"Statistics, Kubernetes, R, GCP",Associate,6,Gaming,2024-03-16,2024-04-27,1216,7.4,TechCorp Inc -AI06146,ML Ops Engineer,101526,USD,101526,SE,FT,Finland,S,Finland,0,"Hadoop, PyTorch, Java, Statistics",Master,7,Media,2024-09-28,2024-10-20,1406,5.7,Algorithmic Solutions -AI06147,Robotics Engineer,46864,AUD,63266,EN,FL,Australia,S,Australia,100,"Azure, Kubernetes, Python, Deep Learning",PhD,1,Telecommunications,2024-11-04,2024-12-30,540,6.2,Smart Analytics -AI06148,Autonomous Systems Engineer,115707,CHF,104136,MI,CT,Switzerland,M,South Africa,50,"NLP, Python, SQL, TensorFlow",Master,3,Media,2024-04-07,2024-05-14,1458,6.7,DeepTech Ventures -AI06149,Data Engineer,94886,USD,94886,MI,FT,Sweden,L,Norway,100,"Statistics, Git, Spark",Bachelor,2,Automotive,2024-01-16,2024-01-31,1256,6.2,Neural Networks Co -AI06150,AI Research Scientist,66330,USD,66330,EN,FL,Ireland,M,Norway,50,"Python, AWS, Azure",Master,1,Real Estate,2024-01-16,2024-02-23,1111,8,Quantum Computing Inc -AI06151,Machine Learning Researcher,66467,EUR,56497,MI,PT,Austria,S,Austria,50,"Linux, SQL, Computer Vision, PyTorch",Bachelor,2,Education,2024-12-27,2025-02-15,1854,5.5,Neural Networks Co -AI06152,Data Scientist,112672,SGD,146474,MI,FT,Singapore,L,Singapore,100,"NLP, Python, Linux, GCP, Git",Associate,2,Education,2024-10-07,2024-11-28,1006,9.8,Digital Transformation LLC -AI06153,Deep Learning Engineer,92337,EUR,78486,MI,FT,Netherlands,M,Netherlands,50,"Mathematics, GCP, Computer Vision, Python",Bachelor,2,Gaming,2024-04-02,2024-05-15,1553,7.1,Smart Analytics -AI06154,ML Ops Engineer,77521,EUR,65893,EN,FL,Germany,L,Japan,100,"Deep Learning, Mathematics, Data Visualization, SQL, Azure",Associate,0,Telecommunications,2024-01-03,2024-03-15,573,7.7,Digital Transformation LLC -AI06155,AI Research Scientist,323583,CHF,291225,EX,FL,Switzerland,L,Kenya,0,"Azure, Java, AWS, Mathematics",Master,13,Manufacturing,2024-05-20,2024-07-29,1566,8.7,Cloud AI Solutions -AI06156,ML Ops Engineer,123796,GBP,92847,MI,FL,United Kingdom,L,Ukraine,0,"Python, Java, Azure",PhD,4,Media,2024-11-05,2024-12-27,2211,6.3,Advanced Robotics -AI06157,Data Engineer,191974,USD,191974,EX,FT,United States,L,United States,100,"Scala, Python, Git, AWS, Spark",Associate,15,Transportation,2024-06-12,2024-08-14,2068,8.2,Neural Networks Co -AI06158,Machine Learning Engineer,92459,USD,92459,MI,CT,Sweden,L,Sweden,0,"Deep Learning, Data Visualization, Statistics, Computer Vision, Azure",Bachelor,3,Energy,2024-03-03,2024-05-12,1148,5.1,Cognitive Computing -AI06159,Deep Learning Engineer,99147,EUR,84275,MI,FT,Germany,S,Germany,50,"Scala, TensorFlow, Spark",Associate,2,Gaming,2025-03-04,2025-04-08,1132,7.1,Machine Intelligence Group -AI06160,Principal Data Scientist,86412,CHF,77771,EN,CT,Switzerland,L,Turkey,0,"AWS, Azure, Git, Data Visualization, SQL",Master,0,Real Estate,2025-03-13,2025-04-06,2437,5.2,Algorithmic Solutions -AI06161,Machine Learning Engineer,208435,USD,208435,EX,FL,Finland,S,Czech Republic,100,"GCP, Scala, SQL",Master,19,Energy,2025-01-03,2025-02-18,2064,5.1,Algorithmic Solutions -AI06162,Head of AI,126593,CHF,113934,MI,FT,Switzerland,M,Switzerland,0,"Spark, Git, Linux",PhD,3,Education,2024-12-21,2025-01-12,1142,7,Neural Networks Co -AI06163,ML Ops Engineer,141683,USD,141683,SE,FL,Denmark,S,Denmark,100,"MLOps, NLP, Python, SQL, R",Associate,7,Finance,2024-02-21,2024-04-15,961,8.5,AI Innovations -AI06164,Data Engineer,72525,USD,72525,EN,PT,Norway,M,Austria,50,"Scala, Statistics, Git, SQL, Linux",PhD,1,Media,2024-04-11,2024-06-07,2328,5.4,Autonomous Tech -AI06165,Head of AI,210148,EUR,178626,EX,FL,Netherlands,S,Netherlands,50,"Git, Linux, Deep Learning, Data Visualization",Associate,16,Technology,2024-11-30,2025-01-04,1851,7.5,Algorithmic Solutions -AI06166,Data Engineer,100933,USD,100933,EX,CT,India,L,India,50,"Hadoop, MLOps, Docker, Git, Spark",Master,18,Government,2024-04-04,2024-05-21,1702,8,AI Innovations -AI06167,AI Product Manager,133499,USD,133499,SE,FT,Denmark,M,Denmark,100,"Spark, PyTorch, Linux",PhD,6,Manufacturing,2024-11-27,2024-12-29,1819,9.2,Algorithmic Solutions -AI06168,Computer Vision Engineer,143384,USD,143384,EX,PT,South Korea,S,South Korea,0,"MLOps, GCP, Docker, Statistics",PhD,19,Technology,2024-01-15,2024-02-23,1599,9.1,Cognitive Computing -AI06169,Head of AI,83098,USD,83098,EN,FL,Denmark,S,Denmark,50,"Linux, SQL, Spark",Associate,0,Telecommunications,2024-02-21,2024-03-12,1501,6.1,DeepTech Ventures -AI06170,ML Ops Engineer,58485,USD,58485,EN,CT,South Korea,S,South Korea,50,"NLP, Azure, Python",Master,1,Government,2024-09-02,2024-10-17,2191,7.2,Advanced Robotics -AI06171,AI Architect,43970,USD,43970,MI,PT,China,M,Luxembourg,0,"Computer Vision, MLOps, NLP, Statistics, PyTorch",PhD,4,Consulting,2025-01-29,2025-03-02,780,7.5,AI Innovations -AI06172,Head of AI,410273,CHF,369246,EX,FT,Switzerland,L,Switzerland,50,"Python, TensorFlow, Deep Learning",PhD,19,Education,2024-03-01,2024-03-28,1739,7,Machine Intelligence Group -AI06173,Principal Data Scientist,76227,SGD,99095,EN,CT,Singapore,L,Canada,50,"Python, Azure, TensorFlow, Java, Docker",Bachelor,0,Real Estate,2024-07-11,2024-09-12,1081,6.2,Predictive Systems -AI06174,Deep Learning Engineer,121236,CAD,151545,SE,FL,Canada,M,Canada,0,"TensorFlow, Linux, Python, MLOps",Bachelor,7,Energy,2024-02-10,2024-04-19,526,6.8,Cognitive Computing -AI06175,Computer Vision Engineer,82912,AUD,111931,EN,CT,Australia,L,Australia,50,"Python, Kubernetes, Tableau, TensorFlow, Deep Learning",Master,1,Consulting,2025-04-15,2025-05-28,1620,8.3,DeepTech Ventures -AI06176,Autonomous Systems Engineer,227232,AUD,306763,EX,FL,Australia,L,Australia,100,"Python, MLOps, SQL, Spark",Associate,14,Finance,2024-07-22,2024-09-21,1893,6,Cloud AI Solutions -AI06177,AI Specialist,46804,USD,46804,SE,FL,India,S,Italy,0,"Hadoop, Docker, Linux",Master,7,Real Estate,2024-06-02,2024-07-20,2125,6.9,Digital Transformation LLC -AI06178,Machine Learning Engineer,269514,USD,269514,EX,PT,Denmark,L,Denmark,50,"Java, Kubernetes, Data Visualization, Docker, GCP",PhD,16,Automotive,2024-07-21,2024-09-01,1570,9.7,Cloud AI Solutions -AI06179,NLP Engineer,37274,USD,37274,SE,CT,India,S,India,100,"GCP, R, Git, NLP",PhD,7,Technology,2024-01-29,2024-03-06,1576,8,TechCorp Inc -AI06180,Deep Learning Engineer,27007,USD,27007,EN,CT,China,M,China,50,"SQL, PyTorch, Git, Deep Learning, Azure",PhD,1,Finance,2024-12-06,2024-12-25,587,7.2,TechCorp Inc -AI06181,Research Scientist,80678,USD,80678,EX,PT,India,S,India,100,"R, Tableau, SQL",PhD,14,Gaming,2024-02-04,2024-04-11,1900,8.5,AI Innovations -AI06182,Data Engineer,270264,CHF,243238,EX,CT,Switzerland,M,Switzerland,0,"NLP, MLOps, Statistics, Scala",PhD,14,Retail,2024-10-28,2024-12-04,578,9.9,TechCorp Inc -AI06183,AI Product Manager,63878,EUR,54296,MI,FL,France,S,France,50,"Azure, Deep Learning, MLOps, TensorFlow, Kubernetes",PhD,3,Retail,2025-04-21,2025-05-16,2333,6,DataVision Ltd -AI06184,Research Scientist,280852,CHF,252767,EX,CT,Switzerland,L,Switzerland,0,"Git, Scala, Tableau, Linux, Statistics",Master,15,Transportation,2025-02-28,2025-05-04,562,9.8,Digital Transformation LLC -AI06185,Head of AI,103833,USD,103833,MI,FL,Ireland,M,Ireland,0,"PyTorch, Linux, Spark, Tableau, Deep Learning",Associate,3,Manufacturing,2024-05-18,2024-07-06,1743,7.9,Neural Networks Co -AI06186,AI Product Manager,200183,AUD,270247,EX,PT,Australia,S,Australia,50,"AWS, Python, Scala, Spark, Deep Learning",PhD,10,Retail,2024-06-06,2024-07-03,1737,6.9,Algorithmic Solutions -AI06187,Machine Learning Researcher,76963,USD,76963,EX,PT,India,M,India,100,"Kubernetes, Hadoop, Docker, Deep Learning, Statistics",PhD,15,Gaming,2025-04-01,2025-05-23,2228,6.1,TechCorp Inc -AI06188,NLP Engineer,119389,USD,119389,SE,PT,Sweden,M,Sweden,100,"Kubernetes, AWS, Python",Master,7,Healthcare,2024-04-06,2024-06-04,1618,6.8,AI Innovations -AI06189,Machine Learning Researcher,187897,EUR,159712,EX,FL,France,M,France,50,"Hadoop, GCP, Scala, Python, TensorFlow",Associate,18,Manufacturing,2024-04-02,2024-06-07,2109,5.5,TechCorp Inc -AI06190,AI Architect,82319,AUD,111131,MI,FL,Australia,M,Denmark,0,"Spark, Java, PyTorch, Docker, AWS",PhD,4,Manufacturing,2025-04-10,2025-06-01,2081,9.6,Predictive Systems -AI06191,Computer Vision Engineer,145319,USD,145319,SE,FT,Norway,M,Norway,100,"Java, MLOps, Linux, Python, GCP",Bachelor,7,Technology,2024-05-05,2024-05-27,549,7.3,Quantum Computing Inc -AI06192,Deep Learning Engineer,159987,EUR,135989,EX,FT,Germany,M,Germany,100,"Spark, Kubernetes, Deep Learning",PhD,15,Media,2024-11-22,2025-01-06,1827,8.1,DataVision Ltd -AI06193,AI Specialist,68999,USD,68999,EN,FT,United States,S,Russia,50,"Scala, Git, Data Visualization",Bachelor,0,Energy,2024-12-01,2025-02-10,2474,7.9,Predictive Systems -AI06194,Data Engineer,96411,JPY,10605210,MI,FT,Japan,M,Japan,100,"Statistics, Java, Git",Master,2,Education,2024-03-13,2024-05-24,1125,7.2,Advanced Robotics -AI06195,Robotics Engineer,262229,USD,262229,EX,PT,Sweden,L,Sweden,50,"Git, Kubernetes, Scala",PhD,17,Healthcare,2024-09-25,2024-12-05,1786,6,Advanced Robotics -AI06196,Data Analyst,77309,USD,77309,MI,CT,Israel,M,Israel,100,"SQL, Java, Python, Data Visualization",Associate,2,Automotive,2024-11-10,2025-01-19,823,6.1,Cloud AI Solutions -AI06197,Robotics Engineer,327821,USD,327821,EX,PT,Denmark,L,Denmark,0,"Azure, Python, MLOps, Scala",PhD,13,Gaming,2024-01-08,2024-02-17,2292,6.7,Future Systems -AI06198,NLP Engineer,97172,GBP,72879,EN,PT,United Kingdom,L,United Kingdom,100,"Statistics, Linux, Mathematics, Tableau, Kubernetes",PhD,0,Retail,2024-02-14,2024-04-02,819,7.2,DeepTech Ventures -AI06199,Autonomous Systems Engineer,58968,EUR,50123,EN,PT,Germany,L,Germany,50,"PyTorch, Java, TensorFlow, R, GCP",Associate,0,Telecommunications,2024-07-09,2024-08-09,2302,6.4,DataVision Ltd -AI06200,Machine Learning Researcher,209608,AUD,282971,EX,FL,Australia,M,Australia,0,"NLP, Python, Hadoop, Kubernetes",Master,18,Automotive,2025-03-04,2025-04-28,1596,5.5,Digital Transformation LLC -AI06201,Head of AI,47165,EUR,40090,EN,PT,Austria,S,Austria,0,"Python, TensorFlow, SQL",Bachelor,0,Finance,2025-02-12,2025-03-30,1483,6.5,Smart Analytics -AI06202,Data Engineer,95552,USD,95552,EN,FT,United States,L,United States,0,"Python, Computer Vision, Scala, TensorFlow, Git",Master,1,Media,2024-09-30,2024-11-30,1965,5.8,Cloud AI Solutions -AI06203,NLP Engineer,140834,EUR,119709,SE,PT,France,M,France,0,"NLP, TensorFlow, Java, Data Visualization, Mathematics",PhD,5,Finance,2024-01-21,2024-03-01,727,9.9,TechCorp Inc -AI06204,NLP Engineer,50964,USD,50964,EN,CT,Finland,M,Israel,100,"Docker, Azure, NLP, Linux",Associate,0,Consulting,2024-03-14,2024-03-31,1190,7.1,Cognitive Computing -AI06205,Machine Learning Researcher,141955,USD,141955,EX,FT,Israel,M,Israel,0,"TensorFlow, Spark, Hadoop, Python",PhD,12,Government,2024-11-10,2025-01-11,1814,6.9,DataVision Ltd -AI06206,Research Scientist,79587,USD,79587,MI,FT,Israel,M,Israel,50,"PyTorch, SQL, NLP",Associate,4,Transportation,2024-03-31,2024-06-03,1811,8.9,DataVision Ltd -AI06207,Data Engineer,114995,USD,114995,EX,PT,China,L,China,100,"Kubernetes, Data Visualization, SQL, Python",Bachelor,17,Consulting,2025-02-15,2025-04-23,566,6.2,DataVision Ltd -AI06208,ML Ops Engineer,65857,USD,65857,EN,PT,Israel,S,Malaysia,0,"Deep Learning, TensorFlow, Computer Vision",PhD,0,Media,2025-04-20,2025-06-08,1998,9.3,Predictive Systems -AI06209,AI Consultant,58926,USD,58926,EN,FT,Ireland,M,Portugal,100,"Scala, NLP, GCP, Hadoop",Associate,1,Manufacturing,2025-04-14,2025-05-12,597,9.8,Autonomous Tech -AI06210,AI Software Engineer,275093,USD,275093,EX,FL,Denmark,S,Denmark,100,"Git, Hadoop, Mathematics",Master,16,Government,2024-04-02,2024-06-11,2078,8.7,Neural Networks Co -AI06211,Machine Learning Engineer,220073,EUR,187062,EX,FL,Netherlands,L,Netherlands,50,"Python, Java, SQL, PyTorch",Bachelor,18,Energy,2024-11-23,2025-01-02,1489,5.1,Cloud AI Solutions -AI06212,Robotics Engineer,58905,GBP,44179,EN,FT,United Kingdom,S,New Zealand,50,"Python, Linux, Azure, AWS, Java",Associate,1,Finance,2024-06-06,2024-07-31,1625,7.1,Predictive Systems -AI06213,Principal Data Scientist,264666,USD,264666,EX,CT,Norway,M,Norway,100,"Git, NLP, SQL, PyTorch",PhD,11,Healthcare,2025-01-14,2025-02-27,1025,6.9,DeepTech Ventures -AI06214,Data Analyst,149181,EUR,126804,EX,PT,Austria,M,Austria,50,"SQL, Spark, Data Visualization, TensorFlow, GCP",Master,17,Healthcare,2024-07-24,2024-08-29,985,9.9,Future Systems -AI06215,ML Ops Engineer,92326,USD,92326,EN,FL,Sweden,L,Sweden,0,"Scala, Java, NLP",Associate,1,Gaming,2024-01-27,2024-04-04,2411,5.3,Autonomous Tech -AI06216,Autonomous Systems Engineer,103737,USD,103737,MI,FT,United States,S,United States,0,"Kubernetes, Docker, Deep Learning",Bachelor,4,Automotive,2024-10-21,2024-11-11,1472,8.1,TechCorp Inc -AI06217,AI Consultant,105787,EUR,89919,SE,PT,France,M,France,100,"Computer Vision, GCP, Deep Learning, PyTorch",Bachelor,9,Healthcare,2024-10-27,2025-01-03,1053,5.4,Digital Transformation LLC -AI06218,Data Engineer,121968,USD,121968,MI,FL,Denmark,M,Denmark,50,"SQL, TensorFlow, Linux",Associate,4,Retail,2025-03-22,2025-06-03,2484,7.9,Cloud AI Solutions -AI06219,Computer Vision Engineer,308831,CHF,277948,EX,FL,Switzerland,S,Switzerland,50,"GCP, Deep Learning, Python, Kubernetes, TensorFlow",PhD,17,Government,2025-01-03,2025-02-25,1901,8.6,Neural Networks Co -AI06220,AI Product Manager,52330,USD,52330,EN,PT,Sweden,M,Sweden,0,"GCP, Tableau, NLP",Associate,1,Gaming,2024-06-29,2024-08-27,623,9.9,Cloud AI Solutions -AI06221,NLP Engineer,105139,EUR,89368,MI,PT,Germany,M,Germany,0,"AWS, Java, Mathematics",Bachelor,2,Automotive,2024-01-09,2024-03-14,806,5.2,Predictive Systems -AI06222,AI Consultant,57833,USD,57833,MI,FT,China,L,Nigeria,100,"Java, Statistics, Tableau",PhD,3,Healthcare,2024-02-26,2024-03-23,1963,6.2,Quantum Computing Inc -AI06223,ML Ops Engineer,136814,CHF,123133,MI,FT,Switzerland,M,Switzerland,50,"GCP, Linux, Statistics, Mathematics",PhD,3,Manufacturing,2024-04-02,2024-05-02,1076,9.1,AI Innovations -AI06224,AI Architect,158438,USD,158438,EX,FL,South Korea,M,Malaysia,100,"Hadoop, MLOps, Java, Python, TensorFlow",Master,15,Retail,2025-03-16,2025-05-18,2329,5.3,AI Innovations -AI06225,NLP Engineer,45309,USD,45309,EN,PT,South Korea,M,South Korea,50,"PyTorch, Git, Kubernetes, Statistics, Deep Learning",Master,0,Finance,2024-03-18,2024-04-08,1552,6.5,Cloud AI Solutions -AI06226,AI Software Engineer,45432,USD,45432,EN,CT,Israel,S,Israel,100,"TensorFlow, Spark, Linux, Deep Learning, Java",Master,1,Manufacturing,2024-06-27,2024-08-22,555,6.4,DeepTech Ventures -AI06227,AI Product Manager,109543,CHF,98589,EN,FL,Switzerland,L,Estonia,100,"Docker, Git, Kubernetes, TensorFlow",PhD,0,Healthcare,2024-05-29,2024-07-02,1108,7.6,Cognitive Computing -AI06228,Head of AI,174342,USD,174342,EX,FT,Israel,M,Mexico,100,"Statistics, SQL, Data Visualization",Bachelor,13,Manufacturing,2024-05-14,2024-07-16,1145,6.4,Autonomous Tech -AI06229,Head of AI,52826,EUR,44902,EN,PT,Germany,M,Italy,0,"Linux, Computer Vision, SQL, Spark, PyTorch",Associate,1,Finance,2024-04-12,2024-05-09,1680,8.7,Predictive Systems -AI06230,AI Research Scientist,43403,USD,43403,MI,FT,China,S,China,0,"Git, NLP, Docker, TensorFlow, AWS",Bachelor,3,Technology,2024-01-20,2024-03-04,2127,5.5,Cognitive Computing -AI06231,AI Specialist,58657,AUD,79187,EN,FT,Australia,L,Australia,50,"Kubernetes, Scala, Linux, Spark",Associate,1,Finance,2024-03-10,2024-05-05,2476,6.8,Quantum Computing Inc -AI06232,ML Ops Engineer,334601,CHF,301141,EX,CT,Switzerland,L,Indonesia,0,"PyTorch, Azure, MLOps",Master,14,Gaming,2024-08-01,2024-09-21,1260,7.9,Predictive Systems -AI06233,Computer Vision Engineer,91169,AUD,123078,MI,FL,Australia,M,Australia,50,"SQL, PyTorch, R, Java",Master,2,Gaming,2024-06-07,2024-06-24,1508,6.8,DeepTech Ventures -AI06234,Machine Learning Engineer,89246,EUR,75859,MI,CT,France,S,France,0,"Spark, Hadoop, Git, SQL",Associate,3,Energy,2024-07-11,2024-09-11,817,7.5,Algorithmic Solutions -AI06235,AI Consultant,70820,AUD,95607,EN,CT,Australia,L,Australia,100,"Tableau, Linux, R, Azure, Scala",Master,1,Transportation,2024-08-24,2024-10-30,2272,9.1,Cognitive Computing -AI06236,Data Engineer,127145,SGD,165289,SE,CT,Singapore,L,Singapore,50,"NLP, Python, SQL, Docker, GCP",PhD,7,Retail,2025-04-29,2025-06-14,1599,6.3,Future Systems -AI06237,Computer Vision Engineer,74447,GBP,55835,EN,CT,United Kingdom,S,United Kingdom,100,"Linux, Data Visualization, TensorFlow",Bachelor,1,Technology,2024-01-21,2024-02-12,1024,9.2,DataVision Ltd -AI06238,AI Product Manager,85168,GBP,63876,MI,FT,United Kingdom,M,Austria,100,"Python, MLOps, Java, Computer Vision, Git",PhD,3,Energy,2024-08-04,2024-09-28,2129,6.1,Digital Transformation LLC -AI06239,AI Consultant,333929,CHF,300536,EX,CT,Switzerland,L,Switzerland,100,"SQL, PyTorch, MLOps, Computer Vision, AWS",PhD,14,Transportation,2024-03-31,2024-06-03,1031,9.5,Smart Analytics -AI06240,Deep Learning Engineer,119472,EUR,101551,SE,FT,Austria,M,Denmark,100,"Python, Spark, TensorFlow",Master,7,Retail,2024-03-17,2024-05-16,914,8.2,Neural Networks Co -AI06241,Machine Learning Engineer,185566,USD,185566,EX,CT,United States,M,Ireland,100,"Kubernetes, Statistics, R, Docker, Computer Vision",Associate,13,Real Estate,2024-01-09,2024-03-18,669,5.1,AI Innovations -AI06242,Deep Learning Engineer,98638,AUD,133161,SE,CT,Australia,S,Philippines,50,"Mathematics, Python, GCP, Azure",Associate,7,Healthcare,2024-10-07,2024-11-12,1188,5.6,Neural Networks Co -AI06243,Machine Learning Engineer,96950,EUR,82408,MI,PT,Netherlands,L,Netherlands,50,"Python, MLOps, Data Visualization",Master,2,Automotive,2024-06-22,2024-07-29,2329,7.2,Machine Intelligence Group -AI06244,AI Product Manager,55210,GBP,41408,EN,FT,United Kingdom,M,United Kingdom,50,"SQL, PyTorch, Mathematics, Java",Associate,0,Healthcare,2024-04-23,2024-07-01,2059,6.1,Autonomous Tech -AI06245,Robotics Engineer,231279,USD,231279,EX,FL,South Korea,L,South Korea,0,"Git, TensorFlow, Python",Bachelor,19,Consulting,2024-10-07,2024-12-06,2187,8.7,Digital Transformation LLC -AI06246,ML Ops Engineer,125808,USD,125808,MI,FT,Denmark,L,Denmark,100,"NLP, Scala, Python",PhD,4,Education,2024-03-25,2024-05-16,532,6.3,Advanced Robotics -AI06247,Head of AI,201000,SGD,261300,EX,CT,Singapore,M,Singapore,100,"NLP, Java, Docker, Deep Learning",Bachelor,10,Education,2024-06-12,2024-08-13,598,5.9,Predictive Systems -AI06248,Machine Learning Researcher,235015,SGD,305520,EX,CT,Singapore,S,Singapore,0,"MLOps, Java, R, Kubernetes, Data Visualization",PhD,10,Finance,2024-10-18,2024-12-06,1281,8.8,Machine Intelligence Group -AI06249,Research Scientist,104461,AUD,141022,SE,PT,Australia,S,Australia,100,"PyTorch, SQL, AWS, Python, Deep Learning",Bachelor,7,Real Estate,2024-10-25,2024-12-24,949,6.9,TechCorp Inc -AI06250,AI Consultant,120951,USD,120951,MI,FT,Sweden,L,Sweden,100,"Deep Learning, Docker, R, Linux, MLOps",Associate,4,Education,2024-05-03,2024-06-20,1048,5.2,DeepTech Ventures -AI06251,Deep Learning Engineer,94126,USD,94126,MI,CT,Ireland,S,Ireland,100,"Statistics, Spark, Java, Deep Learning",Bachelor,4,Automotive,2024-09-30,2024-11-19,1008,5.6,Digital Transformation LLC -AI06252,Machine Learning Researcher,188011,USD,188011,EX,FL,Finland,S,Finland,100,"Git, Mathematics, Scala, PyTorch",Bachelor,16,Retail,2025-01-12,2025-03-08,2175,6.1,Digital Transformation LLC -AI06253,NLP Engineer,143061,USD,143061,SE,PT,Norway,M,China,0,"Statistics, Python, Tableau, Linux",PhD,9,Technology,2024-12-22,2025-02-05,1284,7.8,AI Innovations -AI06254,NLP Engineer,206350,EUR,175398,EX,CT,France,S,France,0,"Kubernetes, GCP, Hadoop, Statistics",Master,16,Gaming,2025-04-13,2025-05-21,919,6.7,Smart Analytics -AI06255,Data Analyst,60881,AUD,82189,EN,CT,Australia,S,Australia,0,"Scala, Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-03-26,2024-05-02,672,10,Smart Analytics -AI06256,Data Analyst,103178,EUR,87701,MI,FT,Austria,L,Austria,0,"Azure, Hadoop, AWS, Statistics",Bachelor,3,Finance,2025-04-08,2025-05-28,687,6.4,DataVision Ltd -AI06257,AI Software Engineer,81446,SGD,105880,MI,FL,Singapore,S,Singapore,100,"Docker, Hadoop, Data Visualization, Java, R",Bachelor,2,Healthcare,2025-01-28,2025-03-28,801,5.3,TechCorp Inc -AI06258,ML Ops Engineer,304317,GBP,228238,EX,FT,United Kingdom,L,Denmark,100,"GCP, Linux, Git",PhD,13,Transportation,2024-06-11,2024-07-10,1876,9.3,Cognitive Computing -AI06259,NLP Engineer,37648,USD,37648,SE,FL,India,S,India,50,"Spark, Scala, Git, Python, Azure",Bachelor,5,Technology,2024-09-29,2024-12-02,1398,5.8,Quantum Computing Inc -AI06260,AI Architect,88718,GBP,66539,EN,CT,United Kingdom,L,United Kingdom,50,"Linux, Scala, Computer Vision",Associate,1,Consulting,2024-02-03,2024-02-17,946,9.1,Smart Analytics -AI06261,AI Consultant,36001,USD,36001,MI,FL,China,M,Ukraine,100,"Git, Mathematics, Spark",PhD,4,Finance,2024-01-26,2024-03-22,986,5.3,Advanced Robotics -AI06262,ML Ops Engineer,78519,CAD,98149,MI,CT,Canada,L,Canada,0,"Linux, Deep Learning, Python, TensorFlow",Associate,2,Transportation,2024-09-30,2024-10-20,870,7.7,AI Innovations -AI06263,AI Product Manager,109953,CHF,98958,MI,FT,Switzerland,M,Switzerland,0,"Java, Docker, Kubernetes, Scala",Master,4,Consulting,2025-01-22,2025-03-11,852,6.5,Algorithmic Solutions -AI06264,Head of AI,105406,AUD,142298,SE,CT,Australia,S,Australia,100,"Docker, MLOps, NLP, Java, R",Master,7,Telecommunications,2024-01-19,2024-03-27,2213,7.6,Quantum Computing Inc -AI06265,AI Specialist,70408,USD,70408,EN,FT,Israel,L,South Korea,0,"Mathematics, AWS, Data Visualization, Docker",Bachelor,0,Gaming,2024-06-27,2024-07-12,562,8.7,AI Innovations -AI06266,AI Architect,220323,USD,220323,EX,PT,Sweden,S,Sweden,0,"PyTorch, Linux, Tableau, Computer Vision",Associate,13,Transportation,2025-04-26,2025-06-01,1088,8.3,Neural Networks Co -AI06267,AI Architect,163354,EUR,138851,EX,PT,France,M,France,0,"Azure, AWS, GCP",Associate,10,Telecommunications,2024-12-15,2024-12-29,814,8.2,AI Innovations -AI06268,Autonomous Systems Engineer,89007,SGD,115709,MI,CT,Singapore,L,Singapore,100,"SQL, Spark, Scala, Azure",Master,4,Finance,2024-01-04,2024-01-28,837,8.8,Quantum Computing Inc -AI06269,Computer Vision Engineer,89914,AUD,121384,EN,FT,Australia,L,Australia,50,"AWS, Scala, GCP",Associate,1,Technology,2024-12-16,2025-02-17,1937,5.5,Machine Intelligence Group -AI06270,NLP Engineer,117917,USD,117917,SE,FL,Israel,M,Israel,0,"Python, NLP, Git",Master,8,Consulting,2024-07-22,2024-09-06,701,9.3,Cognitive Computing -AI06271,AI Specialist,86279,AUD,116477,MI,FT,Australia,S,Australia,0,"AWS, Docker, Git, Data Visualization",Bachelor,3,Gaming,2025-01-25,2025-03-07,828,6.5,AI Innovations -AI06272,Computer Vision Engineer,232296,USD,232296,EX,CT,Denmark,S,Denmark,0,"Statistics, Kubernetes, Linux, NLP",Associate,15,Manufacturing,2024-05-31,2024-07-09,2320,5.7,AI Innovations -AI06273,Principal Data Scientist,84539,USD,84539,MI,PT,Israel,S,Israel,0,"R, Scala, Data Visualization, Java, Statistics",Associate,3,Consulting,2024-05-14,2024-07-11,1864,5.8,TechCorp Inc -AI06274,Autonomous Systems Engineer,191852,CHF,172667,SE,FT,Switzerland,S,Switzerland,50,"Spark, PyTorch, Mathematics, Data Visualization, MLOps",Associate,7,Government,2024-10-11,2024-11-16,1459,9.6,Cognitive Computing -AI06275,Head of AI,271790,USD,271790,EX,CT,Denmark,S,Denmark,50,"NLP, Scala, Git",Master,16,Finance,2024-12-15,2025-02-25,609,6.1,Cloud AI Solutions -AI06276,Head of AI,69511,USD,69511,EN,CT,Ireland,M,Ireland,50,"Python, Docker, Computer Vision, Statistics, GCP",PhD,1,Finance,2024-03-02,2024-03-24,2017,6.3,AI Innovations -AI06277,AI Research Scientist,92982,USD,92982,EN,PT,Denmark,M,Denmark,0,"Linux, PyTorch, Hadoop",PhD,1,Manufacturing,2025-03-18,2025-04-02,2141,7.1,Digital Transformation LLC -AI06278,Machine Learning Researcher,123526,EUR,104997,EX,FL,Germany,S,Germany,0,"Docker, Linux, Data Visualization, Statistics",PhD,10,Automotive,2024-03-03,2024-05-01,856,5.5,Smart Analytics -AI06279,AI Consultant,184103,SGD,239334,SE,PT,Singapore,L,Singapore,100,"Kubernetes, Spark, Tableau, Hadoop, Docker",Master,5,Gaming,2024-08-14,2024-09-25,2427,7.2,Cloud AI Solutions -AI06280,AI Research Scientist,58966,USD,58966,MI,FL,China,L,Estonia,50,"Spark, AWS, Azure, Mathematics",Associate,2,Technology,2024-02-12,2024-04-14,2263,8.1,Cognitive Computing -AI06281,Robotics Engineer,118203,USD,118203,SE,PT,Ireland,M,Ireland,50,"Docker, Kubernetes, Data Visualization, GCP, Deep Learning",PhD,6,Finance,2024-02-16,2024-03-31,1541,9.4,TechCorp Inc -AI06282,Machine Learning Researcher,307747,USD,307747,EX,PT,Norway,L,Norway,0,"PyTorch, Spark, Data Visualization, AWS",PhD,11,Transportation,2024-12-23,2025-02-04,1840,7.3,Advanced Robotics -AI06283,Computer Vision Engineer,180858,JPY,19894380,EX,PT,Japan,L,Japan,100,"TensorFlow, Java, NLP, Docker, Computer Vision",Associate,14,Healthcare,2024-08-31,2024-09-26,1599,6,Machine Intelligence Group -AI06284,NLP Engineer,93668,SGD,121768,EN,FL,Singapore,L,Singapore,0,"Docker, PyTorch, Statistics",PhD,0,Media,2025-03-21,2025-04-22,1615,5.8,AI Innovations -AI06285,Computer Vision Engineer,74686,USD,74686,MI,FL,Ireland,S,Ireland,50,"Python, PyTorch, GCP, Deep Learning",Master,4,Government,2024-01-20,2024-03-19,2252,8.7,Digital Transformation LLC -AI06286,ML Ops Engineer,116392,USD,116392,SE,FL,South Korea,M,South Korea,50,"Hadoop, Scala, Python, R, Statistics",PhD,6,Media,2025-01-25,2025-03-28,1578,7.9,DataVision Ltd -AI06287,AI Architect,76585,GBP,57439,EN,CT,United Kingdom,M,Russia,100,"Tableau, Deep Learning, Git, SQL",Bachelor,1,Retail,2025-03-05,2025-04-16,911,9.1,Neural Networks Co -AI06288,Computer Vision Engineer,178074,CAD,222593,EX,FL,Canada,S,Canada,0,"Linux, SQL, Hadoop, PyTorch, Kubernetes",Master,19,Gaming,2025-01-29,2025-02-12,1184,6.6,Smart Analytics -AI06289,AI Consultant,28737,USD,28737,EN,PT,China,M,China,100,"GCP, R, Data Visualization",PhD,1,Media,2025-04-03,2025-06-14,1804,5.1,AI Innovations -AI06290,AI Research Scientist,175508,USD,175508,EX,CT,Ireland,S,Norway,100,"Kubernetes, AWS, Deep Learning, MLOps, SQL",PhD,19,Finance,2025-03-02,2025-04-29,2085,6,DataVision Ltd -AI06291,AI Product Manager,52615,USD,52615,EN,FL,South Korea,M,South Korea,50,"Data Visualization, MLOps, SQL",Associate,1,Finance,2024-07-10,2024-08-02,1516,7.9,DataVision Ltd -AI06292,ML Ops Engineer,177787,USD,177787,SE,PT,Norway,M,Norway,100,"Python, MLOps, Scala, R",Master,7,Finance,2025-01-07,2025-03-17,1543,7.3,Smart Analytics -AI06293,Robotics Engineer,67831,EUR,57656,EN,FL,France,S,France,100,"Python, Git, Hadoop, Spark",Master,0,Real Estate,2024-01-05,2024-02-03,673,5.5,Autonomous Tech -AI06294,Data Engineer,79450,USD,79450,EN,PT,Sweden,L,Finland,100,"Mathematics, Java, Python",Master,1,Retail,2024-03-19,2024-05-21,873,8.6,Digital Transformation LLC -AI06295,AI Research Scientist,61213,USD,61213,EN,PT,South Korea,L,South Korea,50,"Spark, Scala, Tableau, Linux, Statistics",Bachelor,0,Consulting,2024-11-16,2025-01-14,842,8.2,Neural Networks Co -AI06296,ML Ops Engineer,142856,USD,142856,SE,FL,United States,M,United States,50,"Git, SQL, Data Visualization, Linux, AWS",Associate,6,Government,2024-09-16,2024-11-24,1332,6.9,Predictive Systems -AI06297,AI Architect,49252,CAD,61565,EN,FT,Canada,S,Canada,50,"Java, R, GCP, SQL, Docker",Master,0,Finance,2024-12-20,2025-01-24,2021,8.7,Neural Networks Co -AI06298,ML Ops Engineer,102093,USD,102093,EX,PT,China,S,Netherlands,0,"Kubernetes, Python, R, Java",Associate,13,Consulting,2024-02-24,2024-04-07,902,7.4,AI Innovations -AI06299,Data Scientist,152000,USD,152000,SE,PT,United States,S,United States,100,"Azure, Mathematics, Python, TensorFlow",PhD,8,Retail,2025-01-10,2025-02-20,839,7.6,AI Innovations -AI06300,AI Research Scientist,145423,AUD,196321,SE,FT,Australia,L,Australia,100,"Mathematics, Git, Python, TensorFlow",PhD,7,Manufacturing,2024-06-24,2024-08-22,1828,8.8,DeepTech Ventures -AI06301,AI Architect,65475,USD,65475,SE,FT,China,M,China,0,"Linux, Computer Vision, R, Statistics",PhD,7,Technology,2024-12-30,2025-03-04,2327,9.9,Neural Networks Co -AI06302,ML Ops Engineer,240444,GBP,180333,EX,CT,United Kingdom,M,United Kingdom,0,"Git, SQL, R, NLP",PhD,19,Education,2024-09-12,2024-11-02,2186,6,AI Innovations -AI06303,Autonomous Systems Engineer,82512,EUR,70135,EN,FT,Germany,L,Germany,50,"Azure, AWS, MLOps",Master,1,Consulting,2025-03-08,2025-04-01,609,9.9,DeepTech Ventures -AI06304,AI Software Engineer,130547,JPY,14360170,MI,CT,Japan,L,Japan,100,"PyTorch, GCP, Kubernetes, AWS",PhD,2,Media,2025-02-03,2025-03-02,1276,6.2,TechCorp Inc -AI06305,Data Engineer,88285,EUR,75042,EN,FL,Germany,L,Germany,50,"Azure, R, Deep Learning, Linux",PhD,0,Education,2024-12-07,2025-02-14,2151,5,Cloud AI Solutions -AI06306,AI Software Engineer,127722,USD,127722,EX,PT,South Korea,S,South Korea,50,"SQL, Kubernetes, MLOps, Computer Vision, NLP",Associate,16,Transportation,2024-07-02,2024-08-04,2126,5.6,Quantum Computing Inc -AI06307,AI Consultant,267077,USD,267077,EX,PT,Norway,M,Norway,50,"Python, Kubernetes, Azure",Bachelor,18,Telecommunications,2025-04-01,2025-05-14,766,8.4,DeepTech Ventures -AI06308,ML Ops Engineer,178106,EUR,151390,EX,CT,Germany,L,Germany,0,"Spark, Git, Tableau, Python",Associate,19,Energy,2025-03-29,2025-04-23,814,5.2,Autonomous Tech -AI06309,Principal Data Scientist,160177,USD,160177,SE,CT,Denmark,L,Israel,100,"AWS, Git, Python, Tableau, GCP",Master,7,Manufacturing,2024-08-28,2024-09-28,1921,6,Future Systems -AI06310,Data Engineer,123876,USD,123876,SE,FT,Israel,S,Israel,0,"SQL, Linux, MLOps, TensorFlow",PhD,9,Transportation,2024-03-30,2024-05-28,1307,8.5,Advanced Robotics -AI06311,Machine Learning Researcher,51598,USD,51598,EN,PT,Finland,M,Finland,0,"Data Visualization, Git, Python, Kubernetes",Associate,0,Telecommunications,2024-05-14,2024-07-13,2313,9.1,Cloud AI Solutions -AI06312,Deep Learning Engineer,127577,USD,127577,SE,FL,Israel,S,Israel,50,"Tableau, AWS, Azure, Python",Associate,6,Technology,2024-08-29,2024-09-20,2494,9.5,Digital Transformation LLC -AI06313,Machine Learning Researcher,64037,GBP,48028,EN,CT,United Kingdom,M,United Kingdom,100,"Spark, Python, Data Visualization",Associate,1,Gaming,2024-03-21,2024-05-16,1649,5.9,DeepTech Ventures -AI06314,AI Consultant,27121,USD,27121,EN,CT,India,L,India,50,"Tableau, Kubernetes, Azure, Scala",Bachelor,1,Retail,2024-09-21,2024-10-17,2379,7.9,AI Innovations -AI06315,AI Software Engineer,177989,USD,177989,SE,CT,United States,L,United States,100,"Python, Scala, TensorFlow, Linux, GCP",Master,6,Healthcare,2024-10-12,2024-11-07,522,7.8,Smart Analytics -AI06316,AI Software Engineer,84799,USD,84799,EN,FL,United States,S,United States,100,"NLP, R, Scala, Linux",Bachelor,0,Technology,2024-12-12,2025-02-14,809,6.8,Cognitive Computing -AI06317,ML Ops Engineer,130027,USD,130027,SE,PT,Israel,L,Israel,50,"R, TensorFlow, Tableau, Computer Vision",PhD,8,Real Estate,2024-04-18,2024-05-02,627,6.5,Future Systems -AI06318,Data Engineer,116389,CAD,145486,SE,PT,Canada,S,Canada,0,"Deep Learning, Java, Scala",Master,5,Automotive,2024-01-25,2024-03-27,583,9.2,Machine Intelligence Group -AI06319,AI Product Manager,16795,USD,16795,EN,FL,India,S,India,100,"R, Hadoop, SQL",Bachelor,0,Real Estate,2025-04-27,2025-06-12,1009,5.1,Algorithmic Solutions -AI06320,Research Scientist,79356,JPY,8729160,MI,FL,Japan,S,Japan,50,"Statistics, Git, MLOps",Associate,4,Real Estate,2024-05-07,2024-06-02,1580,7.1,Algorithmic Solutions -AI06321,AI Research Scientist,71342,SGD,92745,EN,PT,Singapore,L,Belgium,50,"Git, Kubernetes, GCP, Mathematics, Azure",Bachelor,0,Automotive,2024-05-19,2024-07-15,1611,9.4,Digital Transformation LLC -AI06322,Data Engineer,66947,GBP,50210,EN,FT,United Kingdom,M,United Kingdom,0,"R, Mathematics, Kubernetes, Deep Learning, NLP",Bachelor,0,Consulting,2024-02-24,2024-04-03,1935,8.7,Autonomous Tech -AI06323,Machine Learning Engineer,66042,USD,66042,EN,FT,Israel,S,Israel,0,"SQL, GCP, Linux, Tableau",Bachelor,1,Healthcare,2025-04-06,2025-05-09,521,9.6,DataVision Ltd -AI06324,AI Software Engineer,232173,CHF,208956,EX,FT,Switzerland,S,Switzerland,0,"Git, PyTorch, Mathematics, Hadoop, Azure",Bachelor,18,Technology,2024-03-31,2024-05-08,2066,8.1,TechCorp Inc -AI06325,Data Scientist,108812,GBP,81609,SE,FT,United Kingdom,S,Turkey,100,"SQL, R, Data Visualization, Azure",Associate,5,Technology,2025-01-05,2025-01-26,654,6.5,Digital Transformation LLC -AI06326,Research Scientist,96625,USD,96625,MI,PT,Ireland,S,Norway,0,"R, Computer Vision, Data Visualization",Master,2,Consulting,2024-06-30,2024-07-28,777,7.6,Quantum Computing Inc -AI06327,Data Scientist,256663,SGD,333662,EX,FL,Singapore,M,Singapore,0,"Python, Linux, TensorFlow, Mathematics",Master,14,Automotive,2024-07-19,2024-09-03,1871,9.5,Autonomous Tech -AI06328,Machine Learning Researcher,92568,USD,92568,MI,CT,Ireland,S,Ireland,0,"Azure, Python, MLOps, Kubernetes",Master,3,Manufacturing,2024-03-30,2024-05-28,2342,9.9,Advanced Robotics -AI06329,Computer Vision Engineer,85546,EUR,72714,MI,CT,France,M,Netherlands,50,"Spark, Python, SQL",Associate,3,Real Estate,2025-04-10,2025-05-17,1014,9.9,Future Systems -AI06330,Data Engineer,185667,USD,185667,EX,PT,Ireland,L,Ireland,0,"SQL, Deep Learning, Hadoop, TensorFlow, Mathematics",Master,15,Transportation,2025-03-07,2025-03-21,1512,9.8,Future Systems -AI06331,AI Research Scientist,94718,USD,94718,SE,CT,Israel,S,Israel,0,"PyTorch, NLP, GCP",Associate,9,Government,2024-03-05,2024-03-22,860,6.4,Algorithmic Solutions -AI06332,Research Scientist,153864,AUD,207716,SE,CT,Australia,L,Australia,100,"Linux, PyTorch, Spark, NLP",Bachelor,5,Energy,2024-03-17,2024-04-29,986,5.1,TechCorp Inc -AI06333,Computer Vision Engineer,49125,SGD,63863,EN,FL,Singapore,S,Singapore,100,"MLOps, Python, TensorFlow",Master,1,Energy,2025-02-20,2025-04-04,1236,8,TechCorp Inc -AI06334,AI Software Engineer,79549,SGD,103414,EN,PT,Singapore,M,Singapore,100,"Python, R, Kubernetes, Computer Vision",Master,1,Transportation,2024-08-03,2024-08-19,1979,8,Cognitive Computing -AI06335,AI Research Scientist,95354,USD,95354,MI,FL,Sweden,S,Sweden,0,"Scala, Kubernetes, Spark, Hadoop",Associate,3,Manufacturing,2024-06-18,2024-07-13,2489,9.8,DeepTech Ventures -AI06336,AI Architect,91154,CHF,82039,EN,FL,Switzerland,L,Switzerland,100,"AWS, Azure, Python, Java",Master,1,Finance,2024-05-19,2024-06-17,1997,7.1,Autonomous Tech -AI06337,AI Specialist,76991,GBP,57743,EN,PT,United Kingdom,M,United Kingdom,50,"Java, Scala, Azure, Hadoop, Computer Vision",PhD,1,Technology,2024-02-21,2024-03-13,2053,9,Machine Intelligence Group -AI06338,AI Software Engineer,64003,USD,64003,EN,FL,Israel,M,Israel,100,"R, Git, Statistics, MLOps",Bachelor,1,Energy,2024-12-19,2025-01-22,1438,9.1,Neural Networks Co -AI06339,AI Product Manager,107493,EUR,91369,MI,FT,Netherlands,M,Netherlands,100,"Scala, Spark, Deep Learning",Master,2,Gaming,2024-04-10,2024-05-24,1960,9.6,Machine Intelligence Group -AI06340,Machine Learning Researcher,54975,JPY,6047250,EN,CT,Japan,S,Japan,0,"Hadoop, Git, Python",PhD,1,Real Estate,2025-04-13,2025-05-24,702,7.9,Future Systems -AI06341,AI Research Scientist,157422,USD,157422,SE,PT,Norway,L,Norway,50,"Spark, Statistics, PyTorch, Kubernetes",Master,8,Telecommunications,2024-10-16,2024-12-09,616,5.9,Digital Transformation LLC -AI06342,Computer Vision Engineer,289891,USD,289891,EX,FL,Norway,L,Finland,100,"Kubernetes, TensorFlow, PyTorch",Associate,11,Finance,2024-08-01,2024-09-09,1979,9.5,Machine Intelligence Group -AI06343,AI Research Scientist,111548,CHF,100393,EN,PT,Switzerland,M,Australia,100,"NLP, R, Hadoop, Java",PhD,0,Gaming,2024-08-07,2024-09-14,1085,8.2,AI Innovations -AI06344,Computer Vision Engineer,89985,EUR,76487,MI,PT,Austria,L,Austria,50,"Computer Vision, Spark, MLOps",Bachelor,4,Real Estate,2024-04-19,2024-06-13,2089,8.6,TechCorp Inc -AI06345,Data Engineer,67846,USD,67846,EN,FL,Finland,S,Finland,100,"Hadoop, MLOps, Computer Vision, SQL, Java",Bachelor,1,Healthcare,2024-04-21,2024-06-19,2207,5.6,Algorithmic Solutions -AI06346,Autonomous Systems Engineer,54041,EUR,45935,EN,PT,Austria,S,Austria,0,"TensorFlow, Scala, Kubernetes, Tableau",PhD,1,Transportation,2024-11-28,2024-12-24,919,7,Neural Networks Co -AI06347,Autonomous Systems Engineer,72359,USD,72359,SE,PT,China,L,China,0,"PyTorch, Computer Vision, Java, AWS",PhD,7,Government,2025-03-13,2025-05-07,1032,6.8,Cognitive Computing -AI06348,NLP Engineer,123879,USD,123879,SE,PT,Finland,S,Austria,0,"AWS, Hadoop, Mathematics",Associate,8,Media,2025-04-30,2025-07-02,828,7.2,Predictive Systems -AI06349,AI Product Manager,166701,USD,166701,SE,FL,Ireland,L,Ghana,100,"NLP, Git, Hadoop, PyTorch",Associate,8,Transportation,2024-12-11,2024-12-30,2134,5.5,Quantum Computing Inc -AI06350,AI Product Manager,129156,CAD,161445,SE,PT,Canada,S,Nigeria,50,"PyTorch, SQL, TensorFlow, Kubernetes",Bachelor,8,Education,2024-02-11,2024-03-16,1419,8.9,Cloud AI Solutions -AI06351,NLP Engineer,120933,USD,120933,MI,FL,Denmark,M,Denmark,50,"Mathematics, Computer Vision, GCP, PyTorch, SQL",Bachelor,4,Media,2025-03-23,2025-05-09,1949,5.5,Advanced Robotics -AI06352,Computer Vision Engineer,81946,USD,81946,EN,PT,Finland,L,Indonesia,100,"Deep Learning, Data Visualization, PyTorch, MLOps, Computer Vision",PhD,0,Media,2024-06-12,2024-08-18,814,8.1,AI Innovations -AI06353,Machine Learning Engineer,70100,USD,70100,EN,FT,Sweden,L,Sweden,100,"R, Linux, Mathematics, TensorFlow",Master,1,Telecommunications,2024-08-28,2024-10-07,1311,6.1,Digital Transformation LLC -AI06354,Machine Learning Engineer,159640,CHF,143676,MI,CT,Switzerland,L,Mexico,50,"Hadoop, Python, Azure, Linux, Java",Associate,3,Government,2024-04-01,2024-05-10,915,8.4,Algorithmic Solutions -AI06355,AI Architect,137323,USD,137323,SE,CT,United States,S,United States,100,"Tableau, Deep Learning, Git",Bachelor,5,Media,2025-01-16,2025-03-10,2296,5.5,DataVision Ltd -AI06356,AI Specialist,173170,USD,173170,SE,FL,Norway,S,Germany,100,"Git, Linux, Python, Tableau",Master,6,Consulting,2024-02-12,2024-04-20,501,8.8,DataVision Ltd -AI06357,Data Engineer,72402,SGD,94123,EN,CT,Singapore,M,Argentina,0,"MLOps, Mathematics, Statistics, Scala",Bachelor,0,Telecommunications,2024-12-27,2025-03-08,1616,6.4,DataVision Ltd -AI06358,AI Software Engineer,138464,CAD,173080,SE,FL,Canada,L,Canada,100,"Azure, R, Statistics, Spark, TensorFlow",PhD,8,Automotive,2025-04-02,2025-05-28,2151,8.2,Machine Intelligence Group -AI06359,Research Scientist,132681,USD,132681,SE,FL,Israel,M,Japan,100,"Git, Java, AWS",Associate,6,Gaming,2024-05-25,2024-06-19,1871,9.8,Cognitive Computing -AI06360,Data Engineer,255255,USD,255255,EX,FL,Denmark,M,Nigeria,100,"Azure, GCP, Statistics, SQL, Deep Learning",Bachelor,16,Media,2025-03-12,2025-05-03,1099,6.1,Autonomous Tech -AI06361,Data Scientist,65881,EUR,55999,EN,FT,Netherlands,L,Netherlands,100,"Python, GCP, Data Visualization",PhD,1,Media,2025-01-08,2025-03-05,704,5.1,Advanced Robotics -AI06362,Data Analyst,100927,USD,100927,SE,FT,Israel,M,Israel,100,"Python, Data Visualization, Mathematics, SQL, Java",Bachelor,6,Telecommunications,2024-08-03,2024-08-21,1875,7.6,TechCorp Inc -AI06363,ML Ops Engineer,158295,USD,158295,EX,FL,Ireland,M,Finland,0,"Tableau, Docker, SQL",Associate,18,Telecommunications,2024-04-27,2024-05-18,1494,9.9,DataVision Ltd -AI06364,NLP Engineer,62963,GBP,47222,EN,FL,United Kingdom,M,United Kingdom,50,"Scala, Java, R, SQL",Master,0,Telecommunications,2024-02-06,2024-04-14,535,6.2,Neural Networks Co -AI06365,Machine Learning Researcher,100228,USD,100228,MI,FT,Israel,L,Israel,100,"Java, Mathematics, TensorFlow, Python",Bachelor,2,Consulting,2024-12-24,2025-01-12,1774,5.4,Quantum Computing Inc -AI06366,Computer Vision Engineer,74437,EUR,63271,EN,PT,France,M,Spain,0,"Kubernetes, Python, Spark, Linux, SQL",Bachelor,1,Energy,2024-07-30,2024-09-13,1328,6.8,Cognitive Computing -AI06367,Computer Vision Engineer,82236,USD,82236,EX,CT,China,M,China,50,"MLOps, SQL, Statistics, Scala",Associate,16,Healthcare,2024-08-21,2024-10-10,2143,5.8,Algorithmic Solutions -AI06368,Data Analyst,161597,EUR,137357,EX,FT,Germany,L,Portugal,100,"PyTorch, Mathematics, Hadoop, NLP",Master,10,Technology,2024-09-02,2024-10-16,1862,5.3,Smart Analytics -AI06369,Research Scientist,158726,USD,158726,EX,FT,United States,S,United States,0,"Kubernetes, R, Computer Vision, Deep Learning, Statistics",Associate,19,Energy,2024-06-24,2024-08-20,1436,7.4,Autonomous Tech -AI06370,Robotics Engineer,42660,USD,42660,SE,FT,India,M,India,0,"NLP, SQL, Git, PyTorch",Master,6,Consulting,2024-08-21,2024-09-14,1864,5.6,Cognitive Computing -AI06371,Head of AI,201912,CHF,181721,EX,FL,Switzerland,S,Switzerland,100,"Python, R, Data Visualization, Computer Vision",PhD,14,Healthcare,2024-10-19,2024-11-23,755,7.7,Predictive Systems -AI06372,AI Research Scientist,16975,USD,16975,EN,FL,India,S,India,50,"Deep Learning, SQL, MLOps, R, Docker",Bachelor,1,Telecommunications,2024-04-07,2024-05-27,1613,8.3,Quantum Computing Inc -AI06373,Data Analyst,65768,USD,65768,EN,FT,United States,M,Czech Republic,0,"Java, Hadoop, Kubernetes, Computer Vision, Statistics",Bachelor,1,Education,2024-06-05,2024-07-05,589,5.9,AI Innovations -AI06374,Machine Learning Engineer,31201,USD,31201,MI,FL,India,M,India,0,"Linux, GCP, Data Visualization",Bachelor,4,Retail,2024-01-18,2024-02-12,1186,6.2,Advanced Robotics -AI06375,AI Research Scientist,99393,EUR,84484,MI,FL,France,L,China,50,"Mathematics, Docker, Python, TensorFlow, Tableau",Master,2,Consulting,2024-08-13,2024-09-20,523,8.9,DeepTech Ventures -AI06376,Data Analyst,184065,EUR,156455,EX,FT,Germany,L,Germany,50,"Kubernetes, PyTorch, Tableau, Mathematics",PhD,12,Gaming,2025-04-03,2025-05-13,703,6.7,TechCorp Inc -AI06377,AI Specialist,173893,USD,173893,SE,CT,Norway,M,Norway,0,"AWS, Mathematics, Python",Master,6,Gaming,2024-05-27,2024-08-03,1454,5.5,Cloud AI Solutions -AI06378,NLP Engineer,112570,USD,112570,SE,FL,South Korea,S,Romania,50,"Spark, Git, MLOps, Scala",PhD,6,Technology,2025-01-29,2025-02-20,1131,8.1,TechCorp Inc -AI06379,AI Product Manager,86672,USD,86672,MI,CT,Finland,M,Finland,50,"Git, R, Docker, AWS",Bachelor,2,Automotive,2024-08-28,2024-10-27,849,7.3,Future Systems -AI06380,Data Scientist,225977,USD,225977,SE,FL,Norway,L,Argentina,50,"Linux, Data Visualization, Spark",PhD,9,Consulting,2024-11-21,2024-12-05,1561,5.2,Digital Transformation LLC -AI06381,AI Consultant,65278,AUD,88125,MI,CT,Australia,S,Austria,100,"AWS, Data Visualization, Tableau",Master,4,Real Estate,2024-02-20,2024-03-09,1960,5.2,Predictive Systems -AI06382,Robotics Engineer,103808,EUR,88237,SE,CT,Austria,S,Norway,100,"Data Visualization, MLOps, Tableau, PyTorch",PhD,7,Education,2024-06-21,2024-07-08,2354,8.6,TechCorp Inc -AI06383,Data Analyst,202963,CAD,253704,EX,FL,Canada,M,Canada,50,"Deep Learning, Scala, Python, Mathematics",Bachelor,11,Technology,2024-03-02,2024-04-12,568,5.6,Neural Networks Co -AI06384,ML Ops Engineer,85463,USD,85463,EX,FT,China,S,China,100,"Scala, Kubernetes, Deep Learning, NLP",Associate,15,Healthcare,2024-08-22,2024-10-15,1703,7.8,TechCorp Inc -AI06385,AI Consultant,104466,USD,104466,EN,FT,Norway,L,Norway,100,"Kubernetes, PyTorch, Hadoop, Computer Vision",PhD,1,Healthcare,2025-01-22,2025-03-04,1730,6.4,Algorithmic Solutions -AI06386,Machine Learning Engineer,63202,USD,63202,MI,FL,South Korea,M,Poland,50,"Python, SQL, Statistics, Spark",Bachelor,3,Telecommunications,2025-03-08,2025-04-10,2044,6.1,Neural Networks Co -AI06387,Head of AI,120132,USD,120132,SE,PT,Norway,S,Norway,0,"Java, SQL, Python, R, Linux",Bachelor,5,Education,2024-03-25,2024-05-09,1500,5,Autonomous Tech -AI06388,Robotics Engineer,83672,CHF,75305,EN,CT,Switzerland,S,India,100,"NLP, Data Visualization, Tableau",Bachelor,1,Automotive,2024-12-11,2024-12-25,2484,6,DeepTech Ventures -AI06389,Data Analyst,74974,USD,74974,EN,FT,Norway,S,Norway,0,"SQL, Computer Vision, R, Hadoop",PhD,1,Healthcare,2024-03-20,2024-05-27,899,8,DeepTech Ventures -AI06390,Research Scientist,70564,USD,70564,EN,CT,Sweden,S,Sweden,50,"SQL, Data Visualization, GCP, MLOps",Master,0,Government,2024-02-26,2024-05-08,2322,8.4,Neural Networks Co -AI06391,AI Consultant,181975,SGD,236568,SE,FL,Singapore,L,South Korea,0,"Azure, Java, Hadoop, PyTorch",Master,6,Transportation,2024-04-30,2024-06-30,2186,5.1,Digital Transformation LLC -AI06392,Data Scientist,125178,CHF,112660,EN,CT,Switzerland,L,Switzerland,100,"Docker, Azure, SQL, Computer Vision",Bachelor,1,Government,2025-03-10,2025-05-04,1828,8,Smart Analytics -AI06393,AI Software Engineer,118802,USD,118802,EX,FT,South Korea,M,Estonia,0,"GCP, Docker, Computer Vision",PhD,10,Education,2024-08-29,2024-10-17,2036,8.6,Cognitive Computing -AI06394,Autonomous Systems Engineer,96565,USD,96565,SE,FL,Ireland,S,Ireland,50,"Mathematics, Python, TensorFlow, Spark, Hadoop",Master,9,Healthcare,2025-03-24,2025-05-18,1179,6.5,Cognitive Computing -AI06395,NLP Engineer,31256,USD,31256,EN,FL,China,S,Singapore,0,"AWS, Docker, Linux, Kubernetes",PhD,1,Energy,2025-04-18,2025-06-06,1804,5.5,Future Systems -AI06396,Data Engineer,75314,USD,75314,EN,FL,Finland,M,Finland,50,"Tableau, PyTorch, Statistics, NLP",PhD,1,Media,2024-10-29,2024-11-12,1581,7.3,Smart Analytics -AI06397,Research Scientist,51533,USD,51533,EN,FT,Sweden,M,Nigeria,0,"Computer Vision, AWS, GCP, Kubernetes",Associate,1,Finance,2024-12-29,2025-01-13,2031,10,Cloud AI Solutions -AI06398,Data Engineer,121829,USD,121829,MI,CT,Ireland,L,Ireland,0,"Python, Docker, Mathematics, Kubernetes",Associate,2,Automotive,2024-07-10,2024-08-01,2140,6.7,Future Systems -AI06399,AI Research Scientist,138335,EUR,117585,EX,PT,Germany,M,Germany,100,"Kubernetes, Spark, Statistics",Associate,19,Transportation,2025-04-21,2025-05-13,808,6.3,Quantum Computing Inc -AI06400,Data Engineer,143264,EUR,121774,SE,CT,Netherlands,M,Netherlands,50,"Hadoop, GCP, NLP",Bachelor,9,Healthcare,2024-02-05,2024-03-21,1023,9.2,Autonomous Tech -AI06401,Principal Data Scientist,121815,EUR,103543,SE,CT,Germany,L,Germany,50,"Scala, Python, Spark, MLOps",Associate,7,Manufacturing,2024-10-11,2024-12-13,1914,9.1,Digital Transformation LLC -AI06402,AI Consultant,49981,USD,49981,EN,PT,Finland,S,Thailand,0,"Python, AWS, SQL, NLP",PhD,1,Energy,2024-12-12,2025-02-17,1018,9.2,DataVision Ltd -AI06403,AI Specialist,150416,EUR,127854,EX,FL,Germany,M,Germany,100,"AWS, Python, TensorFlow, PyTorch, GCP",PhD,13,Telecommunications,2024-05-02,2024-07-03,2420,5.3,Quantum Computing Inc -AI06404,AI Software Engineer,121297,CHF,109167,EN,PT,Switzerland,L,Switzerland,0,"Scala, Docker, Mathematics, AWS, Java",PhD,0,Consulting,2024-06-06,2024-06-27,2283,6.8,AI Innovations -AI06405,Deep Learning Engineer,213889,AUD,288750,EX,FL,Australia,S,Australia,50,"Git, Mathematics, PyTorch, Java",Associate,11,Technology,2024-04-30,2024-06-15,2273,7.6,Algorithmic Solutions -AI06406,Deep Learning Engineer,130442,USD,130442,MI,CT,United States,L,United States,50,"Statistics, Git, PyTorch",PhD,2,Gaming,2024-03-19,2024-05-10,1768,5.4,Algorithmic Solutions -AI06407,Computer Vision Engineer,206439,CAD,258049,EX,FT,Canada,S,Canada,0,"Linux, Deep Learning, NLP",Master,10,Government,2024-01-18,2024-02-03,1229,8.2,AI Innovations -AI06408,Data Analyst,34594,USD,34594,EN,PT,China,L,China,100,"NLP, AWS, Azure, Python",Associate,0,Automotive,2025-04-20,2025-06-24,624,7,AI Innovations -AI06409,Deep Learning Engineer,162384,USD,162384,SE,PT,Israel,L,Kenya,100,"GCP, SQL, Linux",PhD,6,Automotive,2024-12-10,2025-02-19,2298,7.3,Advanced Robotics -AI06410,Data Analyst,102488,CAD,128110,SE,FT,Canada,M,Canada,50,"Statistics, MLOps, TensorFlow, Data Visualization, Spark",Associate,5,Consulting,2024-10-13,2024-11-13,680,8.7,TechCorp Inc -AI06411,ML Ops Engineer,156199,USD,156199,EX,FL,Finland,S,Finland,50,"R, Data Visualization, Docker",PhD,17,Automotive,2024-12-11,2025-02-11,2456,7.6,AI Innovations -AI06412,AI Software Engineer,150000,USD,150000,EX,FT,South Korea,L,South Korea,100,"Kubernetes, Azure, Spark",Associate,16,Government,2025-04-01,2025-04-23,939,9.9,Autonomous Tech -AI06413,Data Scientist,111963,CAD,139954,SE,FT,Canada,L,Canada,100,"Statistics, Scala, Linux",Master,5,Finance,2024-09-15,2024-10-08,638,6.8,Cloud AI Solutions -AI06414,Data Engineer,67558,USD,67558,MI,FL,Sweden,S,Sweden,50,"NLP, Python, Mathematics, AWS, Scala",Bachelor,3,Education,2024-02-01,2024-02-27,2198,5.2,Future Systems -AI06415,Data Scientist,75401,EUR,64091,MI,FL,France,M,France,100,"SQL, Linux, Kubernetes, Java, PyTorch",Bachelor,3,Automotive,2024-01-06,2024-01-25,2376,5.6,AI Innovations -AI06416,AI Research Scientist,77098,CHF,69388,EN,FL,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, GCP, Statistics",Master,1,Healthcare,2024-02-10,2024-04-19,1408,5.9,Future Systems -AI06417,Data Engineer,129667,GBP,97250,MI,PT,United Kingdom,L,United Kingdom,100,"Python, Git, NLP, AWS",Associate,4,Telecommunications,2024-04-08,2024-05-17,1925,9.2,AI Innovations -AI06418,Robotics Engineer,62417,EUR,53054,EN,FL,Netherlands,M,Netherlands,100,"Python, R, Docker",PhD,0,Government,2024-07-22,2024-08-11,1830,6.3,Machine Intelligence Group -AI06419,AI Consultant,161660,JPY,17782600,SE,PT,Japan,M,Romania,0,"Computer Vision, Python, GCP",PhD,6,Real Estate,2024-05-04,2024-05-18,1197,6.1,Advanced Robotics -AI06420,Computer Vision Engineer,85425,AUD,115324,MI,PT,Australia,S,Australia,0,"Spark, Git, Python, Computer Vision, NLP",Associate,4,Consulting,2024-08-12,2024-10-07,1642,8.8,DeepTech Ventures -AI06421,AI Product Manager,269941,CHF,242947,EX,PT,Switzerland,S,Switzerland,0,"SQL, GCP, NLP, Spark",PhD,17,Finance,2024-01-06,2024-03-12,2138,7.5,Advanced Robotics -AI06422,Data Analyst,349432,USD,349432,EX,FT,Denmark,L,Denmark,0,"SQL, Linux, GCP, Hadoop, R",Associate,17,Energy,2024-10-17,2024-12-13,1557,9.9,Quantum Computing Inc -AI06423,Autonomous Systems Engineer,52126,USD,52126,SE,CT,China,S,Brazil,100,"Hadoop, Git, Java",Master,9,Government,2024-09-18,2024-11-02,1709,8,Predictive Systems -AI06424,AI Product Manager,166822,EUR,141799,EX,PT,Germany,M,Germany,0,"Hadoop, Data Visualization, Scala",PhD,11,Consulting,2025-01-23,2025-02-17,2222,5.9,Digital Transformation LLC -AI06425,Robotics Engineer,136925,AUD,184849,EX,CT,Australia,S,Australia,100,"MLOps, AWS, Python, Scala",Associate,17,Healthcare,2024-09-08,2024-09-30,2197,7.5,Advanced Robotics -AI06426,Deep Learning Engineer,98877,CAD,123596,MI,FT,Canada,L,Canada,100,"TensorFlow, Azure, Linux, Git",Master,2,Energy,2024-01-06,2024-03-18,871,5.4,Digital Transformation LLC -AI06427,Deep Learning Engineer,168236,EUR,143001,EX,FT,France,M,France,100,"AWS, Kubernetes, PyTorch",Bachelor,18,Telecommunications,2024-04-08,2024-05-15,1463,7.3,Advanced Robotics -AI06428,Machine Learning Engineer,102521,CAD,128151,MI,PT,Canada,L,Canada,100,"Kubernetes, R, SQL, Python",Bachelor,3,Gaming,2024-04-24,2024-06-19,697,6.9,Machine Intelligence Group -AI06429,Robotics Engineer,106928,USD,106928,MI,PT,Norway,M,Vietnam,0,"TensorFlow, Statistics, Spark",Associate,4,Real Estate,2024-11-10,2025-01-18,829,7.9,DeepTech Ventures -AI06430,Data Scientist,76026,GBP,57020,EN,FL,United Kingdom,S,United Kingdom,100,"Python, Docker, AWS, TensorFlow",PhD,0,Healthcare,2024-02-06,2024-03-14,2063,8.2,Algorithmic Solutions -AI06431,AI Specialist,88213,USD,88213,EN,FT,Sweden,L,Sweden,100,"Linux, TensorFlow, Computer Vision, Python, Hadoop",PhD,1,Energy,2024-05-03,2024-05-19,1771,8.7,Quantum Computing Inc -AI06432,AI Architect,82027,USD,82027,EN,FL,Sweden,L,Romania,0,"Mathematics, Hadoop, Scala",Associate,0,Media,2025-01-10,2025-01-25,2035,6.7,Advanced Robotics -AI06433,Robotics Engineer,109435,USD,109435,EN,FT,Denmark,L,Denmark,100,"Mathematics, GCP, Linux, MLOps, Python",PhD,1,Real Estate,2024-01-10,2024-03-01,545,8.5,Cognitive Computing -AI06434,Autonomous Systems Engineer,123502,AUD,166728,MI,FL,Australia,L,Sweden,100,"Python, Kubernetes, Deep Learning, Computer Vision, Hadoop",Associate,2,Education,2024-07-29,2024-08-27,1793,8,DataVision Ltd -AI06435,Autonomous Systems Engineer,80462,USD,80462,EN,PT,United States,S,Brazil,100,"Kubernetes, AWS, Hadoop",Associate,1,Consulting,2024-12-24,2025-01-24,1904,7.9,Machine Intelligence Group -AI06436,Machine Learning Engineer,109229,USD,109229,MI,PT,Ireland,M,Ireland,50,"Statistics, TensorFlow, Azure, GCP",PhD,4,Telecommunications,2024-04-09,2024-05-02,2303,9.2,Advanced Robotics -AI06437,AI Consultant,159957,EUR,135963,SE,FL,Netherlands,L,Netherlands,50,"GCP, TensorFlow, SQL, Computer Vision, Hadoop",Associate,9,Consulting,2024-07-17,2024-09-06,1452,5.2,Cloud AI Solutions -AI06438,Head of AI,65788,USD,65788,MI,CT,Sweden,S,Portugal,0,"Git, Tableau, Python",PhD,2,Retail,2024-10-17,2024-12-20,1066,9,Predictive Systems -AI06439,AI Software Engineer,100348,USD,100348,MI,FT,Ireland,L,Ireland,100,"Hadoop, Python, Git, AWS, Docker",Bachelor,2,Retail,2024-07-02,2024-09-07,2267,8,Digital Transformation LLC -AI06440,Computer Vision Engineer,47408,USD,47408,SE,FT,China,S,China,50,"NLP, Tableau, Python",Master,6,Gaming,2024-06-14,2024-08-26,2076,6.8,Machine Intelligence Group -AI06441,ML Ops Engineer,104139,USD,104139,SE,FT,Finland,M,Romania,100,"Python, TensorFlow, Statistics, Git",Associate,7,Energy,2024-10-29,2024-12-22,2233,9.6,Autonomous Tech -AI06442,AI Product Manager,88730,JPY,9760300,EN,FL,Japan,L,Japan,0,"R, Spark, MLOps, TensorFlow",PhD,1,Media,2024-05-23,2024-06-30,888,7.2,DataVision Ltd -AI06443,AI Product Manager,352205,USD,352205,EX,FT,Denmark,L,Denmark,100,"Computer Vision, Python, Tableau, NLP",Bachelor,16,Media,2024-10-27,2024-11-28,1380,6.6,Neural Networks Co -AI06444,AI Research Scientist,98921,EUR,84083,MI,FT,Austria,L,Austria,0,"Kubernetes, TensorFlow, Computer Vision, Git, NLP",PhD,2,Finance,2024-11-25,2025-01-28,2210,6.2,DeepTech Ventures -AI06445,Robotics Engineer,183596,EUR,156057,EX,CT,Netherlands,S,Netherlands,100,"Hadoop, Scala, Mathematics",Bachelor,19,Energy,2024-01-01,2024-03-11,1209,8.8,DataVision Ltd -AI06446,AI Architect,80147,USD,80147,MI,CT,Sweden,M,Denmark,50,"Python, Spark, GCP, Deep Learning, MLOps",PhD,2,Automotive,2024-03-28,2024-04-27,2364,6.9,Cloud AI Solutions -AI06447,Head of AI,38802,USD,38802,EN,FL,South Korea,S,South Korea,50,"Data Visualization, Git, Spark",Master,0,Manufacturing,2024-12-28,2025-02-14,1953,9.4,Quantum Computing Inc -AI06448,Robotics Engineer,42256,USD,42256,EN,FT,South Korea,M,South Korea,50,"PyTorch, GCP, SQL, Data Visualization",Bachelor,1,Automotive,2024-04-04,2024-05-22,2290,7.2,DataVision Ltd -AI06449,Machine Learning Researcher,295649,JPY,32521390,EX,FL,Japan,L,Japan,100,"Git, Mathematics, R, Python, Azure",Associate,10,Technology,2024-11-14,2025-01-12,2439,7.2,Cloud AI Solutions -AI06450,Head of AI,139693,GBP,104770,SE,PT,United Kingdom,S,United Kingdom,0,"GCP, Git, Tableau, MLOps",Master,5,Media,2025-03-24,2025-04-22,1262,5,AI Innovations -AI06451,Deep Learning Engineer,252118,USD,252118,EX,FT,Norway,S,Norway,50,"Hadoop, Computer Vision, Python",Associate,12,Automotive,2024-12-02,2025-02-03,1914,5.3,DataVision Ltd -AI06452,Research Scientist,96310,USD,96310,MI,FL,South Korea,L,South Korea,100,"Python, NLP, TensorFlow",Master,3,Real Estate,2024-09-30,2024-10-15,880,7.3,Advanced Robotics -AI06453,Machine Learning Researcher,97905,USD,97905,EX,FL,China,M,United States,50,"Python, Git, Statistics, Computer Vision, Linux",Bachelor,11,Consulting,2024-08-08,2024-09-15,1148,8.1,Smart Analytics -AI06454,AI Product Manager,74082,GBP,55562,EN,PT,United Kingdom,L,United Kingdom,50,"Python, Spark, Tableau, Mathematics, Linux",Master,0,Automotive,2024-08-27,2024-10-01,1197,9.4,Cloud AI Solutions -AI06455,ML Ops Engineer,189768,CHF,170791,SE,FL,Switzerland,S,Switzerland,100,"AWS, Linux, MLOps",Associate,5,Consulting,2024-01-19,2024-03-23,1493,9.4,AI Innovations -AI06456,AI Software Engineer,66570,USD,66570,EN,CT,Sweden,S,Philippines,50,"Computer Vision, GCP, Tableau",Master,1,Telecommunications,2024-07-07,2024-09-08,1957,5.9,Digital Transformation LLC -AI06457,Machine Learning Researcher,326160,CHF,293544,EX,FL,Switzerland,M,Indonesia,100,"Python, Java, Azure",Associate,16,Gaming,2025-01-04,2025-03-02,902,5.9,Cognitive Computing -AI06458,AI Research Scientist,78922,JPY,8681420,EN,FT,Japan,M,Japan,50,"Deep Learning, Computer Vision, PyTorch",Associate,0,Retail,2024-10-15,2024-12-27,1123,5.8,Quantum Computing Inc -AI06459,Data Analyst,49976,USD,49976,MI,PT,China,M,China,100,"Python, GCP, Tableau, SQL",Bachelor,2,Government,2024-12-24,2025-02-03,2010,8.6,Quantum Computing Inc -AI06460,Machine Learning Researcher,64771,USD,64771,EX,CT,China,M,China,50,"Tableau, Python, AWS, Spark, TensorFlow",PhD,10,Government,2025-04-03,2025-05-02,2118,9.9,Neural Networks Co -AI06461,Data Scientist,77752,EUR,66089,EN,CT,Netherlands,M,Netherlands,0,"R, GCP, Tableau, Python, AWS",Master,1,Transportation,2024-01-15,2024-03-05,818,8.1,TechCorp Inc -AI06462,AI Consultant,101180,AUD,136593,SE,CT,Australia,S,India,100,"Java, Data Visualization, PyTorch, Kubernetes, TensorFlow",Associate,5,Telecommunications,2024-04-24,2024-05-13,1032,8.6,Future Systems -AI06463,Computer Vision Engineer,207576,EUR,176440,EX,FL,France,L,France,50,"Statistics, NLP, Scala, Data Visualization",Associate,10,Manufacturing,2025-04-30,2025-05-21,716,8.2,Advanced Robotics -AI06464,AI Software Engineer,30028,USD,30028,MI,FL,India,L,India,50,"Tableau, Kubernetes, GCP, R, Deep Learning",Bachelor,4,Media,2024-01-15,2024-03-04,1402,9.2,Smart Analytics -AI06465,Robotics Engineer,243505,CAD,304381,EX,FT,Canada,L,Canada,50,"Spark, Scala, SQL, Java",Bachelor,12,Finance,2024-07-29,2024-09-12,2274,5.4,TechCorp Inc -AI06466,Robotics Engineer,51214,USD,51214,EN,FT,Finland,S,Finland,0,"Azure, GCP, Java",Master,1,Retail,2024-06-22,2024-07-06,802,7.3,Quantum Computing Inc -AI06467,Data Scientist,76863,CHF,69177,EN,CT,Switzerland,M,Switzerland,0,"Scala, Git, Statistics",Associate,0,Energy,2024-02-05,2024-03-24,1557,7.6,Predictive Systems -AI06468,Machine Learning Engineer,179636,USD,179636,SE,FL,United States,L,United States,0,"Mathematics, Linux, Hadoop, Deep Learning",Master,8,Consulting,2024-12-16,2025-01-29,2432,6.7,Predictive Systems -AI06469,Robotics Engineer,30950,USD,30950,MI,PT,India,L,France,50,"R, SQL, Statistics",PhD,3,Consulting,2024-02-08,2024-03-15,1262,9.1,AI Innovations -AI06470,Principal Data Scientist,148429,USD,148429,SE,CT,Finland,L,South Africa,100,"PyTorch, Computer Vision, TensorFlow, SQL, Java",Associate,5,Manufacturing,2024-08-16,2024-09-13,717,8.9,TechCorp Inc -AI06471,AI Specialist,49035,EUR,41680,EN,FL,Austria,S,Netherlands,100,"Azure, Linux, MLOps",Master,1,Government,2024-11-20,2024-12-28,1457,8.6,Machine Intelligence Group -AI06472,AI Specialist,75189,SGD,97746,EN,CT,Singapore,M,Norway,0,"Mathematics, Azure, TensorFlow, Computer Vision, Hadoop",Master,0,Transportation,2024-12-02,2025-01-04,598,5.7,DeepTech Ventures -AI06473,Robotics Engineer,71967,GBP,53975,EN,PT,United Kingdom,L,United Kingdom,0,"Scala, Tableau, Hadoop, MLOps, NLP",Associate,0,Gaming,2024-05-18,2024-07-10,1985,8.9,Advanced Robotics -AI06474,NLP Engineer,190712,CAD,238390,EX,CT,Canada,S,Canada,50,"PyTorch, R, Kubernetes, Azure",Master,12,Media,2024-12-21,2025-01-10,1967,9.3,DataVision Ltd -AI06475,NLP Engineer,297771,GBP,223328,EX,FL,United Kingdom,L,United Kingdom,50,"AWS, Linux, PyTorch, Azure",PhD,14,Gaming,2025-02-24,2025-03-21,1502,5.7,Future Systems -AI06476,AI Specialist,156829,USD,156829,EX,FT,South Korea,S,South Korea,0,"SQL, Scala, Deep Learning, GCP",Associate,13,Consulting,2025-04-19,2025-05-17,762,7.6,AI Innovations -AI06477,ML Ops Engineer,143894,EUR,122310,EX,CT,France,M,Indonesia,0,"Python, TensorFlow, Computer Vision, Spark",PhD,18,Automotive,2025-04-21,2025-05-12,1614,7.7,Predictive Systems -AI06478,AI Software Engineer,150682,CHF,135614,MI,CT,Switzerland,M,Switzerland,100,"Java, PyTorch, Azure",Master,3,Education,2024-01-15,2024-02-13,1957,6.2,Algorithmic Solutions -AI06479,AI Product Manager,72926,USD,72926,EN,CT,United States,M,United States,0,"Python, Kubernetes, TensorFlow, Mathematics, Docker",PhD,1,Consulting,2024-08-26,2024-09-23,2383,9.7,Future Systems -AI06480,AI Specialist,50034,USD,50034,MI,FL,China,M,China,50,"Computer Vision, Azure, Kubernetes, Scala, MLOps",Associate,3,Healthcare,2025-04-14,2025-05-24,1718,9.8,DataVision Ltd -AI06481,Machine Learning Engineer,227301,USD,227301,EX,FL,Sweden,M,Sweden,0,"Linux, Tableau, R, Docker, Statistics",Bachelor,12,Manufacturing,2024-03-16,2024-05-07,1933,9.2,Future Systems -AI06482,Data Engineer,177520,GBP,133140,SE,FL,United Kingdom,L,Portugal,0,"Scala, Mathematics, Spark, Kubernetes",Associate,7,Retail,2024-12-03,2025-01-10,1975,8.3,Machine Intelligence Group -AI06483,AI Product Manager,290219,CHF,261197,EX,FT,Switzerland,M,Switzerland,100,"PyTorch, Docker, Linux, TensorFlow",Associate,19,Finance,2024-07-22,2024-09-22,513,5.8,DataVision Ltd -AI06484,AI Research Scientist,178653,EUR,151855,EX,CT,Austria,L,Germany,0,"GCP, Kubernetes, Python",Master,18,Healthcare,2025-01-20,2025-02-14,1825,7.3,Autonomous Tech -AI06485,AI Product Manager,122006,EUR,103705,SE,CT,Germany,M,Germany,0,"Git, NLP, Linux, Scala, Data Visualization",Associate,8,Finance,2025-02-07,2025-04-09,1514,9.6,Neural Networks Co -AI06486,Robotics Engineer,168307,GBP,126230,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, SQL",Master,12,Finance,2024-12-01,2024-12-30,1505,9.9,DeepTech Ventures -AI06487,Principal Data Scientist,124629,USD,124629,EX,FT,South Korea,M,South Korea,50,"Git, Python, Azure",PhD,19,Real Estate,2024-12-02,2025-02-12,1102,8.1,Algorithmic Solutions -AI06488,Data Engineer,137796,EUR,117127,EX,CT,Austria,S,Austria,0,"Statistics, TensorFlow, Kubernetes, Linux",PhD,13,Government,2024-08-04,2024-08-28,1582,6.4,DeepTech Ventures -AI06489,AI Specialist,81533,EUR,69303,EN,CT,France,L,France,0,"Data Visualization, Docker, Tableau",Bachelor,1,Telecommunications,2025-04-08,2025-05-21,1781,5.6,Future Systems -AI06490,Principal Data Scientist,86860,USD,86860,EX,CT,China,S,Estonia,50,"SQL, Git, Kubernetes, Deep Learning",Master,18,Consulting,2024-09-02,2024-10-17,1805,7.6,AI Innovations -AI06491,Data Engineer,81781,EUR,69514,EN,FL,Netherlands,L,Netherlands,100,"PyTorch, Computer Vision, Deep Learning, TensorFlow, Azure",PhD,1,Telecommunications,2025-01-15,2025-03-04,2388,5.5,Predictive Systems -AI06492,AI Product Manager,140704,USD,140704,SE,FL,Finland,M,Finland,0,"PyTorch, SQL, Deep Learning, Tableau, NLP",Bachelor,8,Retail,2024-02-05,2024-03-24,1057,5.1,Cognitive Computing -AI06493,AI Specialist,61576,EUR,52340,EN,FL,Germany,S,Germany,50,"Spark, Linux, Git, R, Deep Learning",PhD,0,Consulting,2024-04-02,2024-04-25,698,9.1,Cloud AI Solutions -AI06494,AI Research Scientist,29955,USD,29955,EN,CT,China,M,Netherlands,50,"Hadoop, SQL, Azure, Kubernetes, Tableau",Associate,0,Transportation,2025-02-28,2025-03-26,1800,8.1,DataVision Ltd -AI06495,Computer Vision Engineer,107488,EUR,91365,SE,PT,Netherlands,S,Turkey,0,"Mathematics, Docker, Kubernetes, SQL, TensorFlow",Associate,6,Transportation,2024-03-27,2024-04-20,503,9.8,Autonomous Tech -AI06496,AI Specialist,18247,USD,18247,EN,PT,India,S,India,0,"Scala, Python, Computer Vision, Deep Learning, TensorFlow",Master,1,Gaming,2024-10-09,2024-10-30,1178,7.9,Algorithmic Solutions -AI06497,Machine Learning Engineer,141464,USD,141464,MI,FT,Norway,M,Norway,100,"Git, Java, AWS",PhD,2,Real Estate,2024-02-03,2024-03-11,1296,6.7,AI Innovations -AI06498,AI Product Manager,41759,USD,41759,SE,FL,India,S,India,100,"Mathematics, Scala, MLOps, Statistics, Linux",Master,6,Gaming,2024-01-26,2024-03-05,1858,7.6,Cloud AI Solutions -AI06499,Data Analyst,55004,JPY,6050440,EN,PT,Japan,M,Japan,100,"Git, Kubernetes, NLP",Associate,1,Gaming,2024-02-14,2024-03-20,2454,7,DeepTech Ventures -AI06500,AI Consultant,43128,USD,43128,MI,CT,China,M,China,100,"TensorFlow, Java, Azure, Mathematics, AWS",PhD,4,Transportation,2024-01-22,2024-02-20,871,7.8,Machine Intelligence Group -AI06501,AI Consultant,82614,EUR,70222,EN,CT,Germany,L,Vietnam,100,"Azure, Kubernetes, SQL",Bachelor,1,Real Estate,2024-03-17,2024-05-26,2454,7.5,Smart Analytics -AI06502,AI Research Scientist,306002,EUR,260102,EX,PT,Netherlands,L,Netherlands,100,"Linux, Hadoop, Azure, Deep Learning",Associate,17,Automotive,2024-12-17,2025-02-08,1412,9.2,Cloud AI Solutions -AI06503,Deep Learning Engineer,129451,USD,129451,SE,PT,Ireland,S,Austria,50,"Python, Linux, Deep Learning, Git, Computer Vision",Bachelor,8,Automotive,2024-10-15,2024-11-05,1411,10,Cognitive Computing -AI06504,AI Architect,192815,CHF,173534,EX,FL,Switzerland,M,Switzerland,50,"Git, SQL, TensorFlow",Master,11,Retail,2024-01-02,2024-01-29,2257,8.8,Autonomous Tech -AI06505,Research Scientist,133972,USD,133972,EX,FT,Israel,M,Singapore,0,"AWS, Kubernetes, Mathematics",Bachelor,12,Healthcare,2024-05-14,2024-06-12,1654,6.5,Digital Transformation LLC -AI06506,Data Scientist,77616,USD,77616,MI,FL,South Korea,S,South Korea,50,"AWS, TensorFlow, Scala, Tableau, Deep Learning",Master,4,Technology,2025-04-07,2025-06-12,665,5.5,Machine Intelligence Group -AI06507,Principal Data Scientist,47133,USD,47133,EN,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Spark, NLP, Java",Associate,1,Energy,2025-03-14,2025-04-03,533,5.1,Cognitive Computing -AI06508,Research Scientist,70801,USD,70801,MI,CT,South Korea,S,South Korea,100,"Tableau, Python, Java",Associate,3,Retail,2024-07-18,2024-08-10,1335,6.1,DeepTech Ventures -AI06509,AI Specialist,120997,USD,120997,SE,FL,Finland,M,Finland,50,"AWS, Deep Learning, SQL, Scala",Associate,9,Automotive,2024-05-03,2024-07-06,2203,6.7,Digital Transformation LLC -AI06510,AI Product Manager,263003,EUR,223553,EX,FL,Austria,L,Austria,100,"Scala, R, Hadoop, Deep Learning",Bachelor,15,Real Estate,2024-02-01,2024-03-18,851,6.6,Neural Networks Co -AI06511,AI Consultant,48759,GBP,36569,EN,PT,United Kingdom,S,Australia,50,"Azure, Java, Linux",PhD,0,Transportation,2024-08-30,2024-10-04,1794,7.8,Cognitive Computing -AI06512,Machine Learning Engineer,195629,GBP,146722,EX,CT,United Kingdom,S,United Kingdom,100,"R, GCP, Git",Associate,17,Energy,2024-12-30,2025-02-21,1765,8,Algorithmic Solutions -AI06513,AI Research Scientist,161173,USD,161173,SE,PT,Norway,L,Norway,0,"Computer Vision, AWS, Linux, Spark",Bachelor,9,Gaming,2024-10-01,2024-11-09,968,9.3,Digital Transformation LLC -AI06514,AI Consultant,94896,USD,94896,SE,CT,South Korea,S,South Korea,100,"Python, MLOps, Azure, Tableau",Associate,7,Finance,2024-02-05,2024-03-06,1668,5.9,Cognitive Computing -AI06515,AI Architect,47417,USD,47417,EN,FL,Israel,S,Israel,0,"Spark, Docker, Computer Vision",Bachelor,1,Retail,2025-02-14,2025-03-27,1934,6.2,AI Innovations -AI06516,Deep Learning Engineer,90359,AUD,121985,MI,FL,Australia,S,Australia,50,"Kubernetes, MLOps, Hadoop",Master,3,Government,2024-12-24,2025-02-05,1562,8.3,Advanced Robotics -AI06517,AI Research Scientist,123662,GBP,92747,MI,FL,United Kingdom,L,China,50,"Linux, Data Visualization, Hadoop",Master,2,Energy,2024-07-02,2024-07-21,2185,9,Predictive Systems -AI06518,Machine Learning Researcher,146667,AUD,198000,SE,PT,Australia,M,Australia,50,"R, PyTorch, Linux, Mathematics",Bachelor,5,Retail,2024-03-28,2024-04-18,2204,6.1,Digital Transformation LLC -AI06519,Data Scientist,66452,EUR,56484,EN,FT,Germany,S,Germany,50,"Java, Kubernetes, Tableau, NLP",Associate,0,Government,2024-12-04,2025-01-09,1711,8,Algorithmic Solutions -AI06520,Principal Data Scientist,50813,GBP,38110,EN,CT,United Kingdom,S,United Kingdom,0,"Python, Mathematics, Data Visualization, Spark, TensorFlow",Associate,1,Healthcare,2024-12-11,2025-01-30,880,6.1,DeepTech Ventures -AI06521,AI Research Scientist,226711,USD,226711,EX,PT,Sweden,L,Sweden,50,"SQL, Tableau, Python",Master,17,Consulting,2025-03-27,2025-04-14,1098,6.8,DeepTech Ventures -AI06522,AI Specialist,145967,EUR,124072,EX,FL,Netherlands,S,Netherlands,0,"TensorFlow, Python, Hadoop, Docker",PhD,15,Education,2025-02-04,2025-02-24,913,5.1,Predictive Systems -AI06523,Machine Learning Engineer,214976,USD,214976,EX,CT,Sweden,S,Sweden,0,"Python, Kubernetes, PyTorch",Master,11,Manufacturing,2024-04-16,2024-06-01,2129,7,Cognitive Computing -AI06524,AI Specialist,60294,USD,60294,MI,CT,South Korea,S,South Korea,100,"R, SQL, Tableau",Associate,4,Transportation,2024-03-26,2024-05-28,1820,7.8,Algorithmic Solutions -AI06525,NLP Engineer,100722,USD,100722,MI,CT,Norway,S,Thailand,100,"Python, Azure, Computer Vision, Docker",Master,3,Real Estate,2024-08-20,2024-10-17,1877,6.2,Digital Transformation LLC -AI06526,Machine Learning Engineer,100577,EUR,85490,MI,FL,Netherlands,S,Netherlands,50,"SQL, Scala, Computer Vision, Data Visualization, PyTorch",Bachelor,3,Automotive,2024-04-12,2024-06-05,717,7.7,Future Systems -AI06527,Autonomous Systems Engineer,117696,USD,117696,MI,FL,United States,M,United States,0,"Linux, MLOps, Java, SQL, PyTorch",Associate,3,Energy,2024-12-30,2025-02-11,1640,5.8,Machine Intelligence Group -AI06528,Head of AI,184939,USD,184939,EX,PT,Finland,L,Finland,50,"R, SQL, PyTorch, TensorFlow, Tableau",Master,19,Gaming,2024-03-07,2024-04-18,1259,7.7,Autonomous Tech -AI06529,AI Software Engineer,279576,USD,279576,EX,PT,Norway,S,Netherlands,50,"SQL, PyTorch, Java, Data Visualization, AWS",Bachelor,13,Automotive,2024-03-12,2024-05-03,2005,6,Smart Analytics -AI06530,Data Analyst,223224,USD,223224,SE,PT,Norway,L,Norway,0,"Spark, Mathematics, R, TensorFlow, GCP",Bachelor,6,Government,2024-07-04,2024-09-09,2433,8.4,Cloud AI Solutions -AI06531,Robotics Engineer,154533,USD,154533,EX,FL,South Korea,M,South Korea,100,"Hadoop, AWS, Computer Vision, Azure",Bachelor,18,Gaming,2024-11-26,2025-01-27,2073,5,AI Innovations -AI06532,AI Architect,175373,SGD,227985,EX,FL,Singapore,M,Singapore,0,"SQL, Deep Learning, Kubernetes",Master,11,Healthcare,2024-11-29,2024-12-17,1476,7,Quantum Computing Inc -AI06533,Data Analyst,71134,USD,71134,SE,CT,China,M,China,0,"Linux, Deep Learning, Data Visualization",Bachelor,7,Real Estate,2024-06-29,2024-08-17,727,7.5,Predictive Systems -AI06534,AI Product Manager,61514,EUR,52287,EN,FL,Netherlands,S,Netherlands,100,"TensorFlow, Kubernetes, Data Visualization, Spark, SQL",PhD,0,Telecommunications,2024-10-15,2024-11-22,1193,7.5,Predictive Systems -AI06535,AI Architect,95381,USD,95381,MI,PT,Sweden,S,Sweden,50,"SQL, Scala, Data Visualization",Associate,4,Finance,2025-02-24,2025-03-14,1983,9,Neural Networks Co -AI06536,Machine Learning Researcher,190339,USD,190339,EX,PT,Norway,S,Norway,50,"Tableau, R, AWS",Bachelor,15,Transportation,2024-05-24,2024-07-12,2438,9,Smart Analytics -AI06537,AI Research Scientist,228266,GBP,171200,EX,FL,United Kingdom,M,Austria,0,"Tableau, Scala, Java, Azure",Master,15,Education,2024-04-01,2024-05-03,2081,7.6,Smart Analytics -AI06538,AI Specialist,201526,USD,201526,SE,PT,United States,L,Thailand,50,"Kubernetes, Spark, SQL, Statistics, Mathematics",Associate,5,Healthcare,2024-10-19,2024-11-21,2490,7.2,AI Innovations -AI06539,Data Engineer,165854,USD,165854,EX,FL,Denmark,S,Denmark,0,"Linux, Azure, Mathematics",PhD,18,Real Estate,2024-10-13,2024-11-22,2073,8,Advanced Robotics -AI06540,Head of AI,50399,USD,50399,MI,FT,China,M,Chile,50,"Linux, GCP, Data Visualization",Master,4,Energy,2024-03-30,2024-05-21,2432,7.6,TechCorp Inc -AI06541,Research Scientist,146895,USD,146895,SE,FL,Ireland,M,Ireland,0,"Git, PyTorch, SQL, AWS, Mathematics",PhD,5,Transportation,2024-03-03,2024-04-25,1660,6.8,Cognitive Computing -AI06542,Machine Learning Engineer,141242,USD,141242,EX,FL,Ireland,M,Ireland,0,"Hadoop, Java, PyTorch, TensorFlow",Associate,19,Finance,2025-03-30,2025-04-17,1744,7.6,Smart Analytics -AI06543,AI Research Scientist,227276,GBP,170457,EX,FT,United Kingdom,M,United Kingdom,0,"Data Visualization, Computer Vision, Statistics, Python, R",Master,19,Media,2025-01-02,2025-01-30,640,8.4,Algorithmic Solutions -AI06544,AI Software Engineer,91381,EUR,77674,MI,PT,Netherlands,S,Netherlands,50,"SQL, Computer Vision, Java, R",Master,3,Gaming,2025-03-31,2025-06-04,1247,7.4,AI Innovations -AI06545,Data Analyst,127378,USD,127378,SE,PT,Israel,M,Israel,100,"Statistics, Kubernetes, Data Visualization, Git, PyTorch",Associate,6,Retail,2024-09-28,2024-10-24,2487,8.6,Machine Intelligence Group -AI06546,Principal Data Scientist,67976,USD,67976,EN,FL,Israel,S,Hungary,0,"Python, TensorFlow, Kubernetes",PhD,1,Automotive,2024-07-09,2024-08-06,1680,6.5,Future Systems -AI06547,AI Specialist,213311,CHF,191980,SE,FT,Switzerland,M,Switzerland,100,"Linux, Azure, Kubernetes",Associate,9,Manufacturing,2025-04-15,2025-05-12,2384,8.4,DeepTech Ventures -AI06548,Machine Learning Engineer,68136,EUR,57916,EN,CT,France,S,Nigeria,100,"Kubernetes, Git, Azure, NLP, Deep Learning",Master,0,Gaming,2024-04-01,2024-06-08,976,6.7,Autonomous Tech -AI06549,Robotics Engineer,137648,USD,137648,MI,CT,Norway,L,Norway,100,"SQL, Python, GCP, NLP, Mathematics",Master,2,Finance,2025-03-22,2025-05-07,1030,6.4,Neural Networks Co -AI06550,AI Software Engineer,176624,USD,176624,EX,FT,Sweden,S,Sweden,0,"SQL, Azure, Tableau",Master,18,Transportation,2024-02-02,2024-03-19,1038,7.1,TechCorp Inc -AI06551,Robotics Engineer,117861,USD,117861,EX,FL,Finland,S,Finland,0,"Python, Scala, Java",Bachelor,19,Energy,2024-12-17,2025-01-21,823,7.2,DeepTech Ventures -AI06552,Computer Vision Engineer,95983,USD,95983,MI,FL,Israel,L,Israel,100,"PyTorch, Docker, Tableau, MLOps, Linux",Associate,3,Media,2025-04-07,2025-04-27,678,5.9,Neural Networks Co -AI06553,Head of AI,127320,EUR,108222,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Deep Learning, Computer Vision, Python, R",PhD,8,Healthcare,2024-06-22,2024-08-24,980,6.6,Neural Networks Co -AI06554,Data Analyst,156695,EUR,133191,EX,FT,Austria,M,Japan,100,"Azure, Python, Scala",Associate,17,Telecommunications,2024-09-05,2024-10-05,1229,6.2,DeepTech Ventures -AI06555,ML Ops Engineer,70934,USD,70934,EN,PT,United States,S,United States,50,"AWS, Git, TensorFlow, SQL, Mathematics",Bachelor,0,Media,2024-09-14,2024-10-07,2413,8.2,Future Systems -AI06556,Research Scientist,160766,USD,160766,EX,FL,Israel,L,Israel,50,"Python, TensorFlow, Spark, Linux",PhD,19,Transportation,2024-08-07,2024-09-27,2169,9.9,AI Innovations -AI06557,Autonomous Systems Engineer,112463,USD,112463,SE,PT,Finland,M,Finland,0,"GCP, PyTorch, MLOps",Bachelor,8,Finance,2024-03-30,2024-05-13,1069,7.4,Predictive Systems -AI06558,NLP Engineer,143144,USD,143144,SE,PT,Sweden,M,Sweden,100,"Spark, Git, Tableau",Master,6,Finance,2025-01-13,2025-02-18,892,9.5,DataVision Ltd -AI06559,Principal Data Scientist,38842,USD,38842,MI,FL,China,M,China,50,"MLOps, Python, TensorFlow, PyTorch",Associate,3,Technology,2024-07-21,2024-08-21,2083,9,Algorithmic Solutions -AI06560,Machine Learning Engineer,64116,GBP,48087,EN,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Computer Vision, Kubernetes, Docker",Master,0,Media,2024-07-09,2024-08-12,2386,5.8,Cognitive Computing -AI06561,AI Software Engineer,88010,USD,88010,MI,CT,South Korea,L,South Korea,0,"Python, TensorFlow, Hadoop",Associate,2,Consulting,2024-07-12,2024-07-27,2443,7,Smart Analytics -AI06562,Head of AI,95648,USD,95648,MI,FT,Norway,S,Norway,0,"Scala, Hadoop, Docker, Computer Vision, GCP",Master,4,Healthcare,2024-11-04,2025-01-14,2231,5.3,AI Innovations -AI06563,Deep Learning Engineer,97522,SGD,126779,EN,FT,Singapore,L,Singapore,50,"Git, Python, Statistics, TensorFlow, Mathematics",Master,1,Media,2024-10-06,2024-10-31,1772,6.6,DeepTech Ventures -AI06564,Data Analyst,31058,USD,31058,EN,CT,China,M,China,0,"Azure, R, Hadoop",Bachelor,0,Media,2024-06-07,2024-07-18,605,9.6,Advanced Robotics -AI06565,Research Scientist,278889,CHF,251000,EX,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, Kubernetes, Statistics, Docker",Associate,10,Transportation,2025-01-28,2025-03-16,724,5.2,DeepTech Ventures -AI06566,Data Scientist,83674,SGD,108776,EN,CT,Singapore,L,Singapore,100,"Kubernetes, Scala, Data Visualization, MLOps, GCP",Bachelor,0,Government,2024-11-02,2024-11-20,1581,6.9,Cloud AI Solutions -AI06567,AI Specialist,59348,JPY,6528280,EN,CT,Japan,M,Japan,0,"Hadoop, Java, Linux",Bachelor,0,Telecommunications,2024-12-27,2025-02-05,2315,7.8,Digital Transformation LLC -AI06568,Robotics Engineer,178661,CHF,160795,EX,FL,Switzerland,S,Netherlands,100,"AWS, Linux, NLP",Associate,18,Telecommunications,2024-07-11,2024-09-19,1704,7.8,Predictive Systems -AI06569,AI Specialist,150401,AUD,203041,EX,PT,Australia,M,Italy,0,"Mathematics, PyTorch, MLOps, AWS, TensorFlow",Master,13,Transportation,2024-05-10,2024-07-11,1135,6.6,Advanced Robotics -AI06570,AI Research Scientist,62718,EUR,53310,EN,FL,Austria,L,Austria,50,"MLOps, Scala, TensorFlow, SQL",Associate,1,Consulting,2025-04-12,2025-06-10,896,7,Cognitive Computing -AI06571,Deep Learning Engineer,68205,EUR,57974,EN,PT,Austria,L,Singapore,0,"Docker, GCP, SQL, Git, Statistics",Master,1,Telecommunications,2024-05-26,2024-08-01,2360,7.1,DeepTech Ventures -AI06572,Data Analyst,58067,USD,58067,EN,CT,Israel,L,Israel,50,"MLOps, R, Docker, Python, AWS",PhD,1,Retail,2024-03-26,2024-04-28,833,5.3,Cloud AI Solutions -AI06573,AI Product Manager,94059,SGD,122277,MI,CT,Singapore,S,Singapore,50,"Python, GCP, Statistics, Computer Vision, Kubernetes",Associate,4,Telecommunications,2024-06-27,2024-08-25,1033,9.2,AI Innovations -AI06574,Machine Learning Researcher,124056,USD,124056,SE,FL,Denmark,S,Denmark,100,"Python, Kubernetes, TensorFlow, Scala, Git",Master,5,Technology,2024-09-22,2024-10-06,1381,9.8,Cognitive Computing -AI06575,Principal Data Scientist,103972,USD,103972,EN,FT,Denmark,L,Denmark,100,"Kubernetes, Data Visualization, Hadoop",Associate,1,Healthcare,2024-01-03,2024-03-01,2122,8.4,Predictive Systems -AI06576,AI Research Scientist,120733,SGD,156953,SE,FL,Singapore,M,Singapore,50,"Hadoop, Git, Statistics",Bachelor,8,Automotive,2025-04-20,2025-05-10,2362,6,Advanced Robotics -AI06577,Autonomous Systems Engineer,49939,JPY,5493290,EN,PT,Japan,S,Poland,50,"Java, SQL, Tableau",Master,0,Gaming,2024-08-13,2024-10-22,1862,6.5,Predictive Systems -AI06578,Machine Learning Engineer,131946,USD,131946,EX,PT,Finland,M,Nigeria,0,"AWS, Python, GCP, Scala, Computer Vision",Master,17,Technology,2024-01-30,2024-03-10,1122,8.4,Cloud AI Solutions -AI06579,Principal Data Scientist,74473,CHF,67026,EN,CT,Switzerland,S,Russia,0,"GCP, Computer Vision, SQL, Deep Learning",PhD,1,Gaming,2024-06-19,2024-08-18,1120,6,Digital Transformation LLC -AI06580,ML Ops Engineer,42235,USD,42235,EN,FT,South Korea,M,South Korea,0,"TensorFlow, Tableau, SQL, NLP",Associate,0,Government,2024-02-10,2024-02-29,623,7.1,DeepTech Ventures -AI06581,AI Software Engineer,100391,USD,100391,EX,PT,China,S,China,100,"Python, R, Data Visualization",Master,16,Retail,2024-12-02,2025-02-05,2094,5.7,Autonomous Tech -AI06582,Data Analyst,224884,USD,224884,EX,CT,Ireland,L,Chile,50,"Linux, Python, TensorFlow",Master,17,Manufacturing,2025-03-29,2025-04-12,2203,7.8,Advanced Robotics -AI06583,AI Specialist,138421,USD,138421,SE,PT,Finland,L,Switzerland,0,"Deep Learning, Hadoop, PyTorch",Bachelor,8,Manufacturing,2024-05-10,2024-05-29,1120,8.3,Future Systems -AI06584,Data Analyst,73596,EUR,62557,MI,PT,Germany,S,Germany,50,"Scala, Kubernetes, Tableau, MLOps, GCP",Bachelor,3,Energy,2024-02-07,2024-03-02,783,6.4,Autonomous Tech -AI06585,AI Product Manager,118358,USD,118358,MI,CT,Ireland,L,Ireland,50,"Scala, Python, TensorFlow, AWS",Associate,4,Finance,2025-04-27,2025-06-29,1805,9.6,Autonomous Tech -AI06586,Autonomous Systems Engineer,60553,USD,60553,SE,CT,China,L,France,50,"Python, Data Visualization, Scala",PhD,5,Energy,2024-10-05,2024-12-01,688,6.9,Predictive Systems -AI06587,Principal Data Scientist,151705,EUR,128949,SE,FL,Netherlands,L,Kenya,0,"Deep Learning, Tableau, MLOps",Bachelor,9,Telecommunications,2024-06-10,2024-08-21,1911,9.3,Digital Transformation LLC -AI06588,AI Specialist,119879,EUR,101897,MI,FT,Germany,L,Germany,50,"Python, Java, Azure, Scala, R",Master,4,Manufacturing,2024-06-15,2024-07-29,1659,7.1,Autonomous Tech -AI06589,Head of AI,79545,EUR,67613,MI,FL,France,L,France,100,"Spark, Python, Computer Vision, Data Visualization, Docker",PhD,3,Consulting,2025-03-25,2025-05-06,2147,9.2,Quantum Computing Inc -AI06590,Data Analyst,59043,USD,59043,EN,FT,Finland,L,Ukraine,50,"Scala, Kubernetes, SQL, Linux",PhD,1,Real Estate,2024-06-01,2024-06-24,2127,7,AI Innovations -AI06591,ML Ops Engineer,103365,GBP,77524,MI,PT,United Kingdom,M,United Kingdom,50,"MLOps, Hadoop, Statistics",Master,3,Manufacturing,2024-05-12,2024-07-12,2256,9,Smart Analytics -AI06592,AI Software Engineer,94572,EUR,80386,MI,CT,Netherlands,M,Netherlands,0,"Java, SQL, Git, Hadoop",Master,3,Telecommunications,2025-03-24,2025-04-07,2391,6.5,DataVision Ltd -AI06593,AI Software Engineer,95620,CHF,86058,MI,CT,Switzerland,S,South Africa,100,"R, Tableau, Python, TensorFlow",Master,3,Energy,2024-09-08,2024-10-11,814,6.6,Quantum Computing Inc -AI06594,AI Consultant,333608,USD,333608,EX,FL,United States,L,United States,50,"Kubernetes, Java, NLP, R",Associate,13,Retail,2024-02-23,2024-03-17,677,6.6,Predictive Systems -AI06595,Data Analyst,125818,USD,125818,SE,FT,Norway,S,Norway,50,"SQL, TensorFlow, AWS, Python, Linux",Master,6,Telecommunications,2025-04-04,2025-05-14,2303,7.8,Quantum Computing Inc -AI06596,Robotics Engineer,79536,USD,79536,MI,CT,United States,S,United States,50,"Scala, Kubernetes, Deep Learning, Mathematics, Data Visualization",PhD,4,Telecommunications,2025-03-14,2025-05-18,2441,7.3,Predictive Systems -AI06597,Machine Learning Researcher,112134,USD,112134,MI,CT,Denmark,M,Denmark,0,"Scala, SQL, Mathematics, Java, Python",Associate,3,Consulting,2024-12-30,2025-02-18,1804,7.7,Cloud AI Solutions -AI06598,Robotics Engineer,286727,USD,286727,EX,FL,Ireland,L,Ireland,100,"Java, NLP, Data Visualization",PhD,11,Technology,2024-12-01,2025-01-07,2222,5.2,TechCorp Inc -AI06599,AI Product Manager,86549,EUR,73567,EN,PT,Netherlands,L,Netherlands,100,"Linux, Git, Data Visualization, Python, Computer Vision",PhD,0,Retail,2024-03-27,2024-05-18,1317,8.5,Neural Networks Co -AI06600,Computer Vision Engineer,137974,USD,137974,MI,PT,Norway,M,Norway,0,"Python, R, GCP, AWS, Kubernetes",PhD,2,Manufacturing,2024-10-15,2024-10-29,1016,5.2,Digital Transformation LLC -AI06601,Principal Data Scientist,48191,USD,48191,EN,FT,Israel,S,Israel,50,"R, Scala, TensorFlow, Git",Bachelor,0,Government,2024-03-19,2024-05-06,1811,6.9,DeepTech Ventures -AI06602,Robotics Engineer,137089,EUR,116526,EX,CT,Germany,S,Germany,50,"Java, PyTorch, Hadoop",Master,10,Manufacturing,2025-02-05,2025-04-07,523,9.5,Predictive Systems -AI06603,ML Ops Engineer,146050,JPY,16065500,EX,CT,Japan,S,Japan,50,"SQL, Hadoop, Statistics, PyTorch",Master,16,Gaming,2025-02-10,2025-04-20,1060,8.9,Future Systems -AI06604,Machine Learning Researcher,83076,EUR,70615,EN,CT,Austria,L,Ukraine,0,"Hadoop, Python, GCP",Associate,0,Government,2024-05-17,2024-06-23,1739,9.8,Neural Networks Co -AI06605,Data Scientist,184817,SGD,240262,EX,CT,Singapore,S,Singapore,0,"Python, Scala, Hadoop",Associate,11,Energy,2024-08-24,2024-10-13,1726,7.4,DataVision Ltd -AI06606,Head of AI,76584,EUR,65096,MI,CT,Austria,M,Poland,50,"Kubernetes, Statistics, AWS",Associate,4,Manufacturing,2025-02-04,2025-04-02,1410,5.8,Autonomous Tech -AI06607,NLP Engineer,79065,USD,79065,EN,PT,Sweden,L,Sweden,100,"Python, Scala, Linux",Associate,0,Finance,2024-07-23,2024-09-30,2099,9.3,Future Systems -AI06608,Data Scientist,118313,EUR,100566,MI,PT,France,L,France,100,"Mathematics, SQL, Python",Bachelor,3,Healthcare,2024-11-06,2024-12-21,554,5,DataVision Ltd -AI06609,Data Scientist,177046,USD,177046,EX,FT,Israel,M,Israel,100,"Git, Tableau, Linux, Python",Bachelor,17,Energy,2024-10-10,2024-11-12,2366,5.8,Future Systems -AI06610,Machine Learning Researcher,38680,USD,38680,MI,FL,China,S,China,100,"MLOps, PyTorch, GCP",Associate,2,Real Estate,2024-10-12,2024-12-05,2445,5.7,Machine Intelligence Group -AI06611,AI Architect,161186,EUR,137008,SE,FL,Netherlands,M,Sweden,100,"Python, TensorFlow, NLP, Deep Learning, Statistics",Associate,7,Healthcare,2024-09-22,2024-11-01,1454,8.9,Predictive Systems -AI06612,Data Scientist,121651,EUR,103403,SE,FL,Netherlands,M,Netherlands,100,"Hadoop, GCP, Tableau, Docker, PyTorch",Bachelor,9,Transportation,2024-07-09,2024-07-29,1405,6.6,Autonomous Tech -AI06613,Autonomous Systems Engineer,134960,JPY,14845600,SE,PT,Japan,S,Japan,50,"Java, Tableau, Azure",PhD,6,Energy,2024-06-22,2024-07-27,657,6.7,Advanced Robotics -AI06614,AI Research Scientist,52748,USD,52748,EN,CT,Israel,M,Israel,0,"SQL, Kubernetes, Python, AWS",Master,1,Manufacturing,2025-03-02,2025-05-08,1280,9.5,Cognitive Computing -AI06615,AI Software Engineer,77009,CAD,96261,MI,PT,Canada,M,Canada,100,"Deep Learning, Kubernetes, Mathematics",Bachelor,2,Media,2024-03-01,2024-04-06,2072,9,Smart Analytics -AI06616,Data Analyst,101929,SGD,132508,SE,FT,Singapore,S,Luxembourg,50,"MLOps, Java, Data Visualization",Master,5,Manufacturing,2024-02-22,2024-03-22,1996,9.2,Smart Analytics -AI06617,AI Software Engineer,118002,EUR,100302,SE,PT,France,L,Czech Republic,0,"Kubernetes, GCP, Azure, Java, R",Master,6,Real Estate,2024-09-19,2024-11-13,1549,9.7,Advanced Robotics -AI06618,Machine Learning Engineer,138903,SGD,180574,EX,PT,Singapore,S,Singapore,100,"Tableau, Java, Deep Learning",Associate,11,Energy,2024-03-13,2024-04-22,2245,9.3,DataVision Ltd -AI06619,AI Architect,279851,JPY,30783610,EX,PT,Japan,L,Japan,50,"Spark, SQL, Linux",Associate,10,Automotive,2024-02-01,2024-03-05,2260,8.4,AI Innovations -AI06620,Principal Data Scientist,168724,EUR,143415,EX,PT,Austria,L,Austria,0,"TensorFlow, Tableau, R, Java, Linux",PhD,18,Real Estate,2024-09-15,2024-11-07,942,7,DeepTech Ventures -AI06621,AI Software Engineer,305904,SGD,397675,EX,PT,Singapore,L,Australia,100,"Scala, Data Visualization, R",Master,10,Gaming,2024-01-15,2024-03-27,1819,8.8,Neural Networks Co -AI06622,Robotics Engineer,27196,USD,27196,EN,FT,China,M,China,100,"Linux, NLP, Tableau, Spark",Associate,1,Telecommunications,2025-04-22,2025-05-08,503,8.7,AI Innovations -AI06623,Machine Learning Engineer,108913,USD,108913,SE,CT,South Korea,M,Portugal,100,"GCP, Scala, Statistics, Python",Bachelor,5,Real Estate,2024-03-24,2024-04-24,1058,6.2,Autonomous Tech -AI06624,Computer Vision Engineer,133154,CAD,166443,EX,PT,Canada,M,Estonia,50,"Hadoop, Scala, PyTorch",Associate,10,Media,2024-12-19,2025-01-20,968,5.7,Autonomous Tech -AI06625,AI Research Scientist,253346,SGD,329350,EX,PT,Singapore,L,Estonia,50,"Spark, PyTorch, Kubernetes, Hadoop",Master,17,Gaming,2025-02-10,2025-04-16,1851,10,Cognitive Computing -AI06626,Autonomous Systems Engineer,257998,JPY,28379780,EX,CT,Japan,M,Nigeria,100,"MLOps, Mathematics, AWS, NLP, Linux",PhD,18,Manufacturing,2024-12-22,2025-02-23,1851,6.8,Predictive Systems -AI06627,AI Research Scientist,118724,USD,118724,SE,FL,South Korea,M,South Korea,0,"Hadoop, Docker, Mathematics, Computer Vision, Scala",Bachelor,6,Finance,2025-03-10,2025-03-25,1941,8,Cognitive Computing -AI06628,Data Scientist,88590,GBP,66443,EN,PT,United Kingdom,L,United Kingdom,100,"Data Visualization, Docker, Linux",PhD,0,Transportation,2024-08-13,2024-10-16,881,8.5,AI Innovations -AI06629,Data Scientist,45950,EUR,39058,EN,FT,Germany,S,Germany,100,"Linux, Java, Python, TensorFlow",Master,0,Manufacturing,2024-08-28,2024-11-04,1012,9.8,Autonomous Tech -AI06630,AI Consultant,202145,SGD,262789,EX,CT,Singapore,M,Singapore,50,"Spark, Python, Tableau, Git, TensorFlow",Associate,18,Retail,2025-03-04,2025-04-04,1103,9.7,Machine Intelligence Group -AI06631,ML Ops Engineer,354485,CHF,319037,EX,FL,Switzerland,M,Finland,50,"MLOps, Docker, AWS, SQL",Associate,12,Finance,2024-04-11,2024-05-15,1424,5.4,Quantum Computing Inc -AI06632,AI Architect,145381,EUR,123574,SE,FT,Netherlands,M,Netherlands,100,"TensorFlow, Python, Computer Vision, PyTorch, Git",Bachelor,6,Technology,2024-07-30,2024-09-08,2076,6.1,DeepTech Ventures -AI06633,AI Research Scientist,80273,USD,80273,SE,CT,China,L,China,50,"Azure, NLP, Scala",Associate,7,Energy,2024-09-12,2024-10-21,1925,8.7,Algorithmic Solutions -AI06634,Computer Vision Engineer,93627,CAD,117034,MI,CT,Canada,L,Netherlands,50,"Linux, Docker, Data Visualization",PhD,2,Retail,2024-03-21,2024-05-31,2091,8.7,DeepTech Ventures -AI06635,Machine Learning Researcher,101958,EUR,86664,MI,PT,Germany,L,Germany,50,"SQL, Docker, Java, NLP",Associate,4,Real Estate,2024-02-22,2024-03-17,1416,7.1,Smart Analytics -AI06636,Machine Learning Engineer,310491,EUR,263917,EX,PT,Netherlands,L,Netherlands,50,"SQL, Hadoop, PyTorch",Associate,14,Education,2024-05-13,2024-06-25,2239,7.4,Cloud AI Solutions -AI06637,Machine Learning Researcher,92455,GBP,69341,EN,PT,United Kingdom,L,Colombia,50,"Scala, Linux, Statistics, Java, Docker",Associate,1,Manufacturing,2025-04-09,2025-04-26,1369,7.4,Future Systems -AI06638,Data Engineer,106939,USD,106939,EX,PT,China,M,China,50,"Hadoop, Computer Vision, PyTorch, Data Visualization, R",Master,11,Manufacturing,2024-09-14,2024-11-18,1333,9.9,Digital Transformation LLC -AI06639,AI Product Manager,194351,EUR,165198,EX,FT,Austria,M,Austria,100,"GCP, Azure, SQL, TensorFlow, Statistics",Bachelor,16,Automotive,2025-01-03,2025-03-07,1968,7.8,Future Systems -AI06640,Machine Learning Engineer,110209,USD,110209,EX,PT,China,L,China,100,"R, Scala, Python",Associate,15,Education,2025-03-25,2025-06-01,951,9.1,Future Systems -AI06641,Data Engineer,274986,USD,274986,EX,FT,Finland,L,Finland,50,"Scala, Deep Learning, MLOps",Associate,10,Media,2024-01-31,2024-02-23,1539,6.5,Digital Transformation LLC -AI06642,Deep Learning Engineer,292272,AUD,394567,EX,CT,Australia,L,Luxembourg,0,"Computer Vision, GCP, Azure",Associate,17,Technology,2025-02-23,2025-04-11,1628,7.1,Machine Intelligence Group -AI06643,AI Specialist,70159,USD,70159,EN,PT,Finland,M,Finland,0,"Kubernetes, Spark, Python",PhD,1,Education,2024-03-27,2024-05-05,1064,8.9,Advanced Robotics -AI06644,NLP Engineer,57113,USD,57113,EN,PT,Ireland,M,Hungary,0,"Java, Tableau, Scala",Associate,0,Finance,2024-12-15,2025-02-08,1510,8.6,Cognitive Computing -AI06645,Machine Learning Engineer,67207,USD,67207,EN,CT,Israel,L,Israel,0,"Azure, Data Visualization, Git, Java, R",Associate,1,Automotive,2024-03-02,2024-04-27,1753,5.3,Neural Networks Co -AI06646,AI Product Manager,62513,USD,62513,EN,FT,Israel,M,Israel,50,"Java, MLOps, Azure",PhD,0,Education,2025-04-28,2025-05-15,935,7.3,Predictive Systems -AI06647,AI Software Engineer,120652,USD,120652,MI,PT,Norway,L,Ireland,50,"Kubernetes, Azure, Deep Learning, PyTorch, R",Associate,3,Media,2024-09-07,2024-11-15,2101,8.4,Machine Intelligence Group -AI06648,AI Research Scientist,28595,USD,28595,EN,CT,India,L,India,50,"SQL, Data Visualization, Kubernetes, Spark",Master,1,Gaming,2024-02-20,2024-03-21,588,8.7,Algorithmic Solutions -AI06649,Autonomous Systems Engineer,32487,USD,32487,MI,FT,India,L,India,50,"Spark, Azure, Statistics, Docker",Associate,2,Gaming,2024-07-11,2024-08-26,2166,6.5,TechCorp Inc -AI06650,ML Ops Engineer,124352,SGD,161658,MI,FT,Singapore,L,South Africa,100,"Python, Git, Tableau, TensorFlow, Deep Learning",Associate,2,Education,2024-03-11,2024-04-11,1805,6.1,Autonomous Tech -AI06651,Research Scientist,106533,USD,106533,MI,FT,Ireland,M,Czech Republic,0,"Hadoop, SQL, AWS, MLOps",Associate,2,Telecommunications,2024-01-20,2024-03-12,870,8.6,Advanced Robotics -AI06652,Robotics Engineer,207708,EUR,176552,EX,PT,Austria,L,Austria,50,"Tableau, GCP, AWS, MLOps, Data Visualization",Bachelor,15,Healthcare,2024-04-09,2024-05-01,2248,6.6,Autonomous Tech -AI06653,Machine Learning Engineer,66074,EUR,56163,EN,FL,Netherlands,L,Netherlands,100,"Docker, Git, Statistics, Python",PhD,0,Retail,2024-01-16,2024-01-30,2044,7.4,Quantum Computing Inc -AI06654,Head of AI,73696,USD,73696,EN,FT,Ireland,M,Ireland,0,"Java, GCP, Azure",PhD,0,Retail,2025-01-20,2025-02-25,1925,6.8,Advanced Robotics -AI06655,AI Product Manager,88897,GBP,66673,EN,PT,United Kingdom,L,United Kingdom,100,"Linux, Statistics, GCP, PyTorch",Master,1,Gaming,2025-03-06,2025-03-25,1828,7.3,Machine Intelligence Group -AI06656,AI Specialist,155437,USD,155437,EX,FL,Finland,M,Turkey,50,"Python, Azure, Git, GCP",Associate,15,Manufacturing,2024-05-22,2024-06-16,1408,8.5,Smart Analytics -AI06657,AI Software Engineer,64451,USD,64451,MI,PT,Finland,S,Finland,100,"Azure, PyTorch, Mathematics, GCP, TensorFlow",Bachelor,3,Real Estate,2024-09-05,2024-10-05,843,7.6,Autonomous Tech -AI06658,AI Specialist,105020,USD,105020,SE,PT,South Korea,M,South Korea,100,"Tableau, NLP, Scala",Bachelor,7,Finance,2024-04-28,2024-07-01,2434,5.1,Advanced Robotics -AI06659,AI Architect,116832,USD,116832,SE,FL,Finland,S,Finland,100,"Statistics, GCP, Azure, Hadoop, Mathematics",Master,9,Healthcare,2024-11-21,2024-12-27,885,8.7,Machine Intelligence Group -AI06660,AI Research Scientist,59624,USD,59624,SE,PT,India,L,Chile,0,"PyTorch, Docker, AWS, Tableau",Associate,9,Real Estate,2024-12-26,2025-02-08,597,5.3,DataVision Ltd -AI06661,Machine Learning Researcher,200837,EUR,170711,EX,CT,Germany,S,Vietnam,0,"Kubernetes, Azure, Computer Vision",Master,19,Telecommunications,2024-04-17,2024-05-17,629,9.9,TechCorp Inc -AI06662,Data Analyst,353742,USD,353742,EX,CT,Denmark,L,Denmark,100,"Data Visualization, Azure, Tableau",Associate,16,Consulting,2024-04-07,2024-05-22,1671,7.4,AI Innovations -AI06663,Machine Learning Researcher,118225,GBP,88669,SE,PT,United Kingdom,M,Singapore,0,"Git, Spark, AWS",Master,9,Transportation,2025-03-26,2025-05-25,2351,8.5,AI Innovations -AI06664,ML Ops Engineer,47080,USD,47080,MI,FL,China,M,China,100,"Spark, SQL, R, Docker",Bachelor,4,Media,2024-02-20,2024-03-09,2184,6.6,TechCorp Inc -AI06665,AI Specialist,51135,USD,51135,SE,CT,India,L,Czech Republic,0,"Data Visualization, Scala, PyTorch, Git",Associate,7,Retail,2024-12-23,2025-01-12,1475,8.4,Predictive Systems -AI06666,AI Research Scientist,155505,USD,155505,SE,CT,Israel,L,Israel,50,"R, Hadoop, SQL",PhD,6,Real Estate,2025-03-16,2025-04-30,2108,6.8,Future Systems -AI06667,Robotics Engineer,69674,JPY,7664140,MI,CT,Japan,S,Japan,100,"MLOps, AWS, Java",Bachelor,2,Consulting,2024-09-15,2024-10-05,2064,7,AI Innovations -AI06668,Computer Vision Engineer,124927,JPY,13741970,SE,CT,Japan,L,Brazil,0,"Python, Linux, Computer Vision",PhD,5,Manufacturing,2024-04-02,2024-04-17,1126,7.8,DataVision Ltd -AI06669,AI Architect,112130,USD,112130,MI,PT,United States,L,United States,50,"Statistics, AWS, Azure, MLOps, Java",Bachelor,3,Gaming,2024-06-01,2024-08-01,2120,9,Cognitive Computing -AI06670,AI Software Engineer,104109,USD,104109,EX,CT,China,L,China,100,"Kubernetes, Spark, Data Visualization, Docker",PhD,13,Technology,2025-01-28,2025-03-18,759,6.5,Algorithmic Solutions -AI06671,AI Architect,47100,EUR,40035,EN,FT,Austria,S,New Zealand,0,"Kubernetes, Deep Learning, Computer Vision",Master,0,Media,2025-04-01,2025-04-25,2189,8.6,DataVision Ltd -AI06672,Research Scientist,176096,USD,176096,EX,CT,Sweden,L,Sweden,0,"Python, TensorFlow, PyTorch, NLP, Spark",Bachelor,10,Education,2024-08-13,2024-10-08,2428,9.4,DeepTech Ventures -AI06673,Robotics Engineer,52718,EUR,44810,EN,CT,France,S,France,0,"R, Kubernetes, Spark, SQL",Associate,1,Manufacturing,2025-02-23,2025-03-28,1176,6.6,Cloud AI Solutions -AI06674,Deep Learning Engineer,103610,USD,103610,EN,FT,Norway,L,Norway,100,"Kubernetes, Scala, NLP, PyTorch",Associate,1,Consulting,2025-02-19,2025-03-11,1742,9.3,Autonomous Tech -AI06675,Robotics Engineer,121009,USD,121009,MI,FT,Denmark,L,Denmark,0,"MLOps, Spark, Computer Vision, Linux, AWS",Master,2,Telecommunications,2025-02-04,2025-04-18,2066,8.3,Machine Intelligence Group -AI06676,Research Scientist,41556,USD,41556,MI,FT,India,L,India,50,"Python, PyTorch, Git, Java, Mathematics",Bachelor,4,Manufacturing,2025-01-28,2025-03-30,1688,8.6,Future Systems -AI06677,AI Consultant,185304,GBP,138978,EX,FT,United Kingdom,L,Czech Republic,0,"SQL, Hadoop, MLOps",PhD,16,Automotive,2024-10-23,2024-12-27,1002,6.6,Autonomous Tech -AI06678,Data Engineer,53652,USD,53652,EN,CT,Israel,S,Israel,0,"Azure, TensorFlow, SQL, Java",Bachelor,0,Finance,2024-01-10,2024-03-06,1224,5.8,Machine Intelligence Group -AI06679,ML Ops Engineer,92383,USD,92383,EN,FT,Denmark,L,Denmark,0,"AWS, PyTorch, GCP, Statistics",Master,1,Automotive,2024-06-10,2024-07-11,1190,5.7,Future Systems -AI06680,Robotics Engineer,63352,EUR,53849,EN,FT,Austria,S,Brazil,0,"Tableau, Data Visualization, Docker",Bachelor,1,Real Estate,2024-12-21,2025-02-08,1985,9.5,Quantum Computing Inc -AI06681,Data Analyst,177446,EUR,150829,EX,PT,Netherlands,L,China,50,"SQL, Tableau, Mathematics, MLOps, R",Associate,14,Education,2024-08-22,2024-10-24,1232,5.4,Predictive Systems -AI06682,NLP Engineer,141780,USD,141780,SE,PT,Finland,M,Finland,50,"Python, TensorFlow, Hadoop, Computer Vision",Associate,8,Automotive,2024-09-11,2024-11-06,1148,5.2,DeepTech Ventures -AI06683,Data Scientist,106379,USD,106379,EX,CT,South Korea,S,South Korea,0,"Hadoop, Docker, NLP, MLOps",Master,19,Technology,2024-01-12,2024-03-23,1018,6,Advanced Robotics -AI06684,AI Architect,126231,EUR,107296,MI,PT,Netherlands,L,Netherlands,0,"Git, Deep Learning, Docker",Bachelor,2,Consulting,2024-06-18,2024-07-25,2285,7.4,Cloud AI Solutions -AI06685,NLP Engineer,98327,CHF,88494,EN,CT,Switzerland,M,Switzerland,0,"PyTorch, Linux, Mathematics, Data Visualization, Hadoop",Associate,0,Consulting,2024-07-13,2024-08-13,641,5.1,Machine Intelligence Group -AI06686,Robotics Engineer,48433,EUR,41168,EN,PT,France,S,France,0,"PyTorch, Mathematics, Spark, Data Visualization, Kubernetes",PhD,0,Education,2025-03-11,2025-04-01,995,5.1,Algorithmic Solutions -AI06687,NLP Engineer,98587,USD,98587,MI,FT,Sweden,M,Latvia,0,"PyTorch, Kubernetes, Java, TensorFlow, Mathematics",Associate,2,Telecommunications,2024-04-29,2024-07-10,1796,6.9,Quantum Computing Inc -AI06688,AI Consultant,126335,SGD,164236,MI,FL,Singapore,L,Estonia,100,"Kubernetes, GCP, MLOps",Master,4,Gaming,2024-05-02,2024-06-15,1252,5.6,Machine Intelligence Group -AI06689,Principal Data Scientist,155034,USD,155034,SE,FT,Sweden,L,Belgium,100,"AWS, Git, SQL, Scala",Associate,6,Automotive,2025-02-09,2025-03-07,1045,5.5,Autonomous Tech -AI06690,Machine Learning Researcher,68806,USD,68806,EN,FT,Denmark,S,Denmark,50,"Linux, Git, MLOps, R, NLP",PhD,0,Education,2024-01-10,2024-02-24,1873,8.9,Advanced Robotics -AI06691,Robotics Engineer,161126,EUR,136957,EX,FT,Germany,L,Australia,0,"R, AWS, SQL, Git",PhD,16,Manufacturing,2025-02-12,2025-04-01,1563,9.9,Cognitive Computing -AI06692,Principal Data Scientist,61977,USD,61977,EN,PT,South Korea,M,Netherlands,0,"Scala, Tableau, R, MLOps, Java",Master,1,Gaming,2025-02-03,2025-04-12,535,8.1,Cloud AI Solutions -AI06693,Robotics Engineer,92188,AUD,124454,SE,FT,Australia,S,Australia,100,"NLP, Docker, Scala, Azure",PhD,9,Real Estate,2025-04-28,2025-05-24,2170,5.3,Machine Intelligence Group -AI06694,Data Analyst,34860,USD,34860,SE,FT,India,S,Italy,100,"NLP, PyTorch, Kubernetes",Associate,7,Government,2025-03-11,2025-05-02,2487,7.3,Machine Intelligence Group -AI06695,Data Scientist,65877,USD,65877,EN,FT,Finland,M,Finland,0,"Computer Vision, Statistics, Linux, Git, Data Visualization",Bachelor,0,Government,2024-03-28,2024-05-23,1899,7.2,Future Systems -AI06696,Data Analyst,126854,AUD,171253,SE,CT,Australia,S,Australia,100,"TensorFlow, PyTorch, Statistics",Master,9,Retail,2024-09-02,2024-10-15,1528,6.9,Algorithmic Solutions -AI06697,Machine Learning Researcher,242745,USD,242745,EX,FT,Israel,L,Israel,0,"GCP, Python, NLP, SQL",Master,18,Media,2024-03-20,2024-04-14,1897,5.4,Autonomous Tech -AI06698,Research Scientist,91867,USD,91867,EX,CT,China,L,Ireland,0,"Kubernetes, Git, Linux, Computer Vision, Azure",Master,17,Media,2024-03-21,2024-05-10,1486,8.7,Quantum Computing Inc -AI06699,Computer Vision Engineer,134543,USD,134543,EX,PT,Israel,S,Israel,50,"SQL, Hadoop, Tableau, Deep Learning",Master,14,Education,2024-05-14,2024-07-20,2330,8.2,Smart Analytics -AI06700,AI Product Manager,193446,USD,193446,EX,PT,Sweden,S,Sweden,100,"Git, Python, Deep Learning, Mathematics",Master,13,Government,2024-04-09,2024-06-06,1027,6.2,AI Innovations -AI06701,Machine Learning Engineer,60381,USD,60381,SE,CT,China,S,China,100,"SQL, Docker, Statistics, Tableau",Master,5,Technology,2024-06-10,2024-07-10,2340,9,DataVision Ltd -AI06702,Data Engineer,163915,AUD,221285,SE,CT,Australia,L,Australia,50,"Scala, Azure, Tableau, Python",PhD,8,Real Estate,2024-09-18,2024-11-20,1260,9.1,Advanced Robotics -AI06703,AI Research Scientist,68470,EUR,58200,MI,FT,France,S,France,100,"Kubernetes, Git, Mathematics, PyTorch",PhD,4,Media,2024-03-20,2024-05-22,2278,7,Neural Networks Co -AI06704,AI Product Manager,161796,USD,161796,EX,FL,Norway,S,Switzerland,0,"Docker, PyTorch, Git, Deep Learning",Bachelor,13,Energy,2024-10-01,2024-11-28,529,5.1,Quantum Computing Inc -AI06705,Data Engineer,179771,USD,179771,EX,FL,Sweden,S,South Korea,0,"SQL, Hadoop, PyTorch",Master,12,Healthcare,2024-04-03,2024-05-12,508,7.4,Autonomous Tech -AI06706,AI Software Engineer,93524,USD,93524,EN,FT,Norway,M,Norway,100,"Computer Vision, Docker, Git, Spark",Bachelor,0,Retail,2024-03-09,2024-04-23,1533,7.2,DeepTech Ventures -AI06707,AI Architect,165207,USD,165207,SE,FL,Denmark,S,Germany,100,"Java, Kubernetes, Tableau, Scala, Computer Vision",Master,5,Automotive,2025-03-10,2025-04-07,946,6.8,TechCorp Inc -AI06708,Data Analyst,63790,GBP,47843,EN,PT,United Kingdom,M,United Kingdom,50,"Java, SQL, GCP, Docker",Associate,1,Government,2025-02-06,2025-03-28,644,8.1,Autonomous Tech -AI06709,Autonomous Systems Engineer,166660,USD,166660,EX,CT,Finland,S,Finland,50,"MLOps, Deep Learning, Linux",PhD,11,Government,2025-01-14,2025-02-21,715,9.7,Digital Transformation LLC -AI06710,AI Product Manager,65921,USD,65921,MI,PT,Finland,S,Finland,0,"AWS, Python, Deep Learning, Computer Vision, TensorFlow",Master,4,Retail,2025-01-22,2025-03-19,905,6.7,DataVision Ltd -AI06711,AI Product Manager,126851,EUR,107823,SE,FL,Austria,L,Austria,100,"Mathematics, Computer Vision, PyTorch",PhD,7,Consulting,2024-10-12,2024-11-06,2223,9.8,Neural Networks Co -AI06712,Machine Learning Researcher,90333,USD,90333,SE,FT,Israel,S,Nigeria,100,"SQL, Spark, Deep Learning, Computer Vision",Master,9,Real Estate,2024-10-07,2024-11-05,2265,8.1,Digital Transformation LLC -AI06713,AI Consultant,70882,CAD,88603,EN,FL,Canada,M,Canada,0,"Computer Vision, Scala, SQL, Azure",PhD,1,Media,2024-12-04,2025-02-09,598,7.2,DataVision Ltd -AI06714,AI Specialist,196013,EUR,166611,EX,FL,Austria,M,Austria,100,"PyTorch, Python, Computer Vision",Associate,13,Government,2024-06-22,2024-08-09,1413,8.6,TechCorp Inc -AI06715,AI Software Engineer,81980,EUR,69683,EN,FL,Austria,L,Chile,50,"Kubernetes, Data Visualization, Scala, MLOps, Docker",PhD,1,Media,2024-11-27,2024-12-14,1918,8.3,Cognitive Computing -AI06716,Data Engineer,58677,EUR,49875,EN,PT,Germany,S,Germany,100,"Hadoop, SQL, TensorFlow, Python, Tableau",Associate,1,Telecommunications,2024-07-11,2024-09-09,2173,9.9,AI Innovations -AI06717,Head of AI,73309,EUR,62313,EN,CT,France,M,France,100,"Docker, Computer Vision, MLOps, Python",Associate,0,Telecommunications,2024-02-18,2024-04-13,1884,6.2,Algorithmic Solutions -AI06718,Deep Learning Engineer,201876,CHF,181688,SE,FT,Switzerland,M,Switzerland,0,"SQL, Hadoop, Python, Computer Vision, Statistics",PhD,7,Media,2025-02-08,2025-04-19,2072,9.8,Algorithmic Solutions -AI06719,Computer Vision Engineer,65018,USD,65018,EN,CT,Ireland,S,Ireland,100,"Python, Java, Spark, Linux, Hadoop",Associate,0,Consulting,2024-10-22,2024-11-15,2365,9,DeepTech Ventures -AI06720,Robotics Engineer,161696,GBP,121272,SE,FT,United Kingdom,L,United Kingdom,50,"Hadoop, SQL, Linux, Java, AWS",Master,6,Manufacturing,2024-05-14,2024-06-09,1123,5.1,Cognitive Computing -AI06721,Head of AI,59865,USD,59865,SE,CT,China,S,China,0,"SQL, Python, Docker, TensorFlow, Statistics",Bachelor,7,Healthcare,2024-11-20,2025-01-26,1696,7,Advanced Robotics -AI06722,Principal Data Scientist,73349,GBP,55012,MI,PT,United Kingdom,S,United Kingdom,50,"Statistics, Python, TensorFlow",Master,3,Retail,2024-10-20,2024-12-16,1212,9.7,Predictive Systems -AI06723,AI Consultant,62324,CAD,77905,EN,FL,Canada,S,Canada,100,"Mathematics, SQL, Azure, PyTorch, Scala",PhD,1,Energy,2024-01-27,2024-02-20,1034,7.5,Autonomous Tech -AI06724,AI Software Engineer,125505,USD,125505,MI,FL,Denmark,M,Denmark,50,"PyTorch, Scala, AWS",Bachelor,2,Government,2024-09-21,2024-11-10,1131,7.5,Quantum Computing Inc -AI06725,Data Scientist,124940,USD,124940,MI,CT,Ireland,L,Ireland,100,"Computer Vision, Kubernetes, NLP, Hadoop, Mathematics",Associate,4,Technology,2025-04-06,2025-05-29,1172,8.8,Autonomous Tech -AI06726,Machine Learning Engineer,62978,EUR,53531,EN,CT,Germany,S,Germany,100,"Statistics, Linux, Computer Vision, Deep Learning",PhD,1,Energy,2024-10-20,2024-12-18,889,8.9,Autonomous Tech -AI06727,Head of AI,146869,CAD,183586,EX,FL,Canada,S,Indonesia,50,"Tableau, Scala, Kubernetes, Data Visualization",Master,18,Healthcare,2024-05-12,2024-07-14,595,6.9,Quantum Computing Inc -AI06728,Robotics Engineer,216474,AUD,292240,EX,FT,Australia,M,India,100,"AWS, Kubernetes, Hadoop, Tableau",Bachelor,10,Media,2024-08-23,2024-09-11,1460,7.9,Cognitive Computing -AI06729,Machine Learning Researcher,91542,GBP,68657,MI,FL,United Kingdom,S,Ukraine,50,"TensorFlow, Statistics, Mathematics",PhD,3,Consulting,2024-08-17,2024-09-05,2001,6.9,Quantum Computing Inc -AI06730,Research Scientist,104890,CAD,131113,MI,FL,Canada,L,Canada,0,"Scala, Kubernetes, MLOps, Computer Vision, Git",Associate,4,Automotive,2024-04-29,2024-07-08,1658,5.3,DataVision Ltd -AI06731,AI Product Manager,74588,EUR,63400,MI,FL,France,S,France,100,"Scala, Linux, Git, TensorFlow, Deep Learning",Bachelor,4,Finance,2024-09-16,2024-11-04,1680,5.4,Future Systems -AI06732,Data Scientist,142343,EUR,120992,EX,PT,Germany,S,Germany,50,"Hadoop, Spark, MLOps",PhD,19,Media,2024-08-21,2024-09-18,1251,9.5,Digital Transformation LLC -AI06733,Deep Learning Engineer,161000,GBP,120750,EX,CT,United Kingdom,S,United Kingdom,50,"Git, Statistics, SQL, Deep Learning",Bachelor,13,Government,2024-09-08,2024-10-13,1604,8,DeepTech Ventures -AI06734,Autonomous Systems Engineer,214330,AUD,289346,EX,FT,Australia,S,Spain,50,"Python, TensorFlow, SQL",Bachelor,16,Education,2024-04-04,2024-05-09,2467,6.7,Cloud AI Solutions -AI06735,Deep Learning Engineer,103678,EUR,88126,SE,CT,France,M,Denmark,100,"Python, Git, TensorFlow, SQL, MLOps",Bachelor,9,Energy,2024-06-25,2024-09-02,514,5.5,Predictive Systems -AI06736,Principal Data Scientist,54303,USD,54303,EN,FL,South Korea,M,Israel,100,"PyTorch, Data Visualization, Tableau, Deep Learning, Scala",PhD,0,Retail,2024-01-24,2024-03-27,1109,6.8,Advanced Robotics -AI06737,NLP Engineer,56474,USD,56474,EN,CT,Sweden,M,Sweden,50,"PyTorch, Kubernetes, Hadoop, Mathematics, SQL",Associate,0,Technology,2024-05-23,2024-08-02,1477,6,Neural Networks Co -AI06738,NLP Engineer,300349,GBP,225262,EX,PT,United Kingdom,L,United Kingdom,0,"Java, Data Visualization, Hadoop, Python",Bachelor,18,Media,2024-05-22,2024-07-11,827,7.5,Cloud AI Solutions -AI06739,AI Consultant,44528,EUR,37849,EN,FT,France,S,France,100,"R, MLOps, Data Visualization, Kubernetes",Master,1,Finance,2024-04-01,2024-05-07,1942,5.5,DeepTech Ventures -AI06740,Machine Learning Researcher,118343,USD,118343,SE,FT,Israel,M,Israel,100,"Mathematics, MLOps, Data Visualization",PhD,6,Healthcare,2024-07-30,2024-09-03,1236,8.3,Advanced Robotics -AI06741,AI Architect,125950,USD,125950,MI,FT,Denmark,L,Poland,50,"SQL, AWS, NLP",Bachelor,4,Technology,2025-01-30,2025-03-01,1563,6,Neural Networks Co -AI06742,AI Research Scientist,61502,USD,61502,EN,CT,Israel,M,Austria,50,"R, Python, Java, GCP",Master,1,Media,2025-01-01,2025-01-28,2019,9.1,Quantum Computing Inc -AI06743,Head of AI,44859,EUR,38130,EN,CT,France,S,France,0,"Azure, Tableau, GCP",PhD,1,Healthcare,2024-11-21,2024-12-31,1364,5.3,Advanced Robotics -AI06744,Autonomous Systems Engineer,119175,JPY,13109250,MI,CT,Japan,L,Japan,100,"Kubernetes, Python, MLOps",Bachelor,4,Automotive,2025-04-21,2025-06-27,1528,6.9,Algorithmic Solutions -AI06745,Research Scientist,90723,USD,90723,MI,PT,United States,M,United States,0,"Hadoop, Mathematics, Tableau",Master,3,Government,2024-07-23,2024-10-01,1136,5.5,Quantum Computing Inc -AI06746,Robotics Engineer,239693,EUR,203739,EX,CT,France,L,China,100,"AWS, Scala, Statistics, Spark",PhD,11,Healthcare,2025-02-06,2025-03-01,2160,5.9,DeepTech Ventures -AI06747,Autonomous Systems Engineer,89947,CHF,80952,EN,FT,Switzerland,L,Australia,0,"AWS, Python, MLOps",Bachelor,0,Energy,2024-03-01,2024-05-02,1832,5.7,DataVision Ltd -AI06748,AI Architect,78388,USD,78388,MI,CT,Finland,S,Finland,50,"MLOps, Tableau, Python",Associate,3,Consulting,2024-08-23,2024-10-11,1416,9,TechCorp Inc -AI06749,Deep Learning Engineer,205050,USD,205050,SE,FL,United States,L,United States,100,"Kubernetes, Deep Learning, PyTorch, TensorFlow, SQL",Bachelor,7,Retail,2024-02-28,2024-04-22,2190,5.3,Autonomous Tech -AI06750,Data Scientist,91998,EUR,78198,MI,FL,Netherlands,M,Netherlands,0,"Data Visualization, Python, GCP",PhD,4,Education,2024-03-25,2024-05-20,1349,5.6,Cloud AI Solutions -AI06751,Data Engineer,226755,USD,226755,EX,PT,Finland,L,Finland,0,"Git, PyTorch, SQL, TensorFlow",Master,13,Gaming,2024-12-27,2025-02-28,564,6.4,Algorithmic Solutions -AI06752,NLP Engineer,123422,USD,123422,MI,FT,Denmark,S,Denmark,100,"Python, AWS, TensorFlow, Data Visualization, GCP",Associate,4,Telecommunications,2024-11-16,2024-12-12,2296,6.2,Cloud AI Solutions -AI06753,Data Engineer,206557,USD,206557,SE,FT,Norway,L,Norway,0,"PyTorch, Kubernetes, AWS, Azure, Computer Vision",PhD,9,Automotive,2025-02-18,2025-03-25,2426,6.9,TechCorp Inc -AI06754,Computer Vision Engineer,97955,USD,97955,EN,PT,Denmark,L,Kenya,100,"SQL, Linux, Azure, Spark, Deep Learning",Associate,1,Consulting,2024-07-05,2024-09-01,2218,9.7,Neural Networks Co -AI06755,Robotics Engineer,113968,AUD,153857,SE,CT,Australia,M,Australia,0,"Docker, Java, Python, Azure",Bachelor,9,Telecommunications,2024-06-12,2024-07-17,1975,5.5,Predictive Systems -AI06756,Autonomous Systems Engineer,73215,CAD,91519,EN,PT,Canada,M,Canada,0,"Scala, Python, Tableau",Master,0,Education,2024-06-28,2024-09-06,1660,7.5,Machine Intelligence Group -AI06757,Data Analyst,79628,CAD,99535,EN,FT,Canada,L,Japan,50,"Python, Docker, Computer Vision, Mathematics, Statistics",Bachelor,0,Technology,2024-06-02,2024-06-26,913,9.9,DataVision Ltd -AI06758,Data Engineer,177463,USD,177463,SE,CT,Norway,L,Norway,50,"Kubernetes, Mathematics, NLP, TensorFlow, Computer Vision",PhD,7,Technology,2025-02-24,2025-04-13,849,5.5,Future Systems -AI06759,AI Architect,126055,SGD,163872,SE,PT,Singapore,L,Luxembourg,50,"PyTorch, Scala, Tableau",PhD,5,Education,2024-11-03,2024-12-26,1623,6.6,AI Innovations -AI06760,AI Consultant,41096,USD,41096,SE,PT,India,M,Japan,0,"Scala, Java, Docker, Deep Learning",Associate,7,Real Estate,2024-05-14,2024-07-13,629,8.5,Machine Intelligence Group -AI06761,Principal Data Scientist,141579,AUD,191132,EX,FL,Australia,S,Australia,100,"R, Kubernetes, NLP, SQL",Master,10,Energy,2024-07-28,2024-10-09,608,7.9,Advanced Robotics -AI06762,Principal Data Scientist,117805,CAD,147256,EX,PT,Canada,S,Israel,50,"Python, Scala, MLOps, Linux",Associate,17,Media,2024-04-12,2024-06-08,1141,8.5,Advanced Robotics -AI06763,ML Ops Engineer,76368,USD,76368,SE,FT,China,L,Portugal,50,"Computer Vision, Java, Kubernetes, MLOps, Deep Learning",Bachelor,6,Healthcare,2024-07-06,2024-09-11,2307,9.9,TechCorp Inc -AI06764,NLP Engineer,66318,USD,66318,EN,FL,South Korea,M,Finland,0,"Hadoop, SQL, Computer Vision",Associate,1,Technology,2024-09-28,2024-12-07,548,5.5,Neural Networks Co -AI06765,AI Research Scientist,170692,USD,170692,EX,CT,Ireland,S,Ireland,0,"GCP, AWS, Deep Learning, PyTorch",PhD,15,Transportation,2024-05-15,2024-07-16,706,6.8,Machine Intelligence Group -AI06766,Computer Vision Engineer,289060,SGD,375778,EX,FL,Singapore,L,Singapore,0,"SQL, Git, Computer Vision, Statistics",Master,15,Real Estate,2024-04-28,2024-06-17,2412,8.6,DataVision Ltd -AI06767,Data Analyst,120746,USD,120746,SE,CT,Sweden,S,Sweden,0,"PyTorch, Python, Deep Learning, GCP, NLP",Associate,9,Technology,2024-12-21,2025-01-06,2167,5.5,Machine Intelligence Group -AI06768,Principal Data Scientist,97475,JPY,10722250,MI,FT,Japan,S,Japan,0,"Java, Kubernetes, SQL, Python",Bachelor,4,Finance,2025-01-02,2025-03-11,627,6.8,DataVision Ltd -AI06769,Computer Vision Engineer,228776,USD,228776,EX,FL,Israel,M,Israel,100,"TensorFlow, Python, Scala, Java",Bachelor,18,Manufacturing,2024-04-15,2024-06-22,1406,5.1,Digital Transformation LLC -AI06770,AI Specialist,224210,CAD,280263,EX,FL,Canada,M,Canada,100,"Statistics, Spark, Python, PyTorch",PhD,10,Manufacturing,2024-07-13,2024-09-02,1369,8.2,Quantum Computing Inc -AI06771,Head of AI,71016,USD,71016,EN,CT,Finland,L,Finland,50,"Git, Linux, Tableau",Master,0,Energy,2024-08-26,2024-10-26,2128,5.4,DataVision Ltd -AI06772,AI Product Manager,157055,USD,157055,MI,FT,Norway,L,Latvia,50,"PyTorch, Kubernetes, Statistics",Master,4,Energy,2024-02-13,2024-03-07,679,6.4,Digital Transformation LLC -AI06773,AI Specialist,78910,USD,78910,MI,FL,Israel,S,Latvia,0,"Azure, Deep Learning, Computer Vision",Associate,4,Telecommunications,2025-02-26,2025-04-19,913,5.8,DataVision Ltd -AI06774,AI Product Manager,133220,USD,133220,EX,FT,Finland,S,Estonia,50,"Hadoop, Docker, NLP, Git, PyTorch",PhD,10,Government,2024-02-16,2024-03-28,960,5.1,Quantum Computing Inc -AI06775,Machine Learning Engineer,102537,EUR,87156,MI,FL,France,M,France,100,"Spark, Java, Mathematics",Bachelor,3,Gaming,2025-02-27,2025-04-25,2295,7.7,Cognitive Computing -AI06776,Autonomous Systems Engineer,95026,USD,95026,EN,FT,United States,L,Latvia,50,"Git, Python, Azure",Master,0,Real Estate,2024-06-02,2024-07-14,968,8.4,Neural Networks Co -AI06777,AI Research Scientist,163095,USD,163095,EX,FT,Finland,L,Finland,50,"Git, AWS, MLOps, Statistics",Bachelor,17,Retail,2024-02-15,2024-03-01,1932,8,Algorithmic Solutions -AI06778,Data Scientist,86115,JPY,9472650,MI,FT,Japan,S,Japan,50,"R, Spark, Linux, Data Visualization",Associate,2,Education,2024-10-15,2024-11-03,2194,6.4,Cloud AI Solutions -AI06779,Robotics Engineer,81518,EUR,69290,MI,PT,France,S,France,50,"Computer Vision, Docker, Azure",PhD,2,Finance,2024-03-26,2024-04-23,724,5.6,Autonomous Tech -AI06780,Head of AI,112582,EUR,95695,SE,PT,Austria,S,Austria,100,"Spark, AWS, Docker",PhD,5,Media,2025-01-11,2025-03-09,569,5.7,Digital Transformation LLC -AI06781,Data Engineer,179222,USD,179222,SE,PT,Norway,L,Argentina,100,"Spark, Statistics, PyTorch, SQL, TensorFlow",PhD,8,Retail,2024-03-07,2024-05-02,619,7.4,Algorithmic Solutions -AI06782,AI Research Scientist,267085,CHF,240377,EX,FL,Switzerland,L,Argentina,0,"AWS, PyTorch, Statistics",PhD,14,Transportation,2024-11-18,2025-01-06,591,6.7,DeepTech Ventures -AI06783,AI Specialist,72647,USD,72647,EN,FL,South Korea,L,Estonia,50,"Azure, Spark, Scala, Linux",Bachelor,0,Manufacturing,2024-07-03,2024-07-21,2440,8,Algorithmic Solutions -AI06784,Principal Data Scientist,157364,SGD,204573,EX,CT,Singapore,M,Singapore,0,"Azure, MLOps, Data Visualization, Hadoop",Bachelor,18,Finance,2024-01-23,2024-03-16,2250,9.9,Future Systems -AI06785,Research Scientist,147887,GBP,110915,SE,PT,United Kingdom,L,Chile,100,"Linux, Spark, NLP, Python",Bachelor,7,Education,2024-09-22,2024-11-26,1467,9.6,Advanced Robotics -AI06786,AI Specialist,93908,JPY,10329880,MI,PT,Japan,L,Japan,0,"Hadoop, Deep Learning, Java, Kubernetes",Bachelor,4,Technology,2025-03-28,2025-05-27,1495,6.4,DataVision Ltd -AI06787,Data Scientist,221005,USD,221005,SE,FL,Norway,L,New Zealand,0,"SQL, NLP, Statistics, Deep Learning, R",Associate,9,Energy,2024-07-11,2024-08-06,1072,6.3,Neural Networks Co -AI06788,AI Consultant,188472,USD,188472,SE,FL,Denmark,M,Denmark,0,"Git, AWS, Mathematics, NLP",PhD,8,Finance,2024-04-16,2024-06-13,769,8,DataVision Ltd -AI06789,AI Research Scientist,134644,USD,134644,SE,FL,South Korea,L,South Korea,100,"Scala, TensorFlow, Kubernetes, Statistics, R",PhD,9,Real Estate,2024-10-22,2024-12-15,1688,7.9,DataVision Ltd -AI06790,ML Ops Engineer,158617,AUD,214133,EX,CT,Australia,L,Australia,50,"Python, AWS, TensorFlow",Bachelor,11,Healthcare,2024-06-16,2024-08-11,2165,8.6,Quantum Computing Inc -AI06791,ML Ops Engineer,80635,USD,80635,MI,FT,Israel,L,Canada,50,"Spark, Azure, Data Visualization, Computer Vision",PhD,3,Consulting,2024-12-26,2025-01-23,2490,9.8,Predictive Systems -AI06792,Machine Learning Researcher,186187,SGD,242043,EX,PT,Singapore,M,Singapore,50,"Computer Vision, Git, Python, Deep Learning",Associate,18,Technology,2025-02-26,2025-04-05,1822,5.2,Machine Intelligence Group -AI06793,Computer Vision Engineer,101105,EUR,85939,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP",Bachelor,4,Real Estate,2024-01-19,2024-03-25,888,9.7,Machine Intelligence Group -AI06794,Data Scientist,178163,USD,178163,EX,FT,Ireland,L,Ireland,0,"GCP, TensorFlow, Linux",PhD,15,Manufacturing,2024-06-04,2024-08-07,979,8.8,Cloud AI Solutions -AI06795,ML Ops Engineer,63735,EUR,54175,EN,PT,France,L,France,0,"SQL, PyTorch, Data Visualization",Master,0,Healthcare,2024-05-04,2024-06-12,2161,9.4,Autonomous Tech -AI06796,AI Consultant,148327,CHF,133494,MI,FL,Switzerland,M,Canada,0,"Azure, Scala, Linux",Master,3,Energy,2024-03-23,2024-04-07,1743,8.7,Algorithmic Solutions -AI06797,Computer Vision Engineer,70092,USD,70092,MI,PT,Finland,S,Chile,100,"Java, SQL, Tableau",Bachelor,2,Technology,2025-01-23,2025-03-03,899,5.8,Cognitive Computing -AI06798,AI Research Scientist,168805,USD,168805,SE,PT,Sweden,L,Sweden,50,"AWS, SQL, Data Visualization, Computer Vision",Bachelor,5,Energy,2024-05-07,2024-06-08,1562,10,Algorithmic Solutions -AI06799,AI Product Manager,167702,CAD,209628,EX,PT,Canada,S,Germany,50,"Python, MLOps, TensorFlow, NLP",Associate,16,Gaming,2024-06-26,2024-08-11,1409,9.6,TechCorp Inc -AI06800,Robotics Engineer,77196,EUR,65617,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Spark, Computer Vision, SQL, GCP",Master,3,Energy,2025-01-17,2025-02-05,566,9.7,Quantum Computing Inc -AI06801,AI Product Manager,60668,EUR,51568,EN,FL,Austria,M,Austria,0,"Python, Java, NLP, Azure",Bachelor,0,Telecommunications,2024-07-03,2024-07-22,934,8.5,Autonomous Tech -AI06802,Machine Learning Researcher,238168,AUD,321527,EX,FL,Australia,L,Australia,0,"SQL, Git, Deep Learning",Master,14,Energy,2024-04-05,2024-05-07,1426,7.2,Cognitive Computing -AI06803,Principal Data Scientist,80987,SGD,105283,MI,PT,Singapore,S,Singapore,0,"SQL, Git, NLP, Deep Learning",Bachelor,4,Manufacturing,2024-12-08,2025-02-11,1153,8.3,Autonomous Tech -AI06804,Autonomous Systems Engineer,58908,USD,58908,EN,FL,United States,S,Hungary,100,"PyTorch, TensorFlow, R",Bachelor,1,Gaming,2024-02-06,2024-04-08,1768,5.7,Algorithmic Solutions -AI06805,Machine Learning Engineer,56978,GBP,42734,EN,PT,United Kingdom,S,United Kingdom,0,"NLP, Spark, Python, Hadoop",PhD,1,Manufacturing,2025-01-16,2025-02-20,1809,6.3,Algorithmic Solutions -AI06806,Autonomous Systems Engineer,149583,USD,149583,EX,PT,Israel,M,Israel,50,"TensorFlow, Azure, PyTorch",Master,12,Manufacturing,2024-08-16,2024-10-27,1499,9.5,Digital Transformation LLC -AI06807,Robotics Engineer,275970,USD,275970,EX,CT,Ireland,L,Ireland,50,"Tableau, Scala, R",Bachelor,16,Real Estate,2025-02-18,2025-04-26,2306,5.3,Autonomous Tech -AI06808,Head of AI,154006,EUR,130905,EX,CT,Germany,M,Germany,100,"TensorFlow, Hadoop, AWS, SQL",PhD,12,Energy,2024-07-26,2024-08-17,1303,7.7,Advanced Robotics -AI06809,Principal Data Scientist,131751,JPY,14492610,MI,FT,Japan,L,Japan,0,"Kubernetes, Python, R",Master,4,Automotive,2024-11-12,2024-12-29,2127,6.3,Future Systems -AI06810,Robotics Engineer,163158,JPY,17947380,SE,FL,Japan,L,Mexico,50,"Mathematics, Tableau, Kubernetes",Master,7,Transportation,2024-01-27,2024-03-08,885,6.8,Digital Transformation LLC -AI06811,Principal Data Scientist,52986,USD,52986,EN,PT,Sweden,M,Thailand,0,"SQL, Hadoop, MLOps",Associate,1,Real Estate,2024-09-08,2024-10-02,1605,5.5,Digital Transformation LLC -AI06812,NLP Engineer,326359,CHF,293723,EX,PT,Switzerland,L,Switzerland,0,"Linux, Python, Data Visualization, Computer Vision, Scala",Bachelor,11,Government,2024-05-27,2024-07-26,904,6.1,Cognitive Computing -AI06813,NLP Engineer,78523,USD,78523,EN,FT,Israel,L,United States,100,"Deep Learning, PyTorch, SQL",Associate,1,Technology,2024-10-13,2024-11-24,1039,5.8,AI Innovations -AI06814,NLP Engineer,104203,SGD,135464,MI,FL,Singapore,M,Singapore,100,"Statistics, Python, NLP, Spark, Data Visualization",Bachelor,4,Government,2024-03-19,2024-05-01,937,8,AI Innovations -AI06815,Data Engineer,39561,USD,39561,SE,PT,India,S,India,100,"TensorFlow, Git, Data Visualization",PhD,9,Automotive,2024-08-04,2024-09-18,1448,7.4,Predictive Systems -AI06816,AI Research Scientist,80731,EUR,68621,EN,PT,Austria,L,Austria,100,"Kubernetes, GCP, Java",Bachelor,0,Education,2024-02-07,2024-04-19,2243,9.4,Advanced Robotics -AI06817,Research Scientist,138085,EUR,117372,EX,FT,Austria,M,Austria,100,"SQL, NLP, Kubernetes, R",Associate,14,Transportation,2024-08-10,2024-09-30,875,5.5,Advanced Robotics -AI06818,ML Ops Engineer,77251,GBP,57938,EN,PT,United Kingdom,M,United Kingdom,50,"Data Visualization, Tableau, Python, TensorFlow, Linux",Master,0,Finance,2024-05-02,2024-06-08,1189,7.5,Future Systems -AI06819,Data Engineer,82330,JPY,9056300,EN,CT,Japan,L,Brazil,0,"Azure, PyTorch, Tableau, Data Visualization, Scala",PhD,0,Media,2024-11-10,2025-01-06,988,7.9,Neural Networks Co -AI06820,Data Engineer,78143,EUR,66422,EN,FT,Netherlands,L,India,0,"PyTorch, Hadoop, Tableau, MLOps",PhD,0,Consulting,2024-01-05,2024-03-12,1227,7.5,Algorithmic Solutions -AI06821,Computer Vision Engineer,143711,USD,143711,SE,PT,Israel,M,Israel,100,"Computer Vision, GCP, Statistics, Python, Mathematics",Bachelor,8,Finance,2025-03-22,2025-05-08,1997,7.8,Neural Networks Co -AI06822,Autonomous Systems Engineer,33586,USD,33586,EN,FL,China,S,China,0,"PyTorch, Computer Vision, Linux, Deep Learning, NLP",Bachelor,0,Retail,2024-05-27,2024-07-23,942,7.2,Algorithmic Solutions -AI06823,Research Scientist,22293,USD,22293,EN,FL,India,L,India,50,"SQL, MLOps, PyTorch",PhD,1,Gaming,2024-07-14,2024-09-22,753,8.4,DeepTech Ventures -AI06824,ML Ops Engineer,98076,JPY,10788360,MI,CT,Japan,L,Japan,0,"Docker, Kubernetes, Data Visualization, TensorFlow, Azure",Master,4,Media,2025-04-22,2025-06-27,1933,7.9,Cloud AI Solutions -AI06825,Machine Learning Engineer,98006,EUR,83305,SE,FL,Netherlands,S,Netherlands,100,"SQL, Spark, PyTorch, R, TensorFlow",Bachelor,5,Consulting,2024-03-24,2024-04-14,1977,8.6,Autonomous Tech -AI06826,Data Scientist,66357,USD,66357,EN,FL,South Korea,M,New Zealand,100,"Java, SQL, Tableau",Associate,1,Gaming,2024-08-31,2024-09-16,2478,8.7,DeepTech Ventures -AI06827,AI Architect,193061,CHF,173755,SE,PT,Switzerland,L,Romania,50,"Computer Vision, Statistics, MLOps, NLP, Kubernetes",Master,5,Finance,2024-08-18,2024-10-16,1911,5.8,Autonomous Tech -AI06828,AI Software Engineer,220816,USD,220816,EX,CT,Sweden,M,Sweden,100,"AWS, Hadoop, Deep Learning",PhD,16,Transportation,2024-10-03,2024-11-03,610,5.9,Predictive Systems -AI06829,AI Software Engineer,130692,USD,130692,SE,FL,Sweden,L,Sweden,0,"Python, Linux, Tableau, Java, NLP",Master,9,Finance,2024-12-28,2025-03-08,1297,9.7,Algorithmic Solutions -AI06830,Machine Learning Researcher,207792,CHF,187013,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, SQL, Java",Associate,9,Gaming,2024-06-17,2024-08-10,1818,6.8,Advanced Robotics -AI06831,Data Scientist,65685,USD,65685,EN,PT,United States,S,United States,100,"Azure, SQL, NLP, Python",Master,1,Consulting,2024-01-01,2024-03-10,1366,9.2,Neural Networks Co -AI06832,AI Architect,125757,EUR,106893,SE,CT,Germany,L,Germany,0,"PyTorch, Computer Vision, GCP, Linux",Associate,6,Real Estate,2025-03-02,2025-04-24,1445,6.4,Quantum Computing Inc -AI06833,Head of AI,85426,EUR,72612,EN,CT,Netherlands,L,Netherlands,50,"Java, Python, Tableau",PhD,0,Real Estate,2024-03-22,2024-04-16,551,8.8,Autonomous Tech -AI06834,AI Specialist,25694,USD,25694,EN,FT,India,L,India,100,"AWS, Hadoop, NLP, Java",Bachelor,1,Technology,2025-02-10,2025-03-30,2280,8.3,Algorithmic Solutions -AI06835,Deep Learning Engineer,175415,CHF,157874,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, SQL, Azure",PhD,8,Telecommunications,2025-02-18,2025-03-09,1460,8.6,Neural Networks Co -AI06836,AI Product Manager,123361,USD,123361,SE,PT,Sweden,S,Estonia,50,"Spark, Python, Computer Vision, Kubernetes",Master,5,Consulting,2024-10-15,2024-10-30,1859,6.3,Quantum Computing Inc -AI06837,Robotics Engineer,158738,JPY,17461180,EX,FT,Japan,S,Japan,50,"Docker, Deep Learning, Scala, Spark",PhD,14,Media,2024-04-04,2024-05-13,1906,6,Digital Transformation LLC -AI06838,AI Research Scientist,83310,EUR,70814,EN,PT,Netherlands,L,Netherlands,50,"Linux, Statistics, TensorFlow",Master,0,Gaming,2025-02-04,2025-03-26,1650,10,DeepTech Ventures -AI06839,AI Architect,90940,EUR,77299,MI,FT,Germany,L,Germany,0,"Hadoop, Python, Deep Learning",PhD,3,Finance,2024-06-06,2024-07-03,2371,7,Neural Networks Co -AI06840,Principal Data Scientist,78709,USD,78709,EN,FL,Finland,L,Finland,50,"Tableau, Python, Scala",Master,1,Automotive,2024-10-08,2024-10-28,505,8,Predictive Systems -AI06841,Principal Data Scientist,23429,USD,23429,MI,CT,India,S,India,50,"Python, Azure, Deep Learning, Java, Scala",Bachelor,3,Media,2025-01-26,2025-03-18,2362,9,Autonomous Tech -AI06842,Data Scientist,56096,USD,56096,SE,PT,China,L,France,50,"Deep Learning, Python, Data Visualization, Statistics, Linux",Bachelor,5,Media,2024-05-20,2024-06-07,1141,6.5,Algorithmic Solutions -AI06843,Machine Learning Researcher,79608,USD,79608,MI,FL,South Korea,S,South Korea,100,"GCP, Linux, NLP, Data Visualization, Mathematics",Associate,2,Finance,2024-04-11,2024-05-28,1325,8,Neural Networks Co -AI06844,ML Ops Engineer,62288,USD,62288,EN,FL,Finland,M,Finland,100,"Spark, Scala, GCP",Bachelor,1,Government,2025-01-05,2025-01-29,1712,7.1,Quantum Computing Inc -AI06845,NLP Engineer,231007,AUD,311859,EX,FL,Australia,L,Australia,0,"TensorFlow, Linux, PyTorch, Spark, SQL",Bachelor,15,Automotive,2024-03-26,2024-05-04,1826,8.5,Digital Transformation LLC -AI06846,Principal Data Scientist,100308,USD,100308,EN,FT,United States,L,Australia,100,"Computer Vision, Scala, MLOps, NLP",Master,0,Energy,2024-03-18,2024-04-05,2263,9.2,TechCorp Inc -AI06847,AI Consultant,106652,EUR,90654,MI,PT,Austria,L,Austria,100,"Python, Hadoop, Linux, TensorFlow",PhD,4,Transportation,2025-01-24,2025-03-04,897,9.5,Cognitive Computing -AI06848,Research Scientist,75358,USD,75358,MI,FL,South Korea,M,South Korea,100,"Data Visualization, Python, TensorFlow, Git, Computer Vision",PhD,4,Retail,2024-07-22,2024-09-30,2175,7.9,Autonomous Tech -AI06849,ML Ops Engineer,20791,USD,20791,EN,FL,India,S,India,0,"Computer Vision, MLOps, Data Visualization",Bachelor,0,Automotive,2025-02-22,2025-04-20,946,6.2,Autonomous Tech -AI06850,Principal Data Scientist,97537,EUR,82906,SE,FL,Germany,S,Germany,100,"Deep Learning, Computer Vision, Azure",Associate,6,Gaming,2024-11-09,2025-01-11,704,5.2,Cloud AI Solutions -AI06851,Autonomous Systems Engineer,137228,AUD,185258,SE,CT,Australia,S,Australia,0,"Computer Vision, Azure, AWS",Master,7,Healthcare,2024-03-29,2024-05-14,2399,8.3,DeepTech Ventures -AI06852,AI Consultant,130679,AUD,176417,EX,FL,Australia,S,France,100,"Hadoop, Data Visualization, Python",PhD,19,Telecommunications,2024-05-03,2024-07-06,2270,7.7,Cloud AI Solutions -AI06853,Research Scientist,212506,EUR,180630,EX,CT,Germany,M,Indonesia,50,"Scala, SQL, Linux, AWS",Bachelor,11,Media,2024-05-10,2024-07-13,2220,5.3,Quantum Computing Inc -AI06854,AI Research Scientist,107510,CHF,96759,EN,PT,Switzerland,M,Romania,0,"Kubernetes, MLOps, Docker, AWS",PhD,0,Energy,2024-12-06,2024-12-20,1845,9.5,Algorithmic Solutions -AI06855,Autonomous Systems Engineer,75716,EUR,64359,EN,FL,France,L,Indonesia,100,"SQL, Hadoop, PyTorch",Associate,0,Government,2024-04-30,2024-06-08,2217,5,Autonomous Tech -AI06856,AI Software Engineer,86830,EUR,73806,SE,CT,France,S,France,100,"Statistics, AWS, R, GCP, Azure",Master,6,Automotive,2024-07-14,2024-08-18,1611,5.3,Cognitive Computing -AI06857,Research Scientist,148673,USD,148673,SE,FL,Norway,S,Hungary,100,"Data Visualization, Spark, Python",Bachelor,6,Automotive,2024-07-03,2024-07-19,1209,7.6,Cognitive Computing -AI06858,Data Analyst,128336,USD,128336,EX,FT,Israel,M,Israel,0,"Python, TensorFlow, Mathematics",Associate,18,Gaming,2024-01-08,2024-02-08,1804,5.6,Smart Analytics -AI06859,Data Scientist,281503,USD,281503,EX,CT,United States,M,United States,0,"Deep Learning, GCP, Statistics, Kubernetes, PyTorch",PhD,11,Gaming,2024-11-17,2024-12-02,1099,6.8,Future Systems -AI06860,Robotics Engineer,59139,EUR,50268,EN,CT,Austria,S,Austria,50,"R, MLOps, Azure, NLP, Linux",Associate,1,Finance,2024-10-10,2024-11-25,685,7.9,Algorithmic Solutions -AI06861,Data Engineer,76076,AUD,102703,EN,PT,Australia,L,Australia,0,"TensorFlow, Docker, Kubernetes",Master,1,Energy,2025-01-16,2025-02-11,544,8.6,DataVision Ltd -AI06862,Deep Learning Engineer,116557,USD,116557,SE,FT,South Korea,M,South Korea,50,"Git, SQL, PyTorch",Master,7,Energy,2024-11-26,2025-01-18,1024,9.1,DataVision Ltd -AI06863,Research Scientist,153326,USD,153326,SE,CT,Israel,L,Israel,0,"Data Visualization, Deep Learning, MLOps, Python",Associate,9,Automotive,2024-04-30,2024-06-25,1225,5.5,Cognitive Computing -AI06864,Principal Data Scientist,145710,CHF,131139,SE,FT,Switzerland,S,Finland,100,"Hadoop, GCP, Linux, Kubernetes",Bachelor,7,Consulting,2024-11-06,2024-11-30,1025,6.8,Cloud AI Solutions -AI06865,AI Software Engineer,208806,EUR,177485,EX,FT,Netherlands,L,Poland,100,"Tableau, Scala, Python",Associate,15,Education,2024-09-03,2024-10-09,833,8.3,Digital Transformation LLC -AI06866,Robotics Engineer,59495,USD,59495,EN,FL,Norway,S,Norway,100,"Statistics, GCP, Computer Vision",PhD,1,Consulting,2024-06-27,2024-08-16,2122,8.7,Smart Analytics -AI06867,Research Scientist,161310,AUD,217769,EX,PT,Australia,M,Australia,50,"Deep Learning, Computer Vision, Data Visualization",PhD,12,Technology,2024-12-09,2025-01-05,2010,8.5,Quantum Computing Inc -AI06868,Research Scientist,63732,EUR,54172,EN,FT,Austria,M,China,100,"Spark, Python, Docker, TensorFlow",PhD,1,Manufacturing,2025-03-19,2025-04-08,2143,8.2,DataVision Ltd -AI06869,Data Analyst,144081,USD,144081,SE,PT,Sweden,M,Sweden,0,"Docker, TensorFlow, GCP",Master,6,Telecommunications,2024-10-15,2024-11-12,1553,8.2,Cloud AI Solutions -AI06870,Computer Vision Engineer,81528,USD,81528,MI,FT,South Korea,L,South Korea,50,"Python, Java, Mathematics, Linux",PhD,4,Telecommunications,2024-03-26,2024-04-28,605,6.9,DataVision Ltd -AI06871,Machine Learning Researcher,23844,USD,23844,EN,FL,India,L,India,0,"GCP, AWS, Data Visualization, Statistics, Spark",Bachelor,1,Automotive,2024-08-23,2024-09-25,2315,6.8,Machine Intelligence Group -AI06872,Deep Learning Engineer,46652,USD,46652,MI,CT,China,M,China,100,"Spark, Scala, Git, NLP, Hadoop",PhD,2,Government,2024-06-21,2024-08-28,632,6.8,Quantum Computing Inc -AI06873,Robotics Engineer,63871,USD,63871,MI,CT,Finland,S,Finland,100,"PyTorch, Statistics, Kubernetes",Master,3,Finance,2025-03-13,2025-05-09,2415,7.8,AI Innovations -AI06874,Head of AI,86503,USD,86503,MI,PT,Ireland,M,Ireland,0,"Python, TensorFlow, Computer Vision",Master,2,Transportation,2025-01-16,2025-02-07,1848,6,Machine Intelligence Group -AI06875,Data Engineer,68882,AUD,92991,EN,CT,Australia,M,Australia,100,"Hadoop, Deep Learning, Spark, PyTorch, Statistics",Associate,0,Transportation,2024-08-30,2024-10-11,2401,5.3,Future Systems -AI06876,ML Ops Engineer,120496,EUR,102422,SE,FT,Germany,S,Germany,0,"Data Visualization, Mathematics, R",Master,6,Automotive,2024-12-31,2025-01-26,2097,7,Machine Intelligence Group -AI06877,Data Scientist,67737,EUR,57576,EN,FL,Germany,S,Denmark,50,"Linux, Data Visualization, Docker",Bachelor,0,Consulting,2024-01-31,2024-03-30,1686,7.3,Cloud AI Solutions -AI06878,Head of AI,58637,EUR,49841,EN,FL,Netherlands,S,Thailand,50,"Statistics, Computer Vision, NLP, Git, Kubernetes",Master,1,Technology,2024-06-29,2024-09-04,540,10,Neural Networks Co -AI06879,AI Specialist,130820,EUR,111197,SE,FL,Austria,M,Sweden,0,"Computer Vision, SQL, Statistics, Git",Associate,7,Healthcare,2024-06-24,2024-08-22,913,9.1,Digital Transformation LLC -AI06880,Deep Learning Engineer,101122,USD,101122,MI,CT,Sweden,M,Sweden,0,"Git, Kubernetes, SQL",PhD,3,Automotive,2024-11-20,2025-01-11,1832,7,DeepTech Ventures -AI06881,AI Architect,130892,USD,130892,SE,PT,Finland,L,Finland,0,"Git, R, TensorFlow, Python, PyTorch",PhD,6,Real Estate,2024-07-07,2024-08-29,2367,5.1,Smart Analytics -AI06882,AI Product Manager,26937,USD,26937,EN,CT,India,L,Portugal,0,"R, AWS, Python, Mathematics",Associate,1,Government,2025-04-30,2025-05-25,1341,9.1,Smart Analytics -AI06883,AI Research Scientist,90590,GBP,67943,MI,FT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Azure, Hadoop",Master,3,Real Estate,2024-05-27,2024-08-03,1264,6.8,Quantum Computing Inc -AI06884,AI Consultant,121858,USD,121858,SE,FT,Sweden,S,Sweden,50,"Kubernetes, PyTorch, Statistics, R, Java",Associate,7,Manufacturing,2024-02-09,2024-02-23,1435,6.9,Cognitive Computing -AI06885,Research Scientist,102740,EUR,87329,SE,CT,Netherlands,S,Netherlands,100,"PyTorch, SQL, Linux, Statistics",Bachelor,8,Automotive,2024-05-29,2024-07-23,1550,8.3,DataVision Ltd -AI06886,Data Scientist,250788,USD,250788,EX,FL,Denmark,S,United States,0,"Spark, Tableau, Python, Scala, GCP",Bachelor,11,Consulting,2024-03-25,2024-05-26,626,6.3,DeepTech Ventures -AI06887,Research Scientist,45176,USD,45176,SE,FL,India,S,United Kingdom,0,"Python, Spark, NLP, Data Visualization",PhD,6,Gaming,2024-01-06,2024-01-25,1783,8.5,DeepTech Ventures -AI06888,AI Specialist,107442,USD,107442,SE,FT,South Korea,M,South Korea,0,"Mathematics, Kubernetes, Python, Docker, Data Visualization",Associate,7,Telecommunications,2024-04-22,2024-06-28,1030,5.7,Advanced Robotics -AI06889,Computer Vision Engineer,193572,EUR,164536,EX,FT,Austria,M,Singapore,0,"PyTorch, SQL, GCP",Associate,11,Healthcare,2024-12-13,2025-01-02,1285,6,Future Systems -AI06890,AI Consultant,93956,USD,93956,EX,PT,India,L,India,0,"Azure, PyTorch, TensorFlow, Docker, Git",Master,16,Automotive,2024-03-18,2024-04-07,1868,9.9,DataVision Ltd -AI06891,Autonomous Systems Engineer,77210,EUR,65629,EN,FT,Netherlands,M,Netherlands,0,"Data Visualization, Java, Linux",Associate,1,Technology,2024-08-21,2024-10-04,1539,6.8,Algorithmic Solutions -AI06892,AI Consultant,59058,USD,59058,EX,CT,India,L,Malaysia,50,"NLP, Kubernetes, PyTorch, Git, Tableau",Bachelor,12,Gaming,2024-06-20,2024-08-30,1756,9.9,DeepTech Ventures -AI06893,Machine Learning Researcher,285291,CHF,256762,EX,FT,Switzerland,M,Switzerland,50,"PyTorch, Linux, TensorFlow, Mathematics",Bachelor,12,Technology,2024-03-17,2024-04-25,2134,8.6,Digital Transformation LLC -AI06894,Data Analyst,92251,USD,92251,MI,FT,Sweden,S,Sweden,100,"Python, Tableau, Java, Statistics",PhD,3,Government,2024-09-25,2024-11-26,1721,5.4,Autonomous Tech -AI06895,Machine Learning Engineer,138851,CAD,173564,SE,PT,Canada,L,Canada,50,"Python, Azure, Statistics, Linux",Master,7,Manufacturing,2024-08-14,2024-10-03,2484,5.7,Cloud AI Solutions -AI06896,Deep Learning Engineer,208953,EUR,177610,EX,FT,Netherlands,S,Netherlands,0,"Git, Docker, Scala",PhD,12,Government,2024-02-16,2024-03-28,2051,9.4,Quantum Computing Inc -AI06897,NLP Engineer,187224,CHF,168502,SE,FT,Switzerland,M,Switzerland,100,"Git, Scala, Java",Bachelor,8,Healthcare,2025-02-15,2025-04-14,1158,9.9,Machine Intelligence Group -AI06898,Principal Data Scientist,266395,USD,266395,EX,PT,Sweden,L,Sweden,0,"SQL, Spark, PyTorch, Linux",Bachelor,12,Automotive,2024-03-05,2024-04-05,936,8.4,Smart Analytics -AI06899,AI Specialist,88761,USD,88761,MI,FT,Sweden,S,Brazil,0,"AWS, Linux, Deep Learning, Mathematics",Master,2,Media,2024-01-06,2024-01-28,2134,7.1,Predictive Systems -AI06900,Machine Learning Engineer,81928,USD,81928,EX,CT,China,M,China,50,"Git, Tableau, SQL, Mathematics, Kubernetes",Bachelor,10,Government,2024-08-05,2024-08-25,1453,9.6,Neural Networks Co -AI06901,Machine Learning Researcher,127931,SGD,166310,SE,CT,Singapore,L,Singapore,50,"MLOps, Python, Kubernetes",Master,7,Finance,2024-07-23,2024-10-02,1159,6.3,Predictive Systems -AI06902,Data Analyst,107379,CHF,96641,EN,FT,Switzerland,L,Switzerland,0,"R, Git, Tableau, Azure",Associate,0,Real Estate,2024-09-29,2024-11-23,890,8.2,Smart Analytics -AI06903,Principal Data Scientist,82295,USD,82295,SE,PT,China,L,China,0,"Java, Kubernetes, PyTorch, MLOps",Associate,9,Manufacturing,2024-11-29,2025-02-10,1560,8.6,Neural Networks Co -AI06904,AI Product Manager,91254,EUR,77566,MI,FL,Netherlands,M,Netherlands,100,"Python, Azure, Tableau, SQL",PhD,3,Consulting,2024-02-28,2024-04-28,1098,6.6,Smart Analytics -AI06905,Data Engineer,139532,USD,139532,MI,CT,Denmark,L,Italy,100,"Tableau, TensorFlow, Kubernetes",Associate,2,Telecommunications,2025-04-23,2025-05-19,1554,7.5,Predictive Systems -AI06906,Data Scientist,105160,JPY,11567600,MI,FT,Japan,L,Japan,50,"Scala, AWS, Data Visualization, NLP",Master,2,Energy,2024-03-16,2024-05-11,2229,5.2,Cognitive Computing -AI06907,Research Scientist,123788,JPY,13616680,MI,FT,Japan,L,Japan,100,"Python, SQL, Linux, Deep Learning, Mathematics",Master,3,Real Estate,2025-01-17,2025-02-01,651,8.2,TechCorp Inc -AI06908,Research Scientist,108313,EUR,92066,MI,FL,Netherlands,L,Netherlands,0,"PyTorch, SQL, Kubernetes, R",Bachelor,2,Manufacturing,2025-01-21,2025-02-27,2052,5.7,Predictive Systems -AI06909,Robotics Engineer,105151,USD,105151,SE,CT,Ireland,M,Ireland,50,"Git, TensorFlow, Tableau, SQL, Deep Learning",Bachelor,9,Government,2024-09-09,2024-10-11,1671,6.4,Neural Networks Co -AI06910,Principal Data Scientist,55680,USD,55680,EX,PT,India,M,India,50,"Computer Vision, Hadoop, Azure",Master,12,Manufacturing,2024-08-30,2024-09-17,1329,7.2,DataVision Ltd -AI06911,AI Consultant,141286,JPY,15541460,SE,FL,Japan,S,Japan,100,"Kubernetes, Git, Hadoop",Bachelor,6,Education,2024-06-10,2024-08-07,1364,9.3,TechCorp Inc -AI06912,Machine Learning Engineer,87004,CAD,108755,SE,PT,Canada,S,Norway,0,"Linux, Data Visualization, TensorFlow",Master,8,Retail,2024-09-02,2024-11-02,581,7.4,Advanced Robotics -AI06913,Data Analyst,101540,USD,101540,MI,FL,Sweden,M,India,0,"Linux, Python, R, Java",Master,3,Gaming,2024-12-25,2025-02-06,1662,5.5,Autonomous Tech -AI06914,Research Scientist,176009,USD,176009,SE,PT,Norway,L,Norway,50,"Azure, Java, Scala, Kubernetes",Associate,6,Education,2024-06-02,2024-07-24,2272,6.3,Autonomous Tech -AI06915,Deep Learning Engineer,85561,GBP,64171,EN,PT,United Kingdom,L,Switzerland,50,"R, Kubernetes, Data Visualization",Bachelor,0,Healthcare,2024-12-18,2025-01-04,826,9.2,Smart Analytics -AI06916,Deep Learning Engineer,102426,USD,102426,MI,CT,Ireland,L,Ireland,50,"Computer Vision, Tableau, Linux",Master,3,Automotive,2024-10-13,2024-12-08,1346,8.4,AI Innovations -AI06917,Data Analyst,103962,USD,103962,EN,FT,Norway,L,Norway,0,"SQL, Java, Git, Deep Learning",Associate,1,Retail,2024-05-17,2024-06-20,1235,9.3,Cognitive Computing -AI06918,Head of AI,81801,USD,81801,MI,CT,Israel,M,Israel,50,"MLOps, Kubernetes, SQL, PyTorch",PhD,4,Real Estate,2024-11-03,2025-01-06,1081,6.7,AI Innovations -AI06919,Deep Learning Engineer,141646,USD,141646,SE,FL,Ireland,L,Ireland,0,"Java, SQL, MLOps, Azure",Associate,5,Automotive,2024-08-21,2024-10-11,1664,5.9,Digital Transformation LLC -AI06920,Machine Learning Engineer,197459,USD,197459,EX,CT,Israel,L,Israel,50,"Java, PyTorch, Tableau, Deep Learning",Master,12,Healthcare,2025-03-03,2025-03-23,1470,6.1,Quantum Computing Inc -AI06921,Deep Learning Engineer,86119,EUR,73201,MI,CT,Austria,L,Italy,0,"Azure, Python, Computer Vision, NLP, Tableau",PhD,2,Healthcare,2024-12-06,2024-12-31,665,9.6,Smart Analytics -AI06922,Autonomous Systems Engineer,54196,EUR,46067,EN,CT,Germany,S,Germany,50,"Kubernetes, Statistics, NLP, Azure",Master,1,Real Estate,2025-01-10,2025-02-27,1458,6.9,DataVision Ltd -AI06923,Machine Learning Engineer,83714,USD,83714,EN,FL,Denmark,M,France,100,"Hadoop, TensorFlow, Kubernetes, PyTorch, Git",PhD,1,Finance,2024-09-01,2024-09-25,1593,7,Future Systems -AI06924,Deep Learning Engineer,156483,GBP,117362,SE,CT,United Kingdom,M,United Kingdom,50,"Spark, Hadoop, Linux",Master,7,Technology,2024-10-10,2024-10-30,1052,7.2,TechCorp Inc -AI06925,AI Architect,147145,USD,147145,SE,FT,Norway,S,Norway,0,"Deep Learning, Python, Git, TensorFlow, AWS",PhD,8,Transportation,2024-12-30,2025-02-28,2183,5.1,Smart Analytics -AI06926,NLP Engineer,278709,EUR,236903,EX,FL,Netherlands,L,Brazil,50,"PyTorch, SQL, AWS, R, Java",Associate,18,Transportation,2025-01-24,2025-03-26,2323,6.1,Cloud AI Solutions -AI06927,Computer Vision Engineer,163345,EUR,138843,EX,PT,Austria,S,Austria,100,"Hadoop, Git, Python",Bachelor,14,Automotive,2024-07-23,2024-08-24,2230,9.2,Cloud AI Solutions -AI06928,AI Product Manager,97503,AUD,131629,SE,CT,Australia,S,Australia,50,"Deep Learning, Docker, Java, AWS",Bachelor,6,Manufacturing,2025-01-01,2025-01-20,2440,5.6,Quantum Computing Inc -AI06929,Machine Learning Researcher,173549,CHF,156194,SE,FL,Switzerland,L,Germany,50,"Kubernetes, Scala, Spark",Bachelor,9,Consulting,2025-01-20,2025-03-03,2076,8.6,Advanced Robotics -AI06930,AI Product Manager,229619,GBP,172214,EX,FT,United Kingdom,S,United Kingdom,100,"Azure, Hadoop, Java",Associate,18,Government,2025-01-19,2025-02-07,1585,9.7,DeepTech Ventures -AI06931,Computer Vision Engineer,197390,USD,197390,SE,PT,Denmark,M,Denmark,0,"GCP, MLOps, Git, Computer Vision, Java",Master,5,Government,2024-10-20,2024-12-21,1655,9.9,Digital Transformation LLC -AI06932,Computer Vision Engineer,53391,EUR,45382,EN,FL,Austria,S,Romania,50,"Kubernetes, Linux, Tableau, SQL, Statistics",Bachelor,0,Government,2024-11-17,2024-12-18,2141,6.9,Smart Analytics -AI06933,AI Software Engineer,70421,EUR,59858,MI,FL,France,S,Colombia,0,"SQL, Scala, NLP",Associate,3,Energy,2024-12-25,2025-02-04,2200,7.2,Digital Transformation LLC -AI06934,Machine Learning Engineer,82065,USD,82065,EN,PT,Sweden,L,Romania,0,"Docker, Java, Tableau, Hadoop, NLP",Bachelor,1,Automotive,2025-02-21,2025-04-23,1455,9.8,DataVision Ltd -AI06935,NLP Engineer,114605,USD,114605,SE,FL,Israel,L,Israel,0,"GCP, MLOps, R",Master,6,Gaming,2024-06-27,2024-08-24,1238,5.2,DeepTech Ventures -AI06936,AI Architect,209622,CAD,262028,EX,PT,Canada,M,Ireland,0,"Tableau, PyTorch, Kubernetes",Master,17,Manufacturing,2024-06-09,2024-07-10,1344,6.2,Neural Networks Co -AI06937,Computer Vision Engineer,159369,USD,159369,MI,PT,Denmark,L,Denmark,0,"TensorFlow, SQL, R",Bachelor,2,Education,2024-03-18,2024-05-10,1590,7.7,Cognitive Computing -AI06938,Head of AI,287596,USD,287596,EX,FT,Sweden,L,Sweden,0,"Hadoop, Linux, Docker, Data Visualization",Associate,11,Energy,2024-01-01,2024-02-18,714,9.1,Digital Transformation LLC -AI06939,AI Product Manager,145099,EUR,123334,SE,PT,Germany,L,Germany,100,"TensorFlow, Scala, Linux",Associate,5,Government,2024-04-29,2024-06-28,1557,6.3,Predictive Systems -AI06940,ML Ops Engineer,265723,EUR,225865,EX,PT,Germany,L,Germany,0,"Kubernetes, Mathematics, Data Visualization",Master,16,Real Estate,2025-04-30,2025-06-25,645,5.8,Advanced Robotics -AI06941,Data Scientist,146927,EUR,124888,SE,PT,Germany,L,Germany,0,"TensorFlow, Hadoop, Linux, AWS, Computer Vision",Bachelor,5,Healthcare,2024-01-14,2024-03-16,927,7.7,Advanced Robotics -AI06942,AI Research Scientist,55638,USD,55638,MI,CT,China,L,China,50,"Scala, GCP, Data Visualization, Computer Vision",Associate,2,Transportation,2025-01-09,2025-03-18,2069,7.5,Smart Analytics -AI06943,Head of AI,147236,USD,147236,SE,FT,Norway,M,Norway,100,"TensorFlow, Linux, Java",Bachelor,8,Automotive,2024-11-03,2024-12-23,1031,8.6,Advanced Robotics -AI06944,AI Research Scientist,195009,EUR,165758,EX,FL,France,S,New Zealand,100,"Java, Data Visualization, Python",PhD,18,Energy,2025-02-25,2025-05-07,2121,5.3,Advanced Robotics -AI06945,AI Consultant,75991,EUR,64592,EN,FL,France,L,France,50,"Git, SQL, Java",Bachelor,1,Transportation,2024-02-08,2024-03-13,550,8.8,Predictive Systems -AI06946,Research Scientist,188727,USD,188727,EX,CT,Ireland,M,Ireland,0,"Scala, R, PyTorch",Bachelor,12,Telecommunications,2025-01-23,2025-03-28,1066,8.6,Autonomous Tech -AI06947,Machine Learning Researcher,122620,USD,122620,MI,FT,Denmark,L,Denmark,0,"Kubernetes, Spark, Python, Tableau, Linux",Master,3,Consulting,2024-03-03,2024-05-10,1623,8.8,Predictive Systems -AI06948,Computer Vision Engineer,169343,USD,169343,SE,CT,Ireland,L,Hungary,0,"Mathematics, Git, Java",Bachelor,8,Gaming,2024-01-10,2024-03-05,630,7.5,Future Systems -AI06949,AI Architect,76731,CAD,95914,EN,FT,Canada,L,Canada,100,"Azure, Kubernetes, Git",Associate,0,Real Estate,2024-03-12,2024-04-19,1818,8.1,Machine Intelligence Group -AI06950,Machine Learning Researcher,257911,USD,257911,EX,FL,Ireland,L,Mexico,100,"Python, Kubernetes, AWS, Azure, GCP",Bachelor,10,Real Estate,2024-02-02,2024-02-19,1181,9.7,Smart Analytics -AI06951,Head of AI,163774,AUD,221095,EX,FT,Australia,S,Australia,50,"Computer Vision, R, Tableau",Associate,18,Transportation,2024-07-14,2024-08-29,1817,7.5,Cognitive Computing -AI06952,Computer Vision Engineer,31330,USD,31330,EN,FL,China,M,China,0,"R, Spark, Statistics",Master,1,Education,2024-09-25,2024-10-18,2401,10,TechCorp Inc -AI06953,Data Scientist,145202,USD,145202,SE,FT,Israel,L,Poland,0,"Spark, AWS, Deep Learning",Bachelor,6,Gaming,2025-04-21,2025-06-20,728,5,Autonomous Tech -AI06954,Robotics Engineer,89064,SGD,115783,EN,PT,Singapore,L,Singapore,100,"SQL, Python, Computer Vision, Deep Learning",Bachelor,0,Retail,2025-04-13,2025-05-21,1888,7.8,Algorithmic Solutions -AI06955,Data Analyst,132621,USD,132621,SE,PT,Finland,L,Finland,50,"Scala, Docker, Spark, Statistics",Master,7,Education,2025-02-03,2025-03-11,1598,7.3,Quantum Computing Inc -AI06956,NLP Engineer,84808,USD,84808,EN,CT,Sweden,L,Sweden,100,"SQL, NLP, Spark, Hadoop",Bachelor,0,Government,2024-01-04,2024-01-24,2408,8.7,Machine Intelligence Group -AI06957,AI Consultant,59952,USD,59952,EN,FT,Norway,S,Norway,100,"Kubernetes, NLP, Data Visualization",Associate,1,Media,2025-01-31,2025-04-13,1048,5.1,DataVision Ltd -AI06958,Deep Learning Engineer,100845,USD,100845,MI,FT,Finland,M,Germany,0,"TensorFlow, Mathematics, Java, Linux",Master,2,Media,2024-11-25,2024-12-31,1984,9.4,TechCorp Inc -AI06959,Machine Learning Engineer,98597,EUR,83807,MI,CT,Netherlands,M,Japan,100,"GCP, Scala, R",Bachelor,3,Retail,2024-12-24,2025-01-13,1549,8.5,Future Systems -AI06960,Data Engineer,142965,EUR,121520,SE,FT,Germany,M,Nigeria,0,"Kubernetes, Linux, Azure, GCP, Git",PhD,5,Automotive,2024-06-24,2024-08-13,2341,6.4,TechCorp Inc -AI06961,Machine Learning Researcher,84811,GBP,63608,EN,PT,United Kingdom,L,United Kingdom,100,"Tableau, MLOps, NLP, Linux",PhD,1,Retail,2024-08-10,2024-09-11,1114,6.6,Neural Networks Co -AI06962,AI Software Engineer,150732,USD,150732,SE,CT,Denmark,M,Italy,100,"MLOps, Git, GCP, R, Python",Associate,5,Automotive,2025-01-23,2025-02-20,1915,6.6,Cloud AI Solutions -AI06963,AI Research Scientist,146631,AUD,197952,SE,FT,Australia,M,Australia,50,"Scala, Data Visualization, Linux, SQL",Master,8,Gaming,2024-01-23,2024-03-01,1304,5.2,Digital Transformation LLC -AI06964,AI Consultant,87006,CAD,108758,EN,FT,Canada,L,Canada,100,"Docker, Statistics, Computer Vision, Linux, Deep Learning",PhD,1,Education,2024-11-20,2025-01-03,1023,7.8,Cognitive Computing -AI06965,ML Ops Engineer,93917,AUD,126788,SE,CT,Australia,S,France,100,"Git, Python, NLP",Master,5,Manufacturing,2024-06-17,2024-07-07,1248,9.7,Smart Analytics -AI06966,Data Analyst,168686,EUR,143383,EX,FL,Netherlands,S,Netherlands,50,"Statistics, Python, Git, Linux, SQL",Bachelor,12,Real Estate,2025-01-09,2025-02-01,2404,7.4,AI Innovations -AI06967,Research Scientist,128330,GBP,96248,SE,PT,United Kingdom,S,South Africa,50,"Azure, Mathematics, Kubernetes, Deep Learning",Associate,6,Gaming,2025-02-28,2025-05-05,1920,6.8,TechCorp Inc -AI06968,Data Engineer,111839,SGD,145391,SE,PT,Singapore,S,Singapore,50,"Scala, MLOps, Docker, Hadoop, Statistics",PhD,9,Retail,2024-03-02,2024-03-21,2328,7.3,Predictive Systems -AI06969,AI Software Engineer,187884,USD,187884,EX,PT,South Korea,L,Malaysia,50,"TensorFlow, SQL, Mathematics",Master,18,Consulting,2025-01-31,2025-03-09,675,9,AI Innovations -AI06970,AI Specialist,50117,USD,50117,MI,FT,China,M,China,0,"Python, AWS, Kubernetes, MLOps",Bachelor,4,Consulting,2024-05-19,2024-07-15,1362,6.3,Advanced Robotics -AI06971,Data Scientist,355672,CHF,320105,EX,CT,Switzerland,L,Philippines,0,"Tableau, SQL, Kubernetes, PyTorch",Master,16,Automotive,2025-04-25,2025-05-27,776,8.2,Machine Intelligence Group -AI06972,Deep Learning Engineer,114352,AUD,154375,MI,PT,Australia,L,Australia,0,"PyTorch, Scala, Azure, AWS, TensorFlow",Master,4,Gaming,2025-01-23,2025-03-12,2361,9.8,Quantum Computing Inc -AI06973,Data Engineer,167395,USD,167395,EX,CT,United States,M,United States,0,"Spark, Git, Computer Vision, Data Visualization",Bachelor,17,Retail,2024-02-18,2024-04-03,683,8.9,Cloud AI Solutions -AI06974,Autonomous Systems Engineer,172621,JPY,18988310,SE,PT,Japan,L,Japan,100,"Python, SQL, R",Associate,6,Energy,2025-04-30,2025-06-08,813,9.7,Algorithmic Solutions -AI06975,AI Architect,64356,USD,64356,MI,CT,Finland,S,Finland,100,"Deep Learning, MLOps, PyTorch, Tableau",Master,2,Finance,2024-11-09,2025-01-14,1866,6.1,Machine Intelligence Group -AI06976,Data Scientist,54970,USD,54970,EX,PT,India,M,Belgium,50,"SQL, TensorFlow, Linux, Tableau, Java",PhD,13,Transportation,2024-09-02,2024-10-04,821,7.6,Autonomous Tech -AI06977,Deep Learning Engineer,101375,CHF,91238,EN,CT,Switzerland,L,Switzerland,100,"R, PyTorch, Mathematics, Hadoop, Azure",Associate,1,Government,2025-02-09,2025-02-28,1818,7.6,Algorithmic Solutions -AI06978,Computer Vision Engineer,162080,USD,162080,EX,CT,Finland,S,Finland,50,"TensorFlow, Docker, Mathematics, Linux, AWS",PhD,11,Telecommunications,2025-01-01,2025-03-02,688,9.3,DataVision Ltd -AI06979,AI Product Manager,81146,USD,81146,SE,FT,South Korea,S,South Korea,100,"Tableau, Git, Docker, PyTorch, Data Visualization",Associate,5,Manufacturing,2024-05-31,2024-06-29,540,8.6,Quantum Computing Inc -AI06980,Autonomous Systems Engineer,144815,USD,144815,SE,PT,United States,S,United States,50,"R, NLP, Java",PhD,8,Transportation,2025-02-02,2025-02-23,1685,7.9,Future Systems -AI06981,ML Ops Engineer,145112,USD,145112,SE,FT,Ireland,M,Ireland,100,"Kubernetes, Git, Deep Learning, PyTorch, Docker",PhD,9,Transportation,2024-12-23,2025-02-09,1411,5.7,Digital Transformation LLC -AI06982,Principal Data Scientist,66759,USD,66759,EX,FL,China,S,China,100,"TensorFlow, Git, Azure, Spark",PhD,12,Finance,2024-11-29,2025-01-31,1327,9.9,Advanced Robotics -AI06983,Machine Learning Engineer,163174,EUR,138698,EX,PT,Germany,S,United Kingdom,100,"Linux, PyTorch, Git, Mathematics, Deep Learning",PhD,11,Energy,2024-05-04,2024-05-22,2045,5.1,AI Innovations -AI06984,Deep Learning Engineer,112919,CHF,101627,EN,CT,Switzerland,L,Switzerland,100,"R, SQL, Azure",Master,1,Transportation,2025-03-31,2025-06-10,625,6.7,Predictive Systems -AI06985,Principal Data Scientist,113118,SGD,147053,MI,PT,Singapore,M,Japan,50,"Git, Data Visualization, Scala, Azure, Kubernetes",Associate,4,Manufacturing,2024-02-20,2024-03-27,1777,8.6,Machine Intelligence Group -AI06986,Robotics Engineer,64270,USD,64270,EN,FL,Sweden,L,Sweden,0,"NLP, Git, Java",Associate,0,Healthcare,2024-07-19,2024-08-27,598,9.2,AI Innovations -AI06987,Deep Learning Engineer,167528,USD,167528,SE,CT,Denmark,M,Denmark,50,"Scala, Azure, Mathematics, PyTorch, Statistics",Master,5,Retail,2024-09-21,2024-10-11,1659,5.8,Smart Analytics -AI06988,ML Ops Engineer,82676,CAD,103345,MI,FL,Canada,S,Sweden,100,"Data Visualization, Spark, R, SQL",Master,4,Technology,2024-02-23,2024-03-21,1707,6.4,Cloud AI Solutions -AI06989,Computer Vision Engineer,148614,EUR,126322,SE,CT,Austria,L,Austria,50,"PyTorch, Kubernetes, Git",Associate,9,Gaming,2024-04-05,2024-05-24,1048,7.8,Autonomous Tech -AI06990,Machine Learning Engineer,75332,USD,75332,MI,CT,Finland,M,Australia,100,"TensorFlow, SQL, R, Deep Learning, NLP",Associate,3,Energy,2024-12-09,2025-01-18,2177,5.7,Quantum Computing Inc -AI06991,Head of AI,170124,CHF,153112,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, MLOps, Kubernetes, PyTorch, NLP",PhD,4,Consulting,2025-01-16,2025-03-25,2424,6.5,DataVision Ltd -AI06992,Principal Data Scientist,103653,USD,103653,MI,FT,Israel,M,Israel,0,"R, Git, Statistics",PhD,2,Automotive,2024-08-22,2024-09-26,1801,6.7,Future Systems -AI06993,AI Architect,30142,USD,30142,MI,FL,India,L,India,0,"TensorFlow, Git, SQL, Hadoop",Associate,4,Telecommunications,2025-01-27,2025-03-03,1476,7.8,Digital Transformation LLC -AI06994,Machine Learning Researcher,54940,USD,54940,EN,CT,South Korea,M,Brazil,100,"Git, R, Computer Vision, Java",Master,1,Government,2024-09-06,2024-09-30,2122,9.9,Machine Intelligence Group -AI06995,Principal Data Scientist,84125,USD,84125,MI,FL,United States,S,United States,0,"Hadoop, Linux, Data Visualization, Tableau",Master,3,Media,2024-05-24,2024-06-23,1222,7.4,Cloud AI Solutions -AI06996,NLP Engineer,221441,EUR,188225,EX,FT,France,L,Nigeria,100,"Git, SQL, Spark, Tableau, Kubernetes",Bachelor,19,Media,2024-11-02,2025-01-11,1718,5.9,Future Systems -AI06997,AI Software Engineer,64993,EUR,55244,EN,FT,Netherlands,S,Hungary,0,"Git, Java, Kubernetes",Bachelor,0,Media,2024-01-23,2024-03-24,2180,5.8,Future Systems -AI06998,Research Scientist,114387,CAD,142984,MI,FL,Canada,L,Canada,100,"Java, Scala, Tableau, NLP",Associate,2,Retail,2024-09-04,2024-10-21,2379,5.8,Quantum Computing Inc -AI06999,Data Analyst,87162,SGD,113311,EN,PT,Singapore,L,Luxembourg,50,"GCP, PyTorch, Python",Master,1,Gaming,2024-08-04,2024-09-10,2232,8.4,Autonomous Tech -AI07000,Head of AI,117970,USD,117970,MI,FL,United States,L,Philippines,100,"Mathematics, Java, Python",Bachelor,2,Finance,2024-03-27,2024-04-27,2075,5.6,AI Innovations -AI07001,AI Research Scientist,111336,USD,111336,SE,CT,Ireland,S,Ireland,0,"Tableau, TensorFlow, Scala, Git, Azure",PhD,7,Telecommunications,2024-03-14,2024-05-02,1486,5.5,Algorithmic Solutions -AI07002,Machine Learning Researcher,86134,GBP,64601,MI,FL,United Kingdom,S,United Kingdom,0,"TensorFlow, AWS, Azure",Associate,4,Energy,2024-10-31,2024-11-26,2104,6.7,Neural Networks Co -AI07003,Data Engineer,159132,USD,159132,EX,CT,Finland,M,Finland,50,"R, MLOps, SQL",PhD,18,Manufacturing,2024-08-31,2024-10-04,1832,9,DataVision Ltd -AI07004,Autonomous Systems Engineer,88313,USD,88313,EN,CT,United States,M,United States,0,"PyTorch, TensorFlow, Azure, AWS",Associate,1,Telecommunications,2024-12-10,2025-02-12,2142,7.1,DeepTech Ventures -AI07005,AI Product Manager,147619,USD,147619,EX,FL,United States,S,United States,0,"Java, SQL, Hadoop, Git, GCP",Associate,17,Education,2024-06-29,2024-07-15,1756,5.6,Quantum Computing Inc -AI07006,Machine Learning Engineer,41968,USD,41968,MI,CT,India,L,India,50,"Data Visualization, Kubernetes, Azure",PhD,4,Media,2025-03-13,2025-05-10,2229,9.9,Neural Networks Co -AI07007,Data Scientist,68997,USD,68997,EN,CT,South Korea,L,New Zealand,50,"TensorFlow, Python, Tableau, GCP",Bachelor,1,Manufacturing,2024-08-04,2024-10-07,2237,6.6,Advanced Robotics -AI07008,Data Scientist,81660,USD,81660,EN,FL,Israel,L,Israel,50,"Git, Deep Learning, SQL, Linux, Kubernetes",Master,0,Government,2024-03-15,2024-03-30,2337,5.7,Future Systems -AI07009,Autonomous Systems Engineer,151107,GBP,113330,SE,CT,United Kingdom,M,United Kingdom,100,"Deep Learning, AWS, MLOps",Master,7,Government,2024-07-07,2024-09-18,1900,5.9,Algorithmic Solutions -AI07010,Deep Learning Engineer,54435,USD,54435,EN,FT,Sweden,M,Egypt,50,"MLOps, SQL, PyTorch, GCP",PhD,0,Healthcare,2025-01-25,2025-03-20,1222,8.2,Cloud AI Solutions -AI07011,NLP Engineer,295862,EUR,251483,EX,FT,Netherlands,L,Netherlands,0,"Hadoop, GCP, Tableau, Docker, Scala",PhD,16,Technology,2024-04-07,2024-05-18,1139,8,TechCorp Inc -AI07012,AI Product Manager,110402,EUR,93842,SE,FL,France,M,France,100,"R, SQL, Mathematics",Master,9,Energy,2024-06-24,2024-07-29,2427,7.1,Algorithmic Solutions -AI07013,Data Scientist,97747,CAD,122184,MI,PT,Canada,M,Finland,0,"TensorFlow, Mathematics, Python",PhD,4,Manufacturing,2024-07-21,2024-09-12,1776,9.7,Cognitive Computing -AI07014,AI Consultant,57591,EUR,48952,EN,FL,Netherlands,M,Netherlands,100,"Hadoop, Data Visualization, Spark, Deep Learning, Statistics",Associate,1,Retail,2024-10-31,2025-01-06,1101,9.9,Machine Intelligence Group -AI07015,Autonomous Systems Engineer,202829,USD,202829,EX,FT,Finland,S,Finland,100,"Kubernetes, Python, Linux, GCP",Associate,11,Finance,2024-02-07,2024-03-12,840,6.5,Machine Intelligence Group -AI07016,Autonomous Systems Engineer,49667,CAD,62084,EN,FT,Canada,M,Canada,0,"Data Visualization, Git, R, AWS",Bachelor,0,Education,2024-10-04,2024-11-11,1038,6.7,DataVision Ltd -AI07017,Principal Data Scientist,107663,CHF,96897,EN,PT,Switzerland,L,Switzerland,50,"PyTorch, SQL, NLP",Bachelor,0,Retail,2025-02-26,2025-04-14,1016,6.2,Neural Networks Co -AI07018,Data Engineer,114200,USD,114200,SE,CT,Israel,S,Singapore,100,"Hadoop, Computer Vision, Java, R, Statistics",Associate,6,Retail,2024-05-17,2024-06-11,2297,6.9,Cloud AI Solutions -AI07019,NLP Engineer,195219,GBP,146414,EX,CT,United Kingdom,L,United Kingdom,50,"PyTorch, Hadoop, R, Linux",Associate,11,Consulting,2024-08-13,2024-08-29,1251,9.3,Quantum Computing Inc -AI07020,Principal Data Scientist,174084,JPY,19149240,EX,CT,Japan,M,Japan,100,"Git, NLP, Tableau, Hadoop",Master,10,Transportation,2024-07-07,2024-08-04,877,5.5,Predictive Systems -AI07021,Computer Vision Engineer,86465,EUR,73495,EN,CT,Austria,L,Austria,100,"PyTorch, Computer Vision, Hadoop, Scala",PhD,1,Energy,2025-01-19,2025-03-16,1607,9.6,Smart Analytics -AI07022,Head of AI,112857,USD,112857,MI,FL,United States,M,United States,50,"Kubernetes, TensorFlow, NLP, MLOps, Git",Master,3,Telecommunications,2024-08-15,2024-10-06,1126,8.7,TechCorp Inc -AI07023,Robotics Engineer,122484,EUR,104111,MI,CT,Netherlands,L,Indonesia,50,"Git, Mathematics, Python, Data Visualization",Associate,2,Transportation,2024-08-19,2024-10-27,814,5.7,Machine Intelligence Group -AI07024,NLP Engineer,165700,USD,165700,SE,CT,United States,M,United States,0,"Git, Tableau, R, SQL, Scala",Associate,7,Gaming,2024-12-28,2025-02-21,656,7.1,Predictive Systems -AI07025,Principal Data Scientist,168066,USD,168066,SE,PT,Denmark,S,Denmark,50,"Spark, MLOps, Python, Tableau",Master,6,Technology,2024-10-29,2024-12-28,1679,7.2,Autonomous Tech -AI07026,AI Software Engineer,76293,SGD,99181,EN,PT,Singapore,S,Singapore,0,"MLOps, Azure, Docker, AWS, NLP",Associate,1,Manufacturing,2024-03-07,2024-03-28,567,7.6,TechCorp Inc -AI07027,Principal Data Scientist,52755,AUD,71219,EN,FL,Australia,S,Nigeria,50,"PyTorch, Docker, Mathematics",Master,1,Telecommunications,2024-11-14,2025-01-10,2140,7.9,DataVision Ltd -AI07028,NLP Engineer,194324,SGD,252621,EX,CT,Singapore,S,Singapore,100,"Java, Python, Statistics",Master,12,Finance,2024-12-08,2025-01-19,1413,5.9,Machine Intelligence Group -AI07029,Deep Learning Engineer,118307,CAD,147884,SE,FT,Canada,M,Canada,100,"TensorFlow, Java, Git",Bachelor,9,Manufacturing,2024-04-03,2024-06-09,977,7.9,Cognitive Computing -AI07030,ML Ops Engineer,96881,AUD,130789,MI,PT,Australia,M,Egypt,0,"Mathematics, Kubernetes, R",Master,4,Consulting,2025-04-08,2025-06-05,628,8.5,Smart Analytics -AI07031,Autonomous Systems Engineer,57804,USD,57804,SE,FT,China,M,China,50,"Git, Python, Statistics, Azure",Bachelor,5,Government,2024-03-12,2024-04-09,1288,6.5,Cloud AI Solutions -AI07032,Autonomous Systems Engineer,51971,USD,51971,EN,PT,Ireland,S,Ireland,100,"Azure, Kubernetes, SQL, PyTorch",Master,0,Government,2025-04-28,2025-06-03,1884,5.3,Predictive Systems -AI07033,Machine Learning Researcher,175177,SGD,227730,SE,PT,Singapore,L,Singapore,50,"MLOps, Mathematics, SQL, Computer Vision, Kubernetes",Bachelor,8,Media,2024-04-08,2024-05-22,1954,7.7,Quantum Computing Inc -AI07034,Deep Learning Engineer,119721,USD,119721,SE,CT,Norway,S,Russia,0,"TensorFlow, Python, Azure, Kubernetes",Master,7,Media,2024-04-28,2024-06-30,812,8.4,Autonomous Tech -AI07035,AI Product Manager,227954,USD,227954,EX,FT,Israel,L,Israel,0,"Java, R, GCP",Associate,17,Education,2024-04-20,2024-06-22,859,8.5,Machine Intelligence Group -AI07036,Autonomous Systems Engineer,78211,USD,78211,EN,PT,United States,L,United States,0,"TensorFlow, MLOps, Hadoop",PhD,1,Transportation,2025-02-01,2025-03-05,1038,8.4,Cloud AI Solutions -AI07037,AI Research Scientist,175370,EUR,149065,SE,FL,Netherlands,L,Netherlands,0,"Statistics, Python, Computer Vision, Kubernetes",Master,6,Consulting,2024-03-13,2024-05-23,1321,8.8,Digital Transformation LLC -AI07038,AI Product Manager,74020,CAD,92525,MI,PT,Canada,S,Canada,50,"PyTorch, Spark, SQL",Bachelor,2,Media,2024-06-29,2024-08-27,932,5.7,Autonomous Tech -AI07039,AI Consultant,66966,GBP,50225,EN,CT,United Kingdom,L,France,0,"SQL, Deep Learning, PyTorch, Java",PhD,0,Education,2024-05-20,2024-07-14,1481,7.2,Advanced Robotics -AI07040,NLP Engineer,73557,EUR,62523,EN,FT,Germany,M,Germany,50,"R, Data Visualization, Linux",Associate,0,Automotive,2024-04-08,2024-05-06,2105,7.3,Future Systems -AI07041,AI Architect,73095,SGD,95024,EN,PT,Singapore,M,Egypt,50,"MLOps, Git, R",Bachelor,1,Healthcare,2024-11-22,2025-01-17,2409,8.5,Advanced Robotics -AI07042,Research Scientist,57811,USD,57811,EN,FL,South Korea,M,South Korea,100,"Python, Linux, Data Visualization, Tableau, R",Master,1,Healthcare,2025-01-01,2025-02-07,1723,7.7,AI Innovations -AI07043,Machine Learning Researcher,235424,EUR,200110,EX,FL,Netherlands,M,Netherlands,100,"Java, Python, Tableau",Master,19,Education,2025-01-26,2025-03-26,1778,9.9,Algorithmic Solutions -AI07044,Robotics Engineer,140023,AUD,189031,SE,FT,Australia,L,Australia,50,"Java, Git, Mathematics",PhD,5,Consulting,2025-04-11,2025-05-25,1371,5.5,AI Innovations -AI07045,Data Engineer,142826,USD,142826,SE,CT,Norway,M,Norway,50,"Deep Learning, Python, TensorFlow, Computer Vision",PhD,9,Energy,2024-02-15,2024-03-20,1317,7.4,Machine Intelligence Group -AI07046,Autonomous Systems Engineer,89624,USD,89624,MI,FL,South Korea,M,Netherlands,0,"Scala, Python, Azure, NLP",Bachelor,3,Transportation,2025-01-13,2025-03-19,1805,5.6,TechCorp Inc -AI07047,Computer Vision Engineer,80501,USD,80501,EN,PT,Denmark,M,Portugal,50,"Deep Learning, Data Visualization, R",Bachelor,0,Finance,2025-03-01,2025-05-01,1126,5.3,Machine Intelligence Group -AI07048,Data Engineer,95043,USD,95043,EN,FT,United States,L,United States,100,"SQL, AWS, Deep Learning, Linux",Associate,0,Finance,2024-04-25,2024-06-03,1627,6.6,Future Systems -AI07049,Deep Learning Engineer,134255,SGD,174532,MI,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning",PhD,2,Automotive,2024-06-30,2024-09-07,913,6.3,Predictive Systems -AI07050,Machine Learning Researcher,108386,CHF,97547,EN,FT,Switzerland,M,Switzerland,100,"Statistics, Tableau, Java, SQL, Python",PhD,0,Transportation,2024-10-25,2024-11-18,1501,5.8,Cloud AI Solutions -AI07051,Robotics Engineer,205581,USD,205581,EX,FL,Israel,M,Israel,50,"Spark, SQL, Python, Statistics",PhD,13,Transportation,2024-12-31,2025-02-20,2163,5.2,Cloud AI Solutions -AI07052,Deep Learning Engineer,115712,EUR,98355,MI,PT,France,L,France,100,"AWS, TensorFlow, Mathematics, SQL",PhD,2,Energy,2024-09-15,2024-10-19,1798,8.3,Predictive Systems -AI07053,AI Software Engineer,41871,USD,41871,MI,FT,China,S,China,0,"Scala, Python, Java, Hadoop",Bachelor,4,Real Estate,2025-03-21,2025-04-04,2356,6.7,DataVision Ltd -AI07054,ML Ops Engineer,89638,CAD,112048,SE,FL,Canada,S,Canada,0,"R, Java, GCP, Spark, Mathematics",Associate,5,Technology,2024-12-15,2025-02-16,2116,8.6,Algorithmic Solutions -AI07055,Machine Learning Engineer,62796,USD,62796,EN,FT,South Korea,L,South Korea,100,"SQL, Tableau, PyTorch",Associate,0,Transportation,2024-01-31,2024-02-28,539,6.6,Algorithmic Solutions -AI07056,AI Product Manager,174278,JPY,19170580,EX,PT,Japan,L,Japan,0,"Python, MLOps, TensorFlow, Git",PhD,13,Media,2024-08-08,2024-10-16,1840,8.2,Neural Networks Co -AI07057,AI Product Manager,236382,JPY,26002020,EX,PT,Japan,M,Argentina,50,"Scala, Tableau, Python, Computer Vision, Deep Learning",PhD,15,Technology,2024-04-06,2024-04-24,821,8.4,Future Systems -AI07058,Computer Vision Engineer,119050,USD,119050,EX,FL,Finland,S,Finland,50,"Spark, Statistics, Computer Vision, Git",Bachelor,15,Technology,2024-09-24,2024-11-06,850,7.1,TechCorp Inc -AI07059,Autonomous Systems Engineer,139306,SGD,181098,SE,PT,Singapore,L,Singapore,50,"Spark, SQL, PyTorch",Bachelor,8,Real Estate,2025-01-10,2025-03-21,723,8,DeepTech Ventures -AI07060,AI Research Scientist,146203,USD,146203,SE,CT,Denmark,M,Denmark,0,"Linux, GCP, Python, Data Visualization, Mathematics",Master,6,Energy,2024-05-06,2024-07-05,1191,8.2,Predictive Systems -AI07061,Research Scientist,91867,EUR,78087,MI,PT,Austria,M,Ireland,100,"Scala, MLOps, Docker",Associate,3,Retail,2024-08-26,2024-10-10,623,7.2,Cloud AI Solutions -AI07062,NLP Engineer,139325,USD,139325,SE,PT,Norway,M,Norway,100,"NLP, PyTorch, TensorFlow",Master,5,Automotive,2024-08-29,2024-11-03,1668,9.3,Predictive Systems -AI07063,Robotics Engineer,368470,USD,368470,EX,PT,Norway,L,Australia,0,"Docker, Deep Learning, SQL",Associate,11,Technology,2024-08-31,2024-10-09,1117,8.5,Digital Transformation LLC -AI07064,AI Research Scientist,79264,USD,79264,MI,FL,South Korea,M,Germany,50,"Java, Python, Kubernetes, Mathematics",Master,2,Technology,2025-04-16,2025-06-02,1050,6,Future Systems -AI07065,Robotics Engineer,213820,USD,213820,EX,CT,Finland,L,Sweden,0,"Kubernetes, Linux, Mathematics, Java",Associate,17,Consulting,2024-06-11,2024-07-05,1605,8.6,Future Systems -AI07066,AI Consultant,91365,AUD,123343,MI,CT,Australia,S,Ireland,100,"Git, Scala, GCP, Computer Vision",Bachelor,2,Consulting,2024-10-05,2024-11-11,634,7.6,Predictive Systems -AI07067,Machine Learning Researcher,135173,EUR,114897,SE,PT,Germany,L,Germany,100,"PyTorch, Linux, Java",Associate,6,Finance,2025-01-21,2025-03-27,1073,6,Smart Analytics -AI07068,Deep Learning Engineer,68488,AUD,92459,EN,FT,Australia,S,Australia,50,"R, Docker, Scala, Statistics, MLOps",Bachelor,0,Government,2024-07-16,2024-09-04,1631,6.4,Cloud AI Solutions -AI07069,AI Software Engineer,117333,EUR,99733,SE,CT,Austria,S,Austria,100,"Scala, TensorFlow, Python, PyTorch",Associate,9,Transportation,2024-09-15,2024-10-05,1294,5.1,Digital Transformation LLC -AI07070,Deep Learning Engineer,99292,USD,99292,MI,PT,Finland,L,Finland,0,"Kubernetes, Scala, Statistics",Associate,3,Healthcare,2024-07-13,2024-09-08,939,8.4,Cloud AI Solutions -AI07071,NLP Engineer,215599,USD,215599,SE,CT,Denmark,L,Denmark,100,"MLOps, Git, PyTorch, Java, Scala",Associate,8,Transportation,2024-09-25,2024-11-01,1492,7,TechCorp Inc -AI07072,ML Ops Engineer,159635,USD,159635,EX,FL,South Korea,M,South Korea,0,"Kubernetes, PyTorch, Docker",PhD,10,Real Estate,2024-05-27,2024-07-16,1395,9,Autonomous Tech -AI07073,AI Product Manager,108321,AUD,146233,MI,FL,Australia,L,Brazil,0,"Computer Vision, Hadoop, Git, Kubernetes",Master,2,Real Estate,2024-05-07,2024-06-10,1705,5.7,Smart Analytics -AI07074,Computer Vision Engineer,76476,CAD,95595,MI,FT,Canada,M,Canada,100,"SQL, Python, Docker, AWS",Associate,2,Consulting,2025-01-28,2025-03-03,543,8.9,AI Innovations -AI07075,Head of AI,83952,AUD,113335,MI,PT,Australia,M,Australia,50,"Kubernetes, Azure, AWS, Deep Learning, Java",Associate,2,Real Estate,2025-03-03,2025-04-06,2076,6.5,Advanced Robotics -AI07076,AI Research Scientist,235700,USD,235700,EX,FT,Israel,L,Ghana,0,"Kubernetes, Python, NLP",Associate,12,Energy,2024-04-21,2024-06-12,1601,8.1,Predictive Systems -AI07077,AI Specialist,131627,USD,131627,SE,FT,United States,M,United States,100,"Hadoop, Kubernetes, Statistics",PhD,6,Real Estate,2024-07-22,2024-08-30,758,7.7,Smart Analytics -AI07078,AI Architect,178535,EUR,151755,EX,CT,Austria,M,Japan,0,"MLOps, Git, Java, Kubernetes, Computer Vision",PhD,12,Automotive,2024-11-13,2025-01-13,1594,5.8,Advanced Robotics -AI07079,AI Architect,209551,USD,209551,EX,PT,Denmark,S,Denmark,0,"Hadoop, Python, Statistics, Linux, Data Visualization",Master,11,Real Estate,2024-03-14,2024-05-04,772,9.6,Machine Intelligence Group -AI07080,AI Software Engineer,84533,EUR,71853,MI,CT,Austria,L,Austria,100,"Python, GCP, TensorFlow",Associate,4,Healthcare,2024-09-07,2024-10-12,860,6.1,Neural Networks Co -AI07081,AI Architect,25457,USD,25457,EN,FL,China,M,Chile,0,"NLP, Linux, SQL",Bachelor,0,Finance,2024-11-01,2024-12-12,1856,5.6,DataVision Ltd -AI07082,Data Analyst,91380,USD,91380,EN,PT,Denmark,M,Denmark,0,"Scala, Tableau, Java, SQL",Associate,0,Media,2024-10-13,2024-11-04,925,7.6,Predictive Systems -AI07083,NLP Engineer,60940,GBP,45705,EN,FT,United Kingdom,S,United Kingdom,50,"Scala, GCP, Tableau, Mathematics",Bachelor,1,Real Estate,2024-11-10,2025-01-20,867,7.8,Smart Analytics -AI07084,Machine Learning Researcher,86902,USD,86902,MI,FL,United States,M,India,50,"R, GCP, Azure, SQL",Associate,3,Consulting,2024-05-04,2024-05-31,538,5.8,Smart Analytics -AI07085,AI Product Manager,119818,USD,119818,MI,PT,United States,M,China,50,"NLP, Data Visualization, Java",Master,3,Energy,2024-11-25,2024-12-30,1964,6.1,Quantum Computing Inc -AI07086,Autonomous Systems Engineer,35047,USD,35047,MI,FT,India,L,India,50,"Python, SQL, TensorFlow, NLP, Deep Learning",Bachelor,3,Real Estate,2024-05-15,2024-06-24,1946,7.6,DataVision Ltd -AI07087,Machine Learning Researcher,175805,GBP,131854,EX,CT,United Kingdom,M,United Kingdom,100,"Statistics, Hadoop, NLP",Bachelor,10,Healthcare,2024-07-02,2024-08-24,1033,7.7,DeepTech Ventures -AI07088,AI Research Scientist,45668,EUR,38818,EN,PT,France,S,France,100,"Azure, MLOps, Scala",Associate,1,Real Estate,2024-05-28,2024-06-20,1406,6.6,Predictive Systems -AI07089,Research Scientist,149817,CAD,187271,EX,PT,Canada,S,Canada,50,"R, Hadoop, MLOps, Java",Bachelor,18,Finance,2024-05-02,2024-06-25,957,6.3,Machine Intelligence Group -AI07090,ML Ops Engineer,82947,GBP,62210,EN,FT,United Kingdom,M,Hungary,50,"Python, Java, Data Visualization, Statistics, Tableau",PhD,0,Education,2024-08-15,2024-09-15,2320,8.3,Algorithmic Solutions -AI07091,AI Research Scientist,85406,CHF,76865,EN,CT,Switzerland,S,Latvia,50,"SQL, AWS, NLP, Scala",Bachelor,1,Healthcare,2024-10-15,2024-11-06,1504,5.9,TechCorp Inc -AI07092,Autonomous Systems Engineer,87146,USD,87146,MI,FL,Ireland,M,Ireland,0,"MLOps, Scala, R, Azure, Computer Vision",PhD,3,Healthcare,2024-06-08,2024-08-16,2101,6.4,Predictive Systems -AI07093,NLP Engineer,69088,AUD,93269,EN,PT,Australia,S,Australia,0,"SQL, Mathematics, Spark, Kubernetes, Git",Associate,0,Gaming,2024-04-07,2024-05-01,1029,7.1,Neural Networks Co -AI07094,AI Consultant,37599,USD,37599,MI,FL,China,S,Romania,100,"Python, TensorFlow, Git, AWS",PhD,3,Government,2024-06-10,2024-08-03,1308,7.8,Cognitive Computing -AI07095,Computer Vision Engineer,87778,USD,87778,EX,FL,China,S,China,0,"NLP, Data Visualization, Tableau, Linux, PyTorch",Bachelor,12,Government,2024-07-03,2024-09-07,578,7.8,Smart Analytics -AI07096,AI Research Scientist,141646,USD,141646,SE,FL,Israel,L,Israel,0,"Azure, Java, R, Data Visualization, Computer Vision",Master,8,Telecommunications,2024-10-11,2024-11-10,784,8,DeepTech Ventures -AI07097,Head of AI,64214,USD,64214,EN,FL,Finland,S,Poland,0,"Docker, Azure, Deep Learning",Bachelor,1,Consulting,2025-02-10,2025-04-06,2117,5.9,DataVision Ltd -AI07098,Data Engineer,167315,GBP,125486,EX,PT,United Kingdom,M,United Kingdom,50,"Git, Data Visualization, Kubernetes, Mathematics, PyTorch",Master,17,Finance,2024-08-14,2024-10-19,1552,5.7,Digital Transformation LLC -AI07099,AI Consultant,48070,USD,48070,SE,PT,India,L,Poland,50,"SQL, AWS, Data Visualization, Docker, PyTorch",PhD,5,Consulting,2024-10-13,2024-10-27,1908,5.6,Quantum Computing Inc -AI07100,Autonomous Systems Engineer,274846,USD,274846,EX,PT,Norway,M,Norway,0,"Scala, Kubernetes, Data Visualization",Master,11,Media,2024-12-05,2025-01-30,855,9.1,Predictive Systems -AI07101,Deep Learning Engineer,116699,SGD,151709,MI,FT,Singapore,M,Brazil,100,"Kubernetes, Python, Spark, Data Visualization, Deep Learning",Bachelor,2,Automotive,2024-02-10,2024-04-14,1991,8.2,Cloud AI Solutions -AI07102,AI Architect,192135,GBP,144101,EX,CT,United Kingdom,M,United Kingdom,0,"Scala, Linux, Docker, Spark",Master,15,Government,2024-04-27,2024-05-20,1558,8.3,Neural Networks Co -AI07103,Computer Vision Engineer,129329,EUR,109930,SE,PT,Netherlands,L,Ireland,100,"SQL, Scala, Computer Vision",Bachelor,5,Healthcare,2024-09-21,2024-10-17,1464,7,Cognitive Computing -AI07104,AI Architect,119619,USD,119619,SE,FL,Norway,S,New Zealand,100,"Docker, Kubernetes, Tableau, Mathematics",PhD,9,Automotive,2024-01-30,2024-03-17,1182,5.4,Smart Analytics -AI07105,Machine Learning Researcher,164906,CHF,148415,SE,FL,Switzerland,M,Switzerland,50,"R, SQL, TensorFlow, Tableau, NLP",PhD,7,Retail,2025-04-22,2025-06-10,1394,8.5,Cloud AI Solutions -AI07106,Data Analyst,93246,EUR,79259,SE,PT,Germany,S,Australia,50,"Python, MLOps, Deep Learning, Computer Vision, GCP",Bachelor,7,Education,2024-12-17,2025-01-07,2269,9.7,Digital Transformation LLC -AI07107,Data Engineer,84575,USD,84575,EX,FL,India,L,Argentina,50,"Python, Computer Vision, Java",Associate,13,Transportation,2025-03-25,2025-05-15,1161,5.1,Advanced Robotics -AI07108,AI Specialist,120060,CAD,150075,SE,FL,Canada,M,Canada,0,"Data Visualization, Hadoop, Python, Git",Bachelor,9,Real Estate,2025-04-25,2025-07-07,907,6,Cognitive Computing -AI07109,Deep Learning Engineer,122916,USD,122916,SE,FT,Israel,S,South Korea,100,"Data Visualization, GCP, Linux, PyTorch, Git",Bachelor,5,Manufacturing,2025-02-16,2025-04-20,1429,6.1,Digital Transformation LLC -AI07110,Autonomous Systems Engineer,86361,SGD,112269,MI,CT,Singapore,M,Romania,0,"Python, GCP, Scala, R",Associate,4,Finance,2024-11-16,2024-12-14,741,8.5,Digital Transformation LLC -AI07111,Robotics Engineer,114870,CAD,143588,SE,CT,Canada,S,Canada,100,"PyTorch, Azure, AWS",Associate,8,Education,2025-04-11,2025-05-31,671,9.5,Cognitive Computing -AI07112,Autonomous Systems Engineer,174174,JPY,19159140,EX,FL,Japan,L,Vietnam,100,"Azure, Python, TensorFlow",Bachelor,15,Healthcare,2025-02-06,2025-03-21,1297,6.4,Future Systems -AI07113,Robotics Engineer,174611,USD,174611,EX,CT,Finland,M,Czech Republic,0,"Azure, Git, PyTorch",PhD,18,Technology,2025-04-13,2025-05-02,2132,9.4,Cloud AI Solutions -AI07114,AI Product Manager,79305,USD,79305,MI,FT,Ireland,S,China,100,"R, MLOps, Scala, Mathematics",Associate,4,Government,2024-08-13,2024-09-02,2145,8.8,Neural Networks Co -AI07115,AI Product Manager,104456,USD,104456,SE,FT,South Korea,M,South Korea,50,"Python, Deep Learning, MLOps, TensorFlow",PhD,5,Government,2024-04-09,2024-05-26,1561,9.2,Predictive Systems -AI07116,AI Product Manager,134807,USD,134807,SE,FT,Israel,M,Romania,100,"SQL, AWS, PyTorch",Bachelor,6,Transportation,2025-03-14,2025-04-18,1452,9.1,TechCorp Inc -AI07117,AI Architect,149312,USD,149312,MI,FT,Denmark,L,Denmark,100,"Deep Learning, PyTorch, Mathematics",Master,2,Education,2024-06-26,2024-07-13,549,9.2,DataVision Ltd -AI07118,Research Scientist,138822,USD,138822,MI,CT,Denmark,L,Denmark,100,"Scala, Docker, Azure, Python",Master,4,Telecommunications,2024-04-08,2024-06-11,1428,6.6,Smart Analytics -AI07119,AI Research Scientist,87558,AUD,118203,EN,CT,Australia,L,Australia,0,"NLP, Kubernetes, AWS",PhD,1,Transportation,2024-06-11,2024-08-23,1979,7.5,Neural Networks Co -AI07120,AI Software Engineer,48577,EUR,41290,EN,PT,France,S,Russia,50,"TensorFlow, Scala, Deep Learning, Git",Associate,0,Gaming,2024-09-26,2024-10-11,617,7.6,AI Innovations -AI07121,Machine Learning Engineer,247655,EUR,210507,EX,PT,Germany,M,Germany,50,"Azure, Git, Python",PhD,14,Automotive,2024-07-28,2024-08-16,1618,6.5,Quantum Computing Inc -AI07122,Robotics Engineer,108278,GBP,81209,MI,PT,United Kingdom,M,United Kingdom,50,"Scala, R, SQL, AWS, Tableau",Master,2,Manufacturing,2024-05-03,2024-06-19,799,9.8,TechCorp Inc -AI07123,NLP Engineer,78812,EUR,66990,EN,FL,Germany,L,Germany,0,"R, AWS, Linux",Associate,0,Finance,2025-03-22,2025-05-11,1619,6.9,AI Innovations -AI07124,AI Specialist,116018,USD,116018,MI,PT,Sweden,L,Sweden,0,"PyTorch, Scala, Computer Vision, Mathematics",Bachelor,3,Automotive,2024-04-25,2024-06-25,2267,6.5,Algorithmic Solutions -AI07125,AI Research Scientist,27858,USD,27858,EN,FL,India,M,India,0,"SQL, R, PyTorch",Master,1,Gaming,2024-11-22,2025-01-20,1457,7.7,Cloud AI Solutions -AI07126,AI Consultant,60002,JPY,6600220,EN,CT,Japan,S,Japan,50,"Scala, PyTorch, Statistics, Spark",PhD,0,Government,2025-03-31,2025-05-08,660,6,DeepTech Ventures -AI07127,AI Specialist,167636,CHF,150872,SE,CT,Switzerland,L,Switzerland,0,"Python, Linux, Hadoop, Statistics, Mathematics",Associate,5,Real Estate,2024-02-19,2024-04-15,2370,7.1,Cloud AI Solutions -AI07128,AI Research Scientist,89617,USD,89617,MI,PT,Norway,S,Norway,0,"SQL, GCP, Python, Java, Git",Master,4,Media,2024-10-28,2024-12-24,2284,6.2,Cognitive Computing -AI07129,AI Consultant,133164,EUR,113189,SE,PT,France,L,Germany,100,"Computer Vision, Python, MLOps",Associate,7,Government,2025-03-09,2025-03-25,1886,9.1,Machine Intelligence Group -AI07130,ML Ops Engineer,91502,USD,91502,MI,PT,Finland,M,Finland,0,"Scala, Hadoop, AWS, Spark",Associate,2,Education,2024-04-01,2024-06-05,2387,5.4,Digital Transformation LLC -AI07131,AI Specialist,127869,USD,127869,SE,CT,South Korea,L,South Korea,0,"AWS, Python, Scala, Data Visualization",PhD,7,Manufacturing,2025-02-18,2025-04-04,773,9.6,Predictive Systems -AI07132,AI Architect,127426,CHF,114683,EN,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, NLP",Bachelor,0,Finance,2024-07-27,2024-10-02,1623,6.4,Neural Networks Co -AI07133,Data Analyst,210284,SGD,273369,EX,CT,Singapore,L,Singapore,50,"Java, TensorFlow, Statistics",Master,15,Gaming,2024-06-15,2024-08-07,2166,8.8,Machine Intelligence Group -AI07134,Machine Learning Engineer,78163,USD,78163,EN,PT,Ireland,M,Ireland,50,"SQL, Python, TensorFlow, PyTorch",Bachelor,1,Manufacturing,2024-07-27,2024-08-17,510,9.5,Predictive Systems -AI07135,AI Software Engineer,134757,USD,134757,MI,PT,Norway,L,China,50,"Scala, Mathematics, Git",Associate,4,Manufacturing,2024-08-27,2024-10-09,1181,8.6,TechCorp Inc -AI07136,Autonomous Systems Engineer,71562,CAD,89453,MI,PT,Canada,S,Canada,0,"Hadoop, R, Linux, Computer Vision",Bachelor,4,Gaming,2024-08-25,2024-09-20,2480,6.7,DeepTech Ventures -AI07137,Machine Learning Engineer,47242,CAD,59053,EN,FL,Canada,S,Canada,100,"AWS, Docker, GCP",Master,1,Automotive,2024-06-05,2024-07-01,1580,5.9,DataVision Ltd -AI07138,Head of AI,57033,USD,57033,EX,FT,India,M,Mexico,0,"Scala, PyTorch, Statistics",Bachelor,16,Transportation,2025-02-19,2025-04-04,1212,7,Quantum Computing Inc -AI07139,Data Analyst,119717,USD,119717,SE,PT,Sweden,S,Sweden,100,"GCP, TensorFlow, Python, Kubernetes",PhD,5,Healthcare,2024-03-04,2024-04-11,1807,7.8,Digital Transformation LLC -AI07140,Data Analyst,127727,USD,127727,SE,FL,Sweden,S,Sweden,0,"AWS, PyTorch, Java",Associate,9,Transportation,2024-03-12,2024-05-05,1142,5.6,DeepTech Ventures -AI07141,Machine Learning Engineer,78754,USD,78754,EN,CT,Finland,L,Finland,50,"NLP, SQL, Mathematics, MLOps, PyTorch",Bachelor,1,Energy,2024-10-05,2024-11-27,1435,9.9,Advanced Robotics -AI07142,Autonomous Systems Engineer,76900,USD,76900,MI,FL,Finland,M,Finland,50,"Kubernetes, PyTorch, Git, Linux",Bachelor,3,Government,2024-01-01,2024-01-16,1848,9.7,Algorithmic Solutions -AI07143,NLP Engineer,140463,USD,140463,SE,FT,Ireland,L,Ireland,50,"Data Visualization, TensorFlow, SQL, Git, Scala",PhD,8,Government,2024-04-01,2024-05-10,2156,6.9,Cognitive Computing -AI07144,AI Software Engineer,107972,AUD,145762,SE,FL,Australia,S,Romania,0,"TensorFlow, SQL, Mathematics, Linux",Associate,5,Retail,2025-02-04,2025-02-26,1598,9.4,Machine Intelligence Group -AI07145,Deep Learning Engineer,210162,USD,210162,EX,PT,United States,L,United States,100,"Java, Computer Vision, Python, Hadoop, Scala",Associate,12,Manufacturing,2025-03-06,2025-05-12,2178,9.7,Quantum Computing Inc -AI07146,Data Analyst,199015,CAD,248769,EX,PT,Canada,S,Egypt,50,"Git, TensorFlow, Mathematics, Spark",Master,13,Retail,2024-12-08,2025-02-05,722,7.8,DeepTech Ventures -AI07147,Data Analyst,214251,USD,214251,EX,PT,Ireland,M,Argentina,0,"Python, MLOps, GCP, Statistics, Linux",Master,14,Automotive,2024-04-13,2024-05-26,838,6.6,DataVision Ltd -AI07148,AI Research Scientist,200251,USD,200251,EX,FT,Sweden,M,Sweden,50,"MLOps, Hadoop, NLP, Data Visualization, R",Master,17,Government,2025-02-01,2025-04-09,693,10,Predictive Systems -AI07149,Machine Learning Engineer,56919,AUD,76841,EN,CT,Australia,S,Australia,0,"R, SQL, Git, Mathematics, Kubernetes",Bachelor,1,Technology,2024-06-07,2024-07-31,605,8.9,Quantum Computing Inc -AI07150,ML Ops Engineer,52483,USD,52483,EN,FT,Sweden,M,Sweden,0,"Spark, Mathematics, Data Visualization",Associate,1,Retail,2025-03-01,2025-03-18,2260,8.9,DataVision Ltd -AI07151,Computer Vision Engineer,124533,USD,124533,SE,CT,United States,S,South Africa,0,"Python, TensorFlow, Hadoop, Java",PhD,9,Telecommunications,2024-01-03,2024-01-19,1465,5.4,Future Systems -AI07152,NLP Engineer,122990,AUD,166037,MI,FT,Australia,L,Australia,100,"MLOps, Scala, Statistics",Associate,2,Finance,2025-02-01,2025-03-26,1567,9.2,Predictive Systems -AI07153,Head of AI,149199,USD,149199,EX,PT,Sweden,M,Chile,0,"PyTorch, Scala, Statistics",Bachelor,12,Energy,2024-10-24,2024-11-07,1675,6.6,Neural Networks Co -AI07154,NLP Engineer,82914,EUR,70477,MI,CT,Germany,S,Latvia,100,"Tableau, PyTorch, Kubernetes, GCP, AWS",Bachelor,3,Government,2024-02-19,2024-04-08,1754,5.9,Advanced Robotics -AI07155,Data Scientist,73131,EUR,62161,EN,PT,Austria,M,New Zealand,100,"Azure, Deep Learning, Git, Hadoop",Bachelor,1,Automotive,2024-03-26,2024-04-14,1533,5.3,Algorithmic Solutions -AI07156,AI Software Engineer,84202,JPY,9262220,EN,PT,Japan,M,Japan,50,"Spark, Docker, GCP, AWS, Hadoop",Bachelor,0,Real Estate,2024-11-15,2024-12-02,1057,8.8,Predictive Systems -AI07157,Autonomous Systems Engineer,196071,GBP,147053,EX,PT,United Kingdom,S,Kenya,0,"Linux, SQL, Deep Learning, Python, R",Associate,17,Transportation,2024-06-19,2024-08-27,741,8.2,Algorithmic Solutions -AI07158,AI Software Engineer,56307,USD,56307,EN,PT,Israel,M,Israel,100,"Python, Docker, Hadoop, Git",Bachelor,0,Real Estate,2025-01-27,2025-03-14,1013,6.1,Algorithmic Solutions -AI07159,Robotics Engineer,118127,USD,118127,EX,PT,China,L,China,0,"Python, Docker, MLOps",PhD,10,Energy,2024-12-20,2025-01-15,788,6.3,Cloud AI Solutions -AI07160,Deep Learning Engineer,286081,AUD,386209,EX,CT,Australia,L,Australia,0,"Statistics, Spark, TensorFlow, Linux, Docker",PhD,10,Automotive,2025-01-01,2025-02-22,1102,7.4,DataVision Ltd -AI07161,Data Analyst,38151,USD,38151,MI,FT,China,S,China,0,"PyTorch, TensorFlow, Statistics, Mathematics",Associate,4,Media,2024-10-09,2024-11-24,633,5.2,Cloud AI Solutions -AI07162,AI Product Manager,51436,JPY,5657960,EN,PT,Japan,S,Japan,0,"SQL, GCP, Kubernetes, Docker, Mathematics",Master,1,Manufacturing,2025-02-04,2025-02-20,1703,5.6,Future Systems -AI07163,Head of AI,179375,CHF,161438,MI,PT,Switzerland,L,New Zealand,0,"Python, Computer Vision, Linux, Azure, Deep Learning",Bachelor,3,Real Estate,2024-10-28,2024-12-07,501,9.2,Neural Networks Co -AI07164,AI Research Scientist,224945,USD,224945,EX,FL,Israel,M,Israel,100,"Docker, SQL, PyTorch, Java",PhD,16,Education,2024-08-28,2024-10-23,2317,9.1,Machine Intelligence Group -AI07165,AI Architect,199077,USD,199077,EX,FT,Sweden,S,India,100,"Computer Vision, Tableau, Data Visualization",Associate,14,Retail,2024-11-14,2024-12-25,2448,6.7,Cognitive Computing -AI07166,Data Engineer,154017,USD,154017,SE,PT,United States,L,United States,50,"Python, SQL, Spark, MLOps, TensorFlow",Associate,9,Transportation,2024-08-07,2024-09-11,1991,6.4,AI Innovations -AI07167,Data Engineer,187633,JPY,20639630,EX,CT,Japan,S,Japan,100,"Tableau, Scala, NLP, TensorFlow",Bachelor,17,Consulting,2024-09-28,2024-10-12,1306,8.4,Cloud AI Solutions -AI07168,Research Scientist,113467,USD,113467,MI,FL,Norway,M,Norway,50,"Azure, AWS, NLP, Deep Learning, GCP",Associate,4,Manufacturing,2024-02-16,2024-03-31,1916,8.6,Future Systems -AI07169,AI Product Manager,97170,USD,97170,MI,FL,Sweden,M,Sweden,100,"Kubernetes, GCP, SQL",PhD,4,Consulting,2024-07-01,2024-08-18,1337,6,Autonomous Tech -AI07170,AI Specialist,117600,USD,117600,MI,FT,Norway,S,Norway,50,"Java, Azure, Kubernetes",PhD,2,Technology,2024-09-11,2024-11-01,536,5.1,Neural Networks Co -AI07171,ML Ops Engineer,175430,CAD,219288,EX,CT,Canada,S,Canada,100,"Hadoop, R, SQL",Master,13,Finance,2025-03-17,2025-05-12,2082,9.2,Advanced Robotics -AI07172,Research Scientist,92546,EUR,78664,MI,FL,Netherlands,L,Netherlands,0,"R, Java, SQL",PhD,4,Transportation,2025-03-03,2025-03-17,1865,5.2,Cloud AI Solutions -AI07173,NLP Engineer,78042,USD,78042,MI,FL,United States,S,United States,100,"Python, GCP, TensorFlow, AWS, Deep Learning",Associate,2,Automotive,2024-03-21,2024-04-07,1251,6.2,DataVision Ltd -AI07174,Head of AI,60141,USD,60141,SE,FT,China,S,China,0,"Azure, AWS, Deep Learning, Computer Vision, GCP",PhD,5,Education,2025-01-03,2025-02-16,834,9.5,DeepTech Ventures -AI07175,Computer Vision Engineer,74219,EUR,63086,MI,FT,France,M,France,100,"Spark, NLP, Scala, PyTorch",Master,4,Gaming,2024-11-06,2025-01-03,577,5.7,Future Systems -AI07176,Data Scientist,117670,USD,117670,SE,PT,Finland,M,Finland,0,"Azure, TensorFlow, SQL, Tableau, Deep Learning",Associate,9,Manufacturing,2024-03-07,2024-03-25,585,9.5,Predictive Systems -AI07177,AI Product Manager,43045,USD,43045,EN,PT,South Korea,S,South Korea,100,"Mathematics, Data Visualization, Git, Linux",Associate,0,Healthcare,2024-05-22,2024-06-18,1964,5.9,Future Systems -AI07178,Computer Vision Engineer,204977,USD,204977,EX,FT,Israel,L,Israel,0,"NLP, Docker, Tableau, TensorFlow",Master,13,Retail,2024-01-23,2024-04-01,1912,8.8,Autonomous Tech -AI07179,Data Scientist,99117,USD,99117,MI,PT,Sweden,S,Sweden,50,"Azure, TensorFlow, AWS, Linux",Associate,3,Technology,2024-08-07,2024-08-30,1543,7.4,Autonomous Tech -AI07180,AI Product Manager,71043,USD,71043,EN,FT,Ireland,L,Ireland,50,"Data Visualization, Python, Spark, MLOps",Associate,1,Healthcare,2024-04-28,2024-07-01,2161,9.5,Algorithmic Solutions -AI07181,Machine Learning Engineer,245455,SGD,319092,EX,FL,Singapore,M,Singapore,0,"Git, Azure, Scala",PhD,19,Government,2025-04-25,2025-05-26,1625,7.6,Future Systems -AI07182,NLP Engineer,100152,USD,100152,MI,FL,South Korea,L,South Korea,50,"Java, Spark, Kubernetes",Bachelor,2,Government,2025-03-14,2025-04-16,529,6.5,Advanced Robotics -AI07183,Machine Learning Researcher,184471,EUR,156800,SE,PT,Netherlands,L,Singapore,100,"Python, MLOps, Statistics, Mathematics, Kubernetes",Associate,5,Gaming,2025-02-09,2025-04-13,1628,6.2,Future Systems -AI07184,Research Scientist,192741,EUR,163830,EX,FL,Austria,L,India,100,"Scala, Tableau, SQL, AWS",PhD,14,Real Estate,2024-12-25,2025-01-21,893,6.8,Neural Networks Co -AI07185,Autonomous Systems Engineer,130456,USD,130456,SE,FT,Norway,S,Norway,0,"Mathematics, Spark, NLP, Linux, Git",PhD,7,Healthcare,2025-03-21,2025-04-26,1191,8,Neural Networks Co -AI07186,ML Ops Engineer,131122,USD,131122,MI,CT,Denmark,M,Denmark,50,"Scala, Docker, Kubernetes",Associate,3,Gaming,2024-06-15,2024-08-08,2321,6.7,TechCorp Inc -AI07187,AI Research Scientist,92768,USD,92768,MI,FT,Ireland,S,Ireland,0,"Mathematics, R, SQL",Master,4,Finance,2024-08-20,2024-10-19,774,9.9,DeepTech Ventures -AI07188,AI Architect,117822,USD,117822,SE,FL,Israel,M,Israel,0,"Python, Spark, NLP, SQL, AWS",Associate,7,Telecommunications,2024-07-06,2024-09-11,690,9.3,Future Systems -AI07189,Data Scientist,220795,EUR,187676,EX,CT,Austria,L,Austria,100,"Kubernetes, Python, Tableau",Master,15,Transportation,2024-07-06,2024-08-04,1166,8.1,Digital Transformation LLC -AI07190,AI Specialist,71908,CAD,89885,MI,CT,Canada,M,Canada,0,"Python, TensorFlow, MLOps, Linux, Hadoop",Bachelor,4,Telecommunications,2024-06-19,2024-07-25,1717,9,DeepTech Ventures -AI07191,AI Consultant,217854,USD,217854,EX,FL,Denmark,L,Denmark,0,"Statistics, AWS, Hadoop, Docker, GCP",PhD,19,Media,2024-05-24,2024-07-28,2421,9.4,Machine Intelligence Group -AI07192,Head of AI,50633,JPY,5569630,EN,CT,Japan,S,Japan,0,"R, PyTorch, GCP",Master,0,Manufacturing,2024-05-15,2024-07-20,1102,7,Digital Transformation LLC -AI07193,Data Scientist,67836,CAD,84795,EN,CT,Canada,S,Indonesia,100,"Azure, Python, NLP, Docker",Bachelor,0,Telecommunications,2025-02-13,2025-04-05,2052,7.7,Autonomous Tech -AI07194,Deep Learning Engineer,120724,AUD,162977,MI,PT,Australia,L,Australia,50,"Scala, Java, Kubernetes, Mathematics",PhD,2,Government,2024-11-22,2025-01-30,1133,6.4,Quantum Computing Inc -AI07195,Head of AI,117611,USD,117611,MI,FL,Denmark,S,Denmark,50,"SQL, Mathematics, R, PyTorch",Bachelor,4,Consulting,2024-11-01,2025-01-04,2446,9.4,Autonomous Tech -AI07196,Autonomous Systems Engineer,143600,USD,143600,EX,CT,Ireland,S,Ireland,50,"MLOps, Python, Statistics",Master,12,Automotive,2024-11-11,2025-01-08,907,7.1,Advanced Robotics -AI07197,Deep Learning Engineer,54479,SGD,70823,EN,FL,Singapore,M,Singapore,50,"MLOps, Linux, Azure",Bachelor,0,Manufacturing,2024-06-15,2024-07-18,1974,6.7,Future Systems -AI07198,AI Research Scientist,234608,JPY,25806880,EX,FL,Japan,S,Japan,50,"Spark, Python, Docker, GCP",Associate,17,Telecommunications,2024-10-08,2024-12-16,558,8,Cognitive Computing -AI07199,Computer Vision Engineer,58879,EUR,50047,EN,FL,Germany,L,Germany,100,"TensorFlow, Spark, PyTorch, Git",Master,0,Government,2025-01-03,2025-02-24,1177,7.5,Cloud AI Solutions -AI07200,Principal Data Scientist,94161,USD,94161,MI,FT,Denmark,S,Denmark,50,"Java, SQL, Tableau, Azure, Spark",Associate,3,Energy,2024-06-30,2024-09-02,1398,5.2,Autonomous Tech -AI07201,Head of AI,83285,USD,83285,MI,FL,Ireland,S,Ireland,50,"R, Java, Spark, TensorFlow, Kubernetes",Master,3,Retail,2025-03-07,2025-04-21,2452,8.8,Neural Networks Co -AI07202,AI Software Engineer,203713,AUD,275013,EX,FL,Australia,M,Australia,50,"Mathematics, Kubernetes, MLOps",PhD,14,Transportation,2024-11-21,2025-01-04,594,7.1,Autonomous Tech -AI07203,Data Scientist,31793,USD,31793,MI,PT,China,S,China,100,"MLOps, Docker, Linux, Tableau, Data Visualization",Master,2,Government,2024-05-21,2024-06-24,718,5.4,DataVision Ltd -AI07204,Principal Data Scientist,48887,USD,48887,SE,PT,India,L,India,50,"PyTorch, Tableau, Hadoop, AWS",PhD,9,Technology,2025-04-24,2025-06-04,1126,8.2,Digital Transformation LLC -AI07205,Principal Data Scientist,106359,AUD,143585,MI,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, SQL, GCP",Master,4,Technology,2025-03-20,2025-05-19,905,5.7,TechCorp Inc -AI07206,Deep Learning Engineer,115364,USD,115364,SE,CT,Israel,M,Australia,50,"Python, Java, Deep Learning, TensorFlow",Master,8,Manufacturing,2024-03-05,2024-05-01,844,6.7,Quantum Computing Inc -AI07207,Research Scientist,135236,EUR,114951,SE,CT,Germany,S,Germany,0,"MLOps, Spark, Python, Git",Bachelor,5,Education,2024-08-20,2024-10-31,2100,7.1,Advanced Robotics -AI07208,Data Analyst,196882,EUR,167350,EX,FL,Netherlands,L,Netherlands,100,"Computer Vision, Hadoop, Statistics, TensorFlow",Master,11,Real Estate,2024-05-06,2024-06-26,2375,8.3,DeepTech Ventures -AI07209,AI Specialist,52592,GBP,39444,EN,FT,United Kingdom,S,United Kingdom,0,"TensorFlow, Scala, SQL, NLP",PhD,0,Transportation,2024-12-26,2025-02-02,1544,8.8,Future Systems -AI07210,Machine Learning Researcher,130809,JPY,14388990,SE,CT,Japan,L,Japan,0,"PyTorch, SQL, Git, Hadoop, Mathematics",Associate,7,Healthcare,2024-02-15,2024-03-25,897,6.4,AI Innovations -AI07211,Data Engineer,83254,EUR,70766,EN,FL,Germany,L,Germany,50,"PyTorch, NLP, Deep Learning, Python, MLOps",Master,1,Technology,2024-01-01,2024-02-27,798,9.4,Predictive Systems -AI07212,Deep Learning Engineer,116639,USD,116639,MI,PT,Denmark,S,Denmark,50,"Tableau, Java, MLOps, Hadoop, Azure",Associate,3,Retail,2024-06-28,2024-07-14,892,6,Cloud AI Solutions -AI07213,Data Engineer,188382,CHF,169544,SE,FL,Switzerland,M,Portugal,0,"MLOps, PyTorch, Mathematics, TensorFlow",Bachelor,6,Consulting,2024-06-02,2024-07-11,2297,6.8,Cognitive Computing -AI07214,AI Software Engineer,126123,SGD,163960,SE,PT,Singapore,L,Romania,100,"Scala, Tableau, Python, Data Visualization",Master,7,Healthcare,2025-04-22,2025-06-26,686,8.1,Quantum Computing Inc -AI07215,AI Product Manager,108451,USD,108451,SE,FT,South Korea,M,South Korea,0,"NLP, Docker, SQL, Git",PhD,6,Technology,2024-06-15,2024-08-19,2311,6.2,Future Systems -AI07216,Computer Vision Engineer,241452,EUR,205234,EX,FL,Netherlands,L,Netherlands,0,"Python, Tableau, Deep Learning",Master,11,Finance,2024-09-23,2024-10-15,1584,6.5,Advanced Robotics -AI07217,Robotics Engineer,95945,EUR,81553,MI,CT,Netherlands,S,Netherlands,0,"SQL, Linux, Tableau",Master,2,Consulting,2024-01-02,2024-02-23,1803,10,Machine Intelligence Group -AI07218,Data Scientist,92299,AUD,124604,MI,PT,Australia,L,Portugal,50,"Deep Learning, Scala, SQL, Git",Associate,3,Finance,2024-07-08,2024-08-16,1353,7.7,Neural Networks Co -AI07219,Data Engineer,92328,USD,92328,MI,FT,Israel,M,Ukraine,0,"Java, Python, Hadoop, Spark",Associate,4,Automotive,2024-01-02,2024-02-02,1233,5,AI Innovations -AI07220,AI Consultant,63650,USD,63650,EN,FT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, Mathematics",Associate,1,Government,2024-05-17,2024-06-07,2110,7.3,Quantum Computing Inc -AI07221,AI Consultant,240627,EUR,204533,EX,FT,Netherlands,M,Netherlands,0,"Data Visualization, Spark, Scala, Deep Learning",PhD,18,Retail,2024-06-26,2024-07-19,1850,5.1,AI Innovations -AI07222,AI Specialist,113824,USD,113824,MI,PT,Norway,L,Norway,100,"AWS, Docker, Azure, Computer Vision",PhD,4,Consulting,2024-11-18,2025-01-06,2039,8.2,Algorithmic Solutions -AI07223,Data Analyst,102248,CHF,92023,MI,CT,Switzerland,S,Spain,0,"AWS, Mathematics, Hadoop",PhD,2,Real Estate,2024-03-09,2024-03-30,1863,9.9,Smart Analytics -AI07224,Machine Learning Researcher,72700,USD,72700,MI,PT,South Korea,S,South Korea,100,"Python, Hadoop, Linux, Scala, Java",PhD,4,Consulting,2024-11-18,2024-12-04,1842,5.6,Advanced Robotics -AI07225,AI Product Manager,101760,USD,101760,MI,FL,Ireland,L,Ireland,50,"Scala, Git, Statistics, Computer Vision, Kubernetes",Associate,3,Retail,2024-02-19,2024-03-13,2062,6.9,Digital Transformation LLC -AI07226,Machine Learning Researcher,75850,USD,75850,MI,PT,Israel,S,Israel,0,"Deep Learning, Java, Git, Mathematics, R",Bachelor,4,Retail,2024-05-03,2024-06-26,969,8.4,Cloud AI Solutions -AI07227,Robotics Engineer,54596,EUR,46407,EN,FL,Austria,M,Austria,100,"NLP, Python, Deep Learning",Bachelor,1,Technology,2025-01-12,2025-03-13,1823,9.4,Algorithmic Solutions -AI07228,AI Research Scientist,133583,AUD,180337,EX,PT,Australia,S,Australia,100,"Hadoop, SQL, Spark",Bachelor,11,Retail,2024-10-04,2024-10-18,1642,6.8,Digital Transformation LLC -AI07229,Autonomous Systems Engineer,75968,CAD,94960,MI,FL,Canada,M,Canada,100,"Mathematics, Docker, Python, Hadoop",Master,4,Manufacturing,2024-07-11,2024-08-17,1020,8,Quantum Computing Inc -AI07230,AI Product Manager,142238,AUD,192021,SE,FT,Australia,L,Australia,50,"GCP, R, Mathematics",PhD,7,Government,2024-07-03,2024-08-16,978,6.3,AI Innovations -AI07231,Machine Learning Engineer,211317,USD,211317,EX,FL,Israel,L,Israel,0,"MLOps, Mathematics, SQL, AWS",Master,13,Consulting,2025-01-18,2025-03-18,990,6.7,Autonomous Tech -AI07232,Data Engineer,260422,EUR,221359,EX,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Data Visualization, Spark",PhD,15,Education,2024-06-17,2024-08-13,2056,9.5,Machine Intelligence Group -AI07233,Autonomous Systems Engineer,203781,CAD,254726,EX,FL,Canada,S,Canada,0,"Linux, Java, Data Visualization, MLOps, Hadoop",PhD,11,Healthcare,2024-11-19,2024-12-19,1698,10,Neural Networks Co -AI07234,Machine Learning Engineer,53311,USD,53311,SE,PT,India,M,India,0,"Spark, SQL, Kubernetes, Python, Computer Vision",Associate,8,Transportation,2025-04-19,2025-06-15,727,5.4,Cloud AI Solutions -AI07235,AI Product Manager,111471,JPY,12261810,SE,FL,Japan,S,Japan,100,"SQL, Java, R, Scala",Bachelor,6,Healthcare,2024-05-15,2024-07-21,597,7.5,Predictive Systems -AI07236,Robotics Engineer,195168,EUR,165893,EX,PT,Germany,S,Spain,50,"Python, Docker, AWS",Master,11,Government,2024-12-29,2025-02-03,1452,8.2,Advanced Robotics -AI07237,AI Product Manager,48863,USD,48863,EN,FL,Finland,S,Finland,50,"Python, SQL, Hadoop",Bachelor,0,Transportation,2025-03-31,2025-05-22,870,7.7,Advanced Robotics -AI07238,AI Consultant,272513,CHF,245262,EX,CT,Switzerland,L,Switzerland,50,"PyTorch, AWS, NLP, SQL",Master,16,Real Estate,2024-10-19,2024-12-16,2456,9.1,AI Innovations -AI07239,ML Ops Engineer,180571,USD,180571,EX,CT,Sweden,L,Turkey,0,"GCP, TensorFlow, NLP, SQL, Tableau",Bachelor,19,Gaming,2025-03-18,2025-05-26,642,7.3,Algorithmic Solutions -AI07240,Data Scientist,177014,USD,177014,SE,FT,Denmark,L,Denmark,50,"Data Visualization, R, Deep Learning",Master,7,Automotive,2024-12-17,2024-12-31,2171,6.1,Predictive Systems -AI07241,Research Scientist,105629,USD,105629,EN,FL,United States,L,Finland,50,"SQL, NLP, Git, PyTorch",Bachelor,0,Real Estate,2024-10-28,2024-11-19,1188,8.6,Cognitive Computing -AI07242,NLP Engineer,201624,USD,201624,EX,FL,Ireland,S,Latvia,50,"Scala, Spark, Kubernetes, TensorFlow, Statistics",Bachelor,11,Technology,2024-10-09,2024-12-13,1376,7.5,Predictive Systems -AI07243,NLP Engineer,131783,EUR,112016,SE,CT,France,L,South Africa,100,"Java, GCP, Tableau, Scala",Associate,5,Gaming,2025-04-30,2025-07-04,548,8.6,DeepTech Ventures -AI07244,NLP Engineer,75289,USD,75289,EN,FL,Sweden,L,Sweden,100,"Linux, PyTorch, R, Python, Mathematics",Bachelor,0,Energy,2024-03-02,2024-04-28,1011,8.3,Quantum Computing Inc -AI07245,Data Scientist,336868,USD,336868,EX,PT,Norway,L,Norway,100,"Spark, NLP, Tableau, Docker",Master,14,Media,2024-06-21,2024-08-03,902,8.1,Digital Transformation LLC -AI07246,AI Research Scientist,163534,EUR,139004,SE,FL,Germany,L,Germany,0,"GCP, Hadoop, Docker, Deep Learning, SQL",Master,7,Consulting,2024-07-13,2024-08-06,1179,6.7,Machine Intelligence Group -AI07247,Data Engineer,116592,USD,116592,SE,FT,Finland,S,China,100,"Git, Spark, NLP, Kubernetes",PhD,9,Healthcare,2025-03-10,2025-04-17,2130,8.6,Cloud AI Solutions -AI07248,AI Consultant,124845,JPY,13732950,SE,FL,Japan,L,New Zealand,0,"Kubernetes, Data Visualization, Python, AWS, MLOps",Bachelor,9,Technology,2024-10-16,2024-12-10,1028,7.3,Machine Intelligence Group -AI07249,Robotics Engineer,130238,USD,130238,EX,PT,Sweden,S,Sweden,100,"SQL, Kubernetes, PyTorch, Git",Master,10,Consulting,2024-07-01,2024-07-16,1080,8.9,Digital Transformation LLC -AI07250,Data Engineer,190431,CAD,238039,EX,PT,Canada,M,Canada,50,"Spark, Scala, SQL",Master,19,Healthcare,2024-10-22,2024-11-19,2125,7.1,Quantum Computing Inc -AI07251,Research Scientist,21657,USD,21657,EN,CT,India,L,India,50,"TensorFlow, Java, PyTorch, GCP",Bachelor,0,Real Estate,2024-01-08,2024-02-04,790,5.1,DataVision Ltd -AI07252,Data Engineer,120635,USD,120635,MI,PT,Ireland,L,Ireland,100,"Linux, R, SQL, Deep Learning",PhD,4,Media,2025-02-26,2025-03-18,1761,7,Machine Intelligence Group -AI07253,AI Research Scientist,86185,USD,86185,MI,FL,Israel,L,Israel,50,"Statistics, Computer Vision, Data Visualization, Scala, MLOps",Bachelor,4,Government,2024-09-06,2024-11-18,552,5.6,Neural Networks Co -AI07254,AI Software Engineer,165333,CAD,206666,SE,FL,Canada,L,Australia,0,"Linux, Spark, TensorFlow",Associate,9,Energy,2024-09-01,2024-10-26,2165,6.6,Autonomous Tech -AI07255,Head of AI,160948,USD,160948,EX,FL,Finland,L,Finland,50,"Deep Learning, Kubernetes, Java, Hadoop",Master,15,Finance,2024-12-08,2025-01-19,726,6.3,DeepTech Ventures -AI07256,Deep Learning Engineer,74480,CHF,67032,EN,CT,Switzerland,M,Switzerland,50,"Java, Linux, TensorFlow, AWS, NLP",PhD,1,Energy,2024-04-23,2024-06-30,1898,7.9,Predictive Systems -AI07257,Data Scientist,64243,CAD,80304,EN,PT,Canada,L,Canada,0,"Computer Vision, Python, TensorFlow",Bachelor,0,Finance,2024-10-26,2024-12-21,1629,5.5,DeepTech Ventures -AI07258,Data Engineer,86729,USD,86729,MI,CT,Sweden,S,Switzerland,100,"Computer Vision, Mathematics, Kubernetes, Tableau",Bachelor,4,Manufacturing,2024-08-16,2024-10-01,1998,7.1,Algorithmic Solutions -AI07259,AI Specialist,72797,JPY,8007670,EN,PT,Japan,M,Japan,50,"SQL, GCP, Tableau, TensorFlow, Data Visualization",Master,1,Consulting,2024-09-28,2024-11-02,1471,8,DeepTech Ventures -AI07260,Research Scientist,124502,SGD,161853,SE,PT,Singapore,S,Singapore,100,"Deep Learning, Scala, Computer Vision, SQL, PyTorch",Associate,6,Education,2024-01-02,2024-01-28,619,9.5,Advanced Robotics -AI07261,AI Software Engineer,271059,AUD,365930,EX,CT,Australia,L,Philippines,100,"Git, Azure, Python, TensorFlow",Bachelor,12,Finance,2025-01-19,2025-02-15,1510,5.3,Cognitive Computing -AI07262,AI Product Manager,108790,EUR,92472,MI,CT,Netherlands,M,United States,0,"Kubernetes, Python, Tableau",PhD,3,Media,2024-05-04,2024-05-23,1626,9.1,Predictive Systems -AI07263,AI Product Manager,259708,AUD,350606,EX,PT,Australia,L,Australia,0,"Spark, Kubernetes, Statistics",PhD,17,Healthcare,2025-02-20,2025-03-17,2391,6.6,AI Innovations -AI07264,ML Ops Engineer,83606,USD,83606,EN,CT,United States,S,Germany,100,"TensorFlow, Tableau, Python, Computer Vision",Master,1,Consulting,2025-03-22,2025-05-14,1408,9.1,Cloud AI Solutions -AI07265,Robotics Engineer,160120,AUD,216162,SE,FT,Australia,L,Australia,50,"R, GCP, Deep Learning",Master,5,Manufacturing,2024-06-07,2024-07-16,1221,8.2,Cloud AI Solutions -AI07266,Robotics Engineer,97279,USD,97279,MI,PT,Israel,M,Israel,0,"Kubernetes, Python, Deep Learning, Data Visualization, Java",Master,2,Gaming,2024-05-10,2024-06-19,1144,6.4,Quantum Computing Inc -AI07267,AI Research Scientist,120260,USD,120260,SE,PT,Sweden,S,Sweden,50,"Computer Vision, MLOps, Deep Learning, Spark, PyTorch",Associate,9,Consulting,2024-03-07,2024-04-21,1969,5.4,DataVision Ltd -AI07268,Research Scientist,70585,AUD,95290,EN,FT,Australia,L,Estonia,50,"Mathematics, Hadoop, GCP, PyTorch",Associate,1,Retail,2024-08-18,2024-10-20,1909,6,TechCorp Inc -AI07269,Machine Learning Engineer,88166,AUD,119024,MI,CT,Australia,S,Australia,100,"Python, TensorFlow, Linux",Associate,2,Finance,2024-03-22,2024-05-21,1056,6.5,Smart Analytics -AI07270,Machine Learning Researcher,112078,USD,112078,MI,PT,United States,S,Japan,50,"Hadoop, GCP, Kubernetes, Tableau",Master,3,Technology,2025-03-16,2025-04-25,2346,5.1,Cognitive Computing -AI07271,AI Product Manager,33267,USD,33267,MI,CT,China,S,China,50,"Spark, AWS, Deep Learning",Master,2,Media,2024-06-08,2024-07-27,773,6.7,AI Innovations -AI07272,Machine Learning Researcher,118202,USD,118202,MI,PT,Norway,M,Norway,100,"Docker, Deep Learning, PyTorch",Bachelor,4,Media,2024-02-23,2024-04-29,1741,7,Future Systems -AI07273,Machine Learning Researcher,83199,USD,83199,MI,FT,Ireland,S,Ireland,0,"Kubernetes, Docker, Python, Computer Vision",PhD,4,Automotive,2025-03-20,2025-04-17,1720,7.2,Digital Transformation LLC -AI07274,Deep Learning Engineer,64159,CAD,80199,EN,PT,Canada,M,Canada,0,"Python, Kubernetes, AWS",Bachelor,1,Education,2024-03-28,2024-05-04,1069,5.8,Autonomous Tech -AI07275,ML Ops Engineer,67930,USD,67930,MI,FL,South Korea,S,South Korea,100,"Statistics, TensorFlow, R, Deep Learning, Tableau",Master,4,Real Estate,2024-06-18,2024-08-19,618,7.1,Future Systems -AI07276,Principal Data Scientist,118438,GBP,88829,SE,FT,United Kingdom,M,United Kingdom,50,"Spark, Kubernetes, Mathematics, Tableau",Master,9,Automotive,2024-02-10,2024-04-03,1557,6.5,Cognitive Computing -AI07277,AI Product Manager,49451,USD,49451,SE,PT,India,L,India,0,"SQL, Python, PyTorch",Master,5,Media,2024-04-25,2024-05-28,1974,7,Machine Intelligence Group -AI07278,Head of AI,199445,USD,199445,SE,PT,Norway,L,Norway,0,"NLP, Azure, Spark, Scala, Tableau",PhD,5,Healthcare,2024-12-29,2025-01-14,2056,7,Smart Analytics -AI07279,AI Software Engineer,151206,USD,151206,EX,CT,Sweden,S,Sweden,100,"NLP, R, Kubernetes, Mathematics",Master,14,Energy,2024-12-23,2025-02-15,1491,8.2,Predictive Systems -AI07280,AI Product Manager,129233,JPY,14215630,SE,PT,Japan,S,Japan,50,"SQL, Tableau, Spark",Master,6,Telecommunications,2024-11-17,2024-12-30,1828,6,Cloud AI Solutions -AI07281,Data Engineer,126854,EUR,107826,MI,PT,Germany,L,Denmark,50,"Linux, Kubernetes, Docker, Hadoop",Bachelor,4,Retail,2024-01-23,2024-04-02,1955,6.9,Predictive Systems -AI07282,NLP Engineer,85718,CAD,107148,MI,PT,Canada,M,Canada,50,"GCP, Linux, Spark, PyTorch, R",Bachelor,3,Automotive,2025-01-23,2025-03-28,2152,5.8,Neural Networks Co -AI07283,ML Ops Engineer,79085,USD,79085,MI,FT,South Korea,L,Vietnam,100,"Data Visualization, Mathematics, Python, Git",PhD,4,Consulting,2025-02-11,2025-04-01,2363,5.5,Future Systems -AI07284,Robotics Engineer,95382,USD,95382,MI,FL,Sweden,M,Sweden,100,"Git, TensorFlow, Tableau, Docker, PyTorch",Bachelor,2,Education,2025-03-17,2025-04-21,1788,8.1,TechCorp Inc -AI07285,AI Consultant,114244,GBP,85683,MI,CT,United Kingdom,L,United Kingdom,100,"SQL, Scala, Deep Learning, Tableau",Bachelor,3,Manufacturing,2024-10-28,2024-12-12,1445,6.4,DeepTech Ventures -AI07286,Principal Data Scientist,86971,SGD,113062,EN,FT,Singapore,L,Singapore,0,"Docker, Git, MLOps",Associate,1,Gaming,2024-08-10,2024-09-24,2324,5,AI Innovations -AI07287,AI Product Manager,113959,SGD,148147,SE,PT,Singapore,M,Czech Republic,50,"Python, Mathematics, SQL",Bachelor,7,Consulting,2024-08-13,2024-10-08,1989,8.8,Algorithmic Solutions -AI07288,ML Ops Engineer,138785,USD,138785,SE,FL,South Korea,L,South Korea,0,"Deep Learning, Computer Vision, PyTorch, Java, MLOps",Master,9,Retail,2024-10-20,2024-12-07,1829,7.1,TechCorp Inc -AI07289,Robotics Engineer,122279,GBP,91709,MI,FT,United Kingdom,L,Ukraine,100,"Hadoop, AWS, MLOps, Scala",Associate,4,Retail,2024-06-13,2024-08-01,1295,8.6,DataVision Ltd -AI07290,NLP Engineer,46233,EUR,39298,EN,PT,Austria,S,Austria,100,"Computer Vision, AWS, Git, Tableau",Bachelor,0,Education,2024-07-16,2024-08-11,1131,7.3,Smart Analytics -AI07291,Machine Learning Researcher,298282,USD,298282,EX,FT,Denmark,L,Denmark,50,"Kubernetes, SQL, GCP, PyTorch, Mathematics",Associate,17,Telecommunications,2024-01-30,2024-03-27,1484,5.5,Machine Intelligence Group -AI07292,AI Architect,20587,USD,20587,EN,FL,India,M,Estonia,0,"Kubernetes, R, Computer Vision, Deep Learning",Associate,1,Energy,2024-12-05,2024-12-22,773,8.9,Algorithmic Solutions -AI07293,Data Scientist,85412,USD,85412,MI,PT,Ireland,L,Indonesia,100,"Deep Learning, Statistics, NLP, Kubernetes",Master,2,Government,2025-03-28,2025-06-06,2482,9.8,TechCorp Inc -AI07294,Deep Learning Engineer,164904,EUR,140168,SE,CT,Netherlands,L,Netherlands,100,"SQL, PyTorch, AWS, Scala, Java",Bachelor,9,Healthcare,2024-06-17,2024-08-03,2150,7.8,DataVision Ltd -AI07295,Principal Data Scientist,153719,EUR,130661,EX,FT,Austria,M,Austria,50,"SQL, AWS, Deep Learning, NLP, PyTorch",Associate,10,Healthcare,2024-10-21,2024-12-01,757,9,Predictive Systems -AI07296,Data Analyst,128775,EUR,109459,MI,CT,Netherlands,L,China,0,"Hadoop, PyTorch, Data Visualization, NLP",Master,3,Education,2025-01-07,2025-03-08,2131,7.3,Advanced Robotics -AI07297,AI Architect,74122,EUR,63004,MI,FT,Netherlands,S,Netherlands,50,"Azure, Kubernetes, GCP",Bachelor,3,Technology,2024-01-30,2024-02-28,1960,5.7,Cloud AI Solutions -AI07298,NLP Engineer,153979,USD,153979,EX,CT,Sweden,M,Sweden,50,"Python, Docker, MLOps",PhD,14,Automotive,2025-04-30,2025-07-04,698,9.7,AI Innovations -AI07299,Data Scientist,130397,CHF,117357,SE,CT,Switzerland,S,Switzerland,50,"Statistics, Hadoop, Azure, Java",PhD,9,Manufacturing,2025-02-27,2025-03-25,897,5.8,TechCorp Inc -AI07300,Autonomous Systems Engineer,79354,GBP,59516,EN,FT,United Kingdom,M,Ireland,0,"TensorFlow, Statistics, Docker",PhD,1,Media,2025-02-22,2025-03-12,1379,7.5,Quantum Computing Inc -AI07301,Data Scientist,120736,USD,120736,MI,FL,Ireland,L,Israel,0,"Azure, Linux, NLP",Associate,3,Energy,2024-11-08,2025-01-02,2417,6,Autonomous Tech -AI07302,Research Scientist,92591,USD,92591,SE,FT,Finland,S,Portugal,0,"Deep Learning, Python, GCP",Bachelor,6,Real Estate,2024-06-13,2024-07-23,1341,6.6,Smart Analytics -AI07303,Robotics Engineer,167422,USD,167422,SE,FL,Denmark,S,Denmark,100,"Python, Mathematics, Tableau, Deep Learning, SQL",Master,7,Gaming,2024-11-11,2024-12-18,1682,5.5,Cloud AI Solutions -AI07304,Research Scientist,43875,USD,43875,SE,CT,China,S,China,0,"Statistics, Kubernetes, SQL",Master,6,Healthcare,2024-11-25,2025-01-11,2385,9.1,Algorithmic Solutions -AI07305,Data Engineer,154370,EUR,131215,SE,PT,Austria,L,Austria,0,"Python, Spark, Statistics, Deep Learning, Java",Master,7,Education,2024-10-31,2024-12-07,1667,6,Future Systems -AI07306,Computer Vision Engineer,89756,CAD,112195,MI,PT,Canada,S,Canada,0,"Data Visualization, SQL, Azure, Kubernetes, Mathematics",PhD,2,Energy,2024-08-10,2024-09-19,2415,7.2,Advanced Robotics -AI07307,AI Specialist,58025,EUR,49321,EN,CT,Germany,S,Luxembourg,100,"R, SQL, NLP, Hadoop",Bachelor,1,Government,2024-10-08,2024-12-10,1563,7.1,DataVision Ltd -AI07308,Computer Vision Engineer,52365,EUR,44510,EN,PT,Netherlands,S,Netherlands,0,"Tableau, Linux, SQL, PyTorch",PhD,1,Manufacturing,2025-04-17,2025-05-03,1878,6.7,Machine Intelligence Group -AI07309,Research Scientist,252611,EUR,214719,EX,FL,Netherlands,L,Netherlands,100,"AWS, Data Visualization, MLOps, Spark",Associate,18,Media,2024-05-22,2024-06-28,787,9.3,DeepTech Ventures -AI07310,AI Consultant,292045,JPY,32124950,EX,FT,Japan,L,Japan,50,"Python, Scala, Hadoop, Linux, GCP",Bachelor,15,Telecommunications,2024-12-17,2025-02-16,1701,5.5,Autonomous Tech -AI07311,Research Scientist,180417,SGD,234542,EX,FL,Singapore,S,Singapore,100,"TensorFlow, Java, Tableau",Master,15,Transportation,2025-04-08,2025-04-23,1308,8.1,DataVision Ltd -AI07312,Deep Learning Engineer,65703,USD,65703,EN,FT,Ireland,S,United States,100,"Hadoop, Computer Vision, SQL, R, PyTorch",PhD,1,Gaming,2024-08-24,2024-09-07,1472,9.4,DataVision Ltd -AI07313,ML Ops Engineer,33627,USD,33627,MI,FT,India,L,India,0,"Hadoop, AWS, Kubernetes, NLP, Azure",Master,3,Automotive,2024-12-06,2025-01-03,1675,9.2,Neural Networks Co -AI07314,NLP Engineer,117069,CHF,105362,MI,PT,Switzerland,M,Nigeria,50,"PyTorch, GCP, Deep Learning, Docker, Tableau",Master,3,Automotive,2024-02-03,2024-03-01,1738,8.6,Predictive Systems -AI07315,Deep Learning Engineer,109443,EUR,93027,SE,CT,France,S,France,50,"Kubernetes, Python, Scala",PhD,8,Healthcare,2025-01-11,2025-03-04,2280,8.7,Digital Transformation LLC -AI07316,AI Software Engineer,114421,EUR,97258,MI,FL,Austria,L,Luxembourg,0,"Python, Tableau, Linux, Hadoop",Master,3,Manufacturing,2024-05-10,2024-07-14,1941,5.7,Neural Networks Co -AI07317,Head of AI,297806,USD,297806,EX,FT,United States,M,China,0,"Data Visualization, PyTorch, Tableau, GCP",Bachelor,15,Media,2024-11-07,2024-12-13,1644,9.3,DataVision Ltd -AI07318,Autonomous Systems Engineer,96103,JPY,10571330,MI,FL,Japan,M,Japan,0,"Java, Scala, Hadoop",Master,2,Technology,2024-08-30,2024-10-13,993,6.2,Advanced Robotics -AI07319,AI Consultant,104183,EUR,88556,MI,PT,Netherlands,L,Netherlands,100,"PyTorch, TensorFlow, Scala",PhD,4,Automotive,2024-05-30,2024-07-27,1802,8.3,Quantum Computing Inc -AI07320,Research Scientist,203843,CHF,183459,SE,FT,Switzerland,L,Switzerland,100,"Docker, GCP, Hadoop, Computer Vision",Master,6,Transportation,2025-03-31,2025-05-17,1710,8.4,TechCorp Inc -AI07321,AI Specialist,159445,CHF,143501,SE,CT,Switzerland,S,Switzerland,0,"PyTorch, NLP, Java, GCP",Master,9,Consulting,2025-04-17,2025-06-21,823,7.8,DeepTech Ventures -AI07322,Computer Vision Engineer,98252,USD,98252,SE,CT,Finland,S,Finland,50,"Azure, Tableau, AWS, Linux",Bachelor,7,Gaming,2024-12-14,2025-01-24,1131,6.2,Advanced Robotics -AI07323,Data Engineer,140598,USD,140598,SE,FL,Sweden,L,Switzerland,50,"Python, PyTorch, Docker",PhD,5,Energy,2024-02-08,2024-04-07,1530,6.6,Quantum Computing Inc -AI07324,Data Engineer,122530,USD,122530,SE,FT,Ireland,S,Ireland,0,"SQL, Tableau, Deep Learning",Master,5,Consulting,2025-03-06,2025-03-30,1123,8.1,Advanced Robotics -AI07325,AI Specialist,79216,USD,79216,EN,FT,United States,S,United States,100,"Kubernetes, Java, MLOps",Associate,0,Government,2024-11-24,2025-01-16,1296,5.6,Autonomous Tech -AI07326,AI Software Engineer,208065,USD,208065,EX,FT,South Korea,M,South Korea,100,"Azure, TensorFlow, R, Tableau",Master,14,Real Estate,2025-02-06,2025-04-03,1320,7.5,Digital Transformation LLC -AI07327,Data Engineer,212005,EUR,180204,EX,PT,Germany,M,Germany,0,"GCP, R, Python",PhD,10,Retail,2024-06-10,2024-07-16,1605,5.2,TechCorp Inc -AI07328,Computer Vision Engineer,142069,EUR,120759,SE,PT,Netherlands,L,Netherlands,0,"Data Visualization, Kubernetes, Scala, Python, Mathematics",Bachelor,7,Consulting,2024-11-23,2024-12-18,2476,5.3,Algorithmic Solutions -AI07329,NLP Engineer,189432,USD,189432,EX,PT,Israel,S,Nigeria,50,"GCP, R, SQL, TensorFlow, Java",Master,17,Manufacturing,2024-06-21,2024-08-15,1030,6.3,AI Innovations -AI07330,AI Architect,148090,USD,148090,EX,PT,United States,S,United States,100,"Mathematics, MLOps, Data Visualization, TensorFlow",Associate,13,Media,2025-01-26,2025-04-03,1491,8.1,Cognitive Computing -AI07331,Autonomous Systems Engineer,90214,AUD,121789,MI,FL,Australia,M,Singapore,100,"R, AWS, MLOps, Git",Bachelor,2,Government,2025-02-01,2025-03-13,1301,5.2,Algorithmic Solutions -AI07332,Autonomous Systems Engineer,179077,CAD,223846,EX,FT,Canada,M,Austria,100,"SQL, Data Visualization, MLOps, Mathematics, Java",Bachelor,11,Telecommunications,2024-01-21,2024-02-18,1876,5.3,DeepTech Ventures -AI07333,NLP Engineer,49419,AUD,66716,EN,PT,Australia,S,Australia,50,"AWS, Linux, Kubernetes, Git",Associate,1,Transportation,2025-03-31,2025-05-20,1252,7.8,Algorithmic Solutions -AI07334,Robotics Engineer,121147,USD,121147,SE,FL,Sweden,S,Sweden,50,"SQL, TensorFlow, Java, Scala",Associate,8,Retail,2025-02-22,2025-03-28,1565,9.6,Algorithmic Solutions -AI07335,AI Architect,246001,USD,246001,EX,FL,Ireland,M,Ireland,100,"Mathematics, GCP, SQL",Associate,17,Technology,2025-01-31,2025-03-07,955,6.3,Neural Networks Co -AI07336,Principal Data Scientist,52336,USD,52336,EN,PT,Israel,M,Israel,0,"Data Visualization, Statistics, NLP, Python, Computer Vision",Master,1,Government,2024-12-20,2025-02-01,1645,8.1,Machine Intelligence Group -AI07337,ML Ops Engineer,43262,EUR,36773,EN,PT,France,S,France,100,"Java, Git, Kubernetes, Python",Master,0,Transportation,2024-11-14,2025-01-11,639,5,Cloud AI Solutions -AI07338,Research Scientist,107059,EUR,91000,MI,PT,France,L,France,50,"Python, Java, NLP, AWS",Bachelor,4,Real Estate,2024-05-04,2024-05-18,654,5.4,Machine Intelligence Group -AI07339,Autonomous Systems Engineer,77881,EUR,66199,MI,CT,France,S,Sweden,0,"GCP, Java, Python, Deep Learning",Bachelor,3,Consulting,2024-08-15,2024-09-21,1815,5.6,Cognitive Computing -AI07340,Head of AI,77351,CAD,96689,MI,PT,Canada,M,Italy,0,"PyTorch, TensorFlow, MLOps",Associate,2,Finance,2024-03-15,2024-04-25,1356,9.2,Cloud AI Solutions -AI07341,Principal Data Scientist,148317,USD,148317,EX,FT,United States,S,China,0,"MLOps, Tableau, Python, Docker, Linux",Bachelor,10,Government,2024-01-12,2024-02-04,1930,9.4,Neural Networks Co -AI07342,AI Research Scientist,185184,CHF,166666,SE,FL,Switzerland,M,Switzerland,0,"MLOps, Mathematics, Python, TensorFlow",PhD,9,Healthcare,2024-11-01,2024-12-22,1638,6.6,Quantum Computing Inc -AI07343,AI Consultant,215064,EUR,182804,EX,CT,Austria,L,Austria,50,"PyTorch, SQL, Spark, Computer Vision, Mathematics",PhD,11,Telecommunications,2024-07-12,2024-07-26,581,8.7,Algorithmic Solutions -AI07344,Deep Learning Engineer,38054,USD,38054,EN,FL,South Korea,S,South Korea,100,"Computer Vision, Kubernetes, Mathematics",Associate,0,Government,2024-12-07,2024-12-23,1966,7.2,Predictive Systems -AI07345,Data Engineer,297668,SGD,386968,EX,FT,Singapore,L,Ireland,50,"Kubernetes, SQL, Docker",Master,16,Healthcare,2025-04-16,2025-05-04,1714,7.5,Digital Transformation LLC -AI07346,Machine Learning Engineer,72953,SGD,94839,EN,FT,Singapore,S,Russia,0,"Deep Learning, Data Visualization, Hadoop",Bachelor,1,Consulting,2024-08-17,2024-10-20,706,8.1,AI Innovations -AI07347,ML Ops Engineer,145761,EUR,123897,SE,FT,Netherlands,L,Netherlands,50,"Linux, Hadoop, Mathematics",PhD,8,Healthcare,2024-03-16,2024-04-01,756,5.4,DeepTech Ventures -AI07348,Computer Vision Engineer,203224,USD,203224,SE,PT,Norway,L,Norway,0,"AWS, Azure, Hadoop, Spark",Associate,6,Energy,2024-07-26,2024-08-27,1287,7.6,DataVision Ltd -AI07349,Computer Vision Engineer,242702,EUR,206297,EX,CT,Netherlands,L,Netherlands,0,"SQL, AWS, Computer Vision, Kubernetes, Spark",Associate,14,Finance,2024-05-31,2024-08-10,882,8.1,Smart Analytics -AI07350,Machine Learning Engineer,46733,CAD,58416,EN,FT,Canada,S,Canada,0,"GCP, Linux, Hadoop",Master,0,Automotive,2024-09-16,2024-11-07,698,9.2,Digital Transformation LLC -AI07351,Machine Learning Researcher,85044,USD,85044,MI,CT,Norway,S,Norway,0,"Computer Vision, Linux, SQL, TensorFlow",Master,2,Transportation,2024-09-14,2024-09-28,933,5.4,Machine Intelligence Group -AI07352,AI Specialist,90679,EUR,77077,MI,PT,France,L,Sweden,0,"PyTorch, Deep Learning, Azure, Computer Vision",Associate,4,Technology,2024-09-25,2024-11-05,2118,6.7,Quantum Computing Inc -AI07353,ML Ops Engineer,81449,EUR,69232,MI,CT,Netherlands,M,Netherlands,0,"Linux, Java, Computer Vision",Associate,2,Transportation,2024-09-17,2024-11-27,1721,8.7,Autonomous Tech -AI07354,ML Ops Engineer,79173,EUR,67297,EN,CT,France,L,France,50,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Energy,2025-01-10,2025-03-19,1994,7.1,Quantum Computing Inc -AI07355,Machine Learning Researcher,266789,USD,266789,EX,FL,Denmark,M,Denmark,100,"Kubernetes, Linux, Tableau, TensorFlow",PhD,16,Government,2024-08-28,2024-10-23,693,9.9,Machine Intelligence Group -AI07356,Machine Learning Researcher,170028,CHF,153025,SE,FL,Switzerland,S,Switzerland,50,"Azure, Deep Learning, Tableau, R",Associate,8,Gaming,2024-10-10,2024-12-10,1166,7.2,Predictive Systems -AI07357,AI Software Engineer,26042,USD,26042,EN,PT,India,L,Vietnam,50,"Kubernetes, Git, Mathematics, Python",PhD,0,Transportation,2025-01-01,2025-02-25,2059,5.7,Cognitive Computing -AI07358,NLP Engineer,192917,EUR,163979,EX,PT,France,M,France,50,"Kubernetes, Linux, GCP, Java, R",Bachelor,15,Consulting,2025-04-16,2025-05-10,1803,9.1,DataVision Ltd -AI07359,Head of AI,106638,USD,106638,MI,CT,Finland,L,Czech Republic,100,"Kubernetes, MLOps, Deep Learning, Python",Bachelor,2,Finance,2024-07-26,2024-08-09,1911,9.4,DataVision Ltd -AI07360,Machine Learning Researcher,76474,USD,76474,EX,FL,India,M,India,50,"Git, Statistics, Computer Vision, Deep Learning, R",Bachelor,10,Energy,2024-01-14,2024-02-27,585,7.9,Quantum Computing Inc -AI07361,AI Architect,177950,USD,177950,SE,FT,United States,M,United States,50,"TensorFlow, R, AWS, Mathematics, Computer Vision",PhD,5,Media,2024-11-04,2024-12-09,2298,6.1,Advanced Robotics -AI07362,Machine Learning Researcher,104483,CHF,94035,MI,FL,Switzerland,S,Switzerland,50,"MLOps, Kubernetes, Tableau, Hadoop, Mathematics",Associate,2,Healthcare,2024-10-19,2024-12-13,2315,6.7,Smart Analytics -AI07363,ML Ops Engineer,64384,JPY,7082240,EN,FL,Japan,L,Turkey,0,"Python, TensorFlow, MLOps, GCP",Associate,1,Education,2024-12-06,2024-12-20,1208,6.2,Cognitive Computing -AI07364,AI Consultant,50482,SGD,65627,EN,PT,Singapore,S,Singapore,100,"PyTorch, Hadoop, Deep Learning",Associate,1,Real Estate,2024-09-22,2024-11-01,2204,7.6,Algorithmic Solutions -AI07365,Data Scientist,151120,EUR,128452,SE,FL,Germany,L,Germany,50,"Linux, R, SQL, Spark, TensorFlow",Bachelor,5,Healthcare,2024-08-11,2024-09-26,1422,8.1,Autonomous Tech -AI07366,AI Research Scientist,145148,USD,145148,MI,FL,Norway,L,Norway,50,"TensorFlow, Spark, Computer Vision, Linux",Associate,3,Media,2025-03-06,2025-04-15,2298,8,Algorithmic Solutions -AI07367,Machine Learning Researcher,46232,CAD,57790,EN,PT,Canada,S,Canada,100,"Data Visualization, Azure, PyTorch",Master,0,Telecommunications,2024-07-28,2024-09-01,1275,8.8,Quantum Computing Inc -AI07368,Data Engineer,192522,CAD,240653,EX,FT,Canada,L,Canada,100,"Kubernetes, GCP, AWS, Git, NLP",Master,10,Finance,2024-10-19,2024-12-31,2175,8.2,Algorithmic Solutions -AI07369,Machine Learning Researcher,227433,USD,227433,EX,FT,Sweden,L,Sweden,0,"Python, R, SQL",Associate,18,Government,2024-10-07,2024-11-11,543,7.2,DeepTech Ventures -AI07370,Data Analyst,104134,USD,104134,SE,PT,Finland,M,Finland,0,"AWS, Git, Java, Azure, Python",Associate,5,Energy,2024-11-17,2024-12-20,1295,7.5,Cloud AI Solutions -AI07371,Computer Vision Engineer,193260,USD,193260,SE,PT,Norway,L,Norway,0,"Computer Vision, Data Visualization, Python",Master,7,Finance,2024-06-01,2024-08-04,1662,8.4,Digital Transformation LLC -AI07372,AI Research Scientist,215088,EUR,182825,EX,CT,Germany,M,Germany,50,"Scala, NLP, R, GCP, Python",Associate,15,Gaming,2024-01-20,2024-03-26,1288,6.2,Machine Intelligence Group -AI07373,Autonomous Systems Engineer,74692,USD,74692,MI,FT,Sweden,M,Sweden,0,"SQL, Linux, Statistics",Associate,4,Technology,2024-05-28,2024-08-05,1682,7.3,DataVision Ltd -AI07374,Deep Learning Engineer,89378,EUR,75971,MI,FT,France,S,France,50,"Linux, GCP, Computer Vision",Bachelor,2,Technology,2024-10-01,2024-12-05,2365,5,Advanced Robotics -AI07375,AI Consultant,222964,USD,222964,EX,FL,Finland,L,Colombia,0,"R, Spark, Linux, Java",Bachelor,17,Finance,2024-10-15,2024-12-04,1826,6.1,Machine Intelligence Group -AI07376,Robotics Engineer,219494,USD,219494,EX,CT,Ireland,L,Hungary,50,"AWS, Azure, SQL, Statistics, Git",Associate,17,Transportation,2024-07-05,2024-08-21,996,5.5,Neural Networks Co -AI07377,AI Research Scientist,132643,EUR,112747,SE,CT,Netherlands,M,Netherlands,50,"TensorFlow, NLP, Linux, GCP, Data Visualization",Associate,9,Telecommunications,2024-07-08,2024-09-03,920,8.3,AI Innovations -AI07378,Data Engineer,54621,USD,54621,EX,PT,India,M,Brazil,0,"Hadoop, Python, R, SQL",Associate,18,Real Estate,2024-07-08,2024-08-09,1912,5.8,DataVision Ltd -AI07379,Deep Learning Engineer,149274,GBP,111956,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, Java, PyTorch, Spark, Docker",PhD,5,Energy,2024-11-02,2025-01-09,834,5.2,Cloud AI Solutions -AI07380,AI Software Engineer,79871,SGD,103832,EN,FL,Singapore,L,Singapore,50,"MLOps, SQL, Azure, Mathematics",PhD,0,Retail,2025-04-30,2025-05-18,2489,5.3,Algorithmic Solutions -AI07381,Data Engineer,240902,USD,240902,EX,PT,Sweden,M,Philippines,100,"GCP, Data Visualization, Python",PhD,12,Automotive,2025-01-05,2025-01-23,1762,7.9,DeepTech Ventures -AI07382,Principal Data Scientist,88819,CAD,111024,MI,FL,Canada,M,Canada,100,"Kubernetes, PyTorch, Git",PhD,3,Gaming,2025-01-26,2025-03-13,1594,8.5,Smart Analytics -AI07383,AI Software Engineer,245168,JPY,26968480,EX,FT,Japan,L,Norway,100,"SQL, AWS, Linux, Spark",PhD,11,Telecommunications,2024-10-04,2024-11-17,1753,7,Machine Intelligence Group -AI07384,Research Scientist,226851,USD,226851,EX,FL,Finland,L,Finland,50,"Azure, Linux, Data Visualization, Git, Kubernetes",Associate,17,Consulting,2025-01-17,2025-03-15,1652,9.6,DataVision Ltd -AI07385,AI Architect,65693,USD,65693,MI,PT,South Korea,M,Russia,50,"Linux, Hadoop, Computer Vision",Bachelor,2,Energy,2024-02-22,2024-03-10,910,8.2,Cloud AI Solutions -AI07386,Computer Vision Engineer,173491,EUR,147467,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, Mathematics, Statistics",PhD,9,Gaming,2025-04-01,2025-06-09,515,8.3,AI Innovations -AI07387,Head of AI,78460,CAD,98075,MI,PT,Canada,M,Argentina,50,"Scala, Hadoop, Deep Learning",Bachelor,3,Automotive,2025-01-16,2025-03-30,2303,5.9,Cloud AI Solutions -AI07388,AI Specialist,87156,USD,87156,MI,FT,Sweden,M,Czech Republic,0,"Computer Vision, Scala, Python, TensorFlow",PhD,2,Transportation,2024-03-27,2024-05-18,2028,8.5,AI Innovations -AI07389,Data Engineer,251231,CHF,226108,EX,PT,Switzerland,S,Switzerland,100,"Docker, Linux, Python, Data Visualization, TensorFlow",PhD,17,Media,2024-03-28,2024-05-17,1025,8.3,AI Innovations -AI07390,Data Engineer,75609,USD,75609,EN,FT,Denmark,M,Denmark,50,"Docker, Spark, R, Hadoop",PhD,1,Gaming,2025-04-20,2025-06-25,1240,9.5,Predictive Systems -AI07391,Data Scientist,85774,USD,85774,MI,CT,Sweden,M,Latvia,50,"MLOps, Linux, Mathematics",Bachelor,4,Telecommunications,2024-05-04,2024-07-03,1310,6.9,Smart Analytics -AI07392,Robotics Engineer,270769,USD,270769,EX,PT,Israel,L,Israel,100,"Kubernetes, R, MLOps",PhD,14,Gaming,2025-01-07,2025-03-21,1665,9.4,DataVision Ltd -AI07393,Data Scientist,56999,USD,56999,EN,CT,United States,S,United States,50,"Spark, Data Visualization, AWS, Kubernetes, Hadoop",Associate,1,Transportation,2024-07-25,2024-08-28,1690,5.6,Smart Analytics -AI07394,ML Ops Engineer,95205,EUR,80924,SE,PT,Germany,S,Germany,0,"Python, Scala, MLOps, Statistics",Associate,5,Real Estate,2024-01-19,2024-02-09,923,7.5,Future Systems -AI07395,Data Analyst,116878,USD,116878,SE,FL,South Korea,L,South Korea,100,"Python, TensorFlow, Data Visualization, Computer Vision, Azure",PhD,8,Telecommunications,2024-07-27,2024-10-03,1058,8.2,DataVision Ltd -AI07396,Autonomous Systems Engineer,92083,CAD,115104,MI,FT,Canada,S,Canada,0,"Kubernetes, Linux, R",Bachelor,3,Finance,2024-05-25,2024-07-02,1467,7,Digital Transformation LLC -AI07397,Head of AI,89908,USD,89908,EN,FT,Denmark,L,Denmark,50,"Git, Azure, SQL, Kubernetes",Bachelor,1,Media,2024-01-26,2024-03-01,989,9.4,AI Innovations -AI07398,AI Architect,82155,EUR,69832,MI,CT,France,M,France,50,"Linux, Git, Computer Vision, PyTorch",Associate,2,Real Estate,2024-05-16,2024-06-21,2168,5.9,Future Systems -AI07399,Research Scientist,250839,USD,250839,EX,FT,Finland,L,Finland,100,"SQL, Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,15,Real Estate,2024-02-08,2024-03-25,1727,6.1,Future Systems -AI07400,Autonomous Systems Engineer,141610,USD,141610,SE,FT,United States,L,United States,100,"Python, TensorFlow, Data Visualization, MLOps",PhD,7,Manufacturing,2025-02-07,2025-03-15,2115,8.5,Predictive Systems -AI07401,ML Ops Engineer,134017,USD,134017,SE,FT,Denmark,S,Denmark,0,"Linux, SQL, Statistics, R",PhD,9,Government,2025-02-14,2025-03-31,1735,5.1,Advanced Robotics -AI07402,AI Specialist,287847,EUR,244670,EX,FL,Netherlands,L,Netherlands,100,"SQL, TensorFlow, PyTorch",Master,19,Manufacturing,2024-09-22,2024-10-20,1149,5.7,DataVision Ltd -AI07403,AI Research Scientist,72341,USD,72341,EX,FT,India,M,Turkey,100,"GCP, Computer Vision, Spark, Java, R",Bachelor,15,Telecommunications,2024-08-11,2024-09-10,2228,8,AI Innovations -AI07404,ML Ops Engineer,196644,EUR,167147,EX,CT,France,S,Turkey,0,"GCP, Computer Vision, Data Visualization, Scala",Bachelor,16,Finance,2024-07-11,2024-08-16,2103,5.2,DataVision Ltd -AI07405,AI Consultant,80695,GBP,60521,MI,FT,United Kingdom,M,United Kingdom,100,"NLP, Computer Vision, PyTorch, TensorFlow",Bachelor,4,Manufacturing,2025-02-13,2025-03-05,1974,5.5,Autonomous Tech -AI07406,Robotics Engineer,112650,USD,112650,EN,FL,Denmark,L,Denmark,50,"Kubernetes, Hadoop, Mathematics, Git",Associate,0,Transportation,2024-03-12,2024-04-20,1124,7,Algorithmic Solutions -AI07407,AI Product Manager,138862,USD,138862,MI,FT,United States,L,United States,50,"Hadoop, Mathematics, MLOps",Associate,3,Transportation,2024-07-18,2024-08-03,1894,6.7,Quantum Computing Inc -AI07408,Machine Learning Engineer,92680,CHF,83412,EN,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, MLOps, SQL, Deep Learning",Bachelor,1,Real Estate,2024-05-10,2024-07-01,974,8.1,Cognitive Computing -AI07409,AI Software Engineer,106542,USD,106542,EN,CT,United States,L,United States,0,"Scala, PyTorch, Data Visualization, Tableau",Bachelor,0,Healthcare,2024-05-16,2024-06-19,1892,5.1,Advanced Robotics -AI07410,Machine Learning Engineer,57987,EUR,49289,EN,CT,Germany,S,United States,0,"Docker, Mathematics, TensorFlow",PhD,0,Manufacturing,2025-04-15,2025-05-07,2129,8.9,DeepTech Ventures -AI07411,Machine Learning Engineer,224659,USD,224659,EX,PT,Finland,L,Vietnam,50,"SQL, PyTorch, Kubernetes",Associate,15,Education,2024-08-30,2024-09-14,585,6.2,Quantum Computing Inc -AI07412,AI Consultant,223546,CHF,201191,EX,FT,Switzerland,M,South Korea,100,"TensorFlow, Azure, AWS, GCP, MLOps",PhD,12,Retail,2024-07-08,2024-08-07,1511,9,Digital Transformation LLC -AI07413,AI Research Scientist,151758,CHF,136582,MI,CT,Switzerland,L,Switzerland,0,"Hadoop, Mathematics, Azure, Computer Vision, NLP",Master,3,Education,2024-04-09,2024-05-05,946,9.4,Quantum Computing Inc -AI07414,AI Specialist,46742,USD,46742,EN,CT,Sweden,S,Italy,50,"NLP, Deep Learning, SQL, Tableau, Hadoop",Master,1,Retail,2024-04-24,2024-07-06,1123,6.7,Algorithmic Solutions -AI07415,AI Software Engineer,159242,USD,159242,EX,PT,Finland,S,Finland,100,"Kubernetes, Deep Learning, Data Visualization, GCP",Associate,10,Real Estate,2024-12-31,2025-02-08,1926,6.1,Future Systems -AI07416,Data Analyst,87254,USD,87254,EN,FT,Norway,S,Brazil,0,"Hadoop, Scala, Data Visualization, SQL",Associate,1,Retail,2024-08-12,2024-10-08,992,6.8,Cloud AI Solutions -AI07417,AI Research Scientist,62366,USD,62366,EN,CT,Finland,M,Singapore,50,"Spark, SQL, Hadoop, AWS",PhD,1,Gaming,2024-02-21,2024-04-02,1969,5.4,Cognitive Computing -AI07418,Data Scientist,194278,USD,194278,SE,FL,Norway,L,Israel,50,"Java, Statistics, Deep Learning, Tableau",Master,7,Media,2024-10-24,2024-12-09,809,8.9,Autonomous Tech -AI07419,AI Product Manager,107060,SGD,139178,SE,CT,Singapore,S,Singapore,100,"Statistics, R, Spark, Deep Learning, Linux",PhD,9,Retail,2025-01-31,2025-04-09,884,9.5,Machine Intelligence Group -AI07420,AI Product Manager,125649,USD,125649,SE,FL,Ireland,L,Ireland,50,"Linux, Spark, Data Visualization, NLP",PhD,5,Automotive,2025-03-29,2025-06-06,1974,10,Machine Intelligence Group -AI07421,AI Architect,151908,USD,151908,EX,PT,Sweden,M,Sweden,100,"Tableau, Computer Vision, PyTorch, SQL, Python",Bachelor,10,Gaming,2024-02-24,2024-05-01,1600,9.1,Machine Intelligence Group -AI07422,ML Ops Engineer,207008,CHF,186307,SE,CT,Switzerland,M,Switzerland,0,"Hadoop, MLOps, Deep Learning, GCP",PhD,7,Retail,2024-05-05,2024-06-01,1235,9,Smart Analytics -AI07423,Data Scientist,93359,CHF,84023,EN,CT,Switzerland,S,Switzerland,100,"Linux, Kubernetes, SQL, Java, Deep Learning",Bachelor,1,Telecommunications,2025-01-02,2025-02-02,1179,9.9,TechCorp Inc -AI07424,AI Research Scientist,102494,AUD,138367,MI,FL,Australia,L,Australia,0,"SQL, R, Mathematics, Linux",Master,4,Automotive,2024-07-18,2024-08-23,1974,5.4,Cloud AI Solutions -AI07425,NLP Engineer,82281,EUR,69939,MI,FL,France,M,France,50,"SQL, Spark, Hadoop",PhD,4,Technology,2024-08-16,2024-09-18,828,6,Algorithmic Solutions -AI07426,Deep Learning Engineer,148607,USD,148607,SE,FT,Finland,L,Finland,0,"Git, Spark, NLP, Computer Vision",Bachelor,9,Finance,2024-10-18,2024-11-04,1627,8.7,AI Innovations -AI07427,Autonomous Systems Engineer,97107,USD,97107,MI,FL,Finland,M,Finland,50,"PyTorch, NLP, Kubernetes, Azure",PhD,4,Finance,2025-01-23,2025-03-19,596,7.2,Neural Networks Co -AI07428,Data Engineer,156750,USD,156750,SE,CT,Norway,S,Norway,50,"Java, Tableau, Scala",PhD,6,Gaming,2024-06-24,2024-07-20,617,6.3,Future Systems -AI07429,Data Scientist,43046,USD,43046,MI,CT,China,M,Mexico,100,"Hadoop, Kubernetes, NLP",Master,4,Telecommunications,2024-07-28,2024-09-04,532,7.9,Advanced Robotics -AI07430,Autonomous Systems Engineer,259249,CAD,324061,EX,FL,Canada,L,Canada,50,"Data Visualization, Linux, SQL, R",Master,13,Real Estate,2024-11-16,2025-01-19,1880,8.9,Neural Networks Co -AI07431,Research Scientist,76203,USD,76203,MI,FT,Sweden,S,Sweden,0,"TensorFlow, R, Git, AWS, Computer Vision",PhD,2,Government,2024-01-09,2024-03-20,2304,9,Predictive Systems -AI07432,Data Engineer,145647,USD,145647,SE,PT,Denmark,M,Philippines,100,"Data Visualization, TensorFlow, Kubernetes, NLP, Deep Learning",PhD,8,Transportation,2024-07-05,2024-09-09,1327,8.5,Algorithmic Solutions -AI07433,AI Specialist,61066,EUR,51906,EN,CT,Netherlands,S,Portugal,0,"Scala, Computer Vision, Python, Docker, TensorFlow",Master,1,Technology,2024-03-15,2024-05-11,2259,6.9,Digital Transformation LLC -AI07434,AI Specialist,186576,USD,186576,SE,CT,Norway,M,Norway,100,"Git, Azure, Data Visualization, PyTorch",PhD,6,Automotive,2025-04-15,2025-06-04,1906,8.8,TechCorp Inc -AI07435,Machine Learning Researcher,132277,USD,132277,SE,CT,Ireland,L,Ireland,0,"Docker, GCP, Linux",Bachelor,9,Telecommunications,2024-04-04,2024-05-05,820,8.4,Machine Intelligence Group -AI07436,NLP Engineer,170334,USD,170334,SE,FL,United States,M,Poland,50,"Spark, R, Git",Bachelor,7,Retail,2025-02-01,2025-03-04,807,6,Cognitive Computing -AI07437,AI Research Scientist,124463,USD,124463,SE,CT,South Korea,M,South Korea,100,"TensorFlow, SQL, NLP, MLOps, Deep Learning",PhD,8,Finance,2024-04-24,2024-05-19,2246,6.2,Cognitive Computing -AI07438,AI Specialist,82706,USD,82706,MI,CT,Sweden,S,Sweden,50,"MLOps, Deep Learning, TensorFlow, NLP",PhD,4,Healthcare,2024-11-15,2025-01-18,756,9,Cognitive Computing -AI07439,AI Architect,250961,CHF,225865,EX,FL,Switzerland,M,Switzerland,100,"Spark, MLOps, Kubernetes, Linux",Bachelor,13,Real Estate,2024-04-07,2024-05-06,1666,9.8,Neural Networks Co -AI07440,AI Consultant,77065,EUR,65505,EN,CT,Germany,L,Denmark,50,"TensorFlow, SQL, AWS",PhD,0,Automotive,2025-04-28,2025-06-26,2078,5.5,Autonomous Tech -AI07441,AI Consultant,60980,AUD,82323,EN,FL,Australia,M,Norway,100,"Python, NLP, TensorFlow, Deep Learning",PhD,1,Energy,2024-10-27,2024-11-30,1528,7.9,Algorithmic Solutions -AI07442,Principal Data Scientist,122642,JPY,13490620,SE,FT,Japan,M,Canada,0,"MLOps, Java, Data Visualization, Hadoop, Python",Associate,6,Automotive,2024-09-04,2024-11-04,1486,8.7,Smart Analytics -AI07443,Machine Learning Researcher,126416,USD,126416,MI,FT,Norway,S,Norway,0,"Spark, Mathematics, Python",Master,2,Retail,2024-06-03,2024-07-07,1354,7.2,DataVision Ltd -AI07444,Data Analyst,43069,USD,43069,EN,FT,China,L,China,50,"Java, Python, Git, Spark, TensorFlow",Bachelor,1,Real Estate,2024-05-15,2024-07-09,2034,8.9,Autonomous Tech -AI07445,AI Product Manager,191754,SGD,249280,EX,FL,Singapore,L,Singapore,0,"Spark, MLOps, Docker, NLP, TensorFlow",Master,19,Manufacturing,2024-01-26,2024-03-13,1056,6.3,Future Systems -AI07446,Principal Data Scientist,89978,SGD,116971,MI,PT,Singapore,S,Singapore,100,"PyTorch, TensorFlow, Data Visualization, Computer Vision",PhD,4,Gaming,2025-03-19,2025-05-31,2223,6.2,Predictive Systems -AI07447,Deep Learning Engineer,69497,SGD,90346,EN,CT,Singapore,M,Singapore,0,"Tableau, Python, TensorFlow, NLP, Computer Vision",Associate,1,Education,2024-11-02,2024-12-27,2304,7,Digital Transformation LLC -AI07448,NLP Engineer,68144,CAD,85180,EN,CT,Canada,L,Poland,100,"Kubernetes, Scala, GCP, Docker, Hadoop",PhD,0,Gaming,2024-09-03,2024-11-09,1002,5.6,Predictive Systems -AI07449,Machine Learning Researcher,245939,JPY,27053290,EX,FL,Japan,L,Japan,50,"SQL, Data Visualization, Python",PhD,15,Retail,2025-04-07,2025-06-19,1029,6.1,Cloud AI Solutions -AI07450,Computer Vision Engineer,143618,EUR,122075,EX,CT,France,M,France,100,"Docker, GCP, NLP, Azure, Kubernetes",Master,12,Energy,2024-01-11,2024-03-02,1998,6.3,Cloud AI Solutions -AI07451,AI Software Engineer,118901,EUR,101066,MI,FL,Netherlands,L,Netherlands,100,"Linux, Java, Statistics",Bachelor,4,Transportation,2024-02-11,2024-03-09,2248,5.5,Algorithmic Solutions -AI07452,AI Research Scientist,31907,USD,31907,MI,PT,India,S,India,0,"MLOps, Spark, Linux, Data Visualization, NLP",PhD,4,Real Estate,2025-03-26,2025-05-25,2009,8.9,Quantum Computing Inc -AI07453,AI Specialist,165521,USD,165521,EX,PT,Sweden,M,Sweden,0,"Computer Vision, R, Linux",Master,16,Healthcare,2024-02-17,2024-03-09,993,9.5,Neural Networks Co -AI07454,Principal Data Scientist,143655,USD,143655,SE,FL,Finland,L,Finland,100,"MLOps, Spark, Java, NLP, SQL",Associate,7,Media,2024-01-01,2024-02-16,1009,5.6,DeepTech Ventures -AI07455,Data Engineer,18305,USD,18305,EN,CT,India,M,India,0,"SQL, AWS, Spark",Bachelor,1,Finance,2024-01-02,2024-01-18,1652,5.8,Autonomous Tech -AI07456,Principal Data Scientist,103388,CHF,93049,EN,PT,Switzerland,L,Israel,0,"SQL, Mathematics, Spark, TensorFlow",Associate,0,Education,2025-04-26,2025-07-06,1717,5.4,Digital Transformation LLC -AI07457,Autonomous Systems Engineer,216271,USD,216271,EX,FL,Israel,M,Israel,100,"Python, Linux, Java, TensorFlow",Master,14,Energy,2024-10-25,2024-12-10,666,6.3,Future Systems -AI07458,Autonomous Systems Engineer,54685,JPY,6015350,EN,PT,Japan,M,Japan,50,"Python, Linux, Hadoop, Data Visualization",Master,0,Media,2024-08-28,2024-11-03,1196,6.3,Neural Networks Co -AI07459,ML Ops Engineer,101910,USD,101910,SE,FT,South Korea,M,Canada,50,"Tableau, GCP, Azure",Master,6,Real Estate,2025-04-15,2025-06-11,1897,7.4,Algorithmic Solutions -AI07460,Deep Learning Engineer,232335,JPY,25556850,EX,FL,Japan,M,Japan,100,"Scala, Spark, Java, SQL",Master,19,Technology,2024-10-18,2024-12-11,606,9.1,Machine Intelligence Group -AI07461,Machine Learning Engineer,196676,GBP,147507,EX,PT,United Kingdom,S,United Kingdom,50,"Linux, Azure, TensorFlow, Tableau, PyTorch",Associate,18,Technology,2024-02-11,2024-02-29,1568,8.1,AI Innovations -AI07462,Machine Learning Engineer,97001,USD,97001,MI,PT,United States,M,Singapore,100,"PyTorch, Java, Mathematics, Deep Learning",Associate,2,Healthcare,2024-07-30,2024-08-17,1730,8.6,DeepTech Ventures -AI07463,AI Software Engineer,141916,EUR,120629,SE,FL,Germany,L,Germany,100,"Python, TensorFlow, Azure",Master,9,Manufacturing,2024-10-20,2024-11-28,2447,6.7,Advanced Robotics -AI07464,Machine Learning Engineer,58453,USD,58453,EN,FT,United States,S,Malaysia,0,"Linux, Azure, Statistics",PhD,1,Gaming,2024-01-25,2024-02-08,524,9.4,TechCorp Inc -AI07465,AI Architect,65377,EUR,55570,EN,FT,Germany,M,Germany,0,"SQL, Statistics, AWS, Docker",Master,0,Technology,2024-04-17,2024-06-19,1603,5.8,DeepTech Ventures -AI07466,Machine Learning Engineer,84606,SGD,109988,MI,FL,Singapore,S,Singapore,100,"GCP, NLP, Python, Data Visualization, Spark",Master,3,Government,2024-10-21,2024-11-08,2113,9.1,TechCorp Inc -AI07467,ML Ops Engineer,61087,EUR,51924,EN,FT,France,M,France,0,"NLP, R, MLOps",Master,0,Automotive,2025-04-26,2025-06-18,2334,6.1,Quantum Computing Inc -AI07468,NLP Engineer,66540,AUD,89829,EN,FL,Australia,M,China,0,"Spark, Docker, PyTorch, Computer Vision",PhD,0,Healthcare,2024-06-28,2024-08-14,2020,7.2,DeepTech Ventures -AI07469,Machine Learning Researcher,148528,USD,148528,SE,FT,Israel,L,Israel,0,"MLOps, Java, AWS, Deep Learning",Master,9,Telecommunications,2025-01-23,2025-03-09,874,7.4,Smart Analytics -AI07470,Deep Learning Engineer,126440,USD,126440,EX,FT,South Korea,S,South Korea,100,"R, Computer Vision, Scala, Java",Associate,18,Transportation,2024-09-04,2024-09-23,764,5.9,DataVision Ltd -AI07471,Research Scientist,117780,CHF,106002,EN,FT,Switzerland,L,Switzerland,0,"Computer Vision, Data Visualization, Linux, MLOps",Bachelor,1,Finance,2025-04-28,2025-05-21,2477,6.3,DataVision Ltd -AI07472,AI Research Scientist,129661,USD,129661,EX,FT,Finland,M,Ukraine,50,"NLP, MLOps, Python, Spark, Mathematics",Master,10,Real Estate,2024-03-02,2024-04-02,914,6.2,Smart Analytics -AI07473,Robotics Engineer,46753,EUR,39740,EN,PT,Austria,S,Austria,0,"SQL, Hadoop, Statistics, Spark",Associate,0,Manufacturing,2024-05-25,2024-07-06,1228,6.7,TechCorp Inc -AI07474,Computer Vision Engineer,43491,USD,43491,EX,FL,India,S,Vietnam,0,"Azure, TensorFlow, Scala",Bachelor,12,Healthcare,2024-10-16,2024-12-15,1489,7.5,Autonomous Tech -AI07475,AI Architect,120298,SGD,156387,MI,PT,Singapore,L,Singapore,0,"Kubernetes, Git, Spark, Linux, SQL",PhD,3,Gaming,2024-02-25,2024-04-24,890,5.4,DataVision Ltd -AI07476,ML Ops Engineer,260872,USD,260872,EX,FT,Norway,S,Norway,0,"Java, Data Visualization, MLOps",Associate,13,Education,2025-03-23,2025-04-20,1870,5.4,AI Innovations -AI07477,Robotics Engineer,71601,AUD,96661,EN,FT,Australia,S,Australia,50,"Linux, Hadoop, AWS, Python, Deep Learning",Master,0,Education,2025-04-25,2025-06-10,1267,5.9,Algorithmic Solutions -AI07478,Machine Learning Engineer,49525,USD,49525,EX,FL,India,M,Portugal,50,"Docker, Git, GCP, Scala",PhD,15,Manufacturing,2024-04-28,2024-05-20,1446,8.2,AI Innovations -AI07479,AI Research Scientist,82352,USD,82352,EN,FL,Ireland,L,Ireland,50,"GCP, Python, Computer Vision",PhD,1,Healthcare,2024-04-25,2024-05-30,1036,9.6,Neural Networks Co -AI07480,Machine Learning Researcher,238897,USD,238897,EX,CT,Norway,M,Norway,0,"Git, Linux, Statistics",Bachelor,12,Transportation,2024-05-05,2024-06-11,638,7.1,Neural Networks Co -AI07481,AI Research Scientist,64610,USD,64610,EN,CT,Israel,L,Israel,100,"Spark, Kubernetes, Linux, GCP, AWS",PhD,1,Retail,2024-06-04,2024-07-04,552,6.9,Future Systems -AI07482,Principal Data Scientist,121207,USD,121207,EX,FL,Finland,S,Finland,50,"GCP, Git, Statistics",Associate,12,Healthcare,2024-08-10,2024-09-07,1835,8.7,AI Innovations -AI07483,AI Specialist,118359,JPY,13019490,SE,FL,Japan,M,Japan,50,"MLOps, Linux, Java, TensorFlow, Python",Associate,7,Media,2024-11-13,2024-12-24,1107,6.4,Algorithmic Solutions -AI07484,NLP Engineer,176333,CHF,158700,SE,FL,Switzerland,L,Switzerland,0,"Scala, Kubernetes, Deep Learning",Bachelor,8,Education,2024-11-03,2024-11-30,1123,5.5,Cognitive Computing -AI07485,AI Consultant,137799,USD,137799,SE,CT,Ireland,M,Ireland,50,"Spark, Python, Hadoop",Associate,8,Real Estate,2024-06-20,2024-08-31,1243,7.2,Quantum Computing Inc -AI07486,AI Architect,147983,USD,147983,EX,CT,Sweden,S,Russia,50,"SQL, TensorFlow, Tableau, AWS, Mathematics",Master,16,Energy,2025-02-06,2025-04-01,1503,8.1,Quantum Computing Inc -AI07487,AI Research Scientist,44458,USD,44458,EN,FT,Finland,S,Finland,0,"Azure, Scala, Tableau",Bachelor,0,Telecommunications,2024-03-26,2024-06-06,2344,5.6,Algorithmic Solutions -AI07488,ML Ops Engineer,182046,EUR,154739,EX,CT,Netherlands,M,Netherlands,0,"Python, Java, Linux, Statistics, Deep Learning",Bachelor,17,Retail,2024-02-02,2024-04-12,2221,6,DeepTech Ventures -AI07489,Robotics Engineer,89818,SGD,116763,EN,FL,Singapore,L,Singapore,100,"Java, PyTorch, GCP, Tableau",Master,0,Gaming,2024-03-29,2024-05-26,636,5.7,Machine Intelligence Group -AI07490,NLP Engineer,154108,GBP,115581,SE,CT,United Kingdom,M,New Zealand,0,"PyTorch, Kubernetes, Computer Vision",PhD,8,Manufacturing,2025-02-15,2025-04-01,1863,9.1,Machine Intelligence Group -AI07491,Autonomous Systems Engineer,77976,USD,77976,EN,FT,Ireland,M,Ireland,0,"SQL, GCP, Java, Hadoop, Data Visualization",Associate,1,Retail,2024-06-14,2024-07-24,2169,6.7,AI Innovations -AI07492,Computer Vision Engineer,158800,AUD,214380,SE,FT,Australia,L,Australia,100,"Kubernetes, Python, NLP, R",Associate,5,Technology,2024-08-04,2024-09-29,895,5.4,Digital Transformation LLC -AI07493,AI Software Engineer,269552,CHF,242597,EX,FL,Switzerland,L,Switzerland,50,"NLP, Kubernetes, Spark",Associate,16,Retail,2024-09-26,2024-11-21,1202,8.9,Cloud AI Solutions -AI07494,ML Ops Engineer,40777,USD,40777,SE,FT,India,M,India,50,"AWS, MLOps, Java, Scala",Associate,6,Telecommunications,2024-04-21,2024-05-20,1471,9.3,Future Systems -AI07495,Data Scientist,40524,USD,40524,EN,FL,China,L,China,0,"TensorFlow, Azure, MLOps, Linux",Master,1,Government,2024-01-20,2024-03-08,1447,7.8,DeepTech Ventures -AI07496,AI Product Manager,104604,USD,104604,SE,PT,Finland,S,Mexico,100,"NLP, Docker, Data Visualization, Python",Master,8,Retail,2024-03-17,2024-05-24,1519,7.1,Neural Networks Co -AI07497,Research Scientist,108828,GBP,81621,SE,FL,United Kingdom,S,Indonesia,50,"Python, Kubernetes, MLOps, Linux, Mathematics",Bachelor,7,Real Estate,2024-11-22,2024-12-14,2377,5.6,Digital Transformation LLC -AI07498,AI Product Manager,332899,USD,332899,EX,FL,Denmark,L,Denmark,0,"GCP, SQL, PyTorch",PhD,10,Telecommunications,2024-09-23,2024-10-12,786,8.8,Digital Transformation LLC -AI07499,AI Product Manager,282331,USD,282331,EX,FL,United States,M,United States,0,"Statistics, Tableau, Python, Computer Vision, TensorFlow",PhD,17,Media,2024-09-01,2024-10-17,2115,9.5,Predictive Systems -AI07500,Robotics Engineer,50649,USD,50649,MI,FT,China,L,China,0,"Computer Vision, Git, Hadoop",PhD,3,Government,2024-05-04,2024-07-05,754,7.3,Cognitive Computing -AI07501,AI Product Manager,74786,JPY,8226460,EN,FL,Japan,S,Ukraine,100,"AWS, Statistics, R, Hadoop, TensorFlow",Associate,1,Real Estate,2024-01-11,2024-01-30,1792,8,Cognitive Computing -AI07502,Machine Learning Engineer,246647,USD,246647,EX,CT,Denmark,L,Colombia,50,"Git, Linux, Python, Deep Learning, MLOps",Bachelor,11,Telecommunications,2024-05-12,2024-06-24,1926,8.9,Neural Networks Co -AI07503,Machine Learning Engineer,219909,USD,219909,EX,CT,Norway,S,Norway,0,"SQL, Java, Scala, Spark",Bachelor,17,Media,2024-09-06,2024-10-21,798,7.7,Quantum Computing Inc -AI07504,AI Research Scientist,137360,SGD,178568,EX,PT,Singapore,S,Norway,100,"MLOps, Azure, Scala, AWS",Master,13,Media,2025-03-29,2025-05-29,1811,9.3,DeepTech Ventures -AI07505,Data Analyst,80377,USD,80377,EN,CT,Sweden,M,United States,50,"PyTorch, Hadoop, TensorFlow, Computer Vision",Master,1,Healthcare,2024-05-15,2024-06-13,1584,6,Neural Networks Co -AI07506,AI Software Engineer,150710,JPY,16578100,SE,PT,Japan,L,Japan,100,"Mathematics, Spark, Docker, Statistics",PhD,6,Automotive,2024-06-13,2024-08-14,2040,5.4,Cognitive Computing -AI07507,Head of AI,165703,USD,165703,EX,CT,Israel,L,Ireland,50,"Kubernetes, GCP, Computer Vision",Master,16,Transportation,2025-03-29,2025-05-05,1006,6,AI Innovations -AI07508,AI Product Manager,89181,USD,89181,EN,FL,Denmark,S,Singapore,0,"Python, Azure, Mathematics",PhD,0,Energy,2025-02-18,2025-03-20,875,7.7,Smart Analytics -AI07509,Robotics Engineer,179770,CHF,161793,SE,FL,Switzerland,S,Switzerland,0,"NLP, GCP, Docker, Git, Azure",Associate,6,Manufacturing,2024-09-15,2024-10-17,2220,8.3,DataVision Ltd -AI07510,Machine Learning Researcher,148095,USD,148095,SE,FL,Sweden,M,Sweden,0,"Spark, Scala, Deep Learning, Hadoop",Associate,8,Media,2024-06-17,2024-08-16,784,9.3,Predictive Systems -AI07511,AI Software Engineer,86619,USD,86619,MI,PT,United States,S,Sweden,0,"Spark, GCP, Java, R",Bachelor,4,Government,2024-01-19,2024-03-27,1171,7.7,DeepTech Ventures -AI07512,Data Engineer,94298,USD,94298,SE,FL,South Korea,S,South Korea,100,"Scala, Computer Vision, Docker, Java",Associate,6,Energy,2024-11-06,2024-12-28,1362,6.9,Predictive Systems -AI07513,Computer Vision Engineer,196323,USD,196323,SE,CT,Norway,M,Norway,0,"PyTorch, SQL, Spark, TensorFlow",Master,8,Automotive,2024-12-13,2025-01-04,1981,6.6,Predictive Systems -AI07514,Robotics Engineer,21114,USD,21114,EN,CT,India,L,India,100,"Computer Vision, SQL, Tableau",PhD,0,Energy,2025-03-21,2025-04-15,2127,5.5,Autonomous Tech -AI07515,NLP Engineer,149569,EUR,127134,SE,FL,Austria,L,Austria,100,"Kubernetes, Git, SQL",Bachelor,5,Retail,2024-04-30,2024-06-24,2372,8.1,Future Systems -AI07516,Machine Learning Engineer,103038,USD,103038,MI,FL,Sweden,M,Sweden,0,"Computer Vision, Python, Java, Tableau",PhD,2,Energy,2025-03-14,2025-05-03,1504,7.8,Smart Analytics -AI07517,Head of AI,118703,USD,118703,SE,PT,Israel,M,Israel,50,"GCP, PyTorch, Docker",Associate,5,Gaming,2024-10-09,2024-12-04,536,5.4,Smart Analytics -AI07518,AI Consultant,65083,USD,65083,EN,FL,South Korea,L,Vietnam,50,"Linux, Deep Learning, Data Visualization, TensorFlow, Kubernetes",Bachelor,1,Media,2024-05-31,2024-07-21,2356,7.8,Autonomous Tech -AI07519,Data Analyst,143495,USD,143495,SE,PT,Norway,M,Norway,100,"PyTorch, AWS, Scala, Java",PhD,8,Gaming,2024-12-31,2025-01-18,811,7.4,Autonomous Tech -AI07520,Autonomous Systems Engineer,158654,USD,158654,SE,FL,Norway,L,Norway,50,"AWS, Git, Python, GCP, Scala",Bachelor,7,Gaming,2024-10-28,2024-12-21,1527,6.8,Advanced Robotics -AI07521,Head of AI,76071,EUR,64660,MI,FL,Netherlands,S,Netherlands,100,"Kubernetes, Git, Scala, Computer Vision, Python",PhD,2,Education,2024-07-08,2024-08-14,688,8.4,TechCorp Inc -AI07522,Data Analyst,70355,USD,70355,MI,FL,Finland,M,Finland,50,"Java, Spark, Hadoop, Mathematics",Associate,2,Technology,2024-07-25,2024-08-24,2367,5.2,DeepTech Ventures -AI07523,Data Analyst,100575,CAD,125719,MI,CT,Canada,M,Canada,100,"Spark, Tableau, Azure, NLP, Mathematics",PhD,2,Manufacturing,2025-01-04,2025-01-24,1421,6.6,Advanced Robotics -AI07524,Machine Learning Researcher,137502,GBP,103127,SE,FL,United Kingdom,M,United Kingdom,50,"PyTorch, SQL, NLP",PhD,9,Manufacturing,2024-07-24,2024-09-02,1538,5.6,Quantum Computing Inc -AI07525,Data Analyst,76419,AUD,103166,EN,FT,Australia,M,Australia,0,"Python, Deep Learning, Linux, Mathematics, Kubernetes",PhD,0,Education,2024-10-13,2024-12-25,925,9.2,Algorithmic Solutions -AI07526,AI Research Scientist,76902,USD,76902,MI,PT,Finland,M,Finland,50,"TensorFlow, Kubernetes, Spark, Azure, Git",PhD,4,Education,2024-09-20,2024-10-23,2336,8.8,AI Innovations -AI07527,AI Product Manager,89926,USD,89926,EN,CT,Denmark,S,China,50,"Azure, Git, NLP, GCP, Scala",PhD,1,Retail,2024-06-11,2024-07-23,1513,7.4,Future Systems -AI07528,Research Scientist,213625,EUR,181581,EX,FT,Netherlands,S,Philippines,50,"Docker, Java, Data Visualization, TensorFlow, MLOps",Master,14,Manufacturing,2024-09-14,2024-11-13,2394,9.8,Cognitive Computing -AI07529,AI Architect,160222,EUR,136189,EX,FL,Austria,L,Austria,50,"GCP, Linux, Azure, Git",PhD,14,Transportation,2024-01-07,2024-03-03,885,8.1,Smart Analytics -AI07530,Machine Learning Engineer,35947,USD,35947,MI,FL,India,M,Spain,50,"SQL, GCP, Deep Learning",PhD,4,Finance,2024-11-28,2024-12-18,2230,5,Predictive Systems -AI07531,Research Scientist,53653,SGD,69749,EN,CT,Singapore,S,Brazil,0,"Git, Data Visualization, R, Java, GCP",Associate,1,Government,2024-10-16,2024-12-23,2404,6.5,Machine Intelligence Group -AI07532,NLP Engineer,108963,EUR,92619,SE,CT,Netherlands,M,Portugal,0,"Python, TensorFlow, NLP",Associate,7,Telecommunications,2025-01-20,2025-03-09,1210,8.2,Autonomous Tech -AI07533,AI Software Engineer,77378,USD,77378,MI,CT,South Korea,S,Estonia,0,"Spark, Computer Vision, Scala, SQL",PhD,4,Energy,2024-06-16,2024-08-12,1392,5.7,Advanced Robotics -AI07534,Machine Learning Engineer,84375,EUR,71719,MI,CT,Germany,S,Germany,0,"NLP, Data Visualization, Python, Tableau",PhD,4,Healthcare,2025-03-30,2025-05-07,2486,7.8,Advanced Robotics -AI07535,AI Architect,212229,CAD,265286,EX,CT,Canada,L,Canada,0,"NLP, Mathematics, Git, TensorFlow",Bachelor,18,Media,2024-09-30,2024-11-27,1563,8.4,TechCorp Inc -AI07536,Machine Learning Researcher,122917,USD,122917,EX,FT,Israel,S,Israel,0,"Docker, MLOps, TensorFlow, Data Visualization, Linux",PhD,14,Technology,2024-05-31,2024-07-02,1245,8,Advanced Robotics -AI07537,AI Product Manager,75040,EUR,63784,EN,CT,France,L,France,50,"Azure, Python, Linux, Java",Bachelor,0,Technology,2024-01-03,2024-01-24,843,6.2,Autonomous Tech -AI07538,Data Scientist,302015,USD,302015,EX,CT,Denmark,M,Turkey,50,"Computer Vision, GCP, Git, SQL, Hadoop",Master,11,Transportation,2024-08-11,2024-09-09,1447,5.2,TechCorp Inc -AI07539,Data Scientist,100206,EUR,85175,MI,CT,Germany,M,Germany,0,"NLP, Kubernetes, Mathematics",Bachelor,3,Finance,2024-03-24,2024-05-28,1544,6.6,TechCorp Inc -AI07540,Machine Learning Researcher,74112,CAD,92640,EN,FL,Canada,M,Turkey,100,"SQL, PyTorch, AWS, TensorFlow",Master,0,Retail,2024-06-06,2024-07-31,1498,5.6,Digital Transformation LLC -AI07541,Data Engineer,52847,USD,52847,SE,FL,India,L,India,0,"Statistics, Azure, Computer Vision, Deep Learning, SQL",Associate,9,Consulting,2024-04-22,2024-05-15,614,8.4,Future Systems -AI07542,AI Research Scientist,121952,EUR,103659,SE,CT,Austria,M,Austria,0,"Java, Scala, Spark",PhD,9,Retail,2024-02-03,2024-04-08,808,10,Smart Analytics -AI07543,AI Specialist,22932,USD,22932,EN,FT,India,M,India,0,"SQL, Kubernetes, Tableau",Bachelor,1,Technology,2024-06-08,2024-08-12,1556,7.3,Cloud AI Solutions -AI07544,Robotics Engineer,185551,USD,185551,EX,FL,Ireland,L,Sweden,50,"Azure, SQL, Data Visualization, Linux",Bachelor,12,Real Estate,2024-03-13,2024-05-13,608,6.6,Quantum Computing Inc -AI07545,NLP Engineer,144980,USD,144980,EX,FL,South Korea,M,Poland,50,"Python, Linux, AWS, Deep Learning",PhD,12,Manufacturing,2025-04-20,2025-05-24,1125,8.2,Smart Analytics -AI07546,NLP Engineer,137887,USD,137887,MI,CT,United States,L,United States,100,"NLP, Linux, Tableau",Master,4,Government,2024-04-09,2024-05-12,642,10,AI Innovations -AI07547,Principal Data Scientist,26422,USD,26422,EN,FT,China,S,Latvia,100,"Hadoop, Spark, Java, Scala",Master,0,Technology,2025-01-14,2025-01-30,1300,8.4,Future Systems -AI07548,ML Ops Engineer,92812,USD,92812,EN,FL,United States,M,United States,100,"NLP, Computer Vision, Linux",Master,0,Media,2024-12-18,2025-02-20,1521,7.3,TechCorp Inc -AI07549,AI Software Engineer,60930,USD,60930,MI,FT,South Korea,S,South Korea,0,"SQL, TensorFlow, Statistics, Git",Bachelor,3,Healthcare,2024-11-25,2025-01-23,1040,7.5,Autonomous Tech -AI07550,ML Ops Engineer,218956,USD,218956,EX,PT,Finland,M,Finland,50,"SQL, Java, Azure",PhD,18,Education,2024-01-21,2024-03-13,1594,8.8,Digital Transformation LLC -AI07551,Data Scientist,75273,USD,75273,MI,CT,Israel,M,Israel,50,"MLOps, Tableau, Spark",PhD,4,Transportation,2024-09-16,2024-10-18,801,6,Algorithmic Solutions -AI07552,Autonomous Systems Engineer,49221,USD,49221,MI,CT,China,M,China,0,"PyTorch, Hadoop, Python, SQL",Associate,2,Energy,2024-08-28,2024-10-03,1967,5.6,AI Innovations -AI07553,Robotics Engineer,199243,EUR,169357,EX,FT,Germany,L,Indonesia,0,"Docker, TensorFlow, Tableau, SQL",Bachelor,13,Energy,2024-12-31,2025-01-16,1820,9.5,Advanced Robotics -AI07554,NLP Engineer,98108,USD,98108,SE,CT,Ireland,S,Ireland,0,"Tableau, Deep Learning, Git, Python, Scala",PhD,8,Healthcare,2024-10-19,2024-12-17,710,7.6,AI Innovations -AI07555,Principal Data Scientist,251392,EUR,213683,EX,FT,France,L,France,0,"Kubernetes, PyTorch, GCP",PhD,13,Gaming,2025-04-02,2025-06-01,1365,6.9,Smart Analytics -AI07556,Head of AI,102675,SGD,133478,SE,CT,Singapore,S,South Africa,50,"Spark, Hadoop, SQL, Tableau",Associate,8,Automotive,2024-05-30,2024-06-14,2253,8.5,Machine Intelligence Group -AI07557,NLP Engineer,289291,JPY,31822010,EX,PT,Japan,L,Japan,50,"Scala, Kubernetes, R, MLOps",Master,16,Government,2024-12-13,2025-01-18,537,5.7,Quantum Computing Inc -AI07558,AI Consultant,58763,SGD,76392,EN,FT,Singapore,S,Singapore,100,"Scala, PyTorch, AWS",Master,1,Manufacturing,2024-11-21,2024-12-30,1146,8.1,Algorithmic Solutions -AI07559,Machine Learning Engineer,119668,USD,119668,SE,PT,Israel,M,Italy,0,"NLP, Kubernetes, Scala, GCP",Bachelor,8,Finance,2024-09-26,2024-11-12,986,6.9,Machine Intelligence Group -AI07560,Data Scientist,50856,AUD,68656,EN,FT,Australia,S,New Zealand,0,"Azure, NLP, Kubernetes, Scala",Associate,1,Government,2024-11-11,2024-12-02,1490,7.7,Digital Transformation LLC -AI07561,ML Ops Engineer,98859,USD,98859,MI,FT,Norway,S,Norway,50,"Computer Vision, Java, Scala",Master,3,Media,2025-04-26,2025-07-08,932,7,Predictive Systems -AI07562,Principal Data Scientist,276933,USD,276933,EX,FT,Denmark,M,Denmark,50,"Deep Learning, R, MLOps",PhD,14,Manufacturing,2024-09-28,2024-12-03,2353,9.2,Neural Networks Co -AI07563,AI Research Scientist,154287,USD,154287,SE,FT,Norway,S,Norway,0,"Linux, Statistics, NLP",PhD,7,Gaming,2024-02-06,2024-04-09,1675,5.1,Smart Analytics -AI07564,AI Product Manager,185605,EUR,157764,EX,FL,Germany,M,India,0,"SQL, Scala, Kubernetes, MLOps, Spark",Master,11,Healthcare,2024-10-13,2024-11-02,2420,7.4,Autonomous Tech -AI07565,Computer Vision Engineer,147217,AUD,198743,EX,PT,Australia,M,Australia,50,"PyTorch, Scala, Mathematics",Bachelor,13,Real Estate,2024-12-03,2025-01-23,1945,6.1,Cognitive Computing -AI07566,Machine Learning Engineer,84531,USD,84531,MI,PT,Norway,S,Norway,0,"Linux, Python, Scala, Computer Vision",Master,2,Telecommunications,2024-02-13,2024-03-23,967,8.9,Autonomous Tech -AI07567,AI Specialist,188423,GBP,141317,EX,CT,United Kingdom,S,United Kingdom,100,"Scala, Deep Learning, Git, NLP",Bachelor,13,Manufacturing,2024-10-22,2024-11-23,2357,6.3,Advanced Robotics -AI07568,Machine Learning Engineer,93853,USD,93853,EN,PT,United States,L,Norway,50,"Docker, Kubernetes, AWS, Tableau",Associate,1,Real Estate,2025-01-22,2025-03-03,1530,9.7,Smart Analytics -AI07569,AI Software Engineer,173348,USD,173348,EX,FL,South Korea,L,South Korea,100,"NLP, Linux, SQL",Master,13,Gaming,2025-02-23,2025-04-19,786,6.3,TechCorp Inc -AI07570,Computer Vision Engineer,81621,EUR,69378,MI,CT,France,S,Ghana,100,"Java, NLP, R, Docker, Tableau",PhD,4,Technology,2024-08-04,2024-09-11,2069,7.6,DeepTech Ventures -AI07571,Machine Learning Researcher,171427,USD,171427,EX,FL,Finland,S,Chile,0,"Python, Spark, Docker, Computer Vision",Master,12,Retail,2024-08-07,2024-09-19,1068,9.8,Machine Intelligence Group -AI07572,AI Architect,124261,USD,124261,MI,CT,United States,M,United States,100,"Computer Vision, Java, PyTorch, Git, Linux",PhD,4,Technology,2025-03-02,2025-05-12,1411,8.5,TechCorp Inc -AI07573,Autonomous Systems Engineer,78038,GBP,58529,MI,CT,United Kingdom,M,United Kingdom,100,"Mathematics, Hadoop, R",Master,3,Technology,2024-01-16,2024-02-19,1335,9.3,AI Innovations -AI07574,NLP Engineer,84616,JPY,9307760,MI,FL,Japan,S,Japan,50,"Statistics, R, Computer Vision",PhD,2,Automotive,2025-03-09,2025-03-26,757,6.8,AI Innovations -AI07575,Deep Learning Engineer,56130,USD,56130,EN,CT,Ireland,S,Ireland,50,"NLP, Deep Learning, R, SQL, MLOps",PhD,1,Transportation,2025-04-04,2025-06-12,984,7.1,Algorithmic Solutions -AI07576,Principal Data Scientist,180941,EUR,153800,EX,FL,Austria,L,Vietnam,50,"Deep Learning, NLP, Python",Master,15,Education,2024-12-22,2025-01-15,1773,5.9,Smart Analytics -AI07577,Robotics Engineer,36195,USD,36195,MI,PT,India,M,Spain,0,"Kubernetes, Linux, Git, Python",PhD,2,Technology,2024-02-04,2024-02-22,1586,9.2,Quantum Computing Inc -AI07578,Machine Learning Researcher,74934,USD,74934,EN,FT,Denmark,M,Denmark,100,"GCP, PyTorch, Tableau, Deep Learning",Associate,1,Finance,2024-01-30,2024-02-16,2411,6.4,Neural Networks Co -AI07579,Data Analyst,92668,EUR,78768,MI,FL,France,S,France,0,"Python, Hadoop, Data Visualization, Git, Docker",Bachelor,3,Gaming,2024-05-03,2024-06-03,2476,7.3,Digital Transformation LLC -AI07580,ML Ops Engineer,106319,AUD,143531,MI,PT,Australia,M,Australia,0,"SQL, NLP, MLOps, Hadoop",Associate,4,Media,2025-02-19,2025-04-25,655,5.5,Cognitive Computing -AI07581,AI Product Manager,119428,USD,119428,SE,FT,Finland,L,Finland,50,"Java, GCP, Hadoop, Data Visualization, R",Bachelor,5,Technology,2024-01-10,2024-01-24,2417,9.7,Neural Networks Co -AI07582,Research Scientist,148430,JPY,16327300,EX,CT,Japan,S,Japan,100,"Git, Spark, TensorFlow, SQL, Deep Learning",PhD,18,Automotive,2024-04-18,2024-06-23,907,8.3,Neural Networks Co -AI07583,AI Software Engineer,97277,EUR,82685,SE,FT,France,S,India,0,"Mathematics, Kubernetes, Tableau, NLP",Master,5,Technology,2024-07-22,2024-08-26,2242,5.7,Cloud AI Solutions -AI07584,Head of AI,22873,USD,22873,EN,PT,India,S,India,0,"Python, Computer Vision, Git, TensorFlow",Associate,0,Telecommunications,2025-01-15,2025-02-08,1699,8,Digital Transformation LLC -AI07585,Principal Data Scientist,78064,EUR,66354,MI,PT,Germany,M,Germany,100,"Hadoop, Git, Statistics",Master,4,Technology,2025-01-25,2025-02-08,974,8.5,AI Innovations -AI07586,AI Research Scientist,29207,USD,29207,EN,FL,China,S,China,50,"SQL, Kubernetes, MLOps",Associate,1,Energy,2024-02-19,2024-04-11,893,8.4,DeepTech Ventures -AI07587,ML Ops Engineer,171296,EUR,145602,SE,CT,Netherlands,L,Kenya,0,"Hadoop, Spark, Docker, Azure, Scala",Master,7,Automotive,2024-10-22,2024-11-10,1712,6.6,Machine Intelligence Group -AI07588,Data Engineer,60437,USD,60437,EN,CT,Israel,L,Israel,100,"Java, TensorFlow, Docker, Computer Vision",Associate,1,Transportation,2024-03-28,2024-04-18,975,8.4,Algorithmic Solutions -AI07589,AI Specialist,106204,SGD,138065,SE,PT,Singapore,S,Singapore,100,"Python, Kubernetes, AWS",Bachelor,5,Retail,2024-07-01,2024-09-01,1199,7.2,Advanced Robotics -AI07590,NLP Engineer,30321,USD,30321,MI,FT,India,M,India,100,"Data Visualization, Java, Docker, Python",Bachelor,4,Consulting,2024-08-27,2024-09-13,1329,9.5,Cloud AI Solutions -AI07591,Head of AI,189953,EUR,161460,EX,CT,Austria,L,Austria,0,"Spark, SQL, Data Visualization, Deep Learning",Associate,10,Real Estate,2025-01-01,2025-02-04,1500,8.9,Smart Analytics -AI07592,Machine Learning Researcher,54381,EUR,46224,EN,CT,Germany,S,Germany,0,"Linux, TensorFlow, Statistics, Azure, Scala",Bachelor,0,Automotive,2024-06-23,2024-08-30,942,5.9,Cognitive Computing -AI07593,Machine Learning Researcher,88330,JPY,9716300,EN,FT,Japan,L,Japan,0,"MLOps, Hadoop, SQL, Git, AWS",Associate,0,Healthcare,2025-03-10,2025-04-29,1145,8.1,Cognitive Computing -AI07594,AI Product Manager,154426,USD,154426,SE,FT,Sweden,L,Thailand,100,"Computer Vision, Tableau, MLOps, SQL",Bachelor,7,Education,2024-02-16,2024-03-09,1855,7.6,Digital Transformation LLC -AI07595,AI Software Engineer,119526,EUR,101597,SE,PT,Netherlands,S,Netherlands,50,"Java, Kubernetes, Spark, Mathematics",Master,6,Media,2025-03-21,2025-04-19,2244,8,Cognitive Computing -AI07596,AI Architect,137197,USD,137197,SE,FT,Denmark,M,Vietnam,0,"Java, Docker, PyTorch, AWS, Hadoop",Associate,6,Healthcare,2024-12-25,2025-02-19,1065,6.7,Smart Analytics -AI07597,Head of AI,117462,USD,117462,SE,CT,Israel,M,Colombia,50,"Data Visualization, PyTorch, NLP, Docker",Associate,8,Transportation,2024-09-27,2024-10-24,2441,6.3,DeepTech Ventures -AI07598,Data Analyst,163257,EUR,138768,SE,FT,Germany,L,Germany,0,"TensorFlow, PyTorch, Statistics, Scala",Master,7,Healthcare,2024-11-18,2024-12-09,840,7.3,Neural Networks Co -AI07599,Data Analyst,185659,USD,185659,EX,PT,Israel,L,Israel,50,"Data Visualization, Docker, Computer Vision, NLP",PhD,10,Education,2024-08-29,2024-11-03,1965,7.2,DeepTech Ventures -AI07600,AI Architect,266642,CAD,333303,EX,CT,Canada,L,Germany,0,"PyTorch, GCP, Azure, Mathematics, Statistics",Bachelor,16,Energy,2025-04-16,2025-05-08,1518,5.8,Smart Analytics -AI07601,ML Ops Engineer,73310,USD,73310,EN,FT,Norway,S,Brazil,0,"SQL, Statistics, MLOps, R",Associate,1,Retail,2024-04-26,2024-05-31,530,10,Machine Intelligence Group -AI07602,AI Software Engineer,175822,CHF,158240,MI,FT,Switzerland,L,Portugal,100,"Computer Vision, GCP, Linux, AWS, Tableau",PhD,3,Healthcare,2024-06-05,2024-07-13,1150,5,Neural Networks Co -AI07603,Machine Learning Researcher,82893,USD,82893,EN,FT,Israel,L,Romania,50,"Azure, MLOps, Kubernetes, Docker",PhD,0,Real Estate,2025-02-24,2025-04-14,1318,9.8,Advanced Robotics -AI07604,Computer Vision Engineer,121156,USD,121156,SE,PT,Finland,M,United States,100,"Mathematics, GCP, MLOps, Docker",Associate,7,Technology,2025-04-15,2025-05-01,1153,5.6,Machine Intelligence Group -AI07605,Machine Learning Engineer,85501,USD,85501,MI,CT,Ireland,S,Ireland,100,"Scala, NLP, Java, R",PhD,2,Energy,2024-05-01,2024-06-17,1409,9.7,Cloud AI Solutions -AI07606,Deep Learning Engineer,200592,USD,200592,EX,FL,Sweden,L,Sweden,100,"Scala, PyTorch, Tableau, Mathematics, Kubernetes",PhD,19,Automotive,2024-12-02,2024-12-17,714,6.3,DeepTech Ventures -AI07607,Data Analyst,157367,USD,157367,EX,FL,United States,S,Hungary,50,"MLOps, PyTorch, Kubernetes",PhD,18,Finance,2025-01-09,2025-02-05,1308,8.7,Digital Transformation LLC -AI07608,AI Architect,96408,USD,96408,MI,FL,Norway,S,Norway,50,"R, TensorFlow, SQL, Azure, Spark",Bachelor,4,Automotive,2024-03-23,2024-04-25,574,9,Cloud AI Solutions -AI07609,AI Research Scientist,41086,USD,41086,MI,CT,China,M,China,100,"TensorFlow, Docker, GCP",Bachelor,4,Telecommunications,2025-01-18,2025-03-03,1587,8.9,Quantum Computing Inc -AI07610,AI Architect,87699,EUR,74544,MI,CT,France,L,France,100,"R, PyTorch, Docker, TensorFlow, SQL",Bachelor,2,Government,2024-10-18,2024-11-29,2105,8.6,Predictive Systems -AI07611,AI Architect,173811,CHF,156430,SE,PT,Switzerland,S,Switzerland,0,"Python, PyTorch, Linux",Associate,7,Retail,2025-04-24,2025-05-21,1883,6.7,Cognitive Computing -AI07612,AI Product Manager,126276,EUR,107335,SE,FL,France,S,France,0,"Statistics, GCP, R, Git",Master,5,Government,2024-12-13,2025-01-13,1695,5.4,Quantum Computing Inc -AI07613,Computer Vision Engineer,242933,EUR,206493,EX,FL,Netherlands,M,Finland,100,"Spark, TensorFlow, Linux",PhD,11,Consulting,2024-12-16,2025-01-23,2045,6.3,AI Innovations -AI07614,Robotics Engineer,62515,USD,62515,EN,FL,United States,S,United States,50,"PyTorch, SQL, TensorFlow",Master,1,Media,2025-03-29,2025-04-14,871,7.3,Cognitive Computing -AI07615,AI Software Engineer,96579,USD,96579,SE,FT,Israel,M,Israel,100,"Scala, TensorFlow, Deep Learning",PhD,9,Telecommunications,2024-09-15,2024-11-10,1055,8.3,DataVision Ltd -AI07616,Machine Learning Researcher,66417,USD,66417,EN,FT,Norway,M,Norway,0,"R, NLP, Azure, Git, SQL",Master,0,Consulting,2024-11-07,2024-12-12,795,6.6,TechCorp Inc -AI07617,AI Product Manager,66775,USD,66775,EN,PT,Ireland,M,Mexico,100,"Computer Vision, Git, MLOps, NLP, TensorFlow",Master,0,Education,2024-02-29,2024-04-29,550,9.8,Predictive Systems -AI07618,Autonomous Systems Engineer,112618,SGD,146403,MI,PT,Singapore,L,Singapore,100,"AWS, PyTorch, Docker, TensorFlow, Scala",Associate,4,Finance,2025-02-04,2025-03-31,1936,6.3,Digital Transformation LLC -AI07619,AI Consultant,172134,USD,172134,SE,FT,Norway,M,Brazil,0,"Hadoop, Computer Vision, Python, Docker, GCP",Master,9,Finance,2024-08-12,2024-08-28,2319,6.3,Algorithmic Solutions -AI07620,Research Scientist,89513,EUR,76086,SE,FL,France,S,France,0,"Scala, Git, Python, Azure",Associate,6,Telecommunications,2024-08-08,2024-09-27,2056,6.2,Machine Intelligence Group -AI07621,Head of AI,124617,USD,124617,SE,FL,Denmark,S,Denmark,100,"Azure, NLP, Spark, Hadoop",Associate,9,Gaming,2025-03-19,2025-04-03,1175,7.2,Machine Intelligence Group -AI07622,NLP Engineer,211681,USD,211681,EX,FL,Sweden,S,Colombia,100,"Spark, Tableau, Kubernetes",Bachelor,13,Real Estate,2024-06-25,2024-07-23,2078,6.8,Digital Transformation LLC -AI07623,AI Architect,70756,USD,70756,EN,CT,Sweden,L,Czech Republic,100,"Python, NLP, AWS",PhD,1,Media,2025-03-21,2025-04-29,2181,8.7,Algorithmic Solutions -AI07624,AI Consultant,124712,EUR,106005,SE,PT,Germany,S,Germany,100,"Kubernetes, Tableau, Mathematics, MLOps, Git",Associate,8,Real Estate,2024-01-23,2024-03-07,2333,8,Digital Transformation LLC -AI07625,Research Scientist,81724,USD,81724,EN,FT,Ireland,L,Ireland,0,"Python, Azure, Mathematics, GCP, Statistics",Bachelor,0,Real Estate,2024-10-25,2024-11-21,2292,9.4,TechCorp Inc -AI07626,Data Scientist,98773,USD,98773,MI,FT,Ireland,L,Ireland,50,"TensorFlow, NLP, Git, Hadoop",Bachelor,4,Transportation,2024-04-20,2024-06-29,640,6.3,Future Systems -AI07627,NLP Engineer,123212,SGD,160176,SE,PT,Singapore,S,Singapore,0,"Azure, PyTorch, GCP",PhD,5,Transportation,2024-01-23,2024-03-03,1509,5.9,Future Systems -AI07628,AI Consultant,158235,EUR,134500,EX,CT,France,M,France,100,"Scala, Git, Data Visualization, AWS",PhD,11,Healthcare,2025-04-04,2025-05-28,2070,6.1,Machine Intelligence Group -AI07629,Robotics Engineer,243378,USD,243378,EX,FL,Finland,L,Japan,50,"Linux, Deep Learning, Python, SQL",Master,17,Manufacturing,2024-01-23,2024-03-15,1771,8.9,Smart Analytics -AI07630,Data Engineer,72159,SGD,93807,EN,CT,Singapore,L,Sweden,100,"GCP, Docker, MLOps",Associate,1,Education,2025-04-26,2025-06-29,1183,9,Machine Intelligence Group -AI07631,Computer Vision Engineer,117447,CAD,146809,SE,FT,Canada,M,Canada,50,"Git, Python, TensorFlow",Bachelor,7,Gaming,2025-02-25,2025-04-03,907,6.4,Predictive Systems -AI07632,Data Engineer,93398,EUR,79388,EN,FL,Netherlands,L,Netherlands,50,"Python, TensorFlow, Data Visualization, Spark",PhD,0,Telecommunications,2024-09-21,2024-10-15,595,6.4,DeepTech Ventures -AI07633,Head of AI,130830,USD,130830,SE,FL,Sweden,L,Latvia,0,"Kubernetes, Python, Hadoop",Associate,5,Technology,2024-04-19,2024-05-25,1607,8.3,Quantum Computing Inc -AI07634,Data Engineer,226889,USD,226889,EX,PT,United States,S,Sweden,50,"GCP, Kubernetes, Data Visualization, Deep Learning, Hadoop",Bachelor,12,Retail,2025-02-02,2025-03-11,792,9,Cognitive Computing -AI07635,Data Engineer,81702,JPY,8987220,EN,FT,Japan,M,Japan,50,"SQL, GCP, Statistics",Associate,0,Consulting,2024-06-12,2024-07-20,504,5.3,Quantum Computing Inc -AI07636,AI Product Manager,111373,EUR,94667,SE,FL,Germany,S,Germany,0,"Mathematics, Python, Tableau, TensorFlow, PyTorch",Bachelor,6,Consulting,2025-01-05,2025-02-08,2037,6.3,Neural Networks Co -AI07637,Robotics Engineer,57310,USD,57310,MI,FL,South Korea,S,Switzerland,50,"Docker, NLP, Python, Kubernetes, Mathematics",Master,4,Telecommunications,2024-05-03,2024-06-27,1556,7.6,Smart Analytics -AI07638,Principal Data Scientist,43322,USD,43322,MI,FL,China,S,China,50,"Spark, Python, TensorFlow, Linux",PhD,3,Real Estate,2024-11-02,2024-12-10,1131,7.2,Predictive Systems -AI07639,Computer Vision Engineer,95292,CHF,85763,EN,PT,Switzerland,L,Switzerland,100,"Git, Hadoop, SQL, Computer Vision",Master,0,Education,2024-02-12,2024-03-25,1940,5.2,DataVision Ltd -AI07640,NLP Engineer,174223,GBP,130667,EX,FT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, Azure",Master,10,Telecommunications,2024-05-26,2024-06-19,981,7.2,DeepTech Ventures -AI07641,Machine Learning Engineer,84562,AUD,114159,MI,FT,Australia,M,Australia,100,"Linux, GCP, TensorFlow, Kubernetes, Statistics",Master,3,Technology,2024-11-09,2024-12-11,1796,5.3,DataVision Ltd -AI07642,Data Analyst,166804,AUD,225185,SE,FL,Australia,L,Philippines,100,"Tableau, Python, TensorFlow, Mathematics",Associate,7,Retail,2024-05-09,2024-07-10,745,5.4,Algorithmic Solutions -AI07643,AI Consultant,32768,USD,32768,EN,PT,China,L,China,50,"Python, SQL, Docker, Mathematics",Bachelor,1,Real Estate,2025-04-30,2025-05-24,1770,7.9,Cognitive Computing -AI07644,Head of AI,217646,EUR,184999,EX,PT,Netherlands,S,Brazil,50,"Spark, TensorFlow, Scala, Hadoop, MLOps",PhD,10,Healthcare,2024-12-10,2025-01-15,2225,8.5,TechCorp Inc -AI07645,Computer Vision Engineer,144258,EUR,122619,SE,FL,Netherlands,S,Netherlands,50,"PyTorch, R, Hadoop",Bachelor,5,Media,2025-01-25,2025-02-18,2300,9.7,DeepTech Ventures -AI07646,AI Architect,104597,USD,104597,SE,FL,South Korea,M,South Korea,100,"GCP, SQL, PyTorch, R",Bachelor,8,Transportation,2024-06-27,2024-07-28,1106,8.2,Neural Networks Co -AI07647,AI Specialist,95849,USD,95849,MI,FL,South Korea,L,South Korea,50,"Tableau, Kubernetes, PyTorch",Bachelor,4,Automotive,2024-11-06,2024-11-22,1076,6,DeepTech Ventures -AI07648,Computer Vision Engineer,265185,EUR,225407,EX,FT,Netherlands,L,Netherlands,50,"Python, PyTorch, Java, Computer Vision",Master,18,Energy,2024-12-14,2025-01-29,674,6.9,Predictive Systems -AI07649,AI Specialist,63417,EUR,53904,EN,CT,Austria,L,South Africa,50,"Linux, Scala, Kubernetes, GCP, Mathematics",PhD,1,Media,2024-10-09,2024-11-20,1572,9.6,Algorithmic Solutions -AI07650,Robotics Engineer,162111,USD,162111,SE,PT,Ireland,L,Thailand,50,"Docker, Statistics, GCP, Mathematics, PyTorch",PhD,8,Real Estate,2024-08-04,2024-10-06,1021,7,AI Innovations -AI07651,AI Architect,51830,USD,51830,EN,CT,South Korea,M,South Korea,0,"GCP, Scala, Tableau, PyTorch, Statistics",Bachelor,1,Energy,2024-08-04,2024-09-22,2067,9.2,Cloud AI Solutions -AI07652,AI Architect,80660,USD,80660,EN,CT,Denmark,L,Denmark,0,"Docker, AWS, MLOps",Bachelor,0,Energy,2024-11-03,2024-12-22,1825,5.3,Cognitive Computing -AI07653,Research Scientist,183478,USD,183478,SE,FT,Denmark,M,New Zealand,0,"Python, TensorFlow, Computer Vision, MLOps",PhD,8,Automotive,2024-02-24,2024-03-11,2350,9.6,Machine Intelligence Group -AI07654,Data Scientist,93839,EUR,79763,EN,FT,Netherlands,L,Netherlands,0,"TensorFlow, Spark, Computer Vision",Associate,1,Manufacturing,2024-01-22,2024-02-08,1415,5.5,Smart Analytics -AI07655,Machine Learning Engineer,63882,JPY,7027020,EN,FT,Japan,L,Japan,0,"Git, AWS, Python, Tableau, Linux",Associate,1,Technology,2024-02-27,2024-04-24,2251,6.2,DeepTech Ventures -AI07656,Data Analyst,126076,GBP,94557,SE,FT,United Kingdom,L,Ghana,50,"Data Visualization, SQL, Azure",Master,6,Finance,2024-02-11,2024-04-05,2026,9.8,DeepTech Ventures -AI07657,Principal Data Scientist,91813,JPY,10099430,MI,FL,Japan,S,Australia,100,"Scala, Data Visualization, Kubernetes, SQL, AWS",Master,3,Education,2024-07-23,2024-08-08,1170,7.6,DataVision Ltd -AI07658,AI Architect,44127,USD,44127,EN,PT,Finland,S,Finland,100,"SQL, Java, Data Visualization",Master,1,Media,2024-05-09,2024-06-05,2336,5,Predictive Systems -AI07659,AI Research Scientist,70724,CAD,88405,EN,FT,Canada,M,Canada,50,"Data Visualization, MLOps, SQL",Associate,0,Automotive,2024-01-20,2024-02-05,541,8,Advanced Robotics -AI07660,Data Analyst,306380,GBP,229785,EX,FT,United Kingdom,L,United Kingdom,50,"PyTorch, TensorFlow, Mathematics, Azure, R",Bachelor,16,Finance,2024-06-16,2024-07-03,1441,9.6,Digital Transformation LLC -AI07661,Data Scientist,59061,EUR,50202,EN,PT,Germany,S,Germany,100,"Scala, SQL, Data Visualization, TensorFlow, Git",Associate,0,Gaming,2024-08-28,2024-10-12,2199,5.2,Future Systems -AI07662,Data Scientist,127372,USD,127372,SE,PT,Denmark,S,Hungary,100,"GCP, AWS, Python, Linux",PhD,6,Telecommunications,2025-04-02,2025-06-10,1330,5.6,DataVision Ltd -AI07663,AI Software Engineer,324728,CHF,292255,EX,FT,Switzerland,L,Switzerland,50,"Hadoop, Python, TensorFlow, Linux",PhD,13,Retail,2024-08-03,2024-09-23,1682,5.2,Smart Analytics -AI07664,AI Consultant,132294,USD,132294,SE,FT,Denmark,S,Denmark,100,"Data Visualization, Python, GCP",Master,7,Manufacturing,2024-01-22,2024-03-09,1383,7.8,AI Innovations -AI07665,Data Engineer,110217,EUR,93684,SE,FL,Germany,S,Germany,50,"R, Tableau, Azure, Python, Hadoop",Associate,7,Finance,2024-08-09,2024-08-29,2475,7.2,Smart Analytics -AI07666,Deep Learning Engineer,108463,USD,108463,MI,FL,Denmark,M,Brazil,50,"Statistics, SQL, Linux, NLP, Hadoop",PhD,4,Consulting,2024-04-24,2024-07-05,1652,8.4,AI Innovations -AI07667,AI Consultant,60083,USD,60083,MI,FL,South Korea,M,Italy,100,"AWS, Scala, Docker, NLP, Linux",PhD,2,Transportation,2025-02-19,2025-03-18,1564,8.2,Machine Intelligence Group -AI07668,NLP Engineer,74921,USD,74921,EX,CT,India,L,India,0,"TensorFlow, NLP, R, Python",PhD,11,Government,2024-02-28,2024-03-26,1818,6.1,Digital Transformation LLC -AI07669,AI Consultant,229930,CHF,206937,EX,FT,Switzerland,S,Kenya,0,"Java, GCP, Statistics, Python, TensorFlow",Associate,13,Retail,2024-05-12,2024-06-24,1945,9.9,Advanced Robotics -AI07670,Research Scientist,134348,CAD,167935,SE,FL,Canada,M,Canada,50,"NLP, Kubernetes, MLOps, Java",Bachelor,9,Transportation,2024-11-21,2025-01-17,2441,6.7,Neural Networks Co -AI07671,AI Research Scientist,84844,GBP,63633,MI,FT,United Kingdom,S,United Kingdom,50,"Scala, Hadoop, Data Visualization, Git, Python",Bachelor,2,Media,2024-12-14,2025-01-13,1273,8.1,Smart Analytics -AI07672,Computer Vision Engineer,75519,CAD,94399,MI,CT,Canada,S,Canada,100,"SQL, PyTorch, GCP",PhD,2,Energy,2024-08-15,2024-09-15,2158,8.4,Machine Intelligence Group -AI07673,AI Specialist,83770,USD,83770,MI,FT,Finland,M,Switzerland,100,"Kubernetes, Scala, Statistics, PyTorch, NLP",PhD,4,Education,2024-12-21,2025-01-11,1827,6,Future Systems -AI07674,Computer Vision Engineer,99649,USD,99649,EN,PT,United States,L,Romania,100,"GCP, R, Data Visualization, SQL, Linux",Associate,1,Energy,2025-04-25,2025-05-14,1620,7.7,DeepTech Ventures -AI07675,Data Engineer,288454,USD,288454,EX,FT,Denmark,M,Denmark,100,"AWS, MLOps, GCP, Scala",Master,18,Consulting,2024-06-27,2024-08-26,1751,5.5,Cognitive Computing -AI07676,Research Scientist,185909,EUR,158023,EX,FL,Netherlands,S,Netherlands,100,"PyTorch, TensorFlow, GCP, Statistics, Java",Associate,15,Telecommunications,2024-11-06,2024-12-19,1477,5.7,Digital Transformation LLC -AI07677,Robotics Engineer,82676,USD,82676,EN,FL,United States,M,United States,100,"AWS, Git, Data Visualization",Associate,0,Automotive,2024-03-03,2024-03-28,2443,6,Cognitive Computing -AI07678,Deep Learning Engineer,180023,USD,180023,EX,FT,South Korea,S,China,0,"Scala, GCP, Deep Learning, Data Visualization, Hadoop",Associate,11,Real Estate,2024-06-08,2024-07-05,2224,10,Quantum Computing Inc -AI07679,AI Consultant,85630,USD,85630,EN,PT,Ireland,L,Ireland,0,"Java, Kubernetes, Scala, Deep Learning, Computer Vision",Bachelor,0,Media,2025-04-02,2025-06-01,1688,9.3,Cognitive Computing -AI07680,AI Research Scientist,91309,EUR,77613,MI,FT,France,L,France,0,"Java, NLP, Linux, TensorFlow",Associate,4,Education,2024-08-20,2024-10-08,1703,7.9,Digital Transformation LLC -AI07681,AI Consultant,73734,EUR,62674,EN,FL,Austria,M,Austria,0,"Python, MLOps, PyTorch, R",PhD,1,Gaming,2024-04-15,2024-05-12,577,7.4,Predictive Systems -AI07682,Research Scientist,180469,USD,180469,EX,FT,Sweden,S,Sweden,50,"SQL, Python, MLOps, AWS",PhD,17,Government,2025-02-24,2025-05-08,2313,5.1,Smart Analytics -AI07683,Machine Learning Researcher,55451,EUR,47133,EN,CT,Austria,L,Austria,50,"Spark, Kubernetes, Statistics, Computer Vision, PyTorch",Master,1,Finance,2025-01-05,2025-02-21,1493,9.2,DeepTech Ventures -AI07684,Deep Learning Engineer,113073,USD,113073,EN,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Data Visualization, Python, R",PhD,0,Automotive,2024-11-28,2025-01-28,2139,9.3,Neural Networks Co -AI07685,Computer Vision Engineer,68363,EUR,58109,EN,FT,France,M,France,50,"Hadoop, Linux, Mathematics, Python",Master,0,Government,2024-08-12,2024-08-29,1755,9.5,Advanced Robotics -AI07686,Robotics Engineer,62860,USD,62860,EX,CT,China,S,China,50,"Hadoop, SQL, NLP",Associate,16,Real Estate,2024-06-30,2024-07-19,540,5.1,Predictive Systems -AI07687,NLP Engineer,176108,USD,176108,EX,PT,Ireland,S,Israel,50,"Python, Hadoop, Kubernetes, Scala, Git",Bachelor,11,Telecommunications,2024-05-30,2024-07-11,1478,5.2,TechCorp Inc -AI07688,AI Software Engineer,86453,EUR,73485,MI,FT,France,L,France,0,"Azure, GCP, Spark, Scala, Hadoop",Master,2,Real Estate,2024-07-20,2024-09-24,1547,8.2,Advanced Robotics -AI07689,Head of AI,170116,EUR,144599,EX,FL,Netherlands,L,Czech Republic,0,"Kubernetes, Java, Git, AWS, Computer Vision",PhD,17,Government,2025-02-23,2025-04-03,1237,5.5,Smart Analytics -AI07690,Principal Data Scientist,79589,EUR,67651,EN,CT,Netherlands,L,Sweden,50,"Python, TensorFlow, SQL, Linux",PhD,1,Government,2025-02-01,2025-02-20,1924,7.6,Cloud AI Solutions -AI07691,AI Architect,190789,USD,190789,EX,PT,Finland,S,Finland,50,"PyTorch, Tableau, SQL, Git",Bachelor,10,Education,2024-04-21,2024-06-12,659,9.9,Smart Analytics -AI07692,Data Engineer,79062,USD,79062,EN,PT,United States,M,United States,0,"Data Visualization, Docker, Mathematics",Bachelor,0,Telecommunications,2024-05-15,2024-07-10,1269,8.7,Algorithmic Solutions -AI07693,Deep Learning Engineer,212322,GBP,159242,EX,FL,United Kingdom,M,United Kingdom,0,"Python, Linux, SQL",Bachelor,14,Retail,2024-11-16,2025-01-19,651,8.2,TechCorp Inc -AI07694,Machine Learning Engineer,126710,CAD,158388,SE,FT,Canada,M,Turkey,0,"Git, Kubernetes, GCP, Spark, NLP",Bachelor,6,Healthcare,2024-03-20,2024-05-14,804,8.2,Autonomous Tech -AI07695,Deep Learning Engineer,135567,SGD,176237,SE,FT,Singapore,S,Singapore,100,"Python, Hadoop, SQL, Data Visualization, NLP",Associate,5,Transportation,2024-08-28,2024-09-22,1554,5.1,AI Innovations -AI07696,Autonomous Systems Engineer,77684,GBP,58263,MI,CT,United Kingdom,S,United Kingdom,50,"Kubernetes, AWS, Azure, R",Associate,2,Finance,2024-02-19,2024-03-31,1848,6.3,Quantum Computing Inc -AI07697,Head of AI,87101,CHF,78391,EN,FT,Switzerland,S,Switzerland,50,"TensorFlow, AWS, Mathematics, NLP",PhD,1,Automotive,2024-04-24,2024-05-21,1700,6.2,Quantum Computing Inc -AI07698,Head of AI,65182,USD,65182,EN,FL,Ireland,L,Ireland,100,"NLP, Statistics, SQL, Data Visualization",Master,0,Manufacturing,2024-05-12,2024-06-23,1768,7.2,Predictive Systems -AI07699,Research Scientist,155741,JPY,17131510,SE,CT,Japan,L,Sweden,50,"SQL, Tableau, NLP, Data Visualization, Azure",Master,8,Automotive,2024-06-02,2024-06-19,590,9.5,Advanced Robotics -AI07700,Computer Vision Engineer,35630,USD,35630,MI,PT,India,M,Russia,100,"Scala, R, Deep Learning, Computer Vision, GCP",PhD,2,Gaming,2024-04-07,2024-05-14,501,7.2,Cognitive Computing -AI07701,Machine Learning Engineer,92685,EUR,78782,EN,PT,Netherlands,L,Philippines,50,"Hadoop, Statistics, Scala, TensorFlow, NLP",Master,0,Automotive,2025-03-28,2025-05-08,1696,9.5,Digital Transformation LLC -AI07702,Machine Learning Engineer,63966,EUR,54371,EN,FT,France,S,France,50,"Spark, Python, Statistics",Associate,0,Government,2024-03-03,2024-03-19,562,6.7,TechCorp Inc -AI07703,Data Scientist,193308,AUD,260966,EX,FL,Australia,L,Italy,50,"Azure, Hadoop, SQL, Python",Associate,19,Media,2024-10-08,2024-11-08,2482,8.6,Quantum Computing Inc -AI07704,AI Architect,68810,JPY,7569100,EN,PT,Japan,M,Japan,50,"Linux, Statistics, Python",Bachelor,0,Technology,2024-01-09,2024-02-05,1000,5.1,DataVision Ltd -AI07705,Head of AI,133424,CHF,120082,MI,PT,Switzerland,S,Switzerland,50,"R, Deep Learning, SQL",Associate,2,Finance,2025-03-19,2025-05-25,2253,8.2,Cloud AI Solutions -AI07706,Head of AI,99725,CHF,89753,MI,PT,Switzerland,S,Switzerland,0,"Python, Statistics, Java, TensorFlow",Associate,3,Telecommunications,2024-03-25,2024-05-07,1474,9,Cognitive Computing -AI07707,Principal Data Scientist,92186,USD,92186,MI,CT,Finland,M,Finland,100,"Mathematics, Python, MLOps, Kubernetes, Linux",Associate,3,Consulting,2025-02-12,2025-02-27,1793,6.8,Advanced Robotics -AI07708,AI Consultant,67420,EUR,57307,MI,CT,France,S,France,0,"Scala, AWS, Tableau",Master,4,Telecommunications,2025-04-17,2025-06-03,1056,7.9,Future Systems -AI07709,ML Ops Engineer,63821,CAD,79776,EN,CT,Canada,L,South Korea,50,"TensorFlow, Tableau, Statistics, Java, Linux",PhD,0,Finance,2025-03-14,2025-04-14,1786,7.2,TechCorp Inc -AI07710,ML Ops Engineer,79858,JPY,8784380,MI,PT,Japan,M,Finland,100,"Tableau, Statistics, Hadoop, Scala, Python",Bachelor,2,Media,2024-08-07,2024-08-22,1849,9.5,AI Innovations -AI07711,Autonomous Systems Engineer,92037,GBP,69028,MI,CT,United Kingdom,S,United Kingdom,50,"Python, MLOps, GCP, TensorFlow, Tableau",PhD,3,Telecommunications,2024-05-26,2024-07-15,1867,7.2,Future Systems -AI07712,Deep Learning Engineer,145429,JPY,15997190,SE,CT,Japan,L,Japan,0,"NLP, PyTorch, SQL, R, Kubernetes",Bachelor,6,Healthcare,2024-04-17,2024-05-27,1406,7.6,DeepTech Ventures -AI07713,ML Ops Engineer,49642,USD,49642,EN,FT,South Korea,M,South Korea,50,"Git, Data Visualization, Scala, Python",Bachelor,1,Healthcare,2024-07-27,2024-09-05,1285,5.5,Quantum Computing Inc -AI07714,NLP Engineer,123567,SGD,160637,SE,FT,Singapore,M,Singapore,0,"Git, Java, Tableau",Associate,9,Transportation,2025-01-07,2025-02-19,2046,8.7,Autonomous Tech -AI07715,AI Architect,110776,CHF,99698,EN,FL,Switzerland,M,Switzerland,50,"SQL, Java, Hadoop, Azure, Python",Associate,1,Transportation,2024-10-17,2024-11-13,1304,8.6,Neural Networks Co -AI07716,Principal Data Scientist,173372,AUD,234052,EX,PT,Australia,M,Australia,50,"Deep Learning, Python, Spark, Hadoop, Mathematics",Bachelor,16,Transportation,2024-11-01,2024-12-28,519,9.9,DataVision Ltd -AI07717,Autonomous Systems Engineer,66211,EUR,56279,EN,CT,Germany,L,Germany,100,"Git, Hadoop, Spark, TensorFlow, Java",PhD,1,Gaming,2024-11-22,2024-12-28,2210,9.7,Cognitive Computing -AI07718,Data Scientist,152011,SGD,197614,SE,FT,Singapore,L,Japan,0,"Docker, Linux, Computer Vision, SQL, PyTorch",PhD,5,Transportation,2024-05-29,2024-06-30,501,5.5,Algorithmic Solutions -AI07719,ML Ops Engineer,227332,SGD,295532,EX,FL,Singapore,S,Singapore,50,"Python, Hadoop, SQL, Azure",Bachelor,19,Education,2025-01-15,2025-03-15,1975,8.9,TechCorp Inc -AI07720,Robotics Engineer,124845,CAD,156056,EX,FT,Canada,S,Romania,100,"SQL, NLP, Azure, Statistics, Python",Associate,15,Retail,2024-03-05,2024-05-14,1059,6.6,Machine Intelligence Group -AI07721,NLP Engineer,88027,SGD,114435,MI,FT,Singapore,M,Singapore,0,"PyTorch, Computer Vision, MLOps, Docker",PhD,3,Real Estate,2024-07-28,2024-09-23,652,8.2,Autonomous Tech -AI07722,Head of AI,160105,USD,160105,SE,PT,Ireland,L,Ireland,50,"Python, Kubernetes, Linux",Master,6,Real Estate,2024-01-31,2024-03-13,1280,9,Machine Intelligence Group -AI07723,AI Research Scientist,45928,USD,45928,SE,FT,India,M,India,0,"Linux, Git, Tableau, Data Visualization",Bachelor,7,Media,2024-10-08,2024-12-05,2291,7.7,Smart Analytics -AI07724,Head of AI,71793,USD,71793,EN,CT,Denmark,M,Denmark,100,"Linux, PyTorch, Computer Vision, Git",Bachelor,1,Automotive,2024-12-08,2024-12-23,1035,6.7,Algorithmic Solutions -AI07725,AI Research Scientist,250916,USD,250916,EX,FT,Norway,L,Norway,0,"Deep Learning, Linux, MLOps, NLP, Tableau",PhD,12,Manufacturing,2024-10-26,2024-11-21,1614,6.4,Future Systems -AI07726,Data Scientist,174103,USD,174103,SE,FL,Denmark,L,Denmark,0,"Git, Linux, NLP, Spark",Associate,6,Manufacturing,2024-04-07,2024-06-14,2322,5.4,Advanced Robotics -AI07727,Principal Data Scientist,109543,GBP,82157,MI,PT,United Kingdom,L,United Kingdom,50,"Azure, Python, GCP, Deep Learning, TensorFlow",Associate,2,Healthcare,2024-10-22,2024-12-07,2284,5.4,TechCorp Inc -AI07728,Robotics Engineer,87605,USD,87605,EN,PT,Ireland,L,Ireland,0,"Azure, Python, Kubernetes, Tableau, TensorFlow",PhD,0,Manufacturing,2024-11-23,2024-12-12,1772,5,Predictive Systems -AI07729,AI Software Engineer,146983,EUR,124936,SE,CT,Germany,M,Germany,0,"Spark, AWS, Git, MLOps",Master,9,Real Estate,2024-04-24,2024-05-16,2162,6.3,Cognitive Computing -AI07730,Deep Learning Engineer,102384,USD,102384,SE,CT,Sweden,M,Brazil,50,"R, Deep Learning, Data Visualization, Hadoop, AWS",Master,8,Technology,2024-06-17,2024-08-22,846,6.4,Predictive Systems -AI07731,AI Research Scientist,261474,JPY,28762140,EX,CT,Japan,L,Japan,50,"Computer Vision, GCP, NLP, Kubernetes, Java",Associate,18,Transportation,2024-04-29,2024-05-21,1030,8.1,Advanced Robotics -AI07732,Data Analyst,74595,CAD,93244,EN,FL,Canada,L,Canada,0,"SQL, Computer Vision, PyTorch, Statistics, Kubernetes",Associate,0,Government,2024-02-17,2024-04-28,736,9,DeepTech Ventures -AI07733,Head of AI,96835,USD,96835,EX,CT,China,L,United Kingdom,0,"Kubernetes, Hadoop, Computer Vision",PhD,18,Government,2024-05-01,2024-06-28,1151,6,Quantum Computing Inc -AI07734,Machine Learning Researcher,136419,USD,136419,MI,PT,Denmark,L,Denmark,0,"Python, Hadoop, Deep Learning, TensorFlow",Master,2,Manufacturing,2024-05-11,2024-06-22,1928,6.7,Digital Transformation LLC -AI07735,Autonomous Systems Engineer,62698,USD,62698,SE,FL,China,L,China,100,"Hadoop, Python, Tableau",Associate,9,Energy,2024-01-01,2024-02-07,512,7,Machine Intelligence Group -AI07736,AI Architect,82570,GBP,61928,MI,PT,United Kingdom,M,Turkey,50,"Scala, Git, Tableau, Computer Vision",Bachelor,4,Retail,2024-04-22,2024-05-06,1986,5.6,Predictive Systems -AI07737,Autonomous Systems Engineer,63993,EUR,54394,EN,FT,France,S,Chile,50,"Scala, SQL, Git, Linux",PhD,1,Energy,2024-04-22,2024-07-02,2119,5.6,Quantum Computing Inc -AI07738,Deep Learning Engineer,117183,USD,117183,MI,FT,Israel,L,Israel,0,"TensorFlow, AWS, PyTorch",Master,4,Technology,2024-03-29,2024-05-15,615,8.3,Smart Analytics -AI07739,NLP Engineer,228120,SGD,296556,EX,CT,Singapore,S,Estonia,50,"Kubernetes, Data Visualization, GCP, Scala, Computer Vision",PhD,18,Media,2024-05-29,2024-07-11,982,6.3,Predictive Systems -AI07740,Autonomous Systems Engineer,168150,USD,168150,EX,FL,Ireland,S,Ireland,100,"SQL, Docker, NLP, Mathematics, Computer Vision",Bachelor,10,Telecommunications,2024-07-10,2024-08-22,2461,7.6,DataVision Ltd -AI07741,Data Engineer,251868,EUR,214088,EX,PT,Netherlands,L,Netherlands,0,"Java, Spark, TensorFlow",PhD,10,Energy,2025-02-27,2025-05-01,2060,6,Future Systems -AI07742,AI Consultant,134610,EUR,114419,SE,PT,Netherlands,M,Netherlands,0,"Python, TensorFlow, PyTorch, Linux",Associate,9,Healthcare,2024-01-03,2024-02-22,2155,9.1,DeepTech Ventures -AI07743,Data Scientist,39473,USD,39473,MI,PT,China,M,Poland,0,"Hadoop, Linux, R, Git, SQL",PhD,2,Government,2024-03-09,2024-04-07,1821,7.2,DataVision Ltd -AI07744,Data Engineer,59378,EUR,50471,EN,FT,Germany,S,Germany,50,"Python, AWS, Java",Bachelor,1,Telecommunications,2025-04-22,2025-06-15,1884,5.9,Cognitive Computing -AI07745,AI Research Scientist,126770,EUR,107755,SE,CT,Austria,L,Austria,0,"Docker, Kubernetes, Azure, MLOps",Master,6,Retail,2024-04-12,2024-06-15,1519,5.6,Cloud AI Solutions -AI07746,AI Research Scientist,78592,CAD,98240,MI,CT,Canada,S,Canada,100,"R, TensorFlow, Deep Learning, Git, Docker",Bachelor,2,Retail,2024-11-13,2024-12-29,1997,8,Quantum Computing Inc -AI07747,Deep Learning Engineer,29559,USD,29559,MI,CT,India,L,India,0,"Hadoop, Deep Learning, Java, Tableau",Associate,2,Healthcare,2024-10-04,2024-11-04,754,7,Cloud AI Solutions -AI07748,AI Software Engineer,223895,USD,223895,EX,CT,Sweden,L,Brazil,100,"SQL, AWS, Deep Learning, Statistics, Data Visualization",Master,12,Gaming,2025-01-02,2025-02-11,793,9.4,AI Innovations -AI07749,Principal Data Scientist,170881,AUD,230689,SE,PT,Australia,L,Japan,0,"PyTorch, MLOps, TensorFlow",Bachelor,8,Technology,2024-09-07,2024-10-26,1484,8.9,AI Innovations -AI07750,AI Architect,77100,SGD,100230,MI,FL,Singapore,M,Vietnam,0,"SQL, Git, Data Visualization, PyTorch",Associate,4,Telecommunications,2024-11-01,2024-12-03,1851,8.6,Smart Analytics -AI07751,AI Research Scientist,61337,EUR,52136,EN,PT,France,L,France,0,"Linux, Statistics, Computer Vision",Bachelor,1,Energy,2025-04-29,2025-06-14,1576,9.8,Machine Intelligence Group -AI07752,Data Engineer,90203,AUD,121774,MI,FT,Australia,M,Australia,0,"Linux, Python, Data Visualization, MLOps",Bachelor,2,Manufacturing,2024-07-18,2024-09-13,1980,9.1,Smart Analytics -AI07753,AI Software Engineer,95206,USD,95206,EX,CT,India,L,India,0,"GCP, Scala, Java, Azure",Master,19,Finance,2024-12-17,2025-02-12,1590,8.3,Smart Analytics -AI07754,Machine Learning Engineer,143694,CHF,129325,SE,CT,Switzerland,S,Switzerland,100,"PyTorch, Java, SQL, MLOps, Deep Learning",Associate,7,Transportation,2024-07-13,2024-09-02,1769,5.7,Neural Networks Co -AI07755,AI Software Engineer,205240,CAD,256550,EX,FT,Canada,S,Canada,0,"TensorFlow, Kubernetes, Statistics, R, MLOps",PhD,19,Technology,2024-10-05,2024-11-02,2041,7.4,Future Systems -AI07756,Principal Data Scientist,130858,CAD,163573,SE,FL,Canada,L,Canada,100,"Computer Vision, SQL, PyTorch",Bachelor,5,Consulting,2024-01-14,2024-03-11,835,9.6,DataVision Ltd -AI07757,AI Specialist,109839,USD,109839,MI,PT,Norway,M,Norway,0,"Tableau, AWS, Python",PhD,2,Energy,2025-01-19,2025-03-22,2213,5.6,Digital Transformation LLC -AI07758,AI Architect,234658,EUR,199459,EX,CT,Germany,L,Germany,0,"Computer Vision, GCP, TensorFlow, Deep Learning, Java",Associate,14,Gaming,2025-03-18,2025-05-21,1240,7.2,Cloud AI Solutions -AI07759,Computer Vision Engineer,212824,USD,212824,EX,FL,Israel,S,United States,50,"AWS, GCP, Data Visualization, Computer Vision",Associate,18,Technology,2024-08-27,2024-10-08,1963,9.2,Smart Analytics -AI07760,Computer Vision Engineer,89614,EUR,76172,MI,FT,France,S,France,100,"TensorFlow, Linux, MLOps, R",Master,4,Gaming,2024-09-11,2024-09-26,1242,7.8,DeepTech Ventures -AI07761,AI Research Scientist,230152,EUR,195629,EX,PT,Germany,L,Germany,50,"Python, AWS, Computer Vision, TensorFlow, Mathematics",Bachelor,16,Real Estate,2025-04-05,2025-05-20,2279,5.6,Algorithmic Solutions -AI07762,Machine Learning Engineer,138749,USD,138749,EX,FT,Finland,M,Philippines,0,"Data Visualization, MLOps, Java, R, NLP",Bachelor,17,Retail,2024-06-28,2024-08-19,997,5.1,TechCorp Inc -AI07763,Data Scientist,151433,USD,151433,SE,FL,Denmark,M,Denmark,0,"Linux, Git, AWS, Tableau, SQL",PhD,6,Manufacturing,2024-05-09,2024-07-12,698,7.8,Cognitive Computing -AI07764,Head of AI,113027,USD,113027,MI,FL,United States,M,United States,50,"Scala, Spark, Computer Vision",Master,2,Government,2024-11-12,2025-01-13,522,5.4,Smart Analytics -AI07765,AI Architect,75238,USD,75238,EN,PT,United States,M,Sweden,0,"MLOps, Data Visualization, Statistics, PyTorch",PhD,0,Government,2024-12-04,2024-12-19,2206,6.3,DeepTech Ventures -AI07766,Data Scientist,181300,SGD,235690,EX,CT,Singapore,M,Singapore,0,"Python, GCP, Computer Vision",Bachelor,12,Consulting,2024-04-23,2024-05-28,1081,6.4,DeepTech Ventures -AI07767,Data Analyst,180520,USD,180520,EX,FL,Israel,S,Israel,0,"NLP, Spark, Git",Bachelor,16,Real Estate,2025-03-25,2025-04-14,2169,9.4,Digital Transformation LLC -AI07768,AI Research Scientist,60195,GBP,45146,EN,CT,United Kingdom,S,United Kingdom,100,"R, Python, Tableau, Scala",Bachelor,1,Government,2025-03-01,2025-05-12,2478,7.9,TechCorp Inc -AI07769,Deep Learning Engineer,85237,SGD,110808,EN,FL,Singapore,L,Ghana,50,"Python, Kubernetes, Docker, TensorFlow, SQL",PhD,1,Retail,2024-03-03,2024-05-06,2404,9.4,Advanced Robotics -AI07770,Computer Vision Engineer,120221,USD,120221,SE,FL,Norway,S,New Zealand,100,"Scala, PyTorch, Hadoop, Git, GCP",PhD,8,Government,2024-10-03,2024-12-12,651,7,Cognitive Computing -AI07771,Data Engineer,196214,USD,196214,EX,FT,Finland,M,Finland,50,"Linux, Java, GCP, TensorFlow, NLP",Master,14,Automotive,2024-02-01,2024-03-09,1141,9.8,Advanced Robotics -AI07772,AI Consultant,132988,CAD,166235,SE,FT,Canada,M,Canada,0,"Python, Hadoop, MLOps, TensorFlow, Mathematics",Bachelor,6,Media,2024-06-08,2024-08-09,2131,7.3,Digital Transformation LLC -AI07773,Data Analyst,77664,USD,77664,EN,PT,Ireland,M,Ireland,0,"NLP, Docker, Tableau",PhD,0,Energy,2025-03-06,2025-04-14,2381,6.8,Future Systems -AI07774,Robotics Engineer,148890,CAD,186113,SE,FT,Canada,L,Canada,50,"Scala, Linux, MLOps, Spark, Git",Master,9,Automotive,2025-01-27,2025-03-22,1437,8.6,Machine Intelligence Group -AI07775,Head of AI,95335,USD,95335,MI,PT,Israel,L,China,100,"Python, Hadoop, MLOps",Bachelor,2,Finance,2025-04-12,2025-04-30,2096,9.5,Machine Intelligence Group -AI07776,AI Software Engineer,60390,USD,60390,SE,FT,China,M,China,100,"SQL, GCP, PyTorch, Java",Master,5,Healthcare,2024-02-02,2024-03-19,1377,5.8,TechCorp Inc -AI07777,AI Specialist,113740,CHF,102366,EN,FT,Switzerland,L,Switzerland,50,"Kubernetes, TensorFlow, Python, Linux, Computer Vision",Associate,1,Manufacturing,2024-03-30,2024-05-12,646,7.9,DeepTech Ventures -AI07778,Research Scientist,107116,EUR,91049,SE,PT,France,S,Russia,0,"NLP, PyTorch, AWS, Linux, Computer Vision",Bachelor,5,Automotive,2024-05-31,2024-06-18,1158,9.5,Future Systems -AI07779,Data Scientist,116275,USD,116275,EX,PT,China,L,China,50,"Scala, Java, Spark, Docker",Master,17,Media,2024-03-16,2024-04-07,1611,9,DeepTech Ventures -AI07780,AI Product Manager,75695,EUR,64341,MI,FT,Austria,S,South Korea,50,"Linux, Hadoop, SQL, Spark, Java",Master,4,Education,2024-11-06,2025-01-05,984,5.6,Predictive Systems -AI07781,ML Ops Engineer,123821,EUR,105248,SE,FT,Austria,M,Austria,50,"Kubernetes, Spark, MLOps, NLP",Bachelor,8,Technology,2024-03-08,2024-05-09,2226,8.8,AI Innovations -AI07782,Data Engineer,220673,USD,220673,EX,CT,Ireland,L,Switzerland,50,"Docker, Hadoop, PyTorch, Git",PhD,19,Telecommunications,2024-11-27,2025-02-03,2497,5.6,Smart Analytics -AI07783,ML Ops Engineer,69580,EUR,59143,MI,CT,Netherlands,S,Netherlands,0,"NLP, Git, Kubernetes, Tableau",Master,3,Media,2024-01-10,2024-02-25,752,6.3,Digital Transformation LLC -AI07784,NLP Engineer,64614,USD,64614,EN,CT,Finland,S,Finland,0,"Git, R, Spark, Data Visualization",Master,1,Telecommunications,2024-11-29,2025-01-05,1789,6.1,Cognitive Computing -AI07785,Data Engineer,100944,EUR,85802,SE,CT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch",Master,8,Healthcare,2024-04-10,2024-06-15,1527,6.9,Advanced Robotics -AI07786,Machine Learning Engineer,35266,USD,35266,MI,PT,India,M,India,0,"AWS, SQL, Hadoop, Docker, Computer Vision",PhD,4,Automotive,2024-11-16,2024-11-30,761,7.4,Advanced Robotics -AI07787,AI Software Engineer,79263,AUD,107005,EN,FL,Australia,M,Vietnam,50,"Git, Hadoop, PyTorch",Master,1,Gaming,2024-06-11,2024-07-04,1102,7.8,Smart Analytics -AI07788,Data Scientist,94630,USD,94630,MI,CT,Sweden,S,Sweden,0,"Data Visualization, Azure, Kubernetes, GCP, SQL",PhD,4,Government,2025-02-15,2025-04-03,680,7.7,Neural Networks Co -AI07789,AI Research Scientist,290745,EUR,247133,EX,FT,Netherlands,L,Netherlands,0,"Docker, Linux, AWS",Bachelor,16,Energy,2024-11-05,2024-11-27,2383,7.5,Cloud AI Solutions -AI07790,Computer Vision Engineer,177261,USD,177261,SE,FL,Denmark,M,Vietnam,0,"Azure, PyTorch, SQL, Docker, R",Associate,9,Energy,2024-08-05,2024-10-13,1377,10,Future Systems -AI07791,AI Consultant,79754,SGD,103680,MI,FT,Singapore,S,Singapore,0,"Spark, Computer Vision, Linux, AWS, Statistics",Master,3,Telecommunications,2024-02-15,2024-03-21,970,5.9,AI Innovations -AI07792,AI Specialist,179275,USD,179275,EX,FL,Finland,L,United States,50,"R, AWS, Deep Learning",Master,17,Media,2024-12-11,2025-02-05,2187,5.7,Smart Analytics -AI07793,AI Consultant,120982,CHF,108884,MI,FT,Switzerland,L,Switzerland,0,"Statistics, MLOps, TensorFlow, Java",Master,4,Transportation,2024-01-14,2024-03-19,1448,8,Machine Intelligence Group -AI07794,Data Scientist,56033,USD,56033,EN,FL,Israel,L,Israel,100,"Deep Learning, TensorFlow, Data Visualization, PyTorch",Associate,1,Education,2025-01-20,2025-03-11,1633,8.3,Smart Analytics -AI07795,AI Product Manager,43195,USD,43195,SE,CT,India,L,India,0,"R, Java, Python, Statistics, TensorFlow",Bachelor,6,Technology,2024-06-11,2024-08-05,1479,9.9,Predictive Systems -AI07796,AI Software Engineer,95245,USD,95245,EN,FL,United States,L,Ukraine,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,0,Technology,2024-01-18,2024-03-21,1994,6.3,TechCorp Inc -AI07797,Deep Learning Engineer,68796,USD,68796,MI,PT,South Korea,L,South Korea,0,"Hadoop, Python, Tableau, MLOps, Computer Vision",PhD,4,Education,2024-09-23,2024-10-28,1211,5.1,Future Systems -AI07798,AI Architect,236279,CHF,212651,SE,PT,Switzerland,L,Israel,50,"Kubernetes, SQL, Linux, PyTorch",Master,9,Education,2025-03-05,2025-05-07,1087,6.4,TechCorp Inc -AI07799,Deep Learning Engineer,67944,AUD,91724,EN,CT,Australia,M,Australia,50,"Deep Learning, Kubernetes, Spark, Git",Associate,0,Retail,2025-04-04,2025-05-10,2112,5.6,Predictive Systems -AI07800,Computer Vision Engineer,89810,USD,89810,MI,CT,Denmark,S,Malaysia,100,"Deep Learning, TensorFlow, SQL, Hadoop",Bachelor,4,Media,2024-10-02,2024-11-17,1632,8.6,Machine Intelligence Group -AI07801,Computer Vision Engineer,153315,CAD,191644,EX,FL,Canada,L,Portugal,0,"Java, R, SQL, Deep Learning, Docker",Associate,13,Consulting,2024-11-22,2024-12-17,1764,7.7,TechCorp Inc -AI07802,Machine Learning Researcher,205401,USD,205401,EX,FT,Denmark,M,Denmark,100,"R, TensorFlow, Mathematics",PhD,10,Healthcare,2024-03-18,2024-05-24,1464,8.4,Smart Analytics -AI07803,Robotics Engineer,57780,CAD,72225,EN,PT,Canada,S,Canada,100,"Java, NLP, Mathematics",PhD,1,Retail,2024-10-31,2025-01-10,2381,9.8,TechCorp Inc -AI07804,AI Research Scientist,110762,USD,110762,MI,CT,Norway,L,Sweden,100,"R, Data Visualization, Git, Docker",PhD,2,Real Estate,2024-11-03,2024-12-19,777,6.8,Cognitive Computing -AI07805,Deep Learning Engineer,157791,EUR,134122,SE,FL,France,L,France,50,"Git, Java, GCP, SQL, AWS",PhD,9,Gaming,2024-10-16,2024-11-01,1818,7.8,Cognitive Computing -AI07806,AI Software Engineer,146629,USD,146629,SE,PT,Denmark,S,Denmark,50,"Git, TensorFlow, Deep Learning",Associate,8,Manufacturing,2025-04-25,2025-06-02,1219,8.6,Autonomous Tech -AI07807,AI Consultant,67825,USD,67825,MI,FT,Sweden,S,Poland,100,"Java, Scala, R, SQL, Kubernetes",PhD,3,Education,2025-03-26,2025-06-03,1845,7.4,Autonomous Tech -AI07808,Autonomous Systems Engineer,53522,USD,53522,SE,FL,China,S,China,0,"PyTorch, GCP, Mathematics",Associate,9,Gaming,2025-04-19,2025-05-20,1898,8.6,Future Systems -AI07809,Robotics Engineer,96556,CAD,120695,MI,FT,Canada,L,Portugal,100,"PyTorch, Statistics, Deep Learning",Associate,4,Gaming,2024-10-10,2024-11-19,1150,9.1,DataVision Ltd -AI07810,AI Consultant,161008,USD,161008,SE,CT,Israel,L,Israel,0,"Docker, Deep Learning, Python, Git, Kubernetes",Master,9,Education,2025-03-25,2025-05-08,1648,5.7,Cognitive Computing -AI07811,Head of AI,71917,JPY,7910870,EN,PT,Japan,M,Hungary,100,"Tableau, PyTorch, GCP",Master,1,Media,2024-11-04,2024-12-29,2269,9.6,Neural Networks Co -AI07812,AI Research Scientist,143195,CAD,178994,EX,FL,Canada,S,Canada,50,"Java, Linux, Scala, NLP, Tableau",PhD,13,Healthcare,2025-04-12,2025-06-07,510,5.3,Neural Networks Co -AI07813,Robotics Engineer,135878,SGD,176641,SE,FT,Singapore,S,Singapore,0,"Azure, Kubernetes, Tableau",Bachelor,9,Technology,2024-12-28,2025-02-13,772,8.2,AI Innovations -AI07814,AI Consultant,58123,USD,58123,EN,PT,Finland,L,Finland,50,"Linux, AWS, GCP",Master,1,Manufacturing,2025-01-22,2025-02-10,1596,7.8,Digital Transformation LLC -AI07815,Principal Data Scientist,85459,USD,85459,EX,FT,India,M,Estonia,0,"Scala, Spark, AWS, Statistics",Master,16,Technology,2024-09-10,2024-11-20,1167,7.5,Advanced Robotics -AI07816,AI Consultant,188011,EUR,159809,EX,FL,Germany,S,Germany,0,"SQL, Kubernetes, Tableau",Bachelor,10,Transportation,2024-05-26,2024-07-10,2353,5.7,TechCorp Inc -AI07817,NLP Engineer,76608,USD,76608,EN,CT,United States,M,United States,100,"Hadoop, Spark, Python, GCP, SQL",Associate,1,Transportation,2024-11-19,2025-01-29,617,6.1,AI Innovations -AI07818,Computer Vision Engineer,87288,GBP,65466,MI,PT,United Kingdom,M,Egypt,50,"Statistics, Kubernetes, Tableau, Linux",Master,4,Energy,2024-08-22,2024-09-09,1983,8.5,Cloud AI Solutions -AI07819,AI Specialist,114472,JPY,12591920,SE,CT,Japan,S,France,50,"Mathematics, Hadoop, Spark, Tableau, GCP",Bachelor,5,Education,2024-10-03,2024-11-30,1545,8.3,DeepTech Ventures -AI07820,AI Research Scientist,115293,GBP,86470,MI,CT,United Kingdom,M,Romania,0,"PyTorch, Kubernetes, Deep Learning, Git",Associate,4,Finance,2024-01-17,2024-03-21,1165,6.1,AI Innovations -AI07821,Deep Learning Engineer,85770,USD,85770,SE,PT,South Korea,S,South Korea,50,"GCP, Computer Vision, Hadoop, Azure",PhD,7,Government,2024-08-30,2024-10-31,2128,9.5,Digital Transformation LLC -AI07822,Computer Vision Engineer,153843,EUR,130767,EX,FT,France,M,France,50,"Python, Tableau, SQL, PyTorch, Hadoop",Bachelor,16,Education,2025-02-23,2025-03-23,1151,9.8,DeepTech Ventures -AI07823,NLP Engineer,119824,CHF,107842,MI,FL,Switzerland,M,Switzerland,50,"Linux, Computer Vision, R, Python",PhD,3,Technology,2025-04-25,2025-05-13,2109,8.8,Neural Networks Co -AI07824,Data Engineer,88480,EUR,75208,MI,FL,Germany,M,Finland,100,"PyTorch, Kubernetes, MLOps, Scala, Java",Master,4,Energy,2024-02-16,2024-04-08,1029,9.3,DeepTech Ventures -AI07825,AI Research Scientist,86607,USD,86607,SE,PT,Finland,S,Finland,100,"GCP, AWS, MLOps",PhD,7,Consulting,2024-04-24,2024-05-12,2162,8.8,Digital Transformation LLC -AI07826,AI Research Scientist,185098,EUR,157333,EX,FL,Netherlands,M,Netherlands,50,"Docker, Azure, Git, Deep Learning",Bachelor,18,Gaming,2024-04-11,2024-05-28,902,5.8,AI Innovations -AI07827,AI Specialist,42629,USD,42629,EN,FT,South Korea,S,Sweden,0,"Spark, Hadoop, Tableau",Bachelor,0,Energy,2024-07-06,2024-07-21,1250,5.1,Cloud AI Solutions -AI07828,AI Architect,73796,EUR,62727,EN,FL,France,L,France,100,"Deep Learning, SQL, PyTorch",Bachelor,0,Government,2024-06-09,2024-07-23,2437,5.8,Cognitive Computing -AI07829,AI Consultant,145709,USD,145709,EX,FT,United States,S,Mexico,100,"Python, Azure, Tableau, Statistics",Bachelor,18,Energy,2024-09-11,2024-09-26,1740,7.9,TechCorp Inc -AI07830,Principal Data Scientist,153383,CHF,138045,MI,FT,Switzerland,M,Switzerland,100,"Kubernetes, SQL, Tableau",Associate,4,Consulting,2024-02-21,2024-03-08,686,7.6,Quantum Computing Inc -AI07831,Data Analyst,138997,USD,138997,SE,CT,Israel,L,Israel,50,"Python, Git, Computer Vision, Java, GCP",Bachelor,5,Telecommunications,2024-11-15,2024-12-13,1685,6.3,Algorithmic Solutions -AI07832,ML Ops Engineer,52674,USD,52674,EN,CT,Israel,S,Italy,50,"Git, Tableau, Computer Vision, SQL",Master,0,Gaming,2024-01-12,2024-02-08,1383,7.3,Cloud AI Solutions -AI07833,NLP Engineer,46073,USD,46073,EN,PT,Sweden,S,France,0,"Python, MLOps, R",Bachelor,0,Manufacturing,2024-04-23,2024-06-29,1299,5.1,Advanced Robotics -AI07834,AI Architect,143115,EUR,121648,SE,FT,Austria,M,Austria,50,"Python, Data Visualization, TensorFlow, Statistics",Associate,9,Retail,2024-06-26,2024-08-20,1232,9.1,Smart Analytics -AI07835,Machine Learning Engineer,133093,EUR,113129,EX,CT,Austria,S,Austria,100,"Tableau, Docker, Hadoop, Scala, R",PhD,11,Media,2024-07-25,2024-09-09,1717,5.9,Neural Networks Co -AI07836,Autonomous Systems Engineer,99958,USD,99958,MI,CT,Sweden,M,Romania,50,"Data Visualization, Java, NLP",Associate,2,Retail,2024-10-20,2024-11-14,655,5.9,Autonomous Tech -AI07837,AI Consultant,100906,JPY,11099660,MI,PT,Japan,M,Nigeria,0,"Mathematics, R, Deep Learning",Associate,3,Finance,2024-11-23,2025-01-08,1322,9.6,DeepTech Ventures -AI07838,Principal Data Scientist,73621,USD,73621,EN,PT,Ireland,L,Ireland,0,"Java, Scala, Python",Master,0,Finance,2024-12-14,2025-01-19,1999,7.3,DeepTech Ventures -AI07839,ML Ops Engineer,131785,AUD,177910,SE,CT,Australia,M,Mexico,0,"PyTorch, Linux, Computer Vision, Azure",Master,5,Real Estate,2025-02-03,2025-02-17,785,5.8,Predictive Systems -AI07840,NLP Engineer,302166,USD,302166,EX,FT,United States,L,United States,100,"Python, Linux, Hadoop, MLOps, Azure",PhD,15,Consulting,2024-05-16,2024-07-06,1539,8.4,Cognitive Computing -AI07841,AI Specialist,230443,USD,230443,EX,CT,United States,L,United States,50,"Git, R, AWS, SQL",Associate,11,Gaming,2024-05-24,2024-06-14,589,7.7,Digital Transformation LLC -AI07842,Machine Learning Engineer,52678,USD,52678,EN,PT,Sweden,S,Romania,0,"Kubernetes, SQL, Computer Vision, MLOps, Deep Learning",Master,0,Technology,2025-02-09,2025-04-21,2097,8.8,DataVision Ltd -AI07843,Data Scientist,219188,CHF,197269,EX,PT,Switzerland,M,Switzerland,0,"Kubernetes, Docker, Linux, Azure, Scala",Associate,19,Government,2024-07-05,2024-08-08,1009,8.2,Smart Analytics -AI07844,AI Specialist,63772,USD,63772,SE,PT,China,M,China,0,"PyTorch, Java, GCP, Mathematics",PhD,8,Retail,2024-10-24,2024-12-14,1928,8.2,Advanced Robotics -AI07845,NLP Engineer,63461,EUR,53942,MI,FT,Austria,S,Austria,50,"Computer Vision, Git, Python",Bachelor,2,Telecommunications,2025-01-12,2025-03-25,1638,7.5,Future Systems -AI07846,AI Consultant,125077,USD,125077,MI,PT,Norway,L,Norway,100,"Data Visualization, TensorFlow, Java, Deep Learning",PhD,4,Automotive,2024-02-15,2024-04-06,1340,7.5,Cloud AI Solutions -AI07847,Computer Vision Engineer,157223,EUR,133640,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Scala",Master,7,Manufacturing,2024-03-24,2024-04-12,1193,6.3,AI Innovations -AI07848,Data Scientist,216895,EUR,184361,EX,CT,Netherlands,L,India,100,"Tableau, Scala, AWS",Bachelor,19,Automotive,2024-02-08,2024-02-27,1605,9,Advanced Robotics -AI07849,AI Architect,133507,USD,133507,SE,FT,Sweden,S,Vietnam,50,"TensorFlow, Git, AWS, GCP, Deep Learning",Master,5,Finance,2024-02-28,2024-04-29,1863,6.8,Advanced Robotics -AI07850,Data Engineer,207722,USD,207722,EX,FL,South Korea,L,South Korea,100,"Statistics, Git, Spark, R",Bachelor,17,Media,2024-08-08,2024-09-20,1585,8.9,DataVision Ltd -AI07851,Machine Learning Engineer,91743,EUR,77982,MI,CT,Netherlands,L,Netherlands,50,"Hadoop, Tableau, Scala",Associate,2,Retail,2024-07-16,2024-09-19,1685,7,AI Innovations -AI07852,ML Ops Engineer,87600,USD,87600,MI,FT,Denmark,S,Denmark,100,"GCP, Docker, Python, Spark, NLP",PhD,2,Education,2025-02-18,2025-03-07,881,6.5,Cloud AI Solutions -AI07853,AI Product Manager,78893,USD,78893,MI,PT,South Korea,M,Israel,50,"Docker, PyTorch, Kubernetes, MLOps",PhD,4,Healthcare,2024-09-19,2024-10-29,1284,9.5,Machine Intelligence Group -AI07854,Research Scientist,139691,USD,139691,EX,PT,Israel,S,Israel,100,"Linux, Python, Data Visualization",Master,15,Media,2024-10-24,2024-11-13,800,6.9,Quantum Computing Inc -AI07855,Principal Data Scientist,71086,USD,71086,MI,FL,Finland,S,Finland,0,"Hadoop, Azure, NLP, PyTorch, TensorFlow",Associate,2,Telecommunications,2025-04-12,2025-06-07,2412,6.7,TechCorp Inc -AI07856,AI Consultant,38307,USD,38307,SE,FL,India,M,India,50,"Hadoop, PyTorch, Computer Vision, SQL",Master,7,Education,2024-08-13,2024-10-13,1489,5.8,AI Innovations -AI07857,Principal Data Scientist,236250,USD,236250,EX,FT,Norway,L,Norway,50,"SQL, Mathematics, Java",PhD,15,Automotive,2024-02-24,2024-03-27,1164,7.3,Algorithmic Solutions -AI07858,NLP Engineer,94410,CHF,84969,MI,CT,Switzerland,S,Switzerland,50,"Hadoop, Linux, Computer Vision, Spark, PyTorch",PhD,4,Automotive,2024-03-26,2024-05-03,1633,9.5,Cloud AI Solutions -AI07859,ML Ops Engineer,239612,EUR,203670,EX,PT,Austria,L,Israel,100,"Docker, Scala, Java, Deep Learning, R",Associate,10,Healthcare,2024-05-07,2024-05-29,1636,5.3,Algorithmic Solutions -AI07860,Data Analyst,49846,USD,49846,EN,FT,South Korea,L,South Korea,50,"TensorFlow, SQL, Mathematics",Bachelor,1,Manufacturing,2024-09-12,2024-11-07,602,9.6,Cloud AI Solutions -AI07861,Data Scientist,90589,SGD,117766,MI,CT,Singapore,M,Singapore,50,"Computer Vision, Linux, MLOps, Scala, Kubernetes",Master,3,Real Estate,2024-10-29,2024-11-30,2105,8.8,Cloud AI Solutions -AI07862,Machine Learning Researcher,75857,USD,75857,EN,FT,Denmark,S,Denmark,100,"R, Spark, GCP",Associate,0,Transportation,2025-04-05,2025-06-04,1331,7.5,Future Systems -AI07863,Machine Learning Engineer,229106,USD,229106,EX,PT,United States,S,United States,0,"Python, MLOps, Data Visualization, Deep Learning",Associate,10,Transportation,2024-06-03,2024-06-28,703,8.9,DeepTech Ventures -AI07864,Robotics Engineer,226048,EUR,192141,EX,FT,Germany,M,Germany,100,"Java, PyTorch, TensorFlow, SQL",PhD,15,Media,2025-01-28,2025-02-17,1648,8.8,Cloud AI Solutions -AI07865,Robotics Engineer,74551,EUR,63368,MI,PT,Austria,S,Austria,0,"R, Statistics, Mathematics, Data Visualization",Associate,3,Finance,2024-06-09,2024-08-20,1298,5.1,Autonomous Tech -AI07866,Deep Learning Engineer,209614,EUR,178172,EX,CT,Netherlands,S,Netherlands,100,"Scala, NLP, Kubernetes",Associate,18,Automotive,2024-03-08,2024-04-28,1958,7.1,Algorithmic Solutions -AI07867,Research Scientist,62202,USD,62202,EN,PT,Ireland,S,Hungary,100,"Statistics, Spark, Scala, Linux",Master,1,Technology,2024-09-13,2024-10-19,2499,8.3,Digital Transformation LLC -AI07868,Data Engineer,76226,SGD,99094,EN,CT,Singapore,L,Singapore,100,"Spark, SQL, Python, Scala, Deep Learning",Master,1,Government,2024-10-30,2024-12-11,1269,5.5,DataVision Ltd -AI07869,Principal Data Scientist,186638,CHF,167974,SE,FL,Switzerland,M,Switzerland,100,"Spark, Linux, Python",PhD,9,Consulting,2024-03-01,2024-05-07,1062,8.2,Smart Analytics -AI07870,AI Research Scientist,275375,USD,275375,EX,FT,Ireland,L,Ireland,50,"Mathematics, Azure, Scala",Associate,15,Healthcare,2024-07-29,2024-09-19,1842,6,Autonomous Tech -AI07871,Autonomous Systems Engineer,59693,JPY,6566230,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, SQL, Deep Learning",Associate,1,Finance,2024-11-15,2025-01-22,765,5.1,Cloud AI Solutions -AI07872,Research Scientist,72671,USD,72671,EN,FT,Sweden,L,Sweden,100,"Kubernetes, Scala, Linux, Docker, NLP",Bachelor,1,Retail,2024-10-18,2024-11-25,827,8.9,Cognitive Computing -AI07873,AI Architect,103897,AUD,140261,MI,PT,Australia,L,Australia,50,"Hadoop, Scala, MLOps, SQL, Deep Learning",Master,3,Telecommunications,2024-12-29,2025-03-02,547,9.2,TechCorp Inc -AI07874,Head of AI,101567,AUD,137115,SE,FL,Australia,S,Australia,0,"Linux, Hadoop, MLOps",Master,6,Real Estate,2024-09-11,2024-10-07,1857,9.1,Predictive Systems -AI07875,Head of AI,74940,USD,74940,EN,PT,Sweden,L,Sweden,50,"GCP, Computer Vision, Python",PhD,1,Real Estate,2024-01-16,2024-03-22,2286,6.1,Algorithmic Solutions -AI07876,Machine Learning Researcher,204444,GBP,153333,EX,PT,United Kingdom,M,United Kingdom,50,"MLOps, Azure, TensorFlow, Python",Bachelor,13,Finance,2024-11-19,2024-12-19,1862,7,Autonomous Tech -AI07877,Deep Learning Engineer,264606,CAD,330758,EX,CT,Canada,L,Canada,100,"GCP, SQL, Azure, R",PhD,11,Government,2024-02-07,2024-04-10,2308,6.4,Digital Transformation LLC -AI07878,AI Product Manager,170883,EUR,145251,EX,CT,Germany,S,Germany,50,"Python, Git, Tableau, TensorFlow, Statistics",Master,17,Media,2024-03-23,2024-05-24,1102,7.6,Smart Analytics -AI07879,Data Analyst,152247,USD,152247,MI,FT,Denmark,L,Denmark,100,"SQL, Scala, Statistics",PhD,2,Transportation,2024-05-15,2024-06-06,529,8.5,Machine Intelligence Group -AI07880,AI Specialist,75029,AUD,101289,MI,FT,Australia,M,Australia,100,"Hadoop, MLOps, Tableau, GCP",Bachelor,4,Manufacturing,2024-09-09,2024-10-06,2288,8.7,DeepTech Ventures -AI07881,Machine Learning Engineer,44910,USD,44910,SE,FL,India,M,India,50,"Azure, R, Statistics, NLP",Master,8,Transportation,2024-06-09,2024-07-10,1285,6.9,TechCorp Inc -AI07882,Autonomous Systems Engineer,57794,GBP,43346,EN,FT,United Kingdom,M,United Kingdom,0,"NLP, AWS, R, Python, TensorFlow",Master,0,Finance,2024-03-01,2024-05-11,1515,10,Future Systems -AI07883,AI Research Scientist,155551,USD,155551,SE,FT,Denmark,S,Netherlands,50,"GCP, Linux, MLOps",Master,9,Finance,2024-12-08,2025-01-14,2040,8.3,TechCorp Inc -AI07884,Computer Vision Engineer,185612,USD,185612,EX,FL,Ireland,L,Ireland,50,"Scala, PyTorch, NLP",Master,13,Manufacturing,2025-04-27,2025-06-28,1410,9.3,Cognitive Computing -AI07885,Deep Learning Engineer,69810,JPY,7679100,EN,FL,Japan,M,Japan,50,"Docker, Scala, Python, Statistics, Hadoop",Master,0,Retail,2024-04-20,2024-06-12,874,5.9,Future Systems -AI07886,Machine Learning Engineer,108934,EUR,92594,MI,PT,Netherlands,L,Philippines,0,"Hadoop, Linux, NLP",PhD,3,Real Estate,2024-10-04,2024-10-31,2217,8.1,TechCorp Inc -AI07887,Robotics Engineer,116867,USD,116867,MI,FL,United States,M,United States,100,"Python, Deep Learning, Hadoop, Docker",Bachelor,4,Technology,2024-05-29,2024-07-30,1731,9.8,TechCorp Inc -AI07888,Principal Data Scientist,107417,EUR,91304,MI,FL,Austria,L,Czech Republic,100,"Spark, Computer Vision, Azure, SQL, Scala",Bachelor,2,Manufacturing,2024-12-12,2025-01-29,581,8.2,Quantum Computing Inc -AI07889,Autonomous Systems Engineer,60938,EUR,51797,EN,FT,Austria,S,Austria,50,"Tableau, Python, TensorFlow",Bachelor,1,Telecommunications,2024-04-06,2024-04-24,1259,6.8,AI Innovations -AI07890,Computer Vision Engineer,228287,GBP,171215,EX,FL,United Kingdom,L,United Kingdom,100,"Mathematics, Azure, Scala, SQL, Git",Master,14,Education,2024-04-17,2024-05-28,1740,9.3,DataVision Ltd -AI07891,AI Consultant,149332,USD,149332,SE,PT,Norway,M,Norway,50,"Deep Learning, R, Kubernetes",PhD,7,Energy,2024-07-02,2024-07-31,1673,8.9,Smart Analytics -AI07892,Autonomous Systems Engineer,101212,CAD,126515,SE,PT,Canada,M,Canada,100,"NLP, Scala, Python, PyTorch",Master,6,Media,2024-03-02,2024-03-21,1825,9.5,Algorithmic Solutions -AI07893,AI Architect,136111,USD,136111,MI,PT,Denmark,L,Denmark,0,"Scala, AWS, Hadoop, Python, Git",Associate,2,Automotive,2025-03-24,2025-05-11,1343,5.9,Future Systems -AI07894,Autonomous Systems Engineer,106323,GBP,79742,MI,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, Scala",Bachelor,3,Technology,2024-12-23,2025-02-28,2392,8.7,DeepTech Ventures -AI07895,Computer Vision Engineer,156650,AUD,211478,EX,FT,Australia,M,Netherlands,50,"Data Visualization, Azure, SQL, Hadoop, Java",Master,12,Transportation,2024-08-19,2024-10-15,763,5.7,Algorithmic Solutions -AI07896,Data Scientist,137174,EUR,116598,SE,PT,France,M,Philippines,0,"Java, Python, Data Visualization, AWS",Bachelor,5,Consulting,2025-04-16,2025-05-09,1132,7.2,Cognitive Computing -AI07897,AI Product Manager,106794,USD,106794,MI,CT,Finland,L,South Korea,100,"MLOps, AWS, Tableau, SQL, Python",Associate,2,Retail,2025-04-06,2025-05-12,1189,6.1,Quantum Computing Inc -AI07898,Autonomous Systems Engineer,229594,CAD,286993,EX,PT,Canada,M,Canada,0,"Python, Linux, MLOps",PhD,15,Energy,2024-11-24,2024-12-23,1826,7.1,Quantum Computing Inc -AI07899,Autonomous Systems Engineer,72245,EUR,61408,EN,PT,Netherlands,M,Netherlands,50,"SQL, PyTorch, AWS, Linux",PhD,0,Finance,2024-10-30,2024-12-09,2296,7.6,Autonomous Tech -AI07900,AI Architect,154453,USD,154453,SE,PT,Ireland,L,Ireland,0,"Data Visualization, Linux, R, Python, Azure",Associate,6,Retail,2024-12-25,2025-03-07,1418,8.6,Algorithmic Solutions -AI07901,AI Specialist,64086,EUR,54473,EN,CT,Germany,S,Romania,50,"Java, R, SQL, Git, Deep Learning",Bachelor,1,Technology,2024-07-23,2024-08-17,2472,5.1,Autonomous Tech -AI07902,ML Ops Engineer,101108,EUR,85942,MI,PT,France,L,France,100,"Statistics, Linux, Mathematics",Bachelor,3,Energy,2025-04-03,2025-06-05,2003,6.3,Machine Intelligence Group -AI07903,Head of AI,88469,USD,88469,EN,FL,Denmark,L,Denmark,100,"Python, Linux, MLOps",PhD,1,Gaming,2024-12-01,2025-02-07,626,6,Digital Transformation LLC -AI07904,Data Engineer,111556,USD,111556,EX,CT,China,M,China,50,"SQL, GCP, Kubernetes",Master,15,Telecommunications,2024-11-05,2024-12-19,1737,5.5,Quantum Computing Inc -AI07905,AI Research Scientist,95017,EUR,80764,MI,FT,Netherlands,S,Thailand,100,"Azure, SQL, Computer Vision, R",Bachelor,2,Transportation,2025-03-23,2025-04-09,1717,7.8,Cognitive Computing -AI07906,Data Analyst,98367,AUD,132795,SE,PT,Australia,S,Mexico,50,"Docker, Statistics, Python, NLP, Tableau",PhD,7,Gaming,2024-02-04,2024-04-07,1534,8.7,Smart Analytics -AI07907,AI Product Manager,92735,EUR,78825,EN,PT,Germany,L,Chile,0,"Tableau, SQL, TensorFlow",PhD,0,Finance,2025-04-28,2025-05-30,1976,5.2,TechCorp Inc -AI07908,Principal Data Scientist,135039,USD,135039,SE,FL,Ireland,M,Ireland,0,"Python, Azure, Data Visualization, SQL",Master,7,Media,2024-04-06,2024-05-24,1236,8.6,Machine Intelligence Group -AI07909,Machine Learning Engineer,205457,EUR,174638,EX,FT,Netherlands,M,Netherlands,50,"Git, Kubernetes, Hadoop",Bachelor,10,Technology,2025-03-30,2025-04-17,1285,9.3,Future Systems -AI07910,Deep Learning Engineer,86892,JPY,9558120,MI,FL,Japan,S,Japan,50,"MLOps, Python, Linux, TensorFlow, GCP",PhD,2,Technology,2024-06-24,2024-07-20,1287,5.6,Neural Networks Co -AI07911,AI Product Manager,100067,EUR,85057,MI,FL,Netherlands,L,Netherlands,100,"AWS, Deep Learning, Computer Vision",PhD,4,Healthcare,2024-12-18,2025-02-04,1780,5.7,Advanced Robotics -AI07912,Autonomous Systems Engineer,86435,USD,86435,EN,CT,Sweden,L,Sweden,50,"Kubernetes, NLP, Tableau, Python, Computer Vision",PhD,1,Education,2024-12-18,2025-01-04,2053,6.1,Machine Intelligence Group -AI07913,AI Product Manager,69261,SGD,90039,MI,FL,Singapore,S,Singapore,100,"Python, SQL, Docker",Associate,2,Automotive,2024-05-26,2024-07-27,1673,7,Cloud AI Solutions -AI07914,Computer Vision Engineer,187635,CHF,168872,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, AWS, MLOps, R, GCP",PhD,5,Consulting,2024-06-23,2024-08-21,2261,8.7,Neural Networks Co -AI07915,Data Engineer,150751,CHF,135676,MI,FT,Switzerland,M,Switzerland,50,"Statistics, Python, Tableau, Kubernetes",Associate,3,Manufacturing,2025-02-21,2025-04-12,1563,7.4,Machine Intelligence Group -AI07916,AI Product Manager,117003,AUD,157954,SE,FL,Australia,M,Australia,100,"TensorFlow, AWS, MLOps, Azure, Linux",PhD,8,Manufacturing,2025-02-25,2025-05-09,533,8.4,DataVision Ltd -AI07917,Machine Learning Engineer,81733,EUR,69473,EN,FL,France,L,Belgium,50,"Azure, TensorFlow, Tableau, Python",Associate,0,Real Estate,2024-04-03,2024-05-06,1383,8.5,AI Innovations -AI07918,AI Architect,187345,USD,187345,EX,CT,Ireland,S,Ireland,0,"R, Data Visualization, SQL, Docker",Master,11,Gaming,2024-03-22,2024-05-05,1543,8.3,Cognitive Computing -AI07919,Robotics Engineer,143200,USD,143200,MI,PT,Denmark,L,Denmark,100,"Spark, Computer Vision, Data Visualization, GCP, AWS",PhD,3,Transportation,2025-02-15,2025-03-26,1646,7.2,Smart Analytics -AI07920,AI Product Manager,68868,EUR,58538,EN,FL,Germany,S,Finland,0,"NLP, TensorFlow, Azure",PhD,1,Education,2024-09-02,2024-10-25,571,6.7,Predictive Systems -AI07921,Autonomous Systems Engineer,79844,USD,79844,MI,CT,Sweden,M,Mexico,0,"Kubernetes, AWS, NLP",Master,2,Telecommunications,2024-01-20,2024-02-28,1962,5.4,Smart Analytics -AI07922,Research Scientist,158799,USD,158799,SE,FT,Denmark,L,Denmark,0,"Scala, R, Git",PhD,9,Education,2024-12-30,2025-02-02,1832,6.6,Quantum Computing Inc -AI07923,AI Architect,125614,EUR,106772,SE,FT,Netherlands,L,Argentina,100,"PyTorch, Python, GCP",Bachelor,5,Automotive,2024-05-23,2024-07-05,2140,5.6,Predictive Systems -AI07924,AI Software Engineer,104482,USD,104482,MI,FT,United States,L,United States,0,"Java, SQL, Statistics",PhD,3,Gaming,2024-11-22,2024-12-09,1939,5.3,Neural Networks Co -AI07925,Deep Learning Engineer,196895,EUR,167361,EX,FT,Austria,M,Austria,50,"Scala, Spark, PyTorch",Bachelor,16,Gaming,2024-07-30,2024-10-08,751,6.9,AI Innovations -AI07926,Computer Vision Engineer,133125,EUR,113156,SE,PT,Germany,M,Germany,50,"MLOps, R, Statistics",Master,8,Consulting,2025-03-17,2025-04-28,1400,6.3,DeepTech Ventures -AI07927,AI Specialist,182420,USD,182420,EX,CT,South Korea,L,South Korea,50,"PyTorch, Data Visualization, Spark",Master,17,Energy,2024-07-03,2024-07-26,1745,8.9,Predictive Systems -AI07928,AI Architect,151509,CHF,136358,SE,CT,Switzerland,M,Switzerland,100,"TensorFlow, Python, Kubernetes, AWS",Master,8,Transportation,2024-01-07,2024-02-26,1536,5.8,Advanced Robotics -AI07929,Head of AI,69352,USD,69352,MI,CT,Finland,M,Finland,0,"Data Visualization, TensorFlow, Azure",PhD,3,Manufacturing,2024-12-25,2025-02-02,1882,6.8,Advanced Robotics -AI07930,NLP Engineer,45522,USD,45522,SE,PT,India,S,India,0,"Computer Vision, Hadoop, Git, MLOps",PhD,9,Automotive,2024-04-08,2024-05-06,1194,6.9,Future Systems -AI07931,Data Engineer,43570,USD,43570,SE,PT,India,S,India,100,"MLOps, Hadoop, Spark, NLP, Mathematics",Associate,9,Energy,2024-08-05,2024-09-23,1359,8.8,AI Innovations -AI07932,AI Software Engineer,98915,USD,98915,MI,CT,Israel,M,Israel,0,"Docker, Git, TensorFlow, GCP",Associate,3,Real Estate,2025-03-02,2025-04-18,2083,7.5,Machine Intelligence Group -AI07933,Research Scientist,132893,USD,132893,MI,FT,Norway,M,Thailand,50,"Computer Vision, SQL, Tableau",Bachelor,2,Real Estate,2024-10-23,2024-11-16,1749,6.9,TechCorp Inc -AI07934,ML Ops Engineer,97204,CHF,87484,EN,PT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Docker",Bachelor,1,Finance,2025-03-31,2025-04-29,816,9.8,Predictive Systems -AI07935,Machine Learning Engineer,127523,USD,127523,MI,FL,United States,M,United States,0,"Hadoop, Mathematics, Docker, Data Visualization, Kubernetes",Bachelor,2,Education,2024-04-13,2024-04-27,634,5.7,Quantum Computing Inc -AI07936,AI Product Manager,89735,USD,89735,EN,CT,Norway,L,Norway,50,"Java, Python, Git",Associate,0,Government,2025-03-10,2025-04-14,757,6.2,TechCorp Inc -AI07937,Research Scientist,97385,USD,97385,MI,PT,Norway,S,Norway,0,"Docker, PyTorch, NLP, Python",PhD,4,Education,2024-12-16,2025-02-13,1489,5.8,Autonomous Tech -AI07938,Machine Learning Researcher,52180,USD,52180,EN,CT,Sweden,S,Egypt,100,"PyTorch, Java, Statistics",Associate,0,Finance,2024-12-05,2025-01-07,2313,7.8,DataVision Ltd -AI07939,Robotics Engineer,233176,USD,233176,EX,FT,Denmark,L,Denmark,0,"Hadoop, Python, Azure, TensorFlow",Bachelor,18,Media,2024-07-09,2024-08-04,2378,6.6,Digital Transformation LLC -AI07940,NLP Engineer,151930,AUD,205106,EX,FT,Australia,M,Australia,100,"NLP, Java, PyTorch, TensorFlow",PhD,17,Energy,2024-05-05,2024-07-01,543,9.3,DeepTech Ventures -AI07941,Data Analyst,166632,SGD,216622,EX,PT,Singapore,M,Singapore,100,"Linux, MLOps, Python",Bachelor,15,Media,2025-02-14,2025-03-25,1476,5.7,Cloud AI Solutions -AI07942,Data Analyst,100715,USD,100715,MI,CT,United States,M,United States,0,"SQL, Statistics, Git, Data Visualization, Java",Associate,2,Consulting,2024-06-25,2024-08-27,1320,6,DeepTech Ventures -AI07943,Computer Vision Engineer,74580,JPY,8203800,EN,CT,Japan,S,Japan,0,"Git, Computer Vision, Tableau",Associate,0,Telecommunications,2024-03-02,2024-04-17,616,5.5,DataVision Ltd -AI07944,AI Architect,120355,SGD,156462,SE,FT,Singapore,M,Philippines,50,"Scala, Python, MLOps, SQL",Master,5,Gaming,2024-03-11,2024-03-25,1771,5.8,Neural Networks Co -AI07945,AI Specialist,129835,USD,129835,EX,CT,Ireland,S,Ireland,100,"Deep Learning, Spark, Tableau, Python",Bachelor,11,Media,2025-01-24,2025-03-28,1977,7.4,Cognitive Computing -AI07946,AI Product Manager,143095,EUR,121631,SE,FT,Netherlands,L,Russia,0,"MLOps, Kubernetes, Tableau",Bachelor,5,Media,2024-08-04,2024-10-13,1147,8.4,Predictive Systems -AI07947,AI Consultant,162582,CHF,146324,SE,CT,Switzerland,M,Malaysia,100,"Data Visualization, Docker, Computer Vision, Git",PhD,9,Healthcare,2025-04-30,2025-05-18,558,6.1,Neural Networks Co -AI07948,Deep Learning Engineer,66995,USD,66995,EX,CT,India,M,India,100,"Python, MLOps, TensorFlow",Bachelor,13,Finance,2025-04-30,2025-05-22,1661,6,Cognitive Computing -AI07949,AI Specialist,99477,JPY,10942470,MI,PT,Japan,L,Japan,100,"Hadoop, R, Scala, Azure",Bachelor,2,Government,2024-10-18,2024-12-14,594,8.8,Algorithmic Solutions -AI07950,AI Architect,159574,USD,159574,SE,FT,Denmark,L,Ghana,50,"Python, Data Visualization, Git, PyTorch",Master,9,Finance,2025-04-07,2025-04-29,998,5.3,Predictive Systems -AI07951,AI Product Manager,23228,USD,23228,EN,PT,India,S,India,0,"MLOps, Hadoop, R, TensorFlow, Tableau",Associate,1,Technology,2024-03-01,2024-04-02,1213,7.5,DataVision Ltd -AI07952,AI Architect,173217,USD,173217,SE,CT,United States,M,United States,50,"Statistics, Linux, Docker, Deep Learning",Bachelor,5,Real Estate,2024-02-10,2024-03-18,1019,6.8,DataVision Ltd -AI07953,AI Research Scientist,80075,USD,80075,MI,PT,Finland,L,Finland,100,"SQL, AWS, TensorFlow, Mathematics, Linux",Bachelor,4,Healthcare,2024-05-31,2024-07-03,2425,8.4,Cognitive Computing -AI07954,Data Scientist,55361,JPY,6089710,EN,PT,Japan,S,Japan,100,"SQL, PyTorch, Hadoop, Kubernetes",Bachelor,1,Telecommunications,2024-07-09,2024-09-04,2030,5.8,Quantum Computing Inc -AI07955,Research Scientist,93720,USD,93720,MI,FL,Israel,M,Israel,50,"PyTorch, TensorFlow, MLOps",Master,4,Manufacturing,2024-10-22,2024-11-12,1971,5.9,Future Systems -AI07956,Data Engineer,103590,USD,103590,MI,FT,Finland,M,Ghana,0,"Python, AWS, Azure, Linux",Bachelor,3,Transportation,2024-10-28,2024-11-26,1170,6,Digital Transformation LLC -AI07957,Head of AI,166505,JPY,18315550,EX,PT,Japan,L,Japan,100,"Git, Docker, Python, GCP, Linux",PhD,17,Real Estate,2024-12-13,2025-01-02,858,5.3,Future Systems -AI07958,Deep Learning Engineer,150946,CHF,135851,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, Azure, Deep Learning",Associate,2,Transportation,2024-06-14,2024-08-26,1490,9.1,Cognitive Computing -AI07959,ML Ops Engineer,218604,AUD,295115,EX,PT,Australia,L,Ghana,50,"Tableau, Azure, AWS, Kubernetes, Java",PhD,17,Education,2024-04-17,2024-05-09,1976,5.3,Cognitive Computing -AI07960,Data Analyst,201864,USD,201864,EX,CT,Sweden,S,Sweden,100,"Computer Vision, Java, R",Associate,16,Transportation,2024-09-06,2024-10-26,523,6,Algorithmic Solutions -AI07961,AI Research Scientist,77414,AUD,104509,MI,PT,Australia,M,Argentina,100,"Scala, Java, Tableau",Bachelor,3,Energy,2024-01-13,2024-02-13,1416,5.2,TechCorp Inc -AI07962,Machine Learning Researcher,128494,EUR,109220,EX,FL,Austria,S,Austria,0,"Kubernetes, PyTorch, R",PhD,12,Transportation,2024-05-25,2024-08-04,730,5.5,Cognitive Computing -AI07963,AI Research Scientist,120539,USD,120539,EX,CT,China,L,China,0,"Python, GCP, Docker",Bachelor,10,Real Estate,2025-03-27,2025-06-06,572,8.7,Advanced Robotics -AI07964,AI Software Engineer,60570,USD,60570,EN,PT,Finland,L,Finland,0,"MLOps, Spark, TensorFlow, Kubernetes, SQL",Associate,1,Healthcare,2024-03-25,2024-04-16,1857,5.9,TechCorp Inc -AI07965,Research Scientist,88260,USD,88260,EN,PT,Denmark,S,Philippines,100,"Git, Statistics, Linux, Azure",Bachelor,0,Real Estate,2024-12-09,2025-01-01,1245,8.8,Smart Analytics -AI07966,Deep Learning Engineer,78518,USD,78518,MI,FT,Israel,S,Israel,50,"Hadoop, Kubernetes, Python, Deep Learning, Mathematics",Master,2,Real Estate,2024-09-12,2024-09-27,2279,8.7,TechCorp Inc -AI07967,Machine Learning Engineer,97759,EUR,83095,MI,FT,Netherlands,S,Netherlands,50,"PyTorch, GCP, Statistics, Docker",Master,2,Manufacturing,2025-03-11,2025-05-18,1358,6.1,TechCorp Inc -AI07968,Data Analyst,92686,EUR,78783,MI,FT,Germany,M,Israel,50,"Computer Vision, MLOps, TensorFlow, Python, PyTorch",PhD,2,Gaming,2025-02-10,2025-03-25,1588,9.7,Neural Networks Co -AI07969,Deep Learning Engineer,109730,CHF,98757,EN,CT,Switzerland,M,Switzerland,0,"Python, Spark, Tableau",Master,1,Manufacturing,2024-07-15,2024-09-05,1812,6.5,Neural Networks Co -AI07970,Computer Vision Engineer,61314,USD,61314,EX,FT,India,L,India,100,"Kubernetes, TensorFlow, MLOps",Bachelor,18,Telecommunications,2024-04-01,2024-05-20,953,5.8,Future Systems -AI07971,AI Research Scientist,34450,USD,34450,MI,CT,China,M,Switzerland,0,"Python, TensorFlow, Scala, Kubernetes, Java",Master,3,Retail,2024-07-06,2024-09-15,1840,8,Predictive Systems -AI07972,Deep Learning Engineer,104797,USD,104797,SE,CT,Ireland,S,Ireland,50,"Python, Data Visualization, Spark, SQL, Java",PhD,5,Retail,2025-01-28,2025-02-24,1987,8.8,Cognitive Computing -AI07973,NLP Engineer,143973,AUD,194364,SE,PT,Australia,L,Australia,100,"PyTorch, SQL, Hadoop",Bachelor,7,Education,2024-02-18,2024-04-18,683,9.4,Digital Transformation LLC -AI07974,Data Engineer,60516,USD,60516,EN,FL,Sweden,M,Sweden,50,"Java, PyTorch, Scala, Statistics",Master,0,Automotive,2024-09-13,2024-10-18,818,5.6,Machine Intelligence Group -AI07975,Autonomous Systems Engineer,110800,CHF,99720,MI,PT,Switzerland,M,Switzerland,50,"Python, Computer Vision, Kubernetes, R, TensorFlow",PhD,3,Healthcare,2024-05-13,2024-07-21,1718,5.9,TechCorp Inc -AI07976,Data Scientist,83576,USD,83576,SE,FT,South Korea,S,Norway,0,"Deep Learning, NLP, Data Visualization, Scala, Mathematics",Bachelor,5,Real Estate,2025-02-27,2025-05-03,1461,5.4,Advanced Robotics -AI07977,AI Consultant,150796,USD,150796,SE,CT,Finland,L,Finland,100,"Hadoop, NLP, Linux, Scala, Python",PhD,9,Media,2024-12-03,2024-12-23,766,5.7,Autonomous Tech -AI07978,Head of AI,67072,USD,67072,EN,PT,Israel,L,Israel,0,"Deep Learning, AWS, NLP, Docker, GCP",Associate,1,Telecommunications,2024-03-26,2024-05-01,1888,10,Cloud AI Solutions -AI07979,Robotics Engineer,51985,USD,51985,EN,FT,Sweden,S,Sweden,100,"AWS, R, MLOps, Azure",Master,0,Technology,2024-03-25,2024-05-18,2215,6.4,AI Innovations -AI07980,AI Product Manager,110993,USD,110993,SE,CT,Finland,M,Finland,100,"Linux, Tableau, SQL, Spark, Scala",PhD,5,Education,2024-04-12,2024-04-29,2320,5.5,Cloud AI Solutions -AI07981,Head of AI,94069,USD,94069,EN,FT,Norway,M,Norway,100,"R, TensorFlow, Java, Git, Python",Associate,1,Telecommunications,2024-09-14,2024-10-16,1036,7.7,DeepTech Ventures -AI07982,AI Architect,146889,CHF,132200,MI,PT,Switzerland,L,Switzerland,50,"Python, Computer Vision, Mathematics",PhD,4,Telecommunications,2025-03-04,2025-04-15,726,5.8,Advanced Robotics -AI07983,Principal Data Scientist,155346,USD,155346,SE,FL,United States,S,United States,0,"Computer Vision, Java, Git, Docker",Bachelor,9,Telecommunications,2025-01-01,2025-02-27,1994,9.9,TechCorp Inc -AI07984,Data Scientist,124124,EUR,105505,SE,CT,France,S,France,50,"TensorFlow, PyTorch, Tableau, Computer Vision",PhD,6,Gaming,2024-05-28,2024-08-07,1082,9.7,Cloud AI Solutions -AI07985,Deep Learning Engineer,137231,CAD,171539,EX,FT,Canada,S,Canada,100,"Docker, AWS, PyTorch, SQL",Associate,15,Consulting,2024-01-22,2024-03-22,1011,7.7,Advanced Robotics -AI07986,AI Architect,45728,CAD,57160,EN,CT,Canada,S,Canada,0,"MLOps, Docker, SQL",Master,1,Gaming,2024-04-21,2024-07-03,2066,5.7,Advanced Robotics -AI07987,Machine Learning Researcher,61291,EUR,52097,EN,FL,France,L,France,100,"SQL, MLOps, AWS, Hadoop",Bachelor,0,Education,2024-06-27,2024-08-09,1539,8.3,Neural Networks Co -AI07988,AI Architect,64443,EUR,54777,EN,FL,France,M,France,100,"Git, Kubernetes, Computer Vision",PhD,0,Media,2025-02-01,2025-04-11,2228,6.7,Future Systems -AI07989,Deep Learning Engineer,66409,USD,66409,EN,FL,United States,M,Colombia,50,"MLOps, Azure, Python, Kubernetes, Data Visualization",Bachelor,1,Healthcare,2024-11-05,2025-01-09,1753,8.3,Advanced Robotics -AI07990,NLP Engineer,76025,USD,76025,EX,CT,China,S,China,0,"Deep Learning, PyTorch, Linux",Associate,10,Retail,2024-05-14,2024-06-05,1627,5,Cloud AI Solutions -AI07991,Machine Learning Researcher,211009,USD,211009,EX,FL,Ireland,L,Ireland,100,"SQL, Computer Vision, Tableau",Master,10,Manufacturing,2025-04-11,2025-05-31,1249,5.6,Algorithmic Solutions -AI07992,AI Product Manager,154995,EUR,131746,SE,FL,Germany,L,Poland,50,"Scala, NLP, Mathematics, Docker, Java",PhD,6,Government,2025-03-26,2025-05-17,1985,7.3,Cloud AI Solutions -AI07993,AI Consultant,44675,USD,44675,SE,FL,India,L,Singapore,0,"Docker, Scala, MLOps, Linux, SQL",PhD,7,Finance,2024-11-11,2025-01-21,782,8.5,AI Innovations -AI07994,Research Scientist,87124,SGD,113261,EN,PT,Singapore,L,Singapore,0,"Scala, Java, TensorFlow, GCP, Deep Learning",Bachelor,1,Healthcare,2024-03-10,2024-04-25,1861,5.7,Cognitive Computing -AI07995,Robotics Engineer,122808,USD,122808,MI,PT,Sweden,L,Sweden,0,"PyTorch, SQL, MLOps, Mathematics, GCP",PhD,4,Consulting,2024-03-23,2024-05-16,1697,9,Predictive Systems -AI07996,Data Engineer,133625,JPY,14698750,SE,PT,Japan,L,Ireland,50,"Azure, Python, Mathematics",Associate,8,Government,2024-11-17,2024-12-03,1052,9.2,AI Innovations -AI07997,Autonomous Systems Engineer,71366,USD,71366,EN,CT,Israel,M,Israel,0,"TensorFlow, NLP, Kubernetes, Data Visualization, AWS",Bachelor,0,Energy,2024-10-28,2024-11-22,2129,7.3,Neural Networks Co -AI07998,AI Consultant,123920,USD,123920,SE,CT,Sweden,S,Brazil,50,"Docker, AWS, Hadoop, Java, Azure",Bachelor,5,Automotive,2025-01-23,2025-03-18,972,8.5,Autonomous Tech -AI07999,AI Product Manager,134233,JPY,14765630,MI,CT,Japan,L,Japan,50,"GCP, SQL, Tableau, Kubernetes",PhD,4,Finance,2024-09-13,2024-11-05,1135,6.4,Machine Intelligence Group -AI08000,Machine Learning Researcher,109561,USD,109561,MI,FT,Sweden,L,Netherlands,0,"Python, Java, NLP, Linux",Bachelor,4,Finance,2024-04-09,2024-06-13,1402,8.9,AI Innovations -AI08001,Data Scientist,71713,SGD,93227,EN,PT,Singapore,L,Thailand,50,"GCP, Statistics, Tableau, Scala",Associate,0,Government,2024-05-02,2024-07-10,2238,5.7,Quantum Computing Inc -AI08002,Robotics Engineer,58752,CAD,73440,EN,PT,Canada,M,Canada,100,"SQL, TensorFlow, Git, AWS",Master,0,Automotive,2024-12-13,2025-01-06,878,8,Digital Transformation LLC -AI08003,Autonomous Systems Engineer,118460,USD,118460,MI,FL,Norway,M,Norway,50,"NLP, Mathematics, Deep Learning, Python",Bachelor,4,Retail,2024-06-25,2024-07-30,1000,8.5,DataVision Ltd -AI08004,Machine Learning Researcher,82449,EUR,70082,EN,FL,Netherlands,M,Norway,0,"NLP, Spark, TensorFlow",Bachelor,0,Telecommunications,2024-05-25,2024-06-19,1871,8,Advanced Robotics -AI08005,Machine Learning Engineer,80025,SGD,104033,MI,FT,Singapore,S,Singapore,100,"Hadoop, Tableau, Spark, GCP",PhD,4,Real Estate,2024-04-18,2024-06-12,1556,8.2,Quantum Computing Inc -AI08006,Robotics Engineer,221861,USD,221861,EX,FL,Ireland,S,Ireland,100,"Kubernetes, GCP, Linux, SQL, Data Visualization",Bachelor,10,Manufacturing,2024-11-13,2025-01-24,818,7.2,TechCorp Inc -AI08007,AI Consultant,284268,USD,284268,EX,FT,Ireland,L,Ireland,50,"Data Visualization, AWS, PyTorch, Spark, Hadoop",Master,18,Technology,2024-05-23,2024-06-07,2236,5.1,Autonomous Tech -AI08008,Deep Learning Engineer,171547,SGD,223011,EX,PT,Singapore,S,Singapore,50,"Linux, Java, Tableau, GCP, Kubernetes",PhD,12,Retail,2025-04-09,2025-04-25,1173,9.2,Cloud AI Solutions -AI08009,AI Software Engineer,323208,CHF,290887,EX,FL,Switzerland,L,Switzerland,100,"Tableau, Deep Learning, Data Visualization, SQL, Linux",Master,14,Energy,2024-05-24,2024-07-04,1871,5.7,Cognitive Computing -AI08010,AI Product Manager,113656,USD,113656,MI,FT,United States,M,Ireland,50,"Statistics, SQL, MLOps",Master,2,Government,2024-10-04,2024-11-20,1427,7,Digital Transformation LLC -AI08011,Principal Data Scientist,77152,USD,77152,MI,FL,Ireland,M,Ireland,50,"AWS, TensorFlow, GCP, Deep Learning, SQL",PhD,4,Technology,2025-02-01,2025-04-01,2268,8.4,Algorithmic Solutions -AI08012,NLP Engineer,222207,SGD,288869,EX,FT,Singapore,L,Singapore,100,"Statistics, Tableau, Scala",Associate,13,Telecommunications,2025-01-18,2025-02-28,1899,6.6,Smart Analytics -AI08013,AI Consultant,196407,USD,196407,EX,PT,Denmark,S,Denmark,100,"Java, SQL, Deep Learning, Computer Vision, Spark",Bachelor,17,Government,2024-11-01,2025-01-03,2236,7.5,Autonomous Tech -AI08014,Research Scientist,27068,USD,27068,MI,PT,India,M,India,100,"Spark, Statistics, PyTorch",Bachelor,4,Retail,2024-08-27,2024-11-08,2145,9.7,Neural Networks Co -AI08015,AI Research Scientist,99789,USD,99789,SE,CT,South Korea,L,South Korea,0,"Scala, PyTorch, Statistics, GCP",PhD,7,Automotive,2025-03-14,2025-05-09,564,6.7,Predictive Systems -AI08016,Research Scientist,157360,CHF,141624,SE,CT,Switzerland,S,Czech Republic,50,"Java, Scala, MLOps, NLP",Bachelor,7,Education,2024-12-28,2025-02-03,2474,5,Algorithmic Solutions -AI08017,Data Engineer,73368,CHF,66031,EN,CT,Switzerland,S,Switzerland,0,"Spark, Linux, Python",Bachelor,1,Healthcare,2024-08-03,2024-09-29,764,6.3,Smart Analytics -AI08018,AI Specialist,130971,CHF,117874,EN,FL,Switzerland,L,Switzerland,0,"TensorFlow, Python, Mathematics",Master,1,Transportation,2024-07-09,2024-09-09,2002,8.4,DataVision Ltd -AI08019,Autonomous Systems Engineer,42371,USD,42371,MI,FT,China,S,China,100,"SQL, Scala, Git",Associate,3,Consulting,2024-02-08,2024-03-16,2063,6.8,Machine Intelligence Group -AI08020,AI Architect,96446,USD,96446,EN,PT,United States,L,Denmark,50,"PyTorch, Linux, Statistics",Master,1,Energy,2024-02-11,2024-03-22,1721,8.2,DeepTech Ventures -AI08021,Data Scientist,253346,USD,253346,EX,FT,United States,M,United States,50,"NLP, Linux, Azure",PhD,15,Manufacturing,2024-11-12,2025-01-14,1765,5.8,Smart Analytics -AI08022,AI Specialist,210688,JPY,23175680,EX,FT,Japan,M,Japan,50,"MLOps, Hadoop, Python",Associate,14,Transportation,2024-01-04,2024-02-16,1448,5.1,Algorithmic Solutions -AI08023,Data Analyst,20088,USD,20088,EN,CT,India,S,India,50,"R, Azure, TensorFlow, Tableau, Git",Master,1,Healthcare,2024-11-06,2024-12-07,1065,6.7,AI Innovations -AI08024,AI Research Scientist,115869,EUR,98489,MI,FT,France,L,France,100,"Kubernetes, Azure, TensorFlow, Java, Scala",Bachelor,4,Gaming,2024-12-01,2025-01-14,890,5.5,Neural Networks Co -AI08025,Computer Vision Engineer,27041,USD,27041,MI,FL,India,M,Argentina,0,"Git, GCP, Scala, Deep Learning, TensorFlow",Associate,2,Manufacturing,2024-05-08,2024-07-11,631,8.4,Future Systems -AI08026,AI Research Scientist,133722,USD,133722,SE,FL,Ireland,S,Ireland,50,"Mathematics, Statistics, Java",Master,8,Government,2025-04-11,2025-05-30,2432,6.4,Advanced Robotics -AI08027,Autonomous Systems Engineer,75208,USD,75208,EN,PT,United States,S,Ukraine,0,"PyTorch, Azure, Java, Spark",PhD,0,Finance,2024-07-15,2024-08-15,980,5.1,Future Systems -AI08028,Machine Learning Researcher,109705,EUR,93249,MI,FT,Germany,M,Russia,0,"Python, Linux, NLP",PhD,4,Real Estate,2024-12-18,2025-01-13,2235,7.4,AI Innovations -AI08029,AI Consultant,55926,USD,55926,EN,FT,South Korea,M,Poland,50,"Python, SQL, MLOps",Master,1,Consulting,2024-05-08,2024-06-17,538,7,Advanced Robotics -AI08030,Data Analyst,154681,USD,154681,SE,PT,Denmark,L,Denmark,50,"Git, Hadoop, Tableau, Data Visualization",Associate,7,Government,2025-02-09,2025-04-17,975,9.4,Digital Transformation LLC -AI08031,NLP Engineer,72975,USD,72975,EX,PT,India,M,India,0,"GCP, Tableau, Scala",PhD,14,Technology,2024-04-10,2024-05-03,556,9.2,Machine Intelligence Group -AI08032,Deep Learning Engineer,122344,USD,122344,SE,CT,Sweden,M,Brazil,50,"Spark, AWS, Git, PyTorch",Bachelor,8,Real Estate,2024-05-16,2024-07-25,1732,7,DeepTech Ventures -AI08033,Machine Learning Researcher,78706,EUR,66900,MI,FT,Germany,M,Germany,0,"Data Visualization, AWS, Python, Spark, TensorFlow",PhD,2,Retail,2024-05-22,2024-07-24,737,9.5,Machine Intelligence Group -AI08034,Data Analyst,87488,EUR,74365,SE,FT,Austria,S,Austria,50,"Kubernetes, PyTorch, TensorFlow, Statistics",Bachelor,8,Automotive,2024-11-30,2024-12-30,2075,6.2,DeepTech Ventures -AI08035,Data Scientist,109945,GBP,82459,SE,PT,United Kingdom,S,Australia,50,"AWS, Data Visualization, Scala, Tableau, MLOps",Associate,5,Telecommunications,2025-02-20,2025-03-10,1706,6.6,Algorithmic Solutions -AI08036,Autonomous Systems Engineer,128555,USD,128555,SE,FT,United States,S,Ireland,0,"SQL, Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,9,Automotive,2024-09-23,2024-11-10,2140,6.4,DataVision Ltd -AI08037,Data Engineer,83558,USD,83558,EX,FL,China,M,Portugal,0,"Java, GCP, Tableau, Deep Learning",Associate,13,Healthcare,2024-11-22,2025-01-12,1439,8.8,Advanced Robotics -AI08038,Autonomous Systems Engineer,59257,USD,59257,SE,CT,China,L,China,50,"R, Mathematics, Tableau",Bachelor,8,Education,2024-02-09,2024-04-11,1925,9.6,DeepTech Ventures -AI08039,Research Scientist,211226,USD,211226,EX,CT,Sweden,L,Sweden,50,"Hadoop, Scala, GCP, Docker, R",PhD,10,Real Estate,2024-10-18,2024-12-08,1516,8.5,Cloud AI Solutions -AI08040,Data Engineer,58429,EUR,49665,EN,FT,Austria,S,Austria,50,"Linux, Python, Computer Vision, AWS",Master,0,Healthcare,2024-05-11,2024-07-10,1024,8.5,AI Innovations -AI08041,AI Specialist,30008,USD,30008,EN,CT,India,L,India,100,"Linux, PyTorch, Git, Computer Vision",Master,1,Real Estate,2024-10-29,2024-11-23,799,6.5,Machine Intelligence Group -AI08042,Principal Data Scientist,63440,USD,63440,EX,PT,India,M,India,0,"Hadoop, Java, SQL, Computer Vision",PhD,18,Energy,2024-10-19,2024-12-06,1042,9.3,DataVision Ltd -AI08043,AI Architect,75902,USD,75902,EN,PT,United States,S,United States,50,"AWS, Data Visualization, Tableau, Scala",Associate,0,Real Estate,2024-02-05,2024-03-03,1077,8.2,Algorithmic Solutions -AI08044,AI Consultant,212552,GBP,159414,EX,FL,United Kingdom,S,Austria,100,"SQL, Spark, MLOps",Associate,11,Finance,2025-03-20,2025-05-02,516,7.9,Neural Networks Co -AI08045,AI Product Manager,105830,EUR,89956,MI,FL,France,L,France,100,"Hadoop, GCP, Scala, Tableau",Bachelor,3,Healthcare,2024-08-16,2024-10-12,878,9.8,Autonomous Tech -AI08046,Head of AI,82250,USD,82250,MI,PT,Sweden,M,Sweden,0,"Azure, MLOps, Statistics, R, GCP",Associate,2,Consulting,2024-07-15,2024-08-29,1795,7.2,DataVision Ltd -AI08047,AI Product Manager,106488,EUR,90515,SE,PT,Germany,M,Germany,0,"PyTorch, Kubernetes, Computer Vision, TensorFlow, Spark",Bachelor,9,Telecommunications,2024-12-20,2025-01-31,960,7.2,Quantum Computing Inc -AI08048,Head of AI,147509,USD,147509,SE,CT,Sweden,L,Sweden,0,"Python, Mathematics, Linux, TensorFlow, Deep Learning",Master,6,Healthcare,2024-12-18,2025-01-25,1965,6,Cognitive Computing -AI08049,AI Specialist,107129,EUR,91060,MI,CT,Netherlands,L,Netherlands,0,"R, PyTorch, GCP, Computer Vision, Git",Bachelor,2,Automotive,2024-04-19,2024-05-30,1355,9.2,Machine Intelligence Group -AI08050,AI Research Scientist,263994,CHF,237595,EX,FT,Switzerland,S,Switzerland,100,"Azure, Python, MLOps, Kubernetes, Hadoop",Bachelor,19,Consulting,2024-12-11,2025-01-16,1088,6.4,Quantum Computing Inc -AI08051,NLP Engineer,115888,SGD,150654,MI,FT,Singapore,L,Australia,50,"Kubernetes, Docker, Spark, Linux, Computer Vision",Associate,2,Energy,2024-05-03,2024-06-29,2345,5.2,Autonomous Tech -AI08052,Research Scientist,183653,SGD,238749,EX,PT,Singapore,M,Singapore,100,"Statistics, Computer Vision, Python",Master,14,Government,2024-10-22,2024-12-06,2176,8.6,DeepTech Ventures -AI08053,Autonomous Systems Engineer,136651,SGD,177646,EX,FT,Singapore,S,Singapore,50,"Statistics, Python, AWS, PyTorch",Master,18,Real Estate,2024-12-20,2025-01-29,1776,8.5,Autonomous Tech -AI08054,AI Product Manager,138663,USD,138663,EX,CT,Finland,M,New Zealand,100,"Git, Python, Mathematics, Linux",Associate,13,Gaming,2024-06-16,2024-08-04,2319,6.5,Future Systems -AI08055,AI Software Engineer,156452,GBP,117339,EX,CT,United Kingdom,S,United Kingdom,50,"Azure, Tableau, Statistics",Bachelor,10,Gaming,2024-03-26,2024-05-10,1929,7.2,Neural Networks Co -AI08056,Computer Vision Engineer,91988,USD,91988,MI,CT,United States,M,United States,50,"Git, Scala, Data Visualization",PhD,4,Healthcare,2024-07-23,2024-10-02,1514,8.5,TechCorp Inc -AI08057,AI Product Manager,170809,GBP,128107,EX,CT,United Kingdom,L,United Kingdom,100,"Java, PyTorch, AWS, Computer Vision",Master,11,Telecommunications,2024-08-23,2024-09-06,1384,9.9,Digital Transformation LLC -AI08058,NLP Engineer,102306,EUR,86960,MI,PT,Netherlands,L,Indonesia,100,"SQL, NLP, Python",Master,4,Automotive,2024-10-19,2024-12-24,1838,8.7,Machine Intelligence Group -AI08059,Computer Vision Engineer,66585,EUR,56597,EN,CT,France,S,France,0,"NLP, PyTorch, MLOps, Kubernetes, TensorFlow",Associate,0,Education,2024-02-03,2024-02-27,1482,7.9,Predictive Systems -AI08060,Machine Learning Researcher,207692,CHF,186923,SE,CT,Switzerland,M,Switzerland,100,"Python, Spark, TensorFlow, Tableau, PyTorch",PhD,5,Transportation,2024-03-28,2024-06-02,1924,9.6,Quantum Computing Inc -AI08061,Data Analyst,129361,USD,129361,SE,CT,Sweden,M,Sweden,100,"PyTorch, Spark, Hadoop",Master,8,Finance,2024-06-01,2024-07-16,1043,10,Algorithmic Solutions -AI08062,Head of AI,97125,USD,97125,EN,CT,Denmark,L,Denmark,100,"Scala, Tableau, Kubernetes",PhD,0,Energy,2024-01-18,2024-03-28,760,9.3,Algorithmic Solutions -AI08063,Principal Data Scientist,97060,USD,97060,MI,PT,Finland,M,Finland,0,"R, AWS, Statistics, Linux, Deep Learning",PhD,3,Transportation,2024-12-16,2025-01-03,1883,9.8,Future Systems -AI08064,AI Software Engineer,69840,USD,69840,SE,FT,China,L,Spain,50,"Java, AWS, Computer Vision, Docker, Deep Learning",Master,9,Energy,2024-03-12,2024-04-04,2372,7.1,Machine Intelligence Group -AI08065,ML Ops Engineer,86753,EUR,73740,MI,PT,France,L,France,0,"Java, Hadoop, Linux",Associate,3,Real Estate,2024-11-28,2024-12-30,1934,6.7,Quantum Computing Inc -AI08066,Research Scientist,120164,USD,120164,EN,PT,Norway,L,Norway,50,"Computer Vision, Scala, SQL",Associate,1,Telecommunications,2024-02-21,2024-04-14,2276,8.7,Digital Transformation LLC -AI08067,Deep Learning Engineer,63400,USD,63400,EN,PT,Finland,M,Finland,100,"GCP, Tableau, PyTorch",Master,0,Telecommunications,2025-02-17,2025-04-30,1004,8.3,Neural Networks Co -AI08068,Deep Learning Engineer,195225,AUD,263554,EX,FL,Australia,L,Hungary,50,"Git, Python, Azure",Master,17,Automotive,2024-03-06,2024-04-24,1304,7.9,Neural Networks Co -AI08069,AI Specialist,121448,USD,121448,SE,PT,South Korea,L,Luxembourg,50,"Hadoop, Linux, Git, Scala, Java",Master,9,Finance,2024-09-22,2024-10-19,1260,5.3,Autonomous Tech -AI08070,Autonomous Systems Engineer,127574,CHF,114817,MI,CT,Switzerland,S,Canada,0,"TensorFlow, Azure, Spark, Kubernetes",Master,4,Finance,2024-09-18,2024-10-23,733,9.1,Quantum Computing Inc -AI08071,NLP Engineer,28917,USD,28917,EN,FL,China,L,China,50,"SQL, PyTorch, Java, Docker, Linux",PhD,1,Finance,2024-11-08,2024-11-29,2062,8.5,Advanced Robotics -AI08072,NLP Engineer,175601,USD,175601,SE,CT,Denmark,S,Denmark,100,"Python, Scala, AWS, Spark",Master,5,Technology,2024-05-27,2024-06-16,1276,8.5,Quantum Computing Inc -AI08073,Principal Data Scientist,110916,JPY,12200760,SE,CT,Japan,S,United States,100,"Python, Linux, SQL, R, Statistics",Master,9,Retail,2024-03-07,2024-03-30,2208,9.7,Algorithmic Solutions -AI08074,Research Scientist,93983,CAD,117479,MI,PT,Canada,L,Canada,0,"Data Visualization, Kubernetes, Mathematics",Bachelor,4,Healthcare,2024-03-17,2024-03-31,2013,5.2,DeepTech Ventures -AI08075,NLP Engineer,323422,USD,323422,EX,PT,Norway,M,Norway,0,"Docker, R, Data Visualization, Deep Learning, Git",Associate,10,Education,2024-09-25,2024-11-06,1045,7.1,Smart Analytics -AI08076,Robotics Engineer,179355,USD,179355,SE,CT,United States,L,United States,50,"NLP, Python, Data Visualization, Azure, Java",PhD,5,Finance,2024-02-20,2024-04-12,2445,9.2,Advanced Robotics -AI08077,AI Product Manager,85532,USD,85532,EN,FT,Denmark,S,Denmark,50,"Docker, Kubernetes, AWS",Master,0,Telecommunications,2024-11-03,2024-12-30,837,5.9,Machine Intelligence Group -AI08078,Autonomous Systems Engineer,44071,USD,44071,MI,FT,India,L,India,0,"Java, PyTorch, NLP, R, TensorFlow",Associate,3,Government,2025-01-18,2025-03-02,974,8.9,Autonomous Tech -AI08079,Robotics Engineer,130737,USD,130737,SE,FL,Ireland,M,Ireland,50,"Linux, PyTorch, Java, Tableau, TensorFlow",Master,9,Automotive,2024-10-18,2024-11-29,1011,6.9,Cognitive Computing -AI08080,Deep Learning Engineer,147663,CHF,132897,MI,CT,Switzerland,L,Switzerland,50,"SQL, Computer Vision, Scala, GCP",Master,4,Energy,2025-02-18,2025-03-29,2092,7.6,AI Innovations -AI08081,Machine Learning Engineer,269175,USD,269175,EX,FL,Denmark,M,Argentina,100,"AWS, Hadoop, Java, Statistics, Deep Learning",Master,18,Real Estate,2024-02-26,2024-04-05,2398,6.5,AI Innovations -AI08082,Computer Vision Engineer,152150,EUR,129328,SE,FT,France,L,France,50,"Linux, Python, Data Visualization, Java",PhD,5,Consulting,2024-04-07,2024-05-17,1392,9.8,Autonomous Tech -AI08083,AI Consultant,18965,USD,18965,EN,FL,India,S,India,50,"Python, GCP, Deep Learning",Master,0,Automotive,2025-03-07,2025-03-28,2011,7.6,Cloud AI Solutions -AI08084,NLP Engineer,293774,USD,293774,EX,FT,Norway,S,Norway,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,14,Media,2024-06-15,2024-07-21,2330,9.2,Cognitive Computing -AI08085,Head of AI,116082,USD,116082,SE,CT,South Korea,M,United Kingdom,50,"Tableau, Deep Learning, SQL",PhD,9,Consulting,2025-03-02,2025-04-03,1469,6.8,Machine Intelligence Group -AI08086,AI Consultant,55542,USD,55542,EN,FT,South Korea,S,Argentina,100,"Kubernetes, Tableau, MLOps",Master,1,Real Estate,2024-02-20,2024-04-13,1159,8,Quantum Computing Inc -AI08087,AI Consultant,136996,USD,136996,SE,CT,Norway,M,Norway,100,"Linux, SQL, Deep Learning, PyTorch, Hadoop",Bachelor,6,Retail,2024-02-21,2024-03-08,2025,9.8,Cloud AI Solutions -AI08088,ML Ops Engineer,79319,EUR,67421,MI,PT,France,L,France,0,"MLOps, SQL, TensorFlow, Hadoop",Bachelor,3,Media,2024-02-05,2024-03-31,1325,9.7,DataVision Ltd -AI08089,Computer Vision Engineer,105493,CAD,131866,SE,CT,Canada,S,Canada,0,"PyTorch, Linux, Python, Statistics, GCP",Master,9,Education,2025-01-02,2025-01-23,902,9.8,Cloud AI Solutions -AI08090,AI Research Scientist,58931,USD,58931,EN,CT,Israel,S,Israel,50,"Computer Vision, R, SQL",Associate,0,Transportation,2024-09-03,2024-09-21,1976,8.9,DataVision Ltd -AI08091,AI Specialist,269865,USD,269865,EX,CT,Ireland,L,Ireland,100,"Linux, Azure, Deep Learning",Bachelor,18,Technology,2025-03-30,2025-06-07,729,5.7,Autonomous Tech -AI08092,Head of AI,94339,USD,94339,MI,CT,Norway,S,Norway,50,"Kubernetes, TensorFlow, Azure, Tableau, MLOps",Associate,3,Government,2024-04-14,2024-05-02,1970,5.9,Autonomous Tech -AI08093,AI Product Manager,295017,JPY,32451870,EX,CT,Japan,L,Estonia,50,"Kubernetes, Java, Git, SQL",Master,14,Media,2024-09-22,2024-11-04,1295,6.3,Digital Transformation LLC -AI08094,Machine Learning Engineer,101293,SGD,131681,MI,CT,Singapore,S,Singapore,100,"NLP, SQL, Azure, Scala",PhD,2,Healthcare,2025-01-20,2025-03-07,2199,7.9,Machine Intelligence Group -AI08095,AI Specialist,32078,USD,32078,EN,FT,India,L,India,100,"Computer Vision, Tableau, GCP",Associate,0,Consulting,2025-04-16,2025-06-14,2105,5.5,Autonomous Tech -AI08096,Head of AI,99238,GBP,74429,MI,FT,United Kingdom,M,United Kingdom,0,"NLP, R, Kubernetes",Associate,3,Healthcare,2024-09-01,2024-09-23,956,8.2,DeepTech Ventures -AI08097,Data Analyst,87032,USD,87032,MI,FL,Finland,S,Finland,100,"Python, Kubernetes, Tableau",Bachelor,4,Consulting,2024-04-22,2024-05-17,1298,8.2,DeepTech Ventures -AI08098,Data Scientist,156773,USD,156773,SE,FT,Israel,L,Israel,100,"Statistics, Kubernetes, NLP, Linux",Master,5,Technology,2024-02-16,2024-04-03,2324,9.8,Smart Analytics -AI08099,AI Research Scientist,61019,AUD,82376,EN,FT,Australia,L,Australia,100,"Statistics, Git, NLP, Python",Bachelor,0,Real Estate,2024-11-10,2024-11-24,1197,8.6,DeepTech Ventures -AI08100,AI Research Scientist,70543,EUR,59962,EN,PT,Germany,M,Malaysia,0,"TensorFlow, Linux, Tableau, Hadoop, Kubernetes",Bachelor,1,Automotive,2025-03-20,2025-05-19,1099,8,Cloud AI Solutions -AI08101,Deep Learning Engineer,65930,AUD,89006,EN,CT,Australia,S,Australia,50,"GCP, NLP, Hadoop",Master,0,Gaming,2025-02-13,2025-03-07,1258,9.7,Digital Transformation LLC -AI08102,Data Scientist,61443,EUR,52227,EN,CT,France,M,France,0,"SQL, Hadoop, MLOps",Master,1,Healthcare,2024-08-06,2024-10-08,793,7,Algorithmic Solutions -AI08103,Deep Learning Engineer,389007,CHF,350106,EX,FL,Switzerland,L,Switzerland,50,"GCP, Computer Vision, Hadoop, Deep Learning, Spark",PhD,17,Gaming,2025-01-06,2025-02-22,1261,9.2,Smart Analytics -AI08104,Data Engineer,76813,EUR,65291,MI,PT,Germany,S,Germany,50,"Kubernetes, Spark, NLP, Statistics",Associate,2,Energy,2024-04-22,2024-06-14,1138,8.4,Future Systems -AI08105,ML Ops Engineer,98906,EUR,84070,MI,CT,Austria,L,Austria,0,"Computer Vision, Python, NLP, Spark, TensorFlow",Associate,4,Manufacturing,2025-01-23,2025-03-19,1508,7,DeepTech Ventures -AI08106,Data Scientist,74348,GBP,55761,MI,FL,United Kingdom,S,Singapore,100,"MLOps, Kubernetes, Deep Learning",PhD,3,Government,2025-01-30,2025-04-01,860,6,TechCorp Inc -AI08107,Data Analyst,91122,CHF,82010,EN,FL,Switzerland,M,Switzerland,100,"Mathematics, Deep Learning, Computer Vision, PyTorch, Kubernetes",PhD,0,Government,2024-02-12,2024-04-11,1786,8.6,Advanced Robotics -AI08108,Data Scientist,185096,EUR,157332,EX,FT,France,S,France,100,"Git, Azure, Linux",Bachelor,14,Consulting,2024-01-16,2024-03-06,2314,9.5,Quantum Computing Inc -AI08109,NLP Engineer,94648,EUR,80451,MI,FT,France,M,France,50,"GCP, R, Kubernetes",PhD,3,Automotive,2024-04-14,2024-05-28,2479,7.7,Digital Transformation LLC -AI08110,AI Architect,81723,EUR,69465,MI,PT,France,S,France,0,"Java, R, Spark, SQL, MLOps",Master,3,Gaming,2024-03-14,2024-03-28,724,6.2,Autonomous Tech -AI08111,Autonomous Systems Engineer,249442,GBP,187082,EX,FT,United Kingdom,M,United Kingdom,50,"Deep Learning, R, Tableau, GCP",Bachelor,11,Finance,2025-01-28,2025-03-16,1202,9.4,Digital Transformation LLC -AI08112,Robotics Engineer,111472,CAD,139340,SE,PT,Canada,M,Ghana,100,"Scala, Git, Computer Vision, NLP, AWS",PhD,8,Healthcare,2025-01-04,2025-01-26,2448,6.5,Machine Intelligence Group -AI08113,Data Analyst,107982,USD,107982,MI,PT,Norway,S,Norway,100,"Java, R, Azure, Hadoop, Git",Master,2,Finance,2025-04-03,2025-06-02,2009,8.4,Cognitive Computing -AI08114,NLP Engineer,106322,USD,106322,SE,FT,South Korea,L,South Korea,50,"Kubernetes, TensorFlow, Azure",PhD,5,Technology,2024-03-16,2024-04-16,2356,8.8,Cognitive Computing -AI08115,Data Scientist,97096,USD,97096,MI,PT,South Korea,L,Luxembourg,0,"Linux, NLP, Tableau, Scala",Master,2,Automotive,2025-03-13,2025-05-11,2414,6.3,Advanced Robotics -AI08116,Machine Learning Engineer,71329,USD,71329,SE,FL,China,L,China,0,"GCP, PyTorch, TensorFlow, Kubernetes, AWS",Bachelor,7,Education,2024-10-14,2024-10-31,2022,6.6,DataVision Ltd -AI08117,Machine Learning Researcher,204502,USD,204502,EX,FT,Israel,L,Canada,0,"Computer Vision, Deep Learning, SQL, Linux, Python",Associate,17,Automotive,2024-05-22,2024-06-12,636,7.7,Quantum Computing Inc -AI08118,AI Software Engineer,78540,AUD,106029,EN,PT,Australia,L,Canada,0,"Linux, Deep Learning, Spark, Hadoop",PhD,1,Real Estate,2024-06-27,2024-07-17,1984,8.4,Machine Intelligence Group -AI08119,AI Specialist,102696,USD,102696,MI,FL,Norway,M,Norway,50,"GCP, Statistics, Linux, PyTorch",Bachelor,3,Technology,2024-10-01,2024-11-24,2251,8.7,Digital Transformation LLC -AI08120,Machine Learning Engineer,140672,USD,140672,SE,FL,Ireland,M,Ireland,0,"SQL, Kubernetes, Data Visualization",Master,6,Energy,2025-04-16,2025-05-15,1303,5.4,Smart Analytics -AI08121,AI Consultant,306231,JPY,33685410,EX,FT,Japan,L,Japan,50,"SQL, Linux, Spark, Azure, Hadoop",PhD,11,Transportation,2024-11-09,2025-01-13,2186,7.7,DeepTech Ventures -AI08122,Research Scientist,79751,USD,79751,MI,FT,Israel,L,Israel,0,"Linux, PyTorch, R, NLP",Associate,3,Consulting,2025-01-12,2025-02-10,1412,6.5,Future Systems -AI08123,Data Analyst,59536,AUD,80374,EN,PT,Australia,S,Australia,0,"Python, SQL, AWS",Master,1,Real Estate,2024-03-14,2024-04-17,905,7.5,DeepTech Ventures -AI08124,Data Analyst,217273,USD,217273,EX,CT,Sweden,M,Sweden,100,"GCP, Deep Learning, PyTorch",Bachelor,14,Retail,2024-09-05,2024-10-15,1637,8.5,DataVision Ltd -AI08125,AI Software Engineer,61375,USD,61375,EN,CT,Finland,M,Finland,0,"MLOps, Data Visualization, Python",Associate,1,Technology,2024-04-07,2024-05-06,1196,5.2,Cognitive Computing -AI08126,AI Research Scientist,84104,CHF,75694,EN,PT,Switzerland,S,Switzerland,100,"MLOps, Mathematics, Linux",Associate,0,Energy,2024-12-07,2025-01-11,1663,9.1,Predictive Systems -AI08127,Machine Learning Researcher,119885,JPY,13187350,SE,FT,Japan,M,Japan,50,"Hadoop, Statistics, Git",Master,8,Consulting,2024-04-15,2024-05-15,1847,5.7,Advanced Robotics -AI08128,Head of AI,49872,USD,49872,EN,CT,Finland,M,Germany,100,"GCP, Deep Learning, MLOps, Linux, SQL",Bachelor,1,Telecommunications,2024-03-06,2024-03-30,2282,8.6,AI Innovations -AI08129,AI Product Manager,83785,USD,83785,EX,PT,India,L,Hungary,100,"Scala, R, Statistics",Bachelor,16,Real Estate,2024-12-11,2025-01-24,970,5.9,Cloud AI Solutions -AI08130,Principal Data Scientist,47263,AUD,63805,EN,PT,Australia,S,Australia,100,"AWS, Kubernetes, PyTorch",Associate,1,Education,2025-02-23,2025-05-05,2397,9.9,DataVision Ltd -AI08131,Machine Learning Researcher,82949,CAD,103686,EN,FT,Canada,L,Canada,50,"Mathematics, Git, NLP, Python",PhD,1,Media,2025-04-14,2025-06-10,1455,5.5,Smart Analytics -AI08132,AI Architect,85674,USD,85674,MI,FL,Sweden,M,China,0,"SQL, Python, GCP, Azure",Associate,4,Automotive,2025-04-19,2025-06-25,2146,5.6,Predictive Systems -AI08133,Research Scientist,66353,USD,66353,MI,FL,South Korea,S,South Korea,100,"Python, Hadoop, Deep Learning, SQL",PhD,4,Transportation,2024-08-10,2024-10-12,507,5.8,AI Innovations -AI08134,AI Product Manager,169078,USD,169078,EX,FT,Sweden,S,Sweden,100,"GCP, Statistics, Tableau",Bachelor,18,Automotive,2025-03-05,2025-04-16,814,6.9,Cognitive Computing -AI08135,Autonomous Systems Engineer,181932,EUR,154642,EX,CT,Germany,M,Germany,100,"Docker, Spark, Scala",Master,17,Education,2024-01-02,2024-01-28,1918,7.7,Cognitive Computing -AI08136,Autonomous Systems Engineer,93368,EUR,79363,SE,CT,Germany,S,Germany,50,"R, Scala, Data Visualization",Master,6,Healthcare,2024-08-02,2024-09-01,705,5.2,Neural Networks Co -AI08137,AI Specialist,112677,USD,112677,SE,CT,Israel,S,Israel,50,"Data Visualization, Linux, SQL, R",Bachelor,9,Automotive,2025-02-26,2025-04-06,1251,6.3,Digital Transformation LLC -AI08138,Computer Vision Engineer,145606,EUR,123765,EX,CT,Germany,M,Germany,50,"Java, SQL, Hadoop, Kubernetes",PhD,12,Real Estate,2024-09-20,2024-11-09,1136,6.7,Quantum Computing Inc -AI08139,AI Specialist,60885,USD,60885,EN,FL,Ireland,S,Argentina,50,"Python, SQL, Linux",PhD,0,Manufacturing,2025-03-07,2025-05-08,640,7.1,Digital Transformation LLC -AI08140,Robotics Engineer,53376,AUD,72058,EN,FL,Australia,M,China,100,"Deep Learning, GCP, Kubernetes",Bachelor,0,Technology,2024-08-24,2024-09-26,1725,7,Algorithmic Solutions -AI08141,AI Consultant,75818,EUR,64445,EN,CT,Netherlands,L,Netherlands,0,"Python, Spark, Scala, AWS, R",Master,0,Gaming,2024-10-28,2025-01-08,544,8.3,Quantum Computing Inc -AI08142,Principal Data Scientist,99061,EUR,84202,MI,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, Tableau",Associate,3,Gaming,2025-02-19,2025-04-17,1973,7,Quantum Computing Inc -AI08143,Data Analyst,107756,EUR,91593,MI,FT,Germany,L,Germany,50,"Azure, SQL, Java",Associate,4,Healthcare,2024-10-30,2024-12-10,661,8.1,Cognitive Computing -AI08144,Computer Vision Engineer,75125,USD,75125,SE,FL,China,L,China,0,"Tableau, Azure, Kubernetes, Mathematics",PhD,9,Automotive,2024-01-07,2024-02-08,1592,7.2,Smart Analytics -AI08145,Machine Learning Researcher,96840,CHF,87156,EN,CT,Switzerland,S,Switzerland,50,"Python, TensorFlow, PyTorch, Tableau, Mathematics",Bachelor,0,Finance,2024-12-25,2025-02-03,578,9.1,DataVision Ltd -AI08146,NLP Engineer,78676,USD,78676,EN,CT,Sweden,M,Sweden,100,"Mathematics, Hadoop, Python, Spark",PhD,0,Gaming,2024-07-03,2024-08-25,1565,9.9,Autonomous Tech -AI08147,Computer Vision Engineer,206627,CHF,185964,EX,FL,Switzerland,S,South Korea,100,"TensorFlow, Deep Learning, Tableau, Kubernetes, SQL",Bachelor,10,Transportation,2025-04-14,2025-05-26,767,7.4,Predictive Systems -AI08148,Principal Data Scientist,74509,USD,74509,SE,CT,China,L,Vietnam,100,"TensorFlow, Docker, Kubernetes, GCP, Data Visualization",Bachelor,9,Education,2024-07-17,2024-08-22,2330,7.3,Autonomous Tech -AI08149,Data Engineer,147081,EUR,125019,SE,FL,Germany,L,Malaysia,50,"R, SQL, Statistics",PhD,5,Government,2024-11-05,2024-12-17,1029,7.6,Autonomous Tech -AI08150,AI Consultant,148813,CAD,186016,EX,PT,Canada,M,Canada,0,"Tableau, GCP, Scala, NLP",Bachelor,15,Government,2024-08-22,2024-10-21,2385,8.7,Algorithmic Solutions -AI08151,Deep Learning Engineer,194557,AUD,262652,EX,CT,Australia,M,Australia,100,"Mathematics, Hadoop, Data Visualization, AWS",Master,18,Energy,2024-11-09,2025-01-16,1321,6.4,Quantum Computing Inc -AI08152,Data Analyst,220707,EUR,187601,EX,PT,Germany,S,Germany,100,"Mathematics, SQL, AWS, Kubernetes, Linux",PhD,18,Manufacturing,2024-01-08,2024-02-19,1499,6.4,Cognitive Computing -AI08153,AI Architect,83907,EUR,71321,EN,FT,Austria,L,Brazil,0,"R, Deep Learning, Tableau, PyTorch, Mathematics",PhD,0,Automotive,2024-09-29,2024-10-30,1079,8.8,DataVision Ltd -AI08154,NLP Engineer,203429,CHF,183086,SE,CT,Switzerland,M,China,100,"Kubernetes, AWS, GCP",PhD,5,Technology,2024-06-26,2024-07-22,1030,7.1,Advanced Robotics -AI08155,Head of AI,121903,USD,121903,SE,CT,South Korea,M,South Korea,0,"Python, Hadoop, Mathematics, Tableau, Computer Vision",Master,8,Media,2025-02-28,2025-03-18,667,6.9,Advanced Robotics -AI08156,Computer Vision Engineer,97513,CAD,121891,MI,PT,Canada,L,Canada,50,"Docker, Python, Statistics",Master,3,Real Estate,2024-05-11,2024-07-03,2187,7.1,Machine Intelligence Group -AI08157,AI Consultant,229343,CHF,206409,SE,FL,Switzerland,L,Switzerland,100,"PyTorch, Scala, MLOps, Computer Vision",PhD,6,Automotive,2024-06-20,2024-08-17,548,9.6,Autonomous Tech -AI08158,Data Scientist,135831,SGD,176580,SE,CT,Singapore,S,New Zealand,50,"AWS, Docker, Data Visualization, Deep Learning",Master,8,Manufacturing,2024-10-14,2024-11-18,1245,7.3,Algorithmic Solutions -AI08159,AI Specialist,229897,CHF,206907,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Computer Vision, Hadoop",PhD,9,Gaming,2024-07-14,2024-09-23,1540,5.1,Digital Transformation LLC -AI08160,Data Scientist,75572,AUD,102022,MI,FL,Australia,S,Australia,100,"Tableau, Python, Hadoop",Master,4,Healthcare,2024-09-10,2024-10-03,1850,9.3,Neural Networks Co -AI08161,AI Product Manager,160993,JPY,17709230,EX,FL,Japan,S,Japan,0,"Python, Kubernetes, Git, Linux",PhD,15,Real Estate,2024-05-11,2024-06-24,1652,6.6,Algorithmic Solutions -AI08162,Data Engineer,81776,SGD,106309,MI,CT,Singapore,S,Singapore,50,"R, PyTorch, Spark, Statistics",PhD,3,Consulting,2024-02-11,2024-04-17,820,5.6,Machine Intelligence Group -AI08163,Head of AI,81570,USD,81570,EN,PT,Finland,L,Finland,50,"Linux, Data Visualization, Hadoop, Azure, Tableau",Bachelor,0,Energy,2024-05-11,2024-06-12,507,7.4,Smart Analytics -AI08164,Autonomous Systems Engineer,93162,EUR,79188,MI,CT,Germany,S,Germany,100,"Data Visualization, Git, Python, Scala, Computer Vision",Master,4,Energy,2024-02-23,2024-04-27,535,7.2,Predictive Systems -AI08165,Machine Learning Researcher,227631,AUD,307302,EX,FT,Australia,S,Argentina,100,"SQL, GCP, Git",PhD,19,Gaming,2024-07-21,2024-09-26,640,6.2,AI Innovations -AI08166,AI Architect,131380,USD,131380,SE,FL,Sweden,L,Poland,100,"SQL, Deep Learning, Scala, Computer Vision, PyTorch",Bachelor,5,Telecommunications,2025-02-25,2025-05-01,2251,6.9,Algorithmic Solutions -AI08167,Data Analyst,33242,USD,33242,EN,FT,China,L,Estonia,0,"Kubernetes, SQL, Tableau",Associate,0,Healthcare,2024-08-07,2024-08-24,552,8.7,Cloud AI Solutions -AI08168,Data Scientist,336599,USD,336599,EX,FT,Denmark,L,Denmark,50,"PyTorch, Linux, Statistics, GCP, Python",Bachelor,14,Retail,2024-11-14,2025-01-14,1602,7,Smart Analytics -AI08169,AI Software Engineer,132545,SGD,172309,MI,FT,Singapore,L,United Kingdom,0,"AWS, Kubernetes, NLP, Azure",Bachelor,4,Consulting,2025-02-03,2025-02-21,2499,5.5,Smart Analytics -AI08170,AI Specialist,300635,USD,300635,EX,CT,United States,L,United States,100,"PyTorch, Python, Computer Vision, Scala",Associate,10,Energy,2024-06-18,2024-07-24,1527,7.8,Quantum Computing Inc -AI08171,AI Specialist,94953,USD,94953,MI,FT,Sweden,S,Sweden,0,"PyTorch, Data Visualization, Scala, Linux, TensorFlow",Bachelor,2,Healthcare,2024-01-04,2024-02-03,999,7.1,Machine Intelligence Group -AI08172,AI Architect,178775,AUD,241346,EX,FT,Australia,S,Denmark,0,"Java, Tableau, R, Statistics, GCP",Associate,11,Retail,2024-08-21,2024-10-13,1289,5,Machine Intelligence Group -AI08173,Data Analyst,74369,CAD,92961,MI,FT,Canada,S,Canada,100,"Statistics, Data Visualization, GCP, Hadoop",Associate,3,Real Estate,2024-11-10,2024-11-27,1659,7.9,Digital Transformation LLC -AI08174,Computer Vision Engineer,75798,USD,75798,EN,FL,Norway,M,Norway,0,"Statistics, R, Mathematics",Associate,1,Media,2024-04-28,2024-05-25,1617,6.8,DeepTech Ventures -AI08175,Autonomous Systems Engineer,186114,EUR,158197,EX,FL,Austria,L,Austria,100,"NLP, SQL, Data Visualization, Azure",Associate,19,Consulting,2024-12-15,2025-02-19,762,9.2,Cognitive Computing -AI08176,AI Product Manager,95648,USD,95648,MI,CT,Ireland,M,Austria,50,"Linux, Python, Java, Spark",Bachelor,4,Energy,2024-10-04,2024-11-29,1137,6.4,Digital Transformation LLC -AI08177,AI Research Scientist,359202,CHF,323282,EX,CT,Switzerland,M,Switzerland,0,"Python, MLOps, Computer Vision",Associate,13,Finance,2025-01-26,2025-03-29,1430,7.7,DataVision Ltd -AI08178,Head of AI,76073,GBP,57055,MI,FL,United Kingdom,S,United Kingdom,50,"Python, Git, TensorFlow, MLOps",Master,2,Technology,2024-09-17,2024-11-11,1703,7.3,Advanced Robotics -AI08179,NLP Engineer,49705,USD,49705,EN,FT,Finland,M,Indonesia,50,"Spark, Tableau, Azure, GCP",Bachelor,0,Telecommunications,2024-07-25,2024-08-30,1697,5.1,DataVision Ltd -AI08180,AI Consultant,98961,EUR,84117,MI,FL,Netherlands,S,Ireland,100,"R, PyTorch, Docker, Linux",Master,4,Technology,2025-01-16,2025-02-18,1231,6.1,Cloud AI Solutions -AI08181,Data Scientist,73832,USD,73832,EN,FL,United States,M,United States,0,"NLP, Spark, Deep Learning, MLOps",PhD,0,Healthcare,2025-04-28,2025-06-20,1551,5.2,Cloud AI Solutions -AI08182,NLP Engineer,209012,USD,209012,EX,FL,Sweden,M,Sweden,0,"Python, Kubernetes, Spark",Bachelor,16,Government,2024-10-04,2024-11-26,2115,7.8,DataVision Ltd -AI08183,AI Research Scientist,114933,JPY,12642630,MI,CT,Japan,M,Russia,0,"Kubernetes, Git, SQL",Associate,3,Automotive,2024-03-18,2024-05-29,608,6.3,Digital Transformation LLC -AI08184,Data Analyst,127420,CHF,114678,MI,FL,Switzerland,M,Switzerland,0,"Docker, Python, TensorFlow",PhD,3,Consulting,2024-04-30,2024-05-27,987,9.7,Smart Analytics -AI08185,Machine Learning Engineer,144510,EUR,122834,SE,PT,France,L,France,50,"Computer Vision, Hadoop, Mathematics",Master,5,Retail,2025-02-05,2025-02-24,2346,8.4,Digital Transformation LLC -AI08186,Autonomous Systems Engineer,99445,AUD,134251,SE,FT,Australia,S,Australia,50,"MLOps, Tableau, SQL, Data Visualization, R",PhD,9,Consulting,2024-08-30,2024-09-21,1691,8.9,Autonomous Tech -AI08187,AI Research Scientist,101862,EUR,86583,MI,FT,Netherlands,L,Netherlands,50,"Deep Learning, PyTorch, TensorFlow, GCP",Bachelor,4,Automotive,2024-09-04,2024-10-04,2009,7.1,Future Systems -AI08188,Computer Vision Engineer,54758,USD,54758,EN,CT,Israel,S,Ghana,0,"TensorFlow, SQL, MLOps, GCP",Bachelor,0,Transportation,2024-12-08,2025-02-18,1157,8.2,Neural Networks Co -AI08189,Robotics Engineer,93957,EUR,79863,MI,PT,Netherlands,S,Mexico,50,"GCP, SQL, Azure",PhD,4,Energy,2024-11-03,2025-01-03,569,6.7,Quantum Computing Inc -AI08190,Machine Learning Researcher,184257,EUR,156618,EX,PT,Austria,L,Austria,0,"SQL, Docker, Data Visualization",Associate,17,Telecommunications,2025-02-08,2025-04-17,1806,6.3,Cognitive Computing -AI08191,Head of AI,65196,EUR,55417,MI,PT,France,S,France,50,"SQL, TensorFlow, Data Visualization, Linux",PhD,2,Government,2024-09-16,2024-10-20,909,8.6,Future Systems -AI08192,Data Analyst,121164,USD,121164,EX,FL,South Korea,S,South Korea,50,"GCP, Git, Deep Learning, Docker",Bachelor,12,Education,2024-05-09,2024-06-11,1313,5.9,Machine Intelligence Group -AI08193,Machine Learning Engineer,93873,AUD,126729,SE,PT,Australia,S,Australia,50,"Mathematics, Data Visualization, Tableau, Linux, Hadoop",Bachelor,7,Retail,2024-06-04,2024-06-27,1816,9.2,Digital Transformation LLC -AI08194,Computer Vision Engineer,148307,USD,148307,MI,FL,Denmark,L,Denmark,50,"Java, Computer Vision, Python, Tableau, Data Visualization",PhD,3,Healthcare,2024-10-08,2024-11-09,2328,6.2,AI Innovations -AI08195,AI Specialist,145377,GBP,109033,EX,PT,United Kingdom,S,United Kingdom,100,"Git, Deep Learning, Data Visualization",PhD,10,Technology,2024-03-08,2024-05-14,1526,9.6,DataVision Ltd -AI08196,Autonomous Systems Engineer,42525,USD,42525,EN,PT,South Korea,M,Estonia,50,"SQL, Deep Learning, Java, Python",Associate,1,Finance,2024-10-26,2024-11-25,862,9.3,Cognitive Computing -AI08197,AI Software Engineer,282434,USD,282434,EX,CT,Denmark,S,Denmark,100,"Azure, Java, MLOps, SQL, R",PhD,18,Telecommunications,2024-06-07,2024-06-26,1490,8.2,DeepTech Ventures -AI08198,AI Research Scientist,209133,USD,209133,EX,FT,Norway,L,Germany,50,"Scala, Git, Computer Vision, Spark",Associate,15,Energy,2024-01-01,2024-01-26,2279,8.1,Cognitive Computing -AI08199,Principal Data Scientist,250333,GBP,187750,EX,FT,United Kingdom,L,United Kingdom,0,"Linux, Statistics, PyTorch, Mathematics, Tableau",Bachelor,18,Healthcare,2024-01-23,2024-03-22,1827,8,Predictive Systems -AI08200,Research Scientist,174979,USD,174979,EX,FL,Norway,S,Indonesia,100,"Deep Learning, AWS, Computer Vision, Scala",Bachelor,18,Technology,2024-03-16,2024-03-30,2275,7.5,Smart Analytics -AI08201,Data Scientist,101837,USD,101837,SE,CT,Sweden,S,Sweden,100,"Azure, Scala, PyTorch",Bachelor,6,Government,2024-10-03,2024-10-20,600,6.6,Quantum Computing Inc -AI08202,Machine Learning Researcher,109223,USD,109223,SE,FT,Finland,M,Estonia,100,"TensorFlow, Azure, Mathematics, Kubernetes, AWS",Bachelor,5,Gaming,2024-07-28,2024-08-16,1615,8.2,Algorithmic Solutions -AI08203,Machine Learning Researcher,160180,USD,160180,SE,CT,Norway,S,Norway,50,"Linux, Scala, Mathematics, Kubernetes, Tableau",PhD,8,Real Estate,2024-11-06,2025-01-07,1020,6.1,Autonomous Tech -AI08204,Principal Data Scientist,52809,USD,52809,EN,PT,South Korea,L,South Korea,0,"Tableau, PyTorch, Git",Bachelor,1,Retail,2024-05-04,2024-05-30,1410,6.8,Autonomous Tech -AI08205,Computer Vision Engineer,218360,USD,218360,EX,FT,Norway,M,Norway,0,"Kubernetes, R, AWS, Mathematics, Statistics",Bachelor,12,Healthcare,2025-04-06,2025-04-26,2264,9.8,Digital Transformation LLC -AI08206,AI Consultant,99844,EUR,84867,MI,FT,Austria,L,India,0,"Hadoop, TensorFlow, Java, GCP, Docker",Bachelor,2,Retail,2024-07-28,2024-10-05,1801,8.3,Algorithmic Solutions -AI08207,AI Research Scientist,191537,SGD,248998,EX,FL,Singapore,L,Ireland,0,"Data Visualization, Hadoop, Computer Vision",Associate,12,Finance,2024-03-25,2024-04-29,928,6.4,Algorithmic Solutions -AI08208,Machine Learning Researcher,225775,USD,225775,EX,CT,Israel,M,Israel,0,"Python, Java, Hadoop, GCP, NLP",Bachelor,14,Finance,2024-05-13,2024-06-02,1054,5.5,AI Innovations -AI08209,Data Scientist,83618,USD,83618,EN,FL,Finland,L,Finland,0,"TensorFlow, Python, Hadoop, Tableau",Master,0,Automotive,2024-11-14,2025-01-21,1114,8.9,Neural Networks Co -AI08210,ML Ops Engineer,167785,EUR,142617,EX,FT,Germany,S,Germany,100,"Git, Deep Learning, Azure",Master,14,Manufacturing,2024-09-30,2024-10-29,1951,8.1,Machine Intelligence Group -AI08211,AI Research Scientist,25456,USD,25456,EN,CT,India,S,India,0,"AWS, Mathematics, Python",Bachelor,0,Government,2024-10-05,2024-10-19,1184,6.8,Neural Networks Co -AI08212,Data Analyst,109322,USD,109322,SE,CT,South Korea,L,South Korea,50,"Python, SQL, TensorFlow, AWS, Java",PhD,6,Gaming,2024-03-05,2024-05-03,2326,9.2,TechCorp Inc -AI08213,AI Architect,100260,USD,100260,SE,FL,Finland,M,Belgium,50,"PyTorch, Hadoop, Docker, Computer Vision",PhD,9,Manufacturing,2024-09-07,2024-10-14,1995,10,Smart Analytics -AI08214,Data Analyst,111999,USD,111999,SE,PT,Israel,M,Israel,50,"PyTorch, Python, Java, NLP, Hadoop",PhD,5,Automotive,2025-03-02,2025-05-09,833,5,AI Innovations -AI08215,Robotics Engineer,70798,JPY,7787780,EN,FT,Japan,M,Japan,100,"Tableau, TensorFlow, Python",PhD,1,Finance,2024-12-17,2025-01-04,1022,6.7,DataVision Ltd -AI08216,Robotics Engineer,75569,AUD,102018,MI,PT,Australia,S,Australia,50,"AWS, PyTorch, SQL",Bachelor,4,Gaming,2025-03-15,2025-05-06,1557,6.9,Neural Networks Co -AI08217,Autonomous Systems Engineer,173910,USD,173910,EX,PT,Israel,L,Israel,0,"TensorFlow, Deep Learning, Azure",Master,10,Healthcare,2025-01-18,2025-03-06,1685,5.6,Smart Analytics -AI08218,AI Software Engineer,234620,USD,234620,EX,PT,United States,M,United States,50,"Data Visualization, Git, GCP",Master,11,Consulting,2024-03-19,2024-05-30,2246,5.6,TechCorp Inc -AI08219,Data Scientist,54313,EUR,46166,EN,FL,Netherlands,S,Netherlands,50,"Azure, R, Scala, SQL, Git",Associate,1,Transportation,2024-04-04,2024-05-14,626,5.5,Predictive Systems -AI08220,Machine Learning Engineer,223033,GBP,167275,EX,FL,United Kingdom,S,Mexico,50,"Java, Computer Vision, SQL",Bachelor,14,Telecommunications,2024-05-05,2024-06-16,531,9.2,Autonomous Tech -AI08221,ML Ops Engineer,235007,USD,235007,EX,FT,South Korea,L,South Korea,0,"SQL, Kubernetes, NLP",Master,16,Healthcare,2024-10-22,2024-12-18,2222,9.2,TechCorp Inc -AI08222,AI Specialist,68349,EUR,58097,EN,PT,Netherlands,S,Netherlands,100,"Docker, NLP, Data Visualization, Linux",Master,0,Finance,2025-04-19,2025-06-14,2333,8.6,Future Systems -AI08223,AI Consultant,88924,USD,88924,MI,CT,Israel,L,Israel,100,"SQL, PyTorch, Deep Learning, Azure, AWS",Master,4,Real Estate,2024-03-23,2024-05-25,1368,5.8,Predictive Systems -AI08224,AI Specialist,107723,USD,107723,SE,FT,South Korea,L,South Korea,50,"R, Python, Statistics, Spark, GCP",Associate,5,Energy,2025-04-13,2025-06-23,664,8.2,Machine Intelligence Group -AI08225,AI Architect,100120,USD,100120,MI,FL,Denmark,S,Denmark,100,"Python, Git, Spark",Associate,4,Technology,2024-02-17,2024-04-07,2445,5.5,Neural Networks Co -AI08226,AI Specialist,52959,USD,52959,EN,CT,Israel,S,Israel,50,"Python, Tableau, Git",Master,1,Retail,2024-12-09,2025-01-28,645,5.7,DataVision Ltd -AI08227,ML Ops Engineer,88552,EUR,75269,EN,CT,Germany,L,Portugal,50,"MLOps, Tableau, SQL",PhD,0,Consulting,2025-03-02,2025-04-08,1539,5.8,AI Innovations -AI08228,AI Research Scientist,152649,CHF,137384,SE,FT,Switzerland,S,Switzerland,0,"Hadoop, Kubernetes, MLOps",Bachelor,6,Transportation,2025-04-20,2025-06-07,963,5.9,Cloud AI Solutions -AI08229,Computer Vision Engineer,89988,USD,89988,EX,FL,China,L,China,100,"TensorFlow, Spark, Data Visualization, SQL, Docker",Bachelor,19,Healthcare,2024-12-31,2025-01-23,686,6.8,Algorithmic Solutions -AI08230,Principal Data Scientist,91107,USD,91107,MI,PT,United States,S,Japan,0,"R, Data Visualization, Linux",PhD,4,Retail,2025-04-05,2025-04-23,2056,8.4,Digital Transformation LLC -AI08231,AI Software Engineer,144476,USD,144476,MI,FT,United States,L,Mexico,100,"Python, SQL, Tableau, Git, Java",Master,2,Manufacturing,2024-11-04,2024-12-02,1950,6.9,Advanced Robotics -AI08232,Data Engineer,161347,CHF,145212,SE,PT,Switzerland,M,Switzerland,0,"Data Visualization, Spark, PyTorch, Git, Statistics",Bachelor,6,Telecommunications,2024-11-24,2025-01-11,1879,9.9,DataVision Ltd -AI08233,Principal Data Scientist,140235,AUD,189317,EX,FT,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau",Master,11,Energy,2024-05-27,2024-06-13,2013,9.6,Algorithmic Solutions -AI08234,Data Analyst,148219,USD,148219,EX,CT,Sweden,S,Sweden,100,"Java, Azure, Tableau, Python",Associate,16,Manufacturing,2024-10-26,2024-12-31,1949,8.6,Smart Analytics -AI08235,AI Architect,105601,SGD,137281,SE,FT,Singapore,S,France,100,"Git, Python, Hadoop",Master,7,Media,2024-01-23,2024-03-30,2256,5.8,AI Innovations -AI08236,AI Architect,64809,JPY,7128990,EN,CT,Japan,L,Portugal,0,"Docker, R, NLP",Bachelor,1,Technology,2025-01-14,2025-02-15,1701,7.2,Algorithmic Solutions -AI08237,Machine Learning Researcher,78106,EUR,66390,EN,FT,Austria,L,Germany,50,"Spark, PyTorch, R, Computer Vision",Master,1,Consulting,2025-04-25,2025-06-26,2113,9.1,Advanced Robotics -AI08238,Data Analyst,60250,SGD,78325,EN,FL,Singapore,M,Singapore,100,"SQL, Scala, Kubernetes, Deep Learning",PhD,1,Retail,2025-04-01,2025-05-30,1424,7.3,Cloud AI Solutions -AI08239,Machine Learning Researcher,54773,GBP,41080,EN,CT,United Kingdom,S,United Kingdom,100,"SQL, TensorFlow, Computer Vision, Statistics",Bachelor,0,Automotive,2024-02-22,2024-04-25,2397,7.9,TechCorp Inc -AI08240,Machine Learning Researcher,111174,USD,111174,EN,FL,Denmark,L,Japan,50,"Data Visualization, Hadoop, Python, R",Master,0,Automotive,2024-08-12,2024-09-08,1329,5.9,Cognitive Computing -AI08241,AI Software Engineer,67798,CAD,84748,EN,PT,Canada,L,Malaysia,100,"PyTorch, Python, Docker, Mathematics, SQL",Master,1,Finance,2024-03-10,2024-04-20,631,7.1,Autonomous Tech -AI08242,AI Specialist,124429,USD,124429,SE,FT,Sweden,M,Sweden,50,"Python, Data Visualization, SQL, Computer Vision, Hadoop",Associate,5,Finance,2024-11-02,2024-12-03,1318,8.1,DeepTech Ventures -AI08243,Deep Learning Engineer,61446,EUR,52229,EN,PT,Austria,S,Austria,50,"Statistics, Git, MLOps, GCP",PhD,0,Real Estate,2024-09-06,2024-09-24,1899,6.2,AI Innovations -AI08244,Research Scientist,166025,EUR,141121,EX,CT,Germany,S,Germany,0,"Hadoop, Kubernetes, Git, PyTorch, Linux",PhD,14,Finance,2024-08-11,2024-10-17,782,7.7,Cognitive Computing -AI08245,Deep Learning Engineer,200365,AUD,270493,EX,CT,Australia,M,Australia,100,"Java, SQL, Data Visualization",Bachelor,10,Energy,2024-02-02,2024-03-17,1775,5.6,Cognitive Computing -AI08246,AI Consultant,68661,USD,68661,EN,CT,Denmark,M,Denmark,0,"Python, Git, TensorFlow, Computer Vision",Master,0,Education,2025-03-26,2025-04-10,1038,6.4,Cognitive Computing -AI08247,Research Scientist,128591,USD,128591,MI,CT,United States,L,United States,50,"MLOps, Docker, Data Visualization, PyTorch",Bachelor,2,Government,2024-06-15,2024-08-08,1680,6.5,Predictive Systems -AI08248,Machine Learning Researcher,90540,USD,90540,MI,FT,Norway,S,Chile,100,"Data Visualization, R, Python, TensorFlow",Associate,2,Education,2024-11-11,2024-12-27,2176,9.9,Quantum Computing Inc -AI08249,AI Software Engineer,98359,USD,98359,MI,FL,United States,M,Spain,100,"Git, AWS, Hadoop, R",Associate,2,Real Estate,2024-10-13,2024-12-22,628,7.9,Cognitive Computing -AI08250,Deep Learning Engineer,60172,USD,60172,EN,FT,Finland,M,Finland,50,"Python, Azure, Tableau",Associate,1,Automotive,2024-01-17,2024-02-14,2166,9.6,Cloud AI Solutions -AI08251,Data Engineer,59702,USD,59702,MI,CT,South Korea,S,South Korea,0,"Statistics, Data Visualization, AWS, Mathematics, Python",Bachelor,4,Real Estate,2024-06-30,2024-08-30,2287,8,AI Innovations -AI08252,Research Scientist,231158,USD,231158,EX,CT,United States,M,Belgium,0,"GCP, Java, Hadoop, Scala",Associate,11,Government,2024-09-01,2024-11-09,1335,5.6,Cognitive Computing -AI08253,Principal Data Scientist,56253,EUR,47815,EN,PT,France,S,Sweden,0,"Tableau, Git, PyTorch, TensorFlow",Associate,1,Real Estate,2024-08-26,2024-09-26,1976,6.2,Autonomous Tech -AI08254,AI Product Manager,66100,USD,66100,EN,PT,Ireland,S,Ireland,100,"Deep Learning, Python, Tableau, Hadoop",Master,1,Government,2024-09-23,2024-11-15,1415,9.7,AI Innovations -AI08255,AI Software Engineer,43269,USD,43269,MI,FT,China,M,China,100,"SQL, MLOps, PyTorch, Statistics, Python",Associate,3,Finance,2024-09-20,2024-10-05,2402,8.5,DeepTech Ventures -AI08256,AI Software Engineer,87445,SGD,113679,EN,PT,Singapore,L,Singapore,0,"Scala, Python, TensorFlow, AWS, Mathematics",Associate,0,Consulting,2025-01-13,2025-03-16,2260,6.9,Cloud AI Solutions -AI08257,Deep Learning Engineer,125861,EUR,106982,SE,FL,Netherlands,L,Netherlands,0,"AWS, Java, Python",Bachelor,9,Technology,2025-02-15,2025-03-06,574,7,Machine Intelligence Group -AI08258,AI Specialist,218971,GBP,164228,EX,PT,United Kingdom,S,Ukraine,0,"PyTorch, Hadoop, Kubernetes, Azure",Master,14,Telecommunications,2024-08-27,2024-11-07,2328,5.7,AI Innovations -AI08259,AI Software Engineer,192168,USD,192168,EX,FL,Ireland,L,Ireland,100,"SQL, Azure, Kubernetes, GCP, NLP",Master,13,Finance,2024-08-18,2024-10-01,1469,7.6,Quantum Computing Inc -AI08260,AI Product Manager,159792,EUR,135823,EX,FL,Austria,M,Austria,100,"R, NLP, Data Visualization, Kubernetes",PhD,19,Healthcare,2024-07-01,2024-07-24,576,8.3,AI Innovations -AI08261,Autonomous Systems Engineer,228879,EUR,194547,EX,FT,Germany,L,Australia,100,"Tableau, Java, Python",Master,13,Real Estate,2024-12-20,2025-01-12,1732,7.4,Machine Intelligence Group -AI08262,AI Product Manager,213850,GBP,160388,EX,FT,United Kingdom,S,United Kingdom,50,"Python, Docker, Hadoop, Statistics",Associate,13,Real Estate,2024-12-05,2025-01-07,1984,6.2,Digital Transformation LLC -AI08263,Machine Learning Engineer,161935,USD,161935,EX,CT,Sweden,S,Spain,50,"AWS, Azure, Deep Learning, Python",Bachelor,14,Finance,2025-01-12,2025-02-12,2282,6.1,AI Innovations -AI08264,NLP Engineer,46071,USD,46071,EN,FT,Finland,S,Finland,50,"Python, Kubernetes, R",Associate,1,Finance,2024-09-11,2024-11-23,1573,8.8,AI Innovations -AI08265,Head of AI,138140,SGD,179582,SE,PT,Singapore,M,Singapore,0,"Python, Statistics, Mathematics",Associate,9,Technology,2024-02-11,2024-03-10,1215,5.5,Advanced Robotics -AI08266,NLP Engineer,40218,USD,40218,MI,FT,India,L,India,0,"Deep Learning, Mathematics, Data Visualization",Master,2,Education,2024-01-01,2024-01-23,1620,7.2,Future Systems -AI08267,Robotics Engineer,69695,CAD,87119,EN,CT,Canada,L,Canada,0,"Hadoop, Java, Scala, Azure",Associate,1,Media,2024-06-03,2024-06-22,1729,6.4,Autonomous Tech -AI08268,Machine Learning Researcher,87123,EUR,74055,MI,PT,Germany,L,Germany,100,"Scala, Data Visualization, Statistics",Associate,4,Energy,2025-03-20,2025-05-13,1316,6.3,Cloud AI Solutions -AI08269,Data Engineer,88198,USD,88198,MI,PT,Israel,S,Israel,100,"Spark, PyTorch, Tableau",PhD,3,Energy,2025-01-22,2025-03-21,715,7.3,Smart Analytics -AI08270,AI Product Manager,64179,USD,64179,EN,PT,Sweden,S,Sweden,100,"Java, Git, AWS, Linux, Computer Vision",Associate,0,Consulting,2024-07-13,2024-08-11,1398,9.8,DataVision Ltd -AI08271,ML Ops Engineer,85336,USD,85336,MI,CT,Ireland,M,Ireland,100,"Kubernetes, TensorFlow, Tableau, MLOps, Data Visualization",Master,4,Manufacturing,2024-11-05,2024-12-23,754,6.4,TechCorp Inc -AI08272,Head of AI,83626,AUD,112895,MI,FL,Australia,L,Hungary,0,"Linux, Kubernetes, Scala, Java",PhD,2,Government,2025-03-28,2025-04-18,1439,8.6,Future Systems -AI08273,AI Product Manager,103151,USD,103151,MI,PT,United States,L,United States,50,"Data Visualization, Scala, Tableau",PhD,4,Gaming,2024-11-10,2024-12-04,1252,6.1,Quantum Computing Inc -AI08274,Principal Data Scientist,71248,USD,71248,MI,CT,South Korea,L,South Korea,0,"Data Visualization, Tableau, SQL, NLP, Python",PhD,3,Real Estate,2025-03-01,2025-04-26,1534,10,Advanced Robotics -AI08275,Data Scientist,85197,USD,85197,EN,FL,Ireland,L,Ireland,0,"Docker, Git, Data Visualization",PhD,1,Energy,2024-07-26,2024-09-25,590,6.8,TechCorp Inc -AI08276,AI Consultant,48680,USD,48680,EN,FL,South Korea,S,South Korea,0,"Hadoop, Computer Vision, AWS, PyTorch",Associate,0,Retail,2024-10-05,2024-12-07,1515,9.8,Quantum Computing Inc -AI08277,Head of AI,104442,USD,104442,EN,FL,Norway,M,Norway,50,"Hadoop, R, SQL, MLOps, NLP",PhD,0,Manufacturing,2025-03-21,2025-04-10,1557,8.3,Algorithmic Solutions -AI08278,AI Software Engineer,108808,EUR,92487,SE,FT,Germany,M,Germany,50,"Data Visualization, PyTorch, Scala, AWS",Bachelor,7,Energy,2024-11-29,2025-01-17,851,5.9,DeepTech Ventures -AI08279,Head of AI,222268,EUR,188928,EX,CT,France,L,France,0,"Azure, Kubernetes, Statistics",Associate,12,Automotive,2024-11-20,2024-12-13,1598,8.2,TechCorp Inc -AI08280,AI Research Scientist,69400,USD,69400,MI,CT,Finland,M,Turkey,0,"Deep Learning, Data Visualization, Tableau, Spark, Computer Vision",PhD,2,Real Estate,2024-04-27,2024-06-19,909,6.3,Smart Analytics -AI08281,ML Ops Engineer,146017,JPY,16061870,EX,CT,Japan,S,Colombia,0,"Linux, Deep Learning, SQL",PhD,17,Gaming,2024-02-07,2024-03-10,551,8.4,Advanced Robotics -AI08282,AI Architect,128715,SGD,167330,SE,CT,Singapore,M,Singapore,50,"Python, Deep Learning, Java, SQL",Bachelor,7,Technology,2024-11-05,2024-11-22,1880,6,Smart Analytics -AI08283,Principal Data Scientist,291772,CHF,262595,EX,PT,Switzerland,M,Switzerland,50,"Kubernetes, Docker, SQL, Tableau",Associate,15,Telecommunications,2024-01-02,2024-02-19,1924,6.9,Future Systems -AI08284,Robotics Engineer,88229,USD,88229,SE,FT,South Korea,M,Germany,50,"Docker, Azure, Mathematics, Java",Associate,5,Telecommunications,2024-03-12,2024-04-26,2075,5.3,Cognitive Computing -AI08285,Head of AI,125238,AUD,169071,SE,PT,Australia,S,Japan,0,"Deep Learning, AWS, R, Python",Master,5,Gaming,2024-01-16,2024-02-18,2338,6,Digital Transformation LLC -AI08286,Autonomous Systems Engineer,59375,USD,59375,EN,FL,Finland,S,Finland,0,"R, Tableau, Scala",Bachelor,0,Technology,2024-11-20,2024-12-16,2109,9.5,Advanced Robotics -AI08287,Computer Vision Engineer,200898,USD,200898,EX,FL,Sweden,L,Sweden,100,"MLOps, Git, SQL",Bachelor,16,Automotive,2024-10-11,2024-10-26,2127,9.4,Advanced Robotics -AI08288,AI Architect,70777,USD,70777,EX,CT,India,L,India,0,"Linux, Hadoop, Kubernetes",Associate,18,Retail,2024-10-07,2024-11-10,1846,8.8,DataVision Ltd -AI08289,Head of AI,174280,GBP,130710,EX,PT,United Kingdom,M,Singapore,0,"Git, GCP, MLOps, Python, Azure",PhD,11,Real Estate,2024-10-06,2024-12-05,1269,8.2,DataVision Ltd -AI08290,Autonomous Systems Engineer,83034,CAD,103793,MI,FL,Canada,M,Canada,50,"Azure, PyTorch, Scala, Git, TensorFlow",Bachelor,3,Real Estate,2025-01-07,2025-02-17,2323,7.6,Autonomous Tech -AI08291,Machine Learning Engineer,80523,USD,80523,MI,FT,South Korea,L,South Korea,100,"Statistics, PyTorch, NLP, Azure",Master,3,Real Estate,2025-04-06,2025-05-22,2395,6.7,Quantum Computing Inc -AI08292,Machine Learning Engineer,85363,USD,85363,EN,CT,Sweden,L,Turkey,50,"Python, SQL, Linux, GCP, Hadoop",Bachelor,0,Media,2024-03-19,2024-04-07,601,9.8,Machine Intelligence Group -AI08293,NLP Engineer,84635,USD,84635,EN,CT,Denmark,M,Denmark,0,"Tableau, SQL, Scala",PhD,1,Retail,2024-04-02,2024-04-19,1101,8.4,Machine Intelligence Group -AI08294,AI Research Scientist,92637,EUR,78741,SE,PT,Germany,S,Germany,0,"GCP, Mathematics, Git, SQL",Associate,7,Real Estate,2024-10-31,2024-12-12,716,7.4,AI Innovations -AI08295,AI Research Scientist,135123,SGD,175660,SE,FT,Singapore,S,Singapore,0,"MLOps, Spark, Deep Learning, AWS, R",Associate,7,Telecommunications,2024-08-25,2024-09-10,596,9.9,Future Systems -AI08296,Principal Data Scientist,73693,USD,73693,EX,CT,China,S,China,50,"R, Deep Learning, Statistics, Python, TensorFlow",Associate,13,Healthcare,2024-01-01,2024-02-25,1055,9.1,Cloud AI Solutions -AI08297,AI Specialist,62151,USD,62151,SE,FL,China,M,China,100,"TensorFlow, Python, Java",Bachelor,6,Government,2024-03-16,2024-04-17,1507,7.1,AI Innovations -AI08298,Data Engineer,107829,CHF,97046,MI,FL,Switzerland,S,Switzerland,0,"Spark, TensorFlow, Python, Git",Bachelor,3,Government,2024-07-27,2024-09-17,815,5.8,Cloud AI Solutions -AI08299,Robotics Engineer,149913,GBP,112435,SE,FT,United Kingdom,M,Mexico,100,"Kubernetes, SQL, Statistics, MLOps, Azure",Associate,8,Manufacturing,2024-12-15,2025-01-22,1153,5.7,Neural Networks Co -AI08300,Head of AI,147367,USD,147367,SE,PT,United States,M,Denmark,50,"Data Visualization, Scala, AWS, Computer Vision, SQL",Bachelor,9,Automotive,2025-04-13,2025-06-11,2235,5.2,Cloud AI Solutions -AI08301,Research Scientist,143496,USD,143496,EX,FT,Finland,M,Finland,50,"Linux, Kubernetes, Docker, Tableau",PhD,15,Consulting,2024-01-29,2024-02-23,962,7.3,Machine Intelligence Group -AI08302,AI Architect,265331,USD,265331,EX,FT,Norway,L,Netherlands,50,"Deep Learning, Hadoop, R, SQL, NLP",Master,10,Healthcare,2024-05-25,2024-06-21,605,6.3,Quantum Computing Inc -AI08303,AI Product Manager,72261,EUR,61422,EN,PT,Germany,S,Germany,0,"Data Visualization, Python, Hadoop, Linux, Java",Associate,1,Manufacturing,2024-06-18,2024-08-14,2384,5.7,DataVision Ltd -AI08304,AI Specialist,255237,CHF,229713,EX,CT,Switzerland,S,Mexico,50,"Azure, TensorFlow, Tableau, Data Visualization, GCP",Bachelor,12,Gaming,2024-02-16,2024-03-30,969,7.7,TechCorp Inc -AI08305,AI Specialist,61670,USD,61670,EN,PT,Ireland,M,Ireland,0,"Kubernetes, Python, Spark, Data Visualization",Associate,1,Retail,2024-10-05,2024-12-07,567,8,Smart Analytics -AI08306,AI Product Manager,92113,USD,92113,MI,PT,Ireland,M,Ireland,50,"Azure, Python, Data Visualization, Java, GCP",Master,3,Automotive,2024-05-05,2024-07-02,2339,6.7,Neural Networks Co -AI08307,Head of AI,291884,EUR,248101,EX,PT,Germany,L,Philippines,100,"Data Visualization, Mathematics, SQL",Bachelor,17,Consulting,2025-01-13,2025-02-14,859,7.4,Advanced Robotics -AI08308,Autonomous Systems Engineer,180243,JPY,19826730,EX,PT,Japan,L,Japan,0,"AWS, Hadoop, Java",Bachelor,18,Retail,2025-01-20,2025-03-27,2024,9.9,DeepTech Ventures -AI08309,AI Product Manager,57135,USD,57135,EX,CT,India,M,India,0,"PyTorch, Git, Data Visualization, Scala, Hadoop",Bachelor,10,Automotive,2025-02-07,2025-03-09,1222,8.6,Autonomous Tech -AI08310,Deep Learning Engineer,109488,SGD,142334,SE,FT,Singapore,S,Chile,100,"Linux, SQL, NLP",Bachelor,7,Healthcare,2024-05-13,2024-06-30,1770,5.8,Algorithmic Solutions -AI08311,Head of AI,124520,USD,124520,MI,FT,Denmark,S,Mexico,0,"Git, AWS, Kubernetes",Associate,4,Media,2024-03-09,2024-05-12,922,6.9,DataVision Ltd -AI08312,Deep Learning Engineer,127767,USD,127767,MI,CT,United States,M,United States,50,"Spark, GCP, PyTorch, Mathematics",Associate,4,Transportation,2024-05-01,2024-07-08,1260,7.7,Autonomous Tech -AI08313,Robotics Engineer,80406,USD,80406,MI,FT,Sweden,M,Sweden,0,"MLOps, Azure, Deep Learning",PhD,3,Media,2024-11-01,2024-11-26,1697,6.8,Predictive Systems -AI08314,AI Consultant,82023,CAD,102529,MI,CT,Canada,L,Canada,50,"Linux, Python, TensorFlow, PyTorch",Associate,4,Media,2024-04-14,2024-06-25,1382,9.6,TechCorp Inc -AI08315,Research Scientist,128543,SGD,167106,SE,CT,Singapore,M,Singapore,50,"Python, Spark, PyTorch, Kubernetes",Master,8,Energy,2024-08-05,2024-09-25,514,8,Advanced Robotics -AI08316,Deep Learning Engineer,75558,USD,75558,MI,PT,Sweden,M,Sweden,100,"Spark, Python, SQL, GCP",Associate,2,Transportation,2024-12-21,2025-01-27,1422,6.4,Quantum Computing Inc -AI08317,NLP Engineer,72192,GBP,54144,EN,PT,United Kingdom,M,Poland,50,"Kubernetes, Java, Hadoop",Master,0,Manufacturing,2024-09-08,2024-09-26,501,7.4,Cognitive Computing -AI08318,Data Scientist,68382,EUR,58125,EN,PT,Germany,S,Germany,0,"Deep Learning, Git, Java, SQL",PhD,1,Automotive,2024-03-23,2024-04-26,2001,8.9,Digital Transformation LLC -AI08319,Machine Learning Engineer,37162,USD,37162,SE,FT,India,S,China,100,"Scala, Mathematics, Deep Learning",Master,5,Retail,2024-12-14,2025-02-04,1613,7.5,Algorithmic Solutions -AI08320,Data Engineer,90745,EUR,77133,MI,CT,Netherlands,S,Netherlands,50,"Tableau, SQL, Scala, PyTorch, Python",Master,2,Automotive,2024-08-28,2024-11-03,2203,9.5,AI Innovations -AI08321,Data Engineer,68389,USD,68389,EN,CT,Finland,M,Finland,50,"Hadoop, Python, TensorFlow",Bachelor,1,Automotive,2024-05-27,2024-07-04,1625,8.4,Machine Intelligence Group -AI08322,Deep Learning Engineer,52150,USD,52150,EX,CT,India,S,Japan,50,"PyTorch, MLOps, SQL",Master,16,Telecommunications,2024-02-15,2024-03-10,839,8.4,AI Innovations -AI08323,Machine Learning Engineer,70856,USD,70856,MI,CT,Israel,M,Israel,0,"Kubernetes, Git, Spark, Scala",Bachelor,2,Manufacturing,2024-03-08,2024-05-13,1675,6.1,Cognitive Computing -AI08324,AI Product Manager,70901,USD,70901,EN,FT,Sweden,L,Sweden,0,"AWS, Python, Git, Deep Learning, TensorFlow",Bachelor,0,Education,2024-03-22,2024-04-23,1246,8,Cloud AI Solutions -AI08325,Machine Learning Engineer,18392,USD,18392,EN,CT,India,S,Colombia,100,"Spark, Git, R, Java",PhD,0,Manufacturing,2024-02-18,2024-03-09,1206,9.7,Machine Intelligence Group -AI08326,Machine Learning Engineer,72083,GBP,54062,MI,CT,United Kingdom,S,United Kingdom,100,"Scala, Git, Kubernetes, SQL, AWS",Master,4,Energy,2024-02-27,2024-04-26,1006,9.8,Advanced Robotics -AI08327,Data Engineer,80363,EUR,68309,EN,FL,Netherlands,M,United States,0,"Computer Vision, Spark, Deep Learning, SQL",Bachelor,1,Education,2025-04-30,2025-06-13,2448,8.5,Future Systems -AI08328,Deep Learning Engineer,81508,USD,81508,EX,PT,India,L,India,50,"Hadoop, NLP, Deep Learning, Tableau, Kubernetes",Master,10,Healthcare,2024-07-16,2024-09-17,1183,9.4,Cognitive Computing -AI08329,Computer Vision Engineer,58680,CAD,73350,EN,FT,Canada,M,Ghana,100,"Docker, Scala, SQL, Kubernetes",Bachelor,1,Real Estate,2025-03-24,2025-05-02,1626,5.9,DeepTech Ventures -AI08330,Deep Learning Engineer,127110,EUR,108044,SE,PT,Netherlands,L,Switzerland,100,"NLP, SQL, Linux, Git, GCP",PhD,6,Education,2024-10-21,2024-12-27,1388,9.8,DataVision Ltd -AI08331,Deep Learning Engineer,35777,USD,35777,EN,PT,China,L,China,0,"Hadoop, Java, Data Visualization, NLP",Master,1,Consulting,2024-02-04,2024-03-12,2081,6,Digital Transformation LLC -AI08332,AI Architect,137961,EUR,117267,SE,FL,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Kubernetes",Master,7,Finance,2025-02-23,2025-04-23,1015,8.2,Quantum Computing Inc -AI08333,Data Analyst,93307,CHF,83976,EN,FL,Switzerland,L,Switzerland,50,"SQL, PyTorch, TensorFlow, Linux",Master,0,Manufacturing,2024-03-30,2024-05-22,1208,6.4,Machine Intelligence Group -AI08334,Autonomous Systems Engineer,90828,AUD,122618,EN,FL,Australia,L,Australia,100,"Git, MLOps, Data Visualization",Bachelor,0,Education,2024-02-15,2024-03-30,1635,7.5,Cognitive Computing -AI08335,Data Engineer,42637,USD,42637,SE,PT,India,M,India,0,"SQL, PyTorch, Linux, Scala",PhD,8,Retail,2024-07-27,2024-10-03,1949,7.8,DataVision Ltd -AI08336,Machine Learning Engineer,183463,USD,183463,EX,CT,Denmark,S,Denmark,50,"Python, Computer Vision, Tableau, TensorFlow, Git",Associate,19,Automotive,2024-04-18,2024-05-24,674,5.9,Future Systems -AI08337,Machine Learning Engineer,110858,AUD,149658,MI,CT,Australia,L,Ireland,100,"PyTorch, Java, Tableau, Docker, Statistics",Associate,2,Manufacturing,2025-04-03,2025-05-15,1345,8.7,Cloud AI Solutions -AI08338,AI Consultant,187012,USD,187012,EX,CT,Finland,S,Finland,0,"Git, Azure, Computer Vision, Kubernetes",Master,13,Government,2024-03-21,2024-04-07,640,8.1,Algorithmic Solutions -AI08339,AI Software Engineer,267395,USD,267395,EX,PT,United States,L,United States,0,"Python, TensorFlow, Computer Vision, Statistics",Associate,17,Retail,2024-04-05,2024-05-03,2448,5.1,TechCorp Inc -AI08340,AI Software Engineer,49037,JPY,5394070,EN,PT,Japan,S,Sweden,50,"Computer Vision, Azure, Statistics, SQL, Spark",Bachelor,0,Government,2024-07-25,2024-08-29,2046,8.4,Machine Intelligence Group -AI08341,Deep Learning Engineer,231031,USD,231031,EX,FL,Ireland,L,Ireland,100,"NLP, AWS, SQL, Computer Vision",PhD,16,Automotive,2025-02-18,2025-04-10,1911,8.1,Future Systems -AI08342,AI Specialist,265453,USD,265453,EX,CT,Ireland,L,Ireland,50,"MLOps, AWS, Kubernetes, Scala, Hadoop",Master,14,Automotive,2024-12-24,2025-01-14,1989,7.9,Machine Intelligence Group -AI08343,AI Consultant,82540,USD,82540,MI,CT,Israel,S,Israel,100,"Git, AWS, Python, Computer Vision, Statistics",Bachelor,2,Gaming,2025-02-05,2025-04-01,2265,7.7,Cloud AI Solutions -AI08344,AI Specialist,126029,USD,126029,SE,FL,Israel,S,Israel,50,"Spark, Docker, Computer Vision, Statistics, Python",Master,6,Automotive,2025-02-23,2025-04-07,1666,8.1,Predictive Systems -AI08345,AI Architect,224510,JPY,24696100,EX,PT,Japan,S,Japan,50,"PyTorch, Docker, Git",Bachelor,14,Technology,2025-02-07,2025-04-17,2078,8.4,AI Innovations -AI08346,Research Scientist,76405,USD,76405,EN,FT,Denmark,L,Denmark,0,"Data Visualization, AWS, Spark, Mathematics",Bachelor,1,Gaming,2024-04-13,2024-05-03,1596,7.1,Algorithmic Solutions -AI08347,Machine Learning Researcher,57273,USD,57273,EN,FL,Israel,L,Israel,0,"Kubernetes, SQL, Mathematics",Bachelor,1,Transportation,2025-01-20,2025-03-23,984,7.8,Neural Networks Co -AI08348,Robotics Engineer,78816,USD,78816,MI,FL,South Korea,L,South Korea,50,"Linux, Computer Vision, R, Statistics",Associate,2,Gaming,2024-01-23,2024-02-19,1491,7,DataVision Ltd -AI08349,AI Specialist,129597,USD,129597,EX,FL,Ireland,S,Thailand,50,"Kubernetes, SQL, Statistics, Computer Vision, Java",Master,19,Real Estate,2024-09-25,2024-11-11,1470,7.5,DeepTech Ventures -AI08350,Robotics Engineer,78527,USD,78527,EX,PT,India,L,India,50,"SQL, Tableau, Linux",PhD,16,Energy,2025-01-12,2025-02-13,1545,6.5,Neural Networks Co -AI08351,AI Consultant,147701,GBP,110776,SE,FT,United Kingdom,L,Finland,50,"Computer Vision, Spark, Statistics, Python",Associate,7,Finance,2024-08-08,2024-09-20,623,8,Autonomous Tech -AI08352,Machine Learning Researcher,124500,USD,124500,SE,PT,Israel,L,Israel,100,"Git, Data Visualization, NLP",Associate,6,Consulting,2024-09-22,2024-11-26,2444,7.1,DataVision Ltd -AI08353,Data Engineer,30093,USD,30093,MI,FT,India,L,India,100,"Python, Computer Vision, Statistics",PhD,2,Real Estate,2024-07-08,2024-07-23,1079,5.6,DeepTech Ventures -AI08354,Computer Vision Engineer,95154,USD,95154,MI,CT,Sweden,M,Sweden,100,"Git, NLP, GCP",Bachelor,4,Gaming,2024-03-22,2024-04-23,755,5.8,Future Systems -AI08355,Machine Learning Researcher,125964,USD,125964,EX,FT,Ireland,S,Brazil,0,"SQL, AWS, Mathematics, NLP",Bachelor,14,Media,2025-01-25,2025-02-18,2241,6.7,Cloud AI Solutions -AI08356,Data Engineer,234668,EUR,199468,EX,FL,France,M,China,50,"Linux, NLP, Kubernetes, AWS, Python",PhD,15,Finance,2024-07-17,2024-08-18,1680,9,TechCorp Inc -AI08357,Head of AI,72375,EUR,61519,MI,FL,France,S,Philippines,0,"GCP, Mathematics, SQL, Scala, Deep Learning",Master,4,Consulting,2024-04-07,2024-04-30,759,6.9,DataVision Ltd -AI08358,Data Engineer,199511,USD,199511,EX,CT,Finland,L,Finland,50,"Statistics, NLP, SQL, Kubernetes",Master,15,Consulting,2024-12-19,2025-01-15,523,7.5,AI Innovations -AI08359,AI Specialist,82707,USD,82707,MI,FL,Ireland,S,Ireland,100,"Spark, NLP, Python",Bachelor,4,Manufacturing,2024-07-03,2024-08-19,538,8.9,Predictive Systems -AI08360,AI Architect,49846,USD,49846,EN,CT,Ireland,S,Ireland,50,"Mathematics, Spark, Deep Learning, NLP",Bachelor,0,Transportation,2025-04-03,2025-05-02,1323,5.9,Future Systems -AI08361,AI Research Scientist,231076,SGD,300399,EX,CT,Singapore,S,Singapore,50,"Python, Spark, Statistics, Data Visualization",Bachelor,14,Technology,2024-08-15,2024-09-28,1757,6.8,Neural Networks Co -AI08362,Research Scientist,150796,USD,150796,SE,CT,Denmark,M,Denmark,50,"Python, Mathematics, Kubernetes, Hadoop",Bachelor,7,Telecommunications,2024-05-28,2024-07-20,2287,6.2,Quantum Computing Inc -AI08363,Machine Learning Researcher,116702,USD,116702,SE,CT,Ireland,S,Ireland,50,"NLP, TensorFlow, Java, Linux, R",Bachelor,8,Technology,2025-03-01,2025-03-19,1076,8.3,Advanced Robotics -AI08364,Computer Vision Engineer,127076,CHF,114368,EN,PT,Switzerland,L,Switzerland,0,"NLP, Java, Mathematics, Python",Associate,0,Technology,2024-10-18,2024-12-09,1891,7.8,Quantum Computing Inc -AI08365,Machine Learning Researcher,138133,JPY,15194630,SE,CT,Japan,S,Philippines,100,"MLOps, Python, Data Visualization",PhD,9,Finance,2024-06-12,2024-08-15,1650,8,Cognitive Computing -AI08366,Data Scientist,72519,USD,72519,EN,FT,Finland,M,Switzerland,50,"Java, PyTorch, Spark",Bachelor,1,Manufacturing,2024-11-10,2025-01-22,1763,7.2,Predictive Systems -AI08367,AI Software Engineer,202605,USD,202605,EX,FL,Israel,L,Israel,100,"R, Deep Learning, TensorFlow",Master,19,Energy,2025-04-07,2025-05-04,950,9.1,Neural Networks Co -AI08368,ML Ops Engineer,147327,USD,147327,EX,PT,Finland,L,Vietnam,50,"Scala, GCP, Hadoop, SQL",Associate,12,Transportation,2025-01-07,2025-03-02,1715,5.9,DataVision Ltd -AI08369,AI Specialist,35455,USD,35455,MI,CT,India,M,India,100,"Kubernetes, Deep Learning, Data Visualization, Spark",Associate,4,Media,2025-03-05,2025-05-09,810,8.6,Machine Intelligence Group -AI08370,ML Ops Engineer,85603,USD,85603,MI,FL,Ireland,M,Ireland,100,"Data Visualization, Scala, Spark, Computer Vision",Bachelor,4,Gaming,2025-03-22,2025-05-19,1079,7,Cloud AI Solutions -AI08371,Data Scientist,174323,USD,174323,EX,FL,Israel,M,Spain,100,"Deep Learning, Kubernetes, NLP, Spark",PhD,11,Technology,2025-01-05,2025-01-22,2480,8.9,Autonomous Tech -AI08372,Head of AI,138386,CHF,124547,SE,FL,Switzerland,S,Switzerland,100,"Tableau, Azure, Hadoop, R, NLP",Master,5,Retail,2025-01-21,2025-03-15,2000,8.5,Future Systems -AI08373,AI Specialist,86425,USD,86425,MI,PT,Finland,S,Australia,100,"Python, Statistics, Git",Bachelor,4,Manufacturing,2024-10-24,2024-12-04,1636,9.1,Future Systems -AI08374,AI Architect,79209,EUR,67328,MI,FT,France,M,France,50,"Java, MLOps, TensorFlow",PhD,2,Gaming,2024-05-03,2024-05-22,2438,9.2,Future Systems -AI08375,Robotics Engineer,93206,GBP,69905,MI,PT,United Kingdom,L,United Kingdom,0,"Linux, Mathematics, Deep Learning",Bachelor,2,Consulting,2025-03-19,2025-04-09,692,6.2,Cloud AI Solutions -AI08376,Head of AI,183144,EUR,155672,EX,PT,Germany,S,Germany,50,"Data Visualization, GCP, Spark, TensorFlow",Associate,11,Gaming,2024-04-03,2024-05-12,1696,5.9,Smart Analytics -AI08377,Computer Vision Engineer,115035,USD,115035,MI,FL,United States,L,Poland,50,"Computer Vision, Linux, Mathematics, Git, Kubernetes",PhD,3,Telecommunications,2024-10-05,2024-12-14,1758,8.1,Advanced Robotics -AI08378,Robotics Engineer,52046,USD,52046,EN,PT,Ireland,M,Ireland,0,"Python, Java, Git, Linux, GCP",Master,0,Consulting,2024-04-21,2024-06-18,2451,7.5,Advanced Robotics -AI08379,Data Engineer,27042,USD,27042,MI,FT,India,M,India,0,"Scala, NLP, Java, Hadoop",Associate,3,Retail,2024-08-29,2024-10-21,1230,9.1,Quantum Computing Inc -AI08380,Principal Data Scientist,69140,EUR,58769,MI,FL,Germany,S,Philippines,100,"Java, Computer Vision, R",Associate,4,Education,2024-11-05,2024-11-23,2300,9.2,AI Innovations -AI08381,Principal Data Scientist,54144,USD,54144,SE,FL,China,M,South Korea,50,"Hadoop, Java, AWS, R, MLOps",Bachelor,5,Education,2024-04-07,2024-05-15,1069,8,Digital Transformation LLC -AI08382,Autonomous Systems Engineer,102140,GBP,76605,MI,PT,United Kingdom,M,United Kingdom,50,"Azure, Linux, Deep Learning",PhD,3,Real Estate,2024-09-02,2024-10-26,920,6.4,Smart Analytics -AI08383,Machine Learning Researcher,159981,EUR,135984,SE,PT,Germany,L,Germany,100,"Python, Computer Vision, Deep Learning",Associate,9,Retail,2024-01-16,2024-02-17,1058,7.1,DeepTech Ventures -AI08384,Research Scientist,52315,USD,52315,EN,FT,South Korea,M,South Korea,50,"Hadoop, SQL, Linux, Data Visualization, GCP",PhD,1,Media,2024-05-07,2024-06-17,944,6.2,Quantum Computing Inc -AI08385,AI Research Scientist,174231,AUD,235212,SE,PT,Australia,L,Australia,50,"NLP, Scala, Java, Linux",Associate,7,Manufacturing,2025-02-17,2025-03-14,2270,9.9,Cognitive Computing -AI08386,AI Specialist,97169,GBP,72877,MI,CT,United Kingdom,L,United Kingdom,0,"MLOps, AWS, Java, SQL, Git",Master,3,Government,2024-09-24,2024-10-09,2310,6.1,Predictive Systems -AI08387,Autonomous Systems Engineer,143744,CAD,179680,SE,PT,Canada,M,Poland,0,"Linux, Statistics, Deep Learning, MLOps",Bachelor,9,Energy,2024-12-17,2025-02-03,1811,5.8,Smart Analytics -AI08388,Data Scientist,112243,USD,112243,MI,CT,United States,S,Hungary,100,"Data Visualization, Scala, SQL, AWS",Master,2,Finance,2024-05-28,2024-07-18,978,7.8,Cognitive Computing -AI08389,ML Ops Engineer,127387,USD,127387,MI,FL,Denmark,M,China,0,"Deep Learning, PyTorch, MLOps",Bachelor,3,Technology,2025-04-02,2025-06-08,2393,7.7,Autonomous Tech -AI08390,Machine Learning Researcher,131304,EUR,111608,SE,PT,Austria,M,Austria,0,"SQL, PyTorch, GCP, Hadoop",PhD,6,Consulting,2024-12-16,2025-01-24,1299,8.4,Cognitive Computing -AI08391,Machine Learning Engineer,71777,AUD,96899,EN,FL,Australia,L,Ireland,50,"Java, R, Python, Azure, Mathematics",Master,0,Media,2025-01-03,2025-02-16,1167,8.2,Cognitive Computing -AI08392,Machine Learning Researcher,116676,SGD,151679,SE,PT,Singapore,S,Singapore,100,"Kubernetes, Hadoop, Java",Bachelor,7,Finance,2024-03-06,2024-04-09,764,7.6,AI Innovations -AI08393,AI Consultant,126226,GBP,94670,SE,FL,United Kingdom,S,Mexico,50,"Spark, Java, PyTorch, GCP",Master,6,Technology,2024-10-02,2024-12-11,901,9.1,Advanced Robotics -AI08394,ML Ops Engineer,82894,AUD,111907,MI,CT,Australia,S,Australia,100,"R, GCP, Computer Vision, Spark, SQL",Master,4,Government,2025-02-04,2025-02-18,624,7.8,TechCorp Inc -AI08395,Machine Learning Researcher,38746,USD,38746,EN,FT,China,L,South Korea,0,"Hadoop, Statistics, SQL, Tableau",Bachelor,0,Energy,2025-01-27,2025-02-26,1600,8.4,Quantum Computing Inc -AI08396,AI Consultant,92661,USD,92661,MI,FT,Norway,S,Japan,100,"SQL, Python, Git, Kubernetes",Master,2,Government,2024-04-26,2024-06-25,511,9.4,TechCorp Inc -AI08397,AI Research Scientist,62143,USD,62143,MI,PT,South Korea,M,Czech Republic,100,"Python, TensorFlow, NLP",Associate,4,Media,2025-01-31,2025-02-23,854,5.1,Autonomous Tech -AI08398,AI Software Engineer,176385,GBP,132289,EX,PT,United Kingdom,S,United Kingdom,100,"SQL, Scala, Azure, Computer Vision, GCP",Bachelor,14,Real Estate,2025-02-06,2025-02-21,2442,5.3,Machine Intelligence Group -AI08399,AI Software Engineer,81358,EUR,69154,MI,FL,France,M,France,0,"SQL, Docker, Data Visualization, Hadoop, Deep Learning",Associate,3,Media,2024-04-06,2024-04-28,836,5.3,DeepTech Ventures -AI08400,Robotics Engineer,78489,USD,78489,MI,FL,Israel,M,Israel,0,"Docker, AWS, NLP",PhD,2,Telecommunications,2025-04-02,2025-05-04,712,9,Advanced Robotics -AI08401,Autonomous Systems Engineer,157109,EUR,133543,SE,CT,Germany,L,Portugal,100,"Java, MLOps, R, NLP",PhD,5,Automotive,2025-01-12,2025-01-26,1530,8,Smart Analytics -AI08402,AI Software Engineer,154305,AUD,208312,EX,FL,Australia,S,Ghana,0,"TensorFlow, R, Statistics",Master,17,Telecommunications,2025-01-15,2025-02-19,2485,8,TechCorp Inc -AI08403,Machine Learning Engineer,61309,AUD,82767,EN,PT,Australia,S,India,50,"SQL, Python, Deep Learning, AWS, Statistics",Associate,0,Real Estate,2025-02-06,2025-03-11,820,6.9,DataVision Ltd -AI08404,Data Scientist,189613,AUD,255978,EX,FT,Australia,M,Australia,50,"Java, R, Hadoop",Associate,13,Media,2024-10-29,2024-11-22,1473,9.1,Cloud AI Solutions -AI08405,AI Product Manager,214403,USD,214403,EX,PT,United States,S,United States,0,"Docker, Linux, Azure, Statistics, Tableau",Associate,18,Retail,2025-03-18,2025-04-05,1843,6.3,TechCorp Inc -AI08406,AI Consultant,133222,EUR,113239,SE,PT,Austria,M,Argentina,0,"Scala, PyTorch, GCP, Spark, Computer Vision",Master,7,Transportation,2024-07-03,2024-08-09,1185,8.9,DataVision Ltd -AI08407,Data Engineer,62909,USD,62909,EN,PT,Israel,L,Israel,100,"Tableau, Java, Scala, Data Visualization, TensorFlow",PhD,1,Government,2024-08-19,2024-10-13,2330,5.2,DeepTech Ventures -AI08408,AI Product Manager,19343,USD,19343,EN,FT,India,S,India,50,"GCP, Git, PyTorch",Associate,1,Transportation,2025-01-05,2025-02-08,2174,9.3,Quantum Computing Inc -AI08409,Robotics Engineer,222547,USD,222547,EX,PT,Ireland,S,Ireland,0,"Linux, PyTorch, Data Visualization",Bachelor,14,Manufacturing,2024-02-19,2024-03-09,1579,5.6,Smart Analytics -AI08410,AI Consultant,234130,JPY,25754300,EX,FT,Japan,S,Japan,100,"Linux, Azure, MLOps, Git",Bachelor,11,Real Estate,2025-02-08,2025-02-23,1013,5.8,Cognitive Computing -AI08411,Deep Learning Engineer,215309,USD,215309,EX,CT,Finland,S,Finland,100,"Computer Vision, MLOps, GCP",Master,13,Media,2024-06-30,2024-09-09,1203,7.3,Cognitive Computing -AI08412,AI Product Manager,72372,USD,72372,MI,CT,Israel,S,Chile,50,"Scala, SQL, Spark, GCP",PhD,4,Technology,2024-04-13,2024-05-14,764,8.2,Smart Analytics -AI08413,Deep Learning Engineer,167429,AUD,226029,EX,CT,Australia,L,Austria,100,"SQL, AWS, Scala, GCP, Azure",Bachelor,11,Transportation,2024-04-17,2024-05-05,1020,6.5,Algorithmic Solutions -AI08414,AI Consultant,171432,USD,171432,EX,PT,Israel,L,Israel,50,"Spark, PyTorch, Java, TensorFlow",Bachelor,16,Energy,2024-06-06,2024-07-18,1921,6.1,Predictive Systems -AI08415,AI Research Scientist,162301,USD,162301,SE,FL,Sweden,L,United Kingdom,50,"SQL, Hadoop, Azure",Master,6,Telecommunications,2025-02-03,2025-04-02,1728,6.4,Cognitive Computing -AI08416,Computer Vision Engineer,106745,USD,106745,MI,CT,Sweden,M,Luxembourg,50,"Python, GCP, Azure, SQL, TensorFlow",Bachelor,3,Healthcare,2024-06-27,2024-07-23,2005,9.2,Advanced Robotics -AI08417,AI Specialist,169009,EUR,143658,EX,FL,Netherlands,L,Netherlands,0,"Computer Vision, PyTorch, Tableau",PhD,18,Government,2024-03-24,2024-05-26,1702,6.2,Algorithmic Solutions -AI08418,AI Architect,233941,SGD,304123,EX,PT,Singapore,M,Italy,50,"MLOps, SQL, AWS, NLP, Data Visualization",Bachelor,15,Energy,2024-06-13,2024-07-22,1480,6.3,Machine Intelligence Group -AI08419,AI Software Engineer,179620,EUR,152677,EX,PT,Austria,L,Sweden,50,"Python, Kubernetes, Statistics, AWS",Master,13,Technology,2024-01-28,2024-03-11,1610,9.6,Quantum Computing Inc -AI08420,ML Ops Engineer,128589,JPY,14144790,SE,PT,Japan,S,Japan,50,"PyTorch, TensorFlow, Docker",PhD,6,Gaming,2024-10-13,2024-11-08,2114,9,AI Innovations -AI08421,Deep Learning Engineer,76779,EUR,65262,EN,PT,Netherlands,L,Netherlands,0,"Mathematics, PyTorch, Scala",Associate,1,Retail,2024-12-16,2025-01-12,2438,7,Neural Networks Co -AI08422,AI Specialist,114807,EUR,97586,SE,FL,France,S,Norway,100,"Azure, Java, Git",Master,6,Automotive,2024-06-06,2024-07-31,1526,6.6,DataVision Ltd -AI08423,Autonomous Systems Engineer,126904,AUD,171320,SE,PT,Australia,S,Australia,50,"Scala, Kubernetes, R, GCP, Hadoop",Master,8,Consulting,2024-12-05,2025-01-11,2035,6.8,Neural Networks Co -AI08424,ML Ops Engineer,23823,USD,23823,EN,CT,India,L,India,50,"GCP, Python, TensorFlow, Deep Learning",PhD,0,Media,2024-08-10,2024-09-06,1222,6.2,Cloud AI Solutions -AI08425,Robotics Engineer,91085,USD,91085,MI,FL,United States,S,United States,50,"Computer Vision, Statistics, NLP, Kubernetes",Master,4,Consulting,2025-03-09,2025-05-09,1623,9.9,Cloud AI Solutions -AI08426,AI Software Engineer,123889,EUR,105306,SE,CT,Netherlands,M,Netherlands,0,"Python, Hadoop, R, Linux",Associate,6,Retail,2024-02-10,2024-04-04,1683,8.9,Quantum Computing Inc -AI08427,Machine Learning Engineer,116702,USD,116702,SE,CT,South Korea,M,South Korea,50,"Hadoop, Tableau, AWS, PyTorch",Master,9,Technology,2024-07-14,2024-09-04,1427,6,Predictive Systems -AI08428,Research Scientist,114453,USD,114453,MI,PT,Sweden,L,Argentina,0,"Spark, SQL, Azure, MLOps",PhD,2,Government,2024-06-06,2024-08-04,2473,5.2,TechCorp Inc -AI08429,Data Analyst,127753,GBP,95815,MI,FT,United Kingdom,L,United Kingdom,50,"TensorFlow, Docker, Tableau, Java",Master,4,Technology,2025-01-13,2025-03-14,665,5.1,Smart Analytics -AI08430,AI Research Scientist,279320,SGD,363116,EX,FT,Singapore,L,Turkey,50,"Computer Vision, MLOps, Statistics",Associate,14,Telecommunications,2024-02-28,2024-04-01,1660,8.8,DeepTech Ventures -AI08431,Computer Vision Engineer,193375,EUR,164369,EX,FT,Germany,M,Czech Republic,50,"Tableau, Python, NLP, Spark, Computer Vision",Master,10,Education,2024-06-21,2024-07-06,2499,9.3,Machine Intelligence Group -AI08432,AI Consultant,199737,CHF,179763,SE,FT,Switzerland,M,Switzerland,0,"Java, Scala, MLOps",Master,8,Telecommunications,2025-01-28,2025-02-27,2100,7.8,Cloud AI Solutions -AI08433,AI Software Engineer,53228,USD,53228,EN,CT,Finland,S,Finland,0,"TensorFlow, SQL, Data Visualization, Mathematics",Master,0,Energy,2024-03-06,2024-05-13,1656,9.8,Smart Analytics -AI08434,Autonomous Systems Engineer,124669,EUR,105969,SE,CT,Austria,L,Austria,100,"Deep Learning, Python, Linux",Master,6,Real Estate,2025-02-09,2025-03-21,1166,8.1,Algorithmic Solutions -AI08435,AI Research Scientist,139094,USD,139094,SE,CT,Norway,S,Singapore,50,"SQL, Docker, PyTorch, Hadoop, Scala",Bachelor,5,Education,2024-10-30,2024-11-20,842,9.6,Algorithmic Solutions -AI08436,AI Research Scientist,103028,CHF,92725,EN,FL,Switzerland,L,Portugal,100,"Computer Vision, Tableau, Scala, Deep Learning, Azure",Associate,1,Retail,2024-10-21,2024-11-06,1091,8,Advanced Robotics -AI08437,Data Analyst,140713,USD,140713,SE,PT,Ireland,L,Sweden,50,"Data Visualization, Python, TensorFlow",Associate,5,Automotive,2024-12-10,2025-01-27,2280,9,Cognitive Computing -AI08438,AI Software Engineer,93762,USD,93762,EN,CT,Norway,M,Norway,100,"GCP, Python, Deep Learning, TensorFlow",PhD,1,Education,2025-01-05,2025-03-09,1924,9.2,AI Innovations -AI08439,Machine Learning Engineer,60042,USD,60042,EN,CT,United States,M,United States,50,"Scala, Azure, Tableau",Associate,0,Automotive,2024-06-20,2024-08-16,905,5.2,Neural Networks Co -AI08440,Deep Learning Engineer,125462,USD,125462,SE,FL,Israel,M,Norway,0,"Mathematics, SQL, Data Visualization, Linux",Master,8,Manufacturing,2024-09-18,2024-10-20,1182,9.1,Future Systems -AI08441,Autonomous Systems Engineer,79766,EUR,67801,MI,PT,Germany,M,Germany,0,"Spark, Hadoop, Tableau",Associate,4,Automotive,2025-02-13,2025-03-29,769,7.3,Algorithmic Solutions -AI08442,AI Architect,63995,USD,63995,SE,CT,China,S,China,50,"Java, SQL, Kubernetes, AWS",Associate,9,Energy,2024-05-05,2024-07-09,1467,8,Cognitive Computing -AI08443,Deep Learning Engineer,67575,EUR,57439,EN,CT,France,S,France,0,"R, Scala, GCP, Linux",Bachelor,0,Real Estate,2024-12-28,2025-02-15,2065,9.8,DeepTech Ventures -AI08444,Machine Learning Engineer,180825,GBP,135619,SE,FT,United Kingdom,L,Russia,0,"SQL, Scala, NLP, Statistics, PyTorch",Master,5,Healthcare,2024-02-07,2024-03-17,2210,7.4,Neural Networks Co -AI08445,Autonomous Systems Engineer,46588,USD,46588,SE,CT,China,S,China,0,"Hadoop, Mathematics, NLP, AWS",Bachelor,7,Government,2024-12-04,2025-01-10,1897,8.6,Machine Intelligence Group -AI08446,AI Specialist,70840,USD,70840,EN,FT,Sweden,S,Sweden,0,"SQL, Data Visualization, Linux",Master,0,Telecommunications,2024-06-08,2024-07-21,2485,9,Predictive Systems -AI08447,AI Research Scientist,40656,USD,40656,MI,PT,China,M,China,50,"Python, Mathematics, GCP, AWS",PhD,3,Retail,2025-01-17,2025-03-15,1534,5.3,Advanced Robotics -AI08448,Research Scientist,50149,EUR,42627,EN,PT,Austria,S,Austria,50,"Data Visualization, AWS, SQL, Statistics",Associate,0,Finance,2024-10-15,2024-12-12,1516,6.1,TechCorp Inc -AI08449,Research Scientist,128622,AUD,173640,SE,FL,Australia,M,Australia,100,"Deep Learning, Scala, PyTorch, Mathematics, GCP",Associate,9,Education,2024-12-05,2025-01-22,1434,7.4,Cloud AI Solutions -AI08450,Machine Learning Engineer,100866,GBP,75650,MI,FL,United Kingdom,S,United Kingdom,0,"Java, Scala, Linux, Deep Learning",Bachelor,4,Telecommunications,2024-03-18,2024-04-26,1156,5.5,Quantum Computing Inc -AI08451,AI Architect,98292,GBP,73719,MI,FT,United Kingdom,L,United Kingdom,0,"Scala, Hadoop, Statistics, TensorFlow",Associate,2,Automotive,2024-07-18,2024-09-04,2349,8.4,Quantum Computing Inc -AI08452,Machine Learning Engineer,77362,AUD,104439,MI,FT,Australia,M,Australia,50,"SQL, Linux, Java, PyTorch",Bachelor,4,Gaming,2025-03-18,2025-04-24,834,7.9,DataVision Ltd -AI08453,Data Analyst,78850,AUD,106448,MI,FT,Australia,M,Australia,100,"Tableau, GCP, TensorFlow, PyTorch, Azure",Associate,2,Government,2025-03-06,2025-05-18,1560,5.7,Predictive Systems -AI08454,Computer Vision Engineer,87737,GBP,65803,EN,FT,United Kingdom,L,United Kingdom,0,"R, AWS, NLP, MLOps, Spark",PhD,1,Education,2025-02-09,2025-04-16,552,8.6,Predictive Systems -AI08455,AI Architect,91614,USD,91614,MI,FL,Ireland,L,Ireland,0,"Python, NLP, Kubernetes, Computer Vision",Associate,4,Technology,2024-12-21,2025-02-12,1349,5.5,AI Innovations -AI08456,Computer Vision Engineer,186919,USD,186919,EX,CT,Norway,S,Norway,0,"Java, Linux, SQL, Deep Learning",Bachelor,14,Healthcare,2024-05-16,2024-07-05,1629,9.9,Quantum Computing Inc -AI08457,Data Scientist,70265,CAD,87831,EN,PT,Canada,M,Estonia,50,"Kubernetes, SQL, Tableau, TensorFlow, Mathematics",Bachelor,0,Transportation,2024-07-23,2024-08-07,1608,7.5,AI Innovations -AI08458,Autonomous Systems Engineer,45732,USD,45732,EN,FT,Finland,S,Finland,100,"Kubernetes, SQL, Data Visualization",PhD,1,Energy,2025-02-23,2025-04-05,1157,7.4,DataVision Ltd -AI08459,Machine Learning Researcher,36182,USD,36182,SE,FT,India,M,India,100,"NLP, Data Visualization, PyTorch, MLOps, TensorFlow",Master,6,Automotive,2024-12-03,2025-01-24,2302,7.7,Future Systems -AI08460,AI Software Engineer,64887,EUR,55154,MI,PT,Austria,S,Austria,50,"Linux, Tableau, PyTorch",Associate,4,Consulting,2024-02-26,2024-04-09,1763,7.4,Predictive Systems -AI08461,AI Product Manager,309181,USD,309181,EX,FT,Denmark,L,Estonia,50,"GCP, Python, Spark",Master,15,Government,2025-01-01,2025-02-10,1074,7.6,Smart Analytics -AI08462,Data Analyst,93055,USD,93055,MI,FT,United States,M,United States,100,"Statistics, Kubernetes, Java, GCP, Scala",Master,3,Retail,2024-04-04,2024-05-23,1929,7.2,Cloud AI Solutions -AI08463,Data Analyst,186453,CHF,167808,SE,FL,Switzerland,M,Sweden,100,"Scala, Hadoop, Java, Mathematics, Statistics",Associate,6,Energy,2025-04-06,2025-04-26,567,6.9,DataVision Ltd -AI08464,Computer Vision Engineer,83203,USD,83203,EN,FT,United States,M,United States,100,"SQL, PyTorch, Data Visualization",Associate,0,Gaming,2024-01-27,2024-02-14,1842,6.9,DataVision Ltd -AI08465,Machine Learning Researcher,188584,EUR,160296,EX,FT,Germany,M,Germany,50,"SQL, Kubernetes, Spark, Hadoop",Bachelor,17,Technology,2025-02-16,2025-03-29,1547,9.3,Algorithmic Solutions -AI08466,Data Analyst,121863,USD,121863,MI,FL,Norway,S,Norway,100,"AWS, Linux, Scala",Associate,4,Real Estate,2024-05-16,2024-06-06,2163,9.1,AI Innovations -AI08467,Computer Vision Engineer,53043,CAD,66304,EN,CT,Canada,M,Canada,0,"SQL, Tableau, Java, Kubernetes",PhD,0,Consulting,2024-10-18,2024-11-11,1508,9.8,Predictive Systems -AI08468,Deep Learning Engineer,105766,USD,105766,MI,FL,Norway,S,Norway,50,"TensorFlow, SQL, Scala, Azure",Master,2,Retail,2024-04-03,2024-04-28,1624,9.9,Quantum Computing Inc -AI08469,AI Specialist,127422,EUR,108309,SE,FT,Austria,S,Austria,0,"Statistics, Hadoop, Computer Vision",PhD,6,Healthcare,2024-08-11,2024-10-13,1126,7.4,Future Systems -AI08470,NLP Engineer,274301,CHF,246871,EX,PT,Switzerland,M,Switzerland,0,"Computer Vision, Mathematics, NLP",Bachelor,13,Technology,2024-08-25,2024-09-15,987,5.4,Quantum Computing Inc -AI08471,Machine Learning Engineer,107589,USD,107589,SE,FL,Sweden,S,Sweden,0,"Linux, Docker, Data Visualization, Git",Master,7,Real Estate,2024-07-31,2024-09-23,568,7.7,Quantum Computing Inc -AI08472,ML Ops Engineer,68293,EUR,58049,EN,PT,France,M,France,0,"Git, Scala, Deep Learning, R, Azure",PhD,1,Education,2024-05-15,2024-06-24,2321,7.3,Future Systems -AI08473,Computer Vision Engineer,257050,JPY,28275500,EX,FT,Japan,M,Japan,100,"Deep Learning, Java, Mathematics, Hadoop, PyTorch",Associate,17,Finance,2025-04-27,2025-05-23,2319,9.9,Predictive Systems -AI08474,Deep Learning Engineer,154708,USD,154708,EX,FL,Sweden,M,Hungary,50,"PyTorch, GCP, SQL",Master,13,Healthcare,2024-09-03,2024-09-25,2285,6.8,AI Innovations -AI08475,Machine Learning Researcher,80788,USD,80788,MI,FL,Sweden,S,Sweden,0,"Python, Deep Learning, Docker",PhD,3,Transportation,2024-07-25,2024-09-02,1268,6.9,Digital Transformation LLC -AI08476,Head of AI,117314,USD,117314,SE,FT,Finland,L,Finland,0,"Data Visualization, Python, SQL, Git",Associate,7,Technology,2024-07-05,2024-08-01,1317,5.2,Advanced Robotics -AI08477,Machine Learning Researcher,117690,AUD,158882,SE,CT,Australia,M,Australia,0,"PyTorch, Python, Git",PhD,8,Consulting,2025-04-13,2025-05-08,989,5.6,TechCorp Inc -AI08478,AI Architect,214411,USD,214411,EX,PT,United States,L,United States,50,"NLP, Java, Git, Kubernetes",PhD,11,Finance,2024-11-04,2024-12-13,2395,8.6,Cloud AI Solutions -AI08479,Machine Learning Researcher,155700,USD,155700,SE,PT,United States,S,United States,0,"Python, Statistics, Docker",Bachelor,7,Healthcare,2024-10-15,2024-12-27,1971,9.8,DeepTech Ventures -AI08480,Autonomous Systems Engineer,111686,EUR,94933,SE,CT,Netherlands,M,Colombia,50,"Docker, MLOps, AWS, Deep Learning",Master,7,Finance,2024-08-05,2024-10-04,1018,9.4,Algorithmic Solutions -AI08481,AI Research Scientist,65656,AUD,88636,MI,PT,Australia,S,Malaysia,50,"Computer Vision, SQL, PyTorch, Mathematics, AWS",Master,4,Finance,2024-04-29,2024-07-11,2396,5.1,DataVision Ltd -AI08482,Principal Data Scientist,85926,USD,85926,EX,CT,India,M,India,0,"Data Visualization, R, Java, MLOps",PhD,10,Automotive,2025-02-28,2025-05-12,906,7.2,AI Innovations -AI08483,AI Research Scientist,130166,GBP,97625,EX,FL,United Kingdom,S,United Kingdom,0,"Mathematics, Deep Learning, Hadoop, Docker, Java",Master,11,Education,2024-01-29,2024-03-26,1014,5.4,Machine Intelligence Group -AI08484,Autonomous Systems Engineer,132900,USD,132900,MI,FT,Denmark,L,Denmark,100,"Git, SQL, Python, NLP, Deep Learning",Bachelor,4,Finance,2024-11-06,2024-12-13,660,7.8,DeepTech Ventures -AI08485,Deep Learning Engineer,156100,EUR,132685,SE,PT,Netherlands,L,Netherlands,50,"Python, Java, MLOps",Associate,7,Technology,2024-02-12,2024-03-28,2028,5.2,DataVision Ltd -AI08486,Data Engineer,133627,USD,133627,SE,FT,Norway,M,Norway,100,"Azure, SQL, Kubernetes, Computer Vision, Statistics",Bachelor,9,Education,2024-09-26,2024-11-10,1712,6.4,Cognitive Computing -AI08487,AI Architect,88478,EUR,75206,SE,FT,France,S,France,100,"Hadoop, Linux, AWS, PyTorch, MLOps",Associate,5,Transportation,2024-04-07,2024-06-15,1496,7.5,Smart Analytics -AI08488,Machine Learning Engineer,212608,EUR,180717,EX,PT,Austria,M,Austria,50,"Azure, Computer Vision, Git, AWS, Docker",PhD,12,Telecommunications,2024-07-06,2024-08-09,519,6.5,Quantum Computing Inc -AI08489,AI Architect,58073,USD,58073,EN,FT,Israel,S,Israel,50,"Java, TensorFlow, Mathematics",Master,0,Media,2024-12-23,2025-02-28,903,9.7,DeepTech Ventures -AI08490,AI Consultant,91448,USD,91448,EN,PT,Ireland,L,Czech Republic,50,"PyTorch, MLOps, Spark",PhD,1,Automotive,2025-01-17,2025-02-16,1090,5.6,Digital Transformation LLC -AI08491,Head of AI,95900,USD,95900,MI,PT,Sweden,L,Sweden,0,"TensorFlow, Tableau, R",PhD,4,Transportation,2024-08-14,2024-09-11,647,7.6,Future Systems -AI08492,Principal Data Scientist,179096,AUD,241780,EX,FT,Australia,M,Australia,100,"Spark, SQL, PyTorch, Deep Learning",Associate,18,Transportation,2025-01-25,2025-04-08,1108,6.7,DeepTech Ventures -AI08493,AI Product Manager,59907,USD,59907,EN,FT,Israel,M,Israel,50,"Mathematics, AWS, MLOps, Java",PhD,0,Government,2024-06-23,2024-07-31,1306,9.4,DeepTech Ventures -AI08494,Research Scientist,67233,AUD,90765,EN,FT,Australia,L,Australia,0,"Python, Java, Mathematics, Spark",PhD,1,Automotive,2024-03-15,2024-05-25,943,5.8,Cognitive Computing -AI08495,Data Engineer,203674,CHF,183307,SE,FL,Switzerland,M,Switzerland,50,"Scala, Spark, Azure, Tableau, Kubernetes",Bachelor,9,Real Estate,2024-11-29,2025-01-07,2130,6,Neural Networks Co -AI08496,AI Software Engineer,113013,EUR,96061,SE,FL,Austria,M,Colombia,50,"Python, AWS, Data Visualization, NLP",Bachelor,7,Retail,2025-03-26,2025-05-24,1018,9.9,TechCorp Inc -AI08497,AI Architect,239650,AUD,323528,EX,PT,Australia,M,Australia,50,"Scala, Computer Vision, SQL, Data Visualization",Bachelor,17,Transportation,2024-03-16,2024-05-19,1926,9.1,Neural Networks Co -AI08498,Computer Vision Engineer,237855,CAD,297319,EX,CT,Canada,L,Japan,50,"NLP, Hadoop, MLOps, Scala",PhD,14,Healthcare,2025-01-09,2025-03-17,2032,8.2,DataVision Ltd -AI08499,Machine Learning Researcher,90048,EUR,76541,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Docker, TensorFlow, Scala, AWS",Bachelor,3,Transportation,2025-03-14,2025-05-14,1034,8.4,AI Innovations -AI08500,Robotics Engineer,103593,USD,103593,SE,PT,South Korea,S,South Korea,0,"Spark, Scala, Kubernetes, Hadoop, Java",Master,5,Retail,2024-08-31,2024-09-30,1593,10,Neural Networks Co -AI08501,AI Software Engineer,118005,SGD,153407,SE,PT,Singapore,S,Singapore,0,"Azure, Scala, Deep Learning",Master,9,Media,2024-11-18,2025-01-09,1227,7.1,Predictive Systems -AI08502,Machine Learning Engineer,102645,CHF,92381,EN,FT,Switzerland,M,Switzerland,0,"Hadoop, Kubernetes, Python, Linux",Associate,1,Transportation,2024-09-27,2024-11-30,1269,6,Predictive Systems -AI08503,Research Scientist,213544,AUD,288284,EX,FL,Australia,S,Australia,0,"PyTorch, SQL, MLOps, Spark",Master,16,Telecommunications,2024-05-22,2024-06-21,2216,8.2,Autonomous Tech -AI08504,Autonomous Systems Engineer,99231,EUR,84346,MI,FT,Germany,S,Germany,100,"Azure, SQL, Mathematics, Docker, AWS",Bachelor,2,Finance,2025-03-08,2025-05-04,1765,6.3,Neural Networks Co -AI08505,AI Specialist,189940,CAD,237425,EX,FL,Canada,M,Canada,50,"Azure, Hadoop, SQL, PyTorch",Bachelor,15,Energy,2024-09-09,2024-10-28,949,6.5,Quantum Computing Inc -AI08506,Head of AI,97410,USD,97410,EN,FT,Denmark,M,Denmark,0,"Python, TensorFlow, Linux, PyTorch, Deep Learning",Associate,0,Telecommunications,2025-01-18,2025-02-13,678,8.7,TechCorp Inc -AI08507,AI Specialist,115419,GBP,86564,SE,PT,United Kingdom,M,United Kingdom,0,"Python, Docker, Mathematics",PhD,9,Government,2024-11-06,2024-12-15,2448,9.3,Autonomous Tech -AI08508,Deep Learning Engineer,55421,USD,55421,EN,PT,South Korea,M,South Korea,100,"Python, R, Mathematics, TensorFlow",Bachelor,1,Education,2024-07-09,2024-08-01,2257,8.5,DeepTech Ventures -AI08509,Principal Data Scientist,174114,EUR,147997,SE,FL,Germany,L,Germany,100,"GCP, Python, MLOps",Associate,9,Education,2024-09-02,2024-10-05,1057,7.6,Cloud AI Solutions -AI08510,Data Analyst,223978,USD,223978,EX,PT,Sweden,M,Sweden,0,"R, TensorFlow, Scala, Linux, Mathematics",Master,14,Government,2024-09-15,2024-10-23,1841,7.9,Cloud AI Solutions -AI08511,Principal Data Scientist,239199,GBP,179399,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, Python, Data Visualization",PhD,16,Government,2024-09-24,2024-10-28,2389,6.4,Predictive Systems -AI08512,AI Research Scientist,82844,CHF,74560,EN,FT,Switzerland,M,United Kingdom,0,"Data Visualization, Azure, GCP, Java",PhD,1,Media,2024-06-12,2024-08-18,2214,7.1,Neural Networks Co -AI08513,AI Specialist,122977,USD,122977,SE,PT,Finland,L,Finland,50,"Python, Azure, Spark",Associate,9,Government,2025-02-09,2025-04-12,2372,7.1,Algorithmic Solutions -AI08514,Deep Learning Engineer,113326,USD,113326,MI,PT,Denmark,M,Denmark,50,"Kubernetes, Scala, Git, Azure, AWS",Associate,4,Government,2024-04-16,2024-06-18,850,5,Autonomous Tech -AI08515,Research Scientist,90965,CAD,113706,MI,CT,Canada,S,Turkey,0,"Linux, Kubernetes, Python, TensorFlow, Scala",Associate,3,Education,2025-04-19,2025-05-13,1326,6,Cloud AI Solutions -AI08516,Data Engineer,134158,USD,134158,SE,FL,Finland,L,Finland,50,"Java, SQL, Kubernetes, Hadoop",Associate,5,Media,2024-02-28,2024-04-26,670,5.9,Advanced Robotics -AI08517,Data Engineer,62279,CAD,77849,EN,PT,Canada,M,Canada,50,"Statistics, Python, Computer Vision, Spark, Kubernetes",Master,0,Retail,2024-07-16,2024-08-03,2107,6.4,Neural Networks Co -AI08518,Principal Data Scientist,201716,USD,201716,SE,CT,United States,L,Germany,100,"Spark, NLP, GCP, Tableau",Associate,6,Healthcare,2024-08-06,2024-08-29,572,9.8,AI Innovations -AI08519,AI Software Engineer,165043,USD,165043,EX,PT,Finland,L,Finland,50,"NLP, SQL, Java, GCP",Master,13,Automotive,2024-02-15,2024-03-06,1770,9.4,Predictive Systems -AI08520,NLP Engineer,95834,USD,95834,MI,FT,Denmark,M,Denmark,100,"Python, TensorFlow, Statistics, Azure, GCP",PhD,4,Healthcare,2025-01-03,2025-03-06,1278,7.7,Neural Networks Co -AI08521,AI Architect,131818,USD,131818,SE,FT,South Korea,L,Brazil,0,"Kubernetes, Python, Azure, TensorFlow",Master,5,Energy,2025-03-01,2025-04-03,1547,7,Digital Transformation LLC -AI08522,Robotics Engineer,86510,USD,86510,MI,FT,Denmark,S,South Africa,0,"Deep Learning, Azure, Python",Bachelor,2,Retail,2024-07-23,2024-08-19,2077,6.9,TechCorp Inc -AI08523,AI Software Engineer,83243,USD,83243,EN,PT,Israel,L,United Kingdom,50,"Python, Computer Vision, Linux, TensorFlow, Kubernetes",PhD,1,Gaming,2025-02-25,2025-03-11,1789,5.2,Future Systems -AI08524,AI Software Engineer,76490,CHF,68841,EN,PT,Switzerland,M,United Kingdom,50,"Scala, GCP, Python, Statistics, MLOps",Master,0,Education,2024-01-20,2024-02-08,1601,7.4,Advanced Robotics -AI08525,Head of AI,239503,EUR,203578,EX,CT,Germany,M,Germany,0,"Kubernetes, Hadoop, GCP, TensorFlow, Python",PhD,12,Finance,2025-03-04,2025-03-20,717,9.5,Machine Intelligence Group -AI08526,AI Specialist,159699,AUD,215594,SE,CT,Australia,L,Australia,50,"Scala, Tableau, Azure, Docker",PhD,5,Technology,2024-07-14,2024-08-31,1429,8.8,DeepTech Ventures -AI08527,Machine Learning Engineer,127190,SGD,165347,MI,CT,Singapore,L,Portugal,100,"Linux, NLP, Docker, Hadoop, Computer Vision",Master,2,Technology,2024-06-21,2024-08-27,1630,8.3,Digital Transformation LLC -AI08528,Autonomous Systems Engineer,61030,SGD,79339,EN,FT,Singapore,M,Singapore,50,"Statistics, TensorFlow, Scala, Python",Master,1,Automotive,2024-03-02,2024-04-16,2268,8.9,Future Systems -AI08529,Computer Vision Engineer,30719,USD,30719,MI,FT,India,S,Switzerland,0,"Python, Linux, MLOps, Statistics, Git",Master,2,Healthcare,2024-06-08,2024-06-22,1519,5.4,Neural Networks Co -AI08530,Robotics Engineer,322323,USD,322323,EX,FL,Denmark,M,Denmark,100,"PyTorch, Mathematics, Deep Learning",Bachelor,15,Government,2025-04-11,2025-06-10,1717,7.2,Predictive Systems -AI08531,Data Engineer,239858,CHF,215872,SE,FL,Switzerland,L,Switzerland,0,"TensorFlow, Docker, Linux",PhD,9,Media,2024-01-16,2024-02-12,850,6.6,Smart Analytics -AI08532,AI Specialist,90256,USD,90256,EN,FL,Ireland,L,Norway,100,"TensorFlow, GCP, Statistics, Python",PhD,1,Manufacturing,2025-01-23,2025-02-16,2232,6.8,Quantum Computing Inc -AI08533,Data Scientist,96346,GBP,72260,EN,FT,United Kingdom,L,United Kingdom,50,"MLOps, Spark, GCP",PhD,1,Transportation,2024-11-20,2025-01-15,1593,6.8,Future Systems -AI08534,AI Architect,227082,GBP,170312,EX,FT,United Kingdom,S,United Kingdom,0,"Git, Hadoop, Tableau, AWS",Associate,18,Media,2024-03-18,2024-05-08,1054,8.4,Quantum Computing Inc -AI08535,AI Consultant,174649,USD,174649,EX,FL,Sweden,S,Sweden,100,"PyTorch, GCP, Deep Learning",PhD,19,Telecommunications,2025-01-07,2025-02-01,2161,9.6,Autonomous Tech -AI08536,Principal Data Scientist,244243,EUR,207607,EX,PT,Austria,L,Austria,50,"Mathematics, SQL, Docker, TensorFlow",Master,14,Manufacturing,2025-04-17,2025-05-29,881,5.9,DataVision Ltd -AI08537,AI Software Engineer,140294,GBP,105221,SE,PT,United Kingdom,M,United Kingdom,0,"Deep Learning, Scala, MLOps",Master,6,Automotive,2025-01-23,2025-03-30,2467,6.9,AI Innovations -AI08538,AI Consultant,125410,CAD,156763,SE,CT,Canada,L,Ghana,100,"Scala, Hadoop, AWS",Master,5,Real Estate,2024-11-23,2025-01-04,2245,8.1,Cognitive Computing -AI08539,AI Specialist,102002,CAD,127503,MI,CT,Canada,M,Netherlands,0,"Linux, Mathematics, MLOps",Associate,2,Transportation,2024-02-22,2024-04-04,1720,9.7,Autonomous Tech -AI08540,Machine Learning Researcher,70722,AUD,95475,EN,CT,Australia,M,Belgium,100,"Mathematics, Linux, AWS, Docker, SQL",Master,1,Manufacturing,2025-04-25,2025-05-17,1856,8.8,Machine Intelligence Group -AI08541,AI Product Manager,92261,GBP,69196,MI,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, NLP",PhD,3,Government,2024-01-10,2024-01-29,2021,6.4,Quantum Computing Inc -AI08542,AI Architect,84465,CHF,76019,EN,PT,Switzerland,L,Switzerland,100,"Data Visualization, Spark, Deep Learning",Associate,0,Consulting,2025-01-02,2025-02-15,2374,5,Future Systems -AI08543,Machine Learning Engineer,73370,EUR,62365,EN,PT,Germany,M,Germany,50,"Linux, Docker, Kubernetes",PhD,0,Technology,2024-04-21,2024-06-05,2319,6.5,Algorithmic Solutions -AI08544,Data Scientist,125995,EUR,107096,EX,PT,France,S,United Kingdom,0,"SQL, Spark, PyTorch, Hadoop",PhD,12,Transportation,2024-03-21,2024-04-30,1217,9.4,DataVision Ltd -AI08545,Machine Learning Researcher,109740,SGD,142662,MI,CT,Singapore,L,Singapore,100,"Java, Deep Learning, TensorFlow, Statistics",Bachelor,4,Education,2024-02-25,2024-03-14,1024,9.7,Predictive Systems -AI08546,Principal Data Scientist,126186,USD,126186,MI,FL,Norway,S,Norway,50,"Git, Linux, Python, Kubernetes",PhD,3,Energy,2024-04-12,2024-06-04,2446,7.8,DeepTech Ventures -AI08547,AI Product Manager,114618,EUR,97425,SE,FL,Austria,S,Austria,50,"Git, AWS, Azure, Statistics, Scala",Master,8,Manufacturing,2024-11-01,2025-01-09,543,9.3,Advanced Robotics -AI08548,AI Consultant,194158,EUR,165034,EX,PT,France,L,France,100,"Linux, Azure, TensorFlow, Git",PhD,15,Media,2024-09-14,2024-10-18,971,9.5,Future Systems -AI08549,Machine Learning Engineer,68896,USD,68896,EN,CT,Ireland,L,Ireland,0,"TensorFlow, PyTorch, AWS, Statistics",Associate,1,Energy,2024-12-28,2025-01-19,903,6.7,TechCorp Inc -AI08550,AI Product Manager,179602,JPY,19756220,SE,PT,Japan,L,Japan,50,"Docker, Python, NLP, MLOps",Bachelor,8,Gaming,2024-10-22,2024-11-24,2386,7.6,Predictive Systems -AI08551,Machine Learning Engineer,197099,EUR,167534,EX,CT,Netherlands,S,Netherlands,0,"SQL, Spark, Python, R",PhD,17,Finance,2024-10-01,2024-12-09,874,6.6,Autonomous Tech -AI08552,AI Architect,63579,USD,63579,MI,FT,Israel,S,Israel,50,"Hadoop, Linux, GCP, Tableau, Mathematics",Master,3,Gaming,2024-03-16,2024-05-07,2455,7.2,Algorithmic Solutions -AI08553,Machine Learning Researcher,141152,USD,141152,EX,CT,South Korea,S,South Korea,0,"Spark, Linux, Python, Azure",Master,16,Government,2024-10-01,2024-12-12,1492,5.1,Machine Intelligence Group -AI08554,NLP Engineer,96134,SGD,124974,MI,PT,Singapore,M,Singapore,0,"TensorFlow, Mathematics, Data Visualization",Associate,4,Transportation,2024-09-23,2024-11-17,1025,9.4,AI Innovations -AI08555,Research Scientist,127024,GBP,95268,SE,FT,United Kingdom,L,United Kingdom,100,"R, SQL, MLOps, Statistics, Hadoop",Master,9,Energy,2024-05-14,2024-06-30,1870,6.8,Cognitive Computing -AI08556,Machine Learning Researcher,145838,USD,145838,SE,FL,Denmark,M,Denmark,50,"Docker, NLP, Kubernetes, Statistics, Mathematics",Associate,7,Consulting,2024-02-26,2024-03-29,1533,5.2,DataVision Ltd -AI08557,Robotics Engineer,130985,EUR,111337,SE,FL,Germany,M,Germany,50,"Data Visualization, Linux, Python, TensorFlow, AWS",Master,5,Telecommunications,2024-12-29,2025-02-05,2324,6.5,Cloud AI Solutions -AI08558,Robotics Engineer,154058,EUR,130949,SE,PT,France,L,France,0,"Python, TensorFlow, MLOps, Hadoop",PhD,5,Finance,2024-02-08,2024-03-19,2052,5.5,Smart Analytics -AI08559,Machine Learning Researcher,97591,USD,97591,MI,PT,Norway,S,Russia,0,"R, Git, Kubernetes, Computer Vision",Master,2,Government,2025-02-26,2025-04-24,1877,6.9,AI Innovations -AI08560,Machine Learning Engineer,271305,SGD,352697,EX,FL,Singapore,L,New Zealand,100,"Git, PyTorch, AWS, Data Visualization",Associate,19,Transportation,2024-10-04,2024-10-22,638,9.3,Algorithmic Solutions -AI08561,ML Ops Engineer,98409,EUR,83648,MI,CT,Netherlands,L,Netherlands,100,"TensorFlow, MLOps, Scala",PhD,3,Consulting,2024-01-05,2024-02-14,1500,7.7,Machine Intelligence Group -AI08562,AI Research Scientist,148798,JPY,16367780,SE,CT,Japan,L,Japan,100,"Scala, PyTorch, AWS, TensorFlow",Associate,6,Government,2024-11-21,2024-12-31,747,8.3,Cognitive Computing -AI08563,AI Product Manager,279602,GBP,209702,EX,FL,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, Statistics, Docker, Scala",Associate,16,Education,2025-01-23,2025-02-18,1232,7.6,AI Innovations -AI08564,NLP Engineer,95686,SGD,124392,MI,CT,Singapore,S,Luxembourg,50,"Tableau, TensorFlow, Java, Kubernetes",Bachelor,3,Healthcare,2024-11-18,2024-12-10,582,9.9,Future Systems -AI08565,AI Consultant,64322,USD,64322,EN,FT,Israel,M,Israel,0,"NLP, GCP, Docker",PhD,1,Telecommunications,2025-02-16,2025-04-22,2144,5.5,Smart Analytics -AI08566,NLP Engineer,136594,USD,136594,MI,PT,Denmark,M,Nigeria,0,"Java, Computer Vision, Python, AWS, TensorFlow",PhD,2,Energy,2024-05-03,2024-05-29,1479,6.7,AI Innovations -AI08567,Robotics Engineer,82693,EUR,70289,EN,FL,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure",PhD,0,Energy,2025-04-13,2025-05-14,1302,8.8,DataVision Ltd -AI08568,AI Specialist,153976,USD,153976,EX,CT,United States,S,Argentina,50,"Scala, R, Tableau, TensorFlow, Docker",PhD,19,Retail,2024-09-18,2024-10-19,591,6.5,Autonomous Tech -AI08569,Data Scientist,139600,USD,139600,SE,FL,Norway,M,Japan,0,"GCP, Kubernetes, SQL, Computer Vision",Master,6,Media,2024-12-20,2025-02-13,1575,5.5,Cognitive Computing -AI08570,Robotics Engineer,249090,GBP,186818,EX,FT,United Kingdom,L,Poland,50,"Java, Python, Deep Learning",PhD,17,Energy,2024-04-24,2024-06-13,1346,5.6,Cloud AI Solutions -AI08571,Data Analyst,40276,USD,40276,SE,FT,India,S,India,100,"Computer Vision, Linux, GCP, Statistics",Associate,9,Consulting,2024-11-09,2025-01-19,1140,7.5,Digital Transformation LLC -AI08572,Robotics Engineer,72904,USD,72904,MI,FL,Finland,S,Finland,100,"Python, Java, Docker",Master,4,Healthcare,2024-04-10,2024-05-07,920,5,Quantum Computing Inc -AI08573,Research Scientist,64042,SGD,83255,EN,CT,Singapore,S,Singapore,100,"Linux, SQL, Git, MLOps, Hadoop",Bachelor,1,Consulting,2024-10-11,2024-11-12,1592,8.3,DataVision Ltd -AI08574,Machine Learning Researcher,305717,JPY,33628870,EX,PT,Japan,L,Luxembourg,50,"Kubernetes, Git, GCP, NLP, SQL",PhD,15,Technology,2024-08-03,2024-09-04,1529,9.7,DeepTech Ventures -AI08575,Research Scientist,85542,USD,85542,EN,FL,Norway,S,Norway,100,"TensorFlow, Tableau, Python",Bachelor,0,Gaming,2024-07-12,2024-08-11,620,8.6,Digital Transformation LLC -AI08576,Computer Vision Engineer,62229,USD,62229,MI,FL,South Korea,M,Ukraine,100,"Scala, R, NLP, Linux, Deep Learning",Associate,2,Manufacturing,2025-01-20,2025-03-03,2251,6.6,Predictive Systems -AI08577,Data Scientist,183034,CAD,228793,EX,FT,Canada,S,Canada,100,"Azure, SQL, Scala, Data Visualization, Git",Master,15,Technology,2024-04-02,2024-05-25,1927,7.5,AI Innovations -AI08578,Robotics Engineer,77261,CAD,96576,EN,FT,Canada,L,Canada,100,"Hadoop, PyTorch, Java",PhD,0,Technology,2025-02-21,2025-03-10,1539,7.2,Quantum Computing Inc -AI08579,AI Software Engineer,101020,USD,101020,MI,CT,Ireland,L,Thailand,0,"R, Tableau, Azure",Associate,2,Healthcare,2024-09-04,2024-11-16,661,6.9,Predictive Systems -AI08580,AI Consultant,76948,USD,76948,MI,PT,Finland,S,Hungary,100,"Hadoop, Git, PyTorch, AWS, Linux",Bachelor,4,Consulting,2024-02-28,2024-04-01,1102,7.8,Cognitive Computing -AI08581,AI Specialist,81536,USD,81536,EX,FT,China,M,China,0,"Kubernetes, Python, Azure, Spark",Bachelor,13,Gaming,2024-11-02,2024-12-12,2087,5.4,AI Innovations -AI08582,Principal Data Scientist,95198,USD,95198,SE,FL,Finland,S,Finland,0,"Git, R, Tableau",Bachelor,9,Consulting,2024-03-09,2024-04-10,1619,6.4,Predictive Systems -AI08583,AI Consultant,164093,GBP,123070,SE,PT,United Kingdom,L,Ghana,50,"TensorFlow, AWS, Tableau, Kubernetes, NLP",Master,9,Media,2024-04-02,2024-05-23,2074,9.8,DataVision Ltd -AI08584,Research Scientist,140767,USD,140767,SE,CT,United States,L,Hungary,0,"Tableau, Python, TensorFlow, PyTorch",Bachelor,8,Automotive,2024-08-11,2024-10-16,1142,9.1,Algorithmic Solutions -AI08585,Machine Learning Researcher,102336,USD,102336,EX,FL,China,L,China,50,"PyTorch, Hadoop, Git",Master,19,Consulting,2025-04-27,2025-05-11,662,5.8,Advanced Robotics -AI08586,Research Scientist,58994,EUR,50145,EN,FT,Austria,L,Austria,50,"Spark, Linux, Git, Azure",Master,0,Automotive,2025-02-16,2025-03-15,1940,7,DeepTech Ventures -AI08587,NLP Engineer,51117,AUD,69008,EN,FL,Australia,M,Australia,50,"Python, Java, MLOps",Master,0,Real Estate,2024-09-07,2024-11-02,2071,7,Machine Intelligence Group -AI08588,Data Scientist,82013,USD,82013,EN,FT,United States,L,United States,100,"SQL, Statistics, PyTorch, R",PhD,1,Real Estate,2024-06-09,2024-07-24,1950,8.5,AI Innovations -AI08589,AI Product Manager,204881,USD,204881,EX,PT,Finland,S,Finland,50,"Python, Spark, NLP",Master,10,Manufacturing,2024-01-20,2024-02-05,936,8.9,Future Systems -AI08590,AI Software Engineer,78751,USD,78751,EX,CT,India,M,India,100,"NLP, GCP, Spark, Kubernetes",Bachelor,13,Retail,2024-12-20,2025-01-12,1019,6.5,AI Innovations -AI08591,Head of AI,130461,GBP,97846,MI,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Kubernetes, SQL, GCP",PhD,3,Education,2024-08-14,2024-09-10,1707,9,Digital Transformation LLC -AI08592,AI Product Manager,83311,JPY,9164210,MI,PT,Japan,S,Japan,0,"Docker, Spark, Data Visualization, Git, Python",PhD,4,Consulting,2024-01-16,2024-02-17,1419,5.3,AI Innovations -AI08593,AI Research Scientist,57136,GBP,42852,EN,PT,United Kingdom,M,Sweden,100,"AWS, R, SQL, Deep Learning",Associate,0,Retail,2024-02-06,2024-02-25,2040,8.5,TechCorp Inc -AI08594,Head of AI,109478,USD,109478,MI,CT,Sweden,L,Sweden,0,"GCP, Azure, Tableau, Computer Vision, Git",Bachelor,2,Energy,2024-05-12,2024-07-03,1628,9.1,Autonomous Tech -AI08595,NLP Engineer,86990,USD,86990,MI,PT,Israel,L,Romania,0,"TensorFlow, GCP, NLP, Spark, Scala",Associate,3,Consulting,2024-11-05,2024-12-05,2421,6.1,Predictive Systems -AI08596,Machine Learning Engineer,241562,USD,241562,EX,CT,Ireland,M,Ireland,50,"R, Python, Mathematics, NLP",PhD,11,Government,2025-03-21,2025-05-28,1893,5.8,DataVision Ltd -AI08597,Principal Data Scientist,21704,USD,21704,EN,PT,India,M,India,50,"GCP, Deep Learning, Tableau",Associate,1,Telecommunications,2024-10-18,2024-12-25,1489,7.5,Autonomous Tech -AI08598,ML Ops Engineer,88065,EUR,74855,MI,FT,Netherlands,S,Netherlands,50,"Kubernetes, PyTorch, Azure, GCP, MLOps",Bachelor,3,Retail,2025-04-19,2025-05-13,779,5.9,Predictive Systems -AI08599,Research Scientist,52913,USD,52913,MI,PT,China,L,Ghana,0,"Data Visualization, Spark, Kubernetes, Java, Statistics",Associate,2,Education,2024-05-22,2024-06-05,1036,7.7,DataVision Ltd -AI08600,Robotics Engineer,60550,EUR,51468,EN,CT,Netherlands,M,Poland,0,"SQL, Statistics, Spark, Git",Bachelor,1,Energy,2025-03-23,2025-05-17,1973,6.4,Neural Networks Co -AI08601,Computer Vision Engineer,57164,USD,57164,EN,FT,Israel,L,Israel,50,"Azure, Java, Git, Computer Vision, Python",Master,1,Government,2024-05-08,2024-06-05,1916,9.1,DeepTech Ventures -AI08602,Principal Data Scientist,196044,USD,196044,EX,FL,Finland,L,Finland,100,"Java, Python, R, Docker, AWS",Master,19,Automotive,2025-01-13,2025-03-06,1055,6.4,Future Systems -AI08603,Deep Learning Engineer,205349,CAD,256686,EX,CT,Canada,M,Canada,50,"Kubernetes, NLP, Statistics, Deep Learning",Bachelor,10,Finance,2025-02-13,2025-04-19,1523,7.2,Smart Analytics -AI08604,Machine Learning Engineer,141845,CHF,127661,MI,FL,Switzerland,L,Switzerland,50,"AWS, Statistics, Tableau",PhD,2,Real Estate,2024-07-30,2024-09-23,2215,5.3,Quantum Computing Inc -AI08605,AI Specialist,111688,USD,111688,MI,PT,United States,L,Vietnam,50,"Git, Kubernetes, Statistics, Tableau",Bachelor,4,Media,2024-06-12,2024-08-17,1284,6.3,DeepTech Ventures -AI08606,Head of AI,68031,JPY,7483410,EN,FL,Japan,M,Japan,0,"AWS, Linux, Python, TensorFlow, Java",Bachelor,1,Consulting,2024-11-06,2025-01-07,2344,10,Machine Intelligence Group -AI08607,AI Product Manager,107527,CHF,96774,EN,FT,Switzerland,L,Switzerland,100,"Hadoop, MLOps, TensorFlow",PhD,1,Retail,2024-03-14,2024-05-09,2383,6.7,Advanced Robotics -AI08608,AI Consultant,181374,EUR,154168,EX,FL,Germany,M,Germany,50,"Hadoop, GCP, PyTorch, SQL, Linux",Master,13,Energy,2025-03-02,2025-04-14,865,7.3,Algorithmic Solutions -AI08609,Data Engineer,118961,EUR,101117,SE,PT,Germany,S,Portugal,0,"Kubernetes, AWS, R",PhD,8,Retail,2024-09-04,2024-11-16,1248,9.6,Algorithmic Solutions -AI08610,ML Ops Engineer,52835,USD,52835,MI,FT,China,L,China,50,"Spark, Kubernetes, Deep Learning",Bachelor,4,Education,2025-04-14,2025-05-09,1169,8.6,Smart Analytics -AI08611,Machine Learning Engineer,70673,USD,70673,SE,FT,China,M,China,50,"Java, Kubernetes, Tableau",Master,7,Telecommunications,2024-04-28,2024-05-17,1371,9.1,Quantum Computing Inc -AI08612,ML Ops Engineer,94570,AUD,127670,SE,CT,Australia,S,Australia,0,"Python, TensorFlow, Docker, R, Computer Vision",PhD,8,Transportation,2024-09-09,2024-10-10,1297,5.5,Digital Transformation LLC -AI08613,AI Research Scientist,64693,USD,64693,EN,FT,Israel,L,Israel,0,"AWS, MLOps, GCP, Mathematics",Bachelor,0,Consulting,2024-05-17,2024-07-21,2215,6.2,Quantum Computing Inc -AI08614,Head of AI,191853,USD,191853,SE,PT,Denmark,M,Denmark,0,"Scala, Git, Kubernetes, PyTorch, Python",PhD,8,Media,2025-01-30,2025-03-22,900,7.4,Autonomous Tech -AI08615,Data Analyst,114269,SGD,148550,SE,FT,Singapore,M,Singapore,0,"AWS, Statistics, NLP, Tableau",Bachelor,9,Energy,2024-12-16,2025-01-29,2116,9,Machine Intelligence Group -AI08616,Machine Learning Researcher,269818,JPY,29679980,EX,PT,Japan,M,Japan,50,"Computer Vision, PyTorch, Python, Azure, AWS",Bachelor,15,Real Estate,2024-02-05,2024-03-07,935,9.8,TechCorp Inc -AI08617,AI Software Engineer,120069,USD,120069,SE,CT,Norway,S,Norway,50,"AWS, R, Statistics, PyTorch",PhD,5,Manufacturing,2024-07-10,2024-08-18,1887,7.3,Cognitive Computing -AI08618,Data Analyst,86504,USD,86504,MI,FT,South Korea,M,South Korea,0,"Python, Hadoop, Git, TensorFlow",Bachelor,3,Media,2025-01-13,2025-03-02,2433,6.4,Future Systems -AI08619,Machine Learning Researcher,120570,USD,120570,EX,CT,China,L,China,50,"Python, SQL, AWS, Computer Vision",Bachelor,17,Telecommunications,2024-02-11,2024-03-10,1747,5.2,DeepTech Ventures -AI08620,Data Scientist,184942,USD,184942,EX,CT,Ireland,L,Latvia,50,"Computer Vision, Docker, R",Master,17,Automotive,2024-07-09,2024-08-24,600,9.6,AI Innovations -AI08621,Data Scientist,89220,EUR,75837,EN,PT,Germany,L,Germany,50,"Linux, Git, Computer Vision, Hadoop, Java",PhD,0,Real Estate,2024-03-08,2024-04-13,1551,5.3,Future Systems -AI08622,AI Product Manager,134492,JPY,14794120,SE,FL,Japan,M,Japan,100,"R, Statistics, NLP, Spark",Associate,8,Transportation,2024-10-31,2024-12-23,2443,8.6,DeepTech Ventures -AI08623,Machine Learning Researcher,137903,EUR,117218,EX,FL,France,S,France,50,"Java, Hadoop, NLP",Associate,16,Manufacturing,2024-11-10,2024-12-10,796,7.2,Smart Analytics -AI08624,Deep Learning Engineer,139031,GBP,104273,EX,FT,United Kingdom,S,Norway,0,"Linux, Azure, Mathematics, SQL, Hadoop",PhD,16,Energy,2024-12-15,2025-01-03,1916,5.9,Autonomous Tech -AI08625,AI Software Engineer,202153,USD,202153,EX,FT,South Korea,L,South Korea,50,"Scala, Computer Vision, Linux, Python, Kubernetes",Associate,17,Consulting,2025-03-05,2025-04-09,1250,6.2,DeepTech Ventures -AI08626,AI Architect,71668,USD,71668,MI,PT,Israel,S,South Africa,100,"Kubernetes, Git, R, PyTorch",Associate,3,Retail,2025-01-19,2025-04-02,1593,6,Cloud AI Solutions -AI08627,AI Product Manager,89404,USD,89404,EN,CT,Denmark,L,Denmark,0,"PyTorch, Tableau, TensorFlow",Bachelor,0,Finance,2024-11-04,2024-12-09,1637,8,DeepTech Ventures -AI08628,Head of AI,145615,USD,145615,SE,FT,Sweden,M,Sweden,0,"Linux, MLOps, Data Visualization, Python, NLP",Associate,8,Consulting,2024-10-10,2024-11-09,2127,9.5,Cloud AI Solutions -AI08629,Data Analyst,207813,USD,207813,EX,FL,Finland,L,Finland,0,"R, Linux, Deep Learning",Associate,13,Transportation,2024-12-30,2025-02-17,1223,5.3,Cloud AI Solutions -AI08630,AI Architect,142528,EUR,121149,SE,FT,Netherlands,M,Netherlands,50,"Git, Scala, Statistics, MLOps, SQL",Master,8,Technology,2025-03-21,2025-05-22,1866,6.3,Autonomous Tech -AI08631,AI Specialist,68097,USD,68097,MI,FT,Finland,M,Finland,50,"Kubernetes, Python, GCP",Bachelor,3,Manufacturing,2025-03-11,2025-04-08,1548,7.5,Machine Intelligence Group -AI08632,Data Engineer,224311,SGD,291604,EX,CT,Singapore,S,Singapore,50,"Java, Linux, Mathematics, Azure, Scala",Associate,17,Transportation,2025-01-16,2025-01-30,659,8.8,AI Innovations -AI08633,Autonomous Systems Engineer,114501,CAD,143126,SE,FT,Canada,L,Canada,50,"Tableau, PyTorch, Git, Python, Linux",Bachelor,7,Consulting,2024-10-26,2024-11-11,880,6.1,Autonomous Tech -AI08634,NLP Engineer,65825,USD,65825,SE,FL,China,L,China,0,"AWS, Java, Azure",Bachelor,5,Finance,2024-10-04,2024-10-24,1602,9.2,Autonomous Tech -AI08635,AI Specialist,196121,CAD,245151,EX,PT,Canada,S,Canada,0,"Spark, Kubernetes, GCP, Tableau",Associate,18,Education,2025-04-30,2025-06-18,954,7.6,AI Innovations -AI08636,Principal Data Scientist,94824,USD,94824,EN,PT,United States,M,United States,100,"Hadoop, Linux, Kubernetes",Associate,1,Manufacturing,2024-01-02,2024-03-03,922,5,Machine Intelligence Group -AI08637,AI Software Engineer,48808,USD,48808,SE,PT,China,M,China,100,"Linux, Docker, R, Mathematics",Master,8,Government,2024-04-09,2024-06-16,2216,8.1,Autonomous Tech -AI08638,Robotics Engineer,119252,EUR,101364,SE,CT,Netherlands,M,Finland,0,"PyTorch, TensorFlow, Mathematics, Java, Spark",Master,5,Finance,2024-11-28,2025-02-05,1993,7.6,Machine Intelligence Group -AI08639,AI Architect,77771,CHF,69994,EN,FL,Switzerland,M,Switzerland,50,"Scala, Tableau, Deep Learning",Master,0,Education,2024-02-11,2024-03-05,1677,8.1,Future Systems -AI08640,ML Ops Engineer,106474,USD,106474,SE,CT,Ireland,S,Ireland,0,"PyTorch, SQL, AWS, Docker",Master,6,Consulting,2024-09-22,2024-10-06,1764,6.9,Algorithmic Solutions -AI08641,Computer Vision Engineer,233835,AUD,315677,EX,CT,Australia,M,Australia,100,"R, GCP, Mathematics",Associate,17,Government,2024-12-30,2025-02-18,2214,8.9,Future Systems -AI08642,Data Analyst,95754,SGD,124480,MI,CT,Singapore,M,Singapore,100,"Tableau, TensorFlow, NLP, SQL",Bachelor,2,Telecommunications,2024-07-21,2024-09-24,1939,8.9,AI Innovations -AI08643,Data Engineer,111708,CAD,139635,SE,CT,Canada,S,Russia,0,"Python, TensorFlow, Kubernetes, Hadoop, Docker",Bachelor,5,Government,2024-09-08,2024-11-12,2019,5.3,Quantum Computing Inc -AI08644,Principal Data Scientist,263271,JPY,28959810,EX,CT,Japan,M,Kenya,100,"Kubernetes, TensorFlow, Mathematics, AWS, PyTorch",Bachelor,14,Healthcare,2024-01-07,2024-03-11,1071,9.6,Quantum Computing Inc -AI08645,Robotics Engineer,201498,USD,201498,SE,PT,Norway,L,Norway,100,"Spark, Java, Docker, GCP, Statistics",Master,6,Telecommunications,2024-03-04,2024-04-17,1970,8.9,Cognitive Computing -AI08646,Machine Learning Researcher,98345,USD,98345,EN,PT,Norway,M,Norway,100,"R, Linux, Java",Bachelor,0,Automotive,2024-11-01,2024-11-27,1920,5.9,TechCorp Inc -AI08647,Data Engineer,47321,USD,47321,MI,PT,China,M,China,50,"GCP, Java, Tableau, Statistics",Associate,4,Manufacturing,2024-03-11,2024-04-06,1151,8.8,DataVision Ltd -AI08648,Data Analyst,76662,USD,76662,MI,FT,South Korea,S,Romania,100,"Statistics, Python, NLP",Associate,3,Retail,2025-04-06,2025-05-16,1934,9.5,Quantum Computing Inc -AI08649,Data Scientist,135115,USD,135115,SE,CT,Israel,L,Egypt,100,"Docker, Spark, R, MLOps, Azure",Associate,6,Manufacturing,2024-06-24,2024-08-29,1019,5.6,Cloud AI Solutions -AI08650,Computer Vision Engineer,95343,EUR,81042,MI,PT,France,M,France,100,"SQL, GCP, Docker, Computer Vision, Hadoop",Master,4,Technology,2024-07-08,2024-08-12,2321,7.6,TechCorp Inc -AI08651,Principal Data Scientist,19877,USD,19877,EN,FL,India,S,India,0,"R, Python, Computer Vision",PhD,1,Government,2024-10-25,2024-12-23,1853,6.7,Machine Intelligence Group -AI08652,AI Consultant,120340,SGD,156442,SE,FL,Singapore,M,Singapore,50,"Linux, Java, Python, Kubernetes, Deep Learning",Bachelor,8,Automotive,2024-07-20,2024-08-24,2341,9.6,Autonomous Tech -AI08653,Data Analyst,105495,SGD,137144,SE,CT,Singapore,S,Singapore,0,"Java, GCP, AWS",PhD,8,Transportation,2024-03-04,2024-05-16,715,7.8,Machine Intelligence Group -AI08654,Data Scientist,23760,USD,23760,EN,FL,China,S,China,50,"TensorFlow, Linux, Computer Vision",Associate,0,Telecommunications,2024-09-05,2024-10-10,2121,8.5,Neural Networks Co -AI08655,Research Scientist,81420,JPY,8956200,EN,FT,Japan,M,Japan,50,"PyTorch, Tableau, Scala",Bachelor,1,Technology,2024-08-07,2024-10-08,2240,6.8,Autonomous Tech -AI08656,Machine Learning Researcher,117907,SGD,153279,SE,PT,Singapore,M,Singapore,100,"Python, Git, R, TensorFlow, Statistics",Associate,6,Government,2024-02-08,2024-04-14,2148,7.7,Future Systems -AI08657,Machine Learning Engineer,96703,JPY,10637330,MI,FT,Japan,S,Japan,100,"Azure, Java, GCP, TensorFlow, MLOps",Associate,2,Healthcare,2025-04-06,2025-06-15,1390,8.5,Cloud AI Solutions -AI08658,Data Analyst,64544,AUD,87134,EN,CT,Australia,S,Australia,100,"SQL, Java, Mathematics, PyTorch",Bachelor,1,Transportation,2025-03-27,2025-04-17,1219,5.6,TechCorp Inc -AI08659,Principal Data Scientist,113782,JPY,12516020,SE,FL,Japan,M,Japan,100,"Scala, Azure, PyTorch, SQL",Bachelor,5,Media,2024-04-05,2024-05-10,1092,9.9,Predictive Systems -AI08660,Machine Learning Researcher,128270,USD,128270,MI,FT,United States,L,United States,100,"R, Git, Python, NLP, TensorFlow",Master,2,Telecommunications,2025-02-20,2025-03-25,2100,5.6,Machine Intelligence Group -AI08661,Head of AI,65592,USD,65592,MI,FL,Sweden,S,Sweden,100,"Python, Git, Scala",Master,3,Media,2024-03-04,2024-04-14,2111,9.3,Advanced Robotics -AI08662,AI Software Engineer,54617,CAD,68271,EN,FT,Canada,M,Canada,100,"MLOps, Java, Python",Bachelor,0,Manufacturing,2024-02-12,2024-04-24,993,8.7,Predictive Systems -AI08663,AI Consultant,82192,USD,82192,MI,FT,South Korea,M,Italy,50,"Kubernetes, Scala, Spark",Associate,2,Automotive,2024-03-05,2024-04-18,994,6.1,Advanced Robotics -AI08664,Principal Data Scientist,81981,EUR,69684,MI,FT,France,L,France,50,"Python, NLP, TensorFlow, Git, Java",Master,4,Media,2024-07-08,2024-09-08,1850,6.7,Neural Networks Co -AI08665,AI Research Scientist,76034,EUR,64629,MI,PT,Austria,S,Austria,0,"R, Computer Vision, Python, Kubernetes, MLOps",Bachelor,3,Manufacturing,2024-06-06,2024-07-30,1652,8,Future Systems -AI08666,AI Architect,24952,USD,24952,EN,CT,India,M,India,50,"Linux, PyTorch, Python, Hadoop",Bachelor,0,Manufacturing,2025-01-16,2025-03-24,2290,9.1,Cloud AI Solutions -AI08667,Data Engineer,44314,USD,44314,MI,CT,China,S,Switzerland,0,"PyTorch, GCP, SQL, Data Visualization, Tableau",PhD,2,Telecommunications,2024-09-05,2024-11-17,1117,7.4,Predictive Systems -AI08668,AI Product Manager,160046,CAD,200058,EX,CT,Canada,L,Canada,0,"Tableau, R, Git, Data Visualization, Computer Vision",Associate,10,Technology,2025-02-26,2025-04-08,1302,6.3,DataVision Ltd -AI08669,Data Scientist,224937,EUR,191196,EX,FL,Netherlands,M,China,0,"SQL, PyTorch, Mathematics",Master,13,Real Estate,2025-04-27,2025-06-14,2360,7.6,Predictive Systems -AI08670,Deep Learning Engineer,69057,SGD,89774,MI,PT,Singapore,S,Singapore,50,"R, AWS, Azure, Deep Learning",Associate,3,Technology,2024-01-25,2024-02-10,991,6.4,Cognitive Computing -AI08671,AI Consultant,65525,EUR,55696,EN,FL,Germany,M,Germany,100,"Hadoop, SQL, Computer Vision",PhD,0,Technology,2024-12-31,2025-01-27,1022,5.6,AI Innovations -AI08672,Data Engineer,231770,CHF,208593,EX,FT,Switzerland,M,Switzerland,0,"Kubernetes, Spark, GCP",PhD,10,Telecommunications,2024-03-09,2024-03-24,946,6.2,Quantum Computing Inc -AI08673,Autonomous Systems Engineer,189743,GBP,142307,EX,CT,United Kingdom,S,United Kingdom,0,"Python, Linux, TensorFlow, Data Visualization",Bachelor,11,Education,2024-11-11,2025-01-04,1985,7.6,DeepTech Ventures -AI08674,AI Consultant,84046,CAD,105058,MI,CT,Canada,L,Brazil,50,"NLP, GCP, Python, Tableau",Associate,2,Finance,2024-11-03,2025-01-11,1018,5.7,DeepTech Ventures -AI08675,Robotics Engineer,58018,USD,58018,SE,FL,China,M,China,100,"Computer Vision, Hadoop, Python",Associate,7,Media,2024-02-15,2024-03-11,2304,8,Neural Networks Co -AI08676,Head of AI,82096,USD,82096,EX,FT,China,L,Finland,50,"Git, Linux, Hadoop, GCP, Kubernetes",Associate,10,Finance,2025-02-10,2025-03-14,2277,5.1,Advanced Robotics -AI08677,AI Research Scientist,228962,EUR,194618,EX,FL,France,L,France,50,"Hadoop, SQL, Python",PhD,14,Energy,2024-10-15,2024-12-24,601,9.5,Quantum Computing Inc -AI08678,Head of AI,59789,EUR,50821,EN,CT,Netherlands,S,Netherlands,100,"R, Hadoop, Kubernetes, GCP",PhD,0,Finance,2024-10-26,2024-12-13,1908,7.9,Autonomous Tech -AI08679,AI Product Manager,65661,JPY,7222710,EN,CT,Japan,S,Japan,0,"Spark, Linux, PyTorch",Bachelor,0,Education,2024-09-27,2024-11-06,1374,6.3,Advanced Robotics -AI08680,Head of AI,192079,USD,192079,EX,FT,South Korea,L,South Korea,0,"Spark, Java, TensorFlow, Statistics, AWS",PhD,11,Telecommunications,2025-01-02,2025-03-05,2192,5.7,Predictive Systems -AI08681,Computer Vision Engineer,98259,EUR,83520,MI,FL,Germany,S,Germany,100,"Java, Spark, Mathematics, R",Associate,3,Telecommunications,2025-01-14,2025-03-21,639,8.4,Algorithmic Solutions -AI08682,Data Analyst,152980,SGD,198874,EX,FL,Singapore,M,Singapore,100,"R, Tableau, SQL",Associate,18,Transportation,2024-04-16,2024-05-07,1446,7,Autonomous Tech -AI08683,AI Product Manager,52672,EUR,44771,EN,FL,Austria,S,Austria,0,"R, Statistics, Data Visualization",Bachelor,0,Manufacturing,2024-07-12,2024-08-21,2084,9.1,Algorithmic Solutions -AI08684,ML Ops Engineer,22389,USD,22389,EN,FL,India,S,Luxembourg,0,"Mathematics, Tableau, GCP",Bachelor,1,Manufacturing,2024-10-17,2024-11-01,2404,9.6,Quantum Computing Inc -AI08685,ML Ops Engineer,62477,AUD,84344,EN,CT,Australia,M,Australia,0,"Hadoop, Git, Python",Master,1,Manufacturing,2024-02-07,2024-02-25,797,8.8,DataVision Ltd -AI08686,Principal Data Scientist,76545,USD,76545,MI,CT,Ireland,M,Ireland,100,"PyTorch, NLP, Java, Mathematics",Bachelor,3,Healthcare,2024-12-09,2025-02-01,1782,6.9,Cognitive Computing -AI08687,AI Software Engineer,86947,USD,86947,SE,FL,South Korea,M,Canada,100,"Kubernetes, TensorFlow, Python",PhD,6,Energy,2024-08-24,2024-10-19,976,6.5,Cloud AI Solutions -AI08688,Deep Learning Engineer,83441,GBP,62581,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, Python, TensorFlow, Git, PyTorch",Master,4,Media,2024-01-16,2024-03-19,555,7.4,Algorithmic Solutions -AI08689,AI Architect,300340,GBP,225255,EX,FT,United Kingdom,L,United Kingdom,100,"Git, Kubernetes, R, NLP, Deep Learning",Master,11,Real Estate,2025-03-16,2025-04-09,2004,6.7,Predictive Systems -AI08690,AI Research Scientist,149207,USD,149207,SE,CT,United States,S,United States,100,"Statistics, Azure, Computer Vision",Bachelor,6,Consulting,2024-01-12,2024-03-04,656,5.1,AI Innovations -AI08691,Principal Data Scientist,160666,EUR,136566,SE,PT,Netherlands,L,Nigeria,0,"GCP, Scala, Data Visualization, Spark, Mathematics",Master,9,Energy,2025-01-08,2025-01-30,2146,5.6,Algorithmic Solutions -AI08692,Machine Learning Researcher,150614,EUR,128022,SE,FL,Germany,L,Japan,0,"Python, Git, Spark",Master,7,Consulting,2024-07-28,2024-10-03,1729,8,DataVision Ltd -AI08693,AI Consultant,55468,EUR,47148,EN,CT,Germany,S,Germany,50,"Hadoop, Data Visualization, Git",Master,1,Technology,2024-05-18,2024-07-03,1912,9.4,Algorithmic Solutions -AI08694,Autonomous Systems Engineer,106627,USD,106627,MI,FL,Norway,M,Singapore,50,"Linux, Data Visualization, Python, Deep Learning",Associate,4,Automotive,2025-02-17,2025-04-03,2132,8.7,Future Systems -AI08695,Computer Vision Engineer,151032,SGD,196342,SE,CT,Singapore,M,Singapore,0,"Scala, Computer Vision, Linux, Spark",PhD,6,Automotive,2025-02-17,2025-04-16,2187,9.4,Algorithmic Solutions -AI08696,AI Architect,62996,USD,62996,EN,PT,South Korea,M,Mexico,100,"Scala, Data Visualization, Python, Statistics",PhD,0,Manufacturing,2024-12-15,2025-01-11,710,5.4,Quantum Computing Inc -AI08697,ML Ops Engineer,124463,AUD,168025,SE,PT,Australia,S,Ireland,100,"Spark, AWS, R, Computer Vision, PyTorch",PhD,6,Energy,2024-02-21,2024-04-05,2212,5.3,Predictive Systems -AI08698,Data Engineer,84011,EUR,71409,MI,FT,Germany,L,China,50,"SQL, Python, NLP, Statistics, Deep Learning",Bachelor,2,Healthcare,2024-10-16,2024-11-29,2444,8.4,Digital Transformation LLC -AI08699,Machine Learning Engineer,108909,USD,108909,SE,FL,South Korea,M,South Korea,0,"AWS, SQL, MLOps",PhD,6,Technology,2025-04-07,2025-06-06,2373,9.7,Machine Intelligence Group -AI08700,Autonomous Systems Engineer,117099,AUD,158084,SE,PT,Australia,M,Australia,50,"Azure, Tableau, SQL, Git",Bachelor,7,Telecommunications,2024-06-29,2024-07-16,1572,8.5,AI Innovations -AI08701,AI Architect,243649,CHF,219284,SE,CT,Switzerland,L,Switzerland,50,"R, NLP, Python, Azure",Bachelor,6,Telecommunications,2024-11-25,2024-12-22,734,7,Future Systems -AI08702,AI Consultant,85139,USD,85139,MI,CT,Sweden,S,Sweden,0,"Python, SQL, Computer Vision, Statistics",Bachelor,4,Manufacturing,2024-11-10,2024-12-25,746,9.7,Future Systems -AI08703,AI Architect,149890,CHF,134901,SE,PT,Switzerland,S,South Africa,50,"NLP, GCP, Spark, Linux",Associate,9,Retail,2024-10-04,2024-10-19,933,6.5,DeepTech Ventures -AI08704,Head of AI,72866,USD,72866,MI,FL,South Korea,M,South Korea,50,"Python, TensorFlow, NLP, Deep Learning, MLOps",Master,3,Finance,2024-07-12,2024-07-28,2089,9.4,Digital Transformation LLC -AI08705,AI Specialist,26722,USD,26722,EN,CT,India,L,India,50,"Azure, SQL, Java, PyTorch",Bachelor,1,Education,2024-07-12,2024-08-09,1064,6.8,TechCorp Inc -AI08706,AI Specialist,169001,USD,169001,SE,FT,Norway,L,Czech Republic,100,"Python, R, Computer Vision, Hadoop",Master,8,Finance,2024-09-14,2024-10-06,2184,5.4,Advanced Robotics -AI08707,Principal Data Scientist,71514,USD,71514,MI,PT,South Korea,S,South Korea,50,"Scala, Kubernetes, Azure, Deep Learning, SQL",Bachelor,3,Government,2025-01-30,2025-03-01,708,9.3,Algorithmic Solutions -AI08708,Machine Learning Researcher,128232,EUR,108997,SE,FT,Netherlands,M,Japan,50,"Spark, Data Visualization, TensorFlow, Mathematics, Azure",Master,6,Energy,2024-06-07,2024-07-01,883,6.9,Future Systems -AI08709,AI Software Engineer,58091,USD,58091,EN,FL,Israel,M,Austria,0,"Python, Mathematics, NLP, TensorFlow, Spark",Bachelor,1,Consulting,2025-04-07,2025-06-11,674,7.4,DataVision Ltd -AI08710,Deep Learning Engineer,63424,JPY,6976640,EN,CT,Japan,S,Japan,100,"Kubernetes, R, Hadoop, Azure",Associate,0,Real Estate,2024-08-27,2024-10-23,1625,8.8,Smart Analytics -AI08711,Computer Vision Engineer,65363,USD,65363,SE,FL,China,M,South Africa,0,"Hadoop, Tableau, GCP, Java",Associate,5,Telecommunications,2024-02-21,2024-03-19,2347,6.6,Smart Analytics -AI08712,Robotics Engineer,54587,USD,54587,EX,FL,India,M,India,0,"Python, TensorFlow, Docker, Mathematics, Java",Bachelor,18,Automotive,2024-10-04,2024-12-03,1159,6.4,Quantum Computing Inc -AI08713,Data Scientist,248642,CHF,223778,EX,FT,Switzerland,M,Switzerland,0,"AWS, MLOps, Docker",Master,11,Technology,2024-07-27,2024-09-02,1616,8.6,Algorithmic Solutions -AI08714,AI Software Engineer,64401,USD,64401,EX,FL,China,S,China,50,"Deep Learning, Kubernetes, Tableau, Python",PhD,17,Finance,2025-03-28,2025-04-12,1565,7.8,DeepTech Ventures -AI08715,AI Product Manager,92513,USD,92513,SE,PT,Finland,S,Belgium,50,"Kubernetes, TensorFlow, SQL, Deep Learning, Hadoop",Associate,5,Transportation,2024-10-14,2024-11-26,1362,9.3,Advanced Robotics -AI08716,Robotics Engineer,238453,USD,238453,EX,FT,United States,M,United States,0,"Java, Python, TensorFlow",Associate,11,Media,2025-03-27,2025-05-16,1106,7.8,Machine Intelligence Group -AI08717,Data Engineer,99160,AUD,133866,MI,PT,Australia,M,Australia,50,"Java, Scala, Python",PhD,3,Media,2024-11-29,2025-01-25,2447,7.6,Advanced Robotics -AI08718,Data Scientist,248599,USD,248599,EX,PT,Finland,L,Finland,0,"SQL, PyTorch, Tableau, Docker",Bachelor,13,Finance,2024-05-12,2024-06-26,2240,6.5,TechCorp Inc -AI08719,NLP Engineer,236767,USD,236767,EX,CT,Ireland,M,Ireland,100,"GCP, NLP, AWS, SQL, Kubernetes",Associate,13,Transportation,2024-10-12,2024-12-03,1905,5,AI Innovations -AI08720,Deep Learning Engineer,110782,GBP,83087,MI,FL,United Kingdom,L,United Kingdom,0,"GCP, Data Visualization, Linux, Computer Vision, Kubernetes",Associate,2,Gaming,2024-11-09,2024-12-16,609,8.5,Cloud AI Solutions -AI08721,AI Research Scientist,302161,GBP,226621,EX,CT,United Kingdom,L,United Kingdom,100,"Mathematics, Java, Data Visualization, R",PhD,18,Energy,2025-04-05,2025-05-01,2008,9.9,DataVision Ltd -AI08722,AI Architect,146187,SGD,190043,EX,FL,Singapore,S,Thailand,0,"Kubernetes, GCP, MLOps, Statistics, Git",Associate,12,Technology,2025-01-10,2025-03-23,1238,9.7,Advanced Robotics -AI08723,AI Specialist,94634,EUR,80439,MI,CT,France,L,France,0,"R, Scala, Computer Vision, Mathematics, Python",Master,3,Media,2024-08-26,2024-10-05,712,6.2,Neural Networks Co -AI08724,AI Consultant,115988,USD,115988,SE,FL,Finland,M,Finland,50,"Hadoop, SQL, R, NLP, Scala",Associate,8,Retail,2025-01-16,2025-03-25,1191,5.4,Future Systems -AI08725,Autonomous Systems Engineer,192776,EUR,163860,EX,PT,Austria,L,Chile,100,"Computer Vision, Kubernetes, Mathematics",PhD,12,Retail,2025-04-22,2025-06-07,1757,7.2,DataVision Ltd -AI08726,ML Ops Engineer,33869,USD,33869,EN,PT,China,L,China,0,"Computer Vision, Git, Python, Spark",Master,1,Consulting,2024-02-10,2024-03-09,2019,7.9,Cognitive Computing -AI08727,AI Research Scientist,77360,JPY,8509600,EN,PT,Japan,M,Kenya,100,"SQL, Mathematics, MLOps, Statistics, Azure",PhD,0,Media,2025-01-18,2025-02-24,1156,8.5,TechCorp Inc -AI08728,Data Engineer,236119,JPY,25973090,EX,CT,Japan,L,Japan,50,"AWS, Python, TensorFlow, NLP",PhD,13,Consulting,2024-11-22,2024-12-14,602,5.4,Cloud AI Solutions -AI08729,Machine Learning Researcher,99743,USD,99743,EX,FT,China,M,China,100,"Hadoop, Python, Deep Learning, Linux, Mathematics",Master,17,Healthcare,2024-07-03,2024-07-26,1081,5.7,Quantum Computing Inc -AI08730,Data Scientist,92399,USD,92399,EN,FT,Denmark,S,Germany,0,"Spark, Python, MLOps",PhD,1,Education,2025-04-24,2025-06-25,1223,5.8,TechCorp Inc -AI08731,Computer Vision Engineer,110170,USD,110170,MI,CT,Sweden,M,India,100,"Linux, Docker, R, Git, AWS",PhD,4,Gaming,2025-01-06,2025-02-21,2429,7.4,DataVision Ltd -AI08732,Machine Learning Researcher,198925,USD,198925,EX,CT,Ireland,S,Nigeria,0,"Scala, R, SQL",Master,13,Gaming,2024-03-05,2024-05-09,1898,5.9,Algorithmic Solutions -AI08733,Data Engineer,170795,EUR,145176,EX,PT,Austria,M,Austria,50,"Java, SQL, GCP",PhD,17,Gaming,2025-04-29,2025-05-14,2240,8.1,Quantum Computing Inc -AI08734,Machine Learning Researcher,152232,EUR,129397,EX,FL,Netherlands,M,Netherlands,100,"Java, Hadoop, Tableau, Statistics, Spark",Master,19,Telecommunications,2024-12-19,2025-02-23,1989,7.5,AI Innovations -AI08735,AI Architect,308244,USD,308244,EX,FL,Norway,M,Portugal,0,"Spark, Java, PyTorch, Azure, Linux",Associate,10,Energy,2025-04-07,2025-05-19,1331,6.8,DeepTech Ventures -AI08736,AI Product Manager,58771,USD,58771,SE,CT,India,L,India,50,"Deep Learning, Hadoop, Computer Vision",PhD,7,Government,2024-02-05,2024-03-08,1849,6.6,Algorithmic Solutions -AI08737,Machine Learning Engineer,69542,EUR,59111,EN,CT,Netherlands,M,New Zealand,50,"Azure, Java, AWS, Python",Associate,1,Government,2024-06-04,2024-06-27,680,7.1,Advanced Robotics -AI08738,Principal Data Scientist,99141,USD,99141,MI,FL,Ireland,L,Hungary,50,"AWS, Linux, R, NLP, Docker",Bachelor,2,Government,2024-04-22,2024-05-07,1798,7.7,Autonomous Tech -AI08739,Machine Learning Engineer,115731,AUD,156237,MI,CT,Australia,L,Australia,0,"Git, Kubernetes, R, Spark, Deep Learning",PhD,4,Automotive,2025-02-24,2025-03-17,1199,8.8,AI Innovations -AI08740,AI Architect,73001,SGD,94901,EN,FL,Singapore,L,Singapore,50,"PyTorch, Scala, Docker",PhD,0,Technology,2024-06-13,2024-07-21,1492,9.9,Predictive Systems -AI08741,ML Ops Engineer,354384,USD,354384,EX,CT,Denmark,L,Portugal,100,"Deep Learning, Azure, Data Visualization",Associate,17,Media,2024-08-28,2024-09-28,1776,7.6,Machine Intelligence Group -AI08742,AI Software Engineer,89933,JPY,9892630,MI,PT,Japan,M,Japan,100,"Python, Docker, Azure, AWS",PhD,3,Telecommunications,2024-04-09,2024-04-25,1282,8.2,DeepTech Ventures -AI08743,AI Specialist,165985,JPY,18258350,EX,FL,Japan,L,Japan,0,"Git, Scala, Computer Vision, PyTorch",Associate,11,Real Estate,2024-07-31,2024-09-05,2297,8.6,Machine Intelligence Group -AI08744,Machine Learning Engineer,84231,EUR,71596,MI,PT,France,M,Philippines,100,"Scala, Kubernetes, R, Mathematics",Bachelor,4,Automotive,2024-11-24,2025-01-01,663,7.3,Cloud AI Solutions -AI08745,AI Research Scientist,123845,USD,123845,SE,CT,United States,S,New Zealand,50,"AWS, Deep Learning, Git, Docker, Azure",Bachelor,6,Transportation,2024-01-13,2024-02-15,686,6.2,Algorithmic Solutions -AI08746,Data Scientist,272008,USD,272008,EX,FL,Norway,S,Romania,100,"Python, Kubernetes, Tableau, Deep Learning, Docker",Bachelor,19,Retail,2024-09-07,2024-10-12,1953,9.3,Smart Analytics -AI08747,ML Ops Engineer,338395,USD,338395,EX,PT,United States,L,United States,50,"Linux, Python, Spark, Scala, Deep Learning",PhD,15,Technology,2025-03-16,2025-04-19,2070,6.4,Cognitive Computing -AI08748,AI Consultant,104347,EUR,88695,MI,FL,Germany,M,Netherlands,100,"Spark, Mathematics, Deep Learning, Computer Vision, AWS",Associate,4,Manufacturing,2024-02-18,2024-04-02,821,9.4,Machine Intelligence Group -AI08749,ML Ops Engineer,129907,JPY,14289770,SE,PT,Japan,S,Japan,100,"Data Visualization, Java, Tableau, TensorFlow, GCP",PhD,8,Real Estate,2024-12-04,2025-01-17,2013,5.7,Machine Intelligence Group -AI08750,Robotics Engineer,75071,EUR,63810,EN,CT,Austria,L,Austria,50,"Tableau, Mathematics, Python, TensorFlow, Deep Learning",PhD,1,Finance,2024-03-17,2024-05-28,2359,7.6,TechCorp Inc -AI08751,Data Scientist,89718,USD,89718,EN,FL,Ireland,L,Ireland,0,"SQL, Python, PyTorch",PhD,1,Healthcare,2024-12-28,2025-01-13,883,6.6,Predictive Systems -AI08752,Head of AI,123663,JPY,13602930,SE,CT,Japan,S,Japan,50,"Kubernetes, AWS, Statistics, Computer Vision",Associate,6,Education,2024-03-31,2024-05-07,522,6.3,DataVision Ltd -AI08753,AI Architect,232491,EUR,197617,EX,CT,France,M,France,50,"GCP, AWS, Hadoop, Tableau, Statistics",Bachelor,18,Healthcare,2024-03-27,2024-05-09,1496,9.3,Machine Intelligence Group -AI08754,Machine Learning Researcher,54167,USD,54167,SE,PT,India,L,Norway,0,"Git, Linux, Spark, Mathematics",Master,7,Education,2024-01-31,2024-03-30,2248,8.6,DataVision Ltd -AI08755,AI Product Manager,89079,CAD,111349,MI,CT,Canada,L,Canada,100,"MLOps, SQL, Python",Associate,2,Manufacturing,2024-08-25,2024-09-15,2460,6.6,Smart Analytics -AI08756,Data Scientist,194970,GBP,146228,EX,PT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, R, NLP, Deep Learning",Master,19,Government,2024-10-02,2024-10-16,961,8.8,Smart Analytics -AI08757,ML Ops Engineer,228547,USD,228547,EX,FL,Sweden,S,Sweden,0,"Tableau, Spark, GCP",PhD,13,Government,2025-01-10,2025-02-18,1740,7.2,Digital Transformation LLC -AI08758,Robotics Engineer,52055,USD,52055,SE,FL,India,L,India,50,"Linux, Hadoop, SQL",Bachelor,7,Automotive,2024-03-14,2024-04-05,2193,8.6,Advanced Robotics -AI08759,Head of AI,57328,USD,57328,EX,CT,India,M,India,50,"Python, R, Deep Learning, NLP, AWS",Associate,12,Education,2025-03-02,2025-03-31,1122,8.4,TechCorp Inc -AI08760,Autonomous Systems Engineer,52301,USD,52301,EN,PT,Sweden,S,Sweden,0,"Hadoop, Python, Kubernetes, Computer Vision, TensorFlow",Master,1,Telecommunications,2025-04-04,2025-04-23,1291,7.4,Cloud AI Solutions -AI08761,Robotics Engineer,23552,USD,23552,EN,PT,India,L,India,50,"Azure, Java, NLP, R, Deep Learning",PhD,0,Manufacturing,2025-03-20,2025-04-14,953,9.5,Quantum Computing Inc -AI08762,AI Product Manager,135585,EUR,115247,SE,FT,Netherlands,S,Netherlands,50,"Java, SQL, PyTorch, Deep Learning, Docker",Bachelor,8,Government,2024-10-09,2024-11-29,2293,6.8,Advanced Robotics -AI08763,AI Software Engineer,281620,USD,281620,EX,FT,Ireland,L,Ireland,50,"Git, Kubernetes, Scala, Spark, Computer Vision",Bachelor,13,Gaming,2024-06-15,2024-08-10,770,8.7,Digital Transformation LLC -AI08764,NLP Engineer,158612,SGD,206196,SE,CT,Singapore,M,Singapore,0,"Spark, Data Visualization, Java, MLOps, Linux",Master,5,Retail,2024-07-17,2024-09-15,836,6.9,Advanced Robotics -AI08765,AI Specialist,104480,USD,104480,MI,CT,Ireland,L,Ireland,100,"TensorFlow, Python, Tableau, SQL",PhD,4,Energy,2024-01-29,2024-04-03,734,8.8,Machine Intelligence Group -AI08766,Machine Learning Engineer,50599,EUR,43009,EN,FT,Germany,S,Romania,50,"Python, Hadoop, Data Visualization, Scala",Master,1,Government,2024-09-22,2024-11-07,857,5.1,Future Systems -AI08767,AI Consultant,74316,EUR,63169,MI,FT,Netherlands,S,Netherlands,100,"Linux, Tableau, SQL, Kubernetes",Master,3,Technology,2024-11-05,2024-12-04,763,5.8,Predictive Systems -AI08768,Robotics Engineer,91016,CAD,113770,MI,CT,Canada,L,Switzerland,50,"Hadoop, Spark, Deep Learning, Python",Associate,3,Transportation,2025-04-14,2025-05-10,1257,6.5,Cloud AI Solutions -AI08769,AI Product Manager,83508,USD,83508,MI,FT,Finland,L,Finland,50,"Linux, Git, PyTorch, Hadoop",Bachelor,3,Technology,2024-12-11,2025-01-29,725,7.6,Machine Intelligence Group -AI08770,AI Research Scientist,54579,USD,54579,EN,PT,Israel,S,Luxembourg,100,"Tableau, GCP, Git",Associate,0,Government,2025-04-01,2025-05-12,1489,6.9,Machine Intelligence Group -AI08771,NLP Engineer,147819,EUR,125646,EX,PT,Netherlands,S,Netherlands,50,"Data Visualization, PyTorch, Hadoop",Master,13,Automotive,2025-03-22,2025-04-10,1636,10,Future Systems -AI08772,Autonomous Systems Engineer,85094,USD,85094,MI,FT,Sweden,S,Finland,100,"Scala, Azure, Spark",Master,3,Consulting,2024-10-17,2024-12-04,801,7.3,Digital Transformation LLC -AI08773,AI Product Manager,18730,USD,18730,EN,CT,India,S,India,100,"Data Visualization, R, SQL",Associate,0,Real Estate,2024-08-01,2024-08-18,1893,6,Smart Analytics -AI08774,Deep Learning Engineer,89305,EUR,75909,MI,FT,Netherlands,S,South Korea,100,"AWS, Python, MLOps, TensorFlow, Hadoop",Master,3,Manufacturing,2024-04-16,2024-06-22,659,6.6,Smart Analytics -AI08775,Data Engineer,67597,USD,67597,MI,FT,South Korea,S,South Korea,100,"Deep Learning, Kubernetes, GCP",PhD,2,Telecommunications,2024-11-08,2025-01-03,1645,6.6,Future Systems -AI08776,NLP Engineer,67427,SGD,87655,EN,PT,Singapore,M,Singapore,0,"Linux, Mathematics, Hadoop",Master,0,Automotive,2024-04-20,2024-06-22,563,7.4,Autonomous Tech -AI08777,Machine Learning Engineer,80525,CAD,100656,MI,CT,Canada,S,Canada,0,"Mathematics, Kubernetes, SQL",PhD,3,Technology,2024-04-12,2024-06-24,533,8.2,Cloud AI Solutions -AI08778,Machine Learning Researcher,73119,USD,73119,EN,CT,Israel,M,Australia,100,"R, Kubernetes, Docker",Associate,0,Technology,2024-08-30,2024-11-11,2228,9.9,Smart Analytics -AI08779,Data Engineer,76899,USD,76899,EN,FT,Norway,L,Norway,50,"MLOps, NLP, Docker, Git",PhD,1,Finance,2024-03-06,2024-05-18,728,9.6,Machine Intelligence Group -AI08780,AI Specialist,71826,EUR,61052,EN,CT,Austria,M,Brazil,100,"Docker, Git, Hadoop, SQL, Computer Vision",Master,0,Transportation,2024-11-24,2024-12-20,1285,5.3,Quantum Computing Inc -AI08781,Autonomous Systems Engineer,101327,USD,101327,EN,PT,Norway,M,Norway,50,"Java, GCP, Python",Associate,1,Telecommunications,2024-11-18,2024-12-23,1879,6,Algorithmic Solutions -AI08782,Robotics Engineer,69083,USD,69083,MI,CT,Israel,M,Israel,100,"Python, Kubernetes, Docker",Master,2,Technology,2024-07-22,2024-08-08,1075,5.2,Algorithmic Solutions -AI08783,ML Ops Engineer,90930,EUR,77291,MI,PT,Austria,M,Austria,0,"Scala, TensorFlow, MLOps, Python",Master,2,Media,2024-09-10,2024-09-27,2010,7.2,DeepTech Ventures -AI08784,Autonomous Systems Engineer,124784,USD,124784,SE,PT,South Korea,M,Mexico,100,"Linux, Azure, Python",Bachelor,8,Media,2024-08-10,2024-10-12,632,5.8,DataVision Ltd -AI08785,Deep Learning Engineer,112554,USD,112554,MI,FT,Norway,M,Norway,50,"Python, Computer Vision, TensorFlow, Java, Hadoop",Master,4,Technology,2024-03-26,2024-04-17,644,7.1,Neural Networks Co -AI08786,AI Consultant,138859,EUR,118030,SE,FT,France,M,France,0,"NLP, Git, Azure, R, Python",Master,6,Retail,2024-03-25,2024-05-02,2136,7.2,Future Systems -AI08787,Data Scientist,155807,EUR,132436,EX,CT,France,L,Singapore,100,"AWS, R, Python, Git, Scala",PhD,18,Consulting,2024-11-14,2024-12-10,1084,6.8,Digital Transformation LLC -AI08788,Computer Vision Engineer,70709,EUR,60103,EN,CT,Germany,S,Canada,50,"TensorFlow, SQL, AWS",Master,1,Automotive,2024-05-10,2024-07-16,1987,8.1,Advanced Robotics -AI08789,NLP Engineer,20948,USD,20948,EN,FL,India,S,India,50,"Scala, Spark, Docker",Associate,1,Technology,2025-03-14,2025-05-08,505,9.5,Smart Analytics -AI08790,Head of AI,128719,EUR,109411,SE,PT,Netherlands,M,Turkey,100,"R, GCP, Python, Java, Mathematics",PhD,7,Energy,2024-06-13,2024-08-06,1872,9.6,Neural Networks Co -AI08791,AI Product Manager,73053,USD,73053,EN,PT,Ireland,L,Ireland,50,"PyTorch, Data Visualization, Azure",PhD,1,Telecommunications,2024-07-18,2024-08-03,1480,6.1,DataVision Ltd -AI08792,Research Scientist,127282,USD,127282,MI,PT,Denmark,S,Denmark,50,"Tableau, Spark, Python, Linux",PhD,4,Telecommunications,2024-07-24,2024-09-01,2464,8.9,DeepTech Ventures -AI08793,AI Product Manager,195816,SGD,254561,EX,FT,Singapore,S,Singapore,0,"Git, R, Deep Learning, Mathematics, Java",Master,13,Telecommunications,2024-01-03,2024-02-25,1036,6.2,Autonomous Tech -AI08794,NLP Engineer,169752,USD,169752,EX,CT,United States,M,United States,0,"MLOps, Java, Statistics, Data Visualization",Associate,14,Healthcare,2025-04-23,2025-06-24,956,5.7,Predictive Systems -AI08795,AI Consultant,105502,USD,105502,EX,FT,China,L,China,0,"SQL, Linux, Tableau, Computer Vision",Master,10,Transportation,2025-01-09,2025-02-24,1935,5.5,TechCorp Inc -AI08796,Data Engineer,112014,USD,112014,SE,PT,Ireland,S,Ireland,100,"TensorFlow, Scala, Python, Docker, R",Associate,6,Finance,2025-01-19,2025-03-09,1596,9.5,Machine Intelligence Group -AI08797,Machine Learning Engineer,247688,JPY,27245680,EX,FT,Japan,L,Japan,50,"PyTorch, SQL, Kubernetes, R",Master,18,Real Estate,2025-02-20,2025-05-03,1479,8.2,Autonomous Tech -AI08798,ML Ops Engineer,74961,EUR,63717,EN,PT,France,M,France,0,"TensorFlow, Data Visualization, Linux",PhD,1,Gaming,2024-10-24,2024-12-19,1666,6.3,Neural Networks Co -AI08799,ML Ops Engineer,115927,USD,115927,SE,PT,South Korea,L,Latvia,50,"Kubernetes, Data Visualization, PyTorch, GCP",PhD,8,Real Estate,2024-09-19,2024-10-10,2021,9.5,AI Innovations -AI08800,AI Consultant,60784,EUR,51666,EN,FT,France,S,France,50,"Tableau, NLP, Computer Vision, R",Master,0,Transportation,2025-04-01,2025-05-24,2418,5.9,Advanced Robotics -AI08801,Research Scientist,88808,EUR,75487,MI,FL,Germany,S,Germany,50,"GCP, PyTorch, Computer Vision",Master,2,Telecommunications,2025-04-04,2025-05-14,865,9.4,DeepTech Ventures -AI08802,AI Research Scientist,147363,EUR,125259,SE,CT,Austria,L,Austria,100,"Python, GCP, Computer Vision, TensorFlow, Azure",Associate,6,Manufacturing,2024-10-25,2025-01-02,651,8.3,Digital Transformation LLC -AI08803,AI Specialist,49188,USD,49188,EX,FT,India,S,India,100,"R, Azure, Linux, Computer Vision, Java",Associate,17,Healthcare,2024-07-25,2024-08-18,1743,9.3,Cloud AI Solutions -AI08804,Principal Data Scientist,159673,AUD,215559,EX,PT,Australia,M,Australia,0,"Hadoop, Linux, Java",PhD,18,Transportation,2025-03-01,2025-04-14,594,7.9,Future Systems -AI08805,AI Specialist,113403,EUR,96393,SE,CT,Germany,M,Germany,50,"Spark, Java, Tableau, Python, Statistics",Bachelor,7,Energy,2024-12-18,2025-03-01,2388,7.3,Smart Analytics -AI08806,Deep Learning Engineer,101965,USD,101965,MI,PT,Denmark,M,Denmark,0,"Scala, Python, Spark, Data Visualization",Bachelor,2,Media,2025-02-21,2025-03-26,1964,9.9,Advanced Robotics -AI08807,Head of AI,75727,USD,75727,MI,FL,Ireland,M,Ireland,50,"Data Visualization, Python, Deep Learning",Bachelor,4,Real Estate,2024-04-11,2024-06-07,2012,7.1,Machine Intelligence Group -AI08808,Principal Data Scientist,64011,EUR,54409,MI,CT,France,S,France,0,"R, Scala, NLP",PhD,2,Retail,2024-12-19,2025-01-03,528,5.5,AI Innovations -AI08809,Machine Learning Engineer,108796,JPY,11967560,MI,FL,Japan,L,Brazil,50,"R, Deep Learning, GCP, Computer Vision, Scala",Bachelor,4,Automotive,2024-06-13,2024-08-07,877,7.6,TechCorp Inc -AI08810,Robotics Engineer,235070,JPY,25857700,EX,CT,Japan,L,Japan,100,"Data Visualization, Scala, Linux, Python, Hadoop",Bachelor,11,Technology,2025-04-17,2025-05-07,1540,5.5,AI Innovations -AI08811,Data Engineer,180679,USD,180679,EX,FT,South Korea,M,Netherlands,100,"SQL, Linux, Java, Git",PhD,15,Healthcare,2024-03-17,2024-05-29,2493,8.8,Advanced Robotics -AI08812,Robotics Engineer,151818,EUR,129045,EX,FL,Germany,S,Thailand,0,"SQL, Java, R",PhD,19,Technology,2024-12-21,2025-01-19,887,7.9,Digital Transformation LLC -AI08813,Autonomous Systems Engineer,106856,USD,106856,MI,CT,Israel,L,Portugal,0,"Statistics, R, Tableau",PhD,4,Consulting,2024-02-27,2024-04-09,1290,6.3,Cloud AI Solutions -AI08814,Robotics Engineer,108490,JPY,11933900,MI,PT,Japan,M,Mexico,100,"Azure, Python, Deep Learning",PhD,2,Education,2024-04-06,2024-04-22,1077,6,Smart Analytics -AI08815,ML Ops Engineer,71874,EUR,61093,MI,CT,France,M,France,0,"Kubernetes, Python, SQL, MLOps, Statistics",PhD,3,Real Estate,2024-09-18,2024-11-30,1725,5.5,Quantum Computing Inc -AI08816,AI Consultant,202910,EUR,172474,EX,FL,France,S,Hungary,50,"PyTorch, Tableau, TensorFlow, Computer Vision",Bachelor,19,Real Estate,2025-01-26,2025-03-15,1807,8.3,DataVision Ltd -AI08817,AI Product Manager,118893,EUR,101059,SE,FL,Austria,L,Australia,50,"Deep Learning, Linux, GCP, Mathematics",Master,9,Retail,2024-03-16,2024-04-03,718,5.9,Digital Transformation LLC -AI08818,Data Analyst,90747,USD,90747,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Java, Git",Associate,4,Technology,2024-12-17,2025-02-23,1975,7.1,Digital Transformation LLC -AI08819,AI Software Engineer,55913,USD,55913,EN,FT,Ireland,M,Estonia,50,"Tableau, Spark, PyTorch, SQL, Data Visualization",Master,0,Consulting,2024-01-27,2024-02-27,936,5.8,Future Systems -AI08820,Data Scientist,321130,CHF,289017,EX,PT,Switzerland,S,Finland,100,"AWS, Docker, MLOps, SQL, Kubernetes",Bachelor,16,Telecommunications,2024-01-31,2024-04-03,572,9.1,Cognitive Computing -AI08821,Data Scientist,48284,USD,48284,EN,CT,Finland,S,Finland,50,"Python, Git, Linux, AWS",Master,0,Education,2024-04-26,2024-06-29,1758,7,DataVision Ltd -AI08822,Machine Learning Engineer,93069,USD,93069,EN,PT,Denmark,L,Denmark,0,"Data Visualization, Mathematics, Python, NLP",Bachelor,1,Education,2025-03-20,2025-05-22,1265,9.3,DataVision Ltd -AI08823,AI Architect,154216,USD,154216,SE,CT,Norway,L,Norway,0,"Scala, Git, Mathematics, Spark",Bachelor,5,Finance,2024-09-08,2024-11-01,652,8.7,TechCorp Inc -AI08824,Autonomous Systems Engineer,212745,AUD,287206,EX,PT,Australia,M,Australia,50,"NLP, Data Visualization, Docker, Python, Spark",PhD,10,Automotive,2025-03-11,2025-04-22,1584,9,Cloud AI Solutions -AI08825,ML Ops Engineer,148725,AUD,200779,EX,FT,Australia,M,Australia,50,"Computer Vision, Docker, TensorFlow",PhD,16,Automotive,2025-04-25,2025-05-30,1977,5.7,Predictive Systems -AI08826,Deep Learning Engineer,214868,AUD,290072,EX,CT,Australia,S,South Africa,100,"SQL, Computer Vision, Java, Mathematics, AWS",Master,17,Consulting,2024-12-07,2025-01-17,613,6.9,Neural Networks Co -AI08827,AI Consultant,48192,USD,48192,EN,CT,Sweden,S,Luxembourg,100,"SQL, TensorFlow, Git",Associate,0,Manufacturing,2024-02-11,2024-03-09,1626,7.6,Digital Transformation LLC -AI08828,Autonomous Systems Engineer,53715,USD,53715,EN,FT,Israel,S,Israel,50,"Python, TensorFlow, Linux, AWS, R",Associate,1,Education,2024-07-18,2024-08-02,1454,6.6,AI Innovations -AI08829,Data Engineer,79419,EUR,67506,MI,FL,Netherlands,S,Chile,100,"Python, Java, Computer Vision, AWS",PhD,3,Retail,2024-03-22,2024-05-07,2420,9.3,Quantum Computing Inc -AI08830,ML Ops Engineer,189251,EUR,160863,EX,FL,Austria,M,Austria,100,"Kubernetes, Computer Vision, Python, GCP, Statistics",Bachelor,12,Energy,2024-07-28,2024-08-22,1299,8.1,Cognitive Computing -AI08831,AI Product Manager,82862,USD,82862,MI,FT,United States,S,United States,50,"Tableau, Spark, Python",PhD,2,Technology,2024-03-14,2024-04-21,1366,9.2,TechCorp Inc -AI08832,Research Scientist,312798,CHF,281518,EX,CT,Switzerland,S,Portugal,100,"PyTorch, Mathematics, Deep Learning, TensorFlow",Associate,12,Retail,2024-06-06,2024-06-27,1963,5.8,Cloud AI Solutions -AI08833,ML Ops Engineer,104615,CHF,94154,EN,FL,Switzerland,L,United States,0,"Linux, Spark, Git, SQL, Hadoop",Master,0,Media,2024-06-22,2024-07-29,2231,9.5,Smart Analytics -AI08834,Deep Learning Engineer,42852,USD,42852,MI,FL,China,L,China,50,"R, Java, Azure, Deep Learning, AWS",Bachelor,2,Automotive,2024-05-03,2024-07-04,934,6.3,Smart Analytics -AI08835,Principal Data Scientist,83129,CAD,103911,MI,FT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Linux",Bachelor,3,Real Estate,2024-04-15,2024-05-03,810,5.5,Digital Transformation LLC -AI08836,Robotics Engineer,64763,SGD,84192,EN,PT,Singapore,S,Singapore,50,"R, SQL, Deep Learning",PhD,0,Government,2024-04-30,2024-07-10,1126,9.1,Neural Networks Co -AI08837,Data Scientist,140525,SGD,182683,SE,PT,Singapore,L,China,0,"Docker, Spark, Python, AWS",Associate,6,Automotive,2024-05-15,2024-07-25,816,8.2,TechCorp Inc -AI08838,AI Software Engineer,164731,AUD,222387,SE,FT,Australia,L,Australia,0,"Linux, PyTorch, Data Visualization, SQL",Bachelor,8,Automotive,2024-11-18,2024-12-17,1758,6.2,DataVision Ltd -AI08839,Machine Learning Researcher,58860,USD,58860,MI,CT,China,L,China,100,"Python, R, TensorFlow",PhD,4,Transportation,2024-10-13,2024-12-15,1321,9.7,Cloud AI Solutions -AI08840,AI Specialist,117441,USD,117441,MI,CT,Norway,M,Norway,100,"Mathematics, Kubernetes, NLP, Computer Vision, Linux",Master,4,Automotive,2025-03-10,2025-05-04,1794,8.9,DataVision Ltd -AI08841,Computer Vision Engineer,72350,EUR,61498,EN,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, PyTorch, Tableau",Bachelor,1,Energy,2024-06-22,2024-07-12,504,6.1,TechCorp Inc -AI08842,Deep Learning Engineer,92337,AUD,124655,SE,PT,Australia,S,South Africa,100,"AWS, Spark, Computer Vision, Docker, Mathematics",Bachelor,7,Healthcare,2024-07-16,2024-08-26,1201,5.5,Advanced Robotics -AI08843,Autonomous Systems Engineer,53864,EUR,45784,EN,CT,Austria,M,Mexico,0,"Deep Learning, Hadoop, Linux",PhD,0,Transportation,2024-10-12,2024-12-11,2012,7.7,Machine Intelligence Group -AI08844,AI Architect,33665,USD,33665,MI,CT,India,L,India,0,"Mathematics, Kubernetes, Docker, Scala",Associate,4,Finance,2024-03-13,2024-04-13,1806,9.4,Advanced Robotics -AI08845,Machine Learning Researcher,182110,EUR,154794,EX,PT,France,M,France,50,"Python, Git, Tableau, NLP",Associate,13,Energy,2025-03-18,2025-04-08,1774,9.6,Future Systems -AI08846,Head of AI,115234,SGD,149804,MI,FL,Singapore,L,Singapore,0,"Kubernetes, Computer Vision, Azure",Master,4,Energy,2024-01-16,2024-02-03,2189,8.7,Neural Networks Co -AI08847,Data Analyst,163943,SGD,213126,EX,FL,Singapore,M,Singapore,100,"MLOps, Linux, NLP",PhD,12,Energy,2024-04-04,2024-06-05,843,8,DeepTech Ventures -AI08848,Autonomous Systems Engineer,153511,JPY,16886210,SE,PT,Japan,M,Argentina,50,"Spark, Git, Python, TensorFlow",PhD,9,Education,2024-12-30,2025-02-12,1650,6.8,DataVision Ltd -AI08849,NLP Engineer,110442,SGD,143575,MI,FT,Singapore,L,Singapore,100,"Spark, Python, TensorFlow, R",Master,4,Healthcare,2025-03-17,2025-05-20,894,5.7,TechCorp Inc -AI08850,Research Scientist,136904,USD,136904,EX,FL,Israel,M,Israel,0,"Spark, Linux, Kubernetes",Master,14,Technology,2024-10-31,2024-12-17,2225,9.7,Future Systems -AI08851,ML Ops Engineer,83201,USD,83201,EN,FT,Finland,L,Thailand,50,"Hadoop, NLP, Python",Master,1,Real Estate,2025-02-21,2025-03-27,543,7.2,Predictive Systems -AI08852,Robotics Engineer,134018,CAD,167523,SE,PT,Canada,L,Thailand,50,"Python, Java, Data Visualization",Associate,6,Media,2024-01-08,2024-03-14,889,6.6,Predictive Systems -AI08853,Principal Data Scientist,88509,EUR,75233,MI,PT,France,M,France,100,"PyTorch, R, Computer Vision, Scala",Associate,2,Healthcare,2024-01-14,2024-03-05,2308,8.5,Digital Transformation LLC -AI08854,Research Scientist,126724,USD,126724,MI,PT,Denmark,L,Denmark,100,"Git, Python, TensorFlow, PyTorch",PhD,2,Technology,2024-05-19,2024-06-12,1390,7.3,Future Systems -AI08855,Principal Data Scientist,281410,EUR,239199,EX,FL,Netherlands,L,Egypt,0,"Statistics, Mathematics, NLP, Docker, Computer Vision",Master,15,Government,2024-04-19,2024-05-12,1403,5.5,Digital Transformation LLC -AI08856,Head of AI,162401,CAD,203001,EX,PT,Canada,M,Ghana,0,"PyTorch, Mathematics, MLOps, TensorFlow, NLP",Associate,17,Healthcare,2025-04-20,2025-06-18,1233,7.2,Autonomous Tech -AI08857,Machine Learning Engineer,180046,CHF,162041,SE,FT,Switzerland,M,Ghana,0,"Statistics, R, Java",Associate,8,Consulting,2024-07-23,2024-09-21,740,6.3,Neural Networks Co -AI08858,Data Scientist,73927,USD,73927,MI,CT,Sweden,S,Mexico,0,"Hadoop, MLOps, Linux, Spark, Git",Associate,2,Healthcare,2024-07-31,2024-09-05,2041,5.5,TechCorp Inc -AI08859,Data Engineer,109990,EUR,93492,MI,FL,Germany,M,United States,50,"Python, Java, Hadoop, Statistics, Computer Vision",Master,3,Real Estate,2024-06-28,2024-08-22,2199,5.8,Machine Intelligence Group -AI08860,Data Scientist,126474,USD,126474,SE,CT,Israel,L,Russia,100,"Tableau, Java, Kubernetes",Master,6,Consulting,2025-02-20,2025-04-07,1834,5.9,AI Innovations -AI08861,AI Research Scientist,160685,EUR,136582,EX,PT,Netherlands,M,Netherlands,0,"R, GCP, Git, Spark",PhD,13,Media,2024-05-28,2024-06-13,2083,6,Machine Intelligence Group -AI08862,Deep Learning Engineer,317312,CHF,285581,EX,CT,Switzerland,S,United Kingdom,50,"Git, R, GCP, Kubernetes, Java",Bachelor,16,Technology,2024-09-15,2024-11-12,1711,7.7,Advanced Robotics -AI08863,AI Consultant,85129,USD,85129,EN,PT,Denmark,L,Denmark,0,"NLP, PyTorch, TensorFlow",Bachelor,0,Energy,2024-09-29,2024-12-06,1340,8.8,Quantum Computing Inc -AI08864,AI Consultant,162063,USD,162063,EX,FL,Finland,L,Poland,50,"Deep Learning, Docker, AWS, SQL",Bachelor,16,Gaming,2024-05-05,2024-06-11,1974,8.3,Machine Intelligence Group -AI08865,Computer Vision Engineer,50185,USD,50185,EN,CT,Finland,M,India,50,"AWS, R, Deep Learning",Master,1,Education,2024-06-16,2024-07-02,1048,7.8,AI Innovations -AI08866,Autonomous Systems Engineer,212146,EUR,180324,EX,FT,Austria,L,Austria,50,"Java, TensorFlow, Mathematics, Tableau",Master,12,Technology,2025-03-07,2025-04-18,1448,5.2,DataVision Ltd -AI08867,AI Specialist,205751,JPY,22632610,EX,PT,Japan,M,Norway,50,"TensorFlow, Azure, Scala",Associate,19,Education,2024-04-13,2024-05-12,1542,7.7,DataVision Ltd -AI08868,AI Software Engineer,144178,USD,144178,SE,CT,Sweden,L,Indonesia,50,"PyTorch, GCP, Spark",Associate,5,Energy,2024-01-24,2024-02-18,2406,5.2,Quantum Computing Inc -AI08869,Machine Learning Researcher,154217,CHF,138795,SE,CT,Switzerland,M,Switzerland,0,"Scala, Computer Vision, Kubernetes, Deep Learning, Docker",Master,5,Gaming,2024-10-30,2024-12-09,2011,8.5,Cognitive Computing -AI08870,Data Analyst,118300,USD,118300,SE,FL,Israel,L,Israel,0,"Statistics, MLOps, Spark, Computer Vision, TensorFlow",Associate,6,Retail,2024-03-22,2024-04-14,1823,6.4,Cognitive Computing -AI08871,Data Analyst,164623,USD,164623,SE,CT,Norway,L,Norway,0,"Python, SQL, Computer Vision, Mathematics, TensorFlow",Master,5,Education,2024-12-11,2025-01-19,2283,7.2,Advanced Robotics -AI08872,Data Engineer,209872,USD,209872,EX,PT,Denmark,M,Denmark,0,"Kubernetes, Azure, Tableau, R, NLP",PhD,12,Energy,2025-04-03,2025-05-14,1604,9.2,Quantum Computing Inc -AI08873,Deep Learning Engineer,140537,EUR,119456,SE,CT,France,L,France,100,"Linux, MLOps, TensorFlow, PyTorch, Mathematics",Master,6,Finance,2024-06-08,2024-07-29,1729,5.8,Neural Networks Co -AI08874,Principal Data Scientist,72674,USD,72674,MI,FT,Israel,S,Vietnam,0,"Linux, Java, SQL, Kubernetes, PyTorch",PhD,2,Consulting,2025-04-10,2025-06-22,1258,7.7,TechCorp Inc -AI08875,AI Product Manager,96117,EUR,81699,MI,FT,France,L,Australia,100,"Linux, Java, Scala",Master,2,Education,2025-04-21,2025-06-20,1684,7.7,AI Innovations -AI08876,Data Scientist,132251,EUR,112413,SE,FL,Netherlands,L,Canada,0,"SQL, Kubernetes, Azure, Computer Vision",Master,7,Gaming,2024-08-03,2024-08-22,1336,9.3,Advanced Robotics -AI08877,Robotics Engineer,180163,SGD,234212,SE,PT,Singapore,L,Singapore,100,"Kubernetes, SQL, Linux",Associate,9,Technology,2024-09-26,2024-10-14,2472,6,Machine Intelligence Group -AI08878,AI Software Engineer,64220,GBP,48165,EN,FL,United Kingdom,S,United Kingdom,0,"Data Visualization, Azure, NLP",Associate,0,Media,2024-10-13,2024-11-25,947,8.6,Digital Transformation LLC -AI08879,Computer Vision Engineer,70080,AUD,94608,EN,CT,Australia,L,Australia,0,"Scala, PyTorch, TensorFlow, Tableau, Deep Learning",PhD,1,Real Estate,2025-01-18,2025-03-27,2308,8.5,Algorithmic Solutions -AI08880,Head of AI,72201,USD,72201,MI,PT,Finland,M,Israel,50,"NLP, Deep Learning, MLOps, PyTorch",PhD,3,Manufacturing,2025-03-31,2025-04-16,1516,9.5,Advanced Robotics -AI08881,AI Research Scientist,150170,CAD,187713,EX,FL,Canada,S,Canada,50,"Computer Vision, Java, TensorFlow",PhD,11,Government,2025-02-27,2025-03-29,2288,9,Digital Transformation LLC -AI08882,NLP Engineer,68586,USD,68586,EN,FL,Sweden,M,Estonia,50,"Deep Learning, Spark, GCP",Bachelor,1,Telecommunications,2024-03-21,2024-04-21,2215,9.5,Future Systems -AI08883,AI Specialist,58484,EUR,49711,EN,PT,France,L,France,0,"Docker, Python, Spark, Hadoop",Master,1,Automotive,2024-01-31,2024-04-01,1875,5.3,AI Innovations -AI08884,Data Analyst,53494,USD,53494,EN,FL,South Korea,S,South Korea,0,"MLOps, Docker, Linux, Computer Vision",Master,0,Telecommunications,2024-09-20,2024-11-04,1820,9.5,Smart Analytics -AI08885,AI Software Engineer,175512,USD,175512,SE,FL,Norway,L,Norway,0,"Linux, Computer Vision, PyTorch, Azure, TensorFlow",Associate,7,Automotive,2025-02-11,2025-03-26,2244,9.9,Cloud AI Solutions -AI08886,AI Product Manager,124719,USD,124719,MI,PT,Norway,M,Argentina,100,"Python, Kubernetes, PyTorch",Associate,2,Automotive,2025-01-27,2025-02-27,2326,6.6,Autonomous Tech -AI08887,Machine Learning Researcher,65569,USD,65569,EN,CT,Israel,S,Israel,0,"AWS, Tableau, Mathematics",Bachelor,0,Gaming,2025-02-14,2025-03-04,2433,6.3,AI Innovations -AI08888,AI Software Engineer,184461,USD,184461,EX,CT,Denmark,M,Israel,0,"Python, R, Data Visualization",Associate,13,Education,2024-06-25,2024-08-11,2438,5.9,Neural Networks Co -AI08889,AI Software Engineer,176661,CHF,158995,SE,FL,Switzerland,L,Finland,0,"PyTorch, Mathematics, AWS, Azure, Deep Learning",Associate,8,Media,2024-04-15,2024-05-08,1040,6.3,Algorithmic Solutions -AI08890,Research Scientist,113468,GBP,85101,MI,FT,United Kingdom,L,United Kingdom,50,"Python, Computer Vision, Statistics, Tableau",Associate,3,Transportation,2024-11-24,2025-01-22,1859,7.7,Cognitive Computing -AI08891,Robotics Engineer,94278,EUR,80136,MI,FL,France,M,Belgium,50,"Git, Kubernetes, Computer Vision, Python",PhD,3,Automotive,2024-07-25,2024-08-31,2395,8.6,Quantum Computing Inc -AI08892,AI Research Scientist,124121,EUR,105503,MI,FT,Netherlands,L,Netherlands,0,"Git, PyTorch, TensorFlow",PhD,3,Manufacturing,2025-01-15,2025-02-07,1523,5.8,Smart Analytics -AI08893,ML Ops Engineer,118336,EUR,100586,SE,FL,Netherlands,S,Netherlands,0,"Computer Vision, Git, Docker, Azure, TensorFlow",Bachelor,7,Manufacturing,2024-07-04,2024-08-11,1467,6.5,Algorithmic Solutions -AI08894,AI Consultant,63446,JPY,6979060,EN,CT,Japan,M,Japan,100,"PyTorch, Docker, GCP",Associate,1,Education,2024-08-14,2024-09-07,2327,8.5,Smart Analytics -AI08895,Data Analyst,88302,GBP,66227,MI,CT,United Kingdom,M,United Kingdom,100,"SQL, Git, Docker, Deep Learning",Master,4,Energy,2025-04-18,2025-05-12,1494,7.8,Smart Analytics -AI08896,Data Engineer,69937,CAD,87421,EN,CT,Canada,L,South Korea,0,"Tableau, Git, Java, NLP, Mathematics",PhD,1,Healthcare,2024-07-08,2024-09-03,1246,6.4,Cloud AI Solutions -AI08897,Data Scientist,76500,USD,76500,MI,PT,South Korea,S,South Korea,50,"Python, Kubernetes, Azure",Associate,3,Manufacturing,2025-03-21,2025-05-09,1141,5.4,TechCorp Inc -AI08898,Data Analyst,133991,USD,133991,MI,PT,Denmark,L,Spain,100,"Deep Learning, SQL, TensorFlow, Computer Vision",PhD,2,Automotive,2025-02-27,2025-04-30,1018,7.6,DeepTech Ventures -AI08899,Research Scientist,37472,USD,37472,EN,CT,China,M,China,0,"SQL, Mathematics, Docker, Python, Linux",Master,1,Media,2024-07-30,2024-08-23,597,7.8,Neural Networks Co -AI08900,NLP Engineer,55334,GBP,41501,EN,PT,United Kingdom,S,United Kingdom,50,"SQL, Docker, Hadoop, GCP, Azure",Master,0,Retail,2024-11-01,2024-12-28,1928,8.9,Digital Transformation LLC -AI08901,Data Engineer,118965,CHF,107069,MI,FT,Switzerland,M,Switzerland,0,"SQL, Scala, PyTorch, TensorFlow",Master,4,Finance,2024-11-08,2024-12-10,1082,5.3,TechCorp Inc -AI08902,ML Ops Engineer,59325,EUR,50426,EN,PT,France,M,France,0,"Data Visualization, Git, Computer Vision",Bachelor,0,Retail,2024-03-24,2024-04-26,2308,8.2,DataVision Ltd -AI08903,AI Research Scientist,79037,EUR,67181,MI,FT,Austria,M,United Kingdom,0,"Tableau, R, Deep Learning, Computer Vision, Azure",PhD,3,Healthcare,2025-03-29,2025-05-20,566,8.8,Digital Transformation LLC -AI08904,Computer Vision Engineer,149385,EUR,126977,EX,FT,Austria,L,Belgium,50,"Python, TensorFlow, Git, Spark",Bachelor,15,Real Estate,2024-06-18,2024-07-05,586,6.5,Neural Networks Co -AI08905,AI Product Manager,76318,EUR,64870,MI,CT,Austria,M,Austria,100,"Python, Computer Vision, Linux",PhD,2,Government,2024-03-15,2024-05-03,1441,6.9,DeepTech Ventures -AI08906,Research Scientist,189385,AUD,255670,EX,FT,Australia,M,Australia,50,"Hadoop, GCP, Tableau, Java, Azure",Master,18,Transportation,2024-04-17,2024-05-05,1029,6.1,Cognitive Computing -AI08907,Autonomous Systems Engineer,130219,EUR,110686,SE,CT,Germany,M,Germany,100,"Python, SQL, Java",PhD,9,Government,2024-09-01,2024-11-04,1562,5.4,Smart Analytics -AI08908,NLP Engineer,150596,JPY,16565560,EX,CT,Japan,S,Japan,0,"TensorFlow, Hadoop, SQL, Scala, Python",Associate,16,Education,2024-03-14,2024-05-07,1265,8.4,Digital Transformation LLC -AI08909,Head of AI,144363,USD,144363,EX,PT,Sweden,S,Kenya,0,"Mathematics, Deep Learning, R, SQL, Linux",Master,14,Media,2024-05-19,2024-06-29,1823,7.6,Digital Transformation LLC -AI08910,AI Software Engineer,21072,USD,21072,EN,FT,India,L,India,100,"Kubernetes, GCP, NLP, MLOps",Bachelor,1,Technology,2024-12-15,2025-01-26,905,6.9,Future Systems -AI08911,ML Ops Engineer,186827,USD,186827,EX,FT,Israel,S,Israel,0,"Java, TensorFlow, NLP, Mathematics, PyTorch",Associate,14,Retail,2024-05-12,2024-06-03,1583,6.1,Machine Intelligence Group -AI08912,Principal Data Scientist,143167,USD,143167,SE,PT,South Korea,L,South Korea,100,"PyTorch, Python, NLP",Associate,9,Education,2025-01-19,2025-02-13,1955,8.8,Quantum Computing Inc -AI08913,ML Ops Engineer,128988,USD,128988,SE,CT,Israel,M,Estonia,100,"PyTorch, Data Visualization, Linux, MLOps",PhD,6,Government,2024-09-08,2024-11-01,960,6.1,Quantum Computing Inc -AI08914,Deep Learning Engineer,276188,EUR,234760,EX,FL,Germany,L,Germany,50,"GCP, Git, Data Visualization",Associate,13,Finance,2024-08-23,2024-10-28,1647,8.1,Digital Transformation LLC -AI08915,Autonomous Systems Engineer,41148,USD,41148,MI,PT,India,L,Portugal,100,"SQL, Hadoop, PyTorch, Docker, Git",Master,2,Consulting,2024-10-21,2024-12-28,2149,9.3,TechCorp Inc -AI08916,AI Consultant,79365,USD,79365,EX,FT,India,M,Czech Republic,0,"Data Visualization, Git, R",Master,10,Media,2025-03-02,2025-05-09,2308,5.8,TechCorp Inc -AI08917,Data Scientist,60786,USD,60786,EX,FL,India,M,India,100,"TensorFlow, PyTorch, Linux, Statistics",PhD,17,Manufacturing,2024-06-09,2024-07-14,1544,9.1,Cloud AI Solutions -AI08918,ML Ops Engineer,85296,USD,85296,MI,CT,Finland,S,India,100,"Deep Learning, Data Visualization, Python, Hadoop",PhD,3,Finance,2024-11-10,2024-12-17,2034,7.6,Future Systems -AI08919,Computer Vision Engineer,111246,SGD,144620,MI,FT,Singapore,L,Singapore,50,"Docker, Java, Data Visualization, Azure",Master,2,Consulting,2024-12-09,2025-01-03,1316,9.1,Cognitive Computing -AI08920,Robotics Engineer,89925,USD,89925,MI,PT,Ireland,L,Ireland,100,"Tableau, MLOps, Kubernetes, Hadoop, Computer Vision",PhD,2,Gaming,2024-12-27,2025-01-10,2334,6.3,AI Innovations -AI08921,Computer Vision Engineer,90696,USD,90696,MI,PT,United States,M,Israel,100,"Deep Learning, Statistics, Git, Kubernetes, NLP",Associate,2,Media,2024-08-23,2024-09-27,2447,6.3,Smart Analytics -AI08922,Robotics Engineer,131512,AUD,177541,SE,PT,Australia,S,Australia,0,"PyTorch, Scala, Spark, Deep Learning, Azure",Associate,8,Technology,2024-07-25,2024-09-13,1710,9.6,Cloud AI Solutions -AI08923,AI Product Manager,198409,AUD,267852,EX,CT,Australia,S,Australia,50,"PyTorch, GCP, MLOps, Spark",PhD,15,Healthcare,2025-04-26,2025-06-15,710,9.5,Autonomous Tech -AI08924,Data Analyst,157473,USD,157473,SE,FT,Sweden,L,Sweden,0,"Deep Learning, Tableau, R, NLP",Master,6,Finance,2024-10-24,2024-12-04,1694,7.5,Algorithmic Solutions -AI08925,NLP Engineer,126003,EUR,107103,SE,FL,France,M,France,0,"Java, Statistics, Spark, Computer Vision, TensorFlow",Bachelor,7,Energy,2024-08-04,2024-09-21,703,5.6,DeepTech Ventures -AI08926,AI Research Scientist,119850,USD,119850,SE,FT,South Korea,M,South Korea,0,"MLOps, Linux, Scala",Associate,5,Education,2024-03-29,2024-05-03,2346,9.8,DataVision Ltd -AI08927,AI Specialist,95591,CHF,86032,EN,FL,Switzerland,M,Ireland,100,"TensorFlow, PyTorch, Docker",Bachelor,1,Healthcare,2024-05-18,2024-06-03,618,8.3,TechCorp Inc -AI08928,Data Scientist,73865,GBP,55399,EN,PT,United Kingdom,M,United Kingdom,100,"Java, R, Kubernetes, Git",PhD,0,Transportation,2024-06-13,2024-07-26,2249,5.5,DeepTech Ventures -AI08929,Principal Data Scientist,71155,GBP,53366,EN,CT,United Kingdom,S,United Kingdom,0,"Java, PyTorch, NLP",PhD,0,Education,2025-01-05,2025-01-21,2184,8.6,DeepTech Ventures -AI08930,Robotics Engineer,69945,SGD,90929,MI,FL,Singapore,S,Singapore,50,"Scala, Kubernetes, Docker, Java",Associate,2,Real Estate,2024-08-15,2024-10-07,1353,9.3,Cognitive Computing -AI08931,Computer Vision Engineer,24897,USD,24897,EN,CT,China,M,China,100,"GCP, Azure, AWS",Master,0,Manufacturing,2025-04-01,2025-05-01,1147,5.1,DataVision Ltd -AI08932,Research Scientist,67162,AUD,90669,EN,FL,Australia,L,Australia,100,"Scala, Statistics, Java",Associate,0,Government,2024-08-29,2024-10-24,1973,9.2,Cloud AI Solutions -AI08933,Principal Data Scientist,57928,GBP,43446,EN,PT,United Kingdom,S,United Kingdom,50,"Java, Git, Python",PhD,1,Manufacturing,2024-02-27,2024-04-21,526,7.1,Machine Intelligence Group -AI08934,Autonomous Systems Engineer,153211,CHF,137890,MI,PT,Switzerland,M,Switzerland,50,"TensorFlow, Linux, Mathematics, Kubernetes",Bachelor,4,Transportation,2024-04-30,2024-06-21,891,8.8,Future Systems -AI08935,AI Software Engineer,111274,USD,111274,MI,CT,Denmark,S,Denmark,100,"AWS, Hadoop, Scala",Associate,2,Automotive,2024-09-20,2024-11-19,2435,8.2,Smart Analytics -AI08936,AI Specialist,119212,USD,119212,SE,CT,Israel,M,Kenya,50,"Kubernetes, Azure, Scala, SQL",Associate,5,Telecommunications,2025-03-24,2025-05-03,952,5.4,Neural Networks Co -AI08937,AI Software Engineer,167862,USD,167862,EX,FL,Israel,S,Israel,50,"Mathematics, Spark, NLP, R, Python",Bachelor,15,Automotive,2024-05-17,2024-06-03,622,9.8,Neural Networks Co -AI08938,AI Research Scientist,73151,EUR,62178,MI,PT,Germany,M,Finland,100,"Deep Learning, SQL, PyTorch, AWS",Master,4,Retail,2024-10-06,2024-10-26,1228,9.5,Cloud AI Solutions -AI08939,Research Scientist,159226,CHF,143303,MI,FT,Switzerland,L,China,0,"Linux, MLOps, Data Visualization",Master,4,Gaming,2024-05-26,2024-07-29,794,8.2,Future Systems -AI08940,AI Software Engineer,62380,USD,62380,EN,PT,Ireland,M,Romania,0,"Scala, Kubernetes, SQL, MLOps, Spark",PhD,1,Healthcare,2025-03-02,2025-03-28,1960,6.9,AI Innovations -AI08941,AI Product Manager,113996,JPY,12539560,SE,FL,Japan,M,Japan,50,"AWS, Linux, Java, Hadoop",Master,9,Consulting,2025-01-10,2025-03-06,2463,8.9,DeepTech Ventures -AI08942,NLP Engineer,51094,USD,51094,EN,CT,Ireland,M,Ireland,0,"NLP, MLOps, Statistics",Bachelor,1,Gaming,2025-04-21,2025-05-29,2239,9,TechCorp Inc -AI08943,AI Specialist,69394,USD,69394,EN,FT,Israel,L,Israel,100,"Kubernetes, Python, MLOps, Azure",PhD,1,Automotive,2025-01-08,2025-02-09,571,5.3,Future Systems -AI08944,AI Specialist,105999,CHF,95399,EN,PT,Switzerland,L,Ghana,50,"R, GCP, Hadoop, Kubernetes",Master,0,Consulting,2024-12-04,2025-02-09,1844,8,DeepTech Ventures -AI08945,ML Ops Engineer,99978,EUR,84981,SE,CT,Austria,M,Italy,0,"Kubernetes, NLP, Git, Mathematics, Hadoop",Associate,8,Energy,2025-04-29,2025-05-26,2222,8.3,DeepTech Ventures -AI08946,Data Scientist,52184,USD,52184,EN,FL,South Korea,L,South Korea,50,"SQL, Hadoop, GCP",Bachelor,0,Retail,2024-05-22,2024-06-15,1923,8.4,Digital Transformation LLC -AI08947,Data Scientist,76210,EUR,64779,MI,FL,Germany,M,Germany,50,"Java, Kubernetes, Data Visualization, NLP",PhD,2,Transportation,2024-02-02,2024-03-29,977,5.7,Predictive Systems -AI08948,AI Product Manager,67505,USD,67505,MI,FT,Israel,S,Israel,0,"PyTorch, TensorFlow, Data Visualization, Kubernetes, AWS",Bachelor,4,Consulting,2024-11-02,2024-12-17,1324,9.8,Digital Transformation LLC -AI08949,Robotics Engineer,70420,USD,70420,MI,PT,Israel,S,India,100,"Python, Scala, MLOps, AWS, NLP",PhD,4,Manufacturing,2025-01-22,2025-03-06,1191,8,Machine Intelligence Group -AI08950,AI Consultant,23683,USD,23683,EN,CT,India,L,India,50,"R, Kubernetes, Git",Master,0,Education,2024-08-04,2024-10-12,1085,8.9,Quantum Computing Inc -AI08951,Computer Vision Engineer,120220,USD,120220,MI,PT,United States,M,United States,0,"Python, Scala, Computer Vision, SQL",PhD,3,Telecommunications,2024-09-26,2024-12-01,785,5.1,Advanced Robotics -AI08952,AI Software Engineer,185311,USD,185311,EX,PT,Finland,M,Finland,50,"Hadoop, GCP, NLP, AWS, Tableau",PhD,15,Gaming,2024-09-07,2024-10-11,1773,8.5,Smart Analytics -AI08953,Robotics Engineer,140225,EUR,119191,SE,CT,Netherlands,S,Netherlands,0,"SQL, Kubernetes, Mathematics, Linux, Deep Learning",Associate,6,Real Estate,2024-04-23,2024-06-01,755,8,TechCorp Inc -AI08954,AI Specialist,126983,USD,126983,SE,FL,Israel,L,Israel,0,"Kubernetes, SQL, PyTorch, Git",PhD,9,Telecommunications,2024-12-09,2025-02-12,2196,5.3,AI Innovations -AI08955,Head of AI,198792,USD,198792,EX,FL,Finland,L,Thailand,50,"Git, PyTorch, R",Associate,11,Manufacturing,2024-05-09,2024-07-02,1864,8.1,Autonomous Tech -AI08956,AI Consultant,84341,EUR,71690,MI,FL,Austria,L,Austria,50,"Spark, Hadoop, Azure, Tableau",Bachelor,3,Finance,2024-09-29,2024-12-05,1673,6.8,Advanced Robotics -AI08957,Principal Data Scientist,59341,EUR,50440,EN,FT,Netherlands,M,Netherlands,50,"MLOps, Java, R",Associate,1,Healthcare,2024-04-22,2024-06-02,2363,7.2,Digital Transformation LLC -AI08958,Machine Learning Engineer,26028,USD,26028,MI,FT,India,M,India,0,"R, MLOps, SQL",Bachelor,3,Finance,2024-01-06,2024-02-17,991,6.9,TechCorp Inc -AI08959,AI Architect,146559,JPY,16121490,SE,PT,Japan,L,Denmark,100,"Azure, Hadoop, Python",Bachelor,9,Real Estate,2025-04-18,2025-05-11,550,9.9,Future Systems -AI08960,NLP Engineer,258425,USD,258425,EX,FT,Denmark,M,Mexico,100,"SQL, Deep Learning, AWS, Kubernetes, Mathematics",Master,12,Education,2024-07-28,2024-08-17,964,8.4,Neural Networks Co -AI08961,AI Research Scientist,158120,EUR,134402,SE,FT,Netherlands,L,South Korea,50,"Data Visualization, PyTorch, Kubernetes, Statistics",PhD,7,Real Estate,2024-09-22,2024-11-04,953,7.7,Algorithmic Solutions -AI08962,AI Specialist,77719,USD,77719,EN,CT,United States,M,United States,0,"Azure, Spark, Tableau, NLP",Master,0,Media,2024-07-29,2024-08-27,2030,6.2,Cognitive Computing -AI08963,AI Specialist,28039,USD,28039,EN,PT,China,S,China,0,"AWS, Tableau, Computer Vision, Hadoop, NLP",Master,0,Automotive,2024-08-24,2024-10-09,636,8.7,TechCorp Inc -AI08964,Robotics Engineer,96472,SGD,125414,MI,FT,Singapore,M,Ireland,50,"Python, SQL, GCP",Master,2,Government,2024-06-12,2024-07-20,724,8,Cloud AI Solutions -AI08965,Principal Data Scientist,89844,USD,89844,SE,PT,South Korea,M,Singapore,0,"Computer Vision, Hadoop, AWS, Scala, Spark",Bachelor,5,Finance,2024-02-05,2024-04-16,1977,7.1,Quantum Computing Inc -AI08966,AI Research Scientist,79472,SGD,103314,EN,PT,Singapore,L,Nigeria,0,"Scala, Kubernetes, MLOps, NLP, Mathematics",Bachelor,0,Gaming,2025-02-12,2025-02-28,1571,7,Predictive Systems -AI08967,AI Product Manager,92695,USD,92695,MI,PT,South Korea,L,South Korea,100,"Python, Docker, GCP, TensorFlow",Master,3,Government,2025-04-29,2025-06-19,802,5.6,Quantum Computing Inc -AI08968,NLP Engineer,105477,JPY,11602470,MI,PT,Japan,M,South Africa,0,"Spark, Deep Learning, Mathematics",PhD,2,Finance,2025-03-28,2025-04-16,1334,5.1,Algorithmic Solutions -AI08969,AI Consultant,59744,USD,59744,EN,FT,Finland,S,Finland,100,"Mathematics, Data Visualization, PyTorch, MLOps",Master,0,Consulting,2025-01-11,2025-03-23,1224,6.8,Neural Networks Co -AI08970,NLP Engineer,75054,JPY,8255940,EN,PT,Japan,M,Israel,0,"Data Visualization, Git, R, Scala",Master,0,Technology,2024-01-07,2024-01-26,1701,6.7,Smart Analytics -AI08971,AI Product Manager,75503,USD,75503,MI,FT,South Korea,M,South Korea,100,"Scala, Java, Data Visualization, Git",Associate,4,Education,2024-10-01,2024-10-25,1856,5.5,Cognitive Computing -AI08972,AI Specialist,86929,USD,86929,MI,FT,Israel,L,Israel,100,"R, Deep Learning, Spark",PhD,4,Technology,2024-03-16,2024-04-11,918,8.8,Predictive Systems -AI08973,Data Scientist,80667,EUR,68567,MI,FL,France,L,France,0,"TensorFlow, AWS, Statistics, Mathematics, Spark",Bachelor,4,Real Estate,2024-09-17,2024-10-20,1916,5.3,Predictive Systems -AI08974,Robotics Engineer,142450,USD,142450,EX,FT,South Korea,S,South Korea,50,"R, Scala, Python",Master,11,Education,2025-01-19,2025-03-27,2181,9,DataVision Ltd -AI08975,AI Software Engineer,145577,USD,145577,EX,FL,Ireland,S,Ireland,50,"Scala, Tableau, Spark, Statistics",Bachelor,11,Telecommunications,2024-07-19,2024-08-19,1784,7.6,Machine Intelligence Group -AI08976,Principal Data Scientist,138782,CHF,124904,MI,FT,Switzerland,L,Switzerland,100,"PyTorch, Git, GCP",Associate,2,Government,2024-04-10,2024-06-14,1512,5.7,Digital Transformation LLC -AI08977,Data Scientist,148776,AUD,200848,SE,FL,Australia,M,Australia,100,"R, Tableau, Python, Statistics",PhD,8,Gaming,2025-01-15,2025-03-21,1573,9.5,DeepTech Ventures -AI08978,Data Engineer,150654,USD,150654,MI,PT,Norway,L,Thailand,100,"AWS, Computer Vision, Data Visualization, R",Bachelor,4,Consulting,2024-02-29,2024-03-27,760,7.4,Advanced Robotics -AI08979,AI Consultant,262984,USD,262984,EX,CT,Ireland,L,Ireland,0,"Linux, Java, Spark, Scala, Computer Vision",Bachelor,11,Transportation,2024-12-06,2025-01-22,2032,5.7,Neural Networks Co -AI08980,AI Specialist,82698,GBP,62024,MI,CT,United Kingdom,S,United Kingdom,50,"Docker, Data Visualization, Spark",Master,2,Consulting,2025-03-22,2025-05-04,1128,5.7,Neural Networks Co -AI08981,Robotics Engineer,78355,GBP,58766,MI,FT,United Kingdom,S,United Kingdom,50,"Data Visualization, Python, Statistics, Computer Vision",Master,3,Automotive,2024-02-22,2024-04-23,1032,7,Machine Intelligence Group -AI08982,AI Product Manager,83880,EUR,71298,MI,FL,France,L,France,100,"Hadoop, PyTorch, Tableau, TensorFlow, NLP",PhD,2,Technology,2024-08-08,2024-09-19,1316,9.3,Cloud AI Solutions -AI08983,Data Analyst,67262,GBP,50447,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Scala, R",Master,0,Automotive,2024-06-07,2024-07-05,1330,7.3,Predictive Systems -AI08984,Computer Vision Engineer,65253,USD,65253,SE,FT,China,M,China,0,"NLP, TensorFlow, Spark",Bachelor,5,Consulting,2025-03-22,2025-05-21,882,7.4,AI Innovations -AI08985,ML Ops Engineer,100727,USD,100727,SE,PT,Israel,S,Israel,0,"Tableau, TensorFlow, GCP, Statistics",Master,5,Automotive,2024-01-23,2024-02-23,2081,6,Cloud AI Solutions -AI08986,Principal Data Scientist,201256,CAD,251570,EX,CT,Canada,S,Italy,0,"Azure, Python, Computer Vision",Master,17,Media,2025-03-15,2025-05-14,999,6.2,DataVision Ltd -AI08987,Deep Learning Engineer,98333,CHF,88500,EN,CT,Switzerland,S,Poland,100,"GCP, R, SQL, Statistics, Data Visualization",Bachelor,1,Healthcare,2024-10-04,2024-10-27,1743,6.8,Cognitive Computing -AI08988,AI Product Manager,238048,GBP,178536,EX,CT,United Kingdom,S,Switzerland,100,"Scala, R, Computer Vision, Kubernetes",PhD,19,Automotive,2024-11-09,2024-12-01,696,8,Algorithmic Solutions -AI08989,Computer Vision Engineer,111723,USD,111723,SE,PT,South Korea,S,Ukraine,0,"R, Statistics, Computer Vision, GCP",PhD,6,Transportation,2024-06-15,2024-08-23,909,9.7,Autonomous Tech -AI08990,ML Ops Engineer,62271,EUR,52930,EN,FL,Germany,S,Germany,50,"Linux, R, Git, Hadoop, Docker",Associate,0,Manufacturing,2024-08-25,2024-11-02,1742,7.1,TechCorp Inc -AI08991,Machine Learning Researcher,186844,CAD,233555,EX,FL,Canada,L,Canada,100,"Kubernetes, Statistics, Mathematics, Linux, Java",Associate,18,Retail,2024-08-26,2024-10-11,1541,9.1,Machine Intelligence Group -AI08992,AI Software Engineer,151803,USD,151803,SE,FL,United States,S,United States,0,"Computer Vision, Data Visualization, R, NLP, Deep Learning",Master,9,Manufacturing,2024-07-07,2024-07-25,2344,8,Neural Networks Co -AI08993,AI Product Manager,86780,USD,86780,MI,FL,Norway,S,Estonia,50,"Kubernetes, NLP, SQL",Associate,3,Telecommunications,2024-05-26,2024-06-22,2178,9,Quantum Computing Inc -AI08994,Deep Learning Engineer,92335,USD,92335,EN,FT,Ireland,L,Ireland,100,"AWS, Kubernetes, SQL, Scala",Bachelor,0,Retail,2024-09-08,2024-10-31,1318,8,Algorithmic Solutions -AI08995,Data Analyst,79908,USD,79908,MI,CT,South Korea,L,South Korea,100,"Hadoop, GCP, Computer Vision, Mathematics",Master,4,Technology,2024-06-21,2024-07-17,597,5.5,Autonomous Tech -AI08996,AI Consultant,139660,USD,139660,MI,CT,Denmark,L,Denmark,100,"Deep Learning, Python, MLOps",Master,4,Government,2025-02-01,2025-04-13,2451,6.1,Cognitive Computing -AI08997,Head of AI,55908,CAD,69885,EN,FL,Canada,S,Canada,50,"Linux, SQL, MLOps, Mathematics, Spark",PhD,0,Technology,2025-01-31,2025-03-22,1148,6.3,Cognitive Computing -AI08998,Data Engineer,88659,EUR,75360,MI,CT,Austria,L,Austria,100,"AWS, R, NLP, Data Visualization, Tableau",Bachelor,4,Telecommunications,2024-03-05,2024-04-16,2403,7.5,Neural Networks Co -AI08999,Machine Learning Engineer,205613,USD,205613,SE,PT,Norway,L,Australia,100,"Deep Learning, TensorFlow, R",Bachelor,8,Real Estate,2024-10-01,2024-11-06,1407,5.6,Digital Transformation LLC -AI09000,AI Software Engineer,90371,EUR,76815,EN,FT,Germany,L,Germany,100,"Kubernetes, Java, Mathematics, Scala, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-12-06,1818,7.1,DeepTech Ventures -AI09001,Data Analyst,88134,USD,88134,EN,FT,Sweden,L,Sweden,100,"Hadoop, Git, Computer Vision",Associate,0,Automotive,2025-02-11,2025-03-15,587,7.3,Autonomous Tech -AI09002,Computer Vision Engineer,42049,USD,42049,EN,FT,South Korea,M,South Korea,50,"TensorFlow, Statistics, SQL, Git",Associate,1,Government,2024-08-30,2024-11-05,2280,9.8,Cognitive Computing -AI09003,AI Consultant,53035,USD,53035,SE,PT,India,M,India,50,"SQL, Computer Vision, Tableau",PhD,8,Media,2024-03-28,2024-06-01,2121,9.3,Advanced Robotics -AI09004,Autonomous Systems Engineer,24765,USD,24765,EN,FL,India,S,India,100,"Docker, Python, Mathematics, Kubernetes",PhD,1,Energy,2024-12-11,2024-12-28,1299,10,Quantum Computing Inc -AI09005,Data Analyst,162474,USD,162474,SE,FT,Denmark,S,Colombia,100,"Computer Vision, R, Scala",Master,5,Transportation,2024-04-30,2024-06-30,1769,6.3,Predictive Systems -AI09006,Computer Vision Engineer,156947,USD,156947,EX,FT,Finland,M,Finland,100,"Mathematics, AWS, Deep Learning, Computer Vision",PhD,15,Transportation,2024-07-29,2024-10-05,820,7.6,Neural Networks Co -AI09007,Deep Learning Engineer,174776,USD,174776,EX,CT,Ireland,M,Ireland,50,"Computer Vision, GCP, Scala, Linux, PyTorch",Master,13,Real Estate,2024-08-16,2024-09-27,652,6.6,Future Systems -AI09008,AI Architect,70304,USD,70304,MI,FT,South Korea,L,South Korea,0,"Java, AWS, Tableau",Associate,3,Technology,2024-09-26,2024-11-04,610,9.5,Quantum Computing Inc -AI09009,ML Ops Engineer,172841,USD,172841,EX,PT,Israel,S,Israel,100,"Spark, PyTorch, Git",Master,16,Government,2024-06-24,2024-08-07,2356,8.7,Autonomous Tech -AI09010,AI Software Engineer,130736,EUR,111126,SE,FL,Austria,L,Austria,100,"Spark, R, Hadoop, Statistics, SQL",Master,6,Education,2024-04-28,2024-06-21,1538,9.1,Machine Intelligence Group -AI09011,AI Research Scientist,250854,EUR,213226,EX,PT,Austria,L,Austria,0,"Deep Learning, Kubernetes, Python, Git",PhD,17,Manufacturing,2025-03-10,2025-04-15,2094,6.8,TechCorp Inc -AI09012,AI Consultant,143001,SGD,185901,SE,PT,Singapore,L,Singapore,100,"MLOps, Java, Python, Computer Vision, Docker",Master,7,Healthcare,2024-02-08,2024-03-15,935,6.8,Future Systems -AI09013,AI Product Manager,248777,USD,248777,EX,FL,Sweden,M,Sweden,100,"Tableau, PyTorch, Docker, GCP, TensorFlow",Associate,11,Finance,2024-03-09,2024-04-05,1927,9.3,Future Systems -AI09014,AI Software Engineer,287219,SGD,373385,EX,FL,Singapore,L,Netherlands,50,"AWS, Scala, Mathematics, GCP, Docker",Bachelor,11,Transportation,2024-03-18,2024-05-26,1759,5.1,Autonomous Tech -AI09015,NLP Engineer,116645,USD,116645,MI,CT,Norway,S,Norway,100,"NLP, SQL, Tableau, AWS",Associate,2,Telecommunications,2024-09-28,2024-11-28,1035,10,Future Systems -AI09016,AI Product Manager,52061,USD,52061,EN,FL,South Korea,L,South Korea,100,"Computer Vision, SQL, Kubernetes, Git",PhD,0,Gaming,2024-05-10,2024-07-21,1489,7.8,Cloud AI Solutions -AI09017,AI Architect,104358,EUR,88704,SE,PT,France,S,Philippines,100,"Linux, R, Spark",Associate,5,Media,2024-12-07,2025-02-14,2437,6.8,DeepTech Ventures -AI09018,Machine Learning Engineer,64123,USD,64123,SE,PT,China,S,United States,50,"Computer Vision, Spark, Tableau",Master,7,Real Estate,2024-06-28,2024-08-14,715,7.3,Advanced Robotics -AI09019,AI Specialist,149941,USD,149941,SE,FT,Sweden,L,Ukraine,100,"Hadoop, SQL, TensorFlow, Spark",PhD,6,Gaming,2024-11-13,2024-12-14,1278,5.6,TechCorp Inc -AI09020,Deep Learning Engineer,56400,CAD,70500,EN,FL,Canada,M,Canada,50,"Tableau, NLP, PyTorch, Kubernetes",PhD,0,Technology,2024-01-08,2024-03-12,1632,8.3,DataVision Ltd -AI09021,AI Research Scientist,95750,USD,95750,SE,CT,Ireland,S,Thailand,0,"Docker, Python, Kubernetes, MLOps, Mathematics",Bachelor,6,Real Estate,2024-12-21,2025-01-08,2016,9.2,Predictive Systems -AI09022,AI Research Scientist,64039,EUR,54433,EN,FL,Germany,M,Germany,100,"SQL, Deep Learning, Git, PyTorch",PhD,0,Government,2025-03-24,2025-05-01,778,7.7,Cognitive Computing -AI09023,Data Engineer,56110,EUR,47694,EN,FL,Germany,M,Ireland,50,"Azure, Tableau, TensorFlow, Data Visualization, Deep Learning",PhD,1,Telecommunications,2024-12-23,2025-02-01,1111,7,Future Systems -AI09024,AI Specialist,124462,USD,124462,MI,PT,Denmark,S,Denmark,50,"NLP, AWS, Computer Vision, Python",Associate,4,Energy,2025-03-29,2025-05-26,1940,7.4,Neural Networks Co -AI09025,AI Consultant,190189,EUR,161661,EX,PT,Austria,M,Brazil,50,"Scala, Hadoop, Java, Linux",Master,11,Government,2024-02-21,2024-03-29,1380,9.4,Neural Networks Co -AI09026,AI Research Scientist,110339,USD,110339,SE,FL,United States,S,United States,100,"Kubernetes, PyTorch, TensorFlow, Python",Associate,9,Retail,2024-08-29,2024-10-12,1207,6.2,Quantum Computing Inc -AI09027,Data Engineer,198685,USD,198685,EX,CT,Israel,M,Israel,0,"MLOps, TensorFlow, Kubernetes",PhD,18,Retail,2024-09-11,2024-10-07,2290,8.6,Algorithmic Solutions -AI09028,Robotics Engineer,118424,USD,118424,MI,CT,United States,M,Egypt,100,"Statistics, NLP, Deep Learning",Master,4,Healthcare,2024-04-11,2024-05-28,1308,9.3,TechCorp Inc -AI09029,Research Scientist,77664,CHF,69898,EN,PT,Switzerland,M,Canada,50,"Azure, Spark, Python, MLOps, Computer Vision",Associate,0,Consulting,2024-09-09,2024-11-21,2200,5.3,Future Systems -AI09030,Research Scientist,60040,USD,60040,EN,FL,Israel,M,Israel,0,"Docker, Python, Azure, Hadoop, Deep Learning",Master,1,Education,2024-12-03,2025-01-08,1776,6.9,Machine Intelligence Group -AI09031,NLP Engineer,79791,USD,79791,EN,FL,Denmark,L,Denmark,100,"TensorFlow, Java, Scala, Statistics",Associate,0,Retail,2024-11-20,2024-12-10,1808,9.2,DeepTech Ventures -AI09032,AI Product Manager,124008,USD,124008,MI,FT,Denmark,L,Denmark,50,"GCP, Java, TensorFlow, Deep Learning, Computer Vision",Associate,2,Gaming,2024-02-13,2024-04-16,741,7.2,Cognitive Computing -AI09033,AI Consultant,35031,USD,35031,MI,FT,India,S,India,50,"Java, Mathematics, Deep Learning, Data Visualization, TensorFlow",Associate,4,Energy,2024-12-23,2025-02-18,699,7.6,AI Innovations -AI09034,Head of AI,67240,USD,67240,EN,FL,Norway,S,Norway,0,"AWS, Scala, Data Visualization",Bachelor,0,Education,2024-06-23,2024-08-27,1817,9.8,Quantum Computing Inc -AI09035,AI Specialist,94732,USD,94732,SE,PT,South Korea,M,South Korea,100,"Statistics, R, Deep Learning",PhD,8,Energy,2024-05-05,2024-05-21,1209,9.9,Advanced Robotics -AI09036,Autonomous Systems Engineer,129130,CHF,116217,MI,FT,Switzerland,L,Belgium,0,"Kubernetes, Java, AWS, Azure",Associate,3,Energy,2025-03-16,2025-05-07,1250,5.6,DataVision Ltd -AI09037,Data Analyst,228742,EUR,194431,EX,CT,Austria,L,Chile,50,"PyTorch, SQL, Java",PhD,19,Transportation,2025-04-19,2025-05-31,1839,5.5,DataVision Ltd -AI09038,Machine Learning Engineer,96859,SGD,125917,MI,FL,Singapore,M,Singapore,100,"Kubernetes, SQL, Deep Learning, Hadoop, PyTorch",Master,4,Education,2024-08-17,2024-10-14,2037,9,Machine Intelligence Group -AI09039,AI Software Engineer,86548,JPY,9520280,EN,FL,Japan,L,Japan,0,"TensorFlow, Spark, NLP, PyTorch, Data Visualization",Associate,1,Education,2024-04-29,2024-05-30,2115,5.4,DataVision Ltd -AI09040,Deep Learning Engineer,145427,EUR,123613,SE,CT,France,L,France,0,"Git, Spark, Computer Vision",Associate,9,Telecommunications,2024-01-10,2024-01-30,1730,7.9,AI Innovations -AI09041,Head of AI,144726,USD,144726,SE,FL,South Korea,L,South Korea,0,"Computer Vision, AWS, Docker, PyTorch, Hadoop",Associate,7,Healthcare,2024-04-17,2024-06-28,2490,6.8,Neural Networks Co -AI09042,Data Scientist,118275,USD,118275,MI,FL,Finland,L,France,100,"R, Linux, Computer Vision",Master,2,Real Estate,2024-09-11,2024-11-04,556,7.7,Algorithmic Solutions -AI09043,Head of AI,90563,CHF,81507,EN,FL,Switzerland,L,Switzerland,100,"Git, Linux, AWS, Statistics, Hadoop",Bachelor,0,Healthcare,2024-09-14,2024-11-16,1631,7.9,Quantum Computing Inc -AI09044,Head of AI,107754,USD,107754,SE,PT,South Korea,S,South Korea,100,"Python, Scala, Linux",Master,9,Energy,2024-08-20,2024-09-20,1052,8.4,Cognitive Computing -AI09045,AI Research Scientist,63613,USD,63613,EN,FT,Sweden,S,Sweden,50,"Linux, PyTorch, TensorFlow",Bachelor,1,Finance,2024-04-23,2024-06-13,2070,5.3,Neural Networks Co -AI09046,Research Scientist,185435,USD,185435,EX,CT,Ireland,M,Canada,0,"Spark, Docker, Python",Bachelor,15,Technology,2024-09-11,2024-10-08,1991,8.2,Advanced Robotics -AI09047,Autonomous Systems Engineer,46410,USD,46410,SE,PT,India,M,India,0,"Scala, Spark, Git, Azure",Associate,9,Energy,2024-08-19,2024-09-09,1622,6.3,Smart Analytics -AI09048,ML Ops Engineer,143416,USD,143416,EX,PT,Sweden,S,Sweden,100,"MLOps, R, Computer Vision",PhD,18,Real Estate,2024-11-09,2024-12-08,2151,5.3,Digital Transformation LLC -AI09049,AI Consultant,76825,USD,76825,EN,CT,Norway,S,Norway,100,"Computer Vision, R, SQL, Linux, Docker",Associate,0,Real Estate,2024-04-05,2024-06-02,1986,5.8,Digital Transformation LLC -AI09050,NLP Engineer,198466,CHF,178619,SE,FL,Switzerland,M,Switzerland,0,"SQL, Tableau, Computer Vision, MLOps",Bachelor,7,Government,2024-04-26,2024-07-05,716,9.7,Future Systems -AI09051,Data Analyst,130066,CHF,117059,MI,CT,Switzerland,S,Switzerland,50,"Mathematics, Hadoop, Python",Master,2,Education,2024-06-02,2024-07-05,916,7.7,Advanced Robotics -AI09052,AI Specialist,112733,EUR,95823,MI,FL,Germany,L,Germany,50,"AWS, Git, PyTorch",PhD,4,Government,2024-03-13,2024-05-14,2111,6.3,Quantum Computing Inc -AI09053,Data Scientist,46914,USD,46914,EN,PT,Finland,S,United States,100,"Python, Linux, Spark, Deep Learning",Master,1,Finance,2024-02-26,2024-03-27,2063,5.8,Smart Analytics -AI09054,AI Specialist,275297,USD,275297,EX,FL,Israel,L,Vietnam,50,"Tableau, Python, Kubernetes, Computer Vision",Associate,19,Transportation,2025-01-22,2025-04-03,2364,7.2,Cloud AI Solutions -AI09055,AI Product Manager,161001,GBP,120751,EX,PT,United Kingdom,S,United Kingdom,50,"Deep Learning, Azure, Kubernetes, Java, SQL",Bachelor,10,Technology,2024-03-16,2024-04-11,1985,9.6,Algorithmic Solutions -AI09056,Data Analyst,73717,SGD,95832,EN,PT,Singapore,M,Ukraine,0,"Python, Hadoop, Data Visualization",Master,0,Government,2025-03-05,2025-03-22,2321,8.3,Cognitive Computing -AI09057,Data Engineer,173430,AUD,234131,EX,FL,Australia,S,Indonesia,100,"Azure, Spark, Computer Vision",Associate,16,Media,2024-11-01,2024-12-24,1601,6.3,TechCorp Inc -AI09058,Data Analyst,289418,USD,289418,EX,FT,Sweden,L,Sweden,50,"Hadoop, Spark, TensorFlow, Linux",Associate,10,Healthcare,2024-07-13,2024-08-25,1193,5.4,AI Innovations -AI09059,Autonomous Systems Engineer,25689,USD,25689,MI,FL,India,M,India,0,"Scala, GCP, Tableau, Kubernetes, Java",Associate,4,Automotive,2024-05-19,2024-06-18,1208,9.6,TechCorp Inc -AI09060,Data Engineer,60503,USD,60503,EN,FT,Ireland,M,Ireland,50,"Java, Statistics, Computer Vision, R, SQL",PhD,1,Transportation,2024-02-25,2024-03-17,2322,9.1,DataVision Ltd -AI09061,AI Architect,278853,USD,278853,EX,PT,Sweden,L,Sweden,50,"Python, Tableau, SQL",Associate,16,Manufacturing,2025-03-05,2025-05-04,1316,9.2,Machine Intelligence Group -AI09062,NLP Engineer,84797,EUR,72077,MI,CT,France,L,France,50,"TensorFlow, Python, Hadoop, Kubernetes",Bachelor,4,Real Estate,2025-04-08,2025-05-29,1787,5.1,TechCorp Inc -AI09063,Data Engineer,112505,EUR,95629,SE,FT,France,S,France,50,"Data Visualization, Scala, AWS, TensorFlow, Kubernetes",Associate,5,Healthcare,2024-05-19,2024-06-28,2296,6.5,DeepTech Ventures -AI09064,Autonomous Systems Engineer,322176,USD,322176,EX,FL,United States,L,United States,100,"Python, Hadoop, SQL",PhD,19,Finance,2024-09-04,2024-09-23,2234,9.4,Smart Analytics -AI09065,Machine Learning Engineer,153151,USD,153151,SE,PT,Sweden,L,Sweden,100,"SQL, Spark, MLOps, Data Visualization",Associate,9,Manufacturing,2024-08-26,2024-10-02,2125,7.7,Advanced Robotics -AI09066,AI Software Engineer,89864,USD,89864,EN,CT,Norway,L,Hungary,100,"Python, Docker, Tableau, AWS",PhD,0,Technology,2025-04-02,2025-04-19,2399,9.8,Digital Transformation LLC -AI09067,Data Scientist,103238,SGD,134209,MI,PT,Singapore,M,Japan,100,"Azure, Statistics, Hadoop, R",Master,3,Consulting,2025-01-26,2025-04-06,924,5.3,Autonomous Tech -AI09068,AI Specialist,62237,USD,62237,MI,FT,South Korea,S,Hungary,100,"Statistics, Tableau, SQL, Spark, Data Visualization",Master,4,Energy,2025-03-10,2025-04-13,1059,9.5,Autonomous Tech -AI09069,ML Ops Engineer,250692,EUR,213088,EX,FL,Netherlands,M,Netherlands,50,"Linux, GCP, Python, Mathematics, Azure",PhD,11,Healthcare,2024-12-11,2024-12-28,1030,8,Machine Intelligence Group -AI09070,ML Ops Engineer,75599,USD,75599,MI,PT,Ireland,M,South Africa,0,"Java, Kubernetes, Mathematics, SQL",Master,2,Consulting,2024-05-01,2024-07-12,1978,8.9,Advanced Robotics -AI09071,AI Product Manager,170126,CHF,153113,SE,FT,Switzerland,M,Switzerland,0,"Data Visualization, Statistics, NLP, MLOps",Associate,9,Healthcare,2024-03-14,2024-05-15,1405,5.6,Digital Transformation LLC -AI09072,Machine Learning Engineer,112438,EUR,95572,MI,CT,France,L,France,100,"Python, Statistics, AWS, Kubernetes, NLP",Master,4,Government,2024-04-26,2024-06-06,1829,9.3,DataVision Ltd -AI09073,AI Specialist,202327,USD,202327,EX,PT,Israel,M,Israel,0,"PyTorch, Linux, R",Associate,17,Retail,2024-05-20,2024-06-24,520,7.9,Quantum Computing Inc -AI09074,Head of AI,49609,EUR,42168,EN,CT,France,S,France,100,"Python, Java, NLP",Associate,1,Retail,2024-01-11,2024-03-08,1480,6.9,Machine Intelligence Group -AI09075,Data Analyst,101267,USD,101267,EX,FL,South Korea,S,Indonesia,100,"GCP, Azure, NLP, SQL, R",Bachelor,12,Retail,2024-05-01,2024-06-13,1534,8.8,DataVision Ltd -AI09076,Data Engineer,175412,EUR,149100,EX,FT,Germany,S,Germany,100,"Statistics, MLOps, Java",Associate,17,Manufacturing,2025-03-25,2025-05-04,2138,7.7,Cloud AI Solutions -AI09077,Robotics Engineer,132763,SGD,172592,SE,CT,Singapore,S,Singapore,50,"Hadoop, Tableau, R, Deep Learning",Associate,6,Manufacturing,2024-03-19,2024-05-10,1912,7.5,DeepTech Ventures -AI09078,Head of AI,146012,EUR,124110,EX,CT,Austria,S,United States,50,"Tableau, Linux, Java, R",Master,19,Retail,2025-02-15,2025-04-14,955,9.4,TechCorp Inc -AI09079,AI Architect,128830,USD,128830,SE,PT,Finland,S,Finland,0,"Python, TensorFlow, GCP, Java",Bachelor,9,Consulting,2024-01-15,2024-03-10,2249,6.9,AI Innovations -AI09080,Data Analyst,73935,EUR,62845,MI,PT,Germany,S,Germany,50,"PyTorch, Scala, MLOps",Master,2,Technology,2024-09-13,2024-11-07,1797,8.9,Cognitive Computing -AI09081,Machine Learning Researcher,20704,USD,20704,EN,FL,India,S,India,100,"Hadoop, Linux, GCP, Statistics",Master,0,Education,2024-02-22,2024-03-18,1935,5.9,Digital Transformation LLC -AI09082,AI Software Engineer,106038,USD,106038,EN,PT,United States,L,United States,50,"Spark, R, Deep Learning",Bachelor,1,Telecommunications,2024-03-24,2024-04-15,1621,5.5,Smart Analytics -AI09083,Machine Learning Researcher,256638,USD,256638,EX,FT,United States,L,United States,0,"Docker, Scala, Statistics, Data Visualization",Associate,18,Transportation,2024-04-13,2024-05-09,1801,9.7,DeepTech Ventures -AI09084,ML Ops Engineer,160139,CHF,144125,MI,FL,Switzerland,L,Japan,0,"Azure, Scala, NLP, Deep Learning, Git",Master,4,Automotive,2024-07-12,2024-09-06,1577,7.8,Smart Analytics -AI09085,Data Engineer,125643,USD,125643,MI,CT,United States,L,United States,100,"Linux, Mathematics, Deep Learning, Python, Statistics",Master,2,Media,2024-12-12,2025-02-05,2246,9.7,Machine Intelligence Group -AI09086,Research Scientist,33763,USD,33763,EN,FT,China,M,South Africa,50,"Java, Tableau, AWS, Scala, Linux",Associate,1,Automotive,2024-08-19,2024-09-26,1405,7.1,TechCorp Inc -AI09087,Computer Vision Engineer,51407,USD,51407,EN,PT,Sweden,M,Sweden,100,"Linux, Mathematics, SQL, MLOps",Associate,0,Gaming,2024-07-22,2024-09-28,1140,8.2,Autonomous Tech -AI09088,Data Scientist,93819,USD,93819,SE,FL,Finland,S,Finland,50,"Kubernetes, Java, MLOps, Scala, GCP",Bachelor,9,Manufacturing,2024-06-01,2024-06-18,1272,8.9,DataVision Ltd -AI09089,Data Engineer,108668,USD,108668,MI,PT,United States,S,United States,100,"Kubernetes, TensorFlow, GCP",Associate,3,Energy,2024-06-12,2024-08-13,2463,9,Predictive Systems -AI09090,AI Consultant,128578,AUD,173580,EX,PT,Australia,S,Australia,0,"Kubernetes, SQL, NLP",PhD,19,Technology,2024-11-24,2024-12-16,853,9.9,Predictive Systems -AI09091,AI Specialist,34167,USD,34167,MI,FL,China,M,China,50,"Linux, Scala, Spark, Git",PhD,2,Automotive,2024-09-11,2024-11-02,1155,6.7,Smart Analytics -AI09092,Deep Learning Engineer,82557,JPY,9081270,MI,FL,Japan,S,Colombia,50,"MLOps, NLP, R",Master,3,Manufacturing,2024-01-02,2024-02-29,1336,5.5,Cloud AI Solutions -AI09093,Machine Learning Engineer,73184,EUR,62206,EN,FL,Austria,M,Austria,100,"Python, SQL, GCP",Master,0,Automotive,2024-10-20,2024-12-10,2376,7.1,Predictive Systems -AI09094,Research Scientist,185487,EUR,157664,EX,PT,France,L,France,50,"Python, Deep Learning, Data Visualization, Java",PhD,10,Gaming,2024-07-21,2024-08-18,2304,8.6,TechCorp Inc -AI09095,Computer Vision Engineer,184041,JPY,20244510,EX,PT,Japan,M,Sweden,0,"TensorFlow, Java, Linux",PhD,13,Energy,2024-10-28,2024-12-13,1131,6.9,Machine Intelligence Group -AI09096,Data Analyst,63990,USD,63990,EN,PT,South Korea,L,Czech Republic,0,"Linux, Mathematics, Tableau, MLOps",PhD,0,Real Estate,2024-07-18,2024-09-08,1360,8.4,Autonomous Tech -AI09097,Deep Learning Engineer,77439,USD,77439,EN,FT,Denmark,L,Denmark,100,"Tableau, Git, Linux",PhD,1,Technology,2024-08-13,2024-09-08,526,10,Predictive Systems -AI09098,Machine Learning Researcher,54169,CAD,67711,EN,PT,Canada,S,Switzerland,100,"Spark, Azure, SQL, Hadoop, Statistics",PhD,0,Gaming,2024-08-28,2024-10-20,1818,7.1,Predictive Systems -AI09099,Deep Learning Engineer,97993,EUR,83294,SE,PT,Germany,S,Germany,0,"Kubernetes, Python, TensorFlow, Statistics",Master,6,Government,2024-09-24,2024-11-25,1849,6.6,Cognitive Computing -AI09100,Data Scientist,79820,JPY,8780200,EN,PT,Japan,L,Japan,100,"Azure, Git, R, Java, Scala",Master,1,Technology,2024-10-12,2024-12-04,1735,6.9,DataVision Ltd -AI09101,Principal Data Scientist,104484,USD,104484,EN,FT,United States,L,United States,0,"PyTorch, TensorFlow, R, Scala",Master,1,Automotive,2024-03-14,2024-03-29,1370,5.8,Smart Analytics -AI09102,Machine Learning Researcher,103925,USD,103925,MI,FL,Sweden,M,United Kingdom,0,"R, PyTorch, Mathematics",Master,3,Telecommunications,2024-06-17,2024-08-25,1236,8.4,TechCorp Inc -AI09103,AI Architect,99884,EUR,84901,SE,FL,Germany,S,Germany,0,"Spark, Azure, NLP, Mathematics, SQL",Associate,9,Manufacturing,2025-03-13,2025-05-11,2448,7.6,TechCorp Inc -AI09104,Machine Learning Researcher,153139,JPY,16845290,SE,FL,Japan,L,Japan,0,"Linux, Python, Deep Learning, Statistics, Computer Vision",Associate,5,Technology,2025-04-25,2025-06-21,2037,7.4,Future Systems -AI09105,ML Ops Engineer,61944,EUR,52652,EN,FL,France,L,France,50,"Deep Learning, Hadoop, PyTorch, NLP",Master,0,Retail,2024-09-28,2024-10-18,2126,6.7,TechCorp Inc -AI09106,Data Engineer,65282,EUR,55490,EN,PT,Austria,M,Austria,50,"Docker, Tableau, NLP",Master,1,Automotive,2024-05-21,2024-08-02,837,8.6,Quantum Computing Inc -AI09107,NLP Engineer,96292,EUR,81848,SE,CT,Germany,S,Germany,100,"NLP, Deep Learning, Scala",Bachelor,9,Consulting,2024-05-18,2024-07-17,1311,6.3,Algorithmic Solutions -AI09108,ML Ops Engineer,157918,CHF,142126,MI,CT,Switzerland,L,Switzerland,100,"Docker, Git, Mathematics",PhD,4,Technology,2024-07-16,2024-08-28,1630,5.3,Cloud AI Solutions -AI09109,Robotics Engineer,68722,AUD,92775,EN,FT,Australia,M,Australia,100,"Python, Spark, Java",Master,0,Education,2024-04-17,2024-05-18,2294,7,Neural Networks Co -AI09110,Computer Vision Engineer,34572,USD,34572,MI,FT,India,S,Austria,50,"Statistics, Python, TensorFlow",PhD,4,Manufacturing,2025-04-13,2025-05-02,1135,5.9,Predictive Systems -AI09111,AI Research Scientist,46646,USD,46646,MI,CT,China,L,China,50,"Deep Learning, MLOps, GCP, NLP",PhD,4,Telecommunications,2025-04-10,2025-05-23,1392,5.4,TechCorp Inc -AI09112,AI Architect,235688,EUR,200335,EX,PT,France,M,Argentina,0,"AWS, Git, Data Visualization, Statistics",Master,15,Transportation,2025-03-24,2025-05-18,2377,6.6,Autonomous Tech -AI09113,NLP Engineer,273202,USD,273202,EX,FT,Israel,L,Russia,100,"Scala, R, Azure, SQL",PhD,17,Transportation,2024-04-04,2024-05-13,717,5.6,DataVision Ltd -AI09114,Principal Data Scientist,191484,CAD,239355,EX,FT,Canada,S,Canada,0,"NLP, Spark, Scala, TensorFlow, Deep Learning",Associate,11,Manufacturing,2025-03-03,2025-04-29,674,9.1,AI Innovations -AI09115,AI Research Scientist,59597,USD,59597,EX,CT,India,M,Israel,0,"MLOps, Scala, TensorFlow",Bachelor,12,Manufacturing,2024-04-19,2024-06-24,1996,7,Smart Analytics -AI09116,Autonomous Systems Engineer,152712,USD,152712,EX,FL,Ireland,S,Ireland,50,"Deep Learning, Python, Data Visualization, Git, R",Master,12,Transportation,2024-05-13,2024-07-23,2066,7.7,DataVision Ltd -AI09117,Machine Learning Engineer,260073,EUR,221062,EX,FL,Netherlands,M,Netherlands,50,"Kubernetes, TensorFlow, Computer Vision, Data Visualization",Associate,14,Government,2024-04-27,2024-06-16,2072,9.8,Digital Transformation LLC -AI09118,Principal Data Scientist,21379,USD,21379,EN,PT,India,M,India,50,"Computer Vision, GCP, Hadoop, Python, Data Visualization",PhD,1,Healthcare,2024-06-02,2024-07-05,785,5.4,Machine Intelligence Group -AI09119,Machine Learning Researcher,39561,USD,39561,MI,FT,China,L,China,100,"Computer Vision, TensorFlow, Hadoop",Bachelor,4,Retail,2024-09-21,2024-11-03,930,8.7,Smart Analytics -AI09120,AI Software Engineer,126547,EUR,107565,MI,CT,Germany,L,Germany,50,"Linux, Docker, PyTorch",Bachelor,4,Telecommunications,2025-04-24,2025-07-06,1681,7,Algorithmic Solutions -AI09121,Autonomous Systems Engineer,187489,USD,187489,EX,PT,South Korea,S,South Korea,50,"Java, Kubernetes, Tableau",PhD,17,Energy,2024-08-20,2024-10-06,2373,10,TechCorp Inc -AI09122,NLP Engineer,131267,USD,131267,SE,FL,United States,M,United States,0,"SQL, R, Linux, GCP",Bachelor,8,Finance,2024-01-24,2024-03-11,1746,9,Autonomous Tech -AI09123,AI Architect,77519,USD,77519,EN,FL,Finland,L,Finland,0,"Azure, Kubernetes, Scala",Associate,0,Finance,2025-03-21,2025-05-12,1803,6.2,DeepTech Ventures -AI09124,ML Ops Engineer,108940,AUD,147069,MI,PT,Australia,L,Kenya,100,"Hadoop, Java, Tableau",Bachelor,2,Government,2024-02-24,2024-04-24,2250,8.3,DataVision Ltd -AI09125,Machine Learning Researcher,151325,GBP,113494,EX,FL,United Kingdom,M,Ukraine,0,"Hadoop, PyTorch, Deep Learning",PhD,12,Real Estate,2025-01-05,2025-02-23,2290,8.5,TechCorp Inc -AI09126,Head of AI,164274,USD,164274,EX,FL,Ireland,L,Finland,50,"Python, TensorFlow, PyTorch, Deep Learning",Master,13,Automotive,2024-11-15,2024-12-17,930,6.2,Future Systems -AI09127,Principal Data Scientist,96078,AUD,129705,MI,CT,Australia,S,Australia,0,"Scala, AWS, Azure, R",Master,2,Telecommunications,2024-02-19,2024-03-15,2296,6.6,TechCorp Inc -AI09128,Principal Data Scientist,234097,EUR,198982,EX,FT,Netherlands,S,Luxembourg,100,"Hadoop, Scala, Deep Learning, R, AWS",PhD,17,Manufacturing,2024-09-16,2024-11-26,1852,5.8,Advanced Robotics -AI09129,Research Scientist,285597,USD,285597,EX,CT,Norway,M,Mexico,50,"Kubernetes, Deep Learning, TensorFlow, Scala",Associate,17,Energy,2024-04-09,2024-06-11,1210,7.6,Future Systems -AI09130,Autonomous Systems Engineer,273922,USD,273922,EX,FT,Norway,L,Norway,100,"Python, Docker, Hadoop, Deep Learning, Mathematics",Associate,16,Energy,2024-04-13,2024-05-11,1232,5.6,Quantum Computing Inc -AI09131,AI Software Engineer,61758,EUR,52494,MI,PT,Austria,S,Austria,50,"MLOps, Deep Learning, PyTorch, GCP",PhD,4,Energy,2025-03-06,2025-05-03,2361,7.4,Predictive Systems -AI09132,Autonomous Systems Engineer,216376,EUR,183920,EX,PT,Austria,L,Austria,100,"SQL, Azure, Kubernetes, Docker",Master,15,Transportation,2024-05-28,2024-07-21,2425,6.2,Autonomous Tech -AI09133,Data Engineer,137572,USD,137572,SE,PT,Denmark,S,Kenya,50,"Data Visualization, Azure, Python",Bachelor,7,Education,2025-04-29,2025-07-11,1115,8.3,Neural Networks Co -AI09134,Machine Learning Researcher,206544,JPY,22719840,EX,CT,Japan,S,Japan,50,"MLOps, SQL, TensorFlow, Data Visualization, Statistics",Master,16,Gaming,2024-06-13,2024-07-10,2087,6.2,DataVision Ltd -AI09135,ML Ops Engineer,141517,USD,141517,SE,FT,South Korea,L,Colombia,0,"Kubernetes, Python, AWS",Associate,6,Gaming,2024-04-07,2024-06-11,822,6.1,DeepTech Ventures -AI09136,Research Scientist,87198,EUR,74118,MI,PT,Austria,L,Austria,50,"Kubernetes, Spark, SQL, NLP",Master,4,Automotive,2025-04-11,2025-05-31,1541,9.8,Predictive Systems -AI09137,Machine Learning Researcher,87108,EUR,74042,EN,PT,Netherlands,L,Netherlands,0,"PyTorch, Java, Scala, Docker, TensorFlow",Bachelor,0,Gaming,2024-09-06,2024-11-16,2018,7.6,TechCorp Inc -AI09138,Robotics Engineer,214335,EUR,182185,EX,CT,Austria,S,Denmark,0,"Hadoop, AWS, SQL",Associate,15,Education,2024-10-30,2024-12-27,1232,9.5,Machine Intelligence Group -AI09139,AI Specialist,153507,CAD,191884,EX,FT,Canada,S,Canada,100,"SQL, Docker, Data Visualization, MLOps",PhD,15,Consulting,2024-09-04,2024-11-09,2064,8.6,Cloud AI Solutions -AI09140,Data Analyst,73451,EUR,62433,MI,PT,Austria,S,Austria,0,"Git, Python, Data Visualization, Azure, Tableau",PhD,2,Energy,2024-11-23,2024-12-26,2401,7.7,DeepTech Ventures -AI09141,Robotics Engineer,141812,SGD,184356,SE,PT,Singapore,M,Singapore,0,"Mathematics, Spark, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-02-17,2364,8.8,Future Systems -AI09142,AI Software Engineer,185928,USD,185928,EX,PT,South Korea,M,China,50,"Spark, Scala, Statistics, Hadoop",Master,11,Consulting,2024-05-08,2024-07-17,1047,8.2,Algorithmic Solutions -AI09143,Machine Learning Engineer,114515,USD,114515,SE,PT,Israel,S,Israel,50,"Tableau, NLP, GCP, Computer Vision",Bachelor,7,Education,2024-02-02,2024-03-01,961,7.9,AI Innovations -AI09144,Data Analyst,175467,EUR,149147,EX,CT,Germany,S,Germany,0,"Git, Statistics, Tableau, TensorFlow",Master,15,Retail,2025-02-10,2025-03-05,2273,6.5,DeepTech Ventures -AI09145,Head of AI,88766,EUR,75451,MI,CT,Netherlands,L,Netherlands,0,"R, AWS, Data Visualization",Associate,2,Transportation,2024-10-14,2024-11-16,850,9,Digital Transformation LLC -AI09146,Computer Vision Engineer,111355,JPY,12249050,MI,FL,Japan,M,Poland,0,"Python, PyTorch, Deep Learning, GCP",PhD,4,Telecommunications,2025-01-16,2025-02-20,2186,7.2,Future Systems -AI09147,Machine Learning Engineer,128271,CAD,160339,SE,FT,Canada,S,Canada,100,"Data Visualization, NLP, Tableau",Bachelor,5,Government,2024-11-15,2024-12-07,837,7.7,Advanced Robotics -AI09148,Machine Learning Engineer,123580,EUR,105043,SE,FT,France,M,France,0,"NLP, Spark, Deep Learning",Master,9,Education,2025-03-13,2025-05-21,1067,8.3,AI Innovations -AI09149,ML Ops Engineer,77084,AUD,104063,EN,CT,Australia,L,Australia,0,"Data Visualization, NLP, TensorFlow, Azure",Bachelor,1,Consulting,2024-07-02,2024-07-20,1859,7.6,DataVision Ltd -AI09150,AI Specialist,46762,USD,46762,EN,PT,Ireland,S,Ireland,100,"PyTorch, SQL, Deep Learning, Scala, Tableau",Associate,1,Government,2025-03-26,2025-05-25,1596,9.3,Machine Intelligence Group -AI09151,AI Consultant,218952,USD,218952,EX,PT,Ireland,M,Ireland,50,"MLOps, AWS, SQL, Mathematics, Azure",Bachelor,13,Government,2025-01-30,2025-03-21,628,7.9,Advanced Robotics -AI09152,AI Product Manager,61455,SGD,79892,EN,FT,Singapore,S,Australia,50,"Hadoop, Tableau, Spark, Linux, Computer Vision",Bachelor,1,Finance,2024-04-19,2024-06-14,1344,5.6,Predictive Systems -AI09153,Machine Learning Engineer,66187,USD,66187,EX,PT,China,M,China,100,"Azure, Git, Tableau, SQL",Bachelor,17,Finance,2024-11-22,2024-12-11,1180,6.7,Cloud AI Solutions -AI09154,NLP Engineer,130172,SGD,169224,SE,FT,Singapore,S,Japan,50,"GCP, Java, MLOps, Computer Vision",PhD,8,Automotive,2025-03-01,2025-05-09,1102,9.1,TechCorp Inc -AI09155,Machine Learning Engineer,77763,JPY,8553930,EN,FT,Japan,L,Japan,100,"SQL, PyTorch, Mathematics, Docker",Associate,1,Real Estate,2025-03-15,2025-05-08,648,5.8,Autonomous Tech -AI09156,Research Scientist,100848,USD,100848,MI,CT,Norway,M,Norway,100,"Docker, Git, AWS",PhD,2,Energy,2024-08-19,2024-09-28,752,6.5,Smart Analytics -AI09157,Machine Learning Engineer,144916,JPY,15940760,EX,FT,Japan,S,Japan,50,"PyTorch, Scala, Python",PhD,18,Retail,2025-02-06,2025-03-23,1976,5.7,Quantum Computing Inc -AI09158,Autonomous Systems Engineer,241167,SGD,313517,EX,PT,Singapore,S,Israel,100,"Spark, Statistics, Computer Vision, Git",Associate,17,Technology,2024-06-11,2024-07-22,2278,8.5,Algorithmic Solutions -AI09159,Head of AI,122631,GBP,91973,MI,FL,United Kingdom,L,United Kingdom,0,"Statistics, SQL, Deep Learning, MLOps",Associate,3,Healthcare,2025-03-21,2025-05-10,1649,7.5,AI Innovations -AI09160,ML Ops Engineer,52113,USD,52113,SE,FL,India,M,India,50,"Computer Vision, GCP, Tableau, NLP",Master,9,Telecommunications,2024-05-01,2024-05-19,1707,5.2,Digital Transformation LLC -AI09161,AI Specialist,131239,AUD,177173,SE,PT,Australia,S,Latvia,0,"Spark, Hadoop, TensorFlow, MLOps",Associate,8,Consulting,2024-12-07,2025-02-16,1374,6.6,Autonomous Tech -AI09162,AI Architect,39306,USD,39306,SE,CT,India,S,India,100,"Linux, MLOps, Tableau, AWS, Git",PhD,7,Automotive,2025-04-23,2025-05-24,703,6.6,Smart Analytics -AI09163,Machine Learning Engineer,55092,EUR,46828,EN,FT,Austria,M,Austria,100,"Python, GCP, Mathematics, MLOps",Bachelor,0,Automotive,2024-07-24,2024-09-15,1765,7.5,Quantum Computing Inc -AI09164,Research Scientist,155977,AUD,210569,SE,CT,Australia,L,Australia,50,"Azure, Mathematics, Data Visualization",PhD,7,Real Estate,2024-12-22,2025-02-15,564,9.6,AI Innovations -AI09165,AI Architect,92563,USD,92563,EN,FL,United States,M,United States,100,"Python, Kubernetes, Computer Vision, NLP",Associate,0,Education,2024-09-29,2024-10-17,2497,9.7,Cloud AI Solutions -AI09166,Data Scientist,56883,USD,56883,EN,FL,Finland,M,Finland,50,"Tableau, Hadoop, Python",PhD,1,Energy,2024-08-25,2024-10-24,2304,5.1,Advanced Robotics -AI09167,AI Research Scientist,63119,USD,63119,EN,FT,Norway,S,Norway,0,"Docker, MLOps, Scala, Computer Vision, Azure",Associate,1,Finance,2024-04-17,2024-05-28,1624,9.1,Algorithmic Solutions -AI09168,Robotics Engineer,124054,USD,124054,SE,CT,Finland,S,Argentina,0,"Python, GCP, Computer Vision",Bachelor,7,Energy,2024-09-10,2024-10-17,1475,8.2,DataVision Ltd -AI09169,Head of AI,70626,AUD,95345,EN,CT,Australia,S,Australia,100,"GCP, TensorFlow, MLOps, Python",Master,0,Government,2025-03-21,2025-04-13,2467,9.3,DataVision Ltd -AI09170,AI Consultant,95105,EUR,80839,MI,PT,Germany,M,China,50,"Spark, SQL, MLOps, Hadoop, Statistics",Master,3,Gaming,2024-02-26,2024-03-18,1527,5.9,Smart Analytics -AI09171,AI Architect,142966,GBP,107225,SE,FL,United Kingdom,M,Canada,0,"Computer Vision, SQL, Deep Learning, Git, Hadoop",Bachelor,6,Energy,2024-02-27,2024-04-18,1558,8.4,Machine Intelligence Group -AI09172,Autonomous Systems Engineer,30269,USD,30269,EN,FL,India,L,Israel,50,"NLP, Kubernetes, TensorFlow, MLOps, Git",Master,1,Retail,2024-12-02,2024-12-23,1413,6.7,Future Systems -AI09173,Computer Vision Engineer,172669,USD,172669,SE,FL,Norway,M,Norway,0,"Docker, PyTorch, Java, Python, Scala",Bachelor,8,Real Estate,2024-07-22,2024-08-16,1753,9.4,Future Systems -AI09174,Robotics Engineer,129725,USD,129725,EX,PT,Ireland,S,Ireland,50,"Scala, Azure, Tableau, NLP",Master,14,Media,2024-06-24,2024-09-02,1349,8.5,Digital Transformation LLC -AI09175,Computer Vision Engineer,63167,SGD,82117,EN,CT,Singapore,S,Singapore,100,"NLP, GCP, Deep Learning, Python, Hadoop",Master,0,Retail,2024-09-27,2024-12-09,686,8.7,Neural Networks Co -AI09176,AI Specialist,258786,USD,258786,EX,FL,Norway,S,Norway,50,"Linux, Kubernetes, PyTorch",Master,10,Technology,2024-04-22,2024-05-08,1899,5.4,Cognitive Computing -AI09177,AI Research Scientist,44253,USD,44253,MI,CT,China,S,Finland,50,"Hadoop, Python, Azure, Kubernetes, Scala",Bachelor,2,Energy,2025-01-02,2025-02-15,1158,8.5,Quantum Computing Inc -AI09178,AI Consultant,130321,GBP,97741,SE,FL,United Kingdom,S,United Kingdom,50,"Scala, MLOps, SQL",Master,7,Technology,2024-04-29,2024-05-18,2064,8.7,Advanced Robotics -AI09179,Research Scientist,163239,EUR,138753,EX,FT,France,M,France,0,"Linux, Git, Data Visualization, Deep Learning",Master,13,Healthcare,2024-09-06,2024-11-17,766,9,Smart Analytics -AI09180,Research Scientist,88353,CAD,110441,MI,FL,Canada,S,Philippines,100,"R, Linux, SQL, Git, AWS",Bachelor,4,Manufacturing,2024-05-06,2024-05-31,1684,7.6,Algorithmic Solutions -AI09181,Machine Learning Engineer,99421,CAD,124276,MI,PT,Canada,M,Canada,0,"NLP, GCP, Scala, Tableau",Master,4,Retail,2024-04-20,2024-05-16,1672,6.4,Machine Intelligence Group -AI09182,Deep Learning Engineer,92458,EUR,78589,SE,FL,Germany,S,Germany,0,"Scala, PyTorch, Hadoop",PhD,7,Transportation,2024-05-10,2024-07-15,1982,9.8,Cloud AI Solutions -AI09183,Autonomous Systems Engineer,176930,JPY,19462300,SE,FL,Japan,L,Japan,50,"Kubernetes, Deep Learning, MLOps, Azure",Master,7,Healthcare,2024-03-24,2024-04-25,1765,6.9,DeepTech Ventures -AI09184,Machine Learning Engineer,87956,USD,87956,MI,CT,Israel,S,Israel,50,"Spark, Python, Data Visualization",Master,4,Telecommunications,2024-01-16,2024-02-22,1350,9.5,Algorithmic Solutions -AI09185,Data Scientist,178060,USD,178060,SE,FT,Norway,L,Norway,100,"Spark, Git, NLP, Statistics",Master,7,Energy,2025-01-28,2025-04-11,2470,7.7,Algorithmic Solutions -AI09186,Robotics Engineer,274887,USD,274887,EX,FT,Finland,L,Finland,50,"Python, TensorFlow, Git, Linux, Azure",Bachelor,18,Media,2025-03-19,2025-05-06,524,5.2,Quantum Computing Inc -AI09187,AI Software Engineer,111752,USD,111752,MI,PT,Ireland,L,Ireland,100,"Docker, Spark, NLP, Kubernetes, Computer Vision",Bachelor,4,Gaming,2024-01-05,2024-01-20,1344,8.3,Cloud AI Solutions -AI09188,AI Specialist,58945,CAD,73681,EN,FL,Canada,L,South Africa,100,"R, SQL, Linux",Master,0,Education,2024-12-30,2025-02-24,1925,8.9,Machine Intelligence Group -AI09189,AI Specialist,192129,USD,192129,SE,FL,Denmark,L,Denmark,50,"Linux, Python, Tableau",Master,6,Education,2024-03-30,2024-06-03,1867,9.3,TechCorp Inc -AI09190,Data Analyst,111169,AUD,150078,SE,PT,Australia,M,Canada,50,"PyTorch, Linux, MLOps",Master,8,Education,2024-10-10,2024-10-26,726,6.8,DataVision Ltd -AI09191,Machine Learning Researcher,92985,GBP,69739,MI,PT,United Kingdom,L,United Kingdom,50,"AWS, TensorFlow, SQL, Azure",Master,3,Gaming,2024-07-23,2024-08-21,1875,6.4,Machine Intelligence Group -AI09192,AI Consultant,96505,CHF,86855,EN,PT,Switzerland,S,Switzerland,50,"SQL, TensorFlow, NLP, AWS, Tableau",Bachelor,0,Manufacturing,2024-02-29,2024-04-30,2394,7,Cognitive Computing -AI09193,AI Software Engineer,158342,USD,158342,EX,FT,South Korea,L,South Korea,0,"GCP, TensorFlow, NLP, Statistics, Computer Vision",Master,12,Consulting,2025-03-12,2025-04-27,1649,6.4,Cognitive Computing -AI09194,AI Specialist,93578,JPY,10293580,EN,CT,Japan,L,Japan,0,"Java, TensorFlow, Azure, Tableau, Kubernetes",Associate,1,Gaming,2024-10-26,2024-11-30,2036,9.3,Smart Analytics -AI09195,Data Engineer,214274,USD,214274,EX,CT,United States,M,Czech Republic,100,"Java, Data Visualization, PyTorch",Master,13,Technology,2024-11-12,2024-12-31,743,8,Digital Transformation LLC -AI09196,AI Consultant,178303,CAD,222879,EX,CT,Canada,M,Canada,50,"Mathematics, Computer Vision, Spark, Hadoop, SQL",Associate,17,Government,2025-03-03,2025-04-19,1070,8.9,Advanced Robotics -AI09197,Head of AI,36007,USD,36007,SE,FT,India,M,India,50,"AWS, Tableau, TensorFlow, Git",Associate,7,Finance,2024-02-07,2024-03-03,730,6,Advanced Robotics -AI09198,Deep Learning Engineer,171051,EUR,145393,EX,PT,Austria,S,Canada,50,"Python, AWS, TensorFlow",Bachelor,13,Consulting,2024-05-21,2024-07-03,1012,8.5,Algorithmic Solutions -AI09199,Head of AI,198950,EUR,169108,EX,FT,Austria,S,Austria,50,"Spark, SQL, Statistics",Associate,14,Government,2025-03-12,2025-04-20,2381,9.2,DeepTech Ventures -AI09200,Robotics Engineer,124387,EUR,105729,SE,FT,France,M,France,100,"PyTorch, TensorFlow, Deep Learning, Scala, Java",Associate,8,Gaming,2024-10-15,2024-12-06,911,5,Neural Networks Co -AI09201,Computer Vision Engineer,106704,USD,106704,MI,FL,Ireland,L,Ireland,100,"R, Git, Azure, Scala, Python",PhD,3,Telecommunications,2024-01-15,2024-02-03,1956,5.7,DeepTech Ventures -AI09202,Research Scientist,149562,USD,149562,EX,FL,Finland,L,Finland,0,"Scala, Tableau, Python, SQL, Kubernetes",Associate,16,Education,2024-10-12,2024-12-08,1386,7.2,Cloud AI Solutions -AI09203,AI Software Engineer,112666,USD,112666,SE,FL,Finland,L,Japan,50,"Azure, Java, Computer Vision",PhD,8,Telecommunications,2024-04-27,2024-06-01,1069,7.2,Cloud AI Solutions -AI09204,Data Analyst,102655,USD,102655,MI,CT,Norway,S,Norway,100,"PyTorch, Computer Vision, Git",Master,2,Telecommunications,2024-12-02,2025-02-12,721,5.4,TechCorp Inc -AI09205,Research Scientist,60391,CAD,75489,EN,FT,Canada,M,Canada,50,"SQL, Spark, PyTorch",PhD,1,Manufacturing,2024-01-31,2024-04-13,1304,6.9,DeepTech Ventures -AI09206,Data Analyst,93418,USD,93418,SE,PT,South Korea,S,Estonia,0,"Git, SQL, Hadoop, Mathematics, Scala",Associate,9,Education,2024-04-04,2024-06-10,2248,9.4,Cloud AI Solutions -AI09207,AI Architect,64099,EUR,54484,MI,PT,France,S,Japan,100,"Scala, Spark, Java, Computer Vision, Docker",Associate,4,Education,2024-11-15,2024-12-08,2247,5.1,Cognitive Computing -AI09208,Head of AI,170894,JPY,18798340,SE,FL,Japan,L,Japan,0,"Data Visualization, PyTorch, SQL",Bachelor,8,Real Estate,2024-03-13,2024-05-15,2021,6.9,Algorithmic Solutions -AI09209,Autonomous Systems Engineer,26067,USD,26067,EN,CT,India,M,Russia,100,"Hadoop, Python, TensorFlow, Git",Bachelor,0,Consulting,2024-01-23,2024-03-07,892,7.1,Advanced Robotics -AI09210,AI Specialist,87803,EUR,74633,EN,PT,Germany,L,Germany,100,"TensorFlow, Python, GCP",Master,1,Media,2024-11-08,2024-12-04,822,8.7,Algorithmic Solutions -AI09211,AI Consultant,73822,CAD,92278,EN,FL,Canada,M,Netherlands,0,"Tableau, TensorFlow, Scala, Statistics",Master,1,Technology,2024-10-03,2024-10-20,1230,5.2,Predictive Systems -AI09212,Machine Learning Engineer,92932,CHF,83639,EN,FT,Switzerland,M,Switzerland,100,"AWS, NLP, SQL",Bachelor,0,Education,2024-07-23,2024-09-05,608,6.4,Neural Networks Co -AI09213,AI Consultant,68084,EUR,57871,EN,PT,Netherlands,L,France,100,"Linux, Tableau, Spark, AWS, Azure",PhD,0,Technology,2025-02-23,2025-04-28,1068,8.9,Cloud AI Solutions -AI09214,AI Specialist,207439,SGD,269671,EX,FL,Singapore,M,Singapore,100,"Java, Spark, NLP",Associate,18,Media,2024-03-19,2024-04-21,1904,5.8,Machine Intelligence Group -AI09215,Data Analyst,96026,USD,96026,EX,FL,China,S,China,100,"SQL, PyTorch, Data Visualization, MLOps",Bachelor,10,Telecommunications,2025-04-16,2025-05-31,868,9.4,Digital Transformation LLC -AI09216,Research Scientist,59680,EUR,50728,EN,FT,France,M,France,0,"Hadoop, MLOps, TensorFlow, Mathematics",Associate,1,Retail,2025-03-12,2025-05-20,2217,6.3,DataVision Ltd -AI09217,AI Specialist,56599,USD,56599,EN,CT,Israel,M,Israel,50,"Azure, AWS, Docker",Master,1,Retail,2025-03-09,2025-04-18,2056,7.5,Future Systems -AI09218,Principal Data Scientist,76244,USD,76244,EN,PT,United States,M,Nigeria,50,"PyTorch, Statistics, TensorFlow",Bachelor,1,Government,2024-09-24,2024-11-27,2133,5.8,Cloud AI Solutions -AI09219,Research Scientist,79160,EUR,67286,MI,FT,France,S,France,100,"Kubernetes, PyTorch, MLOps, SQL",Associate,4,Consulting,2024-11-09,2024-12-14,1801,9.4,Quantum Computing Inc -AI09220,Data Scientist,60957,USD,60957,EN,CT,Ireland,L,Ireland,50,"Git, Python, GCP",PhD,0,Gaming,2025-03-31,2025-05-04,1384,8.1,Future Systems -AI09221,Autonomous Systems Engineer,155548,USD,155548,SE,FL,Israel,L,India,100,"MLOps, Python, TensorFlow, PyTorch, Data Visualization",Master,5,Consulting,2024-08-12,2024-09-22,1725,6.7,Algorithmic Solutions -AI09222,AI Product Manager,123088,JPY,13539680,MI,PT,Japan,L,Japan,0,"Statistics, Scala, Python, GCP, R",Master,2,Manufacturing,2024-05-23,2024-06-09,1989,9,Algorithmic Solutions -AI09223,Research Scientist,121682,USD,121682,MI,FL,Norway,L,Vietnam,100,"Hadoop, Tableau, Spark, Mathematics, Scala",Associate,4,Finance,2024-12-25,2025-02-05,1174,5.7,Cognitive Computing -AI09224,AI Consultant,169915,EUR,144428,EX,PT,Germany,L,Germany,0,"GCP, Hadoop, Git, Computer Vision, R",Associate,14,Media,2025-01-19,2025-02-24,852,5.2,Autonomous Tech -AI09225,AI Specialist,119381,CAD,149226,MI,PT,Canada,L,Canada,100,"Java, MLOps, AWS",PhD,4,Manufacturing,2024-09-22,2024-11-04,2129,8.6,Digital Transformation LLC -AI09226,Deep Learning Engineer,133384,GBP,100038,SE,PT,United Kingdom,M,United Kingdom,0,"SQL, TensorFlow, AWS",Associate,6,Government,2024-04-07,2024-05-07,575,9.1,Machine Intelligence Group -AI09227,AI Architect,122154,USD,122154,SE,FT,United States,S,Colombia,100,"Python, Spark, Mathematics",Master,8,Technology,2024-07-25,2024-09-20,2343,6.7,DeepTech Ventures -AI09228,AI Specialist,66659,EUR,56660,EN,FL,Netherlands,S,Netherlands,100,"Kubernetes, PyTorch, TensorFlow, Spark, Computer Vision",PhD,1,Finance,2024-03-02,2024-04-15,2386,6.7,Cloud AI Solutions -AI09229,Data Analyst,92410,EUR,78549,MI,PT,Germany,L,Germany,100,"Hadoop, SQL, AWS",Bachelor,2,Technology,2024-03-28,2024-05-25,2078,8.7,Algorithmic Solutions -AI09230,Principal Data Scientist,81950,USD,81950,SE,FT,South Korea,S,South Korea,50,"Azure, SQL, Python, TensorFlow",Associate,9,Real Estate,2025-01-27,2025-03-31,1513,6.6,Predictive Systems -AI09231,AI Research Scientist,192330,EUR,163481,EX,CT,Netherlands,L,Netherlands,100,"GCP, Spark, Data Visualization, SQL",Bachelor,19,Government,2025-04-30,2025-05-28,1050,6.7,Cloud AI Solutions -AI09232,AI Specialist,194139,CHF,174725,SE,CT,Switzerland,M,Romania,50,"Deep Learning, Java, MLOps, Kubernetes, AWS",Associate,7,Retail,2024-06-18,2024-07-23,2017,9.3,Cognitive Computing -AI09233,Machine Learning Researcher,287100,USD,287100,EX,PT,Denmark,S,Denmark,0,"R, Python, Spark",Master,14,Technology,2025-03-18,2025-04-23,505,7,DataVision Ltd -AI09234,AI Consultant,192660,USD,192660,EX,FT,Finland,S,Finland,50,"GCP, PyTorch, TensorFlow, SQL",Associate,18,Healthcare,2024-06-29,2024-08-24,1758,7,AI Innovations -AI09235,AI Specialist,79472,USD,79472,MI,CT,Israel,M,Kenya,0,"Python, Spark, Kubernetes, PyTorch, Tableau",Master,3,Technology,2024-07-21,2024-09-07,1228,5.5,Advanced Robotics -AI09236,Autonomous Systems Engineer,118867,USD,118867,MI,FL,Norway,L,Norway,0,"MLOps, TensorFlow, Python",PhD,2,Telecommunications,2024-10-11,2024-12-13,2362,9.9,Algorithmic Solutions -AI09237,Research Scientist,123406,USD,123406,SE,PT,South Korea,L,Colombia,100,"SQL, PyTorch, AWS, Kubernetes",Associate,7,Automotive,2024-12-14,2025-02-20,1950,9.1,AI Innovations -AI09238,NLP Engineer,122245,USD,122245,SE,PT,Denmark,S,Denmark,100,"Git, Data Visualization, AWS",Master,5,Gaming,2024-10-30,2024-11-15,1775,9.5,Machine Intelligence Group -AI09239,ML Ops Engineer,191922,EUR,163134,EX,PT,France,S,France,0,"MLOps, Java, Docker, Scala",Associate,14,Gaming,2024-12-15,2025-01-12,2390,6,Cognitive Computing -AI09240,Data Engineer,68565,SGD,89135,EN,PT,Singapore,L,Singapore,50,"Kubernetes, Statistics, Data Visualization, Azure, Computer Vision",Master,0,Retail,2024-03-05,2024-04-21,2290,6.2,Quantum Computing Inc -AI09241,ML Ops Engineer,102495,JPY,11274450,MI,PT,Japan,S,Estonia,0,"Linux, Scala, Java, Azure",PhD,3,Manufacturing,2024-12-06,2025-01-21,1059,9.7,Predictive Systems -AI09242,Research Scientist,69321,SGD,90117,EN,CT,Singapore,L,Singapore,50,"AWS, Scala, Statistics, R",Master,0,Telecommunications,2024-08-31,2024-11-01,1292,8,Autonomous Tech -AI09243,Autonomous Systems Engineer,100703,AUD,135949,MI,FT,Australia,L,Australia,100,"Kubernetes, Tableau, Docker",PhD,4,Education,2024-07-05,2024-09-04,2102,7.8,Cognitive Computing -AI09244,AI Product Manager,87600,AUD,118260,EN,FT,Australia,L,Norway,0,"R, Mathematics, PyTorch, Deep Learning",Associate,1,Gaming,2024-01-06,2024-02-17,2084,7.9,Cloud AI Solutions -AI09245,AI Product Manager,104439,USD,104439,EN,FT,Denmark,M,Denmark,100,"Data Visualization, Linux, Computer Vision, Kubernetes, Mathematics",PhD,1,Real Estate,2024-03-19,2024-04-02,765,5.1,Smart Analytics -AI09246,Machine Learning Engineer,114869,CHF,103382,MI,CT,Switzerland,M,Switzerland,50,"GCP, Python, SQL, Kubernetes, Docker",Bachelor,4,Healthcare,2024-02-02,2024-04-04,1465,6.6,Machine Intelligence Group -AI09247,AI Consultant,77038,USD,77038,MI,CT,South Korea,S,South Korea,50,"Deep Learning, Kubernetes, Tableau, NLP",Master,4,Consulting,2024-03-17,2024-05-05,590,9.9,Autonomous Tech -AI09248,Machine Learning Engineer,115588,USD,115588,SE,FL,Sweden,S,New Zealand,50,"Docker, Mathematics, Tableau, GCP",Associate,7,Gaming,2025-02-23,2025-03-10,1018,7.5,DataVision Ltd -AI09249,Computer Vision Engineer,124933,CAD,156166,SE,FL,Canada,S,Canada,0,"GCP, Python, Data Visualization, Computer Vision, Deep Learning",Associate,8,Gaming,2024-07-16,2024-09-02,2228,6.4,Smart Analytics -AI09250,Robotics Engineer,105467,EUR,89647,MI,FT,Germany,L,Germany,0,"TensorFlow, Computer Vision, PyTorch, Deep Learning, Statistics",Associate,2,Healthcare,2024-11-03,2024-12-29,743,9.4,TechCorp Inc -AI09251,Research Scientist,108242,USD,108242,MI,FT,Ireland,L,Germany,100,"Computer Vision, GCP, Git, Tableau",Master,2,Manufacturing,2024-09-10,2024-09-26,682,9.8,Advanced Robotics -AI09252,AI Architect,92353,AUD,124677,SE,CT,Australia,S,Australia,100,"Mathematics, Azure, Tableau, TensorFlow, Java",Bachelor,6,Consulting,2024-02-04,2024-04-17,1028,9.1,Cloud AI Solutions -AI09253,Head of AI,137894,USD,137894,SE,PT,South Korea,L,Argentina,100,"Mathematics, Docker, GCP, Spark",Bachelor,5,Healthcare,2025-01-25,2025-02-22,1638,8.3,Autonomous Tech -AI09254,AI Specialist,80356,SGD,104463,EN,FL,Singapore,L,India,0,"Python, GCP, Kubernetes, Scala, Linux",Associate,0,Telecommunications,2024-04-19,2024-06-05,512,5.1,Smart Analytics -AI09255,Data Analyst,97471,USD,97471,MI,PT,Ireland,L,New Zealand,0,"Linux, AWS, Hadoop",Bachelor,3,Manufacturing,2024-01-25,2024-03-27,610,9.8,Future Systems -AI09256,Data Scientist,157922,USD,157922,EX,CT,Finland,M,Singapore,50,"R, Python, Statistics, Docker, Deep Learning",Associate,13,Consulting,2024-10-26,2024-12-05,2233,5.2,Cognitive Computing -AI09257,NLP Engineer,86054,CAD,107568,MI,FL,Canada,L,India,0,"Kubernetes, Python, Azure, TensorFlow, PyTorch",Bachelor,3,Real Estate,2024-07-08,2024-08-17,680,5.3,Cognitive Computing -AI09258,Data Scientist,133023,JPY,14632530,SE,FL,Japan,L,Colombia,50,"Azure, Docker, Deep Learning, SQL, MLOps",PhD,8,Real Estate,2025-03-03,2025-04-23,936,7.5,Algorithmic Solutions -AI09259,NLP Engineer,96262,GBP,72197,EN,CT,United Kingdom,L,United Kingdom,0,"Scala, Kubernetes, Git, GCP, Hadoop",PhD,0,Consulting,2024-12-03,2025-01-25,1844,6.4,Digital Transformation LLC -AI09260,Machine Learning Engineer,33333,USD,33333,MI,PT,India,L,India,50,"Hadoop, Scala, Java",Master,4,Technology,2024-05-26,2024-07-21,1580,8.4,DataVision Ltd -AI09261,Deep Learning Engineer,87092,USD,87092,MI,CT,Ireland,L,Ireland,50,"Hadoop, Git, R, GCP",Bachelor,4,Consulting,2025-02-27,2025-03-31,1789,9,Digital Transformation LLC -AI09262,Research Scientist,146551,USD,146551,EX,FL,Ireland,M,Ireland,0,"AWS, Hadoop, R",Master,16,Energy,2024-10-11,2024-12-16,2266,7,Digital Transformation LLC -AI09263,Robotics Engineer,66231,CAD,82789,EN,PT,Canada,L,Canada,0,"Deep Learning, Spark, TensorFlow",Master,1,Energy,2025-02-03,2025-04-13,1660,5.5,Autonomous Tech -AI09264,Robotics Engineer,145114,AUD,195904,SE,FT,Australia,L,Australia,50,"Kubernetes, Data Visualization, NLP",Associate,5,Telecommunications,2024-12-01,2025-02-09,1103,9.5,Autonomous Tech -AI09265,Autonomous Systems Engineer,146269,USD,146269,SE,PT,Sweden,M,Malaysia,0,"NLP, Hadoop, MLOps",Master,7,Finance,2024-12-01,2025-02-05,683,5.6,Quantum Computing Inc -AI09266,Research Scientist,125674,CAD,157093,SE,CT,Canada,L,Ukraine,50,"MLOps, TensorFlow, Mathematics, AWS",Bachelor,9,Government,2025-03-24,2025-05-16,871,8.6,Neural Networks Co -AI09267,Machine Learning Engineer,127447,JPY,14019170,SE,PT,Japan,S,Japan,100,"Java, Kubernetes, SQL",Associate,8,Transportation,2024-02-26,2024-03-27,1801,7.2,Advanced Robotics -AI09268,NLP Engineer,61294,EUR,52100,EN,CT,France,M,France,0,"SQL, Hadoop, Scala, Data Visualization",Bachelor,0,Energy,2024-09-29,2024-10-28,1878,7.2,Cloud AI Solutions -AI09269,ML Ops Engineer,135156,USD,135156,SE,FL,Sweden,S,Sweden,50,"AWS, Linux, SQL",PhD,6,Education,2024-11-09,2024-12-20,1976,8.2,DeepTech Ventures -AI09270,Autonomous Systems Engineer,67394,EUR,57285,EN,FL,Austria,L,Portugal,50,"GCP, PyTorch, SQL",PhD,1,Consulting,2024-06-24,2024-07-31,1455,5.6,DeepTech Ventures -AI09271,Data Scientist,90125,EUR,76606,MI,FL,Germany,M,Germany,0,"Deep Learning, Computer Vision, Linux, SQL",PhD,3,Manufacturing,2024-02-27,2024-03-27,2164,6.7,Machine Intelligence Group -AI09272,Data Engineer,136268,USD,136268,SE,CT,Ireland,L,Ireland,50,"Kubernetes, PyTorch, SQL",PhD,5,Healthcare,2024-04-09,2024-05-26,521,8.3,DataVision Ltd -AI09273,Data Scientist,69814,USD,69814,MI,FL,Finland,M,Portugal,100,"Kubernetes, Linux, Azure, Scala, PyTorch",PhD,2,Healthcare,2024-08-16,2024-10-14,2026,7,TechCorp Inc -AI09274,Robotics Engineer,295783,USD,295783,EX,FT,Denmark,S,Germany,50,"Spark, NLP, Java, PyTorch",Associate,12,Energy,2024-06-03,2024-07-17,2053,10,Cloud AI Solutions -AI09275,Head of AI,85810,JPY,9439100,MI,FL,Japan,M,Japan,100,"Data Visualization, Azure, Python, Kubernetes, Linux",Associate,4,Automotive,2024-10-27,2024-11-23,2108,7.2,Cognitive Computing -AI09276,AI Research Scientist,197095,USD,197095,EX,FL,Finland,S,Finland,0,"R, Statistics, Java",PhD,10,Technology,2025-03-19,2025-04-05,1049,6.7,Advanced Robotics -AI09277,Head of AI,122788,USD,122788,SE,CT,Ireland,S,China,100,"Python, Scala, GCP, TensorFlow",PhD,7,Retail,2024-04-19,2024-06-19,2250,9.2,Algorithmic Solutions -AI09278,Research Scientist,124194,USD,124194,SE,PT,Sweden,S,Sweden,0,"Scala, Git, Docker, Data Visualization, NLP",Master,8,Gaming,2024-01-05,2024-02-24,1663,7.6,DataVision Ltd -AI09279,AI Consultant,58846,USD,58846,MI,CT,South Korea,S,New Zealand,100,"PyTorch, Kubernetes, Linux",PhD,3,Technology,2024-09-02,2024-10-29,1711,5.3,DataVision Ltd -AI09280,Data Engineer,106557,CHF,95901,MI,PT,Switzerland,M,Switzerland,100,"GCP, TensorFlow, Java",Bachelor,3,Telecommunications,2024-11-22,2024-12-10,2401,7.1,Autonomous Tech -AI09281,Research Scientist,128421,EUR,109158,SE,FL,France,S,Germany,0,"PyTorch, Linux, Tableau",Bachelor,9,Gaming,2025-02-26,2025-04-03,2027,7.1,Predictive Systems -AI09282,AI Product Manager,117576,EUR,99940,SE,FL,France,L,Philippines,0,"Python, Deep Learning, Tableau, Kubernetes, GCP",Associate,8,Energy,2024-09-30,2024-11-13,636,9.7,Future Systems -AI09283,AI Specialist,57593,USD,57593,EN,CT,Israel,L,Ukraine,100,"Python, Kubernetes, AWS",Bachelor,0,Real Estate,2024-09-14,2024-09-30,912,6.9,Algorithmic Solutions -AI09284,AI Software Engineer,212215,USD,212215,EX,FL,United States,S,United States,50,"Azure, Git, Hadoop, Spark",Bachelor,16,Finance,2024-10-06,2024-10-21,2111,8.6,TechCorp Inc -AI09285,AI Consultant,135399,CHF,121859,MI,CT,Switzerland,L,Switzerland,100,"Spark, TensorFlow, NLP, Kubernetes",PhD,3,Consulting,2024-04-04,2024-05-28,1618,9.2,Future Systems -AI09286,Machine Learning Researcher,166176,USD,166176,EX,FL,South Korea,L,South Korea,0,"Git, Python, Azure",Associate,15,Gaming,2024-08-08,2024-10-06,1302,7.1,DeepTech Ventures -AI09287,Machine Learning Engineer,144034,GBP,108026,SE,CT,United Kingdom,S,United Kingdom,0,"Git, Docker, R, Statistics",Associate,9,Finance,2024-06-15,2024-07-19,1279,9.7,Neural Networks Co -AI09288,Head of AI,61774,USD,61774,SE,FL,India,L,India,100,"R, Hadoop, Tableau, Java",Master,6,Real Estate,2024-12-05,2025-02-15,2230,7.1,Autonomous Tech -AI09289,Deep Learning Engineer,103881,EUR,88299,SE,FT,Austria,S,Austria,0,"SQL, PyTorch, Linux",Associate,5,Consulting,2024-07-07,2024-07-27,893,5.4,TechCorp Inc -AI09290,Data Analyst,59689,EUR,50736,EN,CT,France,L,France,100,"Git, R, MLOps, Python",Associate,0,Retail,2024-11-04,2024-11-26,1476,6.6,DeepTech Ventures -AI09291,AI Architect,191160,SGD,248508,EX,FL,Singapore,S,Singapore,50,"R, TensorFlow, Spark, Git",PhD,12,Retail,2024-07-27,2024-09-14,928,6.8,Digital Transformation LLC -AI09292,Data Engineer,89134,USD,89134,MI,CT,United States,S,Netherlands,50,"PyTorch, NLP, Kubernetes, Deep Learning, GCP",Bachelor,3,Technology,2024-10-06,2024-12-08,2234,5.7,Future Systems -AI09293,AI Software Engineer,142040,CAD,177550,EX,CT,Canada,M,Canada,50,"Mathematics, R, Data Visualization, SQL, Kubernetes",Bachelor,17,Telecommunications,2024-04-18,2024-05-31,1401,6.1,Digital Transformation LLC -AI09294,Computer Vision Engineer,67255,USD,67255,MI,PT,Sweden,S,Sweden,100,"Hadoop, Docker, Java, Tableau",PhD,2,Media,2025-04-24,2025-06-12,1670,6.1,Digital Transformation LLC -AI09295,Deep Learning Engineer,186135,USD,186135,EX,FT,Israel,M,Singapore,50,"Hadoop, R, Python, TensorFlow, PyTorch",Master,14,Retail,2024-03-17,2024-04-16,1967,9.8,DeepTech Ventures -AI09296,Machine Learning Engineer,53611,USD,53611,EN,FT,Finland,M,United States,0,"Scala, Python, Deep Learning, Spark, Git",Bachelor,0,Automotive,2024-07-22,2024-08-24,1846,6,Predictive Systems -AI09297,Deep Learning Engineer,94103,USD,94103,MI,FL,Sweden,M,Sweden,100,"Scala, SQL, MLOps, Data Visualization",PhD,3,Gaming,2025-04-20,2025-05-23,1959,8.2,AI Innovations -AI09298,AI Specialist,87733,SGD,114053,EN,FT,Singapore,L,Singapore,100,"Spark, Linux, SQL",Associate,0,Finance,2024-01-02,2024-02-29,632,5.9,Algorithmic Solutions -AI09299,Data Engineer,128376,USD,128376,MI,PT,Denmark,M,Denmark,100,"Python, SQL, PyTorch",Master,2,Healthcare,2024-01-22,2024-03-01,985,8.7,Machine Intelligence Group -AI09300,Head of AI,85553,EUR,72720,MI,FL,Germany,L,Germany,0,"Spark, TensorFlow, Tableau",Master,2,Media,2025-04-23,2025-05-27,934,6.8,DeepTech Ventures -AI09301,Robotics Engineer,165398,EUR,140588,EX,PT,Germany,S,Germany,0,"GCP, Kubernetes, SQL, Deep Learning",Master,10,Real Estate,2025-04-05,2025-05-31,2215,9.7,Autonomous Tech -AI09302,AI Product Manager,111102,GBP,83327,SE,FT,United Kingdom,S,United Kingdom,50,"GCP, Scala, Linux",Bachelor,9,Finance,2024-12-25,2025-01-18,2257,5.5,Cloud AI Solutions -AI09303,Machine Learning Researcher,259032,EUR,220177,EX,FT,Netherlands,L,Netherlands,50,"Python, SQL, R",Associate,18,Government,2025-04-20,2025-07-01,2247,9.6,TechCorp Inc -AI09304,Machine Learning Researcher,64774,EUR,55058,MI,FL,Austria,S,Austria,0,"PyTorch, Hadoop, Computer Vision",PhD,3,Education,2025-02-25,2025-05-06,1421,7.3,Neural Networks Co -AI09305,Data Engineer,221161,EUR,187987,EX,FT,Germany,M,Australia,50,"Computer Vision, TensorFlow, Kubernetes",Bachelor,19,Healthcare,2024-12-24,2025-01-19,725,6.8,Cognitive Computing -AI09306,Deep Learning Engineer,240461,AUD,324622,EX,FT,Australia,L,Australia,50,"Git, SQL, Statistics, Linux",Bachelor,18,Healthcare,2025-03-13,2025-05-14,1914,9,Smart Analytics -AI09307,Data Scientist,95043,SGD,123556,MI,FL,Singapore,S,Singapore,50,"Python, TensorFlow, Tableau",PhD,2,Manufacturing,2024-08-02,2024-10-14,2189,9.3,Advanced Robotics -AI09308,AI Consultant,39308,USD,39308,EN,PT,South Korea,S,Poland,0,"Kubernetes, Git, Deep Learning, TensorFlow, Spark",Associate,1,Transportation,2024-05-06,2024-06-20,1885,7.6,Predictive Systems -AI09309,Machine Learning Engineer,118281,USD,118281,SE,FT,South Korea,L,South Korea,100,"Docker, R, Statistics, Hadoop, GCP",Associate,9,Real Estate,2024-06-06,2024-08-05,2323,7.8,DataVision Ltd -AI09310,Data Analyst,107506,EUR,91380,MI,FT,Netherlands,M,Ireland,100,"Docker, Python, Data Visualization",PhD,3,Education,2024-07-29,2024-09-08,2123,5.7,Smart Analytics -AI09311,AI Architect,161533,USD,161533,EX,FL,Ireland,L,Ireland,100,"Data Visualization, TensorFlow, Git, Deep Learning",Bachelor,14,Energy,2024-08-20,2024-09-29,2120,8,Smart Analytics -AI09312,Machine Learning Researcher,106952,EUR,90909,MI,FL,Germany,M,Germany,0,"Tableau, TensorFlow, Git, Kubernetes, Docker",Bachelor,4,Technology,2025-04-07,2025-05-12,1647,5,TechCorp Inc -AI09313,Machine Learning Researcher,117619,JPY,12938090,MI,PT,Japan,L,Japan,100,"NLP, Python, GCP, Deep Learning, MLOps",Associate,3,Manufacturing,2024-04-17,2024-06-20,1171,7.2,Predictive Systems -AI09314,AI Research Scientist,164714,USD,164714,SE,FT,United States,L,United States,50,"Tableau, Java, Kubernetes",Bachelor,7,Real Estate,2024-07-06,2024-08-17,511,8.5,Machine Intelligence Group -AI09315,AI Software Engineer,55967,USD,55967,EN,FT,South Korea,M,South Korea,50,"Python, NLP, Mathematics",Associate,1,Media,2025-04-21,2025-05-15,2102,5.3,Autonomous Tech -AI09316,Research Scientist,48225,EUR,40991,EN,FT,Germany,S,Germany,100,"Azure, AWS, GCP, Git",PhD,1,Transportation,2024-04-11,2024-05-03,1919,5.3,Machine Intelligence Group -AI09317,Machine Learning Researcher,99314,USD,99314,MI,CT,United States,S,United States,50,"Statistics, Git, Kubernetes",Master,2,Automotive,2024-08-26,2024-10-06,1365,7,Quantum Computing Inc -AI09318,Research Scientist,61925,CAD,77406,MI,FT,Canada,S,Canada,50,"Git, Azure, Tableau, MLOps",Master,4,Finance,2024-08-06,2024-09-29,2038,9.6,Future Systems -AI09319,AI Research Scientist,64161,SGD,83409,EN,CT,Singapore,M,Singapore,100,"GCP, Hadoop, Docker, Computer Vision",Bachelor,0,Government,2024-09-17,2024-10-15,1222,7.1,Machine Intelligence Group -AI09320,Machine Learning Engineer,59904,USD,59904,SE,CT,China,L,China,100,"Kubernetes, Scala, Tableau",Bachelor,8,Manufacturing,2024-12-26,2025-02-28,942,9.9,Digital Transformation LLC -AI09321,AI Architect,84843,EUR,72117,MI,CT,Austria,L,Austria,50,"PyTorch, Git, Scala",Master,2,Media,2024-02-17,2024-03-11,1296,7.5,Autonomous Tech -AI09322,NLP Engineer,116882,EUR,99350,MI,FL,Netherlands,M,Ukraine,100,"Java, Kubernetes, Azure, Computer Vision",Associate,2,Transportation,2024-03-22,2024-05-14,893,7.7,Autonomous Tech -AI09323,Robotics Engineer,41992,USD,41992,MI,FT,India,L,India,0,"PyTorch, Deep Learning, Mathematics, Spark",Bachelor,4,Finance,2024-11-26,2025-01-09,556,6.6,Algorithmic Solutions -AI09324,Data Scientist,83559,USD,83559,MI,FT,Ireland,L,Singapore,100,"TensorFlow, SQL, Mathematics, Tableau, AWS",Bachelor,3,Government,2025-01-06,2025-02-19,1509,8.9,Advanced Robotics -AI09325,Machine Learning Engineer,165796,USD,165796,EX,FL,Ireland,L,Ireland,100,"Kubernetes, Docker, R, Tableau",Master,15,Government,2025-04-02,2025-04-28,1526,6.8,Quantum Computing Inc -AI09326,Data Scientist,27209,USD,27209,MI,PT,India,S,India,50,"Python, Computer Vision, Data Visualization, TensorFlow, Docker",PhD,2,Transportation,2024-06-06,2024-07-31,627,6.7,Neural Networks Co -AI09327,AI Specialist,238785,EUR,202967,EX,FT,France,L,Ghana,50,"Azure, Python, TensorFlow, MLOps, Computer Vision",PhD,19,Automotive,2024-05-14,2024-06-21,1303,9.7,Predictive Systems -AI09328,AI Specialist,36971,USD,36971,SE,PT,India,S,Argentina,0,"AWS, Tableau, Spark, Mathematics, Computer Vision",PhD,5,Education,2024-03-14,2024-04-06,1849,5.7,Cloud AI Solutions -AI09329,Deep Learning Engineer,281022,USD,281022,EX,FT,Norway,S,Netherlands,100,"Python, Data Visualization, Spark",PhD,12,Retail,2025-04-18,2025-06-15,1583,7,Predictive Systems -AI09330,AI Architect,69740,JPY,7671400,EN,CT,Japan,S,Japan,0,"NLP, GCP, Mathematics, Kubernetes",PhD,1,Education,2024-02-13,2024-04-14,1821,9.8,Algorithmic Solutions -AI09331,AI Architect,117773,USD,117773,MI,FT,United States,M,United States,100,"Hadoop, PyTorch, GCP, AWS",PhD,4,Real Estate,2025-02-28,2025-03-25,1720,6.3,Machine Intelligence Group -AI09332,Research Scientist,149573,USD,149573,EX,FT,Israel,S,Israel,0,"Python, GCP, Hadoop",Master,17,Government,2024-08-06,2024-10-03,1603,8,DeepTech Ventures -AI09333,Machine Learning Researcher,115785,GBP,86839,MI,CT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, Kubernetes, Scala, Hadoop",PhD,4,Automotive,2024-09-18,2024-10-09,1354,5,Predictive Systems -AI09334,Head of AI,155051,JPY,17055610,EX,FT,Japan,S,Estonia,0,"Hadoop, GCP, Linux",Bachelor,14,Technology,2025-04-04,2025-06-02,2362,8,Autonomous Tech -AI09335,AI Software Engineer,69683,SGD,90588,EN,CT,Singapore,M,Singapore,50,"NLP, SQL, Kubernetes",Bachelor,0,Gaming,2024-05-20,2024-06-10,860,5.3,Autonomous Tech -AI09336,Machine Learning Engineer,63898,USD,63898,EN,CT,Ireland,S,Ireland,100,"Mathematics, MLOps, GCP",Associate,0,Technology,2024-07-13,2024-08-04,1335,6.3,Digital Transformation LLC -AI09337,NLP Engineer,91901,USD,91901,MI,FL,Sweden,M,Sweden,0,"PyTorch, Mathematics, Kubernetes",PhD,4,Finance,2024-06-28,2024-09-07,641,7.8,Autonomous Tech -AI09338,AI Consultant,59695,EUR,50741,EN,FT,France,S,Ghana,100,"R, GCP, PyTorch, AWS",Master,1,Automotive,2024-10-04,2024-10-29,1315,7,Future Systems -AI09339,Data Engineer,65038,GBP,48779,EN,PT,United Kingdom,S,United Kingdom,50,"Docker, Python, Computer Vision, R",Master,0,Real Estate,2024-06-03,2024-08-10,1902,8.5,AI Innovations -AI09340,AI Consultant,86847,USD,86847,MI,FT,Finland,M,Finland,100,"Scala, MLOps, Java",Bachelor,2,Real Estate,2025-03-20,2025-05-08,2066,9,Advanced Robotics -AI09341,Deep Learning Engineer,34236,USD,34236,MI,FT,China,M,China,0,"TensorFlow, R, Linux",Associate,4,Telecommunications,2024-04-18,2024-06-01,2369,5.6,AI Innovations -AI09342,AI Consultant,160503,EUR,136428,SE,FL,France,L,Australia,50,"AWS, Python, Data Visualization",Bachelor,8,Government,2024-12-05,2025-01-07,1991,7,Algorithmic Solutions -AI09343,Machine Learning Engineer,120317,USD,120317,SE,FT,Israel,M,Israel,50,"SQL, Docker, TensorFlow, Linux, Tableau",Bachelor,6,Education,2025-01-05,2025-02-20,1725,9.6,Neural Networks Co -AI09344,Principal Data Scientist,79295,EUR,67401,EN,PT,France,L,France,100,"GCP, SQL, Scala, Python",Master,0,Real Estate,2024-04-13,2024-06-15,2373,6.9,Quantum Computing Inc -AI09345,Principal Data Scientist,57136,EUR,48566,EN,PT,Austria,M,United States,50,"Linux, Scala, TensorFlow",Master,0,Real Estate,2024-02-23,2024-04-03,1669,6.7,Autonomous Tech -AI09346,Research Scientist,109133,USD,109133,SE,PT,Israel,M,Israel,0,"Java, R, Statistics, SQL",PhD,8,Telecommunications,2025-03-17,2025-05-02,2042,8.7,Smart Analytics -AI09347,Machine Learning Engineer,226278,CHF,203650,EX,FT,Switzerland,M,Switzerland,50,"Mathematics, Scala, Azure",PhD,15,Media,2025-01-20,2025-03-29,1514,9.2,Autonomous Tech -AI09348,ML Ops Engineer,67762,USD,67762,EN,FT,Finland,S,Finland,100,"Kubernetes, Data Visualization, MLOps, Python",Associate,0,Gaming,2024-11-21,2024-12-10,1779,8.1,DeepTech Ventures -AI09349,Research Scientist,158626,USD,158626,SE,FT,Norway,S,Norway,0,"Python, Scala, Java, TensorFlow",PhD,9,Government,2024-06-23,2024-07-12,1918,5.6,Smart Analytics -AI09350,Research Scientist,35902,USD,35902,MI,FT,India,M,Philippines,0,"Linux, Spark, Data Visualization, Java, Mathematics",Bachelor,2,Finance,2024-05-30,2024-08-04,2143,6.3,Future Systems -AI09351,AI Specialist,199630,EUR,169686,EX,FL,France,S,France,100,"Linux, Hadoop, Data Visualization, MLOps",Associate,19,Retail,2024-03-14,2024-04-28,2431,6.4,Cognitive Computing -AI09352,ML Ops Engineer,34288,USD,34288,MI,PT,India,L,Austria,0,"Python, AWS, SQL, Data Visualization",Associate,3,Telecommunications,2024-12-29,2025-02-20,688,8.8,Autonomous Tech -AI09353,AI Consultant,64165,USD,64165,EN,PT,Finland,L,Finland,100,"Kubernetes, Deep Learning, Data Visualization, Python",Master,0,Healthcare,2024-02-23,2024-04-20,2185,5.9,Quantum Computing Inc -AI09354,AI Architect,68161,CAD,85201,EN,CT,Canada,L,Canada,100,"Scala, Azure, Statistics, Linux, PyTorch",PhD,1,Transportation,2024-08-25,2024-10-29,1318,5.2,Machine Intelligence Group -AI09355,Deep Learning Engineer,190540,AUD,257229,EX,PT,Australia,S,Australia,100,"SQL, Azure, Scala, Tableau, Spark",Associate,17,Automotive,2025-01-23,2025-02-11,1879,5.1,Digital Transformation LLC -AI09356,AI Consultant,145966,USD,145966,EX,FT,South Korea,S,South Korea,50,"PyTorch, TensorFlow, Python",Bachelor,13,Media,2024-10-09,2024-12-02,2054,8.6,Autonomous Tech -AI09357,AI Research Scientist,64339,USD,64339,MI,PT,South Korea,S,Belgium,0,"Java, R, Python, AWS",Associate,2,Consulting,2024-07-13,2024-08-18,632,6.7,Advanced Robotics -AI09358,Computer Vision Engineer,72089,GBP,54067,EN,FT,United Kingdom,L,Ireland,50,"Deep Learning, Scala, Statistics, Computer Vision, Docker",PhD,0,Finance,2025-02-18,2025-04-30,2314,6.2,TechCorp Inc -AI09359,Data Scientist,121917,USD,121917,MI,PT,Sweden,L,China,100,"PyTorch, Hadoop, Java, Kubernetes, MLOps",PhD,4,Finance,2024-01-15,2024-02-28,794,9.3,Advanced Robotics -AI09360,Computer Vision Engineer,62465,EUR,53095,EN,CT,Netherlands,M,Japan,0,"Python, AWS, Mathematics, SQL, Java",Associate,1,Energy,2024-01-29,2024-03-21,595,8.6,Autonomous Tech -AI09361,AI Consultant,120168,JPY,13218480,SE,PT,Japan,S,Japan,50,"Statistics, Computer Vision, Kubernetes, TensorFlow",Associate,9,Healthcare,2025-02-18,2025-04-10,781,9.7,Predictive Systems -AI09362,Data Scientist,74225,EUR,63091,MI,FL,France,S,France,100,"R, Git, Scala, Kubernetes",PhD,4,Manufacturing,2024-12-20,2025-02-05,524,7,DeepTech Ventures -AI09363,Head of AI,86630,USD,86630,SE,CT,Israel,S,Czech Republic,100,"Statistics, R, Kubernetes, Computer Vision, SQL",Bachelor,8,Education,2024-09-16,2024-11-19,2024,5.3,AI Innovations -AI09364,Data Analyst,45119,USD,45119,MI,FT,China,S,New Zealand,100,"Kubernetes, Python, Statistics, GCP",Master,4,Gaming,2024-09-15,2024-11-23,2360,5.9,DataVision Ltd -AI09365,Data Analyst,70424,USD,70424,SE,FL,China,M,China,100,"AWS, Docker, GCP, Python",Master,6,Manufacturing,2024-08-11,2024-09-30,1551,5.1,DeepTech Ventures -AI09366,Data Scientist,124107,EUR,105491,SE,PT,France,S,France,0,"Spark, Java, NLP, Computer Vision",Bachelor,7,Finance,2024-02-14,2024-03-08,1939,6.9,Machine Intelligence Group -AI09367,Machine Learning Researcher,104599,CHF,94139,MI,FL,Switzerland,S,Israel,0,"Hadoop, Scala, Deep Learning, NLP, TensorFlow",Master,2,Government,2024-07-05,2024-08-23,1948,9,TechCorp Inc -AI09368,AI Product Manager,130443,SGD,169576,SE,PT,Singapore,M,Singapore,50,"Deep Learning, MLOps, Git, SQL, Kubernetes",Bachelor,7,Finance,2024-09-18,2024-10-02,947,8.5,Cognitive Computing -AI09369,Machine Learning Engineer,51380,USD,51380,SE,PT,China,M,Turkey,100,"Linux, Spark, Kubernetes",Bachelor,7,Manufacturing,2024-04-27,2024-06-30,1994,7.2,Algorithmic Solutions -AI09370,ML Ops Engineer,55972,EUR,47576,EN,PT,France,S,Egypt,100,"Linux, Python, Deep Learning, AWS",Associate,0,Telecommunications,2024-01-13,2024-03-01,1786,6.9,Machine Intelligence Group -AI09371,AI Specialist,140112,EUR,119095,EX,PT,Austria,M,Kenya,100,"Linux, R, Data Visualization",PhD,10,Real Estate,2024-07-03,2024-08-18,991,6.3,DeepTech Ventures -AI09372,Research Scientist,77842,EUR,66166,EN,FL,Netherlands,M,Netherlands,100,"Statistics, Hadoop, Python",Master,1,Healthcare,2024-05-09,2024-07-14,1380,5,Cloud AI Solutions -AI09373,Data Analyst,143720,USD,143720,EX,FL,South Korea,M,Ukraine,50,"Scala, AWS, Azure, Computer Vision, Statistics",Associate,16,Technology,2024-06-09,2024-07-23,566,6.9,Cognitive Computing -AI09374,Machine Learning Engineer,93910,USD,93910,MI,CT,South Korea,L,Netherlands,100,"GCP, NLP, Data Visualization, Python, Linux",Master,2,Consulting,2024-12-31,2025-02-27,748,9.8,Autonomous Tech -AI09375,NLP Engineer,92622,JPY,10188420,MI,CT,Japan,M,Estonia,50,"Statistics, Kubernetes, R, Scala",Associate,2,Healthcare,2024-05-09,2024-06-26,508,8.6,Cognitive Computing -AI09376,Data Analyst,207950,USD,207950,EX,FL,Ireland,S,Portugal,0,"Hadoop, GCP, Statistics, Deep Learning",Bachelor,16,Gaming,2024-05-17,2024-06-21,823,5.1,Cognitive Computing -AI09377,AI Research Scientist,52390,CAD,65488,EN,FT,Canada,S,Ireland,50,"Deep Learning, Python, Docker",Master,0,Finance,2024-06-29,2024-08-19,818,8.7,Smart Analytics -AI09378,NLP Engineer,72765,EUR,61850,MI,FT,Germany,S,Germany,50,"AWS, Kubernetes, GCP, NLP",PhD,4,Telecommunications,2024-06-13,2024-08-25,604,9.9,Quantum Computing Inc -AI09379,Robotics Engineer,95125,EUR,80856,SE,PT,France,S,Turkey,0,"Python, Java, Kubernetes, TensorFlow, Docker",Master,7,Media,2024-09-06,2024-11-12,1188,6.3,DataVision Ltd -AI09380,Data Analyst,86783,USD,86783,EX,CT,China,S,China,50,"Kubernetes, Java, MLOps",Associate,10,Real Estate,2025-01-16,2025-02-23,1979,5.6,Predictive Systems -AI09381,Principal Data Scientist,195942,SGD,254725,EX,CT,Singapore,S,Singapore,50,"PyTorch, Python, Linux, Mathematics",Bachelor,18,Automotive,2024-02-24,2024-05-05,2119,9.8,Algorithmic Solutions -AI09382,AI Architect,88045,USD,88045,SE,PT,Finland,S,Finland,0,"AWS, Kubernetes, Java, GCP, Azure",Master,8,Media,2024-05-24,2024-06-10,1613,6.5,DataVision Ltd -AI09383,ML Ops Engineer,34080,USD,34080,EN,PT,China,S,China,100,"Python, Tableau, Statistics, Deep Learning",Associate,0,Telecommunications,2024-08-15,2024-08-30,858,6.4,Algorithmic Solutions -AI09384,Machine Learning Researcher,159791,AUD,215718,SE,CT,Australia,L,Australia,0,"TensorFlow, Mathematics, Data Visualization, Linux",Associate,9,Media,2024-11-05,2025-01-12,1415,5.4,Smart Analytics -AI09385,Computer Vision Engineer,82207,EUR,69876,MI,CT,Germany,M,Germany,100,"Kubernetes, Java, Docker, R, Statistics",Master,2,Telecommunications,2024-08-18,2024-10-28,2049,6.4,DataVision Ltd -AI09386,Computer Vision Engineer,121634,USD,121634,SE,CT,South Korea,M,Argentina,50,"R, SQL, Data Visualization",Master,6,Healthcare,2025-02-04,2025-03-25,1979,8.6,Smart Analytics -AI09387,AI Research Scientist,29142,USD,29142,EN,CT,India,L,India,0,"Linux, Hadoop, Data Visualization, Spark",Bachelor,1,Technology,2024-10-18,2024-11-13,2226,5.3,Advanced Robotics -AI09388,AI Software Engineer,62502,JPY,6875220,EN,PT,Japan,L,Japan,100,"Kubernetes, Python, Spark, Docker, Git",Bachelor,0,Gaming,2025-01-22,2025-03-06,1769,6.4,DeepTech Ventures -AI09389,NLP Engineer,106016,USD,106016,EX,PT,South Korea,S,South Korea,100,"Mathematics, Python, Statistics, Git, TensorFlow",Master,18,Energy,2025-03-19,2025-05-26,658,9,Algorithmic Solutions -AI09390,Machine Learning Engineer,223388,USD,223388,EX,FT,United States,S,United States,0,"Python, Spark, TensorFlow, GCP, PyTorch",Bachelor,13,Retail,2024-04-13,2024-05-02,776,7.7,Autonomous Tech -AI09391,AI Product Manager,260456,JPY,28650160,EX,CT,Japan,L,Poland,50,"Hadoop, Deep Learning, Tableau",Bachelor,13,Manufacturing,2024-04-11,2024-05-12,1344,6.3,Advanced Robotics -AI09392,Deep Learning Engineer,122043,AUD,164758,SE,FL,Australia,S,Malaysia,100,"SQL, R, Python, Statistics",PhD,9,Government,2025-04-14,2025-05-26,528,8.4,Autonomous Tech -AI09393,AI Software Engineer,79246,EUR,67359,MI,CT,Germany,S,Germany,50,"Kubernetes, Deep Learning, Java, Azure, R",Associate,4,Media,2025-01-18,2025-03-04,1975,8.8,AI Innovations -AI09394,AI Specialist,200872,GBP,150654,EX,PT,United Kingdom,L,Sweden,100,"Computer Vision, Statistics, Docker",Associate,14,Technology,2024-06-26,2024-09-05,2354,5.4,TechCorp Inc -AI09395,Head of AI,103261,AUD,139402,SE,FL,Australia,M,Australia,0,"Docker, SQL, Azure, AWS",Bachelor,5,Gaming,2025-03-11,2025-04-08,1989,10,Cloud AI Solutions -AI09396,AI Software Engineer,56852,USD,56852,EN,FT,Sweden,S,Sweden,50,"Git, Computer Vision, Data Visualization",Associate,1,Consulting,2024-02-26,2024-04-12,1249,8,Digital Transformation LLC -AI09397,Data Engineer,87803,AUD,118534,MI,CT,Australia,L,Australia,100,"PyTorch, GCP, Java, Docker, Tableau",Associate,4,Automotive,2024-10-23,2024-12-02,1156,7.5,TechCorp Inc -AI09398,ML Ops Engineer,63510,USD,63510,EN,FL,Israel,L,Israel,50,"SQL, Azure, TensorFlow, Computer Vision, R",Associate,1,Consulting,2025-04-14,2025-04-28,1830,7.1,DataVision Ltd -AI09399,Deep Learning Engineer,92068,USD,92068,EN,PT,United States,M,United States,50,"MLOps, Kubernetes, Python",Associate,1,Telecommunications,2024-10-03,2024-11-21,2475,6.3,Algorithmic Solutions -AI09400,NLP Engineer,75818,GBP,56864,MI,FL,United Kingdom,S,United States,100,"PyTorch, Java, AWS, GCP, TensorFlow",Associate,4,Technology,2025-01-17,2025-03-13,2063,6.9,Autonomous Tech -AI09401,Deep Learning Engineer,120141,USD,120141,SE,PT,Ireland,S,Malaysia,0,"Java, GCP, Python, Linux, MLOps",PhD,6,Media,2024-04-14,2024-06-16,2469,7.6,Quantum Computing Inc -AI09402,Principal Data Scientist,77151,USD,77151,MI,PT,Sweden,S,Sweden,50,"Linux, Statistics, Java",PhD,2,Automotive,2025-03-17,2025-05-05,1385,5.3,AI Innovations -AI09403,Principal Data Scientist,69108,USD,69108,MI,CT,South Korea,S,Turkey,0,"Python, GCP, TensorFlow, Data Visualization",Master,4,Consulting,2024-04-28,2024-05-23,2108,6.2,Quantum Computing Inc -AI09404,Machine Learning Researcher,209966,EUR,178471,EX,PT,France,L,Finland,100,"Linux, Azure, Kubernetes, Docker, Git",PhD,19,Real Estate,2024-06-30,2024-08-14,937,9,Algorithmic Solutions -AI09405,Robotics Engineer,75780,USD,75780,EN,PT,Ireland,M,Ireland,0,"MLOps, PyTorch, Mathematics, Kubernetes",Associate,1,Retail,2024-03-28,2024-05-03,1240,9.9,Future Systems -AI09406,AI Product Manager,59033,AUD,79695,EN,PT,Australia,L,Egypt,50,"Python, NLP, Tableau, TensorFlow",Master,0,Gaming,2025-02-01,2025-03-29,1668,8.1,Future Systems -AI09407,Data Engineer,173659,USD,173659,EX,CT,Ireland,M,Ireland,100,"Hadoop, Statistics, TensorFlow, Spark",PhD,15,Technology,2024-11-21,2025-01-29,1737,7.4,DataVision Ltd -AI09408,AI Architect,218617,USD,218617,EX,FT,Ireland,S,Ireland,50,"MLOps, Git, AWS, Docker",Bachelor,18,Consulting,2025-04-13,2025-06-08,878,6.9,AI Innovations -AI09409,AI Consultant,51900,USD,51900,SE,PT,India,M,South Africa,100,"Git, Python, MLOps",Bachelor,6,Gaming,2024-04-11,2024-06-06,1782,8.4,Digital Transformation LLC -AI09410,Autonomous Systems Engineer,83722,EUR,71164,MI,FT,Germany,S,Germany,100,"Git, Linux, Data Visualization",PhD,4,Real Estate,2025-04-14,2025-06-16,1176,9.3,TechCorp Inc -AI09411,ML Ops Engineer,64831,CAD,81039,EN,FL,Canada,S,Kenya,50,"NLP, Python, SQL, Linux, GCP",Master,1,Transportation,2024-05-16,2024-07-20,1981,5.5,Algorithmic Solutions -AI09412,AI Research Scientist,80478,JPY,8852580,EN,PT,Japan,M,Japan,0,"TensorFlow, Python, GCP, Java, PyTorch",Master,1,Telecommunications,2024-06-15,2024-08-12,1157,9.6,AI Innovations -AI09413,Machine Learning Engineer,152682,CHF,137414,MI,FL,Switzerland,M,Switzerland,100,"Linux, Docker, R",Bachelor,2,Education,2025-01-22,2025-02-08,2221,7.8,Neural Networks Co -AI09414,Research Scientist,73388,USD,73388,EN,FT,Israel,M,Israel,0,"Hadoop, GCP, Data Visualization, Java, MLOps",Bachelor,0,Education,2025-01-22,2025-03-13,998,7.2,Advanced Robotics -AI09415,Head of AI,191472,AUD,258487,EX,FL,Australia,S,Belgium,0,"Azure, Java, TensorFlow, Linux, Git",Master,18,Automotive,2024-12-07,2025-02-06,654,9.3,Cognitive Computing -AI09416,AI Architect,111011,USD,111011,SE,FT,South Korea,M,South Korea,0,"Data Visualization, Linux, Python, Statistics, Mathematics",Master,5,Energy,2025-03-16,2025-05-28,2347,6.7,Digital Transformation LLC -AI09417,Machine Learning Researcher,61781,JPY,6795910,EN,FT,Japan,M,Singapore,100,"Linux, GCP, MLOps",Bachelor,0,Retail,2025-04-08,2025-05-21,548,8.5,DataVision Ltd -AI09418,NLP Engineer,194729,EUR,165520,EX,FT,France,M,France,50,"Mathematics, Java, Data Visualization",Master,13,Consulting,2024-08-04,2024-09-18,510,8.4,Quantum Computing Inc -AI09419,AI Product Manager,100526,EUR,85447,MI,CT,Netherlands,S,Netherlands,100,"Scala, Docker, Data Visualization",Master,3,Media,2024-06-04,2024-07-03,1421,7.6,DataVision Ltd -AI09420,Data Analyst,92755,USD,92755,MI,CT,Israel,L,Israel,0,"SQL, PyTorch, Azure, Git, R",Master,4,Finance,2024-08-15,2024-10-19,2437,9.7,Cloud AI Solutions -AI09421,Robotics Engineer,97289,GBP,72967,SE,PT,United Kingdom,S,United Kingdom,50,"NLP, AWS, Java",Bachelor,8,Automotive,2024-09-12,2024-09-30,1299,5.1,Autonomous Tech -AI09422,Machine Learning Engineer,153741,USD,153741,EX,FL,South Korea,L,South Korea,100,"Java, Deep Learning, Data Visualization",Bachelor,10,Retail,2024-09-19,2024-10-23,1707,6.7,DeepTech Ventures -AI09423,Head of AI,157987,SGD,205383,EX,CT,Singapore,M,Singapore,50,"Azure, Docker, Tableau",Bachelor,18,Healthcare,2024-02-18,2024-03-14,2161,9.1,Advanced Robotics -AI09424,AI Architect,120516,CHF,108464,MI,PT,Switzerland,M,Norway,50,"Linux, SQL, Computer Vision, Kubernetes",Master,3,Telecommunications,2024-08-26,2024-09-20,657,5.5,DataVision Ltd -AI09425,AI Specialist,203853,EUR,173275,EX,PT,Netherlands,L,Netherlands,50,"Spark, Scala, GCP",PhD,18,Real Estate,2024-03-20,2024-04-27,1169,7.2,Future Systems -AI09426,Data Scientist,142413,USD,142413,SE,CT,Finland,M,Finland,100,"TensorFlow, Python, Scala, Azure, MLOps",Associate,7,Retail,2024-12-04,2025-01-10,1806,8.3,Neural Networks Co -AI09427,Head of AI,173201,CHF,155881,SE,FL,Switzerland,S,Switzerland,100,"Computer Vision, Hadoop, Python",PhD,6,Finance,2024-07-02,2024-07-28,1290,8.9,Machine Intelligence Group -AI09428,Autonomous Systems Engineer,204387,CAD,255484,EX,FL,Canada,S,Thailand,50,"Computer Vision, TensorFlow, NLP, Python, Data Visualization",Associate,13,Government,2025-01-08,2025-02-03,1275,5.7,Algorithmic Solutions -AI09429,AI Specialist,24626,USD,24626,EN,PT,India,S,India,50,"Azure, Spark, SQL, Docker, Hadoop",Bachelor,0,Energy,2024-10-25,2024-12-14,2213,6.7,Cognitive Computing -AI09430,Data Engineer,30632,USD,30632,MI,FL,China,S,United States,100,"Docker, Python, GCP, TensorFlow, AWS",Bachelor,3,Technology,2025-02-03,2025-03-09,2442,7.1,Cognitive Computing -AI09431,Data Scientist,51880,CAD,64850,EN,FT,Canada,S,Canada,0,"R, PyTorch, Hadoop",PhD,1,Government,2024-11-23,2025-01-16,1334,8.9,Quantum Computing Inc -AI09432,Autonomous Systems Engineer,105546,USD,105546,SE,CT,Ireland,M,Ireland,0,"Data Visualization, Mathematics, Java, Computer Vision, Scala",Bachelor,5,Manufacturing,2024-07-06,2024-08-07,1958,9.4,TechCorp Inc -AI09433,AI Product Manager,156352,EUR,132899,EX,FT,France,S,France,100,"R, Scala, Computer Vision",Associate,18,Consulting,2024-09-17,2024-10-20,1481,7.5,TechCorp Inc -AI09434,Autonomous Systems Engineer,82869,USD,82869,MI,PT,Sweden,S,Sweden,0,"Hadoop, MLOps, Git",Master,4,Gaming,2024-04-10,2024-06-07,2048,5.3,AI Innovations -AI09435,Robotics Engineer,249284,EUR,211891,EX,PT,Germany,L,Finland,50,"Data Visualization, Hadoop, Statistics",Master,10,Education,2025-02-17,2025-04-19,1549,6.4,DeepTech Ventures -AI09436,AI Consultant,143332,EUR,121832,EX,FT,France,S,South Africa,50,"TensorFlow, Computer Vision, MLOps, Tableau, Kubernetes",Master,12,Telecommunications,2024-03-27,2024-05-14,1786,5.1,Cognitive Computing -AI09437,Data Analyst,102445,USD,102445,MI,CT,Denmark,S,Denmark,50,"SQL, Scala, AWS",Master,3,Consulting,2024-12-01,2025-02-06,1144,8.9,Predictive Systems -AI09438,Computer Vision Engineer,95141,CAD,118926,SE,PT,Canada,S,Netherlands,0,"SQL, PyTorch, R, Mathematics",Bachelor,5,Gaming,2024-07-05,2024-08-10,1531,9.4,Autonomous Tech -AI09439,Computer Vision Engineer,85527,EUR,72698,MI,FL,France,S,France,0,"Linux, R, Statistics, Kubernetes",Bachelor,2,Healthcare,2024-02-19,2024-04-28,543,9.9,DataVision Ltd -AI09440,Autonomous Systems Engineer,84275,EUR,71634,MI,CT,Austria,L,Austria,100,"Git, Linux, Python",Master,4,Healthcare,2024-11-01,2024-11-23,1865,6.5,Digital Transformation LLC -AI09441,Data Analyst,171765,USD,171765,EX,FL,Finland,S,Finland,100,"Tableau, NLP, Hadoop, Python",Master,10,Manufacturing,2024-07-29,2024-08-21,2398,6.2,Cognitive Computing -AI09442,Robotics Engineer,47657,USD,47657,MI,FT,China,L,China,0,"Computer Vision, Kubernetes, Java",Bachelor,4,Transportation,2025-04-26,2025-07-06,1427,6.5,Cloud AI Solutions -AI09443,Robotics Engineer,54748,USD,54748,EN,PT,Israel,S,Israel,50,"PyTorch, AWS, Data Visualization, GCP",Master,0,Education,2024-05-28,2024-07-31,2405,7.4,Future Systems -AI09444,Data Scientist,47134,AUD,63631,EN,FL,Australia,S,United Kingdom,50,"NLP, Statistics, Kubernetes, Python, GCP",PhD,0,Healthcare,2024-06-28,2024-08-26,613,6.1,DataVision Ltd -AI09445,ML Ops Engineer,84635,AUD,114257,MI,CT,Australia,L,Australia,100,"Kubernetes, SQL, Java, Git",PhD,3,Technology,2024-03-25,2024-05-30,1487,5.6,Future Systems -AI09446,ML Ops Engineer,84203,EUR,71573,MI,FL,France,L,France,100,"PyTorch, Mathematics, Scala",PhD,3,Real Estate,2025-02-26,2025-04-17,2353,6.5,Predictive Systems -AI09447,AI Product Manager,105870,EUR,89990,MI,PT,Netherlands,L,Netherlands,100,"Python, Linux, TensorFlow, Hadoop, PyTorch",Bachelor,4,Automotive,2024-07-29,2024-10-04,1615,5.4,DataVision Ltd -AI09448,AI Architect,66252,USD,66252,EX,CT,China,M,Russia,0,"Statistics, PyTorch, Tableau",Master,16,Healthcare,2024-11-30,2024-12-26,897,9.8,Neural Networks Co -AI09449,Data Engineer,91263,USD,91263,MI,FT,Finland,M,Finland,0,"GCP, PyTorch, Deep Learning, Mathematics, Computer Vision",Master,4,Finance,2024-10-01,2024-11-09,1366,7.7,Digital Transformation LLC -AI09450,Machine Learning Researcher,69243,USD,69243,EN,FT,Israel,M,Israel,50,"Azure, Python, SQL, Tableau, TensorFlow",Master,0,Manufacturing,2024-10-10,2024-12-16,689,6.2,TechCorp Inc -AI09451,Principal Data Scientist,137522,USD,137522,SE,PT,Ireland,M,France,100,"AWS, Tableau, Python",Bachelor,7,Government,2024-07-07,2024-07-28,709,6.8,Digital Transformation LLC -AI09452,NLP Engineer,266422,GBP,199817,EX,FT,United Kingdom,L,United Kingdom,50,"R, AWS, Data Visualization",PhD,11,Gaming,2024-03-29,2024-05-03,817,7.1,DeepTech Ventures -AI09453,Machine Learning Researcher,199823,EUR,169850,EX,PT,France,S,France,50,"Java, MLOps, GCP, AWS, PyTorch",Associate,12,Media,2024-02-25,2024-03-31,2329,6.6,Machine Intelligence Group -AI09454,NLP Engineer,69686,USD,69686,EN,CT,Ireland,M,Ireland,100,"Data Visualization, SQL, NLP, Kubernetes, Python",Associate,0,Real Estate,2025-01-25,2025-02-15,1109,7,Autonomous Tech -AI09455,Principal Data Scientist,173317,USD,173317,EX,FT,Denmark,S,Denmark,50,"TensorFlow, Scala, Statistics",PhD,18,Technology,2024-12-17,2025-02-23,1801,8.7,Future Systems -AI09456,Robotics Engineer,181014,EUR,153862,EX,FT,Austria,S,Austria,0,"Kubernetes, GCP, Python, Mathematics",PhD,18,Retail,2024-11-16,2025-01-05,1255,6,Predictive Systems -AI09457,AI Research Scientist,262405,USD,262405,EX,PT,Finland,L,Finland,0,"Deep Learning, Python, Azure, SQL",Master,19,Finance,2024-03-31,2024-05-27,2116,8.8,Machine Intelligence Group -AI09458,Data Engineer,109773,JPY,12075030,MI,FT,Japan,M,Vietnam,50,"Python, Tableau, Computer Vision",Bachelor,2,Gaming,2025-01-06,2025-02-25,2433,5.7,TechCorp Inc -AI09459,Data Scientist,81338,CAD,101673,EN,FL,Canada,L,Canada,0,"MLOps, Data Visualization, AWS, Python, TensorFlow",Bachelor,1,Healthcare,2025-01-23,2025-03-30,550,7.2,DataVision Ltd -AI09460,AI Research Scientist,147302,SGD,191493,SE,PT,Singapore,M,Singapore,0,"SQL, AWS, Kubernetes, Hadoop",Associate,5,Education,2024-05-27,2024-07-17,1214,7.5,Advanced Robotics -AI09461,Data Scientist,89314,CAD,111643,MI,PT,Canada,L,Romania,0,"Python, TensorFlow, Data Visualization, Git, Statistics",PhD,3,Technology,2024-01-25,2024-03-12,590,9.3,DataVision Ltd -AI09462,Head of AI,131205,USD,131205,SE,CT,Ireland,L,Ireland,0,"R, Python, TensorFlow, Java",Associate,8,Finance,2024-10-17,2024-12-12,1799,7.1,Cognitive Computing -AI09463,ML Ops Engineer,236960,EUR,201416,EX,FT,Netherlands,S,Netherlands,50,"Data Visualization, R, Linux, Tableau",Associate,12,Media,2024-05-12,2024-07-10,1716,9.1,Neural Networks Co -AI09464,Research Scientist,70521,EUR,59943,EN,FL,Netherlands,M,Nigeria,50,"Git, Python, TensorFlow",Bachelor,1,Telecommunications,2024-09-23,2024-11-21,2406,9.2,Advanced Robotics -AI09465,NLP Engineer,22718,USD,22718,EN,CT,India,M,India,100,"Computer Vision, SQL, Python",PhD,1,Consulting,2025-04-28,2025-06-01,2464,6.6,AI Innovations -AI09466,Autonomous Systems Engineer,302715,USD,302715,EX,PT,Norway,L,New Zealand,0,"Tableau, Python, NLP, Git, MLOps",PhD,12,Technology,2025-01-28,2025-02-21,655,8.2,Future Systems -AI09467,Data Engineer,148771,USD,148771,SE,FL,Finland,L,Finland,100,"PyTorch, GCP, TensorFlow, AWS, Deep Learning",Master,8,Education,2024-12-09,2025-01-28,1688,9.1,Autonomous Tech -AI09468,Principal Data Scientist,168216,USD,168216,SE,CT,United States,M,United States,50,"GCP, Linux, Docker, Hadoop",Bachelor,6,Telecommunications,2024-12-07,2024-12-27,1732,8.8,DataVision Ltd -AI09469,AI Architect,83184,USD,83184,MI,FL,Sweden,L,Sweden,0,"MLOps, Data Visualization, Hadoop, Java, TensorFlow",Master,4,Real Estate,2024-06-03,2024-08-08,1248,8.2,Cloud AI Solutions -AI09470,Machine Learning Researcher,98439,USD,98439,SE,CT,South Korea,L,South Korea,100,"Python, Git, Computer Vision, NLP, R",Associate,8,Manufacturing,2024-07-25,2024-09-29,1463,7.7,TechCorp Inc -AI09471,ML Ops Engineer,164239,USD,164239,MI,PT,Denmark,L,Denmark,0,"Spark, Computer Vision, Kubernetes, Python, Linux",Bachelor,4,Gaming,2024-06-04,2024-07-26,802,8.3,Digital Transformation LLC -AI09472,AI Product Manager,96933,USD,96933,EN,PT,Norway,L,Nigeria,50,"Data Visualization, AWS, Hadoop, Computer Vision",Bachelor,1,Government,2025-04-21,2025-05-19,1741,8.3,Advanced Robotics -AI09473,Data Analyst,108451,USD,108451,EN,CT,Denmark,L,Denmark,0,"Python, Tableau, Azure",Bachelor,0,Retail,2024-03-30,2024-06-03,620,9,TechCorp Inc -AI09474,Robotics Engineer,63644,AUD,85919,EN,PT,Australia,S,Australia,100,"Docker, Azure, GCP, Python",Master,0,Manufacturing,2024-12-29,2025-02-06,886,6.7,DeepTech Ventures -AI09475,AI Specialist,199800,USD,199800,SE,PT,Norway,L,Norway,100,"GCP, Git, Java",PhD,8,Technology,2024-04-09,2024-05-30,716,6.2,AI Innovations -AI09476,Robotics Engineer,158584,USD,158584,SE,FL,Denmark,L,Denmark,100,"PyTorch, GCP, Scala, Linux, Deep Learning",Associate,8,Real Estate,2024-10-11,2024-11-13,1060,8.8,Future Systems -AI09477,Head of AI,200639,USD,200639,EX,FT,Israel,M,Israel,50,"Docker, Tableau, Python, GCP, Azure",Bachelor,17,Energy,2024-02-10,2024-04-03,2424,6.2,Quantum Computing Inc -AI09478,Research Scientist,76094,USD,76094,EX,FT,China,M,China,50,"GCP, R, NLP, Deep Learning",PhD,19,Automotive,2025-03-28,2025-06-06,612,9.8,Cloud AI Solutions -AI09479,AI Research Scientist,24147,USD,24147,MI,FT,India,S,India,50,"GCP, Computer Vision, Kubernetes, Linux, Data Visualization",Bachelor,3,Retail,2024-10-31,2024-12-02,950,9.5,Machine Intelligence Group -AI09480,AI Research Scientist,50123,EUR,42605,EN,PT,France,M,France,50,"Python, Spark, NLP, R",PhD,1,Manufacturing,2024-01-06,2024-03-10,540,5.5,Smart Analytics -AI09481,Robotics Engineer,110573,USD,110573,SE,CT,South Korea,L,South Korea,0,"NLP, GCP, Hadoop",Associate,7,Retail,2024-07-27,2024-09-07,798,5.2,DeepTech Ventures -AI09482,NLP Engineer,108897,USD,108897,MI,CT,Sweden,M,Norway,0,"Kubernetes, Python, TensorFlow, Docker, PyTorch",PhD,4,Automotive,2024-03-10,2024-05-06,715,8.6,Advanced Robotics -AI09483,Principal Data Scientist,330519,USD,330519,EX,PT,Norway,L,Norway,50,"Statistics, Azure, PyTorch, MLOps, SQL",Master,11,Consulting,2025-02-04,2025-03-03,544,5.8,Cloud AI Solutions -AI09484,Deep Learning Engineer,64196,JPY,7061560,EN,FL,Japan,S,Egypt,0,"Statistics, SQL, Data Visualization",Associate,0,Media,2025-03-23,2025-05-14,911,8,Machine Intelligence Group -AI09485,Data Analyst,112869,USD,112869,EX,FT,China,M,Latvia,50,"Scala, Python, NLP",PhD,19,Media,2025-04-28,2025-06-13,588,5.9,Quantum Computing Inc -AI09486,AI Software Engineer,64664,EUR,54964,EN,FL,Germany,M,Germany,100,"SQL, Hadoop, Kubernetes, PyTorch, AWS",Bachelor,0,Automotive,2024-11-30,2025-01-27,1161,7.8,Algorithmic Solutions -AI09487,AI Consultant,175674,JPY,19324140,SE,PT,Japan,L,Japan,0,"Hadoop, Java, PyTorch",Associate,7,Manufacturing,2024-01-31,2024-03-23,723,6.4,AI Innovations -AI09488,Data Analyst,95581,SGD,124255,MI,CT,Singapore,L,Hungary,0,"Git, Azure, Statistics, TensorFlow, Kubernetes",Associate,2,Manufacturing,2024-08-06,2024-09-03,1006,9.8,Advanced Robotics -AI09489,AI Software Engineer,158682,EUR,134880,SE,CT,Austria,L,Romania,50,"Data Visualization, Spark, Hadoop, MLOps, Scala",Associate,7,Telecommunications,2025-04-09,2025-05-22,2434,6.5,Advanced Robotics -AI09490,NLP Engineer,145879,SGD,189643,SE,PT,Singapore,M,Singapore,0,"Statistics, GCP, Azure",Associate,9,Energy,2024-06-29,2024-07-16,1866,6.5,Predictive Systems -AI09491,AI Specialist,196139,USD,196139,EX,CT,Israel,S,Denmark,50,"R, Mathematics, PyTorch, Kubernetes, Azure",PhD,11,Consulting,2024-11-13,2024-12-27,1979,9.4,AI Innovations -AI09492,Deep Learning Engineer,334470,USD,334470,EX,FL,Denmark,L,Denmark,100,"Git, Computer Vision, Deep Learning, Python, TensorFlow",PhD,13,Media,2025-01-26,2025-02-10,1594,7.8,Machine Intelligence Group -AI09493,Computer Vision Engineer,87626,USD,87626,MI,FT,Ireland,S,Ireland,100,"Java, Data Visualization, Hadoop, R",PhD,3,Technology,2024-12-15,2025-02-15,2127,6.5,Algorithmic Solutions -AI09494,Research Scientist,98110,USD,98110,EX,PT,China,S,China,0,"Azure, Python, Deep Learning",Associate,18,Healthcare,2024-06-23,2024-07-27,774,9.5,Predictive Systems -AI09495,AI Research Scientist,125951,CAD,157439,SE,PT,Canada,S,Brazil,100,"Linux, PyTorch, Kubernetes, Tableau, Git",Bachelor,9,Education,2024-05-31,2024-07-27,2495,7.2,DeepTech Ventures -AI09496,Data Analyst,86390,USD,86390,SE,FL,South Korea,M,Philippines,0,"Kubernetes, Mathematics, Scala, Docker",Bachelor,6,Healthcare,2024-06-06,2024-08-03,1154,7.5,Smart Analytics -AI09497,Data Engineer,28282,USD,28282,EN,FT,India,M,India,0,"R, Statistics, SQL, Azure",Associate,0,Technology,2025-04-05,2025-05-29,1646,5.6,Smart Analytics -AI09498,Data Scientist,145712,CHF,131141,MI,CT,Switzerland,M,South Africa,50,"Scala, Docker, NLP",Bachelor,2,Media,2024-11-01,2024-12-13,1336,6.5,Cognitive Computing -AI09499,Machine Learning Engineer,90645,EUR,77048,MI,CT,Germany,L,Germany,50,"Docker, SQL, GCP, TensorFlow",PhD,4,Healthcare,2025-02-08,2025-03-28,2137,8.3,Autonomous Tech -AI09500,Head of AI,82283,SGD,106968,EN,CT,Singapore,M,Singapore,0,"Spark, Hadoop, AWS, Data Visualization, Java",Associate,1,Gaming,2024-11-27,2024-12-20,1536,7.8,Algorithmic Solutions -AI09501,AI Architect,71045,USD,71045,EX,CT,India,M,India,100,"SQL, TensorFlow, MLOps, Docker, Python",Master,19,Manufacturing,2024-01-20,2024-03-20,717,5.9,Smart Analytics -AI09502,Data Scientist,62430,USD,62430,SE,CT,China,L,China,0,"Scala, Statistics, Python",Master,6,Technology,2024-10-23,2025-01-02,1617,9.3,Algorithmic Solutions -AI09503,Principal Data Scientist,106555,USD,106555,SE,FL,Finland,S,Finland,0,"R, Python, Hadoop",PhD,9,Finance,2024-04-07,2024-04-26,2418,7.8,DeepTech Ventures -AI09504,AI Software Engineer,71729,USD,71729,EN,PT,Finland,L,Finland,100,"SQL, Python, Azure",Master,0,Real Estate,2024-10-03,2024-11-30,1129,7.5,Autonomous Tech -AI09505,AI Architect,50504,EUR,42928,EN,FT,France,S,France,100,"TensorFlow, Statistics, MLOps, Tableau, Linux",Master,0,Telecommunications,2024-01-16,2024-03-05,808,9.4,Neural Networks Co -AI09506,Data Scientist,113850,AUD,153698,SE,CT,Australia,M,Australia,50,"SQL, Hadoop, Data Visualization",Master,9,Manufacturing,2024-11-18,2025-01-26,2066,9.5,TechCorp Inc -AI09507,NLP Engineer,315569,USD,315569,EX,PT,United States,L,United States,50,"Tableau, Scala, R, Statistics, TensorFlow",Associate,14,Technology,2024-04-22,2024-05-08,644,8,Future Systems -AI09508,Machine Learning Engineer,235397,GBP,176548,EX,FT,United Kingdom,L,Israel,0,"Java, SQL, Mathematics, Kubernetes",Master,15,Telecommunications,2025-02-05,2025-04-14,503,8.8,Cloud AI Solutions -AI09509,Machine Learning Engineer,126375,USD,126375,MI,FT,Denmark,L,Argentina,50,"Java, Kubernetes, TensorFlow, NLP",Master,4,Telecommunications,2024-03-02,2024-04-10,1297,9.7,DeepTech Ventures -AI09510,Research Scientist,64708,SGD,84120,EN,CT,Singapore,M,Switzerland,0,"Python, TensorFlow, Mathematics",Master,0,Education,2024-12-29,2025-03-06,2203,8.8,TechCorp Inc -AI09511,Research Scientist,128518,GBP,96389,SE,PT,United Kingdom,M,United Kingdom,100,"Hadoop, Data Visualization, Kubernetes, MLOps, AWS",Bachelor,7,Manufacturing,2024-10-15,2024-11-20,2401,7.7,Neural Networks Co -AI09512,Machine Learning Researcher,103052,USD,103052,SE,FL,South Korea,M,Vietnam,0,"Computer Vision, Spark, Tableau, Python",Associate,9,Telecommunications,2024-10-19,2024-12-15,1990,5.6,Future Systems -AI09513,Data Engineer,98700,EUR,83895,SE,FL,Netherlands,S,Finland,0,"Python, TensorFlow, Azure, Kubernetes",Master,8,Transportation,2024-01-29,2024-03-26,663,8.9,TechCorp Inc -AI09514,Principal Data Scientist,36797,USD,36797,MI,CT,India,L,Philippines,100,"AWS, Python, Kubernetes, Mathematics, Deep Learning",Bachelor,4,Energy,2024-11-23,2025-01-13,1780,8.4,Algorithmic Solutions -AI09515,Head of AI,171574,USD,171574,EX,PT,South Korea,S,South Korea,50,"NLP, Python, Spark, Linux, Java",Master,10,Finance,2024-04-17,2024-06-01,1404,8.9,DataVision Ltd -AI09516,Autonomous Systems Engineer,156283,JPY,17191130,SE,FT,Japan,M,Japan,50,"Data Visualization, R, PyTorch",Master,8,Real Estate,2024-11-29,2025-01-15,939,7.9,TechCorp Inc -AI09517,Robotics Engineer,66972,JPY,7366920,EN,FT,Japan,L,Argentina,50,"Scala, Git, Python, Mathematics, Azure",Associate,0,Consulting,2025-03-20,2025-04-27,769,8.7,Smart Analytics -AI09518,Computer Vision Engineer,122877,CHF,110589,MI,FT,Switzerland,M,Switzerland,50,"Kubernetes, MLOps, SQL, Java, PyTorch",PhD,2,Real Estate,2024-08-12,2024-10-19,1550,5.4,Neural Networks Co -AI09519,Data Analyst,245072,USD,245072,EX,FL,United States,L,United States,100,"Mathematics, R, Scala, Hadoop",Master,15,Technology,2024-12-27,2025-02-16,1935,7.8,Quantum Computing Inc -AI09520,Data Engineer,43038,USD,43038,MI,FT,China,S,China,100,"Spark, SQL, MLOps",PhD,2,Telecommunications,2024-04-08,2024-05-23,1670,8.3,Future Systems -AI09521,Autonomous Systems Engineer,111598,EUR,94858,MI,CT,France,L,France,0,"Computer Vision, Linux, SQL",Associate,4,Consulting,2025-02-18,2025-04-11,2363,8.2,Predictive Systems -AI09522,NLP Engineer,251849,JPY,27703390,EX,PT,Japan,L,Japan,0,"Scala, Docker, GCP",PhD,15,Transportation,2024-04-06,2024-05-17,2248,6.3,Digital Transformation LLC -AI09523,Data Analyst,110989,USD,110989,MI,CT,Norway,M,Hungary,0,"Mathematics, Azure, SQL",PhD,3,Government,2024-06-23,2024-08-23,1859,7.8,Autonomous Tech -AI09524,Data Engineer,127024,USD,127024,SE,CT,United States,S,Chile,0,"Java, MLOps, Spark",PhD,8,Gaming,2024-06-21,2024-08-02,1861,7.6,Quantum Computing Inc -AI09525,Research Scientist,332546,USD,332546,EX,FL,Denmark,L,Denmark,100,"MLOps, Azure, Tableau, Python, TensorFlow",Bachelor,14,Energy,2024-01-11,2024-03-04,1609,8.8,Future Systems -AI09526,Head of AI,133295,AUD,179948,SE,CT,Australia,M,Australia,0,"Python, AWS, NLP",Master,5,Consulting,2024-03-09,2024-05-05,2345,7.6,AI Innovations -AI09527,AI Research Scientist,86259,CAD,107824,MI,PT,Canada,L,Canada,50,"Tableau, Computer Vision, PyTorch",Associate,3,Education,2024-04-23,2024-06-08,1409,6.3,Predictive Systems -AI09528,Research Scientist,110503,USD,110503,MI,FL,Norway,M,Norway,0,"AWS, SQL, Tableau",Associate,3,Real Estate,2025-03-27,2025-04-11,1252,9,Algorithmic Solutions -AI09529,AI Architect,108797,EUR,92477,MI,CT,Netherlands,M,Netherlands,50,"AWS, Docker, Mathematics",Bachelor,4,Transportation,2024-08-13,2024-10-08,1802,8.4,Autonomous Tech -AI09530,Data Analyst,184018,USD,184018,EX,PT,South Korea,L,South Korea,0,"Statistics, Data Visualization, Azure, Linux",Master,17,Real Estate,2024-04-13,2024-05-21,1346,6.3,Digital Transformation LLC -AI09531,AI Software Engineer,147794,SGD,192132,SE,PT,Singapore,M,Singapore,100,"Python, TensorFlow, Kubernetes, Hadoop",Associate,6,Government,2024-08-27,2024-09-29,815,9.6,Future Systems -AI09532,Autonomous Systems Engineer,71774,JPY,7895140,MI,FL,Japan,S,Japan,50,"SQL, Git, Tableau",PhD,3,Manufacturing,2024-01-28,2024-03-05,1074,5.2,Cognitive Computing -AI09533,Data Scientist,219834,EUR,186859,EX,PT,Austria,M,Austria,0,"Linux, Statistics, MLOps",Master,18,Retail,2025-04-22,2025-05-12,1865,6.1,AI Innovations -AI09534,ML Ops Engineer,186565,USD,186565,EX,FL,South Korea,M,South Korea,100,"MLOps, Statistics, Python",PhD,17,Manufacturing,2024-07-10,2024-09-19,538,5.1,Digital Transformation LLC -AI09535,Data Analyst,27602,USD,27602,EN,FT,China,M,China,0,"R, Scala, SQL, PyTorch",Bachelor,1,Real Estate,2024-08-26,2024-09-10,885,6.1,Cognitive Computing -AI09536,Robotics Engineer,57129,USD,57129,EN,PT,Israel,S,Israel,50,"Spark, Python, SQL, Azure",PhD,1,Manufacturing,2025-03-20,2025-05-21,1666,8.3,Predictive Systems -AI09537,AI Consultant,22217,USD,22217,EN,FT,India,S,India,100,"SQL, GCP, Statistics, Mathematics, PyTorch",Master,0,Real Estate,2024-12-05,2025-01-06,1760,9.9,AI Innovations -AI09538,Head of AI,67864,USD,67864,EX,PT,China,S,Turkey,0,"Hadoop, Deep Learning, Docker, Mathematics, Scala",Associate,19,Retail,2024-04-21,2024-06-06,501,7.2,Autonomous Tech -AI09539,AI Research Scientist,84278,EUR,71636,EN,FT,Germany,L,Germany,50,"Git, Data Visualization, Scala, Azure, Statistics",PhD,0,Media,2024-08-12,2024-10-18,1838,9.5,Advanced Robotics -AI09540,Machine Learning Researcher,116369,USD,116369,SE,FL,South Korea,M,South Korea,0,"Docker, Linux, Spark, Mathematics, NLP",Associate,5,Technology,2024-11-02,2024-12-15,2197,7.7,Machine Intelligence Group -AI09541,AI Specialist,110779,USD,110779,SE,FT,Israel,M,Israel,0,"PyTorch, NLP, Java, R, Computer Vision",Associate,7,Government,2025-02-15,2025-04-23,1776,6.2,Neural Networks Co -AI09542,Data Scientist,285402,USD,285402,EX,FL,Denmark,S,Denmark,50,"TensorFlow, R, Docker, Mathematics, Data Visualization",Bachelor,11,Real Estate,2024-12-30,2025-01-13,1349,6,Quantum Computing Inc -AI09543,NLP Engineer,169619,USD,169619,SE,FT,Norway,M,Norway,100,"GCP, Linux, Docker, Python",PhD,9,Consulting,2024-03-19,2024-05-03,1063,9.2,Quantum Computing Inc -AI09544,Data Scientist,119460,USD,119460,EX,CT,South Korea,S,South Korea,50,"Scala, Kubernetes, Hadoop, Git, Computer Vision",Master,16,Government,2025-02-05,2025-03-06,1333,8.1,Quantum Computing Inc -AI09545,Data Engineer,141162,USD,141162,MI,CT,Denmark,M,Kenya,0,"MLOps, Python, TensorFlow, Kubernetes",PhD,2,Technology,2024-04-21,2024-06-06,947,8.8,Future Systems -AI09546,AI Specialist,125984,USD,125984,SE,PT,Israel,S,Israel,0,"Scala, Tableau, Mathematics, Azure",Associate,9,Gaming,2025-03-20,2025-05-22,1335,8,Future Systems -AI09547,Robotics Engineer,121116,EUR,102949,SE,FL,France,L,France,50,"GCP, Scala, MLOps",Bachelor,8,Media,2025-02-02,2025-03-16,2159,8.7,Cognitive Computing -AI09548,Robotics Engineer,116096,SGD,150925,MI,CT,Singapore,L,Malaysia,100,"Tableau, Python, Linux, Hadoop, TensorFlow",Associate,3,Energy,2024-03-28,2024-05-08,1044,5,Autonomous Tech -AI09549,AI Architect,120313,USD,120313,SE,PT,Ireland,M,Ireland,50,"Python, Docker, Data Visualization",PhD,6,Consulting,2024-06-23,2024-07-22,1587,8.8,TechCorp Inc -AI09550,AI Software Engineer,136464,USD,136464,SE,FT,Ireland,L,Ireland,100,"Tableau, Linux, TensorFlow",Master,9,Transportation,2024-10-11,2024-12-03,1255,9.4,Digital Transformation LLC -AI09551,AI Research Scientist,95934,USD,95934,MI,FT,Israel,M,Israel,50,"Python, Data Visualization, Java, Azure",Bachelor,2,Government,2024-12-20,2025-01-10,2205,9.7,Autonomous Tech -AI09552,AI Software Engineer,85570,CHF,77013,EN,FT,Switzerland,S,Switzerland,50,"Kubernetes, Computer Vision, Scala, Python",Master,0,Finance,2024-06-16,2024-07-11,2114,6.6,Autonomous Tech -AI09553,AI Research Scientist,61645,AUD,83221,EN,CT,Australia,L,Singapore,50,"Kubernetes, Python, Scala, Computer Vision, TensorFlow",Bachelor,1,Gaming,2024-11-06,2024-11-22,2038,5.6,Algorithmic Solutions -AI09554,NLP Engineer,83872,EUR,71291,MI,FL,Austria,S,Austria,100,"GCP, Scala, Deep Learning, SQL, Computer Vision",Associate,4,Consulting,2024-12-21,2025-01-07,1490,8.8,Quantum Computing Inc -AI09555,Computer Vision Engineer,102899,EUR,87464,MI,FL,Austria,L,Austria,50,"Spark, Scala, Deep Learning, Data Visualization, TensorFlow",PhD,3,Real Estate,2024-11-08,2024-11-30,2454,5.4,Algorithmic Solutions -AI09556,Data Engineer,71513,SGD,92967,EN,FL,Singapore,S,United Kingdom,100,"Scala, Linux, Computer Vision, Kubernetes, Git",Master,0,Manufacturing,2024-10-29,2024-12-10,1345,8.4,Predictive Systems -AI09557,Machine Learning Engineer,115012,USD,115012,SE,FT,South Korea,M,China,0,"Java, R, Kubernetes, Docker",Associate,9,Technology,2024-09-26,2024-11-16,984,5.2,Neural Networks Co -AI09558,Machine Learning Engineer,47215,CAD,59019,EN,PT,Canada,S,Canada,100,"Kubernetes, TensorFlow, Docker",Bachelor,0,Technology,2024-06-11,2024-08-20,1165,6.6,AI Innovations -AI09559,AI Specialist,118372,EUR,100616,SE,FL,France,L,Belgium,100,"Linux, Spark, AWS, Deep Learning",PhD,8,Energy,2025-04-08,2025-05-18,1304,5,Cloud AI Solutions -AI09560,Computer Vision Engineer,147836,AUD,199579,SE,CT,Australia,L,Australia,50,"Git, Kubernetes, SQL, GCP, Azure",Bachelor,8,Manufacturing,2024-04-16,2024-05-11,1611,5.6,DataVision Ltd -AI09561,Data Analyst,224535,EUR,190855,EX,FT,Germany,M,Germany,0,"Statistics, SQL, Azure, Python",Associate,15,Education,2025-02-06,2025-03-10,1882,6.8,Predictive Systems -AI09562,AI Software Engineer,138016,USD,138016,SE,CT,Denmark,M,Denmark,50,"Python, Scala, NLP, Git",Associate,8,Government,2024-08-27,2024-10-11,2108,9.4,Future Systems -AI09563,AI Consultant,93538,USD,93538,EN,PT,Norway,S,Norway,0,"Kubernetes, PyTorch, Statistics",PhD,0,Manufacturing,2024-10-26,2024-12-02,2026,9.3,TechCorp Inc -AI09564,Computer Vision Engineer,120674,USD,120674,SE,PT,United States,S,United States,50,"NLP, Docker, Git",PhD,9,Transportation,2024-10-26,2024-12-23,634,6.2,Autonomous Tech -AI09565,AI Architect,299206,CHF,269285,EX,CT,Switzerland,S,Chile,50,"PyTorch, Linux, MLOps, TensorFlow",PhD,11,Telecommunications,2025-04-22,2025-06-13,1150,8.1,Future Systems -AI09566,AI Specialist,128478,AUD,173445,SE,CT,Australia,L,Australia,50,"Python, TensorFlow, Azure",Master,6,Government,2024-04-17,2024-05-17,1949,7.9,Digital Transformation LLC -AI09567,Machine Learning Researcher,60265,AUD,81358,EN,PT,Australia,M,Australia,50,"Computer Vision, Java, MLOps",Master,1,Gaming,2024-03-16,2024-05-17,773,6.6,Autonomous Tech -AI09568,Computer Vision Engineer,279290,USD,279290,EX,PT,Denmark,S,Hungary,50,"Git, R, Scala, Docker, MLOps",Master,16,Government,2024-06-24,2024-07-23,1099,7.6,DataVision Ltd -AI09569,Computer Vision Engineer,110511,CAD,138139,SE,FT,Canada,L,Estonia,0,"Python, TensorFlow, Linux",Associate,9,Telecommunications,2025-01-08,2025-01-30,2403,9.4,Smart Analytics -AI09570,Data Analyst,108968,USD,108968,SE,CT,South Korea,S,South Korea,100,"PyTorch, Spark, Git, Kubernetes",Associate,8,Technology,2025-04-02,2025-04-22,1818,6.1,Machine Intelligence Group -AI09571,Data Engineer,81290,GBP,60968,MI,FT,United Kingdom,S,Switzerland,0,"Kubernetes, R, PyTorch",Bachelor,3,Consulting,2025-02-27,2025-04-14,1907,6.4,Predictive Systems -AI09572,Robotics Engineer,191881,CHF,172693,SE,FL,Switzerland,S,Switzerland,50,"Kubernetes, MLOps, Python, Spark",Bachelor,5,Transportation,2024-12-16,2025-01-19,1266,5.1,Predictive Systems -AI09573,Robotics Engineer,106589,CHF,95930,MI,FT,Switzerland,M,Switzerland,100,"Mathematics, AWS, Computer Vision, TensorFlow",Master,2,Manufacturing,2024-09-28,2024-10-21,1384,6.9,Cognitive Computing -AI09574,Machine Learning Engineer,97626,USD,97626,MI,PT,Ireland,L,Austria,100,"Scala, PyTorch, MLOps",Bachelor,3,Telecommunications,2024-10-04,2024-11-26,2239,8.1,Autonomous Tech -AI09575,AI Architect,141618,USD,141618,MI,FT,Denmark,L,Italy,0,"Data Visualization, Scala, Docker, Python, TensorFlow",Master,2,Government,2024-02-18,2024-04-10,1654,5.2,Digital Transformation LLC -AI09576,Autonomous Systems Engineer,95458,EUR,81139,MI,FL,Netherlands,L,Argentina,0,"Linux, SQL, Java",Bachelor,4,Education,2025-03-25,2025-04-22,2104,6.8,AI Innovations -AI09577,Robotics Engineer,105315,CHF,94784,MI,FL,Switzerland,S,Vietnam,100,"Azure, Python, Linux",PhD,3,Technology,2025-03-22,2025-04-23,507,6.3,DataVision Ltd -AI09578,AI Specialist,71116,EUR,60449,MI,PT,Austria,S,Austria,50,"Mathematics, TensorFlow, Python, Computer Vision, Azure",Master,3,Finance,2025-01-11,2025-03-22,2210,6.9,DeepTech Ventures -AI09579,Autonomous Systems Engineer,82679,EUR,70277,EN,FT,Netherlands,L,China,0,"Scala, NLP, GCP",Associate,0,Automotive,2024-03-14,2024-04-12,1625,8.7,Algorithmic Solutions -AI09580,Machine Learning Engineer,177922,EUR,151234,EX,FT,Germany,S,Germany,0,"Data Visualization, Git, TensorFlow",Associate,12,Healthcare,2024-12-05,2025-01-23,1334,9.3,DeepTech Ventures -AI09581,Data Scientist,31465,USD,31465,EN,FT,India,L,India,0,"Scala, Linux, SQL, PyTorch",Master,1,Transportation,2024-05-23,2024-06-11,1808,6.1,DeepTech Ventures -AI09582,AI Specialist,114364,USD,114364,EN,FL,Denmark,L,Denmark,0,"AWS, NLP, Tableau, Docker",Bachelor,1,Finance,2024-08-24,2024-10-02,582,7.7,DeepTech Ventures -AI09583,Data Scientist,206549,USD,206549,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, MLOps",Associate,15,Gaming,2024-05-04,2024-06-07,2093,8,Neural Networks Co -AI09584,Computer Vision Engineer,112749,EUR,95837,SE,FL,Germany,M,Turkey,100,"Hadoop, Git, Computer Vision, R, Java",PhD,6,Education,2024-09-09,2024-11-10,2317,7.4,DataVision Ltd -AI09585,Machine Learning Researcher,97146,EUR,82574,MI,CT,France,M,France,50,"PyTorch, AWS, Hadoop, Azure, Deep Learning",PhD,2,Real Estate,2025-01-13,2025-01-27,1832,7.3,DeepTech Ventures -AI09586,Research Scientist,35698,USD,35698,SE,FL,India,S,India,0,"Linux, GCP, PyTorch, NLP, Scala",Associate,5,Media,2024-02-02,2024-04-10,2048,5.7,Future Systems -AI09587,AI Research Scientist,64209,USD,64209,EN,CT,Israel,M,Israel,100,"Tableau, GCP, Java",Master,1,Telecommunications,2024-07-22,2024-09-02,1711,6.1,Advanced Robotics -AI09588,Robotics Engineer,108749,USD,108749,EN,FT,United States,L,United States,100,"Mathematics, Python, TensorFlow, GCP",Bachelor,0,Manufacturing,2024-10-14,2024-11-09,1228,7.8,DeepTech Ventures -AI09589,AI Research Scientist,78664,USD,78664,MI,CT,Sweden,M,Australia,50,"TensorFlow, Python, GCP, Deep Learning, NLP",Associate,4,Finance,2024-11-26,2024-12-31,1225,9.1,Predictive Systems -AI09590,Autonomous Systems Engineer,72106,SGD,93738,MI,CT,Singapore,S,Singapore,0,"Data Visualization, Python, AWS, GCP, TensorFlow",Associate,4,Government,2024-01-04,2024-03-10,2323,9.6,TechCorp Inc -AI09591,Deep Learning Engineer,41945,USD,41945,MI,FL,China,S,China,0,"TensorFlow, Deep Learning, Data Visualization, Hadoop",PhD,2,Technology,2024-11-01,2025-01-07,2002,5.6,DataVision Ltd -AI09592,AI Consultant,135711,USD,135711,SE,FL,Sweden,S,Sweden,100,"Docker, Tableau, GCP, PyTorch, Statistics",Master,8,Government,2024-11-23,2024-12-07,2244,7.9,Advanced Robotics -AI09593,NLP Engineer,311228,USD,311228,EX,FL,United States,L,United States,50,"Python, Computer Vision, Linux, Spark, TensorFlow",Bachelor,17,Gaming,2024-05-19,2024-06-25,1679,5.7,Neural Networks Co -AI09594,Deep Learning Engineer,80311,USD,80311,EN,FL,Denmark,S,Denmark,50,"TensorFlow, Kubernetes, Git",Master,1,Telecommunications,2024-07-30,2024-09-14,663,6.3,Advanced Robotics -AI09595,Computer Vision Engineer,140434,USD,140434,EX,CT,Finland,M,Finland,100,"Azure, Python, Docker",Associate,17,Real Estate,2024-04-03,2024-05-17,1737,8.8,Autonomous Tech -AI09596,AI Architect,242982,USD,242982,EX,FT,Norway,S,Norway,100,"Spark, NLP, Python, TensorFlow",Associate,10,Retail,2024-03-31,2024-06-11,2335,6.4,Digital Transformation LLC -AI09597,Deep Learning Engineer,71755,USD,71755,EN,PT,Finland,L,Finland,100,"Tableau, PyTorch, Deep Learning, Git, TensorFlow",PhD,1,Retail,2024-08-04,2024-10-03,2271,8.7,DeepTech Ventures -AI09598,AI Software Engineer,31328,USD,31328,MI,CT,India,L,India,100,"Git, Scala, Computer Vision",Master,2,Telecommunications,2024-09-25,2024-11-07,1426,6,TechCorp Inc -AI09599,Data Engineer,108210,USD,108210,SE,PT,South Korea,L,South Korea,100,"Kubernetes, Deep Learning, Spark",Bachelor,9,Energy,2024-04-26,2024-06-04,925,8.1,AI Innovations -AI09600,NLP Engineer,127242,GBP,95432,SE,PT,United Kingdom,M,United Kingdom,100,"SQL, Kubernetes, Scala, AWS",Associate,9,Healthcare,2025-01-21,2025-04-03,1609,9.1,Algorithmic Solutions -AI09601,AI Software Engineer,122440,USD,122440,SE,CT,Finland,L,Finland,100,"Kubernetes, Spark, Hadoop, Git",Bachelor,7,Finance,2024-05-25,2024-06-20,1905,9.4,Smart Analytics -AI09602,Data Analyst,163000,USD,163000,EX,FT,Ireland,M,Belgium,100,"Scala, Linux, MLOps",Associate,17,Gaming,2025-01-09,2025-02-02,502,7.4,DataVision Ltd -AI09603,Machine Learning Researcher,238582,JPY,26244020,EX,FL,Japan,M,Japan,0,"Azure, Scala, Hadoop, Git",Master,12,Finance,2025-01-08,2025-02-10,773,7.3,AI Innovations -AI09604,ML Ops Engineer,56341,USD,56341,EN,PT,South Korea,M,South Korea,0,"SQL, Tableau, PyTorch",Bachelor,1,Media,2024-10-31,2024-12-01,815,7.9,TechCorp Inc -AI09605,ML Ops Engineer,82286,GBP,61715,EN,FL,United Kingdom,L,United Kingdom,50,"Java, Computer Vision, SQL, Deep Learning, PyTorch",Associate,1,Telecommunications,2025-02-24,2025-04-02,1160,7.2,TechCorp Inc -AI09606,ML Ops Engineer,206792,USD,206792,EX,FL,Norway,M,Norway,0,"Scala, GCP, PyTorch",Associate,10,Manufacturing,2024-08-27,2024-10-21,550,7.3,Smart Analytics -AI09607,Data Engineer,111725,EUR,94966,MI,PT,France,L,Russia,100,"Mathematics, MLOps, Data Visualization, Kubernetes",PhD,4,Real Estate,2024-07-24,2024-08-15,1981,5.9,Cloud AI Solutions -AI09608,Principal Data Scientist,256576,USD,256576,EX,FL,Finland,L,Ukraine,0,"Git, R, Computer Vision",Master,14,Finance,2024-04-28,2024-05-29,2329,8.6,Machine Intelligence Group -AI09609,NLP Engineer,157172,EUR,133596,EX,CT,France,S,France,100,"TensorFlow, Docker, Git",PhD,10,Manufacturing,2024-12-17,2025-02-24,703,7.4,AI Innovations -AI09610,Data Analyst,38565,USD,38565,MI,CT,India,L,India,50,"AWS, Computer Vision, SQL",Associate,3,Transportation,2024-09-16,2024-11-19,551,10,Cloud AI Solutions -AI09611,Principal Data Scientist,93643,CHF,84279,EN,FT,Switzerland,S,Egypt,0,"Python, Git, Computer Vision, Deep Learning, Linux",Associate,1,Healthcare,2024-11-15,2025-01-01,651,8.2,Cognitive Computing -AI09612,AI Product Manager,349386,CHF,314447,EX,PT,Switzerland,L,Switzerland,100,"Git, Tableau, TensorFlow",Associate,11,Retail,2024-10-02,2024-12-13,2214,9.4,Cloud AI Solutions -AI09613,ML Ops Engineer,135479,EUR,115157,EX,FT,Austria,S,Austria,50,"SQL, TensorFlow, Tableau, Hadoop, Spark",Bachelor,19,Telecommunications,2025-02-12,2025-04-19,2223,6.1,TechCorp Inc -AI09614,AI Architect,18474,USD,18474,EN,FL,India,S,Netherlands,50,"Git, Deep Learning, Scala, Java, Tableau",Master,1,Technology,2024-03-21,2024-05-07,1106,6.3,Quantum Computing Inc -AI09615,Deep Learning Engineer,84485,USD,84485,SE,FT,South Korea,M,South Korea,50,"TensorFlow, Python, Spark, SQL, AWS",Master,9,Telecommunications,2024-06-08,2024-06-25,1760,8.1,TechCorp Inc -AI09616,Data Engineer,108371,USD,108371,EN,PT,Denmark,L,Denmark,0,"AWS, Tableau, Hadoop",Bachelor,1,Energy,2024-07-29,2024-10-04,710,9.1,Algorithmic Solutions -AI09617,Data Analyst,115972,EUR,98576,SE,FL,Austria,L,Austria,0,"Deep Learning, GCP, Data Visualization, MLOps, NLP",Master,7,Government,2024-09-09,2024-10-17,1584,9.2,Quantum Computing Inc -AI09618,Computer Vision Engineer,107070,USD,107070,MI,CT,Norway,M,Norway,100,"Python, Docker, Azure, Spark",Bachelor,3,Retail,2024-02-09,2024-03-11,642,9.4,DataVision Ltd -AI09619,AI Consultant,63084,USD,63084,EN,FT,Sweden,L,Sweden,50,"Hadoop, Azure, Data Visualization, NLP",Master,0,Automotive,2024-06-20,2024-07-22,1427,5,Digital Transformation LLC -AI09620,Head of AI,152429,USD,152429,MI,CT,Denmark,L,Denmark,0,"TensorFlow, Mathematics, Azure, SQL",Associate,3,Retail,2024-09-18,2024-11-01,2456,9.6,Quantum Computing Inc -AI09621,Computer Vision Engineer,61740,USD,61740,SE,FT,India,L,Estonia,0,"Azure, Java, Deep Learning",PhD,6,Education,2024-05-26,2024-07-17,1435,7.1,Neural Networks Co -AI09622,Autonomous Systems Engineer,135651,USD,135651,SE,CT,Sweden,S,Sweden,50,"Mathematics, Python, TensorFlow, Tableau",Bachelor,5,Retail,2025-04-29,2025-06-07,626,7,Autonomous Tech -AI09623,Computer Vision Engineer,91734,USD,91734,MI,FT,Israel,L,Israel,50,"Scala, SQL, PyTorch, Spark",Associate,3,Transportation,2024-03-07,2024-04-03,2414,7.9,Digital Transformation LLC -AI09624,ML Ops Engineer,178754,USD,178754,SE,PT,United States,L,United States,0,"Python, Kubernetes, Spark, TensorFlow",Associate,7,Gaming,2024-03-28,2024-04-15,2228,9.3,DataVision Ltd -AI09625,Data Analyst,141292,USD,141292,SE,FL,Denmark,S,Denmark,50,"AWS, SQL, Data Visualization, Statistics, Git",Master,5,Energy,2024-12-03,2025-01-22,1969,7.3,Cloud AI Solutions -AI09626,Data Scientist,63976,CAD,79970,EN,FT,Canada,S,Egypt,0,"Spark, PyTorch, Statistics, Data Visualization, R",Associate,1,Technology,2024-08-20,2024-09-20,1847,6.2,Machine Intelligence Group -AI09627,Principal Data Scientist,172992,USD,172992,SE,FT,United States,L,United States,100,"TensorFlow, Python, Deep Learning",Bachelor,6,Healthcare,2024-01-05,2024-02-22,802,7,DeepTech Ventures -AI09628,Data Engineer,274237,USD,274237,EX,PT,Ireland,L,Ireland,50,"Docker, AWS, PyTorch, GCP",Master,12,Gaming,2024-08-27,2024-10-15,1234,8.1,AI Innovations -AI09629,Deep Learning Engineer,191469,USD,191469,EX,FT,Israel,M,Israel,50,"Python, Azure, Data Visualization, TensorFlow",PhD,13,Retail,2025-01-29,2025-02-12,543,6.7,Predictive Systems -AI09630,Research Scientist,203503,EUR,172978,EX,FT,Netherlands,L,Netherlands,50,"Python, AWS, Computer Vision, Linux, TensorFlow",Bachelor,19,Consulting,2025-02-27,2025-05-04,552,7.5,Digital Transformation LLC -AI09631,NLP Engineer,101614,EUR,86372,SE,PT,Austria,S,Austria,100,"Hadoop, Java, NLP, Deep Learning",PhD,6,Retail,2025-04-24,2025-06-07,1662,7.3,TechCorp Inc -AI09632,Machine Learning Engineer,72890,SGD,94757,EN,PT,Singapore,M,Chile,100,"TensorFlow, Kubernetes, Git",Master,0,Retail,2024-02-06,2024-04-12,2204,9.7,Smart Analytics -AI09633,Deep Learning Engineer,241369,USD,241369,EX,CT,Israel,L,Israel,50,"Computer Vision, Git, Mathematics",Master,11,Technology,2024-05-25,2024-08-03,1757,9.2,Algorithmic Solutions -AI09634,Data Analyst,80985,JPY,8908350,EN,PT,Japan,M,Japan,50,"Python, PyTorch, Spark, Mathematics, AWS",PhD,0,Technology,2024-03-16,2024-04-12,749,6.3,Machine Intelligence Group -AI09635,Computer Vision Engineer,48693,USD,48693,SE,FL,China,S,China,0,"Git, Python, NLP, Data Visualization",PhD,6,Healthcare,2024-02-09,2024-04-17,2083,8.9,Predictive Systems -AI09636,AI Software Engineer,120364,USD,120364,SE,FT,Ireland,M,Ireland,100,"Python, Tableau, MLOps, Azure, Computer Vision",PhD,6,Telecommunications,2024-08-20,2024-09-28,632,6.3,Cognitive Computing -AI09637,Data Analyst,119327,EUR,101428,SE,FL,France,M,Nigeria,100,"Mathematics, AWS, Tableau",Master,9,Education,2025-02-17,2025-04-26,1137,7.8,Autonomous Tech -AI09638,ML Ops Engineer,52959,USD,52959,EN,FL,Finland,S,Finland,0,"Java, MLOps, Python, Linux",Associate,1,Telecommunications,2024-11-07,2024-11-23,2153,9.6,DataVision Ltd -AI09639,Principal Data Scientist,44848,USD,44848,EN,PT,South Korea,S,South Korea,0,"Python, TensorFlow, Deep Learning, Linux, Computer Vision",Bachelor,1,Real Estate,2025-03-10,2025-05-20,615,8.8,Future Systems -AI09640,AI Software Engineer,279410,JPY,30735100,EX,CT,Japan,L,Japan,0,"R, Tableau, SQL, Computer Vision, Linux",Master,19,Healthcare,2024-09-30,2024-11-15,898,9.2,Neural Networks Co -AI09641,AI Product Manager,276943,USD,276943,EX,FL,Norway,S,Norway,0,"PyTorch, GCP, Statistics, Tableau",PhD,18,Automotive,2024-12-21,2025-02-03,1529,8.8,Future Systems -AI09642,Autonomous Systems Engineer,190274,USD,190274,SE,FT,Denmark,M,Denmark,0,"AWS, SQL, Kubernetes",Associate,9,Telecommunications,2024-01-12,2024-01-27,1114,9.4,AI Innovations -AI09643,Data Scientist,98262,JPY,10808820,EN,FL,Japan,L,France,0,"Python, SQL, Hadoop, Statistics",PhD,1,Manufacturing,2024-04-03,2024-04-28,1441,5.3,Future Systems -AI09644,AI Research Scientist,70103,USD,70103,EN,PT,South Korea,L,South Korea,100,"Mathematics, Computer Vision, Spark",Bachelor,1,Automotive,2024-02-20,2024-03-20,2351,5.5,Digital Transformation LLC -AI09645,Deep Learning Engineer,244222,USD,244222,EX,CT,Sweden,M,Israel,100,"PyTorch, TensorFlow, Deep Learning, Data Visualization, SQL",PhD,14,Energy,2024-03-18,2024-05-15,909,6.5,DataVision Ltd -AI09646,AI Software Engineer,98207,USD,98207,MI,FL,Sweden,S,Sweden,50,"R, Hadoop, Tableau, SQL, GCP",Associate,4,Real Estate,2024-09-26,2024-11-20,2490,8.4,Predictive Systems -AI09647,Machine Learning Engineer,74097,USD,74097,MI,CT,Finland,S,Brazil,50,"Hadoop, Python, MLOps",Master,4,Healthcare,2024-04-21,2024-05-11,2339,9.1,Quantum Computing Inc -AI09648,AI Specialist,57153,JPY,6286830,EN,CT,Japan,M,Japan,100,"TensorFlow, Scala, Docker, Hadoop",Master,1,Telecommunications,2024-09-12,2024-10-21,2307,8.8,DeepTech Ventures -AI09649,Research Scientist,99157,EUR,84283,MI,CT,France,M,Switzerland,0,"SQL, Hadoop, PyTorch",Master,3,Education,2024-04-23,2024-06-29,1974,9.2,Cloud AI Solutions -AI09650,AI Product Manager,104851,USD,104851,SE,CT,Israel,S,Israel,50,"Git, R, Python, Deep Learning, Java",Master,8,Automotive,2024-02-15,2024-04-26,2450,5.3,Quantum Computing Inc -AI09651,AI Specialist,70704,USD,70704,EN,CT,United States,M,United States,50,"Data Visualization, MLOps, Scala, Statistics, R",Master,1,Real Estate,2024-10-06,2024-12-11,513,5.8,Autonomous Tech -AI09652,AI Research Scientist,86595,AUD,116903,MI,FT,Australia,M,Australia,100,"Spark, TensorFlow, NLP",Master,4,Transportation,2025-01-04,2025-03-02,1800,5.7,Cognitive Computing -AI09653,Autonomous Systems Engineer,139992,USD,139992,SE,PT,Ireland,M,Egypt,0,"Mathematics, Python, Kubernetes",Master,5,Telecommunications,2024-04-30,2024-06-11,1651,8.9,Machine Intelligence Group -AI09654,AI Consultant,69365,EUR,58960,MI,CT,Germany,S,Germany,100,"Scala, Deep Learning, MLOps, Hadoop",PhD,2,Government,2024-01-25,2024-03-31,2284,7.6,Future Systems -AI09655,Data Engineer,98050,USD,98050,MI,FT,Finland,L,Finland,0,"Kubernetes, R, MLOps, Deep Learning, Scala",PhD,2,Telecommunications,2024-06-10,2024-07-19,1741,7,Smart Analytics -AI09656,AI Architect,20880,USD,20880,EN,CT,India,M,India,50,"Spark, Git, Kubernetes, Python",Bachelor,1,Finance,2024-05-11,2024-07-15,603,6.6,Cloud AI Solutions -AI09657,AI Research Scientist,80608,SGD,104790,EN,CT,Singapore,L,Singapore,0,"Scala, R, Hadoop, Deep Learning",PhD,0,Government,2025-04-04,2025-06-08,1483,5.4,Algorithmic Solutions -AI09658,Research Scientist,121634,CHF,109471,EN,PT,Switzerland,L,Czech Republic,50,"Python, Hadoop, AWS",Associate,1,Gaming,2024-03-08,2024-05-19,2259,8.4,Advanced Robotics -AI09659,Principal Data Scientist,200363,EUR,170309,EX,CT,Austria,L,Austria,100,"Tableau, Statistics, TensorFlow, Python",Bachelor,19,Technology,2025-01-07,2025-01-26,2480,7.7,Smart Analytics -AI09660,Machine Learning Researcher,65086,USD,65086,EN,FL,United States,S,United States,0,"Python, Linux, Tableau",PhD,1,Technology,2024-10-04,2024-11-23,2294,6.6,Predictive Systems -AI09661,Machine Learning Engineer,76722,USD,76722,EN,FT,Norway,S,Argentina,50,"Computer Vision, Spark, R, Hadoop, Docker",PhD,0,Government,2024-02-28,2024-05-05,1503,9.2,DataVision Ltd -AI09662,Data Engineer,136698,EUR,116193,SE,FL,Germany,M,Australia,0,"Statistics, Scala, SQL, Hadoop",Master,5,Healthcare,2024-07-28,2024-09-29,1467,8.3,TechCorp Inc -AI09663,Head of AI,89233,AUD,120465,MI,FT,Australia,S,Australia,100,"Azure, Statistics, Python, Data Visualization",Bachelor,3,Automotive,2025-01-11,2025-02-05,1410,9.4,Algorithmic Solutions -AI09664,AI Specialist,51178,AUD,69090,EN,FL,Australia,S,Egypt,50,"PyTorch, GCP, TensorFlow",Associate,1,Manufacturing,2024-01-25,2024-02-19,1458,9.7,Advanced Robotics -AI09665,AI Software Engineer,66263,EUR,56324,EN,FL,Germany,M,Argentina,0,"R, Tableau, Java",Associate,0,Transportation,2024-07-23,2024-09-13,558,9.3,Machine Intelligence Group -AI09666,Data Engineer,173476,USD,173476,EX,FL,Finland,S,Finland,100,"Linux, Kubernetes, Deep Learning, SQL, Git",Master,17,Government,2025-04-07,2025-04-30,2135,6.3,Machine Intelligence Group -AI09667,AI Software Engineer,161253,SGD,209629,EX,PT,Singapore,S,Singapore,100,"NLP, SQL, Statistics, Tableau",PhD,15,Real Estate,2024-03-21,2024-05-18,2353,9,AI Innovations -AI09668,AI Consultant,261254,EUR,222066,EX,PT,Germany,L,Germany,100,"Hadoop, Python, Kubernetes, Statistics, TensorFlow",Associate,12,Education,2025-04-26,2025-07-02,739,5.5,Advanced Robotics -AI09669,ML Ops Engineer,199726,USD,199726,EX,FT,Finland,M,Canada,0,"R, GCP, Deep Learning",Master,14,Technology,2024-09-05,2024-11-06,654,6.1,Smart Analytics -AI09670,Computer Vision Engineer,155809,AUD,210342,SE,PT,Australia,L,Australia,50,"PyTorch, Git, GCP",Master,8,Automotive,2024-04-25,2024-06-11,1358,5.6,Future Systems -AI09671,AI Specialist,27270,USD,27270,EN,FT,China,M,Vietnam,100,"Scala, Git, Azure",Associate,1,Transportation,2025-01-07,2025-02-06,2070,9.8,Smart Analytics -AI09672,NLP Engineer,123021,JPY,13532310,SE,CT,Japan,S,Japan,0,"Python, Scala, NLP, Docker, Kubernetes",Master,5,Finance,2024-10-29,2024-11-24,825,7.1,Neural Networks Co -AI09673,Robotics Engineer,218828,USD,218828,EX,FL,Ireland,S,Ireland,100,"PyTorch, TensorFlow, Azure, Kubernetes, Git",PhD,13,Telecommunications,2025-02-27,2025-05-08,1379,9.3,DeepTech Ventures -AI09674,Data Scientist,96009,USD,96009,EN,PT,Denmark,M,Denmark,100,"Spark, Statistics, SQL, Git",PhD,1,Real Estate,2024-04-02,2024-06-01,1154,7.4,Cloud AI Solutions -AI09675,AI Research Scientist,105293,USD,105293,EX,FT,China,L,China,100,"Tableau, Computer Vision, PyTorch, Linux, Mathematics",Associate,11,Automotive,2024-04-09,2024-06-02,1914,8,AI Innovations -AI09676,Machine Learning Researcher,140098,SGD,182127,SE,CT,Singapore,S,Singapore,50,"PyTorch, Java, GCP",Associate,6,Finance,2025-01-29,2025-03-07,951,6.5,Future Systems -AI09677,AI Product Manager,109453,CHF,98508,EN,FL,Switzerland,L,Switzerland,50,"Python, Scala, TensorFlow, Statistics, Computer Vision",Bachelor,1,Real Estate,2024-09-14,2024-10-27,2333,9.4,Cognitive Computing -AI09678,Data Engineer,135675,USD,135675,SE,FT,Ireland,S,Ghana,0,"Scala, GCP, Python",Associate,5,Real Estate,2025-03-27,2025-04-28,513,5.8,Cognitive Computing -AI09679,Data Analyst,55854,USD,55854,EN,FL,South Korea,S,South Korea,50,"Scala, TensorFlow, NLP",Bachelor,1,Government,2025-01-10,2025-03-03,2440,8.4,Quantum Computing Inc -AI09680,Data Analyst,95094,EUR,80830,SE,FT,Austria,S,Brazil,50,"Kubernetes, Python, Azure",Associate,5,Real Estate,2024-06-14,2024-08-02,2045,10,Smart Analytics -AI09681,Autonomous Systems Engineer,218586,USD,218586,EX,CT,Finland,L,Finland,0,"Linux, Hadoop, GCP, Tableau, Computer Vision",Bachelor,12,Media,2024-11-24,2025-01-25,1646,5.6,Quantum Computing Inc -AI09682,AI Specialist,49538,USD,49538,EN,CT,Finland,S,Finland,0,"Linux, Computer Vision, Docker, SQL",Master,1,Finance,2024-08-01,2024-09-10,1675,8.2,Cognitive Computing -AI09683,AI Software Engineer,133909,EUR,113823,EX,FT,France,S,Spain,50,"Data Visualization, GCP, MLOps, NLP",Associate,15,Manufacturing,2024-03-26,2024-04-24,1593,7.6,Cognitive Computing -AI09684,Principal Data Scientist,48444,EUR,41177,EN,CT,France,M,Hungary,100,"Azure, Scala, Python",Bachelor,1,Transportation,2024-02-02,2024-04-02,561,5.1,TechCorp Inc -AI09685,AI Research Scientist,256902,EUR,218367,EX,CT,Netherlands,M,Netherlands,100,"PyTorch, Tableau, Hadoop",Master,17,Gaming,2024-10-12,2024-11-27,1394,8.3,Autonomous Tech -AI09686,AI Architect,57022,USD,57022,SE,CT,China,M,China,0,"MLOps, Python, Docker",Master,9,Education,2024-05-16,2024-06-16,1314,9.5,Cognitive Computing -AI09687,AI Specialist,26272,USD,26272,EN,FL,India,M,Argentina,100,"Kubernetes, Tableau, Scala",Bachelor,1,Energy,2025-03-18,2025-04-08,1146,7.7,Advanced Robotics -AI09688,Deep Learning Engineer,191403,GBP,143552,EX,FL,United Kingdom,S,Philippines,50,"Tableau, Data Visualization, Computer Vision",PhD,13,Technology,2024-02-27,2024-05-05,2261,6.8,Cognitive Computing -AI09689,Machine Learning Researcher,102609,USD,102609,MI,CT,Ireland,M,Ireland,0,"Python, Linux, TensorFlow, Hadoop, Azure",PhD,3,Government,2024-04-25,2024-06-18,1130,9.7,Future Systems -AI09690,Machine Learning Engineer,86953,USD,86953,MI,PT,South Korea,M,Brazil,100,"R, SQL, TensorFlow, GCP, Computer Vision",Master,2,Energy,2024-01-07,2024-01-25,1942,9.5,DeepTech Ventures -AI09691,AI Architect,220260,EUR,187221,EX,FL,France,M,France,0,"Docker, Azure, Computer Vision, AWS, GCP",Bachelor,19,Automotive,2024-10-27,2025-01-01,2461,9.6,Autonomous Tech -AI09692,Robotics Engineer,129728,SGD,168646,SE,PT,Singapore,S,Singapore,100,"SQL, NLP, Hadoop",Bachelor,7,Gaming,2024-12-01,2025-01-12,2243,9.7,Cloud AI Solutions -AI09693,Principal Data Scientist,140854,USD,140854,SE,FL,Ireland,L,Ireland,0,"Python, Spark, Data Visualization",Bachelor,5,Transportation,2024-07-03,2024-09-14,1262,6.5,Cognitive Computing -AI09694,Data Analyst,247679,JPY,27244690,EX,FL,Japan,L,Japan,100,"PyTorch, NLP, Computer Vision, Java",Associate,19,Healthcare,2024-04-26,2024-06-02,1484,5.7,Predictive Systems -AI09695,Machine Learning Researcher,159898,JPY,17588780,SE,FL,Japan,M,Japan,50,"Spark, PyTorch, Tableau",PhD,9,Education,2024-11-30,2025-01-18,1577,7.7,Future Systems -AI09696,Data Engineer,119549,EUR,101617,SE,FT,Austria,M,Austria,0,"GCP, Docker, Tableau, Git",Bachelor,7,Telecommunications,2024-06-11,2024-08-11,1379,7.3,Cognitive Computing -AI09697,Data Scientist,141626,USD,141626,SE,PT,Finland,L,Finland,100,"MLOps, Docker, Kubernetes, R",PhD,9,Retail,2024-08-31,2024-10-31,688,8.3,Advanced Robotics -AI09698,Machine Learning Engineer,83010,EUR,70559,EN,CT,Germany,L,Malaysia,100,"Hadoop, SQL, Java",Bachelor,0,Retail,2024-12-21,2025-02-03,2456,9.9,Smart Analytics -AI09699,Machine Learning Engineer,102708,JPY,11297880,MI,CT,Japan,L,Japan,100,"TensorFlow, Linux, Tableau, SQL",Associate,2,Gaming,2024-03-24,2024-04-11,1512,7.6,Digital Transformation LLC -AI09700,NLP Engineer,108628,JPY,11949080,MI,FT,Japan,L,Japan,0,"NLP, Hadoop, GCP",Bachelor,3,Energy,2024-01-18,2024-02-26,667,9.1,Algorithmic Solutions -AI09701,Data Analyst,74902,JPY,8239220,EN,FL,Japan,M,Japan,0,"Computer Vision, Python, NLP, GCP, Scala",Associate,0,Manufacturing,2024-07-01,2024-09-12,2409,8,Quantum Computing Inc -AI09702,Data Engineer,87428,CHF,78685,EN,FT,Switzerland,S,Switzerland,0,"Python, AWS, Deep Learning",Bachelor,0,Transportation,2024-03-27,2024-05-09,1937,6,Machine Intelligence Group -AI09703,Robotics Engineer,76047,AUD,102663,MI,PT,Australia,M,Australia,0,"R, AWS, MLOps, Scala, Deep Learning",PhD,3,Energy,2024-08-21,2024-09-08,1513,6.2,TechCorp Inc -AI09704,Deep Learning Engineer,260148,USD,260148,EX,FT,United States,S,Turkey,50,"Git, Scala, Data Visualization",Bachelor,18,Telecommunications,2025-01-10,2025-02-12,2240,8,Digital Transformation LLC -AI09705,Robotics Engineer,74496,USD,74496,MI,CT,Sweden,S,Sweden,0,"Java, Spark, TensorFlow",PhD,2,Energy,2025-04-23,2025-06-29,1834,6.9,Predictive Systems -AI09706,NLP Engineer,79118,EUR,67250,MI,PT,Germany,S,United States,0,"Azure, Tableau, Git",PhD,3,Manufacturing,2024-04-06,2024-05-11,1883,8.8,Advanced Robotics -AI09707,ML Ops Engineer,115756,EUR,98393,SE,FL,Germany,S,Germany,50,"Git, SQL, Kubernetes, Deep Learning, Hadoop",Bachelor,5,Transportation,2025-04-19,2025-05-27,1471,7.4,AI Innovations -AI09708,AI Software Engineer,86602,EUR,73612,SE,PT,France,S,Brazil,0,"SQL, Data Visualization, Scala, Azure",Associate,6,Education,2025-02-22,2025-03-18,1378,9.6,Machine Intelligence Group -AI09709,Principal Data Scientist,125719,AUD,169721,SE,CT,Australia,M,Australia,100,"Scala, Kubernetes, Docker",Master,6,Consulting,2024-03-02,2024-04-01,1265,7.2,Cloud AI Solutions -AI09710,NLP Engineer,18481,USD,18481,EN,CT,India,S,India,50,"Python, TensorFlow, Scala, PyTorch",Associate,0,Automotive,2024-05-11,2024-05-31,2012,6.4,Predictive Systems -AI09711,ML Ops Engineer,88351,USD,88351,SE,CT,Finland,S,Ghana,100,"SQL, Statistics, GCP, Hadoop, Deep Learning",Associate,6,Manufacturing,2024-07-10,2024-07-30,2256,5.5,Quantum Computing Inc -AI09712,AI Consultant,40280,USD,40280,MI,PT,India,L,India,50,"Statistics, PyTorch, Hadoop, Scala, AWS",Master,3,Automotive,2024-08-23,2024-09-27,1701,5.9,AI Innovations -AI09713,Deep Learning Engineer,87759,USD,87759,MI,FL,Ireland,L,Russia,100,"Hadoop, R, Tableau, GCP, Kubernetes",Bachelor,3,Finance,2024-05-29,2024-07-25,1034,6.2,Algorithmic Solutions -AI09714,AI Consultant,140279,USD,140279,SE,FT,Israel,L,Israel,100,"Data Visualization, SQL, Docker, TensorFlow",Bachelor,7,Media,2024-03-27,2024-05-16,725,9.6,Cognitive Computing -AI09715,Data Engineer,113020,EUR,96067,SE,CT,Austria,L,Austria,0,"Data Visualization, Kubernetes, Deep Learning",Associate,5,Consulting,2024-12-27,2025-01-23,753,9.3,Machine Intelligence Group -AI09716,Machine Learning Engineer,213625,USD,213625,EX,FT,Norway,M,Norway,100,"AWS, SQL, Git, Kubernetes",Master,15,Finance,2024-01-08,2024-03-09,562,7.3,Machine Intelligence Group -AI09717,Autonomous Systems Engineer,127115,EUR,108048,SE,FT,Austria,L,Brazil,100,"Spark, MLOps, Python, Tableau",PhD,5,Finance,2024-12-02,2025-02-07,1020,9,Advanced Robotics -AI09718,AI Software Engineer,53464,SGD,69503,EN,PT,Singapore,S,Colombia,0,"Hadoop, Statistics, Mathematics, Docker, AWS",Associate,1,Automotive,2025-04-18,2025-05-21,1121,5.5,Machine Intelligence Group -AI09719,Research Scientist,105947,USD,105947,EN,FT,Denmark,L,Denmark,50,"Kubernetes, Scala, Git",Bachelor,1,Consulting,2024-07-06,2024-08-05,1834,7.7,Cloud AI Solutions -AI09720,AI Research Scientist,389066,CHF,350159,EX,FT,Switzerland,L,Switzerland,0,"Hadoop, SQL, Docker",PhD,10,Finance,2024-08-13,2024-10-19,1479,6.6,Autonomous Tech -AI09721,AI Architect,162534,EUR,138154,EX,FT,Netherlands,S,Chile,100,"Scala, Tableau, Data Visualization, Deep Learning",Bachelor,13,Manufacturing,2024-01-07,2024-02-12,2180,6.9,Neural Networks Co -AI09722,Deep Learning Engineer,67954,EUR,57761,EN,CT,Austria,M,Austria,100,"Mathematics, TensorFlow, MLOps, NLP",Master,1,Transportation,2024-02-23,2024-04-27,2132,9.3,Predictive Systems -AI09723,Machine Learning Researcher,236172,AUD,318832,EX,PT,Australia,M,Australia,0,"SQL, Python, Deep Learning, NLP, Spark",Associate,16,Technology,2025-03-10,2025-04-22,1099,6.6,Cloud AI Solutions -AI09724,AI Architect,235127,EUR,199858,EX,CT,France,L,France,100,"Scala, R, Data Visualization, Azure",Associate,11,Finance,2024-02-14,2024-04-16,1353,7.4,Digital Transformation LLC -AI09725,Robotics Engineer,122654,EUR,104256,MI,FT,Netherlands,L,Netherlands,0,"Azure, Git, GCP, TensorFlow",Master,3,Transportation,2024-03-01,2024-04-29,1111,7.1,Advanced Robotics -AI09726,AI Research Scientist,205223,AUD,277051,EX,FT,Australia,S,Egypt,50,"Deep Learning, Kubernetes, Computer Vision, Hadoop, Data Visualization",Master,15,Transportation,2024-08-03,2024-10-12,2209,5.5,Advanced Robotics -AI09727,Robotics Engineer,148358,SGD,192865,SE,PT,Singapore,M,Egypt,100,"Scala, Statistics, AWS, TensorFlow",Bachelor,6,Healthcare,2024-05-10,2024-06-18,1848,6.6,Quantum Computing Inc -AI09728,Data Scientist,220353,USD,220353,EX,FL,Norway,L,Norway,100,"Python, Azure, Docker",Master,10,Finance,2025-02-25,2025-03-20,648,6.8,Algorithmic Solutions -AI09729,Deep Learning Engineer,189506,EUR,161080,EX,CT,Netherlands,L,Netherlands,50,"Python, MLOps, TensorFlow, AWS, Deep Learning",Associate,17,Healthcare,2024-10-04,2024-10-30,1498,7,Smart Analytics -AI09730,AI Software Engineer,69812,JPY,7679320,EN,FT,Japan,M,Brazil,50,"R, Java, Docker",Master,0,Gaming,2024-06-25,2024-09-04,1792,8.4,Machine Intelligence Group -AI09731,Data Scientist,61754,USD,61754,SE,PT,India,L,India,100,"R, PyTorch, Tableau, Computer Vision",Bachelor,5,Energy,2024-10-30,2025-01-09,993,9.9,Digital Transformation LLC -AI09732,Data Engineer,87674,USD,87674,MI,PT,Finland,S,Finland,0,"Tableau, TensorFlow, Linux, AWS, Computer Vision",Bachelor,3,Automotive,2024-01-27,2024-03-08,1229,8.2,Cloud AI Solutions -AI09733,AI Research Scientist,100642,USD,100642,MI,CT,Norway,S,Vietnam,100,"Scala, SQL, MLOps",PhD,4,Media,2024-08-01,2024-09-25,1487,7.8,Smart Analytics -AI09734,ML Ops Engineer,179394,AUD,242182,EX,FT,Australia,S,Australia,50,"Python, TensorFlow, Statistics",Associate,19,Real Estate,2024-03-19,2024-04-21,1973,7.1,Cognitive Computing -AI09735,AI Consultant,177616,USD,177616,SE,FL,United States,L,United States,50,"Scala, R, Data Visualization",Master,6,Transportation,2024-06-14,2024-08-07,1656,7.7,Cognitive Computing -AI09736,Deep Learning Engineer,31495,USD,31495,EN,CT,China,L,China,100,"NLP, Python, Statistics, SQL",PhD,1,Government,2024-06-21,2024-08-15,1654,6,Predictive Systems -AI09737,AI Consultant,44106,USD,44106,SE,PT,China,S,Nigeria,100,"Computer Vision, PyTorch, Git",Bachelor,9,Government,2024-10-06,2024-10-31,2386,7.4,Neural Networks Co -AI09738,Computer Vision Engineer,60523,EUR,51445,EN,CT,Netherlands,S,Netherlands,100,"SQL, PyTorch, Spark, TensorFlow, Tableau",PhD,0,Manufacturing,2025-02-15,2025-03-29,2025,7.3,Neural Networks Co -AI09739,Deep Learning Engineer,149499,SGD,194349,SE,FT,Singapore,M,Estonia,100,"MLOps, NLP, Tableau, TensorFlow, Java",Bachelor,5,Gaming,2024-09-21,2024-11-16,730,9,Machine Intelligence Group -AI09740,AI Architect,99163,USD,99163,SE,CT,South Korea,L,South Korea,50,"TensorFlow, SQL, Statistics",Bachelor,8,Energy,2024-12-22,2025-02-22,1266,9.5,Predictive Systems -AI09741,Computer Vision Engineer,295991,USD,295991,EX,CT,United States,L,Luxembourg,100,"Spark, TensorFlow, R",PhD,19,Education,2024-05-01,2024-07-04,1775,6.2,Cognitive Computing -AI09742,AI Architect,136129,USD,136129,MI,FL,Norway,L,Norway,100,"PyTorch, Hadoop, Statistics, Git, Deep Learning",PhD,2,Finance,2024-11-04,2024-11-19,1746,5.3,Smart Analytics -AI09743,Deep Learning Engineer,113701,EUR,96646,SE,FT,Austria,S,Austria,100,"R, Linux, Java",Master,5,Automotive,2024-04-06,2024-05-14,1949,7.4,Future Systems -AI09744,AI Architect,81106,CHF,72995,EN,PT,Switzerland,S,Switzerland,0,"Python, Spark, Statistics, Linux",PhD,1,Gaming,2025-02-11,2025-02-25,629,5.7,Advanced Robotics -AI09745,Data Analyst,69980,USD,69980,EX,FL,India,M,India,0,"PyTorch, TensorFlow, Docker, SQL, Statistics",Associate,14,Retail,2025-03-18,2025-04-23,1445,7.7,Digital Transformation LLC -AI09746,ML Ops Engineer,326836,USD,326836,EX,FT,Norway,M,Norway,0,"TensorFlow, SQL, Data Visualization",Bachelor,12,Finance,2024-09-14,2024-11-19,840,6.8,Algorithmic Solutions -AI09747,Data Engineer,99357,EUR,84453,SE,FL,Austria,M,Austria,50,"Python, Java, Azure, AWS",Bachelor,7,Automotive,2024-10-08,2024-11-16,560,6.6,DataVision Ltd -AI09748,Machine Learning Researcher,147291,USD,147291,EX,PT,Israel,L,Israel,50,"PyTorch, Spark, R, Git, Tableau",PhD,16,Manufacturing,2024-11-06,2024-11-27,1962,9.5,Digital Transformation LLC -AI09749,AI Research Scientist,241227,USD,241227,EX,FT,Norway,S,Norway,100,"Python, Spark, Tableau, TensorFlow, Deep Learning",Master,12,Media,2025-04-01,2025-05-12,667,7.5,TechCorp Inc -AI09750,Research Scientist,75529,USD,75529,EN,FL,Finland,L,Argentina,50,"Java, PyTorch, NLP, SQL, Scala",Bachelor,0,Manufacturing,2024-07-30,2024-08-24,1470,9.2,Future Systems -AI09751,Machine Learning Engineer,68543,USD,68543,EN,CT,Norway,S,Norway,100,"MLOps, Deep Learning, Data Visualization",Master,1,Telecommunications,2024-03-08,2024-04-16,2407,8.8,Cognitive Computing -AI09752,Principal Data Scientist,69686,USD,69686,EN,CT,United States,S,Czech Republic,100,"PyTorch, SQL, Data Visualization, Deep Learning",Bachelor,0,Telecommunications,2024-03-26,2024-05-18,1978,6.3,Advanced Robotics -AI09753,AI Architect,240290,EUR,204247,EX,CT,Netherlands,M,Netherlands,0,"Scala, Python, Azure",PhD,18,Retail,2024-04-14,2024-06-26,1249,8.2,Neural Networks Co -AI09754,Robotics Engineer,152827,CHF,137544,MI,CT,Switzerland,M,Poland,100,"Kubernetes, Docker, Mathematics",PhD,4,Automotive,2025-04-09,2025-05-17,2154,9.7,DeepTech Ventures -AI09755,AI Software Engineer,124396,EUR,105737,EX,CT,Germany,S,Germany,0,"PyTorch, Deep Learning, Hadoop, Computer Vision, Linux",PhD,15,Retail,2024-08-18,2024-10-09,708,6.3,Smart Analytics -AI09756,Machine Learning Engineer,246978,EUR,209931,EX,FL,Netherlands,M,Netherlands,100,"Azure, Java, PyTorch, Deep Learning, AWS",Bachelor,13,Transportation,2024-04-17,2024-05-26,605,8.1,TechCorp Inc -AI09757,Research Scientist,102797,JPY,11307670,MI,CT,Japan,M,Japan,0,"PyTorch, TensorFlow, Kubernetes",Associate,3,Manufacturing,2024-02-10,2024-04-23,522,7,Machine Intelligence Group -AI09758,Head of AI,67987,SGD,88383,EN,FL,Singapore,S,Singapore,0,"Python, Hadoop, SQL, Git, AWS",Bachelor,1,Consulting,2024-02-27,2024-05-01,761,7.4,Advanced Robotics -AI09759,Data Analyst,283056,USD,283056,EX,FL,Norway,L,Colombia,100,"Hadoop, Tableau, Python, Kubernetes, Mathematics",Master,15,Gaming,2024-10-17,2024-12-10,1021,7.7,Cloud AI Solutions -AI09760,Principal Data Scientist,362848,USD,362848,EX,CT,Norway,L,Norway,100,"GCP, Statistics, MLOps",Associate,13,Media,2025-01-08,2025-02-20,697,5.8,Predictive Systems -AI09761,Data Engineer,63275,SGD,82258,EN,PT,Singapore,M,Singapore,0,"Linux, Kubernetes, Hadoop, Docker, R",Associate,1,Media,2025-01-26,2025-02-13,1719,9.9,Cognitive Computing -AI09762,Data Scientist,61622,GBP,46217,EN,CT,United Kingdom,S,United Kingdom,50,"R, NLP, SQL",PhD,1,Telecommunications,2024-01-28,2024-03-25,1936,9.8,Predictive Systems -AI09763,Principal Data Scientist,82457,CHF,74211,EN,FL,Switzerland,M,Norway,0,"Python, Git, Computer Vision, TensorFlow",PhD,1,Automotive,2024-01-12,2024-02-13,1591,9,Neural Networks Co -AI09764,Head of AI,71625,EUR,60881,MI,FT,Netherlands,S,Netherlands,50,"Python, TensorFlow, PyTorch, Data Visualization, Azure",Associate,4,Gaming,2024-10-08,2024-12-10,1383,8.7,Advanced Robotics -AI09765,NLP Engineer,119422,EUR,101509,MI,FL,Germany,L,Ukraine,50,"PyTorch, TensorFlow, AWS",PhD,3,Media,2024-09-06,2024-10-02,2426,9.7,Quantum Computing Inc -AI09766,Deep Learning Engineer,54944,EUR,46702,EN,CT,Austria,S,Austria,50,"Python, SQL, Mathematics, Java",Associate,1,Finance,2024-10-17,2024-11-24,722,5,Quantum Computing Inc -AI09767,Robotics Engineer,52068,EUR,44258,EN,CT,France,M,France,100,"Python, SQL, Mathematics",Bachelor,1,Technology,2024-11-23,2025-01-20,908,6.3,Neural Networks Co -AI09768,Data Analyst,34503,USD,34503,EN,PT,China,L,Norway,50,"Statistics, Python, TensorFlow, PyTorch",Associate,0,Education,2025-04-01,2025-05-19,2330,7.6,TechCorp Inc -AI09769,Deep Learning Engineer,95396,USD,95396,SE,CT,Sweden,S,Sweden,100,"TensorFlow, SQL, Docker, Statistics",Bachelor,5,Telecommunications,2024-05-06,2024-06-09,1419,5.9,DeepTech Ventures -AI09770,AI Specialist,143291,EUR,121797,EX,CT,France,S,France,50,"PyTorch, R, TensorFlow, Computer Vision, GCP",PhD,14,Education,2025-02-27,2025-04-06,751,9.6,Cognitive Computing -AI09771,NLP Engineer,66180,USD,66180,EN,PT,Sweden,M,South Korea,50,"PyTorch, Git, Tableau",Bachelor,1,Government,2024-03-25,2024-05-15,1216,6.1,Digital Transformation LLC -AI09772,AI Product Manager,142280,USD,142280,SE,CT,Finland,M,Finland,0,"Python, Scala, Computer Vision, Tableau",Bachelor,9,Education,2024-11-23,2024-12-14,947,9.6,Cognitive Computing -AI09773,Principal Data Scientist,72824,USD,72824,MI,FT,South Korea,S,South Korea,50,"Computer Vision, GCP, Linux",Bachelor,3,Automotive,2024-09-14,2024-10-31,1124,6.5,Quantum Computing Inc -AI09774,AI Software Engineer,91337,JPY,10047070,MI,FT,Japan,M,Japan,0,"PyTorch, Docker, SQL, Deep Learning",PhD,3,Government,2024-07-15,2024-09-01,653,6.4,Quantum Computing Inc -AI09775,Machine Learning Researcher,59812,USD,59812,EN,FT,Israel,S,Hungary,0,"Python, Kubernetes, TensorFlow",PhD,1,Transportation,2024-10-02,2024-12-10,2279,9.5,Machine Intelligence Group -AI09776,Machine Learning Engineer,94416,CAD,118020,MI,PT,Canada,M,Canada,100,"Linux, Spark, Scala, Python",Associate,4,Retail,2024-01-31,2024-04-05,1742,5.1,TechCorp Inc -AI09777,Principal Data Scientist,162702,CHF,146432,MI,FL,Switzerland,L,China,100,"Computer Vision, Java, MLOps, Spark",Bachelor,4,Transportation,2024-08-24,2024-09-15,1799,5.4,Future Systems -AI09778,ML Ops Engineer,208539,CAD,260674,EX,FL,Canada,L,Canada,0,"SQL, Python, Git",PhD,16,Consulting,2024-07-13,2024-08-02,1191,5.7,Neural Networks Co -AI09779,Data Engineer,293805,USD,293805,EX,PT,Norway,L,Norway,100,"Java, Linux, Kubernetes, Deep Learning, Git",Master,13,Retail,2025-03-18,2025-05-24,1990,7.4,Digital Transformation LLC -AI09780,Robotics Engineer,109663,USD,109663,MI,FT,Norway,L,Norway,100,"NLP, Hadoop, Spark, PyTorch",Bachelor,4,Consulting,2024-04-05,2024-06-15,1177,6.5,Smart Analytics -AI09781,AI Product Manager,62003,USD,62003,EX,PT,India,M,Belgium,50,"Kubernetes, Data Visualization, Linux, Python, Scala",PhD,10,Government,2025-04-28,2025-07-07,1364,8.1,TechCorp Inc -AI09782,Deep Learning Engineer,110601,USD,110601,MI,PT,Denmark,S,Denmark,100,"MLOps, Docker, Kubernetes, Tableau, PyTorch",Master,4,Transportation,2024-07-21,2024-08-27,1275,6.7,AI Innovations -AI09783,Machine Learning Engineer,97802,USD,97802,SE,FL,Finland,S,Finland,100,"PyTorch, SQL, GCP, Docker",Master,7,Technology,2025-01-05,2025-03-01,1277,8.1,Future Systems -AI09784,AI Research Scientist,31409,USD,31409,EN,FL,China,S,China,100,"Scala, MLOps, SQL, Hadoop",Bachelor,0,Manufacturing,2024-02-28,2024-04-05,987,7,DataVision Ltd -AI09785,Data Analyst,217049,USD,217049,EX,CT,Ireland,S,Ireland,100,"Scala, Spark, Computer Vision, AWS",Bachelor,15,Energy,2025-01-02,2025-02-14,527,5.7,Future Systems -AI09786,AI Consultant,113873,USD,113873,SE,FL,Finland,L,Finland,0,"Statistics, MLOps, Python, Hadoop",Bachelor,5,Gaming,2024-02-15,2024-04-22,929,6.8,AI Innovations -AI09787,Data Scientist,154501,CHF,139051,MI,CT,Switzerland,M,France,50,"Python, TensorFlow, Linux, PyTorch, Scala",Associate,4,Technology,2024-07-05,2024-08-07,2288,8.3,Cloud AI Solutions -AI09788,Data Analyst,65431,CAD,81789,EN,PT,Canada,S,Belgium,100,"AWS, NLP, Git",Bachelor,1,Finance,2024-11-24,2024-12-11,2365,7.8,Cognitive Computing -AI09789,AI Consultant,182995,CAD,228744,EX,FL,Canada,S,Canada,0,"PyTorch, Hadoop, Mathematics, NLP",Bachelor,14,Transportation,2024-07-11,2024-09-11,1806,8.5,DataVision Ltd -AI09790,Data Engineer,69850,JPY,7683500,EN,FL,Japan,S,Japan,100,"SQL, NLP, Docker",PhD,1,Transportation,2025-01-26,2025-03-23,736,6.1,Neural Networks Co -AI09791,Data Engineer,204758,EUR,174044,EX,FL,Germany,S,Romania,100,"Scala, Kubernetes, Deep Learning",Associate,14,Gaming,2024-01-24,2024-02-07,2040,7.5,DataVision Ltd -AI09792,Robotics Engineer,118924,USD,118924,SE,CT,South Korea,M,South Korea,50,"Kubernetes, Git, TensorFlow",Master,9,Manufacturing,2025-02-14,2025-04-06,2190,8,Algorithmic Solutions -AI09793,AI Specialist,140720,GBP,105540,SE,CT,United Kingdom,M,Austria,50,"Spark, Hadoop, Linux, Scala",Bachelor,7,Technology,2024-10-21,2024-11-09,899,8.4,Cognitive Computing -AI09794,AI Consultant,83079,EUR,70617,MI,FT,Germany,S,Germany,100,"R, SQL, Statistics",Associate,4,Manufacturing,2025-04-08,2025-05-28,2250,9.7,DataVision Ltd -AI09795,Head of AI,160182,SGD,208237,SE,CT,Singapore,L,Canada,50,"Git, NLP, AWS",Bachelor,7,Consulting,2024-10-21,2024-11-07,2076,8.2,Predictive Systems -AI09796,AI Consultant,64536,USD,64536,EN,FL,Ireland,M,Ireland,0,"SQL, Hadoop, Mathematics",Bachelor,0,Healthcare,2024-01-22,2024-03-28,2158,9.8,Neural Networks Co -AI09797,Machine Learning Engineer,250363,AUD,337990,EX,FT,Australia,L,Australia,50,"MLOps, SQL, TensorFlow, R",Master,18,Consulting,2024-02-12,2024-04-03,1816,9.1,Quantum Computing Inc -AI09798,Data Engineer,45433,USD,45433,SE,PT,India,L,India,100,"Computer Vision, Spark, Statistics",Bachelor,7,Education,2024-08-28,2024-10-05,1982,7.3,Advanced Robotics -AI09799,Data Analyst,63135,CAD,78919,EN,FT,Canada,L,Sweden,0,"SQL, MLOps, Scala, TensorFlow",Associate,1,Manufacturing,2025-04-28,2025-07-10,2401,5.4,Neural Networks Co -AI09800,Data Scientist,72576,USD,72576,EX,FL,China,S,Italy,50,"Git, AWS, Scala, Data Visualization",Associate,10,Real Estate,2024-03-25,2024-05-12,678,8.2,DeepTech Ventures -AI09801,Research Scientist,137937,USD,137937,EX,CT,South Korea,M,South Korea,100,"Python, Statistics, Spark",Master,18,Energy,2024-07-11,2024-08-15,1878,8.4,Algorithmic Solutions -AI09802,Autonomous Systems Engineer,137663,EUR,117014,SE,CT,France,L,France,50,"Java, Spark, Mathematics, PyTorch",Bachelor,6,Consulting,2025-02-11,2025-03-12,1432,7,Machine Intelligence Group -AI09803,AI Consultant,201971,USD,201971,EX,FL,Sweden,L,Sweden,50,"Python, Data Visualization, Linux, GCP",Associate,19,Energy,2024-03-02,2024-04-18,1265,7.5,Digital Transformation LLC -AI09804,Data Scientist,49095,USD,49095,MI,CT,China,M,Egypt,0,"Tableau, Java, Azure, NLP, Python",PhD,4,Media,2024-10-20,2024-11-24,1490,6.8,Cognitive Computing -AI09805,Research Scientist,210286,USD,210286,EX,FT,United States,L,Czech Republic,0,"Spark, Linux, Scala",PhD,17,Transportation,2024-11-16,2024-12-02,2014,8.8,TechCorp Inc -AI09806,AI Specialist,196218,USD,196218,SE,PT,Denmark,M,Ghana,50,"Hadoop, Docker, Deep Learning, GCP, SQL",Associate,8,Energy,2024-08-22,2024-10-07,2279,8.6,Future Systems -AI09807,Machine Learning Engineer,18616,USD,18616,EN,FT,India,S,India,50,"Git, Tableau, Kubernetes, Data Visualization",Associate,0,Media,2024-07-20,2024-09-07,894,5.4,Machine Intelligence Group -AI09808,Autonomous Systems Engineer,118826,USD,118826,MI,FT,Finland,L,Finland,0,"Kubernetes, Docker, R",Associate,4,Education,2024-05-17,2024-06-12,1146,8.2,DataVision Ltd -AI09809,Computer Vision Engineer,277649,USD,277649,EX,FT,United States,L,Japan,100,"Statistics, SQL, Deep Learning",Associate,15,Media,2024-10-15,2024-12-11,2120,9.6,Advanced Robotics -AI09810,AI Research Scientist,67075,EUR,57014,MI,PT,France,S,France,50,"Linux, Scala, Computer Vision, PyTorch",Associate,2,Manufacturing,2024-08-24,2024-09-26,669,6.5,Autonomous Tech -AI09811,Machine Learning Engineer,62913,JPY,6920430,EN,FT,Japan,L,Japan,100,"SQL, Java, Mathematics",Bachelor,0,Media,2025-03-09,2025-03-25,1843,5.3,TechCorp Inc -AI09812,AI Software Engineer,95618,CHF,86056,MI,CT,Switzerland,S,India,50,"Computer Vision, Statistics, Kubernetes, Java",PhD,4,Education,2024-03-27,2024-06-01,1596,5.5,Future Systems -AI09813,Head of AI,219644,USD,219644,SE,PT,Norway,L,United States,100,"Git, Deep Learning, Python, Computer Vision",Bachelor,9,Education,2025-02-01,2025-03-18,1841,8.8,Quantum Computing Inc -AI09814,AI Research Scientist,183702,CHF,165332,SE,FT,Switzerland,L,Switzerland,50,"Computer Vision, Tableau, Git, MLOps, NLP",PhD,8,Telecommunications,2024-08-06,2024-08-28,1473,9.6,DeepTech Ventures -AI09815,Computer Vision Engineer,68877,AUD,92984,EN,PT,Australia,S,Australia,100,"SQL, PyTorch, Git, AWS, TensorFlow",Bachelor,1,Telecommunications,2025-03-03,2025-04-29,2430,5.8,Machine Intelligence Group -AI09816,AI Specialist,130605,EUR,111014,EX,CT,Austria,M,Austria,100,"Spark, R, Kubernetes",PhD,13,Consulting,2024-04-21,2024-05-18,1198,5.8,Advanced Robotics -AI09817,Machine Learning Researcher,204630,AUD,276251,EX,FT,Australia,S,Australia,50,"Azure, PyTorch, Linux",Associate,17,Consulting,2024-03-23,2024-05-13,1441,6.7,TechCorp Inc -AI09818,Machine Learning Researcher,52908,USD,52908,SE,PT,China,S,Ghana,0,"Python, Azure, Deep Learning, NLP",PhD,9,Manufacturing,2024-11-07,2024-12-03,1769,5.9,Predictive Systems -AI09819,AI Consultant,94508,CHF,85057,EN,FT,Switzerland,L,Russia,50,"Computer Vision, MLOps, Tableau",PhD,0,Retail,2024-04-23,2024-06-11,970,8.7,Machine Intelligence Group -AI09820,AI Consultant,129697,GBP,97273,SE,PT,United Kingdom,L,Denmark,50,"Hadoop, PyTorch, AWS, Linux, NLP",Associate,6,Consulting,2025-03-07,2025-03-30,895,8.6,Future Systems -AI09821,Computer Vision Engineer,114261,EUR,97122,SE,FT,France,S,France,0,"Computer Vision, Python, Mathematics",Bachelor,8,Retail,2024-10-15,2024-12-24,1576,7.1,Cloud AI Solutions -AI09822,Principal Data Scientist,66838,AUD,90231,EN,CT,Australia,L,Ukraine,50,"Azure, Linux, MLOps, Scala",Master,1,Transportation,2024-04-06,2024-06-15,2404,8,DeepTech Ventures -AI09823,Data Engineer,74558,CHF,67102,EN,CT,Switzerland,S,Switzerland,0,"Mathematics, GCP, Docker, AWS",Bachelor,0,Healthcare,2024-06-05,2024-08-15,1416,8.9,Autonomous Tech -AI09824,Autonomous Systems Engineer,77135,JPY,8484850,EN,FT,Japan,L,Japan,100,"Kubernetes, Statistics, PyTorch",Associate,1,Healthcare,2024-11-19,2025-01-27,805,6.4,Cognitive Computing -AI09825,AI Architect,186851,USD,186851,EX,FL,Norway,M,Norway,50,"Mathematics, R, Spark, Computer Vision",Bachelor,12,Media,2025-03-31,2025-05-03,804,9.9,Machine Intelligence Group -AI09826,AI Product Manager,77859,USD,77859,EN,FT,Sweden,M,Sweden,100,"Spark, Java, Statistics, Mathematics",Master,1,Government,2024-02-14,2024-03-12,1780,9.3,Cognitive Computing -AI09827,Deep Learning Engineer,90139,USD,90139,EN,FT,Denmark,M,Turkey,0,"TensorFlow, SQL, Python, NLP, AWS",Associate,0,Healthcare,2024-09-11,2024-10-03,852,8.2,Cognitive Computing -AI09828,AI Specialist,149714,USD,149714,MI,CT,Denmark,L,Denmark,0,"Python, SQL, NLP, Hadoop",Bachelor,2,Government,2025-04-05,2025-06-09,1519,8.6,Cloud AI Solutions -AI09829,Autonomous Systems Engineer,176198,EUR,149768,EX,CT,Austria,M,Latvia,50,"Deep Learning, Spark, Java, Computer Vision",Master,19,Government,2024-03-12,2024-05-07,1526,8.8,DeepTech Ventures -AI09830,AI Consultant,228336,CHF,205502,EX,FT,Switzerland,M,South Africa,0,"Java, Spark, Azure, Linux",Bachelor,19,Real Estate,2024-08-31,2024-09-16,805,5.5,Digital Transformation LLC -AI09831,Computer Vision Engineer,17942,USD,17942,EN,FL,India,S,South Korea,50,"Data Visualization, PyTorch, TensorFlow, SQL",PhD,1,Technology,2024-08-22,2024-10-28,1023,8.8,DataVision Ltd -AI09832,Autonomous Systems Engineer,140214,USD,140214,SE,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch, Azure",Bachelor,5,Real Estate,2024-09-22,2024-11-15,609,9.5,DeepTech Ventures -AI09833,AI Specialist,234802,USD,234802,EX,CT,Ireland,M,Ireland,0,"Spark, Kubernetes, Tableau, R, Linux",Master,12,Healthcare,2024-05-15,2024-07-25,906,8.3,Cognitive Computing -AI09834,AI Architect,54715,SGD,71130,EN,FL,Singapore,M,Singapore,50,"Data Visualization, Scala, NLP, Python, Mathematics",Master,1,Government,2025-01-29,2025-04-03,2046,6,Algorithmic Solutions -AI09835,AI Architect,288436,USD,288436,EX,FL,Norway,L,Singapore,100,"Java, Computer Vision, PyTorch, TensorFlow",Master,17,Healthcare,2025-01-21,2025-04-01,1751,8.3,Future Systems -AI09836,Robotics Engineer,77512,EUR,65885,MI,PT,Germany,S,Brazil,0,"Scala, R, Kubernetes",Master,3,Finance,2024-01-25,2024-02-29,704,5.5,DataVision Ltd -AI09837,Research Scientist,230817,GBP,173113,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, Hadoop, Spark",Bachelor,16,Healthcare,2025-01-14,2025-03-08,1547,8.9,Smart Analytics -AI09838,Data Analyst,126549,EUR,107567,SE,PT,Netherlands,S,Netherlands,0,"Linux, Kubernetes, MLOps, AWS, Azure",Associate,7,Media,2025-03-07,2025-05-03,634,6.9,Digital Transformation LLC -AI09839,AI Specialist,55058,JPY,6056380,EN,CT,Japan,S,Japan,100,"Python, Mathematics, TensorFlow",Bachelor,0,Consulting,2024-06-15,2024-08-19,1925,6.1,Future Systems -AI09840,Data Engineer,123391,USD,123391,EX,PT,Israel,S,Mexico,50,"Java, Kubernetes, Tableau",Associate,11,Healthcare,2024-06-07,2024-06-23,2028,8.8,Autonomous Tech -AI09841,NLP Engineer,322051,USD,322051,EX,PT,Norway,L,Norway,100,"Git, R, Python, Computer Vision",Associate,11,Healthcare,2024-12-14,2025-01-08,2432,9.6,Quantum Computing Inc -AI09842,Research Scientist,37366,USD,37366,EN,FL,China,L,United Kingdom,0,"Git, SQL, NLP, PyTorch, Computer Vision",Master,0,Consulting,2024-01-24,2024-03-07,979,7.4,Autonomous Tech -AI09843,NLP Engineer,243682,EUR,207130,EX,FT,Netherlands,M,Netherlands,0,"Git, Python, TensorFlow",PhD,11,Manufacturing,2024-05-07,2024-06-26,1216,7.7,Predictive Systems -AI09844,Robotics Engineer,159124,CHF,143212,MI,FT,Switzerland,L,Switzerland,50,"Linux, GCP, Data Visualization",PhD,3,Media,2024-06-20,2024-07-07,2172,8,Algorithmic Solutions -AI09845,Computer Vision Engineer,49586,SGD,64462,EN,FT,Singapore,S,South Africa,0,"AWS, Git, PyTorch, Deep Learning",Associate,1,Finance,2024-02-20,2024-04-16,2441,9.9,Advanced Robotics -AI09846,Research Scientist,307401,USD,307401,EX,FL,United States,L,United States,50,"AWS, MLOps, Azure",PhD,10,Energy,2024-06-07,2024-07-08,1586,7.7,Neural Networks Co -AI09847,Robotics Engineer,173982,USD,173982,EX,CT,South Korea,S,South Korea,100,"Scala, Computer Vision, Python, Git, NLP",Associate,13,Manufacturing,2025-02-12,2025-03-20,725,7.4,Smart Analytics -AI09848,AI Product Manager,143207,USD,143207,SE,CT,Israel,M,Germany,0,"Python, NLP, TensorFlow",PhD,7,Telecommunications,2024-11-05,2024-11-25,1967,8.9,Algorithmic Solutions -AI09849,AI Research Scientist,144621,SGD,188007,EX,CT,Singapore,S,Singapore,0,"Linux, GCP, Scala",Associate,12,Healthcare,2024-05-31,2024-07-01,1397,6.9,Autonomous Tech -AI09850,AI Consultant,80428,EUR,68364,EN,FT,Germany,M,India,0,"SQL, Tableau, Scala, Git",PhD,0,Manufacturing,2024-11-19,2025-01-19,1987,8.8,Autonomous Tech -AI09851,ML Ops Engineer,306456,SGD,398393,EX,FL,Singapore,L,France,0,"Tableau, AWS, TensorFlow, Python, SQL",PhD,17,Manufacturing,2024-02-27,2024-03-27,2234,9.5,TechCorp Inc -AI09852,Data Scientist,123489,USD,123489,MI,PT,Denmark,M,Sweden,0,"Hadoop, Python, Data Visualization, Kubernetes",Associate,3,Gaming,2025-03-05,2025-04-21,761,8.1,Predictive Systems -AI09853,Machine Learning Researcher,131962,USD,131962,EX,CT,China,L,China,100,"Hadoop, SQL, Data Visualization",Bachelor,18,Retail,2024-01-03,2024-03-12,1973,8.6,Predictive Systems -AI09854,Principal Data Scientist,115511,CAD,144389,SE,FT,Canada,L,Canada,0,"Linux, Kubernetes, GCP, NLP",PhD,6,Technology,2024-06-30,2024-08-27,2363,6.6,Cloud AI Solutions -AI09855,Data Analyst,144101,EUR,122486,SE,PT,Netherlands,M,Netherlands,100,"R, Git, SQL, Java, Data Visualization",Master,9,Healthcare,2024-09-29,2024-10-14,961,5.2,Future Systems -AI09856,Data Engineer,187329,GBP,140497,EX,FT,United Kingdom,L,Russia,0,"Python, Java, Tableau, TensorFlow",Master,10,Energy,2024-12-03,2025-02-09,2026,9.2,Algorithmic Solutions -AI09857,Autonomous Systems Engineer,113840,CAD,142300,SE,CT,Canada,S,Canada,50,"Linux, Python, Tableau, Data Visualization",PhD,7,Technology,2024-11-20,2025-01-01,926,9.2,Digital Transformation LLC -AI09858,Principal Data Scientist,246771,USD,246771,EX,CT,Norway,M,Ghana,100,"R, Deep Learning, Azure, Linux, Kubernetes",Bachelor,19,Government,2024-04-29,2024-07-07,1293,7.2,Advanced Robotics -AI09859,AI Software Engineer,126469,SGD,164410,MI,PT,Singapore,L,Singapore,0,"Azure, R, Java, Python, SQL",Associate,4,Education,2024-01-22,2024-04-04,1395,8.6,Machine Intelligence Group -AI09860,Data Scientist,23821,USD,23821,MI,FL,India,S,India,100,"Git, Java, R",Bachelor,4,Gaming,2024-04-07,2024-06-03,1821,9.8,Cloud AI Solutions -AI09861,Research Scientist,165461,EUR,140642,SE,FT,Netherlands,L,Netherlands,100,"Mathematics, Data Visualization, Linux",Associate,8,Media,2024-11-25,2024-12-14,2016,9.1,Machine Intelligence Group -AI09862,AI Consultant,24465,USD,24465,EN,CT,India,L,India,50,"SQL, Scala, Deep Learning",Bachelor,1,Media,2024-12-15,2025-01-16,1653,7,DeepTech Ventures -AI09863,Machine Learning Researcher,83518,EUR,70990,MI,FT,Germany,M,Germany,100,"Python, NLP, Git, Kubernetes",Associate,4,Healthcare,2024-06-10,2024-07-29,1380,5.1,Neural Networks Co -AI09864,AI Software Engineer,172981,USD,172981,EX,PT,Sweden,S,Luxembourg,50,"Git, Linux, Computer Vision",Associate,16,Retail,2024-02-11,2024-04-13,673,7,Smart Analytics -AI09865,AI Specialist,68862,EUR,58533,MI,CT,Austria,M,Austria,0,"Linux, SQL, Tableau",Master,4,Technology,2024-09-03,2024-11-08,1318,6,Cognitive Computing -AI09866,Computer Vision Engineer,126859,USD,126859,SE,PT,Israel,S,Israel,50,"AWS, Git, Java",Master,7,Consulting,2024-09-13,2024-10-13,626,8.2,Smart Analytics -AI09867,Robotics Engineer,71219,CHF,64097,EN,FT,Switzerland,S,Switzerland,100,"SQL, Scala, Data Visualization, Linux, TensorFlow",PhD,0,Transportation,2024-09-07,2024-10-11,1446,7.2,Quantum Computing Inc -AI09868,AI Consultant,125998,EUR,107098,SE,CT,Austria,L,Austria,50,"SQL, Git, R, PyTorch, Computer Vision",Master,6,Media,2024-10-09,2024-11-27,2170,9.9,Cognitive Computing -AI09869,Head of AI,178944,USD,178944,SE,CT,Denmark,M,Denmark,50,"Kubernetes, Hadoop, MLOps",Bachelor,7,Real Estate,2024-02-29,2024-04-12,1915,7.6,Algorithmic Solutions -AI09870,Deep Learning Engineer,147376,USD,147376,EX,PT,Ireland,M,Ireland,0,"Java, Computer Vision, NLP, PyTorch, Statistics",Bachelor,17,Manufacturing,2024-05-03,2024-06-08,947,9,Predictive Systems -AI09871,Data Analyst,76399,USD,76399,MI,FL,Israel,S,Ukraine,50,"R, Azure, SQL, Computer Vision",Master,2,Manufacturing,2024-04-20,2024-05-31,1191,9.2,Machine Intelligence Group -AI09872,AI Research Scientist,136519,EUR,116041,EX,PT,Germany,M,Austria,100,"Scala, Java, Python, Mathematics, AWS",PhD,19,Manufacturing,2024-08-11,2024-10-16,1833,5.1,DataVision Ltd -AI09873,Deep Learning Engineer,116176,EUR,98750,MI,FL,Austria,L,Austria,50,"Spark, Azure, R, AWS",Master,4,Media,2025-04-06,2025-05-30,2202,5.3,Neural Networks Co -AI09874,AI Research Scientist,114218,AUD,154194,MI,CT,Australia,L,Australia,50,"Hadoop, Kubernetes, SQL",Bachelor,4,Gaming,2025-04-27,2025-05-22,1916,7.5,Digital Transformation LLC -AI09875,Data Analyst,79786,USD,79786,EN,PT,Israel,L,Israel,50,"Spark, Data Visualization, MLOps, Kubernetes, Scala",Bachelor,1,Transportation,2024-03-04,2024-04-12,1711,8.5,TechCorp Inc -AI09876,NLP Engineer,102654,USD,102654,MI,FL,United States,S,United States,50,"PyTorch, MLOps, Deep Learning",Bachelor,3,Telecommunications,2024-10-29,2024-12-28,1731,6.8,Cloud AI Solutions -AI09877,AI Consultant,110047,JPY,12105170,MI,FT,Japan,L,Japan,0,"Scala, Azure, Deep Learning, Linux",PhD,3,Education,2024-08-23,2024-10-11,2493,7.8,TechCorp Inc -AI09878,Robotics Engineer,43437,USD,43437,SE,FT,China,S,China,50,"Java, R, Azure, Data Visualization",PhD,9,Consulting,2024-01-24,2024-02-23,1497,8.3,Digital Transformation LLC -AI09879,AI Architect,197171,CHF,177454,SE,FT,Switzerland,M,Switzerland,100,"AWS, R, Tableau, Mathematics",Bachelor,6,Media,2024-02-18,2024-03-16,1025,5.1,DeepTech Ventures -AI09880,AI Software Engineer,174106,USD,174106,EX,FT,Ireland,L,Ireland,100,"Kubernetes, NLP, TensorFlow, GCP, AWS",PhD,12,Technology,2024-07-15,2024-08-17,1972,9.7,Smart Analytics -AI09881,NLP Engineer,88358,USD,88358,MI,CT,Finland,M,Finland,50,"Docker, MLOps, Python, Mathematics, R",PhD,4,Healthcare,2024-09-27,2024-10-14,2123,7.1,Algorithmic Solutions -AI09882,Head of AI,93787,USD,93787,SE,PT,South Korea,M,India,50,"Computer Vision, PyTorch, Data Visualization",Master,5,Manufacturing,2025-03-02,2025-04-09,1784,6.5,DataVision Ltd -AI09883,Research Scientist,116502,USD,116502,MI,FT,United States,L,United States,100,"NLP, Azure, Data Visualization",PhD,3,Education,2024-02-09,2024-03-30,2387,9.2,Algorithmic Solutions -AI09884,AI Consultant,35301,USD,35301,MI,FT,China,S,Italy,0,"GCP, Deep Learning, Tableau, AWS",PhD,2,Finance,2024-10-18,2024-11-18,820,6.5,DeepTech Ventures -AI09885,Computer Vision Engineer,130851,USD,130851,SE,PT,Denmark,S,Ukraine,0,"TensorFlow, Hadoop, Linux, Kubernetes",Bachelor,5,Retail,2025-03-18,2025-04-05,649,8.2,Digital Transformation LLC -AI09886,AI Research Scientist,122176,USD,122176,SE,FL,Sweden,M,Sweden,100,"Python, Git, Scala, TensorFlow",PhD,9,Government,2024-09-15,2024-10-31,2241,9.2,Future Systems -AI09887,AI Specialist,175333,SGD,227933,SE,FL,Singapore,L,Singapore,50,"Spark, Python, TensorFlow, Tableau",Associate,6,Education,2024-11-19,2025-01-16,826,9,TechCorp Inc -AI09888,Data Scientist,113930,USD,113930,SE,CT,Israel,M,Israel,0,"MLOps, Linux, AWS, Deep Learning, PyTorch",PhD,9,Transportation,2024-03-02,2024-04-27,1764,8.6,Autonomous Tech -AI09889,Data Engineer,122929,USD,122929,MI,FL,Ireland,L,Ireland,100,"PyTorch, R, Java, Python, Spark",Bachelor,2,Automotive,2024-07-09,2024-09-15,1307,8.3,Algorithmic Solutions -AI09890,Research Scientist,188908,EUR,160572,EX,FL,Netherlands,M,Netherlands,100,"Docker, Tableau, Python",PhD,16,Retail,2024-01-20,2024-02-11,1747,7.4,TechCorp Inc -AI09891,AI Architect,66033,USD,66033,EN,PT,South Korea,L,South Korea,50,"Deep Learning, SQL, Mathematics, AWS",PhD,1,Media,2024-06-27,2024-07-20,1478,9.1,Machine Intelligence Group -AI09892,Deep Learning Engineer,148648,AUD,200675,SE,PT,Australia,M,Australia,0,"R, SQL, TensorFlow, Azure, Tableau",Associate,6,Government,2024-08-31,2024-09-28,754,8.7,Smart Analytics -AI09893,Research Scientist,142225,EUR,120891,SE,PT,Germany,M,Germany,50,"Kubernetes, Git, NLP, Mathematics, GCP",Bachelor,9,Transportation,2025-03-03,2025-04-09,1697,9.9,Smart Analytics -AI09894,AI Product Manager,163931,USD,163931,EX,FL,Finland,M,Finland,50,"SQL, Kubernetes, Python, Spark, R",Master,13,Real Estate,2024-11-08,2025-01-08,1318,8.9,DataVision Ltd -AI09895,Autonomous Systems Engineer,71392,EUR,60683,EN,FT,Austria,M,Austria,50,"GCP, Java, Kubernetes, Spark",PhD,1,Finance,2024-02-23,2024-04-28,1661,5.7,Neural Networks Co -AI09896,Machine Learning Researcher,111415,JPY,12255650,SE,FL,Japan,S,Sweden,100,"Deep Learning, Kubernetes, R, TensorFlow, Java",Bachelor,6,Retail,2024-04-04,2024-05-16,742,8,Algorithmic Solutions -AI09897,NLP Engineer,67040,CAD,83800,EN,FL,Canada,M,Canada,0,"MLOps, Linux, Docker, Kubernetes",Master,1,Media,2024-10-25,2025-01-05,1056,8.1,Smart Analytics -AI09898,Research Scientist,336020,USD,336020,EX,CT,Denmark,L,Denmark,0,"Java, Git, PyTorch, AWS, Kubernetes",Master,16,Media,2024-01-25,2024-03-09,1964,6.8,DataVision Ltd -AI09899,AI Consultant,194195,USD,194195,SE,FL,Norway,L,Israel,50,"Scala, Python, NLP",Master,6,Retail,2025-02-12,2025-03-31,2305,7.2,DataVision Ltd -AI09900,AI Software Engineer,110004,EUR,93503,MI,FT,Germany,L,Germany,0,"AWS, Computer Vision, Kubernetes, Java, Spark",Bachelor,2,Consulting,2024-08-08,2024-09-03,1401,5.7,Cognitive Computing -AI09901,NLP Engineer,65717,USD,65717,EN,PT,Finland,S,Finland,0,"Data Visualization, Deep Learning, Spark, AWS",Master,1,Telecommunications,2024-10-08,2024-11-06,2155,8.5,Predictive Systems -AI09902,Data Engineer,80715,GBP,60536,EN,CT,United Kingdom,L,United Kingdom,100,"Azure, NLP, SQL, GCP, Docker",Bachelor,1,Healthcare,2025-01-04,2025-02-25,806,7.6,DataVision Ltd -AI09903,Data Scientist,225112,USD,225112,EX,PT,Ireland,M,Canada,100,"Git, Python, AWS, GCP",Master,19,Retail,2025-03-19,2025-05-21,2392,6,Neural Networks Co -AI09904,Data Engineer,206433,EUR,175468,EX,FL,France,L,Nigeria,50,"Mathematics, Linux, Tableau, Azure",Bachelor,16,Transportation,2025-02-13,2025-02-28,2389,8.6,Algorithmic Solutions -AI09905,Research Scientist,163201,USD,163201,SE,CT,Denmark,S,Denmark,0,"Statistics, NLP, SQL, PyTorch",PhD,8,Automotive,2025-03-20,2025-05-25,1445,9.2,Future Systems -AI09906,Robotics Engineer,210688,EUR,179085,EX,CT,Austria,S,Austria,50,"Java, SQL, Linux, AWS",Bachelor,17,Healthcare,2024-11-03,2024-12-21,1482,6,Algorithmic Solutions -AI09907,AI Specialist,135482,USD,135482,SE,CT,Denmark,S,Denmark,0,"Java, Kubernetes, Hadoop",Master,5,Healthcare,2024-09-03,2024-09-17,1042,5.9,Cloud AI Solutions -AI09908,ML Ops Engineer,80264,SGD,104343,EN,FT,Singapore,M,Netherlands,0,"Azure, GCP, SQL, TensorFlow, Data Visualization",PhD,0,Transportation,2025-01-23,2025-04-03,690,9.9,Smart Analytics -AI09909,AI Consultant,121140,USD,121140,SE,PT,Finland,M,Finland,50,"Mathematics, MLOps, Azure, Linux, SQL",Master,8,Technology,2024-06-30,2024-07-16,689,5.9,Machine Intelligence Group -AI09910,Data Scientist,210071,EUR,178560,EX,PT,Germany,M,Germany,0,"Spark, Statistics, PyTorch, Azure, Mathematics",Bachelor,13,Healthcare,2024-06-21,2024-08-24,1513,5.3,Future Systems -AI09911,Autonomous Systems Engineer,252427,EUR,214563,EX,CT,France,L,Thailand,50,"Python, Linux, TensorFlow",Bachelor,10,Manufacturing,2024-09-26,2024-11-01,2275,7.6,Neural Networks Co -AI09912,AI Architect,211690,USD,211690,EX,PT,Israel,M,Israel,100,"Tableau, Computer Vision, Python, AWS",Associate,11,Real Estate,2024-11-26,2025-01-19,1954,9.6,Advanced Robotics -AI09913,Principal Data Scientist,89052,USD,89052,MI,PT,Ireland,M,Japan,50,"NLP, PyTorch, TensorFlow",Master,2,Media,2025-02-10,2025-04-23,1301,6.4,Machine Intelligence Group -AI09914,Autonomous Systems Engineer,105815,USD,105815,MI,FT,Norway,M,Indonesia,50,"Linux, PyTorch, Kubernetes",Associate,2,Government,2025-02-17,2025-04-07,1594,6.6,DeepTech Ventures -AI09915,AI Research Scientist,107540,USD,107540,SE,FT,Israel,S,Israel,50,"NLP, Hadoop, Kubernetes",Bachelor,7,Manufacturing,2025-02-23,2025-04-09,2336,9.3,DeepTech Ventures -AI09916,ML Ops Engineer,95240,USD,95240,EN,FL,Denmark,M,Denmark,0,"SQL, Data Visualization, PyTorch, Linux",PhD,0,Gaming,2024-06-09,2024-07-06,2323,7.3,DeepTech Ventures -AI09917,Research Scientist,191684,USD,191684,EX,FL,Sweden,S,Sweden,100,"Java, Computer Vision, Git",Master,11,Transportation,2024-02-06,2024-03-04,1230,8.8,Advanced Robotics -AI09918,Principal Data Scientist,59242,USD,59242,EN,FT,South Korea,M,South Korea,50,"Spark, Hadoop, Mathematics, TensorFlow",Associate,1,Consulting,2024-04-08,2024-06-12,1353,6.7,Predictive Systems -AI09919,Machine Learning Researcher,83529,USD,83529,MI,FT,Finland,S,Finland,0,"TensorFlow, Docker, MLOps, Git, GCP",PhD,2,Government,2025-01-20,2025-03-02,1757,6.5,Advanced Robotics -AI09920,Machine Learning Engineer,139067,USD,139067,SE,FT,Finland,M,Finland,50,"Hadoop, Git, Kubernetes, AWS, Python",PhD,9,Technology,2024-03-08,2024-04-13,1871,8.2,Cloud AI Solutions -AI09921,AI Architect,49440,SGD,64272,EN,FT,Singapore,S,Turkey,50,"Data Visualization, NLP, Java, SQL, TensorFlow",Associate,0,Media,2025-04-10,2025-04-26,2447,7.1,Future Systems -AI09922,AI Software Engineer,18220,USD,18220,EN,FT,India,M,India,50,"SQL, TensorFlow, Python, R, Data Visualization",Master,0,Education,2024-04-06,2024-06-15,1271,5.5,Algorithmic Solutions -AI09923,NLP Engineer,65418,USD,65418,EN,FT,Israel,M,Israel,50,"Git, Mathematics, Linux",Bachelor,0,Finance,2024-11-02,2025-01-04,1374,5.7,Cloud AI Solutions -AI09924,Data Analyst,157206,USD,157206,EX,FT,Sweden,M,Sweden,0,"Python, NLP, Mathematics, Spark",Master,14,Automotive,2024-07-16,2024-07-31,2023,9.7,DeepTech Ventures -AI09925,AI Consultant,125227,CHF,112704,EN,PT,Switzerland,L,Switzerland,0,"Docker, Python, Computer Vision, SQL, Linux",Master,1,Manufacturing,2024-02-27,2024-04-03,536,8.5,AI Innovations -AI09926,Data Scientist,99081,USD,99081,SE,FT,Israel,M,Israel,100,"Java, Computer Vision, Kubernetes, Spark",PhD,8,Retail,2024-03-02,2024-04-20,1832,8.1,Neural Networks Co -AI09927,AI Architect,137965,USD,137965,SE,CT,Sweden,L,Sweden,50,"TensorFlow, PyTorch, SQL, Docker, Linux",PhD,7,Retail,2024-09-26,2024-10-26,938,6.3,Cloud AI Solutions -AI09928,AI Product Manager,79335,USD,79335,EN,FT,Sweden,L,Indonesia,100,"MLOps, SQL, Azure, PyTorch",Bachelor,0,Energy,2024-03-04,2024-05-13,2184,7.5,Neural Networks Co -AI09929,Computer Vision Engineer,88458,USD,88458,EX,PT,China,S,China,50,"AWS, R, Tableau, Hadoop",Bachelor,16,Real Estate,2024-12-17,2025-02-24,1991,6.2,Neural Networks Co -AI09930,NLP Engineer,122917,USD,122917,SE,PT,Sweden,S,Sweden,100,"Python, R, GCP, MLOps, Deep Learning",Master,6,Manufacturing,2025-01-18,2025-03-15,763,8.6,Advanced Robotics -AI09931,Autonomous Systems Engineer,51646,JPY,5681060,EN,FT,Japan,S,Poland,0,"Spark, GCP, Docker, R, Kubernetes",Master,1,Transportation,2024-08-09,2024-09-20,1648,6.9,Smart Analytics -AI09932,AI Product Manager,105874,USD,105874,SE,FT,South Korea,S,South Korea,50,"Tableau, Linux, GCP, TensorFlow, Spark",Master,7,Transportation,2024-08-16,2024-09-28,1716,5.8,Machine Intelligence Group -AI09933,AI Specialist,52597,USD,52597,SE,PT,China,S,China,100,"AWS, R, Deep Learning, Computer Vision",Master,8,Telecommunications,2024-12-18,2025-02-25,1975,7.7,Algorithmic Solutions -AI09934,Data Scientist,90978,GBP,68234,MI,PT,United Kingdom,S,United Kingdom,100,"Scala, MLOps, TensorFlow",PhD,4,Healthcare,2024-01-09,2024-01-25,1444,6.4,Algorithmic Solutions -AI09935,Data Analyst,170390,USD,170390,EX,CT,Finland,M,Singapore,0,"Tableau, Azure, SQL, Statistics, AWS",Bachelor,18,Technology,2024-07-20,2024-08-26,650,6.9,Cloud AI Solutions -AI09936,Research Scientist,104491,EUR,88817,MI,CT,Germany,M,Germany,0,"Deep Learning, Linux, Computer Vision, GCP, Docker",PhD,2,Consulting,2024-01-17,2024-02-10,832,8,DeepTech Ventures -AI09937,AI Product Manager,89899,USD,89899,EX,FT,China,M,China,50,"R, AWS, Azure, Deep Learning, Python",Master,12,Real Estate,2025-02-28,2025-04-20,1332,5.4,Neural Networks Co -AI09938,Data Scientist,81953,EUR,69660,EN,PT,Germany,L,Germany,50,"Hadoop, Python, GCP, Deep Learning",Bachelor,0,Manufacturing,2024-12-21,2025-01-18,967,7.3,Neural Networks Co -AI09939,AI Product Manager,63919,GBP,47939,EN,FL,United Kingdom,S,United Kingdom,50,"Docker, SQL, AWS, Mathematics",PhD,0,Finance,2024-05-29,2024-07-25,2267,7,Cognitive Computing -AI09940,AI Software Engineer,251077,USD,251077,EX,PT,Sweden,L,Sweden,50,"Python, GCP, Mathematics, AWS",Bachelor,16,Retail,2024-04-16,2024-05-30,1188,7.2,Future Systems -AI09941,Research Scientist,154431,EUR,131266,EX,CT,Netherlands,M,Israel,0,"Scala, Tableau, Hadoop, Linux",Associate,11,Transportation,2024-09-10,2024-10-31,690,7.3,Machine Intelligence Group -AI09942,Data Scientist,84206,CAD,105258,MI,PT,Canada,S,Canada,0,"Hadoop, Java, SQL, Computer Vision, Azure",Bachelor,3,Real Estate,2024-12-02,2024-12-22,2097,6.3,AI Innovations -AI09943,AI Research Scientist,94103,USD,94103,EX,CT,India,L,Hungary,0,"Hadoop, SQL, Kubernetes",Master,10,Consulting,2024-04-30,2024-06-14,1596,8.2,Quantum Computing Inc -AI09944,Robotics Engineer,172742,EUR,146831,EX,FL,Netherlands,M,Netherlands,100,"Data Visualization, GCP, PyTorch, AWS",Associate,14,Media,2024-05-01,2024-06-22,1002,5.4,DeepTech Ventures -AI09945,AI Consultant,202350,AUD,273173,EX,FL,Australia,S,Australia,0,"Hadoop, Kubernetes, GCP",PhD,18,Media,2024-08-30,2024-10-09,2174,8.1,Predictive Systems -AI09946,AI Product Manager,220924,JPY,24301640,EX,PT,Japan,M,Japan,50,"TensorFlow, Deep Learning, Data Visualization",Associate,18,Government,2025-02-24,2025-04-14,717,6.1,Machine Intelligence Group -AI09947,Machine Learning Engineer,202063,EUR,171754,EX,FL,Germany,L,Germany,100,"Python, TensorFlow, SQL, Linux, Hadoop",Associate,16,Consulting,2024-05-29,2024-08-09,2230,8.7,Digital Transformation LLC -AI09948,NLP Engineer,156925,SGD,204003,SE,PT,Singapore,L,New Zealand,50,"Azure, Spark, Hadoop, Linux, SQL",Bachelor,8,Energy,2025-04-13,2025-05-26,679,8.6,DeepTech Ventures -AI09949,Machine Learning Researcher,127958,USD,127958,SE,FT,United States,S,United States,0,"AWS, SQL, Azure",PhD,6,Consulting,2024-11-25,2025-01-14,2152,9.7,Autonomous Tech -AI09950,AI Architect,88010,USD,88010,MI,PT,Finland,M,Finland,50,"SQL, Data Visualization, Spark, MLOps, Statistics",Bachelor,4,Education,2024-03-04,2024-05-05,2274,9.1,Predictive Systems -AI09951,Data Engineer,73299,USD,73299,EX,CT,India,S,India,0,"Python, Spark, SQL, Deep Learning, Linux",Associate,11,Media,2024-04-15,2024-06-03,668,7.4,Machine Intelligence Group -AI09952,Data Analyst,38886,USD,38886,MI,FT,India,L,India,0,"R, Python, Git, Statistics, Azure",Associate,3,Media,2025-01-14,2025-03-03,2418,5.1,Advanced Robotics -AI09953,Research Scientist,87404,EUR,74293,EN,CT,Netherlands,L,Norway,100,"TensorFlow, GCP, Python, Linux",Bachelor,0,Manufacturing,2024-12-19,2025-02-02,1258,8.5,Future Systems -AI09954,AI Product Manager,50608,EUR,43017,EN,FL,Netherlands,S,Denmark,100,"Spark, MLOps, Java, Kubernetes, Statistics",Associate,0,Manufacturing,2024-01-19,2024-03-04,2364,5.5,Advanced Robotics -AI09955,Data Analyst,87958,USD,87958,MI,FL,Sweden,S,Sweden,0,"Java, AWS, Mathematics, Deep Learning",Bachelor,4,Transportation,2024-07-12,2024-09-13,1500,7.9,Cloud AI Solutions -AI09956,NLP Engineer,65492,USD,65492,MI,CT,South Korea,M,Russia,100,"Deep Learning, Python, TensorFlow",Bachelor,2,Gaming,2024-07-06,2024-09-01,1987,9.6,Advanced Robotics -AI09957,Research Scientist,260160,USD,260160,EX,FL,Norway,M,Norway,0,"Linux, Computer Vision, R",Master,17,Finance,2024-03-14,2024-04-12,1484,9.1,AI Innovations -AI09958,Research Scientist,70254,GBP,52691,EN,CT,United Kingdom,M,United Kingdom,0,"Statistics, Tableau, GCP",Master,0,Healthcare,2024-08-06,2024-08-24,1063,7.7,Cognitive Computing -AI09959,NLP Engineer,159037,AUD,214700,EX,FT,Australia,L,Australia,50,"Kubernetes, Docker, Spark",PhD,19,Finance,2025-02-18,2025-03-16,858,6.7,Future Systems -AI09960,Data Scientist,117550,EUR,99918,SE,CT,France,S,France,100,"Computer Vision, Data Visualization, Kubernetes, Scala, Tableau",Master,9,Media,2024-04-08,2024-06-13,1552,7.1,Cognitive Computing -AI09961,Machine Learning Researcher,138817,USD,138817,MI,PT,United States,L,Estonia,50,"R, Deep Learning, TensorFlow, Docker",Master,2,Finance,2025-01-09,2025-03-13,1358,9.7,Neural Networks Co -AI09962,Machine Learning Researcher,233912,AUD,315781,EX,CT,Australia,L,Australia,50,"Hadoop, Linux, Docker",PhD,16,Real Estate,2024-09-26,2024-11-26,1830,8.5,AI Innovations -AI09963,AI Architect,83523,JPY,9187530,EN,FT,Japan,M,Japan,50,"AWS, Docker, Java, R",Associate,1,Transportation,2024-05-26,2024-07-09,1334,8.7,Digital Transformation LLC -AI09964,AI Consultant,49711,USD,49711,SE,CT,India,M,India,0,"PyTorch, Computer Vision, Linux",Bachelor,8,Education,2025-01-13,2025-02-22,1029,7.5,Advanced Robotics -AI09965,AI Product Manager,116921,CAD,146151,SE,FL,Canada,L,Canada,100,"Java, MLOps, SQL",Bachelor,6,Manufacturing,2024-05-09,2024-07-19,2433,8.1,Machine Intelligence Group -AI09966,Data Analyst,213255,CHF,191930,SE,CT,Switzerland,L,Switzerland,100,"Kubernetes, Linux, Computer Vision, Python, Spark",Associate,8,Healthcare,2024-03-12,2024-04-16,749,7.6,DeepTech Ventures -AI09967,Principal Data Scientist,102306,USD,102306,MI,FL,United States,S,Denmark,0,"Python, NLP, Statistics, Spark, Mathematics",PhD,2,Manufacturing,2024-05-02,2024-05-23,2478,6,Digital Transformation LLC -AI09968,ML Ops Engineer,86619,CAD,108274,MI,CT,Canada,L,Canada,100,"Python, Java, Spark, Computer Vision, TensorFlow",Master,2,Retail,2024-02-08,2024-03-06,1030,7.9,AI Innovations -AI09969,ML Ops Engineer,66607,EUR,56616,EN,FL,Germany,M,Czech Republic,100,"PyTorch, Tableau, Python, Docker, AWS",Bachelor,1,Media,2024-02-14,2024-03-11,2276,9.9,Digital Transformation LLC -AI09970,Head of AI,103856,USD,103856,MI,CT,Ireland,M,Ireland,50,"Computer Vision, Azure, Python, Linux",PhD,3,Retail,2024-10-25,2024-12-04,928,6.4,Digital Transformation LLC -AI09971,AI Consultant,128302,GBP,96227,MI,FT,United Kingdom,L,United Kingdom,100,"Spark, GCP, Deep Learning, Python",Bachelor,2,Transportation,2024-06-22,2024-08-20,648,9.9,Quantum Computing Inc -AI09972,ML Ops Engineer,99518,EUR,84590,MI,PT,Germany,L,Germany,0,"Statistics, MLOps, AWS",Associate,4,Transportation,2024-06-04,2024-06-18,2181,5.9,Cognitive Computing -AI09973,Research Scientist,225083,USD,225083,EX,CT,United States,M,Malaysia,0,"Scala, TensorFlow, Tableau, R",PhD,19,Real Estate,2025-01-09,2025-01-30,1316,7,Quantum Computing Inc -AI09974,Data Scientist,76078,EUR,64666,MI,FL,Austria,S,Austria,100,"R, Java, Linux",Associate,2,Manufacturing,2024-11-29,2024-12-23,871,6,Future Systems -AI09975,Data Analyst,208198,USD,208198,EX,FL,United States,L,China,100,"GCP, R, Spark, SQL",PhD,17,Energy,2024-11-26,2024-12-10,2426,6.8,Machine Intelligence Group -AI09976,Machine Learning Researcher,115497,SGD,150146,SE,FL,Singapore,S,France,50,"Python, Git, Computer Vision, Tableau",Associate,6,Manufacturing,2024-03-23,2024-05-27,1337,7,Advanced Robotics -AI09977,Data Analyst,30191,USD,30191,EN,FL,China,S,South Africa,50,"Python, Computer Vision, Docker, Kubernetes, Git",Master,0,Automotive,2024-06-28,2024-08-09,1509,6.8,Cloud AI Solutions -AI09978,Robotics Engineer,122452,USD,122452,MI,CT,Norway,S,Norway,0,"Spark, PyTorch, Kubernetes, Deep Learning, Tableau",Master,2,Telecommunications,2024-09-10,2024-11-17,1088,7,AI Innovations -AI09979,Robotics Engineer,80064,JPY,8807040,EN,CT,Japan,M,New Zealand,100,"Scala, SQL, Kubernetes, Tableau",Associate,1,Media,2024-12-28,2025-01-16,2318,7.6,Smart Analytics -AI09980,AI Architect,156844,USD,156844,SE,FL,United States,S,United States,50,"Docker, Spark, NLP, SQL, R",Master,8,Telecommunications,2024-01-05,2024-02-18,1084,5.8,Digital Transformation LLC -AI09981,AI Consultant,204204,CHF,183784,SE,CT,Switzerland,L,Switzerland,50,"Spark, AWS, Python",Master,8,Technology,2025-02-24,2025-05-02,1083,6.1,Cloud AI Solutions -AI09982,Principal Data Scientist,33152,USD,33152,MI,PT,India,L,India,100,"Deep Learning, Azure, Scala",Associate,3,Real Estate,2025-02-27,2025-03-31,1465,9.2,TechCorp Inc -AI09983,Data Engineer,65768,USD,65768,SE,FL,China,M,France,100,"R, Statistics, Scala, AWS, Azure",PhD,9,Gaming,2024-12-04,2024-12-25,2408,6.3,Machine Intelligence Group -AI09984,Data Scientist,73194,USD,73194,MI,PT,Sweden,M,Sweden,100,"Docker, Data Visualization, Linux",Associate,3,Retail,2024-08-23,2024-09-08,1618,8.2,AI Innovations -AI09985,AI Architect,55370,SGD,71981,EN,FL,Singapore,S,Singapore,50,"Mathematics, AWS, Hadoop",Associate,0,Retail,2024-11-08,2024-12-07,2104,8.3,Advanced Robotics -AI09986,Deep Learning Engineer,210307,GBP,157730,EX,FT,United Kingdom,M,United Kingdom,0,"GCP, Linux, Computer Vision, Java, Deep Learning",PhD,18,Retail,2024-04-30,2024-06-16,1090,5.3,Digital Transformation LLC -AI09987,AI Research Scientist,84436,USD,84436,EN,FT,United States,M,United States,100,"Java, NLP, GCP, Kubernetes",Master,1,Consulting,2024-04-24,2024-05-12,1654,7.3,Cognitive Computing -AI09988,ML Ops Engineer,54161,AUD,73117,EN,FT,Australia,S,Australia,0,"Azure, Scala, Java",PhD,1,Healthcare,2024-10-22,2024-11-13,1338,8.3,Neural Networks Co -AI09989,AI Software Engineer,205169,USD,205169,EX,CT,United States,M,United States,100,"Python, Tableau, NLP, Computer Vision",Master,12,Transportation,2024-09-27,2024-11-13,2197,5.7,DeepTech Ventures -AI09990,Data Engineer,38591,USD,38591,MI,PT,China,M,Colombia,50,"Python, Statistics, MLOps, TensorFlow, Computer Vision",Master,4,Transportation,2025-01-01,2025-02-12,1506,9.6,Neural Networks Co -AI09991,Research Scientist,68630,EUR,58336,EN,FT,France,L,United Kingdom,50,"R, Python, NLP, Data Visualization",PhD,0,Finance,2025-04-30,2025-06-24,2243,6.6,DeepTech Ventures -AI09992,Autonomous Systems Engineer,43605,USD,43605,SE,CT,China,S,China,0,"PyTorch, Deep Learning, TensorFlow",Bachelor,9,Consulting,2025-03-28,2025-05-18,969,7,Advanced Robotics -AI09993,ML Ops Engineer,161575,USD,161575,EX,CT,Finland,M,Finland,0,"Docker, Scala, Hadoop, TensorFlow, NLP",Master,16,Consulting,2024-11-16,2024-12-06,2224,9.9,Cognitive Computing -AI09994,Autonomous Systems Engineer,45084,USD,45084,MI,FL,China,M,China,50,"Linux, SQL, GCP",Bachelor,3,Telecommunications,2024-05-10,2024-05-29,1998,8.6,Neural Networks Co -AI09995,AI Product Manager,88847,USD,88847,SE,CT,South Korea,S,South Korea,100,"Hadoop, Scala, Tableau",Associate,5,Media,2024-07-09,2024-09-19,1406,5.1,Smart Analytics -AI09996,Data Analyst,273652,USD,273652,EX,PT,Norway,L,Norway,50,"Docker, Statistics, Linux, Python",Master,12,Real Estate,2024-04-28,2024-06-03,1723,8.9,Cognitive Computing -AI09997,AI Specialist,77815,JPY,8559650,EN,CT,Japan,M,Japan,50,"Python, SQL, Data Visualization, MLOps",Bachelor,1,Technology,2024-10-14,2024-12-14,1183,8.1,Cognitive Computing -AI09998,Head of AI,71265,USD,71265,MI,CT,Sweden,S,Ireland,100,"PyTorch, GCP, Kubernetes",Associate,2,Transportation,2024-08-02,2024-09-08,937,7.6,Algorithmic Solutions -AI09999,ML Ops Engineer,206399,USD,206399,EX,CT,United States,L,United States,0,"PyTorch, R, Tableau",Master,18,Automotive,2024-12-04,2024-12-27,1313,9,Neural Networks Co -AI10000,AI Consultant,199903,JPY,21989330,EX,FL,Japan,L,France,0,"Git, Python, Docker",PhD,16,Education,2025-04-27,2025-05-11,2171,7.3,Advanced Robotics -AI10001,AI Specialist,167578,USD,167578,SE,FT,Denmark,S,Denmark,100,"Linux, Python, Hadoop",PhD,6,Healthcare,2024-08-07,2024-09-16,996,9.6,Autonomous Tech -AI10002,AI Architect,154721,CHF,139249,SE,CT,Switzerland,M,Sweden,0,"Python, TensorFlow, MLOps, Azure",Bachelor,6,Government,2024-09-15,2024-10-05,1917,8.6,Future Systems -AI10003,AI Consultant,122754,EUR,104341,SE,FT,Netherlands,S,Czech Republic,100,"Spark, MLOps, TensorFlow, NLP, Mathematics",Master,7,Transportation,2025-01-20,2025-03-05,1738,5.5,Autonomous Tech -AI10004,Data Analyst,68729,USD,68729,EN,FL,Israel,M,Israel,0,"Computer Vision, Statistics, SQL, Python",Master,0,Automotive,2025-03-07,2025-04-07,1313,5.1,Cognitive Computing -AI10005,AI Software Engineer,85966,SGD,111756,EN,FT,Singapore,L,Singapore,100,"Hadoop, Docker, Data Visualization, Python",Associate,0,Education,2025-04-01,2025-04-22,1119,9.4,DataVision Ltd -AI10006,Data Analyst,131244,JPY,14436840,SE,FL,Japan,L,Japan,50,"Git, Scala, Java, Computer Vision",Master,8,Media,2024-03-24,2024-04-26,960,8.3,Autonomous Tech -AI10007,Computer Vision Engineer,122218,USD,122218,SE,FL,Sweden,L,Sweden,50,"Computer Vision, Python, Hadoop, MLOps",Associate,7,Automotive,2024-05-12,2024-07-18,2497,8.8,Quantum Computing Inc -AI10008,Research Scientist,79816,USD,79816,EN,PT,Norway,S,Canada,0,"Python, GCP, AWS",Bachelor,1,Manufacturing,2024-04-19,2024-06-25,546,6.3,Cognitive Computing -AI10009,Machine Learning Engineer,76709,EUR,65203,MI,PT,Netherlands,S,Netherlands,0,"TensorFlow, Azure, Kubernetes, Python, MLOps",Bachelor,2,Media,2024-04-28,2024-06-14,531,8.4,DeepTech Ventures -AI10010,Data Analyst,53982,USD,53982,EN,FT,Ireland,S,South Africa,0,"SQL, Scala, Tableau",Bachelor,0,Government,2024-06-29,2024-09-01,1371,8.3,Future Systems -AI10011,ML Ops Engineer,192615,EUR,163723,EX,FL,France,M,France,0,"Kubernetes, Tableau, Python",PhD,11,Energy,2025-01-29,2025-03-17,505,9.4,DataVision Ltd -AI10012,AI Architect,145605,JPY,16016550,SE,PT,Japan,L,Japan,100,"R, GCP, Java",Bachelor,8,Technology,2025-03-10,2025-04-10,2336,7.4,Neural Networks Co -AI10013,Autonomous Systems Engineer,97274,USD,97274,MI,PT,Denmark,S,Denmark,50,"PyTorch, Azure, Git",Bachelor,2,Technology,2024-10-18,2024-11-27,1260,9,TechCorp Inc -AI10014,AI Specialist,244858,USD,244858,EX,FL,Norway,S,Norway,100,"PyTorch, R, SQL, Statistics",Associate,15,Media,2024-03-14,2024-05-20,1932,7.1,Autonomous Tech -AI10015,Data Engineer,104413,EUR,88751,MI,PT,Netherlands,L,Netherlands,0,"GCP, MLOps, Scala, Kubernetes",Associate,4,Healthcare,2025-03-26,2025-05-18,1269,6.8,AI Innovations -AI10016,AI Specialist,213972,USD,213972,SE,CT,Norway,L,Norway,100,"AWS, Docker, Data Visualization, Deep Learning",Bachelor,6,Education,2024-05-04,2024-07-09,2063,5.1,Advanced Robotics -AI10017,Machine Learning Engineer,163739,USD,163739,EX,CT,Finland,S,Finland,0,"AWS, Kubernetes, Statistics, R",Associate,18,Real Estate,2024-12-11,2025-01-28,1031,8.2,Quantum Computing Inc -AI10018,Head of AI,54758,USD,54758,EN,CT,South Korea,S,Chile,0,"Tableau, Linux, AWS, TensorFlow, Deep Learning",Master,0,Technology,2024-12-13,2025-02-18,1502,6.9,DataVision Ltd -AI10019,Principal Data Scientist,90479,EUR,76907,MI,PT,France,M,Ireland,100,"Docker, R, MLOps, Kubernetes",Associate,4,Telecommunications,2024-03-19,2024-05-02,1148,9.7,Future Systems -AI10020,Deep Learning Engineer,159487,USD,159487,SE,PT,Norway,L,Singapore,100,"Docker, MLOps, Tableau, Python, Kubernetes",PhD,7,Real Estate,2024-09-25,2024-11-25,2469,6.3,Future Systems -AI10021,Computer Vision Engineer,64591,EUR,54902,EN,FT,Netherlands,L,Netherlands,0,"Scala, AWS, SQL, Python",Bachelor,1,Finance,2024-03-15,2024-04-23,2168,6.5,Neural Networks Co -AI10022,AI Product Manager,186453,GBP,139840,EX,CT,United Kingdom,M,Philippines,100,"TensorFlow, Hadoop, AWS, Java, Deep Learning",Bachelor,19,Technology,2024-09-17,2024-11-04,1428,5.1,DataVision Ltd -AI10023,Principal Data Scientist,367782,USD,367782,EX,FT,Denmark,L,Switzerland,0,"Data Visualization, Python, Git",Bachelor,16,Finance,2024-08-20,2024-10-12,1285,8.6,Future Systems -AI10024,Data Scientist,122924,AUD,165947,MI,FL,Australia,L,Spain,0,"Java, Linux, TensorFlow, SQL, MLOps",Master,4,Healthcare,2024-09-05,2024-09-19,797,7.6,Neural Networks Co -AI10025,Autonomous Systems Engineer,243749,AUD,329061,EX,PT,Australia,L,Australia,100,"GCP, Data Visualization, Linux, Computer Vision, SQL",PhD,19,Retail,2025-02-08,2025-03-22,2447,6.4,AI Innovations -AI10026,Computer Vision Engineer,78463,JPY,8630930,MI,CT,Japan,S,Japan,50,"Scala, Data Visualization, Git",Associate,3,Manufacturing,2024-04-17,2024-06-10,2462,9.4,TechCorp Inc -AI10027,Machine Learning Engineer,177410,USD,177410,SE,FT,Norway,M,Norway,0,"Linux, Python, PyTorch, Scala, AWS",Master,6,Consulting,2024-06-25,2024-08-15,1228,9.4,Machine Intelligence Group -AI10028,Robotics Engineer,85282,USD,85282,MI,FL,Israel,M,Israel,0,"Scala, Linux, TensorFlow, GCP, Statistics",PhD,2,Manufacturing,2024-07-04,2024-07-20,607,5.8,Digital Transformation LLC -AI10029,AI Consultant,54574,USD,54574,EN,CT,United States,S,United States,100,"Scala, Docker, Computer Vision, SQL",Master,1,Technology,2024-07-18,2024-08-21,1471,9.1,Algorithmic Solutions -AI10030,AI Architect,99684,JPY,10965240,MI,FL,Japan,M,Malaysia,100,"R, SQL, Kubernetes",Master,4,Transportation,2024-12-14,2025-02-25,1017,7,AI Innovations -AI10031,Autonomous Systems Engineer,107913,EUR,91726,SE,FT,France,S,France,100,"Spark, TensorFlow, Kubernetes",PhD,9,Government,2024-04-05,2024-06-09,769,9.3,Quantum Computing Inc -AI10032,Deep Learning Engineer,110437,SGD,143568,MI,FL,Singapore,L,Singapore,100,"Docker, MLOps, GCP, Python",Associate,2,Technology,2024-03-16,2024-05-18,1027,5.6,Cognitive Computing -AI10033,Data Scientist,32139,USD,32139,MI,FL,China,S,China,0,"Git, Python, Mathematics",Bachelor,2,Real Estate,2024-06-18,2024-07-31,1820,7.2,TechCorp Inc -AI10034,Research Scientist,78757,USD,78757,MI,FL,Ireland,M,Thailand,0,"Python, Tableau, NLP, MLOps",PhD,3,Government,2024-06-24,2024-08-26,1381,9.5,Algorithmic Solutions -AI10035,AI Architect,264042,AUD,356457,EX,FT,Australia,L,Australia,0,"Kubernetes, Statistics, MLOps, R",Associate,12,Telecommunications,2024-02-29,2024-05-01,2038,9.1,Autonomous Tech -AI10036,Data Engineer,208291,USD,208291,EX,PT,Ireland,L,Ireland,50,"Linux, AWS, Python, TensorFlow, Deep Learning",Master,11,Retail,2024-03-06,2024-05-15,1662,7.2,Cloud AI Solutions -AI10037,AI Architect,100038,USD,100038,MI,CT,Denmark,M,Egypt,100,"Kubernetes, Computer Vision, Git, NLP, Deep Learning",PhD,4,Retail,2024-01-23,2024-02-06,2234,6.8,DataVision Ltd -AI10038,NLP Engineer,77060,USD,77060,EN,PT,Norway,L,Israel,0,"Kubernetes, PyTorch, Mathematics",Associate,0,Government,2024-12-25,2025-01-08,1416,6.7,DeepTech Ventures -AI10039,Autonomous Systems Engineer,222150,USD,222150,EX,PT,Denmark,L,Switzerland,50,"Statistics, R, Python, Mathematics, Data Visualization",PhD,16,Gaming,2024-07-07,2024-09-10,1253,6.1,DataVision Ltd -AI10040,Robotics Engineer,163117,USD,163117,EX,CT,Israel,S,France,100,"SQL, Mathematics, Java",Bachelor,15,Education,2025-02-09,2025-04-20,584,6.3,Future Systems -AI10041,Research Scientist,221296,JPY,24342560,EX,PT,Japan,S,Austria,50,"AWS, Scala, GCP",PhD,10,Government,2024-02-06,2024-02-25,616,7.2,Advanced Robotics -AI10042,NLP Engineer,75240,USD,75240,MI,PT,Sweden,M,Sweden,50,"MLOps, NLP, TensorFlow",Bachelor,3,Technology,2024-01-03,2024-01-27,2150,9.7,Algorithmic Solutions -AI10043,AI Specialist,190468,GBP,142851,EX,PT,United Kingdom,S,United Kingdom,100,"R, Azure, Tableau, SQL",Associate,10,Gaming,2024-04-07,2024-05-11,2175,6,AI Innovations -AI10044,Machine Learning Engineer,229205,USD,229205,EX,FL,Norway,L,Norway,0,"Mathematics, PyTorch, Docker",Master,19,Government,2024-07-30,2024-08-27,702,5.6,Machine Intelligence Group -AI10045,AI Product Manager,158082,JPY,17389020,EX,FL,Japan,S,Japan,100,"Linux, Data Visualization, Spark",Bachelor,17,Retail,2024-04-13,2024-06-02,1116,6.2,Neural Networks Co -AI10046,Autonomous Systems Engineer,158388,EUR,134630,SE,PT,Austria,L,Austria,50,"MLOps, Azure, Tableau, Data Visualization",PhD,7,Transportation,2024-09-03,2024-11-15,1409,9.8,DataVision Ltd -AI10047,Deep Learning Engineer,270701,USD,270701,EX,CT,Norway,M,Norway,0,"GCP, Kubernetes, Python",Bachelor,10,Technology,2024-04-22,2024-06-02,673,9.5,AI Innovations -AI10048,AI Specialist,106640,EUR,90644,MI,PT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Statistics, Docker",PhD,4,Education,2024-12-18,2025-02-15,1432,8.5,TechCorp Inc -AI10049,AI Research Scientist,69424,EUR,59010,MI,FT,France,M,France,50,"GCP, AWS, Docker, Computer Vision, Python",Associate,2,Government,2024-05-11,2024-07-08,848,7,Cloud AI Solutions -AI10050,AI Research Scientist,93528,USD,93528,EN,FT,United States,L,United States,50,"Kubernetes, Docker, Statistics, Scala, Mathematics",Master,0,Transportation,2025-03-09,2025-05-15,1627,6,Autonomous Tech -AI10051,AI Software Engineer,114025,SGD,148233,MI,CT,Singapore,L,Singapore,50,"Scala, Python, Git, GCP, Computer Vision",Bachelor,3,Energy,2025-01-12,2025-02-16,2470,8.2,Cognitive Computing -AI10052,Machine Learning Engineer,91997,EUR,78197,MI,FL,France,S,France,100,"Python, Spark, Git, TensorFlow, Java",Associate,4,Transportation,2025-01-24,2025-02-13,505,8.6,DataVision Ltd -AI10053,Deep Learning Engineer,120244,SGD,156317,SE,PT,Singapore,S,Argentina,0,"Mathematics, Python, Hadoop, Tableau",Master,7,Gaming,2024-04-17,2024-05-07,721,7.3,DataVision Ltd -AI10054,Data Analyst,132194,USD,132194,EX,CT,China,L,China,50,"SQL, PyTorch, MLOps, TensorFlow",PhD,18,Telecommunications,2024-04-22,2024-06-24,1300,5.8,DataVision Ltd -AI10055,AI Specialist,108571,USD,108571,EX,CT,China,M,Kenya,100,"SQL, Linux, TensorFlow, Deep Learning",Bachelor,11,Media,2024-04-30,2024-05-17,1016,7.8,Predictive Systems -AI10056,Autonomous Systems Engineer,75698,USD,75698,EN,FL,Israel,M,Israel,100,"SQL, AWS, Hadoop, Python",Master,1,Technology,2025-03-25,2025-05-09,1791,8.2,AI Innovations -AI10057,Principal Data Scientist,39365,USD,39365,MI,CT,China,L,China,100,"Statistics, Git, GCP, Azure",Associate,3,Transportation,2024-01-19,2024-03-24,2176,8.1,Advanced Robotics -AI10058,Robotics Engineer,183526,EUR,155997,EX,PT,Germany,L,Germany,0,"NLP, Git, Java",Bachelor,10,Automotive,2024-10-10,2024-11-28,974,7.4,DataVision Ltd -AI10059,AI Consultant,143337,EUR,121836,EX,PT,Germany,M,Poland,100,"Data Visualization, SQL, PyTorch",Master,14,Technology,2024-06-16,2024-07-05,1608,5.2,DeepTech Ventures -AI10060,AI Software Engineer,63211,GBP,47408,EN,FL,United Kingdom,M,United Kingdom,50,"NLP, Git, MLOps",Associate,1,Gaming,2024-07-29,2024-09-17,2029,6.6,TechCorp Inc -AI10061,AI Architect,60718,GBP,45539,EN,FL,United Kingdom,S,United Kingdom,0,"GCP, Tableau, Scala, Java, AWS",Associate,0,Consulting,2024-03-05,2024-04-25,1108,9.2,DeepTech Ventures -AI10062,Robotics Engineer,93597,USD,93597,MI,FL,Finland,L,Poland,100,"Python, Scala, Tableau, MLOps, Azure",Bachelor,2,Government,2024-02-26,2024-03-16,1084,9.8,Quantum Computing Inc -AI10063,Deep Learning Engineer,92670,USD,92670,SE,FL,Israel,S,Israel,0,"Spark, Statistics, Linux, Mathematics",Master,9,Energy,2024-02-20,2024-04-18,674,5.5,Digital Transformation LLC -AI10064,Principal Data Scientist,52329,AUD,70644,EN,FL,Australia,M,Australia,100,"Linux, TensorFlow, Azure",Bachelor,1,Gaming,2025-02-07,2025-03-14,648,9.2,Autonomous Tech -AI10065,Autonomous Systems Engineer,110402,CHF,99362,MI,FT,Switzerland,M,Switzerland,100,"SQL, PyTorch, Azure",Bachelor,4,Finance,2024-02-11,2024-03-08,1722,5.9,Digital Transformation LLC -AI10066,Head of AI,79269,EUR,67379,EN,CT,France,L,France,100,"Python, TensorFlow, AWS",PhD,0,Transportation,2024-08-18,2024-10-10,1318,9.9,Cloud AI Solutions -AI10067,Deep Learning Engineer,147090,AUD,198572,SE,CT,Australia,L,Australia,0,"Statistics, GCP, NLP, MLOps",Bachelor,8,Media,2024-08-23,2024-10-13,1890,7.2,Digital Transformation LLC -AI10068,Research Scientist,95456,CAD,119320,SE,CT,Canada,S,Canada,0,"Scala, R, Hadoop, GCP",PhD,7,Technology,2024-01-06,2024-01-26,2009,9.3,Digital Transformation LLC -AI10069,AI Software Engineer,86713,GBP,65035,MI,CT,United Kingdom,S,United Kingdom,0,"R, Data Visualization, PyTorch, Java, Statistics",Associate,2,Real Estate,2024-06-09,2024-07-18,795,9.6,Cloud AI Solutions -AI10070,Robotics Engineer,267784,EUR,227616,EX,PT,Germany,L,Germany,0,"SQL, Java, Statistics, Computer Vision, GCP",PhD,17,Real Estate,2024-01-04,2024-02-25,2268,9,AI Innovations -AI10071,Autonomous Systems Engineer,107929,EUR,91740,MI,FL,Germany,M,Israel,0,"SQL, R, Data Visualization",PhD,4,Healthcare,2025-01-30,2025-03-16,608,9.1,Algorithmic Solutions -AI10072,Data Engineer,187961,USD,187961,SE,FT,Denmark,M,Denmark,50,"Mathematics, Java, Scala",PhD,5,Healthcare,2024-10-26,2024-11-17,887,8.6,Future Systems -AI10073,Research Scientist,79425,USD,79425,EN,CT,United States,S,Portugal,0,"Spark, R, Scala",Bachelor,0,Retail,2024-04-16,2024-05-04,2159,6.3,Machine Intelligence Group -AI10074,Autonomous Systems Engineer,69795,EUR,59326,MI,FL,France,M,France,50,"Java, Mathematics, Kubernetes, TensorFlow",Master,4,Finance,2025-02-19,2025-03-21,1831,9.8,Algorithmic Solutions -AI10075,NLP Engineer,91415,SGD,118840,MI,FT,Singapore,S,Singapore,0,"Computer Vision, Linux, Statistics",Associate,3,Media,2024-06-17,2024-08-24,607,6,Algorithmic Solutions -AI10076,AI Software Engineer,69308,EUR,58912,EN,PT,France,L,France,100,"R, PyTorch, Statistics, Git",Bachelor,0,Healthcare,2024-09-21,2024-11-28,1355,9.4,TechCorp Inc -AI10077,AI Software Engineer,262289,GBP,196717,EX,FT,United Kingdom,L,United Kingdom,100,"Computer Vision, Deep Learning, Data Visualization",Bachelor,12,Government,2025-03-26,2025-05-15,1644,9,Future Systems -AI10078,Research Scientist,117333,USD,117333,MI,PT,Ireland,L,Ireland,50,"Hadoop, Tableau, Java, Deep Learning",PhD,3,Education,2024-03-06,2024-05-10,1796,8,Digital Transformation LLC -AI10079,AI Architect,109771,USD,109771,MI,FT,United States,M,United States,100,"Linux, R, Kubernetes, Deep Learning",Associate,2,Finance,2024-01-09,2024-03-21,2490,5,Algorithmic Solutions -AI10080,NLP Engineer,150367,USD,150367,MI,FT,Norway,L,Romania,50,"SQL, TensorFlow, Computer Vision, AWS, Tableau",Associate,3,Technology,2024-05-15,2024-06-27,1894,5.2,AI Innovations -AI10081,Deep Learning Engineer,88240,EUR,75004,MI,PT,France,M,United Kingdom,100,"Data Visualization, TensorFlow, Docker, GCP, Deep Learning",Bachelor,2,Government,2025-03-26,2025-05-09,2369,9.8,Autonomous Tech -AI10082,NLP Engineer,158509,JPY,17435990,EX,FL,Japan,M,Japan,0,"PyTorch, Git, Scala, GCP",Master,19,Healthcare,2024-08-08,2024-09-13,2335,7.4,Digital Transformation LLC -AI10083,Computer Vision Engineer,95690,CHF,86121,EN,PT,Switzerland,M,Switzerland,100,"NLP, Spark, Python, Mathematics",Associate,0,Healthcare,2024-11-22,2025-01-23,2223,9.4,Digital Transformation LLC -AI10084,Research Scientist,65431,GBP,49073,EN,FL,United Kingdom,S,United Kingdom,100,"Docker, Tableau, Linux, Kubernetes",Associate,0,Transportation,2025-04-16,2025-05-05,1112,8,Cloud AI Solutions -AI10085,Research Scientist,41112,USD,41112,MI,FT,India,L,India,100,"Hadoop, Kubernetes, Python",PhD,4,Media,2024-05-12,2024-06-04,2195,8.7,Cognitive Computing -AI10086,AI Software Engineer,59137,EUR,50266,EN,FT,Netherlands,M,Netherlands,100,"Hadoop, Java, Azure",PhD,0,Transportation,2024-06-10,2024-08-02,514,9.7,Smart Analytics -AI10087,Autonomous Systems Engineer,78995,EUR,67146,MI,FT,Germany,S,Colombia,50,"Scala, Java, AWS",Bachelor,4,Real Estate,2024-06-15,2024-08-07,1977,5.2,DataVision Ltd -AI10088,Computer Vision Engineer,48283,USD,48283,SE,FL,China,S,Austria,0,"AWS, Deep Learning, Spark, SQL, Scala",Master,7,Technology,2024-05-10,2024-06-15,1845,5.8,Algorithmic Solutions -AI10089,Autonomous Systems Engineer,151012,USD,151012,SE,CT,Denmark,S,Australia,50,"Java, Kubernetes, Linux",Master,6,Healthcare,2025-01-29,2025-04-04,621,9.2,Neural Networks Co -AI10090,Deep Learning Engineer,225202,USD,225202,EX,FL,Norway,S,New Zealand,0,"R, Docker, Deep Learning",Associate,10,Technology,2024-01-15,2024-03-12,2018,7,Predictive Systems -AI10091,Computer Vision Engineer,172242,USD,172242,EX,FT,Denmark,S,Denmark,50,"MLOps, NLP, Spark",Associate,18,Telecommunications,2024-08-15,2024-10-24,500,6.8,Algorithmic Solutions -AI10092,AI Consultant,99624,JPY,10958640,MI,PT,Japan,S,Colombia,100,"R, GCP, Computer Vision, Data Visualization, Hadoop",PhD,3,Technology,2025-03-12,2025-04-17,2365,7.9,Neural Networks Co -AI10093,AI Software Engineer,116417,EUR,98954,SE,CT,Netherlands,M,Netherlands,100,"Kubernetes, GCP, AWS, Tableau",Associate,7,Automotive,2024-12-20,2025-02-26,1379,6.9,DeepTech Ventures -AI10094,Deep Learning Engineer,181783,EUR,154516,EX,PT,France,S,Romania,100,"Python, Mathematics, Hadoop, Java",PhD,19,Education,2024-05-01,2024-06-29,557,5.8,DataVision Ltd -AI10095,AI Research Scientist,150971,AUD,203811,SE,CT,Australia,L,Australia,50,"SQL, Hadoop, Mathematics, Git, Docker",Associate,7,Real Estate,2025-01-16,2025-02-04,2333,7.3,Autonomous Tech -AI10096,ML Ops Engineer,94318,USD,94318,MI,PT,Norway,S,Mexico,50,"Scala, GCP, Java, Git",Bachelor,2,Automotive,2024-03-02,2024-05-07,1541,7.2,Algorithmic Solutions -AI10097,AI Research Scientist,95368,GBP,71526,MI,FL,United Kingdom,S,United Kingdom,50,"Computer Vision, AWS, Docker",Bachelor,2,Finance,2025-04-19,2025-05-17,2341,7,TechCorp Inc -AI10098,AI Product Manager,190518,AUD,257199,EX,FT,Australia,M,Australia,100,"Hadoop, Spark, PyTorch",Associate,15,Energy,2024-01-19,2024-02-10,880,9.8,Machine Intelligence Group -AI10099,Computer Vision Engineer,55407,USD,55407,SE,CT,China,L,China,100,"Statistics, NLP, Scala",Master,5,Government,2024-03-02,2024-03-19,2404,7.2,Neural Networks Co -AI10100,ML Ops Engineer,21909,USD,21909,EN,FL,India,S,India,100,"Spark, Kubernetes, Tableau, Linux, Scala",Master,1,Healthcare,2024-07-27,2024-09-24,2258,6.6,Quantum Computing Inc -AI10101,AI Product Manager,92434,EUR,78569,MI,FL,France,M,South Africa,50,"Spark, SQL, Kubernetes, Deep Learning, Mathematics",PhD,3,Retail,2024-02-18,2024-04-04,562,9.3,Advanced Robotics -AI10102,Data Engineer,161210,USD,161210,SE,PT,Denmark,S,Denmark,100,"SQL, GCP, Statistics, Docker",Associate,6,Manufacturing,2024-02-09,2024-03-15,1008,5.9,Future Systems -AI10103,Head of AI,67818,USD,67818,SE,PT,China,L,Belgium,100,"Git, PyTorch, Tableau, R",Bachelor,5,Education,2024-12-28,2025-03-04,972,6.6,Machine Intelligence Group -AI10104,Computer Vision Engineer,93012,EUR,79060,MI,CT,Netherlands,M,Netherlands,0,"MLOps, Scala, Statistics",PhD,3,Finance,2024-03-20,2024-05-18,1313,5.2,Quantum Computing Inc -AI10105,Data Scientist,44243,USD,44243,MI,FL,China,L,China,100,"Python, Spark, MLOps",Associate,4,Education,2025-04-03,2025-06-01,1470,7.3,Algorithmic Solutions -AI10106,Deep Learning Engineer,73792,CAD,92240,EN,CT,Canada,L,South Korea,50,"MLOps, TensorFlow, Scala, Hadoop",PhD,0,Healthcare,2024-07-27,2024-09-16,1612,7.8,TechCorp Inc -AI10107,Deep Learning Engineer,82816,USD,82816,EX,FL,China,L,China,0,"Java, AWS, Azure, Python",Master,17,Energy,2024-04-16,2024-06-26,1824,5.1,DeepTech Ventures -AI10108,Robotics Engineer,153795,EUR,130726,SE,FT,Netherlands,L,Austria,50,"MLOps, TensorFlow, Docker",PhD,5,Technology,2025-04-25,2025-05-26,1033,5.1,TechCorp Inc -AI10109,Machine Learning Researcher,86614,USD,86614,MI,FT,Finland,L,Finland,0,"Python, TensorFlow, AWS",PhD,3,Education,2025-01-09,2025-02-10,827,8.6,Cloud AI Solutions -AI10110,Autonomous Systems Engineer,75523,EUR,64195,EN,FT,France,L,Russia,100,"R, SQL, Docker, MLOps, PyTorch",Master,1,Transportation,2024-06-18,2024-08-12,1776,6.4,Advanced Robotics -AI10111,Principal Data Scientist,105311,USD,105311,SE,PT,Israel,M,Israel,0,"Java, PyTorch, Statistics",PhD,5,Media,2024-07-16,2024-08-13,1714,8.6,Autonomous Tech -AI10112,Machine Learning Engineer,49131,JPY,5404410,EN,CT,Japan,S,Belgium,50,"Hadoop, GCP, Scala, TensorFlow",Master,1,Healthcare,2024-07-30,2024-09-22,1387,6.7,Machine Intelligence Group -AI10113,Head of AI,26483,USD,26483,EN,FL,China,S,China,50,"Java, Computer Vision, Data Visualization, GCP, PyTorch",PhD,1,Consulting,2024-08-06,2024-10-05,1235,8.1,TechCorp Inc -AI10114,Data Engineer,107269,USD,107269,SE,FT,Israel,S,Australia,100,"PyTorch, Spark, SQL, Linux",Associate,9,Energy,2024-10-02,2024-11-22,1007,6,Future Systems -AI10115,AI Product Manager,78026,USD,78026,EN,FL,Denmark,S,Denmark,100,"Git, Python, Linux, Azure",Bachelor,1,Retail,2024-05-22,2024-07-07,2242,6.5,TechCorp Inc -AI10116,ML Ops Engineer,98849,USD,98849,MI,PT,United States,L,Poland,100,"PyTorch, SQL, Data Visualization, Computer Vision",Associate,4,Consulting,2024-11-04,2024-12-28,540,5.1,DataVision Ltd -AI10117,Machine Learning Engineer,246511,USD,246511,EX,PT,Denmark,S,Russia,50,"Hadoop, Python, Tableau",Master,16,Real Estate,2024-02-18,2024-03-26,812,8.6,Algorithmic Solutions -AI10118,Head of AI,108146,CHF,97331,EN,FL,Switzerland,M,Switzerland,0,"Python, AWS, TensorFlow",PhD,0,Telecommunications,2024-03-07,2024-04-06,794,8.1,Algorithmic Solutions -AI10119,Machine Learning Researcher,66740,JPY,7341400,EN,CT,Japan,M,Canada,50,"Tableau, Linux, Kubernetes, PyTorch, Mathematics",Associate,1,Government,2024-04-25,2024-07-03,1062,5,Machine Intelligence Group -AI10120,Machine Learning Engineer,253573,USD,253573,EX,FT,Norway,L,Norway,50,"PyTorch, Python, Java, Tableau, R",Bachelor,17,Government,2024-05-05,2024-06-14,1950,9.2,Cloud AI Solutions -AI10121,Data Engineer,79168,AUD,106877,MI,FL,Australia,S,Australia,100,"Mathematics, Python, R, Git, TensorFlow",PhD,2,Telecommunications,2024-08-05,2024-09-19,993,6.4,Autonomous Tech -AI10122,Data Analyst,139622,EUR,118679,SE,PT,Netherlands,L,Netherlands,50,"Deep Learning, Mathematics, Hadoop, PyTorch",Master,9,Consulting,2025-04-03,2025-06-01,2392,6.5,Cognitive Computing -AI10123,Machine Learning Engineer,43943,USD,43943,SE,FT,India,S,India,50,"SQL, Scala, Python",PhD,9,Telecommunications,2024-04-13,2024-05-31,1723,7.5,TechCorp Inc -AI10124,AI Research Scientist,162422,GBP,121817,EX,FT,United Kingdom,S,United Kingdom,0,"Git, SQL, NLP, Azure, Linux",Master,17,Education,2024-05-16,2024-07-05,1442,5.3,Advanced Robotics -AI10125,ML Ops Engineer,43406,USD,43406,EN,CT,South Korea,S,Mexico,50,"Kubernetes, Java, R, SQL",Bachelor,0,Consulting,2024-09-10,2024-10-02,2472,9.5,Cloud AI Solutions -AI10126,Data Analyst,95920,JPY,10551200,MI,FT,Japan,L,Japan,100,"Python, TensorFlow, Mathematics",Master,2,Transportation,2024-12-02,2025-01-08,2081,9.2,Neural Networks Co -AI10127,AI Consultant,197698,EUR,168043,EX,FT,Germany,S,Germany,100,"GCP, Azure, Python, PyTorch, Java",Master,13,Finance,2024-10-22,2024-12-02,718,5.8,Future Systems -AI10128,AI Specialist,173515,AUD,234245,EX,FT,Australia,L,Nigeria,0,"Python, Scala, AWS, TensorFlow, Linux",Bachelor,16,Finance,2024-02-11,2024-03-27,1432,5.6,AI Innovations -AI10129,AI Specialist,192426,AUD,259775,EX,FL,Australia,L,Philippines,50,"Statistics, Hadoop, SQL",PhD,11,Gaming,2024-04-02,2024-05-30,1928,8.3,Cognitive Computing -AI10130,Research Scientist,212764,USD,212764,SE,CT,Denmark,L,Denmark,50,"Linux, Kubernetes, Data Visualization",Bachelor,8,Technology,2024-09-05,2024-10-01,2235,8.8,Machine Intelligence Group -AI10131,Autonomous Systems Engineer,50136,USD,50136,EN,PT,Finland,M,Finland,0,"AWS, Git, SQL, Azure, Linux",Master,0,Education,2024-10-12,2024-11-30,1646,5.1,Algorithmic Solutions -AI10132,AI Consultant,199327,EUR,169428,EX,FL,Austria,S,Latvia,50,"Python, SQL, Mathematics, Deep Learning",Bachelor,14,Real Estate,2024-04-05,2024-05-26,1617,5.3,AI Innovations -AI10133,AI Architect,104098,CHF,93688,EN,FL,Switzerland,L,Indonesia,100,"Git, Java, Python, TensorFlow, Mathematics",Associate,0,Manufacturing,2024-03-05,2024-04-23,1488,7.5,Quantum Computing Inc -AI10134,Research Scientist,89534,USD,89534,MI,FT,Finland,S,Finland,0,"Kubernetes, Docker, R, Hadoop, PyTorch",PhD,2,Finance,2024-07-07,2024-09-10,2258,8.5,Cloud AI Solutions -AI10135,NLP Engineer,72126,CAD,90158,EN,CT,Canada,L,Canada,0,"Spark, Git, Computer Vision, PyTorch, Kubernetes",PhD,0,Education,2024-09-06,2024-11-11,679,9.5,DataVision Ltd -AI10136,Autonomous Systems Engineer,120139,USD,120139,SE,FL,Sweden,S,Netherlands,100,"Mathematics, Python, Linux, SQL",Master,6,Healthcare,2024-03-05,2024-03-22,1834,8.2,Smart Analytics -AI10137,NLP Engineer,209827,CHF,188844,EX,CT,Switzerland,M,Switzerland,0,"Python, Tableau, Data Visualization, NLP",Master,17,Government,2024-01-31,2024-03-24,1007,5.5,Machine Intelligence Group -AI10138,NLP Engineer,63620,JPY,6998200,EN,FL,Japan,M,Japan,50,"Computer Vision, R, MLOps, SQL, PyTorch",Master,0,Healthcare,2025-04-13,2025-06-21,696,8.1,Autonomous Tech -AI10139,Robotics Engineer,43464,USD,43464,EN,CT,China,L,China,0,"PyTorch, AWS, Hadoop, NLP, Spark",PhD,0,Retail,2025-02-06,2025-04-15,1875,8.6,DeepTech Ventures -AI10140,Machine Learning Researcher,81847,USD,81847,SE,PT,China,L,Czech Republic,0,"MLOps, Data Visualization, AWS, Scala",PhD,9,Technology,2024-05-22,2024-08-01,799,8.2,Neural Networks Co -AI10141,ML Ops Engineer,125011,GBP,93758,SE,CT,United Kingdom,S,Germany,50,"Linux, Azure, Git, Computer Vision, TensorFlow",Master,9,Gaming,2024-09-08,2024-09-25,977,7,Algorithmic Solutions -AI10142,Deep Learning Engineer,253282,CAD,316603,EX,FT,Canada,L,Kenya,0,"Python, Git, TensorFlow, Azure, PyTorch",Associate,18,Finance,2024-10-09,2024-12-10,1585,6.8,DataVision Ltd -AI10143,Data Analyst,163715,USD,163715,EX,FL,Finland,S,Finland,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Media,2025-01-19,2025-02-05,1900,8.5,Advanced Robotics -AI10144,Head of AI,71407,EUR,60696,EN,FL,Germany,S,Indonesia,50,"SQL, Tableau, PyTorch",Master,0,Energy,2024-12-08,2025-02-12,1897,6.3,Quantum Computing Inc -AI10145,Deep Learning Engineer,66634,USD,66634,EN,PT,Ireland,L,Ireland,100,"AWS, Deep Learning, SQL, Azure, PyTorch",Associate,0,Media,2024-02-24,2024-03-23,1775,9.5,Digital Transformation LLC -AI10146,Autonomous Systems Engineer,160350,EUR,136298,EX,PT,Germany,M,Germany,50,"Spark, Kubernetes, MLOps, Python, Computer Vision",Associate,10,Energy,2025-04-20,2025-05-08,681,7.6,AI Innovations -AI10147,Deep Learning Engineer,119141,EUR,101270,SE,FT,Netherlands,M,Chile,50,"Hadoop, Azure, Git, Computer Vision, Scala",PhD,7,Finance,2024-04-04,2024-05-30,923,7.7,AI Innovations -AI10148,Machine Learning Engineer,92580,USD,92580,MI,FL,Israel,L,Israel,100,"GCP, Kubernetes, Computer Vision",Associate,4,Education,2024-07-19,2024-09-18,2309,9.4,Autonomous Tech -AI10149,Data Engineer,145627,AUD,196596,SE,PT,Australia,L,Australia,50,"Scala, Deep Learning, Computer Vision",PhD,5,Government,2024-08-16,2024-10-08,530,5.3,Algorithmic Solutions -AI10150,AI Specialist,213045,EUR,181088,EX,PT,Germany,M,Thailand,50,"Docker, MLOps, Kubernetes",Bachelor,12,Manufacturing,2025-03-18,2025-05-01,1675,7.7,Cognitive Computing -AI10151,Computer Vision Engineer,297403,SGD,386624,EX,FT,Singapore,L,Singapore,50,"Computer Vision, Python, Azure, Data Visualization",Bachelor,14,Finance,2024-05-18,2024-06-13,964,5.2,TechCorp Inc -AI10152,Data Analyst,69197,EUR,58817,MI,FT,France,S,France,0,"TensorFlow, MLOps, Java",Master,3,Gaming,2024-11-24,2024-12-30,2362,7.6,Smart Analytics -AI10153,Data Analyst,132689,USD,132689,SE,FT,Israel,L,Israel,100,"Computer Vision, Spark, Python, Mathematics, MLOps",Bachelor,7,Gaming,2024-04-14,2024-05-01,1072,6,Neural Networks Co -AI10154,Computer Vision Engineer,83336,GBP,62502,MI,FL,United Kingdom,S,Italy,50,"PyTorch, MLOps, SQL, Spark",PhD,2,Real Estate,2024-12-17,2025-01-23,2268,5.4,Predictive Systems -AI10155,AI Consultant,172090,JPY,18929900,SE,FT,Japan,L,Japan,0,"NLP, SQL, TensorFlow, Spark",Associate,5,Media,2024-10-30,2024-11-30,1316,8.8,DeepTech Ventures -AI10156,AI Product Manager,24926,USD,24926,EN,PT,China,M,China,0,"Mathematics, NLP, Data Visualization, Deep Learning, Hadoop",Associate,0,Healthcare,2025-04-13,2025-06-19,853,9.2,Advanced Robotics -AI10157,Data Analyst,211550,EUR,179818,EX,FL,Austria,L,Austria,100,"AWS, Kubernetes, NLP",Bachelor,17,Gaming,2025-01-31,2025-04-07,1102,5.6,Digital Transformation LLC -AI10158,NLP Engineer,104635,USD,104635,SE,PT,Finland,S,Finland,100,"Deep Learning, Scala, Tableau",Master,6,Real Estate,2024-10-17,2024-12-18,623,6.9,Digital Transformation LLC -AI10159,Data Scientist,67458,USD,67458,EN,FT,Finland,S,Finland,50,"Python, Azure, Tableau, Java",Master,1,Government,2024-03-05,2024-04-03,2364,5.5,Predictive Systems -AI10160,Research Scientist,137160,USD,137160,SE,CT,Sweden,L,Sweden,100,"Docker, Tableau, GCP, R",Associate,8,Retail,2024-01-04,2024-03-13,839,7.5,Cloud AI Solutions -AI10161,Head of AI,68285,USD,68285,EN,PT,Norway,S,Norway,50,"Java, Azure, AWS, Statistics, Computer Vision",Bachelor,0,Automotive,2025-03-24,2025-04-15,1170,9.8,Quantum Computing Inc -AI10162,Machine Learning Researcher,74005,CHF,66605,EN,FT,Switzerland,S,Philippines,100,"Hadoop, R, NLP",Associate,0,Manufacturing,2024-03-18,2024-04-09,1639,6.8,Cognitive Computing -AI10163,AI Architect,127491,JPY,14024010,SE,PT,Japan,M,Czech Republic,0,"SQL, Docker, Data Visualization, Mathematics",Associate,5,Real Estate,2024-08-26,2024-09-24,990,7.8,DeepTech Ventures -AI10164,Principal Data Scientist,64002,USD,64002,EX,FL,China,S,China,0,"Python, GCP, Data Visualization, MLOps",Master,14,Real Estate,2024-04-29,2024-05-31,1479,9.6,Advanced Robotics -AI10165,Data Analyst,87641,USD,87641,MI,FT,South Korea,L,South Korea,100,"SQL, NLP, Statistics, GCP, Java",PhD,4,Media,2024-03-28,2024-06-03,2285,8.9,DataVision Ltd -AI10166,Autonomous Systems Engineer,54064,JPY,5947040,EN,PT,Japan,S,Poland,0,"PyTorch, Docker, R, Deep Learning, Java",Master,0,Retail,2025-01-02,2025-03-06,1094,6.7,Machine Intelligence Group -AI10167,Research Scientist,92164,USD,92164,MI,CT,Denmark,S,Denmark,100,"Azure, NLP, Python, Statistics, Scala",PhD,4,Real Estate,2024-03-28,2024-06-01,2147,9.1,Autonomous Tech -AI10168,AI Product Manager,303272,USD,303272,EX,FT,Norway,L,Norway,0,"SQL, Spark, Tableau, PyTorch, Hadoop",PhD,11,Real Estate,2025-04-02,2025-04-20,1007,8.3,Cognitive Computing -AI10169,Data Analyst,125114,USD,125114,EX,FT,Sweden,S,Sweden,50,"Kubernetes, Git, Deep Learning, Computer Vision, Scala",Bachelor,12,Technology,2024-08-12,2024-09-08,2065,9.5,AI Innovations -AI10170,Deep Learning Engineer,54317,USD,54317,EN,CT,Ireland,M,Egypt,50,"Deep Learning, Spark, TensorFlow, PyTorch, Azure",Bachelor,1,Education,2025-03-20,2025-05-11,1082,6.1,DataVision Ltd -AI10171,Principal Data Scientist,75401,GBP,56551,MI,CT,United Kingdom,S,United Kingdom,0,"TensorFlow, Data Visualization, Java",Bachelor,4,Healthcare,2024-08-02,2024-09-25,1106,8.8,DeepTech Ventures -AI10172,ML Ops Engineer,125780,USD,125780,SE,FL,Ireland,L,Ireland,0,"TensorFlow, Python, Computer Vision, SQL, Scala",Master,5,Real Estate,2024-08-25,2024-09-09,1249,8.9,Quantum Computing Inc -AI10173,Machine Learning Researcher,92433,USD,92433,EN,PT,Denmark,M,Denmark,0,"Python, TensorFlow, Azure, Computer Vision",Associate,0,Finance,2025-03-31,2025-05-24,2132,5.2,Cloud AI Solutions -AI10174,AI Specialist,64856,GBP,48642,EN,CT,United Kingdom,L,Ukraine,50,"Java, R, Tableau",PhD,1,Gaming,2024-07-14,2024-08-09,1592,6.5,TechCorp Inc -AI10175,Autonomous Systems Engineer,403493,CHF,363144,EX,FL,Switzerland,L,Switzerland,100,"Git, SQL, Spark, PyTorch",PhD,14,Gaming,2025-03-15,2025-05-05,1045,5.5,Cognitive Computing -AI10176,NLP Engineer,68862,USD,68862,EX,CT,India,L,India,100,"PyTorch, SQL, Tableau",PhD,17,Manufacturing,2024-10-20,2024-11-11,988,5.2,Machine Intelligence Group -AI10177,AI Consultant,210010,GBP,157508,EX,CT,United Kingdom,S,United Kingdom,0,"Spark, GCP, Linux",Bachelor,18,Media,2025-04-16,2025-06-14,1217,7.5,Neural Networks Co -AI10178,Machine Learning Researcher,123778,AUD,167100,SE,FT,Australia,L,Turkey,0,"Linux, Python, Tableau, Mathematics",Bachelor,5,Healthcare,2024-03-26,2024-06-04,1700,10,Cognitive Computing -AI10179,Machine Learning Researcher,70793,SGD,92031,MI,FT,Singapore,S,Singapore,100,"R, SQL, Azure",Associate,2,Gaming,2025-02-04,2025-03-15,739,8,DataVision Ltd -AI10180,Autonomous Systems Engineer,135779,EUR,115412,EX,PT,Germany,S,Indonesia,50,"Deep Learning, Git, Spark, GCP, Azure",Master,18,Telecommunications,2024-05-03,2024-07-09,1937,5.3,AI Innovations -AI10181,AI Specialist,70351,USD,70351,MI,CT,Finland,S,Finland,100,"SQL, NLP, TensorFlow",Master,4,Healthcare,2024-03-07,2024-03-25,1223,7.8,AI Innovations -AI10182,AI Architect,168478,CHF,151630,MI,FL,Switzerland,L,Switzerland,50,"Git, Kubernetes, PyTorch, R, SQL",Master,2,Education,2024-06-03,2024-08-06,1027,8,DeepTech Ventures -AI10183,Robotics Engineer,132893,USD,132893,EX,FT,Israel,S,Israel,0,"Computer Vision, Python, TensorFlow, Mathematics, Linux",Bachelor,17,Real Estate,2024-11-17,2024-12-02,2289,9.3,Future Systems -AI10184,Data Engineer,277707,GBP,208280,EX,FT,United Kingdom,L,United Kingdom,50,"Git, R, Statistics, Data Visualization",Associate,13,Retail,2024-12-21,2025-01-09,1010,7.9,DataVision Ltd -AI10185,NLP Engineer,131380,USD,131380,MI,FT,United States,L,United States,100,"PyTorch, TensorFlow, Data Visualization, Kubernetes",Associate,3,Telecommunications,2024-02-17,2024-04-04,604,10,TechCorp Inc -AI10186,AI Specialist,104109,USD,104109,SE,FT,South Korea,S,Brazil,100,"Deep Learning, AWS, Kubernetes, SQL, PyTorch",Associate,7,Real Estate,2024-04-29,2024-07-08,1705,6.8,Cloud AI Solutions -AI10187,Autonomous Systems Engineer,144897,EUR,123162,SE,PT,Netherlands,L,Netherlands,100,"Spark, Computer Vision, Hadoop",Associate,7,Manufacturing,2024-10-07,2024-11-07,1202,5.7,DataVision Ltd -AI10188,Machine Learning Engineer,234506,SGD,304858,EX,FL,Singapore,S,Singapore,100,"Python, Kubernetes, Spark, Mathematics",Associate,12,Education,2024-12-28,2025-03-08,1410,6.5,Future Systems -AI10189,NLP Engineer,138684,USD,138684,MI,PT,Denmark,M,Denmark,50,"Python, Tableau, Azure, PyTorch",Master,4,Manufacturing,2024-07-25,2024-08-28,1314,7.5,Cloud AI Solutions -AI10190,Machine Learning Engineer,91626,USD,91626,MI,FL,Ireland,S,Ireland,0,"Data Visualization, Deep Learning, MLOps, Spark",Associate,3,Government,2024-06-30,2024-08-10,1506,6.3,Smart Analytics -AI10191,AI Consultant,227796,USD,227796,EX,FT,United States,S,Germany,100,"R, Hadoop, Docker",Master,11,Finance,2024-10-07,2024-10-22,728,6.8,Quantum Computing Inc -AI10192,Machine Learning Engineer,237622,EUR,201979,EX,FT,Germany,M,Germany,100,"TensorFlow, Python, Scala",Associate,11,Technology,2024-06-30,2024-07-27,788,9.8,Digital Transformation LLC -AI10193,Autonomous Systems Engineer,59553,JPY,6550830,EN,CT,Japan,M,Japan,100,"SQL, GCP, PyTorch, Java",Associate,1,Government,2024-11-02,2024-11-25,2408,5.6,Machine Intelligence Group -AI10194,Data Engineer,75248,EUR,63961,MI,FT,Austria,S,Austria,50,"Spark, TensorFlow, Linux",Bachelor,4,Finance,2024-02-08,2024-04-17,1561,6.8,Cloud AI Solutions -AI10195,AI Product Manager,44563,USD,44563,SE,FT,India,M,Hungary,0,"Java, Linux, Python, Spark",Master,5,Automotive,2024-12-17,2025-02-25,1663,7.9,Quantum Computing Inc -AI10196,AI Consultant,186290,CHF,167661,SE,CT,Switzerland,M,Switzerland,0,"Tableau, Kubernetes, Git",Master,8,Real Estate,2025-04-30,2025-05-31,1747,5.6,DataVision Ltd -AI10197,AI Consultant,130662,EUR,111063,EX,CT,France,S,France,100,"Python, Azure, Tableau, Linux",Master,13,Technology,2024-09-06,2024-10-29,2453,6.7,DeepTech Ventures -AI10198,Principal Data Scientist,202772,USD,202772,EX,CT,Ireland,S,Ireland,100,"Computer Vision, Docker, Statistics",Associate,11,Telecommunications,2025-02-06,2025-04-08,514,5.3,Digital Transformation LLC -AI10199,AI Product Manager,190276,USD,190276,EX,CT,Sweden,L,Sweden,50,"Kubernetes, Docker, Python",Master,18,Gaming,2025-04-02,2025-04-25,1339,5.8,Smart Analytics -AI10200,AI Architect,99498,EUR,84573,SE,CT,Netherlands,S,Switzerland,100,"Mathematics, Tableau, R, Java",Associate,6,Automotive,2024-04-03,2024-04-23,1999,9.7,Cognitive Computing -AI10201,AI Product Manager,190361,AUD,256987,EX,FT,Australia,M,Australia,0,"GCP, Deep Learning, Python, Linux",Master,15,Gaming,2024-12-24,2025-02-04,1361,7.6,Autonomous Tech -AI10202,Head of AI,62384,USD,62384,EN,FT,United States,M,United States,0,"Git, Azure, Deep Learning",Master,1,Energy,2024-09-14,2024-11-17,541,8,Smart Analytics -AI10203,AI Research Scientist,139626,USD,139626,SE,FT,Norway,M,Norway,100,"Scala, Python, NLP, Docker, AWS",Associate,8,Media,2024-12-04,2025-01-11,1764,8.7,AI Innovations -AI10204,AI Software Engineer,76788,USD,76788,EX,FL,India,S,India,50,"NLP, Kubernetes, GCP, Python, Java",Master,17,Manufacturing,2024-08-19,2024-09-07,2043,6.8,TechCorp Inc -AI10205,Robotics Engineer,177449,USD,177449,SE,CT,Norway,L,Norway,0,"Docker, Statistics, Python, Tableau",Bachelor,8,Healthcare,2024-06-08,2024-07-10,2020,8.5,AI Innovations -AI10206,Data Analyst,61915,USD,61915,EN,FL,Finland,L,Finland,0,"Mathematics, R, NLP",PhD,0,Energy,2025-02-24,2025-04-05,2439,7.3,Machine Intelligence Group -AI10207,Research Scientist,59769,SGD,77700,EN,CT,Singapore,S,Singapore,0,"R, AWS, Linux",Bachelor,0,Transportation,2024-09-05,2024-09-26,796,8.3,Cognitive Computing -AI10208,Autonomous Systems Engineer,102469,CHF,92222,MI,CT,Switzerland,M,Germany,0,"PyTorch, Kubernetes, Docker, SQL",PhD,2,Transportation,2024-10-17,2024-11-14,1833,6.8,TechCorp Inc -AI10209,Autonomous Systems Engineer,144818,USD,144818,MI,CT,Denmark,L,Denmark,0,"R, Hadoop, Scala, PyTorch",PhD,2,Technology,2024-09-03,2024-10-10,812,6.3,Digital Transformation LLC -AI10210,Principal Data Scientist,151885,CAD,189856,SE,PT,Canada,L,Canada,50,"Docker, Tableau, Data Visualization",Associate,7,Media,2025-03-27,2025-05-17,1140,9.6,Smart Analytics -AI10211,AI Consultant,76782,USD,76782,EN,PT,United States,L,United States,0,"GCP, Mathematics, AWS",PhD,1,Education,2024-04-03,2024-04-25,1697,5.3,Algorithmic Solutions -AI10212,Head of AI,76167,USD,76167,MI,CT,Sweden,M,Sweden,0,"Spark, Scala, SQL",Bachelor,3,Government,2024-08-09,2024-10-19,1139,7.8,Quantum Computing Inc -AI10213,Research Scientist,109222,SGD,141989,MI,PT,Singapore,M,Singapore,0,"Python, TensorFlow, Java",PhD,3,Automotive,2024-09-26,2024-11-13,1852,8.3,Algorithmic Solutions -AI10214,Robotics Engineer,112535,CAD,140669,SE,FT,Canada,L,Vietnam,50,"Kubernetes, GCP, Data Visualization, SQL",PhD,7,Transportation,2025-03-16,2025-05-24,1174,8.7,Quantum Computing Inc -AI10215,Principal Data Scientist,283415,USD,283415,EX,FT,Sweden,L,Japan,50,"Computer Vision, Statistics, Docker",PhD,19,Automotive,2024-10-10,2024-12-22,1359,5.2,Algorithmic Solutions -AI10216,Data Scientist,75965,EUR,64570,MI,FT,Germany,M,Germany,50,"AWS, Linux, Hadoop, R, MLOps",PhD,4,Government,2024-10-16,2024-11-12,2301,8.4,Machine Intelligence Group -AI10217,NLP Engineer,91675,EUR,77924,MI,FL,Austria,M,Austria,0,"TensorFlow, AWS, Statistics",Bachelor,4,Consulting,2024-12-24,2025-02-16,515,8.9,Quantum Computing Inc -AI10218,Data Scientist,142668,CAD,178335,EX,PT,Canada,S,Canada,0,"Python, Java, Git, Spark, Azure",Associate,15,Consulting,2024-11-03,2024-11-27,2152,6.1,AI Innovations -AI10219,AI Specialist,65229,CAD,81536,EN,FL,Canada,S,Russia,100,"Python, Kubernetes, TensorFlow, Hadoop",Associate,1,Media,2024-01-02,2024-02-16,1513,7.5,Machine Intelligence Group -AI10220,Machine Learning Engineer,80835,CAD,101044,MI,FL,Canada,S,Singapore,100,"Data Visualization, Scala, Kubernetes, Deep Learning, GCP",PhD,2,Healthcare,2024-11-28,2025-01-01,1934,5.8,Autonomous Tech -AI10221,Deep Learning Engineer,250293,SGD,325381,EX,FL,Singapore,M,Singapore,100,"Kubernetes, Java, SQL, PyTorch, Azure",Associate,13,Finance,2024-03-10,2024-04-25,2222,7.5,Algorithmic Solutions -AI10222,AI Architect,162995,CHF,146696,MI,FT,Switzerland,L,Switzerland,0,"Git, Java, Spark, Python, GCP",Master,2,Retail,2025-01-07,2025-02-23,2411,9.5,DataVision Ltd -AI10223,AI Consultant,247822,USD,247822,EX,FL,Norway,M,Norway,100,"Git, Tableau, Deep Learning, Docker",Bachelor,19,Gaming,2024-02-26,2024-04-14,573,8.5,Cloud AI Solutions -AI10224,Machine Learning Engineer,168577,AUD,227579,SE,FL,Australia,L,Indonesia,100,"Hadoop, Kubernetes, Scala, Azure",Bachelor,6,Transportation,2024-06-01,2024-06-22,1731,6.2,Cognitive Computing -AI10225,Deep Learning Engineer,86183,USD,86183,EN,PT,Ireland,L,Ireland,100,"Data Visualization, Linux, PyTorch, TensorFlow",Associate,1,Government,2024-03-24,2024-04-13,929,6.4,Machine Intelligence Group -AI10226,AI Product Manager,95435,USD,95435,EN,FT,Norway,M,Ukraine,50,"SQL, Tableau, AWS, Java, R",PhD,0,Government,2024-09-16,2024-10-25,882,9.1,Advanced Robotics -AI10227,Robotics Engineer,86159,JPY,9477490,MI,FL,Japan,S,Japan,50,"GCP, NLP, PyTorch, Python",Bachelor,4,Education,2024-03-31,2024-05-05,1672,5.1,Advanced Robotics -AI10228,Deep Learning Engineer,30009,USD,30009,EN,CT,China,L,China,100,"Java, Linux, NLP, Git, Spark",Bachelor,0,Retail,2025-01-06,2025-02-09,1576,9.5,Advanced Robotics -AI10229,Robotics Engineer,65632,USD,65632,EN,PT,Finland,S,Finland,100,"Git, Python, SQL, GCP",Bachelor,1,Government,2025-03-24,2025-06-04,911,5.5,Cloud AI Solutions -AI10230,Data Engineer,161846,USD,161846,SE,PT,Israel,L,Israel,50,"GCP, Spark, Linux",PhD,6,Healthcare,2024-11-20,2024-12-15,2142,6.7,Quantum Computing Inc -AI10231,AI Research Scientist,67413,EUR,57301,EN,CT,Netherlands,S,Netherlands,0,"Azure, SQL, Data Visualization",PhD,1,Automotive,2024-06-26,2024-08-10,624,5.2,Digital Transformation LLC -AI10232,AI Architect,95990,USD,95990,SE,FL,Finland,S,Finland,0,"Tableau, TensorFlow, Kubernetes, SQL, GCP",PhD,9,Consulting,2024-02-15,2024-04-20,1850,9.3,TechCorp Inc -AI10233,Research Scientist,80350,CAD,100438,MI,CT,Canada,S,Canada,100,"NLP, SQL, PyTorch, Deep Learning, MLOps",Associate,4,Gaming,2024-10-15,2024-12-27,2154,6.5,Advanced Robotics -AI10234,Robotics Engineer,135564,USD,135564,EX,PT,China,L,China,50,"PyTorch, Kubernetes, TensorFlow, Linux",Master,16,Healthcare,2024-12-06,2025-02-01,586,8.8,Smart Analytics -AI10235,AI Software Engineer,218274,JPY,24010140,EX,PT,Japan,L,Japan,0,"GCP, Spark, Data Visualization",Bachelor,12,Healthcare,2024-12-04,2025-01-27,1162,5.3,Cognitive Computing -AI10236,NLP Engineer,79956,USD,79956,MI,FT,Israel,L,Israel,50,"SQL, Statistics, AWS, Docker",Associate,3,Manufacturing,2024-05-16,2024-07-06,2101,5.8,DeepTech Ventures -AI10237,AI Product Manager,210360,USD,210360,EX,PT,Ireland,L,Hungary,50,"Python, Computer Vision, Mathematics",Master,11,Government,2024-10-08,2024-12-06,1305,7.1,DeepTech Ventures -AI10238,AI Software Engineer,203510,USD,203510,EX,PT,Finland,M,France,50,"Python, Hadoop, Linux",Associate,14,Finance,2024-06-29,2024-08-26,1073,7.3,TechCorp Inc -AI10239,Principal Data Scientist,54946,USD,54946,MI,FL,China,L,Norway,0,"Kubernetes, PyTorch, GCP, Computer Vision",Bachelor,2,Energy,2024-04-27,2024-06-21,761,6.2,TechCorp Inc -AI10240,Deep Learning Engineer,301525,USD,301525,EX,FT,Norway,M,Norway,0,"Tableau, Kubernetes, Linux, AWS",PhD,15,Media,2024-10-16,2024-12-26,1359,9,TechCorp Inc -AI10241,Data Engineer,54730,AUD,73886,EN,CT,Australia,M,Australia,50,"Scala, Kubernetes, Deep Learning, GCP, SQL",Bachelor,0,Automotive,2024-09-07,2024-10-31,641,6.1,TechCorp Inc -AI10242,Data Engineer,70076,USD,70076,MI,CT,South Korea,M,South Korea,0,"Git, Hadoop, GCP",Bachelor,3,Transportation,2024-03-25,2024-05-26,1249,7,Predictive Systems -AI10243,Robotics Engineer,140236,USD,140236,EX,FL,South Korea,M,South Korea,0,"Spark, R, Java, Data Visualization, Tableau",Associate,14,Energy,2025-04-14,2025-06-15,1958,9.3,Machine Intelligence Group -AI10244,AI Consultant,76319,CHF,68687,EN,CT,Switzerland,S,South Africa,0,"Spark, Git, SQL",Associate,1,Gaming,2024-02-18,2024-03-10,1721,7.5,Quantum Computing Inc -AI10245,Principal Data Scientist,117897,USD,117897,EN,PT,Denmark,L,Philippines,0,"Spark, Tableau, Java",Bachelor,1,Retail,2024-12-02,2025-01-09,1874,6,AI Innovations -AI10246,Principal Data Scientist,67144,USD,67144,EX,FT,India,M,India,0,"Git, Python, NLP, Deep Learning, R",Associate,18,Finance,2024-02-13,2024-02-27,849,5.1,Predictive Systems -AI10247,Computer Vision Engineer,77616,EUR,65974,EN,CT,France,L,France,50,"AWS, Computer Vision, Data Visualization, MLOps, Statistics",Bachelor,0,Government,2024-04-04,2024-06-02,1095,6.9,Machine Intelligence Group -AI10248,Research Scientist,141826,USD,141826,MI,CT,Norway,L,Norway,0,"Python, Kubernetes, SQL, Linux, Hadoop",Associate,3,Real Estate,2024-11-12,2025-01-11,2171,5.3,DeepTech Ventures -AI10249,Data Engineer,73463,JPY,8080930,EN,FT,Japan,S,Japan,100,"Python, Git, NLP, GCP, Hadoop",Bachelor,1,Manufacturing,2024-07-11,2024-08-05,1343,6.1,Machine Intelligence Group -AI10250,AI Research Scientist,109715,USD,109715,MI,CT,Denmark,M,Denmark,0,"Docker, SQL, PyTorch, Spark",Bachelor,4,Finance,2024-02-05,2024-03-04,2237,7,DeepTech Ventures -AI10251,Robotics Engineer,69994,EUR,59495,MI,FT,Austria,M,Austria,0,"Statistics, Azure, Python",Bachelor,2,Manufacturing,2025-04-15,2025-05-07,1393,5.8,Predictive Systems -AI10252,NLP Engineer,117074,CHF,105367,MI,CT,Switzerland,S,Colombia,100,"GCP, Azure, NLP, TensorFlow",Master,4,Manufacturing,2025-02-13,2025-03-17,1001,6.5,DataVision Ltd -AI10253,Computer Vision Engineer,105296,GBP,78972,MI,FL,United Kingdom,S,United Kingdom,100,"Scala, Computer Vision, GCP, NLP, Git",Associate,3,Gaming,2024-05-09,2024-07-20,1754,8.6,DeepTech Ventures -AI10254,Head of AI,165753,CHF,149178,SE,FL,Switzerland,S,Netherlands,50,"Deep Learning, Hadoop, Java",Associate,9,Real Estate,2024-07-11,2024-08-17,1737,9.4,Cloud AI Solutions -AI10255,Deep Learning Engineer,136546,SGD,177510,SE,CT,Singapore,L,Japan,50,"SQL, R, NLP",Associate,5,Finance,2024-10-14,2024-11-05,1371,6.2,Cloud AI Solutions -AI10256,ML Ops Engineer,61219,USD,61219,EN,CT,Israel,M,Indonesia,0,"Kubernetes, MLOps, Scala",Master,0,Consulting,2025-01-01,2025-03-09,1568,8.3,DeepTech Ventures -AI10257,Head of AI,86631,EUR,73636,MI,FT,Austria,M,Austria,0,"Docker, SQL, Mathematics",PhD,2,Manufacturing,2024-01-20,2024-03-17,1632,7,Autonomous Tech -AI10258,AI Consultant,226414,USD,226414,EX,PT,Ireland,M,Ireland,100,"NLP, Azure, Deep Learning",Associate,13,Education,2024-07-26,2024-09-18,666,9.4,Neural Networks Co -AI10259,AI Research Scientist,113616,EUR,96574,SE,FT,Netherlands,S,Netherlands,50,"Scala, Hadoop, Computer Vision, Deep Learning",Master,7,Retail,2025-04-09,2025-06-14,1885,6,Smart Analytics -AI10260,Principal Data Scientist,191958,USD,191958,SE,FL,Norway,L,Norway,0,"Mathematics, Computer Vision, Kubernetes",Bachelor,6,Healthcare,2025-04-12,2025-05-03,1954,8.1,AI Innovations -AI10261,AI Research Scientist,50163,CAD,62704,EN,CT,Canada,S,Brazil,50,"Git, PyTorch, TensorFlow",PhD,1,Telecommunications,2025-03-03,2025-03-27,2229,8.6,TechCorp Inc -AI10262,Robotics Engineer,337422,USD,337422,EX,FL,United States,L,Sweden,100,"Linux, NLP, TensorFlow, Docker, Mathematics",PhD,12,Government,2024-04-21,2024-05-20,1783,9.7,Cognitive Computing -AI10263,AI Architect,67566,USD,67566,EN,FT,Sweden,S,Sweden,0,"Kubernetes, Data Visualization, Git",Associate,1,Telecommunications,2024-10-21,2025-01-01,1563,6.5,Cloud AI Solutions -AI10264,AI Specialist,59923,EUR,50935,EN,FL,Netherlands,M,Australia,100,"Docker, Python, Deep Learning, SQL, Statistics",Bachelor,0,Education,2025-03-06,2025-04-26,2410,5.9,DataVision Ltd -AI10265,Data Engineer,238139,EUR,202418,EX,CT,France,M,France,50,"Deep Learning, Hadoop, Python, Docker, Git",Associate,12,Education,2024-01-19,2024-02-27,786,9.9,Advanced Robotics -AI10266,Research Scientist,231140,USD,231140,EX,PT,Israel,L,Israel,100,"SQL, PyTorch, R, Spark",Bachelor,16,Transportation,2024-02-02,2024-04-12,1351,6.2,Neural Networks Co -AI10267,Principal Data Scientist,124660,JPY,13712600,SE,PT,Japan,M,Japan,0,"Scala, Azure, Linux",Bachelor,7,Retail,2024-02-22,2024-05-02,1365,6.9,Cloud AI Solutions -AI10268,AI Product Manager,147934,USD,147934,SE,FL,Sweden,L,Finland,50,"R, SQL, PyTorch, Hadoop, Mathematics",Associate,5,Retail,2024-05-04,2024-07-15,2042,8.7,Digital Transformation LLC -AI10269,NLP Engineer,154109,USD,154109,SE,PT,Sweden,L,Argentina,0,"Python, Kubernetes, MLOps, NLP, TensorFlow",Bachelor,5,Technology,2024-06-14,2024-08-06,652,9.6,Machine Intelligence Group -AI10270,Head of AI,182664,SGD,237463,SE,PT,Singapore,L,Singapore,100,"SQL, PyTorch, NLP, TensorFlow, Statistics",Associate,8,Education,2024-08-08,2024-10-05,1732,5.8,AI Innovations -AI10271,AI Research Scientist,106779,GBP,80084,MI,PT,United Kingdom,L,Thailand,0,"Mathematics, SQL, Git",Associate,2,Retail,2024-03-22,2024-05-25,2379,7.7,TechCorp Inc -AI10272,Principal Data Scientist,76695,SGD,99704,EN,PT,Singapore,S,Indonesia,0,"Data Visualization, TensorFlow, MLOps",Bachelor,0,Manufacturing,2024-08-27,2024-10-30,1852,6.8,Machine Intelligence Group -AI10273,Deep Learning Engineer,33529,USD,33529,EN,CT,China,M,China,50,"Kubernetes, Deep Learning, GCP",PhD,1,Consulting,2024-10-11,2024-11-07,1608,7.6,Advanced Robotics -AI10274,Machine Learning Researcher,92400,EUR,78540,EN,CT,Germany,L,Germany,100,"Linux, Mathematics, Hadoop, Spark, Java",Associate,0,Government,2024-05-15,2024-07-12,1559,8.9,Cognitive Computing -AI10275,Autonomous Systems Engineer,222418,USD,222418,EX,FT,United States,M,United States,100,"Azure, Kubernetes, Deep Learning",Bachelor,17,Media,2025-03-01,2025-04-25,1951,9.3,Quantum Computing Inc -AI10276,AI Product Manager,86393,EUR,73434,EN,CT,Netherlands,L,Ukraine,50,"TensorFlow, Azure, Computer Vision",Associate,1,Automotive,2025-01-02,2025-02-15,1735,5.6,Quantum Computing Inc -AI10277,AI Software Engineer,122637,USD,122637,SE,PT,Norway,S,Norway,100,"NLP, Scala, R, Azure",PhD,8,Automotive,2024-04-15,2024-05-14,1246,9,Algorithmic Solutions -AI10278,ML Ops Engineer,190440,AUD,257094,EX,PT,Australia,L,Brazil,100,"Azure, TensorFlow, Data Visualization",Associate,16,Manufacturing,2024-12-26,2025-03-01,1381,6.6,Neural Networks Co -AI10279,Machine Learning Researcher,72783,CHF,65505,EN,FL,Switzerland,S,Switzerland,50,"AWS, SQL, Hadoop",Bachelor,1,Telecommunications,2024-06-17,2024-07-14,2348,9.5,Predictive Systems -AI10280,AI Software Engineer,191481,EUR,162759,EX,FL,Germany,S,Germany,0,"Docker, Python, Data Visualization",Master,10,Healthcare,2024-05-31,2024-07-08,1695,5.6,Predictive Systems -AI10281,AI Software Engineer,119141,USD,119141,MI,FL,Denmark,S,Denmark,50,"Scala, Python, Deep Learning, Azure, Linux",Bachelor,2,Manufacturing,2024-04-25,2024-06-14,1185,8.7,Neural Networks Co -AI10282,Autonomous Systems Engineer,61294,SGD,79682,EN,FT,Singapore,M,Czech Republic,0,"Docker, Spark, R, Linux",Bachelor,1,Energy,2024-04-16,2024-06-17,1547,8.3,Predictive Systems -AI10283,Machine Learning Researcher,112748,EUR,95836,SE,FT,Austria,L,South Africa,50,"Scala, Python, MLOps",PhD,9,Consulting,2024-01-05,2024-02-24,1639,6.8,Smart Analytics -AI10284,AI Specialist,69817,CAD,87271,MI,FL,Canada,M,Philippines,0,"Git, Statistics, Mathematics, Spark, Azure",Bachelor,2,Technology,2024-04-15,2024-06-11,1463,9.8,Quantum Computing Inc -AI10285,Data Engineer,162528,CAD,203160,EX,PT,Canada,S,Canada,0,"Git, Hadoop, TensorFlow, Scala",Bachelor,16,Energy,2024-09-24,2024-11-22,1815,9.5,Autonomous Tech -AI10286,Principal Data Scientist,80432,USD,80432,EN,PT,Denmark,L,Denmark,0,"Kubernetes, AWS, Java",PhD,1,Telecommunications,2024-11-13,2024-12-01,2443,6.2,DeepTech Ventures -AI10287,Robotics Engineer,263161,CHF,236845,EX,CT,Switzerland,L,Switzerland,0,"Kubernetes, Python, Computer Vision, TensorFlow",Bachelor,15,Government,2025-01-04,2025-02-06,1699,6.4,Predictive Systems -AI10288,AI Research Scientist,70408,CAD,88010,EN,CT,Canada,L,Canada,100,"PyTorch, Computer Vision, Statistics",PhD,0,Gaming,2024-03-29,2024-05-25,643,9.9,AI Innovations -AI10289,Machine Learning Researcher,84533,EUR,71853,MI,FL,France,S,Latvia,100,"Scala, Linux, Kubernetes",Associate,3,Automotive,2024-04-10,2024-04-28,2027,6.5,Quantum Computing Inc -AI10290,Machine Learning Researcher,94145,USD,94145,MI,CT,South Korea,L,South Korea,0,"Java, GCP, R",PhD,4,Energy,2024-04-20,2024-05-26,1087,7.6,Autonomous Tech -AI10291,Research Scientist,52193,USD,52193,EN,PT,Finland,M,Finland,100,"Azure, Spark, Git",Bachelor,0,Telecommunications,2024-12-31,2025-03-12,2340,8.1,Predictive Systems -AI10292,AI Consultant,153253,USD,153253,EX,CT,Ireland,M,Ireland,0,"Kubernetes, Hadoop, Deep Learning",Bachelor,10,Media,2024-01-18,2024-03-30,1495,9.8,Smart Analytics -AI10293,Machine Learning Engineer,87192,USD,87192,MI,CT,Israel,L,Australia,100,"Computer Vision, R, Tableau, Data Visualization",Bachelor,4,Retail,2024-08-20,2024-10-04,1220,9.7,DeepTech Ventures -AI10294,AI Specialist,214211,CHF,192790,EX,PT,Switzerland,S,Turkey,100,"Java, AWS, Statistics, Hadoop",PhD,19,Gaming,2024-01-10,2024-02-05,746,5.5,Algorithmic Solutions -AI10295,AI Product Manager,203264,JPY,22359040,EX,CT,Japan,M,Poland,50,"SQL, Hadoop, Git, Linux",Bachelor,16,Finance,2025-01-19,2025-03-14,1961,5.2,Predictive Systems -AI10296,Autonomous Systems Engineer,172259,JPY,18948490,EX,PT,Japan,M,Russia,100,"Deep Learning, MLOps, Python, Tableau, Scala",Associate,16,Gaming,2024-02-03,2024-03-02,1017,7.4,Algorithmic Solutions -AI10297,Research Scientist,109363,SGD,142172,SE,CT,Singapore,S,Singapore,100,"Deep Learning, Java, Python",Associate,6,Energy,2024-11-02,2024-12-08,1270,7.9,Predictive Systems -AI10298,AI Software Engineer,50885,USD,50885,EX,FL,India,S,India,100,"AWS, Python, Git, Statistics, TensorFlow",Bachelor,17,Government,2025-04-08,2025-05-19,1119,9.6,Algorithmic Solutions -AI10299,ML Ops Engineer,108450,USD,108450,MI,FL,Norway,L,Norway,100,"Linux, PyTorch, TensorFlow, Docker, Mathematics",Associate,2,Media,2025-04-24,2025-07-04,1495,7,Digital Transformation LLC -AI10300,AI Specialist,57880,USD,57880,MI,FL,China,L,China,100,"Python, Spark, Tableau, Scala, Mathematics",Master,3,Transportation,2024-05-27,2024-07-02,2363,9.2,Neural Networks Co -AI10301,AI Software Engineer,113212,USD,113212,SE,FT,South Korea,S,South Korea,100,"GCP, Spark, NLP, TensorFlow, MLOps",PhD,7,Consulting,2024-01-04,2024-02-11,1158,8.9,Advanced Robotics -AI10302,AI Architect,161719,USD,161719,SE,PT,Norway,L,Norway,0,"R, Git, Kubernetes",Associate,8,Finance,2024-05-18,2024-07-18,653,7.1,Digital Transformation LLC -AI10303,Data Engineer,71629,USD,71629,EN,PT,South Korea,L,China,0,"Tableau, GCP, Linux",Bachelor,1,Telecommunications,2024-09-26,2024-11-24,1646,5.5,Smart Analytics -AI10304,Deep Learning Engineer,257527,USD,257527,EX,FL,Ireland,L,Ireland,50,"Linux, Deep Learning, MLOps, PyTorch",Master,10,Technology,2024-03-26,2024-05-21,1258,9.4,Cognitive Computing -AI10305,Computer Vision Engineer,174720,USD,174720,EX,FT,United States,M,Ireland,0,"Kubernetes, Spark, Computer Vision, TensorFlow, Scala",Associate,15,Finance,2024-03-19,2024-04-13,722,6.4,AI Innovations -AI10306,AI Software Engineer,163238,USD,163238,SE,FL,Ireland,L,Ireland,50,"Python, AWS, Scala",Master,7,Healthcare,2024-12-14,2025-01-11,1790,9.2,Algorithmic Solutions -AI10307,AI Consultant,212985,EUR,181037,EX,PT,Netherlands,M,Netherlands,50,"Spark, Deep Learning, Data Visualization",PhD,10,Energy,2024-07-06,2024-07-23,1464,8.8,Predictive Systems -AI10308,AI Specialist,115588,AUD,156044,SE,PT,Australia,S,Australia,0,"PyTorch, Mathematics, NLP, Kubernetes",PhD,8,Education,2025-03-03,2025-03-25,581,7.5,DeepTech Ventures -AI10309,AI Architect,76351,USD,76351,EN,FL,Ireland,L,Ireland,50,"SQL, Python, Tableau, Scala, Statistics",PhD,1,Gaming,2024-06-13,2024-08-05,1297,7.4,Machine Intelligence Group -AI10310,Robotics Engineer,127693,CAD,159616,EX,FL,Canada,S,Canada,100,"Python, TensorFlow, Mathematics, Azure, PyTorch",Associate,16,Gaming,2025-03-14,2025-03-31,1790,7.1,TechCorp Inc -AI10311,Autonomous Systems Engineer,199789,USD,199789,EX,CT,Sweden,L,Chile,50,"Linux, Java, R",Master,10,Government,2024-12-17,2025-01-16,2344,7.5,Neural Networks Co -AI10312,AI Specialist,60987,USD,60987,EN,PT,Ireland,M,Mexico,100,"Deep Learning, Data Visualization, Scala, AWS, Linux",PhD,1,Consulting,2024-07-17,2024-08-05,2185,9.7,Autonomous Tech -AI10313,AI Product Manager,86536,USD,86536,MI,CT,Finland,M,Finland,0,"Scala, R, AWS",Associate,4,Telecommunications,2024-01-06,2024-01-27,1328,9.6,Predictive Systems -AI10314,Data Analyst,96169,EUR,81744,MI,CT,Austria,L,Austria,100,"Scala, Hadoop, Docker, Deep Learning",Bachelor,3,Government,2024-03-16,2024-05-04,1754,8.9,DataVision Ltd -AI10315,Autonomous Systems Engineer,192529,CAD,240661,EX,FT,Canada,M,Canada,50,"AWS, Kubernetes, R, Computer Vision, Statistics",PhD,16,Automotive,2024-01-15,2024-02-16,1373,6.7,DeepTech Ventures -AI10316,Data Analyst,100410,USD,100410,EX,CT,India,L,India,50,"MLOps, Data Visualization, Mathematics, Azure, Java",PhD,19,Manufacturing,2024-11-18,2025-01-04,1798,9.5,Quantum Computing Inc -AI10317,Machine Learning Researcher,52644,USD,52644,EN,PT,Sweden,M,Sweden,0,"SQL, Git, R, Deep Learning",Associate,1,Transportation,2024-04-04,2024-06-08,1491,6.1,Digital Transformation LLC -AI10318,AI Consultant,141234,USD,141234,SE,FT,United States,S,United States,0,"SQL, Kubernetes, GCP",Bachelor,5,Government,2024-11-18,2024-12-08,1135,5.6,Advanced Robotics -AI10319,AI Research Scientist,110559,USD,110559,MI,FL,Denmark,M,Spain,0,"Hadoop, Docker, MLOps, Linux, Data Visualization",Associate,4,Consulting,2024-11-07,2025-01-17,1542,9,DataVision Ltd -AI10320,AI Consultant,217485,USD,217485,EX,PT,Ireland,L,Luxembourg,0,"Scala, Statistics, Python, Mathematics",PhD,11,Government,2024-03-12,2024-04-19,1730,5.2,Predictive Systems -AI10321,Research Scientist,71252,USD,71252,EN,CT,Norway,M,Norway,0,"R, TensorFlow, PyTorch, Spark",Master,0,Retail,2024-12-09,2025-01-19,2090,6.6,DeepTech Ventures -AI10322,Data Scientist,53971,EUR,45875,EN,FL,France,S,France,0,"TensorFlow, Python, Git, Computer Vision, AWS",Master,0,Technology,2025-01-01,2025-02-12,523,7.5,Algorithmic Solutions -AI10323,Machine Learning Engineer,220263,AUD,297355,EX,CT,Australia,L,Australia,0,"NLP, Data Visualization, TensorFlow, Hadoop",Associate,11,Media,2025-03-10,2025-03-27,1532,5.9,Cloud AI Solutions -AI10324,ML Ops Engineer,277182,USD,277182,EX,FL,Norway,M,Norway,50,"Azure, Linux, NLP, GCP",Bachelor,15,Technology,2024-11-16,2025-01-10,652,7.6,Advanced Robotics -AI10325,Computer Vision Engineer,66175,USD,66175,EN,FT,Finland,M,Turkey,0,"Kubernetes, Statistics, Docker, Spark",Bachelor,1,Gaming,2024-07-09,2024-09-19,1983,5.4,DeepTech Ventures -AI10326,Principal Data Scientist,87331,USD,87331,EN,FT,Norway,L,Norway,100,"Hadoop, SQL, MLOps, Statistics, PyTorch",PhD,0,Retail,2024-07-06,2024-08-26,1817,7.5,Neural Networks Co -AI10327,ML Ops Engineer,139322,USD,139322,MI,CT,Norway,M,Norway,100,"Git, MLOps, Java, GCP",Master,4,Manufacturing,2024-10-17,2024-11-29,1376,9.3,Cloud AI Solutions -AI10328,Autonomous Systems Engineer,111301,EUR,94606,SE,FT,Germany,M,Germany,0,"TensorFlow, R, GCP",Master,5,Transportation,2024-08-09,2024-10-07,1598,6.4,TechCorp Inc -AI10329,AI Architect,132825,GBP,99619,EX,FT,United Kingdom,S,United Kingdom,0,"Statistics, R, AWS, PyTorch, TensorFlow",PhD,17,Gaming,2024-12-16,2025-02-20,708,5.1,AI Innovations -AI10330,AI Consultant,169505,AUD,228832,EX,CT,Australia,M,Australia,0,"SQL, Hadoop, PyTorch, Scala, Kubernetes",PhD,14,Media,2024-02-25,2024-04-17,790,8.8,Machine Intelligence Group -AI10331,Machine Learning Researcher,88530,AUD,119516,MI,CT,Australia,L,Australia,0,"SQL, Scala, Docker, Azure, Mathematics",Master,4,Transportation,2024-04-05,2024-05-26,1421,9.5,Cognitive Computing -AI10332,Machine Learning Researcher,127006,EUR,107955,SE,FT,Austria,S,Austria,50,"GCP, Data Visualization, PyTorch, Computer Vision, Deep Learning",Bachelor,6,Energy,2025-01-02,2025-03-03,2400,6.2,Digital Transformation LLC -AI10333,Computer Vision Engineer,244361,AUD,329887,EX,FT,Australia,M,Australia,100,"Java, Deep Learning, Hadoop",Associate,10,Automotive,2025-03-25,2025-06-03,1476,6.4,Cloud AI Solutions -AI10334,Computer Vision Engineer,74201,CAD,92751,EN,PT,Canada,L,Canada,0,"PyTorch, Python, GCP, TensorFlow, Hadoop",Associate,1,Gaming,2024-11-23,2025-01-20,661,6.4,Machine Intelligence Group -AI10335,Robotics Engineer,166881,USD,166881,SE,PT,Norway,S,United Kingdom,0,"Java, PyTorch, Tableau, TensorFlow, Deep Learning",PhD,8,Healthcare,2024-11-09,2024-11-27,2036,5.9,TechCorp Inc -AI10336,Research Scientist,28173,USD,28173,EN,CT,India,L,India,50,"Python, NLP, Hadoop, Computer Vision",Bachelor,1,Real Estate,2024-08-03,2024-09-17,1891,5.5,Autonomous Tech -AI10337,AI Software Engineer,73010,USD,73010,EN,CT,United States,L,United States,100,"Docker, Tableau, Data Visualization, Azure",PhD,1,Government,2025-02-04,2025-04-15,2119,8,Future Systems -AI10338,Computer Vision Engineer,102446,EUR,87079,MI,CT,Austria,L,Argentina,100,"NLP, MLOps, SQL",Master,3,Telecommunications,2024-10-06,2024-11-16,1801,9.8,Predictive Systems -AI10339,Principal Data Scientist,89214,USD,89214,SE,CT,Finland,S,Finland,0,"Statistics, Azure, Python, SQL",Master,8,Education,2024-12-08,2025-01-30,1097,5.2,Autonomous Tech -AI10340,NLP Engineer,203849,USD,203849,EX,FT,South Korea,L,South Korea,0,"Scala, PyTorch, Git, Linux",Master,12,Finance,2024-07-13,2024-09-04,645,6.1,Future Systems -AI10341,AI Consultant,231925,EUR,197136,EX,CT,Austria,L,Austria,100,"TensorFlow, R, Linux, Hadoop",Associate,16,Transportation,2025-04-01,2025-06-12,2122,9.3,TechCorp Inc -AI10342,Principal Data Scientist,135857,CAD,169821,SE,PT,Canada,L,Czech Republic,50,"Mathematics, Spark, Data Visualization",Bachelor,7,Automotive,2025-04-02,2025-05-23,1584,6.5,Cloud AI Solutions -AI10343,AI Research Scientist,135341,SGD,175943,SE,FL,Singapore,L,Singapore,0,"GCP, Linux, Deep Learning",Bachelor,7,Finance,2024-03-20,2024-04-07,1590,7.7,Quantum Computing Inc -AI10344,AI Architect,131968,EUR,112173,SE,CT,France,L,France,0,"Python, Computer Vision, R, Deep Learning",Master,9,Technology,2025-04-03,2025-05-27,1288,9.7,Predictive Systems -AI10345,AI Software Engineer,123858,GBP,92894,SE,FL,United Kingdom,S,Ukraine,0,"Linux, GCP, R, AWS",Bachelor,5,Media,2025-03-02,2025-04-10,2322,5.5,Cognitive Computing -AI10346,NLP Engineer,348262,CHF,313436,EX,CT,Switzerland,M,Ireland,100,"AWS, Python, Kubernetes",Associate,16,Retail,2024-06-26,2024-08-22,720,6.2,Algorithmic Solutions -AI10347,AI Product Manager,139444,USD,139444,SE,CT,Sweden,L,Sweden,50,"Python, Docker, Data Visualization, MLOps, Statistics",Associate,8,Manufacturing,2024-07-20,2024-09-20,1968,5.5,DataVision Ltd -AI10348,Machine Learning Engineer,149870,USD,149870,SE,FL,Denmark,S,Denmark,50,"SQL, Data Visualization, Tableau, Spark, Java",Master,9,Healthcare,2024-01-26,2024-03-10,763,9.5,Machine Intelligence Group -AI10349,Computer Vision Engineer,71964,USD,71964,EN,PT,Sweden,S,Sweden,50,"NLP, MLOps, Python, Scala, Docker",Master,1,Finance,2024-05-07,2024-07-08,1882,9.7,Advanced Robotics -AI10350,Robotics Engineer,27319,USD,27319,EN,FL,India,L,India,0,"Linux, Scala, Python, PyTorch",Associate,0,Automotive,2024-11-16,2025-01-10,1675,7,Algorithmic Solutions -AI10351,Deep Learning Engineer,150456,GBP,112842,EX,FT,United Kingdom,M,United Kingdom,0,"Kubernetes, R, Statistics, Tableau, MLOps",Associate,12,Telecommunications,2025-03-27,2025-04-16,1274,9,AI Innovations -AI10352,AI Specialist,305568,USD,305568,EX,FL,Norway,L,Norway,50,"SQL, PyTorch, Java, Computer Vision, Deep Learning",PhD,12,Transportation,2024-10-01,2024-11-28,1211,9.1,Digital Transformation LLC -AI10353,Data Scientist,181656,EUR,154408,EX,PT,Austria,S,Austria,100,"SQL, Spark, PyTorch",Bachelor,11,Healthcare,2024-01-25,2024-04-04,2218,5,Smart Analytics -AI10354,AI Specialist,83544,CAD,104430,MI,FT,Canada,L,Canada,0,"TensorFlow, Linux, Git, Kubernetes, Mathematics",PhD,4,Energy,2024-05-10,2024-05-27,1605,5.3,Machine Intelligence Group -AI10355,Data Scientist,85383,SGD,110998,EN,CT,Singapore,L,Singapore,0,"MLOps, Statistics, AWS",Master,1,Telecommunications,2024-05-01,2024-07-06,920,8,Cognitive Computing -AI10356,Data Analyst,118808,USD,118808,MI,FL,Israel,L,Portugal,50,"MLOps, TensorFlow, Scala",Master,3,Transportation,2024-05-31,2024-08-06,837,7.5,Smart Analytics -AI10357,Research Scientist,110158,GBP,82619,MI,CT,United Kingdom,M,Belgium,100,"Java, Computer Vision, Data Visualization, MLOps",PhD,3,Finance,2025-03-28,2025-05-05,1881,9.2,AI Innovations -AI10358,Principal Data Scientist,68395,AUD,92333,EN,FT,Australia,M,Australia,50,"AWS, Python, Docker, Deep Learning, Hadoop",Associate,0,Automotive,2024-10-18,2024-11-04,985,9.6,Digital Transformation LLC -AI10359,AI Consultant,83740,EUR,71179,MI,FL,Austria,L,Austria,0,"Hadoop, Linux, Python, Deep Learning",Associate,2,Transportation,2025-03-21,2025-05-24,655,5.2,Cloud AI Solutions -AI10360,Data Scientist,52109,USD,52109,EX,PT,India,S,India,0,"Python, Kubernetes, Tableau, TensorFlow",Bachelor,15,Education,2025-02-03,2025-04-09,1995,6.1,DeepTech Ventures -AI10361,Machine Learning Researcher,103993,AUD,140391,SE,FT,Australia,S,Sweden,100,"Tableau, Java, Python, SQL, AWS",PhD,9,Education,2024-06-14,2024-07-17,1523,9.9,Predictive Systems -AI10362,Machine Learning Researcher,183121,GBP,137341,EX,FT,United Kingdom,L,United Kingdom,50,"Linux, Kubernetes, R, AWS",Bachelor,11,Telecommunications,2024-03-05,2024-03-28,1413,8.2,Advanced Robotics -AI10363,Data Scientist,76735,USD,76735,SE,PT,South Korea,S,New Zealand,0,"NLP, Kubernetes, AWS, SQL",PhD,8,Energy,2024-08-25,2024-09-23,1994,9.6,Future Systems -AI10364,NLP Engineer,206350,GBP,154763,EX,PT,United Kingdom,L,United Kingdom,100,"Tableau, SQL, Spark, Computer Vision",PhD,18,Telecommunications,2024-06-23,2024-08-09,2468,7.2,TechCorp Inc -AI10365,Autonomous Systems Engineer,105977,GBP,79483,MI,PT,United Kingdom,M,United Kingdom,50,"NLP, Java, TensorFlow",PhD,4,Media,2024-05-20,2024-07-02,2109,5.6,Cloud AI Solutions -AI10366,NLP Engineer,216215,JPY,23783650,EX,CT,Japan,L,Japan,100,"NLP, Hadoop, Kubernetes",Bachelor,19,Retail,2024-06-28,2024-07-30,1784,8,Predictive Systems -AI10367,NLP Engineer,75477,EUR,64155,MI,CT,Germany,M,Germany,0,"NLP, Scala, Spark, PyTorch, Linux",Associate,2,Media,2024-03-21,2024-05-21,1501,6.6,Smart Analytics -AI10368,Principal Data Scientist,48875,USD,48875,SE,FT,China,M,China,100,"Linux, Java, Computer Vision, Kubernetes, Mathematics",Associate,5,Healthcare,2024-12-11,2024-12-27,1022,9.1,Neural Networks Co -AI10369,Principal Data Scientist,104599,CHF,94139,EN,PT,Switzerland,M,Switzerland,50,"Python, Git, Linux, TensorFlow, R",Bachelor,1,Consulting,2025-04-10,2025-04-25,991,9.1,Future Systems -AI10370,Machine Learning Engineer,48610,GBP,36458,EN,PT,United Kingdom,S,United Kingdom,100,"MLOps, SQL, Azure, TensorFlow, GCP",Master,0,Education,2024-09-30,2024-11-05,527,8.4,DataVision Ltd -AI10371,Autonomous Systems Engineer,63371,USD,63371,EN,FT,Ireland,M,Ireland,0,"Docker, Tableau, Data Visualization, Python, Statistics",Associate,1,Finance,2024-12-26,2025-01-24,2265,6.7,AI Innovations -AI10372,Head of AI,62938,EUR,53497,EN,FL,Germany,S,Germany,0,"Java, Hadoop, R",PhD,0,Media,2025-01-17,2025-02-08,1240,6.9,Neural Networks Co -AI10373,AI Specialist,90753,EUR,77140,MI,CT,France,M,New Zealand,100,"Linux, Hadoop, Tableau",Master,4,Manufacturing,2024-12-15,2025-01-24,2436,6.4,Future Systems -AI10374,AI Specialist,82651,USD,82651,MI,FL,South Korea,M,South Korea,100,"Python, TensorFlow, Computer Vision, AWS, Java",Master,3,Education,2024-08-29,2024-10-04,794,5.4,DataVision Ltd -AI10375,Principal Data Scientist,76895,EUR,65361,MI,FT,Netherlands,S,Netherlands,0,"Azure, NLP, Python, Computer Vision, Docker",PhD,2,Finance,2024-02-29,2024-05-08,2416,7.8,AI Innovations -AI10376,NLP Engineer,180262,CAD,225328,EX,CT,Canada,L,Canada,100,"MLOps, Spark, Data Visualization, R",Bachelor,13,Government,2025-02-08,2025-04-19,2351,9.9,TechCorp Inc -AI10377,Head of AI,113460,USD,113460,SE,CT,Finland,S,Kenya,100,"Hadoop, Linux, PyTorch",Bachelor,7,Gaming,2024-06-03,2024-08-03,1972,5.3,DataVision Ltd -AI10378,NLP Engineer,153403,USD,153403,SE,PT,Sweden,L,Sweden,50,"GCP, Azure, Mathematics",Bachelor,7,Healthcare,2024-07-23,2024-09-05,2006,5.7,Autonomous Tech -AI10379,Data Engineer,84780,CAD,105975,MI,PT,Canada,S,Canada,100,"Kubernetes, Docker, Tableau, Azure, Git",PhD,4,Education,2024-08-25,2024-10-21,1131,5.2,AI Innovations -AI10380,AI Consultant,157851,JPY,17363610,EX,CT,Japan,M,Belgium,100,"Scala, TensorFlow, Kubernetes, SQL, PyTorch",Bachelor,12,Telecommunications,2024-12-25,2025-01-19,1496,6,DeepTech Ventures -AI10381,ML Ops Engineer,161328,JPY,17746080,EX,PT,Japan,S,Japan,50,"R, Scala, Mathematics, Deep Learning",Associate,12,Automotive,2024-01-01,2024-03-12,1229,7.1,Machine Intelligence Group -AI10382,AI Research Scientist,180015,CAD,225019,EX,FL,Canada,S,Canada,0,"Deep Learning, Statistics, Scala, Azure",Associate,15,Government,2024-06-11,2024-07-21,856,10,Cloud AI Solutions -AI10383,Machine Learning Researcher,169051,USD,169051,SE,PT,United States,L,United States,50,"R, Java, Deep Learning",PhD,6,Retail,2024-11-02,2025-01-01,2205,7.5,Cloud AI Solutions -AI10384,Robotics Engineer,47369,USD,47369,SE,PT,India,L,India,50,"Linux, Docker, AWS, R",Bachelor,7,Energy,2024-09-12,2024-09-30,2206,9.3,Future Systems -AI10385,Computer Vision Engineer,59893,EUR,50909,EN,FT,Austria,L,Luxembourg,50,"Docker, TensorFlow, NLP, GCP",Bachelor,1,Gaming,2025-01-17,2025-03-08,630,7.8,Cognitive Computing -AI10386,AI Research Scientist,77568,JPY,8532480,EN,FT,Japan,M,Japan,0,"Linux, Python, Deep Learning, TensorFlow, Git",PhD,0,Energy,2024-03-12,2024-05-03,2286,7.8,Advanced Robotics -AI10387,Robotics Engineer,65205,USD,65205,SE,PT,China,M,Kenya,100,"PyTorch, TensorFlow, Deep Learning",PhD,9,Finance,2024-03-10,2024-04-06,766,9.5,DataVision Ltd -AI10388,Robotics Engineer,123050,CHF,110745,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Hadoop, MLOps, SQL",Master,0,Transportation,2024-02-18,2024-03-24,961,9.9,Algorithmic Solutions -AI10389,AI Specialist,59751,USD,59751,EN,FL,Finland,M,Finland,50,"Kubernetes, Linux, GCP, Spark",PhD,0,Gaming,2024-01-08,2024-01-27,2237,7.2,TechCorp Inc -AI10390,AI Product Manager,158205,USD,158205,EX,PT,South Korea,S,South Korea,100,"Kubernetes, Spark, Python, Git, AWS",Master,12,Finance,2024-05-12,2024-06-04,1898,5.2,Future Systems -AI10391,Data Scientist,104978,USD,104978,MI,CT,Ireland,M,Netherlands,50,"AWS, Tableau, Java, Azure, Python",Associate,4,Technology,2024-02-14,2024-03-25,1561,5.3,Predictive Systems -AI10392,AI Product Manager,51383,JPY,5652130,EN,FL,Japan,S,Japan,50,"SQL, Kubernetes, Deep Learning, NLP",PhD,1,Gaming,2024-07-26,2024-08-17,1313,5.5,Quantum Computing Inc -AI10393,Head of AI,133639,CHF,120275,MI,FT,Switzerland,L,Switzerland,0,"Linux, AWS, Deep Learning",PhD,2,Education,2025-01-28,2025-03-05,1763,6.2,Predictive Systems -AI10394,NLP Engineer,70113,JPY,7712430,EN,FL,Japan,M,Japan,0,"Deep Learning, GCP, Scala",PhD,0,Gaming,2024-02-20,2024-04-30,2186,6.7,Quantum Computing Inc -AI10395,AI Product Manager,104072,EUR,88461,MI,FL,Germany,M,Germany,50,"Deep Learning, Python, TensorFlow, Mathematics, PyTorch",Bachelor,4,Retail,2024-05-30,2024-08-08,1966,9.8,TechCorp Inc -AI10396,AI Specialist,71642,AUD,96717,EN,PT,Australia,S,Australia,0,"SQL, Scala, Computer Vision, PyTorch, TensorFlow",Bachelor,0,Gaming,2024-10-08,2024-10-30,1976,6.4,DeepTech Ventures -AI10397,Deep Learning Engineer,140288,USD,140288,SE,FT,Sweden,L,Sweden,50,"Python, Mathematics, TensorFlow",Bachelor,8,Government,2024-06-28,2024-09-07,1002,7,Machine Intelligence Group -AI10398,Data Scientist,134675,EUR,114474,SE,CT,Netherlands,S,Argentina,100,"Python, Git, Statistics",Bachelor,8,Technology,2024-03-11,2024-03-27,1466,7.1,Neural Networks Co -AI10399,AI Consultant,22938,USD,22938,EN,FT,India,M,India,100,"GCP, Tableau, Azure, Mathematics, Spark",Associate,0,Education,2024-05-07,2024-06-09,1943,8.4,Cloud AI Solutions -AI10400,Deep Learning Engineer,141684,EUR,120431,SE,FT,France,L,France,0,"AWS, R, PyTorch, Docker, Tableau",Master,7,Retail,2024-05-11,2024-07-20,2266,5.2,AI Innovations -AI10401,Principal Data Scientist,83033,USD,83033,SE,FL,South Korea,S,South Korea,100,"NLP, Python, TensorFlow, Hadoop, Spark",Bachelor,8,Education,2024-10-28,2024-12-03,2458,6.5,Future Systems -AI10402,Data Engineer,222353,EUR,189000,EX,FT,Netherlands,M,Netherlands,50,"R, Tableau, NLP, MLOps, Docker",Bachelor,18,Telecommunications,2025-01-26,2025-04-09,2350,8.2,TechCorp Inc -AI10403,AI Specialist,89362,EUR,75958,MI,PT,Netherlands,L,Netherlands,0,"TensorFlow, PyTorch, Deep Learning",Master,4,Retail,2024-01-19,2024-03-03,906,9.7,AI Innovations -AI10404,AI Specialist,199765,USD,199765,EX,FL,South Korea,M,South Korea,100,"Python, Git, Docker, GCP, Tableau",Master,19,Real Estate,2024-09-30,2024-11-01,2156,8.1,Future Systems -AI10405,Head of AI,102081,AUD,137809,SE,PT,Australia,M,Australia,50,"Mathematics, Scala, R, Kubernetes",Master,9,Retail,2024-07-07,2024-08-26,2167,8.5,Cloud AI Solutions -AI10406,AI Research Scientist,221776,USD,221776,EX,FL,Norway,S,Norway,0,"SQL, Python, NLP",Bachelor,10,Finance,2024-03-30,2024-05-01,801,5.5,Cloud AI Solutions -AI10407,Deep Learning Engineer,95606,USD,95606,EX,CT,China,M,China,0,"Deep Learning, Data Visualization, Python, GCP, Statistics",Associate,14,Retail,2025-04-12,2025-05-04,609,8.6,Advanced Robotics -AI10408,Data Scientist,102808,EUR,87387,MI,PT,Austria,M,Austria,100,"SQL, Linux, NLP, Scala",PhD,4,Real Estate,2024-07-06,2024-08-14,1703,5.2,Digital Transformation LLC -AI10409,ML Ops Engineer,104905,USD,104905,MI,CT,Norway,S,Norway,50,"Spark, AWS, Statistics",Master,4,Healthcare,2024-08-18,2024-10-02,1678,7.7,DataVision Ltd -AI10410,Computer Vision Engineer,133598,CHF,120238,MI,FT,Switzerland,S,Switzerland,0,"Spark, Kubernetes, Data Visualization",Bachelor,3,Energy,2024-10-11,2024-12-05,2492,6.9,Machine Intelligence Group -AI10411,Autonomous Systems Engineer,282463,JPY,31070930,EX,CT,Japan,L,Japan,0,"MLOps, Java, Python",Associate,19,Education,2024-12-22,2025-01-08,1949,9.9,Cloud AI Solutions -AI10412,Data Engineer,146803,EUR,124783,EX,PT,Germany,M,Germany,100,"SQL, Git, Computer Vision, AWS",Master,13,Finance,2025-02-09,2025-04-21,2291,6.2,Predictive Systems -AI10413,AI Product Manager,226731,USD,226731,EX,FT,Ireland,L,Ireland,0,"Linux, Computer Vision, R, Python",Associate,17,Consulting,2024-05-01,2024-06-25,2395,10,Predictive Systems -AI10414,Data Scientist,85796,EUR,72927,MI,FT,France,L,France,0,"Python, TensorFlow, Mathematics",Associate,3,Transportation,2024-06-16,2024-08-01,2131,9.4,Machine Intelligence Group -AI10415,Head of AI,67219,AUD,90746,EN,FT,Australia,L,Australia,50,"MLOps, Deep Learning, TensorFlow, Python, Computer Vision",PhD,0,Telecommunications,2025-03-29,2025-05-16,2183,5.8,Digital Transformation LLC -AI10416,Deep Learning Engineer,19495,USD,19495,EN,CT,India,M,India,50,"Azure, Python, Linux",Associate,1,Manufacturing,2024-11-20,2025-01-18,1129,6.5,Predictive Systems -AI10417,Machine Learning Engineer,143665,USD,143665,SE,CT,Sweden,M,Sweden,0,"Git, Deep Learning, MLOps, PyTorch",Bachelor,8,Manufacturing,2024-08-21,2024-09-04,951,6.9,DeepTech Ventures -AI10418,Computer Vision Engineer,54072,AUD,72997,EN,PT,Australia,S,Germany,100,"SQL, Tableau, PyTorch, AWS, MLOps",Master,0,Media,2024-09-01,2024-11-02,1394,7.4,DataVision Ltd -AI10419,Data Scientist,93668,EUR,79618,SE,FT,Austria,S,Austria,100,"Mathematics, Git, MLOps, Kubernetes",Bachelor,6,Finance,2024-04-26,2024-05-11,2402,5,Predictive Systems -AI10420,ML Ops Engineer,238158,USD,238158,EX,PT,Norway,L,Norway,50,"Git, SQL, Python, GCP",Master,19,Real Estate,2024-06-15,2024-07-29,1932,8.7,Quantum Computing Inc -AI10421,Computer Vision Engineer,71023,GBP,53267,EN,CT,United Kingdom,S,South Africa,100,"Hadoop, Git, R, Java",Master,1,Real Estate,2024-06-14,2024-07-12,1434,9.5,Digital Transformation LLC -AI10422,AI Specialist,86841,EUR,73815,MI,CT,Germany,L,Australia,100,"PyTorch, TensorFlow, MLOps",PhD,2,Media,2024-01-19,2024-03-24,806,9.9,Cognitive Computing -AI10423,ML Ops Engineer,154195,CAD,192744,EX,PT,Canada,S,Belgium,50,"NLP, PyTorch, R, Java",Master,15,Consulting,2024-10-09,2024-10-31,695,5.8,Future Systems -AI10424,Robotics Engineer,92933,SGD,120813,MI,PT,Singapore,M,Singapore,100,"Docker, Kubernetes, Scala",PhD,3,Education,2024-06-03,2024-07-30,1876,7.2,DataVision Ltd -AI10425,Deep Learning Engineer,122175,SGD,158828,SE,PT,Singapore,S,Nigeria,50,"NLP, Scala, Statistics, Deep Learning",Master,8,Technology,2024-05-18,2024-07-22,2133,5.2,Smart Analytics -AI10426,AI Software Engineer,123306,EUR,104810,EX,CT,France,S,France,100,"Python, TensorFlow, GCP",PhD,15,Education,2024-11-15,2025-01-06,1729,6.4,AI Innovations -AI10427,AI Research Scientist,103528,EUR,87999,MI,PT,Austria,L,Austria,100,"GCP, AWS, MLOps",Bachelor,4,Government,2024-08-05,2024-09-24,926,5.8,DataVision Ltd -AI10428,AI Specialist,98123,EUR,83405,SE,FT,Netherlands,S,Netherlands,0,"PyTorch, NLP, Docker, AWS",Associate,6,Telecommunications,2024-08-22,2024-10-12,1172,6.8,Predictive Systems -AI10429,AI Research Scientist,75392,USD,75392,EN,FL,South Korea,L,South Korea,0,"Python, Java, Azure, Kubernetes, Git",Bachelor,1,Finance,2024-02-08,2024-03-21,1380,8.2,Future Systems -AI10430,AI Architect,47588,CAD,59485,EN,FL,Canada,S,Canada,50,"Kubernetes, Git, Tableau",PhD,0,Real Estate,2024-08-23,2024-10-20,2296,6.1,Future Systems -AI10431,Data Engineer,64925,JPY,7141750,EN,CT,Japan,S,Estonia,50,"Scala, Mathematics, SQL, Azure, Data Visualization",Bachelor,1,Manufacturing,2024-10-13,2024-12-11,1706,8.8,DeepTech Ventures -AI10432,AI Consultant,59060,USD,59060,MI,CT,China,L,China,0,"Computer Vision, Java, PyTorch",Master,3,Government,2024-03-23,2024-05-12,2496,6.8,Quantum Computing Inc -AI10433,Machine Learning Researcher,206097,USD,206097,SE,CT,Denmark,L,Denmark,100,"Python, Data Visualization, Spark",Master,8,Energy,2024-10-08,2024-11-26,2416,8.5,AI Innovations -AI10434,Data Engineer,61098,USD,61098,EN,FL,South Korea,M,Indonesia,0,"Statistics, PyTorch, MLOps",Master,1,Telecommunications,2024-05-20,2024-06-27,1175,8,Quantum Computing Inc -AI10435,Data Scientist,63567,USD,63567,EN,CT,Ireland,M,Ireland,0,"AWS, R, Data Visualization",Bachelor,0,Gaming,2024-07-12,2024-07-31,2154,9.2,Quantum Computing Inc -AI10436,Machine Learning Engineer,247728,CHF,222955,SE,FL,Switzerland,L,Indonesia,0,"Hadoop, Kubernetes, NLP",Associate,9,Telecommunications,2024-08-22,2024-09-21,1912,5.7,TechCorp Inc -AI10437,Research Scientist,125206,GBP,93905,SE,CT,United Kingdom,M,Indonesia,50,"Deep Learning, Tableau, Kubernetes, Git",Master,7,Media,2024-09-26,2024-10-16,1042,8.2,Digital Transformation LLC -AI10438,Robotics Engineer,72094,EUR,61280,EN,PT,France,M,France,100,"Linux, Java, Mathematics, Computer Vision, PyTorch",Associate,1,Healthcare,2025-03-31,2025-05-23,2433,5.9,TechCorp Inc -AI10439,AI Research Scientist,85942,CAD,107428,EN,PT,Canada,L,Canada,100,"Linux, Kubernetes, Hadoop, Statistics",Associate,0,Consulting,2024-05-09,2024-06-25,2072,7.1,TechCorp Inc -AI10440,ML Ops Engineer,191299,USD,191299,EX,CT,Ireland,M,Spain,100,"Azure, SQL, PyTorch",Bachelor,17,Telecommunications,2024-05-14,2024-06-24,1221,5.6,Autonomous Tech -AI10441,Computer Vision Engineer,145582,USD,145582,SE,CT,Israel,L,Israel,50,"Deep Learning, Kubernetes, R",Associate,5,Technology,2024-08-24,2024-10-21,1743,7.9,AI Innovations -AI10442,AI Architect,91181,AUD,123094,MI,PT,Australia,S,Australia,100,"Git, Docker, SQL, Kubernetes",Master,4,Media,2024-12-18,2025-02-24,1535,5.8,Smart Analytics -AI10443,NLP Engineer,100215,USD,100215,EX,CT,China,S,Indonesia,0,"Docker, R, Java",Bachelor,11,Manufacturing,2024-03-11,2024-05-09,2088,9.3,Quantum Computing Inc -AI10444,AI Consultant,47259,USD,47259,EX,FT,India,S,India,100,"TensorFlow, Spark, NLP",PhD,14,Energy,2024-11-15,2024-12-28,1642,6.1,Quantum Computing Inc -AI10445,AI Architect,244995,USD,244995,EX,CT,Norway,M,Norway,0,"TensorFlow, Docker, R",PhD,14,Education,2024-09-19,2024-11-18,1936,9.3,TechCorp Inc -AI10446,Data Analyst,131732,AUD,177838,SE,CT,Australia,L,Australia,50,"TensorFlow, Java, Deep Learning, Linux",Associate,7,Government,2024-06-16,2024-08-09,943,6.1,Quantum Computing Inc -AI10447,Autonomous Systems Engineer,142453,SGD,185189,SE,CT,Singapore,M,Singapore,100,"Mathematics, Docker, Python, Scala, Computer Vision",Master,8,Transportation,2024-12-23,2025-02-02,846,6.6,DataVision Ltd -AI10448,Data Scientist,114905,EUR,97669,MI,FL,France,L,France,100,"Python, GCP, Spark",Bachelor,4,Real Estate,2024-03-30,2024-05-07,972,5.5,Smart Analytics -AI10449,Machine Learning Engineer,94309,USD,94309,MI,CT,Sweden,L,Sweden,0,"Python, Git, TensorFlow, Docker, PyTorch",Associate,2,Retail,2024-09-24,2024-12-03,1036,7.7,DeepTech Ventures -AI10450,AI Consultant,269435,CHF,242492,EX,PT,Switzerland,M,Switzerland,100,"MLOps, Java, Azure",Bachelor,18,Manufacturing,2025-02-26,2025-04-08,1393,9.2,Advanced Robotics -AI10451,Machine Learning Engineer,64365,EUR,54710,EN,FL,Germany,S,Germany,0,"Spark, GCP, Mathematics",Associate,1,Gaming,2024-04-26,2024-07-01,1828,10,TechCorp Inc -AI10452,AI Specialist,105348,USD,105348,EN,PT,Norway,L,Norway,100,"NLP, Python, Kubernetes, AWS",Master,0,Technology,2024-12-18,2025-01-13,1099,9.1,Cloud AI Solutions -AI10453,Machine Learning Engineer,157110,GBP,117833,SE,FL,United Kingdom,L,United Kingdom,50,"Scala, Deep Learning, MLOps, Data Visualization",Bachelor,6,Technology,2024-03-26,2024-05-22,1108,9.9,Autonomous Tech -AI10454,Computer Vision Engineer,312583,USD,312583,EX,FL,Denmark,L,United States,0,"SQL, Deep Learning, NLP",Master,19,Manufacturing,2024-08-16,2024-09-16,536,8.6,Digital Transformation LLC -AI10455,Autonomous Systems Engineer,74526,USD,74526,EX,FT,China,M,Canada,0,"TensorFlow, R, Data Visualization",Master,12,Education,2024-07-22,2024-09-24,1101,10,Cognitive Computing -AI10456,Robotics Engineer,172413,JPY,18965430,SE,FL,Japan,L,Japan,100,"Python, Docker, TensorFlow, SQL, AWS",Associate,5,Media,2025-03-02,2025-03-30,1199,5.3,TechCorp Inc -AI10457,Machine Learning Researcher,163535,EUR,139005,SE,PT,Austria,L,Austria,50,"Statistics, Spark, Tableau",Master,8,Government,2024-08-19,2024-10-10,1823,9,TechCorp Inc -AI10458,Data Analyst,132082,USD,132082,EX,FL,South Korea,M,South Korea,50,"SQL, NLP, Azure, Scala, Python",Master,17,Media,2024-06-13,2024-08-15,1298,9.2,Digital Transformation LLC -AI10459,Research Scientist,261749,USD,261749,EX,CT,Norway,S,Finland,100,"Computer Vision, Statistics, PyTorch, Java",PhD,12,Government,2024-02-19,2024-03-06,1489,8.4,Cognitive Computing -AI10460,Head of AI,68534,USD,68534,SE,FL,China,M,China,50,"Deep Learning, GCP, Computer Vision",Master,8,Media,2024-03-08,2024-03-26,1951,6.7,Machine Intelligence Group -AI10461,AI Consultant,95396,EUR,81087,MI,CT,Germany,M,Germany,100,"Linux, SQL, Kubernetes, GCP",Bachelor,4,Retail,2024-06-11,2024-07-03,1007,7.8,Predictive Systems -AI10462,Data Scientist,74131,AUD,100077,EN,CT,Australia,M,Australia,50,"Spark, Hadoop, Tableau, Mathematics",Master,1,Transportation,2024-01-15,2024-03-05,951,8.9,Neural Networks Co -AI10463,Computer Vision Engineer,115232,USD,115232,MI,CT,Denmark,M,Denmark,50,"Tableau, NLP, Scala, Deep Learning, PyTorch",Master,3,Technology,2024-12-25,2025-02-25,667,6.9,Digital Transformation LLC -AI10464,Machine Learning Engineer,58227,SGD,75695,EN,FL,Singapore,S,Singapore,100,"Kubernetes, Deep Learning, NLP, TensorFlow",Bachelor,1,Healthcare,2024-01-03,2024-01-19,2113,9.1,Machine Intelligence Group -AI10465,Data Analyst,188430,CHF,169587,SE,FT,Switzerland,L,Switzerland,100,"Python, Scala, Hadoop, Docker, TensorFlow",Associate,6,Technology,2025-03-01,2025-03-25,955,6.4,Quantum Computing Inc -AI10466,Head of AI,72415,SGD,94140,EN,PT,Singapore,M,Singapore,0,"Git, Scala, Linux, SQL",Associate,0,Retail,2024-05-12,2024-06-18,2310,7.2,DeepTech Ventures -AI10467,AI Consultant,49041,GBP,36781,EN,FT,United Kingdom,S,United Kingdom,100,"Docker, Spark, Deep Learning, TensorFlow, PyTorch",Master,1,Manufacturing,2024-10-28,2024-11-18,660,8.4,Neural Networks Co -AI10468,Research Scientist,78075,USD,78075,MI,FL,Finland,M,Finland,0,"Statistics, Hadoop, Tableau, Kubernetes",Master,3,Automotive,2025-03-27,2025-05-28,657,9,Neural Networks Co -AI10469,Autonomous Systems Engineer,96725,USD,96725,EN,PT,Denmark,L,Denmark,100,"Git, PyTorch, Scala, Azure",Associate,1,Technology,2025-01-26,2025-02-20,1553,5.6,Cloud AI Solutions -AI10470,AI Architect,116451,CAD,145564,MI,FL,Canada,L,Canada,0,"Kubernetes, Azure, SQL, Java, Spark",Bachelor,3,Automotive,2024-06-17,2024-08-24,883,9.6,Autonomous Tech -AI10471,AI Research Scientist,96459,SGD,125397,EN,FT,Singapore,L,Austria,100,"Data Visualization, Azure, Mathematics, PyTorch",PhD,0,Manufacturing,2024-03-26,2024-06-04,1160,7.4,DataVision Ltd -AI10472,AI Research Scientist,254343,CHF,228909,EX,FT,Switzerland,M,Switzerland,100,"Mathematics, Kubernetes, Hadoop, Statistics",Associate,18,Real Estate,2024-02-28,2024-04-15,1326,8.1,Autonomous Tech -AI10473,Autonomous Systems Engineer,131234,EUR,111549,SE,FL,Germany,S,Germany,100,"Java, Spark, Statistics, Mathematics",PhD,6,Manufacturing,2024-08-13,2024-09-24,701,9.5,Future Systems -AI10474,Autonomous Systems Engineer,53585,USD,53585,EN,CT,South Korea,S,South Korea,100,"Tableau, NLP, MLOps, Data Visualization",PhD,0,Media,2025-01-01,2025-03-09,1610,6.6,Future Systems -AI10475,AI Consultant,156371,USD,156371,SE,PT,Denmark,M,Denmark,0,"NLP, Hadoop, GCP, Azure, Java",Bachelor,8,Telecommunications,2025-01-21,2025-02-24,686,6.6,DataVision Ltd -AI10476,NLP Engineer,166022,GBP,124517,EX,FL,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, Docker",PhD,19,Consulting,2024-10-31,2024-12-31,2259,9.8,Predictive Systems -AI10477,AI Software Engineer,87583,SGD,113858,MI,FL,Singapore,M,Belgium,100,"Data Visualization, Docker, Kubernetes, Scala",Bachelor,2,Manufacturing,2024-08-12,2024-09-07,1779,9.8,Predictive Systems -AI10478,Robotics Engineer,131350,USD,131350,SE,FL,Ireland,M,Ireland,100,"NLP, Java, Kubernetes",Bachelor,7,Education,2024-10-07,2024-11-16,1324,5.1,Algorithmic Solutions -AI10479,Robotics Engineer,25847,USD,25847,EN,FL,China,M,China,100,"R, TensorFlow, Docker, Data Visualization",Master,1,Manufacturing,2024-05-13,2024-07-19,567,7.3,Smart Analytics -AI10480,Data Scientist,70279,USD,70279,EN,CT,Sweden,M,Sweden,0,"Docker, Kubernetes, AWS, Tableau, Git",Master,0,Transportation,2025-04-16,2025-05-18,2431,5.9,Quantum Computing Inc -AI10481,Principal Data Scientist,83967,USD,83967,MI,FL,Sweden,L,Sweden,50,"Data Visualization, Git, Scala",Associate,4,Consulting,2024-06-26,2024-07-30,533,5.8,Advanced Robotics -AI10482,Data Analyst,117772,USD,117772,SE,FT,Israel,S,Israel,50,"AWS, GCP, Statistics, Java",PhD,5,Government,2025-04-30,2025-07-02,1085,7,Predictive Systems -AI10483,Data Engineer,77901,USD,77901,MI,PT,Finland,S,Finland,100,"Scala, Spark, AWS, PyTorch, Linux",PhD,4,Government,2024-02-16,2024-04-19,2164,9.6,Digital Transformation LLC -AI10484,Robotics Engineer,251299,USD,251299,EX,FT,Israel,L,Israel,100,"Kubernetes, Scala, GCP",PhD,17,Retail,2024-02-17,2024-03-10,2304,9.5,Quantum Computing Inc -AI10485,ML Ops Engineer,56632,CAD,70790,EN,FL,Canada,S,Canada,0,"Computer Vision, AWS, NLP",Master,1,Media,2025-04-10,2025-06-08,1669,8.2,Cloud AI Solutions -AI10486,Data Scientist,89248,EUR,75861,SE,FT,Austria,S,Austria,0,"PyTorch, MLOps, Python, R",Master,6,Technology,2025-04-03,2025-06-01,819,6.8,Machine Intelligence Group -AI10487,ML Ops Engineer,159129,CHF,143216,SE,FL,Switzerland,S,Switzerland,0,"TensorFlow, SQL, R",Associate,8,Government,2024-09-09,2024-10-10,2320,5.5,Cognitive Computing -AI10488,Deep Learning Engineer,121563,USD,121563,SE,CT,Finland,S,Norway,100,"Python, GCP, Git, TensorFlow, Statistics",Associate,9,Government,2024-11-11,2024-12-16,1300,5.6,Future Systems -AI10489,Computer Vision Engineer,60861,EUR,51732,EN,CT,Austria,L,Austria,0,"Azure, PyTorch, Mathematics, Python",Bachelor,0,Telecommunications,2024-03-13,2024-05-24,1422,8.3,DeepTech Ventures -AI10490,Research Scientist,118967,CHF,107070,MI,CT,Switzerland,L,Canada,50,"Java, MLOps, Python, R",PhD,4,Technology,2024-08-31,2024-10-28,1605,9.3,DataVision Ltd -AI10491,AI Research Scientist,233392,EUR,198383,EX,FT,Germany,L,Germany,100,"Statistics, Java, PyTorch, Deep Learning",Bachelor,16,Government,2024-02-29,2024-05-07,2030,7.7,AI Innovations -AI10492,Data Analyst,132254,EUR,112416,SE,FL,Netherlands,S,Netherlands,0,"Data Visualization, Computer Vision, Tableau",Master,9,Education,2024-06-18,2024-07-04,2009,7.7,DataVision Ltd -AI10493,Data Analyst,64661,USD,64661,EN,FL,Finland,L,Finland,100,"Statistics, TensorFlow, Hadoop, GCP, Deep Learning",PhD,1,Finance,2024-09-08,2024-10-18,621,8.1,Smart Analytics -AI10494,Head of AI,113314,USD,113314,MI,CT,United States,M,Australia,50,"Python, SQL, Linux, GCP, Scala",Master,4,Media,2024-06-26,2024-08-09,936,9.4,AI Innovations -AI10495,Autonomous Systems Engineer,114505,SGD,148857,SE,CT,Singapore,S,Singapore,100,"Java, R, GCP, Mathematics, Hadoop",Associate,8,Media,2024-03-25,2024-04-16,1103,9.3,Smart Analytics -AI10496,AI Software Engineer,176423,EUR,149960,EX,CT,Austria,L,Ghana,100,"PyTorch, Hadoop, Linux, Azure, Scala",PhD,17,Government,2024-11-18,2024-12-08,2133,6.2,Smart Analytics -AI10497,Deep Learning Engineer,47416,EUR,40304,EN,PT,Austria,S,Austria,0,"Linux, AWS, Computer Vision",Associate,0,Telecommunications,2024-10-10,2024-12-09,1205,5.9,DeepTech Ventures -AI10498,Data Scientist,273664,GBP,205248,EX,FL,United Kingdom,L,United Kingdom,100,"Azure, Python, GCP",Bachelor,18,Technology,2024-08-21,2024-10-14,1518,6.8,Predictive Systems -AI10499,AI Product Manager,158106,SGD,205538,SE,PT,Singapore,L,Singapore,100,"Python, Kubernetes, Computer Vision, Hadoop",Bachelor,9,Telecommunications,2024-06-16,2024-07-05,576,8.1,Autonomous Tech -AI10500,Deep Learning Engineer,134252,EUR,114114,SE,CT,Austria,M,Austria,50,"Azure, Scala, AWS",Associate,7,Education,2025-04-01,2025-04-28,821,9.3,Smart Analytics -AI10501,Research Scientist,39883,USD,39883,EN,CT,South Korea,S,Australia,100,"Tableau, PyTorch, AWS, Statistics, Git",Bachelor,0,Real Estate,2024-09-18,2024-11-19,2465,6.2,Quantum Computing Inc -AI10502,AI Architect,86586,USD,86586,MI,FL,Ireland,S,Ireland,100,"SQL, Scala, Statistics, Kubernetes, GCP",Bachelor,4,Transportation,2024-11-26,2024-12-16,1516,8.2,Cognitive Computing -AI10503,NLP Engineer,158006,JPY,17380660,SE,PT,Japan,L,Switzerland,50,"Kubernetes, Spark, R, Deep Learning",Bachelor,9,Finance,2024-09-02,2024-11-12,2181,9.5,Quantum Computing Inc -AI10504,Research Scientist,160380,USD,160380,EX,FL,Israel,L,Israel,50,"Python, Azure, NLP, TensorFlow, AWS",Master,18,Government,2024-10-19,2024-11-29,2304,5.4,Advanced Robotics -AI10505,NLP Engineer,178755,USD,178755,SE,CT,Norway,L,Norway,100,"Hadoop, Spark, Computer Vision",PhD,6,Energy,2025-01-29,2025-02-20,1020,6.4,Predictive Systems -AI10506,Principal Data Scientist,99536,USD,99536,MI,CT,United States,M,United States,100,"Linux, PyTorch, SQL, Statistics, MLOps",Bachelor,2,Manufacturing,2025-04-07,2025-06-13,1184,6.2,Predictive Systems -AI10507,AI Research Scientist,124279,AUD,167777,MI,FT,Australia,L,Australia,50,"Java, PyTorch, R, Tableau",Bachelor,2,Retail,2025-04-27,2025-06-06,862,5.8,DeepTech Ventures -AI10508,Machine Learning Engineer,64888,EUR,55155,EN,FL,Germany,L,Germany,50,"Spark, Linux, PyTorch, Java",Associate,1,Technology,2025-02-11,2025-03-06,1392,5.1,Cloud AI Solutions -AI10509,AI Product Manager,102390,EUR,87032,SE,FL,Germany,S,Germany,0,"GCP, Deep Learning, R, TensorFlow",PhD,9,Gaming,2024-06-27,2024-08-12,1601,5.7,Future Systems -AI10510,Research Scientist,43363,USD,43363,MI,PT,China,L,China,100,"Kubernetes, Python, Data Visualization, Computer Vision, Azure",Master,3,Government,2024-05-10,2024-07-19,1250,9.1,Algorithmic Solutions -AI10511,Machine Learning Engineer,82118,AUD,110859,EN,CT,Australia,L,Australia,50,"Deep Learning, Mathematics, Data Visualization",PhD,0,Transportation,2024-05-22,2024-07-11,2347,9,Machine Intelligence Group -AI10512,Deep Learning Engineer,138768,USD,138768,SE,FL,Ireland,L,Ireland,50,"Hadoop, Kubernetes, Data Visualization, NLP, Spark",Associate,7,Media,2024-08-09,2024-09-26,2439,6.6,Neural Networks Co -AI10513,Computer Vision Engineer,48876,AUD,65983,EN,FL,Australia,S,Australia,50,"NLP, GCP, Tableau, Azure, Docker",Master,1,Gaming,2024-06-01,2024-07-29,1711,7.9,DataVision Ltd -AI10514,Machine Learning Researcher,72281,USD,72281,EN,FT,Ireland,S,Ireland,0,"SQL, Hadoop, Data Visualization",Bachelor,0,Consulting,2024-09-22,2024-10-09,1577,8.4,Neural Networks Co -AI10515,AI Research Scientist,136114,AUD,183754,SE,PT,Australia,S,Australia,100,"Python, Scala, Java, Deep Learning",Bachelor,8,Consulting,2024-01-04,2024-02-22,901,5.5,Predictive Systems -AI10516,Data Analyst,47355,USD,47355,SE,FL,India,S,Israel,100,"Tableau, Spark, AWS, Scala, SQL",Bachelor,6,Gaming,2024-11-09,2024-11-24,1396,6.4,Autonomous Tech -AI10517,AI Architect,116538,USD,116538,MI,FT,Israel,L,Israel,0,"Statistics, Spark, Mathematics",Bachelor,2,Finance,2024-09-06,2024-10-24,1791,9.1,Machine Intelligence Group -AI10518,Data Engineer,101215,USD,101215,MI,CT,Ireland,M,Ireland,0,"Git, Python, NLP, Statistics, Kubernetes",PhD,4,Energy,2024-06-25,2024-08-08,1775,9.3,Smart Analytics -AI10519,Computer Vision Engineer,120939,CHF,108845,MI,CT,Switzerland,L,Switzerland,0,"Git, Java, SQL, Azure",Associate,3,Media,2024-12-16,2025-02-17,1891,8,Smart Analytics -AI10520,AI Consultant,53345,JPY,5867950,EN,PT,Japan,S,Netherlands,50,"Python, TensorFlow, Kubernetes, Linux, MLOps",Master,1,Telecommunications,2024-05-28,2024-07-13,605,7.9,Quantum Computing Inc -AI10521,Machine Learning Researcher,49297,USD,49297,EN,FT,Israel,M,Israel,0,"Kubernetes, PyTorch, GCP",Master,0,Manufacturing,2024-06-15,2024-07-19,2343,8.2,Predictive Systems -AI10522,Data Engineer,85313,SGD,110907,EN,FL,Singapore,M,Singapore,100,"SQL, PyTorch, NLP, Hadoop, MLOps",PhD,1,Gaming,2024-02-03,2024-02-17,960,6.9,Future Systems -AI10523,Computer Vision Engineer,165378,CAD,206723,EX,FT,Canada,S,Canada,50,"Java, Git, Tableau, GCP",Bachelor,18,Real Estate,2024-01-26,2024-03-25,1637,9.5,Algorithmic Solutions -AI10524,AI Product Manager,78358,USD,78358,EN,PT,Israel,L,Israel,0,"Java, SQL, Computer Vision, R",Bachelor,0,Government,2024-01-24,2024-03-07,723,6.1,DeepTech Ventures -AI10525,NLP Engineer,23160,USD,23160,EN,FL,India,S,India,100,"Docker, Git, Statistics, R",Bachelor,1,Manufacturing,2024-05-09,2024-06-14,936,9.7,Quantum Computing Inc -AI10526,Research Scientist,85575,USD,85575,MI,PT,Israel,M,Israel,0,"Python, Kubernetes, Linux, NLP, PyTorch",Bachelor,2,Education,2025-03-28,2025-06-04,2322,7.1,TechCorp Inc -AI10527,AI Specialist,188461,JPY,20730710,EX,FL,Japan,S,Japan,50,"Scala, Spark, Tableau, MLOps",Master,18,Consulting,2025-01-19,2025-03-26,988,5.7,Digital Transformation LLC -AI10528,Autonomous Systems Engineer,16621,USD,16621,EN,CT,India,S,India,0,"Kubernetes, Python, AWS",Master,0,Manufacturing,2025-02-24,2025-04-29,1724,7.9,Advanced Robotics -AI10529,Machine Learning Researcher,154393,CAD,192991,SE,FL,Canada,L,Canada,100,"Kubernetes, Python, TensorFlow, Java",Master,7,Retail,2024-10-23,2024-11-26,2475,6.9,Quantum Computing Inc -AI10530,Machine Learning Researcher,115524,USD,115524,SE,FT,Finland,S,Finland,50,"R, SQL, Data Visualization, Linux, Deep Learning",Associate,6,Education,2024-01-27,2024-03-29,1229,6.9,Advanced Robotics -AI10531,AI Software Engineer,20633,USD,20633,EN,PT,India,S,India,100,"SQL, GCP, Azure",PhD,1,Real Estate,2024-03-02,2024-04-17,1824,6.9,Cognitive Computing -AI10532,Robotics Engineer,190066,GBP,142550,EX,FL,United Kingdom,S,Romania,50,"PyTorch, Docker, AWS, Deep Learning",Associate,11,Government,2024-08-17,2024-10-08,1342,9.3,Quantum Computing Inc -AI10533,Head of AI,296126,JPY,32573860,EX,FT,Japan,L,Japan,0,"PyTorch, Statistics, TensorFlow, NLP, Deep Learning",Associate,18,Gaming,2024-07-21,2024-09-18,775,9.6,Predictive Systems -AI10534,Autonomous Systems Engineer,187800,USD,187800,SE,FL,Norway,L,Norway,100,"Tableau, Git, Deep Learning, Python, SQL",PhD,7,Real Estate,2024-12-30,2025-03-13,1720,9.5,Autonomous Tech -AI10535,Data Scientist,206562,USD,206562,EX,CT,Ireland,S,Ireland,100,"GCP, Java, NLP, Data Visualization",Associate,17,Gaming,2024-06-10,2024-07-15,1196,7.1,Algorithmic Solutions -AI10536,AI Specialist,188230,JPY,20705300,EX,FL,Japan,S,Japan,0,"Python, Computer Vision, Tableau, Linux",PhD,11,Manufacturing,2024-08-20,2024-10-17,1097,7.5,TechCorp Inc -AI10537,Machine Learning Engineer,151183,USD,151183,SE,FT,Norway,S,Norway,50,"Hadoop, SQL, TensorFlow, NLP",PhD,5,Retail,2024-12-27,2025-01-31,1674,6,DeepTech Ventures -AI10538,Principal Data Scientist,84340,JPY,9277400,EN,PT,Japan,L,Japan,0,"MLOps, Git, Java, Kubernetes",Bachelor,1,Transportation,2024-06-05,2024-08-03,1477,7.1,Machine Intelligence Group -AI10539,Head of AI,130206,SGD,169268,SE,CT,Singapore,S,Singapore,100,"R, Scala, SQL, Data Visualization",Bachelor,7,Media,2024-10-05,2024-11-13,566,6,TechCorp Inc -AI10540,Machine Learning Researcher,59063,AUD,79735,EN,CT,Australia,M,Australia,0,"Azure, Python, GCP, Scala",Bachelor,0,Gaming,2024-06-07,2024-07-23,696,8.6,Cloud AI Solutions -AI10541,Data Engineer,105416,CHF,94874,EN,CT,Switzerland,M,Switzerland,50,"R, Python, Data Visualization, TensorFlow, Git",PhD,1,Consulting,2024-01-28,2024-03-11,2392,6.7,DeepTech Ventures -AI10542,Head of AI,116299,USD,116299,EX,PT,China,M,China,100,"Hadoop, Linux, SQL",Bachelor,17,Transportation,2025-01-03,2025-03-15,615,5.2,AI Innovations -AI10543,Data Analyst,123542,USD,123542,SE,FT,Sweden,M,Sweden,50,"Git, Python, AWS",Bachelor,8,Healthcare,2024-03-27,2024-05-07,2113,5.1,Cloud AI Solutions -AI10544,Computer Vision Engineer,268891,CHF,242002,EX,FL,Switzerland,L,Switzerland,50,"Statistics, R, Tableau",Master,19,Consulting,2024-10-05,2024-12-05,1722,5.8,Digital Transformation LLC -AI10545,Robotics Engineer,184006,USD,184006,EX,PT,South Korea,M,France,0,"Spark, Deep Learning, Computer Vision, Python",Bachelor,11,Telecommunications,2024-10-01,2024-11-25,1949,9.3,Future Systems -AI10546,Head of AI,253222,JPY,27854420,EX,CT,Japan,L,Japan,0,"PyTorch, Data Visualization, TensorFlow, GCP, Python",Master,17,Energy,2024-05-03,2024-06-01,1021,8.7,TechCorp Inc -AI10547,AI Software Engineer,117179,USD,117179,EN,PT,Norway,L,Thailand,100,"Data Visualization, Linux, Python",Master,1,Real Estate,2024-05-10,2024-07-06,2212,6.9,Digital Transformation LLC -AI10548,Machine Learning Engineer,267272,GBP,200454,EX,FT,United Kingdom,L,Portugal,0,"Git, Data Visualization, Java, NLP",PhD,10,Real Estate,2024-02-01,2024-03-15,503,8.8,DataVision Ltd -AI10549,Deep Learning Engineer,58015,EUR,49313,EN,FL,France,M,France,50,"Linux, NLP, Mathematics",PhD,0,Retail,2025-03-13,2025-05-25,2176,9,Smart Analytics -AI10550,Computer Vision Engineer,134945,EUR,114703,SE,FL,France,M,Philippines,100,"MLOps, Python, Hadoop, TensorFlow, Git",Master,5,Government,2024-05-20,2024-07-23,935,7.1,Machine Intelligence Group -AI10551,Data Analyst,171640,GBP,128730,SE,CT,United Kingdom,L,United Kingdom,100,"TensorFlow, Linux, Hadoop",PhD,7,Government,2024-03-26,2024-04-22,2475,9.2,Advanced Robotics -AI10552,NLP Engineer,188053,USD,188053,EX,PT,Sweden,S,Sweden,50,"Scala, Deep Learning, Java, PyTorch",Associate,18,Retail,2024-02-24,2024-03-21,2223,6.9,Machine Intelligence Group -AI10553,Research Scientist,174050,EUR,147943,SE,PT,Netherlands,L,Netherlands,100,"Linux, Statistics, Spark",Bachelor,5,Gaming,2024-07-08,2024-09-19,712,8.2,Digital Transformation LLC -AI10554,Machine Learning Researcher,162350,USD,162350,EX,CT,South Korea,S,South Korea,100,"SQL, AWS, MLOps, Azure",Master,15,Consulting,2024-06-01,2024-08-11,1094,7.6,Digital Transformation LLC -AI10555,NLP Engineer,48857,USD,48857,EN,FL,Sweden,S,Singapore,0,"Scala, Java, Computer Vision, Python, TensorFlow",Bachelor,1,Technology,2025-01-17,2025-03-10,2343,9.3,Neural Networks Co -AI10556,Autonomous Systems Engineer,81741,SGD,106263,EN,FT,Singapore,M,Singapore,100,"Mathematics, Git, NLP, SQL",Associate,0,Healthcare,2025-01-16,2025-03-25,2261,6.9,Cognitive Computing -AI10557,Data Scientist,93881,EUR,79799,MI,FT,Austria,M,Austria,100,"Scala, MLOps, Java, TensorFlow",Bachelor,3,Healthcare,2024-07-16,2024-08-24,1606,7.5,Machine Intelligence Group -AI10558,AI Research Scientist,52800,USD,52800,EN,FL,Finland,S,Finland,0,"MLOps, Docker, Data Visualization, R",PhD,0,Finance,2024-08-14,2024-10-18,551,6.8,Predictive Systems -AI10559,AI Consultant,164719,CHF,148247,MI,FL,Switzerland,L,Switzerland,100,"Hadoop, Data Visualization, Scala, Docker",Associate,4,Consulting,2024-06-24,2024-08-24,1239,5.3,Autonomous Tech -AI10560,Research Scientist,89861,GBP,67396,MI,CT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Python, Tableau",Master,2,Education,2024-07-03,2024-07-19,1058,6.4,AI Innovations -AI10561,Autonomous Systems Engineer,182265,USD,182265,EX,FL,Israel,S,Israel,100,"Kubernetes, TensorFlow, Mathematics, AWS",Bachelor,19,Manufacturing,2024-10-28,2025-01-04,1922,7.1,Quantum Computing Inc -AI10562,Head of AI,119526,USD,119526,SE,PT,Israel,M,Austria,100,"Spark, Mathematics, Python",Bachelor,6,Technology,2025-03-05,2025-04-23,1562,7,Cognitive Computing -AI10563,Deep Learning Engineer,167797,USD,167797,EX,FL,Sweden,S,United Kingdom,100,"Computer Vision, NLP, Statistics",Master,19,Healthcare,2024-12-19,2025-02-14,1184,7.9,Algorithmic Solutions -AI10564,Machine Learning Researcher,338875,USD,338875,EX,FT,United States,L,United States,100,"Statistics, PyTorch, Deep Learning, TensorFlow",Master,16,Automotive,2024-07-24,2024-08-10,2085,7.1,Smart Analytics -AI10565,NLP Engineer,191360,EUR,162656,EX,FT,Austria,S,Austria,50,"Mathematics, Hadoop, Git, Computer Vision, Data Visualization",Bachelor,16,Telecommunications,2025-04-06,2025-06-01,2448,6.5,Future Systems -AI10566,Machine Learning Researcher,134565,USD,134565,SE,FL,United States,S,United States,0,"Statistics, Linux, Python, Git, Tableau",PhD,6,Real Estate,2024-09-04,2024-10-21,653,9.5,TechCorp Inc -AI10567,AI Consultant,75173,JPY,8269030,EN,FL,Japan,S,Belgium,100,"Python, TensorFlow, Mathematics, Git",Associate,0,Real Estate,2024-11-01,2024-12-04,2083,5.4,Cloud AI Solutions -AI10568,Machine Learning Engineer,123862,EUR,105283,SE,FL,France,S,France,0,"NLP, Tableau, Computer Vision",PhD,7,Finance,2024-02-29,2024-03-18,1232,5.4,Algorithmic Solutions -AI10569,Research Scientist,118839,AUD,160433,MI,FL,Australia,L,Australia,50,"PyTorch, TensorFlow, GCP, Spark",Master,4,Automotive,2024-04-22,2024-05-25,963,8,TechCorp Inc -AI10570,Robotics Engineer,72716,EUR,61809,EN,FL,Germany,L,Germany,100,"GCP, Python, Data Visualization, TensorFlow, Computer Vision",Bachelor,0,Transportation,2024-07-03,2024-07-27,501,7.8,Smart Analytics -AI10571,Data Scientist,126408,USD,126408,MI,FT,United States,L,Nigeria,0,"R, Python, NLP, Hadoop, Deep Learning",Master,4,Retail,2024-08-10,2024-10-13,1126,5.1,Neural Networks Co -AI10572,AI Research Scientist,116295,EUR,98851,MI,CT,Netherlands,M,Netherlands,100,"SQL, Deep Learning, PyTorch, Git, GCP",Bachelor,4,Telecommunications,2024-06-04,2024-07-25,991,7.3,Digital Transformation LLC -AI10573,AI Architect,104716,EUR,89009,MI,CT,Germany,L,New Zealand,50,"Kubernetes, Docker, Git",Master,3,Media,2025-02-07,2025-04-15,688,7.5,Advanced Robotics -AI10574,AI Product Manager,130494,JPY,14354340,MI,FT,Japan,L,Japan,0,"Kubernetes, TensorFlow, Python",Bachelor,4,Technology,2025-01-27,2025-04-06,1863,7.8,Quantum Computing Inc -AI10575,ML Ops Engineer,150085,AUD,202615,SE,CT,Australia,L,Australia,100,"AWS, Azure, Python, Java, MLOps",Master,5,Automotive,2024-05-03,2024-07-07,523,8.6,DataVision Ltd -AI10576,Deep Learning Engineer,45879,USD,45879,SE,PT,India,S,Latvia,50,"R, GCP, PyTorch, Computer Vision, Statistics",Bachelor,6,Government,2024-01-29,2024-02-25,2273,7.7,Cloud AI Solutions -AI10577,Data Scientist,108528,USD,108528,MI,CT,Denmark,L,Latvia,50,"Git, Kubernetes, Java",PhD,3,Consulting,2024-10-30,2025-01-04,1012,10,DeepTech Ventures -AI10578,Autonomous Systems Engineer,191897,EUR,163112,EX,FL,Austria,L,China,100,"R, SQL, Deep Learning",PhD,19,Automotive,2025-02-18,2025-04-19,1240,5.1,Algorithmic Solutions -AI10579,AI Software Engineer,93358,USD,93358,MI,PT,Norway,S,Norway,50,"Statistics, Kubernetes, NLP, GCP",Associate,4,Technology,2024-04-08,2024-05-16,909,6.4,Predictive Systems -AI10580,Data Engineer,31111,USD,31111,MI,CT,India,M,Argentina,100,"Spark, Kubernetes, Mathematics",PhD,3,Gaming,2024-09-21,2024-11-08,2004,5.8,Predictive Systems -AI10581,NLP Engineer,275338,AUD,371706,EX,CT,Australia,L,Australia,50,"Docker, Data Visualization, Java, Spark",PhD,19,Media,2024-06-14,2024-08-08,784,8.5,AI Innovations -AI10582,AI Consultant,147650,USD,147650,SE,FL,Ireland,L,Ireland,100,"GCP, Kubernetes, PyTorch, Scala, Deep Learning",Master,8,Automotive,2024-09-15,2024-10-03,1084,5.9,Predictive Systems -AI10583,Data Scientist,204393,GBP,153295,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, GCP, Data Visualization",Bachelor,18,Gaming,2025-01-17,2025-02-02,1818,5.9,Cognitive Computing -AI10584,Data Engineer,63051,USD,63051,EN,CT,South Korea,M,South Korea,0,"Git, Java, NLP",Master,1,Energy,2024-10-26,2024-11-24,509,6.6,Smart Analytics -AI10585,Computer Vision Engineer,68170,JPY,7498700,EN,FT,Japan,M,Singapore,0,"Kubernetes, TensorFlow, GCP",Associate,1,Telecommunications,2025-01-08,2025-03-12,2423,6.7,Future Systems -AI10586,Principal Data Scientist,63760,GBP,47820,EN,PT,United Kingdom,L,United Kingdom,0,"Python, Kubernetes, TensorFlow, Scala",Associate,0,Technology,2024-02-04,2024-03-05,1911,6.2,Future Systems -AI10587,Machine Learning Engineer,93851,USD,93851,MI,FL,United States,S,Switzerland,0,"TensorFlow, Scala, GCP, SQL",Master,3,Gaming,2025-04-23,2025-06-22,2028,8.4,Smart Analytics -AI10588,Data Scientist,125553,USD,125553,SE,PT,United States,S,United States,50,"Java, GCP, Azure",Master,6,Education,2024-10-31,2024-11-29,1036,8.1,AI Innovations -AI10589,Computer Vision Engineer,56723,CAD,70904,EN,FT,Canada,L,Canada,100,"Tableau, Python, Kubernetes, Scala",Associate,1,Gaming,2024-11-08,2024-11-25,1997,6.6,Digital Transformation LLC -AI10590,AI Product Manager,78007,USD,78007,EN,CT,United States,S,United States,50,"Azure, Spark, MLOps, Tableau",Bachelor,1,Finance,2024-03-01,2024-03-17,2122,9.3,Advanced Robotics -AI10591,Data Scientist,230768,USD,230768,EX,CT,Finland,L,Spain,50,"MLOps, Scala, TensorFlow, Mathematics",PhD,17,Media,2024-06-26,2024-07-29,1798,8.4,Cognitive Computing -AI10592,Data Scientist,61453,USD,61453,EN,CT,Israel,S,Israel,100,"Java, Python, Git",Bachelor,0,Energy,2024-07-09,2024-08-07,671,9.4,Predictive Systems -AI10593,Robotics Engineer,86143,CAD,107679,MI,PT,Canada,S,Canada,50,"Hadoop, NLP, Scala",Master,2,Manufacturing,2025-01-03,2025-03-05,1242,6.6,TechCorp Inc -AI10594,Head of AI,60433,CAD,75541,EN,FT,Canada,L,Brazil,50,"Java, Kubernetes, MLOps, Computer Vision",Associate,0,Education,2024-08-29,2024-09-21,613,5.9,Quantum Computing Inc -AI10595,AI Architect,71504,EUR,60778,MI,FL,Austria,M,Austria,50,"PyTorch, Git, Kubernetes, Deep Learning, Scala",Bachelor,2,Finance,2024-11-17,2025-01-23,1193,5.3,Autonomous Tech -AI10596,Deep Learning Engineer,141331,CAD,176664,SE,FT,Canada,M,Canada,0,"SQL, Python, GCP, Java, TensorFlow",PhD,9,Consulting,2024-08-25,2024-11-06,2124,5.7,Machine Intelligence Group -AI10597,Data Scientist,182504,JPY,20075440,SE,PT,Japan,L,Finland,100,"Spark, Tableau, Deep Learning, SQL",Associate,5,Finance,2024-09-24,2024-11-09,2236,8.1,Advanced Robotics -AI10598,Data Analyst,32356,USD,32356,MI,FT,China,S,China,50,"NLP, SQL, Scala",PhD,2,Retail,2024-06-06,2024-06-24,1316,8,Neural Networks Co -AI10599,AI Specialist,212698,AUD,287142,EX,FL,Australia,S,Australia,50,"Scala, Git, SQL",Associate,16,Gaming,2024-06-28,2024-08-26,1759,5.3,Future Systems -AI10600,AI Software Engineer,159697,EUR,135742,EX,PT,France,M,France,0,"Linux, Python, R",Bachelor,11,Media,2024-06-17,2024-08-23,2236,9.1,Predictive Systems -AI10601,Principal Data Scientist,104312,USD,104312,EN,CT,United States,L,Australia,0,"Docker, Linux, PyTorch, Data Visualization",Associate,1,Education,2024-09-07,2024-10-06,1298,7.9,Smart Analytics -AI10602,Machine Learning Researcher,80606,USD,80606,EN,FL,Sweden,M,Sweden,50,"Scala, Git, Data Visualization, Mathematics, SQL",PhD,1,Energy,2024-08-06,2024-09-03,721,6.8,Digital Transformation LLC -AI10603,AI Specialist,123309,EUR,104813,SE,FT,Germany,M,United Kingdom,0,"Java, Docker, GCP",Master,7,Media,2024-11-26,2025-01-27,1603,9.3,Future Systems -AI10604,AI Architect,278484,AUD,375953,EX,FL,Australia,L,Norway,0,"Linux, Scala, Git, Python, TensorFlow",Bachelor,14,Education,2025-04-29,2025-05-24,605,8.6,DataVision Ltd -AI10605,NLP Engineer,88219,USD,88219,MI,FT,Ireland,L,Ireland,50,"Python, Linux, Kubernetes",PhD,2,Education,2025-03-04,2025-04-25,963,9.6,Cloud AI Solutions -AI10606,ML Ops Engineer,85752,CHF,77177,EN,FL,Switzerland,S,Canada,100,"Python, TensorFlow, Git, PyTorch, NLP",Master,1,Retail,2024-04-26,2024-06-06,1245,7.8,AI Innovations -AI10607,ML Ops Engineer,152528,USD,152528,SE,FT,Sweden,M,Argentina,100,"NLP, Azure, Java",Associate,5,Healthcare,2024-11-28,2024-12-19,1606,9.8,Advanced Robotics -AI10608,Principal Data Scientist,79883,EUR,67901,MI,PT,Austria,S,Austria,0,"Python, MLOps, TensorFlow, Computer Vision, Statistics",PhD,3,Real Estate,2024-01-25,2024-03-31,635,6.9,Future Systems -AI10609,Data Analyst,71938,USD,71938,MI,PT,Israel,M,United Kingdom,100,"Azure, Spark, Scala, Mathematics, Python",Bachelor,4,Media,2025-02-15,2025-03-31,1038,5.6,Smart Analytics -AI10610,AI Architect,187859,USD,187859,EX,PT,South Korea,M,South Korea,100,"Hadoop, R, PyTorch, SQL",PhD,13,Government,2025-03-13,2025-04-30,991,8.2,TechCorp Inc -AI10611,Research Scientist,80473,USD,80473,SE,FL,South Korea,S,South Korea,100,"NLP, AWS, Java, Computer Vision, Python",Bachelor,6,Consulting,2024-04-15,2024-05-04,2365,7.2,DataVision Ltd -AI10612,Machine Learning Engineer,150968,EUR,128323,SE,FL,Germany,L,Turkey,100,"Python, Scala, TensorFlow, Deep Learning, Java",Master,8,Gaming,2024-03-14,2024-05-18,953,6,Cognitive Computing -AI10613,AI Software Engineer,117941,USD,117941,MI,CT,Finland,L,Denmark,100,"R, Spark, Data Visualization, Deep Learning, Azure",PhD,4,Energy,2024-04-10,2024-06-03,786,9.1,Autonomous Tech -AI10614,AI Software Engineer,67317,USD,67317,EN,CT,Denmark,S,Russia,50,"Docker, Spark, R, GCP",Bachelor,0,Healthcare,2024-01-02,2024-03-04,2454,7.2,AI Innovations -AI10615,Data Engineer,120964,EUR,102819,SE,PT,Netherlands,M,Luxembourg,0,"R, Java, SQL",PhD,8,Healthcare,2024-01-24,2024-02-29,1395,8.5,TechCorp Inc -AI10616,Head of AI,147747,CHF,132972,MI,CT,Switzerland,L,Switzerland,50,"Scala, Spark, Data Visualization",Master,4,Transportation,2024-03-04,2024-03-26,1292,5.9,Algorithmic Solutions -AI10617,Computer Vision Engineer,144492,AUD,195064,SE,PT,Australia,L,Australia,50,"Java, Spark, TensorFlow, Hadoop, Scala",Associate,9,Manufacturing,2025-04-06,2025-06-12,2186,5.3,Algorithmic Solutions -AI10618,Machine Learning Engineer,245526,USD,245526,EX,FT,United States,S,Israel,100,"Python, Git, Kubernetes",Bachelor,12,Manufacturing,2025-02-28,2025-03-19,1919,5.4,Autonomous Tech -AI10619,Machine Learning Researcher,118930,GBP,89198,SE,FL,United Kingdom,S,United Kingdom,100,"GCP, NLP, Hadoop, Python, Scala",Master,8,Technology,2024-02-06,2024-03-12,2485,6.4,Autonomous Tech -AI10620,Data Scientist,173914,USD,173914,SE,PT,United States,L,United States,100,"Scala, Java, NLP, PyTorch, SQL",Bachelor,9,Telecommunications,2024-01-06,2024-02-15,1015,8.9,AI Innovations -AI10621,AI Architect,46392,EUR,39433,EN,FT,Germany,S,Latvia,100,"NLP, Azure, Linux, Kubernetes, Data Visualization",PhD,1,Finance,2024-06-08,2024-06-27,2495,7.9,DeepTech Ventures -AI10622,AI Product Manager,97856,USD,97856,SE,FT,Ireland,S,Ireland,50,"Python, Scala, Spark, GCP, Linux",Bachelor,8,Gaming,2024-06-17,2024-07-05,938,9.4,DeepTech Ventures -AI10623,Machine Learning Engineer,118261,EUR,100522,SE,FT,Germany,S,Germany,0,"MLOps, Git, Kubernetes, NLP",Master,6,Energy,2024-04-25,2024-05-24,1937,8.4,AI Innovations -AI10624,Deep Learning Engineer,85135,EUR,72365,MI,PT,France,M,France,50,"Scala, Spark, Git",Bachelor,3,Technology,2024-07-10,2024-08-30,967,7.4,Cognitive Computing -AI10625,Machine Learning Researcher,178627,AUD,241146,EX,FL,Australia,L,Austria,0,"Python, Deep Learning, Tableau",Bachelor,12,Transportation,2025-02-27,2025-04-23,1070,7.9,Quantum Computing Inc -AI10626,AI Specialist,95464,USD,95464,MI,FL,Sweden,S,Germany,100,"Scala, Java, AWS",Bachelor,3,Finance,2024-12-19,2025-02-11,629,9.5,Predictive Systems -AI10627,Deep Learning Engineer,91229,AUD,123159,EN,PT,Australia,L,Australia,0,"Azure, SQL, Tableau",Associate,0,Energy,2024-08-15,2024-09-26,1126,9.2,Cloud AI Solutions -AI10628,Research Scientist,192344,USD,192344,EX,FL,Sweden,S,Sweden,100,"TensorFlow, GCP, SQL, Docker, Git",Master,14,Automotive,2024-02-19,2024-03-10,2148,9.4,Predictive Systems -AI10629,Data Analyst,47789,USD,47789,EN,CT,Israel,S,Israel,100,"SQL, Linux, PyTorch, Git",Associate,0,Finance,2025-01-05,2025-01-26,1422,6,Predictive Systems -AI10630,Machine Learning Engineer,129729,EUR,110270,SE,FT,Germany,M,Germany,50,"Docker, Linux, Spark, Python",Associate,8,Technology,2024-02-05,2024-03-31,1715,7.5,TechCorp Inc -AI10631,AI Software Engineer,72974,USD,72974,MI,FT,South Korea,S,Canada,50,"Linux, Spark, Python, NLP, TensorFlow",PhD,2,Transportation,2024-03-07,2024-04-28,2093,9.4,Advanced Robotics -AI10632,Computer Vision Engineer,140615,EUR,119523,SE,FT,France,L,France,50,"PyTorch, Computer Vision, R, Scala, AWS",Bachelor,8,Manufacturing,2025-01-30,2025-02-27,876,5.4,Autonomous Tech -AI10633,Data Engineer,111490,SGD,144937,MI,FL,Singapore,M,Singapore,0,"Python, NLP, TensorFlow",PhD,4,Retail,2024-08-30,2024-10-18,1663,6.3,Predictive Systems -AI10634,Deep Learning Engineer,61103,GBP,45827,EN,FL,United Kingdom,S,United Kingdom,50,"Spark, Docker, Python, Deep Learning",PhD,1,Media,2025-01-23,2025-02-23,1769,5.6,Algorithmic Solutions -AI10635,AI Product Manager,116733,USD,116733,EX,CT,Israel,S,Israel,100,"Azure, Scala, MLOps, Python",Master,18,Media,2025-04-25,2025-05-14,1365,6.7,Machine Intelligence Group -AI10636,AI Specialist,283444,USD,283444,EX,PT,Ireland,L,Latvia,0,"SQL, Scala, R, Docker, Deep Learning",Associate,12,Government,2025-04-11,2025-05-02,2143,7.8,AI Innovations -AI10637,AI Architect,107069,EUR,91009,MI,FT,Netherlands,M,South Korea,100,"Python, TensorFlow, GCP",Master,2,Energy,2025-03-05,2025-04-09,1179,8.7,TechCorp Inc -AI10638,AI Consultant,73972,USD,73972,EN,PT,Israel,M,Israel,100,"Docker, MLOps, Mathematics, Linux",Master,0,Media,2024-06-10,2024-07-28,1551,9.9,DataVision Ltd -AI10639,AI Product Manager,52290,JPY,5751900,EN,PT,Japan,S,Japan,0,"NLP, Azure, Mathematics",Bachelor,1,Energy,2024-07-09,2024-09-10,1815,5.8,Advanced Robotics -AI10640,AI Product Manager,204367,CAD,255459,EX,CT,Canada,M,Canada,100,"AWS, Java, Azure, TensorFlow, Linux",Bachelor,15,Healthcare,2024-10-25,2024-11-23,1798,5.2,Smart Analytics -AI10641,Autonomous Systems Engineer,91739,JPY,10091290,MI,CT,Japan,M,Japan,50,"Statistics, R, Python, MLOps, GCP",Bachelor,3,Gaming,2025-01-25,2025-03-08,902,5.1,Autonomous Tech -AI10642,AI Specialist,52164,SGD,67813,EN,PT,Singapore,S,Singapore,100,"R, GCP, Computer Vision",Master,1,Retail,2024-10-23,2024-11-22,2141,5.9,Cognitive Computing -AI10643,Data Analyst,135990,EUR,115592,SE,FL,France,L,France,0,"Tableau, Java, SQL, Azure",Associate,7,Government,2024-10-23,2024-12-17,1398,8.2,Cloud AI Solutions -AI10644,Autonomous Systems Engineer,180546,GBP,135410,SE,CT,United Kingdom,L,United Kingdom,0,"Hadoop, SQL, Spark, Kubernetes",Bachelor,9,Gaming,2025-02-18,2025-03-06,1432,8.4,TechCorp Inc -AI10645,Data Analyst,173391,EUR,147382,EX,PT,France,S,Luxembourg,100,"Java, Python, Mathematics, GCP, Linux",Associate,16,Government,2024-08-24,2024-11-02,2082,8.5,Digital Transformation LLC -AI10646,AI Consultant,131162,JPY,14427820,SE,CT,Japan,S,India,100,"GCP, Azure, Spark, Data Visualization",PhD,5,Technology,2024-05-01,2024-07-03,2200,5.5,DeepTech Ventures -AI10647,Autonomous Systems Engineer,83876,USD,83876,EN,CT,Israel,L,Israel,100,"Python, GCP, Deep Learning, TensorFlow, Data Visualization",Master,1,Consulting,2024-12-27,2025-02-21,524,9.9,DeepTech Ventures -AI10648,AI Product Manager,120528,USD,120528,SE,CT,Denmark,S,Ghana,0,"Java, Python, Linux",Bachelor,5,Consulting,2024-09-05,2024-10-28,675,8.1,Advanced Robotics -AI10649,Head of AI,20105,USD,20105,EN,PT,India,S,India,100,"Java, PyTorch, MLOps, Data Visualization, Linux",Associate,1,Energy,2025-01-08,2025-01-28,926,9.6,Autonomous Tech -AI10650,Computer Vision Engineer,99524,EUR,84595,MI,PT,Austria,M,Austria,0,"GCP, SQL, Tableau, PyTorch",Master,2,Government,2025-01-24,2025-02-08,2434,9.2,Algorithmic Solutions -AI10651,Research Scientist,97168,EUR,82593,EN,FT,Netherlands,L,Australia,0,"Python, TensorFlow, Docker, Statistics, SQL",Bachelor,1,Manufacturing,2025-02-22,2025-04-26,1604,9.4,Advanced Robotics -AI10652,Machine Learning Researcher,79501,AUD,107326,MI,PT,Australia,S,Austria,0,"R, Hadoop, AWS, Docker",Master,3,Energy,2024-05-09,2024-05-23,1453,8.1,DeepTech Ventures -AI10653,NLP Engineer,80406,GBP,60305,EN,PT,United Kingdom,M,United Kingdom,50,"Tableau, Kubernetes, Python",Associate,0,Technology,2025-02-15,2025-04-28,1482,6,DataVision Ltd -AI10654,Principal Data Scientist,179168,SGD,232918,SE,FL,Singapore,L,Singapore,50,"SQL, PyTorch, Java, GCP",Master,5,Manufacturing,2024-07-30,2024-09-23,2303,5.6,Smart Analytics -AI10655,Machine Learning Researcher,117302,USD,117302,SE,FT,United States,S,United States,50,"Docker, Deep Learning, Kubernetes, R, SQL",Bachelor,7,Finance,2025-04-07,2025-06-05,1833,8.9,Predictive Systems -AI10656,Machine Learning Researcher,24496,USD,24496,EN,CT,China,S,Netherlands,0,"Java, Computer Vision, Kubernetes",Associate,1,Telecommunications,2024-04-07,2024-06-16,1991,9.8,Advanced Robotics -AI10657,AI Consultant,136071,GBP,102053,EX,CT,United Kingdom,S,United Kingdom,100,"Python, SQL, GCP, Hadoop, Spark",Associate,16,Real Estate,2025-03-27,2025-04-18,965,7.4,Cognitive Computing -AI10658,Robotics Engineer,238120,USD,238120,EX,PT,Sweden,L,Sweden,50,"Java, Docker, Mathematics, Git, Data Visualization",Master,16,Education,2024-02-25,2024-03-13,1211,8,DeepTech Ventures -AI10659,ML Ops Engineer,156352,JPY,17198720,SE,CT,Japan,M,Belgium,100,"Java, Kubernetes, GCP, Mathematics, TensorFlow",Associate,7,Finance,2024-12-10,2025-01-30,1328,7.7,Cognitive Computing -AI10660,Computer Vision Engineer,36448,USD,36448,EN,FL,China,L,China,0,"TensorFlow, Git, Python, GCP, SQL",Master,0,Healthcare,2024-02-06,2024-04-06,501,7.3,Smart Analytics -AI10661,ML Ops Engineer,225966,USD,225966,EX,FL,South Korea,L,South Korea,50,"R, Git, Tableau",Associate,14,Media,2024-09-11,2024-11-14,661,7,Quantum Computing Inc -AI10662,AI Specialist,30284,USD,30284,MI,CT,India,M,India,0,"Hadoop, Spark, MLOps, Git, Linux",PhD,3,Healthcare,2024-09-21,2024-11-24,2167,8.6,Autonomous Tech -AI10663,Research Scientist,202712,USD,202712,EX,FL,Denmark,S,Chile,100,"GCP, Kubernetes, AWS, R, Spark",Bachelor,12,Automotive,2024-08-20,2024-10-13,1609,5.7,TechCorp Inc -AI10664,AI Research Scientist,166959,USD,166959,EX,FT,Finland,M,Canada,50,"PyTorch, AWS, Azure",Associate,10,Finance,2024-12-21,2025-02-20,850,5.5,Quantum Computing Inc -AI10665,AI Consultant,122284,EUR,103941,SE,PT,France,S,South Africa,100,"MLOps, Python, TensorFlow",PhD,6,Telecommunications,2024-09-30,2024-11-21,1211,8.9,Algorithmic Solutions -AI10666,Head of AI,116235,USD,116235,SE,CT,Ireland,S,Brazil,100,"R, Java, Tableau, MLOps",Master,8,Healthcare,2024-10-27,2024-11-16,973,8.6,Advanced Robotics -AI10667,Head of AI,202957,USD,202957,EX,PT,Sweden,M,Sweden,0,"Git, Docker, Deep Learning, TensorFlow",PhD,19,Energy,2024-08-13,2024-09-02,2052,5.2,Algorithmic Solutions -AI10668,AI Consultant,79718,JPY,8768980,MI,FT,Japan,S,Portugal,100,"Tableau, Spark, Hadoop",Master,3,Real Estate,2024-11-22,2025-01-06,1868,5.3,Cognitive Computing -AI10669,Robotics Engineer,125746,GBP,94310,SE,PT,United Kingdom,M,United Kingdom,0,"TensorFlow, PyTorch, Mathematics",Master,9,Real Estate,2024-02-26,2024-03-16,919,7,Neural Networks Co -AI10670,AI Specialist,154306,GBP,115730,SE,FT,United Kingdom,M,United Kingdom,0,"Docker, MLOps, PyTorch, Spark",Bachelor,9,Transportation,2024-08-31,2024-09-17,987,9.6,Cloud AI Solutions -AI10671,AI Consultant,86374,EUR,73418,MI,CT,Netherlands,M,Norway,100,"MLOps, Git, GCP",Bachelor,4,Finance,2024-10-01,2024-11-08,558,6.8,DataVision Ltd -AI10672,ML Ops Engineer,113235,USD,113235,SE,FT,Finland,M,Switzerland,0,"GCP, Mathematics, Computer Vision",Master,8,Manufacturing,2024-03-08,2024-05-01,1365,7.5,Digital Transformation LLC -AI10673,Data Analyst,266149,USD,266149,EX,FT,Denmark,S,Denmark,100,"Data Visualization, Spark, NLP, Hadoop, Deep Learning",Master,16,Telecommunications,2024-02-10,2024-03-25,595,6.4,Algorithmic Solutions -AI10674,Head of AI,77319,JPY,8505090,MI,FL,Japan,S,Japan,0,"Git, MLOps, TensorFlow, Kubernetes",PhD,3,Transportation,2024-06-20,2024-07-17,1217,7.9,Algorithmic Solutions -AI10675,Data Engineer,74543,USD,74543,MI,FT,South Korea,M,South Korea,0,"Java, Python, Tableau, Azure, Hadoop",Bachelor,4,Finance,2024-11-18,2025-01-30,1362,9.3,TechCorp Inc -AI10676,AI Specialist,51768,SGD,67298,EN,FL,Singapore,S,Singapore,100,"Docker, AWS, Kubernetes, Tableau",PhD,0,Energy,2025-04-30,2025-06-05,1526,9.2,AI Innovations -AI10677,Autonomous Systems Engineer,213531,USD,213531,EX,PT,Norway,S,Norway,50,"AWS, Data Visualization, Docker, GCP, Python",Master,18,Consulting,2024-05-30,2024-07-20,885,8.5,AI Innovations -AI10678,AI Research Scientist,195386,GBP,146540,EX,FT,United Kingdom,L,United Kingdom,100,"Git, PyTorch, SQL, Linux",Bachelor,14,Telecommunications,2025-01-05,2025-03-05,2185,5.4,Machine Intelligence Group -AI10679,Data Engineer,91835,USD,91835,EX,CT,China,L,China,50,"Linux, Mathematics, NLP, Python",PhD,19,Gaming,2024-10-21,2024-12-01,985,6.2,Cloud AI Solutions -AI10680,AI Research Scientist,95351,EUR,81048,SE,PT,Germany,S,Germany,50,"Spark, SQL, Deep Learning, NLP",Associate,9,Healthcare,2024-08-05,2024-10-13,2260,5,DataVision Ltd -AI10681,Robotics Engineer,89630,USD,89630,MI,CT,Finland,L,Finland,0,"Deep Learning, SQL, Computer Vision",PhD,2,Government,2024-07-21,2024-08-27,1413,9.3,Future Systems -AI10682,Computer Vision Engineer,70678,EUR,60076,MI,PT,Germany,S,Germany,0,"TensorFlow, AWS, Linux, MLOps, Azure",Associate,3,Automotive,2024-04-30,2024-06-18,2104,8,DataVision Ltd -AI10683,Computer Vision Engineer,134959,JPY,14845490,SE,CT,Japan,M,Kenya,100,"GCP, Java, Linux",Bachelor,9,Finance,2024-10-29,2025-01-07,1173,6,Advanced Robotics -AI10684,Head of AI,38645,USD,38645,SE,FL,India,S,India,100,"TensorFlow, Docker, SQL, MLOps",PhD,7,Transportation,2025-01-25,2025-03-26,2358,6.5,DataVision Ltd -AI10685,Machine Learning Engineer,156721,JPY,17239310,EX,FT,Japan,M,Japan,50,"NLP, Git, Deep Learning, Python",PhD,18,Education,2024-03-30,2024-06-10,1357,7.7,Machine Intelligence Group -AI10686,Computer Vision Engineer,60173,USD,60173,EN,PT,Sweden,S,Sweden,50,"TensorFlow, Scala, Java, Statistics",Master,1,Government,2024-06-25,2024-07-26,2352,8.5,AI Innovations -AI10687,Machine Learning Researcher,61314,USD,61314,MI,FT,South Korea,S,South Korea,50,"Python, Docker, Tableau",PhD,2,Manufacturing,2024-02-18,2024-04-27,1801,9.7,Cloud AI Solutions -AI10688,Autonomous Systems Engineer,151060,USD,151060,EX,CT,Israel,S,Israel,100,"Azure, Docker, Python",Master,13,Technology,2025-03-28,2025-05-27,2382,9,Quantum Computing Inc -AI10689,Robotics Engineer,78798,SGD,102437,MI,FL,Singapore,M,Singapore,50,"Data Visualization, PyTorch, Git, Docker",Associate,2,Government,2024-10-22,2024-12-02,2429,7.9,Predictive Systems -AI10690,Principal Data Scientist,28501,USD,28501,MI,FL,India,M,India,100,"Data Visualization, TensorFlow, Python, Scala",Bachelor,3,Gaming,2024-09-26,2024-10-16,2203,7.1,Advanced Robotics -AI10691,Data Scientist,147112,USD,147112,SE,FL,Denmark,M,Denmark,0,"SQL, GCP, Java, Statistics",Associate,7,Retail,2024-02-24,2024-03-23,2407,5.9,Future Systems -AI10692,Machine Learning Engineer,57860,EUR,49181,EN,FT,Austria,L,Finland,50,"Data Visualization, Tableau, Spark, Python, Hadoop",Master,0,Transportation,2024-03-13,2024-04-01,2104,5.7,Neural Networks Co -AI10693,Autonomous Systems Engineer,124336,JPY,13676960,SE,CT,Japan,L,Norway,100,"Docker, GCP, MLOps",Bachelor,6,Transportation,2024-04-02,2024-05-23,1518,6.2,AI Innovations -AI10694,Machine Learning Researcher,52712,EUR,44805,EN,FT,France,M,France,50,"Scala, Hadoop, Statistics, Azure, PyTorch",PhD,0,Energy,2024-08-21,2024-11-01,1117,5.2,TechCorp Inc -AI10695,NLP Engineer,151816,CHF,136634,SE,FL,Switzerland,S,Switzerland,100,"R, Scala, Statistics",PhD,8,Automotive,2024-12-18,2025-02-09,680,7.8,Autonomous Tech -AI10696,Data Engineer,136528,USD,136528,EX,PT,China,L,China,0,"Kubernetes, Java, MLOps",Associate,14,Transportation,2024-05-12,2024-06-17,2317,7.3,Advanced Robotics -AI10697,AI Software Engineer,117912,EUR,100225,SE,PT,France,L,France,50,"SQL, Docker, NLP, Statistics",Bachelor,6,Finance,2025-02-02,2025-04-04,2357,8.2,Machine Intelligence Group -AI10698,AI Consultant,152584,EUR,129696,EX,FT,Austria,S,Austria,0,"PyTorch, Docker, Data Visualization, AWS",PhD,16,Technology,2024-09-16,2024-10-23,1903,6.7,Neural Networks Co -AI10699,AI Software Engineer,148386,USD,148386,MI,FL,United States,L,Kenya,50,"AWS, Python, Statistics",PhD,4,Government,2025-03-01,2025-05-06,832,9.3,Neural Networks Co -AI10700,NLP Engineer,170113,USD,170113,SE,FT,United States,M,United States,100,"Data Visualization, Azure, Java, NLP, Hadoop",PhD,5,Automotive,2024-04-09,2024-05-30,2437,9.4,Algorithmic Solutions -AI10701,Data Engineer,76774,EUR,65258,MI,FL,Germany,M,Hungary,0,"Kubernetes, Statistics, Azure, Deep Learning, SQL",Associate,4,Healthcare,2025-03-29,2025-04-20,876,8.2,DeepTech Ventures -AI10702,AI Software Engineer,104215,USD,104215,EN,FT,Norway,L,Norway,50,"PyTorch, TensorFlow, Tableau, Java, Mathematics",Master,1,Government,2024-05-17,2024-06-26,869,9,Cognitive Computing -AI10703,NLP Engineer,214317,USD,214317,EX,FL,Denmark,S,Russia,50,"Statistics, Scala, Kubernetes, GCP",Bachelor,19,Transportation,2025-04-04,2025-06-10,1517,6.9,DeepTech Ventures -AI10704,Data Scientist,134618,EUR,114425,SE,PT,Austria,M,Austria,0,"Mathematics, GCP, PyTorch, TensorFlow",Master,5,Energy,2025-03-25,2025-05-15,1450,9.9,AI Innovations -AI10705,AI Software Engineer,73195,USD,73195,EN,CT,Ireland,L,Vietnam,100,"GCP, Scala, Mathematics",Associate,1,Finance,2024-08-03,2024-10-09,1283,8,Digital Transformation LLC -AI10706,Computer Vision Engineer,116013,USD,116013,SE,PT,Sweden,S,Austria,0,"Spark, PyTorch, NLP, Java",Bachelor,6,Gaming,2024-02-09,2024-03-20,2305,9.4,TechCorp Inc -AI10707,AI Specialist,129732,JPY,14270520,SE,PT,Japan,L,Japan,50,"Computer Vision, Deep Learning, Linux",Master,8,Real Estate,2024-06-01,2024-06-15,2326,6,Cloud AI Solutions -AI10708,AI Specialist,250954,GBP,188216,EX,FT,United Kingdom,L,United Kingdom,100,"Scala, MLOps, Linux, Kubernetes",Master,19,Media,2025-04-23,2025-05-11,1862,5.9,Autonomous Tech -AI10709,Data Scientist,64591,CAD,80739,EN,CT,Canada,L,Canada,100,"Azure, Scala, R",Bachelor,1,Retail,2024-01-21,2024-02-15,2126,9,Autonomous Tech -AI10710,Data Engineer,117699,USD,117699,SE,FT,Ireland,M,Ireland,100,"Docker, Python, SQL",Associate,7,Retail,2024-08-08,2024-10-07,1819,9.9,Future Systems -AI10711,NLP Engineer,111868,USD,111868,EX,FT,China,L,China,50,"Linux, Git, R, Docker",Master,13,Gaming,2024-06-05,2024-07-18,1727,5.4,Autonomous Tech -AI10712,Research Scientist,143592,USD,143592,SE,PT,United States,S,United States,50,"Computer Vision, Hadoop, Tableau",PhD,5,Finance,2024-01-10,2024-03-23,2454,7.9,Autonomous Tech -AI10713,AI Specialist,112805,EUR,95884,MI,FL,Austria,L,Austria,100,"Python, Hadoop, AWS, Statistics",PhD,4,Education,2024-01-04,2024-01-30,2148,8.7,TechCorp Inc -AI10714,AI Architect,161399,USD,161399,EX,FT,Israel,L,Israel,0,"Java, NLP, SQL",PhD,10,Manufacturing,2024-09-19,2024-11-24,1789,7.8,Autonomous Tech -AI10715,AI Architect,243356,USD,243356,EX,FL,Norway,S,Norway,0,"NLP, Scala, R",Master,14,Transportation,2024-05-12,2024-06-12,1489,5.6,Cognitive Computing -AI10716,Principal Data Scientist,91224,USD,91224,MI,CT,Israel,L,Canada,50,"PyTorch, GCP, AWS",Bachelor,2,Manufacturing,2024-07-30,2024-10-10,1336,8.1,Neural Networks Co -AI10717,Data Engineer,42308,USD,42308,MI,FL,China,M,China,50,"Java, SQL, Docker",PhD,2,Gaming,2024-11-19,2025-01-08,764,7.9,AI Innovations -AI10718,AI Research Scientist,44344,USD,44344,MI,PT,China,L,China,100,"Scala, Mathematics, Deep Learning, Data Visualization, PyTorch",Associate,2,Transportation,2025-01-27,2025-03-06,1050,7.7,Quantum Computing Inc -AI10719,AI Consultant,176796,EUR,150277,EX,FT,France,M,France,50,"Python, Docker, Deep Learning, TensorFlow, NLP",Associate,12,Manufacturing,2024-02-26,2024-04-14,1400,9.1,Neural Networks Co -AI10720,Data Analyst,128958,JPY,14185380,SE,CT,Japan,L,Ireland,100,"Python, Git, Docker, Mathematics, Tableau",PhD,5,Retail,2024-06-05,2024-07-24,1906,5.9,Predictive Systems -AI10721,AI Research Scientist,38734,USD,38734,SE,CT,India,S,India,50,"Azure, MLOps, Statistics, Docker",PhD,9,Retail,2024-09-11,2024-09-25,698,9.4,AI Innovations -AI10722,Robotics Engineer,139670,GBP,104753,SE,CT,United Kingdom,M,Canada,0,"Python, Scala, MLOps, AWS",PhD,6,Media,2024-06-22,2024-07-07,1717,6.3,Algorithmic Solutions -AI10723,Principal Data Scientist,151422,EUR,128709,EX,CT,Germany,S,Germany,0,"PyTorch, TensorFlow, R, Linux, Mathematics",PhD,14,Automotive,2025-02-08,2025-03-20,590,7.3,Digital Transformation LLC -AI10724,Computer Vision Engineer,59521,EUR,50593,EN,CT,Netherlands,S,Netherlands,50,"Scala, R, NLP, MLOps",Bachelor,0,Real Estate,2024-09-08,2024-09-26,1095,7.3,DeepTech Ventures -AI10725,ML Ops Engineer,71064,USD,71064,MI,FT,South Korea,M,South Korea,50,"Java, Python, R, Mathematics, PyTorch",PhD,2,Consulting,2024-06-22,2024-08-18,1716,8.6,Future Systems -AI10726,Data Scientist,226728,EUR,192719,EX,CT,France,L,France,100,"Java, MLOps, TensorFlow, Computer Vision",Associate,16,Transportation,2024-06-02,2024-06-18,971,7.2,Cognitive Computing -AI10727,Machine Learning Researcher,112137,CAD,140171,MI,FL,Canada,L,Canada,50,"TensorFlow, Linux, Computer Vision, Git, Java",Associate,4,Retail,2025-04-21,2025-05-21,2367,7.8,AI Innovations -AI10728,Machine Learning Engineer,127819,CAD,159774,SE,CT,Canada,L,Germany,100,"Python, SQL, Scala, Computer Vision",PhD,5,Healthcare,2025-04-05,2025-05-31,2077,9.2,DataVision Ltd -AI10729,Data Analyst,96910,JPY,10660100,MI,FL,Japan,M,Japan,0,"SQL, AWS, GCP",Associate,2,Consulting,2024-02-23,2024-04-02,1569,7.9,Machine Intelligence Group -AI10730,Autonomous Systems Engineer,80604,USD,80604,EX,CT,India,L,Singapore,50,"Python, Mathematics, Tableau",Associate,11,Media,2024-04-19,2024-06-17,897,5.4,DataVision Ltd -AI10731,Head of AI,104712,USD,104712,SE,CT,Ireland,S,Argentina,0,"Kubernetes, Python, AWS, Deep Learning",PhD,9,Real Estate,2024-12-10,2024-12-31,643,6.7,Neural Networks Co -AI10732,Data Engineer,76848,CAD,96060,MI,FT,Canada,M,Canada,0,"Kubernetes, Tableau, Hadoop",Bachelor,4,Energy,2024-09-23,2024-11-14,1993,7.5,Cognitive Computing -AI10733,Deep Learning Engineer,155320,AUD,209682,EX,CT,Australia,M,Australia,0,"SQL, Scala, Computer Vision, Tableau, Linux",Master,14,Government,2025-01-05,2025-02-21,1624,6.7,DataVision Ltd -AI10734,AI Consultant,197617,GBP,148213,EX,PT,United Kingdom,S,United Kingdom,50,"AWS, PyTorch, Deep Learning",Associate,18,Finance,2024-11-11,2024-12-24,1858,7.2,Future Systems -AI10735,AI Research Scientist,49891,EUR,42407,EN,FT,Netherlands,S,Netherlands,0,"NLP, R, Computer Vision, Azure",Associate,0,Media,2024-03-30,2024-05-03,1695,9.3,DataVision Ltd -AI10736,Principal Data Scientist,117730,EUR,100071,SE,FL,Germany,L,Germany,0,"AWS, MLOps, Mathematics, Tableau",Master,5,Automotive,2024-12-21,2025-02-13,1009,5.6,Cognitive Computing -AI10737,AI Architect,115851,USD,115851,SE,PT,South Korea,M,South Korea,100,"Git, Python, Kubernetes, Statistics, Data Visualization",Associate,8,Media,2024-10-08,2024-11-09,990,7,Cloud AI Solutions -AI10738,Machine Learning Engineer,73670,CAD,92088,EN,CT,Canada,M,Egypt,100,"Linux, PyTorch, SQL, Java, Statistics",Associate,0,Government,2024-09-01,2024-10-17,1315,7.8,Predictive Systems -AI10739,AI Software Engineer,214568,CHF,193111,SE,FL,Switzerland,M,Switzerland,50,"AWS, Linux, Computer Vision",Master,7,Retail,2024-08-10,2024-09-15,937,6.8,Algorithmic Solutions -AI10740,AI Architect,258181,USD,258181,EX,CT,United States,L,Mexico,0,"MLOps, Spark, Data Visualization, GCP, Computer Vision",PhD,19,Retail,2024-05-24,2024-07-22,1825,7.1,AI Innovations -AI10741,Deep Learning Engineer,39478,USD,39478,EN,FL,South Korea,S,South Korea,50,"Git, Deep Learning, Spark, Java",Master,0,Automotive,2024-07-01,2024-08-10,922,7.9,DataVision Ltd -AI10742,Robotics Engineer,54274,USD,54274,MI,FT,China,L,China,0,"R, Java, AWS",Master,4,Manufacturing,2024-06-25,2024-07-15,723,7.2,Machine Intelligence Group -AI10743,Data Analyst,48788,USD,48788,SE,FT,China,S,China,0,"SQL, Deep Learning, Java, Computer Vision",Master,5,Healthcare,2025-01-09,2025-01-31,1444,7.1,Algorithmic Solutions -AI10744,NLP Engineer,232286,CHF,209057,SE,PT,Switzerland,L,Switzerland,50,"AWS, Python, GCP",Associate,8,Healthcare,2024-08-26,2024-09-19,637,9.9,Neural Networks Co -AI10745,AI Specialist,251960,USD,251960,EX,FT,United States,S,United States,100,"SQL, Scala, Python, MLOps, R",Master,13,Gaming,2024-04-11,2024-06-03,2323,6.1,Digital Transformation LLC -AI10746,Data Engineer,100923,CHF,90831,MI,FL,Switzerland,S,Malaysia,100,"Kubernetes, Scala, Azure, TensorFlow, SQL",Master,4,Healthcare,2024-07-01,2024-09-09,2073,5.9,Cognitive Computing -AI10747,Robotics Engineer,101479,AUD,136997,MI,CT,Australia,M,Australia,100,"Spark, Git, Computer Vision, AWS",PhD,4,Government,2025-04-16,2025-06-08,867,5.2,Quantum Computing Inc -AI10748,AI Software Engineer,238738,USD,238738,EX,FT,Israel,L,Israel,50,"Python, TensorFlow, Tableau",Associate,18,Retail,2024-09-22,2024-11-14,851,6.6,TechCorp Inc -AI10749,ML Ops Engineer,63999,EUR,54399,EN,CT,Netherlands,L,Kenya,100,"SQL, Python, Kubernetes, Data Visualization",Associate,0,Media,2024-11-25,2025-01-13,2084,7.3,Algorithmic Solutions -AI10750,Deep Learning Engineer,89374,USD,89374,MI,PT,Ireland,M,Ireland,0,"SQL, Spark, Scala, Python, Data Visualization",Master,4,Gaming,2025-04-20,2025-05-06,2047,9.6,AI Innovations -AI10751,NLP Engineer,71485,USD,71485,MI,FL,Sweden,S,France,50,"R, Scala, Data Visualization",Bachelor,4,Gaming,2024-08-21,2024-09-14,979,7.1,AI Innovations -AI10752,AI Software Engineer,173599,CAD,216999,EX,FL,Canada,M,Canada,50,"Deep Learning, SQL, PyTorch",PhD,13,Media,2025-04-16,2025-06-19,876,8.2,Cognitive Computing -AI10753,AI Product Manager,44067,USD,44067,EX,FT,India,S,India,50,"Statistics, NLP, Hadoop, Linux, Deep Learning",Bachelor,11,Consulting,2024-08-13,2024-09-30,778,9.1,Cloud AI Solutions -AI10754,AI Software Engineer,103357,EUR,87853,MI,FT,Netherlands,L,Netherlands,100,"AWS, Linux, Mathematics",PhD,3,Education,2024-08-11,2024-08-31,600,8.9,DataVision Ltd -AI10755,Data Scientist,95805,EUR,81434,MI,FL,Netherlands,M,Netherlands,50,"Linux, Hadoop, Deep Learning",PhD,2,Energy,2025-04-17,2025-06-13,2304,5,Machine Intelligence Group -AI10756,Data Scientist,286492,USD,286492,EX,FT,Norway,M,Norway,0,"R, NLP, Python, Docker",Bachelor,10,Energy,2024-06-02,2024-06-22,746,8.7,Machine Intelligence Group -AI10757,Head of AI,64481,EUR,54809,EN,FL,France,S,Italy,50,"Spark, Linux, Deep Learning, MLOps, PyTorch",Master,0,Energy,2024-03-15,2024-05-16,2443,8.7,Cloud AI Solutions -AI10758,Autonomous Systems Engineer,206801,USD,206801,EX,CT,Israel,M,Israel,100,"NLP, AWS, Scala, Azure, Python",Bachelor,18,Gaming,2024-04-28,2024-06-10,747,8.5,Autonomous Tech -AI10759,AI Specialist,161515,JPY,17766650,SE,FT,Japan,M,Canada,100,"Data Visualization, R, Scala, MLOps",Bachelor,5,Media,2024-03-20,2024-05-15,1508,9.6,Cognitive Computing -AI10760,Machine Learning Engineer,129002,USD,129002,EX,FL,Israel,S,Israel,100,"Statistics, R, Git",PhD,13,Retail,2024-09-03,2024-09-20,1993,7.1,AI Innovations -AI10761,Computer Vision Engineer,77898,CAD,97373,MI,FL,Canada,M,Canada,100,"Azure, Spark, Scala, Java, Git",Associate,2,Automotive,2024-06-21,2024-07-22,984,7.4,Quantum Computing Inc -AI10762,Data Engineer,117229,EUR,99645,SE,FL,Netherlands,S,Norway,100,"Spark, Mathematics, Linux",Master,9,Automotive,2025-04-13,2025-05-18,1881,8.1,Autonomous Tech -AI10763,Machine Learning Researcher,81371,EUR,69165,MI,FL,Netherlands,S,Netherlands,0,"SQL, R, Java, Kubernetes, Git",Associate,3,Manufacturing,2024-01-28,2024-03-02,1429,8.7,Algorithmic Solutions -AI10764,Data Engineer,72322,USD,72322,EN,PT,South Korea,L,South Korea,0,"MLOps, Azure, Python",Bachelor,1,Automotive,2024-09-06,2024-11-18,2024,7.9,Cloud AI Solutions -AI10765,ML Ops Engineer,94388,USD,94388,EX,FT,India,L,India,0,"Azure, SQL, Spark, Statistics, R",Master,12,Media,2024-06-24,2024-08-24,1661,7.3,Advanced Robotics -AI10766,ML Ops Engineer,202122,USD,202122,EX,CT,Denmark,M,Australia,50,"GCP, R, Git, TensorFlow",PhD,16,Energy,2024-09-23,2024-12-01,1479,9.8,Smart Analytics -AI10767,AI Software Engineer,86254,CAD,107818,MI,FL,Canada,L,Canada,50,"TensorFlow, NLP, Linux",PhD,4,Government,2025-04-06,2025-06-05,2494,9.7,Quantum Computing Inc -AI10768,Machine Learning Researcher,83507,SGD,108559,MI,CT,Singapore,S,Singapore,100,"Tableau, Computer Vision, GCP",Bachelor,2,Education,2024-08-19,2024-10-16,2354,6.4,Quantum Computing Inc -AI10769,Research Scientist,173027,EUR,147073,SE,CT,Germany,L,Brazil,100,"Tableau, Git, Hadoop, Spark, PyTorch",PhD,8,Education,2024-12-05,2024-12-21,690,5.5,Advanced Robotics -AI10770,Data Engineer,116393,EUR,98934,SE,FT,Germany,M,Germany,100,"MLOps, Scala, Azure, GCP, Kubernetes",Associate,8,Finance,2024-08-03,2024-09-12,2354,6.9,Cloud AI Solutions -AI10771,AI Software Engineer,99131,CHF,89218,MI,PT,Switzerland,S,Switzerland,100,"Kubernetes, Docker, Tableau, Hadoop, Java",Associate,3,Government,2024-05-07,2024-06-19,2068,6.1,Digital Transformation LLC -AI10772,Autonomous Systems Engineer,50959,USD,50959,EN,PT,Israel,M,Israel,100,"Hadoop, Kubernetes, SQL, Java, R",Bachelor,0,Consulting,2024-04-29,2024-06-16,2134,8.9,AI Innovations -AI10773,Data Analyst,107661,USD,107661,MI,CT,Denmark,S,Denmark,100,"Docker, Hadoop, Kubernetes, Python",Master,2,Finance,2025-01-03,2025-03-15,922,7.6,Cognitive Computing -AI10774,AI Specialist,174458,EUR,148289,EX,CT,Netherlands,M,Netherlands,100,"Python, Git, Kubernetes, Tableau",Bachelor,15,Media,2024-10-04,2024-11-05,1151,9,DataVision Ltd -AI10775,AI Specialist,126182,SGD,164037,SE,FT,Singapore,L,Singapore,0,"Linux, Python, Java, Git",PhD,7,Gaming,2024-03-23,2024-06-04,2236,9.7,Machine Intelligence Group -AI10776,Computer Vision Engineer,293038,CHF,263734,EX,CT,Switzerland,L,Switzerland,100,"Python, TensorFlow, R, Java, Computer Vision",PhD,13,Education,2024-05-12,2024-07-04,872,7.7,Future Systems -AI10777,AI Consultant,171137,EUR,145466,EX,CT,Austria,L,Austria,0,"Statistics, Linux, Scala",PhD,19,Gaming,2024-09-18,2024-10-26,1784,8.5,Smart Analytics -AI10778,AI Architect,106675,CHF,96008,MI,FT,Switzerland,S,Switzerland,0,"MLOps, Git, Deep Learning, Mathematics",PhD,3,Energy,2025-01-19,2025-03-01,1725,8.7,Quantum Computing Inc -AI10779,ML Ops Engineer,266812,USD,266812,EX,CT,Denmark,S,Denmark,100,"Python, NLP, Mathematics, TensorFlow",Bachelor,11,Retail,2024-09-23,2024-12-03,675,5.9,AI Innovations -AI10780,Data Scientist,85605,USD,85605,MI,FT,Finland,M,Estonia,100,"Kubernetes, Python, Computer Vision",Associate,3,Healthcare,2024-04-30,2024-06-10,2427,7.2,Smart Analytics -AI10781,NLP Engineer,201964,USD,201964,EX,CT,Israel,L,Czech Republic,0,"Scala, Python, Kubernetes, Computer Vision, SQL",Bachelor,13,Government,2024-01-29,2024-02-22,1295,7,Smart Analytics -AI10782,AI Specialist,137083,USD,137083,SE,FT,Israel,L,Israel,50,"AWS, Hadoop, Python, Scala, Spark",Bachelor,8,Gaming,2025-04-28,2025-05-18,1859,9,Neural Networks Co -AI10783,Data Analyst,75000,EUR,63750,EN,FL,Netherlands,S,Mexico,100,"R, Hadoop, Deep Learning, Java",Master,0,Finance,2024-02-24,2024-03-16,1353,7.8,AI Innovations -AI10784,Principal Data Scientist,200686,USD,200686,EX,CT,Sweden,L,Sweden,0,"Tableau, Python, NLP, TensorFlow, Scala",Associate,16,Telecommunications,2024-11-02,2024-12-31,1499,9.9,Predictive Systems -AI10785,Principal Data Scientist,129291,JPY,14222010,SE,FL,Japan,L,Japan,50,"R, Computer Vision, Azure, GCP",Associate,8,Transportation,2024-10-01,2024-10-19,1209,6.7,DeepTech Ventures -AI10786,Data Engineer,86101,EUR,73186,MI,PT,France,S,France,50,"SQL, Scala, Hadoop",PhD,4,Gaming,2024-02-20,2024-04-17,1586,5.3,Digital Transformation LLC -AI10787,AI Architect,61948,USD,61948,EN,PT,Sweden,L,Sweden,100,"SQL, PyTorch, Java, Azure",Associate,0,Education,2025-03-18,2025-05-18,1004,9.5,DeepTech Ventures -AI10788,Machine Learning Researcher,53377,USD,53377,MI,PT,China,L,China,0,"Python, Java, TensorFlow",Associate,2,Consulting,2025-01-16,2025-03-02,633,6.6,Digital Transformation LLC -AI10789,Robotics Engineer,125096,CHF,112586,MI,PT,Switzerland,S,Brazil,50,"Kubernetes, Git, Data Visualization, Python, Linux",Bachelor,3,Education,2025-01-05,2025-02-12,567,5.3,Future Systems -AI10790,AI Specialist,303813,CHF,273432,EX,FT,Switzerland,S,Switzerland,100,"SQL, Tableau, NLP, PyTorch, Mathematics",Associate,14,Government,2024-09-14,2024-09-28,1178,8.9,Quantum Computing Inc -AI10791,Machine Learning Researcher,52898,USD,52898,EN,CT,South Korea,M,South Korea,0,"Tableau, Kubernetes, Computer Vision",Bachelor,0,Healthcare,2024-11-19,2024-12-27,1927,6.2,DeepTech Ventures -AI10792,Data Scientist,91033,JPY,10013630,MI,PT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization",PhD,3,Energy,2024-07-25,2024-09-30,1290,6.4,Quantum Computing Inc -AI10793,AI Architect,87585,USD,87585,EN,FL,United States,L,United States,100,"Hadoop, NLP, Linux, GCP, SQL",Bachelor,0,Energy,2025-02-01,2025-04-12,2491,6.7,AI Innovations -AI10794,AI Architect,136182,GBP,102137,SE,FT,United Kingdom,S,United Kingdom,100,"Computer Vision, NLP, Tableau, GCP",Bachelor,9,Automotive,2024-10-18,2024-11-20,1243,5.5,Quantum Computing Inc -AI10795,Data Engineer,132993,EUR,113044,SE,FT,Germany,M,Nigeria,100,"Python, TensorFlow, PyTorch, Spark, Kubernetes",Bachelor,7,Retail,2024-10-21,2024-11-06,2207,5.7,Digital Transformation LLC -AI10796,Autonomous Systems Engineer,165196,EUR,140417,EX,FT,Austria,S,Austria,100,"Python, TensorFlow, Kubernetes, Spark, AWS",Master,13,Education,2024-01-18,2024-02-19,551,9.2,Neural Networks Co -AI10797,AI Research Scientist,171750,GBP,128813,SE,CT,United Kingdom,L,United Kingdom,0,"Spark, NLP, Kubernetes, Data Visualization, Computer Vision",Master,5,Real Estate,2024-02-01,2024-04-04,1748,6.4,Smart Analytics -AI10798,AI Research Scientist,117335,EUR,99735,SE,FT,France,M,France,100,"Linux, GCP, Spark, MLOps",Associate,7,Real Estate,2024-05-23,2024-06-19,1923,8,Neural Networks Co -AI10799,Data Scientist,137278,GBP,102959,SE,PT,United Kingdom,S,United Kingdom,0,"R, SQL, Java, Kubernetes",Bachelor,9,Gaming,2025-01-19,2025-03-29,1473,6.4,Quantum Computing Inc -AI10800,Machine Learning Engineer,147147,USD,147147,EX,CT,Sweden,M,Sweden,100,"TensorFlow, Hadoop, Tableau, Docker, GCP",Master,14,Consulting,2024-08-29,2024-10-19,1580,7.2,Machine Intelligence Group -AI10801,Data Engineer,71205,EUR,60524,MI,FT,Austria,M,China,100,"NLP, SQL, PyTorch",Master,3,Retail,2024-07-10,2024-09-12,1566,8,Smart Analytics -AI10802,Machine Learning Researcher,134161,CAD,167701,SE,PT,Canada,M,Canada,0,"Linux, Hadoop, Kubernetes, Python",Master,6,Automotive,2024-12-15,2025-01-31,2485,5.4,Algorithmic Solutions -AI10803,Autonomous Systems Engineer,82237,USD,82237,MI,PT,Sweden,S,Australia,50,"Python, TensorFlow, Statistics",PhD,4,Retail,2024-10-19,2024-11-27,1074,5.8,Predictive Systems -AI10804,Autonomous Systems Engineer,38622,USD,38622,MI,FT,India,M,India,100,"Git, Linux, AWS, TensorFlow",Associate,3,Technology,2024-05-02,2024-05-22,2055,6.7,Cloud AI Solutions -AI10805,Robotics Engineer,55769,USD,55769,EN,FL,Sweden,M,India,100,"Scala, NLP, Computer Vision",Master,1,Retail,2024-12-22,2025-02-05,2420,7.4,TechCorp Inc -AI10806,ML Ops Engineer,67249,CHF,60524,EN,FL,Switzerland,S,Switzerland,100,"Scala, Java, Deep Learning",Associate,0,Automotive,2024-02-29,2024-04-04,523,7.5,Cloud AI Solutions -AI10807,AI Specialist,42394,USD,42394,MI,CT,China,M,China,0,"MLOps, Kubernetes, Git",Associate,3,Consulting,2024-08-17,2024-09-15,2406,7.8,AI Innovations -AI10808,AI Product Manager,22136,USD,22136,EN,FL,China,S,China,100,"SQL, Mathematics, Tableau, MLOps",Bachelor,1,Consulting,2024-11-10,2025-01-08,1809,8.3,Machine Intelligence Group -AI10809,Computer Vision Engineer,134580,SGD,174954,SE,CT,Singapore,S,Turkey,0,"MLOps, Computer Vision, Python, TensorFlow, Git",Associate,7,Retail,2024-12-27,2025-03-06,1655,6.9,Machine Intelligence Group -AI10810,AI Architect,65961,CAD,82451,EN,CT,Canada,M,Canada,0,"GCP, Spark, Scala, Kubernetes",PhD,1,Education,2024-12-29,2025-03-01,1771,6.4,Neural Networks Co -AI10811,AI Product Manager,117629,USD,117629,MI,CT,Norway,M,Norway,0,"Python, Deep Learning, Computer Vision, R",Associate,4,Transportation,2024-02-08,2024-02-22,795,8.7,Future Systems -AI10812,Machine Learning Researcher,87716,EUR,74559,MI,FT,Germany,S,Finland,50,"Linux, Mathematics, GCP",PhD,3,Energy,2025-01-27,2025-03-06,986,9.1,DeepTech Ventures -AI10813,AI Research Scientist,18861,USD,18861,EN,CT,India,M,India,50,"R, Linux, SQL",Bachelor,0,Manufacturing,2025-04-07,2025-06-04,1425,7.6,Autonomous Tech -AI10814,Robotics Engineer,122512,USD,122512,MI,FT,Norway,M,Norway,0,"PyTorch, R, Linux, Hadoop",Bachelor,2,Consulting,2024-10-09,2024-10-26,2292,6.8,Autonomous Tech -AI10815,Deep Learning Engineer,180159,CAD,225199,EX,FT,Canada,L,Canada,50,"Statistics, Azure, Python, Tableau, Scala",PhD,16,Manufacturing,2024-12-09,2025-01-12,2370,5.4,Neural Networks Co -AI10816,AI Architect,168620,EUR,143327,EX,CT,Austria,L,Austria,100,"Git, PyTorch, NLP, GCP",PhD,15,Real Estate,2025-03-21,2025-05-17,658,6.1,Cloud AI Solutions -AI10817,NLP Engineer,72274,USD,72274,SE,FT,China,L,China,0,"Mathematics, Computer Vision, Statistics, SQL, Spark",PhD,5,Telecommunications,2025-04-12,2025-05-03,1316,6.9,Future Systems -AI10818,Autonomous Systems Engineer,67126,USD,67126,EN,CT,Israel,L,Israel,100,"Mathematics, Kubernetes, Azure, Java",Associate,1,Manufacturing,2024-10-13,2024-12-03,2387,6.5,Advanced Robotics -AI10819,NLP Engineer,94449,EUR,80282,MI,PT,France,L,France,50,"Azure, Scala, Linux",PhD,4,Gaming,2024-06-15,2024-08-26,2175,7.3,Autonomous Tech -AI10820,Machine Learning Engineer,112859,EUR,95930,SE,PT,France,L,France,50,"NLP, SQL, PyTorch, Data Visualization",Master,5,Energy,2024-06-22,2024-08-28,2162,8.8,Advanced Robotics -AI10821,Data Engineer,144547,SGD,187911,SE,FT,Singapore,M,Switzerland,0,"NLP, SQL, PyTorch, AWS",PhD,6,Manufacturing,2024-07-15,2024-09-15,1374,7.1,Digital Transformation LLC -AI10822,Machine Learning Researcher,80627,EUR,68533,MI,FL,Austria,M,Austria,100,"Scala, Python, Docker, Kubernetes, TensorFlow",PhD,3,Education,2024-07-23,2024-08-25,2061,6.9,DataVision Ltd -AI10823,Deep Learning Engineer,151439,EUR,128723,EX,FT,Austria,L,Austria,50,"TensorFlow, Azure, Java, Docker, Git",PhD,11,Education,2024-09-13,2024-11-11,782,9.8,Machine Intelligence Group -AI10824,ML Ops Engineer,43069,USD,43069,MI,FT,China,M,China,50,"PyTorch, Spark, SQL, GCP, AWS",Bachelor,4,Technology,2024-01-03,2024-02-16,2356,6.4,Cognitive Computing -AI10825,AI Specialist,137861,USD,137861,EX,CT,Finland,M,China,0,"NLP, Scala, SQL, PyTorch",PhD,14,Government,2024-11-04,2025-01-13,703,9,Quantum Computing Inc -AI10826,AI Product Manager,192829,USD,192829,EX,CT,Denmark,S,Denmark,0,"Java, Mathematics, Git",Bachelor,10,Real Estate,2024-08-11,2024-09-17,971,7.4,AI Innovations -AI10827,AI Specialist,108163,EUR,91939,SE,FT,Austria,M,Austria,0,"Computer Vision, Linux, PyTorch, SQL, TensorFlow",Associate,7,Gaming,2024-09-16,2024-10-10,1127,7.5,Cognitive Computing -AI10828,ML Ops Engineer,65216,EUR,55434,MI,PT,Austria,S,Colombia,50,"SQL, Linux, Azure, NLP, Git",Master,3,Education,2024-01-08,2024-02-14,2280,9.4,Future Systems -AI10829,Machine Learning Researcher,80149,CAD,100186,MI,PT,Canada,M,Canada,0,"Python, Data Visualization, Docker, Hadoop",PhD,4,Retail,2025-03-26,2025-06-05,1233,5.3,TechCorp Inc -AI10830,ML Ops Engineer,205835,SGD,267586,EX,FT,Singapore,S,Singapore,50,"TensorFlow, Git, Hadoop",Master,12,Technology,2025-04-23,2025-06-15,2294,9.8,Autonomous Tech -AI10831,Head of AI,105584,USD,105584,EN,FT,Norway,L,Norway,100,"Git, Computer Vision, Python",Bachelor,0,Finance,2024-10-21,2024-12-10,2375,8.7,Neural Networks Co -AI10832,Data Scientist,134679,USD,134679,SE,FT,South Korea,L,South Korea,100,"Spark, Data Visualization, Deep Learning, NLP, Scala",PhD,7,Transportation,2025-04-12,2025-05-02,1266,6.8,Future Systems -AI10833,Data Analyst,63653,GBP,47740,EN,FT,United Kingdom,M,China,50,"Scala, Deep Learning, NLP, PyTorch",PhD,0,Government,2024-10-06,2024-11-21,1421,7.2,Digital Transformation LLC -AI10834,AI Architect,116733,EUR,99223,MI,FT,Germany,L,Germany,100,"Hadoop, SQL, Python",Associate,3,Real Estate,2025-04-13,2025-06-15,1457,5.1,Digital Transformation LLC -AI10835,Computer Vision Engineer,171496,USD,171496,EX,FL,Norway,S,Norway,50,"Mathematics, TensorFlow, Statistics, Linux, GCP",Master,18,Finance,2024-04-22,2024-06-09,897,9.1,Quantum Computing Inc -AI10836,Machine Learning Engineer,179259,SGD,233037,EX,FT,Singapore,L,Singapore,0,"PyTorch, Java, R, Statistics, Linux",Associate,16,Technology,2024-03-23,2024-05-04,1256,7.5,Cognitive Computing -AI10837,Data Scientist,222335,USD,222335,SE,FL,Denmark,L,Denmark,0,"PyTorch, AWS, NLP, Linux",Bachelor,8,Telecommunications,2024-11-25,2024-12-14,2295,6.2,Predictive Systems -AI10838,Head of AI,182726,USD,182726,EX,CT,Norway,M,Norway,0,"TensorFlow, Hadoop, PyTorch, Data Visualization, Spark",Bachelor,17,Telecommunications,2024-06-04,2024-07-28,2321,9.9,DeepTech Ventures -AI10839,Data Scientist,59545,USD,59545,SE,CT,China,L,China,100,"R, NLP, Kubernetes, Python, Docker",PhD,5,Education,2024-12-10,2025-01-26,1221,8.6,Algorithmic Solutions -AI10840,Autonomous Systems Engineer,159516,USD,159516,MI,CT,Norway,L,Philippines,0,"Hadoop, Kubernetes, Docker",Associate,3,Gaming,2024-03-30,2024-05-29,1823,7,Machine Intelligence Group -AI10841,Robotics Engineer,61743,USD,61743,EN,CT,Ireland,S,Ireland,0,"NLP, Azure, Spark, Deep Learning, GCP",PhD,1,Education,2024-10-04,2024-12-10,1963,6.5,Quantum Computing Inc -AI10842,Head of AI,68105,USD,68105,MI,FT,Finland,M,Ireland,50,"Python, Docker, Azure",Master,2,Retail,2025-01-08,2025-03-17,1930,6.6,Digital Transformation LLC -AI10843,Data Scientist,199352,EUR,169449,EX,PT,Netherlands,L,Netherlands,0,"Python, TensorFlow, Azure, PyTorch",Associate,11,Real Estate,2024-06-17,2024-07-25,621,5.7,Algorithmic Solutions -AI10844,AI Specialist,177487,USD,177487,EX,CT,Denmark,M,Denmark,0,"Scala, Kubernetes, R",Bachelor,10,Manufacturing,2025-04-03,2025-06-14,878,8.6,Digital Transformation LLC -AI10845,Robotics Engineer,62199,EUR,52869,EN,CT,Germany,S,Russia,50,"Data Visualization, Python, Deep Learning, Computer Vision",Bachelor,0,Retail,2025-02-26,2025-05-02,1586,5.9,DataVision Ltd -AI10846,Head of AI,89631,USD,89631,EN,FL,Ireland,L,Ireland,0,"Git, R, Tableau, PyTorch",Associate,1,Education,2025-02-13,2025-04-16,1377,6.1,DataVision Ltd -AI10847,Data Engineer,73376,CAD,91720,MI,PT,Canada,S,Canada,100,"R, PyTorch, NLP",Associate,4,Media,2024-03-22,2024-05-16,1147,5.2,DeepTech Ventures -AI10848,Research Scientist,94533,USD,94533,MI,FT,Denmark,S,Denmark,50,"Linux, Scala, TensorFlow, Data Visualization, Python",Master,2,Finance,2024-01-12,2024-02-16,1115,8.8,Predictive Systems -AI10849,AI Software Engineer,193687,EUR,164634,EX,PT,Austria,M,Austria,100,"AWS, Scala, R, Tableau",Master,18,Retail,2024-04-19,2024-06-20,901,9.5,Smart Analytics -AI10850,Robotics Engineer,53931,USD,53931,SE,FL,India,L,Kenya,0,"MLOps, Python, Data Visualization, Azure",Associate,9,Retail,2024-12-30,2025-01-21,2014,8.9,TechCorp Inc -AI10851,Machine Learning Engineer,116512,USD,116512,EX,PT,China,M,China,100,"TensorFlow, SQL, MLOps, Deep Learning",PhD,19,Healthcare,2025-03-17,2025-04-24,1614,7.3,Predictive Systems -AI10852,ML Ops Engineer,99823,USD,99823,MI,PT,Denmark,S,Denmark,0,"Git, MLOps, SQL",Associate,2,Telecommunications,2024-03-29,2024-05-25,593,6.8,Future Systems -AI10853,AI Research Scientist,87180,CAD,108975,EN,FL,Canada,L,Canada,100,"GCP, Tableau, Data Visualization, PyTorch",Master,0,Real Estate,2024-04-18,2024-05-08,1341,8.3,Smart Analytics -AI10854,Data Analyst,47973,USD,47973,MI,FL,China,M,China,50,"Hadoop, PyTorch, GCP, Computer Vision",PhD,2,Telecommunications,2024-06-11,2024-08-06,776,8,Quantum Computing Inc -AI10855,Head of AI,313259,USD,313259,EX,FT,Denmark,M,Romania,100,"Python, R, Spark, Linux",Associate,10,Finance,2024-09-23,2024-11-28,2488,6.8,Predictive Systems -AI10856,AI Specialist,199489,USD,199489,SE,FT,Denmark,L,Denmark,50,"SQL, MLOps, Python, Data Visualization, Azure",Associate,8,Government,2024-02-16,2024-03-21,2398,5.9,DeepTech Ventures -AI10857,Autonomous Systems Engineer,32228,USD,32228,EN,CT,China,S,China,50,"Statistics, GCP, SQL, Python, Azure",PhD,1,Gaming,2024-02-17,2024-03-18,1063,6.4,Cloud AI Solutions -AI10858,Principal Data Scientist,113385,USD,113385,MI,PT,Denmark,M,Egypt,50,"GCP, Kubernetes, Tableau",Associate,2,Technology,2024-09-21,2024-11-22,1831,9.4,DataVision Ltd -AI10859,AI Specialist,252641,USD,252641,EX,FT,Ireland,L,Ireland,100,"Tableau, Scala, NLP, Python, Java",Master,17,Transportation,2024-08-30,2024-10-14,2301,7.9,TechCorp Inc -AI10860,Data Engineer,90555,USD,90555,MI,FT,Denmark,S,Denmark,50,"PyTorch, TensorFlow, Linux",Bachelor,4,Finance,2024-03-05,2024-04-18,1969,8.3,Algorithmic Solutions -AI10861,Research Scientist,77655,USD,77655,EN,FT,Norway,M,Norway,50,"Deep Learning, Linux, GCP, Python",Master,1,Manufacturing,2024-03-17,2024-04-15,2224,8.3,Neural Networks Co -AI10862,Data Engineer,141801,USD,141801,MI,FL,Norway,L,Thailand,0,"Spark, Git, Data Visualization, Azure",Bachelor,2,Consulting,2024-06-09,2024-08-15,937,5.9,Future Systems -AI10863,NLP Engineer,163767,USD,163767,SE,FT,Denmark,S,Denmark,100,"SQL, Hadoop, AWS",Bachelor,9,Healthcare,2024-06-13,2024-07-29,1267,6.5,TechCorp Inc -AI10864,Principal Data Scientist,59859,USD,59859,EN,FL,South Korea,L,South Korea,0,"Docker, SQL, Deep Learning, NLP",Associate,1,Healthcare,2025-02-19,2025-03-18,2208,6.4,Quantum Computing Inc -AI10865,Principal Data Scientist,90290,USD,90290,MI,PT,Israel,L,Israel,0,"Python, NLP, Kubernetes, Docker",PhD,3,Media,2024-07-02,2024-09-08,886,6.5,Cognitive Computing -AI10866,Research Scientist,114206,EUR,97075,SE,FT,France,L,France,100,"Python, Docker, Computer Vision, SQL, Kubernetes",PhD,6,Gaming,2025-01-07,2025-03-20,1772,9.1,Smart Analytics -AI10867,Head of AI,99967,USD,99967,SE,PT,Sweden,S,Sweden,50,"R, Java, AWS",Associate,6,Media,2024-12-31,2025-03-06,516,8.1,Neural Networks Co -AI10868,ML Ops Engineer,208430,USD,208430,EX,CT,Sweden,M,Sweden,100,"Azure, Data Visualization, Tableau, Git",PhD,16,Manufacturing,2025-02-18,2025-03-09,883,8.8,Neural Networks Co -AI10869,ML Ops Engineer,88936,GBP,66702,MI,CT,United Kingdom,S,United Kingdom,0,"NLP, Deep Learning, Spark, Git",Master,2,Manufacturing,2024-01-21,2024-04-02,882,7.3,Predictive Systems -AI10870,AI Specialist,172753,USD,172753,SE,CT,Norway,S,Norway,100,"Python, R, GCP, Scala, TensorFlow",Bachelor,6,Gaming,2024-06-04,2024-06-30,892,7.1,Autonomous Tech -AI10871,Robotics Engineer,172661,USD,172661,EX,CT,Finland,L,Finland,50,"SQL, Kubernetes, MLOps, Deep Learning",PhD,10,Telecommunications,2025-02-17,2025-03-03,795,9.9,TechCorp Inc -AI10872,Robotics Engineer,61484,EUR,52261,EN,FL,France,L,France,50,"Docker, SQL, AWS",Bachelor,1,Healthcare,2024-02-23,2024-04-08,2272,6.2,TechCorp Inc -AI10873,Robotics Engineer,71875,EUR,61094,EN,FT,Germany,S,Ukraine,0,"Mathematics, Tableau, Hadoop, Java",PhD,0,Telecommunications,2024-05-18,2024-06-13,1647,6.7,Cloud AI Solutions -AI10874,Data Engineer,79797,USD,79797,MI,FL,Sweden,S,Sweden,50,"Kubernetes, Python, TensorFlow, AWS, NLP",Bachelor,3,Telecommunications,2025-03-21,2025-05-08,527,9.2,Advanced Robotics -AI10875,AI Consultant,91965,USD,91965,EX,FT,India,L,India,50,"Computer Vision, Docker, Python, GCP, Linux",Bachelor,15,Manufacturing,2024-10-03,2024-11-10,1418,7.3,Smart Analytics -AI10876,Robotics Engineer,128584,EUR,109296,SE,FL,Austria,S,Austria,100,"Git, Data Visualization, SQL, Computer Vision",Master,5,Energy,2024-04-07,2024-06-11,2097,6.6,Machine Intelligence Group -AI10877,AI Product Manager,92990,USD,92990,EN,CT,United States,M,United States,100,"Kubernetes, R, GCP, Statistics",Master,0,Telecommunications,2024-12-07,2025-02-18,2231,9.9,DeepTech Ventures -AI10878,AI Architect,85862,USD,85862,EN,FT,Norway,M,Norway,0,"Hadoop, Docker, AWS, Data Visualization",PhD,1,Manufacturing,2024-05-19,2024-07-01,1306,8.6,Cloud AI Solutions -AI10879,AI Product Manager,96557,CAD,120696,MI,CT,Canada,M,Portugal,100,"Git, NLP, Tableau, Data Visualization",Bachelor,3,Telecommunications,2024-01-13,2024-03-13,1805,6.4,Digital Transformation LLC -AI10880,AI Research Scientist,136056,USD,136056,SE,CT,Sweden,S,Austria,50,"AWS, Computer Vision, Mathematics, R",Associate,8,Retail,2024-04-08,2024-05-16,884,9.7,Digital Transformation LLC -AI10881,Principal Data Scientist,191877,EUR,163095,EX,FT,Austria,L,Austria,0,"Spark, GCP, Deep Learning, Scala",Bachelor,15,Transportation,2024-07-08,2024-07-29,2481,7.8,DeepTech Ventures -AI10882,Deep Learning Engineer,58995,USD,58995,EN,CT,Sweden,L,Portugal,0,"Linux, Spark, R",Associate,1,Telecommunications,2025-03-01,2025-03-26,1543,9.8,Smart Analytics -AI10883,Robotics Engineer,171771,USD,171771,SE,FL,Denmark,L,Denmark,50,"AWS, Computer Vision, SQL, Spark",Master,7,Finance,2024-09-14,2024-10-08,1457,9.4,Cognitive Computing -AI10884,AI Software Engineer,124350,USD,124350,SE,PT,United States,M,Netherlands,100,"SQL, Deep Learning, NLP",Master,7,Media,2024-04-04,2024-05-14,1461,9,Autonomous Tech -AI10885,Autonomous Systems Engineer,264027,USD,264027,EX,FT,United States,S,Indonesia,50,"Scala, R, Data Visualization, Python, TensorFlow",Associate,13,Transportation,2024-08-31,2024-09-20,1916,6.7,Future Systems -AI10886,Machine Learning Engineer,254261,EUR,216122,EX,PT,Austria,L,Belgium,50,"Git, TensorFlow, Mathematics",Associate,18,Manufacturing,2024-03-12,2024-05-19,965,5.7,Algorithmic Solutions -AI10887,Head of AI,95509,GBP,71632,MI,FL,United Kingdom,L,United Kingdom,0,"Hadoop, GCP, Data Visualization, Statistics, MLOps",Master,4,Real Estate,2024-11-03,2024-11-24,1264,7.5,DataVision Ltd -AI10888,ML Ops Engineer,144757,CAD,180946,SE,FT,Canada,L,Canada,100,"Hadoop, TensorFlow, NLP",PhD,9,Government,2024-07-08,2024-08-09,1528,5.7,Quantum Computing Inc -AI10889,AI Specialist,80856,USD,80856,EN,FL,Norway,S,Norway,50,"NLP, Scala, Java",Bachelor,0,Energy,2024-11-29,2025-01-14,2142,8.8,DeepTech Ventures -AI10890,Data Engineer,170023,SGD,221030,EX,CT,Singapore,S,Singapore,50,"Mathematics, NLP, Git, Computer Vision, Deep Learning",Bachelor,14,Technology,2024-03-18,2024-05-29,1846,9.5,DataVision Ltd -AI10891,Data Scientist,67573,USD,67573,MI,PT,Israel,S,Kenya,100,"Python, SQL, Java, MLOps",Master,2,Transportation,2024-01-08,2024-03-12,1770,8.9,Cognitive Computing -AI10892,Deep Learning Engineer,43295,USD,43295,MI,FL,India,L,India,0,"Kubernetes, Azure, SQL, Computer Vision",Master,4,Finance,2024-07-25,2024-09-01,1342,7.4,DataVision Ltd -AI10893,Principal Data Scientist,138506,CAD,173133,SE,CT,Canada,L,Canada,0,"Java, Git, Tableau, Kubernetes, R",Bachelor,5,Consulting,2024-08-01,2024-09-17,971,9.6,Cognitive Computing -AI10894,AI Specialist,83927,SGD,109105,EN,FL,Singapore,L,Mexico,0,"Tableau, Kubernetes, Linux",PhD,0,Manufacturing,2024-08-25,2024-11-01,2240,9.8,Cloud AI Solutions -AI10895,AI Product Manager,77484,GBP,58113,EN,FT,United Kingdom,M,United Kingdom,50,"Spark, GCP, Scala, Docker, Hadoop",Bachelor,1,Retail,2025-04-29,2025-05-22,1818,8.7,DeepTech Ventures -AI10896,Deep Learning Engineer,149388,USD,149388,SE,FL,Ireland,M,Ireland,100,"Tableau, Azure, PyTorch, NLP, SQL",PhD,6,Government,2024-06-07,2024-07-30,855,9.9,Autonomous Tech -AI10897,AI Specialist,220434,EUR,187369,EX,PT,Netherlands,S,Netherlands,50,"Kubernetes, Git, Data Visualization, Python",PhD,14,Retail,2024-04-25,2024-05-14,1114,8.6,DataVision Ltd -AI10898,Head of AI,79212,GBP,59409,EN,FL,United Kingdom,M,Romania,100,"AWS, Data Visualization, Git",Associate,1,Finance,2025-03-13,2025-05-04,1636,5.9,Algorithmic Solutions -AI10899,Machine Learning Researcher,169031,EUR,143676,SE,FL,Germany,L,Germany,50,"Linux, Python, NLP, Java",Bachelor,7,Automotive,2024-10-07,2024-11-23,2421,9.2,Advanced Robotics -AI10900,AI Product Manager,165582,USD,165582,SE,CT,Norway,L,Norway,50,"Scala, Data Visualization, Python",PhD,8,Education,2024-02-12,2024-03-04,1890,6.5,Digital Transformation LLC -AI10901,NLP Engineer,323522,CHF,291170,EX,FL,Switzerland,L,Switzerland,100,"Docker, MLOps, Kubernetes, GCP",Bachelor,18,Energy,2025-04-27,2025-05-15,1564,10,Cognitive Computing -AI10902,ML Ops Engineer,89783,USD,89783,EN,FL,United States,L,United States,100,"Azure, MLOps, Statistics",Master,1,Gaming,2024-07-29,2024-10-08,1060,6.7,Advanced Robotics -AI10903,Head of AI,172737,USD,172737,EX,PT,Denmark,S,Denmark,50,"AWS, Linux, Mathematics, Data Visualization, NLP",Master,13,Telecommunications,2025-01-29,2025-03-10,1381,8.9,Algorithmic Solutions -AI10904,Data Scientist,118389,USD,118389,SE,FT,Ireland,M,Ireland,50,"GCP, Linux, SQL, Kubernetes",Associate,5,Consulting,2025-03-18,2025-05-12,1971,6.7,Algorithmic Solutions -AI10905,AI Research Scientist,77597,GBP,58198,EN,FL,United Kingdom,M,United Kingdom,100,"Java, Deep Learning, R, Docker",Associate,0,Gaming,2024-08-11,2024-09-03,2061,9.5,Advanced Robotics -AI10906,Data Scientist,139624,SGD,181511,SE,PT,Singapore,S,Singapore,50,"Python, TensorFlow, Statistics",Associate,7,Media,2024-10-02,2024-11-07,1774,9.6,Smart Analytics -AI10907,Data Scientist,118666,SGD,154266,SE,PT,Singapore,M,Singapore,100,"Linux, Scala, Data Visualization, Kubernetes",Master,5,Media,2025-01-14,2025-01-28,964,5.3,Autonomous Tech -AI10908,Data Scientist,74287,EUR,63144,EN,CT,Netherlands,S,Russia,100,"SQL, Kubernetes, Data Visualization, Deep Learning",PhD,1,Education,2024-04-04,2024-05-24,1947,7.1,DataVision Ltd -AI10909,AI Product Manager,208649,GBP,156487,EX,CT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Java",Associate,13,Finance,2024-12-13,2025-01-16,1064,8.1,Machine Intelligence Group -AI10910,Data Analyst,123996,EUR,105397,SE,FL,France,L,United Kingdom,0,"Kubernetes, Scala, Spark, PyTorch, Java",Bachelor,8,Healthcare,2024-04-07,2024-05-19,1805,8,Quantum Computing Inc -AI10911,Data Analyst,229871,EUR,195390,EX,PT,Germany,L,Germany,50,"PyTorch, Deep Learning, Computer Vision",PhD,15,Healthcare,2025-03-02,2025-04-05,2477,9.5,Cloud AI Solutions -AI10912,Machine Learning Engineer,92771,SGD,120602,MI,FL,Singapore,S,Singapore,50,"Docker, SQL, Azure, TensorFlow",Associate,2,Automotive,2024-08-02,2024-10-14,910,7.1,Autonomous Tech -AI10913,Data Scientist,31230,USD,31230,EN,FL,China,M,Vietnam,100,"Azure, Python, Data Visualization, R, Statistics",Bachelor,1,Consulting,2025-03-26,2025-05-15,1660,8.5,TechCorp Inc -AI10914,AI Specialist,120411,USD,120411,SE,CT,Israel,S,Turkey,50,"Python, AWS, Linux, Git",Associate,7,Energy,2025-02-02,2025-03-25,2299,6.3,Autonomous Tech -AI10915,Computer Vision Engineer,219663,EUR,186714,EX,FT,Germany,S,Germany,100,"Python, R, TensorFlow, Docker",Bachelor,16,Automotive,2024-01-05,2024-02-25,1906,7.1,DeepTech Ventures -AI10916,Research Scientist,62748,EUR,53336,MI,FT,Austria,S,Austria,50,"Tableau, Mathematics, Python, SQL, AWS",Master,3,Real Estate,2024-07-16,2024-08-12,1479,5.8,TechCorp Inc -AI10917,AI Software Engineer,60299,GBP,45224,EN,CT,United Kingdom,S,United Kingdom,50,"SQL, Data Visualization, PyTorch",Master,1,Education,2024-12-06,2025-02-05,1779,7.8,Smart Analytics -AI10918,Head of AI,266091,EUR,226177,EX,PT,Netherlands,M,Netherlands,50,"NLP, Kubernetes, Scala, Statistics, TensorFlow",Associate,13,Media,2025-04-02,2025-04-27,990,5.7,Algorithmic Solutions -AI10919,AI Specialist,252940,AUD,341469,EX,FT,Australia,L,Austria,0,"SQL, GCP, Python, Hadoop",PhD,16,Healthcare,2025-03-07,2025-04-07,2229,8.7,Algorithmic Solutions -AI10920,Principal Data Scientist,100217,JPY,11023870,MI,FT,Japan,L,New Zealand,50,"Scala, SQL, Git, Deep Learning",Associate,3,Gaming,2025-04-25,2025-06-30,1851,6.8,Neural Networks Co -AI10921,Deep Learning Engineer,197325,USD,197325,EX,FL,United States,S,United States,100,"Scala, Java, R",PhD,14,Manufacturing,2024-03-26,2024-06-06,1769,5,Cognitive Computing -AI10922,Head of AI,23752,USD,23752,EN,FT,India,M,India,0,"SQL, Linux, MLOps, GCP",Master,0,Technology,2024-10-22,2024-12-11,1459,6.8,Machine Intelligence Group -AI10923,Machine Learning Researcher,61586,GBP,46190,EN,FL,United Kingdom,S,United Kingdom,50,"Kubernetes, Tableau, Python, Docker, Java",Associate,0,Telecommunications,2024-10-21,2024-11-22,970,9.3,TechCorp Inc -AI10924,AI Software Engineer,32487,USD,32487,MI,FL,India,S,Latvia,100,"SQL, Git, R",Associate,2,Energy,2024-07-23,2024-09-21,2404,7,DataVision Ltd -AI10925,Deep Learning Engineer,71388,USD,71388,EN,FT,Ireland,S,Ireland,100,"SQL, Scala, Statistics, NLP",Associate,1,Transportation,2024-03-15,2024-04-02,2180,8,DataVision Ltd -AI10926,NLP Engineer,218351,CHF,196516,SE,FL,Switzerland,L,Switzerland,50,"SQL, Hadoop, Deep Learning",Bachelor,8,Government,2024-08-26,2024-09-23,1062,9.4,DataVision Ltd -AI10927,AI Specialist,166329,GBP,124747,EX,PT,United Kingdom,L,United Kingdom,100,"Statistics, Git, PyTorch",Master,14,Retail,2024-05-06,2024-06-02,1104,9.6,AI Innovations -AI10928,AI Software Engineer,75044,GBP,56283,EN,FL,United Kingdom,S,United Kingdom,100,"Data Visualization, Azure, Java, MLOps, Scala",Master,0,Gaming,2024-12-01,2024-12-15,933,8.6,Cloud AI Solutions -AI10929,AI Consultant,206933,SGD,269013,EX,CT,Singapore,L,Switzerland,0,"Docker, Python, GCP",Bachelor,19,Real Estate,2025-03-11,2025-04-07,1194,7.7,Smart Analytics -AI10930,Machine Learning Engineer,195026,EUR,165772,EX,CT,Germany,M,Germany,100,"SQL, Spark, AWS",Master,10,Media,2025-03-18,2025-05-15,1217,7.7,Machine Intelligence Group -AI10931,Head of AI,104858,USD,104858,SE,PT,Israel,S,Israel,100,"Python, TensorFlow, AWS, PyTorch",PhD,8,Transportation,2024-07-30,2024-09-27,1048,7.3,Future Systems -AI10932,Autonomous Systems Engineer,118890,USD,118890,SE,CT,Israel,S,Israel,0,"Scala, MLOps, Tableau, Kubernetes, Mathematics",Bachelor,6,Retail,2024-08-31,2024-10-02,1165,8.9,Quantum Computing Inc -AI10933,Deep Learning Engineer,87321,EUR,74223,MI,CT,Germany,L,Germany,50,"Git, Computer Vision, Java",PhD,3,Healthcare,2024-01-11,2024-03-01,2443,10,Smart Analytics -AI10934,AI Product Manager,104724,USD,104724,SE,CT,Ireland,S,Ireland,100,"Linux, Data Visualization, Tableau, MLOps, Kubernetes",PhD,9,Gaming,2024-06-02,2024-06-24,1259,8.3,Cloud AI Solutions -AI10935,AI Research Scientist,65970,EUR,56075,MI,FL,Austria,S,Austria,50,"PyTorch, Python, Linux, Scala",PhD,3,Energy,2024-07-01,2024-09-10,2200,5.2,AI Innovations -AI10936,AI Specialist,102652,USD,102652,SE,CT,South Korea,M,South Korea,100,"Data Visualization, Mathematics, GCP",Bachelor,5,Consulting,2024-04-02,2024-04-17,927,6.8,Quantum Computing Inc -AI10937,Data Scientist,120871,EUR,102740,SE,PT,Netherlands,M,Netherlands,100,"Linux, Hadoop, AWS, Data Visualization, GCP",Associate,6,Healthcare,2024-07-24,2024-10-01,1764,7.3,DataVision Ltd -AI10938,NLP Engineer,91506,JPY,10065660,EN,FT,Japan,L,Japan,100,"SQL, Linux, Mathematics",PhD,1,Energy,2025-03-16,2025-04-29,1817,7,Future Systems -AI10939,Data Scientist,156607,CAD,195759,EX,PT,Canada,L,Canada,0,"Spark, Python, Docker",PhD,12,Energy,2024-04-24,2024-06-02,1016,6.4,Autonomous Tech -AI10940,Computer Vision Engineer,114380,USD,114380,MI,FT,Israel,L,Israel,100,"R, GCP, PyTorch",Associate,4,Retail,2025-01-01,2025-02-01,646,7.1,Smart Analytics -AI10941,NLP Engineer,47258,EUR,40169,EN,FT,Austria,S,Austria,0,"Python, Scala, Computer Vision",Associate,1,Gaming,2024-10-28,2024-12-15,1295,6.9,Smart Analytics -AI10942,Computer Vision Engineer,63033,SGD,81943,EN,PT,Singapore,S,Singapore,100,"Python, GCP, Computer Vision, Azure",Associate,1,Retail,2024-11-23,2025-01-01,961,9.4,Machine Intelligence Group -AI10943,Data Analyst,51890,USD,51890,EX,CT,India,S,India,50,"Scala, Computer Vision, Kubernetes, GCP",Master,18,Finance,2025-01-31,2025-04-02,1200,9.1,Advanced Robotics -AI10944,NLP Engineer,114029,EUR,96925,MI,FL,France,L,Philippines,100,"GCP, Java, NLP",PhD,4,Technology,2025-02-07,2025-04-13,2083,5.4,Autonomous Tech -AI10945,Data Engineer,97612,USD,97612,MI,PT,Ireland,L,Ireland,100,"PyTorch, Kubernetes, GCP, NLP",PhD,4,Retail,2024-12-29,2025-01-20,912,6.7,TechCorp Inc -AI10946,Research Scientist,99042,EUR,84186,MI,PT,France,M,France,100,"Docker, Hadoop, Computer Vision",Bachelor,4,Government,2024-01-17,2024-03-19,1864,6,Predictive Systems -AI10947,Deep Learning Engineer,143114,EUR,121647,SE,FL,Netherlands,L,Netherlands,0,"Git, Python, Kubernetes",Master,8,Government,2024-08-07,2024-09-02,592,9.3,TechCorp Inc -AI10948,AI Consultant,246283,USD,246283,EX,CT,Norway,S,Norway,0,"R, PyTorch, Mathematics, TensorFlow",Bachelor,13,Healthcare,2025-01-06,2025-02-26,1469,7.7,Algorithmic Solutions -AI10949,NLP Engineer,83037,JPY,9134070,MI,PT,Japan,M,Germany,50,"Python, Data Visualization, TensorFlow, Hadoop",Associate,3,Government,2024-05-28,2024-07-26,1776,8.6,Digital Transformation LLC -AI10950,NLP Engineer,64015,USD,64015,EN,PT,Sweden,L,Sweden,0,"Python, Kubernetes, Docker",Bachelor,1,Technology,2024-10-01,2024-10-20,1023,7.3,AI Innovations -AI10951,Data Scientist,121642,USD,121642,EX,CT,Finland,S,Finland,0,"Kubernetes, NLP, Python, Mathematics",Associate,17,Education,2024-03-26,2024-05-23,549,10,Autonomous Tech -AI10952,AI Software Engineer,76327,GBP,57245,EN,PT,United Kingdom,S,Indonesia,50,"Tableau, GCP, Git, Azure, Kubernetes",Associate,0,Energy,2024-05-17,2024-07-19,1246,8.7,DeepTech Ventures -AI10953,Robotics Engineer,165749,EUR,140887,EX,CT,Austria,S,Austria,0,"Hadoop, Python, TensorFlow",Bachelor,16,Technology,2024-01-19,2024-02-07,1686,6.2,Cloud AI Solutions -AI10954,Data Analyst,137659,USD,137659,SE,FL,Sweden,L,Sweden,100,"Statistics, Docker, TensorFlow",PhD,7,Energy,2025-04-18,2025-06-08,1577,7.6,Machine Intelligence Group -AI10955,AI Specialist,105624,GBP,79218,MI,FL,United Kingdom,M,United Kingdom,50,"GCP, R, Azure, Linux",Master,4,Healthcare,2024-08-18,2024-10-30,641,8.8,TechCorp Inc -AI10956,Autonomous Systems Engineer,146967,USD,146967,MI,CT,Norway,L,Norway,100,"Spark, GCP, Hadoop",Bachelor,4,Technology,2024-04-11,2024-05-09,2256,8.4,Smart Analytics -AI10957,Machine Learning Engineer,76091,USD,76091,EN,PT,Ireland,L,Ireland,100,"Docker, Computer Vision, Git, R, GCP",Bachelor,1,Government,2024-02-08,2024-04-05,1762,5.2,Machine Intelligence Group -AI10958,Machine Learning Researcher,79160,USD,79160,EN,FT,Denmark,M,Luxembourg,50,"Kubernetes, Python, TensorFlow",Bachelor,0,Transportation,2024-01-18,2024-03-14,2020,7.1,Cloud AI Solutions -AI10959,Robotics Engineer,176142,CHF,158528,MI,FT,Switzerland,L,Luxembourg,0,"AWS, R, Data Visualization",PhD,3,Education,2024-03-24,2024-04-10,1000,6.3,Cloud AI Solutions -AI10960,Computer Vision Engineer,85509,EUR,72683,MI,PT,Germany,S,Germany,100,"Data Visualization, MLOps, Kubernetes, SQL, Python",Associate,3,Education,2024-11-01,2025-01-06,610,9.4,Cloud AI Solutions -AI10961,Data Analyst,66853,USD,66853,MI,FL,Finland,S,Finland,100,"R, Mathematics, Linux",PhD,4,Finance,2024-08-02,2024-08-21,1589,5.9,Machine Intelligence Group -AI10962,Research Scientist,26651,USD,26651,MI,FL,India,S,India,100,"Java, SQL, Azure, Git, GCP",Bachelor,4,Transportation,2024-01-18,2024-02-23,1808,8.2,Digital Transformation LLC -AI10963,Machine Learning Engineer,60811,USD,60811,EN,FT,United States,M,United States,0,"MLOps, Tableau, Scala, Hadoop, AWS",Bachelor,0,Gaming,2024-02-14,2024-03-30,997,8.2,Future Systems -AI10964,Data Engineer,65850,USD,65850,EN,CT,South Korea,M,South Korea,0,"Hadoop, GCP, Tableau",Associate,0,Retail,2024-12-05,2025-02-09,580,5.1,Future Systems -AI10965,Deep Learning Engineer,159852,EUR,135874,EX,FL,France,M,France,100,"Kubernetes, Hadoop, Python, AWS",Bachelor,12,Technology,2024-02-26,2024-04-15,694,9,Cloud AI Solutions -AI10966,AI Software Engineer,117072,CHF,105365,MI,CT,Switzerland,M,Luxembourg,100,"Data Visualization, TensorFlow, Python",Master,4,Education,2024-02-01,2024-04-06,1043,9,TechCorp Inc -AI10967,Head of AI,73513,USD,73513,EX,FT,India,S,India,50,"Kubernetes, Python, TensorFlow",Bachelor,10,Consulting,2024-12-31,2025-03-03,2106,5.9,AI Innovations -AI10968,AI Specialist,158422,EUR,134659,EX,PT,Germany,M,Germany,50,"Python, Mathematics, TensorFlow",PhD,19,Consulting,2024-06-19,2024-08-12,732,7.7,Quantum Computing Inc -AI10969,AI Consultant,52063,USD,52063,EN,PT,South Korea,M,South Korea,0,"Computer Vision, MLOps, Mathematics, Docker",PhD,1,Finance,2025-04-04,2025-05-02,2052,5.9,TechCorp Inc -AI10970,AI Architect,87999,USD,87999,EN,PT,Norway,L,Norway,50,"Azure, Python, Computer Vision",PhD,0,Consulting,2025-01-25,2025-03-04,2011,9.3,Cognitive Computing -AI10971,Robotics Engineer,65735,AUD,88742,EN,FL,Australia,S,Vietnam,100,"Scala, Git, Statistics",Associate,1,Real Estate,2025-02-02,2025-03-04,776,9.9,AI Innovations -AI10972,Machine Learning Researcher,79748,USD,79748,EX,FT,India,M,India,100,"NLP, Python, Mathematics, GCP",Master,17,Education,2025-02-02,2025-03-10,998,9.9,DeepTech Ventures -AI10973,Machine Learning Engineer,153047,CHF,137742,MI,FT,Switzerland,L,New Zealand,0,"SQL, Python, R",Master,3,Retail,2024-07-25,2024-09-26,1468,5.9,Future Systems -AI10974,Data Analyst,82660,GBP,61995,EN,PT,United Kingdom,L,United Kingdom,100,"Java, R, Mathematics",Bachelor,1,Retail,2024-09-09,2024-10-07,599,9.5,Smart Analytics -AI10975,Computer Vision Engineer,245036,USD,245036,EX,CT,United States,S,United States,100,"Git, Linux, Kubernetes, Deep Learning, NLP",Bachelor,17,Technology,2024-05-15,2024-07-22,804,9.9,Smart Analytics -AI10976,AI Research Scientist,223802,AUD,302133,EX,PT,Australia,S,Australia,100,"AWS, Kubernetes, Computer Vision",Bachelor,11,Energy,2024-11-04,2025-01-10,964,7.1,Cloud AI Solutions -AI10977,Machine Learning Researcher,83891,AUD,113253,MI,FL,Australia,M,Australia,50,"Git, MLOps, Scala, GCP, Spark",Master,3,Real Estate,2025-02-23,2025-04-21,852,6.8,Advanced Robotics -AI10978,Machine Learning Researcher,98442,GBP,73832,SE,PT,United Kingdom,S,United Kingdom,50,"SQL, Git, TensorFlow, Python",PhD,5,Education,2024-03-31,2024-04-21,1604,9.9,Advanced Robotics -AI10979,NLP Engineer,128077,JPY,14088470,SE,FL,Japan,M,Japan,100,"TensorFlow, Python, MLOps, Git",Associate,6,Energy,2024-03-06,2024-04-22,1539,5.5,TechCorp Inc -AI10980,Data Scientist,186264,USD,186264,EX,FT,Sweden,M,Sweden,0,"SQL, Computer Vision, Scala",Bachelor,15,Finance,2024-07-16,2024-09-10,612,7.4,Advanced Robotics -AI10981,AI Research Scientist,110728,USD,110728,MI,CT,Norway,M,Norway,0,"TensorFlow, Python, Kubernetes, R",PhD,3,Technology,2025-03-23,2025-04-11,1637,8.5,Algorithmic Solutions -AI10982,Robotics Engineer,215988,USD,215988,EX,PT,Denmark,M,Denmark,0,"PyTorch, Deep Learning, NLP, Git",Associate,15,Manufacturing,2024-06-09,2024-06-23,508,9.8,Cognitive Computing -AI10983,Autonomous Systems Engineer,125459,USD,125459,SE,CT,Israel,S,Indonesia,50,"Python, Scala, Kubernetes, Deep Learning, AWS",PhD,6,Automotive,2024-03-23,2024-05-26,1423,7.2,AI Innovations -AI10984,ML Ops Engineer,247115,USD,247115,EX,FL,United States,L,United States,0,"TensorFlow, R, Deep Learning, GCP, Git",Associate,19,Consulting,2024-12-03,2025-01-24,1894,5.5,Digital Transformation LLC -AI10985,Machine Learning Engineer,311593,USD,311593,EX,FL,Norway,L,Norway,0,"Linux, Python, TensorFlow",Master,16,Finance,2025-01-23,2025-03-08,1712,7.9,Future Systems -AI10986,Data Analyst,129554,USD,129554,EX,FT,China,L,China,0,"Data Visualization, Kubernetes, Java",Associate,18,Consulting,2025-03-23,2025-05-28,705,9.2,Cloud AI Solutions -AI10987,Deep Learning Engineer,284164,USD,284164,EX,PT,Norway,L,Norway,100,"R, Statistics, SQL, Python, Linux",Master,14,Telecommunications,2024-02-03,2024-02-28,2259,6.5,Cognitive Computing -AI10988,Deep Learning Engineer,144657,EUR,122958,SE,FT,Netherlands,L,Netherlands,0,"SQL, Statistics, Linux",Master,5,Government,2025-02-23,2025-04-30,586,5.7,Predictive Systems -AI10989,Computer Vision Engineer,178156,CAD,222695,EX,FT,Canada,M,Canada,0,"Kubernetes, SQL, Azure, Hadoop",PhD,19,Automotive,2025-02-03,2025-03-22,1702,7.2,Neural Networks Co -AI10990,Data Scientist,86173,CAD,107716,MI,FL,Canada,M,Canada,100,"MLOps, Git, PyTorch, Mathematics",Associate,2,Healthcare,2024-08-09,2024-10-03,1035,8.4,Cloud AI Solutions -AI10991,Data Scientist,106280,SGD,138164,MI,PT,Singapore,L,Czech Republic,100,"Java, SQL, Kubernetes, AWS",Associate,2,Energy,2024-11-26,2025-01-07,779,5.8,TechCorp Inc -AI10992,Data Scientist,80053,AUD,108072,MI,FL,Australia,M,Australia,50,"Deep Learning, Linux, MLOps, SQL, Kubernetes",Master,4,Healthcare,2025-03-05,2025-03-20,1525,9.8,TechCorp Inc -AI10993,AI Architect,91642,CAD,114553,MI,CT,Canada,M,Canada,50,"Git, Docker, Spark, R, Mathematics",Master,2,Real Estate,2024-11-17,2024-12-09,1599,5.7,AI Innovations -AI10994,Data Analyst,72487,EUR,61614,EN,FL,Germany,S,Netherlands,0,"PyTorch, Tableau, Mathematics, MLOps",PhD,1,Education,2025-02-01,2025-02-19,2284,6,Future Systems -AI10995,Data Analyst,40355,USD,40355,EN,FT,China,L,Denmark,0,"Python, TensorFlow, PyTorch, AWS",PhD,0,Gaming,2024-12-21,2025-01-26,1733,5.1,Cognitive Computing -AI10996,AI Architect,185648,USD,185648,EX,FL,Denmark,M,Denmark,50,"Tableau, TensorFlow, Git, Statistics",PhD,18,Education,2024-11-08,2025-01-11,711,7.2,Quantum Computing Inc -AI10997,NLP Engineer,177709,USD,177709,EX,PT,Ireland,M,Ireland,100,"AWS, MLOps, Deep Learning",Master,13,Real Estate,2024-04-13,2024-06-02,1165,6.5,Predictive Systems -AI10998,Computer Vision Engineer,60113,EUR,51096,EN,CT,Netherlands,S,Netherlands,100,"AWS, Data Visualization, Linux, TensorFlow",Associate,0,Consulting,2024-12-01,2025-01-06,1214,6.7,AI Innovations -AI10999,Data Engineer,170719,USD,170719,EX,FL,Norway,S,Norway,100,"Hadoop, Python, TensorFlow",PhD,13,Consulting,2025-01-31,2025-04-04,2355,6.2,AI Innovations -AI11000,Principal Data Scientist,94395,USD,94395,MI,CT,South Korea,L,South Korea,0,"R, SQL, Kubernetes",PhD,4,Telecommunications,2024-11-11,2024-12-13,1904,6.7,Digital Transformation LLC -AI11001,Robotics Engineer,170094,EUR,144580,EX,FL,Netherlands,L,Netherlands,50,"Kubernetes, Git, PyTorch, SQL, Deep Learning",Associate,12,Automotive,2025-02-25,2025-04-07,1931,9,Predictive Systems -AI11002,Robotics Engineer,44187,USD,44187,MI,FT,China,S,China,100,"TensorFlow, Docker, Scala",Associate,4,Manufacturing,2025-04-07,2025-05-06,1790,5.4,Predictive Systems -AI11003,NLP Engineer,199463,USD,199463,EX,FT,Ireland,S,Chile,0,"Tableau, TensorFlow, Linux, Python",Bachelor,16,Manufacturing,2024-10-06,2024-11-13,833,6.1,TechCorp Inc -AI11004,Machine Learning Researcher,103266,CAD,129083,SE,PT,Canada,M,Canada,100,"Python, Kubernetes, Docker",Master,9,Education,2024-10-12,2024-12-17,1567,8.5,Quantum Computing Inc -AI11005,Head of AI,74247,EUR,63110,MI,PT,Austria,M,Poland,100,"SQL, Deep Learning, Python, Hadoop",PhD,2,Finance,2025-03-10,2025-04-26,1921,7.6,DeepTech Ventures -AI11006,Robotics Engineer,267617,GBP,200713,EX,FL,United Kingdom,M,Egypt,100,"Python, TensorFlow, PyTorch, Tableau, Docker",Associate,12,Technology,2024-02-04,2024-04-16,1058,8.6,Future Systems -AI11007,AI Product Manager,170750,EUR,145138,SE,PT,Netherlands,L,Hungary,0,"Python, Data Visualization, MLOps, Hadoop, AWS",Associate,5,Finance,2024-07-14,2024-08-11,1811,7.5,Predictive Systems -AI11008,AI Architect,151644,EUR,128897,EX,FT,Germany,S,Germany,0,"TensorFlow, Tableau, GCP, PyTorch, Statistics",Associate,10,Automotive,2025-02-22,2025-04-29,1657,6.4,DeepTech Ventures -AI11009,Head of AI,19668,USD,19668,EN,CT,India,M,India,50,"MLOps, Scala, GCP, AWS, Kubernetes",Bachelor,0,Real Estate,2024-08-28,2024-09-13,1898,7.2,Advanced Robotics -AI11010,AI Specialist,133233,USD,133233,SE,FT,Sweden,M,Sweden,50,"SQL, PyTorch, Linux, Deep Learning",Master,8,Manufacturing,2024-08-20,2024-10-19,1836,6.2,Advanced Robotics -AI11011,AI Consultant,62844,USD,62844,EN,PT,Ireland,S,Ireland,50,"Git, PyTorch, TensorFlow, Docker",Bachelor,1,Media,2024-03-26,2024-05-17,987,8.8,Machine Intelligence Group -AI11012,Data Scientist,144621,USD,144621,SE,FL,Norway,S,Norway,50,"Spark, Kubernetes, Computer Vision, AWS",Associate,6,Transportation,2024-10-31,2024-11-29,2429,5.4,Digital Transformation LLC -AI11013,AI Product Manager,121548,USD,121548,SE,FT,United States,M,United States,50,"Hadoop, Deep Learning, Kubernetes, Spark, Python",Master,6,Real Estate,2024-11-28,2025-01-20,959,6.8,Algorithmic Solutions -AI11014,ML Ops Engineer,355399,CHF,319859,EX,FT,Switzerland,M,Switzerland,0,"GCP, Git, Computer Vision",Bachelor,14,Technology,2024-07-25,2024-08-29,1808,8.8,Digital Transformation LLC -AI11015,AI Research Scientist,261652,USD,261652,EX,PT,Norway,S,Norway,0,"SQL, AWS, GCP",Bachelor,10,Transportation,2024-12-24,2025-02-12,536,6,Quantum Computing Inc -AI11016,Principal Data Scientist,135239,USD,135239,SE,FL,United States,M,United States,0,"Python, Data Visualization, Hadoop, Scala",Bachelor,9,Automotive,2024-10-13,2024-11-21,941,5.3,AI Innovations -AI11017,AI Research Scientist,136136,USD,136136,SE,FL,United States,M,United States,0,"GCP, Data Visualization, PyTorch, R, Spark",Master,7,Real Estate,2024-02-17,2024-03-04,2020,9.3,Predictive Systems -AI11018,Computer Vision Engineer,162399,USD,162399,EX,FT,Ireland,S,Ireland,100,"R, GCP, MLOps, Python",Associate,16,Media,2025-04-10,2025-05-26,1549,5.8,DataVision Ltd -AI11019,Data Scientist,250763,GBP,188072,EX,FL,United Kingdom,L,Czech Republic,100,"Data Visualization, TensorFlow, NLP, Statistics",Associate,12,Transportation,2024-09-21,2024-10-27,1830,7.4,Cognitive Computing -AI11020,Deep Learning Engineer,63767,EUR,54202,EN,PT,Germany,S,Germany,50,"Hadoop, Data Visualization, GCP",Master,1,Consulting,2025-04-17,2025-05-08,1518,9.1,Cloud AI Solutions -AI11021,Research Scientist,74764,EUR,63549,MI,FL,Austria,M,Austria,50,"Python, TensorFlow, NLP",Master,2,Telecommunications,2024-12-05,2025-02-06,2011,5.2,Quantum Computing Inc -AI11022,Research Scientist,46031,USD,46031,EN,FT,Israel,S,Hungary,50,"Kubernetes, Java, Scala",PhD,1,Transportation,2024-10-28,2024-12-28,648,8.6,Cognitive Computing -AI11023,AI Consultant,52060,EUR,44251,EN,FL,Austria,M,Austria,50,"R, Hadoop, SQL",PhD,0,Automotive,2024-12-10,2025-01-19,1945,5.2,DataVision Ltd -AI11024,Autonomous Systems Engineer,138305,EUR,117559,SE,CT,France,M,France,50,"Java, Hadoop, NLP, Computer Vision",PhD,8,Consulting,2025-01-09,2025-02-16,1084,5.7,AI Innovations -AI11025,AI Product Manager,82393,USD,82393,MI,PT,United States,S,United States,100,"Docker, PyTorch, R, Azure",Bachelor,2,Government,2025-04-07,2025-05-14,2069,8.7,Quantum Computing Inc -AI11026,AI Product Manager,174517,USD,174517,EX,CT,Sweden,L,Sweden,100,"TensorFlow, Docker, R",PhD,16,Telecommunications,2024-10-06,2024-11-22,1820,9.2,TechCorp Inc -AI11027,Robotics Engineer,133855,USD,133855,MI,PT,Norway,L,Norway,0,"SQL, MLOps, Data Visualization",Bachelor,4,Automotive,2024-12-12,2024-12-30,1909,8.8,Future Systems -AI11028,Data Analyst,114683,EUR,97481,SE,FL,Austria,L,Ukraine,50,"Git, Hadoop, Java",PhD,7,Consulting,2025-03-06,2025-04-15,1203,8.5,Cloud AI Solutions -AI11029,Data Analyst,144927,CHF,130434,MI,FL,Switzerland,M,Ghana,50,"R, SQL, Java, Hadoop, Git",Master,3,Government,2025-02-18,2025-04-26,1093,5.9,Smart Analytics -AI11030,AI Software Engineer,125273,AUD,169119,SE,CT,Australia,S,Australia,100,"AWS, Python, GCP, Spark, TensorFlow",PhD,7,Finance,2024-04-14,2024-05-01,2128,9.5,Predictive Systems -AI11031,AI Consultant,147687,EUR,125534,SE,PT,Netherlands,L,Ireland,0,"Hadoop, Spark, PyTorch, Scala",Associate,5,Education,2024-10-21,2024-11-04,2008,7.1,Future Systems -AI11032,Data Scientist,50116,USD,50116,EN,CT,Finland,M,Vietnam,0,"Java, Kubernetes, Data Visualization, GCP, NLP",Bachelor,1,Education,2024-12-25,2025-01-26,1419,7.3,Algorithmic Solutions -AI11033,Data Analyst,104932,EUR,89192,MI,PT,Netherlands,S,Netherlands,100,"Linux, Scala, MLOps",Associate,2,Consulting,2024-12-16,2025-01-17,2408,7.1,Predictive Systems -AI11034,Machine Learning Engineer,109091,CAD,136364,SE,FL,Canada,M,Canada,0,"PyTorch, R, GCP, Tableau",PhD,8,Government,2024-08-31,2024-09-19,1227,7.5,Advanced Robotics -AI11035,Machine Learning Engineer,108563,GBP,81422,MI,CT,United Kingdom,L,Japan,50,"Python, PyTorch, Scala, SQL",Associate,4,Finance,2024-08-20,2024-10-19,663,6.6,Digital Transformation LLC -AI11036,AI Research Scientist,69383,SGD,90198,EN,FT,Singapore,M,Singapore,100,"Kubernetes, Statistics, GCP",Associate,0,Media,2024-04-15,2024-05-30,643,5.7,AI Innovations -AI11037,Principal Data Scientist,83302,JPY,9163220,MI,FL,Japan,S,Japan,0,"Java, MLOps, Tableau",Master,2,Automotive,2024-03-01,2024-04-30,1368,5.8,Algorithmic Solutions -AI11038,NLP Engineer,253256,EUR,215268,EX,FL,Netherlands,M,Netherlands,50,"Scala, Docker, Computer Vision, Python, Mathematics",Associate,14,Education,2024-12-01,2025-01-10,2350,9.3,DeepTech Ventures -AI11039,Autonomous Systems Engineer,247403,USD,247403,EX,PT,United States,M,United States,50,"Tableau, Docker, Python, Git",Bachelor,19,Education,2024-10-06,2024-12-04,2319,6.1,Smart Analytics -AI11040,Computer Vision Engineer,75025,USD,75025,MI,FL,Ireland,S,Canada,0,"PyTorch, R, Spark, MLOps, Git",Associate,2,Transportation,2024-10-06,2024-11-29,1591,8,TechCorp Inc -AI11041,AI Consultant,60929,USD,60929,EN,FT,Israel,M,Israel,0,"Hadoop, Git, Data Visualization",PhD,1,Retail,2025-03-20,2025-04-13,1691,9.7,Algorithmic Solutions -AI11042,AI Consultant,55166,GBP,41375,EN,FT,United Kingdom,M,United Kingdom,50,"Kubernetes, Statistics, Deep Learning, Tableau, MLOps",PhD,0,Media,2024-01-16,2024-03-22,1296,6,Cognitive Computing -AI11043,Data Engineer,70004,USD,70004,EN,PT,Sweden,M,Sweden,0,"R, Git, Java, Linux",Associate,0,Healthcare,2024-05-30,2024-08-02,2277,8.2,Future Systems -AI11044,AI Specialist,275697,USD,275697,EX,CT,Norway,L,Norway,0,"AWS, PyTorch, SQL, TensorFlow",Master,19,Government,2025-02-28,2025-05-04,951,8.6,Smart Analytics -AI11045,Principal Data Scientist,52725,EUR,44816,EN,PT,Germany,M,Ukraine,100,"Python, Computer Vision, Azure",Bachelor,0,Media,2024-08-11,2024-09-10,1030,5.1,Quantum Computing Inc -AI11046,Computer Vision Engineer,268365,USD,268365,EX,FL,Norway,M,United States,0,"Python, Azure, Data Visualization",Associate,11,Gaming,2025-03-04,2025-04-12,1695,9.3,DataVision Ltd -AI11047,Principal Data Scientist,76596,JPY,8425560,MI,PT,Japan,M,China,50,"Java, Linux, Python",Associate,2,Retail,2024-11-08,2024-12-05,623,7.5,Smart Analytics -AI11048,Computer Vision Engineer,285551,AUD,385494,EX,FL,Australia,L,Australia,50,"Python, NLP, Mathematics, PyTorch, Spark",Bachelor,12,Automotive,2024-02-28,2024-03-21,570,5.4,TechCorp Inc -AI11049,Robotics Engineer,118954,CAD,148693,SE,PT,Canada,L,Canada,100,"Python, PyTorch, Statistics",PhD,5,Government,2025-04-25,2025-05-15,2402,8.9,Cloud AI Solutions -AI11050,ML Ops Engineer,153938,CAD,192423,EX,CT,Canada,S,Canada,0,"PyTorch, Kubernetes, Scala, R, Data Visualization",Associate,16,Real Estate,2024-11-11,2024-12-29,1553,8.6,Advanced Robotics -AI11051,Deep Learning Engineer,131972,GBP,98979,MI,PT,United Kingdom,L,United Kingdom,100,"NLP, GCP, Python, Linux, Azure",Master,2,Manufacturing,2024-11-18,2024-12-21,2189,5.1,Advanced Robotics -AI11052,AI Product Manager,123154,USD,123154,EX,PT,Israel,S,Israel,50,"Data Visualization, Linux, Java",Bachelor,18,Energy,2024-07-29,2024-09-27,1275,7.4,Future Systems -AI11053,ML Ops Engineer,84249,JPY,9267390,MI,FL,Japan,M,Italy,50,"Java, NLP, Azure",Associate,4,Education,2024-04-25,2024-06-22,857,6.5,Smart Analytics -AI11054,Principal Data Scientist,93431,USD,93431,MI,PT,Sweden,S,Vietnam,50,"GCP, Tableau, Computer Vision, Linux",Associate,2,Finance,2025-02-04,2025-02-18,939,5,DataVision Ltd -AI11055,Computer Vision Engineer,135625,EUR,115281,EX,FL,France,M,France,0,"MLOps, Scala, NLP, PyTorch",Master,17,Gaming,2024-07-04,2024-08-28,1870,9.5,TechCorp Inc -AI11056,AI Product Manager,218295,EUR,185551,EX,PT,Austria,L,Austria,50,"SQL, Kubernetes, Docker, Tableau",Master,14,Gaming,2024-06-29,2024-08-03,1091,9.3,Predictive Systems -AI11057,ML Ops Engineer,99582,USD,99582,EN,FL,Denmark,L,Netherlands,100,"Linux, Data Visualization, PyTorch",Associate,1,Consulting,2025-03-29,2025-04-25,1168,9.6,Autonomous Tech -AI11058,Robotics Engineer,262079,GBP,196559,EX,FL,United Kingdom,L,United Kingdom,100,"Python, Java, Spark",Master,15,Technology,2024-02-06,2024-03-22,811,9.7,Smart Analytics -AI11059,AI Research Scientist,124785,USD,124785,SE,FT,Israel,M,Israel,50,"GCP, Scala, NLP, Kubernetes",Bachelor,7,Government,2024-12-19,2025-01-07,820,5.3,Cognitive Computing -AI11060,Autonomous Systems Engineer,78762,USD,78762,MI,FT,South Korea,S,South Korea,100,"TensorFlow, Python, Docker",Associate,3,Transportation,2024-01-05,2024-01-28,1893,8.9,Autonomous Tech -AI11061,Computer Vision Engineer,116968,JPY,12866480,MI,PT,Japan,M,Japan,50,"Java, R, Mathematics, Data Visualization, NLP",Bachelor,4,Manufacturing,2024-09-14,2024-10-25,2019,6.7,Machine Intelligence Group -AI11062,Machine Learning Researcher,82720,EUR,70312,MI,FT,Netherlands,M,Netherlands,0,"Data Visualization, Kubernetes, Azure",PhD,2,Telecommunications,2024-12-30,2025-03-08,812,9.1,DeepTech Ventures -AI11063,Data Analyst,105375,USD,105375,MI,FL,United States,M,United States,50,"TensorFlow, GCP, Azure, Hadoop",Master,3,Retail,2024-06-04,2024-07-24,1249,6.6,Algorithmic Solutions -AI11064,Computer Vision Engineer,123190,EUR,104712,EX,PT,Austria,S,Austria,50,"Data Visualization, AWS, Linux, Computer Vision, Statistics",Master,10,Real Estate,2024-07-11,2024-08-26,1042,9.7,DataVision Ltd -AI11065,ML Ops Engineer,277393,EUR,235784,EX,FL,Germany,L,Germany,0,"Kubernetes, Computer Vision, Git, Mathematics",Bachelor,17,Finance,2024-09-07,2024-11-01,996,5.5,DataVision Ltd -AI11066,Robotics Engineer,106542,EUR,90561,SE,FL,Germany,S,Germany,100,"Tableau, Java, Computer Vision",Bachelor,6,Media,2024-07-24,2024-09-12,547,8.7,DataVision Ltd -AI11067,NLP Engineer,94499,EUR,80324,MI,FL,France,L,Kenya,50,"Git, Java, MLOps, Computer Vision",Bachelor,2,Gaming,2024-02-12,2024-04-15,821,7.8,Quantum Computing Inc -AI11068,Autonomous Systems Engineer,189283,CHF,170355,SE,PT,Switzerland,M,Latvia,0,"Scala, GCP, Deep Learning",Master,8,Education,2024-06-16,2024-07-24,1321,9.7,Cloud AI Solutions -AI11069,Computer Vision Engineer,157133,EUR,133563,SE,FL,Germany,L,Germany,100,"Python, Git, Kubernetes, Deep Learning, R",Master,9,Finance,2024-08-07,2024-09-30,913,6.6,Algorithmic Solutions -AI11070,Robotics Engineer,258931,USD,258931,EX,FT,Denmark,S,Argentina,100,"Python, AWS, Docker",Associate,15,Government,2024-06-22,2024-07-31,1270,5.5,AI Innovations -AI11071,AI Specialist,94485,CAD,118106,MI,CT,Canada,M,Canada,50,"Java, Hadoop, SQL, Mathematics, GCP",Bachelor,3,Technology,2025-02-28,2025-03-23,1538,8.3,DataVision Ltd -AI11072,AI Architect,53437,USD,53437,EN,PT,Sweden,S,Sweden,50,"SQL, Hadoop, Linux",Bachelor,1,Government,2024-01-07,2024-02-08,980,9.9,Predictive Systems -AI11073,Computer Vision Engineer,81989,EUR,69691,MI,FT,France,S,Russia,100,"TensorFlow, Tableau, Mathematics, Java",Associate,2,Automotive,2024-03-08,2024-04-05,1163,7.1,Quantum Computing Inc -AI11074,AI Software Engineer,53872,GBP,40404,EN,PT,United Kingdom,S,Vietnam,100,"Python, SQL, Hadoop",PhD,1,Real Estate,2024-08-01,2024-09-27,1286,5.1,Predictive Systems -AI11075,AI Product Manager,112299,USD,112299,MI,PT,Finland,L,Finland,100,"Python, TensorFlow, Docker, PyTorch, Scala",Bachelor,4,Manufacturing,2024-05-06,2024-06-02,2011,8.1,AI Innovations -AI11076,Head of AI,148344,EUR,126092,EX,PT,Austria,M,Nigeria,50,"Git, Kubernetes, GCP, Tableau, MLOps",Associate,17,Education,2024-09-28,2024-11-09,1791,6.3,Future Systems -AI11077,AI Consultant,149732,AUD,202138,EX,PT,Australia,M,Australia,50,"Python, Git, NLP, Scala",PhD,19,Retail,2024-03-31,2024-04-28,1510,9.2,Cloud AI Solutions -AI11078,Research Scientist,86366,USD,86366,MI,FL,United States,S,United States,0,"Git, Scala, MLOps, R",PhD,4,Manufacturing,2025-04-23,2025-05-07,2253,7.7,Digital Transformation LLC -AI11079,AI Specialist,126508,USD,126508,MI,FL,Norway,S,Malaysia,0,"GCP, AWS, Data Visualization, Python, TensorFlow",Bachelor,3,Finance,2024-01-17,2024-03-07,1652,9.3,AI Innovations -AI11080,Data Scientist,88565,USD,88565,MI,FT,Israel,M,Malaysia,0,"MLOps, Mathematics, TensorFlow, GCP, AWS",Master,3,Media,2024-01-27,2024-02-19,1483,9.6,Future Systems -AI11081,AI Software Engineer,67656,USD,67656,EN,FT,Ireland,L,Czech Republic,0,"Python, Azure, Kubernetes",Associate,0,Retail,2024-06-20,2024-08-08,2044,6.3,Neural Networks Co -AI11082,AI Architect,112374,EUR,95518,MI,FT,Netherlands,L,Netherlands,50,"Scala, R, Spark",Associate,4,Retail,2025-01-11,2025-02-20,1000,6.6,DeepTech Ventures -AI11083,AI Research Scientist,117883,JPY,12967130,MI,PT,Japan,L,Japan,0,"Data Visualization, Hadoop, Linux",Master,3,Transportation,2024-01-15,2024-01-29,727,9.2,Autonomous Tech -AI11084,AI Software Engineer,121000,USD,121000,SE,FL,United States,M,China,100,"Java, Deep Learning, MLOps, Git",Bachelor,5,Media,2025-04-16,2025-05-28,2140,6.8,DeepTech Ventures -AI11085,Data Engineer,207170,CAD,258963,EX,FL,Canada,L,Canada,0,"TensorFlow, Statistics, Spark, SQL",Master,17,Healthcare,2024-10-28,2024-12-06,766,9.4,Smart Analytics -AI11086,AI Architect,116459,USD,116459,SE,FT,South Korea,L,South Korea,50,"Tableau, Azure, Java, NLP, R",Associate,5,Education,2025-04-25,2025-05-31,502,9.5,Predictive Systems -AI11087,Autonomous Systems Engineer,122703,CHF,110433,MI,FL,Switzerland,L,Switzerland,0,"Linux, Azure, Mathematics",PhD,2,Government,2024-12-26,2025-03-03,2270,8.4,Future Systems -AI11088,Computer Vision Engineer,97199,USD,97199,EN,CT,Norway,L,Norway,50,"Deep Learning, TensorFlow, Scala, Computer Vision, Linux",Bachelor,0,Gaming,2024-06-12,2024-07-22,2472,9,Future Systems -AI11089,Principal Data Scientist,290472,GBP,217854,EX,FT,United Kingdom,L,Italy,100,"Tableau, AWS, TensorFlow",Master,16,Media,2024-09-15,2024-10-23,1094,7.3,TechCorp Inc -AI11090,AI Specialist,81583,EUR,69346,EN,FL,France,L,France,100,"Spark, MLOps, Linux",Bachelor,1,Manufacturing,2024-04-08,2024-06-20,1025,9.5,Neural Networks Co -AI11091,Robotics Engineer,96594,USD,96594,MI,FT,Finland,L,Finland,50,"Linux, GCP, Tableau",Master,4,Media,2024-11-23,2025-01-26,1434,5.8,Algorithmic Solutions -AI11092,AI Consultant,64211,USD,64211,SE,FT,China,S,China,100,"R, Kubernetes, Tableau, Computer Vision, Azure",Master,7,Transportation,2024-01-19,2024-03-19,629,7,Future Systems -AI11093,Data Analyst,155715,EUR,132358,EX,CT,France,L,France,100,"Statistics, Mathematics, Data Visualization, Hadoop, Python",Master,18,Government,2024-04-25,2024-07-07,749,9.6,TechCorp Inc -AI11094,NLP Engineer,114469,USD,114469,MI,FT,Ireland,L,Switzerland,50,"Docker, Kubernetes, GCP",Associate,4,Media,2024-06-23,2024-07-09,556,8.2,Smart Analytics -AI11095,Autonomous Systems Engineer,90803,USD,90803,MI,FT,Ireland,S,India,100,"R, GCP, Computer Vision, Statistics",Bachelor,2,Gaming,2024-10-05,2024-10-29,983,7.6,Machine Intelligence Group -AI11096,Autonomous Systems Engineer,52790,USD,52790,EN,PT,Finland,S,Finland,0,"Kubernetes, R, Computer Vision, Java, Git",Associate,1,Gaming,2024-02-20,2024-04-06,637,9.2,Quantum Computing Inc -AI11097,AI Product Manager,123158,EUR,104684,SE,FL,Germany,S,Germany,50,"Linux, Tableau, Docker, Deep Learning",Bachelor,9,Gaming,2024-09-26,2024-11-06,1797,9.5,Predictive Systems -AI11098,NLP Engineer,136173,USD,136173,EX,FL,Ireland,M,Ireland,0,"Mathematics, Git, Scala",Bachelor,15,Finance,2024-03-06,2024-03-22,1892,9.9,AI Innovations -AI11099,AI Product Manager,33349,USD,33349,EN,FT,China,S,China,50,"AWS, Hadoop, MLOps, TensorFlow",PhD,1,Education,2025-02-15,2025-04-19,1995,9.9,Advanced Robotics -AI11100,Robotics Engineer,109691,USD,109691,EX,FL,China,L,China,100,"Git, PyTorch, SQL",PhD,12,Retail,2024-12-10,2025-01-27,542,8.7,Advanced Robotics -AI11101,AI Software Engineer,154172,USD,154172,SE,PT,Sweden,L,Sweden,50,"Scala, Deep Learning, Data Visualization, Tableau, Docker",Master,7,Real Estate,2024-12-03,2025-02-02,870,8.2,Quantum Computing Inc -AI11102,NLP Engineer,62316,AUD,84127,EN,FT,Australia,S,United States,100,"Python, AWS, Deep Learning, Kubernetes, Statistics",Associate,1,Finance,2024-09-14,2024-10-28,1518,7.6,Digital Transformation LLC -AI11103,Data Scientist,100179,USD,100179,SE,FT,Sweden,S,Finland,100,"Computer Vision, Mathematics, Linux, AWS",PhD,7,Transportation,2024-12-15,2025-01-25,722,9.9,Cognitive Computing -AI11104,Research Scientist,165296,SGD,214885,EX,FT,Singapore,S,Singapore,0,"NLP, SQL, Java, PyTorch",PhD,10,Consulting,2024-10-06,2024-11-08,1218,8.4,Predictive Systems -AI11105,Research Scientist,199699,AUD,269594,EX,FL,Australia,S,Australia,100,"Data Visualization, Python, Kubernetes, Deep Learning, Tableau",Associate,11,Technology,2024-11-10,2024-11-28,1954,8.6,Digital Transformation LLC -AI11106,Autonomous Systems Engineer,199230,USD,199230,SE,FL,Norway,L,Norway,0,"Azure, TensorFlow, Scala, Python, Java",Associate,8,Media,2025-04-19,2025-05-28,1359,8.2,Quantum Computing Inc -AI11107,Data Analyst,60772,AUD,82042,EN,PT,Australia,L,Australia,50,"Deep Learning, Linux, Data Visualization",Associate,0,Real Estate,2024-04-25,2024-06-22,2427,5.6,Machine Intelligence Group -AI11108,Head of AI,35534,USD,35534,MI,CT,China,S,China,50,"Python, TensorFlow, NLP, Scala",Bachelor,3,Finance,2024-01-16,2024-03-12,1054,7.2,Neural Networks Co -AI11109,Principal Data Scientist,127355,EUR,108252,SE,CT,France,S,Colombia,50,"GCP, Java, Scala, Data Visualization, Computer Vision",Associate,7,Healthcare,2025-02-09,2025-04-11,1012,7.9,Smart Analytics -AI11110,AI Research Scientist,150163,USD,150163,SE,PT,Sweden,M,Sweden,100,"Docker, Azure, Data Visualization, Spark, Kubernetes",Bachelor,8,Media,2025-03-16,2025-04-23,1933,6.9,Cognitive Computing -AI11111,Deep Learning Engineer,34278,USD,34278,SE,CT,India,S,India,0,"Data Visualization, Kubernetes, Scala, Statistics",Associate,8,Real Estate,2024-05-23,2024-06-29,550,8.4,Autonomous Tech -AI11112,Robotics Engineer,50385,JPY,5542350,EN,PT,Japan,S,Japan,0,"GCP, Kubernetes, Java, Spark",Bachelor,1,Energy,2024-01-17,2024-02-08,851,8.2,AI Innovations -AI11113,AI Software Engineer,127626,USD,127626,MI,FL,Norway,S,Nigeria,0,"Python, TensorFlow, Data Visualization",Bachelor,2,Technology,2024-09-05,2024-10-01,782,5.9,Predictive Systems -AI11114,Robotics Engineer,87121,USD,87121,EN,FL,Ireland,L,Ireland,0,"Python, Java, AWS, MLOps, Statistics",Master,0,Transportation,2024-07-14,2024-09-22,1394,6.5,AI Innovations -AI11115,Computer Vision Engineer,242532,EUR,206152,EX,FL,Austria,L,Czech Republic,50,"TensorFlow, GCP, Statistics, AWS",PhD,19,Transportation,2024-02-22,2024-04-09,2387,6.6,DataVision Ltd -AI11116,Autonomous Systems Engineer,42882,USD,42882,EN,PT,South Korea,S,Chile,50,"Data Visualization, Docker, Computer Vision, Hadoop",Master,0,Energy,2024-01-31,2024-03-28,2147,8.2,TechCorp Inc -AI11117,AI Software Engineer,63065,USD,63065,MI,CT,South Korea,S,Portugal,50,"SQL, Scala, Mathematics, R",PhD,2,Energy,2024-12-28,2025-02-24,1177,7.8,Smart Analytics -AI11118,Autonomous Systems Engineer,54039,USD,54039,SE,FL,China,S,China,100,"Spark, TensorFlow, Data Visualization",Associate,8,Healthcare,2025-02-05,2025-04-18,1353,5.6,Cognitive Computing -AI11119,Robotics Engineer,184798,JPY,20327780,EX,PT,Japan,L,South Africa,0,"Mathematics, Statistics, Python",Associate,18,Telecommunications,2025-02-07,2025-02-27,1660,9.1,TechCorp Inc -AI11120,Research Scientist,238260,USD,238260,EX,PT,Sweden,L,Sweden,100,"Python, TensorFlow, R, Computer Vision",Associate,12,Media,2025-04-16,2025-06-01,1703,5.3,Quantum Computing Inc -AI11121,Autonomous Systems Engineer,261853,USD,261853,EX,FL,Denmark,S,Denmark,100,"Docker, Linux, PyTorch",PhD,19,Finance,2024-01-28,2024-03-08,1113,8.7,Predictive Systems -AI11122,Data Engineer,239826,SGD,311774,EX,PT,Singapore,S,Singapore,0,"PyTorch, Linux, TensorFlow, SQL",Associate,16,Technology,2025-02-04,2025-02-18,2109,7.7,Predictive Systems -AI11123,Research Scientist,201246,EUR,171059,EX,CT,Germany,M,Germany,50,"Docker, Azure, Data Visualization",Associate,10,Transportation,2025-04-15,2025-05-27,2412,9.3,Machine Intelligence Group -AI11124,Data Engineer,109684,USD,109684,SE,CT,Finland,M,Finland,100,"Hadoop, R, Linux, Java, SQL",Associate,8,Manufacturing,2024-07-18,2024-09-07,876,5.8,Smart Analytics -AI11125,Data Analyst,83819,EUR,71246,MI,FT,Germany,L,Czech Republic,50,"R, Java, MLOps, Kubernetes",Master,2,Gaming,2024-02-25,2024-04-24,988,9.9,Cloud AI Solutions -AI11126,AI Software Engineer,61837,GBP,46378,EN,FT,United Kingdom,S,United Kingdom,50,"Python, GCP, Tableau, R",Bachelor,0,Telecommunications,2024-07-12,2024-09-14,2451,8,TechCorp Inc -AI11127,AI Architect,75517,GBP,56638,EN,FT,United Kingdom,S,Finland,50,"Data Visualization, TensorFlow, MLOps, Python",Bachelor,1,Retail,2024-11-24,2025-01-21,1177,7.3,AI Innovations -AI11128,NLP Engineer,131115,USD,131115,SE,CT,United States,S,United States,0,"TensorFlow, Python, PyTorch",Master,7,Energy,2024-11-27,2025-02-01,673,9.3,DataVision Ltd -AI11129,Data Engineer,169966,EUR,144471,EX,FL,France,S,Poland,50,"Hadoop, PyTorch, Statistics, Mathematics, Deep Learning",Bachelor,15,Consulting,2024-01-20,2024-02-27,529,6.3,DeepTech Ventures -AI11130,Head of AI,79201,USD,79201,EX,FT,India,S,India,50,"Docker, Python, Data Visualization, Scala",Master,10,Finance,2025-02-08,2025-03-08,2200,10,Predictive Systems -AI11131,AI Consultant,71991,EUR,61192,EN,FL,France,L,Israel,50,"Mathematics, GCP, Deep Learning",Bachelor,0,Transportation,2024-03-03,2024-04-05,2377,9.1,Cloud AI Solutions -AI11132,Data Engineer,211340,GBP,158505,EX,CT,United Kingdom,S,Nigeria,50,"NLP, Java, Kubernetes, Git",PhD,11,Automotive,2025-02-17,2025-04-27,921,9.3,TechCorp Inc -AI11133,Machine Learning Engineer,121942,USD,121942,SE,PT,Israel,S,Israel,100,"Kubernetes, GCP, SQL, Git",Associate,5,Healthcare,2024-06-08,2024-07-29,859,8.9,DataVision Ltd -AI11134,Principal Data Scientist,133708,CAD,167135,SE,FL,Canada,M,Canada,50,"Tableau, PyTorch, NLP",Associate,5,Education,2025-03-01,2025-04-24,1145,9.5,Advanced Robotics -AI11135,Data Scientist,128594,GBP,96446,MI,FT,United Kingdom,L,United Kingdom,0,"Statistics, R, PyTorch, TensorFlow",Associate,2,Automotive,2024-11-03,2024-11-19,895,9.7,Digital Transformation LLC -AI11136,Machine Learning Researcher,90783,EUR,77166,MI,PT,France,L,France,100,"R, Scala, NLP",Associate,4,Retail,2024-09-19,2024-11-13,1985,9.1,Neural Networks Co -AI11137,AI Product Manager,241386,GBP,181040,EX,CT,United Kingdom,S,United Kingdom,50,"Scala, Java, R",PhD,13,Technology,2024-03-19,2024-05-02,1706,6.4,Advanced Robotics -AI11138,Data Scientist,50199,USD,50199,EN,FL,South Korea,M,South Korea,50,"Azure, Hadoop, SQL",Master,0,Automotive,2025-03-05,2025-05-12,1284,9.4,TechCorp Inc -AI11139,Head of AI,69589,AUD,93945,EN,FL,Australia,S,Australia,0,"R, SQL, Data Visualization, Git",Bachelor,1,Transportation,2024-02-04,2024-04-10,2397,7.6,Autonomous Tech -AI11140,Data Analyst,249049,USD,249049,EX,FT,United States,L,United States,50,"Azure, Python, Tableau",Bachelor,19,Finance,2024-10-02,2024-11-20,708,5,Neural Networks Co -AI11141,Data Engineer,74973,USD,74973,EN,FT,United States,M,United States,0,"SQL, Kubernetes, AWS",PhD,1,Technology,2025-02-05,2025-03-23,2354,5.3,DeepTech Ventures -AI11142,AI Specialist,86870,USD,86870,MI,FL,Denmark,S,Australia,100,"NLP, SQL, R",PhD,4,Finance,2024-06-22,2024-08-11,1019,7.6,Cloud AI Solutions -AI11143,Robotics Engineer,132380,USD,132380,SE,FL,Israel,M,Israel,0,"Data Visualization, MLOps, SQL, R",Master,5,Energy,2024-08-18,2024-09-03,883,8.3,DeepTech Ventures -AI11144,AI Specialist,134074,EUR,113963,SE,FT,Germany,M,Germany,100,"Azure, Hadoop, Computer Vision, Kubernetes",Bachelor,7,Manufacturing,2024-05-13,2024-06-13,1001,9.2,TechCorp Inc -AI11145,Autonomous Systems Engineer,29783,USD,29783,MI,PT,India,M,Australia,50,"Java, TensorFlow, AWS, Linux",Bachelor,2,Government,2024-11-25,2024-12-21,567,8.8,Neural Networks Co -AI11146,Autonomous Systems Engineer,129656,JPY,14262160,SE,FT,Japan,M,Japan,50,"Python, Kubernetes, Mathematics, MLOps",Associate,8,Media,2024-02-25,2024-05-03,1544,9.7,Smart Analytics -AI11147,AI Research Scientist,101315,USD,101315,SE,CT,Sweden,S,Sweden,50,"R, PyTorch, Azure, TensorFlow",Associate,9,Telecommunications,2025-01-30,2025-03-22,1720,8.1,Cognitive Computing -AI11148,Head of AI,154178,USD,154178,EX,FT,Israel,M,Austria,50,"Hadoop, Java, Mathematics",Bachelor,18,Government,2025-01-13,2025-03-16,2287,6.1,Cloud AI Solutions -AI11149,Data Scientist,71943,EUR,61152,EN,PT,Austria,L,Austria,50,"Docker, SQL, Python, AWS",Bachelor,0,Automotive,2024-03-13,2024-05-12,2360,5.5,Predictive Systems -AI11150,AI Research Scientist,187201,USD,187201,EX,FL,South Korea,M,Netherlands,50,"GCP, NLP, AWS",PhD,17,Gaming,2025-03-02,2025-05-12,1532,8.8,Machine Intelligence Group -AI11151,AI Software Engineer,69671,AUD,94056,MI,CT,Australia,S,Australia,100,"Python, Tableau, TensorFlow",Master,3,Healthcare,2024-08-18,2024-10-12,2262,6.6,Algorithmic Solutions -AI11152,Deep Learning Engineer,119940,AUD,161919,SE,CT,Australia,M,Australia,50,"SQL, PyTorch, TensorFlow, Deep Learning, Statistics",PhD,7,Gaming,2024-01-03,2024-03-14,1693,6.3,Future Systems -AI11153,Principal Data Scientist,102411,CHF,92170,MI,FL,Switzerland,S,Mexico,100,"Java, Hadoop, SQL, Computer Vision, Mathematics",Master,3,Healthcare,2024-08-23,2024-09-13,762,9.4,Neural Networks Co -AI11154,ML Ops Engineer,94579,CAD,118224,MI,FL,Canada,L,Canada,50,"PyTorch, GCP, Scala, Hadoop",Associate,4,Real Estate,2024-10-21,2024-12-09,813,8.3,Advanced Robotics -AI11155,Head of AI,93077,GBP,69808,EN,CT,United Kingdom,L,United Kingdom,100,"R, Deep Learning, Python, Statistics, Computer Vision",Associate,1,Finance,2024-06-19,2024-07-08,1504,5.2,Digital Transformation LLC -AI11156,AI Architect,215780,USD,215780,EX,FL,Denmark,L,Denmark,0,"Linux, Computer Vision, GCP, Azure",Master,15,Energy,2024-07-20,2024-09-13,2054,7.2,DataVision Ltd -AI11157,Machine Learning Researcher,123240,EUR,104754,SE,PT,Austria,M,Austria,0,"Kubernetes, Deep Learning, Docker, Statistics, Java",Bachelor,5,Education,2024-09-13,2024-10-09,1895,6.2,Predictive Systems -AI11158,Head of AI,172179,USD,172179,SE,PT,Denmark,M,Egypt,50,"GCP, R, MLOps, TensorFlow",Bachelor,6,Consulting,2024-08-30,2024-10-12,987,8.1,Digital Transformation LLC -AI11159,AI Software Engineer,211756,USD,211756,EX,PT,Sweden,L,Sweden,0,"Data Visualization, NLP, GCP",Master,10,Manufacturing,2024-07-04,2024-07-30,1708,7.2,Neural Networks Co -AI11160,Machine Learning Researcher,68820,USD,68820,MI,FL,South Korea,S,South Korea,50,"NLP, GCP, R, Data Visualization, Computer Vision",Master,4,Automotive,2025-01-03,2025-03-10,1419,9.4,Algorithmic Solutions -AI11161,Machine Learning Researcher,40630,USD,40630,EN,CT,South Korea,S,South Korea,0,"Git, Kubernetes, Hadoop, Java",PhD,1,Gaming,2025-02-28,2025-03-28,692,9.2,TechCorp Inc -AI11162,AI Product Manager,79533,EUR,67603,MI,FL,Austria,S,Israel,0,"NLP, SQL, PyTorch, Tableau, Docker",Associate,4,Manufacturing,2025-03-18,2025-05-02,1282,6.9,AI Innovations -AI11163,Data Engineer,85375,CHF,76838,EN,CT,Switzerland,L,Switzerland,100,"Computer Vision, Scala, Linux, Docker, MLOps",PhD,0,Transportation,2024-09-14,2024-11-21,2017,7.8,DataVision Ltd -AI11164,Machine Learning Researcher,34517,USD,34517,MI,CT,China,S,China,50,"PyTorch, TensorFlow, MLOps, Java, R",Associate,3,Transportation,2024-02-18,2024-04-19,2242,9.2,AI Innovations -AI11165,Robotics Engineer,169364,USD,169364,EX,PT,Sweden,M,Sweden,0,"Data Visualization, PyTorch, TensorFlow, Statistics, Azure",Master,14,Real Estate,2025-01-06,2025-03-01,1951,9.6,Cognitive Computing -AI11166,AI Architect,118975,CAD,148719,SE,CT,Canada,L,Canada,50,"Python, Mathematics, Git, Computer Vision",PhD,6,Telecommunications,2024-11-26,2025-01-13,1063,7,Machine Intelligence Group -AI11167,AI Specialist,53965,USD,53965,SE,FL,India,L,India,100,"SQL, Java, PyTorch",Bachelor,5,Consulting,2024-01-13,2024-02-21,581,7.6,Neural Networks Co -AI11168,Principal Data Scientist,163916,USD,163916,EX,CT,Sweden,L,Sweden,0,"Data Visualization, Java, Tableau",Associate,19,Education,2024-03-01,2024-03-30,1789,8.4,Machine Intelligence Group -AI11169,Deep Learning Engineer,82346,USD,82346,MI,FT,Israel,M,New Zealand,0,"Azure, GCP, Deep Learning, Scala",Bachelor,2,Transportation,2024-03-31,2024-05-30,522,8.2,TechCorp Inc -AI11170,AI Specialist,124224,JPY,13664640,SE,FT,Japan,S,Japan,50,"Computer Vision, Python, Azure",Associate,8,Manufacturing,2024-01-18,2024-03-08,965,7.5,DataVision Ltd -AI11171,AI Consultant,141596,USD,141596,SE,CT,Finland,M,Denmark,100,"MLOps, Linux, Kubernetes, Python, Statistics",Bachelor,8,Healthcare,2025-04-29,2025-07-09,1133,8.3,Algorithmic Solutions -AI11172,AI Research Scientist,36117,USD,36117,MI,PT,India,L,Colombia,50,"Mathematics, Git, Python",Bachelor,2,Manufacturing,2024-04-04,2024-05-22,684,5.2,Smart Analytics -AI11173,Data Engineer,72859,USD,72859,MI,FT,Ireland,S,Thailand,100,"Deep Learning, TensorFlow, Git, SQL, Java",Bachelor,4,Real Estate,2024-06-19,2024-08-27,1261,7.3,Autonomous Tech -AI11174,AI Software Engineer,145568,GBP,109176,SE,FT,United Kingdom,S,Estonia,50,"AWS, Python, Tableau, Git",Associate,9,Finance,2024-05-03,2024-05-28,595,6.6,Predictive Systems -AI11175,NLP Engineer,81162,GBP,60872,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, Statistics, NLP, R",Master,4,Transportation,2024-01-29,2024-03-10,1900,7,Quantum Computing Inc -AI11176,NLP Engineer,222942,EUR,189501,EX,PT,Netherlands,M,Netherlands,100,"Docker, Scala, Computer Vision, Linux",Associate,13,Manufacturing,2024-09-15,2024-10-15,1315,8.7,Digital Transformation LLC -AI11177,Computer Vision Engineer,241236,AUD,325669,EX,FL,Australia,M,India,50,"Statistics, Python, R, Linux, SQL",Bachelor,11,Transportation,2024-09-22,2024-11-29,1590,9.6,Autonomous Tech -AI11178,Data Analyst,79043,CAD,98804,EN,FL,Canada,L,Canada,0,"R, Linux, Python, Java",Associate,1,Healthcare,2025-04-10,2025-05-19,556,6.3,Neural Networks Co -AI11179,AI Specialist,118334,USD,118334,MI,PT,United States,M,Chile,50,"GCP, MLOps, Scala, Python",Bachelor,4,Gaming,2024-12-23,2025-01-25,616,9.6,Autonomous Tech -AI11180,Head of AI,90117,USD,90117,SE,PT,Israel,S,Israel,0,"Linux, NLP, PyTorch, Git",PhD,7,Government,2024-08-16,2024-09-24,971,9.9,Neural Networks Co -AI11181,AI Software Engineer,174435,USD,174435,SE,PT,Denmark,L,Denmark,0,"Computer Vision, Kubernetes, Tableau, Linux, Mathematics",PhD,7,Retail,2025-03-17,2025-05-07,2391,6.2,Machine Intelligence Group -AI11182,Machine Learning Researcher,118598,USD,118598,SE,PT,Sweden,L,Sweden,100,"Azure, Python, Mathematics, Kubernetes, AWS",PhD,6,Manufacturing,2024-05-11,2024-07-23,2052,9,Quantum Computing Inc -AI11183,Robotics Engineer,37061,USD,37061,MI,PT,China,S,Argentina,0,"SQL, Docker, Kubernetes, MLOps",PhD,4,Transportation,2025-01-28,2025-02-19,2380,6,Algorithmic Solutions -AI11184,AI Product Manager,229849,EUR,195372,EX,FT,Netherlands,S,Netherlands,100,"Kubernetes, SQL, Computer Vision, Mathematics",Master,17,Technology,2024-10-03,2024-11-08,1912,6.5,Cloud AI Solutions -AI11185,AI Research Scientist,178162,CHF,160346,MI,PT,Switzerland,L,Switzerland,50,"Python, Kubernetes, TensorFlow",Bachelor,4,Education,2024-12-15,2025-01-26,1263,7.9,Advanced Robotics -AI11186,Data Engineer,175805,GBP,131854,EX,CT,United Kingdom,L,Canada,100,"Spark, AWS, Azure, GCP",Bachelor,10,Healthcare,2025-04-22,2025-06-03,984,7.2,DeepTech Ventures -AI11187,Autonomous Systems Engineer,105402,USD,105402,MI,FT,Sweden,L,New Zealand,50,"Computer Vision, Data Visualization, Java",Bachelor,3,Finance,2024-05-11,2024-07-02,2493,9.7,DeepTech Ventures -AI11188,AI Software Engineer,33884,USD,33884,MI,PT,India,M,Luxembourg,50,"PyTorch, GCP, TensorFlow, Scala, Kubernetes",PhD,2,Retail,2024-09-03,2024-11-12,1283,9.6,Machine Intelligence Group -AI11189,Computer Vision Engineer,60249,USD,60249,EN,FL,Ireland,M,Ireland,50,"Data Visualization, Azure, Tableau, TensorFlow, Statistics",Master,0,Education,2024-01-02,2024-02-24,1904,6.3,Digital Transformation LLC -AI11190,NLP Engineer,81942,USD,81942,MI,FT,Finland,M,Finland,100,"Data Visualization, Hadoop, Scala, Tableau",PhD,2,Finance,2025-01-25,2025-03-18,1325,8.5,Smart Analytics -AI11191,ML Ops Engineer,76583,AUD,103387,EN,FT,Australia,M,Belgium,0,"Docker, Spark, TensorFlow, AWS, Computer Vision",Master,1,Government,2024-06-22,2024-08-06,2483,8.6,Algorithmic Solutions -AI11192,AI Specialist,61080,USD,61080,SE,PT,India,L,India,50,"Java, MLOps, Data Visualization, Spark, Statistics",PhD,5,Consulting,2024-03-22,2024-05-14,2326,9.5,Cloud AI Solutions -AI11193,Data Engineer,129718,GBP,97289,SE,CT,United Kingdom,S,United Kingdom,0,"Python, TensorFlow, Docker",Associate,9,Consulting,2024-04-30,2024-07-07,1768,5.2,Cloud AI Solutions -AI11194,AI Specialist,89873,GBP,67405,MI,CT,United Kingdom,S,United Kingdom,100,"Azure, Linux, Tableau, Docker",Master,3,Consulting,2025-03-05,2025-04-11,692,5.9,Neural Networks Co -AI11195,Data Scientist,203419,USD,203419,EX,PT,Finland,S,Finland,100,"Python, Kubernetes, TensorFlow, MLOps, Tableau",Master,10,Manufacturing,2025-04-27,2025-05-27,1819,9.1,Machine Intelligence Group -AI11196,Machine Learning Engineer,154964,CHF,139468,SE,PT,Switzerland,M,Switzerland,50,"PyTorch, Git, Computer Vision, TensorFlow",Bachelor,7,Manufacturing,2024-12-01,2025-01-13,1378,9.5,Autonomous Tech -AI11197,ML Ops Engineer,127404,USD,127404,EX,CT,Israel,S,Austria,100,"TensorFlow, Git, Python, Java",Bachelor,16,Transportation,2024-07-24,2024-09-08,2469,5.1,AI Innovations -AI11198,Head of AI,112946,EUR,96004,MI,PT,Austria,L,Austria,100,"Kubernetes, Linux, Scala, Java, Mathematics",Master,2,Real Estate,2024-10-23,2024-11-15,1555,5.3,AI Innovations -AI11199,Head of AI,166982,CHF,150284,SE,FL,Switzerland,L,Switzerland,0,"GCP, Kubernetes, Mathematics, AWS, Statistics",Master,5,Consulting,2024-04-18,2024-06-19,1128,7,Future Systems -AI11200,AI Architect,79897,USD,79897,EN,FT,Ireland,L,Ireland,0,"Java, Python, R, Kubernetes",Associate,1,Technology,2024-04-11,2024-04-29,1307,6,Algorithmic Solutions -AI11201,Machine Learning Researcher,199034,CHF,179131,EX,CT,Switzerland,S,Switzerland,0,"Linux, Deep Learning, Computer Vision, GCP, Git",PhD,13,Energy,2024-05-27,2024-06-14,2002,7.9,Advanced Robotics -AI11202,Robotics Engineer,121505,USD,121505,MI,CT,United States,L,Mexico,0,"Deep Learning, PyTorch, Kubernetes, Docker, TensorFlow",Bachelor,3,Transportation,2024-12-20,2025-02-22,505,9.6,Neural Networks Co -AI11203,AI Specialist,98949,EUR,84107,SE,FT,Austria,S,Austria,0,"SQL, Git, Docker, TensorFlow, NLP",Bachelor,9,Media,2024-03-12,2024-05-14,2235,7.3,Predictive Systems -AI11204,Autonomous Systems Engineer,175782,USD,175782,EX,PT,Sweden,S,Sweden,50,"Hadoop, GCP, NLP",Master,10,Automotive,2025-03-12,2025-05-08,909,7.6,Cloud AI Solutions -AI11205,Data Engineer,204328,EUR,173679,EX,CT,Netherlands,L,Russia,50,"Linux, R, Azure, Deep Learning",Associate,13,Automotive,2024-08-26,2024-10-17,747,7.8,Quantum Computing Inc -AI11206,Machine Learning Researcher,47111,USD,47111,EN,PT,Ireland,S,Ireland,50,"Python, Git, Hadoop, GCP, Deep Learning",Master,0,Transportation,2024-04-08,2024-05-01,2498,7.9,Smart Analytics -AI11207,Data Analyst,97477,GBP,73108,MI,PT,United Kingdom,S,United Kingdom,100,"Python, Docker, TensorFlow, Statistics, Java",Associate,3,Real Estate,2024-08-05,2024-09-09,1609,5.2,DeepTech Ventures -AI11208,ML Ops Engineer,45439,USD,45439,SE,CT,India,S,India,0,"Mathematics, SQL, Deep Learning, PyTorch",Associate,5,Manufacturing,2024-11-16,2024-12-24,1674,9.8,Quantum Computing Inc -AI11209,ML Ops Engineer,268419,GBP,201314,EX,CT,United Kingdom,M,United Kingdom,0,"Computer Vision, Spark, Python",Master,11,Technology,2024-07-12,2024-08-31,2445,5.6,DeepTech Ventures -AI11210,Head of AI,42030,USD,42030,MI,FT,India,L,Germany,50,"Git, Statistics, Data Visualization, Python, Deep Learning",Bachelor,2,Real Estate,2025-04-11,2025-06-18,1712,6.3,Quantum Computing Inc -AI11211,Research Scientist,134524,USD,134524,SE,FT,Finland,M,Finland,100,"PyTorch, MLOps, Deep Learning",Master,9,Real Estate,2024-03-21,2024-05-13,2193,9,Future Systems -AI11212,AI Research Scientist,178034,USD,178034,EX,FT,Israel,M,Chile,0,"PyTorch, Deep Learning, MLOps, Hadoop, Linux",Bachelor,19,Healthcare,2024-01-17,2024-03-28,2436,9.8,DeepTech Ventures -AI11213,AI Product Manager,79119,USD,79119,MI,PT,Sweden,S,Sweden,100,"Spark, Git, Statistics, Deep Learning, PyTorch",Associate,4,Manufacturing,2024-03-20,2024-05-11,1637,7.7,TechCorp Inc -AI11214,AI Product Manager,168770,USD,168770,EX,PT,Ireland,L,India,50,"PyTorch, TensorFlow, Docker, Mathematics",Associate,15,Transportation,2024-11-09,2024-12-28,1740,6.8,Cognitive Computing -AI11215,Machine Learning Researcher,65252,AUD,88090,EN,FT,Australia,M,Australia,100,"Computer Vision, Mathematics, NLP, Git, MLOps",Bachelor,1,Education,2025-01-15,2025-02-26,1035,6.7,DataVision Ltd -AI11216,Autonomous Systems Engineer,163792,GBP,122844,EX,CT,United Kingdom,M,United Kingdom,50,"Data Visualization, SQL, TensorFlow, Azure, Statistics",Associate,14,Retail,2024-07-25,2024-08-25,664,8.4,Cognitive Computing -AI11217,Machine Learning Engineer,196273,USD,196273,SE,FT,Norway,M,Thailand,0,"Mathematics, PyTorch, Scala, Azure",Master,5,Consulting,2024-09-30,2024-10-16,1052,7,Advanced Robotics -AI11218,Machine Learning Researcher,50242,EUR,42706,EN,CT,France,M,Australia,50,"Python, Java, NLP",Associate,0,Government,2025-03-31,2025-04-29,690,7.3,DeepTech Ventures -AI11219,Machine Learning Engineer,262801,USD,262801,EX,FL,Sweden,L,Sweden,50,"Data Visualization, SQL, Hadoop, MLOps",Associate,19,Transportation,2024-05-07,2024-06-14,1769,6.1,Advanced Robotics -AI11220,Data Analyst,61263,EUR,52074,EN,FL,Germany,L,Singapore,0,"Spark, Hadoop, Statistics, Linux, Python",PhD,0,Real Estate,2024-09-20,2024-10-22,892,9.5,Autonomous Tech -AI11221,ML Ops Engineer,146528,CHF,131875,MI,PT,Switzerland,M,Switzerland,50,"Azure, Python, TensorFlow, Docker",Associate,3,Consulting,2025-02-07,2025-03-22,2279,9.9,Predictive Systems -AI11222,AI Product Manager,163758,USD,163758,SE,FT,Norway,S,Norway,50,"Kubernetes, MLOps, Scala, AWS",Master,9,Media,2024-11-19,2024-12-18,1651,7.6,Algorithmic Solutions -AI11223,AI Research Scientist,166269,JPY,18289590,EX,CT,Japan,L,Japan,0,"Git, Python, Hadoop",Associate,16,Manufacturing,2024-04-18,2024-06-11,2443,8.9,Machine Intelligence Group -AI11224,Autonomous Systems Engineer,233000,EUR,198050,EX,CT,France,M,France,50,"Mathematics, Docker, Kubernetes",PhD,10,Healthcare,2025-01-02,2025-01-17,778,8,DeepTech Ventures -AI11225,AI Research Scientist,91649,USD,91649,MI,PT,United States,S,Ireland,50,"Java, Statistics, Data Visualization, Git, SQL",Associate,4,Media,2024-02-06,2024-03-14,1886,9.4,TechCorp Inc -AI11226,Machine Learning Researcher,152617,CHF,137355,SE,CT,Switzerland,M,Denmark,50,"Java, Mathematics, Kubernetes, Python, Scala",Bachelor,5,Transportation,2024-03-01,2024-04-18,2489,9,Autonomous Tech -AI11227,Deep Learning Engineer,111739,USD,111739,SE,FT,Finland,S,Finland,0,"TensorFlow, Tableau, Spark, GCP, SQL",Bachelor,5,Healthcare,2024-04-14,2024-05-19,2451,7.4,Algorithmic Solutions -AI11228,NLP Engineer,66659,EUR,56660,EN,PT,France,M,Mexico,50,"Tableau, Python, Scala",Bachelor,0,Automotive,2024-01-07,2024-01-22,1040,7.9,Cognitive Computing -AI11229,Machine Learning Engineer,186273,AUD,251469,EX,CT,Australia,L,Australia,50,"Data Visualization, Docker, Tableau, Java",Bachelor,14,Consulting,2024-05-25,2024-07-13,1691,5.6,Algorithmic Solutions -AI11230,AI Specialist,165955,USD,165955,EX,CT,Finland,L,India,100,"TensorFlow, Data Visualization, Tableau, Statistics, AWS",Bachelor,15,Education,2024-10-23,2024-11-29,603,8.8,AI Innovations -AI11231,Data Scientist,206355,EUR,175402,EX,CT,Germany,M,Germany,50,"Linux, Computer Vision, PyTorch, TensorFlow",PhD,14,Government,2024-09-09,2024-10-19,1908,5.4,Digital Transformation LLC -AI11232,Data Analyst,28132,USD,28132,EN,CT,India,M,Argentina,100,"Computer Vision, PyTorch, Spark",Bachelor,1,Energy,2025-01-05,2025-03-18,1774,7.4,Cloud AI Solutions -AI11233,Research Scientist,105432,USD,105432,EX,CT,China,M,China,0,"Spark, Kubernetes, Java, Statistics, TensorFlow",Bachelor,17,Energy,2024-07-19,2024-08-24,2474,7.7,Digital Transformation LLC -AI11234,Machine Learning Engineer,84482,USD,84482,EN,CT,United States,S,Malaysia,100,"Docker, Scala, NLP, AWS",Associate,1,Media,2024-06-27,2024-07-17,2399,5.2,Advanced Robotics -AI11235,Data Analyst,207967,USD,207967,EX,PT,Finland,S,Estonia,0,"Statistics, Mathematics, PyTorch",Master,11,Telecommunications,2024-02-17,2024-04-04,586,7.5,Machine Intelligence Group -AI11236,AI Product Manager,105835,USD,105835,MI,FT,Ireland,M,Ireland,0,"Azure, GCP, Git, AWS",PhD,4,Energy,2024-05-14,2024-07-20,1077,5.6,Predictive Systems -AI11237,Data Scientist,90084,USD,90084,MI,CT,Ireland,L,Japan,50,"R, SQL, Python, Spark, Deep Learning",Associate,3,Transportation,2025-03-24,2025-05-04,1376,5.1,Machine Intelligence Group -AI11238,AI Architect,70560,AUD,95256,EN,FT,Australia,M,Australia,50,"Python, TensorFlow, Java, Spark",Bachelor,0,Finance,2024-01-11,2024-03-09,1687,7.2,Neural Networks Co -AI11239,Data Scientist,119651,EUR,101703,SE,FL,France,S,France,0,"Linux, Python, Statistics, Kubernetes",Master,5,Media,2024-12-29,2025-03-11,1854,7.6,Digital Transformation LLC -AI11240,Deep Learning Engineer,81359,EUR,69155,EN,PT,Netherlands,L,Estonia,100,"Linux, Python, Spark, Computer Vision, Statistics",Bachelor,1,Consulting,2025-03-24,2025-05-11,607,8,Neural Networks Co -AI11241,Head of AI,94506,USD,94506,MI,CT,Ireland,M,Spain,0,"PyTorch, Deep Learning, MLOps",Master,3,Manufacturing,2024-02-08,2024-02-24,854,8.2,Digital Transformation LLC -AI11242,AI Consultant,57555,CAD,71944,EN,FT,Canada,S,Canada,0,"Git, Java, SQL",Bachelor,1,Gaming,2025-01-14,2025-03-01,993,8.6,TechCorp Inc -AI11243,AI Architect,58309,USD,58309,MI,FL,China,L,China,50,"Java, Linux, Tableau, Mathematics",Bachelor,4,Healthcare,2024-07-20,2024-09-03,671,7.1,Cognitive Computing -AI11244,Data Analyst,104581,USD,104581,MI,FT,United States,L,United States,100,"Python, Tableau, AWS",Associate,3,Retail,2024-02-07,2024-03-08,1281,9.1,Smart Analytics -AI11245,AI Architect,51087,USD,51087,SE,FT,China,M,China,50,"Data Visualization, Git, Kubernetes, Spark, R",PhD,8,Government,2024-01-22,2024-02-24,1657,7.2,Autonomous Tech -AI11246,Robotics Engineer,163866,CHF,147479,MI,FT,Switzerland,L,Switzerland,100,"Kubernetes, Scala, Deep Learning, AWS, Linux",PhD,3,Media,2024-04-01,2024-05-04,1667,5.9,DataVision Ltd -AI11247,Data Analyst,48310,USD,48310,EN,CT,Finland,M,Finland,50,"Data Visualization, Kubernetes, Scala",Associate,1,Transportation,2025-04-24,2025-05-29,1452,8.1,Digital Transformation LLC -AI11248,Machine Learning Engineer,189402,USD,189402,SE,FT,Denmark,L,Denmark,100,"Hadoop, GCP, Tableau, Computer Vision",Associate,8,Automotive,2025-03-05,2025-03-30,1720,6.8,Smart Analytics -AI11249,Robotics Engineer,30514,USD,30514,MI,FT,India,L,Czech Republic,0,"Python, Git, TensorFlow, Deep Learning, PyTorch",Bachelor,4,Media,2025-03-30,2025-04-13,1193,5.6,Predictive Systems -AI11250,AI Consultant,69642,GBP,52232,EN,PT,United Kingdom,L,Kenya,50,"Spark, Python, Computer Vision, Data Visualization, TensorFlow",Bachelor,0,Telecommunications,2024-09-17,2024-11-25,1878,10,Future Systems -AI11251,Head of AI,117224,JPY,12894640,SE,FT,Japan,S,South Africa,100,"AWS, R, PyTorch, Java, SQL",Bachelor,5,Media,2024-05-22,2024-06-16,2113,7.6,Digital Transformation LLC -AI11252,Computer Vision Engineer,100484,CAD,125605,MI,FL,Canada,L,Canada,50,"Java, Hadoop, PyTorch, AWS, TensorFlow",PhD,3,Consulting,2024-02-20,2024-04-02,2263,6.1,DeepTech Ventures -AI11253,AI Software Engineer,124618,CHF,112156,EN,PT,Switzerland,L,Switzerland,50,"Git, Python, R, Statistics",PhD,0,Transportation,2024-09-14,2024-10-05,1843,9.9,Future Systems -AI11254,AI Product Manager,191724,USD,191724,EX,FL,Ireland,S,Ireland,50,"Python, Hadoop, Spark, Docker",PhD,18,Education,2024-03-26,2024-06-01,2039,9.3,Machine Intelligence Group -AI11255,ML Ops Engineer,97569,USD,97569,EN,CT,Denmark,M,Denmark,100,"NLP, Statistics, SQL, PyTorch, Linux",Master,0,Education,2024-02-12,2024-03-25,2263,9.5,TechCorp Inc -AI11256,Computer Vision Engineer,118684,USD,118684,SE,CT,Finland,L,Finland,100,"Scala, Python, Statistics, Linux",PhD,9,Manufacturing,2024-08-29,2024-10-17,1785,6,DeepTech Ventures -AI11257,Deep Learning Engineer,80305,CHF,72275,EN,FL,Switzerland,S,Switzerland,50,"Git, GCP, SQL, Spark, Docker",PhD,1,Healthcare,2024-10-22,2024-12-02,1862,6.3,Machine Intelligence Group -AI11258,Principal Data Scientist,214921,USD,214921,EX,CT,Sweden,S,India,100,"Kubernetes, AWS, GCP, Git, Spark",PhD,17,Retail,2024-02-01,2024-03-15,1894,6,Predictive Systems -AI11259,AI Architect,178983,CHF,161085,SE,PT,Switzerland,L,Germany,100,"Java, TensorFlow, Hadoop",Associate,9,Transportation,2024-11-26,2024-12-30,1204,9.5,Algorithmic Solutions -AI11260,AI Product Manager,78327,USD,78327,MI,PT,Finland,L,Finland,50,"Spark, AWS, SQL, Tableau",Associate,4,Finance,2025-02-14,2025-03-28,2387,6.1,Predictive Systems -AI11261,Robotics Engineer,85793,USD,85793,EN,FL,Denmark,S,Denmark,0,"AWS, Java, GCP, PyTorch",Associate,0,Telecommunications,2024-07-25,2024-09-09,866,7.7,Predictive Systems -AI11262,AI Specialist,80644,EUR,68547,EN,FT,Netherlands,L,Netherlands,50,"Git, GCP, Java, Python, Computer Vision",Master,1,Energy,2025-04-08,2025-05-24,2017,6,DataVision Ltd -AI11263,AI Specialist,123929,SGD,161108,MI,CT,Singapore,L,Singapore,50,"PyTorch, TensorFlow, Mathematics, Deep Learning, Git",Bachelor,2,Automotive,2024-05-08,2024-06-25,1499,8.7,Algorithmic Solutions -AI11264,AI Research Scientist,108923,USD,108923,MI,FT,Finland,L,New Zealand,0,"Linux, Docker, Deep Learning, PyTorch",Master,4,Media,2024-09-28,2024-11-21,2273,9.3,AI Innovations -AI11265,Machine Learning Engineer,140940,USD,140940,SE,FL,South Korea,L,South Korea,50,"R, PyTorch, Computer Vision",Bachelor,9,Media,2024-10-03,2024-11-11,1587,8.4,Cognitive Computing -AI11266,NLP Engineer,315420,CHF,283878,EX,PT,Switzerland,L,Switzerland,100,"MLOps, SQL, PyTorch, Linux",PhD,13,Education,2024-10-14,2024-12-14,1791,9.4,TechCorp Inc -AI11267,Head of AI,71258,CAD,89073,EN,FL,Canada,M,Thailand,50,"GCP, Spark, Azure, PyTorch",Master,1,Technology,2024-05-29,2024-07-22,2017,5.9,Digital Transformation LLC -AI11268,Data Engineer,105428,JPY,11597080,MI,PT,Japan,L,Japan,0,"SQL, Python, Java, Tableau, TensorFlow",Associate,4,Technology,2025-03-29,2025-04-29,1302,5.6,Future Systems -AI11269,Data Scientist,167067,EUR,142007,EX,PT,France,L,Hungary,50,"Linux, PyTorch, Git, AWS, Java",Associate,12,Retail,2025-03-24,2025-04-15,1311,9.3,DeepTech Ventures -AI11270,Computer Vision Engineer,75062,USD,75062,EN,FT,Denmark,S,Denmark,50,"AWS, TensorFlow, Computer Vision, NLP",PhD,0,Gaming,2024-04-26,2024-06-17,2110,7,Cognitive Computing -AI11271,Computer Vision Engineer,54168,USD,54168,EX,FL,India,M,India,100,"Scala, PyTorch, Computer Vision, TensorFlow",PhD,10,Education,2024-04-09,2024-05-17,1658,7.9,Cognitive Computing -AI11272,Data Analyst,61930,SGD,80509,EN,PT,Singapore,M,Singapore,0,"Git, Computer Vision, SQL, Python, MLOps",Master,0,Consulting,2024-11-25,2025-01-08,1655,7.3,AI Innovations -AI11273,AI Product Manager,148519,EUR,126241,EX,PT,Austria,M,Austria,100,"Computer Vision, Data Visualization, Python",Master,11,Gaming,2025-04-27,2025-05-21,669,7.5,Smart Analytics -AI11274,Deep Learning Engineer,199528,USD,199528,EX,PT,Norway,S,Norway,100,"Python, Git, Computer Vision, TensorFlow",PhD,12,Finance,2024-02-08,2024-03-17,544,6.2,Quantum Computing Inc -AI11275,AI Architect,53596,USD,53596,EX,FL,India,S,India,50,"Azure, MLOps, Statistics, PyTorch, Computer Vision",Associate,11,Gaming,2024-11-09,2024-12-30,2407,9.4,Autonomous Tech -AI11276,Head of AI,97034,USD,97034,EN,CT,Denmark,M,Denmark,50,"PyTorch, Kubernetes, Deep Learning, Linux, Azure",Master,0,Media,2024-05-24,2024-07-01,1585,5.5,Cognitive Computing -AI11277,ML Ops Engineer,102547,AUD,138438,SE,FT,Australia,S,Australia,100,"Deep Learning, Python, Hadoop",Bachelor,5,Telecommunications,2024-05-07,2024-07-10,1872,7.2,Smart Analytics -AI11278,Machine Learning Engineer,63599,SGD,82679,EN,FT,Singapore,M,Singapore,50,"NLP, SQL, MLOps",Bachelor,1,Manufacturing,2024-10-17,2024-12-12,1319,6.6,Cloud AI Solutions -AI11279,Computer Vision Engineer,93730,EUR,79671,MI,FL,Austria,L,Austria,100,"Scala, Python, Mathematics, Kubernetes, Spark",Bachelor,4,Automotive,2024-11-08,2024-12-08,1254,6.8,DataVision Ltd -AI11280,AI Architect,205424,USD,205424,SE,FL,United States,L,Austria,100,"Data Visualization, Hadoop, Scala, PyTorch, Spark",Associate,7,Gaming,2024-04-03,2024-05-20,2330,8.7,Cognitive Computing -AI11281,Computer Vision Engineer,88065,USD,88065,EN,FL,Denmark,S,Denmark,100,"Linux, R, PyTorch, TensorFlow, Spark",Bachelor,1,Gaming,2025-03-23,2025-04-28,2085,5.6,Cloud AI Solutions -AI11282,ML Ops Engineer,115890,USD,115890,SE,FL,Israel,M,Israel,50,"PyTorch, GCP, Git",Master,9,Transportation,2024-11-04,2024-12-13,1762,7.5,AI Innovations -AI11283,Data Analyst,233264,SGD,303243,EX,CT,Singapore,S,Singapore,100,"Kubernetes, Scala, Tableau, Deep Learning",Associate,11,Telecommunications,2024-06-15,2024-08-03,814,6.1,Digital Transformation LLC -AI11284,AI Consultant,85232,EUR,72447,MI,FT,France,M,France,100,"Linux, Scala, Statistics, Python",PhD,3,Energy,2024-10-01,2024-11-26,2152,9.3,Predictive Systems -AI11285,AI Product Manager,125339,CHF,112805,MI,CT,Switzerland,M,Switzerland,0,"Python, Mathematics, Docker",PhD,2,Retail,2025-02-19,2025-05-02,1397,9.6,DataVision Ltd -AI11286,Research Scientist,185360,USD,185360,EX,CT,Ireland,L,Ireland,50,"NLP, Kubernetes, Docker, Python",Master,16,Retail,2024-01-23,2024-02-18,1618,7.8,Neural Networks Co -AI11287,Head of AI,106629,EUR,90635,MI,CT,France,L,France,0,"Data Visualization, Python, Azure, Scala",Bachelor,3,Retail,2025-02-06,2025-04-10,1496,8.7,Cloud AI Solutions -AI11288,Computer Vision Engineer,97894,USD,97894,EX,PT,India,L,India,0,"Scala, Java, Linux, R, SQL",PhD,13,Gaming,2025-01-01,2025-01-26,1062,9.3,Digital Transformation LLC -AI11289,Research Scientist,79189,USD,79189,EX,PT,India,M,Canada,50,"Java, Kubernetes, Scala",Master,12,Consulting,2024-05-06,2024-07-03,2204,9,Advanced Robotics -AI11290,AI Consultant,89489,JPY,9843790,MI,CT,Japan,L,Japan,50,"Docker, SQL, PyTorch",PhD,3,Retail,2024-11-24,2025-01-17,1809,6.4,AI Innovations -AI11291,Head of AI,119280,USD,119280,MI,CT,Israel,L,Netherlands,0,"Docker, Spark, Kubernetes, Scala, Mathematics",PhD,2,Manufacturing,2024-02-28,2024-05-05,716,7.1,DeepTech Ventures -AI11292,Robotics Engineer,219065,EUR,186205,EX,FT,Germany,S,Germany,0,"Python, Spark, Tableau",Associate,16,Manufacturing,2024-02-21,2024-03-13,800,7.6,TechCorp Inc -AI11293,Head of AI,218346,SGD,283850,EX,PT,Singapore,S,Singapore,50,"TensorFlow, Linux, GCP, Computer Vision, Deep Learning",Master,15,Finance,2024-05-22,2024-07-24,1652,9.7,Algorithmic Solutions -AI11294,AI Specialist,154420,SGD,200746,SE,CT,Singapore,M,Singapore,100,"Python, Git, Spark, Scala, Azure",Associate,7,Technology,2024-04-21,2024-06-29,645,8.8,Neural Networks Co -AI11295,AI Specialist,126566,USD,126566,SE,PT,Denmark,S,Norway,50,"Python, Data Visualization, Statistics",Bachelor,6,Consulting,2025-01-05,2025-01-28,1877,6.3,Cognitive Computing -AI11296,NLP Engineer,67525,AUD,91159,EN,FT,Australia,S,Australia,100,"Python, TensorFlow, Linux, AWS",Master,0,Gaming,2024-02-07,2024-04-03,1711,9.2,Digital Transformation LLC -AI11297,Research Scientist,130551,SGD,169716,SE,PT,Singapore,M,Singapore,0,"SQL, Kubernetes, Python, MLOps, Scala",Master,8,Telecommunications,2025-02-03,2025-03-04,890,7.7,Machine Intelligence Group -AI11298,Robotics Engineer,67815,USD,67815,EN,FL,Sweden,L,Sweden,0,"GCP, Scala, Kubernetes, Deep Learning",Master,1,Real Estate,2024-06-15,2024-07-30,2103,9.3,TechCorp Inc -AI11299,Data Scientist,26237,USD,26237,MI,CT,India,S,India,50,"MLOps, Git, SQL, Azure, Statistics",PhD,3,Transportation,2024-09-28,2024-11-27,850,5.9,Machine Intelligence Group -AI11300,Data Scientist,285608,SGD,371290,EX,PT,Singapore,L,Singapore,0,"PyTorch, Statistics, Computer Vision, GCP, Mathematics",PhD,10,Media,2025-01-09,2025-02-21,953,5.4,Autonomous Tech -AI11301,Machine Learning Engineer,73386,USD,73386,EN,FT,South Korea,L,South Korea,0,"Scala, Python, TensorFlow, Git, Hadoop",Associate,0,Manufacturing,2024-05-15,2024-07-03,1736,9.8,Autonomous Tech -AI11302,AI Specialist,24994,USD,24994,EN,CT,China,S,China,0,"Java, Kubernetes, GCP, Docker",Bachelor,0,Media,2024-04-08,2024-05-15,1010,7.6,Advanced Robotics -AI11303,Machine Learning Researcher,84205,AUD,113677,MI,FL,Australia,M,Australia,100,"Hadoop, MLOps, PyTorch, Scala, Kubernetes",Master,3,Energy,2024-06-17,2024-07-02,2481,9,Smart Analytics -AI11304,Deep Learning Engineer,167419,USD,167419,EX,FL,Israel,S,Australia,100,"AWS, Mathematics, Scala",Bachelor,11,Consulting,2024-08-10,2024-09-19,2109,6.1,Neural Networks Co -AI11305,Data Engineer,83819,EUR,71246,EN,CT,Austria,L,Austria,50,"Spark, Deep Learning, TensorFlow, Python, Git",Bachelor,1,Telecommunications,2025-04-05,2025-06-08,2018,7.8,Autonomous Tech -AI11306,Data Scientist,71467,USD,71467,EX,CT,China,M,China,100,"Python, Kubernetes, Tableau, Computer Vision",Master,11,Telecommunications,2024-09-05,2024-09-23,1673,5.8,Predictive Systems -AI11307,AI Specialist,150771,EUR,128155,SE,PT,Netherlands,L,Finland,0,"PyTorch, Kubernetes, Mathematics, Git",Master,5,Media,2025-02-08,2025-02-24,835,7.9,Cloud AI Solutions -AI11308,Autonomous Systems Engineer,187205,USD,187205,EX,FT,Finland,S,Finland,0,"Python, Scala, Git",Bachelor,15,Manufacturing,2024-05-09,2024-05-31,1333,9.2,Quantum Computing Inc -AI11309,AI Architect,25891,USD,25891,EN,FT,China,M,China,50,"SQL, Scala, Deep Learning",PhD,1,Automotive,2024-10-04,2024-12-05,2089,5.4,Cloud AI Solutions -AI11310,Machine Learning Researcher,62044,USD,62044,SE,CT,China,M,France,0,"Deep Learning, Statistics, SQL",Bachelor,5,Automotive,2025-02-13,2025-03-18,2477,6.4,DeepTech Ventures -AI11311,Data Scientist,155807,USD,155807,SE,CT,Israel,L,Israel,100,"Computer Vision, MLOps, Linux, TensorFlow",PhD,6,Real Estate,2024-07-22,2024-09-07,1354,9.4,Advanced Robotics -AI11312,Autonomous Systems Engineer,75916,EUR,64529,EN,FL,Netherlands,S,Netherlands,50,"TensorFlow, Mathematics, Java, MLOps, SQL",Associate,1,Gaming,2024-01-30,2024-03-29,708,7.8,Machine Intelligence Group -AI11313,Autonomous Systems Engineer,93324,SGD,121321,EN,FL,Singapore,L,Singapore,50,"Azure, GCP, Computer Vision, Deep Learning",PhD,1,Manufacturing,2024-04-18,2024-05-19,1592,9.6,Digital Transformation LLC -AI11314,Research Scientist,176161,EUR,149737,EX,FL,France,M,France,50,"Scala, Computer Vision, Azure",Bachelor,11,Real Estate,2024-12-10,2025-02-04,1294,9.5,Autonomous Tech -AI11315,ML Ops Engineer,135633,CAD,169541,SE,CT,Canada,L,Canada,100,"Python, GCP, TensorFlow",PhD,9,Manufacturing,2025-04-11,2025-05-30,2051,8,Future Systems -AI11316,Computer Vision Engineer,96084,USD,96084,MI,FT,Ireland,S,Thailand,50,"Kubernetes, Java, R, Deep Learning",Master,4,Real Estate,2024-06-19,2024-07-20,2346,9.6,AI Innovations -AI11317,AI Product Manager,229922,CHF,206930,EX,FT,Switzerland,M,Switzerland,50,"Python, TensorFlow, Scala, Kubernetes",Associate,15,Transportation,2025-01-14,2025-02-24,1777,7.5,Neural Networks Co -AI11318,AI Research Scientist,92771,USD,92771,EN,CT,Denmark,L,Denmark,50,"Git, Kubernetes, Python",Bachelor,1,Transportation,2024-09-10,2024-10-17,1267,9.4,Predictive Systems -AI11319,Machine Learning Engineer,137444,JPY,15118840,SE,FL,Japan,L,Japan,100,"Docker, Linux, Tableau, NLP, Mathematics",Associate,6,Energy,2024-01-14,2024-03-05,2117,5.1,Neural Networks Co -AI11320,Research Scientist,72988,CAD,91235,EN,FL,Canada,L,Canada,100,"Git, Python, Java, AWS, Scala",Associate,0,Automotive,2024-05-16,2024-06-12,1189,7.7,Smart Analytics -AI11321,Autonomous Systems Engineer,129227,USD,129227,SE,PT,Denmark,S,Denmark,0,"Python, TensorFlow, Git, Deep Learning",Bachelor,8,Automotive,2024-09-05,2024-10-31,1294,6.7,Future Systems -AI11322,ML Ops Engineer,84467,USD,84467,EN,FT,Ireland,L,Ireland,0,"SQL, Docker, Computer Vision",Master,0,Transportation,2025-01-15,2025-03-20,1191,9.7,Predictive Systems -AI11323,Data Analyst,98088,GBP,73566,MI,FL,United Kingdom,L,United Kingdom,0,"PyTorch, Mathematics, Git, Kubernetes, Python",Master,3,Government,2024-05-09,2024-07-11,988,7.3,Cloud AI Solutions -AI11324,Research Scientist,119116,USD,119116,SE,PT,Sweden,S,Sweden,100,"Docker, Linux, Mathematics, Deep Learning",PhD,9,Consulting,2024-03-26,2024-04-21,1723,6.2,Predictive Systems -AI11325,Autonomous Systems Engineer,181037,USD,181037,EX,FL,Ireland,M,Ireland,100,"Linux, Spark, NLP",PhD,18,Energy,2024-09-11,2024-11-23,1753,5.3,Digital Transformation LLC -AI11326,AI Consultant,79650,JPY,8761500,EN,FT,Japan,M,Thailand,50,"Tableau, GCP, PyTorch, MLOps, TensorFlow",PhD,1,Telecommunications,2025-04-06,2025-06-07,1950,9.7,Cognitive Computing -AI11327,Robotics Engineer,81235,CHF,73112,EN,FL,Switzerland,M,Switzerland,50,"R, Spark, Python, Azure",Bachelor,0,Government,2024-04-01,2024-06-08,1105,7.9,Neural Networks Co -AI11328,AI Architect,71268,EUR,60578,EN,CT,Netherlands,M,Netherlands,50,"Tableau, MLOps, Kubernetes, Scala, Mathematics",PhD,1,Telecommunications,2025-03-14,2025-04-10,630,5.3,Autonomous Tech -AI11329,AI Product Manager,227826,CAD,284783,EX,PT,Canada,M,Canada,50,"R, Scala, PyTorch, Python, Linux",Master,13,Technology,2024-08-30,2024-10-07,1875,6.1,Future Systems -AI11330,Robotics Engineer,96577,USD,96577,MI,PT,Ireland,L,Romania,50,"Deep Learning, Spark, Computer Vision, Scala",PhD,3,Energy,2025-04-18,2025-06-01,1204,7.4,Cognitive Computing -AI11331,Data Analyst,32109,USD,32109,EN,CT,China,L,China,0,"Git, NLP, Data Visualization, Mathematics, Linux",Associate,1,Transportation,2024-02-12,2024-03-10,2181,7.1,Smart Analytics -AI11332,AI Architect,125192,USD,125192,EX,PT,China,L,China,0,"MLOps, Deep Learning, R, SQL",Master,14,Manufacturing,2025-03-17,2025-04-21,1763,9.2,Quantum Computing Inc -AI11333,Machine Learning Researcher,70652,JPY,7771720,EN,FL,Japan,L,Japan,100,"Computer Vision, SQL, Linux, Tableau, Git",Bachelor,1,Transportation,2024-12-25,2025-01-15,2207,6,Quantum Computing Inc -AI11334,NLP Engineer,114477,USD,114477,SE,FT,South Korea,L,South Korea,100,"MLOps, Data Visualization, Azure, Docker",Master,7,Gaming,2024-07-12,2024-09-13,2184,7.6,TechCorp Inc -AI11335,Robotics Engineer,46341,USD,46341,EN,CT,South Korea,S,South Korea,100,"Kubernetes, Tableau, NLP, Spark, Linux",Associate,1,Technology,2024-04-05,2024-05-09,2226,7.3,Cognitive Computing -AI11336,Research Scientist,68397,USD,68397,MI,PT,Israel,M,Israel,50,"Tableau, Scala, GCP",Master,4,Automotive,2024-05-05,2024-06-27,1629,7.2,AI Innovations -AI11337,Machine Learning Researcher,87051,USD,87051,MI,FL,Finland,S,Finland,100,"Linux, Java, Data Visualization, Computer Vision",PhD,4,Government,2025-03-20,2025-04-11,1691,9.9,AI Innovations -AI11338,AI Architect,79887,USD,79887,EN,FT,United States,L,United States,0,"Computer Vision, SQL, R",Bachelor,0,Automotive,2025-02-24,2025-04-28,1084,8.7,Smart Analytics -AI11339,Deep Learning Engineer,134547,EUR,114365,EX,FT,France,S,Turkey,50,"Computer Vision, Python, Tableau, TensorFlow, Statistics",Associate,19,Consulting,2024-05-13,2024-07-07,2369,9.9,Algorithmic Solutions -AI11340,Deep Learning Engineer,108427,EUR,92163,MI,FL,Austria,L,Austria,0,"Tableau, GCP, Linux",Associate,2,Real Estate,2024-01-16,2024-02-05,2062,8.8,Smart Analytics -AI11341,Research Scientist,45769,EUR,38904,EN,FL,Austria,S,Canada,50,"Data Visualization, Hadoop, Mathematics, Kubernetes",Bachelor,1,Technology,2024-07-09,2024-08-09,2381,5.1,Digital Transformation LLC -AI11342,Research Scientist,65686,EUR,55833,EN,FT,Netherlands,L,Netherlands,50,"Python, Deep Learning, Git, Scala, MLOps",PhD,1,Telecommunications,2024-10-01,2024-12-09,1542,7.1,Future Systems -AI11343,AI Research Scientist,134629,USD,134629,EX,PT,Israel,M,Israel,0,"R, GCP, Docker, Kubernetes",Bachelor,16,Consulting,2025-04-07,2025-05-25,1542,8.7,Quantum Computing Inc -AI11344,Machine Learning Engineer,105266,USD,105266,EN,FT,Norway,L,Romania,100,"Python, TensorFlow, Kubernetes, PyTorch",Bachelor,0,Government,2024-10-01,2024-11-13,1447,8.2,AI Innovations -AI11345,ML Ops Engineer,111826,CAD,139783,SE,CT,Canada,L,New Zealand,0,"Linux, Python, AWS, SQL",Associate,9,Automotive,2025-02-26,2025-04-29,949,8.1,Advanced Robotics -AI11346,Robotics Engineer,97870,USD,97870,SE,FL,Sweden,S,Norway,0,"Spark, Deep Learning, R",Associate,8,Energy,2024-01-26,2024-03-14,582,9.6,Future Systems -AI11347,NLP Engineer,56233,USD,56233,SE,CT,China,S,China,50,"Tableau, SQL, PyTorch, MLOps, Docker",PhD,9,Manufacturing,2024-05-14,2024-07-03,710,6,TechCorp Inc -AI11348,Data Scientist,136380,AUD,184113,SE,CT,Australia,M,Australia,100,"Hadoop, Docker, Scala",Bachelor,5,Real Estate,2025-02-05,2025-03-17,711,8.6,Cloud AI Solutions -AI11349,Machine Learning Engineer,129432,USD,129432,SE,PT,Sweden,M,Sweden,0,"Linux, Azure, NLP, Statistics, AWS",Associate,7,Gaming,2025-04-13,2025-05-13,2032,8.1,AI Innovations -AI11350,Deep Learning Engineer,274081,USD,274081,EX,FT,Denmark,S,Luxembourg,0,"SQL, Spark, Statistics, Git, Python",Associate,17,Real Estate,2024-12-26,2025-02-23,1154,8.8,DataVision Ltd -AI11351,Data Engineer,70458,USD,70458,MI,PT,Finland,S,Finland,50,"Scala, SQL, Python, Spark, GCP",Bachelor,3,Telecommunications,2024-12-28,2025-01-25,1865,7.4,DataVision Ltd -AI11352,Deep Learning Engineer,54782,CAD,68478,EN,FT,Canada,S,Canada,50,"Hadoop, Data Visualization, AWS, TensorFlow",PhD,0,Government,2024-07-12,2024-08-29,2043,9.8,Advanced Robotics -AI11353,AI Research Scientist,64330,EUR,54681,EN,FT,Austria,M,Austria,100,"Deep Learning, Tableau, Python, Azure",Bachelor,0,Media,2024-03-05,2024-03-25,1355,7.6,Digital Transformation LLC -AI11354,Head of AI,253257,USD,253257,EX,PT,United States,L,United States,100,"GCP, Python, AWS",PhD,12,Transportation,2025-03-31,2025-05-04,950,7.9,Future Systems -AI11355,AI Research Scientist,72157,JPY,7937270,EN,CT,Japan,S,Japan,50,"Azure, Linux, R, Tableau",Associate,1,Gaming,2025-03-29,2025-04-21,1647,6.3,Digital Transformation LLC -AI11356,AI Specialist,79437,EUR,67521,EN,PT,Netherlands,M,Netherlands,100,"Tableau, Hadoop, Java",Master,0,Finance,2025-03-12,2025-03-29,566,6.8,Cognitive Computing -AI11357,AI Research Scientist,89807,USD,89807,EN,PT,Norway,S,Norway,100,"Docker, Spark, MLOps, Scala",Bachelor,0,Consulting,2024-02-28,2024-04-21,987,7.5,TechCorp Inc -AI11358,Data Engineer,223811,USD,223811,EX,FL,Norway,L,Norway,100,"Deep Learning, TensorFlow, NLP, Hadoop",Associate,13,Government,2025-02-10,2025-03-06,1630,6.3,Cloud AI Solutions -AI11359,Principal Data Scientist,43079,USD,43079,SE,CT,India,M,India,100,"MLOps, GCP, Java, PyTorch, Azure",Bachelor,7,Energy,2024-08-23,2024-10-24,781,9.2,Autonomous Tech -AI11360,Data Engineer,171228,SGD,222596,SE,FL,Singapore,L,Singapore,0,"Data Visualization, Hadoop, Python",Bachelor,7,Automotive,2024-12-23,2025-01-25,1585,7.1,DataVision Ltd -AI11361,AI Software Engineer,320305,USD,320305,EX,FT,United States,L,United States,50,"Scala, Hadoop, Tableau, MLOps, Spark",Associate,11,Healthcare,2025-03-05,2025-04-07,2126,9.8,Advanced Robotics -AI11362,AI Specialist,265506,CAD,331883,EX,FT,Canada,L,Canada,100,"AWS, Data Visualization, GCP, Linux",Bachelor,16,Retail,2025-03-18,2025-05-28,1455,7.6,Machine Intelligence Group -AI11363,AI Product Manager,191096,CHF,171986,SE,CT,Switzerland,S,Switzerland,100,"AWS, PyTorch, Computer Vision",Bachelor,6,Telecommunications,2025-04-21,2025-06-06,1793,9.5,Machine Intelligence Group -AI11364,Computer Vision Engineer,46630,USD,46630,MI,PT,China,L,China,100,"Computer Vision, Mathematics, TensorFlow, Python",PhD,4,Healthcare,2024-01-19,2024-03-24,531,5.1,Cloud AI Solutions -AI11365,AI Specialist,97986,USD,97986,SE,FL,Ireland,S,Russia,100,"Python, GCP, TensorFlow, Java",PhD,5,Healthcare,2025-02-26,2025-03-27,686,8,AI Innovations -AI11366,ML Ops Engineer,136685,USD,136685,SE,PT,South Korea,L,South Korea,0,"PyTorch, AWS, Linux",Bachelor,5,Technology,2024-10-14,2024-11-27,784,6.5,Cloud AI Solutions -AI11367,ML Ops Engineer,90657,CAD,113321,MI,PT,Canada,M,Canada,0,"PyTorch, SQL, Mathematics",Bachelor,2,Automotive,2024-10-09,2024-12-10,991,9.8,AI Innovations -AI11368,Research Scientist,170307,USD,170307,SE,FT,United States,L,United States,100,"Azure, Git, AWS",PhD,9,Technology,2025-01-02,2025-03-08,2456,9,Advanced Robotics -AI11369,Deep Learning Engineer,137251,USD,137251,MI,CT,Denmark,L,Denmark,0,"Java, SQL, PyTorch, AWS",Bachelor,2,Telecommunications,2025-02-12,2025-03-07,2401,9.2,Future Systems -AI11370,Data Scientist,175338,USD,175338,EX,PT,Finland,L,Finland,100,"TensorFlow, R, Mathematics, GCP, Deep Learning",Associate,10,Government,2025-02-19,2025-03-09,602,9.1,Digital Transformation LLC -AI11371,Deep Learning Engineer,81903,JPY,9009330,EN,PT,Japan,L,Japan,100,"Scala, Java, GCP",PhD,1,Energy,2024-11-10,2024-11-27,2492,8.8,Predictive Systems -AI11372,Data Engineer,119281,SGD,155065,SE,FT,Singapore,S,Singapore,0,"SQL, Python, Tableau, Deep Learning, AWS",Bachelor,7,Transportation,2024-05-06,2024-07-01,579,6.1,Machine Intelligence Group -AI11373,Machine Learning Researcher,59467,USD,59467,EN,FT,South Korea,L,South Korea,100,"SQL, Git, PyTorch, Kubernetes, Java",PhD,1,Finance,2024-12-08,2025-01-06,1293,9.8,Neural Networks Co -AI11374,Head of AI,136127,EUR,115708,SE,FT,Germany,M,Germany,100,"Git, Computer Vision, Spark",Associate,8,Healthcare,2024-04-18,2024-06-18,1980,7.5,Algorithmic Solutions -AI11375,Deep Learning Engineer,150034,USD,150034,EX,FT,Israel,S,Israel,100,"AWS, Git, Python, TensorFlow, R",Master,19,Government,2025-02-12,2025-04-21,1236,8.8,Autonomous Tech -AI11376,Research Scientist,293963,EUR,249869,EX,FT,Netherlands,L,Netherlands,50,"Scala, NLP, AWS, Azure, Git",Bachelor,12,Manufacturing,2024-06-26,2024-07-24,1473,8,Cognitive Computing -AI11377,NLP Engineer,93910,USD,93910,EN,PT,Norway,M,South Korea,50,"R, Deep Learning, Git, Python, Docker",PhD,1,Energy,2024-11-19,2025-01-20,782,7.6,Predictive Systems -AI11378,AI Specialist,106154,CAD,132693,SE,FL,Canada,S,Canada,100,"Mathematics, Python, Statistics",PhD,9,Retail,2024-09-22,2024-11-24,869,7.9,AI Innovations -AI11379,Principal Data Scientist,83026,EUR,70572,EN,CT,Germany,L,Germany,100,"Java, R, Hadoop, Scala",Associate,1,Education,2025-02-15,2025-04-11,924,6.6,AI Innovations -AI11380,AI Consultant,62488,USD,62488,EX,FL,India,S,India,0,"Git, NLP, Kubernetes, AWS, Computer Vision",Master,10,Healthcare,2024-05-21,2024-07-22,1404,6.3,Cognitive Computing -AI11381,Data Engineer,82469,JPY,9071590,EN,FL,Japan,L,Japan,100,"PyTorch, TensorFlow, Mathematics, Deep Learning, Data Visualization",Associate,0,Telecommunications,2024-07-21,2024-09-18,1642,5.3,DeepTech Ventures -AI11382,AI Research Scientist,37153,USD,37153,MI,FL,India,M,India,100,"Java, R, GCP, MLOps, Docker",PhD,4,Energy,2024-02-14,2024-04-04,2213,8.1,Cloud AI Solutions -AI11383,Head of AI,100902,USD,100902,SE,PT,South Korea,L,South Korea,50,"Python, Java, Linux, TensorFlow",PhD,8,Education,2024-05-27,2024-07-13,1402,9.1,Predictive Systems -AI11384,Data Engineer,61167,SGD,79517,EN,FT,Singapore,S,Singapore,0,"Python, Java, SQL, Linux, NLP",Associate,1,Real Estate,2024-07-25,2024-09-17,1081,8,Advanced Robotics -AI11385,NLP Engineer,72149,USD,72149,EX,PT,India,L,Ukraine,100,"Python, GCP, Tableau",PhD,16,Education,2024-09-13,2024-11-18,917,8.4,Future Systems -AI11386,Machine Learning Engineer,145674,USD,145674,SE,FL,Finland,L,Finland,0,"Python, Docker, Hadoop",PhD,9,Finance,2025-03-06,2025-04-14,1983,9.4,Neural Networks Co -AI11387,NLP Engineer,121414,CAD,151768,SE,FL,Canada,M,Canada,50,"Linux, Hadoop, Tableau, SQL, Python",Bachelor,7,Education,2024-08-23,2024-10-12,890,6.6,Digital Transformation LLC -AI11388,ML Ops Engineer,78140,EUR,66419,EN,PT,France,L,France,100,"SQL, Git, Scala, Hadoop, NLP",Associate,1,Automotive,2024-12-14,2025-02-06,826,8.9,Digital Transformation LLC -AI11389,Head of AI,141442,USD,141442,SE,FL,United States,M,United States,50,"Kubernetes, AWS, Data Visualization",PhD,9,Real Estate,2025-03-26,2025-05-28,1718,8.5,Smart Analytics -AI11390,Machine Learning Researcher,96067,USD,96067,MI,CT,Israel,L,Israel,50,"Tableau, Spark, Hadoop",PhD,2,Healthcare,2025-04-20,2025-06-26,1870,7.7,Cloud AI Solutions -AI11391,Data Scientist,388535,CHF,349682,EX,CT,Switzerland,L,Egypt,50,"MLOps, Azure, Data Visualization, Scala, SQL",Master,16,Transportation,2024-06-20,2024-07-06,929,9.4,Predictive Systems -AI11392,Deep Learning Engineer,132494,CAD,165618,SE,FL,Canada,L,Canada,100,"Python, Kubernetes, Azure",PhD,6,Transportation,2024-01-25,2024-03-10,1687,8.1,Smart Analytics -AI11393,Machine Learning Engineer,66690,EUR,56687,MI,FT,Austria,S,New Zealand,50,"Docker, Statistics, Deep Learning, Azure, Scala",Bachelor,3,Automotive,2024-02-09,2024-03-23,868,9.6,DataVision Ltd -AI11394,Data Scientist,122287,GBP,91715,MI,PT,United Kingdom,L,United Kingdom,100,"AWS, Python, Spark",Bachelor,2,Retail,2024-09-12,2024-10-29,1159,6,Quantum Computing Inc -AI11395,Machine Learning Engineer,81923,USD,81923,EN,CT,Ireland,L,Ireland,0,"Python, TensorFlow, Git, Docker",Master,0,Real Estate,2025-03-05,2025-05-10,2422,7.5,Future Systems -AI11396,ML Ops Engineer,317576,USD,317576,EX,FL,Denmark,L,United States,100,"NLP, Tableau, SQL",Associate,16,Media,2024-10-17,2024-11-26,1252,8.1,TechCorp Inc -AI11397,AI Architect,111218,EUR,94535,SE,FT,Austria,S,Austria,0,"Mathematics, R, Computer Vision",Bachelor,6,Technology,2025-03-05,2025-03-20,2285,9,AI Innovations -AI11398,Data Engineer,137824,AUD,186062,EX,PT,Australia,S,Australia,0,"Java, SQL, Deep Learning, Azure, Computer Vision",Associate,13,Consulting,2025-02-14,2025-03-07,1942,6.7,Digital Transformation LLC -AI11399,Computer Vision Engineer,124975,EUR,106229,MI,PT,Netherlands,L,Netherlands,0,"Python, Linux, Scala, Data Visualization",Master,3,Automotive,2025-01-04,2025-02-02,1299,6,Digital Transformation LLC -AI11400,AI Product Manager,202807,SGD,263649,EX,PT,Singapore,M,Netherlands,100,"Python, SQL, Tableau",Bachelor,10,Finance,2024-05-11,2024-07-05,1842,7.1,Cognitive Computing -AI11401,AI Product Manager,225578,CHF,203020,EX,CT,Switzerland,S,Switzerland,50,"Docker, Azure, Python",Master,12,Technology,2025-01-06,2025-02-02,2234,5.7,Quantum Computing Inc -AI11402,Data Analyst,67004,EUR,56953,EN,CT,Austria,M,South Africa,0,"R, SQL, GCP, Computer Vision",Associate,1,Retail,2024-05-07,2024-06-07,1313,5.1,Smart Analytics -AI11403,NLP Engineer,91436,USD,91436,MI,PT,Finland,M,Ireland,0,"Data Visualization, Spark, SQL",PhD,4,Telecommunications,2024-12-14,2025-02-10,889,7.2,Machine Intelligence Group -AI11404,Data Engineer,190150,USD,190150,SE,CT,Denmark,M,Denmark,100,"Git, SQL, Tableau",Bachelor,5,Telecommunications,2024-10-10,2024-12-19,1116,6,AI Innovations -AI11405,Research Scientist,190516,AUD,257197,EX,CT,Australia,L,Australia,50,"AWS, SQL, Kubernetes, Python",Master,17,Healthcare,2024-01-22,2024-03-25,1876,8.5,Predictive Systems -AI11406,Machine Learning Engineer,113403,EUR,96393,MI,CT,Netherlands,L,Netherlands,100,"GCP, Computer Vision, Mathematics, SQL, Scala",Bachelor,3,Real Estate,2024-05-05,2024-07-10,2473,9.6,Smart Analytics -AI11407,AI Product Manager,206127,USD,206127,EX,FL,United States,M,Sweden,0,"Java, R, Computer Vision, Git",Master,16,Energy,2025-02-09,2025-03-15,1636,5.7,Predictive Systems -AI11408,Machine Learning Engineer,164366,USD,164366,SE,CT,Sweden,L,Sweden,100,"Scala, Data Visualization, Spark",Bachelor,8,Telecommunications,2024-09-16,2024-11-23,2292,5.6,TechCorp Inc -AI11409,Machine Learning Engineer,135548,CAD,169435,EX,FT,Canada,M,Canada,50,"Computer Vision, PyTorch, GCP, Data Visualization",PhD,14,Automotive,2024-08-21,2024-10-29,731,8.5,Neural Networks Co -AI11410,Robotics Engineer,81926,EUR,69637,EN,CT,Netherlands,L,Singapore,0,"Data Visualization, Scala, AWS, Linux",Associate,1,Retail,2024-08-05,2024-10-07,1080,8.9,DeepTech Ventures -AI11411,NLP Engineer,61432,CAD,76790,MI,FT,Canada,S,Canada,0,"Python, NLP, Linux",Bachelor,4,Retail,2025-01-25,2025-03-22,1959,5.6,Quantum Computing Inc -AI11412,Data Engineer,82350,SGD,107055,EN,CT,Singapore,M,Austria,50,"Hadoop, Deep Learning, Kubernetes, Spark, NLP",PhD,1,Gaming,2024-03-29,2024-04-20,1918,8.6,Machine Intelligence Group -AI11413,Robotics Engineer,91758,USD,91758,EN,PT,Norway,L,Norway,0,"GCP, Docker, R",PhD,1,Media,2025-01-23,2025-02-24,1382,8.3,DataVision Ltd -AI11414,Head of AI,26320,USD,26320,MI,PT,India,M,India,100,"Scala, Python, Mathematics, SQL",Associate,4,Automotive,2024-11-16,2024-12-11,678,8.9,Digital Transformation LLC -AI11415,AI Research Scientist,181477,GBP,136108,SE,CT,United Kingdom,L,United Kingdom,100,"NLP, Python, Linux, Deep Learning, Scala",PhD,5,Finance,2024-07-14,2024-09-10,1750,9.9,DeepTech Ventures -AI11416,AI Product Manager,119031,CAD,148789,SE,FT,Canada,S,Canada,100,"R, PyTorch, Python, MLOps",Bachelor,7,Technology,2024-04-08,2024-05-15,1777,9,Advanced Robotics -AI11417,AI Consultant,199896,JPY,21988560,EX,CT,Japan,S,Japan,100,"Tableau, Computer Vision, Statistics",Associate,10,Healthcare,2024-06-16,2024-08-02,1371,8,Advanced Robotics -AI11418,Machine Learning Researcher,143700,CAD,179625,EX,FL,Canada,M,Norway,100,"Docker, MLOps, GCP, R",PhD,11,Technology,2025-04-17,2025-05-28,2111,5.4,Advanced Robotics -AI11419,Machine Learning Engineer,257865,GBP,193399,EX,CT,United Kingdom,M,United Kingdom,50,"AWS, Spark, TensorFlow, Docker",Bachelor,18,Retail,2025-03-28,2025-06-01,2455,6.7,DeepTech Ventures -AI11420,Data Engineer,88557,SGD,115124,MI,FL,Singapore,S,New Zealand,0,"Kubernetes, Git, Data Visualization",PhD,3,Finance,2024-09-11,2024-10-26,520,6.5,TechCorp Inc -AI11421,Computer Vision Engineer,170140,CAD,212675,EX,FT,Canada,S,Canada,0,"Tableau, PyTorch, Kubernetes, R, Linux",PhD,11,Healthcare,2024-09-27,2024-11-25,1734,5.4,DeepTech Ventures -AI11422,Data Engineer,78293,CAD,97866,MI,FL,Canada,L,Canada,100,"Python, SQL, Statistics, Docker, Java",Associate,2,Healthcare,2024-05-04,2024-06-06,2239,5.1,Machine Intelligence Group -AI11423,AI Product Manager,95607,USD,95607,EN,CT,Norway,M,Norway,0,"GCP, Git, Java, Azure",Bachelor,0,Consulting,2024-07-28,2024-08-16,1686,8.9,Smart Analytics -AI11424,Data Analyst,75288,USD,75288,EN,FT,United States,L,Ghana,50,"Git, Hadoop, Tableau, Linux",Master,1,Healthcare,2024-05-05,2024-06-29,1636,7.1,Advanced Robotics -AI11425,Data Engineer,99770,CHF,89793,MI,FT,Switzerland,S,Switzerland,100,"Tableau, Docker, Deep Learning, Python, Hadoop",Master,2,Retail,2024-08-13,2024-09-16,2414,6.4,Predictive Systems -AI11426,AI Product Manager,107307,EUR,91211,SE,PT,Germany,S,Germany,0,"Tableau, Hadoop, NLP, GCP",Associate,5,Government,2024-03-01,2024-04-25,1825,8.6,DataVision Ltd -AI11427,NLP Engineer,80388,CAD,100485,MI,PT,Canada,S,Australia,0,"Java, SQL, AWS",Master,4,Automotive,2024-03-17,2024-05-17,2261,5.8,AI Innovations -AI11428,AI Consultant,43320,USD,43320,MI,FL,India,L,India,0,"Java, SQL, Scala, Statistics, AWS",Associate,3,Gaming,2024-02-01,2024-04-05,1139,6.7,Digital Transformation LLC -AI11429,AI Product Manager,49686,USD,49686,EX,FL,India,S,India,0,"Spark, Mathematics, Linux, Python",Associate,14,Media,2024-07-22,2024-09-30,1729,5.2,Smart Analytics -AI11430,AI Consultant,41656,USD,41656,MI,FT,China,S,Romania,100,"Python, Java, MLOps, Git",Bachelor,4,Gaming,2024-02-09,2024-03-01,1449,9.6,DataVision Ltd -AI11431,Data Engineer,149191,USD,149191,EX,FT,South Korea,S,South Korea,50,"SQL, Mathematics, MLOps",Bachelor,13,Real Estate,2025-02-25,2025-04-05,2473,6.1,DataVision Ltd -AI11432,Data Analyst,70858,USD,70858,MI,FL,South Korea,S,Canada,100,"Python, PyTorch, Statistics, Data Visualization",Bachelor,4,Government,2024-02-23,2024-05-02,1997,7,TechCorp Inc -AI11433,AI Software Engineer,112994,EUR,96045,SE,FT,France,S,France,100,"TensorFlow, NLP, SQL, Hadoop, Spark",Bachelor,8,Technology,2024-06-16,2024-08-08,1673,5.6,Neural Networks Co -AI11434,NLP Engineer,81456,USD,81456,MI,FL,South Korea,L,South Korea,100,"Tableau, TensorFlow, PyTorch",Bachelor,2,Finance,2024-11-08,2024-11-22,515,5.2,TechCorp Inc -AI11435,Head of AI,54011,EUR,45909,EN,CT,Austria,M,Austria,0,"Deep Learning, PyTorch, Statistics, Computer Vision, R",Master,1,Consulting,2024-10-20,2024-11-08,1295,7.9,Algorithmic Solutions -AI11436,AI Specialist,85091,USD,85091,EN,PT,Denmark,M,Denmark,100,"Mathematics, Spark, Kubernetes",Associate,1,Energy,2024-02-15,2024-04-03,780,6.5,TechCorp Inc -AI11437,AI Software Engineer,115899,USD,115899,EN,PT,Norway,L,Norway,50,"PyTorch, Mathematics, Tableau, Spark",PhD,0,Media,2025-01-11,2025-03-10,2231,6,AI Innovations -AI11438,Research Scientist,89371,JPY,9830810,MI,FL,Japan,M,Japan,0,"GCP, Azure, Tableau, MLOps",PhD,2,Manufacturing,2025-02-13,2025-03-21,1803,8.4,Future Systems -AI11439,Principal Data Scientist,125683,EUR,106831,SE,FT,Netherlands,M,Netherlands,50,"SQL, Java, Python, Azure, R",PhD,9,Education,2025-02-08,2025-03-27,1423,8.8,AI Innovations -AI11440,AI Research Scientist,349284,CHF,314356,EX,PT,Switzerland,L,Switzerland,100,"Python, TensorFlow, Docker, Deep Learning",Bachelor,13,Retail,2025-04-05,2025-04-25,1937,5.4,Cognitive Computing -AI11441,Data Scientist,140809,EUR,119688,EX,PT,Netherlands,S,Denmark,0,"Python, TensorFlow, MLOps, Scala, Java",Associate,18,Government,2024-03-19,2024-05-05,1264,6.7,Algorithmic Solutions -AI11442,Machine Learning Engineer,69956,USD,69956,MI,CT,Finland,S,Finland,100,"R, PyTorch, NLP, Scala",Master,4,Media,2024-03-14,2024-05-13,841,9.4,Digital Transformation LLC -AI11443,Autonomous Systems Engineer,71681,EUR,60929,EN,FL,France,M,Belgium,0,"Deep Learning, Computer Vision, Tableau, Python, Azure",PhD,0,Transportation,2025-04-18,2025-05-09,1084,7.6,AI Innovations -AI11444,NLP Engineer,215291,CAD,269114,EX,FL,Canada,L,Canada,50,"R, SQL, Computer Vision, GCP, Kubernetes",Associate,15,Technology,2024-08-14,2024-09-27,2204,9.3,DataVision Ltd -AI11445,Computer Vision Engineer,22321,USD,22321,EN,FL,India,S,India,0,"Deep Learning, Java, Statistics, Hadoop, Scala",PhD,1,Gaming,2024-09-09,2024-11-01,1646,9.2,TechCorp Inc -AI11446,Machine Learning Researcher,107424,USD,107424,MI,FT,United States,S,United States,100,"Git, Docker, Python, Azure, Computer Vision",PhD,2,Finance,2025-01-17,2025-02-01,759,7.8,Digital Transformation LLC -AI11447,AI Product Manager,97858,AUD,132108,MI,FT,Australia,S,Sweden,100,"Git, Kubernetes, MLOps, Tableau, GCP",PhD,2,Telecommunications,2024-11-12,2024-12-27,948,5.5,DeepTech Ventures -AI11448,Head of AI,131805,USD,131805,SE,PT,Finland,L,Finland,100,"Kubernetes, MLOps, Azure, Deep Learning, Scala",Master,9,Manufacturing,2024-11-12,2024-12-13,1137,7.9,Cloud AI Solutions -AI11449,AI Product Manager,168977,EUR,143630,SE,FL,Germany,L,Norway,0,"Data Visualization, MLOps, PyTorch, Deep Learning",PhD,5,Media,2024-08-24,2024-10-29,1876,6.1,DeepTech Ventures -AI11450,Computer Vision Engineer,112692,USD,112692,SE,CT,Israel,M,Israel,100,"Scala, Kubernetes, Azure",Associate,5,Energy,2024-06-25,2024-08-20,2010,7.9,DataVision Ltd -AI11451,NLP Engineer,24819,USD,24819,EN,FL,India,S,India,100,"Spark, Deep Learning, Tableau",Bachelor,0,Retail,2024-10-01,2024-11-24,916,6.4,Cognitive Computing -AI11452,Autonomous Systems Engineer,50429,USD,50429,MI,CT,China,M,China,0,"AWS, Azure, R, Computer Vision",PhD,4,Transportation,2024-05-08,2024-07-17,2418,7.6,Algorithmic Solutions -AI11453,AI Product Manager,92616,CAD,115770,MI,PT,Canada,L,Canada,100,"TensorFlow, Mathematics, Tableau",PhD,4,Energy,2024-08-22,2024-09-17,1475,6.8,Predictive Systems -AI11454,AI Architect,149371,USD,149371,MI,PT,United States,L,Spain,100,"PyTorch, Azure, Kubernetes, TensorFlow",Bachelor,3,Healthcare,2025-01-02,2025-02-23,2177,6.7,Autonomous Tech -AI11455,Machine Learning Engineer,235873,CHF,212286,EX,PT,Switzerland,S,Brazil,100,"Java, Git, Docker, MLOps",Master,10,Consulting,2024-06-26,2024-09-03,1795,8.8,Smart Analytics -AI11456,AI Consultant,46440,USD,46440,EN,FT,South Korea,S,South Korea,0,"Kubernetes, Spark, NLP, Git, Python",Associate,0,Transportation,2024-05-04,2024-05-27,536,5.3,Neural Networks Co -AI11457,Computer Vision Engineer,227078,EUR,193016,EX,PT,Netherlands,M,Romania,0,"R, Spark, Scala, Python",PhD,14,Media,2024-12-27,2025-01-28,937,7.2,Autonomous Tech -AI11458,Robotics Engineer,63953,EUR,54360,EN,FL,Netherlands,M,Netherlands,100,"AWS, Python, Tableau, TensorFlow",Associate,0,Manufacturing,2024-11-13,2024-12-05,662,5.3,Cloud AI Solutions -AI11459,AI Software Engineer,77328,EUR,65729,MI,FL,Germany,S,Germany,0,"Spark, Scala, PyTorch, Linux",Bachelor,2,Technology,2024-05-01,2024-05-22,2423,7.8,Neural Networks Co -AI11460,AI Product Manager,64672,USD,64672,EN,CT,Sweden,L,Latvia,50,"TensorFlow, R, Spark, Python, Azure",PhD,0,Real Estate,2024-11-21,2024-12-14,1484,7.3,Digital Transformation LLC -AI11461,AI Product Manager,103343,GBP,77507,MI,CT,United Kingdom,S,Switzerland,100,"TensorFlow, Data Visualization, Linux, Mathematics, Kubernetes",PhD,3,Finance,2024-03-05,2024-05-08,1183,8.8,Quantum Computing Inc -AI11462,NLP Engineer,99987,EUR,84989,MI,CT,Netherlands,S,Netherlands,50,"Spark, Linux, Data Visualization, Python",Master,3,Education,2025-01-12,2025-01-26,2303,6.5,Machine Intelligence Group -AI11463,NLP Engineer,37144,USD,37144,MI,PT,China,M,China,0,"Mathematics, Scala, SQL, Python",Master,3,Media,2024-04-01,2024-05-23,2408,5.5,Predictive Systems -AI11464,Head of AI,239050,JPY,26295500,EX,FL,Japan,M,Japan,50,"Azure, SQL, Hadoop",Master,17,Government,2024-11-03,2024-12-21,1181,6.4,DataVision Ltd -AI11465,Research Scientist,63804,USD,63804,EN,FL,Ireland,M,Ireland,50,"MLOps, Mathematics, Statistics, AWS",Bachelor,1,Finance,2024-10-02,2024-10-22,1980,8,Predictive Systems -AI11466,AI Research Scientist,121719,USD,121719,MI,PT,Sweden,L,Germany,50,"Statistics, Hadoop, Deep Learning, R",Master,2,Automotive,2024-11-23,2024-12-15,1865,5.7,DataVision Ltd -AI11467,Robotics Engineer,318346,USD,318346,EX,FL,Norway,M,Norway,50,"Python, TensorFlow, Java",Associate,10,Telecommunications,2024-04-10,2024-06-17,1715,9.3,AI Innovations -AI11468,NLP Engineer,113713,JPY,12508430,SE,PT,Japan,M,Philippines,0,"Java, SQL, Python, TensorFlow, PyTorch",Associate,9,Technology,2024-07-22,2024-09-19,2127,9.1,TechCorp Inc -AI11469,Research Scientist,129110,CAD,161388,SE,FL,Canada,M,Canada,100,"Scala, AWS, Computer Vision, Statistics, Mathematics",Associate,6,Real Estate,2024-04-24,2024-06-15,1850,8.8,Quantum Computing Inc -AI11470,Research Scientist,76550,USD,76550,EN,FT,United States,S,France,0,"SQL, Statistics, R",Associate,1,Telecommunications,2024-03-21,2024-05-01,972,7.6,Neural Networks Co -AI11471,AI Software Engineer,160981,JPY,17707910,EX,CT,Japan,S,Japan,100,"Kubernetes, Computer Vision, NLP",Associate,19,Retail,2024-09-04,2024-10-19,2152,9.3,Cloud AI Solutions -AI11472,AI Software Engineer,249798,CHF,224818,EX,FL,Switzerland,L,Switzerland,100,"Azure, Deep Learning, Spark, Linux, NLP",PhD,13,Real Estate,2024-08-29,2024-10-23,854,7.2,Cloud AI Solutions -AI11473,AI Specialist,110277,USD,110277,MI,CT,Ireland,L,Ireland,0,"Python, Java, Tableau, Spark",PhD,4,Telecommunications,2024-09-11,2024-10-19,1386,5.6,Quantum Computing Inc -AI11474,AI Architect,314219,USD,314219,EX,CT,Denmark,M,Denmark,100,"Python, Azure, Scala",Bachelor,19,Transportation,2025-02-02,2025-03-29,1389,7.3,Quantum Computing Inc -AI11475,Data Analyst,335263,CHF,301737,EX,FL,Switzerland,L,Switzerland,100,"Statistics, SQL, GCP",Master,14,Consulting,2024-09-25,2024-11-23,1870,7.4,Quantum Computing Inc -AI11476,Machine Learning Engineer,124417,CHF,111975,MI,CT,Switzerland,M,Switzerland,0,"Computer Vision, SQL, MLOps, Linux",PhD,2,Gaming,2024-04-26,2024-05-25,2021,8.9,DataVision Ltd -AI11477,AI Research Scientist,124130,USD,124130,SE,FL,Finland,M,Finland,0,"Scala, Hadoop, R, Linux, NLP",Associate,8,Education,2024-06-03,2024-07-07,1239,6.5,Machine Intelligence Group -AI11478,Machine Learning Researcher,80925,USD,80925,EN,FL,United States,S,Netherlands,50,"Python, Kubernetes, Data Visualization, Azure",Master,0,Finance,2024-10-06,2024-11-03,1923,8.3,Quantum Computing Inc -AI11479,Head of AI,79342,USD,79342,MI,CT,Ireland,M,Colombia,100,"Linux, Java, Scala",Master,3,Healthcare,2024-03-18,2024-05-25,1291,9.5,Digital Transformation LLC -AI11480,Autonomous Systems Engineer,97152,USD,97152,EN,CT,United States,L,United States,0,"PyTorch, Scala, Tableau",Bachelor,0,Technology,2025-02-08,2025-04-13,2187,7,Machine Intelligence Group -AI11481,Machine Learning Engineer,142004,EUR,120703,SE,FT,France,L,France,0,"SQL, Computer Vision, AWS",Associate,6,Automotive,2024-02-25,2024-05-05,731,8.5,Future Systems -AI11482,Computer Vision Engineer,147965,USD,147965,SE,PT,United States,M,United States,50,"Azure, Java, GCP",PhD,7,Consulting,2024-03-21,2024-05-08,2334,7.9,Predictive Systems -AI11483,Deep Learning Engineer,192037,USD,192037,EX,CT,Ireland,L,Ireland,50,"Java, Docker, NLP",Bachelor,10,Real Estate,2024-01-11,2024-02-08,1028,5.9,DeepTech Ventures -AI11484,Data Scientist,127383,EUR,108276,SE,FL,France,M,South Korea,0,"Kubernetes, Hadoop, Linux, GCP",PhD,9,Finance,2024-10-29,2024-12-30,1853,8.4,DeepTech Ventures -AI11485,Principal Data Scientist,85256,EUR,72468,MI,CT,Netherlands,S,Netherlands,50,"Scala, Mathematics, Python, Spark, GCP",PhD,3,Healthcare,2024-05-31,2024-08-06,899,5.5,Cloud AI Solutions -AI11486,Data Analyst,191885,USD,191885,SE,CT,Norway,L,Norway,50,"PyTorch, Python, Data Visualization",Bachelor,7,Consulting,2024-04-19,2024-06-15,2006,8.6,DataVision Ltd -AI11487,Data Engineer,106706,USD,106706,SE,FL,Israel,S,Israel,100,"Docker, Git, NLP, MLOps",Bachelor,6,Gaming,2025-03-24,2025-05-22,1323,7.6,Advanced Robotics -AI11488,AI Product Manager,144625,USD,144625,SE,FT,Ireland,L,Ireland,50,"Scala, Python, SQL, Mathematics",Bachelor,6,Government,2025-02-07,2025-04-08,2418,6.6,Machine Intelligence Group -AI11489,NLP Engineer,89096,GBP,66822,MI,CT,United Kingdom,L,United Kingdom,0,"R, SQL, Tableau, Statistics, Azure",PhD,4,Government,2025-02-17,2025-04-27,944,8.8,Predictive Systems -AI11490,AI Product Manager,113094,USD,113094,MI,FL,Denmark,M,Denmark,50,"Java, R, Statistics",Master,3,Real Estate,2024-03-15,2024-05-22,1878,7.7,DeepTech Ventures -AI11491,Machine Learning Researcher,44438,USD,44438,EN,FL,South Korea,S,South Korea,50,"Hadoop, Tableau, GCP, MLOps",PhD,0,Government,2024-03-11,2024-03-25,2149,8.8,Advanced Robotics -AI11492,AI Research Scientist,74828,EUR,63604,EN,CT,Netherlands,S,Netherlands,0,"Computer Vision, Python, Kubernetes, SQL",Master,1,Manufacturing,2024-09-12,2024-10-21,1386,6.3,Quantum Computing Inc -AI11493,Principal Data Scientist,79856,AUD,107806,MI,PT,Australia,M,Australia,0,"Hadoop, Scala, Git, Deep Learning, Java",PhD,2,Retail,2024-05-22,2024-07-24,1575,6.9,Quantum Computing Inc -AI11494,AI Specialist,155247,USD,155247,EX,FT,Ireland,M,Ireland,100,"Python, Mathematics, Git, Hadoop, Computer Vision",Master,17,Consulting,2025-02-04,2025-02-18,1759,9.4,Algorithmic Solutions -AI11495,AI Research Scientist,86084,EUR,73171,EN,PT,France,L,Poland,100,"Java, GCP, Data Visualization, Kubernetes, Python",Bachelor,1,Healthcare,2025-02-05,2025-04-03,1866,5.1,AI Innovations -AI11496,AI Specialist,121255,USD,121255,MI,PT,Norway,L,Norway,0,"SQL, Scala, AWS, GCP",PhD,4,Telecommunications,2024-03-28,2024-06-03,2180,8.1,TechCorp Inc -AI11497,AI Consultant,120964,USD,120964,SE,CT,Denmark,S,Nigeria,50,"Spark, SQL, Deep Learning",Associate,9,Healthcare,2024-05-10,2024-07-02,511,9.3,TechCorp Inc -AI11498,Autonomous Systems Engineer,170957,GBP,128218,SE,FL,United Kingdom,L,United Kingdom,100,"Azure, Hadoop, Python",Associate,6,Retail,2024-11-16,2024-12-12,1965,8.5,DataVision Ltd -AI11499,Machine Learning Engineer,80134,JPY,8814740,MI,FL,Japan,M,Ireland,0,"Java, AWS, TensorFlow, Spark, Tableau",Associate,2,Manufacturing,2024-04-11,2024-06-07,936,6.7,Smart Analytics -AI11500,AI Consultant,139486,JPY,15343460,EX,FT,Japan,S,Canada,50,"NLP, Python, Data Visualization",Associate,13,Finance,2024-09-07,2024-11-17,1203,6.6,Neural Networks Co -AI11501,Deep Learning Engineer,65381,SGD,84995,EN,FT,Singapore,L,Singapore,50,"Linux, R, Docker, Python",Bachelor,0,Education,2024-11-21,2025-01-17,1622,6.9,TechCorp Inc -AI11502,Data Engineer,171324,USD,171324,EX,CT,Norway,S,Norway,0,"Statistics, SQL, Scala, Kubernetes, Data Visualization",Bachelor,15,Education,2024-07-02,2024-08-11,1183,7.5,Advanced Robotics -AI11503,AI Specialist,87775,USD,87775,SE,FL,South Korea,M,South Korea,100,"MLOps, SQL, Python, Scala, Git",Master,6,Media,2024-07-07,2024-08-04,2349,6.3,Cognitive Computing -AI11504,Deep Learning Engineer,172632,EUR,146737,EX,FL,Austria,S,Austria,0,"Tableau, Kubernetes, AWS",Master,11,Manufacturing,2024-11-10,2024-12-30,2272,5.6,Neural Networks Co -AI11505,Data Analyst,88588,USD,88588,MI,PT,Denmark,S,Denmark,50,"Hadoop, Docker, Mathematics",Bachelor,4,Real Estate,2024-10-02,2024-10-18,572,6.8,DeepTech Ventures -AI11506,Data Scientist,168771,EUR,143455,EX,FT,Netherlands,M,Netherlands,0,"TensorFlow, NLP, Python, GCP",Associate,15,Retail,2025-03-16,2025-05-06,1787,5.7,DeepTech Ventures -AI11507,AI Product Manager,90000,USD,90000,MI,FT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, Data Visualization, SQL",Associate,4,Real Estate,2024-04-12,2024-04-29,1336,5.1,Quantum Computing Inc -AI11508,NLP Engineer,38919,USD,38919,MI,PT,China,M,Belgium,0,"R, Hadoop, NLP",Bachelor,3,Finance,2025-03-02,2025-03-24,1440,7.8,Predictive Systems -AI11509,Deep Learning Engineer,63396,EUR,53887,EN,CT,France,M,France,50,"Hadoop, GCP, AWS, Scala, Azure",Bachelor,0,Government,2024-07-03,2024-08-24,1182,5.9,DataVision Ltd -AI11510,AI Software Engineer,127703,USD,127703,EX,FL,South Korea,S,Indonesia,50,"Hadoop, Scala, TensorFlow, GCP",PhD,14,Retail,2024-11-18,2025-01-03,1976,6.3,Algorithmic Solutions -AI11511,Research Scientist,136930,USD,136930,MI,FT,Norway,M,Norway,50,"Azure, SQL, Computer Vision, Spark, Statistics",PhD,2,Manufacturing,2024-02-05,2024-03-06,2481,9.8,Cognitive Computing -AI11512,Machine Learning Researcher,62653,EUR,53255,EN,FL,Austria,S,Austria,0,"SQL, Scala, GCP",Bachelor,0,Media,2024-02-07,2024-04-07,1111,5.1,Smart Analytics -AI11513,AI Consultant,238158,USD,238158,EX,FL,Sweden,L,Sweden,0,"Mathematics, Data Visualization, GCP, Python, Git",PhD,19,Telecommunications,2025-02-03,2025-02-26,2232,7.3,Advanced Robotics -AI11514,AI Specialist,67273,AUD,90819,MI,FL,Australia,S,Australia,100,"AWS, Computer Vision, Linux, NLP",Bachelor,2,Telecommunications,2024-12-05,2024-12-25,1782,8.6,Cloud AI Solutions -AI11515,AI Software Engineer,296408,USD,296408,EX,FL,Denmark,L,Denmark,50,"Azure, Git, Statistics",PhD,12,Real Estate,2024-01-07,2024-02-03,1976,8.8,DeepTech Ventures -AI11516,Deep Learning Engineer,82078,EUR,69766,MI,FT,Netherlands,S,Netherlands,100,"AWS, Statistics, Tableau",Associate,3,Media,2025-03-27,2025-05-19,2475,9.3,Algorithmic Solutions -AI11517,Data Analyst,62170,EUR,52845,MI,CT,France,S,Australia,0,"AWS, Git, Python, GCP",PhD,2,Telecommunications,2025-04-17,2025-05-30,2294,6.8,AI Innovations -AI11518,Principal Data Scientist,156317,GBP,117238,SE,FL,United Kingdom,L,Thailand,100,"SQL, Scala, Kubernetes, Git",Bachelor,8,Government,2025-02-15,2025-03-20,2149,5.3,Algorithmic Solutions -AI11519,Principal Data Scientist,222260,CHF,200034,EX,FL,Switzerland,S,Switzerland,0,"SQL, PyTorch, Linux",Bachelor,11,Transportation,2024-08-15,2024-09-29,1557,8.8,Machine Intelligence Group -AI11520,Deep Learning Engineer,37876,USD,37876,SE,FL,India,S,India,0,"Data Visualization, Scala, R",Associate,5,Manufacturing,2024-09-05,2024-11-03,1333,8.7,Smart Analytics -AI11521,AI Consultant,78486,USD,78486,MI,PT,Sweden,M,Sweden,50,"Java, PyTorch, Linux",Associate,4,Energy,2024-10-03,2024-12-07,2117,9.1,DataVision Ltd -AI11522,Deep Learning Engineer,192938,EUR,163997,EX,CT,Netherlands,S,Kenya,100,"AWS, Scala, Deep Learning",Master,14,Transportation,2024-10-18,2024-12-29,1316,9.7,Predictive Systems -AI11523,Principal Data Scientist,43359,USD,43359,SE,PT,India,L,India,50,"Statistics, MLOps, Mathematics, Data Visualization",PhD,8,Healthcare,2025-01-27,2025-02-27,2445,8.8,Cognitive Computing -AI11524,Principal Data Scientist,118994,EUR,101145,SE,PT,Germany,M,Germany,100,"Spark, GCP, TensorFlow",Associate,9,Technology,2024-08-25,2024-10-07,1049,5.6,Neural Networks Co -AI11525,NLP Engineer,97478,CHF,87730,MI,FL,Switzerland,S,Switzerland,0,"Hadoop, SQL, Scala, Data Visualization, AWS",PhD,4,Telecommunications,2025-03-30,2025-05-01,1307,9.6,Digital Transformation LLC -AI11526,Head of AI,88392,EUR,75133,MI,FT,France,S,France,50,"Data Visualization, R, GCP, SQL",PhD,2,Energy,2024-11-28,2024-12-26,1526,5.8,Smart Analytics -AI11527,Machine Learning Researcher,134966,USD,134966,SE,FL,Sweden,S,Austria,50,"Kubernetes, Hadoop, PyTorch, Data Visualization, Computer Vision",Associate,6,Energy,2024-05-24,2024-06-14,1182,6,Cognitive Computing -AI11528,AI Specialist,106203,AUD,143374,MI,FL,Australia,M,Australia,0,"Azure, Computer Vision, SQL, Kubernetes, Statistics",Master,3,Telecommunications,2024-02-03,2024-02-24,1658,9.8,Predictive Systems -AI11529,AI Software Engineer,202928,USD,202928,EX,CT,Ireland,S,Ireland,0,"R, PyTorch, Git, Java",Bachelor,18,Gaming,2024-06-26,2024-07-24,2250,6.3,TechCorp Inc -AI11530,NLP Engineer,127991,USD,127991,MI,FT,Norway,S,Norway,100,"Mathematics, Data Visualization, R, Computer Vision",Bachelor,3,Real Estate,2024-11-18,2025-01-25,1062,8,AI Innovations -AI11531,AI Architect,92358,EUR,78504,SE,FL,Austria,S,Finland,50,"GCP, Kubernetes, AWS, Computer Vision",Associate,8,Manufacturing,2024-10-03,2024-12-02,2090,9,DataVision Ltd -AI11532,Data Engineer,272629,USD,272629,EX,FL,Norway,S,Russia,50,"MLOps, Docker, Java, Mathematics, PyTorch",Master,19,Retail,2025-02-17,2025-03-27,1463,8.6,Future Systems -AI11533,AI Architect,221472,JPY,24361920,EX,PT,Japan,S,Japan,50,"Tableau, Java, Docker, Scala",PhD,10,Media,2024-09-28,2024-10-19,1044,8.7,Neural Networks Co -AI11534,Autonomous Systems Engineer,73577,CAD,91971,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, MLOps, Java, PyTorch",PhD,1,Automotive,2024-03-30,2024-05-03,1561,7.1,DeepTech Ventures -AI11535,ML Ops Engineer,58063,EUR,49354,EN,CT,Germany,M,Germany,0,"Data Visualization, Scala, Linux, NLP",Master,0,Consulting,2024-09-04,2024-11-05,2249,9.1,DeepTech Ventures -AI11536,Computer Vision Engineer,219400,AUD,296190,EX,FL,Australia,M,Australia,100,"Computer Vision, PyTorch, Tableau, Azure, GCP",PhD,17,Transportation,2024-04-27,2024-07-03,1931,5.6,DeepTech Ventures -AI11537,Machine Learning Engineer,103961,GBP,77971,MI,CT,United Kingdom,M,United Kingdom,50,"PyTorch, R, Docker, Hadoop, Mathematics",Associate,2,Real Estate,2024-10-26,2024-12-20,1011,9.3,Algorithmic Solutions -AI11538,Data Scientist,82413,USD,82413,EX,PT,India,M,India,0,"Python, Spark, TensorFlow, GCP, PyTorch",Master,13,Finance,2024-03-18,2024-05-21,1591,8.7,Machine Intelligence Group -AI11539,Computer Vision Engineer,172900,CHF,155610,SE,FL,Switzerland,L,Switzerland,50,"SQL, Deep Learning, Tableau, TensorFlow, Statistics",Master,6,Media,2024-05-28,2024-06-15,2243,7.4,Quantum Computing Inc -AI11540,Research Scientist,189271,EUR,160880,EX,CT,Netherlands,M,Netherlands,0,"TensorFlow, GCP, Mathematics, Docker",Bachelor,10,Transportation,2024-10-02,2024-11-15,1545,5.3,Advanced Robotics -AI11541,AI Product Manager,111442,EUR,94726,MI,CT,France,L,France,100,"Python, Statistics, NLP",Bachelor,3,Government,2024-05-07,2024-07-01,1973,7.6,Predictive Systems -AI11542,NLP Engineer,67863,GBP,50897,EN,PT,United Kingdom,S,United Kingdom,100,"GCP, Deep Learning, NLP",Bachelor,0,Automotive,2024-07-06,2024-08-11,751,8.8,Cognitive Computing -AI11543,NLP Engineer,37216,USD,37216,MI,FT,India,M,India,100,"Scala, Spark, Tableau, Mathematics, Python",Associate,2,Consulting,2025-01-12,2025-02-18,1396,8.8,Autonomous Tech -AI11544,ML Ops Engineer,146138,USD,146138,SE,FT,Ireland,M,Ireland,0,"Deep Learning, Scala, Tableau, SQL, Computer Vision",Master,9,Media,2024-10-06,2024-11-11,1436,8.5,Cognitive Computing -AI11545,Data Scientist,45328,CAD,56660,EN,PT,Canada,S,Hungary,50,"Deep Learning, R, MLOps, SQL, Spark",Bachelor,0,Automotive,2024-10-18,2024-11-19,2424,8.9,TechCorp Inc -AI11546,Data Scientist,100310,USD,100310,MI,PT,Israel,L,Estonia,50,"Linux, Kubernetes, Scala, Python",PhD,4,Consulting,2024-04-22,2024-05-30,1423,7.2,Quantum Computing Inc -AI11547,Principal Data Scientist,147245,EUR,125158,SE,CT,France,L,France,50,"MLOps, Linux, Data Visualization, Spark",Associate,6,Media,2024-10-23,2024-11-18,729,6.4,Autonomous Tech -AI11548,Autonomous Systems Engineer,88089,EUR,74876,MI,FT,Germany,S,Germany,0,"Git, Azure, Python, Hadoop",PhD,3,Automotive,2024-01-17,2024-02-18,2100,7.4,Digital Transformation LLC -AI11549,Principal Data Scientist,72575,USD,72575,EN,CT,South Korea,L,South Korea,50,"TensorFlow, AWS, Deep Learning, Python, MLOps",Bachelor,0,Media,2024-11-06,2025-01-17,753,9.5,DeepTech Ventures -AI11550,AI Research Scientist,85617,USD,85617,MI,FL,Finland,S,Finland,50,"SQL, GCP, PyTorch, AWS",Bachelor,4,Healthcare,2025-04-26,2025-07-02,911,5.5,Cloud AI Solutions -AI11551,AI Consultant,89607,CAD,112009,MI,PT,Canada,S,Canada,50,"Computer Vision, AWS, SQL",Associate,2,Government,2024-10-17,2024-12-10,851,5.1,AI Innovations -AI11552,Robotics Engineer,51322,EUR,43624,EN,FL,Austria,S,Austria,50,"Git, Hadoop, SQL, NLP",PhD,1,Transportation,2025-01-05,2025-02-16,1864,7.7,Cognitive Computing -AI11553,Computer Vision Engineer,93109,EUR,79143,SE,PT,France,S,France,0,"Docker, Hadoop, Tableau, Statistics, GCP",Bachelor,9,Real Estate,2024-05-09,2024-06-23,1392,5.4,DeepTech Ventures -AI11554,Robotics Engineer,39952,USD,39952,MI,PT,China,S,China,100,"Statistics, R, Docker, Deep Learning",Master,4,Manufacturing,2024-12-22,2025-01-12,2188,7.8,TechCorp Inc -AI11555,Head of AI,53528,USD,53528,SE,CT,China,M,China,100,"TensorFlow, Python, Data Visualization",Bachelor,6,Media,2024-08-30,2024-10-28,1322,5.8,Predictive Systems -AI11556,Data Engineer,87394,EUR,74285,MI,FL,Netherlands,M,Netherlands,0,"Mathematics, GCP, Scala, NLP",Master,3,Healthcare,2024-03-12,2024-05-19,2338,9.7,Smart Analytics -AI11557,Deep Learning Engineer,172148,EUR,146326,EX,PT,Netherlands,S,Netherlands,50,"SQL, Python, Git",Bachelor,19,Manufacturing,2024-07-31,2024-08-24,712,5.6,TechCorp Inc -AI11558,AI Research Scientist,63353,EUR,53850,EN,FT,France,S,France,50,"Linux, PyTorch, R, MLOps, Statistics",Associate,1,Finance,2025-04-04,2025-04-23,1231,7.1,TechCorp Inc -AI11559,Machine Learning Researcher,65724,USD,65724,EN,FL,South Korea,L,South Korea,50,"Git, MLOps, GCP",Bachelor,0,Transportation,2024-02-04,2024-03-14,1883,7.4,Machine Intelligence Group -AI11560,ML Ops Engineer,114291,EUR,97147,SE,PT,Austria,S,Austria,100,"SQL, Kubernetes, Tableau, Linux",Associate,8,Education,2024-09-27,2024-11-09,666,8.2,DataVision Ltd -AI11561,Machine Learning Engineer,85594,USD,85594,EN,PT,Ireland,L,Ireland,50,"Git, Data Visualization, Hadoop, NLP, Deep Learning",Bachelor,0,Automotive,2024-04-04,2024-05-15,2034,7.9,DataVision Ltd -AI11562,AI Specialist,123737,JPY,13611070,SE,PT,Japan,M,Japan,50,"Python, AWS, Computer Vision, TensorFlow",Bachelor,5,Education,2024-09-01,2024-09-25,2237,5,Predictive Systems -AI11563,Deep Learning Engineer,240031,EUR,204026,EX,PT,Germany,M,Germany,0,"Java, Mathematics, TensorFlow",Master,11,Technology,2024-09-07,2024-10-18,683,8.7,Autonomous Tech -AI11564,Research Scientist,31490,USD,31490,MI,PT,India,M,Sweden,100,"Linux, SQL, Computer Vision, Data Visualization",Master,2,Telecommunications,2025-01-14,2025-02-12,1008,7.5,TechCorp Inc -AI11565,AI Specialist,60618,EUR,51525,EN,CT,Germany,L,South Korea,0,"R, Tableau, Deep Learning, Kubernetes",Master,0,Retail,2024-10-29,2024-12-02,1489,7.3,Predictive Systems -AI11566,AI Architect,78418,USD,78418,EN,CT,Israel,L,Israel,100,"Python, NLP, MLOps",Associate,0,Manufacturing,2024-09-05,2024-09-30,846,9.3,AI Innovations -AI11567,Data Scientist,269385,JPY,29632350,EX,CT,Japan,M,Japan,50,"NLP, Kubernetes, Spark, Mathematics, Python",Associate,13,Automotive,2025-01-31,2025-04-09,1439,8,Autonomous Tech -AI11568,Autonomous Systems Engineer,97601,USD,97601,MI,PT,United States,S,Ireland,100,"PyTorch, Azure, Linux, GCP",Bachelor,2,Finance,2024-09-08,2024-10-29,1430,6.3,AI Innovations -AI11569,AI Software Engineer,195834,USD,195834,EX,FL,Finland,S,Argentina,50,"TensorFlow, GCP, SQL",Associate,15,Consulting,2024-09-22,2024-11-15,987,9.9,Cognitive Computing -AI11570,AI Consultant,136182,USD,136182,EX,CT,South Korea,M,South Korea,100,"Scala, Deep Learning, Azure, Statistics, Data Visualization",Master,18,Transportation,2025-02-06,2025-03-05,1479,6.8,Smart Analytics -AI11571,AI Software Engineer,210024,CAD,262530,EX,FT,Canada,S,Switzerland,50,"Scala, Python, Hadoop, Git",Bachelor,11,Healthcare,2025-02-21,2025-03-22,1133,9.1,DeepTech Ventures -AI11572,Principal Data Scientist,54381,USD,54381,EN,FT,Israel,S,Israel,0,"Spark, PyTorch, Azure, R, Scala",Associate,1,Manufacturing,2024-12-06,2024-12-22,1312,5.1,DataVision Ltd -AI11573,AI Product Manager,190082,USD,190082,SE,CT,Denmark,M,Denmark,0,"Docker, GCP, Java, PyTorch, Deep Learning",Bachelor,9,Manufacturing,2024-08-23,2024-10-19,945,6.2,Cloud AI Solutions -AI11574,AI Software Engineer,84428,JPY,9287080,MI,FT,Japan,S,Japan,50,"Hadoop, TensorFlow, GCP",Associate,2,Media,2024-03-14,2024-04-14,1969,6.7,Cognitive Computing -AI11575,Robotics Engineer,111780,SGD,145314,SE,CT,Singapore,S,Singapore,0,"Python, GCP, AWS, Mathematics, TensorFlow",PhD,5,Transportation,2025-03-13,2025-03-30,746,5.1,Machine Intelligence Group -AI11576,Principal Data Scientist,103260,USD,103260,EN,FT,Norway,M,Norway,0,"R, Python, Spark, Java, GCP",Bachelor,0,Education,2024-12-21,2025-02-17,714,8.4,Digital Transformation LLC -AI11577,AI Specialist,129654,USD,129654,MI,CT,Denmark,L,France,50,"Docker, SQL, Data Visualization",Master,2,Gaming,2024-04-03,2024-06-07,815,6.6,Neural Networks Co -AI11578,AI Product Manager,37250,USD,37250,EN,PT,China,M,Indonesia,50,"Python, Scala, TensorFlow, Tableau",Associate,0,Telecommunications,2024-06-22,2024-09-03,1594,5.3,Advanced Robotics -AI11579,Data Scientist,287770,USD,287770,EX,PT,Ireland,L,Ireland,50,"Hadoop, PyTorch, Kubernetes",Master,13,Energy,2025-01-10,2025-03-14,761,5.5,Digital Transformation LLC -AI11580,Data Scientist,65359,JPY,7189490,EN,PT,Japan,M,Colombia,100,"Data Visualization, Git, Scala, Computer Vision",PhD,0,Gaming,2025-03-25,2025-04-14,1483,8.7,Smart Analytics -AI11581,NLP Engineer,122773,USD,122773,SE,FT,Ireland,M,Ireland,100,"SQL, Tableau, Spark",Associate,8,Government,2024-03-14,2024-04-05,1698,9.2,DataVision Ltd -AI11582,Data Engineer,60408,USD,60408,EN,PT,Finland,L,Finland,100,"Git, PyTorch, GCP, Spark, Tableau",Bachelor,1,Manufacturing,2024-08-13,2024-10-01,1351,6.5,TechCorp Inc -AI11583,AI Software Engineer,150096,USD,150096,SE,FT,Sweden,L,Sweden,50,"Python, TensorFlow, Spark",Associate,6,Telecommunications,2024-02-05,2024-04-08,1653,7.2,Future Systems -AI11584,Data Scientist,205206,EUR,174425,EX,FL,France,L,France,100,"SQL, Kubernetes, PyTorch",Bachelor,17,Gaming,2024-05-19,2024-06-11,1708,5.6,TechCorp Inc -AI11585,Data Scientist,26000,USD,26000,MI,FT,India,M,India,100,"PyTorch, Azure, NLP",PhD,4,Consulting,2024-10-17,2024-12-02,1250,9.1,Advanced Robotics -AI11586,Data Engineer,65860,USD,65860,EN,CT,South Korea,L,South Korea,100,"Mathematics, Scala, Python, Git, Computer Vision",Associate,0,Manufacturing,2024-09-19,2024-11-09,1493,7.8,Future Systems -AI11587,Computer Vision Engineer,94548,GBP,70911,MI,FT,United Kingdom,L,United Kingdom,50,"Hadoop, Tableau, Computer Vision",PhD,2,Telecommunications,2024-09-22,2024-11-27,848,9.5,Cognitive Computing -AI11588,Robotics Engineer,139420,USD,139420,SE,CT,Finland,L,Kenya,0,"GCP, Computer Vision, NLP",PhD,6,Automotive,2024-02-08,2024-03-11,1488,7.9,Neural Networks Co -AI11589,AI Consultant,96731,USD,96731,EN,FL,United States,L,United States,50,"Java, R, SQL, Docker",Associate,0,Real Estate,2024-07-19,2024-08-13,2423,5.2,Algorithmic Solutions -AI11590,Data Engineer,166302,EUR,141357,SE,FT,Netherlands,L,Switzerland,50,"Hadoop, Computer Vision, Python, Java, Kubernetes",Bachelor,6,Real Estate,2024-09-08,2024-09-25,622,6.3,Autonomous Tech -AI11591,AI Research Scientist,169852,USD,169852,EX,PT,South Korea,M,South Korea,100,"SQL, Git, Docker, PyTorch",Bachelor,19,Automotive,2024-05-04,2024-06-04,2138,5.4,Future Systems -AI11592,Autonomous Systems Engineer,50112,USD,50112,EN,PT,Ireland,S,Ireland,50,"Data Visualization, Computer Vision, SQL, Hadoop",PhD,0,Energy,2024-10-13,2024-12-03,1750,9.7,Autonomous Tech -AI11593,Data Engineer,25790,USD,25790,EN,FT,India,L,Romania,50,"TensorFlow, SQL, Hadoop, Tableau",Master,0,Media,2024-07-29,2024-08-27,1971,8,Cognitive Computing -AI11594,Robotics Engineer,111118,SGD,144453,SE,PT,Singapore,M,Singapore,50,"AWS, Docker, NLP, Kubernetes, Azure",Associate,7,Telecommunications,2025-03-23,2025-05-02,960,8.7,Cloud AI Solutions -AI11595,Data Engineer,63655,GBP,47741,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, Python, R, TensorFlow",PhD,0,Consulting,2024-03-16,2024-04-29,2498,6.2,Algorithmic Solutions -AI11596,AI Product Manager,180875,USD,180875,EX,CT,Ireland,L,Sweden,0,"Scala, Kubernetes, Python",Master,11,Finance,2024-11-07,2024-12-25,649,8.2,Algorithmic Solutions -AI11597,AI Software Engineer,59927,EUR,50938,EN,CT,France,S,Czech Republic,50,"Mathematics, Computer Vision, Data Visualization",Bachelor,0,Real Estate,2024-03-06,2024-05-12,794,9.5,Machine Intelligence Group -AI11598,AI Research Scientist,254962,EUR,216718,EX,FT,France,L,France,0,"SQL, NLP, Docker",Bachelor,15,Finance,2024-11-30,2025-01-07,1476,9.7,Autonomous Tech -AI11599,Machine Learning Researcher,173503,CHF,156153,SE,CT,Switzerland,S,Kenya,50,"Mathematics, Computer Vision, AWS",Associate,5,Retail,2024-06-02,2024-07-05,2001,7.4,Neural Networks Co -AI11600,Data Engineer,33680,USD,33680,EN,FL,China,M,China,100,"Statistics, AWS, PyTorch, Kubernetes, TensorFlow",Associate,0,Gaming,2024-10-14,2024-11-16,555,6.4,TechCorp Inc -AI11601,Machine Learning Researcher,115942,USD,115942,MI,FL,United States,L,United States,0,"Scala, AWS, Data Visualization, Computer Vision",Bachelor,3,Finance,2024-07-20,2024-09-09,1811,7.7,AI Innovations -AI11602,AI Architect,77384,AUD,104468,EN,FL,Australia,L,Australia,0,"R, Tableau, Linux, GCP",PhD,1,Real Estate,2025-02-28,2025-04-10,593,5.3,DeepTech Ventures -AI11603,Data Analyst,331419,CHF,298277,EX,FT,Switzerland,M,Switzerland,0,"Git, NLP, R",Associate,18,Manufacturing,2024-05-05,2024-06-17,2175,5.8,DeepTech Ventures -AI11604,Data Scientist,131344,USD,131344,SE,CT,Sweden,L,Australia,100,"Statistics, MLOps, Hadoop, Kubernetes, Docker",PhD,6,Government,2025-01-23,2025-03-23,2206,6.1,Advanced Robotics -AI11605,Autonomous Systems Engineer,81352,USD,81352,EX,PT,India,M,Kenya,50,"Python, TensorFlow, Deep Learning, Hadoop, Linux",Master,11,Telecommunications,2024-01-27,2024-03-15,1582,6.7,Quantum Computing Inc -AI11606,NLP Engineer,75140,EUR,63869,EN,FT,Netherlands,S,Netherlands,100,"Java, Spark, Kubernetes",Associate,0,Real Estate,2025-04-26,2025-05-23,2246,9.4,Cloud AI Solutions -AI11607,AI Specialist,57023,USD,57023,EN,FL,Ireland,M,United Kingdom,100,"NLP, Statistics, AWS, Kubernetes",Bachelor,0,Education,2024-03-23,2024-04-25,1207,8,Future Systems -AI11608,Principal Data Scientist,76910,JPY,8460100,EN,FL,Japan,S,Japan,50,"Python, Azure, Tableau, SQL, Deep Learning",Associate,1,Transportation,2025-02-24,2025-04-05,1100,5.5,Machine Intelligence Group -AI11609,Data Engineer,86816,USD,86816,EN,FT,Norway,S,Norway,50,"Hadoop, Python, MLOps, Docker, Tableau",Bachelor,1,Automotive,2024-12-28,2025-02-16,1200,7.4,Predictive Systems -AI11610,Head of AI,177419,EUR,150806,EX,FL,Austria,L,Austria,50,"PyTorch, Hadoop, Kubernetes, TensorFlow, Java",Master,14,Telecommunications,2024-11-19,2025-01-27,1430,7.7,DataVision Ltd -AI11611,Principal Data Scientist,143077,USD,143077,EX,FT,Israel,M,Italy,50,"R, Spark, AWS, Scala, NLP",Master,12,Real Estate,2024-12-05,2025-02-02,2272,5.8,Cognitive Computing -AI11612,Robotics Engineer,55124,SGD,71661,EN,FT,Singapore,S,United Kingdom,50,"Statistics, Scala, Hadoop, Spark",Associate,1,Government,2024-03-23,2024-05-01,792,7,Digital Transformation LLC -AI11613,Data Analyst,202411,USD,202411,EX,FL,Sweden,S,Sweden,100,"SQL, R, Tableau, PyTorch, Java",PhD,16,Healthcare,2024-09-05,2024-10-26,2074,6.4,AI Innovations -AI11614,Deep Learning Engineer,84402,EUR,71742,MI,PT,Austria,S,Belgium,50,"AWS, Git, TensorFlow, R",PhD,2,Healthcare,2024-04-20,2024-05-29,1385,10,Autonomous Tech -AI11615,Machine Learning Engineer,194046,GBP,145535,EX,PT,United Kingdom,L,United Kingdom,100,"Linux, Azure, Statistics, PyTorch",PhD,12,Manufacturing,2024-12-10,2024-12-26,2089,9.9,Smart Analytics -AI11616,Research Scientist,59744,AUD,80654,EN,PT,Australia,S,Australia,100,"MLOps, Computer Vision, Deep Learning, R",Associate,0,Healthcare,2024-04-18,2024-05-12,1076,7.2,Future Systems -AI11617,ML Ops Engineer,102625,USD,102625,SE,FL,Israel,M,Israel,50,"Azure, SQL, GCP",Master,5,Government,2024-01-27,2024-03-18,751,7.9,Neural Networks Co -AI11618,Computer Vision Engineer,56790,EUR,48272,EN,FT,France,S,South Korea,100,"Git, GCP, Java",Master,1,Manufacturing,2024-01-28,2024-04-05,1966,5.2,Autonomous Tech -AI11619,AI Specialist,56948,USD,56948,EN,PT,Ireland,M,Ireland,50,"SQL, Mathematics, TensorFlow, AWS",Master,0,Transportation,2024-01-25,2024-04-04,1345,6.9,Quantum Computing Inc -AI11620,AI Product Manager,124698,USD,124698,MI,FT,United States,M,Chile,50,"Java, R, Scala, Linux",PhD,3,Gaming,2024-10-11,2024-11-24,600,5.1,AI Innovations -AI11621,Principal Data Scientist,158637,USD,158637,SE,PT,Norway,L,Indonesia,50,"Data Visualization, Docker, Azure, R, PyTorch",Associate,6,Real Estate,2024-02-22,2024-04-23,1254,7.8,Quantum Computing Inc -AI11622,AI Product Manager,104750,USD,104750,MI,CT,Israel,L,Switzerland,100,"PyTorch, Spark, Tableau, Computer Vision, Azure",Associate,4,Technology,2024-12-11,2025-01-23,2141,6.4,Autonomous Tech -AI11623,AI Software Engineer,149617,JPY,16457870,EX,CT,Japan,S,Japan,50,"Kubernetes, Scala, Java",PhD,13,Consulting,2024-03-03,2024-03-20,523,6.7,DataVision Ltd -AI11624,Data Analyst,54122,SGD,70359,EN,CT,Singapore,M,Singapore,100,"Spark, PyTorch, Statistics, Docker, Mathematics",Bachelor,1,Real Estate,2024-04-30,2024-07-11,851,7.3,Smart Analytics -AI11625,Deep Learning Engineer,103462,JPY,11380820,MI,PT,Japan,S,Germany,100,"SQL, Kubernetes, Computer Vision, Java",Bachelor,3,Gaming,2024-05-07,2024-05-24,1539,5.1,Future Systems -AI11626,Data Analyst,200620,USD,200620,EX,PT,Denmark,S,Denmark,100,"TensorFlow, NLP, GCP, AWS, PyTorch",PhD,10,Energy,2024-09-26,2024-11-05,1152,9.5,Digital Transformation LLC -AI11627,Deep Learning Engineer,63203,GBP,47402,EN,FT,United Kingdom,S,Israel,0,"NLP, Python, AWS",Bachelor,1,Technology,2024-09-21,2024-10-21,1794,5.4,Advanced Robotics -AI11628,Machine Learning Researcher,92506,EUR,78630,EN,FL,Netherlands,L,Netherlands,50,"Scala, Python, Mathematics",Bachelor,0,Manufacturing,2024-09-26,2024-10-10,565,6.2,Predictive Systems -AI11629,AI Research Scientist,78404,USD,78404,MI,FT,South Korea,S,South Korea,50,"Mathematics, TensorFlow, Tableau, MLOps, Kubernetes",PhD,4,Real Estate,2025-01-19,2025-02-25,2407,9.3,Future Systems -AI11630,AI Product Manager,155868,EUR,132488,SE,FT,Netherlands,L,Netherlands,0,"Hadoop, TensorFlow, NLP",Master,6,Technology,2024-12-05,2025-01-17,2008,5.3,Predictive Systems -AI11631,AI Research Scientist,156517,USD,156517,SE,FL,United States,M,United States,50,"SQL, Linux, Data Visualization",PhD,8,Healthcare,2024-10-11,2024-12-17,1487,6.4,Algorithmic Solutions -AI11632,Data Analyst,212507,USD,212507,EX,FT,United States,S,Estonia,100,"AWS, Scala, Java, Statistics",Associate,12,Finance,2025-03-30,2025-05-04,1171,9.9,Advanced Robotics -AI11633,Machine Learning Researcher,171831,JPY,18901410,SE,CT,Japan,L,Japan,0,"TensorFlow, Hadoop, NLP",Bachelor,5,Technology,2024-03-30,2024-05-12,1514,6.1,AI Innovations -AI11634,Computer Vision Engineer,208009,USD,208009,EX,FT,United States,S,Chile,50,"Spark, PyTorch, SQL",Bachelor,14,Transportation,2024-07-28,2024-10-06,2490,5.8,Quantum Computing Inc -AI11635,Data Scientist,193197,EUR,164217,EX,FL,Germany,L,Germany,50,"Tableau, Python, Spark, Mathematics",Associate,19,Telecommunications,2024-05-18,2024-06-24,1462,5.7,Smart Analytics -AI11636,AI Architect,105371,USD,105371,MI,FT,Norway,S,Colombia,100,"R, MLOps, Spark, PyTorch, GCP",Bachelor,4,Finance,2024-10-16,2024-11-21,797,9.7,Algorithmic Solutions -AI11637,Deep Learning Engineer,166349,CAD,207936,EX,CT,Canada,L,Canada,0,"Spark, NLP, Scala",Bachelor,14,Telecommunications,2024-04-13,2024-06-17,1478,7.6,Autonomous Tech -AI11638,Research Scientist,141464,USD,141464,SE,FT,Denmark,M,Denmark,100,"MLOps, Git, Scala, GCP",Bachelor,6,Manufacturing,2024-12-27,2025-02-09,1520,7.4,Cognitive Computing -AI11639,AI Consultant,28009,USD,28009,EN,CT,China,M,China,100,"Linux, SQL, MLOps",Master,1,Telecommunications,2024-03-04,2024-03-26,2322,5.1,Digital Transformation LLC -AI11640,Head of AI,173041,USD,173041,EX,FL,Finland,S,Finland,100,"NLP, Kubernetes, Deep Learning, Git",Master,10,Government,2024-01-14,2024-02-17,730,8,Autonomous Tech -AI11641,Robotics Engineer,239925,USD,239925,EX,CT,Finland,L,Finland,100,"Python, Linux, Data Visualization, Scala, Mathematics",PhD,10,Manufacturing,2024-08-23,2024-10-29,2431,7.9,TechCorp Inc -AI11642,Deep Learning Engineer,36984,USD,36984,EN,FT,China,L,China,0,"Hadoop, Java, R, Data Visualization, Kubernetes",Associate,0,Government,2024-06-13,2024-07-21,1370,8.3,Predictive Systems -AI11643,AI Consultant,251261,USD,251261,EX,PT,Denmark,L,Poland,100,"Azure, Git, Linux",Bachelor,18,Real Estate,2024-12-13,2025-02-11,593,7.8,Neural Networks Co -AI11644,AI Consultant,139815,USD,139815,EX,PT,South Korea,L,Turkey,0,"NLP, SQL, Java, Deep Learning",Bachelor,13,Gaming,2024-09-26,2024-11-25,969,8.3,DataVision Ltd -AI11645,Deep Learning Engineer,51437,EUR,43721,EN,PT,France,M,France,50,"MLOps, AWS, Python, Hadoop, Statistics",Master,0,Media,2025-01-11,2025-03-08,830,8.6,Quantum Computing Inc -AI11646,AI Software Engineer,89863,USD,89863,SE,CT,South Korea,S,South Korea,50,"Git, Hadoop, Python, Linux, Kubernetes",Master,6,Healthcare,2024-02-06,2024-03-30,1952,8.7,Cloud AI Solutions -AI11647,Machine Learning Researcher,65048,USD,65048,EN,PT,Denmark,S,Denmark,50,"Computer Vision, Scala, R, Mathematics, Azure",PhD,0,Healthcare,2024-12-12,2025-01-30,1762,7,AI Innovations -AI11648,Machine Learning Researcher,136806,USD,136806,SE,PT,Sweden,L,Sweden,100,"TensorFlow, R, NLP",Associate,6,Media,2024-04-21,2024-05-06,952,9,Future Systems -AI11649,Deep Learning Engineer,104749,SGD,136174,SE,FT,Singapore,S,Singapore,0,"GCP, TensorFlow, Deep Learning, Python, Git",Associate,7,Retail,2024-02-29,2024-03-17,1742,6.4,Machine Intelligence Group -AI11650,Robotics Engineer,96999,USD,96999,MI,PT,South Korea,L,South Korea,0,"Python, Deep Learning, NLP",Associate,4,Finance,2024-06-25,2024-08-18,1657,5.2,Advanced Robotics -AI11651,Principal Data Scientist,243815,USD,243815,EX,FL,Norway,S,Ukraine,100,"Scala, Java, AWS, R, NLP",Master,18,Healthcare,2024-08-06,2024-09-04,1774,9.8,Neural Networks Co -AI11652,AI Product Manager,76637,GBP,57478,MI,FL,United Kingdom,S,Australia,100,"R, PyTorch, Mathematics, Kubernetes",PhD,4,Education,2025-03-08,2025-05-18,2173,7.5,Digital Transformation LLC -AI11653,ML Ops Engineer,85502,USD,85502,EN,PT,Denmark,L,Denmark,100,"PyTorch, Data Visualization, Spark, Scala, Deep Learning",Bachelor,1,Education,2025-04-12,2025-06-06,2375,6.9,Advanced Robotics -AI11654,Research Scientist,120897,JPY,13298670,SE,CT,Japan,M,Japan,50,"Python, Java, Mathematics",Master,6,Consulting,2024-11-25,2024-12-11,2364,8.5,Machine Intelligence Group -AI11655,Robotics Engineer,91013,USD,91013,EN,FL,Denmark,M,Denmark,0,"Python, Docker, Linux, Git, Scala",Bachelor,0,Media,2024-01-15,2024-01-29,2453,9.9,Predictive Systems -AI11656,Data Engineer,85335,EUR,72535,MI,FL,Austria,S,Austria,50,"Git, PyTorch, MLOps, Computer Vision",PhD,3,Energy,2024-09-09,2024-11-16,1556,5.4,Cognitive Computing -AI11657,AI Consultant,163644,USD,163644,SE,FL,Ireland,L,Ireland,0,"Git, GCP, Deep Learning, Python",Master,7,Finance,2024-10-14,2024-12-16,2454,7.4,Digital Transformation LLC -AI11658,Autonomous Systems Engineer,95444,USD,95444,EN,FT,Norway,M,Luxembourg,0,"Hadoop, PyTorch, TensorFlow",PhD,0,Media,2025-03-31,2025-05-28,1706,8.3,Neural Networks Co -AI11659,Computer Vision Engineer,246523,EUR,209545,EX,PT,Netherlands,M,Netherlands,0,"Scala, PyTorch, Statistics, SQL, Spark",Associate,11,Healthcare,2024-09-23,2024-11-08,1759,6.4,DataVision Ltd -AI11660,Research Scientist,65060,USD,65060,EN,CT,Finland,S,Finland,50,"Data Visualization, Hadoop, Azure",Master,1,Healthcare,2025-01-24,2025-02-24,2176,5.5,Cloud AI Solutions -AI11661,Principal Data Scientist,78657,GBP,58993,EN,PT,United Kingdom,M,United Kingdom,50,"Docker, Tableau, R",Bachelor,1,Gaming,2025-02-25,2025-04-10,545,6.9,Predictive Systems -AI11662,AI Specialist,138491,JPY,15234010,EX,PT,Japan,S,Denmark,0,"Hadoop, Azure, Python",Master,17,Telecommunications,2024-11-01,2024-12-04,749,8.7,Autonomous Tech -AI11663,AI Research Scientist,78736,SGD,102357,EN,PT,Singapore,L,Singapore,0,"Computer Vision, Data Visualization, Scala",PhD,1,Transportation,2024-09-20,2024-11-22,1390,8.7,Autonomous Tech -AI11664,Research Scientist,72680,EUR,61778,EN,PT,France,L,France,0,"Tableau, Git, Computer Vision, TensorFlow",Master,1,Automotive,2024-08-22,2024-10-16,1594,5.2,Cloud AI Solutions -AI11665,Data Scientist,46963,CAD,58704,EN,FL,Canada,S,Canada,100,"NLP, Python, Azure, TensorFlow, PyTorch",PhD,0,Finance,2024-05-26,2024-07-23,2231,6.8,Algorithmic Solutions -AI11666,AI Software Engineer,196455,AUD,265214,EX,PT,Australia,M,Egypt,0,"TensorFlow, Mathematics, Kubernetes",Master,16,Healthcare,2024-04-15,2024-06-10,714,7.7,Smart Analytics -AI11667,Data Scientist,150699,GBP,113024,SE,FT,United Kingdom,L,United Kingdom,100,"Java, Kubernetes, Scala",PhD,7,Consulting,2024-05-07,2024-07-14,1491,8.2,Neural Networks Co -AI11668,Robotics Engineer,225713,EUR,191856,EX,PT,Netherlands,M,Netherlands,100,"Tableau, Kubernetes, Mathematics",Master,18,Real Estate,2024-02-23,2024-03-09,764,7.6,Predictive Systems -AI11669,Robotics Engineer,89546,USD,89546,EX,PT,India,M,Indonesia,100,"Java, NLP, Hadoop, SQL, Mathematics",Associate,10,Energy,2024-06-28,2024-08-30,2223,7.3,Autonomous Tech -AI11670,Data Scientist,38039,USD,38039,SE,PT,India,M,India,100,"Deep Learning, Git, Kubernetes, GCP",PhD,6,Media,2024-06-30,2024-07-23,1391,6.2,Machine Intelligence Group -AI11671,Data Analyst,157935,CHF,142142,SE,PT,Switzerland,M,Switzerland,50,"Docker, Statistics, NLP, Scala, Python",PhD,6,Consulting,2024-05-13,2024-07-05,2149,8.2,Cognitive Computing -AI11672,Data Analyst,87759,SGD,114087,MI,PT,Singapore,S,Singapore,100,"Git, AWS, Docker, SQL",Bachelor,3,Telecommunications,2024-01-09,2024-03-10,1228,6.9,Advanced Robotics -AI11673,AI Architect,155389,GBP,116542,SE,FL,United Kingdom,L,United Kingdom,0,"Tableau, Hadoop, PyTorch, NLP, Mathematics",Master,7,Manufacturing,2024-05-22,2024-07-04,1487,9.3,Predictive Systems -AI11674,Machine Learning Engineer,73343,EUR,62342,EN,CT,France,M,France,50,"Java, Deep Learning, NLP, SQL, Python",PhD,1,Automotive,2024-08-11,2024-10-04,2451,8.6,Autonomous Tech -AI11675,NLP Engineer,24357,USD,24357,EN,FT,India,L,India,50,"Deep Learning, Hadoop, Kubernetes, Java",Master,1,Automotive,2024-06-03,2024-06-18,950,7.8,Future Systems -AI11676,Autonomous Systems Engineer,69149,USD,69149,EN,FL,Israel,M,Israel,50,"Data Visualization, Java, SQL",PhD,1,Retail,2024-07-30,2024-09-10,2197,8.5,DeepTech Ventures -AI11677,AI Specialist,65314,EUR,55517,EN,PT,France,S,France,50,"Linux, R, PyTorch, GCP, Git",Associate,1,Media,2024-06-20,2024-07-27,1963,5.8,AI Innovations -AI11678,Deep Learning Engineer,133224,USD,133224,SE,PT,Sweden,L,Sweden,50,"TensorFlow, Git, Python, Deep Learning",Master,7,Gaming,2024-07-18,2024-08-18,2306,6.3,Cloud AI Solutions -AI11679,Head of AI,38105,USD,38105,EN,CT,South Korea,S,Italy,0,"AWS, Python, Statistics, TensorFlow",Associate,1,Real Estate,2025-03-17,2025-04-03,563,7.8,Cloud AI Solutions -AI11680,Deep Learning Engineer,63981,USD,63981,EN,FL,Israel,L,Israel,0,"SQL, NLP, Tableau, Computer Vision",PhD,1,Retail,2024-01-09,2024-02-14,1632,8.7,Cognitive Computing -AI11681,AI Software Engineer,231463,GBP,173597,EX,PT,United Kingdom,L,United Kingdom,50,"Data Visualization, Scala, R",Master,12,Education,2024-04-17,2024-06-04,1661,7.4,DataVision Ltd -AI11682,Data Engineer,303234,USD,303234,EX,FL,United States,L,United States,0,"Python, MLOps, Java, TensorFlow, Git",Bachelor,10,Finance,2024-03-14,2024-04-19,2490,6.8,Cognitive Computing -AI11683,Data Analyst,57839,USD,57839,EN,FT,Ireland,S,Ireland,100,"Git, Python, Java, Computer Vision, Scala",PhD,1,Manufacturing,2024-07-04,2024-09-15,746,5.9,DeepTech Ventures -AI11684,Head of AI,105737,USD,105737,MI,FL,Norway,M,Norway,100,"Computer Vision, Kubernetes, TensorFlow, Hadoop, Statistics",Associate,4,Education,2024-11-10,2024-12-31,746,7.9,TechCorp Inc -AI11685,NLP Engineer,83703,GBP,62777,EN,CT,United Kingdom,M,United Kingdom,0,"NLP, Deep Learning, Spark",PhD,1,Technology,2025-01-14,2025-03-14,1926,7,Quantum Computing Inc -AI11686,Research Scientist,374078,USD,374078,EX,FL,Denmark,L,Denmark,100,"Docker, Kubernetes, Deep Learning",PhD,18,Media,2024-04-04,2024-04-27,617,8.4,Predictive Systems -AI11687,AI Consultant,73845,USD,73845,MI,PT,Sweden,S,Sweden,50,"Mathematics, R, AWS",Associate,3,Transportation,2025-03-13,2025-05-22,1960,8.4,Predictive Systems -AI11688,Autonomous Systems Engineer,199570,USD,199570,EX,PT,South Korea,M,South Korea,0,"MLOps, Java, AWS",Master,18,Real Estate,2024-10-29,2024-11-24,1566,5.8,Predictive Systems -AI11689,ML Ops Engineer,59456,USD,59456,EN,FL,Ireland,S,Ireland,50,"Linux, Python, Data Visualization, Mathematics",Master,1,Retail,2024-06-23,2024-09-01,765,5.6,Cloud AI Solutions -AI11690,Principal Data Scientist,46874,USD,46874,MI,CT,China,M,China,50,"PyTorch, GCP, Computer Vision, NLP, AWS",Associate,2,Education,2024-06-09,2024-08-11,730,9.2,Quantum Computing Inc -AI11691,Machine Learning Researcher,264204,USD,264204,EX,PT,United States,M,United States,100,"Kubernetes, Hadoop, NLP",Master,12,Education,2025-04-19,2025-05-21,1029,5.7,Advanced Robotics -AI11692,Autonomous Systems Engineer,92702,USD,92702,MI,CT,Denmark,S,Denmark,100,"Linux, MLOps, Deep Learning, Hadoop",Bachelor,4,Energy,2024-04-13,2024-05-31,803,6,Digital Transformation LLC -AI11693,Machine Learning Engineer,127152,USD,127152,SE,FT,Ireland,M,Ireland,100,"Kubernetes, PyTorch, Git, Hadoop",Master,9,Media,2024-03-11,2024-04-17,821,8.2,Future Systems -AI11694,AI Product Manager,97952,USD,97952,EX,FL,India,L,India,0,"Linux, Data Visualization, Git, Deep Learning",Master,15,Finance,2024-07-17,2024-09-18,957,5.7,Algorithmic Solutions -AI11695,Deep Learning Engineer,119734,EUR,101774,SE,CT,Austria,L,Australia,100,"Scala, Python, NLP, Azure",Master,6,Gaming,2025-02-21,2025-05-03,2012,5.1,Neural Networks Co -AI11696,Head of AI,52313,USD,52313,SE,FL,India,L,India,100,"GCP, NLP, Git, Azure, MLOps",PhD,8,Education,2025-04-03,2025-05-24,2225,6,Algorithmic Solutions -AI11697,Principal Data Scientist,150527,USD,150527,SE,PT,Norway,S,Norway,100,"Tableau, Python, TensorFlow, Spark, Scala",PhD,6,Energy,2025-04-10,2025-05-09,1649,6.3,TechCorp Inc -AI11698,Research Scientist,102071,EUR,86760,SE,CT,Austria,M,Austria,100,"Data Visualization, PyTorch, Tableau, Spark",Bachelor,8,Transportation,2024-09-29,2024-10-24,750,6.4,Digital Transformation LLC -AI11699,AI Specialist,120049,JPY,13205390,SE,FL,Japan,M,Australia,100,"Python, GCP, TensorFlow, Docker, Mathematics",Master,8,Healthcare,2024-09-12,2024-10-31,2407,6.7,Advanced Robotics -AI11700,Data Scientist,57666,USD,57666,EN,FT,United States,S,Germany,0,"Python, TensorFlow, MLOps",Master,1,Telecommunications,2025-02-12,2025-03-09,664,6.4,AI Innovations -AI11701,Research Scientist,48186,USD,48186,EN,FT,South Korea,M,Egypt,0,"Data Visualization, Tableau, Linux, MLOps",Associate,1,Technology,2024-01-18,2024-02-28,1545,7.3,Advanced Robotics -AI11702,Research Scientist,105485,EUR,89662,SE,PT,Germany,S,Germany,0,"Statistics, Azure, Python",PhD,7,Manufacturing,2024-10-31,2025-01-10,2359,8.1,Cloud AI Solutions -AI11703,NLP Engineer,131219,SGD,170585,SE,PT,Singapore,S,Singapore,50,"Azure, NLP, Scala",Bachelor,7,Media,2025-03-22,2025-04-18,1790,9.4,Advanced Robotics -AI11704,Robotics Engineer,51061,AUD,68932,EN,CT,Australia,M,Switzerland,50,"Java, Linux, PyTorch, Azure, Spark",Bachelor,1,Retail,2025-03-07,2025-05-16,900,8.2,Digital Transformation LLC -AI11705,AI Research Scientist,118577,USD,118577,MI,PT,Israel,L,Singapore,0,"Hadoop, Spark, TensorFlow, Mathematics, NLP",Master,3,Telecommunications,2024-11-17,2024-12-08,915,9.3,TechCorp Inc -AI11706,Robotics Engineer,123562,JPY,13591820,MI,PT,Japan,L,Canada,0,"NLP, Computer Vision, Linux",Bachelor,4,Healthcare,2024-01-08,2024-02-17,2221,8.1,Advanced Robotics -AI11707,AI Research Scientist,51487,GBP,38615,EN,FT,United Kingdom,S,United Kingdom,50,"Tableau, Docker, MLOps, R, Kubernetes",Associate,0,Education,2024-05-08,2024-05-29,1828,6.3,Advanced Robotics -AI11708,AI Research Scientist,48045,EUR,40838,EN,CT,Austria,M,South Africa,0,"NLP, Git, PyTorch",PhD,1,Healthcare,2025-01-04,2025-01-22,2067,6.2,Quantum Computing Inc -AI11709,Principal Data Scientist,107844,USD,107844,SE,FT,Sweden,M,India,0,"Hadoop, Linux, Data Visualization",PhD,5,Telecommunications,2024-02-19,2024-03-09,2493,6.6,TechCorp Inc -AI11710,Machine Learning Engineer,39178,USD,39178,EN,FT,South Korea,S,India,50,"R, SQL, MLOps, Statistics, GCP",Bachelor,1,Consulting,2024-02-25,2024-04-07,2194,8.4,Machine Intelligence Group -AI11711,AI Architect,222589,SGD,289366,EX,FL,Singapore,S,Singapore,100,"Scala, R, MLOps, AWS, Tableau",Associate,19,Technology,2025-04-01,2025-04-19,1448,7.8,AI Innovations -AI11712,AI Software Engineer,103634,EUR,88089,MI,CT,Netherlands,L,Netherlands,100,"PyTorch, Data Visualization, Tableau, TensorFlow, Docker",PhD,2,Education,2024-03-26,2024-04-13,1772,6.2,Smart Analytics -AI11713,AI Consultant,144301,SGD,187591,SE,FT,Singapore,M,Singapore,0,"Spark, R, TensorFlow, Computer Vision",Bachelor,6,Healthcare,2024-12-17,2025-02-21,2482,8.9,Predictive Systems -AI11714,AI Specialist,99374,EUR,84468,SE,PT,Austria,M,Austria,0,"Git, Scala, Java",Associate,7,Transportation,2024-04-05,2024-04-22,2414,6.5,Quantum Computing Inc -AI11715,AI Software Engineer,182255,USD,182255,EX,FL,Sweden,M,Sweden,0,"Data Visualization, Spark, Python, TensorFlow",Associate,18,Manufacturing,2024-10-22,2024-11-13,846,8,TechCorp Inc -AI11716,Data Engineer,64006,USD,64006,MI,CT,Finland,S,Finland,100,"Java, Kubernetes, Data Visualization, Scala, AWS",PhD,2,Retail,2025-04-12,2025-06-07,1653,6.9,Autonomous Tech -AI11717,Autonomous Systems Engineer,240322,CHF,216290,SE,FL,Switzerland,L,Switzerland,100,"Docker, Mathematics, PyTorch",Bachelor,7,Government,2024-06-28,2024-08-10,2379,7.5,AI Innovations -AI11718,Computer Vision Engineer,90893,USD,90893,MI,PT,Ireland,M,Ireland,50,"MLOps, Python, Azure, Statistics",Bachelor,4,Automotive,2025-04-26,2025-07-07,1506,5.3,Cognitive Computing -AI11719,AI Research Scientist,126730,GBP,95048,SE,PT,United Kingdom,M,United Kingdom,50,"Java, Python, R, TensorFlow, Kubernetes",Associate,6,Automotive,2024-01-27,2024-03-25,760,8.2,TechCorp Inc -AI11720,Deep Learning Engineer,90617,USD,90617,MI,FT,Ireland,S,Ireland,50,"Deep Learning, Git, Java",PhD,4,Media,2024-12-31,2025-02-16,2047,8.8,DataVision Ltd -AI11721,Head of AI,67532,CAD,84415,EN,FT,Canada,M,Luxembourg,100,"Computer Vision, Git, R, Kubernetes",Associate,0,Education,2024-05-11,2024-07-04,1673,5.8,Cloud AI Solutions -AI11722,AI Product Manager,81482,USD,81482,EN,CT,United States,M,United States,50,"AWS, Scala, Kubernetes, NLP",Associate,0,Finance,2024-12-16,2025-02-01,1186,7.6,Advanced Robotics -AI11723,Data Engineer,100637,JPY,11070070,MI,CT,Japan,M,Japan,0,"Java, Scala, Tableau",Master,2,Manufacturing,2024-06-07,2024-08-09,2037,8.2,Smart Analytics -AI11724,Autonomous Systems Engineer,182186,USD,182186,SE,CT,United States,L,United States,50,"Linux, AWS, NLP, TensorFlow",Master,7,Media,2024-06-11,2024-07-20,1317,6.9,Autonomous Tech -AI11725,Research Scientist,124119,USD,124119,MI,CT,Denmark,S,Belgium,0,"Java, Data Visualization, Scala, TensorFlow",Master,2,Government,2024-12-04,2025-01-23,1255,9.6,Advanced Robotics -AI11726,Robotics Engineer,75711,EUR,64354,EN,FL,France,M,South Korea,0,"R, Scala, GCP",PhD,0,Government,2024-04-26,2024-05-29,1596,7.8,DataVision Ltd -AI11727,AI Specialist,105178,USD,105178,EX,CT,China,L,Indonesia,50,"AWS, Azure, Tableau, SQL",Master,17,Consulting,2024-02-21,2024-05-02,1551,8.1,Advanced Robotics -AI11728,Data Engineer,245876,USD,245876,EX,FL,United States,M,United States,0,"Hadoop, Data Visualization, SQL, AWS",Associate,13,Government,2024-02-17,2024-04-20,1530,5.7,Cognitive Computing -AI11729,Principal Data Scientist,60817,USD,60817,SE,PT,China,M,New Zealand,0,"Kubernetes, PyTorch, Java, Spark, Computer Vision",Bachelor,6,Energy,2025-04-04,2025-06-08,2238,5.3,AI Innovations -AI11730,Autonomous Systems Engineer,159519,AUD,215351,EX,CT,Australia,S,Australia,100,"Linux, Java, Spark",Bachelor,13,Finance,2025-04-30,2025-07-09,686,8.6,TechCorp Inc -AI11731,AI Software Engineer,62606,USD,62606,EN,FL,Norway,S,Norway,100,"Tableau, TensorFlow, Git, Python",PhD,1,Real Estate,2024-09-27,2024-10-24,2295,7.1,TechCorp Inc -AI11732,ML Ops Engineer,87179,USD,87179,MI,FL,Sweden,S,Denmark,50,"Python, GCP, PyTorch, MLOps, AWS",Associate,4,Education,2024-07-30,2024-09-02,2230,5.6,Neural Networks Co -AI11733,Autonomous Systems Engineer,248988,GBP,186741,EX,PT,United Kingdom,L,United Kingdom,0,"Kubernetes, Python, AWS, SQL",PhD,18,Healthcare,2024-01-30,2024-02-15,2260,8.5,DeepTech Ventures -AI11734,Research Scientist,85390,EUR,72582,EN,CT,Austria,L,Austria,50,"Linux, Hadoop, Docker, Python, Kubernetes",Master,0,Manufacturing,2025-03-19,2025-04-19,1718,7.1,Machine Intelligence Group -AI11735,Machine Learning Researcher,85050,USD,85050,EN,FT,Norway,L,Ukraine,0,"TensorFlow, Java, AWS",PhD,0,Healthcare,2024-03-08,2024-05-10,1927,5.7,Machine Intelligence Group -AI11736,Machine Learning Researcher,162248,USD,162248,SE,FL,Denmark,M,China,50,"Python, NLP, TensorFlow",Master,7,Media,2024-11-27,2025-01-11,1029,5.6,Autonomous Tech -AI11737,Machine Learning Engineer,89020,USD,89020,MI,FT,Ireland,M,Ireland,50,"Kubernetes, Data Visualization, Computer Vision, MLOps, NLP",Master,3,Energy,2024-12-05,2024-12-24,1355,7.9,Cloud AI Solutions -AI11738,Head of AI,197899,EUR,168214,EX,FL,Netherlands,L,Netherlands,0,"MLOps, Hadoop, AWS, Scala, TensorFlow",Bachelor,17,Consulting,2024-08-06,2024-10-06,1178,7.4,DataVision Ltd -AI11739,AI Software Engineer,300946,USD,300946,EX,CT,Denmark,L,Denmark,50,"MLOps, Azure, SQL, Kubernetes",Master,11,Gaming,2024-01-05,2024-03-13,949,6.2,Cloud AI Solutions -AI11740,ML Ops Engineer,128716,AUD,173767,SE,FT,Australia,L,Chile,100,"Azure, Scala, SQL, Spark",Associate,6,Technology,2025-01-16,2025-02-04,704,7.8,Autonomous Tech -AI11741,Machine Learning Researcher,69635,USD,69635,MI,FL,Ireland,S,Austria,50,"Mathematics, TensorFlow, Hadoop",Master,4,Energy,2024-04-17,2024-06-02,2256,10,DataVision Ltd -AI11742,Robotics Engineer,75013,USD,75013,EN,FL,Sweden,M,Latvia,0,"Kubernetes, Docker, Hadoop, MLOps",Bachelor,1,Government,2024-01-20,2024-03-25,2410,6.2,Cognitive Computing -AI11743,Head of AI,55579,USD,55579,EX,CT,India,L,India,100,"Spark, Git, R, Computer Vision",PhD,15,Finance,2024-10-15,2024-11-28,2417,8.1,Autonomous Tech -AI11744,Data Engineer,296991,EUR,252442,EX,PT,Netherlands,L,Netherlands,0,"Computer Vision, Python, TensorFlow, Mathematics, GCP",PhD,14,Retail,2024-01-02,2024-02-13,2415,8.6,Algorithmic Solutions -AI11745,Autonomous Systems Engineer,112545,JPY,12379950,MI,PT,Japan,M,Japan,0,"Python, NLP, SQL",PhD,3,Retail,2025-01-21,2025-03-06,1781,7.6,Quantum Computing Inc -AI11746,Computer Vision Engineer,69324,USD,69324,EX,PT,China,M,Colombia,0,"NLP, SQL, Java, R, Tableau",PhD,14,Education,2024-10-24,2024-12-23,519,7.5,DeepTech Ventures -AI11747,AI Research Scientist,98287,USD,98287,SE,FT,South Korea,S,South Korea,100,"R, Hadoop, Java, GCP, NLP",Bachelor,8,Retail,2024-12-05,2024-12-27,2317,7.2,DataVision Ltd -AI11748,AI Research Scientist,115628,SGD,150316,MI,CT,Singapore,L,Singapore,100,"Computer Vision, Python, GCP",Bachelor,2,Energy,2025-04-23,2025-07-03,2069,6.6,TechCorp Inc -AI11749,AI Research Scientist,61446,USD,61446,EN,PT,Finland,L,Finland,50,"Docker, Linux, Tableau",Master,0,Education,2025-02-08,2025-02-26,1567,8.6,Neural Networks Co -AI11750,AI Consultant,120919,USD,120919,MI,FT,Denmark,S,Denmark,50,"Kubernetes, Docker, AWS",Associate,3,Healthcare,2025-03-20,2025-04-13,1792,8.8,Cloud AI Solutions -AI11751,Research Scientist,145685,SGD,189391,SE,FL,Singapore,L,Chile,50,"AWS, Hadoop, NLP",Bachelor,5,Education,2024-11-30,2025-01-18,1182,7.2,DataVision Ltd -AI11752,Autonomous Systems Engineer,67265,USD,67265,EN,FL,South Korea,L,South Africa,100,"SQL, Kubernetes, Mathematics, PyTorch",Master,0,Transportation,2024-03-06,2024-04-05,927,9.6,DeepTech Ventures -AI11753,Principal Data Scientist,93562,CAD,116953,MI,CT,Canada,S,Canada,100,"Tableau, Linux, Kubernetes, GCP, Spark",Bachelor,4,Government,2024-02-26,2024-04-26,1548,5.6,DataVision Ltd -AI11754,AI Software Engineer,128363,EUR,109109,SE,CT,Germany,L,Germany,0,"Azure, Linux, Python, SQL",PhD,9,Media,2024-09-28,2024-12-10,591,5.6,Cognitive Computing -AI11755,Data Scientist,142169,EUR,120844,SE,FL,Netherlands,M,Netherlands,50,"Tableau, NLP, Scala, Java",Master,9,Transportation,2024-10-01,2024-12-03,1840,8.7,Autonomous Tech -AI11756,Data Analyst,82106,EUR,69790,MI,FL,Germany,M,Germany,0,"Java, Git, Computer Vision, Statistics, Data Visualization",PhD,4,Consulting,2024-02-01,2024-04-04,1738,5.8,Cognitive Computing -AI11757,AI Software Engineer,349865,CHF,314879,EX,FL,Switzerland,M,Switzerland,50,"Mathematics, Hadoop, Data Visualization",Associate,17,Automotive,2024-03-27,2024-06-06,661,9.9,Algorithmic Solutions -AI11758,Data Engineer,105787,USD,105787,SE,FL,South Korea,M,South Korea,100,"R, SQL, PyTorch, Mathematics",PhD,5,Telecommunications,2024-12-23,2025-01-18,2347,9.8,Smart Analytics -AI11759,Data Scientist,123402,USD,123402,MI,CT,Sweden,L,Ukraine,100,"NLP, AWS, PyTorch",Master,3,Gaming,2024-11-27,2024-12-22,592,7.6,Autonomous Tech -AI11760,Machine Learning Researcher,239675,USD,239675,EX,FT,Israel,M,Malaysia,100,"Tableau, MLOps, SQL, Mathematics, Git",Associate,12,Transportation,2024-01-13,2024-02-09,1523,8.8,Advanced Robotics -AI11761,Principal Data Scientist,241965,AUD,326653,EX,FT,Australia,L,Australia,100,"Hadoop, Data Visualization, Tableau, Deep Learning, Python",Bachelor,19,Telecommunications,2024-11-07,2024-11-24,853,8.5,Smart Analytics -AI11762,Machine Learning Engineer,76847,USD,76847,MI,FT,Sweden,M,Sweden,50,"MLOps, Computer Vision, SQL, Mathematics",Bachelor,4,Transportation,2024-07-17,2024-09-23,1659,7.9,Cloud AI Solutions -AI11763,Computer Vision Engineer,200851,USD,200851,SE,PT,Denmark,L,Denmark,0,"Mathematics, SQL, Python, Azure",PhD,7,Gaming,2024-11-29,2025-01-11,2272,7.8,Cognitive Computing -AI11764,Research Scientist,130522,USD,130522,MI,FL,Denmark,L,Denmark,50,"Linux, Data Visualization, Hadoop, Git",Associate,3,Automotive,2024-11-22,2025-02-03,1442,5.3,DataVision Ltd -AI11765,AI Research Scientist,68149,USD,68149,EN,PT,South Korea,L,Thailand,50,"GCP, Linux, Spark, Computer Vision, Mathematics",Master,0,Manufacturing,2024-05-29,2024-07-05,673,6.1,Future Systems -AI11766,Principal Data Scientist,61452,EUR,52234,EN,FL,Netherlands,M,Singapore,0,"Python, AWS, Data Visualization, PyTorch, Kubernetes",Associate,0,Education,2025-01-15,2025-03-07,1472,9.6,Neural Networks Co -AI11767,Head of AI,86593,SGD,112571,MI,FL,Singapore,S,Singapore,100,"Mathematics, Computer Vision, Tableau, MLOps, Hadoop",Master,2,Transportation,2024-06-17,2024-08-04,766,9.4,Smart Analytics -AI11768,AI Consultant,62600,USD,62600,EN,FL,Norway,S,Norway,0,"AWS, R, MLOps, SQL",Master,1,Education,2025-03-29,2025-04-29,851,8,TechCorp Inc -AI11769,Machine Learning Researcher,77533,USD,77533,EN,FT,Denmark,M,Denmark,0,"Statistics, SQL, Python",Master,0,Telecommunications,2025-04-18,2025-05-20,2403,6.5,Autonomous Tech -AI11770,Deep Learning Engineer,212689,EUR,180786,EX,PT,Austria,L,Norway,50,"SQL, Git, Hadoop, Docker, GCP",Master,13,Telecommunications,2024-05-17,2024-06-20,2432,9.3,Advanced Robotics -AI11771,Data Scientist,118889,USD,118889,MI,FL,Israel,L,Netherlands,50,"Hadoop, SQL, Scala",PhD,2,Media,2024-08-18,2024-10-17,669,5.3,Advanced Robotics -AI11772,AI Software Engineer,145546,GBP,109160,SE,FT,United Kingdom,M,United Kingdom,100,"Statistics, Python, NLP, Deep Learning, R",Master,7,Telecommunications,2024-09-06,2024-11-05,1299,7.1,Quantum Computing Inc -AI11773,Deep Learning Engineer,91754,EUR,77991,MI,FL,Netherlands,S,Netherlands,100,"Hadoop, TensorFlow, PyTorch",Associate,3,Transportation,2024-07-27,2024-08-18,745,6.8,Autonomous Tech -AI11774,Research Scientist,144229,GBP,108172,EX,FL,United Kingdom,M,Germany,100,"Kubernetes, GCP, SQL",PhD,18,Real Estate,2024-02-16,2024-03-10,1543,8,Neural Networks Co -AI11775,Robotics Engineer,109199,EUR,92819,SE,PT,Austria,S,Austria,0,"Kubernetes, Statistics, Scala, PyTorch",Master,7,Automotive,2025-02-03,2025-03-08,2168,8.3,Quantum Computing Inc -AI11776,Head of AI,56909,USD,56909,EN,CT,Finland,M,Finland,100,"SQL, Scala, PyTorch, GCP, Java",PhD,1,Real Estate,2024-04-16,2024-05-27,1343,7,Algorithmic Solutions -AI11777,AI Consultant,117496,USD,117496,EX,PT,China,M,China,100,"Deep Learning, Docker, Data Visualization, Tableau, R",Associate,19,Transportation,2024-01-09,2024-02-01,1773,6.1,Predictive Systems -AI11778,Machine Learning Researcher,115487,USD,115487,MI,FL,Denmark,L,Denmark,100,"Kubernetes, PyTorch, Azure, Spark",Associate,4,Telecommunications,2024-01-02,2024-03-15,980,7.2,Cognitive Computing -AI11779,Computer Vision Engineer,115188,EUR,97910,MI,FT,Netherlands,M,India,0,"Data Visualization, NLP, SQL",PhD,4,Telecommunications,2024-08-07,2024-09-06,609,6.4,Cognitive Computing -AI11780,ML Ops Engineer,192782,USD,192782,EX,FL,Ireland,M,Ireland,50,"MLOps, Statistics, Mathematics, Scala, Data Visualization",Associate,16,Media,2025-03-21,2025-04-24,648,9.1,DeepTech Ventures -AI11781,Principal Data Scientist,158600,EUR,134810,EX,CT,Netherlands,S,Netherlands,100,"Python, Linux, Deep Learning",PhD,14,Automotive,2024-09-23,2024-11-18,582,5.5,Smart Analytics -AI11782,Robotics Engineer,64447,GBP,48335,EN,CT,United Kingdom,M,United Kingdom,100,"Computer Vision, Git, Tableau",Master,0,Finance,2024-07-25,2024-09-05,1713,6.5,Future Systems -AI11783,Research Scientist,189773,CHF,170796,SE,FL,Switzerland,M,Ukraine,100,"Computer Vision, Python, TensorFlow",Associate,8,Transportation,2024-05-28,2024-07-24,1824,6.1,Predictive Systems -AI11784,ML Ops Engineer,136525,CAD,170656,SE,CT,Canada,L,Canada,100,"Docker, Azure, Mathematics",Bachelor,9,Healthcare,2024-09-22,2024-11-21,1768,5.3,Algorithmic Solutions -AI11785,Head of AI,108746,USD,108746,EX,FT,South Korea,S,South Korea,50,"Azure, R, Scala, Tableau, Statistics",Master,16,Technology,2025-03-14,2025-05-24,2133,6.3,TechCorp Inc -AI11786,Robotics Engineer,79890,USD,79890,EX,PT,China,S,United States,50,"Computer Vision, Hadoop, GCP, Statistics",PhD,15,Automotive,2024-11-29,2024-12-20,1445,5.3,Predictive Systems -AI11787,AI Architect,128508,USD,128508,EX,FT,Finland,S,Nigeria,50,"Kubernetes, Docker, Spark",Master,16,Technology,2024-11-28,2025-01-05,1335,10,Algorithmic Solutions -AI11788,Computer Vision Engineer,149717,EUR,127259,SE,FT,Netherlands,M,Netherlands,0,"Mathematics, GCP, SQL",Master,6,Consulting,2024-05-22,2024-07-12,893,5.5,Cognitive Computing -AI11789,ML Ops Engineer,74780,CHF,67302,EN,CT,Switzerland,M,Italy,100,"Computer Vision, Mathematics, Tableau, Data Visualization",Master,0,Automotive,2025-03-26,2025-04-11,846,8.7,Autonomous Tech -AI11790,Data Analyst,86855,EUR,73827,EN,FT,France,L,France,50,"PyTorch, Deep Learning, NLP, R, AWS",Associate,1,Gaming,2024-03-06,2024-04-30,577,9.1,Cloud AI Solutions -AI11791,AI Research Scientist,153299,AUD,206954,SE,CT,Australia,L,Egypt,0,"TensorFlow, Python, Deep Learning",Master,9,Energy,2024-04-26,2024-05-11,1120,5.6,DeepTech Ventures -AI11792,Head of AI,53256,USD,53256,EN,PT,Ireland,S,Ireland,100,"GCP, R, Data Visualization, Hadoop, Kubernetes",Associate,1,Gaming,2024-03-29,2024-04-27,1989,7.5,Digital Transformation LLC -AI11793,ML Ops Engineer,104761,USD,104761,EN,CT,Norway,L,Norway,0,"Computer Vision, Git, GCP, Data Visualization",Associate,1,Automotive,2024-09-08,2024-11-13,1927,5.5,DeepTech Ventures -AI11794,AI Product Manager,257772,JPY,28354920,EX,CT,Japan,L,United States,0,"Java, R, Linux, SQL, NLP",Bachelor,11,Education,2024-02-19,2024-04-22,1495,7.6,Smart Analytics -AI11795,Data Analyst,113051,USD,113051,SE,FL,Israel,M,Thailand,50,"Mathematics, Deep Learning, Data Visualization",Master,5,Telecommunications,2024-01-04,2024-03-06,728,5.4,AI Innovations -AI11796,AI Architect,184356,JPY,20279160,SE,PT,Japan,L,Japan,100,"AWS, Tableau, Python",Bachelor,9,Consulting,2024-04-03,2024-04-24,1525,6.7,DeepTech Ventures -AI11797,AI Research Scientist,48522,CAD,60653,EN,FT,Canada,M,Canada,50,"Python, TensorFlow, Tableau",Bachelor,1,Education,2024-05-25,2024-07-20,1523,6.9,Machine Intelligence Group -AI11798,Data Engineer,57358,SGD,74565,EN,CT,Singapore,M,Singapore,100,"Kubernetes, Docker, MLOps, Scala, Mathematics",Associate,0,Education,2025-04-18,2025-05-03,1292,8.7,Future Systems -AI11799,AI Architect,92877,CAD,116096,SE,FT,Canada,S,Canada,0,"Statistics, AWS, Deep Learning",Associate,8,Manufacturing,2024-01-06,2024-03-13,2113,9.1,Cloud AI Solutions -AI11800,Data Engineer,64999,USD,64999,MI,FT,Israel,S,Israel,0,"GCP, Mathematics, Data Visualization, Python",Associate,3,Transportation,2024-03-22,2024-04-16,2159,9.7,Neural Networks Co -AI11801,Deep Learning Engineer,216255,EUR,183817,EX,PT,Germany,L,Germany,50,"SQL, AWS, Tableau",Bachelor,14,Technology,2024-05-01,2024-07-07,742,8.8,DataVision Ltd -AI11802,AI Software Engineer,139600,CAD,174500,SE,FT,Canada,L,Canada,50,"PyTorch, Kubernetes, Computer Vision, Python, Tableau",PhD,9,Gaming,2024-05-08,2024-07-01,1981,9.8,Machine Intelligence Group -AI11803,AI Specialist,214259,USD,214259,SE,FT,Norway,L,Norway,50,"Python, Docker, Azure, Mathematics, Java",PhD,9,Automotive,2025-04-27,2025-05-11,2008,5.9,Predictive Systems -AI11804,Machine Learning Engineer,90613,USD,90613,EX,FL,India,L,India,0,"SQL, Git, Deep Learning, AWS",PhD,12,Education,2024-07-17,2024-09-06,1898,5.4,Future Systems -AI11805,AI Software Engineer,237611,AUD,320775,EX,PT,Australia,M,Australia,0,"Java, Computer Vision, Python, Mathematics",Associate,18,Automotive,2024-09-15,2024-11-23,2125,7.3,Quantum Computing Inc -AI11806,AI Specialist,85520,USD,85520,MI,CT,Israel,L,Israel,50,"Linux, SQL, Python, Scala",Master,2,Technology,2025-02-25,2025-03-11,1858,8.4,Digital Transformation LLC -AI11807,Computer Vision Engineer,120980,CAD,151225,EX,CT,Canada,S,Ukraine,0,"Computer Vision, Azure, Spark",Bachelor,10,Healthcare,2024-04-19,2024-05-31,940,7,Cognitive Computing -AI11808,Autonomous Systems Engineer,91834,EUR,78059,MI,PT,Austria,S,Portugal,50,"PyTorch, Scala, Data Visualization",Master,4,Government,2024-02-27,2024-04-21,516,7.9,DeepTech Ventures -AI11809,Computer Vision Engineer,197241,USD,197241,EX,FT,United States,M,Nigeria,0,"Deep Learning, TensorFlow, Hadoop, GCP",Bachelor,19,Education,2024-11-07,2024-12-28,652,7.3,Predictive Systems -AI11810,Machine Learning Researcher,26172,USD,26172,MI,FL,India,S,India,100,"Linux, NLP, Scala, Statistics",PhD,2,Consulting,2025-02-09,2025-03-14,603,5,Smart Analytics -AI11811,ML Ops Engineer,95730,USD,95730,SE,FT,Israel,S,Israel,0,"Tableau, Kubernetes, TensorFlow, Data Visualization, NLP",Master,5,Consulting,2024-02-26,2024-04-07,1257,6.2,Quantum Computing Inc -AI11812,Machine Learning Engineer,269491,USD,269491,EX,FT,United States,S,United States,50,"Tableau, R, Azure",Associate,15,Consulting,2024-11-04,2024-11-29,2469,8.9,Digital Transformation LLC -AI11813,Research Scientist,103816,CHF,93434,EN,FL,Switzerland,M,Switzerland,0,"GCP, R, Mathematics",Master,1,Government,2025-01-21,2025-02-25,1061,9.4,DataVision Ltd -AI11814,Data Analyst,120743,USD,120743,SE,PT,South Korea,M,Nigeria,100,"PyTorch, Java, Data Visualization",Bachelor,8,Education,2024-08-20,2024-10-07,2458,8.4,TechCorp Inc -AI11815,Data Scientist,23025,USD,23025,MI,FT,India,S,Denmark,100,"Linux, Hadoop, Python, Computer Vision",Associate,4,Consulting,2024-04-04,2024-05-15,1444,5.5,Machine Intelligence Group -AI11816,Autonomous Systems Engineer,44505,USD,44505,SE,FT,India,L,Romania,50,"Hadoop, Data Visualization, Git",Associate,6,Telecommunications,2024-10-04,2024-11-23,2406,8.7,Cognitive Computing -AI11817,Head of AI,105183,JPY,11570130,MI,PT,Japan,L,South Korea,100,"GCP, Spark, Deep Learning",PhD,3,Gaming,2024-09-03,2024-09-30,633,5.8,Autonomous Tech -AI11818,Machine Learning Engineer,137294,USD,137294,EX,PT,Israel,S,Mexico,0,"R, Scala, Docker, GCP",Master,12,Finance,2024-02-03,2024-03-05,1274,8.3,DeepTech Ventures -AI11819,ML Ops Engineer,101696,GBP,76272,SE,PT,United Kingdom,S,United Kingdom,100,"Kubernetes, Azure, PyTorch, Statistics, Mathematics",Associate,6,Telecommunications,2024-04-08,2024-06-15,766,7.1,Autonomous Tech -AI11820,Data Analyst,64069,EUR,54459,MI,PT,Austria,S,Austria,50,"Docker, NLP, Mathematics, Data Visualization",Bachelor,3,Energy,2024-02-28,2024-03-14,748,5.4,TechCorp Inc -AI11821,AI Product Manager,111264,USD,111264,SE,PT,South Korea,M,South Korea,100,"Data Visualization, Linux, SQL, R, Deep Learning",PhD,6,Media,2024-09-16,2024-10-28,2399,8.8,Smart Analytics -AI11822,Principal Data Scientist,109807,USD,109807,MI,PT,Denmark,M,Denmark,50,"Python, Spark, Deep Learning",Associate,4,Telecommunications,2024-10-04,2024-11-24,1800,7.9,Cloud AI Solutions -AI11823,AI Research Scientist,92835,EUR,78910,MI,CT,Netherlands,M,Netherlands,100,"Spark, Computer Vision, PyTorch, Tableau",Associate,3,Retail,2025-02-04,2025-03-07,2441,6.1,Neural Networks Co -AI11824,AI Product Manager,203369,EUR,172864,EX,CT,France,M,France,0,"PyTorch, Docker, Deep Learning",Bachelor,13,Retail,2024-09-09,2024-10-29,1041,7.4,Future Systems -AI11825,Head of AI,177370,USD,177370,EX,CT,Israel,S,Israel,100,"Git, AWS, Python, TensorFlow",Master,17,Telecommunications,2024-10-29,2024-12-16,1070,9.3,Quantum Computing Inc -AI11826,AI Software Engineer,244805,CHF,220325,EX,PT,Switzerland,L,Switzerland,100,"Docker, Python, Data Visualization, TensorFlow",PhD,18,Retail,2024-05-25,2024-07-11,1889,8.5,Algorithmic Solutions -AI11827,AI Product Manager,35462,USD,35462,MI,FT,India,L,India,100,"Tableau, AWS, Mathematics, Linux",Bachelor,3,Healthcare,2024-11-22,2024-12-07,1136,9.7,Future Systems -AI11828,Data Scientist,68404,CAD,85505,EN,FL,Canada,L,Romania,100,"Azure, Scala, SQL, PyTorch, Spark",Associate,0,Real Estate,2024-07-18,2024-09-20,2166,6.5,Cognitive Computing -AI11829,Autonomous Systems Engineer,128996,AUD,174145,SE,FT,Australia,L,Ukraine,100,"GCP, Spark, MLOps, NLP, SQL",Bachelor,7,Healthcare,2024-10-08,2024-12-04,1539,5,Machine Intelligence Group -AI11830,Data Analyst,72807,EUR,61886,EN,FT,Austria,M,Austria,100,"Git, R, Scala, Deep Learning, SQL",PhD,0,Energy,2024-03-02,2024-04-10,2177,7.5,Autonomous Tech -AI11831,Deep Learning Engineer,107118,USD,107118,MI,CT,Denmark,M,Denmark,100,"PyTorch, Data Visualization, GCP, TensorFlow, Linux",Bachelor,4,Automotive,2025-04-11,2025-05-01,2040,8.1,Cognitive Computing -AI11832,Principal Data Scientist,27731,USD,27731,MI,FT,India,M,India,0,"Python, Linux, TensorFlow",Master,4,Consulting,2024-09-04,2024-10-14,976,8.5,Autonomous Tech -AI11833,AI Research Scientist,74228,USD,74228,EN,PT,Norway,M,Norway,100,"Mathematics, Kubernetes, R, Spark, Scala",PhD,0,Automotive,2025-03-29,2025-05-21,2187,9.4,Digital Transformation LLC -AI11834,AI Consultant,77712,USD,77712,EN,FL,Sweden,M,Sweden,0,"Hadoop, PyTorch, Git, Computer Vision",Associate,1,Manufacturing,2024-02-25,2024-05-01,826,6.1,AI Innovations -AI11835,AI Specialist,94668,USD,94668,EX,PT,China,S,China,50,"SQL, NLP, Kubernetes, PyTorch, GCP",PhD,19,Consulting,2024-03-18,2024-04-22,1984,5.4,Cloud AI Solutions -AI11836,AI Architect,212705,USD,212705,EX,FT,South Korea,L,Luxembourg,100,"R, GCP, Tableau",Master,16,Manufacturing,2024-01-15,2024-03-28,2206,6.1,Quantum Computing Inc -AI11837,AI Research Scientist,200761,CHF,180685,EX,PT,Switzerland,S,Switzerland,50,"Kubernetes, SQL, PyTorch, R",Master,11,Real Estate,2024-05-02,2024-06-07,1090,7.1,DeepTech Ventures -AI11838,Machine Learning Engineer,85039,AUD,114803,MI,CT,Australia,M,Australia,100,"Statistics, Tableau, MLOps, Java",Bachelor,2,Manufacturing,2024-08-10,2024-09-22,1756,9.5,Predictive Systems -AI11839,AI Product Manager,62080,USD,62080,EX,CT,India,L,India,50,"Scala, Git, Tableau, Kubernetes, Azure",Bachelor,12,Real Estate,2024-10-03,2024-10-30,987,5.1,Cognitive Computing -AI11840,AI Architect,196292,USD,196292,EX,CT,Sweden,M,Argentina,100,"R, SQL, Deep Learning",Associate,18,Education,2024-03-22,2024-04-29,1280,9.4,Quantum Computing Inc -AI11841,AI Specialist,158220,USD,158220,EX,CT,Sweden,M,Sweden,0,"SQL, TensorFlow, Deep Learning",PhD,19,Gaming,2024-03-13,2024-04-13,1358,7.8,Cognitive Computing -AI11842,AI Architect,29068,USD,29068,MI,FT,India,M,Indonesia,100,"Computer Vision, Hadoop, Linux",Master,4,Gaming,2024-09-14,2024-10-28,913,7.7,DataVision Ltd -AI11843,Data Scientist,61344,GBP,46008,EN,CT,United Kingdom,M,France,0,"TensorFlow, Java, Mathematics, GCP",PhD,1,Transportation,2024-06-15,2024-08-16,1521,7.4,Smart Analytics -AI11844,AI Architect,192580,CHF,173322,SE,FL,Switzerland,M,Switzerland,50,"TensorFlow, NLP, Linux",PhD,5,Technology,2024-01-20,2024-02-12,1743,9.7,Predictive Systems -AI11845,Data Engineer,69295,SGD,90084,EN,PT,Singapore,L,Singapore,100,"SQL, GCP, Computer Vision",Master,0,Retail,2024-09-16,2024-11-18,2296,8.5,TechCorp Inc -AI11846,Computer Vision Engineer,132554,EUR,112671,SE,CT,France,M,France,50,"Kubernetes, Scala, Computer Vision, Java, Docker",Associate,7,Real Estate,2024-05-10,2024-07-04,826,8.8,Quantum Computing Inc -AI11847,AI Consultant,172103,EUR,146288,EX,FL,France,S,Czech Republic,0,"R, SQL, Statistics, Azure, Computer Vision",Master,14,Manufacturing,2024-02-10,2024-03-01,1648,7.4,DeepTech Ventures -AI11848,AI Specialist,113947,GBP,85460,SE,FT,United Kingdom,M,United Kingdom,50,"Git, Deep Learning, R",Bachelor,8,Energy,2025-04-13,2025-05-21,1447,9.4,Cognitive Computing -AI11849,AI Consultant,38972,USD,38972,MI,CT,China,M,China,50,"Tableau, Hadoop, Deep Learning, Spark, GCP",Associate,2,Retail,2024-07-28,2024-08-19,2480,9.4,Future Systems -AI11850,Robotics Engineer,129198,EUR,109818,SE,PT,Austria,L,Canada,100,"SQL, Git, NLP, Python, Kubernetes",Associate,9,Healthcare,2024-11-20,2025-01-20,2336,7.3,DataVision Ltd -AI11851,Machine Learning Researcher,85968,USD,85968,EN,FL,Sweden,L,Sweden,0,"R, Azure, NLP, SQL, Data Visualization",Bachelor,1,Government,2024-03-21,2024-04-10,2330,5.2,Cognitive Computing -AI11852,AI Specialist,89602,USD,89602,EN,PT,Denmark,M,Portugal,50,"Computer Vision, Java, Python, Scala",PhD,1,Finance,2024-11-17,2025-01-06,2474,5.5,Digital Transformation LLC -AI11853,AI Software Engineer,75324,USD,75324,EN,PT,United States,S,United States,50,"GCP, Scala, Data Visualization, Spark",PhD,1,Real Estate,2025-02-06,2025-02-26,830,9.3,AI Innovations -AI11854,AI Consultant,89924,USD,89924,MI,CT,Finland,S,Finland,0,"Azure, Docker, Deep Learning",Master,3,Media,2024-11-17,2025-01-10,844,9.8,Digital Transformation LLC -AI11855,Machine Learning Engineer,65329,USD,65329,EN,PT,South Korea,M,Switzerland,100,"R, Hadoop, Spark, Mathematics, Computer Vision",Bachelor,0,Healthcare,2024-04-30,2024-05-28,547,5.2,DataVision Ltd -AI11856,AI Software Engineer,93470,AUD,126185,MI,CT,Australia,M,Australia,0,"MLOps, R, Tableau",Master,4,Media,2024-11-29,2024-12-22,1805,8.1,Digital Transformation LLC -AI11857,Research Scientist,95936,JPY,10552960,EN,PT,Japan,L,Japan,100,"Git, Python, MLOps",Master,0,Finance,2024-08-17,2024-10-26,1297,8.2,Predictive Systems -AI11858,Machine Learning Researcher,112418,SGD,146143,MI,PT,Singapore,M,Singapore,0,"Linux, R, Hadoop, Statistics, MLOps",Associate,4,Consulting,2024-08-31,2024-09-30,1676,9.9,AI Innovations -AI11859,AI Architect,210662,USD,210662,EX,CT,Sweden,S,Sweden,0,"SQL, Hadoop, TensorFlow, Spark",Bachelor,16,Gaming,2024-09-10,2024-10-07,1986,7.4,DataVision Ltd -AI11860,Machine Learning Engineer,55827,USD,55827,EN,FT,South Korea,M,South Korea,0,"SQL, Docker, MLOps, Azure",Associate,1,Real Estate,2024-07-09,2024-08-20,2250,5.2,Neural Networks Co -AI11861,Deep Learning Engineer,174827,USD,174827,SE,PT,Denmark,M,Denmark,50,"Computer Vision, SQL, Kubernetes, Mathematics",Bachelor,5,Healthcare,2024-07-18,2024-09-25,1268,5.9,Machine Intelligence Group -AI11862,Head of AI,222968,USD,222968,EX,FT,South Korea,L,Nigeria,100,"PyTorch, Hadoop, TensorFlow",PhD,17,Energy,2024-10-30,2024-12-18,1644,6,Autonomous Tech -AI11863,Data Analyst,250630,USD,250630,EX,FL,Denmark,L,Estonia,50,"Python, Docker, MLOps, Azure",Bachelor,15,Telecommunications,2024-07-29,2024-09-02,606,6.1,Cloud AI Solutions -AI11864,AI Product Manager,188795,CHF,169916,SE,FT,Switzerland,M,Switzerland,0,"R, Docker, Tableau, Azure, PyTorch",Associate,5,Technology,2025-01-24,2025-02-22,1357,7.6,AI Innovations -AI11865,Data Scientist,116184,EUR,98756,SE,FT,France,S,Italy,50,"Linux, Java, Scala, Kubernetes, MLOps",PhD,5,Automotive,2025-02-15,2025-03-26,2428,5.5,Digital Transformation LLC -AI11866,Deep Learning Engineer,85463,USD,85463,EN,FL,Israel,L,Switzerland,100,"Deep Learning, MLOps, Statistics, NLP",Associate,1,Government,2024-04-16,2024-05-04,2237,6.5,Smart Analytics -AI11867,Robotics Engineer,62097,EUR,52782,EN,PT,Netherlands,S,Netherlands,0,"Hadoop, Kubernetes, Python",Associate,1,Energy,2024-11-30,2025-02-04,1363,9.3,Cognitive Computing -AI11868,Data Scientist,77625,USD,77625,EN,FL,Israel,L,Israel,50,"AWS, Kubernetes, PyTorch, Docker",Bachelor,1,Technology,2025-01-14,2025-03-07,1422,5.7,Digital Transformation LLC -AI11869,Data Engineer,89334,JPY,9826740,MI,CT,Japan,M,Canada,100,"Linux, GCP, Statistics, AWS, Hadoop",Bachelor,2,Manufacturing,2024-09-21,2024-10-19,733,9.5,Neural Networks Co -AI11870,Deep Learning Engineer,115065,EUR,97805,SE,CT,Austria,M,Austria,0,"SQL, Git, Tableau, Linux",Master,7,Consulting,2024-02-05,2024-03-02,1057,6.6,Quantum Computing Inc -AI11871,NLP Engineer,29565,USD,29565,MI,CT,India,M,India,100,"Python, Linux, Tableau, TensorFlow",PhD,2,Manufacturing,2025-03-21,2025-05-10,2038,8.4,Neural Networks Co -AI11872,Autonomous Systems Engineer,151856,USD,151856,SE,FL,Denmark,M,Denmark,0,"PyTorch, Docker, Tableau, Spark, GCP",PhD,6,Real Estate,2024-01-03,2024-03-04,795,6.1,Algorithmic Solutions -AI11873,Principal Data Scientist,59832,USD,59832,EN,FL,Israel,L,Australia,100,"Git, TensorFlow, SQL, NLP",Associate,1,Government,2024-03-07,2024-04-25,2026,9.5,Cloud AI Solutions -AI11874,Data Scientist,100061,USD,100061,SE,FT,Finland,S,Finland,0,"Docker, Python, TensorFlow, Tableau, Kubernetes",Bachelor,7,Gaming,2024-09-16,2024-11-15,2469,8.8,Autonomous Tech -AI11875,Computer Vision Engineer,55729,EUR,47370,EN,FL,France,S,France,50,"Docker, R, GCP, SQL",PhD,0,Education,2024-02-06,2024-02-29,1845,7.7,Quantum Computing Inc -AI11876,Machine Learning Researcher,47262,EUR,40173,EN,FT,France,S,France,50,"Python, TensorFlow, MLOps, Deep Learning, Java",Master,1,Education,2025-03-20,2025-05-04,1036,9,AI Innovations -AI11877,AI Product Manager,126583,USD,126583,EX,PT,Ireland,S,Ireland,100,"Data Visualization, Linux, Java",Master,19,Automotive,2025-04-04,2025-06-11,1998,8.7,Autonomous Tech -AI11878,NLP Engineer,46601,EUR,39611,EN,PT,France,S,France,50,"Scala, Statistics, Linux, TensorFlow, MLOps",Master,0,Consulting,2024-05-26,2024-06-17,1646,7.1,AI Innovations -AI11879,AI Research Scientist,53772,GBP,40329,EN,PT,United Kingdom,S,United Kingdom,100,"Tableau, Git, Computer Vision",PhD,1,Technology,2025-03-20,2025-05-25,1581,5.1,Smart Analytics -AI11880,Data Scientist,203974,USD,203974,EX,FL,Ireland,L,Ireland,100,"Git, Python, Scala",Bachelor,17,Consulting,2024-09-04,2024-10-29,2278,7.8,AI Innovations -AI11881,AI Product Manager,23558,USD,23558,EN,FT,China,S,China,100,"Linux, Scala, Mathematics, Computer Vision",PhD,0,Gaming,2025-01-23,2025-04-01,1696,9.1,Smart Analytics -AI11882,Head of AI,195265,USD,195265,EX,FT,Finland,M,Finland,0,"Kubernetes, PyTorch, Scala, Git, AWS",Bachelor,12,Media,2025-03-21,2025-04-29,2425,9.6,Quantum Computing Inc -AI11883,AI Consultant,125170,USD,125170,MI,PT,United States,L,United States,0,"Tableau, Hadoop, PyTorch",Master,2,Energy,2025-03-05,2025-04-29,574,5.3,Autonomous Tech -AI11884,Machine Learning Researcher,154524,USD,154524,MI,PT,Norway,L,Norway,0,"Python, Scala, GCP, Computer Vision, AWS",Master,4,Gaming,2024-12-19,2025-02-23,1061,6.8,Future Systems -AI11885,Principal Data Scientist,78129,EUR,66410,MI,FT,Germany,M,Switzerland,100,"Mathematics, TensorFlow, Kubernetes",Master,4,Education,2024-12-15,2025-02-02,1911,6.1,AI Innovations -AI11886,AI Specialist,82474,USD,82474,EN,FL,Denmark,L,Denmark,100,"AWS, Linux, Tableau",Master,0,Government,2024-10-31,2024-11-29,1015,6.7,Digital Transformation LLC -AI11887,Data Analyst,60195,USD,60195,EN,CT,Ireland,S,Ireland,50,"Hadoop, NLP, Scala, Azure, Spark",Associate,0,Manufacturing,2025-03-11,2025-04-08,535,7.4,TechCorp Inc -AI11888,Computer Vision Engineer,85391,JPY,9393010,EN,FL,Japan,M,Japan,50,"Scala, Python, Mathematics, GCP",Master,0,Consulting,2025-02-05,2025-02-24,2183,8.4,DeepTech Ventures -AI11889,AI Product Manager,138187,GBP,103640,SE,PT,United Kingdom,M,United Kingdom,0,"NLP, PyTorch, SQL",Associate,7,Government,2025-04-01,2025-05-16,1041,7.6,Future Systems -AI11890,AI Research Scientist,90522,USD,90522,MI,CT,United States,S,Brazil,50,"SQL, Docker, PyTorch",PhD,4,Consulting,2025-02-18,2025-04-13,1067,8.7,TechCorp Inc -AI11891,Data Scientist,118016,EUR,100314,SE,FL,France,S,France,100,"Deep Learning, Spark, Python, Computer Vision, Linux",Bachelor,5,Media,2024-05-20,2024-06-20,2461,7.7,Quantum Computing Inc -AI11892,Principal Data Scientist,45677,USD,45677,MI,FT,China,L,China,50,"TensorFlow, Statistics, Git, MLOps",Master,2,Real Estate,2024-04-06,2024-05-06,1862,7.3,DataVision Ltd -AI11893,AI Specialist,80735,USD,80735,MI,PT,Ireland,S,Ireland,100,"Kubernetes, PyTorch, SQL, MLOps",Associate,3,Energy,2024-10-09,2024-11-16,2497,6.8,Smart Analytics -AI11894,Data Engineer,174749,EUR,148537,SE,FT,Netherlands,L,Nigeria,50,"Kubernetes, SQL, Python",Master,6,Media,2024-01-28,2024-03-02,2235,5.5,DataVision Ltd -AI11895,Autonomous Systems Engineer,153986,USD,153986,EX,FL,South Korea,S,South Korea,50,"GCP, Python, Data Visualization",Master,19,Government,2024-07-05,2024-09-07,1093,6.4,Digital Transformation LLC -AI11896,AI Consultant,239879,GBP,179909,EX,PT,United Kingdom,S,United Kingdom,100,"Java, TensorFlow, Docker, SQL, AWS",Associate,10,Gaming,2025-01-25,2025-02-15,814,7.5,Algorithmic Solutions -AI11897,AI Product Manager,113202,JPY,12452220,MI,PT,Japan,L,Japan,0,"NLP, Spark, Python, TensorFlow, Git",Bachelor,3,Government,2024-05-24,2024-06-15,618,5.6,Quantum Computing Inc -AI11898,Deep Learning Engineer,176289,USD,176289,EX,FT,Sweden,M,Sweden,0,"Data Visualization, GCP, Linux",Associate,19,Real Estate,2024-08-14,2024-10-16,1171,7.7,Quantum Computing Inc -AI11899,AI Specialist,74877,CAD,93596,EN,FL,Canada,M,Romania,100,"Hadoop, Data Visualization, AWS, Java",Master,0,Transportation,2024-04-05,2024-05-19,1958,5.7,Autonomous Tech -AI11900,Deep Learning Engineer,121054,USD,121054,SE,PT,Israel,M,South Africa,50,"GCP, AWS, Mathematics, Tableau",Bachelor,9,Manufacturing,2024-11-17,2025-01-18,2146,7.1,Predictive Systems -AI11901,Head of AI,121862,CAD,152328,SE,FL,Canada,M,Chile,0,"Git, GCP, Spark, R, AWS",Bachelor,8,Finance,2025-04-11,2025-05-05,2480,8.7,Neural Networks Co -AI11902,AI Product Manager,68676,USD,68676,MI,PT,South Korea,L,South Korea,50,"Tableau, Kubernetes, Python",PhD,3,Manufacturing,2024-04-05,2024-05-28,951,7.4,Cognitive Computing -AI11903,AI Specialist,140355,CAD,175444,SE,CT,Canada,L,Canada,100,"Spark, SQL, Computer Vision",Bachelor,7,Automotive,2024-06-20,2024-07-21,738,5.6,Neural Networks Co -AI11904,Data Scientist,107343,EUR,91242,SE,CT,Austria,S,United States,100,"Linux, R, SQL, Spark, GCP",Master,6,Retail,2025-01-17,2025-02-24,1393,5.6,Advanced Robotics -AI11905,Data Analyst,124289,USD,124289,SE,PT,Ireland,M,Ireland,100,"Statistics, Tableau, SQL, Data Visualization, Python",Master,6,Telecommunications,2024-01-19,2024-03-30,1647,7.1,Cloud AI Solutions -AI11906,Deep Learning Engineer,111588,USD,111588,MI,FL,Ireland,L,Ireland,50,"Mathematics, TensorFlow, Tableau, Computer Vision",Associate,2,Consulting,2024-04-17,2024-06-23,2381,5.5,Advanced Robotics -AI11907,NLP Engineer,140602,AUD,189813,SE,PT,Australia,M,Australia,50,"SQL, Azure, AWS",Master,7,Technology,2024-05-08,2024-07-12,583,6.9,Autonomous Tech -AI11908,Deep Learning Engineer,220576,USD,220576,SE,PT,Norway,L,Norway,0,"Deep Learning, Data Visualization, Java, GCP",Master,6,Real Estate,2024-09-12,2024-10-13,1736,5.6,Neural Networks Co -AI11909,Data Scientist,63791,USD,63791,EX,FT,India,L,India,50,"Java, Spark, GCP, Tableau, Computer Vision",PhD,16,Retail,2025-01-06,2025-02-17,1610,9.6,Predictive Systems -AI11910,Robotics Engineer,115544,EUR,98212,SE,FT,Austria,S,Italy,100,"PyTorch, TensorFlow, Computer Vision, GCP, Spark",PhD,5,Gaming,2024-11-21,2024-12-28,2140,6.8,Digital Transformation LLC -AI11911,Computer Vision Engineer,141470,USD,141470,SE,FL,Finland,L,Canada,50,"Java, Python, Kubernetes",Bachelor,7,Transportation,2024-04-17,2024-05-11,1095,5.5,Machine Intelligence Group -AI11912,Robotics Engineer,119546,USD,119546,SE,FL,Sweden,M,Switzerland,100,"Kubernetes, AWS, Computer Vision",Associate,8,Energy,2024-09-13,2024-11-23,1690,7.2,TechCorp Inc -AI11913,Robotics Engineer,70709,SGD,91922,EN,PT,Singapore,L,Singapore,0,"Spark, Linux, Scala, Docker",PhD,0,Technology,2024-05-01,2024-06-11,984,8.9,Cognitive Computing -AI11914,Autonomous Systems Engineer,139969,AUD,188958,SE,FT,Australia,M,Australia,100,"Python, Spark, TensorFlow, MLOps, AWS",Bachelor,7,Gaming,2025-03-01,2025-03-18,1633,6,Machine Intelligence Group -AI11915,Computer Vision Engineer,249239,USD,249239,EX,CT,United States,M,United States,100,"Data Visualization, AWS, TensorFlow",Bachelor,19,Healthcare,2024-11-12,2024-12-16,1154,6.6,DataVision Ltd -AI11916,Data Scientist,72005,EUR,61204,EN,FL,France,M,France,0,"PyTorch, Scala, Data Visualization, Statistics, AWS",Master,1,Real Estate,2024-05-07,2024-05-25,1077,7.7,Digital Transformation LLC -AI11917,Head of AI,82315,USD,82315,MI,FL,Finland,M,Finland,0,"Java, Computer Vision, Tableau, Python",PhD,2,Media,2025-01-19,2025-03-24,653,5.4,DataVision Ltd -AI11918,AI Product Manager,172045,USD,172045,SE,PT,Sweden,L,Sweden,100,"GCP, Linux, Deep Learning, Scala, MLOps",Associate,6,Consulting,2024-12-20,2025-02-20,1852,8.2,Quantum Computing Inc -AI11919,Data Engineer,227310,EUR,193214,EX,CT,Germany,M,Germany,100,"Data Visualization, Python, R",PhD,19,Technology,2025-02-23,2025-04-07,560,9,AI Innovations -AI11920,Head of AI,84752,GBP,63564,MI,FL,United Kingdom,M,United Kingdom,50,"Azure, Tableau, Linux",Bachelor,3,Energy,2024-04-16,2024-06-06,789,5.7,Autonomous Tech -AI11921,Principal Data Scientist,141732,USD,141732,SE,FL,Finland,L,Brazil,50,"MLOps, Scala, TensorFlow, Deep Learning, GCP",PhD,7,Transportation,2024-12-08,2025-01-04,734,9.6,Autonomous Tech -AI11922,AI Architect,169211,USD,169211,SE,PT,Denmark,S,Argentina,100,"Java, Python, MLOps, TensorFlow, Kubernetes",Bachelor,8,Transportation,2025-03-07,2025-04-21,1516,9.5,Machine Intelligence Group -AI11923,Research Scientist,247914,GBP,185936,EX,FL,United Kingdom,M,United Kingdom,50,"SQL, Python, GCP, R, Hadoop",Master,17,Automotive,2024-02-19,2024-03-13,849,7.8,TechCorp Inc -AI11924,Deep Learning Engineer,66536,CAD,83170,EN,FT,Canada,S,Malaysia,0,"PyTorch, Azure, MLOps",PhD,1,Energy,2024-05-29,2024-06-13,1642,5.4,DeepTech Ventures -AI11925,Robotics Engineer,133785,CHF,120407,MI,FL,Switzerland,M,Switzerland,50,"Spark, MLOps, GCP, Docker, Java",PhD,4,Finance,2025-02-01,2025-04-14,1364,5.8,Digital Transformation LLC -AI11926,Data Analyst,65022,GBP,48767,EN,CT,United Kingdom,L,United Kingdom,100,"Spark, GCP, SQL, NLP",Master,1,Real Estate,2025-04-21,2025-05-22,1446,6.4,Cognitive Computing -AI11927,NLP Engineer,247285,USD,247285,EX,FL,Norway,M,Norway,50,"NLP, SQL, Azure",Master,11,Government,2025-01-11,2025-03-04,767,9.8,Neural Networks Co -AI11928,NLP Engineer,51541,USD,51541,EN,FL,Finland,M,Finland,0,"Java, Kubernetes, Data Visualization, Docker",PhD,0,Manufacturing,2024-01-27,2024-02-26,1836,8.4,Digital Transformation LLC -AI11929,AI Consultant,186164,GBP,139623,SE,PT,United Kingdom,L,New Zealand,0,"Linux, Scala, Mathematics, R, Azure",Master,6,Telecommunications,2024-09-01,2024-11-09,2042,7.3,Quantum Computing Inc -AI11930,NLP Engineer,80116,USD,80116,MI,CT,Ireland,S,Ireland,0,"Python, Hadoop, GCP, TensorFlow",PhD,4,Media,2025-01-02,2025-01-21,1716,5.6,Neural Networks Co -AI11931,AI Consultant,62190,EUR,52862,EN,CT,Austria,M,Netherlands,100,"Hadoop, Git, NLP, TensorFlow",PhD,0,Gaming,2024-04-08,2024-04-25,1587,5.8,Cognitive Computing -AI11932,Principal Data Scientist,99982,USD,99982,MI,PT,Sweden,M,Italy,50,"Git, Azure, Kubernetes",Bachelor,3,Finance,2024-03-18,2024-05-28,2079,6.7,Smart Analytics -AI11933,AI Architect,126992,CAD,158740,SE,PT,Canada,L,Austria,100,"Git, Scala, Data Visualization, Python",PhD,5,Consulting,2024-11-05,2024-12-12,1638,6.9,Quantum Computing Inc -AI11934,NLP Engineer,283236,USD,283236,EX,FL,Denmark,M,Denmark,0,"Mathematics, Linux, Git",PhD,12,Real Estate,2024-10-07,2024-11-14,1479,8.2,AI Innovations -AI11935,Machine Learning Engineer,211425,CHF,190283,SE,PT,Switzerland,L,Singapore,100,"Linux, Data Visualization, Hadoop",PhD,8,Manufacturing,2024-07-10,2024-09-08,2048,7.7,Cloud AI Solutions -AI11936,Data Scientist,44730,CAD,55913,EN,PT,Canada,S,Israel,0,"Linux, GCP, R, Hadoop, SQL",Associate,0,Retail,2024-10-24,2024-12-23,1274,8.7,Digital Transformation LLC -AI11937,Data Analyst,34838,USD,34838,MI,PT,China,S,China,50,"Scala, AWS, Docker",Associate,4,Finance,2024-02-18,2024-03-21,2184,6.9,Smart Analytics -AI11938,AI Software Engineer,225196,USD,225196,EX,FL,United States,S,United States,0,"Java, R, Hadoop, Kubernetes, PyTorch",PhD,12,Transportation,2024-03-07,2024-04-13,1541,7.1,Neural Networks Co -AI11939,Head of AI,122390,USD,122390,MI,FT,United States,M,United States,0,"PyTorch, TensorFlow, Computer Vision, Docker, Mathematics",Associate,2,Media,2024-09-02,2024-10-09,1198,6.3,TechCorp Inc -AI11940,Deep Learning Engineer,134314,USD,134314,SE,FL,Finland,M,Finland,100,"AWS, SQL, PyTorch",Master,9,Government,2024-05-03,2024-05-19,2257,9.4,Machine Intelligence Group -AI11941,Autonomous Systems Engineer,63509,USD,63509,EN,PT,Israel,M,Israel,100,"Hadoop, Deep Learning, Scala, Python",Master,1,Transportation,2024-08-10,2024-09-13,1368,6.5,Algorithmic Solutions -AI11942,AI Software Engineer,179124,JPY,19703640,SE,CT,Japan,L,Japan,50,"Spark, SQL, R, Scala",Bachelor,6,Gaming,2024-10-09,2024-12-13,2235,7.7,DataVision Ltd -AI11943,AI Architect,128394,GBP,96296,MI,PT,United Kingdom,L,Poland,100,"SQL, Tableau, Mathematics, Data Visualization",PhD,3,Manufacturing,2024-12-16,2025-02-07,1582,6.4,TechCorp Inc -AI11944,Deep Learning Engineer,126623,CHF,113961,MI,FL,Switzerland,L,Brazil,0,"SQL, Scala, MLOps, R, Git",PhD,3,Energy,2024-05-23,2024-07-18,2276,6.4,Algorithmic Solutions -AI11945,AI Architect,113817,EUR,96744,SE,PT,Germany,M,Germany,50,"TensorFlow, Docker, Kubernetes",Master,8,Finance,2024-02-03,2024-02-24,1339,8,Quantum Computing Inc -AI11946,AI Architect,139320,USD,139320,EX,CT,South Korea,L,South Korea,100,"MLOps, Scala, Linux, Deep Learning, Computer Vision",Master,16,Technology,2025-04-05,2025-06-13,2440,7.6,Advanced Robotics -AI11947,AI Product Manager,123195,EUR,104716,SE,FL,Germany,S,Germany,100,"Python, MLOps, Tableau, TensorFlow, GCP",Master,6,Transportation,2024-01-02,2024-03-03,1983,8.6,Quantum Computing Inc -AI11948,AI Architect,59966,CAD,74958,EN,PT,Canada,M,Ireland,0,"Computer Vision, NLP, GCP, Linux, Azure",PhD,0,Finance,2024-01-24,2024-02-14,1953,5.8,Digital Transformation LLC -AI11949,AI Research Scientist,32241,USD,32241,EN,CT,India,L,India,100,"Kubernetes, Data Visualization, Azure",Bachelor,1,Energy,2024-12-07,2025-02-02,1441,6.2,Cognitive Computing -AI11950,Autonomous Systems Engineer,125879,CAD,157349,EX,FT,Canada,S,Canada,0,"Git, GCP, MLOps",Bachelor,13,Retail,2024-04-20,2024-05-25,1270,8.7,Quantum Computing Inc -AI11951,Head of AI,63170,USD,63170,MI,FL,Israel,S,Israel,0,"SQL, PyTorch, Azure, MLOps, Git",Bachelor,2,Media,2025-03-23,2025-04-21,1528,5.1,Digital Transformation LLC -AI11952,NLP Engineer,155126,JPY,17063860,EX,CT,Japan,M,New Zealand,50,"Python, TensorFlow, NLP",Associate,16,Real Estate,2024-09-30,2024-12-04,2446,10,Neural Networks Co -AI11953,AI Architect,86565,CAD,108206,MI,CT,Canada,M,Canada,100,"SQL, Python, Spark, Scala",Bachelor,2,Manufacturing,2024-03-29,2024-05-19,1589,6.7,Quantum Computing Inc -AI11954,Principal Data Scientist,103951,EUR,88358,MI,CT,Germany,L,Germany,100,"TensorFlow, Data Visualization, Python, Mathematics, Kubernetes",PhD,4,Retail,2024-04-23,2024-05-07,955,9.4,Algorithmic Solutions -AI11955,Data Engineer,121572,USD,121572,SE,FL,Ireland,L,Ireland,100,"Linux, TensorFlow, Docker",Associate,8,Real Estate,2024-07-01,2024-08-10,1827,8.3,TechCorp Inc -AI11956,Deep Learning Engineer,80289,USD,80289,EN,CT,Denmark,M,Denmark,50,"R, Azure, AWS",Associate,0,Transportation,2024-11-04,2025-01-06,1019,9.5,Smart Analytics -AI11957,Head of AI,142312,USD,142312,SE,FL,United States,L,United States,100,"NLP, Hadoop, Scala, Tableau",Bachelor,9,Media,2024-08-18,2024-10-13,1326,7.4,Future Systems -AI11958,ML Ops Engineer,45228,USD,45228,MI,PT,China,L,China,100,"Deep Learning, Kubernetes, Spark, NLP",Associate,3,Government,2025-01-01,2025-03-10,994,5.3,Algorithmic Solutions -AI11959,AI Architect,105421,SGD,137047,MI,FL,Singapore,M,Singapore,50,"NLP, TensorFlow, Tableau",Associate,3,Transportation,2025-03-20,2025-04-19,1425,7,Cognitive Computing -AI11960,Autonomous Systems Engineer,253979,CHF,228581,EX,FL,Switzerland,M,Thailand,100,"Hadoop, Scala, PyTorch, AWS, Data Visualization",Associate,11,Government,2025-04-18,2025-05-21,1367,7.3,Neural Networks Co -AI11961,Autonomous Systems Engineer,80682,EUR,68580,MI,PT,Netherlands,S,Chile,50,"NLP, Git, Spark, AWS, Hadoop",Bachelor,4,Education,2025-04-09,2025-05-09,1274,6.8,Machine Intelligence Group -AI11962,Machine Learning Engineer,58564,USD,58564,SE,PT,China,L,China,0,"Java, GCP, Deep Learning",Master,5,Energy,2024-08-17,2024-09-08,1669,7.7,Future Systems -AI11963,ML Ops Engineer,165885,EUR,141002,EX,FL,France,M,France,0,"Python, Deep Learning, Data Visualization",PhD,19,Media,2024-08-07,2024-09-19,783,10,Digital Transformation LLC -AI11964,Data Engineer,190838,USD,190838,SE,PT,Denmark,M,Austria,100,"Deep Learning, AWS, Statistics",Bachelor,6,Telecommunications,2024-02-14,2024-04-06,2414,9.6,Predictive Systems -AI11965,AI Specialist,55369,USD,55369,EX,FL,India,M,India,0,"Docker, GCP, Data Visualization, Mathematics, Tableau",Associate,17,Automotive,2024-01-09,2024-02-27,1164,10,AI Innovations -AI11966,Data Scientist,71105,EUR,60439,EN,FL,Netherlands,L,Netherlands,0,"Spark, PyTorch, Mathematics",Master,0,Telecommunications,2024-03-25,2024-05-30,1018,7.5,Quantum Computing Inc -AI11967,Deep Learning Engineer,75264,USD,75264,EN,FL,Sweden,M,Sweden,0,"GCP, Tableau, Python, Data Visualization, TensorFlow",Associate,0,Retail,2024-07-03,2024-07-22,1393,6.1,Smart Analytics -AI11968,Autonomous Systems Engineer,164799,USD,164799,SE,FT,Norway,M,Norway,100,"Hadoop, Kubernetes, Python, R, SQL",Master,9,Gaming,2024-05-10,2024-06-23,518,6.2,Neural Networks Co -AI11969,Machine Learning Engineer,76924,EUR,65385,MI,FT,Austria,M,Portugal,50,"Spark, Azure, Kubernetes",PhD,3,Telecommunications,2024-11-09,2024-12-18,913,6.5,Cognitive Computing -AI11970,Principal Data Scientist,43350,USD,43350,MI,PT,India,L,Ireland,50,"Git, Azure, Hadoop",Associate,3,Healthcare,2025-04-15,2025-06-19,1003,9.3,Predictive Systems -AI11971,AI Product Manager,61506,EUR,52280,EN,FL,Austria,S,Austria,0,"Kubernetes, Hadoop, PyTorch, Git, Data Visualization",Associate,0,Education,2025-03-18,2025-05-22,1927,6.3,Cognitive Computing -AI11972,AI Architect,102342,AUD,138162,MI,PT,Australia,M,Australia,100,"Python, SQL, Hadoop",PhD,4,Consulting,2024-04-13,2024-05-08,1056,9.6,Digital Transformation LLC -AI11973,AI Product Manager,167315,CHF,150584,SE,CT,Switzerland,L,Switzerland,50,"Scala, Computer Vision, SQL, GCP, MLOps",PhD,8,Transportation,2024-12-07,2025-01-08,1876,6.2,Quantum Computing Inc -AI11974,AI Consultant,128451,EUR,109183,EX,PT,France,M,France,0,"Spark, Python, Statistics, Java, TensorFlow",Master,19,Real Estate,2024-08-06,2024-09-04,2292,9.4,Autonomous Tech -AI11975,Robotics Engineer,71957,GBP,53968,EN,FT,United Kingdom,S,United Kingdom,0,"Scala, GCP, Computer Vision, Docker",Master,0,Healthcare,2024-04-15,2024-05-17,529,6.3,DataVision Ltd -AI11976,ML Ops Engineer,117836,AUD,159079,SE,PT,Australia,L,Argentina,50,"Python, PyTorch, Git, Computer Vision, Statistics",PhD,6,Education,2024-06-29,2024-07-16,2090,5.9,Algorithmic Solutions -AI11977,Data Engineer,121319,SGD,157715,MI,PT,Singapore,L,New Zealand,50,"GCP, Git, Mathematics, Computer Vision, TensorFlow",Bachelor,4,Real Estate,2024-05-16,2024-07-28,1785,8.7,TechCorp Inc -AI11978,Machine Learning Researcher,118151,EUR,100428,EX,FL,France,S,France,100,"TensorFlow, SQL, MLOps",Associate,13,Retail,2025-04-12,2025-06-22,1142,6.1,Cognitive Computing -AI11979,AI Software Engineer,82974,GBP,62231,MI,FL,United Kingdom,S,United Kingdom,0,"Linux, AWS, Deep Learning, Scala",Bachelor,3,Telecommunications,2024-01-09,2024-02-03,662,7.9,Future Systems -AI11980,Data Analyst,91372,USD,91372,EN,FT,Ireland,L,Ireland,50,"Python, TensorFlow, PyTorch",Bachelor,0,Consulting,2024-10-03,2024-10-26,2231,9.5,Predictive Systems -AI11981,AI Product Manager,33654,USD,33654,EN,FL,China,M,China,0,"Spark, SQL, Linux, Hadoop",Associate,0,Healthcare,2025-03-07,2025-05-19,1924,5.9,Neural Networks Co -AI11982,Head of AI,156264,EUR,132824,SE,FL,France,L,South Africa,50,"Kubernetes, SQL, PyTorch, Data Visualization, Computer Vision",PhD,8,Education,2024-11-24,2025-01-21,1009,7.4,Cognitive Computing -AI11983,Data Analyst,84928,CAD,106160,MI,FL,Canada,M,Canada,50,"PyTorch, Spark, Data Visualization, SQL, Docker",Master,4,Technology,2024-11-12,2024-12-15,574,9.6,DataVision Ltd -AI11984,Research Scientist,129254,CAD,161568,SE,PT,Canada,M,Canada,0,"Python, Azure, Statistics, Java, Computer Vision",Master,9,Consulting,2024-12-28,2025-02-11,2081,9.1,Autonomous Tech -AI11985,AI Consultant,206297,USD,206297,EX,CT,Finland,M,Finland,50,"AWS, Spark, Mathematics, Hadoop, GCP",Master,10,Real Estate,2024-06-25,2024-08-25,2117,6.1,Algorithmic Solutions -AI11986,Data Analyst,105092,EUR,89328,MI,CT,Austria,L,Austria,0,"Linux, TensorFlow, Scala, Azure",Master,3,Government,2024-04-25,2024-05-27,2118,6.5,DataVision Ltd -AI11987,Deep Learning Engineer,216314,USD,216314,EX,PT,Denmark,L,Denmark,0,"TensorFlow, Scala, GCP, R, Tableau",PhD,19,Media,2025-03-05,2025-04-18,2302,8.6,Quantum Computing Inc -AI11988,AI Software Engineer,114139,EUR,97018,SE,FT,France,S,France,0,"Java, NLP, Git, Statistics",Master,6,Gaming,2024-11-06,2025-01-18,2402,8.2,DataVision Ltd -AI11989,Autonomous Systems Engineer,253207,GBP,189905,EX,FT,United Kingdom,L,United Kingdom,0,"R, Mathematics, SQL, Java",Bachelor,12,Manufacturing,2024-11-08,2024-12-27,534,9.6,Cloud AI Solutions -AI11990,Data Engineer,117195,CHF,105476,MI,CT,Switzerland,M,Switzerland,50,"Tableau, Docker, NLP, PyTorch",PhD,4,Technology,2024-03-28,2024-04-27,998,5.9,Quantum Computing Inc -AI11991,AI Research Scientist,75215,USD,75215,EN,FT,United States,S,United States,100,"TensorFlow, GCP, Java, Scala, Python",Master,1,Energy,2025-03-13,2025-03-30,2257,8.4,AI Innovations -AI11992,Data Scientist,91308,USD,91308,MI,CT,Ireland,S,Ireland,100,"Azure, Linux, Scala",PhD,2,Telecommunications,2024-05-29,2024-07-03,1125,9.7,Cloud AI Solutions -AI11993,NLP Engineer,101994,USD,101994,MI,FT,United States,L,United States,50,"Python, R, PyTorch, Deep Learning",Master,3,Healthcare,2025-03-09,2025-04-03,1316,7.3,Digital Transformation LLC -AI11994,AI Consultant,63814,SGD,82958,EN,FT,Singapore,M,Singapore,0,"Java, AWS, PyTorch",PhD,1,Gaming,2024-12-23,2025-02-07,1775,5.5,Predictive Systems -AI11995,AI Software Engineer,82096,CHF,73886,EN,FL,Switzerland,M,Switzerland,50,"SQL, Tableau, TensorFlow, Docker",PhD,1,Manufacturing,2024-01-26,2024-03-03,2046,7.2,Future Systems -AI11996,Data Analyst,139446,USD,139446,SE,FL,United States,L,United States,0,"Python, Data Visualization, Kubernetes",Associate,8,Consulting,2025-04-27,2025-05-31,1178,5.2,Cognitive Computing -AI11997,AI Consultant,50489,CAD,63111,EN,PT,Canada,S,Canada,0,"Mathematics, SQL, AWS, Deep Learning",Master,1,Healthcare,2024-07-07,2024-08-30,1144,8.2,Autonomous Tech -AI11998,AI Architect,202463,EUR,172094,EX,CT,France,L,France,50,"R, Statistics, Tableau",Associate,18,Retail,2024-05-07,2024-06-08,2361,5.1,TechCorp Inc -AI11999,AI Consultant,257007,USD,257007,EX,FL,Israel,L,Israel,0,"SQL, Git, Spark",Associate,16,Healthcare,2025-03-29,2025-06-02,2113,8.4,Future Systems -AI12000,Data Analyst,165859,JPY,18244490,SE,FL,Japan,L,Japan,50,"Kubernetes, Mathematics, MLOps",PhD,5,Education,2024-11-04,2025-01-12,1168,5.2,Quantum Computing Inc -AI12001,NLP Engineer,269890,USD,269890,EX,FL,Norway,S,Norway,0,"PyTorch, Python, Git, Kubernetes",Associate,19,Technology,2024-03-09,2024-03-25,1218,5.8,Algorithmic Solutions -AI12002,AI Product Manager,249468,EUR,212048,EX,FL,Netherlands,M,Netherlands,100,"Azure, Tableau, Statistics",PhD,16,Telecommunications,2024-06-14,2024-07-15,534,5,Cognitive Computing -AI12003,Robotics Engineer,146512,SGD,190466,SE,FT,Singapore,M,Singapore,100,"Python, Deep Learning, Computer Vision, Scala",Master,7,Manufacturing,2024-12-29,2025-01-27,728,5.8,Smart Analytics -AI12004,Robotics Engineer,74373,EUR,63217,MI,CT,Austria,S,Austria,0,"NLP, Docker, PyTorch, Azure, Mathematics",Master,4,Gaming,2024-11-09,2025-01-16,1187,8.1,Cognitive Computing -AI12005,AI Consultant,191280,USD,191280,EX,CT,Israel,M,Ukraine,100,"SQL, R, MLOps, Docker",Associate,18,Gaming,2024-03-28,2024-05-16,789,5.7,Algorithmic Solutions -AI12006,Machine Learning Engineer,122748,EUR,104336,SE,CT,Germany,M,Germany,100,"Java, R, NLP, Computer Vision, Azure",Bachelor,8,Healthcare,2024-11-22,2025-02-03,1419,5.3,Autonomous Tech -AI12007,Deep Learning Engineer,40909,USD,40909,SE,PT,India,M,India,50,"NLP, Hadoop, MLOps",Associate,7,Government,2024-08-07,2024-09-08,2498,9.3,TechCorp Inc -AI12008,Principal Data Scientist,51031,USD,51031,EX,CT,India,M,India,0,"Kubernetes, Docker, Azure",PhD,12,Telecommunications,2025-01-21,2025-02-12,1890,10,Advanced Robotics -AI12009,Deep Learning Engineer,111269,CHF,100142,MI,PT,Switzerland,M,Switzerland,0,"Java, TensorFlow, Linux",Associate,4,Automotive,2024-09-13,2024-10-07,1949,6.5,Machine Intelligence Group -AI12010,AI Architect,68234,EUR,57999,EN,FT,Austria,L,Switzerland,100,"Scala, Python, Docker, SQL, Statistics",Associate,1,Transportation,2024-12-05,2025-02-01,2202,5.9,Cognitive Computing -AI12011,Deep Learning Engineer,138852,USD,138852,MI,FT,Denmark,L,Romania,50,"Deep Learning, Python, Scala, GCP, SQL",Bachelor,2,Retail,2024-03-29,2024-05-12,2392,8.3,TechCorp Inc -AI12012,AI Research Scientist,112322,USD,112322,SE,PT,Israel,M,Israel,0,"Java, Git, Mathematics, Statistics",Bachelor,8,Government,2024-03-31,2024-04-21,1766,5.1,Autonomous Tech -AI12013,AI Consultant,172547,AUD,232938,EX,PT,Australia,L,Australia,0,"Python, PyTorch, Mathematics, Java, Tableau",Bachelor,19,Energy,2025-01-13,2025-02-03,1606,5.6,TechCorp Inc -AI12014,Machine Learning Engineer,210775,CHF,189698,SE,CT,Switzerland,M,Switzerland,50,"Docker, R, Computer Vision, Hadoop, MLOps",Associate,7,Education,2025-02-25,2025-03-24,891,6.1,Cognitive Computing -AI12015,ML Ops Engineer,42437,USD,42437,SE,CT,India,M,India,0,"Hadoop, R, Statistics, Git, Docker",Master,5,Education,2025-02-20,2025-03-15,1846,7.9,Predictive Systems -AI12016,Research Scientist,75457,USD,75457,MI,FT,South Korea,M,South Korea,0,"Docker, Tableau, Computer Vision, Java, Hadoop",Master,2,Technology,2024-01-16,2024-03-09,510,5.1,Cognitive Computing -AI12017,AI Architect,81055,AUD,109424,MI,FT,Australia,S,Israel,0,"Data Visualization, TensorFlow, Tableau",Associate,3,Manufacturing,2025-03-19,2025-04-30,1842,8.3,Autonomous Tech -AI12018,Data Analyst,158028,GBP,118521,EX,CT,United Kingdom,S,United Kingdom,100,"Python, TensorFlow, Mathematics, Hadoop, MLOps",Associate,13,Telecommunications,2024-11-20,2025-01-02,2151,6.6,Quantum Computing Inc -AI12019,Computer Vision Engineer,85667,EUR,72817,MI,FT,Austria,L,Austria,100,"Scala, Mathematics, MLOps, Java",Associate,3,Automotive,2025-03-06,2025-04-14,1455,7.1,Neural Networks Co -AI12020,AI Consultant,92565,USD,92565,MI,FL,South Korea,L,South Korea,100,"Mathematics, AWS, MLOps, R, Java",Bachelor,2,Media,2024-02-15,2024-04-03,2106,7.6,Cloud AI Solutions -AI12021,Data Scientist,218585,USD,218585,EX,FL,United States,S,United States,0,"Azure, SQL, Linux",Master,19,Technology,2025-02-21,2025-04-29,1692,7.1,Smart Analytics -AI12022,Machine Learning Engineer,135669,CHF,122102,MI,FT,Switzerland,S,Switzerland,100,"Kubernetes, SQL, Computer Vision, PyTorch",Bachelor,4,Transportation,2024-06-19,2024-07-10,1965,5.8,Autonomous Tech -AI12023,Machine Learning Engineer,161267,SGD,209647,SE,FT,Singapore,M,Canada,50,"Scala, Python, Docker, Kubernetes, Tableau",Associate,5,Consulting,2024-08-07,2024-09-11,1851,5.4,Digital Transformation LLC -AI12024,Machine Learning Researcher,161659,EUR,137410,EX,PT,Austria,L,Austria,100,"Python, AWS, Azure, Deep Learning, R",Associate,12,Finance,2024-01-06,2024-02-24,730,5.1,Digital Transformation LLC -AI12025,ML Ops Engineer,84538,GBP,63404,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Java, Tableau, Statistics",Bachelor,0,Media,2024-02-18,2024-03-04,1481,8.2,Cloud AI Solutions -AI12026,AI Consultant,123396,EUR,104887,SE,CT,Germany,S,Poland,100,"Git, SQL, Kubernetes",Master,7,Finance,2025-03-17,2025-05-03,1628,9.6,Cognitive Computing -AI12027,NLP Engineer,94740,USD,94740,SE,FT,Sweden,S,Sweden,50,"SQL, NLP, Azure, Mathematics, Python",Bachelor,7,Automotive,2024-09-21,2024-11-21,1527,9.1,DataVision Ltd -AI12028,Machine Learning Engineer,237856,USD,237856,EX,PT,Denmark,M,Denmark,100,"Scala, NLP, Java, Data Visualization",Master,11,Technology,2024-10-29,2024-12-31,1067,9.5,Digital Transformation LLC -AI12029,Computer Vision Engineer,144410,USD,144410,EX,PT,South Korea,L,South Korea,100,"Data Visualization, Python, Tableau, Docker, Deep Learning",PhD,11,Technology,2024-08-16,2024-10-08,1659,7.5,TechCorp Inc -AI12030,Autonomous Systems Engineer,62979,EUR,53532,EN,FL,Netherlands,S,Latvia,50,"R, Deep Learning, Tableau",Bachelor,0,Gaming,2024-12-04,2024-12-27,1609,6.9,Smart Analytics -AI12031,AI Consultant,134825,CHF,121343,MI,FL,Switzerland,L,Argentina,50,"PyTorch, Computer Vision, TensorFlow",Master,4,Gaming,2024-01-15,2024-03-22,853,7.2,Machine Intelligence Group -AI12032,Deep Learning Engineer,115226,USD,115226,MI,PT,Ireland,L,Ireland,50,"Docker, Tableau, Statistics, GCP, Deep Learning",Master,4,Media,2024-02-19,2024-03-12,1816,5.4,Smart Analytics -AI12033,AI Consultant,128090,JPY,14089900,MI,FL,Japan,L,Japan,100,"Statistics, Spark, PyTorch, Data Visualization",Master,3,Education,2024-10-11,2024-12-12,2013,5.1,TechCorp Inc -AI12034,Machine Learning Engineer,148729,USD,148729,EX,FT,Sweden,S,Sweden,100,"Data Visualization, Git, PyTorch, Hadoop",Master,11,Media,2024-02-10,2024-03-19,1419,5.6,Smart Analytics -AI12035,AI Research Scientist,42922,USD,42922,MI,FL,China,L,China,100,"Computer Vision, Tableau, GCP, Spark, PyTorch",Bachelor,3,Telecommunications,2024-01-25,2024-03-15,582,6,Algorithmic Solutions -AI12036,Robotics Engineer,97362,USD,97362,EN,CT,Norway,L,Norway,100,"Computer Vision, Data Visualization, MLOps, Tableau, NLP",Associate,0,Healthcare,2024-09-09,2024-09-29,1851,9.7,DeepTech Ventures -AI12037,Machine Learning Researcher,59118,USD,59118,SE,CT,China,M,China,0,"Hadoop, Linux, SQL",Bachelor,7,Consulting,2024-07-02,2024-08-19,871,7.8,Advanced Robotics -AI12038,Computer Vision Engineer,73489,CAD,91861,EN,PT,Canada,M,Israel,50,"AWS, Azure, SQL, PyTorch, NLP",PhD,0,Gaming,2024-01-07,2024-02-24,2056,5.3,Smart Analytics -AI12039,Deep Learning Engineer,111684,CAD,139605,SE,PT,Canada,L,Brazil,50,"Linux, Hadoop, Data Visualization, Kubernetes",PhD,7,Automotive,2024-04-02,2024-05-09,957,7.3,Cloud AI Solutions -AI12040,AI Research Scientist,64479,EUR,54807,EN,FT,France,S,Switzerland,100,"PyTorch, NLP, Deep Learning",PhD,0,Energy,2025-02-25,2025-04-11,1960,5.1,Predictive Systems -AI12041,AI Specialist,175295,USD,175295,SE,CT,United States,M,United States,0,"Hadoop, Tableau, Linux, Scala, Python",Master,8,Technology,2024-09-16,2024-11-24,2420,5.5,Neural Networks Co -AI12042,Deep Learning Engineer,29310,USD,29310,EN,FL,China,L,China,100,"Java, R, NLP, GCP, Tableau",Associate,0,Real Estate,2024-08-06,2024-10-11,1524,7.3,DataVision Ltd -AI12043,Data Engineer,109138,EUR,92767,MI,FL,Germany,M,Canada,50,"Data Visualization, TensorFlow, PyTorch",Bachelor,3,Technology,2024-07-28,2024-09-08,1065,6.9,Future Systems -AI12044,AI Software Engineer,74590,USD,74590,EX,FT,India,L,India,0,"GCP, Java, Linux",Master,11,Manufacturing,2024-10-05,2024-12-16,1788,8.5,Neural Networks Co -AI12045,AI Consultant,137100,USD,137100,MI,CT,United States,L,Egypt,100,"Tableau, Java, Mathematics, SQL, R",Associate,3,Media,2024-05-21,2024-07-26,1922,7.8,Advanced Robotics -AI12046,AI Research Scientist,169631,USD,169631,EX,FL,Ireland,L,Ireland,50,"SQL, Git, Mathematics, AWS",Master,15,Manufacturing,2024-05-25,2024-07-31,2372,5.4,Digital Transformation LLC -AI12047,Machine Learning Engineer,182100,USD,182100,SE,PT,Norway,L,Norway,0,"TensorFlow, SQL, Java, Computer Vision, Git",Master,6,Retail,2025-03-10,2025-04-11,1534,6.7,Neural Networks Co -AI12048,Robotics Engineer,30598,USD,30598,EN,FT,India,L,India,50,"Data Visualization, Kubernetes, Scala",Associate,0,Consulting,2025-04-20,2025-05-24,707,5.7,Smart Analytics -AI12049,AI Research Scientist,59506,EUR,50580,EN,CT,France,S,France,50,"Computer Vision, NLP, Git, Kubernetes",Bachelor,0,Healthcare,2025-02-24,2025-05-06,2354,5.9,Machine Intelligence Group -AI12050,AI Consultant,176984,CAD,221230,EX,FT,Canada,S,Belgium,50,"Computer Vision, Java, Spark, Statistics, Deep Learning",Bachelor,19,Transportation,2025-04-06,2025-05-11,753,5.1,Machine Intelligence Group -AI12051,Head of AI,76635,USD,76635,MI,FL,Finland,M,Argentina,0,"PyTorch, Python, MLOps",PhD,3,Transportation,2024-10-21,2024-11-09,2223,5.7,Cognitive Computing -AI12052,ML Ops Engineer,142757,USD,142757,SE,CT,Israel,M,Israel,0,"Tableau, NLP, Mathematics",PhD,6,Gaming,2024-10-27,2024-11-28,2278,9.3,Cloud AI Solutions -AI12053,Machine Learning Engineer,157767,AUD,212985,SE,FL,Australia,L,Australia,100,"NLP, Linux, Mathematics",Associate,5,Transportation,2025-01-19,2025-03-14,1357,10,Smart Analytics -AI12054,Data Scientist,155133,JPY,17064630,SE,FL,Japan,M,Japan,50,"MLOps, AWS, R",Associate,8,Education,2024-04-22,2024-05-14,679,8.7,Machine Intelligence Group -AI12055,AI Consultant,103814,USD,103814,MI,FL,Finland,M,Indonesia,50,"Mathematics, AWS, Linux",Associate,3,Finance,2024-02-21,2024-05-04,619,7.6,Smart Analytics -AI12056,NLP Engineer,126742,CHF,114068,MI,PT,Switzerland,M,Switzerland,0,"AWS, Kubernetes, Tableau",Associate,3,Real Estate,2024-09-05,2024-10-20,1227,7.1,Advanced Robotics -AI12057,Machine Learning Engineer,149642,SGD,194535,EX,PT,Singapore,S,Singapore,0,"Python, NLP, SQL, AWS, TensorFlow",Associate,14,Telecommunications,2024-04-11,2024-06-04,599,5.6,Quantum Computing Inc -AI12058,Machine Learning Engineer,119639,GBP,89729,SE,PT,United Kingdom,S,United Kingdom,50,"Tableau, Python, Data Visualization",Bachelor,9,Retail,2025-01-06,2025-02-27,1845,5.5,Quantum Computing Inc -AI12059,AI Architect,94779,CAD,118474,SE,FT,Canada,S,Canada,100,"Scala, Java, Docker, Kubernetes, Data Visualization",Master,7,Media,2024-05-15,2024-07-19,2195,7.1,Advanced Robotics -AI12060,Data Scientist,289132,USD,289132,EX,FT,Norway,S,Norway,100,"TensorFlow, R, NLP",Associate,12,Automotive,2025-01-12,2025-02-15,1149,7.1,Cloud AI Solutions -AI12061,NLP Engineer,81914,EUR,69627,EN,CT,Germany,L,Germany,0,"Linux, Git, SQL",Master,1,Government,2024-08-06,2024-10-05,2272,6.8,DataVision Ltd -AI12062,Autonomous Systems Engineer,143423,EUR,121910,SE,FT,Austria,L,Austria,100,"Python, Java, Deep Learning",Associate,5,Healthcare,2024-03-01,2024-04-12,2001,7.8,Predictive Systems -AI12063,Autonomous Systems Engineer,67712,EUR,57555,EN,CT,Austria,S,Austria,0,"Scala, Linux, Python, AWS, Docker",Bachelor,0,Government,2025-01-18,2025-03-03,2191,5.6,Autonomous Tech -AI12064,Robotics Engineer,119637,GBP,89728,SE,FT,United Kingdom,S,Spain,50,"Python, AWS, Data Visualization",PhD,9,Education,2024-04-23,2024-06-03,787,5.7,Digital Transformation LLC -AI12065,Computer Vision Engineer,95673,EUR,81322,MI,FL,Netherlands,L,South Korea,0,"Tableau, TensorFlow, Python, Linux",PhD,3,Finance,2024-08-30,2024-10-22,1692,6.9,Predictive Systems -AI12066,ML Ops Engineer,206540,EUR,175559,EX,FT,Germany,M,Germany,50,"R, Mathematics, TensorFlow",PhD,11,Media,2025-02-23,2025-04-21,1614,9.8,TechCorp Inc -AI12067,ML Ops Engineer,251443,USD,251443,EX,FT,United States,S,United States,0,"Python, Scala, Docker, Deep Learning, NLP",Associate,10,Automotive,2024-03-08,2024-04-10,620,7.3,DataVision Ltd -AI12068,Data Engineer,116790,CAD,145988,SE,CT,Canada,M,Canada,100,"Java, PyTorch, TensorFlow, Computer Vision, R",Associate,7,Education,2025-01-18,2025-03-12,1376,5.8,Algorithmic Solutions -AI12069,Computer Vision Engineer,113165,EUR,96190,SE,FT,Germany,S,Portugal,0,"Docker, Python, NLP, Computer Vision",Master,6,Consulting,2024-09-18,2024-11-17,1378,5.3,Digital Transformation LLC -AI12070,AI Research Scientist,117256,CHF,105530,MI,PT,Switzerland,S,Switzerland,100,"AWS, Scala, Computer Vision",PhD,3,Healthcare,2024-06-12,2024-07-14,1082,8.6,Algorithmic Solutions -AI12071,AI Specialist,300778,USD,300778,EX,PT,Norway,M,Norway,0,"Java, Python, GCP, Spark, TensorFlow",Bachelor,12,Technology,2025-02-04,2025-04-13,867,7.6,Predictive Systems -AI12072,Robotics Engineer,141137,SGD,183478,SE,CT,Singapore,L,Singapore,100,"Git, Linux, GCP, Spark",Associate,6,Finance,2024-02-12,2024-03-12,975,6.3,Advanced Robotics -AI12073,Robotics Engineer,46660,USD,46660,MI,CT,China,S,China,0,"AWS, Kubernetes, Docker",Bachelor,4,Consulting,2024-06-19,2024-08-01,2391,8.2,Autonomous Tech -AI12074,Principal Data Scientist,167557,USD,167557,EX,PT,Israel,L,Israel,0,"Azure, SQL, Data Visualization, Deep Learning",Associate,10,Consulting,2024-06-19,2024-08-16,820,5,Digital Transformation LLC -AI12075,Data Engineer,152794,USD,152794,SE,PT,United States,L,United States,100,"Scala, GCP, Docker",Associate,9,Automotive,2024-05-24,2024-06-07,1160,7.9,Neural Networks Co -AI12076,AI Consultant,96217,USD,96217,EX,FL,China,L,Romania,100,"R, SQL, Linux, Docker",Master,18,Healthcare,2024-12-25,2025-02-03,1390,8.2,Digital Transformation LLC -AI12077,AI Architect,93192,CHF,83873,EN,CT,Switzerland,L,Switzerland,50,"Azure, Python, MLOps, Scala, R",Master,0,Education,2024-03-12,2024-04-16,2202,6.2,Autonomous Tech -AI12078,Robotics Engineer,104902,USD,104902,MI,FL,Ireland,L,Ireland,0,"Azure, NLP, Spark, AWS",Master,4,Real Estate,2024-01-09,2024-03-22,1676,9.4,Future Systems -AI12079,AI Software Engineer,77869,USD,77869,MI,PT,South Korea,S,South Korea,100,"GCP, Kubernetes, Tableau, Mathematics, SQL",Associate,4,Finance,2024-05-23,2024-06-22,2322,9.6,DataVision Ltd -AI12080,AI Software Engineer,61860,USD,61860,SE,FT,China,M,China,100,"Kubernetes, Python, Computer Vision, TensorFlow, Linux",Master,6,Transportation,2024-10-05,2024-11-14,2429,6.5,Predictive Systems -AI12081,ML Ops Engineer,149417,USD,149417,SE,FT,Ireland,L,Ireland,0,"Docker, Azure, Linux, GCP, Java",PhD,9,Government,2024-11-12,2024-12-01,1510,7.5,Smart Analytics -AI12082,Head of AI,46702,USD,46702,MI,PT,China,M,China,100,"Kubernetes, R, SQL",Bachelor,2,Media,2024-11-09,2024-12-11,850,9.8,Quantum Computing Inc -AI12083,Data Scientist,65493,USD,65493,EN,PT,Ireland,L,Ireland,50,"Data Visualization, Linux, Mathematics, Python, Computer Vision",Associate,0,Finance,2024-09-02,2024-10-04,1196,9.4,DeepTech Ventures -AI12084,Head of AI,84582,JPY,9304020,MI,FL,Japan,M,Japan,100,"Scala, Spark, TensorFlow, AWS",Associate,4,Government,2024-07-14,2024-08-05,922,9.1,Smart Analytics -AI12085,AI Software Engineer,168343,JPY,18517730,SE,FT,Japan,L,Japan,0,"Git, Scala, Statistics, Mathematics",Associate,7,Education,2024-02-01,2024-04-04,1613,5.8,DataVision Ltd -AI12086,Machine Learning Researcher,122314,USD,122314,EX,FT,South Korea,S,Portugal,50,"R, Java, AWS, Deep Learning",PhD,10,Manufacturing,2025-04-18,2025-06-13,1322,7.9,DeepTech Ventures -AI12087,Autonomous Systems Engineer,177998,USD,177998,SE,CT,United States,L,United States,50,"Deep Learning, Mathematics, NLP",PhD,9,Energy,2024-12-30,2025-03-07,1399,5.9,Digital Transformation LLC -AI12088,Data Analyst,53354,USD,53354,EN,PT,South Korea,S,South Korea,100,"TensorFlow, Python, MLOps",Associate,0,Real Estate,2024-05-15,2024-07-05,1721,7.6,Digital Transformation LLC -AI12089,Head of AI,160257,USD,160257,MI,CT,Norway,L,Italy,100,"PyTorch, AWS, Mathematics, Docker",Master,4,Retail,2024-02-05,2024-03-04,2077,6.3,Future Systems -AI12090,Robotics Engineer,47255,USD,47255,EN,CT,South Korea,S,Poland,100,"R, Docker, Statistics, GCP, Git",Bachelor,1,Media,2024-12-07,2025-02-05,1532,7.3,Advanced Robotics -AI12091,AI Research Scientist,244976,SGD,318469,EX,CT,Singapore,M,Singapore,100,"Java, AWS, MLOps, Computer Vision",Associate,15,Gaming,2024-01-12,2024-02-17,730,6.1,TechCorp Inc -AI12092,Principal Data Scientist,18580,USD,18580,EN,FL,India,S,India,50,"Spark, NLP, Statistics, Linux, Python",Master,0,Real Estate,2025-02-24,2025-03-10,1215,9.6,Digital Transformation LLC -AI12093,Robotics Engineer,92541,GBP,69406,EN,FT,United Kingdom,L,Spain,50,"NLP, GCP, MLOps",Bachelor,1,Finance,2024-09-11,2024-10-10,1775,7.6,Predictive Systems -AI12094,AI Software Engineer,136851,USD,136851,SE,FT,United States,S,United States,100,"R, GCP, Scala",Bachelor,5,Finance,2024-07-29,2024-09-06,1209,5.3,Machine Intelligence Group -AI12095,AI Specialist,74577,GBP,55933,EN,FL,United Kingdom,L,Russia,0,"Git, Spark, Computer Vision, Hadoop, AWS",PhD,1,Education,2025-02-16,2025-03-16,1122,8,Machine Intelligence Group -AI12096,Data Engineer,130249,SGD,169324,MI,PT,Singapore,L,Hungary,0,"Mathematics, Statistics, Tableau, Spark",PhD,3,Consulting,2024-12-27,2025-02-11,1095,9.4,Autonomous Tech -AI12097,Machine Learning Researcher,279715,USD,279715,EX,FL,Denmark,S,Singapore,50,"Docker, SQL, Hadoop, AWS",Master,10,Telecommunications,2024-01-12,2024-01-28,2016,9.8,Digital Transformation LLC -AI12098,Data Analyst,25917,USD,25917,MI,CT,India,S,India,0,"SQL, GCP, MLOps",Associate,2,Retail,2024-05-29,2024-06-28,2476,5.5,Cognitive Computing -AI12099,Deep Learning Engineer,192954,EUR,164011,EX,CT,Netherlands,S,Netherlands,50,"AWS, Kubernetes, Scala",Bachelor,10,Retail,2024-06-16,2024-07-23,1690,6.4,DeepTech Ventures -AI12100,Machine Learning Engineer,151696,USD,151696,EX,FT,United States,S,United States,0,"Python, Computer Vision, Git",Master,19,Education,2024-05-28,2024-06-27,1075,5.5,AI Innovations -AI12101,Computer Vision Engineer,181487,USD,181487,EX,CT,United States,M,United States,100,"Python, TensorFlow, Tableau",PhD,15,Manufacturing,2024-09-05,2024-10-20,729,9.3,Neural Networks Co -AI12102,Machine Learning Engineer,290032,CHF,261029,EX,FL,Switzerland,S,Switzerland,100,"AWS, Spark, R, Statistics, Mathematics",Master,18,Gaming,2024-12-07,2025-01-10,1549,5.5,Algorithmic Solutions -AI12103,Principal Data Scientist,88078,USD,88078,MI,PT,Israel,L,Israel,100,"Kubernetes, TensorFlow, SQL, Spark",Bachelor,2,Automotive,2024-03-31,2024-04-24,1515,8.7,Machine Intelligence Group -AI12104,Robotics Engineer,120897,USD,120897,MI,FT,Ireland,L,Ireland,100,"SQL, Java, PyTorch",PhD,3,Gaming,2024-05-11,2024-06-25,830,5.6,Neural Networks Co -AI12105,Head of AI,99552,GBP,74664,MI,CT,United Kingdom,L,United Kingdom,100,"Azure, TensorFlow, GCP, Kubernetes, Computer Vision",PhD,3,Manufacturing,2024-06-16,2024-07-10,1141,7.8,Predictive Systems -AI12106,AI Architect,229166,EUR,194791,EX,FT,Germany,S,Canada,50,"Scala, Linux, PyTorch",Master,15,Healthcare,2025-02-12,2025-03-20,1754,5.9,DataVision Ltd -AI12107,Data Engineer,65688,EUR,55835,EN,CT,Netherlands,S,Netherlands,0,"SQL, PyTorch, Azure, Computer Vision",Bachelor,0,Healthcare,2024-10-29,2024-12-09,586,9.5,Digital Transformation LLC -AI12108,Data Analyst,94258,GBP,70694,MI,FT,United Kingdom,S,Vietnam,100,"Java, Deep Learning, R",Bachelor,4,Manufacturing,2024-05-15,2024-06-18,2486,7.2,Autonomous Tech -AI12109,Machine Learning Researcher,61046,EUR,51889,EN,CT,France,S,South Korea,50,"Spark, Tableau, R, AWS",Associate,0,Real Estate,2024-08-25,2024-10-20,2285,8.2,Future Systems -AI12110,AI Research Scientist,200891,AUD,271203,EX,FT,Australia,S,Estonia,50,"Spark, TensorFlow, PyTorch, Computer Vision, Docker",PhD,12,Gaming,2024-12-01,2025-01-01,2100,7.9,Algorithmic Solutions -AI12111,AI Software Engineer,135505,JPY,14905550,SE,FL,Japan,L,Japan,0,"AWS, MLOps, Tableau, Statistics, Computer Vision",Bachelor,7,Education,2025-03-20,2025-05-29,664,8.6,Predictive Systems -AI12112,Computer Vision Engineer,98227,USD,98227,MI,CT,Norway,S,Switzerland,0,"Python, Git, Tableau, Computer Vision",Associate,3,Retail,2024-07-31,2024-10-10,1973,7.5,TechCorp Inc -AI12113,Principal Data Scientist,156496,USD,156496,EX,PT,South Korea,M,South Korea,0,"AWS, R, Python, Statistics",PhD,15,Retail,2024-05-28,2024-08-01,1858,7.7,Future Systems -AI12114,Machine Learning Researcher,102263,AUD,138055,MI,FL,Australia,M,Australia,0,"AWS, Tableau, Hadoop, TensorFlow, Azure",Associate,4,Retail,2024-06-28,2024-07-23,1553,6.3,Algorithmic Solutions -AI12115,Data Scientist,82355,GBP,61766,MI,FL,United Kingdom,S,United Kingdom,50,"Scala, Kubernetes, MLOps, SQL",Associate,4,Government,2024-11-04,2024-12-31,1044,7.3,Algorithmic Solutions -AI12116,AI Software Engineer,102312,USD,102312,EX,CT,China,M,China,100,"AWS, Scala, PyTorch",Master,14,Government,2025-03-24,2025-05-07,1376,9.9,DataVision Ltd -AI12117,Machine Learning Engineer,213639,USD,213639,EX,FL,Sweden,S,Hungary,50,"R, SQL, Docker, Computer Vision",Associate,14,Transportation,2024-12-04,2025-01-07,2256,7.8,Algorithmic Solutions -AI12118,Autonomous Systems Engineer,79347,USD,79347,EN,FT,Denmark,M,Denmark,0,"Python, Mathematics, Spark",Master,1,Healthcare,2024-11-12,2024-12-03,2385,9.2,Cloud AI Solutions -AI12119,Machine Learning Engineer,378082,USD,378082,EX,PT,Denmark,L,Denmark,100,"Scala, Statistics, R, Linux",PhD,14,Transportation,2024-12-21,2025-01-17,1551,8.5,DataVision Ltd -AI12120,AI Specialist,90690,USD,90690,MI,FL,Israel,M,Netherlands,0,"R, SQL, Python, TensorFlow",Bachelor,3,Telecommunications,2024-01-27,2024-03-19,2135,8.9,Advanced Robotics -AI12121,AI Software Engineer,183050,USD,183050,EX,CT,Israel,L,Philippines,50,"Deep Learning, NLP, PyTorch, GCP",Master,19,Retail,2024-09-11,2024-11-03,562,7.9,Autonomous Tech -AI12122,AI Research Scientist,106292,EUR,90348,MI,FT,France,L,France,0,"GCP, Python, PyTorch, Tableau",Associate,2,Gaming,2025-02-13,2025-03-12,2000,7.8,DataVision Ltd -AI12123,Data Engineer,281331,CHF,253198,EX,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Mathematics",Associate,19,Automotive,2025-04-15,2025-05-08,1116,5.1,Advanced Robotics -AI12124,Deep Learning Engineer,269789,JPY,29676790,EX,PT,Japan,M,Brazil,50,"SQL, Python, Kubernetes, Computer Vision, Data Visualization",PhD,18,Transportation,2025-01-03,2025-02-14,1006,9.3,DataVision Ltd -AI12125,Principal Data Scientist,55691,EUR,47337,EN,PT,Germany,M,Germany,0,"Azure, Tableau, Spark, Git",Bachelor,1,Energy,2024-06-14,2024-07-04,1510,5.8,Predictive Systems -AI12126,AI Research Scientist,162401,EUR,138041,EX,FL,Netherlands,M,Netherlands,50,"Deep Learning, Linux, SQL, MLOps",PhD,19,Education,2024-04-29,2024-06-03,2255,5.9,Cognitive Computing -AI12127,Robotics Engineer,185193,CHF,166674,SE,FT,Switzerland,S,Switzerland,50,"Data Visualization, Spark, SQL, Java, Deep Learning",Associate,8,Government,2024-04-05,2024-05-31,1191,5.6,Quantum Computing Inc -AI12128,AI Product Manager,288184,EUR,244956,EX,FT,Germany,L,Germany,100,"Docker, MLOps, R, Hadoop",Bachelor,13,Manufacturing,2024-11-25,2024-12-20,1153,5.8,Algorithmic Solutions -AI12129,Machine Learning Researcher,124643,CAD,155804,SE,CT,Canada,L,Ghana,0,"MLOps, Scala, Java",PhD,9,Automotive,2025-04-30,2025-05-21,1770,9.9,Neural Networks Co -AI12130,AI Software Engineer,43362,USD,43362,EN,FT,Israel,S,Israel,0,"GCP, PyTorch, Kubernetes, AWS, Docker",Master,0,Consulting,2025-02-13,2025-04-10,597,5,DataVision Ltd -AI12131,ML Ops Engineer,79374,USD,79374,SE,PT,South Korea,S,South Korea,50,"GCP, Mathematics, TensorFlow, Python",Bachelor,5,Telecommunications,2024-12-21,2025-01-14,1133,8.1,Neural Networks Co -AI12132,AI Consultant,316394,CHF,284755,EX,FT,Switzerland,S,Switzerland,50,"Azure, SQL, Git",Bachelor,10,Finance,2024-07-24,2024-10-04,891,5.4,Advanced Robotics -AI12133,Autonomous Systems Engineer,96744,EUR,82232,SE,PT,Germany,S,Germany,50,"AWS, Docker, GCP, Tableau, PyTorch",Master,8,Real Estate,2024-11-05,2024-12-12,1905,9,Cloud AI Solutions -AI12134,Head of AI,95183,SGD,123738,EN,FT,Singapore,L,Singapore,0,"PyTorch, Kubernetes, GCP",PhD,1,Finance,2024-11-17,2025-01-08,1001,8,Algorithmic Solutions -AI12135,Machine Learning Researcher,121586,USD,121586,SE,PT,United States,M,United States,100,"Scala, PyTorch, Mathematics, MLOps, Git",Bachelor,9,Consulting,2024-06-23,2024-07-25,1663,9.6,DeepTech Ventures -AI12136,Machine Learning Researcher,64380,SGD,83694,EN,FL,Singapore,M,Singapore,50,"Spark, Data Visualization, Java, TensorFlow",Bachelor,1,Healthcare,2024-11-11,2024-12-27,579,5.6,Predictive Systems -AI12137,Computer Vision Engineer,142065,GBP,106549,SE,PT,United Kingdom,S,United Kingdom,0,"R, Computer Vision, Data Visualization, NLP",PhD,9,Transportation,2024-09-14,2024-11-07,1555,5.9,Quantum Computing Inc -AI12138,Autonomous Systems Engineer,30742,USD,30742,EN,FT,China,S,China,0,"Azure, TensorFlow, GCP, Deep Learning",Bachelor,0,Media,2025-04-19,2025-05-17,1319,7.5,Smart Analytics -AI12139,Head of AI,207496,CHF,186746,SE,FL,Switzerland,L,Switzerland,50,"Git, Scala, Docker, Tableau",Master,5,Consulting,2024-03-27,2024-04-18,1801,6.2,Advanced Robotics -AI12140,AI Research Scientist,89982,USD,89982,MI,CT,Israel,S,Brazil,0,"Deep Learning, Kubernetes, Scala",Associate,4,Transportation,2025-03-29,2025-06-04,2083,5.7,Machine Intelligence Group -AI12141,Deep Learning Engineer,116355,USD,116355,SE,FT,Ireland,S,Luxembourg,50,"Python, TensorFlow, MLOps, Deep Learning",Bachelor,9,Gaming,2024-07-26,2024-08-23,2384,8.5,Advanced Robotics -AI12142,AI Architect,87703,USD,87703,MI,FT,Israel,L,Israel,0,"Docker, Tableau, R",Master,4,Manufacturing,2025-02-15,2025-03-14,1525,5.7,Cognitive Computing -AI12143,Data Scientist,75219,CHF,67697,EN,FT,Switzerland,M,Switzerland,100,"Git, R, Tableau, NLP",Associate,0,Government,2024-07-03,2024-07-20,1775,9.1,Future Systems -AI12144,Deep Learning Engineer,71478,EUR,60756,EN,FT,France,L,France,0,"Docker, PyTorch, Spark",PhD,0,Education,2024-09-11,2024-11-12,622,7.3,Digital Transformation LLC -AI12145,AI Research Scientist,132922,GBP,99692,SE,FL,United Kingdom,L,United Kingdom,0,"Linux, Spark, MLOps, Mathematics, Python",Bachelor,9,Automotive,2025-03-13,2025-05-04,721,9.8,Machine Intelligence Group -AI12146,Robotics Engineer,155903,CAD,194879,SE,PT,Canada,L,Canada,100,"Scala, MLOps, Data Visualization",Bachelor,5,Finance,2025-01-05,2025-02-28,1869,5.4,DeepTech Ventures -AI12147,AI Research Scientist,176781,USD,176781,EX,FL,South Korea,S,Singapore,0,"PyTorch, Statistics, Java, GCP",Bachelor,16,Manufacturing,2024-04-05,2024-05-08,2499,8.8,Cloud AI Solutions -AI12148,ML Ops Engineer,125692,AUD,169684,SE,FT,Australia,S,Australia,50,"SQL, Python, Git, Deep Learning",Associate,8,Consulting,2024-11-23,2025-01-19,2471,9.8,Cognitive Computing -AI12149,AI Product Manager,118577,USD,118577,EX,PT,South Korea,M,South Korea,50,"SQL, AWS, Java, Azure, R",PhD,10,Media,2024-10-24,2024-11-14,1747,9.7,AI Innovations -AI12150,AI Product Manager,56555,USD,56555,EN,FT,South Korea,S,South Korea,0,"TensorFlow, Java, Data Visualization",Associate,1,Real Estate,2024-12-30,2025-01-13,2499,7.3,DeepTech Ventures -AI12151,Research Scientist,60065,USD,60065,EN,FT,Finland,L,Finland,0,"Mathematics, PyTorch, Spark",PhD,0,Manufacturing,2024-12-26,2025-02-14,859,9.9,Future Systems -AI12152,Research Scientist,139198,USD,139198,SE,CT,Sweden,L,France,0,"Spark, Hadoop, GCP, Java, Mathematics",Associate,6,Gaming,2024-07-26,2024-09-19,879,8.4,Algorithmic Solutions -AI12153,Machine Learning Researcher,143607,USD,143607,SE,FT,Ireland,M,Ireland,0,"Azure, Hadoop, Python, GCP",Associate,6,Retail,2025-03-20,2025-04-04,1532,10,Digital Transformation LLC -AI12154,Data Analyst,176811,USD,176811,EX,CT,South Korea,L,South Korea,50,"Kubernetes, Scala, Git, Java, GCP",Associate,16,Consulting,2024-11-04,2025-01-09,1133,10,Advanced Robotics -AI12155,Principal Data Scientist,166590,EUR,141602,SE,CT,Netherlands,L,Netherlands,100,"Tableau, Docker, Azure, Scala, Python",Bachelor,5,Media,2024-07-20,2024-09-09,2307,7,Quantum Computing Inc -AI12156,Computer Vision Engineer,34463,USD,34463,MI,FL,India,M,India,100,"PyTorch, Python, Kubernetes, AWS",PhD,2,Technology,2024-07-20,2024-08-26,2225,6.4,Neural Networks Co -AI12157,AI Software Engineer,195880,USD,195880,EX,FL,Finland,S,Finland,0,"Hadoop, Python, TensorFlow, GCP, R",PhD,18,Retail,2024-01-17,2024-03-05,1179,5.6,Neural Networks Co -AI12158,Research Scientist,41697,USD,41697,MI,PT,China,M,China,50,"Azure, Python, TensorFlow",PhD,3,Manufacturing,2024-12-11,2025-02-07,1376,5.2,AI Innovations -AI12159,Research Scientist,61900,USD,61900,EN,CT,Norway,S,Norway,50,"TensorFlow, Scala, Deep Learning",Master,1,Healthcare,2024-11-20,2024-12-30,665,6.2,DataVision Ltd -AI12160,AI Consultant,32827,USD,32827,MI,FL,China,S,China,100,"Python, Kubernetes, SQL, Linux, Docker",Associate,2,Manufacturing,2024-11-03,2024-12-09,2369,7,DataVision Ltd -AI12161,Research Scientist,71766,CAD,89708,EN,FL,Canada,L,Canada,50,"Spark, Java, Mathematics, PyTorch, Computer Vision",Bachelor,1,Technology,2024-06-17,2024-07-07,1130,8.3,DeepTech Ventures -AI12162,ML Ops Engineer,221363,EUR,188159,EX,CT,Austria,M,Austria,0,"PyTorch, TensorFlow, Spark, Hadoop, Azure",Associate,16,Telecommunications,2024-04-08,2024-05-14,2389,5.5,Machine Intelligence Group -AI12163,Autonomous Systems Engineer,125926,AUD,170000,MI,FT,Australia,L,Australia,50,"Spark, Python, Mathematics, TensorFlow, Data Visualization",PhD,2,Gaming,2025-03-11,2025-04-16,1021,8.7,Autonomous Tech -AI12164,Deep Learning Engineer,121421,USD,121421,MI,FL,Denmark,M,Denmark,0,"Docker, AWS, Azure, Tableau, Spark",PhD,3,Telecommunications,2024-06-25,2024-07-18,824,9.4,Quantum Computing Inc -AI12165,Machine Learning Engineer,252757,AUD,341222,EX,FL,Australia,L,Australia,50,"Deep Learning, Scala, PyTorch, GCP, Azure",Associate,15,Automotive,2024-08-13,2024-09-04,2321,6.6,Autonomous Tech -AI12166,Data Scientist,132931,USD,132931,SE,PT,United States,S,United States,50,"Azure, Deep Learning, SQL",Associate,7,Finance,2024-09-07,2024-11-12,792,9.2,Autonomous Tech -AI12167,NLP Engineer,76358,GBP,57269,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, SQL, Computer Vision",Bachelor,1,Telecommunications,2024-12-28,2025-02-05,2476,7.7,Advanced Robotics -AI12168,Research Scientist,243166,AUD,328274,EX,CT,Australia,M,Estonia,0,"PyTorch, Mathematics, NLP, Computer Vision, TensorFlow",Bachelor,17,Automotive,2024-08-22,2024-11-01,2356,6.4,Smart Analytics -AI12169,Principal Data Scientist,101437,USD,101437,EN,CT,Norway,L,Israel,100,"SQL, Docker, Scala",Bachelor,0,Automotive,2024-07-28,2024-09-09,2330,9,Machine Intelligence Group -AI12170,Deep Learning Engineer,99518,USD,99518,MI,CT,United States,L,Luxembourg,100,"Python, TensorFlow, Git, Tableau",PhD,3,Retail,2024-06-25,2024-07-30,600,5.5,Advanced Robotics -AI12171,Deep Learning Engineer,240736,USD,240736,EX,PT,South Korea,L,Vietnam,100,"Scala, Kubernetes, Computer Vision",PhD,17,Telecommunications,2024-02-15,2024-04-24,1757,9.6,Future Systems -AI12172,Data Scientist,296026,SGD,384834,EX,FT,Singapore,L,India,100,"AWS, Scala, Data Visualization, MLOps",Master,12,Transportation,2025-02-05,2025-02-26,1392,5.6,Neural Networks Co -AI12173,Data Engineer,229184,JPY,25210240,EX,FT,Japan,L,Japan,0,"Java, SQL, GCP, NLP",Associate,17,Real Estate,2025-04-24,2025-06-01,1733,9.9,Smart Analytics -AI12174,ML Ops Engineer,151494,USD,151494,SE,FL,Ireland,M,Brazil,0,"Git, Python, MLOps, Java",Associate,7,Automotive,2024-12-04,2025-01-06,1744,6.3,Cloud AI Solutions -AI12175,NLP Engineer,237805,USD,237805,EX,CT,Sweden,L,Sweden,100,"PyTorch, Scala, Git, Mathematics",Master,10,Government,2024-08-03,2024-10-13,1883,5.1,Digital Transformation LLC -AI12176,Autonomous Systems Engineer,71970,AUD,97160,EN,FT,Australia,S,Australia,100,"R, Hadoop, NLP, SQL, Java",Master,0,Consulting,2025-03-22,2025-05-05,1066,6.9,Future Systems -AI12177,AI Architect,142468,SGD,185208,SE,CT,Singapore,S,Singapore,100,"PyTorch, Hadoop, AWS, R, Statistics",PhD,9,Automotive,2024-09-18,2024-10-09,2447,7.8,Predictive Systems -AI12178,NLP Engineer,88665,GBP,66499,MI,FT,United Kingdom,L,Kenya,100,"TensorFlow, Computer Vision, Scala, Tableau, Linux",Bachelor,4,Education,2024-04-12,2024-04-28,2448,7.7,Quantum Computing Inc -AI12179,AI Research Scientist,30066,USD,30066,EN,FL,China,L,China,50,"Azure, Python, Kubernetes, Deep Learning",Associate,1,Finance,2024-04-18,2024-05-10,2492,8.4,Predictive Systems -AI12180,AI Product Manager,90082,EUR,76570,MI,FL,France,S,France,0,"Linux, Docker, Statistics",Bachelor,4,Finance,2025-01-19,2025-02-12,1737,5.8,TechCorp Inc -AI12181,Research Scientist,101851,SGD,132406,MI,CT,Singapore,S,Singapore,0,"Kubernetes, SQL, PyTorch, MLOps",Bachelor,2,Automotive,2024-10-19,2024-12-14,1603,5.2,DeepTech Ventures -AI12182,ML Ops Engineer,246833,USD,246833,EX,FL,United States,S,United States,0,"Spark, AWS, MLOps",Associate,11,Government,2024-01-14,2024-01-28,1238,7.5,DataVision Ltd -AI12183,AI Software Engineer,89470,CHF,80523,EN,PT,Switzerland,S,Switzerland,0,"AWS, Python, GCP, Hadoop",PhD,1,Retail,2024-03-07,2024-05-02,2108,9.5,AI Innovations -AI12184,Deep Learning Engineer,71297,CAD,89121,EN,FT,Canada,M,Luxembourg,0,"SQL, Data Visualization, R",Bachelor,1,Finance,2024-06-28,2024-07-17,1898,9.1,Future Systems -AI12185,Data Scientist,86039,GBP,64529,MI,CT,United Kingdom,S,United Kingdom,100,"SQL, Scala, NLP, Computer Vision, Deep Learning",Master,2,Education,2024-05-30,2024-07-07,1586,9.9,Future Systems -AI12186,Data Scientist,34424,USD,34424,MI,CT,India,L,India,50,"GCP, Linux, Statistics",PhD,3,Technology,2024-08-22,2024-10-29,521,9.1,Predictive Systems -AI12187,Machine Learning Researcher,29840,USD,29840,MI,FT,India,M,India,0,"Python, Scala, Tableau, GCP",Master,4,Education,2025-03-20,2025-05-26,1867,8.5,Advanced Robotics -AI12188,Machine Learning Researcher,82805,AUD,111787,MI,PT,Australia,M,Ukraine,100,"TensorFlow, AWS, MLOps",Master,4,Government,2024-07-09,2024-08-15,1520,9.1,Neural Networks Co -AI12189,AI Specialist,90863,USD,90863,MI,CT,Ireland,M,Ireland,100,"Scala, R, Data Visualization",Bachelor,3,Telecommunications,2025-02-05,2025-02-19,928,7.1,Cloud AI Solutions -AI12190,AI Software Engineer,75880,USD,75880,EN,FL,Finland,L,Finland,100,"NLP, TensorFlow, AWS, Tableau, Java",PhD,1,Government,2025-01-11,2025-02-01,2354,8.3,DeepTech Ventures -AI12191,AI Specialist,90998,USD,90998,MI,CT,Norway,S,Norway,100,"Linux, Python, Kubernetes, Spark, Hadoop",PhD,2,Real Estate,2024-10-01,2024-10-15,1560,8.3,AI Innovations -AI12192,AI Product Manager,83633,EUR,71088,MI,CT,Netherlands,S,Netherlands,0,"PyTorch, GCP, Mathematics, Linux",Associate,2,Real Estate,2024-05-25,2024-07-09,2074,5.8,Algorithmic Solutions -AI12193,Deep Learning Engineer,64326,USD,64326,EN,FL,Israel,M,Israel,100,"Computer Vision, Linux, GCP",PhD,0,Finance,2024-07-02,2024-08-21,2230,8.7,Smart Analytics -AI12194,Computer Vision Engineer,111239,CHF,100115,MI,CT,Switzerland,S,Switzerland,50,"PyTorch, SQL, Computer Vision, Java",Bachelor,4,Real Estate,2024-07-08,2024-08-11,2220,7.8,Cognitive Computing -AI12195,AI Product Manager,193976,USD,193976,EX,FL,Norway,M,Belgium,100,"Mathematics, Python, SQL, GCP",PhD,17,Healthcare,2024-12-01,2025-02-03,636,5.3,Smart Analytics -AI12196,AI Architect,252737,USD,252737,EX,CT,Sweden,L,Sweden,0,"Java, Scala, MLOps, Python, Computer Vision",Master,11,Media,2024-08-30,2024-10-12,729,6.4,Quantum Computing Inc -AI12197,AI Specialist,83997,EUR,71397,MI,FL,France,M,France,0,"Kubernetes, Spark, PyTorch",Master,3,Real Estate,2025-02-25,2025-03-30,1849,7.4,Autonomous Tech -AI12198,AI Research Scientist,243739,EUR,207178,EX,PT,Germany,M,Germany,0,"Tableau, Mathematics, MLOps, Hadoop, Python",PhD,16,Technology,2024-07-27,2024-09-28,1990,9.4,Smart Analytics -AI12199,AI Consultant,169734,USD,169734,EX,FL,South Korea,M,South Korea,0,"Scala, Mathematics, Docker, Kubernetes",PhD,17,Energy,2024-12-07,2025-02-15,829,6.6,Algorithmic Solutions -AI12200,Machine Learning Researcher,59827,EUR,50853,EN,FL,Netherlands,S,China,0,"Git, Java, PyTorch, MLOps",Master,0,Finance,2024-04-20,2024-07-02,1072,5.9,Cloud AI Solutions -AI12201,Machine Learning Engineer,107719,SGD,140035,MI,PT,Singapore,L,Singapore,100,"AWS, Deep Learning, Hadoop, Linux",Master,4,Media,2024-04-16,2024-06-15,1335,8.5,AI Innovations -AI12202,AI Software Engineer,75575,JPY,8313250,EN,FT,Japan,M,Japan,50,"Computer Vision, Tableau, Deep Learning, MLOps",PhD,0,Media,2024-12-18,2025-02-17,1152,9.3,Autonomous Tech -AI12203,Autonomous Systems Engineer,281411,GBP,211058,EX,PT,United Kingdom,L,Russia,0,"Git, Spark, TensorFlow, Docker",Bachelor,13,Technology,2024-06-06,2024-07-22,1091,8.9,Cognitive Computing -AI12204,Deep Learning Engineer,88523,USD,88523,MI,FT,Ireland,L,Ireland,50,"Java, Python, Mathematics, Azure, Deep Learning",Bachelor,3,Automotive,2025-04-08,2025-06-13,1762,6.7,Digital Transformation LLC -AI12205,Deep Learning Engineer,61599,USD,61599,EN,PT,South Korea,L,South Korea,0,"Java, Spark, Tableau, Mathematics",Master,1,Government,2024-03-21,2024-05-06,794,7.6,Neural Networks Co -AI12206,Robotics Engineer,74511,SGD,96864,EN,CT,Singapore,L,Singapore,50,"NLP, Statistics, Python",Bachelor,1,Telecommunications,2024-09-22,2024-10-29,2068,6.3,DeepTech Ventures -AI12207,AI Research Scientist,23318,USD,23318,MI,FL,India,S,Thailand,50,"Scala, GCP, Python",Master,3,Government,2025-01-04,2025-02-14,1584,6.2,Quantum Computing Inc -AI12208,Computer Vision Engineer,136734,USD,136734,SE,CT,Finland,L,Finland,100,"Java, Scala, GCP, Kubernetes",Master,7,Telecommunications,2024-06-16,2024-07-24,1494,8,Predictive Systems -AI12209,Deep Learning Engineer,21533,USD,21533,EN,FL,India,L,India,100,"TensorFlow, Python, Data Visualization, Azure",Master,0,Transportation,2024-06-20,2024-07-27,759,9.6,Predictive Systems -AI12210,AI Consultant,69344,EUR,58942,EN,PT,France,M,France,50,"Kubernetes, AWS, Deep Learning",PhD,1,Automotive,2024-11-21,2024-12-21,760,6.5,Quantum Computing Inc -AI12211,Data Engineer,77016,USD,77016,EN,CT,Denmark,M,Thailand,50,"R, GCP, Kubernetes",PhD,0,Consulting,2024-12-05,2024-12-21,1323,7.8,Advanced Robotics -AI12212,AI Product Manager,79033,AUD,106695,MI,FT,Australia,M,Australia,50,"NLP, GCP, Spark",PhD,3,Manufacturing,2024-12-07,2025-01-30,1300,7.2,Future Systems -AI12213,AI Research Scientist,98816,CHF,88934,EN,FT,Switzerland,M,Switzerland,100,"Spark, Statistics, TensorFlow, Tableau",Master,1,Telecommunications,2024-06-05,2024-08-08,1929,7.3,Digital Transformation LLC -AI12214,Robotics Engineer,149985,USD,149985,SE,PT,Israel,L,Hungary,0,"TensorFlow, SQL, GCP, NLP, AWS",Master,6,Government,2024-08-14,2024-09-22,658,5.7,DataVision Ltd -AI12215,Data Scientist,129162,EUR,109788,SE,CT,Netherlands,S,Netherlands,0,"Mathematics, Git, R, SQL",Master,8,Retail,2024-03-24,2024-06-04,1376,8.6,Quantum Computing Inc -AI12216,Robotics Engineer,162024,CAD,202530,EX,CT,Canada,M,Canada,0,"Spark, SQL, Mathematics, PyTorch",Bachelor,14,Healthcare,2024-09-24,2024-11-28,2158,7.9,Algorithmic Solutions -AI12217,AI Consultant,72727,USD,72727,MI,PT,South Korea,S,South Korea,50,"MLOps, GCP, Scala, Computer Vision",Associate,4,Healthcare,2024-11-19,2025-01-02,914,5.4,Machine Intelligence Group -AI12218,Machine Learning Researcher,74894,USD,74894,EN,FL,Ireland,L,Ireland,100,"Kubernetes, MLOps, Linux, PyTorch, Git",PhD,0,Transportation,2025-02-13,2025-04-20,619,6.5,Advanced Robotics -AI12219,AI Specialist,106226,CAD,132783,SE,CT,Canada,M,Canada,100,"Scala, PyTorch, Docker",Associate,5,Energy,2024-12-02,2025-01-14,1075,9.4,Future Systems -AI12220,Computer Vision Engineer,103330,USD,103330,SE,FT,South Korea,L,South Korea,0,"NLP, AWS, Python",Associate,7,Finance,2024-01-07,2024-02-22,1951,6.2,Smart Analytics -AI12221,AI Software Engineer,228843,GBP,171632,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, Python, Computer Vision",Bachelor,18,Manufacturing,2024-10-31,2024-12-16,2231,7.7,Neural Networks Co -AI12222,Deep Learning Engineer,129776,USD,129776,MI,FT,Denmark,M,Vietnam,50,"Hadoop, Linux, SQL",Associate,3,Healthcare,2025-01-30,2025-03-07,1368,8.4,Quantum Computing Inc -AI12223,Research Scientist,146735,USD,146735,SE,FL,Norway,S,United States,50,"Computer Vision, TensorFlow, GCP",Associate,6,Automotive,2024-05-05,2024-05-20,623,8,DeepTech Ventures -AI12224,AI Research Scientist,128592,USD,128592,MI,CT,Denmark,S,Poland,50,"Hadoop, Deep Learning, Spark, AWS",Associate,4,Automotive,2024-06-11,2024-06-26,1115,6.1,TechCorp Inc -AI12225,AI Architect,166057,USD,166057,SE,PT,United States,L,United States,50,"R, MLOps, PyTorch, TensorFlow, Azure",PhD,9,Real Estate,2025-02-05,2025-03-11,2164,6.4,TechCorp Inc -AI12226,Principal Data Scientist,183692,CHF,165323,EX,FT,Switzerland,S,Switzerland,0,"R, Statistics, Git, Mathematics, GCP",Associate,10,Energy,2024-10-19,2024-11-15,2045,7,Machine Intelligence Group -AI12227,AI Software Engineer,43783,USD,43783,EN,FT,South Korea,M,South Korea,50,"SQL, Kubernetes, AWS, R",PhD,0,Education,2024-03-23,2024-04-12,2327,6.8,Quantum Computing Inc -AI12228,Data Scientist,131756,SGD,171283,SE,CT,Singapore,S,Singapore,100,"Mathematics, Deep Learning, Python, Java",Associate,7,Media,2024-01-01,2024-01-27,967,5.1,DeepTech Ventures -AI12229,AI Product Manager,93277,EUR,79285,MI,CT,Germany,S,Nigeria,100,"SQL, Azure, Computer Vision, Scala",PhD,4,Automotive,2024-03-16,2024-03-31,764,5.9,Machine Intelligence Group -AI12230,NLP Engineer,75614,SGD,98298,MI,FT,Singapore,S,Singapore,50,"Kubernetes, R, GCP, MLOps, Docker",Master,2,Government,2024-12-02,2025-01-19,2241,9.1,Cognitive Computing -AI12231,AI Consultant,247382,USD,247382,EX,FT,Ireland,M,Ireland,50,"TensorFlow, Docker, Deep Learning, Python",Master,15,Consulting,2024-10-29,2024-12-25,2013,6,Cloud AI Solutions -AI12232,AI Architect,106997,SGD,139096,MI,CT,Singapore,M,Singapore,50,"MLOps, Data Visualization, R",PhD,2,Healthcare,2024-11-27,2025-01-31,2177,8.8,Cognitive Computing -AI12233,Data Scientist,138109,GBP,103582,SE,CT,United Kingdom,S,United Kingdom,100,"Scala, Azure, Hadoop, Docker",Bachelor,6,Manufacturing,2024-02-24,2024-04-07,1495,6.9,Machine Intelligence Group -AI12234,Computer Vision Engineer,138794,USD,138794,EX,FT,Ireland,M,Ireland,100,"Statistics, Computer Vision, PyTorch, Azure, Deep Learning",Master,16,Media,2024-02-04,2024-04-09,2355,7.7,DataVision Ltd -AI12235,Autonomous Systems Engineer,168757,USD,168757,EX,CT,South Korea,L,Mexico,0,"TensorFlow, Hadoop, Linux, Docker",Master,11,Media,2024-06-03,2024-07-19,2255,9.6,Digital Transformation LLC -AI12236,AI Consultant,124514,USD,124514,MI,FT,Sweden,L,Spain,0,"Linux, R, Spark, Python, GCP",Associate,4,Government,2024-08-28,2024-10-03,587,9.7,Advanced Robotics -AI12237,Head of AI,59609,GBP,44707,EN,CT,United Kingdom,M,United Kingdom,0,"SQL, PyTorch, Computer Vision",Master,0,Retail,2024-05-19,2024-06-03,1917,7.4,Autonomous Tech -AI12238,Computer Vision Engineer,96741,JPY,10641510,MI,PT,Japan,S,Japan,0,"Computer Vision, Azure, Git, TensorFlow, Mathematics",Associate,4,Energy,2024-02-11,2024-04-18,2132,6.9,Quantum Computing Inc -AI12239,Data Analyst,263387,EUR,223879,EX,FL,Netherlands,L,Czech Republic,0,"Statistics, PyTorch, Java, MLOps, Deep Learning",PhD,16,Education,2024-08-08,2024-10-12,2083,6.1,TechCorp Inc -AI12240,Computer Vision Engineer,98959,GBP,74219,MI,PT,United Kingdom,S,United Kingdom,50,"Computer Vision, Hadoop, R, Scala",Bachelor,2,Healthcare,2025-02-15,2025-03-20,1818,7.3,Future Systems -AI12241,Data Scientist,120653,USD,120653,MI,FL,United States,L,United States,100,"Mathematics, Python, Tableau, Data Visualization",Associate,3,Government,2025-04-28,2025-05-19,2337,7.3,DeepTech Ventures -AI12242,AI Architect,157279,AUD,212327,EX,PT,Australia,S,India,100,"Scala, Python, Computer Vision",PhD,18,Real Estate,2024-08-03,2024-09-05,2318,7.4,Cloud AI Solutions -AI12243,AI Specialist,252708,EUR,214802,EX,PT,France,L,France,100,"GCP, Azure, Scala, Data Visualization",Master,18,Government,2024-07-16,2024-09-12,1823,5.1,Advanced Robotics -AI12244,Computer Vision Engineer,98348,USD,98348,EN,FT,Denmark,M,Denmark,0,"NLP, MLOps, Git",PhD,1,Retail,2024-11-22,2024-12-13,1969,7,Smart Analytics -AI12245,AI Architect,195438,USD,195438,EX,FT,Denmark,M,Denmark,50,"Scala, Kubernetes, NLP, Statistics, Python",Associate,11,Gaming,2024-11-18,2024-12-13,1555,9.1,TechCorp Inc -AI12246,Deep Learning Engineer,118243,USD,118243,SE,FT,Israel,M,Luxembourg,50,"Git, MLOps, R, Data Visualization",Master,8,Automotive,2024-09-19,2024-10-11,1355,8.2,Digital Transformation LLC -AI12247,Principal Data Scientist,70867,SGD,92127,MI,CT,Singapore,S,Estonia,100,"R, SQL, Deep Learning",Associate,4,Real Estate,2024-11-03,2024-12-09,715,5.6,Advanced Robotics -AI12248,Data Scientist,108015,USD,108015,SE,PT,South Korea,L,Spain,50,"Hadoop, Python, GCP",PhD,7,Manufacturing,2024-02-22,2024-03-07,2082,5.4,AI Innovations -AI12249,Computer Vision Engineer,68609,USD,68609,MI,FT,South Korea,S,South Korea,50,"Kubernetes, Linux, Docker",Master,3,Transportation,2024-02-01,2024-03-29,652,7.1,Smart Analytics -AI12250,Research Scientist,138450,USD,138450,SE,FL,Norway,M,France,100,"Azure, Java, MLOps, Computer Vision",Bachelor,7,Healthcare,2024-06-18,2024-08-17,1731,5.6,Neural Networks Co -AI12251,Autonomous Systems Engineer,129185,USD,129185,SE,PT,Israel,L,Israel,0,"GCP, Python, Git, Java",PhD,8,Telecommunications,2024-05-18,2024-07-11,2162,8.2,Cognitive Computing -AI12252,Data Engineer,62912,EUR,53475,EN,PT,Austria,L,Austria,50,"SQL, Docker, Linux",PhD,0,Transportation,2024-08-06,2024-09-25,926,6.4,Machine Intelligence Group -AI12253,Machine Learning Engineer,185718,USD,185718,EX,PT,Israel,L,Israel,50,"Python, Mathematics, MLOps, TensorFlow, Deep Learning",Bachelor,11,Manufacturing,2024-02-08,2024-04-04,2195,5.2,DataVision Ltd -AI12254,Machine Learning Engineer,159827,USD,159827,EX,FL,Israel,M,Israel,100,"Python, GCP, Linux, Statistics, Hadoop",Master,19,Finance,2024-12-09,2024-12-28,963,5.4,Autonomous Tech -AI12255,Computer Vision Engineer,93928,SGD,122106,MI,FT,Singapore,M,China,0,"Computer Vision, Python, TensorFlow, Docker, Statistics",Master,3,Media,2024-11-11,2024-11-30,870,6.1,Digital Transformation LLC -AI12256,Research Scientist,75790,GBP,56843,EN,FL,United Kingdom,S,Japan,0,"Java, Scala, GCP, Spark",Bachelor,1,Energy,2024-01-24,2024-03-03,1431,6.5,Neural Networks Co -AI12257,AI Consultant,34200,USD,34200,EN,FT,China,L,China,0,"NLP, Mathematics, Tableau, R, MLOps",Associate,0,Media,2024-04-13,2024-06-24,912,8.4,AI Innovations -AI12258,AI Software Engineer,90286,USD,90286,EN,FT,Denmark,M,Denmark,50,"Deep Learning, Spark, Azure, Tableau, AWS",Master,0,Telecommunications,2024-08-27,2024-10-29,1571,5.3,Digital Transformation LLC -AI12259,Robotics Engineer,146547,CAD,183184,EX,FL,Canada,S,Canada,100,"Kubernetes, Spark, Deep Learning, Statistics, PyTorch",PhD,17,Automotive,2025-03-30,2025-06-01,1978,8.4,TechCorp Inc -AI12260,Computer Vision Engineer,31797,USD,31797,MI,FT,India,M,Belgium,50,"Linux, Kubernetes, Statistics, Deep Learning, R",Associate,3,Gaming,2024-07-10,2024-09-18,923,8.9,Predictive Systems -AI12261,Machine Learning Engineer,54017,CAD,67521,EN,FT,Canada,M,Canada,50,"Git, Python, Spark, Scala",Associate,0,Transportation,2024-09-12,2024-10-08,513,9.2,Quantum Computing Inc -AI12262,Head of AI,272906,EUR,231970,EX,FT,Netherlands,L,India,50,"Python, Spark, Java, Data Visualization",Associate,16,Automotive,2025-03-10,2025-04-11,1833,7.6,Smart Analytics -AI12263,Machine Learning Engineer,43901,CAD,54876,EN,FT,Canada,S,Romania,100,"Deep Learning, AWS, Docker",Master,1,Energy,2024-01-11,2024-03-13,1700,6.7,Advanced Robotics -AI12264,Data Engineer,127644,AUD,172319,SE,FT,Australia,L,India,50,"Mathematics, Python, Computer Vision",Master,8,Finance,2024-07-14,2024-08-25,1260,5.1,Cognitive Computing -AI12265,AI Product Manager,128688,USD,128688,MI,PT,Denmark,L,Ireland,0,"R, Azure, Statistics",Master,4,Automotive,2024-06-28,2024-08-30,2202,9.9,Cognitive Computing -AI12266,AI Product Manager,94657,USD,94657,SE,FT,South Korea,S,South Korea,100,"SQL, TensorFlow, Deep Learning, Hadoop",PhD,8,Government,2025-04-09,2025-05-28,1489,8.8,TechCorp Inc -AI12267,AI Architect,109965,USD,109965,EN,PT,Denmark,L,Mexico,50,"Java, PyTorch, Docker, TensorFlow",Master,1,Gaming,2024-03-07,2024-04-29,752,7,Future Systems -AI12268,Head of AI,206612,USD,206612,EX,CT,Denmark,S,Denmark,0,"Java, R, SQL",Associate,17,Finance,2024-11-19,2025-01-18,1979,9.5,Autonomous Tech -AI12269,Data Engineer,181402,USD,181402,EX,FL,Sweden,S,China,100,"Statistics, SQL, Linux, Spark, Computer Vision",Associate,10,Transportation,2024-09-09,2024-11-09,1526,5,DataVision Ltd -AI12270,Machine Learning Engineer,193935,CHF,174542,SE,FT,Switzerland,L,Switzerland,100,"Git, Docker, Python",Associate,8,Finance,2024-12-22,2025-02-01,671,8.6,Advanced Robotics -AI12271,AI Architect,59622,USD,59622,SE,FT,China,L,China,100,"PyTorch, GCP, Scala",Master,8,Retail,2024-08-19,2024-09-10,616,6.9,DeepTech Ventures -AI12272,Data Engineer,82962,EUR,70518,MI,FL,Netherlands,S,Luxembourg,50,"Hadoop, AWS, NLP",Associate,4,Telecommunications,2024-03-05,2024-05-03,2217,6.5,AI Innovations -AI12273,AI Research Scientist,179005,USD,179005,EX,PT,Sweden,S,New Zealand,50,"Python, TensorFlow, Deep Learning, AWS, Statistics",Master,13,Consulting,2024-02-09,2024-03-09,1916,9.8,Cloud AI Solutions -AI12274,NLP Engineer,45061,USD,45061,EN,FL,South Korea,M,South Korea,50,"Java, SQL, GCP, Deep Learning",PhD,1,Gaming,2024-02-07,2024-02-24,2265,7.7,Future Systems -AI12275,Robotics Engineer,183033,USD,183033,EX,PT,Israel,L,Israel,100,"Git, GCP, MLOps, Computer Vision",PhD,18,Healthcare,2024-10-31,2025-01-03,1456,6.2,DataVision Ltd -AI12276,AI Architect,85926,USD,85926,EN,FL,United States,L,United States,50,"Linux, R, Mathematics, SQL",PhD,0,Technology,2024-02-14,2024-03-31,724,7.7,Cognitive Computing -AI12277,AI Specialist,90585,EUR,76997,SE,FL,Austria,S,United Kingdom,0,"Python, Azure, TensorFlow, Statistics",Bachelor,8,Finance,2024-12-16,2025-01-28,694,7.3,Cognitive Computing -AI12278,ML Ops Engineer,175783,CHF,158205,SE,CT,Switzerland,L,Austria,100,"Docker, Tableau, NLP, Linux, AWS",Associate,7,Gaming,2025-02-12,2025-03-25,1058,8.5,Machine Intelligence Group -AI12279,AI Consultant,136939,USD,136939,SE,FT,Denmark,M,Denmark,0,"Java, GCP, Python, R, Computer Vision",Master,5,Education,2024-12-16,2025-02-04,2284,6.8,Autonomous Tech -AI12280,Computer Vision Engineer,91436,USD,91436,MI,FL,Israel,M,Denmark,50,"Kubernetes, Spark, Tableau",Bachelor,3,Telecommunications,2024-12-28,2025-03-06,596,7.2,TechCorp Inc -AI12281,Computer Vision Engineer,149033,CHF,134130,MI,FT,Switzerland,M,Switzerland,0,"Git, TensorFlow, Data Visualization, Computer Vision, Docker",PhD,4,Media,2024-02-01,2024-04-01,1269,9.8,Advanced Robotics -AI12282,Machine Learning Engineer,66306,USD,66306,EN,CT,Denmark,M,Denmark,100,"SQL, TensorFlow, NLP, Linux",Master,0,Consulting,2024-02-25,2024-05-01,939,5.2,DataVision Ltd -AI12283,AI Software Engineer,59399,USD,59399,SE,CT,China,M,China,100,"Python, TensorFlow, Deep Learning, Git",PhD,5,Healthcare,2024-06-27,2024-08-24,2474,6.1,TechCorp Inc -AI12284,Data Analyst,99702,USD,99702,SE,CT,Sweden,S,Sweden,100,"Python, TensorFlow, Data Visualization",Bachelor,7,Transportation,2025-04-01,2025-05-15,874,9.5,TechCorp Inc -AI12285,AI Architect,100196,USD,100196,SE,CT,South Korea,S,South Korea,50,"Docker, Scala, Python",Master,6,Healthcare,2024-04-04,2024-05-03,600,9.7,Machine Intelligence Group -AI12286,AI Architect,247639,CAD,309549,EX,CT,Canada,L,Spain,100,"R, GCP, Python, Mathematics",Master,10,Media,2024-11-25,2024-12-11,1628,9.1,Digital Transformation LLC -AI12287,Autonomous Systems Engineer,98862,USD,98862,MI,FT,Norway,S,Chile,50,"Python, Computer Vision, GCP, Java, MLOps",Master,4,Manufacturing,2024-05-22,2024-07-16,1346,9.2,Cloud AI Solutions -AI12288,AI Software Engineer,100088,EUR,85075,MI,FL,Netherlands,S,Colombia,100,"Java, Azure, GCP, R",Associate,4,Gaming,2025-01-31,2025-03-12,677,9,Digital Transformation LLC -AI12289,ML Ops Engineer,67854,USD,67854,MI,FL,Israel,S,Israel,50,"Data Visualization, Computer Vision, PyTorch, Spark, GCP",Bachelor,2,Finance,2024-03-28,2024-06-07,1834,7.5,AI Innovations -AI12290,Research Scientist,133071,USD,133071,SE,CT,Finland,M,Finland,0,"Python, Linux, MLOps, Statistics",PhD,8,Healthcare,2024-03-17,2024-05-18,859,8.6,AI Innovations -AI12291,AI Research Scientist,94334,SGD,122634,MI,FL,Singapore,L,Singapore,0,"NLP, Docker, Mathematics, Hadoop",Bachelor,3,Healthcare,2024-12-19,2025-01-24,871,6,Digital Transformation LLC -AI12292,AI Research Scientist,79114,USD,79114,EX,PT,China,L,China,50,"NLP, SQL, Python, Kubernetes",Bachelor,14,Real Estate,2024-08-07,2024-09-27,1681,9.1,Machine Intelligence Group -AI12293,Autonomous Systems Engineer,140641,USD,140641,SE,FL,Sweden,M,Sweden,50,"Python, Kubernetes, GCP, Statistics, Tableau",Master,7,Telecommunications,2024-05-01,2024-05-21,2152,9.2,DeepTech Ventures -AI12294,Computer Vision Engineer,108378,CHF,97540,MI,FT,Switzerland,S,Switzerland,0,"R, Azure, MLOps, Spark, Python",Master,2,Gaming,2024-05-13,2024-06-08,2394,8.6,Autonomous Tech -AI12295,Deep Learning Engineer,66720,USD,66720,EN,FL,Denmark,M,Thailand,0,"Python, TensorFlow, MLOps",Bachelor,0,Technology,2024-04-28,2024-06-22,2040,6.9,Algorithmic Solutions -AI12296,AI Architect,103843,EUR,88267,MI,PT,Germany,L,Germany,100,"Linux, R, Azure, Python",PhD,3,Healthcare,2025-04-03,2025-05-26,789,8.4,Predictive Systems -AI12297,Principal Data Scientist,180949,USD,180949,SE,FL,Norway,M,Norway,0,"SQL, Java, Spark",Associate,7,Real Estate,2024-04-29,2024-06-17,740,8.6,TechCorp Inc -AI12298,Robotics Engineer,320986,USD,320986,EX,CT,United States,L,United States,100,"NLP, Azure, Scala",Bachelor,11,Media,2025-02-28,2025-03-15,1339,8.7,Neural Networks Co -AI12299,AI Product Manager,164065,SGD,213285,SE,PT,Singapore,L,Singapore,100,"Statistics, GCP, Linux, Hadoop",Bachelor,9,Technology,2024-09-19,2024-11-02,1815,8.8,TechCorp Inc -AI12300,Data Analyst,84134,USD,84134,MI,FT,Sweden,S,Sweden,0,"Python, Java, Tableau",PhD,3,Healthcare,2024-01-29,2024-02-19,2364,8.2,Algorithmic Solutions -AI12301,AI Product Manager,59000,USD,59000,EN,FT,Ireland,L,Ireland,0,"Spark, Mathematics, R",Master,0,Energy,2024-11-17,2025-01-16,975,6.3,AI Innovations -AI12302,Data Analyst,184365,USD,184365,EX,FL,Sweden,M,Sweden,50,"SQL, Python, Linux, Docker, Java",Bachelor,17,Automotive,2024-03-21,2024-04-05,2378,5.9,Cognitive Computing -AI12303,AI Architect,74246,CAD,92808,MI,PT,Canada,S,Thailand,100,"PyTorch, SQL, Docker, Computer Vision, R",Master,2,Automotive,2024-08-11,2024-10-22,819,5.2,Cloud AI Solutions -AI12304,Machine Learning Researcher,116928,USD,116928,SE,PT,Ireland,S,Ireland,0,"Docker, MLOps, Scala, Python, AWS",PhD,7,Finance,2024-03-31,2024-04-22,1068,5.2,AI Innovations -AI12305,Principal Data Scientist,64457,USD,64457,SE,FT,China,L,China,50,"Statistics, Scala, Kubernetes",PhD,7,Finance,2024-03-27,2024-05-17,915,9.4,Autonomous Tech -AI12306,AI Architect,34017,USD,34017,EN,CT,China,S,China,50,"Git, Docker, Azure, Tableau, Python",Associate,1,Government,2025-03-01,2025-04-15,1811,8.1,Cognitive Computing -AI12307,Principal Data Scientist,86245,USD,86245,EN,FL,Ireland,L,Ireland,0,"Deep Learning, R, SQL, PyTorch",Master,1,Technology,2024-05-14,2024-06-24,1477,6.9,Predictive Systems -AI12308,Data Analyst,304034,USD,304034,EX,CT,Denmark,M,Denmark,50,"MLOps, Linux, Hadoop, PyTorch",Master,11,Retail,2024-01-06,2024-01-23,683,9,Machine Intelligence Group -AI12309,Machine Learning Researcher,207016,USD,207016,EX,FT,Finland,S,Finland,100,"Hadoop, R, PyTorch, Java, Docker",Associate,11,Media,2024-12-11,2025-01-06,593,5.3,AI Innovations -AI12310,AI Research Scientist,192387,GBP,144290,EX,FL,United Kingdom,M,Singapore,50,"Java, Python, R",PhD,17,Consulting,2024-09-18,2024-11-22,2353,8.6,Future Systems -AI12311,Data Analyst,23733,USD,23733,MI,FT,India,S,Switzerland,100,"Git, Python, MLOps, Tableau",Master,3,Gaming,2024-08-25,2024-09-15,628,8.6,Advanced Robotics -AI12312,AI Architect,154274,USD,154274,SE,PT,Denmark,L,United States,0,"Deep Learning, Mathematics, Scala, AWS",PhD,9,Retail,2024-02-13,2024-03-27,1673,6,DeepTech Ventures -AI12313,NLP Engineer,43529,USD,43529,MI,CT,China,S,Colombia,50,"Scala, Kubernetes, R, Computer Vision",Master,4,Education,2025-01-04,2025-02-27,855,8.4,Future Systems -AI12314,AI Product Manager,214849,EUR,182622,EX,FL,Austria,M,Austria,50,"Git, Hadoop, Mathematics, PyTorch, Statistics",Bachelor,11,Government,2024-10-25,2024-11-09,2133,8.4,Algorithmic Solutions -AI12315,AI Research Scientist,49530,USD,49530,MI,PT,China,M,China,50,"Kubernetes, GCP, Python",PhD,3,Transportation,2024-12-16,2025-02-12,1247,5.3,Algorithmic Solutions -AI12316,AI Product Manager,90866,USD,90866,EN,FL,Denmark,S,Denmark,0,"Tableau, TensorFlow, Linux, Java",PhD,1,Education,2024-09-04,2024-11-03,2019,9.6,Neural Networks Co -AI12317,Principal Data Scientist,38519,USD,38519,EN,CT,South Korea,S,South Korea,0,"Tableau, AWS, SQL, Computer Vision",PhD,1,Healthcare,2024-07-04,2024-09-02,1845,5.3,DeepTech Ventures -AI12318,Principal Data Scientist,190560,SGD,247728,EX,PT,Singapore,L,Singapore,50,"Kubernetes, Spark, TensorFlow, Data Visualization, Mathematics",PhD,14,Automotive,2024-01-07,2024-03-06,1253,8.5,Future Systems -AI12319,Data Scientist,111397,USD,111397,SE,FL,Sweden,M,Sweden,0,"NLP, Java, Git, SQL",Bachelor,9,Healthcare,2024-04-21,2024-05-27,2032,9.6,DeepTech Ventures -AI12320,Head of AI,100635,USD,100635,MI,CT,Finland,M,Finland,0,"Linux, Java, SQL, Mathematics",PhD,2,Automotive,2025-04-28,2025-05-20,2219,9,Quantum Computing Inc -AI12321,Robotics Engineer,108577,USD,108577,SE,FT,Finland,M,Finland,100,"Statistics, GCP, Docker, Git, Computer Vision",Associate,7,Healthcare,2024-07-23,2024-09-11,641,5,TechCorp Inc -AI12322,AI Product Manager,34193,USD,34193,MI,PT,India,L,India,0,"Scala, GCP, Linux, SQL, Hadoop",Bachelor,3,Healthcare,2024-06-08,2024-07-20,679,6.1,Quantum Computing Inc -AI12323,AI Software Engineer,110241,EUR,93705,SE,PT,Austria,M,Indonesia,50,"GCP, Computer Vision, TensorFlow, Tableau",Bachelor,6,Real Estate,2024-06-06,2024-07-21,1072,8.8,DeepTech Ventures -AI12324,Data Scientist,184497,USD,184497,EX,PT,Denmark,S,Denmark,50,"Tableau, Azure, Java, Kubernetes, MLOps",Master,16,Real Estate,2024-07-24,2024-09-07,1516,5.3,DeepTech Ventures -AI12325,AI Architect,84774,USD,84774,EN,FL,Finland,L,Finland,50,"Hadoop, PyTorch, Git, Azure, TensorFlow",Bachelor,0,Manufacturing,2024-09-12,2024-11-17,1470,6.4,Cloud AI Solutions -AI12326,Robotics Engineer,235792,USD,235792,EX,CT,United States,L,Philippines,0,"MLOps, Java, Docker",Bachelor,14,Finance,2024-10-20,2024-11-03,1360,6,Advanced Robotics -AI12327,Autonomous Systems Engineer,54131,USD,54131,EX,FL,India,M,India,0,"Computer Vision, GCP, Scala, Git",Master,15,Government,2024-07-09,2024-07-25,1390,7,Cognitive Computing -AI12328,Research Scientist,154810,CAD,193513,EX,FT,Canada,L,Canada,100,"Computer Vision, Kubernetes, NLP, R, Scala",Bachelor,15,Media,2024-09-03,2024-10-30,1652,6,DataVision Ltd -AI12329,AI Software Engineer,86911,EUR,73874,EN,PT,Netherlands,L,Netherlands,0,"Python, Spark, GCP, AWS, Azure",PhD,0,Telecommunications,2024-03-02,2024-05-11,2154,5.1,Digital Transformation LLC -AI12330,Machine Learning Engineer,83432,JPY,9177520,MI,CT,Japan,S,Austria,0,"Kubernetes, Git, MLOps, GCP",PhD,3,Media,2024-11-03,2024-12-08,1132,8.1,AI Innovations -AI12331,Data Analyst,104994,USD,104994,EX,CT,China,M,China,100,"Deep Learning, PyTorch, Data Visualization, TensorFlow, MLOps",PhD,11,Healthcare,2025-02-05,2025-03-22,1601,9.4,Cloud AI Solutions -AI12332,Principal Data Scientist,114869,EUR,97639,SE,PT,France,L,France,50,"Scala, Git, PyTorch",PhD,6,Consulting,2024-06-12,2024-07-28,1537,6.3,Predictive Systems -AI12333,AI Consultant,108366,USD,108366,SE,FT,South Korea,M,South Korea,100,"Azure, AWS, Data Visualization, Git, Computer Vision",Associate,7,Transportation,2024-04-07,2024-06-17,1379,8.2,Future Systems -AI12334,Machine Learning Engineer,112203,USD,112203,MI,FL,Ireland,L,Ireland,50,"SQL, R, Python, AWS",PhD,2,Media,2024-12-04,2025-01-07,1218,8.6,Smart Analytics -AI12335,Data Analyst,152809,EUR,129888,EX,FL,France,S,France,100,"Spark, Python, Tableau, Statistics",Master,19,Retail,2024-05-07,2024-06-07,1099,6.6,Autonomous Tech -AI12336,AI Consultant,55945,USD,55945,MI,CT,China,L,Finland,0,"Azure, Scala, Python, Statistics, Mathematics",Bachelor,4,Gaming,2024-01-01,2024-01-23,2346,6.7,Machine Intelligence Group -AI12337,Research Scientist,139128,USD,139128,SE,PT,Finland,L,Finland,100,"Hadoop, Scala, Computer Vision, TensorFlow, Docker",PhD,8,Media,2024-09-19,2024-10-07,761,6.9,Quantum Computing Inc -AI12338,NLP Engineer,74433,USD,74433,MI,PT,Ireland,S,Ireland,50,"R, GCP, Hadoop",Master,2,Real Estate,2024-05-15,2024-07-04,888,6.7,Predictive Systems -AI12339,Deep Learning Engineer,62585,USD,62585,EN,PT,Finland,L,Russia,100,"GCP, SQL, NLP, Statistics",PhD,1,Real Estate,2024-03-14,2024-04-09,1943,8.9,Cognitive Computing -AI12340,Deep Learning Engineer,64130,JPY,7054300,EN,PT,Japan,S,Japan,50,"Hadoop, Tableau, AWS, Java, Data Visualization",PhD,1,Telecommunications,2025-01-16,2025-01-31,2403,8.8,DataVision Ltd -AI12341,Head of AI,24000,USD,24000,EN,FL,India,M,India,50,"Spark, Hadoop, Statistics, Python",PhD,1,Retail,2024-06-20,2024-08-19,1168,9.5,Advanced Robotics -AI12342,ML Ops Engineer,63740,EUR,54179,EN,FL,France,L,Belgium,100,"Computer Vision, MLOps, Deep Learning, Python",Associate,0,Telecommunications,2024-12-15,2025-01-26,2452,5,Cognitive Computing -AI12343,AI Architect,75688,EUR,64335,EN,FT,Netherlands,M,Netherlands,100,"TensorFlow, Spark, Tableau, Data Visualization, Scala",PhD,0,Retail,2024-12-01,2025-02-10,1406,6.3,Smart Analytics -AI12344,Autonomous Systems Engineer,91038,USD,91038,EN,CT,Sweden,L,Sweden,0,"Python, Java, AWS, Mathematics",Associate,1,Consulting,2024-02-05,2024-03-18,908,5.5,Predictive Systems -AI12345,Autonomous Systems Engineer,171871,USD,171871,EX,FT,Israel,M,Malaysia,50,"PyTorch, R, Mathematics, MLOps",Associate,10,Real Estate,2024-06-03,2024-07-14,2018,8.2,Predictive Systems -AI12346,ML Ops Engineer,92855,USD,92855,EN,FL,Norway,S,Ukraine,0,"Python, Data Visualization, TensorFlow, Spark, Hadoop",Associate,1,Education,2024-08-01,2024-09-11,1286,9.5,Future Systems -AI12347,AI Specialist,138709,USD,138709,MI,PT,Norway,M,Norway,100,"Scala, MLOps, TensorFlow, Hadoop",Master,2,Government,2025-04-27,2025-06-27,1095,7.7,Predictive Systems -AI12348,AI Product Manager,89902,USD,89902,EX,CT,India,L,India,50,"Java, Statistics, Tableau, NLP, PyTorch",Bachelor,12,Telecommunications,2024-03-08,2024-04-04,791,9.8,TechCorp Inc -AI12349,Machine Learning Engineer,172633,USD,172633,SE,CT,United States,M,Poland,50,"Python, R, Git, GCP, Deep Learning",Associate,8,Retail,2024-10-08,2024-12-08,645,6.9,TechCorp Inc -AI12350,Robotics Engineer,113910,USD,113910,SE,FT,Israel,M,Israel,0,"Azure, Scala, Data Visualization, Java, Spark",Bachelor,5,Retail,2024-08-20,2024-10-17,1576,5.7,Neural Networks Co -AI12351,Robotics Engineer,145181,USD,145181,SE,FT,United States,S,United Kingdom,50,"Spark, Tableau, MLOps, R, Computer Vision",Associate,8,Gaming,2024-06-23,2024-07-19,1128,5.5,Smart Analytics -AI12352,Data Scientist,126932,CAD,158665,SE,FL,Canada,S,Canada,0,"Computer Vision, Scala, Azure, SQL, Hadoop",PhD,7,Education,2024-11-02,2025-01-14,1822,6.6,Algorithmic Solutions -AI12353,Data Engineer,237969,EUR,202274,EX,FT,Austria,L,Austria,100,"Computer Vision, Azure, Hadoop, Git",Bachelor,13,Manufacturing,2024-03-22,2024-04-19,1312,9.3,Cloud AI Solutions -AI12354,ML Ops Engineer,70164,USD,70164,EX,CT,China,S,China,50,"Kubernetes, Scala, GCP",PhD,12,Energy,2024-02-05,2024-02-25,1714,6.4,Algorithmic Solutions -AI12355,Principal Data Scientist,91580,USD,91580,MI,PT,Sweden,L,Sweden,50,"Java, TensorFlow, NLP, R, Linux",Associate,2,Retail,2025-04-17,2025-05-30,1576,8.7,Algorithmic Solutions -AI12356,Data Scientist,210798,SGD,274037,EX,CT,Singapore,L,Czech Republic,50,"Azure, Python, TensorFlow",Bachelor,16,Automotive,2025-04-27,2025-06-03,1488,5.4,Advanced Robotics -AI12357,Data Scientist,172275,SGD,223958,EX,FL,Singapore,S,Norway,100,"PyTorch, MLOps, Scala, Mathematics, Computer Vision",Associate,11,Telecommunications,2024-01-22,2024-03-26,1642,5.1,DeepTech Ventures -AI12358,Data Scientist,181539,GBP,136154,SE,FT,United Kingdom,L,United Kingdom,50,"Azure, Python, AWS",Bachelor,5,Gaming,2024-03-29,2024-04-30,849,9.6,AI Innovations -AI12359,Principal Data Scientist,83912,JPY,9230320,EN,FT,Japan,L,Japan,100,"Docker, Data Visualization, Computer Vision",Master,0,Automotive,2024-09-05,2024-10-07,1372,5.8,Predictive Systems -AI12360,AI Product Manager,126540,USD,126540,MI,PT,Sweden,L,Sweden,0,"Deep Learning, Kubernetes, Python, Git",Bachelor,3,Government,2024-11-17,2024-12-20,747,8.2,Future Systems -AI12361,Machine Learning Researcher,136341,USD,136341,MI,FL,Denmark,L,South Africa,100,"SQL, NLP, MLOps",Master,2,Finance,2024-08-19,2024-10-08,2113,7.4,Machine Intelligence Group -AI12362,Principal Data Scientist,134759,EUR,114545,SE,FT,Germany,S,Germany,50,"NLP, Spark, Azure, Python",Bachelor,6,Energy,2024-08-24,2024-10-23,901,5.4,Digital Transformation LLC -AI12363,AI Research Scientist,71946,EUR,61154,MI,FT,Netherlands,S,Turkey,100,"Spark, Hadoop, TensorFlow, MLOps",Master,3,Healthcare,2024-08-14,2024-10-03,1113,7.5,Quantum Computing Inc -AI12364,NLP Engineer,93601,EUR,79561,MI,PT,France,L,France,50,"Python, GCP, Kubernetes, TensorFlow, Git",Master,2,Telecommunications,2025-01-18,2025-02-19,986,5.6,Predictive Systems -AI12365,Autonomous Systems Engineer,96130,CAD,120163,SE,FL,Canada,M,Canada,50,"Scala, AWS, Tableau, TensorFlow, Spark",Bachelor,7,Transportation,2024-08-16,2024-09-13,547,5.1,Neural Networks Co -AI12366,AI Consultant,62895,CAD,78619,EN,FT,Canada,L,Canada,0,"Hadoop, SQL, TensorFlow, Python",Associate,0,Telecommunications,2025-04-07,2025-05-17,903,7.6,Predictive Systems -AI12367,ML Ops Engineer,71053,USD,71053,EN,FT,Finland,M,Finland,50,"Scala, Java, GCP, Spark",Bachelor,1,Finance,2024-04-25,2024-05-17,626,5.2,Algorithmic Solutions -AI12368,Data Scientist,235335,USD,235335,EX,CT,Ireland,M,Ireland,100,"Scala, R, NLP",PhD,10,Finance,2024-12-12,2025-01-02,826,7.7,Neural Networks Co -AI12369,Data Analyst,189502,EUR,161077,EX,CT,Austria,S,Australia,50,"Hadoop, PyTorch, SQL, GCP",Bachelor,15,Finance,2025-02-24,2025-04-25,2412,8.9,Algorithmic Solutions -AI12370,Deep Learning Engineer,60818,USD,60818,SE,FT,China,M,China,50,"Scala, Data Visualization, SQL, TensorFlow",PhD,7,Education,2024-11-13,2024-12-05,1109,6.7,Quantum Computing Inc -AI12371,Data Analyst,139977,EUR,118980,SE,CT,Netherlands,L,Norway,50,"Java, GCP, Azure, Tableau, AWS",PhD,5,Energy,2024-02-25,2024-03-24,1555,6,DeepTech Ventures -AI12372,Autonomous Systems Engineer,305019,GBP,228764,EX,FT,United Kingdom,L,United Kingdom,0,"Kubernetes, Spark, Python, Java",PhD,19,Gaming,2024-08-06,2024-08-24,907,6.5,Autonomous Tech -AI12373,AI Architect,74292,EUR,63148,MI,FT,Austria,M,Philippines,0,"Python, Mathematics, PyTorch, SQL, Deep Learning",Associate,3,Finance,2025-02-24,2025-04-25,2408,8.3,Cloud AI Solutions -AI12374,ML Ops Engineer,65497,USD,65497,EN,FL,Finland,L,Finland,0,"Linux, Deep Learning, Python, Mathematics, Git",PhD,1,Media,2024-11-18,2025-01-05,1132,9.1,Advanced Robotics -AI12375,Principal Data Scientist,17450,USD,17450,EN,FT,India,S,India,50,"MLOps, Azure, Git",Bachelor,0,Real Estate,2024-12-03,2025-02-13,517,6.4,Neural Networks Co -AI12376,Machine Learning Engineer,56393,CAD,70491,EN,FL,Canada,S,Canada,100,"R, Tableau, Docker",Bachelor,0,Real Estate,2024-08-28,2024-10-25,2498,6.7,Algorithmic Solutions -AI12377,Machine Learning Researcher,28903,USD,28903,EN,FT,India,L,India,0,"Python, Deep Learning, Computer Vision",Associate,0,Finance,2025-03-14,2025-05-09,2425,5.8,Cognitive Computing -AI12378,Machine Learning Researcher,204225,JPY,22464750,EX,FL,Japan,M,Japan,100,"NLP, SQL, PyTorch",Bachelor,14,Manufacturing,2025-02-25,2025-03-16,735,9.2,Neural Networks Co -AI12379,Head of AI,182487,EUR,155114,EX,CT,Austria,M,Italy,100,"Python, PyTorch, Linux, Java, GCP",Associate,13,Consulting,2024-03-12,2024-04-02,891,6.2,AI Innovations -AI12380,Robotics Engineer,122104,USD,122104,SE,PT,United States,M,South Africa,50,"R, Data Visualization, Linux",PhD,8,Transportation,2024-05-09,2024-05-30,933,5.6,Neural Networks Co -AI12381,Data Engineer,107231,USD,107231,SE,CT,Sweden,S,Sweden,100,"Git, Kubernetes, PyTorch",Bachelor,9,Telecommunications,2024-06-15,2024-08-14,643,9.2,Quantum Computing Inc -AI12382,Deep Learning Engineer,37458,USD,37458,MI,PT,India,M,Czech Republic,50,"Tableau, Hadoop, Java, Azure",Bachelor,4,Consulting,2024-12-02,2024-12-22,1953,5.2,AI Innovations -AI12383,AI Architect,145761,USD,145761,EX,CT,Israel,S,Israel,100,"Java, Statistics, Python, Tableau",Master,13,Media,2024-06-05,2024-07-08,2475,9.1,Predictive Systems -AI12384,Data Engineer,200170,CHF,180153,EX,FL,Switzerland,S,Switzerland,0,"Git, PyTorch, Tableau, Data Visualization, Docker",Master,13,Manufacturing,2025-04-24,2025-06-27,780,5.6,Future Systems -AI12385,ML Ops Engineer,82455,CAD,103069,MI,PT,Canada,S,Canada,50,"Deep Learning, Git, MLOps",Bachelor,4,Retail,2024-01-29,2024-04-09,1588,6,AI Innovations -AI12386,Principal Data Scientist,77760,AUD,104976,EN,PT,Australia,M,Australia,50,"Hadoop, Mathematics, TensorFlow, R",PhD,1,Government,2024-05-01,2024-06-01,1392,8.5,Algorithmic Solutions -AI12387,AI Architect,142182,USD,142182,SE,FT,Finland,M,Finland,100,"Statistics, Kubernetes, Python, Computer Vision, TensorFlow",Associate,5,Government,2024-04-24,2024-05-10,853,9.9,Cloud AI Solutions -AI12388,Robotics Engineer,132350,USD,132350,SE,CT,Ireland,L,Ireland,100,"Data Visualization, Scala, Python, Azure",Associate,9,Real Estate,2025-01-28,2025-02-21,2147,8.2,Advanced Robotics -AI12389,Data Engineer,141077,USD,141077,SE,FL,South Korea,L,South Korea,100,"Docker, Linux, Spark, Deep Learning",Master,7,Government,2025-01-14,2025-02-13,1331,7.2,DeepTech Ventures -AI12390,Research Scientist,237360,CHF,213624,EX,FT,Switzerland,M,Switzerland,100,"MLOps, Statistics, Hadoop",Bachelor,13,Real Estate,2024-12-24,2025-01-21,1615,8.4,Future Systems -AI12391,Data Engineer,138254,JPY,15207940,EX,CT,Japan,S,Japan,50,"Spark, Kubernetes, Data Visualization, SQL",PhD,15,Healthcare,2024-11-01,2025-01-07,1803,9.5,TechCorp Inc -AI12392,AI Consultant,181342,EUR,154141,EX,FL,Netherlands,S,Netherlands,50,"Mathematics, PyTorch, Data Visualization, Scala, Spark",PhD,16,Technology,2025-03-11,2025-05-20,2346,6.8,Autonomous Tech -AI12393,Deep Learning Engineer,154049,JPY,16945390,SE,PT,Japan,M,Japan,100,"Git, Hadoop, Tableau",PhD,8,Healthcare,2024-04-27,2024-05-25,830,6.3,Advanced Robotics -AI12394,Machine Learning Researcher,57960,EUR,49266,EN,FT,Netherlands,S,Netherlands,0,"Python, Azure, Scala, Linux",Master,1,Education,2024-06-01,2024-07-07,1746,5.7,Machine Intelligence Group -AI12395,Principal Data Scientist,281214,USD,281214,EX,CT,Sweden,L,Russia,50,"Data Visualization, Tableau, Python",Bachelor,11,Manufacturing,2024-12-13,2025-01-05,775,8,Autonomous Tech -AI12396,ML Ops Engineer,78328,EUR,66579,EN,CT,Austria,L,Italy,100,"Linux, Scala, Azure, Statistics, Kubernetes",Associate,0,Transportation,2024-03-20,2024-04-12,662,6,Cloud AI Solutions -AI12397,Deep Learning Engineer,253374,CAD,316718,EX,FT,Canada,L,Canada,50,"SQL, Spark, Hadoop",Bachelor,16,Energy,2024-09-16,2024-10-24,1534,8.8,Algorithmic Solutions -AI12398,Autonomous Systems Engineer,168477,USD,168477,SE,CT,Norway,M,Norway,0,"Spark, Linux, PyTorch, SQL",Master,8,Gaming,2024-07-30,2024-08-24,1899,9.6,Autonomous Tech -AI12399,Machine Learning Engineer,87035,USD,87035,MI,FT,United States,S,United States,0,"Data Visualization, Computer Vision, Java, Spark, Statistics",PhD,3,Healthcare,2025-04-22,2025-06-14,2493,8.2,Future Systems -AI12400,AI Specialist,152751,SGD,198576,EX,FL,Singapore,S,Australia,50,"Azure, Scala, Python, TensorFlow, Spark",Associate,16,Energy,2024-02-06,2024-02-21,1240,8,DeepTech Ventures -AI12401,Data Engineer,92050,USD,92050,MI,FT,Sweden,S,Sweden,0,"Docker, MLOps, Python, R, Statistics",Bachelor,4,Automotive,2025-01-28,2025-02-16,1432,6.2,Autonomous Tech -AI12402,Data Scientist,55016,EUR,46764,EN,FT,France,M,Indonesia,0,"Statistics, Python, PyTorch",Associate,1,Retail,2024-06-07,2024-06-21,1512,9.1,Autonomous Tech -AI12403,Computer Vision Engineer,135145,GBP,101359,SE,PT,United Kingdom,M,United Kingdom,100,"AWS, Linux, TensorFlow",Associate,9,Consulting,2024-05-16,2024-06-04,711,10,DeepTech Ventures -AI12404,Head of AI,118429,GBP,88822,SE,CT,United Kingdom,S,Egypt,100,"Spark, Mathematics, Linux, Deep Learning, TensorFlow",Master,7,Consulting,2025-01-19,2025-03-13,995,8.6,Autonomous Tech -AI12405,NLP Engineer,57898,GBP,43424,EN,FL,United Kingdom,M,United Kingdom,50,"Java, Spark, Tableau, MLOps",Master,0,Energy,2024-02-16,2024-03-25,717,7.3,Quantum Computing Inc -AI12406,AI Architect,51180,EUR,43503,EN,CT,Austria,S,Italy,0,"Python, NLP, Data Visualization",Associate,0,Media,2024-11-22,2024-12-06,698,5.5,Quantum Computing Inc -AI12407,Data Scientist,103458,USD,103458,EX,PT,India,L,India,0,"AWS, Docker, Spark, Java, Tableau",Master,19,Media,2024-06-16,2024-08-12,2212,5.5,Future Systems -AI12408,Data Scientist,102748,USD,102748,EX,CT,China,L,China,0,"AWS, Azure, PyTorch, Scala",Bachelor,10,Finance,2025-02-08,2025-04-08,1986,8.1,Smart Analytics -AI12409,Data Analyst,151467,USD,151467,SE,PT,Ireland,M,Ireland,0,"Statistics, TensorFlow, NLP, Mathematics, Java",Bachelor,8,Real Estate,2024-03-12,2024-04-02,1772,9.7,Cognitive Computing -AI12410,Data Scientist,74836,USD,74836,MI,PT,South Korea,M,Singapore,100,"Statistics, NLP, GCP",Associate,2,Telecommunications,2024-08-19,2024-09-23,571,8.7,Neural Networks Co -AI12411,Machine Learning Engineer,169620,EUR,144177,EX,CT,Netherlands,S,Hungary,100,"Java, Git, Hadoop, Docker",PhD,14,Education,2024-10-07,2024-12-17,2161,6,Cognitive Computing -AI12412,AI Software Engineer,113721,CHF,102349,EN,CT,Switzerland,L,Russia,100,"Java, Python, Statistics, Azure",PhD,1,Automotive,2025-03-08,2025-04-10,2083,8.3,Cognitive Computing -AI12413,Head of AI,127743,CHF,114969,MI,FT,Switzerland,S,Austria,0,"SQL, Mathematics, NLP, Spark, Python",PhD,4,Consulting,2024-11-21,2024-12-07,527,8.6,Quantum Computing Inc -AI12414,Principal Data Scientist,305463,USD,305463,EX,FL,Norway,M,Belgium,50,"Scala, Linux, Computer Vision, Tableau, Java",PhD,13,Media,2024-11-13,2024-12-16,1809,5.9,DataVision Ltd -AI12415,AI Specialist,75828,USD,75828,SE,FT,South Korea,S,Indonesia,100,"Scala, GCP, Spark, Java, Mathematics",PhD,6,Education,2024-03-12,2024-04-26,909,8.5,DeepTech Ventures -AI12416,Data Scientist,116542,GBP,87407,SE,FT,United Kingdom,S,United Kingdom,0,"Docker, Linux, AWS, GCP",Master,7,Technology,2024-05-31,2024-07-31,749,5.4,Machine Intelligence Group -AI12417,Deep Learning Engineer,53985,USD,53985,EN,CT,Finland,M,Finland,0,"Java, Tableau, SQL, GCP",Master,0,Retail,2024-05-19,2024-07-09,1864,5.6,Machine Intelligence Group -AI12418,Computer Vision Engineer,60582,EUR,51495,EN,FT,Netherlands,S,Netherlands,100,"Python, Kubernetes, PyTorch, MLOps",Associate,1,Media,2024-04-10,2024-05-02,2394,6.1,Cognitive Computing -AI12419,Machine Learning Engineer,135425,USD,135425,SE,FL,Norway,S,Norway,100,"PyTorch, Linux, Java, R, Git",Associate,6,Energy,2024-07-24,2024-10-04,1969,5.9,Neural Networks Co -AI12420,AI Specialist,62590,JPY,6884900,EN,CT,Japan,L,Japan,100,"Kubernetes, Java, Hadoop",Bachelor,0,Technology,2024-01-07,2024-02-26,2155,9.5,Smart Analytics -AI12421,AI Architect,231935,GBP,173951,EX,PT,United Kingdom,S,United Kingdom,0,"Scala, Spark, R",Bachelor,11,Retail,2024-03-18,2024-05-29,1567,8.6,Neural Networks Co -AI12422,Machine Learning Researcher,71430,USD,71430,EN,FL,Norway,S,Singapore,0,"Python, Statistics, Data Visualization, AWS",Associate,0,Education,2024-03-30,2024-06-01,1777,6.7,Advanced Robotics -AI12423,Computer Vision Engineer,220600,EUR,187510,EX,FT,France,L,France,0,"Java, TensorFlow, Statistics, Computer Vision",PhD,10,Healthcare,2024-10-19,2024-12-04,1423,9.7,Predictive Systems -AI12424,Head of AI,82694,USD,82694,EN,FT,Norway,S,Norway,50,"Python, Mathematics, Azure",Bachelor,1,Gaming,2024-04-06,2024-05-10,1192,9.6,DeepTech Ventures -AI12425,Robotics Engineer,123932,USD,123932,MI,PT,Sweden,L,Belgium,100,"Python, PyTorch, GCP",Master,3,Education,2024-10-30,2024-12-07,1401,6.8,Smart Analytics -AI12426,AI Consultant,137592,EUR,116953,SE,FT,Germany,M,Germany,100,"Kubernetes, AWS, Data Visualization",Associate,7,Automotive,2025-01-18,2025-03-07,1087,9.8,Predictive Systems -AI12427,Machine Learning Engineer,57950,USD,57950,EN,FL,South Korea,S,South Korea,100,"Tableau, Scala, Python, Deep Learning",PhD,1,Energy,2025-03-05,2025-04-08,2003,8.6,Neural Networks Co -AI12428,AI Architect,126435,USD,126435,SE,FT,Israel,S,Israel,0,"PyTorch, SQL, Linux",Bachelor,5,Real Estate,2024-12-21,2025-02-08,2132,5.6,Algorithmic Solutions -AI12429,Machine Learning Researcher,128267,JPY,14109370,SE,CT,Japan,M,Japan,50,"PyTorch, GCP, TensorFlow, Azure, Python",Bachelor,8,Transportation,2025-04-10,2025-05-17,2324,5.4,Autonomous Tech -AI12430,AI Research Scientist,309048,SGD,401762,EX,PT,Singapore,L,Singapore,50,"MLOps, Data Visualization, Java, Linux, R",PhD,12,Finance,2025-04-07,2025-05-31,1545,8.1,Neural Networks Co -AI12431,Data Analyst,134105,JPY,14751550,SE,FL,Japan,L,Japan,0,"Python, MLOps, Spark, NLP, Kubernetes",Bachelor,6,Education,2024-03-17,2024-05-23,2363,10,DeepTech Ventures -AI12432,AI Software Engineer,84521,USD,84521,MI,FT,Israel,S,Israel,0,"GCP, AWS, NLP, Python, Spark",PhD,4,Retail,2024-02-20,2024-04-29,1050,8.6,Smart Analytics -AI12433,Research Scientist,61395,SGD,79814,EN,CT,Singapore,M,Singapore,50,"Statistics, Tableau, NLP",Master,1,Real Estate,2024-04-29,2024-07-05,1577,9.7,Machine Intelligence Group -AI12434,NLP Engineer,152906,USD,152906,SE,CT,Norway,S,Norway,50,"R, GCP, Computer Vision, Linux",Master,6,Technology,2025-04-27,2025-06-19,2345,6.9,TechCorp Inc -AI12435,AI Research Scientist,150492,USD,150492,EX,FT,Israel,S,Switzerland,50,"Linux, TensorFlow, SQL, Deep Learning",Bachelor,18,Transportation,2024-10-24,2024-11-26,2445,5.1,DataVision Ltd -AI12436,Head of AI,261388,SGD,339804,EX,FT,Singapore,M,Singapore,0,"Java, Python, NLP, Docker",Master,10,Healthcare,2025-02-23,2025-04-23,1326,8.3,AI Innovations -AI12437,AI Software Engineer,181176,USD,181176,EX,CT,Finland,S,South Africa,50,"Computer Vision, Linux, Hadoop, Kubernetes, Scala",Bachelor,11,Real Estate,2024-11-22,2025-01-08,1295,6.7,Cognitive Computing -AI12438,Robotics Engineer,185060,EUR,157301,EX,FT,Germany,M,Germany,100,"R, Spark, SQL, Mathematics, Java",Bachelor,12,Media,2024-07-13,2024-08-14,1670,7.3,Neural Networks Co -AI12439,Data Scientist,128763,SGD,167392,SE,PT,Singapore,L,Singapore,100,"Python, Statistics, PyTorch, Spark",Associate,5,Education,2024-11-10,2024-12-24,1042,9,Cloud AI Solutions -AI12440,AI Software Engineer,125753,USD,125753,MI,FL,Denmark,M,Malaysia,50,"Scala, R, Kubernetes, Git, Python",Master,3,Education,2024-11-24,2024-12-11,2160,6.6,Neural Networks Co -AI12441,Data Scientist,121075,USD,121075,SE,FT,Israel,S,Israel,0,"PyTorch, Scala, Deep Learning, MLOps",PhD,6,Consulting,2024-12-24,2025-01-29,1737,5.8,Autonomous Tech -AI12442,ML Ops Engineer,27334,USD,27334,EN,CT,India,M,India,0,"Kubernetes, PyTorch, Statistics, Computer Vision, TensorFlow",PhD,1,Education,2025-04-01,2025-06-09,1734,8.9,Quantum Computing Inc -AI12443,Computer Vision Engineer,234245,CHF,210821,SE,FT,Switzerland,L,Egypt,50,"PyTorch, SQL, Git, Statistics, GCP",Associate,5,Media,2024-02-08,2024-04-13,2405,9.8,DataVision Ltd -AI12444,AI Software Engineer,79787,USD,79787,EN,FT,Norway,S,Norway,50,"TensorFlow, Tableau, AWS, MLOps",Associate,0,Government,2025-04-27,2025-06-17,695,6.3,Algorithmic Solutions -AI12445,Head of AI,46395,USD,46395,EN,FT,Sweden,S,Sweden,100,"PyTorch, Java, Git, Azure",Bachelor,0,Manufacturing,2024-10-19,2024-12-23,1792,5.6,Cognitive Computing -AI12446,AI Consultant,82377,EUR,70020,EN,CT,Austria,L,Poland,50,"TensorFlow, Python, Tableau",Bachelor,0,Healthcare,2024-02-20,2024-05-02,1384,7.5,Smart Analytics -AI12447,Machine Learning Engineer,63540,CAD,79425,EN,CT,Canada,M,Canada,0,"SQL, NLP, Kubernetes, Git",Associate,0,Energy,2024-12-19,2025-01-08,1756,6.7,Advanced Robotics -AI12448,NLP Engineer,90047,USD,90047,EX,PT,China,M,China,100,"SQL, Deep Learning, Spark, R, Tableau",Bachelor,18,Telecommunications,2025-04-22,2025-06-01,1548,9.9,Predictive Systems -AI12449,Head of AI,108278,USD,108278,SE,PT,Sweden,M,Sweden,50,"PyTorch, Git, Mathematics, Scala",Bachelor,5,Manufacturing,2024-05-13,2024-05-31,1662,8.1,Cognitive Computing -AI12450,Machine Learning Engineer,255205,JPY,28072550,EX,CT,Japan,L,Japan,100,"R, Mathematics, Linux",Bachelor,17,Technology,2024-09-12,2024-10-16,1755,5.2,Algorithmic Solutions -AI12451,Machine Learning Engineer,63780,USD,63780,SE,PT,China,M,China,100,"PyTorch, Computer Vision, Tableau",Associate,8,Energy,2024-08-13,2024-10-04,1419,6.3,Predictive Systems -AI12452,Machine Learning Researcher,57335,GBP,43001,EN,FT,United Kingdom,S,Belgium,50,"Git, Mathematics, MLOps, Deep Learning, R",PhD,0,Retail,2024-01-31,2024-03-11,814,10,Neural Networks Co -AI12453,AI Consultant,68846,USD,68846,EN,PT,Finland,M,Finland,50,"Scala, Tableau, Deep Learning",PhD,1,Gaming,2025-02-18,2025-03-12,2445,7.5,DataVision Ltd -AI12454,Autonomous Systems Engineer,127642,EUR,108496,SE,CT,Netherlands,L,India,50,"MLOps, TensorFlow, AWS, Hadoop",Master,6,Technology,2025-04-24,2025-07-04,1015,7.5,Machine Intelligence Group -AI12455,Data Engineer,119425,USD,119425,SE,PT,Ireland,M,Nigeria,0,"Hadoop, Python, MLOps",Associate,9,Education,2025-04-15,2025-05-14,1732,5.9,Advanced Robotics -AI12456,Data Scientist,29224,USD,29224,EN,PT,China,S,China,0,"Data Visualization, Scala, Kubernetes, SQL, R",Associate,0,Finance,2024-12-08,2024-12-28,2189,9.1,Predictive Systems -AI12457,Computer Vision Engineer,198486,EUR,168713,EX,PT,Austria,M,Austria,100,"TensorFlow, Azure, NLP, Computer Vision",Associate,13,Telecommunications,2024-07-25,2024-09-25,1275,8.2,Advanced Robotics -AI12458,Machine Learning Engineer,203533,CHF,183180,EX,FT,Switzerland,S,Switzerland,0,"GCP, SQL, PyTorch, Kubernetes, Statistics",Bachelor,14,Technology,2025-04-24,2025-05-20,696,6.6,TechCorp Inc -AI12459,AI Product Manager,194939,EUR,165698,EX,FL,France,L,France,50,"Linux, Mathematics, NLP, PyTorch",Bachelor,10,Telecommunications,2024-03-26,2024-05-07,1719,6.7,Algorithmic Solutions -AI12460,Data Analyst,61708,EUR,52452,EN,PT,Germany,S,Germany,50,"Hadoop, Python, Git",Bachelor,1,Manufacturing,2024-05-22,2024-06-14,629,7.5,DataVision Ltd -AI12461,AI Research Scientist,100793,USD,100793,MI,FL,Ireland,L,Ireland,50,"Linux, Hadoop, R, Computer Vision, Statistics",Master,4,Gaming,2024-05-29,2024-08-09,2070,9,Advanced Robotics -AI12462,AI Architect,75694,GBP,56771,EN,PT,United Kingdom,M,Austria,0,"Statistics, PyTorch, Docker, Azure, SQL",Associate,0,Manufacturing,2025-01-06,2025-02-11,2171,8.3,Cognitive Computing -AI12463,Data Scientist,115446,EUR,98129,MI,FL,Netherlands,L,Netherlands,50,"Docker, Python, Deep Learning, Spark",Associate,2,Transportation,2024-07-21,2024-08-23,2121,7.9,Smart Analytics -AI12464,Research Scientist,49167,EUR,41792,EN,FT,Austria,S,Austria,100,"R, Mathematics, Hadoop",Associate,0,Automotive,2024-07-10,2024-08-10,614,8.4,DataVision Ltd -AI12465,AI Product Manager,70180,USD,70180,EN,FL,Sweden,S,Sweden,0,"Docker, R, Deep Learning, SQL",Master,1,Government,2024-03-23,2024-05-12,580,7.5,DeepTech Ventures -AI12466,Data Analyst,19503,USD,19503,EN,CT,India,S,India,0,"PyTorch, Azure, R, SQL",Bachelor,0,Education,2025-03-12,2025-03-26,2448,5.9,Digital Transformation LLC -AI12467,Data Engineer,92958,USD,92958,SE,FT,South Korea,M,South Korea,0,"Azure, SQL, Kubernetes, Spark, Linux",Associate,7,Government,2024-03-19,2024-04-03,1193,6.8,AI Innovations -AI12468,ML Ops Engineer,46075,USD,46075,EX,CT,India,S,India,50,"Scala, NLP, Git",Bachelor,17,Media,2024-10-06,2024-11-30,1655,10,Algorithmic Solutions -AI12469,Data Engineer,31356,USD,31356,MI,FT,China,S,China,0,"Mathematics, Python, Tableau, Computer Vision, SQL",Bachelor,4,Real Estate,2025-03-05,2025-04-06,857,7.5,AI Innovations -AI12470,Data Engineer,169277,EUR,143885,EX,FL,Austria,M,Vietnam,0,"SQL, Git, PyTorch, NLP",Master,12,Media,2024-08-17,2024-10-27,664,7.8,Smart Analytics -AI12471,Machine Learning Engineer,34533,USD,34533,MI,CT,China,M,China,100,"AWS, Tableau, TensorFlow, Spark",PhD,3,Government,2024-04-18,2024-05-15,1855,8.2,DataVision Ltd -AI12472,Deep Learning Engineer,72285,JPY,7951350,EN,FL,Japan,S,Japan,50,"Linux, MLOps, Git, Java",PhD,0,Healthcare,2024-09-24,2024-10-28,1564,7.9,Machine Intelligence Group -AI12473,Machine Learning Researcher,212718,USD,212718,EX,CT,Finland,S,Finland,50,"SQL, Python, Hadoop, Mathematics, Computer Vision",PhD,17,Education,2025-04-05,2025-06-06,2270,8.6,Machine Intelligence Group -AI12474,Machine Learning Engineer,202624,EUR,172230,EX,CT,France,S,France,50,"PyTorch, Hadoop, TensorFlow, SQL",PhD,16,Finance,2024-12-30,2025-01-13,1686,7.2,Machine Intelligence Group -AI12475,ML Ops Engineer,71740,USD,71740,MI,CT,South Korea,L,South Korea,50,"SQL, AWS, Computer Vision, Spark, Linux",Associate,3,Automotive,2025-04-06,2025-05-13,756,9.9,Cloud AI Solutions -AI12476,Autonomous Systems Engineer,232339,CHF,209105,EX,CT,Switzerland,L,Switzerland,0,"AWS, Python, Kubernetes",Master,18,Retail,2024-12-07,2025-01-25,1266,7.2,AI Innovations -AI12477,Machine Learning Engineer,147817,USD,147817,EX,CT,Israel,S,India,0,"Scala, R, SQL",Bachelor,15,Telecommunications,2024-12-13,2025-01-18,1399,6.3,Future Systems -AI12478,Data Engineer,73011,EUR,62059,MI,PT,Germany,S,Germany,50,"SQL, Scala, Tableau",Associate,3,Education,2024-11-22,2024-12-16,1245,7.3,Cognitive Computing -AI12479,ML Ops Engineer,69151,USD,69151,EN,CT,Israel,M,Israel,100,"PyTorch, Python, Statistics",PhD,0,Technology,2024-06-09,2024-08-07,1621,6.5,Digital Transformation LLC -AI12480,Machine Learning Engineer,200050,CHF,180045,SE,FL,Switzerland,M,Switzerland,50,"Kubernetes, Scala, Data Visualization, Statistics, Git",Associate,5,Transportation,2024-05-24,2024-07-16,982,5.5,Autonomous Tech -AI12481,Data Engineer,68571,AUD,92571,MI,FL,Australia,S,Romania,0,"MLOps, Azure, Tableau",Bachelor,3,Consulting,2025-04-10,2025-05-15,578,9.6,DataVision Ltd -AI12482,AI Specialist,27494,USD,27494,EN,FL,China,S,Brazil,50,"Python, Azure, Git, R, Computer Vision",PhD,0,Finance,2024-10-05,2024-11-07,1180,9.1,Cloud AI Solutions -AI12483,AI Research Scientist,54178,USD,54178,SE,CT,China,M,United States,100,"Linux, Scala, PyTorch",PhD,5,Healthcare,2025-04-02,2025-05-31,1625,7.5,Advanced Robotics -AI12484,Robotics Engineer,147943,USD,147943,SE,CT,Denmark,M,Denmark,0,"GCP, Python, Mathematics, Linux",Bachelor,9,Finance,2025-03-19,2025-04-15,1829,6.6,Cloud AI Solutions -AI12485,Research Scientist,246165,CHF,221549,SE,FT,Switzerland,L,Switzerland,50,"Deep Learning, Data Visualization, Docker",Associate,8,Transportation,2024-08-13,2024-09-19,1412,6.4,DataVision Ltd -AI12486,Autonomous Systems Engineer,31203,USD,31203,MI,FT,India,M,India,50,"Data Visualization, SQL, Scala, Tableau, Git",Bachelor,2,Energy,2024-02-27,2024-04-03,1073,5.4,Digital Transformation LLC -AI12487,Head of AI,109051,USD,109051,SE,PT,South Korea,S,South Korea,100,"Scala, AWS, Python",Master,7,Technology,2024-11-09,2024-12-11,1828,7.7,DataVision Ltd -AI12488,AI Consultant,76767,EUR,65252,EN,FL,Netherlands,M,Romania,100,"Tableau, Scala, Docker",Associate,0,Transportation,2024-08-22,2024-10-22,1011,5.9,TechCorp Inc -AI12489,Computer Vision Engineer,64846,GBP,48635,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Scala, TensorFlow",Master,0,Gaming,2024-10-08,2024-12-06,621,6.9,TechCorp Inc -AI12490,Data Engineer,126205,AUD,170377,SE,FT,Australia,L,Australia,100,"Spark, Linux, GCP",Associate,7,Real Estate,2024-01-19,2024-03-08,2036,6.5,Future Systems -AI12491,Data Engineer,162483,USD,162483,MI,PT,Norway,L,Norway,100,"Java, Statistics, R, Docker, Scala",Master,3,Consulting,2024-12-17,2025-02-02,1825,8.3,DeepTech Ventures -AI12492,Machine Learning Engineer,77554,USD,77554,MI,CT,Israel,S,Israel,50,"Azure, AWS, TensorFlow, Linux, Mathematics",Master,3,Education,2024-10-26,2024-11-30,807,5.5,Algorithmic Solutions -AI12493,AI Product Manager,216415,JPY,23805650,EX,FT,Japan,L,Japan,0,"Scala, Python, Hadoop, Git",Master,14,Transportation,2024-01-20,2024-02-15,1804,7.5,Future Systems -AI12494,AI Architect,130182,EUR,110655,SE,FL,Germany,S,Germany,50,"SQL, TensorFlow, GCP",Bachelor,9,Education,2025-03-27,2025-05-17,662,5.9,Machine Intelligence Group -AI12495,Data Scientist,187797,SGD,244136,EX,FL,Singapore,S,Singapore,100,"R, MLOps, Kubernetes, Statistics, Deep Learning",PhD,18,Healthcare,2024-06-30,2024-09-03,799,5.2,Advanced Robotics -AI12496,AI Software Engineer,123365,USD,123365,MI,FL,Ireland,L,Ireland,100,"Kubernetes, Mathematics, TensorFlow, AWS",Associate,4,Manufacturing,2025-01-20,2025-03-24,1723,5.6,Quantum Computing Inc -AI12497,Data Analyst,69926,EUR,59437,EN,FT,Austria,L,Austria,50,"GCP, MLOps, Statistics",Master,1,Real Estate,2024-04-23,2024-06-20,2381,7.5,Cognitive Computing -AI12498,AI Architect,80574,GBP,60431,EN,FT,United Kingdom,M,Poland,50,"Python, Deep Learning, Kubernetes",Associate,0,Finance,2024-07-31,2024-08-23,2300,6.7,Neural Networks Co -AI12499,Computer Vision Engineer,80148,USD,80148,EN,CT,United States,S,United States,50,"Kubernetes, TensorFlow, Computer Vision, Hadoop, Linux",PhD,1,Transportation,2024-10-28,2024-12-23,1220,6.7,DataVision Ltd -AI12500,Machine Learning Engineer,270850,EUR,230223,EX,CT,Germany,L,Indonesia,100,"Statistics, Python, Data Visualization, Scala",Associate,11,Gaming,2025-02-04,2025-03-09,1919,9.5,Neural Networks Co -AI12501,Deep Learning Engineer,160933,CHF,144840,SE,CT,Switzerland,M,Switzerland,100,"Docker, R, Mathematics, Spark, Azure",PhD,7,Energy,2024-03-19,2024-04-19,2404,8,DataVision Ltd -AI12502,Machine Learning Researcher,165119,USD,165119,EX,FT,Ireland,M,Ireland,0,"Data Visualization, Hadoop, Python, Linux",Bachelor,16,Energy,2024-02-05,2024-02-27,709,5.5,Cognitive Computing -AI12503,Deep Learning Engineer,145099,EUR,123334,SE,PT,Germany,L,Germany,50,"GCP, Linux, Tableau, Spark, Data Visualization",Master,7,Media,2025-03-11,2025-05-07,717,6.9,Smart Analytics -AI12504,NLP Engineer,51742,JPY,5691620,EN,FL,Japan,S,Japan,100,"Kubernetes, Python, Data Visualization, Git",PhD,1,Education,2024-02-28,2024-03-19,1536,8.3,Autonomous Tech -AI12505,AI Software Engineer,109327,USD,109327,SE,CT,Sweden,M,Sweden,50,"Docker, MLOps, AWS",PhD,9,Consulting,2024-07-03,2024-07-24,1297,9,DataVision Ltd -AI12506,AI Specialist,151570,CHF,136413,MI,PT,Switzerland,M,Switzerland,100,"Tableau, Kubernetes, TensorFlow, Spark",Master,2,Government,2024-05-27,2024-07-18,2059,7.2,Advanced Robotics -AI12507,Deep Learning Engineer,214037,USD,214037,EX,PT,Sweden,S,Sweden,0,"Mathematics, Computer Vision, Linux",Master,19,Government,2024-03-18,2024-04-11,1865,9.1,Advanced Robotics -AI12508,AI Product Manager,238972,USD,238972,EX,CT,Finland,L,Finland,0,"GCP, Hadoop, Tableau, Deep Learning",Master,18,Healthcare,2024-01-10,2024-02-29,1350,9.8,Predictive Systems -AI12509,Data Analyst,120788,EUR,102670,SE,PT,Germany,L,Germany,50,"Spark, Linux, Deep Learning, Git, TensorFlow",Associate,7,Retail,2024-07-24,2024-09-15,606,8.3,Cognitive Computing -AI12510,AI Product Manager,161084,USD,161084,SE,FT,United States,L,Spain,0,"Linux, Tableau, Data Visualization, Hadoop",Bachelor,7,Telecommunications,2024-01-23,2024-03-16,1681,8,Future Systems -AI12511,AI Specialist,224471,CAD,280589,EX,PT,Canada,M,Canada,100,"SQL, NLP, Azure",Master,17,Government,2024-12-04,2025-02-02,2031,5.4,Neural Networks Co -AI12512,Robotics Engineer,162992,AUD,220039,SE,CT,Australia,L,South Korea,100,"R, NLP, Linux, SQL",Bachelor,8,Government,2024-08-22,2024-09-27,746,6.8,Future Systems -AI12513,Data Analyst,30696,USD,30696,EN,CT,China,S,Portugal,0,"GCP, NLP, Linux, R",Master,0,Media,2024-10-08,2024-11-14,1377,9.1,Algorithmic Solutions -AI12514,Research Scientist,98339,EUR,83588,SE,CT,Austria,M,Austria,0,"PyTorch, R, TensorFlow",Associate,5,Retail,2025-03-28,2025-06-07,1314,5.7,Neural Networks Co -AI12515,Research Scientist,129262,EUR,109873,SE,CT,Austria,M,Austria,0,"Python, Azure, Docker, R, Git",PhD,7,Energy,2024-01-08,2024-02-05,2298,8.5,Autonomous Tech -AI12516,Machine Learning Engineer,112931,CAD,141164,SE,PT,Canada,L,Canada,0,"Python, Tableau, Docker",Associate,8,Consulting,2024-12-14,2025-01-25,2110,6.5,Cognitive Computing -AI12517,AI Product Manager,109950,USD,109950,MI,FT,Ireland,L,Estonia,0,"Azure, AWS, Linux, Docker",Associate,3,Media,2024-07-25,2024-09-12,1158,8.2,Autonomous Tech -AI12518,Computer Vision Engineer,84503,EUR,71828,EN,FT,Germany,L,Germany,0,"R, Linux, NLP",PhD,1,Gaming,2024-04-19,2024-06-20,1765,5.6,Smart Analytics -AI12519,Principal Data Scientist,89243,USD,89243,MI,FL,Sweden,M,South Africa,100,"Azure, Data Visualization, Kubernetes, Docker",PhD,3,Retail,2024-11-09,2024-12-14,592,8,Predictive Systems -AI12520,Data Analyst,194683,CHF,175215,SE,FL,Switzerland,M,Switzerland,100,"Hadoop, SQL, Linux, Scala",PhD,8,Real Estate,2024-03-03,2024-05-11,2107,7.7,Autonomous Tech -AI12521,Data Scientist,34111,USD,34111,MI,PT,China,S,China,50,"Statistics, AWS, R",Master,2,Telecommunications,2024-08-10,2024-09-03,870,6.5,AI Innovations -AI12522,NLP Engineer,104286,SGD,135572,MI,PT,Singapore,L,Singapore,100,"MLOps, Docker, Java, Spark",PhD,4,Finance,2024-04-19,2024-06-07,2023,8.2,Cognitive Computing -AI12523,Research Scientist,87236,EUR,74151,MI,FL,Germany,M,Germany,100,"Java, Hadoop, Python, Spark, TensorFlow",Associate,3,Technology,2024-02-23,2024-04-13,1927,9.6,DataVision Ltd -AI12524,Head of AI,61002,EUR,51852,EN,PT,Germany,L,Germany,50,"Computer Vision, Kubernetes, Hadoop",Master,1,Media,2024-07-14,2024-07-31,2002,5.9,Advanced Robotics -AI12525,Autonomous Systems Engineer,131108,GBP,98331,MI,FL,United Kingdom,L,United Kingdom,100,"AWS, MLOps, Tableau",PhD,3,Government,2024-02-18,2024-04-21,1902,5.8,TechCorp Inc -AI12526,NLP Engineer,109470,GBP,82103,MI,PT,United Kingdom,L,Egypt,100,"Python, TensorFlow, Statistics",Master,3,Media,2025-03-03,2025-05-01,1242,6.5,Autonomous Tech -AI12527,AI Consultant,63355,GBP,47516,EN,FT,United Kingdom,S,United Kingdom,50,"PyTorch, Linux, Python, Scala",Bachelor,0,Healthcare,2024-07-12,2024-09-09,1354,9.1,DataVision Ltd -AI12528,Data Engineer,199949,EUR,169957,EX,PT,Austria,M,Austria,50,"Git, Spark, GCP",Master,17,Retail,2024-08-30,2024-11-10,1410,8.9,TechCorp Inc -AI12529,Principal Data Scientist,59401,CAD,74251,EN,FL,Canada,S,Portugal,50,"Git, SQL, Scala",PhD,0,Energy,2024-04-27,2024-05-16,2043,9.9,Algorithmic Solutions -AI12530,Head of AI,100922,USD,100922,MI,PT,South Korea,L,South Korea,100,"Python, Git, SQL, Java, Computer Vision",PhD,3,Real Estate,2024-12-21,2025-02-20,2101,8,Machine Intelligence Group -AI12531,Data Analyst,64014,USD,64014,EN,FT,Israel,M,Israel,50,"SQL, PyTorch, Computer Vision, Git",Master,1,Finance,2024-08-01,2024-08-16,2168,8.9,Predictive Systems -AI12532,AI Consultant,164409,AUD,221952,SE,CT,Australia,L,Canada,0,"Kubernetes, PyTorch, Mathematics, SQL, Tableau",Master,6,Gaming,2024-08-30,2024-11-01,2111,7.2,Digital Transformation LLC -AI12533,NLP Engineer,214487,EUR,182314,EX,FL,France,M,France,100,"Kubernetes, SQL, PyTorch",Master,11,Government,2024-09-29,2024-11-04,1748,8.5,Cloud AI Solutions -AI12534,Autonomous Systems Engineer,133642,USD,133642,MI,PT,Norway,L,Norway,100,"Scala, Statistics, Spark",Master,4,Manufacturing,2024-05-25,2024-07-13,850,7.5,Predictive Systems -AI12535,AI Software Engineer,93357,USD,93357,EN,CT,United States,L,United States,0,"Computer Vision, NLP, Tableau, Python",PhD,1,Healthcare,2024-06-28,2024-08-07,1914,7.6,TechCorp Inc -AI12536,Robotics Engineer,68512,USD,68512,SE,FL,China,M,China,0,"Linux, MLOps, AWS, Statistics",PhD,9,Technology,2024-12-11,2025-01-29,1339,8,Algorithmic Solutions -AI12537,AI Specialist,134492,USD,134492,MI,PT,Denmark,M,Denmark,50,"MLOps, GCP, Java, Hadoop",Master,4,Retail,2024-02-21,2024-03-23,2035,5.2,AI Innovations -AI12538,Autonomous Systems Engineer,131311,JPY,14444210,SE,CT,Japan,M,Vietnam,0,"Scala, R, Azure, Git, Kubernetes",Associate,5,Manufacturing,2024-08-10,2024-09-23,1940,8.9,DeepTech Ventures -AI12539,Principal Data Scientist,255914,GBP,191936,EX,PT,United Kingdom,M,South Korea,0,"Git, Kubernetes, NLP",PhD,15,Gaming,2025-01-29,2025-03-25,1748,7.6,Machine Intelligence Group -AI12540,ML Ops Engineer,49654,USD,49654,EN,FT,Ireland,S,Ireland,100,"Scala, Linux, SQL, Statistics",PhD,0,Real Estate,2024-04-14,2024-06-16,2019,7.4,Predictive Systems -AI12541,AI Architect,47136,USD,47136,EN,CT,Israel,S,Israel,0,"PyTorch, SQL, Docker, AWS, Linux",PhD,1,Technology,2024-05-06,2024-06-21,721,9,Quantum Computing Inc -AI12542,AI Research Scientist,42011,USD,42011,MI,FT,India,L,India,50,"Computer Vision, Java, Python, Azure, Git",Master,3,Real Estate,2024-01-15,2024-02-12,1652,8.1,DataVision Ltd -AI12543,AI Consultant,119147,USD,119147,MI,FL,Finland,L,Russia,100,"Java, PyTorch, MLOps, Hadoop, NLP",Associate,4,Consulting,2024-04-21,2024-05-23,1670,7.3,DeepTech Ventures -AI12544,ML Ops Engineer,98976,USD,98976,MI,CT,United States,S,Mexico,50,"Computer Vision, TensorFlow, Python, Git, R",Bachelor,2,Consulting,2024-10-22,2024-12-31,613,6.7,Smart Analytics -AI12545,Autonomous Systems Engineer,50267,EUR,42727,EN,FT,Germany,S,Philippines,100,"Spark, TensorFlow, Kubernetes, Java, Mathematics",Master,1,Real Estate,2025-04-25,2025-05-25,1081,8.6,Machine Intelligence Group -AI12546,Robotics Engineer,26722,USD,26722,EN,FT,China,S,China,0,"Git, SQL, R, GCP",Bachelor,0,Consulting,2024-10-13,2024-11-11,2251,6.1,Digital Transformation LLC -AI12547,ML Ops Engineer,131283,GBP,98462,SE,CT,United Kingdom,M,Thailand,50,"Tableau, TensorFlow, Docker, GCP, Scala",Bachelor,6,Telecommunications,2024-04-07,2024-05-30,2032,8.5,Cognitive Computing -AI12548,AI Product Manager,117952,SGD,153338,SE,FL,Singapore,M,France,50,"MLOps, SQL, Python, Computer Vision",PhD,5,Technology,2024-04-25,2024-06-10,2174,5.7,AI Innovations -AI12549,Deep Learning Engineer,25607,USD,25607,MI,PT,India,M,Ukraine,100,"PyTorch, Linux, Tableau, GCP",Bachelor,2,Media,2024-12-30,2025-01-17,518,6.9,Digital Transformation LLC -AI12550,Deep Learning Engineer,233172,USD,233172,EX,PT,United States,M,Netherlands,50,"SQL, Tableau, Deep Learning, Java",PhD,18,Telecommunications,2024-04-30,2024-06-19,802,6,TechCorp Inc -AI12551,Data Analyst,74780,AUD,100953,EN,PT,Australia,L,Australia,100,"AWS, GCP, Kubernetes",Bachelor,1,Consulting,2025-03-04,2025-03-24,1215,8.9,Quantum Computing Inc -AI12552,AI Research Scientist,166556,CHF,149900,SE,FT,Switzerland,L,Australia,0,"NLP, R, Scala",Bachelor,7,Finance,2024-09-15,2024-10-14,911,7.1,Advanced Robotics -AI12553,AI Research Scientist,332451,USD,332451,EX,CT,United States,L,United States,50,"Spark, Hadoop, PyTorch",Associate,17,Technology,2024-12-15,2025-01-03,1752,8.2,Advanced Robotics -AI12554,Research Scientist,226551,CHF,203896,SE,FL,Switzerland,L,Switzerland,0,"R, Python, Tableau, Deep Learning",Bachelor,9,Retail,2024-02-08,2024-03-21,1144,9,Advanced Robotics -AI12555,AI Consultant,182206,USD,182206,EX,PT,Sweden,M,Sweden,50,"SQL, Java, Tableau, Statistics, PyTorch",Master,18,Media,2024-09-21,2024-11-02,1591,7.5,Machine Intelligence Group -AI12556,AI Consultant,155691,EUR,132337,SE,CT,Austria,L,Brazil,100,"Hadoop, TensorFlow, GCP, Spark",PhD,6,Telecommunications,2025-01-12,2025-02-16,568,7.4,Smart Analytics -AI12557,Machine Learning Researcher,69981,USD,69981,EN,PT,Sweden,S,Sweden,50,"Python, Deep Learning, TensorFlow, Scala",Master,0,Technology,2024-03-27,2024-06-04,809,5.3,Cognitive Computing -AI12558,Computer Vision Engineer,115602,USD,115602,MI,FL,Denmark,S,Denmark,50,"TensorFlow, Git, Tableau, Statistics, Scala",Associate,2,Consulting,2024-07-31,2024-09-20,2388,7.9,Autonomous Tech -AI12559,Data Analyst,65661,GBP,49246,EN,FT,United Kingdom,L,United Kingdom,100,"AWS, R, NLP, Kubernetes",Associate,1,Automotive,2024-03-10,2024-04-01,2178,6.6,Future Systems -AI12560,ML Ops Engineer,54988,EUR,46740,EN,FL,France,M,France,100,"Hadoop, SQL, Deep Learning",Bachelor,1,Energy,2024-06-20,2024-08-16,904,5.6,Machine Intelligence Group -AI12561,Deep Learning Engineer,255127,GBP,191345,EX,FT,United Kingdom,L,United Kingdom,0,"Git, PyTorch, Java",Associate,13,Healthcare,2024-01-15,2024-03-25,2312,7.5,Quantum Computing Inc -AI12562,NLP Engineer,60129,USD,60129,EN,CT,Finland,L,Finland,50,"AWS, PyTorch, TensorFlow",Associate,0,Real Estate,2024-01-12,2024-03-12,1811,6.7,Smart Analytics -AI12563,NLP Engineer,151050,USD,151050,EX,FT,Finland,M,Romania,100,"Git, PyTorch, Statistics, R",Bachelor,13,Technology,2024-07-08,2024-09-04,1605,7.8,Smart Analytics -AI12564,NLP Engineer,102467,EUR,87097,MI,FL,France,L,France,0,"PyTorch, Hadoop, Deep Learning, Statistics",PhD,3,Healthcare,2024-05-19,2024-07-26,2339,8.1,Future Systems -AI12565,AI Software Engineer,91655,USD,91655,MI,FL,Sweden,M,Sweden,50,"R, Linux, Spark, Scala, Python",Associate,3,Gaming,2024-09-13,2024-11-11,598,9.4,Digital Transformation LLC -AI12566,Machine Learning Engineer,114161,EUR,97037,MI,FT,France,L,France,50,"Java, Python, Spark",Master,2,Government,2024-11-30,2025-01-30,521,9.2,DeepTech Ventures -AI12567,Data Analyst,73257,EUR,62268,MI,CT,Austria,M,Austria,100,"AWS, PyTorch, Spark, Statistics",Bachelor,2,Education,2024-05-28,2024-07-25,1845,9.4,AI Innovations -AI12568,Computer Vision Engineer,108618,USD,108618,MI,FL,Israel,L,Israel,0,"Java, Docker, GCP, R",PhD,3,Finance,2024-01-18,2024-02-22,581,7.5,Predictive Systems -AI12569,AI Specialist,62843,USD,62843,EN,FL,Denmark,S,Denmark,50,"AWS, Azure, Mathematics, Docker, Kubernetes",Bachelor,1,Education,2024-02-23,2024-04-25,2065,6.3,Quantum Computing Inc -AI12570,Research Scientist,178712,EUR,151905,SE,FL,Netherlands,L,Netherlands,50,"PyTorch, SQL, NLP, Docker, Spark",Bachelor,8,Finance,2025-02-22,2025-03-23,1151,8.8,Cloud AI Solutions -AI12571,Machine Learning Researcher,66399,USD,66399,EN,FT,Sweden,M,Sweden,0,"Deep Learning, Python, SQL, GCP, Hadoop",Bachelor,0,Consulting,2024-05-05,2024-06-23,1774,6.6,Algorithmic Solutions -AI12572,Deep Learning Engineer,26206,USD,26206,MI,PT,India,S,Australia,50,"PyTorch, Scala, Git, Data Visualization, Spark",Master,4,Gaming,2024-05-02,2024-06-25,2135,9.7,Smart Analytics -AI12573,Autonomous Systems Engineer,132926,CAD,166158,SE,CT,Canada,M,Canada,100,"R, Deep Learning, Hadoop",Bachelor,9,Healthcare,2024-12-05,2025-01-30,779,6.3,Advanced Robotics -AI12574,Machine Learning Researcher,212788,USD,212788,SE,FT,Norway,L,Spain,100,"Python, Statistics, TensorFlow, Tableau",PhD,9,Consulting,2025-02-24,2025-04-01,743,5.6,Algorithmic Solutions -AI12575,AI Specialist,38991,USD,38991,EN,FL,South Korea,S,South Korea,100,"Docker, Python, TensorFlow",Master,1,Telecommunications,2024-07-02,2024-08-15,955,9.8,Machine Intelligence Group -AI12576,AI Product Manager,50232,USD,50232,EN,PT,Israel,S,Israel,100,"Statistics, R, Data Visualization, Tableau, Deep Learning",PhD,1,Manufacturing,2025-01-07,2025-02-06,2141,7.2,Algorithmic Solutions -AI12577,AI Software Engineer,134499,USD,134499,EX,PT,Finland,M,Finland,50,"SQL, NLP, Spark, Python",PhD,13,Real Estate,2024-11-15,2024-12-05,1800,7.2,DataVision Ltd -AI12578,Research Scientist,148779,USD,148779,EX,PT,South Korea,L,South Korea,100,"R, Azure, Tableau, Docker",Associate,17,Telecommunications,2025-04-24,2025-05-20,2101,9.9,Future Systems -AI12579,Principal Data Scientist,70847,USD,70847,EN,FL,Norway,S,Norway,100,"R, Data Visualization, GCP",Associate,1,Energy,2024-10-23,2024-11-13,1102,9.5,Autonomous Tech -AI12580,AI Software Engineer,62204,USD,62204,EN,FT,Ireland,L,New Zealand,0,"AWS, NLP, Kubernetes, R",Associate,0,Manufacturing,2024-10-06,2024-12-09,1579,5.9,Algorithmic Solutions -AI12581,AI Software Engineer,129841,SGD,168793,EX,FT,Singapore,S,Singapore,100,"R, SQL, NLP, Azure, Python",Master,17,Finance,2024-01-01,2024-03-14,591,9.3,DataVision Ltd -AI12582,Data Analyst,155034,EUR,131779,SE,FT,Netherlands,M,Mexico,50,"TensorFlow, Python, MLOps, PyTorch, Tableau",Master,9,Healthcare,2024-11-14,2024-12-31,2353,9.2,Cognitive Computing -AI12583,AI Software Engineer,187509,JPY,20625990,EX,FL,Japan,S,Israel,100,"R, MLOps, Java, Statistics, TensorFlow",Master,15,Automotive,2024-05-13,2024-05-31,2287,9.4,Algorithmic Solutions -AI12584,AI Consultant,177222,EUR,150639,EX,FL,France,M,Colombia,50,"AWS, Git, NLP, Linux",Bachelor,10,Automotive,2025-02-25,2025-04-07,1455,7.7,DataVision Ltd -AI12585,ML Ops Engineer,333553,USD,333553,EX,FL,Norway,L,Norway,100,"TensorFlow, Python, MLOps, Java, R",PhD,17,Healthcare,2025-04-16,2025-06-27,638,9,Predictive Systems -AI12586,AI Product Manager,51703,EUR,43948,EN,PT,Germany,S,Luxembourg,100,"Linux, Docker, Git, R",Associate,1,Retail,2025-02-26,2025-04-15,914,6.4,Future Systems -AI12587,Data Analyst,161634,USD,161634,SE,FL,Israel,L,Israel,50,"Python, Azure, Mathematics",Bachelor,7,Retail,2025-02-22,2025-03-31,2194,7,AI Innovations -AI12588,AI Product Manager,166572,JPY,18322920,SE,FL,Japan,L,Japan,100,"Docker, Java, R, SQL, AWS",PhD,8,Retail,2024-09-17,2024-10-27,2063,9.2,Predictive Systems -AI12589,NLP Engineer,208798,USD,208798,EX,CT,Sweden,L,Indonesia,50,"Kubernetes, Data Visualization, TensorFlow",Master,19,Automotive,2024-12-02,2025-01-28,1995,5.2,AI Innovations -AI12590,Data Analyst,86613,USD,86613,MI,FL,Finland,L,Finland,100,"Git, GCP, Computer Vision, AWS, Hadoop",PhD,2,Manufacturing,2024-11-16,2024-12-04,1178,6.7,Neural Networks Co -AI12591,Machine Learning Engineer,117597,CHF,105837,MI,PT,Switzerland,L,Switzerland,0,"Data Visualization, Docker, Java",Bachelor,4,Automotive,2024-03-30,2024-04-20,2021,5.2,Machine Intelligence Group -AI12592,Data Analyst,22513,USD,22513,EN,CT,India,L,India,0,"Deep Learning, GCP, Mathematics, R",Associate,0,Telecommunications,2024-05-05,2024-06-20,1160,7.9,Future Systems -AI12593,Machine Learning Engineer,105654,SGD,137350,MI,CT,Singapore,L,Singapore,0,"Mathematics, Git, Scala, Linux",Bachelor,4,Education,2025-01-15,2025-02-03,938,9.7,Quantum Computing Inc -AI12594,AI Consultant,224641,SGD,292033,EX,FT,Singapore,L,Israel,100,"Linux, Java, Mathematics, Hadoop, SQL",Associate,12,Education,2024-09-20,2024-10-09,1957,6.6,Autonomous Tech -AI12595,Computer Vision Engineer,92817,USD,92817,MI,CT,Denmark,S,Denmark,100,"PyTorch, Linux, TensorFlow, R, Mathematics",Associate,4,Finance,2024-06-05,2024-06-23,1419,8.8,Neural Networks Co -AI12596,Deep Learning Engineer,87012,EUR,73960,EN,PT,Austria,L,Austria,100,"Linux, PyTorch, Computer Vision",Bachelor,1,Retail,2025-01-26,2025-02-20,2106,9.6,Autonomous Tech -AI12597,AI Product Manager,176978,USD,176978,EX,PT,Finland,S,New Zealand,100,"Hadoop, Docker, Linux",PhD,19,Automotive,2024-07-11,2024-08-06,776,8.9,Digital Transformation LLC -AI12598,AI Software Engineer,31871,USD,31871,MI,CT,India,L,India,0,"Statistics, Mathematics, TensorFlow",Associate,4,Transportation,2024-04-08,2024-06-08,905,7.7,Future Systems -AI12599,Data Engineer,111513,USD,111513,MI,FL,United States,S,Finland,0,"Kubernetes, Azure, Deep Learning, Data Visualization, SQL",Associate,3,Healthcare,2024-06-09,2024-06-23,901,7.5,AI Innovations -AI12600,Data Scientist,124502,EUR,105827,SE,CT,Austria,M,Austria,100,"Linux, Tableau, Python, Computer Vision, TensorFlow",Master,7,Retail,2024-03-07,2024-03-30,1777,6,DeepTech Ventures -AI12601,AI Architect,143750,EUR,122188,SE,CT,France,M,Brazil,50,"Java, AWS, Git",PhD,9,Finance,2024-06-10,2024-07-15,1569,9.6,Predictive Systems -AI12602,Deep Learning Engineer,107546,EUR,91414,SE,PT,Germany,M,Czech Republic,0,"Tableau, Python, PyTorch",Master,9,Finance,2025-02-20,2025-04-09,641,8.7,Quantum Computing Inc -AI12603,Research Scientist,208493,EUR,177219,EX,FL,Germany,L,Germany,100,"R, SQL, PyTorch",PhD,19,Manufacturing,2024-10-07,2024-11-03,615,6.4,AI Innovations -AI12604,Computer Vision Engineer,290203,USD,290203,EX,CT,Norway,M,Norway,100,"GCP, Python, SQL",Bachelor,18,Real Estate,2024-10-06,2024-11-20,1734,5.3,Autonomous Tech -AI12605,AI Product Manager,79948,USD,79948,MI,CT,Ireland,S,Israel,100,"Scala, Kubernetes, Computer Vision, Tableau, Docker",Bachelor,4,Healthcare,2025-02-15,2025-03-30,1869,9,AI Innovations -AI12606,AI Research Scientist,139049,CHF,125144,MI,FL,Switzerland,M,Canada,50,"Scala, Java, TensorFlow, Tableau",Master,3,Healthcare,2024-02-23,2024-04-12,1656,6.1,DeepTech Ventures -AI12607,NLP Engineer,123828,USD,123828,MI,FL,United States,L,Belgium,100,"Spark, Azure, MLOps, R, GCP",Bachelor,4,Automotive,2025-04-13,2025-05-20,1675,5.3,Quantum Computing Inc -AI12608,Research Scientist,125635,USD,125635,MI,PT,Norway,L,Norway,100,"PyTorch, Tableau, SQL, NLP",Master,4,Government,2024-07-30,2024-08-27,681,7.2,Neural Networks Co -AI12609,Data Scientist,102852,USD,102852,MI,PT,United States,S,United States,100,"Scala, Linux, Python, AWS",Associate,2,Automotive,2024-06-14,2024-07-13,1842,9.2,Smart Analytics -AI12610,Autonomous Systems Engineer,126788,EUR,107770,SE,CT,France,S,France,100,"Tableau, Computer Vision, Kubernetes, R",Bachelor,9,Government,2024-03-12,2024-04-21,1769,9,Smart Analytics -AI12611,Research Scientist,140019,GBP,105014,EX,CT,United Kingdom,S,United Kingdom,0,"Scala, TensorFlow, Hadoop",PhD,15,Consulting,2024-04-05,2024-06-17,1104,7.8,Cloud AI Solutions -AI12612,ML Ops Engineer,225786,JPY,24836460,EX,FL,Japan,M,Japan,100,"Git, Kubernetes, Computer Vision, Python, Deep Learning",Master,13,Gaming,2024-09-03,2024-11-04,859,9.1,Algorithmic Solutions -AI12613,Principal Data Scientist,126761,EUR,107747,SE,FL,Austria,S,Austria,0,"Java, Kubernetes, Python, Computer Vision, TensorFlow",Associate,9,Energy,2024-08-23,2024-09-20,1014,8.6,DeepTech Ventures -AI12614,AI Specialist,97895,USD,97895,SE,FT,Israel,S,Israel,0,"Python, Scala, Docker, Azure, Deep Learning",Master,6,Transportation,2024-05-06,2024-06-24,1202,5.6,Neural Networks Co -AI12615,AI Architect,234625,EUR,199431,EX,PT,Netherlands,L,Norway,50,"Git, Python, NLP, TensorFlow, AWS",Bachelor,15,Healthcare,2024-09-17,2024-11-25,1955,6.4,Quantum Computing Inc -AI12616,Data Engineer,118185,GBP,88639,SE,PT,United Kingdom,M,Germany,100,"Computer Vision, Git, Hadoop, Java",Associate,8,Gaming,2025-01-17,2025-02-13,1198,9.1,Advanced Robotics -AI12617,Deep Learning Engineer,66948,USD,66948,EN,FL,Denmark,S,Denmark,100,"Deep Learning, Scala, Data Visualization",Master,0,Healthcare,2024-09-27,2024-11-26,1683,5.1,Digital Transformation LLC -AI12618,Autonomous Systems Engineer,64481,EUR,54809,EN,FL,France,S,Mexico,100,"Python, Hadoop, GCP",PhD,1,Consulting,2024-05-02,2024-05-22,1179,6.6,Future Systems -AI12619,Research Scientist,153732,CHF,138359,MI,FT,Switzerland,L,Switzerland,0,"MLOps, Spark, Scala, Java, Azure",PhD,3,Consulting,2025-03-10,2025-05-03,789,6.4,Algorithmic Solutions -AI12620,Computer Vision Engineer,130492,USD,130492,SE,FT,Ireland,S,Egypt,50,"Python, Data Visualization, Kubernetes",Associate,8,Education,2024-02-16,2024-03-26,1900,7.4,Neural Networks Co -AI12621,NLP Engineer,116529,USD,116529,MI,FT,Sweden,L,Sweden,50,"SQL, MLOps, Computer Vision, Data Visualization",Bachelor,2,Gaming,2024-12-12,2025-01-19,926,6.1,Algorithmic Solutions -AI12622,Autonomous Systems Engineer,125193,AUD,169011,SE,FT,Australia,L,Australia,100,"AWS, Java, Docker",Bachelor,6,Government,2025-03-21,2025-05-16,1239,7.8,Smart Analytics -AI12623,ML Ops Engineer,153136,EUR,130166,SE,PT,Netherlands,L,Netherlands,0,"Python, Kubernetes, Mathematics, Data Visualization, AWS",Associate,9,Media,2024-08-28,2024-11-01,1464,7.7,Advanced Robotics -AI12624,Data Analyst,174479,USD,174479,EX,FT,United States,S,United States,50,"Python, Hadoop, Linux, Tableau, Computer Vision",Bachelor,12,Government,2024-01-24,2024-03-18,2121,7.5,Machine Intelligence Group -AI12625,Machine Learning Researcher,137316,AUD,185377,SE,PT,Australia,M,Austria,50,"Deep Learning, Spark, AWS, Azure",Bachelor,8,Gaming,2024-05-04,2024-06-13,2081,9.3,DeepTech Ventures -AI12626,Deep Learning Engineer,160330,USD,160330,SE,FL,Norway,S,Norway,100,"R, Statistics, Scala, AWS, Computer Vision",Bachelor,7,Government,2024-04-05,2024-05-14,1371,5.6,TechCorp Inc -AI12627,AI Architect,41342,USD,41342,MI,FL,China,L,Denmark,100,"Python, Git, Scala, GCP, Kubernetes",Bachelor,3,Education,2025-03-18,2025-05-15,1068,6.3,DataVision Ltd -AI12628,Autonomous Systems Engineer,31869,USD,31869,EN,CT,China,S,China,100,"SQL, Linux, PyTorch, GCP, R",Associate,1,Education,2024-11-11,2025-01-20,2218,5.2,Cloud AI Solutions -AI12629,Autonomous Systems Engineer,190329,USD,190329,SE,FL,United States,L,Ghana,0,"R, Python, Docker, SQL",PhD,5,Media,2024-05-18,2024-06-04,615,8,DataVision Ltd -AI12630,Research Scientist,80831,USD,80831,EN,FT,Finland,L,Finland,50,"Git, R, MLOps",Bachelor,1,Gaming,2024-07-01,2024-07-20,1907,7.2,Cloud AI Solutions -AI12631,AI Product Manager,102054,USD,102054,SE,FT,Sweden,S,Sweden,100,"Docker, Linux, MLOps, SQL, Deep Learning",Bachelor,7,Media,2025-03-22,2025-04-19,1223,9.2,Future Systems -AI12632,Computer Vision Engineer,198047,USD,198047,EX,PT,South Korea,M,South Korea,100,"Kubernetes, Tableau, Python",Bachelor,12,Healthcare,2024-05-27,2024-07-15,1391,6.6,Predictive Systems -AI12633,NLP Engineer,70324,USD,70324,EN,CT,United States,M,United States,0,"Linux, Docker, PyTorch, Spark",Master,0,Education,2024-03-24,2024-06-02,578,9.9,Future Systems -AI12634,AI Consultant,61593,USD,61593,EN,FL,Ireland,M,Ireland,0,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-07-15,2024-08-30,2459,7.4,Smart Analytics -AI12635,NLP Engineer,225178,EUR,191401,EX,FL,Austria,M,Austria,100,"Python, Data Visualization, Tableau, Java",Master,17,Healthcare,2024-07-10,2024-08-13,1008,7.2,Algorithmic Solutions -AI12636,Machine Learning Engineer,119102,CAD,148878,SE,FL,Canada,M,Canada,50,"Statistics, Linux, Python, Java, Scala",PhD,9,Telecommunications,2025-03-13,2025-05-11,687,8.1,Smart Analytics -AI12637,AI Architect,188552,USD,188552,EX,CT,Finland,S,Finland,0,"Docker, Computer Vision, Python",Associate,10,Automotive,2025-04-16,2025-05-28,1801,7.3,Algorithmic Solutions -AI12638,Head of AI,226063,CHF,203457,SE,CT,Switzerland,L,Romania,0,"Scala, Hadoop, Deep Learning",Master,5,Technology,2025-02-23,2025-04-07,1020,5.1,DataVision Ltd -AI12639,AI Product Manager,62015,USD,62015,MI,CT,Israel,S,Israel,50,"Python, Scala, PyTorch, Statistics",PhD,3,Technology,2024-11-08,2024-12-28,1879,9.2,Cognitive Computing -AI12640,Computer Vision Engineer,93014,CAD,116268,MI,FT,Canada,M,Canada,0,"MLOps, SQL, PyTorch, Mathematics",PhD,3,Energy,2024-10-12,2024-11-05,1673,8.5,Cloud AI Solutions -AI12641,Machine Learning Researcher,128718,SGD,167333,SE,PT,Singapore,M,Singapore,50,"Mathematics, Hadoop, AWS, Statistics",Associate,7,Manufacturing,2024-12-15,2025-02-03,669,9.6,Autonomous Tech -AI12642,Data Engineer,66805,EUR,56784,EN,CT,Austria,M,Italy,0,"Spark, Git, Deep Learning, Statistics",Associate,1,Real Estate,2024-01-23,2024-02-23,554,5.2,Autonomous Tech -AI12643,ML Ops Engineer,90978,USD,90978,EN,FT,Norway,S,Norway,50,"Python, AWS, Data Visualization, Spark, MLOps",Bachelor,1,Finance,2024-06-14,2024-08-04,2462,8.6,Advanced Robotics -AI12644,Data Scientist,139567,USD,139567,SE,PT,Ireland,L,Ireland,0,"PyTorch, Azure, Docker, GCP",Associate,5,Healthcare,2024-11-17,2024-12-05,1020,9.1,Neural Networks Co -AI12645,Machine Learning Engineer,133001,USD,133001,MI,FL,Denmark,M,Denmark,100,"Git, Linux, Python",Master,3,Healthcare,2024-04-02,2024-06-01,731,7.5,Advanced Robotics -AI12646,AI Product Manager,117366,EUR,99761,SE,FT,Netherlands,S,Netherlands,100,"Statistics, TensorFlow, AWS",Bachelor,5,Retail,2025-02-07,2025-03-23,1523,8.1,Quantum Computing Inc -AI12647,Machine Learning Engineer,56948,USD,56948,EN,PT,South Korea,S,South Korea,100,"Statistics, SQL, Scala, PyTorch, Git",Associate,1,Retail,2025-04-04,2025-05-18,2302,7.3,Digital Transformation LLC -AI12648,AI Product Manager,271210,SGD,352573,EX,PT,Singapore,L,Switzerland,100,"Computer Vision, Scala, SQL, PyTorch, R",Master,11,Media,2024-06-23,2024-07-15,583,9.2,Cloud AI Solutions -AI12649,NLP Engineer,108474,EUR,92203,MI,CT,France,L,Australia,0,"Git, SQL, Tableau, Deep Learning",Master,3,Government,2024-10-09,2024-11-12,966,7.2,TechCorp Inc -AI12650,Data Engineer,74225,USD,74225,MI,PT,Ireland,M,Ireland,0,"PyTorch, Statistics, Docker, Kubernetes",Associate,2,Education,2024-08-21,2024-10-13,1353,8.7,DataVision Ltd -AI12651,AI Research Scientist,97911,CAD,122389,SE,PT,Canada,S,Canada,0,"SQL, R, Tableau, Kubernetes",Master,9,Education,2024-02-28,2024-03-31,2122,9.1,Cognitive Computing -AI12652,Deep Learning Engineer,87471,USD,87471,MI,PT,Finland,L,Finland,50,"Git, Azure, Statistics",Master,3,Technology,2024-06-05,2024-06-19,831,5.3,Digital Transformation LLC -AI12653,AI Consultant,66358,USD,66358,MI,FL,South Korea,M,Poland,0,"Kubernetes, Deep Learning, Python, Data Visualization, Mathematics",Master,3,Transportation,2024-05-18,2024-07-25,1793,8.5,Predictive Systems -AI12654,AI Research Scientist,67502,USD,67502,EN,CT,Ireland,L,Ireland,50,"Statistics, Docker, Python, Hadoop, Git",Associate,0,Healthcare,2024-01-09,2024-01-30,2491,7,Cognitive Computing -AI12655,AI Architect,84581,USD,84581,MI,FL,Ireland,M,Ireland,50,"Linux, Java, R",PhD,2,Energy,2024-10-10,2024-12-21,1998,10,Machine Intelligence Group -AI12656,Autonomous Systems Engineer,94615,USD,94615,EN,FT,United States,M,United States,0,"PyTorch, Scala, Linux",Associate,0,Consulting,2024-09-20,2024-11-27,2355,5.3,Algorithmic Solutions -AI12657,Computer Vision Engineer,126277,EUR,107335,SE,FL,Netherlands,S,Philippines,100,"Python, TensorFlow, Tableau, Azure, Statistics",Master,9,Manufacturing,2025-03-28,2025-05-13,1919,6.5,Smart Analytics -AI12658,Autonomous Systems Engineer,108046,EUR,91839,MI,FT,Netherlands,M,Netherlands,100,"Deep Learning, AWS, Hadoop",Master,4,Consulting,2024-10-22,2024-12-19,2301,9.5,Predictive Systems -AI12659,Machine Learning Researcher,214302,EUR,182157,EX,FT,Netherlands,S,Netherlands,50,"Spark, Docker, Data Visualization, NLP",Associate,16,Retail,2025-04-23,2025-05-19,1213,8.9,Predictive Systems -AI12660,Head of AI,60614,USD,60614,EN,FL,Finland,S,Portugal,100,"Linux, Docker, MLOps",PhD,0,Education,2024-02-24,2024-04-28,2024,7,Advanced Robotics -AI12661,Robotics Engineer,126247,SGD,164121,SE,FT,Singapore,S,Singapore,100,"PyTorch, Python, Docker",Master,8,Finance,2024-10-11,2024-11-08,1708,6.3,Smart Analytics -AI12662,Research Scientist,153207,USD,153207,SE,CT,Denmark,S,Denmark,0,"Python, Java, Git",Bachelor,9,Transportation,2024-11-07,2025-01-02,1270,5.6,DataVision Ltd -AI12663,NLP Engineer,91093,EUR,77429,MI,CT,Austria,M,Austria,0,"Deep Learning, Mathematics, Java, Spark, NLP",PhD,4,Technology,2024-06-13,2024-08-02,1465,7.1,Advanced Robotics -AI12664,Data Analyst,177639,USD,177639,EX,FL,Denmark,S,Denmark,100,"Deep Learning, Linux, Kubernetes",PhD,13,Real Estate,2024-11-11,2024-12-28,1835,7.9,Neural Networks Co -AI12665,AI Architect,72729,EUR,61820,EN,PT,Netherlands,M,Netherlands,50,"Docker, Kubernetes, Scala, Git, Mathematics",Bachelor,1,Real Estate,2024-08-17,2024-09-07,1687,5.5,Predictive Systems -AI12666,ML Ops Engineer,231764,EUR,196999,EX,PT,Netherlands,S,South Korea,50,"Kubernetes, Spark, Scala, Data Visualization",Master,14,Manufacturing,2024-07-28,2024-08-25,1535,7.3,Cloud AI Solutions -AI12667,Robotics Engineer,91852,USD,91852,MI,FT,Israel,M,South Korea,50,"Deep Learning, TensorFlow, Azure",Bachelor,2,Energy,2024-02-09,2024-02-27,876,6.7,Smart Analytics -AI12668,Data Scientist,108220,USD,108220,EN,CT,Denmark,L,Ukraine,50,"Tableau, Computer Vision, AWS, Git",PhD,1,Finance,2024-12-09,2025-02-12,2251,8.5,Smart Analytics -AI12669,NLP Engineer,44513,USD,44513,EN,FL,Israel,S,Israel,100,"Scala, Azure, Statistics",Master,0,Education,2024-01-27,2024-02-16,1799,6.1,Quantum Computing Inc -AI12670,Autonomous Systems Engineer,115978,USD,115978,MI,PT,Finland,L,Germany,50,"Azure, Spark, Mathematics, Java",PhD,4,Government,2024-08-19,2024-10-25,2133,8,DeepTech Ventures -AI12671,AI Architect,60623,USD,60623,EN,FT,Ireland,L,Ireland,0,"Git, Python, TensorFlow, GCP, Linux",Associate,0,Manufacturing,2024-05-10,2024-06-12,1778,8.5,AI Innovations -AI12672,Machine Learning Researcher,193676,USD,193676,SE,FT,Denmark,M,Denmark,100,"Docker, Mathematics, Python",Associate,6,Technology,2024-03-05,2024-05-13,1107,6.2,Cloud AI Solutions -AI12673,Computer Vision Engineer,101827,USD,101827,MI,CT,Norway,S,Norway,100,"Kubernetes, Git, Deep Learning, Python",Bachelor,2,Real Estate,2025-03-06,2025-05-05,1206,9.4,Autonomous Tech -AI12674,AI Consultant,90586,SGD,117762,EN,FT,Singapore,L,Hungary,0,"Statistics, AWS, Python",PhD,0,Real Estate,2024-01-22,2024-03-16,1090,5.1,Cognitive Computing -AI12675,AI Specialist,194601,CAD,243251,EX,PT,Canada,M,Canada,50,"SQL, Kubernetes, GCP",PhD,11,Transportation,2024-09-21,2024-10-16,1795,5.7,Future Systems -AI12676,Data Engineer,382222,CHF,344000,EX,FL,Switzerland,L,Thailand,50,"R, PyTorch, Java, GCP, Deep Learning",Associate,15,Government,2024-05-24,2024-08-04,674,9.9,Algorithmic Solutions -AI12677,AI Specialist,111690,CAD,139613,SE,CT,Canada,L,Canada,100,"Git, Python, Spark",Master,5,Transportation,2024-04-04,2024-05-23,1034,6.3,Future Systems -AI12678,Machine Learning Researcher,74807,EUR,63586,MI,CT,France,S,France,100,"Scala, Python, Mathematics, GCP, Linux",Bachelor,3,Automotive,2024-09-19,2024-11-05,2286,8.2,Predictive Systems -AI12679,Machine Learning Researcher,68533,AUD,92520,EN,FT,Australia,S,Colombia,100,"GCP, R, Linux, Mathematics, Java",PhD,0,Gaming,2024-08-14,2024-10-10,1038,7.9,Quantum Computing Inc -AI12680,Robotics Engineer,130226,EUR,110692,SE,CT,Netherlands,L,Netherlands,100,"PyTorch, Docker, TensorFlow, Java, AWS",Bachelor,5,Healthcare,2024-05-24,2024-06-22,513,5.1,Future Systems -AI12681,AI Specialist,112790,GBP,84593,MI,PT,United Kingdom,L,United Kingdom,50,"TensorFlow, Java, Tableau, Computer Vision, R",Associate,4,Manufacturing,2025-02-28,2025-04-25,1695,6,Cloud AI Solutions -AI12682,Data Scientist,189996,CAD,237495,EX,PT,Canada,L,France,100,"Python, Azure, Scala, Statistics, PyTorch",Associate,11,Retail,2024-12-15,2025-01-28,1151,9.4,DataVision Ltd -AI12683,AI Research Scientist,114387,USD,114387,MI,CT,Norway,M,Norway,50,"Tableau, Spark, Linux, Python",PhD,4,Media,2024-06-10,2024-07-15,640,6.5,Autonomous Tech -AI12684,Machine Learning Engineer,185728,CHF,167155,SE,FL,Switzerland,S,Switzerland,50,"Spark, Java, Scala, AWS",PhD,7,Technology,2024-01-25,2024-02-08,2147,8.7,AI Innovations -AI12685,Computer Vision Engineer,142898,EUR,121463,EX,PT,France,M,France,50,"SQL, Hadoop, Scala",PhD,16,Real Estate,2024-07-13,2024-08-14,1190,9.6,TechCorp Inc -AI12686,Autonomous Systems Engineer,84890,USD,84890,EN,FT,Finland,L,Finland,100,"Kubernetes, Python, Git",Associate,1,Retail,2024-08-01,2024-09-07,772,8.7,AI Innovations -AI12687,Machine Learning Researcher,95220,JPY,10474200,EN,CT,Japan,L,Luxembourg,0,"Scala, Spark, NLP, Tableau",Associate,1,Technology,2025-03-11,2025-04-23,536,9.8,Neural Networks Co -AI12688,Machine Learning Engineer,73529,USD,73529,EN,FT,Norway,M,Russia,0,"Linux, Data Visualization, Spark, SQL",Bachelor,0,Consulting,2024-12-10,2025-01-27,979,9,Advanced Robotics -AI12689,AI Specialist,96565,EUR,82080,MI,FT,Netherlands,S,Netherlands,100,"Python, SQL, PyTorch, Deep Learning",Bachelor,4,Technology,2025-04-05,2025-05-14,713,9.1,Quantum Computing Inc -AI12690,AI Research Scientist,81266,USD,81266,EN,PT,Israel,L,Israel,100,"GCP, Kubernetes, Java, Python, SQL",Master,1,Consulting,2024-01-20,2024-03-02,2055,7.2,Cloud AI Solutions -AI12691,Deep Learning Engineer,120489,CAD,150611,SE,FL,Canada,L,Canada,100,"GCP, Linux, R, SQL",Master,8,Retail,2024-07-17,2024-09-15,1009,9.3,TechCorp Inc -AI12692,ML Ops Engineer,160293,SGD,208381,SE,CT,Singapore,L,Chile,100,"Docker, Deep Learning, NLP, PyTorch, Scala",Associate,7,Transportation,2024-04-29,2024-07-11,2163,6.5,DataVision Ltd -AI12693,Research Scientist,259694,CAD,324618,EX,FL,Canada,L,Canada,100,"R, Deep Learning, Mathematics, Statistics",Bachelor,16,Healthcare,2025-02-20,2025-04-04,2352,6.2,TechCorp Inc -AI12694,NLP Engineer,134216,AUD,181192,SE,PT,Australia,M,Ghana,50,"Linux, Spark, MLOps, PyTorch",Associate,7,Government,2025-01-05,2025-03-15,1073,5.1,DeepTech Ventures -AI12695,Machine Learning Engineer,70756,USD,70756,MI,FL,South Korea,M,South Korea,50,"Linux, Scala, Mathematics",PhD,3,Healthcare,2024-06-09,2024-08-01,1480,8.6,DataVision Ltd -AI12696,AI Software Engineer,74648,USD,74648,MI,CT,Israel,M,Israel,50,"Scala, Tableau, R, SQL",Associate,2,Healthcare,2024-08-05,2024-09-18,581,5.5,TechCorp Inc -AI12697,Deep Learning Engineer,62208,EUR,52877,EN,FT,France,M,Singapore,100,"Java, Scala, MLOps, NLP, TensorFlow",Bachelor,0,Technology,2024-02-06,2024-04-03,1324,9.7,Cognitive Computing -AI12698,AI Research Scientist,127798,USD,127798,SE,PT,Ireland,M,Ireland,0,"Kubernetes, Scala, MLOps",Associate,6,Government,2024-12-16,2025-02-18,2486,9.1,Machine Intelligence Group -AI12699,Research Scientist,44314,USD,44314,MI,FT,China,L,China,0,"Statistics, R, Git, Computer Vision",Bachelor,3,Transportation,2024-03-22,2024-04-18,2342,5.3,Autonomous Tech -AI12700,Machine Learning Researcher,112441,USD,112441,SE,FT,Sweden,S,Sweden,100,"Scala, Azure, NLP, Deep Learning",Master,5,Finance,2025-01-16,2025-02-24,1319,9.8,Cloud AI Solutions -AI12701,AI Architect,67815,EUR,57643,EN,PT,Netherlands,S,United States,0,"Statistics, Docker, R, GCP",Associate,0,Technology,2024-01-16,2024-02-19,1170,9.4,Advanced Robotics -AI12702,AI Software Engineer,116101,USD,116101,MI,FT,Norway,L,Norway,50,"MLOps, Python, Data Visualization, NLP, TensorFlow",Master,4,Manufacturing,2024-07-11,2024-08-14,527,6.6,DeepTech Ventures -AI12703,AI Software Engineer,142224,EUR,120890,EX,PT,Germany,M,Germany,50,"Data Visualization, MLOps, R, Spark",Associate,15,Transportation,2024-08-17,2024-09-12,1792,5.2,Cloud AI Solutions -AI12704,Data Engineer,122247,USD,122247,SE,PT,United States,M,United States,50,"SQL, PyTorch, MLOps, Java, TensorFlow",Master,5,Healthcare,2024-02-18,2024-04-16,507,6.7,Algorithmic Solutions -AI12705,Data Analyst,68996,USD,68996,SE,PT,China,L,China,100,"SQL, Linux, GCP",Bachelor,5,Energy,2024-06-10,2024-07-22,1239,5.9,Cloud AI Solutions -AI12706,AI Research Scientist,58278,GBP,43709,EN,CT,United Kingdom,S,Norway,100,"TensorFlow, Kubernetes, Linux, Tableau",Associate,1,Retail,2024-08-16,2024-09-16,1495,8.6,Digital Transformation LLC -AI12707,AI Product Manager,161500,AUD,218025,SE,CT,Australia,L,Colombia,100,"Kubernetes, R, SQL",Associate,8,Technology,2024-11-14,2025-01-07,1847,8.2,TechCorp Inc -AI12708,Data Analyst,97036,USD,97036,EN,PT,Denmark,L,United Kingdom,0,"Python, NLP, Docker",PhD,0,Transportation,2024-12-20,2025-02-20,1466,6.7,Smart Analytics -AI12709,AI Product Manager,97890,USD,97890,MI,PT,Finland,L,Finland,100,"Statistics, Mathematics, Deep Learning, Linux",PhD,2,Media,2024-09-14,2024-10-07,1422,9.9,DataVision Ltd -AI12710,AI Product Manager,192865,EUR,163935,EX,CT,France,L,France,0,"SQL, Statistics, Mathematics, NLP",Associate,11,Manufacturing,2024-07-12,2024-09-07,1150,9.7,DeepTech Ventures -AI12711,Computer Vision Engineer,19662,USD,19662,EN,FL,India,M,India,0,"Linux, AWS, SQL, Data Visualization",Master,1,Manufacturing,2024-01-08,2024-02-15,2190,8.7,Algorithmic Solutions -AI12712,Research Scientist,95674,USD,95674,SE,CT,Sweden,S,Czech Republic,0,"NLP, Git, Kubernetes, Azure, AWS",PhD,7,Finance,2024-08-24,2024-09-16,855,8.1,Autonomous Tech -AI12713,Head of AI,83952,EUR,71359,EN,CT,Netherlands,L,Netherlands,50,"Statistics, R, Azure, GCP",Bachelor,1,Healthcare,2025-01-22,2025-03-12,798,8.3,Neural Networks Co -AI12714,Autonomous Systems Engineer,70247,USD,70247,EN,PT,Ireland,S,Ireland,0,"Spark, Tableau, Azure",Associate,1,Gaming,2025-02-10,2025-04-16,2099,7.3,Cloud AI Solutions -AI12715,Computer Vision Engineer,194385,GBP,145789,EX,FL,United Kingdom,S,Poland,50,"Python, Tableau, AWS, Azure",Bachelor,14,Transportation,2025-04-07,2025-05-11,1896,8.8,Autonomous Tech -AI12716,Machine Learning Researcher,50464,USD,50464,MI,FT,China,M,China,100,"NLP, Python, Kubernetes, Docker",Associate,2,Telecommunications,2024-11-11,2024-12-17,792,5.9,Neural Networks Co -AI12717,AI Architect,71270,EUR,60580,EN,FL,Netherlands,S,Netherlands,0,"GCP, Linux, MLOps",Bachelor,0,Energy,2024-03-05,2024-03-28,2402,6.4,Autonomous Tech -AI12718,AI Specialist,243177,AUD,328289,EX,FT,Australia,M,Australia,50,"Mathematics, Python, SQL",Bachelor,12,Automotive,2024-11-04,2024-11-26,1744,9.4,Cloud AI Solutions -AI12719,Data Scientist,239543,EUR,203612,EX,FL,Austria,M,India,0,"MLOps, SQL, Deep Learning, Kubernetes",Bachelor,15,Manufacturing,2025-01-08,2025-03-18,2258,6.6,Cognitive Computing -AI12720,Machine Learning Engineer,53499,USD,53499,EN,PT,South Korea,S,South Korea,0,"Data Visualization, AWS, Mathematics, Tableau, Deep Learning",Master,1,Energy,2025-04-03,2025-05-08,1026,5.8,Advanced Robotics -AI12721,Computer Vision Engineer,150607,USD,150607,EX,FT,Israel,M,Israel,50,"R, SQL, PyTorch",Associate,18,Government,2024-01-27,2024-04-08,2485,5.7,Cognitive Computing -AI12722,AI Specialist,79623,USD,79623,EN,FL,United States,L,Australia,0,"Computer Vision, Tableau, Kubernetes, Linux",Master,1,Transportation,2024-06-12,2024-08-09,1144,7.7,Autonomous Tech -AI12723,AI Architect,81308,USD,81308,EN,PT,United States,L,United States,50,"R, Python, Tableau",Associate,0,Media,2025-02-23,2025-03-09,749,6.6,Cloud AI Solutions -AI12724,Head of AI,123946,AUD,167327,SE,FT,Australia,S,Australia,100,"Tableau, Data Visualization, Mathematics",PhD,9,Government,2024-01-19,2024-03-29,2481,8.6,Digital Transformation LLC -AI12725,ML Ops Engineer,42381,USD,42381,SE,CT,India,S,Romania,0,"Python, NLP, Azure, TensorFlow",Associate,9,Retail,2025-01-24,2025-03-22,1466,5.4,Autonomous Tech -AI12726,Data Analyst,35803,USD,35803,MI,CT,China,S,China,0,"Git, TensorFlow, Python, AWS, Kubernetes",Associate,4,Education,2024-06-04,2024-07-16,2091,6.4,Algorithmic Solutions -AI12727,Data Analyst,126100,EUR,107185,SE,FT,Netherlands,L,Netherlands,50,"PyTorch, Tableau, Hadoop, Kubernetes",Bachelor,7,Government,2024-04-10,2024-05-24,2184,7.4,Digital Transformation LLC -AI12728,NLP Engineer,138184,USD,138184,SE,FT,Norway,M,Norway,100,"PyTorch, Hadoop, MLOps, Azure",Master,9,Gaming,2025-03-30,2025-04-25,516,5.2,Algorithmic Solutions -AI12729,AI Architect,38303,USD,38303,MI,FT,India,M,India,50,"Python, TensorFlow, Docker, Mathematics, Hadoop",Master,3,Telecommunications,2024-07-21,2024-08-27,1857,7.1,Neural Networks Co -AI12730,Autonomous Systems Engineer,41682,USD,41682,MI,PT,India,L,India,0,"Python, SQL, Mathematics",Bachelor,4,Manufacturing,2024-08-04,2024-10-16,2045,6.4,Algorithmic Solutions -AI12731,AI Specialist,255802,USD,255802,EX,PT,Israel,L,Romania,100,"Hadoop, Git, GCP, Computer Vision",Associate,12,Telecommunications,2024-04-20,2024-05-05,1123,9.5,Cloud AI Solutions -AI12732,Machine Learning Researcher,80108,CAD,100135,MI,PT,Canada,L,Canada,0,"Kubernetes, Docker, R, Linux, Statistics",Master,3,Telecommunications,2025-03-07,2025-04-06,1393,6.1,Quantum Computing Inc -AI12733,Autonomous Systems Engineer,60460,CAD,75575,EN,PT,Canada,M,Canada,100,"Java, Kubernetes, Data Visualization",PhD,1,Energy,2024-09-25,2024-12-03,1853,10,DataVision Ltd -AI12734,Principal Data Scientist,110481,USD,110481,SE,PT,Sweden,S,Sweden,100,"Kubernetes, Hadoop, Data Visualization, Scala, Java",Bachelor,6,Technology,2024-01-30,2024-03-10,1762,9.4,Digital Transformation LLC -AI12735,AI Research Scientist,181707,EUR,154451,EX,PT,Germany,L,Germany,50,"MLOps, Linux, Hadoop",Bachelor,17,Automotive,2024-07-29,2024-08-19,500,9.7,Autonomous Tech -AI12736,AI Architect,171315,CAD,214144,EX,CT,Canada,S,Colombia,100,"SQL, Java, PyTorch",Bachelor,18,Consulting,2025-01-14,2025-02-22,2115,6,AI Innovations -AI12737,Machine Learning Researcher,186907,EUR,158871,EX,PT,France,S,France,0,"NLP, Hadoop, SQL, Statistics, R",Master,12,Real Estate,2025-04-10,2025-05-12,952,9.4,Cloud AI Solutions -AI12738,Computer Vision Engineer,197246,GBP,147935,EX,FL,United Kingdom,S,United Kingdom,50,"SQL, TensorFlow, Linux, Java",PhD,12,Technology,2024-12-10,2024-12-31,2123,6.2,Future Systems -AI12739,AI Research Scientist,62903,AUD,84919,EN,FL,Australia,M,Australia,0,"Python, Tableau, Scala",Bachelor,0,Media,2024-10-09,2024-12-06,834,6.6,Autonomous Tech -AI12740,Robotics Engineer,168184,CAD,210230,EX,PT,Canada,L,Canada,0,"Hadoop, Mathematics, Spark, Computer Vision, Python",Bachelor,10,Finance,2024-04-05,2024-05-31,2000,5.3,Smart Analytics -AI12741,AI Software Engineer,147859,CAD,184824,EX,FL,Canada,M,Germany,100,"SQL, Tableau, Statistics, Linux, Mathematics",Master,10,Gaming,2024-11-02,2025-01-09,858,8.9,Neural Networks Co -AI12742,Machine Learning Researcher,87226,EUR,74142,MI,FT,Netherlands,S,Romania,50,"Azure, R, SQL, AWS",PhD,2,Education,2024-08-09,2024-09-21,1357,5.7,Predictive Systems -AI12743,Machine Learning Engineer,138319,EUR,117571,SE,FL,France,L,France,0,"Computer Vision, Python, TensorFlow",PhD,9,Manufacturing,2024-11-03,2025-01-06,824,9.1,Future Systems -AI12744,Autonomous Systems Engineer,103507,GBP,77630,MI,CT,United Kingdom,M,Luxembourg,0,"Azure, Data Visualization, Python",PhD,4,Media,2024-04-16,2024-05-29,2078,8,Advanced Robotics -AI12745,Data Engineer,223904,EUR,190318,EX,FT,France,M,France,100,"Azure, PyTorch, Hadoop, Kubernetes, Spark",Associate,11,Transportation,2024-04-12,2024-05-29,581,6.1,Neural Networks Co -AI12746,ML Ops Engineer,142980,USD,142980,EX,FL,Finland,M,Austria,100,"R, SQL, Scala, AWS",Bachelor,15,Telecommunications,2024-10-10,2024-11-15,1600,7.9,DataVision Ltd -AI12747,Head of AI,64103,EUR,54488,EN,FL,Austria,M,Austria,100,"Scala, NLP, Java, GCP, Azure",Master,1,Technology,2025-01-14,2025-02-12,1817,6,Algorithmic Solutions -AI12748,Autonomous Systems Engineer,91062,EUR,77403,MI,PT,Austria,S,Austria,100,"Statistics, PyTorch, Spark, Git, Data Visualization",Master,4,Healthcare,2024-02-14,2024-04-27,1057,9.1,DataVision Ltd -AI12749,Robotics Engineer,78579,EUR,66792,EN,CT,Netherlands,L,Germany,100,"Python, Azure, Scala, Tableau",Bachelor,1,Telecommunications,2024-04-29,2024-05-16,1050,5,Advanced Robotics -AI12750,Deep Learning Engineer,115061,EUR,97802,MI,FL,France,L,France,50,"Linux, Java, R, Mathematics, Kubernetes",Bachelor,4,Manufacturing,2024-02-20,2024-03-05,1225,8.8,Cognitive Computing -AI12751,AI Software Engineer,61569,SGD,80040,EN,PT,Singapore,S,Colombia,0,"Azure, NLP, GCP, Java, Mathematics",PhD,0,Retail,2025-03-05,2025-05-06,1412,5.4,Machine Intelligence Group -AI12752,Principal Data Scientist,106803,SGD,138844,SE,CT,Singapore,S,Singapore,100,"Mathematics, Spark, Java, PyTorch",Associate,7,Finance,2024-09-24,2024-10-27,2223,7.5,Neural Networks Co -AI12753,Data Scientist,88775,USD,88775,MI,FT,Ireland,M,Ireland,50,"Python, Scala, NLP, Kubernetes, TensorFlow",Bachelor,4,Manufacturing,2024-07-23,2024-08-08,677,9.9,Cognitive Computing -AI12754,Principal Data Scientist,143329,CAD,179161,EX,FT,Canada,M,Indonesia,100,"Kubernetes, SQL, PyTorch",Associate,16,Consulting,2024-12-06,2025-01-24,1069,8,Machine Intelligence Group -AI12755,Machine Learning Researcher,83311,CHF,74980,EN,CT,Switzerland,S,China,50,"Git, Mathematics, SQL, PyTorch, Azure",Bachelor,0,Consulting,2025-02-01,2025-02-22,1003,8.6,Algorithmic Solutions -AI12756,Machine Learning Engineer,200496,GBP,150372,EX,FT,United Kingdom,S,United Kingdom,50,"R, Java, Computer Vision, Kubernetes",Associate,18,Finance,2024-04-07,2024-05-03,2129,5.8,Future Systems -AI12757,Principal Data Scientist,60235,SGD,78306,EN,CT,Singapore,S,Singapore,100,"Spark, SQL, R, Scala",Master,1,Media,2024-10-15,2024-12-08,963,6.9,Future Systems -AI12758,Head of AI,74675,USD,74675,EN,FT,Sweden,L,Netherlands,50,"Python, TensorFlow, Kubernetes",Associate,0,Energy,2024-10-02,2024-11-06,1444,5.8,Cloud AI Solutions -AI12759,AI Consultant,61377,EUR,52170,EN,FT,Austria,S,Austria,100,"SQL, NLP, Spark, MLOps",Associate,1,Transportation,2024-08-06,2024-10-02,1373,6.2,AI Innovations -AI12760,AI Specialist,23390,USD,23390,MI,PT,India,S,India,100,"Linux, R, SQL, Data Visualization, NLP",Associate,2,Telecommunications,2025-02-05,2025-03-01,882,7,TechCorp Inc -AI12761,Machine Learning Researcher,91528,EUR,77799,EN,CT,Netherlands,L,Netherlands,100,"Spark, Python, R, Linux",Master,1,Real Estate,2024-08-22,2024-09-25,2097,7.1,DataVision Ltd -AI12762,Robotics Engineer,146429,USD,146429,SE,PT,Denmark,S,Portugal,50,"Docker, AWS, Tableau, Computer Vision, Kubernetes",Associate,6,Retail,2025-02-08,2025-03-12,1796,5.6,DeepTech Ventures -AI12763,Machine Learning Engineer,44242,USD,44242,SE,FT,India,L,New Zealand,50,"Python, Hadoop, AWS, Statistics",Associate,6,Telecommunications,2025-01-07,2025-01-25,1911,6.5,Quantum Computing Inc -AI12764,Principal Data Scientist,141895,USD,141895,MI,PT,United States,L,United States,50,"Statistics, MLOps, Python",PhD,4,Finance,2025-04-15,2025-06-22,1539,6.5,DataVision Ltd -AI12765,Head of AI,172701,EUR,146796,EX,FT,France,L,Estonia,100,"TensorFlow, Git, Computer Vision, Tableau",Bachelor,16,Media,2024-11-21,2024-12-13,1649,6.9,Machine Intelligence Group -AI12766,AI Research Scientist,122947,JPY,13524170,SE,CT,Japan,S,Switzerland,50,"GCP, Git, Statistics",Master,6,Education,2024-11-02,2024-12-17,1589,8.2,Future Systems -AI12767,Data Analyst,76332,EUR,64882,EN,PT,Netherlands,M,Japan,50,"Java, Docker, PyTorch, Computer Vision, Azure",PhD,1,Energy,2024-09-19,2024-11-09,572,5.1,Predictive Systems -AI12768,ML Ops Engineer,165380,EUR,140573,EX,PT,Austria,S,China,100,"Kubernetes, NLP, GCP, Computer Vision",Associate,17,Education,2024-11-17,2024-12-18,551,5.7,Smart Analytics -AI12769,Head of AI,142751,EUR,121338,EX,FT,Austria,M,Austria,0,"Data Visualization, PyTorch, Tableau, Kubernetes",Bachelor,15,Technology,2024-06-24,2024-08-10,848,9.7,Algorithmic Solutions -AI12770,AI Architect,62156,USD,62156,EX,FL,India,M,India,100,"Java, R, NLP, Computer Vision, Kubernetes",Bachelor,14,Gaming,2024-10-21,2024-12-30,539,5.8,Smart Analytics -AI12771,AI Product Manager,152270,USD,152270,SE,FT,United States,M,United States,50,"Linux, AWS, Data Visualization",Associate,5,Media,2025-03-15,2025-04-17,1162,7.3,Autonomous Tech -AI12772,AI Software Engineer,86405,EUR,73444,MI,CT,Netherlands,M,Denmark,0,"NLP, Mathematics, SQL",Master,2,Automotive,2024-06-04,2024-06-27,1890,10,Cloud AI Solutions -AI12773,Machine Learning Engineer,82630,JPY,9089300,MI,FL,Japan,M,Japan,50,"Python, GCP, Data Visualization",PhD,3,Government,2024-10-04,2024-11-27,1829,7.5,Autonomous Tech -AI12774,AI Specialist,57873,USD,57873,EX,CT,China,S,Malaysia,100,"AWS, Azure, Mathematics",Associate,13,Telecommunications,2024-06-07,2024-07-12,1519,6.3,Digital Transformation LLC -AI12775,Robotics Engineer,28348,USD,28348,EN,FL,India,M,India,0,"Statistics, Spark, Python, Computer Vision, Git",PhD,0,Technology,2024-09-22,2024-11-17,723,8.3,Cognitive Computing -AI12776,Computer Vision Engineer,87180,SGD,113334,MI,FT,Singapore,M,Czech Republic,100,"Linux, Data Visualization, GCP, TensorFlow",PhD,2,Consulting,2024-07-15,2024-09-09,1059,9.7,Cloud AI Solutions -AI12777,Head of AI,91044,GBP,68283,EN,PT,United Kingdom,L,United Kingdom,0,"R, PyTorch, Spark, Git, SQL",Master,0,Retail,2025-03-04,2025-04-03,596,5.4,Digital Transformation LLC -AI12778,NLP Engineer,76331,USD,76331,MI,FT,South Korea,L,South Korea,100,"GCP, Kubernetes, Mathematics, Python",PhD,4,Retail,2025-02-17,2025-03-29,1303,5.6,Digital Transformation LLC -AI12779,Robotics Engineer,118613,EUR,100821,SE,CT,France,L,France,0,"Linux, AWS, Deep Learning",Bachelor,8,Telecommunications,2025-01-19,2025-03-09,615,5.2,DataVision Ltd -AI12780,Machine Learning Researcher,92441,GBP,69331,EN,FL,United Kingdom,L,United Kingdom,50,"R, Computer Vision, Linux, Hadoop, SQL",Associate,0,Retail,2024-01-28,2024-03-27,1260,8.2,Advanced Robotics -AI12781,Data Analyst,268946,CHF,242051,EX,CT,Switzerland,M,Switzerland,50,"Data Visualization, Linux, R, Tableau, NLP",Associate,11,Gaming,2024-05-10,2024-07-03,1285,6.6,Quantum Computing Inc -AI12782,Robotics Engineer,32200,USD,32200,EN,FT,China,S,Estonia,100,"SQL, Git, Azure",Bachelor,1,Finance,2024-10-15,2024-12-11,1756,8.6,AI Innovations -AI12783,Robotics Engineer,138675,GBP,104006,SE,FL,United Kingdom,L,United Kingdom,0,"NLP, Git, Kubernetes",PhD,8,Energy,2024-12-09,2025-02-01,1248,8.5,TechCorp Inc -AI12784,Robotics Engineer,68778,EUR,58461,EN,PT,Germany,L,Germany,100,"TensorFlow, Scala, PyTorch, MLOps",PhD,0,Automotive,2025-02-04,2025-03-16,693,6.4,Future Systems -AI12785,Machine Learning Engineer,209006,CHF,188105,SE,CT,Switzerland,M,Switzerland,100,"PyTorch, Python, NLP, Azure",Associate,9,Transportation,2024-06-10,2024-07-04,2219,8.9,Smart Analytics -AI12786,Machine Learning Engineer,131992,CAD,164990,EX,PT,Canada,M,Canada,0,"Python, NLP, Linux, MLOps, AWS",Associate,15,Gaming,2024-09-22,2024-11-16,1295,6.1,Cognitive Computing -AI12787,Data Engineer,94712,USD,94712,MI,FL,Sweden,L,Sweden,50,"Mathematics, PyTorch, Tableau",PhD,2,Technology,2024-03-28,2024-06-07,1216,8.4,Advanced Robotics -AI12788,NLP Engineer,134256,USD,134256,SE,FL,Sweden,S,Sweden,100,"Kubernetes, TensorFlow, GCP",PhD,5,Media,2025-04-24,2025-06-26,1279,7.7,AI Innovations -AI12789,Deep Learning Engineer,103820,USD,103820,MI,PT,Israel,M,Israel,50,"Python, Tableau, Statistics, TensorFlow, Spark",Bachelor,2,Real Estate,2025-03-01,2025-04-10,1980,6.8,Smart Analytics -AI12790,Research Scientist,90645,USD,90645,MI,PT,United States,M,Portugal,0,"PyTorch, Statistics, Kubernetes, NLP",Master,3,Media,2024-05-09,2024-07-02,585,8.9,Smart Analytics -AI12791,ML Ops Engineer,119424,USD,119424,MI,PT,Finland,L,Canada,100,"SQL, Deep Learning, AWS, PyTorch, Spark",PhD,2,Retail,2024-11-11,2024-12-03,2449,5.3,DeepTech Ventures -AI12792,AI Specialist,100887,USD,100887,MI,FL,Ireland,M,Ireland,100,"Git, GCP, Scala, Linux, PyTorch",Master,3,Manufacturing,2024-07-28,2024-09-22,2297,6.9,Quantum Computing Inc -AI12793,NLP Engineer,99370,USD,99370,EX,FT,China,S,China,0,"Python, Java, AWS",PhD,19,Education,2024-04-06,2024-05-03,1851,7.8,Advanced Robotics -AI12794,Deep Learning Engineer,136900,AUD,184815,EX,FT,Australia,M,Australia,100,"MLOps, Kubernetes, Scala",PhD,19,Finance,2024-11-07,2025-01-14,2396,7.5,Cognitive Computing -AI12795,Autonomous Systems Engineer,46438,USD,46438,EN,PT,South Korea,M,South Korea,0,"Kubernetes, SQL, Hadoop, GCP, Computer Vision",Bachelor,1,Manufacturing,2024-02-01,2024-03-09,2305,5.7,Predictive Systems -AI12796,Machine Learning Engineer,49841,USD,49841,MI,FL,China,M,China,0,"Scala, Git, Spark, SQL, Data Visualization",Associate,2,Gaming,2024-07-09,2024-08-19,2197,8.9,DataVision Ltd -AI12797,AI Research Scientist,87830,USD,87830,EX,FL,China,M,China,0,"Spark, Statistics, Python, Docker, Scala",Associate,12,Education,2024-04-02,2024-06-02,2416,9.3,Neural Networks Co -AI12798,Autonomous Systems Engineer,78608,EUR,66817,MI,CT,Austria,M,Austria,0,"R, Scala, TensorFlow, Java",PhD,3,Education,2024-02-26,2024-03-20,2454,5.2,TechCorp Inc -AI12799,Principal Data Scientist,76299,USD,76299,EN,FL,South Korea,L,Estonia,100,"Scala, Java, GCP",Master,0,Media,2024-07-24,2024-09-17,1410,6.9,TechCorp Inc -AI12800,Machine Learning Engineer,70823,USD,70823,MI,FT,Sweden,S,Sweden,100,"SQL, Hadoop, Git",Master,2,Transportation,2024-04-28,2024-06-09,1116,9,Neural Networks Co -AI12801,Head of AI,161626,USD,161626,SE,PT,Norway,L,Norway,50,"PyTorch, SQL, TensorFlow, Python, Deep Learning",Bachelor,7,Finance,2024-11-10,2024-12-06,2400,5.1,Quantum Computing Inc -AI12802,AI Specialist,94357,GBP,70768,MI,PT,United Kingdom,L,United Kingdom,0,"Scala, Spark, Mathematics, Git",PhD,3,Energy,2024-01-11,2024-03-21,1784,8.3,Future Systems -AI12803,AI Architect,154775,USD,154775,EX,CT,Sweden,M,Sweden,50,"Python, Hadoop, Mathematics",Master,15,Telecommunications,2024-04-16,2024-05-30,2227,8.8,Predictive Systems -AI12804,AI Software Engineer,81393,EUR,69184,MI,PT,France,M,France,100,"Deep Learning, SQL, Azure",Associate,4,Consulting,2025-02-09,2025-03-25,1445,6.4,DeepTech Ventures -AI12805,AI Software Engineer,64623,USD,64623,EN,PT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",Master,1,Energy,2024-06-21,2024-08-28,1928,5.5,DeepTech Ventures -AI12806,Autonomous Systems Engineer,53147,USD,53147,EN,CT,Finland,S,Egypt,100,"AWS, Python, Statistics, Tableau, Hadoop",PhD,1,Technology,2024-08-03,2024-10-07,1518,6.8,DeepTech Ventures -AI12807,Data Scientist,95590,USD,95590,SE,PT,Israel,S,Israel,100,"MLOps, AWS, GCP, NLP, Azure",Bachelor,5,Telecommunications,2024-07-03,2024-08-05,1154,6,Machine Intelligence Group -AI12808,Robotics Engineer,72897,USD,72897,EN,CT,Norway,S,Norway,0,"Spark, MLOps, Kubernetes, Linux, TensorFlow",Associate,1,Telecommunications,2024-06-07,2024-07-16,2207,6.8,Neural Networks Co -AI12809,AI Consultant,150728,USD,150728,EX,PT,United States,S,India,100,"Docker, Java, Statistics, SQL, Hadoop",Associate,14,Government,2024-08-13,2024-09-23,2349,8.2,Cognitive Computing -AI12810,ML Ops Engineer,117055,USD,117055,MI,CT,Norway,M,Norway,100,"Git, Docker, Python, Tableau, Azure",PhD,4,Manufacturing,2024-10-09,2024-12-19,794,5.6,Algorithmic Solutions -AI12811,Machine Learning Researcher,87825,EUR,74651,MI,FL,Austria,M,Austria,50,"SQL, Hadoop, TensorFlow, AWS",Bachelor,2,Media,2024-01-07,2024-02-23,2030,9.6,Algorithmic Solutions -AI12812,Data Analyst,199854,AUD,269803,EX,PT,Australia,S,United States,100,"Tableau, Hadoop, SQL, Data Visualization",Bachelor,13,Media,2024-08-28,2024-10-20,1378,6.7,Quantum Computing Inc -AI12813,Deep Learning Engineer,159183,EUR,135306,SE,FL,Netherlands,L,Netherlands,0,"Docker, Python, Tableau",Master,6,Transportation,2024-11-30,2025-01-19,1835,8,Digital Transformation LLC -AI12814,AI Specialist,64547,GBP,48410,EN,PT,United Kingdom,S,United Kingdom,100,"TensorFlow, SQL, Deep Learning, Docker, NLP",Master,0,Energy,2024-08-12,2024-10-21,666,5.8,Autonomous Tech -AI12815,Data Analyst,95432,CHF,85889,EN,FL,Switzerland,S,Switzerland,100,"Linux, SQL, Azure, Hadoop",Associate,0,Education,2024-08-22,2024-10-27,2451,7.1,Cloud AI Solutions -AI12816,AI Research Scientist,38213,USD,38213,MI,FT,India,M,India,50,"Hadoop, Python, Java",Master,2,Finance,2024-10-09,2024-11-24,2359,5.3,Cloud AI Solutions -AI12817,Computer Vision Engineer,122719,USD,122719,SE,PT,Finland,L,Finland,0,"Python, Data Visualization, Kubernetes, Docker, Linux",Bachelor,7,Gaming,2024-09-18,2024-11-22,1724,7.1,DeepTech Ventures -AI12818,Computer Vision Engineer,126604,CHF,113944,MI,PT,Switzerland,L,Switzerland,0,"AWS, Spark, Statistics, SQL, R",Associate,2,Consulting,2024-10-26,2024-11-29,605,8.4,Neural Networks Co -AI12819,Autonomous Systems Engineer,27641,USD,27641,MI,FT,India,S,India,50,"Git, TensorFlow, AWS",PhD,3,Education,2024-05-21,2024-07-16,1784,7.8,Predictive Systems -AI12820,Data Analyst,106504,USD,106504,EN,CT,Denmark,L,Denmark,0,"TensorFlow, Git, Statistics, Tableau, MLOps",Master,1,Finance,2025-04-29,2025-07-02,2091,8.6,TechCorp Inc -AI12821,AI Product Manager,211310,EUR,179614,EX,PT,Netherlands,M,Netherlands,50,"Git, NLP, AWS, Hadoop",Associate,13,Energy,2024-11-07,2024-11-24,1971,6.2,DeepTech Ventures -AI12822,Autonomous Systems Engineer,55929,USD,55929,MI,CT,China,L,China,0,"Java, Linux, Python, GCP",Associate,3,Telecommunications,2024-03-26,2024-05-25,2125,8.5,Cognitive Computing -AI12823,Principal Data Scientist,189125,GBP,141844,EX,FT,United Kingdom,L,Singapore,0,"AWS, PyTorch, Java, TensorFlow, Statistics",Master,16,Education,2024-06-21,2024-07-30,2004,5.9,TechCorp Inc -AI12824,AI Product Manager,232230,JPY,25545300,EX,FT,Japan,L,Japan,50,"Scala, Docker, Linux, Azure",PhD,14,Consulting,2024-02-10,2024-03-25,719,7.2,Cloud AI Solutions -AI12825,AI Architect,92533,AUD,124920,MI,FT,Australia,M,Australia,100,"Kubernetes, SQL, Azure, Linux",Bachelor,3,Real Estate,2024-04-26,2024-05-30,1982,5.1,Advanced Robotics -AI12826,Head of AI,170727,USD,170727,EX,CT,South Korea,S,France,0,"TensorFlow, Java, Computer Vision",Associate,15,Real Estate,2024-09-04,2024-11-03,829,5.8,DeepTech Ventures -AI12827,Machine Learning Researcher,64528,USD,64528,EN,CT,Finland,M,Finland,0,"Git, Java, Statistics",Bachelor,0,Consulting,2025-03-14,2025-04-02,1203,9.1,Quantum Computing Inc -AI12828,Robotics Engineer,86994,GBP,65246,EN,PT,United Kingdom,L,Malaysia,50,"Azure, AWS, GCP, Linux",Master,1,Automotive,2025-04-13,2025-05-02,1858,8.6,Cloud AI Solutions -AI12829,AI Architect,195324,USD,195324,EX,FL,Israel,L,Canada,50,"GCP, Spark, SQL, PyTorch, Computer Vision",Master,11,Technology,2024-06-13,2024-07-28,511,9.3,Digital Transformation LLC -AI12830,AI Architect,107212,EUR,91130,SE,CT,Netherlands,S,Germany,50,"Docker, Java, Mathematics",Associate,9,Education,2025-04-30,2025-05-28,1555,7.1,DataVision Ltd -AI12831,Data Scientist,63595,USD,63595,EN,CT,Ireland,M,Ireland,50,"Scala, Python, TensorFlow, Mathematics",Bachelor,0,Gaming,2024-01-14,2024-03-16,2066,7.9,Algorithmic Solutions -AI12832,Data Engineer,146168,USD,146168,SE,PT,United States,M,United States,50,"Tableau, Java, Azure, SQL, PyTorch",Associate,7,Media,2025-04-18,2025-05-15,1733,8.2,Smart Analytics -AI12833,AI Product Manager,23158,USD,23158,EN,FT,China,S,China,0,"Git, NLP, SQL",Master,1,Government,2024-03-17,2024-04-18,1055,8.3,Digital Transformation LLC -AI12834,Data Engineer,74146,EUR,63024,EN,FT,Austria,M,Austria,0,"Linux, Tableau, Git, R, Statistics",Bachelor,1,Media,2024-11-16,2024-12-24,2186,9.8,Future Systems -AI12835,NLP Engineer,244490,SGD,317837,EX,FL,Singapore,M,Vietnam,50,"Python, TensorFlow, AWS, Scala, PyTorch",Master,16,Consulting,2024-08-20,2024-09-05,1520,7.4,DeepTech Ventures -AI12836,Data Analyst,135650,USD,135650,MI,FT,United States,L,Czech Republic,0,"Scala, Azure, PyTorch, Deep Learning, Tableau",Master,2,Technology,2025-02-25,2025-03-23,1602,6.2,Machine Intelligence Group -AI12837,AI Product Manager,161057,EUR,136898,SE,PT,France,L,France,0,"Deep Learning, NLP, MLOps, Scala, TensorFlow",Associate,8,Retail,2025-02-26,2025-04-30,873,5.7,Future Systems -AI12838,AI Research Scientist,95999,SGD,124799,MI,FL,Singapore,L,Australia,50,"SQL, R, MLOps, NLP",Associate,4,Transportation,2024-03-27,2024-06-02,897,5.7,AI Innovations -AI12839,Autonomous Systems Engineer,75071,USD,75071,EN,CT,Sweden,L,Sweden,50,"Tableau, TensorFlow, PyTorch",Associate,0,Manufacturing,2025-04-25,2025-06-11,2289,8,Cloud AI Solutions -AI12840,AI Research Scientist,80156,USD,80156,EN,CT,Sweden,L,Sweden,100,"Scala, SQL, MLOps",Bachelor,0,Manufacturing,2024-04-21,2024-06-27,2425,5.1,Algorithmic Solutions -AI12841,NLP Engineer,77757,CHF,69981,EN,FL,Switzerland,M,Switzerland,0,"SQL, Kubernetes, TensorFlow, Git",PhD,0,Media,2024-01-07,2024-03-20,964,8.7,AI Innovations -AI12842,Machine Learning Engineer,56236,USD,56236,EN,PT,South Korea,M,South Korea,50,"Python, R, Data Visualization, Java, MLOps",Bachelor,1,Consulting,2025-03-15,2025-05-07,2054,9.7,Machine Intelligence Group -AI12843,Computer Vision Engineer,240245,JPY,26426950,EX,CT,Japan,M,Japan,100,"Scala, Java, R, Computer Vision, Git",PhD,14,Technology,2025-01-31,2025-04-01,1258,8.5,Future Systems -AI12844,Data Analyst,275028,USD,275028,EX,PT,Ireland,L,Ireland,100,"Deep Learning, Azure, GCP",Master,12,Manufacturing,2024-02-22,2024-04-02,1031,6.5,Digital Transformation LLC -AI12845,AI Consultant,186213,EUR,158281,EX,CT,Austria,L,Austria,100,"Data Visualization, Linux, SQL, Deep Learning",Bachelor,18,Media,2024-01-25,2024-03-19,2022,7.2,Algorithmic Solutions -AI12846,Data Engineer,287124,USD,287124,EX,FT,Norway,S,Norway,50,"Linux, Tableau, Hadoop, Computer Vision",Bachelor,15,Transportation,2025-02-11,2025-04-13,2175,6.8,Digital Transformation LLC -AI12847,Data Scientist,135404,CHF,121864,MI,PT,Switzerland,M,Switzerland,100,"SQL, Kubernetes, Tableau, Linux",Master,3,Transportation,2025-02-14,2025-04-05,2281,8.1,Quantum Computing Inc -AI12848,Principal Data Scientist,159276,EUR,135385,SE,PT,France,L,France,50,"Hadoop, Docker, Kubernetes, MLOps",PhD,8,Consulting,2024-11-12,2025-01-08,673,8.6,AI Innovations -AI12849,Data Engineer,93350,USD,93350,SE,FL,Sweden,S,Sweden,100,"Linux, Data Visualization, Python",Associate,8,Government,2025-01-28,2025-04-02,533,6.7,AI Innovations -AI12850,AI Product Manager,264276,USD,264276,EX,PT,Ireland,L,Nigeria,50,"Java, SQL, Deep Learning, Hadoop, Spark",Associate,10,Consulting,2025-01-09,2025-02-28,2452,7.7,Machine Intelligence Group -AI12851,ML Ops Engineer,31006,USD,31006,MI,CT,India,S,India,50,"Deep Learning, Python, AWS, Tableau, Spark",Bachelor,4,Manufacturing,2025-04-17,2025-05-19,1090,7.9,Advanced Robotics -AI12852,AI Architect,132059,USD,132059,SE,FT,Israel,M,Israel,50,"Spark, SQL, MLOps",PhD,8,Automotive,2025-01-23,2025-02-12,1688,7,Cloud AI Solutions -AI12853,NLP Engineer,85658,AUD,115638,MI,FL,Australia,L,Japan,50,"Python, NLP, Computer Vision, Git",Bachelor,2,Manufacturing,2024-04-03,2024-05-21,1069,8.1,Neural Networks Co -AI12854,Data Scientist,107273,EUR,91182,SE,PT,Germany,S,Germany,0,"Python, Git, Hadoop",Bachelor,6,Government,2024-07-11,2024-08-21,1704,8.7,Algorithmic Solutions -AI12855,Data Scientist,120446,EUR,102379,SE,CT,Netherlands,S,Netherlands,0,"Linux, Java, Git, Tableau",Bachelor,7,Manufacturing,2024-02-22,2024-04-23,1512,5.8,Future Systems -AI12856,Principal Data Scientist,92064,USD,92064,MI,FL,Israel,L,Israel,100,"Python, GCP, Computer Vision, TensorFlow",Bachelor,2,Real Estate,2025-04-30,2025-05-29,779,7.7,AI Innovations -AI12857,ML Ops Engineer,170651,USD,170651,EX,PT,Finland,S,Brazil,100,"AWS, Azure, Python, TensorFlow",Associate,17,Gaming,2024-05-08,2024-05-29,1131,8.1,DeepTech Ventures -AI12858,Principal Data Scientist,209732,USD,209732,EX,FL,United States,L,United States,0,"Python, Docker, Data Visualization, Azure",PhD,13,Healthcare,2024-09-09,2024-10-09,1392,8.9,Autonomous Tech -AI12859,Data Scientist,90595,EUR,77006,MI,FL,France,M,France,100,"Data Visualization, Docker, Tableau, SQL",Bachelor,2,Retail,2025-04-17,2025-05-23,1909,9.4,Cognitive Computing -AI12860,ML Ops Engineer,134103,GBP,100577,SE,PT,United Kingdom,L,United Kingdom,0,"GCP, Spark, Tableau",Associate,6,Telecommunications,2024-09-05,2024-10-15,2247,5.8,Predictive Systems -AI12861,AI Software Engineer,328767,USD,328767,EX,CT,Norway,M,Norway,50,"Git, Mathematics, Deep Learning, PyTorch",PhD,14,Gaming,2024-03-27,2024-04-23,813,8.1,TechCorp Inc -AI12862,Head of AI,201006,USD,201006,EX,CT,Israel,M,Denmark,0,"TensorFlow, Python, Docker",PhD,14,Transportation,2025-02-28,2025-04-20,999,5.7,DataVision Ltd -AI12863,Research Scientist,127726,JPY,14049860,SE,PT,Japan,S,Japan,50,"Mathematics, AWS, PyTorch, Deep Learning, Java",PhD,8,Gaming,2025-04-10,2025-04-30,742,6.3,Predictive Systems -AI12864,Computer Vision Engineer,269096,USD,269096,EX,FL,United States,L,United States,50,"TensorFlow, MLOps, Tableau",Associate,17,Education,2024-10-04,2024-11-24,1224,7.5,Cognitive Computing -AI12865,Data Engineer,149753,EUR,127290,SE,FT,Austria,L,China,100,"GCP, Spark, Scala, Data Visualization, Python",Master,7,Education,2024-11-28,2025-01-08,637,5.5,Future Systems -AI12866,ML Ops Engineer,145711,SGD,189424,SE,PT,Singapore,M,Singapore,100,"Scala, Docker, Statistics, Deep Learning, Computer Vision",Bachelor,5,Real Estate,2025-02-18,2025-04-01,2320,9.4,Predictive Systems -AI12867,AI Consultant,20533,USD,20533,EN,FT,India,S,India,100,"Scala, Kubernetes, Hadoop",Associate,0,Technology,2025-01-16,2025-02-02,1142,9.7,Future Systems -AI12868,NLP Engineer,80896,USD,80896,EN,CT,United States,L,United States,0,"Python, TensorFlow, Azure, Java, Tableau",PhD,0,Telecommunications,2024-02-09,2024-04-07,1088,6.5,Digital Transformation LLC -AI12869,Autonomous Systems Engineer,128356,EUR,109103,SE,FT,Netherlands,L,Netherlands,0,"NLP, TensorFlow, R, Computer Vision, Scala",Bachelor,5,Consulting,2024-12-27,2025-02-25,520,9.3,Cloud AI Solutions -AI12870,Data Engineer,118886,USD,118886,SE,FL,United States,S,Kenya,50,"Java, MLOps, Computer Vision, AWS, Azure",PhD,7,Education,2024-03-06,2024-03-26,1504,8.8,Future Systems -AI12871,AI Architect,115314,USD,115314,MI,FT,Denmark,S,Denmark,100,"Linux, Python, NLP, Git",Associate,2,Consulting,2024-11-16,2024-12-24,777,6,Quantum Computing Inc -AI12872,Data Scientist,132602,CHF,119342,MI,CT,Switzerland,S,Switzerland,100,"Python, Spark, Deep Learning",PhD,2,Consulting,2024-07-23,2024-08-12,2381,9.1,Advanced Robotics -AI12873,AI Software Engineer,145255,GBP,108941,EX,CT,United Kingdom,S,United Kingdom,50,"MLOps, Mathematics, Docker, PyTorch, TensorFlow",Associate,17,Automotive,2024-10-21,2024-11-20,2468,5.5,Cloud AI Solutions -AI12874,ML Ops Engineer,139099,USD,139099,SE,PT,South Korea,L,South Korea,0,"Spark, Azure, Data Visualization, GCP",Bachelor,8,Transportation,2025-03-16,2025-04-18,2132,7.1,Machine Intelligence Group -AI12875,AI Architect,112407,CHF,101166,MI,FL,Switzerland,M,Netherlands,100,"Hadoop, NLP, Tableau",Bachelor,3,Government,2025-01-10,2025-02-26,1032,8,Advanced Robotics -AI12876,Data Scientist,113716,USD,113716,MI,FL,Ireland,L,Ireland,100,"PyTorch, GCP, Statistics",Associate,4,Real Estate,2024-11-24,2024-12-16,2045,5.2,Machine Intelligence Group -AI12877,Data Scientist,45202,USD,45202,EN,FT,South Korea,S,South Korea,50,"Tableau, Java, Kubernetes, Azure, Scala",Master,0,Education,2024-02-17,2024-03-13,1242,6.1,Cloud AI Solutions -AI12878,Autonomous Systems Engineer,131630,USD,131630,EX,PT,Israel,M,Israel,50,"Git, Java, Linux, TensorFlow, Deep Learning",Master,13,Automotive,2025-01-24,2025-03-21,1311,5,TechCorp Inc -AI12879,Computer Vision Engineer,130641,JPY,14370510,MI,FT,Japan,L,Japan,50,"Python, Spark, Scala, Data Visualization, SQL",Associate,3,Real Estate,2024-12-18,2025-01-23,2057,6.3,TechCorp Inc -AI12880,Deep Learning Engineer,270691,GBP,203018,EX,CT,United Kingdom,L,United Kingdom,100,"Tableau, Azure, Java, SQL, Computer Vision",Master,16,Education,2025-03-14,2025-04-22,1824,6.9,Neural Networks Co -AI12881,AI Product Manager,90830,USD,90830,MI,PT,United States,M,United States,100,"MLOps, Data Visualization, Python, SQL, GCP",Master,3,Education,2025-01-14,2025-02-11,1273,6.8,Smart Analytics -AI12882,AI Architect,155288,USD,155288,EX,CT,South Korea,S,Canada,50,"Python, Deep Learning, TensorFlow, Java, Statistics",PhD,18,Manufacturing,2025-01-27,2025-03-23,1295,7.8,Algorithmic Solutions -AI12883,NLP Engineer,55458,USD,55458,EN,CT,Finland,M,Finland,0,"Python, TensorFlow, Statistics",Associate,0,Healthcare,2024-02-11,2024-02-25,1132,6.2,Cloud AI Solutions -AI12884,Research Scientist,142729,USD,142729,MI,FL,Norway,M,Norway,100,"Kubernetes, MLOps, Scala, Computer Vision",Master,2,Transportation,2024-03-24,2024-05-13,2222,6.5,Smart Analytics -AI12885,Data Engineer,72858,USD,72858,EN,CT,Denmark,M,Switzerland,100,"SQL, R, Tableau, AWS, Computer Vision",Bachelor,0,Retail,2025-01-12,2025-02-06,1491,5.6,Future Systems -AI12886,Robotics Engineer,107428,AUD,145028,MI,FT,Australia,L,Australia,0,"Computer Vision, Python, Git, Kubernetes, Docker",Associate,3,Telecommunications,2024-06-09,2024-07-13,1024,9.4,Machine Intelligence Group -AI12887,Data Scientist,86669,EUR,73669,MI,FT,Netherlands,M,Netherlands,0,"Docker, Hadoop, MLOps, Git",Bachelor,3,Finance,2025-02-07,2025-03-21,1124,9.1,Digital Transformation LLC -AI12888,Research Scientist,128076,CAD,160095,EX,CT,Canada,M,Singapore,50,"Deep Learning, NLP, Data Visualization, Kubernetes",PhD,13,Media,2025-01-16,2025-03-10,923,9.5,DeepTech Ventures -AI12889,Machine Learning Engineer,106104,USD,106104,SE,PT,Israel,M,Israel,0,"Azure, SQL, Data Visualization, Python",Associate,5,Transportation,2024-03-23,2024-04-15,1567,9.3,Algorithmic Solutions -AI12890,Deep Learning Engineer,68721,USD,68721,MI,FL,Sweden,S,South Korea,50,"Scala, Spark, MLOps",Master,2,Energy,2024-05-15,2024-07-17,771,6.1,Future Systems -AI12891,NLP Engineer,86559,CAD,108199,MI,CT,Canada,M,Canada,50,"SQL, Kubernetes, Mathematics, Computer Vision, Azure",Associate,4,Gaming,2024-04-18,2024-06-28,2191,5,DeepTech Ventures -AI12892,ML Ops Engineer,61330,USD,61330,EN,FL,Israel,S,Israel,100,"NLP, PyTorch, Tableau, Scala, Java",PhD,1,Government,2024-03-06,2024-04-27,2174,5.7,Algorithmic Solutions -AI12893,Research Scientist,119858,AUD,161808,MI,PT,Australia,L,China,50,"Tableau, Statistics, Azure",Master,3,Media,2024-10-30,2024-11-13,1341,8.4,Quantum Computing Inc -AI12894,Robotics Engineer,118666,USD,118666,EN,FL,Norway,L,United States,0,"Scala, GCP, MLOps",PhD,1,Real Estate,2024-05-18,2024-07-03,1551,7.1,Digital Transformation LLC -AI12895,Autonomous Systems Engineer,25726,USD,25726,EN,FL,China,S,China,50,"TensorFlow, Linux, MLOps, R",Master,0,Transportation,2025-03-03,2025-03-22,2314,7.6,Machine Intelligence Group -AI12896,AI Specialist,29930,USD,29930,EN,CT,India,L,India,50,"Linux, Python, Tableau",Bachelor,0,Gaming,2024-04-21,2024-06-12,2416,7.5,DeepTech Ventures -AI12897,AI Architect,37505,USD,37505,MI,PT,India,M,India,0,"Mathematics, MLOps, Data Visualization",Bachelor,2,Media,2024-01-01,2024-01-22,1487,6.2,Predictive Systems -AI12898,Head of AI,116283,USD,116283,MI,CT,United States,S,Nigeria,0,"Git, Computer Vision, PyTorch, Hadoop",PhD,2,Automotive,2024-10-10,2024-12-09,1497,9.3,Neural Networks Co -AI12899,AI Product Manager,45147,USD,45147,SE,CT,India,S,India,0,"Python, TensorFlow, GCP",Associate,5,Real Estate,2024-05-06,2024-07-13,1498,5.7,Machine Intelligence Group -AI12900,Principal Data Scientist,66746,USD,66746,EN,CT,Israel,S,Israel,0,"Kubernetes, GCP, Tableau",PhD,0,Technology,2025-02-23,2025-04-21,1410,9.4,AI Innovations -AI12901,Data Analyst,61929,CAD,77411,EN,CT,Canada,M,Canada,100,"Git, Computer Vision, Statistics, Data Visualization, Java",Master,1,Retail,2024-06-06,2024-07-29,1877,6.8,Quantum Computing Inc -AI12902,Head of AI,210982,USD,210982,EX,FT,Sweden,M,Sweden,50,"Data Visualization, Tableau, Linux, TensorFlow, Java",Associate,11,Media,2024-03-04,2024-05-01,2082,9.4,Smart Analytics -AI12903,NLP Engineer,82621,SGD,107407,EN,FL,Singapore,L,Germany,100,"Tableau, PyTorch, TensorFlow, Python",Associate,1,Telecommunications,2025-03-15,2025-04-29,1755,7.7,AI Innovations -AI12904,Machine Learning Engineer,227131,EUR,193061,EX,FT,Germany,L,Germany,50,"Spark, PyTorch, Azure",Master,16,Automotive,2024-12-17,2025-01-21,640,7,Digital Transformation LLC -AI12905,Machine Learning Researcher,113462,USD,113462,MI,FL,United States,S,United States,0,"Azure, Tableau, Scala",Associate,2,Technology,2024-11-30,2024-12-19,2147,6,Algorithmic Solutions -AI12906,Machine Learning Researcher,146522,USD,146522,SE,PT,Denmark,M,Denmark,50,"Data Visualization, MLOps, Docker, Scala, R",Bachelor,7,Consulting,2024-12-31,2025-01-22,2267,8.2,Cloud AI Solutions -AI12907,AI Architect,310444,USD,310444,EX,FL,Denmark,M,Denmark,0,"NLP, TensorFlow, Java",PhD,17,Gaming,2025-02-07,2025-03-14,1768,5.4,Future Systems -AI12908,Machine Learning Engineer,212270,CAD,265338,EX,FL,Canada,S,Canada,50,"Scala, AWS, Computer Vision",PhD,10,Consulting,2024-12-01,2024-12-15,821,9.7,Autonomous Tech -AI12909,Principal Data Scientist,55426,USD,55426,MI,PT,South Korea,S,South Korea,0,"NLP, TensorFlow, PyTorch, Linux",Master,3,Technology,2025-01-25,2025-03-15,2111,9.6,Autonomous Tech -AI12910,NLP Engineer,284645,USD,284645,EX,PT,Denmark,M,Denmark,0,"SQL, Hadoop, Mathematics, MLOps, AWS",Bachelor,17,Automotive,2025-04-30,2025-05-15,1964,5.2,Advanced Robotics -AI12911,Machine Learning Engineer,91905,EUR,78119,MI,PT,France,M,France,100,"Kubernetes, MLOps, Linux, Java",Associate,3,Real Estate,2024-09-04,2024-10-07,1258,8.4,Neural Networks Co -AI12912,AI Consultant,46252,USD,46252,EN,FT,South Korea,S,South Korea,100,"Mathematics, Spark, MLOps, Computer Vision",Associate,1,Education,2024-07-15,2024-08-06,596,5.6,Digital Transformation LLC -AI12913,Data Engineer,140999,EUR,119849,SE,CT,Germany,L,Germany,0,"TensorFlow, Python, Hadoop",Master,6,Government,2024-04-19,2024-05-24,969,5.3,DataVision Ltd -AI12914,AI Architect,61460,USD,61460,EN,FT,Ireland,L,Philippines,100,"MLOps, Python, TensorFlow",PhD,0,Transportation,2024-12-28,2025-02-06,1746,8.3,TechCorp Inc -AI12915,AI Product Manager,107693,USD,107693,EN,FT,United States,L,United States,0,"Data Visualization, Kubernetes, NLP, AWS",Master,1,Telecommunications,2024-01-18,2024-02-22,1186,5.5,DataVision Ltd -AI12916,Deep Learning Engineer,202576,CAD,253220,EX,FT,Canada,L,Canada,100,"Azure, Deep Learning, GCP, Docker",Associate,15,Telecommunications,2024-09-09,2024-10-15,1817,9.4,DataVision Ltd -AI12917,AI Architect,61666,USD,61666,EN,FT,Israel,S,Israel,0,"Hadoop, R, Mathematics",Associate,1,Energy,2024-08-31,2024-09-15,2378,8.5,Cloud AI Solutions -AI12918,Data Scientist,40597,USD,40597,MI,FT,China,M,China,0,"R, MLOps, PyTorch",Master,4,Real Estate,2024-12-25,2025-03-01,1634,6.4,Cloud AI Solutions -AI12919,AI Research Scientist,136441,SGD,177373,SE,FL,Singapore,L,Singapore,0,"Docker, GCP, MLOps",Master,8,Automotive,2024-02-03,2024-04-05,1625,5.8,Predictive Systems -AI12920,Principal Data Scientist,64127,USD,64127,SE,PT,China,L,China,50,"Scala, TensorFlow, Kubernetes",Master,8,Gaming,2024-09-04,2024-10-11,581,7.2,Machine Intelligence Group -AI12921,ML Ops Engineer,104753,AUD,141417,SE,FL,Australia,M,Turkey,0,"GCP, Spark, Statistics",Bachelor,5,Gaming,2024-07-07,2024-08-15,1289,9.6,Quantum Computing Inc -AI12922,Principal Data Scientist,122222,USD,122222,MI,PT,Denmark,M,United Kingdom,50,"Docker, Deep Learning, Scala",Bachelor,2,Education,2024-07-30,2024-09-01,584,9.3,Predictive Systems -AI12923,NLP Engineer,101788,EUR,86520,SE,FL,France,M,France,50,"Data Visualization, Python, SQL, R, Java",Bachelor,9,Consulting,2024-08-30,2024-10-18,2421,9.7,AI Innovations -AI12924,Autonomous Systems Engineer,341521,CHF,307369,EX,FT,Switzerland,L,Australia,50,"Linux, Docker, SQL, GCP",Bachelor,11,Consulting,2024-11-01,2024-11-24,736,5.9,Cloud AI Solutions -AI12925,AI Specialist,63658,USD,63658,EN,PT,Israel,M,Israel,0,"Data Visualization, MLOps, Python, Java",PhD,0,Education,2024-04-18,2024-05-13,1176,9,Neural Networks Co -AI12926,Data Engineer,172241,USD,172241,EX,PT,Finland,M,Finland,50,"Scala, Hadoop, Data Visualization, NLP",Bachelor,11,Energy,2025-03-25,2025-04-20,1125,7.9,Algorithmic Solutions -AI12927,Data Engineer,80284,EUR,68241,MI,CT,Netherlands,M,Netherlands,100,"Linux, PyTorch, SQL",PhD,3,Energy,2024-11-19,2025-01-10,2146,8.8,Autonomous Tech -AI12928,Head of AI,82705,USD,82705,EN,FT,Sweden,L,Sweden,0,"Mathematics, Tableau, Hadoop, PyTorch",PhD,0,Finance,2024-03-09,2024-04-10,1351,8.1,Neural Networks Co -AI12929,ML Ops Engineer,82163,USD,82163,EN,PT,Finland,L,Finland,0,"Docker, MLOps, Deep Learning, Kubernetes, GCP",Associate,1,Manufacturing,2025-04-24,2025-06-19,1669,8.8,Algorithmic Solutions -AI12930,Principal Data Scientist,134609,USD,134609,SE,FT,Ireland,S,Ireland,100,"R, TensorFlow, Hadoop",Associate,9,Transportation,2025-02-10,2025-03-15,2238,7.6,Future Systems -AI12931,Machine Learning Researcher,50356,EUR,42803,EN,PT,Germany,S,Germany,0,"Git, TensorFlow, Data Visualization",Bachelor,1,Education,2025-04-13,2025-06-15,777,6.3,Digital Transformation LLC -AI12932,Robotics Engineer,100882,USD,100882,MI,CT,United States,S,United States,100,"Hadoop, Tableau, Git",Associate,3,Media,2024-11-07,2025-01-13,1996,6,Cloud AI Solutions -AI12933,AI Software Engineer,97133,USD,97133,SE,CT,Finland,M,Finland,100,"Computer Vision, Python, SQL, Docker",Associate,6,Education,2024-04-20,2024-05-18,2044,7.9,Cognitive Computing -AI12934,Data Engineer,169587,USD,169587,SE,PT,United States,L,United States,50,"R, GCP, SQL",Bachelor,6,Retail,2025-04-07,2025-05-13,612,7.6,Neural Networks Co -AI12935,AI Consultant,218131,EUR,185411,EX,CT,France,M,Turkey,0,"Hadoop, SQL, GCP, Git",Bachelor,10,Education,2025-02-18,2025-03-22,2034,8.5,Machine Intelligence Group -AI12936,NLP Engineer,103226,USD,103226,MI,CT,United States,M,Turkey,0,"Python, Hadoop, MLOps, Data Visualization, PyTorch",Bachelor,4,Retail,2024-09-23,2024-10-30,1512,6.2,AI Innovations -AI12937,Principal Data Scientist,100052,USD,100052,EN,PT,United States,L,United States,50,"PyTorch, R, Linux, Kubernetes, Scala",PhD,0,Consulting,2025-01-27,2025-04-08,1611,6.2,Algorithmic Solutions -AI12938,Deep Learning Engineer,166634,USD,166634,SE,FL,Norway,M,United States,0,"GCP, Python, Scala, Docker",Bachelor,8,Real Estate,2024-02-04,2024-02-29,673,9.3,Future Systems -AI12939,AI Consultant,116226,USD,116226,SE,FT,Sweden,M,Sweden,50,"PyTorch, Java, TensorFlow",Bachelor,6,Finance,2024-05-14,2024-07-11,1881,6.1,DeepTech Ventures -AI12940,NLP Engineer,95173,EUR,80897,SE,FL,Germany,S,Canada,0,"Scala, Java, Mathematics, Linux, Git",Master,6,Gaming,2024-08-21,2024-10-31,1306,9.8,Future Systems -AI12941,Data Scientist,164965,EUR,140220,EX,CT,Germany,S,Germany,0,"TensorFlow, Docker, Deep Learning, Python, Git",Bachelor,17,Consulting,2025-02-06,2025-03-09,1669,7.8,AI Innovations -AI12942,AI Architect,110208,CHF,99187,MI,CT,Switzerland,S,Switzerland,0,"SQL, Hadoop, R",PhD,4,Technology,2024-05-28,2024-07-06,712,9.8,AI Innovations -AI12943,AI Consultant,66541,USD,66541,EN,FT,United States,S,Brazil,100,"Kubernetes, Mathematics, NLP, SQL, Tableau",Bachelor,0,Consulting,2025-04-07,2025-05-14,2176,8.2,Digital Transformation LLC -AI12944,Computer Vision Engineer,349894,USD,349894,EX,FT,Norway,L,Norway,100,"SQL, Python, MLOps, Statistics",Master,14,Technology,2025-02-07,2025-03-15,1449,8.7,AI Innovations -AI12945,Machine Learning Engineer,186739,CHF,168065,SE,FT,Switzerland,S,Switzerland,0,"Deep Learning, Git, Java",PhD,9,Manufacturing,2024-05-22,2024-07-01,1850,7.5,Digital Transformation LLC -AI12946,Machine Learning Researcher,239337,SGD,311138,EX,FT,Singapore,S,Singapore,50,"Tableau, Java, NLP",Master,19,Education,2024-04-03,2024-04-29,2231,9.4,Algorithmic Solutions -AI12947,Machine Learning Researcher,36462,USD,36462,MI,FL,India,M,India,100,"TensorFlow, PyTorch, MLOps, GCP",PhD,4,Finance,2024-05-15,2024-07-10,2444,5.7,Machine Intelligence Group -AI12948,Data Analyst,91501,USD,91501,EN,CT,Denmark,M,Denmark,0,"Mathematics, R, Python",Master,1,Real Estate,2024-09-28,2024-10-18,747,5.5,DataVision Ltd -AI12949,Head of AI,112775,USD,112775,SE,CT,South Korea,L,Austria,0,"SQL, Computer Vision, Linux",Bachelor,5,Manufacturing,2024-10-03,2024-11-23,1899,8.5,Machine Intelligence Group -AI12950,Principal Data Scientist,114451,CAD,143064,SE,PT,Canada,L,Denmark,50,"Java, Hadoop, Tableau, Computer Vision, Statistics",PhD,9,Consulting,2024-02-04,2024-02-24,1992,8.1,Predictive Systems -AI12951,AI Specialist,106509,SGD,138462,SE,PT,Singapore,S,Singapore,0,"Kubernetes, SQL, Azure, PyTorch, TensorFlow",Associate,5,Consulting,2024-03-26,2024-05-09,2482,5.1,Future Systems -AI12952,AI Research Scientist,122296,JPY,13452560,SE,FL,Japan,S,Japan,50,"Kubernetes, SQL, Git, Data Visualization, NLP",Master,7,Retail,2024-06-17,2024-08-08,1647,9.2,DeepTech Ventures -AI12953,ML Ops Engineer,105130,USD,105130,EX,FL,South Korea,S,Egypt,0,"PyTorch, NLP, Python, Hadoop, GCP",Associate,18,Finance,2025-02-07,2025-04-21,1519,6,Advanced Robotics -AI12954,AI Consultant,54001,USD,54001,EN,PT,Israel,S,Israel,0,"SQL, Mathematics, TensorFlow, Python, Kubernetes",PhD,0,Gaming,2024-08-06,2024-09-01,2349,9.3,Digital Transformation LLC -AI12955,Data Scientist,48008,USD,48008,EN,FL,Finland,M,Singapore,50,"Data Visualization, Linux, Deep Learning, MLOps",Bachelor,1,Government,2024-02-20,2024-04-03,1739,8.7,Future Systems -AI12956,AI Software Engineer,48486,CAD,60608,EN,FT,Canada,S,Canada,0,"Spark, TensorFlow, SQL, Data Visualization, Kubernetes",Bachelor,1,Media,2025-01-18,2025-02-09,1337,10,Smart Analytics -AI12957,Machine Learning Researcher,270112,EUR,229595,EX,CT,Germany,L,Germany,0,"AWS, Python, Computer Vision",PhD,14,Manufacturing,2024-05-16,2024-07-01,855,7.7,DataVision Ltd -AI12958,AI Research Scientist,90538,EUR,76957,MI,FL,Germany,S,India,100,"Kubernetes, Hadoop, TensorFlow, Computer Vision",PhD,2,Real Estate,2024-02-03,2024-02-29,1388,9.1,Advanced Robotics -AI12959,Principal Data Scientist,151418,USD,151418,SE,FL,Israel,L,Israel,100,"Computer Vision, SQL, Scala, GCP, Spark",Master,8,Telecommunications,2024-06-07,2024-08-17,2032,10,Quantum Computing Inc -AI12960,Data Engineer,198647,CHF,178782,EX,FT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, Hadoop, SQL, AWS",PhD,10,Telecommunications,2025-02-12,2025-03-07,909,8.2,Autonomous Tech -AI12961,Deep Learning Engineer,156122,CAD,195153,SE,FT,Canada,L,Canada,100,"Spark, Tableau, Java, Data Visualization",Bachelor,5,Automotive,2025-01-16,2025-02-09,585,9.2,Predictive Systems -AI12962,ML Ops Engineer,164345,USD,164345,EX,PT,Israel,S,Israel,100,"Git, Kubernetes, Statistics",Associate,14,Education,2025-01-23,2025-02-09,2343,6.5,DataVision Ltd -AI12963,Computer Vision Engineer,156737,USD,156737,MI,CT,Denmark,L,Denmark,50,"Spark, R, SQL, Java, Mathematics",Master,2,Gaming,2024-10-24,2024-11-12,860,9.5,Quantum Computing Inc -AI12964,Research Scientist,134102,EUR,113987,SE,PT,Netherlands,M,Netherlands,50,"Data Visualization, Computer Vision, AWS, GCP, Statistics",Bachelor,9,Government,2024-10-06,2024-12-18,847,8.9,Future Systems -AI12965,Head of AI,112325,USD,112325,SE,FL,Israel,M,Israel,50,"Tableau, Azure, Python, Hadoop, Docker",PhD,9,Automotive,2025-02-07,2025-04-12,1786,5.7,Predictive Systems -AI12966,ML Ops Engineer,92446,USD,92446,EX,FT,China,S,New Zealand,50,"Spark, Python, Tableau, TensorFlow, GCP",Master,12,Technology,2025-03-05,2025-03-27,996,5.8,Cloud AI Solutions -AI12967,AI Research Scientist,262159,USD,262159,EX,FT,Ireland,L,Ireland,0,"Python, Spark, TensorFlow",Bachelor,18,Media,2025-04-27,2025-05-12,639,8.4,Predictive Systems -AI12968,Data Engineer,44890,USD,44890,MI,FL,China,M,China,0,"Hadoop, Data Visualization, MLOps, Deep Learning",PhD,4,Finance,2024-09-04,2024-11-04,1790,8.9,DeepTech Ventures -AI12969,AI Product Manager,217707,USD,217707,EX,PT,Ireland,S,Belgium,100,"Docker, Python, AWS, TensorFlow",Master,12,Telecommunications,2024-03-22,2024-04-05,1857,8.4,Autonomous Tech -AI12970,AI Product Manager,154903,USD,154903,EX,FT,Sweden,M,Brazil,50,"Scala, PyTorch, Spark, MLOps, Git",Bachelor,17,Energy,2025-02-03,2025-04-11,1604,7.5,Digital Transformation LLC -AI12971,Computer Vision Engineer,224171,USD,224171,EX,FL,United States,L,United States,50,"Deep Learning, Linux, Java, Python, SQL",Master,16,Education,2024-02-11,2024-04-24,1888,7.7,Autonomous Tech -AI12972,Principal Data Scientist,193696,USD,193696,EX,FL,Norway,M,Norway,100,"Mathematics, Deep Learning, Git, Spark",Associate,10,Manufacturing,2024-09-22,2024-11-11,1564,8.1,Cognitive Computing -AI12973,Robotics Engineer,75949,EUR,64557,EN,PT,Netherlands,S,Netherlands,100,"TensorFlow, Python, Docker",Master,0,Education,2024-07-07,2024-08-17,743,9.4,Cloud AI Solutions -AI12974,Data Scientist,54686,USD,54686,EN,FL,Ireland,S,Netherlands,50,"Scala, AWS, Python",Bachelor,1,Healthcare,2024-08-16,2024-10-05,1467,6.8,Machine Intelligence Group -AI12975,Principal Data Scientist,103836,EUR,88261,MI,CT,France,M,Argentina,0,"Azure, Python, Deep Learning",Bachelor,3,Manufacturing,2025-03-15,2025-04-14,2314,9.8,Machine Intelligence Group -AI12976,Machine Learning Researcher,80675,USD,80675,MI,FT,Ireland,S,Ireland,50,"Scala, Java, Kubernetes, Spark, Statistics",Bachelor,4,Retail,2024-05-18,2024-06-01,1182,6.5,DeepTech Ventures -AI12977,Computer Vision Engineer,96576,USD,96576,MI,FT,United States,S,Argentina,50,"GCP, Hadoop, SQL",PhD,4,Government,2024-09-16,2024-10-05,1345,7,Machine Intelligence Group -AI12978,AI Architect,186491,CAD,233114,EX,CT,Canada,L,Canada,0,"NLP, Docker, Tableau, Computer Vision",Associate,19,Consulting,2024-08-15,2024-10-07,912,9.7,DataVision Ltd -AI12979,ML Ops Engineer,112803,CHF,101523,EN,FL,Switzerland,M,Switzerland,0,"R, Tableau, Scala",Associate,1,Transportation,2025-04-13,2025-05-17,1292,5.9,Smart Analytics -AI12980,Data Scientist,66258,CAD,82823,EN,FL,Canada,S,Canada,50,"Scala, Python, Statistics",PhD,1,Manufacturing,2025-04-02,2025-06-01,1933,7.8,Smart Analytics -AI12981,AI Architect,122843,GBP,92132,MI,FL,United Kingdom,L,Ukraine,0,"SQL, Java, Python",PhD,4,Media,2024-01-28,2024-02-12,786,5.7,Autonomous Tech -AI12982,AI Research Scientist,70436,USD,70436,EX,PT,India,M,India,100,"NLP, PyTorch, Statistics, Linux",PhD,12,Finance,2024-10-06,2024-11-30,1345,6.4,Digital Transformation LLC -AI12983,Head of AI,111112,USD,111112,MI,FL,Sweden,L,United States,100,"Python, Tableau, SQL",Bachelor,2,Education,2024-08-27,2024-10-01,1822,8.5,Digital Transformation LLC -AI12984,NLP Engineer,62688,USD,62688,EN,FT,Ireland,S,Mexico,100,"Java, Docker, Statistics, Linux",Bachelor,0,Technology,2025-03-11,2025-03-31,1549,7.4,TechCorp Inc -AI12985,Principal Data Scientist,109993,AUD,148491,MI,FT,Australia,M,Australia,50,"MLOps, Git, NLP, Computer Vision",PhD,3,Energy,2024-01-04,2024-02-26,891,9,Quantum Computing Inc -AI12986,Robotics Engineer,90739,AUD,122498,MI,PT,Australia,M,Malaysia,100,"Computer Vision, NLP, MLOps, PyTorch, Docker",PhD,2,Retail,2024-09-13,2024-10-23,1603,8,TechCorp Inc -AI12987,NLP Engineer,116788,EUR,99270,SE,FL,France,M,France,50,"R, Kubernetes, Computer Vision, Hadoop, Docker",Associate,5,Education,2025-02-14,2025-03-14,2471,9.7,Quantum Computing Inc -AI12988,Data Scientist,89119,EUR,75751,MI,FL,Germany,M,Germany,100,"Hadoop, Linux, Tableau, Docker, Kubernetes",Bachelor,4,Telecommunications,2024-09-23,2024-11-23,2175,6.7,TechCorp Inc -AI12989,Machine Learning Engineer,80678,SGD,104881,MI,FT,Singapore,S,Singapore,100,"Git, SQL, Azure",Master,3,Real Estate,2025-04-23,2025-05-12,1070,9.1,Future Systems -AI12990,Head of AI,146187,EUR,124259,SE,PT,Austria,L,Austria,100,"SQL, MLOps, R",Associate,5,Education,2025-02-17,2025-04-21,1463,8.1,DataVision Ltd -AI12991,Machine Learning Engineer,77845,USD,77845,EX,CT,India,S,India,0,"GCP, Java, Data Visualization",PhD,12,Transportation,2024-02-29,2024-04-30,720,8.2,AI Innovations -AI12992,Autonomous Systems Engineer,73922,USD,73922,EN,FT,United States,M,United Kingdom,50,"TensorFlow, Python, Computer Vision, R, Hadoop",Bachelor,0,Healthcare,2024-01-13,2024-02-19,1487,5.1,Cloud AI Solutions -AI12993,Data Scientist,103867,EUR,88287,MI,PT,Netherlands,S,Netherlands,100,"Linux, Java, R",Master,2,Gaming,2024-06-24,2024-08-24,1252,5.4,DeepTech Ventures -AI12994,AI Research Scientist,125902,EUR,107017,EX,PT,France,S,France,50,"SQL, MLOps, Kubernetes, Mathematics, Computer Vision",PhD,13,Transportation,2025-02-07,2025-04-18,593,9.1,TechCorp Inc -AI12995,AI Architect,29129,USD,29129,MI,FT,India,M,India,0,"Spark, R, Hadoop",Associate,4,Automotive,2025-03-13,2025-04-11,1097,9.8,Digital Transformation LLC -AI12996,AI Software Engineer,43029,USD,43029,EN,PT,South Korea,S,South Korea,100,"Docker, Tableau, SQL",Bachelor,0,Healthcare,2024-02-03,2024-03-06,610,7.4,DeepTech Ventures -AI12997,Machine Learning Engineer,79088,USD,79088,EN,FT,Sweden,L,Sweden,0,"Data Visualization, Tableau, SQL, Mathematics",Bachelor,0,Media,2024-02-17,2024-04-13,1246,8.9,Advanced Robotics -AI12998,AI Specialist,49171,USD,49171,EN,FT,Sweden,S,Turkey,50,"Computer Vision, Python, MLOps",Bachelor,0,Automotive,2024-08-19,2024-09-27,1611,5.5,Digital Transformation LLC -AI12999,Data Analyst,62847,SGD,81701,EN,CT,Singapore,L,Singapore,100,"Git, TensorFlow, Tableau, Scala",PhD,1,Transportation,2024-01-01,2024-02-24,1985,7,Cognitive Computing -AI13000,AI Specialist,80522,USD,80522,SE,CT,South Korea,S,Ghana,100,"PyTorch, Docker, Azure, TensorFlow",Associate,6,Gaming,2025-03-11,2025-03-28,978,8.9,Quantum Computing Inc -AI13001,AI Consultant,64623,EUR,54930,EN,PT,Netherlands,S,Netherlands,50,"Mathematics, AWS, Docker, Statistics",PhD,0,Telecommunications,2024-04-15,2024-06-18,764,9.8,Quantum Computing Inc -AI13002,Machine Learning Engineer,138114,USD,138114,SE,CT,United States,S,United States,0,"MLOps, Linux, Kubernetes",PhD,8,Telecommunications,2024-07-17,2024-09-09,1795,5.7,Digital Transformation LLC -AI13003,AI Consultant,175938,AUD,237516,EX,FL,Australia,L,Australia,100,"Linux, Tableau, Git",Bachelor,12,Gaming,2024-05-23,2024-06-12,1700,9.3,Algorithmic Solutions -AI13004,Data Engineer,58622,USD,58622,EX,PT,China,S,Indonesia,0,"Hadoop, SQL, Computer Vision",Bachelor,17,Automotive,2025-04-30,2025-06-14,807,7.7,Future Systems -AI13005,Data Engineer,79766,GBP,59825,MI,FT,United Kingdom,M,United Kingdom,50,"Statistics, Java, TensorFlow, PyTorch, Computer Vision",PhD,4,Manufacturing,2024-05-13,2024-06-04,905,5.8,AI Innovations -AI13006,Machine Learning Researcher,89995,USD,89995,MI,CT,Norway,S,Norway,0,"TensorFlow, Statistics, R, Docker, Java",Bachelor,2,Government,2024-04-21,2024-06-17,641,5.6,Neural Networks Co -AI13007,NLP Engineer,160586,USD,160586,SE,FL,Ireland,L,Portugal,0,"Git, AWS, Mathematics",Master,7,Transportation,2024-06-17,2024-08-09,2063,6.9,Smart Analytics -AI13008,AI Specialist,109290,USD,109290,EX,FL,China,M,Switzerland,0,"Java, Python, Statistics, GCP, NLP",Master,11,Energy,2025-04-23,2025-05-13,2189,9.8,Cognitive Computing -AI13009,Robotics Engineer,222632,EUR,189237,EX,FL,Netherlands,M,Netherlands,0,"Azure, Kubernetes, GCP, SQL, Hadoop",Master,19,Finance,2024-11-13,2024-12-28,881,5.7,AI Innovations -AI13010,Research Scientist,154841,CHF,139357,MI,CT,Switzerland,L,Australia,0,"Hadoop, MLOps, Kubernetes, Java",Bachelor,4,Automotive,2024-06-24,2024-07-10,1923,6.5,Predictive Systems -AI13011,Machine Learning Engineer,350148,CHF,315133,EX,CT,Switzerland,M,Switzerland,0,"Java, Git, Azure",Associate,15,Finance,2024-08-24,2024-10-06,691,7.7,Smart Analytics -AI13012,AI Research Scientist,85240,USD,85240,MI,CT,South Korea,L,South Korea,100,"TensorFlow, Hadoop, Mathematics",Bachelor,2,Finance,2025-01-09,2025-02-16,731,9.7,Future Systems -AI13013,Robotics Engineer,129453,GBP,97090,SE,FT,United Kingdom,M,United Kingdom,0,"MLOps, Git, Mathematics, Spark",Bachelor,7,Retail,2024-01-19,2024-03-26,2363,6.9,Predictive Systems -AI13014,Data Engineer,269378,SGD,350191,EX,FT,Singapore,M,Singapore,0,"NLP, Python, SQL, Data Visualization",Master,15,Energy,2024-07-27,2024-08-19,2033,8.8,AI Innovations -AI13015,Deep Learning Engineer,280599,USD,280599,EX,PT,Ireland,L,Ireland,0,"Linux, SQL, NLP, GCP",Master,16,Retail,2024-04-22,2024-07-02,893,7.5,DataVision Ltd -AI13016,Machine Learning Engineer,71137,EUR,60466,MI,FL,Netherlands,S,Netherlands,50,"Kubernetes, Computer Vision, SQL, Deep Learning, PyTorch",PhD,3,Education,2024-02-20,2024-03-14,676,9.4,Advanced Robotics -AI13017,Data Scientist,174913,EUR,148676,EX,CT,Netherlands,M,France,0,"NLP, Statistics, Hadoop",Bachelor,19,Manufacturing,2024-08-10,2024-09-04,840,5.5,Digital Transformation LLC -AI13018,Deep Learning Engineer,115630,USD,115630,SE,PT,Israel,S,Estonia,50,"Java, Data Visualization, Scala, Azure, GCP",Master,9,Gaming,2024-09-15,2024-10-26,2138,9.3,DataVision Ltd -AI13019,Robotics Engineer,70395,SGD,91514,EN,PT,Singapore,M,Singapore,100,"SQL, TensorFlow, Java, MLOps",Bachelor,0,Real Estate,2024-12-30,2025-01-20,1089,5.6,DeepTech Ventures -AI13020,Deep Learning Engineer,53458,EUR,45439,EN,FT,Austria,S,Austria,50,"TensorFlow, Python, MLOps, Statistics",Associate,0,Retail,2024-06-19,2024-07-15,1120,8.6,Smart Analytics -AI13021,AI Architect,28054,USD,28054,MI,FT,India,S,Nigeria,0,"Python, Java, TensorFlow",PhD,2,Technology,2024-04-12,2024-05-27,530,6.3,Machine Intelligence Group -AI13022,Head of AI,162934,EUR,138494,SE,CT,Germany,L,Philippines,0,"SQL, Data Visualization, Python, Azure",Master,7,Transportation,2024-09-18,2024-10-30,2064,7.5,Neural Networks Co -AI13023,NLP Engineer,111667,USD,111667,MI,FL,Norway,L,Norway,0,"NLP, Tableau, Azure, Git, Linux",Associate,3,Transportation,2025-01-06,2025-02-25,1817,9.1,Smart Analytics -AI13024,ML Ops Engineer,219405,EUR,186494,EX,FL,Netherlands,L,Netherlands,0,"Java, MLOps, TensorFlow, NLP, SQL",Master,14,Automotive,2024-03-05,2024-04-28,1117,6.1,Future Systems -AI13025,ML Ops Engineer,111552,USD,111552,MI,FL,Sweden,L,Sweden,50,"Scala, Python, GCP",Bachelor,2,Automotive,2024-05-15,2024-06-11,841,6.9,Advanced Robotics -AI13026,AI Consultant,123560,USD,123560,MI,PT,Norway,L,Norway,100,"Spark, Data Visualization, Azure, Java, Docker",Associate,2,Media,2024-04-24,2024-05-09,2045,7.7,Algorithmic Solutions -AI13027,AI Specialist,304170,USD,304170,EX,CT,Norway,M,Spain,50,"Python, Data Visualization, AWS, Docker, TensorFlow",Associate,17,Manufacturing,2024-04-28,2024-06-17,1464,8.9,Digital Transformation LLC -AI13028,AI Software Engineer,151323,USD,151323,EX,FL,South Korea,L,South Korea,0,"Python, TensorFlow, Data Visualization, Scala, AWS",PhD,10,Media,2024-11-14,2025-01-13,1035,5.6,Algorithmic Solutions -AI13029,Head of AI,57091,USD,57091,EN,FT,United States,S,United States,50,"R, Linux, Tableau, Git",PhD,1,Gaming,2024-03-13,2024-05-21,2015,7.2,Algorithmic Solutions -AI13030,Research Scientist,160113,USD,160113,SE,FL,Finland,L,Finland,0,"Kubernetes, Tableau, Computer Vision",Associate,6,Education,2024-09-02,2024-09-25,1518,5.5,Predictive Systems -AI13031,AI Consultant,69137,JPY,7605070,EN,PT,Japan,L,Japan,50,"Git, MLOps, Data Visualization, PyTorch, Azure",PhD,0,Consulting,2024-03-07,2024-05-15,1334,5.5,Future Systems -AI13032,Computer Vision Engineer,52465,AUD,70828,EN,FL,Australia,S,Canada,100,"Scala, Linux, AWS",PhD,0,Transportation,2025-02-12,2025-03-07,1863,7.9,TechCorp Inc -AI13033,Machine Learning Researcher,74221,JPY,8164310,MI,FT,Japan,S,Japan,100,"SQL, PyTorch, Data Visualization, Computer Vision",Associate,4,Retail,2025-02-17,2025-04-02,1139,5.2,AI Innovations -AI13034,Robotics Engineer,73237,USD,73237,MI,FT,Ireland,S,Ireland,50,"Kubernetes, Python, TensorFlow",PhD,4,Media,2024-02-22,2024-04-08,644,5.8,Quantum Computing Inc -AI13035,Data Scientist,116610,USD,116610,MI,FT,Finland,L,Finland,50,"Hadoop, SQL, Mathematics",PhD,2,Consulting,2024-06-17,2024-08-10,2042,5.3,Autonomous Tech -AI13036,AI Product Manager,155471,CAD,194339,SE,PT,Canada,L,Canada,50,"GCP, PyTorch, Java",Bachelor,8,Energy,2024-12-25,2025-01-17,1576,5.5,AI Innovations -AI13037,Robotics Engineer,53502,USD,53502,SE,CT,India,M,Finland,0,"PyTorch, TensorFlow, Tableau, AWS, Linux",Master,6,Government,2025-02-14,2025-04-24,2130,9.6,Machine Intelligence Group -AI13038,Autonomous Systems Engineer,174189,USD,174189,EX,PT,Ireland,L,United States,50,"R, Mathematics, Hadoop",PhD,16,Consulting,2024-10-05,2024-11-02,1656,8.7,Advanced Robotics -AI13039,Machine Learning Engineer,140960,SGD,183248,SE,CT,Singapore,L,Singapore,0,"PyTorch, TensorFlow, Deep Learning, Java, R",PhD,9,Finance,2025-01-28,2025-03-07,2233,7.5,Smart Analytics -AI13040,Deep Learning Engineer,65603,SGD,85284,EN,PT,Singapore,S,Singapore,50,"Linux, AWS, Python",Associate,0,Finance,2024-08-01,2024-08-21,1584,5.1,Smart Analytics -AI13041,AI Specialist,280472,EUR,238401,EX,CT,Netherlands,L,Thailand,50,"R, NLP, Java, Data Visualization, Scala",PhD,17,Consulting,2024-07-30,2024-09-25,1827,6.7,Autonomous Tech -AI13042,Research Scientist,194338,EUR,165187,EX,CT,Germany,L,Philippines,100,"SQL, Hadoop, Kubernetes, Java, NLP",Master,17,Manufacturing,2025-01-31,2025-03-20,2167,5.9,Future Systems -AI13043,Autonomous Systems Engineer,162690,USD,162690,MI,FL,Norway,L,Norway,50,"Git, Linux, Docker",Associate,3,Real Estate,2025-04-08,2025-06-18,2084,6.3,TechCorp Inc -AI13044,Machine Learning Researcher,178197,USD,178197,SE,PT,Denmark,M,Colombia,0,"MLOps, Python, TensorFlow",Master,7,Media,2024-05-29,2024-07-07,2093,8.1,Cognitive Computing -AI13045,Machine Learning Researcher,75976,USD,75976,EX,FL,China,S,China,100,"Python, Linux, TensorFlow, Mathematics",Bachelor,15,Transportation,2024-05-16,2024-07-28,1108,6,DeepTech Ventures -AI13046,Machine Learning Engineer,129457,JPY,14240270,SE,CT,Japan,S,Luxembourg,0,"Linux, Python, Git",Associate,8,Education,2024-01-04,2024-01-26,1084,9.9,Advanced Robotics -AI13047,Data Analyst,116495,CAD,145619,EX,FL,Canada,S,Canada,50,"Git, Python, SQL, Data Visualization, Spark",Bachelor,16,Consulting,2025-02-08,2025-03-31,1552,9.2,Neural Networks Co -AI13048,Head of AI,148839,USD,148839,EX,PT,Sweden,S,Sweden,0,"Hadoop, Spark, Deep Learning",Bachelor,17,Media,2024-03-17,2024-04-03,1358,5.5,DataVision Ltd -AI13049,AI Architect,123589,CHF,111230,MI,CT,Switzerland,M,Ireland,50,"Linux, Mathematics, Data Visualization, Docker, PyTorch",PhD,3,Government,2024-06-25,2024-08-22,1871,9.7,Advanced Robotics -AI13050,Deep Learning Engineer,83978,EUR,71381,EN,FT,France,L,France,50,"Python, Mathematics, Scala, Java, TensorFlow",PhD,1,Real Estate,2024-11-18,2024-12-21,1434,9.3,Algorithmic Solutions -AI13051,Principal Data Scientist,66441,EUR,56475,EN,PT,Germany,L,Germany,50,"Spark, Java, Statistics, R",PhD,0,Gaming,2024-08-28,2024-10-13,1565,6.3,TechCorp Inc -AI13052,Machine Learning Researcher,282786,EUR,240368,EX,PT,Netherlands,L,Netherlands,50,"Git, Python, TensorFlow",Master,14,Retail,2024-01-24,2024-03-14,1684,9.8,Predictive Systems -AI13053,Robotics Engineer,102501,CHF,92251,EN,FL,Switzerland,M,Switzerland,0,"SQL, GCP, Data Visualization, PyTorch, R",Master,1,Gaming,2024-09-07,2024-10-01,975,7.9,Cognitive Computing -AI13054,AI Software Engineer,71975,USD,71975,EN,FT,United States,M,Turkey,50,"AWS, Mathematics, Scala, Hadoop",Bachelor,1,Real Estate,2025-03-11,2025-04-05,2168,9.1,Smart Analytics -AI13055,Robotics Engineer,66498,USD,66498,MI,CT,South Korea,M,South Korea,0,"MLOps, PyTorch, Spark, NLP",PhD,3,Manufacturing,2024-07-07,2024-07-22,1418,7.1,Predictive Systems -AI13056,Research Scientist,88009,EUR,74808,EN,FT,Germany,L,Germany,0,"R, SQL, Azure",PhD,1,Technology,2025-03-09,2025-04-20,2288,5.1,DeepTech Ventures -AI13057,AI Consultant,163347,USD,163347,MI,CT,Norway,L,Ireland,100,"GCP, Python, Java, Docker",Master,4,Energy,2024-11-02,2024-11-25,984,8.5,Advanced Robotics -AI13058,Principal Data Scientist,80967,GBP,60725,EN,CT,United Kingdom,L,Luxembourg,100,"Deep Learning, Linux, Python, Hadoop",Associate,1,Technology,2024-11-01,2024-12-16,2453,5,Advanced Robotics -AI13059,AI Architect,108015,EUR,91813,MI,FL,Germany,M,Hungary,0,"Kubernetes, SQL, MLOps, Docker",Associate,4,Telecommunications,2024-08-15,2024-10-11,549,10,Future Systems -AI13060,AI Research Scientist,237965,USD,237965,EX,FT,Norway,L,Norway,100,"Tableau, MLOps, SQL, Linux, Java",Associate,12,Automotive,2024-09-18,2024-10-30,760,9.4,DeepTech Ventures -AI13061,Computer Vision Engineer,48996,USD,48996,MI,FL,China,L,China,100,"Java, Linux, Python",Associate,3,Manufacturing,2024-12-13,2025-01-22,2075,6.9,DeepTech Ventures -AI13062,Machine Learning Engineer,293914,CHF,264523,EX,CT,Switzerland,L,Estonia,50,"Statistics, Python, Linux",Bachelor,16,Manufacturing,2025-03-04,2025-04-15,1936,8.8,Algorithmic Solutions -AI13063,Research Scientist,68050,USD,68050,EN,FT,Ireland,M,Ireland,0,"Statistics, GCP, Deep Learning, Java, Python",Master,1,Healthcare,2024-12-29,2025-01-13,620,7,Digital Transformation LLC -AI13064,Machine Learning Researcher,66356,USD,66356,EN,PT,Ireland,M,Ireland,100,"Data Visualization, Docker, Python",Associate,0,Real Estate,2024-03-31,2024-05-26,1050,6.3,Cognitive Computing -AI13065,Data Analyst,68146,USD,68146,EN,FL,Finland,L,Thailand,0,"Python, Scala, Tableau",Associate,1,Real Estate,2024-09-20,2024-11-21,733,5.9,TechCorp Inc -AI13066,Data Scientist,133642,CAD,167053,SE,PT,Canada,L,Canada,50,"PyTorch, Statistics, Azure, Python",Bachelor,8,Technology,2025-04-27,2025-05-15,1623,5.8,Machine Intelligence Group -AI13067,AI Software Engineer,53834,USD,53834,SE,FT,China,M,China,0,"Git, GCP, Docker",Master,9,Government,2025-04-01,2025-06-03,2469,7.3,Cloud AI Solutions -AI13068,Head of AI,38246,USD,38246,EN,CT,South Korea,S,Turkey,100,"Git, Docker, SQL, Deep Learning, GCP",Master,1,Automotive,2024-06-15,2024-07-29,2133,7.9,Future Systems -AI13069,NLP Engineer,87601,JPY,9636110,EN,FL,Japan,L,Malaysia,0,"Spark, Git, Kubernetes",Master,1,Retail,2024-02-26,2024-04-05,521,6.7,AI Innovations -AI13070,AI Research Scientist,83658,AUD,112938,MI,FT,Australia,L,Australia,0,"Linux, TensorFlow, Hadoop, PyTorch",Associate,3,Healthcare,2024-06-30,2024-08-28,2162,5.8,Predictive Systems -AI13071,Robotics Engineer,109147,AUD,147348,SE,CT,Australia,S,Australia,0,"Mathematics, Git, Deep Learning, Spark, Linux",Associate,9,Transportation,2024-09-15,2024-10-26,1351,5.6,AI Innovations -AI13072,AI Specialist,61946,USD,61946,EN,PT,Israel,L,Vietnam,100,"Linux, Kubernetes, PyTorch",Associate,1,Technology,2025-04-19,2025-05-16,1210,6.7,AI Innovations -AI13073,Data Scientist,343823,CHF,309441,EX,CT,Switzerland,L,United Kingdom,0,"SQL, Docker, TensorFlow",PhD,16,Manufacturing,2024-07-14,2024-09-24,1773,6.3,Future Systems -AI13074,Data Analyst,109859,USD,109859,MI,PT,Norway,L,Denmark,50,"GCP, Docker, Computer Vision, Kubernetes, Linux",Master,4,Automotive,2024-05-04,2024-06-20,1533,7.7,Machine Intelligence Group -AI13075,Machine Learning Researcher,186936,EUR,158896,EX,CT,Germany,S,Germany,100,"GCP, AWS, MLOps, TensorFlow, Deep Learning",Bachelor,14,Automotive,2024-06-01,2024-06-16,1693,6,Quantum Computing Inc -AI13076,AI Specialist,56525,EUR,48046,EN,PT,France,M,France,50,"GCP, SQL, Data Visualization, Hadoop",Associate,1,Real Estate,2024-09-21,2024-10-26,715,5.9,Neural Networks Co -AI13077,Data Scientist,65610,CAD,82013,EN,FT,Canada,S,Canada,100,"Azure, Kubernetes, SQL, Docker",PhD,1,Education,2025-01-22,2025-02-18,642,6.6,Advanced Robotics -AI13078,Research Scientist,66543,USD,66543,EN,CT,Sweden,L,Sweden,50,"Data Visualization, Spark, TensorFlow, Java",Master,1,Education,2025-02-12,2025-03-17,1971,5.9,Cloud AI Solutions -AI13079,Head of AI,95195,GBP,71396,EN,CT,United Kingdom,L,Switzerland,50,"Statistics, PyTorch, SQL, GCP, Docker",Master,1,Education,2024-07-27,2024-08-27,1362,8.4,Predictive Systems -AI13080,Data Engineer,88191,USD,88191,MI,CT,Norway,S,Norway,0,"Java, Deep Learning, Python",PhD,2,Telecommunications,2024-09-30,2024-12-08,788,7.8,Machine Intelligence Group -AI13081,AI Software Engineer,85673,USD,85673,MI,FL,Finland,S,Finland,0,"Python, Hadoop, TensorFlow, Linux",PhD,4,Healthcare,2024-10-02,2024-10-17,917,5.6,Advanced Robotics -AI13082,Computer Vision Engineer,250835,USD,250835,EX,FT,Finland,L,Finland,0,"Hadoop, MLOps, R, Python",Master,14,Retail,2025-04-22,2025-07-03,918,9.8,Machine Intelligence Group -AI13083,Machine Learning Engineer,65750,EUR,55888,MI,FT,Austria,S,Austria,50,"Tableau, TensorFlow, Python, NLP, R",PhD,3,Automotive,2025-04-03,2025-05-27,2456,8.9,Future Systems -AI13084,Principal Data Scientist,96483,USD,96483,MI,PT,Norway,M,Norway,0,"Python, Kubernetes, Azure, Statistics, Linux",PhD,2,Media,2024-02-05,2024-02-28,605,8.1,TechCorp Inc -AI13085,Principal Data Scientist,111619,EUR,94876,MI,PT,Germany,L,Japan,0,"Computer Vision, PyTorch, NLP, TensorFlow, Kubernetes",Associate,3,Consulting,2025-03-10,2025-04-05,967,5.3,Machine Intelligence Group -AI13086,Data Analyst,68910,USD,68910,MI,FT,Sweden,S,France,100,"SQL, GCP, Tableau, TensorFlow",Associate,2,Technology,2024-04-12,2024-05-02,2143,6.5,Quantum Computing Inc -AI13087,Research Scientist,32232,USD,32232,MI,FL,India,M,Finland,0,"Linux, AWS, Hadoop, SQL",Master,4,Energy,2024-08-15,2024-10-12,1713,8.9,Digital Transformation LLC -AI13088,AI Product Manager,85895,USD,85895,MI,PT,South Korea,L,South Korea,100,"MLOps, Scala, Docker, AWS, Spark",Associate,4,Gaming,2024-07-16,2024-09-18,1126,5,Machine Intelligence Group -AI13089,AI Research Scientist,151896,EUR,129112,EX,PT,Netherlands,S,United Kingdom,100,"Kubernetes, Java, Scala",Associate,18,Media,2024-07-14,2024-09-15,2330,6.7,Advanced Robotics -AI13090,Computer Vision Engineer,282442,USD,282442,EX,CT,United States,M,United States,100,"SQL, Spark, Python, Docker",Master,15,Technology,2024-02-23,2024-03-25,1246,9.6,Autonomous Tech -AI13091,Data Analyst,132020,USD,132020,SE,PT,United States,M,United States,100,"SQL, Java, AWS, Spark",PhD,9,Transportation,2024-10-22,2024-12-30,1902,8.7,TechCorp Inc -AI13092,AI Research Scientist,118211,EUR,100479,SE,PT,Austria,S,Austria,50,"Hadoop, Mathematics, Python, Scala, TensorFlow",Associate,7,Government,2024-11-04,2024-12-26,1773,8.1,Neural Networks Co -AI13093,Machine Learning Engineer,95484,USD,95484,MI,FT,Sweden,L,Sweden,50,"Linux, Azure, Kubernetes, AWS, SQL",PhD,3,Media,2024-12-31,2025-02-19,2495,8,Cloud AI Solutions -AI13094,Deep Learning Engineer,211850,SGD,275405,EX,PT,Singapore,M,Singapore,50,"Tableau, Python, Linux, Computer Vision, TensorFlow",Master,11,Technology,2024-05-22,2024-06-19,1157,5.6,Advanced Robotics -AI13095,Research Scientist,120477,USD,120477,MI,PT,Denmark,S,Canada,0,"GCP, Kubernetes, TensorFlow, Spark, Data Visualization",PhD,4,Telecommunications,2024-11-21,2024-12-15,701,7.1,Predictive Systems -AI13096,NLP Engineer,218123,USD,218123,EX,FT,Ireland,M,Vietnam,0,"GCP, Azure, Python",Bachelor,17,Energy,2025-03-17,2025-04-24,1056,5.3,Advanced Robotics -AI13097,AI Software Engineer,98570,USD,98570,MI,FT,Sweden,M,Russia,100,"Scala, Computer Vision, Azure, Mathematics, Data Visualization",Master,2,Technology,2024-06-21,2024-08-03,672,8.2,Autonomous Tech -AI13098,AI Architect,81790,USD,81790,MI,FL,Israel,L,Thailand,50,"SQL, Kubernetes, Hadoop, PyTorch, GCP",Bachelor,4,Media,2024-06-30,2024-08-17,830,7.7,Digital Transformation LLC -AI13099,NLP Engineer,91536,CAD,114420,MI,FT,Canada,L,Canada,100,"Spark, Linux, TensorFlow, MLOps, Java",PhD,2,Real Estate,2024-04-11,2024-05-08,1728,9.3,Cognitive Computing -AI13100,AI Specialist,116205,EUR,98774,SE,PT,Austria,M,Austria,0,"Java, SQL, Data Visualization",Bachelor,8,Media,2025-01-23,2025-03-26,2388,9.5,Predictive Systems -AI13101,Principal Data Scientist,58576,EUR,49790,EN,CT,France,M,Hungary,100,"Docker, Linux, Data Visualization, GCP",PhD,0,Transportation,2024-09-13,2024-10-14,2244,7.6,Advanced Robotics -AI13102,AI Software Engineer,106840,CHF,96156,MI,PT,Switzerland,S,Switzerland,0,"Spark, Scala, SQL, Statistics, Deep Learning",Bachelor,4,Transportation,2024-10-09,2024-12-14,862,9.3,Future Systems -AI13103,Computer Vision Engineer,123259,CAD,154074,SE,FL,Canada,L,Canada,50,"Data Visualization, NLP, R",Associate,9,Automotive,2024-07-12,2024-08-10,1202,9.9,Predictive Systems -AI13104,Deep Learning Engineer,88273,JPY,9710030,MI,PT,Japan,M,Australia,50,"NLP, Docker, Computer Vision, SQL",Master,2,Real Estate,2024-04-08,2024-05-04,775,8.3,Cloud AI Solutions -AI13105,AI Specialist,133522,USD,133522,SE,PT,Denmark,M,Turkey,100,"Mathematics, R, Linux, Java",Associate,9,Finance,2024-12-28,2025-02-08,1878,6.2,Predictive Systems -AI13106,AI Consultant,159549,USD,159549,EX,FL,Finland,L,Finland,100,"Linux, PyTorch, MLOps, Java, Kubernetes",PhD,13,Media,2024-03-04,2024-04-15,1430,8.6,Machine Intelligence Group -AI13107,ML Ops Engineer,106103,CAD,132629,SE,FT,Canada,M,Canada,50,"Hadoop, PyTorch, MLOps",PhD,5,Automotive,2024-10-23,2024-12-21,1229,7.9,TechCorp Inc -AI13108,AI Consultant,98258,EUR,83519,SE,FL,France,M,France,50,"Docker, AWS, Tableau, Git",Associate,5,Telecommunications,2024-03-24,2024-05-25,2457,5.9,Cognitive Computing -AI13109,Autonomous Systems Engineer,125492,USD,125492,EX,FT,Ireland,S,Ireland,100,"Spark, Scala, MLOps, Linux",PhD,14,Retail,2025-03-27,2025-05-12,1351,8.2,Predictive Systems -AI13110,AI Research Scientist,166393,EUR,141434,EX,PT,Austria,S,Egypt,100,"AWS, Kubernetes, MLOps",Associate,15,Finance,2025-02-09,2025-04-20,1894,5.5,Neural Networks Co -AI13111,ML Ops Engineer,86105,EUR,73189,MI,FT,Austria,M,Austria,0,"Linux, Java, R, GCP",Bachelor,4,Healthcare,2024-08-27,2024-10-28,2399,7.6,Cloud AI Solutions -AI13112,Data Engineer,125111,USD,125111,SE,FT,Finland,S,Finland,0,"Scala, SQL, Mathematics, Statistics, Linux",Associate,5,Manufacturing,2024-01-14,2024-03-27,1070,5,DataVision Ltd -AI13113,ML Ops Engineer,103754,USD,103754,MI,FT,Sweden,M,Egypt,100,"Docker, Deep Learning, Python, Computer Vision, Git",Associate,2,Consulting,2025-04-22,2025-05-20,731,5.5,Machine Intelligence Group -AI13114,Research Scientist,65132,USD,65132,EN,PT,Sweden,M,Mexico,100,"Docker, Statistics, R, PyTorch, TensorFlow",Bachelor,1,Education,2025-04-16,2025-05-22,1489,9.5,DataVision Ltd -AI13115,AI Architect,195654,CHF,176089,EX,FT,Switzerland,S,Switzerland,100,"SQL, MLOps, Scala",Bachelor,11,Consulting,2024-06-08,2024-07-12,658,6.5,Autonomous Tech -AI13116,Data Engineer,65035,EUR,55280,EN,FL,Austria,S,Philippines,0,"TensorFlow, Data Visualization, Tableau, Scala",Associate,0,Energy,2024-11-12,2025-01-23,1952,9.1,Cognitive Computing -AI13117,AI Product Manager,248091,EUR,210877,EX,CT,France,L,France,50,"Statistics, Spark, SQL, Hadoop",PhD,15,Energy,2024-10-10,2024-12-10,860,5.9,Autonomous Tech -AI13118,Robotics Engineer,141327,EUR,120128,SE,FL,Austria,M,Philippines,0,"GCP, PyTorch, TensorFlow",Bachelor,9,Media,2024-07-29,2024-08-29,1588,7.3,Cloud AI Solutions -AI13119,Data Engineer,343050,USD,343050,EX,PT,Denmark,L,Denmark,100,"MLOps, Kubernetes, SQL",Associate,13,Media,2024-10-26,2024-11-26,1308,5.8,Cloud AI Solutions -AI13120,NLP Engineer,169592,USD,169592,SE,FL,Norway,M,Estonia,0,"Spark, SQL, Data Visualization, Deep Learning",Master,6,Education,2024-12-23,2025-01-27,1423,8.5,Quantum Computing Inc -AI13121,Computer Vision Engineer,73049,EUR,62092,EN,PT,Germany,M,Canada,0,"Mathematics, AWS, SQL",Master,0,Transportation,2024-09-25,2024-11-30,1971,5.8,Quantum Computing Inc -AI13122,Data Analyst,107795,USD,107795,MI,FT,United States,L,United States,0,"R, SQL, AWS",PhD,3,Education,2024-11-18,2024-12-29,1861,9.3,DataVision Ltd -AI13123,Principal Data Scientist,103946,AUD,140327,SE,FT,Australia,M,Australia,100,"Tableau, Python, Statistics",Master,6,Education,2024-10-15,2024-11-09,645,6.3,AI Innovations -AI13124,AI Specialist,141419,JPY,15556090,SE,PT,Japan,S,Japan,100,"Python, MLOps, TensorFlow, Kubernetes, Docker",Master,5,Finance,2024-09-20,2024-10-14,1712,5.6,Neural Networks Co -AI13125,Robotics Engineer,56273,USD,56273,SE,FT,China,S,China,0,"Linux, Python, TensorFlow, Computer Vision",Associate,8,Healthcare,2024-03-03,2024-03-21,1241,8.3,Cloud AI Solutions -AI13126,ML Ops Engineer,225699,AUD,304694,EX,FL,Australia,S,Australia,50,"Linux, Spark, Git, Mathematics, Python",Bachelor,18,Transportation,2024-06-09,2024-07-01,834,7.2,Cognitive Computing -AI13127,Autonomous Systems Engineer,191962,USD,191962,EX,FT,Israel,S,Israel,100,"Tableau, AWS, Statistics",Master,12,Technology,2025-03-15,2025-05-19,1939,9.3,DataVision Ltd -AI13128,Robotics Engineer,65172,EUR,55396,EN,PT,Austria,L,Austria,100,"Docker, Kubernetes, Java, R, Hadoop",PhD,0,Consulting,2024-05-13,2024-07-13,2202,6.3,DataVision Ltd -AI13129,Data Engineer,152054,AUD,205273,SE,FL,Australia,L,Australia,50,"Python, Kubernetes, R, Mathematics",Bachelor,8,Finance,2024-06-24,2024-08-02,685,10,Smart Analytics -AI13130,AI Product Manager,27800,USD,27800,EN,FT,India,M,Kenya,100,"AWS, Git, Python, SQL, Statistics",PhD,1,Media,2024-06-19,2024-08-28,2359,5.1,DataVision Ltd -AI13131,ML Ops Engineer,87373,AUD,117954,MI,PT,Australia,S,Australia,0,"Linux, Git, Scala, R",Master,3,Education,2024-03-01,2024-04-23,1287,9.8,DataVision Ltd -AI13132,AI Product Manager,121517,USD,121517,EX,FL,China,L,China,50,"Computer Vision, Git, MLOps, Tableau",Bachelor,17,Retail,2024-01-02,2024-01-26,714,5.2,Neural Networks Co -AI13133,Principal Data Scientist,95651,USD,95651,MI,FL,Sweden,S,Turkey,100,"GCP, Tableau, Spark",Master,4,Retail,2024-05-05,2024-06-09,1097,6.3,Quantum Computing Inc -AI13134,NLP Engineer,135229,EUR,114945,SE,CT,Germany,S,Singapore,0,"GCP, Docker, Tableau, Linux",Associate,5,Finance,2024-03-03,2024-04-19,1628,7.6,Predictive Systems -AI13135,Machine Learning Researcher,59742,USD,59742,EN,CT,South Korea,L,Italy,0,"Docker, Python, NLP, Kubernetes, Data Visualization",Associate,1,Automotive,2025-03-08,2025-05-01,2448,6.7,Predictive Systems -AI13136,Head of AI,285325,AUD,385189,EX,CT,Australia,L,Ireland,100,"Scala, Spark, GCP, Deep Learning, MLOps",Associate,14,Finance,2024-02-01,2024-03-18,1668,5.3,Cognitive Computing -AI13137,Machine Learning Engineer,177700,GBP,133275,EX,PT,United Kingdom,M,United Kingdom,100,"Kubernetes, SQL, Python",PhD,14,Retail,2024-03-13,2024-05-11,504,8.2,Quantum Computing Inc -AI13138,AI Architect,129173,USD,129173,MI,PT,United States,L,United States,50,"Scala, MLOps, Spark, NLP",PhD,2,Technology,2024-08-20,2024-10-29,1608,6,Predictive Systems -AI13139,AI Product Manager,124365,EUR,105710,SE,FL,Germany,L,Germany,100,"Statistics, AWS, Java",Master,5,Real Estate,2025-03-21,2025-05-30,2132,9.4,Digital Transformation LLC -AI13140,Data Scientist,28510,USD,28510,EN,CT,India,L,India,100,"TensorFlow, Scala, Java, Python",Associate,0,Manufacturing,2024-01-19,2024-04-01,514,7.1,Future Systems -AI13141,Autonomous Systems Engineer,147366,AUD,198944,SE,CT,Australia,L,India,50,"PyTorch, AWS, TensorFlow, SQL",Master,8,Government,2024-05-16,2024-06-30,2032,9.6,Smart Analytics -AI13142,Data Engineer,54967,EUR,46722,EN,PT,Netherlands,S,Netherlands,0,"Linux, SQL, TensorFlow, Deep Learning, AWS",Master,1,Education,2024-03-17,2024-04-05,1683,6.5,AI Innovations -AI13143,Machine Learning Researcher,56049,EUR,47642,EN,PT,France,S,France,50,"Kubernetes, Linux, Git, Azure, Mathematics",Bachelor,0,Government,2024-09-14,2024-10-18,1354,8.9,Machine Intelligence Group -AI13144,Data Scientist,50627,USD,50627,EN,CT,Ireland,S,Ireland,100,"AWS, Git, Python",Bachelor,0,Finance,2024-09-29,2024-10-22,767,7,Quantum Computing Inc -AI13145,Principal Data Scientist,129562,JPY,14251820,SE,PT,Japan,L,Japan,100,"Deep Learning, Azure, NLP, Python",PhD,7,Media,2024-12-02,2024-12-22,1863,7.5,Smart Analytics -AI13146,Autonomous Systems Engineer,86193,USD,86193,MI,FL,Finland,M,Finland,50,"Kubernetes, Statistics, Python",Bachelor,2,Automotive,2024-03-16,2024-04-19,855,8.9,Quantum Computing Inc -AI13147,AI Research Scientist,242707,CAD,303384,EX,PT,Canada,L,Canada,50,"Python, Spark, PyTorch, R",Associate,13,Telecommunications,2025-02-19,2025-03-22,1183,5.7,Quantum Computing Inc -AI13148,Data Engineer,22180,USD,22180,EN,FL,China,S,China,100,"Statistics, Data Visualization, Git, Linux",Bachelor,1,Energy,2024-05-22,2024-08-01,2339,8.8,Digital Transformation LLC -AI13149,Computer Vision Engineer,144736,CHF,130262,MI,CT,Switzerland,L,Switzerland,50,"Git, Docker, Azure",Associate,2,Telecommunications,2024-10-23,2024-12-31,2474,8.9,Predictive Systems -AI13150,Data Scientist,89075,EUR,75714,MI,FT,Netherlands,M,Brazil,100,"Mathematics, SQL, NLP, Computer Vision",Associate,4,Telecommunications,2024-02-06,2024-04-17,1369,8.4,Algorithmic Solutions -AI13151,Research Scientist,146125,JPY,16073750,SE,CT,Japan,M,Vietnam,100,"Scala, Statistics, Azure",Bachelor,5,Manufacturing,2024-01-11,2024-02-22,1903,8.1,Quantum Computing Inc -AI13152,Data Analyst,57872,EUR,49191,EN,FT,France,S,Czech Republic,50,"Scala, Docker, Statistics, Spark",Master,1,Healthcare,2024-12-22,2025-01-06,1208,9.7,Cognitive Computing -AI13153,Machine Learning Researcher,49720,USD,49720,EX,PT,India,M,Finland,100,"Deep Learning, Python, Tableau",Master,16,Retail,2024-10-19,2024-11-05,1858,8.1,AI Innovations -AI13154,AI Architect,94893,USD,94893,EX,FL,China,S,Germany,50,"Docker, Python, AWS, TensorFlow",Master,11,Manufacturing,2024-08-29,2024-11-07,1073,6.1,AI Innovations -AI13155,NLP Engineer,124615,EUR,105923,SE,PT,Austria,S,Austria,100,"Git, SQL, Java",Bachelor,6,Retail,2025-01-30,2025-04-03,911,5.3,DeepTech Ventures -AI13156,Data Analyst,136314,CHF,122683,SE,CT,Switzerland,S,Switzerland,50,"Docker, R, AWS",PhD,7,Telecommunications,2024-04-19,2024-06-25,1481,6,Advanced Robotics -AI13157,Deep Learning Engineer,60206,EUR,51175,EN,FL,France,S,Philippines,50,"Data Visualization, Linux, Tableau",Associate,0,Consulting,2024-12-01,2025-01-06,912,8.4,DataVision Ltd -AI13158,AI Product Manager,99753,USD,99753,MI,FT,Ireland,M,Denmark,100,"SQL, Scala, Linux",Associate,2,Consulting,2025-04-13,2025-05-07,1352,9.4,DataVision Ltd -AI13159,Machine Learning Engineer,93871,AUD,126726,SE,FL,Australia,S,Australia,100,"Scala, Java, AWS",Bachelor,5,Finance,2025-04-15,2025-05-10,2344,9.1,Cognitive Computing -AI13160,Data Scientist,116623,EUR,99130,EX,PT,France,S,India,100,"AWS, NLP, MLOps, Linux, GCP",Bachelor,14,Retail,2024-07-12,2024-08-02,825,8.8,Quantum Computing Inc -AI13161,Robotics Engineer,102693,SGD,133501,SE,CT,Singapore,S,Singapore,100,"Tableau, R, Linux, Java, PyTorch",Master,5,Automotive,2024-05-27,2024-06-21,1700,8,Predictive Systems -AI13162,Head of AI,62122,USD,62122,EN,PT,Finland,M,Finland,100,"Spark, Scala, Azure, Statistics, MLOps",Bachelor,1,Gaming,2024-04-08,2024-06-05,854,8.2,Autonomous Tech -AI13163,NLP Engineer,58719,USD,58719,SE,CT,China,L,China,100,"Python, MLOps, Scala, Computer Vision, Statistics",Master,8,Real Estate,2025-03-01,2025-05-03,2172,9.7,Machine Intelligence Group -AI13164,AI Software Engineer,59864,USD,59864,EN,CT,Sweden,M,Mexico,50,"Deep Learning, SQL, Data Visualization, MLOps, PyTorch",PhD,1,Real Estate,2024-09-30,2024-10-16,906,9.1,DataVision Ltd -AI13165,Data Engineer,248769,CHF,223892,EX,CT,Switzerland,L,Switzerland,50,"Python, TensorFlow, SQL, Docker, AWS",Associate,12,Real Estate,2025-04-23,2025-05-09,1869,9.4,Algorithmic Solutions -AI13166,Head of AI,100787,USD,100787,MI,FL,Israel,L,Colombia,0,"Hadoop, Kubernetes, SQL, Computer Vision",Master,2,Media,2024-03-18,2024-04-12,878,9.6,Predictive Systems -AI13167,Deep Learning Engineer,90501,EUR,76926,MI,PT,Germany,L,Germany,50,"GCP, MLOps, Azure",Associate,4,Finance,2025-03-13,2025-04-12,1900,7.7,Advanced Robotics -AI13168,AI Product Manager,98721,USD,98721,MI,FT,Sweden,M,Belgium,50,"Data Visualization, PyTorch, NLP",Associate,3,Automotive,2024-09-17,2024-10-20,1279,6.1,Quantum Computing Inc -AI13169,ML Ops Engineer,216873,USD,216873,EX,FT,Sweden,L,Sweden,0,"TensorFlow, Linux, MLOps, Computer Vision",PhD,11,Automotive,2024-04-17,2024-06-14,500,9.5,Quantum Computing Inc -AI13170,AI Consultant,51793,EUR,44024,EN,PT,Austria,S,South Africa,50,"Statistics, Mathematics, GCP, Spark",Bachelor,1,Healthcare,2024-10-12,2024-11-27,625,9.8,Quantum Computing Inc -AI13171,Machine Learning Engineer,89005,EUR,75654,MI,FL,Netherlands,S,Netherlands,50,"PyTorch, Mathematics, NLP",Master,3,Telecommunications,2025-04-02,2025-04-29,1954,5.2,DeepTech Ventures -AI13172,Data Analyst,112200,USD,112200,SE,FL,Israel,M,Israel,100,"TensorFlow, Scala, Mathematics",Associate,9,Consulting,2025-01-13,2025-03-09,1087,5.2,TechCorp Inc -AI13173,AI Product Manager,93493,USD,93493,MI,FL,Ireland,S,Switzerland,50,"TensorFlow, Python, Tableau, Deep Learning",Bachelor,4,Technology,2024-09-14,2024-09-29,1688,5.5,TechCorp Inc -AI13174,Machine Learning Researcher,150175,AUD,202736,EX,PT,Australia,M,Australia,100,"Java, R, SQL",Master,17,Government,2024-12-20,2025-02-24,2485,8.3,TechCorp Inc -AI13175,AI Research Scientist,66666,CAD,83333,EN,CT,Canada,L,China,100,"Linux, TensorFlow, Deep Learning, Python",Associate,0,Finance,2024-07-05,2024-09-02,1773,6.9,Future Systems -AI13176,Robotics Engineer,101266,USD,101266,MI,FT,Finland,L,Finland,100,"MLOps, Git, Python, Statistics, Linux",PhD,4,Education,2024-09-13,2024-10-30,1769,5.8,Digital Transformation LLC -AI13177,Autonomous Systems Engineer,76613,USD,76613,EN,FT,United States,M,United States,50,"Linux, Java, TensorFlow, MLOps",Master,1,Telecommunications,2024-08-02,2024-09-02,1973,8.5,Digital Transformation LLC -AI13178,Machine Learning Researcher,49536,USD,49536,EX,PT,India,S,Austria,50,"Spark, Docker, R, Deep Learning",PhD,18,Real Estate,2024-11-24,2024-12-24,2071,8.5,Digital Transformation LLC -AI13179,Deep Learning Engineer,61260,USD,61260,SE,CT,China,L,China,0,"Scala, R, Python",Master,9,Automotive,2025-01-07,2025-03-04,859,6.5,Cognitive Computing -AI13180,AI Specialist,149430,USD,149430,EX,PT,Finland,L,Argentina,100,"R, Python, Java, PyTorch, Tableau",Associate,14,Media,2024-12-09,2024-12-29,1331,7.2,Neural Networks Co -AI13181,Data Scientist,123078,EUR,104616,SE,FT,Austria,L,Austria,0,"Docker, Git, Deep Learning, Statistics, Hadoop",Bachelor,6,Education,2024-08-21,2024-10-24,1714,9.4,Advanced Robotics -AI13182,Machine Learning Engineer,70132,EUR,59612,MI,FL,Austria,S,Thailand,0,"Computer Vision, NLP, Python",Bachelor,2,Automotive,2025-04-22,2025-05-12,1803,9.6,Future Systems -AI13183,Data Analyst,141806,USD,141806,MI,PT,United States,L,United States,100,"MLOps, Kubernetes, GCP, R",Associate,2,Energy,2025-01-03,2025-03-08,818,5.4,Smart Analytics -AI13184,AI Specialist,111124,USD,111124,EX,PT,China,M,Germany,50,"Python, Data Visualization, TensorFlow, Java",Associate,10,Consulting,2024-04-15,2024-05-07,1584,5.1,Predictive Systems -AI13185,Deep Learning Engineer,152448,EUR,129581,EX,FL,Germany,S,Germany,100,"GCP, Hadoop, NLP, Tableau, Computer Vision",PhD,10,Gaming,2024-06-20,2024-08-06,1048,6.7,Cloud AI Solutions -AI13186,ML Ops Engineer,147859,EUR,125680,EX,FL,Germany,S,Germany,0,"Kubernetes, Tableau, AWS, Computer Vision",PhD,13,Energy,2024-03-20,2024-04-04,1994,5.9,AI Innovations -AI13187,AI Architect,71833,CAD,89791,MI,FT,Canada,M,Belgium,100,"Java, SQL, Spark",Master,4,Telecommunications,2024-09-15,2024-11-25,2415,8.3,Predictive Systems -AI13188,Autonomous Systems Engineer,265945,USD,265945,EX,CT,Denmark,L,Denmark,0,"Data Visualization, AWS, Tableau",PhD,13,Real Estate,2024-02-05,2024-04-10,1051,8.5,Smart Analytics -AI13189,Deep Learning Engineer,182312,EUR,154965,EX,PT,Austria,L,Austria,100,"Python, Data Visualization, Statistics, MLOps",PhD,18,Telecommunications,2024-11-19,2024-12-11,1525,7.7,Smart Analytics -AI13190,Robotics Engineer,81783,USD,81783,MI,FL,Ireland,M,Israel,0,"Hadoop, Mathematics, MLOps",Master,2,Energy,2024-11-18,2025-01-03,1787,5.5,Cognitive Computing -AI13191,Computer Vision Engineer,283095,JPY,31140450,EX,PT,Japan,L,Japan,50,"Computer Vision, Python, MLOps, PyTorch",Bachelor,12,Manufacturing,2024-08-02,2024-08-28,2074,5.4,Future Systems -AI13192,AI Research Scientist,140169,EUR,119144,SE,CT,Austria,M,Austria,100,"PyTorch, Data Visualization, SQL",PhD,5,Retail,2025-01-20,2025-02-22,1103,7.7,Cognitive Computing -AI13193,Deep Learning Engineer,55566,EUR,47231,EN,CT,France,S,France,50,"Hadoop, Scala, Java",PhD,0,Energy,2024-06-03,2024-07-12,2240,7.9,Advanced Robotics -AI13194,ML Ops Engineer,312518,CHF,281266,EX,PT,Switzerland,L,New Zealand,50,"Python, GCP, NLP, SQL",Master,17,Finance,2024-09-23,2024-12-01,2430,5.9,Cloud AI Solutions -AI13195,Data Analyst,42317,USD,42317,EN,PT,South Korea,S,Russia,0,"GCP, Python, Git",Associate,0,Education,2025-02-05,2025-03-17,1394,10,Smart Analytics -AI13196,Autonomous Systems Engineer,115876,USD,115876,SE,CT,Finland,S,United States,0,"Git, Data Visualization, Deep Learning, MLOps",Bachelor,9,Energy,2025-03-20,2025-05-19,925,6,Cloud AI Solutions -AI13197,AI Software Engineer,59246,AUD,79982,EN,FT,Australia,L,Australia,0,"Docker, Spark, Data Visualization",PhD,0,Healthcare,2024-07-11,2024-08-30,830,9,Machine Intelligence Group -AI13198,Data Scientist,138647,GBP,103985,SE,PT,United Kingdom,M,Poland,50,"NLP, Docker, Kubernetes, Statistics",Master,7,Telecommunications,2024-03-21,2024-05-27,1264,6.5,Cloud AI Solutions -AI13199,AI Consultant,28360,USD,28360,EN,FL,China,M,Luxembourg,0,"Python, TensorFlow, PyTorch",Associate,0,Retail,2024-04-14,2024-05-08,1103,9.6,Cognitive Computing -AI13200,Autonomous Systems Engineer,197908,JPY,21769880,EX,FL,Japan,M,Japan,50,"Git, Linux, Azure, Data Visualization",Associate,16,Real Estate,2025-02-18,2025-04-15,1951,6.4,AI Innovations -AI13201,AI Software Engineer,181959,AUD,245645,EX,CT,Australia,S,Australia,50,"SQL, GCP, Azure, NLP, Spark",Associate,17,Consulting,2024-11-09,2024-12-19,1213,8.5,Machine Intelligence Group -AI13202,ML Ops Engineer,27691,USD,27691,EN,FL,India,M,India,100,"Kubernetes, TensorFlow, GCP, Statistics, Azure",Associate,1,Healthcare,2025-03-15,2025-04-13,1099,7.8,Quantum Computing Inc -AI13203,Research Scientist,142866,JPY,15715260,SE,CT,Japan,M,Japan,50,"Azure, AWS, Statistics, Scala",PhD,9,Government,2025-01-08,2025-01-24,2332,7.9,Smart Analytics -AI13204,Data Engineer,79744,CAD,99680,MI,PT,Canada,L,Japan,100,"Python, R, GCP, Azure, Spark",Bachelor,4,Real Estate,2024-01-13,2024-02-03,574,8.8,Autonomous Tech -AI13205,AI Architect,198736,USD,198736,EX,PT,United States,S,United States,0,"Linux, Mathematics, Git, NLP, Spark",Associate,18,Government,2024-09-01,2024-10-20,1551,7.1,Digital Transformation LLC -AI13206,Research Scientist,104891,USD,104891,MI,CT,Denmark,M,South Korea,100,"Data Visualization, Azure, GCP, SQL",Associate,2,Retail,2024-05-08,2024-07-17,1911,8.8,Machine Intelligence Group -AI13207,Data Scientist,61269,USD,61269,SE,FL,India,L,India,100,"PyTorch, TensorFlow, GCP",Bachelor,6,Real Estate,2024-01-08,2024-03-12,1695,6.8,AI Innovations -AI13208,Research Scientist,25071,USD,25071,MI,CT,India,S,India,50,"Linux, Deep Learning, Spark",Associate,2,Technology,2025-01-13,2025-03-08,1449,7.7,DeepTech Ventures -AI13209,Data Engineer,84490,CHF,76041,EN,FT,Switzerland,M,Switzerland,0,"Python, Kubernetes, Tableau",PhD,0,Transportation,2024-06-22,2024-08-22,1823,7.3,Algorithmic Solutions -AI13210,AI Architect,58087,USD,58087,MI,PT,South Korea,S,Luxembourg,50,"NLP, Statistics, AWS, Kubernetes",Bachelor,2,Real Estate,2024-08-19,2024-09-29,2017,8.8,Future Systems -AI13211,Autonomous Systems Engineer,50417,EUR,42854,EN,CT,Austria,M,Austria,0,"Azure, Java, Data Visualization",PhD,0,Manufacturing,2024-05-04,2024-06-09,1748,7.7,Cloud AI Solutions -AI13212,AI Software Engineer,149113,SGD,193847,SE,CT,Singapore,M,Singapore,0,"Java, Docker, NLP, Statistics, Scala",Associate,7,Education,2025-01-17,2025-02-18,1353,8.8,Cognitive Computing -AI13213,AI Consultant,94092,EUR,79978,SE,PT,Austria,S,Austria,100,"Hadoop, Tableau, Computer Vision, Python",Bachelor,9,Finance,2024-07-03,2024-08-25,1449,8.6,TechCorp Inc -AI13214,Head of AI,185420,USD,185420,SE,PT,United States,L,Mexico,0,"SQL, Scala, Data Visualization",Associate,6,Consulting,2024-04-25,2024-07-03,1896,9.4,Autonomous Tech -AI13215,Data Analyst,93085,EUR,79122,MI,PT,Netherlands,M,Ghana,100,"Statistics, MLOps, Computer Vision, Java, AWS",Associate,3,Government,2025-01-13,2025-02-28,2006,10,Cognitive Computing -AI13216,NLP Engineer,102367,GBP,76775,MI,FL,United Kingdom,M,United Kingdom,0,"Azure, Spark, Docker",Master,3,Healthcare,2025-02-11,2025-04-14,2318,9.9,Advanced Robotics -AI13217,Machine Learning Engineer,213126,AUD,287720,EX,FT,Australia,L,Australia,100,"Python, Data Visualization, SQL, AWS",Master,18,Gaming,2025-02-17,2025-03-10,1670,5.7,Cognitive Computing -AI13218,Data Engineer,70624,USD,70624,MI,PT,South Korea,S,South Korea,100,"Linux, TensorFlow, Data Visualization",Associate,3,Transportation,2024-07-08,2024-09-13,511,7.5,Cognitive Computing -AI13219,Machine Learning Engineer,48905,EUR,41569,EN,FL,Netherlands,S,Vietnam,0,"Docker, Tableau, PyTorch, TensorFlow, NLP",Associate,1,Real Estate,2024-01-25,2024-03-01,847,9.9,Advanced Robotics -AI13220,Research Scientist,98101,JPY,10791110,SE,FL,Japan,S,Portugal,50,"SQL, Linux, R",PhD,8,Consulting,2024-05-23,2024-06-22,1283,7.4,Neural Networks Co -AI13221,AI Consultant,141464,EUR,120244,SE,PT,Austria,M,Austria,50,"MLOps, Data Visualization, Python, TensorFlow, Docker",Master,9,Automotive,2024-02-13,2024-04-10,1489,8.7,DeepTech Ventures -AI13222,AI Specialist,140338,USD,140338,SE,CT,United States,S,Colombia,0,"Hadoop, Kubernetes, MLOps, SQL",Bachelor,6,Education,2024-12-05,2025-01-05,1117,8,Quantum Computing Inc -AI13223,AI Research Scientist,102674,JPY,11294140,SE,FT,Japan,S,Japan,50,"Python, AWS, R",PhD,5,Automotive,2024-07-31,2024-10-02,503,9.4,Smart Analytics -AI13224,AI Consultant,50281,CAD,62851,EN,FL,Canada,M,Czech Republic,100,"Spark, TensorFlow, Python",PhD,1,Media,2024-05-19,2024-06-23,2064,6.4,AI Innovations -AI13225,ML Ops Engineer,126345,SGD,164249,SE,CT,Singapore,L,Singapore,0,"Python, Linux, Git, Computer Vision",Associate,6,Consulting,2025-01-09,2025-03-04,1300,6.5,Algorithmic Solutions -AI13226,Head of AI,310457,USD,310457,EX,FL,Denmark,M,Denmark,100,"Linux, Kubernetes, PyTorch, Hadoop, Azure",Bachelor,19,Energy,2024-08-04,2024-09-29,693,8,DataVision Ltd -AI13227,AI Architect,133886,USD,133886,SE,CT,Denmark,M,Mexico,100,"Python, NLP, Scala, Computer Vision",Associate,7,Real Estate,2024-07-06,2024-08-23,796,8.3,Cognitive Computing -AI13228,Research Scientist,266548,USD,266548,EX,FL,Finland,L,Finland,100,"Kubernetes, Azure, SQL, AWS",PhD,14,Real Estate,2024-03-04,2024-03-20,1603,5.2,Machine Intelligence Group -AI13229,ML Ops Engineer,45522,USD,45522,MI,FT,China,L,China,50,"Scala, Statistics, Data Visualization, Java, Mathematics",Bachelor,2,Telecommunications,2024-07-29,2024-09-04,534,9.7,Predictive Systems -AI13230,Principal Data Scientist,110658,GBP,82994,MI,PT,United Kingdom,L,United Kingdom,100,"Scala, Kubernetes, Spark, Docker",Associate,4,Transportation,2024-03-24,2024-06-01,2049,8.3,Digital Transformation LLC -AI13231,Research Scientist,80074,USD,80074,EN,FL,Denmark,L,Denmark,50,"Data Visualization, Linux, SQL",Bachelor,1,Manufacturing,2025-02-08,2025-03-10,1335,8,Machine Intelligence Group -AI13232,AI Architect,135856,USD,135856,SE,FL,Sweden,S,Sweden,100,"Azure, R, PyTorch, AWS",Associate,9,Government,2024-09-18,2024-10-02,2285,7.6,DeepTech Ventures -AI13233,Principal Data Scientist,116833,CAD,146041,SE,CT,Canada,S,Canada,50,"Tableau, Linux, AWS, MLOps",Bachelor,8,Consulting,2025-03-02,2025-05-07,1983,9.1,Quantum Computing Inc -AI13234,AI Architect,134634,USD,134634,MI,CT,United States,L,United States,0,"Kubernetes, Statistics, Spark",Master,2,Healthcare,2024-04-03,2024-05-07,1639,9.1,Cognitive Computing -AI13235,ML Ops Engineer,129280,CHF,116352,MI,FL,Switzerland,L,Switzerland,100,"Computer Vision, Tableau, TensorFlow, Python, Statistics",Master,4,Automotive,2024-06-19,2024-08-16,1739,9,AI Innovations -AI13236,Data Engineer,246914,USD,246914,EX,FL,Denmark,L,Thailand,50,"Java, PyTorch, Mathematics, NLP",Bachelor,17,Consulting,2024-11-09,2024-12-15,2011,5.5,Future Systems -AI13237,Research Scientist,94188,JPY,10360680,MI,FL,Japan,M,Turkey,100,"Linux, Python, MLOps, Hadoop, TensorFlow",PhD,4,Gaming,2024-03-17,2024-04-04,2004,6.4,Autonomous Tech -AI13238,Deep Learning Engineer,114774,AUD,154945,MI,FT,Australia,L,Australia,100,"Python, TensorFlow, NLP, Hadoop",Associate,4,Technology,2024-05-31,2024-08-05,1786,5.2,Smart Analytics -AI13239,ML Ops Engineer,59249,USD,59249,EN,CT,Ireland,L,Ireland,0,"SQL, R, Kubernetes",Master,1,Retail,2024-08-14,2024-08-28,516,8.2,DataVision Ltd -AI13240,Principal Data Scientist,81389,USD,81389,MI,PT,South Korea,L,Turkey,0,"SQL, Hadoop, Tableau, Data Visualization",Associate,2,Technology,2024-03-02,2024-05-04,892,7.9,DataVision Ltd -AI13241,Deep Learning Engineer,60315,USD,60315,EN,PT,United States,S,China,50,"Git, PyTorch, Kubernetes",Bachelor,1,Healthcare,2024-02-27,2024-03-25,902,7.3,Algorithmic Solutions -AI13242,Research Scientist,187520,SGD,243776,EX,PT,Singapore,M,Ghana,100,"Azure, Docker, SQL, Python",PhD,17,Finance,2025-04-09,2025-06-03,1424,6.4,AI Innovations -AI13243,Data Analyst,137040,USD,137040,MI,CT,Denmark,M,Denmark,0,"NLP, TensorFlow, Docker, GCP, Python",Master,3,Consulting,2024-08-30,2024-10-22,1172,5.7,DataVision Ltd -AI13244,Computer Vision Engineer,180365,SGD,234475,SE,FL,Singapore,L,Spain,0,"SQL, PyTorch, Tableau, MLOps",PhD,5,Healthcare,2024-08-04,2024-10-12,1304,6.4,AI Innovations -AI13245,AI Research Scientist,40180,USD,40180,EN,PT,China,L,China,50,"GCP, TensorFlow, Hadoop, Python, Kubernetes",Bachelor,1,Real Estate,2024-08-09,2024-09-10,1172,7.6,DeepTech Ventures -AI13246,AI Research Scientist,93313,JPY,10264430,MI,FL,Japan,S,Japan,50,"Python, Spark, Statistics, AWS, Mathematics",Master,2,Telecommunications,2025-01-12,2025-03-03,1062,6.3,Algorithmic Solutions -AI13247,Machine Learning Engineer,106766,SGD,138796,MI,FT,Singapore,M,Singapore,50,"Kubernetes, R, Docker, PyTorch, Git",Associate,3,Government,2024-01-27,2024-03-06,2237,6.4,Algorithmic Solutions -AI13248,Machine Learning Engineer,210437,USD,210437,EX,PT,Israel,L,Israel,100,"Tableau, Kubernetes, Java, Python",Bachelor,14,Telecommunications,2024-05-29,2024-07-18,2171,8,Cognitive Computing -AI13249,AI Product Manager,75988,JPY,8358680,MI,FT,Japan,S,Japan,100,"Kubernetes, NLP, Tableau, Data Visualization",PhD,2,Telecommunications,2024-03-05,2024-04-02,1882,5.4,Cognitive Computing -AI13250,Computer Vision Engineer,144385,JPY,15882350,SE,PT,Japan,S,Japan,50,"Deep Learning, Docker, Tableau, Kubernetes, Spark",Associate,6,Manufacturing,2024-09-04,2024-11-14,1730,7.3,Quantum Computing Inc -AI13251,NLP Engineer,90091,USD,90091,SE,CT,Israel,S,Japan,100,"TensorFlow, MLOps, AWS, Java",Bachelor,8,Finance,2024-06-28,2024-07-24,1937,5.9,Digital Transformation LLC -AI13252,Deep Learning Engineer,105779,USD,105779,SE,PT,Sweden,S,Sweden,0,"Azure, AWS, Computer Vision, Python, Docker",Bachelor,6,Transportation,2025-02-16,2025-04-04,2095,5.7,Quantum Computing Inc -AI13253,NLP Engineer,306666,USD,306666,EX,PT,Norway,L,Belgium,100,"Git, Mathematics, Spark, PyTorch, Statistics",PhD,15,Manufacturing,2024-12-16,2025-01-07,2167,6.7,DeepTech Ventures -AI13254,Machine Learning Researcher,53085,USD,53085,EN,PT,Finland,S,Finland,50,"Java, Tableau, Kubernetes",PhD,1,Telecommunications,2024-07-23,2024-09-23,1112,9.7,Future Systems -AI13255,AI Research Scientist,100104,EUR,85088,SE,FL,Austria,M,Denmark,0,"Python, Statistics, Hadoop",Master,5,Energy,2024-03-23,2024-04-24,1623,7,Predictive Systems -AI13256,NLP Engineer,271861,USD,271861,EX,FL,Norway,L,Norway,50,"Azure, Python, Java",Bachelor,15,Technology,2024-12-06,2025-02-01,2332,9.2,DeepTech Ventures -AI13257,Data Engineer,49399,USD,49399,EN,FT,South Korea,M,South Korea,50,"MLOps, Python, Tableau, AWS, Java",Associate,1,Energy,2024-06-19,2024-08-18,675,8.6,Smart Analytics -AI13258,Data Analyst,103468,JPY,11381480,SE,FT,Japan,S,Japan,100,"Hadoop, R, Scala",Associate,5,Technology,2024-08-24,2024-09-23,1561,9.3,Quantum Computing Inc -AI13259,Machine Learning Engineer,93578,USD,93578,MI,CT,United States,M,United States,50,"TensorFlow, AWS, Spark, Kubernetes, SQL",Associate,3,Retail,2024-11-07,2024-12-18,1889,9.3,Quantum Computing Inc -AI13260,Machine Learning Engineer,84233,EUR,71598,EN,CT,France,L,France,0,"Python, TensorFlow, Deep Learning, Statistics",PhD,1,Media,2024-07-11,2024-07-25,742,5.7,Cloud AI Solutions -AI13261,AI Consultant,112337,USD,112337,EN,CT,Denmark,L,Denmark,0,"Tableau, Linux, Kubernetes",PhD,1,Government,2024-07-11,2024-09-02,1248,9,Advanced Robotics -AI13262,AI Consultant,239391,USD,239391,EX,FT,Denmark,M,Sweden,50,"Hadoop, Scala, MLOps, R, Git",Bachelor,12,Energy,2025-04-29,2025-06-29,2480,5,DataVision Ltd -AI13263,Computer Vision Engineer,45215,USD,45215,EN,PT,South Korea,S,South Korea,0,"GCP, Linux, NLP, Hadoop",PhD,0,Media,2024-07-13,2024-09-13,1982,5.5,Neural Networks Co -AI13264,Machine Learning Researcher,48795,EUR,41476,EN,FT,France,S,Romania,50,"TensorFlow, Python, SQL, Kubernetes",Bachelor,1,Real Estate,2025-01-23,2025-03-11,1982,8.7,DataVision Ltd -AI13265,AI Consultant,119095,CHF,107186,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, Hadoop, GCP, Computer Vision, Azure",PhD,2,Telecommunications,2024-04-13,2024-05-30,958,8.9,Smart Analytics -AI13266,ML Ops Engineer,98669,GBP,74002,SE,CT,United Kingdom,S,United Kingdom,100,"MLOps, Python, Data Visualization",Master,9,Automotive,2024-05-10,2024-07-06,1095,8.3,TechCorp Inc -AI13267,AI Architect,128617,SGD,167202,SE,CT,Singapore,M,Netherlands,100,"Computer Vision, SQL, Data Visualization, Kubernetes, Docker",PhD,6,Retail,2024-08-17,2024-09-09,2213,8.5,DataVision Ltd -AI13268,Robotics Engineer,95556,USD,95556,MI,FT,Sweden,M,Sweden,0,"Kubernetes, Deep Learning, Linux",PhD,2,Manufacturing,2024-12-13,2025-01-31,1250,6.2,Advanced Robotics -AI13269,Machine Learning Engineer,200162,SGD,260211,EX,FL,Singapore,L,Singapore,50,"R, Spark, MLOps, Mathematics",PhD,11,Manufacturing,2025-01-23,2025-02-09,840,8.3,Autonomous Tech -AI13270,Principal Data Scientist,109357,EUR,92953,MI,PT,Netherlands,L,Norway,0,"NLP, Git, Java, MLOps",Associate,4,Government,2025-02-01,2025-03-30,2304,6.7,Quantum Computing Inc -AI13271,Head of AI,122021,USD,122021,MI,FT,Norway,M,United Kingdom,0,"Kubernetes, Python, Tableau",Master,2,Manufacturing,2024-08-19,2024-10-07,669,5.3,DataVision Ltd -AI13272,Head of AI,325087,CHF,292578,EX,PT,Switzerland,L,Ghana,100,"Python, Git, Tableau",Associate,11,Retail,2025-03-25,2025-05-21,2055,5.5,DataVision Ltd -AI13273,Machine Learning Engineer,168996,JPY,18589560,EX,FT,Japan,M,Chile,0,"Deep Learning, Scala, Spark, Python",Associate,16,Healthcare,2024-01-30,2024-03-25,1234,6.2,Digital Transformation LLC -AI13274,ML Ops Engineer,43570,USD,43570,EN,FT,South Korea,S,South Korea,50,"Java, SQL, Git, Data Visualization, Python",Master,0,Manufacturing,2024-03-31,2024-05-26,1032,6.9,Algorithmic Solutions -AI13275,AI Architect,149909,USD,149909,SE,PT,United States,L,United States,50,"GCP, Python, TensorFlow, Deep Learning, Tableau",PhD,9,Gaming,2025-03-25,2025-05-05,1503,5.8,Future Systems -AI13276,Computer Vision Engineer,82164,USD,82164,EN,FL,United States,S,Sweden,50,"TensorFlow, NLP, Linux, Statistics, Deep Learning",Bachelor,1,Transportation,2024-01-04,2024-01-27,1031,6,Digital Transformation LLC -AI13277,AI Consultant,92430,USD,92430,MI,CT,Israel,S,Brazil,100,"Data Visualization, Tableau, PyTorch, Python, Mathematics",Associate,4,Real Estate,2025-01-29,2025-02-12,1295,8.4,Autonomous Tech -AI13278,AI Specialist,49758,USD,49758,EN,FT,South Korea,S,South Korea,100,"R, Statistics, Hadoop, Git",Master,0,Healthcare,2024-11-03,2025-01-07,2206,7.6,Neural Networks Co -AI13279,AI Product Manager,74628,GBP,55971,EN,CT,United Kingdom,L,Russia,100,"Git, Hadoop, MLOps",PhD,1,Healthcare,2024-02-16,2024-03-14,1505,5.7,Cloud AI Solutions -AI13280,Robotics Engineer,128025,GBP,96019,MI,FT,United Kingdom,L,South Africa,50,"Python, Linux, Azure, Deep Learning",Master,2,Education,2024-03-30,2024-04-23,2160,7.1,Cognitive Computing -AI13281,Data Engineer,100244,EUR,85207,SE,CT,Germany,S,Netherlands,50,"R, SQL, Scala, Python",Master,8,Education,2024-08-14,2024-09-05,865,7,Future Systems -AI13282,Autonomous Systems Engineer,34992,USD,34992,MI,FL,India,S,Belgium,100,"PyTorch, Java, NLP",Associate,3,Retail,2024-02-17,2024-04-08,1855,9.9,DataVision Ltd -AI13283,AI Research Scientist,94904,EUR,80668,MI,CT,France,L,Israel,100,"GCP, Linux, Hadoop, Java",PhD,2,Healthcare,2024-05-04,2024-06-17,1361,9.8,Digital Transformation LLC -AI13284,Data Analyst,134647,JPY,14811170,EX,CT,Japan,S,Japan,0,"Kubernetes, Python, TensorFlow, Deep Learning",Associate,19,Automotive,2025-01-31,2025-03-28,1051,8.8,DataVision Ltd -AI13285,AI Consultant,47733,USD,47733,EN,FL,Finland,S,Argentina,50,"NLP, Python, Java, R, GCP",PhD,1,Transportation,2024-11-14,2024-12-17,2101,5.6,Neural Networks Co -AI13286,AI Research Scientist,126186,GBP,94640,SE,FT,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Deep Learning, Python, NLP",PhD,8,Manufacturing,2024-04-25,2024-06-21,706,5.2,Cloud AI Solutions -AI13287,Robotics Engineer,178018,USD,178018,EX,FL,Finland,M,Finland,50,"GCP, NLP, Scala, Java",Master,11,Education,2024-05-21,2024-06-30,600,6.7,AI Innovations -AI13288,Computer Vision Engineer,58807,EUR,49986,EN,FL,France,L,France,100,"Computer Vision, R, Python, Kubernetes, MLOps",Associate,1,Media,2024-06-09,2024-07-29,713,6.8,Cognitive Computing -AI13289,ML Ops Engineer,78517,EUR,66739,EN,FT,France,L,France,100,"GCP, Deep Learning, Linux",Master,0,Technology,2024-12-31,2025-02-15,692,9.8,Machine Intelligence Group -AI13290,Computer Vision Engineer,152471,EUR,129600,SE,FT,Germany,L,Germany,0,"Git, Statistics, Kubernetes, Linux, PyTorch",PhD,9,Automotive,2024-05-12,2024-05-28,632,6.8,DataVision Ltd -AI13291,AI Research Scientist,83053,USD,83053,EN,FT,Ireland,L,Ireland,0,"Kubernetes, Python, AWS, TensorFlow, Data Visualization",PhD,1,Transportation,2024-12-18,2025-02-03,1920,7.4,TechCorp Inc -AI13292,Deep Learning Engineer,55419,EUR,47106,EN,FL,Austria,S,Czech Republic,100,"Data Visualization, GCP, Kubernetes, R",Master,1,Real Estate,2025-01-19,2025-02-18,2179,8.7,Machine Intelligence Group -AI13293,Data Analyst,226088,CAD,282610,EX,CT,Canada,M,Latvia,0,"Tableau, Hadoop, Kubernetes, Mathematics, Scala",PhD,13,Retail,2024-02-24,2024-03-19,777,9.9,Cognitive Computing -AI13294,Machine Learning Researcher,140926,GBP,105695,SE,FT,United Kingdom,S,United Kingdom,100,"MLOps, PyTorch, Docker, Mathematics",Bachelor,5,Consulting,2024-03-17,2024-04-10,566,7.9,DataVision Ltd -AI13295,Machine Learning Researcher,97767,EUR,83102,SE,FT,Netherlands,S,Netherlands,50,"Linux, Git, MLOps, Computer Vision, Python",Associate,9,Automotive,2024-01-07,2024-02-23,1471,5.5,Neural Networks Co -AI13296,Data Scientist,100990,GBP,75743,SE,FL,United Kingdom,S,United Kingdom,100,"Python, Deep Learning, SQL, GCP",Associate,8,Technology,2024-10-31,2024-11-22,904,8.7,DeepTech Ventures -AI13297,Data Analyst,136795,GBP,102596,SE,PT,United Kingdom,M,United Kingdom,100,"MLOps, Hadoop, Scala, Linux, Java",Master,7,Telecommunications,2024-06-13,2024-06-29,2464,6.1,AI Innovations -AI13298,AI Architect,76815,USD,76815,MI,FT,Sweden,S,Sweden,100,"Mathematics, AWS, Hadoop, Deep Learning",Bachelor,3,Manufacturing,2024-09-24,2024-10-11,1123,5.5,Smart Analytics -AI13299,Head of AI,80644,USD,80644,EN,PT,United States,M,United States,50,"Python, TensorFlow, Tableau",PhD,1,Gaming,2024-08-17,2024-09-20,1924,10,TechCorp Inc -AI13300,Deep Learning Engineer,90240,JPY,9926400,MI,FL,Japan,S,Japan,50,"SQL, PyTorch, MLOps",Associate,3,Government,2024-09-16,2024-11-26,591,9.1,Machine Intelligence Group -AI13301,Machine Learning Engineer,199372,USD,199372,EX,PT,Norway,S,Luxembourg,0,"Python, Scala, NLP, Azure, Kubernetes",PhD,17,Technology,2024-07-05,2024-09-07,1177,8.6,Quantum Computing Inc -AI13302,Robotics Engineer,232839,EUR,197913,EX,CT,France,M,France,100,"Linux, GCP, R, Spark, Python",Master,10,Media,2024-12-12,2025-02-11,1555,6.9,Cloud AI Solutions -AI13303,AI Research Scientist,120541,USD,120541,MI,CT,Denmark,M,Denmark,100,"PyTorch, Kubernetes, Hadoop, NLP, GCP",Master,2,Consulting,2025-01-02,2025-01-30,2358,6.2,Predictive Systems -AI13304,ML Ops Engineer,94694,USD,94694,EN,CT,Norway,M,Romania,0,"Spark, Computer Vision, SQL",Associate,1,Gaming,2024-02-19,2024-05-02,1701,8.5,TechCorp Inc -AI13305,NLP Engineer,69183,AUD,93397,EN,PT,Australia,M,Japan,50,"Azure, Linux, PyTorch",Master,0,Finance,2024-08-25,2024-11-03,657,7.3,AI Innovations -AI13306,AI Software Engineer,101698,EUR,86443,SE,FT,Austria,M,China,100,"Linux, Python, Azure, TensorFlow, AWS",Master,6,Real Estate,2024-05-15,2024-06-20,976,7.9,Quantum Computing Inc -AI13307,Head of AI,131365,USD,131365,SE,FL,Israel,M,Israel,50,"Data Visualization, Spark, GCP, Docker",PhD,7,Gaming,2024-02-14,2024-04-15,1663,6.3,Quantum Computing Inc -AI13308,AI Consultant,130237,GBP,97678,SE,PT,United Kingdom,S,United Kingdom,50,"Data Visualization, NLP, R, AWS",PhD,8,Finance,2024-01-14,2024-03-15,1184,10,TechCorp Inc -AI13309,AI Architect,171976,USD,171976,SE,FT,Ireland,L,Ireland,100,"Deep Learning, Azure, Spark",Associate,6,Energy,2024-04-23,2024-05-26,811,6.3,Quantum Computing Inc -AI13310,AI Product Manager,219348,USD,219348,EX,FT,Denmark,L,Denmark,50,"Python, TensorFlow, PyTorch, Docker, Statistics",Associate,18,Telecommunications,2024-02-28,2024-04-28,629,5.6,Autonomous Tech -AI13311,AI Research Scientist,215507,USD,215507,EX,FL,Israel,M,Israel,100,"Scala, TensorFlow, Azure, Python, PyTorch",PhD,19,Education,2024-07-10,2024-08-07,2042,7.6,Digital Transformation LLC -AI13312,Data Analyst,168512,USD,168512,SE,FL,Sweden,L,Canada,100,"GCP, Data Visualization, Python",PhD,7,Transportation,2024-04-23,2024-06-29,1881,9.1,Algorithmic Solutions -AI13313,AI Research Scientist,121328,JPY,13346080,SE,FL,Japan,S,Japan,0,"SQL, PyTorch, GCP, Tableau",Master,8,Real Estate,2024-04-18,2024-05-21,733,7.3,Machine Intelligence Group -AI13314,AI Software Engineer,289498,USD,289498,EX,PT,Denmark,M,Denmark,0,"Scala, GCP, Deep Learning, R",Associate,10,Healthcare,2024-12-23,2025-01-15,670,9.1,Digital Transformation LLC -AI13315,AI Research Scientist,109391,AUD,147678,SE,CT,Australia,S,Australia,50,"AWS, Kubernetes, Mathematics, Java",Bachelor,5,Technology,2024-07-09,2024-09-04,571,8.7,Neural Networks Co -AI13316,Head of AI,92796,USD,92796,MI,PT,South Korea,L,South Korea,100,"Data Visualization, TensorFlow, NLP, Kubernetes",Associate,4,Telecommunications,2024-02-15,2024-04-14,1608,9.6,Future Systems -AI13317,Computer Vision Engineer,254375,SGD,330688,EX,FT,Singapore,M,Singapore,0,"GCP, Scala, Git, R",Associate,19,Education,2024-05-08,2024-05-29,1024,6.5,Smart Analytics -AI13318,Machine Learning Researcher,64737,CAD,80921,MI,FL,Canada,S,Canada,0,"Git, Tableau, Python, Data Visualization, TensorFlow",Bachelor,2,Gaming,2024-01-31,2024-04-05,1165,6.2,Future Systems -AI13319,Robotics Engineer,101753,EUR,86490,SE,PT,Netherlands,S,Netherlands,50,"Kubernetes, NLP, Data Visualization, GCP, Linux",PhD,9,Real Estate,2025-04-07,2025-05-07,1334,7.5,Predictive Systems -AI13320,Autonomous Systems Engineer,208375,EUR,177119,EX,FT,Netherlands,M,Netherlands,100,"Git, Mathematics, Computer Vision",Bachelor,11,Education,2025-04-21,2025-06-24,977,9.1,Quantum Computing Inc -AI13321,Autonomous Systems Engineer,127596,AUD,172255,SE,FL,Australia,S,Netherlands,50,"SQL, PyTorch, Java",Master,6,Healthcare,2024-09-01,2024-11-02,2402,6.6,Digital Transformation LLC -AI13322,Data Analyst,231910,EUR,197124,EX,FL,France,L,France,50,"MLOps, PyTorch, Hadoop",Associate,12,Automotive,2024-09-29,2024-11-15,1309,9.4,Neural Networks Co -AI13323,ML Ops Engineer,40030,USD,40030,SE,FL,India,M,India,0,"GCP, Deep Learning, Kubernetes",Bachelor,5,Transportation,2024-11-08,2024-12-02,1632,5.6,Cloud AI Solutions -AI13324,AI Architect,108886,USD,108886,EX,FT,China,L,China,100,"NLP, Scala, SQL",Master,11,Technology,2024-03-22,2024-04-27,1355,6,DeepTech Ventures -AI13325,Data Scientist,25902,USD,25902,EN,PT,China,M,Romania,50,"TensorFlow, Linux, Hadoop",Bachelor,0,Technology,2024-12-03,2025-01-12,1563,6,Algorithmic Solutions -AI13326,AI Research Scientist,86757,AUD,117122,MI,CT,Australia,L,Australia,100,"Kubernetes, GCP, Data Visualization, Mathematics, SQL",Bachelor,3,Retail,2025-01-15,2025-03-04,1437,7,Smart Analytics -AI13327,Data Analyst,38963,USD,38963,MI,FT,China,M,China,0,"Kubernetes, Spark, Python, Linux, Mathematics",Associate,3,Automotive,2024-11-17,2024-12-02,1495,6.7,Machine Intelligence Group -AI13328,AI Architect,308292,CHF,277463,EX,FL,Switzerland,L,Switzerland,100,"Kubernetes, Spark, Tableau, Hadoop, Git",PhD,11,Education,2024-06-07,2024-07-04,1113,7.9,DeepTech Ventures -AI13329,AI Software Engineer,194259,CHF,174833,SE,FL,Switzerland,L,Ukraine,50,"Kubernetes, Scala, Statistics, Tableau, Spark",Associate,7,Gaming,2024-06-11,2024-07-30,2266,7.6,Algorithmic Solutions -AI13330,Machine Learning Researcher,90499,AUD,122174,EN,CT,Australia,L,Kenya,100,"Linux, Python, Mathematics, Kubernetes, Hadoop",PhD,0,Government,2025-02-01,2025-03-16,1479,7.1,Cognitive Computing -AI13331,AI Research Scientist,152866,EUR,129936,EX,FT,Netherlands,S,Nigeria,0,"Git, Linux, Kubernetes, Python",PhD,14,Consulting,2024-02-13,2024-04-24,1604,5.9,Future Systems -AI13332,AI Consultant,207262,USD,207262,EX,FT,Norway,M,United States,0,"PyTorch, TensorFlow, Spark, Python, Hadoop",Master,19,Media,2025-04-07,2025-06-18,1968,9,Quantum Computing Inc -AI13333,Autonomous Systems Engineer,97380,CAD,121725,MI,FT,Canada,L,Russia,100,"R, MLOps, Data Visualization, SQL, Mathematics",Bachelor,4,Consulting,2024-06-21,2024-07-13,2191,5.9,Algorithmic Solutions -AI13334,AI Software Engineer,163759,USD,163759,SE,PT,Denmark,L,Denmark,0,"Kubernetes, Docker, Scala, Hadoop, Statistics",Associate,5,Real Estate,2024-03-04,2024-04-02,2380,6.1,Digital Transformation LLC -AI13335,Machine Learning Researcher,121421,EUR,103208,SE,FL,France,S,France,0,"Java, Linux, Tableau, MLOps, Statistics",Associate,6,Telecommunications,2025-04-01,2025-05-06,595,7.4,Future Systems -AI13336,Data Engineer,43568,EUR,37033,EN,PT,France,S,China,50,"Statistics, GCP, Data Visualization, Java",Bachelor,0,Technology,2024-04-02,2024-06-09,880,9.1,Machine Intelligence Group -AI13337,Research Scientist,119350,USD,119350,EX,FT,China,L,China,0,"Java, NLP, Python, Kubernetes",Associate,10,Healthcare,2024-02-11,2024-03-29,1105,9.2,Predictive Systems -AI13338,Computer Vision Engineer,95494,USD,95494,SE,PT,South Korea,S,South Korea,50,"Python, TensorFlow, Java",Associate,6,Energy,2024-04-16,2024-05-16,2058,6,Predictive Systems -AI13339,Deep Learning Engineer,62202,EUR,52872,EN,CT,Germany,S,Germany,50,"Scala, SQL, Python, Java, NLP",Master,1,Media,2025-04-17,2025-06-22,997,6.6,TechCorp Inc -AI13340,AI Consultant,88967,USD,88967,EN,PT,Sweden,L,Turkey,50,"TensorFlow, Azure, Deep Learning, Computer Vision, Linux",PhD,1,Real Estate,2024-12-20,2025-02-09,2438,7.1,Autonomous Tech -AI13341,Robotics Engineer,63313,CAD,79141,EN,FT,Canada,M,Canada,100,"Kubernetes, PyTorch, Mathematics, Computer Vision, GCP",Bachelor,1,Telecommunications,2024-12-24,2025-02-28,1312,7.3,Quantum Computing Inc -AI13342,Autonomous Systems Engineer,59228,CAD,74035,EN,PT,Canada,S,Canada,0,"TensorFlow, Python, Java, Spark, Kubernetes",Associate,0,Retail,2024-07-23,2024-09-19,924,8.8,Algorithmic Solutions -AI13343,Autonomous Systems Engineer,125001,USD,125001,SE,CT,Israel,S,Israel,100,"AWS, Spark, Data Visualization, Git",Associate,8,Energy,2024-08-01,2024-09-07,1524,6.6,TechCorp Inc -AI13344,Principal Data Scientist,36642,USD,36642,EN,PT,China,L,China,100,"Python, Scala, Java",Master,0,Telecommunications,2024-10-28,2024-12-27,1096,5.9,Neural Networks Co -AI13345,Principal Data Scientist,113963,USD,113963,MI,PT,Denmark,M,Denmark,100,"Python, Data Visualization, AWS, Spark",PhD,2,Energy,2024-07-20,2024-09-26,1472,8.2,Autonomous Tech -AI13346,Machine Learning Engineer,135609,USD,135609,SE,FT,Denmark,M,Luxembourg,100,"R, Tableau, Statistics, NLP",Master,8,Healthcare,2024-01-29,2024-03-21,1855,8.7,AI Innovations -AI13347,Deep Learning Engineer,129508,GBP,97131,SE,FT,United Kingdom,M,United Kingdom,0,"Linux, Docker, PyTorch, R",Master,9,Transportation,2024-09-28,2024-11-13,1340,9,AI Innovations -AI13348,Head of AI,222566,JPY,24482260,EX,PT,Japan,S,Japan,0,"Docker, Deep Learning, SQL, MLOps",PhD,11,Gaming,2024-05-13,2024-07-15,766,6.3,Machine Intelligence Group -AI13349,AI Architect,263402,JPY,28974220,EX,PT,Japan,L,Japan,0,"Kubernetes, Java, R, Statistics",Associate,11,Education,2024-09-18,2024-10-15,2271,6.6,AI Innovations -AI13350,Computer Vision Engineer,60120,GBP,45090,EN,FL,United Kingdom,S,Ukraine,0,"MLOps, Computer Vision, GCP, Kubernetes",PhD,1,Telecommunications,2025-03-03,2025-05-10,1798,6.9,Autonomous Tech -AI13351,Machine Learning Engineer,76589,USD,76589,MI,FT,Finland,S,Finland,100,"Kubernetes, Git, SQL",Associate,2,Real Estate,2024-08-18,2024-10-29,2474,9.2,Algorithmic Solutions -AI13352,Deep Learning Engineer,73963,USD,73963,EN,FL,United States,L,United States,50,"Python, TensorFlow, Azure, Spark, PyTorch",Master,1,Finance,2024-09-24,2024-10-19,714,9.9,Quantum Computing Inc -AI13353,Machine Learning Researcher,320290,USD,320290,EX,FT,Denmark,L,Denmark,100,"Hadoop, Python, Scala, AWS",Bachelor,13,Media,2024-11-02,2024-12-29,1220,5.6,DeepTech Ventures -AI13354,Deep Learning Engineer,148841,JPY,16372510,SE,FL,Japan,L,Russia,0,"Kubernetes, Scala, Java, Spark, R",Associate,8,Real Estate,2024-07-22,2024-08-20,828,6.6,Neural Networks Co -AI13355,Head of AI,111086,USD,111086,EN,FL,Denmark,L,Denmark,100,"Computer Vision, Azure, Python, TensorFlow, GCP",Master,1,Automotive,2024-06-01,2024-07-19,2404,7,AI Innovations -AI13356,Computer Vision Engineer,259096,USD,259096,EX,FL,United States,M,United States,50,"Spark, Statistics, NLP, Python",Bachelor,17,Telecommunications,2024-07-23,2024-08-08,1084,7,Quantum Computing Inc -AI13357,Computer Vision Engineer,90325,CAD,112906,MI,PT,Canada,L,New Zealand,100,"Kubernetes, Deep Learning, Python, Data Visualization",Bachelor,4,Healthcare,2024-09-05,2024-10-04,1127,5.4,TechCorp Inc -AI13358,AI Product Manager,92718,SGD,120533,MI,CT,Singapore,L,Singapore,0,"Python, MLOps, Tableau, TensorFlow",Associate,2,Manufacturing,2024-07-11,2024-09-07,893,9.6,DeepTech Ventures -AI13359,Deep Learning Engineer,124245,USD,124245,SE,PT,Israel,M,Israel,0,"PyTorch, TensorFlow, Mathematics",Bachelor,6,Energy,2025-01-10,2025-02-16,2472,5,Cloud AI Solutions -AI13360,Data Scientist,235413,GBP,176560,EX,FT,United Kingdom,S,United Kingdom,0,"Java, Hadoop, Tableau",Bachelor,12,Education,2025-02-11,2025-03-15,1436,8,Quantum Computing Inc -AI13361,Machine Learning Engineer,137922,EUR,117234,SE,PT,France,L,France,0,"AWS, Kubernetes, MLOps, Scala, Python",Bachelor,9,Telecommunications,2024-09-11,2024-11-20,2186,9.5,Future Systems -AI13362,Data Scientist,123420,USD,123420,MI,FT,United States,M,United States,100,"Mathematics, SQL, PyTorch, GCP",Bachelor,3,Energy,2024-10-30,2024-12-31,855,8.3,Advanced Robotics -AI13363,AI Software Engineer,234411,USD,234411,EX,PT,Israel,L,Russia,50,"Spark, Computer Vision, Docker, Data Visualization, R",Bachelor,16,Manufacturing,2024-08-28,2024-09-24,2452,6.8,DataVision Ltd -AI13364,Deep Learning Engineer,28209,USD,28209,MI,PT,India,S,India,100,"Azure, Scala, Mathematics, Linux, SQL",Master,3,Transportation,2025-02-06,2025-03-31,1105,9.3,Future Systems -AI13365,Machine Learning Engineer,77044,USD,77044,EN,FL,Norway,S,France,100,"Azure, AWS, Git",PhD,1,Transportation,2025-01-31,2025-03-24,852,5.4,Autonomous Tech -AI13366,Principal Data Scientist,126485,JPY,13913350,SE,FT,Japan,M,Japan,50,"SQL, Kubernetes, PyTorch, Tableau, Deep Learning",Associate,8,Technology,2024-10-05,2024-12-04,2474,5.5,Neural Networks Co -AI13367,NLP Engineer,75977,USD,75977,EN,FL,Ireland,L,Ireland,50,"R, Git, TensorFlow, Computer Vision, Spark",PhD,1,Media,2024-10-09,2024-12-10,1540,7.5,AI Innovations -AI13368,Data Engineer,53042,EUR,45086,EN,CT,Austria,M,Mexico,0,"Python, TensorFlow, Scala, Azure",Associate,0,Education,2024-01-28,2024-03-09,1094,8.1,Digital Transformation LLC -AI13369,AI Product Manager,88798,EUR,75478,MI,FL,Netherlands,M,Nigeria,0,"Deep Learning, Azure, MLOps",Bachelor,3,Technology,2024-07-01,2024-07-26,2121,5.7,Cloud AI Solutions -AI13370,Autonomous Systems Engineer,133645,EUR,113598,EX,PT,Austria,S,Austria,0,"Spark, Python, TensorFlow",Bachelor,18,Retail,2024-06-05,2024-06-24,2153,9.9,Cloud AI Solutions -AI13371,Machine Learning Engineer,123940,USD,123940,SE,CT,Sweden,L,Sweden,50,"Computer Vision, NLP, Scala, Python, Kubernetes",Associate,8,Transportation,2024-03-08,2024-03-25,2348,8.9,Smart Analytics -AI13372,AI Product Manager,250927,USD,250927,EX,FL,Finland,L,Finland,50,"Python, Kubernetes, Tableau, Hadoop, Data Visualization",Master,11,Healthcare,2025-02-12,2025-03-07,1895,7.2,Algorithmic Solutions -AI13373,AI Research Scientist,68177,SGD,88630,EN,FL,Singapore,S,Singapore,0,"Tableau, SQL, Statistics, TensorFlow, Docker",Bachelor,0,Finance,2024-05-18,2024-07-12,1152,7.8,TechCorp Inc -AI13374,AI Software Engineer,92501,USD,92501,MI,FL,Israel,L,Israel,100,"Python, TensorFlow, Scala, Hadoop",Associate,2,Real Estate,2025-02-24,2025-04-21,535,7.1,Neural Networks Co -AI13375,Computer Vision Engineer,117573,EUR,99937,SE,CT,Netherlands,M,Indonesia,50,"Azure, GCP, Scala, Mathematics, Spark",Master,5,Real Estate,2024-09-24,2024-10-13,1801,7.8,Autonomous Tech -AI13376,AI Software Engineer,48867,USD,48867,EN,FL,South Korea,M,South Korea,100,"Data Visualization, Linux, AWS, PyTorch, Java",Master,1,Gaming,2024-04-10,2024-05-06,1455,8.8,Quantum Computing Inc -AI13377,AI Product Manager,65451,AUD,88359,EN,CT,Australia,S,Australia,50,"Hadoop, Data Visualization, TensorFlow, Mathematics, Azure",Associate,1,Transportation,2025-02-28,2025-04-18,973,8.5,Smart Analytics -AI13378,NLP Engineer,96257,EUR,81818,SE,CT,Austria,M,Thailand,100,"Scala, Linux, Tableau, Data Visualization",Bachelor,9,Technology,2024-11-22,2025-01-31,2016,9.9,DeepTech Ventures -AI13379,Computer Vision Engineer,64758,USD,64758,MI,FL,Israel,S,Israel,50,"Tableau, Spark, GCP, PyTorch, Data Visualization",Associate,4,Telecommunications,2024-07-17,2024-08-06,1475,9.7,Cognitive Computing -AI13380,AI Architect,76008,EUR,64607,EN,CT,Germany,M,Hungary,50,"Tableau, Kubernetes, Data Visualization",PhD,0,Manufacturing,2024-02-26,2024-04-03,2311,7.7,Future Systems -AI13381,ML Ops Engineer,61682,EUR,52430,EN,CT,Netherlands,S,Netherlands,50,"Python, Docker, Hadoop",PhD,0,Energy,2024-02-28,2024-03-27,1643,9.9,Cloud AI Solutions -AI13382,AI Specialist,193425,USD,193425,EX,FL,Ireland,S,Ireland,0,"NLP, PyTorch, Statistics, Spark, Mathematics",Bachelor,19,Media,2024-11-23,2024-12-24,1129,9.6,Advanced Robotics -AI13383,Computer Vision Engineer,96082,EUR,81670,SE,FL,France,M,France,0,"PyTorch, Mathematics, Python",Master,9,Energy,2024-08-15,2024-10-24,2178,6.7,Cloud AI Solutions -AI13384,AI Research Scientist,118266,CHF,106439,MI,CT,Switzerland,M,Turkey,50,"SQL, Mathematics, Spark, Kubernetes",Bachelor,3,Finance,2024-07-29,2024-09-22,1546,10,TechCorp Inc -AI13385,Head of AI,92143,AUD,124393,EN,FT,Australia,L,Australia,100,"Git, Docker, Kubernetes, Spark, GCP",Associate,1,Government,2024-03-27,2024-04-11,1750,5.5,Neural Networks Co -AI13386,Computer Vision Engineer,53657,SGD,69754,EN,FL,Singapore,S,Singapore,100,"PyTorch, GCP, Python",PhD,1,Gaming,2024-10-03,2024-11-27,1961,6.1,Predictive Systems -AI13387,AI Software Engineer,219960,USD,219960,EX,FT,United States,M,United States,100,"SQL, PyTorch, Kubernetes",Bachelor,17,Automotive,2024-03-14,2024-04-01,1905,8.2,Digital Transformation LLC -AI13388,AI Software Engineer,227427,USD,227427,EX,FT,Ireland,S,Ireland,0,"Scala, Git, Hadoop",Bachelor,15,Finance,2025-03-05,2025-03-23,1930,7.2,Machine Intelligence Group -AI13389,AI Research Scientist,140704,USD,140704,EX,PT,South Korea,L,South Korea,100,"SQL, Python, PyTorch, Azure, Mathematics",Bachelor,19,Retail,2024-10-08,2024-11-30,1659,6,Predictive Systems -AI13390,AI Architect,90170,USD,90170,EN,FL,Denmark,S,Norway,0,"R, Hadoop, Mathematics",PhD,1,Automotive,2025-01-27,2025-02-18,1589,7.9,Smart Analytics -AI13391,AI Architect,75174,AUD,101485,MI,FT,Australia,S,Australia,100,"GCP, Python, Tableau, MLOps",Associate,2,Consulting,2024-06-18,2024-07-25,2007,7.6,Digital Transformation LLC -AI13392,Data Scientist,98977,EUR,84130,MI,CT,Germany,S,Germany,100,"Deep Learning, Spark, Python",Associate,2,Retail,2025-02-10,2025-04-06,760,6.2,Advanced Robotics -AI13393,Data Engineer,92614,USD,92614,EN,PT,Norway,L,Norway,100,"SQL, Linux, MLOps, Python, GCP",Bachelor,1,Real Estate,2024-04-27,2024-06-06,2066,8,Advanced Robotics -AI13394,Research Scientist,24682,USD,24682,EN,CT,China,S,China,0,"AWS, Linux, TensorFlow",Bachelor,0,Government,2024-07-20,2024-09-27,1943,8.2,Neural Networks Co -AI13395,Head of AI,169552,USD,169552,EX,FT,Finland,S,Finland,100,"TensorFlow, Python, Tableau",Bachelor,11,Finance,2024-08-15,2024-10-27,1956,7.4,Digital Transformation LLC -AI13396,ML Ops Engineer,152388,EUR,129530,EX,PT,Germany,M,Germany,0,"PyTorch, GCP, Azure, SQL, Mathematics",Bachelor,14,Government,2024-05-28,2024-06-13,1778,7.6,Cognitive Computing -AI13397,Research Scientist,56108,EUR,47692,EN,FL,Netherlands,S,Netherlands,50,"NLP, Python, Java",Master,0,Automotive,2025-02-17,2025-04-14,576,5.4,Machine Intelligence Group -AI13398,AI Consultant,185781,USD,185781,SE,CT,Norway,M,Norway,100,"Computer Vision, Kubernetes, NLP, Java, TensorFlow",Bachelor,6,Real Estate,2024-03-26,2024-05-19,1329,9.7,AI Innovations -AI13399,ML Ops Engineer,175075,SGD,227598,EX,PT,Singapore,S,Singapore,0,"Spark, PyTorch, Docker, SQL",Associate,18,Telecommunications,2025-03-27,2025-05-23,588,6.2,DataVision Ltd -AI13400,AI Specialist,69174,USD,69174,EN,PT,United States,M,United States,100,"Kubernetes, Spark, Python, Java",PhD,0,Telecommunications,2024-03-20,2024-04-08,1954,9.9,Cognitive Computing -AI13401,Data Engineer,114304,CHF,102874,EN,FT,Switzerland,L,Switzerland,50,"R, Python, Mathematics, Java",Associate,0,Energy,2024-06-02,2024-06-16,634,7.5,Neural Networks Co -AI13402,AI Specialist,205622,EUR,174779,EX,FL,Netherlands,M,Netherlands,100,"Mathematics, SQL, Data Visualization",PhD,18,Healthcare,2025-04-11,2025-05-27,501,8,Quantum Computing Inc -AI13403,Computer Vision Engineer,162908,EUR,138472,SE,FT,France,L,Argentina,100,"Scala, Docker, Statistics",PhD,7,Consulting,2024-07-19,2024-09-19,2059,7,Autonomous Tech -AI13404,Principal Data Scientist,357781,USD,357781,EX,PT,Denmark,L,Denmark,100,"Python, TensorFlow, AWS, Computer Vision, Statistics",Associate,10,Government,2025-03-02,2025-03-25,994,10,DeepTech Ventures -AI13405,ML Ops Engineer,204495,USD,204495,EX,CT,Sweden,M,Sweden,0,"Python, Docker, Data Visualization",PhD,10,Telecommunications,2024-06-16,2024-07-08,2403,9.1,DeepTech Ventures -AI13406,AI Software Engineer,70678,GBP,53009,EN,FL,United Kingdom,M,United Kingdom,100,"Python, Hadoop, Git, TensorFlow, Statistics",Associate,0,Automotive,2025-04-30,2025-06-01,1363,7.6,Machine Intelligence Group -AI13407,Machine Learning Engineer,114963,EUR,97719,MI,CT,Netherlands,M,Netherlands,50,"PyTorch, Data Visualization, SQL, TensorFlow, Java",Master,4,Telecommunications,2024-09-17,2024-10-16,905,6.7,Future Systems -AI13408,Research Scientist,67163,USD,67163,EX,FL,India,S,India,100,"TensorFlow, Deep Learning, Tableau",Bachelor,17,Education,2025-04-03,2025-05-16,1435,8.1,Autonomous Tech -AI13409,Machine Learning Engineer,211419,SGD,274845,EX,FL,Singapore,S,Switzerland,100,"Hadoop, Java, NLP, TensorFlow, Kubernetes",PhD,12,Technology,2024-12-17,2025-01-05,1204,9.8,DataVision Ltd -AI13410,AI Software Engineer,134096,USD,134096,SE,FT,Sweden,L,Sweden,50,"Deep Learning, Docker, GCP, Data Visualization, AWS",Bachelor,6,Gaming,2025-01-27,2025-03-15,2282,5.1,Autonomous Tech -AI13411,AI Architect,146850,USD,146850,SE,PT,Finland,L,Finland,100,"Mathematics, PyTorch, Hadoop, Spark, TensorFlow",Master,8,Automotive,2024-04-28,2024-05-15,1904,7.5,Autonomous Tech -AI13412,Robotics Engineer,67285,JPY,7401350,EN,CT,Japan,M,Egypt,100,"NLP, Deep Learning, Hadoop, Computer Vision",Associate,0,Energy,2024-06-10,2024-07-11,1776,9.8,Future Systems -AI13413,Data Scientist,287563,USD,287563,EX,FL,United States,M,Spain,50,"Python, TensorFlow, Git, Hadoop",PhD,10,Energy,2024-10-21,2024-12-06,1959,5.3,DataVision Ltd -AI13414,Data Analyst,86376,USD,86376,MI,FT,Israel,L,Israel,50,"TensorFlow, Data Visualization, Statistics",Associate,3,Telecommunications,2024-04-21,2024-06-24,821,5.2,Digital Transformation LLC -AI13415,Data Engineer,78208,USD,78208,SE,FL,South Korea,S,South Korea,50,"GCP, PyTorch, NLP, MLOps, Java",Bachelor,7,Government,2024-06-13,2024-08-21,2037,6.7,Predictive Systems -AI13416,AI Research Scientist,83692,USD,83692,MI,CT,United States,S,Poland,100,"Git, Tableau, Data Visualization, Kubernetes",Master,2,Real Estate,2024-03-31,2024-05-15,1315,8.6,Autonomous Tech -AI13417,Robotics Engineer,143315,USD,143315,EX,FT,Ireland,M,Ireland,100,"Linux, Data Visualization, Docker",Associate,16,Healthcare,2024-10-09,2024-10-29,1430,8.1,Cognitive Computing -AI13418,AI Architect,75949,AUD,102531,EN,FL,Australia,L,Australia,0,"R, PyTorch, Docker",Bachelor,0,Technology,2024-11-21,2025-01-14,1323,5.7,Smart Analytics -AI13419,AI Architect,124751,EUR,106038,SE,FL,France,M,France,50,"Python, TensorFlow, Data Visualization, Hadoop",PhD,7,Healthcare,2024-10-23,2024-12-08,866,5.4,AI Innovations -AI13420,NLP Engineer,189998,EUR,161498,EX,FT,Netherlands,L,Ghana,50,"Kubernetes, SQL, Data Visualization, MLOps, PyTorch",Associate,17,Real Estate,2024-08-31,2024-09-23,1284,6.9,Advanced Robotics -AI13421,Data Engineer,193193,EUR,164214,EX,CT,France,L,France,50,"Linux, Azure, SQL, R, Java",Associate,14,Healthcare,2024-06-21,2024-07-10,1148,8.1,Digital Transformation LLC -AI13422,AI Consultant,180069,SGD,234090,EX,PT,Singapore,L,Singapore,50,"PyTorch, GCP, Hadoop",Master,11,Consulting,2024-09-29,2024-11-16,2011,7.2,Digital Transformation LLC -AI13423,Deep Learning Engineer,202205,USD,202205,EX,FT,Israel,L,Israel,0,"PyTorch, Spark, Python",PhD,14,Energy,2024-12-20,2025-01-21,1805,8.6,Advanced Robotics -AI13424,NLP Engineer,84851,USD,84851,EN,FL,Sweden,L,Sweden,50,"Kubernetes, Tableau, TensorFlow, GCP, Python",PhD,1,Gaming,2024-01-23,2024-02-26,691,7.6,Quantum Computing Inc -AI13425,Autonomous Systems Engineer,100135,GBP,75101,MI,FL,United Kingdom,S,United Kingdom,0,"Computer Vision, Scala, PyTorch, Linux",Associate,4,Retail,2024-06-22,2024-07-08,942,5.8,Smart Analytics -AI13426,Principal Data Scientist,149157,EUR,126783,SE,FT,Netherlands,L,Netherlands,0,"GCP, Docker, Data Visualization, Scala",Associate,9,Energy,2024-07-08,2024-09-14,2036,5.2,Quantum Computing Inc -AI13427,Data Engineer,255277,CAD,319096,EX,CT,Canada,L,Canada,50,"Kubernetes, NLP, R, Deep Learning",Bachelor,17,Retail,2024-08-22,2024-09-28,530,5,Advanced Robotics -AI13428,NLP Engineer,118601,CHF,106741,EN,CT,Switzerland,L,Switzerland,50,"Kubernetes, Git, SQL, TensorFlow",Master,1,Government,2024-07-25,2024-09-22,2069,5.3,TechCorp Inc -AI13429,AI Specialist,204430,AUD,275981,EX,FL,Australia,M,South Africa,0,"TensorFlow, Python, NLP, AWS, Git",Bachelor,16,Gaming,2024-05-25,2024-07-13,2183,8.1,Neural Networks Co -AI13430,AI Specialist,148777,USD,148777,SE,FT,Norway,S,India,0,"Java, Linux, PyTorch, NLP, Kubernetes",Master,5,Telecommunications,2025-04-24,2025-06-11,1673,8.5,Digital Transformation LLC -AI13431,AI Software Engineer,280124,USD,280124,EX,PT,Norway,L,Turkey,50,"Tableau, Data Visualization, Java, TensorFlow",PhD,19,Automotive,2024-12-15,2025-01-22,617,5.6,Advanced Robotics -AI13432,AI Software Engineer,68849,EUR,58522,EN,PT,Germany,L,Germany,100,"MLOps, Hadoop, Spark",Master,1,Energy,2025-03-14,2025-04-03,2099,8.6,Machine Intelligence Group -AI13433,AI Research Scientist,29926,USD,29926,MI,FT,India,L,India,50,"Statistics, Azure, Spark, PyTorch, Deep Learning",Master,4,Education,2024-05-06,2024-07-01,1172,7.6,Future Systems -AI13434,ML Ops Engineer,70863,USD,70863,EN,FT,Israel,L,Israel,50,"R, MLOps, SQL",PhD,0,Manufacturing,2025-02-23,2025-04-18,1950,7.9,Quantum Computing Inc -AI13435,Research Scientist,63834,USD,63834,EN,CT,Israel,M,Israel,0,"Java, GCP, MLOps, Deep Learning",Master,0,Transportation,2024-04-30,2024-07-09,922,9.3,Digital Transformation LLC -AI13436,Deep Learning Engineer,332210,CHF,298989,EX,FT,Switzerland,M,South Africa,100,"GCP, Deep Learning, Git",PhD,15,Energy,2025-02-03,2025-03-22,2134,10,Quantum Computing Inc -AI13437,AI Product Manager,67710,USD,67710,EN,PT,Denmark,S,Sweden,0,"Statistics, Linux, Data Visualization",Master,0,Manufacturing,2024-12-29,2025-02-24,1974,9.9,Future Systems -AI13438,Data Scientist,129621,EUR,110178,EX,CT,Austria,M,Argentina,0,"Git, Docker, Java, R, Hadoop",Bachelor,15,Real Estate,2024-01-25,2024-03-27,2066,9.4,Advanced Robotics -AI13439,Research Scientist,84399,USD,84399,MI,FL,Ireland,L,Switzerland,0,"AWS, MLOps, Python",Bachelor,4,Energy,2024-05-01,2024-07-01,1456,8.2,Machine Intelligence Group -AI13440,Research Scientist,140977,GBP,105733,SE,FT,United Kingdom,M,United Kingdom,100,"GCP, PyTorch, Java",PhD,9,Media,2024-07-26,2024-10-04,1604,7.4,TechCorp Inc -AI13441,Research Scientist,130649,CHF,117584,EN,CT,Switzerland,L,Switzerland,0,"Spark, Deep Learning, Python, Computer Vision",PhD,0,Retail,2024-04-03,2024-05-07,1426,5.7,Machine Intelligence Group -AI13442,AI Product Manager,94972,EUR,80726,MI,PT,France,L,New Zealand,100,"SQL, MLOps, Computer Vision, Linux, GCP",Bachelor,4,Consulting,2024-05-18,2024-06-12,1705,7.4,Predictive Systems -AI13443,AI Specialist,176030,EUR,149626,EX,PT,Austria,S,Finland,50,"Git, Scala, AWS",Master,18,Real Estate,2024-04-14,2024-06-13,1595,7.6,DeepTech Ventures -AI13444,Research Scientist,101314,USD,101314,SE,PT,Israel,M,Israel,100,"Linux, Spark, Computer Vision, MLOps, Python",PhD,9,Telecommunications,2024-10-10,2024-11-28,1405,6,Cloud AI Solutions -AI13445,AI Consultant,59806,EUR,50835,EN,PT,Germany,S,Germany,0,"Docker, Scala, Statistics",Associate,1,Consulting,2025-01-08,2025-01-24,965,6.3,Neural Networks Co -AI13446,Data Analyst,106748,USD,106748,SE,PT,Israel,S,Netherlands,100,"Scala, Python, Computer Vision, Tableau",Bachelor,5,Education,2024-04-23,2024-06-05,1187,7.4,TechCorp Inc -AI13447,Autonomous Systems Engineer,49405,CAD,61756,EN,PT,Canada,M,Canada,0,"Linux, Python, Tableau",PhD,0,Automotive,2025-01-10,2025-02-22,2350,5,Digital Transformation LLC -AI13448,Data Scientist,230116,SGD,299151,EX,PT,Singapore,L,Turkey,100,"Python, Java, Computer Vision, TensorFlow, GCP",Bachelor,18,Energy,2024-12-25,2025-02-15,1605,8,Autonomous Tech -AI13449,AI Specialist,155786,EUR,132418,SE,FL,Netherlands,M,United States,50,"NLP, SQL, MLOps",Bachelor,8,Education,2024-01-02,2024-01-26,1425,8.5,AI Innovations -AI13450,Data Scientist,78295,EUR,66551,MI,PT,Germany,M,Germany,0,"Scala, Python, Tableau, NLP, MLOps",Master,4,Technology,2024-08-02,2024-08-31,2422,6.2,Machine Intelligence Group -AI13451,ML Ops Engineer,116184,USD,116184,MI,CT,Ireland,L,Czech Republic,0,"SQL, MLOps, TensorFlow, Git, Data Visualization",PhD,4,Gaming,2024-03-22,2024-05-06,1048,8.4,DeepTech Ventures -AI13452,Machine Learning Engineer,70480,USD,70480,EN,FT,United States,S,United States,50,"Mathematics, Statistics, TensorFlow, PyTorch",Master,1,Media,2024-02-26,2024-03-24,1238,9.2,Quantum Computing Inc -AI13453,Machine Learning Engineer,257142,EUR,218571,EX,FL,France,L,South Korea,50,"Python, Kubernetes, GCP, R",PhD,10,Retail,2024-04-19,2024-05-06,2218,9.8,Advanced Robotics -AI13454,Head of AI,75895,CHF,68306,EN,PT,Switzerland,M,Spain,0,"Hadoop, AWS, Tableau",PhD,0,Energy,2024-10-11,2024-11-27,1842,7.3,DataVision Ltd -AI13455,Autonomous Systems Engineer,130146,JPY,14316060,MI,FL,Japan,L,Japan,0,"GCP, Docker, MLOps, Tableau, Hadoop",Bachelor,2,Telecommunications,2024-09-28,2024-10-18,2259,6.4,Quantum Computing Inc -AI13456,Head of AI,62607,USD,62607,SE,PT,China,S,China,0,"Spark, R, Linux, SQL",Bachelor,9,Media,2024-08-08,2024-10-04,2050,5.1,DataVision Ltd -AI13457,AI Specialist,213739,USD,213739,SE,CT,Denmark,L,Denmark,50,"SQL, Scala, Data Visualization, Linux, AWS",Associate,5,Energy,2024-03-28,2024-06-04,561,5.3,AI Innovations -AI13458,Research Scientist,239862,AUD,323814,EX,CT,Australia,L,Australia,50,"GCP, Hadoop, R",Bachelor,18,Government,2024-06-03,2024-07-22,713,5.4,AI Innovations -AI13459,Deep Learning Engineer,85775,EUR,72909,EN,FT,Austria,L,Colombia,50,"Spark, Data Visualization, Hadoop, Docker",Master,0,Retail,2024-06-15,2024-07-07,1378,6.3,Cognitive Computing -AI13460,Head of AI,52732,CAD,65915,EN,FL,Canada,M,Canada,100,"GCP, TensorFlow, Python, NLP",Bachelor,1,Finance,2025-02-04,2025-03-01,2406,6.5,AI Innovations -AI13461,Data Scientist,134420,SGD,174746,SE,FT,Singapore,M,Singapore,100,"Hadoop, SQL, Kubernetes",Bachelor,8,Education,2025-01-17,2025-03-06,1438,8.8,Quantum Computing Inc -AI13462,Robotics Engineer,261477,CHF,235329,EX,PT,Switzerland,S,Switzerland,100,"Deep Learning, Python, GCP",Associate,12,Retail,2024-10-29,2024-12-02,1127,7,Cognitive Computing -AI13463,AI Consultant,163591,CHF,147232,SE,CT,Switzerland,M,Switzerland,100,"SQL, Hadoop, Scala, Deep Learning",Bachelor,9,Telecommunications,2024-09-24,2024-10-20,1728,8.4,Quantum Computing Inc -AI13464,AI Architect,140181,AUD,189244,SE,PT,Australia,M,Chile,0,"Azure, Tableau, Linux, Docker",Bachelor,9,Media,2024-03-23,2024-05-13,2319,6.6,Autonomous Tech -AI13465,Deep Learning Engineer,142202,AUD,191973,SE,PT,Australia,M,Australia,100,"Deep Learning, PyTorch, TensorFlow, Statistics",Master,6,Real Estate,2024-03-20,2024-05-09,1741,9.8,Predictive Systems -AI13466,Research Scientist,157835,GBP,118376,EX,CT,United Kingdom,S,Italy,50,"GCP, AWS, Linux, Deep Learning, SQL",Master,16,Consulting,2024-02-25,2024-04-11,620,9.3,Cognitive Computing -AI13467,Deep Learning Engineer,186913,USD,186913,SE,FL,United States,L,United States,50,"TensorFlow, GCP, Deep Learning",Associate,8,Government,2024-02-04,2024-04-08,1879,9.4,Predictive Systems -AI13468,Machine Learning Engineer,133440,USD,133440,SE,FT,Sweden,S,Sweden,0,"Hadoop, Scala, Kubernetes, Mathematics, Python",Bachelor,9,Telecommunications,2025-03-15,2025-04-21,1873,5.5,DeepTech Ventures -AI13469,Robotics Engineer,138149,USD,138149,EX,CT,Ireland,S,New Zealand,50,"Deep Learning, Kubernetes, Computer Vision",PhD,10,Technology,2024-03-27,2024-05-11,617,6.3,AI Innovations -AI13470,Principal Data Scientist,130691,EUR,111087,SE,FL,Austria,L,Austria,0,"Kubernetes, Deep Learning, Java, AWS, Computer Vision",PhD,9,Media,2024-09-13,2024-10-24,1605,5.8,Machine Intelligence Group -AI13471,AI Research Scientist,87469,USD,87469,MI,PT,Israel,M,Israel,100,"Hadoop, SQL, Tableau, Azure, Kubernetes",Master,3,Government,2024-10-23,2024-11-28,2305,9.2,TechCorp Inc -AI13472,AI Specialist,106777,GBP,80083,MI,FL,United Kingdom,L,United Kingdom,0,"Deep Learning, SQL, Spark",PhD,3,Finance,2024-12-08,2024-12-26,1723,10,Neural Networks Co -AI13473,NLP Engineer,50461,USD,50461,SE,PT,China,M,China,100,"Data Visualization, Hadoop, Computer Vision",Associate,7,Finance,2024-04-01,2024-05-03,2354,5.8,Algorithmic Solutions -AI13474,Computer Vision Engineer,159609,EUR,135668,EX,FL,Austria,M,Indonesia,0,"Python, Git, TensorFlow",Associate,11,Consulting,2024-03-14,2024-03-29,1071,8.5,Predictive Systems -AI13475,Machine Learning Researcher,154149,EUR,131027,EX,PT,France,M,France,0,"Python, SQL, Linux, GCP",Master,18,Manufacturing,2024-07-14,2024-09-09,1775,8.5,Autonomous Tech -AI13476,AI Software Engineer,64819,GBP,48614,EN,FL,United Kingdom,L,United Kingdom,100,"Scala, PyTorch, Azure",Associate,1,Consulting,2024-05-16,2024-07-22,2036,5.7,TechCorp Inc -AI13477,Principal Data Scientist,125314,SGD,162908,MI,FL,Singapore,L,Singapore,100,"AWS, Azure, Spark, Computer Vision",Bachelor,2,Manufacturing,2024-11-03,2024-11-17,2038,9.1,Algorithmic Solutions -AI13478,AI Specialist,55051,USD,55051,EN,PT,Israel,S,Australia,100,"Scala, SQL, Azure",PhD,0,Technology,2024-11-01,2024-12-01,1137,7.1,Algorithmic Solutions -AI13479,AI Specialist,32595,USD,32595,MI,FT,India,L,India,100,"Hadoop, Java, NLP",Associate,4,Media,2024-04-13,2024-05-19,548,9.6,Digital Transformation LLC -AI13480,AI Architect,71110,EUR,60444,MI,FL,Netherlands,S,Belgium,100,"Git, R, TensorFlow",PhD,2,Finance,2024-06-25,2024-09-04,2334,7.8,Cognitive Computing -AI13481,AI Software Engineer,169547,JPY,18650170,EX,PT,Japan,S,Japan,100,"NLP, GCP, Tableau, PyTorch",Master,18,Finance,2024-03-09,2024-05-04,848,5.8,Algorithmic Solutions -AI13482,ML Ops Engineer,178084,CHF,160276,SE,CT,Switzerland,S,Switzerland,100,"Python, TensorFlow, AWS",Master,8,Real Estate,2025-03-29,2025-05-13,1319,8.4,Autonomous Tech -AI13483,AI Architect,62829,GBP,47122,EN,FL,United Kingdom,S,Romania,50,"NLP, Hadoop, Scala, SQL, GCP",PhD,1,Finance,2025-01-03,2025-01-24,1496,5.4,Neural Networks Co -AI13484,AI Research Scientist,159514,USD,159514,EX,CT,South Korea,M,South Korea,50,"Python, NLP, Mathematics, Git",Associate,17,Healthcare,2025-02-06,2025-04-13,2270,6.4,AI Innovations -AI13485,AI Architect,127374,USD,127374,MI,PT,Norway,S,Chile,50,"Python, MLOps, NLP, Linux, AWS",PhD,2,Finance,2024-04-24,2024-05-13,2290,6.2,Quantum Computing Inc -AI13486,ML Ops Engineer,123377,USD,123377,MI,FT,Sweden,L,Ireland,100,"Hadoop, Scala, Mathematics, Linux",Master,2,Automotive,2024-10-31,2024-12-05,603,5.5,TechCorp Inc -AI13487,AI Product Manager,131293,JPY,14442230,SE,CT,Japan,M,Japan,0,"Deep Learning, AWS, Python, Mathematics, Hadoop",Master,5,Retail,2024-06-16,2024-08-22,760,8,AI Innovations -AI13488,Data Engineer,69197,EUR,58817,EN,PT,Germany,M,Germany,50,"SQL, Docker, MLOps, Hadoop",Associate,0,Energy,2025-02-20,2025-03-25,1451,7.2,Advanced Robotics -AI13489,ML Ops Engineer,96379,EUR,81922,MI,FL,France,M,Argentina,100,"Tableau, Computer Vision, Docker",Associate,3,Transportation,2024-04-06,2024-06-07,557,7.9,Autonomous Tech -AI13490,Robotics Engineer,57105,USD,57105,EN,CT,Israel,L,Spain,50,"R, Tableau, SQL, Deep Learning",Associate,1,Media,2024-10-16,2024-12-07,2426,6.8,Machine Intelligence Group -AI13491,AI Consultant,41328,USD,41328,MI,FL,China,M,New Zealand,50,"Docker, SQL, Azure, Python, Mathematics",Master,2,Government,2024-02-10,2024-02-27,576,9.9,Machine Intelligence Group -AI13492,Data Scientist,119623,USD,119623,MI,CT,Denmark,L,Denmark,0,"Python, TensorFlow, Deep Learning, SQL",Bachelor,2,Technology,2025-04-29,2025-06-22,1740,6.8,DataVision Ltd -AI13493,Robotics Engineer,158417,USD,158417,EX,PT,Ireland,M,Ireland,50,"Python, Azure, TensorFlow",Associate,10,Technology,2025-01-18,2025-03-01,2083,8,Autonomous Tech -AI13494,Data Scientist,82345,AUD,111166,MI,FT,Australia,S,Australia,100,"Deep Learning, Tableau, Statistics",Bachelor,4,Gaming,2025-04-15,2025-05-22,2475,5.6,DataVision Ltd -AI13495,Computer Vision Engineer,28336,USD,28336,EN,CT,India,M,India,50,"Statistics, Mathematics, AWS",Bachelor,0,Telecommunications,2024-12-21,2025-02-04,2180,6.9,TechCorp Inc -AI13496,Computer Vision Engineer,176246,USD,176246,EX,FT,South Korea,S,South Korea,50,"Docker, Kubernetes, MLOps, Deep Learning",Bachelor,15,Retail,2025-01-16,2025-03-29,1879,5.4,Smart Analytics -AI13497,NLP Engineer,47000,USD,47000,SE,FL,India,S,India,100,"Python, NLP, TensorFlow, GCP",Master,7,Transportation,2025-03-26,2025-04-12,1770,8.1,AI Innovations -AI13498,ML Ops Engineer,47164,USD,47164,EN,FL,South Korea,M,South Korea,50,"Computer Vision, Deep Learning, Scala, Python",PhD,1,Media,2025-04-08,2025-05-29,2331,5.5,DataVision Ltd -AI13499,Principal Data Scientist,132818,SGD,172663,SE,CT,Singapore,M,Singapore,0,"Linux, MLOps, Scala, Data Visualization",PhD,5,Real Estate,2024-12-06,2025-01-29,1896,8.9,Neural Networks Co -AI13500,AI Specialist,85866,EUR,72986,MI,CT,Germany,L,Germany,100,"PyTorch, Deep Learning, Kubernetes, AWS, Computer Vision",PhD,3,Media,2024-11-23,2025-01-19,2172,8,Neural Networks Co -AI13501,NLP Engineer,92368,EUR,78513,SE,FL,Germany,S,Germany,100,"AWS, Linux, Spark",Master,8,Automotive,2024-06-05,2024-06-25,1291,6.5,Autonomous Tech -AI13502,Computer Vision Engineer,100531,USD,100531,SE,PT,South Korea,L,South Korea,0,"SQL, Docker, Python, MLOps",Associate,6,Consulting,2024-07-17,2024-08-12,988,6.4,Algorithmic Solutions -AI13503,Data Analyst,87818,USD,87818,MI,PT,Finland,S,Argentina,50,"Kubernetes, Azure, Java, Data Visualization, GCP",Associate,3,Energy,2025-04-15,2025-06-10,1287,9.1,Digital Transformation LLC -AI13504,Robotics Engineer,214112,AUD,289051,EX,CT,Australia,S,Australia,100,"Python, Mathematics, Hadoop, Scala, Azure",PhD,16,Telecommunications,2025-03-02,2025-03-24,1204,7.7,Future Systems -AI13505,Data Engineer,137081,JPY,15078910,SE,FL,Japan,L,Switzerland,100,"Tableau, Python, Scala, Spark",Bachelor,7,Automotive,2024-01-28,2024-03-22,1876,5.3,DataVision Ltd -AI13506,Data Analyst,53421,USD,53421,SE,PT,India,M,India,0,"Kubernetes, Git, NLP, TensorFlow, PyTorch",Associate,8,Healthcare,2024-08-02,2024-09-04,931,5.6,Autonomous Tech -AI13507,AI Architect,75794,GBP,56846,EN,CT,United Kingdom,L,United Kingdom,0,"SQL, Docker, Spark, Computer Vision, PyTorch",Associate,0,Gaming,2025-03-24,2025-04-24,1153,6.2,Cognitive Computing -AI13508,NLP Engineer,175103,EUR,148838,EX,CT,Austria,L,Austria,50,"Java, Scala, GCP",PhD,17,Telecommunications,2024-06-03,2024-07-02,1294,5.3,Neural Networks Co -AI13509,ML Ops Engineer,175669,CHF,158102,SE,FL,Switzerland,S,Switzerland,100,"TensorFlow, Git, SQL",PhD,6,Media,2024-08-29,2024-09-28,1991,7.7,Autonomous Tech -AI13510,AI Architect,152942,USD,152942,EX,CT,Israel,L,Israel,0,"Kubernetes, Java, Git",PhD,14,Transportation,2024-10-04,2024-10-25,2411,8.4,Future Systems -AI13511,AI Architect,115652,USD,115652,MI,PT,Finland,L,Finland,100,"Linux, SQL, PyTorch, GCP, TensorFlow",Master,4,Gaming,2025-04-16,2025-05-09,691,5.9,Cognitive Computing -AI13512,AI Product Manager,254643,EUR,216447,EX,CT,Netherlands,L,Netherlands,0,"Hadoop, Statistics, Linux, Data Visualization",Associate,17,Gaming,2024-03-05,2024-05-17,1152,6.3,Autonomous Tech -AI13513,Machine Learning Researcher,113576,EUR,96540,MI,PT,Germany,L,Latvia,0,"SQL, Linux, R, Hadoop, Computer Vision",Master,4,Media,2024-10-20,2024-11-21,1737,7.2,Smart Analytics -AI13514,Data Engineer,82775,USD,82775,EN,FL,Norway,M,Norway,100,"Mathematics, R, Docker, Spark, SQL",PhD,1,Telecommunications,2024-02-14,2024-03-18,1834,9.4,Quantum Computing Inc -AI13515,AI Architect,166158,USD,166158,SE,PT,Norway,S,Norway,100,"Java, MLOps, NLP, Git, Mathematics",PhD,5,Transportation,2024-11-05,2024-12-28,604,9.8,AI Innovations -AI13516,Computer Vision Engineer,128965,USD,128965,MI,FT,United States,L,United States,0,"GCP, TensorFlow, Mathematics, Computer Vision, AWS",PhD,4,Consulting,2024-10-04,2024-11-27,871,8,Autonomous Tech -AI13517,Data Scientist,117391,USD,117391,SE,CT,South Korea,M,South Korea,50,"Spark, TensorFlow, GCP",Associate,9,Telecommunications,2024-11-06,2025-01-14,1903,8.8,Autonomous Tech -AI13518,Data Analyst,270558,USD,270558,EX,FL,Norway,S,Norway,0,"GCP, Python, MLOps, Tableau, Kubernetes",Master,17,Media,2025-01-07,2025-03-07,2124,9.3,Neural Networks Co -AI13519,Data Engineer,190549,CAD,238186,EX,FL,Canada,S,Spain,50,"Python, Git, MLOps",Bachelor,10,Education,2024-08-18,2024-10-22,1395,6.6,AI Innovations -AI13520,Computer Vision Engineer,53483,USD,53483,EN,CT,South Korea,S,Thailand,0,"Python, Deep Learning, SQL",Bachelor,1,Gaming,2024-04-20,2024-06-01,1095,6.2,DataVision Ltd -AI13521,Computer Vision Engineer,119338,USD,119338,SE,FT,United States,S,Kenya,50,"TensorFlow, R, MLOps, Java, AWS",PhD,6,Gaming,2024-09-06,2024-11-05,2370,6.9,Cloud AI Solutions -AI13522,AI Architect,66333,USD,66333,MI,PT,South Korea,S,Thailand,100,"Statistics, Hadoop, Tableau, GCP",PhD,4,Education,2024-10-09,2024-11-12,1271,7.9,Predictive Systems -AI13523,Machine Learning Researcher,102503,GBP,76877,MI,CT,United Kingdom,M,United Kingdom,0,"Hadoop, Scala, Docker, Java, Deep Learning",Master,4,Media,2024-01-23,2024-03-11,1799,6.3,Cloud AI Solutions -AI13524,AI Architect,135092,USD,135092,SE,CT,Finland,M,Finland,0,"Scala, SQL, PyTorch, Spark",Bachelor,8,Healthcare,2024-11-29,2024-12-25,2206,5.5,Cloud AI Solutions -AI13525,Machine Learning Engineer,102919,USD,102919,SE,CT,South Korea,S,South Korea,100,"GCP, Python, Java, Docker",PhD,5,Government,2024-06-09,2024-08-01,897,9.4,Cognitive Computing -AI13526,Principal Data Scientist,135359,SGD,175967,SE,CT,Singapore,M,Singapore,100,"TensorFlow, SQL, GCP, Java, Statistics",Bachelor,9,Transportation,2024-12-16,2025-02-11,1370,6.7,AI Innovations -AI13527,Machine Learning Engineer,125939,USD,125939,MI,CT,Norway,L,Norway,50,"Mathematics, Linux, Hadoop, TensorFlow",PhD,2,Retail,2025-01-19,2025-03-22,674,6.3,Autonomous Tech -AI13528,Research Scientist,187712,CHF,168941,SE,CT,Switzerland,S,Switzerland,0,"MLOps, R, Azure",Associate,8,Retail,2024-10-31,2024-12-06,1040,8,Advanced Robotics -AI13529,AI Research Scientist,243121,SGD,316057,EX,PT,Singapore,M,Singapore,50,"Java, SQL, Data Visualization",Associate,11,Transportation,2024-01-06,2024-03-04,716,5.8,AI Innovations -AI13530,AI Software Engineer,53273,USD,53273,SE,FT,India,M,India,50,"Python, Statistics, Hadoop, TensorFlow",PhD,6,Government,2024-12-27,2025-02-09,2149,7.2,Neural Networks Co -AI13531,Data Analyst,34231,USD,34231,EN,PT,China,L,China,0,"Kubernetes, Python, Git",Master,0,Education,2024-01-25,2024-03-09,2443,8.8,Algorithmic Solutions -AI13532,Research Scientist,64663,GBP,48497,EN,FT,United Kingdom,S,United Kingdom,0,"MLOps, Azure, TensorFlow, Deep Learning, Python",PhD,1,Manufacturing,2024-12-11,2025-02-16,2320,7.7,Cognitive Computing -AI13533,Robotics Engineer,145887,CHF,131298,SE,FL,Switzerland,S,Switzerland,50,"Deep Learning, SQL, PyTorch, Linux",Associate,7,Manufacturing,2024-12-23,2025-01-08,2106,6,Quantum Computing Inc -AI13534,Robotics Engineer,225404,GBP,169053,EX,FL,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning",Master,16,Technology,2025-03-07,2025-03-31,1137,8.3,Future Systems -AI13535,Machine Learning Researcher,118211,USD,118211,SE,FL,South Korea,M,South Korea,0,"Spark, GCP, SQL, MLOps",Master,5,Healthcare,2024-04-01,2024-05-24,817,8,DeepTech Ventures -AI13536,AI Product Manager,121319,USD,121319,MI,CT,Norway,M,Romania,50,"R, Tableau, Java, Git, Computer Vision",Associate,4,Consulting,2024-03-10,2024-05-14,737,7.2,Autonomous Tech -AI13537,Robotics Engineer,83754,JPY,9212940,MI,FL,Japan,S,Denmark,50,"Computer Vision, Kubernetes, Deep Learning",Bachelor,4,Manufacturing,2024-08-23,2024-10-25,2217,8.4,Neural Networks Co -AI13538,Head of AI,41420,USD,41420,SE,CT,India,M,India,100,"Java, Azure, MLOps, Hadoop, Spark",PhD,7,Retail,2024-03-24,2024-04-13,511,8.4,Advanced Robotics -AI13539,ML Ops Engineer,167184,USD,167184,SE,CT,Denmark,L,Nigeria,50,"Computer Vision, SQL, Python, Azure",Associate,7,Energy,2025-04-05,2025-05-14,1470,5.7,TechCorp Inc -AI13540,Data Engineer,79973,USD,79973,EN,FL,Norway,S,Norway,0,"Scala, Kubernetes, PyTorch",Associate,0,Retail,2024-02-29,2024-04-20,1710,7.4,DataVision Ltd -AI13541,Machine Learning Engineer,215068,USD,215068,SE,CT,Norway,L,Norway,50,"Python, TensorFlow, Computer Vision, Git, Linux",Master,5,Manufacturing,2024-07-15,2024-09-14,1303,9.2,Cloud AI Solutions -AI13542,AI Research Scientist,61811,USD,61811,EN,FT,Israel,S,Estonia,0,"Python, Tableau, Kubernetes",Master,0,Media,2025-02-18,2025-04-21,1234,8.9,DeepTech Ventures -AI13543,AI Architect,105290,SGD,136877,SE,FL,Singapore,S,Singapore,0,"SQL, Spark, Scala, Git, Azure",Associate,6,Telecommunications,2025-03-12,2025-05-21,1211,5.4,Quantum Computing Inc -AI13544,AI Consultant,87480,SGD,113724,MI,FL,Singapore,M,Singapore,100,"SQL, Tableau, Spark, PyTorch",Associate,3,Education,2024-12-24,2025-01-25,1963,7.2,Advanced Robotics -AI13545,Computer Vision Engineer,100005,CAD,125006,MI,FL,Canada,M,Romania,0,"Computer Vision, R, Linux, PyTorch, Git",PhD,3,Education,2024-11-14,2024-12-19,1834,6.6,Cognitive Computing -AI13546,Robotics Engineer,162358,CHF,146122,MI,CT,Switzerland,L,Switzerland,50,"SQL, Python, Tableau, MLOps, Spark",Bachelor,3,Finance,2024-01-23,2024-03-14,504,9.3,AI Innovations -AI13547,Machine Learning Researcher,158769,USD,158769,EX,FL,South Korea,S,Ireland,0,"MLOps, NLP, R, Python, Tableau",Associate,10,Government,2025-02-24,2025-03-31,1856,9,Cognitive Computing -AI13548,Machine Learning Engineer,231743,EUR,196982,EX,CT,Netherlands,S,Netherlands,100,"SQL, Scala, Docker, Mathematics, Computer Vision",Associate,12,Healthcare,2025-04-04,2025-05-12,1675,8.3,Advanced Robotics -AI13549,Robotics Engineer,198048,EUR,168341,EX,FL,Germany,L,Germany,100,"Java, MLOps, Git, Spark, Scala",PhD,14,Retail,2025-02-17,2025-04-30,2389,7.9,Neural Networks Co -AI13550,Computer Vision Engineer,170409,USD,170409,SE,FT,Norway,M,Norway,50,"Python, Data Visualization, PyTorch, Tableau, AWS",Bachelor,8,Technology,2024-03-22,2024-05-18,1565,8.9,Predictive Systems -AI13551,Data Scientist,137317,JPY,15104870,SE,FT,Japan,M,Japan,100,"Kubernetes, Spark, GCP, Python, Mathematics",Master,7,Real Estate,2025-04-16,2025-06-17,506,9.5,TechCorp Inc -AI13552,Data Analyst,215252,USD,215252,EX,FT,Norway,L,Norway,50,"Spark, Python, Data Visualization",PhD,16,Government,2025-03-02,2025-05-08,1376,7.6,DeepTech Ventures -AI13553,NLP Engineer,115357,AUD,155732,SE,PT,Australia,S,Colombia,100,"R, Kubernetes, SQL, Hadoop, Statistics",Master,6,Education,2025-02-13,2025-03-17,737,7.6,Smart Analytics -AI13554,NLP Engineer,78765,EUR,66950,MI,CT,Netherlands,M,Netherlands,100,"TensorFlow, Hadoop, Scala",Associate,2,Gaming,2025-01-01,2025-03-11,1847,6.3,Autonomous Tech -AI13555,Deep Learning Engineer,111065,CHF,99959,EN,CT,Switzerland,M,Switzerland,50,"Git, NLP, Scala, Computer Vision",Bachelor,0,Gaming,2024-02-06,2024-03-28,1593,7.4,Machine Intelligence Group -AI13556,Data Scientist,79550,USD,79550,SE,PT,China,L,China,100,"Tableau, Data Visualization, AWS",Associate,8,Government,2024-05-13,2024-07-24,2221,5.3,TechCorp Inc -AI13557,Data Analyst,155394,USD,155394,EX,PT,South Korea,S,New Zealand,50,"R, Tableau, Computer Vision",Associate,12,Healthcare,2025-01-03,2025-02-28,2068,7.5,Advanced Robotics -AI13558,Deep Learning Engineer,92899,USD,92899,MI,FL,Israel,L,Israel,100,"Java, MLOps, AWS",Bachelor,4,Manufacturing,2024-09-14,2024-10-24,1009,9.6,Digital Transformation LLC -AI13559,Data Engineer,94215,GBP,70661,MI,CT,United Kingdom,S,Argentina,50,"NLP, Mathematics, Kubernetes, MLOps",Bachelor,3,Technology,2024-12-30,2025-03-07,1513,8.3,Quantum Computing Inc -AI13560,Robotics Engineer,80817,AUD,109103,MI,PT,Australia,M,Nigeria,50,"Computer Vision, Linux, MLOps",PhD,3,Gaming,2024-09-29,2024-10-14,1084,8.4,DeepTech Ventures -AI13561,Machine Learning Researcher,142421,EUR,121058,EX,FT,Austria,S,Austria,100,"Spark, Scala, Deep Learning, TensorFlow, Azure",Associate,16,Healthcare,2024-07-13,2024-09-16,1113,5.2,Neural Networks Co -AI13562,AI Software Engineer,162016,SGD,210621,EX,FL,Singapore,M,France,50,"NLP, Python, TensorFlow, Spark",Bachelor,10,Gaming,2025-02-15,2025-03-29,2037,9,Quantum Computing Inc -AI13563,AI Specialist,240723,USD,240723,EX,CT,Ireland,M,Ireland,100,"Computer Vision, AWS, Kubernetes, Data Visualization, Git",PhD,17,Consulting,2024-02-07,2024-04-13,624,7.6,Cloud AI Solutions -AI13564,Computer Vision Engineer,177202,USD,177202,EX,FT,Denmark,M,United States,0,"Kubernetes, R, SQL, Java",Associate,11,Telecommunications,2025-01-09,2025-02-20,713,9.7,Digital Transformation LLC -AI13565,AI Software Engineer,19994,USD,19994,EN,PT,India,S,India,0,"Deep Learning, Mathematics, Scala",Associate,1,Consulting,2024-12-07,2025-01-07,1936,6.2,AI Innovations -AI13566,Research Scientist,87827,GBP,65870,MI,CT,United Kingdom,M,China,100,"Scala, R, AWS",Bachelor,4,Government,2025-03-13,2025-05-19,859,5.3,Digital Transformation LLC -AI13567,Data Engineer,246485,SGD,320431,EX,CT,Singapore,L,Singapore,50,"Kubernetes, Azure, Deep Learning, R",PhD,17,Real Estate,2025-01-02,2025-03-16,561,9,TechCorp Inc -AI13568,AI Architect,185718,JPY,20428980,EX,FL,Japan,S,Japan,50,"Scala, R, SQL, GCP, Mathematics",Associate,12,Technology,2024-01-31,2024-02-25,2094,7.8,Digital Transformation LLC -AI13569,AI Consultant,80076,USD,80076,SE,FT,China,L,Portugal,100,"Docker, Java, Statistics, Git",PhD,9,Manufacturing,2024-01-15,2024-02-12,1429,8.4,Advanced Robotics -AI13570,AI Software Engineer,184303,GBP,138227,SE,FL,United Kingdom,L,Mexico,0,"Python, Deep Learning, TensorFlow, Computer Vision, Kubernetes",Associate,5,Gaming,2024-10-28,2025-01-07,1685,6.5,TechCorp Inc -AI13571,Computer Vision Engineer,144334,CAD,180418,EX,CT,Canada,S,Canada,50,"Data Visualization, Java, Deep Learning",Associate,10,Government,2024-08-16,2024-10-01,1155,5.5,DeepTech Ventures -AI13572,Principal Data Scientist,136225,EUR,115791,SE,CT,Austria,L,Austria,50,"Python, Data Visualization, Kubernetes, MLOps",Associate,9,Energy,2025-01-05,2025-03-08,1676,8.4,Smart Analytics -AI13573,Machine Learning Researcher,132186,USD,132186,SE,CT,Finland,M,Finland,100,"Java, NLP, AWS, Statistics",Associate,7,Manufacturing,2025-01-30,2025-03-03,1939,5.3,Advanced Robotics -AI13574,Deep Learning Engineer,125855,USD,125855,MI,CT,Sweden,L,Sweden,50,"R, TensorFlow, Kubernetes",Bachelor,3,Media,2024-12-21,2025-01-05,1426,9.5,Machine Intelligence Group -AI13575,Head of AI,56288,USD,56288,EN,FT,South Korea,S,South Korea,100,"Data Visualization, Java, Scala, Python, TensorFlow",PhD,0,Retail,2024-10-27,2024-12-20,2134,9.3,DataVision Ltd -AI13576,Data Scientist,249001,EUR,211651,EX,CT,Austria,L,Austria,0,"Tableau, Kubernetes, TensorFlow, Scala, AWS",Master,12,Telecommunications,2024-09-17,2024-11-26,1570,6.3,Predictive Systems -AI13577,Principal Data Scientist,132994,EUR,113045,EX,PT,Netherlands,S,Netherlands,100,"R, Computer Vision, NLP",Master,13,Healthcare,2025-04-22,2025-07-02,2196,8.9,TechCorp Inc -AI13578,AI Architect,108206,AUD,146078,MI,PT,Australia,M,Australia,50,"Tableau, Mathematics, Data Visualization, Python, Spark",Associate,2,Consulting,2024-06-30,2024-07-18,579,8.4,Quantum Computing Inc -AI13579,AI Consultant,55261,GBP,41446,EN,CT,United Kingdom,M,United Kingdom,100,"Python, Java, PyTorch",PhD,1,Telecommunications,2024-11-09,2024-12-14,831,5.7,Smart Analytics -AI13580,Head of AI,212757,EUR,180843,EX,FL,France,S,France,50,"Spark, Tableau, Scala, Linux",Master,10,Manufacturing,2024-05-19,2024-07-09,2126,7.6,Machine Intelligence Group -AI13581,Principal Data Scientist,115527,USD,115527,MI,PT,Denmark,S,United States,50,"SQL, Git, NLP, GCP, PyTorch",Associate,4,Education,2024-03-10,2024-05-20,785,5.8,Digital Transformation LLC -AI13582,Research Scientist,90576,USD,90576,EX,FT,China,S,Spain,50,"Linux, Hadoop, GCP",Associate,17,Telecommunications,2024-04-29,2024-07-01,652,5.8,Autonomous Tech -AI13583,NLP Engineer,68314,EUR,58067,EN,FL,Austria,S,Austria,50,"SQL, Linux, Computer Vision, Scala",Bachelor,0,Consulting,2024-02-02,2024-03-24,1389,9.8,Future Systems -AI13584,Data Analyst,80632,USD,80632,EN,FT,Norway,S,Norway,100,"Tableau, GCP, Linux",PhD,1,Media,2024-01-09,2024-02-12,845,9.2,Advanced Robotics -AI13585,Head of AI,85732,USD,85732,MI,PT,South Korea,L,South Korea,0,"Scala, MLOps, Tableau, SQL",Associate,4,Education,2024-03-17,2024-05-11,888,6.3,Digital Transformation LLC -AI13586,Machine Learning Engineer,89212,USD,89212,EN,CT,Denmark,M,Denmark,0,"TensorFlow, Data Visualization, Linux, PyTorch",Bachelor,1,Healthcare,2024-01-12,2024-02-27,2145,5.6,AI Innovations -AI13587,AI Product Manager,58528,USD,58528,SE,FL,India,L,India,50,"Hadoop, Git, PyTorch, Azure",PhD,5,Consulting,2024-10-31,2024-12-19,2079,9.9,Advanced Robotics -AI13588,Data Engineer,111013,EUR,94361,SE,PT,Netherlands,M,Mexico,100,"Scala, AWS, Java, Kubernetes, Deep Learning",Associate,5,Transportation,2025-03-11,2025-03-28,2267,9.5,Advanced Robotics -AI13589,ML Ops Engineer,161974,EUR,137678,SE,PT,France,L,Austria,0,"Statistics, R, Tableau",Bachelor,9,Finance,2024-02-26,2024-03-31,1545,6.2,Quantum Computing Inc -AI13590,AI Consultant,100290,USD,100290,MI,FT,Denmark,S,Denmark,0,"Kubernetes, Hadoop, PyTorch",Bachelor,2,Consulting,2024-04-13,2024-05-20,1342,5.8,Digital Transformation LLC -AI13591,Machine Learning Engineer,66642,USD,66642,EN,FL,Norway,M,Germany,50,"SQL, Hadoop, Tableau, Git, Scala",Associate,1,Finance,2025-02-23,2025-05-04,2080,5.4,Neural Networks Co -AI13592,Head of AI,162695,USD,162695,EX,PT,South Korea,M,Finland,0,"R, NLP, SQL",Associate,12,Government,2024-10-29,2024-12-06,2391,9.4,Smart Analytics -AI13593,AI Specialist,137077,EUR,116515,SE,FL,Austria,M,Austria,0,"Statistics, SQL, PyTorch, Deep Learning, Python",Associate,5,Transportation,2024-01-06,2024-03-17,1084,6.5,Advanced Robotics -AI13594,AI Software Engineer,132459,GBP,99344,SE,FL,United Kingdom,S,France,50,"Linux, Computer Vision, Deep Learning",Associate,8,Transportation,2024-08-25,2024-09-29,1483,5.4,AI Innovations -AI13595,Computer Vision Engineer,19457,USD,19457,EN,CT,India,S,India,0,"Scala, Kubernetes, Azure",PhD,0,Gaming,2025-04-09,2025-05-29,2272,8.1,TechCorp Inc -AI13596,Machine Learning Researcher,38912,USD,38912,MI,PT,India,L,India,50,"Mathematics, PyTorch, Python, Java, TensorFlow",PhD,2,Media,2024-10-30,2024-12-19,505,9.7,Advanced Robotics -AI13597,Data Scientist,111322,CAD,139153,MI,CT,Canada,L,Canada,100,"Docker, PyTorch, Computer Vision, AWS",Bachelor,4,Healthcare,2024-03-06,2024-05-02,1667,6.7,Machine Intelligence Group -AI13598,NLP Engineer,39729,USD,39729,MI,FL,China,S,China,100,"Python, Java, Docker",Bachelor,4,Education,2024-01-16,2024-02-08,820,7.6,Quantum Computing Inc -AI13599,Data Analyst,64601,USD,64601,EN,CT,Sweden,M,Sweden,100,"Java, MLOps, Kubernetes, Mathematics",Bachelor,1,Media,2024-09-14,2024-10-21,1542,5.8,Algorithmic Solutions -AI13600,Head of AI,199532,USD,199532,EX,PT,Ireland,S,Ireland,100,"Statistics, Hadoop, Spark",Associate,17,Finance,2024-10-17,2024-12-20,1422,9.4,Cloud AI Solutions -AI13601,ML Ops Engineer,204827,USD,204827,EX,PT,Norway,M,Malaysia,100,"MLOps, Mathematics, SQL",PhD,13,Education,2024-06-13,2024-08-11,1453,5.2,Algorithmic Solutions -AI13602,AI Software Engineer,131492,USD,131492,MI,CT,Norway,L,Norway,100,"Python, Linux, Docker, Git",PhD,3,Automotive,2025-01-26,2025-03-11,1257,5.2,Machine Intelligence Group -AI13603,Head of AI,200548,USD,200548,EX,CT,Ireland,M,Thailand,100,"SQL, NLP, PyTorch",PhD,17,Media,2024-05-22,2024-06-30,657,9,DeepTech Ventures -AI13604,Research Scientist,109537,SGD,142398,MI,PT,Singapore,L,Philippines,100,"PyTorch, Scala, NLP, Tableau",Master,3,Real Estate,2024-06-20,2024-07-08,1744,8.9,Autonomous Tech -AI13605,Deep Learning Engineer,169432,USD,169432,SE,PT,Ireland,L,Ireland,50,"Kubernetes, Python, Computer Vision",Master,6,Automotive,2024-09-12,2024-10-19,1222,6.2,Future Systems -AI13606,NLP Engineer,166233,USD,166233,EX,PT,United States,M,United States,0,"GCP, Azure, Computer Vision",Master,12,Government,2025-01-20,2025-02-05,1119,7.8,Machine Intelligence Group -AI13607,AI Consultant,67397,AUD,90986,MI,FT,Australia,S,Australia,50,"Scala, PyTorch, SQL",PhD,2,Technology,2025-03-16,2025-04-30,2214,8.1,DataVision Ltd -AI13608,AI Consultant,56703,USD,56703,SE,FT,China,S,China,0,"Git, R, Computer Vision",Bachelor,8,Manufacturing,2024-11-11,2024-12-21,2219,8.7,DeepTech Ventures -AI13609,Research Scientist,26374,USD,26374,EN,CT,China,S,China,0,"Kubernetes, Python, Scala, Deep Learning, Computer Vision",Associate,1,Government,2024-10-18,2024-11-24,575,9.3,Digital Transformation LLC -AI13610,AI Architect,45657,USD,45657,SE,CT,India,L,India,0,"Computer Vision, Deep Learning, R",Bachelor,9,Gaming,2024-01-16,2024-03-03,624,7.4,Digital Transformation LLC -AI13611,Computer Vision Engineer,39452,USD,39452,EN,CT,South Korea,S,Norway,50,"Git, NLP, Python",Associate,0,Education,2025-01-25,2025-02-28,1967,7.1,Machine Intelligence Group -AI13612,Data Analyst,123631,USD,123631,SE,PT,Sweden,S,Sweden,100,"TensorFlow, Mathematics, GCP",Bachelor,9,Healthcare,2024-02-25,2024-04-28,1819,7.7,DataVision Ltd -AI13613,ML Ops Engineer,102463,SGD,133202,MI,CT,Singapore,S,Singapore,100,"MLOps, Statistics, Scala, Data Visualization",Associate,2,Healthcare,2024-08-21,2024-09-15,799,7.2,Neural Networks Co -AI13614,Data Engineer,38458,USD,38458,MI,FT,China,M,China,100,"Azure, Computer Vision, Docker, PyTorch",Master,3,Manufacturing,2025-04-05,2025-05-30,2158,6,Autonomous Tech -AI13615,AI Software Engineer,50577,EUR,42990,EN,PT,Germany,S,Germany,50,"TensorFlow, R, Azure, AWS, NLP",Associate,0,Technology,2024-10-21,2024-12-28,1836,8.4,DeepTech Ventures -AI13616,Machine Learning Engineer,91272,AUD,123217,EN,FL,Australia,L,Malaysia,50,"Python, TensorFlow, Data Visualization",Master,0,Real Estate,2025-03-05,2025-04-03,1752,8.1,Quantum Computing Inc -AI13617,AI Software Engineer,92478,USD,92478,EN,CT,United States,L,United States,100,"Computer Vision, Statistics, MLOps",PhD,0,Automotive,2024-05-03,2024-06-24,1054,5.5,Cloud AI Solutions -AI13618,NLP Engineer,213025,USD,213025,EX,CT,Sweden,S,Sweden,100,"Python, Linux, GCP, Hadoop, PyTorch",Bachelor,10,Government,2025-02-15,2025-03-14,534,6.2,Algorithmic Solutions -AI13619,Autonomous Systems Engineer,240149,USD,240149,EX,FT,United States,L,United States,100,"SQL, GCP, Azure, NLP",PhD,15,Government,2024-10-28,2024-12-15,1242,5.9,Machine Intelligence Group -AI13620,Data Analyst,97727,EUR,83068,MI,PT,Austria,L,Austria,50,"Deep Learning, SQL, Data Visualization, PyTorch",Associate,3,Gaming,2025-04-25,2025-06-22,1949,9.7,Autonomous Tech -AI13621,Robotics Engineer,81590,CAD,101988,MI,CT,Canada,S,Netherlands,50,"Hadoop, Kubernetes, Mathematics",Associate,3,Government,2024-09-05,2024-11-03,1546,7.3,Cloud AI Solutions -AI13622,NLP Engineer,80741,AUD,109000,MI,FT,Australia,M,Colombia,100,"SQL, Python, MLOps",Bachelor,2,Technology,2024-08-29,2024-11-08,2250,7.9,DeepTech Ventures -AI13623,Head of AI,207242,USD,207242,EX,PT,Israel,S,Argentina,50,"Linux, Hadoop, Tableau",Associate,14,Manufacturing,2024-11-11,2024-12-18,2227,5.1,Cloud AI Solutions -AI13624,Principal Data Scientist,162118,USD,162118,EX,FL,Israel,S,Israel,100,"AWS, Docker, Mathematics",Associate,13,Telecommunications,2024-03-18,2024-05-07,1676,8.7,Autonomous Tech -AI13625,AI Software Engineer,95549,USD,95549,MI,FL,Israel,L,Israel,0,"Java, AWS, NLP, Tableau, Azure",Master,2,Gaming,2025-04-05,2025-06-14,1519,6.8,Advanced Robotics -AI13626,Autonomous Systems Engineer,22852,USD,22852,EN,PT,China,S,China,50,"Java, Spark, TensorFlow, Kubernetes",Master,0,Transportation,2024-11-11,2024-12-15,2127,7.1,Digital Transformation LLC -AI13627,Robotics Engineer,99707,USD,99707,EN,FT,United States,L,United States,0,"NLP, GCP, AWS, Git, Hadoop",Bachelor,1,Transportation,2024-03-02,2024-04-20,1827,5.9,Smart Analytics -AI13628,Autonomous Systems Engineer,82711,USD,82711,EN,FL,Finland,L,Finland,100,"Kubernetes, Python, Statistics, GCP, Java",Associate,1,Telecommunications,2024-03-23,2024-05-25,832,5.9,Autonomous Tech -AI13629,Data Analyst,114447,USD,114447,MI,PT,Norway,M,Norway,100,"Tableau, Linux, AWS",Associate,3,Transportation,2024-01-24,2024-02-27,2294,6.1,Predictive Systems -AI13630,Principal Data Scientist,80841,CAD,101051,MI,FL,Canada,S,Canada,50,"Hadoop, Git, MLOps, Statistics",Bachelor,3,Gaming,2025-01-10,2025-02-08,1943,7.7,DataVision Ltd -AI13631,Data Scientist,75011,USD,75011,EN,PT,Israel,L,Israel,100,"Tableau, Statistics, Computer Vision",Master,0,Transportation,2025-02-10,2025-03-21,1721,8.4,Neural Networks Co -AI13632,AI Specialist,48013,USD,48013,EX,PT,India,S,India,0,"TensorFlow, Scala, PyTorch, Statistics, Data Visualization",Bachelor,10,Healthcare,2024-03-05,2024-05-06,965,6.6,Cloud AI Solutions -AI13633,Head of AI,210553,EUR,178970,EX,CT,Germany,L,Germany,50,"Kubernetes, Scala, Data Visualization, Hadoop",Master,19,Consulting,2025-04-13,2025-05-07,956,7,Cloud AI Solutions -AI13634,Principal Data Scientist,68238,EUR,58002,EN,FT,Germany,S,Austria,100,"Kubernetes, Hadoop, PyTorch, AWS",Associate,0,Finance,2024-11-05,2025-01-16,1327,7.8,TechCorp Inc -AI13635,Autonomous Systems Engineer,211620,CHF,190458,SE,CT,Switzerland,M,Switzerland,50,"Java, Scala, SQL, Git",Bachelor,6,Telecommunications,2025-02-22,2025-04-19,709,8.4,Cloud AI Solutions -AI13636,AI Research Scientist,200684,USD,200684,EX,PT,Sweden,M,Sweden,50,"SQL, AWS, Hadoop",Associate,19,Telecommunications,2025-04-06,2025-06-08,1175,7.6,AI Innovations -AI13637,AI Software Engineer,91715,USD,91715,SE,PT,South Korea,S,Netherlands,100,"Tableau, Deep Learning, R, Python, TensorFlow",PhD,7,Education,2025-01-23,2025-02-06,1869,8.6,Neural Networks Co -AI13638,Principal Data Scientist,93185,JPY,10250350,EN,FL,Japan,L,Japan,50,"Python, AWS, Azure",Master,0,Technology,2025-04-13,2025-05-20,1885,9,AI Innovations -AI13639,Machine Learning Researcher,87268,USD,87268,EN,FT,Denmark,M,Denmark,100,"Azure, Java, SQL",Associate,1,Education,2025-01-31,2025-02-22,2387,6.9,Algorithmic Solutions -AI13640,Data Scientist,267540,CHF,240786,EX,PT,Switzerland,S,Switzerland,50,"MLOps, Tableau, Scala",Master,11,Telecommunications,2024-11-06,2024-11-29,2360,7.7,Autonomous Tech -AI13641,Data Engineer,126759,USD,126759,SE,FL,Sweden,M,Sweden,50,"Python, Docker, Data Visualization, PyTorch",Bachelor,7,Media,2024-02-08,2024-03-09,1723,6,Cognitive Computing -AI13642,Data Scientist,129742,USD,129742,SE,FT,Ireland,L,Ireland,50,"Linux, Mathematics, MLOps",Bachelor,9,Healthcare,2024-07-20,2024-08-23,1374,7.2,Digital Transformation LLC -AI13643,NLP Engineer,78149,GBP,58612,EN,FL,United Kingdom,M,United Kingdom,0,"R, AWS, TensorFlow, Mathematics",Master,0,Gaming,2024-04-24,2024-05-13,897,7.2,Cloud AI Solutions -AI13644,AI Consultant,84880,USD,84880,MI,FL,Norway,S,Norway,50,"SQL, GCP, NLP",Master,3,Finance,2024-03-22,2024-04-08,1412,8.2,Neural Networks Co -AI13645,Data Scientist,106468,USD,106468,EX,CT,China,L,China,50,"Linux, Docker, Tableau, Scala, GCP",Master,17,Finance,2024-03-09,2024-04-05,1740,9.2,DataVision Ltd -AI13646,AI Specialist,77051,USD,77051,EN,PT,Denmark,L,Mexico,50,"Hadoop, Docker, Kubernetes",PhD,1,Telecommunications,2024-12-28,2025-02-07,2495,6.8,TechCorp Inc -AI13647,AI Consultant,54386,AUD,73421,EN,FT,Australia,M,Australia,0,"PyTorch, TensorFlow, Git",Bachelor,1,Technology,2024-12-10,2025-01-19,561,9.2,Neural Networks Co -AI13648,Research Scientist,241352,SGD,313758,EX,CT,Singapore,L,Singapore,50,"Mathematics, Azure, Hadoop",Associate,12,Healthcare,2024-10-10,2024-11-02,1924,8.7,Algorithmic Solutions -AI13649,Computer Vision Engineer,122023,USD,122023,MI,CT,Denmark,S,Denmark,100,"Kubernetes, NLP, R, PyTorch, Docker",PhD,3,Finance,2024-10-11,2024-11-08,955,5.7,Neural Networks Co -AI13650,Computer Vision Engineer,69776,SGD,90709,MI,FT,Singapore,S,Ireland,0,"Java, Tableau, Hadoop, Scala, AWS",Master,4,Energy,2024-01-09,2024-03-11,602,8.3,DeepTech Ventures -AI13651,ML Ops Engineer,150163,USD,150163,SE,FL,Ireland,L,Ireland,100,"Kubernetes, Deep Learning, Azure",PhD,5,Transportation,2024-10-16,2024-12-22,868,7.7,Autonomous Tech -AI13652,Data Analyst,46451,CAD,58064,EN,CT,Canada,S,Canada,50,"NLP, Kubernetes, R, Java",Master,0,Manufacturing,2024-10-29,2024-11-15,718,8.2,Cognitive Computing -AI13653,Data Scientist,78071,AUD,105396,MI,PT,Australia,S,Australia,50,"Spark, Tableau, Java, Python",Associate,4,Consulting,2025-02-15,2025-04-21,648,9.9,Advanced Robotics -AI13654,Machine Learning Engineer,141974,USD,141974,SE,FL,South Korea,L,South Korea,100,"Spark, Tableau, PyTorch, Deep Learning, GCP",Associate,8,Finance,2024-03-15,2024-04-14,2050,8.6,Digital Transformation LLC -AI13655,Robotics Engineer,101301,JPY,11143110,MI,FT,Japan,L,Japan,50,"Tableau, SQL, GCP, Java",Bachelor,2,Automotive,2024-02-08,2024-02-27,1956,9.6,Cloud AI Solutions -AI13656,AI Architect,147615,USD,147615,SE,FL,Israel,L,Israel,100,"Docker, SQL, Kubernetes",Master,7,Healthcare,2024-12-01,2025-01-24,2115,5.3,Algorithmic Solutions -AI13657,Robotics Engineer,59247,USD,59247,EX,FT,India,M,Italy,100,"TensorFlow, PyTorch, Deep Learning",Associate,12,Gaming,2024-01-27,2024-03-09,1303,8.7,Digital Transformation LLC -AI13658,Computer Vision Engineer,68387,AUD,92322,EN,CT,Australia,S,Australia,0,"Scala, Git, SQL, Python, R",Associate,1,Real Estate,2025-03-29,2025-05-15,2393,9.4,Cognitive Computing -AI13659,Machine Learning Engineer,94339,SGD,122641,EN,FL,Singapore,L,Malaysia,50,"Git, SQL, GCP, Mathematics",Bachelor,1,Education,2024-02-27,2024-04-21,1382,6.9,Machine Intelligence Group -AI13660,Machine Learning Engineer,246518,SGD,320473,EX,FL,Singapore,L,Mexico,0,"Python, Kubernetes, Azure",Master,18,Consulting,2024-03-31,2024-05-07,594,8.7,TechCorp Inc -AI13661,Data Analyst,102322,USD,102322,MI,FT,Finland,M,Finland,100,"R, PyTorch, TensorFlow, Git",Master,2,Transportation,2024-03-19,2024-04-17,1537,9,Algorithmic Solutions -AI13662,Autonomous Systems Engineer,209756,USD,209756,EX,FT,United States,M,United States,100,"Tableau, Java, Kubernetes",PhD,10,Healthcare,2025-03-31,2025-05-19,1441,6.2,Advanced Robotics -AI13663,Data Scientist,130034,SGD,169044,SE,FT,Singapore,M,South Korea,100,"SQL, Linux, Git, Deep Learning, Statistics",Master,6,Gaming,2024-12-19,2025-02-15,1705,6.3,Predictive Systems -AI13664,AI Specialist,112402,EUR,95542,SE,PT,Germany,M,Germany,0,"Git, Python, Scala",Associate,7,Gaming,2024-12-30,2025-02-04,1356,5.6,AI Innovations -AI13665,Data Analyst,111935,USD,111935,SE,FL,Sweden,M,Sweden,50,"Deep Learning, Linux, Data Visualization, Statistics, Tableau",Bachelor,7,Real Estate,2024-10-26,2024-12-26,1616,7.5,AI Innovations -AI13666,ML Ops Engineer,210290,USD,210290,EX,PT,Finland,S,Finland,0,"Hadoop, Scala, Spark, Computer Vision",Bachelor,17,Real Estate,2024-04-15,2024-05-27,1321,6.2,Future Systems -AI13667,Data Engineer,156011,USD,156011,SE,PT,Norway,S,Norway,0,"Spark, Linux, Computer Vision, Python, Azure",Associate,9,Manufacturing,2024-09-28,2024-11-18,1382,8.2,AI Innovations -AI13668,Machine Learning Researcher,72835,USD,72835,EN,PT,United States,S,Italy,50,"Java, Scala, Deep Learning, Docker",Master,1,Healthcare,2024-01-03,2024-03-10,1536,9,Advanced Robotics -AI13669,Data Analyst,182390,USD,182390,SE,FL,Norway,M,Japan,50,"Tableau, Data Visualization, Azure, Docker",Associate,7,Real Estate,2024-04-23,2024-06-03,1277,5.7,Predictive Systems -AI13670,Machine Learning Researcher,69023,CAD,86279,EN,FL,Canada,M,Canada,50,"Scala, Python, Azure",Bachelor,1,Energy,2024-10-10,2024-11-03,2005,9.1,Cloud AI Solutions -AI13671,NLP Engineer,92468,GBP,69351,MI,FL,United Kingdom,M,United Kingdom,50,"Spark, Java, Data Visualization, GCP",PhD,3,Automotive,2024-06-13,2024-06-28,1890,8.1,Smart Analytics -AI13672,Research Scientist,65251,USD,65251,EN,CT,Israel,L,Israel,50,"PyTorch, Deep Learning, Spark",Master,0,Real Estate,2025-01-07,2025-02-15,651,5.6,Cognitive Computing -AI13673,AI Specialist,217187,USD,217187,EX,FL,Ireland,M,Ireland,100,"R, PyTorch, Data Visualization",Associate,15,Education,2024-03-17,2024-04-08,1446,8.3,Smart Analytics -AI13674,Autonomous Systems Engineer,54380,EUR,46223,EN,PT,Germany,S,Germany,0,"Linux, Python, Git, Statistics",Master,0,Finance,2025-01-01,2025-02-03,1960,9.6,DataVision Ltd -AI13675,AI Consultant,295717,EUR,251359,EX,CT,Netherlands,L,Netherlands,100,"Java, Data Visualization, Spark",Master,11,Finance,2024-12-19,2025-01-16,1535,9,Algorithmic Solutions -AI13676,NLP Engineer,122502,AUD,165378,SE,FT,Australia,M,Hungary,100,"NLP, TensorFlow, Hadoop",Associate,6,Consulting,2025-04-24,2025-05-09,2498,6.8,Algorithmic Solutions -AI13677,Deep Learning Engineer,109823,USD,109823,MI,CT,Sweden,L,Sweden,100,"Hadoop, AWS, Java, Statistics, Azure",Bachelor,3,Energy,2024-05-16,2024-07-01,976,8.4,Smart Analytics -AI13678,Autonomous Systems Engineer,82666,USD,82666,EN,FT,Finland,L,Finland,100,"Spark, Python, Azure, Java",PhD,0,Automotive,2025-04-08,2025-05-07,1809,7.3,Machine Intelligence Group -AI13679,Robotics Engineer,69269,GBP,51952,EN,FT,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python, Data Visualization",Master,1,Retail,2024-10-19,2024-12-20,1443,7.5,Smart Analytics -AI13680,AI Specialist,193819,USD,193819,EX,PT,Sweden,S,Sweden,50,"Linux, TensorFlow, Git, Kubernetes",PhD,11,Finance,2025-04-28,2025-05-28,630,7.4,Machine Intelligence Group -AI13681,Head of AI,104297,SGD,135586,MI,PT,Singapore,M,Singapore,100,"Java, R, AWS, Computer Vision, Statistics",PhD,4,Manufacturing,2025-02-23,2025-03-28,1501,8.7,Algorithmic Solutions -AI13682,NLP Engineer,64787,EUR,55069,EN,FL,France,S,France,0,"Hadoop, MLOps, Docker, Linux, TensorFlow",PhD,1,Energy,2025-02-08,2025-04-20,2254,7.7,DeepTech Ventures -AI13683,AI Architect,321641,USD,321641,EX,FT,Norway,M,Norway,100,"Git, TensorFlow, Scala",Bachelor,11,Education,2025-04-14,2025-06-22,1672,7.7,AI Innovations -AI13684,Computer Vision Engineer,55628,SGD,72316,EN,CT,Singapore,M,Turkey,100,"Azure, Java, R, Computer Vision, Hadoop",PhD,1,Healthcare,2025-04-18,2025-06-28,1517,5.8,Future Systems -AI13685,AI Architect,45870,USD,45870,MI,FT,China,S,Colombia,100,"AWS, Java, R, MLOps, SQL",Associate,3,Finance,2024-09-25,2024-11-27,530,5.4,Quantum Computing Inc -AI13686,AI Architect,152656,USD,152656,MI,FT,Denmark,L,Denmark,100,"MLOps, Kubernetes, PyTorch",Bachelor,3,Education,2024-03-03,2024-05-07,1022,7.1,Future Systems -AI13687,AI Software Engineer,26656,USD,26656,MI,FT,India,M,India,100,"Java, R, Data Visualization, Scala",Master,2,Retail,2025-01-27,2025-03-22,717,9.5,Advanced Robotics -AI13688,Data Analyst,146759,USD,146759,SE,PT,United States,L,United Kingdom,50,"R, Spark, Kubernetes, Python, AWS",Associate,7,Government,2024-08-10,2024-09-20,1615,8.4,TechCorp Inc -AI13689,AI Specialist,44241,CAD,55301,EN,FL,Canada,S,Canada,0,"Python, TensorFlow, PyTorch",Master,0,Finance,2025-01-01,2025-02-28,1287,6.1,TechCorp Inc -AI13690,Principal Data Scientist,124494,CHF,112045,EN,CT,Switzerland,L,Switzerland,50,"Linux, Hadoop, SQL, PyTorch, GCP",Bachelor,1,Media,2024-02-14,2024-03-12,1057,7.4,Cognitive Computing -AI13691,AI Specialist,83827,USD,83827,EX,PT,India,M,India,100,"Azure, Linux, Java, SQL",Bachelor,18,Automotive,2024-11-17,2024-12-01,1223,6.5,Advanced Robotics -AI13692,Machine Learning Researcher,133335,EUR,113335,SE,FL,Germany,M,Germany,100,"MLOps, Kubernetes, PyTorch, Statistics, SQL",PhD,8,Real Estate,2024-08-10,2024-09-29,1968,8.7,Future Systems -AI13693,Autonomous Systems Engineer,161531,EUR,137301,SE,FL,France,L,France,0,"Hadoop, Python, SQL, NLP",PhD,7,Retail,2024-12-06,2025-01-24,2300,5.5,Future Systems -AI13694,Deep Learning Engineer,80194,USD,80194,EN,FT,Ireland,M,Ireland,0,"SQL, R, Data Visualization",Master,0,Consulting,2024-12-28,2025-02-11,924,5.9,DataVision Ltd -AI13695,Data Scientist,181350,GBP,136013,EX,PT,United Kingdom,M,United Kingdom,0,"Tableau, Scala, NLP, TensorFlow",Bachelor,18,Consulting,2024-11-25,2025-01-11,2264,6.7,Predictive Systems -AI13696,AI Software Engineer,102985,USD,102985,MI,FT,Finland,M,Finland,50,"SQL, NLP, Git",PhD,3,Transportation,2025-02-20,2025-03-30,1591,8.7,Quantum Computing Inc -AI13697,AI Consultant,70147,USD,70147,EN,FT,Norway,M,Norway,0,"SQL, Scala, Git",Master,0,Education,2024-03-25,2024-04-30,598,9.5,Algorithmic Solutions -AI13698,Machine Learning Researcher,95188,SGD,123744,MI,PT,Singapore,L,Singapore,0,"Azure, PyTorch, Statistics, Hadoop, Java",Associate,3,Media,2024-12-04,2024-12-22,1227,9.4,Quantum Computing Inc -AI13699,Robotics Engineer,274623,USD,274623,EX,FL,United States,L,United States,50,"Python, PyTorch, Git, Azure, Java",Associate,14,Government,2024-02-08,2024-03-11,2135,6.4,Quantum Computing Inc -AI13700,Robotics Engineer,79001,EUR,67151,EN,CT,Germany,L,Germany,50,"Python, TensorFlow, NLP, Java",Master,1,Real Estate,2024-06-01,2024-07-07,1648,7.8,Digital Transformation LLC -AI13701,Autonomous Systems Engineer,133645,AUD,180421,SE,FL,Australia,M,Estonia,50,"Tableau, AWS, NLP, Docker",Bachelor,8,Education,2025-03-18,2025-05-26,706,9.9,AI Innovations -AI13702,Machine Learning Researcher,63052,USD,63052,SE,CT,China,S,China,0,"Computer Vision, Tableau, Data Visualization, NLP",Associate,5,Manufacturing,2024-08-12,2024-08-29,1774,6.5,Quantum Computing Inc -AI13703,AI Research Scientist,150556,AUD,203251,SE,PT,Australia,M,Australia,100,"SQL, Hadoop, Computer Vision, R",Associate,6,Technology,2024-11-02,2024-12-24,1164,8.4,Advanced Robotics -AI13704,AI Specialist,44619,USD,44619,SE,FL,China,S,China,50,"Java, TensorFlow, Git, AWS",PhD,6,Automotive,2025-04-15,2025-05-09,1572,7.6,AI Innovations -AI13705,Autonomous Systems Engineer,243017,USD,243017,EX,CT,Israel,L,Israel,0,"Scala, Data Visualization, Kubernetes, Computer Vision, Spark",Associate,12,Gaming,2024-03-09,2024-03-28,2181,8.1,Predictive Systems -AI13706,AI Specialist,201305,EUR,171109,EX,FT,Germany,L,Germany,0,"GCP, Git, PyTorch, SQL, Mathematics",Master,15,Automotive,2024-04-26,2024-06-08,1686,9.2,Quantum Computing Inc -AI13707,AI Research Scientist,94123,SGD,122360,EN,FL,Singapore,L,Singapore,50,"Java, SQL, Azure, MLOps, PyTorch",Master,0,Media,2024-01-05,2024-03-12,1613,5.4,Digital Transformation LLC -AI13708,Data Engineer,52016,GBP,39012,EN,FT,United Kingdom,S,Switzerland,100,"Azure, Kubernetes, Docker, AWS, Scala",PhD,0,Manufacturing,2024-10-14,2024-11-09,2014,6.2,Predictive Systems -AI13709,Computer Vision Engineer,48238,EUR,41002,EN,PT,France,S,Ireland,100,"Java, PyTorch, GCP",Master,0,Manufacturing,2024-03-23,2024-05-24,710,5.1,DataVision Ltd -AI13710,Data Analyst,189852,USD,189852,EX,CT,Ireland,M,Ireland,100,"Azure, Spark, SQL, Python",Master,12,Automotive,2024-07-21,2024-09-03,2343,8.2,AI Innovations -AI13711,Autonomous Systems Engineer,71233,CAD,89041,MI,FT,Canada,M,Vietnam,0,"Kubernetes, Computer Vision, Data Visualization, Azure, R",PhD,4,Transportation,2024-03-05,2024-05-04,979,8,Digital Transformation LLC -AI13712,Research Scientist,152809,EUR,129888,SE,PT,Germany,M,Germany,50,"Git, Java, R, NLP, Kubernetes",Associate,8,Real Estate,2025-01-17,2025-02-07,855,9.3,DataVision Ltd -AI13713,Principal Data Scientist,79844,USD,79844,MI,FL,Sweden,M,Sweden,50,"GCP, TensorFlow, Data Visualization, PyTorch, MLOps",Master,4,Retail,2024-11-04,2024-12-22,2002,5.7,DeepTech Ventures -AI13714,AI Specialist,90766,USD,90766,EN,CT,Sweden,L,Sweden,0,"Hadoop, Git, Spark, TensorFlow, GCP",PhD,1,Retail,2024-02-19,2024-04-22,2059,7.7,Neural Networks Co -AI13715,AI Specialist,94607,EUR,80416,MI,CT,France,M,France,50,"Linux, Spark, Azure",Associate,3,Education,2024-10-22,2024-12-14,1778,8.7,Smart Analytics -AI13716,Machine Learning Engineer,155537,JPY,17109070,SE,FT,Japan,L,Ireland,50,"Spark, Kubernetes, SQL, NLP",PhD,7,Gaming,2024-01-26,2024-02-14,1465,9.6,Algorithmic Solutions -AI13717,Principal Data Scientist,84059,GBP,63044,MI,FL,United Kingdom,M,Indonesia,0,"Spark, Python, TensorFlow, Hadoop",Bachelor,3,Media,2024-10-18,2024-12-03,1930,6.4,Smart Analytics -AI13718,Head of AI,214035,USD,214035,EX,FL,Israel,S,Israel,50,"Linux, MLOps, Hadoop, GCP, Python",PhD,12,Retail,2024-02-02,2024-02-22,1111,10,AI Innovations -AI13719,Machine Learning Engineer,62794,USD,62794,SE,FT,China,M,China,100,"Hadoop, Git, Docker, NLP",Associate,9,Telecommunications,2024-09-09,2024-09-24,858,10,Autonomous Tech -AI13720,Principal Data Scientist,78666,USD,78666,MI,FT,Sweden,S,Sweden,0,"Git, SQL, Python, R",Master,4,Automotive,2025-04-16,2025-05-18,1482,8.3,TechCorp Inc -AI13721,Head of AI,73536,JPY,8088960,EN,FT,Japan,M,Turkey,100,"Scala, Kubernetes, Java, PyTorch",PhD,0,Media,2024-08-15,2024-09-25,1805,8.9,Cloud AI Solutions -AI13722,Research Scientist,35544,USD,35544,MI,PT,China,M,Luxembourg,50,"Deep Learning, PyTorch, Java",Master,4,Education,2024-08-11,2024-10-22,1603,5.9,DeepTech Ventures -AI13723,AI Research Scientist,49579,USD,49579,EN,PT,South Korea,L,South Korea,50,"AWS, PyTorch, Scala, Linux",Associate,1,Automotive,2024-06-14,2024-08-20,2298,8.8,Digital Transformation LLC -AI13724,Data Engineer,37102,USD,37102,SE,PT,India,M,India,100,"Spark, Java, Git, Data Visualization, R",PhD,7,Finance,2024-07-23,2024-10-01,1467,5.6,Machine Intelligence Group -AI13725,Data Engineer,151791,CHF,136612,SE,FL,Switzerland,S,Switzerland,0,"Kubernetes, Mathematics, PyTorch, Spark",PhD,7,Media,2025-02-09,2025-04-23,1366,6.5,Cognitive Computing -AI13726,Head of AI,114945,USD,114945,SE,FT,Sweden,M,Sweden,100,"Computer Vision, Mathematics, NLP, PyTorch",Associate,7,Automotive,2025-02-01,2025-03-28,2374,9.5,AI Innovations -AI13727,Machine Learning Engineer,74998,CAD,93748,EN,FT,Canada,M,Canada,100,"Scala, Java, Docker",Associate,0,Transportation,2024-03-22,2024-05-02,1851,8.3,Digital Transformation LLC -AI13728,AI Software Engineer,119208,USD,119208,SE,FT,Israel,S,Israel,0,"Python, TensorFlow, Git",PhD,5,Gaming,2024-09-10,2024-11-12,762,6.6,Digital Transformation LLC -AI13729,Data Engineer,215124,USD,215124,EX,FL,Finland,M,Canada,100,"Data Visualization, Scala, AWS",Master,16,Manufacturing,2024-02-06,2024-02-26,626,8,Quantum Computing Inc -AI13730,Data Engineer,111381,JPY,12251910,SE,PT,Japan,M,Japan,50,"Scala, GCP, TensorFlow",PhD,6,Government,2024-01-05,2024-02-28,545,8.7,Future Systems -AI13731,AI Specialist,62659,EUR,53260,EN,FL,Germany,M,Germany,100,"Linux, Hadoop, Data Visualization, Python",PhD,0,Healthcare,2024-08-05,2024-09-19,1980,9.3,DeepTech Ventures -AI13732,Data Scientist,174509,EUR,148333,EX,PT,Austria,M,Austria,0,"Deep Learning, Hadoop, SQL",Associate,10,Manufacturing,2025-03-12,2025-04-12,1714,6.1,Cloud AI Solutions -AI13733,Principal Data Scientist,76295,USD,76295,SE,PT,China,L,China,0,"Python, SQL, AWS, Computer Vision",PhD,6,Real Estate,2024-09-30,2024-10-15,1025,6.9,TechCorp Inc -AI13734,Computer Vision Engineer,82190,CHF,73971,EN,CT,Switzerland,M,Malaysia,50,"Scala, Tableau, Python, Linux",Bachelor,1,Transportation,2024-06-27,2024-08-18,2364,5.3,Future Systems -AI13735,Data Scientist,60176,USD,60176,SE,FT,China,S,China,50,"R, Git, SQL",Bachelor,6,Finance,2024-07-30,2024-08-19,1300,9.1,Smart Analytics -AI13736,Computer Vision Engineer,91041,USD,91041,SE,FL,South Korea,S,Ukraine,100,"Computer Vision, Kubernetes, Git, Scala, Azure",Bachelor,8,Consulting,2024-10-06,2024-11-24,913,6.3,Quantum Computing Inc -AI13737,Robotics Engineer,51392,USD,51392,MI,FT,China,L,China,100,"Deep Learning, Hadoop, GCP",Master,2,Government,2024-01-03,2024-03-04,1175,8.8,Algorithmic Solutions -AI13738,Autonomous Systems Engineer,291795,USD,291795,EX,PT,Denmark,M,Denmark,50,"Scala, Statistics, AWS",Associate,13,Education,2025-03-18,2025-04-02,1768,7.8,Smart Analytics -AI13739,Head of AI,95963,USD,95963,EX,FL,India,L,India,0,"Kubernetes, Tableau, Hadoop",Bachelor,16,Energy,2024-10-21,2025-01-02,652,6.2,DeepTech Ventures -AI13740,AI Product Manager,48317,USD,48317,EN,FT,Ireland,S,Indonesia,50,"Python, TensorFlow, Mathematics",PhD,1,Media,2025-02-22,2025-04-20,1696,9.4,Quantum Computing Inc -AI13741,Machine Learning Researcher,66508,USD,66508,EN,FL,United States,S,Australia,100,"Docker, Python, PyTorch, Linux",PhD,1,Manufacturing,2025-02-04,2025-03-17,1858,6.4,Future Systems -AI13742,AI Architect,160872,EUR,136741,SE,FT,Germany,L,Israel,0,"AWS, Scala, SQL",Bachelor,5,Manufacturing,2024-02-02,2024-04-14,769,9.8,Cognitive Computing -AI13743,Autonomous Systems Engineer,170265,EUR,144725,EX,CT,Netherlands,S,Netherlands,0,"PyTorch, R, Deep Learning, Mathematics, NLP",PhD,14,Healthcare,2024-05-10,2024-07-21,2311,8.8,Algorithmic Solutions -AI13744,Computer Vision Engineer,67378,AUD,90960,EN,FT,Australia,M,Portugal,100,"Mathematics, PyTorch, Deep Learning, Data Visualization",Associate,0,Healthcare,2024-05-19,2024-07-26,2047,6.8,Digital Transformation LLC -AI13745,AI Consultant,201053,EUR,170895,EX,FL,Germany,L,Germany,0,"TensorFlow, Scala, SQL",Master,14,Gaming,2024-02-13,2024-04-08,793,5.1,Quantum Computing Inc -AI13746,Autonomous Systems Engineer,61127,EUR,51958,EN,FT,Germany,M,Germany,100,"Python, Azure, Tableau, MLOps, Computer Vision",Bachelor,0,Media,2025-04-04,2025-05-20,736,8.2,Predictive Systems -AI13747,Head of AI,132422,USD,132422,SE,CT,Ireland,M,Ireland,50,"Data Visualization, Python, Azure, Linux, R",Associate,7,Manufacturing,2024-12-16,2025-01-23,1166,9.4,Autonomous Tech -AI13748,Computer Vision Engineer,99521,EUR,84593,MI,CT,Netherlands,L,Netherlands,0,"Spark, SQL, Tableau, NLP, GCP",Master,3,Retail,2024-03-01,2024-04-05,1557,5.4,Advanced Robotics -AI13749,Data Engineer,187640,EUR,159494,EX,FT,France,M,United States,0,"MLOps, AWS, R",Associate,12,Manufacturing,2025-02-14,2025-03-09,1734,8.2,Cognitive Computing -AI13750,ML Ops Engineer,79512,CHF,71561,EN,FT,Switzerland,M,Switzerland,50,"SQL, GCP, Mathematics",Bachelor,1,Gaming,2024-11-03,2025-01-04,1933,6.2,Machine Intelligence Group -AI13751,ML Ops Engineer,76070,USD,76070,EN,FT,United States,M,United States,50,"SQL, Statistics, PyTorch, Spark, Kubernetes",Master,0,Energy,2025-04-30,2025-07-09,502,9.2,TechCorp Inc -AI13752,Research Scientist,214448,CHF,193003,SE,PT,Switzerland,M,Germany,0,"MLOps, PyTorch, TensorFlow, Docker",Master,6,Retail,2024-04-27,2024-06-01,1168,8.2,Smart Analytics -AI13753,ML Ops Engineer,197364,SGD,256573,EX,PT,Singapore,S,Singapore,100,"Linux, Docker, GCP, Hadoop, R",Master,13,Retail,2024-05-20,2024-07-04,689,9.1,Autonomous Tech -AI13754,Deep Learning Engineer,106426,EUR,90462,SE,CT,Netherlands,S,Kenya,100,"AWS, Kubernetes, Computer Vision, Python, Data Visualization",Associate,6,Energy,2024-08-26,2024-09-29,978,5.9,Cognitive Computing -AI13755,Computer Vision Engineer,64010,EUR,54409,MI,PT,France,S,France,100,"Data Visualization, PyTorch, Python, Azure, Docker",Master,3,Energy,2024-07-03,2024-09-10,1583,7.7,Predictive Systems -AI13756,AI Software Engineer,208320,USD,208320,EX,PT,Israel,L,Vietnam,50,"Kubernetes, Linux, TensorFlow",Bachelor,19,Energy,2024-10-06,2024-11-06,1807,6,Future Systems -AI13757,AI Product Manager,93335,USD,93335,MI,PT,Ireland,S,Ireland,0,"PyTorch, Kubernetes, Java, Deep Learning, Spark",Bachelor,4,Gaming,2025-04-08,2025-05-03,1110,5.6,Digital Transformation LLC -AI13758,AI Consultant,102368,USD,102368,SE,FT,Israel,S,Israel,0,"TensorFlow, Python, Data Visualization, Git, Hadoop",PhD,7,Gaming,2024-02-18,2024-04-18,1249,7.6,AI Innovations -AI13759,AI Product Manager,64929,EUR,55190,EN,PT,Netherlands,S,Netherlands,50,"Git, Java, Hadoop, SQL, Spark",Associate,0,Consulting,2025-01-18,2025-03-09,1113,5.9,AI Innovations -AI13760,AI Software Engineer,206784,USD,206784,EX,FL,Sweden,M,Sweden,100,"AWS, Linux, Scala, Statistics",Bachelor,17,Transportation,2024-04-06,2024-06-03,2115,6.2,DataVision Ltd -AI13761,Research Scientist,203979,USD,203979,EX,FT,South Korea,L,Latvia,100,"Git, Spark, MLOps, Docker",PhD,14,Real Estate,2024-03-30,2024-05-25,1655,7,Digital Transformation LLC -AI13762,Research Scientist,124710,CHF,112239,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, PyTorch, SQL, Deep Learning",PhD,2,Technology,2024-01-03,2024-02-05,1509,5.3,Cloud AI Solutions -AI13763,AI Software Engineer,60824,USD,60824,EN,FT,South Korea,L,Mexico,0,"PyTorch, Tableau, Deep Learning",Master,1,Automotive,2025-04-06,2025-06-12,1468,7,AI Innovations -AI13764,Robotics Engineer,133068,EUR,113108,EX,FT,France,S,France,0,"Hadoop, NLP, Mathematics, GCP",Associate,13,Finance,2024-08-25,2024-09-28,1755,7,Quantum Computing Inc -AI13765,Data Scientist,122346,USD,122346,SE,PT,Denmark,S,Chile,0,"Java, Kubernetes, GCP, SQL",Master,6,Gaming,2025-04-23,2025-06-25,1865,9.7,Future Systems -AI13766,Principal Data Scientist,180133,EUR,153113,EX,FT,Netherlands,L,Netherlands,100,"Python, Git, Kubernetes",Bachelor,14,Technology,2024-01-11,2024-03-01,1372,5.9,AI Innovations -AI13767,AI Product Manager,79220,USD,79220,MI,FT,Israel,L,Spain,0,"Mathematics, Kubernetes, Scala, Spark, TensorFlow",Associate,3,Transportation,2024-02-20,2024-03-12,2424,7.9,Algorithmic Solutions -AI13768,AI Research Scientist,129587,USD,129587,SE,FT,Israel,L,Israel,0,"AWS, Java, TensorFlow",Master,5,Consulting,2024-11-02,2025-01-11,2071,6.8,Cognitive Computing -AI13769,NLP Engineer,58088,USD,58088,EN,FT,South Korea,S,South Korea,0,"Hadoop, Computer Vision, Azure",Master,1,Transportation,2024-06-26,2024-07-22,1400,8.5,Machine Intelligence Group -AI13770,Computer Vision Engineer,202346,USD,202346,EX,CT,Norway,M,Spain,0,"Linux, NLP, Mathematics, Tableau, Spark",Bachelor,12,Technology,2024-03-18,2024-04-29,2120,8.8,Autonomous Tech -AI13771,Data Scientist,242484,USD,242484,EX,PT,Israel,L,Israel,100,"Computer Vision, PyTorch, Deep Learning, TensorFlow, MLOps",PhD,19,Government,2024-06-12,2024-07-02,938,9.3,AI Innovations -AI13772,AI Consultant,89975,GBP,67481,EN,FL,United Kingdom,L,United Kingdom,0,"SQL, Kubernetes, TensorFlow",Bachelor,1,Gaming,2024-11-05,2025-01-16,2206,8.6,TechCorp Inc -AI13773,NLP Engineer,89837,GBP,67378,MI,FL,United Kingdom,M,Finland,100,"NLP, Java, Data Visualization, Python, Deep Learning",Master,3,Energy,2024-10-08,2024-11-25,1152,8.9,Quantum Computing Inc -AI13774,NLP Engineer,218325,EUR,185576,EX,FT,Germany,M,Germany,100,"NLP, Scala, Git",Master,15,Manufacturing,2024-04-01,2024-06-11,2033,5.6,TechCorp Inc -AI13775,Robotics Engineer,75754,EUR,64391,EN,PT,Germany,M,Germany,100,"Git, Docker, Azure, GCP, Java",Bachelor,1,Government,2024-05-24,2024-08-03,1675,8.8,Future Systems -AI13776,Machine Learning Engineer,117509,EUR,99883,MI,FL,Austria,L,Australia,100,"Java, R, MLOps, Linux",Associate,4,Education,2024-04-20,2024-06-04,1885,7.8,Cloud AI Solutions -AI13777,Data Scientist,84791,USD,84791,EX,FT,India,M,Poland,0,"Python, Java, NLP, GCP",Bachelor,13,Retail,2024-07-03,2024-08-18,925,9.1,Predictive Systems -AI13778,Machine Learning Engineer,55644,USD,55644,EN,FL,South Korea,M,South Korea,100,"Statistics, Kubernetes, R, Linux",PhD,0,Education,2024-01-17,2024-03-23,800,7.5,Advanced Robotics -AI13779,Data Scientist,32651,USD,32651,MI,PT,India,L,India,50,"Computer Vision, NLP, Data Visualization, Python",Bachelor,3,Technology,2024-10-25,2024-12-28,1578,5.3,Neural Networks Co -AI13780,AI Software Engineer,207687,EUR,176534,EX,FT,Germany,M,Israel,50,"Python, Mathematics, Kubernetes",Bachelor,17,Finance,2024-04-19,2024-06-03,707,6.2,Cognitive Computing -AI13781,Machine Learning Engineer,251818,GBP,188864,EX,FT,United Kingdom,L,Latvia,100,"Deep Learning, Linux, Tableau, AWS",PhD,12,Telecommunications,2025-03-18,2025-05-13,775,6.7,Cognitive Computing -AI13782,Computer Vision Engineer,117307,USD,117307,MI,FL,Denmark,S,Denmark,0,"Git, Data Visualization, PyTorch, NLP, Java",PhD,4,Media,2024-08-30,2024-09-29,1371,7.6,Cloud AI Solutions -AI13783,Data Analyst,67912,JPY,7470320,EN,FT,Japan,S,Japan,0,"Scala, SQL, AWS, Docker",Master,0,Technology,2025-04-10,2025-05-14,2390,6,DataVision Ltd -AI13784,Data Engineer,221812,JPY,24399320,EX,FT,Japan,M,Japan,50,"Python, PyTorch, R, Mathematics",Bachelor,19,Gaming,2025-01-21,2025-03-24,1380,7.3,Autonomous Tech -AI13785,NLP Engineer,67496,USD,67496,SE,FT,China,M,Malaysia,100,"R, Hadoop, Computer Vision, Python, Scala",PhD,6,Transportation,2024-11-19,2024-12-15,862,8.1,Cognitive Computing -AI13786,Robotics Engineer,75744,CAD,94680,EN,CT,Canada,M,Canada,0,"Java, Linux, Mathematics",PhD,1,Energy,2024-07-28,2024-09-08,1383,9.6,AI Innovations -AI13787,Deep Learning Engineer,78980,SGD,102674,MI,CT,Singapore,S,Singapore,0,"SQL, PyTorch, Azure, R",PhD,4,Finance,2025-03-17,2025-04-15,1515,7.6,Neural Networks Co -AI13788,AI Consultant,138142,EUR,117421,SE,FL,Netherlands,S,South Africa,0,"Java, MLOps, Scala",PhD,6,Healthcare,2025-04-13,2025-06-14,1676,7.4,Smart Analytics -AI13789,ML Ops Engineer,183795,USD,183795,EX,CT,Sweden,M,Sweden,50,"Spark, Python, Tableau, Azure, GCP",Master,16,Energy,2024-06-20,2024-08-15,858,5.3,Digital Transformation LLC -AI13790,Autonomous Systems Engineer,181750,JPY,19992500,SE,FL,Japan,L,Japan,0,"GCP, Linux, Kubernetes, Scala",PhD,6,Consulting,2024-07-23,2024-09-07,1634,6.1,TechCorp Inc -AI13791,Autonomous Systems Engineer,122129,AUD,164874,SE,FT,Australia,S,Romania,100,"Spark, Kubernetes, MLOps",Master,6,Healthcare,2024-03-14,2024-04-03,685,5.9,Machine Intelligence Group -AI13792,Data Engineer,227275,CHF,204548,EX,CT,Switzerland,M,Switzerland,0,"GCP, Kubernetes, Deep Learning, Scala",Bachelor,16,Government,2024-04-10,2024-06-22,768,7.7,Neural Networks Co -AI13793,Machine Learning Engineer,164834,USD,164834,SE,FT,Denmark,S,Czech Republic,50,"SQL, Scala, Hadoop",PhD,9,Education,2024-01-01,2024-01-16,1996,7.8,Cognitive Computing -AI13794,Data Scientist,86870,CHF,78183,EN,FT,Switzerland,M,Brazil,50,"Java, Kubernetes, NLP",PhD,1,Consulting,2024-11-12,2025-01-21,983,5.4,Algorithmic Solutions -AI13795,ML Ops Engineer,75356,USD,75356,EN,FL,Sweden,L,Sweden,50,"Docker, PyTorch, Data Visualization, Azure",Associate,1,Consulting,2024-05-20,2024-07-06,845,9.2,Autonomous Tech -AI13796,AI Research Scientist,70888,USD,70888,MI,FT,Finland,M,Finland,100,"Spark, Mathematics, SQL, AWS",Bachelor,4,Healthcare,2024-11-22,2024-12-10,2303,5.4,DataVision Ltd -AI13797,Research Scientist,85683,AUD,115672,MI,FL,Australia,L,Philippines,100,"Scala, Python, Java, Docker, Data Visualization",Associate,3,Finance,2024-09-13,2024-11-22,1167,9.8,Future Systems -AI13798,Robotics Engineer,136342,EUR,115891,SE,CT,Austria,M,Australia,100,"TensorFlow, Java, MLOps",Bachelor,5,Energy,2024-06-07,2024-07-11,922,8.1,AI Innovations -AI13799,Deep Learning Engineer,308880,CHF,277992,EX,FT,Switzerland,S,Switzerland,0,"Deep Learning, Docker, AWS, Mathematics, Statistics",Associate,15,Automotive,2024-05-29,2024-07-01,1649,9.1,Smart Analytics -AI13800,Machine Learning Engineer,163206,USD,163206,EX,PT,United States,S,United States,50,"PyTorch, Linux, Azure, Hadoop, Kubernetes",Bachelor,19,Energy,2024-02-20,2024-04-18,2044,6.7,Cloud AI Solutions -AI13801,Data Engineer,268727,AUD,362781,EX,FT,Australia,L,Australia,100,"Kubernetes, SQL, Data Visualization, Tableau, Spark",Bachelor,13,Technology,2025-04-26,2025-06-21,1933,6.1,DeepTech Ventures -AI13802,AI Consultant,158218,CAD,197773,EX,PT,Canada,L,Canada,50,"GCP, Python, Computer Vision, Kubernetes, MLOps",Master,19,Technology,2024-03-23,2024-04-08,1759,7,AI Innovations -AI13803,Robotics Engineer,90014,GBP,67511,MI,FT,United Kingdom,S,United Kingdom,0,"Hadoop, Deep Learning, Linux, Java",PhD,3,Real Estate,2024-03-17,2024-04-30,2183,8.9,Cloud AI Solutions -AI13804,Deep Learning Engineer,350601,CHF,315541,EX,FL,Switzerland,M,Switzerland,50,"R, Computer Vision, Hadoop",Bachelor,17,Finance,2024-10-24,2025-01-05,674,7.5,Autonomous Tech -AI13805,Machine Learning Researcher,162040,USD,162040,EX,PT,Denmark,S,Denmark,0,"Statistics, Linux, Deep Learning",Bachelor,11,Government,2024-07-06,2024-08-25,808,6.6,Autonomous Tech -AI13806,AI Research Scientist,195569,CAD,244461,EX,FT,Canada,L,Canada,0,"Scala, TensorFlow, Java, Docker, SQL",Bachelor,14,Telecommunications,2024-01-26,2024-02-21,1230,5,DataVision Ltd -AI13807,AI Consultant,65095,USD,65095,EX,PT,China,S,China,50,"GCP, Mathematics, Python",Associate,14,Consulting,2024-08-05,2024-10-06,1770,5.3,Cognitive Computing -AI13808,Principal Data Scientist,135374,AUD,182755,SE,PT,Australia,S,Estonia,0,"Git, NLP, Linux, Hadoop",Master,6,Manufacturing,2025-02-14,2025-04-10,1991,6.5,Neural Networks Co -AI13809,Machine Learning Engineer,114011,USD,114011,SE,CT,South Korea,M,South Korea,0,"Kubernetes, Python, Linux, NLP",Associate,7,Gaming,2024-11-07,2024-12-28,1423,8.7,Machine Intelligence Group -AI13810,Data Engineer,67057,EUR,56998,MI,FT,Austria,S,Mexico,100,"NLP, Python, Hadoop, Linux, Azure",Associate,2,Education,2024-06-16,2024-08-01,1249,9.3,DeepTech Ventures -AI13811,AI Specialist,59067,EUR,50207,EN,FL,France,L,France,50,"Linux, MLOps, Spark, Python, Git",Bachelor,1,Retail,2024-10-07,2024-10-31,1401,9.7,Quantum Computing Inc -AI13812,AI Architect,178851,USD,178851,SE,FL,United States,L,United States,0,"Python, TensorFlow, GCP, Tableau",Associate,8,Consulting,2024-09-14,2024-11-01,2079,5.4,Neural Networks Co -AI13813,Robotics Engineer,91673,USD,91673,EX,FL,China,S,Spain,0,"Docker, Java, Linux",Master,12,Automotive,2025-03-26,2025-05-18,896,9.3,Machine Intelligence Group -AI13814,Machine Learning Researcher,176800,USD,176800,SE,FL,Norway,M,Austria,100,"Linux, NLP, Scala, Java",Bachelor,6,Manufacturing,2024-06-17,2024-08-03,807,8.2,Cognitive Computing -AI13815,AI Product Manager,56994,GBP,42746,EN,FL,United Kingdom,S,Spain,50,"Docker, Statistics, Scala, Java",Associate,1,Technology,2024-07-07,2024-08-16,1916,5.5,DeepTech Ventures -AI13816,AI Consultant,152056,EUR,129248,SE,CT,Netherlands,M,Netherlands,100,"Spark, Data Visualization, Linux, GCP",Bachelor,7,Automotive,2024-03-08,2024-03-23,711,6.9,Predictive Systems -AI13817,Principal Data Scientist,77428,SGD,100656,MI,PT,Singapore,S,Singapore,100,"PyTorch, Linux, SQL, Data Visualization",Master,4,Government,2024-09-09,2024-10-03,994,9.7,Machine Intelligence Group -AI13818,Computer Vision Engineer,232854,AUD,314353,EX,PT,Australia,M,Turkey,50,"TensorFlow, AWS, Python, NLP",Master,14,Gaming,2024-03-27,2024-05-23,2158,5.8,Autonomous Tech -AI13819,AI Software Engineer,198603,CHF,178743,SE,FL,Switzerland,L,Turkey,100,"Spark, Git, Docker",Master,7,Technology,2025-01-28,2025-04-07,1864,8.2,Cognitive Computing -AI13820,AI Specialist,119402,USD,119402,SE,CT,Finland,L,Finland,100,"GCP, Scala, SQL, Tableau",Master,7,Telecommunications,2024-10-25,2024-12-17,742,8.4,Future Systems -AI13821,Machine Learning Engineer,62647,AUD,84573,EN,FL,Australia,M,Australia,50,"Azure, Git, Computer Vision, Tableau, Docker",Associate,1,Transportation,2024-03-19,2024-04-06,2182,5.9,TechCorp Inc -AI13822,AI Software Engineer,226045,USD,226045,EX,FL,Denmark,S,Latvia,100,"Hadoop, Scala, PyTorch",Associate,17,Education,2024-05-28,2024-07-25,664,7.2,Neural Networks Co -AI13823,Head of AI,220671,AUD,297906,EX,FL,Australia,L,Australia,0,"Kubernetes, MLOps, Mathematics, SQL",Bachelor,10,Energy,2024-10-29,2024-12-11,900,6,TechCorp Inc -AI13824,Principal Data Scientist,88695,CHF,79826,EN,PT,Switzerland,S,Switzerland,50,"NLP, SQL, R, Computer Vision, Docker",Associate,0,Real Estate,2024-07-31,2024-09-18,1805,5.8,DataVision Ltd -AI13825,NLP Engineer,55419,USD,55419,SE,PT,India,L,India,0,"Kubernetes, Computer Vision, Spark, Python, Docker",PhD,9,Energy,2024-04-17,2024-06-28,2238,9.1,AI Innovations -AI13826,AI Architect,121382,USD,121382,MI,FT,Norway,M,Finland,100,"SQL, Scala, Git, Computer Vision",Associate,4,Technology,2024-02-20,2024-03-05,1592,9.6,Digital Transformation LLC -AI13827,AI Research Scientist,80405,EUR,68344,EN,FL,Austria,L,Finland,0,"Azure, Git, Tableau, TensorFlow",Master,1,Education,2024-12-16,2025-01-09,2261,7.1,Predictive Systems -AI13828,NLP Engineer,234097,EUR,198982,EX,CT,France,L,Turkey,0,"Spark, Hadoop, SQL",Master,13,Gaming,2024-05-04,2024-06-14,1819,5.9,Future Systems -AI13829,Robotics Engineer,122139,USD,122139,SE,PT,Finland,M,Turkey,100,"GCP, Kubernetes, Hadoop, MLOps, Scala",Bachelor,8,Consulting,2024-09-08,2024-11-16,1113,9.6,Smart Analytics -AI13830,Autonomous Systems Engineer,61146,EUR,51974,EN,PT,Germany,L,Italy,100,"Computer Vision, Hadoop, Linux, SQL, Statistics",Bachelor,1,Education,2024-12-22,2025-03-03,2096,8.7,Autonomous Tech -AI13831,AI Research Scientist,72035,USD,72035,EN,FL,United States,S,United States,100,"Python, NLP, Docker, Kubernetes, Git",Associate,0,Gaming,2025-02-14,2025-04-22,2448,7,DeepTech Ventures -AI13832,Computer Vision Engineer,224347,USD,224347,EX,FT,Sweden,M,Belgium,50,"TensorFlow, GCP, Scala, R",Associate,19,Government,2025-04-03,2025-06-15,1747,8,Predictive Systems -AI13833,Principal Data Scientist,54240,USD,54240,SE,CT,China,S,Canada,100,"Spark, Python, PyTorch, SQL",Bachelor,5,Telecommunications,2024-08-16,2024-10-22,1611,7.8,Machine Intelligence Group -AI13834,Principal Data Scientist,153995,USD,153995,SE,FL,Denmark,M,Denmark,0,"GCP, Data Visualization, R",Associate,5,Retail,2024-09-07,2024-10-26,1386,9.7,Predictive Systems -AI13835,Autonomous Systems Engineer,196504,USD,196504,SE,FT,United States,L,United Kingdom,0,"Hadoop, Docker, TensorFlow, Mathematics, Git",Associate,6,Real Estate,2024-09-22,2024-10-06,2223,8.4,Predictive Systems -AI13836,Deep Learning Engineer,164839,GBP,123629,EX,FL,United Kingdom,S,United Kingdom,0,"Kubernetes, MLOps, R, GCP",Bachelor,10,Government,2024-12-24,2025-01-08,2256,10,AI Innovations -AI13837,NLP Engineer,57984,USD,57984,EN,PT,South Korea,M,South Korea,50,"Python, Mathematics, TensorFlow",Bachelor,0,Energy,2025-02-20,2025-05-03,2117,7.1,Advanced Robotics -AI13838,AI Architect,269893,EUR,229409,EX,PT,Netherlands,L,Germany,100,"Azure, Data Visualization, Git",PhD,13,Education,2025-03-24,2025-04-08,2342,5.2,Cloud AI Solutions -AI13839,Data Analyst,72103,EUR,61288,EN,FT,Netherlands,S,Netherlands,100,"Mathematics, Computer Vision, SQL, Kubernetes",Bachelor,1,Education,2025-02-13,2025-04-19,1864,5.7,Neural Networks Co -AI13840,Principal Data Scientist,130093,JPY,14310230,SE,PT,Japan,S,Japan,50,"Data Visualization, Git, Mathematics, Deep Learning, NLP",Master,7,Media,2024-12-05,2025-01-30,1903,8.2,Algorithmic Solutions -AI13841,AI Specialist,68572,USD,68572,EN,FT,Ireland,L,Ireland,100,"Kubernetes, Java, GCP, Mathematics, Scala",Associate,0,Technology,2024-12-15,2024-12-31,663,7.8,Cloud AI Solutions -AI13842,AI Architect,55431,EUR,47116,EN,FT,Germany,M,Germany,0,"PyTorch, Java, Statistics",Bachelor,1,Gaming,2024-05-01,2024-05-27,585,5.5,Future Systems -AI13843,AI Consultant,104409,AUD,140952,MI,FT,Australia,L,Hungary,100,"R, Python, GCP",Master,2,Finance,2024-07-06,2024-08-17,1477,6.3,Smart Analytics -AI13844,AI Product Manager,98179,USD,98179,MI,CT,Norway,S,Norway,100,"PyTorch, TensorFlow, Java, Hadoop",PhD,2,Technology,2024-10-30,2024-12-28,1392,9.2,Smart Analytics -AI13845,AI Product Manager,138780,USD,138780,EX,FT,Finland,S,New Zealand,0,"Deep Learning, Data Visualization, Python",PhD,11,Retail,2024-03-19,2024-05-12,2161,5.6,AI Innovations -AI13846,Principal Data Scientist,222699,CHF,200429,SE,PT,Switzerland,L,Switzerland,50,"Python, Linux, SQL",Bachelor,9,Retail,2025-01-22,2025-03-10,849,6.4,DeepTech Ventures -AI13847,AI Architect,50170,USD,50170,EN,PT,South Korea,L,South Korea,0,"PyTorch, Python, MLOps",Master,1,Retail,2025-04-16,2025-05-10,2460,7.6,Advanced Robotics -AI13848,Research Scientist,38746,USD,38746,MI,FT,China,S,Philippines,0,"R, Git, Tableau, Scala, Docker",PhD,4,Manufacturing,2025-03-10,2025-05-08,2240,5.9,Predictive Systems -AI13849,Principal Data Scientist,74319,USD,74319,EN,PT,Israel,M,Canada,100,"Python, Scala, AWS",Associate,0,Education,2025-02-20,2025-03-06,1598,9.8,Cognitive Computing -AI13850,Data Engineer,273668,JPY,30103480,EX,PT,Japan,L,Ghana,100,"Tableau, Spark, Deep Learning, GCP, Python",Bachelor,10,Education,2024-08-18,2024-09-08,2356,7.9,Cloud AI Solutions -AI13851,Data Engineer,66041,USD,66041,EN,PT,Denmark,M,Ukraine,100,"Mathematics, TensorFlow, Git, Python, Linux",Master,0,Telecommunications,2024-11-18,2024-12-30,1290,5.5,Advanced Robotics -AI13852,AI Product Manager,75268,EUR,63978,EN,PT,Germany,M,Germany,100,"Data Visualization, Scala, Statistics, NLP",Bachelor,1,Transportation,2024-12-18,2025-01-24,1933,7.4,Future Systems -AI13853,Robotics Engineer,177163,EUR,150589,EX,CT,Germany,M,Russia,100,"Java, Spark, Computer Vision, Docker",Master,13,Retail,2025-01-01,2025-02-11,1434,9.5,Advanced Robotics -AI13854,AI Software Engineer,169340,JPY,18627400,EX,CT,Japan,L,Japan,50,"Kubernetes, Computer Vision, Python, Scala",Master,16,Retail,2024-12-16,2025-02-18,903,9,DeepTech Ventures -AI13855,Research Scientist,150295,SGD,195384,SE,FT,Singapore,M,Malaysia,50,"R, Python, Data Visualization",Associate,5,Real Estate,2024-02-24,2024-04-01,1181,5.5,Neural Networks Co -AI13856,AI Product Manager,154260,CHF,138834,SE,FL,Switzerland,M,Germany,50,"GCP, Python, Tableau, Statistics, Mathematics",Associate,6,Gaming,2024-06-26,2024-07-13,1751,7.1,Predictive Systems -AI13857,AI Specialist,100497,CAD,125621,MI,CT,Canada,M,Canada,50,"TensorFlow, Python, Java",PhD,2,Retail,2024-12-24,2025-02-12,2099,6.5,DeepTech Ventures -AI13858,Machine Learning Engineer,193134,USD,193134,EX,FL,Sweden,L,South Korea,50,"Kubernetes, GCP, Python",Associate,14,Consulting,2024-08-13,2024-10-23,786,6.8,Algorithmic Solutions -AI13859,ML Ops Engineer,170026,CHF,153023,MI,FL,Switzerland,L,Switzerland,50,"Hadoop, Azure, Tableau, Data Visualization, Git",Bachelor,3,Automotive,2024-09-18,2024-11-07,2419,7.7,AI Innovations -AI13860,Data Analyst,237130,USD,237130,EX,FL,Finland,M,Hungary,50,"AWS, Hadoop, Tableau, Git",Associate,13,Technology,2024-01-23,2024-03-02,1588,7.8,Algorithmic Solutions -AI13861,Principal Data Scientist,122855,CHF,110570,MI,CT,Switzerland,S,Switzerland,100,"AWS, R, Git",PhD,4,Healthcare,2024-09-08,2024-11-18,1670,8.5,Smart Analytics -AI13862,AI Consultant,73055,CHF,65750,EN,FL,Switzerland,S,Egypt,50,"TensorFlow, Python, Docker, Statistics",PhD,0,Media,2024-08-22,2024-10-22,1510,8.9,Future Systems -AI13863,Research Scientist,38444,USD,38444,SE,CT,India,S,India,100,"PyTorch, Linux, TensorFlow, Data Visualization",Associate,9,Transportation,2024-06-14,2024-07-23,1791,9.6,Machine Intelligence Group -AI13864,Data Scientist,174441,USD,174441,EX,PT,Ireland,M,Romania,50,"Data Visualization, Azure, Python",Bachelor,11,Real Estate,2025-02-26,2025-03-27,1148,9.5,Future Systems -AI13865,AI Research Scientist,120189,USD,120189,SE,FL,Denmark,S,Denmark,0,"Python, SQL, Scala, TensorFlow, AWS",Master,5,Telecommunications,2025-04-06,2025-06-12,953,9.9,Future Systems -AI13866,Principal Data Scientist,112460,USD,112460,SE,PT,Ireland,S,Ireland,100,"Azure, Python, GCP, Scala, Mathematics",Associate,8,Technology,2024-08-17,2024-09-22,2399,9.8,Autonomous Tech -AI13867,AI Architect,230551,AUD,311244,EX,CT,Australia,M,Australia,100,"Spark, Statistics, Scala, Computer Vision, SQL",Bachelor,17,Education,2024-03-28,2024-05-17,1060,5.4,Neural Networks Co -AI13868,AI Research Scientist,143999,EUR,122399,SE,FL,Netherlands,L,Netherlands,0,"Deep Learning, Python, NLP, Hadoop, Java",PhD,6,Consulting,2024-05-05,2024-06-29,2418,8.8,Quantum Computing Inc -AI13869,AI Specialist,181922,CHF,163730,SE,CT,Switzerland,L,Hungary,50,"AWS, Git, Java",PhD,7,Transportation,2025-04-08,2025-06-03,1333,9.8,Cloud AI Solutions -AI13870,Autonomous Systems Engineer,121801,USD,121801,SE,FL,South Korea,L,France,0,"Python, TensorFlow, Computer Vision",Bachelor,8,Telecommunications,2024-04-09,2024-04-25,739,10,AI Innovations -AI13871,Research Scientist,158462,GBP,118847,SE,PT,United Kingdom,M,United Kingdom,0,"R, Python, PyTorch, Git, SQL",Master,9,Manufacturing,2024-04-12,2024-05-03,2349,9.4,Future Systems -AI13872,NLP Engineer,113678,USD,113678,SE,CT,Finland,L,Finland,0,"Python, Computer Vision, Linux, Azure",Bachelor,7,Education,2024-12-07,2025-02-04,1789,9.6,Future Systems -AI13873,ML Ops Engineer,151647,GBP,113735,SE,CT,United Kingdom,M,United Kingdom,50,"Git, R, Java",Bachelor,7,Telecommunications,2024-08-05,2024-09-18,1696,8.9,Quantum Computing Inc -AI13874,AI Software Engineer,111894,USD,111894,SE,FL,United States,S,United States,0,"Deep Learning, Kubernetes, Scala",PhD,8,Energy,2024-04-04,2024-04-22,1512,7.9,Advanced Robotics -AI13875,Autonomous Systems Engineer,99898,USD,99898,MI,PT,Sweden,M,Sweden,100,"Linux, Python, TensorFlow, Scala",PhD,3,Gaming,2024-08-24,2024-10-23,2166,7.9,TechCorp Inc -AI13876,Computer Vision Engineer,88708,USD,88708,MI,PT,Sweden,M,Egypt,50,"Computer Vision, MLOps, Java, Kubernetes, Docker",Master,2,Retail,2025-01-23,2025-04-02,788,8.2,Quantum Computing Inc -AI13877,AI Specialist,101550,JPY,11170500,MI,CT,Japan,M,Russia,0,"AWS, R, Deep Learning, Python",Master,4,Transportation,2024-05-27,2024-07-19,2250,7.9,TechCorp Inc -AI13878,ML Ops Engineer,69360,CAD,86700,EN,CT,Canada,L,Canada,100,"Kubernetes, Scala, Computer Vision",PhD,1,Retail,2024-05-19,2024-06-15,540,7.1,TechCorp Inc -AI13879,Robotics Engineer,124351,SGD,161656,SE,PT,Singapore,S,Singapore,100,"MLOps, SQL, Data Visualization, TensorFlow",Bachelor,6,Healthcare,2024-05-22,2024-06-11,2292,7.5,Quantum Computing Inc -AI13880,AI Specialist,174613,GBP,130960,EX,CT,United Kingdom,S,Finland,100,"SQL, Azure, NLP, Hadoop",Bachelor,17,Healthcare,2024-09-26,2024-10-15,2365,5.6,Machine Intelligence Group -AI13881,AI Software Engineer,164314,GBP,123236,SE,FT,United Kingdom,L,United Kingdom,0,"Git, Deep Learning, MLOps, Java",Bachelor,7,Healthcare,2025-01-11,2025-03-25,1645,8.6,TechCorp Inc -AI13882,NLP Engineer,33496,USD,33496,MI,FT,India,M,India,100,"PyTorch, Kubernetes, Deep Learning, MLOps, GCP",Associate,4,Telecommunications,2024-04-21,2024-07-01,1093,8,Advanced Robotics -AI13883,NLP Engineer,90700,USD,90700,EN,CT,United States,M,United States,50,"Tableau, Data Visualization, SQL, Python, GCP",Master,0,Government,2024-11-18,2025-01-20,1192,9.6,Neural Networks Co -AI13884,Machine Learning Researcher,43580,USD,43580,SE,PT,India,L,India,0,"Python, Computer Vision, Data Visualization",Associate,6,Healthcare,2025-01-19,2025-02-10,725,9.1,Future Systems -AI13885,Autonomous Systems Engineer,134932,USD,134932,SE,PT,United States,S,United States,0,"GCP, Python, PyTorch, Computer Vision, Hadoop",Master,8,Media,2024-04-05,2024-04-24,1152,5.6,TechCorp Inc -AI13886,Machine Learning Researcher,97649,USD,97649,MI,PT,Denmark,S,Denmark,100,"Python, Azure, GCP, Scala, Docker",Associate,2,Transportation,2024-02-26,2024-04-26,1846,9.1,Algorithmic Solutions -AI13887,Data Scientist,150764,EUR,128149,EX,FT,Germany,S,Ukraine,100,"Azure, Data Visualization, AWS, Python, Computer Vision",Bachelor,15,Healthcare,2024-10-24,2024-12-25,1536,9.2,Machine Intelligence Group -AI13888,Machine Learning Engineer,136387,GBP,102290,SE,FL,United Kingdom,M,United Kingdom,0,"Hadoop, Python, Statistics",PhD,9,Gaming,2025-01-20,2025-02-10,2089,9.9,Advanced Robotics -AI13889,AI Research Scientist,99958,USD,99958,MI,CT,United States,M,United States,100,"Linux, Kubernetes, Java, Computer Vision, NLP",Master,3,Government,2024-06-03,2024-07-14,1509,5.7,Neural Networks Co -AI13890,Autonomous Systems Engineer,98300,CAD,122875,SE,PT,Canada,S,Canada,0,"Python, Data Visualization, TensorFlow",Associate,7,Technology,2025-01-04,2025-03-07,566,5.5,Advanced Robotics -AI13891,Machine Learning Researcher,22579,USD,22579,EN,FT,India,S,India,100,"TensorFlow, SQL, Azure",Associate,0,Telecommunications,2024-05-19,2024-06-05,548,5.6,Future Systems -AI13892,Data Engineer,159778,USD,159778,SE,CT,Ireland,L,Romania,100,"Spark, Kubernetes, SQL, PyTorch",Bachelor,8,Manufacturing,2024-12-02,2025-02-11,1797,9.3,Autonomous Tech -AI13893,Autonomous Systems Engineer,52353,USD,52353,EX,CT,India,M,India,50,"R, Computer Vision, MLOps, Spark",Master,19,Government,2024-05-01,2024-06-16,2384,6.8,TechCorp Inc -AI13894,Data Scientist,82987,EUR,70539,MI,FT,Netherlands,M,Netherlands,0,"PyTorch, TensorFlow, NLP, R, Python",Master,2,Automotive,2025-02-09,2025-03-28,2186,9.1,Cognitive Computing -AI13895,Machine Learning Engineer,76339,USD,76339,SE,FL,South Korea,S,South Korea,50,"Python, GCP, Computer Vision",Associate,5,Healthcare,2025-02-19,2025-04-15,521,7.2,DeepTech Ventures -AI13896,Research Scientist,100750,USD,100750,EN,FL,Norway,L,Norway,50,"Azure, R, Docker",Master,1,Gaming,2024-09-26,2024-11-10,1045,7.3,Quantum Computing Inc -AI13897,Principal Data Scientist,73199,SGD,95159,EN,FT,Singapore,S,Singapore,50,"Python, PyTorch, Hadoop, Java",PhD,1,Government,2024-09-24,2024-11-02,668,5.6,Algorithmic Solutions -AI13898,Computer Vision Engineer,76495,USD,76495,EN,FT,United States,M,United States,100,"R, Docker, Data Visualization, NLP, PyTorch",Master,1,Automotive,2025-01-19,2025-03-12,1924,7.5,Algorithmic Solutions -AI13899,Machine Learning Researcher,101641,USD,101641,EN,FT,Norway,M,Norway,100,"Azure, NLP, SQL, Computer Vision, PyTorch",Bachelor,0,Technology,2024-01-03,2024-01-18,1481,5.7,Advanced Robotics -AI13900,Head of AI,66025,EUR,56121,EN,PT,Germany,M,Germany,50,"Python, R, TensorFlow, Statistics, AWS",Bachelor,1,Transportation,2024-07-20,2024-08-03,908,9,Machine Intelligence Group -AI13901,AI Product Manager,55150,USD,55150,SE,FT,India,L,India,100,"Hadoop, Tableau, Scala",Master,6,Energy,2025-02-20,2025-04-07,2055,9.2,DeepTech Ventures -AI13902,Data Engineer,132349,GBP,99262,EX,FT,United Kingdom,S,United Kingdom,50,"Spark, Tableau, AWS, Java",Master,17,Healthcare,2024-08-31,2024-10-30,750,5.6,Algorithmic Solutions -AI13903,AI Software Engineer,84903,EUR,72168,MI,PT,Netherlands,M,Netherlands,0,"Kubernetes, PyTorch, Data Visualization, Computer Vision",Bachelor,3,Manufacturing,2024-02-06,2024-04-15,761,5.5,Autonomous Tech -AI13904,Robotics Engineer,172144,JPY,18935840,SE,FT,Japan,L,Kenya,50,"Git, PyTorch, Java, Spark",Master,9,Telecommunications,2025-01-04,2025-02-06,710,6.3,TechCorp Inc -AI13905,AI Software Engineer,83302,SGD,108293,EN,PT,Singapore,M,Singapore,50,"Mathematics, Deep Learning, Python, Kubernetes, Azure",Bachelor,1,Media,2025-04-10,2025-05-09,2257,7.8,Cloud AI Solutions -AI13906,NLP Engineer,109085,CHF,98177,MI,CT,Switzerland,S,Australia,50,"SQL, Data Visualization, AWS, MLOps",Bachelor,3,Retail,2024-01-01,2024-02-09,1601,7.5,Neural Networks Co -AI13907,Machine Learning Engineer,354720,CHF,319248,EX,FT,Switzerland,M,Denmark,100,"SQL, Java, Linux",Master,17,Finance,2024-06-27,2024-07-19,1806,5.9,DeepTech Ventures -AI13908,Data Engineer,106171,EUR,90245,SE,PT,France,M,Ukraine,0,"Scala, Deep Learning, Computer Vision",Bachelor,5,Finance,2024-08-13,2024-09-08,1723,8.6,Cloud AI Solutions -AI13909,AI Specialist,86810,USD,86810,EX,PT,India,M,Germany,50,"Spark, PyTorch, Git, Data Visualization",Master,15,Energy,2024-05-29,2024-07-01,1002,8.6,Algorithmic Solutions -AI13910,Machine Learning Engineer,131624,USD,131624,SE,CT,Sweden,M,Ireland,50,"Docker, Linux, Kubernetes, NLP",PhD,8,Transportation,2024-02-11,2024-04-22,1531,9,DeepTech Ventures -AI13911,AI Research Scientist,68905,SGD,89577,EN,FL,Singapore,S,Singapore,50,"Kubernetes, R, TensorFlow, Statistics, Hadoop",Bachelor,0,Government,2024-03-06,2024-04-17,775,6.6,Predictive Systems -AI13912,Machine Learning Engineer,134463,GBP,100847,SE,FL,United Kingdom,M,Netherlands,0,"Spark, Linux, TensorFlow, Java",Bachelor,5,Manufacturing,2025-04-11,2025-05-04,1935,5.3,Quantum Computing Inc -AI13913,Principal Data Scientist,98904,USD,98904,EX,FL,India,L,India,0,"Git, GCP, Tableau, Spark, Scala",Master,14,Energy,2024-02-25,2024-04-09,1310,9.9,Digital Transformation LLC -AI13914,Data Engineer,257480,USD,257480,EX,FT,Norway,S,Japan,0,"GCP, Statistics, Linux, Scala, R",Master,13,Energy,2024-11-24,2025-01-09,890,5.5,Digital Transformation LLC -AI13915,AI Architect,117881,SGD,153245,SE,FL,Singapore,S,Singapore,0,"SQL, Git, Data Visualization, PyTorch, MLOps",Master,7,Government,2025-04-03,2025-06-01,680,9.4,Future Systems -AI13916,ML Ops Engineer,131840,EUR,112064,EX,CT,France,M,France,50,"Kubernetes, Java, Azure, Python, TensorFlow",PhD,13,Consulting,2024-07-24,2024-08-17,1098,8.7,AI Innovations -AI13917,Machine Learning Researcher,235864,SGD,306623,EX,PT,Singapore,S,Romania,0,"R, Data Visualization, GCP, Tableau",PhD,12,Technology,2024-12-30,2025-02-10,1394,8.7,DataVision Ltd -AI13918,Robotics Engineer,151764,EUR,128999,SE,FL,Germany,M,Germany,100,"Python, TensorFlow, Java, PyTorch, Mathematics",Associate,6,Media,2024-12-08,2025-01-21,2196,7.8,Future Systems -AI13919,AI Consultant,120897,USD,120897,MI,CT,Norway,L,Turkey,0,"GCP, Spark, Deep Learning",PhD,3,Retail,2025-03-16,2025-05-03,1528,5.6,DataVision Ltd -AI13920,Deep Learning Engineer,319778,USD,319778,EX,CT,Denmark,M,Denmark,0,"MLOps, Tableau, Linux, Git",Bachelor,18,Energy,2024-10-18,2024-11-05,1330,7.2,Cloud AI Solutions -AI13921,Data Engineer,213125,EUR,181156,EX,CT,Germany,M,Philippines,100,"TensorFlow, MLOps, GCP, Java",PhD,16,Energy,2025-01-11,2025-03-14,1895,8.2,TechCorp Inc -AI13922,AI Specialist,99994,EUR,84995,MI,PT,Netherlands,L,Czech Republic,50,"Computer Vision, AWS, TensorFlow, Python, R",Bachelor,2,Retail,2025-04-14,2025-06-13,1090,5.2,Algorithmic Solutions -AI13923,Deep Learning Engineer,42397,USD,42397,EN,FT,China,L,China,0,"TensorFlow, AWS, Azure, PyTorch",Master,1,Gaming,2024-03-01,2024-04-13,2322,6.3,AI Innovations -AI13924,Data Engineer,268816,GBP,201612,EX,CT,United Kingdom,M,United Kingdom,50,"Tableau, SQL, R, Docker, Kubernetes",Master,11,Telecommunications,2025-01-07,2025-03-02,1846,7.4,Cloud AI Solutions -AI13925,Machine Learning Engineer,146336,USD,146336,MI,CT,Denmark,L,United States,0,"PyTorch, R, Mathematics",Bachelor,4,Automotive,2024-11-15,2024-12-13,1227,8.2,Digital Transformation LLC -AI13926,ML Ops Engineer,163963,EUR,139369,EX,PT,Germany,M,Israel,100,"SQL, Data Visualization, Hadoop",PhD,15,Government,2024-08-13,2024-10-15,916,6.7,Predictive Systems -AI13927,Research Scientist,50533,USD,50533,SE,PT,India,M,India,0,"Statistics, R, Computer Vision, Hadoop, Git",Bachelor,5,Energy,2024-03-31,2024-05-29,1703,5.5,Smart Analytics -AI13928,AI Architect,82127,SGD,106765,EN,FT,Singapore,L,Colombia,50,"AWS, Spark, Linux, TensorFlow, Python",Master,0,Energy,2024-12-25,2025-01-23,2258,5.2,Cloud AI Solutions -AI13929,AI Consultant,116006,GBP,87005,SE,FT,United Kingdom,S,United Kingdom,50,"Python, PyTorch, Tableau, Mathematics, MLOps",Master,9,Education,2024-08-12,2024-10-10,1582,8,Algorithmic Solutions -AI13930,Robotics Engineer,126184,USD,126184,MI,PT,Norway,M,Norway,100,"Java, Linux, TensorFlow, R, Data Visualization",Master,4,Transportation,2024-11-14,2024-12-31,1710,5.6,Predictive Systems -AI13931,Machine Learning Researcher,160147,EUR,136125,SE,FL,Netherlands,L,Netherlands,0,"Kubernetes, TensorFlow, NLP, Statistics, Data Visualization",Master,7,Manufacturing,2024-04-13,2024-06-12,1699,5.9,Predictive Systems -AI13932,AI Product Manager,107865,SGD,140225,MI,CT,Singapore,M,Vietnam,100,"Python, Data Visualization, TensorFlow, PyTorch",Master,4,Gaming,2025-01-11,2025-02-26,1084,9.1,DeepTech Ventures -AI13933,AI Architect,187028,CHF,168325,SE,FT,Switzerland,S,Switzerland,0,"Python, Docker, Hadoop, Azure",Master,7,Transportation,2024-04-15,2024-06-12,1931,9,Machine Intelligence Group -AI13934,ML Ops Engineer,110875,CHF,99788,MI,FT,Switzerland,S,Switzerland,100,"Hadoop, Python, Data Visualization",Master,3,Education,2024-12-13,2025-01-14,1288,7.1,Autonomous Tech -AI13935,Data Engineer,206757,USD,206757,EX,FL,United States,S,Ghana,0,"Scala, PyTorch, Data Visualization, GCP",PhD,13,Technology,2024-11-09,2024-12-02,1852,8.6,Advanced Robotics -AI13936,Machine Learning Engineer,56474,USD,56474,EN,FT,Ireland,M,Ireland,50,"Python, R, PyTorch",Bachelor,0,Government,2024-08-11,2024-09-09,1099,8.2,Cognitive Computing -AI13937,AI Specialist,85570,USD,85570,EX,FL,India,M,Italy,0,"PyTorch, TensorFlow, Linux, NLP",Bachelor,15,Automotive,2024-02-19,2024-04-21,689,7.9,Digital Transformation LLC -AI13938,Autonomous Systems Engineer,212458,CHF,191212,SE,FL,Switzerland,L,Switzerland,100,"Scala, Python, TensorFlow",Bachelor,6,Manufacturing,2024-06-06,2024-07-22,889,9.5,Advanced Robotics -AI13939,AI Architect,70580,SGD,91754,EN,PT,Singapore,S,Chile,100,"Azure, GCP, Python",Associate,1,Media,2024-01-16,2024-02-12,1169,9.8,AI Innovations -AI13940,Data Engineer,36309,USD,36309,SE,CT,India,S,Norway,100,"Linux, Git, Kubernetes, PyTorch, SQL",Master,9,Consulting,2024-05-21,2024-07-06,747,6.6,DeepTech Ventures -AI13941,Deep Learning Engineer,64560,USD,64560,EN,FT,Israel,M,Turkey,50,"Python, Data Visualization, Linux, Kubernetes, Computer Vision",Bachelor,0,Technology,2024-12-18,2025-02-16,1314,6,Smart Analytics -AI13942,Deep Learning Engineer,94949,EUR,80707,MI,CT,France,L,France,100,"R, Computer Vision, Data Visualization, Java",Bachelor,4,Transportation,2024-08-19,2024-09-25,979,6,Cloud AI Solutions -AI13943,Research Scientist,74347,USD,74347,MI,PT,South Korea,M,South Korea,50,"PyTorch, GCP, Scala, Java",Bachelor,3,Media,2024-10-04,2024-12-01,1926,7.9,AI Innovations -AI13944,AI Product Manager,321456,USD,321456,EX,FL,United States,L,United States,100,"Docker, GCP, Statistics",Master,15,Automotive,2024-10-25,2024-12-06,1311,8.6,Quantum Computing Inc -AI13945,Head of AI,72159,EUR,61335,EN,FT,Germany,L,Germany,0,"R, Spark, Mathematics",PhD,0,Retail,2024-04-16,2024-06-08,1412,8.4,Advanced Robotics -AI13946,Machine Learning Researcher,185190,USD,185190,EX,PT,Finland,S,Finland,100,"GCP, Scala, MLOps, Python, Azure",Bachelor,12,Automotive,2024-07-10,2024-09-20,977,8.5,Autonomous Tech -AI13947,AI Product Manager,150333,EUR,127783,SE,FT,Germany,L,Poland,0,"R, Azure, Git, Python",PhD,9,Automotive,2025-01-18,2025-02-24,1452,9.1,Quantum Computing Inc -AI13948,Research Scientist,265558,AUD,358503,EX,PT,Australia,L,Australia,0,"Java, Deep Learning, NLP",Master,12,Education,2024-06-07,2024-07-09,874,9.9,Cognitive Computing -AI13949,Machine Learning Researcher,82299,EUR,69954,MI,FT,Austria,L,Kenya,0,"Data Visualization, Deep Learning, Java",Master,2,Consulting,2024-11-14,2024-12-25,981,8.1,Cloud AI Solutions -AI13950,AI Specialist,148281,JPY,16310910,SE,FL,Japan,L,Japan,50,"Linux, Java, R, Kubernetes",PhD,5,Healthcare,2025-03-02,2025-03-17,892,7.8,Cognitive Computing -AI13951,AI Product Manager,33202,USD,33202,MI,FT,China,S,China,0,"Java, Python, Data Visualization, TensorFlow, Git",Bachelor,2,Education,2024-05-18,2024-07-19,821,8.5,Algorithmic Solutions -AI13952,AI Software Engineer,67300,USD,67300,EN,CT,Israel,M,Israel,0,"TensorFlow, Python, Linux, Statistics",Bachelor,0,Finance,2024-05-23,2024-06-25,2327,7.1,Cloud AI Solutions -AI13953,AI Product Manager,120081,USD,120081,MI,FL,Ireland,L,Ireland,100,"Data Visualization, R, Azure",Master,4,Real Estate,2024-01-15,2024-02-21,2086,7.6,Cognitive Computing -AI13954,Machine Learning Engineer,73036,EUR,62081,MI,CT,France,S,France,0,"Python, MLOps, Tableau",PhD,2,Technology,2025-04-08,2025-05-05,1365,9.2,AI Innovations -AI13955,Robotics Engineer,87908,USD,87908,EN,FT,Norway,S,Norway,100,"Kubernetes, Data Visualization, NLP, R, TensorFlow",Associate,0,Consulting,2024-11-29,2025-01-21,609,8.3,Quantum Computing Inc -AI13956,Machine Learning Researcher,70146,USD,70146,EX,PT,India,S,India,0,"Git, Python, Data Visualization, Linux, Scala",Bachelor,14,Education,2024-05-14,2024-07-25,669,5.5,DeepTech Ventures -AI13957,Principal Data Scientist,32133,USD,32133,MI,FL,India,S,India,100,"Azure, Python, Tableau, GCP",Bachelor,3,Media,2024-10-21,2024-12-25,1969,8.9,Algorithmic Solutions -AI13958,Data Scientist,108840,JPY,11972400,SE,CT,Japan,S,Japan,50,"TensorFlow, Kubernetes, GCP, Spark",Associate,8,Consulting,2024-06-17,2024-07-06,1758,7.5,Neural Networks Co -AI13959,Machine Learning Researcher,122926,EUR,104487,SE,PT,Netherlands,M,United States,0,"Kubernetes, Scala, Tableau",Master,9,Retail,2024-03-17,2024-04-03,1477,8.5,Autonomous Tech -AI13960,AI Product Manager,287863,CHF,259077,EX,PT,Switzerland,M,Norway,50,"Scala, Deep Learning, Hadoop",PhD,19,Automotive,2024-04-07,2024-05-24,1944,6.5,Predictive Systems -AI13961,Machine Learning Engineer,99266,USD,99266,SE,FT,Ireland,S,Ireland,50,"MLOps, Spark, PyTorch",Associate,7,Finance,2024-07-15,2024-08-10,2461,5.3,Neural Networks Co -AI13962,NLP Engineer,228899,JPY,25178890,EX,FT,Japan,M,China,50,"MLOps, Docker, Kubernetes, Python, AWS",PhD,18,Real Estate,2024-06-05,2024-07-28,2258,8.4,Advanced Robotics -AI13963,Data Scientist,162574,USD,162574,EX,PT,Ireland,M,Ireland,100,"Kubernetes, Spark, Tableau, Deep Learning",Bachelor,16,Real Estate,2024-10-29,2024-12-21,2146,6.7,AI Innovations -AI13964,Data Engineer,225255,USD,225255,EX,PT,Finland,L,Finland,100,"Deep Learning, Computer Vision, Tableau, Azure, Docker",PhD,13,Manufacturing,2024-06-12,2024-08-12,632,5.5,Autonomous Tech -AI13965,Head of AI,132938,CHF,119644,MI,FL,Switzerland,S,Switzerland,0,"Git, Azure, MLOps, Linux, R",PhD,2,Education,2025-02-04,2025-03-01,551,9.9,Smart Analytics -AI13966,AI Consultant,90671,USD,90671,SE,FT,Israel,S,Poland,50,"PyTorch, Kubernetes, TensorFlow, SQL",PhD,7,Finance,2025-02-08,2025-02-25,2316,9.8,Algorithmic Solutions -AI13967,AI Architect,179691,SGD,233598,EX,CT,Singapore,L,Singapore,0,"Scala, MLOps, Python",Bachelor,13,Telecommunications,2024-10-13,2024-12-18,1094,7.5,Cognitive Computing -AI13968,AI Specialist,80674,USD,80674,EX,FL,India,L,India,0,"Git, PyTorch, Hadoop",PhD,13,Real Estate,2024-06-30,2024-07-27,1834,9.6,Quantum Computing Inc -AI13969,Research Scientist,96450,CAD,120563,SE,PT,Canada,S,Canada,50,"Hadoop, Python, TensorFlow, Computer Vision",Master,9,Transportation,2024-03-17,2024-05-05,1744,5.3,TechCorp Inc -AI13970,AI Research Scientist,132495,USD,132495,SE,FL,Sweden,L,Sweden,50,"Kubernetes, Docker, NLP",Bachelor,9,Automotive,2024-10-12,2024-12-04,1918,8.9,Cloud AI Solutions -AI13971,Machine Learning Engineer,70645,CAD,88306,EN,CT,Canada,L,Canada,50,"Linux, Tableau, Python, PyTorch",Associate,1,Media,2025-03-27,2025-05-11,1527,9.3,Machine Intelligence Group -AI13972,Robotics Engineer,24476,USD,24476,EN,PT,China,S,China,50,"Statistics, Scala, Java, MLOps, Deep Learning",Associate,1,Telecommunications,2024-12-18,2025-01-21,996,7.5,Neural Networks Co -AI13973,Machine Learning Engineer,219297,SGD,285086,EX,FL,Singapore,L,Singapore,50,"Kubernetes, Scala, Spark, Deep Learning, Statistics",Associate,15,Automotive,2024-06-27,2024-07-25,705,6.6,Machine Intelligence Group -AI13974,Computer Vision Engineer,139564,GBP,104673,EX,PT,United Kingdom,S,United Kingdom,100,"Linux, GCP, Scala",PhD,15,Telecommunications,2025-03-10,2025-04-17,1455,9.2,Machine Intelligence Group -AI13975,NLP Engineer,232693,USD,232693,EX,FT,United States,S,United States,50,"Computer Vision, Python, TensorFlow, Java, R",PhD,14,Gaming,2024-06-29,2024-08-03,2116,7.7,AI Innovations -AI13976,Machine Learning Engineer,97324,USD,97324,MI,PT,Ireland,S,Sweden,50,"AWS, Linux, NLP, Kubernetes",PhD,3,Energy,2024-01-31,2024-04-01,970,6.7,Autonomous Tech -AI13977,AI Specialist,83572,USD,83572,MI,FT,South Korea,L,Italy,0,"Docker, Hadoop, Kubernetes, Statistics, R",Bachelor,3,Real Estate,2024-01-03,2024-03-13,2121,8.2,Cloud AI Solutions -AI13978,Computer Vision Engineer,119106,USD,119106,MI,FL,United States,M,Nigeria,100,"Tableau, Java, Python",Bachelor,2,Government,2025-04-19,2025-06-14,1345,7.8,Machine Intelligence Group -AI13979,Deep Learning Engineer,107752,SGD,140078,MI,PT,Singapore,L,Singapore,100,"AWS, Docker, Data Visualization, GCP, Kubernetes",Master,2,Energy,2024-06-08,2024-06-28,2045,5.3,Cloud AI Solutions -AI13980,AI Consultant,62312,SGD,81006,EN,FL,Singapore,M,Singapore,0,"Deep Learning, Data Visualization, Python, Tableau, MLOps",PhD,1,Education,2024-05-02,2024-05-26,1829,7.8,Neural Networks Co -AI13981,Principal Data Scientist,118029,USD,118029,SE,FT,Ireland,L,Ireland,0,"TensorFlow, SQL, Tableau",PhD,7,Retail,2024-05-14,2024-07-25,1262,7.4,TechCorp Inc -AI13982,Computer Vision Engineer,204810,AUD,276494,EX,FL,Australia,S,Australia,0,"AWS, Data Visualization, R, NLP",Master,18,Retail,2024-01-28,2024-03-03,727,6.1,Neural Networks Co -AI13983,Research Scientist,79470,EUR,67550,MI,FT,Netherlands,M,Portugal,100,"Deep Learning, Mathematics, MLOps, Java, GCP",Associate,3,Finance,2024-09-06,2024-10-18,2268,9.1,Future Systems -AI13984,Data Analyst,86228,AUD,116408,MI,CT,Australia,M,Switzerland,100,"Statistics, Spark, GCP, Git",PhD,2,Real Estate,2024-06-17,2024-07-02,1626,6.6,Neural Networks Co -AI13985,Data Engineer,118142,CAD,147678,MI,FT,Canada,L,Canada,100,"NLP, Python, Tableau",PhD,3,Retail,2024-02-16,2024-03-02,984,5.8,Smart Analytics -AI13986,Principal Data Scientist,149989,USD,149989,EX,CT,Israel,S,Israel,100,"AWS, PyTorch, Deep Learning, Mathematics",Bachelor,11,Energy,2024-09-14,2024-10-04,1455,6.8,TechCorp Inc -AI13987,Data Scientist,59094,USD,59094,EN,CT,South Korea,M,United States,0,"Kubernetes, Data Visualization, Git",Master,1,Retail,2024-07-09,2024-07-29,1869,8,Cognitive Computing -AI13988,Machine Learning Engineer,177285,USD,177285,SE,FL,Norway,L,Norway,0,"Scala, MLOps, Tableau, Data Visualization, R",Associate,8,Government,2024-03-30,2024-04-29,1226,8.2,Quantum Computing Inc -AI13989,Autonomous Systems Engineer,86720,USD,86720,EN,PT,Denmark,M,Denmark,0,"Computer Vision, Tableau, Scala",Master,1,Education,2024-04-01,2024-06-07,1124,6.8,Advanced Robotics -AI13990,Data Scientist,86353,USD,86353,EX,CT,China,L,China,0,"Computer Vision, Statistics, NLP, Tableau, Scala",Associate,17,Real Estate,2024-11-30,2025-01-08,1182,9.3,Cognitive Computing -AI13991,AI Specialist,43936,USD,43936,SE,PT,India,M,India,50,"Data Visualization, PyTorch, Docker, Hadoop, AWS",PhD,8,Real Estate,2025-03-07,2025-05-17,1226,6.7,Neural Networks Co -AI13992,Computer Vision Engineer,143556,USD,143556,EX,FT,Finland,M,Spain,100,"Data Visualization, Statistics, Python, Git",Master,16,Education,2025-03-05,2025-04-16,2169,8.9,Predictive Systems -AI13993,Robotics Engineer,78380,USD,78380,EX,PT,India,M,China,50,"Python, Java, PyTorch, Mathematics",PhD,18,Government,2024-12-24,2025-01-20,768,5.9,Predictive Systems -AI13994,AI Consultant,72730,EUR,61821,MI,FL,Austria,S,Austria,100,"GCP, SQL, Kubernetes, Data Visualization",Bachelor,2,Energy,2024-08-03,2024-09-03,519,7.1,Digital Transformation LLC -AI13995,Head of AI,290341,USD,290341,EX,CT,Sweden,L,Sweden,0,"Computer Vision, Python, MLOps",Associate,16,Retail,2024-06-15,2024-08-25,618,5.1,DataVision Ltd -AI13996,Data Engineer,217967,USD,217967,EX,CT,Ireland,S,Brazil,50,"PyTorch, AWS, TensorFlow",Master,17,Media,2024-09-18,2024-11-03,1350,8.7,Digital Transformation LLC -AI13997,Data Engineer,102309,USD,102309,EX,FL,India,L,India,100,"SQL, Python, Computer Vision, Mathematics",Bachelor,11,Technology,2024-05-17,2024-06-25,1370,8.2,Neural Networks Co -AI13998,Research Scientist,80525,EUR,68446,MI,FT,Netherlands,M,Indonesia,0,"Java, R, TensorFlow",Associate,3,Consulting,2024-12-18,2025-01-09,2180,7.3,Advanced Robotics -AI13999,Data Scientist,202160,USD,202160,SE,FT,United States,L,United States,100,"MLOps, Git, Tableau, Scala",Bachelor,6,Transportation,2025-04-12,2025-06-24,1769,7,Algorithmic Solutions -AI14000,Head of AI,220964,USD,220964,EX,FT,Sweden,S,Sweden,100,"PyTorch, Computer Vision, Hadoop, Python, Spark",PhD,19,Automotive,2024-11-14,2025-01-15,2217,8.3,Quantum Computing Inc -AI14001,AI Specialist,56149,USD,56149,EN,PT,Israel,L,Israel,100,"TensorFlow, NLP, Data Visualization, Scala",Master,0,Technology,2025-03-06,2025-04-20,2102,8.5,Algorithmic Solutions -AI14002,Principal Data Scientist,145157,CAD,181446,SE,FT,Canada,L,Canada,100,"Azure, Data Visualization, AWS, Kubernetes",PhD,9,Education,2025-01-16,2025-02-09,2214,5.6,Neural Networks Co -AI14003,Data Engineer,172667,USD,172667,SE,PT,Sweden,L,Mexico,0,"SQL, GCP, Java, Deep Learning",Bachelor,6,Education,2024-12-28,2025-01-17,1466,5.4,AI Innovations -AI14004,NLP Engineer,138247,AUD,186633,EX,FL,Australia,M,Chile,100,"SQL, Python, Computer Vision, NLP, Spark",Master,12,Consulting,2024-12-28,2025-02-25,1737,6,Machine Intelligence Group -AI14005,Robotics Engineer,129293,USD,129293,MI,PT,Norway,M,South Africa,0,"Mathematics, Linux, MLOps",Master,4,Media,2024-04-10,2024-05-06,1752,7,TechCorp Inc -AI14006,AI Specialist,106869,CAD,133586,SE,FT,Canada,M,New Zealand,100,"SQL, Python, Statistics, GCP, Kubernetes",Master,7,Media,2024-08-21,2024-10-15,1926,5.1,Machine Intelligence Group -AI14007,NLP Engineer,57671,EUR,49020,EN,FT,France,L,France,50,"Azure, Git, Hadoop",Associate,1,Healthcare,2025-04-02,2025-05-01,1741,6.8,DataVision Ltd -AI14008,AI Product Manager,279242,GBP,209432,EX,FT,United Kingdom,L,United Kingdom,0,"Hadoop, Linux, Computer Vision",Master,12,Transportation,2024-10-21,2024-11-15,1138,6.9,Machine Intelligence Group -AI14009,Data Scientist,204632,JPY,22509520,EX,FT,Japan,L,Japan,100,"Scala, Spark, Deep Learning, Git, PyTorch",Associate,14,Retail,2025-02-27,2025-04-07,1462,9.9,AI Innovations -AI14010,Data Engineer,203509,EUR,172983,EX,FT,Germany,M,Germany,100,"Python, MLOps, Data Visualization, Scala, Tableau",Associate,11,Real Estate,2024-03-29,2024-05-25,1317,6.1,Machine Intelligence Group -AI14011,AI Research Scientist,76433,EUR,64968,EN,CT,Netherlands,S,Netherlands,50,"Python, Data Visualization, Hadoop, GCP",Associate,1,Technology,2025-04-23,2025-06-06,1324,7.1,TechCorp Inc -AI14012,Machine Learning Engineer,143395,CAD,179244,EX,FL,Canada,M,Singapore,0,"NLP, Data Visualization, Python",Associate,15,Energy,2025-01-28,2025-03-27,1767,7.8,AI Innovations -AI14013,Data Scientist,190317,USD,190317,EX,PT,United States,M,United States,0,"Tableau, Spark, R",PhD,13,Gaming,2024-10-23,2024-11-17,1196,6.9,Machine Intelligence Group -AI14014,Deep Learning Engineer,18052,USD,18052,EN,FL,India,M,Russia,50,"AWS, SQL, Computer Vision, NLP, Azure",Associate,0,Finance,2024-09-24,2024-11-05,1104,5,Machine Intelligence Group -AI14015,Data Analyst,157903,EUR,134218,SE,FL,Germany,L,Germany,50,"Hadoop, Linux, R",Associate,7,Energy,2024-02-29,2024-04-23,766,5.4,DataVision Ltd -AI14016,Deep Learning Engineer,208955,USD,208955,EX,FL,United States,L,United States,100,"Computer Vision, PyTorch, Git",Master,19,Consulting,2024-04-18,2024-06-22,2055,8.9,Autonomous Tech -AI14017,Research Scientist,34807,USD,34807,EN,CT,China,L,China,100,"Linux, R, Statistics, Kubernetes",Bachelor,1,Education,2025-02-23,2025-04-28,1827,7.1,Future Systems -AI14018,Research Scientist,81021,AUD,109378,MI,FT,Australia,S,Australia,100,"Linux, GCP, Mathematics, NLP",PhD,2,Energy,2024-12-18,2025-01-16,1620,9.9,Machine Intelligence Group -AI14019,Data Analyst,64631,EUR,54936,EN,CT,France,L,France,50,"Azure, Deep Learning, Scala, Computer Vision",Master,1,Healthcare,2024-07-28,2024-09-18,665,9.9,Smart Analytics -AI14020,AI Specialist,92162,USD,92162,EN,FT,Denmark,S,Denmark,0,"GCP, Data Visualization, Spark",PhD,0,Gaming,2024-06-16,2024-08-26,1011,9.5,Future Systems -AI14021,AI Product Manager,110327,USD,110327,MI,FT,Ireland,M,Ireland,100,"Tableau, Hadoop, Java, Spark, Deep Learning",Bachelor,2,Consulting,2024-09-18,2024-10-29,1272,7.4,Quantum Computing Inc -AI14022,Robotics Engineer,102765,USD,102765,MI,FL,Denmark,S,Denmark,0,"Linux, Git, Tableau",Bachelor,3,Technology,2025-02-10,2025-03-29,1076,8.5,DataVision Ltd -AI14023,Deep Learning Engineer,91759,USD,91759,EN,CT,United States,M,South Africa,100,"R, SQL, Hadoop",PhD,0,Automotive,2024-01-09,2024-03-01,2033,5,Digital Transformation LLC -AI14024,AI Product Manager,159836,USD,159836,EX,CT,Ireland,L,United States,50,"GCP, SQL, Hadoop",PhD,17,Consulting,2024-09-19,2024-11-09,2184,5.4,DataVision Ltd -AI14025,AI Software Engineer,120984,CHF,108886,EN,CT,Switzerland,L,Switzerland,0,"Data Visualization, Kubernetes, AWS, MLOps, SQL",Associate,1,Real Estate,2024-12-20,2025-02-11,658,5.3,Predictive Systems -AI14026,Data Scientist,159881,USD,159881,SE,PT,Ireland,L,Ireland,0,"Scala, PyTorch, Azure, AWS, Statistics",Bachelor,5,Telecommunications,2025-04-07,2025-05-31,2464,6.7,Digital Transformation LLC -AI14027,NLP Engineer,89150,JPY,9806500,EN,FL,Japan,L,Japan,0,"Git, GCP, Mathematics, PyTorch, TensorFlow",Master,1,Gaming,2024-02-13,2024-04-24,691,5.7,Autonomous Tech -AI14028,AI Consultant,67892,EUR,57708,MI,CT,France,S,France,100,"Kubernetes, Docker, Java",Master,3,Finance,2025-03-14,2025-04-01,1181,5.6,Quantum Computing Inc -AI14029,ML Ops Engineer,92548,GBP,69411,EN,CT,United Kingdom,L,United Kingdom,100,"PyTorch, Mathematics, Computer Vision, R",Master,1,Transportation,2024-09-14,2024-11-16,1462,5.9,Neural Networks Co -AI14030,Head of AI,53496,USD,53496,EN,FT,South Korea,S,Israel,0,"Deep Learning, Python, Tableau",Master,1,Energy,2024-11-03,2024-11-21,1703,9,Cognitive Computing -AI14031,Computer Vision Engineer,70599,EUR,60009,MI,FL,Austria,S,Colombia,50,"Java, Scala, Azure",Associate,3,Gaming,2025-02-16,2025-04-22,661,6.9,Quantum Computing Inc -AI14032,ML Ops Engineer,61691,EUR,52437,MI,CT,Austria,S,Austria,100,"Kubernetes, Computer Vision, Java",Master,4,Finance,2024-06-22,2024-08-10,1223,9,TechCorp Inc -AI14033,Data Analyst,128526,USD,128526,SE,FL,Ireland,L,Ireland,50,"AWS, SQL, GCP, Java",Master,9,Gaming,2024-01-21,2024-02-16,2257,5.5,Smart Analytics -AI14034,Autonomous Systems Engineer,211888,JPY,23307680,EX,FT,Japan,M,Japan,50,"Linux, MLOps, Azure, Hadoop, Spark",Associate,14,Energy,2024-09-08,2024-10-15,2247,6.9,Predictive Systems -AI14035,Robotics Engineer,111691,CAD,139614,SE,FL,Canada,S,Canada,50,"Scala, Git, R, AWS",Bachelor,6,Telecommunications,2025-03-28,2025-05-12,1360,10,AI Innovations -AI14036,Data Scientist,38446,USD,38446,SE,PT,India,S,India,100,"Docker, Python, TensorFlow, GCP",Associate,9,Government,2024-10-08,2024-11-18,1097,5.3,TechCorp Inc -AI14037,NLP Engineer,90939,CAD,113674,MI,CT,Canada,L,Canada,50,"SQL, Data Visualization, MLOps, Git, Kubernetes",Master,4,Finance,2024-05-03,2024-06-16,592,9.7,Neural Networks Co -AI14038,AI Software Engineer,89119,CAD,111399,MI,FL,Canada,S,Canada,100,"R, Data Visualization, Statistics, Scala",Master,2,Real Estate,2024-03-15,2024-05-22,805,6.7,AI Innovations -AI14039,Principal Data Scientist,334067,USD,334067,EX,FT,Norway,L,Norway,50,"Python, Statistics, Git",Master,11,Media,2025-02-20,2025-03-12,929,9.1,Digital Transformation LLC -AI14040,Head of AI,168122,USD,168122,EX,FT,South Korea,S,South Korea,0,"Mathematics, Linux, Scala, Statistics, SQL",PhD,12,Manufacturing,2025-01-15,2025-03-21,2195,6.3,Neural Networks Co -AI14041,ML Ops Engineer,130674,CHF,117607,SE,PT,Switzerland,S,Switzerland,0,"Azure, Python, Tableau, GCP",Associate,9,Telecommunications,2025-01-05,2025-02-15,2192,5.3,TechCorp Inc -AI14042,Research Scientist,147848,EUR,125671,EX,CT,Austria,S,Austria,50,"Java, Azure, GCP",PhD,19,Automotive,2024-01-23,2024-02-11,1992,9.4,Neural Networks Co -AI14043,Data Engineer,206878,CHF,186190,EX,PT,Switzerland,M,United States,50,"Linux, TensorFlow, Python, Deep Learning",PhD,10,Telecommunications,2024-02-25,2024-03-27,2374,9.9,Neural Networks Co -AI14044,ML Ops Engineer,120770,USD,120770,MI,FT,Denmark,S,Denmark,0,"Statistics, Python, Computer Vision, PyTorch",Bachelor,4,Manufacturing,2025-02-20,2025-03-08,1180,7.4,Cloud AI Solutions -AI14045,ML Ops Engineer,209060,CAD,261325,EX,CT,Canada,S,Canada,50,"TensorFlow, Kubernetes, Scala",Associate,17,Technology,2024-12-02,2025-01-27,600,9.1,Predictive Systems -AI14046,Robotics Engineer,55846,USD,55846,EN,PT,Ireland,S,Ireland,0,"Deep Learning, Data Visualization, Tableau, Mathematics",Associate,1,Consulting,2024-12-05,2025-01-12,1994,6.8,TechCorp Inc -AI14047,Autonomous Systems Engineer,96258,USD,96258,MI,FL,Ireland,M,Ireland,50,"Scala, Data Visualization, Azure, NLP, Git",Associate,3,Manufacturing,2025-01-12,2025-01-28,1073,8,Machine Intelligence Group -AI14048,Principal Data Scientist,76228,AUD,102908,EN,CT,Australia,L,Australia,100,"SQL, Git, PyTorch, Tableau, Kubernetes",Bachelor,1,Government,2024-05-08,2024-06-03,1156,7.1,Autonomous Tech -AI14049,AI Research Scientist,202209,USD,202209,SE,PT,Norway,L,Estonia,100,"TensorFlow, Computer Vision, SQL, Java, Linux",Bachelor,6,Gaming,2025-04-17,2025-06-21,1599,6.4,TechCorp Inc -AI14050,Autonomous Systems Engineer,106972,CHF,96275,MI,PT,Switzerland,S,Egypt,100,"MLOps, Linux, Tableau, PyTorch, Hadoop",PhD,4,Finance,2024-01-09,2024-03-09,636,7.1,Advanced Robotics -AI14051,Computer Vision Engineer,79068,USD,79068,EX,FT,China,S,China,50,"Tableau, Deep Learning, PyTorch",PhD,16,Energy,2024-01-06,2024-02-04,1101,9.8,Quantum Computing Inc -AI14052,Autonomous Systems Engineer,101691,CHF,91522,MI,PT,Switzerland,S,Switzerland,50,"Java, Scala, Git, Statistics",Bachelor,2,Transportation,2024-09-01,2024-10-13,1488,5.8,Autonomous Tech -AI14053,AI Software Engineer,113366,SGD,147376,MI,PT,Singapore,L,Singapore,100,"Java, NLP, Spark, TensorFlow, Azure",Master,4,Manufacturing,2024-11-11,2024-12-04,772,8.5,Quantum Computing Inc -AI14054,ML Ops Engineer,309967,GBP,232475,EX,FL,United Kingdom,L,United Kingdom,50,"SQL, Java, Data Visualization, Hadoop, Computer Vision",Bachelor,18,Technology,2025-01-08,2025-02-20,830,6.8,Quantum Computing Inc -AI14055,AI Research Scientist,137461,EUR,116842,SE,CT,Netherlands,S,Luxembourg,50,"GCP, Python, TensorFlow, R",Associate,9,Healthcare,2025-01-06,2025-03-09,1144,8.2,AI Innovations -AI14056,AI Software Engineer,87443,USD,87443,EN,CT,United States,L,United States,0,"Computer Vision, Hadoop, Python, Kubernetes, Docker",Associate,0,Finance,2024-11-12,2024-12-06,2171,8.1,Digital Transformation LLC -AI14057,ML Ops Engineer,116059,SGD,150877,MI,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Azure, Computer Vision, Git",PhD,4,Retail,2024-07-05,2024-08-28,810,9.1,Advanced Robotics -AI14058,Principal Data Scientist,82475,USD,82475,EN,CT,Denmark,S,Netherlands,0,"GCP, SQL, Spark, Java, Mathematics",Associate,1,Retail,2025-02-19,2025-03-24,1099,9.4,Neural Networks Co -AI14059,Machine Learning Researcher,134959,USD,134959,SE,PT,Ireland,M,Ireland,50,"Git, Azure, MLOps, Linux",Bachelor,8,Finance,2024-02-26,2024-04-03,1639,9.7,AI Innovations -AI14060,NLP Engineer,295543,USD,295543,EX,FL,United States,L,Portugal,0,"SQL, Scala, Mathematics, Azure, Hadoop",Associate,14,Manufacturing,2024-03-10,2024-04-19,739,8.7,Smart Analytics -AI14061,Head of AI,69846,USD,69846,EN,FL,United States,M,Estonia,100,"Java, PyTorch, Scala, SQL",Associate,1,Finance,2024-11-09,2024-12-29,2048,8.7,DataVision Ltd -AI14062,Data Analyst,129073,JPY,14198030,SE,CT,Japan,L,Japan,100,"Linux, Data Visualization, Kubernetes, NLP, R",Bachelor,6,Transportation,2024-03-12,2024-04-27,1605,8.8,Machine Intelligence Group -AI14063,Principal Data Scientist,60030,EUR,51026,EN,CT,France,L,France,0,"Python, Java, Azure",PhD,1,Healthcare,2024-02-09,2024-04-13,810,5.2,Smart Analytics -AI14064,Machine Learning Engineer,90890,CAD,113613,MI,FL,Canada,L,Romania,50,"Statistics, Kubernetes, Python, TensorFlow",Master,2,Real Estate,2024-04-19,2024-06-12,1477,5.8,Neural Networks Co -AI14065,AI Architect,166381,USD,166381,SE,PT,Ireland,L,Germany,100,"Java, Data Visualization, AWS, Docker, Computer Vision",Bachelor,7,Media,2024-08-24,2024-09-19,2450,7.8,Smart Analytics -AI14066,AI Product Manager,281704,USD,281704,EX,FL,Ireland,L,New Zealand,100,"Computer Vision, Azure, Spark, AWS",Master,17,Energy,2024-09-24,2024-11-10,2033,9.6,DeepTech Ventures -AI14067,Computer Vision Engineer,132917,USD,132917,SE,FT,Ireland,S,Ireland,50,"SQL, Git, Python",Associate,7,Real Estate,2024-10-05,2024-11-07,980,5.5,AI Innovations -AI14068,AI Product Manager,29350,USD,29350,MI,FL,India,S,India,100,"Kubernetes, PyTorch, Hadoop, MLOps, Spark",Master,3,Education,2024-07-19,2024-09-18,1755,8.1,Quantum Computing Inc -AI14069,Data Analyst,72631,USD,72631,EN,FL,Norway,S,Norway,0,"Mathematics, Statistics, Kubernetes, Azure",PhD,0,Energy,2025-03-23,2025-04-09,1392,6.1,DataVision Ltd -AI14070,AI Research Scientist,57268,USD,57268,SE,FT,China,M,China,50,"TensorFlow, SQL, Data Visualization, GCP, Azure",Master,5,Retail,2024-02-18,2024-04-01,1414,7.5,Autonomous Tech -AI14071,AI Research Scientist,83126,CHF,74813,EN,FL,Switzerland,L,Sweden,0,"Python, TensorFlow, Scala, Kubernetes, Computer Vision",PhD,1,Transportation,2024-09-19,2024-10-28,1399,7.1,Advanced Robotics -AI14072,AI Product Manager,114645,USD,114645,MI,FL,Norway,M,Norway,0,"Git, SQL, MLOps",Master,4,Transportation,2024-11-23,2024-12-10,2416,6,DeepTech Ventures -AI14073,ML Ops Engineer,63688,USD,63688,EN,FT,Israel,S,Israel,50,"Data Visualization, Git, Computer Vision",PhD,1,Real Estate,2024-03-03,2024-04-06,1831,8.3,Advanced Robotics -AI14074,Research Scientist,122807,EUR,104386,SE,FT,Germany,S,Switzerland,0,"GCP, Docker, Statistics",Master,8,Healthcare,2025-02-26,2025-04-20,1672,6.2,Quantum Computing Inc -AI14075,Deep Learning Engineer,102173,USD,102173,SE,PT,Ireland,S,Ireland,100,"Azure, Linux, Git, Java, TensorFlow",Associate,7,Automotive,2024-07-29,2024-09-13,795,8.7,Quantum Computing Inc -AI14076,Computer Vision Engineer,139906,GBP,104930,SE,FT,United Kingdom,S,United Kingdom,0,"Git, Data Visualization, AWS, Computer Vision",PhD,8,Transportation,2024-12-23,2025-02-17,1359,8.9,DeepTech Ventures -AI14077,AI Architect,161399,JPY,17753890,EX,PT,Japan,S,Japan,100,"PyTorch, R, Kubernetes",Associate,15,Transportation,2024-12-26,2025-02-07,945,8.9,Advanced Robotics -AI14078,Principal Data Scientist,104420,EUR,88757,SE,PT,Austria,S,Netherlands,50,"Data Visualization, Statistics, Tableau",PhD,9,Healthcare,2025-04-11,2025-04-30,624,7.7,Quantum Computing Inc -AI14079,AI Software Engineer,88018,EUR,74815,MI,FT,Austria,L,Austria,100,"Spark, GCP, Scala",Bachelor,4,Gaming,2024-08-17,2024-09-12,1130,5.3,Smart Analytics -AI14080,AI Consultant,65855,USD,65855,SE,PT,China,M,China,0,"Java, Linux, MLOps",Associate,6,Automotive,2024-10-08,2024-11-26,2119,8.8,Cognitive Computing -AI14081,AI Software Engineer,153926,JPY,16931860,SE,PT,Japan,L,Japan,0,"Java, GCP, Mathematics, Docker, Python",Bachelor,7,Gaming,2024-02-27,2024-03-31,1128,8.4,Cloud AI Solutions -AI14082,Autonomous Systems Engineer,133543,SGD,173606,MI,FT,Singapore,L,Singapore,0,"NLP, GCP, Azure, Scala, Statistics",Bachelor,3,Real Estate,2024-10-18,2024-12-25,653,7.3,Machine Intelligence Group -AI14083,Machine Learning Researcher,132804,USD,132804,SE,PT,United States,M,United States,50,"Linux, Python, SQL, NLP, Computer Vision",Master,8,Transportation,2024-11-19,2024-12-14,965,8.5,Cloud AI Solutions -AI14084,Head of AI,185999,SGD,241799,EX,FT,Singapore,M,Singapore,0,"Git, Python, Statistics",Associate,11,Consulting,2024-03-07,2024-05-07,1393,8.7,Quantum Computing Inc -AI14085,Data Scientist,160037,USD,160037,SE,FT,Denmark,M,Denmark,100,"Java, Spark, Computer Vision",Bachelor,5,Real Estate,2024-06-11,2024-07-20,2246,5.4,Algorithmic Solutions -AI14086,Data Scientist,71318,SGD,92713,MI,FT,Singapore,S,Singapore,50,"Spark, Linux, NLP, AWS",Master,2,Energy,2024-10-28,2024-11-21,1534,9.5,Cloud AI Solutions -AI14087,Data Analyst,210874,GBP,158156,EX,CT,United Kingdom,L,United Kingdom,100,"SQL, PyTorch, Azure, Scala, Java",Bachelor,14,Manufacturing,2024-05-18,2024-07-18,551,9.9,Quantum Computing Inc -AI14088,Head of AI,171409,EUR,145698,SE,FT,Netherlands,L,Netherlands,0,"Tableau, Git, Kubernetes, AWS, GCP",Bachelor,7,Gaming,2025-01-28,2025-03-20,2499,7,Advanced Robotics -AI14089,Deep Learning Engineer,41300,USD,41300,EN,FL,South Korea,S,Chile,100,"Scala, Hadoop, Data Visualization, Spark",Associate,0,Automotive,2024-02-10,2024-03-28,1754,8.5,DeepTech Ventures -AI14090,NLP Engineer,61734,USD,61734,SE,FT,China,M,China,50,"Kubernetes, Scala, AWS",Associate,6,Automotive,2024-12-19,2025-01-07,2073,7.4,Smart Analytics -AI14091,Machine Learning Engineer,171718,CAD,214648,EX,FL,Canada,L,Romania,0,"GCP, PyTorch, Statistics, Spark",PhD,19,Media,2024-03-27,2024-04-11,1548,6.2,Advanced Robotics -AI14092,Research Scientist,72603,JPY,7986330,EN,FT,Japan,S,Japan,100,"NLP, Kubernetes, Data Visualization",Master,1,Telecommunications,2024-02-27,2024-04-23,1185,8.5,TechCorp Inc -AI14093,AI Research Scientist,147559,SGD,191827,SE,FT,Singapore,M,Singapore,50,"Python, TensorFlow, Data Visualization, MLOps, NLP",PhD,7,Telecommunications,2025-03-05,2025-04-17,2433,6.6,Advanced Robotics -AI14094,Principal Data Scientist,117163,JPY,12887930,MI,PT,Japan,L,Spain,50,"SQL, Python, Data Visualization",Bachelor,4,Gaming,2024-01-27,2024-02-15,2052,7.4,Quantum Computing Inc -AI14095,Research Scientist,112263,EUR,95424,MI,FL,Netherlands,M,Netherlands,0,"Hadoop, R, TensorFlow",PhD,2,Energy,2024-12-21,2025-02-02,2463,9.3,Cloud AI Solutions -AI14096,AI Software Engineer,29429,USD,29429,EN,FL,China,M,China,0,"GCP, R, Statistics, Spark",Bachelor,1,Gaming,2024-12-16,2025-01-21,1928,8.6,Cloud AI Solutions -AI14097,Head of AI,125096,USD,125096,MI,FL,United States,L,United States,50,"Tableau, Scala, Kubernetes",PhD,4,Healthcare,2025-04-16,2025-06-12,896,6.1,Digital Transformation LLC -AI14098,Autonomous Systems Engineer,290902,JPY,31999220,EX,FT,Japan,L,Japan,50,"Hadoop, Java, R, Kubernetes",Bachelor,12,Education,2024-06-04,2024-07-30,2175,5.4,Neural Networks Co -AI14099,Deep Learning Engineer,139674,USD,139674,SE,FL,Sweden,M,Egypt,100,"TensorFlow, PyTorch, Tableau, Statistics, Mathematics",PhD,8,Transportation,2024-05-19,2024-07-31,978,5.3,Digital Transformation LLC -AI14100,Data Engineer,112288,USD,112288,SE,FT,Ireland,S,Singapore,50,"Linux, Deep Learning, Kubernetes",PhD,7,Manufacturing,2024-12-20,2025-01-27,544,8.8,Machine Intelligence Group -AI14101,AI Specialist,55248,USD,55248,EX,CT,India,M,Mexico,50,"Tableau, Python, TensorFlow, AWS",PhD,16,Technology,2025-02-12,2025-03-02,1131,7,Smart Analytics -AI14102,Data Engineer,222488,USD,222488,SE,PT,Norway,L,Norway,0,"Scala, Computer Vision, Mathematics, R, NLP",Master,5,Technology,2025-02-12,2025-04-21,854,5.3,Quantum Computing Inc -AI14103,AI Software Engineer,186626,USD,186626,SE,PT,Norway,L,Denmark,100,"MLOps, SQL, Kubernetes",Associate,9,Education,2024-03-30,2024-05-07,1277,8.1,Quantum Computing Inc -AI14104,Deep Learning Engineer,262649,JPY,28891390,EX,FT,Japan,L,Japan,0,"Python, Kubernetes, Docker, TensorFlow",Master,17,Gaming,2024-10-01,2024-11-01,773,7.2,Machine Intelligence Group -AI14105,ML Ops Engineer,103455,USD,103455,MI,CT,United States,S,United States,50,"Azure, GCP, Statistics, MLOps, Python",Bachelor,3,Education,2024-07-06,2024-09-16,2487,6.3,DataVision Ltd -AI14106,Data Scientist,122416,USD,122416,MI,FL,Norway,M,Norway,0,"Kubernetes, Java, PyTorch, SQL, Spark",Bachelor,3,Education,2024-12-12,2025-01-02,1535,9.5,Autonomous Tech -AI14107,AI Product Manager,126398,SGD,164317,SE,FT,Singapore,L,Belgium,50,"GCP, Statistics, Hadoop, TensorFlow",Associate,9,Real Estate,2024-06-13,2024-07-11,2140,6.6,Machine Intelligence Group -AI14108,Deep Learning Engineer,104577,USD,104577,EN,PT,Denmark,L,Denmark,0,"SQL, Docker, Azure, R",Bachelor,0,Transportation,2025-02-06,2025-02-24,2202,8.4,Future Systems -AI14109,Machine Learning Researcher,222225,GBP,166669,EX,FT,United Kingdom,M,United Kingdom,100,"Linux, Hadoop, PyTorch, Scala, Kubernetes",PhD,12,Automotive,2024-11-03,2025-01-11,2381,8.1,DataVision Ltd -AI14110,Head of AI,153799,EUR,130729,EX,CT,Netherlands,S,Netherlands,100,"AWS, Spark, Kubernetes, SQL, Linux",Associate,12,Consulting,2025-03-24,2025-05-08,508,7.2,Predictive Systems -AI14111,Machine Learning Engineer,77712,GBP,58284,EN,CT,United Kingdom,L,Hungary,0,"Python, Kubernetes, Computer Vision, Deep Learning, Tableau",Bachelor,1,Automotive,2024-01-31,2024-04-08,938,7.4,Cognitive Computing -AI14112,Data Analyst,68332,USD,68332,EN,CT,Finland,M,Indonesia,0,"Docker, PyTorch, Data Visualization, Linux, Git",Associate,1,Government,2024-03-11,2024-03-25,1373,9.4,Digital Transformation LLC -AI14113,AI Consultant,81904,USD,81904,SE,FT,China,L,China,50,"GCP, Git, Mathematics, Data Visualization",Master,7,Technology,2024-11-08,2024-11-26,832,8.5,Machine Intelligence Group -AI14114,ML Ops Engineer,67175,GBP,50381,EN,PT,United Kingdom,M,United Kingdom,50,"Python, Kubernetes, SQL",Associate,1,Gaming,2024-10-29,2024-12-24,2341,6.8,Machine Intelligence Group -AI14115,Computer Vision Engineer,71427,USD,71427,EN,PT,Finland,L,South Africa,0,"Azure, PyTorch, Tableau",PhD,0,Healthcare,2024-01-21,2024-03-15,1801,7.8,Cloud AI Solutions -AI14116,Principal Data Scientist,163454,AUD,220663,EX,PT,Australia,S,Thailand,50,"Python, GCP, NLP",PhD,10,Automotive,2024-03-24,2024-05-30,2143,9.6,Algorithmic Solutions -AI14117,Robotics Engineer,70727,EUR,60118,MI,FL,Germany,S,Germany,0,"Linux, Computer Vision, Tableau, Azure, Python",PhD,4,Manufacturing,2025-04-21,2025-06-28,1474,8.3,Cognitive Computing -AI14118,Machine Learning Researcher,136745,SGD,177769,EX,PT,Singapore,S,Singapore,0,"Scala, Hadoop, Python, TensorFlow",PhD,14,Telecommunications,2024-01-26,2024-03-28,1093,5.3,DeepTech Ventures -AI14119,Autonomous Systems Engineer,122312,USD,122312,SE,PT,United States,M,Canada,50,"SQL, Git, AWS, GCP",Master,8,Manufacturing,2024-02-11,2024-04-21,2457,9.7,Quantum Computing Inc -AI14120,ML Ops Engineer,88018,SGD,114423,EN,CT,Singapore,L,Singapore,50,"Mathematics, Deep Learning, Java, Python, AWS",PhD,1,Education,2024-08-14,2024-10-25,2109,8.2,Predictive Systems -AI14121,AI Architect,107618,EUR,91475,SE,FT,France,S,France,0,"SQL, PyTorch, Tableau, Hadoop, Azure",PhD,8,Healthcare,2024-08-30,2024-10-27,2427,5.6,Advanced Robotics -AI14122,NLP Engineer,82542,GBP,61907,EN,PT,United Kingdom,L,United Kingdom,50,"Linux, Java, Scala, Kubernetes",Bachelor,1,Retail,2025-01-05,2025-02-02,954,5.8,Future Systems -AI14123,NLP Engineer,37476,USD,37476,EN,PT,China,L,China,50,"Java, PyTorch, TensorFlow, Deep Learning",Associate,1,Consulting,2024-08-13,2024-09-10,2224,9.9,DeepTech Ventures -AI14124,Principal Data Scientist,24095,USD,24095,EN,PT,India,M,India,100,"Kubernetes, PyTorch, TensorFlow, Mathematics",Master,1,Healthcare,2024-05-30,2024-07-16,2200,6.9,Cognitive Computing -AI14125,Research Scientist,295505,GBP,221629,EX,FL,United Kingdom,L,Italy,50,"Python, Deep Learning, Java, Azure, GCP",Bachelor,19,Automotive,2024-08-27,2024-09-17,1366,7,Autonomous Tech -AI14126,Deep Learning Engineer,85346,JPY,9388060,EN,PT,Japan,L,Japan,100,"Scala, Java, Python, MLOps, TensorFlow",Associate,1,Manufacturing,2024-09-14,2024-11-16,1248,8.7,DeepTech Ventures -AI14127,Principal Data Scientist,142448,USD,142448,SE,PT,Finland,L,Finland,50,"Kubernetes, SQL, AWS, Git",Bachelor,7,Consulting,2024-08-21,2024-09-18,559,7.9,Predictive Systems -AI14128,ML Ops Engineer,60149,USD,60149,EN,CT,Sweden,L,Sweden,100,"Azure, SQL, TensorFlow",Associate,1,Government,2024-08-19,2024-10-11,2102,6,Future Systems -AI14129,Principal Data Scientist,92230,USD,92230,MI,FL,Israel,M,Israel,100,"Azure, Python, Java, Computer Vision",PhD,3,Gaming,2024-11-15,2024-12-01,1355,5.7,Smart Analytics -AI14130,Data Engineer,93635,EUR,79590,SE,CT,Austria,S,Austria,100,"Scala, GCP, Hadoop, Statistics",Associate,9,Consulting,2024-11-01,2024-11-26,568,7.3,Advanced Robotics -AI14131,NLP Engineer,109810,GBP,82358,SE,FT,United Kingdom,M,United Kingdom,50,"Mathematics, AWS, NLP",Master,9,Transportation,2024-09-29,2024-10-15,1683,9.8,Algorithmic Solutions -AI14132,Data Scientist,268003,EUR,227803,EX,CT,Austria,L,Austria,0,"R, Hadoop, Scala",PhD,14,Media,2024-04-12,2024-06-15,1657,6.2,Quantum Computing Inc -AI14133,AI Consultant,241976,EUR,205680,EX,FT,France,L,France,100,"Kubernetes, SQL, NLP, Java, Hadoop",Master,11,Gaming,2025-02-01,2025-03-26,2290,6.1,Predictive Systems -AI14134,Data Scientist,60314,GBP,45236,EN,PT,United Kingdom,M,Ireland,50,"Kubernetes, Git, Computer Vision, Hadoop",Master,0,Telecommunications,2024-10-28,2024-12-16,2263,8.5,Cloud AI Solutions -AI14135,Autonomous Systems Engineer,34598,USD,34598,MI,FT,China,M,Russia,100,"Linux, Mathematics, Java",Bachelor,2,Consulting,2025-03-08,2025-04-17,1270,6.7,Quantum Computing Inc -AI14136,Data Analyst,174612,USD,174612,EX,CT,Israel,M,Israel,100,"R, Git, Scala, Python, Mathematics",Associate,17,Healthcare,2024-04-20,2024-06-14,1197,9.4,Neural Networks Co -AI14137,AI Research Scientist,119374,USD,119374,SE,CT,Denmark,S,India,50,"Java, R, Data Visualization, Azure",Master,9,Transportation,2024-09-25,2024-10-15,1604,6.3,Smart Analytics -AI14138,Research Scientist,121158,GBP,90869,SE,PT,United Kingdom,M,Kenya,0,"PyTorch, TensorFlow, Computer Vision, Azure, Git",PhD,9,Manufacturing,2025-03-19,2025-05-25,1718,8.2,AI Innovations -AI14139,Robotics Engineer,126193,USD,126193,SE,FL,Ireland,M,Kenya,50,"TensorFlow, Linux, Java",Bachelor,5,Consulting,2024-10-05,2024-11-22,530,9.7,Predictive Systems -AI14140,ML Ops Engineer,41111,USD,41111,MI,FT,China,M,China,100,"SQL, Java, Git, Kubernetes, PyTorch",PhD,2,Consulting,2024-01-17,2024-03-01,2487,9.7,DataVision Ltd -AI14141,Autonomous Systems Engineer,22562,USD,22562,EN,CT,India,S,India,0,"Tableau, TensorFlow, Kubernetes",Bachelor,0,Retail,2024-12-16,2025-01-11,1698,7.5,TechCorp Inc -AI14142,Data Scientist,219263,USD,219263,EX,FT,Sweden,S,Sweden,50,"Azure, Mathematics, Data Visualization, Git",Master,14,Manufacturing,2024-11-06,2024-12-18,1340,5.1,TechCorp Inc -AI14143,Data Analyst,96400,SGD,125320,MI,CT,Singapore,S,Singapore,0,"Tableau, Scala, Python, TensorFlow",Bachelor,4,Telecommunications,2024-12-06,2024-12-29,927,6,Autonomous Tech -AI14144,Autonomous Systems Engineer,128818,USD,128818,SE,PT,Ireland,M,Norway,0,"GCP, Data Visualization, Computer Vision",Master,7,Telecommunications,2024-02-07,2024-03-05,1702,7.8,Neural Networks Co -AI14145,NLP Engineer,216334,USD,216334,EX,PT,Israel,M,Israel,50,"PyTorch, SQL, MLOps, TensorFlow, AWS",Bachelor,12,Real Estate,2024-02-04,2024-02-19,1082,6.2,Quantum Computing Inc -AI14146,Machine Learning Researcher,94530,USD,94530,MI,FT,United States,S,United States,100,"Git, Docker, Data Visualization",Bachelor,2,Manufacturing,2025-04-23,2025-06-24,2094,6.1,AI Innovations -AI14147,Head of AI,89370,EUR,75965,MI,FL,Germany,M,Germany,0,"TensorFlow, Java, Mathematics",PhD,3,Retail,2024-11-14,2025-01-26,650,8.2,Cloud AI Solutions -AI14148,Data Engineer,127066,AUD,171539,SE,FL,Australia,M,Kenya,50,"Python, AWS, Scala, TensorFlow, Git",PhD,6,Transportation,2025-01-12,2025-03-13,1023,7.8,Cognitive Computing -AI14149,Principal Data Scientist,110035,EUR,93530,MI,FT,Netherlands,L,Netherlands,100,"SQL, Python, Scala",Associate,4,Automotive,2024-09-15,2024-11-14,1887,7.8,TechCorp Inc -AI14150,Machine Learning Researcher,139926,USD,139926,EX,FT,South Korea,M,South Korea,100,"PyTorch, Git, TensorFlow, R, Computer Vision",Master,12,Education,2024-01-04,2024-02-04,1739,6.9,Smart Analytics -AI14151,Machine Learning Engineer,77667,USD,77667,MI,FL,Finland,S,Finland,0,"Statistics, GCP, NLP",Associate,4,Gaming,2024-08-16,2024-10-20,1023,8.6,Algorithmic Solutions -AI14152,Deep Learning Engineer,178132,USD,178132,EX,FT,Finland,M,United States,50,"Linux, Data Visualization, Kubernetes, TensorFlow, Python",Associate,16,Finance,2024-01-04,2024-01-27,505,5.8,Autonomous Tech -AI14153,AI Research Scientist,86792,EUR,73773,MI,PT,Austria,S,Austria,0,"Data Visualization, PyTorch, Spark, Kubernetes",Associate,3,Telecommunications,2025-02-25,2025-04-13,1744,7.6,Advanced Robotics -AI14154,Autonomous Systems Engineer,316782,CHF,285104,EX,FT,Switzerland,L,Argentina,50,"MLOps, Linux, Java",Associate,16,Real Estate,2024-06-11,2024-08-12,579,5.9,Predictive Systems -AI14155,Machine Learning Engineer,96906,USD,96906,MI,FT,Ireland,L,Ireland,50,"Linux, GCP, Kubernetes, AWS",Master,4,Real Estate,2024-09-21,2024-11-23,2050,7.7,Predictive Systems -AI14156,Computer Vision Engineer,69233,SGD,90003,EN,PT,Singapore,M,Singapore,50,"Linux, Docker, Tableau",Master,0,Gaming,2024-02-26,2024-04-03,1093,6.5,Future Systems -AI14157,Data Engineer,108244,EUR,92007,SE,FT,Netherlands,S,Netherlands,50,"R, NLP, Azure",Bachelor,8,Telecommunications,2024-03-02,2024-03-29,1838,7.9,Digital Transformation LLC -AI14158,Deep Learning Engineer,93348,EUR,79346,MI,FT,Austria,L,Austria,100,"Linux, Java, Spark, Python",Bachelor,2,Finance,2024-03-20,2024-04-12,1098,8.3,Autonomous Tech -AI14159,AI Product Manager,79789,USD,79789,EN,CT,United States,M,India,0,"Spark, Linux, Tableau, Computer Vision",Associate,1,Healthcare,2024-07-17,2024-09-15,618,8.8,Cloud AI Solutions -AI14160,Machine Learning Engineer,69277,JPY,7620470,EN,PT,Japan,L,Hungary,100,"Kubernetes, Scala, Spark",Master,1,Automotive,2024-04-20,2024-06-03,1022,7,Predictive Systems -AI14161,AI Research Scientist,182548,USD,182548,EX,PT,Norway,S,Vietnam,0,"Python, GCP, MLOps, Scala, Hadoop",Master,17,Telecommunications,2024-08-07,2024-09-01,1375,5.5,Autonomous Tech -AI14162,Head of AI,80971,EUR,68825,MI,CT,Netherlands,S,Norway,100,"GCP, Mathematics, Azure, Linux, NLP",Associate,2,Automotive,2025-03-11,2025-04-24,554,9.9,Quantum Computing Inc -AI14163,Deep Learning Engineer,84774,USD,84774,EN,FT,Norway,S,Spain,0,"MLOps, Python, SQL, Statistics, Azure",PhD,1,Real Estate,2024-07-25,2024-09-06,1881,5.2,DataVision Ltd -AI14164,ML Ops Engineer,88260,EUR,75021,MI,PT,Austria,M,Austria,100,"Docker, Mathematics, Scala, Statistics, Linux",Master,3,Consulting,2024-06-15,2024-08-14,2124,8.7,Future Systems -AI14165,Research Scientist,105933,USD,105933,EN,FL,Norway,L,Norway,100,"Git, Mathematics, Data Visualization, AWS",PhD,0,Technology,2025-03-14,2025-05-15,2088,6.2,Algorithmic Solutions -AI14166,AI Product Manager,252207,USD,252207,EX,FT,Norway,M,Norway,0,"Kubernetes, Azure, MLOps, Computer Vision, NLP",Master,15,Automotive,2025-02-08,2025-02-22,1166,8.9,Algorithmic Solutions -AI14167,AI Consultant,24594,USD,24594,EN,PT,India,L,India,0,"Python, AWS, SQL",Master,0,Transportation,2024-05-11,2024-07-01,1973,8.1,AI Innovations -AI14168,Head of AI,133353,SGD,173359,MI,FT,Singapore,L,Singapore,50,"Mathematics, Computer Vision, NLP, Tableau, Python",Master,2,Media,2024-06-25,2024-07-29,1940,8.6,Machine Intelligence Group -AI14169,ML Ops Engineer,116932,USD,116932,SE,FT,Israel,M,Israel,100,"Tableau, TensorFlow, Computer Vision, Spark, Statistics",Bachelor,6,Gaming,2025-02-03,2025-03-05,898,6.2,Algorithmic Solutions -AI14170,AI Research Scientist,169884,USD,169884,EX,FL,South Korea,L,South Korea,0,"Kubernetes, R, Python",PhD,16,Technology,2024-07-12,2024-07-30,1070,7.1,Machine Intelligence Group -AI14171,AI Specialist,171722,JPY,18889420,EX,PT,Japan,M,Estonia,50,"Kubernetes, Git, Computer Vision, Deep Learning, Spark",Associate,12,Education,2024-02-26,2024-04-11,2486,9.9,Cloud AI Solutions -AI14172,AI Consultant,303831,USD,303831,EX,FL,Norway,M,Norway,0,"AWS, MLOps, R",Bachelor,18,Automotive,2025-03-30,2025-06-04,1522,8.3,Cognitive Computing -AI14173,NLP Engineer,28602,USD,28602,EN,FL,China,S,China,100,"Python, Spark, Docker",Associate,1,Gaming,2024-08-01,2024-09-28,1209,5.2,Autonomous Tech -AI14174,AI Specialist,267508,EUR,227382,EX,FL,Netherlands,M,Netherlands,100,"Kubernetes, Scala, Statistics, Azure, Tableau",Master,16,Retail,2025-03-05,2025-03-23,1209,9.6,Future Systems -AI14175,ML Ops Engineer,115925,EUR,98536,SE,FL,Austria,L,Russia,100,"Python, TensorFlow, Mathematics, PyTorch, Spark",Bachelor,8,Consulting,2024-02-12,2024-03-26,1614,9.3,Future Systems -AI14176,Data Analyst,80656,USD,80656,MI,PT,Finland,S,Kenya,100,"Python, Deep Learning, Azure, SQL, Git",PhD,2,Real Estate,2024-02-22,2024-04-10,1277,8.1,Future Systems -AI14177,Machine Learning Engineer,27562,USD,27562,EN,FL,India,M,India,0,"TensorFlow, Deep Learning, Tableau, Kubernetes",Master,1,Manufacturing,2024-07-29,2024-08-22,1304,6.8,Advanced Robotics -AI14178,Principal Data Scientist,192999,EUR,164049,EX,PT,Austria,S,Austria,50,"MLOps, NLP, Linux, TensorFlow",PhD,19,Gaming,2024-12-18,2025-02-07,701,8.5,Advanced Robotics -AI14179,AI Consultant,254016,JPY,27941760,EX,FT,Japan,M,Japan,0,"Python, Kubernetes, Mathematics, Deep Learning",Bachelor,17,Energy,2024-03-14,2024-05-22,1852,9.1,Future Systems -AI14180,Data Analyst,63794,EUR,54225,EN,FT,Austria,S,Austria,50,"PyTorch, R, NLP, Python",Master,1,Healthcare,2024-08-25,2024-10-24,1738,8.1,Autonomous Tech -AI14181,Machine Learning Engineer,82068,GBP,61551,EN,FL,United Kingdom,M,United Kingdom,100,"Tableau, PyTorch, Spark, Deep Learning, Computer Vision",PhD,1,Consulting,2024-09-09,2024-10-21,1023,6.7,Autonomous Tech -AI14182,AI Product Manager,68103,CAD,85129,EN,CT,Canada,S,Canada,50,"Data Visualization, Docker, Python, Computer Vision, Hadoop",Bachelor,1,Automotive,2024-01-07,2024-02-29,2000,6.3,DataVision Ltd -AI14183,NLP Engineer,108322,USD,108322,SE,FT,Israel,S,Israel,100,"Python, TensorFlow, MLOps",Associate,5,Government,2024-02-23,2024-04-06,1554,8.9,Predictive Systems -AI14184,Principal Data Scientist,80835,USD,80835,EN,FT,Norway,M,Norway,0,"Statistics, Scala, Linux",Bachelor,0,Automotive,2024-07-20,2024-08-17,1986,5.4,AI Innovations -AI14185,Head of AI,114660,USD,114660,SE,CT,Ireland,S,Ireland,50,"R, Git, Deep Learning, SQL",Associate,8,Automotive,2025-02-08,2025-03-25,2061,9.5,TechCorp Inc -AI14186,AI Consultant,106582,GBP,79937,MI,CT,United Kingdom,L,Ukraine,100,"Hadoop, Scala, Computer Vision, Python",Master,3,Consulting,2024-09-12,2024-11-02,2032,8.1,Digital Transformation LLC -AI14187,Machine Learning Engineer,96014,EUR,81612,MI,CT,Germany,S,Germany,50,"Scala, Java, TensorFlow, Statistics, Deep Learning",PhD,4,Media,2024-09-16,2024-11-02,1645,8.4,Predictive Systems -AI14188,Robotics Engineer,91689,USD,91689,MI,CT,Ireland,M,Ireland,100,"PyTorch, TensorFlow, Mathematics, Statistics",Master,3,Technology,2024-02-18,2024-04-18,996,7,Future Systems -AI14189,Machine Learning Researcher,64501,SGD,83851,EN,FT,Singapore,S,Singapore,0,"Linux, Deep Learning, PyTorch, Mathematics, NLP",PhD,1,Real Estate,2024-05-01,2024-06-12,1800,9.5,DataVision Ltd -AI14190,NLP Engineer,75701,CAD,94626,EN,PT,Canada,L,Canada,50,"AWS, Git, Statistics",PhD,0,Finance,2024-04-19,2024-05-03,1321,5.8,Neural Networks Co -AI14191,Head of AI,45437,USD,45437,EN,PT,Israel,S,Israel,50,"Git, Deep Learning, Kubernetes",PhD,0,Automotive,2025-04-27,2025-06-06,1697,6.6,Cloud AI Solutions -AI14192,Machine Learning Researcher,74737,USD,74737,EN,PT,Finland,M,Germany,0,"GCP, Java, R, Docker",PhD,0,Media,2024-05-13,2024-07-15,2338,9.9,DataVision Ltd -AI14193,Computer Vision Engineer,57174,USD,57174,EN,FL,Finland,L,Finland,0,"NLP, SQL, Java, AWS",Master,1,Retail,2024-05-01,2024-07-06,1347,6.9,Cloud AI Solutions -AI14194,Research Scientist,152694,USD,152694,EX,PT,Sweden,M,Sweden,0,"Data Visualization, AWS, Java, SQL",Associate,14,Healthcare,2024-03-28,2024-05-23,776,9.2,Algorithmic Solutions -AI14195,Head of AI,118599,EUR,100809,SE,PT,France,L,Philippines,100,"Kubernetes, Scala, Tableau, GCP, Data Visualization",Bachelor,9,Automotive,2024-10-30,2024-11-20,1006,5.2,TechCorp Inc -AI14196,Research Scientist,87706,CHF,78935,EN,FL,Switzerland,S,Switzerland,0,"Kubernetes, NLP, GCP, Linux, Computer Vision",Associate,0,Energy,2025-02-11,2025-03-29,1980,6,Quantum Computing Inc -AI14197,Machine Learning Researcher,88238,EUR,75002,MI,FT,France,M,France,0,"Azure, PyTorch, AWS, GCP",Associate,3,Telecommunications,2024-11-27,2024-12-19,1198,8.9,Future Systems -AI14198,AI Specialist,92582,USD,92582,SE,FT,South Korea,S,South Korea,0,"NLP, Statistics, Hadoop",PhD,5,Healthcare,2025-03-16,2025-04-14,1582,9.9,Algorithmic Solutions -AI14199,Data Analyst,38341,USD,38341,MI,FT,China,M,China,100,"Kubernetes, Python, Deep Learning, MLOps",Associate,3,Automotive,2024-10-29,2024-12-08,2212,7.7,Cloud AI Solutions -AI14200,AI Architect,40454,USD,40454,SE,FT,India,M,India,0,"R, Azure, Java",PhD,9,Automotive,2025-04-20,2025-06-07,1755,6.9,Future Systems -AI14201,Robotics Engineer,67022,SGD,87129,EN,CT,Singapore,M,Singapore,50,"SQL, Java, AWS",Master,1,Healthcare,2025-02-09,2025-03-16,1201,8.7,Quantum Computing Inc -AI14202,Research Scientist,46195,USD,46195,EN,CT,South Korea,S,Norway,50,"Python, Linux, Java, Docker",PhD,0,Real Estate,2024-01-31,2024-03-23,1062,9.5,Neural Networks Co -AI14203,Machine Learning Engineer,184717,USD,184717,EX,FT,Sweden,L,Sweden,100,"Java, R, SQL, Spark, Mathematics",Master,16,Consulting,2024-11-13,2024-12-11,1866,7.5,Predictive Systems -AI14204,Machine Learning Researcher,84313,SGD,109607,EN,PT,Singapore,M,Singapore,50,"Python, TensorFlow, Linux, Azure",Bachelor,0,Government,2024-11-20,2025-01-22,1994,7.4,Machine Intelligence Group -AI14205,Research Scientist,171948,JPY,18914280,EX,PT,Japan,M,China,0,"GCP, Spark, Docker, NLP, PyTorch",Bachelor,17,Telecommunications,2024-08-12,2024-10-04,938,7.8,Quantum Computing Inc -AI14206,Data Scientist,65079,EUR,55317,EN,PT,Netherlands,L,Sweden,50,"Scala, SQL, PyTorch, Hadoop, Azure",Bachelor,0,Consulting,2025-03-01,2025-05-02,507,6.6,TechCorp Inc -AI14207,Machine Learning Researcher,257240,USD,257240,EX,CT,United States,S,United States,100,"PyTorch, MLOps, NLP, Python",Master,15,Media,2025-04-29,2025-06-28,2003,5.1,Algorithmic Solutions -AI14208,Deep Learning Engineer,71462,AUD,96474,EN,PT,Australia,M,Colombia,100,"SQL, Linux, Mathematics",PhD,0,Healthcare,2024-04-23,2024-05-26,859,8.6,Digital Transformation LLC -AI14209,NLP Engineer,123699,USD,123699,MI,PT,United States,M,Ghana,100,"Git, PyTorch, TensorFlow, Kubernetes",Bachelor,3,Retail,2024-06-19,2024-08-02,1773,5.6,Autonomous Tech -AI14210,AI Architect,72589,USD,72589,EN,FL,Finland,M,Finland,100,"Linux, Python, Hadoop, TensorFlow",Associate,1,Energy,2024-02-29,2024-05-01,596,7,Quantum Computing Inc -AI14211,Data Engineer,128822,AUD,173910,SE,PT,Australia,S,Australia,50,"Data Visualization, Python, Git",Master,5,Manufacturing,2025-03-12,2025-04-02,1922,9.9,Algorithmic Solutions -AI14212,AI Consultant,76617,USD,76617,EN,FL,Sweden,M,Sweden,0,"Mathematics, Linux, Computer Vision, PyTorch",Associate,1,Automotive,2024-08-12,2024-09-19,1012,5.6,TechCorp Inc -AI14213,AI Specialist,93353,USD,93353,EN,PT,Norway,S,Norway,100,"Linux, Kubernetes, Scala",Associate,0,Retail,2025-02-09,2025-04-04,537,5.6,Autonomous Tech -AI14214,Deep Learning Engineer,128582,CHF,115724,MI,FT,Switzerland,L,Switzerland,50,"GCP, Python, Mathematics",Master,4,Transportation,2024-03-02,2024-05-14,1475,8,Machine Intelligence Group -AI14215,Data Analyst,105420,USD,105420,SE,CT,Israel,S,Israel,50,"Python, Kubernetes, Deep Learning, AWS, R",Master,8,Energy,2024-10-22,2024-12-12,1192,8.9,AI Innovations -AI14216,AI Specialist,158281,JPY,17410910,SE,FL,Japan,L,Japan,0,"Linux, AWS, GCP, Mathematics, Docker",Bachelor,5,Real Estate,2024-06-21,2024-08-03,2371,5.4,Neural Networks Co -AI14217,Robotics Engineer,90700,USD,90700,EN,PT,United States,M,United States,50,"PyTorch, TensorFlow, Computer Vision",PhD,1,Energy,2024-03-06,2024-03-27,1800,8.6,Quantum Computing Inc -AI14218,NLP Engineer,163549,USD,163549,SE,FL,Israel,L,Israel,100,"Java, MLOps, GCP",Master,9,Technology,2024-07-16,2024-09-05,1715,6.7,Machine Intelligence Group -AI14219,AI Architect,91126,USD,91126,EN,FL,Denmark,M,Denmark,50,"GCP, Kubernetes, Linux, Computer Vision, Python",PhD,0,Transportation,2024-05-01,2024-05-21,1952,5.9,Cognitive Computing -AI14220,AI Specialist,197097,USD,197097,SE,FL,Norway,L,Norway,0,"Java, Hadoop, TensorFlow",Associate,5,Healthcare,2024-05-28,2024-06-12,2047,5.8,Future Systems -AI14221,AI Architect,130848,USD,130848,SE,PT,Ireland,S,Ireland,50,"Python, Mathematics, Computer Vision, NLP, TensorFlow",PhD,7,Education,2024-09-10,2024-11-02,1856,9.1,DataVision Ltd -AI14222,Machine Learning Engineer,115185,EUR,97907,SE,PT,France,L,Switzerland,100,"Data Visualization, Python, TensorFlow, PyTorch",Bachelor,7,Education,2025-03-14,2025-03-31,1921,9.2,DeepTech Ventures -AI14223,AI Specialist,74184,USD,74184,MI,FT,Finland,S,Philippines,50,"Hadoop, Linux, Git, SQL, Java",PhD,2,Education,2025-03-27,2025-06-05,1287,7.9,AI Innovations -AI14224,Machine Learning Engineer,85351,EUR,72548,EN,CT,Germany,L,Germany,0,"PyTorch, Kubernetes, GCP, NLP, Git",Bachelor,1,Real Estate,2024-12-04,2024-12-22,761,8.2,DataVision Ltd -AI14225,Autonomous Systems Engineer,65593,USD,65593,EN,PT,United States,S,United States,50,"Computer Vision, Azure, Data Visualization",Master,1,Media,2024-09-12,2024-10-22,2483,6,Predictive Systems -AI14226,Robotics Engineer,123894,USD,123894,SE,CT,Ireland,S,Ireland,50,"Spark, Azure, Tableau, SQL, PyTorch",Master,6,Government,2024-02-12,2024-02-27,1054,5.9,DataVision Ltd -AI14227,AI Architect,152751,USD,152751,MI,PT,Denmark,L,Denmark,100,"Scala, Computer Vision, SQL, Git, PyTorch",PhD,2,Energy,2024-04-14,2024-05-04,1986,9.9,Cloud AI Solutions -AI14228,AI Software Engineer,94949,USD,94949,MI,CT,Norway,S,Norway,0,"Python, MLOps, Spark, Scala, TensorFlow",Associate,3,Gaming,2024-01-03,2024-01-18,1610,9.6,Neural Networks Co -AI14229,Machine Learning Researcher,199664,USD,199664,EX,FL,South Korea,L,South Korea,0,"Kubernetes, Python, Linux",Associate,18,Healthcare,2024-10-11,2024-11-15,538,6.3,Future Systems -AI14230,Research Scientist,51090,USD,51090,EN,PT,South Korea,L,South Korea,50,"Git, Scala, Kubernetes, Statistics",Master,1,Manufacturing,2024-06-29,2024-08-26,1607,7.1,Predictive Systems -AI14231,Head of AI,80797,EUR,68677,MI,FL,Germany,S,Germany,100,"PyTorch, Azure, Hadoop, Tableau",Associate,4,Telecommunications,2024-01-20,2024-03-22,1039,9.1,Cognitive Computing -AI14232,AI Product Manager,148078,EUR,125866,SE,PT,France,L,India,100,"Data Visualization, Tableau, Azure, Python, GCP",Associate,5,Government,2024-09-27,2024-11-01,1476,5,DataVision Ltd -AI14233,Research Scientist,241116,EUR,204949,EX,CT,Netherlands,L,Netherlands,50,"Hadoop, Python, Spark, Kubernetes",Bachelor,15,Technology,2024-12-27,2025-02-03,1545,9.9,Cloud AI Solutions -AI14234,AI Specialist,71525,CAD,89406,MI,FL,Canada,M,Canada,100,"GCP, Azure, R, Data Visualization",Bachelor,4,Transportation,2024-01-05,2024-03-13,852,8.8,Cognitive Computing -AI14235,Machine Learning Researcher,228052,USD,228052,EX,FL,Denmark,S,Denmark,0,"Hadoop, Python, Computer Vision, Git, Scala",Bachelor,13,Real Estate,2025-02-07,2025-04-06,1439,7,TechCorp Inc -AI14236,Deep Learning Engineer,92722,SGD,120539,MI,FL,Singapore,L,Singapore,100,"MLOps, Spark, Data Visualization",Bachelor,3,Consulting,2024-03-20,2024-05-18,1536,9.8,Future Systems -AI14237,Principal Data Scientist,177606,JPY,19536660,SE,FL,Japan,L,Japan,50,"Scala, Spark, PyTorch, TensorFlow",Master,5,Government,2024-04-05,2024-05-02,2385,7.5,DataVision Ltd -AI14238,Deep Learning Engineer,65911,USD,65911,EN,CT,South Korea,L,South Korea,50,"PyTorch, Tableau, TensorFlow",PhD,1,Energy,2024-02-19,2024-03-30,1306,9.3,Autonomous Tech -AI14239,Machine Learning Engineer,91391,GBP,68543,MI,FT,United Kingdom,S,Mexico,0,"Scala, Python, MLOps, Kubernetes, TensorFlow",Bachelor,2,Healthcare,2024-01-11,2024-02-05,1946,9.2,Algorithmic Solutions -AI14240,Machine Learning Researcher,201317,USD,201317,EX,FT,Israel,M,Israel,50,"Hadoop, PyTorch, R, Tableau",Master,17,Gaming,2024-08-13,2024-10-07,2364,6.2,Neural Networks Co -AI14241,AI Research Scientist,63528,EUR,53999,EN,FT,France,M,France,50,"Scala, Python, PyTorch",PhD,1,Gaming,2025-01-11,2025-03-08,1363,8.2,Smart Analytics -AI14242,AI Consultant,74903,EUR,63668,EN,PT,Austria,L,Austria,0,"Git, Tableau, Python",Master,1,Education,2024-02-15,2024-04-27,1458,9.9,Algorithmic Solutions -AI14243,Computer Vision Engineer,33431,USD,33431,EN,PT,China,S,Latvia,0,"SQL, Spark, PyTorch, Deep Learning, Git",Associate,0,Automotive,2024-04-14,2024-05-30,1801,8.1,DataVision Ltd -AI14244,AI Software Engineer,58058,AUD,78378,EN,PT,Australia,S,Australia,50,"Git, TensorFlow, Deep Learning, MLOps, Scala",Bachelor,1,Energy,2025-03-09,2025-04-04,2334,5,Neural Networks Co -AI14245,NLP Engineer,125186,USD,125186,SE,FL,Ireland,L,Colombia,100,"R, Java, TensorFlow, Computer Vision, Hadoop",PhD,5,Manufacturing,2024-11-02,2025-01-13,2404,5.2,Neural Networks Co -AI14246,AI Research Scientist,157137,USD,157137,SE,CT,Denmark,L,Singapore,100,"Computer Vision, Linux, SQL",Associate,7,Automotive,2024-03-14,2024-03-30,644,6,Quantum Computing Inc -AI14247,Data Scientist,32212,USD,32212,MI,PT,India,M,India,0,"Scala, PyTorch, Azure, Hadoop, Linux",Bachelor,3,Energy,2024-05-04,2024-06-08,2216,6.5,Future Systems -AI14248,Head of AI,96262,USD,96262,MI,CT,Finland,L,Romania,0,"Spark, SQL, Kubernetes, Git, AWS",Bachelor,2,Manufacturing,2025-04-19,2025-06-02,749,8.3,DeepTech Ventures -AI14249,AI Specialist,87709,USD,87709,SE,CT,South Korea,M,Vietnam,100,"PyTorch, Kubernetes, Hadoop, AWS, SQL",Associate,7,Media,2024-07-24,2024-08-10,1821,6.8,Predictive Systems -AI14250,Robotics Engineer,150226,JPY,16524860,EX,FL,Japan,M,Japan,100,"Git, NLP, Data Visualization",Master,17,Government,2024-02-05,2024-03-15,642,9.7,Algorithmic Solutions -AI14251,AI Product Manager,68640,USD,68640,EN,PT,South Korea,L,South Korea,100,"Spark, Python, Tableau, MLOps, TensorFlow",PhD,0,Technology,2024-01-03,2024-03-07,1794,8.8,TechCorp Inc -AI14252,Data Analyst,54111,EUR,45994,EN,PT,France,M,Germany,0,"GCP, Data Visualization, Java, Computer Vision",PhD,0,Energy,2025-03-16,2025-04-30,2028,6.2,AI Innovations -AI14253,Computer Vision Engineer,144317,SGD,187612,EX,FT,Singapore,S,Ghana,50,"GCP, Git, Kubernetes, AWS",Associate,15,Gaming,2024-08-07,2024-10-10,969,6.8,Smart Analytics -AI14254,Principal Data Scientist,136724,AUD,184577,SE,FL,Australia,L,Australia,50,"Linux, Data Visualization, Python, Scala",Associate,8,Gaming,2024-11-08,2024-12-07,1981,9.5,Cognitive Computing -AI14255,Robotics Engineer,100385,EUR,85327,MI,CT,Austria,L,Russia,50,"Docker, Python, MLOps, TensorFlow, SQL",Bachelor,4,Technology,2024-02-10,2024-04-12,811,6.8,Autonomous Tech -AI14256,AI Specialist,90275,EUR,76734,EN,PT,Germany,L,Italy,100,"Git, Linux, TensorFlow, R, Computer Vision",Bachelor,0,Education,2025-01-08,2025-03-22,1806,6,DataVision Ltd -AI14257,Principal Data Scientist,180652,EUR,153554,EX,PT,Netherlands,S,Poland,100,"Deep Learning, AWS, Data Visualization, TensorFlow",Master,17,Real Estate,2024-07-31,2024-09-30,2331,7.9,Neural Networks Co -AI14258,Research Scientist,51128,EUR,43459,EN,FT,Germany,M,Germany,0,"SQL, Kubernetes, MLOps, GCP, Azure",Bachelor,0,Government,2024-09-23,2024-11-20,1099,6.9,Digital Transformation LLC -AI14259,Computer Vision Engineer,129737,EUR,110276,SE,FL,Austria,L,Austria,50,"Scala, Git, Kubernetes, TensorFlow, Python",PhD,9,Healthcare,2025-01-09,2025-02-11,1980,8.9,Autonomous Tech -AI14260,Machine Learning Researcher,81423,SGD,105850,EN,CT,Singapore,L,Canada,100,"Python, Kubernetes, Deep Learning, Docker",Associate,1,Healthcare,2024-11-20,2025-01-16,2142,5.5,Autonomous Tech -AI14261,Data Engineer,171399,CHF,154259,MI,FL,Switzerland,L,Poland,0,"PyTorch, SQL, TensorFlow, Tableau, Computer Vision",Master,2,Energy,2024-08-30,2024-11-02,1386,7.1,Algorithmic Solutions -AI14262,Principal Data Scientist,299540,USD,299540,EX,CT,Norway,L,Norway,100,"Spark, Linux, Data Visualization, Scala, PyTorch",PhD,16,Media,2024-07-29,2024-09-12,971,6.9,Machine Intelligence Group -AI14263,ML Ops Engineer,23079,USD,23079,MI,FL,India,S,India,50,"TensorFlow, Tableau, PyTorch",Associate,2,Real Estate,2024-12-15,2025-01-01,1015,6.9,Predictive Systems -AI14264,AI Software Engineer,160236,USD,160236,MI,PT,Norway,L,Mexico,0,"Deep Learning, Git, Kubernetes, Azure, Java",Associate,2,Gaming,2024-08-23,2024-10-26,2377,6.8,Machine Intelligence Group -AI14265,Machine Learning Researcher,75808,USD,75808,EN,FT,Sweden,L,Sweden,100,"Tableau, MLOps, Kubernetes, Hadoop, Azure",Associate,1,Media,2024-03-28,2024-05-31,1175,8.2,Future Systems -AI14266,Machine Learning Engineer,109582,USD,109582,MI,PT,Finland,L,Russia,50,"Computer Vision, Python, Java, R",PhD,3,Consulting,2025-01-10,2025-02-28,1714,8.8,Smart Analytics -AI14267,Robotics Engineer,85941,CAD,107426,MI,PT,Canada,M,Canada,0,"Scala, R, Data Visualization, Linux",Associate,2,Automotive,2025-01-17,2025-02-16,1525,7.9,DeepTech Ventures -AI14268,Computer Vision Engineer,160982,SGD,209277,SE,CT,Singapore,L,Turkey,100,"SQL, Azure, Statistics",Associate,5,Healthcare,2025-04-10,2025-05-05,642,9.5,Cognitive Computing -AI14269,AI Specialist,111319,GBP,83489,SE,CT,United Kingdom,S,United Kingdom,0,"Java, Azure, AWS, Spark, TensorFlow",Bachelor,7,Healthcare,2024-12-20,2025-02-26,913,8.1,TechCorp Inc -AI14270,NLP Engineer,99974,EUR,84978,SE,FT,France,M,France,0,"Python, Computer Vision, Tableau, Scala, Azure",Master,9,Finance,2024-01-11,2024-03-02,1351,8.9,TechCorp Inc -AI14271,AI Research Scientist,103001,CAD,128751,MI,PT,Canada,M,Finland,50,"Java, Kubernetes, PyTorch",Bachelor,4,Retail,2024-12-17,2025-01-01,963,9.7,Neural Networks Co -AI14272,AI Software Engineer,207251,EUR,176163,EX,PT,Austria,S,United States,100,"PyTorch, Computer Vision, Python, TensorFlow",Master,11,Technology,2024-08-17,2024-10-18,1504,9.1,Cloud AI Solutions -AI14273,ML Ops Engineer,65060,USD,65060,EN,FT,Finland,L,Finland,0,"AWS, Data Visualization, Hadoop",Master,1,Media,2025-03-15,2025-04-09,1904,7.6,TechCorp Inc -AI14274,AI Consultant,90343,EUR,76792,MI,CT,Austria,M,Austria,50,"Python, TensorFlow, Git",Master,3,Gaming,2024-05-26,2024-07-10,1702,6.8,Neural Networks Co -AI14275,AI Specialist,99304,USD,99304,SE,PT,Israel,M,Poland,50,"PyTorch, Git, Kubernetes",Bachelor,7,Manufacturing,2025-03-15,2025-04-23,1905,6.7,Machine Intelligence Group -AI14276,Robotics Engineer,79942,USD,79942,EN,PT,Sweden,M,Sweden,50,"Computer Vision, SQL, Kubernetes, Docker",PhD,1,Education,2024-10-29,2025-01-07,1330,9.8,Smart Analytics -AI14277,Computer Vision Engineer,105304,GBP,78978,SE,PT,United Kingdom,S,United Kingdom,50,"Azure, Linux, Hadoop, Mathematics, Kubernetes",Associate,8,Manufacturing,2025-01-18,2025-02-23,619,8.7,Future Systems -AI14278,Data Engineer,118101,USD,118101,SE,FL,Finland,M,Denmark,50,"TensorFlow, Spark, Statistics, Linux, AWS",Associate,7,Gaming,2024-11-06,2025-01-06,1101,5,Cloud AI Solutions -AI14279,AI Product Manager,64827,USD,64827,SE,FL,China,L,China,0,"Scala, Python, MLOps, Hadoop",Master,8,Finance,2025-02-11,2025-03-16,855,9.2,Algorithmic Solutions -AI14280,Head of AI,136792,USD,136792,MI,FL,Norway,L,United Kingdom,0,"Hadoop, Azure, Statistics",Master,4,Education,2024-11-15,2025-01-23,2468,8.3,Smart Analytics -AI14281,Deep Learning Engineer,125716,EUR,106859,SE,FL,France,L,France,0,"SQL, Python, Java, NLP, Spark",PhD,8,Education,2024-12-05,2025-01-07,1744,7.8,Algorithmic Solutions -AI14282,ML Ops Engineer,74299,USD,74299,EN,CT,Sweden,M,Sweden,0,"Java, Python, NLP",PhD,0,Consulting,2024-02-26,2024-05-05,2071,9.9,Digital Transformation LLC -AI14283,Machine Learning Engineer,279034,USD,279034,EX,FL,United States,L,Egypt,0,"Computer Vision, GCP, MLOps, NLP",Associate,19,Consulting,2024-09-05,2024-10-30,1323,6.5,Digital Transformation LLC -AI14284,Data Scientist,84474,GBP,63356,EN,FL,United Kingdom,M,United Kingdom,0,"Spark, NLP, TensorFlow",Associate,1,Education,2024-01-08,2024-02-02,1232,5.6,Neural Networks Co -AI14285,NLP Engineer,105225,USD,105225,EX,FL,China,L,Mexico,0,"MLOps, Azure, Kubernetes, NLP",Bachelor,17,Media,2024-02-17,2024-04-30,2011,9.9,Algorithmic Solutions -AI14286,Machine Learning Researcher,140938,USD,140938,SE,PT,South Korea,L,Romania,0,"Docker, Linux, Hadoop, NLP, R",PhD,6,Healthcare,2025-03-26,2025-05-04,804,7.2,TechCorp Inc -AI14287,Autonomous Systems Engineer,51274,USD,51274,EN,FT,South Korea,L,South Korea,50,"GCP, Azure, AWS, Deep Learning, Mathematics",Master,1,Technology,2024-10-08,2024-11-14,1708,9.1,DeepTech Ventures -AI14288,Data Scientist,78815,JPY,8669650,MI,PT,Japan,S,Japan,100,"Computer Vision, Java, NLP, Mathematics, Linux",PhD,3,Telecommunications,2024-04-07,2024-05-18,2219,9.4,Cloud AI Solutions -AI14289,Robotics Engineer,62675,USD,62675,EN,PT,Israel,L,Israel,50,"MLOps, Git, GCP",Associate,1,Healthcare,2025-01-10,2025-02-13,767,5.8,DeepTech Ventures -AI14290,Head of AI,44043,USD,44043,SE,FL,India,S,India,50,"Kubernetes, Scala, GCP, Python",Master,8,Media,2025-02-10,2025-04-17,1249,9.5,DataVision Ltd -AI14291,Machine Learning Engineer,91908,GBP,68931,MI,PT,United Kingdom,S,United Kingdom,100,"Data Visualization, Kubernetes, GCP, Scala",PhD,2,Real Estate,2024-06-08,2024-07-23,1802,9.7,DataVision Ltd -AI14292,Machine Learning Researcher,161960,EUR,137666,EX,CT,Austria,M,Austria,0,"Docker, Java, MLOps",PhD,14,Telecommunications,2024-10-31,2024-11-15,633,9.2,Future Systems -AI14293,AI Product Manager,59982,USD,59982,EN,FL,Israel,S,Indonesia,0,"AWS, Kubernetes, SQL, GCP, Data Visualization",PhD,0,Energy,2024-11-03,2024-12-06,1024,5.5,Neural Networks Co -AI14294,Data Analyst,73332,USD,73332,MI,FT,Israel,S,Malaysia,100,"Data Visualization, Statistics, Spark, Tableau",Associate,3,Energy,2024-01-17,2024-03-26,1881,6.4,Advanced Robotics -AI14295,Machine Learning Engineer,235865,USD,235865,EX,FT,Israel,M,Israel,0,"Hadoop, Linux, Kubernetes",PhD,17,Telecommunications,2024-12-15,2025-02-16,1931,7.2,DeepTech Ventures -AI14296,Computer Vision Engineer,62646,EUR,53249,EN,CT,France,L,Japan,50,"Hadoop, Statistics, Git",Bachelor,0,Government,2024-05-03,2024-05-21,2160,8.5,Autonomous Tech -AI14297,ML Ops Engineer,81857,USD,81857,MI,PT,United States,S,Finland,0,"TensorFlow, Linux, Python, Hadoop",Associate,2,Government,2025-03-31,2025-05-26,2393,9.2,Quantum Computing Inc -AI14298,Computer Vision Engineer,98405,AUD,132847,MI,PT,Australia,S,Denmark,0,"PyTorch, Computer Vision, Kubernetes, GCP, AWS",Master,4,Telecommunications,2025-02-17,2025-03-20,2240,8,Cognitive Computing -AI14299,Principal Data Scientist,52393,USD,52393,EN,FL,Sweden,S,Thailand,0,"Python, Kubernetes, TensorFlow",PhD,0,Transportation,2024-10-06,2024-11-27,969,9.3,Neural Networks Co -AI14300,Computer Vision Engineer,51076,USD,51076,EN,FL,Ireland,S,Ireland,0,"PyTorch, Deep Learning, SQL, GCP",Associate,0,Retail,2025-03-16,2025-05-19,1948,5.6,Quantum Computing Inc -AI14301,Data Engineer,109859,CHF,98873,EN,FT,Switzerland,L,Switzerland,0,"Mathematics, Scala, Tableau",Bachelor,0,Energy,2024-07-10,2024-09-16,620,7.6,DataVision Ltd -AI14302,Machine Learning Researcher,140133,SGD,182173,SE,PT,Singapore,S,Poland,50,"Scala, Java, Docker",Master,9,Healthcare,2024-05-15,2024-06-10,1824,8.6,Autonomous Tech -AI14303,Head of AI,233979,USD,233979,EX,FT,United States,S,United States,50,"MLOps, R, GCP, Linux",Bachelor,19,Gaming,2024-08-06,2024-10-18,1936,7.7,Quantum Computing Inc -AI14304,AI Architect,61640,EUR,52394,EN,FL,France,S,France,100,"Java, PyTorch, Azure",Associate,1,Manufacturing,2025-01-26,2025-03-09,1512,7.2,Advanced Robotics -AI14305,NLP Engineer,162855,EUR,138427,SE,PT,Germany,L,Germany,100,"Python, Spark, TensorFlow, Statistics, Git",Master,8,Healthcare,2024-11-29,2025-01-24,1320,5.5,Quantum Computing Inc -AI14306,Autonomous Systems Engineer,102016,EUR,86714,MI,FT,Austria,L,Austria,0,"Azure, Git, Python, Linux",Bachelor,2,Consulting,2024-04-10,2024-05-10,1178,7.1,AI Innovations -AI14307,Data Scientist,65504,CAD,81880,EN,PT,Canada,L,Canada,100,"Docker, Data Visualization, Tableau, TensorFlow, Mathematics",Associate,0,Technology,2024-12-08,2025-02-10,678,5.2,Digital Transformation LLC -AI14308,AI Product Manager,75588,USD,75588,MI,FT,South Korea,S,South Korea,0,"GCP, R, NLP",Bachelor,4,Technology,2024-04-17,2024-05-28,1720,8,TechCorp Inc -AI14309,AI Architect,112458,CAD,140573,SE,FL,Canada,M,Canada,50,"Docker, Computer Vision, PyTorch",Associate,6,Education,2024-01-23,2024-03-11,1021,8.7,Cloud AI Solutions -AI14310,Computer Vision Engineer,124536,EUR,105856,EX,PT,Austria,S,Denmark,100,"TensorFlow, Deep Learning, Data Visualization, Computer Vision, Java",PhD,10,Media,2024-10-01,2024-11-07,550,9.6,Cognitive Computing -AI14311,Head of AI,175373,EUR,149067,EX,FL,Germany,L,Germany,50,"Statistics, PyTorch, Deep Learning",Master,17,Transportation,2024-07-03,2024-08-29,1193,10,Neural Networks Co -AI14312,AI Architect,116773,USD,116773,MI,CT,Ireland,L,Argentina,100,"Java, Hadoop, MLOps",PhD,3,Finance,2024-11-21,2024-12-26,502,6.2,Smart Analytics -AI14313,Machine Learning Engineer,81273,EUR,69082,EN,CT,Netherlands,M,Japan,0,"R, SQL, NLP, Git, GCP",Master,0,Media,2024-07-06,2024-08-16,862,9.9,Predictive Systems -AI14314,Machine Learning Engineer,90934,USD,90934,MI,PT,United States,S,United States,50,"Linux, GCP, Statistics, Deep Learning",Master,2,Manufacturing,2024-09-10,2024-10-19,2041,6.1,DataVision Ltd -AI14315,Computer Vision Engineer,141213,SGD,183577,SE,FL,Singapore,S,Philippines,100,"AWS, Python, Statistics, TensorFlow",PhD,9,Telecommunications,2024-07-23,2024-08-26,661,6.1,Cognitive Computing -AI14316,Head of AI,275394,SGD,358012,EX,FL,Singapore,L,Romania,100,"Python, Spark, Git, TensorFlow",Bachelor,18,Healthcare,2024-05-24,2024-07-29,874,6.6,Digital Transformation LLC -AI14317,Principal Data Scientist,107900,CAD,134875,SE,PT,Canada,S,Canada,0,"PyTorch, Azure, Spark",Bachelor,6,Government,2025-01-04,2025-01-19,1643,6,Future Systems -AI14318,Research Scientist,94985,JPY,10448350,EN,FT,Japan,L,Germany,100,"Python, Git, Deep Learning, PyTorch",PhD,1,Transportation,2024-03-03,2024-03-23,675,7.4,Autonomous Tech -AI14319,Computer Vision Engineer,123657,JPY,13602270,SE,FL,Japan,M,Italy,0,"Git, PyTorch, TensorFlow",PhD,8,Transportation,2024-06-07,2024-07-05,1062,8.8,Cloud AI Solutions -AI14320,AI Specialist,18446,USD,18446,EN,FL,India,S,India,100,"PyTorch, Scala, Git, NLP",Master,1,Transportation,2024-01-03,2024-02-01,2179,7.4,TechCorp Inc -AI14321,Robotics Engineer,125558,USD,125558,EX,FL,China,L,Romania,50,"Spark, MLOps, SQL, Hadoop",Bachelor,14,Technology,2024-04-09,2024-04-23,1998,7,DataVision Ltd -AI14322,Data Engineer,55209,EUR,46928,EN,FT,France,L,France,0,"Deep Learning, Kubernetes, Git, Statistics",Bachelor,1,Media,2024-12-14,2025-01-29,1887,6.6,Algorithmic Solutions -AI14323,AI Research Scientist,233676,EUR,198625,EX,FL,France,L,France,50,"SQL, Hadoop, PyTorch, Tableau",PhD,11,Manufacturing,2024-04-26,2024-07-01,2101,6.6,Cognitive Computing -AI14324,Principal Data Scientist,30081,USD,30081,MI,FT,India,L,India,0,"SQL, Git, Docker",PhD,2,Education,2024-09-03,2024-10-21,2325,5.8,Autonomous Tech -AI14325,Robotics Engineer,155252,EUR,131964,EX,CT,Austria,M,Austria,50,"Kubernetes, Hadoop, Spark, Docker, Git",Associate,11,Real Estate,2024-01-24,2024-03-31,1042,9.8,Predictive Systems -AI14326,Machine Learning Researcher,132368,CAD,165460,SE,FT,Canada,M,Canada,100,"SQL, Git, Data Visualization, Java, Spark",Master,7,Finance,2025-02-24,2025-04-04,1828,5.2,DeepTech Ventures -AI14327,Computer Vision Engineer,84373,USD,84373,MI,CT,South Korea,M,South Korea,0,"SQL, Computer Vision, Kubernetes, MLOps, Python",PhD,2,Telecommunications,2024-07-26,2024-10-07,2348,6.8,Digital Transformation LLC -AI14328,AI Architect,264528,USD,264528,EX,CT,Denmark,M,Denmark,100,"GCP, Linux, Computer Vision",Associate,11,Gaming,2024-09-15,2024-11-27,2001,7.5,AI Innovations -AI14329,Data Engineer,29715,USD,29715,EN,CT,India,L,India,0,"Mathematics, Scala, Python, AWS, Data Visualization",PhD,0,Automotive,2025-04-06,2025-06-07,2490,9.3,Advanced Robotics -AI14330,AI Specialist,164165,EUR,139540,SE,CT,Germany,L,Germany,50,"Java, MLOps, Linux, Deep Learning",Bachelor,9,Consulting,2024-01-14,2024-02-05,1341,9.4,TechCorp Inc -AI14331,Research Scientist,223621,USD,223621,EX,FL,Denmark,L,Czech Republic,0,"Scala, Tableau, Kubernetes, R",PhD,11,Manufacturing,2024-12-14,2025-02-06,705,6,Neural Networks Co -AI14332,AI Architect,226374,SGD,294286,EX,FL,Singapore,S,Singapore,100,"Kubernetes, Python, Data Visualization",Bachelor,16,Finance,2024-01-11,2024-03-22,1812,8.8,AI Innovations -AI14333,Machine Learning Engineer,76615,USD,76615,EN,FT,Sweden,M,Norway,50,"Scala, Tableau, R, Azure, Linux",Master,0,Gaming,2024-08-01,2024-08-20,1375,5.9,Algorithmic Solutions -AI14334,AI Consultant,85551,CHF,76996,EN,PT,Switzerland,L,Switzerland,100,"PyTorch, Linux, TensorFlow",Master,0,Telecommunications,2024-12-19,2025-01-18,2033,8.9,TechCorp Inc -AI14335,AI Consultant,156675,GBP,117506,EX,FT,United Kingdom,M,France,50,"Hadoop, Scala, Linux, Computer Vision",Master,18,Finance,2024-09-03,2024-10-07,1584,9,Predictive Systems -AI14336,Principal Data Scientist,55271,EUR,46980,EN,FL,France,M,France,50,"Git, TensorFlow, PyTorch, Scala",Bachelor,0,Finance,2024-05-15,2024-06-11,1717,8.4,Cloud AI Solutions -AI14337,AI Software Engineer,166389,USD,166389,EX,FL,Finland,M,Ghana,50,"R, Python, Hadoop",Bachelor,12,Retail,2025-03-11,2025-04-15,2042,7.1,Predictive Systems -AI14338,NLP Engineer,82549,SGD,107314,EN,FL,Singapore,L,United States,0,"MLOps, Azure, Kubernetes, Tableau, Docker",Master,1,Consulting,2025-01-21,2025-03-24,1901,6.8,Smart Analytics -AI14339,Principal Data Scientist,76753,GBP,57565,EN,CT,United Kingdom,M,United Kingdom,0,"Python, TensorFlow, PyTorch",Master,1,Real Estate,2024-02-20,2024-04-02,975,9.2,Neural Networks Co -AI14340,AI Research Scientist,73157,EUR,62183,MI,PT,Netherlands,S,Netherlands,50,"Scala, SQL, Data Visualization, GCP, PyTorch",PhD,4,Finance,2025-01-21,2025-03-29,678,8,Cognitive Computing -AI14341,Data Analyst,116897,USD,116897,SE,FL,South Korea,M,Belgium,100,"PyTorch, TensorFlow, Git, GCP, Linux",PhD,6,Retail,2024-11-19,2025-01-26,1136,6.6,Future Systems -AI14342,AI Software Engineer,130794,USD,130794,SE,FL,Finland,L,Vietnam,0,"Python, AWS, Statistics, Computer Vision",PhD,9,Media,2024-08-25,2024-10-23,1247,8.4,DataVision Ltd -AI14343,Deep Learning Engineer,102032,JPY,11223520,MI,FL,Japan,M,Japan,100,"Kubernetes, Computer Vision, AWS, Azure",Associate,4,Healthcare,2025-01-30,2025-03-25,2399,8.4,AI Innovations -AI14344,AI Product Manager,142857,EUR,121428,SE,FT,Austria,L,South Africa,50,"SQL, Python, AWS, Java, TensorFlow",PhD,7,Consulting,2024-03-29,2024-05-11,2479,9.5,Cognitive Computing -AI14345,AI Research Scientist,187842,SGD,244195,EX,PT,Singapore,M,Singapore,50,"Hadoop, TensorFlow, Computer Vision, MLOps",PhD,14,Media,2025-01-24,2025-02-10,1075,7.9,Neural Networks Co -AI14346,AI Research Scientist,157194,SGD,204352,EX,FL,Singapore,S,Poland,100,"Python, Java, SQL",Bachelor,17,Automotive,2025-01-20,2025-02-05,2120,5.7,Cloud AI Solutions -AI14347,Deep Learning Engineer,104641,EUR,88945,MI,CT,Netherlands,S,Belgium,0,"SQL, Git, Kubernetes",Master,4,Transportation,2025-03-17,2025-04-25,2022,9.4,Advanced Robotics -AI14348,Machine Learning Engineer,70047,USD,70047,EN,CT,United States,S,Indonesia,100,"Deep Learning, Scala, AWS",Master,1,Manufacturing,2024-07-12,2024-08-14,1560,6.3,Algorithmic Solutions -AI14349,AI Consultant,174437,USD,174437,SE,CT,Norway,S,Egypt,0,"AWS, Docker, SQL, Git, Scala",Associate,5,Energy,2024-02-12,2024-04-05,1526,8.2,Algorithmic Solutions -AI14350,Head of AI,291903,AUD,394069,EX,FT,Australia,L,Australia,50,"Statistics, Scala, Deep Learning, Data Visualization, Mathematics",Bachelor,17,Government,2024-10-26,2024-11-10,2021,8.3,Machine Intelligence Group -AI14351,Data Engineer,257612,USD,257612,EX,CT,United States,S,Japan,50,"R, Deep Learning, Azure",Associate,19,Telecommunications,2024-04-01,2024-05-13,1277,9.2,Cloud AI Solutions -AI14352,ML Ops Engineer,138666,USD,138666,MI,FT,Norway,M,India,50,"Linux, Data Visualization, TensorFlow, Mathematics",Master,2,Telecommunications,2024-12-07,2025-02-04,1782,6.3,Cognitive Computing -AI14353,Autonomous Systems Engineer,139390,SGD,181207,SE,PT,Singapore,M,Singapore,50,"Python, TensorFlow, PyTorch, Azure, Linux",PhD,9,Retail,2025-01-21,2025-04-03,2156,9,Cloud AI Solutions -AI14354,Data Engineer,137009,EUR,116458,SE,CT,Austria,L,Austria,100,"Java, Spark, Computer Vision",Associate,9,Gaming,2024-03-21,2024-04-25,1105,9.6,Advanced Robotics -AI14355,AI Architect,154759,USD,154759,EX,FL,Ireland,M,Ireland,100,"SQL, PyTorch, GCP",Bachelor,17,Automotive,2024-04-06,2024-05-03,1786,7.4,Cognitive Computing -AI14356,Data Engineer,132746,SGD,172570,SE,CT,Singapore,M,Sweden,100,"Python, NLP, TensorFlow, PyTorch, Git",PhD,6,Technology,2024-02-14,2024-03-01,2443,7.7,Neural Networks Co -AI14357,Data Engineer,100856,GBP,75642,MI,FT,United Kingdom,L,United Kingdom,100,"SQL, Kubernetes, Deep Learning, Python",PhD,3,Government,2024-02-16,2024-04-09,763,8,AI Innovations -AI14358,Machine Learning Engineer,49761,GBP,37321,EN,FL,United Kingdom,S,Romania,50,"R, Tableau, SQL",Master,0,Education,2024-02-02,2024-02-23,1476,5.9,DeepTech Ventures -AI14359,Research Scientist,77665,GBP,58249,EN,CT,United Kingdom,L,United Kingdom,0,"Python, TensorFlow, Deep Learning, Hadoop",PhD,0,Education,2024-01-08,2024-02-20,654,7.7,Digital Transformation LLC -AI14360,Data Scientist,71610,USD,71610,EN,FT,Ireland,L,Italy,0,"Spark, AWS, SQL",PhD,0,Finance,2024-09-20,2024-10-13,1560,5.9,Cloud AI Solutions -AI14361,Head of AI,57686,CAD,72108,EN,FT,Canada,M,Canada,100,"Git, Mathematics, SQL, TensorFlow, Computer Vision",Master,1,Energy,2024-06-11,2024-08-06,2351,8.3,Smart Analytics -AI14362,Machine Learning Researcher,131219,EUR,111536,SE,CT,Netherlands,M,Netherlands,50,"Docker, PyTorch, Azure, Hadoop, TensorFlow",Master,6,Transportation,2024-06-12,2024-07-12,1918,7.8,Cognitive Computing -AI14363,Robotics Engineer,104036,AUD,140449,MI,FT,Australia,M,Australia,100,"Kubernetes, Computer Vision, NLP",Bachelor,3,Media,2024-12-11,2025-02-06,1735,7.2,Smart Analytics -AI14364,NLP Engineer,154548,USD,154548,EX,FT,Finland,L,India,50,"PyTorch, TensorFlow, Java",Master,18,Retail,2024-02-04,2024-03-05,1766,8.9,Autonomous Tech -AI14365,ML Ops Engineer,189083,USD,189083,EX,PT,Sweden,L,Sweden,50,"SQL, Linux, Statistics, Hadoop",PhD,19,Healthcare,2024-10-27,2024-11-11,1412,7.5,TechCorp Inc -AI14366,Head of AI,107559,USD,107559,SE,PT,Sweden,S,Sweden,0,"Azure, Kubernetes, Mathematics, Docker",Associate,6,Energy,2024-03-13,2024-05-05,1206,8.8,Quantum Computing Inc -AI14367,Machine Learning Engineer,197070,CAD,246338,EX,FT,Canada,S,Canada,100,"PyTorch, Hadoop, Python, Git",Bachelor,10,Government,2024-07-20,2024-09-10,1688,10,Digital Transformation LLC -AI14368,Data Analyst,158181,CAD,197726,SE,PT,Canada,L,Egypt,0,"Linux, R, MLOps",Bachelor,8,Telecommunications,2024-04-26,2024-06-18,799,6.6,Cloud AI Solutions -AI14369,Data Analyst,118102,EUR,100387,SE,FL,France,S,France,100,"R, Mathematics, Scala, Statistics",Bachelor,9,Healthcare,2024-04-13,2024-05-05,1809,6.9,AI Innovations -AI14370,Data Engineer,112990,USD,112990,MI,CT,Norway,S,Norway,0,"Linux, Java, PyTorch, Git, MLOps",Master,4,Transportation,2025-04-02,2025-04-26,2482,6.6,AI Innovations -AI14371,ML Ops Engineer,147657,JPY,16242270,EX,PT,Japan,M,Japan,50,"Spark, MLOps, Azure, SQL, Docker",Master,11,Education,2024-05-16,2024-06-25,1666,5.6,Machine Intelligence Group -AI14372,Machine Learning Engineer,145533,EUR,123703,SE,PT,Netherlands,M,China,100,"Python, TensorFlow, Docker",Associate,6,Education,2024-01-10,2024-02-28,730,7.6,Cognitive Computing -AI14373,Data Scientist,128282,USD,128282,MI,CT,Denmark,M,Russia,0,"Python, Scala, SQL",Bachelor,2,Retail,2024-10-04,2024-10-24,1809,8.2,DataVision Ltd -AI14374,Principal Data Scientist,118956,EUR,101113,SE,PT,Germany,L,Germany,50,"NLP, Deep Learning, Kubernetes",PhD,9,Consulting,2024-12-07,2024-12-30,1671,7.2,Future Systems -AI14375,AI Consultant,64457,USD,64457,EX,FT,China,M,China,50,"R, Python, Linux, Docker, MLOps",Bachelor,12,Finance,2024-08-06,2024-09-15,2061,6.6,DeepTech Ventures -AI14376,ML Ops Engineer,75849,EUR,64472,EN,CT,Netherlands,M,Netherlands,100,"Data Visualization, TensorFlow, Deep Learning, Tableau, Hadoop",Master,0,Automotive,2024-03-01,2024-03-23,1079,5.1,Neural Networks Co -AI14377,Data Engineer,137657,USD,137657,EX,FT,China,L,New Zealand,0,"Docker, Data Visualization, Tableau, R",Bachelor,18,Media,2024-10-31,2024-12-05,1668,7.7,Predictive Systems -AI14378,Robotics Engineer,144216,USD,144216,SE,PT,Sweden,M,Sweden,0,"Git, GCP, Tableau, PyTorch, Java",Bachelor,6,Consulting,2024-11-17,2025-01-07,2242,7.7,Cognitive Computing -AI14379,AI Consultant,113094,SGD,147022,SE,PT,Singapore,M,Singapore,0,"NLP, Kubernetes, GCP",Bachelor,5,Gaming,2024-07-30,2024-10-11,2205,5.1,Future Systems -AI14380,Data Engineer,138816,GBP,104112,SE,FT,United Kingdom,S,United Kingdom,100,"Data Visualization, R, Python",Bachelor,7,Gaming,2024-12-11,2025-02-10,1227,9.5,Cloud AI Solutions -AI14381,AI Research Scientist,105524,EUR,89695,SE,FT,France,S,France,50,"Python, Data Visualization, GCP, Mathematics",Bachelor,5,Telecommunications,2024-06-11,2024-08-17,1248,6.9,Future Systems -AI14382,Machine Learning Engineer,235370,JPY,25890700,EX,CT,Japan,L,Estonia,50,"Python, Azure, SQL, Spark, AWS",Master,19,Automotive,2024-02-07,2024-03-18,960,8.3,DataVision Ltd -AI14383,Machine Learning Engineer,53545,USD,53545,EN,FT,Finland,M,Finland,0,"Docker, Linux, Computer Vision",Master,0,Retail,2025-01-24,2025-03-25,520,9.6,Quantum Computing Inc -AI14384,Principal Data Scientist,246044,AUD,332159,EX,FL,Australia,L,Australia,50,"Statistics, R, Kubernetes, PyTorch",Master,10,Transportation,2024-04-06,2024-05-07,1758,5.3,TechCorp Inc -AI14385,Machine Learning Engineer,79749,EUR,67787,MI,FL,Austria,S,Austria,100,"Deep Learning, Data Visualization, Java, Tableau",Bachelor,3,Healthcare,2025-04-16,2025-06-05,2163,7.1,Digital Transformation LLC -AI14386,AI Product Manager,45513,USD,45513,MI,FL,China,S,China,50,"GCP, Spark, PyTorch, MLOps",PhD,2,Education,2024-11-09,2024-12-03,1131,9.9,Machine Intelligence Group -AI14387,ML Ops Engineer,147346,SGD,191550,SE,FT,Singapore,L,Singapore,50,"Kubernetes, Azure, Linux, Statistics, Spark",Associate,8,Telecommunications,2024-04-09,2024-05-03,1332,9.2,Advanced Robotics -AI14388,Autonomous Systems Engineer,96801,EUR,82281,MI,FL,Austria,M,Romania,50,"Statistics, PyTorch, Azure, Spark",Master,4,Government,2024-03-22,2024-05-26,616,7.2,Cognitive Computing -AI14389,Data Scientist,112083,USD,112083,MI,CT,Ireland,L,Ireland,50,"Tableau, SQL, Kubernetes, PyTorch",Bachelor,3,Transportation,2024-07-26,2024-09-25,1774,5.2,Advanced Robotics -AI14390,Computer Vision Engineer,119874,AUD,161830,MI,PT,Australia,L,Australia,50,"Git, PyTorch, Tableau, AWS",Bachelor,2,Healthcare,2025-04-12,2025-05-20,681,5.9,Advanced Robotics -AI14391,AI Product Manager,37440,USD,37440,SE,FT,India,M,India,0,"SQL, PyTorch, R, Statistics",Bachelor,5,Consulting,2024-07-03,2024-08-02,1668,8.8,Cognitive Computing -AI14392,AI Software Engineer,156018,USD,156018,SE,PT,United States,S,United States,100,"Spark, TensorFlow, Computer Vision",Master,7,Education,2024-01-01,2024-02-28,1438,8.6,Future Systems -AI14393,AI Architect,77323,USD,77323,MI,FT,Finland,S,Finland,100,"MLOps, AWS, GCP, Spark, Tableau",Master,3,Consulting,2024-03-05,2024-04-12,2405,7,Predictive Systems -AI14394,Machine Learning Researcher,157671,USD,157671,EX,PT,South Korea,S,South Korea,0,"GCP, R, Kubernetes",Master,11,Real Estate,2024-10-13,2024-11-17,1026,7.5,Digital Transformation LLC -AI14395,Deep Learning Engineer,107434,SGD,139664,MI,FT,Singapore,M,Singapore,50,"Hadoop, Docker, AWS, PyTorch",PhD,3,Energy,2024-07-25,2024-09-19,2130,7.5,Cloud AI Solutions -AI14396,Robotics Engineer,69805,EUR,59334,MI,FT,France,M,France,50,"SQL, Data Visualization, Azure, Spark",PhD,2,Media,2024-10-02,2024-10-16,1607,9.8,Advanced Robotics -AI14397,AI Research Scientist,80668,EUR,68568,MI,FL,Austria,L,Austria,100,"Hadoop, Tableau, SQL, NLP",PhD,4,Consulting,2025-02-06,2025-04-05,594,6,Digital Transformation LLC -AI14398,Head of AI,140967,EUR,119822,EX,FT,Germany,M,Philippines,100,"Data Visualization, R, SQL",Master,11,Finance,2024-04-10,2024-04-29,1541,6.4,Algorithmic Solutions -AI14399,Principal Data Scientist,112216,USD,112216,SE,PT,Sweden,M,Belgium,0,"Python, TensorFlow, Docker",Master,7,Real Estate,2024-08-12,2024-09-20,1853,7.9,TechCorp Inc -AI14400,Autonomous Systems Engineer,210828,JPY,23191080,EX,PT,Japan,S,Japan,50,"SQL, Python, R",Bachelor,19,Healthcare,2025-04-16,2025-06-28,2384,6.5,TechCorp Inc -AI14401,Principal Data Scientist,44332,USD,44332,SE,FL,India,S,India,0,"Git, MLOps, Tableau, Kubernetes, Computer Vision",Master,9,Manufacturing,2024-08-28,2024-09-21,942,9.8,AI Innovations -AI14402,Data Engineer,68896,EUR,58562,EN,FL,France,M,France,50,"Computer Vision, SQL, Kubernetes, Linux",Bachelor,1,Education,2024-09-01,2024-11-04,847,8,Future Systems -AI14403,Data Scientist,165554,CHF,148999,MI,FL,Switzerland,L,Netherlands,50,"SQL, Kubernetes, MLOps, Hadoop",Bachelor,4,Consulting,2024-06-05,2024-06-19,1740,8.3,Digital Transformation LLC -AI14404,AI Architect,114670,USD,114670,MI,PT,Denmark,S,Denmark,100,"Python, TensorFlow, MLOps, Docker",PhD,4,Government,2024-05-19,2024-06-09,1820,9.2,Algorithmic Solutions -AI14405,Data Analyst,97405,JPY,10714550,EN,PT,Japan,L,Ireland,50,"Spark, Linux, Data Visualization, Git",Master,1,Energy,2024-05-02,2024-06-27,2381,7.8,DataVision Ltd -AI14406,AI Specialist,92003,EUR,78203,SE,PT,France,S,Hungary,0,"SQL, Linux, Scala, Docker, Kubernetes",Master,8,Consulting,2024-07-03,2024-07-28,1265,6.2,Digital Transformation LLC -AI14407,Principal Data Scientist,85732,USD,85732,EN,FT,Denmark,S,Denmark,0,"Scala, Computer Vision, R, SQL",Master,0,Healthcare,2024-07-01,2024-08-01,2168,9,DataVision Ltd -AI14408,Data Analyst,158515,EUR,134738,EX,FT,Netherlands,M,Netherlands,50,"Java, Spark, Data Visualization, MLOps, Mathematics",PhD,16,Consulting,2024-08-10,2024-09-21,1073,8.2,Predictive Systems -AI14409,AI Specialist,119601,USD,119601,SE,CT,Sweden,M,Sweden,50,"Python, Hadoop, Data Visualization, Docker, Computer Vision",Associate,9,Consulting,2025-03-05,2025-05-04,1855,5.6,Machine Intelligence Group -AI14410,NLP Engineer,72330,EUR,61481,EN,PT,France,M,France,0,"Computer Vision, GCP, Docker",Bachelor,0,Transportation,2024-02-22,2024-04-01,1518,5.4,Machine Intelligence Group -AI14411,AI Specialist,109208,GBP,81906,SE,PT,United Kingdom,M,United Kingdom,100,"Tableau, Git, GCP, PyTorch",PhD,7,Energy,2024-02-01,2024-02-26,1993,7,Predictive Systems -AI14412,Computer Vision Engineer,59992,USD,59992,EX,PT,India,M,Turkey,100,"NLP, PyTorch, AWS, GCP, Java",Master,11,Consulting,2025-03-26,2025-05-29,901,8,Cognitive Computing -AI14413,Data Scientist,81724,USD,81724,EN,FL,Sweden,L,Sweden,0,"Java, Hadoop, Azure, Computer Vision, Git",PhD,1,Manufacturing,2024-05-20,2024-07-27,1347,8.9,TechCorp Inc -AI14414,Autonomous Systems Engineer,152556,USD,152556,SE,PT,Norway,S,Norway,0,"Deep Learning, SQL, Computer Vision, Scala, Azure",Master,5,Automotive,2025-02-27,2025-03-17,563,5.3,Advanced Robotics -AI14415,AI Consultant,93627,SGD,121715,MI,CT,Singapore,M,Singapore,50,"Data Visualization, TensorFlow, Scala",Bachelor,2,Media,2024-12-22,2025-01-18,2345,6.4,Predictive Systems -AI14416,AI Consultant,368934,USD,368934,EX,PT,Norway,L,Norway,0,"TensorFlow, Azure, PyTorch, Tableau, Python",Associate,12,Energy,2024-11-07,2025-01-03,594,8.8,Smart Analytics -AI14417,ML Ops Engineer,62871,USD,62871,EN,FT,Ireland,M,Thailand,100,"AWS, SQL, Python",Master,1,Media,2025-04-02,2025-04-24,2391,6.5,Machine Intelligence Group -AI14418,AI Software Engineer,163945,SGD,213129,EX,FT,Singapore,M,Germany,100,"GCP, Data Visualization, AWS",Associate,13,Technology,2024-01-10,2024-03-02,2184,8.1,Predictive Systems -AI14419,AI Software Engineer,282346,CHF,254111,EX,PT,Switzerland,S,Ireland,0,"Scala, TensorFlow, AWS, R",Bachelor,18,Finance,2025-02-06,2025-04-10,949,7.3,Neural Networks Co -AI14420,AI Architect,198337,USD,198337,EX,FT,Finland,L,Israel,100,"Kubernetes, Azure, Statistics, Git",Bachelor,17,Real Estate,2024-03-03,2024-03-25,2005,6.5,AI Innovations -AI14421,Data Analyst,75384,USD,75384,SE,FT,China,L,Turkey,50,"Kubernetes, Linux, Data Visualization",Master,9,Consulting,2024-10-06,2024-11-05,1413,9.4,Cloud AI Solutions -AI14422,NLP Engineer,209294,EUR,177900,EX,PT,Germany,M,Germany,100,"R, Python, AWS",Master,17,Energy,2024-10-27,2024-11-25,1635,8.9,Neural Networks Co -AI14423,Robotics Engineer,61021,USD,61021,EN,PT,Israel,M,Israel,100,"Tableau, Azure, Spark, Java",PhD,1,Telecommunications,2025-03-09,2025-04-03,715,6.4,Neural Networks Co -AI14424,AI Software Engineer,132259,GBP,99194,SE,FT,United Kingdom,S,United Kingdom,0,"Python, AWS, Data Visualization, Linux, GCP",Bachelor,8,Media,2024-06-09,2024-07-27,711,9.2,TechCorp Inc -AI14425,AI Specialist,131957,USD,131957,SE,PT,Sweden,S,Sweden,100,"Python, AWS, TensorFlow",PhD,9,Media,2024-09-19,2024-10-08,694,5.3,Machine Intelligence Group -AI14426,Deep Learning Engineer,87003,USD,87003,EN,PT,United States,L,United States,100,"Tableau, Docker, Hadoop, PyTorch, R",Bachelor,0,Education,2024-07-07,2024-08-17,1928,5.9,Smart Analytics -AI14427,AI Product Manager,220540,EUR,187459,EX,CT,Netherlands,S,Netherlands,50,"AWS, Linux, Kubernetes, Statistics, Mathematics",Associate,11,Education,2024-08-16,2024-09-06,1340,10,Algorithmic Solutions -AI14428,Data Analyst,167769,CHF,150992,SE,PT,Switzerland,L,Switzerland,50,"Hadoop, Java, NLP, Mathematics, Deep Learning",Associate,7,Government,2024-01-26,2024-03-16,1036,5.7,Machine Intelligence Group -AI14429,Head of AI,187950,USD,187950,EX,FL,South Korea,S,China,50,"Data Visualization, AWS, TensorFlow, Hadoop, Azure",Associate,19,Gaming,2024-12-24,2025-02-17,920,5.7,DeepTech Ventures -AI14430,ML Ops Engineer,58695,EUR,49891,EN,FT,Germany,S,Singapore,0,"Linux, Kubernetes, NLP, Mathematics",Master,0,Automotive,2024-02-21,2024-03-29,588,7.4,DeepTech Ventures -AI14431,Machine Learning Engineer,265749,USD,265749,EX,CT,Ireland,L,Ireland,0,"PyTorch, Java, MLOps, Scala, Azure",Bachelor,11,Gaming,2024-10-23,2024-11-23,697,8.8,DataVision Ltd -AI14432,Research Scientist,110493,EUR,93919,SE,PT,Germany,S,Germany,100,"R, NLP, Python",PhD,7,Healthcare,2025-01-11,2025-03-17,2345,6.9,Quantum Computing Inc -AI14433,Computer Vision Engineer,20337,USD,20337,EN,FT,India,S,Switzerland,0,"GCP, SQL, PyTorch",PhD,0,Consulting,2025-04-08,2025-05-31,1553,9.3,Algorithmic Solutions -AI14434,Computer Vision Engineer,123983,JPY,13638130,MI,CT,Japan,L,Japan,100,"Python, Kubernetes, Spark, Data Visualization",Associate,2,Gaming,2025-01-20,2025-02-19,830,9.8,Machine Intelligence Group -AI14435,AI Software Engineer,206076,USD,206076,EX,FL,United States,L,United States,0,"GCP, Scala, R",Master,14,Transportation,2025-01-22,2025-02-27,1893,5.4,Predictive Systems -AI14436,Computer Vision Engineer,76678,CAD,95848,MI,FT,Canada,S,Canada,100,"Linux, Deep Learning, Docker, TensorFlow",PhD,4,Media,2024-05-27,2024-07-02,1571,6.1,Autonomous Tech -AI14437,AI Specialist,108696,USD,108696,EX,CT,China,L,China,50,"SQL, Python, Git, Tableau",Associate,13,Education,2024-04-14,2024-05-10,1504,9.3,DataVision Ltd -AI14438,NLP Engineer,124557,CAD,155696,SE,FT,Canada,S,Canada,100,"Scala, PyTorch, SQL, Data Visualization",Associate,9,Technology,2024-10-08,2024-10-26,2225,9.7,Cloud AI Solutions -AI14439,Research Scientist,95689,EUR,81336,MI,PT,Germany,S,South Africa,0,"GCP, Azure, PyTorch, TensorFlow, AWS",Bachelor,4,Transportation,2024-05-16,2024-07-15,1331,7.1,Autonomous Tech -AI14440,AI Specialist,295651,SGD,384346,EX,FT,Singapore,L,Vietnam,0,"Python, GCP, Tableau, TensorFlow, Spark",PhD,15,Telecommunications,2024-10-10,2024-11-30,1805,6.3,DataVision Ltd -AI14441,AI Software Engineer,219218,CAD,274023,EX,PT,Canada,L,Canada,100,"Data Visualization, Scala, Mathematics, Java, AWS",Associate,10,Energy,2025-03-13,2025-04-26,2212,5.1,Predictive Systems -AI14442,Machine Learning Engineer,125323,CAD,156654,SE,CT,Canada,M,Canada,50,"PyTorch, TensorFlow, Scala, AWS, Java",Master,5,Telecommunications,2025-01-23,2025-03-22,1414,6,Smart Analytics -AI14443,Data Scientist,62189,EUR,52861,EN,CT,France,L,Ghana,0,"Python, TensorFlow, Linux, Azure",PhD,0,Healthcare,2025-03-02,2025-03-20,779,9.4,Cognitive Computing -AI14444,Research Scientist,82731,USD,82731,EN,FT,United States,M,Argentina,50,"Spark, MLOps, Scala",Master,1,Finance,2025-02-14,2025-03-10,2269,9.3,Digital Transformation LLC -AI14445,Data Engineer,104548,SGD,135912,SE,CT,Singapore,S,Singapore,100,"Python, TensorFlow, Deep Learning, MLOps",Associate,9,Real Estate,2024-02-06,2024-03-11,1024,6.9,Smart Analytics -AI14446,AI Research Scientist,186864,SGD,242923,EX,CT,Singapore,S,China,0,"Python, TensorFlow, Data Visualization, R",Associate,10,Retail,2024-12-30,2025-02-12,1927,8.8,Advanced Robotics -AI14447,Computer Vision Engineer,90839,CHF,81755,EN,PT,Switzerland,M,Switzerland,50,"Java, Azure, Deep Learning, Scala",PhD,0,Real Estate,2025-03-31,2025-05-22,1877,9,Advanced Robotics -AI14448,AI Consultant,70876,USD,70876,SE,CT,China,L,China,0,"Python, GCP, Git, Deep Learning",PhD,8,Retail,2024-09-18,2024-11-18,1534,8.4,AI Innovations -AI14449,Robotics Engineer,124242,EUR,105606,EX,FT,France,S,Spain,0,"Spark, Git, Python",Associate,13,Consulting,2025-02-17,2025-03-16,919,5.2,Autonomous Tech -AI14450,Deep Learning Engineer,82268,USD,82268,MI,PT,United States,S,United States,100,"R, MLOps, Hadoop, GCP",Master,4,Retail,2025-01-16,2025-03-19,2139,6.8,Cognitive Computing -AI14451,Data Scientist,108994,EUR,92645,MI,FL,Germany,L,Germany,100,"Deep Learning, NLP, Python",Bachelor,4,Media,2024-05-24,2024-06-12,777,5.2,Algorithmic Solutions -AI14452,Principal Data Scientist,88271,USD,88271,MI,FL,Israel,M,Israel,50,"SQL, R, Linux, Docker",Associate,3,Government,2024-12-21,2025-02-05,1348,5.6,Advanced Robotics -AI14453,Deep Learning Engineer,141697,GBP,106273,SE,FL,United Kingdom,M,United Kingdom,0,"Java, AWS, MLOps, Python, Computer Vision",PhD,8,Transportation,2024-10-20,2024-12-04,1060,6,Advanced Robotics -AI14454,AI Software Engineer,77206,CAD,96508,MI,FL,Canada,M,Canada,100,"Spark, Hadoop, Kubernetes, SQL",Master,2,Transportation,2024-03-17,2024-04-28,1765,6,DataVision Ltd -AI14455,Deep Learning Engineer,63781,USD,63781,EN,FT,Ireland,M,Ireland,0,"Scala, GCP, MLOps, Computer Vision, Linux",PhD,1,Consulting,2024-09-06,2024-09-22,2327,7.3,DataVision Ltd -AI14456,Autonomous Systems Engineer,107579,GBP,80684,MI,CT,United Kingdom,L,United Kingdom,0,"Linux, NLP, Spark, Python",Associate,2,Technology,2024-11-08,2024-12-27,654,6.3,DeepTech Ventures -AI14457,AI Architect,210771,CHF,189694,SE,FT,Switzerland,M,Switzerland,50,"Scala, Hadoop, Docker, Computer Vision, Spark",PhD,8,Technology,2024-02-17,2024-04-09,1854,8,Digital Transformation LLC -AI14458,Principal Data Scientist,71437,JPY,7858070,MI,CT,Japan,S,Poland,100,"Kubernetes, Scala, Docker",PhD,4,Healthcare,2024-06-23,2024-08-29,1933,5.2,Machine Intelligence Group -AI14459,Computer Vision Engineer,57340,USD,57340,EN,CT,Sweden,S,Sweden,0,"PyTorch, Python, Mathematics",Associate,1,Manufacturing,2025-03-10,2025-04-22,2221,6.5,TechCorp Inc -AI14460,Robotics Engineer,89880,CAD,112350,MI,CT,Canada,L,Japan,0,"GCP, Hadoop, Git, Tableau, PyTorch",Master,2,Technology,2024-09-28,2024-11-06,1323,8.9,AI Innovations -AI14461,ML Ops Engineer,68307,USD,68307,MI,CT,Israel,S,Israel,100,"AWS, Python, TensorFlow, PyTorch",PhD,4,Real Estate,2025-02-06,2025-03-01,2079,7.2,Cloud AI Solutions -AI14462,Autonomous Systems Engineer,149703,CAD,187129,EX,PT,Canada,S,Canada,0,"Hadoop, Java, Linux",Associate,15,Automotive,2024-05-15,2024-07-27,2181,6.4,AI Innovations -AI14463,ML Ops Engineer,31779,USD,31779,EN,CT,India,L,India,0,"Scala, Azure, Statistics, Python",Associate,1,Automotive,2024-12-22,2025-02-13,533,9.4,TechCorp Inc -AI14464,AI Product Manager,131531,GBP,98648,MI,PT,United Kingdom,L,United Kingdom,50,"Git, Data Visualization, Hadoop",PhD,4,Education,2024-03-01,2024-04-14,1022,5.8,Smart Analytics -AI14465,AI Product Manager,200424,CAD,250530,EX,PT,Canada,M,Canada,0,"MLOps, Python, Kubernetes, TensorFlow, Java",Master,17,Transportation,2024-11-15,2024-12-29,2202,6.9,Quantum Computing Inc -AI14466,Robotics Engineer,129718,GBP,97289,MI,FL,United Kingdom,L,Ukraine,100,"Statistics, SQL, MLOps, Hadoop, Scala",PhD,3,Retail,2024-06-15,2024-07-12,1936,6.9,Cloud AI Solutions -AI14467,AI Software Engineer,84762,USD,84762,MI,FL,Finland,S,Hungary,100,"Python, Computer Vision, Java, Deep Learning",Bachelor,3,Gaming,2024-03-06,2024-05-06,1062,6.3,Digital Transformation LLC -AI14468,Data Analyst,143526,CAD,179408,SE,FL,Canada,L,Austria,100,"Java, Kubernetes, AWS, PyTorch",Master,9,Education,2024-06-19,2024-07-05,1739,8.8,Algorithmic Solutions -AI14469,AI Consultant,134652,USD,134652,EX,PT,Finland,S,Finland,50,"MLOps, AWS, Git, SQL",Associate,18,Media,2024-03-21,2024-04-10,2226,7.2,AI Innovations -AI14470,Principal Data Scientist,72770,USD,72770,EN,FL,Finland,M,Finland,50,"SQL, PyTorch, Deep Learning, GCP, Mathematics",Master,1,Telecommunications,2025-02-01,2025-03-28,2147,8.6,Cloud AI Solutions -AI14471,Data Scientist,165036,CHF,148532,SE,FT,Switzerland,S,Switzerland,50,"Azure, Git, Data Visualization, TensorFlow, Kubernetes",Associate,9,Finance,2024-03-14,2024-04-18,973,8.5,Machine Intelligence Group -AI14472,Machine Learning Researcher,277879,USD,277879,EX,PT,Denmark,L,Denmark,50,"Data Visualization, Azure, R, SQL",Bachelor,10,Energy,2024-01-25,2024-03-31,2242,7.7,Cloud AI Solutions -AI14473,AI Specialist,292246,USD,292246,EX,FL,Ireland,L,Ireland,100,"AWS, Scala, Mathematics, MLOps",PhD,16,Consulting,2024-07-01,2024-08-04,1417,8.9,Machine Intelligence Group -AI14474,AI Software Engineer,122288,EUR,103945,MI,PT,Netherlands,L,Netherlands,50,"TensorFlow, Kubernetes, Scala",PhD,4,Consulting,2024-08-16,2024-09-22,1424,7,Autonomous Tech -AI14475,AI Architect,185384,USD,185384,EX,CT,Denmark,M,Denmark,100,"Spark, Deep Learning, Python",Associate,18,Telecommunications,2024-12-22,2025-01-09,734,9.1,AI Innovations -AI14476,AI Architect,204233,EUR,173598,EX,FL,Austria,S,Austria,0,"Git, Computer Vision, Tableau",Master,14,Finance,2024-03-22,2024-04-16,1045,7.6,Cognitive Computing -AI14477,AI Consultant,57991,CAD,72489,EN,CT,Canada,L,Austria,50,"Computer Vision, Python, Data Visualization",Bachelor,1,Telecommunications,2024-02-09,2024-04-01,2183,8.7,Advanced Robotics -AI14478,Autonomous Systems Engineer,235868,USD,235868,EX,FL,Finland,L,Finland,100,"Deep Learning, Scala, SQL",PhD,11,Technology,2025-01-30,2025-02-15,1745,5.8,Cognitive Computing -AI14479,Research Scientist,150822,EUR,128199,SE,FT,Netherlands,L,Netherlands,50,"Kubernetes, Scala, MLOps, Mathematics, Statistics",Master,7,Government,2024-05-20,2024-06-18,526,8.5,Machine Intelligence Group -AI14480,Machine Learning Researcher,112953,USD,112953,EN,FL,Denmark,L,Denmark,50,"Tableau, Statistics, Spark, MLOps, Git",Bachelor,0,Manufacturing,2024-01-25,2024-02-19,876,8.4,Algorithmic Solutions -AI14481,ML Ops Engineer,201083,AUD,271462,EX,PT,Australia,S,Colombia,0,"Java, Hadoop, SQL, Git, Docker",Associate,14,Real Estate,2024-07-03,2024-08-11,1486,7.3,Future Systems -AI14482,Machine Learning Engineer,63962,CAD,79953,MI,CT,Canada,S,Canada,50,"Azure, PyTorch, SQL, Computer Vision, Mathematics",Bachelor,2,Consulting,2025-02-08,2025-04-02,1369,8.1,Cognitive Computing -AI14483,AI Consultant,124552,CHF,112097,MI,CT,Switzerland,M,Switzerland,100,"SQL, Azure, Scala, Python",PhD,4,Telecommunications,2025-01-26,2025-03-02,1392,9,Predictive Systems -AI14484,Data Analyst,65428,USD,65428,EN,FL,Israel,M,Chile,50,"SQL, Hadoop, Mathematics, Computer Vision, Deep Learning",Associate,0,Real Estate,2025-04-06,2025-06-14,1254,6.9,DeepTech Ventures -AI14485,Computer Vision Engineer,122062,CHF,109856,MI,FT,Switzerland,M,Switzerland,0,"Data Visualization, TensorFlow, Statistics, R, Deep Learning",Bachelor,2,Telecommunications,2024-05-11,2024-06-15,2116,7.8,Smart Analytics -AI14486,AI Research Scientist,111469,AUD,150483,SE,FL,Australia,S,Brazil,0,"MLOps, Git, Kubernetes, NLP",PhD,8,Media,2025-03-25,2025-05-16,581,5.9,Machine Intelligence Group -AI14487,Deep Learning Engineer,181761,USD,181761,EX,FT,South Korea,M,South Korea,50,"Tableau, Computer Vision, Kubernetes",PhD,10,Government,2025-01-17,2025-02-08,1234,9.5,Cloud AI Solutions -AI14488,Data Analyst,116229,GBP,87172,SE,PT,United Kingdom,M,Latvia,100,"Kubernetes, Docker, MLOps, Git",Bachelor,8,Finance,2025-01-03,2025-02-16,1852,9.8,DataVision Ltd -AI14489,Data Scientist,82622,USD,82622,EN,CT,Finland,L,Finland,100,"SQL, Kubernetes, Statistics, Deep Learning, PyTorch",Master,0,Gaming,2025-01-20,2025-03-16,1749,8.5,Autonomous Tech -AI14490,AI Research Scientist,96369,USD,96369,EN,FL,Norway,L,Norway,50,"MLOps, Git, Python",PhD,0,Consulting,2024-01-30,2024-03-08,1367,9.4,Cognitive Computing -AI14491,Research Scientist,53103,USD,53103,EN,CT,Israel,M,Israel,0,"Tableau, Kubernetes, Scala, R, Mathematics",Bachelor,1,Consulting,2024-04-27,2024-07-04,1971,9.2,Algorithmic Solutions -AI14492,NLP Engineer,57126,EUR,48557,EN,PT,France,S,United Kingdom,50,"Python, Spark, NLP",Master,0,Media,2024-08-11,2024-10-23,1473,7.3,Machine Intelligence Group -AI14493,Machine Learning Engineer,94857,JPY,10434270,EN,PT,Japan,L,Japan,0,"AWS, Java, Scala, Spark",Bachelor,0,Automotive,2025-03-30,2025-05-04,1942,8.4,Advanced Robotics -AI14494,Research Scientist,99850,EUR,84873,SE,PT,Austria,S,Germany,100,"NLP, Java, Tableau, GCP",Master,7,Automotive,2024-10-14,2024-12-12,1764,9.5,Autonomous Tech -AI14495,Machine Learning Researcher,26941,USD,26941,EN,FT,India,L,India,50,"Kubernetes, Docker, Data Visualization, GCP",Bachelor,1,Healthcare,2024-01-29,2024-03-18,929,5.2,Autonomous Tech -AI14496,Principal Data Scientist,37543,USD,37543,MI,FT,India,L,Romania,100,"Data Visualization, Hadoop, TensorFlow",PhD,4,Manufacturing,2025-02-09,2025-03-27,1623,9.6,Cognitive Computing -AI14497,Head of AI,145765,USD,145765,SE,PT,Israel,L,Israel,50,"Python, TensorFlow, PyTorch",Associate,9,Energy,2024-07-07,2024-08-09,1970,7.4,Machine Intelligence Group -AI14498,Data Analyst,109358,USD,109358,SE,FT,Sweden,M,Ukraine,100,"Data Visualization, SQL, Kubernetes",Associate,6,Education,2025-03-23,2025-05-26,1121,6,Quantum Computing Inc -AI14499,Computer Vision Engineer,85375,USD,85375,EX,CT,China,M,Vietnam,0,"Hadoop, Java, Azure, GCP, Scala",Associate,16,Energy,2024-02-13,2024-04-14,1288,9.6,Autonomous Tech -AI14500,AI Research Scientist,34369,USD,34369,MI,FT,China,S,China,50,"Java, Kubernetes, Hadoop, Statistics",Associate,2,Finance,2024-10-24,2024-12-15,2200,8.1,Smart Analytics -AI14501,Head of AI,101172,USD,101172,MI,FT,United States,S,United States,100,"Python, NLP, TensorFlow, GCP",PhD,3,Finance,2024-10-26,2024-12-02,1033,5.6,AI Innovations -AI14502,Robotics Engineer,100350,USD,100350,EN,FT,Denmark,L,Denmark,50,"SQL, AWS, GCP",Bachelor,0,Manufacturing,2024-12-20,2025-03-03,1176,7.2,Cloud AI Solutions -AI14503,Computer Vision Engineer,53409,SGD,69432,EN,FL,Singapore,S,Singapore,50,"Hadoop, Java, PyTorch",PhD,1,Media,2024-06-25,2024-09-03,2077,7.7,Future Systems -AI14504,Head of AI,109264,USD,109264,MI,PT,Finland,L,Czech Republic,0,"Java, Linux, AWS",Bachelor,3,Finance,2024-03-29,2024-06-06,677,6.5,Digital Transformation LLC -AI14505,Research Scientist,67190,USD,67190,EN,FL,United States,M,United States,0,"SQL, Spark, Computer Vision",Master,0,Energy,2024-06-12,2024-07-13,1965,8.4,TechCorp Inc -AI14506,AI Architect,68547,JPY,7540170,EN,FT,Japan,S,Argentina,0,"Mathematics, PyTorch, Computer Vision",PhD,0,Automotive,2025-02-05,2025-03-18,1778,5.3,Cloud AI Solutions -AI14507,Machine Learning Researcher,86075,USD,86075,MI,PT,Israel,S,Israel,50,"Hadoop, Java, Mathematics",Master,2,Gaming,2024-05-15,2024-06-18,1624,9.5,Advanced Robotics -AI14508,ML Ops Engineer,71794,USD,71794,SE,FL,China,M,China,50,"GCP, Java, Python, Git, NLP",Master,8,Telecommunications,2024-07-21,2024-08-14,1256,8.3,Quantum Computing Inc -AI14509,AI Product Manager,89033,EUR,75678,MI,CT,Netherlands,S,Netherlands,0,"Data Visualization, R, SQL, Computer Vision",Bachelor,2,Media,2024-09-30,2024-10-17,1062,5.3,Digital Transformation LLC -AI14510,Principal Data Scientist,241780,GBP,181335,EX,FT,United Kingdom,S,United Kingdom,50,"SQL, Java, GCP, PyTorch",Associate,13,Gaming,2025-03-26,2025-06-02,1804,5.4,Advanced Robotics -AI14511,Head of AI,90029,GBP,67522,MI,PT,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, TensorFlow, Kubernetes",Associate,2,Media,2024-07-29,2024-08-25,1922,8.2,Machine Intelligence Group -AI14512,NLP Engineer,125238,USD,125238,SE,FL,Israel,S,Israel,0,"Hadoop, Spark, Kubernetes",Bachelor,9,Retail,2024-07-16,2024-09-27,764,8.6,AI Innovations -AI14513,ML Ops Engineer,60541,USD,60541,MI,FL,South Korea,S,South Korea,50,"Git, Linux, NLP",Bachelor,2,Automotive,2024-08-17,2024-09-17,1236,8.7,DataVision Ltd -AI14514,AI Specialist,45630,EUR,38786,EN,FT,France,S,France,0,"TensorFlow, GCP, Linux",Associate,1,Healthcare,2024-07-04,2024-07-29,676,6.1,Smart Analytics -AI14515,AI Consultant,159534,CHF,143581,SE,FL,Switzerland,M,Switzerland,0,"Deep Learning, GCP, R",Bachelor,6,Finance,2024-11-09,2025-01-21,1441,7.5,Algorithmic Solutions -AI14516,Data Analyst,68523,USD,68523,EN,FL,Ireland,M,Ireland,0,"Kubernetes, Deep Learning, Hadoop, Statistics",Bachelor,0,Energy,2024-11-15,2025-01-23,836,6.5,TechCorp Inc -AI14517,Computer Vision Engineer,93997,EUR,79897,MI,FT,Austria,M,Austria,50,"GCP, PyTorch, Data Visualization, SQL",Master,3,Transportation,2025-01-27,2025-03-02,1646,6.8,DeepTech Ventures -AI14518,Robotics Engineer,61638,EUR,52392,MI,FL,France,S,United Kingdom,100,"Java, Mathematics, AWS, Computer Vision",PhD,3,Automotive,2025-02-07,2025-03-14,2027,6.3,DeepTech Ventures -AI14519,Data Engineer,111944,USD,111944,SE,FL,Finland,L,Finland,100,"Hadoop, Spark, Java, Linux, MLOps",Associate,9,Consulting,2024-02-19,2024-04-24,1783,9.6,DataVision Ltd -AI14520,Computer Vision Engineer,99102,JPY,10901220,SE,FL,Japan,S,Japan,100,"Hadoop, MLOps, Git, Statistics",Associate,6,Government,2024-06-26,2024-08-05,2283,9.9,Smart Analytics -AI14521,AI Product Manager,66373,USD,66373,EN,FL,Ireland,S,Ireland,0,"Python, Docker, Git",Bachelor,0,Gaming,2024-12-27,2025-02-22,2425,6.7,DataVision Ltd -AI14522,Machine Learning Engineer,286837,USD,286837,EX,FT,Sweden,L,Sweden,100,"Hadoop, Mathematics, Linux, PyTorch, GCP",Bachelor,10,Government,2024-01-06,2024-03-19,737,6.3,AI Innovations -AI14523,Computer Vision Engineer,163282,EUR,138790,EX,CT,France,M,France,100,"Scala, Python, Deep Learning, TensorFlow, AWS",PhD,12,Consulting,2025-01-27,2025-02-16,1004,6.4,Machine Intelligence Group -AI14524,Machine Learning Engineer,116441,USD,116441,SE,FT,South Korea,M,South Korea,100,"TensorFlow, Azure, Data Visualization",Master,9,Manufacturing,2025-02-28,2025-03-30,1732,5.6,Future Systems -AI14525,AI Software Engineer,72672,CAD,90840,EN,FT,Canada,M,China,0,"Scala, AWS, Computer Vision",Master,1,Media,2024-09-13,2024-10-15,789,5.4,Cloud AI Solutions -AI14526,Principal Data Scientist,125105,USD,125105,SE,FT,Sweden,S,Sweden,0,"R, Kubernetes, MLOps",PhD,8,Healthcare,2024-09-01,2024-10-22,623,5.4,Future Systems -AI14527,AI Architect,160966,SGD,209256,SE,CT,Singapore,L,Singapore,50,"Data Visualization, Docker, Statistics, Azure, MLOps",Bachelor,5,Manufacturing,2024-08-09,2024-10-12,1920,7.8,Cloud AI Solutions -AI14528,NLP Engineer,87326,CAD,109158,MI,CT,Canada,S,Canada,50,"Kubernetes, TensorFlow, SQL",PhD,4,Energy,2024-05-15,2024-06-07,754,7,Smart Analytics -AI14529,AI Product Manager,135601,USD,135601,SE,PT,Ireland,M,China,50,"Linux, Python, Statistics, AWS",Master,8,Gaming,2024-03-17,2024-04-17,1413,6.1,Algorithmic Solutions -AI14530,Principal Data Scientist,217533,CHF,195780,EX,PT,Switzerland,M,Romania,0,"GCP, Docker, SQL",Master,17,Finance,2025-03-26,2025-06-01,633,8.2,Cloud AI Solutions -AI14531,Head of AI,98113,EUR,83396,MI,FL,Austria,M,France,50,"Python, Tableau, Kubernetes, Linux, Java",Associate,3,Automotive,2024-10-30,2024-11-16,2184,8.1,DeepTech Ventures -AI14532,Autonomous Systems Engineer,81244,USD,81244,EN,PT,Israel,L,Hungary,50,"Spark, PyTorch, R, AWS, MLOps",Associate,1,Gaming,2024-02-01,2024-03-22,628,6.4,Autonomous Tech -AI14533,AI Architect,89895,EUR,76411,EN,CT,Netherlands,L,Italy,100,"Scala, Statistics, Java, Azure",PhD,0,Healthcare,2024-06-24,2024-08-11,1131,8,Autonomous Tech -AI14534,Research Scientist,171139,USD,171139,EX,FL,Sweden,M,Latvia,100,"TensorFlow, Git, SQL, Java, Python",Master,15,Technology,2024-06-10,2024-07-11,1799,9.7,Neural Networks Co -AI14535,Robotics Engineer,62756,SGD,81583,EN,FL,Singapore,M,Singapore,50,"Tableau, PyTorch, MLOps, TensorFlow, Linux",Master,0,Education,2024-06-04,2024-07-10,918,7.3,Smart Analytics -AI14536,Deep Learning Engineer,335964,CHF,302368,EX,CT,Switzerland,M,Switzerland,50,"R, Hadoop, Azure, GCP",PhD,11,Consulting,2025-02-20,2025-05-03,707,7.6,DataVision Ltd -AI14537,Data Scientist,106920,EUR,90882,MI,FT,Germany,M,United Kingdom,50,"Linux, AWS, Mathematics",Master,3,Healthcare,2024-09-17,2024-11-29,2132,7.3,Digital Transformation LLC -AI14538,Deep Learning Engineer,119575,EUR,101639,MI,CT,Austria,L,Austria,100,"Kubernetes, Java, Python, NLP, Spark",Bachelor,4,Energy,2024-12-04,2024-12-24,2163,6.1,AI Innovations -AI14539,Computer Vision Engineer,84559,USD,84559,EX,FT,China,M,China,50,"TensorFlow, SQL, Mathematics",PhD,10,Gaming,2025-04-15,2025-05-18,1877,8.6,Predictive Systems -AI14540,Head of AI,101252,USD,101252,MI,FL,Norway,M,Norway,100,"NLP, SQL, R, Docker",Associate,2,Media,2024-01-05,2024-03-01,1702,9.2,Digital Transformation LLC -AI14541,Deep Learning Engineer,236723,CHF,213051,EX,FL,Switzerland,L,Switzerland,0,"SQL, Scala, TensorFlow, GCP, Git",Master,17,Real Estate,2024-10-13,2024-11-13,2464,9.2,Machine Intelligence Group -AI14542,Data Analyst,244256,USD,244256,EX,FL,United States,S,United States,0,"Tableau, PyTorch, R",Bachelor,16,Finance,2024-07-03,2024-07-20,2238,5.9,Machine Intelligence Group -AI14543,Machine Learning Engineer,158103,EUR,134388,EX,FT,Germany,M,Denmark,50,"Hadoop, SQL, Java, GCP, PyTorch",PhD,11,Transportation,2025-01-30,2025-02-26,955,5.6,AI Innovations -AI14544,Head of AI,130549,EUR,110967,SE,CT,Germany,S,Germany,50,"R, GCP, Scala",Bachelor,5,Manufacturing,2025-03-06,2025-04-19,2156,7,TechCorp Inc -AI14545,AI Product Manager,175962,USD,175962,SE,FT,Denmark,M,Denmark,100,"Data Visualization, Docker, AWS, SQL, Linux",Master,7,Education,2025-03-23,2025-05-10,2102,5.9,Future Systems -AI14546,Head of AI,140334,USD,140334,EX,PT,Ireland,M,Ireland,100,"TensorFlow, Linux, Azure",PhD,13,Healthcare,2025-01-26,2025-03-27,1612,5.6,Cloud AI Solutions -AI14547,Machine Learning Engineer,83160,CHF,74844,EN,PT,Switzerland,M,Switzerland,50,"Docker, Linux, Deep Learning, TensorFlow, Git",Associate,0,Consulting,2024-12-10,2025-01-21,1282,9,Algorithmic Solutions -AI14548,Computer Vision Engineer,195354,AUD,263728,EX,CT,Australia,L,Indonesia,100,"Kubernetes, Scala, NLP, GCP, Tableau",Associate,19,Education,2025-04-21,2025-05-31,2365,9.6,AI Innovations -AI14549,AI Product Manager,62596,AUD,84505,EN,FL,Australia,L,Canada,100,"Python, Scala, Statistics",Bachelor,1,Consulting,2024-10-21,2024-12-22,1983,5.5,Algorithmic Solutions -AI14550,Machine Learning Engineer,246772,EUR,209756,EX,PT,Austria,L,Austria,100,"Deep Learning, Git, Scala, Java, Computer Vision",Associate,13,Energy,2024-10-24,2024-11-28,770,9.6,Cognitive Computing -AI14551,Data Engineer,59096,USD,59096,EN,CT,South Korea,S,South Korea,100,"Java, Hadoop, Data Visualization, Linux, Tableau",Master,1,Energy,2024-06-14,2024-08-19,2494,8,Predictive Systems -AI14552,Principal Data Scientist,144657,USD,144657,EX,FT,Sweden,S,Portugal,50,"NLP, Deep Learning, Data Visualization, Hadoop, SQL",Bachelor,12,Gaming,2024-02-12,2024-03-29,2372,9.8,AI Innovations -AI14553,Research Scientist,98312,USD,98312,EX,FT,China,L,China,100,"Scala, Python, NLP, R",Associate,17,Retail,2024-10-08,2024-11-24,574,9.4,Advanced Robotics -AI14554,Machine Learning Researcher,268721,EUR,228413,EX,CT,Germany,L,Germany,100,"Python, SQL, AWS",Master,10,Transportation,2024-12-16,2025-01-21,2163,5.8,Machine Intelligence Group -AI14555,Robotics Engineer,24804,USD,24804,EN,CT,China,S,Ukraine,50,"Python, Azure, TensorFlow, R",PhD,1,Real Estate,2024-06-09,2024-07-22,563,6.5,Cognitive Computing -AI14556,Robotics Engineer,116955,AUD,157889,SE,FT,Australia,S,Australia,100,"Python, Kubernetes, Data Visualization",Associate,8,Automotive,2025-03-15,2025-05-19,1300,9.5,Digital Transformation LLC -AI14557,Computer Vision Engineer,102088,EUR,86775,MI,CT,France,L,France,100,"Azure, GCP, SQL, Deep Learning, PyTorch",Associate,3,Healthcare,2025-04-02,2025-06-03,1698,6.4,Advanced Robotics -AI14558,Autonomous Systems Engineer,150619,EUR,128026,SE,CT,Germany,L,Germany,50,"Scala, Python, Mathematics, Deep Learning",Associate,7,Technology,2025-02-28,2025-03-30,1410,8.2,Neural Networks Co -AI14559,AI Specialist,110839,CAD,138549,MI,PT,Canada,L,Malaysia,50,"SQL, NLP, Kubernetes, Mathematics",Bachelor,4,Gaming,2025-04-15,2025-05-02,1293,6,Cloud AI Solutions -AI14560,Computer Vision Engineer,201264,CHF,181138,EX,PT,Switzerland,M,Germany,0,"GCP, Scala, SQL, Computer Vision",Master,15,Manufacturing,2024-11-01,2024-12-17,2398,9.8,Cloud AI Solutions -AI14561,Autonomous Systems Engineer,87432,USD,87432,EN,PT,United States,M,United States,100,"TensorFlow, GCP, MLOps",Master,0,Transportation,2024-09-30,2024-12-02,1262,5.5,Future Systems -AI14562,AI Software Engineer,63493,EUR,53969,EN,PT,Netherlands,L,Netherlands,50,"NLP, SQL, Linux",Associate,0,Real Estate,2024-10-14,2024-12-24,2168,9.5,Digital Transformation LLC -AI14563,Research Scientist,184467,JPY,20291370,EX,FL,Japan,L,Japan,50,"Mathematics, Kubernetes, Azure, Deep Learning",PhD,18,Government,2024-05-23,2024-06-11,872,5.7,Advanced Robotics -AI14564,AI Research Scientist,209096,EUR,177732,EX,FT,Germany,M,Germany,100,"Kubernetes, Azure, Spark, GCP, Java",PhD,19,Real Estate,2024-02-29,2024-04-25,1107,8.6,Algorithmic Solutions -AI14565,Research Scientist,98677,SGD,128280,MI,PT,Singapore,S,Singapore,100,"NLP, AWS, Kubernetes, SQL, GCP",Associate,2,Retail,2024-02-23,2024-03-20,741,5.5,Advanced Robotics -AI14566,ML Ops Engineer,99800,CAD,124750,SE,FL,Canada,M,Canada,50,"PyTorch, Spark, TensorFlow, Kubernetes",PhD,5,Real Estate,2024-11-10,2025-01-21,1041,9.6,Digital Transformation LLC -AI14567,AI Research Scientist,109379,USD,109379,MI,CT,Finland,L,Finland,100,"Java, SQL, Linux",PhD,3,Transportation,2025-01-01,2025-03-06,1690,6.2,TechCorp Inc -AI14568,Data Analyst,68608,USD,68608,SE,CT,China,L,China,0,"Hadoop, Python, TensorFlow",Associate,5,Telecommunications,2024-08-01,2024-09-10,2444,8.5,TechCorp Inc -AI14569,Head of AI,70451,USD,70451,EX,CT,India,S,India,100,"Linux, Azure, Deep Learning, GCP",Bachelor,19,Consulting,2024-02-28,2024-03-21,985,8.7,DataVision Ltd -AI14570,NLP Engineer,127444,USD,127444,SE,FT,Norway,S,Norway,0,"Python, TensorFlow, Mathematics, AWS",Bachelor,6,Healthcare,2024-10-08,2024-11-11,1031,9.7,Neural Networks Co -AI14571,AI Research Scientist,59585,GBP,44689,EN,CT,United Kingdom,M,Spain,0,"Linux, PyTorch, Statistics, Scala",Associate,1,Transportation,2024-10-02,2024-12-05,2342,7.6,TechCorp Inc -AI14572,Principal Data Scientist,129467,GBP,97100,MI,CT,United Kingdom,L,New Zealand,50,"R, Computer Vision, Mathematics, SQL",Bachelor,2,Technology,2024-12-27,2025-02-02,983,5.9,Machine Intelligence Group -AI14573,AI Architect,89818,CHF,80836,EN,FL,Switzerland,S,Romania,50,"Git, Python, AWS, Deep Learning",PhD,1,Energy,2024-04-01,2024-06-03,1846,5.6,Algorithmic Solutions -AI14574,AI Specialist,168508,USD,168508,EX,FL,Israel,S,Kenya,50,"Hadoop, PyTorch, SQL",Associate,18,Telecommunications,2024-07-26,2024-09-09,2122,5.1,Autonomous Tech -AI14575,Machine Learning Researcher,139480,GBP,104610,SE,PT,United Kingdom,L,Colombia,100,"Azure, Scala, NLP, Mathematics, PyTorch",Master,8,Healthcare,2024-01-04,2024-02-01,2378,8.2,TechCorp Inc -AI14576,Machine Learning Researcher,192002,EUR,163202,EX,FL,Austria,L,Austria,50,"GCP, TensorFlow, Deep Learning, Data Visualization, SQL",Bachelor,18,Education,2024-07-12,2024-08-08,559,7.7,Autonomous Tech -AI14577,NLP Engineer,58121,USD,58121,MI,CT,China,L,China,0,"Mathematics, R, Tableau, SQL",PhD,2,Healthcare,2025-01-12,2025-02-15,1764,8,DeepTech Ventures -AI14578,Research Scientist,134623,EUR,114430,EX,FL,France,S,France,0,"NLP, Data Visualization, Java, R",Associate,15,Education,2025-04-08,2025-05-05,1864,9.3,TechCorp Inc -AI14579,AI Architect,97785,USD,97785,MI,CT,Norway,S,Norway,0,"Java, PyTorch, TensorFlow, Python",PhD,4,Gaming,2024-03-28,2024-05-26,807,7.5,AI Innovations -AI14580,Principal Data Scientist,219292,AUD,296044,EX,FL,Australia,L,Australia,100,"SQL, Mathematics, GCP",Master,11,Real Estate,2024-01-16,2024-03-12,974,6.3,DeepTech Ventures -AI14581,Principal Data Scientist,52713,USD,52713,MI,CT,China,L,China,100,"MLOps, Python, Spark, Scala",Bachelor,2,Telecommunications,2024-05-13,2024-07-10,1083,9.5,Autonomous Tech -AI14582,AI Architect,318665,USD,318665,EX,FT,Denmark,M,Denmark,50,"AWS, PyTorch, Deep Learning",Bachelor,13,Healthcare,2024-11-02,2024-11-19,1618,8.7,Digital Transformation LLC -AI14583,Data Analyst,150768,CHF,135691,MI,FL,Switzerland,M,Switzerland,50,"Statistics, Scala, R, Kubernetes, Python",Master,4,Telecommunications,2024-09-28,2024-11-19,1321,9.3,Predictive Systems -AI14584,Robotics Engineer,130419,USD,130419,MI,CT,Denmark,M,Denmark,50,"Spark, Scala, Deep Learning, TensorFlow, NLP",PhD,2,Manufacturing,2024-11-10,2024-12-18,1361,5.6,Autonomous Tech -AI14585,Machine Learning Researcher,134257,USD,134257,MI,FL,Denmark,L,Sweden,50,"Python, AWS, Computer Vision, Azure",Associate,2,Telecommunications,2025-03-12,2025-05-06,1297,8.8,Digital Transformation LLC -AI14586,Robotics Engineer,88859,GBP,66644,MI,PT,United Kingdom,L,Latvia,50,"Java, R, MLOps, GCP, Scala",PhD,2,Finance,2024-09-12,2024-10-09,1916,6.4,Machine Intelligence Group -AI14587,Head of AI,124958,USD,124958,SE,FT,South Korea,M,South Korea,50,"Python, Scala, AWS, TensorFlow, Java",Master,8,Telecommunications,2024-09-10,2024-10-13,2029,9.9,Smart Analytics -AI14588,Data Engineer,173410,GBP,130058,SE,FL,United Kingdom,L,United Kingdom,50,"Spark, Statistics, Python",Bachelor,9,Healthcare,2024-02-11,2024-03-13,2108,8.5,Neural Networks Co -AI14589,AI Specialist,119770,EUR,101805,SE,PT,France,M,France,50,"Python, Mathematics, Azure, TensorFlow",Associate,7,Automotive,2025-04-17,2025-06-29,648,7.8,DeepTech Ventures -AI14590,Data Scientist,57438,EUR,48822,EN,FT,Netherlands,M,Netherlands,50,"Kubernetes, Deep Learning, Computer Vision, GCP",Master,1,Transportation,2024-08-16,2024-10-23,717,8.2,Digital Transformation LLC -AI14591,Machine Learning Engineer,168237,CAD,210296,EX,PT,Canada,S,Canada,100,"AWS, Java, R, Data Visualization",Associate,10,Government,2024-03-14,2024-05-09,2119,9.1,DeepTech Ventures -AI14592,Principal Data Scientist,198127,USD,198127,EX,FT,Sweden,M,Ireland,100,"Linux, Git, MLOps, Tableau, Computer Vision",PhD,19,Retail,2025-04-26,2025-05-10,2065,6.7,Advanced Robotics -AI14593,AI Software Engineer,91754,USD,91754,SE,FT,South Korea,S,South Korea,0,"Computer Vision, Tableau, AWS, Data Visualization, Python",Bachelor,5,Education,2024-10-23,2024-12-28,2354,9.8,Autonomous Tech -AI14594,AI Research Scientist,59433,CAD,74291,EN,FL,Canada,L,Romania,0,"Linux, Data Visualization, Deep Learning",PhD,1,Media,2025-01-12,2025-01-30,1618,9,Quantum Computing Inc -AI14595,AI Consultant,128719,EUR,109411,SE,CT,Germany,M,Germany,100,"Scala, SQL, Linux, Azure",Master,5,Consulting,2025-03-18,2025-05-26,1435,8.1,DataVision Ltd -AI14596,NLP Engineer,225590,CHF,203031,EX,FT,Switzerland,M,Switzerland,50,"Data Visualization, Statistics, SQL, Deep Learning, Mathematics",PhD,10,Healthcare,2024-08-17,2024-10-03,832,9.9,Machine Intelligence Group -AI14597,Data Engineer,327266,USD,327266,EX,FL,Norway,M,Norway,0,"Deep Learning, Python, Java, Computer Vision, SQL",Master,19,Consulting,2024-06-19,2024-08-03,1607,9.6,Quantum Computing Inc -AI14598,Computer Vision Engineer,77377,USD,77377,MI,FL,Ireland,M,Italy,100,"TensorFlow, Scala, Mathematics",Master,3,Manufacturing,2024-09-09,2024-11-13,1176,9.6,Autonomous Tech -AI14599,Research Scientist,172505,USD,172505,SE,FL,Norway,M,Norway,0,"Linux, Azure, Deep Learning, Python",Master,5,Automotive,2025-03-18,2025-04-29,789,5.2,Advanced Robotics -AI14600,Head of AI,97488,GBP,73116,MI,FT,United Kingdom,M,United Kingdom,100,"Scala, Java, Kubernetes, TensorFlow",Master,4,Healthcare,2024-02-23,2024-04-12,506,9.9,Future Systems -AI14601,Head of AI,71688,USD,71688,EN,CT,Ireland,M,Ireland,100,"Data Visualization, Python, SQL, TensorFlow",Master,0,Telecommunications,2024-08-13,2024-09-13,518,9,Autonomous Tech -AI14602,Machine Learning Researcher,177939,USD,177939,EX,PT,Finland,L,United Kingdom,50,"Java, Hadoop, Computer Vision",Master,15,Government,2024-07-13,2024-08-31,2444,8.5,DeepTech Ventures -AI14603,Deep Learning Engineer,176846,CHF,159161,EX,CT,Switzerland,S,Switzerland,100,"Computer Vision, Docker, Data Visualization, Linux, Statistics",PhD,16,Consulting,2024-04-01,2024-06-05,1132,8.3,DataVision Ltd -AI14604,AI Consultant,75786,EUR,64418,MI,FL,Netherlands,S,Netherlands,50,"Python, TensorFlow, NLP, Java, Scala",PhD,2,Consulting,2024-12-22,2025-02-12,517,8.1,Algorithmic Solutions -AI14605,AI Consultant,57729,USD,57729,EN,CT,Finland,L,Finland,50,"Scala, Hadoop, Git, Data Visualization",Bachelor,1,Gaming,2024-01-05,2024-02-26,1690,5.2,Cloud AI Solutions -AI14606,Head of AI,103984,USD,103984,SE,FT,South Korea,S,South Africa,50,"Tableau, Azure, SQL, Java, Spark",Associate,8,Government,2024-11-24,2024-12-08,1783,9.7,Cognitive Computing -AI14607,NLP Engineer,109857,GBP,82393,SE,FL,United Kingdom,M,United Kingdom,50,"Kubernetes, Java, NLP",Master,8,Telecommunications,2024-02-25,2024-04-07,814,6,Cloud AI Solutions -AI14608,Data Analyst,211073,USD,211073,EX,CT,Ireland,S,Ireland,0,"GCP, Git, MLOps",PhD,11,Technology,2024-10-18,2024-11-02,674,9,Quantum Computing Inc -AI14609,Data Engineer,134522,USD,134522,SE,CT,Sweden,L,Sweden,0,"AWS, Hadoop, MLOps, Python",Master,5,Education,2025-03-14,2025-04-04,1612,5.7,Predictive Systems -AI14610,AI Architect,161100,CHF,144990,SE,CT,Switzerland,M,Switzerland,50,"PyTorch, TensorFlow, AWS, MLOps, Scala",Associate,6,Transportation,2025-01-31,2025-03-14,1781,8,DeepTech Ventures -AI14611,Autonomous Systems Engineer,122301,EUR,103956,SE,FL,Germany,M,Germany,50,"Kubernetes, Python, Computer Vision",Associate,6,Government,2024-09-07,2024-10-23,2201,5.8,Autonomous Tech -AI14612,NLP Engineer,85699,EUR,72844,MI,FT,Germany,S,Mexico,50,"Kubernetes, Java, R, Docker, Statistics",PhD,2,Healthcare,2024-06-12,2024-07-09,1286,9.8,Quantum Computing Inc -AI14613,AI Consultant,70435,CAD,88044,EN,FL,Canada,M,India,0,"Linux, PyTorch, MLOps, R",Associate,1,Consulting,2025-02-02,2025-03-08,889,8.9,DeepTech Ventures -AI14614,Machine Learning Researcher,83577,EUR,71040,MI,FT,Austria,L,Austria,0,"Scala, Tableau, Python",PhD,2,Transportation,2024-05-12,2024-07-13,880,10,Digital Transformation LLC -AI14615,Machine Learning Researcher,224546,USD,224546,EX,CT,Denmark,L,Denmark,100,"PyTorch, AWS, TensorFlow",Associate,18,Real Estate,2024-11-18,2024-12-17,1647,5.1,Advanced Robotics -AI14616,AI Consultant,164191,JPY,18061010,SE,CT,Japan,L,Japan,100,"R, Linux, SQL, PyTorch, AWS",Bachelor,7,Technology,2024-01-02,2024-03-03,1513,7.5,DataVision Ltd -AI14617,AI Architect,234520,SGD,304876,EX,CT,Singapore,S,Singapore,0,"Tableau, Hadoop, Kubernetes, SQL, NLP",Master,14,Manufacturing,2024-03-23,2024-04-26,2487,8.6,Cloud AI Solutions -AI14618,Deep Learning Engineer,50375,USD,50375,SE,CT,China,S,China,100,"Python, Docker, Linux, Mathematics, Kubernetes",Bachelor,8,Technology,2024-08-29,2024-09-29,1638,9.7,Digital Transformation LLC -AI14619,Research Scientist,60031,EUR,51026,EN,CT,France,L,Vietnam,50,"Tableau, Data Visualization, AWS, Azure",Associate,1,Finance,2025-03-17,2025-05-24,1254,9.6,Quantum Computing Inc -AI14620,Computer Vision Engineer,38594,USD,38594,MI,FL,China,M,Hungary,100,"AWS, PyTorch, MLOps, NLP, Kubernetes",PhD,4,Automotive,2025-04-19,2025-06-06,2450,8.4,DeepTech Ventures -AI14621,AI Architect,115790,EUR,98422,SE,PT,Germany,M,Germany,0,"Scala, Python, AWS",Master,5,Gaming,2024-10-12,2024-12-11,2193,7.6,Advanced Robotics -AI14622,AI Product Manager,134490,USD,134490,SE,PT,Denmark,M,Denmark,50,"Python, Mathematics, Deep Learning, Git",PhD,7,Manufacturing,2024-02-22,2024-03-21,1593,7,Future Systems -AI14623,ML Ops Engineer,80936,USD,80936,MI,CT,United States,S,United States,100,"Docker, Python, AWS",PhD,3,Gaming,2024-11-01,2024-12-27,1341,8.3,TechCorp Inc -AI14624,Computer Vision Engineer,142227,USD,142227,SE,CT,Finland,M,Finland,0,"Spark, Tableau, Linux",PhD,5,Retail,2024-04-03,2024-05-13,2195,6.1,Quantum Computing Inc -AI14625,Data Analyst,301196,USD,301196,EX,FT,Norway,M,Australia,100,"Spark, TensorFlow, Azure, Docker, Tableau",Master,11,Education,2025-04-09,2025-05-24,664,7.3,Digital Transformation LLC -AI14626,AI Specialist,42683,USD,42683,SE,FL,India,M,India,0,"Mathematics, Kubernetes, Python",PhD,5,Telecommunications,2025-03-12,2025-05-06,527,9.5,TechCorp Inc -AI14627,Data Scientist,104271,USD,104271,SE,FT,South Korea,L,Chile,50,"R, Tableau, Scala, Deep Learning",PhD,9,Automotive,2024-10-09,2024-10-28,2307,7.7,Machine Intelligence Group -AI14628,Deep Learning Engineer,53911,USD,53911,SE,FT,India,L,India,50,"Java, Scala, Statistics, Azure, Python",PhD,9,Healthcare,2024-02-10,2024-04-15,1406,6.8,Advanced Robotics -AI14629,Data Scientist,119029,GBP,89272,MI,CT,United Kingdom,L,United Kingdom,50,"Java, PyTorch, Tableau, Deep Learning",Bachelor,3,Transportation,2024-10-27,2024-11-21,1815,8,Advanced Robotics -AI14630,Data Engineer,213288,EUR,181295,EX,CT,Germany,S,Germany,50,"SQL, Docker, GCP, AWS, R",Master,10,Government,2024-02-28,2024-04-02,879,8.5,Autonomous Tech -AI14631,AI Product Manager,109524,USD,109524,MI,PT,Denmark,S,Canada,50,"SQL, Docker, Statistics, Python",Master,3,Manufacturing,2024-05-03,2024-07-06,1628,6.9,Algorithmic Solutions -AI14632,AI Product Manager,58198,USD,58198,MI,CT,China,L,China,50,"Scala, Hadoop, Computer Vision, Java, Python",PhD,4,Automotive,2024-04-13,2024-06-11,1765,6.8,Quantum Computing Inc -AI14633,AI Research Scientist,113671,USD,113671,MI,CT,United States,L,Mexico,100,"Python, PyTorch, GCP, R",Master,3,Technology,2024-06-26,2024-09-05,1239,7.3,Digital Transformation LLC -AI14634,Head of AI,49824,USD,49824,SE,CT,India,M,India,0,"TensorFlow, GCP, SQL, Scala",Bachelor,6,Government,2024-12-28,2025-01-28,2279,9.9,Cloud AI Solutions -AI14635,Autonomous Systems Engineer,89500,EUR,76075,EN,PT,Netherlands,L,Netherlands,100,"Docker, Scala, Tableau",PhD,0,Gaming,2024-09-30,2024-11-12,935,5.9,Smart Analytics -AI14636,AI Research Scientist,224343,USD,224343,EX,FT,South Korea,L,South Korea,0,"Mathematics, AWS, Python, Deep Learning, Azure",Master,13,Technology,2024-11-12,2024-12-16,572,7.9,AI Innovations -AI14637,AI Consultant,175920,SGD,228696,EX,FT,Singapore,M,Singapore,50,"PyTorch, Azure, Mathematics, GCP",Master,14,Retail,2024-07-05,2024-07-25,956,8.7,Digital Transformation LLC -AI14638,Data Engineer,158352,AUD,213775,SE,FL,Australia,L,Australia,50,"TensorFlow, Python, Statistics, Git, Computer Vision",PhD,8,Gaming,2025-01-21,2025-03-21,1254,9,Cognitive Computing -AI14639,NLP Engineer,99340,USD,99340,EX,FT,China,S,China,0,"Computer Vision, Mathematics, PyTorch, TensorFlow",Master,19,Healthcare,2024-09-11,2024-10-11,535,7.4,Autonomous Tech -AI14640,Research Scientist,62050,JPY,6825500,EN,CT,Japan,M,Japan,50,"MLOps, PyTorch, Data Visualization, Docker",Bachelor,0,Education,2025-04-19,2025-06-13,2134,5.1,Machine Intelligence Group -AI14641,Head of AI,73299,USD,73299,EN,CT,United States,L,Argentina,100,"Python, Docker, SQL, Statistics",Master,1,Finance,2024-05-02,2024-06-12,2290,6.4,DeepTech Ventures -AI14642,AI Research Scientist,127142,EUR,108071,SE,CT,Austria,L,Austria,50,"Kubernetes, Java, Python, AWS",Bachelor,6,Transportation,2024-08-13,2024-10-23,1104,8.6,Predictive Systems -AI14643,AI Research Scientist,103463,USD,103463,SE,CT,Israel,S,Israel,100,"R, AWS, Computer Vision",Bachelor,6,Media,2024-03-16,2024-04-23,1690,6,Cloud AI Solutions -AI14644,Research Scientist,81210,USD,81210,MI,CT,South Korea,S,South Korea,100,"Kubernetes, Linux, Data Visualization",Associate,3,Telecommunications,2024-07-10,2024-07-27,1925,9,AI Innovations -AI14645,Data Engineer,26249,USD,26249,EN,CT,India,M,India,50,"R, SQL, Computer Vision, Hadoop, PyTorch",PhD,0,Finance,2025-01-09,2025-02-05,2316,9.9,DataVision Ltd -AI14646,Research Scientist,92398,AUD,124737,MI,CT,Australia,L,Australia,0,"Kubernetes, Spark, TensorFlow",Bachelor,4,Gaming,2024-06-09,2024-06-26,1440,5.3,Cognitive Computing -AI14647,Deep Learning Engineer,81062,GBP,60797,EN,FL,United Kingdom,L,United Kingdom,50,"Kubernetes, Azure, MLOps, Git, Statistics",Bachelor,1,Technology,2025-03-10,2025-05-05,2360,7.4,AI Innovations -AI14648,AI Software Engineer,194332,CHF,174899,SE,FT,Switzerland,L,Switzerland,50,"Python, Git, TensorFlow, SQL",Bachelor,9,Government,2024-06-15,2024-07-09,2134,9.5,TechCorp Inc -AI14649,AI Research Scientist,166789,JPY,18346790,SE,FL,Japan,L,United Kingdom,0,"Python, Scala, Statistics, GCP, Computer Vision",Bachelor,5,Telecommunications,2024-06-11,2024-07-08,989,8.4,Neural Networks Co -AI14650,AI Product Manager,271121,USD,271121,EX,FL,United States,L,United States,50,"Azure, Mathematics, NLP, Spark",Bachelor,19,Government,2024-11-10,2025-01-15,2193,9.6,DeepTech Ventures -AI14651,Principal Data Scientist,121488,EUR,103265,SE,FL,Germany,S,Germany,100,"Python, Kubernetes, Git, Deep Learning",PhD,6,Automotive,2024-07-31,2024-10-07,799,8,Smart Analytics -AI14652,Machine Learning Engineer,146495,AUD,197768,EX,CT,Australia,S,Australia,0,"GCP, Deep Learning, SQL, Kubernetes, Linux",Associate,13,Consulting,2024-12-08,2025-01-19,1963,5.9,Quantum Computing Inc -AI14653,AI Consultant,113007,USD,113007,MI,CT,Denmark,S,Estonia,100,"Python, Tableau, SQL",Bachelor,2,Media,2025-01-11,2025-03-12,1510,5.2,DataVision Ltd -AI14654,AI Research Scientist,79500,USD,79500,EN,CT,United States,L,Luxembourg,100,"SQL, Scala, Hadoop, Deep Learning",PhD,0,Government,2024-04-12,2024-05-16,1217,6.4,Autonomous Tech -AI14655,Autonomous Systems Engineer,84593,SGD,109971,MI,PT,Singapore,M,Singapore,0,"Linux, Git, SQL",Associate,2,Transportation,2024-12-03,2025-02-08,2411,7.9,TechCorp Inc -AI14656,Head of AI,87458,EUR,74339,MI,FL,France,L,France,50,"Deep Learning, Linux, NLP, Computer Vision, SQL",Master,3,Automotive,2024-06-16,2024-08-05,2258,8.2,DataVision Ltd -AI14657,AI Specialist,207998,USD,207998,EX,CT,Norway,L,Norway,100,"Kubernetes, MLOps, Python, Data Visualization, Docker",Bachelor,19,Media,2025-04-26,2025-07-01,2207,7.6,Machine Intelligence Group -AI14658,ML Ops Engineer,53800,GBP,40350,EN,FL,United Kingdom,S,United Kingdom,0,"Hadoop, Data Visualization, Python, MLOps, NLP",PhD,1,Telecommunications,2024-10-05,2024-11-01,1568,9.7,Smart Analytics -AI14659,Machine Learning Researcher,56084,EUR,47671,EN,CT,Netherlands,M,Netherlands,50,"Tableau, Linux, Statistics",PhD,0,Media,2024-05-21,2024-07-31,1910,6.7,Digital Transformation LLC -AI14660,Robotics Engineer,92516,USD,92516,EN,FT,Norway,S,Norway,0,"Python, Kubernetes, MLOps, GCP, Spark",Bachelor,0,Retail,2025-02-16,2025-03-04,1766,9.7,Predictive Systems -AI14661,AI Product Manager,119724,USD,119724,EX,FL,China,M,China,0,"Docker, Python, MLOps",Associate,14,Telecommunications,2024-04-04,2024-05-04,1543,6.6,Cognitive Computing -AI14662,Machine Learning Researcher,104136,USD,104136,EX,FL,China,S,China,100,"Java, Computer Vision, NLP, R, MLOps",Bachelor,13,Manufacturing,2024-11-14,2025-01-02,647,8.6,Neural Networks Co -AI14663,Machine Learning Researcher,96383,USD,96383,MI,FT,Sweden,M,Sweden,0,"Spark, Git, Deep Learning, Computer Vision, Python",Associate,2,Media,2024-07-18,2024-09-26,543,8.5,Future Systems -AI14664,Robotics Engineer,75403,USD,75403,EN,FL,United States,L,United States,0,"Python, Data Visualization, TensorFlow, Computer Vision, Deep Learning",Bachelor,0,Transportation,2024-04-25,2024-05-26,2493,7.1,DataVision Ltd -AI14665,Machine Learning Researcher,100534,USD,100534,EN,FL,Denmark,M,Mexico,0,"Tableau, Git, Data Visualization",Master,1,Manufacturing,2024-09-15,2024-11-09,2459,7.8,Machine Intelligence Group -AI14666,Research Scientist,97918,USD,97918,MI,CT,Norway,S,Norway,0,"PyTorch, Python, Statistics, Git, Tableau",Associate,3,Government,2025-03-16,2025-04-15,1112,5.9,Machine Intelligence Group -AI14667,Principal Data Scientist,46643,USD,46643,EN,FL,Finland,S,Finland,50,"Data Visualization, Kubernetes, Python, Spark, NLP",Bachelor,1,Manufacturing,2024-08-22,2024-10-02,1297,9.3,DeepTech Ventures -AI14668,AI Product Manager,161683,EUR,137431,EX,FT,Germany,L,Germany,50,"Hadoop, SQL, Python, TensorFlow, MLOps",PhD,19,Energy,2024-04-30,2024-06-28,819,9.5,Cognitive Computing -AI14669,Data Scientist,78579,USD,78579,MI,CT,Israel,S,Israel,0,"Java, Data Visualization, MLOps, R, AWS",Associate,2,Telecommunications,2024-02-15,2024-04-20,1410,8.9,Predictive Systems -AI14670,AI Architect,98927,EUR,84088,MI,FT,Netherlands,S,Netherlands,0,"Tableau, GCP, Azure, Hadoop, Scala",Associate,3,Government,2024-01-29,2024-03-14,1021,8.2,Future Systems -AI14671,Computer Vision Engineer,74384,JPY,8182240,EN,FL,Japan,M,Japan,50,"Data Visualization, PyTorch, Deep Learning, NLP",Associate,1,Manufacturing,2024-08-08,2024-08-31,1730,8.2,Advanced Robotics -AI14672,AI Product Manager,203594,AUD,274852,EX,FT,Australia,L,Australia,0,"Java, Data Visualization, MLOps, SQL",Master,17,Technology,2024-01-13,2024-03-17,2249,9.3,TechCorp Inc -AI14673,Head of AI,304108,SGD,395340,EX,CT,Singapore,L,Singapore,0,"Python, TensorFlow, Kubernetes, Spark, Statistics",Bachelor,11,Retail,2024-12-25,2025-03-02,2030,7.1,Cloud AI Solutions -AI14674,AI Architect,128907,CAD,161134,SE,CT,Canada,M,Canada,0,"SQL, Azure, Python",Master,8,Energy,2025-02-19,2025-03-08,1987,6.9,DeepTech Ventures -AI14675,Machine Learning Researcher,103434,EUR,87919,MI,PT,Austria,M,Austria,100,"TensorFlow, Mathematics, Linux, SQL",PhD,2,Finance,2024-04-19,2024-05-27,1328,5.4,Digital Transformation LLC -AI14676,AI Specialist,126930,USD,126930,MI,FL,Norway,S,Norway,0,"Linux, Python, Computer Vision",Bachelor,2,Media,2025-02-11,2025-04-05,1625,7.2,Machine Intelligence Group -AI14677,Research Scientist,150089,EUR,127576,EX,FL,Germany,M,Germany,100,"Python, R, Java, Git, Tableau",Bachelor,19,Transportation,2025-02-22,2025-04-15,1964,7.4,Machine Intelligence Group -AI14678,Machine Learning Engineer,84084,CAD,105105,MI,FL,Canada,M,Singapore,0,"Java, PyTorch, Kubernetes, Azure, R",PhD,4,Media,2024-06-30,2024-09-01,1516,9.8,Algorithmic Solutions -AI14679,NLP Engineer,137388,USD,137388,SE,CT,South Korea,L,South Korea,100,"Docker, PyTorch, Kubernetes",Bachelor,8,Technology,2024-07-18,2024-09-02,2379,6.2,Advanced Robotics -AI14680,AI Consultant,70308,USD,70308,MI,PT,Finland,M,Finland,100,"SQL, Scala, Git, PyTorch",PhD,4,Real Estate,2024-07-21,2024-09-02,1317,8,TechCorp Inc -AI14681,AI Product Manager,121990,SGD,158587,MI,PT,Singapore,L,Ireland,50,"SQL, Linux, TensorFlow",Master,2,Technology,2024-03-06,2024-04-16,926,9,DataVision Ltd -AI14682,ML Ops Engineer,69409,USD,69409,EN,CT,Sweden,L,Sweden,0,"AWS, Mathematics, GCP, Azure",Master,1,Consulting,2024-06-09,2024-08-19,594,5.5,Future Systems -AI14683,AI Research Scientist,89827,USD,89827,EN,CT,Denmark,M,Denmark,0,"Tableau, Java, Data Visualization, Python",Master,1,Consulting,2024-10-17,2024-11-20,1703,9.2,Smart Analytics -AI14684,Head of AI,48806,USD,48806,SE,PT,China,S,China,50,"Python, Computer Vision, Hadoop, Scala, Git",Bachelor,6,Retail,2024-10-27,2024-12-17,1758,6.4,AI Innovations -AI14685,Head of AI,94120,CAD,117650,SE,FT,Canada,S,Canada,0,"PyTorch, SQL, NLP",Associate,6,Finance,2024-11-13,2025-01-19,2290,5.4,Quantum Computing Inc -AI14686,Data Analyst,175493,USD,175493,SE,FL,United States,L,United States,100,"Kubernetes, NLP, Scala, MLOps, Spark",PhD,5,Media,2024-05-26,2024-06-28,2336,5.7,Predictive Systems -AI14687,Data Scientist,257356,EUR,218753,EX,CT,Austria,L,Austria,50,"Python, Spark, Mathematics, Git",Master,16,Energy,2024-01-20,2024-02-12,2229,8.3,TechCorp Inc -AI14688,Computer Vision Engineer,200799,CAD,250999,EX,FL,Canada,M,Canada,50,"Linux, Tableau, Docker",Bachelor,15,Healthcare,2024-06-14,2024-07-05,1406,6.5,AI Innovations -AI14689,Data Scientist,210158,EUR,178634,EX,PT,Austria,M,Czech Republic,0,"SQL, PyTorch, Mathematics",Bachelor,15,Transportation,2024-11-22,2025-01-24,1727,8.6,Smart Analytics -AI14690,Autonomous Systems Engineer,46770,USD,46770,EN,FL,Sweden,S,Switzerland,0,"AWS, Kubernetes, Tableau, GCP, Linux",Associate,0,Healthcare,2024-11-28,2025-01-25,1620,5.6,TechCorp Inc -AI14691,Data Engineer,114132,CHF,102719,MI,CT,Switzerland,M,Switzerland,50,"Java, TensorFlow, SQL, Deep Learning",Associate,4,Real Estate,2024-05-24,2024-06-30,2162,7.2,AI Innovations -AI14692,Computer Vision Engineer,71064,USD,71064,EN,FT,Ireland,S,Ireland,0,"Docker, Python, TensorFlow, R",Master,1,Automotive,2024-06-11,2024-08-15,2497,5.7,Cloud AI Solutions -AI14693,Data Scientist,181541,SGD,236003,SE,FT,Singapore,L,Singapore,50,"Tableau, Hadoop, SQL, MLOps, Git",Master,5,Finance,2024-04-19,2024-05-06,1193,8.1,Future Systems -AI14694,Research Scientist,24046,USD,24046,EN,PT,China,S,China,100,"SQL, Python, Java, GCP, Computer Vision",PhD,0,Automotive,2025-02-24,2025-04-05,2443,7.6,Neural Networks Co -AI14695,AI Specialist,107262,USD,107262,SE,CT,South Korea,M,South Korea,50,"Java, Computer Vision, Mathematics",PhD,5,Government,2024-12-02,2024-12-30,2342,9.6,Neural Networks Co -AI14696,Head of AI,120857,USD,120857,SE,FL,South Korea,L,South Korea,50,"Python, TensorFlow, Deep Learning",PhD,9,Finance,2024-06-05,2024-07-05,1291,5.6,Algorithmic Solutions -AI14697,Head of AI,71387,CAD,89234,EN,CT,Canada,M,Canada,0,"Docker, Git, Python",Master,0,Finance,2024-02-11,2024-03-29,2059,5.9,Neural Networks Co -AI14698,Data Engineer,64859,USD,64859,MI,PT,South Korea,S,South Korea,0,"MLOps, Git, Python",PhD,4,Energy,2025-04-24,2025-06-14,2136,5.9,Neural Networks Co -AI14699,AI Consultant,69368,JPY,7630480,EN,FT,Japan,M,Japan,0,"Kubernetes, Computer Vision, Git",PhD,0,Consulting,2024-03-16,2024-04-22,550,8,Advanced Robotics -AI14700,AI Product Manager,57640,EUR,48994,EN,PT,Netherlands,M,Netherlands,50,"Java, Linux, Spark, Azure",Bachelor,0,Real Estate,2024-07-20,2024-08-11,2226,8,Cloud AI Solutions -AI14701,Research Scientist,100171,CAD,125214,SE,FT,Canada,S,Canada,0,"Git, MLOps, Linux, Data Visualization, Azure",Bachelor,5,Transportation,2024-02-08,2024-03-07,1994,5,Advanced Robotics -AI14702,Deep Learning Engineer,66219,SGD,86085,EN,CT,Singapore,S,Singapore,100,"GCP, Data Visualization, Azure, AWS",PhD,0,Retail,2024-12-23,2025-02-25,1170,6.5,Cognitive Computing -AI14703,Deep Learning Engineer,133384,EUR,113376,EX,PT,Austria,S,Austria,0,"Python, TensorFlow, Tableau",Master,11,Real Estate,2024-01-07,2024-03-03,1888,8.8,TechCorp Inc -AI14704,Machine Learning Researcher,133208,EUR,113227,SE,FL,Netherlands,L,Japan,100,"Git, Data Visualization, SQL",Bachelor,8,Media,2024-06-06,2024-08-17,640,7.6,Advanced Robotics -AI14705,AI Consultant,179309,USD,179309,EX,FT,Ireland,S,Ireland,0,"Data Visualization, R, Linux",Associate,15,Telecommunications,2024-01-18,2024-02-18,1899,8,DeepTech Ventures -AI14706,Principal Data Scientist,85394,JPY,9393340,MI,FL,Japan,S,Japan,0,"Azure, Scala, Deep Learning, GCP, AWS",PhD,4,Transportation,2024-09-29,2024-11-01,557,7.1,Digital Transformation LLC -AI14707,NLP Engineer,150883,AUD,203692,SE,FT,Australia,L,Australia,0,"Hadoop, Git, Spark, SQL, Python",PhD,5,Education,2024-12-26,2025-01-16,2237,7.9,Autonomous Tech -AI14708,Research Scientist,140306,JPY,15433660,EX,FL,Japan,S,Turkey,100,"Kubernetes, PyTorch, Data Visualization, Hadoop, Docker",Master,15,Finance,2025-03-04,2025-04-07,2469,8.7,Quantum Computing Inc -AI14709,ML Ops Engineer,132345,USD,132345,MI,CT,Norway,L,Switzerland,100,"MLOps, PyTorch, Data Visualization, Scala",Associate,3,Retail,2025-01-29,2025-03-14,1930,7.7,DataVision Ltd -AI14710,AI Specialist,81632,EUR,69387,EN,CT,Germany,L,Netherlands,0,"Scala, Python, NLP, Tableau, Git",PhD,0,Healthcare,2024-04-09,2024-04-26,1361,7.6,Future Systems -AI14711,Robotics Engineer,145334,SGD,188934,SE,FT,Singapore,M,Singapore,0,"NLP, Java, Python, Statistics, Deep Learning",PhD,9,Energy,2025-03-28,2025-05-21,2432,8.3,AI Innovations -AI14712,AI Product Manager,103134,CHF,92821,EN,CT,Switzerland,M,Switzerland,100,"Spark, R, GCP, TensorFlow, PyTorch",Master,0,Media,2024-09-14,2024-11-23,679,6.6,Digital Transformation LLC -AI14713,Machine Learning Engineer,73844,USD,73844,EN,PT,Denmark,M,Denmark,50,"SQL, Statistics, MLOps, Mathematics",Associate,0,Transportation,2024-04-03,2024-05-20,1162,7,DataVision Ltd -AI14714,NLP Engineer,53224,USD,53224,EN,PT,Israel,S,Israel,50,"Python, Mathematics, Kubernetes",Associate,0,Telecommunications,2024-11-29,2025-01-30,1152,7.7,TechCorp Inc -AI14715,NLP Engineer,96148,USD,96148,EN,FL,Norway,L,Norway,50,"SQL, GCP, Kubernetes, PyTorch",Associate,0,Transportation,2025-02-18,2025-05-02,1244,9.6,Advanced Robotics -AI14716,AI Research Scientist,61479,USD,61479,MI,FL,South Korea,M,South Korea,50,"Docker, Hadoop, TensorFlow, Spark",Master,3,Finance,2024-06-19,2024-07-15,1985,6,Predictive Systems -AI14717,AI Product Manager,89485,CHF,80537,EN,FL,Switzerland,L,Switzerland,50,"Scala, GCP, Statistics, Python",Master,1,Automotive,2025-03-13,2025-05-08,660,5.9,TechCorp Inc -AI14718,AI Specialist,119054,AUD,160723,MI,FT,Australia,L,Australia,100,"Git, Python, R",PhD,2,Manufacturing,2024-10-02,2024-11-15,1819,8.1,Neural Networks Co -AI14719,Data Scientist,39720,USD,39720,SE,FT,India,S,India,0,"R, Kubernetes, Python",Bachelor,9,Automotive,2024-01-14,2024-03-07,580,7.3,DeepTech Ventures -AI14720,Deep Learning Engineer,148540,GBP,111405,SE,FT,United Kingdom,L,United Kingdom,100,"Hadoop, Computer Vision, Git, Azure, Tableau",Master,5,Retail,2025-04-11,2025-05-09,643,6.5,Advanced Robotics -AI14721,AI Architect,67388,USD,67388,EN,PT,Ireland,S,Ireland,0,"MLOps, SQL, Linux, Git",Master,1,Media,2024-04-11,2024-05-19,835,5.6,Advanced Robotics -AI14722,Machine Learning Researcher,71198,USD,71198,MI,PT,South Korea,L,South Korea,50,"SQL, Scala, Hadoop, AWS",PhD,3,Government,2024-09-26,2024-10-28,2030,5.2,TechCorp Inc -AI14723,Computer Vision Engineer,114413,USD,114413,MI,PT,United States,L,United States,0,"MLOps, PyTorch, Kubernetes, TensorFlow, AWS",PhD,4,Real Estate,2024-07-12,2024-09-12,1436,7.9,Digital Transformation LLC -AI14724,AI Research Scientist,75404,USD,75404,EN,PT,United States,M,United States,50,"Python, Hadoop, Java, TensorFlow, Computer Vision",Associate,0,Transportation,2024-10-17,2024-11-16,2155,5.8,Quantum Computing Inc -AI14725,Data Scientist,72723,USD,72723,MI,FL,South Korea,M,South Korea,0,"Computer Vision, Python, SQL, R",Bachelor,3,Technology,2024-01-18,2024-02-13,2430,9.7,Predictive Systems -AI14726,Data Analyst,87914,USD,87914,EX,CT,China,M,China,100,"Spark, Python, Git, Docker",PhD,14,Technology,2024-08-22,2024-09-13,1342,6.6,Smart Analytics -AI14727,Machine Learning Engineer,121462,EUR,103243,SE,CT,Germany,L,Germany,0,"Kubernetes, Java, Computer Vision",Associate,7,Healthcare,2024-03-08,2024-04-08,1728,8.5,Future Systems -AI14728,AI Specialist,28481,USD,28481,EN,FL,China,S,China,50,"Scala, Spark, Git",Associate,0,Energy,2025-01-04,2025-02-12,2191,7.9,Advanced Robotics -AI14729,AI Consultant,168933,SGD,219613,EX,CT,Singapore,L,Singapore,0,"Linux, MLOps, Python, TensorFlow, NLP",Bachelor,11,Automotive,2024-05-22,2024-07-08,2084,9.9,Neural Networks Co -AI14730,AI Consultant,116189,USD,116189,MI,CT,Sweden,L,Sweden,50,"Python, GCP, Tableau, Deep Learning",PhD,3,Education,2024-05-04,2024-06-15,1686,6.9,Neural Networks Co -AI14731,Autonomous Systems Engineer,162901,USD,162901,EX,FL,Norway,S,Nigeria,0,"Scala, Kubernetes, Linux, NLP",PhD,12,Retail,2024-04-21,2024-05-14,1580,7.4,AI Innovations -AI14732,Data Scientist,312986,USD,312986,EX,CT,Norway,M,Norway,0,"Git, Docker, Deep Learning, Hadoop",Associate,17,Technology,2024-05-23,2024-07-21,2326,6.7,Autonomous Tech -AI14733,Data Engineer,118449,EUR,100682,SE,PT,France,L,France,100,"Python, TensorFlow, Azure, Computer Vision",Associate,8,Manufacturing,2024-02-27,2024-05-07,2232,6.7,DataVision Ltd -AI14734,AI Research Scientist,105386,EUR,89578,MI,PT,Germany,M,Germany,0,"Java, Mathematics, Kubernetes",Bachelor,2,Finance,2024-06-08,2024-08-14,1140,8.7,TechCorp Inc -AI14735,AI Specialist,79025,EUR,67171,MI,FL,Netherlands,S,Netherlands,50,"Python, MLOps, Git, TensorFlow",Bachelor,3,Technology,2024-02-05,2024-04-09,686,5.1,Predictive Systems -AI14736,Research Scientist,102196,USD,102196,MI,PT,Sweden,M,Russia,100,"Python, Spark, Hadoop, Statistics",Master,2,Gaming,2024-01-15,2024-03-10,1781,6.5,DeepTech Ventures -AI14737,NLP Engineer,67175,EUR,57099,EN,FL,Austria,S,Austria,50,"Deep Learning, PyTorch, Linux, Java, AWS",Bachelor,1,Retail,2024-08-25,2024-10-23,782,9.3,Machine Intelligence Group -AI14738,ML Ops Engineer,59042,AUD,79707,EN,CT,Australia,S,Australia,0,"Data Visualization, SQL, Statistics, MLOps, Spark",PhD,1,Manufacturing,2024-06-19,2024-08-02,1419,6.6,Machine Intelligence Group -AI14739,AI Consultant,245998,CHF,221398,EX,PT,Switzerland,S,Russia,100,"Python, Mathematics, Scala, GCP",Associate,15,Consulting,2024-04-12,2024-05-24,1628,9.4,Future Systems -AI14740,AI Specialist,48852,SGD,63508,EN,CT,Singapore,S,Singapore,0,"Docker, TensorFlow, Git, GCP, AWS",Master,0,Finance,2025-01-18,2025-02-25,2134,8.4,Digital Transformation LLC -AI14741,AI Software Engineer,133871,EUR,113790,SE,CT,Netherlands,S,Netherlands,100,"Python, TensorFlow, Statistics, PyTorch, Git",Master,9,Technology,2024-03-13,2024-05-22,736,5.1,Quantum Computing Inc -AI14742,Machine Learning Researcher,210751,CHF,189676,EX,FT,Switzerland,S,Switzerland,100,"SQL, GCP, Spark",Associate,16,Government,2024-09-12,2024-09-29,506,5,Cognitive Computing -AI14743,Machine Learning Researcher,178193,CHF,160374,SE,PT,Switzerland,S,South Africa,0,"Python, SQL, Azure, TensorFlow, Git",Associate,5,Consulting,2024-11-29,2025-01-11,2214,5.5,TechCorp Inc -AI14744,Robotics Engineer,119308,USD,119308,SE,FL,Sweden,M,Sweden,100,"Scala, R, Azure",Master,5,Manufacturing,2024-01-20,2024-02-26,857,7.9,Future Systems -AI14745,Robotics Engineer,153010,EUR,130059,EX,FT,Austria,L,Austria,50,"Python, SQL, Java, Docker",Master,17,Consulting,2024-07-12,2024-08-24,2272,9.5,Neural Networks Co -AI14746,Principal Data Scientist,52312,AUD,70621,EN,FL,Australia,S,Australia,50,"SQL, Kubernetes, Docker",Master,1,Transportation,2024-06-28,2024-08-29,1897,9.4,Quantum Computing Inc -AI14747,NLP Engineer,240647,AUD,324873,EX,FL,Australia,M,Sweden,0,"Docker, NLP, Linux, Python",Bachelor,17,Government,2025-03-06,2025-05-05,1227,9,Digital Transformation LLC -AI14748,Autonomous Systems Engineer,68811,EUR,58489,EN,FT,Germany,M,Germany,0,"Spark, Linux, GCP, Scala",Associate,1,Energy,2025-02-18,2025-03-05,791,9.9,Digital Transformation LLC -AI14749,Data Engineer,133800,SGD,173940,MI,FT,Singapore,L,Belgium,100,"SQL, Docker, Java, R",Bachelor,2,Manufacturing,2024-05-08,2024-06-23,944,5.6,DeepTech Ventures -AI14750,AI Research Scientist,110037,AUD,148550,MI,PT,Australia,L,Australia,50,"SQL, Kubernetes, Tableau, Hadoop",Associate,2,Telecommunications,2025-04-13,2025-05-29,1320,6,Autonomous Tech -AI14751,Machine Learning Researcher,43790,USD,43790,SE,PT,India,L,Chile,50,"R, SQL, GCP",Associate,6,Education,2024-05-16,2024-07-25,850,10,Cloud AI Solutions -AI14752,AI Specialist,101457,USD,101457,MI,CT,Ireland,M,Argentina,50,"Python, SQL, Azure",PhD,4,Education,2024-05-12,2024-06-29,2256,7.5,DataVision Ltd -AI14753,AI Specialist,82442,SGD,107175,MI,FL,Singapore,S,Singapore,100,"AWS, TensorFlow, Git",Associate,3,Transportation,2024-02-28,2024-03-16,2365,8.8,Machine Intelligence Group -AI14754,AI Product Manager,76359,USD,76359,EN,CT,Israel,L,Israel,0,"Hadoop, MLOps, Java, Computer Vision, Mathematics",PhD,0,Education,2024-01-31,2024-03-19,1856,9.6,Advanced Robotics -AI14755,AI Specialist,166212,USD,166212,SE,PT,Sweden,L,Sweden,100,"Linux, Spark, Computer Vision, Data Visualization, Python",PhD,7,Manufacturing,2024-04-24,2024-06-27,1511,7.3,Future Systems -AI14756,Head of AI,74070,EUR,62960,MI,FL,Austria,M,Austria,0,"Python, Statistics, Computer Vision",Master,4,Media,2024-01-01,2024-02-25,708,9.8,Cognitive Computing -AI14757,Machine Learning Researcher,23662,USD,23662,EN,FT,India,S,India,0,"SQL, Data Visualization, PyTorch",PhD,0,Real Estate,2024-10-02,2024-10-25,2397,7.1,Machine Intelligence Group -AI14758,Data Scientist,68764,EUR,58449,EN,FL,France,M,Estonia,0,"GCP, TensorFlow, Azure",Bachelor,1,Consulting,2024-09-09,2024-10-14,1164,7,Quantum Computing Inc -AI14759,Research Scientist,55947,USD,55947,EN,CT,Sweden,M,Sweden,100,"Mathematics, Java, PyTorch, Azure",Associate,0,Real Estate,2025-04-21,2025-05-19,806,9,Future Systems -AI14760,AI Product Manager,174977,CHF,157479,SE,PT,Switzerland,L,Switzerland,50,"Tableau, Computer Vision, Spark, Azure, SQL",Master,7,Automotive,2024-08-21,2024-10-11,1609,9.6,Predictive Systems -AI14761,Principal Data Scientist,141796,SGD,184335,SE,PT,Singapore,S,Singapore,50,"Scala, Spark, Python, TensorFlow, Computer Vision",Bachelor,8,Government,2024-04-05,2024-05-09,1338,8.1,AI Innovations -AI14762,Machine Learning Researcher,72370,USD,72370,EX,FL,China,S,China,0,"SQL, Python, Spark, Deep Learning, MLOps",Associate,11,Technology,2024-07-26,2024-08-23,1131,6.9,Autonomous Tech -AI14763,NLP Engineer,90342,EUR,76791,EN,FL,Germany,L,Argentina,50,"Kubernetes, NLP, SQL, PyTorch, R",Associate,0,Manufacturing,2024-08-19,2024-09-03,810,7.3,TechCorp Inc -AI14764,AI Software Engineer,65389,AUD,88275,EN,CT,Australia,S,Poland,0,"Java, Spark, Python, Azure, AWS",PhD,1,Energy,2024-03-02,2024-04-13,848,6.3,TechCorp Inc -AI14765,Robotics Engineer,191753,AUD,258867,EX,FT,Australia,S,Argentina,50,"R, Kubernetes, Scala, Deep Learning, Mathematics",Associate,18,Government,2024-05-06,2024-06-07,1998,5.8,Machine Intelligence Group -AI14766,Computer Vision Engineer,87202,GBP,65402,MI,FT,United Kingdom,S,United Kingdom,50,"Docker, SQL, Java, TensorFlow",Associate,4,Education,2024-04-20,2024-06-22,726,6.4,DeepTech Ventures -AI14767,Research Scientist,78313,USD,78313,MI,FL,Finland,M,Finland,50,"SQL, Data Visualization, Java",Associate,4,Education,2024-09-19,2024-11-04,1662,6.6,Neural Networks Co -AI14768,Principal Data Scientist,65799,USD,65799,EN,FT,United States,M,United States,0,"NLP, R, Kubernetes",PhD,0,Real Estate,2025-01-10,2025-03-14,1239,9.1,Advanced Robotics -AI14769,Research Scientist,29517,USD,29517,EN,CT,China,M,Mexico,50,"GCP, SQL, MLOps, NLP",Associate,0,Technology,2024-08-26,2024-11-05,2343,8.9,Digital Transformation LLC -AI14770,AI Product Manager,81826,USD,81826,EX,CT,India,L,India,0,"PyTorch, SQL, Kubernetes, Statistics",Associate,13,Transportation,2025-02-11,2025-04-07,1718,5.1,DeepTech Ventures -AI14771,Principal Data Scientist,117961,AUD,159247,MI,CT,Australia,L,Australia,100,"Data Visualization, GCP, Hadoop, MLOps",Bachelor,4,Education,2024-12-18,2025-01-01,1811,6.5,DeepTech Ventures -AI14772,AI Specialist,120810,USD,120810,EX,CT,China,L,Japan,100,"Mathematics, Python, Tableau",Bachelor,17,Automotive,2025-01-13,2025-01-27,2403,8.4,Cognitive Computing -AI14773,Data Analyst,43667,USD,43667,MI,FT,China,M,Israel,50,"Spark, Python, Docker, Git",Master,4,Education,2024-05-17,2024-06-22,1403,8.6,Predictive Systems -AI14774,Head of AI,128893,USD,128893,SE,FT,Finland,M,Finland,50,"Java, Linux, Deep Learning, Spark, Mathematics",Master,6,Transportation,2024-06-26,2024-07-13,1199,6.7,Quantum Computing Inc -AI14775,ML Ops Engineer,119069,CAD,148836,SE,FT,Canada,M,Canada,50,"PyTorch, GCP, TensorFlow",Bachelor,8,Energy,2024-07-24,2024-09-30,2205,7.6,Machine Intelligence Group -AI14776,NLP Engineer,66333,AUD,89550,EN,FL,Australia,M,Australia,100,"SQL, Kubernetes, Hadoop",Bachelor,1,Retail,2024-09-30,2024-10-21,2227,6.8,Algorithmic Solutions -AI14777,Machine Learning Researcher,89432,USD,89432,MI,FT,South Korea,L,South Korea,0,"GCP, Data Visualization, Kubernetes, Docker",Associate,2,Education,2025-02-28,2025-04-17,1204,8.6,Predictive Systems -AI14778,AI Consultant,56324,EUR,47875,EN,FL,Netherlands,S,Latvia,100,"Git, Mathematics, R",Associate,1,Retail,2024-01-18,2024-03-15,853,9.1,Machine Intelligence Group -AI14779,Research Scientist,145285,USD,145285,MI,FT,United States,L,United States,100,"R, Mathematics, Kubernetes, NLP",Associate,3,Gaming,2024-04-04,2024-05-07,1091,6.9,Future Systems -AI14780,AI Product Manager,227003,USD,227003,EX,FL,Israel,L,China,50,"SQL, AWS, GCP, Kubernetes",Associate,19,Education,2024-01-21,2024-03-23,858,5,Cloud AI Solutions -AI14781,Deep Learning Engineer,123976,EUR,105380,EX,CT,Germany,S,Germany,0,"Linux, Hadoop, Spark, Python",Bachelor,12,Education,2024-09-08,2024-11-08,742,7.2,Quantum Computing Inc -AI14782,Principal Data Scientist,63982,USD,63982,EN,PT,Sweden,S,Sweden,100,"Scala, TensorFlow, MLOps, Git, Computer Vision",Associate,1,Telecommunications,2024-07-08,2024-08-23,1255,8.9,TechCorp Inc -AI14783,Data Scientist,26617,USD,26617,EN,CT,India,M,India,0,"GCP, Kubernetes, Mathematics, NLP",Associate,0,Gaming,2025-04-21,2025-05-16,1994,8.2,Autonomous Tech -AI14784,Data Scientist,213307,CHF,191976,EX,FT,Switzerland,S,Switzerland,50,"Computer Vision, Python, TensorFlow, Linux",Bachelor,19,Education,2024-12-12,2025-02-21,2249,6.8,Cognitive Computing -AI14785,Machine Learning Engineer,68856,USD,68856,MI,CT,Finland,M,Finland,0,"GCP, Python, Spark",Associate,4,Government,2024-10-16,2024-10-31,1095,9.7,Autonomous Tech -AI14786,Head of AI,75179,USD,75179,EN,FT,United States,S,United States,0,"Kubernetes, Python, Linux, AWS, Deep Learning",PhD,0,Healthcare,2024-12-03,2025-01-22,1923,8.3,Autonomous Tech -AI14787,ML Ops Engineer,164858,AUD,222558,SE,FT,Australia,L,Australia,0,"AWS, Azure, PyTorch, Data Visualization",Bachelor,6,Gaming,2024-08-26,2024-10-31,1342,8.6,Autonomous Tech -AI14788,AI Software Engineer,70806,USD,70806,SE,FL,China,M,Germany,50,"Tableau, Spark, Scala",PhD,6,Manufacturing,2024-06-24,2024-08-16,1063,8.6,Digital Transformation LLC -AI14789,ML Ops Engineer,118788,USD,118788,SE,FT,Finland,L,Mexico,50,"Hadoop, Python, SQL",Master,7,Education,2025-04-29,2025-05-26,1420,9.1,Neural Networks Co -AI14790,AI Software Engineer,60352,AUD,81475,EN,FT,Australia,M,New Zealand,50,"Kubernetes, Java, MLOps, Azure",PhD,1,Energy,2024-01-29,2024-02-22,808,9.6,Digital Transformation LLC -AI14791,AI Software Engineer,87016,CAD,108770,MI,PT,Canada,L,South Korea,50,"Tableau, Docker, Java, GCP",Master,4,Healthcare,2024-02-16,2024-04-13,1869,6,Quantum Computing Inc -AI14792,Principal Data Scientist,192474,AUD,259840,EX,FL,Australia,M,Turkey,50,"Linux, R, Tableau",PhD,11,Finance,2024-01-21,2024-04-01,1558,7.5,Cloud AI Solutions -AI14793,Head of AI,83774,JPY,9215140,MI,FT,Japan,S,Japan,0,"NLP, TensorFlow, Scala, Docker",Associate,3,Energy,2024-10-06,2024-11-18,1800,6.6,Machine Intelligence Group -AI14794,Data Scientist,177589,CHF,159830,SE,CT,Switzerland,S,Switzerland,50,"Kubernetes, Python, TensorFlow, PyTorch, R",Associate,7,Education,2024-01-28,2024-04-03,1582,5.6,DeepTech Ventures -AI14795,Computer Vision Engineer,63063,USD,63063,EN,FT,Sweden,L,Argentina,50,"R, Hadoop, Linux, Statistics, Spark",PhD,1,Healthcare,2025-04-02,2025-04-24,557,7.9,Cognitive Computing -AI14796,AI Specialist,32842,USD,32842,MI,FT,India,L,Romania,100,"Python, Git, Data Visualization, Java, Statistics",Master,3,Telecommunications,2024-07-20,2024-08-26,2406,5.8,Cognitive Computing -AI14797,Robotics Engineer,307133,USD,307133,EX,FT,Norway,M,Norway,0,"PyTorch, Hadoop, Scala",Master,18,Manufacturing,2025-03-06,2025-05-11,1874,5.8,Neural Networks Co -AI14798,Deep Learning Engineer,260543,JPY,28659730,EX,CT,Japan,M,Latvia,100,"R, Mathematics, Deep Learning",PhD,17,Manufacturing,2025-01-16,2025-03-29,1213,5.5,Quantum Computing Inc -AI14799,AI Specialist,44958,USD,44958,SE,PT,China,S,China,0,"GCP, Azure, NLP",Associate,9,Gaming,2024-11-22,2025-01-17,684,6.2,Smart Analytics -AI14800,Head of AI,131487,AUD,177507,SE,CT,Australia,S,Australia,50,"Python, R, TensorFlow, Deep Learning",PhD,8,Real Estate,2025-04-24,2025-06-18,1130,7.6,Advanced Robotics -AI14801,AI Architect,59373,EUR,50467,EN,PT,Netherlands,M,Netherlands,100,"Python, Mathematics, TensorFlow, Kubernetes",Master,0,Consulting,2024-11-30,2025-01-05,1456,8.2,Smart Analytics -AI14802,Machine Learning Engineer,142471,USD,142471,SE,FT,Finland,M,Finland,50,"TensorFlow, Hadoop, Data Visualization, NLP",Associate,9,Technology,2024-11-18,2024-12-24,1489,6.2,Digital Transformation LLC -AI14803,AI Specialist,33282,USD,33282,MI,PT,India,L,India,50,"SQL, Azure, Kubernetes, Deep Learning",PhD,3,Energy,2024-12-21,2025-01-30,2210,6.1,Autonomous Tech -AI14804,AI Architect,70038,EUR,59532,MI,FL,Austria,M,Austria,50,"Git, PyTorch, Deep Learning",Associate,3,Finance,2024-03-12,2024-03-28,1625,8.5,Machine Intelligence Group -AI14805,Machine Learning Engineer,74946,USD,74946,EN,CT,Denmark,M,Austria,100,"SQL, Java, Azure",Bachelor,0,Government,2024-12-16,2025-02-02,2150,9.3,Algorithmic Solutions -AI14806,Data Scientist,45967,USD,45967,MI,FL,China,S,Ghana,50,"SQL, Computer Vision, AWS",PhD,3,Gaming,2024-11-19,2024-12-21,1627,7.2,Future Systems -AI14807,Principal Data Scientist,292646,SGD,380440,EX,PT,Singapore,L,Singapore,50,"GCP, Git, Azure",PhD,14,Energy,2024-04-23,2024-05-11,846,7.6,Neural Networks Co -AI14808,Data Scientist,133770,USD,133770,MI,PT,United States,L,United States,100,"Java, Mathematics, SQL, PyTorch, Docker",Bachelor,2,Retail,2024-05-19,2024-07-15,2117,7.4,Predictive Systems -AI14809,Principal Data Scientist,103086,USD,103086,MI,CT,Sweden,M,Sweden,0,"Mathematics, SQL, Tableau",Associate,3,Consulting,2024-03-10,2024-04-13,2029,5.9,Cognitive Computing -AI14810,Data Scientist,151977,USD,151977,EX,FT,Israel,S,Israel,100,"Java, PyTorch, Mathematics, Docker, Spark",Bachelor,18,Energy,2024-10-02,2024-10-24,792,7.3,Autonomous Tech -AI14811,AI Software Engineer,42791,USD,42791,MI,FL,India,L,Singapore,100,"Statistics, SQL, PyTorch, AWS",Master,2,Automotive,2024-06-29,2024-08-01,1814,6.1,Cognitive Computing -AI14812,Robotics Engineer,145130,USD,145130,EX,CT,Finland,M,Finland,50,"Java, Linux, Git, AWS",Associate,16,Transportation,2024-03-15,2024-04-30,1409,8.8,DataVision Ltd -AI14813,AI Specialist,50395,USD,50395,EN,CT,Finland,M,Thailand,0,"Git, NLP, Java, Python",PhD,1,Media,2024-12-28,2025-01-12,2037,9.8,TechCorp Inc -AI14814,Deep Learning Engineer,164649,EUR,139952,EX,FL,France,M,France,100,"Git, Python, Spark, Deep Learning",Associate,18,Energy,2025-03-20,2025-04-23,2316,9.6,Quantum Computing Inc -AI14815,Deep Learning Engineer,269435,EUR,229020,EX,PT,Netherlands,L,Netherlands,100,"Git, TensorFlow, Data Visualization",Associate,13,Real Estate,2024-10-23,2024-12-26,2295,9.9,Advanced Robotics -AI14816,Data Engineer,224881,USD,224881,SE,CT,Denmark,L,Denmark,0,"PyTorch, R, Docker, Statistics, Computer Vision",Bachelor,5,Technology,2024-05-16,2024-07-16,1110,9.6,AI Innovations -AI14817,Research Scientist,75931,JPY,8352410,EN,CT,Japan,S,Japan,50,"Azure, PyTorch, Mathematics, SQL, Python",Bachelor,1,Healthcare,2025-04-29,2025-07-02,1616,6.2,Algorithmic Solutions -AI14818,Machine Learning Researcher,138815,EUR,117993,SE,FT,Germany,M,Germany,100,"Statistics, Git, Data Visualization",Master,8,Energy,2025-04-13,2025-05-30,589,7.8,DataVision Ltd -AI14819,Head of AI,302646,CHF,272381,EX,PT,Switzerland,L,Switzerland,100,"Git, R, Hadoop",Associate,13,Finance,2024-03-08,2024-04-17,1931,7.7,Neural Networks Co -AI14820,Data Analyst,84254,AUD,113743,MI,PT,Australia,S,Australia,0,"Git, PyTorch, SQL",Bachelor,2,Education,2024-03-20,2024-05-22,1957,7,Cloud AI Solutions -AI14821,Robotics Engineer,91671,GBP,68753,MI,CT,United Kingdom,L,United Kingdom,100,"Spark, Tableau, Git, GCP",Associate,3,Retail,2024-08-29,2024-10-06,2086,5.6,AI Innovations -AI14822,NLP Engineer,140621,JPY,15468310,SE,PT,Japan,L,Japan,100,"Data Visualization, Python, Java, Statistics",Bachelor,8,Energy,2024-12-04,2025-01-11,1005,5.2,Neural Networks Co -AI14823,Robotics Engineer,93091,USD,93091,MI,PT,Israel,S,Israel,50,"Scala, AWS, Azure, Python",PhD,4,Telecommunications,2024-11-29,2024-12-20,2271,8,Cognitive Computing -AI14824,AI Architect,69964,USD,69964,MI,PT,Israel,S,Malaysia,100,"MLOps, PyTorch, Kubernetes, NLP, Mathematics",Bachelor,2,Consulting,2024-11-15,2025-01-24,2121,6.5,AI Innovations -AI14825,Deep Learning Engineer,235481,GBP,176611,EX,FL,United Kingdom,S,France,100,"Tableau, Linux, MLOps, Python",Master,14,Telecommunications,2024-02-01,2024-04-10,1339,7.5,Algorithmic Solutions -AI14826,Principal Data Scientist,104957,GBP,78718,MI,PT,United Kingdom,M,United Kingdom,0,"Computer Vision, PyTorch, SQL",PhD,3,Manufacturing,2024-06-09,2024-06-23,1178,7.2,Algorithmic Solutions -AI14827,AI Product Manager,70827,EUR,60203,EN,CT,Netherlands,L,Netherlands,0,"Scala, Hadoop, Python",Master,1,Gaming,2024-10-20,2024-12-06,1126,7.9,TechCorp Inc -AI14828,Data Engineer,125048,CAD,156310,SE,FL,Canada,M,Canada,0,"Python, Java, Docker",Master,8,Media,2025-04-26,2025-06-12,2044,7.3,DeepTech Ventures -AI14829,Research Scientist,212816,CAD,266020,EX,CT,Canada,M,Canada,50,"PyTorch, Python, Data Visualization, Kubernetes",Associate,15,Real Estate,2024-08-12,2024-09-29,658,6.7,Predictive Systems -AI14830,Head of AI,58316,USD,58316,EN,FT,Sweden,S,Germany,50,"Spark, Scala, GCP, Java, SQL",PhD,0,Gaming,2024-05-17,2024-07-18,2200,6.5,Future Systems -AI14831,NLP Engineer,100481,EUR,85409,MI,PT,Netherlands,L,Netherlands,100,"TensorFlow, Kubernetes, Spark",Associate,4,Manufacturing,2024-03-04,2024-04-20,2061,6.4,Cognitive Computing -AI14832,Head of AI,49599,USD,49599,MI,PT,China,L,China,100,"SQL, Kubernetes, GCP, Statistics, Hadoop",Master,2,Real Estate,2024-10-31,2024-12-15,708,5.8,DeepTech Ventures -AI14833,Data Analyst,79810,USD,79810,EN,PT,United States,S,Italy,50,"Python, Linux, NLP, TensorFlow, Hadoop",PhD,1,Healthcare,2025-03-24,2025-05-08,2386,6.8,DataVision Ltd -AI14834,AI Architect,57873,USD,57873,SE,FT,China,L,Luxembourg,50,"Kubernetes, Data Visualization, Java, PyTorch, NLP",Associate,9,Government,2024-07-13,2024-08-26,2487,5.4,Digital Transformation LLC -AI14835,Autonomous Systems Engineer,135214,SGD,175778,SE,CT,Singapore,S,Singapore,50,"R, SQL, Computer Vision, Java, Deep Learning",PhD,9,Education,2024-01-28,2024-03-01,2415,8.2,DataVision Ltd -AI14836,Principal Data Scientist,44068,USD,44068,EN,FL,South Korea,S,South Korea,50,"Git, Azure, Computer Vision",Associate,0,Energy,2024-05-30,2024-07-18,1291,6.8,Cloud AI Solutions -AI14837,ML Ops Engineer,218509,USD,218509,EX,CT,United States,S,Malaysia,100,"GCP, TensorFlow, Hadoop, Mathematics, SQL",PhD,19,Finance,2024-08-15,2024-09-04,2459,5.5,Autonomous Tech -AI14838,NLP Engineer,210813,CHF,189732,EX,CT,Switzerland,S,Switzerland,100,"NLP, Git, Data Visualization",Associate,10,Telecommunications,2024-03-25,2024-04-18,857,7.3,Digital Transformation LLC -AI14839,AI Architect,55157,SGD,71704,EN,FL,Singapore,S,Singapore,0,"Python, TensorFlow, Azure, Computer Vision",PhD,0,Finance,2024-06-01,2024-07-01,1582,9.5,Smart Analytics -AI14840,Deep Learning Engineer,70464,EUR,59894,EN,CT,France,M,France,0,"Mathematics, SQL, Tableau, PyTorch",Bachelor,1,Telecommunications,2025-04-27,2025-05-21,643,5.5,Smart Analytics -AI14841,Head of AI,55034,GBP,41276,EN,FL,United Kingdom,M,Sweden,100,"PyTorch, Docker, Data Visualization, Java, Spark",Bachelor,1,Government,2024-09-09,2024-10-05,1608,7,Digital Transformation LLC -AI14842,Machine Learning Engineer,278029,CHF,250226,EX,CT,Switzerland,M,Switzerland,100,"GCP, NLP, SQL, Python, Hadoop",Bachelor,10,Technology,2024-07-17,2024-08-17,1027,9,Smart Analytics -AI14843,ML Ops Engineer,100795,EUR,85676,SE,FT,Austria,S,France,100,"Python, SQL, NLP, Linux",Associate,7,Automotive,2025-04-26,2025-06-28,1660,5.5,AI Innovations -AI14844,Machine Learning Researcher,75234,USD,75234,MI,FL,South Korea,S,Malaysia,50,"Computer Vision, Python, Hadoop, AWS",PhD,3,Telecommunications,2024-05-28,2024-07-27,1864,5.6,DeepTech Ventures -AI14845,Machine Learning Researcher,149192,USD,149192,EX,FL,Sweden,S,Sweden,100,"Linux, Python, Data Visualization, TensorFlow",Master,16,Real Estate,2024-07-27,2024-09-08,646,5.8,Autonomous Tech -AI14846,AI Consultant,182753,USD,182753,EX,FT,Israel,M,Israel,50,"Docker, Mathematics, AWS",Master,11,Real Estate,2025-02-27,2025-04-10,2315,10,DeepTech Ventures -AI14847,Principal Data Scientist,134537,EUR,114356,SE,PT,Austria,M,Austria,0,"Python, Tableau, Java, GCP, TensorFlow",Associate,7,Government,2025-04-03,2025-05-05,965,8.4,Predictive Systems -AI14848,ML Ops Engineer,97397,EUR,82787,MI,FT,Netherlands,L,Netherlands,0,"SQL, Kubernetes, Git",Associate,4,Transportation,2025-01-22,2025-03-29,549,10,AI Innovations -AI14849,AI Product Manager,37126,USD,37126,MI,PT,India,M,India,50,"R, Python, Statistics, Docker",PhD,2,Education,2024-05-30,2024-08-08,1709,8.7,Neural Networks Co -AI14850,AI Research Scientist,67086,USD,67086,MI,FT,South Korea,S,Egypt,50,"Computer Vision, Scala, NLP",Bachelor,3,Education,2024-02-27,2024-04-30,821,5.6,Future Systems -AI14851,AI Specialist,62522,USD,62522,EX,FT,India,S,Germany,100,"Spark, AWS, Scala",Associate,14,Consulting,2025-03-11,2025-04-27,1422,9.7,Future Systems -AI14852,AI Product Manager,107430,AUD,145031,SE,FT,Australia,S,Australia,0,"Git, NLP, Docker, Scala",Master,7,Healthcare,2024-09-02,2024-10-12,1641,9.6,Advanced Robotics -AI14853,AI Architect,115217,CAD,144021,SE,FT,Canada,S,Canada,0,"Kubernetes, SQL, Docker",Bachelor,7,Manufacturing,2024-10-18,2024-11-20,753,9.3,Digital Transformation LLC -AI14854,Head of AI,142120,USD,142120,SE,FT,Denmark,S,Denmark,0,"Scala, Python, AWS, TensorFlow",Associate,6,Healthcare,2024-09-29,2024-10-31,2135,5.2,Cognitive Computing -AI14855,AI Consultant,92445,CAD,115556,MI,FT,Canada,M,Canada,0,"R, TensorFlow, Scala, Git, Computer Vision",Master,4,Real Estate,2024-11-29,2025-01-06,2134,8.9,Digital Transformation LLC -AI14856,Data Scientist,41824,USD,41824,SE,CT,India,L,New Zealand,50,"MLOps, GCP, R, Azure",Associate,6,Retail,2024-05-17,2024-07-21,994,8.6,Autonomous Tech -AI14857,ML Ops Engineer,51207,CAD,64009,EN,FL,Canada,M,Canada,50,"SQL, PyTorch, Git, AWS",PhD,0,Healthcare,2025-01-10,2025-02-06,745,6.5,Cognitive Computing -AI14858,AI Software Engineer,96900,CHF,87210,MI,PT,Switzerland,S,Switzerland,100,"TensorFlow, Mathematics, Hadoop, Data Visualization",PhD,3,Consulting,2024-07-17,2024-08-28,2381,9.4,Smart Analytics -AI14859,Machine Learning Engineer,139440,EUR,118524,SE,FT,Austria,L,Portugal,50,"SQL, Deep Learning, Tableau, GCP",PhD,7,Education,2024-10-01,2024-11-07,898,8,AI Innovations -AI14860,Data Engineer,149725,USD,149725,SE,FT,Finland,L,Finland,100,"MLOps, Computer Vision, SQL, Mathematics, Data Visualization",Bachelor,5,Healthcare,2024-11-12,2025-01-01,1796,8.6,Quantum Computing Inc -AI14861,AI Software Engineer,95613,CHF,86052,EN,FL,Switzerland,S,Switzerland,100,"SQL, PyTorch, Data Visualization, Deep Learning",PhD,0,Manufacturing,2024-01-14,2024-02-05,2410,8.1,Machine Intelligence Group -AI14862,Deep Learning Engineer,84360,EUR,71706,MI,PT,Austria,M,Austria,50,"TensorFlow, Scala, Statistics",Bachelor,2,Media,2025-04-23,2025-05-31,1028,5,TechCorp Inc -AI14863,Principal Data Scientist,109354,EUR,92951,MI,CT,Austria,L,Austria,100,"Statistics, PyTorch, NLP, AWS, Linux",Master,3,Finance,2025-01-13,2025-02-17,1507,6.5,Predictive Systems -AI14864,AI Product Manager,49153,USD,49153,EN,FL,South Korea,M,South Korea,0,"TensorFlow, Deep Learning, Docker",Bachelor,0,Automotive,2024-02-26,2024-03-16,1274,6.4,Predictive Systems -AI14865,AI Specialist,79494,USD,79494,MI,FT,South Korea,M,Vietnam,100,"Kubernetes, SQL, Data Visualization, Mathematics",Bachelor,4,Government,2024-05-30,2024-08-05,1674,5.1,Future Systems -AI14866,AI Architect,99985,JPY,10998350,MI,PT,Japan,L,Japan,100,"Git, SQL, Hadoop",PhD,3,Real Estate,2024-09-14,2024-11-16,2196,8.1,Autonomous Tech -AI14867,Data Scientist,82532,JPY,9078520,EN,PT,Japan,L,Japan,50,"Hadoop, Python, Docker, Mathematics",Bachelor,0,Healthcare,2024-07-11,2024-08-09,1231,9.1,Autonomous Tech -AI14868,Autonomous Systems Engineer,295948,USD,295948,EX,FT,Norway,M,Romania,50,"SQL, Scala, Python",PhD,12,Healthcare,2024-05-01,2024-06-05,630,9.7,Quantum Computing Inc -AI14869,AI Architect,62843,USD,62843,MI,CT,Finland,S,Finland,50,"R, SQL, TensorFlow, AWS, Python",PhD,3,Manufacturing,2024-07-16,2024-07-30,2195,9.7,Predictive Systems -AI14870,Data Scientist,209564,CHF,188608,EX,FT,Switzerland,M,Switzerland,100,"TensorFlow, Git, Scala",Associate,17,Manufacturing,2024-08-23,2024-09-11,1446,5.4,Algorithmic Solutions -AI14871,NLP Engineer,152425,USD,152425,MI,FT,Denmark,L,Denmark,50,"Spark, R, SQL, Python",Bachelor,4,Manufacturing,2024-09-18,2024-11-29,911,5.9,Machine Intelligence Group -AI14872,Robotics Engineer,84147,USD,84147,MI,CT,South Korea,L,South Korea,50,"SQL, Python, Java, Git",PhD,4,Education,2024-10-08,2024-11-09,2252,8.4,Autonomous Tech -AI14873,Data Scientist,119112,USD,119112,MI,CT,Ireland,L,Ireland,100,"Scala, TensorFlow, Mathematics, Java",Associate,2,Consulting,2024-01-24,2024-03-24,945,8.6,Machine Intelligence Group -AI14874,Data Engineer,49882,USD,49882,SE,PT,China,S,China,50,"Java, PyTorch, Kubernetes",Master,8,Manufacturing,2024-06-02,2024-07-18,966,5.4,DeepTech Ventures -AI14875,Data Scientist,223969,USD,223969,EX,CT,Denmark,S,Russia,100,"SQL, Kubernetes, TensorFlow",Master,18,Real Estate,2024-08-30,2024-10-28,1774,6.1,Advanced Robotics -AI14876,Head of AI,118219,USD,118219,MI,PT,Norway,L,Norway,50,"Mathematics, Tableau, Python, Deep Learning, Kubernetes",PhD,2,Telecommunications,2024-07-14,2024-08-15,819,8.8,DataVision Ltd -AI14877,Research Scientist,53669,EUR,45619,EN,CT,Netherlands,S,Netherlands,100,"Scala, Mathematics, MLOps, Java",Master,1,Education,2025-01-28,2025-03-30,820,9.6,Machine Intelligence Group -AI14878,Research Scientist,103628,USD,103628,MI,FT,Ireland,L,Japan,50,"PyTorch, Mathematics, Spark, TensorFlow",Associate,4,Media,2024-12-27,2025-02-16,1923,5.3,Predictive Systems -AI14879,AI Specialist,56178,CAD,70223,EN,FT,Canada,S,Canada,0,"Linux, MLOps, Hadoop, PyTorch",Bachelor,0,Telecommunications,2024-05-02,2024-06-04,2267,9.5,Machine Intelligence Group -AI14880,AI Software Engineer,146442,USD,146442,SE,PT,United States,L,United States,50,"Spark, TensorFlow, Mathematics, MLOps, Data Visualization",Bachelor,9,Healthcare,2024-05-01,2024-06-12,2052,6.5,Cognitive Computing -AI14881,Computer Vision Engineer,63769,GBP,47827,EN,CT,United Kingdom,L,Norway,50,"PyTorch, Python, Data Visualization, SQL, Docker",Associate,1,Gaming,2024-01-30,2024-03-23,1175,8.2,Smart Analytics -AI14882,AI Software Engineer,24026,USD,24026,EN,FT,India,L,India,50,"Java, SQL, Hadoop, GCP",Master,0,Energy,2024-11-20,2025-01-31,1643,7.3,Cloud AI Solutions -AI14883,Deep Learning Engineer,128886,EUR,109553,SE,FL,France,S,France,0,"Kubernetes, Scala, Linux",Master,7,Healthcare,2025-02-11,2025-03-04,559,9.1,Future Systems -AI14884,Data Engineer,86675,EUR,73674,EN,CT,Netherlands,L,Ukraine,50,"Python, TensorFlow, MLOps, PyTorch, Spark",Master,0,Media,2025-03-19,2025-05-12,954,7.9,Smart Analytics -AI14885,Principal Data Scientist,112837,USD,112837,SE,FT,Finland,L,Ukraine,100,"Python, Java, Scala, AWS",Master,7,Government,2025-02-26,2025-03-25,1527,7.3,AI Innovations -AI14886,AI Specialist,79915,CAD,99894,MI,CT,Canada,L,Ireland,100,"PyTorch, Spark, Scala, SQL, TensorFlow",PhD,3,Government,2024-06-15,2024-07-24,1978,9.8,Algorithmic Solutions -AI14887,Principal Data Scientist,55583,EUR,47246,EN,CT,Germany,S,Germany,0,"SQL, Java, Statistics",Master,0,Government,2025-02-14,2025-03-04,1427,8.5,Quantum Computing Inc -AI14888,AI Consultant,102567,EUR,87182,MI,FL,France,L,France,0,"Scala, Mathematics, R, Hadoop, Computer Vision",PhD,2,Consulting,2024-01-15,2024-03-07,1168,7.6,Autonomous Tech -AI14889,Data Scientist,63765,EUR,54200,EN,FL,Austria,S,Austria,50,"Scala, Linux, NLP, Tableau",Associate,1,Healthcare,2024-11-23,2024-12-22,926,9.6,Quantum Computing Inc -AI14890,Research Scientist,109816,JPY,12079760,SE,PT,Japan,M,Japan,100,"Tableau, Python, Kubernetes, NLP",Bachelor,7,Gaming,2024-04-24,2024-06-23,2297,9.3,Predictive Systems -AI14891,Machine Learning Engineer,147705,EUR,125549,SE,FT,Austria,L,Turkey,100,"Spark, Kubernetes, Data Visualization",Associate,7,Telecommunications,2024-01-08,2024-02-19,1790,5.3,Machine Intelligence Group -AI14892,NLP Engineer,180262,USD,180262,EX,CT,South Korea,L,South Korea,100,"SQL, PyTorch, AWS, Deep Learning, TensorFlow",Master,14,Healthcare,2024-04-04,2024-05-06,984,8.7,Digital Transformation LLC -AI14893,Research Scientist,26108,USD,26108,MI,CT,India,M,Nigeria,50,"MLOps, Python, PyTorch, Java, SQL",Master,3,Retail,2024-01-12,2024-03-18,2323,7.5,TechCorp Inc -AI14894,Data Scientist,85429,AUD,115329,MI,FL,Australia,S,Portugal,50,"Computer Vision, TensorFlow, Python",Associate,2,Finance,2024-02-07,2024-03-04,1715,8.6,Digital Transformation LLC -AI14895,Data Scientist,85824,GBP,64368,EN,PT,United Kingdom,L,Sweden,0,"SQL, Spark, PyTorch, Mathematics",Associate,1,Healthcare,2024-01-15,2024-03-12,1941,7.1,Advanced Robotics -AI14896,Deep Learning Engineer,36761,USD,36761,MI,PT,China,S,China,0,"Python, Scala, Git",PhD,4,Government,2025-03-03,2025-03-22,1141,6.6,DeepTech Ventures -AI14897,Machine Learning Researcher,178346,USD,178346,SE,FL,United States,M,United States,50,"Java, NLP, MLOps",PhD,8,Technology,2025-01-22,2025-02-28,1669,10,Quantum Computing Inc -AI14898,Principal Data Scientist,210345,USD,210345,EX,FT,Denmark,L,Norway,0,"Mathematics, Hadoop, Kubernetes, Linux, Azure",PhD,19,Finance,2024-02-22,2024-05-01,1614,7,DeepTech Ventures -AI14899,AI Product Manager,219044,CAD,273805,EX,CT,Canada,L,Belgium,50,"Hadoop, R, Scala, Data Visualization",Master,18,Education,2024-01-26,2024-03-29,1456,7.7,Quantum Computing Inc -AI14900,Principal Data Scientist,64885,CAD,81106,EN,CT,Canada,L,South Africa,0,"AWS, Hadoop, R, Kubernetes",Associate,1,Retail,2024-06-10,2024-07-13,1036,8.2,Neural Networks Co -AI14901,Machine Learning Researcher,98266,JPY,10809260,EN,FT,Japan,L,Russia,0,"Linux, Statistics, Mathematics, Hadoop, PyTorch",PhD,0,Real Estate,2025-01-27,2025-04-05,1598,5.5,Advanced Robotics -AI14902,Head of AI,104995,USD,104995,SE,PT,Ireland,S,Ireland,50,"Scala, MLOps, Azure, Git, Computer Vision",PhD,6,Government,2025-04-04,2025-05-30,1420,9.8,Machine Intelligence Group -AI14903,Head of AI,150009,USD,150009,SE,PT,United States,S,United States,0,"Java, Deep Learning, TensorFlow",Associate,8,Gaming,2024-05-20,2024-07-31,1122,5.1,Autonomous Tech -AI14904,AI Architect,213345,USD,213345,SE,FL,Denmark,L,Ghana,50,"Python, Tableau, Azure, Spark, Kubernetes",Master,8,Telecommunications,2024-08-09,2024-09-30,1207,8.6,Neural Networks Co -AI14905,Machine Learning Engineer,105646,EUR,89799,MI,PT,Germany,M,Kenya,50,"Scala, Hadoop, AWS, Python, Statistics",Master,2,Consulting,2025-03-17,2025-04-19,884,8.6,Neural Networks Co -AI14906,Deep Learning Engineer,155943,EUR,132552,SE,PT,Germany,L,Germany,50,"Deep Learning, Spark, Git, Kubernetes",PhD,9,Gaming,2024-02-19,2024-03-20,1251,9.1,Future Systems -AI14907,Autonomous Systems Engineer,108937,EUR,92596,SE,FL,Germany,M,Ghana,0,"Python, TensorFlow, Kubernetes, Data Visualization, Computer Vision",Bachelor,7,Real Estate,2024-11-11,2024-11-29,2247,9.5,Predictive Systems -AI14908,Computer Vision Engineer,107249,CHF,96524,EN,PT,Switzerland,M,Switzerland,0,"Deep Learning, PyTorch, SQL, Java, Scala",PhD,0,Consulting,2025-02-19,2025-04-02,2331,7.7,Neural Networks Co -AI14909,Machine Learning Engineer,92023,USD,92023,MI,FL,Ireland,S,Ireland,50,"TensorFlow, Java, SQL, R",PhD,3,Education,2025-03-06,2025-04-02,1052,5.7,DeepTech Ventures -AI14910,AI Architect,67935,USD,67935,MI,FT,Finland,S,Canada,100,"SQL, PyTorch, GCP",PhD,3,Energy,2024-01-06,2024-02-15,1292,5.1,Cognitive Computing -AI14911,AI Architect,35800,USD,35800,MI,CT,India,L,India,100,"TensorFlow, Mathematics, Azure, Scala, Java",Master,4,Technology,2024-10-26,2024-12-10,2131,9.1,DataVision Ltd -AI14912,Computer Vision Engineer,35601,USD,35601,SE,PT,India,S,India,50,"Python, MLOps, R, Statistics, Hadoop",Bachelor,6,Technology,2024-05-31,2024-07-15,729,7.6,AI Innovations -AI14913,Data Scientist,122019,EUR,103716,SE,PT,Netherlands,M,Netherlands,0,"Spark, PyTorch, GCP, Azure, Statistics",Master,7,Manufacturing,2024-05-13,2024-06-20,770,8.6,DataVision Ltd -AI14914,Data Analyst,65215,AUD,88040,EN,PT,Australia,S,Australia,50,"SQL, Scala, Computer Vision, Deep Learning",PhD,0,Manufacturing,2024-07-17,2024-08-19,1315,7.7,Future Systems -AI14915,Robotics Engineer,151010,USD,151010,SE,CT,Norway,S,Norway,50,"Hadoop, Spark, Data Visualization, SQL",Bachelor,9,Finance,2024-01-24,2024-02-22,2036,7.2,AI Innovations -AI14916,NLP Engineer,90626,USD,90626,MI,FT,Israel,L,Israel,0,"PyTorch, Docker, Deep Learning, GCP",Bachelor,4,Gaming,2024-10-06,2024-10-20,2024,7.5,Predictive Systems -AI14917,AI Research Scientist,114235,EUR,97100,MI,FT,Austria,L,Austria,100,"Hadoop, Python, NLP",Master,2,Transportation,2024-11-06,2024-12-21,1677,7.6,Advanced Robotics -AI14918,AI Consultant,99643,USD,99643,EN,FT,Norway,M,Norway,0,"TensorFlow, Kubernetes, GCP, Linux",Bachelor,0,Media,2024-08-02,2024-08-29,1430,5.1,TechCorp Inc -AI14919,Machine Learning Researcher,114099,USD,114099,SE,FT,United States,S,United States,0,"Hadoop, MLOps, SQL, Data Visualization",Bachelor,9,Automotive,2024-12-05,2025-02-11,589,5,Cloud AI Solutions -AI14920,Robotics Engineer,187262,SGD,243441,EX,FL,Singapore,M,Singapore,100,"Kubernetes, AWS, Git, Data Visualization",PhD,14,Automotive,2025-01-09,2025-03-14,1439,7.9,Advanced Robotics -AI14921,Data Scientist,41245,USD,41245,SE,FL,India,M,India,0,"GCP, Spark, Java, Data Visualization",Bachelor,8,Finance,2024-10-22,2024-12-30,2167,6.3,Algorithmic Solutions -AI14922,Autonomous Systems Engineer,60902,USD,60902,EN,FL,Denmark,S,Denmark,100,"GCP, SQL, Azure, Mathematics",PhD,1,Technology,2025-04-10,2025-05-31,1742,5.4,TechCorp Inc -AI14923,Data Engineer,57892,EUR,49208,EN,PT,France,M,France,0,"GCP, Spark, Git",Bachelor,1,Automotive,2024-11-18,2025-01-18,2050,7.4,Quantum Computing Inc -AI14924,AI Consultant,127852,CAD,159815,EX,PT,Canada,S,Ghana,100,"Azure, AWS, NLP, Computer Vision, TensorFlow",Associate,18,Transportation,2024-02-03,2024-03-01,1403,8.6,DataVision Ltd -AI14925,Data Analyst,214783,JPY,23626130,EX,CT,Japan,S,Japan,50,"R, Linux, Mathematics, MLOps, SQL",Master,12,Energy,2024-02-26,2024-04-23,2345,6.1,Predictive Systems -AI14926,Data Engineer,87394,EUR,74285,MI,PT,France,S,France,0,"Python, NLP, Deep Learning, Hadoop, Computer Vision",Associate,2,Automotive,2024-09-10,2024-11-05,1737,7.3,Autonomous Tech -AI14927,Autonomous Systems Engineer,98451,USD,98451,EN,FT,Norway,M,Norway,0,"SQL, Linux, Kubernetes, Azure, NLP",Associate,0,Real Estate,2024-10-04,2024-10-18,2299,6,Digital Transformation LLC -AI14928,NLP Engineer,74127,GBP,55595,EN,FT,United Kingdom,L,United Kingdom,0,"AWS, Hadoop, Data Visualization, NLP",Bachelor,0,Automotive,2024-12-18,2025-01-04,2454,7.4,Quantum Computing Inc -AI14929,Machine Learning Researcher,51492,USD,51492,EX,PT,India,S,India,50,"Docker, GCP, Computer Vision, Kubernetes",Bachelor,10,Media,2024-07-28,2024-10-06,2116,5.7,Advanced Robotics -AI14930,Head of AI,168869,SGD,219530,EX,PT,Singapore,S,Singapore,0,"Deep Learning, Docker, PyTorch, AWS",Associate,11,Automotive,2024-01-20,2024-02-28,956,8.3,AI Innovations -AI14931,AI Software Engineer,104543,JPY,11499730,SE,CT,Japan,S,Japan,0,"R, Azure, TensorFlow, MLOps",Master,9,Transportation,2024-09-20,2024-10-22,1456,6.1,Digital Transformation LLC -AI14932,AI Product Manager,88186,SGD,114642,MI,PT,Singapore,M,Mexico,50,"Java, Computer Vision, Linux, Data Visualization, PyTorch",Associate,4,Transportation,2024-06-11,2024-07-09,1523,9.3,Advanced Robotics -AI14933,Data Scientist,135656,USD,135656,EX,FT,Finland,S,Latvia,0,"Linux, SQL, Git, Python",PhD,12,Telecommunications,2024-08-17,2024-09-18,1864,5.9,AI Innovations -AI14934,AI Software Engineer,124876,EUR,106145,EX,FT,Germany,S,Germany,0,"Statistics, MLOps, AWS, Computer Vision, Linux",PhD,12,Government,2024-04-22,2024-06-29,540,5.8,Smart Analytics -AI14935,Data Engineer,75356,CAD,94195,EN,FT,Canada,M,Canada,100,"PyTorch, TensorFlow, AWS",Bachelor,0,Automotive,2025-04-25,2025-06-14,1057,9.3,Algorithmic Solutions -AI14936,Data Engineer,95193,EUR,80914,SE,CT,France,S,France,0,"Linux, Computer Vision, Git, Spark, TensorFlow",Associate,5,Technology,2025-03-22,2025-05-31,2416,9.1,Cloud AI Solutions -AI14937,Autonomous Systems Engineer,203347,SGD,264351,EX,PT,Singapore,L,Singapore,50,"Data Visualization, Python, Git, NLP",PhD,16,Energy,2024-08-31,2024-10-13,2016,5.3,Predictive Systems -AI14938,Machine Learning Researcher,95262,GBP,71447,MI,PT,United Kingdom,M,South Africa,100,"Kubernetes, Data Visualization, Spark",Associate,2,Retail,2024-02-01,2024-04-01,1027,8.3,Machine Intelligence Group -AI14939,Computer Vision Engineer,162617,USD,162617,MI,PT,Denmark,L,Denmark,50,"Hadoop, Kubernetes, Linux, Scala, Azure",Associate,2,Automotive,2024-12-05,2024-12-27,2086,5.3,Autonomous Tech -AI14940,AI Research Scientist,119770,GBP,89828,SE,FL,United Kingdom,S,Malaysia,100,"Java, Azure, AWS, Hadoop",Associate,9,Technology,2025-01-27,2025-04-02,2470,7.5,Autonomous Tech -AI14941,Data Scientist,220001,CAD,275001,EX,PT,Canada,L,Canada,100,"Java, Scala, MLOps, Kubernetes",Bachelor,19,Telecommunications,2024-06-15,2024-08-07,757,5.3,AI Innovations -AI14942,AI Consultant,64943,EUR,55202,EN,FL,France,S,France,100,"PyTorch, AWS, MLOps, Tableau",Master,1,Manufacturing,2024-08-11,2024-10-11,1367,8.7,Machine Intelligence Group -AI14943,Data Scientist,218883,EUR,186051,EX,FL,Netherlands,S,Netherlands,0,"Hadoop, Docker, Spark, Deep Learning",Master,10,Energy,2024-04-06,2024-05-03,1713,9.4,Autonomous Tech -AI14944,AI Research Scientist,86404,USD,86404,MI,FL,Israel,M,Switzerland,50,"Computer Vision, Docker, Python",Master,2,Manufacturing,2024-02-14,2024-03-16,2410,7.7,Quantum Computing Inc -AI14945,AI Architect,175545,SGD,228209,EX,PT,Singapore,S,Singapore,100,"Git, Statistics, Python, Mathematics, Scala",Master,13,Automotive,2024-07-30,2024-09-12,571,9.1,Autonomous Tech -AI14946,AI Product Manager,148458,USD,148458,MI,FL,Norway,L,Norway,100,"Azure, Python, Statistics",Master,4,Gaming,2024-06-10,2024-08-06,1292,6,Advanced Robotics -AI14947,Deep Learning Engineer,104899,EUR,89164,MI,CT,Austria,L,Austria,50,"Computer Vision, Python, Spark, R",Associate,2,Healthcare,2024-01-12,2024-03-25,1839,5.6,Future Systems -AI14948,Data Engineer,101094,USD,101094,SE,FL,Finland,S,Finland,0,"Spark, SQL, Linux",Master,5,Finance,2025-04-12,2025-05-06,723,6.3,Predictive Systems -AI14949,AI Product Manager,125424,USD,125424,SE,FL,Finland,M,Finland,50,"Linux, SQL, Python, Git",PhD,7,Consulting,2024-10-27,2025-01-02,2396,6.3,Advanced Robotics -AI14950,Autonomous Systems Engineer,82744,JPY,9101840,MI,PT,Japan,M,South Africa,0,"GCP, Docker, Java, SQL",PhD,4,Gaming,2024-01-23,2024-02-19,1773,7.4,Machine Intelligence Group -AI14951,Computer Vision Engineer,117343,USD,117343,MI,PT,Norway,L,Norway,100,"Docker, Computer Vision, MLOps",Associate,2,Energy,2024-04-02,2024-06-01,515,6.7,AI Innovations -AI14952,ML Ops Engineer,118354,USD,118354,MI,CT,Sweden,L,Sweden,0,"Python, TensorFlow, R",Master,2,Education,2024-11-27,2025-01-31,1583,5.6,Predictive Systems -AI14953,Autonomous Systems Engineer,124093,USD,124093,EX,CT,South Korea,S,South Korea,100,"SQL, TensorFlow, Data Visualization",Bachelor,14,Real Estate,2024-09-28,2024-11-21,1677,6.8,DeepTech Ventures -AI14954,Deep Learning Engineer,63367,SGD,82377,EN,CT,Singapore,S,Singapore,0,"Data Visualization, GCP, Mathematics, Statistics, Scala",Bachelor,0,Retail,2025-04-29,2025-06-07,2329,5.4,Future Systems -AI14955,Machine Learning Researcher,161652,USD,161652,SE,FL,Norway,M,France,50,"MLOps, Deep Learning, NLP, PyTorch",Bachelor,5,Healthcare,2024-03-02,2024-05-07,1578,8.2,Cloud AI Solutions -AI14956,AI Research Scientist,104435,USD,104435,SE,FT,South Korea,M,South Korea,50,"Python, TensorFlow, AWS, PyTorch, SQL",PhD,5,Education,2024-11-17,2025-01-21,1555,7.3,Future Systems -AI14957,Data Scientist,140824,EUR,119700,SE,CT,Netherlands,S,Australia,50,"Statistics, Mathematics, Python",Bachelor,7,Government,2025-01-24,2025-03-17,2252,5.9,Future Systems -AI14958,NLP Engineer,33429,USD,33429,MI,PT,China,S,China,0,"SQL, MLOps, Mathematics, TensorFlow, GCP",Master,4,Education,2025-04-20,2025-05-06,628,9.8,Cloud AI Solutions -AI14959,Data Engineer,56924,USD,56924,EX,FL,India,L,India,100,"Kubernetes, Scala, Mathematics, TensorFlow, Linux",Master,12,Media,2025-02-13,2025-02-27,632,8.4,Cognitive Computing -AI14960,AI Specialist,108996,USD,108996,EN,FT,Norway,L,India,50,"GCP, Spark, Python",PhD,1,Government,2024-07-04,2024-08-23,1049,6.1,Future Systems -AI14961,AI Specialist,159001,USD,159001,SE,FL,United States,M,United States,50,"Data Visualization, NLP, AWS, R",Master,9,Transportation,2024-02-25,2024-04-03,1217,7.9,AI Innovations -AI14962,Machine Learning Researcher,186143,USD,186143,EX,FL,Norway,S,Norway,50,"Linux, Spark, Data Visualization",Associate,10,Healthcare,2024-07-18,2024-08-29,1432,8.4,Machine Intelligence Group -AI14963,AI Specialist,67937,USD,67937,SE,CT,China,L,China,0,"GCP, NLP, Scala, R, Java",PhD,6,Healthcare,2024-03-11,2024-04-02,2287,7.1,Cognitive Computing -AI14964,Machine Learning Engineer,62318,USD,62318,EN,PT,South Korea,L,South Korea,0,"Linux, TensorFlow, Deep Learning, Scala",PhD,1,Energy,2024-07-06,2024-08-10,1687,8.4,TechCorp Inc -AI14965,Deep Learning Engineer,92518,USD,92518,MI,FL,Israel,M,Israel,50,"Python, Data Visualization, Linux, Azure",Bachelor,2,Gaming,2024-11-17,2024-12-04,1191,6.2,Cognitive Computing -AI14966,Research Scientist,212794,AUD,287272,EX,FL,Australia,M,Australia,50,"Tableau, Kubernetes, TensorFlow, Mathematics",Bachelor,11,Consulting,2024-12-25,2025-02-26,1380,9.5,Neural Networks Co -AI14967,Research Scientist,116954,USD,116954,EX,FL,South Korea,M,Czech Republic,0,"SQL, Python, Docker",Master,12,Finance,2024-06-11,2024-07-26,1484,7.9,Quantum Computing Inc -AI14968,AI Specialist,146064,USD,146064,SE,PT,Sweden,L,Sweden,0,"Kubernetes, SQL, Linux",Associate,8,Healthcare,2024-12-29,2025-02-06,1882,6.3,DeepTech Ventures -AI14969,Principal Data Scientist,105890,SGD,137657,MI,FL,Singapore,L,Luxembourg,100,"Python, Computer Vision, Tableau",PhD,4,Real Estate,2024-05-10,2024-06-04,2107,7.7,Neural Networks Co -AI14970,Data Analyst,62944,AUD,84974,EN,FL,Australia,S,Malaysia,100,"Docker, TensorFlow, Mathematics, AWS, SQL",Master,0,Automotive,2024-04-01,2024-06-12,1846,6.4,Machine Intelligence Group -AI14971,AI Research Scientist,142892,USD,142892,MI,FL,Denmark,L,Denmark,0,"Data Visualization, Scala, SQL, Kubernetes",Bachelor,4,Automotive,2024-09-20,2024-10-18,770,5.7,Neural Networks Co -AI14972,Data Engineer,182144,USD,182144,EX,FL,Denmark,M,Nigeria,100,"Python, NLP, TensorFlow, Docker",Associate,17,Telecommunications,2024-11-20,2025-01-24,1514,6.3,DataVision Ltd -AI14973,Computer Vision Engineer,184474,USD,184474,EX,PT,Finland,S,Finland,0,"Java, GCP, SQL, Docker, PyTorch",PhD,11,Real Estate,2024-03-31,2024-05-20,921,6.9,Cloud AI Solutions -AI14974,AI Architect,105686,USD,105686,SE,CT,South Korea,L,Japan,0,"Data Visualization, Docker, Spark",PhD,8,Technology,2024-09-07,2024-11-01,2269,6.3,Cloud AI Solutions -AI14975,Computer Vision Engineer,40256,USD,40256,EN,FL,South Korea,S,South Korea,100,"Tableau, Linux, PyTorch, GCP, Python",Master,1,Consulting,2024-11-26,2024-12-18,2172,9.6,Quantum Computing Inc -AI14976,AI Specialist,116503,USD,116503,MI,FL,Sweden,L,Sweden,0,"Kubernetes, Hadoop, GCP, Spark, Java",PhD,3,Government,2024-09-11,2024-11-05,2035,9.7,Cognitive Computing -AI14977,AI Specialist,161707,CAD,202134,EX,PT,Canada,L,Estonia,0,"MLOps, Java, Linux",Master,18,Consulting,2024-05-03,2024-06-26,1766,9,Smart Analytics -AI14978,AI Architect,176965,USD,176965,SE,FL,Denmark,M,Denmark,50,"Python, GCP, Hadoop, Statistics",Master,6,Healthcare,2024-03-20,2024-05-22,1431,5.3,Future Systems -AI14979,Data Analyst,165811,USD,165811,EX,FT,Ireland,M,Ireland,50,"Python, SQL, GCP",Associate,18,Telecommunications,2024-06-25,2024-07-21,840,6.7,TechCorp Inc -AI14980,Deep Learning Engineer,64531,JPY,7098410,EN,FT,Japan,M,United States,100,"PyTorch, TensorFlow, GCP",PhD,0,Healthcare,2024-11-30,2024-12-31,1047,9.2,Predictive Systems -AI14981,Data Scientist,102580,CHF,92322,EN,FT,Switzerland,S,Switzerland,50,"Java, AWS, Data Visualization, Statistics",Master,0,Education,2025-04-07,2025-06-04,2165,5.9,Predictive Systems -AI14982,NLP Engineer,203175,USD,203175,EX,PT,Israel,S,Israel,0,"Spark, Docker, PyTorch, Kubernetes",PhD,14,Automotive,2025-03-20,2025-05-13,1966,6,Predictive Systems -AI14983,Data Scientist,49068,USD,49068,EN,PT,Israel,M,Israel,0,"Kubernetes, GCP, Linux",PhD,0,Healthcare,2024-02-04,2024-04-08,1800,6,Algorithmic Solutions -AI14984,Research Scientist,224701,USD,224701,SE,FT,Denmark,L,Denmark,0,"PyTorch, Data Visualization, NLP, Statistics",Master,5,Gaming,2024-06-27,2024-08-24,2392,7.9,Predictive Systems -AI14985,Computer Vision Engineer,74923,USD,74923,MI,PT,Ireland,M,Ireland,100,"PyTorch, Linux, TensorFlow, GCP, Java",PhD,4,Manufacturing,2024-03-19,2024-05-19,1755,8.2,Digital Transformation LLC -AI14986,Computer Vision Engineer,87266,GBP,65450,EN,CT,United Kingdom,L,United Kingdom,100,"Tableau, Python, Computer Vision, MLOps, Azure",PhD,0,Telecommunications,2024-11-19,2024-12-24,2402,5.1,DataVision Ltd -AI14987,ML Ops Engineer,200074,EUR,170063,EX,CT,Austria,M,Austria,50,"MLOps, Kubernetes, Mathematics",Associate,18,Energy,2024-07-26,2024-08-16,2163,6.5,Cognitive Computing -AI14988,Data Analyst,108520,JPY,11937200,MI,FT,Japan,M,Japan,100,"SQL, Hadoop, Scala, Kubernetes, Mathematics",Associate,3,Education,2025-03-19,2025-05-16,914,8.3,Neural Networks Co -AI14989,Autonomous Systems Engineer,104423,SGD,135750,MI,FT,Singapore,M,Singapore,100,"Docker, Kubernetes, Azure, TensorFlow, Deep Learning",Bachelor,2,Technology,2024-07-14,2024-08-04,844,5.3,Cloud AI Solutions -AI14990,ML Ops Engineer,68334,EUR,58084,EN,FT,Germany,L,Australia,100,"Scala, SQL, Java, R",Bachelor,0,Gaming,2024-04-22,2024-06-19,1506,9.2,Smart Analytics -AI14991,AI Product Manager,58388,SGD,75904,EN,FT,Singapore,M,Singapore,50,"Deep Learning, Git, Data Visualization, Tableau",PhD,0,Real Estate,2024-11-17,2025-01-23,2186,5.5,Neural Networks Co -AI14992,AI Research Scientist,40912,USD,40912,EN,FT,South Korea,S,South Korea,100,"Mathematics, AWS, Computer Vision, Docker, Hadoop",Bachelor,0,Energy,2025-02-05,2025-02-26,2027,6.6,DeepTech Ventures -AI14993,Machine Learning Researcher,93530,EUR,79501,MI,PT,Netherlands,S,Netherlands,50,"Tableau, Docker, Java, Deep Learning",PhD,3,Telecommunications,2024-09-27,2024-10-14,1825,6.1,Future Systems -AI14994,Deep Learning Engineer,54536,CAD,68170,EN,FL,Canada,M,Canada,0,"Linux, Kubernetes, Python, TensorFlow",Bachelor,1,Government,2024-08-18,2024-10-16,1547,7.9,Advanced Robotics -AI14995,AI Research Scientist,151756,USD,151756,SE,FT,United States,M,United States,0,"Mathematics, Python, Tableau",Bachelor,7,Gaming,2025-03-19,2025-04-09,837,9.3,Cognitive Computing -AI14996,AI Product Manager,39171,USD,39171,MI,CT,China,M,China,50,"Azure, R, NLP, Docker, Computer Vision",PhD,4,Consulting,2025-01-07,2025-02-07,1107,5.2,Smart Analytics -AI14997,AI Product Manager,77555,EUR,65922,EN,CT,Netherlands,M,Netherlands,50,"Python, TensorFlow, Mathematics, AWS, Computer Vision",PhD,0,Energy,2024-12-22,2025-02-12,1870,9.7,Autonomous Tech -AI14998,Data Engineer,28380,USD,28380,EN,FL,India,M,India,50,"Azure, Kubernetes, Spark, Statistics, MLOps",Associate,1,Government,2024-05-04,2024-05-21,1558,9,Digital Transformation LLC -AI14999,AI Specialist,58764,EUR,49949,EN,PT,France,M,France,100,"MLOps, Statistics, Data Visualization, R, Python",Master,0,Real Estate,2024-05-08,2024-06-22,546,8.4,Machine Intelligence Group -AI15000,Principal Data Scientist,58623,USD,58623,SE,FT,China,M,China,0,"AWS, Spark, Computer Vision, Data Visualization, Tableau",PhD,6,Transportation,2024-11-23,2024-12-15,1034,9.7,Quantum Computing Inc \ No newline at end of file From 31048b24e7a292ca54d59a8b5ad67c86f0454057 Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Tue, 9 Dec 2025 12:49:10 +0100 Subject: [PATCH 09/26] Github overwrite with Jupyter notebook and data csv --- .virtual_documents/notebooks/Untitled.ipynb | 27 + Project1.ipynb | 445 - anaconda_projects/db/project_filebrowser.db | Bin 0 -> 32768 bytes notebooks/Airline_Project1.ipynb | 1536 + notebooks/explore_clean_data_username.ipynb | 1 - notebooks/functions.py | 26 - notebooks/load_and_clean_data_username.ipynb | 1 - notebooks/train.csv | 103905 ++++++++++++++++ 8 files changed, 105468 insertions(+), 473 deletions(-) create mode 100644 .virtual_documents/notebooks/Untitled.ipynb delete mode 100644 Project1.ipynb create mode 100644 anaconda_projects/db/project_filebrowser.db create mode 100644 notebooks/Airline_Project1.ipynb delete mode 100644 notebooks/explore_clean_data_username.ipynb delete mode 100644 notebooks/functions.py delete mode 100644 notebooks/load_and_clean_data_username.ipynb create mode 100644 notebooks/train.csv diff --git a/.virtual_documents/notebooks/Untitled.ipynb b/.virtual_documents/notebooks/Untitled.ipynb new file mode 100644 index 00000000..9bc45505 --- /dev/null +++ b/.virtual_documents/notebooks/Untitled.ipynb @@ -0,0 +1,27 @@ +import pandas as pd +import numpy as np + +df=pd.read_csv('train.csv') +df + + +df['satisfaction'].value_counts() + + +df['Customer Type'].value_counts() + + +dfSatisfied=df[df['satisfaction'] == 'satisfied'] +dfDisatisfied=df[df['satisfaction'] == 'neutral or dissatisfied'] + + +dfSatisfied.describe() + + +dfDisatisfied.describe() + + +dfSatisfied + + + diff --git a/Project1.ipynb b/Project1.ipynb deleted file mode 100644 index 24e7c65d..00000000 --- a/Project1.ipynb +++ /dev/null @@ -1,445 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 5, - "id": "05ae7d72-68d0-412d-b459-ceded1805bd8", - "metadata": {}, - "outputs": [], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "\n", - "df=pd.read_csv('ai_job_dataset1.csv')" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "b60dc083-ca2a-4103-869d-4b5bcb04da03", - "metadata": {}, - 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job_idjob_titlesalary_usdsalary_currencysalary_localexperience_levelemployment_typecompany_locationcompany_sizeemployee_residenceremote_ratiorequired_skillseducation_requiredyears_experienceindustryposting_dateapplication_deadlinejob_description_lengthbenefits_scorecompany_name
0AI00001Data Scientist219728USD219728EXPTSwedenMSweden0Python, Computer Vision, R, DockerAssociate13Transportation2024-09-232024-10-3111326.6TechCorp Inc
1AI00002Head of AI230237JPY25326070EXPTJapanLJapan50Kubernetes, MLOps, Tableau, PythonBachelor10Transportation2024-07-262024-09-1222998.5Cloud AI Solutions
2AI00003Data Engineer128890EUR109557EXCTGermanySGermany100Spark, Scala, Hadoop, PyTorch, GCPBachelor12Automotive2025-01-192025-03-2813295.5Quantum Computing Inc
3AI00004Computer Vision Engineer96349USD96349MIFLFinlandLFinland50MLOps, Linux, Tableau, PythonPhD2Automotive2024-07-202024-09-0611326.8Cognitive Computing
4AI00005Robotics Engineer63065EUR53605ENFTFranceSFrance100R, Scala, SQL, GCP, PythonAssociate0Finance2025-03-162025-05-0920119.3Advanced Robotics
...............................................................
14995AI14996AI Product Manager39171USD39171MICTChinaMChina50Azure, R, NLP, Docker, Computer VisionPhD4Consulting2025-01-072025-02-0711075.2Smart Analytics
14996AI14997AI Product Manager77555EUR65922ENCTNetherlandsMNetherlands50Python, TensorFlow, Mathematics, AWS, Computer...PhD0Energy2024-12-222025-02-1218709.7Autonomous Tech
14997AI14998Data Engineer28380USD28380ENFLIndiaMIndia50Azure, Kubernetes, Spark, Statistics, MLOpsAssociate1Government2024-05-042024-05-2115589.0Digital Transformation LLC
14998AI14999AI Specialist58764EUR49949ENPTFranceMFrance100MLOps, Statistics, Data Visualization, R, PythonMaster0Real Estate2024-05-082024-06-225468.4Machine Intelligence Group
14999AI15000Principal Data Scientist58623USD58623SEFTChinaMChina0AWS, Spark, Computer Vision, Data Visualizatio...PhD6Transportation2024-11-232024-12-1510349.7Quantum Computing Inc
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3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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Unnamed: 0idAgeFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online bookingGate locationFood and drinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutes
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Unnamed: 0idAgeFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online bookingGate locationFood and drinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutes
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
7796462FemaleLoyal Customer52Business travelBusiness203543...555545440.0satisfied
131383502MaleLoyal Customer33Personal TravelEco94642...445222400.0satisfied
161671142FemaleLoyal Customer26Business travelBusiness212333...45345444951.0satisfied
..................................................................
10389010389080087FemaleLoyal Customer56Business travelEco Plus55035...333343300.0satisfied
10389110389183013MaleLoyal Customer54Business travelBusiness199155...44545443531.0satisfied
10389410389486549MaleLoyal Customer26Business travelBusiness71244...53443451726.0satisfied
103897103897102203FemaleLoyal Customer60Business travelBusiness159955...444444497.0satisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
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Inflight entertainment \\\n", + "2 2 ... 5 \n", + "4 3 ... 3 \n", + "7 3 ... 5 \n", + "13 2 ... 4 \n", + "16 3 ... 4 \n", + "... ... ... ... \n", + "103890 5 ... 3 \n", + "103891 5 ... 4 \n", + "103894 4 ... 5 \n", + "103897 5 ... 4 \n", + "103900 4 ... 5 \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "2 4 3 4 4 \n", + "4 3 4 4 3 \n", + "7 5 5 5 4 \n", + "13 4 5 2 2 \n", + "16 5 3 4 5 \n", + "... ... ... ... ... \n", + "103890 3 3 3 4 \n", + "103891 4 5 4 5 \n", + "103894 3 4 4 3 \n", + "103897 4 4 4 4 \n", + "103900 5 5 5 5 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "2 4 5 0 \n", + "4 3 3 0 \n", + "7 5 4 4 \n", + "13 2 4 0 \n", + "16 4 4 49 \n", + "... ... ... ... \n", + "103890 3 3 0 \n", + "103891 4 4 35 \n", + "103894 4 5 17 \n", + "103897 4 4 9 \n", + "103900 5 4 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction \n", + "2 0.0 satisfied \n", + "4 0.0 satisfied \n", + "7 0.0 satisfied \n", + "13 0.0 satisfied \n", + "16 51.0 satisfied \n", + "... ... ... \n", + "103890 0.0 satisfied \n", + "103891 31.0 satisfied \n", + "103894 26.0 satisfied \n", + "103897 7.0 satisfied \n", + "103900 0.0 satisfied \n", + "\n", + "[45025 rows x 25 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfSatisfied" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/explore_clean_data_username.ipynb b/notebooks/explore_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/explore_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/functions.py b/notebooks/functions.py deleted file mode 100644 index 7804c676..00000000 --- a/notebooks/functions.py +++ /dev/null @@ -1,26 +0,0 @@ -# Add all the imports needed by the functions in the project here -#================================================================ -# -#================================================================ - -# Remember to modify your functions to use the template shown below - -def function_name(input1: data_type1, input2: data_type2,..., opt_arg: data_type_opt= default_value) -> output_data_type: - """ - Add a description of what the function does - - Arguments: - --------- - input1: data_type and which information should contain - input2: data_type and which information should contain - opt_arg: data_type and which information should contain - - Outputs: - ------- - data_type and which information will contain - """ - - # Your function code here - - - return opuput diff --git a/notebooks/load_and_clean_data_username.ipynb b/notebooks/load_and_clean_data_username.ipynb deleted file mode 100644 index 792d6005..00000000 --- a/notebooks/load_and_clean_data_username.ipynb +++ /dev/null @@ -1 +0,0 @@ -# diff --git a/notebooks/train.csv b/notebooks/train.csv new file mode 100644 index 00000000..e2a77505 --- /dev/null +++ b/notebooks/train.csv @@ -0,0 +1,103905 @@ +,id,Gender,Customer Type,Age,Type of Travel,Class,Flight Distance,Inflight wifi service,Departure/Arrival time convenient,Ease of Online booking,Gate location,Food and drink,Online boarding,Seat comfort,Inflight entertainment,On-board service,Leg room service,Baggage handling,Checkin service,Inflight service,Cleanliness,Departure Delay in Minutes,Arrival Delay in Minutes,satisfaction +0,70172,Male,Loyal Customer,13,Personal Travel,Eco Plus,460,3,4,3,1,5,3,5,5,4,3,4,4,5,5,25,18.0,neutral or dissatisfied +1,5047,Male,disloyal Customer,25,Business travel,Business,235,3,2,3,3,1,3,1,1,1,5,3,1,4,1,1,6.0,neutral or dissatisfied +2,110028,Female,Loyal Customer,26,Business travel,Business,1142,2,2,2,2,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +3,24026,Female,Loyal Customer,25,Business travel,Business,562,2,5,5,5,2,2,2,2,2,5,3,1,4,2,11,9.0,neutral or dissatisfied +4,119299,Male,Loyal Customer,61,Business travel,Business,214,3,3,3,3,4,5,5,3,3,4,4,3,3,3,0,0.0,satisfied +5,111157,Female,Loyal Customer,26,Personal Travel,Eco,1180,3,4,2,1,1,2,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +6,82113,Male,Loyal Customer,47,Personal Travel,Eco,1276,2,4,2,3,2,2,2,2,3,3,4,3,5,2,9,23.0,neutral or dissatisfied +7,96462,Female,Loyal Customer,52,Business travel,Business,2035,4,3,4,4,5,5,5,5,5,5,5,4,5,4,4,0.0,satisfied +8,79485,Female,Loyal Customer,41,Business travel,Business,853,1,2,2,2,4,3,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +9,65725,Male,disloyal Customer,20,Business travel,Eco,1061,3,3,3,4,2,3,3,2,2,3,4,4,3,2,0,0.0,neutral or dissatisfied +10,34991,Female,disloyal Customer,24,Business travel,Eco,1182,4,5,5,4,2,5,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +11,51412,Female,Loyal Customer,12,Personal Travel,Eco Plus,308,2,4,2,2,1,2,1,1,1,2,5,5,5,1,0,0.0,neutral or dissatisfied +12,98628,Male,Loyal Customer,53,Business travel,Eco,834,1,4,4,4,1,1,1,1,1,1,3,4,4,1,28,8.0,neutral or dissatisfied +13,83502,Male,Loyal Customer,33,Personal Travel,Eco,946,4,2,4,3,4,4,4,4,4,5,2,2,2,4,0,0.0,satisfied +14,95789,Female,Loyal Customer,26,Personal Travel,Eco,453,3,2,3,2,2,3,2,2,4,3,2,2,1,2,43,35.0,neutral or dissatisfied +15,100580,Male,disloyal Customer,13,Business travel,Eco,486,2,1,2,3,4,2,1,4,2,1,4,1,3,4,1,0.0,neutral or dissatisfied +16,71142,Female,Loyal Customer,26,Business travel,Business,2123,3,3,3,3,4,4,4,4,5,3,4,5,4,4,49,51.0,satisfied +17,127461,Male,Loyal Customer,41,Business travel,Business,2075,4,4,2,4,4,4,4,5,5,5,5,3,5,5,0,10.0,satisfied +18,70354,Female,Loyal Customer,45,Business travel,Business,2486,4,4,4,4,3,4,5,5,5,5,5,3,5,4,7,5.0,satisfied +19,66246,Male,Loyal Customer,38,Personal Travel,Eco,460,2,3,3,2,5,3,5,5,1,2,4,3,2,5,17,18.0,neutral or dissatisfied +20,39076,Male,Loyal Customer,9,Business travel,Eco,1174,2,4,2,4,2,2,1,2,1,5,3,4,3,2,0,4.0,neutral or dissatisfied +21,22434,Female,Loyal Customer,17,Personal Travel,Eco,208,3,1,3,3,5,3,5,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +22,43510,Female,Loyal Customer,43,Personal Travel,Eco,752,3,5,3,5,5,4,5,3,3,3,5,3,3,4,52,29.0,neutral or dissatisfied +23,114090,Female,Loyal Customer,58,Personal Travel,Eco,2139,4,5,4,5,4,3,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +24,105420,Female,disloyal Customer,23,Business travel,Eco,452,5,0,5,1,1,5,1,1,4,5,5,3,5,1,54,44.0,satisfied +25,102956,Male,Loyal Customer,57,Personal Travel,Eco,719,4,4,4,1,5,4,5,5,3,2,4,4,5,5,27,28.0,neutral or dissatisfied +26,18510,Female,Loyal Customer,33,Business travel,Business,1561,1,1,1,1,1,5,3,4,4,4,3,5,4,2,0,0.0,satisfied +27,14925,Female,Loyal Customer,49,Business travel,Eco Plus,315,4,4,4,4,2,2,1,4,4,4,4,2,4,2,0,8.0,satisfied +28,118319,Female,Loyal Customer,36,Business travel,Business,3347,3,1,1,1,1,2,1,3,3,3,3,2,3,2,18,12.0,neutral or dissatisfied +29,75460,Male,Loyal Customer,22,Personal Travel,Eco,2342,3,2,3,3,3,3,1,3,2,4,3,4,2,3,19,0.0,neutral or dissatisfied +30,48492,Female,Loyal Customer,31,Business travel,Business,819,4,4,4,4,5,5,5,5,5,4,3,1,5,5,0,0.0,satisfied +31,27809,Female,disloyal Customer,15,Business travel,Eco,1043,2,2,2,3,5,2,5,5,3,1,4,2,4,5,3,0.0,neutral or dissatisfied +32,70594,Female,Loyal Customer,35,Business travel,Business,2611,4,5,4,4,4,4,4,3,3,4,5,4,3,4,109,120.0,satisfied +33,30089,Female,Loyal Customer,67,Personal Travel,Eco,1192,4,5,4,1,2,4,5,5,5,4,3,5,5,5,18,24.0,neutral or dissatisfied +34,58779,Male,disloyal Customer,37,Business travel,Business,1182,3,3,3,4,1,3,1,1,4,1,3,1,4,1,9,0.0,neutral or dissatisfied +35,79659,Female,Loyal Customer,40,Business travel,Eco,349,1,4,4,4,1,1,1,1,3,5,3,3,3,1,0,1.0,neutral or dissatisfied +36,110293,Female,disloyal Customer,34,Business travel,Business,883,3,4,4,3,5,4,2,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +37,48014,Male,Loyal Customer,40,Personal Travel,Eco Plus,550,4,3,4,2,2,4,2,2,5,1,4,3,4,2,23,20.0,neutral or dissatisfied +38,96517,Female,Loyal Customer,47,Personal Travel,Eco,302,4,4,4,3,2,4,5,4,4,4,4,4,4,4,23,31.0,satisfied +39,64685,Male,disloyal Customer,41,Business travel,Business,354,1,1,1,2,1,1,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +40,64138,Male,Loyal Customer,39,Business travel,Business,1734,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +41,60373,Female,disloyal Customer,25,Business travel,Business,1452,3,5,3,4,3,3,3,3,4,4,5,5,5,3,9,23.0,neutral or dissatisfied +42,14849,Male,Loyal Customer,41,Business travel,Business,296,0,0,0,3,2,5,3,4,4,4,4,4,4,3,0,0.0,satisfied +43,28319,Female,Loyal Customer,38,Business travel,Business,2882,3,3,3,3,2,1,4,5,5,5,5,2,5,4,0,0.0,satisfied +44,103012,Female,Loyal Customer,50,Business travel,Business,460,1,1,1,1,3,5,5,3,3,3,3,4,3,5,1,15.0,satisfied +45,124114,Male,Loyal Customer,29,Business travel,Business,529,1,1,1,1,5,5,5,5,4,2,5,5,4,5,4,0.0,satisfied +46,107794,Female,Loyal Customer,22,Personal Travel,Business,349,2,4,2,1,4,2,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +47,81983,Female,Loyal Customer,13,Business travel,Business,1522,1,1,1,1,1,1,1,1,3,5,3,1,4,1,0,0.0,neutral or dissatisfied +48,53164,Male,Loyal Customer,54,Business travel,Business,612,3,3,3,3,5,2,3,5,5,5,5,4,5,3,8,0.0,satisfied +49,82042,Male,Loyal Customer,21,Personal Travel,Eco,1454,2,2,2,3,5,2,5,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +50,72127,Male,Loyal Customer,28,Business travel,Eco,731,2,1,1,1,2,2,2,2,3,3,2,3,3,2,14,8.0,neutral or dissatisfied +51,113046,Male,Loyal Customer,27,Business travel,Business,2076,3,3,3,3,4,4,4,4,3,4,4,4,5,4,0,1.0,satisfied +52,1050,Female,Loyal Customer,69,Business travel,Eco,309,5,5,5,5,1,2,3,5,5,5,5,4,5,2,0,0.0,satisfied +53,54886,Male,Loyal Customer,35,Personal Travel,Eco,775,2,3,2,4,4,2,4,4,4,4,3,4,1,4,1,0.0,neutral or dissatisfied +54,125918,Female,Loyal Customer,60,Personal Travel,Eco,861,2,2,2,3,1,3,4,4,4,2,4,4,4,4,10,10.0,neutral or dissatisfied +55,7467,Female,Loyal Customer,45,Business travel,Business,3334,2,4,2,2,4,5,5,4,4,4,4,3,4,5,51,48.0,satisfied +56,78972,Female,Loyal Customer,57,Business travel,Business,2496,0,0,0,1,3,4,5,5,5,5,5,4,5,5,0,5.0,satisfied +57,126625,Male,Loyal Customer,40,Business travel,Business,602,5,5,5,5,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +58,114501,Female,disloyal Customer,38,Business travel,Business,308,3,3,3,3,4,3,4,4,1,1,4,2,3,4,39,26.0,neutral or dissatisfied +59,114813,Male,disloyal Customer,23,Business travel,Eco,446,2,4,2,1,4,2,4,4,4,2,4,5,5,4,4,0.0,neutral or dissatisfied +60,32167,Male,disloyal Customer,39,Business travel,Business,216,2,2,2,3,3,2,3,3,2,1,4,2,4,3,0,0.0,neutral or dissatisfied +61,68001,Female,Loyal Customer,52,Business travel,Business,3475,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +62,117052,Male,disloyal Customer,25,Business travel,Eco,646,2,1,2,2,4,2,3,4,4,4,3,2,2,4,13,1.0,neutral or dissatisfied +63,8661,Female,Loyal Customer,48,Business travel,Business,2501,3,3,3,3,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +64,57165,Female,Loyal Customer,59,Business travel,Business,2227,5,5,5,5,2,4,4,4,4,4,4,3,4,4,30,15.0,satisfied +65,78610,Male,Loyal Customer,25,Business travel,Business,1426,3,3,3,3,4,5,4,4,5,4,4,4,4,4,4,0.0,satisfied +66,51058,Male,Loyal Customer,38,Personal Travel,Eco,190,2,4,2,3,4,2,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +67,92027,Male,Loyal Customer,46,Business travel,Business,1532,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +68,115534,Male,Loyal Customer,50,Business travel,Eco,308,2,1,1,1,2,2,2,2,3,2,2,2,3,2,18,12.0,neutral or dissatisfied +69,9261,Female,Loyal Customer,38,Business travel,Eco Plus,157,4,4,4,4,4,4,4,4,3,3,1,1,4,4,0,0.0,satisfied +70,61033,Female,Loyal Customer,53,Business travel,Business,1506,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +71,75930,Male,Loyal Customer,30,Business travel,Eco Plus,205,3,2,2,2,3,3,3,3,2,5,1,1,2,3,64,49.0,neutral or dissatisfied +72,112142,Male,disloyal Customer,39,Business travel,Business,895,2,2,2,4,5,2,5,5,5,4,4,5,5,5,0,2.0,neutral or dissatisfied +73,24518,Male,Loyal Customer,66,Personal Travel,Eco Plus,516,1,4,1,2,2,1,2,2,4,4,5,5,5,2,0,37.0,neutral or dissatisfied +74,112524,Male,Loyal Customer,45,Personal Travel,Eco,909,3,5,3,2,1,3,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +75,101639,Female,disloyal Customer,25,Business travel,Business,1435,5,1,5,4,1,5,1,1,4,2,5,4,5,1,1,1.0,satisfied +76,85018,Male,Loyal Customer,52,Business travel,Business,1190,2,4,4,4,1,4,3,2,2,2,2,1,2,4,0,6.0,neutral or dissatisfied +77,106922,Male,Loyal Customer,64,Personal Travel,Eco,1259,4,5,4,2,2,4,2,2,4,5,3,4,4,2,20,5.0,satisfied +78,32564,Female,disloyal Customer,50,Business travel,Eco,216,4,0,4,4,4,4,4,4,5,2,1,4,4,4,0,0.0,neutral or dissatisfied +79,92242,Female,disloyal Customer,41,Business travel,Business,1670,2,1,1,2,3,2,4,3,3,5,3,4,5,3,0,0.0,neutral or dissatisfied +80,73302,Male,Loyal Customer,26,Business travel,Business,3960,1,1,1,1,4,4,4,4,4,2,5,4,4,4,45,48.0,satisfied +81,42267,Female,disloyal Customer,25,Business travel,Eco,817,4,4,4,3,3,4,3,3,2,3,2,3,3,3,0,0.0,neutral or dissatisfied +82,121358,Female,disloyal Customer,44,Business travel,Business,1670,3,3,3,4,5,3,5,5,3,2,4,2,4,5,0,8.0,neutral or dissatisfied +83,65655,Female,disloyal Customer,21,Business travel,Business,861,4,0,4,4,1,4,1,1,3,4,4,4,5,1,0,0.0,satisfied +84,88062,Male,Loyal Customer,47,Business travel,Business,406,2,2,2,2,3,5,5,4,4,4,4,5,4,4,44,50.0,satisfied +85,91330,Male,Loyal Customer,31,Business travel,Eco Plus,404,4,4,4,4,4,4,4,4,1,2,2,4,2,4,17,3.0,satisfied +86,22031,Female,Loyal Customer,57,Personal Travel,Eco Plus,500,3,5,3,2,3,4,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +87,27921,Male,Loyal Customer,44,Personal Travel,Eco,689,3,5,3,4,5,3,2,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +88,51947,Male,Loyal Customer,45,Business travel,Business,3100,3,3,3,3,1,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +89,40017,Male,disloyal Customer,13,Business travel,Eco,525,2,2,2,3,3,2,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +90,76392,Male,Loyal Customer,60,Personal Travel,Eco,931,0,5,0,3,4,0,3,4,4,5,5,4,5,4,0,0.0,satisfied +91,118486,Female,disloyal Customer,41,Business travel,Business,304,5,5,5,3,2,5,2,2,3,4,4,4,4,2,31,19.0,satisfied +92,6012,Male,Loyal Customer,30,Business travel,Business,1896,4,1,1,1,4,4,4,4,2,2,3,4,2,4,81,72.0,neutral or dissatisfied +93,30183,Female,Loyal Customer,51,Business travel,Eco Plus,261,5,4,4,4,4,3,1,5,5,5,5,1,5,1,0,0.0,satisfied +94,41652,Female,Loyal Customer,61,Business travel,Eco,347,2,5,5,5,5,2,4,3,3,2,3,3,3,4,0,11.0,satisfied +95,15138,Female,Loyal Customer,32,Business travel,Eco,1042,4,1,1,1,4,4,4,4,4,3,1,5,2,4,35,34.0,satisfied +96,123589,Female,Loyal Customer,39,Personal Travel,Eco,1773,4,5,4,5,5,4,5,5,2,2,3,3,1,5,14,18.0,neutral or dissatisfied +97,114534,Male,Loyal Customer,19,Personal Travel,Business,342,3,1,3,2,3,3,3,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +98,93076,Female,Loyal Customer,15,Personal Travel,Eco Plus,297,1,5,1,3,5,1,5,5,5,1,1,3,4,5,67,62.0,neutral or dissatisfied +99,96963,Female,disloyal Customer,42,Business travel,Business,883,3,3,3,3,3,3,4,3,5,2,4,3,4,3,22,27.0,satisfied +100,85494,Female,Loyal Customer,16,Personal Travel,Eco,332,2,5,2,1,3,2,4,3,5,4,5,4,4,3,40,52.0,neutral or dissatisfied +101,72989,Male,Loyal Customer,19,Business travel,Business,2388,5,5,5,5,4,5,4,4,5,5,1,5,4,4,0,0.0,satisfied +102,42357,Female,Loyal Customer,29,Personal Travel,Eco,748,2,5,2,2,5,2,1,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +103,23040,Female,disloyal Customer,27,Business travel,Eco Plus,1080,3,3,3,3,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +104,65420,Male,disloyal Customer,22,Business travel,Business,231,5,0,5,4,5,5,5,5,3,4,4,3,1,5,0,0.0,satisfied +105,65045,Female,Loyal Customer,15,Personal Travel,Eco,551,3,4,3,3,4,3,4,4,1,1,4,2,1,4,3,0.0,neutral or dissatisfied +106,37373,Male,disloyal Customer,11,Business travel,Eco,972,1,1,1,3,1,1,1,1,4,3,4,2,1,1,0,0.0,neutral or dissatisfied +107,44405,Female,Loyal Customer,34,Personal Travel,Eco,265,4,3,4,3,5,4,5,5,2,5,2,1,4,5,0,23.0,neutral or dissatisfied +108,16653,Female,disloyal Customer,26,Business travel,Eco,488,2,0,2,4,1,2,1,1,3,2,5,1,3,1,0,0.0,neutral or dissatisfied +109,71655,Female,Loyal Customer,26,Personal Travel,Eco,1144,3,5,2,2,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +110,77591,Male,Loyal Customer,53,Business travel,Business,2332,5,5,5,5,5,5,5,4,4,5,4,4,4,3,0,3.0,satisfied +111,4585,Male,Loyal Customer,36,Business travel,Business,3024,4,2,2,2,1,3,4,4,4,4,4,4,4,1,30,13.0,neutral or dissatisfied +112,108347,Male,Loyal Customer,32,Business travel,Business,1750,1,5,4,5,1,1,1,1,1,1,2,4,3,1,0,0.0,neutral or dissatisfied +113,23400,Male,Loyal Customer,20,Personal Travel,Eco,483,2,3,2,3,5,2,5,5,5,2,3,2,4,5,91,82.0,neutral or dissatisfied +114,31010,Female,Loyal Customer,35,Business travel,Business,2128,2,2,2,2,1,5,1,4,4,4,4,5,4,4,0,0.0,satisfied +115,57513,Male,Loyal Customer,15,Personal Travel,Eco,235,2,4,2,1,1,2,1,1,3,3,4,4,4,1,1,10.0,neutral or dissatisfied +116,20979,Male,Loyal Customer,52,Personal Travel,Eco,689,2,5,2,3,3,2,3,3,1,1,2,2,2,3,0,0.0,neutral or dissatisfied +117,95841,Male,Loyal Customer,45,Business travel,Business,1852,1,1,1,1,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +118,114684,Female,disloyal Customer,24,Business travel,Eco,372,4,4,4,3,3,4,5,3,5,4,4,4,4,3,21,23.0,neutral or dissatisfied +119,111667,Female,Loyal Customer,46,Business travel,Business,3705,4,3,3,3,4,3,4,4,4,4,4,4,4,4,4,0.0,neutral or dissatisfied +120,20101,Male,disloyal Customer,26,Business travel,Eco,416,3,0,3,3,1,3,1,1,3,5,2,3,3,1,0,9.0,neutral or dissatisfied +121,63212,Male,Loyal Customer,28,Business travel,Eco,337,4,1,1,1,4,4,4,4,1,3,2,3,2,4,3,0.0,neutral or dissatisfied +122,8256,Male,Loyal Customer,11,Personal Travel,Eco,335,1,5,1,3,3,1,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +123,56161,Male,Loyal Customer,45,Business travel,Business,1400,5,5,5,5,2,5,5,4,4,4,4,3,4,5,4,9.0,satisfied +124,121196,Male,Loyal Customer,62,Personal Travel,Eco,2521,4,5,4,3,4,1,1,5,3,5,4,1,4,1,7,30.0,neutral or dissatisfied +125,23788,Female,Loyal Customer,34,Business travel,Business,374,3,3,3,3,4,4,1,4,4,4,4,5,4,3,0,0.0,satisfied +126,129579,Male,Loyal Customer,51,Business travel,Business,308,2,2,2,2,4,5,5,4,4,4,4,3,4,5,17,8.0,satisfied +127,127516,Female,Loyal Customer,58,Business travel,Eco Plus,575,1,4,4,4,2,3,4,2,2,1,2,2,2,4,14,16.0,neutral or dissatisfied +128,18012,Male,Loyal Customer,22,Personal Travel,Eco,618,3,5,3,2,3,3,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +129,45561,Male,Loyal Customer,8,Business travel,Eco,1304,4,4,4,4,4,4,4,4,2,2,4,2,1,4,0,0.0,satisfied +130,5228,Male,disloyal Customer,26,Business travel,Business,351,4,4,4,3,2,4,2,2,4,5,4,4,5,2,4,11.0,satisfied +131,18311,Female,Loyal Customer,22,Personal Travel,Eco,549,4,0,4,3,3,4,1,3,3,2,5,4,5,3,15,3.0,neutral or dissatisfied +132,59891,Female,Loyal Customer,21,Business travel,Business,3510,3,1,1,1,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +133,60651,Male,Loyal Customer,31,Business travel,Business,1620,3,2,4,2,3,3,3,3,2,2,2,3,4,3,0,0.0,neutral or dissatisfied +134,51013,Female,Loyal Customer,44,Personal Travel,Eco,326,2,0,2,2,2,3,5,1,1,2,1,2,1,5,0,0.0,neutral or dissatisfied +135,91746,Male,Loyal Customer,27,Business travel,Business,588,2,2,2,2,5,5,5,5,5,2,5,3,5,5,0,0.0,satisfied +136,4233,Female,Loyal Customer,47,Business travel,Business,1020,3,1,3,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +137,14187,Male,Loyal Customer,24,Business travel,Business,2903,3,3,3,3,3,3,3,3,4,2,2,2,2,3,0,0.0,neutral or dissatisfied +138,19669,Male,Loyal Customer,67,Business travel,Business,2659,1,1,1,1,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +139,31147,Male,Loyal Customer,32,Business travel,Business,3037,2,2,2,2,4,4,4,4,4,1,1,3,5,4,0,0.0,satisfied +140,128842,Female,Loyal Customer,58,Personal Travel,Eco,2475,4,4,4,3,4,1,1,3,3,3,4,1,3,1,29,10.0,satisfied +141,27562,Male,Loyal Customer,12,Personal Travel,Eco,978,4,5,4,5,1,4,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +142,775,Female,Loyal Customer,56,Business travel,Business,2568,3,1,1,1,5,3,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +143,14070,Female,Loyal Customer,58,Personal Travel,Business,371,3,5,5,1,2,3,5,1,1,5,1,3,1,3,0,0.0,neutral or dissatisfied +144,106007,Male,disloyal Customer,24,Business travel,Eco,791,3,3,3,3,5,3,5,5,2,1,3,1,3,5,39,6.0,neutral or dissatisfied +145,116004,Male,Loyal Customer,68,Personal Travel,Eco,480,3,4,3,3,5,3,5,5,2,4,3,4,4,5,7,6.0,neutral or dissatisfied +146,68886,Male,Loyal Customer,46,Business travel,Business,1786,1,1,1,1,3,5,5,5,5,5,5,5,5,3,1,7.0,satisfied +147,72413,Male,Loyal Customer,43,Business travel,Business,1849,2,2,2,2,2,4,4,3,3,4,3,3,3,4,0,7.0,satisfied +148,73604,Female,Loyal Customer,55,Business travel,Business,3634,0,4,0,4,4,5,5,4,4,1,1,4,4,3,0,0.0,satisfied +149,48415,Female,Loyal Customer,54,Personal Travel,Business,844,4,5,5,2,2,4,4,3,3,5,3,3,3,4,0,0.0,neutral or dissatisfied +150,105708,Female,Loyal Customer,42,Business travel,Business,3094,5,5,5,5,4,4,5,2,2,2,2,5,2,3,0,10.0,satisfied +151,65579,Female,Loyal Customer,47,Business travel,Business,3465,1,3,3,3,3,3,4,1,1,1,1,1,1,4,13,15.0,neutral or dissatisfied +152,73058,Female,disloyal Customer,29,Business travel,Business,1035,1,1,1,1,5,1,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +153,65585,Female,Loyal Customer,36,Business travel,Eco,237,2,4,4,4,2,2,2,2,2,4,2,1,1,2,0,0.0,neutral or dissatisfied +154,8346,Female,Loyal Customer,50,Business travel,Business,3175,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +155,79678,Female,Loyal Customer,31,Personal Travel,Eco,760,4,2,4,4,1,4,1,1,3,4,4,4,4,1,17,27.0,neutral or dissatisfied +156,112483,Male,Loyal Customer,13,Personal Travel,Eco,853,1,4,1,4,4,1,4,4,5,2,5,4,4,4,105,122.0,neutral or dissatisfied +157,31698,Male,disloyal Customer,24,Business travel,Eco,446,3,4,4,4,5,4,5,5,4,4,4,2,4,5,0,0.0,neutral or dissatisfied +158,74030,Female,Loyal Customer,60,Business travel,Business,1071,2,2,2,2,4,5,1,3,3,4,3,5,3,1,0,0.0,satisfied +159,124931,Female,Loyal Customer,42,Personal Travel,Eco,728,2,3,2,3,5,3,4,3,3,2,3,3,3,2,0,3.0,neutral or dissatisfied +160,73924,Female,Loyal Customer,57,Business travel,Business,2585,2,2,2,2,4,4,4,4,3,5,4,4,3,4,0,0.0,satisfied +161,76073,Female,Loyal Customer,42,Business travel,Business,707,2,2,4,2,2,5,4,3,3,4,3,4,3,3,27,11.0,satisfied +162,104623,Male,disloyal Customer,20,Business travel,Eco,861,0,0,0,5,2,0,2,2,4,3,5,3,5,2,0,0.0,satisfied +163,58523,Female,Loyal Customer,51,Personal Travel,Eco,719,3,5,2,4,3,5,4,4,4,2,4,4,4,3,19,0.0,neutral or dissatisfied +164,121929,Male,Loyal Customer,45,Business travel,Business,1790,2,5,2,2,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +165,30704,Female,Loyal Customer,26,Business travel,Eco Plus,680,5,5,5,5,5,5,5,5,1,4,5,1,3,5,12,27.0,satisfied +166,58896,Male,disloyal Customer,26,Business travel,Eco,888,2,2,2,3,5,2,5,5,4,3,3,2,4,5,51,30.0,neutral or dissatisfied +167,26920,Female,Loyal Customer,24,Personal Travel,Eco,1660,2,1,2,3,3,2,5,3,1,4,2,2,2,3,0,2.0,neutral or dissatisfied +168,13884,Male,Loyal Customer,49,Business travel,Eco,578,5,1,1,1,5,5,5,1,1,1,4,5,4,5,162,179.0,satisfied +169,87681,Female,Loyal Customer,17,Business travel,Eco,606,5,1,4,1,5,5,4,5,5,1,2,5,3,5,15,15.0,satisfied +170,81719,Female,Loyal Customer,39,Business travel,Business,1487,3,3,3,3,4,4,5,4,4,4,4,4,4,3,7,0.0,satisfied +171,85554,Female,Loyal Customer,49,Business travel,Business,317,0,1,1,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +172,12645,Female,Loyal Customer,48,Personal Travel,Eco,844,3,4,4,3,4,4,4,4,4,4,4,3,4,3,0,1.0,neutral or dissatisfied +173,101275,Male,Loyal Customer,52,Business travel,Business,3747,5,5,5,5,2,4,5,4,4,4,4,5,4,5,24,20.0,satisfied +174,95982,Female,Loyal Customer,25,Business travel,Business,2748,4,4,4,4,3,3,3,3,3,2,4,5,4,3,0,0.0,satisfied +175,74610,Female,Loyal Customer,16,Business travel,Business,1503,3,5,5,5,3,3,3,3,2,4,3,2,3,3,0,0.0,neutral or dissatisfied +176,76449,Male,Loyal Customer,58,Business travel,Business,1717,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +177,14030,Male,disloyal Customer,8,Business travel,Business,1117,4,3,4,3,3,4,3,3,4,5,4,4,3,3,0,7.0,neutral or dissatisfied +178,69692,Male,Loyal Customer,42,Business travel,Business,1372,3,3,5,3,4,4,4,5,4,5,4,4,3,4,141,125.0,satisfied +179,47648,Female,Loyal Customer,52,Business travel,Business,2768,4,1,1,1,2,4,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +180,52168,Female,Loyal Customer,47,Business travel,Eco,370,5,3,3,3,2,1,1,5,5,5,5,3,5,4,0,0.0,satisfied +181,60251,Female,Loyal Customer,69,Personal Travel,Eco,1546,1,5,1,2,4,3,4,1,1,1,1,4,1,3,1,26.0,neutral or dissatisfied +182,35881,Female,Loyal Customer,47,Personal Travel,Eco,1023,2,3,3,3,5,3,3,4,4,3,1,3,4,4,0,0.0,neutral or dissatisfied +183,28852,Female,Loyal Customer,41,Business travel,Business,3636,1,1,1,1,3,5,4,4,4,4,4,5,4,2,0,0.0,satisfied +184,55341,Female,Loyal Customer,40,Personal Travel,Eco,1325,4,4,4,3,1,4,1,1,4,2,4,5,5,1,0,9.0,neutral or dissatisfied +185,84553,Female,Loyal Customer,56,Personal Travel,Eco,2556,1,4,1,3,3,3,1,5,5,1,5,1,5,2,0,0.0,neutral or dissatisfied +186,100249,Male,Loyal Customer,41,Business travel,Business,1052,2,2,2,2,4,4,4,4,4,4,4,3,4,4,6,0.0,satisfied +187,2463,Female,Loyal Customer,40,Business travel,Eco,773,3,4,4,4,3,3,3,3,2,5,4,4,4,3,15,26.0,neutral or dissatisfied +188,22924,Male,Loyal Customer,12,Personal Travel,Business,817,2,3,2,2,1,2,1,1,1,3,5,3,2,1,0,0.0,neutral or dissatisfied +189,25542,Male,Loyal Customer,59,Personal Travel,Eco,516,4,5,3,4,1,3,1,1,5,3,4,5,4,1,3,0.0,satisfied +190,115972,Female,Loyal Customer,21,Personal Travel,Eco,447,1,5,1,1,2,1,2,2,3,5,5,3,4,2,34,19.0,neutral or dissatisfied +191,2980,Male,Loyal Customer,12,Personal Travel,Eco,462,2,4,2,3,2,2,2,2,3,4,2,2,1,2,0,0.0,neutral or dissatisfied +192,125097,Male,Loyal Customer,31,Business travel,Eco,361,1,5,5,5,1,1,1,1,2,5,3,4,4,1,0,0.0,neutral or dissatisfied +193,46701,Female,Loyal Customer,37,Personal Travel,Eco,125,3,2,3,3,2,3,2,2,3,3,3,4,3,2,6,4.0,neutral or dissatisfied +194,108006,Female,Loyal Customer,38,Personal Travel,Eco,271,4,0,5,3,2,5,2,2,4,2,4,3,5,2,0,0.0,satisfied +195,19578,Male,Loyal Customer,45,Personal Travel,Eco,173,2,5,0,1,2,0,5,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +196,59508,Male,Loyal Customer,43,Business travel,Business,1950,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +197,56446,Female,Loyal Customer,52,Personal Travel,Eco,719,1,5,2,2,3,5,5,3,3,2,3,3,3,3,0,17.0,neutral or dissatisfied +198,48800,Female,Loyal Customer,57,Business travel,Business,153,3,4,4,4,5,3,4,2,2,2,3,4,2,2,0,0.0,neutral or dissatisfied +199,129592,Female,Loyal Customer,13,Personal Travel,Business,337,2,3,2,3,1,2,1,1,4,5,2,5,5,1,0,18.0,neutral or dissatisfied +200,114039,Female,Loyal Customer,45,Business travel,Business,3732,5,5,5,5,5,5,5,5,5,5,5,3,5,4,17,0.0,satisfied +201,66800,Female,Loyal Customer,43,Business travel,Business,3854,5,5,5,5,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +202,106799,Male,Loyal Customer,53,Business travel,Eco,977,2,4,2,4,2,2,2,2,3,2,3,2,3,2,20,17.0,neutral or dissatisfied +203,47057,Male,Loyal Customer,23,Business travel,Business,3073,4,4,1,4,5,5,5,5,1,3,1,3,3,5,0,3.0,satisfied +204,61824,Female,Loyal Customer,16,Personal Travel,Eco,1379,2,5,2,2,2,2,2,2,5,2,4,3,5,2,2,0.0,neutral or dissatisfied +205,68207,Male,Loyal Customer,23,Business travel,Eco,631,2,2,2,2,2,1,1,2,3,5,4,3,4,2,0,8.0,neutral or dissatisfied +206,125512,Male,Loyal Customer,45,Personal Travel,Eco,666,2,5,2,4,4,2,4,4,4,5,5,4,5,4,0,0.0,neutral or dissatisfied +207,93019,Female,Loyal Customer,46,Business travel,Business,2820,2,2,2,2,2,1,2,5,5,5,5,2,5,3,1,0.0,satisfied +208,87296,Female,Loyal Customer,49,Personal Travel,Eco,577,2,5,2,2,3,4,5,1,1,2,1,4,1,3,23,2.0,neutral or dissatisfied +209,76748,Female,Loyal Customer,40,Business travel,Business,2808,4,3,3,3,3,3,4,3,3,3,4,4,3,3,7,2.0,neutral or dissatisfied +210,85879,Female,Loyal Customer,19,Business travel,Business,2172,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +211,63961,Female,Loyal Customer,48,Personal Travel,Eco,1192,4,2,4,3,4,3,3,1,1,4,2,3,1,1,0,0.0,neutral or dissatisfied +212,94760,Female,Loyal Customer,64,Business travel,Business,1773,2,4,3,4,5,3,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +213,49608,Female,Loyal Customer,38,Business travel,Eco,109,5,3,3,3,5,5,5,5,5,2,4,1,1,5,31,,satisfied +214,80520,Male,Loyal Customer,23,Personal Travel,Eco,1749,2,1,1,4,3,1,3,3,1,1,4,2,3,3,97,89.0,neutral or dissatisfied +215,23328,Female,Loyal Customer,38,Business travel,Business,3753,2,2,2,2,1,1,5,4,4,4,4,4,4,1,0,0.0,satisfied +216,13560,Male,Loyal Customer,41,Personal Travel,Eco,214,1,4,1,2,2,1,1,2,4,3,5,4,5,2,16,34.0,neutral or dissatisfied +217,119121,Male,Loyal Customer,29,Personal Travel,Eco,1020,1,4,1,4,1,1,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +218,42917,Male,Loyal Customer,47,Business travel,Eco Plus,368,5,1,2,1,4,5,4,4,5,5,2,4,3,4,0,0.0,satisfied +219,52954,Male,Loyal Customer,50,Personal Travel,Eco Plus,1448,2,3,2,5,4,2,4,4,4,3,4,3,1,4,20,4.0,neutral or dissatisfied +220,83112,Female,Loyal Customer,18,Personal Travel,Eco,1127,2,5,2,3,3,2,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +221,88574,Female,Loyal Customer,20,Personal Travel,Eco,545,2,0,2,3,5,2,1,5,3,4,3,3,1,5,4,0.0,neutral or dissatisfied +222,111570,Female,Loyal Customer,41,Business travel,Business,3238,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +223,28662,Female,Loyal Customer,12,Personal Travel,Eco,2466,2,4,2,3,1,2,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +224,27177,Female,Loyal Customer,36,Personal Travel,Eco,2715,2,3,2,3,2,3,2,4,5,3,3,2,3,2,0,0.0,neutral or dissatisfied +225,129585,Male,Loyal Customer,49,Business travel,Business,337,3,4,3,3,4,5,5,4,4,4,4,5,4,3,10,0.0,satisfied +226,35759,Female,Loyal Customer,55,Personal Travel,Eco,1608,2,2,2,4,2,3,4,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +227,49475,Female,Loyal Customer,43,Business travel,Business,3004,3,3,3,3,2,4,3,2,2,2,3,1,2,2,0,0.0,neutral or dissatisfied +228,78904,Female,disloyal Customer,49,Business travel,Business,980,2,2,2,2,3,2,3,3,3,5,5,4,4,3,11,6.0,neutral or dissatisfied +229,29619,Female,disloyal Customer,35,Business travel,Eco,1462,1,1,1,1,3,1,3,3,1,5,1,3,2,3,0,0.0,neutral or dissatisfied +230,77512,Male,Loyal Customer,45,Business travel,Business,1521,1,1,3,1,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +231,31631,Female,Loyal Customer,28,Business travel,Business,862,5,5,5,5,5,5,5,5,2,3,1,1,2,5,9,5.0,satisfied +232,38913,Male,Loyal Customer,60,Business travel,Business,1833,4,4,4,4,1,4,5,4,4,4,4,1,4,2,0,0.0,satisfied +233,35366,Male,Loyal Customer,35,Business travel,Business,2398,2,4,2,4,1,3,2,2,2,2,2,4,2,3,0,9.0,neutral or dissatisfied +234,111817,Female,disloyal Customer,38,Business travel,Business,349,3,3,3,5,4,3,4,4,5,4,4,5,5,4,29,28.0,neutral or dissatisfied +235,12259,Male,Loyal Customer,48,Business travel,Business,1722,4,5,4,4,4,2,3,4,4,4,4,2,4,1,0,0.0,satisfied +236,19790,Female,Loyal Customer,65,Personal Travel,Eco,578,2,4,3,4,2,4,4,3,3,3,3,4,3,3,99,101.0,neutral or dissatisfied +237,33260,Male,Loyal Customer,30,Personal Travel,Eco Plus,163,3,5,3,2,1,3,1,1,4,2,4,5,5,1,9,11.0,neutral or dissatisfied +238,107079,Female,Loyal Customer,51,Personal Travel,Eco,395,2,4,5,1,2,4,5,3,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +239,15174,Male,disloyal Customer,23,Business travel,Eco,416,5,0,5,2,4,5,4,4,3,5,5,3,2,4,18,4.0,satisfied +240,23620,Female,Loyal Customer,37,Business travel,Eco,977,3,4,4,4,3,3,3,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +241,18128,Male,Loyal Customer,23,Business travel,Business,3095,5,5,5,5,5,5,3,5,2,5,4,3,3,5,9,0.0,satisfied +242,105291,Male,Loyal Customer,32,Business travel,Business,738,4,4,4,4,4,4,4,4,4,2,4,3,3,4,0,3.0,neutral or dissatisfied +243,56451,Male,Loyal Customer,67,Personal Travel,Eco,719,3,3,3,4,1,3,1,1,2,2,3,1,5,1,24,14.0,neutral or dissatisfied +244,102068,Male,Loyal Customer,65,Personal Travel,Business,226,1,4,1,1,5,5,4,4,4,1,4,5,4,3,37,20.0,neutral or dissatisfied +245,57995,Female,Loyal Customer,48,Business travel,Business,1943,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +246,146,Male,Loyal Customer,60,Business travel,Business,2371,4,4,4,4,2,4,5,4,4,4,4,3,4,3,66,61.0,satisfied +247,18770,Female,Loyal Customer,31,Business travel,Business,551,3,1,1,1,3,3,3,3,3,4,3,4,4,3,53,48.0,neutral or dissatisfied +248,42774,Male,Loyal Customer,22,Business travel,Eco Plus,493,4,1,5,5,4,4,4,4,2,4,2,3,4,4,19,6.0,satisfied +249,13776,Male,disloyal Customer,27,Business travel,Eco,925,2,2,2,5,5,2,5,5,2,5,5,1,4,5,4,3.0,neutral or dissatisfied +250,103702,Female,Loyal Customer,19,Personal Travel,Eco,405,2,2,2,4,1,2,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +251,69826,Female,disloyal Customer,26,Business travel,Eco,1055,3,3,3,4,4,3,4,4,3,5,4,2,4,4,0,0.0,neutral or dissatisfied +252,57906,Male,Loyal Customer,72,Business travel,Eco,305,4,3,3,3,4,4,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +253,31358,Female,Loyal Customer,34,Business travel,Business,589,5,5,5,5,1,1,5,5,5,5,5,5,5,5,0,11.0,satisfied +254,92805,Female,Loyal Customer,45,Business travel,Business,1587,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +255,104375,Male,Loyal Customer,51,Business travel,Business,3090,2,4,4,4,3,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +256,109896,Female,disloyal Customer,26,Business travel,Eco,804,2,2,2,3,4,2,3,4,1,4,4,1,4,4,7,0.0,neutral or dissatisfied +257,102955,Female,Loyal Customer,12,Personal Travel,Eco,719,3,4,3,3,1,3,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +258,44736,Female,Loyal Customer,72,Business travel,Eco Plus,67,2,5,3,5,2,3,4,3,3,2,3,4,3,3,28,18.0,neutral or dissatisfied +259,28135,Male,Loyal Customer,45,Business travel,Eco,550,4,2,4,4,4,4,4,4,4,4,3,5,5,4,0,0.0,satisfied +260,55871,Female,Loyal Customer,22,Business travel,Business,2809,2,2,2,2,5,5,5,5,3,4,4,5,4,5,36,28.0,satisfied +261,8818,Female,Loyal Customer,53,Personal Travel,Eco,552,4,4,4,1,4,5,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +262,86148,Female,disloyal Customer,33,Business travel,Business,356,3,3,3,4,4,3,4,4,4,5,5,5,5,4,12,0.0,neutral or dissatisfied +263,120162,Female,Loyal Customer,46,Personal Travel,Business,119,4,0,4,1,5,5,4,4,4,4,4,3,4,3,13,32.0,neutral or dissatisfied +264,117547,Male,Loyal Customer,54,Business travel,Business,1545,2,2,2,2,5,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +265,112385,Female,Loyal Customer,40,Business travel,Eco,819,4,2,3,3,4,4,4,4,1,2,3,1,3,4,23,6.0,neutral or dissatisfied +266,19908,Female,Loyal Customer,37,Business travel,Business,1801,2,4,3,3,4,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +267,45098,Female,Loyal Customer,35,Business travel,Business,1658,2,2,5,2,1,2,1,5,5,5,3,3,5,3,6,6.0,satisfied +268,43810,Female,disloyal Customer,26,Business travel,Business,114,4,0,5,3,4,5,4,4,4,2,5,4,4,4,0,13.0,satisfied +269,22981,Female,Loyal Customer,62,Business travel,Eco,128,4,3,3,3,2,5,1,5,5,4,5,3,5,1,0,16.0,satisfied +270,68134,Male,Loyal Customer,58,Business travel,Business,813,1,1,1,1,5,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +271,23518,Female,Loyal Customer,55,Personal Travel,Eco,349,2,3,2,3,2,3,5,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +272,109188,Female,Loyal Customer,60,Business travel,Business,1508,3,1,1,1,2,2,2,3,3,3,3,2,3,2,15,15.0,neutral or dissatisfied +273,1150,Female,Loyal Customer,15,Personal Travel,Eco,89,3,5,3,4,5,3,1,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +274,44586,Male,Loyal Customer,67,Personal Travel,Eco,157,4,1,4,3,5,4,5,5,4,5,3,4,3,5,45,33.0,neutral or dissatisfied +275,84299,Male,Loyal Customer,43,Business travel,Business,2828,0,1,1,2,5,5,4,3,3,3,3,5,3,5,39,41.0,satisfied +276,103793,Male,Loyal Customer,30,Business travel,Business,3131,1,1,1,1,5,4,5,5,5,5,4,5,5,5,7,0.0,satisfied +277,35032,Female,Loyal Customer,42,Business travel,Eco,718,5,1,4,1,3,3,3,5,5,5,5,3,5,1,0,0.0,satisfied +278,103291,Male,Loyal Customer,40,Business travel,Business,1959,3,3,3,3,4,4,4,4,3,5,5,4,5,4,209,191.0,satisfied +279,93909,Male,Loyal Customer,47,Business travel,Business,3496,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,2.0,satisfied +280,127925,Male,Loyal Customer,38,Business travel,Business,2300,4,2,2,2,4,4,3,4,4,4,4,3,4,2,60,37.0,neutral or dissatisfied +281,128097,Female,Loyal Customer,25,Personal Travel,Eco,2845,3,0,3,5,3,3,3,1,1,3,2,3,3,3,0,1.0,neutral or dissatisfied +282,26149,Male,disloyal Customer,26,Business travel,Eco,406,3,5,3,4,3,3,3,5,5,4,1,3,4,3,149,138.0,neutral or dissatisfied +283,95886,Male,Loyal Customer,66,Personal Travel,Eco,580,2,4,2,3,4,2,4,4,5,3,5,3,4,4,26,13.0,neutral or dissatisfied +284,125425,Female,Loyal Customer,69,Business travel,Eco,735,1,4,4,4,3,3,4,1,1,1,1,4,1,2,12,4.0,neutral or dissatisfied +285,120078,Female,Loyal Customer,22,Business travel,Business,1722,2,5,5,5,2,2,2,2,2,4,3,3,3,2,0,53.0,neutral or dissatisfied +286,60625,Male,Loyal Customer,8,Personal Travel,Eco Plus,1201,2,5,2,3,3,2,3,3,4,2,1,5,5,3,24,14.0,neutral or dissatisfied +287,115031,Female,disloyal Customer,37,Business travel,Business,372,5,5,5,4,4,5,4,4,4,4,5,3,4,4,11,0.0,satisfied +288,37077,Female,Loyal Customer,69,Personal Travel,Eco,1072,1,5,1,5,4,4,4,1,1,1,1,4,1,4,18,7.0,neutral or dissatisfied +289,69252,Male,Loyal Customer,28,Business travel,Eco,733,4,2,2,2,4,4,4,4,3,4,3,3,4,4,15,22.0,neutral or dissatisfied +290,12194,Male,Loyal Customer,51,Business travel,Eco Plus,1075,2,4,1,4,2,2,2,2,1,2,4,4,3,2,5,0.0,neutral or dissatisfied +291,80188,Female,Loyal Customer,46,Personal Travel,Eco,2586,3,1,3,3,3,4,4,2,4,4,3,4,1,4,59,57.0,neutral or dissatisfied +292,10430,Male,disloyal Customer,39,Business travel,Business,140,4,4,4,3,4,4,2,4,3,4,4,4,4,4,0,7.0,satisfied +293,21262,Female,disloyal Customer,21,Business travel,Eco Plus,903,4,3,4,4,1,4,1,1,4,5,3,1,4,1,35,28.0,neutral or dissatisfied +294,55236,Male,Loyal Customer,46,Business travel,Business,2423,4,4,4,4,2,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +295,126917,Female,Loyal Customer,36,Business travel,Business,3130,2,2,2,2,5,5,5,5,5,5,5,5,5,3,62,65.0,satisfied +296,112190,Male,Loyal Customer,60,Business travel,Business,2198,3,3,3,3,3,4,4,4,4,4,4,3,4,3,23,4.0,satisfied +297,16342,Male,Loyal Customer,23,Business travel,Eco Plus,602,2,5,5,5,2,2,1,2,3,4,4,4,4,2,21,44.0,neutral or dissatisfied +298,2201,Male,Loyal Customer,52,Personal Travel,Eco,685,4,4,4,5,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +299,53687,Male,Loyal Customer,36,Business travel,Eco,1208,4,5,5,5,4,4,4,4,2,1,2,2,3,4,3,0.0,satisfied +300,47168,Male,Loyal Customer,41,Business travel,Business,2789,3,3,2,3,4,3,3,4,4,3,4,3,4,5,10,0.0,satisfied +301,8782,Male,Loyal Customer,45,Business travel,Business,3305,2,2,2,2,3,5,5,4,4,4,4,4,4,3,8,0.0,satisfied +302,75468,Male,Loyal Customer,67,Personal Travel,Eco,2342,3,4,3,3,5,3,2,5,4,2,3,1,4,5,0,0.0,neutral or dissatisfied +303,663,Female,Loyal Customer,45,Business travel,Business,3712,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +304,74740,Female,Loyal Customer,56,Personal Travel,Eco,1431,3,5,3,3,4,5,5,1,1,3,1,2,1,5,91,76.0,neutral or dissatisfied +305,117904,Female,disloyal Customer,62,Business travel,Eco,255,3,3,2,2,2,2,2,2,1,5,3,1,3,2,113,107.0,neutral or dissatisfied +306,59599,Female,Loyal Customer,30,Business travel,Business,3720,2,1,1,1,2,3,2,2,2,4,3,3,4,2,27,12.0,neutral or dissatisfied +307,29479,Male,Loyal Customer,48,Business travel,Eco,1107,4,5,5,5,4,4,4,4,3,5,4,1,2,4,0,0.0,satisfied +308,105096,Female,Loyal Customer,32,Business travel,Business,2999,2,2,2,2,4,4,4,4,3,4,5,3,4,4,28,11.0,satisfied +309,94421,Female,Loyal Customer,30,Business travel,Business,2438,0,1,1,1,2,2,2,2,5,3,5,3,4,2,38,28.0,satisfied +310,49058,Female,disloyal Customer,40,Business travel,Business,156,1,1,1,5,4,1,2,4,2,4,5,5,2,4,0,0.0,neutral or dissatisfied +311,47795,Male,Loyal Customer,42,Business travel,Business,3665,5,5,5,5,5,5,4,4,4,4,4,4,4,3,83,92.0,satisfied +312,125451,Female,Loyal Customer,52,Business travel,Business,2917,5,5,5,5,5,5,5,3,4,4,4,5,3,5,15,32.0,satisfied +313,96114,Male,Loyal Customer,50,Business travel,Business,1235,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +314,23241,Female,Loyal Customer,18,Personal Travel,Eco Plus,549,2,5,2,3,2,2,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +315,106258,Male,Loyal Customer,30,Business travel,Business,1500,3,3,3,3,5,4,5,5,4,3,4,3,5,5,0,0.0,satisfied +316,64874,Female,disloyal Customer,26,Business travel,Eco,190,3,2,3,3,1,3,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +317,100136,Male,disloyal Customer,37,Business travel,Business,468,4,4,4,4,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +318,51774,Male,Loyal Customer,64,Personal Travel,Eco,261,1,4,0,3,1,0,1,1,3,1,3,3,4,1,0,0.0,neutral or dissatisfied +319,124301,Male,disloyal Customer,21,Business travel,Business,255,5,0,5,1,2,5,2,2,5,4,5,3,4,2,0,0.0,satisfied +320,36127,Female,Loyal Customer,52,Business travel,Business,1609,3,2,4,4,3,4,4,3,3,3,3,1,3,3,0,8.0,neutral or dissatisfied +321,121855,Female,Loyal Customer,52,Business travel,Business,413,5,5,5,5,5,5,4,5,5,5,5,4,5,3,4,2.0,satisfied +322,52648,Female,Loyal Customer,29,Personal Travel,Eco,119,2,2,2,2,5,2,2,5,4,5,3,2,3,5,0,0.0,neutral or dissatisfied +323,38803,Female,Loyal Customer,13,Personal Travel,Eco,387,2,1,2,3,1,2,1,1,4,1,3,1,4,1,16,12.0,neutral or dissatisfied +324,39916,Male,Loyal Customer,28,Business travel,Business,1087,1,1,3,1,5,5,5,5,3,2,4,5,5,5,0,0.0,satisfied +325,95301,Male,Loyal Customer,13,Personal Travel,Eco,323,2,4,2,3,2,2,2,2,1,5,4,4,4,2,15,7.0,neutral or dissatisfied +326,16505,Male,Loyal Customer,16,Personal Travel,Eco,282,2,5,2,3,5,2,5,5,3,3,5,5,4,5,8,16.0,neutral or dissatisfied +327,63771,Male,Loyal Customer,58,Business travel,Business,1721,3,3,3,3,3,4,5,4,4,4,4,4,4,5,18,0.0,satisfied +328,51960,Male,disloyal Customer,24,Business travel,Eco,347,3,0,3,1,5,3,5,5,3,5,4,5,3,5,0,0.0,neutral or dissatisfied +329,111305,Male,Loyal Customer,25,Business travel,Business,3465,2,4,4,4,2,2,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +330,114340,Male,Loyal Customer,34,Personal Travel,Eco,948,2,4,2,2,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +331,17379,Female,Loyal Customer,44,Business travel,Business,1707,5,5,5,5,5,5,3,5,5,5,5,2,5,3,0,0.0,satisfied +332,65992,Female,Loyal Customer,23,Personal Travel,Eco Plus,1372,3,5,3,1,1,3,1,1,3,2,3,4,5,1,0,0.0,neutral or dissatisfied +333,104578,Male,disloyal Customer,20,Business travel,Business,369,5,3,5,4,1,5,1,1,5,2,4,4,4,1,0,0.0,satisfied +334,7443,Male,Loyal Customer,8,Personal Travel,Eco,552,4,3,4,1,3,4,3,3,3,2,2,3,5,3,0,11.0,neutral or dissatisfied +335,67768,Female,Loyal Customer,26,Business travel,Eco,1188,1,5,5,5,1,1,4,1,2,3,4,3,3,1,0,13.0,neutral or dissatisfied +336,89581,Male,Loyal Customer,43,Business travel,Eco,1005,4,4,4,4,5,4,5,5,4,1,4,3,3,5,0,1.0,neutral or dissatisfied +337,47417,Female,Loyal Customer,72,Business travel,Business,1870,2,1,1,1,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +338,30231,Female,Loyal Customer,48,Business travel,Eco,896,2,4,4,4,4,2,4,2,2,2,2,5,2,1,12,8.0,satisfied +339,14343,Male,Loyal Customer,27,Personal Travel,Eco,429,4,5,4,3,3,4,1,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +340,79924,Male,Loyal Customer,25,Business travel,Business,1796,4,2,2,2,4,4,4,1,5,3,3,4,2,4,176,164.0,neutral or dissatisfied +341,105654,Male,disloyal Customer,26,Business travel,Eco,842,1,1,1,2,5,1,5,5,1,3,3,4,2,5,38,28.0,neutral or dissatisfied +342,29495,Male,disloyal Customer,16,Business travel,Business,1107,3,4,3,3,1,3,3,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +343,98183,Female,disloyal Customer,36,Business travel,Business,327,2,2,2,3,5,2,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +344,87554,Male,Loyal Customer,55,Personal Travel,Business,432,4,4,2,1,5,4,4,3,3,2,2,4,3,5,0,0.0,neutral or dissatisfied +345,83683,Female,disloyal Customer,23,Business travel,Eco,577,0,0,1,1,5,1,5,5,4,2,4,2,1,5,0,0.0,satisfied +346,74603,Male,Loyal Customer,50,Business travel,Business,1877,2,4,4,4,5,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +347,83191,Female,Loyal Customer,45,Business travel,Business,1123,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,5.0,satisfied +348,110103,Male,Loyal Customer,57,Business travel,Business,1749,1,1,1,1,4,5,5,5,5,5,5,4,5,4,19,5.0,satisfied +349,57026,Female,Loyal Customer,50,Business travel,Business,2454,3,3,3,3,5,3,5,3,3,3,3,3,3,5,46,24.0,satisfied +350,91205,Female,Loyal Customer,42,Personal Travel,Eco,270,1,2,1,4,3,3,3,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +351,55470,Female,Loyal Customer,34,Business travel,Business,1825,2,2,2,2,3,3,5,5,5,4,5,3,5,3,13,0.0,satisfied +352,53922,Female,disloyal Customer,17,Business travel,Eco Plus,191,1,1,1,4,4,1,2,4,4,1,4,2,3,4,39,34.0,neutral or dissatisfied +353,129138,Male,Loyal Customer,45,Business travel,Business,679,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,6.0,satisfied +354,2034,Female,Loyal Customer,59,Business travel,Business,812,2,2,2,2,4,4,5,2,2,2,2,5,2,4,0,3.0,satisfied +355,37286,Male,Loyal Customer,39,Business travel,Eco,1056,5,3,3,3,5,5,5,5,3,2,4,5,2,5,20,9.0,satisfied +356,32818,Male,Loyal Customer,28,Business travel,Business,101,2,1,1,1,2,2,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +357,46695,Female,Loyal Customer,44,Personal Travel,Eco,73,2,3,2,3,4,3,4,1,1,2,1,2,1,1,0,32.0,neutral or dissatisfied +358,121598,Male,Loyal Customer,9,Personal Travel,Eco,936,5,5,4,2,4,4,4,4,5,4,5,5,5,4,22,22.0,satisfied +359,44039,Female,Loyal Customer,24,Business travel,Eco,287,1,1,0,3,5,0,5,5,2,2,2,2,2,5,0,8.0,neutral or dissatisfied +360,102733,Female,Loyal Customer,37,Personal Travel,Eco,255,3,1,3,4,3,3,3,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +361,85600,Female,disloyal Customer,25,Business travel,Eco,317,0,4,0,4,5,0,5,5,5,1,2,4,3,5,9,5.0,satisfied +362,10833,Male,Loyal Customer,22,Business travel,Business,2027,2,2,2,2,4,4,4,4,5,3,4,4,4,4,7,2.0,satisfied +363,81553,Male,Loyal Customer,55,Business travel,Business,936,3,3,3,3,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +364,24745,Male,Loyal Customer,53,Business travel,Eco,432,4,3,3,3,4,4,4,4,4,3,3,1,4,4,0,5.0,satisfied +365,58871,Female,Loyal Customer,46,Business travel,Business,888,3,3,3,3,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +366,68900,Male,Loyal Customer,62,Personal Travel,Eco,1061,0,5,0,3,5,0,5,5,4,4,5,5,5,5,0,0.0,satisfied +367,31952,Female,Loyal Customer,53,Business travel,Business,216,5,5,4,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +368,98758,Female,Loyal Customer,50,Business travel,Business,1814,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +369,59963,Male,Loyal Customer,57,Business travel,Business,2993,5,5,5,5,2,4,2,4,4,4,4,4,4,3,0,6.0,satisfied +370,38236,Female,Loyal Customer,54,Business travel,Business,2632,3,3,3,3,2,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +371,43811,Female,Loyal Customer,42,Business travel,Business,199,1,1,1,1,5,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +372,58215,Male,Loyal Customer,17,Personal Travel,Eco,802,2,5,2,2,4,2,4,4,2,5,3,1,4,4,0,5.0,neutral or dissatisfied +373,88293,Female,Loyal Customer,53,Business travel,Business,581,1,1,1,1,3,4,4,4,4,4,4,3,4,3,1,0.0,satisfied +374,37225,Male,Loyal Customer,49,Business travel,Business,1938,2,2,2,2,3,4,5,4,4,4,4,5,4,4,22,21.0,satisfied +375,43935,Female,Loyal Customer,37,Business travel,Eco Plus,174,5,3,5,3,5,5,5,5,5,1,5,3,5,5,0,0.0,satisfied +376,48899,Male,Loyal Customer,35,Business travel,Eco,326,4,2,2,2,4,4,4,4,2,5,5,5,3,4,0,0.0,satisfied +377,99082,Male,Loyal Customer,30,Business travel,Business,1821,1,1,1,1,2,2,1,2,1,2,2,4,2,2,5,7.0,neutral or dissatisfied +378,75859,Female,Loyal Customer,16,Personal Travel,Eco,1437,1,5,0,4,5,0,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +379,85109,Male,Loyal Customer,46,Business travel,Business,3995,4,4,4,4,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +380,118135,Female,Loyal Customer,51,Business travel,Business,1488,2,3,3,3,4,3,4,2,2,2,2,4,2,2,73,62.0,neutral or dissatisfied +381,89169,Male,Loyal Customer,70,Personal Travel,Eco,1892,1,4,1,3,1,1,1,1,4,4,4,4,3,1,0,0.0,neutral or dissatisfied +382,4988,Male,disloyal Customer,26,Business travel,Business,502,2,2,2,5,5,2,2,5,4,3,4,4,4,5,53,52.0,neutral or dissatisfied +383,81441,Male,Loyal Customer,46,Business travel,Business,2491,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +384,37707,Female,Loyal Customer,12,Personal Travel,Eco,944,2,2,2,4,1,2,1,1,1,4,4,1,4,1,20,15.0,neutral or dissatisfied +385,94317,Male,Loyal Customer,25,Business travel,Business,496,4,4,4,4,4,4,4,4,3,2,5,4,5,4,0,0.0,satisfied +386,42242,Female,Loyal Customer,63,Business travel,Business,329,2,2,2,2,5,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +387,8085,Female,Loyal Customer,48,Business travel,Business,402,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,4.0,satisfied +388,42926,Female,Loyal Customer,43,Business travel,Business,3946,3,3,3,3,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +389,114663,Female,Loyal Customer,35,Business travel,Business,337,5,5,5,5,2,4,5,4,4,4,4,3,4,5,54,40.0,satisfied +390,63597,Female,Loyal Customer,32,Business travel,Business,2133,4,4,4,4,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +391,78220,Male,Loyal Customer,44,Personal Travel,Eco,192,2,4,2,5,4,2,4,4,3,1,4,1,2,4,0,0.0,neutral or dissatisfied +392,2902,Male,Loyal Customer,60,Personal Travel,Eco,491,1,3,1,3,5,1,5,5,3,2,2,5,1,5,22,49.0,neutral or dissatisfied +393,71673,Female,Loyal Customer,20,Personal Travel,Eco,1120,2,1,2,4,2,2,2,2,2,4,4,3,3,2,0,3.0,neutral or dissatisfied +394,128042,Female,Loyal Customer,10,Personal Travel,Eco,1440,1,4,1,4,4,1,4,4,5,3,3,5,5,4,0,7.0,neutral or dissatisfied +395,53847,Female,Loyal Customer,51,Business travel,Business,140,2,1,3,1,1,3,3,3,3,3,2,2,3,2,0,0.0,neutral or dissatisfied +396,42369,Female,Loyal Customer,22,Personal Travel,Eco,451,2,4,2,3,2,2,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +397,110474,Female,Loyal Customer,42,Personal Travel,Eco,798,1,1,1,3,5,2,2,3,3,1,3,3,3,3,1,4.0,neutral or dissatisfied +398,17284,Male,Loyal Customer,32,Business travel,Business,3607,1,1,1,1,5,5,5,5,4,2,5,1,5,5,0,0.0,satisfied +399,69457,Male,Loyal Customer,24,Personal Travel,Eco,1096,2,5,2,3,1,2,1,1,5,4,4,3,1,1,1,0.0,neutral or dissatisfied +400,83974,Female,Loyal Customer,43,Business travel,Business,373,2,5,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +401,107761,Male,Loyal Customer,7,Personal Travel,Eco,405,3,5,3,2,4,3,4,4,3,5,4,3,5,4,3,0.0,neutral or dissatisfied +402,37834,Male,Loyal Customer,29,Business travel,Business,2542,5,5,4,5,5,5,5,5,5,2,1,3,2,5,18,55.0,satisfied +403,25904,Female,Loyal Customer,48,Business travel,Eco Plus,907,4,2,2,2,5,5,3,4,4,4,4,2,4,5,0,1.0,satisfied +404,73190,Male,disloyal Customer,25,Business travel,Eco,1258,3,3,3,3,3,2,2,1,2,3,3,2,1,2,199,185.0,neutral or dissatisfied +405,70160,Male,Loyal Customer,25,Personal Travel,Eco,550,2,2,2,3,1,2,1,1,4,2,4,4,5,1,56,63.0,neutral or dissatisfied +406,126642,Female,Loyal Customer,35,Business travel,Business,602,4,4,4,4,3,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +407,76228,Female,Loyal Customer,57,Business travel,Eco,1399,2,2,2,2,4,3,3,2,2,2,2,1,2,4,3,0.0,neutral or dissatisfied +408,18983,Male,Loyal Customer,52,Business travel,Business,3245,4,4,4,4,2,3,3,5,5,5,5,4,5,3,93,77.0,satisfied +409,42803,Female,Loyal Customer,17,Business travel,Eco,677,0,3,0,3,4,3,4,4,4,5,5,5,5,4,0,0.0,satisfied +410,65527,Female,Loyal Customer,30,Personal Travel,Eco,1616,2,4,3,1,1,3,1,1,3,2,4,4,5,1,70,89.0,neutral or dissatisfied +411,5441,Male,Loyal Customer,38,Business travel,Business,1561,3,5,3,3,2,4,4,5,5,5,5,5,5,5,0,23.0,satisfied +412,18473,Female,Loyal Customer,38,Business travel,Business,285,5,5,5,5,1,1,3,4,4,4,4,5,4,5,0,0.0,satisfied +413,98337,Female,disloyal Customer,38,Business travel,Business,1189,1,1,1,3,3,1,3,3,5,5,5,3,5,3,3,0.0,neutral or dissatisfied +414,68782,Male,disloyal Customer,23,Business travel,Eco,1021,2,2,2,3,3,2,3,3,3,5,5,5,4,3,0,0.0,satisfied +415,98247,Female,Loyal Customer,39,Business travel,Business,2442,5,4,5,5,2,4,4,4,4,4,4,4,4,4,80,86.0,satisfied +416,67119,Female,Loyal Customer,55,Business travel,Business,918,1,2,2,2,5,2,2,1,1,1,1,1,1,4,12,5.0,neutral or dissatisfied +417,91319,Female,disloyal Customer,25,Business travel,Business,545,3,5,3,1,5,3,5,5,4,4,5,3,5,5,0,2.0,neutral or dissatisfied +418,111275,Male,Loyal Customer,59,Business travel,Business,459,4,2,2,2,4,3,4,4,4,4,4,1,4,3,0,5.0,neutral or dissatisfied +419,60787,Female,Loyal Customer,9,Personal Travel,Eco Plus,804,1,5,1,3,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +420,65894,Female,disloyal Customer,26,Business travel,Business,569,0,0,0,3,3,0,1,3,4,2,4,5,4,3,96,91.0,satisfied +421,67702,Male,Loyal Customer,51,Business travel,Business,3991,5,5,5,5,3,4,5,4,4,3,4,5,4,3,0,0.0,satisfied +422,55982,Male,Loyal Customer,40,Business travel,Business,1620,2,2,2,2,4,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +423,38230,Male,Loyal Customer,56,Business travel,Business,1173,3,3,5,3,4,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +424,48253,Female,Loyal Customer,56,Personal Travel,Eco,236,3,3,3,3,5,2,5,4,4,3,4,1,4,5,57,52.0,neutral or dissatisfied +425,89431,Female,Loyal Customer,18,Personal Travel,Eco,134,2,2,2,3,3,2,4,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +426,117314,Female,Loyal Customer,8,Personal Travel,Eco Plus,647,3,2,3,3,2,3,5,2,2,4,3,3,2,2,0,0.0,neutral or dissatisfied +427,14155,Male,Loyal Customer,33,Business travel,Eco Plus,654,4,3,3,3,4,4,4,4,4,5,2,1,3,4,0,0.0,satisfied +428,123078,Male,Loyal Customer,46,Business travel,Business,2623,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +429,50137,Female,Loyal Customer,41,Business travel,Business,209,4,4,4,4,1,3,3,2,2,2,4,1,2,2,95,100.0,neutral or dissatisfied +430,41799,Female,Loyal Customer,36,Business travel,Business,257,3,3,3,3,4,4,3,4,4,4,4,1,4,1,0,0.0,satisfied +431,47037,Male,Loyal Customer,26,Business travel,Business,1629,1,1,1,1,5,5,5,5,4,4,2,3,3,5,0,0.0,satisfied +432,115397,Female,disloyal Customer,36,Business travel,Eco,371,3,2,3,3,5,3,5,5,4,4,2,4,3,5,11,6.0,neutral or dissatisfied +433,35221,Male,Loyal Customer,31,Business travel,Business,2201,5,5,5,5,2,2,2,2,5,3,3,3,1,2,0,0.0,satisfied +434,52892,Male,Loyal Customer,24,Personal Travel,Eco,836,2,4,2,1,1,2,1,1,5,4,1,1,2,1,27,54.0,neutral or dissatisfied +435,90041,Female,Loyal Customer,39,Business travel,Business,3081,5,5,5,5,2,5,4,2,2,2,2,3,2,4,7,0.0,satisfied +436,26751,Female,disloyal Customer,20,Business travel,Eco,859,3,4,4,3,4,4,4,4,3,1,3,2,3,4,3,24.0,neutral or dissatisfied +437,66071,Female,Loyal Customer,69,Personal Travel,Eco,1055,2,5,2,1,3,4,5,2,2,2,2,5,2,3,29,17.0,neutral or dissatisfied +438,33552,Female,disloyal Customer,27,Business travel,Eco,399,1,0,1,4,5,1,5,5,5,1,3,2,1,5,0,0.0,neutral or dissatisfied +439,107354,Female,Loyal Customer,10,Business travel,Eco,632,3,4,4,4,3,3,2,3,3,2,4,4,4,3,44,40.0,neutral or dissatisfied +440,83598,Male,Loyal Customer,60,Business travel,Business,3626,2,2,2,2,4,5,4,5,5,5,5,3,5,5,35,36.0,satisfied +441,117725,Male,Loyal Customer,44,Business travel,Business,833,2,2,2,2,3,5,4,4,4,4,4,3,4,4,15,1.0,satisfied +442,34210,Female,Loyal Customer,68,Personal Travel,Eco,1288,2,5,2,3,4,3,5,4,4,2,4,4,4,5,6,24.0,neutral or dissatisfied +443,129245,Male,Loyal Customer,41,Business travel,Business,2163,3,3,3,3,5,3,4,3,3,3,3,3,3,4,60,70.0,neutral or dissatisfied +444,16810,Female,Loyal Customer,46,Business travel,Eco,645,3,2,2,2,3,3,3,2,1,2,4,3,3,3,141,139.0,neutral or dissatisfied +445,88356,Male,Loyal Customer,54,Business travel,Eco,515,3,2,2,2,3,3,3,3,4,3,3,2,3,3,44,33.0,neutral or dissatisfied +446,3875,Female,Loyal Customer,44,Business travel,Business,3767,1,1,1,1,5,2,2,2,2,2,1,4,2,2,44,92.0,neutral or dissatisfied +447,4749,Male,disloyal Customer,43,Personal Travel,Eco,888,5,1,5,3,4,1,4,4,4,4,4,2,4,4,0,0.0,satisfied +448,9559,Female,disloyal Customer,44,Business travel,Business,288,5,5,5,5,4,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +449,112110,Female,disloyal Customer,26,Business travel,Business,1024,4,4,4,1,5,4,5,5,3,2,4,4,5,5,16,14.0,neutral or dissatisfied +450,114915,Male,Loyal Customer,48,Business travel,Business,3185,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +451,66011,Male,Loyal Customer,30,Business travel,Business,2974,4,4,4,4,4,4,4,4,3,3,4,3,5,4,74,67.0,satisfied +452,60450,Female,Loyal Customer,46,Business travel,Business,2981,1,1,1,1,2,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +453,129469,Male,disloyal Customer,23,Business travel,Eco,1428,2,2,2,2,2,2,2,2,4,3,5,3,4,2,0,7.0,neutral or dissatisfied +454,62153,Male,Loyal Customer,39,Business travel,Business,2454,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +455,39499,Male,Loyal Customer,24,Business travel,Business,3482,5,5,5,5,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +456,19091,Female,Loyal Customer,48,Personal Travel,Eco,296,2,5,4,3,4,4,4,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +457,48260,Male,Loyal Customer,63,Personal Travel,Eco,391,3,4,3,5,5,3,4,5,3,4,5,3,5,5,0,4.0,neutral or dissatisfied +458,96830,Male,Loyal Customer,37,Business travel,Business,3744,5,5,5,5,5,5,5,5,4,4,4,5,4,5,172,163.0,satisfied +459,126561,Male,Loyal Customer,37,Business travel,Business,1558,4,1,1,1,1,3,4,4,4,3,4,1,4,3,0,8.0,neutral or dissatisfied +460,69098,Male,Loyal Customer,57,Business travel,Business,1389,1,1,3,1,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +461,89178,Male,Loyal Customer,21,Personal Travel,Eco,1947,2,4,2,3,1,2,1,1,4,2,3,5,4,1,0,0.0,neutral or dissatisfied +462,48501,Male,Loyal Customer,9,Business travel,Eco,776,2,2,2,2,2,2,4,2,1,1,3,1,3,2,16,6.0,neutral or dissatisfied +463,109465,Female,Loyal Customer,24,Business travel,Business,3536,5,5,5,5,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +464,62274,Male,disloyal Customer,36,Business travel,Business,414,3,3,3,5,3,3,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +465,98908,Male,Loyal Customer,44,Business travel,Business,3165,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +466,17357,Female,Loyal Customer,49,Business travel,Business,1600,2,5,5,5,4,4,4,0,0,1,2,2,0,3,0,0.0,neutral or dissatisfied +467,115331,Male,Loyal Customer,42,Business travel,Business,3605,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +468,65150,Female,Loyal Customer,52,Personal Travel,Eco,247,4,4,0,2,5,4,4,5,5,0,5,3,5,3,0,0.0,satisfied +469,42257,Male,Loyal Customer,52,Business travel,Eco,550,2,4,4,4,2,2,2,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +470,116136,Male,Loyal Customer,20,Personal Travel,Eco,446,4,3,4,3,1,4,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +471,36244,Male,Loyal Customer,47,Business travel,Business,728,1,1,1,1,1,3,2,5,5,5,5,1,5,3,0,0.0,satisfied +472,109049,Male,Loyal Customer,45,Business travel,Business,3692,2,2,2,2,1,2,2,2,2,2,2,3,2,4,63,52.0,neutral or dissatisfied +473,111496,Female,Loyal Customer,44,Business travel,Business,3979,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +474,8105,Female,Loyal Customer,47,Business travel,Business,3546,2,2,2,2,4,2,2,2,2,2,2,2,2,2,19,21.0,neutral or dissatisfied +475,19478,Female,Loyal Customer,57,Business travel,Business,177,5,5,5,5,1,1,1,5,5,5,3,4,5,5,91,128.0,satisfied +476,79579,Female,Loyal Customer,34,Business travel,Business,760,4,4,4,4,4,4,4,3,3,3,3,3,3,3,6,0.0,satisfied +477,26935,Female,Loyal Customer,26,Business travel,Eco,2378,4,5,5,5,4,5,5,4,3,2,5,4,5,4,4,0.0,satisfied +478,81010,Female,Loyal Customer,45,Business travel,Business,228,0,0,0,3,3,4,5,3,3,3,3,4,3,5,0,21.0,satisfied +479,32348,Female,Loyal Customer,33,Business travel,Business,163,3,3,4,3,2,2,5,4,4,5,3,4,4,3,0,3.0,satisfied +480,122747,Male,disloyal Customer,22,Business travel,Eco,251,1,0,1,3,2,1,3,2,4,2,5,4,3,2,0,0.0,neutral or dissatisfied +481,88118,Male,Loyal Customer,51,Business travel,Business,406,5,5,5,5,5,4,5,4,4,4,4,4,4,4,9,4.0,satisfied +482,5622,Male,Loyal Customer,60,Personal Travel,Eco,624,4,3,4,1,4,4,4,1,2,5,2,4,5,4,175,180.0,satisfied +483,97335,Male,Loyal Customer,40,Business travel,Business,3764,1,1,1,1,4,5,4,4,4,5,4,4,4,3,16,3.0,satisfied +484,72995,Male,Loyal Customer,62,Business travel,Eco,696,3,3,5,3,2,3,2,2,2,5,2,3,2,2,24,1.0,neutral or dissatisfied +485,21707,Female,Loyal Customer,68,Personal Travel,Eco,746,3,5,3,2,5,5,5,2,2,3,2,4,2,3,27,37.0,neutral or dissatisfied +486,120201,Male,Loyal Customer,38,Business travel,Business,2930,2,5,5,5,2,4,4,2,2,2,2,4,2,3,7,23.0,neutral or dissatisfied +487,42929,Male,Loyal Customer,44,Business travel,Business,192,5,5,5,5,3,5,4,5,5,5,5,3,5,3,23,13.0,satisfied +488,117511,Male,Loyal Customer,11,Personal Travel,Eco,507,3,5,3,1,1,3,1,1,4,4,4,5,5,1,11,5.0,neutral or dissatisfied +489,125569,Female,Loyal Customer,33,Personal Travel,Eco,226,1,4,1,1,2,1,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +490,128566,Female,Loyal Customer,10,Personal Travel,Eco Plus,338,1,5,3,3,5,3,4,5,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +491,16040,Male,Loyal Customer,51,Business travel,Eco Plus,380,2,4,4,4,2,2,2,2,1,1,3,3,4,2,16,0.0,satisfied +492,27289,Male,Loyal Customer,34,Business travel,Business,3144,4,4,4,4,3,5,4,5,5,5,5,5,5,1,3,0.0,satisfied +493,61198,Male,Loyal Customer,69,Business travel,Business,3714,4,1,1,1,1,2,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +494,120723,Female,Loyal Customer,49,Business travel,Business,90,4,4,2,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +495,73793,Male,Loyal Customer,30,Business travel,Eco Plus,204,2,5,5,5,2,2,2,2,3,5,4,2,4,2,105,93.0,neutral or dissatisfied +496,36093,Female,Loyal Customer,40,Personal Travel,Eco,399,3,4,3,1,1,3,1,1,5,1,2,5,1,1,0,0.0,neutral or dissatisfied +497,66777,Female,Loyal Customer,29,Personal Travel,Eco Plus,802,2,3,2,4,2,2,2,2,3,2,4,4,3,2,0,0.0,neutral or dissatisfied +498,91068,Male,Loyal Customer,68,Personal Travel,Eco,406,3,3,3,2,3,3,3,3,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +499,120574,Female,Loyal Customer,53,Business travel,Eco Plus,676,2,5,5,5,5,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +500,30294,Female,Loyal Customer,24,Business travel,Business,1476,4,4,4,4,5,5,5,5,2,3,4,4,5,5,0,8.0,satisfied +501,99081,Male,Loyal Customer,43,Business travel,Business,3677,4,4,4,4,4,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +502,12094,Male,Loyal Customer,7,Personal Travel,Business,1034,2,4,2,2,2,4,4,5,5,2,3,4,2,4,143,121.0,neutral or dissatisfied +503,11849,Female,Loyal Customer,65,Personal Travel,Business,1042,4,5,4,4,3,5,4,4,4,4,2,5,4,5,48,30.0,neutral or dissatisfied +504,2671,Female,Loyal Customer,8,Personal Travel,Eco,597,4,4,4,2,2,4,2,2,5,4,5,4,4,2,0,6.0,neutral or dissatisfied +505,55140,Male,Loyal Customer,50,Personal Travel,Eco,1635,1,5,1,3,4,1,4,4,3,5,5,3,4,4,0,4.0,neutral or dissatisfied +506,75362,Male,Loyal Customer,26,Personal Travel,Eco Plus,2556,3,2,3,3,3,4,4,4,1,2,4,4,4,4,0,33.0,neutral or dissatisfied +507,5763,Female,Loyal Customer,24,Personal Travel,Eco,859,3,5,3,5,2,3,2,2,3,5,4,3,4,2,37,52.0,neutral or dissatisfied +508,12659,Female,Loyal Customer,55,Personal Travel,Eco,1236,1,4,1,3,3,3,4,5,5,1,5,5,5,5,0,9.0,neutral or dissatisfied +509,21207,Female,disloyal Customer,21,Business travel,Eco,192,3,3,3,4,1,3,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +510,45421,Female,Loyal Customer,57,Business travel,Eco,649,4,4,4,4,4,1,3,4,4,4,4,5,4,3,27,17.0,satisfied +511,51952,Male,Loyal Customer,22,Business travel,Business,936,2,5,2,2,4,4,4,4,5,1,1,4,2,4,0,7.0,satisfied +512,80873,Female,Loyal Customer,49,Personal Travel,Eco,484,3,4,3,3,3,5,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +513,119054,Female,Loyal Customer,31,Personal Travel,Eco,2279,1,5,1,2,3,1,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +514,128651,Male,disloyal Customer,21,Business travel,Eco,1444,5,4,4,1,5,1,1,4,4,5,4,1,3,1,1,2.0,satisfied +515,65790,Female,disloyal Customer,38,Business travel,Business,1389,5,5,5,1,2,5,2,2,4,5,5,3,4,2,3,0.0,satisfied +516,71834,Female,Loyal Customer,42,Business travel,Business,1846,1,2,2,2,5,2,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +517,94138,Male,Loyal Customer,55,Business travel,Business,1884,4,4,1,4,3,4,5,4,4,4,5,4,4,5,4,2.0,satisfied +518,5255,Male,disloyal Customer,26,Business travel,Business,285,1,2,1,2,3,1,3,3,4,2,3,1,2,3,0,3.0,neutral or dissatisfied +519,115771,Male,Loyal Customer,43,Business travel,Business,2256,1,1,1,1,5,4,4,1,1,1,1,1,1,2,19,6.0,neutral or dissatisfied +520,73967,Male,Loyal Customer,12,Personal Travel,Eco,2342,3,1,3,4,4,3,3,4,2,3,4,3,3,4,31,22.0,neutral or dissatisfied +521,32801,Female,Loyal Customer,32,Business travel,Eco,163,2,4,4,4,2,2,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +522,36503,Female,Loyal Customer,46,Business travel,Business,2502,2,2,2,2,3,1,3,4,4,4,4,3,4,5,5,0.0,satisfied +523,63315,Male,Loyal Customer,19,Business travel,Eco,337,4,2,2,2,4,4,3,4,4,4,3,4,3,4,12,17.0,neutral or dissatisfied +524,51581,Female,Loyal Customer,38,Business travel,Business,261,2,2,5,2,4,5,3,4,4,4,4,3,4,3,0,0.0,satisfied +525,77979,Female,Loyal Customer,52,Business travel,Business,332,3,3,3,3,4,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +526,117451,Male,disloyal Customer,47,Business travel,Eco,707,1,1,1,4,3,1,3,3,1,1,3,1,3,3,16,9.0,neutral or dissatisfied +527,58912,Male,Loyal Customer,19,Personal Travel,Eco,888,2,4,2,3,1,2,1,1,4,4,4,5,4,1,1,0.0,neutral or dissatisfied +528,11244,Female,Loyal Customer,43,Personal Travel,Eco,301,3,4,3,3,5,4,5,4,4,3,2,4,4,5,0,0.0,neutral or dissatisfied +529,122058,Female,Loyal Customer,23,Business travel,Eco,130,2,1,1,1,2,2,2,2,3,1,3,1,3,2,8,26.0,neutral or dissatisfied +530,6133,Male,Loyal Customer,45,Business travel,Business,3052,1,1,5,1,3,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +531,63668,Female,Loyal Customer,58,Personal Travel,Eco,2405,5,2,5,4,2,3,4,3,3,5,3,2,3,2,10,0.0,satisfied +532,73903,Male,disloyal Customer,25,Business travel,Eco,2585,3,3,3,4,3,3,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +533,104087,Female,Loyal Customer,68,Personal Travel,Eco,666,4,3,4,2,1,5,2,1,1,4,1,5,1,5,2,0.0,neutral or dissatisfied +534,9170,Female,Loyal Customer,64,Business travel,Business,3239,3,5,3,3,3,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +535,105685,Male,Loyal Customer,57,Business travel,Business,2718,2,2,2,2,3,5,5,5,5,5,5,4,5,4,2,0.0,satisfied +536,115282,Female,Loyal Customer,43,Business travel,Business,362,4,4,4,4,4,4,3,4,4,3,4,3,4,3,47,45.0,neutral or dissatisfied +537,16311,Male,Loyal Customer,28,Business travel,Business,3545,2,2,2,2,5,4,5,5,2,1,5,3,5,5,45,51.0,satisfied +538,77671,Male,disloyal Customer,30,Business travel,Eco,813,3,2,2,3,3,2,3,3,4,1,4,3,3,3,105,105.0,neutral or dissatisfied +539,19381,Male,Loyal Customer,23,Business travel,Business,1698,2,2,2,2,5,5,5,5,3,2,1,4,3,5,101,126.0,satisfied +540,94026,Male,disloyal Customer,37,Business travel,Business,148,4,4,4,2,4,4,3,4,3,4,5,4,5,4,1,0.0,satisfied +541,122163,Male,Loyal Customer,54,Business travel,Business,544,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +542,7179,Female,Loyal Customer,40,Business travel,Business,3011,5,5,5,5,4,5,5,5,5,4,5,5,5,4,9,56.0,satisfied +543,20625,Male,Loyal Customer,47,Business travel,Eco,783,5,2,2,2,5,5,5,5,4,1,1,4,5,5,0,0.0,satisfied +544,124273,Female,disloyal Customer,24,Business travel,Business,255,5,0,5,1,3,5,4,3,5,3,4,4,5,3,0,0.0,satisfied +545,1600,Female,Loyal Customer,25,Personal Travel,Eco,140,3,3,3,4,4,3,4,4,4,2,3,1,4,4,27,31.0,neutral or dissatisfied +546,23359,Female,Loyal Customer,40,Business travel,Eco Plus,809,4,2,4,2,4,4,4,4,4,3,2,4,4,4,118,100.0,satisfied +547,80613,Female,Loyal Customer,38,Business travel,Business,2472,5,5,3,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +548,45303,Female,Loyal Customer,45,Business travel,Eco,175,3,1,1,1,1,1,5,3,3,3,3,3,3,1,0,0.0,satisfied +549,21580,Female,Loyal Customer,29,Personal Travel,Eco Plus,331,2,5,2,2,3,2,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +550,65318,Female,Loyal Customer,42,Business travel,Business,2243,5,5,4,5,4,5,4,2,2,2,2,3,2,5,18,18.0,satisfied +551,52768,Female,disloyal Customer,42,Business travel,Eco,1874,3,3,3,3,3,3,3,3,5,3,3,2,3,3,0,5.0,neutral or dissatisfied +552,49507,Male,disloyal Customer,27,Business travel,Eco,326,3,3,3,2,5,3,5,5,1,1,1,4,5,5,5,0.0,neutral or dissatisfied +553,121964,Male,disloyal Customer,38,Business travel,Business,130,4,4,4,4,1,4,1,1,4,3,4,3,5,1,15,8.0,neutral or dissatisfied +554,63942,Female,Loyal Customer,64,Personal Travel,Eco,1158,1,4,0,1,4,5,5,4,4,0,4,4,4,3,0,0.0,neutral or dissatisfied +555,81471,Male,Loyal Customer,46,Business travel,Business,2074,4,4,4,4,3,3,2,4,4,3,4,4,4,3,27,45.0,neutral or dissatisfied +556,54997,Male,Loyal Customer,46,Business travel,Business,1635,3,3,3,3,5,3,4,2,2,2,2,3,2,5,26,27.0,satisfied +557,59017,Female,Loyal Customer,53,Business travel,Business,1744,3,3,3,3,4,3,5,2,2,2,2,4,2,4,0,4.0,satisfied +558,112287,Male,Loyal Customer,48,Personal Travel,Eco,1703,4,4,4,1,4,4,4,4,5,2,1,4,5,4,45,40.0,neutral or dissatisfied +559,97003,Female,Loyal Customer,9,Personal Travel,Eco,883,4,5,3,1,1,3,1,1,4,4,3,3,1,1,28,19.0,neutral or dissatisfied +560,102913,Male,Loyal Customer,39,Business travel,Business,1979,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +561,21546,Male,Loyal Customer,16,Personal Travel,Eco,306,2,4,2,1,5,2,5,5,3,2,5,5,4,5,76,73.0,neutral or dissatisfied +562,121044,Male,Loyal Customer,29,Personal Travel,Eco,992,2,4,2,3,5,2,5,5,4,3,5,4,4,5,0,10.0,neutral or dissatisfied +563,126814,Female,Loyal Customer,41,Business travel,Business,2077,2,2,2,2,5,3,5,5,5,5,5,3,5,3,0,0.0,satisfied +564,1936,Male,Loyal Customer,51,Business travel,Business,3304,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +565,17630,Female,Loyal Customer,42,Business travel,Business,2274,2,2,2,2,3,2,2,5,5,5,5,3,5,3,0,0.0,satisfied +566,82979,Male,Loyal Customer,51,Business travel,Business,1084,5,5,5,5,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +567,9557,Female,Loyal Customer,50,Business travel,Business,2335,5,5,5,5,4,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +568,76350,Male,Loyal Customer,48,Business travel,Business,1851,1,2,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +569,94609,Male,Loyal Customer,50,Business travel,Business,3960,4,4,4,4,3,5,4,5,5,5,4,4,5,5,0,1.0,satisfied +570,86573,Male,disloyal Customer,20,Business travel,Eco,1269,2,2,2,4,3,2,3,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +571,38421,Female,disloyal Customer,36,Business travel,Eco,965,3,3,3,3,3,3,3,3,4,3,1,5,4,3,4,11.0,neutral or dissatisfied +572,12479,Male,disloyal Customer,10,Personal Travel,Eco,192,2,5,2,2,2,2,5,2,3,2,4,5,4,2,3,4.0,neutral or dissatisfied +573,108382,Male,Loyal Customer,64,Personal Travel,Eco,1728,4,1,4,3,1,4,1,1,3,1,3,2,4,1,18,24.0,neutral or dissatisfied +574,99249,Male,Loyal Customer,58,Personal Travel,Eco,541,2,2,2,3,1,2,1,1,4,4,4,3,4,1,4,0.0,neutral or dissatisfied +575,128013,Female,Loyal Customer,55,Business travel,Business,1440,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +576,3468,Female,Loyal Customer,64,Personal Travel,Eco Plus,213,2,0,2,1,5,5,5,5,5,2,5,5,5,5,0,6.0,neutral or dissatisfied +577,71012,Male,Loyal Customer,52,Business travel,Business,3496,5,5,5,5,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +578,116293,Male,Loyal Customer,10,Personal Travel,Eco,325,3,4,3,4,1,3,1,1,3,1,4,3,2,1,13,5.0,neutral or dissatisfied +579,103164,Male,disloyal Customer,7,Business travel,Eco,491,4,2,4,4,5,4,5,5,4,2,3,3,4,5,22,11.0,neutral or dissatisfied +580,29908,Female,Loyal Customer,43,Business travel,Business,253,5,5,5,5,5,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +581,37280,Female,Loyal Customer,42,Business travel,Eco,1010,5,4,4,4,1,2,3,5,5,5,5,1,5,2,0,0.0,satisfied +582,90266,Female,Loyal Customer,16,Business travel,Business,2899,5,5,5,5,4,4,4,3,5,5,5,4,3,4,220,212.0,satisfied +583,63145,Male,Loyal Customer,51,Business travel,Business,2093,1,1,1,1,3,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +584,113897,Male,Loyal Customer,35,Business travel,Business,2295,1,5,1,5,1,1,2,1,1,1,1,1,1,2,18,14.0,neutral or dissatisfied +585,80519,Male,Loyal Customer,47,Personal Travel,Eco,1749,3,5,3,2,5,3,5,5,3,1,5,1,5,5,0,3.0,neutral or dissatisfied +586,107210,Female,disloyal Customer,35,Business travel,Business,668,2,2,2,2,5,2,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +587,48034,Female,Loyal Customer,13,Business travel,Eco Plus,1384,4,5,5,5,4,1,4,3,1,4,3,4,2,4,141,126.0,neutral or dissatisfied +588,49907,Male,Loyal Customer,24,Business travel,Eco,326,0,3,0,4,3,0,3,3,5,2,3,3,4,3,1,0.0,satisfied +589,15360,Male,Loyal Customer,34,Business travel,Business,2627,1,1,1,1,3,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +590,107856,Male,Loyal Customer,51,Business travel,Business,1644,2,2,2,2,4,5,5,5,5,5,5,4,5,5,9,0.0,satisfied +591,96716,Male,disloyal Customer,39,Business travel,Eco,813,1,1,1,4,2,1,2,2,2,3,3,3,3,2,0,0.0,neutral or dissatisfied +592,57625,Female,disloyal Customer,35,Business travel,Business,200,2,1,1,3,2,1,2,2,5,3,5,4,4,2,0,8.0,neutral or dissatisfied +593,87442,Female,Loyal Customer,48,Business travel,Business,304,2,2,4,2,4,5,4,5,5,5,5,4,5,3,33,27.0,satisfied +594,115872,Male,Loyal Customer,44,Business travel,Eco,373,5,1,1,1,5,5,5,5,2,1,2,5,5,5,0,0.0,satisfied +595,37667,Female,Loyal Customer,66,Personal Travel,Eco,1097,4,3,4,3,4,4,5,3,3,4,3,5,3,2,0,0.0,neutral or dissatisfied +596,102881,Male,Loyal Customer,26,Personal Travel,Eco,472,3,5,3,4,3,3,3,3,4,1,3,5,3,3,18,18.0,neutral or dissatisfied +597,107099,Female,Loyal Customer,65,Personal Travel,Eco,745,3,5,4,4,1,2,5,3,3,4,1,4,3,5,0,0.0,neutral or dissatisfied +598,55791,Female,disloyal Customer,20,Business travel,Eco,1394,2,1,1,4,2,4,4,3,5,2,4,4,2,4,0,3.0,neutral or dissatisfied +599,4388,Male,Loyal Customer,30,Personal Travel,Eco,607,3,5,3,1,3,3,3,3,3,4,4,3,5,3,55,88.0,neutral or dissatisfied +600,44731,Male,Loyal Customer,40,Business travel,Eco Plus,67,4,4,5,5,4,4,4,4,2,1,1,4,4,4,0,4.0,satisfied +601,102620,Male,Loyal Customer,45,Personal Travel,Eco,1294,3,5,3,5,2,3,2,2,3,3,4,3,4,2,11,4.0,neutral or dissatisfied +602,53749,Male,Loyal Customer,58,Personal Travel,Eco Plus,1208,3,3,4,4,2,4,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +603,126263,Male,disloyal Customer,37,Business travel,Eco,107,2,2,2,3,2,1,4,3,3,3,4,4,2,4,232,241.0,neutral or dissatisfied +604,18176,Female,disloyal Customer,37,Business travel,Business,235,4,4,4,3,4,4,4,4,5,3,5,4,4,4,0,30.0,neutral or dissatisfied +605,121318,Male,Loyal Customer,25,Personal Travel,Eco,1009,0,5,0,4,5,0,5,5,5,3,5,3,4,5,0,0.0,satisfied +606,120225,Female,disloyal Customer,26,Business travel,Eco,1303,2,2,2,4,3,2,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +607,60742,Female,Loyal Customer,27,Business travel,Business,628,2,2,2,2,4,4,4,4,5,3,4,5,5,4,46,51.0,satisfied +608,82016,Male,Loyal Customer,52,Personal Travel,Eco,1517,4,5,4,4,3,4,3,3,4,2,5,5,4,3,0,0.0,satisfied +609,58490,Male,Loyal Customer,26,Business travel,Business,2836,5,5,5,5,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +610,100263,Male,Loyal Customer,58,Business travel,Business,1034,4,4,4,4,5,5,5,3,5,4,5,5,3,5,170,172.0,satisfied +611,57121,Male,Loyal Customer,50,Business travel,Business,2350,3,1,1,1,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +612,15260,Female,disloyal Customer,11,Business travel,Eco,529,4,3,4,4,4,4,4,4,4,5,4,4,4,4,15,15.0,neutral or dissatisfied +613,97911,Male,disloyal Customer,25,Business travel,Business,483,0,4,0,4,5,0,5,5,4,4,5,5,5,5,0,0.0,satisfied +614,115837,Male,disloyal Customer,22,Business travel,Eco,480,3,0,3,2,3,3,3,3,1,3,4,1,5,3,17,4.0,neutral or dissatisfied +615,28457,Male,Loyal Customer,43,Personal Travel,Eco,2588,0,5,0,1,0,5,5,3,4,5,5,5,5,5,0,0.0,satisfied +616,104313,Female,Loyal Customer,41,Business travel,Business,3396,3,3,2,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +617,39072,Female,disloyal Customer,40,Business travel,Business,384,3,3,3,4,2,3,2,2,1,1,4,3,4,2,0,6.0,neutral or dissatisfied +618,128176,Female,Loyal Customer,20,Business travel,Business,1788,1,2,5,2,1,2,1,1,2,2,3,4,4,1,25,12.0,neutral or dissatisfied +619,112243,Male,Loyal Customer,43,Business travel,Business,1506,3,2,3,3,5,5,5,4,2,5,4,5,5,5,173,175.0,satisfied +620,24065,Female,Loyal Customer,50,Business travel,Eco Plus,427,4,5,5,5,5,4,1,4,4,4,4,4,4,1,38,23.0,satisfied +621,12170,Female,disloyal Customer,24,Business travel,Eco,1042,3,3,3,4,1,3,1,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +622,5803,Male,disloyal Customer,32,Business travel,Business,157,3,3,3,3,2,3,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +623,17005,Male,Loyal Customer,47,Business travel,Business,3349,3,3,5,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +624,9072,Female,disloyal Customer,28,Business travel,Eco,160,4,2,4,4,1,4,1,1,2,4,3,1,4,1,52,44.0,neutral or dissatisfied +625,56156,Female,Loyal Customer,23,Business travel,Business,1400,1,1,1,1,4,4,4,4,3,4,5,3,5,4,0,6.0,satisfied +626,49879,Male,Loyal Customer,38,Business travel,Business,2027,3,3,3,3,5,1,1,4,4,4,4,2,4,1,124,111.0,satisfied +627,78234,Male,Loyal Customer,53,Business travel,Business,1741,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +628,23979,Male,Loyal Customer,52,Business travel,Business,3092,1,1,1,1,2,4,5,4,4,4,4,5,4,3,7,16.0,satisfied +629,113199,Female,disloyal Customer,20,Business travel,Business,386,5,0,5,3,4,5,2,4,3,5,5,3,5,4,0,0.0,satisfied +630,73887,Female,Loyal Customer,43,Business travel,Business,2585,1,1,1,1,5,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +631,68000,Female,Loyal Customer,40,Business travel,Business,304,0,0,0,3,3,5,5,1,1,1,1,4,1,4,0,0.0,satisfied +632,69413,Male,Loyal Customer,43,Business travel,Business,2835,4,3,4,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +633,26761,Male,Loyal Customer,34,Personal Travel,Eco,859,3,5,4,2,4,4,4,4,5,3,4,5,4,4,0,88.0,neutral or dissatisfied +634,64701,Female,Loyal Customer,37,Business travel,Business,3969,1,3,3,3,5,3,3,4,4,4,1,3,4,3,27,61.0,neutral or dissatisfied +635,36377,Female,Loyal Customer,61,Business travel,Business,2402,4,4,4,4,4,4,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +636,25233,Female,Loyal Customer,29,Personal Travel,Eco,925,0,5,0,2,1,0,1,1,5,1,3,5,1,1,0,3.0,satisfied +637,36416,Female,disloyal Customer,41,Business travel,Business,369,4,4,4,3,3,4,3,3,2,5,5,5,1,3,0,0.0,satisfied +638,71469,Female,Loyal Customer,28,Personal Travel,Eco Plus,867,4,4,4,4,5,4,5,5,4,3,5,4,4,5,30,13.0,neutral or dissatisfied +639,26626,Female,Loyal Customer,58,Business travel,Eco,515,2,3,3,3,1,2,3,2,2,2,2,2,2,2,5,27.0,neutral or dissatisfied +640,72406,Male,Loyal Customer,50,Business travel,Eco,964,1,1,1,1,1,1,1,1,4,2,4,2,4,1,93,99.0,neutral or dissatisfied +641,79582,Male,Loyal Customer,46,Business travel,Business,762,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +642,55969,Female,Loyal Customer,28,Business travel,Business,1620,3,3,3,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +643,85246,Male,Loyal Customer,61,Personal Travel,Eco,731,5,5,5,2,1,5,1,1,1,2,5,3,5,1,0,0.0,satisfied +644,75174,Female,Loyal Customer,27,Business travel,Eco,1744,3,1,1,1,3,3,3,3,2,2,2,3,3,3,0,0.0,neutral or dissatisfied +645,50505,Female,Loyal Customer,43,Personal Travel,Eco,109,4,3,4,3,2,4,3,3,3,4,5,4,3,2,0,0.0,neutral or dissatisfied +646,57856,Male,Loyal Customer,34,Personal Travel,Eco,2457,2,4,2,4,2,1,2,4,2,4,4,2,5,2,0,0.0,neutral or dissatisfied +647,75346,Male,Loyal Customer,56,Personal Travel,Eco,2615,2,4,2,4,2,3,5,3,3,4,5,5,4,5,0,1.0,neutral or dissatisfied +648,23259,Male,Loyal Customer,69,Personal Travel,Eco,783,3,5,3,4,2,3,2,2,5,3,5,5,4,2,112,111.0,neutral or dissatisfied +649,46011,Male,Loyal Customer,62,Personal Travel,Eco Plus,483,2,0,2,4,1,2,5,1,5,4,5,3,5,1,12,25.0,neutral or dissatisfied +650,53413,Male,Loyal Customer,30,Business travel,Business,2253,5,5,5,5,5,5,5,5,1,3,3,4,1,5,40,42.0,satisfied +651,123560,Male,disloyal Customer,25,Business travel,Eco,1264,5,5,5,3,2,5,2,2,4,3,3,4,4,2,3,0.0,satisfied +652,128777,Male,Loyal Customer,53,Business travel,Business,2248,3,3,3,3,2,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +653,114619,Male,Loyal Customer,46,Business travel,Business,480,2,2,2,2,2,5,4,4,4,4,4,4,4,3,94,76.0,satisfied +654,217,Male,Loyal Customer,48,Personal Travel,Eco,290,2,5,2,1,5,2,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +655,4110,Female,Loyal Customer,46,Business travel,Business,544,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,6.0,satisfied +656,78446,Female,disloyal Customer,40,Business travel,Business,666,4,4,4,4,2,4,2,2,5,3,4,5,4,2,0,0.0,satisfied +657,7017,Male,Loyal Customer,39,Personal Travel,Eco,299,2,4,2,4,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +658,16254,Male,disloyal Customer,22,Business travel,Eco,748,4,4,4,3,3,4,3,3,2,5,3,4,1,3,0,0.0,satisfied +659,45852,Female,Loyal Customer,35,Business travel,Eco Plus,391,5,1,1,1,5,4,5,5,1,1,3,4,3,5,0,0.0,satisfied +660,64004,Female,Loyal Customer,29,Personal Travel,Eco,612,2,4,2,2,4,2,4,4,1,3,5,3,5,4,0,5.0,neutral or dissatisfied +661,78310,Female,Loyal Customer,33,Business travel,Eco Plus,1598,1,5,4,4,1,2,1,1,3,1,3,3,4,1,0,0.0,neutral or dissatisfied +662,127082,Male,disloyal Customer,26,Business travel,Eco,304,2,0,2,4,4,2,2,4,4,3,5,4,1,4,0,6.0,neutral or dissatisfied +663,47006,Female,Loyal Customer,27,Personal Travel,Eco Plus,776,2,1,2,2,4,2,4,4,4,3,2,1,2,4,6,10.0,neutral or dissatisfied +664,43972,Female,disloyal Customer,24,Business travel,Business,411,5,3,5,3,2,5,2,2,5,5,5,4,4,2,0,0.0,satisfied +665,119682,Female,Loyal Customer,16,Personal Travel,Business,1325,5,4,5,3,5,4,4,5,5,4,5,4,4,4,243,226.0,satisfied +666,3616,Male,Loyal Customer,47,Business travel,Business,427,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +667,40304,Female,Loyal Customer,45,Personal Travel,Eco,531,1,3,1,3,3,4,2,2,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +668,120760,Female,Loyal Customer,39,Business travel,Business,1582,3,3,2,3,2,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +669,8115,Male,Loyal Customer,35,Business travel,Business,2392,2,3,5,3,5,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +670,36058,Female,Loyal Customer,23,Business travel,Eco,399,4,2,2,2,4,4,1,4,2,3,1,1,2,4,0,0.0,neutral or dissatisfied +671,58068,Male,Loyal Customer,35,Business travel,Business,589,2,4,1,4,2,3,4,2,2,2,2,1,2,3,44,46.0,neutral or dissatisfied +672,125757,Male,Loyal Customer,50,Business travel,Business,993,2,2,2,2,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +673,94659,Female,Loyal Customer,40,Business travel,Eco,192,2,5,5,5,2,2,2,2,4,2,4,4,4,2,7,0.0,neutral or dissatisfied +674,97953,Male,Loyal Customer,45,Business travel,Business,483,4,4,4,4,4,1,2,4,4,4,4,2,4,2,128,131.0,neutral or dissatisfied +675,78114,Female,Loyal Customer,60,Business travel,Business,1797,4,4,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +676,77532,Male,Loyal Customer,11,Personal Travel,Eco,1310,3,4,4,3,5,4,3,5,4,3,4,3,5,5,24,12.0,neutral or dissatisfied +677,80601,Male,disloyal Customer,38,Business travel,Business,762,4,3,3,2,4,3,4,4,5,2,5,5,4,4,0,4.0,satisfied +678,62020,Female,disloyal Customer,26,Business travel,Business,2475,3,3,3,1,4,3,1,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +679,99600,Female,Loyal Customer,17,Personal Travel,Eco,808,3,5,3,5,5,3,5,5,2,4,4,1,4,5,0,0.0,neutral or dissatisfied +680,62446,Male,Loyal Customer,40,Business travel,Business,1723,3,3,3,3,5,4,4,5,5,5,5,3,5,3,2,0.0,satisfied +681,29914,Female,Loyal Customer,60,Business travel,Eco,123,5,1,1,1,5,2,2,5,5,5,5,1,5,4,0,0.0,satisfied +682,96450,Female,Loyal Customer,43,Business travel,Business,2825,1,1,1,1,3,4,5,5,5,5,5,5,5,3,16,10.0,satisfied +683,107479,Male,Loyal Customer,50,Business travel,Business,3610,4,4,4,4,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +684,115588,Male,Loyal Customer,46,Business travel,Eco,337,2,3,3,3,2,2,2,2,1,2,4,1,3,2,0,6.0,neutral or dissatisfied +685,112892,Male,Loyal Customer,29,Business travel,Business,1642,1,5,5,5,1,1,1,1,2,1,3,1,3,1,24,14.0,neutral or dissatisfied +686,96804,Male,disloyal Customer,23,Business travel,Business,1041,4,4,4,1,2,4,2,2,4,5,5,4,5,2,15,1.0,satisfied +687,98887,Male,Loyal Customer,17,Personal Travel,Eco,991,2,3,3,4,5,3,5,5,3,5,3,2,3,5,0,0.0,neutral or dissatisfied +688,58394,Male,disloyal Customer,65,Business travel,Business,473,5,5,5,3,1,5,1,1,4,5,4,5,4,1,11,33.0,satisfied +689,17658,Male,disloyal Customer,47,Business travel,Eco,608,4,1,3,3,1,3,4,1,4,1,3,2,3,1,83,45.0,neutral or dissatisfied +690,51563,Male,Loyal Customer,34,Business travel,Eco,455,4,1,1,1,4,4,4,4,3,3,1,2,3,4,0,0.0,satisfied +691,114287,Male,Loyal Customer,64,Personal Travel,Eco,862,3,5,2,3,4,2,4,4,3,5,5,4,5,4,25,21.0,neutral or dissatisfied +692,95974,Male,Loyal Customer,42,Business travel,Business,3381,2,3,2,2,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +693,35423,Male,Loyal Customer,53,Personal Travel,Eco,972,3,4,3,2,2,3,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +694,98723,Male,Loyal Customer,38,Personal Travel,Eco Plus,834,4,4,3,3,4,3,4,4,5,1,3,2,1,4,92,100.0,neutral or dissatisfied +695,117443,Female,disloyal Customer,8,Business travel,Eco,1107,4,4,4,3,5,4,5,5,3,3,4,3,5,5,18,5.0,neutral or dissatisfied +696,47902,Male,Loyal Customer,31,Business travel,Business,3561,1,1,5,1,5,5,5,5,3,3,3,1,3,5,0,4.0,satisfied +697,84336,Male,Loyal Customer,41,Business travel,Eco,606,1,4,4,4,1,1,1,1,1,4,4,2,4,1,18,2.0,neutral or dissatisfied +698,35611,Male,Loyal Customer,32,Personal Travel,Eco Plus,1069,1,5,1,1,2,1,5,2,3,2,4,3,4,2,49,31.0,neutral or dissatisfied +699,787,Female,Loyal Customer,56,Business travel,Business,1707,4,4,4,4,3,4,5,4,4,5,4,3,4,4,7,15.0,satisfied +700,6164,Male,disloyal Customer,19,Business travel,Eco,501,3,3,3,4,3,3,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +701,111698,Male,disloyal Customer,25,Business travel,Business,541,2,5,1,3,4,1,3,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +702,51329,Female,disloyal Customer,39,Business travel,Business,421,1,1,1,1,4,1,4,4,1,4,4,4,5,4,0,0.0,neutral or dissatisfied +703,97195,Male,Loyal Customer,9,Personal Travel,Eco,1390,2,3,2,3,2,2,2,3,3,4,4,2,3,2,270,260.0,neutral or dissatisfied +704,51306,Female,Loyal Customer,39,Business travel,Eco Plus,266,2,1,4,1,2,2,2,2,1,3,3,4,3,2,49,56.0,neutral or dissatisfied +705,60876,Female,Loyal Customer,21,Business travel,Business,1062,3,3,3,3,4,5,4,4,3,2,4,4,4,4,17,32.0,satisfied +706,98658,Male,Loyal Customer,20,Personal Travel,Eco,992,3,4,3,3,3,3,3,3,4,5,4,4,4,3,0,7.0,neutral or dissatisfied +707,79373,Male,Loyal Customer,55,Business travel,Business,502,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,6.0,satisfied +708,41573,Female,disloyal Customer,69,Personal Travel,Eco,1334,5,4,5,3,4,5,4,4,5,4,4,3,4,4,4,0.0,satisfied +709,17698,Female,Loyal Customer,25,Business travel,Business,854,2,2,2,2,5,4,5,5,2,5,2,1,3,5,9,0.0,satisfied +710,9064,Male,Loyal Customer,69,Business travel,Business,173,1,3,3,3,1,2,2,3,3,3,1,4,3,1,0,0.0,neutral or dissatisfied +711,109937,Female,Loyal Customer,67,Personal Travel,Eco,1033,3,5,3,4,2,4,5,2,2,3,5,3,2,5,37,22.0,neutral or dissatisfied +712,91986,Male,Loyal Customer,33,Business travel,Business,236,1,3,3,3,1,1,1,1,4,1,4,1,4,1,2,0.0,neutral or dissatisfied +713,85593,Male,Loyal Customer,39,Business travel,Business,1685,0,0,0,1,2,2,5,3,3,3,3,1,3,4,0,5.0,satisfied +714,127131,Female,Loyal Customer,17,Personal Travel,Eco,647,2,2,2,4,2,2,2,2,2,1,3,4,4,2,6,0.0,neutral or dissatisfied +715,72336,Female,Loyal Customer,39,Business travel,Business,2088,2,2,2,2,5,5,5,4,4,4,4,5,4,5,10,0.0,satisfied +716,92079,Female,disloyal Customer,25,Business travel,Eco,1576,3,3,3,3,1,3,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +717,129624,Male,Loyal Customer,32,Business travel,Business,3802,0,0,0,1,5,5,5,5,3,2,5,4,5,5,90,86.0,satisfied +718,33264,Female,Loyal Customer,23,Personal Travel,Eco Plus,101,4,4,4,4,5,4,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +719,7809,Female,Loyal Customer,46,Business travel,Eco,650,1,5,5,5,2,4,3,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +720,15204,Female,Loyal Customer,50,Business travel,Business,416,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +721,91327,Female,Loyal Customer,43,Business travel,Eco Plus,223,2,1,1,1,4,1,1,2,2,2,2,3,2,1,28,20.0,neutral or dissatisfied +722,35098,Male,Loyal Customer,35,Business travel,Eco,1005,4,1,2,2,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +723,109569,Male,Loyal Customer,62,Personal Travel,Eco,834,4,3,4,3,2,4,3,2,2,4,3,4,3,2,110,92.0,neutral or dissatisfied +724,1016,Female,disloyal Customer,47,Business travel,Eco,247,1,1,1,1,4,1,4,4,4,2,2,2,2,4,0,6.0,neutral or dissatisfied +725,101713,Female,disloyal Customer,13,Business travel,Eco,986,2,1,1,3,1,1,1,1,3,3,4,3,4,1,2,26.0,neutral or dissatisfied +726,61813,Female,Loyal Customer,68,Personal Travel,Eco,1635,1,5,1,1,3,4,5,2,2,1,5,3,2,3,0,0.0,neutral or dissatisfied +727,119989,Female,disloyal Customer,29,Business travel,Eco Plus,868,2,2,2,4,3,2,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +728,51604,Male,Loyal Customer,57,Business travel,Business,370,3,3,3,3,3,4,4,5,5,5,5,3,5,2,0,0.0,satisfied +729,109352,Female,Loyal Customer,32,Personal Travel,Business,1237,3,5,3,1,4,3,5,4,4,3,3,4,4,4,8,1.0,neutral or dissatisfied +730,128573,Male,Loyal Customer,55,Business travel,Eco Plus,110,3,1,1,1,3,3,3,3,2,3,4,2,3,3,0,0.0,neutral or dissatisfied +731,79499,Female,Loyal Customer,31,Business travel,Business,749,1,1,5,1,5,5,5,5,4,5,4,5,4,5,11,11.0,satisfied +732,99632,Male,Loyal Customer,7,Personal Travel,Eco,1154,3,4,3,2,3,3,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +733,22493,Female,Loyal Customer,59,Personal Travel,Eco,145,1,3,1,4,5,4,3,5,5,1,5,1,5,2,0,0.0,neutral or dissatisfied +734,88713,Male,Loyal Customer,62,Personal Travel,Eco,581,2,4,2,1,2,2,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +735,36663,Male,Loyal Customer,33,Personal Travel,Eco,1197,3,4,3,5,4,3,3,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +736,54626,Female,Loyal Customer,30,Business travel,Business,2450,3,3,3,3,2,2,2,2,3,3,3,2,3,2,2,0.0,satisfied +737,68235,Female,Loyal Customer,30,Business travel,Business,1966,3,4,4,4,3,3,3,3,4,1,3,4,3,3,0,5.0,neutral or dissatisfied +738,40073,Male,Loyal Customer,41,Business travel,Eco,493,3,3,3,3,3,3,3,3,3,4,4,4,2,3,0,0.0,satisfied +739,52290,Male,Loyal Customer,60,Business travel,Business,3664,1,3,3,3,1,3,3,1,1,1,1,4,1,3,0,3.0,neutral or dissatisfied +740,22475,Female,Loyal Customer,60,Personal Travel,Eco,214,3,2,0,4,1,4,4,1,1,0,1,1,1,3,0,0.0,neutral or dissatisfied +741,61452,Male,disloyal Customer,15,Business travel,Business,1039,0,0,0,3,5,0,5,5,4,5,4,4,4,5,4,0.0,satisfied +742,53871,Female,disloyal Customer,36,Business travel,Eco,140,1,0,1,2,2,1,2,2,5,4,3,2,4,2,2,9.0,neutral or dissatisfied +743,93869,Male,Loyal Customer,50,Business travel,Business,1937,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +744,31387,Male,disloyal Customer,22,Business travel,Eco,434,3,1,3,2,1,3,1,1,4,3,1,3,2,1,5,6.0,neutral or dissatisfied +745,8229,Male,Loyal Customer,39,Personal Travel,Eco,294,1,5,1,3,1,1,1,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +746,43957,Male,Loyal Customer,24,Personal Travel,Eco,473,3,1,3,3,1,3,1,1,3,5,4,2,3,1,0,26.0,neutral or dissatisfied +747,81025,Female,Loyal Customer,51,Business travel,Business,2818,5,5,5,5,2,5,5,4,4,4,4,3,4,5,6,0.0,satisfied +748,10342,Male,Loyal Customer,49,Business travel,Business,74,1,1,1,1,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +749,119130,Female,Loyal Customer,56,Business travel,Business,3538,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +750,49877,Male,Loyal Customer,57,Business travel,Eco,308,2,3,3,3,2,2,2,2,1,1,3,2,2,2,0,0.0,neutral or dissatisfied +751,49324,Male,Loyal Customer,57,Business travel,Eco,308,3,1,1,1,3,3,3,3,1,4,3,2,4,3,0,0.0,satisfied +752,60275,Female,Loyal Customer,50,Business travel,Business,2583,4,4,4,4,5,4,4,5,2,3,4,4,3,4,6,0.0,satisfied +753,52082,Female,Loyal Customer,53,Business travel,Business,1621,4,3,3,3,1,3,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +754,107758,Female,Loyal Customer,53,Personal Travel,Eco,251,2,5,0,3,3,5,5,5,5,0,5,4,5,3,5,0.0,neutral or dissatisfied +755,71587,Female,Loyal Customer,41,Business travel,Business,3247,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +756,73094,Male,Loyal Customer,42,Business travel,Eco Plus,685,4,2,2,2,4,4,4,4,1,4,1,2,5,4,0,0.0,satisfied +757,95553,Male,Loyal Customer,62,Personal Travel,Eco Plus,148,4,5,4,3,4,4,4,4,3,3,4,3,5,4,31,27.0,neutral or dissatisfied +758,104483,Female,Loyal Customer,50,Business travel,Business,860,2,5,5,5,5,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +759,104897,Female,Loyal Customer,54,Business travel,Business,1565,3,3,3,3,3,5,5,5,5,5,5,5,5,4,4,19.0,satisfied +760,53833,Male,Loyal Customer,49,Business travel,Eco,224,4,2,2,2,5,4,5,5,4,5,1,1,2,5,3,0.0,satisfied +761,13037,Female,Loyal Customer,60,Personal Travel,Eco,438,3,4,3,3,5,4,4,4,4,3,4,3,4,5,1,0.0,neutral or dissatisfied +762,54986,Female,Loyal Customer,59,Business travel,Business,1379,3,5,5,5,2,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +763,23505,Female,disloyal Customer,24,Business travel,Eco,303,0,4,0,2,3,0,3,3,2,2,2,4,4,3,0,0.0,satisfied +764,44741,Male,Loyal Customer,60,Personal Travel,Eco Plus,67,1,5,1,3,5,1,5,5,5,3,4,5,5,5,25,16.0,neutral or dissatisfied +765,112372,Male,disloyal Customer,23,Business travel,Eco,862,3,4,4,3,4,4,4,4,1,5,3,3,3,4,1,33.0,neutral or dissatisfied +766,113838,Male,Loyal Customer,37,Personal Travel,Eco Plus,223,3,5,0,2,4,0,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +767,113052,Male,Loyal Customer,49,Business travel,Business,569,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +768,62069,Male,Loyal Customer,62,Personal Travel,Eco,2475,3,2,2,3,1,2,1,1,3,2,3,3,2,1,0,0.0,neutral or dissatisfied +769,123872,Male,Loyal Customer,56,Business travel,Business,1835,2,3,3,3,2,3,2,2,2,2,2,2,2,1,0,33.0,neutral or dissatisfied +770,118170,Female,disloyal Customer,25,Business travel,Eco,1444,3,3,3,3,4,3,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +771,71934,Female,Loyal Customer,49,Business travel,Eco Plus,346,2,3,3,3,2,2,5,2,2,2,2,3,2,2,9,0.0,satisfied +772,112283,Male,Loyal Customer,32,Personal Travel,Eco,1546,2,5,2,2,3,2,3,3,4,2,5,4,5,3,20,5.0,neutral or dissatisfied +773,31461,Male,Loyal Customer,25,Business travel,Eco,846,4,4,4,4,4,4,3,4,5,4,3,2,1,4,10,0.0,satisfied +774,111274,Male,Loyal Customer,55,Business travel,Eco,459,3,4,4,4,3,3,3,3,4,1,2,4,2,3,50,69.0,neutral or dissatisfied +775,90137,Female,Loyal Customer,50,Business travel,Business,2731,4,4,4,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +776,5487,Male,Loyal Customer,39,Business travel,Business,2040,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +777,110992,Female,Loyal Customer,42,Business travel,Business,1971,4,4,4,4,4,4,5,5,5,5,4,3,5,5,0,5.0,satisfied +778,50393,Male,Loyal Customer,52,Business travel,Business,3807,1,3,3,3,1,4,3,3,3,3,1,2,3,3,0,0.0,neutral or dissatisfied +779,80171,Female,Loyal Customer,57,Business travel,Business,2446,2,3,3,3,2,2,2,1,4,3,4,2,2,2,54,49.0,neutral or dissatisfied +780,56924,Female,disloyal Customer,34,Business travel,Eco,1142,2,2,2,4,2,2,4,1,4,3,3,4,4,4,4,26.0,neutral or dissatisfied +781,107024,Male,disloyal Customer,22,Business travel,Business,395,5,3,5,3,5,5,5,5,5,2,4,4,4,5,8,0.0,satisfied +782,52497,Female,Loyal Customer,42,Business travel,Business,160,2,2,5,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +783,40922,Female,Loyal Customer,61,Personal Travel,Eco,588,1,2,1,3,1,3,3,5,5,1,2,3,5,1,0,0.0,neutral or dissatisfied +784,35817,Female,Loyal Customer,40,Business travel,Business,937,2,2,2,2,4,3,2,2,2,2,2,3,2,3,0,0.0,satisfied +785,24382,Female,Loyal Customer,55,Business travel,Business,3275,2,1,3,1,3,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +786,30503,Male,Loyal Customer,66,Personal Travel,Eco,484,3,2,4,4,2,4,2,2,3,3,2,2,3,2,2,0.0,neutral or dissatisfied +787,125286,Male,disloyal Customer,26,Business travel,Business,678,1,1,1,1,4,1,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +788,40195,Female,disloyal Customer,43,Business travel,Eco,358,2,5,1,1,5,1,5,5,1,4,2,4,5,5,0,45.0,neutral or dissatisfied +789,29132,Female,Loyal Customer,24,Personal Travel,Eco,605,2,4,2,4,2,2,5,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +790,73526,Male,Loyal Customer,60,Business travel,Business,594,4,4,4,4,3,4,4,5,5,5,5,3,5,4,7,27.0,satisfied +791,27085,Female,disloyal Customer,17,Business travel,Eco,876,2,2,2,4,2,2,2,2,3,1,3,4,4,2,2,0.0,neutral or dissatisfied +792,38072,Female,disloyal Customer,22,Business travel,Eco,1249,2,2,2,4,2,2,2,4,1,1,3,2,3,2,144,142.0,neutral or dissatisfied +793,125941,Female,Loyal Customer,27,Personal Travel,Eco,992,3,4,3,4,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +794,6274,Female,Loyal Customer,43,Business travel,Business,3967,3,4,4,4,1,4,3,3,3,3,3,4,3,4,0,2.0,neutral or dissatisfied +795,15661,Male,Loyal Customer,46,Business travel,Eco,764,5,4,4,4,5,5,5,5,4,1,4,4,2,5,39,58.0,satisfied +796,47330,Male,Loyal Customer,40,Business travel,Eco,588,5,1,1,1,5,5,5,5,1,4,3,3,5,5,0,0.0,satisfied +797,76908,Male,Loyal Customer,68,Personal Travel,Eco,630,2,4,2,2,1,2,1,1,3,1,1,1,1,1,4,1.0,neutral or dissatisfied +798,20699,Female,Loyal Customer,42,Business travel,Eco,510,2,1,1,1,1,3,4,2,2,2,2,4,2,4,112,100.0,neutral or dissatisfied +799,105516,Female,Loyal Customer,44,Business travel,Business,3954,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +800,15954,Male,Loyal Customer,44,Personal Travel,Eco,528,1,3,1,5,1,1,1,1,2,1,5,5,3,1,20,8.0,neutral or dissatisfied +801,90062,Male,Loyal Customer,29,Business travel,Business,1963,5,5,5,5,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +802,75964,Male,Loyal Customer,50,Business travel,Business,3548,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +803,49278,Female,disloyal Customer,37,Business travel,Eco,308,2,0,2,1,5,2,5,5,2,2,3,1,5,5,0,3.0,neutral or dissatisfied +804,77611,Male,disloyal Customer,33,Business travel,Business,731,2,1,1,4,3,1,2,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +805,15635,Female,Loyal Customer,58,Business travel,Eco Plus,229,4,5,5,5,4,4,1,4,4,4,4,1,4,4,63,75.0,satisfied +806,39624,Female,Loyal Customer,26,Personal Travel,Eco,908,3,4,3,4,2,3,2,2,2,3,5,1,1,2,0,0.0,neutral or dissatisfied +807,88385,Male,Loyal Customer,49,Business travel,Business,2537,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +808,23805,Female,Loyal Customer,22,Business travel,Eco,304,5,1,1,1,5,5,5,5,5,5,4,2,1,5,0,0.0,satisfied +809,94249,Male,Loyal Customer,50,Business travel,Business,189,0,5,0,1,5,5,4,3,3,3,3,4,3,5,56,61.0,satisfied +810,129860,Male,disloyal Customer,22,Business travel,Business,447,0,1,0,2,2,0,2,2,3,2,4,3,4,2,0,0.0,satisfied +811,49027,Female,Loyal Customer,41,Business travel,Eco,373,5,2,2,2,5,5,5,5,2,5,4,3,2,5,0,0.0,satisfied +812,117434,Female,Loyal Customer,11,Personal Travel,Business,1020,2,2,2,3,2,2,1,2,1,1,4,3,4,2,2,0.0,neutral or dissatisfied +813,36119,Female,Loyal Customer,59,Business travel,Eco,1562,5,1,1,1,1,4,1,5,5,5,5,1,5,4,35,27.0,satisfied +814,108847,Female,Loyal Customer,41,Business travel,Business,2139,3,3,3,3,2,5,5,4,4,5,4,5,4,4,19,23.0,satisfied +815,6188,Female,Loyal Customer,56,Personal Travel,Eco,409,3,5,5,5,4,5,4,4,4,5,4,5,4,5,36,38.0,neutral or dissatisfied +816,112196,Female,Loyal Customer,31,Business travel,Business,2918,4,4,4,4,5,4,5,5,5,2,5,3,5,5,12,6.0,satisfied +817,128755,Male,Loyal Customer,27,Business travel,Business,3657,3,3,4,3,5,5,5,5,4,3,4,4,5,5,31,33.0,satisfied +818,20202,Female,disloyal Customer,56,Business travel,Business,179,4,4,4,4,4,4,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +819,94882,Female,Loyal Customer,38,Business travel,Business,2318,1,0,0,3,5,3,3,2,2,0,1,4,2,3,0,0.0,neutral or dissatisfied +820,105189,Male,Loyal Customer,56,Personal Travel,Eco,220,3,3,3,1,2,3,2,2,1,3,5,3,3,2,29,22.0,neutral or dissatisfied +821,3683,Female,Loyal Customer,56,Business travel,Business,431,3,4,4,4,4,2,3,3,3,3,3,4,3,2,0,5.0,neutral or dissatisfied +822,59771,Male,disloyal Customer,25,Business travel,Eco,495,4,5,4,4,3,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +823,94669,Female,Loyal Customer,47,Business travel,Business,528,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +824,110029,Male,Loyal Customer,72,Business travel,Eco Plus,1204,2,4,4,4,2,2,2,2,2,1,3,1,3,2,55,34.0,neutral or dissatisfied +825,101614,Male,Loyal Customer,43,Business travel,Business,1371,4,4,4,4,3,4,4,3,3,4,3,5,3,5,4,3.0,satisfied +826,91499,Male,Loyal Customer,27,Personal Travel,Eco,391,2,5,2,5,1,2,1,1,3,4,5,4,5,1,1,0.0,neutral or dissatisfied +827,49265,Male,Loyal Customer,39,Business travel,Business,1724,0,3,0,1,1,2,3,4,4,4,4,3,4,4,0,0.0,satisfied +828,26940,Female,Loyal Customer,11,Personal Travel,Eco,2378,2,4,2,1,3,2,3,3,4,2,4,5,1,3,0,0.0,neutral or dissatisfied +829,70422,Male,disloyal Customer,21,Business travel,Eco,187,3,4,3,4,4,3,4,4,3,4,5,5,4,4,71,66.0,neutral or dissatisfied +830,53072,Male,Loyal Customer,43,Business travel,Eco Plus,1190,5,1,1,1,5,5,5,5,5,2,3,4,3,5,118,100.0,satisfied +831,24772,Female,Loyal Customer,47,Business travel,Business,3391,1,1,1,1,4,4,4,5,5,5,5,2,5,1,0,14.0,satisfied +832,69268,Male,Loyal Customer,40,Personal Travel,Eco,733,1,2,1,3,3,1,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +833,45409,Female,Loyal Customer,52,Business travel,Business,458,3,3,3,3,4,2,3,4,4,4,4,4,4,1,3,12.0,satisfied +834,106509,Male,disloyal Customer,38,Business travel,Business,271,1,1,1,3,5,1,5,5,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +835,86905,Male,Loyal Customer,66,Business travel,Business,2243,0,0,0,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +836,126448,Female,Loyal Customer,44,Business travel,Business,1788,3,3,3,3,3,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +837,11604,Female,Loyal Customer,42,Personal Travel,Eco,468,2,4,2,1,1,2,5,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +838,76118,Male,disloyal Customer,39,Business travel,Business,689,1,1,1,3,3,1,3,3,3,5,4,3,5,3,1,0.0,neutral or dissatisfied +839,126508,Female,Loyal Customer,55,Business travel,Business,1849,3,3,3,3,5,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +840,97029,Female,Loyal Customer,8,Personal Travel,Eco Plus,794,2,4,2,4,5,2,5,5,4,2,4,4,5,5,11,7.0,neutral or dissatisfied +841,48727,Female,Loyal Customer,50,Business travel,Business,3455,0,5,0,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +842,60235,Female,Loyal Customer,58,Business travel,Business,1958,1,1,1,1,2,1,1,5,5,5,5,4,5,5,13,18.0,satisfied +843,4278,Female,Loyal Customer,41,Business travel,Business,502,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +844,129841,Female,Loyal Customer,18,Personal Travel,Eco,447,2,3,2,3,3,2,3,3,4,5,3,1,3,3,0,0.0,neutral or dissatisfied +845,33126,Male,Loyal Customer,30,Personal Travel,Eco,163,3,5,3,5,5,3,5,5,2,1,2,5,2,5,0,2.0,neutral or dissatisfied +846,51916,Female,Loyal Customer,19,Personal Travel,Eco,601,2,4,2,2,1,2,1,1,3,2,4,3,4,1,46,39.0,neutral or dissatisfied +847,6667,Male,disloyal Customer,25,Business travel,Business,403,2,5,2,5,4,2,4,4,3,2,4,5,5,4,20,1.0,neutral or dissatisfied +848,123198,Male,Loyal Customer,58,Personal Travel,Eco,631,3,1,2,2,1,2,1,1,1,1,3,4,2,1,0,0.0,neutral or dissatisfied +849,63650,Male,Loyal Customer,23,Business travel,Business,1448,1,1,1,1,3,4,3,3,3,2,5,4,5,3,0,0.0,satisfied +850,7757,Female,Loyal Customer,49,Personal Travel,Eco,1013,3,3,3,3,5,2,2,4,4,3,4,3,4,4,31,22.0,neutral or dissatisfied +851,91112,Female,Loyal Customer,18,Personal Travel,Eco,581,3,5,3,3,2,3,2,2,5,3,4,3,5,2,56,56.0,neutral or dissatisfied +852,17321,Female,Loyal Customer,26,Personal Travel,Eco,403,3,4,2,3,2,2,2,2,3,5,4,5,5,2,53,36.0,neutral or dissatisfied +853,48958,Female,Loyal Customer,50,Business travel,Eco,421,4,4,4,4,2,3,4,4,4,4,4,4,4,1,27,20.0,satisfied +854,98244,Female,Loyal Customer,32,Business travel,Business,3066,4,4,4,4,5,5,5,5,5,4,5,3,4,5,0,0.0,satisfied +855,42260,Female,Loyal Customer,70,Business travel,Eco,315,5,5,5,5,1,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +856,15496,Male,Loyal Customer,14,Personal Travel,Eco,377,3,5,3,2,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +857,43188,Male,Loyal Customer,56,Business travel,Business,1886,1,1,1,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +858,78190,Female,Loyal Customer,70,Business travel,Business,1810,3,5,5,5,5,4,3,5,5,4,3,4,5,3,0,12.0,neutral or dissatisfied +859,18621,Male,Loyal Customer,22,Personal Travel,Eco,253,3,5,0,2,2,0,2,2,5,3,5,4,2,2,113,103.0,neutral or dissatisfied +860,38896,Female,Loyal Customer,37,Business travel,Eco,320,5,5,5,5,5,5,5,5,1,2,4,1,3,5,0,0.0,satisfied +861,45223,Female,Loyal Customer,24,Business travel,Business,1013,3,3,3,3,3,3,3,3,1,1,2,2,2,3,25,13.0,satisfied +862,36798,Female,Loyal Customer,33,Personal Travel,Eco,2602,1,4,1,4,1,3,3,4,4,5,4,3,5,3,1,13.0,neutral or dissatisfied +863,78687,Female,Loyal Customer,37,Personal Travel,Eco,761,2,5,2,3,3,2,4,3,4,5,4,4,5,3,2,0.0,neutral or dissatisfied +864,110051,Male,Loyal Customer,70,Personal Travel,Eco,2173,1,5,1,3,4,1,4,4,4,5,4,5,4,4,30,55.0,neutral or dissatisfied +865,25848,Male,disloyal Customer,36,Business travel,Eco,292,1,0,1,4,1,1,1,1,1,5,4,1,3,1,5,1.0,neutral or dissatisfied +866,53234,Male,Loyal Customer,32,Personal Travel,Eco,612,1,5,1,4,4,1,4,4,5,2,5,2,4,4,67,93.0,neutral or dissatisfied +867,73548,Female,Loyal Customer,8,Personal Travel,Eco,594,3,1,4,2,3,4,4,3,3,1,3,4,3,3,37,46.0,neutral or dissatisfied +868,73085,Male,Loyal Customer,26,Business travel,Eco,1085,4,5,2,5,4,3,3,4,3,5,4,1,3,4,94,86.0,neutral or dissatisfied +869,68153,Female,Loyal Customer,51,Business travel,Business,3993,1,1,1,1,4,5,4,4,4,4,4,3,4,4,8,0.0,satisfied +870,120499,Male,Loyal Customer,47,Business travel,Eco Plus,449,1,1,1,1,1,1,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +871,86286,Female,Loyal Customer,36,Personal Travel,Eco,226,2,5,2,4,2,2,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +872,92452,Male,Loyal Customer,25,Business travel,Business,1947,3,4,5,5,3,2,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +873,80419,Male,Loyal Customer,51,Business travel,Business,2248,1,1,1,1,3,4,5,5,5,5,5,5,5,5,1,8.0,satisfied +874,56744,Female,Loyal Customer,49,Personal Travel,Eco,1023,1,4,1,4,1,2,2,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +875,58845,Male,Loyal Customer,44,Business travel,Business,783,1,1,1,1,5,5,5,2,2,2,2,5,2,3,3,4.0,satisfied +876,35204,Male,Loyal Customer,31,Business travel,Business,1076,5,5,5,5,4,4,4,4,2,2,5,5,4,4,13,44.0,satisfied +877,67010,Male,Loyal Customer,27,Business travel,Business,3534,5,5,5,5,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +878,106606,Female,disloyal Customer,27,Business travel,Eco,589,2,0,2,2,3,2,3,3,4,2,2,3,5,3,0,0.0,neutral or dissatisfied +879,117009,Male,Loyal Customer,52,Business travel,Business,3885,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +880,10659,Male,Loyal Customer,55,Business travel,Eco,667,1,1,1,1,1,1,1,1,4,1,3,4,3,1,25,27.0,neutral or dissatisfied +881,9724,Female,Loyal Customer,64,Personal Travel,Eco,277,2,2,2,2,5,3,3,1,1,2,1,3,1,1,8,1.0,neutral or dissatisfied +882,65056,Female,Loyal Customer,8,Personal Travel,Eco,354,3,2,3,4,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +883,22381,Female,Loyal Customer,37,Business travel,Business,145,3,5,5,5,4,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +884,84932,Male,Loyal Customer,44,Personal Travel,Eco,547,3,5,3,3,1,3,1,1,1,4,1,2,2,1,28,31.0,neutral or dissatisfied +885,58816,Male,Loyal Customer,41,Personal Travel,Eco,1182,3,5,3,4,2,3,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +886,29077,Female,Loyal Customer,37,Personal Travel,Eco,679,2,4,2,3,3,2,3,3,4,3,5,4,4,3,10,20.0,neutral or dissatisfied +887,74031,Female,Loyal Customer,59,Personal Travel,Eco,1471,1,5,1,1,2,4,4,3,3,1,3,4,3,3,0,44.0,neutral or dissatisfied +888,116208,Female,Loyal Customer,43,Personal Travel,Eco,372,4,0,4,3,4,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +889,80494,Female,disloyal Customer,25,Business travel,Business,1318,5,1,5,1,4,5,4,4,4,2,3,3,4,4,8,0.0,satisfied +890,1489,Female,Loyal Customer,54,Business travel,Business,737,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,3.0,satisfied +891,53230,Male,Loyal Customer,58,Personal Travel,Eco,589,4,1,4,4,4,4,4,4,1,3,4,2,4,4,29,17.0,neutral or dissatisfied +892,47141,Male,Loyal Customer,46,Business travel,Eco,954,2,2,2,2,2,2,2,2,5,4,2,2,4,2,0,0.0,satisfied +893,36015,Female,Loyal Customer,39,Business travel,Eco,399,4,2,2,2,4,4,4,4,4,3,1,5,2,4,0,0.0,satisfied +894,62074,Female,Loyal Customer,58,Business travel,Business,2475,2,2,3,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +895,75734,Male,Loyal Customer,10,Business travel,Eco,868,2,4,4,4,2,3,2,3,1,4,3,2,2,2,315,307.0,neutral or dissatisfied +896,31498,Female,Loyal Customer,16,Business travel,Business,3494,3,1,1,1,3,3,3,3,1,2,3,2,4,3,0,0.0,neutral or dissatisfied +897,18036,Male,Loyal Customer,43,Business travel,Business,488,4,4,4,4,5,1,1,4,4,4,4,3,4,4,0,0.0,satisfied +898,14781,Female,Loyal Customer,63,Personal Travel,Eco,487,2,5,2,3,3,4,5,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +899,91784,Female,Loyal Customer,25,Personal Travel,Eco,588,1,3,1,1,4,1,4,4,1,2,1,3,5,4,0,0.0,neutral or dissatisfied +900,117339,Male,Loyal Customer,47,Business travel,Business,393,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +901,18566,Female,Loyal Customer,23,Business travel,Business,190,1,1,1,1,2,1,2,4,2,3,3,2,1,2,158,156.0,neutral or dissatisfied +902,54914,Female,Loyal Customer,58,Business travel,Eco Plus,862,4,2,2,2,4,3,3,4,4,4,4,1,4,2,0,3.0,neutral or dissatisfied +903,78089,Female,Loyal Customer,49,Personal Travel,Eco Plus,332,3,5,3,2,5,4,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +904,89153,Female,Loyal Customer,49,Business travel,Business,3465,1,1,1,1,1,4,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +905,116444,Female,Loyal Customer,16,Personal Travel,Eco,337,2,4,3,2,3,3,1,3,4,5,2,5,5,3,2,0.0,neutral or dissatisfied +906,92504,Male,disloyal Customer,40,Business travel,Eco,639,1,3,1,1,4,1,4,4,2,4,1,2,1,4,0,0.0,neutral or dissatisfied +907,35145,Male,Loyal Customer,58,Business travel,Eco,950,5,4,4,4,5,5,5,5,3,2,4,3,4,5,0,25.0,satisfied +908,93708,Male,Loyal Customer,27,Personal Travel,Eco,689,3,2,3,4,3,3,3,3,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +909,15307,Female,disloyal Customer,29,Business travel,Business,589,4,4,4,3,4,4,4,4,4,5,3,1,4,4,6,2.0,neutral or dissatisfied +910,8194,Male,Loyal Customer,43,Business travel,Business,125,2,2,2,2,5,2,2,5,5,5,5,5,5,5,0,0.0,satisfied +911,10311,Male,Loyal Customer,58,Business travel,Business,2415,2,2,2,2,4,4,5,4,4,4,4,3,4,3,19,19.0,satisfied +912,47781,Male,Loyal Customer,46,Business travel,Eco,451,5,5,5,5,5,5,5,5,5,1,1,3,2,5,88,74.0,satisfied +913,25090,Female,Loyal Customer,38,Business travel,Business,1947,5,5,5,5,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +914,80225,Female,Loyal Customer,15,Personal Travel,Eco,2153,1,4,1,1,3,1,1,3,5,2,4,4,5,3,38,2.0,neutral or dissatisfied +915,36251,Female,Loyal Customer,49,Business travel,Eco,612,5,1,1,1,3,2,1,5,5,5,5,3,5,2,0,7.0,satisfied +916,32424,Male,Loyal Customer,49,Business travel,Business,163,2,1,5,1,4,2,3,3,3,3,2,1,3,4,0,0.0,neutral or dissatisfied +917,97427,Female,Loyal Customer,42,Personal Travel,Eco,587,4,4,3,3,4,4,5,3,3,3,3,4,3,3,1,0.0,neutral or dissatisfied +918,92570,Female,Loyal Customer,63,Business travel,Eco Plus,1947,1,5,5,5,3,1,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +919,96271,Female,Loyal Customer,33,Personal Travel,Eco,546,3,4,4,4,5,4,5,5,1,5,3,1,5,5,80,76.0,neutral or dissatisfied +920,67772,Female,Loyal Customer,55,Business travel,Eco,1438,2,3,3,3,1,4,3,2,2,2,2,4,2,3,65,91.0,neutral or dissatisfied +921,63943,Male,Loyal Customer,29,Personal Travel,Eco,1192,1,5,1,2,3,1,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +922,82906,Female,Loyal Customer,25,Personal Travel,Eco,594,3,3,3,3,4,3,1,4,4,1,2,1,2,4,0,9.0,neutral or dissatisfied +923,22832,Male,Loyal Customer,45,Business travel,Eco,170,4,5,5,5,4,4,4,4,3,1,3,3,4,4,0,0.0,satisfied +924,43497,Male,Loyal Customer,70,Personal Travel,Eco,679,0,2,0,3,1,0,1,1,3,1,2,3,2,1,0,0.0,satisfied +925,27257,Female,disloyal Customer,25,Business travel,Business,978,5,5,5,1,4,5,4,4,4,5,5,4,4,4,0,0.0,satisfied +926,22495,Female,Loyal Customer,67,Personal Travel,Eco,143,3,1,3,4,2,3,3,2,2,3,2,3,2,2,64,109.0,neutral or dissatisfied +927,74512,Male,Loyal Customer,45,Business travel,Business,2337,1,1,1,1,4,4,5,4,4,4,4,3,4,3,1,10.0,satisfied +928,122778,Female,Loyal Customer,39,Business travel,Business,2358,2,2,2,2,5,5,4,2,2,2,2,5,2,4,1,4.0,satisfied +929,112588,Male,Loyal Customer,41,Business travel,Business,602,2,4,4,4,2,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +930,94038,Female,Loyal Customer,56,Business travel,Business,189,0,5,0,4,5,4,4,5,5,5,5,5,5,4,111,109.0,satisfied +931,11226,Male,Loyal Customer,11,Personal Travel,Eco,301,2,2,2,4,1,2,1,1,1,3,3,4,3,1,2,0.0,neutral or dissatisfied +932,22938,Male,Loyal Customer,19,Business travel,Business,528,4,5,5,5,4,4,4,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +933,119345,Female,disloyal Customer,22,Business travel,Eco,214,4,3,3,1,5,3,5,5,5,5,5,4,5,5,2,0.0,satisfied +934,32488,Female,disloyal Customer,27,Business travel,Eco,163,3,3,3,2,2,3,2,2,5,1,1,2,3,2,0,0.0,neutral or dissatisfied +935,39522,Female,Loyal Customer,29,Personal Travel,Eco,1024,5,5,5,1,4,5,4,4,3,2,4,3,5,4,26,22.0,satisfied +936,2618,Female,Loyal Customer,34,Personal Travel,Eco,280,2,5,2,3,3,2,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +937,29113,Male,Loyal Customer,21,Personal Travel,Eco,605,2,4,2,4,1,2,1,1,3,4,4,5,4,1,32,33.0,neutral or dissatisfied +938,48524,Female,Loyal Customer,51,Business travel,Eco,833,1,2,2,2,3,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +939,74085,Female,Loyal Customer,52,Business travel,Business,3895,4,4,4,4,4,4,4,4,4,4,4,4,4,3,24,5.0,satisfied +940,118815,Male,disloyal Customer,34,Business travel,Business,304,1,0,0,1,2,0,2,2,5,5,4,5,4,2,74,77.0,neutral or dissatisfied +941,14253,Male,Loyal Customer,40,Business travel,Business,429,3,1,2,1,5,4,3,3,3,3,3,4,3,2,25,25.0,neutral or dissatisfied +942,77844,Female,Loyal Customer,33,Business travel,Eco Plus,874,2,1,1,1,2,2,2,2,2,1,3,3,4,2,0,9.0,neutral or dissatisfied +943,43832,Male,Loyal Customer,26,Business travel,Business,3434,0,4,0,5,1,1,1,1,4,2,4,4,2,1,0,0.0,satisfied +944,74000,Female,Loyal Customer,56,Personal Travel,Eco,1972,4,2,4,3,5,3,3,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +945,56718,Female,Loyal Customer,28,Personal Travel,Eco,1085,2,5,2,3,4,2,3,4,4,4,5,3,5,4,17,51.0,neutral or dissatisfied +946,123711,Male,Loyal Customer,53,Personal Travel,Eco,214,2,2,2,3,4,2,4,4,3,4,2,4,2,4,0,0.0,neutral or dissatisfied +947,15900,Male,Loyal Customer,56,Personal Travel,Eco,378,3,4,3,4,1,3,1,1,3,3,4,3,4,1,34,33.0,neutral or dissatisfied +948,122086,Male,Loyal Customer,23,Personal Travel,Eco,130,1,4,1,3,5,1,3,5,2,4,3,4,3,5,0,9.0,neutral or dissatisfied +949,30688,Male,Loyal Customer,27,Business travel,Eco,680,2,5,5,5,2,3,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +950,44347,Male,Loyal Customer,38,Business travel,Eco,308,2,1,3,1,2,2,2,2,2,3,2,3,2,2,0,15.0,neutral or dissatisfied +951,80521,Female,Loyal Customer,23,Personal Travel,Eco,1749,2,1,2,4,1,2,1,1,3,4,3,1,4,1,8,0.0,neutral or dissatisfied +952,63372,Male,Loyal Customer,41,Personal Travel,Eco,337,2,5,5,3,3,5,3,3,3,3,4,3,5,3,66,65.0,neutral or dissatisfied +953,129540,Male,Loyal Customer,31,Business travel,Business,2342,1,1,1,1,4,4,4,4,3,2,4,3,4,4,8,11.0,satisfied +954,55001,Female,Loyal Customer,42,Business travel,Business,1346,5,5,5,5,5,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +955,11174,Female,Loyal Customer,52,Personal Travel,Eco,316,3,5,3,2,4,3,1,4,4,3,4,5,4,2,112,101.0,neutral or dissatisfied +956,37393,Female,Loyal Customer,16,Business travel,Eco,1056,5,3,3,3,5,4,5,5,5,3,5,2,5,5,0,0.0,satisfied +957,26831,Male,disloyal Customer,29,Business travel,Business,224,3,3,3,4,3,3,3,3,5,3,5,2,2,3,0,3.0,neutral or dissatisfied +958,122143,Female,Loyal Customer,35,Business travel,Business,1834,5,5,5,5,5,4,4,5,5,5,5,5,5,5,10,0.0,satisfied +959,110601,Male,Loyal Customer,29,Personal Travel,Eco,488,1,5,1,3,2,1,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +960,9911,Male,disloyal Customer,21,Business travel,Eco,534,3,5,3,3,3,3,3,3,3,2,4,3,4,3,26,34.0,neutral or dissatisfied +961,103675,Male,Loyal Customer,38,Business travel,Business,1642,1,3,3,3,1,1,1,4,4,2,2,1,2,1,156,155.0,neutral or dissatisfied +962,116540,Female,Loyal Customer,48,Personal Travel,Eco,337,4,4,4,4,2,5,5,5,5,4,5,5,5,4,4,0.0,neutral or dissatisfied +963,96574,Male,Loyal Customer,61,Personal Travel,Eco,333,2,4,2,2,5,2,5,5,3,3,4,4,4,5,4,1.0,neutral or dissatisfied +964,43726,Female,Loyal Customer,52,Business travel,Eco Plus,257,5,2,5,2,3,3,4,5,5,5,5,4,5,2,0,0.0,satisfied +965,71277,Male,Loyal Customer,52,Personal Travel,Eco,733,3,5,3,3,1,3,1,1,4,4,3,4,4,1,13,2.0,neutral or dissatisfied +966,51385,Male,Loyal Customer,33,Personal Travel,Eco Plus,262,3,1,3,3,3,3,3,3,4,2,3,1,3,3,4,16.0,neutral or dissatisfied +967,46321,Male,Loyal Customer,39,Business travel,Eco,420,4,2,2,2,4,4,4,4,2,4,4,4,4,4,9,2.0,neutral or dissatisfied +968,30777,Female,disloyal Customer,26,Business travel,Eco,895,1,2,2,3,2,2,4,2,2,5,5,2,5,2,0,0.0,neutral or dissatisfied +969,412,Male,Loyal Customer,58,Business travel,Business,158,2,2,2,2,2,4,4,1,1,1,2,3,1,2,0,0.0,neutral or dissatisfied +970,93624,Male,disloyal Customer,24,Business travel,Eco,177,5,0,4,5,1,4,1,1,1,1,3,5,5,1,0,0.0,satisfied +971,124194,Male,Loyal Customer,45,Business travel,Business,2176,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +972,54086,Female,Loyal Customer,28,Personal Travel,Eco,1416,1,5,1,1,3,1,3,3,4,2,3,5,4,3,1,0.0,neutral or dissatisfied +973,114776,Male,Loyal Customer,30,Business travel,Business,390,4,4,4,4,5,5,5,5,5,2,5,4,5,5,10,11.0,satisfied +974,21256,Male,Loyal Customer,34,Personal Travel,Eco Plus,153,1,3,1,3,3,1,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +975,36006,Male,Loyal Customer,49,Business travel,Business,2538,4,4,4,4,2,1,3,3,3,5,3,2,3,5,0,4.0,satisfied +976,129530,Female,Loyal Customer,58,Business travel,Business,2342,5,5,5,5,5,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +977,47162,Male,Loyal Customer,41,Business travel,Business,2285,4,4,4,4,1,4,3,5,5,5,5,3,5,1,0,1.0,satisfied +978,99991,Female,Loyal Customer,58,Business travel,Business,3944,0,0,0,4,4,4,5,1,1,1,1,3,1,4,0,0.0,satisfied +979,122017,Female,disloyal Customer,21,Business travel,Business,185,0,5,0,5,3,0,3,3,5,4,4,4,5,3,0,0.0,satisfied +980,81197,Female,Loyal Customer,27,Personal Travel,Business,1426,3,4,3,2,1,3,1,1,2,3,3,3,2,1,12,21.0,neutral or dissatisfied +981,24228,Female,Loyal Customer,49,Business travel,Eco,302,5,4,4,4,1,5,4,5,5,5,5,1,5,4,30,19.0,satisfied +982,98566,Male,Loyal Customer,13,Personal Travel,Business,861,2,1,2,4,2,2,2,2,3,1,4,2,3,2,0,7.0,neutral or dissatisfied +983,117549,Female,Loyal Customer,27,Business travel,Business,347,3,3,3,3,4,4,4,4,3,5,4,3,4,4,43,38.0,satisfied +984,24452,Male,Loyal Customer,28,Business travel,Business,1680,4,4,4,4,5,5,5,5,4,1,5,5,4,5,0,14.0,satisfied +985,52506,Male,Loyal Customer,17,Personal Travel,Business,160,1,5,1,4,1,1,2,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +986,127230,Female,disloyal Customer,54,Business travel,Eco,1209,2,2,2,3,4,2,4,4,4,4,3,3,3,4,0,2.0,neutral or dissatisfied +987,47554,Male,Loyal Customer,59,Business travel,Eco Plus,590,3,3,3,3,3,3,3,3,2,4,2,2,2,3,0,0.0,neutral or dissatisfied +988,48272,Female,disloyal Customer,24,Business travel,Eco Plus,391,3,5,3,2,3,3,3,3,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +989,36902,Male,Loyal Customer,27,Business travel,Business,2072,2,2,2,2,4,4,4,4,2,3,4,1,5,4,6,13.0,satisfied +990,47000,Female,Loyal Customer,29,Business travel,Eco Plus,737,4,2,2,2,4,4,4,4,3,2,1,4,2,4,0,0.0,satisfied +991,71358,Male,Loyal Customer,40,Business travel,Business,258,2,2,2,2,5,4,4,4,4,4,4,5,4,3,62,60.0,satisfied +992,100351,Female,Loyal Customer,26,Personal Travel,Eco,1073,2,2,2,4,3,2,3,3,3,2,4,4,3,3,16,0.0,neutral or dissatisfied +993,128131,Male,Loyal Customer,60,Business travel,Business,1587,3,3,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +994,59271,Female,Loyal Customer,26,Business travel,Business,4243,2,2,2,2,4,4,4,3,5,4,4,4,5,4,26,0.0,satisfied +995,36608,Male,Loyal Customer,28,Business travel,Business,1091,2,2,2,2,4,4,4,4,5,2,2,2,5,4,0,0.0,satisfied +996,121263,Male,Loyal Customer,53,Personal Travel,Eco,2075,1,5,2,4,5,2,1,5,5,3,4,3,5,5,45,19.0,neutral or dissatisfied +997,16712,Male,Loyal Customer,48,Personal Travel,Eco,284,2,5,3,4,5,3,5,5,3,3,2,1,2,5,0,0.0,neutral or dissatisfied +998,22022,Female,Loyal Customer,46,Business travel,Eco Plus,448,2,3,3,3,2,5,4,1,1,2,1,5,1,5,0,0.0,satisfied +999,59019,Female,Loyal Customer,50,Business travel,Business,1744,5,5,5,5,5,3,5,5,5,4,5,4,5,4,0,0.0,satisfied +1000,72926,Male,disloyal Customer,27,Business travel,Business,1089,2,2,2,1,1,2,1,1,4,5,4,5,4,1,0,7.0,neutral or dissatisfied +1001,95776,Female,Loyal Customer,55,Personal Travel,Eco,419,2,4,3,3,3,1,4,1,1,3,2,3,1,4,0,0.0,neutral or dissatisfied +1002,47318,Male,Loyal Customer,28,Business travel,Business,1942,4,4,3,4,5,5,5,5,1,2,5,5,4,5,0,0.0,satisfied +1003,31364,Female,disloyal Customer,56,Personal Travel,Eco,589,1,5,1,3,3,1,4,3,4,1,1,5,4,3,7,12.0,neutral or dissatisfied +1004,104372,Female,Loyal Customer,51,Business travel,Business,2246,5,5,5,5,4,5,5,3,3,4,3,3,3,5,41,32.0,satisfied +1005,82961,Female,Loyal Customer,42,Business travel,Business,1086,4,4,5,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +1006,87906,Male,disloyal Customer,21,Business travel,Eco,594,1,5,1,2,3,1,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +1007,11534,Female,disloyal Customer,62,Business travel,Eco Plus,316,4,4,4,4,4,4,4,4,2,1,4,2,3,4,0,0.0,neutral or dissatisfied +1008,33680,Female,Loyal Customer,42,Business travel,Eco,899,3,5,5,5,3,1,3,3,3,3,3,5,3,5,0,0.0,satisfied +1009,105268,Male,Loyal Customer,8,Personal Travel,Eco,2106,2,2,2,4,3,2,3,3,2,5,4,1,3,3,7,32.0,neutral or dissatisfied +1010,29117,Female,Loyal Customer,35,Personal Travel,Eco,954,4,0,4,3,2,4,2,2,5,3,4,2,1,2,23,32.0,neutral or dissatisfied +1011,113585,Female,Loyal Customer,37,Business travel,Business,258,2,2,2,2,5,3,1,4,4,4,4,2,4,1,0,0.0,satisfied +1012,104955,Male,Loyal Customer,69,Personal Travel,Business,337,3,2,3,3,5,2,3,1,1,3,1,2,1,3,14,0.0,neutral or dissatisfied +1013,13060,Male,disloyal Customer,34,Business travel,Eco,936,1,1,1,2,1,1,1,1,1,4,4,5,1,1,0,0.0,neutral or dissatisfied +1014,128738,Male,Loyal Customer,7,Personal Travel,Business,2521,4,2,4,3,4,1,1,4,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +1015,43908,Female,Loyal Customer,20,Personal Travel,Eco,255,3,5,3,4,5,3,5,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +1016,76882,Female,Loyal Customer,30,Business travel,Business,630,2,2,2,2,2,2,2,2,5,4,5,5,5,2,0,13.0,satisfied +1017,36626,Female,Loyal Customer,57,Business travel,Eco,837,2,1,1,1,2,3,4,2,2,2,2,4,2,3,7,1.0,neutral or dissatisfied +1018,86574,Female,disloyal Customer,12,Business travel,Eco,1269,3,3,3,4,4,3,4,4,4,4,4,1,4,4,18,19.0,neutral or dissatisfied +1019,15607,Male,Loyal Customer,57,Business travel,Business,229,3,3,3,3,2,3,2,4,4,4,4,5,4,2,0,0.0,satisfied +1020,94892,Male,Loyal Customer,22,Business travel,Eco,323,4,1,1,1,4,4,5,4,2,3,1,4,4,4,28,45.0,satisfied +1021,91704,Male,Loyal Customer,29,Business travel,Business,588,3,3,3,3,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +1022,78909,Male,Loyal Customer,43,Business travel,Business,980,5,5,5,5,2,4,4,5,5,5,5,3,5,3,4,0.0,satisfied +1023,110219,Male,disloyal Customer,24,Business travel,Business,1138,4,4,4,4,5,4,4,5,3,2,4,4,5,5,0,0.0,satisfied +1024,25915,Female,Loyal Customer,52,Business travel,Eco,594,4,4,4,4,3,2,4,4,4,4,4,4,4,5,2,0.0,satisfied +1025,82183,Female,Loyal Customer,52,Business travel,Business,1927,1,1,1,1,3,3,4,4,4,4,4,3,4,4,3,0.0,satisfied +1026,6802,Male,Loyal Customer,60,Business travel,Eco,224,3,5,5,5,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +1027,74325,Male,Loyal Customer,45,Business travel,Business,1968,5,5,5,5,4,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +1028,21216,Male,Loyal Customer,41,Business travel,Eco,317,4,5,5,5,5,4,5,5,2,4,3,1,1,5,0,0.0,satisfied +1029,119032,Male,Loyal Customer,23,Personal Travel,Eco,1460,2,4,2,4,1,2,1,1,4,2,4,4,4,1,0,17.0,neutral or dissatisfied +1030,13650,Female,disloyal Customer,23,Business travel,Eco,196,5,0,5,1,5,1,3,5,2,4,4,3,4,3,154,154.0,satisfied +1031,7286,Female,Loyal Customer,42,Personal Travel,Eco,135,4,0,4,4,5,4,5,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +1032,14336,Male,Loyal Customer,35,Personal Travel,Eco,395,1,4,1,1,4,1,2,4,5,4,5,3,5,4,23,33.0,neutral or dissatisfied +1033,48622,Male,Loyal Customer,37,Personal Travel,Eco Plus,819,2,3,2,2,4,2,4,4,2,1,3,1,3,4,6,7.0,neutral or dissatisfied +1034,17810,Female,Loyal Customer,25,Business travel,Business,2582,4,4,4,4,4,4,4,4,4,3,1,1,2,4,0,0.0,satisfied +1035,127066,Male,Loyal Customer,57,Business travel,Business,651,1,4,5,4,4,1,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +1036,96512,Male,Loyal Customer,51,Personal Travel,Eco,302,4,5,4,1,5,4,5,5,3,4,4,5,4,5,37,29.0,neutral or dissatisfied +1037,86040,Female,Loyal Customer,16,Personal Travel,Eco,447,3,5,3,2,3,3,3,3,4,2,5,4,4,3,19,15.0,neutral or dissatisfied +1038,105204,Male,Loyal Customer,46,Personal Travel,Eco Plus,289,3,4,3,3,3,3,3,3,5,4,4,4,4,3,0,0.0,neutral or dissatisfied +1039,12217,Female,Loyal Customer,9,Personal Travel,Business,253,2,5,2,4,3,2,1,3,3,2,3,1,5,3,0,0.0,neutral or dissatisfied +1040,48544,Female,disloyal Customer,34,Business travel,Eco,833,2,2,2,4,2,2,2,2,3,1,3,2,3,2,46,41.0,neutral or dissatisfied +1041,30065,Female,disloyal Customer,37,Business travel,Eco,399,1,3,1,4,2,1,2,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +1042,19928,Female,Loyal Customer,54,Personal Travel,Eco,315,1,5,1,2,3,4,5,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +1043,122772,Female,Loyal Customer,49,Personal Travel,Eco Plus,427,4,4,5,1,2,4,5,3,3,5,3,5,3,3,0,0.0,neutral or dissatisfied +1044,106274,Male,disloyal Customer,39,Business travel,Business,689,1,1,1,3,1,1,1,1,3,2,5,4,4,1,4,3.0,neutral or dissatisfied +1045,57548,Female,Loyal Customer,70,Personal Travel,Eco Plus,413,2,4,1,4,2,3,4,1,1,1,3,2,1,3,20,20.0,neutral or dissatisfied +1046,114903,Female,Loyal Customer,41,Business travel,Business,2097,2,2,2,2,2,4,4,4,4,4,4,4,4,4,55,43.0,satisfied +1047,13822,Female,Loyal Customer,17,Business travel,Eco,594,5,5,5,5,5,5,3,5,4,1,1,3,5,5,0,5.0,satisfied +1048,32828,Male,disloyal Customer,21,Business travel,Eco,101,1,2,1,4,1,1,1,1,2,5,4,4,3,1,0,0.0,neutral or dissatisfied +1049,24138,Female,Loyal Customer,53,Business travel,Business,302,2,1,1,1,5,4,4,2,2,2,2,1,2,2,2,0.0,neutral or dissatisfied +1050,74440,Female,Loyal Customer,39,Business travel,Business,1930,2,2,2,2,2,5,5,4,4,3,4,4,4,3,0,0.0,satisfied +1051,127658,Male,Loyal Customer,55,Business travel,Business,2153,2,1,1,1,4,2,3,2,2,2,2,2,2,3,44,43.0,neutral or dissatisfied +1052,74641,Female,Loyal Customer,80,Business travel,Eco,1064,4,3,4,4,4,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +1053,67623,Female,Loyal Customer,46,Business travel,Business,1235,5,5,5,5,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +1054,80620,Female,Loyal Customer,18,Personal Travel,Eco,236,4,4,4,4,2,4,2,2,1,5,4,3,4,2,14,2.0,neutral or dissatisfied +1055,29282,Male,disloyal Customer,25,Business travel,Eco,569,3,2,3,2,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +1056,77895,Female,Loyal Customer,34,Business travel,Business,3169,2,3,3,3,3,3,3,2,2,2,2,4,2,4,1,0.0,neutral or dissatisfied +1057,34099,Female,Loyal Customer,15,Personal Travel,Business,1189,1,5,2,1,3,2,2,3,4,5,5,5,4,3,7,0.0,neutral or dissatisfied +1058,13199,Female,Loyal Customer,69,Personal Travel,Eco,419,1,4,1,3,1,1,4,4,2,3,4,4,4,4,150,147.0,neutral or dissatisfied +1059,129461,Female,Loyal Customer,47,Business travel,Business,414,1,1,1,1,5,5,4,4,4,4,4,5,4,4,3,2.0,satisfied +1060,77884,Male,Loyal Customer,69,Personal Travel,Eco,700,3,5,3,2,5,3,5,5,4,4,2,5,1,5,0,0.0,neutral or dissatisfied +1061,115386,Male,Loyal Customer,57,Business travel,Business,3902,1,1,1,1,5,5,5,5,5,5,5,4,5,3,55,53.0,satisfied +1062,117910,Male,Loyal Customer,59,Business travel,Business,2511,1,1,1,1,5,4,5,4,4,5,4,4,4,4,0,1.0,satisfied +1063,32774,Male,disloyal Customer,18,Business travel,Eco,163,3,5,3,3,5,3,5,5,3,2,2,3,3,5,0,1.0,neutral or dissatisfied +1064,33755,Female,Loyal Customer,52,Business travel,Eco,266,2,3,3,3,4,3,3,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +1065,19328,Male,Loyal Customer,23,Business travel,Business,694,1,1,1,1,1,1,1,1,1,2,4,1,3,1,1,11.0,neutral or dissatisfied +1066,129650,Male,Loyal Customer,47,Business travel,Business,2770,0,0,0,3,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +1067,1309,Female,Loyal Customer,18,Business travel,Business,354,3,3,5,3,5,5,5,5,3,3,4,4,4,5,15,18.0,satisfied +1068,26826,Female,Loyal Customer,33,Business travel,Business,3972,5,5,5,5,5,3,2,5,5,5,4,5,5,3,0,5.0,satisfied +1069,75883,Male,Loyal Customer,47,Business travel,Business,3227,4,4,4,4,5,5,4,4,4,4,4,3,4,5,55,60.0,satisfied +1070,4661,Female,Loyal Customer,19,Business travel,Eco,327,3,4,4,4,3,3,2,3,2,1,3,1,3,3,35,62.0,neutral or dissatisfied +1071,85999,Male,Loyal Customer,39,Business travel,Business,3467,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +1072,64039,Male,Loyal Customer,45,Business travel,Business,919,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,13.0,satisfied +1073,73753,Male,Loyal Customer,19,Personal Travel,Eco,192,2,4,0,4,1,0,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +1074,78395,Male,Loyal Customer,10,Personal Travel,Eco,980,2,4,3,3,4,3,4,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +1075,111805,Female,disloyal Customer,33,Business travel,Eco,349,3,1,3,3,4,3,4,4,4,3,4,1,4,4,19,39.0,neutral or dissatisfied +1076,19403,Female,Loyal Customer,51,Personal Travel,Eco,261,3,1,3,4,3,3,4,2,5,4,4,4,1,4,228,217.0,neutral or dissatisfied +1077,40124,Male,Loyal Customer,25,Personal Travel,Eco,200,3,1,0,2,2,0,2,2,4,4,3,2,3,2,0,4.0,neutral or dissatisfied +1078,45729,Female,Loyal Customer,50,Business travel,Eco Plus,1068,3,5,5,5,3,4,3,3,3,3,3,4,3,2,0,60.0,neutral or dissatisfied +1079,83946,Female,Loyal Customer,28,Business travel,Business,2032,1,1,1,1,5,5,5,5,4,3,5,3,4,5,0,0.0,satisfied +1080,33009,Male,Loyal Customer,19,Personal Travel,Eco,102,3,4,3,3,1,3,1,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +1081,58371,Female,disloyal Customer,35,Business travel,Business,723,3,4,4,5,1,4,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +1082,90203,Male,Loyal Customer,14,Personal Travel,Eco,1127,4,4,4,2,5,4,3,5,5,2,5,4,5,5,0,3.0,satisfied +1083,104120,Female,disloyal Customer,25,Business travel,Business,393,4,0,4,2,4,4,2,4,5,2,4,5,4,4,1,0.0,satisfied +1084,124849,Female,Loyal Customer,59,Personal Travel,Eco,280,2,4,2,3,3,4,5,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +1085,77123,Male,Loyal Customer,50,Personal Travel,Eco,1481,2,5,2,4,3,2,3,3,3,3,2,2,4,3,2,0.0,neutral or dissatisfied +1086,104611,Male,Loyal Customer,58,Personal Travel,Eco Plus,369,1,2,2,3,3,2,3,3,2,2,3,2,2,3,8,0.0,neutral or dissatisfied +1087,37336,Male,Loyal Customer,58,Business travel,Eco,828,4,2,2,2,4,4,4,4,1,5,3,4,3,4,101,124.0,satisfied +1088,75015,Male,disloyal Customer,19,Business travel,Business,236,3,4,3,3,2,3,2,2,2,2,4,3,4,2,0,0.0,neutral or dissatisfied +1089,48947,Female,Loyal Customer,33,Business travel,Business,372,2,2,2,2,5,1,4,5,5,5,5,2,5,5,55,48.0,satisfied +1090,108414,Female,Loyal Customer,43,Business travel,Business,1444,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +1091,60676,Female,Loyal Customer,46,Personal Travel,Eco Plus,1620,3,4,2,1,5,4,5,4,4,2,4,3,4,5,0,1.0,neutral or dissatisfied +1092,37035,Female,Loyal Customer,15,Business travel,Business,3746,2,2,2,2,4,4,4,4,1,5,3,4,1,4,0,0.0,satisfied +1093,41891,Female,Loyal Customer,48,Business travel,Business,2922,4,4,4,4,4,4,3,4,4,4,4,1,4,3,0,0.0,satisfied +1094,70571,Male,Loyal Customer,8,Personal Travel,Eco,1258,4,5,4,3,3,4,3,3,3,3,3,3,5,3,0,0.0,satisfied +1095,4338,Female,disloyal Customer,20,Business travel,Eco,473,4,2,4,3,3,4,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +1096,15964,Female,Loyal Customer,17,Personal Travel,Eco,473,4,5,4,3,4,4,4,4,3,5,5,4,3,4,0,0.0,neutral or dissatisfied +1097,96639,Male,Loyal Customer,11,Business travel,Business,2945,1,1,1,1,4,4,4,4,5,2,4,4,4,4,0,3.0,satisfied +1098,106005,Female,Loyal Customer,49,Business travel,Business,1999,5,5,5,5,2,3,4,5,5,4,5,3,5,5,23,0.0,satisfied +1099,63578,Female,Loyal Customer,45,Business travel,Business,2133,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +1100,93879,Male,disloyal Customer,33,Business travel,Business,588,1,1,1,1,3,1,3,3,3,2,4,3,5,3,40,30.0,neutral or dissatisfied +1101,120873,Male,Loyal Customer,50,Business travel,Business,3839,1,1,1,1,3,5,5,4,4,4,4,5,4,4,36,53.0,satisfied +1102,28205,Male,Loyal Customer,22,Personal Travel,Eco,933,3,5,3,4,3,3,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +1103,44569,Male,Loyal Customer,57,Business travel,Eco,177,5,2,4,4,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +1104,79044,Female,Loyal Customer,46,Business travel,Business,306,4,3,3,3,5,3,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +1105,83924,Female,Loyal Customer,13,Personal Travel,Business,304,4,4,4,3,1,4,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +1106,87679,Female,disloyal Customer,80,Business travel,Business,206,1,0,0,4,2,3,4,1,1,1,1,3,1,2,8,9.0,neutral or dissatisfied +1107,122677,Male,Loyal Customer,59,Business travel,Business,361,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +1108,30511,Female,Loyal Customer,20,Personal Travel,Eco,1620,3,2,3,3,2,3,5,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +1109,65615,Female,Loyal Customer,30,Personal Travel,Eco,175,4,4,4,4,3,4,3,3,1,1,3,1,2,3,0,0.0,neutral or dissatisfied +1110,119596,Female,Loyal Customer,34,Business travel,Business,1979,1,1,1,1,5,5,4,3,3,3,3,4,3,3,72,47.0,satisfied +1111,40624,Female,Loyal Customer,14,Personal Travel,Eco,391,1,1,1,3,3,1,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +1112,105440,Male,Loyal Customer,39,Business travel,Business,998,3,4,3,3,5,5,5,4,2,4,4,5,3,5,137,150.0,satisfied +1113,6964,Male,disloyal Customer,26,Business travel,Business,196,5,1,5,4,2,5,2,2,3,2,4,3,4,2,27,40.0,satisfied +1114,95839,Female,Loyal Customer,41,Business travel,Business,3857,2,1,1,1,5,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +1115,49898,Female,disloyal Customer,33,Business travel,Eco,109,3,0,2,5,5,2,5,5,1,3,3,5,5,5,0,0.0,neutral or dissatisfied +1116,23127,Female,Loyal Customer,36,Business travel,Business,300,3,1,1,1,2,3,3,3,3,3,3,1,3,1,0,9.0,neutral or dissatisfied +1117,75440,Male,disloyal Customer,28,Business travel,Business,2342,3,3,3,4,3,3,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +1118,96698,Female,Loyal Customer,58,Business travel,Business,696,4,4,3,4,4,5,4,4,4,5,4,5,4,5,126,116.0,satisfied +1119,20910,Female,Loyal Customer,23,Business travel,Business,721,1,1,1,1,3,5,3,3,5,1,4,3,3,3,45,39.0,satisfied +1120,41533,Female,Loyal Customer,36,Business travel,Business,3979,2,2,2,2,3,3,2,2,2,2,2,1,2,2,6,0.0,neutral or dissatisfied +1121,6983,Male,Loyal Customer,44,Business travel,Business,299,3,3,3,3,3,5,5,4,4,4,4,3,4,5,7,4.0,satisfied +1122,70108,Female,disloyal Customer,42,Business travel,Business,460,3,3,3,2,5,3,5,5,3,3,5,4,5,5,0,0.0,neutral or dissatisfied +1123,119756,Female,disloyal Customer,18,Business travel,Eco,1351,5,5,5,5,4,5,4,4,3,4,5,3,5,4,0,0.0,satisfied +1124,73442,Male,Loyal Customer,53,Personal Travel,Eco,1012,3,2,3,4,4,3,4,4,4,4,4,3,3,4,38,,neutral or dissatisfied +1125,73141,Female,Loyal Customer,69,Personal Travel,Eco,1068,4,5,4,3,3,4,5,3,3,4,3,4,3,3,7,1.0,satisfied +1126,63506,Female,Loyal Customer,47,Personal Travel,Eco,1956,2,4,2,1,4,5,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +1127,64837,Male,Loyal Customer,40,Business travel,Business,3523,4,2,2,2,2,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +1128,49287,Male,Loyal Customer,35,Business travel,Business,158,4,4,4,4,4,5,2,5,5,5,3,5,5,4,13,4.0,satisfied +1129,955,Female,Loyal Customer,35,Business travel,Business,134,2,1,1,1,3,2,3,3,1,2,2,3,2,3,161,171.0,neutral or dissatisfied +1130,90813,Male,disloyal Customer,26,Business travel,Business,594,0,0,0,5,2,0,1,2,5,3,4,4,5,2,0,0.0,satisfied +1131,21866,Male,Loyal Customer,24,Business travel,Business,1893,2,2,2,2,5,5,5,5,5,1,4,3,4,5,0,0.0,satisfied +1132,44104,Male,Loyal Customer,51,Business travel,Business,2131,4,4,4,4,5,5,3,5,5,5,5,3,5,3,0,0.0,satisfied +1133,58512,Female,Loyal Customer,27,Personal Travel,Eco,719,2,5,2,4,3,2,2,3,5,4,4,5,5,3,124,105.0,neutral or dissatisfied +1134,75149,Male,Loyal Customer,54,Business travel,Business,1846,5,5,5,5,2,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +1135,85236,Male,Loyal Customer,46,Business travel,Business,474,3,2,2,2,4,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +1136,3974,Female,Loyal Customer,70,Personal Travel,Eco Plus,764,3,5,3,4,2,5,5,1,1,3,1,3,1,3,26,22.0,neutral or dissatisfied +1137,113008,Male,Loyal Customer,64,Personal Travel,Eco,1751,1,4,1,3,1,1,1,1,2,5,3,2,4,1,4,5.0,neutral or dissatisfied +1138,15804,Male,Loyal Customer,59,Personal Travel,Eco,246,4,5,4,3,5,4,5,5,3,3,3,3,4,5,0,0.0,neutral or dissatisfied +1139,24367,Male,Loyal Customer,34,Business travel,Business,3162,1,1,4,1,1,2,5,5,5,5,5,1,5,2,80,73.0,satisfied +1140,53231,Female,Loyal Customer,60,Personal Travel,Eco,589,2,4,2,2,3,5,5,5,5,2,5,3,5,4,54,84.0,neutral or dissatisfied +1141,87683,Male,Loyal Customer,57,Business travel,Business,3132,2,1,1,1,4,3,3,3,3,3,2,1,3,2,19,15.0,neutral or dissatisfied +1142,84509,Male,Loyal Customer,47,Business travel,Business,2486,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +1143,47586,Male,Loyal Customer,29,Business travel,Eco,1235,0,1,1,3,1,1,1,1,2,4,2,5,2,1,50,40.0,satisfied +1144,43998,Male,Loyal Customer,24,Business travel,Business,2536,1,3,5,3,1,1,1,1,2,3,3,4,3,1,10,22.0,neutral or dissatisfied +1145,9223,Female,Loyal Customer,55,Business travel,Business,1682,4,4,4,4,3,4,4,3,3,4,5,4,3,3,0,0.0,satisfied +1146,129346,Female,Loyal Customer,26,Personal Travel,Eco,2475,4,1,3,3,1,3,1,1,2,5,3,2,4,1,16,15.0,neutral or dissatisfied +1147,53032,Male,Loyal Customer,27,Business travel,Business,2378,3,3,3,3,4,4,4,4,1,5,5,4,1,4,0,0.0,satisfied +1148,20523,Female,Loyal Customer,42,Business travel,Business,3529,2,2,2,2,3,5,2,4,4,4,4,5,4,4,0,11.0,satisfied +1149,102646,Female,Loyal Customer,46,Business travel,Business,2414,3,3,2,3,2,5,5,3,3,3,3,3,3,4,42,30.0,satisfied +1150,10835,Male,Loyal Customer,44,Business travel,Business,316,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +1151,97798,Male,Loyal Customer,63,Personal Travel,Eco,471,3,4,3,1,3,3,5,3,5,4,4,5,4,3,126,123.0,neutral or dissatisfied +1152,7971,Female,Loyal Customer,56,Business travel,Business,2221,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,7.0,satisfied +1153,19331,Female,Loyal Customer,42,Personal Travel,Eco,694,2,5,2,2,4,4,4,1,1,2,1,4,1,5,27,0.0,neutral or dissatisfied +1154,72382,Female,Loyal Customer,31,Business travel,Business,2908,2,2,2,2,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +1155,123573,Female,Loyal Customer,58,Business travel,Eco,1773,2,3,3,3,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +1156,115598,Male,Loyal Customer,42,Business travel,Eco,446,2,2,2,2,2,2,2,2,3,3,4,2,3,2,174,165.0,neutral or dissatisfied +1157,107826,Male,Loyal Customer,26,Personal Travel,Eco,349,3,3,3,3,1,3,1,1,1,1,3,3,3,1,0,0.0,neutral or dissatisfied +1158,64058,Male,disloyal Customer,18,Business travel,Eco,919,2,2,2,3,4,2,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +1159,69022,Female,disloyal Customer,22,Business travel,Eco,1389,2,2,2,4,5,2,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +1160,35169,Male,Loyal Customer,40,Business travel,Business,2874,2,2,2,2,5,1,5,4,4,4,4,3,4,2,0,11.0,satisfied +1161,82719,Female,Loyal Customer,62,Personal Travel,Eco,632,4,4,4,2,2,4,5,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +1162,45591,Female,Loyal Customer,59,Business travel,Business,3553,2,2,2,2,5,2,2,3,3,4,3,5,3,2,18,29.0,satisfied +1163,52903,Male,Loyal Customer,48,Business travel,Business,3020,5,5,5,5,5,3,1,5,5,5,5,3,5,1,54,41.0,satisfied +1164,56401,Male,disloyal Customer,26,Business travel,Business,719,5,5,5,2,4,5,2,4,4,4,5,5,4,4,0,56.0,satisfied +1165,70548,Male,Loyal Customer,43,Business travel,Business,3221,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,39.0,satisfied +1166,9097,Female,Loyal Customer,30,Personal Travel,Eco Plus,108,3,4,3,3,4,3,1,4,5,3,5,3,4,4,0,39.0,neutral or dissatisfied +1167,59234,Female,Loyal Customer,31,Business travel,Business,1549,2,2,2,2,4,4,4,4,5,2,5,3,2,4,0,0.0,satisfied +1168,31573,Male,Loyal Customer,63,Business travel,Business,371,3,3,3,3,3,3,3,1,4,3,3,3,1,3,137,165.0,neutral or dissatisfied +1169,51594,Female,Loyal Customer,31,Business travel,Business,3331,1,1,1,1,5,5,5,5,4,1,2,2,5,5,0,0.0,satisfied +1170,33693,Male,disloyal Customer,30,Business travel,Eco,759,1,1,1,1,4,1,4,4,5,2,4,2,1,4,0,0.0,neutral or dissatisfied +1171,35215,Female,disloyal Customer,19,Business travel,Eco,950,2,2,2,4,2,2,2,2,5,5,4,2,5,2,0,0.0,neutral or dissatisfied +1172,17965,Female,Loyal Customer,44,Personal Travel,Eco,501,4,2,4,4,4,4,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +1173,41080,Female,Loyal Customer,63,Business travel,Eco,224,3,2,2,2,1,1,2,3,3,3,3,4,3,4,5,6.0,satisfied +1174,5035,Male,disloyal Customer,26,Business travel,Business,235,1,0,1,2,5,1,5,5,4,2,5,3,5,5,0,5.0,neutral or dissatisfied +1175,74141,Male,Loyal Customer,33,Business travel,Business,1819,3,2,2,2,3,3,3,3,3,4,2,1,1,3,0,0.0,neutral or dissatisfied +1176,24981,Male,Loyal Customer,44,Business travel,Eco,692,5,2,2,2,5,5,5,5,4,2,2,2,3,5,0,0.0,satisfied +1177,61257,Female,Loyal Customer,37,Personal Travel,Eco,948,2,1,2,3,5,2,5,5,2,4,3,3,3,5,0,0.0,neutral or dissatisfied +1178,116315,Female,Loyal Customer,40,Personal Travel,Eco,480,1,4,1,3,3,1,2,3,5,2,1,5,1,3,5,0.0,neutral or dissatisfied +1179,90924,Male,Loyal Customer,17,Business travel,Business,271,0,0,0,4,3,3,3,3,5,5,4,1,2,3,11,0.0,satisfied +1180,30454,Male,Loyal Customer,40,Business travel,Business,991,4,2,2,2,4,2,2,4,4,3,4,1,4,2,22,27.0,neutral or dissatisfied +1181,43417,Female,Loyal Customer,30,Business travel,Eco Plus,402,3,1,1,1,3,3,3,3,4,2,3,1,3,3,0,6.0,neutral or dissatisfied +1182,31833,Female,Loyal Customer,13,Personal Travel,Eco,2762,4,4,4,4,4,4,4,2,4,4,4,4,3,4,3,0.0,satisfied +1183,103464,Female,Loyal Customer,53,Personal Travel,Eco,448,2,4,2,2,5,4,5,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +1184,101915,Female,Loyal Customer,46,Personal Travel,Eco,2173,4,4,4,3,2,4,4,2,2,4,2,4,2,5,12,0.0,neutral or dissatisfied +1185,105006,Female,Loyal Customer,46,Business travel,Business,255,0,0,0,3,4,4,5,3,3,2,2,5,3,4,0,0.0,satisfied +1186,65305,Female,Loyal Customer,40,Business travel,Business,3857,4,4,4,4,5,4,5,5,5,5,5,5,5,4,6,0.0,satisfied +1187,80381,Male,Loyal Customer,34,Business travel,Business,1565,3,5,1,1,5,3,3,3,3,3,3,2,3,3,3,1.0,neutral or dissatisfied +1188,41348,Female,Loyal Customer,41,Business travel,Eco,956,4,2,2,2,5,4,5,5,4,1,2,1,1,5,29,94.0,satisfied +1189,5825,Female,Loyal Customer,69,Personal Travel,Eco,177,4,5,4,3,4,4,5,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +1190,42828,Female,disloyal Customer,65,Business travel,Eco,328,4,3,4,3,4,4,4,4,2,1,5,2,4,4,0,0.0,satisfied +1191,112942,Female,Loyal Customer,22,Personal Travel,Eco,1390,1,4,2,2,1,2,1,1,4,2,1,3,5,1,0,0.0,neutral or dissatisfied +1192,121107,Male,Loyal Customer,43,Personal Travel,Business,2521,5,2,5,2,5,1,1,3,4,1,3,1,1,1,60,51.0,satisfied +1193,97557,Female,Loyal Customer,40,Business travel,Business,2708,3,3,3,3,4,5,5,5,5,5,5,4,5,4,5,0.0,satisfied +1194,52543,Female,Loyal Customer,49,Business travel,Eco,160,4,1,1,1,4,4,2,3,3,4,3,2,3,2,0,0.0,satisfied +1195,111988,Male,Loyal Customer,23,Personal Travel,Eco,533,2,5,2,3,5,2,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +1196,19383,Female,Loyal Customer,17,Business travel,Business,844,4,4,4,4,5,5,5,5,4,2,3,5,4,5,103,83.0,satisfied +1197,60045,Male,Loyal Customer,42,Business travel,Business,1807,4,4,4,4,4,4,4,5,5,5,5,3,5,5,53,20.0,satisfied +1198,31049,Male,Loyal Customer,10,Business travel,Business,641,3,4,4,4,3,2,3,3,2,2,4,1,4,3,0,6.0,neutral or dissatisfied +1199,40475,Female,Loyal Customer,37,Business travel,Business,1966,5,1,5,5,1,3,5,4,4,4,4,1,4,1,0,0.0,satisfied +1200,18851,Female,disloyal Customer,15,Business travel,Eco,448,2,4,2,4,2,2,2,2,2,1,5,5,5,2,1,0.0,neutral or dissatisfied +1201,53638,Male,Loyal Customer,47,Personal Travel,Eco,1874,4,2,4,4,5,4,5,5,4,3,3,3,3,5,11,39.0,neutral or dissatisfied +1202,84123,Female,Loyal Customer,27,Personal Travel,Eco,2036,2,4,2,1,3,2,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +1203,41856,Male,Loyal Customer,33,Business travel,Eco,483,4,4,4,4,4,4,4,4,3,1,3,4,5,4,313,336.0,satisfied +1204,35248,Female,disloyal Customer,27,Business travel,Eco,1076,1,1,1,2,2,1,2,2,3,3,3,3,3,2,44,44.0,neutral or dissatisfied +1205,91710,Female,disloyal Customer,24,Business travel,Eco,532,2,0,2,4,3,2,4,3,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +1206,63277,Female,Loyal Customer,44,Business travel,Business,337,0,0,0,2,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +1207,56922,Male,disloyal Customer,43,Business travel,Business,2454,2,2,2,1,1,2,1,1,3,5,5,4,5,1,19,0.0,neutral or dissatisfied +1208,9300,Male,Loyal Customer,58,Business travel,Business,3697,4,4,4,4,2,4,5,5,5,5,5,3,5,5,5,0.0,satisfied +1209,49637,Male,Loyal Customer,33,Business travel,Business,337,1,1,1,1,5,5,5,5,2,3,1,5,1,5,0,0.0,satisfied +1210,38857,Female,disloyal Customer,37,Business travel,Eco,1036,4,4,4,3,1,4,1,1,1,4,5,5,4,1,5,17.0,neutral or dissatisfied +1211,52857,Female,Loyal Customer,39,Business travel,Eco Plus,1721,4,4,4,4,4,4,4,4,4,3,3,2,1,4,0,0.0,satisfied +1212,41195,Male,Loyal Customer,59,Business travel,Eco,1174,5,1,1,1,4,5,4,4,5,5,3,5,3,4,0,14.0,satisfied +1213,129286,Female,Loyal Customer,51,Business travel,Business,3324,4,4,4,4,3,4,5,4,4,4,4,3,4,3,23,17.0,satisfied +1214,13842,Male,Loyal Customer,55,Personal Travel,Eco,628,3,5,3,2,3,3,3,3,5,2,2,1,1,3,0,0.0,neutral or dissatisfied +1215,91569,Female,Loyal Customer,39,Business travel,Business,1123,5,5,5,5,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +1216,103088,Female,Loyal Customer,9,Personal Travel,Eco,687,2,5,2,3,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +1217,57223,Male,Loyal Customer,16,Personal Travel,Eco,1514,3,4,3,4,4,3,4,4,2,3,4,1,4,4,7,0.0,neutral or dissatisfied +1218,9735,Female,Loyal Customer,20,Personal Travel,Eco,926,3,5,3,4,3,1,1,5,4,5,5,1,5,1,136,124.0,neutral or dissatisfied +1219,7518,Male,Loyal Customer,32,Business travel,Business,2072,5,5,5,5,2,2,2,5,2,5,4,2,5,2,160,155.0,satisfied +1220,96249,Male,Loyal Customer,29,Personal Travel,Eco,546,0,2,0,4,5,0,5,5,3,2,4,4,4,5,0,0.0,satisfied +1221,53388,Male,Loyal Customer,13,Personal Travel,Eco,1452,2,4,2,3,5,2,5,5,2,5,5,5,2,5,2,0.0,neutral or dissatisfied +1222,106771,Male,Loyal Customer,16,Personal Travel,Eco,945,3,1,3,3,2,3,2,2,3,1,3,1,4,2,46,59.0,neutral or dissatisfied +1223,118043,Female,Loyal Customer,33,Business travel,Business,1262,3,3,2,3,4,4,4,5,3,5,5,4,3,4,232,219.0,satisfied +1224,114100,Male,disloyal Customer,35,Business travel,Eco Plus,1947,2,2,2,3,5,2,2,5,4,5,4,3,3,5,8,13.0,neutral or dissatisfied +1225,43129,Male,Loyal Customer,66,Business travel,Eco Plus,192,2,2,4,2,2,2,2,2,2,5,3,1,3,2,53,42.0,neutral or dissatisfied +1226,113510,Male,Loyal Customer,69,Business travel,Business,2274,2,5,4,5,2,2,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +1227,108448,Female,Loyal Customer,59,Business travel,Business,1444,1,1,1,1,2,5,4,5,5,5,5,3,5,4,11,15.0,satisfied +1228,19322,Female,Loyal Customer,29,Business travel,Business,1853,3,3,3,3,3,5,3,3,2,1,3,3,5,3,0,0.0,satisfied +1229,38790,Female,disloyal Customer,25,Business travel,Eco,353,1,3,1,3,5,1,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +1230,119352,Female,Loyal Customer,60,Personal Travel,Eco Plus,214,2,5,2,1,4,5,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +1231,96284,Male,Loyal Customer,46,Personal Travel,Eco,687,4,4,4,4,2,4,2,2,3,3,5,5,5,2,22,12.0,neutral or dissatisfied +1232,70260,Female,Loyal Customer,43,Personal Travel,Eco Plus,1592,3,5,3,2,5,3,5,1,1,3,1,4,1,3,4,34.0,neutral or dissatisfied +1233,58514,Female,Loyal Customer,61,Personal Travel,Eco,719,2,5,1,3,1,2,2,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +1234,55126,Male,Loyal Customer,60,Personal Travel,Eco,1609,3,5,3,4,3,3,3,3,4,5,4,5,4,3,80,82.0,neutral or dissatisfied +1235,63077,Male,Loyal Customer,41,Personal Travel,Eco,967,3,4,3,3,4,3,4,4,4,2,3,1,3,4,12,8.0,neutral or dissatisfied +1236,124340,Male,Loyal Customer,33,Business travel,Business,3988,1,1,2,1,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +1237,75764,Female,Loyal Customer,59,Personal Travel,Eco,868,4,4,4,2,4,5,5,1,1,4,1,2,1,3,7,0.0,satisfied +1238,3631,Male,Loyal Customer,58,Business travel,Business,1885,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +1239,29412,Female,Loyal Customer,11,Personal Travel,Eco,2378,2,5,2,5,1,2,4,1,5,4,5,5,3,1,0,0.0,neutral or dissatisfied +1240,121765,Female,disloyal Customer,62,Business travel,Business,449,4,4,4,1,2,4,2,2,3,5,5,4,5,2,2,1.0,neutral or dissatisfied +1241,11640,Male,Loyal Customer,65,Personal Travel,Eco,835,4,3,4,4,5,4,5,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +1242,117986,Male,Loyal Customer,44,Personal Travel,Eco,601,1,4,1,5,4,1,4,4,1,1,1,1,5,4,1,0.0,neutral or dissatisfied +1243,105222,Female,Loyal Customer,45,Business travel,Business,3597,4,4,4,4,3,4,5,2,2,2,2,3,2,4,22,11.0,satisfied +1244,53763,Female,Loyal Customer,55,Business travel,Eco,1195,3,1,1,1,3,5,5,3,3,3,3,4,3,1,0,0.0,satisfied +1245,93948,Male,Loyal Customer,67,Personal Travel,Eco,507,2,5,2,3,1,2,1,1,3,5,5,5,4,1,38,37.0,neutral or dissatisfied +1246,2251,Female,Loyal Customer,22,Business travel,Business,3152,1,4,4,4,1,1,1,1,4,3,3,1,3,1,46,46.0,neutral or dissatisfied +1247,41686,Male,Loyal Customer,55,Personal Travel,Eco,347,1,4,1,4,5,1,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +1248,100137,Male,Loyal Customer,57,Business travel,Business,3743,2,2,2,2,3,5,4,5,5,5,5,5,5,4,2,0.0,satisfied +1249,129721,Female,Loyal Customer,51,Business travel,Eco,337,1,5,5,5,2,4,3,1,1,1,1,2,1,2,90,87.0,neutral or dissatisfied +1250,109085,Female,Loyal Customer,55,Personal Travel,Eco,957,3,5,3,2,2,5,4,3,3,3,3,3,3,4,41,39.0,neutral or dissatisfied +1251,71567,Female,Loyal Customer,50,Business travel,Business,3710,4,4,4,4,3,4,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +1252,73696,Female,Loyal Customer,36,Business travel,Business,3964,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,1.0,satisfied +1253,45998,Male,Loyal Customer,26,Personal Travel,Eco,483,3,1,3,3,3,3,3,3,1,2,2,2,4,3,5,4.0,neutral or dissatisfied +1254,125252,Female,Loyal Customer,69,Personal Travel,Eco,427,2,4,2,4,5,3,4,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +1255,20294,Female,Loyal Customer,66,Personal Travel,Eco,346,3,5,3,2,4,5,5,1,1,3,1,4,1,5,1,0.0,neutral or dissatisfied +1256,123386,Female,Loyal Customer,38,Business travel,Business,1337,3,4,4,4,1,4,4,3,3,4,3,1,3,3,44,35.0,neutral or dissatisfied +1257,49994,Female,disloyal Customer,40,Business travel,Business,156,3,2,2,2,4,2,5,4,4,2,3,4,1,4,0,0.0,neutral or dissatisfied +1258,62729,Female,Loyal Customer,51,Business travel,Business,2486,4,4,5,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +1259,1383,Female,disloyal Customer,23,Business travel,Eco,164,3,1,3,2,2,3,2,2,2,1,2,1,1,2,36,40.0,neutral or dissatisfied +1260,27185,Male,Loyal Customer,7,Personal Travel,Eco,2677,4,1,4,3,4,3,4,4,1,3,3,4,1,4,0,0.0,neutral or dissatisfied +1261,77320,Female,disloyal Customer,39,Business travel,Business,590,3,3,3,2,5,3,3,5,3,5,5,3,5,5,0,3.0,neutral or dissatisfied +1262,26797,Male,disloyal Customer,30,Business travel,Eco,843,4,4,4,3,4,3,3,3,5,3,2,3,4,3,149,116.0,neutral or dissatisfied +1263,88194,Female,disloyal Customer,25,Business travel,Eco,545,4,2,4,3,2,4,2,2,2,2,4,4,3,2,0,5.0,neutral or dissatisfied +1264,91467,Female,disloyal Customer,26,Business travel,Eco,459,4,4,5,4,5,2,4,2,3,2,4,4,4,4,412,459.0,satisfied +1265,93229,Female,Loyal Customer,50,Personal Travel,Eco,1460,1,5,1,1,3,5,5,2,2,1,2,4,2,3,21,0.0,neutral or dissatisfied +1266,73049,Male,Loyal Customer,52,Business travel,Business,3448,1,1,1,1,5,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +1267,2123,Male,Loyal Customer,51,Business travel,Business,3466,2,2,2,2,3,4,4,4,4,4,4,3,4,5,30,31.0,satisfied +1268,100441,Male,Loyal Customer,39,Business travel,Business,1180,5,5,5,5,2,4,4,5,5,5,5,4,5,3,14,2.0,satisfied +1269,30901,Female,Loyal Customer,24,Business travel,Business,3931,3,3,3,3,3,4,3,3,1,3,5,4,4,3,0,0.0,satisfied +1270,85467,Female,Loyal Customer,42,Business travel,Business,2381,0,0,0,2,4,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +1271,120400,Male,Loyal Customer,54,Business travel,Eco,366,3,4,4,4,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +1272,103612,Female,disloyal Customer,26,Business travel,Business,251,1,5,1,4,5,1,3,5,3,2,4,5,5,5,5,4.0,neutral or dissatisfied +1273,112616,Female,Loyal Customer,29,Personal Travel,Eco,602,3,4,3,4,2,3,2,2,3,2,5,4,4,2,7,10.0,neutral or dissatisfied +1274,18045,Male,Loyal Customer,45,Business travel,Business,488,3,3,3,3,4,2,2,5,5,5,5,2,5,5,70,89.0,satisfied +1275,10657,Male,Loyal Customer,45,Business travel,Business,2788,0,0,0,1,2,5,4,2,2,2,2,3,2,5,39,33.0,satisfied +1276,83709,Female,Loyal Customer,62,Personal Travel,Eco,577,3,5,3,3,3,4,4,2,2,3,4,3,2,3,9,13.0,neutral or dissatisfied +1277,112429,Male,disloyal Customer,20,Business travel,Eco,846,3,3,3,2,2,3,2,2,1,4,2,1,3,2,15,41.0,neutral or dissatisfied +1278,105809,Male,Loyal Customer,48,Personal Travel,Eco,787,2,4,2,3,3,2,3,3,3,3,4,5,5,3,8,11.0,neutral or dissatisfied +1279,6313,Female,Loyal Customer,52,Business travel,Business,296,3,3,4,3,4,5,5,5,5,5,5,3,5,4,25,23.0,satisfied +1280,86731,Male,Loyal Customer,25,Personal Travel,Eco,1747,4,1,4,3,1,4,1,1,3,1,2,1,3,1,0,0.0,neutral or dissatisfied +1281,56592,Female,Loyal Customer,59,Business travel,Business,2490,5,5,5,5,5,4,4,4,4,4,4,3,4,5,64,53.0,satisfied +1282,28504,Male,Loyal Customer,25,Business travel,Business,2701,2,2,2,2,3,3,3,3,5,5,4,2,5,3,0,0.0,satisfied +1283,73746,Male,Loyal Customer,62,Personal Travel,Eco,192,2,2,2,4,1,2,1,1,2,2,3,3,3,1,0,0.0,neutral or dissatisfied +1284,62378,Female,Loyal Customer,18,Business travel,Business,2611,3,3,1,3,4,4,4,4,5,3,3,3,5,4,0,0.0,satisfied +1285,42905,Male,Loyal Customer,39,Business travel,Eco,422,4,2,2,2,4,4,4,4,1,3,5,3,1,4,0,0.0,satisfied +1286,86155,Male,Loyal Customer,39,Business travel,Business,306,3,2,3,2,5,4,4,3,3,3,3,4,3,2,42,28.0,neutral or dissatisfied +1287,116276,Female,Loyal Customer,67,Personal Travel,Eco,296,2,4,5,2,4,5,5,2,2,5,2,5,2,4,40,49.0,neutral or dissatisfied +1288,25351,Male,disloyal Customer,25,Business travel,Business,591,5,5,5,2,5,5,5,5,5,3,4,3,5,5,1,0.0,satisfied +1289,121730,Male,Loyal Customer,62,Business travel,Business,1475,4,2,2,2,4,3,2,4,4,4,4,2,4,4,0,15.0,neutral or dissatisfied +1290,21975,Female,Loyal Customer,50,Personal Travel,Eco,448,1,4,5,3,4,5,4,5,5,5,5,4,5,3,69,54.0,neutral or dissatisfied +1291,10654,Female,disloyal Customer,64,Business travel,Business,312,4,4,4,4,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +1292,89175,Female,Loyal Customer,67,Personal Travel,Eco,1947,1,4,1,3,4,4,5,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +1293,87902,Female,Loyal Customer,49,Business travel,Business,3235,4,4,4,4,5,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +1294,28960,Male,Loyal Customer,47,Business travel,Business,2432,2,2,2,2,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +1295,68474,Female,Loyal Customer,32,Business travel,Business,1303,5,5,5,5,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +1296,14880,Male,disloyal Customer,64,Business travel,Eco,315,4,3,4,4,5,4,4,5,4,5,3,2,3,5,0,24.0,neutral or dissatisfied +1297,93577,Female,Loyal Customer,57,Business travel,Business,2183,2,2,4,2,2,4,5,4,4,4,5,3,4,5,16,11.0,satisfied +1298,113790,Female,disloyal Customer,17,Business travel,Eco Plus,258,1,0,1,4,4,1,4,4,2,2,4,4,4,4,0,0.0,neutral or dissatisfied +1299,70841,Male,disloyal Customer,24,Business travel,Eco,761,3,3,3,5,1,3,1,1,4,3,4,3,4,1,7,12.0,neutral or dissatisfied +1300,37929,Female,Loyal Customer,21,Personal Travel,Eco,937,4,4,4,2,4,4,4,2,2,3,3,4,1,4,185,175.0,neutral or dissatisfied +1301,10152,Female,Loyal Customer,56,Personal Travel,Eco,1157,3,4,3,3,4,5,5,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +1302,86710,Male,Loyal Customer,25,Business travel,Business,1747,1,1,1,1,4,4,4,4,5,3,4,5,5,4,0,2.0,satisfied +1303,116161,Female,Loyal Customer,14,Personal Travel,Eco,308,4,4,4,2,2,4,2,2,3,2,4,4,5,2,2,0.0,neutral or dissatisfied +1304,78051,Male,Loyal Customer,64,Personal Travel,Eco,214,4,3,4,4,5,4,5,5,3,1,3,1,3,5,0,4.0,neutral or dissatisfied +1305,24003,Male,Loyal Customer,34,Business travel,Business,2164,4,4,4,4,1,1,2,2,2,2,2,1,2,4,0,6.0,satisfied +1306,28746,Male,Loyal Customer,10,Business travel,Business,1024,2,2,2,2,4,4,4,4,1,2,4,1,3,4,0,0.0,satisfied +1307,99649,Female,Loyal Customer,56,Personal Travel,Eco,1670,2,3,2,3,3,3,4,4,4,2,4,1,4,2,1,0.0,neutral or dissatisfied +1308,113567,Female,disloyal Customer,26,Business travel,Business,386,5,4,5,5,1,5,1,1,3,3,4,4,5,1,5,4.0,satisfied +1309,26855,Male,Loyal Customer,42,Personal Travel,Eco,224,3,4,0,2,2,0,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +1310,94631,Female,disloyal Customer,34,Business travel,Eco,458,2,3,2,4,5,2,5,5,4,4,4,2,3,5,35,31.0,neutral or dissatisfied +1311,59751,Female,Loyal Customer,55,Business travel,Business,895,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +1312,112928,Female,Loyal Customer,52,Personal Travel,Eco,1390,1,4,1,1,2,4,2,3,3,1,3,5,3,1,0,0.0,neutral or dissatisfied +1313,2898,Female,Loyal Customer,51,Personal Travel,Eco,409,3,5,3,3,3,5,5,3,3,3,5,5,3,4,70,68.0,neutral or dissatisfied +1314,39717,Male,disloyal Customer,25,Business travel,Eco,320,2,5,2,4,2,2,2,2,4,4,5,5,3,2,0,0.0,neutral or dissatisfied +1315,28061,Male,Loyal Customer,55,Business travel,Business,2607,5,5,5,5,4,4,4,1,5,3,1,4,3,4,0,0.0,satisfied +1316,73486,Female,Loyal Customer,35,Personal Travel,Eco,1197,4,4,4,4,2,4,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +1317,126224,Female,disloyal Customer,55,Business travel,Eco,468,4,0,4,2,1,4,1,1,5,1,5,4,1,1,0,0.0,neutral or dissatisfied +1318,20308,Male,Loyal Customer,11,Business travel,Business,622,2,5,5,5,2,1,2,2,1,4,3,4,3,2,21,19.0,neutral or dissatisfied +1319,38446,Female,Loyal Customer,21,Personal Travel,Eco,588,1,5,1,2,4,1,4,4,4,1,1,4,3,4,0,0.0,neutral or dissatisfied +1320,43128,Male,Loyal Customer,63,Business travel,Eco Plus,236,5,2,2,2,5,5,5,5,2,1,4,5,1,5,0,0.0,satisfied +1321,107636,Male,disloyal Customer,28,Business travel,Business,405,5,5,5,1,3,5,3,3,5,4,5,3,4,3,14,11.0,satisfied +1322,30141,Male,Loyal Customer,49,Personal Travel,Eco,160,1,1,1,3,5,1,5,5,2,3,3,1,3,5,4,6.0,neutral or dissatisfied +1323,104185,Male,Loyal Customer,54,Personal Travel,Eco,349,1,5,1,2,4,1,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +1324,121619,Male,Loyal Customer,39,Personal Travel,Eco,936,3,2,3,4,5,3,5,5,3,5,4,2,3,5,0,8.0,neutral or dissatisfied +1325,115210,Female,disloyal Customer,42,Business travel,Business,337,2,2,2,3,2,2,2,2,5,4,4,5,4,2,0,25.0,neutral or dissatisfied +1326,12778,Male,Loyal Customer,50,Business travel,Business,3550,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +1327,37503,Female,disloyal Customer,26,Business travel,Eco,972,2,2,2,2,4,2,4,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +1328,24310,Male,Loyal Customer,17,Personal Travel,Eco Plus,302,3,5,3,3,4,3,4,4,4,4,3,4,3,4,0,0.0,neutral or dissatisfied +1329,6511,Male,Loyal Customer,60,Business travel,Business,3159,2,2,1,2,5,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +1330,108345,Female,Loyal Customer,59,Business travel,Eco,1706,2,3,3,3,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +1331,116139,Male,Loyal Customer,59,Personal Travel,Eco,325,3,2,3,3,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +1332,35841,Male,disloyal Customer,8,Business travel,Eco,1023,1,1,1,3,1,1,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +1333,25220,Female,Loyal Customer,61,Business travel,Eco,787,1,2,4,2,5,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +1334,18081,Male,Loyal Customer,11,Personal Travel,Eco,605,1,4,1,2,2,1,2,2,4,2,5,5,5,2,24,22.0,neutral or dissatisfied +1335,62715,Female,Loyal Customer,25,Business travel,Business,2504,4,4,4,4,4,4,4,3,5,3,5,4,3,4,199,175.0,satisfied +1336,69862,Female,Loyal Customer,65,Personal Travel,Eco,1055,3,5,3,5,3,4,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +1337,47885,Female,Loyal Customer,39,Business travel,Business,1543,3,3,3,3,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +1338,92241,Male,disloyal Customer,50,Business travel,Business,1670,2,2,2,3,2,2,2,2,4,3,3,3,5,2,18,3.0,neutral or dissatisfied +1339,80364,Female,disloyal Customer,29,Business travel,Business,368,2,3,3,4,2,3,2,2,4,2,5,5,4,2,0,2.0,neutral or dissatisfied +1340,21182,Male,disloyal Customer,20,Business travel,Eco,153,3,3,2,3,5,2,1,5,2,1,5,2,1,5,0,0.0,neutral or dissatisfied +1341,119238,Male,Loyal Customer,51,Business travel,Business,1651,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +1342,87390,Female,Loyal Customer,51,Business travel,Eco,425,4,1,1,1,5,3,2,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +1343,84184,Male,disloyal Customer,26,Business travel,Business,432,1,5,1,1,2,1,2,2,4,4,4,4,4,2,0,31.0,neutral or dissatisfied +1344,117690,Female,Loyal Customer,28,Business travel,Business,1814,4,4,4,4,4,4,4,4,3,5,4,5,5,4,0,2.0,satisfied +1345,7780,Female,Loyal Customer,23,Personal Travel,Eco,1080,3,1,3,3,2,3,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +1346,65586,Male,disloyal Customer,39,Business travel,Eco,237,1,3,1,3,4,1,4,4,4,2,4,3,4,4,7,50.0,neutral or dissatisfied +1347,89717,Male,Loyal Customer,62,Personal Travel,Eco,950,0,0,0,4,5,0,5,5,1,3,2,2,4,5,0,0.0,satisfied +1348,22258,Female,Loyal Customer,59,Business travel,Eco,145,4,2,2,2,1,1,3,4,4,4,4,5,4,4,1,9.0,satisfied +1349,58903,Male,Loyal Customer,48,Business travel,Business,1739,3,3,3,3,4,4,1,4,4,4,4,4,4,5,5,5.0,satisfied +1350,29210,Female,Loyal Customer,31,Business travel,Eco,2311,2,3,3,3,2,2,2,2,1,3,3,3,4,2,24,4.0,neutral or dissatisfied +1351,30327,Female,disloyal Customer,36,Business travel,Eco,391,2,1,2,4,1,2,1,1,1,3,4,1,3,1,70,62.0,neutral or dissatisfied +1352,92631,Female,Loyal Customer,52,Business travel,Eco,453,1,0,0,4,5,4,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +1353,55769,Male,Loyal Customer,61,Personal Travel,Business,646,2,2,1,4,1,4,3,2,2,1,4,4,2,2,40,21.0,neutral or dissatisfied +1354,99662,Male,Loyal Customer,9,Personal Travel,Eco,1050,4,2,3,3,5,3,5,5,4,4,3,1,3,5,1,0.0,satisfied +1355,102131,Female,disloyal Customer,21,Business travel,Business,407,5,0,5,2,5,5,5,5,5,3,4,5,5,5,39,38.0,satisfied +1356,125834,Male,Loyal Customer,28,Business travel,Business,2597,1,1,1,1,5,5,5,5,4,5,4,3,5,5,6,1.0,satisfied +1357,111523,Male,Loyal Customer,46,Personal Travel,Eco Plus,391,2,3,1,2,4,1,4,4,4,5,2,3,3,4,0,0.0,neutral or dissatisfied +1358,100877,Female,Loyal Customer,51,Business travel,Business,2133,2,5,5,5,2,4,4,2,2,2,2,1,2,2,114,104.0,neutral or dissatisfied +1359,59912,Female,disloyal Customer,26,Business travel,Eco,1068,2,2,2,3,3,2,3,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +1360,55356,Male,disloyal Customer,25,Business travel,Business,678,3,4,3,3,1,3,1,1,3,4,5,4,5,1,2,0.0,neutral or dissatisfied +1361,50403,Female,disloyal Customer,36,Business travel,Eco,326,2,0,2,4,3,2,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +1362,10023,Male,Loyal Customer,70,Personal Travel,Eco Plus,534,2,4,2,2,4,2,4,4,5,3,4,4,4,4,19,18.0,neutral or dissatisfied +1363,75570,Female,disloyal Customer,26,Business travel,Business,337,2,0,2,4,4,2,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +1364,77914,Male,disloyal Customer,37,Business travel,Business,214,5,5,5,4,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +1365,77820,Male,Loyal Customer,68,Personal Travel,Eco,874,2,3,2,4,4,2,4,4,4,2,3,3,3,4,0,2.0,neutral or dissatisfied +1366,34754,Female,Loyal Customer,47,Business travel,Eco,209,1,1,1,1,2,3,2,1,1,1,1,3,1,3,62,60.0,neutral or dissatisfied +1367,118777,Male,Loyal Customer,59,Personal Travel,Eco,304,3,4,3,1,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +1368,41200,Male,Loyal Customer,27,Business travel,Business,2837,2,2,3,2,5,4,5,5,2,1,1,1,5,5,0,0.0,satisfied +1369,120391,Female,Loyal Customer,35,Business travel,Business,449,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +1370,40839,Male,Loyal Customer,36,Business travel,Business,188,3,5,5,5,2,3,2,2,1,4,3,2,2,2,135,133.0,neutral or dissatisfied +1371,124948,Female,Loyal Customer,47,Business travel,Eco Plus,728,3,1,1,1,2,3,3,3,3,3,3,4,3,2,0,17.0,neutral or dissatisfied +1372,106979,Female,Loyal Customer,40,Business travel,Business,537,2,2,2,2,1,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +1373,31950,Male,Loyal Customer,47,Business travel,Business,102,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,1.0,satisfied +1374,754,Male,Loyal Customer,56,Business travel,Business,3435,3,3,3,3,4,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +1375,61312,Female,Loyal Customer,34,Business travel,Business,1668,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +1376,105805,Female,Loyal Customer,66,Personal Travel,Eco,883,1,3,1,3,5,5,4,5,5,1,5,2,5,3,44,52.0,neutral or dissatisfied +1377,83736,Male,Loyal Customer,41,Personal Travel,Business,1183,4,4,4,3,2,3,5,1,1,4,1,3,1,5,0,8.0,neutral or dissatisfied +1378,86964,Male,Loyal Customer,43,Business travel,Business,3576,4,4,4,4,5,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +1379,117151,Male,Loyal Customer,42,Personal Travel,Eco,304,2,3,2,3,2,2,2,2,3,5,3,4,3,2,8,7.0,neutral or dissatisfied +1380,129471,Female,Loyal Customer,53,Business travel,Business,2704,3,1,1,1,5,2,4,3,3,3,3,2,3,3,4,6.0,neutral or dissatisfied +1381,60122,Female,Loyal Customer,21,Business travel,Business,1005,2,1,1,1,2,2,2,2,3,1,4,1,3,2,18,16.0,neutral or dissatisfied +1382,66711,Male,disloyal Customer,22,Business travel,Eco,802,0,0,0,3,2,0,2,2,2,4,4,4,5,2,4,46.0,satisfied +1383,117256,Female,Loyal Customer,21,Personal Travel,Eco,368,3,3,3,3,3,3,3,3,2,4,1,2,3,3,16,10.0,neutral or dissatisfied +1384,13014,Male,Loyal Customer,38,Business travel,Eco,374,2,3,3,3,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +1385,82365,Female,Loyal Customer,64,Personal Travel,Eco,453,2,5,2,5,5,4,4,2,2,2,2,4,2,4,0,3.0,neutral or dissatisfied +1386,76867,Female,disloyal Customer,29,Business travel,Business,867,4,4,4,4,2,4,2,2,3,5,3,3,4,2,0,0.0,satisfied +1387,41105,Female,Loyal Customer,38,Business travel,Eco,224,5,5,5,5,5,5,5,5,5,4,5,3,4,5,4,9.0,satisfied +1388,24353,Female,Loyal Customer,63,Personal Travel,Eco,634,4,4,4,2,3,5,5,3,3,4,2,3,3,3,0,0.0,neutral or dissatisfied +1389,29244,Male,Loyal Customer,40,Business travel,Eco,550,2,1,1,1,2,2,2,2,3,1,4,4,3,2,4,6.0,neutral or dissatisfied +1390,104337,Male,Loyal Customer,50,Personal Travel,Eco,409,3,4,3,1,1,3,1,1,4,5,4,4,4,1,48,32.0,neutral or dissatisfied +1391,127596,Female,Loyal Customer,59,Business travel,Business,1773,4,4,2,4,2,4,5,5,5,5,5,3,5,5,64,49.0,satisfied +1392,99863,Male,Loyal Customer,67,Personal Travel,Eco,680,2,5,2,3,4,2,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +1393,115144,Female,Loyal Customer,46,Business travel,Business,371,1,1,4,1,4,4,4,4,2,4,4,4,5,4,142,134.0,satisfied +1394,26442,Female,Loyal Customer,43,Business travel,Eco,919,4,5,5,5,1,1,3,4,4,4,4,1,4,3,0,1.0,satisfied +1395,112462,Male,Loyal Customer,15,Business travel,Business,853,2,4,4,4,2,2,2,2,4,1,3,1,4,2,46,43.0,neutral or dissatisfied +1396,69182,Female,Loyal Customer,37,Personal Travel,Eco,187,2,4,2,5,4,2,4,4,4,3,4,3,4,4,2,0.0,neutral or dissatisfied +1397,54065,Female,Loyal Customer,44,Business travel,Business,1416,1,1,1,1,5,1,3,4,4,4,4,5,4,3,0,0.0,satisfied +1398,48645,Female,disloyal Customer,24,Business travel,Eco,109,1,4,1,4,1,1,1,1,5,4,5,5,4,1,59,81.0,neutral or dissatisfied +1399,34700,Female,Loyal Customer,64,Business travel,Business,209,4,4,4,4,5,3,5,4,4,3,2,5,2,5,147,259.0,satisfied +1400,83889,Female,Loyal Customer,47,Personal Travel,Eco Plus,1670,4,4,5,2,3,2,4,2,2,5,2,2,2,5,0,0.0,neutral or dissatisfied +1401,91417,Female,Loyal Customer,60,Personal Travel,Eco,1050,1,3,1,4,1,5,1,3,3,1,3,5,3,4,53,77.0,neutral or dissatisfied +1402,89741,Male,Loyal Customer,41,Personal Travel,Eco,944,3,5,3,5,1,3,1,1,4,5,3,1,1,1,85,80.0,neutral or dissatisfied +1403,37814,Male,Loyal Customer,61,Personal Travel,Eco Plus,989,3,5,3,3,3,3,3,3,4,3,4,5,5,3,16,12.0,neutral or dissatisfied +1404,74867,Male,Loyal Customer,30,Personal Travel,Business,2239,3,4,4,2,4,4,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +1405,79747,Male,Loyal Customer,21,Business travel,Eco Plus,762,3,1,1,1,3,4,4,3,2,4,5,2,2,3,0,0.0,satisfied +1406,30699,Male,Loyal Customer,59,Personal Travel,Eco,680,1,5,1,2,1,1,1,1,1,2,5,4,1,1,52,79.0,neutral or dissatisfied +1407,10286,Female,Loyal Customer,44,Business travel,Business,201,1,1,1,1,4,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +1408,7445,Female,Loyal Customer,30,Personal Travel,Eco,522,3,5,3,4,4,3,4,4,5,2,5,3,5,4,0,3.0,neutral or dissatisfied +1409,57680,Male,Loyal Customer,35,Business travel,Business,867,4,4,4,4,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +1410,67508,Male,Loyal Customer,15,Business travel,Business,1235,5,5,1,5,4,4,4,4,5,3,4,4,5,4,0,16.0,satisfied +1411,26718,Male,Loyal Customer,68,Personal Travel,Eco,404,1,5,1,3,1,1,4,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +1412,52423,Female,Loyal Customer,54,Personal Travel,Eco,651,3,5,3,4,2,3,4,5,5,3,5,4,5,5,5,16.0,neutral or dissatisfied +1413,5923,Female,Loyal Customer,47,Personal Travel,Eco,173,1,4,1,2,5,4,5,4,4,1,2,5,4,5,0,0.0,neutral or dissatisfied +1414,15814,Male,Loyal Customer,31,Personal Travel,Eco,246,4,4,4,3,4,4,4,4,2,5,2,2,5,4,1,6.0,neutral or dissatisfied +1415,32055,Male,Loyal Customer,43,Business travel,Business,101,0,4,0,1,3,5,4,3,3,3,3,1,3,1,2,1.0,satisfied +1416,106406,Female,Loyal Customer,52,Personal Travel,Eco,551,2,3,2,2,1,1,5,3,3,2,3,4,3,5,4,4.0,neutral or dissatisfied +1417,73635,Female,Loyal Customer,39,Business travel,Business,3873,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +1418,16759,Female,Loyal Customer,31,Business travel,Business,642,3,3,3,3,4,4,4,4,1,5,3,1,5,4,66,68.0,satisfied +1419,7772,Female,Loyal Customer,51,Business travel,Business,990,1,1,4,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +1420,67826,Female,Loyal Customer,74,Business travel,Business,3589,3,3,3,3,3,4,2,3,3,3,3,1,3,4,0,3.0,satisfied +1421,89824,Female,Loyal Customer,36,Personal Travel,Eco Plus,944,2,4,2,3,4,2,4,4,2,4,5,3,3,4,0,0.0,neutral or dissatisfied +1422,78634,Male,Loyal Customer,54,Business travel,Business,1953,1,1,1,1,4,4,4,4,2,5,4,4,5,4,235,222.0,satisfied +1423,95987,Female,Loyal Customer,35,Business travel,Business,1655,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +1424,83619,Female,disloyal Customer,22,Business travel,Eco,409,2,5,2,4,2,2,2,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +1425,113549,Female,Loyal Customer,56,Business travel,Business,3911,2,1,1,1,4,2,3,2,2,2,2,1,2,4,21,15.0,neutral or dissatisfied +1426,56817,Female,disloyal Customer,43,Business travel,Eco,779,2,2,2,3,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +1427,34956,Male,Loyal Customer,57,Personal Travel,Eco,187,3,5,3,4,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +1428,55788,Female,Loyal Customer,59,Business travel,Business,2400,2,2,2,2,5,5,5,4,5,4,5,5,5,5,0,0.0,satisfied +1429,96173,Male,Loyal Customer,45,Business travel,Business,460,3,3,3,3,2,4,4,4,4,5,4,5,4,5,5,6.0,satisfied +1430,99997,Male,Loyal Customer,59,Business travel,Business,3261,4,4,4,4,3,5,5,4,4,4,4,4,4,5,7,6.0,satisfied +1431,81174,Female,Loyal Customer,43,Business travel,Business,2899,0,0,0,5,4,5,5,2,2,2,2,3,2,4,6,0.0,satisfied +1432,89220,Male,Loyal Customer,24,Personal Travel,Eco,1947,5,5,5,1,1,5,1,1,5,4,4,3,5,1,9,2.0,satisfied +1433,72365,Female,Loyal Customer,30,Business travel,Business,3513,5,5,1,5,3,3,3,3,5,4,4,5,4,3,0,0.0,satisfied +1434,29105,Male,Loyal Customer,54,Personal Travel,Eco,697,3,5,3,2,2,3,2,2,3,2,2,5,2,2,0,0.0,neutral or dissatisfied +1435,20144,Male,Loyal Customer,37,Business travel,Eco,258,2,1,1,1,2,2,2,2,1,5,2,5,4,2,0,0.0,satisfied +1436,106519,Male,disloyal Customer,26,Business travel,Business,271,2,0,2,3,2,2,5,1,4,3,4,5,1,5,113,203.0,neutral or dissatisfied +1437,87760,Female,Loyal Customer,40,Business travel,Business,1798,4,4,1,4,5,4,4,5,5,5,4,5,5,5,6,0.0,satisfied +1438,123588,Female,Loyal Customer,17,Personal Travel,Eco,1773,2,2,2,2,5,2,5,5,3,2,1,3,2,5,18,6.0,neutral or dissatisfied +1439,11821,Female,Loyal Customer,42,Business travel,Business,1922,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,2.0,satisfied +1440,51905,Male,Loyal Customer,44,Business travel,Business,507,4,4,4,4,5,4,1,4,4,4,4,1,4,2,25,24.0,satisfied +1441,81103,Female,disloyal Customer,30,Business travel,Business,991,2,2,2,5,3,2,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +1442,48033,Female,Loyal Customer,20,Personal Travel,Eco,1384,1,3,1,2,2,1,2,2,5,2,1,1,1,2,0,0.0,neutral or dissatisfied +1443,42447,Male,Loyal Customer,23,Business travel,Eco,866,4,5,4,5,4,4,4,4,2,3,1,4,2,4,0,0.0,satisfied +1444,64181,Male,Loyal Customer,26,Business travel,Business,1047,5,5,5,5,2,3,2,2,4,3,5,4,4,2,0,0.0,satisfied +1445,77813,Male,Loyal Customer,28,Personal Travel,Eco,731,2,3,2,2,3,2,3,3,4,1,5,4,1,3,13,9.0,neutral or dissatisfied +1446,1747,Female,Loyal Customer,57,Personal Travel,Eco,364,1,5,1,3,4,4,4,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +1447,57664,Male,Loyal Customer,57,Personal Travel,Eco,200,3,5,3,2,4,3,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +1448,70049,Male,Loyal Customer,39,Personal Travel,Eco,583,2,5,2,2,2,2,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +1449,26587,Male,Loyal Customer,47,Business travel,Business,270,1,1,1,1,5,2,4,4,4,4,4,5,4,2,0,0.0,satisfied +1450,69270,Female,Loyal Customer,28,Personal Travel,Eco,733,2,1,2,4,4,2,4,4,1,3,4,3,3,4,30,47.0,neutral or dissatisfied +1451,111810,Male,Loyal Customer,34,Personal Travel,Eco,349,2,3,2,4,2,2,2,2,3,5,3,4,3,2,8,12.0,neutral or dissatisfied +1452,13702,Female,Loyal Customer,61,Personal Travel,Eco,300,3,1,3,2,2,2,1,3,3,3,3,1,3,1,5,28.0,neutral or dissatisfied +1453,21173,Male,Loyal Customer,51,Personal Travel,Business,192,1,5,1,3,2,4,5,2,2,1,1,5,2,4,21,11.0,neutral or dissatisfied +1454,70121,Male,Loyal Customer,39,Business travel,Business,550,2,2,2,2,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +1455,39018,Male,disloyal Customer,26,Business travel,Eco,113,3,1,3,2,3,3,3,3,3,4,2,4,2,3,0,22.0,neutral or dissatisfied +1456,21375,Male,Loyal Customer,61,Business travel,Business,2458,3,4,4,4,4,2,3,3,3,3,3,4,3,1,5,1.0,neutral or dissatisfied +1457,67805,Female,Loyal Customer,41,Business travel,Business,1514,2,2,2,2,5,3,5,2,2,2,2,2,2,4,4,0.0,satisfied +1458,623,Male,disloyal Customer,39,Business travel,Business,309,2,2,2,1,1,2,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +1459,123379,Female,Loyal Customer,49,Business travel,Business,2063,2,2,5,2,5,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +1460,121372,Female,Loyal Customer,12,Personal Travel,Eco Plus,1670,2,3,2,1,5,2,5,5,5,2,5,1,4,5,0,0.0,neutral or dissatisfied +1461,29324,Female,Loyal Customer,62,Personal Travel,Eco,834,2,5,2,4,3,5,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +1462,126024,Female,disloyal Customer,21,Business travel,Eco,468,5,0,5,4,1,5,4,1,4,2,4,3,5,1,30,19.0,satisfied +1463,4967,Female,Loyal Customer,52,Personal Travel,Eco,931,2,4,2,4,4,5,4,3,3,2,3,5,3,3,9,0.0,neutral or dissatisfied +1464,5346,Female,Loyal Customer,26,Business travel,Eco,812,2,5,2,5,1,1,2,2,4,4,3,2,2,2,125,154.0,neutral or dissatisfied +1465,57729,Female,Loyal Customer,25,Business travel,Business,1754,1,1,1,1,5,5,5,5,4,2,5,4,5,5,5,3.0,satisfied +1466,25816,Male,Loyal Customer,72,Business travel,Business,1747,1,3,3,3,5,1,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +1467,74564,Male,Loyal Customer,27,Business travel,Eco,1235,4,1,1,1,4,4,4,1,1,3,4,4,2,4,391,354.0,neutral or dissatisfied +1468,63540,Male,Loyal Customer,62,Personal Travel,Eco,1009,2,5,2,3,5,2,4,5,3,3,5,3,5,5,28,24.0,neutral or dissatisfied +1469,24794,Female,Loyal Customer,47,Personal Travel,Eco,447,1,4,1,4,4,3,3,3,3,1,3,4,3,2,1,6.0,neutral or dissatisfied +1470,122538,Female,Loyal Customer,38,Business travel,Business,3453,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +1471,103582,Male,Loyal Customer,40,Business travel,Business,689,3,3,3,3,4,4,4,5,5,5,5,5,5,4,11,0.0,satisfied +1472,56611,Male,Loyal Customer,25,Business travel,Business,2803,1,3,3,3,1,1,1,1,4,5,3,2,4,1,10,14.0,neutral or dissatisfied +1473,28420,Female,Loyal Customer,51,Business travel,Eco,1399,4,3,3,3,4,5,2,4,4,4,4,3,4,2,0,0.0,satisfied +1474,4202,Female,Loyal Customer,59,Business travel,Business,888,1,1,1,1,5,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +1475,51912,Male,Loyal Customer,35,Personal Travel,Eco,507,3,3,3,4,3,3,3,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +1476,77455,Male,Loyal Customer,40,Business travel,Business,507,3,5,3,3,4,4,4,4,4,4,4,4,4,3,26,16.0,satisfied +1477,34384,Female,Loyal Customer,52,Business travel,Eco,728,4,1,1,1,2,2,4,4,4,4,4,4,4,5,0,0.0,satisfied +1478,108583,Female,Loyal Customer,58,Business travel,Business,2255,3,3,3,3,4,4,5,5,5,5,5,5,5,5,2,9.0,satisfied +1479,47534,Female,Loyal Customer,49,Personal Travel,Eco,558,3,2,3,3,2,4,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +1480,56356,Male,Loyal Customer,34,Personal Travel,Eco,200,3,1,3,3,2,3,2,2,2,2,2,1,3,2,0,0.0,neutral or dissatisfied +1481,120922,Male,Loyal Customer,51,Business travel,Business,920,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,1.0,satisfied +1482,58177,Female,disloyal Customer,39,Business travel,Business,925,1,1,1,2,2,1,2,2,1,2,2,4,3,2,0,6.0,neutral or dissatisfied +1483,118731,Female,Loyal Customer,46,Personal Travel,Eco,304,3,4,3,4,3,4,5,4,4,3,4,5,4,4,9,7.0,neutral or dissatisfied +1484,90511,Male,disloyal Customer,25,Business travel,Business,646,5,0,5,3,1,5,1,1,3,2,4,4,5,1,0,0.0,satisfied +1485,97971,Male,Loyal Customer,13,Personal Travel,Eco,401,5,5,5,1,5,5,5,5,5,2,5,5,4,5,0,0.0,satisfied +1486,125628,Male,Loyal Customer,35,Business travel,Business,2521,1,4,4,4,1,4,3,1,1,1,1,4,1,2,0,1.0,neutral or dissatisfied +1487,27597,Male,Loyal Customer,60,Personal Travel,Eco,697,2,5,2,5,2,2,2,2,2,1,1,2,4,2,0,7.0,neutral or dissatisfied +1488,63620,Male,Loyal Customer,32,Personal Travel,Eco,1440,5,4,5,5,1,4,1,1,5,5,4,3,5,1,0,0.0,satisfied +1489,7313,Female,Loyal Customer,67,Business travel,Eco Plus,135,4,3,3,3,1,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +1490,60808,Female,disloyal Customer,27,Business travel,Business,455,1,1,1,1,2,1,2,2,5,4,4,5,5,2,0,40.0,neutral or dissatisfied +1491,60691,Male,disloyal Customer,30,Business travel,Business,1605,3,2,2,3,1,2,1,1,4,5,4,3,5,1,9,1.0,neutral or dissatisfied +1492,59181,Female,Loyal Customer,22,Business travel,Business,1440,2,2,2,2,4,4,4,4,4,4,4,4,5,4,26,37.0,satisfied +1493,12914,Male,Loyal Customer,60,Business travel,Eco,563,3,4,4,4,3,3,3,3,4,3,4,4,3,3,15,5.0,neutral or dissatisfied +1494,116840,Female,Loyal Customer,53,Business travel,Business,451,2,4,4,4,3,4,4,2,2,2,2,4,2,4,22,20.0,neutral or dissatisfied +1495,69667,Female,Loyal Customer,59,Personal Travel,Eco,569,2,5,2,2,4,1,5,2,2,2,2,1,2,1,31,19.0,neutral or dissatisfied +1496,25165,Male,Loyal Customer,40,Business travel,Business,3858,1,1,1,1,4,1,5,3,3,3,3,4,3,3,0,0.0,satisfied +1497,44810,Male,Loyal Customer,53,Business travel,Eco,1041,3,5,5,5,3,3,3,3,4,2,3,2,3,3,84,52.0,neutral or dissatisfied +1498,61480,Female,Loyal Customer,25,Business travel,Business,2419,1,2,2,2,1,1,1,1,1,3,2,1,3,1,0,5.0,neutral or dissatisfied +1499,18837,Male,Loyal Customer,57,Business travel,Eco,448,4,3,3,3,4,4,4,4,4,1,3,3,2,4,0,0.0,satisfied +1500,14815,Female,Loyal Customer,58,Business travel,Eco Plus,95,2,2,2,2,2,1,4,2,2,2,2,5,2,5,0,0.0,satisfied +1501,99451,Female,Loyal Customer,49,Business travel,Business,2149,1,1,1,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +1502,26730,Female,Loyal Customer,35,Business travel,Eco Plus,515,4,4,4,4,4,4,4,4,4,1,1,4,5,4,138,138.0,satisfied +1503,72833,Female,disloyal Customer,49,Business travel,Business,1013,1,2,2,5,4,1,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +1504,35839,Male,Loyal Customer,31,Business travel,Business,1068,1,5,5,5,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +1505,85083,Male,Loyal Customer,48,Business travel,Business,696,2,2,4,2,5,4,4,3,3,3,3,4,3,4,2,0.0,satisfied +1506,30869,Male,Loyal Customer,22,Business travel,Business,1546,1,1,1,1,4,4,4,4,5,3,4,2,4,4,1,0.0,satisfied +1507,68537,Male,Loyal Customer,56,Business travel,Eco,1013,3,4,4,4,3,3,3,3,4,5,3,3,4,3,13,7.0,neutral or dissatisfied +1508,128680,Male,Loyal Customer,28,Personal Travel,Eco,2419,1,5,1,1,1,3,2,3,5,3,4,2,5,2,0,0.0,neutral or dissatisfied +1509,22701,Female,Loyal Customer,34,Personal Travel,Eco,589,2,5,2,1,1,2,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +1510,648,Male,disloyal Customer,21,Business travel,Eco,396,3,0,3,2,2,3,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +1511,118114,Female,Loyal Customer,68,Business travel,Eco,900,5,1,1,1,2,4,2,5,5,5,5,5,5,4,0,0.0,satisfied +1512,126525,Male,Loyal Customer,61,Personal Travel,Eco Plus,196,1,5,1,2,5,1,5,5,1,4,4,5,5,5,2,16.0,neutral or dissatisfied +1513,19161,Female,disloyal Customer,42,Business travel,Eco,304,4,2,4,3,2,4,4,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +1514,115947,Male,Loyal Customer,12,Personal Travel,Eco,447,5,5,2,3,3,2,5,3,4,3,2,3,5,3,102,93.0,satisfied +1515,30140,Male,Loyal Customer,42,Personal Travel,Eco,160,4,3,4,3,2,4,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +1516,90391,Male,Loyal Customer,24,Personal Travel,Business,271,0,1,0,3,4,0,4,4,2,3,3,1,4,4,5,0.0,satisfied +1517,101207,Female,Loyal Customer,32,Personal Travel,Eco,1235,3,5,3,2,4,3,4,4,4,4,4,4,5,4,0,2.0,neutral or dissatisfied +1518,97585,Male,Loyal Customer,30,Personal Travel,Eco,337,3,4,3,3,2,3,4,2,4,2,5,4,4,2,30,22.0,neutral or dissatisfied +1519,84479,Female,disloyal Customer,36,Business travel,Business,2677,3,3,3,3,3,3,3,3,5,5,3,3,4,3,0,0.0,neutral or dissatisfied +1520,100862,Female,Loyal Customer,53,Business travel,Business,1605,3,3,3,3,3,3,5,4,4,4,4,3,4,5,0,21.0,satisfied +1521,104965,Female,Loyal Customer,39,Business travel,Business,2904,5,5,5,5,2,4,4,5,5,4,5,5,5,3,6,23.0,satisfied +1522,34543,Male,Loyal Customer,29,Business travel,Business,1598,5,5,5,5,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +1523,44756,Male,Loyal Customer,36,Personal Travel,Eco,589,1,4,2,4,4,2,3,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +1524,2808,Female,disloyal Customer,23,Business travel,Eco Plus,764,2,0,2,4,2,2,2,2,4,3,5,1,1,2,0,0.0,neutral or dissatisfied +1525,55878,Male,Loyal Customer,36,Business travel,Business,733,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +1526,73367,Female,Loyal Customer,38,Business travel,Business,2570,4,4,4,4,2,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +1527,74797,Female,Loyal Customer,48,Business travel,Business,2091,4,4,4,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +1528,51402,Female,Loyal Customer,31,Personal Travel,Eco Plus,109,2,2,2,3,4,2,3,4,4,3,3,4,3,4,25,17.0,neutral or dissatisfied +1529,71178,Male,Loyal Customer,39,Business travel,Business,733,2,5,5,5,2,4,3,2,2,2,2,2,2,3,11,,neutral or dissatisfied +1530,60445,Male,Loyal Customer,43,Business travel,Business,3687,2,2,1,2,2,4,4,4,4,4,4,4,4,3,70,61.0,satisfied +1531,20052,Male,Loyal Customer,40,Business travel,Eco,207,4,5,5,5,4,3,4,4,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +1532,6544,Male,Loyal Customer,53,Personal Travel,Business,473,3,4,3,5,5,2,2,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +1533,572,Male,disloyal Customer,64,Business travel,Business,282,3,3,3,3,4,3,3,4,3,2,3,2,4,4,0,0.0,neutral or dissatisfied +1534,108243,Female,disloyal Customer,32,Business travel,Business,895,1,1,1,3,2,1,2,2,5,2,5,3,4,2,10,2.0,neutral or dissatisfied +1535,125423,Female,Loyal Customer,44,Business travel,Business,735,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +1536,92598,Female,Loyal Customer,19,Business travel,Business,2158,4,1,3,1,4,4,4,4,4,3,4,4,3,4,35,27.0,neutral or dissatisfied +1537,78532,Female,Loyal Customer,63,Personal Travel,Eco,666,2,1,2,4,5,4,3,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +1538,26676,Male,Loyal Customer,7,Personal Travel,Eco,515,4,4,2,4,1,2,1,1,5,2,4,3,5,1,10,0.0,neutral or dissatisfied +1539,54,Male,Loyal Customer,40,Business travel,Business,2853,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +1540,27765,Female,disloyal Customer,44,Business travel,Eco,1448,2,2,2,5,5,2,5,5,1,5,4,1,1,5,0,0.0,neutral or dissatisfied +1541,724,Male,Loyal Customer,45,Business travel,Business,3934,2,2,4,2,1,2,2,1,1,1,2,2,1,4,0,0.0,neutral or dissatisfied +1542,105173,Female,Loyal Customer,12,Personal Travel,Eco,289,2,4,2,3,1,2,1,1,4,3,5,3,4,1,1,0.0,neutral or dissatisfied +1543,84681,Female,disloyal Customer,16,Business travel,Eco,1464,1,1,1,3,1,1,2,1,3,1,4,4,4,1,5,28.0,neutral or dissatisfied +1544,125038,Male,disloyal Customer,21,Business travel,Eco,1202,3,3,3,3,3,3,3,4,1,2,4,3,2,3,7,32.0,neutral or dissatisfied +1545,38551,Male,disloyal Customer,35,Business travel,Eco,1152,2,2,2,2,1,2,1,1,2,2,1,3,1,1,0,0.0,neutral or dissatisfied +1546,83080,Male,Loyal Customer,53,Business travel,Eco,583,5,3,3,3,4,5,4,4,1,1,3,1,3,4,1,8.0,satisfied +1547,49286,Male,Loyal Customer,33,Business travel,Business,109,3,3,3,3,4,4,5,4,2,3,4,4,5,4,0,1.0,satisfied +1548,116830,Male,Loyal Customer,43,Business travel,Business,3802,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +1549,63965,Female,Loyal Customer,56,Business travel,Business,1682,5,5,5,5,4,4,5,5,5,5,5,5,5,4,0,3.0,satisfied +1550,126654,Female,Loyal Customer,7,Personal Travel,Eco,602,3,2,3,4,3,3,3,3,4,5,4,3,4,3,0,4.0,neutral or dissatisfied +1551,66822,Female,Loyal Customer,42,Business travel,Business,2500,5,5,5,5,2,5,4,5,5,5,5,4,5,5,85,75.0,satisfied +1552,79070,Female,Loyal Customer,25,Business travel,Eco,356,3,2,2,2,3,3,1,3,1,2,1,1,2,3,0,24.0,neutral or dissatisfied +1553,66385,Male,disloyal Customer,37,Business travel,Business,1562,3,3,3,3,4,3,5,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +1554,31441,Male,Loyal Customer,25,Business travel,Eco,1541,0,5,0,2,2,5,2,2,5,1,1,3,2,2,28,22.0,satisfied +1555,345,Male,Loyal Customer,9,Personal Travel,Eco,853,1,1,1,2,2,1,4,2,4,5,3,3,2,2,23,17.0,neutral or dissatisfied +1556,122391,Female,Loyal Customer,68,Personal Travel,Eco,529,2,4,2,2,5,5,4,3,3,2,3,2,3,5,0,0.0,neutral or dissatisfied +1557,14185,Female,disloyal Customer,17,Business travel,Eco,714,1,1,1,1,5,1,5,5,3,3,2,5,5,5,14,9.0,neutral or dissatisfied +1558,22414,Female,disloyal Customer,18,Business travel,Eco,143,2,3,2,4,1,2,1,1,4,4,5,1,5,1,0,5.0,neutral or dissatisfied +1559,128342,Female,Loyal Customer,51,Business travel,Business,2318,1,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +1560,36866,Male,Loyal Customer,40,Personal Travel,Eco,273,2,5,2,2,2,2,2,2,3,1,4,3,4,2,0,5.0,neutral or dissatisfied +1561,24989,Female,Loyal Customer,55,Business travel,Eco,692,2,4,4,4,1,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +1562,29576,Female,Loyal Customer,37,Business travel,Business,1448,5,5,5,5,5,5,4,5,5,5,5,5,5,2,0,0.0,satisfied +1563,101347,Female,Loyal Customer,17,Personal Travel,Eco,2026,3,4,3,2,2,3,2,2,4,3,4,4,5,2,22,12.0,neutral or dissatisfied +1564,124722,Female,Loyal Customer,27,Personal Travel,Eco,399,3,4,3,3,1,3,1,1,3,4,5,4,5,1,0,80.0,neutral or dissatisfied +1565,61125,Female,Loyal Customer,46,Business travel,Business,967,3,3,3,3,5,5,4,4,4,4,4,4,4,3,3,16.0,satisfied +1566,84166,Female,disloyal Customer,21,Business travel,Eco,231,2,0,2,3,1,2,1,1,4,2,4,3,5,1,0,0.0,neutral or dissatisfied +1567,87276,Female,disloyal Customer,33,Business travel,Business,577,2,2,2,3,4,2,3,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +1568,98810,Female,Loyal Customer,41,Business travel,Business,763,4,4,4,4,4,4,5,4,4,4,4,3,4,3,3,0.0,satisfied +1569,37071,Male,disloyal Customer,28,Business travel,Business,1188,1,2,2,3,3,2,4,3,3,1,4,4,2,3,0,0.0,neutral or dissatisfied +1570,41247,Female,Loyal Customer,48,Personal Travel,Eco,643,2,4,2,2,3,4,4,5,5,2,5,4,5,3,7,8.0,neutral or dissatisfied +1571,66358,Female,Loyal Customer,61,Business travel,Eco,986,2,5,5,5,2,3,2,2,2,2,2,1,2,3,17,11.0,neutral or dissatisfied +1572,62949,Female,Loyal Customer,58,Business travel,Business,3529,5,5,4,5,4,5,4,4,4,4,4,4,4,5,9,2.0,satisfied +1573,9050,Male,Loyal Customer,38,Business travel,Business,1619,2,4,4,4,5,4,4,2,2,2,2,2,2,2,47,39.0,neutral or dissatisfied +1574,11606,Female,Loyal Customer,59,Personal Travel,Eco,468,2,4,2,2,1,2,3,5,5,2,5,5,5,2,4,0.0,neutral or dissatisfied +1575,118301,Female,Loyal Customer,24,Business travel,Business,3410,5,5,5,5,4,4,4,4,3,2,4,4,4,4,0,0.0,satisfied +1576,32719,Male,Loyal Customer,46,Business travel,Eco,163,5,4,4,4,5,5,5,5,1,4,2,1,2,5,0,0.0,satisfied +1577,52943,Female,Loyal Customer,49,Business travel,Eco Plus,679,4,5,5,5,2,1,1,4,4,4,4,4,4,4,0,0.0,satisfied +1578,79471,Female,disloyal Customer,15,Business travel,Eco,1183,3,3,3,4,4,3,1,4,4,1,4,2,3,4,34,41.0,neutral or dissatisfied +1579,89316,Female,Loyal Customer,70,Personal Travel,Business,1587,3,4,3,3,2,4,4,5,5,3,2,5,5,5,52,31.0,neutral or dissatisfied +1580,108588,Female,Loyal Customer,44,Business travel,Business,696,5,5,5,5,5,4,4,4,4,4,4,3,4,3,21,26.0,satisfied +1581,1626,Female,Loyal Customer,47,Business travel,Business,999,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +1582,27153,Female,disloyal Customer,24,Business travel,Eco,2640,1,1,1,4,1,5,5,4,3,3,4,5,4,5,0,33.0,neutral or dissatisfied +1583,103994,Male,Loyal Customer,31,Business travel,Business,1363,1,1,1,1,4,4,4,4,3,3,5,5,4,4,29,15.0,satisfied +1584,37592,Female,disloyal Customer,30,Business travel,Eco,1069,2,2,2,4,5,2,5,5,2,4,3,1,3,5,28,23.0,neutral or dissatisfied +1585,103408,Female,disloyal Customer,38,Business travel,Eco,237,2,1,2,3,2,3,2,4,3,2,3,2,4,2,196,214.0,neutral or dissatisfied +1586,72953,Male,Loyal Customer,33,Business travel,Business,2445,4,4,4,4,4,4,4,4,3,3,4,5,5,4,0,0.0,satisfied +1587,106645,Female,Loyal Customer,43,Business travel,Business,3936,3,3,3,3,5,5,4,4,4,4,4,3,4,4,16,17.0,satisfied +1588,115998,Female,Loyal Customer,41,Personal Travel,Eco,372,2,4,3,5,2,3,2,2,3,2,5,4,4,2,0,14.0,neutral or dissatisfied +1589,37062,Male,Loyal Customer,20,Business travel,Business,3372,3,3,3,3,5,5,5,5,4,4,3,1,1,5,5,0.0,satisfied +1590,99461,Male,Loyal Customer,57,Business travel,Business,283,3,3,3,3,5,4,5,3,3,4,3,4,3,3,9,1.0,satisfied +1591,120454,Female,Loyal Customer,53,Personal Travel,Eco,366,2,4,2,2,3,5,5,2,2,2,2,1,2,5,83,83.0,neutral or dissatisfied +1592,6833,Male,Loyal Customer,33,Personal Travel,Eco,137,4,1,0,3,5,0,4,5,1,2,4,1,3,5,16,17.0,neutral or dissatisfied +1593,86291,Male,Loyal Customer,61,Personal Travel,Eco,356,4,2,3,3,3,3,2,3,3,5,3,4,3,3,2,4.0,neutral or dissatisfied +1594,70596,Female,Loyal Customer,46,Business travel,Business,2611,4,4,4,4,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +1595,3434,Female,Loyal Customer,57,Personal Travel,Eco,240,1,4,0,2,4,4,5,1,1,0,1,4,1,4,0,2.0,neutral or dissatisfied +1596,54096,Female,Loyal Customer,50,Personal Travel,Eco,1416,1,4,1,1,3,5,4,3,3,1,4,5,3,3,13,0.0,neutral or dissatisfied +1597,123751,Male,Loyal Customer,59,Business travel,Business,1971,0,4,0,2,3,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +1598,88288,Female,Loyal Customer,40,Business travel,Business,444,2,2,2,2,4,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +1599,51598,Male,disloyal Customer,25,Business travel,Eco,370,3,0,3,2,3,3,3,3,5,5,1,1,3,3,0,0.0,neutral or dissatisfied +1600,36438,Female,Loyal Customer,29,Personal Travel,Eco,369,1,1,1,4,4,1,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +1601,52606,Male,Loyal Customer,35,Business travel,Eco,119,5,5,3,5,5,5,5,5,5,2,3,1,2,5,0,0.0,satisfied +1602,6987,Female,Loyal Customer,34,Business travel,Business,1903,5,5,5,5,4,4,5,5,5,5,5,3,5,3,12,8.0,satisfied +1603,13545,Male,disloyal Customer,27,Business travel,Business,227,3,3,3,4,2,3,2,2,4,4,4,2,4,2,0,8.0,neutral or dissatisfied +1604,29602,Male,Loyal Customer,25,Business travel,Business,1709,5,5,5,5,3,4,3,3,5,3,2,3,5,3,0,0.0,satisfied +1605,104614,Male,Loyal Customer,68,Personal Travel,Eco Plus,369,1,2,4,3,2,4,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +1606,31371,Male,Loyal Customer,43,Business travel,Eco,977,2,3,3,3,2,2,2,2,4,3,2,4,3,2,5,10.0,neutral or dissatisfied +1607,79357,Male,Loyal Customer,16,Personal Travel,Eco,1020,4,4,4,3,2,4,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +1608,68285,Male,Loyal Customer,53,Business travel,Business,3472,2,5,5,5,4,3,3,2,2,2,2,3,2,2,6,38.0,neutral or dissatisfied +1609,107805,Female,disloyal Customer,20,Business travel,Eco,349,0,1,0,3,1,0,4,1,5,5,4,4,4,1,9,0.0,satisfied +1610,61490,Female,Loyal Customer,67,Business travel,Business,2288,1,3,5,5,5,2,2,1,1,1,1,3,1,1,92,78.0,neutral or dissatisfied +1611,104490,Male,disloyal Customer,34,Business travel,Eco,860,3,3,3,1,3,3,3,3,1,5,2,1,5,3,0,0.0,neutral or dissatisfied +1612,77862,Female,Loyal Customer,58,Personal Travel,Eco Plus,689,3,5,3,3,5,4,4,2,2,3,1,5,2,5,0,0.0,neutral or dissatisfied +1613,20905,Male,Loyal Customer,43,Business travel,Business,803,3,3,3,3,3,2,2,5,5,5,5,1,5,5,0,0.0,satisfied +1614,28980,Female,Loyal Customer,31,Business travel,Business,937,4,4,4,4,5,5,5,5,1,5,4,2,4,5,29,31.0,satisfied +1615,86246,Female,Loyal Customer,17,Personal Travel,Eco,356,4,4,4,3,5,4,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +1616,81750,Female,disloyal Customer,27,Business travel,Business,1310,4,4,4,5,3,4,5,3,3,5,5,5,5,3,0,0.0,satisfied +1617,87702,Male,Loyal Customer,37,Personal Travel,Eco,606,4,4,4,4,3,4,3,3,1,3,4,1,4,3,0,0.0,satisfied +1618,67831,Female,disloyal Customer,54,Business travel,Eco,1031,5,5,5,4,4,5,4,4,5,3,1,5,3,4,0,8.0,satisfied +1619,68217,Male,Loyal Customer,32,Business travel,Business,1904,4,4,4,4,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +1620,38966,Female,Loyal Customer,51,Business travel,Business,3461,0,0,0,1,5,1,4,4,4,4,4,1,4,1,13,0.0,satisfied +1621,93108,Female,Loyal Customer,40,Personal Travel,Eco Plus,641,5,4,5,4,4,5,4,4,3,2,4,5,5,4,13,0.0,satisfied +1622,113400,Male,disloyal Customer,26,Business travel,Business,386,1,0,1,4,3,1,3,3,3,2,5,4,5,3,1,10.0,neutral or dissatisfied +1623,60747,Male,Loyal Customer,45,Business travel,Business,628,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +1624,55988,Female,Loyal Customer,44,Business travel,Business,2475,2,2,2,2,2,2,2,5,2,5,5,2,5,2,0,12.0,satisfied +1625,72178,Male,Loyal Customer,29,Business travel,Business,594,2,2,4,2,5,5,5,5,5,2,5,3,5,5,0,4.0,satisfied +1626,117305,Female,disloyal Customer,33,Business travel,Eco Plus,338,1,1,1,3,1,1,1,1,3,3,2,3,2,1,17,8.0,neutral or dissatisfied +1627,37889,Male,Loyal Customer,54,Business travel,Eco,937,2,2,2,2,2,2,2,2,2,2,2,2,3,2,13,9.0,neutral or dissatisfied +1628,34871,Female,Loyal Customer,40,Business travel,Business,2248,2,2,2,2,3,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +1629,92768,Female,Loyal Customer,44,Business travel,Business,1671,4,4,4,4,4,3,4,4,4,4,4,4,4,5,25,18.0,satisfied +1630,119464,Male,disloyal Customer,40,Business travel,Business,857,2,2,2,3,4,2,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +1631,10537,Female,Loyal Customer,48,Business travel,Business,163,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1632,53491,Male,Loyal Customer,50,Personal Travel,Eco,2358,1,4,1,5,1,4,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +1633,121455,Female,Loyal Customer,33,Business travel,Eco,257,0,0,0,4,3,0,3,3,3,1,3,2,3,3,0,0.0,satisfied +1634,67545,Female,Loyal Customer,63,Personal Travel,Business,1431,3,1,3,4,4,3,3,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +1635,1314,Male,Loyal Customer,34,Business travel,Business,247,0,0,0,3,4,5,5,3,3,1,1,4,3,5,0,0.0,satisfied +1636,94600,Female,Loyal Customer,23,Business travel,Business,1842,0,0,0,2,3,3,3,3,5,3,4,4,4,3,8,0.0,satisfied +1637,7171,Female,disloyal Customer,25,Business travel,Eco,116,2,1,2,3,2,4,4,1,3,4,3,4,2,4,140,133.0,neutral or dissatisfied +1638,46310,Male,Loyal Customer,34,Business travel,Business,2322,3,3,3,3,1,4,4,5,5,5,5,2,5,3,0,0.0,satisfied +1639,123935,Male,Loyal Customer,47,Personal Travel,Eco,546,4,5,4,3,4,4,4,4,2,5,2,4,4,4,0,14.0,neutral or dissatisfied +1640,105931,Male,Loyal Customer,37,Business travel,Business,1491,3,4,4,4,5,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +1641,33450,Male,Loyal Customer,61,Personal Travel,Eco,2462,3,4,3,3,1,3,1,1,4,5,5,4,4,1,0,2.0,neutral or dissatisfied +1642,80905,Male,Loyal Customer,63,Business travel,Business,2621,2,2,3,2,5,5,5,5,5,5,5,5,5,5,8,7.0,satisfied +1643,7788,Male,Loyal Customer,43,Business travel,Business,3048,5,5,5,5,4,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +1644,98656,Male,Loyal Customer,16,Personal Travel,Eco,920,0,4,0,3,4,0,4,4,4,2,5,5,4,4,4,14.0,satisfied +1645,95371,Female,Loyal Customer,46,Personal Travel,Eco,187,1,4,1,2,5,4,5,1,1,1,1,4,1,4,9,3.0,neutral or dissatisfied +1646,79030,Female,Loyal Customer,47,Business travel,Business,226,3,2,4,2,5,3,3,3,3,3,3,1,3,3,22,12.0,neutral or dissatisfied +1647,4517,Female,disloyal Customer,20,Business travel,Eco,435,3,2,3,3,5,3,5,5,1,3,3,1,4,5,0,0.0,neutral or dissatisfied +1648,57978,Male,disloyal Customer,26,Business travel,Business,589,3,3,3,1,4,3,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +1649,25412,Male,Loyal Customer,11,Personal Travel,Eco,1105,4,3,3,3,2,3,2,2,2,3,4,3,4,2,13,18.0,neutral or dissatisfied +1650,61713,Male,disloyal Customer,28,Business travel,Eco,1220,4,4,4,3,3,4,3,3,4,5,3,3,2,3,20,9.0,neutral or dissatisfied +1651,52626,Male,Loyal Customer,34,Business travel,Eco,160,4,3,3,3,4,4,4,4,1,3,4,3,2,4,0,7.0,satisfied +1652,127542,Male,Loyal Customer,11,Business travel,Business,3187,4,2,1,2,4,4,4,4,2,2,3,4,4,4,1,0.0,neutral or dissatisfied +1653,88620,Female,Loyal Customer,43,Personal Travel,Eco,444,3,4,3,1,2,4,5,1,1,3,1,3,1,4,7,10.0,neutral or dissatisfied +1654,64550,Male,Loyal Customer,37,Business travel,Business,3476,3,3,3,3,3,4,4,3,3,4,3,3,3,4,2,0.0,satisfied +1655,48895,Male,Loyal Customer,41,Business travel,Eco,262,3,4,4,4,3,3,3,3,1,3,2,2,4,3,0,0.0,satisfied +1656,38449,Male,Loyal Customer,44,Business travel,Business,3187,2,2,2,2,2,3,5,5,5,5,5,1,5,1,0,0.0,satisfied +1657,65560,Female,Loyal Customer,49,Business travel,Business,3043,0,0,0,3,4,4,4,3,3,3,2,3,3,5,0,0.0,satisfied +1658,32993,Male,Loyal Customer,70,Personal Travel,Eco,102,2,5,2,3,4,2,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +1659,13502,Male,Loyal Customer,53,Business travel,Business,3316,4,4,3,4,5,1,5,4,4,4,3,1,4,3,0,0.0,satisfied +1660,2173,Female,Loyal Customer,41,Business travel,Business,3108,3,1,1,1,3,3,3,3,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +1661,48856,Male,Loyal Customer,36,Business travel,Business,3635,5,5,5,5,4,2,4,4,4,4,4,1,4,1,26,32.0,satisfied +1662,59146,Male,Loyal Customer,17,Personal Travel,Eco,1744,1,5,1,5,3,1,3,3,4,2,4,4,5,3,71,69.0,neutral or dissatisfied +1663,31611,Male,Loyal Customer,32,Business travel,Business,3712,2,2,2,2,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +1664,51347,Male,Loyal Customer,42,Business travel,Eco Plus,110,4,4,4,4,4,4,4,4,1,4,5,2,5,4,0,0.0,satisfied +1665,6276,Male,Loyal Customer,23,Business travel,Business,585,1,2,1,2,1,1,1,1,1,3,3,3,4,1,37,47.0,neutral or dissatisfied +1666,63905,Male,Loyal Customer,39,Business travel,Business,3724,4,3,3,3,3,3,3,4,4,4,4,4,4,1,3,9.0,neutral or dissatisfied +1667,77054,Female,disloyal Customer,25,Business travel,Business,920,0,0,1,1,1,1,1,1,4,3,4,5,5,1,0,0.0,satisfied +1668,89004,Female,Loyal Customer,42,Business travel,Business,1947,2,2,2,2,2,4,4,4,4,4,4,4,4,4,29,20.0,satisfied +1669,105694,Female,Loyal Customer,54,Business travel,Business,3598,2,2,4,2,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +1670,35834,Female,Loyal Customer,34,Business travel,Business,1065,1,5,5,5,1,2,2,1,1,1,1,3,1,4,0,19.0,neutral or dissatisfied +1671,56536,Male,disloyal Customer,25,Business travel,Business,997,1,4,1,2,5,1,3,5,3,4,4,4,5,5,20,41.0,neutral or dissatisfied +1672,99710,Female,Loyal Customer,53,Business travel,Business,667,4,4,4,4,4,4,5,4,4,4,4,5,4,3,6,6.0,satisfied +1673,87573,Female,Loyal Customer,38,Business travel,Business,432,3,1,1,1,4,3,2,3,3,3,3,1,3,4,44,31.0,neutral or dissatisfied +1674,80180,Female,Loyal Customer,55,Personal Travel,Eco,2475,1,3,1,4,1,2,2,3,1,4,3,2,1,2,0,7.0,neutral or dissatisfied +1675,56048,Female,Loyal Customer,29,Business travel,Business,2586,3,3,3,3,2,2,2,4,2,5,5,2,2,2,0,8.0,satisfied +1676,107581,Female,disloyal Customer,27,Business travel,Business,1521,1,2,2,2,4,2,4,4,4,2,5,4,5,4,1,0.0,neutral or dissatisfied +1677,61166,Female,Loyal Customer,41,Business travel,Business,1624,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +1678,117683,Male,disloyal Customer,29,Business travel,Business,1070,5,5,5,5,3,0,3,3,4,3,4,5,5,3,2,0.0,satisfied +1679,57563,Male,Loyal Customer,29,Business travel,Business,1597,4,4,4,4,3,4,3,3,5,2,5,5,4,3,39,27.0,satisfied +1680,99619,Male,Loyal Customer,46,Business travel,Business,1224,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +1681,107647,Female,Loyal Customer,27,Business travel,Business,2227,4,4,4,4,5,5,5,5,3,4,5,3,5,5,0,0.0,satisfied +1682,74252,Male,Loyal Customer,67,Business travel,Business,2726,1,2,3,2,2,3,4,1,1,1,1,3,1,2,2,17.0,neutral or dissatisfied +1683,62533,Male,disloyal Customer,27,Business travel,Business,1744,0,0,0,2,1,0,1,1,3,5,4,3,4,1,10,0.0,satisfied +1684,71707,Male,Loyal Customer,45,Personal Travel,Eco Plus,1197,3,2,3,4,3,3,3,3,4,3,2,1,3,3,26,31.0,neutral or dissatisfied +1685,96560,Female,Loyal Customer,45,Business travel,Business,2270,2,2,2,2,2,4,5,5,5,5,5,5,5,3,1,3.0,satisfied +1686,14811,Female,Loyal Customer,20,Personal Travel,Eco,95,2,2,2,4,3,2,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +1687,122911,Male,Loyal Customer,50,Business travel,Business,3467,1,1,1,1,2,4,5,4,4,4,5,5,4,4,2,0.0,satisfied +1688,28742,Female,Loyal Customer,23,Business travel,Business,3306,4,4,4,4,5,5,5,5,4,1,5,3,2,5,0,0.0,satisfied +1689,107288,Male,disloyal Customer,19,Business travel,Eco,283,4,1,4,4,1,4,1,1,1,2,3,2,4,1,22,19.0,neutral or dissatisfied +1690,15304,Male,Loyal Customer,23,Business travel,Business,489,1,5,5,5,1,1,1,1,2,1,2,2,3,1,54,30.0,neutral or dissatisfied +1691,42439,Female,Loyal Customer,64,Personal Travel,Eco,1119,3,3,2,4,5,4,3,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +1692,73048,Male,Loyal Customer,28,Personal Travel,Eco,1089,1,1,0,4,5,0,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +1693,97924,Female,Loyal Customer,31,Business travel,Business,401,4,4,4,4,2,2,2,2,4,3,4,4,4,2,0,0.0,satisfied +1694,77121,Male,Loyal Customer,23,Personal Travel,Eco,1481,4,5,4,4,3,4,3,3,2,4,1,1,5,3,0,0.0,neutral or dissatisfied +1695,126248,Male,Loyal Customer,53,Business travel,Business,1502,3,3,3,3,5,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +1696,105452,Male,Loyal Customer,32,Business travel,Business,3200,3,5,5,5,3,3,3,3,4,2,3,3,3,3,45,40.0,neutral or dissatisfied +1697,125298,Female,Loyal Customer,57,Business travel,Business,3488,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +1698,81252,Male,Loyal Customer,40,Personal Travel,Business,1020,1,5,2,4,4,4,5,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +1699,122104,Male,Loyal Customer,35,Personal Travel,Eco,130,2,4,2,1,5,2,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +1700,27857,Male,Loyal Customer,24,Personal Travel,Eco,1448,5,2,5,3,3,5,3,3,3,4,4,1,3,3,0,4.0,satisfied +1701,81002,Female,Loyal Customer,51,Personal Travel,Eco,297,3,4,3,1,3,4,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +1702,99618,Male,disloyal Customer,22,Business travel,Business,1154,4,0,4,1,2,4,2,2,3,5,4,5,4,2,0,0.0,satisfied +1703,55360,Female,disloyal Customer,40,Business travel,Business,594,2,2,2,4,4,2,4,4,4,5,5,3,5,4,0,0.0,satisfied +1704,113171,Female,Loyal Customer,19,Personal Travel,Eco,889,4,5,4,1,3,4,3,3,3,3,4,3,5,3,6,11.0,satisfied +1705,121782,Female,Loyal Customer,61,Business travel,Business,3749,5,5,5,5,2,4,5,4,4,4,4,3,4,5,5,18.0,satisfied +1706,38897,Female,disloyal Customer,22,Business travel,Eco,320,4,5,4,1,5,4,5,5,4,2,4,4,3,5,0,14.0,satisfied +1707,38145,Male,Loyal Customer,50,Personal Travel,Eco,1121,4,5,4,3,4,4,4,4,5,4,4,3,4,4,0,5.0,neutral or dissatisfied +1708,62969,Male,Loyal Customer,20,Business travel,Business,862,3,3,3,3,5,5,5,5,4,4,4,5,4,5,0,9.0,satisfied +1709,47189,Female,Loyal Customer,29,Business travel,Business,965,3,4,4,4,3,3,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +1710,113800,Female,Loyal Customer,49,Business travel,Business,3428,3,3,5,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +1711,70782,Male,Loyal Customer,55,Business travel,Business,3412,2,5,5,5,1,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +1712,9604,Male,Loyal Customer,27,Personal Travel,Eco,288,2,4,2,2,5,2,5,5,5,5,4,5,4,5,21,23.0,neutral or dissatisfied +1713,31589,Female,disloyal Customer,25,Business travel,Eco,602,4,1,4,3,4,4,5,4,3,4,4,2,3,4,18,18.0,neutral or dissatisfied +1714,56134,Female,Loyal Customer,53,Business travel,Business,1400,4,4,4,4,4,4,4,4,4,4,4,3,4,5,12,22.0,satisfied +1715,12972,Female,Loyal Customer,59,Business travel,Business,1661,1,1,1,1,2,4,4,4,4,4,4,5,4,5,2,4.0,satisfied +1716,127983,Male,disloyal Customer,63,Business travel,Eco,749,3,3,3,3,1,3,1,1,2,2,4,2,4,1,0,17.0,neutral or dissatisfied +1717,56174,Male,Loyal Customer,56,Business travel,Eco,1000,1,1,1,1,1,1,1,1,1,1,4,4,4,1,88,125.0,neutral or dissatisfied +1718,116298,Female,Loyal Customer,51,Personal Travel,Eco,417,3,5,3,1,3,1,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +1719,77985,Female,Loyal Customer,60,Business travel,Eco,332,3,5,5,5,1,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +1720,25107,Male,Loyal Customer,40,Business travel,Business,946,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +1721,126039,Female,Loyal Customer,40,Business travel,Business,468,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,3.0,satisfied +1722,2224,Female,Loyal Customer,41,Business travel,Business,642,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,12.0,satisfied +1723,58557,Female,Loyal Customer,40,Personal Travel,Eco,1514,4,4,4,3,1,4,3,1,3,4,3,4,5,1,15,10.0,neutral or dissatisfied +1724,35672,Male,Loyal Customer,34,Business travel,Business,2475,2,3,2,2,4,4,4,1,1,4,1,4,3,4,0,0.0,satisfied +1725,1790,Female,disloyal Customer,27,Business travel,Business,500,4,5,5,4,3,5,3,3,3,2,5,5,4,3,0,0.0,satisfied +1726,6976,Male,Loyal Customer,55,Business travel,Business,234,3,3,3,3,4,4,5,4,4,4,4,4,4,3,0,5.0,satisfied +1727,125953,Male,Loyal Customer,54,Business travel,Business,1013,5,5,5,5,5,5,4,2,2,2,2,5,2,3,9,3.0,satisfied +1728,101640,Female,Loyal Customer,45,Business travel,Business,1733,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +1729,121004,Female,Loyal Customer,62,Personal Travel,Eco,861,3,4,3,3,4,5,4,4,4,3,1,3,4,3,10,17.0,neutral or dissatisfied +1730,83846,Male,Loyal Customer,69,Personal Travel,Eco,425,3,1,3,2,2,3,2,2,1,1,2,3,3,2,0,0.0,neutral or dissatisfied +1731,122445,Male,disloyal Customer,50,Business travel,Business,575,4,4,4,4,3,4,3,3,3,4,4,5,5,3,0,0.0,satisfied +1732,72245,Male,Loyal Customer,57,Business travel,Business,2844,1,1,1,1,3,4,5,4,4,4,4,4,4,3,56,41.0,satisfied +1733,116814,Female,Loyal Customer,26,Business travel,Business,3005,1,1,1,1,5,5,5,5,4,4,5,5,4,5,11,0.0,satisfied +1734,36541,Female,Loyal Customer,42,Business travel,Eco,1121,4,4,4,4,3,2,1,4,4,4,4,4,4,1,24,21.0,satisfied +1735,67369,Male,Loyal Customer,36,Business travel,Business,1652,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1736,73865,Female,Loyal Customer,41,Business travel,Business,2585,1,1,1,1,4,4,4,5,5,5,5,4,3,4,0,0.0,satisfied +1737,101040,Male,Loyal Customer,55,Business travel,Business,368,1,1,1,1,2,4,5,4,4,4,4,4,4,4,0,1.0,satisfied +1738,74672,Male,Loyal Customer,41,Personal Travel,Eco,1171,0,4,0,1,2,0,2,2,4,2,3,5,4,2,24,27.0,satisfied +1739,99763,Male,Loyal Customer,19,Personal Travel,Eco,255,2,4,2,4,3,2,3,3,1,1,3,1,2,3,0,3.0,neutral or dissatisfied +1740,34622,Male,Loyal Customer,44,Business travel,Eco,2454,4,1,1,1,4,4,4,3,4,5,4,4,5,4,0,0.0,satisfied +1741,24728,Male,Loyal Customer,8,Personal Travel,Eco,406,2,4,5,3,1,5,1,1,4,3,4,3,5,1,25,38.0,neutral or dissatisfied +1742,99280,Female,Loyal Customer,18,Business travel,Business,3277,4,4,2,4,4,4,4,4,4,3,4,4,3,4,26,15.0,neutral or dissatisfied +1743,52688,Female,Loyal Customer,44,Business travel,Eco Plus,160,5,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +1744,39864,Female,Loyal Customer,61,Business travel,Eco,272,4,5,5,5,2,5,4,4,4,4,4,1,4,2,0,0.0,satisfied +1745,75491,Female,disloyal Customer,34,Business travel,Business,2342,2,2,2,4,1,2,1,1,4,2,4,3,5,1,0,0.0,neutral or dissatisfied +1746,41909,Male,Loyal Customer,37,Business travel,Business,129,4,3,3,3,2,3,4,2,2,1,4,4,2,4,77,78.0,neutral or dissatisfied +1747,120670,Female,Loyal Customer,66,Business travel,Business,280,2,3,3,3,4,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +1748,81571,Female,Loyal Customer,57,Personal Travel,Eco,936,4,1,4,3,4,4,3,3,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +1749,89443,Female,Loyal Customer,34,Personal Travel,Eco,151,3,4,0,1,3,0,2,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +1750,123749,Male,Loyal Customer,44,Business travel,Eco Plus,96,4,1,1,1,4,4,4,4,4,3,3,3,4,4,0,1.0,neutral or dissatisfied +1751,30970,Female,Loyal Customer,16,Personal Travel,Business,1476,3,5,3,4,4,3,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +1752,122511,Male,Loyal Customer,49,Business travel,Business,3805,3,2,2,2,4,4,3,3,3,4,3,1,3,2,10,0.0,neutral or dissatisfied +1753,79995,Female,Loyal Customer,44,Personal Travel,Eco,1076,3,5,3,3,5,4,4,2,2,3,2,4,2,5,28,31.0,neutral or dissatisfied +1754,116226,Male,Loyal Customer,25,Personal Travel,Eco,337,2,4,2,4,3,2,3,3,4,4,4,2,3,3,12,2.0,neutral or dissatisfied +1755,68016,Female,disloyal Customer,28,Business travel,Business,280,3,3,3,1,4,3,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +1756,88328,Male,Loyal Customer,42,Business travel,Business,404,2,5,5,5,4,2,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +1757,117198,Female,Loyal Customer,53,Personal Travel,Eco,338,1,5,4,3,2,5,5,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +1758,38687,Female,Loyal Customer,33,Business travel,Eco Plus,2611,3,2,2,2,3,3,3,3,1,4,3,3,4,3,0,0.0,neutral or dissatisfied +1759,96493,Female,Loyal Customer,47,Business travel,Business,2744,3,3,3,3,5,3,2,3,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +1760,59461,Male,disloyal Customer,16,Business travel,Eco,758,4,4,4,4,3,4,2,3,4,2,4,4,4,3,2,0.0,neutral or dissatisfied +1761,23374,Male,Loyal Customer,16,Personal Travel,Eco,1014,2,4,2,4,1,2,1,1,3,5,4,5,5,1,91,120.0,neutral or dissatisfied +1762,69653,Female,disloyal Customer,21,Business travel,Eco,569,2,1,3,3,2,3,2,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +1763,13405,Male,disloyal Customer,18,Business travel,Business,491,5,0,5,3,1,5,1,1,3,3,4,4,4,1,0,0.0,satisfied +1764,122703,Female,Loyal Customer,30,Business travel,Eco Plus,361,1,4,4,4,1,1,1,1,4,2,3,2,3,1,1,0.0,neutral or dissatisfied +1765,72292,Female,Loyal Customer,23,Personal Travel,Eco,919,3,2,3,3,3,3,3,3,3,3,4,4,3,3,112,95.0,neutral or dissatisfied +1766,19474,Male,Loyal Customer,64,Business travel,Eco,177,2,2,2,2,2,2,2,2,3,3,3,4,2,2,1,0.0,neutral or dissatisfied +1767,14088,Male,Loyal Customer,65,Business travel,Business,425,3,4,4,4,3,3,4,3,3,3,3,4,3,2,0,2.0,neutral or dissatisfied +1768,121998,Male,Loyal Customer,54,Business travel,Business,185,3,3,4,3,5,4,5,5,5,5,4,5,5,3,25,24.0,satisfied +1769,124984,Male,Loyal Customer,59,Business travel,Business,184,4,4,4,4,5,5,5,3,3,4,4,3,3,4,0,0.0,satisfied +1770,89674,Male,Loyal Customer,45,Business travel,Eco,944,4,2,1,1,4,4,4,1,3,3,2,4,3,4,187,214.0,neutral or dissatisfied +1771,105723,Male,Loyal Customer,55,Business travel,Eco,663,2,4,5,5,2,2,2,2,2,3,3,4,3,2,19,7.0,neutral or dissatisfied +1772,84873,Male,Loyal Customer,41,Personal Travel,Eco,481,3,4,3,4,2,3,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +1773,111159,Male,Loyal Customer,14,Personal Travel,Eco,1050,4,4,4,1,3,4,3,3,4,3,1,3,1,3,11,0.0,neutral or dissatisfied +1774,82773,Male,Loyal Customer,8,Personal Travel,Eco Plus,409,4,5,4,2,5,4,5,5,4,4,5,3,5,5,0,0.0,satisfied +1775,22778,Female,disloyal Customer,48,Business travel,Eco,170,2,0,3,2,5,3,5,5,4,3,1,1,4,5,21,50.0,neutral or dissatisfied +1776,106793,Female,disloyal Customer,42,Business travel,Business,977,3,3,3,3,3,3,3,4,3,4,5,3,4,3,131,125.0,neutral or dissatisfied +1777,66432,Female,Loyal Customer,53,Business travel,Business,3643,5,5,5,5,4,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +1778,2784,Male,Loyal Customer,47,Business travel,Business,3065,3,2,2,2,3,2,2,3,3,3,3,2,3,1,57,54.0,neutral or dissatisfied +1779,44334,Male,Loyal Customer,37,Business travel,Eco,230,3,5,5,5,3,4,3,3,4,4,5,2,2,3,0,0.0,satisfied +1780,105174,Male,Loyal Customer,14,Personal Travel,Eco,220,1,5,1,3,5,1,5,5,4,5,3,4,5,5,11,1.0,neutral or dissatisfied +1781,129036,Male,Loyal Customer,40,Personal Travel,Business,1744,5,3,5,3,5,3,3,2,2,5,3,3,2,1,0,5.0,satisfied +1782,4601,Male,Loyal Customer,31,Personal Travel,Eco,416,2,5,2,4,3,2,3,3,1,3,4,5,2,3,0,1.0,neutral or dissatisfied +1783,125404,Female,Loyal Customer,49,Personal Travel,Eco,1440,3,4,3,4,4,5,5,1,1,3,1,5,1,3,25,38.0,neutral or dissatisfied +1784,64238,Male,disloyal Customer,44,Business travel,Business,1660,2,2,2,1,1,2,1,1,3,3,4,3,5,1,11,7.0,neutral or dissatisfied +1785,37229,Female,disloyal Customer,27,Business travel,Business,1028,3,3,3,3,3,1,4,1,2,3,4,4,1,4,170,164.0,neutral or dissatisfied +1786,32894,Female,Loyal Customer,26,Personal Travel,Eco,101,2,3,2,3,4,2,4,4,3,5,3,1,4,4,4,10.0,neutral or dissatisfied +1787,92601,Female,disloyal Customer,48,Business travel,Business,2158,4,4,4,3,4,4,4,4,3,5,4,3,5,4,12,0.0,satisfied +1788,42458,Male,Loyal Customer,58,Personal Travel,Eco,866,4,5,4,1,5,4,5,5,5,3,5,4,4,5,0,0.0,satisfied +1789,81057,Male,Loyal Customer,22,Personal Travel,Eco,1399,2,4,2,4,5,2,4,5,5,2,3,4,5,5,0,0.0,neutral or dissatisfied +1790,116563,Male,Loyal Customer,60,Business travel,Business,2259,5,5,4,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +1791,28716,Male,Loyal Customer,51,Business travel,Eco,1217,5,1,5,1,5,5,5,2,3,5,3,5,3,5,0,7.0,satisfied +1792,100696,Female,Loyal Customer,61,Personal Travel,Eco,628,2,4,2,4,2,4,3,1,1,2,1,4,1,1,20,6.0,neutral or dissatisfied +1793,119588,Male,Loyal Customer,67,Personal Travel,Eco,2276,3,2,3,4,3,4,4,4,4,2,4,4,1,4,0,5.0,neutral or dissatisfied +1794,76710,Female,disloyal Customer,21,Business travel,Eco,547,3,5,3,3,2,3,2,2,4,5,4,5,5,2,0,4.0,neutral or dissatisfied +1795,120333,Male,Loyal Customer,23,Business travel,Eco Plus,268,1,5,5,5,1,1,1,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +1796,28084,Male,Loyal Customer,51,Business travel,Eco,2172,5,3,3,3,5,5,5,5,5,4,3,5,4,5,0,0.0,satisfied +1797,43446,Male,Loyal Customer,43,Business travel,Business,2520,5,4,5,5,4,4,1,3,3,3,3,2,3,3,0,0.0,satisfied +1798,103072,Female,Loyal Customer,45,Business travel,Eco,146,2,3,3,3,4,4,4,2,2,2,2,1,2,1,1,4.0,neutral or dissatisfied +1799,77232,Female,Loyal Customer,21,Business travel,Business,1590,4,4,4,4,5,4,5,5,4,4,4,5,4,5,0,0.0,satisfied +1800,109837,Female,disloyal Customer,24,Business travel,Business,1130,4,0,4,1,4,4,4,4,4,5,5,3,5,4,26,15.0,satisfied +1801,90117,Male,Loyal Customer,35,Business travel,Business,1084,3,1,1,1,1,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +1802,42383,Male,Loyal Customer,66,Personal Travel,Eco,451,4,4,4,3,1,4,1,1,2,5,4,3,2,1,0,0.0,neutral or dissatisfied +1803,36445,Female,Loyal Customer,38,Business travel,Business,1368,2,2,2,2,2,4,4,3,3,3,3,5,3,3,4,2.0,satisfied +1804,78366,Male,Loyal Customer,49,Personal Travel,Business,726,3,3,3,4,1,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +1805,14252,Male,Loyal Customer,52,Business travel,Business,1897,4,4,4,4,3,5,4,4,4,4,4,4,4,3,8,10.0,satisfied +1806,125288,Male,Loyal Customer,18,Business travel,Eco,678,3,1,1,1,3,3,4,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +1807,38881,Female,Loyal Customer,42,Business travel,Eco,261,1,2,5,2,1,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +1808,129781,Female,Loyal Customer,60,Personal Travel,Eco,447,4,4,4,5,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +1809,101205,Male,Loyal Customer,68,Personal Travel,Eco,1235,2,4,2,4,2,2,2,2,3,5,4,3,5,2,65,71.0,neutral or dissatisfied +1810,10260,Male,Loyal Customer,63,Personal Travel,Business,316,3,0,4,4,3,4,4,5,5,4,5,3,5,5,27,16.0,neutral or dissatisfied +1811,127092,Female,disloyal Customer,25,Business travel,Eco,221,2,1,2,3,3,2,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +1812,54690,Female,disloyal Customer,29,Business travel,Eco,964,4,4,4,3,1,4,1,1,2,3,2,3,4,1,0,0.0,satisfied +1813,39460,Female,Loyal Customer,34,Personal Travel,Eco,129,1,4,1,5,4,1,4,4,4,5,5,4,3,4,0,4.0,neutral or dissatisfied +1814,43026,Male,disloyal Customer,20,Business travel,Eco,236,4,1,4,3,4,4,4,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +1815,11951,Female,Loyal Customer,29,Personal Travel,Eco,781,5,4,5,5,4,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +1816,120674,Male,Loyal Customer,45,Business travel,Business,280,2,2,2,2,3,2,5,5,5,4,5,1,5,3,38,59.0,satisfied +1817,30053,Male,Loyal Customer,27,Business travel,Business,183,4,4,4,4,5,4,4,5,4,3,4,3,4,5,0,7.0,neutral or dissatisfied +1818,59374,Male,Loyal Customer,29,Business travel,Eco,2556,1,5,5,5,1,1,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +1819,125229,Female,Loyal Customer,29,Business travel,Eco Plus,651,3,3,4,3,3,3,3,3,2,4,3,1,2,3,0,0.0,neutral or dissatisfied +1820,4264,Male,Loyal Customer,48,Business travel,Business,1713,3,3,3,3,2,5,4,5,5,5,5,5,5,4,32,43.0,satisfied +1821,43498,Female,Loyal Customer,26,Personal Travel,Eco,679,2,5,2,1,3,2,3,3,3,5,5,5,5,3,82,70.0,neutral or dissatisfied +1822,14650,Female,Loyal Customer,64,Business travel,Eco,112,3,4,4,4,3,3,4,3,3,3,3,5,3,2,48,40.0,satisfied +1823,99240,Female,Loyal Customer,54,Personal Travel,Eco,541,5,4,5,4,3,2,2,1,1,5,1,5,1,2,0,0.0,satisfied +1824,58974,Male,disloyal Customer,37,Business travel,Business,1723,1,1,1,1,3,1,3,3,5,3,3,4,5,3,23,5.0,neutral or dissatisfied +1825,1840,Male,Loyal Customer,58,Personal Travel,Eco,500,3,4,5,3,3,5,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +1826,116867,Male,disloyal Customer,39,Business travel,Business,370,1,1,1,4,5,1,5,5,4,5,5,5,5,5,11,9.0,neutral or dissatisfied +1827,126055,Male,Loyal Customer,53,Business travel,Business,2277,3,2,3,3,2,5,5,4,4,4,4,5,4,5,7,1.0,satisfied +1828,109567,Male,Loyal Customer,16,Personal Travel,Eco,861,2,5,2,3,2,2,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +1829,113808,Male,Loyal Customer,49,Business travel,Business,258,4,4,2,4,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +1830,20691,Female,disloyal Customer,22,Business travel,Eco,779,2,2,2,1,1,2,1,1,2,1,5,2,5,1,126,110.0,neutral or dissatisfied +1831,68786,Male,Loyal Customer,22,Business travel,Business,861,5,5,5,5,3,4,3,3,5,2,4,5,5,3,0,0.0,satisfied +1832,114554,Female,Loyal Customer,15,Personal Travel,Business,417,4,5,4,4,1,4,1,1,4,3,3,2,4,1,8,7.0,neutral or dissatisfied +1833,64111,Male,Loyal Customer,30,Business travel,Business,2288,2,2,2,2,5,4,5,5,3,4,5,5,5,5,0,4.0,satisfied +1834,109374,Female,disloyal Customer,25,Business travel,Eco,1189,3,3,3,4,4,3,4,4,3,4,4,1,4,4,31,29.0,neutral or dissatisfied +1835,51769,Female,Loyal Customer,24,Personal Travel,Eco,455,3,2,3,3,5,3,4,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +1836,53471,Female,Loyal Customer,60,Business travel,Eco,2253,4,5,3,5,5,1,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +1837,81486,Male,Loyal Customer,62,Personal Travel,Eco,528,2,5,2,4,2,2,2,2,4,5,4,2,2,2,0,0.0,neutral or dissatisfied +1838,27820,Female,Loyal Customer,27,Business travel,Business,1533,4,2,2,2,4,4,4,4,3,5,4,3,4,4,56,60.0,neutral or dissatisfied +1839,109343,Female,disloyal Customer,22,Business travel,Eco,1136,3,3,3,2,4,3,4,4,4,4,4,3,5,4,100,104.0,satisfied +1840,71950,Male,Loyal Customer,50,Business travel,Business,1437,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,21.0,satisfied +1841,27780,Male,Loyal Customer,36,Business travel,Business,1448,3,3,3,3,3,2,1,4,4,4,4,2,4,1,0,0.0,satisfied +1842,4727,Female,Loyal Customer,47,Business travel,Business,2586,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +1843,25969,Female,Loyal Customer,23,Personal Travel,Eco,946,0,4,0,3,2,0,2,2,4,1,3,5,3,2,0,0.0,satisfied +1844,73609,Male,Loyal Customer,40,Business travel,Business,192,3,3,4,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +1845,106644,Male,Loyal Customer,37,Business travel,Business,2601,3,4,4,4,1,4,3,3,3,3,3,3,3,1,0,2.0,neutral or dissatisfied +1846,79559,Male,Loyal Customer,53,Business travel,Business,3825,3,3,3,3,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +1847,110967,Female,Loyal Customer,80,Business travel,Business,3859,5,1,1,1,2,4,4,5,5,4,5,2,5,4,0,0.0,neutral or dissatisfied +1848,89494,Female,Loyal Customer,56,Personal Travel,Eco Plus,1931,2,4,1,2,4,4,4,4,4,1,5,3,4,5,0,0.0,neutral or dissatisfied +1849,8195,Female,Loyal Customer,54,Business travel,Business,335,2,2,2,2,1,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +1850,113272,Male,Loyal Customer,47,Business travel,Business,3136,2,2,2,2,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +1851,25628,Male,Loyal Customer,60,Business travel,Business,526,1,1,1,1,1,5,1,4,4,4,4,4,4,1,0,0.0,satisfied +1852,515,Male,disloyal Customer,21,Business travel,Business,89,4,0,5,1,3,5,3,3,4,4,5,5,4,3,0,0.0,satisfied +1853,124214,Male,Loyal Customer,7,Personal Travel,Eco,2176,2,5,2,2,5,2,5,5,3,2,2,1,4,5,0,0.0,neutral or dissatisfied +1854,121646,Female,Loyal Customer,21,Personal Travel,Eco Plus,912,4,5,4,5,2,4,1,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +1855,98967,Male,Loyal Customer,65,Business travel,Business,479,2,2,5,2,3,5,4,5,5,5,5,5,5,3,11,13.0,satisfied +1856,81883,Female,Loyal Customer,60,Business travel,Business,1561,2,5,5,5,3,1,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +1857,112479,Male,Loyal Customer,52,Personal Travel,Eco,853,2,5,2,3,5,2,5,5,5,2,5,3,4,5,86,85.0,neutral or dissatisfied +1858,103058,Female,disloyal Customer,27,Business travel,Eco,460,2,3,1,3,4,1,4,4,1,5,2,2,2,4,62,43.0,neutral or dissatisfied +1859,16009,Male,Loyal Customer,35,Business travel,Business,3153,3,3,3,3,1,5,5,5,5,4,5,3,5,4,81,73.0,satisfied +1860,8972,Female,Loyal Customer,29,Business travel,Business,3458,2,5,5,5,2,3,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +1861,92364,Male,Loyal Customer,45,Business travel,Business,2139,3,3,3,3,3,3,4,5,5,5,5,3,5,3,0,0.0,satisfied +1862,121174,Female,Loyal Customer,50,Personal Travel,Eco,2521,2,1,2,4,2,4,5,1,1,3,3,5,2,5,10,10.0,neutral or dissatisfied +1863,71391,Female,Loyal Customer,59,Business travel,Business,258,5,5,2,5,3,5,5,5,5,5,5,3,5,5,10,12.0,satisfied +1864,67573,Male,disloyal Customer,36,Business travel,Business,1126,1,1,1,4,1,1,1,1,5,5,5,3,5,1,13,5.0,neutral or dissatisfied +1865,128705,Male,Loyal Customer,14,Business travel,Eco,1504,3,3,3,3,3,3,2,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +1866,21068,Male,Loyal Customer,46,Business travel,Eco,152,3,4,4,4,3,3,3,3,2,5,3,2,2,3,3,0.0,neutral or dissatisfied +1867,67570,Male,Loyal Customer,49,Business travel,Business,1188,2,2,2,2,4,5,5,4,4,4,4,3,4,5,8,23.0,satisfied +1868,61749,Female,Loyal Customer,29,Personal Travel,Eco,1464,5,5,5,3,4,5,4,4,5,5,5,4,4,4,30,6.0,satisfied +1869,125135,Male,Loyal Customer,58,Personal Travel,Eco,361,1,4,1,4,2,1,2,2,3,3,5,5,4,2,0,3.0,neutral or dissatisfied +1870,55549,Male,Loyal Customer,69,Personal Travel,Eco,550,3,4,3,4,2,3,4,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +1871,96023,Male,disloyal Customer,25,Business travel,Business,1235,5,5,5,3,4,5,1,4,3,2,5,3,4,4,10,0.0,satisfied +1872,78437,Male,disloyal Customer,28,Business travel,Business,666,0,0,0,2,2,0,2,2,3,4,5,3,5,2,41,68.0,satisfied +1873,114719,Male,disloyal Customer,42,Business travel,Business,296,3,3,3,4,4,3,4,4,5,4,4,3,4,4,13,0.0,neutral or dissatisfied +1874,55397,Male,Loyal Customer,52,Business travel,Eco Plus,678,2,2,2,2,2,2,2,2,1,1,3,1,3,2,0,20.0,neutral or dissatisfied +1875,113489,Female,Loyal Customer,19,Business travel,Eco,223,4,5,5,5,4,4,4,4,2,5,3,2,3,4,2,0.0,neutral or dissatisfied +1876,66058,Male,Loyal Customer,66,Business travel,Business,3829,3,5,5,5,3,3,3,3,3,3,3,1,3,3,42,41.0,neutral or dissatisfied +1877,17723,Male,Loyal Customer,36,Business travel,Business,2194,3,3,2,3,3,4,1,4,4,4,4,2,4,5,14,0.0,satisfied +1878,28169,Female,disloyal Customer,30,Business travel,Eco,933,3,3,3,4,3,3,4,3,5,5,3,5,1,3,4,3.0,neutral or dissatisfied +1879,12449,Male,Loyal Customer,58,Personal Travel,Eco,201,2,5,2,5,5,2,5,5,4,2,1,5,3,5,10,15.0,neutral or dissatisfied +1880,112309,Male,Loyal Customer,29,Business travel,Business,909,1,1,1,1,4,4,4,4,3,2,4,3,4,4,1,0.0,satisfied +1881,123737,Male,Loyal Customer,39,Business travel,Business,3264,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +1882,106866,Female,disloyal Customer,25,Business travel,Business,577,4,0,4,4,2,4,2,2,5,4,5,4,4,2,26,22.0,neutral or dissatisfied +1883,111069,Male,Loyal Customer,24,Personal Travel,Eco,319,2,3,2,1,5,2,5,5,3,3,2,1,3,5,49,37.0,neutral or dissatisfied +1884,85212,Female,disloyal Customer,21,Business travel,Eco,689,3,3,3,3,5,3,5,5,3,1,3,4,4,5,0,0.0,neutral or dissatisfied +1885,92896,Female,disloyal Customer,59,Business travel,Business,134,1,1,1,1,2,1,2,2,3,2,5,4,4,2,11,12.0,neutral or dissatisfied +1886,114705,Female,Loyal Customer,39,Business travel,Eco,358,1,4,4,4,1,1,1,1,2,1,4,1,3,1,23,21.0,neutral or dissatisfied +1887,119101,Female,Loyal Customer,46,Business travel,Business,2294,1,1,1,1,3,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +1888,39572,Female,disloyal Customer,27,Business travel,Eco,620,1,0,1,3,3,1,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +1889,94244,Female,Loyal Customer,55,Business travel,Business,1939,0,0,0,1,3,4,4,3,3,3,3,3,3,5,34,37.0,satisfied +1890,769,Male,Loyal Customer,49,Business travel,Business,158,4,4,4,4,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +1891,80195,Male,Loyal Customer,48,Personal Travel,Eco,2475,3,3,3,4,3,1,1,2,2,5,3,1,4,1,5,13.0,neutral or dissatisfied +1892,974,Female,disloyal Customer,37,Business travel,Business,158,1,1,1,3,5,1,4,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +1893,53360,Male,Loyal Customer,22,Business travel,Business,1476,4,4,4,4,4,4,4,4,3,5,3,1,1,4,2,0.0,satisfied +1894,123551,Female,Loyal Customer,52,Business travel,Business,1773,2,2,2,2,2,3,5,3,3,3,3,5,3,4,14,11.0,satisfied +1895,18758,Male,Loyal Customer,34,Business travel,Business,1039,1,1,1,1,2,3,5,5,5,5,5,2,5,1,30,33.0,satisfied +1896,18971,Female,Loyal Customer,66,Personal Travel,Eco Plus,448,4,5,4,4,2,4,5,4,4,4,4,3,4,4,17,13.0,neutral or dissatisfied +1897,118263,Male,disloyal Customer,19,Business travel,Eco,1788,4,4,4,2,5,4,5,5,5,3,3,4,5,5,19,3.0,neutral or dissatisfied +1898,75489,Male,Loyal Customer,52,Business travel,Business,2342,5,5,5,5,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +1899,14930,Male,Loyal Customer,13,Personal Travel,Business,554,4,4,4,1,1,4,2,1,5,4,4,4,4,1,0,12.0,satisfied +1900,49829,Female,Loyal Customer,38,Business travel,Business,308,3,3,4,3,3,4,5,4,4,4,4,3,4,2,0,0.0,satisfied +1901,106632,Male,Loyal Customer,41,Business travel,Business,3161,3,4,4,4,4,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +1902,60517,Male,Loyal Customer,62,Personal Travel,Eco,862,2,4,2,4,4,2,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +1903,40888,Male,Loyal Customer,41,Personal Travel,Eco,558,0,4,0,4,5,0,3,5,5,4,4,5,5,5,0,0.0,satisfied +1904,96288,Female,Loyal Customer,15,Personal Travel,Eco,687,3,1,3,2,2,3,2,2,1,5,1,4,2,2,0,0.0,neutral or dissatisfied +1905,61132,Male,Loyal Customer,21,Personal Travel,Business,862,5,4,5,2,2,5,5,2,4,4,5,3,5,2,2,0.0,satisfied +1906,125338,Male,Loyal Customer,56,Business travel,Business,1610,1,1,3,1,5,4,4,5,5,5,5,4,5,4,0,9.0,satisfied +1907,9229,Female,disloyal Customer,50,Business travel,Eco,100,1,2,1,3,2,1,2,2,3,2,3,4,4,2,0,10.0,neutral or dissatisfied +1908,83528,Female,disloyal Customer,39,Business travel,Business,946,2,2,2,4,5,2,5,5,2,2,4,3,3,5,0,25.0,neutral or dissatisfied +1909,46138,Female,disloyal Customer,25,Business travel,Eco,604,3,5,3,3,1,3,1,1,1,5,5,5,2,1,0,0.0,neutral or dissatisfied +1910,49544,Male,Loyal Customer,48,Business travel,Eco,89,3,5,5,5,3,3,3,3,2,5,4,3,3,3,0,0.0,satisfied +1911,107125,Female,Loyal Customer,26,Personal Travel,Eco,842,0,5,0,1,4,0,4,4,3,3,5,4,3,4,12,0.0,satisfied +1912,29620,Female,Loyal Customer,22,Business travel,Business,3652,5,5,5,5,5,5,5,5,2,2,1,2,1,5,0,0.0,satisfied +1913,47324,Female,Loyal Customer,46,Business travel,Business,3460,4,4,4,4,4,2,2,4,4,5,4,2,4,1,0,0.0,satisfied +1914,6362,Male,Loyal Customer,70,Business travel,Business,296,4,1,1,1,2,3,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +1915,87,Male,Loyal Customer,65,Personal Travel,Eco,67,3,5,3,3,5,3,5,5,4,3,5,4,5,5,1,0.0,neutral or dissatisfied +1916,11230,Male,Loyal Customer,40,Personal Travel,Eco,134,3,2,3,3,1,3,1,1,1,5,3,3,2,1,0,0.0,neutral or dissatisfied +1917,114345,Male,Loyal Customer,25,Personal Travel,Eco,909,2,2,3,3,2,3,2,2,1,3,4,3,3,2,11,0.0,neutral or dissatisfied +1918,77076,Male,Loyal Customer,60,Business travel,Business,2231,2,2,2,2,2,4,4,2,2,2,2,1,2,4,0,2.0,neutral or dissatisfied +1919,97456,Male,Loyal Customer,36,Business travel,Business,670,2,2,2,2,3,5,4,4,4,5,4,4,4,5,10,16.0,satisfied +1920,3676,Female,disloyal Customer,42,Business travel,Business,431,3,3,3,5,3,3,3,3,5,2,4,5,5,3,0,4.0,neutral or dissatisfied +1921,52120,Female,Loyal Customer,23,Business travel,Eco Plus,438,4,5,5,5,4,4,5,4,5,3,4,3,2,4,0,2.0,satisfied +1922,21570,Male,Loyal Customer,23,Business travel,Eco Plus,377,2,2,2,2,2,2,4,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +1923,68107,Female,Loyal Customer,19,Personal Travel,Eco,868,5,2,5,3,5,1,1,3,4,3,4,1,2,1,165,146.0,satisfied +1924,100541,Male,Loyal Customer,27,Personal Travel,Eco,580,3,4,3,3,2,3,2,2,4,4,4,3,5,2,6,4.0,neutral or dissatisfied +1925,40288,Female,Loyal Customer,30,Personal Travel,Eco,402,1,5,1,3,4,1,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +1926,94437,Female,Loyal Customer,56,Business travel,Business,1713,1,1,1,1,3,4,5,4,4,5,4,5,4,3,7,0.0,satisfied +1927,85045,Male,Loyal Customer,54,Business travel,Business,874,3,2,3,3,3,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +1928,125592,Male,Loyal Customer,60,Business travel,Business,1587,5,2,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +1929,48234,Male,Loyal Customer,60,Personal Travel,Eco,259,1,2,1,4,4,1,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +1930,88291,Female,disloyal Customer,37,Business travel,Eco,404,2,1,2,4,1,2,1,1,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +1931,73178,Male,disloyal Customer,27,Business travel,Business,1258,5,5,5,4,1,5,1,1,5,4,5,3,4,1,0,0.0,satisfied +1932,22684,Female,Loyal Customer,60,Business travel,Business,3851,2,3,3,3,3,3,4,2,2,2,2,1,2,4,23,22.0,neutral or dissatisfied +1933,101396,Female,disloyal Customer,27,Business travel,Eco,486,2,2,2,4,5,2,5,5,3,3,3,3,3,5,10,4.0,neutral or dissatisfied +1934,68930,Male,Loyal Customer,31,Business travel,Business,3695,1,1,1,1,5,5,5,5,5,4,5,3,5,5,13,40.0,satisfied +1935,68954,Male,Loyal Customer,57,Business travel,Business,700,3,3,3,3,3,2,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +1936,63827,Male,disloyal Customer,24,Business travel,Eco,1172,4,4,4,2,3,4,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +1937,109438,Male,Loyal Customer,31,Business travel,Business,873,4,4,4,4,5,5,5,5,5,5,4,5,5,5,3,3.0,satisfied +1938,41285,Female,Loyal Customer,29,Business travel,Business,542,5,3,5,5,5,4,5,5,1,3,4,3,5,5,0,0.0,satisfied +1939,17773,Male,disloyal Customer,31,Business travel,Business,1075,4,4,4,3,1,4,1,1,2,3,3,5,2,1,3,4.0,neutral or dissatisfied +1940,44995,Male,Loyal Customer,44,Business travel,Business,222,1,2,3,2,3,2,2,5,5,4,1,1,5,3,0,9.0,neutral or dissatisfied +1941,125488,Female,Loyal Customer,67,Business travel,Eco Plus,1417,4,5,5,5,1,4,2,4,4,4,4,1,4,3,0,0.0,satisfied +1942,60874,Male,Loyal Customer,72,Business travel,Business,3081,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +1943,9854,Female,Loyal Customer,28,Business travel,Business,2298,4,2,2,2,4,4,4,4,1,1,3,2,4,4,7,18.0,neutral or dissatisfied +1944,114208,Female,disloyal Customer,36,Business travel,Eco,846,3,3,3,3,1,3,1,1,2,4,3,1,3,1,5,0.0,neutral or dissatisfied +1945,63178,Male,disloyal Customer,33,Business travel,Business,337,4,4,4,1,2,4,2,2,4,4,4,4,4,2,87,75.0,neutral or dissatisfied +1946,95873,Female,Loyal Customer,36,Business travel,Eco,580,2,4,4,4,2,2,2,2,4,2,2,1,3,2,1,0.0,neutral or dissatisfied +1947,1036,Female,Loyal Customer,40,Business travel,Business,3608,3,3,3,3,2,1,1,5,5,5,5,4,5,1,0,0.0,satisfied +1948,30351,Male,Loyal Customer,48,Business travel,Business,3842,2,1,2,2,2,4,2,3,3,3,3,2,3,5,36,34.0,satisfied +1949,123391,Female,Loyal Customer,9,Business travel,Business,1337,5,5,5,5,5,5,5,5,5,3,4,4,4,5,4,0.0,satisfied +1950,111860,Female,Loyal Customer,42,Business travel,Business,2751,4,4,4,4,3,5,5,4,4,4,4,5,4,4,17,22.0,satisfied +1951,107519,Male,Loyal Customer,46,Business travel,Business,2790,2,1,1,1,4,3,3,2,2,2,2,4,2,2,4,0.0,neutral or dissatisfied +1952,18700,Female,Loyal Customer,37,Business travel,Eco Plus,383,4,2,2,2,4,4,4,4,4,2,5,5,1,4,0,0.0,satisfied +1953,801,Female,Loyal Customer,55,Business travel,Business,1688,2,2,2,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +1954,10633,Male,Loyal Customer,47,Business travel,Business,2182,0,5,0,4,3,5,4,3,3,3,3,5,3,4,21,24.0,satisfied +1955,83998,Male,Loyal Customer,70,Personal Travel,Eco,321,2,5,2,5,2,2,2,2,3,2,2,5,1,2,0,0.0,neutral or dissatisfied +1956,75202,Female,disloyal Customer,44,Business travel,Business,1744,4,4,4,2,4,4,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +1957,47686,Female,Loyal Customer,62,Personal Travel,Eco,1428,4,3,4,2,1,4,3,2,2,4,2,1,2,2,0,0.0,satisfied +1958,73731,Female,Loyal Customer,28,Personal Travel,Eco,204,2,3,0,2,3,0,3,3,4,1,3,4,4,3,0,6.0,neutral or dissatisfied +1959,111052,Male,Loyal Customer,33,Business travel,Business,240,2,2,3,2,2,2,2,2,2,5,4,3,3,2,1,0.0,neutral or dissatisfied +1960,39185,Female,Loyal Customer,45,Personal Travel,Eco,287,2,4,2,2,5,4,4,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +1961,90366,Female,Loyal Customer,53,Business travel,Business,1963,3,3,3,3,4,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +1962,51400,Male,Loyal Customer,57,Personal Travel,Eco Plus,156,2,5,2,3,4,2,4,4,3,3,1,1,5,4,0,0.0,neutral or dissatisfied +1963,40401,Female,Loyal Customer,58,Business travel,Business,222,5,5,5,5,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +1964,88862,Male,Loyal Customer,50,Business travel,Business,2149,2,5,5,5,3,3,3,2,2,2,2,2,2,4,5,0.0,neutral or dissatisfied +1965,62177,Female,disloyal Customer,26,Business travel,Eco,934,3,3,3,3,1,3,1,1,1,4,2,3,3,1,0,0.0,neutral or dissatisfied +1966,77788,Female,Loyal Customer,53,Personal Travel,Eco,874,3,0,4,3,3,4,1,5,5,4,5,5,5,5,0,9.0,neutral or dissatisfied +1967,84672,Female,Loyal Customer,51,Business travel,Business,2182,2,2,2,2,2,3,4,5,5,5,5,4,5,3,14,29.0,satisfied +1968,107722,Female,disloyal Customer,37,Business travel,Eco,251,3,2,3,3,3,3,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +1969,65077,Male,Loyal Customer,24,Personal Travel,Eco,190,2,3,2,2,5,2,5,5,3,2,2,1,3,5,0,0.0,neutral or dissatisfied +1970,117010,Female,Loyal Customer,58,Business travel,Business,1905,2,3,3,3,5,4,4,2,2,2,2,3,2,2,7,0.0,neutral or dissatisfied +1971,21883,Female,Loyal Customer,52,Business travel,Eco,448,4,2,2,2,2,2,3,4,4,4,4,5,4,5,2,63.0,satisfied +1972,68114,Male,Loyal Customer,32,Personal Travel,Eco,868,3,3,3,1,4,3,4,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +1973,104822,Female,disloyal Customer,27,Business travel,Eco,472,3,4,3,4,3,3,3,3,1,5,4,2,4,3,8,5.0,neutral or dissatisfied +1974,33785,Male,Loyal Customer,29,Business travel,Business,2145,2,5,5,5,2,2,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +1975,84560,Male,Loyal Customer,40,Personal Travel,Eco,2504,4,5,5,1,4,5,4,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +1976,26208,Female,Loyal Customer,59,Business travel,Business,1568,3,4,2,2,5,3,4,3,3,3,3,4,3,2,0,2.0,neutral or dissatisfied +1977,117721,Female,Loyal Customer,26,Personal Travel,Eco Plus,1009,3,4,3,5,5,3,5,5,5,1,1,3,5,5,0,9.0,neutral or dissatisfied +1978,115695,Female,Loyal Customer,52,Business travel,Business,333,4,3,5,5,5,4,3,4,4,4,4,4,4,1,19,9.0,neutral or dissatisfied +1979,99946,Female,Loyal Customer,50,Business travel,Eco,1986,2,3,3,3,3,2,4,2,2,2,2,3,2,4,7,16.0,neutral or dissatisfied +1980,104044,Male,Loyal Customer,35,Business travel,Eco,1044,2,1,1,1,2,2,2,2,4,2,4,4,4,2,4,13.0,neutral or dissatisfied +1981,71947,Male,Loyal Customer,47,Personal Travel,Business,1437,0,4,0,3,5,5,4,1,1,0,1,4,1,3,0,0.0,satisfied +1982,3621,Female,Loyal Customer,20,Personal Travel,Business,427,4,0,4,3,1,4,1,1,3,4,5,3,4,1,93,92.0,satisfied +1983,82916,Male,Loyal Customer,39,Personal Travel,Eco,645,3,3,3,5,3,3,1,3,5,4,5,3,3,3,21,74.0,neutral or dissatisfied +1984,18669,Female,Loyal Customer,32,Personal Travel,Eco,201,1,4,1,4,1,1,1,1,3,3,3,1,4,1,63,66.0,neutral or dissatisfied +1985,95728,Female,disloyal Customer,23,Business travel,Eco,419,3,4,3,5,1,3,1,1,5,3,4,3,5,1,0,6.0,neutral or dissatisfied +1986,4422,Male,Loyal Customer,59,Business travel,Business,762,1,1,1,1,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +1987,88144,Male,Loyal Customer,50,Business travel,Business,366,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +1988,64411,Male,Loyal Customer,42,Business travel,Eco Plus,758,4,5,5,5,4,4,4,4,3,5,5,5,5,4,5,0.0,satisfied +1989,60978,Female,Loyal Customer,37,Personal Travel,Eco,888,3,2,4,3,3,4,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +1990,101233,Female,Loyal Customer,9,Personal Travel,Eco Plus,775,3,5,3,2,2,3,1,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +1991,85450,Female,Loyal Customer,46,Business travel,Business,2799,1,1,1,1,2,4,4,4,4,4,4,5,4,5,43,42.0,satisfied +1992,102474,Male,Loyal Customer,39,Personal Travel,Eco,236,1,3,1,4,4,1,4,4,4,4,4,3,5,4,1,0.0,neutral or dissatisfied +1993,114500,Female,disloyal Customer,40,Business travel,Business,325,1,1,1,1,3,1,3,3,2,2,1,4,1,3,11,5.0,neutral or dissatisfied +1994,36791,Male,Loyal Customer,54,Personal Travel,Eco,2611,3,4,3,3,3,2,2,2,5,3,2,2,1,2,0,6.0,neutral or dissatisfied +1995,25368,Male,Loyal Customer,46,Business travel,Business,3533,4,4,4,4,3,1,3,3,3,3,3,1,3,2,0,0.0,satisfied +1996,86226,Female,disloyal Customer,27,Business travel,Eco,356,2,0,2,1,2,2,2,2,2,4,2,4,2,2,0,0.0,neutral or dissatisfied +1997,97164,Male,Loyal Customer,49,Personal Travel,Eco,1390,4,4,4,4,5,4,2,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +1998,17174,Female,Loyal Customer,28,Business travel,Business,1626,1,4,1,1,4,4,4,4,2,4,1,4,1,4,0,0.0,satisfied +1999,2981,Female,Loyal Customer,43,Personal Travel,Eco,462,3,4,3,3,4,4,3,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +2000,56007,Male,Loyal Customer,27,Business travel,Business,2586,2,2,2,2,2,2,2,3,3,4,5,2,4,2,0,0.0,satisfied +2001,30434,Female,Loyal Customer,28,Business travel,Eco,483,0,0,0,4,3,0,3,3,2,3,3,1,5,3,0,0.0,satisfied +2002,68109,Female,Loyal Customer,43,Personal Travel,Eco,813,1,3,1,3,5,4,4,4,4,1,4,3,4,1,2,0.0,neutral or dissatisfied +2003,72887,Female,Loyal Customer,41,Business travel,Business,1035,3,5,3,3,2,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +2004,72940,Female,disloyal Customer,26,Business travel,Business,1035,3,3,3,1,2,3,2,2,3,3,4,5,5,2,41,,neutral or dissatisfied +2005,4384,Male,Loyal Customer,18,Personal Travel,Eco,618,3,5,3,4,5,3,5,5,4,3,5,5,5,5,15,44.0,neutral or dissatisfied +2006,81658,Female,Loyal Customer,29,Business travel,Business,907,5,5,5,5,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +2007,87180,Female,Loyal Customer,50,Business travel,Business,946,4,4,4,4,3,5,5,4,4,4,4,5,4,4,51,44.0,satisfied +2008,79868,Female,Loyal Customer,40,Business travel,Business,1937,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +2009,81239,Male,Loyal Customer,71,Business travel,Eco Plus,223,2,1,1,1,1,2,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +2010,33528,Female,Loyal Customer,42,Business travel,Business,228,2,3,3,3,1,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +2011,71189,Female,Loyal Customer,58,Business travel,Business,2773,5,5,1,5,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +2012,121155,Male,Loyal Customer,35,Business travel,Business,2370,4,2,3,3,4,4,4,4,4,4,4,3,4,1,53,22.0,neutral or dissatisfied +2013,51822,Female,Loyal Customer,45,Business travel,Eco Plus,355,2,3,3,3,5,2,5,2,2,2,2,5,2,2,0,9.0,satisfied +2014,45291,Female,Loyal Customer,33,Business travel,Eco,150,2,2,2,2,2,2,2,2,4,1,3,1,4,2,0,20.0,neutral or dissatisfied +2015,31623,Female,Loyal Customer,51,Business travel,Business,3591,3,3,3,3,2,2,1,5,5,5,5,5,5,1,0,6.0,satisfied +2016,109823,Female,Loyal Customer,58,Business travel,Business,2553,3,3,2,3,5,4,5,2,2,2,2,3,2,4,72,63.0,satisfied +2017,42949,Female,Loyal Customer,48,Business travel,Business,1895,2,2,2,2,2,1,1,4,4,4,4,3,4,4,6,4.0,satisfied +2018,118663,Female,Loyal Customer,17,Business travel,Business,646,4,5,5,5,4,4,4,4,1,3,2,2,3,4,5,9.0,neutral or dissatisfied +2019,88839,Male,Loyal Customer,49,Personal Travel,Eco Plus,594,2,1,2,3,4,2,4,4,2,2,3,4,3,4,0,0.0,neutral or dissatisfied +2020,122697,Male,Loyal Customer,49,Personal Travel,Eco,361,4,4,4,4,5,4,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +2021,37455,Female,Loyal Customer,23,Business travel,Business,2520,1,1,1,1,5,5,5,5,2,5,4,1,4,5,0,0.0,satisfied +2022,12805,Female,Loyal Customer,12,Business travel,Business,2725,2,2,2,2,4,4,4,4,1,5,5,4,3,4,129,122.0,satisfied +2023,8581,Male,Loyal Customer,85,Business travel,Business,1904,3,2,2,2,2,3,3,1,2,3,3,3,1,3,14,7.0,neutral or dissatisfied +2024,96110,Male,Loyal Customer,26,Personal Travel,Eco,1069,3,5,3,3,5,3,5,5,4,3,4,5,5,5,17,21.0,neutral or dissatisfied +2025,30791,Female,Loyal Customer,59,Personal Travel,Eco,895,2,4,1,5,1,1,1,5,2,5,4,1,3,1,204,196.0,neutral or dissatisfied +2026,6417,Female,Loyal Customer,38,Personal Travel,Eco,296,4,4,4,3,2,4,5,2,4,3,5,5,5,2,42,29.0,neutral or dissatisfied +2027,110242,Male,Loyal Customer,31,Business travel,Business,1011,2,2,2,2,2,2,2,2,3,3,3,2,3,2,20,14.0,neutral or dissatisfied +2028,79344,Female,Loyal Customer,43,Business travel,Business,2191,4,4,4,4,3,4,5,4,4,4,4,3,4,2,0,0.0,satisfied +2029,4122,Female,Loyal Customer,71,Business travel,Business,431,3,5,5,5,4,3,2,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +2030,10909,Female,disloyal Customer,49,Business travel,Eco,216,3,4,3,3,4,3,4,4,1,1,3,1,4,4,0,23.0,neutral or dissatisfied +2031,5503,Female,Loyal Customer,67,Personal Travel,Eco,948,2,0,2,4,2,5,5,5,5,2,5,4,5,5,18,24.0,neutral or dissatisfied +2032,112537,Male,Loyal Customer,28,Personal Travel,Eco,957,2,1,2,4,1,2,1,1,1,3,4,3,4,1,3,5.0,neutral or dissatisfied +2033,71794,Female,disloyal Customer,22,Business travel,Eco,1723,5,5,5,5,2,5,2,2,4,4,4,3,4,2,0,0.0,satisfied +2034,97690,Female,disloyal Customer,11,Business travel,Eco,491,3,5,3,3,4,3,3,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +2035,67068,Male,Loyal Customer,58,Business travel,Eco,1017,1,4,4,4,1,1,1,1,4,1,3,1,4,1,19,0.0,neutral or dissatisfied +2036,42309,Female,Loyal Customer,9,Personal Travel,Eco,817,2,2,2,3,2,2,1,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +2037,29199,Female,Loyal Customer,23,Personal Travel,Eco Plus,679,1,5,1,2,5,1,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +2038,65770,Female,Loyal Customer,69,Personal Travel,Eco Plus,936,3,5,3,1,4,5,4,3,3,3,3,3,3,5,1,0.0,neutral or dissatisfied +2039,87499,Male,Loyal Customer,19,Business travel,Business,321,3,1,1,1,3,3,3,3,4,5,3,1,4,3,0,0.0,neutral or dissatisfied +2040,118654,Male,Loyal Customer,60,Business travel,Business,370,2,1,2,1,1,3,3,2,2,1,2,3,2,4,4,1.0,neutral or dissatisfied +2041,106086,Male,Loyal Customer,48,Business travel,Business,302,0,0,0,1,4,4,4,2,2,4,4,4,2,4,18,10.0,satisfied +2042,41821,Male,Loyal Customer,48,Personal Travel,Eco,489,2,3,2,2,5,2,4,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +2043,26073,Female,disloyal Customer,26,Business travel,Eco,591,4,3,4,1,4,4,4,4,2,1,5,5,2,4,3,0.0,neutral or dissatisfied +2044,111139,Female,Loyal Customer,23,Business travel,Business,3264,3,2,2,2,3,3,3,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +2045,44805,Female,Loyal Customer,47,Business travel,Eco,1041,2,2,2,2,1,4,4,2,2,2,2,2,2,2,4,20.0,neutral or dissatisfied +2046,129129,Male,Loyal Customer,52,Business travel,Business,954,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +2047,85849,Male,disloyal Customer,21,Business travel,Eco,666,2,0,3,4,5,3,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +2048,113737,Female,Loyal Customer,7,Personal Travel,Eco,223,3,5,3,3,3,3,3,3,3,5,4,3,4,3,11,18.0,neutral or dissatisfied +2049,70440,Male,Loyal Customer,41,Business travel,Eco,187,3,2,2,2,3,3,3,3,3,2,4,3,3,3,1,4.0,neutral or dissatisfied +2050,26661,Female,disloyal Customer,22,Business travel,Eco,404,2,0,2,3,5,2,5,5,2,2,5,1,5,5,0,17.0,neutral or dissatisfied +2051,114052,Female,Loyal Customer,40,Business travel,Business,1947,3,3,5,3,4,3,4,5,5,5,5,5,5,3,21,7.0,satisfied +2052,43542,Female,Loyal Customer,42,Business travel,Eco,393,4,4,4,4,1,4,3,4,4,4,4,4,4,3,11,1.0,satisfied +2053,74646,Male,Loyal Customer,59,Personal Travel,Eco,1464,3,3,3,4,5,3,5,5,2,1,3,3,3,5,67,50.0,neutral or dissatisfied +2054,27341,Male,Loyal Customer,46,Business travel,Business,3128,4,2,4,4,1,1,1,2,2,2,2,5,2,2,0,4.0,satisfied +2055,105035,Male,disloyal Customer,23,Business travel,Eco,361,2,0,2,4,4,2,4,4,3,3,5,4,4,4,5,0.0,neutral or dissatisfied +2056,21799,Male,Loyal Customer,36,Business travel,Business,241,1,1,5,1,3,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +2057,23454,Female,Loyal Customer,27,Business travel,Eco,516,1,4,2,2,1,1,1,1,4,2,4,3,3,1,43,40.0,neutral or dissatisfied +2058,84381,Female,disloyal Customer,37,Business travel,Eco,606,2,3,2,3,5,2,5,5,2,2,3,1,3,5,0,0.0,neutral or dissatisfied +2059,1603,Male,Loyal Customer,28,Personal Travel,Eco,140,2,4,2,4,5,2,5,5,3,5,3,1,4,5,10,14.0,neutral or dissatisfied +2060,86323,Female,Loyal Customer,57,Business travel,Business,2591,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +2061,116965,Male,Loyal Customer,42,Business travel,Business,3376,5,5,5,5,3,5,4,5,5,5,5,5,5,4,69,55.0,satisfied +2062,37636,Female,Loyal Customer,37,Personal Travel,Eco,1041,3,5,3,3,3,3,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +2063,17855,Female,disloyal Customer,26,Business travel,Business,425,0,0,0,1,2,0,2,2,5,5,4,3,4,2,0,0.0,satisfied +2064,95169,Female,Loyal Customer,34,Personal Travel,Eco,148,4,4,4,3,5,4,5,5,5,4,5,5,4,5,38,26.0,neutral or dissatisfied +2065,30115,Male,Loyal Customer,33,Personal Travel,Eco,95,2,4,2,5,5,2,5,5,3,3,2,3,5,5,0,0.0,neutral or dissatisfied +2066,114820,Female,Loyal Customer,56,Business travel,Business,447,5,5,5,5,2,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +2067,105567,Female,Loyal Customer,35,Business travel,Business,577,2,2,2,2,5,5,4,4,4,4,4,5,4,5,21,7.0,satisfied +2068,17915,Female,Loyal Customer,44,Business travel,Eco,789,4,1,1,1,3,4,4,4,4,4,4,3,4,4,113,98.0,satisfied +2069,23116,Male,Loyal Customer,45,Business travel,Eco,250,5,2,3,2,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +2070,49234,Male,Loyal Customer,45,Business travel,Eco,190,4,4,4,4,4,4,4,4,3,5,4,1,5,4,0,0.0,satisfied +2071,75590,Male,disloyal Customer,47,Business travel,Eco,337,3,4,2,4,1,2,1,1,4,3,3,2,4,1,10,7.0,neutral or dissatisfied +2072,54943,Female,disloyal Customer,23,Business travel,Eco,700,2,2,2,5,3,2,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +2073,27446,Male,Loyal Customer,55,Business travel,Eco,672,3,3,3,3,4,3,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +2074,62243,Female,Loyal Customer,7,Personal Travel,Eco,2454,3,3,3,1,3,3,3,3,1,1,1,2,2,3,0,0.0,neutral or dissatisfied +2075,91443,Male,Loyal Customer,32,Business travel,Business,859,5,5,5,5,4,4,4,3,3,5,5,4,3,4,435,470.0,satisfied +2076,28672,Female,Loyal Customer,31,Personal Travel,Eco Plus,2409,3,3,2,3,4,2,4,4,1,1,3,2,3,4,0,0.0,neutral or dissatisfied +2077,101809,Female,Loyal Customer,60,Business travel,Business,1521,3,3,3,3,5,5,5,4,5,5,5,5,5,5,166,264.0,satisfied +2078,68631,Female,Loyal Customer,57,Business travel,Business,3425,5,5,4,5,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2079,93224,Female,disloyal Customer,39,Business travel,Business,1460,4,4,4,3,3,4,3,3,3,4,3,2,3,3,24,16.0,neutral or dissatisfied +2080,56970,Male,Loyal Customer,44,Personal Travel,Eco,2454,2,3,3,4,3,4,4,2,2,3,3,4,2,4,22,25.0,neutral or dissatisfied +2081,29922,Female,disloyal Customer,22,Business travel,Eco,571,3,0,2,3,4,2,4,4,4,1,4,4,5,4,0,0.0,neutral or dissatisfied +2082,110649,Female,disloyal Customer,26,Business travel,Business,1005,2,5,2,1,2,2,2,2,4,5,5,4,5,2,39,33.0,neutral or dissatisfied +2083,58263,Male,Loyal Customer,33,Business travel,Eco Plus,2072,3,2,2,2,3,3,3,3,1,2,3,1,3,3,9,0.0,neutral or dissatisfied +2084,72836,Male,disloyal Customer,40,Personal Travel,Eco,1013,1,2,1,4,1,1,1,1,1,4,4,4,3,1,0,0.0,neutral or dissatisfied +2085,64404,Male,Loyal Customer,45,Business travel,Business,3469,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +2086,108357,Male,disloyal Customer,17,Business travel,Eco,1324,1,1,1,4,4,1,4,4,3,4,4,2,4,4,49,40.0,neutral or dissatisfied +2087,32305,Male,Loyal Customer,42,Business travel,Eco,121,4,3,3,3,4,4,4,4,5,2,1,3,1,4,0,0.0,satisfied +2088,98747,Female,Loyal Customer,59,Personal Travel,Eco,1558,2,4,3,3,5,3,5,4,4,3,4,3,4,4,6,12.0,neutral or dissatisfied +2089,99409,Female,Loyal Customer,42,Business travel,Business,2226,4,4,4,4,5,4,5,4,4,4,4,3,4,5,9,9.0,satisfied +2090,30382,Male,Loyal Customer,34,Business travel,Business,2551,5,2,2,2,2,4,3,5,5,4,5,4,5,3,14,9.0,neutral or dissatisfied +2091,14836,Male,Loyal Customer,50,Business travel,Business,261,2,2,2,2,2,2,4,5,5,5,5,3,5,2,0,0.0,satisfied +2092,98087,Male,Loyal Customer,57,Business travel,Business,845,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +2093,91967,Male,Loyal Customer,29,Personal Travel,Eco,2475,2,1,2,2,5,2,5,5,4,3,2,4,2,5,0,0.0,neutral or dissatisfied +2094,14032,Male,Loyal Customer,44,Business travel,Business,717,4,4,4,4,2,1,5,5,5,5,5,3,5,2,0,0.0,satisfied +2095,105394,Female,Loyal Customer,62,Personal Travel,Eco,369,3,4,3,2,4,3,4,3,3,3,3,1,3,5,5,7.0,neutral or dissatisfied +2096,114025,Male,Loyal Customer,8,Business travel,Eco Plus,1844,4,1,1,1,4,4,3,4,3,5,2,3,3,4,0,0.0,neutral or dissatisfied +2097,15387,Male,Loyal Customer,33,Business travel,Business,1907,5,5,5,5,4,4,4,4,5,4,1,3,1,4,0,0.0,satisfied +2098,70553,Male,Loyal Customer,48,Business travel,Business,3478,3,3,3,3,5,5,5,3,3,3,3,3,3,4,0,9.0,satisfied +2099,46968,Male,Loyal Customer,36,Personal Travel,Eco,848,3,5,3,3,2,3,2,2,3,3,5,5,4,2,14,0.0,neutral or dissatisfied +2100,100345,Female,Loyal Customer,49,Personal Travel,Eco,1092,4,2,4,4,4,4,3,1,1,4,1,4,1,2,0,0.0,satisfied +2101,77495,Male,Loyal Customer,63,Business travel,Eco,589,4,2,5,2,4,4,4,4,5,2,1,5,3,4,0,0.0,satisfied +2102,47211,Female,Loyal Customer,63,Personal Travel,Eco,679,1,1,1,3,5,3,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +2103,27076,Male,Loyal Customer,54,Business travel,Eco,2496,2,5,5,5,3,2,3,3,4,2,4,3,4,3,16,2.0,satisfied +2104,110801,Female,Loyal Customer,16,Personal Travel,Eco,849,3,5,3,2,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +2105,37945,Female,Loyal Customer,29,Business travel,Eco Plus,937,0,0,0,2,5,0,5,5,4,1,4,2,3,5,22,20.0,satisfied +2106,115666,Male,Loyal Customer,39,Business travel,Eco,333,2,1,1,1,2,2,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +2107,22192,Female,disloyal Customer,27,Business travel,Eco,633,4,0,4,2,1,4,4,1,5,4,1,1,4,1,0,0.0,satisfied +2108,116374,Female,Loyal Customer,24,Personal Travel,Eco,417,2,1,2,2,5,2,5,5,1,4,2,1,2,5,1,,neutral or dissatisfied +2109,59621,Male,disloyal Customer,8,Business travel,Eco,787,3,3,3,1,4,3,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +2110,66213,Female,Loyal Customer,35,Business travel,Business,460,2,3,5,3,1,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +2111,50455,Female,Loyal Customer,43,Business travel,Eco,262,5,3,3,3,4,5,1,5,5,5,5,1,5,3,0,0.0,satisfied +2112,109267,Female,Loyal Customer,34,Personal Travel,Eco Plus,391,1,2,1,3,1,1,1,1,2,2,3,3,3,1,0,0.0,neutral or dissatisfied +2113,49345,Male,disloyal Customer,22,Business travel,Eco,109,2,5,2,1,2,2,2,2,1,2,4,3,2,2,5,3.0,neutral or dissatisfied +2114,78910,Female,Loyal Customer,13,Business travel,Business,930,4,3,5,3,4,4,4,4,3,2,4,4,4,4,8,0.0,neutral or dissatisfied +2115,62143,Female,Loyal Customer,35,Business travel,Business,2565,5,2,5,5,5,5,5,3,5,5,5,5,3,5,177,149.0,satisfied +2116,34788,Male,Loyal Customer,16,Personal Travel,Eco,301,2,5,2,4,5,2,5,5,5,5,4,5,4,5,28,38.0,neutral or dissatisfied +2117,79166,Female,Loyal Customer,48,Business travel,Business,2422,2,2,2,2,4,4,4,5,3,5,4,4,4,4,0,0.0,satisfied +2118,54145,Male,Loyal Customer,22,Business travel,Eco,1400,4,5,5,5,4,5,4,4,2,1,3,1,3,4,2,0.0,satisfied +2119,22803,Male,disloyal Customer,35,Business travel,Eco,302,3,2,3,4,3,3,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +2120,39066,Female,Loyal Customer,49,Business travel,Eco,784,5,3,3,3,1,4,3,5,5,5,5,4,5,4,111,110.0,satisfied +2121,2953,Male,disloyal Customer,24,Business travel,Eco,737,0,0,0,1,2,0,4,2,5,2,4,5,5,2,0,2.0,satisfied +2122,118883,Female,Loyal Customer,40,Personal Travel,Eco Plus,1136,3,5,3,3,4,3,4,4,5,2,5,5,4,4,29,17.0,neutral or dissatisfied +2123,8606,Male,Loyal Customer,37,Personal Travel,Eco Plus,109,3,1,3,2,4,3,4,4,2,1,3,1,2,4,0,0.0,neutral or dissatisfied +2124,30989,Female,Loyal Customer,39,Personal Travel,Eco Plus,1476,2,3,2,3,1,2,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +2125,93201,Female,Loyal Customer,22,Personal Travel,Eco,896,4,4,5,3,4,5,3,4,1,3,3,3,3,4,12,0.0,neutral or dissatisfied +2126,67226,Female,Loyal Customer,27,Personal Travel,Eco,929,1,5,1,1,5,1,1,5,4,1,1,1,5,5,5,0.0,neutral or dissatisfied +2127,31246,Male,Loyal Customer,18,Personal Travel,Eco,472,2,3,2,5,2,2,2,2,2,2,1,5,2,2,28,18.0,neutral or dissatisfied +2128,53810,Male,disloyal Customer,20,Business travel,Eco,140,1,5,1,3,4,1,5,4,3,5,1,1,5,4,0,0.0,neutral or dissatisfied +2129,33547,Male,disloyal Customer,61,Business travel,Eco,399,3,3,3,5,4,3,1,4,4,2,3,1,3,4,1,4.0,neutral or dissatisfied +2130,31792,Male,Loyal Customer,43,Business travel,Business,2640,4,4,4,4,5,5,5,2,4,4,1,5,4,5,3,10.0,satisfied +2131,109044,Male,Loyal Customer,38,Business travel,Eco,849,1,1,1,1,1,1,1,1,2,4,4,2,4,1,6,8.0,neutral or dissatisfied +2132,84959,Male,Loyal Customer,64,Personal Travel,Eco Plus,481,2,2,3,3,2,3,2,2,3,4,2,1,3,2,67,78.0,neutral or dissatisfied +2133,51434,Female,Loyal Customer,42,Personal Travel,Eco Plus,373,1,4,1,4,4,5,4,1,1,1,1,5,1,3,6,10.0,neutral or dissatisfied +2134,128601,Female,Loyal Customer,30,Business travel,Business,679,2,2,2,2,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +2135,73783,Male,Loyal Customer,41,Business travel,Business,192,5,5,5,5,4,5,5,4,4,4,4,3,4,5,6,0.0,satisfied +2136,27310,Male,disloyal Customer,39,Business travel,Eco,671,4,4,4,4,1,4,1,1,2,1,4,1,5,1,0,0.0,neutral or dissatisfied +2137,77412,Female,Loyal Customer,30,Personal Travel,Eco,588,1,1,0,2,4,0,4,4,1,1,2,4,3,4,0,0.0,neutral or dissatisfied +2138,71880,Female,Loyal Customer,29,Personal Travel,Eco,1846,3,4,3,4,4,3,4,4,3,2,4,1,4,4,0,7.0,neutral or dissatisfied +2139,92153,Female,Loyal Customer,26,Business travel,Eco Plus,1535,3,4,4,4,3,3,1,3,3,5,3,3,4,3,31,53.0,neutral or dissatisfied +2140,23223,Female,Loyal Customer,45,Business travel,Business,476,4,4,4,4,5,5,5,4,4,4,4,5,4,4,60,53.0,satisfied +2141,57446,Male,Loyal Customer,38,Business travel,Business,334,3,3,3,3,2,5,4,4,4,4,4,4,4,4,25,45.0,satisfied +2142,34018,Male,Loyal Customer,31,Personal Travel,Eco,1598,1,5,0,1,3,0,3,3,4,5,4,4,5,3,46,50.0,neutral or dissatisfied +2143,79125,Male,Loyal Customer,25,Personal Travel,Eco,356,1,5,1,2,3,1,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +2144,83519,Male,Loyal Customer,44,Personal Travel,Eco,946,3,2,3,3,4,3,4,4,4,5,3,4,4,4,0,10.0,neutral or dissatisfied +2145,33984,Female,Loyal Customer,31,Business travel,Business,1598,4,4,4,4,4,4,4,4,1,5,2,1,4,4,0,0.0,neutral or dissatisfied +2146,19147,Female,Loyal Customer,67,Personal Travel,Business,304,1,5,1,1,3,5,4,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +2147,115784,Male,Loyal Customer,53,Business travel,Business,2819,5,5,1,5,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +2148,105217,Female,Loyal Customer,49,Business travel,Business,377,4,4,4,4,3,5,5,5,5,5,5,3,5,4,13,6.0,satisfied +2149,109207,Male,Loyal Customer,50,Business travel,Business,2832,3,5,3,3,3,4,5,4,4,5,4,5,4,3,1,1.0,satisfied +2150,13856,Female,Loyal Customer,18,Personal Travel,Eco Plus,583,3,4,3,1,4,3,1,4,5,3,5,3,4,4,35,27.0,neutral or dissatisfied +2151,76447,Male,Loyal Customer,34,Business travel,Business,481,2,2,2,2,5,5,5,5,5,5,5,3,5,3,2,14.0,satisfied +2152,47209,Female,Loyal Customer,68,Personal Travel,Eco,748,2,3,2,2,3,5,3,2,2,2,4,2,2,4,0,0.0,neutral or dissatisfied +2153,51605,Male,Loyal Customer,48,Business travel,Eco,451,4,2,2,2,4,4,4,4,1,4,2,5,1,4,0,0.0,satisfied +2154,120702,Male,Loyal Customer,19,Personal Travel,Eco,280,1,1,1,4,4,1,1,4,3,1,3,1,3,4,4,0.0,neutral or dissatisfied +2155,77277,Female,Loyal Customer,59,Business travel,Eco,1931,2,2,2,2,1,3,3,1,1,2,1,2,1,1,64,35.0,neutral or dissatisfied +2156,84135,Male,Loyal Customer,42,Business travel,Business,3777,2,2,1,2,2,4,5,5,5,5,5,5,5,5,1,0.0,satisfied +2157,39810,Female,disloyal Customer,27,Business travel,Eco,272,2,4,2,1,3,2,4,3,1,2,1,4,3,3,0,3.0,neutral or dissatisfied +2158,28636,Female,Loyal Customer,25,Business travel,Business,2676,4,4,4,4,3,3,3,3,5,5,3,5,2,3,11,0.0,satisfied +2159,119614,Female,disloyal Customer,26,Business travel,Eco Plus,1979,1,1,1,4,4,1,4,4,2,5,2,4,4,4,20,0.0,neutral or dissatisfied +2160,12651,Male,Loyal Customer,18,Personal Travel,Eco,844,2,4,2,1,1,2,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +2161,68370,Female,Loyal Customer,53,Business travel,Business,1045,2,3,3,3,4,4,4,2,2,2,2,1,2,1,1,0.0,neutral or dissatisfied +2162,55039,Female,disloyal Customer,34,Business travel,Business,1635,2,2,2,3,5,2,2,5,3,2,5,3,5,5,18,29.0,neutral or dissatisfied +2163,31075,Female,Loyal Customer,50,Personal Travel,Eco,862,3,5,3,4,5,4,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +2164,59279,Female,Loyal Customer,58,Business travel,Business,3365,4,4,4,4,2,2,2,4,3,5,5,2,4,2,0,0.0,satisfied +2165,48732,Male,Loyal Customer,35,Business travel,Business,3036,1,1,4,1,4,5,5,5,5,5,5,3,5,5,0,5.0,satisfied +2166,53180,Male,Loyal Customer,30,Business travel,Business,2560,3,3,3,3,5,5,5,5,1,5,1,2,5,5,48,47.0,satisfied +2167,67954,Female,Loyal Customer,9,Business travel,Business,2590,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +2168,8392,Male,disloyal Customer,25,Business travel,Business,888,4,4,4,4,1,4,1,1,3,5,5,5,5,1,5,9.0,neutral or dissatisfied +2169,114716,Male,disloyal Customer,22,Business travel,Business,296,4,4,4,2,1,4,1,1,3,5,5,4,5,1,0,0.0,satisfied +2170,107364,Male,Loyal Customer,43,Personal Travel,Eco,632,4,5,4,3,2,4,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +2171,71408,Male,Loyal Customer,55,Business travel,Eco,334,5,4,3,4,5,5,5,5,4,4,5,5,4,5,5,6.0,satisfied +2172,12810,Female,Loyal Customer,42,Business travel,Business,489,3,4,2,4,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +2173,38887,Male,Loyal Customer,7,Personal Travel,Eco Plus,261,2,3,2,3,5,2,5,5,2,5,1,1,3,5,0,0.0,neutral or dissatisfied +2174,104589,Male,Loyal Customer,42,Business travel,Eco,369,5,4,4,4,5,5,5,5,2,5,5,5,4,5,0,0.0,satisfied +2175,128857,Male,Loyal Customer,50,Business travel,Business,2475,5,5,5,5,2,3,5,4,4,4,4,5,4,4,0,0.0,satisfied +2176,89318,Male,disloyal Customer,35,Business travel,Business,1587,3,3,3,4,5,3,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +2177,70877,Male,Loyal Customer,17,Business travel,Eco Plus,761,1,2,2,2,1,1,1,1,2,4,3,3,4,1,0,0.0,neutral or dissatisfied +2178,46286,Male,Loyal Customer,34,Personal Travel,Eco Plus,679,2,4,2,1,5,2,5,5,4,3,5,3,4,5,13,36.0,neutral or dissatisfied +2179,50074,Male,Loyal Customer,46,Business travel,Eco,278,4,1,1,1,4,4,4,4,1,1,4,1,1,4,0,0.0,satisfied +2180,93205,Female,Loyal Customer,34,Business travel,Business,1756,3,3,3,3,2,3,5,4,4,4,4,3,4,4,2,26.0,satisfied +2181,99910,Male,Loyal Customer,64,Business travel,Business,1428,2,3,2,3,3,2,1,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +2182,68804,Female,Loyal Customer,25,Personal Travel,Eco,1021,2,0,3,1,5,3,5,5,4,2,1,5,2,5,6,0.0,neutral or dissatisfied +2183,68097,Male,Loyal Customer,40,Business travel,Business,868,3,1,2,1,3,4,4,3,3,3,3,4,3,2,28,22.0,neutral or dissatisfied +2184,33132,Male,Loyal Customer,59,Personal Travel,Eco,201,3,3,3,4,3,3,3,3,3,4,3,2,3,3,13,13.0,neutral or dissatisfied +2185,18687,Female,Loyal Customer,13,Personal Travel,Eco,201,4,4,4,3,1,4,4,1,3,1,3,2,3,1,27,42.0,neutral or dissatisfied +2186,70854,Female,Loyal Customer,23,Business travel,Business,1607,3,3,1,1,3,3,3,3,1,5,2,4,3,3,4,0.0,neutral or dissatisfied +2187,14900,Female,Loyal Customer,23,Business travel,Business,315,1,1,1,1,4,4,4,4,2,3,4,4,4,4,28,67.0,satisfied +2188,122868,Female,Loyal Customer,16,Business travel,Business,2704,4,2,4,2,4,4,4,4,2,2,3,2,4,4,36,30.0,neutral or dissatisfied +2189,13766,Female,disloyal Customer,36,Business travel,Eco Plus,401,2,1,1,3,1,1,1,1,5,1,5,2,4,1,0,0.0,neutral or dissatisfied +2190,34887,Male,Loyal Customer,67,Business travel,Business,187,0,4,0,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +2191,114212,Female,disloyal Customer,46,Business travel,Eco,862,3,3,3,4,3,3,3,3,1,3,4,4,4,3,0,0.0,neutral or dissatisfied +2192,36220,Male,Loyal Customer,37,Business travel,Business,2599,1,1,1,1,5,3,5,5,5,4,5,3,5,5,0,0.0,satisfied +2193,123582,Female,Loyal Customer,40,Personal Travel,Eco,1773,4,1,4,4,2,4,2,2,1,4,2,3,4,2,0,0.0,neutral or dissatisfied +2194,93250,Female,Loyal Customer,47,Business travel,Business,3776,5,4,4,4,5,4,4,5,5,4,5,1,5,3,17,5.0,neutral or dissatisfied +2195,68352,Female,Loyal Customer,42,Business travel,Business,1598,2,5,5,5,5,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +2196,101580,Male,Loyal Customer,46,Business travel,Business,1099,3,3,3,3,5,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +2197,62749,Female,disloyal Customer,23,Business travel,Business,1275,4,0,4,4,4,4,4,3,2,3,4,4,5,4,4,0.0,satisfied +2198,80391,Male,Loyal Customer,12,Personal Travel,Eco,368,2,5,2,3,1,2,1,1,3,3,4,2,3,1,123,113.0,neutral or dissatisfied +2199,78116,Female,disloyal Customer,48,Business travel,Eco,1181,3,2,2,4,3,3,3,3,2,4,3,1,4,3,16,0.0,neutral or dissatisfied +2200,69755,Female,Loyal Customer,46,Personal Travel,Eco,1085,3,4,3,4,4,5,5,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +2201,105937,Male,Loyal Customer,38,Personal Travel,Eco,1491,2,1,2,4,1,2,1,1,1,5,2,2,4,1,28,0.0,neutral or dissatisfied +2202,42314,Female,Loyal Customer,7,Personal Travel,Eco,784,4,5,3,1,1,3,1,1,3,3,5,4,5,1,4,0.0,neutral or dissatisfied +2203,6698,Male,Loyal Customer,39,Business travel,Business,2308,4,4,3,4,3,4,4,1,1,2,1,3,1,5,0,0.0,satisfied +2204,86967,Female,Loyal Customer,46,Business travel,Eco,907,2,3,3,3,4,4,3,2,2,2,2,2,2,3,3,7.0,neutral or dissatisfied +2205,113902,Female,Loyal Customer,29,Business travel,Business,2295,1,5,1,5,1,1,1,1,2,2,2,4,3,1,3,0.0,neutral or dissatisfied +2206,81505,Male,Loyal Customer,64,Personal Travel,Eco,528,2,5,2,1,3,2,3,3,5,2,5,3,5,3,12,0.0,neutral or dissatisfied +2207,47140,Female,Loyal Customer,40,Business travel,Eco,679,4,1,1,1,4,4,4,4,3,3,1,4,1,4,35,38.0,satisfied +2208,29941,Female,Loyal Customer,64,Business travel,Business,3942,0,4,0,1,3,2,1,3,3,3,3,1,3,4,0,0.0,satisfied +2209,33168,Female,Loyal Customer,37,Personal Travel,Eco,101,2,5,2,2,1,2,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +2210,99023,Male,Loyal Customer,52,Business travel,Business,1564,1,1,1,1,5,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +2211,118530,Male,Loyal Customer,45,Business travel,Business,3124,2,2,2,2,5,5,5,4,3,5,4,5,5,5,139,134.0,satisfied +2212,102965,Male,Loyal Customer,23,Business travel,Business,3414,2,2,2,2,5,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +2213,112161,Female,Loyal Customer,64,Business travel,Business,3866,2,5,5,5,5,2,2,2,2,2,2,2,2,1,34,4.0,neutral or dissatisfied +2214,64880,Male,Loyal Customer,47,Business travel,Business,551,4,4,4,4,4,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +2215,6048,Female,Loyal Customer,8,Personal Travel,Eco,925,2,4,2,5,1,2,1,1,4,3,4,5,4,1,33,58.0,neutral or dissatisfied +2216,105507,Female,Loyal Customer,47,Business travel,Business,1735,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +2217,81958,Male,Loyal Customer,56,Business travel,Business,1535,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2218,14035,Female,Loyal Customer,67,Personal Travel,Eco,1117,3,4,3,4,4,4,5,2,2,3,2,5,2,5,0,21.0,neutral or dissatisfied +2219,59693,Male,Loyal Customer,13,Personal Travel,Eco,854,2,3,2,4,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +2220,126352,Male,Loyal Customer,46,Personal Travel,Eco,631,1,4,1,1,3,1,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +2221,81477,Male,Loyal Customer,20,Business travel,Eco,528,3,5,5,5,3,2,2,3,3,4,2,2,2,3,12,10.0,neutral or dissatisfied +2222,114522,Female,Loyal Customer,40,Personal Travel,Business,337,0,5,0,4,2,4,4,4,4,0,4,5,4,4,129,119.0,satisfied +2223,15301,Female,Loyal Customer,62,Personal Travel,Eco,612,2,4,2,4,2,3,1,4,4,2,2,2,4,4,0,0.0,neutral or dissatisfied +2224,31376,Male,Loyal Customer,68,Personal Travel,Eco,977,2,4,2,3,2,2,4,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +2225,119992,Female,Loyal Customer,49,Business travel,Business,328,4,5,5,5,2,3,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +2226,84590,Female,Loyal Customer,48,Business travel,Business,669,2,5,2,2,4,5,4,5,5,5,5,4,5,3,116,110.0,satisfied +2227,119361,Female,Loyal Customer,53,Business travel,Business,399,3,4,3,3,2,4,5,5,5,5,5,5,5,5,0,12.0,satisfied +2228,80796,Female,Loyal Customer,59,Business travel,Business,3018,3,3,3,3,4,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +2229,91342,Female,Loyal Customer,58,Personal Travel,Eco Plus,581,1,4,1,5,3,1,2,2,2,1,2,3,2,1,27,10.0,neutral or dissatisfied +2230,42654,Female,Loyal Customer,10,Personal Travel,Eco Plus,223,2,4,2,3,3,2,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +2231,82573,Female,disloyal Customer,26,Business travel,Eco,528,2,4,2,3,4,2,4,4,4,1,4,4,4,4,18,17.0,neutral or dissatisfied +2232,57893,Female,Loyal Customer,45,Business travel,Business,2103,5,5,5,5,4,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +2233,85766,Male,Loyal Customer,47,Business travel,Business,666,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +2234,68973,Female,disloyal Customer,23,Business travel,Eco,700,2,2,2,3,1,2,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +2235,5360,Female,disloyal Customer,49,Business travel,Eco,812,4,4,4,3,3,4,1,3,1,4,4,3,3,3,36,13.0,neutral or dissatisfied +2236,96948,Male,disloyal Customer,23,Business travel,Business,883,5,4,5,3,5,5,3,5,4,4,5,4,4,5,0,0.0,satisfied +2237,99472,Female,disloyal Customer,24,Business travel,Eco,283,3,1,3,3,5,3,5,5,4,5,3,3,3,5,45,65.0,neutral or dissatisfied +2238,76581,Male,Loyal Customer,33,Business travel,Business,547,1,1,1,1,4,4,4,4,4,5,4,5,5,4,0,5.0,satisfied +2239,92521,Male,Loyal Customer,69,Personal Travel,Eco,1947,3,5,3,2,1,3,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +2240,32050,Male,disloyal Customer,26,Business travel,Business,216,5,0,5,3,4,5,4,4,4,4,1,5,2,4,3,5.0,satisfied +2241,10573,Female,Loyal Customer,48,Business travel,Business,2160,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +2242,34052,Female,Loyal Customer,40,Business travel,Eco,1674,2,1,1,1,2,3,2,2,3,5,4,5,3,2,0,0.0,satisfied +2243,13311,Male,Loyal Customer,73,Business travel,Eco,448,4,4,4,4,4,4,4,4,4,3,4,4,5,4,3,0.0,satisfied +2244,76222,Male,disloyal Customer,29,Business travel,Business,1399,4,4,4,2,3,4,3,3,5,4,5,4,4,3,0,0.0,satisfied +2245,60161,Male,Loyal Customer,55,Personal Travel,Eco,1012,4,5,4,2,5,4,5,5,4,2,5,3,4,5,0,0.0,satisfied +2246,73341,Male,disloyal Customer,45,Business travel,Business,1182,4,4,4,3,3,4,1,3,3,5,4,5,4,3,30,1.0,neutral or dissatisfied +2247,62348,Female,Loyal Customer,48,Business travel,Business,1735,1,1,1,1,5,4,5,4,4,5,4,3,4,5,30,34.0,satisfied +2248,22356,Male,Loyal Customer,48,Business travel,Business,3734,1,4,5,4,5,3,2,2,2,2,1,3,2,1,0,0.0,neutral or dissatisfied +2249,779,Male,Loyal Customer,42,Business travel,Business,247,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,4.0,satisfied +2250,580,Male,Loyal Customer,46,Business travel,Business,1598,3,3,3,3,4,5,4,5,5,5,4,3,5,5,11,12.0,satisfied +2251,128318,Female,Loyal Customer,40,Business travel,Business,621,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,3.0,satisfied +2252,53786,Female,Loyal Customer,56,Personal Travel,Business,140,0,0,0,3,5,3,5,4,4,0,1,5,4,4,0,0.0,satisfied +2253,20949,Female,Loyal Customer,27,Business travel,Business,721,1,2,2,2,1,1,1,1,4,5,4,4,3,1,0,0.0,neutral or dissatisfied +2254,59381,Male,Loyal Customer,47,Business travel,Eco,1004,5,3,3,3,4,5,4,4,2,4,5,3,4,4,7,0.0,satisfied +2255,6474,Male,Loyal Customer,14,Personal Travel,Eco Plus,213,2,0,2,1,2,2,2,2,4,2,4,5,4,2,0,9.0,neutral or dissatisfied +2256,45916,Female,disloyal Customer,27,Business travel,Eco,563,4,0,4,5,2,4,3,2,4,5,3,3,3,2,0,0.0,satisfied +2257,110324,Male,Loyal Customer,28,Business travel,Business,883,2,2,2,2,5,5,5,5,3,3,5,4,4,5,18,6.0,satisfied +2258,60718,Female,disloyal Customer,40,Business travel,Business,1605,4,4,4,4,5,4,5,5,4,4,3,3,3,5,1,0.0,neutral or dissatisfied +2259,63336,Male,Loyal Customer,38,Business travel,Business,2386,5,5,5,5,1,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +2260,76995,Male,disloyal Customer,25,Business travel,Business,368,2,0,2,1,2,2,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +2261,12469,Female,Loyal Customer,53,Personal Travel,Eco,127,2,3,2,4,4,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +2262,114344,Male,Loyal Customer,18,Personal Travel,Eco,862,3,5,3,4,5,3,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +2263,117487,Female,Loyal Customer,25,Business travel,Business,507,3,5,4,5,3,2,3,3,1,2,3,3,3,3,7,14.0,neutral or dissatisfied +2264,107431,Female,Loyal Customer,53,Personal Travel,Eco,725,2,3,1,3,1,1,5,5,5,1,5,1,5,2,0,0.0,neutral or dissatisfied +2265,62395,Female,Loyal Customer,16,Personal Travel,Eco,2611,3,3,3,3,3,3,3,3,2,1,2,4,3,3,0,0.0,neutral or dissatisfied +2266,33076,Male,Loyal Customer,46,Personal Travel,Eco,102,3,4,3,2,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +2267,14682,Female,Loyal Customer,56,Business travel,Business,419,3,3,3,3,2,4,4,5,5,5,5,4,5,5,16,30.0,satisfied +2268,27482,Male,disloyal Customer,15,Business travel,Eco,987,3,3,3,4,4,3,4,4,4,4,4,3,3,4,4,6.0,neutral or dissatisfied +2269,32076,Female,Loyal Customer,32,Business travel,Business,2861,3,3,3,3,5,5,4,5,1,5,5,1,5,5,0,4.0,satisfied +2270,44460,Male,Loyal Customer,52,Business travel,Eco,196,4,1,1,1,5,4,5,5,4,1,3,4,1,5,37,32.0,satisfied +2271,110660,Female,Loyal Customer,31,Business travel,Business,829,2,2,4,2,2,2,2,2,3,2,4,3,4,2,0,5.0,satisfied +2272,77063,Female,Loyal Customer,43,Business travel,Business,2156,3,2,2,2,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +2273,124303,Female,disloyal Customer,27,Business travel,Eco,601,3,3,3,3,5,3,5,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +2274,29768,Male,Loyal Customer,34,Business travel,Business,2497,3,3,3,3,5,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +2275,2716,Male,Loyal Customer,62,Personal Travel,Eco,562,2,4,2,1,4,2,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +2276,94693,Male,Loyal Customer,60,Business travel,Business,148,3,3,3,3,5,5,5,4,4,4,5,3,4,4,9,11.0,satisfied +2277,5918,Male,Loyal Customer,32,Personal Travel,Eco,173,1,3,1,3,5,1,5,5,1,3,3,4,3,5,0,0.0,neutral or dissatisfied +2278,37178,Female,Loyal Customer,22,Personal Travel,Eco,1189,1,5,0,3,1,0,1,1,5,2,4,3,4,1,108,106.0,neutral or dissatisfied +2279,71827,Male,Loyal Customer,56,Business travel,Business,1846,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +2280,87504,Female,Loyal Customer,16,Business travel,Business,1983,2,2,2,2,4,4,4,4,3,4,1,1,3,4,0,0.0,satisfied +2281,36725,Female,Loyal Customer,35,Personal Travel,Eco Plus,1197,2,3,2,3,3,2,3,3,2,4,1,3,2,3,1,0.0,neutral or dissatisfied +2282,42618,Male,disloyal Customer,33,Business travel,Eco,546,3,3,3,4,3,3,3,3,2,1,4,3,1,3,0,3.0,neutral or dissatisfied +2283,62700,Male,Loyal Customer,40,Business travel,Business,2338,4,4,4,4,4,4,5,4,4,4,4,4,4,5,32,36.0,satisfied +2284,11492,Male,Loyal Customer,64,Personal Travel,Eco Plus,224,2,4,0,3,3,0,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +2285,74071,Female,disloyal Customer,22,Business travel,Business,641,4,0,4,2,3,4,3,3,3,3,5,3,4,3,0,0.0,satisfied +2286,121785,Male,Loyal Customer,34,Business travel,Business,3870,1,1,1,1,3,4,5,5,5,5,5,3,5,3,80,67.0,satisfied +2287,3340,Female,disloyal Customer,45,Business travel,Eco,296,4,2,4,3,3,4,3,3,3,2,4,4,4,3,0,6.0,neutral or dissatisfied +2288,95223,Female,Loyal Customer,21,Personal Travel,Eco,441,1,5,1,3,2,1,3,2,5,3,4,5,5,2,4,0.0,neutral or dissatisfied +2289,25675,Female,Loyal Customer,67,Personal Travel,Eco,761,2,5,2,4,2,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +2290,43167,Female,Loyal Customer,15,Personal Travel,Eco,840,3,3,3,4,4,3,4,4,1,4,4,2,4,4,0,5.0,neutral or dissatisfied +2291,16323,Male,Loyal Customer,60,Business travel,Business,628,3,3,3,3,2,4,3,3,3,3,3,4,3,2,0,8.0,neutral or dissatisfied +2292,117329,Female,disloyal Customer,9,Business travel,Eco Plus,646,2,2,2,2,2,2,5,2,3,2,3,1,2,2,4,0.0,neutral or dissatisfied +2293,75001,Male,disloyal Customer,25,Business travel,Business,236,5,0,5,4,1,5,1,1,4,5,5,5,5,1,3,0.0,satisfied +2294,22250,Female,disloyal Customer,24,Business travel,Eco,143,4,4,4,3,2,4,2,2,1,2,3,2,4,2,4,26.0,neutral or dissatisfied +2295,78182,Male,disloyal Customer,27,Business travel,Eco,153,3,2,3,4,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +2296,11406,Female,Loyal Customer,26,Business travel,Business,2562,0,5,0,5,3,3,3,3,3,2,4,3,5,3,16,34.0,satisfied +2297,2718,Female,Loyal Customer,29,Business travel,Business,3877,2,2,4,2,5,5,5,5,5,5,5,4,5,5,5,3.0,satisfied +2298,114009,Male,Loyal Customer,18,Personal Travel,Eco,1855,4,5,5,5,4,5,1,4,3,3,2,5,5,4,0,0.0,neutral or dissatisfied +2299,3765,Male,Loyal Customer,40,Personal Travel,Business,599,4,0,4,4,2,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +2300,124983,Male,Loyal Customer,59,Business travel,Business,184,0,5,0,2,2,5,5,3,3,3,3,4,3,4,9,0.0,satisfied +2301,17334,Female,Loyal Customer,41,Business travel,Business,2246,1,5,5,5,1,1,1,2,1,3,4,1,1,1,228,216.0,neutral or dissatisfied +2302,15858,Female,Loyal Customer,37,Business travel,Business,332,0,0,0,5,3,3,3,3,3,3,3,3,3,1,0,0.0,satisfied +2303,122045,Female,Loyal Customer,54,Business travel,Business,130,4,3,3,3,3,4,4,2,2,2,4,4,2,2,28,21.0,neutral or dissatisfied +2304,60763,Male,Loyal Customer,22,Business travel,Business,1937,2,2,4,4,2,2,2,1,1,4,3,2,2,2,167,160.0,neutral or dissatisfied +2305,111866,Male,Loyal Customer,60,Business travel,Business,628,2,2,2,2,3,5,5,4,4,4,4,5,4,4,5,0.0,satisfied +2306,40141,Male,Loyal Customer,48,Personal Travel,Eco Plus,368,2,1,2,2,2,2,1,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +2307,79496,Female,disloyal Customer,34,Business travel,Business,760,2,2,2,4,3,2,2,3,3,5,4,5,5,3,95,71.0,neutral or dissatisfied +2308,80285,Male,Loyal Customer,52,Business travel,Business,2366,5,5,5,5,5,4,4,2,2,2,2,5,2,5,0,8.0,satisfied +2309,15845,Female,Loyal Customer,14,Personal Travel,Eco,888,3,5,3,2,2,3,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +2310,54699,Female,Loyal Customer,31,Business travel,Business,2598,4,2,2,2,4,4,4,4,4,1,3,1,2,4,0,0.0,neutral or dissatisfied +2311,112248,Male,Loyal Customer,30,Business travel,Business,1546,4,4,4,4,4,4,4,4,5,4,5,4,5,4,2,0.0,satisfied +2312,65280,Female,Loyal Customer,62,Personal Travel,Eco Plus,247,4,2,4,4,3,3,3,1,1,4,5,4,1,1,67,72.0,neutral or dissatisfied +2313,5272,Male,Loyal Customer,52,Personal Travel,Eco,295,2,5,2,4,2,2,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +2314,92667,Female,Loyal Customer,57,Business travel,Business,3283,1,1,1,1,1,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +2315,44037,Female,Loyal Customer,33,Business travel,Business,2246,2,2,2,2,4,4,3,5,5,4,5,5,5,1,0,0.0,satisfied +2316,23108,Female,Loyal Customer,18,Business travel,Eco,646,5,3,3,3,5,5,5,5,3,2,1,2,4,5,3,0.0,satisfied +2317,34608,Male,Loyal Customer,21,Personal Travel,Eco,1598,3,5,3,3,4,3,4,4,3,4,5,5,4,4,42,25.0,neutral or dissatisfied +2318,100454,Female,Loyal Customer,51,Business travel,Business,2865,3,3,3,3,5,5,4,4,4,4,4,3,4,5,12,0.0,satisfied +2319,87653,Male,disloyal Customer,38,Business travel,Business,606,3,3,3,3,3,3,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +2320,33537,Female,Loyal Customer,53,Business travel,Business,2811,5,5,5,5,5,5,5,5,5,5,5,5,5,4,65,48.0,satisfied +2321,81946,Female,disloyal Customer,24,Business travel,Eco,1050,3,3,3,4,1,3,1,1,4,3,2,4,3,1,0,0.0,neutral or dissatisfied +2322,123899,Male,Loyal Customer,63,Personal Travel,Eco,541,3,1,3,4,4,3,4,4,4,3,4,4,3,4,36,23.0,neutral or dissatisfied +2323,39315,Female,Loyal Customer,28,Personal Travel,Eco,268,1,0,0,2,3,0,2,3,4,1,2,2,3,3,0,0.0,neutral or dissatisfied +2324,27231,Male,Loyal Customer,29,Business travel,Business,3351,4,4,4,4,4,4,4,4,2,3,3,3,1,4,0,0.0,satisfied +2325,82339,Female,Loyal Customer,52,Business travel,Business,2653,2,2,2,2,5,4,4,2,2,3,2,3,2,3,42,35.0,satisfied +2326,58336,Female,disloyal Customer,24,Business travel,Eco,296,2,0,1,4,5,1,5,5,3,3,4,4,4,5,9,0.0,neutral or dissatisfied +2327,95528,Male,Loyal Customer,27,Personal Travel,Eco Plus,248,4,1,4,2,1,4,1,1,1,1,3,3,3,1,0,22.0,neutral or dissatisfied +2328,112689,Female,disloyal Customer,24,Business travel,Eco,605,1,0,2,2,1,2,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +2329,44791,Male,Loyal Customer,35,Personal Travel,Eco,1250,3,4,3,2,2,3,2,2,3,4,4,4,4,2,7,30.0,neutral or dissatisfied +2330,43199,Female,Loyal Customer,30,Personal Travel,Eco Plus,651,4,4,4,3,5,4,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +2331,101778,Male,Loyal Customer,34,Personal Travel,Business,1521,4,4,4,5,5,4,4,4,4,4,4,3,4,4,9,0.0,satisfied +2332,52919,Female,Loyal Customer,36,Business travel,Eco,679,4,3,3,3,4,4,4,4,1,3,5,2,3,4,12,48.0,satisfied +2333,57137,Male,Loyal Customer,10,Personal Travel,Eco,1222,3,1,3,4,4,3,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +2334,54778,Male,Loyal Customer,27,Personal Travel,Eco Plus,965,2,4,2,1,4,2,4,4,4,3,5,5,4,4,4,0.0,neutral or dissatisfied +2335,9180,Male,Loyal Customer,43,Business travel,Eco Plus,416,4,1,3,1,4,4,4,4,2,3,3,2,3,4,38,35.0,neutral or dissatisfied +2336,11800,Male,Loyal Customer,63,Business travel,Eco Plus,395,2,2,2,2,2,2,2,2,1,2,4,4,4,2,0,2.0,neutral or dissatisfied +2337,61861,Female,Loyal Customer,62,Personal Travel,Eco Plus,1464,3,5,3,4,3,3,5,1,1,3,1,4,1,3,26,30.0,neutral or dissatisfied +2338,72385,Male,Loyal Customer,60,Business travel,Business,985,4,4,4,4,3,4,4,4,4,4,4,3,4,5,0,10.0,satisfied +2339,59479,Female,Loyal Customer,28,Business travel,Business,2399,3,3,3,3,4,5,4,4,5,3,4,4,5,4,19,0.0,satisfied +2340,8166,Female,Loyal Customer,31,Business travel,Business,2110,2,2,5,2,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +2341,9920,Male,Loyal Customer,57,Business travel,Business,357,2,1,1,1,1,3,3,2,2,2,2,4,2,1,48,49.0,neutral or dissatisfied +2342,10242,Female,Loyal Customer,18,Personal Travel,Business,166,4,4,4,3,3,4,2,3,3,3,4,4,5,3,0,0.0,satisfied +2343,53309,Female,Loyal Customer,35,Personal Travel,Eco,758,4,5,4,3,5,4,5,5,5,5,4,3,4,5,3,0.0,neutral or dissatisfied +2344,98344,Male,disloyal Customer,23,Business travel,Business,1189,4,0,4,5,1,4,1,1,5,2,5,3,4,1,0,0.0,satisfied +2345,103158,Female,Loyal Customer,57,Business travel,Business,2383,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +2346,51261,Male,Loyal Customer,40,Business travel,Eco Plus,447,5,5,5,5,5,5,5,5,2,3,1,5,1,5,0,0.0,satisfied +2347,40567,Male,disloyal Customer,21,Business travel,Eco,391,4,0,4,4,3,4,1,3,2,1,5,2,5,3,0,0.0,satisfied +2348,50292,Male,Loyal Customer,23,Business travel,Business,337,4,5,3,5,4,4,4,4,3,5,4,4,3,4,43,38.0,neutral or dissatisfied +2349,40140,Female,Loyal Customer,9,Personal Travel,Eco Plus,200,3,3,3,3,5,3,4,5,4,3,3,1,4,5,0,0.0,neutral or dissatisfied +2350,122949,Male,Loyal Customer,47,Business travel,Business,3094,4,1,4,4,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +2351,57492,Female,Loyal Customer,59,Business travel,Business,1618,1,4,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +2352,80692,Male,disloyal Customer,20,Business travel,Eco,748,2,2,2,3,4,2,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +2353,73879,Male,disloyal Customer,24,Business travel,Eco,1422,3,3,3,1,3,3,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +2354,83983,Female,Loyal Customer,49,Business travel,Business,1897,5,5,5,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +2355,7004,Female,Loyal Customer,22,Business travel,Business,436,1,1,1,1,2,2,2,2,3,4,4,3,3,2,57,47.0,satisfied +2356,55123,Female,Loyal Customer,12,Personal Travel,Eco,1635,3,4,4,3,3,4,3,3,3,3,4,3,4,3,27,41.0,neutral or dissatisfied +2357,104400,Male,disloyal Customer,26,Business travel,Business,1138,2,2,2,3,2,4,4,5,2,5,4,4,3,4,285,285.0,neutral or dissatisfied +2358,44352,Female,disloyal Customer,26,Business travel,Business,596,4,4,4,4,4,4,4,4,4,5,4,3,4,4,0,1.0,satisfied +2359,111708,Female,Loyal Customer,33,Business travel,Business,2774,2,2,2,2,4,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +2360,13306,Female,Loyal Customer,44,Business travel,Business,1800,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +2361,37246,Male,Loyal Customer,43,Personal Travel,Business,1005,3,3,3,3,5,3,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +2362,31219,Female,Loyal Customer,23,Personal Travel,Eco,628,2,5,2,4,4,2,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +2363,14315,Female,Loyal Customer,55,Business travel,Business,3861,2,1,1,1,3,3,3,2,2,3,2,1,2,1,42,39.0,neutral or dissatisfied +2364,26882,Female,Loyal Customer,25,Business travel,Business,3145,3,3,3,3,4,4,4,4,4,1,1,5,1,4,0,0.0,satisfied +2365,2011,Female,Loyal Customer,72,Business travel,Eco Plus,293,1,2,2,2,3,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +2366,62931,Female,Loyal Customer,51,Business travel,Business,967,1,1,1,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +2367,12620,Female,Loyal Customer,35,Personal Travel,Eco,802,1,4,1,5,2,1,2,2,2,5,5,4,3,2,0,0.0,neutral or dissatisfied +2368,58402,Male,Loyal Customer,51,Business travel,Eco,528,2,3,3,3,2,2,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +2369,9070,Male,disloyal Customer,37,Business travel,Business,108,5,5,5,5,3,5,3,3,3,2,5,5,5,3,0,5.0,satisfied +2370,117902,Male,Loyal Customer,44,Business travel,Business,3331,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,12.0,satisfied +2371,42068,Female,Loyal Customer,44,Personal Travel,Eco,241,4,4,4,3,2,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +2372,127591,Female,Loyal Customer,40,Business travel,Business,1773,2,2,2,2,2,2,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +2373,26729,Female,Loyal Customer,55,Business travel,Eco Plus,270,5,2,2,2,2,3,3,5,5,5,5,5,5,3,42,43.0,satisfied +2374,11653,Female,Loyal Customer,40,Business travel,Business,837,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +2375,127948,Female,Loyal Customer,53,Business travel,Business,1999,4,4,4,4,2,4,5,4,4,4,4,4,4,3,7,0.0,satisfied +2376,44573,Male,Loyal Customer,67,Business travel,Business,157,3,4,4,4,1,3,3,2,2,2,3,1,2,2,14,32.0,neutral or dissatisfied +2377,95812,Female,Loyal Customer,56,Personal Travel,Eco,1050,1,5,1,1,5,1,1,1,1,1,1,5,1,2,0,3.0,neutral or dissatisfied +2378,110437,Female,Loyal Customer,12,Personal Travel,Eco,919,4,3,4,2,5,4,5,5,3,5,4,4,3,5,10,2.0,neutral or dissatisfied +2379,100494,Male,Loyal Customer,27,Business travel,Business,2978,5,5,5,5,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +2380,3927,Female,Loyal Customer,63,Personal Travel,Eco Plus,213,4,2,0,3,2,4,4,2,2,0,1,3,2,4,0,0.0,satisfied +2381,126303,Female,Loyal Customer,31,Personal Travel,Eco,507,2,5,2,5,3,2,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +2382,39516,Female,Loyal Customer,48,Business travel,Business,452,3,3,3,3,3,1,3,4,4,4,4,2,4,1,0,3.0,satisfied +2383,29190,Male,Loyal Customer,30,Personal Travel,Eco Plus,1050,3,4,3,3,4,3,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +2384,48927,Male,Loyal Customer,59,Business travel,Eco,363,4,1,1,1,4,4,4,4,4,3,1,5,4,4,0,0.0,satisfied +2385,53704,Male,disloyal Customer,9,Business travel,Eco,1208,1,2,2,4,4,2,4,4,4,1,3,1,3,4,54,58.0,neutral or dissatisfied +2386,101255,Female,Loyal Customer,47,Business travel,Business,2176,3,3,3,3,4,5,4,5,5,5,5,4,5,3,61,40.0,satisfied +2387,44074,Female,disloyal Customer,39,Business travel,Business,651,2,2,2,4,5,2,3,5,2,3,4,5,5,5,0,0.0,satisfied +2388,18828,Female,disloyal Customer,21,Business travel,Business,448,5,0,5,4,4,5,5,4,4,3,2,4,3,4,8,11.0,satisfied +2389,14779,Female,Loyal Customer,40,Business travel,Business,2365,4,1,1,1,3,3,3,4,4,4,4,2,4,2,1,2.0,neutral or dissatisfied +2390,70538,Male,Loyal Customer,33,Business travel,Business,2908,3,3,3,3,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +2391,68712,Male,Loyal Customer,15,Personal Travel,Eco,237,5,5,5,2,2,5,2,2,3,2,4,5,4,2,0,0.0,satisfied +2392,125078,Female,Loyal Customer,59,Business travel,Business,3803,5,5,5,5,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +2393,56837,Female,Loyal Customer,58,Business travel,Business,1605,4,4,3,4,2,5,5,3,3,3,3,4,3,5,5,0.0,satisfied +2394,535,Female,Loyal Customer,42,Business travel,Business,1956,0,0,0,4,3,4,4,1,1,1,1,3,1,4,31,22.0,satisfied +2395,82593,Male,disloyal Customer,70,Business travel,Business,408,3,3,3,5,2,3,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +2396,98837,Female,Loyal Customer,19,Personal Travel,Eco,763,5,5,5,2,4,5,4,4,3,4,5,3,4,4,0,0.0,satisfied +2397,51514,Female,Loyal Customer,49,Business travel,Eco,261,4,5,5,5,1,5,2,4,4,4,4,4,4,4,0,0.0,satisfied +2398,21371,Male,Loyal Customer,48,Business travel,Business,554,2,1,1,1,4,2,3,2,2,2,2,3,2,4,105,93.0,neutral or dissatisfied +2399,70635,Female,Loyal Customer,36,Business travel,Business,1217,3,3,3,3,2,5,5,4,4,4,4,4,4,4,13,0.0,satisfied +2400,23763,Male,Loyal Customer,39,Personal Travel,Eco Plus,1048,3,4,3,2,3,3,3,3,5,3,5,3,5,3,29,27.0,neutral or dissatisfied +2401,59270,Female,Loyal Customer,25,Personal Travel,Eco,4963,2,5,2,4,2,5,2,5,3,4,4,2,3,2,0,0.0,neutral or dissatisfied +2402,101078,Male,Loyal Customer,43,Business travel,Business,795,3,1,1,1,3,3,4,3,3,3,3,4,3,4,27,13.0,neutral or dissatisfied +2403,105265,Female,Loyal Customer,11,Personal Travel,Eco,2106,3,3,3,1,5,3,5,5,4,3,3,3,3,5,0,0.0,neutral or dissatisfied +2404,8336,Male,Loyal Customer,43,Business travel,Business,1815,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +2405,127882,Male,Loyal Customer,48,Personal Travel,Eco,1276,4,4,4,2,5,4,5,5,5,3,5,5,5,5,2,0.0,neutral or dissatisfied +2406,106903,Male,Loyal Customer,50,Personal Travel,Eco,704,3,4,3,1,2,3,2,2,1,5,4,1,1,2,2,0.0,neutral or dissatisfied +2407,63272,Female,Loyal Customer,45,Business travel,Business,3709,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +2408,27469,Female,Loyal Customer,50,Business travel,Eco,671,2,1,1,1,1,2,2,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +2409,37278,Male,disloyal Customer,25,Business travel,Business,1074,4,3,4,5,4,4,4,4,4,1,3,4,1,4,0,0.0,satisfied +2410,103939,Male,disloyal Customer,24,Business travel,Eco,770,3,3,3,3,4,3,4,4,1,2,4,2,4,4,32,35.0,neutral or dissatisfied +2411,125917,Male,Loyal Customer,11,Personal Travel,Eco,920,3,1,3,2,1,3,1,1,2,2,2,3,2,1,95,88.0,neutral or dissatisfied +2412,45151,Female,Loyal Customer,32,Business travel,Eco,174,5,4,5,4,5,5,5,5,1,1,2,2,2,5,0,0.0,satisfied +2413,48571,Male,Loyal Customer,9,Personal Travel,Eco,853,1,3,1,3,3,1,3,3,2,1,1,1,4,3,39,36.0,neutral or dissatisfied +2414,55034,Male,Loyal Customer,30,Business travel,Business,1635,3,5,5,5,3,3,3,3,1,1,2,2,4,3,0,30.0,neutral or dissatisfied +2415,123286,Male,Loyal Customer,40,Personal Travel,Eco,650,5,4,5,3,3,5,3,3,5,1,3,3,2,3,0,0.0,satisfied +2416,45820,Female,Loyal Customer,62,Personal Travel,Eco,216,3,4,3,3,3,4,4,5,5,3,5,2,5,1,0,0.0,neutral or dissatisfied +2417,75634,Male,Loyal Customer,48,Personal Travel,Eco Plus,337,3,4,3,3,4,3,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +2418,5394,Female,Loyal Customer,27,Personal Travel,Eco,812,3,1,3,3,3,3,2,3,3,1,4,1,3,3,16,20.0,neutral or dissatisfied +2419,55260,Female,Loyal Customer,58,Business travel,Business,1571,2,2,2,2,4,4,5,5,5,4,5,4,5,5,16,0.0,satisfied +2420,66454,Male,Loyal Customer,47,Personal Travel,Eco,1217,3,4,3,2,4,3,4,4,4,5,4,3,4,4,17,3.0,neutral or dissatisfied +2421,69515,Female,Loyal Customer,40,Business travel,Business,2475,5,5,5,5,5,5,5,3,3,3,5,5,4,5,4,0.0,satisfied +2422,75683,Male,Loyal Customer,22,Personal Travel,Business,868,1,1,1,3,4,1,4,4,4,1,3,4,4,4,7,18.0,neutral or dissatisfied +2423,91702,Female,disloyal Customer,29,Business travel,Business,626,1,1,1,1,3,1,3,3,4,2,4,4,4,3,5,9.0,neutral or dissatisfied +2424,72511,Female,Loyal Customer,54,Business travel,Eco,1121,3,3,3,3,2,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +2425,51410,Male,Loyal Customer,45,Personal Travel,Eco Plus,86,1,5,1,1,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +2426,33234,Female,disloyal Customer,27,Business travel,Eco Plus,101,3,3,3,3,1,3,1,1,2,1,2,2,4,1,0,0.0,neutral or dissatisfied +2427,66310,Female,Loyal Customer,51,Business travel,Business,852,1,2,1,1,4,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +2428,18582,Male,Loyal Customer,50,Business travel,Eco,190,4,5,5,5,4,4,4,4,1,1,4,2,3,4,0,0.0,neutral or dissatisfied +2429,46352,Female,Loyal Customer,17,Personal Travel,Eco,977,3,3,3,3,2,3,2,2,3,3,2,5,2,2,20,17.0,neutral or dissatisfied +2430,79425,Male,Loyal Customer,43,Personal Travel,Eco,502,1,4,1,3,4,1,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +2431,87697,Male,Loyal Customer,35,Personal Travel,Eco,606,2,5,2,2,3,2,3,3,3,2,4,4,4,3,39,48.0,neutral or dissatisfied +2432,50049,Female,Loyal Customer,35,Business travel,Eco,337,3,1,1,1,3,3,3,3,3,1,3,4,4,3,34,33.0,neutral or dissatisfied +2433,9491,Male,Loyal Customer,42,Business travel,Eco,239,2,5,5,5,2,2,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +2434,66943,Male,Loyal Customer,41,Business travel,Business,1119,1,1,4,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +2435,82689,Female,disloyal Customer,38,Business travel,Eco,632,1,3,2,2,1,2,1,1,2,2,3,4,2,1,5,16.0,neutral or dissatisfied +2436,117735,Female,Loyal Customer,34,Business travel,Business,3349,1,2,2,2,3,3,3,1,1,1,1,4,1,4,128,115.0,neutral or dissatisfied +2437,102662,Male,Loyal Customer,37,Business travel,Business,2646,1,1,1,1,5,4,5,5,5,5,5,3,5,3,27,24.0,satisfied +2438,83558,Female,Loyal Customer,28,Personal Travel,Eco,1865,2,3,2,4,5,2,5,5,4,3,4,1,3,5,51,43.0,neutral or dissatisfied +2439,54317,Male,Loyal Customer,48,Business travel,Business,1597,1,1,1,1,2,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +2440,106705,Female,Loyal Customer,16,Personal Travel,Eco,516,1,1,1,3,1,1,3,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +2441,41341,Male,Loyal Customer,16,Personal Travel,Eco,689,1,2,1,2,4,1,4,4,2,2,3,3,2,4,1,0.0,neutral or dissatisfied +2442,65710,Male,Loyal Customer,56,Business travel,Business,2805,4,4,4,4,5,5,5,5,5,5,5,3,5,5,84,75.0,satisfied +2443,74694,Male,Loyal Customer,61,Personal Travel,Eco,1235,2,5,2,4,3,2,3,3,3,2,4,5,4,3,0,10.0,neutral or dissatisfied +2444,82867,Male,disloyal Customer,25,Business travel,Business,594,2,0,2,4,5,2,5,5,4,4,4,3,4,5,19,60.0,neutral or dissatisfied +2445,50783,Female,Loyal Customer,70,Personal Travel,Eco,209,2,2,2,3,5,3,4,2,2,2,2,3,2,1,0,4.0,neutral or dissatisfied +2446,119217,Male,Loyal Customer,21,Personal Travel,Eco,331,3,2,2,2,5,2,5,5,2,2,2,3,3,5,12,11.0,neutral or dissatisfied +2447,38621,Female,Loyal Customer,51,Business travel,Business,2611,2,2,2,2,2,5,5,4,4,4,4,5,4,5,41,20.0,satisfied +2448,35067,Male,Loyal Customer,39,Business travel,Business,2502,3,4,4,4,5,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +2449,36685,Female,Loyal Customer,9,Personal Travel,Eco,1185,4,1,4,4,5,4,5,5,1,3,3,4,3,5,0,0.0,neutral or dissatisfied +2450,7545,Male,Loyal Customer,40,Business travel,Business,2694,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +2451,123616,Female,Loyal Customer,49,Business travel,Eco Plus,1773,3,4,4,4,5,3,4,2,2,3,2,3,2,2,0,6.0,neutral or dissatisfied +2452,32976,Male,Loyal Customer,54,Personal Travel,Eco,101,2,4,2,3,3,2,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +2453,33841,Male,Loyal Customer,30,Business travel,Eco,1562,0,0,0,3,4,0,4,4,5,3,5,5,3,4,29,1.0,satisfied +2454,22331,Female,Loyal Customer,39,Business travel,Business,2329,5,5,5,5,4,5,1,4,4,4,5,2,4,2,0,0.0,satisfied +2455,127202,Female,Loyal Customer,49,Business travel,Eco Plus,370,2,3,2,3,4,5,3,2,2,2,2,5,2,1,0,0.0,satisfied +2456,8321,Female,Loyal Customer,70,Personal Travel,Eco Plus,294,2,4,2,1,5,5,4,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +2457,5423,Female,Loyal Customer,35,Personal Travel,Eco Plus,589,2,4,2,2,2,2,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +2458,104937,Female,Loyal Customer,56,Business travel,Business,3303,5,5,5,5,2,4,4,5,5,5,5,3,5,3,17,5.0,satisfied +2459,49789,Female,disloyal Customer,62,Business travel,Eco,86,4,0,5,5,3,5,1,3,1,2,1,1,3,3,67,81.0,satisfied +2460,27394,Female,Loyal Customer,25,Business travel,Business,1563,4,4,4,4,4,5,4,4,5,3,4,4,3,4,0,0.0,satisfied +2461,129217,Male,Loyal Customer,53,Personal Travel,Business,1504,2,4,2,2,4,4,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +2462,124162,Female,Loyal Customer,27,Business travel,Eco,2133,4,4,4,4,4,4,4,4,2,1,4,4,4,4,0,0.0,neutral or dissatisfied +2463,85588,Female,disloyal Customer,22,Business travel,Eco,259,1,1,1,2,4,1,4,4,2,4,2,2,3,4,34,27.0,neutral or dissatisfied +2464,57903,Female,Loyal Customer,66,Business travel,Business,305,3,5,5,5,1,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +2465,17210,Female,Loyal Customer,66,Personal Travel,Eco Plus,487,3,2,3,3,3,4,4,4,4,3,4,3,4,4,0,2.0,neutral or dissatisfied +2466,88058,Female,Loyal Customer,57,Business travel,Business,2099,5,5,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +2467,58086,Female,Loyal Customer,25,Business travel,Business,3104,2,2,2,2,2,2,2,2,1,2,3,3,3,2,105,100.0,neutral or dissatisfied +2468,17220,Male,Loyal Customer,18,Personal Travel,Business,872,5,5,4,1,4,4,4,4,3,3,4,2,1,4,0,0.0,satisfied +2469,86697,Male,Loyal Customer,52,Business travel,Business,1747,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,4.0,satisfied +2470,29977,Female,disloyal Customer,44,Business travel,Eco,95,1,1,1,3,5,1,5,5,4,5,4,4,3,5,0,0.0,neutral or dissatisfied +2471,66569,Male,Loyal Customer,45,Business travel,Business,624,5,5,5,5,5,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +2472,83438,Male,Loyal Customer,71,Business travel,Eco Plus,632,1,5,5,5,1,1,1,1,3,1,3,1,3,1,73,89.0,neutral or dissatisfied +2473,55613,Male,Loyal Customer,68,Personal Travel,Eco,404,4,5,4,5,5,4,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +2474,18893,Male,disloyal Customer,38,Business travel,Eco,151,1,2,1,3,2,1,2,2,3,5,4,2,3,2,0,0.0,neutral or dissatisfied +2475,47966,Male,Loyal Customer,16,Personal Travel,Eco,451,1,5,1,1,5,1,4,5,3,2,5,2,1,5,0,0.0,neutral or dissatisfied +2476,93052,Female,Loyal Customer,57,Business travel,Business,2195,0,0,0,5,2,5,4,4,4,2,2,3,4,4,0,0.0,satisfied +2477,56926,Female,disloyal Customer,18,Business travel,Business,733,0,0,0,3,0,4,4,3,2,5,5,4,3,4,4,0.0,satisfied +2478,69257,Female,Loyal Customer,59,Business travel,Business,733,5,5,5,5,3,4,5,5,5,5,5,3,5,4,48,49.0,satisfied +2479,34449,Male,Loyal Customer,76,Business travel,Business,228,1,1,1,1,2,4,3,1,1,1,1,1,1,4,0,13.0,neutral or dissatisfied +2480,97510,Male,Loyal Customer,22,Business travel,Business,1750,5,5,3,5,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +2481,28818,Female,Loyal Customer,46,Business travel,Business,2447,4,4,2,4,2,1,3,5,5,5,5,1,5,2,0,0.0,satisfied +2482,89805,Female,disloyal Customer,17,Business travel,Eco,1089,3,4,4,1,3,4,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +2483,37754,Male,Loyal Customer,46,Business travel,Eco Plus,1069,4,4,2,4,3,4,3,3,2,4,3,2,5,3,117,125.0,satisfied +2484,3024,Female,Loyal Customer,18,Personal Travel,Eco,922,1,5,1,1,2,1,5,2,4,4,4,3,5,2,0,6.0,neutral or dissatisfied +2485,121173,Female,Loyal Customer,28,Personal Travel,Eco,2370,4,5,4,3,3,4,3,3,5,4,4,5,4,3,3,,satisfied +2486,12171,Female,Loyal Customer,37,Business travel,Business,1075,5,5,5,5,1,1,1,4,4,4,4,2,4,4,3,0.0,satisfied +2487,114682,Female,Loyal Customer,43,Business travel,Business,3527,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +2488,66576,Female,disloyal Customer,25,Business travel,Business,624,2,5,2,4,5,2,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +2489,44773,Male,Loyal Customer,31,Business travel,Business,1820,2,2,2,2,2,2,2,2,3,3,3,1,3,2,0,1.0,neutral or dissatisfied +2490,74985,Female,Loyal Customer,62,Personal Travel,Eco,2475,3,4,3,2,2,3,4,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +2491,48993,Male,Loyal Customer,55,Business travel,Eco,199,5,3,3,3,5,5,5,5,1,4,3,4,5,5,40,40.0,satisfied +2492,33170,Female,Loyal Customer,35,Personal Travel,Eco,102,2,5,0,4,2,0,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +2493,93202,Female,Loyal Customer,39,Business travel,Business,3026,1,1,1,1,3,5,5,5,5,5,5,4,5,4,7,0.0,satisfied +2494,94094,Female,Loyal Customer,65,Personal Travel,Business,562,3,4,2,5,5,4,4,5,5,2,5,5,5,4,72,66.0,neutral or dissatisfied +2495,66938,Male,Loyal Customer,21,Business travel,Business,3874,2,2,5,2,4,4,4,4,4,4,4,3,4,4,24,20.0,satisfied +2496,70061,Female,disloyal Customer,36,Business travel,Business,550,2,2,2,1,1,2,1,1,4,4,4,4,4,1,0,2.0,neutral or dissatisfied +2497,45500,Female,Loyal Customer,20,Personal Travel,Eco,522,4,5,4,3,1,4,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +2498,120551,Male,Loyal Customer,28,Business travel,Business,2176,3,4,4,4,3,3,3,3,3,5,2,3,4,3,0,15.0,neutral or dissatisfied +2499,111227,Female,Loyal Customer,11,Personal Travel,Eco,1703,2,2,2,4,2,2,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +2500,22277,Male,disloyal Customer,24,Business travel,Eco,83,3,0,3,4,5,3,2,5,5,4,3,5,3,5,0,0.0,neutral or dissatisfied +2501,118110,Female,Loyal Customer,50,Personal Travel,Eco,1999,1,5,1,2,3,5,5,5,5,1,5,4,5,5,26,19.0,neutral or dissatisfied +2502,127726,Female,Loyal Customer,47,Business travel,Business,255,2,2,2,2,5,4,5,4,4,4,4,4,4,4,6,12.0,satisfied +2503,83378,Female,Loyal Customer,60,Personal Travel,Eco,1124,3,4,3,2,5,1,5,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +2504,116396,Male,Loyal Customer,34,Personal Travel,Eco,390,4,5,4,2,4,4,1,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +2505,27570,Female,Loyal Customer,45,Personal Travel,Eco,679,4,1,4,4,3,3,4,3,3,4,5,3,3,3,0,0.0,neutral or dissatisfied +2506,17553,Female,Loyal Customer,13,Personal Travel,Eco,1045,3,5,3,3,2,3,5,2,3,4,5,3,5,2,84,75.0,neutral or dissatisfied +2507,52933,Female,Loyal Customer,57,Personal Travel,Eco,679,4,5,4,4,5,5,4,4,4,4,4,5,4,5,1,24.0,neutral or dissatisfied +2508,69236,Female,Loyal Customer,51,Business travel,Business,2013,3,2,2,2,2,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +2509,5589,Female,Loyal Customer,60,Business travel,Business,3215,5,1,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +2510,116397,Male,Loyal Customer,22,Personal Travel,Eco,296,2,5,4,2,2,4,3,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +2511,86060,Female,Loyal Customer,50,Business travel,Business,1913,3,3,2,3,2,5,4,4,4,4,4,3,4,5,0,14.0,satisfied +2512,44742,Female,Loyal Customer,28,Personal Travel,Eco Plus,67,2,3,2,3,4,2,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +2513,10421,Male,Loyal Customer,59,Business travel,Business,2323,3,3,3,3,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +2514,71475,Female,Loyal Customer,33,Business travel,Business,2867,3,4,4,4,3,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +2515,123112,Female,disloyal Customer,26,Business travel,Business,631,3,0,3,3,2,3,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +2516,117112,Male,Loyal Customer,46,Business travel,Eco,247,2,1,1,1,2,2,2,2,1,3,4,3,3,2,48,30.0,neutral or dissatisfied +2517,83221,Female,Loyal Customer,57,Business travel,Business,2079,3,3,3,3,4,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +2518,110727,Male,Loyal Customer,27,Business travel,Business,2648,2,1,2,2,4,4,4,4,4,2,5,3,5,4,15,18.0,satisfied +2519,105060,Male,Loyal Customer,33,Personal Travel,Eco Plus,361,1,5,1,4,3,1,5,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +2520,77494,Male,disloyal Customer,37,Business travel,Eco,687,4,4,4,3,5,4,5,5,4,2,5,4,1,5,0,0.0,neutral or dissatisfied +2521,122293,Male,Loyal Customer,39,Personal Travel,Eco,546,3,4,3,4,1,3,1,1,3,2,2,5,3,1,5,2.0,neutral or dissatisfied +2522,5198,Female,Loyal Customer,51,Business travel,Business,3061,4,4,4,4,5,5,4,5,5,5,5,5,5,4,40,46.0,satisfied +2523,119912,Female,disloyal Customer,60,Business travel,Business,1009,3,3,3,2,2,3,2,2,3,4,4,5,4,2,0,20.0,neutral or dissatisfied +2524,9745,Male,Loyal Customer,39,Business travel,Business,3706,1,1,1,1,5,3,4,4,4,4,4,2,4,4,1,0.0,satisfied +2525,10403,Male,Loyal Customer,43,Business travel,Business,3146,0,0,0,1,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +2526,60068,Female,disloyal Customer,24,Business travel,Eco,1050,3,3,3,4,2,3,2,2,3,1,4,2,3,2,21,46.0,neutral or dissatisfied +2527,129629,Female,disloyal Customer,22,Business travel,Business,337,0,0,0,1,2,0,2,2,5,5,4,4,4,2,0,0.0,satisfied +2528,15115,Female,disloyal Customer,31,Business travel,Eco,1042,3,4,4,5,4,4,4,4,1,5,2,1,4,4,0,0.0,neutral or dissatisfied +2529,56655,Male,disloyal Customer,37,Business travel,Eco,623,2,2,3,4,3,3,3,3,2,5,4,1,4,3,30,13.0,neutral or dissatisfied +2530,17656,Female,Loyal Customer,53,Business travel,Eco,608,5,5,5,5,4,4,4,5,5,5,5,2,5,1,0,0.0,satisfied +2531,43515,Male,Loyal Customer,30,Personal Travel,Eco,752,3,4,4,3,4,4,4,4,5,3,4,5,4,4,0,4.0,neutral or dissatisfied +2532,103686,Female,disloyal Customer,49,Business travel,Eco,251,4,1,4,3,4,4,4,4,2,5,3,4,2,4,0,0.0,neutral or dissatisfied +2533,100261,Male,Loyal Customer,36,Business travel,Business,1011,3,3,3,3,3,5,5,4,4,5,4,5,4,4,11,0.0,satisfied +2534,2566,Female,Loyal Customer,52,Business travel,Business,227,2,5,5,5,4,2,3,2,2,3,2,4,2,1,0,5.0,neutral or dissatisfied +2535,36954,Female,disloyal Customer,38,Business travel,Business,359,1,1,1,2,4,1,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +2536,85887,Female,Loyal Customer,9,Personal Travel,Eco,2172,1,4,1,3,1,1,1,1,5,4,3,3,4,1,7,18.0,neutral or dissatisfied +2537,112790,Male,Loyal Customer,53,Business travel,Business,715,1,1,2,1,4,5,5,4,4,4,4,3,4,3,5,8.0,satisfied +2538,48562,Female,Loyal Customer,34,Personal Travel,Eco,776,3,4,3,2,1,3,1,1,3,4,5,3,4,1,8,14.0,neutral or dissatisfied +2539,29431,Female,Loyal Customer,59,Business travel,Business,2149,3,3,3,3,3,5,1,4,4,4,4,2,4,3,0,0.0,satisfied +2540,76375,Female,Loyal Customer,30,Business travel,Business,1817,4,2,2,2,4,4,4,4,3,5,4,2,4,4,0,14.0,neutral or dissatisfied +2541,7348,Male,Loyal Customer,58,Business travel,Business,464,3,3,3,3,4,5,5,4,4,4,4,4,4,3,19,29.0,satisfied +2542,102585,Female,disloyal Customer,22,Business travel,Eco,414,2,0,2,5,1,2,1,1,5,4,4,3,5,1,9,0.0,neutral or dissatisfied +2543,120820,Female,Loyal Customer,38,Personal Travel,Eco,666,5,0,5,4,3,5,3,3,4,3,5,5,5,3,0,0.0,satisfied +2544,30570,Female,Loyal Customer,46,Business travel,Business,3828,5,5,5,5,4,3,3,4,4,4,4,5,4,4,8,5.0,satisfied +2545,129632,Male,Loyal Customer,46,Business travel,Business,2358,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +2546,111435,Male,Loyal Customer,58,Business travel,Business,1953,3,5,3,3,4,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +2547,99051,Male,Loyal Customer,44,Business travel,Business,1663,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,1.0,satisfied +2548,91089,Male,Loyal Customer,11,Personal Travel,Eco,515,2,4,2,5,1,2,1,1,4,3,4,3,4,1,9,14.0,neutral or dissatisfied +2549,9218,Female,Loyal Customer,52,Business travel,Business,3094,2,1,5,1,5,4,4,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +2550,44142,Female,Loyal Customer,56,Personal Travel,Eco,207,1,4,0,2,5,1,3,4,4,0,4,2,4,3,0,10.0,neutral or dissatisfied +2551,8662,Male,disloyal Customer,32,Business travel,Business,227,4,4,4,4,2,4,2,2,3,3,5,5,4,2,7,18.0,neutral or dissatisfied +2552,77313,Male,disloyal Customer,23,Business travel,Business,590,5,0,5,3,4,5,4,4,4,4,4,4,4,4,0,2.0,satisfied +2553,24091,Male,Loyal Customer,41,Business travel,Business,554,5,5,5,5,5,4,5,4,4,4,4,4,4,5,27,9.0,satisfied +2554,129799,Female,Loyal Customer,25,Personal Travel,Eco,308,3,5,3,2,2,3,2,2,3,5,4,3,5,2,49,42.0,neutral or dissatisfied +2555,8907,Male,Loyal Customer,46,Business travel,Business,510,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +2556,60755,Male,Loyal Customer,27,Business travel,Business,3848,2,3,3,3,2,2,2,2,1,4,3,4,3,2,20,8.0,neutral or dissatisfied +2557,7475,Female,Loyal Customer,60,Business travel,Business,3587,1,1,1,1,3,4,5,5,5,5,5,4,5,5,18,19.0,satisfied +2558,13904,Female,Loyal Customer,44,Business travel,Eco,192,2,4,5,5,4,1,1,1,1,2,1,5,1,1,23,13.0,satisfied +2559,24207,Male,disloyal Customer,18,Business travel,Eco,302,2,1,2,4,1,2,1,1,1,5,3,3,3,1,0,0.0,neutral or dissatisfied +2560,127387,Female,disloyal Customer,26,Business travel,Business,868,4,4,4,4,3,4,3,3,5,2,5,5,5,3,0,6.0,neutral or dissatisfied +2561,32102,Male,disloyal Customer,25,Business travel,Business,216,3,0,3,3,2,3,2,2,1,2,5,1,5,2,4,0.0,neutral or dissatisfied +2562,60923,Male,disloyal Customer,22,Business travel,Eco,888,1,1,1,1,3,1,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +2563,74301,Female,disloyal Customer,25,Business travel,Eco Plus,811,1,5,1,2,5,1,4,5,2,2,5,1,4,5,0,0.0,neutral or dissatisfied +2564,123959,Female,Loyal Customer,53,Business travel,Business,1724,2,2,2,2,4,2,3,4,4,4,2,3,4,1,0,0.0,neutral or dissatisfied +2565,17522,Female,Loyal Customer,59,Personal Travel,Eco,341,3,1,3,2,1,1,1,5,5,3,5,2,5,1,0,0.0,neutral or dissatisfied +2566,12026,Male,Loyal Customer,44,Business travel,Eco,351,5,2,2,2,5,5,5,5,3,3,3,4,2,5,0,0.0,satisfied +2567,119692,Female,Loyal Customer,43,Business travel,Business,1430,5,5,5,5,4,5,4,3,3,4,3,3,3,5,106,119.0,satisfied +2568,14064,Male,Loyal Customer,37,Personal Travel,Eco Plus,319,3,4,3,3,1,3,1,1,1,4,4,4,2,1,0,0.0,neutral or dissatisfied +2569,45126,Male,Loyal Customer,62,Personal Travel,Eco,157,1,3,1,3,3,1,3,3,4,1,3,2,4,3,0,54.0,neutral or dissatisfied +2570,36410,Male,disloyal Customer,45,Business travel,Eco,369,4,0,4,4,1,4,5,1,3,5,4,2,1,1,0,0.0,neutral or dissatisfied +2571,77677,Male,disloyal Customer,26,Business travel,Business,689,1,1,1,3,5,1,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +2572,93080,Male,disloyal Customer,28,Business travel,Business,860,4,4,4,4,2,4,2,2,3,4,5,5,4,2,62,54.0,neutral or dissatisfied +2573,29286,Female,disloyal Customer,24,Business travel,Eco,933,1,1,1,3,1,1,1,1,1,1,2,4,2,1,0,10.0,neutral or dissatisfied +2574,28414,Female,Loyal Customer,26,Personal Travel,Business,1399,4,2,4,4,4,4,5,4,1,2,4,4,4,4,0,0.0,neutral or dissatisfied +2575,21840,Male,Loyal Customer,63,Business travel,Business,448,2,2,2,2,5,4,5,4,4,5,4,3,4,4,15,8.0,satisfied +2576,42486,Female,disloyal Customer,26,Business travel,Eco,693,3,3,3,3,3,3,3,3,5,5,1,1,1,3,0,0.0,neutral or dissatisfied +2577,49355,Male,Loyal Customer,41,Business travel,Business,3306,5,5,5,5,1,5,4,5,5,5,5,2,5,2,28,24.0,satisfied +2578,46728,Female,Loyal Customer,17,Personal Travel,Eco,125,3,2,0,4,5,0,5,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +2579,34516,Female,Loyal Customer,36,Personal Travel,Eco,1521,2,2,2,3,5,2,5,5,3,4,3,3,3,5,0,4.0,neutral or dissatisfied +2580,7236,Female,Loyal Customer,30,Business travel,Business,2237,2,2,3,2,4,4,3,4,1,3,3,5,4,4,0,0.0,satisfied +2581,85813,Female,Loyal Customer,27,Personal Travel,Eco,666,2,0,2,1,3,2,3,3,3,5,4,5,4,3,1,5.0,neutral or dissatisfied +2582,76379,Female,Loyal Customer,65,Business travel,Business,931,4,5,5,5,1,3,4,4,4,4,4,4,4,3,0,1.0,neutral or dissatisfied +2583,35230,Female,disloyal Customer,23,Business travel,Eco,1056,3,3,3,4,4,3,4,4,3,3,1,1,4,4,0,0.0,neutral or dissatisfied +2584,127167,Male,Loyal Customer,10,Personal Travel,Eco,325,3,3,3,5,3,3,3,3,2,3,3,2,5,3,0,0.0,neutral or dissatisfied +2585,56679,Male,Loyal Customer,16,Personal Travel,Eco,937,4,5,4,3,3,4,3,3,5,4,4,5,4,3,2,8.0,neutral or dissatisfied +2586,54901,Female,Loyal Customer,8,Personal Travel,Eco,862,2,4,2,5,3,2,5,3,3,2,5,4,5,3,0,10.0,neutral or dissatisfied +2587,30642,Female,disloyal Customer,32,Business travel,Eco,533,2,4,2,3,2,2,4,2,2,1,3,3,4,2,20,24.0,neutral or dissatisfied +2588,49038,Female,Loyal Customer,56,Business travel,Business,2138,2,2,2,2,4,1,1,3,3,4,3,1,3,1,1,0.0,satisfied +2589,65666,Female,Loyal Customer,59,Business travel,Business,861,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,17.0,satisfied +2590,77986,Male,disloyal Customer,23,Business travel,Eco,332,1,0,1,4,2,1,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +2591,69194,Female,Loyal Customer,59,Business travel,Business,3660,0,4,0,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +2592,104096,Female,disloyal Customer,38,Business travel,Business,297,3,3,3,4,5,3,5,5,4,5,3,2,4,5,0,2.0,neutral or dissatisfied +2593,24109,Female,Loyal Customer,37,Business travel,Business,1654,1,5,4,4,2,4,4,1,1,1,1,2,1,1,15,15.0,neutral or dissatisfied +2594,117444,Male,Loyal Customer,39,Business travel,Eco,1020,3,2,2,2,3,3,3,3,4,5,3,4,4,3,32,17.0,neutral or dissatisfied +2595,103292,Male,Loyal Customer,46,Business travel,Eco,872,2,1,1,1,3,2,3,3,2,4,4,4,4,3,42,32.0,neutral or dissatisfied +2596,62028,Male,Loyal Customer,40,Business travel,Business,2475,4,4,4,4,5,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +2597,117607,Male,Loyal Customer,24,Business travel,Business,2197,2,2,2,2,4,4,4,4,4,3,5,4,4,4,2,0.0,satisfied +2598,115217,Female,Loyal Customer,37,Business travel,Business,325,4,4,4,4,3,4,5,4,4,4,4,3,4,5,39,37.0,satisfied +2599,78888,Female,disloyal Customer,21,Business travel,Eco,826,2,2,2,3,3,2,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +2600,60946,Male,disloyal Customer,20,Business travel,Eco,888,2,2,2,2,4,2,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +2601,74656,Female,Loyal Customer,38,Personal Travel,Eco,1431,3,5,3,3,3,3,5,3,4,3,4,5,4,3,5,0.0,neutral or dissatisfied +2602,106036,Female,Loyal Customer,19,Personal Travel,Eco Plus,682,2,5,1,2,1,1,1,1,4,2,5,4,4,1,38,24.0,neutral or dissatisfied +2603,80877,Male,Loyal Customer,49,Personal Travel,Eco,692,2,4,3,1,5,3,5,5,3,2,4,4,4,5,0,6.0,neutral or dissatisfied +2604,55426,Male,Loyal Customer,58,Business travel,Business,2136,2,1,2,2,4,4,5,2,2,2,2,3,2,3,9,0.0,satisfied +2605,66392,Female,Loyal Customer,35,Business travel,Business,1562,4,4,4,4,2,5,4,4,4,4,4,4,4,4,12,31.0,satisfied +2606,31173,Male,Loyal Customer,28,Business travel,Eco Plus,604,2,2,2,2,2,2,2,2,1,5,3,2,3,2,42,42.0,neutral or dissatisfied +2607,117447,Male,Loyal Customer,47,Business travel,Eco,1107,3,4,4,4,3,3,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +2608,62437,Male,Loyal Customer,46,Business travel,Business,1943,2,2,2,2,2,5,4,5,5,5,5,5,5,5,18,12.0,satisfied +2609,75660,Female,Loyal Customer,40,Personal Travel,Eco,304,2,4,2,3,2,2,2,2,3,4,4,4,4,2,7,5.0,neutral or dissatisfied +2610,100582,Male,Loyal Customer,46,Business travel,Business,486,4,4,4,4,4,4,4,4,4,4,4,3,4,3,11,18.0,satisfied +2611,13287,Male,Loyal Customer,67,Personal Travel,Eco,771,1,4,1,2,2,1,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +2612,10685,Male,disloyal Customer,39,Business travel,Business,458,5,5,5,1,1,5,1,1,3,5,4,5,4,1,0,0.0,satisfied +2613,63255,Female,disloyal Customer,22,Business travel,Business,447,4,2,4,4,4,4,4,4,3,5,4,4,4,4,190,186.0,satisfied +2614,114748,Male,Loyal Customer,52,Business travel,Business,3187,4,5,4,4,2,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +2615,90641,Female,disloyal Customer,40,Business travel,Business,250,3,3,3,1,2,3,5,2,3,5,5,3,5,2,0,13.0,satisfied +2616,65806,Female,Loyal Customer,54,Business travel,Business,1389,2,5,5,5,3,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +2617,123657,Male,Loyal Customer,32,Business travel,Business,214,5,5,5,5,4,4,4,4,4,2,5,4,5,4,0,0.0,satisfied +2618,105042,Male,Loyal Customer,24,Personal Travel,Eco,255,3,5,3,4,3,3,3,3,5,2,5,4,5,3,53,30.0,neutral or dissatisfied +2619,13900,Female,Loyal Customer,50,Business travel,Business,3796,4,1,1,1,2,4,3,2,2,2,4,1,2,1,2,2.0,neutral or dissatisfied +2620,7618,Male,Loyal Customer,50,Business travel,Business,3477,5,5,5,5,2,5,4,2,2,2,2,5,2,5,0,52.0,satisfied +2621,27420,Male,Loyal Customer,23,Business travel,Business,2291,4,4,4,4,5,5,5,5,3,1,5,2,4,5,0,0.0,satisfied +2622,996,Female,disloyal Customer,34,Business travel,Eco,309,1,4,1,4,1,3,3,2,5,2,5,3,5,3,168,165.0,neutral or dissatisfied +2623,101160,Female,Loyal Customer,25,Business travel,Business,2895,2,1,1,1,2,3,2,2,3,1,3,4,2,2,16,6.0,neutral or dissatisfied +2624,47483,Male,Loyal Customer,54,Personal Travel,Eco,532,1,4,1,2,3,1,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +2625,62757,Female,Loyal Customer,49,Business travel,Business,2338,2,2,2,2,5,3,4,3,3,3,3,4,3,5,2,0.0,satisfied +2626,70036,Male,Loyal Customer,54,Business travel,Eco,583,4,1,1,1,4,4,4,4,4,2,4,1,3,4,13,0.0,neutral or dissatisfied +2627,115693,Male,Loyal Customer,37,Business travel,Business,2835,2,5,5,5,4,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +2628,80458,Female,Loyal Customer,57,Business travel,Business,3755,2,2,2,2,3,4,5,5,5,5,5,3,5,5,28,35.0,satisfied +2629,91302,Female,Loyal Customer,41,Business travel,Eco Plus,240,3,1,1,1,3,3,2,3,3,3,3,2,3,1,3,0.0,neutral or dissatisfied +2630,3638,Male,Loyal Customer,35,Business travel,Business,1534,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,,satisfied +2631,19415,Female,Loyal Customer,25,Business travel,Business,2474,1,1,1,1,5,5,5,5,3,3,4,4,4,5,10,8.0,satisfied +2632,55903,Male,Loyal Customer,62,Business travel,Business,2853,3,3,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +2633,99068,Male,disloyal Customer,37,Business travel,Business,419,3,3,3,2,5,3,5,5,5,5,4,3,5,5,23,26.0,neutral or dissatisfied +2634,81224,Female,Loyal Customer,64,Personal Travel,Eco,1426,1,1,1,3,3,2,2,4,4,1,4,2,4,2,48,75.0,neutral or dissatisfied +2635,115684,Female,Loyal Customer,23,Business travel,Business,1665,1,1,1,1,5,5,5,5,5,2,5,5,4,5,1,0.0,satisfied +2636,1429,Male,Loyal Customer,45,Business travel,Business,772,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +2637,23577,Female,Loyal Customer,30,Business travel,Business,2846,2,2,2,2,5,5,5,5,5,3,1,2,2,5,0,0.0,satisfied +2638,28006,Male,Loyal Customer,47,Business travel,Eco,763,4,2,2,2,4,4,4,4,3,1,3,5,5,4,0,0.0,satisfied +2639,68393,Male,Loyal Customer,53,Business travel,Business,2306,4,4,4,4,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +2640,42303,Female,Loyal Customer,35,Personal Travel,Eco,329,1,5,1,2,4,1,2,4,1,2,2,3,2,4,5,0.0,neutral or dissatisfied +2641,19419,Male,Loyal Customer,44,Business travel,Eco,645,3,4,4,4,3,3,3,3,4,2,3,1,4,3,44,32.0,neutral or dissatisfied +2642,60093,Male,Loyal Customer,30,Business travel,Business,1012,3,2,3,3,4,4,4,4,4,2,5,3,4,4,6,0.0,satisfied +2643,76117,Male,Loyal Customer,16,Business travel,Business,1716,3,3,4,3,5,5,5,5,4,5,5,3,4,5,0,0.0,satisfied +2644,32336,Female,disloyal Customer,25,Business travel,Eco,102,2,0,2,4,1,2,1,1,2,3,3,1,4,1,0,0.0,neutral or dissatisfied +2645,43200,Female,Loyal Customer,29,Business travel,Business,466,4,4,4,4,4,4,4,4,1,4,1,1,5,4,66,67.0,satisfied +2646,9789,Male,Loyal Customer,49,Personal Travel,Eco,383,4,4,4,1,2,4,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +2647,35739,Male,Loyal Customer,48,Business travel,Eco,2153,4,5,5,5,4,4,4,4,3,1,3,5,4,4,0,0.0,satisfied +2648,100988,Male,Loyal Customer,57,Business travel,Business,867,2,4,4,4,3,4,3,2,2,2,2,4,2,2,15,10.0,neutral or dissatisfied +2649,78426,Female,Loyal Customer,30,Business travel,Business,2002,5,5,5,5,4,5,5,5,4,4,4,5,5,5,211,211.0,satisfied +2650,60870,Male,disloyal Customer,34,Business travel,Business,1491,1,1,1,2,1,1,1,1,5,5,5,3,4,1,59,46.0,neutral or dissatisfied +2651,25531,Female,Loyal Customer,16,Personal Travel,Eco,547,2,5,2,2,5,2,5,5,5,3,4,3,4,5,32,44.0,neutral or dissatisfied +2652,7880,Male,disloyal Customer,42,Business travel,Eco,910,1,1,1,3,5,1,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +2653,88304,Male,disloyal Customer,15,Business travel,Eco,545,3,2,2,4,2,2,3,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +2654,55153,Male,Loyal Customer,17,Personal Travel,Eco,1635,2,4,2,4,1,2,3,1,5,3,4,3,4,1,1,0.0,neutral or dissatisfied +2655,72204,Male,Loyal Customer,56,Business travel,Business,2724,3,5,3,3,5,5,5,3,3,5,4,5,5,5,6,0.0,satisfied +2656,7159,Female,Loyal Customer,42,Business travel,Business,135,3,3,3,3,5,4,5,4,4,4,5,4,4,3,4,0.0,satisfied +2657,37224,Female,Loyal Customer,39,Business travel,Business,989,2,2,2,2,4,4,4,4,4,4,4,4,4,3,77,67.0,satisfied +2658,6894,Female,Loyal Customer,50,Business travel,Business,1793,4,4,4,4,2,4,5,4,4,4,4,4,4,4,25,73.0,satisfied +2659,88038,Male,Loyal Customer,52,Business travel,Business,3889,5,5,1,5,4,5,5,5,5,5,5,3,5,5,0,1.0,satisfied +2660,120011,Female,Loyal Customer,70,Personal Travel,Eco,328,0,0,0,3,4,3,4,2,2,0,2,4,2,5,0,0.0,satisfied +2661,98052,Female,Loyal Customer,14,Business travel,Eco,1797,1,4,4,4,1,2,1,1,4,3,3,1,4,1,0,0.0,neutral or dissatisfied +2662,128984,Male,Loyal Customer,70,Personal Travel,Eco,236,4,5,4,3,4,4,4,4,1,1,5,1,2,4,0,0.0,neutral or dissatisfied +2663,84774,Male,disloyal Customer,32,Business travel,Business,534,3,3,3,4,1,3,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +2664,69358,Male,Loyal Customer,54,Business travel,Business,1096,5,5,1,5,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +2665,66338,Female,disloyal Customer,26,Business travel,Business,986,1,1,1,2,3,1,3,3,4,5,4,4,5,3,5,0.0,neutral or dissatisfied +2666,408,Female,Loyal Customer,47,Business travel,Business,3169,2,5,5,5,1,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +2667,54566,Female,Loyal Customer,28,Business travel,Eco Plus,925,0,0,0,2,5,0,5,5,1,1,4,2,1,5,89,92.0,satisfied +2668,70576,Male,Loyal Customer,51,Personal Travel,Eco,1258,5,5,5,1,3,5,3,3,5,4,5,5,4,3,0,0.0,satisfied +2669,70236,Male,disloyal Customer,25,Business travel,Eco,782,4,4,4,1,5,4,5,5,3,2,3,3,5,5,0,32.0,satisfied +2670,22909,Female,Loyal Customer,30,Business travel,Business,1597,3,3,3,3,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +2671,96609,Male,Loyal Customer,43,Business travel,Business,3723,2,2,2,2,4,4,5,2,2,2,2,5,2,5,5,10.0,satisfied +2672,84781,Male,Loyal Customer,43,Business travel,Business,2970,2,2,3,2,2,5,5,4,4,4,4,4,4,5,45,74.0,satisfied +2673,100336,Female,Loyal Customer,67,Business travel,Eco,633,3,5,1,5,3,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +2674,105982,Female,Loyal Customer,13,Personal Travel,Eco,2295,3,1,3,3,3,2,2,4,4,1,3,2,1,2,6,17.0,neutral or dissatisfied +2675,50277,Female,Loyal Customer,58,Business travel,Business,1787,3,2,2,2,4,4,3,5,5,4,3,4,5,3,0,0.0,neutral or dissatisfied +2676,120722,Male,disloyal Customer,21,Business travel,Eco,90,3,0,3,4,1,3,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +2677,126881,Male,Loyal Customer,44,Personal Travel,Eco,2125,2,5,3,3,3,3,3,3,1,4,1,2,1,3,0,22.0,neutral or dissatisfied +2678,24965,Male,Loyal Customer,54,Personal Travel,Eco,226,3,5,3,2,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +2679,66197,Male,disloyal Customer,36,Business travel,Eco,550,4,4,4,3,2,4,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +2680,96113,Male,Loyal Customer,46,Business travel,Business,1069,1,1,1,1,3,5,4,5,5,5,5,4,5,5,16,18.0,satisfied +2681,67483,Male,Loyal Customer,58,Personal Travel,Eco,641,1,5,0,4,3,0,3,3,5,2,4,3,4,3,31,24.0,neutral or dissatisfied +2682,73479,Female,Loyal Customer,69,Personal Travel,Eco,1005,3,5,3,3,5,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +2683,12632,Female,Loyal Customer,18,Business travel,Business,2046,5,5,1,5,4,4,4,4,2,3,4,1,2,4,33,16.0,satisfied +2684,57387,Male,Loyal Customer,36,Business travel,Business,3491,5,5,5,5,4,4,4,3,3,3,3,5,3,4,0,4.0,satisfied +2685,6534,Female,Loyal Customer,35,Personal Travel,Eco Plus,599,5,3,5,3,3,5,1,3,2,5,2,3,3,3,0,0.0,satisfied +2686,102668,Female,Loyal Customer,52,Business travel,Business,1709,3,3,3,3,2,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +2687,34710,Female,Loyal Customer,27,Business travel,Business,2462,4,4,4,4,4,4,4,4,2,4,5,2,1,4,0,0.0,satisfied +2688,104713,Female,Loyal Customer,27,Business travel,Business,1342,4,4,4,4,3,3,3,3,5,5,4,3,5,3,0,4.0,satisfied +2689,14787,Male,Loyal Customer,34,Business travel,Business,3488,3,3,3,3,1,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +2690,119874,Female,Loyal Customer,21,Personal Travel,Eco,912,0,5,0,1,1,0,1,1,4,3,5,3,5,1,2,0.0,satisfied +2691,45527,Female,Loyal Customer,36,Personal Travel,Eco Plus,689,2,5,2,2,3,2,3,3,5,3,4,5,4,3,26,22.0,neutral or dissatisfied +2692,23970,Male,disloyal Customer,23,Business travel,Eco,596,0,0,1,4,3,1,3,3,5,2,4,3,5,3,0,0.0,satisfied +2693,80331,Male,Loyal Customer,25,Personal Travel,Eco,746,4,4,4,4,3,4,3,3,3,4,4,3,5,3,0,0.0,satisfied +2694,25682,Male,Loyal Customer,46,Business travel,Eco Plus,361,3,4,4,4,3,3,3,3,3,1,1,2,1,3,0,6.0,satisfied +2695,14560,Male,Loyal Customer,31,Personal Travel,Eco Plus,288,1,4,1,1,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +2696,112391,Female,Loyal Customer,40,Business travel,Eco,846,2,5,5,5,2,2,2,2,3,3,2,3,3,2,2,0.0,neutral or dissatisfied +2697,124711,Female,Loyal Customer,62,Personal Travel,Eco,399,1,4,1,2,4,4,5,2,2,1,2,4,2,3,0,1.0,neutral or dissatisfied +2698,1896,Male,Loyal Customer,45,Business travel,Business,295,0,0,0,3,3,5,4,1,1,1,1,4,1,4,29,28.0,satisfied +2699,89848,Female,Loyal Customer,10,Personal Travel,Business,1306,1,5,1,3,2,1,2,2,5,2,3,5,5,2,89,76.0,neutral or dissatisfied +2700,105539,Male,Loyal Customer,53,Business travel,Eco,211,4,4,4,4,4,4,4,4,5,3,1,1,4,4,5,0.0,satisfied +2701,62398,Female,Loyal Customer,49,Personal Travel,Eco,2704,3,2,4,2,2,3,3,2,2,4,2,1,2,1,4,0.0,neutral or dissatisfied +2702,61386,Male,disloyal Customer,20,Business travel,Business,679,4,0,4,5,2,4,2,2,4,5,5,4,4,2,25,6.0,satisfied +2703,95491,Female,disloyal Customer,33,Business travel,Business,189,3,2,2,4,2,2,5,3,3,4,4,5,4,5,324,323.0,neutral or dissatisfied +2704,27775,Male,Loyal Customer,32,Business travel,Business,1917,3,5,5,5,3,2,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +2705,85022,Female,Loyal Customer,50,Personal Travel,Eco,1590,4,4,4,4,5,5,4,5,5,4,5,3,5,4,72,69.0,neutral or dissatisfied +2706,25778,Female,Loyal Customer,21,Business travel,Eco,762,4,4,4,4,4,4,3,4,3,2,4,5,5,4,3,7.0,satisfied +2707,109225,Male,Loyal Customer,49,Personal Travel,Eco,616,2,4,2,1,5,2,4,5,5,3,5,5,4,5,46,39.0,neutral or dissatisfied +2708,71928,Female,disloyal Customer,36,Business travel,Business,1846,4,4,4,3,4,4,4,4,5,4,3,3,4,4,11,4.0,neutral or dissatisfied +2709,62473,Female,Loyal Customer,58,Business travel,Business,1744,4,4,4,4,2,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +2710,113983,Male,Loyal Customer,12,Business travel,Business,1844,5,5,3,5,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +2711,28690,Female,Loyal Customer,36,Business travel,Eco,2182,3,2,2,2,3,3,3,3,2,5,3,5,2,3,0,0.0,satisfied +2712,128718,Male,Loyal Customer,58,Business travel,Business,1464,2,2,2,2,2,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +2713,78035,Male,Loyal Customer,59,Personal Travel,Eco,214,5,0,5,4,4,5,4,4,3,4,4,3,5,4,5,0.0,satisfied +2714,97863,Female,Loyal Customer,36,Business travel,Business,793,1,1,1,1,3,5,4,4,4,4,4,3,4,3,60,79.0,satisfied +2715,84867,Female,Loyal Customer,9,Personal Travel,Eco,516,5,2,5,2,2,5,1,2,3,1,2,1,2,2,21,5.0,satisfied +2716,47932,Female,Loyal Customer,32,Personal Travel,Eco,834,2,5,2,1,1,2,3,1,2,3,1,5,2,1,0,0.0,neutral or dissatisfied +2717,119302,Female,Loyal Customer,66,Business travel,Eco,214,3,4,4,4,4,4,3,3,3,3,3,3,3,2,7,0.0,neutral or dissatisfied +2718,76644,Female,Loyal Customer,67,Personal Travel,Eco,481,1,3,2,4,4,4,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +2719,8026,Male,Loyal Customer,53,Business travel,Business,1517,0,4,0,4,5,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +2720,36504,Male,Loyal Customer,26,Business travel,Business,3087,3,3,3,3,4,4,4,4,4,1,5,2,2,4,85,91.0,satisfied +2721,85490,Male,Loyal Customer,23,Personal Travel,Eco,152,0,5,0,2,2,0,2,2,3,4,4,3,4,2,1,0.0,satisfied +2722,6978,Female,Loyal Customer,54,Business travel,Business,147,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +2723,93212,Female,Loyal Customer,7,Personal Travel,Eco,1845,2,4,2,3,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +2724,84183,Female,Loyal Customer,35,Business travel,Business,432,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,2.0,satisfied +2725,67968,Female,disloyal Customer,38,Business travel,Eco Plus,1126,2,1,1,4,2,1,2,2,2,3,4,3,3,2,20,13.0,neutral or dissatisfied +2726,45719,Male,Loyal Customer,47,Business travel,Business,624,1,4,3,4,3,4,3,1,1,2,1,4,1,1,14,15.0,neutral or dissatisfied +2727,109062,Female,disloyal Customer,8,Business travel,Eco,849,4,4,4,3,4,4,4,4,1,2,3,2,4,4,39,29.0,neutral or dissatisfied +2728,114835,Female,Loyal Customer,55,Business travel,Business,447,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +2729,100982,Male,Loyal Customer,36,Business travel,Business,1669,5,5,1,5,2,1,2,2,2,2,2,1,2,5,0,0.0,satisfied +2730,63793,Male,Loyal Customer,38,Personal Travel,Eco,1721,2,4,2,2,2,2,2,2,5,2,3,4,4,2,0,0.0,neutral or dissatisfied +2731,53580,Male,Loyal Customer,23,Personal Travel,Eco,1195,3,5,3,2,1,3,2,1,5,3,4,5,4,1,4,0.0,neutral or dissatisfied +2732,58033,Male,disloyal Customer,20,Business travel,Business,612,5,4,5,2,3,5,3,3,3,4,5,5,5,3,0,0.0,satisfied +2733,72620,Male,Loyal Customer,47,Personal Travel,Eco,929,4,4,4,3,5,4,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +2734,60598,Female,Loyal Customer,24,Business travel,Business,1558,4,4,4,4,4,4,4,4,5,5,5,5,5,4,5,12.0,satisfied +2735,115292,Male,disloyal Customer,23,Business travel,Eco,337,4,1,4,2,2,4,5,2,3,1,3,1,2,2,11,12.0,neutral or dissatisfied +2736,96135,Male,Loyal Customer,43,Business travel,Business,3890,1,2,2,2,4,3,3,1,1,2,1,1,1,3,30,18.0,neutral or dissatisfied +2737,107633,Female,Loyal Customer,7,Personal Travel,Eco Plus,423,2,2,4,3,3,4,3,3,4,4,3,2,4,3,1,0.0,neutral or dissatisfied +2738,79516,Male,Loyal Customer,28,Business travel,Business,2472,2,2,2,2,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +2739,29681,Male,Loyal Customer,31,Business travel,Eco Plus,909,5,2,2,2,5,5,5,5,2,5,2,4,5,5,0,1.0,satisfied +2740,24613,Female,disloyal Customer,28,Business travel,Eco,526,4,3,4,2,3,4,3,3,1,2,5,1,5,3,0,1.0,satisfied +2741,81952,Male,Loyal Customer,56,Business travel,Business,1535,5,5,5,5,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2742,109154,Male,Loyal Customer,48,Business travel,Business,1528,4,4,4,4,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +2743,2018,Male,Loyal Customer,55,Business travel,Business,1520,1,1,1,1,5,5,4,3,3,3,3,5,3,3,48,48.0,satisfied +2744,22363,Male,Loyal Customer,35,Business travel,Business,83,1,1,5,1,1,5,2,5,5,4,5,5,5,2,1,0.0,satisfied +2745,54312,Male,Loyal Customer,45,Business travel,Business,1597,4,1,4,4,1,5,1,4,4,4,4,3,4,4,0,0.0,satisfied +2746,13977,Female,Loyal Customer,28,Personal Travel,Eco Plus,192,2,4,0,2,2,0,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +2747,4849,Male,Loyal Customer,29,Business travel,Business,3198,1,3,3,3,1,1,1,1,4,5,4,1,3,1,0,0.0,neutral or dissatisfied +2748,78821,Male,Loyal Customer,40,Personal Travel,Eco,554,2,4,2,3,4,2,4,4,4,4,5,3,4,4,0,3.0,neutral or dissatisfied +2749,19409,Female,Loyal Customer,69,Personal Travel,Business,645,3,5,2,2,2,4,3,2,2,2,2,3,2,2,69,46.0,neutral or dissatisfied +2750,1491,Female,Loyal Customer,54,Business travel,Business,737,4,4,4,4,4,2,2,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +2751,91845,Male,disloyal Customer,26,Business travel,Business,1797,2,2,2,3,2,2,1,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +2752,92791,Male,disloyal Customer,33,Business travel,Eco,1423,2,2,2,3,4,2,5,4,1,2,2,2,4,4,0,0.0,neutral or dissatisfied +2753,38522,Female,Loyal Customer,46,Business travel,Eco,2475,4,3,3,3,3,5,1,4,4,4,4,3,4,2,0,0.0,satisfied +2754,24309,Female,Loyal Customer,42,Personal Travel,Eco Plus,302,4,5,4,2,4,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +2755,70599,Male,disloyal Customer,27,Business travel,Business,2611,2,2,2,3,2,4,4,3,3,5,4,4,5,4,0,17.0,neutral or dissatisfied +2756,55386,Female,Loyal Customer,21,Personal Travel,Eco,413,1,4,1,2,3,1,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +2757,52337,Male,Loyal Customer,53,Business travel,Eco,261,2,4,4,4,2,2,2,2,3,3,1,1,1,2,0,1.0,neutral or dissatisfied +2758,58253,Male,Loyal Customer,67,Personal Travel,Eco,849,0,3,0,3,5,0,5,5,3,1,5,4,1,5,0,0.0,satisfied +2759,86750,Male,Loyal Customer,23,Business travel,Business,2530,4,4,4,4,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +2760,50911,Female,Loyal Customer,22,Personal Travel,Eco,373,3,2,5,3,4,5,4,4,2,2,3,1,3,4,0,0.0,neutral or dissatisfied +2761,105702,Male,Loyal Customer,22,Business travel,Business,2785,4,1,1,1,4,4,4,4,2,4,3,4,3,4,14,19.0,neutral or dissatisfied +2762,61818,Female,Loyal Customer,40,Personal Travel,Eco,1635,1,4,2,3,1,2,1,1,4,3,4,5,5,1,45,28.0,neutral or dissatisfied +2763,95500,Female,Loyal Customer,77,Business travel,Eco Plus,496,4,2,2,2,4,2,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +2764,36435,Male,Loyal Customer,25,Personal Travel,Eco,369,3,3,3,2,4,3,4,4,4,3,3,4,2,4,0,0.0,neutral or dissatisfied +2765,79734,Male,Loyal Customer,26,Business travel,Business,3510,1,1,1,1,3,3,3,3,4,3,4,3,4,3,35,47.0,satisfied +2766,71907,Female,Loyal Customer,52,Personal Travel,Eco,1846,2,5,2,3,4,5,4,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +2767,97307,Female,Loyal Customer,52,Business travel,Business,1843,2,2,2,2,4,4,5,5,5,5,5,4,5,5,23,15.0,satisfied +2768,51029,Male,Loyal Customer,56,Personal Travel,Eco,78,3,4,3,2,3,3,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +2769,34313,Female,Loyal Customer,55,Business travel,Eco Plus,280,3,3,3,3,4,3,3,3,3,3,3,2,3,2,4,21.0,neutral or dissatisfied +2770,95908,Female,Loyal Customer,50,Business travel,Business,2612,2,2,2,2,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +2771,17612,Male,Loyal Customer,31,Business travel,Business,1892,4,4,4,4,5,5,5,5,2,5,3,3,4,5,0,0.0,satisfied +2772,91370,Female,Loyal Customer,54,Personal Travel,Eco Plus,406,3,5,3,1,2,5,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +2773,56813,Male,Loyal Customer,35,Business travel,Business,1605,2,2,2,2,3,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +2774,91908,Female,disloyal Customer,29,Business travel,Eco,1368,4,4,4,3,2,4,2,2,4,5,2,3,4,2,29,11.0,neutral or dissatisfied +2775,92527,Female,Loyal Customer,62,Personal Travel,Eco,2139,5,5,5,3,4,4,4,3,3,5,1,4,3,3,0,0.0,satisfied +2776,58544,Male,disloyal Customer,35,Business travel,Business,1514,3,3,3,1,4,3,1,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +2777,54336,Female,Loyal Customer,61,Personal Travel,Eco,1597,1,5,1,4,3,5,5,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +2778,114069,Male,Loyal Customer,52,Business travel,Business,2139,1,1,5,1,2,5,4,4,4,4,4,3,4,4,0,7.0,satisfied +2779,22676,Male,disloyal Customer,23,Business travel,Eco,589,2,0,2,2,2,5,5,1,2,5,2,5,2,5,154,176.0,neutral or dissatisfied +2780,50358,Male,Loyal Customer,33,Business travel,Eco,86,4,4,4,4,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +2781,8408,Female,disloyal Customer,54,Business travel,Business,862,2,2,2,3,3,2,3,3,3,5,4,3,4,3,84,103.0,neutral or dissatisfied +2782,35769,Male,Loyal Customer,48,Business travel,Business,200,4,4,4,4,3,1,5,4,4,4,5,1,4,1,0,0.0,satisfied +2783,42679,Female,Loyal Customer,39,Business travel,Business,627,1,1,1,1,5,2,3,4,4,4,4,3,4,2,51,38.0,satisfied +2784,57490,Female,Loyal Customer,12,Personal Travel,Business,1075,2,2,2,2,3,2,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +2785,43974,Female,disloyal Customer,21,Business travel,Business,411,4,0,4,2,1,4,1,1,3,4,1,1,4,1,0,2.0,satisfied +2786,92016,Female,Loyal Customer,41,Business travel,Business,1532,4,4,4,4,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +2787,104863,Female,Loyal Customer,31,Business travel,Business,1813,2,4,4,4,2,2,2,2,3,1,4,1,4,2,0,3.0,neutral or dissatisfied +2788,11993,Male,Loyal Customer,14,Personal Travel,Eco,643,4,4,4,3,1,4,1,1,3,5,4,5,4,1,54,45.0,neutral or dissatisfied +2789,81354,Female,Loyal Customer,9,Personal Travel,Eco,1299,2,5,2,1,3,2,3,3,3,4,3,5,5,3,0,0.0,neutral or dissatisfied +2790,45486,Male,Loyal Customer,37,Business travel,Business,1950,3,4,4,4,5,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +2791,48595,Male,Loyal Customer,40,Personal Travel,Eco,916,2,5,2,1,1,2,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +2792,17657,Male,disloyal Customer,17,Business travel,Eco,1008,1,1,1,3,1,1,4,1,2,5,3,4,4,1,33,32.0,neutral or dissatisfied +2793,54905,Female,Loyal Customer,11,Personal Travel,Eco,862,1,4,2,3,2,2,3,2,4,4,4,4,4,2,1,21.0,neutral or dissatisfied +2794,31194,Female,Loyal Customer,39,Business travel,Eco,628,2,4,4,4,2,2,2,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +2795,80566,Male,Loyal Customer,36,Business travel,Business,1747,4,4,4,4,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +2796,110750,Female,Loyal Customer,53,Business travel,Business,1105,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,6.0,satisfied +2797,104994,Male,Loyal Customer,9,Personal Travel,Eco,337,3,5,3,4,2,3,2,2,5,3,3,3,1,2,0,0.0,neutral or dissatisfied +2798,115021,Female,Loyal Customer,33,Business travel,Business,3240,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +2799,75783,Male,Loyal Customer,9,Personal Travel,Eco,813,2,4,2,4,4,2,4,4,3,3,3,3,4,4,0,0.0,neutral or dissatisfied +2800,34660,Female,Loyal Customer,56,Business travel,Business,264,2,2,2,2,3,5,4,5,5,5,5,4,5,5,2,7.0,satisfied +2801,37772,Male,Loyal Customer,33,Business travel,Eco Plus,950,4,5,5,5,4,4,4,4,1,3,3,3,2,4,17,12.0,satisfied +2802,1409,Female,Loyal Customer,53,Personal Travel,Eco Plus,229,2,4,2,2,2,5,5,3,3,2,3,4,3,5,27,19.0,neutral or dissatisfied +2803,66794,Female,Loyal Customer,53,Personal Travel,Eco,3784,3,4,3,3,3,5,5,4,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +2804,31892,Male,Loyal Customer,40,Personal Travel,Eco,2762,3,0,3,1,1,3,1,1,5,5,5,2,3,1,0,0.0,neutral or dissatisfied +2805,108887,Female,Loyal Customer,43,Business travel,Business,2327,4,4,4,4,4,5,5,5,5,5,5,5,5,5,106,104.0,satisfied +2806,108467,Male,Loyal Customer,33,Personal Travel,Eco,1444,4,2,4,3,5,4,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +2807,80214,Female,Loyal Customer,41,Business travel,Business,2153,3,3,3,3,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +2808,58312,Male,Loyal Customer,60,Business travel,Business,1739,4,4,4,4,5,3,5,2,2,2,2,3,2,5,6,0.0,satisfied +2809,63935,Male,Loyal Customer,43,Personal Travel,Eco,1158,2,4,2,3,3,2,5,3,3,4,5,3,4,3,8,0.0,neutral or dissatisfied +2810,119036,Female,Loyal Customer,22,Business travel,Business,2378,5,5,5,5,4,4,4,4,5,4,3,3,4,4,0,0.0,satisfied +2811,92774,Female,disloyal Customer,18,Business travel,Eco,1314,3,2,2,4,5,3,3,5,1,2,4,4,3,5,0,0.0,neutral or dissatisfied +2812,66236,Male,Loyal Customer,70,Business travel,Eco,150,2,1,1,1,2,2,2,2,2,2,3,3,3,2,38,40.0,neutral or dissatisfied +2813,98962,Female,Loyal Customer,72,Business travel,Eco,543,2,5,4,5,3,4,3,2,2,2,2,3,2,1,2,0.0,neutral or dissatisfied +2814,42509,Male,Loyal Customer,46,Business travel,Eco Plus,495,4,5,3,5,3,4,3,3,4,2,5,3,3,3,9,16.0,satisfied +2815,26507,Female,disloyal Customer,23,Business travel,Eco,829,1,2,2,4,2,2,2,2,1,4,3,1,4,2,6,0.0,neutral or dissatisfied +2816,21486,Female,Loyal Customer,36,Business travel,Business,2490,2,3,3,3,3,4,4,3,3,3,2,4,3,2,44,23.0,neutral or dissatisfied +2817,45866,Male,Loyal Customer,49,Personal Travel,Business,913,3,3,3,3,5,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +2818,117358,Male,Loyal Customer,50,Business travel,Business,3929,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +2819,53715,Male,Loyal Customer,27,Personal Travel,Eco,1208,1,2,1,4,1,1,1,1,2,2,4,3,3,1,0,0.0,neutral or dissatisfied +2820,96598,Female,Loyal Customer,57,Business travel,Eco Plus,461,4,3,4,4,5,1,2,4,4,4,4,4,4,5,0,14.0,satisfied +2821,72560,Male,disloyal Customer,23,Business travel,Eco,929,3,3,3,3,3,3,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +2822,66498,Female,Loyal Customer,39,Business travel,Business,447,5,5,5,5,4,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +2823,122787,Male,Loyal Customer,48,Business travel,Business,2894,5,5,5,5,4,4,4,4,4,4,4,4,4,3,0,11.0,satisfied +2824,63584,Male,disloyal Customer,23,Business travel,Eco,2133,3,3,3,3,1,3,1,1,1,1,3,3,3,1,1,0.0,neutral or dissatisfied +2825,118882,Male,Loyal Customer,49,Business travel,Business,3249,4,4,4,4,3,4,4,5,5,5,5,5,5,5,9,1.0,satisfied +2826,78533,Male,Loyal Customer,64,Personal Travel,Eco,526,2,4,2,1,3,2,3,3,5,2,4,3,4,3,0,2.0,neutral or dissatisfied +2827,75175,Male,Loyal Customer,42,Business travel,Business,1744,5,2,5,5,4,3,5,3,3,3,3,5,3,5,8,5.0,satisfied +2828,26213,Female,disloyal Customer,21,Business travel,Eco,270,4,0,4,1,3,4,4,3,5,2,1,4,4,3,15,0.0,neutral or dissatisfied +2829,95358,Female,Loyal Customer,19,Personal Travel,Eco,496,4,4,4,3,5,4,1,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +2830,102041,Male,Loyal Customer,43,Business travel,Business,3075,2,2,2,2,5,3,3,2,2,2,2,1,2,3,16,0.0,neutral or dissatisfied +2831,108387,Male,Loyal Customer,56,Personal Travel,Eco,1750,3,4,3,4,2,3,2,2,1,4,3,3,4,2,1,0.0,neutral or dissatisfied +2832,34205,Female,Loyal Customer,24,Personal Travel,Eco,1046,2,2,2,3,3,2,3,3,2,5,4,4,3,3,3,0.0,neutral or dissatisfied +2833,63804,Male,Loyal Customer,33,Business travel,Business,2724,4,4,4,4,5,5,5,5,3,2,4,3,5,5,2,5.0,satisfied +2834,68404,Male,Loyal Customer,44,Business travel,Business,1045,3,3,3,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +2835,123202,Female,Loyal Customer,66,Personal Travel,Eco,650,3,5,3,5,5,5,3,5,5,3,5,1,5,4,0,0.0,neutral or dissatisfied +2836,90963,Female,Loyal Customer,33,Business travel,Business,515,3,3,3,3,4,2,5,4,4,4,4,5,4,1,0,0.0,satisfied +2837,55239,Female,Loyal Customer,36,Business travel,Eco,609,3,5,4,5,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +2838,25942,Male,Loyal Customer,69,Business travel,Eco Plus,594,5,5,5,5,5,5,5,5,1,3,1,5,4,5,0,0.0,satisfied +2839,45935,Female,Loyal Customer,41,Personal Travel,Eco,563,2,4,2,1,2,2,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +2840,105848,Male,Loyal Customer,57,Business travel,Business,842,2,2,2,2,3,4,5,4,4,4,4,5,4,3,8,11.0,satisfied +2841,88334,Female,Loyal Customer,53,Business travel,Business,444,3,1,3,3,5,2,2,3,3,3,3,1,3,1,19,27.0,neutral or dissatisfied +2842,90987,Male,Loyal Customer,21,Business travel,Eco,581,2,3,3,3,2,2,1,2,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +2843,17452,Female,Loyal Customer,65,Business travel,Eco Plus,351,2,1,1,1,2,2,2,1,3,4,3,2,4,2,156,167.0,neutral or dissatisfied +2844,86671,Female,Loyal Customer,58,Personal Travel,Eco Plus,746,3,5,3,3,3,4,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +2845,129736,Female,Loyal Customer,32,Business travel,Business,308,3,3,3,3,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +2846,81350,Female,Loyal Customer,62,Personal Travel,Eco,1299,1,4,1,3,2,4,4,5,5,1,4,4,5,4,118,111.0,neutral or dissatisfied +2847,31870,Female,Loyal Customer,63,Personal Travel,Business,4983,0,5,0,2,0,5,1,3,2,4,3,1,5,1,3,0.0,satisfied +2848,45258,Female,Loyal Customer,37,Personal Travel,Eco,584,1,4,1,2,1,1,5,1,3,4,4,4,4,1,23,23.0,neutral or dissatisfied +2849,15891,Male,Loyal Customer,37,Business travel,Eco Plus,489,4,1,1,1,4,4,4,4,4,3,4,1,3,4,11,21.0,satisfied +2850,93314,Male,Loyal Customer,19,Personal Travel,Eco Plus,1733,3,5,3,4,1,3,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +2851,48084,Female,Loyal Customer,25,Business travel,Business,3518,2,2,2,2,4,4,4,4,5,3,2,4,4,4,0,0.0,satisfied +2852,83944,Male,Loyal Customer,30,Business travel,Business,321,0,0,0,3,4,2,2,4,4,3,4,5,4,4,0,7.0,satisfied +2853,40841,Female,Loyal Customer,39,Business travel,Business,2532,0,3,0,4,3,4,3,2,2,2,2,5,2,3,26,7.0,satisfied +2854,92408,Male,Loyal Customer,50,Business travel,Business,1892,4,4,2,4,2,3,5,5,5,5,5,3,5,5,28,14.0,satisfied +2855,11281,Male,Loyal Customer,67,Personal Travel,Eco,224,1,5,0,4,3,0,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +2856,23693,Male,Loyal Customer,42,Business travel,Eco,212,3,4,4,4,3,3,3,3,2,1,3,1,2,3,0,0.0,neutral or dissatisfied +2857,69419,Male,Loyal Customer,20,Business travel,Business,1096,4,5,5,5,4,4,4,4,4,3,4,4,3,4,75,65.0,neutral or dissatisfied +2858,125557,Female,disloyal Customer,47,Business travel,Eco,226,1,3,1,3,2,1,2,2,2,3,1,1,2,2,0,0.0,neutral or dissatisfied +2859,26249,Female,disloyal Customer,27,Business travel,Eco Plus,404,5,5,5,1,3,1,3,2,4,1,4,3,1,3,202,242.0,satisfied +2860,47602,Female,Loyal Customer,44,Business travel,Business,1549,2,2,2,2,3,2,1,4,4,4,4,2,4,2,0,0.0,satisfied +2861,18997,Male,Loyal Customer,38,Personal Travel,Eco Plus,388,2,5,2,1,4,2,3,4,4,3,4,4,5,4,11,21.0,neutral or dissatisfied +2862,91137,Male,Loyal Customer,21,Personal Travel,Eco,406,2,5,4,3,3,4,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +2863,88010,Female,Loyal Customer,40,Business travel,Business,545,4,4,4,4,3,4,5,4,4,4,4,4,4,5,17,15.0,satisfied +2864,75413,Female,disloyal Customer,19,Business travel,Eco,790,2,2,2,3,3,2,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +2865,125485,Female,Loyal Customer,8,Business travel,Eco Plus,2917,3,3,2,3,3,3,3,2,5,4,4,3,2,3,1,0.0,neutral or dissatisfied +2866,76051,Female,Loyal Customer,25,Business travel,Business,3003,2,2,2,2,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +2867,103107,Male,Loyal Customer,25,Personal Travel,Eco,546,3,3,5,4,5,5,3,5,1,3,2,4,5,5,0,0.0,neutral or dissatisfied +2868,121490,Female,Loyal Customer,52,Personal Travel,Eco,290,3,1,3,3,1,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +2869,17525,Female,Loyal Customer,30,Personal Travel,Eco,352,2,4,2,4,3,2,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +2870,34311,Male,Loyal Customer,32,Personal Travel,Eco,280,3,4,3,1,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +2871,31616,Male,Loyal Customer,57,Business travel,Business,2574,4,1,1,1,1,3,4,4,4,4,4,1,4,2,10,8.0,neutral or dissatisfied +2872,122839,Female,Loyal Customer,49,Business travel,Business,226,2,2,2,2,3,4,4,4,4,4,4,3,4,4,8,0.0,satisfied +2873,17127,Female,Loyal Customer,54,Business travel,Business,2607,1,1,2,1,5,5,5,3,5,2,3,5,4,5,290,284.0,satisfied +2874,107658,Male,Loyal Customer,40,Business travel,Business,3667,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +2875,89860,Female,Loyal Customer,55,Business travel,Business,1416,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +2876,105061,Male,Loyal Customer,18,Personal Travel,Eco Plus,255,2,4,2,1,2,2,2,2,3,4,4,4,5,2,7,6.0,neutral or dissatisfied +2877,86089,Male,disloyal Customer,23,Business travel,Eco,356,3,2,3,3,3,3,3,3,3,5,2,4,2,3,28,18.0,neutral or dissatisfied +2878,84180,Male,Loyal Customer,12,Personal Travel,Eco Plus,231,2,2,2,4,2,2,2,2,2,3,4,1,3,2,0,0.0,neutral or dissatisfied +2879,27244,Male,Loyal Customer,60,Personal Travel,Eco,1024,1,4,1,3,4,1,1,4,1,3,4,1,4,4,11,10.0,neutral or dissatisfied +2880,82329,Female,Loyal Customer,29,Personal Travel,Eco,456,1,5,1,3,2,1,1,2,4,5,5,4,5,2,53,69.0,neutral or dissatisfied +2881,75227,Female,Loyal Customer,41,Business travel,Eco,226,5,1,1,1,5,5,5,5,3,5,2,1,1,5,0,0.0,satisfied +2882,46987,Female,Loyal Customer,41,Personal Travel,Eco,737,3,4,3,2,3,3,3,3,3,4,4,5,5,3,21,26.0,neutral or dissatisfied +2883,102226,Male,Loyal Customer,49,Business travel,Business,2956,2,2,2,2,5,5,5,4,4,5,5,5,3,5,189,165.0,satisfied +2884,103753,Male,Loyal Customer,53,Personal Travel,Eco Plus,251,2,5,0,5,2,0,2,2,3,3,2,2,3,2,0,16.0,neutral or dissatisfied +2885,33873,Female,Loyal Customer,36,Business travel,Business,2203,5,4,5,5,2,3,5,3,3,3,3,2,3,1,0,1.0,satisfied +2886,104000,Male,Loyal Customer,56,Business travel,Eco,1363,3,4,4,4,3,3,3,3,2,5,4,2,4,3,0,0.0,neutral or dissatisfied +2887,10106,Male,Loyal Customer,34,Business travel,Business,391,2,5,5,5,1,4,3,2,2,2,2,3,2,2,72,67.0,neutral or dissatisfied +2888,3119,Male,Loyal Customer,46,Business travel,Eco,613,5,4,3,4,5,5,5,5,1,3,4,4,3,5,0,13.0,satisfied +2889,19586,Female,Loyal Customer,13,Personal Travel,Eco,160,3,4,3,2,2,3,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +2890,88203,Female,Loyal Customer,45,Business travel,Business,1530,5,5,5,5,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +2891,39578,Male,Loyal Customer,43,Business travel,Business,2202,2,2,2,2,4,5,4,4,4,4,4,2,4,1,0,0.0,satisfied +2892,114863,Female,Loyal Customer,43,Business travel,Business,2921,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +2893,118887,Female,Loyal Customer,44,Business travel,Business,2565,1,1,1,1,3,3,3,4,4,5,5,3,4,3,203,200.0,satisfied +2894,119648,Male,Loyal Customer,45,Business travel,Business,2788,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2895,33607,Female,Loyal Customer,53,Business travel,Eco,399,5,1,1,1,4,5,4,5,5,5,5,1,5,2,0,0.0,satisfied +2896,112707,Female,disloyal Customer,9,Business travel,Eco,697,4,4,4,4,5,4,5,5,3,3,4,1,4,5,22,19.0,neutral or dissatisfied +2897,21402,Female,Loyal Customer,50,Business travel,Eco,164,4,2,2,2,1,2,4,4,4,4,4,5,4,2,20,14.0,satisfied +2898,122749,Female,Loyal Customer,14,Personal Travel,Eco,651,5,5,5,2,5,5,5,5,4,2,1,3,4,5,24,27.0,satisfied +2899,16794,Female,Loyal Customer,35,Business travel,Business,1017,4,3,4,4,2,4,3,5,5,5,5,2,5,4,0,31.0,satisfied +2900,48177,Male,Loyal Customer,43,Business travel,Eco,192,4,4,4,4,4,4,4,4,1,4,2,4,1,4,0,0.0,neutral or dissatisfied +2901,116954,Female,Loyal Customer,53,Business travel,Business,370,2,2,2,2,5,4,5,5,5,5,5,4,5,4,19,13.0,satisfied +2902,91567,Male,disloyal Customer,28,Business travel,Business,1123,3,2,2,4,2,2,2,2,1,1,3,4,3,2,0,0.0,neutral or dissatisfied +2903,15729,Female,Loyal Customer,19,Personal Travel,Eco,419,3,4,1,4,3,1,3,3,2,5,5,2,5,3,120,128.0,neutral or dissatisfied +2904,89697,Female,Loyal Customer,33,Business travel,Business,1076,4,4,4,4,5,1,2,5,5,5,5,5,5,3,0,22.0,satisfied +2905,63074,Male,Loyal Customer,27,Personal Travel,Eco,846,3,5,3,4,3,3,3,5,4,5,4,3,4,3,157,145.0,neutral or dissatisfied +2906,114798,Female,Loyal Customer,51,Business travel,Business,2949,2,2,2,2,2,5,4,4,4,4,4,5,4,4,87,80.0,satisfied +2907,43558,Female,disloyal Customer,35,Business travel,Eco,770,2,2,2,4,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +2908,126168,Female,Loyal Customer,13,Business travel,Business,3092,1,2,2,2,1,1,1,1,3,4,3,1,3,1,5,12.0,neutral or dissatisfied +2909,39858,Male,Loyal Customer,58,Business travel,Eco,184,4,1,1,1,4,4,4,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +2910,25100,Male,Loyal Customer,58,Personal Travel,Eco,369,3,5,3,1,2,3,2,2,5,5,1,3,2,2,1,1.0,neutral or dissatisfied +2911,50861,Female,Loyal Customer,29,Personal Travel,Eco,373,4,4,4,1,3,4,2,3,4,2,5,2,4,3,59,52.0,neutral or dissatisfied +2912,98576,Female,disloyal Customer,17,Business travel,Eco,861,0,1,1,4,3,1,3,3,4,5,5,4,5,3,113,94.0,satisfied +2913,51846,Female,Loyal Customer,48,Personal Travel,Eco Plus,425,3,0,3,3,2,3,4,3,3,3,4,5,3,4,0,0.0,neutral or dissatisfied +2914,94542,Female,Loyal Customer,70,Business travel,Business,239,2,3,3,3,4,4,4,2,2,2,2,1,2,4,10,0.0,neutral or dissatisfied +2915,77610,Male,disloyal Customer,42,Business travel,Business,731,4,3,3,2,2,4,2,2,5,4,5,5,4,2,0,5.0,satisfied +2916,117936,Male,disloyal Customer,21,Business travel,Eco,255,2,4,2,4,1,2,1,1,1,2,3,4,4,1,119,108.0,neutral or dissatisfied +2917,9555,Female,Loyal Customer,54,Business travel,Business,3661,2,2,2,2,3,5,5,5,5,5,5,5,5,5,39,40.0,satisfied +2918,28851,Female,Loyal Customer,38,Business travel,Business,2763,1,1,1,1,5,1,3,4,4,4,4,2,4,4,0,0.0,satisfied +2919,96143,Male,disloyal Customer,33,Business travel,Business,328,3,3,3,2,5,3,1,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +2920,67329,Male,disloyal Customer,18,Business travel,Business,1471,5,3,5,3,5,5,4,5,5,2,5,3,5,5,0,0.0,satisfied +2921,122355,Female,Loyal Customer,49,Business travel,Business,529,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +2922,89374,Female,Loyal Customer,50,Personal Travel,Business,151,3,5,3,2,4,5,4,5,5,3,4,5,5,5,0,6.0,neutral or dissatisfied +2923,25962,Male,disloyal Customer,40,Business travel,Eco,946,4,4,4,5,3,4,3,3,1,2,2,4,2,3,0,0.0,neutral or dissatisfied +2924,117523,Female,disloyal Customer,49,Business travel,Business,843,3,3,3,1,3,3,3,3,3,5,4,5,5,3,6,0.0,satisfied +2925,11608,Female,Loyal Customer,9,Personal Travel,Eco,657,2,5,2,4,2,2,2,2,4,2,2,5,1,2,18,12.0,neutral or dissatisfied +2926,50957,Male,Loyal Customer,61,Personal Travel,Eco,110,3,1,3,4,5,3,5,5,3,2,3,2,3,5,0,0.0,neutral or dissatisfied +2927,78653,Female,Loyal Customer,59,Personal Travel,Eco,2172,4,4,4,1,5,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +2928,57890,Female,disloyal Customer,45,Business travel,Business,305,4,4,4,2,1,4,1,1,4,5,5,5,4,1,1,0.0,satisfied +2929,110753,Male,Loyal Customer,38,Business travel,Business,2745,1,1,3,1,2,5,5,5,5,5,5,5,5,5,4,0.0,satisfied +2930,90140,Male,Loyal Customer,36,Business travel,Business,727,5,5,5,5,2,4,1,4,4,4,4,5,4,4,0,0.0,satisfied +2931,3520,Female,Loyal Customer,43,Business travel,Business,3542,4,4,4,4,2,4,4,5,5,5,5,3,5,4,51,78.0,satisfied +2932,3913,Female,Loyal Customer,62,Personal Travel,Eco,213,3,5,3,4,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +2933,80093,Male,Loyal Customer,48,Business travel,Business,2762,5,5,5,5,4,5,5,5,5,5,5,4,5,4,41,26.0,satisfied +2934,40265,Female,Loyal Customer,37,Business travel,Eco,402,5,4,4,4,5,5,5,5,1,4,1,3,2,5,0,0.0,satisfied +2935,85590,Female,disloyal Customer,42,Business travel,Eco,259,3,3,3,3,3,3,3,3,4,2,4,2,3,3,68,60.0,neutral or dissatisfied +2936,5644,Male,Loyal Customer,50,Personal Travel,Business,299,1,5,1,3,3,5,4,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +2937,2519,Female,Loyal Customer,30,Business travel,Business,2403,1,1,1,1,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +2938,46744,Male,Loyal Customer,44,Personal Travel,Eco,152,2,2,0,3,1,0,1,1,1,2,4,1,4,1,20,10.0,neutral or dissatisfied +2939,74177,Male,Loyal Customer,29,Personal Travel,Eco,641,1,4,1,1,5,1,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +2940,54340,Female,Loyal Customer,34,Personal Travel,Eco,1597,3,4,4,1,5,4,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +2941,957,Female,Loyal Customer,17,Business travel,Business,312,2,2,2,2,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +2942,96489,Male,Loyal Customer,33,Business travel,Eco,302,3,4,3,3,3,3,3,3,2,3,2,4,2,3,1,0.0,neutral or dissatisfied +2943,25318,Male,Loyal Customer,7,Personal Travel,Eco,432,3,3,3,4,5,3,5,5,4,5,4,2,3,5,41,29.0,neutral or dissatisfied +2944,73463,Male,Loyal Customer,28,Personal Travel,Eco,1197,5,4,5,5,5,5,5,5,5,4,4,5,5,5,19,1.0,satisfied +2945,39220,Male,disloyal Customer,38,Business travel,Eco,173,3,0,3,3,3,3,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +2946,58918,Male,Loyal Customer,14,Personal Travel,Eco,888,3,5,3,3,2,3,5,2,3,4,5,1,4,2,0,0.0,neutral or dissatisfied +2947,2239,Male,Loyal Customer,55,Business travel,Business,859,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +2948,26918,Female,Loyal Customer,60,Personal Travel,Eco,1660,3,4,3,5,4,5,4,5,5,3,5,5,5,4,2,0.0,neutral or dissatisfied +2949,13676,Male,Loyal Customer,40,Personal Travel,Eco,462,2,4,2,1,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +2950,39053,Female,Loyal Customer,48,Personal Travel,Eco Plus,313,5,4,4,4,2,4,4,1,1,4,2,3,1,4,0,0.0,satisfied +2951,93851,Male,Loyal Customer,56,Personal Travel,Eco,391,2,4,3,2,1,3,2,1,3,2,4,3,4,1,10,7.0,neutral or dissatisfied +2952,91425,Female,Loyal Customer,49,Personal Travel,Eco,549,4,4,4,3,4,3,4,5,5,4,5,1,5,4,0,0.0,satisfied +2953,10367,Female,disloyal Customer,22,Business travel,Business,517,5,0,5,1,5,5,1,5,3,4,5,3,5,5,0,0.0,satisfied +2954,69055,Female,disloyal Customer,36,Business travel,Business,1389,2,2,2,2,5,2,5,5,5,2,5,5,5,5,2,0.0,neutral or dissatisfied +2955,69948,Female,Loyal Customer,53,Business travel,Business,2174,3,3,3,3,4,2,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +2956,110841,Female,Loyal Customer,33,Personal Travel,Eco Plus,990,4,5,4,2,2,4,2,2,4,3,5,3,5,2,5,0.0,neutral or dissatisfied +2957,59801,Male,Loyal Customer,17,Business travel,Business,3335,5,5,5,5,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +2958,106107,Male,Loyal Customer,39,Business travel,Business,302,0,0,0,5,2,5,5,3,3,3,3,5,3,5,39,48.0,satisfied +2959,21290,Female,disloyal Customer,14,Business travel,Eco,714,3,4,4,2,1,4,1,1,2,4,5,1,3,1,0,0.0,neutral or dissatisfied +2960,122083,Female,Loyal Customer,39,Personal Travel,Eco,130,2,4,0,4,4,0,4,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +2961,35497,Female,Loyal Customer,60,Personal Travel,Eco,1074,3,4,3,1,3,5,4,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +2962,106531,Female,Loyal Customer,66,Personal Travel,Eco,271,3,4,3,3,3,3,3,1,1,3,1,3,1,4,23,19.0,neutral or dissatisfied +2963,32243,Female,Loyal Customer,42,Business travel,Eco,101,1,4,4,4,3,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +2964,85050,Female,Loyal Customer,44,Business travel,Business,874,5,5,5,5,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +2965,84411,Female,Loyal Customer,20,Personal Travel,Eco,606,2,4,2,2,5,2,5,5,5,4,4,3,5,5,12,21.0,neutral or dissatisfied +2966,39052,Male,Loyal Customer,44,Personal Travel,Eco Plus,313,3,3,3,3,4,3,4,4,1,4,3,4,3,4,0,13.0,neutral or dissatisfied +2967,51780,Female,Loyal Customer,50,Personal Travel,Eco,355,2,5,2,2,2,5,5,5,5,2,1,4,5,5,0,6.0,neutral or dissatisfied +2968,22758,Female,Loyal Customer,55,Business travel,Business,3609,4,4,4,4,5,5,5,3,1,2,2,5,5,5,142,139.0,satisfied +2969,58616,Female,Loyal Customer,57,Business travel,Business,235,4,4,4,4,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +2970,120215,Female,Loyal Customer,13,Business travel,Business,3990,3,5,2,5,3,3,3,3,4,1,3,1,3,3,36,19.0,neutral or dissatisfied +2971,70180,Male,Loyal Customer,53,Business travel,Business,2339,5,5,5,5,5,5,5,4,4,4,4,5,4,4,9,13.0,satisfied +2972,75318,Male,Loyal Customer,60,Business travel,Business,2504,1,1,1,1,5,5,5,4,4,3,5,5,3,5,0,9.0,satisfied +2973,58306,Male,Loyal Customer,56,Business travel,Business,1739,3,3,3,3,2,3,4,5,5,5,5,4,5,4,26,7.0,satisfied +2974,3185,Male,disloyal Customer,29,Business travel,Eco,693,1,1,1,4,3,1,3,3,2,1,3,2,4,3,32,35.0,neutral or dissatisfied +2975,110092,Female,Loyal Customer,51,Business travel,Business,882,1,1,1,1,3,4,4,4,4,4,4,3,4,4,33,45.0,satisfied +2976,12117,Male,Loyal Customer,62,Business travel,Eco,1034,4,3,3,3,4,4,4,4,4,5,5,4,2,4,0,0.0,satisfied +2977,47826,Female,disloyal Customer,14,Business travel,Eco,550,3,1,3,4,5,3,5,5,4,4,4,2,4,5,23,16.0,neutral or dissatisfied +2978,106791,Male,Loyal Customer,66,Personal Travel,Business,977,3,4,3,1,5,4,4,4,4,3,4,3,4,4,29,28.0,neutral or dissatisfied +2979,94722,Male,disloyal Customer,22,Business travel,Eco,189,4,1,3,3,4,3,4,4,1,4,4,3,4,4,0,0.0,neutral or dissatisfied +2980,50363,Male,Loyal Customer,26,Business travel,Business,1759,2,2,4,2,3,4,3,3,5,1,5,5,5,3,0,0.0,satisfied +2981,7651,Female,Loyal Customer,26,Business travel,Business,3877,3,5,5,5,3,3,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +2982,65862,Female,Loyal Customer,64,Personal Travel,Eco,1389,4,2,4,2,3,1,2,3,3,4,3,1,3,3,4,0.0,satisfied +2983,100270,Male,Loyal Customer,49,Business travel,Business,2630,4,3,4,4,2,4,4,5,5,5,5,3,5,5,110,106.0,satisfied +2984,70405,Female,Loyal Customer,20,Personal Travel,Eco,1562,4,2,4,3,3,4,3,3,4,4,3,2,4,3,0,0.0,satisfied +2985,93864,Male,Loyal Customer,58,Business travel,Business,3084,1,1,1,1,3,4,5,3,3,4,3,4,3,5,16,12.0,satisfied +2986,45100,Male,Loyal Customer,43,Business travel,Business,3072,4,4,4,4,4,2,2,5,5,5,5,5,5,5,71,67.0,satisfied +2987,116981,Female,Loyal Customer,42,Business travel,Business,2283,2,2,2,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +2988,72497,Female,Loyal Customer,42,Business travel,Business,2709,2,5,4,5,1,3,3,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +2989,117841,Male,Loyal Customer,32,Personal Travel,Eco Plus,328,4,5,5,5,3,5,3,3,4,4,4,5,4,3,11,0.0,neutral or dissatisfied +2990,80343,Male,Loyal Customer,70,Personal Travel,Eco,952,1,5,1,2,5,1,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +2991,78711,Male,Loyal Customer,43,Business travel,Business,528,3,3,3,3,5,4,5,3,3,3,3,4,3,3,11,0.0,satisfied +2992,66461,Male,Loyal Customer,52,Personal Travel,Eco,1217,2,0,1,3,3,1,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +2993,28379,Male,disloyal Customer,14,Business travel,Eco,763,4,5,5,5,2,5,2,2,3,1,1,4,1,2,0,3.0,satisfied +2994,129306,Female,Loyal Customer,52,Personal Travel,Business,2586,0,1,0,2,1,2,2,1,1,0,1,2,1,3,0,0.0,satisfied +2995,30943,Female,disloyal Customer,20,Business travel,Eco,1024,3,3,3,4,5,3,5,5,1,5,3,1,4,5,12,34.0,neutral or dissatisfied +2996,4330,Female,Loyal Customer,51,Business travel,Business,265,2,2,2,2,1,4,1,5,5,5,5,2,5,3,0,8.0,satisfied +2997,5268,Male,Loyal Customer,50,Personal Travel,Eco,383,5,2,5,4,2,5,2,2,1,2,4,2,4,2,0,0.0,satisfied +2998,109208,Female,Loyal Customer,23,Business travel,Business,2440,3,1,5,1,3,3,3,3,2,1,2,2,2,3,15,9.0,neutral or dissatisfied +2999,102061,Male,Loyal Customer,22,Personal Travel,Business,258,3,3,0,4,3,0,3,3,3,1,5,2,4,3,18,19.0,neutral or dissatisfied +3000,25991,Male,Loyal Customer,45,Business travel,Business,577,2,4,4,4,3,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +3001,46107,Female,disloyal Customer,44,Business travel,Eco,1201,4,4,4,4,5,4,5,5,1,3,4,2,3,5,16,3.0,satisfied +3002,51907,Male,Loyal Customer,36,Business travel,Eco,201,4,5,5,5,4,4,4,4,2,5,1,1,4,4,0,0.0,satisfied +3003,57241,Female,Loyal Customer,60,Personal Travel,Business,628,3,5,3,4,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +3004,123896,Female,Loyal Customer,45,Personal Travel,Eco,541,4,5,4,1,2,2,5,1,1,4,1,5,1,1,31,24.0,neutral or dissatisfied +3005,118355,Male,Loyal Customer,13,Personal Travel,Eco,602,4,5,4,3,4,2,2,5,4,1,1,2,3,2,165,174.0,neutral or dissatisfied +3006,128823,Female,disloyal Customer,26,Business travel,Eco,2586,3,3,3,4,3,4,2,4,5,4,4,2,2,2,0,14.0,neutral or dissatisfied +3007,40181,Male,Loyal Customer,69,Business travel,Business,387,2,3,3,3,5,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +3008,77039,Female,Loyal Customer,8,Personal Travel,Eco Plus,368,3,4,3,2,1,3,1,1,4,4,3,5,3,1,0,0.0,neutral or dissatisfied +3009,53655,Male,Loyal Customer,53,Business travel,Business,3716,3,3,3,3,3,5,4,5,5,5,5,3,5,3,15,6.0,satisfied +3010,61362,Female,Loyal Customer,22,Business travel,Business,2405,2,1,1,1,2,2,2,3,2,3,4,2,1,2,0,8.0,neutral or dissatisfied +3011,33269,Male,Loyal Customer,41,Personal Travel,Eco Plus,101,3,3,3,3,1,3,1,1,1,3,4,1,1,1,3,4.0,neutral or dissatisfied +3012,81427,Female,Loyal Customer,48,Business travel,Eco,448,2,2,2,2,5,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +3013,105475,Female,Loyal Customer,42,Business travel,Business,3336,3,2,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +3014,24917,Male,disloyal Customer,27,Business travel,Eco,762,2,1,1,3,3,1,3,3,1,2,4,1,3,3,1,0.0,neutral or dissatisfied +3015,38328,Female,Loyal Customer,18,Business travel,Business,2094,4,4,4,4,5,5,5,5,1,5,5,4,1,5,0,0.0,satisfied +3016,101554,Male,Loyal Customer,18,Personal Travel,Eco,345,5,3,5,3,1,5,1,1,3,2,5,3,4,1,0,0.0,satisfied +3017,6825,Male,Loyal Customer,50,Personal Travel,Eco,122,1,5,1,2,3,1,1,3,1,2,3,4,5,3,59,60.0,neutral or dissatisfied +3018,70492,Female,Loyal Customer,80,Business travel,Business,3502,2,3,5,3,1,3,4,2,2,2,2,1,2,3,8,27.0,neutral or dissatisfied +3019,7039,Female,disloyal Customer,56,Business travel,Eco Plus,196,2,2,2,3,2,2,2,2,2,5,4,4,4,2,1,6.0,neutral or dissatisfied +3020,101371,Male,Loyal Customer,7,Personal Travel,Eco,1986,2,4,2,3,2,2,2,2,1,3,3,3,3,2,9,0.0,neutral or dissatisfied +3021,84332,Female,Loyal Customer,60,Business travel,Business,3380,4,4,4,4,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +3022,37744,Male,Loyal Customer,39,Personal Travel,Eco,972,4,5,4,3,3,4,3,3,3,5,5,3,5,3,29,14.0,neutral or dissatisfied +3023,61381,Male,disloyal Customer,22,Business travel,Eco,679,4,4,4,4,4,4,4,4,5,4,5,3,4,4,13,13.0,satisfied +3024,77926,Male,Loyal Customer,17,Personal Travel,Business,214,4,3,4,4,4,4,4,4,4,1,3,2,4,4,0,16.0,neutral or dissatisfied +3025,33509,Male,Loyal Customer,67,Personal Travel,Eco,965,4,4,4,3,3,4,3,3,4,4,4,3,4,3,3,0.0,satisfied +3026,93270,Male,disloyal Customer,23,Business travel,Business,867,5,3,5,3,5,5,5,5,5,2,5,3,4,5,22,8.0,satisfied +3027,121347,Female,Loyal Customer,46,Business travel,Business,3934,4,4,4,4,2,4,4,4,4,4,4,5,4,3,4,0.0,satisfied +3028,108684,Female,Loyal Customer,59,Business travel,Business,577,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +3029,124925,Female,disloyal Customer,27,Business travel,Eco,728,5,5,5,5,4,5,4,4,1,2,4,3,5,4,17,19.0,satisfied +3030,125236,Male,Loyal Customer,42,Business travel,Business,3869,2,2,5,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +3031,101314,Male,disloyal Customer,27,Business travel,Business,1076,3,3,3,3,1,3,5,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +3032,121287,Male,Loyal Customer,22,Business travel,Business,2282,4,4,4,4,5,5,5,5,3,3,5,4,5,5,3,0.0,satisfied +3033,79510,Male,Loyal Customer,55,Business travel,Business,3079,1,1,1,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +3034,15510,Male,Loyal Customer,59,Personal Travel,Eco,164,3,5,3,4,5,3,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +3035,129182,Female,Loyal Customer,44,Business travel,Business,2288,5,5,5,5,5,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +3036,1225,Female,Loyal Customer,65,Personal Travel,Eco,229,4,4,4,5,2,5,5,3,3,4,1,4,3,3,0,0.0,neutral or dissatisfied +3037,35147,Female,disloyal Customer,26,Business travel,Eco,1102,1,0,0,4,5,0,5,5,4,2,4,2,1,5,3,7.0,neutral or dissatisfied +3038,14724,Male,disloyal Customer,40,Business travel,Eco Plus,317,2,3,3,2,5,3,5,5,5,5,3,4,4,5,56,44.0,neutral or dissatisfied +3039,101380,Male,Loyal Customer,56,Business travel,Business,1647,4,4,5,4,5,5,4,4,4,4,4,3,4,3,9,6.0,satisfied +3040,112213,Male,Loyal Customer,30,Business travel,Business,3470,1,5,1,1,4,4,4,4,3,4,5,3,5,4,21,10.0,satisfied +3041,14196,Male,disloyal Customer,22,Business travel,Eco,620,2,0,3,2,1,3,1,1,2,3,1,3,5,1,0,0.0,neutral or dissatisfied +3042,110528,Male,disloyal Customer,25,Business travel,Business,551,5,3,4,1,2,4,2,2,5,5,5,5,5,2,0,0.0,satisfied +3043,114028,Male,Loyal Customer,47,Personal Travel,Eco Plus,1844,2,3,2,3,3,2,3,3,1,2,4,2,4,3,52,30.0,neutral or dissatisfied +3044,56221,Male,Loyal Customer,18,Business travel,Business,1608,3,4,4,4,3,3,3,3,1,5,2,4,4,3,0,0.0,neutral or dissatisfied +3045,58819,Female,Loyal Customer,41,Personal Travel,Eco,1005,3,5,3,2,4,3,4,4,5,4,5,4,5,4,9,0.0,neutral or dissatisfied +3046,54019,Female,Loyal Customer,42,Business travel,Business,3818,1,1,1,1,2,2,3,4,4,4,4,2,4,5,0,0.0,satisfied +3047,25065,Male,Loyal Customer,65,Personal Travel,Eco,594,3,3,3,4,5,3,5,5,4,4,3,1,4,5,32,29.0,neutral or dissatisfied +3048,29957,Male,disloyal Customer,59,Business travel,Business,213,1,1,1,5,5,1,5,5,1,2,2,5,4,5,0,0.0,neutral or dissatisfied +3049,90753,Male,Loyal Customer,24,Business travel,Business,2802,4,3,3,3,4,4,4,4,4,1,4,3,4,4,9,9.0,neutral or dissatisfied +3050,22557,Female,disloyal Customer,38,Business travel,Business,223,5,5,5,3,3,5,3,3,4,2,5,4,4,3,1,0.0,satisfied +3051,122081,Male,Loyal Customer,11,Personal Travel,Eco,130,1,1,1,4,3,1,3,3,1,2,4,4,3,3,14,9.0,neutral or dissatisfied +3052,71697,Male,Loyal Customer,65,Personal Travel,Eco,1197,3,2,3,4,3,3,3,4,1,4,3,3,1,3,113,132.0,neutral or dissatisfied +3053,78572,Female,disloyal Customer,21,Business travel,Eco,630,5,0,5,1,3,5,3,3,3,2,5,4,5,3,0,0.0,satisfied +3054,60201,Male,Loyal Customer,29,Business travel,Business,1546,4,4,4,4,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +3055,46022,Female,Loyal Customer,60,Business travel,Eco,991,4,3,3,3,4,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +3056,35220,Female,Loyal Customer,40,Business travel,Eco,1074,5,1,1,1,5,5,5,5,4,3,5,5,1,5,0,0.0,satisfied +3057,83770,Male,Loyal Customer,25,Personal Travel,Eco,926,3,4,3,1,3,4,4,5,3,5,5,4,3,4,299,313.0,neutral or dissatisfied +3058,2364,Female,disloyal Customer,32,Business travel,Eco,925,4,4,4,4,4,4,4,4,4,4,3,2,4,4,0,20.0,neutral or dissatisfied +3059,32574,Female,Loyal Customer,53,Business travel,Eco,101,3,4,4,4,5,3,4,3,3,3,3,2,3,1,0,0.0,satisfied +3060,45415,Female,Loyal Customer,29,Business travel,Business,3204,1,1,1,1,4,4,4,4,3,5,1,3,4,4,0,8.0,satisfied +3061,4502,Female,Loyal Customer,49,Business travel,Business,435,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +3062,83245,Female,Loyal Customer,55,Business travel,Eco,1979,3,2,2,2,2,3,3,3,3,3,3,4,3,2,7,15.0,neutral or dissatisfied +3063,32406,Female,disloyal Customer,22,Business travel,Eco,163,4,0,4,3,4,4,4,4,4,3,2,5,2,4,0,0.0,satisfied +3064,34410,Male,Loyal Customer,54,Personal Travel,Eco,728,2,4,2,3,5,2,5,5,3,2,4,2,3,5,5,0.0,neutral or dissatisfied +3065,70762,Male,Loyal Customer,57,Business travel,Business,1795,0,0,0,1,5,5,5,4,4,4,4,5,4,5,60,55.0,satisfied +3066,21748,Female,Loyal Customer,50,Personal Travel,Eco,563,2,5,2,2,3,5,4,2,2,2,2,3,2,5,3,0.0,neutral or dissatisfied +3067,63137,Male,Loyal Customer,44,Business travel,Business,3381,3,3,3,3,4,4,5,5,5,5,5,5,5,5,14,15.0,satisfied +3068,1629,Male,disloyal Customer,11,Business travel,Eco,999,2,2,2,4,1,2,1,1,2,1,4,2,3,1,7,21.0,neutral or dissatisfied +3069,127813,Female,Loyal Customer,38,Business travel,Business,1582,3,2,2,2,4,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +3070,10512,Female,disloyal Customer,20,Business travel,Eco,74,2,4,3,3,5,3,4,5,3,2,5,3,5,5,0,4.0,neutral or dissatisfied +3071,16504,Male,Loyal Customer,11,Personal Travel,Eco,246,2,4,2,4,2,2,2,2,3,5,4,4,5,2,46,30.0,neutral or dissatisfied +3072,71605,Male,Loyal Customer,30,Business travel,Business,1844,3,1,1,1,3,3,3,3,3,4,3,3,4,3,10,5.0,neutral or dissatisfied +3073,124227,Female,disloyal Customer,37,Business travel,Business,1423,5,5,5,4,2,5,2,2,4,3,5,5,5,2,0,0.0,satisfied +3074,127589,Male,disloyal Customer,23,Business travel,Business,1074,0,0,0,1,3,0,3,3,4,3,4,3,4,3,0,0.0,satisfied +3075,17566,Female,disloyal Customer,15,Business travel,Eco,1097,1,0,0,4,2,0,5,2,1,1,3,1,4,2,7,0.0,neutral or dissatisfied +3076,85206,Female,Loyal Customer,56,Business travel,Business,3097,2,3,4,4,3,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +3077,882,Male,Loyal Customer,49,Business travel,Business,3474,4,4,4,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +3078,4311,Female,disloyal Customer,26,Business travel,Eco,184,4,2,3,2,3,3,3,3,2,5,2,3,2,3,0,15.0,neutral or dissatisfied +3079,7416,Male,Loyal Customer,28,Business travel,Business,1906,5,5,5,5,2,2,2,2,5,4,5,5,5,2,10,37.0,satisfied +3080,2454,Female,Loyal Customer,26,Personal Travel,Business,674,4,3,4,2,2,4,2,2,5,1,4,1,1,2,6,4.0,neutral or dissatisfied +3081,69770,Male,Loyal Customer,31,Business travel,Business,2454,1,1,1,1,5,5,5,4,5,5,4,5,3,5,14,5.0,satisfied +3082,33692,Female,disloyal Customer,21,Business travel,Eco,805,1,1,1,5,5,1,5,5,1,5,3,1,3,5,9,4.0,neutral or dissatisfied +3083,76492,Female,disloyal Customer,37,Business travel,Business,481,4,4,4,2,3,4,3,3,4,3,5,3,5,3,0,3.0,satisfied +3084,103013,Male,disloyal Customer,24,Business travel,Eco,687,1,1,1,4,5,1,2,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +3085,90096,Male,Loyal Customer,66,Business travel,Business,3088,5,5,5,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +3086,98667,Female,Loyal Customer,49,Personal Travel,Eco,920,3,4,3,5,4,4,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +3087,78611,Female,disloyal Customer,22,Business travel,Eco,1272,2,2,2,3,4,2,2,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +3088,71238,Female,Loyal Customer,57,Business travel,Business,1656,2,1,1,1,2,3,3,2,2,2,2,1,2,1,11,29.0,neutral or dissatisfied +3089,129027,Female,Loyal Customer,22,Business travel,Business,2611,5,5,5,5,5,5,5,4,4,3,5,5,3,5,0,0.0,satisfied +3090,3697,Female,Loyal Customer,31,Business travel,Business,3802,4,1,4,1,4,4,4,4,1,5,4,3,3,4,0,8.0,neutral or dissatisfied +3091,67848,Male,Loyal Customer,8,Personal Travel,Eco,1464,4,4,4,4,2,4,2,2,3,3,5,4,5,2,0,3.0,neutral or dissatisfied +3092,27159,Female,Loyal Customer,42,Business travel,Business,2701,4,4,4,4,5,4,4,2,4,3,5,4,1,4,0,0.0,satisfied +3093,28630,Female,Loyal Customer,30,Business travel,Eco,2349,5,1,1,1,5,5,5,5,4,5,4,1,2,5,0,0.0,satisfied +3094,13366,Female,Loyal Customer,30,Personal Travel,Eco,946,2,4,2,4,2,2,2,2,2,2,4,1,3,2,8,0.0,neutral or dissatisfied +3095,81429,Male,Loyal Customer,19,Personal Travel,Eco,393,4,4,4,3,3,4,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +3096,13720,Male,Loyal Customer,46,Business travel,Eco,401,5,3,3,3,5,5,5,5,5,4,3,2,5,5,0,0.0,satisfied +3097,29830,Male,disloyal Customer,22,Business travel,Eco,399,2,0,2,3,5,2,5,5,1,1,4,3,3,5,2,4.0,neutral or dissatisfied +3098,65980,Male,Loyal Customer,25,Personal Travel,Eco,1372,2,1,2,3,2,2,2,2,2,5,2,4,3,2,22,6.0,neutral or dissatisfied +3099,120213,Female,Loyal Customer,35,Business travel,Business,1325,3,2,2,2,3,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +3100,114961,Female,Loyal Customer,33,Business travel,Business,3723,3,1,3,3,4,5,4,4,4,4,4,4,4,5,8,5.0,satisfied +3101,45134,Female,disloyal Customer,23,Business travel,Business,174,5,0,5,4,1,5,1,1,5,4,2,1,3,1,0,0.0,satisfied +3102,13462,Male,Loyal Customer,31,Personal Travel,Eco,409,3,3,3,4,3,3,3,3,1,1,3,1,3,3,0,0.0,neutral or dissatisfied +3103,69748,Male,Loyal Customer,58,Business travel,Business,2474,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +3104,18034,Female,Loyal Customer,17,Business travel,Eco,488,5,4,4,4,5,5,5,5,3,5,2,5,4,5,52,38.0,satisfied +3105,60752,Male,Loyal Customer,39,Business travel,Business,628,3,3,3,3,4,5,5,4,4,4,4,3,4,5,80,88.0,satisfied +3106,119675,Female,Loyal Customer,56,Business travel,Business,1325,5,5,1,5,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +3107,13630,Female,disloyal Customer,24,Business travel,Eco,1014,3,3,3,3,3,3,3,3,4,1,3,4,4,3,46,42.0,neutral or dissatisfied +3108,64505,Female,disloyal Customer,26,Business travel,Business,247,3,5,3,4,2,3,2,2,4,5,5,3,4,2,2,5.0,neutral or dissatisfied +3109,111270,Female,Loyal Customer,42,Business travel,Business,2305,3,3,3,3,2,2,2,3,3,3,3,3,3,2,11,0.0,neutral or dissatisfied +3110,290,Male,disloyal Customer,39,Business travel,Business,1250,1,1,1,2,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +3111,1995,Male,Loyal Customer,57,Personal Travel,Eco,383,3,4,3,1,5,3,3,5,3,4,4,4,4,5,1,0.0,neutral or dissatisfied +3112,9701,Female,Loyal Customer,41,Personal Travel,Eco,277,1,3,1,2,2,1,2,2,2,4,5,5,5,2,1,4.0,neutral or dissatisfied +3113,128307,Male,disloyal Customer,33,Business travel,Business,338,2,2,2,2,1,2,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +3114,88308,Male,disloyal Customer,22,Business travel,Eco,271,3,0,3,4,2,3,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +3115,107883,Female,disloyal Customer,55,Business travel,Business,228,3,3,3,5,3,3,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +3116,69724,Female,Loyal Customer,69,Personal Travel,Eco,1372,3,4,3,1,4,5,5,5,5,3,5,5,5,5,20,30.0,neutral or dissatisfied +3117,17813,Male,Loyal Customer,47,Business travel,Business,2738,2,2,4,2,2,3,1,2,2,2,2,5,2,1,0,0.0,satisfied +3118,10867,Male,disloyal Customer,39,Business travel,Business,74,1,1,1,4,5,1,1,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +3119,11444,Female,Loyal Customer,46,Business travel,Eco Plus,140,2,1,1,1,2,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +3120,115563,Male,disloyal Customer,37,Business travel,Eco,480,2,1,2,4,3,2,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +3121,72480,Male,Loyal Customer,59,Business travel,Business,918,3,2,2,2,5,2,3,3,3,3,3,2,3,4,34,29.0,neutral or dissatisfied +3122,57276,Female,Loyal Customer,38,Personal Travel,Eco,628,1,4,1,3,2,1,2,2,4,2,4,4,4,2,41,31.0,neutral or dissatisfied +3123,115696,Male,Loyal Customer,41,Business travel,Business,3232,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +3124,76328,Female,Loyal Customer,60,Personal Travel,Eco,2182,1,2,1,3,1,4,3,5,5,1,5,3,5,4,0,4.0,neutral or dissatisfied +3125,95610,Female,disloyal Customer,24,Business travel,Eco,822,4,4,4,4,5,4,4,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +3126,102649,Male,Loyal Customer,25,Business travel,Business,255,3,3,5,3,5,5,5,5,4,4,4,5,4,5,7,0.0,satisfied +3127,7215,Male,Loyal Customer,31,Business travel,Business,135,2,4,4,4,1,1,2,1,2,3,2,1,3,1,0,0.0,neutral or dissatisfied +3128,36552,Female,Loyal Customer,33,Business travel,Eco,1197,0,0,0,1,2,0,2,2,4,3,1,1,4,2,53,58.0,satisfied +3129,104471,Male,Loyal Customer,32,Business travel,Business,3840,2,2,2,2,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +3130,54177,Female,Loyal Customer,32,Business travel,Business,1400,4,1,1,1,4,4,4,3,3,1,2,4,1,4,292,331.0,neutral or dissatisfied +3131,89186,Female,Loyal Customer,31,Personal Travel,Eco,2139,1,5,1,3,5,1,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +3132,82907,Female,Loyal Customer,53,Personal Travel,Eco,594,3,4,3,1,1,1,2,1,1,3,1,4,1,1,32,20.0,neutral or dissatisfied +3133,19356,Male,disloyal Customer,26,Business travel,Eco,692,3,3,3,3,5,3,5,5,4,5,3,1,4,5,9,13.0,neutral or dissatisfied +3134,45589,Female,Loyal Customer,55,Business travel,Business,2002,2,2,2,2,4,4,2,5,5,5,5,3,5,3,78,82.0,satisfied +3135,18399,Male,disloyal Customer,22,Business travel,Eco,284,5,0,5,4,3,5,3,3,1,4,5,2,2,3,105,125.0,satisfied +3136,69175,Male,disloyal Customer,27,Business travel,Eco,187,2,4,2,3,5,2,5,5,3,5,3,2,4,5,0,3.0,neutral or dissatisfied +3137,82532,Female,Loyal Customer,17,Personal Travel,Business,440,3,4,3,3,2,3,1,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +3138,29006,Female,disloyal Customer,26,Business travel,Eco,205,1,0,2,4,4,2,4,4,2,1,1,3,5,4,0,0.0,neutral or dissatisfied +3139,91418,Female,Loyal Customer,39,Business travel,Business,2134,2,2,2,2,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +3140,65683,Male,Loyal Customer,63,Personal Travel,Eco,861,3,4,3,2,5,3,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +3141,47048,Male,Loyal Customer,26,Business travel,Business,1842,4,4,4,4,4,4,4,4,5,5,2,4,3,4,0,8.0,satisfied +3142,27030,Male,Loyal Customer,52,Business travel,Eco Plus,954,5,4,3,4,5,5,5,5,1,5,1,3,5,5,42,35.0,satisfied +3143,49307,Male,Loyal Customer,70,Business travel,Business,109,0,4,0,2,3,4,1,2,2,2,2,3,2,3,0,0.0,satisfied +3144,19698,Female,Loyal Customer,47,Business travel,Business,475,2,2,2,2,5,4,3,2,2,1,2,2,2,2,10,0.0,neutral or dissatisfied +3145,49505,Male,Loyal Customer,22,Business travel,Business,2536,5,5,5,5,5,5,5,5,5,5,5,2,4,5,0,0.0,satisfied +3146,69198,Male,Loyal Customer,60,Business travel,Business,2569,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +3147,118338,Male,Loyal Customer,43,Business travel,Eco,202,3,1,4,4,2,3,2,2,3,5,4,4,4,2,8,3.0,neutral or dissatisfied +3148,110506,Female,Loyal Customer,43,Business travel,Business,842,3,3,3,3,2,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +3149,72708,Female,Loyal Customer,43,Business travel,Business,1121,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +3150,77969,Female,Loyal Customer,35,Business travel,Business,2483,0,5,0,4,4,4,5,5,5,3,3,5,5,4,2,0.0,satisfied +3151,40550,Female,Loyal Customer,24,Business travel,Business,2961,2,2,4,2,4,4,4,4,5,3,4,5,1,4,0,7.0,satisfied +3152,24752,Female,Loyal Customer,46,Business travel,Eco,528,5,1,1,1,4,5,4,5,5,5,5,2,5,2,0,7.0,satisfied +3153,7158,Female,Loyal Customer,45,Business travel,Business,139,5,5,3,5,3,5,5,5,5,5,4,5,5,5,39,33.0,satisfied +3154,117463,Female,Loyal Customer,44,Personal Travel,Eco Plus,1107,2,5,2,2,3,4,1,1,1,2,1,2,1,4,42,39.0,neutral or dissatisfied +3155,110519,Female,Loyal Customer,49,Business travel,Business,3490,3,3,3,3,4,4,4,2,2,2,2,3,2,5,11,3.0,satisfied +3156,109859,Female,Loyal Customer,38,Business travel,Business,1165,2,1,1,1,1,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +3157,8409,Male,Loyal Customer,22,Business travel,Business,3485,2,2,2,2,4,4,4,4,5,4,4,4,5,4,48,39.0,satisfied +3158,97098,Female,disloyal Customer,28,Business travel,Business,1242,4,3,3,2,2,3,2,2,5,3,4,3,4,2,37,36.0,neutral or dissatisfied +3159,21759,Female,disloyal Customer,23,Business travel,Business,341,0,0,0,4,1,0,1,1,5,4,4,5,4,1,29,14.0,satisfied +3160,60378,Female,Loyal Customer,37,Business travel,Business,1452,4,4,4,4,4,5,5,5,5,5,5,5,5,3,37,30.0,satisfied +3161,119581,Male,Loyal Customer,34,Business travel,Business,2276,2,2,2,2,4,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +3162,17464,Female,Loyal Customer,55,Business travel,Business,3234,5,5,3,5,2,5,5,5,5,5,5,3,5,3,3,0.0,satisfied +3163,23954,Male,Loyal Customer,21,Business travel,Business,3294,1,1,1,1,5,5,5,5,2,2,1,4,5,5,0,0.0,satisfied +3164,39497,Female,Loyal Customer,15,Personal Travel,Eco,1368,3,4,3,3,5,3,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +3165,115878,Male,disloyal Customer,39,Business travel,Eco,325,4,4,4,2,3,4,3,3,3,2,1,5,5,3,6,0.0,neutral or dissatisfied +3166,96733,Male,Loyal Customer,63,Personal Travel,Eco,696,1,5,1,3,4,1,4,4,5,3,4,5,5,4,19,24.0,neutral or dissatisfied +3167,62105,Female,disloyal Customer,27,Business travel,Business,2425,5,5,5,2,4,5,4,4,4,4,3,5,4,4,5,0.0,satisfied +3168,61516,Male,Loyal Customer,62,Personal Travel,Eco,2253,2,5,2,2,1,2,2,1,3,5,5,3,2,1,4,4.0,neutral or dissatisfied +3169,70931,Male,Loyal Customer,29,Business travel,Business,612,4,4,4,4,5,5,5,5,3,3,4,5,5,5,17,19.0,satisfied +3170,1640,Female,Loyal Customer,17,Personal Travel,Eco Plus,999,1,5,1,5,2,1,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +3171,45558,Male,Loyal Customer,52,Business travel,Business,1545,4,4,4,4,2,5,3,5,5,5,5,1,5,5,7,24.0,satisfied +3172,98683,Male,Loyal Customer,11,Personal Travel,Eco,966,3,5,3,3,1,3,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +3173,47454,Female,Loyal Customer,18,Personal Travel,Eco,599,2,0,2,1,5,2,5,5,5,4,3,3,3,5,0,0.0,neutral or dissatisfied +3174,103465,Female,Loyal Customer,17,Personal Travel,Eco,393,1,5,1,4,5,1,5,5,3,3,5,5,5,5,5,2.0,neutral or dissatisfied +3175,112388,Female,Loyal Customer,48,Business travel,Business,3150,3,4,3,3,4,4,4,3,3,3,3,5,3,4,21,14.0,satisfied +3176,114983,Male,disloyal Customer,38,Business travel,Business,373,5,5,5,5,2,5,2,2,5,2,5,3,4,2,0,0.0,satisfied +3177,116522,Female,Loyal Customer,58,Personal Travel,Eco,358,4,3,4,3,4,4,4,4,4,4,4,3,4,4,6,0.0,neutral or dissatisfied +3178,117896,Male,Loyal Customer,41,Business travel,Business,365,5,5,5,5,4,5,5,5,5,5,5,3,5,4,19,13.0,satisfied +3179,3069,Female,disloyal Customer,25,Business travel,Business,413,3,4,3,1,1,3,1,1,4,2,5,3,4,1,0,12.0,neutral or dissatisfied +3180,110244,Male,Loyal Customer,38,Business travel,Business,3427,3,1,1,1,2,3,3,3,3,3,3,4,3,1,27,9.0,neutral or dissatisfied +3181,72003,Male,Loyal Customer,51,Business travel,Business,1440,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +3182,88943,Female,Loyal Customer,25,Business travel,Business,2333,3,3,3,3,4,4,4,4,5,5,4,3,5,4,0,6.0,satisfied +3183,38910,Female,Loyal Customer,39,Business travel,Business,1615,5,5,5,5,2,3,2,2,2,2,2,5,2,1,9,14.0,satisfied +3184,66278,Female,Loyal Customer,22,Business travel,Eco Plus,460,2,1,4,1,2,2,4,2,1,3,4,3,4,2,0,15.0,neutral or dissatisfied +3185,44373,Female,Loyal Customer,31,Business travel,Eco Plus,596,5,5,5,5,5,5,5,5,3,2,4,4,2,5,0,0.0,satisfied +3186,27324,Male,Loyal Customer,24,Business travel,Business,3782,5,5,5,5,3,5,3,3,5,2,3,1,2,3,0,0.0,satisfied +3187,94245,Male,Loyal Customer,42,Business travel,Business,3369,4,4,5,4,2,4,4,4,4,4,4,5,4,3,2,2.0,satisfied +3188,103596,Female,disloyal Customer,26,Business travel,Business,451,4,3,3,3,2,3,2,2,4,4,4,5,5,2,0,0.0,satisfied +3189,25732,Female,Loyal Customer,34,Personal Travel,Eco,528,2,3,2,3,2,2,2,2,3,3,4,2,4,2,17,0.0,neutral or dissatisfied +3190,71236,Female,disloyal Customer,26,Business travel,Eco,733,1,1,1,4,1,1,1,1,4,4,3,4,3,1,5,0.0,neutral or dissatisfied +3191,27618,Male,Loyal Customer,28,Business travel,Eco Plus,679,4,1,1,1,4,4,4,4,4,5,2,4,2,4,62,54.0,satisfied +3192,32374,Female,Loyal Customer,37,Business travel,Business,3155,5,5,5,5,4,1,4,5,5,4,3,2,5,4,4,10.0,satisfied +3193,58015,Male,Loyal Customer,39,Business travel,Business,1721,4,4,4,4,2,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +3194,14551,Male,Loyal Customer,10,Personal Travel,Eco,362,3,5,3,1,1,3,1,1,3,3,4,4,4,1,25,55.0,neutral or dissatisfied +3195,27026,Male,Loyal Customer,70,Personal Travel,Eco,867,3,4,3,3,5,3,5,5,5,3,3,4,4,5,0,0.0,neutral or dissatisfied +3196,101258,Female,Loyal Customer,40,Business travel,Business,2176,1,1,2,1,4,3,5,4,4,4,4,3,4,3,43,31.0,satisfied +3197,72457,Male,disloyal Customer,23,Business travel,Eco,964,2,2,2,3,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +3198,115678,Female,Loyal Customer,74,Business travel,Business,3231,1,1,1,1,1,4,3,1,1,1,1,3,1,4,25,5.0,neutral or dissatisfied +3199,116176,Female,Loyal Customer,52,Personal Travel,Eco,337,1,3,1,1,2,2,3,1,1,1,1,2,1,5,18,6.0,neutral or dissatisfied +3200,50871,Male,Loyal Customer,66,Personal Travel,Eco,77,3,4,0,2,2,0,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +3201,8503,Female,Loyal Customer,38,Business travel,Business,862,2,2,2,2,2,5,4,2,2,2,2,3,2,3,25,27.0,satisfied +3202,29591,Female,disloyal Customer,40,Business travel,Business,1448,2,3,3,4,1,3,1,1,5,5,3,1,5,1,0,0.0,neutral or dissatisfied +3203,50999,Male,Loyal Customer,52,Personal Travel,Eco,78,1,4,1,5,3,1,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +3204,104303,Female,Loyal Customer,42,Business travel,Business,2993,1,1,1,1,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +3205,43511,Female,Loyal Customer,47,Personal Travel,Eco,594,2,5,2,4,1,1,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +3206,1018,Female,Loyal Customer,57,Business travel,Business,2031,5,5,3,5,4,5,2,5,5,5,3,5,5,3,0,0.0,satisfied +3207,104273,Female,disloyal Customer,31,Business travel,Business,1749,4,4,4,1,1,4,1,1,3,4,3,5,5,1,10,0.0,neutral or dissatisfied +3208,110588,Female,Loyal Customer,29,Personal Travel,Eco,643,3,5,3,2,3,3,3,3,5,4,4,3,4,3,21,32.0,neutral or dissatisfied +3209,94135,Male,disloyal Customer,21,Business travel,Business,248,5,0,5,4,4,0,4,4,3,4,5,4,5,4,20,22.0,satisfied +3210,89566,Male,Loyal Customer,27,Business travel,Business,2267,1,1,5,1,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +3211,50226,Female,disloyal Customer,29,Business travel,Eco,190,1,2,1,4,4,1,4,4,3,5,3,2,3,4,0,12.0,neutral or dissatisfied +3212,23440,Male,Loyal Customer,28,Business travel,Business,488,5,4,5,5,5,5,5,5,2,3,5,4,5,5,72,76.0,satisfied +3213,81227,Female,Loyal Customer,36,Business travel,Eco Plus,1026,4,5,5,5,4,4,4,4,3,2,5,2,3,4,3,0.0,satisfied +3214,34617,Male,Loyal Customer,43,Business travel,Eco Plus,998,4,4,4,4,4,3,3,3,1,4,3,3,4,3,258,288.0,satisfied +3215,50297,Male,Loyal Customer,58,Business travel,Business,1770,2,2,2,2,3,4,1,4,4,4,5,2,4,2,0,0.0,satisfied +3216,93943,Male,Loyal Customer,32,Personal Travel,Eco,507,5,4,5,3,2,5,2,2,5,3,4,3,5,2,1,3.0,satisfied +3217,45385,Female,Loyal Customer,20,Personal Travel,Eco Plus,150,2,4,2,4,2,2,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +3218,109023,Female,Loyal Customer,13,Business travel,Eco,816,4,1,5,1,4,4,2,4,3,5,3,2,4,4,8,12.0,neutral or dissatisfied +3219,96262,Male,Loyal Customer,50,Personal Travel,Eco,460,3,4,3,2,2,3,2,2,5,3,5,3,5,2,5,0.0,neutral or dissatisfied +3220,29912,Male,Loyal Customer,46,Business travel,Business,160,0,3,0,4,2,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +3221,40104,Female,disloyal Customer,27,Business travel,Eco,422,2,0,2,4,3,2,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +3222,69048,Female,Loyal Customer,61,Business travel,Business,1521,2,4,2,4,4,3,4,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +3223,11600,Female,Loyal Customer,52,Business travel,Eco,257,2,3,3,3,1,2,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +3224,30121,Female,Loyal Customer,7,Personal Travel,Eco,82,3,4,0,4,2,0,2,2,1,3,1,5,5,2,104,105.0,neutral or dissatisfied +3225,91927,Female,Loyal Customer,59,Business travel,Business,2475,4,4,2,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +3226,5620,Female,Loyal Customer,18,Personal Travel,Eco,624,1,2,1,3,5,1,3,5,2,1,3,3,2,5,10,5.0,neutral or dissatisfied +3227,8468,Male,Loyal Customer,47,Business travel,Business,1187,4,4,4,4,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +3228,58614,Male,disloyal Customer,39,Business travel,Business,235,5,5,5,3,5,5,5,5,4,4,4,3,5,5,121,118.0,satisfied +3229,123846,Male,Loyal Customer,38,Business travel,Business,603,4,1,1,1,4,3,3,4,4,4,4,3,4,3,40,25.0,neutral or dissatisfied +3230,118109,Male,Loyal Customer,22,Personal Travel,Eco,1999,5,4,5,3,3,5,3,3,4,3,5,5,4,3,6,5.0,satisfied +3231,20047,Female,disloyal Customer,24,Business travel,Eco,473,2,3,2,3,5,2,5,5,5,4,1,5,5,5,0,0.0,neutral or dissatisfied +3232,127517,Male,Loyal Customer,27,Personal Travel,Eco Plus,2075,3,5,3,2,1,3,1,1,2,4,3,5,4,1,18,51.0,neutral or dissatisfied +3233,10334,Male,disloyal Customer,24,Business travel,Eco,224,2,0,2,2,3,2,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +3234,9055,Female,Loyal Customer,24,Business travel,Business,212,0,5,0,3,2,2,2,2,3,3,5,3,5,2,1,0.0,satisfied +3235,98990,Male,Loyal Customer,23,Personal Travel,Eco,569,2,4,2,4,5,2,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +3236,44738,Female,Loyal Customer,35,Business travel,Eco Plus,67,5,2,2,2,5,5,5,5,1,3,5,2,2,5,8,5.0,satisfied +3237,93031,Female,disloyal Customer,42,Business travel,Business,317,2,2,2,3,4,2,4,4,4,5,4,5,4,4,3,32.0,neutral or dissatisfied +3238,69556,Male,Loyal Customer,51,Business travel,Business,2475,4,4,4,4,5,5,5,3,3,5,5,5,3,5,8,34.0,satisfied +3239,107361,Female,Loyal Customer,36,Personal Travel,Eco,632,5,3,4,5,2,4,2,2,3,2,1,1,4,2,2,0.0,satisfied +3240,81325,Female,Loyal Customer,46,Business travel,Business,1299,1,1,1,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +3241,44612,Male,Loyal Customer,50,Business travel,Eco,566,3,2,2,2,3,3,3,3,1,5,3,1,3,3,2,0.0,neutral or dissatisfied +3242,25893,Female,Loyal Customer,49,Business travel,Business,507,2,1,1,1,4,3,3,2,2,2,2,1,2,3,28,42.0,neutral or dissatisfied +3243,25092,Male,Loyal Customer,55,Business travel,Eco,369,5,4,4,4,5,5,5,5,3,5,2,3,5,5,0,13.0,satisfied +3244,106444,Male,Loyal Customer,56,Personal Travel,Eco,1062,2,3,2,3,4,2,4,4,3,3,3,1,4,4,27,39.0,neutral or dissatisfied +3245,121252,Female,disloyal Customer,35,Business travel,Eco,755,1,1,1,4,2,1,2,2,1,2,2,3,4,2,0,0.0,neutral or dissatisfied +3246,66425,Male,Loyal Customer,50,Personal Travel,Eco,1562,2,4,2,3,2,2,2,2,3,5,4,3,5,2,4,0.0,neutral or dissatisfied +3247,113999,Female,disloyal Customer,33,Business travel,Eco,999,3,3,3,4,1,3,1,1,1,4,3,1,4,1,33,19.0,neutral or dissatisfied +3248,47297,Male,Loyal Customer,47,Business travel,Eco,584,5,1,3,1,5,5,5,5,4,2,3,4,1,5,0,0.0,satisfied +3249,95914,Female,Loyal Customer,56,Business travel,Business,1504,1,1,5,1,5,3,2,1,1,1,1,3,1,2,58,69.0,neutral or dissatisfied +3250,10937,Female,Loyal Customer,57,Business travel,Business,2191,5,5,5,5,5,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +3251,127886,Female,Loyal Customer,38,Business travel,Eco Plus,1276,3,5,5,5,3,3,3,3,3,4,3,1,3,3,0,36.0,neutral or dissatisfied +3252,52711,Male,Loyal Customer,38,Business travel,Business,2860,1,1,1,1,1,2,3,5,5,5,5,2,5,2,9,0.0,satisfied +3253,49638,Female,Loyal Customer,38,Business travel,Business,156,5,5,5,5,4,5,1,4,4,4,5,4,4,1,0,0.0,satisfied +3254,41952,Female,Loyal Customer,52,Business travel,Eco,575,5,4,4,4,1,1,1,5,5,5,5,2,5,1,0,0.0,satisfied +3255,21882,Male,disloyal Customer,23,Business travel,Eco,448,5,0,5,4,2,5,2,2,5,5,5,4,3,2,18,8.0,satisfied +3256,125054,Female,Loyal Customer,61,Personal Travel,Eco Plus,2300,3,4,3,3,3,1,1,2,2,5,1,1,3,1,17,66.0,neutral or dissatisfied +3257,109018,Female,disloyal Customer,22,Business travel,Eco,928,3,2,2,4,2,2,2,2,2,2,3,4,4,2,14,15.0,neutral or dissatisfied +3258,39442,Male,Loyal Customer,66,Business travel,Business,2342,3,3,3,3,1,3,3,3,3,3,3,1,3,2,0,6.0,neutral or dissatisfied +3259,87712,Male,Loyal Customer,59,Personal Travel,Eco,606,3,4,3,1,1,3,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +3260,129331,Female,disloyal Customer,16,Business travel,Eco,964,2,3,3,2,4,3,3,4,3,5,3,3,4,4,16,4.0,neutral or dissatisfied +3261,102588,Male,Loyal Customer,65,Business travel,Eco Plus,397,2,1,1,1,2,2,2,2,2,1,3,1,3,2,14,8.0,neutral or dissatisfied +3262,100659,Male,Loyal Customer,52,Business travel,Business,2361,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +3263,91188,Female,Loyal Customer,29,Personal Travel,Eco,545,3,5,3,3,5,3,5,5,2,2,5,5,2,5,0,0.0,neutral or dissatisfied +3264,102686,Female,Loyal Customer,54,Business travel,Eco,365,4,2,2,2,4,3,4,4,4,4,4,1,4,2,24,15.0,neutral or dissatisfied +3265,56728,Female,Loyal Customer,69,Personal Travel,Eco,937,3,4,3,3,5,5,4,2,2,3,5,4,2,5,15,3.0,neutral or dissatisfied +3266,41655,Female,Loyal Customer,36,Business travel,Business,1780,5,4,5,5,4,2,4,5,5,5,5,1,5,5,0,0.0,satisfied +3267,86725,Female,Loyal Customer,39,Personal Travel,Eco,1747,1,0,1,4,2,1,2,2,3,4,5,5,4,2,26,19.0,neutral or dissatisfied +3268,74213,Female,Loyal Customer,22,Personal Travel,Eco Plus,592,2,4,3,4,3,3,3,3,3,5,1,2,3,3,0,0.0,neutral or dissatisfied +3269,114731,Male,Loyal Customer,43,Business travel,Business,337,2,2,2,2,4,4,4,4,4,4,4,3,4,3,25,33.0,satisfied +3270,67304,Male,Loyal Customer,22,Business travel,Eco Plus,929,3,5,5,5,3,3,3,3,4,3,4,3,3,3,43,42.0,neutral or dissatisfied +3271,44220,Female,disloyal Customer,23,Business travel,Eco,222,5,0,5,1,3,5,3,3,3,3,5,5,5,3,0,7.0,satisfied +3272,1363,Male,Loyal Customer,42,Business travel,Business,354,3,3,3,3,2,3,2,3,3,3,3,3,3,1,0,2.0,neutral or dissatisfied +3273,110050,Male,Loyal Customer,13,Personal Travel,Eco,1984,4,2,4,4,1,4,3,1,2,5,4,4,4,1,0,0.0,satisfied +3274,92092,Female,disloyal Customer,38,Business travel,Business,1576,2,2,2,3,2,2,2,2,5,2,4,4,4,2,2,0.0,neutral or dissatisfied +3275,40542,Male,Loyal Customer,46,Business travel,Business,2045,3,3,3,3,5,4,5,4,4,4,4,2,4,5,0,0.0,satisfied +3276,128079,Female,Loyal Customer,58,Business travel,Business,2860,2,2,5,2,5,5,5,5,2,4,4,5,5,5,15,21.0,satisfied +3277,67909,Female,Loyal Customer,19,Personal Travel,Eco,1171,1,4,1,3,1,1,1,1,5,5,4,5,5,1,15,22.0,neutral or dissatisfied +3278,44550,Male,Loyal Customer,13,Personal Travel,Eco,157,2,5,0,5,1,0,1,1,3,3,1,5,2,1,0,0.0,neutral or dissatisfied +3279,6572,Male,Loyal Customer,53,Business travel,Business,607,2,2,2,2,2,4,4,5,5,5,5,5,5,4,22,9.0,satisfied +3280,93566,Male,Loyal Customer,54,Personal Travel,Business,159,1,5,1,4,3,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +3281,62750,Male,Loyal Customer,42,Business travel,Business,2486,5,5,3,5,4,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +3282,11644,Female,Loyal Customer,55,Business travel,Business,3750,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +3283,70888,Female,Loyal Customer,69,Personal Travel,Business,1721,3,1,3,3,2,2,3,3,3,3,3,2,3,2,12,38.0,neutral or dissatisfied +3284,53251,Female,Loyal Customer,56,Personal Travel,Eco Plus,612,1,3,1,1,2,2,5,5,5,1,5,4,5,5,2,0.0,neutral or dissatisfied +3285,66606,Female,Loyal Customer,56,Personal Travel,Eco,761,1,2,1,3,4,4,4,1,1,1,1,4,1,3,71,58.0,neutral or dissatisfied +3286,124861,Male,Loyal Customer,58,Business travel,Business,3282,4,4,4,4,3,4,4,5,5,5,5,3,5,5,28,24.0,satisfied +3287,4555,Female,Loyal Customer,42,Business travel,Business,3680,2,2,2,2,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +3288,113674,Female,Loyal Customer,15,Personal Travel,Eco,407,3,3,3,3,3,3,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +3289,85803,Female,Loyal Customer,33,Business travel,Business,3705,1,1,1,1,4,3,4,1,1,1,1,3,1,4,0,14.0,neutral or dissatisfied +3290,8631,Female,Loyal Customer,7,Personal Travel,Business,181,1,1,1,3,3,1,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +3291,93186,Female,Loyal Customer,59,Business travel,Business,2387,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +3292,35920,Female,Loyal Customer,65,Business travel,Eco Plus,2248,3,1,1,1,4,2,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +3293,88404,Male,Loyal Customer,41,Business travel,Business,2208,2,2,4,2,2,4,3,2,2,1,2,3,2,1,16,11.0,neutral or dissatisfied +3294,125214,Female,Loyal Customer,55,Personal Travel,Eco,651,1,4,1,3,3,3,4,1,1,1,1,1,1,3,10,14.0,neutral or dissatisfied +3295,19123,Male,Loyal Customer,58,Business travel,Eco,287,4,5,5,5,4,4,4,4,1,5,4,3,1,4,0,1.0,satisfied +3296,30223,Female,Loyal Customer,44,Personal Travel,Eco,1109,3,4,3,4,4,5,5,1,1,3,1,5,1,3,0,31.0,neutral or dissatisfied +3297,60734,Male,Loyal Customer,7,Personal Travel,Eco,1605,3,4,3,3,3,3,4,3,4,4,5,5,5,3,15,0.0,neutral or dissatisfied +3298,85742,Female,Loyal Customer,45,Business travel,Business,1999,2,2,2,2,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +3299,3861,Female,Loyal Customer,47,Business travel,Business,213,2,1,1,1,5,2,2,3,3,3,2,1,3,2,74,63.0,neutral or dissatisfied +3300,107039,Female,Loyal Customer,45,Business travel,Business,395,1,1,1,1,2,4,5,4,4,5,4,3,4,3,56,49.0,satisfied +3301,72562,Female,Loyal Customer,58,Business travel,Business,1972,1,5,5,5,4,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +3302,101950,Female,disloyal Customer,25,Business travel,Business,628,2,0,2,1,2,2,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +3303,41833,Male,Loyal Customer,59,Business travel,Business,462,1,1,1,1,3,1,2,1,1,2,1,1,1,1,0,1.0,satisfied +3304,109738,Female,Loyal Customer,47,Personal Travel,Eco,468,2,4,2,2,4,4,4,4,4,2,4,3,4,5,45,51.0,neutral or dissatisfied +3305,45611,Male,Loyal Customer,31,Business travel,Business,1852,5,3,5,5,5,5,5,5,5,5,5,1,5,5,15,37.0,satisfied +3306,107729,Male,Loyal Customer,17,Personal Travel,Eco,405,0,4,0,4,4,0,4,4,4,3,3,1,3,4,14,14.0,satisfied +3307,109878,Female,disloyal Customer,28,Business travel,Eco,971,3,3,3,3,2,3,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +3308,102793,Female,Loyal Customer,27,Personal Travel,Eco,1099,3,4,3,1,5,3,5,5,1,2,5,1,2,5,1,1.0,neutral or dissatisfied +3309,57788,Male,Loyal Customer,36,Personal Travel,Eco,2704,3,1,2,2,2,2,4,1,5,2,2,4,1,4,8,39.0,neutral or dissatisfied +3310,44926,Female,Loyal Customer,32,Business travel,Eco,438,2,4,4,4,2,2,2,2,1,1,2,1,2,2,1,11.0,neutral or dissatisfied +3311,112791,Female,Loyal Customer,50,Business travel,Business,1390,1,1,1,1,4,5,4,4,4,4,4,3,4,5,21,0.0,satisfied +3312,8761,Male,Loyal Customer,45,Personal Travel,Eco,1147,1,5,1,3,2,1,2,2,4,3,4,4,4,2,19,0.0,neutral or dissatisfied +3313,23365,Female,Loyal Customer,42,Business travel,Eco,1014,5,4,4,4,2,1,3,5,5,5,5,3,5,3,117,100.0,satisfied +3314,83817,Female,disloyal Customer,27,Business travel,Eco,425,3,1,3,3,4,3,4,4,4,3,2,3,3,4,2,0.0,neutral or dissatisfied +3315,28198,Male,Loyal Customer,25,Personal Travel,Eco,834,3,1,3,3,2,3,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +3316,16644,Female,disloyal Customer,25,Business travel,Eco,488,3,4,3,3,1,3,1,1,2,1,3,4,4,1,10,0.0,neutral or dissatisfied +3317,18698,Male,Loyal Customer,62,Business travel,Eco Plus,383,4,2,2,2,4,4,4,4,1,4,3,3,4,4,7,14.0,satisfied +3318,71180,Male,Loyal Customer,33,Personal Travel,Business,733,2,2,2,4,4,2,4,4,1,3,4,1,3,4,57,38.0,neutral or dissatisfied +3319,48004,Male,disloyal Customer,13,Business travel,Eco,550,2,2,2,4,1,2,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +3320,29409,Female,Loyal Customer,65,Personal Travel,Eco,2614,4,2,4,3,4,2,2,3,2,3,3,2,1,2,0,0.0,satisfied +3321,99798,Male,disloyal Customer,30,Business travel,Eco,584,2,2,2,4,2,2,2,1,1,3,4,2,2,2,135,134.0,neutral or dissatisfied +3322,83573,Male,Loyal Customer,38,Business travel,Business,3653,4,4,4,4,4,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +3323,37578,Male,disloyal Customer,30,Business travel,Business,1069,3,3,3,2,4,3,4,4,2,5,3,5,5,4,0,0.0,neutral or dissatisfied +3324,56171,Male,Loyal Customer,56,Business travel,Business,1000,3,3,3,3,4,4,1,4,4,5,4,1,4,2,10,0.0,satisfied +3325,99197,Female,disloyal Customer,22,Business travel,Business,1180,5,5,5,2,2,5,2,2,3,5,5,4,5,2,0,0.0,satisfied +3326,101420,Female,disloyal Customer,26,Business travel,Business,345,5,0,5,3,1,5,1,1,3,3,4,4,5,1,14,12.0,satisfied +3327,17457,Male,Loyal Customer,28,Personal Travel,Eco Plus,351,3,3,3,2,5,3,5,5,1,1,3,2,2,5,0,0.0,neutral or dissatisfied +3328,4053,Male,Loyal Customer,9,Personal Travel,Eco,483,2,5,2,2,4,2,4,4,1,2,4,1,2,4,0,13.0,neutral or dissatisfied +3329,108271,Female,Loyal Customer,7,Personal Travel,Eco,895,3,4,3,3,3,3,3,3,1,1,4,2,3,3,1,0.0,neutral or dissatisfied +3330,128944,Male,disloyal Customer,23,Business travel,Eco,414,3,4,3,3,2,3,2,2,3,5,4,4,5,2,1,0.0,neutral or dissatisfied +3331,48736,Female,Loyal Customer,50,Business travel,Business,1571,4,3,3,3,4,2,2,4,4,4,4,1,4,4,56,47.0,neutral or dissatisfied +3332,79235,Male,Loyal Customer,64,Personal Travel,Eco,1521,3,4,3,3,5,3,5,5,1,1,2,5,5,5,46,67.0,neutral or dissatisfied +3333,57007,Female,Loyal Customer,48,Personal Travel,Eco,2565,2,3,2,5,2,3,2,5,5,4,3,2,1,2,0,0.0,neutral or dissatisfied +3334,6814,Male,Loyal Customer,26,Personal Travel,Eco,122,4,4,4,3,5,4,5,5,3,1,4,3,3,5,1,0.0,satisfied +3335,13128,Female,disloyal Customer,40,Business travel,Business,427,4,4,4,4,2,4,3,2,4,2,4,1,4,2,1,0.0,neutral or dissatisfied +3336,54447,Male,disloyal Customer,26,Business travel,Business,844,0,0,0,3,2,0,2,2,3,4,5,5,5,2,0,0.0,satisfied +3337,49429,Male,Loyal Customer,38,Business travel,Business,3193,3,3,3,3,5,3,3,5,5,5,4,1,5,5,10,3.0,satisfied +3338,90644,Female,Loyal Customer,44,Business travel,Business,366,1,1,1,1,3,5,4,4,4,4,4,3,4,4,8,43.0,satisfied +3339,118816,Female,disloyal Customer,36,Business travel,Business,369,1,1,1,1,4,1,4,4,4,4,5,5,4,4,42,40.0,neutral or dissatisfied +3340,5870,Male,Loyal Customer,55,Personal Travel,Business,173,1,5,1,1,2,5,1,2,2,1,2,2,2,5,25,22.0,neutral or dissatisfied +3341,19011,Male,disloyal Customer,49,Business travel,Eco,788,2,2,2,3,2,2,2,1,3,3,4,2,3,2,222,225.0,neutral or dissatisfied +3342,55059,Male,disloyal Customer,10,Business travel,Eco,908,5,5,5,4,4,5,3,4,3,2,5,4,4,4,20,0.0,satisfied +3343,30086,Female,Loyal Customer,38,Personal Travel,Eco,261,5,5,5,1,5,5,5,5,4,3,1,4,3,5,0,0.0,satisfied +3344,117665,Male,Loyal Customer,51,Business travel,Business,1449,4,4,4,4,4,5,5,5,5,5,5,3,5,4,4,0.0,satisfied +3345,12065,Female,Loyal Customer,18,Personal Travel,Eco,376,3,4,3,4,1,3,3,1,4,5,5,4,4,1,46,41.0,neutral or dissatisfied +3346,61168,Male,Loyal Customer,35,Business travel,Business,3126,3,3,5,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +3347,63298,Male,Loyal Customer,33,Business travel,Business,1697,3,4,4,4,3,2,3,3,1,5,4,1,3,3,0,13.0,neutral or dissatisfied +3348,16808,Female,Loyal Customer,40,Business travel,Eco,645,2,3,3,3,2,2,2,2,2,5,2,1,3,2,73,64.0,satisfied +3349,119156,Male,Loyal Customer,23,Business travel,Business,2513,0,0,0,3,2,2,2,2,4,2,5,3,4,2,0,0.0,satisfied +3350,119771,Male,Loyal Customer,41,Business travel,Business,936,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +3351,13313,Male,disloyal Customer,47,Business travel,Eco,448,3,2,3,4,2,3,2,2,1,5,3,3,4,2,52,46.0,neutral or dissatisfied +3352,93987,Female,Loyal Customer,8,Personal Travel,Eco,1315,1,5,1,4,1,1,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +3353,125129,Male,Loyal Customer,55,Personal Travel,Eco,361,2,4,2,5,3,2,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +3354,94325,Female,Loyal Customer,42,Business travel,Business,562,5,5,5,5,2,4,5,3,3,4,3,3,3,4,94,86.0,satisfied +3355,102688,Female,disloyal Customer,38,Business travel,Eco,365,1,4,1,4,2,1,2,2,3,1,4,3,3,2,1,0.0,neutral or dissatisfied +3356,31203,Female,Loyal Customer,29,Business travel,Business,628,2,3,3,3,2,2,2,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +3357,17223,Female,Loyal Customer,12,Business travel,Business,3468,2,2,1,2,2,2,2,2,3,3,1,5,1,2,0,11.0,satisfied +3358,45926,Male,disloyal Customer,59,Business travel,Eco,409,4,2,4,4,3,4,3,3,3,4,5,3,5,3,0,5.0,satisfied +3359,123273,Female,Loyal Customer,51,Personal Travel,Eco,468,2,4,2,3,5,3,4,2,2,2,2,1,2,2,1,30.0,neutral or dissatisfied +3360,109373,Female,Loyal Customer,39,Business travel,Business,2440,1,1,1,1,3,5,4,4,4,4,4,5,4,5,20,10.0,satisfied +3361,118482,Male,Loyal Customer,35,Business travel,Business,370,2,2,2,2,3,5,5,3,3,3,3,3,3,3,10,4.0,satisfied +3362,21715,Male,Loyal Customer,54,Business travel,Eco,952,4,3,3,3,5,4,5,5,2,4,3,4,4,5,0,0.0,satisfied +3363,121889,Female,Loyal Customer,66,Personal Travel,Eco,366,3,3,3,4,1,4,4,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +3364,46490,Female,Loyal Customer,53,Business travel,Eco,73,4,3,3,3,1,5,4,4,4,4,4,5,4,5,17,13.0,satisfied +3365,47535,Male,Loyal Customer,14,Personal Travel,Eco,599,4,5,4,5,3,4,3,3,3,2,5,1,1,3,0,0.0,neutral or dissatisfied +3366,75426,Female,Loyal Customer,43,Business travel,Eco,2342,1,4,4,4,3,2,4,1,1,1,1,2,1,1,2,13.0,neutral or dissatisfied +3367,17516,Female,Loyal Customer,36,Personal Travel,Eco,352,3,3,3,2,3,3,3,3,4,1,4,2,3,3,0,12.0,neutral or dissatisfied +3368,3899,Female,disloyal Customer,56,Business travel,Eco,213,3,4,2,1,4,2,4,4,3,3,1,3,3,4,0,0.0,neutral or dissatisfied +3369,89782,Male,Loyal Customer,43,Personal Travel,Eco,950,4,1,4,3,3,4,4,3,4,5,3,3,4,3,49,32.0,neutral or dissatisfied +3370,61211,Female,Loyal Customer,57,Business travel,Eco,967,1,5,3,3,4,3,3,1,1,1,1,2,1,3,5,0.0,neutral or dissatisfied +3371,8077,Male,Loyal Customer,57,Business travel,Business,335,3,3,3,3,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +3372,80963,Female,Loyal Customer,43,Business travel,Business,2066,0,0,0,3,4,4,4,1,1,1,1,4,1,5,0,0.0,satisfied +3373,114709,Female,Loyal Customer,46,Business travel,Business,371,4,4,4,4,3,5,5,2,2,2,2,3,2,3,9,9.0,satisfied +3374,89504,Male,Loyal Customer,60,Personal Travel,Eco,684,2,4,2,2,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +3375,27096,Male,disloyal Customer,23,Business travel,Eco,1373,2,2,2,2,2,2,2,2,4,1,4,2,1,2,0,0.0,neutral or dissatisfied +3376,69140,Female,Loyal Customer,33,Business travel,Business,2248,1,1,1,1,4,3,3,5,4,4,4,3,4,3,317,324.0,satisfied +3377,25399,Male,Loyal Customer,25,Business travel,Business,990,4,4,4,4,5,5,5,5,1,1,4,2,2,5,0,0.0,satisfied +3378,84151,Female,disloyal Customer,22,Business travel,Eco,1355,3,3,3,2,3,3,3,3,1,5,2,3,2,3,18,19.0,neutral or dissatisfied +3379,49215,Male,Loyal Customer,35,Business travel,Business,3946,4,4,4,4,5,3,4,5,5,4,5,3,5,1,0,0.0,satisfied +3380,73989,Female,Loyal Customer,37,Personal Travel,Eco Plus,2218,1,2,1,3,1,1,1,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +3381,46030,Female,Loyal Customer,65,Business travel,Eco,964,4,2,2,2,1,5,5,4,4,4,4,2,4,4,0,0.0,satisfied +3382,32047,Female,disloyal Customer,37,Business travel,Eco,101,2,0,1,3,3,1,3,3,5,1,5,3,1,3,0,0.0,neutral or dissatisfied +3383,25662,Female,Loyal Customer,52,Business travel,Eco,761,5,1,1,1,1,1,5,5,5,5,5,3,5,5,0,0.0,satisfied +3384,25472,Male,disloyal Customer,18,Business travel,Eco,547,0,0,0,4,2,0,2,2,4,2,3,1,3,2,17,0.0,satisfied +3385,51505,Male,disloyal Customer,20,Business travel,Eco,370,4,0,4,5,4,4,4,4,2,5,2,5,5,4,0,0.0,neutral or dissatisfied +3386,113791,Male,Loyal Customer,40,Business travel,Business,2779,2,2,2,2,4,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +3387,116304,Female,Loyal Customer,33,Personal Travel,Eco,373,4,0,4,5,4,4,4,4,5,4,4,5,5,4,27,28.0,neutral or dissatisfied +3388,18596,Female,Loyal Customer,30,Business travel,Business,3293,3,2,3,3,4,4,3,4,2,5,1,3,3,4,3,0.0,satisfied +3389,62589,Female,disloyal Customer,43,Business travel,Eco,226,4,0,4,3,4,4,3,4,5,1,1,5,3,4,3,0.0,neutral or dissatisfied +3390,44985,Female,Loyal Customer,52,Business travel,Eco,222,3,2,2,2,5,4,2,3,3,3,3,5,3,2,0,0.0,satisfied +3391,25615,Male,Loyal Customer,49,Business travel,Business,526,3,3,1,3,2,5,2,4,4,4,4,5,4,5,48,51.0,satisfied +3392,79119,Male,Loyal Customer,45,Personal Travel,Eco,226,4,4,4,2,4,4,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +3393,109775,Female,Loyal Customer,55,Business travel,Business,2872,2,1,1,1,5,3,3,2,2,2,2,1,2,4,6,0.0,neutral or dissatisfied +3394,69690,Female,Loyal Customer,42,Business travel,Business,1372,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,26.0,satisfied +3395,86666,Male,Loyal Customer,41,Personal Travel,Eco,746,1,1,1,2,2,1,2,2,1,2,3,2,2,2,25,32.0,neutral or dissatisfied +3396,24470,Female,Loyal Customer,27,Business travel,Business,3186,3,3,3,3,4,4,4,4,2,2,4,1,5,4,109,120.0,satisfied +3397,124501,Female,Loyal Customer,40,Business travel,Business,3473,1,1,1,1,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +3398,41035,Female,disloyal Customer,22,Business travel,Eco,1086,1,1,1,3,5,1,5,5,2,3,3,3,4,5,0,0.0,neutral or dissatisfied +3399,43619,Male,Loyal Customer,65,Business travel,Eco,297,3,5,5,5,4,3,4,4,2,4,3,4,4,4,40,26.0,neutral or dissatisfied +3400,113860,Male,Loyal Customer,38,Business travel,Eco,1334,3,2,2,2,3,3,3,3,3,2,4,3,4,3,15,0.0,neutral or dissatisfied +3401,114459,Female,Loyal Customer,34,Business travel,Business,3951,1,3,3,3,2,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +3402,22464,Male,Loyal Customer,58,Personal Travel,Eco,238,1,4,1,3,1,1,1,1,5,3,5,5,4,1,0,13.0,neutral or dissatisfied +3403,50022,Female,Loyal Customer,49,Business travel,Eco,308,3,5,5,5,4,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +3404,97107,Male,Loyal Customer,59,Business travel,Business,1390,2,2,5,2,2,5,4,4,4,4,4,4,4,5,15,8.0,satisfied +3405,31370,Male,Loyal Customer,32,Business travel,Business,3749,4,4,4,4,2,2,2,2,3,3,3,4,3,2,0,0.0,satisfied +3406,103369,Male,Loyal Customer,46,Personal Travel,Eco,342,1,2,1,3,2,1,2,2,2,3,3,4,3,2,6,0.0,neutral or dissatisfied +3407,64293,Female,Loyal Customer,58,Business travel,Business,3893,1,1,1,1,2,4,4,4,4,4,4,5,4,3,23,16.0,satisfied +3408,105081,Male,Loyal Customer,60,Business travel,Business,220,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +3409,44080,Male,Loyal Customer,32,Business travel,Eco Plus,651,5,1,1,1,5,5,5,5,4,4,4,1,4,5,0,0.0,satisfied +3410,18017,Female,Loyal Customer,61,Personal Travel,Eco,332,1,5,1,4,5,4,5,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +3411,69894,Female,Loyal Customer,48,Business travel,Business,1671,4,4,4,4,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +3412,111812,Female,Loyal Customer,28,Personal Travel,Eco,349,4,5,4,3,2,4,2,2,5,2,4,4,4,2,0,2.0,neutral or dissatisfied +3413,57003,Male,Loyal Customer,27,Personal Travel,Eco,2454,4,5,4,3,4,3,3,3,5,5,5,3,5,3,7,0.0,satisfied +3414,25181,Male,Loyal Customer,27,Business travel,Business,577,3,3,3,3,4,4,4,4,1,5,2,4,1,4,35,17.0,satisfied +3415,79612,Female,Loyal Customer,53,Business travel,Eco,749,2,4,4,4,2,3,3,2,2,2,2,4,2,2,52,35.0,neutral or dissatisfied +3416,112164,Male,Loyal Customer,39,Business travel,Business,2130,2,3,3,3,4,3,3,2,2,2,2,4,2,2,14,27.0,neutral or dissatisfied +3417,27757,Female,Loyal Customer,49,Business travel,Business,1448,1,1,1,1,1,5,3,5,5,4,5,2,5,4,6,0.0,satisfied +3418,127316,Male,Loyal Customer,33,Personal Travel,Eco,1979,1,4,1,4,1,1,1,1,5,1,1,1,4,1,0,0.0,neutral or dissatisfied +3419,100401,Female,Loyal Customer,51,Business travel,Business,1646,4,4,2,4,3,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +3420,25131,Male,Loyal Customer,44,Business travel,Business,2832,4,4,4,4,5,5,5,2,2,3,3,5,1,5,161,175.0,satisfied +3421,96336,Female,Loyal Customer,58,Business travel,Business,1609,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +3422,89231,Male,Loyal Customer,30,Business travel,Business,2139,3,3,3,3,4,4,4,4,5,3,5,4,4,4,78,68.0,satisfied +3423,56762,Female,disloyal Customer,38,Business travel,Business,937,1,1,1,4,5,1,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +3424,11980,Male,Loyal Customer,43,Business travel,Eco,643,5,2,2,2,4,5,4,4,1,1,2,5,3,4,2,0.0,satisfied +3425,8295,Male,Loyal Customer,56,Personal Travel,Eco,125,4,4,4,4,2,4,2,2,5,5,2,4,4,2,0,0.0,neutral or dissatisfied +3426,18771,Female,disloyal Customer,21,Business travel,Business,448,4,2,4,5,2,4,2,2,4,4,5,3,5,2,0,0.0,satisfied +3427,100157,Female,disloyal Customer,23,Business travel,Eco,725,3,3,3,4,1,3,1,1,3,4,4,1,4,1,11,18.0,neutral or dissatisfied +3428,59467,Female,Loyal Customer,53,Business travel,Business,758,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +3429,99873,Female,disloyal Customer,25,Business travel,Business,1436,5,0,5,2,3,5,5,3,5,4,4,4,5,3,0,0.0,satisfied +3430,124062,Female,disloyal Customer,35,Business travel,Eco,2153,4,4,4,2,4,4,4,4,3,1,2,4,3,4,0,0.0,neutral or dissatisfied +3431,78662,Male,disloyal Customer,25,Business travel,Business,834,4,0,4,2,3,4,3,3,5,2,4,4,5,3,0,5.0,neutral or dissatisfied +3432,42092,Female,Loyal Customer,26,Business travel,Eco,964,4,5,3,5,4,4,5,4,3,4,1,5,2,4,0,0.0,satisfied +3433,72285,Male,Loyal Customer,18,Personal Travel,Eco,921,0,4,0,4,3,0,3,3,4,3,4,5,5,3,1,0.0,satisfied +3434,45168,Male,Loyal Customer,68,Personal Travel,Eco,174,3,4,3,4,3,3,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +3435,44754,Male,Loyal Customer,61,Personal Travel,Eco,612,4,0,4,3,1,4,1,1,4,5,4,3,4,1,18,10.0,neutral or dissatisfied +3436,5781,Male,Loyal Customer,40,Business travel,Business,157,0,4,0,4,3,4,5,3,3,3,3,3,3,5,95,122.0,satisfied +3437,49369,Male,Loyal Customer,39,Business travel,Business,86,4,3,4,4,5,3,5,5,5,5,3,4,5,3,0,0.0,satisfied +3438,26102,Male,Loyal Customer,65,Personal Travel,Eco,591,1,5,1,1,4,1,4,4,3,3,4,5,4,4,20,20.0,neutral or dissatisfied +3439,89760,Female,Loyal Customer,23,Personal Travel,Eco,1010,2,4,2,3,2,2,2,4,5,1,4,2,1,2,102,190.0,neutral or dissatisfied +3440,42986,Female,Loyal Customer,62,Business travel,Business,3467,3,3,3,3,1,5,4,5,5,5,5,2,5,2,0,0.0,satisfied +3441,86384,Female,Loyal Customer,48,Business travel,Business,2706,2,2,2,2,4,5,5,5,5,5,5,4,5,4,36,40.0,satisfied +3442,66722,Female,Loyal Customer,50,Personal Travel,Eco,978,4,5,4,3,2,5,5,5,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +3443,91438,Female,disloyal Customer,23,Business travel,Eco,859,2,2,2,1,5,2,5,5,5,4,4,3,5,5,17,21.0,neutral or dissatisfied +3444,113405,Female,Loyal Customer,57,Business travel,Business,3273,4,4,4,4,3,5,4,4,4,5,4,3,4,5,64,51.0,satisfied +3445,105564,Female,Loyal Customer,39,Business travel,Business,2614,4,4,4,4,4,4,5,5,5,5,5,5,5,5,23,17.0,satisfied +3446,42171,Male,Loyal Customer,61,Business travel,Eco,451,5,3,3,3,5,5,5,5,1,5,2,2,4,5,0,0.0,satisfied +3447,124528,Male,Loyal Customer,30,Business travel,Business,3496,3,3,3,3,2,2,2,2,3,2,5,4,4,2,0,0.0,satisfied +3448,32264,Female,Loyal Customer,39,Business travel,Eco,101,4,2,2,2,4,4,4,4,3,2,4,3,2,4,2,13.0,satisfied +3449,114687,Female,disloyal Customer,22,Business travel,Eco,308,1,4,1,2,4,1,2,4,3,2,4,3,4,4,11,10.0,neutral or dissatisfied +3450,104220,Female,Loyal Customer,16,Business travel,Business,1979,4,4,4,4,4,4,4,4,3,4,4,5,4,4,7,2.0,satisfied +3451,15761,Female,Loyal Customer,36,Personal Travel,Eco,544,2,4,2,4,1,2,1,1,4,4,3,4,4,1,46,30.0,neutral or dissatisfied +3452,48065,Female,Loyal Customer,47,Business travel,Business,2143,3,3,3,3,5,4,5,4,4,4,4,3,4,3,104,109.0,satisfied +3453,89390,Male,disloyal Customer,59,Business travel,Business,151,3,3,3,3,5,3,5,5,4,2,5,4,4,5,10,2.0,neutral or dissatisfied +3454,124794,Female,disloyal Customer,21,Business travel,Business,280,5,0,5,1,3,5,3,3,4,3,5,4,5,3,0,0.0,satisfied +3455,34375,Female,Loyal Customer,51,Personal Travel,Business,612,2,1,3,3,1,3,2,2,2,3,3,1,2,2,0,0.0,neutral or dissatisfied +3456,10482,Male,Loyal Customer,56,Business travel,Business,2013,3,3,3,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +3457,18146,Female,disloyal Customer,43,Business travel,Business,296,4,4,4,4,2,4,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +3458,48342,Female,Loyal Customer,45,Business travel,Eco,522,4,3,3,3,5,4,3,4,4,4,4,3,4,4,99,87.0,satisfied +3459,15914,Male,Loyal Customer,44,Business travel,Eco,607,4,4,3,4,4,4,4,4,5,5,2,2,1,4,66,60.0,satisfied +3460,64938,Female,Loyal Customer,55,Business travel,Business,2511,1,3,3,3,3,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +3461,7104,Female,Loyal Customer,21,Personal Travel,Eco,157,0,4,0,4,5,0,5,5,5,2,4,5,4,5,0,0.0,satisfied +3462,48150,Male,Loyal Customer,21,Business travel,Eco,391,5,5,4,5,4,3,5,4,5,4,3,5,2,5,176,177.0,neutral or dissatisfied +3463,121738,Male,Loyal Customer,45,Personal Travel,Eco,1475,3,4,3,4,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +3464,109219,Male,Loyal Customer,36,Business travel,Business,255,1,1,1,1,2,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +3465,55811,Female,Loyal Customer,47,Business travel,Business,1416,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +3466,15461,Male,Loyal Customer,36,Business travel,Eco,399,5,5,5,5,5,5,5,5,2,4,1,3,5,5,0,0.0,satisfied +3467,36095,Male,Loyal Customer,35,Personal Travel,Eco,399,4,4,3,2,3,3,4,3,4,3,5,5,5,3,0,0.0,satisfied +3468,62746,Male,Loyal Customer,36,Business travel,Business,2556,3,3,3,3,4,4,4,4,2,4,5,4,4,4,6,9.0,satisfied +3469,37950,Male,Loyal Customer,10,Personal Travel,Eco Plus,937,5,4,5,1,3,5,3,3,5,1,1,5,5,3,0,0.0,satisfied +3470,99114,Male,Loyal Customer,17,Personal Travel,Eco,237,3,5,0,2,2,0,2,2,4,2,4,3,5,2,8,45.0,neutral or dissatisfied +3471,4974,Male,Loyal Customer,43,Business travel,Business,2333,1,3,1,1,5,5,5,3,3,3,3,5,3,4,119,125.0,satisfied +3472,59349,Male,disloyal Customer,36,Business travel,Business,2447,3,3,3,3,2,3,1,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +3473,29125,Female,Loyal Customer,63,Personal Travel,Eco,605,2,4,2,4,5,4,5,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +3474,12515,Male,Loyal Customer,46,Business travel,Business,3422,3,3,3,3,5,4,3,4,4,4,4,4,4,3,10,21.0,satisfied +3475,22108,Female,Loyal Customer,33,Business travel,Business,3432,2,2,2,2,5,3,2,4,4,4,4,3,4,2,0,0.0,satisfied +3476,72556,Male,Loyal Customer,53,Business travel,Eco,929,4,3,3,3,3,4,3,3,4,2,2,4,2,3,0,0.0,neutral or dissatisfied +3477,89556,Female,disloyal Customer,22,Business travel,Eco,1096,4,4,4,1,4,4,4,4,4,2,4,5,4,4,41,21.0,neutral or dissatisfied +3478,13780,Male,Loyal Customer,39,Business travel,Business,837,1,1,1,1,5,2,1,4,4,4,4,3,4,2,0,4.0,satisfied +3479,81758,Male,Loyal Customer,55,Business travel,Business,1310,2,2,2,2,4,5,5,5,4,5,4,5,3,5,135,136.0,satisfied +3480,9368,Male,Loyal Customer,49,Business travel,Business,3072,4,4,5,4,3,5,1,5,5,5,5,1,5,2,0,0.0,satisfied +3481,44270,Male,Loyal Customer,34,Personal Travel,Eco,137,3,0,3,4,5,3,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +3482,62634,Female,Loyal Customer,13,Personal Travel,Eco,1723,3,1,3,3,5,3,5,5,1,4,2,2,2,5,0,32.0,neutral or dissatisfied +3483,75031,Female,Loyal Customer,16,Personal Travel,Eco,236,2,2,2,2,1,2,1,1,3,4,2,1,1,1,0,0.0,neutral or dissatisfied +3484,127117,Male,Loyal Customer,54,Personal Travel,Eco,370,2,0,2,3,5,2,4,5,4,5,5,3,4,5,0,7.0,neutral or dissatisfied +3485,16318,Male,Loyal Customer,59,Business travel,Business,3986,2,5,5,5,4,3,4,2,2,2,2,4,2,1,0,14.0,neutral or dissatisfied +3486,7985,Female,Loyal Customer,55,Business travel,Business,3980,1,1,3,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +3487,23344,Female,Loyal Customer,61,Personal Travel,Eco,674,0,4,1,2,3,4,4,1,1,1,1,4,1,5,0,0.0,satisfied +3488,66305,Male,Loyal Customer,47,Business travel,Business,1575,5,5,5,5,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +3489,602,Female,Loyal Customer,58,Business travel,Business,2797,1,1,1,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +3490,51750,Female,Loyal Customer,45,Personal Travel,Eco,355,5,4,5,4,4,3,3,3,3,5,3,1,3,2,0,1.0,satisfied +3491,78762,Male,Loyal Customer,29,Business travel,Eco,528,2,3,3,3,2,2,2,2,1,5,4,4,3,2,95,91.0,neutral or dissatisfied +3492,56217,Female,Loyal Customer,56,Business travel,Business,1608,4,2,5,2,5,2,4,4,4,4,4,3,4,2,9,10.0,neutral or dissatisfied +3493,99811,Female,disloyal Customer,24,Business travel,Business,584,4,0,4,4,3,4,4,3,3,4,5,3,5,3,27,8.0,satisfied +3494,77403,Female,Loyal Customer,70,Personal Travel,Eco,590,2,3,2,3,5,4,4,5,5,2,4,1,5,4,3,0.0,neutral or dissatisfied +3495,18692,Male,Loyal Customer,61,Personal Travel,Eco,127,4,3,4,4,2,4,4,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +3496,118575,Male,Loyal Customer,53,Business travel,Business,2041,3,1,3,3,4,4,5,5,5,5,5,3,5,3,3,0.0,satisfied +3497,82652,Female,Loyal Customer,51,Business travel,Business,120,5,5,5,5,2,5,5,3,3,4,5,4,3,5,63,69.0,satisfied +3498,32905,Male,Loyal Customer,19,Personal Travel,Eco,163,2,4,2,4,1,2,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +3499,75980,Female,Loyal Customer,59,Personal Travel,Eco,297,1,3,1,3,1,2,2,5,5,1,5,1,5,3,15,2.0,neutral or dissatisfied +3500,82660,Female,Loyal Customer,47,Personal Travel,Eco,120,4,4,4,3,2,4,4,1,1,4,4,2,1,3,0,0.0,neutral or dissatisfied +3501,62512,Female,Loyal Customer,49,Business travel,Business,1744,1,1,1,1,4,5,5,5,5,5,5,5,5,5,12,0.0,satisfied +3502,76032,Female,Loyal Customer,63,Personal Travel,Eco,311,1,5,1,1,5,5,4,2,2,1,2,3,2,3,0,4.0,neutral or dissatisfied +3503,68075,Female,disloyal Customer,24,Business travel,Eco,813,2,2,2,3,5,2,5,5,1,3,4,1,3,5,0,7.0,neutral or dissatisfied +3504,112407,Female,Loyal Customer,33,Business travel,Business,1862,2,2,2,2,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +3505,101725,Female,Loyal Customer,28,Personal Travel,Business,1216,3,1,3,3,5,3,5,5,1,1,4,3,4,5,3,0.0,neutral or dissatisfied +3506,112551,Female,Loyal Customer,45,Business travel,Business,967,5,2,5,5,2,5,4,4,4,4,4,5,4,4,44,20.0,satisfied +3507,101616,Female,Loyal Customer,49,Business travel,Eco,1139,1,3,4,3,4,4,4,1,1,1,1,2,1,4,9,0.0,neutral or dissatisfied +3508,106874,Female,disloyal Customer,25,Business travel,Business,577,3,4,3,1,4,3,5,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +3509,87969,Male,disloyal Customer,21,Business travel,Eco,594,4,0,4,3,4,4,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +3510,124823,Male,Loyal Customer,21,Business travel,Business,1561,4,4,4,4,5,5,5,5,4,1,2,3,1,5,0,0.0,satisfied +3511,114911,Male,Loyal Customer,35,Business travel,Business,1610,4,4,4,4,3,5,5,4,4,4,4,3,4,5,20,18.0,satisfied +3512,101182,Male,Loyal Customer,69,Personal Travel,Eco,1090,3,2,3,4,4,3,2,4,1,1,4,3,4,4,13,0.0,neutral or dissatisfied +3513,27165,Male,Loyal Customer,58,Business travel,Business,2640,4,4,4,4,4,4,4,2,2,3,5,4,2,4,3,0.0,satisfied +3514,73018,Female,Loyal Customer,20,Personal Travel,Eco,1096,4,3,4,1,3,4,3,3,1,1,4,5,5,3,0,0.0,neutral or dissatisfied +3515,62655,Female,Loyal Customer,7,Personal Travel,Eco,1744,1,5,1,4,4,1,1,4,4,4,4,5,4,4,4,22.0,neutral or dissatisfied +3516,8685,Female,Loyal Customer,38,Business travel,Business,3939,3,3,3,3,3,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +3517,9035,Male,Loyal Customer,60,Business travel,Eco,173,3,5,5,5,3,3,3,3,2,5,3,1,3,3,49,49.0,neutral or dissatisfied +3518,94549,Male,disloyal Customer,24,Business travel,Business,239,0,5,0,4,3,0,3,3,4,4,4,5,4,3,106,105.0,satisfied +3519,73628,Male,Loyal Customer,54,Business travel,Business,2800,0,5,1,4,2,5,4,3,3,3,3,5,3,5,8,5.0,satisfied +3520,94981,Female,Loyal Customer,53,Business travel,Eco,189,5,1,1,1,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +3521,104944,Male,Loyal Customer,64,Personal Travel,Eco,1180,3,5,3,1,2,3,2,2,3,2,5,4,5,2,12,3.0,neutral or dissatisfied +3522,102555,Female,Loyal Customer,28,Personal Travel,Eco,258,2,2,2,4,5,2,5,5,3,2,3,2,4,5,13,7.0,neutral or dissatisfied +3523,55256,Female,Loyal Customer,13,Personal Travel,Eco,1009,3,5,3,2,5,3,5,5,4,5,2,1,2,5,0,0.0,neutral or dissatisfied +3524,29034,Female,disloyal Customer,24,Business travel,Eco,578,3,0,3,3,3,3,3,3,5,1,4,2,3,3,0,0.0,neutral or dissatisfied +3525,90776,Female,Loyal Customer,44,Business travel,Business,3994,1,1,1,1,5,5,4,4,4,4,4,5,4,4,2,17.0,satisfied +3526,74020,Female,Loyal Customer,58,Business travel,Business,1471,1,1,1,1,3,5,4,3,3,4,3,3,3,4,59,60.0,satisfied +3527,35078,Female,Loyal Customer,13,Personal Travel,Business,1097,3,1,3,2,3,3,3,3,2,3,3,4,3,3,18,11.0,neutral or dissatisfied +3528,63847,Male,Loyal Customer,30,Business travel,Business,1172,1,1,1,1,4,4,4,4,4,2,4,5,5,4,15,11.0,satisfied +3529,24884,Male,Loyal Customer,53,Business travel,Business,1842,2,3,2,3,1,1,2,2,2,2,2,2,2,2,0,1.0,neutral or dissatisfied +3530,33332,Female,Loyal Customer,24,Business travel,Business,2556,3,3,3,3,5,5,5,5,1,1,4,4,4,5,10,0.0,satisfied +3531,91219,Female,Loyal Customer,10,Personal Travel,Eco,594,1,3,1,4,2,1,2,2,5,1,2,2,1,2,0,0.0,neutral or dissatisfied +3532,13111,Female,Loyal Customer,51,Business travel,Eco,595,3,3,4,3,4,5,2,3,3,3,3,5,3,3,9,5.0,satisfied +3533,56016,Female,Loyal Customer,26,Business travel,Business,2586,2,4,4,4,2,2,2,4,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +3534,13330,Female,disloyal Customer,40,Business travel,Business,748,4,4,4,3,5,4,2,5,1,4,2,3,4,5,0,0.0,neutral or dissatisfied +3535,18345,Female,Loyal Customer,34,Personal Travel,Eco,563,2,2,2,2,3,2,3,3,2,5,1,4,2,3,10,0.0,neutral or dissatisfied +3536,38922,Male,Loyal Customer,55,Business travel,Eco,410,3,3,3,3,3,3,3,3,4,3,3,3,4,3,125,132.0,neutral or dissatisfied +3537,15795,Male,disloyal Customer,39,Business travel,Business,282,3,3,3,3,4,3,3,4,3,5,2,4,3,4,0,0.0,satisfied +3538,29346,Female,Loyal Customer,67,Personal Travel,Eco Plus,569,1,5,2,4,2,5,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +3539,38998,Female,disloyal Customer,24,Business travel,Eco,230,2,3,2,3,1,2,1,1,1,2,5,1,1,1,0,3.0,neutral or dissatisfied +3540,57819,Female,Loyal Customer,43,Business travel,Business,622,5,1,5,5,3,5,5,4,4,5,4,5,4,4,1,0.0,satisfied +3541,123766,Female,disloyal Customer,22,Business travel,Business,603,4,3,4,3,1,4,1,1,1,3,4,3,3,1,0,32.0,neutral or dissatisfied +3542,125487,Female,Loyal Customer,30,Business travel,Eco Plus,2917,0,0,0,3,1,0,1,1,5,1,1,4,5,1,0,0.0,satisfied +3543,105177,Female,Loyal Customer,55,Personal Travel,Eco,289,2,5,2,4,3,4,5,4,4,2,4,3,4,5,18,0.0,neutral or dissatisfied +3544,105294,Male,Loyal Customer,55,Business travel,Business,1787,2,2,2,2,5,5,4,5,5,4,5,3,5,3,6,40.0,satisfied +3545,58337,Female,Loyal Customer,70,Business travel,Business,2113,4,4,4,4,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +3546,32240,Female,Loyal Customer,57,Business travel,Business,2012,5,5,4,5,2,2,5,4,4,4,3,1,4,2,12,17.0,satisfied +3547,106854,Female,Loyal Customer,25,Business travel,Business,577,2,2,5,2,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +3548,3441,Female,Loyal Customer,62,Personal Travel,Eco,315,2,5,2,2,5,4,4,3,3,2,3,3,3,3,15,2.0,neutral or dissatisfied +3549,53995,Female,Loyal Customer,25,Business travel,Eco,325,3,5,5,5,3,3,4,3,1,1,3,4,4,3,31,8.0,neutral or dissatisfied +3550,99741,Female,Loyal Customer,36,Business travel,Business,361,4,1,4,4,5,4,4,4,4,4,4,4,4,3,43,43.0,satisfied +3551,70844,Female,disloyal Customer,29,Business travel,Eco,761,4,4,4,4,3,4,3,3,4,4,3,3,4,3,0,20.0,neutral or dissatisfied +3552,3009,Female,Loyal Customer,47,Business travel,Business,2989,1,1,1,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +3553,29920,Female,Loyal Customer,57,Business travel,Eco,548,5,5,5,5,2,5,5,5,5,5,5,1,5,4,24,27.0,satisfied +3554,108899,Male,Loyal Customer,45,Business travel,Eco,1183,3,3,3,3,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +3555,124435,Female,Loyal Customer,30,Personal Travel,Eco,1044,3,4,3,4,5,3,1,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +3556,108956,Female,Loyal Customer,57,Business travel,Business,2920,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +3557,25108,Female,Loyal Customer,34,Personal Travel,Business,946,2,4,2,3,1,3,4,4,4,2,4,4,4,4,13,4.0,neutral or dissatisfied +3558,80199,Male,Loyal Customer,26,Personal Travel,Eco,2475,0,2,0,4,2,0,2,2,3,1,3,2,4,2,0,0.0,satisfied +3559,52429,Female,Loyal Customer,19,Personal Travel,Eco,370,3,1,3,3,1,3,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +3560,100811,Female,disloyal Customer,25,Business travel,Eco,1167,2,3,3,3,2,3,1,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +3561,6334,Male,disloyal Customer,37,Business travel,Business,296,3,3,3,2,4,3,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +3562,330,Male,Loyal Customer,46,Business travel,Business,3293,2,4,4,4,2,4,3,2,2,2,2,1,2,3,0,5.0,neutral or dissatisfied +3563,122263,Female,Loyal Customer,17,Personal Travel,Eco,544,4,5,4,3,5,4,5,5,5,3,2,5,3,5,3,7.0,satisfied +3564,104404,Male,disloyal Customer,23,Business travel,Business,1041,0,4,0,1,3,0,3,3,5,3,5,5,5,3,0,0.0,satisfied +3565,104679,Male,disloyal Customer,30,Business travel,Eco Plus,641,3,3,3,4,1,3,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +3566,64008,Female,Loyal Customer,14,Personal Travel,Eco,612,3,5,3,1,4,3,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +3567,76639,Female,Loyal Customer,7,Personal Travel,Eco,481,4,5,4,3,1,4,1,1,1,5,2,2,2,1,2,0.0,satisfied +3568,55302,Male,disloyal Customer,30,Business travel,Business,1475,0,0,0,2,5,0,5,5,3,5,5,3,4,5,9,0.0,satisfied +3569,36304,Male,disloyal Customer,23,Business travel,Eco,187,2,0,2,3,4,2,4,4,1,3,5,1,3,4,0,0.0,neutral or dissatisfied +3570,32398,Female,disloyal Customer,26,Business travel,Eco,216,1,5,0,1,5,0,5,5,1,5,5,4,1,5,0,0.0,neutral or dissatisfied +3571,57298,Male,Loyal Customer,46,Business travel,Business,3150,0,0,0,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +3572,50626,Female,Loyal Customer,45,Personal Travel,Eco,109,4,5,4,2,4,3,5,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +3573,100817,Female,Loyal Customer,31,Business travel,Business,711,3,3,3,3,4,4,4,4,3,2,5,3,4,4,24,25.0,satisfied +3574,40963,Male,Loyal Customer,40,Business travel,Eco,601,1,4,2,4,1,1,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +3575,91290,Female,Loyal Customer,61,Business travel,Business,404,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +3576,44150,Female,Loyal Customer,57,Business travel,Eco Plus,120,4,2,2,2,5,4,2,3,3,4,3,3,3,2,1,4.0,satisfied +3577,119457,Female,Loyal Customer,21,Personal Travel,Business,899,1,3,1,1,4,1,5,4,5,5,4,4,1,4,9,0.0,neutral or dissatisfied +3578,126848,Female,Loyal Customer,29,Business travel,Business,2125,2,2,2,2,2,2,2,2,1,2,2,2,2,2,6,0.0,neutral or dissatisfied +3579,112405,Female,Loyal Customer,44,Business travel,Business,2239,2,2,2,2,2,4,4,5,5,5,5,5,5,4,22,22.0,satisfied +3580,30023,Male,disloyal Customer,34,Business travel,Eco,725,2,1,1,2,3,1,1,3,3,1,2,1,3,3,21,21.0,neutral or dissatisfied +3581,21429,Male,disloyal Customer,22,Business travel,Eco,377,3,0,3,2,3,3,2,3,1,2,4,5,3,3,44,38.0,neutral or dissatisfied +3582,128256,Female,disloyal Customer,33,Business travel,Business,651,1,1,1,2,4,1,5,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +3583,75817,Female,Loyal Customer,26,Personal Travel,Eco Plus,868,3,2,3,3,2,3,2,2,1,4,2,2,3,2,24,17.0,neutral or dissatisfied +3584,13860,Female,Loyal Customer,30,Personal Travel,Business,667,1,5,1,3,4,1,4,4,3,4,4,3,4,4,4,25.0,neutral or dissatisfied +3585,13092,Male,disloyal Customer,42,Business travel,Eco,427,2,5,2,2,5,2,5,5,2,5,3,5,4,5,0,12.0,neutral or dissatisfied +3586,79928,Male,Loyal Customer,51,Business travel,Business,1562,2,2,1,2,5,4,5,4,4,4,4,4,4,5,17,2.0,satisfied +3587,128234,Male,Loyal Customer,35,Personal Travel,Eco,602,3,4,4,2,5,4,5,5,3,3,5,2,4,5,0,0.0,neutral or dissatisfied +3588,94551,Female,Loyal Customer,58,Business travel,Business,2880,5,5,5,5,4,5,4,4,4,4,4,4,4,5,11,9.0,satisfied +3589,16388,Female,Loyal Customer,41,Business travel,Eco,404,4,4,4,4,3,4,3,3,2,1,5,1,5,3,34,24.0,satisfied +3590,59230,Male,Loyal Customer,40,Business travel,Business,649,4,2,2,2,2,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +3591,85028,Female,Loyal Customer,23,Personal Travel,Eco,1590,3,4,3,1,2,3,2,2,3,2,5,3,5,2,14,24.0,neutral or dissatisfied +3592,5910,Female,disloyal Customer,29,Business travel,Eco,173,1,0,1,4,5,1,5,5,5,2,4,5,2,5,3,5.0,neutral or dissatisfied +3593,61392,Female,disloyal Customer,24,Business travel,Eco,679,5,5,5,3,2,5,2,2,4,3,4,5,5,2,0,0.0,satisfied +3594,114839,Female,Loyal Customer,53,Business travel,Business,480,3,3,3,3,4,4,4,4,4,4,4,5,4,4,8,1.0,satisfied +3595,70424,Female,Loyal Customer,55,Business travel,Business,187,0,5,0,1,4,5,4,3,3,3,3,3,3,3,0,8.0,satisfied +3596,92250,Male,disloyal Customer,25,Business travel,Eco,700,2,3,3,3,3,2,1,3,1,1,4,3,4,3,51,38.0,neutral or dissatisfied +3597,56104,Female,disloyal Customer,25,Business travel,Eco,2402,2,2,2,4,2,2,5,2,3,1,4,3,3,2,0,0.0,neutral or dissatisfied +3598,16436,Female,Loyal Customer,37,Business travel,Eco,416,2,2,4,2,2,2,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +3599,18834,Male,Loyal Customer,28,Business travel,Business,551,4,4,4,4,5,5,5,5,3,2,3,3,4,5,0,0.0,satisfied +3600,83778,Male,Loyal Customer,51,Business travel,Business,2848,1,4,2,4,5,2,3,1,1,1,1,4,1,3,8,6.0,neutral or dissatisfied +3601,89626,Male,Loyal Customer,34,Business travel,Business,3418,5,5,5,5,5,5,5,4,2,4,4,5,5,5,320,320.0,satisfied +3602,82578,Female,Loyal Customer,57,Business travel,Business,528,2,2,2,2,5,5,5,4,4,4,4,5,4,4,3,0.0,satisfied +3603,7123,Male,Loyal Customer,17,Personal Travel,Eco Plus,157,4,4,4,1,2,4,2,2,5,3,4,5,5,2,62,110.0,neutral or dissatisfied +3604,40199,Female,Loyal Customer,28,Business travel,Business,347,1,1,1,1,4,4,4,4,1,3,2,2,4,4,0,0.0,satisfied +3605,10673,Male,Loyal Customer,46,Business travel,Business,2688,3,3,3,3,2,4,4,4,4,4,4,5,4,3,99,107.0,satisfied +3606,115509,Female,Loyal Customer,60,Business travel,Business,342,3,3,2,3,3,5,4,5,5,5,5,4,5,5,5,2.0,satisfied +3607,16981,Male,Loyal Customer,33,Business travel,Business,610,5,5,5,5,1,2,1,1,3,5,5,4,5,1,3,4.0,satisfied +3608,27083,Female,Loyal Customer,42,Business travel,Eco,2496,4,4,4,4,4,4,3,4,4,4,4,2,4,1,3,0.0,satisfied +3609,53370,Female,disloyal Customer,45,Business travel,Eco,1452,1,2,2,3,2,1,4,2,1,3,4,2,4,2,2,30.0,neutral or dissatisfied +3610,120044,Male,Loyal Customer,32,Business travel,Eco,168,3,5,5,5,3,3,3,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +3611,59201,Female,disloyal Customer,22,Business travel,Eco,1044,2,2,2,2,5,2,5,5,4,5,4,4,4,5,0,4.0,neutral or dissatisfied +3612,85763,Male,Loyal Customer,47,Business travel,Business,666,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +3613,92927,Male,disloyal Customer,42,Business travel,Eco,134,3,0,3,2,2,3,2,2,1,2,1,3,3,2,69,66.0,neutral or dissatisfied +3614,22028,Male,Loyal Customer,44,Business travel,Eco Plus,500,3,1,1,1,3,3,3,3,1,3,4,2,2,3,0,5.0,satisfied +3615,66251,Female,Loyal Customer,32,Personal Travel,Eco,460,3,2,3,3,2,3,2,2,1,4,4,2,4,2,0,5.0,neutral or dissatisfied +3616,48657,Female,Loyal Customer,40,Business travel,Business,326,0,0,0,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3617,66691,Female,Loyal Customer,40,Business travel,Business,802,2,2,2,2,2,5,4,4,4,4,4,3,4,5,1,0.0,satisfied +3618,83074,Female,Loyal Customer,44,Business travel,Eco,1127,4,3,3,3,1,3,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +3619,35510,Female,Loyal Customer,9,Personal Travel,Eco,972,2,4,2,3,4,2,4,4,5,4,4,5,5,4,0,10.0,neutral or dissatisfied +3620,1170,Female,Loyal Customer,59,Personal Travel,Eco,282,4,5,4,3,4,3,3,2,2,4,2,5,2,1,14,16.0,neutral or dissatisfied +3621,48387,Male,Loyal Customer,47,Personal Travel,Eco,587,1,2,1,3,4,1,4,4,1,1,4,4,4,4,17,,neutral or dissatisfied +3622,66819,Male,Loyal Customer,62,Business travel,Business,731,1,1,1,1,5,4,5,5,5,5,5,4,5,5,43,61.0,satisfied +3623,126983,Male,Loyal Customer,56,Business travel,Business,1623,5,5,3,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +3624,90697,Male,Loyal Customer,34,Business travel,Business,1867,1,1,1,1,4,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +3625,42182,Male,Loyal Customer,26,Business travel,Eco,550,4,1,1,1,4,4,4,4,2,1,5,3,5,4,0,0.0,satisfied +3626,62918,Female,Loyal Customer,55,Business travel,Business,1586,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +3627,33792,Male,Loyal Customer,42,Business travel,Eco Plus,588,3,3,1,1,2,3,2,2,4,1,4,4,4,2,14,11.0,neutral or dissatisfied +3628,61621,Male,Loyal Customer,24,Business travel,Business,1504,3,3,3,3,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +3629,81570,Male,Loyal Customer,58,Personal Travel,Eco,936,4,4,4,2,1,4,1,1,4,3,5,3,5,1,0,3.0,neutral or dissatisfied +3630,73912,Male,Loyal Customer,58,Business travel,Business,2342,2,2,2,2,2,5,4,4,4,4,4,5,4,5,44,21.0,satisfied +3631,114177,Male,Loyal Customer,47,Business travel,Business,3289,1,2,1,1,5,5,4,4,4,3,4,3,4,4,0,0.0,satisfied +3632,98735,Female,disloyal Customer,11,Business travel,Eco,1290,1,1,1,3,3,1,3,3,3,2,4,4,3,3,4,46.0,neutral or dissatisfied +3633,120232,Female,Loyal Customer,15,Personal Travel,Eco,1303,2,5,2,2,2,2,1,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +3634,76983,Male,Loyal Customer,47,Business travel,Business,2613,3,3,3,3,2,5,5,4,4,4,4,5,4,4,14,18.0,satisfied +3635,37138,Female,Loyal Customer,23,Business travel,Eco,1046,5,1,1,1,5,5,3,5,5,5,2,3,3,5,76,67.0,satisfied +3636,51499,Female,Loyal Customer,59,Personal Travel,Business,598,3,0,2,5,2,4,5,2,2,2,4,4,2,4,82,77.0,neutral or dissatisfied +3637,39678,Male,Loyal Customer,74,Business travel,Business,3321,1,5,5,5,4,1,2,1,1,1,1,3,1,1,19,48.0,neutral or dissatisfied +3638,48416,Female,Loyal Customer,19,Personal Travel,Business,819,2,4,2,2,3,2,3,3,1,4,1,2,3,3,37,50.0,neutral or dissatisfied +3639,76045,Male,Loyal Customer,25,Personal Travel,Business,669,2,5,3,3,2,3,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +3640,114466,Female,Loyal Customer,45,Business travel,Business,371,3,3,3,3,4,4,4,5,5,5,5,3,5,3,8,7.0,satisfied +3641,4874,Male,Loyal Customer,28,Personal Travel,Eco,408,2,4,2,3,3,2,3,3,5,5,5,4,5,3,0,12.0,neutral or dissatisfied +3642,104300,Male,Loyal Customer,13,Personal Travel,Eco,440,4,3,4,4,5,4,1,5,3,3,3,4,4,5,2,14.0,neutral or dissatisfied +3643,111296,Male,Loyal Customer,21,Business travel,Business,2297,3,5,5,5,3,3,3,3,3,2,3,2,4,3,12,8.0,neutral or dissatisfied +3644,3289,Female,Loyal Customer,29,Personal Travel,Eco,483,1,4,1,3,2,1,2,2,5,1,3,4,4,2,40,40.0,neutral or dissatisfied +3645,51432,Male,Loyal Customer,50,Personal Travel,Eco Plus,363,1,1,4,4,2,4,2,2,4,2,4,2,4,2,3,0.0,neutral or dissatisfied +3646,84172,Female,disloyal Customer,23,Business travel,Eco,231,3,1,3,3,3,3,3,3,1,5,4,1,3,3,0,0.0,neutral or dissatisfied +3647,75830,Male,Loyal Customer,43,Business travel,Business,1437,2,2,2,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +3648,31742,Male,Loyal Customer,53,Business travel,Eco Plus,853,2,2,2,2,1,2,1,1,4,5,4,1,4,1,2,2.0,neutral or dissatisfied +3649,91127,Male,Loyal Customer,17,Personal Travel,Eco,366,3,4,3,3,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +3650,92404,Male,disloyal Customer,35,Business travel,Business,1947,2,2,2,1,1,2,1,1,4,5,3,4,4,1,0,9.0,neutral or dissatisfied +3651,101345,Male,Loyal Customer,47,Business travel,Business,526,2,4,4,4,3,2,1,2,2,3,2,2,2,4,7,0.0,neutral or dissatisfied +3652,70849,Male,Loyal Customer,16,Business travel,Business,3262,2,3,1,3,2,2,2,2,4,3,4,2,3,2,77,70.0,neutral or dissatisfied +3653,108827,Male,Loyal Customer,50,Business travel,Business,2647,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +3654,34387,Male,disloyal Customer,22,Business travel,Eco,612,1,4,1,4,2,1,5,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +3655,86872,Male,disloyal Customer,25,Business travel,Business,484,2,0,3,4,1,3,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +3656,60252,Male,Loyal Customer,42,Personal Travel,Eco,1546,2,5,2,3,1,2,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +3657,71609,Male,Loyal Customer,29,Business travel,Eco,1012,3,5,4,4,3,3,3,3,1,2,3,4,2,3,0,3.0,neutral or dissatisfied +3658,50712,Male,Loyal Customer,63,Personal Travel,Eco,209,4,2,4,4,5,4,2,5,4,4,3,3,3,5,0,3.0,neutral or dissatisfied +3659,45531,Female,Loyal Customer,40,Business travel,Business,566,5,5,5,5,1,2,1,5,5,5,5,2,5,5,0,10.0,satisfied +3660,85971,Male,Loyal Customer,59,Business travel,Business,3824,1,1,1,1,4,5,4,4,4,4,4,4,4,4,3,7.0,satisfied +3661,37267,Female,Loyal Customer,28,Business travel,Eco,1056,3,1,1,1,3,4,3,3,4,4,2,2,2,3,0,0.0,satisfied +3662,77325,Female,disloyal Customer,28,Business travel,Business,532,2,2,2,2,2,2,5,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +3663,120146,Female,Loyal Customer,20,Personal Travel,Eco,1475,5,4,5,4,2,5,2,2,1,5,2,4,3,2,0,0.0,satisfied +3664,62082,Male,Loyal Customer,57,Business travel,Eco Plus,2475,2,4,4,4,1,2,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +3665,41977,Female,Loyal Customer,35,Personal Travel,Eco,575,4,5,4,4,1,4,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +3666,6962,Female,disloyal Customer,47,Business travel,Business,436,1,1,1,3,5,1,5,5,4,3,4,5,5,5,7,0.0,neutral or dissatisfied +3667,69520,Female,Loyal Customer,50,Business travel,Business,2475,5,5,5,5,4,4,4,5,3,4,5,4,4,4,0,35.0,satisfied +3668,25207,Male,disloyal Customer,14,Business travel,Eco,787,3,3,3,4,2,3,2,2,3,1,3,3,3,2,106,107.0,neutral or dissatisfied +3669,35662,Female,Loyal Customer,23,Business travel,Business,2475,1,1,1,1,2,2,2,5,4,3,4,2,2,2,14,82.0,satisfied +3670,30028,Female,Loyal Customer,52,Business travel,Eco,399,5,2,2,2,2,1,4,5,5,5,5,2,5,1,84,84.0,satisfied +3671,111389,Male,Loyal Customer,28,Personal Travel,Eco,1173,1,1,0,1,2,0,2,2,1,2,1,4,2,2,0,0.0,neutral or dissatisfied +3672,14452,Female,disloyal Customer,29,Business travel,Eco,761,2,2,2,4,3,2,3,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +3673,60008,Female,Loyal Customer,41,Personal Travel,Eco,937,2,2,2,4,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +3674,58385,Male,Loyal Customer,51,Business travel,Business,1833,1,1,3,1,3,4,4,4,4,4,4,5,4,5,2,0.0,satisfied +3675,1064,Female,Loyal Customer,31,Personal Travel,Eco,354,4,4,3,1,3,5,1,4,5,5,5,1,5,1,200,201.0,neutral or dissatisfied +3676,539,Female,Loyal Customer,46,Business travel,Business,3437,5,5,5,5,5,4,4,5,5,5,5,5,5,3,58,53.0,satisfied +3677,108488,Male,Loyal Customer,51,Business travel,Eco,570,1,3,5,5,2,1,2,2,1,5,4,2,4,2,0,0.0,neutral or dissatisfied +3678,91318,Female,disloyal Customer,23,Business travel,Business,545,1,3,1,3,4,1,4,4,3,4,3,1,3,4,5,17.0,neutral or dissatisfied +3679,59798,Male,Loyal Customer,28,Business travel,Business,1065,3,3,3,3,4,4,4,4,5,5,5,4,4,4,134,133.0,satisfied +3680,98409,Male,Loyal Customer,28,Personal Travel,Eco,675,4,1,4,4,5,4,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +3681,128849,Female,Loyal Customer,18,Personal Travel,Eco,2586,4,4,4,3,4,1,1,4,3,3,5,1,3,1,248,271.0,neutral or dissatisfied +3682,46113,Male,Loyal Customer,16,Personal Travel,Eco,1085,3,4,3,3,4,3,4,4,4,2,5,3,5,4,0,2.0,neutral or dissatisfied +3683,101976,Male,Loyal Customer,32,Personal Travel,Eco,628,3,1,3,2,5,3,5,5,2,3,3,4,3,5,20,14.0,neutral or dissatisfied +3684,91860,Male,Loyal Customer,58,Personal Travel,Business,1995,4,3,4,4,4,4,3,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +3685,21,Female,Loyal Customer,14,Personal Travel,Eco,853,3,1,3,3,4,3,4,4,1,3,2,4,3,4,12,1.0,neutral or dissatisfied +3686,106477,Female,Loyal Customer,45,Business travel,Business,1624,2,2,2,2,5,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +3687,12456,Male,disloyal Customer,19,Personal Travel,Eco,253,5,4,0,5,3,0,4,3,2,3,2,1,4,3,0,0.0,satisfied +3688,76178,Female,Loyal Customer,30,Business travel,Business,2422,3,3,3,3,4,4,4,4,3,2,4,4,4,4,0,0.0,satisfied +3689,34421,Male,Loyal Customer,13,Business travel,Eco Plus,612,3,4,4,4,3,3,4,3,1,1,4,4,4,3,0,12.0,neutral or dissatisfied +3690,73046,Male,Loyal Customer,43,Personal Travel,Eco,1096,4,3,4,3,2,4,2,2,2,4,4,4,4,2,0,0.0,satisfied +3691,12099,Male,disloyal Customer,26,Business travel,Eco,1034,4,4,4,2,3,4,5,3,4,1,2,1,1,3,64,47.0,satisfied +3692,55761,Male,Loyal Customer,41,Business travel,Business,224,0,0,0,3,2,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +3693,54071,Female,Loyal Customer,52,Business travel,Business,1416,4,4,4,4,5,4,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +3694,121345,Female,Loyal Customer,33,Business travel,Business,430,3,2,2,2,1,3,3,3,3,4,3,4,3,3,3,2.0,neutral or dissatisfied +3695,37791,Male,Loyal Customer,49,Business travel,Eco Plus,1074,4,1,1,1,4,4,4,4,3,4,5,3,2,4,0,0.0,satisfied +3696,7938,Male,disloyal Customer,20,Business travel,Business,594,4,5,4,2,3,4,3,3,5,3,5,5,4,3,0,0.0,satisfied +3697,70504,Male,Loyal Customer,51,Personal Travel,Eco,867,3,2,3,2,4,3,4,4,3,2,2,4,2,4,2,0.0,neutral or dissatisfied +3698,63445,Male,Loyal Customer,30,Personal Travel,Eco,447,3,4,3,3,5,3,5,5,4,3,4,4,4,5,42,27.0,neutral or dissatisfied +3699,41220,Male,Loyal Customer,34,Personal Travel,Eco Plus,1091,0,3,0,4,1,0,2,1,2,5,3,1,3,1,0,2.0,satisfied +3700,127822,Female,Loyal Customer,41,Personal Travel,Eco,1262,5,5,5,3,1,5,1,1,3,3,4,4,5,1,0,0.0,satisfied +3701,59665,Female,Loyal Customer,40,Personal Travel,Eco,854,3,5,3,3,4,3,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +3702,127283,Male,Loyal Customer,7,Personal Travel,Eco,1107,3,2,3,2,3,3,3,3,2,1,2,2,3,3,0,0.0,neutral or dissatisfied +3703,44470,Male,Loyal Customer,23,Personal Travel,Eco,196,0,5,0,1,2,0,2,2,4,1,5,1,5,2,18,13.0,satisfied +3704,24788,Female,Loyal Customer,54,Personal Travel,Eco,528,4,1,4,4,4,4,4,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +3705,39983,Female,Loyal Customer,9,Personal Travel,Eco,1262,3,4,2,4,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +3706,9287,Female,Loyal Customer,9,Personal Travel,Eco,1190,4,4,4,3,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +3707,103092,Female,Loyal Customer,55,Personal Travel,Eco,687,2,4,1,5,2,4,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +3708,33812,Male,Loyal Customer,50,Business travel,Business,1428,3,1,1,1,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +3709,53551,Female,disloyal Customer,48,Business travel,Eco,960,2,2,2,1,3,2,2,3,1,4,5,5,5,3,32,2.0,neutral or dissatisfied +3710,650,Male,Loyal Customer,58,Business travel,Business,3593,4,4,5,4,4,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +3711,62855,Female,disloyal Customer,41,Business travel,Business,2446,1,1,1,3,4,1,4,4,5,5,4,3,4,4,2,0.0,neutral or dissatisfied +3712,49623,Female,Loyal Customer,39,Business travel,Business,89,4,3,3,3,3,4,3,2,2,2,4,2,2,3,0,0.0,neutral or dissatisfied +3713,36792,Female,Loyal Customer,25,Personal Travel,Eco,2611,4,3,4,4,4,1,1,4,3,4,3,1,2,1,53,71.0,neutral or dissatisfied +3714,72954,Male,Loyal Customer,28,Business travel,Business,2136,2,1,1,1,2,2,2,2,3,2,3,2,3,2,23,96.0,neutral or dissatisfied +3715,46059,Male,Loyal Customer,53,Personal Travel,Eco,996,2,5,2,4,2,2,2,2,4,2,5,5,4,2,8,31.0,neutral or dissatisfied +3716,96251,Male,Loyal Customer,15,Personal Travel,Eco,546,3,3,3,2,2,3,4,2,4,1,1,4,3,2,37,37.0,neutral or dissatisfied +3717,125905,Male,Loyal Customer,26,Personal Travel,Eco,861,1,2,1,4,1,4,4,4,5,3,3,4,1,4,158,152.0,neutral or dissatisfied +3718,59768,Female,Loyal Customer,33,Business travel,Business,1987,4,4,4,4,3,4,3,4,4,4,4,2,4,1,1,0.0,neutral or dissatisfied +3719,7936,Female,Loyal Customer,44,Business travel,Business,3555,2,2,5,2,2,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +3720,22735,Female,Loyal Customer,40,Business travel,Eco,147,4,4,4,4,4,4,4,4,4,5,1,4,2,4,0,0.0,satisfied +3721,117739,Male,Loyal Customer,60,Business travel,Business,3123,2,1,1,1,3,4,3,2,2,2,2,4,2,4,3,0.0,neutral or dissatisfied +3722,109989,Male,disloyal Customer,23,Business travel,Business,1165,4,0,4,2,1,4,1,1,3,2,5,4,5,1,79,63.0,satisfied +3723,123755,Female,Loyal Customer,36,Business travel,Business,3394,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,9.0,satisfied +3724,117144,Male,Loyal Customer,63,Personal Travel,Eco,304,2,5,2,3,1,2,1,1,3,5,5,4,5,1,4,0.0,neutral or dissatisfied +3725,69121,Female,Loyal Customer,35,Business travel,Business,1598,1,1,1,1,5,1,4,5,5,5,5,3,5,2,0,0.0,satisfied +3726,25641,Female,Loyal Customer,34,Personal Travel,Eco,526,3,5,3,1,5,3,5,5,4,4,5,5,5,5,8,9.0,neutral or dissatisfied +3727,28277,Male,Loyal Customer,55,Business travel,Business,902,5,5,5,5,3,3,3,2,4,1,5,3,2,3,57,30.0,satisfied +3728,36908,Female,Loyal Customer,55,Personal Travel,Eco,2072,2,5,2,3,4,4,4,5,5,2,1,5,5,4,0,0.0,neutral or dissatisfied +3729,61384,Female,Loyal Customer,12,Business travel,Business,3496,4,4,5,4,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +3730,46209,Male,Loyal Customer,21,Personal Travel,Business,679,2,5,2,4,4,2,4,4,3,3,5,4,4,4,46,58.0,neutral or dissatisfied +3731,72329,Female,Loyal Customer,54,Business travel,Business,3305,5,5,2,5,2,5,5,4,4,4,4,4,4,5,11,41.0,satisfied +3732,12,Female,disloyal Customer,27,Business travel,Business,421,1,2,2,4,1,2,2,1,2,5,4,1,3,1,20,21.0,neutral or dissatisfied +3733,23742,Male,Loyal Customer,40,Business travel,Eco Plus,639,4,2,2,2,4,4,4,4,3,2,4,1,4,4,14,8.0,satisfied +3734,48439,Female,Loyal Customer,32,Business travel,Business,1857,5,5,5,5,3,4,3,3,4,1,5,4,1,3,0,0.0,satisfied +3735,97595,Male,Loyal Customer,57,Business travel,Business,442,2,1,1,1,2,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +3736,77841,Male,Loyal Customer,25,Business travel,Business,1579,3,3,3,3,5,5,5,5,5,5,4,5,5,5,240,280.0,satisfied +3737,49646,Female,Loyal Customer,56,Business travel,Business,1663,5,5,5,5,2,2,4,4,4,4,5,2,4,1,4,11.0,satisfied +3738,61436,Male,Loyal Customer,47,Business travel,Business,2288,2,2,2,2,5,5,5,5,5,4,5,5,5,5,4,0.0,satisfied +3739,90918,Male,disloyal Customer,41,Business travel,Eco,406,2,0,2,5,4,2,4,4,2,4,2,3,4,4,0,0.0,neutral or dissatisfied +3740,77930,Female,Loyal Customer,59,Business travel,Business,2533,1,1,1,1,4,4,4,4,4,4,4,4,4,3,11,23.0,satisfied +3741,61519,Female,Loyal Customer,8,Personal Travel,Eco,2288,2,2,2,4,2,2,2,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +3742,14125,Male,Loyal Customer,45,Business travel,Business,528,1,1,1,1,2,2,1,5,5,5,5,5,5,3,0,10.0,satisfied +3743,88548,Male,Loyal Customer,25,Personal Travel,Eco,515,4,5,4,4,4,4,4,4,5,4,4,4,5,4,0,10.0,satisfied +3744,21217,Male,disloyal Customer,21,Business travel,Eco,153,1,2,1,4,5,1,1,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +3745,123771,Female,disloyal Customer,33,Business travel,Business,544,1,1,1,3,5,1,4,5,1,3,4,4,4,5,0,27.0,neutral or dissatisfied +3746,100496,Male,Loyal Customer,60,Business travel,Eco,759,3,4,4,4,2,3,2,2,3,5,4,4,3,2,29,15.0,neutral or dissatisfied +3747,62932,Male,Loyal Customer,52,Business travel,Business,2565,4,4,4,4,3,4,5,4,4,4,4,5,4,5,9,7.0,satisfied +3748,62892,Male,disloyal Customer,24,Business travel,Business,776,4,0,4,4,2,4,1,2,4,5,5,3,4,2,51,42.0,satisfied +3749,28306,Female,Loyal Customer,28,Business travel,Business,867,3,3,1,1,3,3,3,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +3750,107327,Male,disloyal Customer,23,Business travel,Business,632,4,5,4,4,4,2,2,5,3,5,5,2,3,2,154,141.0,satisfied +3751,67224,Female,Loyal Customer,68,Personal Travel,Eco,1119,3,4,3,4,3,3,2,3,3,3,1,3,3,3,40,31.0,neutral or dissatisfied +3752,24722,Male,Loyal Customer,38,Business travel,Business,3464,1,0,0,3,1,4,3,5,5,0,5,2,5,1,0,0.0,neutral or dissatisfied +3753,35340,Female,Loyal Customer,54,Business travel,Business,1074,3,3,5,3,1,3,2,3,3,3,3,2,3,3,0,3.0,neutral or dissatisfied +3754,19399,Male,Loyal Customer,42,Business travel,Eco,261,4,2,2,2,4,4,4,4,1,4,3,2,4,4,0,0.0,satisfied +3755,27245,Male,Loyal Customer,33,Business travel,Eco Plus,1024,0,0,0,2,5,0,5,5,5,2,4,5,1,5,0,0.0,satisfied +3756,2354,Female,Loyal Customer,37,Business travel,Business,925,1,1,3,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +3757,70541,Male,Loyal Customer,44,Business travel,Business,1258,5,5,5,5,2,4,5,5,5,5,5,3,5,5,27,26.0,satisfied +3758,60829,Female,Loyal Customer,56,Business travel,Business,680,4,4,4,4,2,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +3759,22449,Female,Loyal Customer,64,Personal Travel,Eco,238,3,4,3,2,3,5,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +3760,38069,Male,Loyal Customer,51,Business travel,Business,1237,3,3,3,3,4,4,3,3,3,3,3,2,3,1,13,0.0,neutral or dissatisfied +3761,102722,Male,Loyal Customer,17,Personal Travel,Eco,255,5,2,5,2,5,5,5,5,1,3,3,3,3,5,0,0.0,satisfied +3762,113978,Male,Loyal Customer,24,Business travel,Business,1750,3,3,3,3,5,4,5,5,3,4,3,5,5,5,1,2.0,satisfied +3763,54658,Female,disloyal Customer,22,Business travel,Eco,854,4,4,4,3,1,4,1,1,3,4,1,5,5,1,6,0.0,satisfied +3764,91396,Male,Loyal Customer,22,Business travel,Eco,2342,2,3,3,3,2,2,4,2,1,2,2,1,4,2,0,5.0,neutral or dissatisfied +3765,67987,Male,Loyal Customer,63,Business travel,Eco Plus,771,3,4,4,4,3,3,3,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +3766,82630,Male,Loyal Customer,34,Personal Travel,Eco,528,2,5,2,2,2,2,4,2,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +3767,118251,Female,Loyal Customer,51,Business travel,Eco,1788,4,4,4,4,1,3,3,4,4,4,4,1,4,2,0,6.0,neutral or dissatisfied +3768,35003,Male,Loyal Customer,7,Personal Travel,Eco,1182,3,5,2,2,1,2,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +3769,13088,Female,Loyal Customer,23,Business travel,Business,2930,4,4,2,4,5,5,5,5,2,2,5,4,1,5,10,0.0,satisfied +3770,118791,Female,Loyal Customer,49,Personal Travel,Eco,325,2,2,2,3,2,3,3,2,2,2,1,2,2,4,9,8.0,neutral or dissatisfied +3771,43890,Male,Loyal Customer,32,Business travel,Eco,144,4,1,1,1,4,5,4,4,2,3,1,4,3,4,0,10.0,satisfied +3772,86086,Female,disloyal Customer,22,Business travel,Eco,164,2,0,2,4,3,2,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +3773,124485,Male,Loyal Customer,42,Business travel,Business,3847,2,2,2,2,5,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +3774,111586,Male,Loyal Customer,16,Personal Travel,Eco,883,3,4,3,3,1,3,1,1,5,3,4,2,3,1,0,0.0,neutral or dissatisfied +3775,51688,Female,Loyal Customer,47,Business travel,Business,3305,0,0,0,4,5,3,4,2,2,2,2,1,2,2,0,0.0,satisfied +3776,39237,Male,Loyal Customer,55,Business travel,Business,67,5,5,5,5,1,2,1,5,5,5,5,5,5,2,10,12.0,satisfied +3777,118130,Male,Loyal Customer,52,Business travel,Business,1488,5,5,4,5,2,4,4,5,5,5,5,3,5,3,21,2.0,satisfied +3778,58786,Female,Loyal Customer,29,Business travel,Eco,1012,2,5,5,5,2,2,2,1,2,2,2,2,4,2,156,157.0,neutral or dissatisfied +3779,77373,Male,Loyal Customer,22,Business travel,Business,1755,2,4,4,4,2,2,2,2,2,2,4,1,3,2,10,13.0,neutral or dissatisfied +3780,114841,Male,Loyal Customer,58,Business travel,Business,446,1,1,1,1,3,4,5,4,4,4,4,4,4,5,76,74.0,satisfied +3781,111427,Male,Loyal Customer,27,Personal Travel,Eco,896,5,4,5,3,4,5,1,4,4,3,4,5,4,4,0,0.0,satisfied +3782,15563,Male,disloyal Customer,23,Business travel,Eco,296,3,5,3,5,3,3,1,3,5,2,4,3,1,3,0,0.0,neutral or dissatisfied +3783,68125,Male,Loyal Customer,38,Personal Travel,Eco,813,0,1,0,4,5,0,2,5,4,2,3,2,4,5,0,1.0,satisfied +3784,107010,Male,Loyal Customer,44,Business travel,Business,2456,3,3,3,3,2,4,5,3,3,3,3,3,3,5,37,48.0,satisfied +3785,122336,Male,Loyal Customer,24,Personal Travel,Eco Plus,544,2,1,2,4,5,2,2,5,2,5,3,2,4,5,0,0.0,neutral or dissatisfied +3786,58891,Male,Loyal Customer,33,Business travel,Business,3549,2,2,2,2,5,5,5,5,3,3,4,3,5,5,6,0.0,satisfied +3787,20484,Male,disloyal Customer,43,Business travel,Eco,139,3,0,3,3,4,3,4,4,5,3,3,2,5,4,0,0.0,neutral or dissatisfied +3788,60960,Female,Loyal Customer,53,Business travel,Business,2163,1,1,1,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +3789,91237,Male,Loyal Customer,41,Personal Travel,Eco,250,1,4,1,4,1,1,1,1,4,2,5,3,4,1,11,26.0,neutral or dissatisfied +3790,81234,Male,Loyal Customer,67,Personal Travel,Eco,449,2,5,4,3,2,4,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +3791,45960,Male,Loyal Customer,16,Personal Travel,Eco Plus,913,3,5,2,2,2,2,2,2,3,4,3,2,5,2,0,0.0,neutral or dissatisfied +3792,103344,Male,Loyal Customer,40,Personal Travel,Eco,1139,2,5,2,1,1,2,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +3793,31490,Female,Loyal Customer,42,Business travel,Business,853,3,3,3,3,1,1,5,3,3,2,3,5,3,5,5,7.0,satisfied +3794,6088,Female,disloyal Customer,40,Business travel,Business,691,3,3,3,4,1,3,1,1,2,5,4,4,3,1,37,65.0,neutral or dissatisfied +3795,11751,Female,Loyal Customer,32,Business travel,Business,1932,2,4,4,4,2,2,2,2,4,1,4,1,3,2,27,27.0,neutral or dissatisfied +3796,108196,Female,Loyal Customer,58,Business travel,Eco Plus,766,5,2,2,2,3,2,3,5,5,5,5,4,5,3,13,7.0,satisfied +3797,31280,Female,disloyal Customer,23,Business travel,Eco,133,3,2,3,4,1,3,1,1,2,4,3,2,4,1,0,0.0,neutral or dissatisfied +3798,118980,Female,Loyal Customer,39,Personal Travel,Eco Plus,570,1,2,2,4,2,2,2,2,4,5,4,2,4,2,14,15.0,neutral or dissatisfied +3799,117968,Female,Loyal Customer,25,Personal Travel,Eco,365,2,5,3,2,4,3,4,4,3,3,4,3,4,4,2,0.0,neutral or dissatisfied +3800,1789,Male,Loyal Customer,52,Business travel,Eco,500,1,2,2,2,1,1,1,1,4,5,3,1,4,1,16,13.0,neutral or dissatisfied +3801,77556,Male,Loyal Customer,44,Personal Travel,Eco,986,5,4,5,5,5,5,5,5,3,3,5,4,5,5,16,5.0,satisfied +3802,52636,Male,disloyal Customer,36,Business travel,Eco,160,3,3,3,3,2,3,1,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +3803,117093,Male,Loyal Customer,56,Business travel,Business,2201,5,5,5,5,1,1,5,5,5,5,5,2,5,1,0,1.0,satisfied +3804,117155,Female,Loyal Customer,56,Personal Travel,Eco,304,3,3,3,4,2,3,4,2,2,3,2,2,2,2,3,0.0,neutral or dissatisfied +3805,12142,Male,Loyal Customer,36,Business travel,Business,2028,3,3,3,3,1,4,2,4,4,4,4,5,4,4,43,15.0,satisfied +3806,49591,Male,Loyal Customer,38,Business travel,Business,2734,4,4,4,4,4,3,1,4,4,4,4,2,4,1,0,4.0,satisfied +3807,38417,Female,Loyal Customer,38,Business travel,Business,2532,1,1,1,1,1,2,3,5,5,5,5,3,5,5,0,0.0,satisfied +3808,73472,Female,Loyal Customer,19,Personal Travel,Eco,1012,1,2,2,4,1,2,1,1,1,3,4,2,3,1,0,5.0,neutral or dissatisfied +3809,72874,Male,Loyal Customer,55,Business travel,Business,3596,1,1,4,1,3,4,5,5,5,5,5,4,5,5,1,2.0,satisfied +3810,98898,Female,Loyal Customer,59,Business travel,Business,169,3,1,1,1,1,3,1,3,1,3,3,1,3,1,169,153.0,neutral or dissatisfied +3811,3951,Male,Loyal Customer,28,Business travel,Business,1648,3,3,3,3,3,3,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +3812,34060,Female,Loyal Customer,43,Business travel,Business,1674,2,2,2,2,2,4,2,5,5,5,5,4,5,2,0,0.0,satisfied +3813,62554,Male,Loyal Customer,30,Business travel,Business,1846,4,1,1,1,4,4,4,4,2,2,4,1,3,4,2,0.0,neutral or dissatisfied +3814,33445,Female,Loyal Customer,58,Personal Travel,Eco,2349,2,1,2,2,1,2,3,3,3,2,3,2,3,2,0,26.0,neutral or dissatisfied +3815,72538,Male,Loyal Customer,37,Business travel,Business,985,3,3,3,3,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +3816,43661,Female,Loyal Customer,27,Business travel,Business,695,1,4,4,4,1,1,1,1,2,5,2,1,3,1,0,17.0,neutral or dissatisfied +3817,34347,Male,Loyal Customer,57,Business travel,Eco,541,4,1,1,1,3,4,3,3,1,1,4,2,2,3,0,0.0,satisfied +3818,75026,Female,Loyal Customer,34,Business travel,Business,3540,3,3,3,3,3,4,3,5,5,5,5,5,5,2,23,30.0,satisfied +3819,62132,Male,Loyal Customer,27,Business travel,Business,2434,4,4,4,4,4,4,4,4,3,5,5,3,4,4,4,0.0,satisfied +3820,57843,Female,Loyal Customer,32,Personal Travel,Eco,1491,2,4,2,1,5,2,5,5,5,5,4,3,5,5,8,0.0,neutral or dissatisfied +3821,91779,Male,Loyal Customer,40,Personal Travel,Eco,626,2,1,2,3,5,2,5,5,4,2,3,4,3,5,0,0.0,neutral or dissatisfied +3822,79756,Female,Loyal Customer,43,Business travel,Business,1076,5,5,3,5,5,4,5,5,5,5,5,3,5,5,8,57.0,satisfied +3823,28560,Male,disloyal Customer,41,Business travel,Business,2640,3,3,3,4,2,3,2,2,3,3,4,2,4,2,23,0.0,neutral or dissatisfied +3824,96755,Female,Loyal Customer,48,Business travel,Business,957,3,3,3,3,4,4,5,4,4,4,4,3,4,5,13,2.0,satisfied +3825,2833,Male,Loyal Customer,43,Business travel,Business,3159,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,5.0,satisfied +3826,70885,Male,disloyal Customer,55,Business travel,Business,1721,3,4,4,4,4,3,4,4,4,4,4,3,4,4,29,31.0,neutral or dissatisfied +3827,112859,Male,Loyal Customer,49,Business travel,Business,1523,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +3828,5335,Male,Loyal Customer,46,Business travel,Business,2749,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +3829,21027,Male,disloyal Customer,40,Business travel,Eco,152,4,0,4,4,4,2,4,4,4,4,1,4,3,4,138,130.0,satisfied +3830,100354,Female,Loyal Customer,11,Personal Travel,Eco,1034,2,5,3,1,4,3,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +3831,80311,Male,disloyal Customer,34,Business travel,Eco,746,2,2,2,4,4,2,4,4,2,2,3,2,4,4,1,18.0,neutral or dissatisfied +3832,90904,Male,Loyal Customer,48,Business travel,Eco,545,2,2,1,2,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +3833,65590,Female,Loyal Customer,42,Business travel,Business,175,0,4,0,2,5,5,5,3,3,5,5,5,3,5,98,140.0,satisfied +3834,95678,Male,disloyal Customer,42,Business travel,Business,237,1,1,1,4,2,1,2,2,4,4,5,5,5,2,5,8.0,neutral or dissatisfied +3835,123479,Female,Loyal Customer,44,Business travel,Business,2125,4,4,4,4,4,3,5,5,5,4,5,3,5,3,0,0.0,satisfied +3836,40730,Male,Loyal Customer,27,Business travel,Eco,590,4,1,1,1,4,4,4,4,5,4,3,5,1,4,0,0.0,satisfied +3837,127220,Female,Loyal Customer,53,Personal Travel,Eco Plus,621,2,3,2,2,3,5,4,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +3838,44391,Female,Loyal Customer,35,Business travel,Business,3950,1,4,4,4,4,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +3839,61361,Male,Loyal Customer,40,Business travel,Business,2405,4,5,2,2,4,3,4,4,4,3,4,1,4,3,4,11.0,neutral or dissatisfied +3840,40552,Female,Loyal Customer,47,Business travel,Business,517,2,2,2,2,5,4,5,4,4,4,4,3,4,1,29,12.0,satisfied +3841,14634,Female,Loyal Customer,34,Business travel,Business,363,3,4,4,4,2,3,3,3,3,3,3,2,3,2,84,112.0,neutral or dissatisfied +3842,19067,Female,Loyal Customer,48,Business travel,Eco,642,1,3,3,3,2,3,4,1,1,1,1,3,1,3,71,61.0,neutral or dissatisfied +3843,71359,Female,disloyal Customer,36,Business travel,Business,258,1,1,1,4,2,1,2,2,4,3,5,4,5,2,8,6.0,neutral or dissatisfied +3844,99524,Female,Loyal Customer,28,Business travel,Business,528,4,4,4,4,5,5,5,5,4,3,5,4,4,5,0,18.0,satisfied +3845,3059,Male,Loyal Customer,22,Personal Travel,Eco,340,1,1,1,2,3,1,3,3,4,3,2,1,2,3,0,0.0,neutral or dissatisfied +3846,111501,Male,disloyal Customer,44,Business travel,Business,391,1,1,1,5,5,1,5,5,5,4,4,4,4,5,1,0.0,neutral or dissatisfied +3847,18671,Female,Loyal Customer,48,Personal Travel,Eco,262,2,3,2,3,4,4,3,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +3848,78545,Female,Loyal Customer,44,Personal Travel,Eco,666,2,0,2,3,5,4,4,1,1,2,1,3,1,5,22,22.0,neutral or dissatisfied +3849,25276,Male,Loyal Customer,22,Personal Travel,Eco,425,3,2,3,2,5,3,5,5,4,1,1,4,1,5,0,0.0,neutral or dissatisfied +3850,60402,Female,Loyal Customer,42,Personal Travel,Eco,1476,4,4,4,4,2,4,3,5,5,4,2,1,5,4,31,26.0,neutral or dissatisfied +3851,73665,Male,disloyal Customer,26,Business travel,Business,192,3,0,3,3,4,3,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +3852,21344,Female,Loyal Customer,62,Business travel,Business,674,1,4,1,1,1,2,3,4,4,4,4,2,4,3,0,0.0,satisfied +3853,60919,Male,disloyal Customer,32,Business travel,Business,888,2,2,2,3,3,2,3,3,3,2,5,5,4,3,7,1.0,neutral or dissatisfied +3854,91059,Female,Loyal Customer,25,Personal Travel,Eco,581,0,4,0,1,3,0,2,3,4,4,4,5,5,3,2,0.0,satisfied +3855,96864,Female,Loyal Customer,36,Business travel,Eco,381,1,4,4,4,1,1,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +3856,127503,Female,Loyal Customer,23,Personal Travel,Eco,2075,3,5,3,5,1,3,1,1,3,3,5,2,4,1,5,0.0,neutral or dissatisfied +3857,26145,Male,Loyal Customer,47,Business travel,Eco,581,2,1,1,1,1,2,1,1,1,4,2,5,3,1,14,4.0,satisfied +3858,43419,Male,Loyal Customer,49,Business travel,Eco Plus,531,5,4,4,4,3,5,3,3,3,1,2,4,5,3,0,0.0,satisfied +3859,57784,Male,Loyal Customer,61,Personal Travel,Eco,2611,2,4,2,2,2,5,5,2,3,3,1,5,4,5,0,43.0,neutral or dissatisfied +3860,67645,Male,disloyal Customer,23,Business travel,Eco,1188,1,1,1,4,2,1,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +3861,11474,Female,Loyal Customer,34,Business travel,Eco Plus,201,2,2,4,4,2,2,2,2,3,4,2,2,2,2,2,0.0,neutral or dissatisfied +3862,42692,Female,Loyal Customer,65,Personal Travel,Eco,627,0,4,1,1,3,5,5,3,3,1,4,5,3,4,0,0.0,satisfied +3863,76324,Male,Loyal Customer,9,Personal Travel,Eco,2182,4,1,4,4,4,4,4,4,1,1,3,2,3,4,0,0.0,neutral or dissatisfied +3864,25512,Male,Loyal Customer,40,Business travel,Business,2049,4,4,4,4,1,1,1,4,4,4,4,4,4,2,2,0.0,satisfied +3865,51228,Female,Loyal Customer,57,Business travel,Eco Plus,156,5,3,3,3,4,3,4,5,5,5,5,3,5,2,5,25.0,satisfied +3866,78196,Male,Loyal Customer,53,Business travel,Business,3761,2,2,3,2,4,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +3867,98214,Female,Loyal Customer,50,Business travel,Business,3135,2,2,2,2,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +3868,30534,Male,Loyal Customer,36,Personal Travel,Eco,683,4,2,3,4,2,3,2,2,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +3869,88995,Female,Loyal Customer,68,Business travel,Eco Plus,1199,1,4,4,4,3,3,2,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +3870,74289,Female,Loyal Customer,23,Business travel,Eco,2288,2,4,4,4,2,2,3,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +3871,2140,Female,Loyal Customer,69,Personal Travel,Eco,431,4,4,4,4,5,4,5,2,2,4,2,3,2,5,0,0.0,satisfied +3872,29579,Male,Loyal Customer,25,Business travel,Business,1448,1,1,1,1,4,4,4,4,5,5,1,2,1,4,0,0.0,satisfied +3873,52900,Female,Loyal Customer,46,Business travel,Eco Plus,1024,3,1,1,1,2,2,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +3874,105595,Female,Loyal Customer,40,Business travel,Business,2556,1,1,1,1,5,4,5,5,5,4,5,3,5,3,4,7.0,satisfied +3875,102424,Male,Loyal Customer,48,Personal Travel,Eco,386,1,4,2,4,4,2,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +3876,71057,Female,Loyal Customer,37,Business travel,Eco,402,4,2,2,2,4,4,4,4,1,1,1,3,2,4,73,87.0,neutral or dissatisfied +3877,72847,Female,Loyal Customer,69,Personal Travel,Eco Plus,1013,5,4,5,2,5,5,5,1,1,4,1,5,1,3,0,0.0,satisfied +3878,8411,Female,Loyal Customer,44,Business travel,Business,862,2,5,5,5,3,4,4,2,2,1,2,2,2,3,0,44.0,neutral or dissatisfied +3879,57972,Male,Loyal Customer,47,Business travel,Business,420,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +3880,108908,Female,Loyal Customer,35,Business travel,Eco,1183,2,1,1,1,2,3,2,2,4,2,3,4,3,2,49,58.0,neutral or dissatisfied +3881,41161,Female,Loyal Customer,51,Personal Travel,Eco,667,1,5,1,1,3,5,4,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +3882,57722,Female,Loyal Customer,29,Business travel,Business,1754,3,3,3,3,4,4,4,4,4,2,3,3,5,4,0,0.0,satisfied +3883,62595,Female,Loyal Customer,39,Business travel,Eco,244,5,1,1,1,5,5,5,5,4,4,5,5,4,5,0,1.0,satisfied +3884,84728,Female,Loyal Customer,48,Business travel,Business,547,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +3885,64988,Female,Loyal Customer,53,Business travel,Business,3083,0,0,0,5,5,4,5,2,2,2,2,1,2,1,0,0.0,satisfied +3886,2340,Female,Loyal Customer,59,Business travel,Business,2721,3,3,3,3,2,4,4,5,5,5,5,5,5,3,15,68.0,satisfied +3887,23140,Male,disloyal Customer,21,Business travel,Eco,223,3,0,3,1,4,3,5,4,1,1,2,5,4,4,0,0.0,neutral or dissatisfied +3888,11812,Male,Loyal Customer,41,Business travel,Business,1949,1,1,4,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +3889,78591,Male,Loyal Customer,30,Business travel,Business,2894,3,3,3,3,3,3,3,3,5,5,4,3,5,3,8,5.0,satisfied +3890,13828,Female,Loyal Customer,49,Business travel,Eco,594,3,4,4,4,4,4,3,3,3,3,3,4,3,2,89,77.0,neutral or dissatisfied +3891,24726,Male,Loyal Customer,59,Personal Travel,Eco,406,3,5,4,1,1,4,1,1,3,5,4,1,5,1,0,18.0,neutral or dissatisfied +3892,98367,Male,Loyal Customer,7,Personal Travel,Eco,1046,3,3,3,4,1,3,1,1,3,5,4,4,4,1,65,65.0,neutral or dissatisfied +3893,61652,Male,Loyal Customer,30,Business travel,Business,1379,4,2,2,2,4,4,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +3894,119738,Male,Loyal Customer,40,Personal Travel,Eco,1303,3,3,3,3,2,3,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +3895,53942,Male,Loyal Customer,44,Personal Travel,Eco,2007,2,4,2,2,4,2,4,4,5,2,3,3,4,4,17,9.0,neutral or dissatisfied +3896,103749,Female,Loyal Customer,52,Business travel,Business,2960,4,4,4,4,5,5,5,5,5,5,5,4,5,4,0,6.0,satisfied +3897,114407,Female,Loyal Customer,33,Business travel,Business,3081,4,4,4,4,5,4,4,4,4,4,4,4,4,5,15,8.0,satisfied +3898,8237,Male,Loyal Customer,61,Personal Travel,Eco,530,4,2,4,3,4,4,3,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +3899,30578,Male,Loyal Customer,49,Business travel,Business,628,4,4,4,4,5,3,3,4,4,3,4,2,4,4,51,43.0,neutral or dissatisfied +3900,94452,Male,Loyal Customer,45,Business travel,Business,239,2,2,4,2,2,5,5,4,4,4,4,4,4,4,3,0.0,satisfied +3901,25267,Male,Loyal Customer,46,Business travel,Eco,425,1,2,2,2,1,1,1,1,4,5,4,2,3,1,0,0.0,neutral or dissatisfied +3902,103225,Female,Loyal Customer,10,Personal Travel,Eco,462,2,5,2,2,3,2,3,3,4,3,4,5,2,3,22,24.0,neutral or dissatisfied +3903,73407,Male,disloyal Customer,47,Business travel,Eco,720,3,3,3,3,2,3,5,2,4,2,5,3,3,2,0,7.0,neutral or dissatisfied +3904,107214,Female,disloyal Customer,33,Business travel,Eco Plus,402,2,2,2,3,5,2,5,5,4,5,3,3,3,5,0,0.0,neutral or dissatisfied +3905,61424,Male,Loyal Customer,49,Business travel,Business,2253,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +3906,13325,Female,Loyal Customer,52,Personal Travel,Business,748,3,4,3,4,3,4,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +3907,69649,Female,Loyal Customer,51,Business travel,Eco,569,2,2,2,2,2,2,2,4,2,4,4,2,2,2,249,257.0,neutral or dissatisfied +3908,43125,Male,Loyal Customer,22,Business travel,Eco Plus,236,5,4,4,4,5,5,5,5,5,2,1,5,5,5,3,0.0,satisfied +3909,95804,Male,disloyal Customer,54,Business travel,Business,1050,2,2,2,3,1,2,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +3910,10122,Female,Loyal Customer,30,Business travel,Business,1983,3,3,5,3,3,3,3,3,3,4,5,5,5,3,28,24.0,satisfied +3911,11824,Female,disloyal Customer,11,Business travel,Eco,986,4,4,4,4,4,4,4,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +3912,87064,Male,Loyal Customer,27,Business travel,Business,3816,1,1,3,1,5,5,5,5,4,4,4,4,5,5,13,2.0,satisfied +3913,76587,Male,disloyal Customer,25,Business travel,Business,516,3,4,3,1,4,3,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +3914,118917,Female,Loyal Customer,42,Personal Travel,Eco,587,2,5,2,1,3,5,5,4,4,2,5,3,4,5,13,24.0,neutral or dissatisfied +3915,109592,Female,Loyal Customer,42,Business travel,Business,951,4,4,4,4,5,4,4,5,5,5,5,3,5,4,63,51.0,satisfied +3916,119763,Male,Loyal Customer,60,Personal Travel,Eco Plus,1430,1,1,1,2,3,1,3,3,4,3,2,1,2,3,4,26.0,neutral or dissatisfied +3917,109503,Male,Loyal Customer,47,Business travel,Business,861,2,2,2,2,3,4,5,3,3,4,3,5,3,3,13,15.0,satisfied +3918,124613,Male,Loyal Customer,46,Business travel,Business,1671,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +3919,68055,Male,disloyal Customer,28,Business travel,Business,868,4,4,4,5,3,4,3,3,5,5,5,3,4,3,0,0.0,satisfied +3920,113074,Male,Loyal Customer,44,Business travel,Business,2858,2,1,2,2,4,4,5,4,4,4,4,3,4,4,0,4.0,satisfied +3921,74417,Female,disloyal Customer,23,Business travel,Eco,1242,4,4,4,2,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +3922,109918,Male,Loyal Customer,61,Personal Travel,Eco,1033,3,5,4,3,3,4,3,3,4,5,5,4,5,3,1,0.0,neutral or dissatisfied +3923,50853,Female,Loyal Customer,39,Personal Travel,Eco,250,4,4,0,4,1,0,1,1,4,2,4,4,4,1,21,11.0,neutral or dissatisfied +3924,38947,Male,Loyal Customer,64,Business travel,Eco Plus,320,1,3,5,5,1,1,1,1,4,3,4,2,3,1,0,14.0,neutral or dissatisfied +3925,49701,Male,Loyal Customer,36,Business travel,Business,1538,0,1,1,4,3,3,4,3,3,3,3,4,3,4,0,2.0,satisfied +3926,26725,Female,Loyal Customer,31,Business travel,Eco Plus,515,5,5,5,5,5,5,5,5,1,4,5,2,3,5,0,3.0,satisfied +3927,27417,Male,Loyal Customer,51,Business travel,Business,3898,4,4,1,4,5,5,4,5,5,4,5,3,5,3,2,0.0,satisfied +3928,108655,Male,Loyal Customer,29,Business travel,Business,1747,3,3,3,3,3,3,3,3,1,1,2,3,3,3,11,14.0,neutral or dissatisfied +3929,66801,Male,Loyal Customer,39,Business travel,Business,2165,3,4,4,4,5,3,4,3,3,3,3,1,3,1,66,68.0,neutral or dissatisfied +3930,64962,Female,Loyal Customer,54,Business travel,Business,247,2,2,2,2,2,5,5,4,4,4,4,3,4,1,24,15.0,satisfied +3931,33271,Male,Loyal Customer,34,Personal Travel,Eco Plus,101,1,3,1,2,5,1,5,5,4,2,2,4,4,5,0,0.0,neutral or dissatisfied +3932,110467,Male,Loyal Customer,54,Personal Travel,Eco,883,3,4,3,3,1,3,1,1,4,4,3,4,4,1,55,28.0,neutral or dissatisfied +3933,84029,Female,Loyal Customer,63,Personal Travel,Eco Plus,321,2,3,2,2,3,1,4,2,2,2,2,2,2,4,3,0.0,neutral or dissatisfied +3934,96885,Male,Loyal Customer,42,Personal Travel,Eco,928,1,3,1,4,3,1,2,3,3,3,3,4,3,3,14,17.0,neutral or dissatisfied +3935,82038,Female,Loyal Customer,39,Personal Travel,Eco,1454,1,4,1,2,4,1,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +3936,80923,Female,Loyal Customer,52,Business travel,Business,341,0,0,0,1,4,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +3937,61998,Male,Loyal Customer,47,Business travel,Business,2475,5,5,5,5,2,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +3938,17930,Female,Loyal Customer,41,Business travel,Eco Plus,789,4,1,1,1,5,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +3939,108302,Male,disloyal Customer,23,Business travel,Business,1434,5,0,5,1,3,5,3,3,3,2,5,4,5,3,17,20.0,satisfied +3940,61899,Female,Loyal Customer,40,Personal Travel,Business,550,4,1,4,3,5,4,4,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +3941,3895,Female,Loyal Customer,57,Business travel,Business,213,2,4,4,4,2,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +3942,111147,Female,Loyal Customer,49,Business travel,Eco,780,5,5,5,5,3,1,4,5,5,5,5,4,5,4,28,5.0,satisfied +3943,99960,Female,Loyal Customer,56,Business travel,Business,888,2,2,2,2,2,5,4,5,5,5,5,4,5,3,17,0.0,satisfied +3944,24647,Female,Loyal Customer,20,Business travel,Eco Plus,666,4,1,1,1,4,5,3,4,4,4,1,5,4,4,0,0.0,satisfied +3945,43033,Female,Loyal Customer,33,Business travel,Eco,192,1,5,3,5,1,1,1,1,3,5,3,3,3,1,0,0.0,neutral or dissatisfied +3946,115339,Female,Loyal Customer,67,Business travel,Eco,308,2,5,2,2,1,4,3,2,2,2,2,2,2,1,0,6.0,neutral or dissatisfied +3947,78334,Female,disloyal Customer,38,Business travel,Business,1547,5,5,5,2,3,5,3,3,5,5,4,4,5,3,9,3.0,satisfied +3948,1580,Female,Loyal Customer,64,Business travel,Business,2659,1,5,5,5,2,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +3949,111232,Male,Loyal Customer,10,Personal Travel,Eco,1546,2,5,2,2,1,2,1,1,3,5,3,4,4,1,19,28.0,neutral or dissatisfied +3950,65990,Male,Loyal Customer,27,Business travel,Eco Plus,1372,3,2,1,1,3,3,3,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +3951,38728,Male,Loyal Customer,16,Personal Travel,Business,354,4,5,4,2,3,4,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +3952,57813,Female,disloyal Customer,66,Personal Travel,Business,622,3,3,3,3,2,3,2,2,1,5,3,3,1,2,13,24.0,neutral or dissatisfied +3953,126895,Male,Loyal Customer,50,Business travel,Business,2296,2,2,2,2,3,3,3,4,4,4,4,3,3,3,145,117.0,satisfied +3954,90338,Male,Loyal Customer,34,Business travel,Business,3260,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +3955,123194,Female,Loyal Customer,66,Personal Travel,Eco,600,3,1,3,4,1,3,4,5,5,3,5,4,5,3,2,9.0,neutral or dissatisfied +3956,42933,Male,Loyal Customer,46,Business travel,Business,259,1,1,1,1,3,5,5,4,4,4,4,3,4,3,13,3.0,satisfied +3957,31227,Female,Loyal Customer,18,Personal Travel,Eco Plus,628,1,2,1,4,1,1,1,1,4,2,4,3,3,1,46,56.0,neutral or dissatisfied +3958,4539,Male,disloyal Customer,29,Business travel,Business,719,2,2,2,1,3,2,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +3959,52270,Male,Loyal Customer,36,Business travel,Eco,509,4,5,5,5,4,4,4,4,4,3,4,3,3,4,0,2.0,neutral or dissatisfied +3960,49454,Female,Loyal Customer,63,Business travel,Business,3472,3,3,3,3,3,5,1,5,5,5,5,3,5,3,0,6.0,satisfied +3961,62870,Male,Loyal Customer,52,Business travel,Eco,2218,4,1,1,1,4,4,4,4,3,3,5,4,1,4,4,0.0,satisfied +3962,5039,Male,Loyal Customer,53,Business travel,Business,235,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,13.0,satisfied +3963,70170,Male,Loyal Customer,25,Personal Travel,Eco Plus,460,2,5,2,4,1,2,1,1,5,4,5,5,5,1,19,8.0,neutral or dissatisfied +3964,32932,Male,Loyal Customer,68,Personal Travel,Eco,216,2,4,2,4,4,2,4,4,5,3,4,4,4,4,4,8.0,neutral or dissatisfied +3965,100657,Male,Loyal Customer,33,Business travel,Business,2489,5,5,5,5,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +3966,67341,Male,Loyal Customer,39,Business travel,Eco,1071,5,3,3,3,5,5,5,5,3,5,1,5,5,5,0,0.0,satisfied +3967,123925,Male,Loyal Customer,54,Personal Travel,Eco,541,2,5,2,5,4,2,4,4,5,4,1,1,4,4,0,0.0,neutral or dissatisfied +3968,98107,Female,disloyal Customer,21,Business travel,Eco,472,1,5,0,2,1,0,1,1,3,4,5,5,5,1,76,70.0,neutral or dissatisfied +3969,80178,Male,Loyal Customer,39,Personal Travel,Eco,2475,4,4,4,3,4,4,4,4,5,4,4,4,3,4,0,0.0,neutral or dissatisfied +3970,82104,Male,Loyal Customer,11,Personal Travel,Eco,1276,1,2,1,4,3,1,3,3,4,2,3,2,4,3,0,0.0,neutral or dissatisfied +3971,51107,Female,Loyal Customer,15,Personal Travel,Eco,250,2,5,0,3,3,0,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +3972,113997,Male,Loyal Customer,39,Business travel,Eco,228,4,4,2,4,4,4,4,4,1,5,4,5,5,4,0,0.0,satisfied +3973,22265,Male,Loyal Customer,33,Business travel,Business,83,0,5,0,1,3,3,3,3,5,4,5,1,3,3,0,0.0,satisfied +3974,61180,Female,Loyal Customer,32,Business travel,Business,853,2,2,2,2,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +3975,4172,Male,Loyal Customer,65,Personal Travel,Eco,427,3,5,3,3,4,3,4,4,2,1,5,1,1,4,20,22.0,neutral or dissatisfied +3976,110314,Male,Loyal Customer,36,Business travel,Business,2041,5,5,5,5,4,4,4,5,5,5,5,4,5,3,0,1.0,satisfied +3977,116157,Male,Loyal Customer,29,Personal Travel,Eco,371,3,3,3,4,2,3,2,2,2,4,3,4,4,2,42,34.0,neutral or dissatisfied +3978,21331,Female,Loyal Customer,25,Business travel,Business,674,5,5,5,5,4,4,4,4,1,5,4,5,5,4,9,4.0,satisfied +3979,10810,Female,disloyal Customer,38,Business travel,Business,429,1,1,1,5,2,1,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +3980,21369,Male,disloyal Customer,28,Business travel,Eco,554,3,0,2,2,4,2,4,4,5,1,2,5,1,4,0,0.0,neutral or dissatisfied +3981,108663,Male,Loyal Customer,29,Business travel,Eco Plus,1747,2,4,4,4,2,2,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +3982,7444,Female,Loyal Customer,39,Personal Travel,Eco,522,3,4,3,4,4,3,3,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +3983,84330,Female,Loyal Customer,31,Business travel,Business,606,3,5,3,3,5,5,5,5,3,3,5,3,4,5,1,0.0,satisfied +3984,87354,Female,Loyal Customer,44,Business travel,Business,425,4,1,4,4,5,4,4,4,4,5,4,4,4,5,94,89.0,satisfied +3985,7019,Male,Loyal Customer,25,Personal Travel,Eco,299,3,4,3,3,2,3,2,2,3,5,5,4,5,2,91,92.0,neutral or dissatisfied +3986,55390,Female,Loyal Customer,31,Personal Travel,Eco,413,4,5,4,1,1,4,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +3987,23836,Male,Loyal Customer,31,Business travel,Business,705,2,2,2,2,5,5,5,5,4,4,2,3,1,5,0,0.0,satisfied +3988,63999,Female,Loyal Customer,19,Business travel,Business,1575,4,4,4,4,3,3,3,3,5,5,4,5,5,3,10,0.0,satisfied +3989,118676,Female,Loyal Customer,46,Business travel,Business,3703,2,3,3,3,2,4,3,1,1,1,2,3,1,3,37,42.0,neutral or dissatisfied +3990,73603,Male,disloyal Customer,21,Business travel,Eco,204,5,4,4,2,1,4,1,1,5,2,5,4,4,1,0,0.0,satisfied +3991,72150,Male,Loyal Customer,11,Personal Travel,Eco,731,1,3,1,4,3,1,3,3,4,3,4,4,4,3,85,78.0,neutral or dissatisfied +3992,128098,Female,Loyal Customer,46,Personal Travel,Eco,2917,3,2,3,4,3,5,5,3,3,4,3,5,2,5,3,11.0,neutral or dissatisfied +3993,47834,Female,Loyal Customer,38,Business travel,Eco,550,4,3,3,3,4,3,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +3994,48267,Male,disloyal Customer,23,Business travel,Eco,192,5,4,5,2,5,5,5,5,4,1,4,5,4,5,0,0.0,satisfied +3995,62671,Male,Loyal Customer,32,Business travel,Business,1846,2,2,2,2,3,4,3,3,5,3,5,5,4,3,8,2.0,satisfied +3996,21488,Male,disloyal Customer,54,Business travel,Eco,331,4,0,4,3,5,4,5,5,3,3,2,4,3,5,0,0.0,neutral or dissatisfied +3997,47608,Male,Loyal Customer,41,Business travel,Business,1428,4,4,4,4,4,2,3,4,4,4,4,4,4,1,4,0.0,satisfied +3998,106324,Female,Loyal Customer,45,Business travel,Business,3028,3,3,2,3,2,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +3999,48307,Female,Loyal Customer,65,Business travel,Business,2614,2,2,2,2,5,1,4,5,5,5,5,4,5,2,27,17.0,satisfied +4000,59585,Male,Loyal Customer,41,Business travel,Eco,787,1,0,0,4,4,1,5,4,2,5,3,1,3,4,11,0.0,neutral or dissatisfied +4001,85392,Male,disloyal Customer,36,Business travel,Business,214,3,3,3,2,5,3,5,5,4,4,5,4,5,5,1,0.0,neutral or dissatisfied +4002,86749,Female,Loyal Customer,42,Business travel,Business,821,3,3,3,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +4003,68839,Male,Loyal Customer,49,Business travel,Business,3848,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +4004,81020,Male,Loyal Customer,61,Business travel,Business,3734,3,2,2,2,1,4,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +4005,22387,Male,disloyal Customer,25,Business travel,Eco,83,3,3,3,4,1,3,1,1,1,2,4,4,4,1,27,21.0,neutral or dissatisfied +4006,115593,Female,disloyal Customer,59,Business travel,Eco,417,2,3,2,3,4,2,4,4,3,1,3,2,3,4,35,58.0,neutral or dissatisfied +4007,108180,Male,Loyal Customer,51,Personal Travel,Eco,1105,1,2,1,4,4,1,4,4,1,5,4,2,4,4,8,3.0,neutral or dissatisfied +4008,120115,Female,disloyal Customer,27,Business travel,Business,1576,2,2,2,3,3,2,4,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +4009,43195,Male,disloyal Customer,52,Business travel,Eco,651,3,5,3,2,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +4010,89022,Male,Loyal Customer,59,Personal Travel,Business,2092,3,2,3,3,2,4,4,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +4011,62597,Male,Loyal Customer,39,Business travel,Eco,226,3,3,3,3,3,3,3,3,1,4,4,3,4,3,4,0.0,neutral or dissatisfied +4012,104988,Male,Loyal Customer,72,Business travel,Eco,337,5,3,3,3,5,5,5,5,1,2,5,4,3,5,0,0.0,satisfied +4013,86825,Male,Loyal Customer,30,Business travel,Business,3953,2,3,2,3,2,2,2,4,2,3,3,2,2,2,238,219.0,neutral or dissatisfied +4014,90522,Male,Loyal Customer,43,Business travel,Business,2167,4,4,4,4,3,5,5,4,4,4,4,5,4,3,2,2.0,satisfied +4015,32450,Female,Loyal Customer,30,Business travel,Business,101,0,5,0,5,1,1,1,1,1,2,5,1,3,1,0,0.0,satisfied +4016,10469,Male,Loyal Customer,54,Business travel,Business,312,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +4017,101972,Female,Loyal Customer,40,Business travel,Eco,228,3,3,3,3,3,3,3,3,2,1,3,4,4,3,43,35.0,neutral or dissatisfied +4018,57646,Female,Loyal Customer,55,Business travel,Eco,200,3,1,4,1,5,3,4,4,4,3,4,3,4,3,0,15.0,satisfied +4019,105812,Male,Loyal Customer,25,Personal Travel,Eco,919,3,1,3,2,5,3,5,5,3,4,3,3,3,5,1,0.0,neutral or dissatisfied +4020,104739,Male,Loyal Customer,58,Business travel,Business,1342,3,3,4,3,3,5,5,5,5,5,5,3,5,4,9,1.0,satisfied +4021,123570,Female,Loyal Customer,24,Business travel,Business,1773,5,3,5,5,5,5,5,5,3,4,3,5,5,5,15,0.0,satisfied +4022,66765,Male,Loyal Customer,52,Business travel,Business,978,5,5,5,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +4023,17701,Female,Loyal Customer,65,Business travel,Business,311,1,1,1,1,2,5,4,4,4,4,4,2,4,4,0,0.0,satisfied +4024,47229,Male,Loyal Customer,51,Business travel,Eco Plus,945,4,2,3,2,4,4,4,4,2,3,2,1,2,4,36,30.0,neutral or dissatisfied +4025,83290,Female,Loyal Customer,57,Personal Travel,Eco,2079,3,3,3,3,4,3,3,5,5,3,5,2,5,2,0,32.0,neutral or dissatisfied +4026,7054,Female,Loyal Customer,53,Business travel,Business,273,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +4027,31265,Male,disloyal Customer,19,Business travel,Eco,770,2,2,2,3,4,2,4,4,1,5,1,5,4,4,0,6.0,neutral or dissatisfied +4028,54708,Male,Loyal Customer,51,Business travel,Eco,854,1,5,5,5,1,1,1,1,1,3,3,3,4,1,25,33.0,neutral or dissatisfied +4029,121245,Male,Loyal Customer,32,Business travel,Business,2075,3,3,3,3,3,3,3,3,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +4030,5426,Male,Loyal Customer,52,Personal Travel,Business,265,3,2,0,3,2,3,3,1,1,0,1,3,1,4,33,28.0,neutral or dissatisfied +4031,6886,Female,Loyal Customer,44,Business travel,Business,3931,5,5,5,5,2,4,4,5,5,5,5,3,5,4,28,43.0,satisfied +4032,69446,Female,Loyal Customer,56,Personal Travel,Eco,1096,2,4,2,4,1,2,1,2,2,2,4,5,2,2,0,0.0,neutral or dissatisfied +4033,43720,Female,Loyal Customer,19,Personal Travel,Eco,257,3,1,0,4,2,0,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +4034,65151,Female,Loyal Customer,12,Personal Travel,Eco,190,2,5,2,2,1,2,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +4035,58309,Male,Loyal Customer,30,Business travel,Business,1739,5,5,5,5,4,4,4,4,4,5,4,5,4,4,25,35.0,satisfied +4036,32157,Male,Loyal Customer,60,Business travel,Business,3322,4,4,4,4,4,5,4,3,3,4,5,4,3,4,0,0.0,satisfied +4037,16003,Male,disloyal Customer,30,Business travel,Eco,780,4,4,4,3,2,4,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +4038,92232,Male,Loyal Customer,19,Business travel,Business,1979,2,2,2,2,4,4,4,4,5,3,5,5,5,4,3,0.0,satisfied +4039,110496,Male,Loyal Customer,65,Personal Travel,Eco,842,1,5,1,1,4,1,4,4,3,3,5,4,4,4,33,29.0,neutral or dissatisfied +4040,26289,Female,Loyal Customer,54,Business travel,Business,1199,3,4,4,4,5,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +4041,66091,Male,Loyal Customer,31,Business travel,Business,2490,1,1,1,1,4,4,4,4,3,5,5,4,4,4,6,,satisfied +4042,27505,Male,Loyal Customer,36,Business travel,Eco,271,4,5,5,5,4,4,4,4,3,1,4,3,5,4,0,1.0,satisfied +4043,80379,Female,disloyal Customer,20,Business travel,Eco,368,2,3,2,3,1,2,1,1,3,3,2,4,3,1,24,10.0,neutral or dissatisfied +4044,32377,Female,Loyal Customer,51,Business travel,Business,101,0,4,0,1,4,5,1,5,5,1,1,2,5,1,10,11.0,satisfied +4045,31078,Male,Loyal Customer,29,Business travel,Eco Plus,641,1,3,4,4,1,2,1,1,3,3,4,3,4,1,0,2.0,neutral or dissatisfied +4046,104504,Female,Loyal Customer,40,Business travel,Business,1609,4,2,2,2,4,4,4,1,2,2,4,4,4,4,246,235.0,neutral or dissatisfied +4047,36091,Male,Loyal Customer,18,Personal Travel,Eco,399,3,5,3,1,3,3,3,3,3,4,4,4,5,3,6,39.0,neutral or dissatisfied +4048,80637,Female,Loyal Customer,36,Business travel,Business,282,2,2,2,2,4,3,3,4,4,4,4,1,4,1,60,58.0,satisfied +4049,100017,Male,Loyal Customer,44,Business travel,Business,3712,2,2,3,2,4,5,4,5,5,5,5,5,5,4,10,8.0,satisfied +4050,24946,Female,Loyal Customer,42,Business travel,Eco,1747,5,4,4,4,3,3,4,5,5,5,5,1,5,1,4,0.0,satisfied +4051,107952,Male,Loyal Customer,27,Business travel,Eco Plus,611,1,3,2,3,1,1,1,1,2,4,4,2,3,1,0,0.0,neutral or dissatisfied +4052,129668,Female,Loyal Customer,28,Business travel,Eco,447,4,1,1,1,4,4,4,4,2,1,3,1,4,4,0,0.0,neutral or dissatisfied +4053,47487,Female,Loyal Customer,46,Personal Travel,Eco,574,2,4,2,3,5,4,5,4,4,2,4,3,4,5,61,64.0,neutral or dissatisfied +4054,78471,Female,Loyal Customer,51,Business travel,Business,3040,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +4055,13575,Male,Loyal Customer,39,Personal Travel,Eco,227,3,5,3,3,4,3,4,4,5,5,4,5,4,4,0,8.0,neutral or dissatisfied +4056,33575,Male,disloyal Customer,62,Business travel,Eco,399,1,4,1,3,2,1,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +4057,1779,Female,Loyal Customer,34,Business travel,Business,500,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +4058,61273,Male,Loyal Customer,63,Personal Travel,Eco,909,4,3,4,4,5,4,5,5,2,2,3,3,3,5,3,4.0,neutral or dissatisfied +4059,9797,Female,Loyal Customer,69,Personal Travel,Eco Plus,383,2,5,4,4,4,2,1,5,5,4,5,3,5,4,8,3.0,neutral or dissatisfied +4060,39475,Male,disloyal Customer,37,Business travel,Eco,867,1,1,1,2,1,1,1,1,3,5,4,5,4,1,0,4.0,neutral or dissatisfied +4061,27335,Female,Loyal Customer,36,Business travel,Eco,697,5,2,2,2,5,5,5,5,2,5,5,5,5,5,0,0.0,satisfied +4062,47734,Female,Loyal Customer,30,Business travel,Business,3380,2,4,4,4,2,2,2,2,3,1,3,4,3,2,1,20.0,neutral or dissatisfied +4063,99602,Female,Loyal Customer,39,Business travel,Business,2347,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4064,118020,Male,Loyal Customer,61,Personal Travel,Eco Plus,1037,1,4,1,3,1,4,5,3,3,5,5,5,4,5,139,119.0,neutral or dissatisfied +4065,29446,Female,Loyal Customer,56,Business travel,Business,2266,5,5,4,5,3,3,2,5,5,5,5,3,5,1,0,0.0,satisfied +4066,116320,Female,Loyal Customer,29,Personal Travel,Eco,362,1,2,2,3,5,2,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +4067,47375,Female,Loyal Customer,53,Business travel,Eco,558,1,4,4,4,5,3,4,1,1,1,1,4,1,4,14,6.0,neutral or dissatisfied +4068,38440,Female,Loyal Customer,40,Business travel,Business,588,4,4,4,4,2,4,5,4,4,4,4,5,4,5,10,15.0,satisfied +4069,33570,Male,Loyal Customer,31,Business travel,Business,413,4,4,4,4,4,4,4,4,4,1,3,1,1,4,6,2.0,satisfied +4070,1138,Male,Loyal Customer,70,Personal Travel,Eco,312,1,1,1,2,1,1,1,1,3,5,2,4,3,1,0,0.0,neutral or dissatisfied +4071,81624,Female,Loyal Customer,30,Business travel,Business,3807,3,3,3,3,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +4072,98874,Female,Loyal Customer,60,Business travel,Business,991,1,1,1,1,3,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +4073,26756,Female,Loyal Customer,43,Business travel,Business,3859,3,3,3,3,1,3,3,5,5,5,5,1,5,3,0,5.0,satisfied +4074,44693,Male,Loyal Customer,59,Business travel,Business,67,5,5,5,5,2,2,5,4,4,4,5,2,4,1,55,48.0,satisfied +4075,98520,Female,Loyal Customer,68,Personal Travel,Eco,668,3,2,3,4,1,3,3,5,5,3,4,4,5,2,20,82.0,neutral or dissatisfied +4076,12283,Female,Loyal Customer,48,Business travel,Business,201,1,1,1,1,3,5,5,5,5,5,5,2,5,3,0,0.0,satisfied +4077,11087,Female,Loyal Customer,58,Personal Travel,Eco,517,2,4,5,4,2,5,5,5,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +4078,5912,Male,Loyal Customer,54,Personal Travel,Eco,67,2,2,2,4,5,2,5,5,3,2,3,4,3,5,28,19.0,neutral or dissatisfied +4079,57766,Female,disloyal Customer,22,Business travel,Business,1378,5,5,5,3,5,2,2,4,4,4,4,2,5,2,0,0.0,satisfied +4080,781,Male,Loyal Customer,37,Business travel,Business,2421,3,3,3,3,2,4,4,5,5,5,5,3,5,5,4,1.0,satisfied +4081,116258,Female,Loyal Customer,68,Personal Travel,Eco,308,4,1,4,2,2,3,2,2,2,4,2,1,2,1,18,12.0,neutral or dissatisfied +4082,11074,Female,Loyal Customer,60,Personal Travel,Eco,166,1,5,1,3,2,4,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +4083,54303,Male,Loyal Customer,36,Business travel,Business,1597,5,5,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +4084,65217,Female,Loyal Customer,44,Business travel,Business,1516,0,4,0,2,3,4,4,2,2,2,1,3,2,4,4,0.0,satisfied +4085,10372,Male,disloyal Customer,19,Business travel,Business,517,4,0,4,4,3,4,3,3,5,4,5,4,5,3,7,8.0,satisfied +4086,72453,Female,Loyal Customer,33,Business travel,Business,1121,4,4,3,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +4087,36720,Male,Loyal Customer,75,Business travel,Eco Plus,797,4,1,1,1,4,4,4,4,2,3,3,3,4,4,0,19.0,neutral or dissatisfied +4088,114314,Female,Loyal Customer,52,Personal Travel,Eco,846,2,5,2,1,4,4,5,4,4,2,4,4,4,5,1,0.0,neutral or dissatisfied +4089,40846,Female,disloyal Customer,30,Business travel,Eco,501,1,5,1,1,1,1,4,1,5,5,3,5,5,1,0,0.0,neutral or dissatisfied +4090,26992,Female,Loyal Customer,49,Business travel,Eco,867,5,3,3,3,4,1,2,5,5,5,5,1,5,3,0,3.0,satisfied +4091,10086,Female,Loyal Customer,43,Business travel,Business,266,1,1,3,1,1,1,1,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +4092,117478,Female,Loyal Customer,57,Business travel,Business,507,4,4,4,4,2,5,5,4,4,4,4,3,4,5,26,18.0,satisfied +4093,5479,Female,Loyal Customer,32,Personal Travel,Eco Plus,265,1,3,1,4,4,1,4,4,1,2,2,3,4,4,0,4.0,neutral or dissatisfied +4094,72123,Male,Loyal Customer,33,Business travel,Business,1607,4,4,4,4,5,5,5,5,3,3,4,3,5,5,8,16.0,satisfied +4095,73984,Female,Loyal Customer,18,Business travel,Eco Plus,2585,3,3,5,3,3,1,3,1,1,4,3,3,4,3,6,0.0,neutral or dissatisfied +4096,54652,Male,disloyal Customer,12,Business travel,Eco,854,2,2,2,3,5,2,5,5,3,2,4,1,3,5,84,78.0,neutral or dissatisfied +4097,46194,Female,Loyal Customer,55,Business travel,Business,1541,2,1,1,1,4,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +4098,77897,Male,Loyal Customer,48,Business travel,Business,1935,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +4099,17339,Male,Loyal Customer,44,Business travel,Eco,563,5,4,4,4,5,5,5,5,5,4,3,4,4,5,4,1.0,satisfied +4100,59759,Female,Loyal Customer,26,Business travel,Business,2275,3,3,3,3,4,4,4,4,4,4,5,5,5,4,33,17.0,satisfied +4101,118683,Male,Loyal Customer,41,Business travel,Eco,451,3,3,3,3,4,3,4,4,1,1,2,5,5,4,0,0.0,satisfied +4102,81072,Male,Loyal Customer,54,Business travel,Business,931,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,5.0,satisfied +4103,40853,Male,Loyal Customer,15,Personal Travel,Eco,590,2,5,3,3,3,3,3,3,4,3,4,5,5,3,32,42.0,neutral or dissatisfied +4104,120509,Male,Loyal Customer,36,Business travel,Eco Plus,366,5,2,2,2,5,5,5,5,1,3,2,3,2,5,0,0.0,satisfied +4105,109683,Male,Loyal Customer,28,Personal Travel,Eco,802,2,2,2,1,2,2,2,2,1,3,1,3,1,2,35,21.0,neutral or dissatisfied +4106,12626,Male,Loyal Customer,55,Business travel,Business,844,2,2,2,2,5,5,4,4,4,4,4,4,4,3,36,27.0,satisfied +4107,97255,Female,Loyal Customer,60,Business travel,Eco,296,4,4,4,4,2,3,3,4,4,4,4,4,4,3,51,33.0,neutral or dissatisfied +4108,7992,Female,Loyal Customer,41,Business travel,Business,402,2,4,4,4,3,3,3,2,2,2,2,3,2,2,0,31.0,neutral or dissatisfied +4109,91070,Male,Loyal Customer,20,Personal Travel,Eco,404,3,4,3,1,3,3,3,4,5,4,4,3,5,3,97,140.0,neutral or dissatisfied +4110,58186,Male,disloyal Customer,8,Business travel,Eco,925,2,3,3,4,4,3,4,4,2,2,4,2,3,4,2,21.0,neutral or dissatisfied +4111,22251,Male,disloyal Customer,22,Business travel,Eco,238,1,4,1,2,2,1,2,2,4,3,1,1,5,2,0,0.0,neutral or dissatisfied +4112,12504,Female,Loyal Customer,18,Personal Travel,Eco Plus,192,4,4,4,3,4,5,5,4,2,5,5,5,4,5,132,128.0,neutral or dissatisfied +4113,96299,Female,Loyal Customer,30,Personal Travel,Eco,786,3,4,3,2,5,3,3,5,4,3,4,3,4,5,1,0.0,neutral or dissatisfied +4114,77543,Male,Loyal Customer,32,Business travel,Business,3876,4,4,4,4,4,4,4,4,5,5,4,3,4,4,32,26.0,satisfied +4115,6355,Female,disloyal Customer,42,Business travel,Business,213,2,1,1,5,1,2,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +4116,24934,Male,Loyal Customer,36,Business travel,Eco,2106,5,2,2,2,5,5,5,5,2,5,4,1,3,5,6,0.0,satisfied +4117,52561,Male,disloyal Customer,57,Business travel,Eco,119,5,2,5,1,4,5,3,4,1,2,4,5,4,4,0,0.0,satisfied +4118,124966,Female,Loyal Customer,59,Business travel,Business,3181,0,5,0,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +4119,8,Female,Loyal Customer,60,Business travel,Business,853,4,3,4,4,4,4,4,3,3,4,3,3,3,4,0,3.0,satisfied +4120,91444,Female,disloyal Customer,21,Business travel,Eco,859,4,4,4,3,5,4,5,5,4,5,4,4,4,5,0,0.0,satisfied +4121,123443,Male,Loyal Customer,55,Business travel,Business,2125,3,3,3,3,2,3,5,2,2,2,2,4,2,3,0,0.0,satisfied +4122,83094,Female,Loyal Customer,19,Personal Travel,Eco,957,2,4,2,4,2,2,2,2,3,2,4,5,5,2,0,2.0,neutral or dissatisfied +4123,115935,Female,Loyal Customer,51,Business travel,Business,2198,3,2,2,2,3,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +4124,114558,Male,Loyal Customer,43,Personal Travel,Business,446,1,5,1,1,3,5,5,5,5,1,5,3,5,3,2,0.0,neutral or dissatisfied +4125,2461,Male,Loyal Customer,31,Business travel,Business,1697,5,5,5,5,5,5,5,5,4,5,4,5,4,5,0,9.0,satisfied +4126,33371,Female,Loyal Customer,26,Personal Travel,Eco,2409,3,4,3,1,5,3,5,5,1,5,4,1,5,5,0,0.0,neutral or dissatisfied +4127,74977,Male,Loyal Customer,17,Personal Travel,Eco,2475,2,0,2,1,3,2,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +4128,86109,Female,Loyal Customer,41,Business travel,Business,226,1,1,4,1,4,5,4,5,5,5,5,3,5,4,12,0.0,satisfied +4129,44160,Male,disloyal Customer,21,Business travel,Eco,229,2,0,2,3,4,2,4,4,2,5,1,1,5,4,51,47.0,neutral or dissatisfied +4130,3154,Male,Loyal Customer,63,Personal Travel,Eco,140,5,3,5,4,5,5,5,5,4,5,2,2,5,5,0,0.0,satisfied +4131,99779,Male,Loyal Customer,43,Business travel,Business,2937,4,4,4,4,5,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +4132,88263,Male,Loyal Customer,46,Business travel,Business,545,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +4133,128642,Male,Loyal Customer,25,Personal Travel,Eco,679,1,3,1,4,1,1,1,1,5,5,2,5,3,1,1,0.0,neutral or dissatisfied +4134,94050,Male,Loyal Customer,39,Business travel,Business,3771,2,2,2,2,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +4135,115448,Female,Loyal Customer,30,Business travel,Business,2189,5,5,5,5,3,3,3,3,3,4,4,4,5,3,0,0.0,satisfied +4136,10671,Female,Loyal Customer,40,Business travel,Business,2735,5,5,5,5,5,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +4137,10498,Female,Loyal Customer,50,Business travel,Business,2320,4,4,4,4,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +4138,9423,Female,disloyal Customer,26,Business travel,Business,368,2,4,2,1,4,2,3,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +4139,118745,Female,Loyal Customer,26,Personal Travel,Eco,621,4,5,4,2,1,4,1,1,5,5,4,5,5,1,31,35.0,neutral or dissatisfied +4140,45773,Female,Loyal Customer,57,Business travel,Eco,391,4,5,5,5,4,1,4,4,4,4,4,1,4,5,29,33.0,satisfied +4141,19130,Male,Loyal Customer,30,Personal Travel,Eco,287,3,4,3,4,3,3,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +4142,98313,Male,Loyal Customer,14,Personal Travel,Eco,1565,3,5,3,4,2,3,2,2,3,5,5,3,5,2,56,63.0,neutral or dissatisfied +4143,53875,Female,disloyal Customer,35,Business travel,Eco,140,3,4,2,4,5,2,5,5,1,3,4,4,3,5,7,0.0,neutral or dissatisfied +4144,33301,Female,Loyal Customer,31,Personal Travel,Eco Plus,163,3,5,0,4,4,0,3,4,4,2,4,5,4,4,25,30.0,neutral or dissatisfied +4145,7022,Male,Loyal Customer,18,Personal Travel,Eco,234,1,3,1,3,3,1,1,3,3,3,3,2,2,3,34,32.0,neutral or dissatisfied +4146,93953,Male,Loyal Customer,36,Personal Travel,Eco,507,3,2,3,4,1,3,1,1,1,2,3,1,3,1,1,0.0,neutral or dissatisfied +4147,4111,Male,Loyal Customer,59,Business travel,Business,431,3,3,5,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +4148,100257,Female,disloyal Customer,24,Business travel,Eco,1204,2,2,2,1,2,2,2,2,3,4,4,4,5,2,0,10.0,neutral or dissatisfied +4149,50404,Female,disloyal Customer,42,Business travel,Eco,86,3,1,3,4,1,3,1,1,2,1,4,3,4,1,0,0.0,neutral or dissatisfied +4150,35738,Male,disloyal Customer,36,Business travel,Eco,1005,3,3,3,4,4,3,4,4,1,2,5,3,2,4,35,21.0,neutral or dissatisfied +4151,85153,Male,disloyal Customer,28,Business travel,Business,874,0,0,0,4,3,0,3,3,4,5,5,4,4,3,0,0.0,satisfied +4152,2776,Female,Loyal Customer,53,Business travel,Business,1963,2,2,2,2,4,5,5,4,4,4,4,4,4,3,1,1.0,satisfied +4153,121171,Male,Loyal Customer,33,Personal Travel,Eco,2521,4,3,4,3,4,2,2,3,5,2,2,2,3,2,0,0.0,satisfied +4154,52340,Female,Loyal Customer,68,Business travel,Business,2923,4,3,3,3,3,3,3,2,2,2,4,3,2,2,0,6.0,neutral or dissatisfied +4155,33295,Female,Loyal Customer,61,Personal Travel,Eco Plus,101,3,1,3,3,5,4,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +4156,35166,Male,Loyal Customer,28,Business travel,Business,1010,2,2,2,2,4,4,4,4,2,5,2,4,1,4,31,88.0,satisfied +4157,106197,Female,Loyal Customer,46,Business travel,Business,302,5,5,5,5,2,5,5,5,5,5,5,5,5,4,50,42.0,satisfied +4158,105747,Female,Loyal Customer,40,Business travel,Business,3185,2,4,4,4,4,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +4159,115719,Female,Loyal Customer,29,Business travel,Business,2193,2,2,4,2,3,3,3,3,3,3,5,3,5,3,13,4.0,satisfied +4160,113752,Male,Loyal Customer,46,Personal Travel,Eco,236,2,4,2,1,1,2,4,1,5,3,4,4,5,1,31,23.0,neutral or dissatisfied +4161,107752,Male,Loyal Customer,69,Personal Travel,Eco,251,3,4,3,1,5,3,5,5,3,3,4,5,1,5,14,7.0,neutral or dissatisfied +4162,93203,Female,Loyal Customer,40,Personal Travel,Business,1756,3,4,3,5,4,2,1,1,1,3,1,5,1,2,11,0.0,neutral or dissatisfied +4163,29329,Female,Loyal Customer,35,Personal Travel,Eco,859,4,5,4,4,1,4,1,1,4,2,4,4,5,1,0,0.0,satisfied +4164,15715,Female,Loyal Customer,39,Business travel,Eco,419,3,4,4,4,3,3,3,3,2,1,3,4,4,3,7,30.0,neutral or dissatisfied +4165,94309,Female,Loyal Customer,49,Business travel,Business,3263,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +4166,71802,Female,disloyal Customer,62,Business travel,Business,1744,1,0,0,2,1,1,1,1,4,2,4,3,4,1,16,35.0,neutral or dissatisfied +4167,5223,Female,Loyal Customer,61,Business travel,Business,295,2,2,3,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +4168,88301,Male,disloyal Customer,24,Business travel,Eco,545,3,2,3,4,4,3,4,4,1,5,4,1,4,4,16,17.0,neutral or dissatisfied +4169,65245,Male,Loyal Customer,54,Business travel,Business,3091,2,2,3,2,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +4170,107970,Male,Loyal Customer,37,Business travel,Eco,825,4,1,1,1,4,3,4,4,4,4,3,1,4,4,0,0.0,neutral or dissatisfied +4171,82027,Male,Loyal Customer,40,Personal Travel,Eco,1576,3,4,3,4,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +4172,63845,Male,Loyal Customer,32,Business travel,Business,1212,3,4,4,4,3,4,3,3,2,3,3,1,4,3,0,2.0,neutral or dissatisfied +4173,116038,Female,Loyal Customer,41,Personal Travel,Eco,325,3,4,3,4,1,3,1,1,4,4,4,3,3,1,1,2.0,neutral or dissatisfied +4174,67975,Female,disloyal Customer,17,Business travel,Business,1242,0,0,0,3,4,0,4,4,4,4,4,4,5,4,18,11.0,satisfied +4175,64117,Female,Loyal Customer,41,Business travel,Business,2288,1,1,1,1,5,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +4176,22342,Male,Loyal Customer,30,Business travel,Eco,238,3,3,5,3,3,3,3,3,4,3,3,1,3,3,0,0.0,neutral or dissatisfied +4177,51842,Male,Loyal Customer,19,Personal Travel,Eco Plus,455,2,5,2,1,2,2,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +4178,70529,Female,Loyal Customer,46,Business travel,Business,3017,4,4,3,4,4,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +4179,48502,Female,disloyal Customer,28,Business travel,Eco,853,3,3,3,3,5,3,3,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +4180,126963,Male,Loyal Customer,44,Business travel,Business,1828,1,1,1,1,3,5,4,2,2,2,2,4,2,3,1,12.0,satisfied +4181,41145,Male,Loyal Customer,50,Personal Travel,Eco,224,3,4,3,1,1,3,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +4182,110032,Male,Loyal Customer,55,Personal Travel,Eco Plus,1204,3,2,3,4,5,3,5,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +4183,88174,Female,disloyal Customer,22,Business travel,Eco,515,4,2,4,3,3,4,3,3,5,3,4,3,4,3,81,84.0,satisfied +4184,60765,Male,Loyal Customer,25,Business travel,Business,628,1,4,4,4,1,1,1,1,4,1,3,2,4,1,17,52.0,neutral or dissatisfied +4185,87271,Male,Loyal Customer,53,Business travel,Eco,577,1,0,0,3,4,1,2,4,4,4,2,2,2,4,0,0.0,neutral or dissatisfied +4186,35613,Male,Loyal Customer,7,Personal Travel,Eco Plus,828,2,5,2,4,3,2,3,3,3,5,5,4,5,3,11,20.0,neutral or dissatisfied +4187,128879,Male,Loyal Customer,36,Business travel,Business,2454,3,3,3,3,3,5,4,4,4,4,4,4,4,5,2,22.0,satisfied +4188,1868,Female,disloyal Customer,32,Business travel,Business,931,3,3,3,2,3,3,3,3,2,2,3,4,3,3,24,6.0,neutral or dissatisfied +4189,23210,Female,Loyal Customer,34,Business travel,Business,2101,3,3,1,3,4,3,5,5,5,5,5,1,5,5,0,0.0,satisfied +4190,108112,Male,Loyal Customer,51,Business travel,Business,3320,4,4,5,4,4,5,4,5,5,5,5,3,5,3,0,4.0,satisfied +4191,115746,Male,Loyal Customer,36,Business travel,Business,2346,3,4,4,4,2,2,2,3,3,3,3,2,3,1,12,25.0,neutral or dissatisfied +4192,40243,Female,Loyal Customer,34,Business travel,Business,2698,4,4,4,4,5,2,5,5,5,5,5,1,5,1,0,0.0,satisfied +4193,117207,Female,Loyal Customer,23,Personal Travel,Eco,370,1,4,1,5,4,1,4,4,5,3,3,3,5,4,30,12.0,neutral or dissatisfied +4194,21084,Male,Loyal Customer,30,Business travel,Business,3101,1,0,0,4,3,0,3,3,2,1,3,4,4,3,61,48.0,neutral or dissatisfied +4195,73334,Male,Loyal Customer,49,Business travel,Business,1197,1,1,1,1,3,5,5,4,4,5,4,5,4,3,0,5.0,satisfied +4196,61660,Female,Loyal Customer,58,Business travel,Business,1504,3,3,3,3,3,4,4,5,5,5,5,4,5,5,29,14.0,satisfied +4197,105806,Female,Loyal Customer,50,Personal Travel,Eco,883,4,3,4,1,4,3,4,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +4198,17051,Female,disloyal Customer,28,Business travel,Eco,1134,5,5,5,4,5,5,5,5,1,2,2,2,1,5,16,3.0,satisfied +4199,6143,Female,Loyal Customer,48,Business travel,Business,409,2,5,5,5,4,3,4,2,2,2,2,3,2,2,60,56.0,neutral or dissatisfied +4200,19708,Female,Loyal Customer,51,Business travel,Business,1961,3,2,2,2,2,2,3,3,3,3,3,1,3,2,3,0.0,neutral or dissatisfied +4201,109,Female,Loyal Customer,72,Business travel,Business,1954,1,1,3,1,1,1,1,4,5,3,2,1,4,1,60,145.0,neutral or dissatisfied +4202,123288,Male,Loyal Customer,57,Personal Travel,Eco,507,3,5,3,5,3,3,3,3,3,1,1,4,4,3,0,0.0,neutral or dissatisfied +4203,58785,Female,Loyal Customer,54,Business travel,Business,1197,4,2,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +4204,40256,Male,disloyal Customer,29,Business travel,Business,347,4,4,4,3,4,4,4,4,1,3,2,2,2,4,0,0.0,neutral or dissatisfied +4205,56246,Male,Loyal Customer,39,Business travel,Business,2434,2,2,2,2,5,5,5,3,2,5,5,5,4,5,107,90.0,satisfied +4206,36487,Female,Loyal Customer,61,Business travel,Business,2260,3,3,1,1,5,3,3,3,3,3,3,2,3,2,50,81.0,neutral or dissatisfied +4207,29332,Female,Loyal Customer,46,Personal Travel,Eco,834,0,5,0,4,5,5,4,3,3,0,3,3,3,4,0,5.0,satisfied +4208,108009,Female,Loyal Customer,41,Business travel,Business,271,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +4209,81375,Male,Loyal Customer,27,Business travel,Business,1767,2,3,3,3,2,3,2,2,3,4,4,4,4,2,51,38.0,neutral or dissatisfied +4210,60823,Male,Loyal Customer,59,Personal Travel,Eco,455,3,4,3,3,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +4211,121459,Female,Loyal Customer,26,Personal Travel,Eco,290,4,4,3,4,5,3,5,5,5,5,5,4,4,5,0,0.0,satisfied +4212,55859,Male,Loyal Customer,29,Business travel,Business,1907,4,4,4,4,4,4,4,4,4,5,5,3,4,4,35,35.0,satisfied +4213,108968,Male,Loyal Customer,25,Personal Travel,Eco,542,3,5,3,3,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +4214,72688,Male,Loyal Customer,11,Personal Travel,Eco,964,3,3,2,3,5,2,5,5,4,1,3,3,3,5,14,0.0,neutral or dissatisfied +4215,63046,Female,Loyal Customer,63,Personal Travel,Eco,967,3,4,3,3,2,5,5,3,3,3,3,4,3,5,0,2.0,neutral or dissatisfied +4216,21578,Female,Loyal Customer,10,Personal Travel,Eco Plus,331,4,4,4,4,2,4,2,2,3,4,4,3,5,2,43,45.0,neutral or dissatisfied +4217,98471,Female,Loyal Customer,7,Personal Travel,Eco,210,3,3,3,4,1,3,1,1,2,5,2,3,5,1,9,4.0,neutral or dissatisfied +4218,96054,Male,Loyal Customer,61,Business travel,Eco,835,2,3,3,3,2,2,2,2,1,4,3,1,3,2,66,57.0,neutral or dissatisfied +4219,40121,Male,Loyal Customer,47,Personal Travel,Eco,368,2,4,2,4,2,2,2,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +4220,7264,Female,Loyal Customer,10,Personal Travel,Eco,135,1,0,1,4,3,1,3,3,4,3,4,5,4,3,6,1.0,neutral or dissatisfied +4221,79708,Male,Loyal Customer,24,Personal Travel,Eco,762,2,5,2,1,2,2,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +4222,109921,Female,Loyal Customer,16,Personal Travel,Eco,971,0,5,0,3,4,0,4,4,3,3,4,5,4,4,127,118.0,satisfied +4223,124820,Male,Loyal Customer,39,Business travel,Business,280,3,3,3,3,1,3,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +4224,86107,Male,Loyal Customer,46,Business travel,Business,3145,5,5,5,5,2,4,4,5,5,5,5,4,5,3,21,18.0,satisfied +4225,89654,Female,Loyal Customer,35,Business travel,Business,2017,3,1,1,1,3,4,3,3,3,3,3,1,3,2,99,81.0,neutral or dissatisfied +4226,110930,Male,Loyal Customer,61,Personal Travel,Eco,406,2,1,2,4,5,2,1,5,2,5,3,4,3,5,21,19.0,neutral or dissatisfied +4227,37310,Female,Loyal Customer,60,Business travel,Eco,1035,5,2,5,2,2,4,1,4,4,5,4,1,4,1,9,0.0,satisfied +4228,43568,Male,Loyal Customer,60,Personal Travel,Business,1499,2,4,2,2,3,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +4229,75008,Female,disloyal Customer,34,Business travel,Business,236,1,1,1,2,2,1,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +4230,52718,Female,Loyal Customer,14,Personal Travel,Business,406,2,5,2,1,3,2,5,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +4231,7269,Male,Loyal Customer,55,Personal Travel,Eco,139,2,4,2,1,4,2,4,4,5,3,5,5,4,4,28,21.0,neutral or dissatisfied +4232,124266,Female,Loyal Customer,64,Business travel,Business,2160,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +4233,34498,Female,Loyal Customer,46,Business travel,Eco Plus,1990,3,1,1,1,1,3,3,3,3,3,3,2,3,4,4,0.0,neutral or dissatisfied +4234,114995,Male,Loyal Customer,34,Business travel,Business,308,0,0,0,1,1,1,1,3,3,4,5,1,4,1,180,181.0,satisfied +4235,37054,Male,Loyal Customer,42,Business travel,Business,1072,1,1,1,1,2,1,2,4,4,4,4,4,4,1,2,0.0,satisfied +4236,64023,Male,disloyal Customer,35,Business travel,Business,919,2,2,2,3,2,2,2,2,3,2,5,5,5,2,85,87.0,neutral or dissatisfied +4237,4822,Male,Loyal Customer,56,Business travel,Business,408,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +4238,94214,Female,disloyal Customer,22,Business travel,Business,248,4,0,4,1,3,4,1,3,3,2,5,5,5,3,11,3.0,satisfied +4239,124475,Female,Loyal Customer,18,Personal Travel,Eco,980,2,5,3,2,4,3,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +4240,129206,Female,disloyal Customer,38,Business travel,Eco,919,3,3,3,4,4,3,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +4241,47232,Male,Loyal Customer,14,Business travel,Eco Plus,954,2,1,1,1,2,2,4,2,1,1,3,3,4,2,100,109.0,neutral or dissatisfied +4242,22000,Male,Loyal Customer,57,Personal Travel,Eco,500,2,4,2,3,2,2,1,2,4,3,5,4,5,2,6,0.0,neutral or dissatisfied +4243,17445,Male,Loyal Customer,36,Personal Travel,Eco,376,2,4,2,3,4,2,4,4,4,4,4,4,4,4,0,1.0,neutral or dissatisfied +4244,98869,Female,disloyal Customer,42,Business travel,Business,991,4,4,4,1,2,4,2,2,3,4,5,4,4,2,10,8.0,neutral or dissatisfied +4245,44601,Female,Loyal Customer,47,Business travel,Eco,508,2,4,5,4,3,4,5,2,2,2,2,3,2,5,0,7.0,satisfied +4246,88075,Male,Loyal Customer,39,Business travel,Business,442,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +4247,113101,Female,Loyal Customer,29,Personal Travel,Eco,479,3,2,3,4,2,3,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +4248,5701,Female,Loyal Customer,12,Personal Travel,Eco,196,4,5,4,1,1,4,1,1,3,4,5,4,4,1,0,0.0,satisfied +4249,62632,Female,Loyal Customer,62,Personal Travel,Eco,1744,1,2,1,2,3,2,2,4,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +4250,99218,Female,Loyal Customer,47,Business travel,Business,1813,4,4,4,4,2,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +4251,116999,Male,disloyal Customer,35,Business travel,Business,338,2,2,2,3,4,2,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +4252,70792,Male,Loyal Customer,53,Business travel,Business,328,0,0,0,3,4,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +4253,105810,Female,Loyal Customer,63,Personal Travel,Eco,663,2,4,2,3,4,4,3,2,2,2,1,2,2,3,76,57.0,neutral or dissatisfied +4254,119565,Female,Loyal Customer,49,Business travel,Business,2968,4,4,4,4,5,5,5,5,5,5,5,4,5,5,13,26.0,satisfied +4255,62225,Female,Loyal Customer,35,Personal Travel,Eco,2454,1,5,1,4,2,1,2,2,3,2,3,5,5,2,0,0.0,neutral or dissatisfied +4256,119211,Female,disloyal Customer,29,Personal Travel,Eco,290,5,5,5,3,2,5,2,2,3,3,4,4,4,2,0,0.0,satisfied +4257,104977,Female,disloyal Customer,37,Business travel,Business,314,4,4,4,5,2,4,2,2,5,2,4,5,5,2,0,0.0,satisfied +4258,104882,Male,Loyal Customer,22,Personal Travel,Eco,327,2,2,2,4,4,2,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +4259,118840,Female,Loyal Customer,39,Business travel,Eco Plus,221,2,2,2,2,2,2,2,2,2,2,1,5,2,2,0,3.0,satisfied +4260,119132,Female,disloyal Customer,43,Business travel,Business,356,4,4,4,3,4,4,4,4,4,5,5,5,4,4,6,19.0,neutral or dissatisfied +4261,98178,Female,Loyal Customer,56,Business travel,Business,3710,3,3,3,3,3,4,5,5,5,5,5,5,5,5,31,37.0,satisfied +4262,50180,Female,disloyal Customer,22,Business travel,Eco,109,3,1,3,2,3,1,1,3,1,3,3,1,4,1,235,235.0,neutral or dissatisfied +4263,76122,Female,Loyal Customer,49,Business travel,Business,689,5,5,5,5,5,4,4,2,2,2,2,4,2,4,15,10.0,satisfied +4264,24574,Female,Loyal Customer,25,Business travel,Eco Plus,696,3,4,4,4,3,3,1,3,3,1,3,1,3,3,0,11.0,neutral or dissatisfied +4265,19277,Female,Loyal Customer,32,Business travel,Business,430,3,3,3,3,4,4,4,4,3,5,4,1,4,4,0,0.0,satisfied +4266,129640,Female,Loyal Customer,35,Business travel,Business,337,2,5,5,5,2,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +4267,99611,Male,Loyal Customer,53,Personal Travel,Eco Plus,808,1,1,1,2,3,1,3,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +4268,117002,Male,disloyal Customer,25,Business travel,Business,370,1,0,1,2,3,1,2,3,3,5,4,3,5,3,126,119.0,neutral or dissatisfied +4269,74062,Male,Loyal Customer,44,Business travel,Business,1812,3,3,3,3,5,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +4270,14245,Male,Loyal Customer,31,Personal Travel,Eco,1027,5,5,5,1,4,5,3,4,4,4,5,3,5,4,10,0.0,satisfied +4271,113160,Female,Loyal Customer,42,Business travel,Eco,677,2,2,3,2,1,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +4272,5354,Female,Loyal Customer,37,Business travel,Business,2620,3,3,3,3,5,5,4,4,4,4,4,4,4,3,64,71.0,satisfied +4273,8205,Female,Loyal Customer,41,Business travel,Business,130,3,3,3,3,4,3,5,5,5,4,4,5,5,5,0,5.0,satisfied +4274,57767,Male,Loyal Customer,37,Business travel,Business,2611,2,5,5,5,2,2,2,1,4,3,2,2,2,2,28,9.0,neutral or dissatisfied +4275,84395,Male,Loyal Customer,25,Business travel,Eco,606,4,2,4,4,4,4,2,4,1,3,4,4,4,4,13,0.0,neutral or dissatisfied +4276,116190,Female,Loyal Customer,56,Personal Travel,Eco,337,4,3,4,4,5,3,3,1,1,4,1,4,1,2,0,0.0,neutral or dissatisfied +4277,99327,Female,Loyal Customer,12,Personal Travel,Eco,448,3,5,4,2,1,4,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +4278,48053,Male,Loyal Customer,17,Personal Travel,Eco,896,2,5,2,2,4,2,1,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +4279,110990,Male,disloyal Customer,29,Business travel,Business,197,5,4,4,3,2,4,2,2,3,4,4,5,4,2,47,55.0,satisfied +4280,99771,Female,Loyal Customer,33,Business travel,Eco Plus,361,1,3,3,3,1,1,1,1,1,2,3,2,3,1,0,0.0,neutral or dissatisfied +4281,27580,Female,Loyal Customer,46,Personal Travel,Eco,956,4,4,4,2,4,5,5,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +4282,109283,Male,Loyal Customer,30,Personal Travel,Business,1136,1,2,1,4,5,1,5,5,3,2,2,1,3,5,99,89.0,neutral or dissatisfied +4283,58619,Male,Loyal Customer,65,Personal Travel,Eco,137,2,0,2,2,3,2,1,3,4,4,4,4,4,3,4,0.0,neutral or dissatisfied +4284,17746,Male,Loyal Customer,40,Business travel,Eco,129,4,4,4,4,4,4,4,4,1,5,2,4,5,4,0,0.0,satisfied +4285,54891,Male,Loyal Customer,43,Personal Travel,Eco,934,2,4,2,4,3,2,3,3,4,2,5,4,5,3,0,2.0,neutral or dissatisfied +4286,5501,Male,Loyal Customer,23,Business travel,Business,548,4,4,4,4,5,5,5,5,2,4,5,3,3,5,0,0.0,satisfied +4287,115643,Female,Loyal Customer,20,Business travel,Business,325,1,3,3,3,1,1,1,1,4,1,4,3,4,1,5,0.0,neutral or dissatisfied +4288,64812,Female,Loyal Customer,72,Business travel,Business,2223,1,1,1,1,2,3,3,1,1,1,1,2,1,1,34,35.0,neutral or dissatisfied +4289,112374,Male,Loyal Customer,31,Business travel,Business,853,4,4,4,4,4,4,4,4,5,5,5,5,4,4,43,39.0,satisfied +4290,85570,Male,Loyal Customer,48,Business travel,Business,259,0,0,0,1,4,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +4291,101665,Male,Loyal Customer,73,Business travel,Eco,606,2,2,2,2,2,2,2,2,3,3,3,3,4,2,7,13.0,neutral or dissatisfied +4292,42846,Male,disloyal Customer,35,Business travel,Eco,328,4,5,5,1,2,5,2,2,1,4,4,2,3,2,2,0.0,neutral or dissatisfied +4293,24803,Female,Loyal Customer,21,Business travel,Business,861,1,0,0,4,4,0,2,4,4,5,3,1,3,4,0,13.0,neutral or dissatisfied +4294,87501,Male,Loyal Customer,22,Business travel,Business,3182,3,4,4,4,3,3,3,3,1,2,4,1,4,3,41,34.0,neutral or dissatisfied +4295,85549,Female,Loyal Customer,52,Business travel,Business,317,3,3,3,3,2,4,4,4,4,4,4,4,4,5,35,34.0,satisfied +4296,79980,Male,Loyal Customer,58,Personal Travel,Eco,1080,2,4,2,3,1,2,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +4297,72827,Male,Loyal Customer,44,Business travel,Business,1803,3,3,3,3,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +4298,54256,Female,Loyal Customer,51,Personal Travel,Eco,1222,4,0,5,3,4,4,5,2,2,5,2,4,2,3,0,0.0,neutral or dissatisfied +4299,48637,Male,disloyal Customer,33,Business travel,Business,109,3,4,4,2,4,4,4,4,5,3,4,5,5,4,26,46.0,neutral or dissatisfied +4300,1417,Male,Loyal Customer,56,Personal Travel,Eco Plus,270,2,5,2,3,2,2,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +4301,33720,Male,Loyal Customer,64,Personal Travel,Eco,667,4,5,4,3,2,4,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +4302,47107,Female,Loyal Customer,44,Business travel,Eco,737,2,3,2,3,3,4,5,2,2,2,2,2,2,4,48,42.0,satisfied +4303,106752,Female,Loyal Customer,37,Business travel,Business,545,2,5,5,5,3,3,3,2,2,2,2,4,2,3,9,0.0,neutral or dissatisfied +4304,50394,Female,Loyal Customer,30,Business travel,Business,2436,2,2,2,2,3,3,2,3,4,2,3,4,3,3,73,70.0,neutral or dissatisfied +4305,115718,Female,Loyal Customer,54,Business travel,Business,2154,4,4,4,4,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +4306,119697,Male,Loyal Customer,59,Business travel,Business,1325,3,3,3,3,5,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +4307,37505,Male,Loyal Customer,29,Business travel,Business,1102,1,1,1,1,5,5,5,5,4,3,2,1,1,5,0,0.0,satisfied +4308,89154,Male,Loyal Customer,55,Business travel,Business,1927,4,4,4,4,2,5,4,5,5,5,5,4,5,2,0,24.0,satisfied +4309,57280,Female,Loyal Customer,57,Personal Travel,Eco,628,4,5,4,5,4,5,5,5,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +4310,39491,Female,Loyal Customer,70,Personal Travel,Eco Plus,867,2,4,2,2,4,3,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +4311,32911,Male,Loyal Customer,67,Personal Travel,Eco,102,4,1,0,2,2,0,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +4312,20342,Female,disloyal Customer,45,Business travel,Eco,323,3,3,3,2,3,3,3,3,2,4,4,5,3,3,0,0.0,neutral or dissatisfied +4313,120616,Male,Loyal Customer,55,Business travel,Eco Plus,453,2,2,2,2,2,2,2,2,4,5,4,2,4,2,2,0.0,neutral or dissatisfied +4314,75766,Male,Loyal Customer,47,Personal Travel,Eco,813,5,3,5,3,3,5,3,3,3,2,3,4,3,3,2,0.0,satisfied +4315,55389,Male,Loyal Customer,37,Personal Travel,Eco,678,2,4,2,4,5,2,2,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +4316,97716,Male,Loyal Customer,35,Personal Travel,Eco,942,3,3,2,1,3,2,3,3,1,4,3,4,5,3,0,0.0,neutral or dissatisfied +4317,74166,Male,Loyal Customer,47,Personal Travel,Eco,641,2,5,2,2,2,2,4,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +4318,117810,Female,disloyal Customer,43,Business travel,Eco,328,3,1,3,4,2,3,2,2,4,1,4,3,3,2,29,35.0,neutral or dissatisfied +4319,71865,Male,Loyal Customer,17,Personal Travel,Eco,1744,5,4,5,4,1,5,1,1,1,2,4,4,3,1,0,9.0,satisfied +4320,106173,Male,Loyal Customer,32,Personal Travel,Eco,436,4,4,5,3,5,5,5,5,1,5,1,2,5,5,3,1.0,neutral or dissatisfied +4321,89694,Male,disloyal Customer,34,Business travel,Business,1080,2,3,3,3,3,3,3,3,4,2,3,1,4,3,14,40.0,neutral or dissatisfied +4322,101869,Male,Loyal Customer,23,Business travel,Business,1747,1,4,4,4,1,1,1,1,3,3,3,4,2,1,5,0.0,neutral or dissatisfied +4323,60414,Female,Loyal Customer,56,Business travel,Business,1452,3,3,2,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +4324,123193,Male,Loyal Customer,69,Personal Travel,Eco,631,4,3,4,5,3,4,1,3,1,4,5,4,4,3,0,0.0,neutral or dissatisfied +4325,17289,Male,disloyal Customer,36,Business travel,Eco,258,3,0,3,1,3,3,3,3,2,4,5,3,3,3,61,58.0,neutral or dissatisfied +4326,115345,Male,Loyal Customer,56,Business travel,Business,325,0,0,0,1,5,4,4,2,2,2,2,3,2,5,1,0.0,satisfied +4327,35051,Female,Loyal Customer,48,Business travel,Business,2127,2,2,2,2,3,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +4328,124237,Female,Loyal Customer,47,Business travel,Business,1916,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +4329,51496,Female,Loyal Customer,27,Personal Travel,Business,451,3,4,3,5,3,3,3,3,5,1,4,3,3,3,0,0.0,neutral or dissatisfied +4330,85014,Female,Loyal Customer,56,Business travel,Eco,1590,3,4,4,4,5,2,3,2,2,3,2,4,2,3,3,0.0,neutral or dissatisfied +4331,63034,Male,Loyal Customer,53,Business travel,Business,462,3,5,5,5,4,3,3,3,3,3,3,3,3,4,93,69.0,neutral or dissatisfied +4332,87468,Female,Loyal Customer,29,Business travel,Business,304,1,1,4,1,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +4333,85194,Female,disloyal Customer,20,Business travel,Eco,874,3,3,3,3,5,3,4,5,3,5,3,2,4,5,3,11.0,neutral or dissatisfied +4334,40082,Male,Loyal Customer,38,Personal Travel,Eco,493,2,4,2,3,3,2,3,3,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +4335,101774,Male,Loyal Customer,64,Business travel,Business,1521,2,4,4,4,3,2,2,2,2,2,2,1,2,4,22,7.0,neutral or dissatisfied +4336,92632,Female,Loyal Customer,33,Business travel,Business,2166,2,2,2,2,2,3,3,2,2,2,2,2,2,1,0,11.0,neutral or dissatisfied +4337,129839,Male,Loyal Customer,61,Personal Travel,Eco,337,2,4,2,3,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +4338,108063,Male,Loyal Customer,55,Business travel,Business,997,5,5,5,5,3,4,5,4,4,4,4,4,4,5,17,10.0,satisfied +4339,28441,Male,Loyal Customer,69,Personal Travel,Eco,2496,3,1,3,3,3,4,4,4,5,2,2,4,3,4,6,0.0,neutral or dissatisfied +4340,92417,Female,Loyal Customer,19,Business travel,Business,1892,4,4,4,4,5,5,5,5,5,5,5,3,4,5,2,19.0,satisfied +4341,15095,Male,Loyal Customer,22,Personal Travel,Eco,239,2,3,0,3,2,0,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +4342,50149,Female,Loyal Customer,34,Business travel,Business,2708,1,3,3,3,3,4,4,1,1,1,1,1,1,4,5,0.0,neutral or dissatisfied +4343,95228,Male,Loyal Customer,70,Personal Travel,Eco,239,2,4,2,4,3,2,3,3,4,3,5,4,4,3,46,48.0,neutral or dissatisfied +4344,96403,Male,Loyal Customer,8,Personal Travel,Eco,1246,1,4,1,1,1,1,1,1,4,4,3,5,5,1,0,0.0,neutral or dissatisfied +4345,105480,Male,Loyal Customer,58,Business travel,Business,2580,5,5,5,5,5,4,4,5,5,5,5,4,5,4,27,39.0,satisfied +4346,90134,Female,Loyal Customer,43,Business travel,Eco,1086,3,3,3,3,2,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +4347,13656,Male,Loyal Customer,39,Personal Travel,Eco,196,3,4,3,1,4,3,4,4,5,4,4,4,5,4,26,15.0,neutral or dissatisfied +4348,658,Male,Loyal Customer,48,Business travel,Business,1940,1,1,1,1,5,4,5,4,4,4,4,5,4,4,21,14.0,satisfied +4349,46091,Male,Loyal Customer,19,Personal Travel,Eco,495,1,5,1,3,3,1,3,3,4,3,4,5,4,3,5,33.0,neutral or dissatisfied +4350,122360,Female,disloyal Customer,22,Business travel,Eco,529,2,2,2,2,3,2,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +4351,13352,Female,Loyal Customer,47,Business travel,Eco,946,2,5,4,5,5,3,3,1,1,2,1,1,1,4,28,16.0,neutral or dissatisfied +4352,54776,Male,Loyal Customer,31,Personal Travel,Eco Plus,956,1,5,2,4,2,3,5,3,3,4,5,5,5,5,136,134.0,neutral or dissatisfied +4353,15405,Male,disloyal Customer,33,Business travel,Eco,164,2,2,2,3,1,2,1,1,4,5,3,2,3,1,4,26.0,neutral or dissatisfied +4354,66328,Female,Loyal Customer,48,Business travel,Business,2136,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +4355,84666,Female,disloyal Customer,29,Business travel,Business,1090,0,0,0,5,5,0,5,5,5,3,5,5,4,5,0,1.0,satisfied +4356,68399,Male,Loyal Customer,51,Business travel,Business,1045,3,3,1,3,2,4,4,5,5,5,5,3,5,3,0,4.0,satisfied +4357,43477,Male,Loyal Customer,10,Business travel,Business,3189,4,4,4,4,4,3,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +4358,71720,Male,Loyal Customer,29,Business travel,Business,2566,1,1,1,1,5,5,5,5,3,5,5,5,4,5,1,0.0,satisfied +4359,19844,Male,Loyal Customer,38,Business travel,Eco,585,5,5,5,5,5,5,5,5,4,3,2,1,3,5,28,16.0,satisfied +4360,46772,Male,Loyal Customer,44,Personal Travel,Eco Plus,125,4,5,0,3,4,0,4,4,2,4,5,3,1,4,0,0.0,neutral or dissatisfied +4361,39716,Female,Loyal Customer,63,Business travel,Eco,162,2,4,4,4,4,4,3,2,2,2,2,4,2,4,0,13.0,neutral or dissatisfied +4362,10777,Male,Loyal Customer,23,Business travel,Business,3873,4,3,3,3,4,4,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +4363,109515,Female,Loyal Customer,23,Business travel,Business,3824,2,5,5,5,2,2,2,2,3,4,3,3,3,2,14,7.0,neutral or dissatisfied +4364,41712,Male,Loyal Customer,57,Business travel,Eco,1404,3,4,4,4,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +4365,55690,Female,disloyal Customer,42,Business travel,Eco,1062,1,1,1,3,2,1,4,2,4,2,3,4,3,2,14,23.0,neutral or dissatisfied +4366,59151,Male,Loyal Customer,59,Business travel,Business,1744,4,4,4,4,2,4,4,4,4,4,4,3,4,3,39,4.0,satisfied +4367,79330,Female,disloyal Customer,26,Business travel,Business,1020,3,3,3,3,5,3,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +4368,24077,Male,Loyal Customer,39,Business travel,Business,2627,1,0,0,4,5,4,4,1,1,0,1,4,1,4,0,0.0,neutral or dissatisfied +4369,95939,Female,Loyal Customer,44,Personal Travel,Eco Plus,1411,2,4,2,2,3,4,2,3,3,2,3,4,3,5,6,0.0,neutral or dissatisfied +4370,18949,Female,Loyal Customer,38,Personal Travel,Eco,448,3,4,3,2,3,3,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +4371,68698,Male,Loyal Customer,41,Personal Travel,Eco,175,3,5,3,3,3,3,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +4372,55017,Male,disloyal Customer,40,Business travel,Business,1635,5,5,5,4,5,1,1,3,2,3,4,1,5,1,173,183.0,satisfied +4373,63593,Male,Loyal Customer,49,Personal Travel,Eco,2133,1,3,0,3,3,0,2,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +4374,109471,Female,Loyal Customer,24,Business travel,Business,1964,2,2,2,2,5,5,5,5,5,4,5,3,4,5,89,89.0,satisfied +4375,34807,Female,Loyal Customer,44,Personal Travel,Eco,301,4,5,4,1,5,5,5,2,2,4,2,5,2,4,0,0.0,neutral or dissatisfied +4376,66916,Male,Loyal Customer,41,Business travel,Business,1966,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +4377,30951,Male,Loyal Customer,23,Business travel,Business,3470,4,3,5,3,4,4,4,4,1,3,4,1,3,4,15,56.0,neutral or dissatisfied +4378,31545,Female,Loyal Customer,46,Personal Travel,Eco,846,2,5,2,3,2,2,1,4,4,2,4,3,4,4,0,23.0,neutral or dissatisfied +4379,22805,Female,disloyal Customer,26,Business travel,Eco,170,3,0,3,4,4,3,1,4,1,5,3,2,1,4,20,11.0,neutral or dissatisfied +4380,40040,Female,Loyal Customer,42,Business travel,Business,3436,3,3,3,3,1,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +4381,8613,Female,disloyal Customer,15,Business travel,Eco,1371,1,1,1,1,2,1,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +4382,8801,Female,Loyal Customer,37,Business travel,Business,1941,3,4,4,4,1,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +4383,39720,Male,Loyal Customer,34,Business travel,Business,2991,2,2,2,2,4,4,1,5,5,5,5,4,5,4,0,0.0,satisfied +4384,64566,Female,disloyal Customer,37,Business travel,Business,247,4,4,4,3,2,4,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +4385,98948,Male,Loyal Customer,22,Business travel,Business,543,2,1,1,1,2,2,2,2,1,1,3,1,4,2,0,3.0,neutral or dissatisfied +4386,71510,Female,disloyal Customer,24,Business travel,Eco,1197,3,3,3,2,5,3,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +4387,73196,Male,disloyal Customer,36,Business travel,Eco,1258,3,3,3,2,5,3,5,5,1,5,3,4,3,5,0,11.0,neutral or dissatisfied +4388,31821,Female,Loyal Customer,50,Business travel,Business,2762,3,3,3,3,5,5,5,2,4,3,3,5,2,5,0,0.0,satisfied +4389,98208,Female,Loyal Customer,34,Personal Travel,Eco,327,2,0,5,4,5,5,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +4390,122565,Male,Loyal Customer,26,Personal Travel,Eco Plus,500,3,5,3,3,1,3,1,1,3,5,4,4,5,1,74,62.0,neutral or dissatisfied +4391,77090,Female,disloyal Customer,20,Business travel,Eco,1481,4,4,4,3,5,4,1,5,5,2,4,5,4,5,5,0.0,satisfied +4392,112976,Female,Loyal Customer,79,Business travel,Eco Plus,913,4,4,4,4,1,3,5,4,4,4,4,1,4,2,0,0.0,satisfied +4393,105211,Male,Loyal Customer,35,Business travel,Business,377,3,3,3,3,3,4,5,4,4,4,4,4,4,5,11,0.0,satisfied +4394,21477,Male,Loyal Customer,47,Business travel,Eco,164,2,1,3,1,2,2,2,2,1,1,2,1,3,2,23,23.0,neutral or dissatisfied +4395,74590,Female,Loyal Customer,40,Business travel,Business,1438,4,4,4,4,3,4,5,2,2,3,2,4,2,3,0,0.0,satisfied +4396,101831,Female,Loyal Customer,19,Personal Travel,Eco,1521,2,4,2,1,4,2,4,4,3,5,3,5,5,4,63,56.0,neutral or dissatisfied +4397,72467,Male,Loyal Customer,54,Business travel,Business,2383,2,2,2,2,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +4398,31032,Female,Loyal Customer,66,Personal Travel,Business,775,2,4,2,4,3,4,4,4,4,2,4,2,4,4,32,27.0,neutral or dissatisfied +4399,63267,Male,Loyal Customer,44,Business travel,Business,3135,5,5,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +4400,31794,Female,disloyal Customer,26,Business travel,Eco,878,3,3,3,3,3,2,2,4,1,3,5,2,4,2,0,0.0,neutral or dissatisfied +4401,75970,Male,Loyal Customer,55,Business travel,Eco,297,2,1,3,1,2,2,2,2,3,1,3,3,3,2,6,7.0,neutral or dissatisfied +4402,17116,Male,Loyal Customer,42,Business travel,Eco,821,2,3,3,3,2,2,2,2,4,5,2,4,1,2,0,7.0,neutral or dissatisfied +4403,45406,Female,Loyal Customer,46,Business travel,Eco,649,4,5,4,4,1,4,2,4,4,4,4,1,4,2,0,0.0,satisfied +4404,126592,Male,Loyal Customer,33,Business travel,Business,1337,4,4,4,4,4,4,4,4,3,2,5,3,4,4,19,1.0,satisfied +4405,87562,Female,Loyal Customer,43,Business travel,Business,432,4,3,4,4,5,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +4406,21016,Female,Loyal Customer,29,Business travel,Business,214,1,1,1,1,5,5,3,5,1,3,5,1,4,5,106,98.0,satisfied +4407,66648,Female,Loyal Customer,52,Business travel,Business,2958,5,5,5,5,4,5,5,2,2,3,2,3,2,5,0,0.0,satisfied +4408,28372,Male,Loyal Customer,29,Business travel,Business,3324,1,1,5,1,5,5,5,5,5,4,3,1,2,5,0,0.0,satisfied +4409,120472,Female,Loyal Customer,40,Personal Travel,Eco,337,2,4,2,3,1,2,1,1,5,3,5,3,3,1,0,0.0,neutral or dissatisfied +4410,1300,Male,Loyal Customer,20,Personal Travel,Eco,247,3,4,0,2,3,0,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +4411,39846,Male,Loyal Customer,58,Business travel,Eco,221,4,2,2,2,4,4,4,4,1,5,1,1,3,4,0,0.0,satisfied +4412,52777,Male,Loyal Customer,33,Business travel,Business,1874,4,4,3,4,2,3,2,2,5,3,4,3,5,2,25,15.0,satisfied +4413,82072,Male,Loyal Customer,31,Business travel,Business,1934,3,2,2,2,3,3,3,3,2,4,3,1,3,3,0,10.0,neutral or dissatisfied +4414,28404,Female,Loyal Customer,64,Personal Travel,Eco,1709,3,4,4,3,5,3,3,2,2,4,2,4,2,1,0,0.0,neutral or dissatisfied +4415,61339,Female,Loyal Customer,28,Business travel,Business,602,2,2,2,2,5,5,5,5,4,5,4,5,5,5,7,20.0,satisfied +4416,10404,Male,disloyal Customer,22,Business travel,Business,224,5,0,5,5,4,5,3,4,3,2,5,4,4,4,0,8.0,satisfied +4417,33072,Female,Loyal Customer,47,Personal Travel,Eco,163,3,1,3,2,3,2,3,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +4418,81818,Male,Loyal Customer,41,Business travel,Business,1487,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +4419,34187,Female,Loyal Customer,27,Personal Travel,Eco,1046,1,1,1,3,5,1,5,5,3,4,2,3,2,5,30,21.0,neutral or dissatisfied +4420,81079,Male,Loyal Customer,39,Business travel,Business,1968,2,1,5,5,3,3,4,2,2,2,2,3,2,2,42,31.0,neutral or dissatisfied +4421,54903,Female,Loyal Customer,44,Personal Travel,Eco,934,1,5,1,4,4,5,4,1,1,1,1,5,1,5,0,4.0,neutral or dissatisfied +4422,103255,Male,Loyal Customer,41,Business travel,Business,2990,1,1,1,1,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +4423,116203,Male,Loyal Customer,16,Personal Travel,Eco,333,3,5,3,1,4,3,2,4,5,2,5,5,4,4,8,3.0,neutral or dissatisfied +4424,118601,Female,Loyal Customer,55,Business travel,Business,451,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +4425,74171,Male,Loyal Customer,12,Personal Travel,Eco,592,4,2,4,3,3,4,3,3,2,4,4,1,4,3,0,0.0,satisfied +4426,90141,Male,Loyal Customer,32,Business travel,Eco,1127,5,4,4,4,5,5,5,5,2,4,4,3,3,5,0,0.0,satisfied +4427,122608,Male,Loyal Customer,38,Business travel,Business,728,3,2,2,2,1,3,2,3,3,2,3,4,3,1,28,30.0,neutral or dissatisfied +4428,101119,Male,Loyal Customer,29,Business travel,Business,1730,1,2,2,2,1,1,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +4429,67514,Female,Loyal Customer,40,Business travel,Business,1205,1,1,1,1,2,4,4,1,1,1,1,2,1,3,2,0.0,neutral or dissatisfied +4430,54692,Male,Loyal Customer,61,Business travel,Business,854,2,4,4,4,5,3,3,2,2,2,2,2,2,4,11,0.0,neutral or dissatisfied +4431,66619,Male,Loyal Customer,33,Business travel,Business,802,1,1,1,1,4,4,4,4,4,5,4,4,5,4,14,4.0,satisfied +4432,30421,Female,Loyal Customer,43,Business travel,Eco,1014,4,3,3,3,5,3,3,4,4,4,4,5,4,5,0,0.0,satisfied +4433,5660,Male,Loyal Customer,55,Business travel,Business,299,4,4,4,4,4,5,5,4,4,4,4,4,4,4,11,8.0,satisfied +4434,74434,Female,disloyal Customer,37,Business travel,Business,1464,3,3,3,3,1,3,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +4435,16095,Female,disloyal Customer,38,Business travel,Eco,303,3,1,3,2,4,3,2,4,3,5,2,1,2,4,23,6.0,neutral or dissatisfied +4436,5787,Male,disloyal Customer,26,Business travel,Business,157,5,0,5,3,4,5,4,4,5,4,5,3,4,4,96,117.0,satisfied +4437,118034,Male,Loyal Customer,56,Business travel,Business,2396,2,2,2,2,4,4,4,5,5,5,5,3,5,3,9,0.0,satisfied +4438,69837,Male,disloyal Customer,27,Business travel,Eco,945,3,3,3,2,3,3,3,3,2,1,4,1,5,3,0,0.0,neutral or dissatisfied +4439,74896,Male,disloyal Customer,36,Business travel,Business,2475,3,3,3,2,5,3,5,5,3,3,4,4,5,5,5,0.0,neutral or dissatisfied +4440,48120,Male,Loyal Customer,38,Business travel,Business,192,0,4,0,1,1,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +4441,101808,Female,Loyal Customer,35,Business travel,Eco,1521,4,2,3,2,4,4,4,4,3,1,4,3,4,4,28,25.0,neutral or dissatisfied +4442,18722,Female,Loyal Customer,52,Personal Travel,Eco Plus,253,3,3,3,3,4,4,4,4,4,3,4,4,4,4,84,80.0,neutral or dissatisfied +4443,114186,Female,disloyal Customer,46,Business travel,Business,967,4,4,4,1,5,4,5,5,3,2,5,4,4,5,10,0.0,neutral or dissatisfied +4444,52123,Male,Loyal Customer,36,Business travel,Eco Plus,438,3,1,1,1,3,3,3,3,4,5,4,4,3,3,0,9.0,neutral or dissatisfied +4445,34395,Male,disloyal Customer,8,Business travel,Eco,612,2,2,2,3,5,2,5,5,3,5,3,4,4,5,0,0.0,neutral or dissatisfied +4446,21982,Male,Loyal Customer,18,Personal Travel,Eco,448,2,3,2,3,5,2,5,5,4,1,2,1,4,5,0,0.0,neutral or dissatisfied +4447,106652,Female,Loyal Customer,39,Business travel,Business,1590,4,4,4,4,3,5,4,5,5,4,5,4,5,3,3,0.0,satisfied +4448,117647,Female,Loyal Customer,40,Business travel,Business,872,1,1,1,1,2,4,4,4,4,4,4,3,4,4,0,3.0,satisfied +4449,30827,Male,Loyal Customer,30,Business travel,Business,955,1,1,1,1,5,5,5,5,2,5,2,3,4,5,0,4.0,satisfied +4450,9237,Female,disloyal Customer,38,Business travel,Eco,100,1,5,1,1,5,1,5,5,2,5,3,1,4,5,60,52.0,neutral or dissatisfied +4451,39459,Male,Loyal Customer,57,Personal Travel,Eco,129,2,0,2,3,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +4452,44603,Male,Loyal Customer,30,Business travel,Business,566,1,2,4,2,1,1,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +4453,129812,Male,Loyal Customer,69,Personal Travel,Eco,447,1,5,1,2,4,1,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +4454,99130,Male,Loyal Customer,8,Personal Travel,Eco,419,2,5,2,4,5,2,5,5,4,1,3,3,1,5,7,0.0,neutral or dissatisfied +4455,35128,Male,Loyal Customer,25,Business travel,Business,3572,2,5,5,5,2,2,2,2,2,4,3,2,4,2,0,0.0,neutral or dissatisfied +4456,62147,Male,Loyal Customer,60,Business travel,Business,2454,4,4,4,4,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +4457,713,Male,Loyal Customer,54,Business travel,Business,89,2,3,3,3,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +4458,14347,Female,Loyal Customer,29,Personal Travel,Eco,395,2,4,2,4,3,2,4,3,4,4,5,4,4,3,55,63.0,neutral or dissatisfied +4459,99193,Female,Loyal Customer,29,Business travel,Business,351,1,1,1,1,4,4,4,4,4,3,5,3,4,4,0,5.0,satisfied +4460,78499,Female,Loyal Customer,44,Business travel,Business,126,4,4,4,4,2,3,1,5,5,5,5,1,5,3,0,0.0,satisfied +4461,70288,Male,Loyal Customer,28,Business travel,Business,852,4,4,4,4,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +4462,62191,Male,Loyal Customer,55,Business travel,Business,1065,3,3,3,3,1,4,1,4,4,4,4,2,4,3,0,0.0,satisfied +4463,37058,Female,Loyal Customer,25,Business travel,Business,2192,3,1,3,3,3,3,3,3,5,1,3,2,3,3,0,0.0,satisfied +4464,17593,Male,Loyal Customer,50,Personal Travel,Eco Plus,1034,4,4,4,1,3,4,3,3,3,5,5,5,4,3,2,0.0,satisfied +4465,88377,Female,disloyal Customer,37,Business travel,Business,581,3,3,3,1,2,3,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +4466,83700,Male,Loyal Customer,58,Personal Travel,Eco,577,2,4,2,5,1,2,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +4467,69577,Female,Loyal Customer,70,Business travel,Business,2146,1,2,2,2,1,1,1,3,2,3,3,1,4,1,0,3.0,neutral or dissatisfied +4468,63641,Female,Loyal Customer,54,Personal Travel,Eco,602,3,4,4,2,4,5,4,5,5,4,5,3,5,5,1,6.0,neutral or dissatisfied +4469,15208,Male,Loyal Customer,65,Personal Travel,Business,445,3,4,3,2,2,4,5,2,2,3,2,4,2,5,0,1.0,neutral or dissatisfied +4470,3828,Male,Loyal Customer,22,Business travel,Business,650,1,3,3,3,1,1,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +4471,128041,Male,Loyal Customer,57,Personal Travel,Eco,1440,4,4,4,4,2,4,2,2,4,2,3,3,5,2,16,36.0,neutral or dissatisfied +4472,22322,Female,disloyal Customer,23,Business travel,Eco,143,5,3,5,3,4,5,1,4,5,3,3,5,3,4,0,0.0,satisfied +4473,55487,Male,Loyal Customer,51,Business travel,Business,1739,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +4474,95717,Female,disloyal Customer,37,Business travel,Business,237,2,2,2,2,2,2,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +4475,72390,Female,disloyal Customer,32,Business travel,Business,985,4,4,4,3,2,4,2,2,5,5,4,4,5,2,5,0.0,neutral or dissatisfied +4476,11950,Female,Loyal Customer,36,Personal Travel,Eco,781,2,3,2,3,3,2,4,3,3,3,2,3,3,3,32,16.0,neutral or dissatisfied +4477,23888,Female,disloyal Customer,22,Business travel,Eco,589,2,0,2,4,1,2,1,1,3,2,3,4,3,1,13,9.0,neutral or dissatisfied +4478,73838,Female,Loyal Customer,29,Business travel,Business,1709,2,2,2,2,5,5,5,5,5,3,4,5,4,5,0,14.0,satisfied +4479,4839,Female,Loyal Customer,42,Business travel,Business,3065,4,4,4,4,4,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +4480,33980,Female,disloyal Customer,24,Business travel,Eco,987,1,1,1,3,4,1,4,4,5,2,5,5,2,4,14,2.0,neutral or dissatisfied +4481,62420,Female,Loyal Customer,28,Personal Travel,Eco,2457,4,4,4,2,1,4,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +4482,137,Female,Loyal Customer,45,Business travel,Business,227,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,16.0,satisfied +4483,116382,Male,Loyal Customer,37,Personal Travel,Eco,333,3,5,5,5,1,5,1,1,5,2,5,3,4,1,0,2.0,neutral or dissatisfied +4484,1845,Male,Loyal Customer,37,Personal Travel,Eco,408,3,5,3,1,3,3,3,3,5,5,3,1,3,3,0,0.0,neutral or dissatisfied +4485,115813,Male,Loyal Customer,40,Business travel,Eco,417,4,1,1,1,4,4,4,4,2,3,2,5,1,4,0,0.0,satisfied +4486,89291,Male,Loyal Customer,46,Business travel,Business,453,1,1,5,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +4487,115322,Female,Loyal Customer,42,Business travel,Eco,480,2,4,4,4,2,4,3,2,2,2,2,3,2,1,0,11.0,neutral or dissatisfied +4488,60053,Male,Loyal Customer,30,Personal Travel,Eco Plus,997,4,3,4,1,5,4,4,5,1,4,4,4,3,5,1,0.0,neutral or dissatisfied +4489,3444,Female,Loyal Customer,23,Personal Travel,Eco,296,4,4,4,3,4,4,4,4,1,2,3,2,4,4,55,63.0,neutral or dissatisfied +4490,48504,Male,disloyal Customer,30,Business travel,Eco,737,4,4,4,3,2,4,2,2,5,1,4,1,3,2,22,,neutral or dissatisfied +4491,75125,Female,Loyal Customer,42,Business travel,Business,1744,5,5,5,5,4,4,5,4,4,4,4,4,4,5,23,15.0,satisfied +4492,29573,Male,Loyal Customer,44,Business travel,Eco,680,5,3,3,3,5,5,5,5,3,4,3,1,2,5,0,0.0,satisfied +4493,4741,Female,Loyal Customer,57,Personal Travel,Eco,888,2,3,2,4,4,5,4,3,3,2,2,5,3,5,107,104.0,neutral or dissatisfied +4494,104224,Male,Loyal Customer,26,Personal Travel,Eco,680,3,4,3,1,2,3,2,2,3,4,4,4,5,2,4,0.0,neutral or dissatisfied +4495,5552,Female,Loyal Customer,33,Business travel,Eco Plus,404,4,4,4,4,4,4,4,4,3,4,3,2,4,4,0,0.0,neutral or dissatisfied +4496,16502,Female,Loyal Customer,27,Personal Travel,Eco,246,4,2,4,4,3,4,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +4497,121291,Female,Loyal Customer,56,Business travel,Business,1009,5,5,5,5,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +4498,30242,Female,Loyal Customer,37,Personal Travel,Eco,896,3,2,3,4,4,3,4,4,2,5,4,1,3,4,0,7.0,neutral or dissatisfied +4499,46405,Male,Loyal Customer,15,Personal Travel,Business,649,3,5,3,5,1,3,1,1,2,3,2,4,3,1,14,11.0,neutral or dissatisfied +4500,8002,Male,Loyal Customer,44,Personal Travel,Business,335,1,4,1,3,4,5,5,1,1,1,1,3,1,5,0,2.0,neutral or dissatisfied +4501,15657,Female,Loyal Customer,33,Business travel,Eco Plus,258,4,4,4,4,4,4,4,4,1,5,1,5,5,4,0,0.0,satisfied +4502,96004,Male,Loyal Customer,58,Business travel,Business,2145,4,4,4,4,5,5,4,5,5,5,5,3,5,5,20,16.0,satisfied +4503,128465,Female,Loyal Customer,16,Personal Travel,Eco,304,1,2,1,2,3,1,1,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +4504,1467,Male,Loyal Customer,49,Personal Travel,Eco,695,1,4,1,4,3,1,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +4505,8742,Male,disloyal Customer,35,Business travel,Business,280,1,1,1,4,2,1,2,2,1,5,4,4,4,2,4,22.0,neutral or dissatisfied +4506,19492,Male,Loyal Customer,33,Business travel,Eco,508,4,5,5,5,5,5,5,5,4,2,2,2,5,5,0,0.0,satisfied +4507,70348,Female,Loyal Customer,49,Personal Travel,Eco,986,0,4,0,4,2,3,4,5,5,0,1,1,5,1,0,0.0,satisfied +4508,72956,Female,disloyal Customer,35,Business travel,Business,1089,1,2,2,3,2,2,3,2,5,4,5,5,4,2,2,0.0,neutral or dissatisfied +4509,77425,Male,Loyal Customer,11,Personal Travel,Eco,626,3,5,4,5,3,4,3,3,4,5,1,3,4,3,0,26.0,neutral or dissatisfied +4510,81845,Male,Loyal Customer,66,Personal Travel,Eco,1416,1,4,1,2,4,1,1,4,4,2,3,5,4,4,0,0.0,neutral or dissatisfied +4511,30853,Female,Loyal Customer,42,Personal Travel,Eco Plus,841,3,5,3,3,4,5,5,1,1,3,1,3,1,4,15,16.0,neutral or dissatisfied +4512,80338,Male,Loyal Customer,26,Business travel,Business,2139,5,5,5,5,4,4,4,4,4,4,4,3,5,4,2,0.0,satisfied +4513,29015,Male,disloyal Customer,27,Business travel,Business,271,3,3,3,4,4,3,4,4,4,5,1,1,3,4,2,0.0,neutral or dissatisfied +4514,42644,Male,Loyal Customer,37,Personal Travel,Eco,546,1,1,1,3,3,1,3,3,4,1,3,4,3,3,0,6.0,neutral or dissatisfied +4515,101357,Female,Loyal Customer,40,Business travel,Business,1986,5,5,5,5,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +4516,67309,Female,disloyal Customer,29,Business travel,Eco Plus,985,3,3,3,3,1,3,1,1,4,3,4,1,3,1,22,28.0,neutral or dissatisfied +4517,89501,Female,Loyal Customer,52,Business travel,Business,2284,4,4,4,4,1,5,5,4,4,4,4,2,4,3,0,2.0,satisfied +4518,32835,Female,Loyal Customer,63,Personal Travel,Eco,163,5,4,5,3,4,5,4,2,2,5,2,4,2,5,0,0.0,satisfied +4519,75733,Female,Loyal Customer,49,Business travel,Business,813,1,1,1,1,4,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +4520,75408,Male,disloyal Customer,21,Business travel,Eco,745,4,4,4,5,1,4,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +4521,63138,Male,disloyal Customer,36,Business travel,Business,447,2,2,2,2,3,2,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +4522,104564,Male,Loyal Customer,42,Business travel,Business,2045,4,4,4,4,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +4523,125969,Female,Loyal Customer,39,Business travel,Business,2419,5,5,4,5,4,4,4,5,5,5,5,3,5,4,0,1.0,satisfied +4524,33928,Male,Loyal Customer,31,Business travel,Eco Plus,818,5,4,4,4,5,5,5,5,3,1,1,4,1,5,0,0.0,satisfied +4525,147,Female,Loyal Customer,47,Business travel,Business,1946,2,1,1,1,2,2,2,4,1,4,4,2,2,2,117,136.0,neutral or dissatisfied +4526,125646,Female,Loyal Customer,34,Business travel,Business,857,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +4527,63488,Female,Loyal Customer,27,Business travel,Business,3461,4,4,4,4,5,4,5,5,3,4,5,5,5,5,0,0.0,satisfied +4528,98227,Male,Loyal Customer,43,Business travel,Business,1072,1,1,1,1,5,4,5,5,5,5,5,3,5,4,16,6.0,satisfied +4529,4205,Female,disloyal Customer,34,Business travel,Business,888,3,3,3,1,1,3,1,1,5,5,5,3,4,1,0,16.0,neutral or dissatisfied +4530,57780,Male,Loyal Customer,38,Personal Travel,Eco,2704,5,3,5,2,5,4,3,1,5,3,5,3,1,3,2,0.0,satisfied +4531,43147,Male,Loyal Customer,15,Personal Travel,Eco Plus,236,3,5,3,1,4,3,4,4,4,4,5,5,4,4,0,5.0,neutral or dissatisfied +4532,21268,Male,Loyal Customer,67,Personal Travel,Business,620,1,5,2,4,2,3,3,4,2,5,5,3,4,3,165,142.0,neutral or dissatisfied +4533,103933,Female,Loyal Customer,30,Business travel,Business,770,2,2,2,2,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +4534,102193,Female,Loyal Customer,20,Business travel,Business,226,1,4,4,4,1,1,1,1,2,3,4,1,3,1,26,18.0,neutral or dissatisfied +4535,108441,Male,Loyal Customer,56,Business travel,Business,1444,1,2,3,2,2,3,4,1,1,1,1,1,1,3,0,3.0,neutral or dissatisfied +4536,122927,Male,Loyal Customer,23,Business travel,Business,2920,1,1,1,1,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +4537,40632,Female,Loyal Customer,49,Business travel,Eco Plus,391,5,3,3,3,5,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +4538,12216,Male,Loyal Customer,43,Business travel,Business,3200,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,2.0,satisfied +4539,12379,Male,Loyal Customer,68,Business travel,Business,3744,0,4,0,5,1,1,2,4,4,2,2,5,4,5,0,0.0,satisfied +4540,42830,Male,Loyal Customer,42,Business travel,Eco,328,5,3,2,3,5,5,5,5,1,2,3,4,1,5,0,0.0,satisfied +4541,51397,Male,Loyal Customer,15,Personal Travel,Eco Plus,109,3,1,3,4,3,3,3,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +4542,3926,Male,Loyal Customer,44,Business travel,Business,213,4,4,4,4,4,5,4,4,4,4,4,5,4,3,5,1.0,satisfied +4543,63967,Male,Loyal Customer,35,Business travel,Business,1172,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +4544,36281,Female,disloyal Customer,42,Business travel,Eco Plus,212,2,2,2,4,5,2,5,5,3,4,4,4,2,5,0,0.0,neutral or dissatisfied +4545,63829,Female,Loyal Customer,48,Business travel,Business,3816,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,1.0,satisfied +4546,52568,Female,disloyal Customer,33,Business travel,Eco,119,3,2,3,3,3,3,1,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +4547,74272,Male,Loyal Customer,35,Business travel,Business,2288,1,1,2,1,4,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +4548,24337,Female,Loyal Customer,47,Business travel,Eco,634,3,1,1,1,2,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +4549,6951,Female,Loyal Customer,9,Personal Travel,Eco,501,3,4,3,1,5,3,5,5,4,5,4,5,5,5,15,14.0,neutral or dissatisfied +4550,116366,Male,Loyal Customer,9,Personal Travel,Eco,337,3,3,3,3,2,3,2,2,4,3,1,1,3,2,47,40.0,neutral or dissatisfied +4551,38918,Male,disloyal Customer,35,Business travel,Eco,298,3,0,3,4,5,3,5,5,4,5,1,2,3,5,0,0.0,neutral or dissatisfied +4552,48815,Male,Loyal Customer,16,Personal Travel,Business,109,2,4,2,1,1,2,1,1,4,4,4,3,5,1,0,4.0,neutral or dissatisfied +4553,27401,Male,Loyal Customer,43,Business travel,Eco,679,2,4,4,4,2,2,2,2,2,4,3,2,4,2,9,0.0,neutral or dissatisfied +4554,18323,Female,Loyal Customer,36,Personal Travel,Eco,715,1,5,1,4,5,1,5,5,4,5,3,2,4,5,114,103.0,neutral or dissatisfied +4555,126381,Male,Loyal Customer,19,Personal Travel,Eco,328,2,0,2,1,3,2,1,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +4556,11657,Male,Loyal Customer,24,Personal Travel,Eco,837,1,5,1,3,4,1,4,4,3,1,4,2,5,4,27,23.0,neutral or dissatisfied +4557,58629,Male,Loyal Customer,41,Business travel,Business,867,2,2,3,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +4558,33947,Female,Loyal Customer,21,Personal Travel,Eco,1072,5,4,5,2,3,5,3,3,4,4,5,5,4,3,0,0.0,satisfied +4559,67978,Female,Loyal Customer,39,Business travel,Business,3235,2,2,2,2,2,5,4,5,5,4,5,5,5,5,11,0.0,satisfied +4560,35616,Female,Loyal Customer,37,Personal Travel,Eco Plus,1035,3,5,3,2,4,3,4,4,5,5,5,5,4,4,0,21.0,neutral or dissatisfied +4561,26975,Male,Loyal Customer,53,Business travel,Eco,867,3,2,5,2,3,3,3,3,4,3,4,1,1,3,0,15.0,satisfied +4562,118269,Female,Loyal Customer,24,Business travel,Business,2480,1,1,1,1,4,4,4,4,4,3,5,3,5,4,3,0.0,satisfied +4563,24320,Male,Loyal Customer,44,Business travel,Business,1048,4,4,4,4,4,4,2,3,3,3,3,2,3,1,0,0.0,satisfied +4564,11489,Female,Loyal Customer,24,Personal Travel,Eco Plus,312,1,4,4,4,3,4,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +4565,10560,Male,Loyal Customer,47,Business travel,Business,3672,4,2,2,2,5,4,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +4566,123690,Male,disloyal Customer,16,Business travel,Eco,214,2,4,1,3,4,1,4,4,1,5,4,4,4,4,14,24.0,neutral or dissatisfied +4567,109307,Female,Loyal Customer,53,Business travel,Business,2734,1,1,4,1,5,4,5,4,4,4,4,5,4,3,54,33.0,satisfied +4568,69687,Female,disloyal Customer,23,Business travel,Eco,169,1,2,1,4,1,1,4,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +4569,89927,Male,disloyal Customer,36,Business travel,Business,1087,2,1,1,5,3,1,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +4570,29062,Male,Loyal Customer,70,Personal Travel,Eco,954,4,5,4,5,1,4,4,1,1,1,1,5,3,1,0,0.0,neutral or dissatisfied +4571,83523,Female,Loyal Customer,27,Personal Travel,Eco,946,3,4,3,2,3,3,3,3,1,2,4,4,4,3,0,26.0,neutral or dissatisfied +4572,125923,Female,Loyal Customer,53,Personal Travel,Eco,861,4,4,4,3,4,4,4,3,3,4,3,5,3,5,20,5.0,neutral or dissatisfied +4573,90726,Female,disloyal Customer,23,Business travel,Business,404,5,4,5,3,4,5,4,4,4,4,5,3,5,4,0,0.0,satisfied +4574,293,Male,Loyal Customer,52,Business travel,Business,1517,2,4,4,4,5,3,3,2,2,1,2,1,2,2,43,17.0,neutral or dissatisfied +4575,90428,Female,disloyal Customer,36,Business travel,Business,404,2,2,2,2,1,2,1,1,4,3,5,4,4,1,6,15.0,neutral or dissatisfied +4576,8095,Male,Loyal Customer,38,Business travel,Business,402,4,4,4,4,4,4,5,3,3,3,3,5,3,4,0,9.0,satisfied +4577,124934,Female,Loyal Customer,45,Personal Travel,Eco,728,2,3,2,4,2,4,1,5,5,2,5,4,5,3,16,27.0,neutral or dissatisfied +4578,7312,Male,Loyal Customer,51,Business travel,Eco Plus,135,3,5,5,5,3,3,3,3,2,2,1,4,2,3,0,18.0,neutral or dissatisfied +4579,57118,Male,Loyal Customer,51,Business travel,Eco,1222,1,4,4,4,1,1,1,3,1,2,2,1,1,1,151,127.0,neutral or dissatisfied +4580,125121,Male,Loyal Customer,16,Personal Travel,Eco,361,3,5,3,5,5,3,4,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +4581,2368,Male,Loyal Customer,12,Personal Travel,Eco,925,3,1,3,4,4,3,4,4,4,2,3,1,3,4,0,19.0,neutral or dissatisfied +4582,81133,Male,Loyal Customer,70,Personal Travel,Eco,991,0,4,0,5,2,0,2,2,3,2,4,4,4,2,0,0.0,satisfied +4583,83146,Female,Loyal Customer,65,Personal Travel,Eco,957,3,4,3,3,4,4,4,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +4584,122671,Male,Loyal Customer,46,Business travel,Business,2453,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +4585,30504,Female,Loyal Customer,33,Personal Travel,Eco,373,2,5,2,3,5,2,5,5,4,3,4,5,5,5,55,94.0,neutral or dissatisfied +4586,62004,Male,Loyal Customer,51,Business travel,Business,2586,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +4587,106864,Female,Loyal Customer,27,Business travel,Business,3183,1,1,1,1,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +4588,27120,Male,Loyal Customer,33,Business travel,Business,2701,3,3,3,3,5,5,5,5,4,5,5,2,5,5,0,,satisfied +4589,90905,Male,Loyal Customer,38,Business travel,Eco,444,3,4,4,4,3,3,3,3,4,1,3,2,3,3,1,0.0,neutral or dissatisfied +4590,76476,Male,Loyal Customer,36,Business travel,Business,2159,4,4,4,4,4,5,4,5,5,5,5,4,5,5,21,7.0,satisfied +4591,98091,Female,Loyal Customer,26,Personal Travel,Eco,928,4,4,4,4,2,4,2,2,1,2,3,1,5,2,0,0.0,neutral or dissatisfied +4592,4025,Male,Loyal Customer,33,Business travel,Business,2447,4,5,5,5,4,4,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +4593,55576,Male,Loyal Customer,45,Business travel,Business,3923,5,5,5,5,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +4594,63183,Female,Loyal Customer,40,Business travel,Business,2068,4,4,3,4,3,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +4595,28977,Male,Loyal Customer,47,Business travel,Eco,978,4,3,3,3,4,4,4,4,5,2,2,2,3,4,0,0.0,satisfied +4596,83874,Male,Loyal Customer,46,Business travel,Business,1670,1,1,1,1,5,5,5,4,3,3,5,5,5,5,480,471.0,satisfied +4597,48333,Male,Loyal Customer,34,Business travel,Eco,522,4,3,4,3,4,4,4,4,5,3,2,2,5,4,0,0.0,satisfied +4598,97267,Male,Loyal Customer,41,Personal Travel,Eco,296,3,5,2,4,5,2,5,5,4,3,4,5,4,5,0,5.0,neutral or dissatisfied +4599,19155,Female,disloyal Customer,37,Business travel,Eco,304,1,5,1,4,2,1,5,2,5,2,3,1,3,2,0,3.0,neutral or dissatisfied +4600,84757,Female,disloyal Customer,25,Business travel,Business,547,2,4,2,5,4,2,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +4601,92728,Female,disloyal Customer,22,Business travel,Eco,1276,4,4,4,4,3,4,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +4602,62506,Female,disloyal Customer,38,Business travel,Business,911,4,4,4,3,2,4,2,2,4,4,5,4,4,2,4,0.0,satisfied +4603,9175,Female,Loyal Customer,30,Business travel,Business,416,1,2,2,2,1,1,1,1,3,1,3,4,3,1,52,51.0,neutral or dissatisfied +4604,54342,Male,Loyal Customer,48,Business travel,Eco Plus,1597,5,1,1,1,5,5,5,5,1,1,3,2,2,5,14,26.0,satisfied +4605,47031,Male,Loyal Customer,34,Business travel,Business,602,4,2,2,2,5,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +4606,54979,Female,Loyal Customer,49,Business travel,Business,1635,4,4,4,4,4,4,5,5,5,5,5,3,5,5,7,0.0,satisfied +4607,127327,Female,Loyal Customer,18,Business travel,Business,507,4,4,4,4,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +4608,118492,Female,Loyal Customer,55,Business travel,Business,370,1,1,1,1,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +4609,58846,Female,disloyal Customer,47,Business travel,Business,783,3,3,3,2,1,3,1,1,3,4,4,5,4,1,12,9.0,neutral or dissatisfied +4610,9870,Female,Loyal Customer,47,Business travel,Eco Plus,642,2,3,3,3,2,3,3,2,2,2,2,2,2,2,0,4.0,neutral or dissatisfied +4611,68701,Male,Loyal Customer,67,Personal Travel,Eco,237,4,4,4,1,1,4,1,1,3,4,4,4,4,1,0,0.0,satisfied +4612,85932,Female,disloyal Customer,37,Business travel,Business,447,5,5,5,3,1,5,1,1,4,5,4,4,5,1,0,0.0,satisfied +4613,129467,Male,Loyal Customer,53,Business travel,Business,2704,4,4,4,4,2,4,4,4,4,4,4,5,4,5,1,6.0,satisfied +4614,71901,Male,Loyal Customer,53,Personal Travel,Eco,1726,5,4,5,2,4,4,3,4,5,4,5,4,5,4,0,0.0,satisfied +4615,89990,Female,disloyal Customer,24,Business travel,Eco,957,4,4,4,3,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +4616,9543,Female,Loyal Customer,47,Business travel,Business,229,1,1,1,1,2,5,5,5,5,5,5,5,5,5,35,22.0,satisfied +4617,109612,Male,Loyal Customer,54,Business travel,Business,808,3,3,3,3,4,4,4,5,4,5,5,4,4,4,241,227.0,satisfied +4618,121995,Male,Loyal Customer,52,Business travel,Business,130,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +4619,55144,Male,Loyal Customer,23,Personal Travel,Eco,1609,1,5,1,2,5,1,3,5,5,3,3,4,5,5,3,7.0,neutral or dissatisfied +4620,38095,Male,disloyal Customer,29,Business travel,Eco,1121,3,3,3,3,3,3,3,3,4,4,2,4,2,3,24,20.0,neutral or dissatisfied +4621,72432,Male,Loyal Customer,37,Business travel,Business,1119,2,2,1,2,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +4622,55677,Male,Loyal Customer,48,Business travel,Business,895,5,5,5,5,2,4,4,2,2,2,2,3,2,5,0,6.0,satisfied +4623,109853,Male,Loyal Customer,49,Business travel,Business,2471,1,1,1,1,4,4,5,5,5,5,5,5,5,4,59,77.0,satisfied +4624,75978,Female,disloyal Customer,38,Business travel,Eco,297,2,4,2,2,4,2,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +4625,112130,Male,disloyal Customer,22,Business travel,Business,895,4,0,4,5,2,4,1,2,5,3,4,3,4,2,0,0.0,satisfied +4626,23300,Male,Loyal Customer,36,Business travel,Business,3667,1,1,1,1,3,3,1,5,5,5,5,2,5,4,36,36.0,satisfied +4627,9910,Female,disloyal Customer,21,Business travel,Business,508,5,0,5,3,2,5,2,2,3,3,5,3,5,2,0,0.0,satisfied +4628,79911,Male,disloyal Customer,10,Business travel,Business,1069,3,4,3,4,1,3,2,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +4629,127164,Female,Loyal Customer,14,Personal Travel,Eco,338,4,3,1,3,2,1,1,2,3,5,2,1,2,2,0,0.0,neutral or dissatisfied +4630,33781,Female,Loyal Customer,19,Business travel,Business,3197,5,5,5,5,5,5,5,5,4,2,4,4,2,5,0,0.0,satisfied +4631,373,Male,Loyal Customer,43,Business travel,Business,2169,3,3,3,3,5,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +4632,102568,Male,disloyal Customer,25,Business travel,Business,386,4,4,4,5,2,4,3,2,4,2,4,3,5,2,94,94.0,neutral or dissatisfied +4633,121769,Male,Loyal Customer,48,Business travel,Business,366,3,3,3,3,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +4634,56359,Female,Loyal Customer,52,Personal Travel,Eco,200,3,3,0,4,3,3,3,5,5,0,5,2,5,4,0,0.0,neutral or dissatisfied +4635,80179,Female,Loyal Customer,58,Personal Travel,Eco,2475,2,0,2,1,2,1,1,4,5,4,5,1,4,1,61,102.0,neutral or dissatisfied +4636,89596,Female,disloyal Customer,25,Business travel,Eco,950,2,2,2,2,4,2,4,4,4,4,2,1,2,4,0,0.0,neutral or dissatisfied +4637,83518,Male,Loyal Customer,64,Personal Travel,Eco,946,3,5,3,1,4,3,4,4,2,1,5,4,4,4,2,0.0,neutral or dissatisfied +4638,82609,Male,disloyal Customer,27,Business travel,Eco,528,2,3,2,4,3,2,2,3,3,2,3,3,3,3,8,3.0,neutral or dissatisfied +4639,94482,Male,Loyal Customer,40,Business travel,Business,2356,0,4,0,4,5,4,5,4,4,4,4,5,4,4,4,0.0,satisfied +4640,77557,Female,Loyal Customer,43,Personal Travel,Eco,986,5,5,5,1,4,4,5,4,4,5,4,5,4,4,12,0.0,satisfied +4641,101753,Male,disloyal Customer,38,Business travel,Eco,927,2,2,2,2,1,2,1,1,3,3,1,2,2,1,0,0.0,neutral or dissatisfied +4642,50088,Female,Loyal Customer,75,Business travel,Business,2802,1,2,5,2,1,3,4,4,4,3,1,2,4,3,0,0.0,neutral or dissatisfied +4643,128260,Male,disloyal Customer,39,Business travel,Business,338,4,4,4,4,4,4,4,4,4,4,4,1,3,4,0,0.0,neutral or dissatisfied +4644,29222,Female,Loyal Customer,39,Business travel,Business,1672,4,2,2,2,3,3,4,4,4,4,4,2,4,4,0,11.0,neutral or dissatisfied +4645,6112,Female,Loyal Customer,20,Personal Travel,Business,501,3,5,3,5,4,3,5,4,5,3,4,3,4,4,98,96.0,neutral or dissatisfied +4646,21081,Female,Loyal Customer,39,Business travel,Eco,332,2,4,4,4,2,2,2,2,1,5,5,1,1,2,1,17.0,satisfied +4647,99646,Female,disloyal Customer,50,Business travel,Business,1670,2,2,2,5,2,2,2,2,5,3,5,5,5,2,0,4.0,neutral or dissatisfied +4648,74851,Male,Loyal Customer,27,Business travel,Eco,2136,2,5,5,5,2,2,2,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +4649,128411,Male,disloyal Customer,23,Business travel,Eco,370,2,1,2,3,2,2,2,2,4,4,3,1,3,2,52,47.0,neutral or dissatisfied +4650,64281,Male,Loyal Customer,48,Business travel,Business,2722,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +4651,35100,Male,Loyal Customer,31,Business travel,Business,1028,3,3,3,3,5,5,5,5,1,5,3,3,2,5,0,49.0,satisfied +4652,121529,Male,Loyal Customer,42,Business travel,Business,3678,2,2,2,2,4,5,5,5,5,5,5,4,5,4,3,0.0,satisfied +4653,22267,Male,Loyal Customer,40,Business travel,Business,1653,3,3,3,3,1,3,3,5,5,5,4,3,5,4,10,1.0,satisfied +4654,937,Male,Loyal Customer,61,Business travel,Business,3504,2,5,5,5,3,4,3,2,2,2,2,1,2,3,127,124.0,neutral or dissatisfied +4655,21783,Female,disloyal Customer,25,Business travel,Eco,352,1,0,1,3,4,1,4,4,4,1,2,5,1,4,12,5.0,neutral or dissatisfied +4656,77636,Female,Loyal Customer,54,Business travel,Business,2382,4,4,2,4,5,4,5,5,5,5,5,5,5,3,57,49.0,satisfied +4657,25739,Male,Loyal Customer,26,Personal Travel,Eco,432,2,5,4,3,2,4,1,2,3,4,5,5,5,2,1,0.0,neutral or dissatisfied +4658,33029,Male,Loyal Customer,54,Personal Travel,Eco,101,3,5,3,1,1,3,1,1,5,2,5,3,4,1,0,3.0,neutral or dissatisfied +4659,62759,Male,disloyal Customer,48,Business travel,Eco,1119,1,0,0,4,2,1,2,2,4,3,4,3,3,2,6,1.0,neutral or dissatisfied +4660,16051,Male,Loyal Customer,39,Business travel,Business,744,5,5,5,5,5,5,5,4,4,5,4,5,4,4,5,16.0,satisfied +4661,56254,Male,Loyal Customer,41,Business travel,Business,3479,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +4662,120602,Male,Loyal Customer,25,Personal Travel,Eco Plus,980,4,1,4,4,3,4,2,3,1,3,4,4,3,3,0,6.0,neutral or dissatisfied +4663,69995,Male,Loyal Customer,68,Personal Travel,Eco,236,4,4,0,1,1,0,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +4664,103996,Male,disloyal Customer,12,Business travel,Eco,1084,5,5,5,4,4,5,4,4,3,4,4,5,4,4,10,3.0,satisfied +4665,92901,Male,Loyal Customer,46,Business travel,Business,134,5,5,5,5,3,4,5,4,4,4,4,4,4,3,12,16.0,satisfied +4666,129338,Female,Loyal Customer,38,Business travel,Business,3297,3,3,3,3,1,2,1,5,5,5,5,1,5,5,0,0.0,satisfied +4667,128319,Female,Loyal Customer,52,Business travel,Business,3093,4,4,4,4,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +4668,79508,Female,Loyal Customer,51,Business travel,Business,2643,2,5,5,5,5,4,3,2,2,2,2,3,2,4,0,14.0,neutral or dissatisfied +4669,109179,Female,Loyal Customer,57,Business travel,Eco,391,2,1,1,1,4,4,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +4670,114394,Male,disloyal Customer,23,Business travel,Business,480,5,5,5,2,3,5,3,3,3,5,5,4,4,3,0,0.0,satisfied +4671,51691,Female,disloyal Customer,39,Business travel,Eco,369,2,0,3,2,2,3,4,2,4,4,3,1,5,2,0,0.0,neutral or dissatisfied +4672,124854,Female,Loyal Customer,58,Personal Travel,Eco,280,1,4,1,1,3,5,4,5,5,1,5,4,5,4,9,38.0,neutral or dissatisfied +4673,85701,Female,Loyal Customer,24,Business travel,Business,1547,1,1,1,1,3,3,3,3,2,1,4,5,1,3,0,0.0,satisfied +4674,11362,Female,Loyal Customer,30,Personal Travel,Eco,140,2,4,0,4,4,0,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +4675,65018,Female,Loyal Customer,43,Business travel,Business,469,4,1,1,1,2,3,4,4,4,4,4,2,4,4,99,99.0,neutral or dissatisfied +4676,6732,Male,Loyal Customer,60,Business travel,Business,3822,5,5,5,5,2,4,5,4,4,4,4,4,4,4,2,0.0,satisfied +4677,65434,Male,Loyal Customer,60,Business travel,Business,2165,4,4,4,4,3,4,4,5,5,5,5,3,5,4,60,98.0,satisfied +4678,3893,Male,disloyal Customer,38,Business travel,Business,213,4,3,3,4,2,3,3,2,3,2,4,3,4,2,0,0.0,satisfied +4679,129227,Male,Loyal Customer,53,Business travel,Business,1235,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +4680,128912,Male,Loyal Customer,62,Personal Travel,Eco,2248,4,4,4,4,2,4,2,2,2,5,3,4,5,2,56,34.0,neutral or dissatisfied +4681,43369,Female,Loyal Customer,38,Personal Travel,Eco,436,2,5,2,4,5,2,4,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +4682,97247,Female,Loyal Customer,59,Business travel,Business,296,5,5,5,5,5,4,5,5,5,5,5,3,5,4,5,12.0,satisfied +4683,111601,Female,Loyal Customer,18,Personal Travel,Eco Plus,794,2,4,2,3,1,2,4,1,3,5,4,4,5,1,6,0.0,neutral or dissatisfied +4684,44427,Male,Loyal Customer,59,Business travel,Eco,542,2,3,3,3,2,2,2,2,1,5,1,1,5,2,15,9.0,satisfied +4685,33019,Male,Loyal Customer,7,Personal Travel,Eco,163,1,4,0,1,1,0,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +4686,91770,Male,Loyal Customer,34,Business travel,Business,2431,3,2,2,2,5,3,4,3,3,2,3,4,3,1,16,9.0,neutral or dissatisfied +4687,2205,Female,Loyal Customer,46,Personal Travel,Eco,685,2,5,2,4,3,4,4,2,2,2,2,4,2,3,9,8.0,neutral or dissatisfied +4688,55447,Female,Loyal Customer,34,Personal Travel,Eco,2521,4,5,4,1,5,4,1,5,2,1,3,1,2,5,100,,neutral or dissatisfied +4689,20848,Female,Loyal Customer,40,Personal Travel,Eco,534,2,4,2,1,1,2,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +4690,120082,Female,Loyal Customer,47,Personal Travel,Eco,683,0,5,0,3,2,5,4,1,1,0,1,4,1,4,0,0.0,satisfied +4691,42576,Male,Loyal Customer,33,Business travel,Eco,296,2,1,1,1,2,2,2,2,3,1,4,4,3,2,0,7.0,neutral or dissatisfied +4692,118277,Female,disloyal Customer,25,Business travel,Business,639,4,0,4,3,4,4,5,4,5,2,5,5,4,4,23,23.0,satisfied +4693,29164,Female,Loyal Customer,32,Business travel,Eco Plus,954,1,3,4,3,1,1,1,1,1,4,4,1,4,1,0,1.0,neutral or dissatisfied +4694,96554,Male,disloyal Customer,17,Business travel,Eco Plus,302,3,0,3,3,4,3,4,4,1,5,1,3,2,4,0,0.0,neutral or dissatisfied +4695,26225,Male,Loyal Customer,19,Personal Travel,Eco,404,3,4,3,2,3,3,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +4696,67969,Male,Loyal Customer,52,Business travel,Business,1235,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,5.0,satisfied +4697,118569,Male,disloyal Customer,39,Business travel,Business,651,5,5,5,2,4,5,4,4,5,5,4,5,4,4,10,0.0,satisfied +4698,92630,Male,Loyal Customer,57,Business travel,Eco,453,2,3,4,3,2,2,2,2,4,3,3,3,2,2,0,15.0,neutral or dissatisfied +4699,9743,Female,Loyal Customer,54,Business travel,Business,970,1,4,4,4,3,2,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +4700,19306,Female,Loyal Customer,12,Personal Travel,Eco,299,5,4,3,4,5,3,5,5,5,3,5,3,4,5,6,0.0,satisfied +4701,68650,Male,disloyal Customer,26,Business travel,Business,237,2,1,2,3,5,2,5,5,3,4,3,3,4,5,1,0.0,neutral or dissatisfied +4702,65047,Male,Loyal Customer,43,Personal Travel,Eco,190,1,3,1,4,4,1,4,4,3,4,4,2,5,4,2,36.0,neutral or dissatisfied +4703,65175,Female,Loyal Customer,26,Personal Travel,Eco,354,1,4,1,3,1,1,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +4704,24940,Male,disloyal Customer,33,Business travel,Business,1747,2,2,2,3,4,2,4,4,4,2,4,5,5,4,6,0.0,neutral or dissatisfied +4705,59063,Male,Loyal Customer,53,Business travel,Eco,1744,2,2,4,2,2,2,2,2,4,2,4,3,3,2,126,94.0,neutral or dissatisfied +4706,60694,Female,Loyal Customer,53,Business travel,Business,1605,5,2,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +4707,123083,Female,disloyal Customer,36,Business travel,Business,468,3,3,3,3,3,1,1,4,4,4,5,1,5,1,157,135.0,neutral or dissatisfied +4708,21029,Female,Loyal Customer,34,Business travel,Business,106,4,4,4,4,3,5,1,4,4,4,5,4,4,5,0,3.0,satisfied +4709,80325,Female,Loyal Customer,27,Personal Travel,Eco,746,4,4,4,3,5,4,5,5,1,1,4,4,3,5,0,0.0,satisfied +4710,87168,Female,disloyal Customer,36,Business travel,Business,946,4,4,4,4,2,4,2,2,4,3,4,3,4,2,6,0.0,neutral or dissatisfied +4711,72991,Male,Loyal Customer,16,Business travel,Business,1096,3,5,5,5,3,3,3,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +4712,23279,Female,Loyal Customer,42,Business travel,Business,862,5,5,5,5,2,3,3,4,4,3,4,2,4,2,15,5.0,satisfied +4713,87345,Male,Loyal Customer,40,Business travel,Business,2333,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +4714,110766,Male,Loyal Customer,62,Business travel,Eco,990,2,1,1,1,2,2,2,2,3,4,2,3,3,2,22,22.0,neutral or dissatisfied +4715,62516,Female,Loyal Customer,52,Business travel,Business,1846,2,2,2,2,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +4716,10357,Male,Loyal Customer,27,Business travel,Business,3008,2,2,2,2,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +4717,67116,Female,Loyal Customer,25,Business travel,Business,2964,3,3,3,3,3,4,3,3,1,3,4,1,4,3,26,10.0,neutral or dissatisfied +4718,113131,Male,Loyal Customer,38,Personal Travel,Eco Plus,543,3,4,3,3,5,3,5,5,4,2,5,3,5,5,13,1.0,neutral or dissatisfied +4719,54897,Male,Loyal Customer,27,Personal Travel,Eco,862,1,5,1,5,3,1,3,3,5,5,5,5,5,3,9,0.0,neutral or dissatisfied +4720,79715,Male,Loyal Customer,14,Personal Travel,Eco,762,2,4,2,3,1,2,2,1,5,3,1,5,5,1,0,0.0,neutral or dissatisfied +4721,126241,Male,disloyal Customer,23,Business travel,Eco,590,3,4,3,3,3,3,3,3,1,1,4,3,4,3,2,19.0,neutral or dissatisfied +4722,126904,Male,Loyal Customer,68,Personal Travel,Eco Plus,2125,4,2,4,3,5,4,4,5,1,5,4,3,3,5,6,4.0,neutral or dissatisfied +4723,4984,Male,Loyal Customer,33,Business travel,Business,502,5,5,5,5,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +4724,85860,Female,Loyal Customer,22,Personal Travel,Eco Plus,526,2,4,2,4,3,2,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +4725,3090,Male,Loyal Customer,49,Business travel,Business,3889,1,4,4,4,4,2,2,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +4726,122702,Female,Loyal Customer,59,Business travel,Business,2372,1,1,1,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +4727,100646,Female,Loyal Customer,51,Personal Travel,Eco,349,2,5,4,2,1,5,1,4,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +4728,63508,Female,Loyal Customer,40,Business travel,Business,1009,5,5,5,5,5,4,5,3,3,3,3,4,3,4,3,4.0,satisfied +4729,88079,Male,Loyal Customer,20,Business travel,Business,3634,5,5,5,5,2,2,2,2,3,4,4,4,5,2,0,0.0,satisfied +4730,65819,Male,Loyal Customer,51,Business travel,Business,1389,2,2,2,2,4,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +4731,93503,Male,Loyal Customer,31,Personal Travel,Eco,1020,4,4,4,4,4,4,4,4,2,3,4,4,3,4,14,0.0,neutral or dissatisfied +4732,107965,Female,Loyal Customer,38,Business travel,Business,2256,5,5,5,5,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +4733,76859,Female,Loyal Customer,51,Business travel,Business,1262,2,2,4,2,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +4734,7894,Male,Loyal Customer,35,Business travel,Business,948,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,10.0,satisfied +4735,28553,Male,Loyal Customer,44,Personal Travel,Eco,2715,1,4,1,4,1,4,4,5,4,4,4,4,3,4,0,0.0,neutral or dissatisfied +4736,27171,Male,Loyal Customer,14,Personal Travel,Eco,2677,4,0,4,4,4,2,2,2,5,4,4,2,1,2,0,0.0,neutral or dissatisfied +4737,76275,Male,Loyal Customer,44,Business travel,Eco,1927,2,2,5,2,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +4738,51136,Female,Loyal Customer,37,Personal Travel,Eco,134,2,1,0,4,2,0,2,2,2,3,4,2,4,2,0,9.0,neutral or dissatisfied +4739,26439,Female,disloyal Customer,29,Business travel,Eco,925,1,1,1,3,1,1,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +4740,39183,Male,Loyal Customer,14,Personal Travel,Eco,311,2,4,2,5,4,2,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +4741,84201,Male,Loyal Customer,63,Business travel,Business,432,4,1,4,4,4,5,5,5,5,5,5,5,5,3,8,10.0,satisfied +4742,5138,Male,Loyal Customer,53,Personal Travel,Eco,184,3,5,3,2,2,3,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +4743,128061,Female,Loyal Customer,54,Business travel,Business,2917,4,5,4,4,5,5,5,4,3,3,5,5,5,5,11,0.0,satisfied +4744,12816,Male,Loyal Customer,62,Business travel,Business,2251,3,5,2,5,4,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +4745,106779,Female,Loyal Customer,52,Business travel,Eco Plus,837,2,2,4,4,3,3,3,2,2,2,2,1,2,3,0,8.0,neutral or dissatisfied +4746,37808,Female,Loyal Customer,8,Personal Travel,Eco Plus,1028,4,5,4,2,1,4,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +4747,12873,Female,disloyal Customer,25,Business travel,Eco,674,4,4,4,1,5,4,5,5,2,5,5,1,5,5,1,9.0,neutral or dissatisfied +4748,13041,Female,Loyal Customer,65,Personal Travel,Eco,438,2,4,2,3,5,3,4,4,4,2,4,1,4,2,1,0.0,neutral or dissatisfied +4749,58242,Female,disloyal Customer,26,Business travel,Eco Plus,925,2,2,2,4,4,2,2,4,4,1,4,2,3,4,65,51.0,neutral or dissatisfied +4750,126747,Male,Loyal Customer,22,Personal Travel,Eco,2521,4,4,4,4,4,4,4,4,4,4,5,4,5,4,9,0.0,neutral or dissatisfied +4751,5210,Male,Loyal Customer,46,Business travel,Business,383,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +4752,23520,Male,Loyal Customer,33,Personal Travel,Eco,303,3,4,1,4,2,1,2,2,3,5,4,3,3,2,0,0.0,neutral or dissatisfied +4753,38299,Male,Loyal Customer,44,Business travel,Business,2342,3,2,2,2,5,2,3,3,3,3,3,4,3,2,72,83.0,neutral or dissatisfied +4754,70144,Female,Loyal Customer,66,Personal Travel,Eco,550,3,3,3,3,4,4,3,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +4755,129045,Female,Loyal Customer,60,Business travel,Business,1744,2,2,2,2,5,5,5,2,2,2,2,4,2,3,0,4.0,satisfied +4756,87395,Female,Loyal Customer,20,Business travel,Business,1687,1,0,0,3,1,0,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +4757,77268,Male,Loyal Customer,77,Business travel,Eco Plus,1190,5,3,3,3,5,5,5,5,5,2,3,1,4,5,0,0.0,satisfied +4758,75625,Female,disloyal Customer,33,Business travel,Eco Plus,337,3,3,3,3,2,3,2,2,1,5,3,4,3,2,4,0.0,neutral or dissatisfied +4759,44866,Male,Loyal Customer,29,Personal Travel,Business,315,2,2,3,4,3,3,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +4760,51692,Male,disloyal Customer,23,Business travel,Eco,370,1,3,1,4,3,1,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +4761,112032,Male,Loyal Customer,42,Business travel,Business,680,5,5,5,5,2,4,4,5,5,5,5,4,5,3,22,9.0,satisfied +4762,90006,Male,Loyal Customer,63,Business travel,Business,3919,2,2,2,2,1,4,3,2,2,2,2,4,2,2,17,11.0,neutral or dissatisfied +4763,36088,Male,Loyal Customer,67,Personal Travel,Eco,413,3,3,1,1,1,1,5,5,5,1,3,5,1,5,170,155.0,neutral or dissatisfied +4764,49342,Female,disloyal Customer,27,Business travel,Eco,326,2,0,2,2,5,2,5,5,1,3,5,5,4,5,0,2.0,neutral or dissatisfied +4765,37132,Male,Loyal Customer,36,Business travel,Business,1189,1,3,3,3,2,3,4,1,1,1,1,2,1,1,12,4.0,neutral or dissatisfied +4766,17291,Female,Loyal Customer,23,Business travel,Business,438,4,4,4,4,4,4,4,4,1,2,2,5,3,4,0,12.0,satisfied +4767,118409,Female,Loyal Customer,65,Business travel,Business,1923,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,7.0,satisfied +4768,117610,Female,disloyal Customer,25,Business travel,Eco,347,2,0,2,3,1,2,1,1,5,4,2,1,5,1,14,11.0,neutral or dissatisfied +4769,22906,Female,Loyal Customer,49,Personal Travel,Eco Plus,151,2,4,2,4,4,5,5,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +4770,53762,Male,disloyal Customer,26,Business travel,Eco,1195,3,3,3,1,1,3,1,1,4,3,5,1,1,1,0,0.0,neutral or dissatisfied +4771,101006,Male,Loyal Customer,57,Business travel,Eco,867,1,0,0,3,2,1,2,2,3,3,3,2,3,2,130,126.0,neutral or dissatisfied +4772,71141,Female,Loyal Customer,68,Business travel,Business,1911,3,3,3,3,1,4,4,2,2,3,3,1,2,1,59,54.0,neutral or dissatisfied +4773,11578,Male,Loyal Customer,25,Business travel,Business,771,1,2,2,2,1,1,1,1,2,3,3,4,3,1,0,0.0,neutral or dissatisfied +4774,110787,Female,Loyal Customer,37,Business travel,Business,3629,3,3,3,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +4775,117785,Male,Loyal Customer,55,Business travel,Business,328,0,0,0,3,2,5,5,2,2,2,2,3,2,3,10,9.0,satisfied +4776,65838,Male,Loyal Customer,51,Business travel,Business,1389,1,2,2,2,2,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +4777,105780,Female,Loyal Customer,46,Personal Travel,Eco,787,2,5,2,4,4,4,5,2,2,2,5,3,2,4,67,84.0,neutral or dissatisfied +4778,59089,Female,Loyal Customer,60,Business travel,Eco,244,4,2,2,2,5,3,5,4,4,4,4,1,4,1,16,0.0,satisfied +4779,60016,Female,Loyal Customer,14,Personal Travel,Eco,937,3,3,3,3,1,3,1,1,5,1,5,4,5,1,14,0.0,neutral or dissatisfied +4780,103007,Male,Loyal Customer,59,Business travel,Business,1675,5,5,5,5,4,5,5,4,4,5,4,4,4,5,1,0.0,satisfied +4781,6703,Male,Loyal Customer,31,Personal Travel,Eco,438,4,4,4,1,4,4,4,4,5,4,4,5,4,4,0,1.0,neutral or dissatisfied +4782,89846,Male,Loyal Customer,7,Personal Travel,Business,1306,4,4,4,1,4,2,2,5,4,4,5,2,5,2,33,153.0,satisfied +4783,435,Male,Loyal Customer,53,Personal Travel,Business,134,2,2,2,3,5,3,3,2,2,2,2,4,2,3,80,71.0,neutral or dissatisfied +4784,28893,Male,Loyal Customer,38,Business travel,Business,954,5,5,5,5,2,2,5,4,4,4,4,4,4,5,0,0.0,satisfied +4785,91577,Male,disloyal Customer,35,Business travel,Business,1123,3,4,4,4,5,4,5,5,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +4786,10876,Male,Loyal Customer,38,Business travel,Business,224,2,3,3,3,4,3,2,2,2,2,2,4,2,1,20,24.0,neutral or dissatisfied +4787,24877,Female,Loyal Customer,36,Business travel,Eco Plus,356,4,2,2,2,4,4,4,4,3,5,5,3,3,4,0,0.0,satisfied +4788,52955,Male,Loyal Customer,66,Personal Travel,Business,2306,3,3,3,3,4,3,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +4789,108469,Male,Loyal Customer,13,Personal Travel,Eco,1440,2,4,2,4,5,2,5,5,3,4,5,4,5,5,11,0.0,neutral or dissatisfied +4790,17751,Female,Loyal Customer,59,Personal Travel,Eco,383,3,3,3,3,5,3,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +4791,47215,Male,Loyal Customer,59,Personal Travel,Eco,908,2,3,2,1,4,2,4,4,4,2,2,2,2,4,39,34.0,neutral or dissatisfied +4792,110504,Male,Loyal Customer,35,Business travel,Eco Plus,787,3,4,4,4,3,3,3,3,4,3,4,2,4,3,22,10.0,neutral or dissatisfied +4793,2791,Female,disloyal Customer,22,Business travel,Eco,764,2,2,2,4,3,2,3,3,1,2,3,3,3,3,67,50.0,neutral or dissatisfied +4794,14540,Male,Loyal Customer,55,Business travel,Business,3761,1,4,4,4,2,4,3,1,1,1,1,3,1,2,0,5.0,neutral or dissatisfied +4795,69549,Male,disloyal Customer,11,Business travel,Business,784,0,0,0,4,0,4,4,5,3,3,4,4,3,4,0,0.0,satisfied +4796,26175,Male,Loyal Customer,49,Business travel,Business,2492,2,3,3,3,2,1,2,2,2,2,2,4,2,1,16,25.0,neutral or dissatisfied +4797,33442,Female,Loyal Customer,36,Personal Travel,Eco,2556,3,4,3,3,3,4,4,3,2,3,5,4,4,4,2,25.0,neutral or dissatisfied +4798,114369,Female,Loyal Customer,47,Business travel,Business,1595,4,4,4,4,2,5,4,4,4,4,4,5,4,3,6,2.0,satisfied +4799,4780,Female,Loyal Customer,44,Business travel,Business,438,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +4800,3715,Female,Loyal Customer,42,Personal Travel,Eco,544,3,3,3,3,4,3,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +4801,9323,Male,Loyal Customer,65,Business travel,Business,3714,1,1,1,1,3,3,2,5,5,5,5,1,5,3,11,1.0,satisfied +4802,107453,Male,Loyal Customer,23,Business travel,Eco Plus,725,2,4,4,4,2,2,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +4803,10596,Female,Loyal Customer,49,Business travel,Business,517,4,4,4,4,4,5,4,3,3,3,3,4,3,4,0,2.0,satisfied +4804,35320,Male,Loyal Customer,49,Business travel,Eco,1028,3,1,1,1,3,3,3,3,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +4805,89218,Male,Loyal Customer,48,Personal Travel,Eco,1947,2,4,2,4,2,2,1,2,4,3,4,4,5,2,28,19.0,neutral or dissatisfied +4806,103427,Female,Loyal Customer,51,Personal Travel,Eco,237,2,5,2,1,2,2,2,4,4,5,4,2,3,2,132,129.0,neutral or dissatisfied +4807,126788,Male,Loyal Customer,32,Business travel,Business,2296,1,1,1,1,5,5,5,5,3,2,3,4,4,5,11,0.0,satisfied +4808,37502,Female,disloyal Customer,25,Business travel,Eco,944,3,4,4,4,4,4,4,4,1,4,3,2,3,4,0,7.0,neutral or dissatisfied +4809,107299,Female,Loyal Customer,14,Personal Travel,Eco,283,3,5,3,1,3,3,3,3,4,3,5,4,5,3,0,1.0,neutral or dissatisfied +4810,41627,Male,disloyal Customer,33,Business travel,Business,438,1,1,1,4,1,1,1,1,3,3,3,3,4,1,0,0.0,neutral or dissatisfied +4811,113460,Male,disloyal Customer,59,Business travel,Business,236,2,2,2,4,4,2,4,4,4,2,3,2,4,4,53,55.0,neutral or dissatisfied +4812,16962,Female,Loyal Customer,26,Personal Travel,Eco,1131,5,4,5,1,3,5,3,3,3,5,5,4,4,3,0,0.0,satisfied +4813,91768,Female,Loyal Customer,50,Business travel,Eco,190,4,1,1,1,3,3,5,4,4,4,4,2,4,5,0,0.0,satisfied +4814,120319,Male,Loyal Customer,38,Business travel,Business,3194,1,5,5,5,5,4,3,1,1,1,1,3,1,2,1,42.0,neutral or dissatisfied +4815,93452,Female,Loyal Customer,34,Personal Travel,Eco,671,3,5,3,3,5,3,4,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +4816,112289,Male,Loyal Customer,57,Business travel,Business,1703,2,2,2,2,3,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +4817,77025,Female,Loyal Customer,22,Business travel,Business,2474,3,3,3,3,4,4,4,4,1,5,4,4,4,4,0,0.0,satisfied +4818,86385,Female,disloyal Customer,26,Business travel,Business,762,1,1,1,5,4,1,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +4819,108879,Male,Loyal Customer,43,Business travel,Business,2728,2,2,2,2,2,2,2,2,1,4,4,2,2,2,268,255.0,neutral or dissatisfied +4820,3751,Male,Loyal Customer,47,Business travel,Business,427,3,3,3,3,3,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +4821,57278,Male,Loyal Customer,51,Personal Travel,Eco,628,4,5,5,2,2,5,1,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +4822,31434,Female,Loyal Customer,30,Personal Travel,Eco,1546,3,4,3,4,2,3,2,2,5,5,4,5,4,2,28,17.0,neutral or dissatisfied +4823,83659,Female,Loyal Customer,25,Business travel,Business,2198,2,3,3,3,2,2,2,2,3,4,4,3,3,2,67,66.0,neutral or dissatisfied +4824,37833,Female,Loyal Customer,54,Business travel,Business,1554,2,2,2,2,2,5,1,4,4,4,4,2,4,1,39,53.0,satisfied +4825,127506,Male,Loyal Customer,15,Personal Travel,Eco,2075,3,4,3,4,5,3,2,5,4,5,4,2,4,5,0,0.0,neutral or dissatisfied +4826,100746,Female,Loyal Customer,50,Personal Travel,Eco,328,3,5,3,2,5,4,5,4,4,3,4,4,4,3,0,2.0,neutral or dissatisfied +4827,71753,Female,Loyal Customer,52,Business travel,Business,1829,2,2,2,2,5,3,4,3,3,4,3,3,3,3,0,0.0,satisfied +4828,45669,Female,Loyal Customer,9,Personal Travel,Eco Plus,313,3,4,3,2,4,3,4,4,4,4,4,5,4,4,0,29.0,neutral or dissatisfied +4829,2119,Female,Loyal Customer,49,Business travel,Business,431,5,5,5,5,2,5,4,4,4,4,4,4,4,5,18,10.0,satisfied +4830,72671,Female,Loyal Customer,15,Personal Travel,Eco,1121,4,5,4,3,4,4,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +4831,102791,Male,Loyal Customer,58,Personal Travel,Eco,1099,5,3,5,2,2,5,2,2,3,1,4,2,2,2,0,0.0,satisfied +4832,86380,Male,Loyal Customer,55,Business travel,Business,3834,2,2,2,2,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +4833,127582,Male,Loyal Customer,35,Business travel,Business,1773,1,1,1,1,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +4834,119269,Female,Loyal Customer,42,Business travel,Business,2720,0,4,0,3,5,5,5,5,5,4,5,5,3,5,144,134.0,satisfied +4835,66644,Male,Loyal Customer,55,Business travel,Business,3295,3,3,3,3,3,5,4,3,3,4,3,5,3,4,23,25.0,satisfied +4836,49191,Male,disloyal Customer,39,Business travel,Eco,326,2,5,2,4,5,2,5,5,1,1,2,3,3,5,14,10.0,neutral or dissatisfied +4837,93900,Female,disloyal Customer,56,Personal Travel,Eco,590,2,1,1,3,4,1,4,4,1,3,2,2,2,4,1,0.0,neutral or dissatisfied +4838,96294,Female,Loyal Customer,17,Personal Travel,Eco,687,2,4,2,5,5,2,5,5,2,5,1,3,4,5,0,0.0,neutral or dissatisfied +4839,31030,Male,Loyal Customer,60,Business travel,Business,3227,1,1,4,1,4,4,4,2,2,3,2,4,2,4,0,0.0,satisfied +4840,75665,Male,Loyal Customer,27,Personal Travel,Eco Plus,304,1,5,1,4,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +4841,77801,Female,Loyal Customer,7,Personal Travel,Eco,813,3,2,3,3,4,3,4,4,4,3,3,3,3,4,0,0.0,neutral or dissatisfied +4842,119483,Female,disloyal Customer,48,Business travel,Eco,814,2,3,3,4,4,3,4,4,4,4,3,3,4,4,6,10.0,neutral or dissatisfied +4843,29625,Female,disloyal Customer,23,Business travel,Eco,1242,3,3,3,2,4,3,1,4,4,5,1,4,3,4,0,0.0,satisfied +4844,47616,Female,Loyal Customer,45,Business travel,Business,1428,4,4,4,4,1,5,4,4,4,4,4,1,4,2,16,0.0,satisfied +4845,9021,Male,Loyal Customer,60,Business travel,Business,2256,2,2,2,2,4,4,4,3,3,4,4,5,3,4,0,0.0,satisfied +4846,86930,Female,Loyal Customer,51,Business travel,Business,3568,5,5,5,5,4,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +4847,84554,Female,Loyal Customer,20,Personal Travel,Eco,2556,1,5,0,3,1,0,1,1,5,4,5,1,3,1,1,0.0,neutral or dissatisfied +4848,20627,Female,Loyal Customer,26,Business travel,Business,3299,4,4,4,4,4,4,4,4,2,1,4,5,1,4,0,0.0,satisfied +4849,100262,Female,Loyal Customer,41,Business travel,Business,3974,4,4,1,4,3,5,5,4,4,5,4,5,4,5,25,19.0,satisfied +4850,45468,Male,Loyal Customer,26,Business travel,Eco,522,4,2,1,2,4,4,5,4,2,2,3,2,3,4,9,18.0,satisfied +4851,104992,Male,Loyal Customer,50,Personal Travel,Eco,314,2,4,2,4,3,2,3,3,5,2,5,3,5,3,19,15.0,neutral or dissatisfied +4852,114292,Male,Loyal Customer,17,Personal Travel,Eco,853,3,4,3,5,1,3,1,1,3,5,5,3,5,1,4,0.0,neutral or dissatisfied +4853,85808,Female,Loyal Customer,21,Personal Travel,Eco,666,2,4,2,2,2,2,2,2,4,5,5,5,4,2,22,7.0,neutral or dissatisfied +4854,20352,Male,disloyal Customer,27,Business travel,Business,287,2,2,2,3,5,2,5,5,4,2,2,3,3,5,104,91.0,neutral or dissatisfied +4855,79026,Female,Loyal Customer,46,Business travel,Business,1771,3,3,3,3,4,2,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +4856,37756,Male,Loyal Customer,22,Business travel,Eco Plus,944,5,1,1,1,5,5,3,5,2,5,1,4,3,5,16,19.0,satisfied +4857,88460,Female,Loyal Customer,41,Business travel,Business,3720,4,4,4,4,2,3,5,5,5,5,5,4,5,4,11,5.0,satisfied +4858,101445,Male,Loyal Customer,47,Business travel,Business,1854,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +4859,101253,Female,disloyal Customer,31,Business travel,Business,1910,3,3,3,4,3,3,2,3,4,2,2,3,4,3,0,0.0,neutral or dissatisfied +4860,93422,Female,Loyal Customer,51,Business travel,Business,723,4,3,3,3,2,2,2,4,4,4,4,3,4,3,20,14.0,neutral or dissatisfied +4861,24085,Male,Loyal Customer,60,Personal Travel,Eco,854,2,5,2,4,5,2,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +4862,63201,Male,Loyal Customer,28,Business travel,Business,337,2,5,5,5,2,3,2,2,1,1,3,2,4,2,19,27.0,neutral or dissatisfied +4863,18548,Female,Loyal Customer,48,Business travel,Eco,383,4,5,5,5,5,1,2,4,4,4,4,4,4,3,0,0.0,satisfied +4864,87193,Male,disloyal Customer,26,Business travel,Eco,946,1,1,1,2,4,1,4,4,3,5,3,2,3,4,0,17.0,neutral or dissatisfied +4865,2406,Female,Loyal Customer,58,Business travel,Business,767,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4866,65769,Female,Loyal Customer,24,Personal Travel,Eco Plus,936,3,4,2,3,1,2,5,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +4867,84194,Male,disloyal Customer,38,Business travel,Business,432,2,2,2,2,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +4868,39400,Female,Loyal Customer,46,Business travel,Eco,546,2,3,3,3,3,2,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +4869,114918,Female,Loyal Customer,40,Business travel,Business,3336,1,1,1,1,5,5,4,4,4,4,4,3,4,5,48,42.0,satisfied +4870,98311,Male,Loyal Customer,37,Personal Travel,Eco,1565,3,4,4,4,4,4,4,4,4,4,5,3,4,4,2,0.0,neutral or dissatisfied +4871,105783,Female,Loyal Customer,67,Personal Travel,Eco,663,2,2,2,4,3,4,3,2,2,2,2,1,2,4,1,0.0,neutral or dissatisfied +4872,45040,Male,disloyal Customer,25,Business travel,Eco,323,4,3,4,1,5,4,5,5,4,5,4,4,4,5,33,23.0,satisfied +4873,40418,Female,Loyal Customer,33,Business travel,Eco,188,5,1,4,1,5,5,5,5,2,5,1,2,3,5,0,12.0,satisfied +4874,44671,Female,Loyal Customer,32,Business travel,Business,3134,4,4,4,4,5,5,5,5,3,3,3,2,4,5,0,0.0,satisfied +4875,17624,Male,Loyal Customer,27,Personal Travel,Eco,622,3,5,3,3,1,3,1,1,5,5,5,3,4,1,115,104.0,neutral or dissatisfied +4876,57769,Male,disloyal Customer,24,Business travel,Eco,2704,2,1,1,2,2,2,2,4,3,3,3,2,4,2,6,10.0,neutral or dissatisfied +4877,98854,Male,Loyal Customer,27,Business travel,Eco,1751,1,2,2,2,1,1,1,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +4878,39608,Female,Loyal Customer,8,Personal Travel,Eco,954,1,1,0,3,4,0,4,4,3,4,3,3,3,4,0,4.0,neutral or dissatisfied +4879,63669,Male,disloyal Customer,35,Business travel,Eco Plus,2405,2,2,2,1,2,2,2,2,2,2,1,5,1,2,0,0.0,neutral or dissatisfied +4880,3285,Female,Loyal Customer,14,Personal Travel,Eco,479,4,2,4,3,4,4,4,4,3,5,3,1,3,4,0,2.0,neutral or dissatisfied +4881,105726,Male,Loyal Customer,28,Business travel,Business,787,2,2,2,2,5,4,5,5,5,3,5,4,5,5,1,0.0,satisfied +4882,118612,Female,Loyal Customer,26,Business travel,Business,3493,3,3,3,3,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +4883,109210,Female,Loyal Customer,55,Business travel,Eco,284,4,5,5,5,3,1,2,4,4,4,4,3,4,1,50,44.0,satisfied +4884,3523,Male,Loyal Customer,46,Business travel,Eco,557,2,5,5,5,2,2,2,2,3,1,3,4,4,2,0,4.0,neutral or dissatisfied +4885,67150,Male,Loyal Customer,46,Business travel,Eco,529,5,3,3,3,5,5,5,5,3,4,2,4,5,5,53,52.0,satisfied +4886,108478,Female,disloyal Customer,22,Business travel,Eco,570,0,0,0,3,2,0,2,2,5,4,4,5,5,2,7,12.0,satisfied +4887,58355,Male,Loyal Customer,52,Business travel,Business,646,2,4,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4888,80282,Female,Loyal Customer,26,Business travel,Business,2136,5,5,5,5,5,4,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +4889,73524,Female,Loyal Customer,58,Business travel,Business,3399,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,12.0,satisfied +4890,79935,Female,disloyal Customer,9,Business travel,Eco,1047,1,2,2,3,2,2,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +4891,85630,Male,Loyal Customer,41,Personal Travel,Eco,259,1,3,1,3,5,1,5,5,1,1,4,3,1,5,0,2.0,neutral or dissatisfied +4892,50052,Female,Loyal Customer,27,Business travel,Business,2611,0,0,0,1,4,3,3,4,1,5,5,4,4,4,0,0.0,satisfied +4893,66435,Female,Loyal Customer,58,Personal Travel,Business,1217,4,0,4,4,2,5,5,1,1,4,1,4,1,1,40,34.0,neutral or dissatisfied +4894,44878,Male,Loyal Customer,34,Personal Travel,Eco,315,3,3,3,3,1,3,1,1,4,4,2,2,2,1,0,0.0,neutral or dissatisfied +4895,18583,Male,Loyal Customer,25,Business travel,Business,1722,2,5,4,5,2,3,2,2,1,5,3,2,2,2,22,19.0,neutral or dissatisfied +4896,81567,Female,disloyal Customer,21,Business travel,Business,536,4,0,4,3,5,4,5,5,2,1,4,5,2,5,0,0.0,satisfied +4897,2408,Female,Loyal Customer,55,Business travel,Business,2904,4,5,5,5,5,3,3,4,4,4,4,3,4,4,58,,neutral or dissatisfied +4898,4286,Male,Loyal Customer,41,Personal Travel,Eco,502,4,5,4,5,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +4899,104657,Female,Loyal Customer,46,Business travel,Business,3389,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +4900,81706,Male,Loyal Customer,23,Personal Travel,Eco,907,2,5,2,3,3,2,2,3,4,3,4,5,4,3,0,4.0,neutral or dissatisfied +4901,109806,Male,disloyal Customer,22,Business travel,Eco,1034,4,4,4,2,2,4,2,2,4,4,5,5,5,2,80,66.0,satisfied +4902,84987,Female,Loyal Customer,46,Business travel,Business,1590,4,4,4,4,4,5,4,5,5,5,5,3,5,4,30,17.0,satisfied +4903,43258,Female,Loyal Customer,49,Business travel,Eco,436,4,1,1,1,2,5,5,4,4,4,4,1,4,4,0,0.0,satisfied +4904,49727,Male,Loyal Customer,52,Business travel,Eco,190,3,5,5,5,3,3,3,3,1,1,3,2,4,3,38,38.0,neutral or dissatisfied +4905,19183,Male,Loyal Customer,52,Business travel,Business,2760,3,3,3,3,5,4,5,5,5,5,5,2,5,4,35,55.0,satisfied +4906,111769,Female,disloyal Customer,22,Business travel,Business,753,4,0,4,1,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +4907,25116,Male,Loyal Customer,37,Business travel,Eco,946,4,3,3,3,4,4,4,4,1,3,4,2,5,4,0,0.0,satisfied +4908,102361,Female,Loyal Customer,33,Business travel,Eco,223,2,2,2,2,2,2,2,2,1,2,4,3,4,2,0,0.0,neutral or dissatisfied +4909,74950,Female,Loyal Customer,50,Business travel,Business,2475,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +4910,47887,Male,disloyal Customer,33,Business travel,Eco,329,3,1,3,4,2,3,2,2,1,4,3,2,4,2,60,62.0,neutral or dissatisfied +4911,62789,Female,Loyal Customer,13,Personal Travel,Eco,2338,3,4,2,3,4,2,4,4,3,5,4,3,5,4,25,11.0,neutral or dissatisfied +4912,27802,Male,Loyal Customer,13,Business travel,Business,1448,3,3,3,3,4,4,4,4,3,5,4,3,3,4,0,0.0,satisfied +4913,8158,Female,Loyal Customer,22,Business travel,Business,335,3,1,1,1,3,3,3,3,3,5,4,1,3,3,0,0.0,neutral or dissatisfied +4914,52851,Female,Loyal Customer,69,Personal Travel,Eco,1721,4,4,4,1,5,5,4,4,4,4,4,3,4,4,0,7.0,satisfied +4915,7898,Male,Loyal Customer,48,Business travel,Business,2079,4,4,3,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +4916,55100,Male,disloyal Customer,17,Business travel,Eco,1346,4,3,3,3,4,4,4,4,2,2,1,5,2,4,0,0.0,neutral or dissatisfied +4917,97516,Female,Loyal Customer,53,Business travel,Business,265,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +4918,23027,Female,disloyal Customer,26,Business travel,Eco,1080,3,4,4,3,4,4,4,4,1,1,2,5,1,4,2,13.0,neutral or dissatisfied +4919,43051,Female,Loyal Customer,62,Business travel,Eco,192,1,1,1,1,1,3,3,1,1,1,1,3,1,3,5,18.0,neutral or dissatisfied +4920,88809,Male,Loyal Customer,72,Business travel,Eco Plus,270,1,1,5,1,1,1,1,1,1,1,4,1,4,1,6,0.0,neutral or dissatisfied +4921,20508,Male,Loyal Customer,48,Personal Travel,Eco,139,1,5,1,3,1,2,2,4,2,3,5,2,3,2,133,135.0,neutral or dissatisfied +4922,124885,Female,Loyal Customer,40,Business travel,Business,728,1,1,4,1,4,4,4,4,4,4,4,5,4,5,6,0.0,satisfied +4923,60584,Female,Loyal Customer,42,Business travel,Eco,890,2,3,3,3,3,5,4,2,2,2,2,2,2,2,0,3.0,satisfied +4924,110918,Male,Loyal Customer,38,Business travel,Eco,404,5,4,4,4,5,5,5,5,1,4,1,2,5,5,0,0.0,satisfied +4925,103998,Female,disloyal Customer,37,Business travel,Eco,887,2,2,2,4,5,2,5,5,3,3,4,2,3,5,9,0.0,neutral or dissatisfied +4926,66080,Female,Loyal Customer,68,Personal Travel,Eco,1345,2,5,2,3,2,5,5,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +4927,21649,Male,Loyal Customer,30,Business travel,Eco Plus,853,4,5,5,5,4,4,4,4,1,3,2,3,3,4,90,88.0,neutral or dissatisfied +4928,79056,Female,disloyal Customer,57,Business travel,Eco,226,1,3,1,3,1,1,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +4929,93096,Female,Loyal Customer,24,Business travel,Eco,641,3,4,4,4,3,3,2,3,3,2,2,1,3,3,6,8.0,neutral or dissatisfied +4930,10053,Female,Loyal Customer,28,Business travel,Business,3758,1,1,1,1,4,4,4,4,3,3,5,4,5,4,8,0.0,satisfied +4931,10466,Female,Loyal Customer,28,Business travel,Business,1918,3,3,3,3,4,5,4,4,4,3,4,4,5,4,0,0.0,satisfied +4932,110780,Male,Loyal Customer,77,Business travel,Business,3535,3,3,3,3,5,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +4933,95735,Female,Loyal Customer,60,Business travel,Business,3565,3,3,3,3,5,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +4934,13096,Female,disloyal Customer,28,Business travel,Eco,427,3,0,3,4,3,3,3,3,4,2,5,4,4,3,19,0.0,neutral or dissatisfied +4935,127321,Male,Loyal Customer,30,Business travel,Business,3752,5,5,5,5,5,5,5,5,4,3,4,4,5,5,3,6.0,satisfied +4936,50668,Female,Loyal Customer,38,Personal Travel,Eco,109,1,3,1,1,5,1,5,5,3,5,1,2,5,5,31,27.0,neutral or dissatisfied +4937,64613,Male,disloyal Customer,48,Business travel,Eco,247,4,2,4,3,1,4,1,1,1,5,3,2,4,1,55,42.0,neutral or dissatisfied +4938,45113,Female,Loyal Customer,23,Business travel,Eco,157,2,4,4,4,2,3,2,2,5,3,3,2,1,2,172,185.0,neutral or dissatisfied +4939,75748,Female,Loyal Customer,38,Business travel,Business,3983,5,5,5,5,4,2,2,5,5,5,5,5,5,5,0,0.0,satisfied +4940,22270,Male,Loyal Customer,39,Business travel,Eco,238,5,5,5,5,5,5,5,5,4,5,4,3,2,5,48,45.0,satisfied +4941,99531,Male,Loyal Customer,40,Business travel,Business,3777,1,5,5,5,2,3,4,1,1,1,1,2,1,2,8,15.0,neutral or dissatisfied +4942,55668,Female,Loyal Customer,46,Business travel,Business,1917,3,3,3,3,2,4,5,3,3,3,3,4,3,3,1,17.0,satisfied +4943,60135,Male,Loyal Customer,49,Business travel,Business,2868,4,4,4,4,2,4,5,5,5,5,5,3,5,5,6,0.0,satisfied +4944,18136,Male,Loyal Customer,57,Business travel,Business,632,2,2,2,2,5,5,5,2,3,2,3,5,3,5,171,164.0,satisfied +4945,92857,Female,Loyal Customer,55,Business travel,Business,2519,4,4,4,4,3,4,5,4,4,4,4,4,4,5,5,0.0,satisfied +4946,89396,Female,disloyal Customer,38,Business travel,Eco,134,3,4,4,3,2,4,2,2,3,1,3,1,4,2,24,19.0,neutral or dissatisfied +4947,74461,Male,Loyal Customer,36,Business travel,Business,1438,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +4948,65463,Male,Loyal Customer,54,Business travel,Business,2373,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4949,9932,Female,Loyal Customer,33,Business travel,Business,3585,1,5,5,5,4,3,3,1,1,1,1,4,1,3,14,24.0,neutral or dissatisfied +4950,16730,Female,Loyal Customer,25,Business travel,Business,2748,2,4,4,4,2,2,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +4951,63876,Female,disloyal Customer,25,Business travel,Business,1172,5,0,5,2,4,5,4,4,5,2,5,3,5,4,0,0.0,satisfied +4952,68859,Male,Loyal Customer,60,Business travel,Business,1061,2,2,2,2,4,4,4,4,4,4,4,3,4,4,20,0.0,satisfied +4953,22120,Male,Loyal Customer,33,Personal Travel,Eco,694,2,5,2,3,2,2,2,2,3,3,5,4,5,2,1,0.0,neutral or dissatisfied +4954,53863,Female,disloyal Customer,25,Business travel,Eco,191,1,2,1,4,3,1,4,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +4955,11253,Male,Loyal Customer,44,Personal Travel,Eco,517,3,5,3,4,4,3,1,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +4956,106808,Female,Loyal Customer,49,Business travel,Eco Plus,977,3,3,3,3,3,3,3,3,3,3,3,4,3,4,11,4.0,neutral or dissatisfied +4957,97010,Male,Loyal Customer,68,Personal Travel,Eco,775,2,1,2,4,3,2,3,3,4,2,4,1,3,3,0,6.0,neutral or dissatisfied +4958,25548,Female,disloyal Customer,34,Business travel,Eco Plus,481,4,4,4,3,1,4,1,1,4,1,5,4,2,1,0,0.0,neutral or dissatisfied +4959,121301,Male,Loyal Customer,51,Business travel,Business,2962,4,4,4,4,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +4960,104628,Female,Loyal Customer,59,Business travel,Business,861,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +4961,98828,Female,Loyal Customer,25,Personal Travel,Eco,763,4,3,4,2,3,4,3,3,4,2,3,3,2,3,0,0.0,satisfied +4962,62344,Male,Loyal Customer,33,Personal Travel,Eco Plus,414,3,1,3,2,4,3,4,4,1,4,2,2,3,4,6,0.0,neutral or dissatisfied +4963,126331,Female,Loyal Customer,19,Personal Travel,Eco,507,2,5,2,1,3,2,3,3,3,4,4,3,5,3,62,60.0,neutral or dissatisfied +4964,38706,Female,disloyal Customer,35,Business travel,Eco,1133,3,3,3,3,5,3,3,5,2,4,2,4,3,5,0,0.0,neutral or dissatisfied +4965,59990,Male,Loyal Customer,30,Personal Travel,Eco,997,3,5,3,3,5,3,5,5,1,2,5,2,5,5,0,0.0,neutral or dissatisfied +4966,120102,Female,Loyal Customer,41,Business travel,Business,1576,2,2,2,2,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +4967,86326,Male,disloyal Customer,37,Business travel,Business,762,2,2,2,4,5,2,5,5,1,2,3,1,3,5,18,16.0,neutral or dissatisfied +4968,100881,Female,Loyal Customer,56,Business travel,Eco,2133,3,1,1,1,3,1,2,3,3,3,3,4,3,1,42,54.0,neutral or dissatisfied +4969,1871,Female,Loyal Customer,54,Business travel,Business,2517,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,1.0,satisfied +4970,40819,Male,Loyal Customer,28,Business travel,Business,3414,2,2,2,2,2,2,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +4971,91086,Male,Loyal Customer,57,Personal Travel,Eco,404,1,4,1,3,1,1,1,1,3,2,4,3,4,1,24,20.0,neutral or dissatisfied +4972,42015,Female,Loyal Customer,57,Business travel,Eco,106,4,2,2,2,4,5,1,4,4,4,4,5,4,5,0,0.0,satisfied +4973,115418,Male,Loyal Customer,33,Business travel,Business,325,2,2,2,2,5,5,5,5,3,5,4,5,5,5,0,0.0,satisfied +4974,120940,Female,disloyal Customer,26,Business travel,Business,993,4,4,4,4,5,4,5,5,5,2,4,5,4,5,0,0.0,satisfied +4975,86819,Male,disloyal Customer,23,Business travel,Eco,692,2,2,2,3,4,2,4,4,5,2,5,5,5,4,67,80.0,neutral or dissatisfied +4976,25249,Male,Loyal Customer,48,Business travel,Eco Plus,842,3,3,3,3,3,3,3,3,3,3,1,1,4,3,0,0.0,satisfied +4977,4495,Female,Loyal Customer,38,Business travel,Business,2710,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +4978,90425,Male,Loyal Customer,52,Business travel,Business,1861,5,5,5,5,4,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +4979,123466,Female,Loyal Customer,25,Business travel,Business,2125,4,4,4,4,4,4,4,4,4,1,3,2,3,4,0,12.0,neutral or dissatisfied +4980,125361,Male,Loyal Customer,19,Personal Travel,Eco,599,1,2,1,3,2,1,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +4981,28078,Male,Loyal Customer,11,Business travel,Eco Plus,2631,5,2,5,2,5,3,5,5,3,5,2,5,2,5,0,0.0,satisfied +4982,71188,Female,disloyal Customer,25,Business travel,Business,733,0,1,0,2,3,0,3,3,4,5,5,4,5,3,0,0.0,satisfied +4983,100367,Female,Loyal Customer,34,Personal Travel,Eco,1052,4,5,4,4,2,4,2,2,4,4,4,5,5,2,0,0.0,satisfied +4984,85904,Male,disloyal Customer,22,Business travel,Business,761,4,0,5,4,5,5,5,5,5,5,4,3,5,5,10,8.0,satisfied +4985,1190,Female,Loyal Customer,33,Personal Travel,Eco,113,4,5,4,4,5,4,5,5,1,5,2,4,3,5,0,0.0,neutral or dissatisfied +4986,79898,Male,Loyal Customer,44,Business travel,Eco,944,3,3,3,3,3,3,3,3,2,4,3,2,4,3,37,33.0,neutral or dissatisfied +4987,10823,Female,Loyal Customer,35,Business travel,Business,1634,2,2,5,2,2,4,3,2,2,1,2,2,2,3,14,13.0,neutral or dissatisfied +4988,104217,Female,Loyal Customer,45,Business travel,Eco,680,2,2,5,5,1,3,4,2,2,2,2,2,2,2,46,47.0,neutral or dissatisfied +4989,76717,Female,disloyal Customer,22,Business travel,Eco,534,2,2,2,3,1,2,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +4990,67448,Female,Loyal Customer,60,Personal Travel,Eco,641,4,4,5,3,4,5,5,3,3,5,4,5,3,3,2,4.0,satisfied +4991,117717,Female,Loyal Customer,32,Personal Travel,Eco,1009,3,4,3,5,1,3,5,1,5,5,4,5,5,1,50,30.0,neutral or dissatisfied +4992,106717,Male,Loyal Customer,42,Business travel,Business,2599,2,2,4,2,4,4,5,5,5,5,5,4,5,4,0,7.0,satisfied +4993,81982,Female,disloyal Customer,22,Business travel,Business,1589,5,4,5,3,3,5,3,3,3,2,5,4,4,3,24,0.0,satisfied +4994,124878,Male,Loyal Customer,23,Personal Travel,Business,728,1,1,1,3,4,1,4,4,1,2,2,4,3,4,2,0.0,neutral or dissatisfied +4995,88948,Female,Loyal Customer,33,Business travel,Business,1340,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +4996,102542,Female,Loyal Customer,54,Personal Travel,Eco,223,1,4,1,1,2,5,5,5,5,1,5,3,5,5,37,28.0,neutral or dissatisfied +4997,31577,Female,disloyal Customer,23,Business travel,Eco,602,2,5,2,3,2,2,2,2,2,5,4,5,3,2,0,0.0,neutral or dissatisfied +4998,19212,Male,Loyal Customer,40,Business travel,Business,459,4,4,4,4,4,4,2,5,5,4,5,2,5,2,0,0.0,satisfied +4999,47783,Female,Loyal Customer,34,Business travel,Business,2621,1,1,1,1,5,4,2,5,5,5,5,2,5,3,0,17.0,satisfied +5000,49243,Female,disloyal Customer,20,Business travel,Eco,110,3,0,3,3,4,3,4,4,1,1,2,3,4,4,0,4.0,neutral or dissatisfied +5001,127184,Male,disloyal Customer,22,Business travel,Business,651,4,2,4,3,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +5002,20359,Female,disloyal Customer,19,Business travel,Eco,287,5,0,5,1,1,0,1,1,3,4,3,4,5,1,0,0.0,satisfied +5003,116219,Male,Loyal Customer,11,Personal Travel,Eco,417,1,4,1,3,3,1,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +5004,28889,Female,Loyal Customer,28,Business travel,Eco,679,5,1,1,1,5,5,5,5,4,4,3,5,3,5,35,69.0,satisfied +5005,53318,Male,Loyal Customer,12,Personal Travel,Eco,758,3,4,3,1,4,3,4,4,4,2,5,5,4,4,10,6.0,neutral or dissatisfied +5006,68633,Male,Loyal Customer,45,Business travel,Business,175,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +5007,95625,Male,Loyal Customer,10,Personal Travel,Eco,822,0,5,1,4,5,1,4,5,3,3,5,3,5,5,0,0.0,satisfied +5008,99476,Male,Loyal Customer,62,Business travel,Eco,283,1,1,1,1,1,1,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +5009,100512,Female,disloyal Customer,39,Business travel,Eco,180,3,0,2,3,5,2,5,5,3,3,2,5,4,5,7,0.0,neutral or dissatisfied +5010,18483,Female,Loyal Customer,53,Business travel,Business,1907,1,1,1,1,2,5,5,4,4,4,5,1,4,2,6,13.0,satisfied +5011,69214,Male,Loyal Customer,46,Business travel,Business,2870,5,3,5,5,4,4,5,4,4,4,4,5,4,3,0,39.0,satisfied +5012,95130,Male,Loyal Customer,39,Personal Travel,Eco,341,3,2,3,3,4,3,3,4,4,3,2,4,3,4,4,0.0,neutral or dissatisfied +5013,66393,Female,Loyal Customer,56,Business travel,Business,1562,1,1,1,1,5,5,4,5,5,5,5,3,5,5,29,79.0,satisfied +5014,6990,Male,Loyal Customer,43,Business travel,Business,3061,5,5,3,5,5,5,5,4,5,5,4,5,5,5,190,192.0,satisfied +5015,62287,Female,Loyal Customer,32,Business travel,Business,2936,2,4,4,4,2,2,2,2,2,3,3,4,3,2,0,0.0,neutral or dissatisfied +5016,25271,Male,Loyal Customer,25,Business travel,Business,3681,3,3,3,3,4,4,4,4,4,5,5,1,1,4,0,0.0,satisfied +5017,105734,Male,Loyal Customer,49,Business travel,Business,2172,3,3,3,3,3,3,3,3,3,4,3,3,2,3,164,177.0,neutral or dissatisfied +5018,16849,Female,Loyal Customer,27,Business travel,Business,1728,2,2,2,2,4,4,4,4,3,2,4,3,4,4,4,22.0,satisfied +5019,117769,Male,Loyal Customer,17,Business travel,Business,1891,2,2,2,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +5020,116347,Female,Loyal Customer,39,Personal Travel,Eco,296,2,4,4,1,5,4,3,5,3,3,5,3,4,5,54,55.0,neutral or dissatisfied +5021,60006,Female,Loyal Customer,60,Personal Travel,Eco,1023,2,4,2,3,1,3,3,2,2,2,2,1,2,4,69,50.0,neutral or dissatisfied +5022,27727,Male,Loyal Customer,37,Business travel,Business,1448,3,3,3,3,2,4,2,5,5,5,5,2,5,1,0,0.0,satisfied +5023,16976,Female,Loyal Customer,38,Personal Travel,Eco,209,4,2,0,4,1,0,1,1,4,1,4,2,3,1,0,0.0,satisfied +5024,118770,Male,Loyal Customer,56,Personal Travel,Eco,646,4,2,4,4,4,4,4,4,1,2,3,4,4,4,1,2.0,neutral or dissatisfied +5025,31831,Female,Loyal Customer,37,Business travel,Business,2762,1,1,1,1,3,3,3,2,4,4,3,3,3,3,0,0.0,satisfied +5026,90957,Female,disloyal Customer,20,Business travel,Eco,250,2,0,2,3,4,2,4,4,5,4,3,1,4,4,0,0.0,neutral or dissatisfied +5027,111083,Female,Loyal Customer,27,Personal Travel,Eco,197,2,3,2,3,2,2,2,2,1,4,5,1,3,2,0,0.0,neutral or dissatisfied +5028,41619,Female,Loyal Customer,35,Business travel,Eco Plus,1269,5,5,5,5,5,5,5,5,5,4,1,3,1,5,23,41.0,satisfied +5029,129635,Male,Loyal Customer,39,Business travel,Business,1966,1,1,1,1,5,4,5,4,4,4,4,5,4,3,0,2.0,satisfied +5030,18310,Female,Loyal Customer,14,Personal Travel,Eco,549,2,1,2,4,4,2,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +5031,54982,Female,disloyal Customer,21,Business travel,Business,1303,0,5,0,4,3,0,3,3,4,4,5,3,5,3,18,0.0,satisfied +5032,129846,Male,Loyal Customer,44,Personal Travel,Eco,447,2,5,2,3,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +5033,98008,Male,Loyal Customer,32,Business travel,Business,1014,3,3,3,3,2,2,2,3,4,4,5,2,4,2,135,136.0,satisfied +5034,70743,Female,Loyal Customer,44,Personal Travel,Eco,675,1,4,0,4,2,4,4,3,3,0,3,3,3,4,0,0.0,neutral or dissatisfied +5035,21651,Male,disloyal Customer,30,Business travel,Business,746,3,3,3,3,4,3,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +5036,9538,Female,Loyal Customer,60,Business travel,Business,2775,0,0,0,3,2,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +5037,118919,Male,Loyal Customer,27,Personal Travel,Eco,587,3,5,3,4,1,3,1,1,3,2,5,4,4,1,43,38.0,neutral or dissatisfied +5038,78453,Male,Loyal Customer,40,Business travel,Business,666,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +5039,5804,Male,Loyal Customer,79,Business travel,Business,177,1,5,4,5,3,1,3,3,4,4,4,3,4,3,330,348.0,neutral or dissatisfied +5040,85893,Female,Loyal Customer,48,Business travel,Business,3078,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +5041,83401,Female,Loyal Customer,43,Business travel,Business,632,3,3,2,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +5042,50599,Female,Loyal Customer,41,Personal Travel,Eco,266,4,4,4,3,3,4,3,3,3,2,2,4,2,3,0,0.0,neutral or dissatisfied +5043,37786,Male,Loyal Customer,24,Business travel,Eco Plus,1074,3,4,5,4,3,3,1,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +5044,60154,Male,Loyal Customer,68,Personal Travel,Eco,1182,5,5,5,3,5,5,5,5,2,5,4,5,1,5,14,0.0,satisfied +5045,34091,Female,disloyal Customer,20,Business travel,Business,1129,0,0,0,3,5,0,5,5,3,4,4,4,4,5,0,0.0,satisfied +5046,126932,Female,Loyal Customer,49,Business travel,Business,338,2,1,2,2,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +5047,89765,Male,Loyal Customer,34,Personal Travel,Eco,1096,3,2,3,3,2,3,4,2,4,2,4,3,4,2,114,88.0,neutral or dissatisfied +5048,104432,Female,Loyal Customer,55,Personal Travel,Eco,1024,3,4,3,3,2,4,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +5049,68656,Female,Loyal Customer,30,Business travel,Business,3506,1,1,1,1,3,3,1,3,4,4,4,2,3,3,36,21.0,neutral or dissatisfied +5050,45608,Female,disloyal Customer,44,Business travel,Eco,230,2,3,2,4,3,2,3,3,2,1,1,5,3,3,0,0.0,neutral or dissatisfied +5051,94713,Male,Loyal Customer,59,Business travel,Business,3248,4,4,4,4,4,4,5,5,5,5,5,5,5,4,14,0.0,satisfied +5052,113350,Male,Loyal Customer,33,Business travel,Business,3538,3,4,4,4,3,3,3,3,2,3,4,3,4,3,50,45.0,neutral or dissatisfied +5053,50581,Male,Loyal Customer,62,Personal Travel,Eco,250,2,4,2,3,3,2,3,3,2,5,4,1,3,3,8,8.0,neutral or dissatisfied +5054,39395,Female,Loyal Customer,48,Business travel,Eco,546,4,1,1,1,1,2,4,4,4,4,4,1,4,2,0,0.0,satisfied +5055,33096,Female,Loyal Customer,40,Personal Travel,Eco,101,2,4,0,1,4,0,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +5056,39675,Female,Loyal Customer,41,Business travel,Business,3517,1,1,5,1,4,4,4,5,3,2,4,4,5,4,438,438.0,satisfied +5057,16074,Female,Loyal Customer,7,Personal Travel,Eco,744,2,5,2,2,5,2,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +5058,89989,Female,Loyal Customer,42,Business travel,Business,1084,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +5059,48403,Male,Loyal Customer,50,Personal Travel,Eco Plus,674,3,4,3,5,3,3,3,3,5,3,4,4,5,3,32,28.0,neutral or dissatisfied +5060,40844,Male,disloyal Customer,55,Business travel,Eco,199,1,1,1,2,4,1,4,4,2,2,2,3,1,4,0,0.0,neutral or dissatisfied +5061,97345,Male,Loyal Customer,16,Business travel,Eco,347,2,4,4,4,2,2,2,2,4,4,3,1,3,2,1,0.0,neutral or dissatisfied +5062,111608,Male,Loyal Customer,41,Business travel,Business,2867,4,4,4,4,5,5,4,5,5,5,5,3,5,3,26,14.0,satisfied +5063,20283,Male,Loyal Customer,45,Personal Travel,Eco,235,3,4,3,4,1,3,4,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +5064,3772,Male,Loyal Customer,47,Business travel,Business,599,1,1,1,1,4,4,4,5,5,5,5,3,5,4,1,5.0,satisfied +5065,34381,Male,Loyal Customer,28,Business travel,Eco,612,4,3,4,4,4,4,4,4,3,5,3,5,1,4,27,48.0,satisfied +5066,399,Male,disloyal Customer,38,Business travel,Business,164,4,4,4,3,1,4,2,1,4,4,5,5,4,1,0,0.0,satisfied +5067,113748,Female,Loyal Customer,54,Personal Travel,Eco,386,4,5,4,1,3,5,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +5068,73065,Male,Loyal Customer,54,Personal Travel,Eco Plus,944,3,3,3,4,3,3,1,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +5069,48646,Female,Loyal Customer,60,Business travel,Business,89,1,1,4,1,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +5070,54750,Male,Loyal Customer,29,Personal Travel,Eco,964,2,4,2,1,1,2,1,1,4,4,5,4,5,1,18,8.0,neutral or dissatisfied +5071,14627,Female,Loyal Customer,45,Business travel,Business,541,1,1,1,1,5,4,3,3,3,4,3,2,3,5,0,0.0,satisfied +5072,12688,Male,Loyal Customer,41,Business travel,Eco,721,3,5,5,5,3,3,3,3,3,3,3,1,5,3,0,8.0,satisfied +5073,57357,Male,Loyal Customer,9,Personal Travel,Eco,414,4,3,4,3,4,4,4,4,4,5,4,1,3,4,9,0.0,neutral or dissatisfied +5074,125107,Female,Loyal Customer,61,Business travel,Business,3470,3,3,3,3,5,4,4,5,5,5,5,4,5,4,0,5.0,satisfied +5075,74096,Female,Loyal Customer,53,Business travel,Business,678,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +5076,77948,Female,Loyal Customer,37,Business travel,Eco,214,1,5,5,5,1,1,1,1,4,3,2,3,3,1,0,4.0,neutral or dissatisfied +5077,67026,Male,Loyal Customer,29,Business travel,Business,1121,4,4,5,4,5,5,5,5,3,2,4,5,4,5,0,0.0,satisfied +5078,56936,Female,Loyal Customer,54,Business travel,Business,2434,1,1,1,1,5,5,5,4,2,3,5,5,5,5,1,0.0,satisfied +5079,16821,Male,Loyal Customer,56,Business travel,Business,645,1,0,0,3,2,4,4,4,4,0,4,4,4,3,66,50.0,neutral or dissatisfied +5080,46928,Male,disloyal Customer,38,Business travel,Eco,419,3,1,3,4,4,3,2,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +5081,55850,Male,Loyal Customer,27,Personal Travel,Eco,1416,1,1,1,3,1,1,1,1,4,1,3,2,3,1,0,12.0,neutral or dissatisfied +5082,9848,Male,Loyal Customer,58,Business travel,Eco,642,3,1,1,1,3,3,3,3,1,4,4,2,4,3,43,46.0,neutral or dissatisfied +5083,20207,Female,Loyal Customer,55,Personal Travel,Business,179,3,5,3,2,2,5,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +5084,33690,Female,Loyal Customer,59,Business travel,Business,2864,3,3,3,3,5,2,3,3,3,3,3,1,3,1,9,19.0,neutral or dissatisfied +5085,27208,Male,Loyal Customer,65,Business travel,Business,1217,3,5,5,5,3,3,3,3,5,3,3,3,4,3,0,27.0,neutral or dissatisfied +5086,85204,Male,Loyal Customer,46,Business travel,Business,2938,4,4,4,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +5087,51954,Female,Loyal Customer,39,Business travel,Eco,347,5,1,1,1,5,4,5,5,2,2,2,2,2,5,0,0.0,satisfied +5088,46042,Female,disloyal Customer,23,Business travel,Eco,991,1,1,1,4,4,1,4,4,3,1,3,1,4,4,7,48.0,neutral or dissatisfied +5089,86144,Female,Loyal Customer,43,Business travel,Business,356,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +5090,118814,Male,Loyal Customer,27,Business travel,Business,2487,2,2,2,2,5,5,5,5,3,3,4,4,4,5,24,27.0,satisfied +5091,127330,Male,Loyal Customer,60,Business travel,Business,507,2,2,2,2,5,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +5092,86021,Male,Loyal Customer,51,Business travel,Business,2397,2,2,2,2,3,4,1,4,4,4,4,5,4,3,0,0.0,satisfied +5093,935,Male,Loyal Customer,24,Business travel,Business,2357,2,2,2,2,4,4,5,4,3,2,5,3,4,4,0,0.0,satisfied +5094,111622,Male,Loyal Customer,48,Personal Travel,Eco,1014,3,3,3,4,1,3,1,1,2,1,4,1,4,1,33,14.0,neutral or dissatisfied +5095,49893,Female,Loyal Customer,30,Business travel,Eco,77,1,4,3,3,1,1,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +5096,129491,Female,Loyal Customer,18,Personal Travel,Eco,2611,3,5,3,2,3,3,3,3,4,2,3,5,4,3,0,0.0,neutral or dissatisfied +5097,2939,Male,Loyal Customer,38,Personal Travel,Business,737,4,4,4,4,3,5,5,1,1,4,1,5,1,3,15,82.0,neutral or dissatisfied +5098,20297,Female,Loyal Customer,36,Personal Travel,Eco,228,2,4,2,3,3,2,3,3,3,3,4,4,4,3,31,10.0,neutral or dissatisfied +5099,51328,Female,Loyal Customer,49,Business travel,Eco Plus,109,2,3,5,3,1,2,2,2,2,2,2,3,2,2,62,55.0,neutral or dissatisfied +5100,56896,Female,Loyal Customer,41,Business travel,Business,2454,4,4,4,4,3,3,4,2,2,2,2,4,2,4,5,0.0,satisfied +5101,7265,Female,Loyal Customer,19,Personal Travel,Eco,130,3,3,3,5,2,3,2,2,1,3,5,2,4,2,0,0.0,neutral or dissatisfied +5102,108404,Female,Loyal Customer,54,Business travel,Business,1855,2,2,2,2,3,5,5,2,2,3,2,5,2,4,5,0.0,satisfied +5103,15901,Male,Loyal Customer,44,Personal Travel,Eco,378,3,5,3,1,2,3,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +5104,72720,Male,Loyal Customer,57,Business travel,Business,1121,4,4,4,4,4,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +5105,60780,Female,Loyal Customer,63,Personal Travel,Eco,628,1,4,1,2,3,5,5,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +5106,62478,Male,Loyal Customer,48,Business travel,Business,1744,2,2,2,2,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +5107,11806,Male,Loyal Customer,32,Personal Travel,Eco Plus,395,2,3,2,4,2,2,2,2,4,4,4,4,3,2,16,5.0,neutral or dissatisfied +5108,832,Female,Loyal Customer,38,Business travel,Business,134,1,3,3,3,3,4,4,2,2,2,1,1,2,3,0,16.0,neutral or dissatisfied +5109,28966,Female,Loyal Customer,36,Business travel,Business,2421,1,5,5,5,4,3,2,1,1,2,1,4,1,3,24,24.0,neutral or dissatisfied +5110,10413,Male,Loyal Customer,43,Business travel,Business,201,0,4,0,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +5111,125170,Female,Loyal Customer,45,Personal Travel,Eco,1089,3,5,3,5,2,3,2,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +5112,23037,Male,Loyal Customer,24,Personal Travel,Eco,1080,1,5,1,4,2,1,2,2,3,3,4,3,2,2,11,28.0,neutral or dissatisfied +5113,59642,Female,disloyal Customer,22,Business travel,Business,964,2,2,2,3,2,2,5,2,1,5,3,3,3,2,17,3.0,neutral or dissatisfied +5114,28719,Male,Loyal Customer,28,Personal Travel,Eco,2554,3,4,3,5,3,2,2,4,2,3,5,2,5,2,0,0.0,neutral or dissatisfied +5115,110952,Male,Loyal Customer,60,Personal Travel,Eco Plus,404,3,5,3,1,1,3,1,1,2,2,1,3,4,1,33,16.0,neutral or dissatisfied +5116,2610,Male,Loyal Customer,10,Personal Travel,Eco,304,3,4,3,3,3,3,3,3,5,2,4,5,5,3,20,31.0,neutral or dissatisfied +5117,120916,Male,Loyal Customer,34,Business travel,Business,1965,1,1,1,1,3,5,5,3,3,3,3,5,3,3,0,48.0,satisfied +5118,68026,Female,Loyal Customer,28,Personal Travel,Eco,304,2,4,2,1,5,2,5,5,3,2,4,5,5,5,0,2.0,neutral or dissatisfied +5119,48745,Male,Loyal Customer,58,Business travel,Business,109,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +5120,17866,Female,Loyal Customer,39,Business travel,Business,2814,2,2,2,2,4,3,1,4,4,4,4,3,4,2,12,0.0,satisfied +5121,25957,Female,Loyal Customer,48,Business travel,Business,946,2,2,2,2,3,4,5,5,5,5,5,4,5,2,10,0.0,satisfied +5122,1065,Female,Loyal Customer,42,Personal Travel,Eco,164,3,1,3,2,4,3,3,1,1,3,1,1,1,1,2,1.0,neutral or dissatisfied +5123,117054,Female,Loyal Customer,72,Business travel,Business,2991,2,3,5,3,1,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +5124,129407,Male,Loyal Customer,56,Business travel,Eco,236,3,3,3,3,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +5125,78977,Male,Loyal Customer,51,Business travel,Business,1989,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,31.0,satisfied +5126,41802,Female,Loyal Customer,37,Business travel,Eco,196,2,3,3,3,2,2,2,2,4,3,3,2,2,2,0,0.0,neutral or dissatisfied +5127,104580,Male,Loyal Customer,30,Business travel,Business,2883,4,4,4,4,4,4,4,4,4,5,5,5,4,4,86,93.0,satisfied +5128,90192,Female,Loyal Customer,11,Personal Travel,Eco,1022,3,2,3,3,4,3,4,4,4,2,3,2,3,4,10,13.0,neutral or dissatisfied +5129,86280,Male,Loyal Customer,48,Personal Travel,Eco,306,3,5,3,1,4,3,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +5130,26503,Female,Loyal Customer,66,Business travel,Eco,837,3,4,4,4,3,3,2,3,3,3,3,1,3,4,14,8.0,neutral or dissatisfied +5131,31288,Female,Loyal Customer,29,Personal Travel,Eco,533,3,5,3,1,4,3,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +5132,62574,Female,Loyal Customer,27,Business travel,Business,1846,2,4,4,4,2,2,2,2,4,3,3,4,4,2,16,1.0,neutral or dissatisfied +5133,127149,Male,Loyal Customer,65,Personal Travel,Eco,304,2,4,2,2,5,2,5,5,5,3,5,3,4,5,8,11.0,neutral or dissatisfied +5134,87002,Female,Loyal Customer,38,Personal Travel,Eco,907,4,5,3,1,1,3,1,1,5,3,5,4,4,1,17,5.0,satisfied +5135,94787,Male,Loyal Customer,42,Business travel,Business,2124,4,4,3,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +5136,88500,Female,Loyal Customer,58,Business travel,Eco,246,5,3,3,3,3,3,5,5,5,5,5,3,5,2,5,1.0,satisfied +5137,66345,Female,Loyal Customer,37,Business travel,Business,2037,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +5138,2275,Female,Loyal Customer,52,Business travel,Business,691,4,4,4,4,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +5139,12046,Female,Loyal Customer,53,Business travel,Business,3025,2,2,1,2,5,3,3,4,4,4,4,2,4,4,0,7.0,satisfied +5140,43798,Female,Loyal Customer,60,Business travel,Business,748,2,4,4,4,4,4,3,2,2,2,2,2,2,2,0,20.0,neutral or dissatisfied +5141,68123,Female,Loyal Customer,47,Personal Travel,Eco,813,3,2,3,3,2,2,2,4,4,3,3,1,4,1,13,9.0,neutral or dissatisfied +5142,113044,Male,Loyal Customer,23,Business travel,Business,479,5,5,5,5,5,4,5,5,3,5,5,3,4,5,0,0.0,satisfied +5143,24219,Male,disloyal Customer,26,Business travel,Eco,147,2,2,2,4,4,2,3,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +5144,29932,Female,disloyal Customer,51,Business travel,Eco,548,3,1,3,3,2,3,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +5145,80028,Male,Loyal Customer,36,Personal Travel,Eco,1076,3,3,3,3,1,3,1,1,2,4,3,3,3,1,3,0.0,neutral or dissatisfied +5146,101764,Female,Loyal Customer,30,Personal Travel,Eco,1590,5,1,5,4,4,5,3,4,1,1,3,4,4,4,0,0.0,satisfied +5147,89071,Female,Loyal Customer,51,Business travel,Business,1947,4,4,4,4,5,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +5148,12948,Male,Loyal Customer,57,Personal Travel,Eco,775,1,1,1,4,1,1,1,1,4,5,4,2,4,1,0,0.0,neutral or dissatisfied +5149,64944,Female,Loyal Customer,48,Business travel,Business,2745,4,4,4,4,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +5150,39419,Female,disloyal Customer,22,Business travel,Eco,129,4,5,4,2,4,4,4,4,5,4,2,2,1,4,0,0.0,satisfied +5151,127846,Female,Loyal Customer,43,Business travel,Business,3635,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +5152,121333,Female,Loyal Customer,61,Business travel,Business,2384,4,2,2,2,1,4,4,4,4,4,4,4,4,3,0,11.0,neutral or dissatisfied +5153,122681,Female,Loyal Customer,47,Business travel,Business,1737,5,3,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +5154,95015,Female,Loyal Customer,60,Personal Travel,Eco,248,2,5,0,1,2,5,5,2,2,0,3,4,2,3,0,0.0,neutral or dissatisfied +5155,83532,Male,Loyal Customer,33,Personal Travel,Business,1121,3,5,3,3,4,3,4,4,5,2,4,5,5,4,0,3.0,neutral or dissatisfied +5156,95692,Female,Loyal Customer,55,Business travel,Eco,419,3,3,4,4,4,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +5157,65394,Male,Loyal Customer,55,Personal Travel,Eco,432,2,4,2,1,4,2,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +5158,113725,Female,Loyal Customer,56,Personal Travel,Eco,391,4,5,4,5,2,3,2,4,4,4,5,2,4,5,0,0.0,neutral or dissatisfied +5159,92066,Female,Loyal Customer,39,Business travel,Business,1535,3,3,5,3,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +5160,74863,Female,Loyal Customer,56,Personal Travel,Eco,1995,2,1,2,4,4,3,4,3,3,2,3,4,3,4,0,8.0,neutral or dissatisfied +5161,64245,Male,Loyal Customer,45,Personal Travel,Eco,1660,4,3,4,2,5,4,5,5,1,4,4,5,4,5,16,14.0,satisfied +5162,98283,Female,disloyal Customer,62,Business travel,Eco,736,5,5,5,2,5,5,1,5,3,4,5,5,3,5,8,0.0,satisfied +5163,113782,Female,Loyal Customer,56,Business travel,Business,3358,4,5,4,4,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +5164,63635,Male,Loyal Customer,49,Business travel,Business,2683,2,2,2,2,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +5165,73148,Female,Loyal Customer,42,Business travel,Eco Plus,1068,3,3,3,3,2,4,3,2,2,3,2,2,2,1,0,4.0,neutral or dissatisfied +5166,17366,Female,Loyal Customer,32,Personal Travel,Eco,563,2,4,2,1,3,2,2,3,4,5,5,5,3,3,9,3.0,neutral or dissatisfied +5167,14541,Male,Loyal Customer,38,Business travel,Business,368,2,5,5,5,2,2,2,4,5,3,3,2,3,2,147,135.0,neutral or dissatisfied +5168,127845,Female,disloyal Customer,48,Business travel,Business,1276,5,5,5,1,1,5,1,1,3,5,4,4,4,1,0,0.0,satisfied +5169,96847,Female,Loyal Customer,59,Business travel,Business,849,2,2,2,2,4,5,4,3,3,3,3,4,3,3,6,0.0,satisfied +5170,54581,Male,disloyal Customer,42,Business travel,Business,3904,3,3,3,3,3,5,5,5,2,4,3,5,2,5,43,26.0,satisfied +5171,15837,Female,disloyal Customer,57,Business travel,Eco Plus,1148,1,1,1,3,1,1,1,1,1,3,4,1,2,1,149,115.0,neutral or dissatisfied +5172,25528,Male,Loyal Customer,17,Personal Travel,Eco,547,2,4,2,3,2,2,2,2,3,2,5,4,4,2,19,2.0,neutral or dissatisfied +5173,101520,Male,Loyal Customer,35,Personal Travel,Eco,345,2,3,2,3,1,2,1,1,3,5,4,5,1,1,6,1.0,neutral or dissatisfied +5174,52287,Male,Loyal Customer,55,Business travel,Eco,451,2,5,5,5,2,2,2,2,3,4,3,1,4,2,16,7.0,neutral or dissatisfied +5175,76239,Female,Loyal Customer,51,Business travel,Eco,999,5,1,1,1,4,5,1,5,5,5,5,4,5,2,9,38.0,satisfied +5176,7865,Female,Loyal Customer,57,Business travel,Eco,910,2,4,4,4,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +5177,1110,Female,Loyal Customer,10,Personal Travel,Eco,102,3,3,3,2,1,3,4,1,1,1,2,3,1,1,0,0.0,neutral or dissatisfied +5178,81253,Male,Loyal Customer,58,Business travel,Business,2671,2,2,2,2,3,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +5179,24462,Male,Loyal Customer,41,Business travel,Business,2299,1,1,4,1,1,5,1,4,4,4,4,5,4,5,0,0.0,satisfied +5180,44503,Female,Loyal Customer,29,Personal Travel,Eco,411,1,2,1,3,5,1,4,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +5181,89882,Male,Loyal Customer,49,Business travel,Business,1306,1,2,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +5182,119991,Male,Loyal Customer,60,Personal Travel,Eco Plus,1009,1,2,1,3,5,1,5,5,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +5183,16344,Male,Loyal Customer,31,Business travel,Business,1693,3,2,2,2,2,2,3,2,4,2,4,1,4,2,110,99.0,neutral or dissatisfied +5184,102281,Female,disloyal Customer,38,Business travel,Eco,226,3,2,3,3,3,3,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +5185,23178,Male,Loyal Customer,18,Personal Travel,Eco,250,1,4,1,5,3,1,5,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +5186,111073,Male,Loyal Customer,52,Personal Travel,Eco,197,3,5,3,3,5,3,5,5,4,4,5,4,4,5,8,0.0,neutral or dissatisfied +5187,24190,Male,Loyal Customer,51,Business travel,Eco,151,4,2,5,5,4,4,4,4,1,5,4,3,1,4,0,0.0,satisfied +5188,76177,Female,Loyal Customer,17,Personal Travel,Eco Plus,689,2,3,2,3,3,2,3,3,4,4,3,2,4,3,2,10.0,neutral or dissatisfied +5189,87182,Male,Loyal Customer,30,Business travel,Business,1631,3,5,5,5,3,3,3,3,3,3,4,2,3,3,1,8.0,neutral or dissatisfied +5190,97446,Female,Loyal Customer,39,Business travel,Business,670,1,1,1,1,2,5,4,5,5,5,5,5,5,4,6,3.0,satisfied +5191,23808,Female,Loyal Customer,24,Personal Travel,Eco,374,2,2,2,3,5,2,4,5,3,2,3,4,4,5,3,5.0,neutral or dissatisfied +5192,1373,Male,Loyal Customer,46,Business travel,Business,3492,3,1,1,1,3,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +5193,87198,Female,disloyal Customer,25,Business travel,Eco,946,1,1,1,4,4,1,4,4,2,2,4,4,4,4,1,17.0,neutral or dissatisfied +5194,88423,Male,Loyal Customer,44,Business travel,Business,1889,2,2,1,2,3,5,5,3,3,3,3,5,3,5,0,1.0,satisfied +5195,81547,Male,Loyal Customer,31,Personal Travel,Eco,1124,4,5,5,2,1,5,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +5196,78056,Male,Loyal Customer,48,Personal Travel,Eco,214,3,0,3,3,4,3,4,4,4,1,3,1,5,4,11,22.0,neutral or dissatisfied +5197,129210,Female,Loyal Customer,67,Personal Travel,Eco,2442,2,5,2,5,2,5,5,1,1,2,1,3,1,3,12,30.0,neutral or dissatisfied +5198,66653,Female,disloyal Customer,26,Business travel,Business,802,3,0,3,3,1,3,1,1,4,4,4,3,5,1,1,22.0,neutral or dissatisfied +5199,16162,Male,Loyal Customer,55,Business travel,Eco,199,5,4,4,4,5,5,5,5,5,4,3,1,5,5,0,0.0,satisfied +5200,120320,Male,Loyal Customer,70,Personal Travel,Eco,268,4,5,0,2,4,0,4,4,4,1,1,3,4,4,0,0.0,neutral or dissatisfied +5201,495,Female,Loyal Customer,59,Business travel,Business,3621,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,4.0,satisfied +5202,20936,Male,Loyal Customer,43,Business travel,Eco,803,5,3,3,3,5,5,5,5,4,5,1,4,3,5,11,0.0,satisfied +5203,29699,Male,Loyal Customer,60,Business travel,Business,1542,4,4,4,4,1,5,4,4,4,4,4,3,4,2,0,0.0,satisfied +5204,41796,Female,disloyal Customer,20,Business travel,Eco,489,4,3,4,5,3,4,3,3,2,5,1,2,2,3,1,15.0,satisfied +5205,37698,Female,Loyal Customer,34,Personal Travel,Eco,944,3,3,2,4,3,2,3,3,3,4,4,4,3,3,85,72.0,neutral or dissatisfied +5206,93113,Male,Loyal Customer,57,Business travel,Business,1723,5,5,1,5,5,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +5207,40613,Female,Loyal Customer,54,Personal Travel,Eco,391,0,4,0,2,3,5,5,2,2,0,3,3,2,3,18,14.0,satisfied +5208,80839,Female,Loyal Customer,29,Business travel,Business,484,1,1,2,1,5,5,5,5,5,5,5,3,4,5,9,5.0,satisfied +5209,10100,Male,Loyal Customer,32,Personal Travel,Eco,961,1,5,2,3,2,5,5,3,5,5,5,5,3,5,472,446.0,neutral or dissatisfied +5210,127518,Female,Loyal Customer,49,Personal Travel,Eco Plus,1814,2,5,2,4,3,4,5,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +5211,104394,Female,Loyal Customer,24,Business travel,Business,1011,1,1,5,1,3,3,3,3,4,2,4,5,5,3,0,0.0,satisfied +5212,116770,Female,Loyal Customer,56,Personal Travel,Eco Plus,372,3,4,5,1,4,4,5,2,2,5,2,5,2,3,0,0.0,neutral or dissatisfied +5213,45489,Male,Loyal Customer,24,Personal Travel,Eco,522,4,4,4,3,4,4,3,4,3,2,4,3,4,4,0,0.0,satisfied +5214,44278,Male,Loyal Customer,29,Business travel,Eco Plus,222,5,5,5,5,5,5,5,5,1,4,5,3,2,5,0,0.0,satisfied +5215,102301,Male,Loyal Customer,35,Business travel,Business,397,1,0,0,3,1,3,2,3,3,0,3,1,3,2,0,0.0,neutral or dissatisfied +5216,114914,Male,Loyal Customer,32,Business travel,Business,3942,1,1,1,1,5,5,5,5,3,2,5,4,4,5,6,0.0,satisfied +5217,6454,Female,Loyal Customer,43,Business travel,Business,3245,0,0,0,4,5,5,5,2,2,2,2,4,2,5,27,102.0,satisfied +5218,48777,Female,Loyal Customer,58,Business travel,Business,1543,2,2,2,2,4,3,4,3,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +5219,82888,Male,Loyal Customer,70,Personal Travel,Eco,594,5,4,5,2,5,5,1,5,4,3,4,1,5,5,0,0.0,satisfied +5220,44353,Female,Loyal Customer,48,Business travel,Business,596,2,2,4,2,5,5,4,5,5,5,5,5,5,4,0,8.0,satisfied +5221,71754,Female,Loyal Customer,50,Business travel,Business,1744,2,2,2,2,2,5,4,2,2,2,2,5,2,5,20,37.0,satisfied +5222,121057,Female,Loyal Customer,48,Personal Travel,Eco,951,2,5,2,1,2,4,5,4,4,2,4,4,4,1,6,0.0,neutral or dissatisfied +5223,37557,Male,Loyal Customer,36,Business travel,Business,702,3,3,3,3,5,2,1,5,5,5,5,3,5,3,0,0.0,satisfied +5224,104146,Male,Loyal Customer,46,Business travel,Business,349,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +5225,93351,Female,Loyal Customer,38,Business travel,Business,836,3,3,3,3,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +5226,27617,Female,Loyal Customer,44,Business travel,Eco Plus,1050,5,1,1,1,4,2,2,5,5,5,5,1,5,1,0,0.0,satisfied +5227,100037,Female,Loyal Customer,25,Business travel,Eco,289,4,3,3,3,4,4,3,4,3,3,4,2,2,4,1,0.0,satisfied +5228,125741,Male,disloyal Customer,20,Business travel,Eco,861,4,4,4,1,2,4,3,2,5,4,5,4,5,2,0,0.0,satisfied +5229,10195,Female,Loyal Customer,49,Business travel,Business,2712,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +5230,18124,Male,Loyal Customer,54,Business travel,Eco,120,4,4,5,5,4,4,4,4,4,1,1,1,3,4,0,0.0,satisfied +5231,91426,Male,Loyal Customer,11,Personal Travel,Eco,549,4,3,4,3,1,4,1,1,1,2,4,1,4,1,3,3.0,neutral or dissatisfied +5232,127090,Female,Loyal Customer,43,Business travel,Business,221,1,5,5,5,4,4,4,2,2,2,1,4,2,3,0,0.0,neutral or dissatisfied +5233,97011,Male,Loyal Customer,49,Personal Travel,Eco,359,3,5,4,1,1,4,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +5234,46400,Male,Loyal Customer,68,Business travel,Eco Plus,613,5,2,3,2,4,5,4,4,4,2,2,5,5,4,0,0.0,satisfied +5235,10669,Female,Loyal Customer,45,Business travel,Business,247,2,2,3,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +5236,72454,Male,Loyal Customer,41,Business travel,Business,1966,5,5,5,5,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +5237,42222,Male,disloyal Customer,27,Business travel,Eco,451,2,5,2,3,4,2,4,4,1,3,4,2,4,4,92,93.0,neutral or dissatisfied +5238,123653,Male,Loyal Customer,38,Business travel,Business,214,3,3,5,5,4,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +5239,31226,Female,Loyal Customer,54,Business travel,Eco Plus,628,5,1,1,1,5,3,1,5,5,5,5,2,5,2,2,0.0,satisfied +5240,73427,Male,Loyal Customer,31,Personal Travel,Eco,1197,2,5,2,4,2,2,2,2,1,1,3,2,2,2,0,0.0,neutral or dissatisfied +5241,87649,Male,Loyal Customer,66,Business travel,Eco,606,2,5,4,5,2,3,3,3,3,3,3,3,3,3,149,142.0,neutral or dissatisfied +5242,43288,Female,disloyal Customer,39,Business travel,Business,387,2,2,2,5,5,2,3,5,2,1,3,3,5,5,0,0.0,neutral or dissatisfied +5243,50819,Male,Loyal Customer,15,Personal Travel,Eco,86,4,4,4,1,3,4,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +5244,12631,Male,Loyal Customer,53,Business travel,Eco,844,4,5,5,5,4,4,4,4,3,5,3,3,4,4,33,19.0,satisfied +5245,59079,Male,disloyal Customer,24,Business travel,Eco,1723,3,3,3,3,3,3,3,3,5,4,5,1,3,3,9,0.0,neutral or dissatisfied +5246,29924,Male,Loyal Customer,46,Business travel,Business,503,3,3,3,3,1,5,5,3,3,4,3,1,3,3,29,44.0,satisfied +5247,97541,Male,Loyal Customer,9,Business travel,Eco,675,1,4,4,4,1,1,4,1,3,1,3,1,3,1,48,40.0,neutral or dissatisfied +5248,67243,Female,Loyal Customer,31,Personal Travel,Eco,985,3,4,3,3,1,3,1,1,5,4,5,5,5,1,0,11.0,neutral or dissatisfied +5249,124669,Male,Loyal Customer,42,Business travel,Business,1558,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +5250,90447,Female,disloyal Customer,36,Business travel,Business,270,1,0,0,2,1,0,1,1,4,5,4,5,5,1,0,1.0,neutral or dissatisfied +5251,3469,Female,Loyal Customer,61,Personal Travel,Eco Plus,315,3,3,3,3,1,3,4,5,5,3,5,3,5,1,0,60.0,neutral or dissatisfied +5252,26555,Female,Loyal Customer,29,Business travel,Business,581,3,3,3,3,4,4,4,4,4,5,4,4,4,4,15,39.0,satisfied +5253,83818,Female,Loyal Customer,59,Business travel,Business,425,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +5254,23548,Female,disloyal Customer,18,Business travel,Eco Plus,455,2,4,2,4,3,2,4,3,5,4,1,4,4,3,27,30.0,neutral or dissatisfied +5255,62957,Female,Loyal Customer,25,Business travel,Business,2089,2,5,5,5,2,2,2,2,3,1,3,1,4,2,12,27.0,neutral or dissatisfied +5256,67948,Female,Loyal Customer,65,Personal Travel,Eco,1235,2,4,2,1,4,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +5257,115623,Female,Loyal Customer,51,Business travel,Business,417,3,3,3,3,1,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +5258,84423,Female,Loyal Customer,13,Personal Travel,Eco,591,2,1,2,3,3,2,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +5259,82754,Male,Loyal Customer,33,Business travel,Business,409,2,4,2,4,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +5260,53997,Female,Loyal Customer,64,Personal Travel,Eco,1825,4,3,4,4,5,2,3,4,4,4,1,2,4,4,14,44.0,neutral or dissatisfied +5261,53500,Male,Loyal Customer,28,Personal Travel,Eco,2442,3,1,3,4,3,3,3,3,1,4,3,3,3,3,8,14.0,neutral or dissatisfied +5262,96376,Male,Loyal Customer,45,Business travel,Eco,1407,3,1,3,1,2,3,2,2,3,2,4,3,4,2,43,41.0,neutral or dissatisfied +5263,19688,Male,Loyal Customer,34,Business travel,Business,3444,5,1,5,5,3,2,4,5,5,5,5,4,5,5,104,106.0,satisfied +5264,51247,Female,Loyal Customer,26,Business travel,Eco Plus,363,0,4,0,5,4,0,4,4,5,3,3,1,2,4,4,0.0,satisfied +5265,45947,Female,Loyal Customer,35,Personal Travel,Eco,775,4,4,4,3,2,4,4,2,5,4,4,4,5,2,61,65.0,neutral or dissatisfied +5266,53058,Male,Loyal Customer,42,Personal Travel,Eco,1208,4,4,4,3,1,4,1,1,4,3,3,3,3,1,0,5.0,neutral or dissatisfied +5267,62741,Female,Loyal Customer,29,Business travel,Business,2556,3,3,3,3,5,5,5,3,4,3,4,5,4,5,0,19.0,satisfied +5268,69410,Female,Loyal Customer,43,Business travel,Business,2377,2,2,2,2,3,2,3,2,2,1,2,4,2,4,0,2.0,neutral or dissatisfied +5269,95216,Female,Loyal Customer,43,Personal Travel,Eco,293,4,3,4,3,1,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +5270,74446,Male,Loyal Customer,46,Business travel,Business,1431,5,5,4,5,2,4,4,4,4,4,4,5,4,3,14,0.0,satisfied +5271,78562,Male,disloyal Customer,24,Business travel,Business,630,4,0,4,3,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +5272,72279,Male,disloyal Customer,25,Business travel,Eco,519,2,2,2,2,5,2,5,5,2,3,1,3,1,5,0,2.0,neutral or dissatisfied +5273,122159,Male,Loyal Customer,43,Business travel,Business,541,1,1,3,1,5,5,4,4,4,4,4,4,4,3,115,115.0,satisfied +5274,35328,Female,Loyal Customer,26,Business travel,Business,944,4,3,4,4,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +5275,117514,Male,Loyal Customer,17,Business travel,Eco Plus,507,3,5,3,3,3,3,1,3,2,3,4,4,3,3,90,85.0,neutral or dissatisfied +5276,97150,Female,Loyal Customer,58,Business travel,Business,3858,2,1,1,1,4,3,3,2,2,2,2,3,2,4,0,13.0,neutral or dissatisfied +5277,47368,Female,disloyal Customer,22,Business travel,Business,558,3,4,4,4,1,4,1,1,4,1,3,4,4,1,23,21.0,neutral or dissatisfied +5278,34245,Female,Loyal Customer,46,Business travel,Business,1666,4,4,4,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +5279,91609,Male,disloyal Customer,38,Business travel,Business,1199,1,1,1,2,2,1,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +5280,60644,Female,Loyal Customer,46,Business travel,Business,1620,3,3,3,3,3,4,4,5,5,5,5,5,5,5,52,61.0,satisfied +5281,64062,Male,Loyal Customer,60,Business travel,Eco,919,2,3,2,3,2,2,2,2,3,4,4,1,3,2,0,0.0,neutral or dissatisfied +5282,97135,Male,disloyal Customer,23,Business travel,Eco,971,4,4,4,4,5,4,5,5,2,5,4,4,3,5,15,4.0,neutral or dissatisfied +5283,23467,Female,disloyal Customer,34,Business travel,Eco,488,2,0,2,2,5,2,5,5,5,3,2,1,5,5,68,87.0,neutral or dissatisfied +5284,122296,Female,Loyal Customer,62,Personal Travel,Eco,544,2,0,2,2,2,5,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +5285,110878,Female,Loyal Customer,50,Business travel,Business,2873,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +5286,62617,Female,Loyal Customer,50,Personal Travel,Eco,1846,3,0,3,2,5,5,2,2,2,3,2,2,2,4,5,0.0,neutral or dissatisfied +5287,80404,Female,Loyal Customer,58,Business travel,Business,1416,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5288,27666,Female,Loyal Customer,39,Business travel,Business,1710,5,5,5,5,3,1,4,5,5,5,5,4,5,5,0,0.0,satisfied +5289,67447,Female,Loyal Customer,18,Personal Travel,Eco,592,4,4,4,4,1,4,1,1,3,1,5,2,2,1,0,0.0,neutral or dissatisfied +5290,63480,Male,Loyal Customer,34,Personal Travel,Eco Plus,372,2,2,2,3,5,2,1,5,1,1,3,3,3,5,5,0.0,neutral or dissatisfied +5291,76387,Male,Loyal Customer,61,Business travel,Business,531,5,5,5,5,3,3,5,5,5,5,5,2,5,4,0,0.0,satisfied +5292,62124,Male,disloyal Customer,20,Business travel,Eco,1234,4,4,4,3,5,4,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +5293,47892,Male,Loyal Customer,52,Business travel,Eco,451,4,1,1,1,4,4,4,4,3,4,4,1,5,4,0,0.0,satisfied +5294,65580,Female,Loyal Customer,56,Business travel,Business,2843,1,1,1,1,4,4,5,4,4,4,5,5,4,4,2,0.0,satisfied +5295,19597,Male,Loyal Customer,28,Personal Travel,Eco,173,0,5,0,3,5,0,5,5,4,4,5,3,4,5,24,,satisfied +5296,47977,Female,Loyal Customer,47,Personal Travel,Eco,834,1,1,1,3,2,2,3,3,3,1,2,4,3,2,0,,neutral or dissatisfied +5297,12880,Female,Loyal Customer,30,Business travel,Business,3196,3,1,1,1,3,3,3,3,2,4,3,1,1,3,14,14.0,neutral or dissatisfied +5298,14205,Female,Loyal Customer,48,Business travel,Business,3465,1,4,4,4,1,3,4,1,1,1,1,1,1,1,0,4.0,neutral or dissatisfied +5299,102893,Male,Loyal Customer,40,Business travel,Business,1037,2,2,2,2,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +5300,63547,Male,Loyal Customer,25,Personal Travel,Eco,1009,2,1,2,2,1,2,1,1,2,2,2,1,3,1,0,0.0,neutral or dissatisfied +5301,69599,Female,Loyal Customer,10,Personal Travel,Eco,2475,4,4,3,4,3,1,1,5,3,4,5,1,3,1,0,7.0,neutral or dissatisfied +5302,108338,Male,Loyal Customer,59,Business travel,Business,1855,4,4,4,4,5,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +5303,70825,Male,Loyal Customer,57,Personal Travel,Eco Plus,624,1,5,0,3,1,0,1,1,3,1,2,5,3,1,0,0.0,neutral or dissatisfied +5304,15671,Female,Loyal Customer,41,Business travel,Eco,617,5,3,3,3,5,5,5,5,5,3,5,5,2,5,0,0.0,satisfied +5305,103296,Male,Loyal Customer,7,Personal Travel,Eco,872,2,1,2,2,1,2,1,1,4,5,3,4,3,1,27,14.0,neutral or dissatisfied +5306,127696,Male,Loyal Customer,57,Business travel,Business,2133,4,4,4,4,2,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +5307,2506,Female,Loyal Customer,46,Business travel,Business,2141,1,1,1,1,3,5,4,3,3,4,3,4,3,3,10,3.0,satisfied +5308,125421,Female,Loyal Customer,51,Business travel,Business,735,4,4,5,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +5309,1543,Male,Loyal Customer,63,Business travel,Business,587,2,3,3,3,3,2,2,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +5310,33107,Female,Loyal Customer,30,Personal Travel,Eco,163,1,4,1,4,3,1,3,3,1,3,1,3,2,3,0,0.0,neutral or dissatisfied +5311,51810,Female,Loyal Customer,33,Personal Travel,Eco,751,2,5,2,1,3,2,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +5312,105228,Female,Loyal Customer,57,Business travel,Business,1914,1,1,1,1,2,1,1,1,1,1,1,2,1,1,31,26.0,neutral or dissatisfied +5313,128062,Male,Loyal Customer,60,Business travel,Business,2979,4,4,2,4,4,4,4,5,4,4,5,4,4,4,0,42.0,satisfied +5314,46967,Female,Loyal Customer,36,Personal Travel,Eco,964,3,4,3,5,2,3,2,2,5,3,5,3,4,2,41,51.0,neutral or dissatisfied +5315,123463,Male,Loyal Customer,40,Business travel,Business,2077,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +5316,18127,Male,Loyal Customer,35,Business travel,Eco,120,4,4,3,4,4,4,4,4,5,2,5,1,2,4,0,0.0,satisfied +5317,14194,Male,disloyal Customer,38,Business travel,Eco,620,1,3,0,3,5,0,5,5,1,4,3,4,3,5,0,9.0,neutral or dissatisfied +5318,38217,Male,Loyal Customer,63,Business travel,Eco Plus,721,3,3,3,3,3,3,3,3,3,5,3,1,3,3,42,47.0,neutral or dissatisfied +5319,65416,Male,Loyal Customer,14,Personal Travel,Eco Plus,631,2,4,2,3,2,2,2,2,3,4,4,1,3,2,4,9.0,neutral or dissatisfied +5320,20546,Male,Loyal Customer,29,Business travel,Business,3065,1,1,1,1,5,5,5,5,4,3,2,4,1,5,0,7.0,satisfied +5321,91210,Male,Loyal Customer,36,Personal Travel,Eco,404,2,5,2,4,4,2,3,4,4,2,4,5,5,4,0,26.0,neutral or dissatisfied +5322,18805,Male,Loyal Customer,53,Business travel,Business,1961,2,2,4,2,4,4,3,5,5,4,5,5,5,3,0,0.0,satisfied +5323,38455,Female,Loyal Customer,26,Business travel,Business,3579,2,4,4,4,2,2,2,2,3,4,3,1,4,2,6,0.0,neutral or dissatisfied +5324,54506,Male,disloyal Customer,8,Business travel,Eco,978,3,3,3,1,4,3,2,4,1,5,3,3,2,4,3,0.0,neutral or dissatisfied +5325,97883,Female,Loyal Customer,36,Business travel,Business,612,4,4,4,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +5326,112901,Female,disloyal Customer,25,Business travel,Business,1476,3,4,2,2,4,2,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +5327,33375,Female,Loyal Customer,58,Personal Travel,Eco,2399,2,2,2,3,5,1,3,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +5328,15492,Female,Loyal Customer,65,Personal Travel,Eco,331,2,4,2,2,2,5,4,2,2,2,2,4,2,5,5,3.0,neutral or dissatisfied +5329,121438,Female,disloyal Customer,61,Business travel,Eco,331,2,1,2,4,3,2,3,3,3,5,4,2,3,3,0,0.0,neutral or dissatisfied +5330,61113,Female,Loyal Customer,16,Personal Travel,Eco Plus,1506,2,5,2,4,3,2,3,3,2,2,5,2,2,3,0,0.0,neutral or dissatisfied +5331,37493,Male,Loyal Customer,25,Business travel,Business,2191,3,5,5,5,3,2,3,3,1,4,3,1,3,3,0,0.0,neutral or dissatisfied +5332,68168,Male,Loyal Customer,44,Business travel,Eco,597,4,5,5,5,4,4,4,4,1,2,2,4,3,4,14,6.0,neutral or dissatisfied +5333,113393,Female,disloyal Customer,42,Business travel,Business,414,1,2,2,2,2,1,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +5334,118696,Female,Loyal Customer,10,Personal Travel,Eco,647,3,4,3,4,5,3,2,5,3,1,2,3,4,5,15,9.0,neutral or dissatisfied +5335,102525,Male,Loyal Customer,61,Personal Travel,Eco,236,4,5,4,2,4,4,4,4,5,2,4,4,4,4,15,3.0,neutral or dissatisfied +5336,22149,Female,Loyal Customer,27,Business travel,Eco,633,4,1,1,1,4,4,4,4,3,1,3,1,2,4,68,58.0,satisfied +5337,35821,Female,disloyal Customer,28,Business travel,Eco,1023,2,2,2,4,4,2,1,4,2,3,3,2,5,4,0,0.0,neutral or dissatisfied +5338,31691,Female,Loyal Customer,16,Business travel,Business,846,4,4,4,4,1,2,1,1,1,2,4,1,5,1,0,0.0,satisfied +5339,17662,Female,Loyal Customer,24,Personal Travel,Eco,1008,3,4,3,2,2,3,2,2,4,5,4,3,4,2,126,112.0,neutral or dissatisfied +5340,37561,Male,Loyal Customer,60,Business travel,Business,674,3,3,4,3,4,5,3,5,5,5,5,1,5,2,47,38.0,satisfied +5341,88849,Female,Loyal Customer,33,Personal Travel,Eco Plus,250,4,4,4,2,1,4,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +5342,10088,Male,Loyal Customer,53,Business travel,Business,3825,5,5,5,5,5,3,2,4,4,4,4,1,4,5,0,0.0,satisfied +5343,124584,Male,Loyal Customer,56,Business travel,Business,2406,2,2,2,2,3,4,3,2,2,2,2,1,2,1,1,7.0,neutral or dissatisfied +5344,36709,Male,Loyal Customer,36,Business travel,Eco Plus,1197,5,1,1,1,5,5,5,5,1,3,1,3,4,5,0,22.0,satisfied +5345,62496,Female,Loyal Customer,40,Business travel,Business,1744,2,2,2,2,5,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +5346,96952,Male,Loyal Customer,57,Business travel,Business,1991,3,3,3,3,4,5,5,5,5,5,5,5,5,5,16,12.0,satisfied +5347,27113,Female,disloyal Customer,28,Business travel,Business,2677,3,3,3,4,3,2,2,3,3,3,4,2,3,2,1,0.0,neutral or dissatisfied +5348,90264,Female,Loyal Customer,56,Business travel,Business,2888,3,3,3,3,3,4,4,4,4,4,4,3,4,4,83,84.0,satisfied +5349,18121,Female,Loyal Customer,56,Business travel,Business,120,1,1,4,1,3,4,3,2,2,2,1,3,2,4,17,3.0,neutral or dissatisfied +5350,113582,Female,Loyal Customer,44,Business travel,Business,1712,5,5,5,5,1,3,1,5,5,5,5,5,5,5,17,4.0,satisfied +5351,127467,Female,Loyal Customer,43,Business travel,Business,2075,3,3,3,3,5,3,4,5,5,5,5,3,5,5,13,29.0,satisfied +5352,20229,Male,Loyal Customer,48,Business travel,Eco,224,5,3,3,3,5,5,5,5,3,3,4,5,5,5,54,51.0,satisfied +5353,50449,Female,disloyal Customer,26,Business travel,Eco,262,3,3,3,4,3,3,3,3,3,1,3,1,3,3,39,27.0,neutral or dissatisfied +5354,34074,Female,Loyal Customer,45,Personal Travel,Eco,1674,1,5,1,4,1,4,4,4,4,2,4,4,1,4,189,184.0,neutral or dissatisfied +5355,59574,Female,Loyal Customer,45,Business travel,Business,854,2,2,2,2,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +5356,103341,Male,Loyal Customer,39,Personal Travel,Eco,1139,3,5,3,3,2,3,2,2,4,3,5,2,2,2,5,0.0,neutral or dissatisfied +5357,96448,Female,Loyal Customer,52,Business travel,Business,2943,2,2,1,2,5,5,4,5,5,5,5,3,5,3,19,2.0,satisfied +5358,4060,Male,Loyal Customer,40,Personal Travel,Eco,479,2,4,2,3,1,2,1,1,2,2,4,3,3,1,124,129.0,neutral or dissatisfied +5359,54785,Female,Loyal Customer,60,Business travel,Business,2673,4,4,4,4,5,5,5,4,5,4,5,5,3,5,163,149.0,satisfied +5360,64666,Male,Loyal Customer,44,Business travel,Eco,190,3,2,4,4,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +5361,114346,Female,Loyal Customer,58,Personal Travel,Eco,862,3,5,3,3,3,4,4,4,4,3,5,3,4,3,36,15.0,neutral or dissatisfied +5362,94998,Female,Loyal Customer,25,Personal Travel,Eco,239,3,3,3,4,4,3,4,4,2,2,3,3,3,4,51,46.0,neutral or dissatisfied +5363,21095,Male,Loyal Customer,72,Business travel,Business,2723,4,5,5,5,3,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +5364,99049,Female,disloyal Customer,22,Business travel,Business,453,0,0,0,1,1,0,1,1,5,4,5,5,4,1,12,0.0,satisfied +5365,109019,Male,disloyal Customer,49,Business travel,Business,781,3,3,3,2,4,3,4,4,4,2,5,3,5,4,93,89.0,neutral or dissatisfied +5366,46805,Male,Loyal Customer,22,Business travel,Business,819,4,4,4,4,3,4,3,3,2,1,5,4,3,3,55,43.0,satisfied +5367,9879,Male,Loyal Customer,45,Business travel,Business,1952,3,4,4,4,3,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +5368,62327,Male,Loyal Customer,8,Personal Travel,Eco,414,3,5,3,4,3,3,2,3,4,1,4,5,3,3,0,0.0,neutral or dissatisfied +5369,78396,Female,Loyal Customer,19,Personal Travel,Eco,726,1,3,0,1,1,0,1,1,1,2,4,1,3,1,0,0.0,neutral or dissatisfied +5370,76070,Male,Loyal Customer,31,Business travel,Business,3844,5,5,5,5,5,5,5,5,4,3,5,4,5,5,0,3.0,satisfied +5371,117252,Female,Loyal Customer,67,Personal Travel,Eco,369,4,3,4,3,4,2,5,3,3,4,3,3,3,4,0,0.0,satisfied +5372,616,Male,disloyal Customer,27,Business travel,Business,89,2,2,2,4,1,2,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +5373,129335,Female,Loyal Customer,18,Business travel,Business,2475,1,4,1,1,1,2,1,1,4,1,2,2,3,1,0,0.0,neutral or dissatisfied +5374,11737,Male,Loyal Customer,23,Business travel,Eco,395,2,3,3,3,2,2,1,2,1,5,4,1,3,2,0,1.0,neutral or dissatisfied +5375,88735,Male,Loyal Customer,59,Personal Travel,Eco,581,4,4,4,1,4,4,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +5376,49432,Male,Loyal Customer,40,Business travel,Eco,373,3,2,2,2,3,4,3,3,4,2,2,3,1,3,79,71.0,satisfied +5377,617,Female,Loyal Customer,54,Business travel,Business,1586,1,1,1,1,2,3,3,2,2,2,1,2,2,3,10,19.0,neutral or dissatisfied +5378,12041,Female,Loyal Customer,60,Business travel,Business,3633,2,5,5,5,5,2,3,2,2,2,2,2,2,3,49,43.0,neutral or dissatisfied +5379,65390,Female,Loyal Customer,8,Personal Travel,Eco,631,3,1,4,4,2,4,4,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +5380,115586,Female,Loyal Customer,57,Business travel,Business,417,3,3,3,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +5381,59254,Female,Loyal Customer,51,Business travel,Eco,3904,3,1,1,1,3,3,3,3,5,4,3,3,1,3,17,0.0,neutral or dissatisfied +5382,41913,Male,Loyal Customer,36,Business travel,Eco,129,4,1,1,1,4,4,4,4,2,4,3,3,2,4,0,0.0,satisfied +5383,120214,Female,Loyal Customer,55,Business travel,Business,3890,2,2,2,2,4,4,5,4,4,4,4,3,4,4,16,0.0,satisfied +5384,106455,Male,disloyal Customer,25,Business travel,Eco,1223,3,3,3,3,5,3,1,5,2,2,3,4,2,5,30,45.0,neutral or dissatisfied +5385,59761,Female,Loyal Customer,58,Business travel,Business,1614,3,3,3,3,2,4,4,3,3,3,3,3,3,5,21,13.0,satisfied +5386,127010,Male,Loyal Customer,51,Business travel,Business,2510,5,5,5,5,2,5,4,5,5,5,5,3,5,4,8,19.0,satisfied +5387,101176,Male,Loyal Customer,38,Business travel,Business,1540,2,2,5,2,3,1,3,4,4,4,4,4,4,1,0,0.0,satisfied +5388,44200,Male,Loyal Customer,35,Personal Travel,Eco,128,2,5,0,3,2,0,2,2,5,1,3,5,4,2,0,0.0,neutral or dissatisfied +5389,89006,Female,Loyal Customer,43,Business travel,Business,1947,2,2,2,2,5,3,4,2,2,2,2,1,2,3,1,12.0,neutral or dissatisfied +5390,30363,Male,Loyal Customer,26,Business travel,Eco,641,5,1,1,1,5,5,3,5,5,5,1,4,2,5,0,1.0,satisfied +5391,122801,Female,disloyal Customer,20,Business travel,Eco,599,2,4,2,3,3,2,3,3,4,2,3,1,4,3,28,31.0,neutral or dissatisfied +5392,54034,Female,Loyal Customer,68,Personal Travel,Business,1416,2,5,2,3,4,4,1,5,5,2,5,2,5,3,60,20.0,neutral or dissatisfied +5393,22703,Female,Loyal Customer,13,Personal Travel,Eco,579,2,2,2,3,5,2,5,5,3,2,3,2,3,5,10,0.0,neutral or dissatisfied +5394,22891,Female,Loyal Customer,26,Personal Travel,Eco,147,2,4,2,4,1,2,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +5395,110315,Female,Loyal Customer,52,Business travel,Business,2480,3,5,5,5,4,3,3,3,3,3,3,2,3,2,4,6.0,neutral or dissatisfied +5396,105770,Male,Loyal Customer,65,Business travel,Business,442,1,1,1,1,2,2,2,5,5,5,5,4,5,3,4,0.0,satisfied +5397,74153,Male,Loyal Customer,53,Business travel,Eco,592,5,1,1,1,3,5,3,3,4,3,4,3,2,3,0,0.0,satisfied +5398,116227,Male,Loyal Customer,36,Personal Travel,Eco,308,1,4,1,3,2,1,2,2,3,4,5,3,4,2,22,23.0,neutral or dissatisfied +5399,100949,Female,Loyal Customer,42,Business travel,Eco,1142,2,4,4,4,4,3,4,2,2,2,2,2,2,4,2,6.0,neutral or dissatisfied +5400,91043,Male,Loyal Customer,60,Personal Travel,Eco,444,1,1,2,3,5,2,5,5,2,2,2,4,3,5,0,0.0,neutral or dissatisfied +5401,60536,Male,Loyal Customer,38,Personal Travel,Eco,862,3,4,3,1,2,3,2,2,4,2,5,3,5,2,11,0.0,neutral or dissatisfied +5402,15831,Female,Loyal Customer,54,Business travel,Business,2395,4,4,4,4,2,1,4,4,4,4,3,4,4,4,0,0.0,satisfied +5403,89720,Female,Loyal Customer,36,Personal Travel,Eco,944,4,3,4,1,3,4,2,3,4,3,2,2,5,3,0,0.0,neutral or dissatisfied +5404,17947,Male,Loyal Customer,43,Personal Travel,Eco,95,3,3,0,3,3,0,3,3,1,4,4,2,4,3,0,0.0,neutral or dissatisfied +5405,115581,Male,Loyal Customer,22,Business travel,Business,2069,2,2,2,2,2,2,2,2,3,2,2,4,2,2,52,41.0,neutral or dissatisfied +5406,54830,Male,Loyal Customer,49,Business travel,Business,3715,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,1.0,satisfied +5407,102541,Female,Loyal Customer,60,Personal Travel,Eco,226,4,4,4,1,3,5,4,2,2,4,2,4,2,4,0,0.0,satisfied +5408,110418,Male,Loyal Customer,35,Business travel,Business,2632,2,2,2,2,4,4,4,2,3,2,5,4,2,4,74,190.0,satisfied +5409,49458,Male,Loyal Customer,59,Business travel,Business,3839,2,2,4,2,2,5,3,4,4,5,4,3,4,5,0,0.0,satisfied +5410,84888,Male,Loyal Customer,52,Personal Travel,Eco,547,4,3,4,4,3,4,3,3,2,5,1,3,1,3,5,0.0,neutral or dissatisfied +5411,59686,Female,Loyal Customer,64,Personal Travel,Eco,964,4,5,5,3,5,5,5,5,5,5,5,5,5,5,10,0.0,satisfied +5412,15770,Male,Loyal Customer,60,Business travel,Business,254,0,0,0,1,5,3,3,3,3,3,3,2,3,4,0,22.0,satisfied +5413,16993,Female,disloyal Customer,57,Business travel,Eco,843,3,3,3,4,4,3,2,4,3,2,4,3,3,4,2,1.0,neutral or dissatisfied +5414,14580,Male,Loyal Customer,39,Business travel,Business,2706,3,2,2,2,2,3,3,3,3,3,3,3,3,1,3,33.0,neutral or dissatisfied +5415,33926,Female,Loyal Customer,36,Personal Travel,Eco,818,2,4,2,2,3,2,3,3,3,3,2,4,1,3,18,7.0,neutral or dissatisfied +5416,20331,Female,Loyal Customer,47,Business travel,Eco,265,3,3,3,3,5,3,1,3,3,3,3,3,3,5,36,30.0,satisfied +5417,92448,Male,Loyal Customer,56,Business travel,Business,1892,3,3,3,3,5,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +5418,20714,Male,Loyal Customer,56,Business travel,Eco,707,5,5,4,4,5,5,5,5,4,3,3,3,5,5,0,0.0,satisfied +5419,22317,Male,disloyal Customer,49,Business travel,Eco,208,3,0,3,4,4,3,2,4,5,1,1,2,5,4,2,0.0,neutral or dissatisfied +5420,90591,Female,disloyal Customer,21,Business travel,Eco,250,4,0,5,1,1,5,1,1,5,2,5,4,4,1,0,0.0,satisfied +5421,66458,Female,Loyal Customer,50,Personal Travel,Eco,1217,1,0,0,4,5,3,3,2,2,0,2,1,2,3,1,3.0,neutral or dissatisfied +5422,91508,Male,Loyal Customer,60,Business travel,Business,1620,5,5,5,5,4,3,4,3,3,3,3,3,3,3,0,0.0,satisfied +5423,76136,Female,Loyal Customer,56,Business travel,Business,689,3,3,3,3,5,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +5424,26356,Male,disloyal Customer,20,Business travel,Eco,894,0,0,0,5,2,0,2,2,4,5,1,1,3,2,40,38.0,satisfied +5425,53686,Female,Loyal Customer,29,Business travel,Business,3709,3,1,1,1,3,3,3,3,4,1,3,1,3,3,2,9.0,neutral or dissatisfied +5426,117396,Female,disloyal Customer,34,Business travel,Business,544,2,2,2,3,2,2,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +5427,59489,Male,Loyal Customer,54,Personal Travel,Eco,901,2,1,2,3,4,2,4,4,1,4,4,4,4,4,3,0.0,neutral or dissatisfied +5428,95738,Female,disloyal Customer,26,Business travel,Business,181,5,4,5,4,4,5,4,4,4,2,5,4,5,4,0,0.0,satisfied +5429,116584,Female,Loyal Customer,42,Business travel,Business,1944,2,2,2,2,5,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +5430,112989,Female,Loyal Customer,48,Business travel,Business,1797,5,5,5,5,4,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +5431,24169,Female,Loyal Customer,40,Business travel,Business,1987,0,3,0,5,5,5,5,5,5,4,1,5,1,5,166,168.0,satisfied +5432,60682,Male,Loyal Customer,49,Business travel,Business,1605,2,4,4,4,2,2,4,2,2,2,2,2,2,1,3,0.0,neutral or dissatisfied +5433,58577,Male,Loyal Customer,19,Personal Travel,Eco,403,2,4,5,2,2,5,1,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +5434,117242,Female,Loyal Customer,67,Personal Travel,Eco,368,2,5,2,4,2,5,2,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +5435,101837,Male,Loyal Customer,43,Personal Travel,Eco,1521,3,4,3,4,2,3,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +5436,720,Female,Loyal Customer,51,Business travel,Business,309,1,1,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +5437,104874,Male,Loyal Customer,57,Business travel,Business,2056,3,3,3,3,5,3,1,5,5,5,5,2,5,4,0,0.0,satisfied +5438,6077,Female,Loyal Customer,8,Personal Travel,Eco,691,3,4,3,3,3,3,3,3,3,2,4,5,5,3,0,2.0,neutral or dissatisfied +5439,122427,Male,Loyal Customer,53,Business travel,Business,1916,4,1,2,1,5,1,3,4,4,4,4,2,4,3,7,24.0,neutral or dissatisfied +5440,33039,Female,Loyal Customer,49,Personal Travel,Eco,101,3,5,0,2,4,5,5,5,5,0,5,5,5,5,0,2.0,neutral or dissatisfied +5441,107052,Male,Loyal Customer,40,Business travel,Business,1724,4,4,5,4,5,2,3,4,4,4,4,1,4,2,27,21.0,neutral or dissatisfied +5442,20190,Male,Loyal Customer,18,Business travel,Business,677,2,2,2,2,5,5,5,5,3,4,4,1,2,5,1,9.0,satisfied +5443,95244,Female,Loyal Customer,16,Personal Travel,Eco,189,2,4,0,1,3,0,3,3,4,5,5,4,5,3,13,11.0,neutral or dissatisfied +5444,76455,Male,Loyal Customer,57,Business travel,Business,516,1,1,5,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5445,96232,Male,disloyal Customer,48,Business travel,Eco,328,2,3,2,4,4,2,2,4,1,3,3,3,4,4,8,2.0,neutral or dissatisfied +5446,21171,Female,Loyal Customer,44,Business travel,Business,3537,4,4,4,4,5,4,4,4,4,4,4,1,4,1,60,44.0,neutral or dissatisfied +5447,123455,Male,Loyal Customer,49,Business travel,Business,2077,3,3,3,3,4,5,5,2,2,2,2,5,2,3,1,0.0,satisfied +5448,120489,Female,Loyal Customer,12,Personal Travel,Eco,366,2,1,2,2,2,2,2,2,2,3,3,2,3,2,10,24.0,neutral or dissatisfied +5449,61783,Male,Loyal Customer,14,Personal Travel,Eco,1608,2,1,2,2,3,2,3,3,4,1,2,1,1,3,0,0.0,neutral or dissatisfied +5450,72597,Male,Loyal Customer,44,Personal Travel,Eco,1017,2,2,2,4,1,2,1,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +5451,35383,Male,Loyal Customer,59,Business travel,Eco,676,4,1,3,3,4,4,4,4,2,4,4,1,2,4,7,1.0,satisfied +5452,54044,Female,Loyal Customer,41,Business travel,Eco,1416,4,2,2,2,5,4,5,5,3,4,1,2,3,5,0,0.0,satisfied +5453,125730,Female,Loyal Customer,64,Business travel,Business,814,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +5454,123354,Male,Loyal Customer,45,Business travel,Business,2506,4,4,4,4,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +5455,120464,Male,Loyal Customer,14,Personal Travel,Eco,366,2,5,2,3,3,2,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +5456,77939,Female,disloyal Customer,27,Business travel,Business,214,2,2,2,2,3,2,3,3,4,4,4,4,4,3,0,3.0,neutral or dissatisfied +5457,24834,Female,Loyal Customer,69,Business travel,Business,494,1,4,4,4,1,3,3,1,1,1,1,4,1,3,64,70.0,neutral or dissatisfied +5458,58575,Female,Loyal Customer,49,Business travel,Eco,403,3,5,5,5,1,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +5459,12106,Female,Loyal Customer,41,Business travel,Eco,1034,5,3,3,3,5,5,5,5,1,3,4,2,3,5,41,14.0,satisfied +5460,88463,Female,disloyal Customer,25,Business travel,Eco,594,4,3,4,2,2,4,2,2,4,4,4,2,2,2,0,0.0,neutral or dissatisfied +5461,105974,Male,Loyal Customer,69,Personal Travel,Eco,2295,2,4,2,4,1,2,2,1,5,4,2,4,4,1,31,0.0,neutral or dissatisfied +5462,110607,Male,Loyal Customer,51,Business travel,Business,1867,5,5,5,5,5,4,5,4,4,4,4,3,4,3,25,10.0,satisfied +5463,125212,Female,Loyal Customer,51,Personal Travel,Eco,651,5,2,5,4,5,2,4,4,4,2,1,1,4,3,1,0.0,satisfied +5464,106008,Male,Loyal Customer,18,Business travel,Business,1999,1,1,1,1,1,1,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +5465,3954,Female,disloyal Customer,24,Business travel,Eco,364,2,5,2,2,4,2,4,4,5,3,5,1,4,4,0,10.0,neutral or dissatisfied +5466,123981,Male,Loyal Customer,50,Business travel,Business,3922,3,3,3,3,2,5,5,5,5,5,4,4,5,4,0,0.0,satisfied +5467,98618,Female,disloyal Customer,48,Business travel,Business,951,2,2,2,2,1,2,1,1,4,5,4,3,4,1,16,15.0,neutral or dissatisfied +5468,66444,Male,Loyal Customer,59,Business travel,Business,2086,1,4,4,4,3,3,4,1,1,1,1,3,1,2,1,0.0,neutral or dissatisfied +5469,87943,Female,Loyal Customer,36,Personal Travel,Business,240,4,5,4,2,4,3,3,5,5,4,5,5,5,4,69,66.0,neutral or dissatisfied +5470,24553,Male,Loyal Customer,40,Business travel,Business,874,4,3,3,3,4,3,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +5471,49968,Male,Loyal Customer,21,Business travel,Business,3679,2,2,2,2,4,4,3,4,4,3,3,4,2,4,0,0.0,satisfied +5472,107003,Male,Loyal Customer,25,Personal Travel,Eco,937,2,5,2,3,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +5473,30032,Female,disloyal Customer,55,Business travel,Eco,399,1,4,1,3,2,1,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +5474,82005,Male,disloyal Customer,21,Business travel,Eco,1220,3,3,3,4,5,3,3,5,2,2,4,2,4,5,0,7.0,neutral or dissatisfied +5475,73332,Female,disloyal Customer,39,Business travel,Business,1197,3,4,4,1,1,4,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +5476,92666,Male,Loyal Customer,32,Business travel,Business,2992,4,4,4,4,5,5,5,5,3,4,4,4,5,5,23,21.0,satisfied +5477,16055,Female,disloyal Customer,28,Business travel,Eco,744,2,1,1,4,1,1,1,1,1,5,1,2,4,1,0,0.0,neutral or dissatisfied +5478,116580,Female,disloyal Customer,20,Business travel,Business,342,0,0,0,5,4,0,4,4,4,2,5,4,5,4,6,0.0,satisfied +5479,122262,Female,Loyal Customer,55,Personal Travel,Eco,646,3,3,3,5,1,5,3,4,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +5480,5812,Male,Loyal Customer,30,Personal Travel,Eco,177,4,4,4,3,2,4,5,2,5,4,5,4,5,2,14,7.0,satisfied +5481,23265,Male,Loyal Customer,27,Business travel,Business,2829,2,5,5,5,2,2,2,2,1,5,2,1,2,2,5,0.0,neutral or dissatisfied +5482,56966,Female,disloyal Customer,57,Business travel,Eco,925,4,4,4,2,4,3,4,3,3,2,1,4,2,4,16,17.0,neutral or dissatisfied +5483,111110,Male,Loyal Customer,26,Personal Travel,Eco Plus,240,1,3,1,2,4,1,4,4,2,5,2,3,3,4,22,19.0,neutral or dissatisfied +5484,102189,Female,Loyal Customer,41,Business travel,Business,1639,2,2,2,2,4,5,4,4,4,4,4,5,4,3,49,43.0,satisfied +5485,25883,Female,disloyal Customer,24,Business travel,Eco,907,2,2,2,5,5,2,3,5,5,1,3,4,4,5,23,23.0,neutral or dissatisfied +5486,104329,Male,Loyal Customer,30,Business travel,Business,3575,2,2,2,2,2,2,2,2,1,4,3,3,4,2,26,25.0,neutral or dissatisfied +5487,102453,Female,Loyal Customer,30,Personal Travel,Eco,397,3,4,3,3,5,3,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +5488,115407,Male,disloyal Customer,36,Business travel,Business,358,2,2,2,3,2,2,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +5489,116969,Male,disloyal Customer,45,Business travel,Business,370,5,5,5,2,4,5,3,4,5,4,4,5,5,4,94,88.0,satisfied +5490,94505,Male,Loyal Customer,56,Business travel,Business,3342,4,4,4,4,4,4,4,5,5,5,5,4,5,4,1,1.0,satisfied +5491,7688,Female,disloyal Customer,37,Business travel,Eco,204,3,0,3,4,4,3,4,4,2,1,3,4,5,4,0,0.0,neutral or dissatisfied +5492,43602,Male,Loyal Customer,36,Business travel,Business,2315,4,4,4,4,5,2,5,5,5,4,5,5,5,1,0,0.0,satisfied +5493,37759,Male,Loyal Customer,38,Business travel,Eco Plus,944,5,5,4,4,5,5,5,5,3,4,4,5,3,5,21,36.0,satisfied +5494,44583,Male,Loyal Customer,60,Personal Travel,Eco,177,3,3,0,3,4,0,4,4,3,3,2,4,4,4,37,40.0,neutral or dissatisfied +5495,42234,Male,Loyal Customer,44,Business travel,Eco,834,4,3,3,3,5,4,5,5,5,4,2,1,3,5,0,19.0,satisfied +5496,60650,Female,Loyal Customer,43,Business travel,Eco,1620,3,5,5,5,4,2,2,3,3,3,3,3,3,4,35,,neutral or dissatisfied +5497,77704,Female,disloyal Customer,36,Business travel,Eco,689,4,4,4,3,3,4,3,3,1,4,3,3,2,3,0,0.0,neutral or dissatisfied +5498,105134,Male,Loyal Customer,36,Business travel,Business,1586,0,0,0,4,2,4,4,2,2,2,2,4,2,3,14,4.0,satisfied +5499,35978,Male,Loyal Customer,39,Business travel,Business,3694,3,3,3,3,4,3,3,4,4,4,4,2,4,5,14,0.0,satisfied +5500,56972,Female,Loyal Customer,18,Personal Travel,Eco,2454,1,1,1,2,1,2,2,1,4,3,3,2,2,2,5,0.0,neutral or dissatisfied +5501,91019,Female,Loyal Customer,9,Personal Travel,Eco,406,1,5,1,2,3,1,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +5502,111628,Female,Loyal Customer,46,Business travel,Business,1014,5,5,5,5,5,4,5,5,5,5,5,5,5,5,19,1.0,satisfied +5503,123473,Male,disloyal Customer,27,Business travel,Business,2125,2,2,2,2,5,2,5,5,3,4,3,3,4,5,0,0.0,neutral or dissatisfied +5504,6005,Female,Loyal Customer,60,Business travel,Business,3913,2,2,2,2,3,4,5,2,2,2,2,3,2,4,22,0.0,satisfied +5505,39838,Male,disloyal Customer,58,Business travel,Business,272,2,2,2,4,4,2,4,4,3,3,2,5,1,4,0,0.0,satisfied +5506,51418,Female,Loyal Customer,17,Personal Travel,Eco Plus,209,2,4,2,3,4,2,4,4,2,5,3,4,3,4,36,36.0,neutral or dissatisfied +5507,35548,Male,Loyal Customer,63,Personal Travel,Eco,828,1,4,1,5,3,1,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +5508,8308,Female,Loyal Customer,50,Business travel,Business,2148,4,4,4,4,3,4,4,5,5,5,5,3,5,4,16,5.0,satisfied +5509,56977,Male,Loyal Customer,39,Personal Travel,Eco,2454,3,5,3,3,3,4,4,5,2,2,4,4,4,4,0,0.0,neutral or dissatisfied +5510,129339,Male,disloyal Customer,68,Business travel,Eco,975,2,2,2,4,4,2,4,4,1,5,4,4,3,4,0,0.0,neutral or dissatisfied +5511,29276,Female,Loyal Customer,60,Business travel,Eco,859,5,3,3,3,3,5,3,5,5,5,5,3,5,4,9,10.0,satisfied +5512,18586,Male,Loyal Customer,40,Business travel,Eco,190,1,4,4,4,1,1,1,1,4,3,3,1,3,1,0,0.0,neutral or dissatisfied +5513,21532,Female,Loyal Customer,14,Personal Travel,Eco,331,3,3,3,3,5,3,5,5,2,2,3,3,4,5,3,15.0,neutral or dissatisfied +5514,1644,Male,Loyal Customer,46,Business travel,Business,435,4,1,1,1,2,3,4,4,4,4,4,4,4,2,2,15.0,neutral or dissatisfied +5515,41590,Male,Loyal Customer,47,Personal Travel,Eco,1482,4,4,4,4,1,4,3,1,1,4,5,3,5,1,0,0.0,neutral or dissatisfied +5516,19085,Male,disloyal Customer,57,Business travel,Eco,296,2,4,2,4,3,2,3,3,5,2,2,4,2,3,0,0.0,neutral or dissatisfied +5517,126420,Female,Loyal Customer,59,Business travel,Business,3634,5,5,5,5,3,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +5518,49235,Male,disloyal Customer,26,Business travel,Eco,89,2,4,2,1,4,2,4,4,5,1,4,3,3,4,0,0.0,neutral or dissatisfied +5519,51193,Male,Loyal Customer,20,Business travel,Eco Plus,89,5,3,3,3,5,5,5,5,1,1,1,3,1,5,0,0.0,satisfied +5520,52007,Female,Loyal Customer,44,Business travel,Business,1710,4,4,4,4,4,1,5,5,5,5,5,1,5,2,0,0.0,satisfied +5521,94733,Female,Loyal Customer,49,Business travel,Eco,233,4,2,2,2,2,2,1,4,4,4,4,4,4,4,28,23.0,neutral or dissatisfied +5522,120671,Female,disloyal Customer,72,Business travel,Eco,280,3,2,3,4,3,3,3,3,4,2,4,2,4,3,0,8.0,neutral or dissatisfied +5523,38134,Female,disloyal Customer,43,Business travel,Eco,721,4,3,3,5,4,3,4,4,3,1,5,5,4,4,6,0.0,neutral or dissatisfied +5524,109639,Male,Loyal Customer,41,Business travel,Business,829,4,4,4,4,3,5,5,5,5,5,5,5,5,5,51,37.0,satisfied +5525,91811,Female,Loyal Customer,12,Personal Travel,Eco,599,3,3,3,2,1,3,1,1,4,3,4,5,3,1,72,70.0,neutral or dissatisfied +5526,102941,Male,Loyal Customer,48,Business travel,Business,719,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,13.0,satisfied +5527,121493,Male,Loyal Customer,52,Business travel,Business,3019,1,1,1,1,4,5,4,4,4,4,4,4,4,3,55,47.0,satisfied +5528,16930,Female,disloyal Customer,37,Business travel,Eco,820,4,3,3,3,2,3,2,2,5,4,3,4,4,2,0,17.0,neutral or dissatisfied +5529,27603,Male,Loyal Customer,44,Personal Travel,Eco,679,2,4,2,3,4,2,2,4,5,2,5,4,4,4,30,32.0,neutral or dissatisfied +5530,92368,Male,Loyal Customer,42,Business travel,Business,1892,1,1,5,1,3,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +5531,102141,Female,Loyal Customer,54,Business travel,Business,1544,1,1,1,1,3,4,5,5,5,4,5,3,5,3,6,1.0,satisfied +5532,125562,Female,Loyal Customer,68,Business travel,Business,226,1,1,1,1,1,1,5,5,5,5,5,3,5,3,0,10.0,satisfied +5533,101264,Male,Loyal Customer,45,Business travel,Business,676,5,5,2,5,3,3,3,4,4,4,4,2,4,3,0,0.0,satisfied +5534,55082,Female,Loyal Customer,38,Business travel,Business,1609,3,3,3,3,5,2,3,3,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +5535,115524,Female,Loyal Customer,48,Business travel,Business,1922,5,5,5,5,5,5,4,2,2,3,2,4,2,4,0,0.0,satisfied +5536,60266,Male,Loyal Customer,44,Personal Travel,Eco Plus,1607,3,4,3,3,3,3,5,3,3,3,4,5,4,3,38,33.0,neutral or dissatisfied +5537,30360,Male,Loyal Customer,43,Business travel,Business,2055,1,1,1,1,4,1,1,4,4,4,4,5,4,3,0,0.0,satisfied +5538,12520,Female,Loyal Customer,44,Business travel,Eco,871,4,4,4,4,5,3,5,4,4,4,4,1,4,2,0,0.0,satisfied +5539,105785,Male,Loyal Customer,68,Personal Travel,Eco,919,2,3,2,4,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +5540,74473,Female,Loyal Customer,48,Business travel,Business,1464,2,2,2,2,4,5,5,4,4,4,4,3,4,5,64,62.0,satisfied +5541,69230,Female,Loyal Customer,46,Business travel,Business,3601,2,2,2,2,3,5,5,2,2,2,2,3,2,4,94,69.0,satisfied +5542,83631,Male,Loyal Customer,26,Personal Travel,Eco,409,1,3,1,4,4,1,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +5543,30274,Male,Loyal Customer,52,Business travel,Eco,1024,3,3,3,3,4,3,4,4,4,5,3,1,1,4,0,0.0,satisfied +5544,24969,Female,disloyal Customer,29,Business travel,Business,692,3,3,3,3,2,3,3,2,2,2,3,2,4,2,0,5.0,neutral or dissatisfied +5545,85730,Male,Loyal Customer,26,Business travel,Business,666,5,5,1,5,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +5546,83076,Female,disloyal Customer,38,Business travel,Eco,1127,1,1,1,4,4,1,2,4,2,2,4,3,3,4,0,5.0,neutral or dissatisfied +5547,82488,Female,disloyal Customer,35,Business travel,Business,488,3,3,3,4,2,3,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +5548,101922,Male,Loyal Customer,45,Business travel,Eco Plus,2173,3,1,1,1,3,3,3,3,4,1,1,4,3,3,58,35.0,neutral or dissatisfied +5549,64640,Female,Loyal Customer,54,Business travel,Business,469,1,1,1,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +5550,22415,Male,disloyal Customer,26,Business travel,Eco,145,3,0,3,2,5,3,5,5,4,1,1,1,4,5,0,0.0,neutral or dissatisfied +5551,87423,Female,Loyal Customer,24,Personal Travel,Eco,425,2,0,2,2,1,2,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +5552,36471,Female,Loyal Customer,33,Personal Travel,Eco,901,2,3,2,2,4,2,4,4,2,2,3,3,3,4,0,21.0,neutral or dissatisfied +5553,73927,Male,Loyal Customer,29,Business travel,Business,2342,1,5,5,5,1,1,1,1,2,1,3,2,3,1,1,0.0,neutral or dissatisfied +5554,95458,Female,Loyal Customer,52,Business travel,Business,3833,1,1,1,1,3,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +5555,95499,Female,Loyal Customer,33,Business travel,Business,528,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +5556,87255,Male,Loyal Customer,47,Business travel,Business,3234,5,5,5,5,3,4,5,4,4,4,4,5,4,4,13,3.0,satisfied +5557,71361,Male,Loyal Customer,38,Business travel,Business,2554,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +5558,88413,Female,Loyal Customer,32,Business travel,Eco,442,2,3,1,3,2,2,2,2,1,5,1,3,1,2,0,0.0,neutral or dissatisfied +5559,25685,Female,Loyal Customer,44,Business travel,Business,2409,2,2,2,2,2,4,5,4,4,4,4,3,4,3,8,5.0,satisfied +5560,62180,Female,disloyal Customer,49,Business travel,Business,2565,4,4,4,3,1,4,1,1,5,3,3,3,5,1,1,0.0,satisfied +5561,50428,Female,Loyal Customer,18,Business travel,Business,158,4,3,3,3,2,2,4,2,2,3,3,3,4,2,58,53.0,neutral or dissatisfied +5562,68822,Female,Loyal Customer,38,Personal Travel,Eco Plus,926,1,3,1,4,5,1,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +5563,40302,Female,Loyal Customer,54,Personal Travel,Eco,387,2,3,2,3,1,2,4,2,2,2,2,3,2,5,0,6.0,neutral or dissatisfied +5564,121106,Male,Loyal Customer,58,Business travel,Business,2521,3,3,3,3,5,5,5,5,2,4,5,5,3,5,4,14.0,satisfied +5565,104583,Male,disloyal Customer,18,Business travel,Eco,369,0,0,0,2,2,0,2,2,5,2,5,4,5,2,0,3.0,satisfied +5566,109560,Male,Loyal Customer,49,Personal Travel,Eco,920,1,2,1,3,5,1,5,5,2,4,3,2,3,5,18,0.0,neutral or dissatisfied +5567,29224,Male,Loyal Customer,37,Business travel,Business,2857,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,11.0,satisfied +5568,2273,Female,Loyal Customer,54,Business travel,Business,3630,1,1,1,1,3,5,4,5,5,5,5,4,5,5,18,14.0,satisfied +5569,20259,Female,Loyal Customer,18,Business travel,Business,1843,4,2,5,5,4,4,4,4,1,2,4,3,4,4,0,0.0,neutral or dissatisfied +5570,112051,Male,Loyal Customer,56,Business travel,Business,2255,4,1,4,4,2,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +5571,14140,Male,Loyal Customer,23,Personal Travel,Eco,594,3,3,3,3,1,3,1,1,2,1,4,5,2,1,28,33.0,neutral or dissatisfied +5572,82272,Male,Loyal Customer,57,Business travel,Business,1481,3,1,1,1,3,4,4,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +5573,92186,Female,Loyal Customer,59,Business travel,Business,1956,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,2.0,satisfied +5574,51176,Female,Loyal Customer,53,Personal Travel,Eco,250,4,5,4,3,5,5,4,3,3,4,3,3,3,4,68,61.0,neutral or dissatisfied +5575,3906,Male,Loyal Customer,10,Personal Travel,Eco,213,2,0,0,2,2,0,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +5576,76562,Male,Loyal Customer,52,Business travel,Business,3358,2,1,1,1,2,3,4,2,2,2,2,1,2,3,0,9.0,neutral or dissatisfied +5577,78964,Female,Loyal Customer,46,Business travel,Business,1983,2,2,2,2,4,5,5,4,3,4,4,5,5,5,176,166.0,satisfied +5578,100306,Female,Loyal Customer,26,Business travel,Business,1587,2,2,2,2,4,4,4,4,4,2,4,4,4,4,39,17.0,satisfied +5579,106734,Female,Loyal Customer,41,Business travel,Business,1939,3,3,3,3,5,4,5,4,4,4,4,5,4,4,71,78.0,satisfied +5580,100288,Male,Loyal Customer,40,Business travel,Business,1073,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +5581,96780,Female,Loyal Customer,41,Business travel,Business,849,5,5,5,5,4,4,4,2,2,3,2,4,2,4,0,0.0,satisfied +5582,75113,Male,disloyal Customer,35,Business travel,Business,1723,1,1,1,2,4,1,4,4,3,4,4,3,5,4,62,90.0,neutral or dissatisfied +5583,7086,Male,Loyal Customer,48,Business travel,Business,3901,2,1,1,1,2,4,3,2,2,2,2,3,2,3,2,23.0,neutral or dissatisfied +5584,96240,Female,Loyal Customer,38,Business travel,Eco,386,2,3,3,3,2,2,2,2,4,3,1,2,4,2,0,0.0,satisfied +5585,66084,Male,Loyal Customer,15,Personal Travel,Eco,1055,3,5,3,5,2,3,2,2,4,3,4,3,5,2,4,0.0,neutral or dissatisfied +5586,95178,Female,Loyal Customer,33,Personal Travel,Eco,189,1,3,1,4,2,1,2,2,4,5,1,3,1,2,15,33.0,neutral or dissatisfied +5587,3410,Male,Loyal Customer,11,Personal Travel,Eco,213,1,0,1,3,2,1,2,2,4,4,5,5,5,2,0,37.0,neutral or dissatisfied +5588,32562,Male,disloyal Customer,26,Business travel,Eco,102,2,3,2,3,5,2,5,5,4,1,1,1,2,5,0,0.0,neutral or dissatisfied +5589,97104,Male,disloyal Customer,15,Business travel,Business,1357,5,0,5,4,3,5,3,3,3,3,5,4,5,3,0,2.0,satisfied +5590,7221,Female,Loyal Customer,62,Business travel,Business,3574,1,4,4,4,1,4,3,3,3,3,1,1,3,1,24,15.0,neutral or dissatisfied +5591,126474,Female,Loyal Customer,27,Business travel,Eco,1849,1,1,1,1,1,1,1,1,2,2,2,4,3,1,0,9.0,neutral or dissatisfied +5592,112577,Female,Loyal Customer,26,Business travel,Business,2934,3,3,3,3,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +5593,94473,Male,disloyal Customer,40,Business travel,Business,677,4,4,4,3,2,4,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +5594,57408,Female,disloyal Customer,70,Business travel,Business,455,2,2,2,1,2,2,4,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +5595,16853,Male,Loyal Customer,33,Business travel,Eco,746,5,2,2,2,5,5,5,5,5,2,4,4,3,5,44,35.0,satisfied +5596,8180,Female,Loyal Customer,56,Business travel,Eco,125,3,5,4,4,2,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +5597,76040,Male,disloyal Customer,21,Business travel,Eco,669,4,0,4,2,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +5598,37181,Female,Loyal Customer,9,Personal Travel,Eco,1046,3,5,3,3,1,3,5,1,4,4,3,1,2,1,0,0.0,neutral or dissatisfied +5599,93528,Female,Loyal Customer,27,Business travel,Business,1218,5,5,5,5,4,4,4,4,3,2,5,4,5,4,3,0.0,satisfied +5600,53867,Male,Loyal Customer,22,Business travel,Business,2055,1,1,1,1,4,4,1,4,4,3,3,4,3,4,0,0.0,neutral or dissatisfied +5601,49975,Female,Loyal Customer,37,Business travel,Business,2079,5,5,5,5,5,3,5,5,5,5,5,1,5,2,0,0.0,satisfied +5602,64775,Female,Loyal Customer,35,Business travel,Business,1807,2,5,4,4,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +5603,120426,Male,Loyal Customer,39,Business travel,Business,449,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +5604,78625,Female,Loyal Customer,39,Business travel,Business,1426,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5605,72452,Male,Loyal Customer,60,Business travel,Business,1121,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +5606,18371,Male,Loyal Customer,39,Personal Travel,Eco,169,2,4,2,3,4,2,4,4,3,2,4,4,5,4,0,3.0,neutral or dissatisfied +5607,96308,Male,Loyal Customer,49,Business travel,Business,490,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +5608,76470,Male,disloyal Customer,28,Business travel,Business,534,0,0,0,5,4,0,4,4,4,2,5,5,4,4,0,19.0,satisfied +5609,128859,Male,Loyal Customer,24,Business travel,Business,2475,5,5,5,5,4,4,4,4,4,4,5,3,4,4,11,0.0,satisfied +5610,26961,Female,Loyal Customer,58,Personal Travel,Business,867,3,3,3,1,3,2,3,5,5,3,4,1,5,3,0,0.0,neutral or dissatisfied +5611,107688,Male,Loyal Customer,37,Business travel,Business,405,1,1,2,1,4,3,3,1,1,2,1,1,1,4,50,49.0,neutral or dissatisfied +5612,103129,Female,disloyal Customer,20,Business travel,Eco,687,2,2,2,1,1,2,1,1,3,5,4,3,4,1,8,0.0,neutral or dissatisfied +5613,38452,Female,Loyal Customer,46,Business travel,Eco,1226,2,5,5,5,3,5,4,2,2,2,2,4,2,3,14,23.0,satisfied +5614,37956,Male,Loyal Customer,56,Business travel,Business,1211,2,2,2,2,5,4,4,2,2,2,2,4,2,5,0,4.0,satisfied +5615,81649,Male,Loyal Customer,29,Business travel,Business,2510,4,4,4,4,4,4,4,4,3,2,5,3,5,4,2,0.0,satisfied +5616,42169,Female,Loyal Customer,34,Business travel,Business,748,5,5,3,5,3,1,2,5,5,5,5,4,5,2,9,0.0,satisfied +5617,86759,Male,Loyal Customer,38,Personal Travel,Eco,821,1,5,1,3,3,1,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +5618,90483,Male,Loyal Customer,44,Business travel,Business,581,4,4,2,4,3,4,5,3,3,3,3,4,3,4,2,0.0,satisfied +5619,13387,Male,disloyal Customer,27,Business travel,Eco,505,0,0,0,4,1,0,1,1,5,5,2,3,2,1,0,0.0,satisfied +5620,66817,Male,Loyal Customer,40,Business travel,Business,2269,5,5,5,5,2,4,5,5,5,5,5,3,5,3,122,108.0,satisfied +5621,13026,Female,Loyal Customer,12,Personal Travel,Eco,374,2,4,2,4,1,2,1,1,4,3,5,4,4,1,48,43.0,neutral or dissatisfied +5622,53123,Female,Loyal Customer,14,Personal Travel,Eco,2065,3,4,3,4,3,4,4,3,5,4,5,4,3,4,0,37.0,neutral or dissatisfied +5623,5062,Male,disloyal Customer,22,Business travel,Eco,303,2,4,2,3,1,2,1,1,3,5,4,4,5,1,0,25.0,neutral or dissatisfied +5624,9190,Female,Loyal Customer,51,Personal Travel,Eco,363,1,4,1,2,4,4,4,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +5625,96768,Female,disloyal Customer,16,Business travel,Business,972,0,0,0,3,4,0,4,4,4,5,4,3,4,4,0,0.0,satisfied +5626,7174,Male,Loyal Customer,61,Business travel,Eco,116,1,3,3,3,1,1,1,3,3,3,3,1,2,1,100,154.0,neutral or dissatisfied +5627,128466,Female,Loyal Customer,15,Personal Travel,Eco,370,2,2,2,4,2,2,2,2,2,5,4,3,4,2,1,0.0,neutral or dissatisfied +5628,29107,Male,Loyal Customer,37,Personal Travel,Eco,987,3,5,3,5,3,3,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +5629,80501,Female,Loyal Customer,47,Business travel,Business,1749,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,1.0,satisfied +5630,27636,Female,Loyal Customer,11,Business travel,Eco Plus,956,1,4,4,4,1,1,3,1,1,4,3,4,3,1,0,0.0,neutral or dissatisfied +5631,62399,Male,Loyal Customer,51,Personal Travel,Eco,2704,2,4,1,5,4,1,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +5632,99581,Male,Loyal Customer,32,Business travel,Eco,930,2,5,3,5,2,2,2,2,3,1,3,1,4,2,54,70.0,neutral or dissatisfied +5633,21460,Male,Loyal Customer,44,Business travel,Business,1922,1,3,3,3,4,2,2,1,1,1,1,3,1,3,27,18.0,neutral or dissatisfied +5634,116989,Male,disloyal Customer,25,Business travel,Business,621,3,5,2,3,4,2,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +5635,13214,Female,Loyal Customer,53,Business travel,Eco,468,4,5,5,5,4,4,4,3,2,5,1,4,1,4,134,120.0,satisfied +5636,126538,Male,Loyal Customer,55,Business travel,Business,644,2,2,3,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +5637,1462,Male,Loyal Customer,49,Business travel,Eco,372,4,1,1,1,4,4,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +5638,5766,Male,Loyal Customer,51,Personal Travel,Eco,642,1,5,1,1,2,1,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +5639,106154,Male,Loyal Customer,37,Business travel,Business,3990,3,5,5,5,3,4,3,3,3,2,3,1,3,2,44,40.0,neutral or dissatisfied +5640,97416,Male,disloyal Customer,52,Business travel,Business,587,5,5,5,1,3,5,3,3,3,5,4,5,4,3,0,0.0,satisfied +5641,126554,Male,Loyal Customer,18,Personal Travel,Eco,644,2,5,2,1,3,2,3,3,4,5,4,4,5,3,24,33.0,neutral or dissatisfied +5642,36825,Female,disloyal Customer,58,Business travel,Eco,369,3,0,3,2,4,3,2,4,3,1,4,2,5,4,0,0.0,neutral or dissatisfied +5643,49099,Female,Loyal Customer,43,Business travel,Eco,190,5,2,2,2,3,1,2,5,5,5,5,4,5,4,38,63.0,satisfied +5644,82403,Female,Loyal Customer,63,Personal Travel,Eco,500,3,4,3,3,4,5,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +5645,93475,Female,Loyal Customer,31,Business travel,Business,1595,2,2,4,2,4,5,4,4,3,2,4,5,5,4,0,0.0,satisfied +5646,110185,Female,Loyal Customer,27,Personal Travel,Eco,882,3,3,2,3,3,2,4,3,2,1,4,1,3,3,0,0.0,neutral or dissatisfied +5647,89900,Male,Loyal Customer,38,Business travel,Eco,1306,3,1,2,1,3,3,3,3,4,2,2,1,2,3,0,32.0,neutral or dissatisfied +5648,82309,Female,disloyal Customer,22,Business travel,Eco,986,3,3,3,3,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +5649,127244,Male,Loyal Customer,53,Business travel,Business,1107,2,2,2,2,5,5,5,5,5,5,5,3,5,4,12,34.0,satisfied +5650,13525,Female,Loyal Customer,36,Business travel,Business,3770,3,3,3,3,2,4,1,5,5,5,5,2,5,2,0,0.0,satisfied +5651,93975,Male,Loyal Customer,62,Business travel,Business,1218,3,3,3,3,4,5,5,5,5,5,5,4,5,4,47,34.0,satisfied +5652,53453,Female,Loyal Customer,31,Business travel,Eco,2288,4,3,3,3,4,4,4,2,3,3,2,4,1,4,326,310.0,satisfied +5653,28891,Male,Loyal Customer,50,Business travel,Eco,937,4,3,3,3,5,4,5,5,5,2,2,4,2,5,0,0.0,satisfied +5654,23249,Male,disloyal Customer,29,Business travel,Eco,783,1,1,1,4,1,2,2,2,5,5,3,2,3,2,186,200.0,neutral or dissatisfied +5655,65051,Female,Loyal Customer,60,Personal Travel,Eco,190,2,5,0,1,3,5,4,3,3,0,3,3,3,4,0,0.0,neutral or dissatisfied +5656,56594,Female,Loyal Customer,51,Business travel,Business,1065,1,1,1,1,3,4,4,5,5,5,5,3,5,4,16,17.0,satisfied +5657,101424,Male,Loyal Customer,27,Business travel,Business,2359,5,5,5,5,4,4,4,4,5,2,4,4,5,4,23,11.0,satisfied +5658,92638,Female,Loyal Customer,61,Business travel,Business,1606,3,1,1,1,1,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +5659,24158,Female,disloyal Customer,27,Business travel,Eco,134,2,0,2,2,1,2,1,1,3,1,4,5,4,1,0,0.0,neutral or dissatisfied +5660,55509,Female,Loyal Customer,56,Business travel,Business,991,3,3,3,3,2,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +5661,126621,Male,Loyal Customer,63,Personal Travel,Business,602,3,5,3,1,5,5,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +5662,79107,Female,Loyal Customer,47,Personal Travel,Eco,306,4,2,4,3,5,4,3,2,2,4,2,2,2,2,0,22.0,neutral or dissatisfied +5663,99300,Female,Loyal Customer,55,Business travel,Business,3599,5,5,5,5,3,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +5664,55258,Male,Loyal Customer,44,Business travel,Business,1009,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +5665,112877,Male,Loyal Customer,59,Business travel,Business,1357,5,5,4,5,5,4,5,4,4,4,4,3,4,4,12,0.0,satisfied +5666,125929,Male,Loyal Customer,16,Personal Travel,Eco,861,2,5,3,2,5,3,4,5,4,3,4,3,4,5,46,33.0,neutral or dissatisfied +5667,62590,Male,disloyal Customer,23,Business travel,Business,226,5,0,5,3,2,5,2,2,2,1,4,1,5,2,2,4.0,satisfied +5668,40490,Female,Loyal Customer,14,Personal Travel,Eco,175,2,5,2,4,3,2,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +5669,28152,Male,Loyal Customer,31,Business travel,Business,2808,2,3,3,3,2,2,2,2,2,4,3,2,2,2,0,1.0,neutral or dissatisfied +5670,67306,Male,disloyal Customer,22,Business travel,Eco,929,1,1,1,2,3,1,3,3,5,2,4,5,4,3,3,4.0,neutral or dissatisfied +5671,81891,Female,disloyal Customer,30,Business travel,Business,680,1,1,1,5,5,1,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +5672,117765,Male,Loyal Customer,31,Business travel,Business,1670,2,1,3,1,2,2,2,2,2,3,2,4,3,2,40,77.0,neutral or dissatisfied +5673,103053,Male,Loyal Customer,22,Business travel,Eco,687,2,3,3,3,2,2,1,2,1,3,3,4,2,2,74,78.0,neutral or dissatisfied +5674,110863,Male,Loyal Customer,45,Business travel,Business,3730,3,3,3,3,5,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +5675,25998,Male,Loyal Customer,12,Personal Travel,Eco,577,0,3,0,4,3,3,3,3,2,1,3,4,4,3,0,0.0,satisfied +5676,30876,Female,Loyal Customer,24,Personal Travel,Eco,1607,5,5,5,2,5,5,5,5,5,5,4,1,2,5,0,0.0,satisfied +5677,8069,Male,Loyal Customer,38,Business travel,Business,3611,4,4,4,4,3,4,5,5,5,5,5,4,5,4,23,26.0,satisfied +5678,3448,Female,Loyal Customer,37,Personal Travel,Eco,296,2,5,2,3,5,2,5,5,5,4,5,4,5,5,14,11.0,neutral or dissatisfied +5679,36210,Male,Loyal Customer,37,Business travel,Business,280,0,0,0,4,3,5,5,5,5,5,1,2,5,2,0,24.0,satisfied +5680,105739,Female,Loyal Customer,40,Business travel,Business,1841,3,2,2,2,2,3,3,3,3,3,3,3,3,3,7,0.0,neutral or dissatisfied +5681,71523,Male,disloyal Customer,25,Business travel,Eco,1120,2,2,2,4,5,2,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +5682,33975,Male,disloyal Customer,22,Business travel,Eco,1034,3,3,3,5,1,3,1,1,1,4,4,5,1,1,4,0.0,neutral or dissatisfied +5683,123851,Male,disloyal Customer,27,Business travel,Eco,544,3,1,3,4,3,3,3,3,2,4,3,4,4,3,0,0.0,neutral or dissatisfied +5684,21742,Female,Loyal Customer,17,Business travel,Business,563,3,3,3,3,5,5,5,5,3,2,2,2,1,5,0,0.0,satisfied +5685,45079,Female,Loyal Customer,63,Personal Travel,Eco,588,3,4,3,5,3,4,5,5,5,3,5,4,5,3,32,20.0,neutral or dissatisfied +5686,33112,Female,Loyal Customer,29,Personal Travel,Eco,102,3,1,3,1,2,3,2,2,1,4,2,2,2,2,0,0.0,neutral or dissatisfied +5687,64774,Female,Loyal Customer,39,Business travel,Business,247,2,2,2,2,4,4,5,4,4,4,4,4,4,5,10,0.0,satisfied +5688,108848,Female,Loyal Customer,50,Business travel,Business,1947,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,4.0,satisfied +5689,49773,Male,Loyal Customer,38,Business travel,Eco,109,1,5,5,5,1,1,1,1,4,3,3,4,3,1,0,0.0,neutral or dissatisfied +5690,49569,Female,Loyal Customer,37,Business travel,Eco,337,5,5,5,5,5,5,5,5,2,1,5,4,2,5,0,0.0,satisfied +5691,118183,Male,disloyal Customer,9,Business travel,Business,1444,0,4,1,2,1,1,1,1,3,4,4,3,5,1,0,0.0,satisfied +5692,116192,Female,Loyal Customer,41,Personal Travel,Eco,296,4,3,4,1,3,4,3,3,3,3,1,1,2,3,0,0.0,satisfied +5693,7132,Male,Loyal Customer,32,Business travel,Business,135,1,3,3,3,1,1,1,1,2,1,4,2,4,1,0,0.0,neutral or dissatisfied +5694,17811,Female,Loyal Customer,44,Business travel,Eco,675,4,4,4,4,4,2,1,4,4,4,4,4,4,5,2,5.0,satisfied +5695,121164,Male,Loyal Customer,55,Business travel,Business,902,4,5,5,5,3,4,4,2,1,3,3,4,2,4,29,60.0,neutral or dissatisfied +5696,89311,Female,Loyal Customer,47,Business travel,Eco Plus,453,3,4,4,4,5,4,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +5697,53301,Male,Loyal Customer,42,Business travel,Business,3521,4,1,1,1,1,2,2,4,4,4,4,2,4,2,3,5.0,neutral or dissatisfied +5698,99518,Female,Loyal Customer,49,Business travel,Business,2974,2,2,2,2,5,4,4,4,4,4,4,3,4,4,4,0.0,satisfied +5699,12967,Female,Loyal Customer,23,Personal Travel,Eco Plus,359,2,5,2,1,2,2,2,2,4,5,5,3,4,2,0,2.0,neutral or dissatisfied +5700,31359,Male,Loyal Customer,51,Business travel,Business,589,2,2,2,2,5,3,4,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +5701,39817,Female,disloyal Customer,23,Business travel,Eco,272,1,0,1,3,3,1,3,3,2,3,1,4,5,3,0,0.0,neutral or dissatisfied +5702,90822,Male,Loyal Customer,31,Business travel,Business,594,5,5,4,5,5,5,5,5,3,4,5,3,4,5,0,2.0,satisfied +5703,102970,Female,Loyal Customer,40,Business travel,Business,3951,5,5,5,5,5,4,4,5,5,5,5,5,5,3,5,0.0,satisfied +5704,63792,Male,Loyal Customer,17,Personal Travel,Eco,1721,1,5,1,5,3,1,3,3,4,5,5,4,4,3,4,0.0,neutral or dissatisfied +5705,90068,Female,Loyal Customer,39,Business travel,Business,1933,5,5,2,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +5706,41390,Male,disloyal Customer,36,Business travel,Eco,809,3,4,4,4,1,4,1,1,3,3,4,4,4,1,118,105.0,neutral or dissatisfied +5707,10608,Male,Loyal Customer,40,Business travel,Business,3643,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +5708,46867,Female,disloyal Customer,27,Business travel,Eco,909,5,5,5,3,1,5,1,1,3,5,3,4,1,1,0,0.0,satisfied +5709,94514,Female,Loyal Customer,52,Business travel,Business,248,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +5710,39984,Male,Loyal Customer,17,Business travel,Eco Plus,1262,3,1,1,1,3,4,4,3,2,5,5,1,3,3,0,0.0,satisfied +5711,45901,Male,Loyal Customer,29,Business travel,Business,3139,2,2,2,2,5,5,5,5,2,2,2,1,5,5,40,26.0,satisfied +5712,113416,Male,Loyal Customer,58,Business travel,Business,3596,3,3,3,3,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +5713,71207,Male,disloyal Customer,28,Business travel,Eco,733,2,2,2,2,2,2,1,2,3,3,3,2,3,2,82,84.0,neutral or dissatisfied +5714,63293,Male,Loyal Customer,54,Business travel,Business,2468,2,2,4,2,1,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +5715,58831,Female,Loyal Customer,46,Business travel,Business,2590,3,3,3,3,4,4,5,4,4,4,4,5,4,3,3,0.0,satisfied +5716,65529,Male,Loyal Customer,66,Personal Travel,Eco,1616,2,4,2,3,4,2,4,4,4,3,4,3,5,4,23,23.0,neutral or dissatisfied +5717,82266,Male,disloyal Customer,12,Business travel,Eco,1481,4,4,4,4,1,4,1,1,4,3,3,1,4,1,10,13.0,neutral or dissatisfied +5718,28232,Male,Loyal Customer,9,Business travel,Eco,1009,0,3,0,1,5,0,3,5,4,3,5,2,2,5,0,0.0,satisfied +5719,22199,Female,Loyal Customer,49,Personal Travel,Eco,606,5,1,5,3,2,4,3,2,2,5,2,3,2,2,0,0.0,satisfied +5720,107528,Male,Loyal Customer,9,Personal Travel,Eco Plus,838,3,4,3,3,1,3,1,1,3,4,4,4,5,1,33,23.0,neutral or dissatisfied +5721,3959,Female,Loyal Customer,58,Personal Travel,Eco,764,3,3,3,3,2,4,3,5,5,3,2,1,5,3,0,6.0,neutral or dissatisfied +5722,100173,Male,Loyal Customer,31,Personal Travel,Eco,468,3,4,3,1,3,3,2,3,5,3,5,5,5,3,9,9.0,neutral or dissatisfied +5723,126419,Male,Loyal Customer,57,Business travel,Business,2134,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +5724,86796,Male,disloyal Customer,44,Business travel,Business,692,3,3,3,4,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +5725,17488,Female,disloyal Customer,25,Business travel,Eco,352,1,3,1,3,3,1,3,3,5,3,3,2,2,3,0,0.0,neutral or dissatisfied +5726,102384,Female,disloyal Customer,27,Business travel,Eco,197,4,2,3,4,4,3,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +5727,9483,Male,disloyal Customer,33,Business travel,Business,322,3,3,3,3,3,3,3,3,4,5,5,3,5,3,57,87.0,neutral or dissatisfied +5728,3213,Female,Loyal Customer,35,Business travel,Eco Plus,585,4,3,5,3,4,4,4,4,4,5,4,2,4,4,47,50.0,neutral or dissatisfied +5729,77710,Male,disloyal Customer,33,Business travel,Business,696,1,1,1,3,4,1,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +5730,70368,Female,disloyal Customer,31,Business travel,Eco,1145,1,1,1,4,4,1,4,4,3,3,4,4,4,4,0,14.0,neutral or dissatisfied +5731,127664,Male,Loyal Customer,38,Business travel,Business,2153,2,2,2,2,4,4,4,4,5,5,4,4,3,4,173,173.0,satisfied +5732,70437,Female,Loyal Customer,54,Business travel,Business,3801,1,5,5,5,5,3,3,4,4,3,1,1,4,4,38,28.0,neutral or dissatisfied +5733,37111,Male,Loyal Customer,44,Business travel,Business,3768,2,3,2,2,1,2,2,4,4,5,4,5,4,3,11,14.0,satisfied +5734,33165,Male,Loyal Customer,33,Personal Travel,Eco,163,3,4,3,2,4,3,4,4,4,5,5,4,5,4,0,0.0,neutral or dissatisfied +5735,80777,Female,Loyal Customer,49,Business travel,Business,2442,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +5736,82169,Female,Loyal Customer,15,Personal Travel,Eco,311,3,4,3,1,5,3,2,5,4,2,4,4,5,5,0,8.0,neutral or dissatisfied +5737,121257,Female,Loyal Customer,51,Business travel,Business,3201,3,3,3,3,4,5,2,5,5,5,5,4,5,5,0,0.0,satisfied +5738,35014,Male,Loyal Customer,62,Business travel,Business,740,2,1,1,1,1,3,4,2,2,2,2,4,2,1,0,14.0,neutral or dissatisfied +5739,55790,Female,Loyal Customer,30,Business travel,Eco,2400,1,3,3,3,1,1,1,1,3,2,3,1,1,1,0,11.0,neutral or dissatisfied +5740,2353,Male,Loyal Customer,48,Business travel,Business,925,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +5741,48383,Male,disloyal Customer,47,Personal Travel,Eco,674,3,4,3,2,4,3,4,4,4,3,4,3,5,4,16,9.0,neutral or dissatisfied +5742,92634,Female,Loyal Customer,56,Business travel,Business,1564,5,5,5,5,3,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +5743,63218,Female,Loyal Customer,36,Business travel,Business,3856,3,3,3,3,5,5,4,2,2,2,2,5,2,4,1,0.0,satisfied +5744,82051,Female,disloyal Customer,44,Business travel,Business,1535,5,5,5,2,5,5,5,5,5,5,5,3,5,5,21,34.0,satisfied +5745,5745,Female,Loyal Customer,51,Business travel,Business,1524,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +5746,119059,Female,Loyal Customer,66,Personal Travel,Eco,2279,1,5,1,2,2,5,5,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +5747,12537,Male,Loyal Customer,38,Business travel,Business,2421,2,5,1,5,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +5748,109946,Male,Loyal Customer,33,Personal Travel,Eco,971,0,1,0,3,1,0,4,1,4,5,4,3,3,1,15,0.0,satisfied +5749,103330,Male,Loyal Customer,30,Personal Travel,Eco,1139,2,4,3,3,4,3,4,4,1,2,4,1,4,4,24,17.0,neutral or dissatisfied +5750,3271,Female,Loyal Customer,39,Business travel,Business,3938,3,3,3,3,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +5751,39898,Male,disloyal Customer,44,Business travel,Business,272,3,3,3,2,4,3,4,4,2,4,1,1,2,4,10,24.0,neutral or dissatisfied +5752,57670,Female,disloyal Customer,30,Business travel,Eco Plus,200,1,1,1,3,4,1,2,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +5753,125202,Male,Loyal Customer,24,Business travel,Business,651,4,5,5,5,4,4,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +5754,42809,Female,disloyal Customer,50,Business travel,Eco,677,4,4,4,3,3,4,3,3,3,3,1,3,5,3,4,1.0,satisfied +5755,22432,Female,disloyal Customer,70,Personal Travel,Eco,238,5,4,5,1,5,5,5,5,3,2,4,5,4,5,54,46.0,satisfied +5756,40471,Female,Loyal Customer,57,Business travel,Business,3423,0,4,0,3,3,3,3,2,2,2,2,5,2,2,0,0.0,satisfied +5757,71615,Female,Loyal Customer,48,Business travel,Eco,1197,4,2,5,2,5,3,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +5758,72744,Female,Loyal Customer,48,Business travel,Business,3943,2,1,2,2,3,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +5759,125220,Male,Loyal Customer,16,Personal Travel,Eco,651,3,4,2,2,2,2,1,2,5,1,5,5,3,2,7,0.0,neutral or dissatisfied +5760,82151,Female,Loyal Customer,41,Business travel,Business,2399,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +5761,53831,Male,Loyal Customer,62,Business travel,Eco,224,4,5,5,5,4,4,4,4,3,4,1,1,4,4,1,0.0,satisfied +5762,124295,Male,Loyal Customer,56,Business travel,Business,255,5,5,5,5,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +5763,89538,Male,Loyal Customer,27,Business travel,Business,950,4,3,4,4,3,3,3,3,4,3,5,5,5,3,0,0.0,satisfied +5764,52731,Female,Loyal Customer,42,Business travel,Business,2306,1,1,1,1,3,5,3,4,4,4,4,1,4,4,16,11.0,satisfied +5765,113347,Male,Loyal Customer,64,Business travel,Business,258,0,0,0,4,2,4,5,2,2,5,5,5,2,4,29,29.0,satisfied +5766,121346,Female,Loyal Customer,25,Business travel,Business,2130,5,5,5,5,4,3,3,5,3,5,5,3,4,3,150,120.0,satisfied +5767,55749,Female,Loyal Customer,26,Business travel,Business,1737,3,3,3,3,4,4,4,4,4,4,5,5,4,4,3,4.0,satisfied +5768,19630,Female,disloyal Customer,36,Business travel,Eco,642,1,0,1,3,5,1,2,5,5,2,4,2,4,5,4,0.0,neutral or dissatisfied +5769,71285,Female,Loyal Customer,24,Business travel,Business,740,4,4,4,4,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +5770,84634,Male,Loyal Customer,33,Personal Travel,Eco,707,1,4,1,2,1,1,1,1,3,2,4,4,5,1,62,52.0,neutral or dissatisfied +5771,18632,Female,Loyal Customer,31,Personal Travel,Eco,192,3,5,3,2,3,5,5,4,5,5,4,5,4,5,241,261.0,neutral or dissatisfied +5772,36422,Male,Loyal Customer,37,Business travel,Eco,369,4,4,4,4,4,5,4,4,3,5,4,5,4,4,0,0.0,satisfied +5773,102933,Male,Loyal Customer,31,Personal Travel,Eco,436,1,5,1,5,1,2,2,3,5,4,5,2,5,2,136,124.0,neutral or dissatisfied +5774,122377,Female,Loyal Customer,62,Business travel,Business,2551,2,3,3,3,3,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +5775,99400,Male,Loyal Customer,39,Business travel,Business,2637,2,3,3,3,1,3,4,2,2,2,2,2,2,4,54,47.0,neutral or dissatisfied +5776,87983,Male,Loyal Customer,32,Business travel,Business,223,1,1,1,1,5,5,4,5,5,4,4,3,4,5,0,0.0,satisfied +5777,49539,Female,Loyal Customer,37,Business travel,Business,308,4,4,4,4,1,5,3,5,5,5,5,5,5,1,6,8.0,satisfied +5778,19916,Female,disloyal Customer,36,Business travel,Eco,315,4,3,4,2,2,4,4,2,3,3,4,1,3,2,12,4.0,neutral or dissatisfied +5779,55077,Male,Loyal Customer,58,Business travel,Business,3820,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +5780,108715,Female,disloyal Customer,27,Business travel,Eco,321,4,3,4,3,5,4,1,5,3,2,4,4,4,5,11,8.0,neutral or dissatisfied +5781,107512,Female,Loyal Customer,54,Business travel,Business,3994,4,4,4,4,4,5,5,5,5,5,5,5,5,5,13,6.0,satisfied +5782,59545,Male,Loyal Customer,44,Business travel,Business,787,1,1,1,1,2,4,4,4,4,4,4,4,4,4,20,6.0,satisfied +5783,76659,Female,Loyal Customer,21,Personal Travel,Eco,481,2,2,2,4,2,2,2,2,4,2,4,2,4,2,65,65.0,neutral or dissatisfied +5784,63639,Female,disloyal Customer,37,Business travel,Eco,202,4,3,4,4,2,4,2,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +5785,31146,Male,disloyal Customer,22,Business travel,Eco,495,4,0,4,2,5,4,1,5,4,2,4,3,4,5,0,0.0,satisfied +5786,47406,Male,Loyal Customer,53,Business travel,Eco,599,2,4,4,4,3,2,3,3,2,3,3,3,4,3,29,25.0,neutral or dissatisfied +5787,49450,Female,Loyal Customer,34,Business travel,Business,3149,0,3,0,4,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +5788,63176,Female,Loyal Customer,40,Business travel,Business,2251,5,5,2,5,3,4,4,5,5,5,5,5,5,5,25,25.0,satisfied +5789,1788,Male,Loyal Customer,50,Business travel,Business,500,3,5,3,3,5,5,4,5,5,5,5,4,5,5,25,31.0,satisfied +5790,47565,Female,Loyal Customer,11,Personal Travel,Eco Plus,590,1,4,1,2,4,1,4,4,5,1,4,5,5,4,29,28.0,neutral or dissatisfied +5791,38950,Male,Loyal Customer,30,Personal Travel,Eco Plus,320,1,5,1,1,2,1,2,2,1,4,4,1,1,2,0,9.0,neutral or dissatisfied +5792,89618,Female,disloyal Customer,25,Business travel,Eco,1089,2,2,2,4,2,2,2,2,1,5,4,3,4,2,0,21.0,neutral or dissatisfied +5793,99806,Male,Loyal Customer,12,Personal Travel,Eco,584,2,4,2,3,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +5794,20555,Male,Loyal Customer,45,Business travel,Business,2891,5,5,5,5,2,2,1,5,5,5,5,5,5,3,0,0.0,satisfied +5795,115830,Female,disloyal Customer,39,Business travel,Eco,358,3,1,3,4,2,3,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +5796,92775,Female,Loyal Customer,24,Business travel,Business,1671,2,2,3,2,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +5797,67458,Male,Loyal Customer,55,Personal Travel,Eco,641,3,4,3,2,1,3,1,1,4,4,4,4,4,1,50,66.0,neutral or dissatisfied +5798,55936,Female,disloyal Customer,21,Business travel,Eco,733,5,5,5,1,1,5,1,1,5,2,5,4,5,1,0,0.0,satisfied +5799,102721,Male,Loyal Customer,54,Personal Travel,Eco,365,1,4,1,2,3,1,3,3,4,4,5,3,5,3,9,1.0,neutral or dissatisfied +5800,32991,Male,Loyal Customer,8,Personal Travel,Eco,102,0,5,0,5,3,0,3,3,4,3,1,1,1,3,0,0.0,satisfied +5801,86372,Male,Loyal Customer,30,Business travel,Business,2271,3,3,3,3,2,2,2,2,3,4,4,4,5,2,0,0.0,satisfied +5802,4079,Female,disloyal Customer,11,Business travel,Business,544,0,0,0,2,5,0,5,5,3,4,5,3,4,5,0,2.0,satisfied +5803,31447,Female,disloyal Customer,21,Business travel,Eco,862,1,1,1,4,3,1,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +5804,59567,Female,Loyal Customer,58,Business travel,Business,2617,2,2,2,2,4,5,5,5,5,5,5,4,5,5,10,0.0,satisfied +5805,80441,Female,Loyal Customer,27,Personal Travel,Eco,2248,3,5,3,4,3,5,5,4,3,4,5,5,4,5,157,149.0,neutral or dissatisfied +5806,42813,Male,disloyal Customer,36,Business travel,Business,277,1,1,1,4,3,1,3,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +5807,4030,Male,Loyal Customer,58,Business travel,Business,3240,1,2,2,2,3,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +5808,44629,Male,Loyal Customer,13,Personal Travel,Business,268,3,4,0,4,3,0,2,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +5809,87509,Male,Loyal Customer,69,Personal Travel,Eco,321,2,5,2,3,2,2,2,2,5,5,1,5,1,2,41,31.0,neutral or dissatisfied +5810,60195,Male,Loyal Customer,58,Business travel,Business,1546,2,2,5,2,4,4,5,4,4,4,4,4,4,3,1,4.0,satisfied +5811,95146,Male,Loyal Customer,8,Personal Travel,Eco,192,4,4,4,3,1,4,1,1,4,5,4,5,5,1,3,0.0,neutral or dissatisfied +5812,30007,Male,disloyal Customer,33,Business travel,Eco,183,1,3,1,4,4,1,4,4,2,4,4,1,4,4,57,55.0,neutral or dissatisfied +5813,29970,Female,Loyal Customer,36,Business travel,Business,204,4,2,2,2,1,3,4,1,1,1,4,4,1,3,13,7.0,neutral or dissatisfied +5814,1948,Male,Loyal Customer,36,Business travel,Business,293,2,4,4,4,5,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +5815,109936,Male,Loyal Customer,51,Personal Travel,Eco,1073,1,1,2,4,2,2,3,2,3,2,3,2,4,2,19,0.0,neutral or dissatisfied +5816,48860,Male,Loyal Customer,36,Business travel,Eco,209,5,4,5,4,5,5,5,5,5,2,2,2,5,5,0,0.0,satisfied +5817,60002,Male,Loyal Customer,40,Personal Travel,Eco,1023,4,5,4,5,3,4,3,3,5,5,2,2,1,3,0,0.0,neutral or dissatisfied +5818,63605,Female,Loyal Customer,22,Business travel,Business,1440,1,1,1,1,2,2,2,2,3,3,5,4,5,2,0,0.0,satisfied +5819,129397,Male,Loyal Customer,46,Personal Travel,Business,414,2,2,1,3,4,3,4,3,3,1,2,4,3,1,1,0.0,neutral or dissatisfied +5820,37420,Male,Loyal Customer,51,Business travel,Business,3582,2,4,2,4,4,4,4,2,2,2,2,2,2,2,51,24.0,neutral or dissatisfied +5821,100707,Male,Loyal Customer,13,Business travel,Eco Plus,677,3,5,5,5,3,3,2,3,3,5,4,1,4,3,4,6.0,neutral or dissatisfied +5822,2065,Male,Loyal Customer,24,Business travel,Eco,812,1,4,4,4,1,1,4,1,1,5,4,3,4,1,30,33.0,neutral or dissatisfied +5823,31671,Male,Loyal Customer,40,Business travel,Eco,967,5,1,1,1,5,4,5,5,3,2,5,1,4,5,0,0.0,satisfied +5824,98790,Male,disloyal Customer,7,Business travel,Eco,630,3,2,2,4,2,2,2,2,2,1,4,2,4,2,38,32.0,neutral or dissatisfied +5825,83641,Female,Loyal Customer,45,Business travel,Business,3722,3,5,5,5,2,4,4,3,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +5826,107286,Male,Loyal Customer,62,Business travel,Business,1524,3,2,2,2,5,3,2,3,3,3,3,3,3,1,15,20.0,neutral or dissatisfied +5827,90257,Female,Loyal Customer,52,Personal Travel,Business,757,2,4,2,5,4,4,4,3,3,2,3,4,3,4,84,85.0,neutral or dissatisfied +5828,47144,Male,Loyal Customer,27,Business travel,Business,3225,1,1,3,1,4,5,4,4,1,1,3,4,5,4,103,109.0,satisfied +5829,17576,Female,Loyal Customer,48,Business travel,Business,3328,3,3,3,3,5,3,1,5,5,5,5,1,5,4,24,22.0,satisfied +5830,43492,Male,Loyal Customer,36,Personal Travel,Eco,752,2,5,2,2,1,2,1,1,3,5,5,4,4,1,84,70.0,neutral or dissatisfied +5831,98481,Male,disloyal Customer,22,Business travel,Eco,668,4,5,4,2,1,4,1,1,5,5,5,3,4,1,36,24.0,neutral or dissatisfied +5832,40535,Male,Loyal Customer,55,Business travel,Eco,411,5,3,3,3,5,5,5,5,4,2,2,1,5,5,0,0.0,satisfied +5833,78524,Female,Loyal Customer,23,Personal Travel,Eco,526,1,5,2,3,2,2,2,2,4,5,4,4,5,2,30,26.0,neutral or dissatisfied +5834,54526,Male,Loyal Customer,70,Personal Travel,Eco,802,2,1,2,4,3,2,3,3,3,2,3,4,3,3,0,9.0,neutral or dissatisfied +5835,98304,Male,Loyal Customer,39,Personal Travel,Eco Plus,1072,1,2,1,2,5,1,5,5,3,3,2,4,3,5,14,6.0,neutral or dissatisfied +5836,39696,Male,disloyal Customer,23,Business travel,Business,298,5,4,5,5,3,5,3,3,5,2,5,4,4,3,0,0.0,satisfied +5837,15722,Female,Loyal Customer,29,Business travel,Business,1793,3,1,2,1,3,3,3,3,2,1,3,1,3,3,0,11.0,neutral or dissatisfied +5838,4543,Female,Loyal Customer,68,Business travel,Business,3222,1,4,4,4,5,4,4,1,1,2,1,4,1,2,67,85.0,neutral or dissatisfied +5839,36475,Male,Loyal Customer,32,Business travel,Business,1237,3,3,3,3,4,4,4,4,5,3,5,5,4,4,0,10.0,satisfied +5840,70342,Female,Loyal Customer,28,Personal Travel,Eco,986,4,5,4,1,4,4,4,4,4,3,4,4,4,4,8,0.0,neutral or dissatisfied +5841,123217,Male,Loyal Customer,40,Personal Travel,Eco,328,2,3,2,3,5,2,5,5,5,1,2,3,4,5,0,4.0,neutral or dissatisfied +5842,103891,Male,Loyal Customer,9,Personal Travel,Eco,634,0,5,0,3,1,0,1,1,4,2,5,3,4,1,0,0.0,satisfied +5843,85625,Female,Loyal Customer,39,Personal Travel,Eco,259,3,3,0,4,3,0,1,3,2,5,4,2,3,3,0,8.0,neutral or dissatisfied +5844,72563,Female,Loyal Customer,29,Business travel,Business,929,3,5,5,5,3,3,3,3,3,5,4,4,3,3,8,16.0,neutral or dissatisfied +5845,91992,Male,Loyal Customer,40,Business travel,Business,1826,3,4,3,3,3,5,5,4,4,4,4,5,4,3,5,0.0,satisfied +5846,42820,Male,Loyal Customer,53,Personal Travel,Eco,896,1,2,1,4,2,1,2,2,1,3,3,3,3,2,0,4.0,neutral or dissatisfied +5847,101854,Female,disloyal Customer,32,Business travel,Eco,519,1,2,1,3,2,1,3,2,4,2,4,3,3,2,1,0.0,neutral or dissatisfied +5848,115099,Female,Loyal Customer,51,Business travel,Business,2254,1,1,1,1,4,5,5,4,4,4,4,3,4,3,67,58.0,satisfied +5849,55759,Female,Loyal Customer,56,Business travel,Business,3325,0,0,0,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +5850,63256,Female,disloyal Customer,25,Business travel,Business,372,1,4,0,3,5,0,5,5,5,3,5,5,5,5,0,2.0,neutral or dissatisfied +5851,111059,Female,Loyal Customer,69,Personal Travel,Eco,197,3,4,3,1,1,3,2,2,2,3,2,2,2,2,2,0.0,neutral or dissatisfied +5852,3609,Male,Loyal Customer,22,Personal Travel,Eco,999,3,3,3,3,4,3,4,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +5853,45582,Male,Loyal Customer,43,Business travel,Eco,260,4,3,3,3,4,4,4,4,5,3,4,4,3,4,49,42.0,satisfied +5854,98777,Male,Loyal Customer,60,Business travel,Business,2075,1,1,1,1,3,4,4,5,5,5,5,4,5,3,3,0.0,satisfied +5855,24236,Male,Loyal Customer,68,Business travel,Business,302,0,0,0,3,1,5,1,4,4,4,4,2,4,4,6,0.0,satisfied +5856,40007,Female,Loyal Customer,43,Business travel,Business,3629,5,5,5,5,5,1,1,3,3,4,3,4,3,4,0,0.0,satisfied +5857,90976,Male,disloyal Customer,41,Business travel,Eco,115,4,0,4,3,5,4,5,5,4,3,4,4,1,5,0,0.0,neutral or dissatisfied +5858,88125,Male,Loyal Customer,50,Business travel,Business,444,1,1,1,1,3,4,4,2,2,2,2,3,2,4,9,11.0,satisfied +5859,83161,Female,Loyal Customer,41,Business travel,Business,1858,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +5860,16865,Female,Loyal Customer,36,Business travel,Business,3724,4,1,4,4,2,1,2,4,4,4,4,3,4,4,7,11.0,satisfied +5861,57881,Male,Loyal Customer,39,Business travel,Business,305,3,3,3,3,2,4,5,4,4,5,4,3,4,3,4,6.0,satisfied +5862,74501,Male,Loyal Customer,56,Business travel,Business,3006,3,3,2,3,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +5863,45141,Male,disloyal Customer,48,Business travel,Eco,174,1,3,0,5,1,0,1,1,3,4,2,5,2,1,1,0.0,neutral or dissatisfied +5864,25148,Female,Loyal Customer,28,Business travel,Business,2061,1,1,1,1,5,5,5,5,5,2,1,3,3,5,6,0.0,satisfied +5865,29897,Female,Loyal Customer,36,Business travel,Business,3545,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +5866,93153,Female,Loyal Customer,44,Business travel,Business,3850,5,5,5,5,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +5867,96502,Male,Loyal Customer,33,Business travel,Eco,302,4,4,4,4,4,4,4,4,1,5,4,4,2,4,17,10.0,satisfied +5868,118258,Female,Loyal Customer,41,Business travel,Eco,349,4,5,5,5,4,4,4,4,1,4,3,2,5,4,12,4.0,satisfied +5869,33201,Female,Loyal Customer,50,Business travel,Eco Plus,216,4,1,1,1,3,4,5,4,4,4,4,4,4,1,0,0.0,satisfied +5870,41001,Male,Loyal Customer,54,Business travel,Eco,1297,4,4,4,4,4,4,4,4,3,3,4,2,1,4,0,0.0,satisfied +5871,76298,Female,Loyal Customer,44,Business travel,Business,2182,1,1,1,1,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +5872,105451,Male,disloyal Customer,9,Business travel,Business,998,4,1,5,3,1,5,1,1,3,4,5,5,5,1,0,0.0,satisfied +5873,64240,Female,disloyal Customer,11,Business travel,Eco,995,1,1,1,4,5,1,5,5,3,1,3,1,3,5,15,10.0,neutral or dissatisfied +5874,128677,Female,disloyal Customer,21,Business travel,Eco,768,1,1,1,4,1,4,1,3,4,3,4,1,3,1,64,71.0,neutral or dissatisfied +5875,57803,Male,disloyal Customer,25,Business travel,Eco,1235,2,2,2,3,2,2,2,2,4,3,3,1,4,2,1,0.0,neutral or dissatisfied +5876,62940,Female,Loyal Customer,42,Business travel,Business,862,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +5877,88391,Male,Loyal Customer,25,Business travel,Business,2225,2,5,4,5,2,2,2,2,4,2,4,3,4,2,14,18.0,neutral or dissatisfied +5878,20621,Male,disloyal Customer,13,Business travel,Eco,783,2,2,2,4,5,2,5,5,4,5,4,1,3,5,30,20.0,neutral or dissatisfied +5879,58821,Male,Loyal Customer,26,Personal Travel,Eco,1012,1,3,1,2,1,1,1,1,3,3,4,2,4,1,12,7.0,neutral or dissatisfied +5880,4560,Female,Loyal Customer,52,Business travel,Eco,561,3,1,1,1,3,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +5881,50736,Female,Loyal Customer,21,Personal Travel,Eco,193,2,5,2,2,1,2,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +5882,78258,Female,Loyal Customer,47,Business travel,Business,1645,2,2,2,2,5,5,4,4,4,4,4,4,4,5,7,8.0,satisfied +5883,50522,Female,Loyal Customer,56,Personal Travel,Eco,109,4,3,4,1,2,4,4,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +5884,52484,Female,Loyal Customer,10,Personal Travel,Eco Plus,651,3,2,3,3,3,3,3,3,1,2,2,3,3,3,0,0.0,neutral or dissatisfied +5885,43279,Female,disloyal Customer,32,Business travel,Eco,531,3,0,4,4,3,4,3,3,1,1,5,2,4,3,0,0.0,neutral or dissatisfied +5886,103883,Female,Loyal Customer,33,Personal Travel,Eco,1072,2,5,2,1,1,2,1,1,5,2,4,4,5,1,1,0.0,neutral or dissatisfied +5887,52186,Male,disloyal Customer,27,Business travel,Eco,493,4,0,4,2,5,4,5,5,1,2,2,4,1,5,0,2.0,neutral or dissatisfied +5888,119042,Female,disloyal Customer,39,Business travel,Business,2279,2,2,2,4,3,2,3,3,3,5,3,3,4,3,19,0.0,neutral or dissatisfied +5889,56894,Male,disloyal Customer,26,Business travel,Business,2565,3,3,3,2,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +5890,52283,Female,disloyal Customer,38,Business travel,Eco,425,4,5,4,1,4,4,4,4,4,4,3,4,3,4,0,0.0,neutral or dissatisfied +5891,24420,Male,Loyal Customer,58,Business travel,Eco,634,5,4,5,4,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +5892,49837,Female,disloyal Customer,36,Business travel,Eco,134,3,0,4,4,2,4,2,2,3,2,5,2,1,2,0,5.0,neutral or dissatisfied +5893,31676,Female,Loyal Customer,43,Business travel,Business,3547,2,3,3,3,4,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +5894,61219,Male,Loyal Customer,30,Business travel,Business,3071,2,1,4,1,2,2,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +5895,70850,Female,Loyal Customer,30,Business travel,Business,2813,1,1,1,1,5,5,5,5,5,4,5,5,5,5,8,0.0,satisfied +5896,117174,Male,Loyal Customer,20,Personal Travel,Eco,651,3,4,3,4,3,3,3,2,4,5,2,3,3,3,176,161.0,neutral or dissatisfied +5897,126003,Male,disloyal Customer,39,Business travel,Business,631,1,1,1,4,5,1,1,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +5898,48818,Female,Loyal Customer,59,Personal Travel,Business,86,4,4,4,4,5,4,4,4,4,4,4,4,4,1,0,0.0,satisfied +5899,84193,Female,Loyal Customer,37,Business travel,Business,3729,2,2,2,2,2,5,5,4,4,5,4,4,4,3,24,40.0,satisfied +5900,92739,Female,Loyal Customer,58,Business travel,Business,1276,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +5901,1531,Male,disloyal Customer,40,Business travel,Business,862,3,2,2,2,3,2,5,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +5902,46841,Male,Loyal Customer,52,Business travel,Eco,850,5,5,5,5,5,5,5,5,2,4,2,5,1,5,38,56.0,satisfied +5903,58704,Female,Loyal Customer,25,Business travel,Business,4243,4,5,3,5,3,4,4,3,2,3,4,4,4,4,4,0.0,neutral or dissatisfied +5904,2446,Male,Loyal Customer,47,Business travel,Business,604,5,5,5,5,3,4,4,5,5,5,5,4,5,4,17,3.0,satisfied +5905,38393,Female,Loyal Customer,23,Personal Travel,Eco,1626,2,5,2,2,4,2,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +5906,92461,Female,Loyal Customer,45,Business travel,Eco,1947,1,1,3,1,4,3,3,1,1,1,1,1,1,4,33,30.0,neutral or dissatisfied +5907,46590,Male,disloyal Customer,33,Business travel,Eco,125,1,2,1,3,3,1,3,3,4,5,4,1,4,3,40,55.0,neutral or dissatisfied +5908,113398,Male,disloyal Customer,23,Business travel,Eco,397,3,0,3,3,4,3,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +5909,110687,Male,Loyal Customer,59,Personal Travel,Eco,837,2,4,2,3,5,2,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +5910,33993,Male,disloyal Customer,27,Business travel,Eco,899,3,3,3,4,4,3,1,4,3,2,5,2,5,4,0,0.0,neutral or dissatisfied +5911,26854,Male,Loyal Customer,65,Personal Travel,Eco,224,2,1,2,3,2,2,2,2,3,4,3,3,3,2,6,8.0,neutral or dissatisfied +5912,76370,Male,Loyal Customer,44,Business travel,Business,3339,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,19.0,satisfied +5913,26170,Female,disloyal Customer,29,Business travel,Eco,515,3,4,3,4,4,3,4,4,3,1,4,3,4,4,21,4.0,neutral or dissatisfied +5914,71502,Male,Loyal Customer,51,Business travel,Business,2820,5,5,5,5,4,4,5,4,4,5,4,3,4,5,2,0.0,satisfied +5915,98071,Female,Loyal Customer,46,Business travel,Business,1449,2,2,2,2,2,4,4,3,3,4,3,5,3,5,2,0.0,satisfied +5916,33558,Female,Loyal Customer,37,Business travel,Eco,399,4,4,4,4,4,4,4,4,3,1,2,4,1,4,0,6.0,satisfied +5917,126648,Male,disloyal Customer,37,Business travel,Eco,202,3,0,3,4,4,3,3,4,2,2,5,2,2,4,0,0.0,neutral or dissatisfied +5918,5541,Male,Loyal Customer,52,Personal Travel,Eco,431,1,5,1,2,2,1,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +5919,119914,Female,Loyal Customer,48,Business travel,Business,872,2,4,4,4,4,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +5920,5960,Female,Loyal Customer,26,Personal Travel,Eco,1250,2,3,2,3,2,2,2,2,3,1,2,4,3,2,3,7.0,neutral or dissatisfied +5921,60374,Male,Loyal Customer,42,Business travel,Business,1452,5,5,5,5,3,5,5,5,5,5,5,3,5,4,42,68.0,satisfied +5922,58841,Female,disloyal Customer,24,Business travel,Eco,1012,1,1,1,4,3,1,3,3,4,2,4,5,4,3,32,35.0,neutral or dissatisfied +5923,21279,Male,Loyal Customer,20,Business travel,Business,2940,2,4,4,4,2,2,2,2,2,4,3,2,4,2,6,1.0,neutral or dissatisfied +5924,45787,Male,Loyal Customer,41,Business travel,Eco,391,3,1,1,1,4,3,4,4,3,3,2,3,2,4,0,0.0,satisfied +5925,66126,Female,Loyal Customer,37,Business travel,Business,2801,2,4,4,4,1,4,3,5,5,4,2,1,5,2,18,18.0,neutral or dissatisfied +5926,79505,Female,Loyal Customer,58,Business travel,Business,2166,5,5,5,5,2,2,2,4,3,4,4,2,4,2,164,152.0,satisfied +5927,120040,Female,Loyal Customer,41,Business travel,Business,2911,5,5,5,5,2,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +5928,47204,Female,Loyal Customer,12,Personal Travel,Eco,954,2,3,2,4,1,2,1,1,5,3,5,3,3,1,6,0.0,neutral or dissatisfied +5929,37537,Female,Loyal Customer,28,Business travel,Eco,1005,4,3,3,3,4,4,4,4,1,4,3,2,2,4,24,26.0,neutral or dissatisfied +5930,90604,Male,disloyal Customer,44,Business travel,Business,366,3,3,3,3,4,3,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +5931,94869,Female,Loyal Customer,42,Business travel,Business,3234,3,3,3,3,4,4,3,3,3,3,3,2,3,3,50,48.0,neutral or dissatisfied +5932,56804,Female,disloyal Customer,42,Business travel,Business,1725,3,3,3,4,3,3,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +5933,48762,Female,disloyal Customer,24,Business travel,Business,110,5,5,5,2,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +5934,77908,Female,Loyal Customer,43,Personal Travel,Eco,456,3,5,3,3,2,5,5,3,3,3,1,5,3,4,0,2.0,neutral or dissatisfied +5935,105308,Female,Loyal Customer,43,Personal Travel,Eco,967,2,5,2,3,4,5,5,3,3,2,5,4,3,3,24,42.0,neutral or dissatisfied +5936,127064,Female,disloyal Customer,43,Business travel,Eco,647,2,4,2,3,4,2,4,4,3,1,4,1,3,4,0,0.0,neutral or dissatisfied +5937,55623,Female,Loyal Customer,45,Business travel,Business,1824,2,2,3,2,4,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +5938,94636,Female,Loyal Customer,56,Business travel,Business,2067,1,0,0,4,1,3,4,4,4,0,4,2,4,4,0,0.0,neutral or dissatisfied +5939,23303,Female,Loyal Customer,56,Business travel,Eco,359,4,4,4,4,3,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +5940,103741,Female,Loyal Customer,45,Personal Travel,Eco,405,5,4,5,3,4,5,5,4,4,5,1,4,4,3,0,0.0,satisfied +5941,103688,Male,Loyal Customer,22,Business travel,Eco,405,3,3,1,3,3,3,1,3,2,3,3,4,2,3,0,0.0,neutral or dissatisfied +5942,54927,Female,disloyal Customer,24,Business travel,Eco,1303,5,5,5,1,5,5,5,5,5,4,4,5,4,5,2,0.0,satisfied +5943,1216,Female,Loyal Customer,58,Personal Travel,Eco,113,1,2,0,3,1,3,3,4,4,0,4,2,4,2,0,0.0,neutral or dissatisfied +5944,100484,Female,Loyal Customer,28,Business travel,Eco,580,1,2,2,2,1,1,1,1,3,4,1,2,1,1,28,20.0,neutral or dissatisfied +5945,88696,Male,Loyal Customer,21,Personal Travel,Eco,404,2,5,2,4,5,2,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +5946,115736,Female,Loyal Customer,32,Business travel,Business,2614,5,4,4,4,5,4,5,5,3,3,2,4,3,5,44,40.0,neutral or dissatisfied +5947,54220,Female,Loyal Customer,53,Business travel,Eco,1222,5,3,3,3,1,2,3,5,5,5,5,1,5,4,11,0.0,satisfied +5948,85579,Female,disloyal Customer,68,Business travel,Eco,259,4,2,4,4,2,4,3,2,2,2,3,2,3,2,4,6.0,neutral or dissatisfied +5949,114639,Male,disloyal Customer,28,Business travel,Business,480,1,1,1,3,1,1,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +5950,65605,Male,disloyal Customer,72,Business travel,Eco,237,2,3,3,4,4,3,3,4,3,3,3,3,3,4,0,8.0,neutral or dissatisfied +5951,62920,Female,Loyal Customer,26,Business travel,Business,3071,2,2,2,2,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +5952,86058,Female,Loyal Customer,49,Business travel,Business,2448,5,5,5,5,2,5,5,4,4,4,4,3,4,4,12,9.0,satisfied +5953,37588,Male,disloyal Customer,18,Business travel,Eco,1005,2,1,1,3,5,1,5,5,1,5,3,2,3,5,59,47.0,neutral or dissatisfied +5954,7573,Male,Loyal Customer,30,Business travel,Business,594,1,1,1,1,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +5955,50494,Female,Loyal Customer,50,Personal Travel,Eco,207,2,3,2,1,4,2,3,3,3,2,3,5,3,4,0,1.0,neutral or dissatisfied +5956,103123,Female,Loyal Customer,55,Personal Travel,Eco,460,3,5,3,4,4,5,5,4,4,3,2,4,4,3,0,0.0,neutral or dissatisfied +5957,97578,Female,Loyal Customer,37,Business travel,Business,448,2,4,4,4,3,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +5958,48278,Female,Loyal Customer,43,Business travel,Eco Plus,391,3,1,1,1,2,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +5959,121483,Male,Loyal Customer,22,Personal Travel,Eco,331,2,4,2,3,2,2,2,2,3,3,5,5,5,2,0,1.0,neutral or dissatisfied +5960,68958,Male,Loyal Customer,51,Business travel,Business,700,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +5961,113016,Male,Loyal Customer,21,Personal Travel,Eco Plus,1751,1,2,1,3,3,1,3,3,1,2,4,1,3,3,19,45.0,neutral or dissatisfied +5962,99982,Male,Loyal Customer,35,Personal Travel,Business,281,2,1,2,2,3,2,2,1,1,2,1,1,1,4,0,6.0,neutral or dissatisfied +5963,7339,Female,Loyal Customer,35,Business travel,Business,2644,4,4,5,4,2,4,5,4,4,4,4,4,4,4,14,0.0,satisfied +5964,72653,Female,Loyal Customer,41,Personal Travel,Eco,1119,4,5,4,2,1,4,1,1,5,3,5,3,4,1,20,41.0,neutral or dissatisfied +5965,105216,Male,Loyal Customer,52,Business travel,Eco,377,2,2,2,2,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +5966,20424,Female,Loyal Customer,37,Personal Travel,Eco,299,1,4,1,2,5,1,3,5,3,2,4,4,4,5,72,72.0,neutral or dissatisfied +5967,96740,Female,Loyal Customer,48,Business travel,Business,1606,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +5968,83029,Male,disloyal Customer,25,Business travel,Business,957,4,0,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +5969,22526,Male,disloyal Customer,30,Business travel,Eco Plus,143,3,3,3,5,5,3,3,5,1,5,1,3,3,5,0,0.0,neutral or dissatisfied +5970,16170,Female,Loyal Customer,51,Business travel,Business,277,3,3,3,3,4,4,1,4,4,4,4,2,4,3,0,0.0,satisfied +5971,127097,Male,Loyal Customer,59,Business travel,Eco,221,4,3,3,3,3,4,3,3,4,2,2,1,2,3,0,0.0,satisfied +5972,15279,Female,Loyal Customer,66,Personal Travel,Eco,460,2,5,2,3,1,3,4,3,3,2,5,2,3,1,1,0.0,neutral or dissatisfied +5973,49612,Male,Loyal Customer,37,Business travel,Business,110,4,4,4,4,5,3,3,4,4,4,4,4,4,4,1,0.0,satisfied +5974,46364,Male,disloyal Customer,29,Business travel,Business,1081,4,4,4,3,2,4,1,2,2,1,2,3,1,2,0,0.0,satisfied +5975,15150,Male,Loyal Customer,55,Personal Travel,Eco,1042,5,1,5,3,4,5,3,4,1,2,4,1,3,4,114,116.0,satisfied +5976,70799,Female,Loyal Customer,42,Personal Travel,Eco,328,3,3,3,3,1,4,3,1,1,3,1,4,1,1,0,1.0,neutral or dissatisfied +5977,30413,Male,Loyal Customer,51,Business travel,Eco Plus,775,2,5,5,5,3,2,3,3,1,5,3,3,4,3,0,1.0,neutral or dissatisfied +5978,65986,Male,Loyal Customer,10,Personal Travel,Eco,1372,4,4,4,3,3,4,1,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +5979,26722,Male,Loyal Customer,25,Business travel,Eco Plus,406,5,1,1,1,5,5,3,5,2,4,3,1,5,5,0,0.0,satisfied +5980,76676,Female,Loyal Customer,49,Personal Travel,Eco,516,3,4,3,3,3,5,4,5,5,3,2,5,5,4,0,0.0,neutral or dissatisfied +5981,6683,Male,Loyal Customer,50,Business travel,Business,3632,3,3,3,3,5,5,5,4,4,4,4,5,4,5,23,26.0,satisfied +5982,114964,Male,Loyal Customer,72,Business travel,Eco,447,1,4,4,4,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +5983,36775,Female,Loyal Customer,54,Business travel,Business,2611,3,2,2,2,3,3,3,3,3,4,4,3,4,3,235,236.0,neutral or dissatisfied +5984,73339,Female,Loyal Customer,43,Business travel,Business,3004,5,5,5,5,5,5,4,5,5,5,5,5,5,3,21,38.0,satisfied +5985,49524,Male,Loyal Customer,39,Business travel,Business,3886,4,1,1,1,3,2,2,4,4,4,4,2,4,4,4,0.0,neutral or dissatisfied +5986,52609,Female,disloyal Customer,27,Business travel,Eco,160,5,0,5,4,2,5,2,2,1,5,5,3,3,2,0,0.0,satisfied +5987,79345,Female,disloyal Customer,23,Business travel,Eco,620,3,1,3,2,4,3,4,4,1,3,1,1,1,4,0,8.0,neutral or dissatisfied +5988,28163,Male,disloyal Customer,30,Business travel,Eco,834,1,1,1,4,1,1,2,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +5989,77762,Female,disloyal Customer,19,Business travel,Eco,696,4,4,4,1,2,4,2,2,5,2,4,1,2,2,1,0.0,satisfied +5990,57640,Male,Loyal Customer,49,Business travel,Business,2719,2,4,4,4,2,1,1,4,4,4,2,2,4,2,0,0.0,neutral or dissatisfied +5991,31167,Male,Loyal Customer,36,Business travel,Business,516,4,4,4,4,2,2,5,5,5,5,5,5,5,2,19,19.0,satisfied +5992,23831,Female,Loyal Customer,66,Personal Travel,Eco,1131,3,4,3,1,2,4,4,2,2,3,2,4,2,3,4,1.0,neutral or dissatisfied +5993,92274,Male,Loyal Customer,56,Business travel,Eco,2036,1,4,4,4,1,1,1,1,2,4,2,2,4,1,0,0.0,neutral or dissatisfied +5994,56052,Male,Loyal Customer,80,Business travel,Business,3263,3,2,2,2,4,4,4,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +5995,113600,Female,Loyal Customer,38,Business travel,Business,236,2,2,2,2,4,5,4,5,5,4,5,5,5,3,8,0.0,satisfied +5996,52657,Male,Loyal Customer,48,Personal Travel,Eco,119,3,4,0,3,5,0,5,5,1,2,5,2,5,5,0,12.0,neutral or dissatisfied +5997,39122,Female,Loyal Customer,42,Business travel,Business,3391,3,3,3,3,2,3,3,4,4,4,3,2,4,4,0,2.0,satisfied +5998,85158,Male,Loyal Customer,26,Business travel,Business,696,5,5,5,5,4,5,4,4,3,2,4,3,5,4,17,7.0,satisfied +5999,87630,Female,disloyal Customer,48,Business travel,Business,606,4,4,4,5,4,4,1,4,5,3,5,3,5,4,0,0.0,satisfied +6000,44147,Female,Loyal Customer,24,Personal Travel,Eco,120,2,4,0,3,4,0,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +6001,51163,Female,Loyal Customer,35,Personal Travel,Eco,190,1,4,1,2,2,1,4,2,3,5,4,4,4,2,48,31.0,neutral or dissatisfied +6002,124532,Male,Loyal Customer,52,Business travel,Business,2168,2,2,2,2,5,5,5,5,5,5,5,4,5,4,0,5.0,satisfied +6003,95122,Male,Loyal Customer,50,Personal Travel,Eco,319,2,2,2,3,1,2,1,1,3,3,3,3,4,1,0,0.0,neutral or dissatisfied +6004,6984,Female,Loyal Customer,49,Business travel,Business,299,0,0,0,5,3,5,4,1,1,1,1,5,1,5,0,4.0,satisfied +6005,115982,Male,Loyal Customer,67,Personal Travel,Eco,333,4,5,2,2,5,2,5,5,5,3,5,3,4,5,74,66.0,neutral or dissatisfied +6006,73568,Male,Loyal Customer,54,Business travel,Business,2312,4,5,5,5,3,3,3,2,2,3,4,1,2,4,0,0.0,neutral or dissatisfied +6007,32572,Male,Loyal Customer,38,Business travel,Eco,101,5,4,4,4,5,5,5,5,4,4,1,1,2,5,0,1.0,satisfied +6008,24632,Female,Loyal Customer,60,Personal Travel,Eco,526,1,4,1,1,3,4,5,2,2,1,2,4,2,5,47,55.0,neutral or dissatisfied +6009,106358,Female,disloyal Customer,27,Business travel,Business,551,2,2,2,1,3,2,1,3,4,2,5,4,5,3,63,63.0,neutral or dissatisfied +6010,128906,Female,Loyal Customer,53,Business travel,Business,2248,5,5,5,5,5,3,5,5,5,5,5,5,5,3,4,0.0,satisfied +6011,15178,Female,disloyal Customer,38,Business travel,Eco,416,3,1,3,4,4,3,3,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +6012,946,Male,Loyal Customer,56,Business travel,Business,140,4,1,1,1,2,3,3,2,2,2,4,3,2,4,15,21.0,neutral or dissatisfied +6013,114650,Female,Loyal Customer,49,Business travel,Business,337,3,3,3,3,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +6014,71719,Female,Loyal Customer,44,Business travel,Business,1990,2,3,3,3,2,3,3,2,2,2,2,1,2,4,99,92.0,neutral or dissatisfied +6015,104318,Female,Loyal Customer,47,Business travel,Eco,409,2,3,3,3,2,3,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +6016,100272,Male,Loyal Customer,24,Business travel,Business,2639,4,4,4,4,5,5,5,5,4,3,4,5,5,5,0,0.0,satisfied +6017,36697,Female,Loyal Customer,66,Personal Travel,Eco,1185,2,4,2,4,3,4,5,4,4,2,4,5,4,4,0,15.0,neutral or dissatisfied +6018,103279,Female,Loyal Customer,21,Personal Travel,Eco Plus,888,2,2,2,2,2,2,2,2,2,5,2,3,3,2,5,0.0,neutral or dissatisfied +6019,31465,Male,Loyal Customer,32,Business travel,Business,2407,4,4,4,4,5,5,5,5,3,2,5,2,2,5,0,0.0,satisfied +6020,120583,Female,Loyal Customer,29,Business travel,Business,980,3,4,5,4,3,4,3,3,4,4,3,4,4,3,9,0.0,neutral or dissatisfied +6021,127912,Male,Loyal Customer,45,Personal Travel,Eco,1671,2,5,2,4,4,2,4,4,1,4,4,2,3,4,1,0.0,neutral or dissatisfied +6022,1599,Male,Loyal Customer,53,Personal Travel,Eco,140,3,1,3,4,4,3,4,4,4,5,3,4,3,4,0,1.0,neutral or dissatisfied +6023,84243,Female,Loyal Customer,16,Personal Travel,Eco Plus,432,3,4,3,1,4,3,4,4,4,5,5,4,5,4,44,48.0,neutral or dissatisfied +6024,31135,Female,Loyal Customer,51,Business travel,Eco,591,3,3,4,3,1,4,4,4,4,3,4,2,4,1,17,30.0,neutral or dissatisfied +6025,100028,Male,disloyal Customer,36,Business travel,Business,289,1,1,1,3,5,1,3,5,4,5,5,4,5,5,1,0.0,neutral or dissatisfied +6026,65259,Male,disloyal Customer,23,Business travel,Eco,190,5,4,5,1,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +6027,45736,Male,Loyal Customer,32,Personal Travel,Eco,1463,3,4,3,3,2,3,2,2,1,4,4,2,3,2,122,125.0,neutral or dissatisfied +6028,82987,Female,Loyal Customer,27,Business travel,Business,3388,3,3,3,3,4,4,4,4,3,5,5,3,4,4,64,43.0,satisfied +6029,1877,Female,disloyal Customer,80,Business travel,Business,531,3,3,3,4,5,3,4,2,2,3,2,2,2,3,0,13.0,neutral or dissatisfied +6030,20994,Male,Loyal Customer,48,Business travel,Eco Plus,689,5,5,5,5,5,5,5,5,4,3,4,1,4,5,10,6.0,satisfied +6031,112742,Female,disloyal Customer,22,Business travel,Eco,697,3,3,3,3,1,3,1,1,1,5,3,1,4,1,38,20.0,neutral or dissatisfied +6032,104836,Female,Loyal Customer,44,Business travel,Business,1520,2,2,2,2,3,2,3,5,5,5,5,1,5,4,102,116.0,satisfied +6033,112939,Female,Loyal Customer,37,Personal Travel,Eco,715,4,3,4,3,3,4,1,3,3,2,2,3,3,3,55,55.0,neutral or dissatisfied +6034,26271,Male,Loyal Customer,55,Business travel,Eco,859,1,5,5,5,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +6035,46410,Male,Loyal Customer,50,Business travel,Business,458,1,1,1,1,1,2,5,5,5,5,5,4,5,1,38,89.0,satisfied +6036,98532,Female,Loyal Customer,64,Personal Travel,Eco,668,3,3,2,1,3,2,4,4,4,2,4,4,4,1,9,1.0,neutral or dissatisfied +6037,123162,Female,Loyal Customer,31,Business travel,Business,1603,2,2,5,2,5,5,5,5,3,3,5,4,5,5,21,27.0,satisfied +6038,49987,Male,disloyal Customer,26,Business travel,Eco,250,4,0,4,4,4,3,3,3,4,3,4,3,2,3,155,153.0,neutral or dissatisfied +6039,13457,Female,Loyal Customer,47,Personal Travel,Eco,475,3,3,3,4,5,3,3,1,1,3,1,2,1,2,20,7.0,neutral or dissatisfied +6040,62772,Male,Loyal Customer,32,Business travel,Business,2556,1,4,4,4,1,1,1,2,1,2,1,1,3,1,0,6.0,neutral or dissatisfied +6041,8487,Male,Loyal Customer,50,Business travel,Business,2370,2,2,5,2,2,4,5,3,3,3,3,4,3,4,0,4.0,satisfied +6042,20428,Female,Loyal Customer,48,Personal Travel,Eco,196,3,5,3,5,2,4,1,3,3,3,3,3,3,5,0,12.0,neutral or dissatisfied +6043,17069,Male,Loyal Customer,28,Business travel,Eco,282,5,1,5,1,5,5,5,5,3,5,1,4,2,5,0,0.0,satisfied +6044,106901,Female,Loyal Customer,61,Personal Travel,Eco,704,2,4,1,5,2,3,5,5,5,1,5,5,5,1,13,2.0,neutral or dissatisfied +6045,29982,Male,Loyal Customer,39,Business travel,Business,213,3,3,3,3,2,2,2,5,5,5,4,5,5,2,0,0.0,satisfied +6046,36849,Female,Loyal Customer,44,Business travel,Eco Plus,369,3,2,2,2,3,3,4,3,3,3,3,4,3,3,21,14.0,neutral or dissatisfied +6047,51902,Male,Loyal Customer,29,Business travel,Business,2334,1,1,2,1,5,4,5,5,2,1,2,3,4,5,0,0.0,satisfied +6048,33488,Female,Loyal Customer,50,Business travel,Business,1930,1,4,2,4,1,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +6049,45088,Female,Loyal Customer,52,Business travel,Eco,299,4,3,3,3,2,2,2,4,4,4,4,2,4,4,6,5.0,neutral or dissatisfied +6050,102574,Female,Loyal Customer,48,Business travel,Business,223,4,4,4,4,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +6051,19203,Female,Loyal Customer,8,Personal Travel,Eco,542,3,2,3,2,4,3,4,4,1,1,1,2,2,4,0,10.0,neutral or dissatisfied +6052,113435,Female,disloyal Customer,26,Business travel,Business,223,4,0,4,1,5,4,2,5,4,5,4,3,4,5,26,11.0,satisfied +6053,123586,Female,Loyal Customer,40,Personal Travel,Eco,1773,2,4,3,1,2,3,4,2,2,3,3,1,2,2,0,3.0,neutral or dissatisfied +6054,8019,Female,disloyal Customer,22,Business travel,Eco,335,4,2,4,3,1,4,1,1,5,4,5,5,4,1,0,0.0,satisfied +6055,101848,Female,Loyal Customer,31,Business travel,Business,519,4,4,4,4,3,4,3,3,3,5,5,5,4,3,0,0.0,satisfied +6056,126127,Male,Loyal Customer,59,Business travel,Business,600,1,1,1,1,3,5,5,5,5,5,5,3,5,3,0,2.0,satisfied +6057,51134,Female,Loyal Customer,12,Personal Travel,Eco,262,1,4,0,2,1,0,1,1,5,1,1,3,4,1,45,48.0,neutral or dissatisfied +6058,97431,Female,Loyal Customer,56,Business travel,Business,3771,3,3,3,3,3,4,4,4,4,4,4,5,4,5,16,0.0,satisfied +6059,49363,Female,Loyal Customer,40,Business travel,Eco,156,4,5,5,5,4,4,4,4,1,2,4,1,4,4,0,0.0,satisfied +6060,30568,Female,Loyal Customer,42,Business travel,Business,628,1,1,1,1,1,2,2,4,4,4,4,3,4,1,57,70.0,satisfied +6061,3201,Male,Loyal Customer,16,Personal Travel,Eco,585,3,5,3,1,4,3,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +6062,28058,Female,Loyal Customer,46,Business travel,Business,2607,1,1,1,1,2,2,2,3,1,3,3,2,4,2,3,0.0,satisfied +6063,69370,Male,Loyal Customer,57,Business travel,Business,3144,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6064,75332,Female,disloyal Customer,29,Business travel,Eco,1071,2,2,2,3,2,5,5,2,2,4,3,5,3,5,0,7.0,neutral or dissatisfied +6065,116884,Female,Loyal Customer,50,Business travel,Business,3595,2,1,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +6066,70606,Male,Loyal Customer,44,Personal Travel,Eco,2611,4,4,4,3,4,4,4,4,2,1,2,4,1,4,0,0.0,neutral or dissatisfied +6067,120862,Female,disloyal Customer,50,Business travel,Business,992,3,3,3,2,2,3,1,2,4,5,4,3,4,2,0,8.0,satisfied +6068,39545,Male,disloyal Customer,20,Business travel,Eco,945,4,4,4,1,4,2,2,5,1,5,2,2,2,2,131,117.0,satisfied +6069,96892,Female,Loyal Customer,54,Personal Travel,Eco,957,1,4,1,2,5,5,5,3,3,1,3,4,3,5,24,30.0,neutral or dissatisfied +6070,65257,Female,Loyal Customer,35,Business travel,Eco Plus,354,3,3,3,3,3,3,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +6071,22714,Female,Loyal Customer,65,Personal Travel,Eco Plus,579,3,4,3,4,2,4,5,4,4,3,2,3,4,3,0,0.0,neutral or dissatisfied +6072,126047,Female,Loyal Customer,44,Business travel,Business,1664,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +6073,85993,Male,disloyal Customer,27,Business travel,Eco,528,2,2,2,3,5,2,5,5,4,2,4,3,4,5,10,16.0,neutral or dissatisfied +6074,93585,Male,Loyal Customer,35,Personal Travel,Eco,159,2,5,2,3,1,2,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +6075,72000,Female,Loyal Customer,57,Personal Travel,Eco,1440,2,4,2,4,4,4,5,3,3,2,3,3,3,4,31,69.0,neutral or dissatisfied +6076,128471,Male,Loyal Customer,31,Personal Travel,Eco,621,2,5,2,1,2,2,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +6077,40380,Male,Loyal Customer,61,Personal Travel,Eco,1250,1,2,2,3,2,2,3,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +6078,53801,Female,Loyal Customer,58,Business travel,Eco,191,5,1,1,1,1,5,3,5,5,5,5,1,5,3,17,4.0,satisfied +6079,777,Female,Loyal Customer,50,Business travel,Business,3623,0,0,0,5,4,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +6080,36520,Male,Loyal Customer,23,Business travel,Eco,1237,0,5,0,5,3,0,3,3,2,4,1,4,3,3,76,69.0,satisfied +6081,26096,Female,Loyal Customer,13,Personal Travel,Eco,591,3,5,3,3,2,3,2,2,2,2,5,1,1,2,0,0.0,neutral or dissatisfied +6082,43099,Female,Loyal Customer,61,Personal Travel,Eco,236,3,4,3,2,3,4,4,2,2,3,2,5,2,3,1,19.0,neutral or dissatisfied +6083,61402,Male,Loyal Customer,13,Personal Travel,Eco,679,1,4,0,3,1,0,1,1,5,3,5,3,4,1,5,10.0,neutral or dissatisfied +6084,79074,Male,Loyal Customer,45,Business travel,Business,356,1,3,3,3,4,4,3,1,1,1,1,4,1,3,11,0.0,neutral or dissatisfied +6085,110545,Male,Loyal Customer,13,Business travel,Business,1752,1,5,5,5,1,1,1,1,2,5,3,3,4,1,15,10.0,neutral or dissatisfied +6086,90258,Female,Loyal Customer,34,Personal Travel,Business,879,2,5,2,4,4,3,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +6087,67721,Male,Loyal Customer,29,Business travel,Eco,1235,4,3,3,3,4,3,4,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +6088,11817,Female,disloyal Customer,19,Business travel,Eco,986,2,2,2,3,2,2,2,2,4,5,5,3,5,2,3,8.0,neutral or dissatisfied +6089,111752,Female,Loyal Customer,47,Business travel,Business,3011,4,2,4,4,5,5,5,5,5,5,5,3,5,4,0,11.0,satisfied +6090,57195,Female,Loyal Customer,39,Business travel,Business,1514,3,3,5,3,5,4,5,4,4,4,4,5,4,4,0,2.0,satisfied +6091,125030,Female,Loyal Customer,19,Personal Travel,Eco Plus,184,3,4,0,3,4,0,4,4,3,4,4,3,5,4,6,44.0,neutral or dissatisfied +6092,30549,Female,disloyal Customer,50,Business travel,Eco,1028,4,3,3,3,1,3,1,1,2,4,3,4,2,1,5,12.0,neutral or dissatisfied +6093,10444,Female,Loyal Customer,52,Business travel,Business,396,5,5,5,5,5,5,5,3,5,4,5,5,3,5,66,139.0,satisfied +6094,90189,Female,Loyal Customer,61,Personal Travel,Eco,983,3,3,4,3,1,4,3,5,5,4,5,4,5,1,1,2.0,neutral or dissatisfied +6095,497,Female,Loyal Customer,41,Business travel,Business,164,1,1,1,1,2,5,5,4,4,4,5,5,4,3,9,0.0,satisfied +6096,53243,Male,Loyal Customer,16,Business travel,Eco Plus,589,4,2,2,2,4,4,5,4,2,4,1,1,2,4,4,1.0,satisfied +6097,119177,Male,Loyal Customer,60,Business travel,Business,3048,2,2,2,2,4,4,4,5,5,5,5,5,5,3,25,37.0,satisfied +6098,113844,Male,Loyal Customer,61,Business travel,Eco,1363,1,3,3,3,1,1,1,1,2,2,2,2,3,1,39,12.0,neutral or dissatisfied +6099,119209,Female,disloyal Customer,18,Business travel,Eco,257,1,3,2,3,3,2,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +6100,84750,Female,disloyal Customer,34,Business travel,Business,481,1,1,1,1,2,1,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +6101,68986,Female,Loyal Customer,32,Personal Travel,Eco,2239,0,5,0,2,5,5,5,5,3,5,4,5,5,5,0,0.0,satisfied +6102,49659,Female,disloyal Customer,24,Business travel,Business,250,5,0,5,2,2,5,2,2,2,5,4,3,5,2,0,0.0,satisfied +6103,40221,Male,Loyal Customer,60,Business travel,Eco,387,2,5,5,5,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +6104,22193,Male,Loyal Customer,36,Business travel,Business,3608,3,3,3,3,1,1,3,4,4,5,4,4,4,2,3,0.0,satisfied +6105,66990,Male,Loyal Customer,47,Business travel,Business,1119,1,1,2,1,5,5,4,4,4,4,4,4,4,5,0,6.0,satisfied +6106,1846,Male,Loyal Customer,13,Personal Travel,Eco,408,5,5,5,2,5,5,5,5,5,5,5,5,5,5,13,1.0,satisfied +6107,26586,Female,Loyal Customer,28,Business travel,Business,2452,2,2,2,2,4,4,4,4,2,5,2,2,4,4,0,0.0,satisfied +6108,27333,Male,Loyal Customer,31,Business travel,Business,1755,1,1,1,1,4,4,4,4,3,5,2,4,1,4,0,17.0,satisfied +6109,81744,Female,Loyal Customer,22,Business travel,Business,3074,1,5,5,5,1,2,1,1,3,2,3,2,3,1,2,0.0,neutral or dissatisfied +6110,33503,Male,Loyal Customer,51,Business travel,Eco,965,3,2,2,2,3,3,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +6111,33989,Male,Loyal Customer,55,Business travel,Eco,1576,1,4,4,4,1,1,1,1,4,4,4,2,4,1,28,2.0,neutral or dissatisfied +6112,6415,Female,Loyal Customer,37,Personal Travel,Eco,315,1,5,1,4,1,1,1,1,2,3,4,3,3,1,0,0.0,neutral or dissatisfied +6113,116290,Male,Loyal Customer,53,Personal Travel,Eco,333,2,4,2,2,1,2,1,1,4,2,2,1,3,1,5,0.0,neutral or dissatisfied +6114,43145,Female,Loyal Customer,10,Personal Travel,Eco Plus,173,2,4,2,3,1,2,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +6115,63412,Male,Loyal Customer,49,Personal Travel,Eco,337,2,5,2,4,3,2,3,3,2,4,2,2,2,3,0,1.0,neutral or dissatisfied +6116,106920,Male,Loyal Customer,39,Business travel,Business,2516,3,3,3,3,1,1,3,5,5,4,5,1,5,1,24,7.0,satisfied +6117,37836,Female,Loyal Customer,50,Business travel,Eco,1065,2,3,3,3,2,5,2,2,2,2,2,2,2,5,42,24.0,satisfied +6118,7279,Female,Loyal Customer,40,Personal Travel,Eco,139,2,0,0,1,0,3,2,4,2,5,5,2,5,2,114,155.0,neutral or dissatisfied +6119,9973,Male,Loyal Customer,31,Personal Travel,Eco,508,1,1,4,3,5,4,5,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +6120,29465,Female,Loyal Customer,39,Personal Travel,Eco,2345,3,4,3,4,4,3,4,4,1,4,4,3,4,4,5,11.0,neutral or dissatisfied +6121,77456,Male,disloyal Customer,24,Business travel,Business,507,4,0,4,3,3,4,2,3,4,2,4,3,5,3,0,0.0,satisfied +6122,42607,Female,Loyal Customer,40,Business travel,Business,2500,1,2,2,2,4,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +6123,78316,Female,Loyal Customer,29,Business travel,Business,1930,5,5,5,5,5,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +6124,36718,Female,Loyal Customer,24,Business travel,Eco Plus,1249,3,2,2,2,3,3,1,3,2,4,3,1,3,3,23,20.0,neutral or dissatisfied +6125,74539,Male,Loyal Customer,26,Business travel,Business,1926,2,3,3,3,2,2,2,2,2,2,3,1,2,2,20,11.0,neutral or dissatisfied +6126,84880,Female,Loyal Customer,12,Personal Travel,Eco,547,2,4,2,3,4,2,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +6127,31503,Male,Loyal Customer,55,Business travel,Eco,846,2,4,4,4,2,2,2,2,4,2,3,2,2,2,16,40.0,neutral or dissatisfied +6128,84648,Female,Loyal Customer,48,Business travel,Business,2657,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +6129,105682,Female,Loyal Customer,46,Business travel,Business,787,1,1,1,1,4,4,5,3,3,4,3,4,3,4,103,118.0,satisfied +6130,44792,Female,Loyal Customer,68,Personal Travel,Eco,1250,3,2,3,2,4,3,2,4,4,3,4,2,4,2,0,29.0,neutral or dissatisfied +6131,72583,Female,disloyal Customer,22,Business travel,Eco,585,5,0,5,3,1,5,1,1,2,4,5,4,5,1,0,0.0,satisfied +6132,65997,Female,disloyal Customer,43,Business travel,Business,1055,4,5,5,2,3,4,2,3,5,4,5,3,5,3,0,9.0,satisfied +6133,116984,Male,Loyal Customer,39,Business travel,Business,2483,1,1,1,1,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +6134,27552,Male,Loyal Customer,21,Personal Travel,Eco,987,3,4,3,3,1,3,2,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +6135,48498,Female,Loyal Customer,41,Business travel,Business,3819,3,3,3,3,5,2,1,5,5,5,5,1,5,2,0,0.0,satisfied +6136,40939,Female,disloyal Customer,27,Business travel,Eco Plus,188,3,3,3,3,1,3,1,1,4,2,4,1,4,1,14,27.0,neutral or dissatisfied +6137,63108,Male,Loyal Customer,18,Personal Travel,Eco Plus,948,1,3,1,3,3,1,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +6138,55664,Male,Loyal Customer,26,Business travel,Business,2607,1,1,1,1,5,5,5,5,3,4,5,4,4,5,42,74.0,satisfied +6139,109593,Female,disloyal Customer,28,Business travel,Eco Plus,994,3,3,3,3,5,3,5,5,3,4,3,1,2,5,4,9.0,neutral or dissatisfied +6140,85168,Female,Loyal Customer,31,Business travel,Business,3702,2,1,1,1,2,3,2,2,1,3,1,3,1,2,2,14.0,neutral or dissatisfied +6141,54378,Male,Loyal Customer,54,Business travel,Eco,305,4,3,3,3,4,4,4,4,3,4,1,1,2,4,36,34.0,satisfied +6142,35195,Male,Loyal Customer,30,Business travel,Business,3602,4,4,4,4,4,4,4,4,1,1,1,1,5,4,78,48.0,satisfied +6143,66429,Male,Loyal Customer,28,Business travel,Business,1562,4,4,2,4,5,5,5,5,5,3,5,3,4,5,0,20.0,satisfied +6144,25525,Female,Loyal Customer,39,Personal Travel,Eco,516,4,5,4,1,5,4,5,5,3,2,4,5,5,5,2,3.0,neutral or dissatisfied +6145,57071,Male,Loyal Customer,52,Business travel,Business,2065,3,3,3,3,5,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +6146,111106,Male,Loyal Customer,56,Business travel,Eco Plus,197,1,2,2,2,1,1,1,1,3,4,4,3,3,1,0,0.0,neutral or dissatisfied +6147,8455,Female,disloyal Customer,39,Business travel,Business,1379,2,2,2,4,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +6148,112716,Female,Loyal Customer,41,Personal Travel,Eco,671,3,3,3,4,1,3,1,1,5,3,2,1,2,1,46,39.0,neutral or dissatisfied +6149,18452,Female,disloyal Customer,23,Business travel,Eco,305,4,0,4,1,5,4,5,5,5,2,3,2,1,5,0,0.0,satisfied +6150,16137,Female,disloyal Customer,10,Business travel,Eco,725,2,2,2,2,2,2,2,2,1,4,3,3,3,2,0,17.0,neutral or dissatisfied +6151,95953,Male,disloyal Customer,47,Business travel,Business,775,2,2,2,4,1,2,1,1,3,4,5,3,4,1,1,0.0,neutral or dissatisfied +6152,36996,Male,Loyal Customer,36,Business travel,Eco,267,4,1,1,1,4,4,4,2,1,1,1,4,3,4,155,151.0,satisfied +6153,8147,Female,Loyal Customer,18,Business travel,Eco,530,1,3,3,3,1,2,4,1,1,3,3,1,4,1,0,23.0,neutral or dissatisfied +6154,102844,Female,Loyal Customer,50,Business travel,Eco,423,1,4,4,4,4,4,4,1,1,1,1,4,1,3,9,0.0,neutral or dissatisfied +6155,73829,Male,Loyal Customer,45,Personal Travel,Eco,1194,4,5,4,3,5,4,5,5,4,5,4,4,4,5,0,6.0,neutral or dissatisfied +6156,101589,Female,Loyal Customer,72,Business travel,Eco Plus,699,1,2,2,2,4,4,3,1,1,1,1,2,1,3,15,15.0,neutral or dissatisfied +6157,13144,Female,Loyal Customer,23,Personal Travel,Eco,595,2,4,2,1,1,2,1,1,1,1,2,4,1,1,0,8.0,neutral or dissatisfied +6158,25609,Female,disloyal Customer,44,Business travel,Eco,666,2,0,3,3,3,3,4,3,1,1,1,3,1,3,26,18.0,neutral or dissatisfied +6159,24235,Female,Loyal Customer,40,Business travel,Business,3932,1,2,2,2,2,1,2,4,4,4,1,3,4,3,96,79.0,neutral or dissatisfied +6160,33082,Female,Loyal Customer,58,Personal Travel,Eco,102,1,5,1,2,1,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +6161,41972,Male,Loyal Customer,51,Personal Travel,Eco,618,1,5,1,1,3,1,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +6162,99963,Male,Loyal Customer,45,Business travel,Business,888,2,2,2,2,4,5,4,4,4,4,4,4,4,5,32,10.0,satisfied +6163,104675,Female,Loyal Customer,15,Personal Travel,Eco,641,3,5,3,3,2,3,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +6164,58452,Female,Loyal Customer,26,Personal Travel,Eco,473,2,2,2,3,5,2,5,5,1,3,2,3,3,5,0,0.0,neutral or dissatisfied +6165,13255,Male,Loyal Customer,55,Business travel,Business,2333,1,3,3,3,4,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +6166,17047,Female,Loyal Customer,48,Business travel,Business,1134,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,7.0,satisfied +6167,88248,Female,Loyal Customer,59,Business travel,Business,270,1,1,1,1,3,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +6168,20062,Male,Loyal Customer,7,Personal Travel,Eco,607,2,5,2,1,5,2,1,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +6169,113655,Female,Loyal Customer,20,Personal Travel,Eco,391,4,4,4,4,2,4,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +6170,3513,Female,Loyal Customer,59,Business travel,Business,557,5,5,5,5,5,5,5,4,4,4,4,3,4,4,24,22.0,satisfied +6171,14376,Female,Loyal Customer,68,Personal Travel,Eco Plus,1215,3,0,3,3,5,3,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +6172,105252,Female,Loyal Customer,51,Business travel,Business,2106,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6173,91963,Male,Loyal Customer,51,Personal Travel,Eco,2475,2,4,2,1,2,2,4,2,3,2,4,5,5,2,0,20.0,neutral or dissatisfied +6174,126075,Female,Loyal Customer,51,Business travel,Business,600,3,3,1,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +6175,110321,Male,Loyal Customer,40,Business travel,Business,2640,3,1,3,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +6176,34400,Male,Loyal Customer,32,Business travel,Eco,612,4,3,3,3,4,4,4,4,1,2,3,1,1,4,0,0.0,satisfied +6177,65206,Male,Loyal Customer,60,Business travel,Business,1880,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +6178,18564,Male,Loyal Customer,66,Business travel,Eco,190,3,2,2,2,3,3,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +6179,124117,Female,Loyal Customer,29,Business travel,Business,529,3,3,3,3,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +6180,67134,Male,disloyal Customer,29,Business travel,Business,929,3,2,2,1,4,2,4,4,5,2,4,4,4,4,0,1.0,neutral or dissatisfied +6181,52426,Male,Loyal Customer,42,Personal Travel,Eco,751,3,4,3,3,1,3,1,1,5,2,1,1,2,1,16,17.0,neutral or dissatisfied +6182,54108,Female,Loyal Customer,50,Business travel,Business,1400,4,4,4,4,3,4,5,5,5,5,5,4,5,4,5,2.0,satisfied +6183,67174,Female,Loyal Customer,64,Personal Travel,Eco,918,3,4,3,5,3,1,1,3,3,3,3,5,3,3,55,60.0,neutral or dissatisfied +6184,1354,Male,Loyal Customer,34,Business travel,Business,282,1,0,0,4,4,3,3,3,3,0,3,2,3,3,0,0.0,neutral or dissatisfied +6185,125459,Male,Loyal Customer,55,Business travel,Business,2860,3,3,3,3,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +6186,109237,Male,Loyal Customer,50,Personal Travel,Eco,655,3,3,3,4,2,3,3,2,1,2,2,3,3,2,33,31.0,neutral or dissatisfied +6187,113167,Male,Loyal Customer,43,Business travel,Business,2399,0,0,0,2,2,5,5,4,4,4,4,3,4,2,6,7.0,satisfied +6188,26031,Male,Loyal Customer,61,Personal Travel,Eco,321,2,3,4,5,4,4,4,4,5,4,1,5,2,4,3,2.0,neutral or dissatisfied +6189,61181,Male,Loyal Customer,22,Business travel,Business,3346,1,1,1,1,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +6190,58319,Male,disloyal Customer,22,Business travel,Eco,822,3,3,3,3,5,3,5,5,1,5,2,2,4,5,35,17.0,neutral or dissatisfied +6191,82114,Female,Loyal Customer,14,Personal Travel,Eco,1298,2,5,2,5,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +6192,30464,Female,Loyal Customer,31,Business travel,Eco,495,4,1,1,1,4,4,4,4,2,5,4,5,3,4,27,19.0,satisfied +6193,128024,Female,Loyal Customer,60,Business travel,Business,1440,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,13.0,satisfied +6194,84345,Male,Loyal Customer,34,Business travel,Business,2436,5,5,5,5,4,4,4,4,4,4,4,5,4,3,17,49.0,satisfied +6195,60416,Male,Loyal Customer,48,Business travel,Business,391,5,5,5,5,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6196,122005,Female,Loyal Customer,59,Business travel,Business,130,2,2,2,2,3,4,4,3,3,4,5,3,3,4,18,23.0,satisfied +6197,50833,Male,Loyal Customer,33,Personal Travel,Eco,109,2,4,2,3,5,2,5,5,5,2,5,5,4,5,46,46.0,neutral or dissatisfied +6198,68621,Male,Loyal Customer,48,Business travel,Business,237,5,5,5,5,3,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +6199,72811,Female,Loyal Customer,39,Business travel,Business,3153,2,2,2,2,5,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +6200,125845,Male,Loyal Customer,56,Business travel,Business,861,4,4,4,4,5,4,5,5,5,5,5,5,5,3,0,1.0,satisfied +6201,31028,Male,Loyal Customer,58,Business travel,Business,2603,4,5,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +6202,95249,Male,Loyal Customer,43,Personal Travel,Eco,239,2,3,0,1,0,5,5,3,4,2,3,5,4,5,158,147.0,neutral or dissatisfied +6203,114708,Female,Loyal Customer,41,Business travel,Business,2369,0,0,0,3,3,5,5,2,2,5,5,4,2,4,0,6.0,satisfied +6204,94362,Female,Loyal Customer,41,Business travel,Business,239,5,5,5,5,2,4,5,5,5,5,5,3,5,4,1,6.0,satisfied +6205,7745,Male,Loyal Customer,48,Business travel,Business,2257,1,1,1,1,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +6206,117328,Female,Loyal Customer,20,Business travel,Eco Plus,370,1,4,4,4,1,1,4,1,4,1,3,1,3,1,43,28.0,neutral or dissatisfied +6207,19995,Female,disloyal Customer,24,Business travel,Eco,646,3,0,3,3,2,3,2,2,4,4,1,5,1,2,96,102.0,neutral or dissatisfied +6208,121091,Male,Loyal Customer,24,Business travel,Business,1558,4,1,1,1,4,4,4,4,4,2,4,1,3,4,0,16.0,neutral or dissatisfied +6209,3753,Male,Loyal Customer,17,Personal Travel,Eco Plus,431,0,4,0,4,1,0,3,1,4,3,5,5,5,1,0,0.0,satisfied +6210,54736,Female,Loyal Customer,66,Personal Travel,Eco,787,2,4,2,1,5,5,4,2,2,2,2,5,2,5,19,12.0,neutral or dissatisfied +6211,50884,Male,Loyal Customer,22,Personal Travel,Eco,209,2,3,2,3,4,2,4,4,1,5,4,3,3,4,0,25.0,neutral or dissatisfied +6212,60867,Male,Loyal Customer,39,Business travel,Business,1491,2,5,5,5,5,3,3,2,2,3,2,1,2,4,12,7.0,neutral or dissatisfied +6213,106564,Female,disloyal Customer,35,Business travel,Eco,1024,4,5,5,3,4,5,4,4,2,5,3,2,4,4,0,17.0,neutral or dissatisfied +6214,90608,Female,disloyal Customer,65,Business travel,Business,442,3,3,3,5,5,3,2,5,5,3,4,5,4,5,18,7.0,neutral or dissatisfied +6215,33608,Female,Loyal Customer,27,Business travel,Business,399,2,2,2,2,2,1,2,2,1,2,2,1,3,2,16,19.0,neutral or dissatisfied +6216,113225,Female,disloyal Customer,38,Business travel,Business,407,4,4,4,4,1,4,5,1,4,2,5,5,4,1,0,0.0,satisfied +6217,97439,Male,disloyal Customer,25,Business travel,Eco,185,1,5,1,3,2,1,2,2,1,2,3,3,4,2,17,17.0,neutral or dissatisfied +6218,3766,Male,Loyal Customer,32,Personal Travel,Business,599,2,3,2,5,3,2,3,3,1,3,4,5,5,3,7,8.0,neutral or dissatisfied +6219,112330,Male,Loyal Customer,50,Business travel,Business,1663,2,2,1,2,5,4,5,2,2,2,2,3,2,3,15,8.0,satisfied +6220,84630,Female,Loyal Customer,53,Personal Travel,Eco,707,3,4,3,2,2,4,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +6221,71661,Female,Loyal Customer,58,Personal Travel,Eco,1197,2,3,2,4,2,4,1,3,3,2,3,5,3,1,5,0.0,neutral or dissatisfied +6222,43865,Male,disloyal Customer,48,Business travel,Eco,174,4,4,5,2,4,5,4,4,1,3,3,3,5,4,0,0.0,neutral or dissatisfied +6223,80130,Female,Loyal Customer,36,Business travel,Business,2586,1,1,1,1,4,4,4,3,3,5,4,4,4,4,0,23.0,satisfied +6224,2030,Female,disloyal Customer,26,Business travel,Eco,733,3,2,2,4,4,2,4,4,1,5,3,2,4,4,0,0.0,neutral or dissatisfied +6225,83762,Female,Loyal Customer,47,Business travel,Business,3610,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,5.0,satisfied +6226,65370,Female,disloyal Customer,34,Business travel,Eco,631,3,1,3,3,2,3,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +6227,15418,Female,Loyal Customer,52,Business travel,Business,377,5,5,5,5,5,2,2,3,3,3,3,3,3,2,0,0.0,satisfied +6228,121606,Male,Loyal Customer,26,Personal Travel,Eco,936,1,4,1,4,2,1,5,2,4,3,4,3,5,2,10,65.0,neutral or dissatisfied +6229,11922,Female,Loyal Customer,33,Personal Travel,Eco,744,1,4,1,2,1,1,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +6230,13437,Female,Loyal Customer,52,Business travel,Business,2328,4,4,4,4,5,4,2,4,4,4,4,4,4,1,0,0.0,satisfied +6231,5639,Male,disloyal Customer,32,Business travel,Business,196,2,2,2,1,1,2,1,1,4,5,5,5,4,1,0,3.0,neutral or dissatisfied +6232,115010,Male,Loyal Customer,50,Business travel,Business,337,2,2,2,2,2,4,5,5,5,5,5,4,5,5,11,0.0,satisfied +6233,1623,Male,Loyal Customer,42,Business travel,Business,2087,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +6234,81493,Female,Loyal Customer,59,Personal Travel,Eco,528,2,3,5,4,2,4,4,5,5,5,5,1,5,1,0,0.0,neutral or dissatisfied +6235,52944,Female,disloyal Customer,29,Business travel,Eco,770,2,2,2,3,5,2,5,5,4,4,1,3,3,5,35,16.0,neutral or dissatisfied +6236,19907,Female,Loyal Customer,46,Business travel,Eco,315,2,2,2,2,5,4,3,2,2,2,2,4,2,2,9,15.0,neutral or dissatisfied +6237,126622,Female,Loyal Customer,44,Business travel,Eco,602,2,5,3,5,1,4,3,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +6238,20799,Male,Loyal Customer,47,Business travel,Business,2555,4,2,5,2,5,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +6239,71649,Male,Loyal Customer,12,Personal Travel,Eco,1197,2,5,2,3,4,2,4,4,3,3,5,4,5,4,6,0.0,neutral or dissatisfied +6240,24226,Female,Loyal Customer,27,Business travel,Business,147,4,4,4,4,4,4,4,4,2,3,2,3,4,4,0,0.0,satisfied +6241,110924,Female,Loyal Customer,59,Personal Travel,Eco,545,3,3,3,5,5,1,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +6242,93332,Male,disloyal Customer,20,Business travel,Business,836,0,4,0,2,1,0,5,1,3,3,4,5,5,1,0,0.0,satisfied +6243,111781,Male,disloyal Customer,30,Business travel,Eco,1137,3,3,3,3,5,3,5,5,4,1,2,3,4,5,0,0.0,neutral or dissatisfied +6244,101064,Male,Loyal Customer,42,Personal Travel,Eco,368,5,5,5,4,4,5,4,4,1,5,1,1,2,4,5,0.0,satisfied +6245,6430,Male,Loyal Customer,32,Personal Travel,Eco,315,1,5,1,4,1,1,1,1,5,4,5,1,1,1,56,49.0,neutral or dissatisfied +6246,4690,Male,Loyal Customer,18,Personal Travel,Eco,364,3,4,3,1,1,3,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +6247,87357,Female,disloyal Customer,23,Business travel,Eco,425,3,2,3,3,3,3,3,3,4,4,3,3,2,3,36,33.0,neutral or dissatisfied +6248,124466,Male,Loyal Customer,64,Personal Travel,Eco,980,1,5,1,2,3,1,3,3,4,2,4,3,5,3,0,9.0,neutral or dissatisfied +6249,43388,Female,Loyal Customer,49,Personal Travel,Eco,463,4,5,4,3,4,4,4,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +6250,128027,Female,Loyal Customer,37,Business travel,Business,1440,2,2,2,2,5,5,4,4,4,4,4,3,4,4,40,20.0,satisfied +6251,50780,Female,Loyal Customer,52,Personal Travel,Eco,250,2,4,2,1,5,5,5,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +6252,29472,Female,Loyal Customer,14,Personal Travel,Business,1107,2,2,2,3,3,2,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +6253,2887,Female,Loyal Customer,12,Personal Travel,Eco,409,4,2,4,2,2,4,2,2,1,3,2,2,2,2,0,0.0,neutral or dissatisfied +6254,53409,Male,Loyal Customer,26,Business travel,Business,2253,5,5,2,5,5,5,5,5,2,3,5,5,4,5,189,191.0,satisfied +6255,25474,Female,Loyal Customer,54,Business travel,Business,481,2,2,2,2,4,3,3,5,5,5,5,5,5,1,0,0.0,satisfied +6256,106958,Female,disloyal Customer,24,Business travel,Business,937,5,0,5,3,2,5,2,2,4,4,4,4,4,2,31,39.0,satisfied +6257,105881,Male,Loyal Customer,43,Business travel,Business,3146,3,3,3,3,2,5,4,4,4,5,4,3,4,4,2,0.0,satisfied +6258,71151,Female,Loyal Customer,36,Business travel,Business,646,4,4,4,4,4,4,5,4,4,5,4,4,4,3,7,0.0,satisfied +6259,101309,Female,Loyal Customer,30,Business travel,Business,3987,4,4,4,4,5,5,5,5,5,4,4,4,5,5,44,42.0,satisfied +6260,21694,Female,Loyal Customer,36,Personal Travel,Eco,746,3,4,3,3,4,3,4,4,3,3,4,4,5,4,0,6.0,neutral or dissatisfied +6261,83814,Female,disloyal Customer,26,Business travel,Eco,425,2,3,2,3,3,2,3,3,1,5,3,3,3,3,0,0.0,neutral or dissatisfied +6262,69548,Female,Loyal Customer,40,Business travel,Business,2475,1,1,1,1,4,4,4,4,2,3,4,4,5,4,14,5.0,satisfied +6263,60344,Female,Loyal Customer,20,Personal Travel,Eco,1024,2,1,2,3,2,2,2,2,4,5,3,2,4,2,0,1.0,neutral or dissatisfied +6264,79325,Female,Loyal Customer,44,Business travel,Business,3447,2,1,2,2,4,4,5,5,5,5,5,5,5,3,0,1.0,satisfied +6265,33230,Male,Loyal Customer,69,Business travel,Eco Plus,163,3,1,4,1,3,3,3,3,4,4,4,1,2,3,2,4.0,satisfied +6266,98131,Female,Loyal Customer,56,Personal Travel,Eco,472,3,5,3,3,3,4,4,4,4,3,4,3,4,4,12,0.0,neutral or dissatisfied +6267,129505,Female,disloyal Customer,37,Business travel,Business,1744,2,2,2,3,1,2,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +6268,44013,Female,Loyal Customer,55,Personal Travel,Eco,397,3,4,3,3,3,4,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +6269,92246,Male,Loyal Customer,27,Business travel,Business,1670,1,1,1,1,5,4,5,5,5,4,3,3,4,5,10,0.0,satisfied +6270,94697,Male,Loyal Customer,22,Business travel,Business,3322,3,4,4,4,3,3,3,3,4,2,3,2,4,3,15,13.0,neutral or dissatisfied +6271,35863,Male,Loyal Customer,63,Personal Travel,Eco,1065,4,4,4,1,2,4,3,2,3,5,5,4,4,2,26,57.0,neutral or dissatisfied +6272,121859,Female,Loyal Customer,57,Business travel,Business,3614,4,4,1,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +6273,89719,Female,Loyal Customer,10,Personal Travel,Eco,1076,5,4,5,3,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +6274,56832,Male,Loyal Customer,61,Personal Travel,Eco,1725,4,5,4,4,2,4,2,2,3,5,3,5,4,2,0,0.0,neutral or dissatisfied +6275,127618,Male,disloyal Customer,43,Business travel,Business,1773,3,3,3,1,2,3,1,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +6276,117162,Male,Loyal Customer,11,Personal Travel,Eco,370,2,0,2,1,1,2,1,1,3,4,3,5,4,1,23,11.0,neutral or dissatisfied +6277,101952,Female,Loyal Customer,56,Business travel,Business,628,4,4,4,4,2,4,5,4,4,4,4,5,4,4,28,13.0,satisfied +6278,21847,Female,disloyal Customer,21,Business travel,Business,448,0,4,0,5,2,0,2,2,5,3,5,3,5,2,0,0.0,satisfied +6279,74910,Female,Loyal Customer,48,Business travel,Business,2475,2,2,2,2,5,5,5,4,5,4,5,5,4,5,27,62.0,satisfied +6280,51025,Male,Loyal Customer,38,Personal Travel,Eco,109,3,3,3,3,4,3,4,4,3,3,4,2,4,4,10,27.0,neutral or dissatisfied +6281,95562,Female,Loyal Customer,61,Personal Travel,Eco Plus,458,4,5,4,2,5,4,4,1,1,4,1,3,1,5,0,0.0,neutral or dissatisfied +6282,100476,Male,disloyal Customer,28,Business travel,Business,580,4,4,4,5,1,4,3,1,5,5,5,5,5,1,37,31.0,satisfied +6283,126492,Female,Loyal Customer,48,Personal Travel,Eco,1788,4,4,4,3,5,5,5,2,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +6284,71343,Male,Loyal Customer,27,Personal Travel,Eco,1671,3,3,3,4,4,3,4,4,2,3,4,4,4,4,35,49.0,neutral or dissatisfied +6285,94937,Female,disloyal Customer,24,Business travel,Eco,189,1,2,2,3,1,2,1,1,4,3,4,3,3,1,3,10.0,neutral or dissatisfied +6286,7687,Female,Loyal Customer,21,Business travel,Eco,604,2,4,4,4,2,2,4,2,4,3,4,4,3,2,0,11.0,neutral or dissatisfied +6287,45479,Female,Loyal Customer,43,Business travel,Business,3603,3,3,3,3,2,2,2,5,5,5,5,4,5,2,0,0.0,satisfied +6288,19848,Female,Loyal Customer,31,Business travel,Eco,693,4,4,4,4,4,4,4,4,1,2,4,3,1,4,0,0.0,satisfied +6289,94266,Male,Loyal Customer,41,Business travel,Business,248,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +6290,73323,Male,Loyal Customer,58,Business travel,Business,1005,5,5,5,5,5,5,5,4,4,4,4,5,4,3,18,0.0,satisfied +6291,118112,Female,Loyal Customer,50,Personal Travel,Eco,1999,4,5,4,5,5,5,4,5,5,4,5,5,5,3,3,0.0,neutral or dissatisfied +6292,77322,Male,Loyal Customer,59,Business travel,Business,626,4,4,4,4,3,4,4,3,3,3,3,3,3,3,5,0.0,satisfied +6293,124567,Male,Loyal Customer,64,Personal Travel,Eco,453,1,4,5,5,3,5,3,3,5,4,5,5,5,3,104,129.0,neutral or dissatisfied +6294,76557,Male,disloyal Customer,10,Business travel,Eco,516,2,2,2,3,1,2,1,1,2,4,2,1,3,1,0,0.0,neutral or dissatisfied +6295,35250,Female,Loyal Customer,47,Business travel,Business,950,4,4,4,4,1,2,1,4,4,4,4,4,4,4,0,0.0,satisfied +6296,2532,Male,Loyal Customer,44,Business travel,Business,304,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +6297,31455,Female,Loyal Customer,27,Personal Travel,Business,862,3,4,3,5,4,3,5,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +6298,92007,Female,Loyal Customer,50,Business travel,Business,1522,4,3,4,4,2,4,4,4,4,4,4,1,4,3,0,16.0,neutral or dissatisfied +6299,101749,Male,Loyal Customer,56,Business travel,Business,1590,2,2,2,2,2,3,4,5,5,5,5,3,5,3,13,0.0,satisfied +6300,65530,Female,Loyal Customer,54,Personal Travel,Eco,1616,1,5,2,5,2,4,4,3,3,2,3,4,3,5,0,8.0,neutral or dissatisfied +6301,21985,Female,Loyal Customer,45,Personal Travel,Eco,448,4,2,4,4,2,4,4,4,4,4,4,2,4,2,0,0.0,satisfied +6302,25409,Female,Loyal Customer,66,Personal Travel,Eco,990,1,4,1,3,2,3,4,2,2,1,2,1,2,4,0,9.0,neutral or dissatisfied +6303,107825,Male,Loyal Customer,67,Personal Travel,Eco,349,2,2,3,4,4,3,4,4,2,2,4,2,3,4,0,0.0,neutral or dissatisfied +6304,26359,Male,Loyal Customer,54,Business travel,Business,828,3,3,3,3,3,5,1,5,5,5,5,2,5,1,0,0.0,satisfied +6305,47181,Female,Loyal Customer,17,Business travel,Business,3465,3,5,5,5,3,3,3,3,2,3,3,3,3,3,16,20.0,neutral or dissatisfied +6306,77700,Female,disloyal Customer,30,Business travel,Eco,689,4,4,4,4,1,4,1,1,1,3,3,3,3,1,22,7.0,neutral or dissatisfied +6307,46402,Female,Loyal Customer,60,Personal Travel,Eco Plus,1013,4,2,4,3,5,2,2,4,4,4,3,4,4,2,7,0.0,satisfied +6308,58676,Male,Loyal Customer,15,Personal Travel,Eco,622,1,5,1,5,5,1,5,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +6309,12739,Male,Loyal Customer,53,Personal Travel,Eco,696,4,5,4,3,4,4,2,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +6310,54395,Female,disloyal Customer,22,Business travel,Business,305,0,5,0,5,2,0,2,2,2,3,4,5,1,2,7,0.0,satisfied +6311,106887,Male,disloyal Customer,11,Business travel,Eco,577,5,0,5,4,3,5,3,3,3,2,4,3,5,3,1,0.0,satisfied +6312,129405,Female,disloyal Customer,38,Business travel,Business,414,5,5,5,4,2,5,2,2,3,5,5,3,4,2,0,0.0,satisfied +6313,72875,Male,disloyal Customer,23,Business travel,Eco,1096,5,5,5,1,5,5,5,5,4,5,5,4,4,5,15,3.0,satisfied +6314,127318,Female,Loyal Customer,20,Personal Travel,Eco,1979,2,3,2,4,4,2,2,4,4,2,4,1,4,4,0,2.0,neutral or dissatisfied +6315,46822,Female,Loyal Customer,33,Business travel,Business,845,1,1,3,1,1,3,1,4,4,4,4,1,4,5,0,0.0,satisfied +6316,31563,Female,Loyal Customer,25,Business travel,Eco Plus,862,5,2,3,2,5,5,5,5,5,4,2,1,3,5,0,0.0,satisfied +6317,101509,Female,Loyal Customer,36,Business travel,Business,3600,0,0,0,5,1,1,5,2,2,2,2,3,2,2,0,0.0,satisfied +6318,39172,Male,Loyal Customer,68,Business travel,Business,2130,5,5,5,5,5,4,5,4,4,4,4,2,4,1,0,0.0,satisfied +6319,123129,Female,Loyal Customer,25,Business travel,Business,1766,1,4,4,4,1,1,1,1,4,4,2,1,3,1,0,9.0,neutral or dissatisfied +6320,12486,Female,Loyal Customer,53,Business travel,Eco Plus,190,5,1,1,1,2,5,3,5,5,5,5,1,5,4,0,0.0,satisfied +6321,13073,Male,Loyal Customer,58,Personal Travel,Eco,936,3,5,3,5,1,3,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +6322,72355,Male,Loyal Customer,26,Personal Travel,Business,964,4,5,4,4,5,4,5,5,4,4,5,5,4,5,0,0.0,satisfied +6323,17228,Male,Loyal Customer,47,Business travel,Eco,872,5,2,2,2,5,5,5,5,5,4,1,5,5,5,7,19.0,satisfied +6324,28775,Female,disloyal Customer,26,Business travel,Business,954,5,5,5,3,5,5,5,5,5,3,4,4,4,5,0,3.0,satisfied +6325,69612,Female,Loyal Customer,15,Personal Travel,Eco,2446,4,2,3,2,3,3,3,3,4,2,2,3,1,3,0,19.0,neutral or dissatisfied +6326,9873,Female,Loyal Customer,50,Business travel,Business,515,5,5,1,5,4,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +6327,15919,Male,disloyal Customer,39,Business travel,Eco,607,2,4,2,1,3,2,3,3,1,3,3,2,5,3,11,25.0,neutral or dissatisfied +6328,127345,Female,Loyal Customer,40,Business travel,Business,3964,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +6329,5492,Female,Loyal Customer,20,Business travel,Business,948,2,1,1,1,2,2,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +6330,109417,Male,Loyal Customer,48,Business travel,Business,861,1,5,5,5,3,2,2,1,1,1,1,1,1,3,16,0.0,neutral or dissatisfied +6331,97540,Female,Loyal Customer,48,Business travel,Business,2947,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +6332,86043,Female,Loyal Customer,23,Personal Travel,Eco,447,2,5,2,1,5,2,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +6333,121555,Male,Loyal Customer,55,Business travel,Eco,912,3,4,5,5,3,4,4,4,5,3,3,4,2,4,170,151.0,neutral or dissatisfied +6334,61251,Male,Loyal Customer,32,Personal Travel,Eco,862,1,5,1,3,5,1,4,5,5,5,4,5,5,5,6,16.0,neutral or dissatisfied +6335,58690,Female,disloyal Customer,80,Business travel,Business,299,2,2,2,3,3,3,4,2,2,2,1,1,2,4,8,23.0,neutral or dissatisfied +6336,39101,Female,disloyal Customer,38,Business travel,Eco,402,1,2,0,3,5,0,3,5,1,4,3,3,4,5,35,25.0,neutral or dissatisfied +6337,97996,Male,Loyal Customer,28,Business travel,Business,483,5,5,5,5,3,3,3,3,3,2,5,4,5,3,28,35.0,satisfied +6338,14381,Male,Loyal Customer,28,Business travel,Business,789,1,2,3,2,1,1,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +6339,114727,Male,Loyal Customer,36,Business travel,Business,390,5,5,5,5,3,4,4,4,4,4,4,3,4,3,68,69.0,satisfied +6340,127191,Male,Loyal Customer,45,Business travel,Business,2884,2,2,3,2,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +6341,93376,Female,Loyal Customer,43,Business travel,Business,2156,5,5,5,5,2,5,4,5,5,4,5,3,5,3,2,0.0,satisfied +6342,10135,Female,Loyal Customer,31,Business travel,Eco Plus,975,3,4,4,4,3,3,3,3,1,2,3,1,2,3,0,0.0,neutral or dissatisfied +6343,51190,Male,Loyal Customer,24,Business travel,Eco Plus,109,1,3,5,3,1,1,2,1,2,2,4,4,3,1,7,7.0,neutral or dissatisfied +6344,57743,Female,Loyal Customer,41,Business travel,Business,2704,1,1,1,1,4,4,4,4,5,5,4,4,3,4,3,0.0,satisfied +6345,115343,Female,disloyal Customer,42,Business travel,Eco,337,2,0,2,4,1,2,1,1,1,2,4,3,4,1,18,8.0,neutral or dissatisfied +6346,92460,Female,Loyal Customer,63,Business travel,Business,1947,3,5,5,5,1,2,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +6347,115151,Male,Loyal Customer,40,Business travel,Business,404,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +6348,21656,Male,Loyal Customer,40,Business travel,Business,3776,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +6349,16562,Male,Loyal Customer,42,Business travel,Eco,872,4,2,2,2,4,4,4,4,4,2,1,3,5,4,37,53.0,satisfied +6350,108616,Male,disloyal Customer,53,Personal Travel,Eco,813,3,4,3,3,5,3,5,5,1,5,4,4,4,5,0,0.0,neutral or dissatisfied +6351,107097,Male,disloyal Customer,28,Business travel,Business,562,1,1,1,5,3,1,4,3,3,4,5,5,4,3,8,0.0,neutral or dissatisfied +6352,50925,Male,Loyal Customer,53,Personal Travel,Eco,77,2,5,2,3,1,2,1,1,5,4,4,4,4,1,28,31.0,neutral or dissatisfied +6353,101577,Female,Loyal Customer,24,Business travel,Business,2763,1,1,1,1,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +6354,90493,Female,disloyal Customer,38,Business travel,Business,444,2,2,2,4,3,2,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +6355,93894,Female,Loyal Customer,67,Personal Travel,Eco,590,1,4,1,5,4,5,4,4,4,1,4,3,4,5,44,45.0,neutral or dissatisfied +6356,42422,Male,Loyal Customer,45,Personal Travel,Eco Plus,817,1,3,1,5,5,1,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +6357,119870,Female,Loyal Customer,36,Personal Travel,Eco,912,2,5,2,3,3,2,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +6358,3007,Male,Loyal Customer,47,Business travel,Business,862,5,2,5,5,4,4,5,5,5,5,5,4,5,5,14,0.0,satisfied +6359,62034,Female,Loyal Customer,50,Business travel,Business,2586,2,3,1,3,3,2,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +6360,97054,Female,Loyal Customer,45,Business travel,Business,3293,5,5,5,5,4,5,4,5,5,5,5,3,5,3,31,16.0,satisfied +6361,108636,Female,disloyal Customer,26,Personal Travel,Eco,1547,2,4,2,2,2,2,2,2,3,5,5,3,5,3,15,0.0,neutral or dissatisfied +6362,21122,Male,Loyal Customer,43,Personal Travel,Eco,152,3,2,3,4,4,3,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +6363,68225,Female,disloyal Customer,34,Business travel,Business,631,1,1,1,5,2,1,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +6364,45433,Male,Loyal Customer,52,Business travel,Business,3690,2,4,4,4,3,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +6365,20661,Female,Loyal Customer,31,Business travel,Business,552,4,4,4,4,5,5,5,5,3,1,1,1,1,5,35,34.0,satisfied +6366,58142,Female,disloyal Customer,26,Business travel,Business,925,3,3,3,3,3,3,3,3,2,2,3,1,4,3,2,0.0,neutral or dissatisfied +6367,26824,Male,Loyal Customer,57,Business travel,Eco,224,5,4,4,4,5,5,5,5,2,5,2,2,2,5,13,7.0,satisfied +6368,57336,Male,disloyal Customer,37,Business travel,Eco,414,3,1,3,4,5,3,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +6369,8090,Female,Loyal Customer,39,Business travel,Business,3446,3,3,3,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +6370,52743,Male,Loyal Customer,53,Business travel,Business,2306,1,5,5,5,5,1,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +6371,116983,Male,Loyal Customer,50,Business travel,Business,2522,0,0,0,1,4,4,4,2,2,2,2,4,2,4,5,0.0,satisfied +6372,16419,Female,disloyal Customer,25,Business travel,Eco,529,3,0,3,5,1,3,1,1,5,1,2,1,4,1,0,0.0,neutral or dissatisfied +6373,4490,Male,Loyal Customer,43,Personal Travel,Business,551,4,4,4,3,4,4,1,4,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +6374,126559,Male,Loyal Customer,56,Business travel,Business,1558,1,1,3,1,2,4,4,4,4,4,4,5,4,5,33,18.0,satisfied +6375,55451,Male,Loyal Customer,28,Personal Travel,Eco Plus,2521,4,4,5,1,5,5,5,5,2,5,5,5,3,5,6,0.0,neutral or dissatisfied +6376,38978,Female,Loyal Customer,47,Business travel,Business,313,1,1,1,1,4,1,1,5,5,5,5,2,5,1,0,0.0,satisfied +6377,90234,Male,Loyal Customer,50,Personal Travel,Eco Plus,1084,1,4,1,4,3,1,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +6378,116919,Male,disloyal Customer,36,Business travel,Business,338,3,3,3,1,3,3,3,3,4,3,4,5,5,3,1,0.0,neutral or dissatisfied +6379,98271,Female,disloyal Customer,25,Business travel,Eco,1072,1,1,1,4,4,1,3,4,4,3,3,4,3,4,10,0.0,neutral or dissatisfied +6380,112949,Male,Loyal Customer,29,Personal Travel,Eco,1390,3,4,3,2,1,3,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +6381,51511,Female,Loyal Customer,38,Business travel,Business,3062,5,5,5,5,2,1,3,5,5,4,5,2,5,1,0,0.0,satisfied +6382,15101,Female,Loyal Customer,28,Personal Travel,Eco,224,1,4,1,2,5,1,2,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +6383,66756,Female,disloyal Customer,22,Personal Travel,Eco,802,2,4,1,2,3,1,3,3,2,4,3,3,2,3,11,0.0,neutral or dissatisfied +6384,86513,Male,Loyal Customer,8,Personal Travel,Eco,762,3,4,3,3,5,3,5,5,3,2,5,4,4,5,10,0.0,neutral or dissatisfied +6385,45084,Male,Loyal Customer,48,Business travel,Eco,196,4,1,1,1,4,4,4,4,1,5,4,2,4,4,1,0.0,neutral or dissatisfied +6386,74108,Female,Loyal Customer,42,Business travel,Business,1736,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,16.0,satisfied +6387,33239,Male,Loyal Customer,60,Business travel,Eco Plus,216,4,5,5,5,3,4,3,3,1,1,5,1,2,3,2,4.0,satisfied +6388,106192,Female,Loyal Customer,55,Personal Travel,Eco,302,1,5,1,3,1,2,2,1,1,1,1,2,1,2,63,60.0,neutral or dissatisfied +6389,99825,Female,Loyal Customer,60,Business travel,Business,1555,5,5,5,5,5,5,5,3,2,5,5,5,3,5,223,212.0,satisfied +6390,77578,Male,Loyal Customer,52,Business travel,Business,3309,1,3,3,3,1,3,4,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +6391,69779,Female,Loyal Customer,41,Business travel,Business,1792,4,4,4,4,2,5,5,4,4,4,4,4,4,5,8,3.0,satisfied +6392,76830,Male,Loyal Customer,29,Business travel,Eco,1851,3,3,3,3,3,3,3,3,4,1,2,3,4,3,0,0.0,neutral or dissatisfied +6393,117570,Female,disloyal Customer,21,Business travel,Business,843,5,0,5,2,5,5,5,5,3,3,5,4,5,5,0,2.0,satisfied +6394,94830,Male,Loyal Customer,46,Business travel,Eco,189,2,1,1,1,2,2,2,2,1,4,2,2,2,2,12,7.0,neutral or dissatisfied +6395,5414,Male,Loyal Customer,57,Business travel,Business,2653,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +6396,43722,Male,Loyal Customer,66,Personal Travel,Eco,489,1,2,1,4,4,1,4,4,1,2,4,2,3,4,79,62.0,neutral or dissatisfied +6397,125128,Male,Loyal Customer,29,Personal Travel,Eco,361,4,3,4,3,3,4,3,3,4,1,3,2,4,3,0,45.0,satisfied +6398,71981,Male,Loyal Customer,30,Business travel,Business,1440,1,1,1,1,4,4,4,4,1,5,1,4,4,4,54,41.0,satisfied +6399,30724,Female,disloyal Customer,46,Business travel,Business,1062,3,3,3,3,2,3,2,2,4,3,5,4,5,2,0,2.0,neutral or dissatisfied +6400,59725,Male,Loyal Customer,32,Business travel,Eco Plus,956,4,5,1,5,4,4,4,4,3,1,2,4,2,4,163,155.0,satisfied +6401,125344,Female,Loyal Customer,51,Business travel,Business,2800,3,3,3,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +6402,55020,Male,Loyal Customer,57,Business travel,Business,1346,3,3,3,3,3,4,4,5,5,5,5,3,5,5,5,0.0,satisfied +6403,108750,Female,Loyal Customer,40,Business travel,Business,404,2,2,2,2,5,5,4,4,4,4,4,5,4,3,0,8.0,satisfied +6404,94360,Male,Loyal Customer,56,Business travel,Business,293,0,0,0,1,2,4,4,3,3,3,3,5,3,4,4,0.0,satisfied +6405,67094,Male,Loyal Customer,23,Business travel,Business,2043,1,0,0,4,1,0,1,1,2,4,3,2,4,1,14,7.0,neutral or dissatisfied +6406,42713,Female,Loyal Customer,25,Business travel,Eco Plus,627,1,3,3,3,1,1,4,1,1,4,4,4,3,1,81,112.0,neutral or dissatisfied +6407,86978,Female,Loyal Customer,42,Business travel,Business,907,5,5,5,5,4,5,5,4,4,4,4,5,4,4,7,4.0,satisfied +6408,46065,Female,Loyal Customer,41,Business travel,Business,1883,1,1,1,1,4,5,4,5,5,5,5,4,5,4,31,53.0,satisfied +6409,21828,Female,Loyal Customer,59,Business travel,Eco,640,3,5,5,5,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +6410,2228,Male,Loyal Customer,15,Business travel,Business,1917,4,4,4,4,3,3,3,3,3,4,4,5,5,3,0,0.0,satisfied +6411,106998,Female,Loyal Customer,20,Personal Travel,Eco,937,1,3,1,4,1,1,1,1,3,4,3,5,4,1,15,9.0,neutral or dissatisfied +6412,109913,Male,Loyal Customer,36,Business travel,Business,804,2,2,2,2,4,3,5,4,4,4,4,2,4,3,14,0.0,satisfied +6413,24288,Female,Loyal Customer,53,Personal Travel,Eco,302,4,4,3,1,4,5,5,2,2,3,1,4,2,5,0,8.0,neutral or dissatisfied +6414,16533,Female,Loyal Customer,67,Personal Travel,Eco,209,2,2,2,3,2,2,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +6415,19401,Male,Loyal Customer,43,Business travel,Business,2912,1,1,1,1,5,5,3,4,4,4,4,2,4,4,0,0.0,satisfied +6416,58226,Female,Loyal Customer,31,Personal Travel,Eco,925,2,3,2,4,2,2,2,2,2,3,4,1,4,2,46,52.0,neutral or dissatisfied +6417,81768,Male,disloyal Customer,24,Business travel,Eco,1416,5,5,5,4,1,5,1,1,3,4,5,5,5,1,0,0.0,satisfied +6418,100260,Female,Loyal Customer,59,Business travel,Business,971,3,3,3,3,3,5,5,4,4,4,4,5,4,3,115,93.0,satisfied +6419,124082,Female,Loyal Customer,34,Business travel,Business,1617,2,2,2,2,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +6420,114271,Male,disloyal Customer,47,Business travel,Eco,446,1,1,1,4,4,1,5,4,4,1,3,3,4,4,4,0.0,neutral or dissatisfied +6421,34278,Female,Loyal Customer,35,Business travel,Eco,496,4,1,1,1,4,4,4,4,4,4,3,2,3,4,39,34.0,neutral or dissatisfied +6422,69393,Male,disloyal Customer,24,Business travel,Eco,1096,2,1,1,3,2,1,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +6423,83949,Male,Loyal Customer,44,Business travel,Business,373,1,1,4,1,4,4,4,3,5,5,5,4,4,4,180,182.0,satisfied +6424,73200,Female,Loyal Customer,15,Personal Travel,Eco,1258,4,5,4,2,2,4,1,2,4,3,4,3,5,2,0,6.0,neutral or dissatisfied +6425,115256,Male,disloyal Customer,44,Business travel,Business,417,5,5,5,1,5,5,4,5,4,5,5,5,4,5,0,2.0,satisfied +6426,28116,Female,Loyal Customer,46,Business travel,Business,3069,1,1,5,1,5,5,3,4,4,5,4,3,4,1,0,0.0,satisfied +6427,8299,Male,disloyal Customer,37,Business travel,Business,294,4,5,5,3,1,5,1,1,4,4,4,4,4,1,0,0.0,satisfied +6428,16210,Female,Loyal Customer,43,Personal Travel,Eco,277,4,1,4,3,5,2,3,2,2,4,2,2,2,2,0,0.0,neutral or dissatisfied +6429,44065,Male,Loyal Customer,29,Personal Travel,Eco,610,2,4,2,4,3,2,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +6430,63239,Female,Loyal Customer,28,Business travel,Business,2444,2,2,2,2,3,4,3,3,5,2,4,3,5,3,0,0.0,satisfied +6431,57277,Female,Loyal Customer,47,Personal Travel,Eco,804,2,5,2,2,1,2,2,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +6432,3156,Female,Loyal Customer,58,Business travel,Business,1700,5,5,5,5,4,5,5,5,5,5,5,3,5,3,6,6.0,satisfied +6433,63884,Female,Loyal Customer,59,Business travel,Business,2608,1,3,3,3,5,3,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +6434,50441,Female,Loyal Customer,54,Business travel,Eco,250,4,5,5,5,3,3,5,4,4,4,4,5,4,4,0,0.0,satisfied +6435,118865,Male,Loyal Customer,56,Personal Travel,Eco Plus,338,3,4,3,5,4,3,4,4,4,3,5,5,5,4,43,44.0,neutral or dissatisfied +6436,105792,Male,Loyal Customer,67,Personal Travel,Eco,883,5,3,5,3,3,5,3,3,3,5,3,1,4,3,12,3.0,satisfied +6437,74735,Male,Loyal Customer,41,Personal Travel,Eco,1205,2,5,2,4,4,2,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +6438,97729,Female,Loyal Customer,40,Business travel,Business,587,5,5,3,5,5,4,4,5,5,5,5,3,5,5,6,0.0,satisfied +6439,16881,Male,Loyal Customer,29,Business travel,Business,746,2,4,4,4,2,2,2,2,4,5,2,3,3,2,0,0.0,neutral or dissatisfied +6440,35470,Male,Loyal Customer,47,Personal Travel,Eco,1102,3,1,3,3,4,3,4,4,2,4,3,1,3,4,0,0.0,neutral or dissatisfied +6441,53950,Male,Loyal Customer,43,Business travel,Business,1325,3,3,3,3,5,5,5,5,5,4,5,2,5,2,35,20.0,satisfied +6442,58344,Female,Loyal Customer,76,Business travel,Eco,296,2,2,2,2,2,3,3,2,2,2,2,2,2,1,48,50.0,neutral or dissatisfied +6443,77630,Male,Loyal Customer,57,Business travel,Business,731,5,5,4,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +6444,119902,Male,Loyal Customer,37,Business travel,Eco Plus,936,3,5,2,5,3,3,3,3,3,1,3,3,4,3,2,10.0,neutral or dissatisfied +6445,109860,Male,Loyal Customer,41,Business travel,Eco,1053,3,3,3,3,3,3,3,3,1,3,3,4,4,3,2,0.0,neutral or dissatisfied +6446,121131,Female,Loyal Customer,52,Business travel,Eco,2370,4,2,2,2,4,4,4,2,3,2,4,4,2,4,0,0.0,neutral or dissatisfied +6447,124311,Female,disloyal Customer,11,Business travel,Business,601,5,5,5,4,1,5,1,1,5,5,4,5,5,1,0,0.0,satisfied +6448,76023,Female,disloyal Customer,21,Business travel,Eco,237,2,1,1,3,3,1,3,3,3,5,2,4,2,3,8,6.0,neutral or dissatisfied +6449,97067,Female,disloyal Customer,24,Business travel,Eco,1129,3,3,3,1,5,3,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +6450,56937,Female,disloyal Customer,62,Business travel,Eco,1408,2,2,2,3,2,2,3,1,3,2,3,3,4,3,2,15.0,neutral or dissatisfied +6451,127389,Male,Loyal Customer,59,Business travel,Business,868,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +6452,109050,Male,disloyal Customer,27,Business travel,Eco,849,3,3,3,2,5,3,5,5,3,1,3,1,2,5,10,6.0,neutral or dissatisfied +6453,78394,Male,Loyal Customer,49,Personal Travel,Eco,726,3,2,3,3,5,3,5,5,4,3,3,1,3,5,127,128.0,neutral or dissatisfied +6454,67609,Female,Loyal Customer,21,Business travel,Business,1464,3,3,3,3,2,2,2,2,3,2,5,3,5,2,0,0.0,satisfied +6455,54948,Female,Loyal Customer,9,Personal Travel,Business,1379,2,4,1,3,2,1,2,2,5,1,1,2,1,2,23,17.0,neutral or dissatisfied +6456,118976,Male,Loyal Customer,53,Business travel,Business,570,5,5,5,5,3,5,4,3,3,3,3,4,3,3,4,6.0,satisfied +6457,40326,Female,Loyal Customer,35,Business travel,Eco Plus,463,3,1,3,1,3,3,3,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +6458,92439,Female,Loyal Customer,52,Business travel,Business,1919,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,1.0,satisfied +6459,110287,Male,Loyal Customer,30,Business travel,Business,1618,3,3,5,3,5,5,5,5,3,4,4,5,5,5,34,38.0,satisfied +6460,113151,Female,disloyal Customer,8,Business travel,Eco,677,3,3,3,3,4,3,4,4,3,3,3,2,3,4,0,1.0,neutral or dissatisfied +6461,73008,Female,Loyal Customer,31,Personal Travel,Eco,1096,3,4,3,4,3,3,3,3,4,1,3,1,3,3,1,0.0,neutral or dissatisfied +6462,91674,Female,Loyal Customer,25,Personal Travel,Eco,954,3,5,3,5,1,3,2,1,5,3,4,5,5,1,1,11.0,neutral or dissatisfied +6463,17987,Male,Loyal Customer,36,Business travel,Business,332,0,0,0,1,2,2,1,2,2,2,2,3,2,5,0,0.0,satisfied +6464,2675,Female,Loyal Customer,24,Personal Travel,Eco,622,2,5,2,2,4,2,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +6465,100845,Female,Loyal Customer,39,Personal Travel,Eco,711,2,5,2,4,2,2,2,2,3,3,1,5,4,2,0,0.0,neutral or dissatisfied +6466,47328,Female,Loyal Customer,33,Business travel,Business,599,2,2,2,2,4,1,1,3,3,3,3,3,3,5,53,51.0,satisfied +6467,70566,Male,disloyal Customer,38,Business travel,Eco,858,1,1,1,1,1,1,1,1,4,5,5,4,2,1,0,0.0,neutral or dissatisfied +6468,11634,Male,Loyal Customer,41,Business travel,Business,2079,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,3.0,satisfied +6469,27230,Male,Loyal Customer,30,Business travel,Business,1839,2,1,1,1,2,2,2,2,3,2,3,2,4,2,0,2.0,neutral or dissatisfied +6470,91160,Female,Loyal Customer,40,Personal Travel,Eco,581,4,4,4,3,4,4,5,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +6471,55924,Male,Loyal Customer,55,Personal Travel,Eco,733,4,5,4,2,5,4,5,5,3,3,4,5,4,5,4,1.0,neutral or dissatisfied +6472,16970,Male,Loyal Customer,9,Personal Travel,Eco Plus,195,3,3,3,4,4,3,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +6473,47228,Female,Loyal Customer,28,Business travel,Eco Plus,908,5,3,5,3,5,5,5,5,5,2,4,4,3,5,0,0.0,satisfied +6474,92064,Female,Loyal Customer,46,Business travel,Business,1517,5,5,5,5,2,5,5,4,4,4,4,4,4,4,2,0.0,satisfied +6475,111248,Female,Loyal Customer,56,Business travel,Business,1849,1,1,1,1,3,5,5,5,5,5,5,3,5,4,11,0.0,satisfied +6476,83306,Female,Loyal Customer,38,Personal Travel,Eco Plus,2079,3,2,3,3,4,3,4,4,3,5,4,1,4,4,0,22.0,neutral or dissatisfied +6477,119831,Male,Loyal Customer,40,Business travel,Business,3365,2,2,2,2,5,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +6478,104867,Male,Loyal Customer,56,Business travel,Business,1784,4,4,4,4,1,3,3,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +6479,97840,Female,Loyal Customer,70,Personal Travel,Eco,395,2,5,2,1,5,3,2,1,1,2,1,5,1,5,13,5.0,neutral or dissatisfied +6480,125277,Male,Loyal Customer,31,Business travel,Business,1874,3,3,3,3,5,5,5,5,4,5,4,4,4,5,19,20.0,satisfied +6481,37199,Female,Loyal Customer,52,Personal Travel,Eco Plus,1189,3,4,2,3,4,3,4,1,1,2,1,3,1,5,26,15.0,neutral or dissatisfied +6482,38883,Female,Loyal Customer,62,Business travel,Business,3486,2,4,4,4,3,3,3,2,2,3,2,1,2,4,12,9.0,neutral or dissatisfied +6483,107994,Male,Loyal Customer,71,Business travel,Eco,271,4,3,3,3,4,4,4,4,1,1,3,4,3,4,23,6.0,neutral or dissatisfied +6484,114013,Male,Loyal Customer,35,Personal Travel,Eco,1844,2,4,2,4,1,2,1,1,3,2,3,3,5,1,29,11.0,neutral or dissatisfied +6485,24114,Male,Loyal Customer,46,Business travel,Business,779,4,5,5,5,2,3,4,4,4,4,4,2,4,3,5,14.0,neutral or dissatisfied +6486,48156,Male,Loyal Customer,72,Business travel,Business,3196,2,5,5,5,1,4,4,2,2,2,2,1,2,4,4,3.0,neutral or dissatisfied +6487,60632,Male,Loyal Customer,54,Business travel,Business,1620,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +6488,119290,Male,Loyal Customer,44,Business travel,Business,1913,5,5,5,5,5,5,5,4,4,5,5,3,4,4,0,14.0,satisfied +6489,24333,Male,Loyal Customer,60,Business travel,Business,3849,2,2,2,2,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +6490,91788,Male,Loyal Customer,16,Personal Travel,Eco,590,4,5,4,2,3,4,3,3,1,4,2,3,2,3,0,0.0,neutral or dissatisfied +6491,1854,Male,Loyal Customer,24,Personal Travel,Business,931,4,4,4,5,2,4,2,2,5,4,5,4,4,2,0,42.0,neutral or dissatisfied +6492,99520,Male,Loyal Customer,16,Business travel,Eco Plus,307,2,2,2,2,2,2,2,2,4,2,4,3,3,2,9,9.0,neutral or dissatisfied +6493,50570,Female,Loyal Customer,49,Personal Travel,Eco,89,4,3,4,4,1,4,4,3,3,4,3,1,3,3,22,13.0,neutral or dissatisfied +6494,29144,Male,Loyal Customer,14,Personal Travel,Eco,937,1,2,1,3,5,1,5,5,2,4,3,3,4,5,0,0.0,neutral or dissatisfied +6495,62263,Female,disloyal Customer,22,Business travel,Business,2565,2,2,2,4,5,2,5,5,2,5,3,4,3,5,0,0.0,neutral or dissatisfied +6496,110245,Male,Loyal Customer,33,Personal Travel,Eco,1011,4,5,4,5,4,4,4,4,1,3,4,1,4,4,67,63.0,satisfied +6497,61958,Female,Loyal Customer,48,Personal Travel,Eco,2161,4,5,3,3,4,5,4,3,3,3,5,4,3,4,0,0.0,satisfied +6498,51453,Female,Loyal Customer,41,Personal Travel,Eco Plus,262,3,1,0,2,4,2,3,2,2,0,2,1,2,2,0,0.0,neutral or dissatisfied +6499,54990,Male,disloyal Customer,28,Business travel,Business,1635,4,5,5,1,4,5,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +6500,2321,Female,Loyal Customer,20,Personal Travel,Eco,672,2,3,2,3,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +6501,57632,Male,Loyal Customer,60,Business travel,Business,200,5,5,5,5,3,5,4,5,5,4,4,5,5,4,0,0.0,satisfied +6502,15350,Female,disloyal Customer,33,Business travel,Business,399,2,2,2,1,5,2,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +6503,56347,Male,Loyal Customer,37,Business travel,Business,1645,2,1,1,1,3,4,3,3,3,3,2,2,3,2,19,37.0,neutral or dissatisfied +6504,104076,Male,Loyal Customer,22,Personal Travel,Eco,359,1,2,1,4,2,1,3,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +6505,115929,Male,Loyal Customer,49,Business travel,Eco,371,5,2,3,3,3,5,3,3,2,4,1,2,3,3,34,30.0,satisfied +6506,77549,Male,Loyal Customer,34,Business travel,Business,3755,5,5,1,5,2,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +6507,51542,Female,disloyal Customer,37,Business travel,Eco,355,1,5,0,2,3,0,3,3,2,5,2,1,1,3,0,0.0,neutral or dissatisfied +6508,56494,Male,Loyal Customer,52,Business travel,Business,3392,1,1,1,1,4,4,4,3,3,3,3,5,3,3,5,1.0,satisfied +6509,78549,Male,Loyal Customer,64,Personal Travel,Eco,666,5,4,5,3,2,5,2,2,1,2,4,1,3,2,0,0.0,satisfied +6510,50567,Female,Loyal Customer,21,Personal Travel,Eco,308,4,3,4,3,5,4,3,5,2,2,3,1,3,5,0,0.0,neutral or dissatisfied +6511,55921,Female,Loyal Customer,26,Personal Travel,Eco,733,3,2,3,4,2,3,2,2,3,1,4,4,3,2,25,16.0,neutral or dissatisfied +6512,28151,Male,disloyal Customer,23,Business travel,Eco,550,3,2,3,4,3,3,3,3,3,2,3,3,4,3,104,110.0,neutral or dissatisfied +6513,59492,Male,Loyal Customer,15,Personal Travel,Eco,901,5,3,5,4,1,5,1,1,4,1,3,3,3,1,0,0.0,satisfied +6514,65950,Male,Loyal Customer,27,Business travel,Business,1372,1,1,4,1,5,5,5,5,5,4,4,4,5,5,2,0.0,satisfied +6515,21933,Female,Loyal Customer,40,Business travel,Business,448,1,1,1,1,4,2,5,4,4,4,4,1,4,4,0,9.0,satisfied +6516,33543,Female,Loyal Customer,26,Personal Travel,Business,399,1,4,1,2,2,1,4,2,3,4,4,4,4,2,10,36.0,neutral or dissatisfied +6517,18637,Female,Loyal Customer,57,Personal Travel,Eco,192,3,5,3,1,2,1,4,1,1,3,1,1,1,3,21,15.0,neutral or dissatisfied +6518,23415,Female,Loyal Customer,30,Business travel,Business,541,2,2,2,2,2,2,2,2,4,4,4,4,4,2,0,12.0,neutral or dissatisfied +6519,73310,Male,Loyal Customer,57,Business travel,Business,1197,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +6520,64191,Male,Loyal Customer,26,Personal Travel,Business,853,3,5,2,4,2,2,5,2,5,5,4,5,5,2,39,49.0,neutral or dissatisfied +6521,48834,Female,Loyal Customer,22,Personal Travel,Business,209,2,1,2,1,1,2,3,1,3,3,2,4,2,1,4,1.0,neutral or dissatisfied +6522,63644,Male,Loyal Customer,42,Personal Travel,Eco,602,2,4,2,2,4,2,4,4,3,2,1,4,2,4,7,1.0,neutral or dissatisfied +6523,122212,Female,disloyal Customer,25,Business travel,Business,541,5,4,5,1,4,5,4,4,3,3,5,4,4,4,0,0.0,satisfied +6524,11252,Female,Loyal Customer,20,Personal Travel,Eco,429,2,3,2,2,4,2,4,4,1,5,5,1,5,4,22,18.0,neutral or dissatisfied +6525,79388,Female,Loyal Customer,34,Business travel,Business,502,5,5,5,5,5,5,4,3,3,4,3,5,3,5,36,12.0,satisfied +6526,43223,Female,Loyal Customer,43,Personal Travel,Eco,423,1,3,1,4,5,5,1,4,4,1,4,5,4,5,0,6.0,neutral or dissatisfied +6527,110548,Female,Loyal Customer,60,Business travel,Business,2005,3,2,3,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +6528,33676,Male,disloyal Customer,21,Business travel,Eco,759,2,2,2,5,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +6529,62150,Male,Loyal Customer,42,Business travel,Eco,2454,2,4,2,4,2,2,2,2,3,3,1,2,3,2,0,0.0,neutral or dissatisfied +6530,24679,Male,Loyal Customer,30,Business travel,Business,2586,4,4,4,4,4,4,4,4,1,3,1,3,2,4,0,2.0,satisfied +6531,78824,Male,Loyal Customer,54,Personal Travel,Eco,447,3,5,3,1,4,3,4,4,2,2,1,2,5,4,0,0.0,neutral or dissatisfied +6532,35891,Female,Loyal Customer,17,Personal Travel,Eco,1068,1,4,1,1,4,1,4,4,3,4,3,2,1,4,0,0.0,neutral or dissatisfied +6533,83800,Male,Loyal Customer,59,Business travel,Business,2148,1,1,1,1,3,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +6534,68762,Female,Loyal Customer,21,Business travel,Business,3340,4,4,4,4,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +6535,93483,Male,Loyal Customer,44,Business travel,Business,3752,2,2,4,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +6536,46308,Female,Loyal Customer,50,Business travel,Eco,1069,4,2,3,2,2,4,4,4,4,4,4,1,4,1,0,0.0,satisfied +6537,108381,Female,Loyal Customer,61,Personal Travel,Eco,1844,2,4,2,2,3,5,5,2,2,2,2,3,2,3,4,0.0,neutral or dissatisfied +6538,38387,Male,Loyal Customer,59,Personal Travel,Eco Plus,1133,2,4,2,3,5,2,4,5,3,3,5,4,5,5,6,0.0,neutral or dissatisfied +6539,27812,Female,disloyal Customer,27,Business travel,Eco,877,4,4,4,4,4,4,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +6540,122054,Female,disloyal Customer,18,Business travel,Eco,130,1,2,1,4,4,1,3,4,1,3,3,4,3,4,34,44.0,neutral or dissatisfied +6541,98621,Male,Loyal Customer,38,Business travel,Business,834,4,1,1,1,1,4,4,4,4,3,4,2,4,1,0,24.0,neutral or dissatisfied +6542,122765,Male,Loyal Customer,13,Personal Travel,Eco Plus,651,3,1,3,2,5,3,5,5,3,1,1,4,2,5,14,10.0,neutral or dissatisfied +6543,9852,Male,Loyal Customer,25,Business travel,Business,3327,2,4,4,4,2,2,2,2,4,4,3,2,4,2,12,24.0,neutral or dissatisfied +6544,11933,Male,disloyal Customer,16,Business travel,Eco,781,3,3,3,5,3,3,3,3,5,2,5,3,4,3,4,3.0,neutral or dissatisfied +6545,122552,Female,Loyal Customer,72,Business travel,Business,500,2,3,3,3,3,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +6546,100397,Female,Loyal Customer,48,Personal Travel,Eco,1034,2,5,2,5,5,1,4,1,1,2,1,1,1,4,0,19.0,neutral or dissatisfied +6547,44764,Male,Loyal Customer,48,Business travel,Business,1250,1,1,1,1,3,5,1,4,4,5,4,5,4,1,51,57.0,satisfied +6548,62429,Female,Loyal Customer,18,Business travel,Business,1670,3,3,3,3,5,5,5,5,4,5,4,1,3,5,0,0.0,satisfied +6549,34055,Male,Loyal Customer,26,Business travel,Eco,1674,4,3,3,3,5,4,4,4,3,4,4,4,5,4,332,321.0,satisfied +6550,121838,Male,disloyal Customer,26,Business travel,Business,449,2,0,2,4,1,2,1,1,4,4,4,3,5,1,1,0.0,neutral or dissatisfied +6551,39407,Female,Loyal Customer,65,Personal Travel,Eco,546,4,4,4,4,5,3,1,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +6552,50792,Female,Loyal Customer,63,Personal Travel,Eco,86,2,4,0,2,2,5,4,5,5,0,3,4,5,5,0,0.0,neutral or dissatisfied +6553,87190,Male,disloyal Customer,9,Business travel,Business,946,5,0,5,3,4,0,4,4,3,4,5,4,4,4,3,0.0,satisfied +6554,79992,Female,Loyal Customer,8,Personal Travel,Eco,1076,2,4,2,4,4,2,4,4,5,3,4,5,5,4,47,27.0,neutral or dissatisfied +6555,60628,Male,Loyal Customer,51,Business travel,Business,1620,1,4,4,4,2,2,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +6556,84111,Female,Loyal Customer,30,Business travel,Business,1900,1,1,1,1,4,4,4,4,5,5,4,4,4,4,8,3.0,satisfied +6557,43898,Female,disloyal Customer,26,Business travel,Eco,114,3,4,3,3,3,3,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +6558,102046,Male,Loyal Customer,57,Business travel,Business,2757,3,4,4,4,5,3,4,3,3,3,3,4,3,4,5,0.0,neutral or dissatisfied +6559,3957,Male,Loyal Customer,44,Business travel,Business,3288,3,3,3,3,5,5,5,4,4,4,4,1,4,4,0,0.0,satisfied +6560,118310,Female,disloyal Customer,18,Business travel,Eco,639,1,0,1,4,2,1,2,2,4,3,4,2,4,2,4,14.0,neutral or dissatisfied +6561,29899,Female,disloyal Customer,40,Business travel,Business,183,2,2,2,2,4,2,3,4,4,4,1,3,2,4,0,0.0,neutral or dissatisfied +6562,15889,Female,Loyal Customer,30,Personal Travel,Eco,332,1,5,1,4,2,1,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +6563,79923,Male,Loyal Customer,54,Business travel,Business,1096,4,4,3,4,5,5,4,4,4,4,4,5,4,5,0,12.0,satisfied +6564,108998,Female,Loyal Customer,41,Business travel,Business,3715,3,3,3,3,2,4,5,5,5,5,5,4,5,3,36,32.0,satisfied +6565,54266,Male,Loyal Customer,19,Personal Travel,Eco,1222,3,3,3,3,1,3,1,1,4,3,4,1,4,1,5,0.0,neutral or dissatisfied +6566,18374,Female,Loyal Customer,19,Personal Travel,Eco,169,4,4,4,4,3,4,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +6567,21544,Female,Loyal Customer,55,Personal Travel,Eco,164,3,4,3,4,3,4,4,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +6568,94420,Male,Loyal Customer,53,Business travel,Business,239,4,4,4,4,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +6569,108130,Male,Loyal Customer,60,Business travel,Business,2273,3,3,3,3,1,4,4,3,3,3,3,3,3,2,22,25.0,neutral or dissatisfied +6570,37087,Male,disloyal Customer,34,Business travel,Business,1046,1,1,1,2,2,1,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +6571,46309,Male,disloyal Customer,36,Business travel,Eco,669,3,3,3,2,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +6572,57577,Male,Loyal Customer,38,Business travel,Eco,1597,1,5,5,5,1,2,1,1,2,2,2,4,3,1,0,0.0,neutral or dissatisfied +6573,64220,Male,Loyal Customer,46,Business travel,Business,1660,3,3,3,3,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +6574,60801,Female,disloyal Customer,27,Business travel,Eco,472,3,2,3,3,1,3,1,1,3,5,3,2,4,1,19,51.0,neutral or dissatisfied +6575,62802,Female,Loyal Customer,57,Personal Travel,Eco,2504,3,4,3,2,5,3,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +6576,36739,Female,Loyal Customer,60,Business travel,Eco,1754,2,4,4,4,1,2,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +6577,90834,Female,Loyal Customer,31,Business travel,Eco,271,4,4,2,4,4,4,4,4,4,3,3,1,2,4,100,91.0,neutral or dissatisfied +6578,76805,Male,Loyal Customer,34,Personal Travel,Eco,689,3,4,3,3,2,3,2,2,1,5,2,1,2,2,5,0.0,neutral or dissatisfied +6579,36887,Female,Loyal Customer,27,Personal Travel,Eco,1182,3,1,3,4,3,3,3,3,3,1,2,2,4,3,0,0.0,neutral or dissatisfied +6580,21093,Female,Loyal Customer,44,Business travel,Business,214,4,5,5,5,1,4,0,4,4,3,3,0,1,0,200,233.0,neutral or dissatisfied +6581,119330,Male,Loyal Customer,48,Personal Travel,Eco,214,3,5,3,3,1,3,1,1,3,2,5,5,4,1,7,0.0,neutral or dissatisfied +6582,1052,Female,Loyal Customer,68,Personal Travel,Eco,134,5,4,5,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +6583,128364,Male,Loyal Customer,49,Business travel,Business,646,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6584,123540,Female,Loyal Customer,51,Business travel,Business,1773,5,2,5,5,2,3,5,4,4,3,4,5,4,5,4,8.0,satisfied +6585,85306,Male,Loyal Customer,50,Personal Travel,Eco,731,3,2,3,2,1,3,1,1,3,3,3,3,2,1,0,0.0,neutral or dissatisfied +6586,40917,Female,Loyal Customer,16,Personal Travel,Eco,532,3,5,3,4,2,3,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +6587,51875,Female,Loyal Customer,22,Business travel,Eco,771,0,4,0,3,3,0,3,3,5,3,5,4,4,3,0,2.0,satisfied +6588,87312,Female,disloyal Customer,27,Business travel,Business,577,5,5,5,2,2,5,2,2,5,5,4,3,4,2,2,0.0,satisfied +6589,129279,Male,Loyal Customer,66,Personal Travel,Eco Plus,2402,3,5,3,4,5,3,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +6590,95607,Female,Loyal Customer,23,Business travel,Eco,670,4,1,1,1,4,3,2,4,3,1,1,1,2,4,15,20.0,neutral or dissatisfied +6591,62244,Female,Loyal Customer,29,Personal Travel,Eco,2425,4,5,4,3,5,4,5,5,3,2,3,5,5,5,0,0.0,neutral or dissatisfied +6592,104616,Male,Loyal Customer,41,Business travel,Business,861,3,3,3,3,5,5,5,5,4,4,5,5,3,5,133,123.0,satisfied +6593,26934,Male,Loyal Customer,25,Personal Travel,Eco Plus,1774,4,5,4,3,1,4,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +6594,107979,Female,Loyal Customer,68,Personal Travel,Eco,825,3,4,3,4,5,4,4,1,1,3,1,3,1,3,14,12.0,neutral or dissatisfied +6595,19859,Male,Loyal Customer,64,Business travel,Business,693,1,1,1,1,1,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +6596,87378,Male,disloyal Customer,40,Business travel,Eco,425,2,1,2,4,4,2,4,4,4,3,4,2,3,4,74,68.0,neutral or dissatisfied +6597,8589,Female,Loyal Customer,55,Personal Travel,Eco,109,2,5,2,4,4,5,5,2,2,2,4,1,2,2,0,0.0,neutral or dissatisfied +6598,98917,Male,disloyal Customer,34,Business travel,Business,543,3,3,3,1,1,3,1,1,5,5,5,5,5,1,36,26.0,neutral or dissatisfied +6599,56768,Female,disloyal Customer,23,Business travel,Eco,1065,4,4,4,3,5,4,5,5,4,2,3,3,4,5,7,0.0,neutral or dissatisfied +6600,2401,Female,disloyal Customer,26,Business travel,Business,767,1,5,1,4,1,1,1,1,5,2,5,5,5,1,8,15.0,neutral or dissatisfied +6601,128719,Male,disloyal Customer,24,Business travel,Eco,1064,2,1,1,4,3,1,3,3,3,2,4,3,4,3,0,14.0,neutral or dissatisfied +6602,116099,Male,Loyal Customer,12,Personal Travel,Eco,373,2,3,2,2,3,2,3,3,4,4,4,2,3,3,1,0.0,neutral or dissatisfied +6603,102032,Male,Loyal Customer,59,Business travel,Business,3262,4,4,4,4,4,5,4,4,4,4,4,5,4,3,2,11.0,satisfied +6604,6576,Male,Loyal Customer,52,Business travel,Business,473,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +6605,50293,Male,disloyal Customer,34,Business travel,Eco,447,2,0,2,4,1,2,1,1,2,2,2,4,3,1,0,0.0,neutral or dissatisfied +6606,10701,Male,disloyal Customer,22,Business travel,Eco,667,1,4,1,4,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +6607,47440,Male,Loyal Customer,30,Business travel,Business,2391,3,3,3,3,3,3,3,3,4,3,3,2,3,3,0,0.0,neutral or dissatisfied +6608,113766,Male,Loyal Customer,28,Personal Travel,Eco,197,4,5,0,2,5,0,5,5,4,5,4,5,5,5,19,11.0,neutral or dissatisfied +6609,14684,Female,Loyal Customer,51,Personal Travel,Business,424,4,3,4,3,4,4,3,4,4,4,4,4,4,2,21,34.0,neutral or dissatisfied +6610,78094,Male,disloyal Customer,23,Business travel,Eco,655,3,5,3,1,2,3,2,2,4,2,4,4,4,2,5,10.0,neutral or dissatisfied +6611,64641,Male,Loyal Customer,44,Business travel,Business,2023,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +6612,4128,Male,Loyal Customer,58,Business travel,Business,431,1,1,1,1,3,4,4,4,4,4,4,3,4,3,2,12.0,satisfied +6613,94240,Female,Loyal Customer,41,Business travel,Business,3496,3,3,3,3,2,4,4,5,5,5,5,3,5,5,35,20.0,satisfied +6614,86764,Male,Loyal Customer,24,Business travel,Business,2753,1,1,3,1,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +6615,72622,Male,Loyal Customer,52,Personal Travel,Eco,1102,2,3,2,4,2,4,4,1,2,4,3,4,3,4,103,137.0,neutral or dissatisfied +6616,45810,Male,disloyal Customer,36,Business travel,Eco,391,2,3,2,3,2,2,2,2,5,5,4,4,3,2,0,0.0,neutral or dissatisfied +6617,9824,Female,Loyal Customer,42,Business travel,Business,3996,2,3,3,3,2,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +6618,33973,Male,Loyal Customer,50,Business travel,Business,1576,5,5,5,5,4,3,3,3,3,3,3,4,3,3,0,0.0,satisfied +6619,44797,Female,Loyal Customer,52,Personal Travel,Eco Plus,1250,4,5,3,1,2,5,5,2,2,3,2,5,2,5,22,34.0,neutral or dissatisfied +6620,87218,Female,Loyal Customer,35,Personal Travel,Eco,946,1,5,0,2,5,0,5,5,2,4,4,1,1,5,0,0.0,neutral or dissatisfied +6621,110865,Male,Loyal Customer,51,Business travel,Business,3276,1,1,1,1,2,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +6622,108587,Male,Loyal Customer,53,Business travel,Business,2149,4,3,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +6623,6928,Female,Loyal Customer,31,Personal Travel,Eco Plus,265,3,4,0,3,1,0,1,1,1,1,3,1,4,1,76,129.0,neutral or dissatisfied +6624,111078,Female,Loyal Customer,56,Personal Travel,Eco,197,2,4,0,5,2,4,5,3,3,0,3,3,3,4,0,0.0,neutral or dissatisfied +6625,18058,Male,disloyal Customer,28,Business travel,Eco,605,3,3,4,3,1,4,1,1,2,3,3,2,3,1,0,0.0,neutral or dissatisfied +6626,31730,Male,Loyal Customer,46,Personal Travel,Eco,862,3,5,3,3,4,3,4,4,2,4,1,2,2,4,1,0.0,neutral or dissatisfied +6627,47427,Female,disloyal Customer,34,Business travel,Eco,590,1,4,1,2,3,1,3,3,3,3,2,3,1,3,0,6.0,neutral or dissatisfied +6628,29639,Male,Loyal Customer,38,Personal Travel,Eco,909,3,4,3,1,3,3,3,3,2,5,2,2,1,3,0,0.0,neutral or dissatisfied +6629,105961,Male,Loyal Customer,36,Business travel,Business,2329,4,1,2,1,4,4,4,4,1,4,4,4,4,4,0,13.0,neutral or dissatisfied +6630,100177,Female,Loyal Customer,58,Personal Travel,Eco,725,1,4,1,3,4,4,4,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +6631,107539,Female,disloyal Customer,23,Business travel,Eco,1360,5,4,4,3,5,5,5,5,3,3,5,3,5,5,35,15.0,satisfied +6632,58345,Female,Loyal Customer,56,Personal Travel,Eco,296,4,4,4,3,2,4,5,5,5,4,5,4,5,3,23,13.0,neutral or dissatisfied +6633,33361,Male,Loyal Customer,35,Business travel,Eco,2556,5,5,5,5,5,5,5,5,4,2,4,1,1,5,0,0.0,satisfied +6634,71200,Female,Loyal Customer,23,Business travel,Business,3679,2,2,2,2,4,4,4,4,5,4,4,3,4,4,23,10.0,satisfied +6635,40983,Female,Loyal Customer,42,Business travel,Eco,984,4,3,3,3,4,5,5,4,4,4,4,5,4,1,56,53.0,satisfied +6636,14563,Male,disloyal Customer,11,Business travel,Business,986,1,4,1,4,4,1,2,4,1,5,3,3,4,4,0,9.0,neutral or dissatisfied +6637,8607,Female,Loyal Customer,54,Personal Travel,Eco Plus,109,3,5,3,3,2,4,4,1,1,3,1,1,1,5,0,0.0,neutral or dissatisfied +6638,7860,Male,Loyal Customer,18,Personal Travel,Business,948,3,3,3,3,4,3,4,4,4,3,1,3,2,4,0,11.0,neutral or dissatisfied +6639,84756,Male,Loyal Customer,30,Business travel,Business,547,3,3,3,3,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +6640,120931,Male,disloyal Customer,25,Business travel,Business,993,1,0,1,1,3,1,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +6641,48340,Female,Loyal Customer,52,Business travel,Eco,674,4,2,2,2,1,5,1,4,4,4,4,4,4,1,33,25.0,satisfied +6642,27138,Female,Loyal Customer,41,Business travel,Business,2677,1,5,1,1,5,4,4,1,4,3,5,4,4,4,4,0.0,satisfied +6643,62992,Male,Loyal Customer,39,Business travel,Business,2503,2,2,2,2,5,5,4,3,3,3,3,5,3,3,10,0.0,satisfied +6644,94239,Female,Loyal Customer,37,Business travel,Business,3484,2,4,4,4,4,3,4,2,2,2,2,3,2,3,0,4.0,neutral or dissatisfied +6645,121872,Female,disloyal Customer,21,Business travel,Eco,366,1,1,1,4,5,1,1,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +6646,15678,Female,disloyal Customer,27,Business travel,Eco,217,2,3,2,4,2,2,3,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +6647,57228,Female,Loyal Customer,38,Personal Travel,Eco,1514,2,3,2,4,5,2,5,5,4,5,3,4,3,5,2,23.0,neutral or dissatisfied +6648,38778,Female,Loyal Customer,36,Business travel,Business,387,3,3,3,3,1,1,4,5,5,5,5,4,5,5,0,0.0,satisfied +6649,71060,Male,Loyal Customer,62,Personal Travel,Eco,802,1,4,1,3,2,1,3,2,2,4,5,4,3,2,0,17.0,neutral or dissatisfied +6650,50382,Male,Loyal Customer,32,Business travel,Business,1552,2,4,4,4,2,2,2,3,2,2,1,2,4,2,108,176.0,neutral or dissatisfied +6651,69313,Male,Loyal Customer,16,Personal Travel,Business,944,3,4,3,4,1,3,1,1,4,5,4,3,3,1,0,6.0,neutral or dissatisfied +6652,67434,Male,Loyal Customer,48,Business travel,Business,592,2,5,5,5,4,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +6653,109042,Female,Loyal Customer,35,Business travel,Business,2897,3,3,4,3,5,5,5,5,5,5,5,3,5,3,1,0.0,satisfied +6654,109375,Female,Loyal Customer,40,Business travel,Business,1237,3,3,3,3,2,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +6655,94099,Male,Loyal Customer,56,Personal Travel,Business,189,1,5,1,2,5,4,4,2,2,1,4,5,2,5,26,15.0,neutral or dissatisfied +6656,1899,Male,Loyal Customer,32,Business travel,Business,2916,4,4,4,4,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +6657,28369,Female,Loyal Customer,31,Business travel,Business,1754,1,3,3,3,1,1,1,1,4,3,2,2,2,1,0,0.0,neutral or dissatisfied +6658,51897,Male,Loyal Customer,54,Business travel,Business,507,1,1,1,1,5,5,4,4,4,5,4,2,4,2,0,0.0,satisfied +6659,40354,Female,Loyal Customer,32,Personal Travel,Eco,1428,1,5,1,1,5,1,5,5,4,2,3,4,5,5,11,5.0,neutral or dissatisfied +6660,19250,Female,Loyal Customer,52,Business travel,Eco Plus,782,5,1,1,1,1,2,4,4,4,5,4,2,4,3,24,17.0,satisfied +6661,68807,Female,Loyal Customer,19,Personal Travel,Eco,926,2,1,2,3,2,2,2,2,4,3,3,1,2,2,0,0.0,neutral or dissatisfied +6662,13009,Male,disloyal Customer,34,Business travel,Eco,438,1,2,1,4,4,1,4,4,1,5,4,4,4,4,91,77.0,neutral or dissatisfied +6663,80162,Male,Loyal Customer,22,Business travel,Business,2446,5,5,2,5,5,4,4,4,2,4,5,4,5,4,0,0.0,satisfied +6664,121548,Female,Loyal Customer,69,Business travel,Business,2221,3,4,4,4,2,4,4,3,3,3,3,4,3,4,14,17.0,neutral or dissatisfied +6665,94191,Female,Loyal Customer,40,Business travel,Business,3052,1,1,1,1,3,4,4,5,5,5,5,5,5,3,9,8.0,satisfied +6666,18579,Male,Loyal Customer,42,Business travel,Business,3311,1,1,1,1,2,1,1,1,1,1,1,1,1,3,0,7.0,neutral or dissatisfied +6667,77453,Male,disloyal Customer,16,Business travel,Eco,507,4,0,4,1,3,4,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +6668,45822,Female,Loyal Customer,61,Personal Travel,Eco,391,2,4,2,5,5,5,5,4,4,2,4,3,4,4,0,27.0,neutral or dissatisfied +6669,1197,Female,Loyal Customer,7,Personal Travel,Eco,309,2,5,2,3,3,2,3,3,3,2,4,1,3,3,58,71.0,neutral or dissatisfied +6670,106299,Male,Loyal Customer,46,Business travel,Business,2500,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +6671,97612,Male,Loyal Customer,41,Business travel,Business,442,1,1,1,1,2,4,4,3,3,3,3,5,3,3,8,7.0,satisfied +6672,1649,Male,Loyal Customer,77,Business travel,Business,1621,4,1,1,1,5,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +6673,3430,Female,Loyal Customer,50,Personal Travel,Eco,315,3,4,3,3,4,5,5,5,5,3,5,5,5,4,54,87.0,neutral or dissatisfied +6674,49752,Female,Loyal Customer,38,Business travel,Business,109,1,1,1,1,1,3,3,5,5,5,5,5,5,2,0,0.0,satisfied +6675,29305,Male,Loyal Customer,41,Personal Travel,Eco,834,5,1,5,1,5,5,5,5,4,4,1,3,1,5,0,0.0,satisfied +6676,80583,Female,Loyal Customer,13,Personal Travel,Eco,1747,2,2,1,2,2,1,2,2,1,4,1,2,1,2,23,3.0,neutral or dissatisfied +6677,94754,Female,Loyal Customer,38,Business travel,Eco,248,3,3,3,3,3,3,3,3,1,1,4,1,3,3,9,9.0,neutral or dissatisfied +6678,58116,Male,Loyal Customer,43,Personal Travel,Eco,612,3,2,3,4,4,3,4,4,2,5,4,3,4,4,16,2.0,neutral or dissatisfied +6679,50378,Female,disloyal Customer,24,Business travel,Eco,373,4,0,4,4,3,4,1,3,2,1,1,4,5,3,0,0.0,satisfied +6680,108762,Female,Loyal Customer,50,Business travel,Business,406,4,4,4,4,3,4,4,4,4,4,4,4,4,4,15,0.0,satisfied +6681,120835,Male,Loyal Customer,59,Business travel,Business,2988,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +6682,84435,Female,Loyal Customer,46,Business travel,Business,1646,1,1,1,1,5,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +6683,44088,Female,Loyal Customer,53,Business travel,Business,473,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +6684,40867,Male,Loyal Customer,37,Personal Travel,Eco,541,2,4,2,3,2,2,2,2,4,3,4,3,4,2,0,9.0,neutral or dissatisfied +6685,91286,Male,Loyal Customer,40,Business travel,Business,2246,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,15.0,satisfied +6686,113149,Female,disloyal Customer,21,Business travel,Business,889,3,3,3,4,5,3,4,5,4,4,4,2,3,5,29,20.0,neutral or dissatisfied +6687,60524,Female,Loyal Customer,36,Personal Travel,Eco,862,2,3,2,3,2,2,3,2,2,2,3,1,2,2,65,49.0,neutral or dissatisfied +6688,127914,Female,disloyal Customer,25,Business travel,Business,1671,3,0,3,2,2,3,2,2,3,2,5,4,4,2,61,52.0,neutral or dissatisfied +6689,46764,Female,Loyal Customer,43,Business travel,Eco Plus,73,2,3,3,3,2,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +6690,75977,Male,disloyal Customer,36,Business travel,Eco,297,1,4,1,3,1,4,4,3,2,4,3,4,4,4,447,433.0,neutral or dissatisfied +6691,85795,Female,disloyal Customer,27,Business travel,Eco,266,1,0,1,4,1,1,4,1,2,3,3,2,4,1,1,20.0,neutral or dissatisfied +6692,57049,Female,Loyal Customer,53,Business travel,Business,2133,3,5,3,3,3,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +6693,39871,Male,Loyal Customer,45,Personal Travel,Eco,221,4,1,4,2,2,4,2,2,2,5,2,2,2,2,0,7.0,satisfied +6694,5666,Male,disloyal Customer,24,Business travel,Eco,436,5,0,5,2,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +6695,95384,Male,Loyal Customer,50,Personal Travel,Eco,248,4,4,4,2,3,4,3,3,4,4,4,3,4,3,11,0.0,neutral or dissatisfied +6696,93077,Female,Loyal Customer,17,Business travel,Business,860,1,1,1,1,5,5,5,5,3,3,5,5,4,5,37,30.0,satisfied +6697,127765,Female,Loyal Customer,68,Personal Travel,Eco,255,3,0,3,1,5,5,4,4,4,3,4,4,4,5,40,33.0,neutral or dissatisfied +6698,60256,Male,Loyal Customer,60,Personal Travel,Eco,1546,3,1,3,3,2,3,2,2,2,5,2,1,4,2,2,16.0,neutral or dissatisfied +6699,53311,Female,Loyal Customer,52,Personal Travel,Eco,758,4,2,4,3,2,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +6700,30556,Female,Loyal Customer,49,Business travel,Business,628,5,5,5,5,3,4,4,2,2,2,2,3,2,3,0,15.0,satisfied +6701,64996,Male,disloyal Customer,24,Business travel,Eco,190,4,0,4,3,2,4,2,2,3,1,2,3,1,2,27,20.0,neutral or dissatisfied +6702,47799,Female,Loyal Customer,51,Business travel,Business,2100,4,4,4,4,5,3,2,2,2,2,2,5,2,2,0,3.0,satisfied +6703,28085,Male,disloyal Customer,29,Business travel,Eco,1385,2,2,2,3,2,2,1,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +6704,7915,Female,disloyal Customer,26,Business travel,Eco,620,4,2,4,2,5,4,5,5,2,4,1,1,2,5,0,0.0,neutral or dissatisfied +6705,18532,Female,Loyal Customer,36,Business travel,Eco,253,5,4,3,4,5,4,5,5,1,2,4,3,5,5,0,0.0,satisfied +6706,87211,Female,Loyal Customer,56,Personal Travel,Eco,946,4,2,4,4,1,3,4,5,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +6707,40277,Male,Loyal Customer,60,Personal Travel,Eco,387,2,4,2,3,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +6708,98386,Female,disloyal Customer,21,Business travel,Eco,1131,1,1,1,3,3,1,4,3,2,2,4,1,4,3,20,8.0,neutral or dissatisfied +6709,74857,Female,Loyal Customer,54,Business travel,Business,1995,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +6710,66016,Male,Loyal Customer,41,Business travel,Business,1055,2,2,5,2,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +6711,37741,Female,Loyal Customer,32,Personal Travel,Eco,1005,3,4,3,3,2,3,2,2,4,3,5,5,4,2,12,16.0,neutral or dissatisfied +6712,14974,Female,disloyal Customer,32,Business travel,Eco,927,2,2,2,4,1,2,1,1,4,1,3,2,4,1,8,19.0,neutral or dissatisfied +6713,23837,Female,Loyal Customer,43,Business travel,Business,2798,5,5,5,5,2,5,5,5,5,5,5,5,5,2,38,24.0,satisfied +6714,34428,Female,Loyal Customer,28,Business travel,Business,680,2,2,2,2,5,5,5,5,1,5,5,3,5,5,0,0.0,satisfied +6715,118860,Male,Loyal Customer,12,Personal Travel,Eco Plus,646,2,2,3,1,5,3,5,5,2,2,1,4,2,5,67,46.0,neutral or dissatisfied +6716,70587,Female,Loyal Customer,40,Business travel,Eco Plus,1258,2,1,1,1,2,2,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +6717,79644,Male,Loyal Customer,52,Business travel,Eco,360,5,1,1,1,4,5,4,4,4,3,1,5,5,4,0,0.0,satisfied +6718,126457,Male,Loyal Customer,23,Business travel,Business,1788,5,5,5,5,4,4,4,4,5,3,3,4,4,4,0,0.0,satisfied +6719,26558,Male,Loyal Customer,47,Business travel,Business,404,5,5,5,5,3,5,5,5,5,5,5,4,5,3,21,19.0,satisfied +6720,79797,Female,Loyal Customer,47,Business travel,Business,1080,3,3,3,3,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +6721,121380,Male,Loyal Customer,54,Business travel,Business,779,4,2,2,2,4,4,3,4,4,3,4,1,4,2,27,30.0,neutral or dissatisfied +6722,1248,Female,Loyal Customer,29,Personal Travel,Eco,89,4,4,4,1,2,4,2,2,5,2,4,3,5,2,29,24.0,neutral or dissatisfied +6723,34685,Female,Loyal Customer,38,Business travel,Business,209,0,4,0,4,5,4,4,4,4,4,3,1,4,3,0,0.0,satisfied +6724,115389,Male,Loyal Customer,43,Business travel,Business,337,3,5,3,5,3,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +6725,13864,Female,Loyal Customer,54,Business travel,Eco,760,4,4,4,4,1,4,2,4,4,4,4,4,4,4,29,38.0,satisfied +6726,43690,Female,Loyal Customer,54,Business travel,Eco,489,4,1,1,1,2,4,5,4,4,4,4,1,4,1,0,0.0,satisfied +6727,7931,Female,Loyal Customer,54,Personal Travel,Eco Plus,864,1,4,1,4,5,4,3,5,5,1,5,4,5,3,29,34.0,neutral or dissatisfied +6728,129496,Male,Loyal Customer,7,Personal Travel,Business,1744,2,5,1,2,2,1,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +6729,60142,Male,Loyal Customer,38,Business travel,Eco,744,2,3,5,5,2,3,2,2,2,1,5,2,1,2,13,21.0,satisfied +6730,77927,Male,Loyal Customer,21,Personal Travel,Business,332,2,4,2,2,3,2,3,3,5,5,5,5,5,3,5,8.0,neutral or dissatisfied +6731,64933,Male,Loyal Customer,37,Business travel,Business,354,2,5,5,5,4,3,3,2,2,2,2,1,2,4,1,4.0,neutral or dissatisfied +6732,105235,Male,Loyal Customer,33,Personal Travel,Eco,377,3,4,3,1,5,3,5,5,5,5,4,4,4,5,10,0.0,neutral or dissatisfied +6733,116113,Male,Loyal Customer,12,Personal Travel,Eco,362,5,5,2,3,4,2,4,4,5,2,4,3,4,4,0,0.0,satisfied +6734,94222,Female,Loyal Customer,46,Business travel,Business,2894,3,3,3,3,4,4,5,4,4,4,4,5,4,5,36,31.0,satisfied +6735,2782,Male,Loyal Customer,49,Business travel,Business,764,3,3,3,3,4,5,4,4,4,4,4,4,4,4,0,10.0,satisfied +6736,65988,Male,Loyal Customer,58,Business travel,Eco Plus,1372,1,0,0,2,4,1,2,4,1,1,2,2,3,4,0,0.0,neutral or dissatisfied +6737,78410,Female,Loyal Customer,20,Business travel,Business,3391,3,1,1,1,3,3,3,3,4,1,4,1,4,3,2,7.0,neutral or dissatisfied +6738,89994,Male,Loyal Customer,40,Business travel,Business,957,4,4,4,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6739,94533,Male,Loyal Customer,59,Business travel,Business,239,5,5,5,5,3,4,5,5,5,5,5,4,5,3,4,7.0,satisfied +6740,91297,Male,Loyal Customer,57,Business travel,Business,271,5,5,5,5,3,4,4,5,5,5,5,4,5,3,6,3.0,satisfied +6741,101895,Male,Loyal Customer,40,Business travel,Business,1984,3,3,3,3,3,4,5,5,5,5,5,4,5,4,12,0.0,satisfied +6742,83452,Male,Loyal Customer,59,Business travel,Business,946,3,3,3,3,5,5,4,4,4,4,4,4,4,4,12,7.0,satisfied +6743,73651,Male,Loyal Customer,31,Business travel,Business,2084,2,1,5,5,3,3,2,3,3,1,4,1,4,3,0,0.0,neutral or dissatisfied +6744,69661,Male,Loyal Customer,32,Business travel,Business,2916,2,2,2,2,5,5,5,3,4,5,4,5,3,5,1305,1280.0,satisfied +6745,51866,Female,Loyal Customer,50,Personal Travel,Eco,552,2,4,2,2,4,4,4,3,3,2,3,4,3,5,1,0.0,neutral or dissatisfied +6746,110398,Male,disloyal Customer,19,Business travel,Eco,883,2,2,2,1,1,2,3,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +6747,94809,Female,disloyal Customer,23,Business travel,Eco,189,4,4,4,3,3,4,3,3,2,3,4,2,4,3,14,17.0,neutral or dissatisfied +6748,63154,Female,Loyal Customer,48,Business travel,Business,2938,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +6749,77002,Female,Loyal Customer,55,Business travel,Business,3608,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +6750,127426,Male,Loyal Customer,21,Personal Travel,Eco,868,1,3,1,3,1,1,1,1,5,4,2,2,4,1,0,0.0,neutral or dissatisfied +6751,127973,Male,Loyal Customer,48,Business travel,Business,1569,2,2,2,2,2,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +6752,47723,Male,Loyal Customer,46,Business travel,Business,2144,2,2,1,2,4,4,4,4,4,4,4,5,4,3,1,0.0,satisfied +6753,109480,Male,Loyal Customer,46,Business travel,Business,3792,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +6754,110145,Female,Loyal Customer,29,Business travel,Business,2264,1,1,1,1,3,3,3,3,3,5,5,3,4,3,0,0.0,satisfied +6755,94613,Female,Loyal Customer,39,Business travel,Business,3327,1,1,1,1,4,4,5,4,4,4,4,3,4,4,75,69.0,satisfied +6756,104877,Female,Loyal Customer,14,Personal Travel,Eco,327,1,1,1,2,1,1,1,1,5,5,5,3,4,1,28,29.0,neutral or dissatisfied +6757,82157,Male,disloyal Customer,30,Business travel,Eco,311,2,1,2,3,2,2,2,2,4,1,2,1,2,2,0,0.0,neutral or dissatisfied +6758,7950,Female,Loyal Customer,40,Business travel,Business,3557,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +6759,113269,Male,Loyal Customer,59,Business travel,Business,397,4,4,3,4,4,5,5,4,4,4,4,3,4,4,6,10.0,satisfied +6760,44337,Male,Loyal Customer,39,Business travel,Eco,230,1,4,4,4,1,1,1,1,1,2,2,4,3,1,0,0.0,neutral or dissatisfied +6761,24677,Female,Loyal Customer,24,Business travel,Business,3010,5,5,2,5,4,4,4,4,1,5,4,2,2,4,0,4.0,satisfied +6762,88525,Female,Loyal Customer,31,Personal Travel,Eco,404,2,5,2,4,5,2,5,5,4,5,5,4,5,5,10,1.0,neutral or dissatisfied +6763,80068,Female,Loyal Customer,24,Business travel,Business,2298,1,1,1,1,4,4,4,4,3,3,5,4,5,4,23,0.0,satisfied +6764,21463,Male,Loyal Customer,59,Business travel,Business,3473,1,1,1,1,1,2,4,4,4,5,4,5,4,3,0,0.0,satisfied +6765,19611,Male,Loyal Customer,43,Business travel,Eco,416,2,4,4,4,2,2,2,2,2,4,3,4,2,2,21,24.0,neutral or dissatisfied +6766,8396,Male,Loyal Customer,36,Business travel,Business,488,2,5,5,5,5,3,3,2,2,2,2,4,2,3,73,62.0,neutral or dissatisfied +6767,57806,Male,disloyal Customer,38,Business travel,Eco,835,2,2,2,4,1,2,5,1,4,3,4,1,3,1,10,8.0,neutral or dissatisfied +6768,89633,Male,Loyal Customer,57,Business travel,Business,1966,1,1,1,1,2,5,5,5,5,5,5,4,5,5,71,47.0,satisfied +6769,117158,Male,Loyal Customer,61,Personal Travel,Eco,646,4,3,4,3,3,4,3,3,1,4,4,4,3,3,11,3.0,neutral or dissatisfied +6770,51179,Female,Loyal Customer,38,Business travel,Eco Plus,86,5,2,3,2,5,5,5,5,3,5,3,2,2,5,2,0.0,satisfied +6771,121592,Male,Loyal Customer,25,Personal Travel,Eco,912,0,3,1,2,3,1,2,3,3,1,2,5,1,3,0,0.0,satisfied +6772,26846,Male,Loyal Customer,54,Business travel,Business,224,5,5,5,5,3,3,3,4,4,4,4,2,4,3,0,0.0,satisfied +6773,78645,Male,Loyal Customer,7,Business travel,Eco,2172,4,5,5,5,4,4,1,4,3,1,2,1,3,4,27,7.0,neutral or dissatisfied +6774,49578,Male,Loyal Customer,55,Business travel,Business,278,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,16.0,satisfied +6775,114752,Male,Loyal Customer,55,Business travel,Business,296,3,4,3,3,5,5,4,4,4,4,4,4,4,5,27,19.0,satisfied +6776,97661,Female,Loyal Customer,25,Business travel,Business,3939,1,1,3,1,5,4,5,5,5,4,5,4,4,5,22,11.0,satisfied +6777,17003,Male,Loyal Customer,68,Personal Travel,Eco,952,1,3,1,4,3,1,4,3,5,1,5,1,2,3,0,7.0,neutral or dissatisfied +6778,96000,Male,Loyal Customer,57,Business travel,Business,3868,1,1,1,1,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +6779,81671,Male,disloyal Customer,27,Business travel,Business,907,4,3,3,3,5,3,5,5,5,4,5,5,4,5,2,0.0,neutral or dissatisfied +6780,16733,Male,Loyal Customer,69,Business travel,Business,767,2,2,2,2,3,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +6781,96859,Male,Loyal Customer,31,Business travel,Eco,781,1,5,5,5,1,1,1,1,1,4,4,3,3,1,50,42.0,neutral or dissatisfied +6782,15522,Female,Loyal Customer,54,Business travel,Eco Plus,306,5,3,3,3,5,1,1,4,4,5,4,2,4,5,9,4.0,satisfied +6783,15707,Male,Loyal Customer,28,Business travel,Business,3066,5,5,5,5,2,2,2,2,5,3,4,4,3,2,29,0.0,satisfied +6784,26169,Male,disloyal Customer,27,Business travel,Eco,581,2,2,2,2,4,2,4,4,4,5,3,4,2,4,12,0.0,neutral or dissatisfied +6785,117399,Female,Loyal Customer,59,Personal Travel,Eco,544,0,5,0,3,4,4,2,1,1,0,1,2,1,2,0,16.0,satisfied +6786,121112,Male,Loyal Customer,47,Business travel,Business,2521,3,3,3,3,4,4,4,4,2,4,4,4,3,4,0,14.0,satisfied +6787,86708,Female,Loyal Customer,45,Business travel,Business,1747,2,5,4,5,1,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +6788,90862,Female,disloyal Customer,29,Business travel,Eco,545,3,1,3,4,3,3,3,3,3,3,3,1,4,3,20,20.0,neutral or dissatisfied +6789,56038,Female,Loyal Customer,29,Business travel,Eco,2586,2,4,4,4,2,2,2,1,2,4,4,2,1,2,71,47.0,neutral or dissatisfied +6790,1795,Male,Loyal Customer,60,Business travel,Business,1613,4,4,5,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +6791,113760,Male,Loyal Customer,8,Personal Travel,Eco,391,2,2,2,4,4,2,4,4,3,4,3,4,4,4,17,13.0,neutral or dissatisfied +6792,68915,Male,Loyal Customer,47,Personal Travel,Eco,936,4,4,5,1,5,5,5,5,1,1,3,3,2,5,0,2.0,neutral or dissatisfied +6793,97465,Female,Loyal Customer,50,Business travel,Business,2574,2,2,1,2,4,4,5,3,3,4,3,3,3,4,83,80.0,satisfied +6794,3824,Female,Loyal Customer,77,Business travel,Business,2108,3,1,2,1,5,2,3,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +6795,11908,Female,Loyal Customer,49,Business travel,Business,1701,3,3,3,3,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +6796,105842,Female,Loyal Customer,53,Business travel,Business,2168,5,5,5,5,5,4,4,4,4,4,4,5,4,3,46,17.0,satisfied +6797,101058,Male,Loyal Customer,38,Business travel,Business,3736,3,3,4,4,1,2,3,3,3,3,3,1,3,4,19,6.0,neutral or dissatisfied +6798,52938,Female,Loyal Customer,27,Business travel,Eco Plus,679,4,4,4,4,4,4,4,4,1,3,4,4,2,4,0,0.0,satisfied +6799,19954,Male,Loyal Customer,42,Personal Travel,Eco,315,3,1,3,2,2,3,1,2,2,3,2,3,2,2,1,0.0,neutral or dissatisfied +6800,119198,Male,Loyal Customer,37,Business travel,Business,1628,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +6801,35083,Female,Loyal Customer,41,Business travel,Eco,1011,4,4,3,4,4,4,4,4,3,2,4,5,2,4,0,0.0,satisfied +6802,27117,Female,Loyal Customer,38,Business travel,Business,2677,1,1,1,1,5,5,5,2,5,4,1,5,3,5,6,8.0,satisfied +6803,23412,Female,Loyal Customer,53,Business travel,Eco,495,5,2,2,2,3,5,5,5,5,5,5,2,5,2,46,34.0,satisfied +6804,35199,Female,Loyal Customer,27,Business travel,Business,1988,3,3,3,3,5,5,5,5,3,1,3,2,1,5,2,11.0,satisfied +6805,74002,Female,Loyal Customer,21,Personal Travel,Eco,1972,1,2,1,3,1,1,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +6806,80664,Female,disloyal Customer,28,Business travel,Eco,821,2,1,1,4,1,1,1,1,3,1,3,3,3,1,0,4.0,neutral or dissatisfied +6807,105665,Male,Loyal Customer,45,Business travel,Business,1964,3,3,3,3,5,5,5,4,4,4,4,3,4,4,43,38.0,satisfied +6808,78730,Male,disloyal Customer,37,Business travel,Business,554,4,4,4,2,1,4,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +6809,9493,Female,disloyal Customer,64,Business travel,Eco,224,1,0,0,4,4,0,4,4,3,5,3,3,4,4,16,9.0,neutral or dissatisfied +6810,31012,Male,disloyal Customer,23,Business travel,Eco,391,2,1,3,2,2,3,2,2,1,4,3,3,2,2,107,117.0,neutral or dissatisfied +6811,18197,Female,Loyal Customer,32,Business travel,Eco,224,5,2,2,2,5,5,5,5,2,3,1,1,4,5,0,0.0,satisfied +6812,61346,Male,Loyal Customer,28,Business travel,Business,3785,3,3,3,3,2,2,2,2,5,4,4,3,5,2,8,0.0,satisfied +6813,42800,Male,Loyal Customer,36,Business travel,Business,3024,4,4,4,4,5,4,2,3,3,4,3,1,3,1,6,0.0,satisfied +6814,57618,Female,Loyal Customer,43,Business travel,Business,3351,5,2,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +6815,53282,Male,Loyal Customer,34,Business travel,Business,901,3,3,3,3,4,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +6816,115578,Female,disloyal Customer,16,Business travel,Eco,325,5,4,5,3,5,5,5,5,3,5,5,3,4,5,10,0.0,satisfied +6817,115438,Female,Loyal Customer,48,Business travel,Eco,373,2,2,2,2,5,3,4,2,2,2,2,2,2,1,13,1.0,neutral or dissatisfied +6818,101251,Female,Loyal Customer,50,Personal Travel,Eco Plus,1587,2,3,2,3,2,4,4,2,2,2,5,1,2,2,0,0.0,neutral or dissatisfied +6819,13475,Male,Loyal Customer,38,Business travel,Eco Plus,409,2,3,3,3,2,2,2,2,1,2,4,2,4,2,0,9.0,neutral or dissatisfied +6820,40749,Male,Loyal Customer,42,Business travel,Business,3453,3,3,3,3,2,1,5,5,5,5,5,1,5,4,0,0.0,satisfied +6821,63502,Female,disloyal Customer,27,Business travel,Business,797,4,5,5,3,2,5,1,2,5,5,5,3,5,2,4,0.0,satisfied +6822,11885,Female,Loyal Customer,48,Business travel,Business,2271,3,3,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +6823,5963,Female,disloyal Customer,25,Business travel,Business,672,4,3,4,4,5,4,5,5,4,2,4,1,4,5,0,0.0,neutral or dissatisfied +6824,62154,Male,disloyal Customer,25,Business travel,Eco,1283,5,5,5,4,2,5,2,2,5,4,3,5,5,2,0,0.0,satisfied +6825,102580,Male,Loyal Customer,30,Business travel,Eco Plus,236,2,1,4,1,2,2,2,2,1,3,4,4,4,2,19,12.0,neutral or dissatisfied +6826,72342,Male,disloyal Customer,45,Business travel,Business,1119,1,1,1,1,1,1,1,1,1,5,2,1,1,1,0,0.0,neutral or dissatisfied +6827,113141,Male,disloyal Customer,24,Business travel,Business,677,4,0,4,3,3,4,3,3,5,3,4,3,5,3,37,30.0,satisfied +6828,124672,Female,disloyal Customer,34,Business travel,Business,399,3,3,3,5,2,3,2,2,4,5,4,5,4,2,23,32.0,neutral or dissatisfied +6829,97608,Male,Loyal Customer,17,Business travel,Eco,442,2,4,4,4,2,2,3,2,4,2,3,3,3,2,6,0.0,neutral or dissatisfied +6830,91139,Female,Loyal Customer,37,Personal Travel,Eco,581,4,5,4,2,2,4,3,2,5,4,5,4,4,2,3,0.0,neutral or dissatisfied +6831,98622,Female,disloyal Customer,14,Business travel,Eco,966,1,1,1,4,2,1,3,2,4,4,4,3,4,2,0,6.0,neutral or dissatisfied +6832,70381,Male,Loyal Customer,39,Business travel,Business,1162,1,1,1,1,3,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +6833,89223,Female,Loyal Customer,19,Personal Travel,Eco,2116,2,3,2,3,4,2,4,4,1,5,2,3,5,4,0,0.0,neutral or dissatisfied +6834,56390,Male,Loyal Customer,7,Personal Travel,Eco,1167,2,1,2,3,4,2,4,4,1,2,3,3,2,4,0,0.0,neutral or dissatisfied +6835,23811,Female,Loyal Customer,19,Personal Travel,Eco,374,4,5,4,4,4,4,4,4,3,3,5,3,4,4,41,56.0,neutral or dissatisfied +6836,21655,Female,disloyal Customer,26,Business travel,Business,746,2,2,2,4,1,2,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +6837,79810,Female,disloyal Customer,16,Business travel,Eco,1076,4,4,4,3,1,4,1,1,5,2,4,4,4,1,0,22.0,neutral or dissatisfied +6838,4375,Female,Loyal Customer,30,Business travel,Eco,618,4,1,1,1,4,3,4,4,1,5,3,2,4,4,12,37.0,neutral or dissatisfied +6839,50592,Male,Loyal Customer,16,Personal Travel,Eco,266,1,4,1,2,2,1,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +6840,67491,Female,Loyal Customer,45,Business travel,Business,592,5,5,5,5,2,4,5,5,5,5,5,4,5,3,56,50.0,satisfied +6841,115676,Female,Loyal Customer,53,Business travel,Business,373,1,1,1,1,3,4,4,4,4,4,4,3,4,5,5,4.0,satisfied +6842,50111,Male,Loyal Customer,59,Business travel,Eco,86,2,1,3,1,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +6843,14912,Male,Loyal Customer,12,Personal Travel,Eco,315,4,3,4,3,2,4,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +6844,78820,Female,Loyal Customer,21,Personal Travel,Eco,528,3,3,3,4,4,3,4,4,3,1,3,3,4,4,0,0.0,neutral or dissatisfied +6845,23287,Female,Loyal Customer,29,Business travel,Business,862,2,2,2,2,5,5,5,5,4,3,3,5,3,5,14,2.0,satisfied +6846,45340,Female,Loyal Customer,22,Business travel,Business,3761,1,1,1,1,4,4,4,4,1,1,2,2,4,4,0,0.0,satisfied +6847,127317,Male,Loyal Customer,31,Personal Travel,Eco,1979,1,2,1,3,4,1,4,4,3,3,4,4,3,4,39,14.0,neutral or dissatisfied +6848,123434,Male,Loyal Customer,11,Personal Travel,Business,2296,3,4,3,4,3,3,3,2,5,2,3,3,3,3,0,8.0,neutral or dissatisfied +6849,113732,Male,Loyal Customer,58,Personal Travel,Eco,226,2,5,2,3,4,2,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +6850,21272,Male,Loyal Customer,51,Business travel,Eco,692,4,2,2,2,4,4,4,4,1,2,3,1,5,4,7,1.0,satisfied +6851,104974,Male,Loyal Customer,63,Business travel,Business,337,2,4,4,4,2,2,2,2,2,2,2,2,2,4,0,5.0,neutral or dissatisfied +6852,73647,Male,disloyal Customer,22,Business travel,Eco,204,2,0,2,1,1,2,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +6853,76151,Female,Loyal Customer,44,Business travel,Business,1735,1,1,3,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +6854,128791,Male,Loyal Customer,60,Business travel,Business,2586,3,3,5,3,5,5,5,5,2,5,4,5,3,5,60,69.0,satisfied +6855,104244,Male,disloyal Customer,23,Business travel,Eco,1276,2,2,2,2,1,2,1,1,4,3,5,5,5,1,3,0.0,neutral or dissatisfied +6856,36278,Male,Loyal Customer,49,Personal Travel,Eco,612,3,5,3,4,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +6857,20350,Female,Loyal Customer,30,Business travel,Business,3073,4,4,3,4,4,4,4,4,2,4,4,1,3,4,3,6.0,neutral or dissatisfied +6858,29189,Male,Loyal Customer,26,Personal Travel,Eco Plus,605,4,4,4,3,2,4,1,2,5,3,5,3,5,2,0,14.0,neutral or dissatisfied +6859,52405,Male,Loyal Customer,67,Personal Travel,Eco,237,2,4,0,5,2,0,3,2,5,3,5,3,5,2,1,0.0,neutral or dissatisfied +6860,75624,Female,Loyal Customer,57,Business travel,Business,3216,1,1,1,1,5,4,4,4,4,5,4,4,4,4,35,45.0,satisfied +6861,93040,Male,Loyal Customer,59,Business travel,Business,436,3,1,2,1,2,4,3,3,3,3,3,2,3,2,9,6.0,neutral or dissatisfied +6862,63188,Male,Loyal Customer,30,Business travel,Business,337,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +6863,51495,Male,Loyal Customer,18,Personal Travel,Business,455,3,4,3,3,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +6864,50629,Female,Loyal Customer,38,Personal Travel,Eco,110,2,3,2,3,3,2,3,3,2,1,3,4,4,3,0,4.0,neutral or dissatisfied +6865,100830,Male,Loyal Customer,35,Business travel,Business,711,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +6866,55271,Female,Loyal Customer,47,Business travel,Business,2007,5,5,5,5,4,5,4,5,5,5,5,3,5,3,10,10.0,satisfied +6867,23226,Female,Loyal Customer,47,Business travel,Eco,476,4,4,5,4,3,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +6868,117104,Male,Loyal Customer,21,Business travel,Eco,647,5,2,2,2,5,5,3,5,4,5,4,4,2,5,0,0.0,satisfied +6869,22397,Female,Loyal Customer,36,Business travel,Eco,143,1,3,3,3,1,1,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +6870,31353,Male,Loyal Customer,38,Business travel,Eco,692,5,5,5,5,5,5,5,5,3,2,1,2,5,5,0,0.0,satisfied +6871,32287,Male,Loyal Customer,51,Business travel,Business,101,0,3,1,3,5,2,4,3,3,3,3,4,3,5,0,5.0,satisfied +6872,119724,Male,Loyal Customer,44,Business travel,Business,1303,4,4,1,4,5,4,3,4,4,3,4,4,4,3,0,2.0,neutral or dissatisfied +6873,103393,Female,Loyal Customer,63,Business travel,Business,237,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,1.0,satisfied +6874,91552,Female,Loyal Customer,31,Personal Travel,Eco,680,2,3,2,4,5,2,5,5,3,3,3,3,4,5,0,0.0,neutral or dissatisfied +6875,117369,Male,Loyal Customer,14,Personal Travel,Eco,296,2,2,2,3,3,2,3,3,1,2,3,4,3,3,6,6.0,neutral or dissatisfied +6876,34345,Female,Loyal Customer,26,Business travel,Business,2105,2,3,3,3,2,2,2,2,3,1,3,1,3,2,1,36.0,neutral or dissatisfied +6877,113143,Male,Loyal Customer,39,Business travel,Business,2964,3,3,3,3,3,4,4,5,5,5,5,4,5,4,26,27.0,satisfied +6878,23501,Male,Loyal Customer,54,Business travel,Eco,349,4,1,1,1,3,4,3,3,1,4,5,3,2,3,0,0.0,satisfied +6879,2899,Male,Loyal Customer,40,Personal Travel,Eco,491,2,3,2,3,5,2,5,5,1,3,3,2,3,5,36,30.0,neutral or dissatisfied +6880,8980,Female,Loyal Customer,43,Business travel,Eco,399,2,3,3,3,4,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +6881,105010,Male,Loyal Customer,60,Business travel,Business,255,3,2,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +6882,2122,Female,Loyal Customer,57,Business travel,Business,3907,2,2,2,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6883,90617,Male,Loyal Customer,42,Business travel,Business,406,1,1,3,1,4,5,4,2,2,2,2,4,2,3,4,12.0,satisfied +6884,29570,Male,Loyal Customer,24,Business travel,Business,680,5,5,5,5,5,5,5,5,5,1,1,5,5,5,78,84.0,satisfied +6885,123914,Female,Loyal Customer,22,Personal Travel,Eco,544,2,1,2,4,1,2,1,1,1,3,4,3,4,1,0,0.0,neutral or dissatisfied +6886,35591,Female,Loyal Customer,20,Business travel,Eco Plus,1097,3,4,2,4,3,3,2,3,3,2,3,1,4,3,0,1.0,neutral or dissatisfied +6887,100507,Female,disloyal Customer,25,Business travel,Eco,580,4,0,4,3,4,4,4,4,1,1,4,4,3,4,1,0.0,neutral or dissatisfied +6888,120891,Female,disloyal Customer,29,Business travel,Business,920,0,0,0,2,2,0,2,2,4,3,4,5,5,2,0,10.0,satisfied +6889,48371,Female,Loyal Customer,53,Business travel,Eco,122,4,5,5,5,1,4,4,4,4,4,4,2,4,1,94,108.0,neutral or dissatisfied +6890,85876,Female,Loyal Customer,43,Business travel,Business,2172,3,3,3,3,2,3,4,5,5,5,5,4,5,5,0,8.0,satisfied +6891,127480,Female,Loyal Customer,72,Business travel,Business,2075,2,2,2,2,5,5,5,4,4,4,4,3,4,3,3,2.0,satisfied +6892,122047,Female,Loyal Customer,61,Business travel,Business,3090,1,1,1,1,4,2,3,2,2,2,1,4,2,3,3,6.0,neutral or dissatisfied +6893,55398,Male,disloyal Customer,30,Business travel,Eco Plus,594,4,4,4,4,2,4,2,2,3,1,3,3,3,2,18,32.0,neutral or dissatisfied +6894,12617,Male,disloyal Customer,11,Business travel,Eco,802,3,2,2,4,1,2,1,1,4,1,3,3,1,1,6,0.0,neutral or dissatisfied +6895,45092,Male,Loyal Customer,35,Personal Travel,Eco,299,4,5,4,5,4,4,4,4,4,5,4,3,4,4,1,0.0,neutral or dissatisfied +6896,10996,Female,disloyal Customer,41,Business travel,Business,163,2,2,2,3,5,2,5,5,3,2,3,1,3,5,22,17.0,neutral or dissatisfied +6897,49033,Female,disloyal Customer,23,Business travel,Eco,262,3,3,3,1,3,2,2,1,5,2,2,2,5,2,145,146.0,neutral or dissatisfied +6898,93149,Female,Loyal Customer,41,Business travel,Eco,1183,3,3,3,3,3,3,3,3,3,3,3,2,4,3,3,25.0,neutral or dissatisfied +6899,63316,Female,disloyal Customer,20,Business travel,Eco,447,4,1,4,4,3,4,3,3,3,3,4,1,4,3,0,16.0,neutral or dissatisfied +6900,82175,Female,Loyal Customer,49,Business travel,Eco Plus,311,1,5,2,2,3,2,2,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +6901,38920,Male,Loyal Customer,30,Business travel,Eco,205,5,1,3,3,5,5,5,5,2,3,4,2,5,5,21,11.0,satisfied +6902,74644,Female,Loyal Customer,14,Personal Travel,Eco,1464,3,4,3,3,3,1,1,5,4,3,4,1,3,1,208,218.0,neutral or dissatisfied +6903,46978,Male,Loyal Customer,21,Personal Travel,Eco,948,1,1,1,2,4,1,4,4,5,5,5,5,5,4,0,3.0,neutral or dissatisfied +6904,112230,Female,Loyal Customer,36,Personal Travel,Eco,1199,3,5,4,2,1,4,4,1,2,5,1,4,1,1,0,0.0,neutral or dissatisfied +6905,49054,Male,Loyal Customer,41,Business travel,Eco,134,5,1,1,1,5,5,5,5,2,4,4,1,3,5,0,0.0,satisfied +6906,13947,Male,Loyal Customer,61,Business travel,Business,2908,3,2,2,2,3,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +6907,81210,Female,Loyal Customer,51,Business travel,Business,1426,5,5,5,5,4,5,5,4,4,4,4,3,4,5,33,57.0,satisfied +6908,68218,Female,disloyal Customer,33,Business travel,Business,631,2,3,3,2,1,3,2,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +6909,99226,Female,Loyal Customer,45,Business travel,Business,541,4,2,4,4,5,5,5,5,5,5,5,4,5,4,0,10.0,satisfied +6910,31818,Male,Loyal Customer,54,Business travel,Business,2762,3,3,3,3,4,4,4,5,2,3,4,4,4,4,0,1.0,satisfied +6911,49255,Male,Loyal Customer,47,Business travel,Business,1901,3,3,3,3,1,3,1,5,5,5,5,4,5,3,0,0.0,satisfied +6912,26057,Male,Loyal Customer,68,Personal Travel,Eco,432,4,4,4,4,4,4,4,4,1,3,2,3,3,4,0,0.0,neutral or dissatisfied +6913,30638,Male,Loyal Customer,20,Business travel,Business,3509,2,2,2,2,5,5,5,5,4,3,3,4,2,5,45,51.0,satisfied +6914,12825,Male,disloyal Customer,24,Business travel,Eco,641,1,1,1,1,1,1,1,1,1,3,1,2,1,1,0,0.0,neutral or dissatisfied +6915,59692,Male,Loyal Customer,41,Personal Travel,Eco,787,1,5,1,3,1,1,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +6916,23255,Male,Loyal Customer,34,Business travel,Business,2554,3,3,3,3,2,2,4,4,4,4,4,4,4,1,34,38.0,satisfied +6917,34620,Female,Loyal Customer,22,Personal Travel,Eco Plus,1576,3,5,3,1,4,3,4,4,3,4,3,3,5,4,2,2.0,neutral or dissatisfied +6918,68512,Male,Loyal Customer,31,Personal Travel,Eco Plus,1067,3,4,3,2,4,3,4,4,3,3,5,3,4,4,0,10.0,neutral or dissatisfied +6919,8588,Female,Loyal Customer,22,Personal Travel,Eco,109,2,4,2,3,2,2,2,2,2,4,3,3,4,2,24,26.0,neutral or dissatisfied +6920,68334,Male,Loyal Customer,35,Personal Travel,Business,1598,4,4,4,3,5,5,5,2,2,4,4,5,2,3,0,0.0,neutral or dissatisfied +6921,6134,Female,Loyal Customer,49,Business travel,Business,2921,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +6922,38012,Female,Loyal Customer,25,Business travel,Business,3468,3,3,5,3,5,4,5,5,5,5,3,1,3,5,10,0.0,satisfied +6923,92881,Male,Loyal Customer,43,Business travel,Business,2175,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +6924,52917,Male,Loyal Customer,16,Business travel,Eco,679,5,1,1,1,5,5,5,5,5,1,2,1,3,5,0,0.0,satisfied +6925,107561,Female,Loyal Customer,49,Business travel,Business,3164,4,4,4,4,1,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +6926,46721,Female,Loyal Customer,41,Personal Travel,Eco,73,1,1,1,1,4,1,4,4,2,4,1,1,2,4,0,18.0,neutral or dissatisfied +6927,121020,Male,Loyal Customer,18,Personal Travel,Eco,861,4,3,4,3,4,4,4,4,2,4,5,1,4,4,0,0.0,satisfied +6928,93143,Male,Loyal Customer,60,Business travel,Business,1066,3,2,2,2,4,3,3,3,3,3,3,3,3,3,5,10.0,neutral or dissatisfied +6929,80622,Female,Loyal Customer,56,Business travel,Business,1902,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +6930,24633,Female,Loyal Customer,17,Personal Travel,Eco,526,3,4,3,2,2,3,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +6931,39648,Male,Loyal Customer,14,Personal Travel,Eco Plus,1172,4,4,4,3,1,4,1,1,5,2,3,3,4,1,0,0.0,satisfied +6932,49813,Female,Loyal Customer,31,Business travel,Business,209,3,3,4,3,5,4,3,5,3,5,5,4,3,5,0,0.0,satisfied +6933,119842,Female,Loyal Customer,22,Business travel,Eco,912,4,1,5,5,4,4,3,4,3,3,4,1,4,4,0,7.0,neutral or dissatisfied +6934,91891,Female,Loyal Customer,43,Business travel,Business,2475,5,5,5,5,5,3,5,5,5,5,5,5,5,3,19,18.0,satisfied +6935,18809,Male,disloyal Customer,59,Business travel,Eco,448,2,0,2,1,3,2,1,3,1,3,2,2,3,3,0,0.0,neutral or dissatisfied +6936,38827,Male,Loyal Customer,45,Personal Travel,Eco,354,3,4,3,4,5,3,5,5,2,2,5,3,4,5,35,24.0,neutral or dissatisfied +6937,72006,Female,Loyal Customer,43,Business travel,Eco Plus,1440,2,3,3,3,5,3,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +6938,24973,Male,disloyal Customer,13,Business travel,Eco,692,2,1,1,3,2,1,2,2,5,3,1,2,3,2,0,3.0,neutral or dissatisfied +6939,99173,Female,Loyal Customer,14,Personal Travel,Eco Plus,1076,1,5,2,3,1,2,1,1,3,4,5,3,5,1,6,1.0,neutral or dissatisfied +6940,51580,Female,Loyal Customer,55,Business travel,Eco,493,3,2,2,2,5,3,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +6941,95493,Female,disloyal Customer,27,Business travel,Eco Plus,562,1,1,1,3,3,1,3,3,4,5,3,1,4,3,7,0.0,neutral or dissatisfied +6942,49958,Male,Loyal Customer,36,Business travel,Business,2880,2,2,2,2,3,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +6943,9636,Female,disloyal Customer,25,Business travel,Business,277,4,3,4,3,4,4,4,4,3,4,4,4,4,4,0,94.0,neutral or dissatisfied +6944,94828,Male,Loyal Customer,52,Business travel,Eco,248,2,5,3,5,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +6945,127737,Female,Loyal Customer,55,Business travel,Business,2788,2,2,3,2,1,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +6946,100519,Female,Loyal Customer,12,Personal Travel,Eco,580,0,2,0,2,2,0,2,2,2,5,1,4,1,2,0,0.0,satisfied +6947,25024,Male,Loyal Customer,28,Business travel,Business,907,2,1,1,1,2,1,2,2,3,1,3,2,4,2,27,,neutral or dissatisfied +6948,87435,Male,Loyal Customer,34,Business travel,Business,3037,2,2,2,2,3,4,4,4,4,4,4,3,4,3,17,16.0,satisfied +6949,91980,Female,Loyal Customer,68,Personal Travel,Eco Plus,2586,3,5,3,4,5,2,3,5,5,3,3,2,5,5,0,0.0,neutral or dissatisfied +6950,43653,Female,Loyal Customer,34,Business travel,Business,695,5,5,5,5,2,5,3,3,3,4,3,2,3,4,8,17.0,satisfied +6951,24861,Male,Loyal Customer,38,Business travel,Eco,356,4,2,1,2,4,4,4,4,4,2,5,2,1,4,0,3.0,satisfied +6952,97492,Female,Loyal Customer,54,Personal Travel,Eco,670,2,4,2,1,3,4,1,3,3,2,3,5,3,4,25,34.0,neutral or dissatisfied +6953,19748,Female,Loyal Customer,46,Business travel,Business,2382,2,1,2,2,3,4,4,5,5,5,5,3,5,5,70,62.0,satisfied +6954,76244,Male,Loyal Customer,63,Personal Travel,Eco,1399,1,1,1,2,3,1,3,3,3,1,3,2,2,3,0,0.0,neutral or dissatisfied +6955,128599,Female,Loyal Customer,27,Business travel,Business,2628,3,3,1,3,3,4,3,3,3,4,4,4,4,3,1,0.0,satisfied +6956,12597,Male,Loyal Customer,62,Personal Travel,Eco,542,2,3,2,1,1,2,1,1,5,5,5,4,2,1,0,1.0,neutral or dissatisfied +6957,20798,Male,disloyal Customer,32,Business travel,Business,357,2,2,2,3,4,2,4,4,5,1,2,4,1,4,0,0.0,neutral or dissatisfied +6958,39335,Female,Loyal Customer,55,Personal Travel,Eco Plus,67,3,5,3,3,2,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +6959,82993,Female,Loyal Customer,59,Business travel,Business,3887,2,2,2,2,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +6960,111990,Female,Loyal Customer,70,Personal Travel,Eco,533,1,4,1,4,2,4,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +6961,100873,Female,Loyal Customer,12,Personal Travel,Eco,1605,3,5,3,1,3,3,3,3,5,5,5,5,5,3,17,8.0,neutral or dissatisfied +6962,105138,Female,Loyal Customer,30,Business travel,Business,3731,4,2,2,2,4,3,4,4,1,2,3,1,3,4,9,8.0,neutral or dissatisfied +6963,72052,Female,Loyal Customer,50,Business travel,Business,2556,2,2,2,2,2,4,4,4,4,4,4,5,4,3,5,0.0,satisfied +6964,52847,Male,Loyal Customer,53,Personal Travel,Eco,1721,1,4,1,3,3,1,2,3,5,5,5,3,4,3,19,0.0,neutral or dissatisfied +6965,94788,Male,Loyal Customer,51,Business travel,Business,2498,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +6966,97299,Male,Loyal Customer,39,Business travel,Business,347,1,1,4,1,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +6967,45520,Female,Loyal Customer,39,Business travel,Business,4000,3,3,3,3,4,1,3,5,5,5,5,3,5,3,0,0.0,satisfied +6968,66856,Male,Loyal Customer,10,Personal Travel,Eco,731,1,4,1,4,4,1,4,4,1,2,2,4,4,4,12,0.0,neutral or dissatisfied +6969,94334,Male,Loyal Customer,53,Business travel,Business,1881,1,1,1,1,4,5,5,5,5,5,4,3,5,3,95,98.0,satisfied +6970,12567,Female,Loyal Customer,55,Business travel,Eco Plus,871,4,5,2,5,2,2,2,4,4,4,4,2,4,4,0,0.0,satisfied +6971,122650,Male,Loyal Customer,60,Business travel,Business,1905,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,12.0,satisfied +6972,57837,Male,Loyal Customer,36,Business travel,Business,1491,5,5,4,5,3,4,4,4,4,4,4,5,4,5,0,4.0,satisfied +6973,88464,Male,Loyal Customer,38,Business travel,Business,444,1,5,5,5,5,4,4,1,1,1,1,1,1,3,13,10.0,neutral or dissatisfied +6974,82747,Male,disloyal Customer,19,Business travel,Business,409,0,2,0,4,3,0,3,3,3,5,5,4,4,3,0,0.0,satisfied +6975,97155,Female,disloyal Customer,27,Business travel,Eco,1390,3,3,3,4,2,3,2,2,2,3,4,2,4,2,55,43.0,neutral or dissatisfied +6976,64209,Male,Loyal Customer,41,Business travel,Eco Plus,853,3,5,5,5,3,3,3,3,4,1,2,4,2,3,41,35.0,neutral or dissatisfied +6977,121429,Female,Loyal Customer,24,Business travel,Business,331,1,0,0,3,4,0,3,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +6978,124829,Male,Loyal Customer,42,Personal Travel,Eco,280,3,4,3,2,1,3,1,1,4,4,5,5,4,1,2,34.0,neutral or dissatisfied +6979,67031,Female,Loyal Customer,20,Business travel,Business,2790,5,5,5,5,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +6980,102500,Female,Loyal Customer,38,Personal Travel,Eco,407,3,2,3,2,3,3,3,3,1,1,3,2,2,3,60,46.0,neutral or dissatisfied +6981,85603,Female,Loyal Customer,72,Business travel,Business,2627,1,3,3,3,2,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +6982,56072,Male,Loyal Customer,40,Personal Travel,Eco,2475,2,5,1,4,1,1,1,3,4,4,4,1,3,1,201,191.0,neutral or dissatisfied +6983,126000,Male,Loyal Customer,19,Personal Travel,Business,507,3,5,3,3,5,3,5,5,4,2,5,3,5,5,7,16.0,neutral or dissatisfied +6984,52221,Female,Loyal Customer,30,Business travel,Business,651,4,4,4,4,5,5,5,5,1,5,5,1,2,5,0,0.0,satisfied +6985,26050,Female,Loyal Customer,39,Business travel,Business,432,1,1,1,1,1,1,5,2,2,2,2,4,2,1,0,0.0,satisfied +6986,48208,Male,disloyal Customer,25,Business travel,Business,236,3,0,3,3,4,3,4,4,5,4,1,3,2,4,0,1.0,neutral or dissatisfied +6987,79402,Female,Loyal Customer,43,Business travel,Eco,502,2,3,4,4,2,2,2,2,2,2,2,2,2,2,80,77.0,neutral or dissatisfied +6988,68174,Female,Loyal Customer,25,Business travel,Business,597,3,5,4,5,3,3,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +6989,47174,Male,disloyal Customer,15,Business travel,Eco,620,2,4,2,4,1,2,1,1,4,1,4,4,4,1,4,3.0,neutral or dissatisfied +6990,120471,Female,Loyal Customer,54,Personal Travel,Eco,366,1,3,1,4,1,4,1,4,4,1,4,2,4,2,11,0.0,neutral or dissatisfied +6991,89562,Male,Loyal Customer,47,Business travel,Eco,1005,3,2,2,2,3,3,3,3,1,4,3,1,3,3,0,0.0,neutral or dissatisfied +6992,19975,Male,Loyal Customer,12,Personal Travel,Eco,557,3,5,3,2,2,3,2,2,2,5,4,3,5,2,0,9.0,neutral or dissatisfied +6993,95994,Male,Loyal Customer,39,Business travel,Business,3203,5,5,5,5,5,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +6994,70856,Female,Loyal Customer,49,Business travel,Business,2830,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +6995,106983,Female,Loyal Customer,49,Personal Travel,Eco,972,3,5,3,2,3,4,5,3,3,3,3,5,3,5,8,0.0,neutral or dissatisfied +6996,107750,Female,Loyal Customer,58,Personal Travel,Eco,405,2,5,2,3,2,5,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +6997,9194,Female,Loyal Customer,49,Business travel,Eco Plus,363,4,1,1,1,3,3,3,4,4,4,4,3,4,1,89,74.0,neutral or dissatisfied +6998,95897,Male,Loyal Customer,17,Personal Travel,Eco,759,2,5,2,1,3,2,3,3,3,2,5,3,3,3,56,61.0,neutral or dissatisfied +6999,76894,Female,Loyal Customer,58,Business travel,Business,3158,3,3,3,3,5,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +7000,110578,Female,Loyal Customer,58,Business travel,Eco,551,3,4,4,4,4,4,3,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +7001,89449,Male,Loyal Customer,18,Personal Travel,Eco,151,2,5,2,1,4,2,4,4,5,5,5,3,4,4,2,6.0,neutral or dissatisfied +7002,49571,Male,Loyal Customer,44,Business travel,Business,209,4,4,4,4,1,5,4,5,5,5,4,4,5,2,0,0.0,satisfied +7003,113715,Female,Loyal Customer,35,Personal Travel,Eco,197,1,4,1,4,3,1,3,3,4,5,5,3,4,3,4,0.0,neutral or dissatisfied +7004,24730,Male,Loyal Customer,41,Personal Travel,Eco Plus,406,2,5,2,3,2,2,2,2,5,5,5,4,4,2,5,11.0,neutral or dissatisfied +7005,28650,Male,Loyal Customer,9,Personal Travel,Eco,2404,4,3,4,2,5,4,5,5,4,1,2,2,3,5,0,0.0,neutral or dissatisfied +7006,10223,Female,Loyal Customer,49,Business travel,Business,301,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +7007,30639,Female,Loyal Customer,43,Business travel,Eco,533,4,5,5,5,5,2,5,4,4,4,4,4,4,2,15,20.0,satisfied +7008,52748,Male,Loyal Customer,52,Personal Travel,Eco,2306,4,4,4,1,2,4,2,2,3,2,5,3,5,2,80,62.0,neutral or dissatisfied +7009,29143,Female,Loyal Customer,63,Personal Travel,Eco,954,2,4,2,3,2,5,5,4,4,2,4,3,4,5,0,8.0,neutral or dissatisfied +7010,120091,Male,Loyal Customer,29,Business travel,Business,683,5,5,5,5,4,4,4,4,5,3,5,5,5,4,0,4.0,satisfied +7011,45732,Male,Loyal Customer,72,Business travel,Eco Plus,852,2,2,2,2,2,2,2,2,3,4,3,4,3,2,90,91.0,neutral or dissatisfied +7012,9880,Male,disloyal Customer,27,Business travel,Business,534,0,0,0,2,5,0,4,5,3,4,4,5,4,5,32,19.0,satisfied +7013,43495,Female,Loyal Customer,54,Personal Travel,Eco,752,2,4,2,3,4,5,4,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +7014,44277,Male,Loyal Customer,17,Business travel,Eco Plus,224,3,1,1,1,3,3,3,3,1,4,4,3,4,3,0,5.0,neutral or dissatisfied +7015,100766,Female,Loyal Customer,24,Business travel,Business,1411,4,4,4,4,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +7016,103254,Female,Loyal Customer,32,Business travel,Business,888,1,1,1,1,3,3,3,3,5,5,5,4,4,3,13,14.0,satisfied +7017,76305,Female,Loyal Customer,39,Business travel,Business,2182,5,5,5,5,3,4,4,5,5,5,5,3,5,5,9,2.0,satisfied +7018,62639,Male,Loyal Customer,45,Personal Travel,Eco,1723,3,4,3,4,5,3,5,5,5,2,5,5,4,5,18,0.0,neutral or dissatisfied +7019,71978,Female,Loyal Customer,39,Business travel,Business,1440,3,2,2,2,4,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +7020,32007,Female,Loyal Customer,69,Personal Travel,Business,216,2,0,2,5,2,5,5,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +7021,112755,Male,Loyal Customer,23,Business travel,Business,588,2,2,2,2,3,3,3,3,5,3,4,4,5,3,9,1.0,satisfied +7022,72272,Male,Loyal Customer,53,Business travel,Eco,919,2,5,5,5,2,2,2,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +7023,54088,Female,Loyal Customer,66,Personal Travel,Eco,1416,2,5,2,1,5,5,5,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +7024,102205,Female,Loyal Customer,46,Business travel,Eco,391,4,4,4,4,1,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +7025,75126,Female,Loyal Customer,50,Business travel,Business,1723,5,5,5,5,3,4,4,4,4,5,4,3,4,4,0,22.0,satisfied +7026,69840,Female,Loyal Customer,42,Business travel,Eco,655,4,4,4,4,5,5,4,4,4,4,4,1,4,4,0,0.0,satisfied +7027,661,Female,Loyal Customer,53,Business travel,Business,3574,3,3,3,3,5,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +7028,51456,Male,Loyal Customer,49,Personal Travel,Eco Plus,109,2,5,2,1,3,2,3,3,5,2,1,3,1,3,0,0.0,neutral or dissatisfied +7029,20465,Male,Loyal Customer,59,Personal Travel,Eco,177,3,5,3,3,2,3,2,2,5,3,2,1,5,2,58,53.0,neutral or dissatisfied +7030,76062,Female,Loyal Customer,45,Business travel,Business,3085,3,3,3,3,5,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +7031,19176,Female,Loyal Customer,35,Business travel,Eco,1024,4,5,5,5,4,4,4,4,5,2,2,1,2,4,0,0.0,satisfied +7032,24903,Female,Loyal Customer,30,Personal Travel,Business,762,4,4,4,1,5,4,4,5,3,4,4,3,4,5,44,48.0,neutral or dissatisfied +7033,87797,Female,Loyal Customer,33,Business travel,Business,214,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +7034,67650,Male,disloyal Customer,48,Business travel,Business,1235,3,3,3,3,4,3,4,4,3,5,4,5,4,4,74,65.0,satisfied +7035,13165,Female,Loyal Customer,17,Business travel,Eco Plus,427,4,5,5,5,4,4,3,4,2,1,3,2,2,4,0,0.0,satisfied +7036,27708,Male,Loyal Customer,45,Business travel,Business,909,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +7037,129354,Female,Loyal Customer,16,Personal Travel,Eco,2586,2,4,2,4,5,2,5,5,3,5,5,3,4,5,22,14.0,neutral or dissatisfied +7038,112206,Female,disloyal Customer,24,Business travel,Eco,649,4,5,4,4,3,4,3,3,3,3,4,5,5,3,38,45.0,neutral or dissatisfied +7039,119885,Female,Loyal Customer,29,Personal Travel,Eco,936,2,5,2,1,4,2,4,4,2,5,3,3,2,4,40,36.0,neutral or dissatisfied +7040,13832,Male,disloyal Customer,10,Business travel,Eco,594,3,1,4,4,3,4,1,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +7041,58829,Male,disloyal Customer,20,Business travel,Business,1005,4,3,4,4,1,4,1,1,4,5,4,5,5,1,0,0.0,satisfied +7042,109169,Female,Loyal Customer,59,Business travel,Business,483,2,2,2,2,4,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +7043,58597,Male,Loyal Customer,9,Personal Travel,Eco,334,4,4,4,5,1,4,1,1,5,3,5,3,5,1,3,0.0,satisfied +7044,19787,Male,Loyal Customer,48,Business travel,Business,3160,2,2,2,2,5,3,3,2,2,2,2,3,2,4,13,30.0,neutral or dissatisfied +7045,98275,Male,Loyal Customer,48,Business travel,Business,2042,4,4,4,4,3,4,5,2,2,3,2,5,2,5,0,0.0,satisfied +7046,75697,Male,Loyal Customer,52,Business travel,Business,813,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7047,59684,Male,Loyal Customer,11,Personal Travel,Eco,854,4,5,3,2,2,3,2,2,3,4,4,4,5,2,30,48.0,neutral or dissatisfied +7048,74309,Female,Loyal Customer,37,Business travel,Business,1205,2,2,4,2,5,5,5,5,5,5,5,5,5,3,1,0.0,satisfied +7049,75861,Female,Loyal Customer,10,Personal Travel,Eco,1440,3,2,3,1,2,3,3,2,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +7050,14006,Male,disloyal Customer,22,Business travel,Eco,615,3,5,3,3,5,3,5,5,3,5,4,5,5,5,92,71.0,neutral or dissatisfied +7051,55428,Female,Loyal Customer,32,Business travel,Business,2521,5,2,5,5,4,5,5,3,3,4,5,5,5,5,0,0.0,satisfied +7052,89920,Male,Loyal Customer,27,Business travel,Business,1487,4,2,2,2,4,3,4,4,2,4,2,2,3,4,0,0.0,neutral or dissatisfied +7053,110373,Male,Loyal Customer,45,Business travel,Eco,842,1,5,5,5,1,1,1,1,3,1,3,4,2,1,0,0.0,neutral or dissatisfied +7054,126465,Female,Loyal Customer,51,Business travel,Business,1972,1,1,1,1,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +7055,66104,Male,Loyal Customer,59,Business travel,Business,2082,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +7056,53134,Female,disloyal Customer,35,Business travel,Eco,413,3,4,3,3,1,3,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +7057,82331,Female,Loyal Customer,11,Personal Travel,Eco,456,3,4,3,4,1,3,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +7058,70324,Male,Loyal Customer,59,Business travel,Business,986,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,2.0,satisfied +7059,128349,Female,disloyal Customer,24,Business travel,Eco,304,2,0,2,2,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +7060,89475,Male,Loyal Customer,44,Personal Travel,Eco Plus,302,2,4,3,3,4,3,4,4,5,3,1,3,5,4,8,7.0,neutral or dissatisfied +7061,1939,Male,Loyal Customer,59,Business travel,Business,2480,3,3,3,3,4,4,4,4,4,4,4,5,4,4,4,0.0,satisfied +7062,16680,Male,Loyal Customer,42,Personal Travel,Eco,488,1,0,1,2,1,1,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +7063,2036,Female,Loyal Customer,22,Business travel,Business,3692,2,2,2,2,4,4,4,4,4,3,4,3,4,4,36,26.0,satisfied +7064,13710,Female,Loyal Customer,41,Business travel,Business,1965,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7065,36190,Female,Loyal Customer,53,Business travel,Business,3173,3,5,3,3,4,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +7066,97028,Female,Loyal Customer,60,Business travel,Business,2195,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +7067,21437,Female,Loyal Customer,38,Business travel,Business,377,1,1,1,1,2,2,3,4,4,4,4,2,4,4,61,49.0,satisfied +7068,42016,Female,Loyal Customer,70,Business travel,Business,2104,2,2,2,2,2,2,2,5,5,5,4,3,5,1,8,5.0,satisfied +7069,59625,Male,Loyal Customer,46,Business travel,Eco,964,4,1,1,1,4,4,4,4,2,2,4,3,4,4,3,4.0,neutral or dissatisfied +7070,112732,Female,Loyal Customer,37,Personal Travel,Eco,605,2,3,2,3,3,2,3,3,2,2,4,4,4,3,11,11.0,neutral or dissatisfied +7071,57584,Male,Loyal Customer,15,Business travel,Business,1597,1,1,1,1,1,2,1,1,4,2,3,3,4,1,0,8.0,neutral or dissatisfied +7072,63744,Male,Loyal Customer,62,Personal Travel,Eco,1660,2,5,2,2,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +7073,66020,Female,disloyal Customer,25,Business travel,Business,1055,4,5,4,3,4,4,2,4,3,3,4,5,4,4,60,45.0,satisfied +7074,117579,Female,Loyal Customer,45,Business travel,Business,1920,0,0,0,4,5,5,5,3,3,3,3,3,3,3,4,0.0,satisfied +7075,53043,Female,disloyal Customer,25,Business travel,Eco,1190,3,4,4,4,3,4,3,3,3,2,3,2,3,3,0,1.0,neutral or dissatisfied +7076,54560,Female,Loyal Customer,31,Business travel,Eco Plus,925,4,4,4,4,5,5,5,5,2,4,2,4,4,5,5,0.0,satisfied +7077,22613,Male,Loyal Customer,52,Business travel,Business,223,3,3,3,3,5,4,3,1,1,1,3,2,1,2,1,5.0,neutral or dissatisfied +7078,67008,Male,Loyal Customer,39,Business travel,Business,1817,5,3,5,5,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +7079,49254,Female,disloyal Customer,41,Business travel,Business,308,3,3,3,2,2,3,2,2,1,3,4,3,3,2,25,16.0,neutral or dissatisfied +7080,109964,Male,Loyal Customer,45,Personal Travel,Eco,1092,2,3,2,4,4,2,4,4,4,3,4,1,4,4,20,5.0,neutral or dissatisfied +7081,113649,Female,Loyal Customer,65,Personal Travel,Eco,258,2,5,2,1,2,4,3,3,3,2,5,5,3,5,21,4.0,neutral or dissatisfied +7082,32878,Male,Loyal Customer,17,Personal Travel,Eco,101,4,4,4,3,3,4,3,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +7083,76369,Male,Loyal Customer,36,Business travel,Business,3074,1,1,1,1,3,5,4,5,5,5,5,5,5,4,0,62.0,satisfied +7084,100418,Male,Loyal Customer,32,Personal Travel,Eco Plus,1073,2,5,2,4,1,2,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +7085,44597,Female,Loyal Customer,47,Business travel,Business,2585,2,2,2,2,5,4,5,4,4,4,4,4,4,5,19,13.0,satisfied +7086,51078,Male,Loyal Customer,20,Personal Travel,Eco,86,1,4,1,5,4,1,5,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +7087,59055,Male,disloyal Customer,25,Business travel,Eco,1744,4,4,4,1,4,4,4,4,1,4,2,2,1,4,9,0.0,neutral or dissatisfied +7088,86343,Male,Loyal Customer,15,Business travel,Business,749,3,3,3,3,4,4,4,4,5,5,5,5,5,4,12,15.0,satisfied +7089,120490,Male,Loyal Customer,29,Personal Travel,Eco,366,3,1,3,4,1,3,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +7090,118012,Female,Loyal Customer,44,Business travel,Eco,1037,2,3,3,3,1,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +7091,100533,Male,Loyal Customer,31,Personal Travel,Eco,580,2,5,2,4,5,2,1,5,3,3,4,4,4,5,24,18.0,neutral or dissatisfied +7092,56231,Male,Loyal Customer,34,Personal Travel,Eco,1608,3,5,3,3,1,3,2,1,3,3,3,5,4,1,0,0.0,neutral or dissatisfied +7093,4169,Male,Loyal Customer,17,Personal Travel,Eco,431,2,5,2,5,5,2,5,5,5,4,5,5,5,5,5,0.0,neutral or dissatisfied +7094,69450,Female,Loyal Customer,18,Personal Travel,Eco,1096,2,1,2,3,5,2,2,5,4,5,2,3,2,5,0,2.0,neutral or dissatisfied +7095,68173,Male,Loyal Customer,44,Business travel,Eco,597,3,2,2,2,3,3,3,3,4,2,2,2,2,3,0,7.0,neutral or dissatisfied +7096,27999,Female,Loyal Customer,45,Business travel,Business,363,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +7097,276,Female,disloyal Customer,43,Business travel,Eco,402,2,0,3,1,2,3,2,2,4,1,4,5,2,2,0,0.0,neutral or dissatisfied +7098,117131,Male,Loyal Customer,69,Personal Travel,Eco,338,2,4,2,4,5,2,5,5,4,3,3,3,3,5,2,0.0,neutral or dissatisfied +7099,81276,Female,disloyal Customer,50,Business travel,Business,1020,2,2,2,3,5,2,5,5,4,3,5,4,5,5,0,0.0,satisfied +7100,30799,Female,Loyal Customer,47,Personal Travel,Eco,701,3,2,3,4,3,3,4,5,5,3,1,1,5,3,23,29.0,neutral or dissatisfied +7101,71338,Male,Loyal Customer,39,Personal Travel,Eco,1514,1,1,1,3,4,1,4,4,2,4,3,4,2,4,0,0.0,neutral or dissatisfied +7102,90400,Male,Loyal Customer,62,Personal Travel,Business,270,3,5,3,1,5,5,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +7103,126918,Female,Loyal Customer,43,Business travel,Business,2033,0,0,0,1,4,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +7104,1506,Male,Loyal Customer,42,Business travel,Business,3853,2,1,1,1,3,3,3,2,2,2,2,3,2,2,0,5.0,neutral or dissatisfied +7105,66674,Male,disloyal Customer,27,Business travel,Business,802,4,4,4,3,1,4,1,1,3,2,5,3,5,1,0,0.0,satisfied +7106,6506,Female,Loyal Customer,32,Business travel,Business,3964,1,1,1,1,4,3,4,4,3,3,4,4,4,4,27,32.0,satisfied +7107,52854,Male,Loyal Customer,38,Personal Travel,Eco,1721,3,1,3,2,3,3,3,3,2,2,2,4,2,3,127,124.0,neutral or dissatisfied +7108,53829,Female,Loyal Customer,47,Business travel,Business,1503,5,5,5,5,3,1,4,4,4,4,5,5,4,5,59,43.0,satisfied +7109,11680,Male,disloyal Customer,27,Business travel,Business,395,2,2,2,2,5,2,5,5,1,4,2,1,2,5,0,19.0,neutral or dissatisfied +7110,58287,Male,Loyal Customer,65,Personal Travel,Eco,594,1,3,1,4,3,1,3,3,5,2,2,3,2,3,4,4.0,neutral or dissatisfied +7111,79342,Male,Loyal Customer,38,Business travel,Eco,1020,3,5,5,5,3,3,3,3,4,4,3,2,3,3,1,0.0,neutral or dissatisfied +7112,83825,Male,Loyal Customer,52,Business travel,Business,425,1,1,1,1,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +7113,111312,Male,Loyal Customer,47,Business travel,Business,1952,4,3,4,4,4,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +7114,90607,Male,Loyal Customer,23,Business travel,Business,545,1,1,1,1,5,5,5,5,4,4,5,5,4,5,28,17.0,satisfied +7115,121937,Female,Loyal Customer,35,Business travel,Business,2282,3,3,3,3,1,5,5,4,4,4,4,2,4,4,0,0.0,satisfied +7116,89170,Female,Loyal Customer,54,Personal Travel,Eco,2139,5,4,5,2,3,4,4,2,2,5,4,4,2,5,3,0.0,satisfied +7117,28507,Male,Loyal Customer,54,Business travel,Business,2688,5,5,5,5,2,2,2,2,3,3,2,2,4,2,0,0.0,satisfied +7118,46854,Female,Loyal Customer,44,Business travel,Business,1701,1,1,5,1,3,1,3,5,5,5,5,2,5,3,68,69.0,satisfied +7119,115204,Male,Loyal Customer,50,Business travel,Business,1949,2,2,2,2,5,4,4,5,5,5,5,5,5,3,8,1.0,satisfied +7120,12251,Female,Loyal Customer,44,Business travel,Business,3910,3,3,5,3,4,4,2,4,4,4,4,1,4,3,0,0.0,satisfied +7121,121279,Female,Loyal Customer,40,Business travel,Eco Plus,2075,3,4,5,5,3,3,3,3,2,4,3,1,4,3,5,12.0,neutral or dissatisfied +7122,48928,Male,Loyal Customer,29,Business travel,Business,326,3,3,3,3,4,4,4,4,4,5,5,4,2,4,0,0.0,satisfied +7123,54131,Male,disloyal Customer,24,Business travel,Eco,1337,5,5,5,3,2,5,2,2,2,3,4,2,3,2,26,2.0,satisfied +7124,2392,Female,Loyal Customer,44,Business travel,Business,2461,3,3,3,3,3,5,4,4,4,4,4,3,4,5,21,12.0,satisfied +7125,18362,Male,Loyal Customer,40,Business travel,Business,1586,1,1,1,1,5,3,1,5,5,5,4,2,5,5,0,0.0,satisfied +7126,108120,Female,Loyal Customer,54,Business travel,Eco,997,1,5,2,5,4,3,3,1,1,1,1,3,1,4,114,108.0,neutral or dissatisfied +7127,126244,Male,Loyal Customer,61,Business travel,Business,1886,2,2,2,2,3,3,3,3,3,3,2,1,3,3,80,71.0,neutral or dissatisfied +7128,112772,Male,Loyal Customer,17,Personal Travel,Eco,590,3,4,3,3,3,5,5,4,1,1,2,5,3,5,233,222.0,neutral or dissatisfied +7129,106489,Female,Loyal Customer,54,Personal Travel,Business,495,3,4,3,4,5,2,1,5,5,3,5,3,5,2,8,10.0,neutral or dissatisfied +7130,41492,Female,Loyal Customer,37,Business travel,Business,1464,1,1,1,1,4,2,4,4,4,4,4,5,4,4,0,11.0,satisfied +7131,28536,Female,Loyal Customer,47,Business travel,Business,2640,4,1,1,1,4,4,4,1,1,2,4,4,2,4,210,161.0,neutral or dissatisfied +7132,88035,Male,Loyal Customer,23,Business travel,Business,2975,3,3,5,3,5,4,5,5,5,5,5,3,5,5,4,0.0,satisfied +7133,99113,Female,Loyal Customer,12,Personal Travel,Eco,419,5,2,1,2,2,1,2,2,2,1,2,2,2,2,0,0.0,satisfied +7134,77149,Male,Loyal Customer,40,Business travel,Business,1865,5,5,5,5,3,3,4,2,2,2,2,3,2,3,0,0.0,satisfied +7135,105223,Female,disloyal Customer,42,Business travel,Business,377,2,2,2,3,2,2,2,2,5,4,5,5,4,2,44,46.0,neutral or dissatisfied +7136,97381,Female,Loyal Customer,47,Personal Travel,Eco,1020,4,3,4,1,1,3,5,1,1,4,1,1,1,5,0,0.0,neutral or dissatisfied +7137,7854,Female,Loyal Customer,46,Business travel,Business,1005,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +7138,93671,Female,Loyal Customer,27,Business travel,Business,3918,1,5,1,1,4,4,4,4,4,1,3,4,1,4,0,0.0,satisfied +7139,38061,Female,Loyal Customer,35,Business travel,Eco,1249,5,5,5,5,5,5,5,5,1,2,4,1,5,5,32,10.0,satisfied +7140,51170,Female,Loyal Customer,40,Personal Travel,Eco,199,3,4,3,3,5,3,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +7141,128002,Female,Loyal Customer,61,Personal Travel,Eco,1488,1,5,1,3,1,1,1,5,2,2,1,1,5,1,129,148.0,neutral or dissatisfied +7142,128486,Female,Loyal Customer,49,Personal Travel,Eco,325,4,4,2,3,4,4,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +7143,25000,Male,Loyal Customer,34,Personal Travel,Eco,692,2,2,2,3,2,2,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +7144,60294,Female,Loyal Customer,21,Personal Travel,Eco,783,1,4,2,4,5,2,5,5,3,3,4,5,4,5,0,14.0,neutral or dissatisfied +7145,95762,Female,Loyal Customer,12,Personal Travel,Eco,453,4,4,4,3,5,4,5,5,3,2,4,5,4,5,28,10.0,neutral or dissatisfied +7146,15552,Male,Loyal Customer,53,Business travel,Business,2455,1,2,2,2,1,1,1,1,4,3,2,1,3,1,182,155.0,neutral or dissatisfied +7147,108166,Female,Loyal Customer,39,Personal Travel,Eco,990,4,4,4,1,4,4,1,4,5,4,4,3,4,4,5,0.0,neutral or dissatisfied +7148,30,Male,Loyal Customer,48,Business travel,Business,3088,4,4,5,4,3,4,4,4,4,4,4,3,4,3,0,12.0,satisfied +7149,109783,Female,Loyal Customer,70,Personal Travel,Business,1052,3,5,3,3,2,5,5,1,1,3,1,5,1,4,16,24.0,neutral or dissatisfied +7150,6727,Male,Loyal Customer,40,Business travel,Business,3906,5,5,5,5,2,4,4,5,5,5,5,5,5,4,7,1.0,satisfied +7151,67064,Female,Loyal Customer,36,Business travel,Business,1121,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +7152,116610,Male,Loyal Customer,39,Business travel,Business,342,5,5,5,5,5,4,4,5,5,4,5,4,5,3,5,7.0,satisfied +7153,40547,Female,Loyal Customer,43,Business travel,Business,3580,4,4,4,4,3,5,3,5,5,5,5,4,5,5,0,0.0,satisfied +7154,121904,Male,Loyal Customer,54,Personal Travel,Eco,337,3,4,2,2,4,2,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +7155,9127,Male,Loyal Customer,53,Personal Travel,Eco,765,3,5,3,3,2,3,1,2,3,3,5,5,4,2,21,0.0,neutral or dissatisfied +7156,78181,Male,Loyal Customer,71,Business travel,Eco,259,3,1,1,1,3,3,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +7157,23351,Female,Loyal Customer,67,Business travel,Eco Plus,979,4,1,3,1,3,1,1,4,4,4,4,5,4,4,0,0.0,satisfied +7158,124709,Male,Loyal Customer,30,Personal Travel,Eco,399,5,5,5,5,1,5,1,1,3,5,1,4,5,1,0,0.0,satisfied +7159,110025,Female,Loyal Customer,38,Personal Travel,Eco,1142,3,4,3,5,5,3,5,5,5,3,3,5,4,5,0,0.0,neutral or dissatisfied +7160,66407,Male,Loyal Customer,24,Business travel,Business,1562,2,4,4,4,2,2,2,2,2,1,3,1,3,2,0,3.0,neutral or dissatisfied +7161,38605,Male,Loyal Customer,17,Business travel,Business,231,3,1,1,1,3,3,3,3,2,5,4,3,3,3,17,15.0,neutral or dissatisfied +7162,92626,Male,disloyal Customer,28,Business travel,Eco,453,4,3,5,3,1,5,3,1,3,5,3,1,3,1,0,43.0,neutral or dissatisfied +7163,48964,Female,Loyal Customer,57,Business travel,Eco,337,5,2,1,2,1,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +7164,127329,Male,Loyal Customer,48,Business travel,Business,507,3,3,3,3,3,4,5,5,5,5,5,3,5,5,8,0.0,satisfied +7165,9708,Male,Loyal Customer,34,Personal Travel,Eco,277,2,2,2,3,2,2,2,2,2,1,3,2,4,2,44,53.0,neutral or dissatisfied +7166,107189,Female,Loyal Customer,37,Business travel,Eco,268,3,4,4,4,3,3,3,3,1,3,3,1,3,3,20,15.0,neutral or dissatisfied +7167,70421,Female,disloyal Customer,23,Business travel,Eco,187,1,3,1,4,2,1,2,2,3,4,4,1,4,2,16,14.0,neutral or dissatisfied +7168,111668,Female,disloyal Customer,12,Business travel,Eco,991,1,1,1,3,2,1,2,2,1,4,3,2,4,2,62,53.0,neutral or dissatisfied +7169,44086,Male,Loyal Customer,54,Business travel,Business,473,4,4,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +7170,12010,Female,Loyal Customer,43,Business travel,Business,3121,3,5,5,5,2,2,3,3,3,3,3,3,3,4,9,8.0,neutral or dissatisfied +7171,35708,Male,Loyal Customer,53,Personal Travel,Eco,2475,2,3,2,3,2,3,3,3,4,2,2,3,1,3,0,0.0,neutral or dissatisfied +7172,96426,Male,Loyal Customer,53,Business travel,Business,302,1,1,1,1,4,4,4,4,4,4,4,3,4,5,68,64.0,satisfied +7173,27269,Male,disloyal Customer,34,Business travel,Business,697,2,2,2,4,2,2,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +7174,24035,Female,Loyal Customer,15,Personal Travel,Eco,427,2,0,2,4,2,2,3,2,3,3,4,4,5,2,1,0.0,neutral or dissatisfied +7175,106737,Male,disloyal Customer,39,Business travel,Business,829,4,5,5,4,1,5,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +7176,60918,Female,Loyal Customer,13,Personal Travel,Business,888,2,2,2,3,4,2,4,4,1,4,3,3,3,4,7,1.0,neutral or dissatisfied +7177,80994,Male,disloyal Customer,18,Business travel,Eco,228,2,2,2,3,1,2,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +7178,2309,Female,disloyal Customer,41,Business travel,Business,291,2,2,2,4,5,4,2,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +7179,65080,Female,Loyal Customer,46,Personal Travel,Eco,247,4,4,4,3,4,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +7180,84376,Female,Loyal Customer,27,Business travel,Business,606,2,2,2,2,2,2,2,2,3,4,4,3,3,2,0,66.0,neutral or dissatisfied +7181,78219,Male,Loyal Customer,14,Personal Travel,Eco,153,2,5,2,3,5,2,4,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +7182,111287,Male,Loyal Customer,11,Personal Travel,Eco,479,2,4,1,3,4,1,1,4,3,3,3,5,1,4,0,5.0,neutral or dissatisfied +7183,125630,Male,disloyal Customer,35,Business travel,Business,899,3,4,4,3,3,4,3,3,3,4,4,5,4,3,17,21.0,neutral or dissatisfied +7184,26563,Female,Loyal Customer,42,Business travel,Business,3671,1,1,1,1,5,4,4,4,4,4,4,3,4,3,14,10.0,satisfied +7185,63782,Male,Loyal Customer,56,Business travel,Business,1721,2,1,1,1,4,3,4,2,2,2,2,4,2,3,41,45.0,neutral or dissatisfied +7186,95379,Female,Loyal Customer,18,Personal Travel,Eco,189,3,1,0,3,1,0,1,1,3,4,2,3,3,1,15,8.0,neutral or dissatisfied +7187,44172,Female,Loyal Customer,52,Business travel,Business,1831,5,3,5,5,1,5,2,4,4,4,4,4,4,5,0,6.0,satisfied +7188,87891,Female,Loyal Customer,50,Business travel,Business,2803,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +7189,1086,Female,Loyal Customer,50,Personal Travel,Eco,247,2,5,2,5,2,4,4,3,3,2,3,4,3,5,11,17.0,neutral or dissatisfied +7190,65934,Female,Loyal Customer,41,Personal Travel,Eco,569,2,5,2,4,2,2,2,2,1,5,3,3,1,2,0,0.0,neutral or dissatisfied +7191,33934,Male,Loyal Customer,45,Business travel,Business,3576,4,4,4,4,1,5,1,5,5,5,5,3,5,1,0,17.0,satisfied +7192,123369,Female,Loyal Customer,42,Business travel,Business,2704,4,5,5,5,3,4,3,4,4,4,4,4,4,4,0,2.0,neutral or dissatisfied +7193,57114,Male,disloyal Customer,29,Business travel,Eco,1222,3,3,3,3,3,3,1,3,1,1,4,3,3,3,3,0.0,neutral or dissatisfied +7194,18330,Male,Loyal Customer,39,Business travel,Business,554,3,3,3,3,3,3,1,3,3,3,3,1,3,5,31,11.0,satisfied +7195,5314,Male,Loyal Customer,59,Business travel,Eco Plus,190,2,4,4,4,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +7196,106315,Male,Loyal Customer,57,Personal Travel,Eco,998,3,3,3,5,3,3,3,3,5,5,1,1,1,3,25,7.0,neutral or dissatisfied +7197,126129,Male,Loyal Customer,38,Business travel,Business,1517,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +7198,94269,Female,Loyal Customer,44,Business travel,Business,323,3,3,3,3,3,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +7199,47918,Female,Loyal Customer,35,Personal Travel,Eco,329,3,3,2,1,3,2,3,3,3,5,4,1,4,3,59,39.0,neutral or dissatisfied +7200,37208,Male,disloyal Customer,25,Business travel,Eco,680,5,5,5,2,3,5,1,3,3,5,3,2,2,3,0,0.0,satisfied +7201,63861,Male,disloyal Customer,27,Business travel,Business,1192,2,2,2,4,3,2,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +7202,123461,Male,Loyal Customer,44,Business travel,Business,2296,3,3,3,3,5,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +7203,76207,Female,Loyal Customer,48,Business travel,Business,2422,1,1,1,1,4,5,5,5,5,5,5,5,5,3,25,42.0,satisfied +7204,24815,Male,disloyal Customer,40,Business travel,Eco,894,3,3,3,5,1,3,1,1,5,2,5,5,2,1,7,0.0,neutral or dissatisfied +7205,59027,Male,Loyal Customer,47,Business travel,Business,1846,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +7206,105336,Female,Loyal Customer,48,Business travel,Business,3927,4,4,4,4,2,5,4,3,3,4,3,5,3,4,32,18.0,satisfied +7207,103310,Male,Loyal Customer,35,Business travel,Business,1371,1,1,1,1,4,5,4,3,3,4,3,3,3,5,13,23.0,satisfied +7208,107047,Female,disloyal Customer,24,Business travel,Business,395,3,3,3,3,5,3,5,5,3,5,4,2,4,5,52,48.0,neutral or dissatisfied +7209,24086,Female,Loyal Customer,52,Personal Travel,Eco,854,5,4,5,2,4,4,5,3,3,5,3,4,3,4,0,0.0,satisfied +7210,15055,Male,Loyal Customer,63,Business travel,Eco,116,4,4,4,4,4,4,4,4,3,2,4,1,4,4,12,0.0,neutral or dissatisfied +7211,6519,Male,Loyal Customer,11,Business travel,Business,2421,3,2,2,2,3,3,3,3,2,2,3,2,4,3,50,91.0,neutral or dissatisfied +7212,74095,Male,Loyal Customer,60,Business travel,Business,641,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +7213,68475,Male,disloyal Customer,44,Business travel,Eco,1303,1,1,1,4,2,1,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +7214,30922,Female,Loyal Customer,41,Personal Travel,Eco,896,1,2,1,4,3,1,4,3,4,5,4,4,4,3,4,8.0,neutral or dissatisfied +7215,37130,Male,Loyal Customer,47,Business travel,Business,1189,2,1,1,1,5,4,3,2,2,2,2,3,2,2,0,7.0,neutral or dissatisfied +7216,18238,Female,disloyal Customer,37,Business travel,Eco,228,3,4,3,3,5,3,5,5,3,4,3,4,4,5,0,0.0,neutral or dissatisfied +7217,111873,Female,Loyal Customer,59,Business travel,Business,2984,4,4,2,4,5,4,5,5,5,4,5,5,5,3,7,3.0,satisfied +7218,95281,Female,Loyal Customer,19,Personal Travel,Eco,496,3,5,3,5,1,3,1,1,1,4,2,2,1,1,0,0.0,neutral or dissatisfied +7219,126452,Male,Loyal Customer,47,Business travel,Business,1788,2,2,2,2,4,3,5,4,4,5,4,3,4,5,64,46.0,satisfied +7220,16895,Male,Loyal Customer,37,Personal Travel,Eco,746,5,2,5,4,3,5,3,3,2,5,4,1,3,3,0,0.0,satisfied +7221,1500,Male,Loyal Customer,59,Personal Travel,Eco,737,1,2,1,4,3,1,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +7222,74464,Female,Loyal Customer,37,Business travel,Business,1171,3,1,1,1,1,2,3,3,3,3,3,2,3,4,20,14.0,neutral or dissatisfied +7223,87756,Female,Loyal Customer,61,Business travel,Business,2897,4,4,4,4,2,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +7224,183,Male,disloyal Customer,26,Business travel,Business,213,3,0,3,3,2,3,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +7225,97948,Male,Loyal Customer,48,Business travel,Business,391,1,1,1,1,4,5,4,5,5,5,5,4,5,5,0,,satisfied +7226,15464,Female,Loyal Customer,73,Business travel,Business,399,2,2,2,2,2,2,4,5,5,5,5,3,5,4,0,0.0,satisfied +7227,75626,Male,Loyal Customer,70,Business travel,Eco Plus,337,3,5,4,5,3,3,3,3,3,3,2,1,3,3,0,0.0,neutral or dissatisfied +7228,45545,Male,Loyal Customer,69,Personal Travel,Eco,508,5,5,5,3,3,5,3,3,4,5,5,4,5,3,0,0.0,satisfied +7229,78733,Female,Loyal Customer,47,Business travel,Business,3014,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +7230,110356,Male,Loyal Customer,47,Business travel,Eco,919,2,2,2,2,2,2,2,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +7231,54229,Female,Loyal Customer,25,Business travel,Eco,1222,5,4,4,4,5,5,4,5,5,2,5,2,5,5,34,11.0,satisfied +7232,70101,Male,Loyal Customer,60,Business travel,Business,3591,5,5,5,5,2,4,4,5,5,5,5,5,5,4,97,108.0,satisfied +7233,38274,Female,Loyal Customer,68,Personal Travel,Eco,1111,2,5,2,2,2,5,5,5,5,2,5,4,5,5,37,29.0,neutral or dissatisfied +7234,2135,Female,Loyal Customer,48,Personal Travel,Eco,431,5,3,5,1,2,5,2,2,2,5,2,2,2,5,13,18.0,satisfied +7235,69343,Male,Loyal Customer,30,Business travel,Business,3462,4,2,4,4,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +7236,45987,Male,Loyal Customer,60,Business travel,Eco,483,4,3,3,3,4,4,4,4,3,2,4,2,2,4,0,6.0,satisfied +7237,27518,Male,Loyal Customer,26,Personal Travel,Eco,671,2,1,2,4,2,2,2,2,1,3,4,4,4,2,22,18.0,neutral or dissatisfied +7238,65383,Female,Loyal Customer,25,Personal Travel,Eco,631,2,5,2,5,1,2,1,1,5,4,5,3,4,1,47,53.0,neutral or dissatisfied +7239,112389,Female,Loyal Customer,22,Business travel,Business,3287,4,4,4,4,4,4,4,4,5,3,5,5,5,4,39,50.0,satisfied +7240,88524,Male,Loyal Customer,52,Personal Travel,Eco,240,2,4,2,2,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +7241,115930,Female,disloyal Customer,23,Business travel,Eco,337,1,1,1,1,4,1,4,4,3,3,2,2,2,4,0,0.0,neutral or dissatisfied +7242,92128,Male,Loyal Customer,68,Personal Travel,Eco,1454,1,4,1,4,3,1,3,3,3,3,4,3,4,3,23,4.0,neutral or dissatisfied +7243,96649,Male,Loyal Customer,60,Business travel,Business,3294,2,4,2,4,4,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +7244,17490,Female,Loyal Customer,47,Business travel,Business,3709,3,3,3,3,4,5,2,5,5,5,5,4,5,2,0,0.0,satisfied +7245,117715,Male,Loyal Customer,16,Personal Travel,Eco,1009,5,5,5,4,4,5,4,4,3,2,4,5,4,4,26,15.0,satisfied +7246,44651,Female,Loyal Customer,53,Business travel,Business,67,3,3,3,3,2,5,1,5,5,5,5,1,5,1,0,0.0,satisfied +7247,9918,Female,Loyal Customer,54,Business travel,Eco,515,3,4,4,4,2,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +7248,87686,Male,Loyal Customer,28,Personal Travel,Eco,606,4,4,4,3,4,4,4,4,5,4,4,3,5,4,35,29.0,satisfied +7249,12293,Male,disloyal Customer,49,Business travel,Eco,190,3,0,3,2,5,3,5,5,1,3,4,5,2,5,0,0.0,neutral or dissatisfied +7250,105858,Female,Loyal Customer,28,Business travel,Eco Plus,842,1,3,3,3,1,1,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +7251,27530,Male,Loyal Customer,47,Personal Travel,Eco,978,4,5,4,3,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +7252,100435,Female,Loyal Customer,69,Business travel,Eco Plus,1620,2,1,1,1,5,3,4,2,2,2,2,3,2,4,36,8.0,neutral or dissatisfied +7253,69698,Male,Loyal Customer,53,Business travel,Business,1372,4,4,4,4,5,5,4,5,5,4,5,4,5,4,0,4.0,satisfied +7254,9940,Male,disloyal Customer,25,Business travel,Eco,508,1,4,1,4,4,1,4,4,1,1,3,1,3,4,10,4.0,neutral or dissatisfied +7255,2677,Female,Loyal Customer,53,Personal Travel,Eco,622,2,4,2,3,5,4,4,4,4,2,4,4,4,3,17,13.0,neutral or dissatisfied +7256,64407,Male,Loyal Customer,43,Business travel,Eco Plus,1172,1,3,3,3,1,1,1,1,4,1,3,3,3,1,0,5.0,neutral or dissatisfied +7257,108380,Male,Loyal Customer,38,Personal Travel,Eco,1728,2,5,2,1,5,2,5,5,4,2,3,3,5,5,14,9.0,neutral or dissatisfied +7258,60717,Female,Loyal Customer,22,Business travel,Eco,1605,2,1,1,1,2,1,2,3,4,4,4,2,2,2,138,144.0,neutral or dissatisfied +7259,94771,Female,Loyal Customer,44,Business travel,Business,192,1,3,3,3,5,2,2,3,3,3,1,4,3,3,13,12.0,neutral or dissatisfied +7260,83492,Female,Loyal Customer,48,Business travel,Eco,946,4,5,5,5,2,1,2,4,4,4,4,3,4,1,0,23.0,neutral or dissatisfied +7261,115738,Male,Loyal Customer,80,Business travel,Business,3521,3,5,5,5,4,3,4,3,3,3,3,3,3,2,30,29.0,neutral or dissatisfied +7262,51459,Female,Loyal Customer,8,Personal Travel,Eco Plus,77,1,4,1,3,3,1,4,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +7263,81432,Female,Loyal Customer,47,Personal Travel,Eco,393,3,4,3,4,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +7264,15351,Female,Loyal Customer,66,Personal Travel,Business,164,3,4,3,3,3,5,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +7265,51895,Male,Loyal Customer,43,Business travel,Business,2610,2,5,5,5,5,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +7266,6102,Male,Loyal Customer,57,Business travel,Business,491,4,4,4,4,3,4,4,3,3,3,3,5,3,3,4,2.0,satisfied +7267,116705,Female,disloyal Customer,24,Business travel,Eco,337,3,0,3,2,1,3,1,1,1,3,1,5,3,1,58,65.0,neutral or dissatisfied +7268,91149,Male,Loyal Customer,28,Personal Travel,Eco,581,3,3,3,2,5,3,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +7269,48945,Male,Loyal Customer,49,Business travel,Eco,326,5,2,2,2,5,5,5,5,1,2,1,3,5,5,0,0.0,satisfied +7270,124798,Female,Loyal Customer,56,Business travel,Business,2793,2,2,2,2,2,2,2,1,5,2,2,2,3,2,144,187.0,neutral or dissatisfied +7271,116582,Male,Loyal Customer,54,Business travel,Business,1855,4,4,4,4,2,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +7272,77631,Female,Loyal Customer,40,Business travel,Business,2683,1,3,3,3,2,4,4,1,1,1,1,4,1,2,114,107.0,neutral or dissatisfied +7273,89603,Female,Loyal Customer,26,Business travel,Business,1977,1,1,1,1,4,4,4,4,3,2,4,4,5,4,60,47.0,satisfied +7274,109259,Female,Loyal Customer,48,Business travel,Eco Plus,612,3,4,4,4,2,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +7275,21502,Female,Loyal Customer,52,Personal Travel,Eco,306,2,5,2,4,4,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +7276,31517,Female,disloyal Customer,8,Business travel,Eco,776,1,1,1,4,1,4,4,2,4,4,4,4,1,4,154,180.0,neutral or dissatisfied +7277,30544,Male,Loyal Customer,28,Business travel,Eco,955,5,2,2,2,5,5,5,5,5,5,5,3,5,5,6,8.0,satisfied +7278,75791,Female,Loyal Customer,58,Personal Travel,Eco,868,2,3,2,3,4,3,4,5,5,2,1,3,5,3,0,0.0,neutral or dissatisfied +7279,108967,Male,Loyal Customer,30,Personal Travel,Eco,655,2,0,3,1,3,3,2,3,1,4,5,5,5,3,0,0.0,neutral or dissatisfied +7280,54037,Male,disloyal Customer,36,Business travel,Eco,1416,3,3,3,2,3,3,5,3,5,2,3,5,1,3,22,0.0,neutral or dissatisfied +7281,37616,Female,Loyal Customer,43,Personal Travel,Eco,1047,2,4,1,3,5,5,4,1,1,1,1,5,1,4,29,23.0,neutral or dissatisfied +7282,60966,Male,Loyal Customer,74,Business travel,Eco,488,2,3,3,3,2,2,2,2,4,5,3,3,4,2,0,7.0,neutral or dissatisfied +7283,56311,Male,Loyal Customer,63,Personal Travel,Business,200,4,4,4,2,5,5,2,5,5,4,1,5,5,3,35,34.0,neutral or dissatisfied +7284,67390,Male,disloyal Customer,26,Business travel,Business,592,2,1,1,2,3,1,3,3,5,4,5,4,4,3,112,125.0,neutral or dissatisfied +7285,102548,Male,Loyal Customer,62,Personal Travel,Eco,236,3,5,3,3,5,3,5,5,5,5,4,4,4,5,8,11.0,neutral or dissatisfied +7286,81209,Female,Loyal Customer,31,Business travel,Business,1426,2,2,2,2,5,5,5,5,3,4,5,5,5,5,5,4.0,satisfied +7287,107775,Male,Loyal Customer,62,Business travel,Eco Plus,405,2,2,2,2,2,2,2,2,3,1,4,3,3,2,1,2.0,neutral or dissatisfied +7288,40224,Male,Loyal Customer,51,Business travel,Business,3702,2,5,5,5,3,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +7289,77974,Male,Loyal Customer,33,Business travel,Eco,214,1,4,4,4,1,1,1,1,4,5,3,4,3,1,76,76.0,neutral or dissatisfied +7290,81538,Female,Loyal Customer,38,Personal Travel,Eco,1124,3,5,3,3,3,3,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +7291,34640,Female,Loyal Customer,28,Personal Travel,Eco,541,4,5,4,3,4,4,4,4,4,4,5,5,4,4,73,61.0,neutral or dissatisfied +7292,50795,Female,Loyal Customer,47,Personal Travel,Eco,110,3,2,3,4,5,4,3,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +7293,33478,Female,Loyal Customer,34,Business travel,Business,2422,3,3,3,3,2,5,5,4,4,4,4,1,4,4,34,29.0,satisfied +7294,33437,Male,Loyal Customer,58,Business travel,Eco,2614,1,5,5,5,1,1,1,3,1,4,4,1,1,1,0,0.0,neutral or dissatisfied +7295,121510,Female,disloyal Customer,18,Business travel,Eco,1009,2,2,2,4,4,2,4,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +7296,21506,Female,Loyal Customer,38,Personal Travel,Eco,331,3,5,3,3,5,3,5,5,5,3,2,5,1,5,67,59.0,neutral or dissatisfied +7297,128527,Male,Loyal Customer,57,Personal Travel,Eco,355,3,2,3,4,3,3,5,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +7298,111074,Female,Loyal Customer,18,Personal Travel,Eco,197,1,5,1,5,1,1,1,1,5,2,5,2,2,1,15,34.0,neutral or dissatisfied +7299,89180,Male,Loyal Customer,18,Personal Travel,Eco,1947,3,5,3,1,3,3,3,3,4,3,4,5,5,3,88,83.0,neutral or dissatisfied +7300,113220,Male,disloyal Customer,27,Business travel,Business,236,2,2,2,1,4,2,3,4,4,4,4,3,4,4,7,6.0,neutral or dissatisfied +7301,17803,Male,Loyal Customer,45,Business travel,Eco,986,4,2,2,2,4,4,4,4,5,1,1,5,3,4,0,0.0,satisfied +7302,9713,Female,Loyal Customer,55,Personal Travel,Eco,277,2,0,2,3,5,5,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +7303,26576,Female,Loyal Customer,50,Business travel,Eco,581,2,3,3,3,3,4,4,2,2,2,2,4,2,4,0,1.0,neutral or dissatisfied +7304,10982,Female,Loyal Customer,37,Business travel,Eco,429,2,4,4,4,2,2,2,2,2,4,4,1,3,2,0,0.0,neutral or dissatisfied +7305,112205,Female,Loyal Customer,34,Personal Travel,Eco,649,4,5,4,1,3,4,2,3,2,1,5,2,4,3,0,0.0,neutral or dissatisfied +7306,99478,Female,Loyal Customer,50,Business travel,Business,3833,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +7307,57547,Female,Loyal Customer,44,Business travel,Business,1748,1,1,4,1,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +7308,97000,Male,Loyal Customer,19,Personal Travel,Eco,359,3,4,3,3,5,3,2,5,2,3,4,4,2,5,7,2.0,neutral or dissatisfied +7309,129294,Female,Loyal Customer,70,Personal Travel,Eco,550,1,4,1,4,2,5,5,3,3,1,3,3,3,5,0,0.0,neutral or dissatisfied +7310,97666,Female,Loyal Customer,39,Business travel,Business,3563,1,4,4,4,4,4,4,1,1,1,1,2,1,3,40,41.0,neutral or dissatisfied +7311,27501,Male,disloyal Customer,38,Business travel,Eco,578,2,4,3,3,5,3,5,5,3,5,3,3,4,5,0,9.0,neutral or dissatisfied +7312,26140,Female,Loyal Customer,30,Business travel,Business,3013,1,1,1,1,5,5,5,5,1,3,3,1,2,5,13,3.0,satisfied +7313,122096,Female,Loyal Customer,27,Personal Travel,Eco,130,2,4,2,3,5,2,3,5,2,2,1,1,3,5,5,0.0,neutral or dissatisfied +7314,27017,Female,Loyal Customer,39,Personal Travel,Eco,867,2,4,2,1,3,2,3,3,3,3,5,3,5,3,40,51.0,neutral or dissatisfied +7315,110457,Male,Loyal Customer,57,Personal Travel,Eco,842,1,4,1,2,3,1,3,3,3,2,4,5,2,3,0,0.0,neutral or dissatisfied +7316,38027,Female,Loyal Customer,62,Business travel,Eco,1237,3,4,4,4,5,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +7317,107928,Male,disloyal Customer,24,Business travel,Eco,611,1,0,0,2,1,0,1,1,3,3,4,3,4,1,1,0.0,neutral or dissatisfied +7318,18601,Female,Loyal Customer,38,Business travel,Business,2947,5,5,4,5,2,1,3,4,4,5,3,3,4,1,10,3.0,satisfied +7319,45268,Female,disloyal Customer,22,Business travel,Eco,188,3,3,3,4,4,3,1,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +7320,64468,Male,Loyal Customer,40,Business travel,Business,190,2,2,2,2,3,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +7321,57959,Female,Loyal Customer,54,Business travel,Business,1670,2,2,2,2,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7322,106772,Male,Loyal Customer,66,Personal Travel,Eco,837,2,5,2,3,3,2,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +7323,72963,Female,Loyal Customer,55,Business travel,Business,1096,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +7324,115342,Female,Loyal Customer,41,Business travel,Business,3623,5,5,3,5,4,4,4,4,4,4,4,3,4,3,17,0.0,satisfied +7325,47105,Male,Loyal Customer,31,Business travel,Eco Plus,639,2,5,5,5,2,2,2,2,4,4,4,3,3,2,2,0.0,neutral or dissatisfied +7326,57519,Male,Loyal Customer,31,Business travel,Business,3826,2,2,2,2,5,5,5,5,4,4,5,3,5,5,0,0.0,satisfied +7327,112198,Male,Loyal Customer,45,Business travel,Business,649,1,1,1,1,2,4,4,5,5,5,5,3,5,5,19,21.0,satisfied +7328,13816,Male,Loyal Customer,51,Business travel,Business,228,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,3.0,satisfied +7329,86452,Male,Loyal Customer,36,Business travel,Business,762,4,4,4,4,4,4,5,3,3,3,3,4,3,4,0,14.0,satisfied +7330,113262,Male,Loyal Customer,49,Business travel,Business,258,3,1,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +7331,18626,Female,Loyal Customer,25,Personal Travel,Eco,285,3,4,3,4,2,3,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +7332,25420,Male,disloyal Customer,22,Business travel,Eco Plus,590,4,2,4,1,5,4,5,5,1,5,2,1,2,5,0,0.0,neutral or dissatisfied +7333,117393,Male,disloyal Customer,62,Business travel,Business,544,2,2,2,2,1,2,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +7334,12618,Female,Loyal Customer,70,Business travel,Business,402,1,1,1,1,2,2,1,4,4,4,4,3,4,4,0,0.0,satisfied +7335,26952,Male,Loyal Customer,30,Business travel,Eco Plus,2402,1,1,1,1,1,1,1,1,1,2,4,1,3,1,0,15.0,neutral or dissatisfied +7336,115171,Female,Loyal Customer,41,Business travel,Business,1991,5,5,3,5,3,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +7337,52028,Male,Loyal Customer,20,Personal Travel,Eco,328,4,5,4,4,1,4,1,1,5,2,5,1,1,1,0,0.0,neutral or dissatisfied +7338,46207,Male,Loyal Customer,59,Business travel,Business,679,3,2,2,2,2,3,4,3,3,3,3,1,3,3,3,0.0,neutral or dissatisfied +7339,71273,Male,Loyal Customer,39,Personal Travel,Eco,733,2,3,2,1,3,2,2,3,5,5,4,4,1,3,0,0.0,neutral or dissatisfied +7340,31922,Female,Loyal Customer,53,Business travel,Business,1921,3,3,3,3,4,5,4,5,5,5,4,3,5,3,0,7.0,satisfied +7341,85931,Female,Loyal Customer,43,Business travel,Business,3179,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +7342,1402,Female,Loyal Customer,47,Personal Travel,Eco Plus,482,4,1,2,2,2,2,2,2,2,2,1,1,2,2,0,0.0,neutral or dissatisfied +7343,22787,Female,Loyal Customer,39,Business travel,Business,2606,1,1,1,1,5,1,2,5,5,5,5,2,5,2,15,3.0,satisfied +7344,94624,Male,disloyal Customer,48,Business travel,Business,189,1,1,1,1,3,1,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +7345,56715,Male,Loyal Customer,59,Personal Travel,Eco,997,2,4,2,1,4,2,2,4,3,5,4,3,4,4,1,0.0,neutral or dissatisfied +7346,103372,Female,Loyal Customer,60,Business travel,Business,3824,1,1,1,1,5,5,5,4,4,4,4,3,4,3,21,0.0,satisfied +7347,64059,Male,disloyal Customer,19,Business travel,Eco,919,2,2,2,3,5,2,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +7348,42218,Female,disloyal Customer,36,Business travel,Eco,748,2,2,2,2,5,2,5,5,3,5,3,2,2,5,0,0.0,neutral or dissatisfied +7349,25798,Male,Loyal Customer,63,Personal Travel,Eco,762,2,4,2,4,1,2,2,1,2,2,4,2,3,1,0,0.0,neutral or dissatisfied +7350,4795,Female,Loyal Customer,67,Personal Travel,Eco,403,2,4,2,4,4,4,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +7351,104240,Female,Loyal Customer,55,Business travel,Business,3740,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +7352,36032,Female,Loyal Customer,23,Business travel,Eco,413,4,4,4,4,4,4,4,4,3,2,2,5,3,4,0,0.0,satisfied +7353,98929,Male,disloyal Customer,37,Business travel,Business,543,3,3,3,1,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +7354,123740,Female,disloyal Customer,36,Business travel,Business,96,3,3,3,2,2,3,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +7355,43308,Male,Loyal Customer,45,Business travel,Business,3908,5,5,2,5,5,4,1,4,4,4,4,2,4,2,0,0.0,satisfied +7356,87209,Female,Loyal Customer,16,Personal Travel,Eco,946,2,5,2,5,4,2,4,4,3,1,2,3,4,4,0,0.0,neutral or dissatisfied +7357,120397,Female,disloyal Customer,26,Business travel,Business,366,2,0,2,4,1,2,1,1,3,5,4,3,4,1,1,0.0,neutral or dissatisfied +7358,94225,Male,disloyal Customer,49,Business travel,Business,239,4,4,4,5,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +7359,108113,Female,disloyal Customer,25,Business travel,Business,997,0,2,0,2,3,0,3,3,5,5,5,4,5,3,38,49.0,satisfied +7360,66395,Male,Loyal Customer,47,Business travel,Business,1562,5,5,5,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +7361,94465,Male,Loyal Customer,40,Business travel,Eco,562,4,5,5,5,4,4,4,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +7362,19646,Female,Loyal Customer,27,Personal Travel,Eco Plus,531,2,5,5,1,2,5,2,2,4,2,4,5,4,2,2,0.0,neutral or dissatisfied +7363,97506,Female,Loyal Customer,70,Personal Travel,Eco,756,3,4,3,4,3,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +7364,101588,Female,Loyal Customer,10,Personal Travel,Eco,1099,3,3,3,5,3,3,3,3,2,2,1,3,3,3,66,57.0,neutral or dissatisfied +7365,38060,Male,Loyal Customer,31,Business travel,Business,1982,2,2,2,2,5,5,5,5,5,4,3,5,4,5,0,0.0,satisfied +7366,93449,Female,Loyal Customer,24,Personal Travel,Eco,671,2,3,2,2,4,2,4,4,4,3,4,3,3,4,19,4.0,neutral or dissatisfied +7367,729,Female,disloyal Customer,37,Business travel,Business,164,2,2,2,4,3,2,3,3,3,5,5,3,4,3,63,60.0,satisfied +7368,51448,Male,Loyal Customer,33,Personal Travel,Eco Plus,158,2,4,2,5,2,2,2,2,4,3,5,3,4,2,13,8.0,neutral or dissatisfied +7369,87894,Male,Loyal Customer,46,Business travel,Business,271,1,1,1,1,2,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +7370,37448,Male,Loyal Customer,54,Business travel,Business,944,5,5,5,5,4,4,4,1,1,5,5,4,3,4,221,206.0,satisfied +7371,102316,Male,Loyal Customer,37,Business travel,Business,1633,2,2,5,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7372,74785,Male,Loyal Customer,45,Business travel,Business,3366,5,5,5,5,3,4,5,5,5,5,5,5,5,3,0,3.0,satisfied +7373,15339,Male,Loyal Customer,45,Personal Travel,Eco Plus,599,2,1,2,3,5,2,5,5,1,5,3,3,3,5,0,0.0,neutral or dissatisfied +7374,42195,Male,Loyal Customer,51,Business travel,Business,451,2,2,2,2,3,5,3,4,4,5,4,4,4,4,89,84.0,satisfied +7375,117133,Female,Loyal Customer,45,Personal Travel,Eco,646,4,3,3,3,3,4,1,1,1,3,1,4,1,3,37,22.0,neutral or dissatisfied +7376,96849,Female,disloyal Customer,31,Business travel,Eco,1041,2,2,2,3,4,2,4,4,1,5,3,1,4,4,31,23.0,neutral or dissatisfied +7377,387,Female,Loyal Customer,54,Business travel,Business,2722,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7378,100312,Male,Loyal Customer,41,Business travel,Business,971,5,5,5,5,3,4,5,5,5,5,5,5,5,4,16,15.0,satisfied +7379,81237,Female,Loyal Customer,29,Personal Travel,Eco,223,2,4,2,3,5,2,5,5,4,5,5,3,5,5,6,0.0,neutral or dissatisfied +7380,117885,Male,Loyal Customer,49,Business travel,Business,255,3,3,3,3,2,4,4,5,5,5,5,4,5,5,40,41.0,satisfied +7381,70094,Male,Loyal Customer,56,Business travel,Business,2776,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +7382,79458,Male,Loyal Customer,41,Business travel,Business,2286,4,4,4,4,4,5,4,5,5,5,5,4,5,5,55,19.0,satisfied +7383,83738,Female,Loyal Customer,54,Personal Travel,Business,1183,2,4,2,2,4,3,5,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +7384,24459,Male,Loyal Customer,38,Business travel,Business,3634,1,1,1,1,1,1,2,5,5,5,5,2,5,1,0,0.0,satisfied +7385,5839,Female,disloyal Customer,47,Business travel,Eco Plus,273,3,3,3,1,5,3,5,5,4,5,5,5,3,5,28,31.0,neutral or dissatisfied +7386,6198,Female,Loyal Customer,59,Personal Travel,Eco Plus,409,5,3,2,4,2,4,4,4,4,3,3,4,1,4,77,144.0,satisfied +7387,10759,Female,Loyal Customer,55,Business travel,Eco,667,1,1,1,1,5,4,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +7388,91538,Male,disloyal Customer,42,Business travel,Business,680,5,5,5,1,4,5,4,4,4,3,5,5,4,4,29,28.0,satisfied +7389,35386,Male,Loyal Customer,38,Business travel,Eco,605,5,1,1,1,5,5,5,5,4,1,5,1,5,5,7,12.0,satisfied +7390,63678,Male,Loyal Customer,53,Business travel,Business,2095,4,4,4,4,5,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +7391,115918,Male,disloyal Customer,30,Business travel,Eco,333,1,3,1,4,5,1,5,5,2,5,4,4,3,5,0,0.0,neutral or dissatisfied +7392,110887,Male,Loyal Customer,25,Business travel,Business,1847,1,1,1,1,5,5,5,5,3,4,5,4,5,5,1,0.0,satisfied +7393,78256,Male,Loyal Customer,57,Business travel,Business,3786,5,5,5,5,5,5,5,3,3,5,4,5,4,5,159,149.0,satisfied +7394,17651,Male,Loyal Customer,30,Business travel,Business,1627,1,1,1,1,4,4,4,4,3,5,5,2,5,4,88,117.0,satisfied +7395,12999,Male,Loyal Customer,52,Business travel,Eco,374,4,1,2,1,4,4,4,4,2,4,3,3,3,4,0,0.0,satisfied +7396,65108,Male,Loyal Customer,40,Personal Travel,Eco,469,3,5,3,3,2,3,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +7397,78177,Female,Loyal Customer,59,Business travel,Eco,192,2,2,2,2,3,3,3,1,1,2,1,3,1,4,0,7.0,neutral or dissatisfied +7398,84264,Male,disloyal Customer,22,Business travel,Eco,334,1,4,1,3,3,1,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +7399,46193,Female,Loyal Customer,43,Business travel,Eco,423,4,4,4,4,1,3,3,4,4,4,4,3,4,4,98,91.0,neutral or dissatisfied +7400,31023,Female,Loyal Customer,19,Personal Travel,Eco,391,5,5,5,1,3,5,3,3,5,4,5,3,4,3,0,0.0,satisfied +7401,52549,Male,Loyal Customer,41,Business travel,Business,119,1,1,1,1,3,2,2,4,4,5,4,5,4,2,0,15.0,satisfied +7402,38275,Female,Loyal Customer,67,Personal Travel,Eco,1050,2,5,2,2,3,5,5,4,4,2,4,5,4,3,11,3.0,neutral or dissatisfied +7403,66499,Male,disloyal Customer,22,Business travel,Eco,447,2,4,2,4,5,2,5,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +7404,111723,Female,Loyal Customer,45,Personal Travel,Eco,495,2,1,2,3,4,4,3,2,2,2,2,1,2,4,10,7.0,neutral or dissatisfied +7405,54111,Female,Loyal Customer,24,Business travel,Business,1400,3,1,1,1,3,3,3,3,4,4,4,3,4,3,14,11.0,neutral or dissatisfied +7406,121496,Female,disloyal Customer,42,Business travel,Eco Plus,257,2,2,2,3,2,2,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +7407,73816,Female,Loyal Customer,58,Business travel,Business,1725,2,2,2,2,3,4,4,5,5,5,4,5,5,5,0,0.0,satisfied +7408,94117,Male,Loyal Customer,8,Personal Travel,Business,248,3,4,3,3,1,3,1,1,5,5,4,4,5,1,1,0.0,neutral or dissatisfied +7409,4266,Female,Loyal Customer,72,Business travel,Eco,502,1,4,4,4,3,3,3,1,1,1,1,2,1,2,6,0.0,neutral or dissatisfied +7410,29670,Female,Loyal Customer,27,Personal Travel,Eco,909,3,1,3,3,2,3,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +7411,129534,Male,Loyal Customer,29,Business travel,Business,2583,3,3,3,3,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +7412,28587,Female,Loyal Customer,41,Personal Travel,Eco,2631,4,5,4,3,2,4,2,2,5,2,4,5,4,2,11,0.0,satisfied +7413,41904,Male,disloyal Customer,27,Business travel,Eco,129,3,3,3,3,5,3,4,5,5,5,2,2,3,5,0,5.0,neutral or dissatisfied +7414,95243,Male,Loyal Customer,9,Personal Travel,Eco,496,1,4,1,3,5,1,5,5,5,4,5,5,1,5,0,0.0,neutral or dissatisfied +7415,35178,Male,disloyal Customer,24,Business travel,Business,1118,4,5,4,3,1,4,1,1,3,3,5,2,4,1,0,3.0,satisfied +7416,33835,Male,Loyal Customer,49,Business travel,Eco,1609,5,5,5,5,5,5,5,5,3,1,5,1,5,5,0,0.0,satisfied +7417,31168,Female,Loyal Customer,50,Business travel,Business,516,1,1,5,1,4,2,3,4,4,4,4,3,4,2,0,0.0,satisfied +7418,75534,Female,Loyal Customer,39,Personal Travel,Business,337,5,4,5,3,3,4,4,2,2,5,2,4,2,3,0,0.0,satisfied +7419,11257,Male,Loyal Customer,18,Personal Travel,Eco,270,1,5,0,1,3,0,3,3,3,3,5,4,4,3,26,65.0,neutral or dissatisfied +7420,66738,Female,Loyal Customer,63,Personal Travel,Eco,802,4,4,3,2,5,4,4,4,4,3,4,5,4,3,0,2.0,neutral or dissatisfied +7421,114387,Male,Loyal Customer,46,Business travel,Business,3474,1,1,1,1,5,4,4,4,4,4,4,4,4,4,12,12.0,satisfied +7422,62341,Male,Loyal Customer,43,Business travel,Eco Plus,414,3,5,5,5,3,3,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +7423,18905,Male,Loyal Customer,10,Personal Travel,Eco,551,3,3,3,3,3,3,5,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +7424,16385,Female,Loyal Customer,41,Business travel,Eco,463,5,5,2,5,4,5,4,4,3,1,2,5,5,4,9,1.0,satisfied +7425,48607,Female,Loyal Customer,26,Business travel,Eco Plus,909,3,5,5,5,3,4,3,3,5,4,4,5,1,3,3,2.0,satisfied +7426,27355,Male,Loyal Customer,32,Business travel,Eco,1050,0,1,1,3,2,1,2,2,2,2,5,1,4,2,0,0.0,satisfied +7427,50586,Male,Loyal Customer,64,Personal Travel,Eco,86,3,4,3,1,2,3,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +7428,46279,Female,Loyal Customer,35,Personal Travel,Eco,624,2,4,1,1,4,1,3,4,3,5,5,4,4,4,3,11.0,neutral or dissatisfied +7429,85979,Female,Loyal Customer,59,Business travel,Eco,432,4,5,5,5,4,3,3,4,4,4,4,1,4,1,2,0.0,neutral or dissatisfied +7430,102595,Female,disloyal Customer,35,Business travel,Eco Plus,226,2,2,2,4,1,2,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +7431,68426,Male,Loyal Customer,61,Personal Travel,Eco,1045,3,4,3,3,4,3,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +7432,67720,Male,Loyal Customer,39,Business travel,Business,2401,3,2,2,2,3,3,4,3,3,3,3,2,3,3,0,16.0,neutral or dissatisfied +7433,30543,Male,Loyal Customer,45,Business travel,Business,1028,1,1,1,1,5,5,1,4,4,3,4,3,4,3,1,0.0,satisfied +7434,124197,Female,disloyal Customer,21,Business travel,Eco,1260,3,3,3,4,4,3,4,4,5,3,5,5,4,4,2,0.0,neutral or dissatisfied +7435,43857,Female,Loyal Customer,37,Business travel,Eco,255,3,3,4,3,3,3,3,3,4,3,5,5,1,3,0,0.0,satisfied +7436,12101,Female,Loyal Customer,38,Business travel,Business,2552,3,3,3,3,5,3,1,4,4,3,4,4,4,4,49,68.0,satisfied +7437,91536,Female,Loyal Customer,47,Business travel,Business,680,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +7438,13666,Female,disloyal Customer,38,Business travel,Eco,462,2,0,2,3,1,2,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +7439,12435,Male,Loyal Customer,35,Personal Travel,Eco,285,2,1,2,4,5,2,5,5,4,4,3,4,4,5,0,17.0,neutral or dissatisfied +7440,44357,Male,Loyal Customer,31,Business travel,Business,2906,5,5,5,5,3,3,3,3,2,1,3,2,4,3,20,19.0,satisfied +7441,128340,Male,Loyal Customer,47,Business travel,Business,1510,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,21.0,satisfied +7442,75537,Female,Loyal Customer,38,Business travel,Business,2806,5,5,5,5,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +7443,26009,Male,Loyal Customer,20,Business travel,Eco,425,0,3,0,3,3,0,3,3,2,3,2,5,5,3,0,0.0,satisfied +7444,58943,Female,Loyal Customer,43,Business travel,Eco Plus,888,3,2,2,2,2,2,3,3,3,3,3,2,3,2,17,4.0,neutral or dissatisfied +7445,54324,Female,Loyal Customer,42,Business travel,Business,2988,5,5,5,5,2,2,3,4,4,4,4,1,4,4,0,0.0,satisfied +7446,37459,Female,Loyal Customer,71,Business travel,Business,1590,1,1,4,1,3,2,3,1,1,1,1,3,1,1,25,15.0,neutral or dissatisfied +7447,39602,Male,Loyal Customer,35,Personal Travel,Eco,679,2,4,2,4,5,2,5,5,3,4,4,5,5,5,45,101.0,neutral or dissatisfied +7448,65190,Female,Loyal Customer,64,Personal Travel,Eco,551,3,5,3,5,3,1,2,3,3,3,3,3,3,2,97,95.0,neutral or dissatisfied +7449,121135,Male,Loyal Customer,42,Business travel,Business,2370,4,4,4,4,2,2,2,4,4,5,4,2,5,2,0,0.0,satisfied +7450,104459,Male,Loyal Customer,27,Business travel,Business,1123,4,2,2,2,4,4,4,4,2,4,2,4,3,4,11,35.0,neutral or dissatisfied +7451,12330,Male,Loyal Customer,20,Business travel,Eco,201,5,3,3,3,5,5,5,5,5,2,2,5,1,5,0,2.0,satisfied +7452,27068,Female,Loyal Customer,17,Business travel,Business,1399,2,2,2,2,5,5,5,5,2,3,5,1,4,5,0,0.0,satisfied +7453,22416,Female,Loyal Customer,37,Business travel,Business,214,2,1,1,1,2,4,3,5,5,4,2,1,5,2,0,0.0,neutral or dissatisfied +7454,40540,Female,Loyal Customer,32,Business travel,Business,3666,0,5,0,2,5,5,5,5,4,3,4,5,1,5,0,0.0,satisfied +7455,109960,Female,Loyal Customer,67,Personal Travel,Eco,1204,3,3,3,3,2,3,3,1,1,3,4,4,1,4,0,0.0,neutral or dissatisfied +7456,25663,Male,disloyal Customer,48,Business travel,Eco,761,3,3,3,1,2,3,3,2,5,3,2,3,3,2,12,3.0,neutral or dissatisfied +7457,27726,Male,Loyal Customer,31,Business travel,Business,2981,4,4,4,4,4,4,4,4,3,1,4,1,3,4,1,6.0,neutral or dissatisfied +7458,6666,Female,Loyal Customer,57,Business travel,Business,403,2,2,1,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +7459,8454,Female,Loyal Customer,52,Business travel,Eco,1379,3,5,5,5,4,4,3,3,3,3,3,3,3,3,69,47.0,neutral or dissatisfied +7460,25050,Female,Loyal Customer,22,Business travel,Business,1703,3,2,4,2,3,3,3,3,2,1,4,2,4,3,1,10.0,neutral or dissatisfied +7461,15697,Male,Loyal Customer,44,Business travel,Business,419,3,2,2,2,1,3,4,3,3,3,3,3,3,4,31,8.0,neutral or dissatisfied +7462,57192,Male,Loyal Customer,48,Business travel,Business,1514,5,1,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +7463,20623,Male,Loyal Customer,53,Business travel,Business,783,4,4,4,4,4,3,3,4,4,4,4,1,4,4,0,0.0,satisfied +7464,106317,Male,Loyal Customer,54,Business travel,Business,2800,2,1,2,2,4,4,5,5,5,5,5,3,5,5,27,6.0,satisfied +7465,10943,Male,Loyal Customer,59,Business travel,Business,2109,5,5,5,5,3,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +7466,39457,Male,Loyal Customer,67,Personal Travel,Eco,129,2,0,2,1,2,2,2,2,3,2,5,4,4,2,16,16.0,neutral or dissatisfied +7467,92333,Male,Loyal Customer,30,Business travel,Business,2486,5,5,5,5,4,4,4,3,5,5,5,4,5,4,0,9.0,satisfied +7468,34904,Female,disloyal Customer,36,Business travel,Eco,187,2,5,2,4,3,2,3,3,2,4,3,4,2,3,2,3.0,neutral or dissatisfied +7469,18505,Female,Loyal Customer,68,Business travel,Business,2185,2,1,1,1,3,3,3,3,3,3,2,2,3,2,0,0.0,neutral or dissatisfied +7470,120706,Male,Loyal Customer,68,Personal Travel,Eco,280,2,5,2,4,1,2,1,1,5,2,5,2,4,1,1,0.0,neutral or dissatisfied +7471,114378,Male,Loyal Customer,53,Personal Travel,Eco Plus,862,2,3,2,3,4,2,1,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +7472,5218,Male,Loyal Customer,58,Business travel,Business,2029,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +7473,14728,Male,Loyal Customer,54,Personal Travel,Eco Plus,419,1,1,1,3,5,1,5,5,4,1,3,3,3,5,0,0.0,neutral or dissatisfied +7474,49573,Female,disloyal Customer,20,Business travel,Eco,86,4,2,5,4,2,5,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +7475,35256,Female,disloyal Customer,47,Business travel,Eco,1032,2,2,2,3,4,2,4,4,5,3,4,1,5,4,4,16.0,neutral or dissatisfied +7476,92251,Female,Loyal Customer,69,Business travel,Business,1670,3,4,4,4,3,2,2,3,3,3,3,2,3,1,4,0.0,neutral or dissatisfied +7477,107881,Female,Loyal Customer,57,Personal Travel,Eco,228,1,1,1,3,3,3,4,1,1,1,1,2,1,4,2,12.0,neutral or dissatisfied +7478,114607,Female,Loyal Customer,54,Business travel,Business,342,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +7479,71633,Female,disloyal Customer,38,Business travel,Eco,797,3,3,3,4,5,3,5,5,4,3,3,1,4,5,13,10.0,neutral or dissatisfied +7480,60868,Female,disloyal Customer,43,Business travel,Eco,1091,2,3,3,4,5,3,5,5,4,1,4,4,3,5,105,112.0,neutral or dissatisfied +7481,111513,Male,Loyal Customer,21,Personal Travel,Eco,391,2,1,2,4,5,2,5,5,2,5,4,4,4,5,21,16.0,neutral or dissatisfied +7482,89114,Female,Loyal Customer,31,Business travel,Business,1892,1,1,4,1,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +7483,4342,Female,Loyal Customer,41,Personal Travel,Business,607,5,5,5,2,4,4,4,2,2,5,4,4,2,5,0,0.0,satisfied +7484,95044,Female,Loyal Customer,23,Personal Travel,Eco,189,2,2,2,4,3,2,3,3,3,4,4,4,4,3,28,20.0,neutral or dissatisfied +7485,128122,Female,disloyal Customer,48,Business travel,Business,1587,3,3,3,2,1,3,1,1,4,4,3,4,5,1,4,0.0,neutral or dissatisfied +7486,60309,Female,Loyal Customer,25,Personal Travel,Eco,406,2,2,2,3,2,2,2,2,1,2,3,3,3,2,0,13.0,neutral or dissatisfied +7487,60001,Male,Loyal Customer,53,Personal Travel,Eco,937,2,5,2,1,5,2,5,5,3,2,3,5,2,5,0,0.0,neutral or dissatisfied +7488,77242,Male,Loyal Customer,31,Business travel,Eco,1590,3,3,3,3,3,3,3,3,3,1,4,1,4,3,0,1.0,neutral or dissatisfied +7489,68379,Female,disloyal Customer,35,Business travel,Business,1045,2,2,2,3,2,2,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +7490,4461,Female,Loyal Customer,37,Business travel,Eco,1005,3,2,2,2,3,3,3,3,1,1,3,4,2,3,0,0.0,neutral or dissatisfied +7491,127986,Male,Loyal Customer,61,Business travel,Business,749,2,1,1,1,5,3,3,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +7492,29195,Female,Loyal Customer,16,Personal Travel,Eco Plus,697,3,4,3,3,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +7493,122910,Female,Loyal Customer,36,Business travel,Business,328,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,10.0,satisfied +7494,79230,Male,disloyal Customer,25,Business travel,Business,1521,5,0,5,1,5,5,5,4,3,4,5,5,4,5,241,241.0,satisfied +7495,123412,Male,Loyal Customer,51,Business travel,Business,1337,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +7496,85179,Female,Loyal Customer,45,Business travel,Business,3914,1,1,1,1,3,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +7497,92124,Female,Loyal Customer,36,Personal Travel,Eco,1522,3,1,3,3,5,3,5,5,2,4,3,3,4,5,44,36.0,neutral or dissatisfied +7498,66570,Male,disloyal Customer,38,Business travel,Business,624,2,2,2,3,2,2,2,2,4,2,5,4,5,2,9,9.0,neutral or dissatisfied +7499,33636,Male,Loyal Customer,43,Personal Travel,Eco,399,3,2,5,4,1,5,1,1,2,3,3,4,4,1,0,1.0,neutral or dissatisfied +7500,53678,Male,Loyal Customer,58,Business travel,Business,1190,2,3,3,3,1,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +7501,32913,Female,Loyal Customer,9,Personal Travel,Eco,163,2,1,2,3,4,2,4,4,4,1,4,3,3,4,0,3.0,neutral or dissatisfied +7502,48560,Female,Loyal Customer,66,Personal Travel,Eco,845,2,4,2,2,2,4,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +7503,93928,Female,Loyal Customer,42,Business travel,Business,2340,1,1,1,1,2,3,3,1,1,1,1,1,1,4,18,11.0,neutral or dissatisfied +7504,74112,Female,disloyal Customer,25,Business travel,Business,592,4,4,4,3,2,4,2,2,5,5,4,4,5,2,0,0.0,satisfied +7505,128034,Female,Loyal Customer,11,Business travel,Business,1440,1,4,4,4,1,1,1,1,2,1,4,3,3,1,0,0.0,neutral or dissatisfied +7506,54922,Female,Loyal Customer,66,Personal Travel,Eco Plus,862,2,5,3,3,4,5,5,3,3,3,3,3,3,5,23,9.0,neutral or dissatisfied +7507,63920,Female,disloyal Customer,24,Business travel,Eco,1158,1,1,1,3,1,1,1,1,2,4,4,4,4,1,92,76.0,neutral or dissatisfied +7508,67642,Female,Loyal Customer,27,Business travel,Business,1464,4,5,5,5,4,4,4,4,3,4,3,4,3,4,73,65.0,neutral or dissatisfied +7509,43151,Female,disloyal Customer,59,Business travel,Eco Plus,173,2,2,2,4,1,2,1,1,4,2,5,1,5,1,0,0.0,neutral or dissatisfied +7510,88321,Male,Loyal Customer,35,Business travel,Business,2938,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +7511,98842,Male,Loyal Customer,39,Personal Travel,Eco Plus,763,1,4,1,4,5,1,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +7512,103948,Female,Loyal Customer,35,Business travel,Business,3579,1,3,1,1,4,1,1,3,3,4,3,5,3,1,0,0.0,satisfied +7513,117977,Male,Loyal Customer,58,Personal Travel,Eco,255,3,5,3,4,4,3,4,4,2,2,4,5,4,4,6,4.0,neutral or dissatisfied +7514,82919,Female,Loyal Customer,60,Personal Travel,Eco,645,1,2,2,4,1,4,3,5,5,2,5,1,5,4,12,27.0,neutral or dissatisfied +7515,89208,Male,Loyal Customer,23,Personal Travel,Eco,1947,3,5,4,1,3,4,3,3,4,3,3,3,5,3,0,0.0,neutral or dissatisfied +7516,68008,Male,Loyal Customer,41,Business travel,Business,2433,4,4,4,4,2,4,4,5,5,5,5,3,5,3,9,8.0,satisfied +7517,33852,Male,Loyal Customer,31,Business travel,Eco,1562,1,5,5,5,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +7518,82378,Female,Loyal Customer,9,Business travel,Eco Plus,1953,2,3,3,3,2,3,1,2,3,3,4,4,4,2,0,9.0,neutral or dissatisfied +7519,80541,Female,Loyal Customer,13,Business travel,Business,1747,3,3,3,3,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +7520,112240,Female,Loyal Customer,42,Business travel,Business,1506,2,2,2,2,4,4,4,4,4,4,4,5,4,5,15,1.0,satisfied +7521,656,Male,disloyal Customer,39,Business travel,Business,312,4,4,4,3,3,4,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +7522,94340,Female,Loyal Customer,57,Business travel,Business,2468,4,2,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +7523,105522,Male,disloyal Customer,18,Business travel,Eco,611,4,1,4,4,1,4,1,1,4,2,5,4,4,1,15,8.0,satisfied +7524,87437,Male,Loyal Customer,49,Business travel,Business,2698,3,3,3,3,2,5,5,4,4,4,4,3,4,5,19,6.0,satisfied +7525,90287,Male,Loyal Customer,9,Business travel,Eco,757,3,5,5,5,3,3,1,3,4,3,3,3,3,3,10,11.0,neutral or dissatisfied +7526,25564,Female,disloyal Customer,24,Business travel,Eco,696,1,1,1,4,3,1,3,3,5,2,5,4,4,3,2,0.0,neutral or dissatisfied +7527,91911,Female,Loyal Customer,46,Business travel,Eco,2446,3,5,5,5,3,4,3,4,4,3,4,1,4,2,0,8.0,neutral or dissatisfied +7528,29031,Female,disloyal Customer,18,Business travel,Eco,954,3,3,3,4,5,3,5,5,3,5,3,4,3,5,0,6.0,neutral or dissatisfied +7529,77177,Female,Loyal Customer,42,Business travel,Business,2890,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +7530,55709,Female,Loyal Customer,17,Personal Travel,Eco,895,2,5,2,1,2,2,5,2,3,5,4,4,5,2,5,7.0,neutral or dissatisfied +7531,2413,Female,Loyal Customer,49,Business travel,Business,2189,4,4,4,4,5,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +7532,105439,Male,Loyal Customer,61,Personal Travel,Business,998,2,3,2,3,5,1,1,3,3,2,4,5,3,3,5,13.0,neutral or dissatisfied +7533,84327,Male,Loyal Customer,59,Business travel,Eco,591,4,4,4,4,4,4,4,4,1,2,4,1,4,4,0,0.0,neutral or dissatisfied +7534,13375,Female,Loyal Customer,55,Personal Travel,Eco,748,3,1,3,2,5,3,2,1,1,3,5,1,1,2,24,7.0,neutral or dissatisfied +7535,51850,Male,Loyal Customer,68,Business travel,Eco Plus,370,4,1,1,1,4,4,4,4,4,2,3,3,3,4,0,11.0,satisfied +7536,31674,Male,Loyal Customer,46,Business travel,Business,3567,2,2,2,2,4,4,3,2,2,2,2,4,2,1,13,17.0,neutral or dissatisfied +7537,101276,Male,Loyal Customer,47,Personal Travel,Business,763,2,4,2,5,4,4,4,2,2,2,2,4,2,4,12,7.0,neutral or dissatisfied +7538,53039,Male,Loyal Customer,52,Business travel,Business,2592,3,1,1,1,3,3,4,3,3,3,3,3,3,4,0,18.0,neutral or dissatisfied +7539,98821,Female,Loyal Customer,40,Business travel,Business,1893,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,2.0,satisfied +7540,128827,Female,disloyal Customer,25,Business travel,Eco,2586,3,3,3,2,3,3,4,1,2,1,2,4,2,4,26,0.0,neutral or dissatisfied +7541,13893,Male,Loyal Customer,29,Business travel,Eco Plus,760,2,2,5,2,2,2,2,1,3,4,4,2,1,2,157,170.0,neutral or dissatisfied +7542,45128,Female,Loyal Customer,52,Business travel,Eco Plus,177,3,4,4,4,4,3,4,3,3,3,3,3,3,1,4,0.0,neutral or dissatisfied +7543,129863,Male,Loyal Customer,51,Business travel,Business,308,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +7544,94986,Male,Loyal Customer,62,Personal Travel,Eco,148,4,2,4,4,1,4,1,1,4,3,3,2,4,1,0,0.0,satisfied +7545,6018,Female,Loyal Customer,11,Business travel,Business,690,2,3,3,3,2,2,2,2,4,3,4,2,3,2,188,209.0,neutral or dissatisfied +7546,129855,Female,Loyal Customer,56,Business travel,Business,1972,0,0,0,4,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +7547,25152,Female,Loyal Customer,68,Personal Travel,Eco Plus,406,4,4,4,5,3,5,4,2,2,4,2,4,2,4,19,14.0,neutral or dissatisfied +7548,102311,Male,Loyal Customer,61,Business travel,Eco,386,4,1,1,1,5,4,5,5,1,5,2,3,1,5,0,0.0,neutral or dissatisfied +7549,106261,Female,Loyal Customer,26,Business travel,Business,1500,5,5,5,5,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +7550,24074,Male,Loyal Customer,40,Business travel,Eco,866,3,4,4,4,3,3,3,3,4,1,4,4,4,3,1,0.0,neutral or dissatisfied +7551,61011,Male,Loyal Customer,53,Business travel,Business,3365,5,5,5,5,5,5,5,3,2,5,5,5,5,5,12,14.0,satisfied +7552,66428,Male,Loyal Customer,55,Business travel,Business,1562,1,1,1,1,4,5,5,2,2,2,2,5,2,4,4,0.0,satisfied +7553,105930,Male,disloyal Customer,27,Business travel,Business,1491,2,2,2,1,4,2,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +7554,14214,Female,Loyal Customer,54,Personal Travel,Eco,692,2,2,2,3,1,3,4,4,4,2,4,3,4,1,20,20.0,neutral or dissatisfied +7555,117415,Female,Loyal Customer,45,Business travel,Business,1460,5,3,5,5,3,5,5,5,5,5,5,5,5,3,4,0.0,satisfied +7556,94681,Female,disloyal Customer,23,Business travel,Eco,233,4,3,4,3,4,4,4,4,3,3,5,5,4,4,29,29.0,satisfied +7557,63809,Male,Loyal Customer,34,Personal Travel,Eco,2724,1,5,1,2,3,1,1,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +7558,92156,Male,Loyal Customer,14,Personal Travel,Eco Plus,1522,2,3,2,2,5,2,5,5,2,5,5,1,1,5,0,2.0,neutral or dissatisfied +7559,113677,Male,Loyal Customer,20,Personal Travel,Eco,386,3,4,3,1,5,3,3,5,5,4,5,4,4,5,9,1.0,neutral or dissatisfied +7560,118499,Female,Loyal Customer,47,Business travel,Business,2461,5,5,5,5,4,5,4,4,4,4,4,3,4,3,11,0.0,satisfied +7561,84812,Female,Loyal Customer,38,Business travel,Business,2054,2,3,3,3,2,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +7562,103359,Female,Loyal Customer,57,Business travel,Business,3543,3,3,3,3,2,5,4,4,4,4,4,3,4,3,6,2.0,satisfied +7563,15706,Female,Loyal Customer,30,Business travel,Business,1784,5,5,5,5,5,5,5,5,1,2,2,2,3,5,0,0.0,satisfied +7564,3030,Female,Loyal Customer,15,Personal Travel,Eco,922,2,2,1,2,5,1,5,5,2,1,2,1,3,5,0,7.0,neutral or dissatisfied +7565,881,Male,disloyal Customer,59,Business travel,Business,134,3,2,2,3,1,3,1,1,1,1,3,2,3,1,0,0.0,neutral or dissatisfied +7566,68990,Male,disloyal Customer,34,Business travel,Eco,1305,3,3,3,3,3,5,5,1,1,2,3,5,1,5,0,0.0,neutral or dissatisfied +7567,54040,Male,disloyal Customer,38,Business travel,Eco,1416,1,1,1,1,4,1,4,4,2,1,2,4,4,4,66,57.0,neutral or dissatisfied +7568,3539,Male,Loyal Customer,13,Personal Travel,Eco Plus,557,1,5,1,5,4,1,1,4,1,1,2,1,5,4,0,0.0,neutral or dissatisfied +7569,79532,Male,disloyal Customer,23,Business travel,Business,762,4,0,4,2,3,4,3,3,5,3,5,3,4,3,10,6.0,satisfied +7570,78145,Male,Loyal Customer,52,Business travel,Business,153,2,2,2,2,2,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +7571,46998,Female,Loyal Customer,11,Business travel,Eco Plus,819,3,2,4,4,3,3,1,3,4,5,3,3,4,3,0,5.0,neutral or dissatisfied +7572,6853,Female,Loyal Customer,60,Business travel,Business,1624,3,2,2,2,1,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +7573,126614,Male,Loyal Customer,66,Personal Travel,Eco,1337,2,4,2,3,1,2,1,1,3,2,4,4,4,1,7,6.0,neutral or dissatisfied +7574,3249,Female,Loyal Customer,46,Business travel,Business,2146,5,5,1,5,4,5,4,4,4,4,4,4,4,4,27,10.0,satisfied +7575,46498,Male,Loyal Customer,37,Business travel,Eco,125,4,4,4,4,4,4,4,4,3,5,5,3,3,4,5,9.0,satisfied +7576,1398,Female,Loyal Customer,45,Personal Travel,Eco Plus,270,4,3,2,4,2,4,3,3,3,2,3,2,3,4,8,0.0,neutral or dissatisfied +7577,38599,Male,Loyal Customer,59,Business travel,Business,2745,0,0,0,2,5,1,3,5,5,5,5,5,5,2,0,0.0,satisfied +7578,43478,Male,disloyal Customer,25,Business travel,Eco,524,4,2,4,4,2,4,2,2,4,5,3,3,4,2,25,14.0,neutral or dissatisfied +7579,70624,Female,Loyal Customer,49,Business travel,Eco,817,4,3,3,3,4,3,4,4,4,4,4,1,4,3,3,0.0,satisfied +7580,123,Female,Loyal Customer,33,Personal Travel,Eco,562,1,3,1,4,4,1,4,4,2,5,3,1,3,4,30,41.0,neutral or dissatisfied +7581,94670,Female,Loyal Customer,52,Business travel,Business,3333,1,1,4,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7582,128209,Male,Loyal Customer,49,Business travel,Business,1548,3,3,5,3,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +7583,35121,Male,Loyal Customer,28,Business travel,Eco,944,0,0,0,2,3,0,3,3,2,4,2,2,2,3,10,3.0,satisfied +7584,38934,Female,Loyal Customer,38,Personal Travel,Eco,410,2,5,5,1,4,5,4,4,4,5,5,4,4,4,0,16.0,neutral or dissatisfied +7585,39736,Female,Loyal Customer,50,Personal Travel,Eco,320,3,3,3,3,1,4,5,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +7586,87828,Male,Loyal Customer,49,Business travel,Eco,214,5,4,4,4,5,5,5,5,4,2,4,3,2,5,1,0.0,satisfied +7587,110283,Female,Loyal Customer,48,Personal Travel,Business,919,0,4,0,4,5,3,3,1,1,0,1,4,1,4,0,0.0,satisfied +7588,82308,Male,Loyal Customer,41,Business travel,Business,986,2,2,2,2,5,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +7589,43963,Female,Loyal Customer,47,Business travel,Eco,596,3,5,5,5,3,3,2,3,3,3,3,2,3,3,2,0.0,neutral or dissatisfied +7590,128478,Female,Loyal Customer,8,Personal Travel,Eco,338,3,2,3,3,2,3,2,2,4,3,3,2,2,2,1,0.0,neutral or dissatisfied +7591,78710,Male,Loyal Customer,57,Business travel,Business,3621,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +7592,97635,Male,Loyal Customer,17,Personal Travel,Eco,748,1,4,0,1,1,0,1,1,3,2,4,3,5,1,1,2.0,neutral or dissatisfied +7593,128878,Male,Loyal Customer,58,Business travel,Business,2454,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +7594,28548,Male,Loyal Customer,14,Personal Travel,Eco,2688,1,5,0,3,0,3,3,4,2,4,5,3,4,3,0,2.0,neutral or dissatisfied +7595,123824,Female,disloyal Customer,29,Business travel,Eco,541,2,3,2,4,1,2,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +7596,2432,Male,Loyal Customer,51,Personal Travel,Eco,641,1,5,1,5,1,1,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +7597,10415,Male,Loyal Customer,41,Business travel,Business,3303,5,5,4,5,5,4,5,5,2,5,4,5,3,5,171,183.0,satisfied +7598,41528,Female,Loyal Customer,55,Business travel,Business,1334,2,2,2,2,3,4,4,2,2,2,2,3,2,2,0,18.0,neutral or dissatisfied +7599,78613,Male,disloyal Customer,44,Business travel,Business,1426,1,2,2,2,5,1,4,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +7600,91310,Male,Loyal Customer,44,Business travel,Eco Plus,444,3,5,5,5,2,3,2,2,2,5,2,2,3,2,13,9.0,neutral or dissatisfied +7601,31608,Male,Loyal Customer,17,Personal Travel,Eco,602,2,5,2,2,4,2,4,4,3,2,4,3,4,4,8,25.0,neutral or dissatisfied +7602,24247,Male,Loyal Customer,45,Personal Travel,Eco,302,5,4,5,4,4,5,4,4,5,5,5,3,4,4,0,0.0,satisfied +7603,91294,Female,disloyal Customer,44,Business travel,Eco Plus,406,2,2,2,4,5,2,1,5,2,4,3,1,3,5,0,0.0,neutral or dissatisfied +7604,7149,Male,Loyal Customer,60,Business travel,Business,130,4,4,4,4,3,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +7605,4793,Female,Loyal Customer,25,Personal Travel,Eco,438,3,4,3,4,4,3,1,4,5,3,4,5,5,4,1,2.0,neutral or dissatisfied +7606,78691,Male,Loyal Customer,58,Personal Travel,Eco,761,4,1,4,3,4,4,4,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +7607,29734,Male,Loyal Customer,27,Personal Travel,Eco,2552,3,4,3,1,5,3,5,5,2,2,5,3,5,5,2,0.0,neutral or dissatisfied +7608,3327,Female,Loyal Customer,43,Business travel,Business,2374,1,1,1,1,2,5,4,4,4,4,4,3,4,3,18,13.0,satisfied +7609,82366,Male,Loyal Customer,36,Personal Travel,Eco,453,2,4,2,4,3,2,3,3,5,3,4,5,1,3,9,30.0,neutral or dissatisfied +7610,46870,Female,Loyal Customer,30,Business travel,Business,1683,5,5,5,5,5,5,5,5,3,4,2,4,1,5,0,0.0,satisfied +7611,72803,Female,Loyal Customer,20,Personal Travel,Eco,1045,3,5,3,5,3,3,3,3,4,1,3,5,1,3,0,0.0,neutral or dissatisfied +7612,72798,Male,Loyal Customer,20,Personal Travel,Eco,1045,2,5,2,2,4,2,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +7613,11162,Male,Loyal Customer,14,Personal Travel,Eco,201,1,3,1,4,5,1,5,5,4,5,3,4,4,5,75,70.0,neutral or dissatisfied +7614,3447,Male,Loyal Customer,51,Personal Travel,Eco,240,4,2,4,3,4,4,4,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +7615,1209,Female,Loyal Customer,18,Personal Travel,Eco,229,3,4,3,4,4,3,4,4,5,4,5,3,5,4,12,27.0,neutral or dissatisfied +7616,40470,Male,Loyal Customer,54,Business travel,Business,1642,1,1,1,1,5,3,2,4,4,4,3,5,4,5,0,0.0,satisfied +7617,101512,Male,Loyal Customer,38,Business travel,Business,2660,5,3,3,3,1,4,3,5,5,4,5,1,5,3,7,12.0,neutral or dissatisfied +7618,23231,Male,Loyal Customer,31,Business travel,Business,2465,1,3,3,3,1,1,1,1,1,3,2,4,2,1,0,0.0,neutral or dissatisfied +7619,27054,Male,Loyal Customer,43,Personal Travel,Eco,1489,3,5,3,2,2,3,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +7620,65681,Male,Loyal Customer,63,Personal Travel,Eco,861,1,4,1,2,1,1,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +7621,4540,Female,Loyal Customer,38,Business travel,Business,719,5,5,5,5,3,4,5,4,4,3,4,4,4,5,0,7.0,satisfied +7622,60564,Male,Loyal Customer,36,Personal Travel,Eco Plus,862,5,4,5,3,4,5,4,4,5,3,4,4,4,4,0,0.0,satisfied +7623,41902,Male,disloyal Customer,26,Business travel,Eco,129,1,3,1,2,4,1,4,4,3,5,2,5,2,4,0,5.0,neutral or dissatisfied +7624,114286,Male,Loyal Customer,20,Personal Travel,Eco,909,3,2,3,4,3,3,3,3,3,2,3,3,4,3,3,0.0,neutral or dissatisfied +7625,92668,Female,Loyal Customer,19,Personal Travel,Business,507,4,4,4,1,1,4,2,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +7626,10866,Female,disloyal Customer,38,Business travel,Business,429,5,5,5,2,2,5,2,2,5,5,4,4,4,2,0,0.0,satisfied +7627,67307,Female,Loyal Customer,58,Business travel,Eco Plus,1119,3,4,2,4,3,2,2,3,3,3,3,4,3,4,61,48.0,neutral or dissatisfied +7628,120298,Male,Loyal Customer,39,Business travel,Business,268,4,3,4,4,5,4,4,4,4,4,4,3,4,3,7,23.0,satisfied +7629,6252,Male,Loyal Customer,61,Personal Travel,Eco,678,1,4,1,3,4,1,4,4,5,4,5,4,5,4,1,0.0,neutral or dissatisfied +7630,44555,Male,Loyal Customer,49,Business travel,Eco Plus,157,4,5,5,5,4,4,4,4,4,2,1,4,1,4,0,0.0,satisfied +7631,100909,Male,Loyal Customer,65,Personal Travel,Eco,377,2,5,2,2,3,2,2,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +7632,129793,Male,Loyal Customer,40,Personal Travel,Eco,337,0,4,0,2,2,0,2,2,3,2,5,5,4,2,0,0.0,satisfied +7633,103074,Female,Loyal Customer,19,Personal Travel,Eco,460,5,5,3,3,4,3,2,4,2,2,3,3,5,4,7,0.0,satisfied +7634,103491,Female,Loyal Customer,49,Personal Travel,Eco,440,3,4,3,4,2,4,5,4,4,3,4,4,4,4,2,0.0,neutral or dissatisfied +7635,99940,Male,Loyal Customer,65,Personal Travel,Eco Plus,764,2,2,3,3,5,3,5,5,2,4,4,3,3,5,0,0.0,neutral or dissatisfied +7636,2575,Female,disloyal Customer,23,Business travel,Eco,280,4,2,4,2,3,4,3,3,2,1,2,1,1,3,16,13.0,neutral or dissatisfied +7637,122692,Female,Loyal Customer,30,Personal Travel,Eco,361,3,2,3,4,3,4,4,1,5,3,4,4,1,4,184,176.0,neutral or dissatisfied +7638,84549,Female,Loyal Customer,25,Personal Travel,Eco,2556,4,1,4,3,3,4,3,3,1,3,3,4,2,3,0,0.0,neutral or dissatisfied +7639,78720,Male,Loyal Customer,42,Business travel,Business,1967,3,3,3,3,2,4,5,2,2,2,2,3,2,4,0,8.0,satisfied +7640,19645,Male,Loyal Customer,45,Business travel,Eco Plus,642,2,4,4,4,3,2,3,3,3,5,2,1,5,3,0,0.0,satisfied +7641,105422,Male,Loyal Customer,48,Business travel,Business,452,2,3,3,3,5,4,3,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +7642,51596,Male,Loyal Customer,34,Business travel,Business,237,1,1,1,1,3,5,5,3,3,4,3,1,3,4,21,20.0,satisfied +7643,23872,Female,disloyal Customer,27,Business travel,Eco Plus,552,2,2,2,4,2,2,4,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +7644,121653,Female,Loyal Customer,26,Business travel,Business,511,4,4,4,4,5,5,5,5,4,2,5,3,5,5,2,0.0,satisfied +7645,69165,Female,Loyal Customer,55,Business travel,Business,3603,3,3,4,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +7646,107962,Male,Loyal Customer,42,Business travel,Business,2879,3,1,3,3,4,5,5,4,4,4,4,3,4,4,52,48.0,satisfied +7647,24773,Male,Loyal Customer,23,Business travel,Business,447,2,2,2,2,2,2,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +7648,85793,Female,Loyal Customer,51,Business travel,Business,3806,2,1,1,1,5,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +7649,73611,Female,Loyal Customer,39,Business travel,Business,204,0,4,0,4,3,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +7650,95258,Male,Loyal Customer,12,Personal Travel,Eco,293,1,4,2,4,2,2,1,2,4,5,5,4,5,2,9,8.0,neutral or dissatisfied +7651,27763,Male,Loyal Customer,39,Business travel,Eco,1448,4,5,5,5,4,4,4,4,5,2,3,2,2,4,5,10.0,satisfied +7652,114564,Male,Loyal Customer,35,Personal Travel,Business,362,3,5,3,3,4,4,4,3,3,3,3,5,3,5,37,36.0,neutral or dissatisfied +7653,53042,Female,Loyal Customer,21,Business travel,Eco,1208,1,5,5,5,1,1,2,1,4,2,3,1,3,1,13,20.0,neutral or dissatisfied +7654,73570,Female,Loyal Customer,73,Business travel,Business,1676,4,3,3,3,3,4,3,1,1,1,4,2,1,4,0,0.0,neutral or dissatisfied +7655,80369,Female,Loyal Customer,43,Business travel,Business,2370,3,2,2,2,2,3,3,3,3,3,3,1,3,4,8,4.0,neutral or dissatisfied +7656,73201,Female,Loyal Customer,19,Personal Travel,Eco,1258,1,2,1,3,2,1,2,2,1,4,1,2,2,2,30,18.0,neutral or dissatisfied +7657,29624,Female,Loyal Customer,35,Business travel,Business,1448,2,5,2,5,2,2,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +7658,104427,Male,disloyal Customer,29,Business travel,Eco,1024,4,4,4,4,5,4,5,5,4,2,4,4,4,5,0,15.0,neutral or dissatisfied +7659,14862,Female,Loyal Customer,35,Business travel,Eco,315,4,4,4,4,5,4,4,4,5,5,1,4,4,4,167,174.0,satisfied +7660,43348,Female,disloyal Customer,24,Business travel,Eco,387,4,3,3,2,1,3,1,1,5,1,4,3,2,1,0,4.0,satisfied +7661,41749,Female,Loyal Customer,68,Business travel,Business,2710,2,2,2,2,5,4,3,5,5,5,5,3,5,2,3,15.0,satisfied +7662,64978,Male,disloyal Customer,63,Business travel,Eco,247,2,1,2,4,2,2,2,2,2,1,3,1,4,2,19,11.0,neutral or dissatisfied +7663,25111,Male,disloyal Customer,27,Business travel,Eco,946,2,2,2,1,1,2,1,1,3,4,1,4,1,1,0,0.0,neutral or dissatisfied +7664,3459,Female,Loyal Customer,31,Business travel,Eco Plus,296,3,4,3,4,3,3,3,3,1,5,3,2,3,3,0,17.0,neutral or dissatisfied +7665,82335,Male,Loyal Customer,42,Business travel,Business,1930,1,1,1,1,3,5,4,4,4,4,4,5,4,4,24,33.0,satisfied +7666,121071,Female,Loyal Customer,39,Business travel,Eco Plus,861,3,2,2,2,3,3,3,3,4,5,2,4,1,3,4,15.0,neutral or dissatisfied +7667,120452,Male,Loyal Customer,64,Personal Travel,Eco,449,3,2,3,4,4,3,3,4,1,1,4,1,3,4,6,43.0,neutral or dissatisfied +7668,35138,Male,Loyal Customer,39,Business travel,Business,944,4,4,4,4,5,5,5,1,2,1,5,5,4,5,224,216.0,satisfied +7669,45554,Female,Loyal Customer,38,Business travel,Business,3563,1,1,1,1,5,3,4,4,4,4,4,3,4,5,12,12.0,satisfied +7670,74152,Male,Loyal Customer,43,Business travel,Eco,592,3,1,1,1,4,3,4,4,4,1,5,4,5,4,0,0.0,satisfied +7671,40074,Male,disloyal Customer,21,Business travel,Eco,493,3,0,3,2,1,3,1,1,4,1,2,1,4,1,0,0.0,neutral or dissatisfied +7672,128046,Male,disloyal Customer,36,Business travel,Business,735,3,3,3,3,3,3,3,3,3,3,5,3,5,3,33,17.0,neutral or dissatisfied +7673,107404,Female,Loyal Customer,28,Business travel,Eco,468,2,2,2,2,2,2,2,2,3,2,4,4,4,2,30,21.0,neutral or dissatisfied +7674,123255,Female,Loyal Customer,9,Personal Travel,Eco,507,2,4,5,1,3,5,3,3,3,2,4,1,2,3,0,0.0,neutral or dissatisfied +7675,48687,Female,Loyal Customer,54,Business travel,Business,89,4,1,4,4,4,4,5,5,5,5,5,5,5,5,5,0.0,satisfied +7676,86083,Male,disloyal Customer,44,Business travel,Business,306,2,2,2,1,1,2,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +7677,36334,Male,Loyal Customer,69,Personal Travel,Eco,187,0,3,0,3,5,0,3,5,3,2,3,4,4,5,0,0.0,satisfied +7678,67016,Female,Loyal Customer,46,Business travel,Business,1121,2,2,2,2,5,4,5,5,5,5,5,5,5,3,8,2.0,satisfied +7679,66376,Male,Loyal Customer,9,Personal Travel,Eco Plus,986,2,3,2,3,4,2,1,4,3,3,4,5,1,4,0,0.0,neutral or dissatisfied +7680,61415,Male,disloyal Customer,18,Business travel,Business,679,5,4,5,2,1,5,1,1,4,4,4,3,5,1,0,0.0,satisfied +7681,50938,Female,Loyal Customer,46,Personal Travel,Eco,209,4,4,0,3,4,3,5,4,4,0,4,4,4,2,0,2.0,neutral or dissatisfied +7682,48769,Male,Loyal Customer,51,Business travel,Business,308,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +7683,24187,Female,Loyal Customer,46,Business travel,Business,3931,4,4,4,4,4,3,2,5,5,4,5,1,5,3,0,0.0,satisfied +7684,31460,Male,Loyal Customer,32,Business travel,Eco,846,0,0,0,5,4,0,4,4,5,3,1,3,1,4,0,0.0,satisfied +7685,5956,Female,Loyal Customer,28,Business travel,Business,1691,4,4,4,4,5,5,5,5,4,3,4,3,4,5,11,5.0,satisfied +7686,57989,Male,disloyal Customer,47,Business travel,Business,844,1,1,1,5,1,1,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +7687,28687,Male,Loyal Customer,23,Personal Travel,Eco,2777,2,2,2,4,2,2,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +7688,49132,Female,Loyal Customer,43,Business travel,Business,3811,4,4,4,4,2,4,2,4,4,4,4,4,4,5,0,0.0,satisfied +7689,17159,Female,disloyal Customer,33,Business travel,Eco,643,4,3,4,1,4,4,4,4,1,1,5,3,3,4,0,0.0,neutral or dissatisfied +7690,125191,Female,Loyal Customer,44,Business travel,Business,3984,3,3,4,3,5,5,5,4,4,4,4,5,4,5,12,10.0,satisfied +7691,33172,Female,Loyal Customer,44,Personal Travel,Eco,101,1,4,1,1,4,4,4,1,1,1,1,3,1,5,5,17.0,neutral or dissatisfied +7692,22103,Female,Loyal Customer,48,Personal Travel,Business,743,2,5,2,5,2,4,5,1,1,2,1,4,1,5,14,2.0,neutral or dissatisfied +7693,47519,Female,Loyal Customer,16,Personal Travel,Eco,590,4,4,4,3,5,4,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +7694,100906,Male,Loyal Customer,29,Personal Travel,Eco,377,4,5,4,3,1,4,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +7695,29909,Male,Loyal Customer,39,Business travel,Business,548,1,1,2,1,5,4,1,5,5,5,5,1,5,5,11,3.0,satisfied +7696,84796,Female,Loyal Customer,41,Business travel,Business,547,5,5,5,5,4,5,5,5,5,5,5,4,5,5,11,2.0,satisfied +7697,11382,Male,Loyal Customer,30,Business travel,Business,3583,4,4,4,4,5,5,5,5,5,2,5,5,5,5,54,39.0,satisfied +7698,79807,Female,Loyal Customer,50,Business travel,Business,3211,3,3,3,3,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +7699,43428,Male,Loyal Customer,40,Business travel,Eco,748,4,2,2,2,4,4,4,4,3,2,4,4,2,4,0,0.0,satisfied +7700,112155,Female,disloyal Customer,20,Business travel,Eco,895,3,2,2,3,1,2,1,1,1,3,3,3,4,1,119,114.0,neutral or dissatisfied +7701,17565,Female,disloyal Customer,29,Business travel,Eco,852,1,1,1,3,5,1,5,5,4,2,3,1,3,5,0,7.0,neutral or dissatisfied +7702,33100,Female,Loyal Customer,47,Personal Travel,Eco,216,2,4,0,3,5,3,3,2,2,0,2,2,2,1,0,0.0,neutral or dissatisfied +7703,27275,Male,Loyal Customer,42,Personal Travel,Business,1050,2,4,2,4,2,5,5,3,3,2,3,4,3,3,0,28.0,neutral or dissatisfied +7704,64170,Male,Loyal Customer,22,Personal Travel,Eco,989,5,4,5,5,3,5,3,3,4,4,5,4,4,3,0,0.0,satisfied +7705,107483,Female,Loyal Customer,41,Business travel,Business,2764,3,3,3,3,5,4,4,5,5,5,5,5,5,4,54,51.0,satisfied +7706,66517,Female,Loyal Customer,59,Personal Travel,Eco,447,3,5,3,4,2,5,5,1,1,3,1,4,1,3,8,9.0,neutral or dissatisfied +7707,43050,Female,disloyal Customer,48,Business travel,Eco,236,3,0,3,3,5,3,5,5,5,1,3,2,3,5,0,2.0,neutral or dissatisfied +7708,22060,Female,disloyal Customer,32,Business travel,Eco,304,2,4,2,3,4,2,4,4,1,2,3,4,4,4,0,43.0,neutral or dissatisfied +7709,125444,Female,Loyal Customer,43,Business travel,Business,2845,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7710,104610,Female,Loyal Customer,41,Personal Travel,Eco Plus,369,4,2,4,3,5,4,3,2,2,4,2,4,2,2,60,54.0,neutral or dissatisfied +7711,27382,Female,disloyal Customer,31,Business travel,Eco,954,3,3,3,3,1,3,1,1,4,5,2,1,2,1,59,80.0,neutral or dissatisfied +7712,42202,Male,Loyal Customer,33,Business travel,Business,3692,2,1,2,2,5,5,5,5,1,3,4,1,2,5,0,0.0,satisfied +7713,111258,Male,Loyal Customer,26,Personal Travel,Eco,1972,2,3,2,2,4,2,4,4,1,3,2,2,3,4,14,17.0,neutral or dissatisfied +7714,121104,Female,disloyal Customer,46,Business travel,Business,2370,5,5,5,3,5,5,4,5,4,5,5,3,4,5,0,0.0,satisfied +7715,107916,Male,Loyal Customer,38,Business travel,Eco Plus,861,1,4,5,4,1,1,1,1,4,2,3,2,3,1,7,0.0,neutral or dissatisfied +7716,65424,Male,disloyal Customer,28,Business travel,Business,2165,2,2,2,3,4,2,2,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +7717,68584,Male,Loyal Customer,49,Personal Travel,Eco,1616,4,4,3,5,1,3,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +7718,47865,Male,Loyal Customer,22,Business travel,Business,2042,2,1,1,1,2,2,2,2,1,1,3,4,3,2,0,0.0,neutral or dissatisfied +7719,108531,Female,Loyal Customer,46,Business travel,Eco,249,4,2,2,2,4,1,5,4,4,4,4,3,4,3,0,0.0,satisfied +7720,82149,Female,Loyal Customer,58,Business travel,Business,237,5,5,4,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +7721,78165,Female,Loyal Customer,23,Business travel,Business,3208,4,4,4,4,4,4,5,4,5,2,4,5,5,4,14,25.0,satisfied +7722,14474,Male,disloyal Customer,32,Business travel,Eco Plus,674,2,2,2,1,4,2,4,4,3,5,3,2,5,4,0,0.0,neutral or dissatisfied +7723,56418,Male,Loyal Customer,57,Business travel,Business,1900,2,2,2,2,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +7724,34932,Female,Loyal Customer,50,Personal Travel,Eco,187,1,4,1,4,3,4,5,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +7725,65456,Female,Loyal Customer,49,Business travel,Business,2353,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +7726,98335,Male,Loyal Customer,39,Business travel,Business,1046,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +7727,72146,Female,Loyal Customer,65,Personal Travel,Eco,731,2,3,1,3,4,2,2,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +7728,104725,Male,Loyal Customer,46,Business travel,Business,1407,4,4,4,4,5,5,4,5,5,5,5,3,5,5,17,13.0,satisfied +7729,57934,Male,disloyal Customer,20,Business travel,Eco,837,1,1,1,5,1,1,1,1,5,5,5,5,5,1,3,17.0,neutral or dissatisfied +7730,73300,Female,Loyal Customer,32,Business travel,Business,1005,5,5,5,5,4,4,4,4,5,5,4,4,4,4,248,261.0,satisfied +7731,14351,Male,Loyal Customer,20,Personal Travel,Eco,395,3,3,5,3,5,5,5,5,2,1,3,3,3,5,22,19.0,neutral or dissatisfied +7732,106865,Female,Loyal Customer,48,Business travel,Business,704,2,4,2,2,4,4,4,3,3,3,3,4,3,5,8,0.0,satisfied +7733,121702,Female,disloyal Customer,21,Business travel,Business,683,0,4,0,3,3,0,3,3,5,3,5,5,5,3,0,0.0,satisfied +7734,80954,Male,Loyal Customer,23,Personal Travel,Eco,872,2,2,2,3,4,2,4,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +7735,34915,Male,disloyal Customer,26,Business travel,Eco,187,2,1,2,3,2,2,2,2,1,4,3,2,3,2,16,19.0,neutral or dissatisfied +7736,38804,Female,Loyal Customer,39,Personal Travel,Eco,353,4,4,4,3,1,4,1,1,1,1,5,3,2,1,0,0.0,neutral or dissatisfied +7737,72211,Male,Loyal Customer,54,Business travel,Business,3157,3,3,3,3,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +7738,5280,Male,Loyal Customer,20,Personal Travel,Eco,351,4,4,4,4,3,4,3,3,3,2,4,5,5,3,11,3.0,neutral or dissatisfied +7739,46159,Male,Loyal Customer,13,Personal Travel,Eco,604,2,4,2,2,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +7740,108741,Female,disloyal Customer,39,Business travel,Business,406,4,4,4,4,4,4,4,4,1,1,4,2,3,4,0,0.0,neutral or dissatisfied +7741,62658,Male,Loyal Customer,36,Personal Travel,Eco,1723,4,4,4,3,5,4,5,5,4,3,4,3,4,5,0,0.0,satisfied +7742,121680,Female,Loyal Customer,34,Personal Travel,Eco,328,3,4,3,3,4,3,5,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +7743,24499,Female,Loyal Customer,32,Personal Travel,Eco,547,3,3,3,1,3,3,3,3,4,5,4,1,3,3,31,50.0,neutral or dissatisfied +7744,74379,Female,disloyal Customer,37,Business travel,Business,1171,5,5,5,4,2,5,2,2,5,4,4,3,5,2,0,0.0,satisfied +7745,55429,Male,Loyal Customer,51,Business travel,Business,2521,1,1,1,1,2,2,2,4,2,4,4,2,3,2,0,3.0,satisfied +7746,17974,Male,Loyal Customer,40,Personal Travel,Eco Plus,500,2,4,2,3,4,2,1,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +7747,42008,Male,Loyal Customer,36,Business travel,Eco,106,5,2,1,2,5,5,5,5,4,4,5,2,3,5,0,0.0,satisfied +7748,73917,Female,disloyal Customer,37,Business travel,Business,904,2,2,2,1,4,2,4,4,4,3,4,4,5,4,0,0.0,satisfied +7749,38602,Female,Loyal Customer,43,Business travel,Business,2585,2,2,2,2,1,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +7750,59277,Female,Loyal Customer,36,Business travel,Business,3414,1,1,1,1,5,5,5,4,5,3,4,5,5,5,0,0.0,satisfied +7751,66111,Male,disloyal Customer,23,Business travel,Eco,583,3,5,3,5,4,3,4,4,5,4,5,3,4,4,3,0.0,neutral or dissatisfied +7752,81379,Male,Loyal Customer,39,Business travel,Business,748,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +7753,129708,Male,disloyal Customer,17,Business travel,Eco,337,3,4,3,4,1,3,1,1,4,5,4,4,3,1,26,10.0,neutral or dissatisfied +7754,95830,Female,Loyal Customer,48,Personal Travel,Eco Plus,1428,3,2,3,4,2,4,4,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +7755,90712,Female,Loyal Customer,51,Business travel,Business,2550,2,1,1,1,5,3,3,2,2,2,2,2,2,4,23,20.0,neutral or dissatisfied +7756,38690,Female,disloyal Customer,21,Business travel,Business,1500,0,5,0,1,2,0,2,2,4,2,5,3,5,2,15,10.0,satisfied +7757,34114,Female,Loyal Customer,30,Business travel,Business,2199,1,1,4,1,5,5,5,5,2,3,3,3,3,5,0,0.0,satisfied +7758,17016,Female,disloyal Customer,24,Business travel,Eco,781,3,3,3,4,2,3,2,2,5,2,3,2,2,2,0,0.0,neutral or dissatisfied +7759,17594,Male,disloyal Customer,36,Business travel,Business,700,3,4,4,4,2,4,2,2,1,3,3,2,4,2,1,23.0,neutral or dissatisfied +7760,86321,Male,Loyal Customer,41,Business travel,Business,2236,5,5,5,5,2,4,4,4,4,4,4,5,4,4,7,42.0,satisfied +7761,39120,Female,Loyal Customer,51,Business travel,Eco,190,5,3,3,3,4,5,5,5,5,5,5,2,5,2,0,0.0,satisfied +7762,87210,Female,Loyal Customer,57,Personal Travel,Eco,946,2,3,2,1,2,2,2,2,2,2,4,2,2,4,5,0.0,neutral or dissatisfied +7763,119836,Male,Loyal Customer,54,Business travel,Business,912,3,3,3,3,4,4,4,4,4,4,4,3,4,4,0,5.0,satisfied +7764,13409,Female,Loyal Customer,26,Business travel,Eco,409,4,2,2,2,4,4,4,4,1,4,2,3,2,4,12,39.0,satisfied +7765,72554,Male,Loyal Customer,45,Business travel,Business,2092,2,4,4,4,5,3,4,2,2,2,2,2,2,4,0,7.0,neutral or dissatisfied +7766,12698,Female,Loyal Customer,59,Business travel,Eco,721,5,2,2,2,5,5,5,2,2,2,4,5,2,5,208,224.0,satisfied +7767,113801,Female,Loyal Customer,42,Business travel,Business,258,2,2,2,2,5,4,4,5,5,5,5,4,5,4,7,0.0,satisfied +7768,73467,Female,Loyal Customer,45,Personal Travel,Eco,1005,3,4,3,4,5,4,4,5,5,3,5,4,5,4,11,0.0,neutral or dissatisfied +7769,15957,Male,Loyal Customer,60,Personal Travel,Eco,738,2,5,2,1,5,2,5,5,4,5,5,5,5,5,77,64.0,neutral or dissatisfied +7770,58493,Female,disloyal Customer,12,Business travel,Eco,719,2,2,2,4,5,2,5,5,1,5,4,1,4,5,52,32.0,neutral or dissatisfied +7771,118863,Female,Loyal Customer,51,Personal Travel,Eco Plus,646,4,3,4,2,1,2,3,4,4,4,4,3,4,2,15,18.0,neutral or dissatisfied +7772,129089,Female,Loyal Customer,69,Business travel,Eco,2342,1,1,1,1,1,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +7773,24157,Male,Loyal Customer,33,Business travel,Business,1934,3,4,2,4,3,3,3,3,4,4,3,4,4,3,0,4.0,neutral or dissatisfied +7774,86415,Male,Loyal Customer,47,Business travel,Business,2051,3,2,2,2,5,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +7775,18911,Male,Loyal Customer,12,Personal Travel,Eco,500,3,4,3,3,5,3,5,5,3,2,4,5,4,5,0,7.0,neutral or dissatisfied +7776,31020,Female,Loyal Customer,65,Personal Travel,Eco,391,3,5,3,3,3,1,3,5,5,3,5,5,5,4,0,3.0,neutral or dissatisfied +7777,54663,Male,Loyal Customer,40,Business travel,Business,3572,3,3,3,3,4,2,2,5,5,5,5,1,5,3,19,9.0,satisfied +7778,112470,Female,disloyal Customer,17,Business travel,Eco,967,5,5,5,5,1,5,1,1,4,2,4,4,1,1,32,19.0,satisfied +7779,86624,Male,Loyal Customer,40,Business travel,Business,2370,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +7780,56917,Male,Loyal Customer,51,Business travel,Business,2565,5,5,5,5,2,2,2,4,5,5,4,2,3,2,0,0.0,satisfied +7781,30079,Male,Loyal Customer,19,Personal Travel,Eco,261,3,2,3,3,3,3,3,3,3,3,4,4,3,3,0,0.0,neutral or dissatisfied +7782,32630,Male,disloyal Customer,40,Business travel,Eco,201,4,0,4,5,2,4,2,2,2,1,3,1,3,2,5,7.0,neutral or dissatisfied +7783,37823,Female,Loyal Customer,53,Business travel,Business,3133,4,4,4,4,4,4,5,5,5,5,5,3,5,5,61,53.0,satisfied +7784,53391,Male,Loyal Customer,40,Business travel,Eco Plus,1452,5,1,1,1,5,5,5,5,1,3,2,5,4,5,0,16.0,satisfied +7785,109340,Female,Loyal Customer,44,Business travel,Business,1072,1,1,1,1,4,4,5,5,5,5,5,3,5,5,8,0.0,satisfied +7786,129436,Male,Loyal Customer,57,Business travel,Business,2456,2,3,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +7787,89552,Male,Loyal Customer,58,Business travel,Business,1750,2,2,2,2,3,5,4,4,4,4,4,5,4,5,24,8.0,satisfied +7788,65248,Female,Loyal Customer,65,Business travel,Eco Plus,190,3,1,1,1,3,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +7789,72716,Male,disloyal Customer,25,Business travel,Business,985,4,0,4,3,3,4,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +7790,38647,Female,disloyal Customer,24,Business travel,Eco,720,4,5,5,4,4,5,4,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +7791,39041,Male,Loyal Customer,17,Personal Travel,Eco,113,2,3,2,3,4,2,4,4,2,5,5,5,4,4,0,1.0,neutral or dissatisfied +7792,124479,Male,Loyal Customer,50,Business travel,Business,930,1,1,1,1,5,4,5,4,4,4,4,5,4,4,1,28.0,satisfied +7793,90942,Female,disloyal Customer,21,Business travel,Eco,366,3,4,3,3,3,3,3,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +7794,17030,Female,Loyal Customer,46,Personal Travel,Eco,781,2,5,2,4,3,1,4,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +7795,81200,Male,Loyal Customer,32,Business travel,Business,1426,2,2,1,2,4,4,4,4,5,2,4,3,4,4,21,7.0,satisfied +7796,7504,Female,Loyal Customer,60,Business travel,Business,2030,4,4,4,4,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +7797,67990,Male,Loyal Customer,56,Personal Travel,Eco Plus,1171,1,4,1,3,3,1,3,3,2,5,3,2,3,3,4,1.0,neutral or dissatisfied +7798,73229,Male,Loyal Customer,17,Personal Travel,Eco,946,0,5,0,3,2,0,2,2,3,2,4,2,1,2,0,0.0,satisfied +7799,104416,Male,Loyal Customer,48,Business travel,Eco,1011,1,3,3,3,1,1,1,1,4,2,2,1,2,1,0,4.0,neutral or dissatisfied +7800,33210,Male,Loyal Customer,21,Business travel,Eco Plus,102,4,2,2,2,4,4,4,4,5,5,5,4,4,4,15,18.0,satisfied +7801,100196,Female,disloyal Customer,50,Business travel,Business,523,5,5,5,2,2,5,2,2,5,4,5,4,5,2,0,13.0,satisfied +7802,60401,Female,Loyal Customer,8,Personal Travel,Eco,1452,4,3,4,1,5,4,5,5,1,5,4,2,1,5,0,5.0,neutral or dissatisfied +7803,124497,Female,disloyal Customer,36,Business travel,Business,930,1,1,1,1,1,3,3,5,5,4,4,3,5,3,178,183.0,neutral or dissatisfied +7804,48983,Male,disloyal Customer,32,Business travel,Eco,373,1,4,1,1,4,1,4,4,2,5,1,1,3,4,4,0.0,neutral or dissatisfied +7805,49080,Male,disloyal Customer,25,Business travel,Eco,238,3,0,3,4,5,3,5,5,4,3,5,3,3,5,31,32.0,neutral or dissatisfied +7806,18976,Female,disloyal Customer,24,Business travel,Eco,792,5,5,5,1,5,4,4,4,4,2,5,4,1,4,170,182.0,satisfied +7807,79097,Female,Loyal Customer,47,Personal Travel,Eco,306,2,3,5,3,3,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +7808,10892,Female,Loyal Customer,42,Business travel,Business,312,1,1,1,1,2,5,5,5,5,5,5,5,5,4,4,1.0,satisfied +7809,2958,Male,Loyal Customer,49,Business travel,Business,2857,3,5,5,5,2,2,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +7810,21619,Male,Loyal Customer,42,Business travel,Business,2744,1,1,1,1,3,3,2,2,2,2,2,4,2,2,0,0.0,satisfied +7811,92238,Male,disloyal Customer,22,Business travel,Business,1201,4,0,5,3,3,5,3,3,5,3,3,4,4,3,0,0.0,satisfied +7812,40157,Female,Loyal Customer,41,Personal Travel,Business,463,1,5,1,3,3,4,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +7813,91585,Female,Loyal Customer,55,Personal Travel,Eco Plus,1123,1,4,1,1,3,5,5,2,2,1,2,3,2,5,16,30.0,neutral or dissatisfied +7814,75862,Female,Loyal Customer,25,Business travel,Eco Plus,1440,2,1,1,1,2,2,2,2,4,5,4,1,4,2,0,0.0,neutral or dissatisfied +7815,116521,Female,Loyal Customer,13,Personal Travel,Eco,308,2,4,2,3,2,2,2,2,3,4,4,4,5,2,0,3.0,neutral or dissatisfied +7816,23930,Female,Loyal Customer,30,Personal Travel,Eco,579,2,5,2,2,2,2,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +7817,1958,Male,disloyal Customer,22,Business travel,Eco,383,0,5,1,1,5,1,2,5,5,5,5,3,5,5,0,0.0,satisfied +7818,78880,Female,Loyal Customer,20,Personal Travel,Eco,449,2,4,2,2,1,2,1,1,3,3,4,4,5,1,15,4.0,neutral or dissatisfied +7819,53424,Male,disloyal Customer,26,Business travel,Eco,2419,1,1,1,4,1,3,4,1,4,2,4,4,1,4,0,13.0,neutral or dissatisfied +7820,85120,Male,Loyal Customer,42,Business travel,Business,689,4,4,4,4,2,4,4,4,4,4,4,3,4,5,8,16.0,satisfied +7821,80769,Male,Loyal Customer,29,Personal Travel,Eco,629,1,2,1,2,2,1,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +7822,40094,Male,Loyal Customer,44,Business travel,Business,368,1,1,1,1,3,4,3,4,4,4,4,2,4,1,0,2.0,satisfied +7823,27336,Female,Loyal Customer,55,Business travel,Eco,672,4,3,3,3,1,1,3,5,5,4,5,5,5,3,0,0.0,satisfied +7824,22574,Female,Loyal Customer,41,Business travel,Business,300,4,4,4,4,2,1,4,5,5,5,5,5,5,1,0,0.0,satisfied +7825,65282,Female,Loyal Customer,18,Personal Travel,Eco Plus,247,4,3,4,2,2,4,5,2,3,3,2,3,2,2,21,13.0,neutral or dissatisfied +7826,42529,Male,Loyal Customer,48,Personal Travel,Eco,328,4,1,4,4,1,4,1,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +7827,129685,Female,disloyal Customer,27,Business travel,Business,447,4,4,4,4,3,4,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +7828,106092,Male,disloyal Customer,21,Business travel,Eco,444,2,4,2,2,4,2,4,4,5,2,4,5,4,4,7,2.0,neutral or dissatisfied +7829,84249,Female,Loyal Customer,59,Personal Travel,Eco,829,3,4,3,4,3,5,4,5,5,3,5,4,5,4,2,2.0,neutral or dissatisfied +7830,78554,Female,Loyal Customer,35,Business travel,Eco Plus,526,1,2,2,2,1,1,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +7831,31547,Female,Loyal Customer,43,Personal Travel,Eco,967,2,4,2,1,3,4,4,4,4,2,4,5,4,4,44,49.0,neutral or dissatisfied +7832,66574,Male,disloyal Customer,40,Business travel,Eco,624,2,1,2,4,3,2,3,3,3,4,4,2,4,3,0,0.0,neutral or dissatisfied +7833,120094,Female,Loyal Customer,48,Business travel,Business,1576,3,3,3,3,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +7834,7235,Male,Loyal Customer,37,Business travel,Business,1543,2,5,5,5,2,1,2,3,3,3,2,2,3,3,0,0.0,neutral or dissatisfied +7835,121955,Female,Loyal Customer,51,Business travel,Business,2736,2,2,2,2,3,4,5,5,5,5,5,3,5,5,16,26.0,satisfied +7836,104041,Female,Loyal Customer,52,Business travel,Eco,1262,4,3,3,3,1,2,3,4,4,4,4,1,4,2,31,37.0,neutral or dissatisfied +7837,110552,Male,Loyal Customer,52,Business travel,Business,2522,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +7838,19528,Female,Loyal Customer,17,Personal Travel,Business,173,4,4,4,1,4,4,4,4,1,2,5,5,4,4,0,2.0,satisfied +7839,26091,Male,Loyal Customer,55,Business travel,Eco,591,5,1,1,1,5,5,5,5,4,2,4,2,2,5,0,2.0,satisfied +7840,70607,Female,Loyal Customer,17,Personal Travel,Eco,2611,5,2,5,4,5,5,3,3,3,4,4,3,3,3,0,0.0,satisfied +7841,15290,Female,Loyal Customer,28,Personal Travel,Eco,500,2,5,2,1,2,5,5,3,2,5,4,5,5,5,266,281.0,neutral or dissatisfied +7842,129317,Male,Loyal Customer,41,Business travel,Business,2586,2,2,2,2,5,3,4,5,5,5,5,3,5,4,0,3.0,satisfied +7843,57918,Male,Loyal Customer,60,Personal Travel,Eco,305,2,5,2,3,3,2,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +7844,83344,Male,Loyal Customer,52,Personal Travel,Eco,187,1,5,1,5,5,1,5,5,4,4,5,3,5,5,0,5.0,neutral or dissatisfied +7845,109743,Female,Loyal Customer,43,Personal Travel,Eco,468,3,4,3,2,4,2,4,3,3,3,3,1,3,2,40,35.0,neutral or dissatisfied +7846,102948,Female,Loyal Customer,57,Business travel,Business,2161,3,3,2,3,3,5,4,4,4,4,4,4,4,3,0,9.0,satisfied +7847,87939,Male,Loyal Customer,39,Personal Travel,Business,545,3,2,3,4,5,4,3,5,5,3,5,4,5,3,5,0.0,neutral or dissatisfied +7848,6819,Male,Loyal Customer,70,Personal Travel,Eco,235,2,5,2,2,4,2,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +7849,108395,Female,Loyal Customer,48,Business travel,Eco Plus,1728,2,5,5,5,5,4,3,2,2,2,2,3,2,1,26,50.0,neutral or dissatisfied +7850,60133,Male,Loyal Customer,52,Business travel,Business,1182,2,3,3,3,2,3,4,2,2,2,2,2,2,2,31,9.0,neutral or dissatisfied +7851,46099,Male,Loyal Customer,16,Personal Travel,Eco Plus,541,1,5,1,3,5,1,5,5,1,2,4,3,5,5,1,3.0,neutral or dissatisfied +7852,43758,Male,Loyal Customer,40,Business travel,Business,2738,3,4,4,4,2,2,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +7853,47751,Female,disloyal Customer,22,Business travel,Eco,451,0,0,0,1,1,0,1,1,4,4,1,4,2,1,0,0.0,satisfied +7854,27938,Female,Loyal Customer,29,Business travel,Business,1660,4,4,4,4,4,4,4,4,1,3,5,4,1,4,0,20.0,satisfied +7855,91814,Male,Loyal Customer,55,Personal Travel,Eco,588,2,5,3,1,1,3,3,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +7856,7574,Female,disloyal Customer,27,Business travel,Eco,594,1,2,1,4,1,1,1,1,2,4,3,3,4,1,0,0.0,neutral or dissatisfied +7857,106825,Female,disloyal Customer,19,Business travel,Eco,817,5,5,5,2,3,5,3,3,2,3,1,2,4,3,6,6.0,satisfied +7858,25631,Female,Loyal Customer,51,Business travel,Eco,666,2,2,2,2,2,4,4,2,2,2,2,4,2,2,24,16.0,neutral or dissatisfied +7859,68372,Male,Loyal Customer,58,Personal Travel,Business,1045,2,4,2,1,5,5,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +7860,16809,Female,Loyal Customer,41,Business travel,Business,2713,4,4,4,4,3,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +7861,89707,Male,Loyal Customer,51,Personal Travel,Eco,1010,3,5,3,3,1,3,1,1,3,1,2,4,2,1,0,0.0,neutral or dissatisfied +7862,25611,Female,disloyal Customer,39,Business travel,Business,666,1,1,1,4,2,1,3,2,1,2,3,1,4,2,26,0.0,neutral or dissatisfied +7863,53464,Male,disloyal Customer,29,Business travel,Eco,2442,5,5,5,2,5,3,3,1,3,5,1,3,3,3,0,2.0,satisfied +7864,12487,Male,Loyal Customer,52,Business travel,Eco Plus,253,5,2,2,2,5,5,5,5,2,5,5,4,5,5,0,0.0,satisfied +7865,57991,Female,Loyal Customer,44,Business travel,Business,3551,1,2,2,2,4,3,4,1,1,1,1,1,1,1,51,41.0,neutral or dissatisfied +7866,122834,Female,Loyal Customer,61,Business travel,Business,2524,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +7867,122616,Male,Loyal Customer,52,Personal Travel,Eco,728,3,5,3,4,4,3,4,4,1,1,2,4,4,4,0,1.0,neutral or dissatisfied +7868,11794,Female,Loyal Customer,45,Personal Travel,Eco,429,2,2,2,3,3,3,4,2,2,2,2,4,2,1,70,55.0,neutral or dissatisfied +7869,26876,Female,Loyal Customer,51,Personal Travel,Eco,2329,1,2,1,1,1,2,1,4,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +7870,86730,Female,Loyal Customer,8,Personal Travel,Eco,1747,2,0,2,3,1,2,1,1,1,2,3,5,5,1,0,0.0,neutral or dissatisfied +7871,111450,Female,Loyal Customer,12,Business travel,Business,2717,3,4,4,4,3,3,3,3,4,4,3,4,3,3,26,19.0,neutral or dissatisfied +7872,45039,Female,Loyal Customer,18,Personal Travel,Business,323,3,4,3,4,3,3,1,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +7873,57605,Female,Loyal Customer,44,Business travel,Business,563,5,5,5,5,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +7874,24129,Female,disloyal Customer,65,Personal Travel,Eco,584,1,1,1,4,4,1,4,4,3,4,4,4,3,4,0,13.0,neutral or dissatisfied +7875,60037,Female,disloyal Customer,46,Business travel,Business,1023,3,3,3,3,2,3,2,2,3,2,5,5,4,2,10,6.0,neutral or dissatisfied +7876,66292,Female,Loyal Customer,52,Business travel,Business,852,5,5,5,5,3,4,4,4,4,4,4,4,4,5,32,23.0,satisfied +7877,12953,Male,Loyal Customer,16,Personal Travel,Eco,674,4,4,4,2,3,4,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +7878,119859,Male,Loyal Customer,60,Business travel,Eco,936,2,3,5,5,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +7879,93454,Male,Loyal Customer,41,Personal Travel,Eco,671,3,3,3,1,3,3,1,3,1,3,2,3,1,3,0,0.0,neutral or dissatisfied +7880,51562,Female,Loyal Customer,69,Business travel,Eco,370,1,2,2,2,2,2,2,1,1,1,1,4,1,4,1,8.0,neutral or dissatisfied +7881,56095,Female,Loyal Customer,34,Business travel,Business,1628,3,3,3,3,2,3,4,3,3,3,3,3,3,2,6,0.0,neutral or dissatisfied +7882,2558,Female,disloyal Customer,61,Business travel,Eco,304,4,2,4,3,4,4,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +7883,46617,Female,Loyal Customer,31,Business travel,Business,2239,0,5,0,2,3,3,3,3,2,5,3,4,5,3,0,0.0,satisfied +7884,62360,Male,Loyal Customer,22,Personal Travel,Eco,1589,5,5,5,2,1,5,3,1,4,2,5,5,4,1,15,0.0,satisfied +7885,7111,Female,Loyal Customer,37,Personal Travel,Eco,177,2,5,2,4,5,2,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +7886,8733,Female,Loyal Customer,46,Business travel,Business,3384,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +7887,3485,Female,Loyal Customer,39,Business travel,Business,990,3,2,2,2,5,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +7888,69096,Female,Loyal Customer,59,Personal Travel,Eco,1389,4,4,4,1,2,4,5,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +7889,123082,Male,Loyal Customer,49,Business travel,Business,468,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +7890,32756,Female,Loyal Customer,66,Business travel,Business,101,2,3,3,3,2,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +7891,115572,Female,Loyal Customer,56,Business travel,Eco,337,2,3,3,3,5,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +7892,43996,Female,Loyal Customer,37,Business travel,Business,1586,2,2,3,2,4,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +7893,61172,Female,disloyal Customer,32,Business travel,Business,776,2,2,2,3,1,2,5,1,3,2,5,5,5,1,22,25.0,neutral or dissatisfied +7894,1684,Female,disloyal Customer,22,Business travel,Eco,561,1,0,1,1,4,1,4,4,5,3,5,4,4,4,35,39.0,neutral or dissatisfied +7895,21325,Female,disloyal Customer,27,Business travel,Business,674,3,3,3,2,1,3,1,1,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +7896,61263,Female,Loyal Customer,40,Personal Travel,Eco,853,3,4,3,2,1,3,1,1,4,5,5,5,4,1,0,2.0,neutral or dissatisfied +7897,43296,Female,Loyal Customer,52,Business travel,Eco,387,2,2,2,2,2,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +7898,96628,Female,disloyal Customer,28,Business travel,Eco,937,3,3,3,3,3,3,1,3,3,2,4,2,4,3,2,0.0,neutral or dissatisfied +7899,109475,Female,disloyal Customer,21,Business travel,Eco,994,1,1,1,2,3,1,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +7900,87208,Male,Loyal Customer,37,Personal Travel,Eco,946,3,5,2,2,2,2,2,2,4,3,5,2,5,2,0,0.0,neutral or dissatisfied +7901,30106,Female,Loyal Customer,21,Personal Travel,Eco,503,3,4,3,1,4,3,4,4,5,5,5,5,4,4,16,26.0,neutral or dissatisfied +7902,11923,Male,Loyal Customer,28,Personal Travel,Eco,501,2,4,2,1,2,2,1,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +7903,97264,Male,Loyal Customer,34,Personal Travel,Eco,296,0,4,0,2,2,0,2,2,5,3,4,5,5,2,3,3.0,satisfied +7904,127314,Male,Loyal Customer,7,Personal Travel,Eco,1979,2,5,2,5,3,2,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +7905,78424,Male,Loyal Customer,44,Business travel,Business,666,2,2,5,2,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +7906,41699,Male,Loyal Customer,35,Personal Travel,Eco,347,2,5,2,1,1,2,1,1,5,4,4,3,5,1,0,3.0,neutral or dissatisfied +7907,30538,Male,Loyal Customer,19,Personal Travel,Eco,701,3,4,3,4,2,3,2,2,4,5,5,4,3,2,11,33.0,neutral or dissatisfied +7908,105437,Female,Loyal Customer,43,Business travel,Business,1669,4,4,4,4,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +7909,104271,Male,Loyal Customer,39,Business travel,Business,1733,2,2,2,2,3,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +7910,75973,Male,Loyal Customer,69,Business travel,Business,297,1,1,1,1,4,1,3,4,4,4,4,4,4,5,0,0.0,satisfied +7911,49065,Male,Loyal Customer,45,Business travel,Eco,86,4,1,1,1,4,4,4,4,1,5,2,4,4,4,0,3.0,satisfied +7912,28475,Male,Loyal Customer,47,Business travel,Business,1721,3,4,3,4,2,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +7913,52984,Female,Loyal Customer,59,Business travel,Eco,1208,3,1,1,1,5,1,5,3,3,3,3,3,3,5,25,26.0,satisfied +7914,71024,Female,Loyal Customer,43,Business travel,Eco,978,4,4,4,4,4,4,4,4,4,4,4,1,4,2,15,0.0,neutral or dissatisfied +7915,76203,Male,Loyal Customer,25,Personal Travel,Eco,2422,3,5,3,4,1,3,1,1,4,3,5,5,5,1,7,0.0,neutral or dissatisfied +7916,36417,Female,Loyal Customer,55,Business travel,Eco,369,4,3,3,3,3,5,2,4,4,4,4,4,4,4,0,7.0,satisfied +7917,69344,Female,Loyal Customer,59,Business travel,Business,944,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,9.0,satisfied +7918,61298,Male,Loyal Customer,9,Personal Travel,Eco,967,3,1,3,3,4,3,4,4,1,4,2,3,3,4,4,0.0,neutral or dissatisfied +7919,125022,Male,Loyal Customer,14,Personal Travel,Eco,184,3,4,3,3,1,3,1,1,3,1,3,3,4,1,0,0.0,neutral or dissatisfied +7920,32815,Female,Loyal Customer,49,Business travel,Eco,101,3,3,3,3,3,4,4,3,3,3,3,3,3,1,13,29.0,neutral or dissatisfied +7921,87141,Male,Loyal Customer,22,Business travel,Eco Plus,640,1,2,2,2,1,1,2,1,3,3,3,1,3,1,57,53.0,neutral or dissatisfied +7922,32195,Female,Loyal Customer,42,Business travel,Business,2478,2,3,3,3,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +7923,65298,Male,Loyal Customer,30,Personal Travel,Eco Plus,551,1,5,1,5,1,1,1,1,5,2,2,1,4,1,0,3.0,neutral or dissatisfied +7924,86670,Male,Loyal Customer,30,Business travel,Business,3520,5,5,5,5,5,5,5,5,4,3,5,3,5,5,5,0.0,satisfied +7925,56329,Male,Loyal Customer,42,Business travel,Business,3088,0,5,0,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +7926,108080,Male,Loyal Customer,58,Business travel,Business,1166,3,3,3,3,2,4,4,4,4,5,4,3,4,5,2,0.0,satisfied +7927,19223,Male,disloyal Customer,34,Business travel,Eco,459,2,3,3,4,2,3,2,2,1,3,1,5,4,2,0,0.0,neutral or dissatisfied +7928,62776,Female,Loyal Customer,39,Business travel,Business,899,4,4,4,4,1,4,5,5,5,5,5,4,5,5,1,16.0,satisfied +7929,106355,Male,disloyal Customer,23,Business travel,Eco,551,0,5,0,2,5,0,5,5,3,4,4,4,4,5,0,0.0,satisfied +7930,20408,Male,Loyal Customer,39,Business travel,Business,299,5,5,3,5,3,2,3,5,5,5,5,3,5,2,0,21.0,satisfied +7931,113610,Male,Loyal Customer,52,Personal Travel,Eco,397,2,5,2,3,4,2,4,4,5,5,5,4,2,4,3,4.0,neutral or dissatisfied +7932,76057,Male,Loyal Customer,54,Business travel,Business,669,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +7933,115670,Female,Loyal Customer,20,Business travel,Business,1569,3,5,2,5,3,3,3,3,3,3,2,2,2,3,2,0.0,neutral or dissatisfied +7934,126156,Male,disloyal Customer,24,Business travel,Eco,600,1,3,1,3,4,1,4,4,3,5,4,4,4,4,0,6.0,neutral or dissatisfied +7935,15082,Female,disloyal Customer,39,Business travel,Business,239,4,3,3,4,5,3,5,5,4,2,5,3,2,5,0,0.0,satisfied +7936,90648,Female,Loyal Customer,33,Business travel,Business,3636,2,2,2,2,3,4,5,5,5,5,5,3,5,5,5,14.0,satisfied +7937,76890,Female,disloyal Customer,41,Business travel,Business,630,5,5,5,5,2,5,3,2,3,2,5,3,4,2,0,0.0,satisfied +7938,73619,Male,Loyal Customer,41,Business travel,Business,3329,4,3,4,4,3,4,4,4,4,4,4,3,4,3,29,24.0,satisfied +7939,66968,Female,Loyal Customer,29,Business travel,Business,1119,1,1,1,1,5,5,5,5,3,2,4,5,5,5,0,6.0,satisfied +7940,69334,Male,Loyal Customer,42,Business travel,Eco,1096,2,4,4,4,2,2,2,2,3,5,3,2,3,2,0,22.0,neutral or dissatisfied +7941,18313,Male,Loyal Customer,42,Business travel,Eco,715,5,1,1,1,5,5,5,5,2,3,1,5,3,5,0,0.0,satisfied +7942,37340,Male,Loyal Customer,44,Business travel,Eco,1035,4,5,3,5,4,4,4,4,2,5,5,3,5,4,37,25.0,satisfied +7943,95400,Male,Loyal Customer,20,Personal Travel,Eco,148,2,4,2,3,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +7944,97131,Female,disloyal Customer,29,Business travel,Business,1390,3,3,3,2,4,3,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +7945,77953,Male,Loyal Customer,39,Business travel,Business,3441,3,3,2,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +7946,125668,Male,Loyal Customer,32,Business travel,Business,899,4,4,4,4,3,3,3,3,4,5,4,3,5,3,0,0.0,satisfied +7947,86826,Male,Loyal Customer,39,Business travel,Eco,484,1,2,2,2,1,1,1,1,2,3,3,4,4,1,34,27.0,neutral or dissatisfied +7948,7679,Male,Loyal Customer,30,Business travel,Business,2971,2,2,3,2,4,4,4,4,1,1,1,4,3,4,8,12.0,satisfied +7949,28411,Male,Loyal Customer,27,Business travel,Eco Plus,1709,3,3,3,3,3,3,3,3,2,2,4,1,4,3,0,0.0,neutral or dissatisfied +7950,99459,Female,Loyal Customer,44,Business travel,Business,283,5,5,5,5,4,5,4,4,4,4,4,4,4,5,11,18.0,satisfied +7951,124245,Male,Loyal Customer,18,Personal Travel,Eco,1916,4,5,4,1,4,4,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +7952,23880,Male,disloyal Customer,16,Business travel,Eco,589,3,0,4,5,2,4,2,2,3,5,4,5,2,2,0,0.0,neutral or dissatisfied +7953,126077,Female,disloyal Customer,29,Business travel,Business,600,2,1,1,1,4,1,4,4,4,3,4,3,5,4,3,0.0,neutral or dissatisfied +7954,107407,Male,Loyal Customer,52,Business travel,Business,2654,1,1,1,1,3,4,3,1,1,1,1,1,1,4,1,0.0,neutral or dissatisfied +7955,106306,Male,Loyal Customer,12,Business travel,Business,1851,3,2,2,2,3,3,3,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +7956,98684,Female,Loyal Customer,41,Personal Travel,Eco,992,4,5,5,2,1,5,1,1,4,5,4,5,5,1,0,0.0,satisfied +7957,104452,Male,Loyal Customer,48,Business travel,Business,2500,5,5,5,5,2,4,4,5,5,5,5,5,5,3,15,0.0,satisfied +7958,115126,Female,Loyal Customer,57,Business travel,Business,308,0,0,0,1,5,4,5,4,4,4,4,5,4,4,57,55.0,satisfied +7959,22954,Female,Loyal Customer,27,Business travel,Business,817,1,1,1,1,2,2,2,2,4,4,1,1,2,2,20,13.0,satisfied +7960,78325,Female,Loyal Customer,30,Business travel,Business,1547,1,1,1,1,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +7961,68676,Male,disloyal Customer,38,Business travel,Eco,175,2,3,2,2,1,2,2,1,3,4,3,3,5,1,0,0.0,neutral or dissatisfied +7962,108368,Male,Loyal Customer,50,Personal Travel,Eco,1750,1,1,1,3,3,1,1,3,1,5,4,3,4,3,10,17.0,neutral or dissatisfied +7963,81112,Female,Loyal Customer,40,Business travel,Business,991,5,5,5,5,2,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +7964,70680,Male,Loyal Customer,23,Personal Travel,Eco,447,4,4,3,4,1,3,1,1,2,1,4,3,1,1,0,0.0,neutral or dissatisfied +7965,43382,Female,Loyal Customer,57,Personal Travel,Eco,387,1,5,4,3,3,5,4,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +7966,88363,Male,Loyal Customer,55,Business travel,Eco,581,4,4,4,4,4,4,4,4,4,1,3,4,4,4,0,3.0,neutral or dissatisfied +7967,86147,Male,disloyal Customer,45,Business travel,Business,356,2,2,2,4,5,2,5,5,4,2,4,3,5,5,15,5.0,neutral or dissatisfied +7968,78787,Female,Loyal Customer,39,Business travel,Business,2197,3,5,5,5,5,3,4,3,3,3,3,1,3,1,0,31.0,neutral or dissatisfied +7969,62119,Female,disloyal Customer,42,Business travel,Business,1289,4,4,4,4,1,4,1,1,5,5,5,4,4,1,0,0.0,satisfied +7970,31409,Female,Loyal Customer,18,Business travel,Business,1546,3,3,3,3,4,4,4,4,4,3,5,2,2,4,95,105.0,satisfied +7971,52950,Female,Loyal Customer,32,Personal Travel,Eco,1448,3,2,3,3,5,3,5,5,1,1,4,4,4,5,72,55.0,neutral or dissatisfied +7972,50789,Female,Loyal Customer,11,Personal Travel,Eco,326,2,1,2,3,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +7973,75180,Male,disloyal Customer,49,Business travel,Business,1726,3,3,3,4,5,3,4,5,5,2,3,4,5,5,0,0.0,neutral or dissatisfied +7974,20677,Female,Loyal Customer,57,Business travel,Eco,152,3,5,5,5,3,3,3,2,4,4,4,3,2,3,131,151.0,neutral or dissatisfied +7975,73252,Male,Loyal Customer,52,Business travel,Business,3792,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +7976,53120,Male,Loyal Customer,33,Business travel,Business,2065,2,2,2,2,2,3,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +7977,106400,Male,Loyal Customer,41,Business travel,Eco,488,5,3,3,3,5,5,5,5,5,4,3,1,3,5,0,0.0,satisfied +7978,120585,Female,Loyal Customer,35,Business travel,Business,980,3,3,3,3,2,3,4,3,3,3,3,4,3,4,8,45.0,neutral or dissatisfied +7979,61109,Male,Loyal Customer,65,Personal Travel,Eco,1546,2,4,2,5,1,2,1,1,4,5,5,3,5,1,9,0.0,neutral or dissatisfied +7980,28124,Male,Loyal Customer,42,Business travel,Eco,859,5,2,2,2,5,5,5,5,5,5,2,5,1,5,0,0.0,satisfied +7981,119549,Male,Loyal Customer,70,Personal Travel,Eco,759,4,4,4,2,2,4,5,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +7982,85327,Male,Loyal Customer,46,Personal Travel,Eco,813,4,1,4,1,5,4,5,5,3,4,2,4,1,5,63,36.0,neutral or dissatisfied +7983,23137,Female,Loyal Customer,54,Business travel,Business,3637,2,4,4,4,2,4,3,1,1,1,2,3,1,2,6,0.0,neutral or dissatisfied +7984,8933,Female,disloyal Customer,29,Business travel,Eco Plus,984,3,3,3,3,5,3,5,5,1,5,3,1,4,5,113,109.0,neutral or dissatisfied +7985,36249,Female,disloyal Customer,26,Business travel,Eco,612,3,3,3,5,2,3,2,2,3,1,1,5,2,2,0,0.0,neutral or dissatisfied +7986,7328,Female,Loyal Customer,52,Business travel,Business,3287,1,2,3,2,4,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +7987,100538,Male,Loyal Customer,8,Personal Travel,Eco,580,3,5,3,3,4,3,4,4,3,4,3,4,4,4,5,0.0,neutral or dissatisfied +7988,27436,Male,Loyal Customer,43,Business travel,Business,937,4,4,4,4,2,4,2,4,4,4,4,3,4,5,0,0.0,satisfied +7989,63405,Male,Loyal Customer,7,Personal Travel,Eco,447,4,5,2,3,4,2,4,4,3,5,5,3,5,4,0,0.0,satisfied +7990,100082,Male,Loyal Customer,55,Personal Travel,Eco Plus,281,1,4,1,3,1,1,1,1,4,3,4,5,4,1,4,6.0,neutral or dissatisfied +7991,89500,Female,Loyal Customer,28,Business travel,Business,655,2,1,1,1,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +7992,89445,Female,Loyal Customer,68,Personal Travel,Eco,134,1,5,1,2,2,4,4,1,1,1,1,3,1,4,16,14.0,neutral or dissatisfied +7993,49395,Female,disloyal Customer,22,Business travel,Eco,109,5,0,5,2,5,5,2,5,3,2,1,4,2,5,69,69.0,satisfied +7994,88660,Male,Loyal Customer,57,Personal Travel,Eco,404,2,4,5,4,3,5,3,3,4,3,4,3,4,3,54,79.0,neutral or dissatisfied +7995,64476,Female,Loyal Customer,47,Business travel,Business,551,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,18.0,satisfied +7996,55055,Female,Loyal Customer,54,Business travel,Business,1609,4,4,4,4,4,4,4,5,5,5,5,3,5,3,6,9.0,satisfied +7997,558,Male,Loyal Customer,42,Business travel,Business,164,3,3,3,3,5,5,4,4,4,5,5,5,4,5,0,0.0,satisfied +7998,112787,Female,Loyal Customer,44,Business travel,Business,1129,4,4,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +7999,18243,Male,disloyal Customer,37,Business travel,Eco,137,1,0,1,2,3,1,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +8000,55018,Male,Loyal Customer,40,Business travel,Business,1379,4,4,4,4,3,4,4,5,5,5,5,5,5,4,99,109.0,satisfied +8001,122368,Male,Loyal Customer,26,Business travel,Business,1506,3,2,2,2,3,3,3,3,4,1,3,2,4,3,13,13.0,neutral or dissatisfied +8002,35906,Male,Loyal Customer,22,Personal Travel,Business,2248,4,4,4,1,4,4,4,4,3,3,4,4,4,4,41,12.0,neutral or dissatisfied +8003,63535,Female,disloyal Customer,47,Business travel,Eco,609,4,1,4,1,3,4,3,3,2,1,2,2,1,3,0,0.0,neutral or dissatisfied +8004,41839,Female,Loyal Customer,35,Business travel,Business,462,3,4,4,4,5,4,3,3,3,3,3,3,3,4,0,31.0,neutral or dissatisfied +8005,75213,Male,Loyal Customer,56,Business travel,Eco,1829,3,4,4,4,3,3,3,2,4,2,3,3,3,3,191,182.0,neutral or dissatisfied +8006,57543,Male,Loyal Customer,48,Personal Travel,Eco,413,2,5,2,1,3,2,3,3,4,2,5,5,5,3,34,34.0,neutral or dissatisfied +8007,70186,Female,Loyal Customer,40,Business travel,Eco,258,4,2,2,2,4,4,4,4,1,4,4,1,3,4,8,11.0,neutral or dissatisfied +8008,75711,Male,Loyal Customer,45,Business travel,Business,1743,2,2,2,2,5,4,4,2,2,2,2,3,2,5,17,20.0,satisfied +8009,13371,Female,Loyal Customer,24,Personal Travel,Eco,748,4,4,4,1,1,4,4,1,2,5,1,3,5,1,0,0.0,neutral or dissatisfied +8010,122484,Male,Loyal Customer,51,Personal Travel,Eco,575,3,4,3,1,3,3,3,3,1,4,1,2,4,3,0,0.0,neutral or dissatisfied +8011,11847,Male,Loyal Customer,40,Business travel,Business,1843,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +8012,2977,Female,Loyal Customer,16,Business travel,Business,3063,4,5,5,5,4,4,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +8013,36795,Male,Loyal Customer,33,Personal Travel,Eco,2704,2,5,2,4,2,1,1,4,5,3,4,1,5,1,2,45.0,neutral or dissatisfied +8014,4604,Male,Loyal Customer,39,Business travel,Business,3861,1,1,1,1,4,4,5,5,5,5,5,4,5,3,0,1.0,satisfied +8015,90052,Female,Loyal Customer,16,Business travel,Eco,1127,3,4,4,4,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +8016,925,Female,disloyal Customer,45,Business travel,Business,282,3,3,3,4,5,3,5,5,1,4,3,1,3,5,2,0.0,neutral or dissatisfied +8017,85137,Male,Loyal Customer,28,Business travel,Business,874,2,2,2,2,2,2,2,2,1,5,3,3,4,2,47,26.0,neutral or dissatisfied +8018,67889,Male,Loyal Customer,20,Personal Travel,Eco,1205,5,2,5,3,1,2,1,1,1,4,4,2,4,1,0,0.0,satisfied +8019,18391,Male,disloyal Customer,43,Business travel,Eco,378,3,0,4,5,2,4,2,2,3,5,5,1,3,2,0,0.0,neutral or dissatisfied +8020,1634,Female,Loyal Customer,21,Personal Travel,Eco,999,3,3,3,3,2,3,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +8021,103962,Female,Loyal Customer,18,Personal Travel,Eco,533,2,1,2,3,5,2,4,5,1,3,3,3,4,5,25,11.0,neutral or dissatisfied +8022,67229,Male,Loyal Customer,69,Personal Travel,Eco,964,2,5,1,2,2,1,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +8023,63140,Male,Loyal Customer,55,Personal Travel,Business,337,3,5,3,4,5,5,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +8024,67875,Male,Loyal Customer,65,Personal Travel,Eco,1171,1,3,1,4,3,1,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +8025,50057,Male,Loyal Customer,52,Business travel,Eco,326,4,4,4,4,4,4,4,4,3,4,1,1,1,4,0,0.0,satisfied +8026,55296,Male,Loyal Customer,38,Personal Travel,Eco,1608,2,5,2,1,3,2,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +8027,52440,Male,Loyal Customer,40,Personal Travel,Eco,370,3,2,3,1,4,3,4,4,4,1,1,1,2,4,0,0.0,neutral or dissatisfied +8028,90985,Male,Loyal Customer,41,Business travel,Business,3224,5,5,3,5,5,4,4,5,5,5,5,2,5,5,0,0.0,satisfied +8029,28308,Female,Loyal Customer,29,Business travel,Business,867,4,4,4,4,3,4,3,3,3,5,2,4,3,3,0,0.0,satisfied +8030,87369,Female,Loyal Customer,44,Business travel,Business,3541,2,2,2,2,2,4,3,2,2,3,2,2,2,4,11,18.0,neutral or dissatisfied +8031,66500,Female,Loyal Customer,42,Business travel,Business,2650,3,4,2,4,5,4,4,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +8032,60750,Female,disloyal Customer,36,Business travel,Business,628,2,2,2,3,2,2,3,2,3,3,5,3,4,2,7,19.0,neutral or dissatisfied +8033,28461,Male,Loyal Customer,34,Personal Travel,Eco,2588,2,5,2,4,2,3,4,5,3,3,4,4,5,4,10,1.0,neutral or dissatisfied +8034,31963,Male,Loyal Customer,52,Business travel,Business,3681,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +8035,64304,Female,Loyal Customer,40,Business travel,Business,2075,5,5,5,5,5,5,5,2,2,2,2,4,2,4,0,,satisfied +8036,51790,Female,Loyal Customer,11,Personal Travel,Eco,370,1,1,1,4,3,1,4,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +8037,63773,Female,disloyal Customer,28,Business travel,Business,1293,5,5,5,1,2,5,2,2,5,4,3,5,4,2,1,0.0,satisfied +8038,37820,Male,disloyal Customer,35,Business travel,Business,937,3,3,3,1,1,3,1,1,5,3,5,3,5,1,1,22.0,neutral or dissatisfied +8039,45154,Male,Loyal Customer,43,Business travel,Business,3781,3,3,3,3,1,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +8040,60059,Male,Loyal Customer,41,Personal Travel,Eco Plus,997,2,5,2,4,1,2,1,1,5,4,4,5,5,1,5,0.0,neutral or dissatisfied +8041,206,Male,Loyal Customer,53,Business travel,Business,3728,3,4,4,4,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +8042,74041,Male,Loyal Customer,46,Business travel,Business,2378,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +8043,96270,Male,Loyal Customer,14,Personal Travel,Eco,460,2,5,2,3,4,2,5,4,4,1,1,3,3,4,0,0.0,neutral or dissatisfied +8044,124997,Male,Loyal Customer,51,Business travel,Business,3778,5,5,5,5,5,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +8045,118762,Female,Loyal Customer,60,Personal Travel,Eco,646,2,3,2,3,3,3,3,2,2,2,2,4,2,3,0,6.0,neutral or dissatisfied +8046,74693,Male,Loyal Customer,51,Personal Travel,Eco,1464,2,4,2,2,1,2,1,1,4,5,4,5,4,1,49,39.0,neutral or dissatisfied +8047,68575,Male,Loyal Customer,21,Business travel,Business,1616,5,5,5,5,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +8048,104311,Male,Loyal Customer,15,Personal Travel,Business,528,2,4,2,1,2,2,2,2,4,1,2,4,3,2,3,13.0,neutral or dissatisfied +8049,80429,Female,Loyal Customer,34,Business travel,Business,2248,2,2,2,2,4,1,2,5,5,5,5,4,5,4,0,0.0,satisfied +8050,95853,Male,Loyal Customer,54,Business travel,Business,580,3,3,3,3,2,4,4,4,4,4,4,4,4,4,6,0.0,satisfied +8051,123490,Female,Loyal Customer,48,Business travel,Business,2077,5,5,2,5,4,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +8052,98146,Female,Loyal Customer,24,Business travel,Business,3037,3,3,3,3,2,2,2,2,4,4,4,3,4,2,16,5.0,satisfied +8053,35560,Female,Loyal Customer,40,Business travel,Eco Plus,1076,4,3,4,3,4,4,4,4,4,3,4,2,3,4,0,0.0,satisfied +8054,45403,Male,disloyal Customer,25,Business travel,Eco,649,3,4,2,4,4,2,4,4,3,5,1,4,5,4,0,0.0,neutral or dissatisfied +8055,64492,Female,disloyal Customer,24,Business travel,Business,551,4,0,4,3,4,4,4,4,4,3,5,4,4,4,0,17.0,satisfied +8056,101360,Female,disloyal Customer,26,Business travel,Business,1986,4,4,4,1,4,4,4,4,5,5,4,3,4,4,87,85.0,neutral or dissatisfied +8057,127106,Female,Loyal Customer,40,Personal Travel,Eco,621,2,5,2,4,5,2,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +8058,92329,Male,Loyal Customer,29,Business travel,Business,2615,2,2,4,2,4,4,4,4,5,3,5,4,3,4,0,20.0,satisfied +8059,6948,Female,disloyal Customer,25,Business travel,Eco,501,3,5,3,1,3,3,3,3,2,5,3,5,1,3,0,0.0,neutral or dissatisfied +8060,106576,Female,Loyal Customer,51,Business travel,Business,1506,2,5,5,5,3,2,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +8061,60637,Female,disloyal Customer,23,Business travel,Eco,1380,4,4,4,1,1,4,1,1,4,4,4,5,5,1,0,0.0,satisfied +8062,10708,Female,Loyal Customer,37,Business travel,Business,2140,1,1,1,1,5,5,4,5,5,5,5,4,5,5,111,106.0,satisfied +8063,41176,Female,Loyal Customer,56,Business travel,Business,468,4,3,3,3,5,3,3,4,4,3,4,3,4,1,0,12.0,neutral or dissatisfied +8064,56467,Female,disloyal Customer,27,Business travel,Eco Plus,719,1,1,1,3,2,1,2,2,3,2,4,2,3,2,61,46.0,neutral or dissatisfied +8065,116384,Male,Loyal Customer,41,Personal Travel,Eco,404,2,3,2,2,2,2,2,2,1,3,1,2,2,2,0,0.0,neutral or dissatisfied +8066,45891,Female,Loyal Customer,40,Business travel,Business,1557,5,5,5,5,1,1,3,4,4,4,4,3,4,4,0,0.0,satisfied +8067,80257,Male,Loyal Customer,40,Business travel,Eco,1969,1,2,2,2,1,1,1,1,2,2,2,4,4,1,0,0.0,neutral or dissatisfied +8068,89115,Male,Loyal Customer,44,Business travel,Business,2116,2,2,2,2,4,4,4,4,4,4,4,3,4,3,25,14.0,satisfied +8069,101954,Male,Loyal Customer,38,Business travel,Business,3660,4,4,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +8070,126770,Male,Loyal Customer,42,Business travel,Business,2521,3,3,3,3,2,5,4,2,2,2,2,3,2,5,3,0.0,satisfied +8071,9024,Female,Loyal Customer,31,Business travel,Eco,173,2,1,1,1,2,2,2,2,2,2,3,2,4,2,120,114.0,neutral or dissatisfied +8072,36752,Male,Loyal Customer,50,Business travel,Business,2611,1,1,1,1,4,4,4,1,1,3,2,4,2,4,21,54.0,satisfied +8073,89639,Female,disloyal Customer,29,Business travel,Business,1096,5,5,5,1,3,5,3,3,5,5,4,5,4,3,0,0.0,satisfied +8074,113541,Female,Loyal Customer,55,Business travel,Business,2836,1,5,5,5,2,3,3,2,2,2,1,2,2,4,19,20.0,neutral or dissatisfied +8075,69589,Male,Loyal Customer,17,Personal Travel,Eco,2586,2,4,2,4,2,4,4,5,2,4,5,4,4,4,0,15.0,neutral or dissatisfied +8076,42128,Male,Loyal Customer,34,Business travel,Eco Plus,964,5,4,4,4,5,5,5,5,1,1,3,4,3,5,0,18.0,satisfied +8077,4275,Female,disloyal Customer,50,Business travel,Eco,502,2,2,2,3,4,2,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +8078,22614,Female,disloyal Customer,39,Business travel,Eco,300,3,0,3,4,3,3,2,3,4,1,1,4,2,3,0,0.0,neutral or dissatisfied +8079,68467,Male,disloyal Customer,22,Business travel,Eco,1303,3,3,3,5,4,3,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +8080,109550,Female,Loyal Customer,8,Personal Travel,Eco,834,2,4,2,3,3,2,2,3,4,5,1,2,4,3,0,0.0,neutral or dissatisfied +8081,6574,Female,Loyal Customer,55,Business travel,Eco,528,3,1,1,1,5,4,3,3,3,3,3,3,3,1,48,31.0,neutral or dissatisfied +8082,64717,Female,disloyal Customer,18,Business travel,Eco,247,2,2,1,4,4,1,4,4,4,4,3,2,3,4,3,0.0,neutral or dissatisfied +8083,69240,Female,Loyal Customer,29,Business travel,Business,740,3,3,3,3,4,4,4,5,3,5,5,4,3,4,219,223.0,satisfied +8084,119520,Female,Loyal Customer,46,Business travel,Eco,759,3,5,5,5,4,4,4,2,2,3,2,2,2,3,7,9.0,satisfied +8085,17275,Male,Loyal Customer,52,Personal Travel,Eco,1092,4,2,4,1,4,4,4,4,1,3,1,1,2,4,19,33.0,neutral or dissatisfied +8086,19319,Male,disloyal Customer,24,Business travel,Eco,743,2,2,2,4,4,2,4,4,4,1,3,5,2,4,14,18.0,neutral or dissatisfied +8087,93795,Female,disloyal Customer,18,Business travel,Eco,1259,3,4,4,4,4,4,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +8088,115064,Female,Loyal Customer,47,Business travel,Business,1963,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +8089,53999,Male,Loyal Customer,10,Personal Travel,Eco,1825,3,4,3,4,1,3,1,1,2,2,3,4,4,1,0,0.0,neutral or dissatisfied +8090,43186,Female,Loyal Customer,35,Personal Travel,Eco,282,2,4,5,4,3,5,3,3,4,3,4,3,5,3,0,31.0,neutral or dissatisfied +8091,14679,Female,Loyal Customer,52,Business travel,Eco Plus,416,5,1,1,1,3,2,4,5,5,5,5,1,5,1,0,3.0,satisfied +8092,47741,Male,Loyal Customer,9,Personal Travel,Business,451,3,2,3,4,2,3,5,2,2,2,3,1,4,2,9,10.0,neutral or dissatisfied +8093,106346,Female,disloyal Customer,41,Business travel,Business,488,2,1,1,4,4,4,4,4,4,5,3,2,4,4,18,13.0,neutral or dissatisfied +8094,1207,Male,Loyal Customer,42,Personal Travel,Eco,282,3,5,3,4,1,3,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +8095,27513,Male,Loyal Customer,57,Personal Travel,Eco,1050,1,5,1,3,2,1,3,2,4,5,5,4,4,2,3,0.0,neutral or dissatisfied +8096,114891,Male,Loyal Customer,52,Business travel,Business,2261,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +8097,43202,Female,disloyal Customer,18,Business travel,Eco,466,2,3,2,4,2,2,2,2,5,4,3,2,1,2,142,137.0,neutral or dissatisfied +8098,119240,Female,Loyal Customer,56,Business travel,Business,3576,1,1,1,1,3,5,4,4,4,4,4,5,4,3,18,22.0,satisfied +8099,83048,Male,Loyal Customer,51,Business travel,Business,2437,3,3,3,3,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +8100,12570,Female,Loyal Customer,8,Business travel,Eco Plus,788,3,1,1,1,3,3,2,3,3,2,4,1,4,3,0,8.0,neutral or dissatisfied +8101,125348,Male,Loyal Customer,38,Business travel,Business,2566,2,3,3,3,3,3,3,2,2,2,2,4,2,3,0,5.0,neutral or dissatisfied +8102,3188,Male,Loyal Customer,31,Business travel,Business,1900,2,3,3,3,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +8103,47150,Male,Loyal Customer,44,Business travel,Business,1840,1,1,1,1,3,4,2,5,5,5,5,1,5,1,0,6.0,satisfied +8104,118374,Female,Loyal Customer,50,Business travel,Business,646,5,5,5,5,5,5,4,5,5,5,5,5,5,4,65,72.0,satisfied +8105,123607,Male,Loyal Customer,61,Personal Travel,Eco,1773,5,4,5,3,4,5,4,4,3,4,2,3,4,4,1,0.0,satisfied +8106,30205,Female,Loyal Customer,59,Personal Travel,Eco Plus,95,2,3,2,4,3,4,2,5,5,2,3,1,5,3,0,0.0,neutral or dissatisfied +8107,116883,Male,disloyal Customer,40,Business travel,Business,325,4,4,4,3,2,4,2,2,3,4,5,4,4,2,0,0.0,satisfied +8108,77107,Male,Loyal Customer,27,Business travel,Eco,1481,2,1,1,1,2,2,2,2,3,4,1,3,2,2,29,19.0,neutral or dissatisfied +8109,86387,Female,disloyal Customer,23,Business travel,Eco,749,5,5,5,1,1,5,1,1,5,5,4,4,5,1,0,0.0,satisfied +8110,55486,Male,disloyal Customer,18,Business travel,Eco,828,3,3,3,3,3,3,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +8111,21098,Male,Loyal Customer,66,Business travel,Eco,227,4,2,4,2,4,4,4,4,2,2,2,4,1,4,0,0.0,satisfied +8112,78985,Male,Loyal Customer,54,Business travel,Business,2994,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +8113,60515,Female,Loyal Customer,42,Personal Travel,Eco,862,3,4,4,2,3,5,5,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +8114,95398,Male,Loyal Customer,60,Personal Travel,Eco,239,3,4,3,3,2,3,3,2,2,4,4,3,4,2,64,58.0,neutral or dissatisfied +8115,14348,Female,Loyal Customer,39,Personal Travel,Eco,429,3,3,3,3,4,3,4,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +8116,114392,Male,Loyal Customer,39,Business travel,Business,417,5,5,5,5,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +8117,110988,Female,disloyal Customer,35,Business travel,Eco,319,3,1,3,3,1,3,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +8118,12886,Male,Loyal Customer,32,Business travel,Eco,979,5,5,5,5,5,5,5,5,3,5,4,4,3,5,4,24.0,satisfied +8119,113076,Female,Loyal Customer,45,Business travel,Business,2863,1,1,1,1,4,5,4,4,4,4,4,3,4,4,8,0.0,satisfied +8120,77267,Female,Loyal Customer,51,Business travel,Eco Plus,1590,4,1,1,1,5,2,4,4,4,4,4,1,4,3,3,0.0,neutral or dissatisfied +8121,48366,Female,Loyal Customer,40,Business travel,Business,2192,2,2,2,2,2,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +8122,16596,Female,disloyal Customer,25,Business travel,Business,1008,4,4,4,3,1,4,1,1,3,5,4,4,4,1,11,0.0,satisfied +8123,72136,Female,Loyal Customer,61,Business travel,Eco,731,2,4,4,4,3,3,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +8124,89939,Male,Loyal Customer,44,Personal Travel,Eco,1306,2,5,1,2,4,1,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +8125,54664,Male,Loyal Customer,39,Business travel,Business,861,1,1,1,1,3,1,1,5,5,5,5,4,5,4,0,0.0,satisfied +8126,34758,Male,Loyal Customer,46,Business travel,Business,1530,3,3,3,3,4,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +8127,36904,Female,Loyal Customer,23,Business travel,Business,2072,1,3,3,3,1,2,1,1,1,4,2,2,4,1,0,8.0,neutral or dissatisfied +8128,53171,Female,Loyal Customer,36,Business travel,Eco,589,5,4,4,4,5,5,5,5,5,3,3,2,2,5,0,0.0,satisfied +8129,40474,Male,disloyal Customer,26,Business travel,Eco,175,2,0,2,3,2,2,2,2,1,5,5,3,4,2,39,35.0,neutral or dissatisfied +8130,86732,Male,Loyal Customer,40,Personal Travel,Eco,1747,2,1,2,1,3,2,3,3,3,2,2,4,2,3,0,0.0,neutral or dissatisfied +8131,79663,Male,Loyal Customer,25,Personal Travel,Eco,762,3,1,3,2,1,3,1,1,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +8132,10574,Male,Loyal Customer,28,Business travel,Business,229,4,4,4,4,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +8133,66659,Female,disloyal Customer,21,Business travel,Eco,802,4,4,4,3,1,4,3,1,5,5,5,5,4,1,0,0.0,satisfied +8134,25199,Male,Loyal Customer,46,Business travel,Business,842,3,3,3,3,4,5,5,4,4,4,4,3,4,5,20,17.0,satisfied +8135,106363,Male,Loyal Customer,55,Business travel,Business,551,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +8136,75454,Female,disloyal Customer,27,Business travel,Eco,1046,2,2,2,2,3,2,2,3,3,2,5,5,1,3,0,0.0,neutral or dissatisfied +8137,111784,Male,Loyal Customer,31,Business travel,Eco,1620,3,5,4,5,3,3,3,3,3,2,4,3,4,3,24,11.0,neutral or dissatisfied +8138,113608,Male,Loyal Customer,65,Personal Travel,Eco,226,0,4,0,4,5,0,4,5,4,4,4,5,4,5,0,0.0,satisfied +8139,24442,Male,Loyal Customer,17,Business travel,Business,3389,2,2,2,2,4,4,4,4,5,2,4,3,4,4,18,7.0,satisfied +8140,109041,Female,disloyal Customer,8,Business travel,Eco,849,3,3,3,3,5,3,5,5,3,5,2,4,2,5,23,14.0,neutral or dissatisfied +8141,36284,Male,Loyal Customer,59,Business travel,Business,187,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +8142,43618,Female,Loyal Customer,44,Business travel,Business,190,3,5,5,5,4,3,4,3,3,4,3,2,3,4,23,6.0,neutral or dissatisfied +8143,91225,Male,Loyal Customer,35,Personal Travel,Eco,581,2,5,2,5,1,2,1,1,5,2,4,1,2,1,0,0.0,neutral or dissatisfied +8144,12326,Female,Loyal Customer,50,Business travel,Business,3795,5,5,5,5,5,4,2,4,4,4,3,2,4,3,0,0.0,satisfied +8145,11832,Female,Loyal Customer,69,Personal Travel,Eco,986,4,5,4,1,2,5,4,3,3,4,3,4,3,3,0,2.0,satisfied +8146,23406,Male,Loyal Customer,47,Business travel,Eco Plus,300,5,3,2,3,5,5,5,5,2,4,1,5,5,5,0,0.0,satisfied +8147,105278,Male,Loyal Customer,44,Business travel,Business,2198,5,5,5,5,2,5,5,5,5,4,5,4,5,5,15,20.0,satisfied +8148,100482,Female,Loyal Customer,43,Business travel,Business,580,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +8149,109028,Female,Loyal Customer,26,Business travel,Business,849,2,2,2,2,4,4,4,4,4,3,5,5,4,4,5,0.0,satisfied +8150,4966,Female,Loyal Customer,45,Personal Travel,Eco,931,3,5,3,2,3,5,4,5,5,3,5,4,5,3,0,3.0,neutral or dissatisfied +8151,114930,Female,disloyal Customer,22,Business travel,Eco,417,3,2,3,4,2,3,2,2,3,1,4,4,3,2,1,0.0,neutral or dissatisfied +8152,104079,Male,Loyal Customer,14,Personal Travel,Eco,359,4,4,4,3,2,4,2,2,3,4,5,3,5,2,0,0.0,satisfied +8153,63703,Female,Loyal Customer,50,Personal Travel,Eco,853,3,5,3,1,2,4,4,4,4,3,1,4,4,4,0,0.0,neutral or dissatisfied +8154,9373,Male,Loyal Customer,67,Business travel,Eco,384,3,4,4,4,3,3,3,2,1,2,2,3,2,3,151,146.0,neutral or dissatisfied +8155,27086,Female,Loyal Customer,21,Personal Travel,Eco,2496,5,5,5,3,1,5,1,1,4,1,3,3,3,1,0,0.0,satisfied +8156,96618,Male,Loyal Customer,60,Business travel,Business,1885,5,5,3,5,5,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +8157,119792,Male,Loyal Customer,31,Business travel,Business,936,2,2,3,2,5,4,5,5,5,3,5,4,4,5,0,0.0,satisfied +8158,129430,Male,disloyal Customer,42,Business travel,Business,236,1,1,1,3,1,1,1,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +8159,97118,Female,Loyal Customer,55,Business travel,Eco,1164,3,5,5,5,3,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +8160,21183,Female,Loyal Customer,59,Business travel,Eco,192,4,1,3,3,4,4,1,4,4,4,4,1,4,2,17,3.0,satisfied +8161,73083,Female,disloyal Customer,39,Business travel,Eco,685,3,3,3,3,3,4,4,5,3,1,5,4,1,4,652,638.0,neutral or dissatisfied +8162,63268,Female,Loyal Customer,42,Business travel,Business,447,3,3,1,3,5,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +8163,71574,Female,Loyal Customer,35,Business travel,Eco,1005,3,5,5,5,3,3,3,3,1,4,1,1,2,3,0,0.0,neutral or dissatisfied +8164,86739,Female,disloyal Customer,21,Business travel,Business,821,0,5,0,2,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +8165,73327,Female,Loyal Customer,51,Business travel,Business,1738,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +8166,76467,Male,Loyal Customer,43,Business travel,Business,3095,1,1,1,1,3,4,5,5,5,5,5,3,5,3,41,29.0,satisfied +8167,47447,Female,Loyal Customer,37,Business travel,Business,199,2,5,5,5,1,3,3,3,3,3,2,2,3,1,0,0.0,neutral or dissatisfied +8168,3935,Male,Loyal Customer,46,Personal Travel,Business,765,2,4,2,5,4,2,5,5,5,2,5,2,5,4,0,21.0,neutral or dissatisfied +8169,86578,Female,disloyal Customer,39,Business travel,Business,1269,1,1,1,4,1,1,1,1,3,1,4,4,4,1,0,0.0,neutral or dissatisfied +8170,71148,Male,Loyal Customer,27,Business travel,Business,646,5,5,4,5,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +8171,35797,Female,Loyal Customer,26,Business travel,Eco Plus,200,4,4,4,4,4,3,4,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +8172,80434,Female,Loyal Customer,57,Personal Travel,Eco,2248,2,5,2,3,2,3,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +8173,79694,Female,Loyal Customer,31,Personal Travel,Eco,712,1,4,1,4,5,1,5,5,2,3,4,4,4,5,0,0.0,neutral or dissatisfied +8174,4315,Female,Loyal Customer,65,Personal Travel,Eco,184,2,4,2,4,1,3,3,1,1,2,1,3,1,3,0,3.0,neutral or dissatisfied +8175,129316,Male,Loyal Customer,53,Business travel,Business,2586,5,5,2,5,3,5,5,5,5,5,5,3,5,3,5,9.0,satisfied +8176,108502,Male,disloyal Customer,40,Business travel,Business,287,4,4,4,3,5,4,5,5,4,2,2,1,1,5,0,0.0,satisfied +8177,106691,Female,Loyal Customer,34,Business travel,Business,516,4,4,2,4,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +8178,107499,Male,disloyal Customer,34,Business travel,Eco,711,2,2,2,4,4,2,4,4,4,4,4,1,4,4,7,37.0,neutral or dissatisfied +8179,14296,Female,disloyal Customer,26,Business travel,Eco,429,3,0,2,2,3,2,3,3,2,3,4,2,3,3,0,0.0,neutral or dissatisfied +8180,58347,Female,Loyal Customer,49,Personal Travel,Eco,315,1,3,1,2,5,2,3,1,1,1,1,3,1,1,0,10.0,neutral or dissatisfied +8181,15256,Male,Loyal Customer,30,Personal Travel,Eco,529,3,5,3,3,4,3,4,4,5,5,5,5,4,4,17,23.0,neutral or dissatisfied +8182,27453,Male,Loyal Customer,47,Business travel,Business,978,4,4,2,4,4,5,4,4,4,4,4,2,4,1,0,0.0,satisfied +8183,104487,Female,disloyal Customer,15,Business travel,Eco,860,2,2,2,2,4,2,1,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +8184,15488,Male,Loyal Customer,31,Personal Travel,Eco,164,2,5,0,2,2,0,2,2,3,5,4,3,4,2,79,78.0,neutral or dissatisfied +8185,45936,Male,Loyal Customer,29,Personal Travel,Eco,563,2,4,2,1,3,2,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +8186,68691,Female,Loyal Customer,7,Personal Travel,Eco,237,3,1,0,3,1,0,1,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +8187,89408,Female,Loyal Customer,17,Business travel,Business,151,2,2,2,2,4,4,2,4,2,2,3,1,3,4,11,6.0,neutral or dissatisfied +8188,35129,Female,Loyal Customer,41,Business travel,Eco,1076,5,3,3,3,4,5,4,4,1,3,5,1,2,4,2,11.0,satisfied +8189,51083,Male,Loyal Customer,58,Personal Travel,Eco,308,1,5,2,1,5,2,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +8190,50734,Female,Loyal Customer,9,Personal Travel,Eco,363,4,5,4,4,2,4,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +8191,16014,Female,Loyal Customer,72,Business travel,Eco,380,5,3,3,3,5,4,2,5,5,5,5,2,5,1,0,0.0,satisfied +8192,73350,Male,Loyal Customer,31,Business travel,Business,1667,2,1,1,1,2,2,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +8193,65561,Male,Loyal Customer,56,Business travel,Business,2308,0,5,1,4,5,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +8194,75234,Female,Loyal Customer,32,Personal Travel,Eco,1726,1,5,1,1,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +8195,112252,Male,Loyal Customer,36,Business travel,Business,1703,2,2,2,2,5,3,4,3,3,4,3,5,3,4,41,31.0,satisfied +8196,6706,Male,Loyal Customer,32,Personal Travel,Eco,258,3,4,3,5,5,3,5,5,1,2,4,4,1,5,22,20.0,neutral or dissatisfied +8197,115278,Male,Loyal Customer,52,Business travel,Business,325,2,2,1,2,5,5,5,4,4,4,4,5,4,5,17,15.0,satisfied +8198,16451,Male,Loyal Customer,37,Personal Travel,Eco,529,4,4,4,3,2,4,2,2,4,3,5,5,5,2,60,63.0,satisfied +8199,115551,Female,Loyal Customer,53,Business travel,Business,1546,2,2,1,2,5,4,4,5,5,5,5,4,5,3,20,24.0,satisfied +8200,62912,Female,Loyal Customer,57,Business travel,Business,967,5,5,5,5,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +8201,99417,Female,Loyal Customer,41,Business travel,Eco,406,4,3,3,3,4,4,4,4,1,4,1,4,4,4,15,16.0,satisfied +8202,47509,Female,Loyal Customer,67,Personal Travel,Eco,541,2,4,2,4,2,5,4,1,1,2,1,3,1,3,0,4.0,neutral or dissatisfied +8203,76003,Male,Loyal Customer,48,Business travel,Business,2805,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +8204,1825,Female,Loyal Customer,48,Business travel,Eco,408,2,5,5,5,2,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +8205,64052,Male,Loyal Customer,40,Business travel,Eco,921,3,1,1,1,3,3,3,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +8206,5599,Male,Loyal Customer,55,Business travel,Business,1878,5,5,5,5,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +8207,46272,Female,Loyal Customer,38,Personal Travel,Eco,679,2,1,2,2,1,2,1,1,3,3,1,4,1,1,0,9.0,neutral or dissatisfied +8208,2854,Male,Loyal Customer,47,Business travel,Business,2137,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +8209,30609,Female,Loyal Customer,62,Personal Travel,Eco,472,3,2,3,4,5,3,3,4,4,3,4,4,4,4,23,35.0,neutral or dissatisfied +8210,39136,Female,Loyal Customer,33,Personal Travel,Eco,190,3,5,3,1,2,3,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +8211,128937,Male,Loyal Customer,34,Business travel,Business,236,2,1,1,1,4,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +8212,94299,Male,Loyal Customer,30,Business travel,Business,323,0,0,0,2,3,4,4,3,4,3,4,4,5,3,24,17.0,satisfied +8213,38125,Female,disloyal Customer,39,Business travel,Eco,797,1,0,0,4,2,0,3,2,1,3,4,5,5,2,0,0.0,neutral or dissatisfied +8214,42047,Male,Loyal Customer,51,Business travel,Eco,116,1,3,3,3,1,1,1,1,1,5,4,3,4,1,0,0.0,neutral or dissatisfied +8215,98316,Male,disloyal Customer,30,Business travel,Business,1547,2,1,1,5,5,1,4,5,4,3,5,4,5,5,40,44.0,neutral or dissatisfied +8216,72998,Male,disloyal Customer,22,Business travel,Business,1096,5,3,5,1,1,5,1,1,3,3,5,2,3,1,0,1.0,satisfied +8217,36215,Female,Loyal Customer,48,Business travel,Business,3857,3,3,3,3,2,2,2,3,3,3,3,3,3,4,0,10.0,neutral or dissatisfied +8218,39209,Female,Loyal Customer,56,Business travel,Business,67,1,4,4,4,1,1,1,3,3,3,1,4,3,3,0,0.0,neutral or dissatisfied +8219,118384,Female,Loyal Customer,28,Business travel,Business,2285,5,5,5,5,5,5,5,5,4,3,5,4,5,5,0,0.0,satisfied +8220,113784,Female,Loyal Customer,56,Business travel,Business,2162,3,3,3,3,4,4,4,4,4,4,4,5,4,3,0,2.0,satisfied +8221,97353,Female,Loyal Customer,53,Business travel,Eco,872,5,3,3,3,3,5,1,5,5,5,5,1,5,5,0,0.0,satisfied +8222,8401,Female,Loyal Customer,52,Business travel,Business,888,4,4,5,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +8223,48476,Male,disloyal Customer,36,Business travel,Eco,737,3,3,3,5,5,3,5,5,1,2,5,2,2,5,44,32.0,neutral or dissatisfied +8224,8472,Male,Loyal Customer,54,Business travel,Business,2784,3,3,3,3,3,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +8225,85290,Female,Loyal Customer,56,Personal Travel,Eco,731,2,3,2,5,5,2,1,1,1,2,4,2,1,3,0,0.0,neutral or dissatisfied +8226,21929,Male,Loyal Customer,49,Business travel,Eco,551,4,1,1,1,4,4,4,4,1,3,2,2,5,4,9,0.0,satisfied +8227,38567,Female,Loyal Customer,35,Personal Travel,Eco,2475,3,4,4,1,5,4,5,5,3,5,4,3,5,5,1,0.0,neutral or dissatisfied +8228,11797,Male,disloyal Customer,20,Business travel,Eco,429,4,5,4,3,4,4,4,4,4,2,4,4,5,4,19,14.0,satisfied +8229,13967,Male,Loyal Customer,41,Personal Travel,Eco,192,3,5,3,1,3,3,5,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +8230,91437,Female,Loyal Customer,33,Personal Travel,Business,859,2,5,2,4,3,4,5,5,5,2,5,3,5,5,6,2.0,neutral or dissatisfied +8231,129271,Male,disloyal Customer,25,Business travel,Eco,2402,1,1,1,4,5,1,5,5,1,3,3,4,3,5,11,29.0,neutral or dissatisfied +8232,20816,Female,disloyal Customer,34,Business travel,Eco,457,2,4,2,3,1,2,1,1,1,5,4,3,3,1,0,0.0,neutral or dissatisfied +8233,29903,Female,Loyal Customer,41,Business travel,Business,213,2,2,2,2,4,2,3,4,4,4,4,2,4,2,37,38.0,satisfied +8234,24540,Male,Loyal Customer,40,Business travel,Eco,696,5,2,2,2,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +8235,43005,Female,disloyal Customer,30,Business travel,Eco,391,3,4,3,4,4,3,4,4,4,4,2,1,5,4,7,7.0,neutral or dissatisfied +8236,119751,Female,Loyal Customer,25,Personal Travel,Eco,1496,2,5,2,2,4,2,4,4,3,5,3,1,5,4,0,0.0,neutral or dissatisfied +8237,106535,Male,Loyal Customer,51,Business travel,Business,2166,1,1,4,1,5,5,5,5,5,5,5,3,5,4,3,1.0,satisfied +8238,127762,Male,Loyal Customer,51,Personal Travel,Eco,601,3,1,3,4,2,3,2,2,4,2,4,4,3,2,2,0.0,neutral or dissatisfied +8239,20346,Female,disloyal Customer,44,Business travel,Eco,287,3,4,4,2,4,4,1,4,3,3,1,3,2,4,8,10.0,neutral or dissatisfied +8240,54124,Female,Loyal Customer,40,Business travel,Eco,1400,4,4,4,4,4,4,4,4,1,3,5,2,5,4,18,9.0,satisfied +8241,122506,Male,Loyal Customer,56,Business travel,Business,1918,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +8242,42254,Male,Loyal Customer,60,Business travel,Business,3226,4,4,4,4,1,2,3,3,3,3,3,4,3,4,0,0.0,satisfied +8243,106706,Male,Loyal Customer,8,Personal Travel,Eco,516,4,5,4,5,5,4,5,5,4,2,5,4,5,5,0,0.0,satisfied +8244,91915,Male,disloyal Customer,30,Business travel,Eco,1445,2,2,2,4,2,2,2,2,1,2,4,1,4,2,1,0.0,neutral or dissatisfied +8245,32151,Female,Loyal Customer,39,Business travel,Eco,102,4,2,2,2,4,4,4,4,3,3,4,2,2,4,0,0.0,satisfied +8246,35904,Male,disloyal Customer,41,Business travel,Business,1331,2,2,2,5,3,2,3,3,4,4,5,4,4,3,1,0.0,satisfied +8247,61683,Male,Loyal Customer,52,Business travel,Business,1609,4,4,3,4,5,4,5,2,2,2,2,3,2,4,5,0.0,satisfied +8248,103715,Male,Loyal Customer,52,Personal Travel,Eco,251,1,5,1,3,5,1,5,5,3,5,5,5,5,5,26,23.0,neutral or dissatisfied +8249,23868,Female,Loyal Customer,59,Personal Travel,Eco,522,2,4,2,1,4,5,4,3,3,2,1,3,3,4,0,0.0,neutral or dissatisfied +8250,86051,Female,Loyal Customer,47,Personal Travel,Eco,554,1,5,2,4,5,5,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +8251,43339,Female,disloyal Customer,21,Business travel,Eco,402,2,0,2,3,1,2,1,1,2,1,3,1,4,1,0,0.0,neutral or dissatisfied +8252,108984,Male,Loyal Customer,59,Business travel,Business,2899,3,3,2,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +8253,98170,Female,disloyal Customer,17,Business travel,Eco,562,4,3,4,3,5,4,2,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +8254,19866,Female,Loyal Customer,24,Business travel,Eco Plus,693,2,4,4,4,2,3,1,2,3,5,3,1,3,2,53,42.0,neutral or dissatisfied +8255,44958,Male,Loyal Customer,44,Business travel,Eco Plus,334,4,3,3,3,4,4,4,4,3,1,4,5,2,4,48,40.0,satisfied +8256,24455,Male,Loyal Customer,48,Business travel,Eco,547,4,4,4,4,4,4,4,4,5,5,1,5,3,4,0,0.0,satisfied +8257,39241,Male,Loyal Customer,47,Business travel,Business,67,5,5,5,5,3,1,1,4,4,4,5,1,4,2,0,0.0,satisfied +8258,30795,Female,disloyal Customer,23,Business travel,Eco,301,1,2,1,3,5,1,2,5,1,1,3,4,4,5,25,15.0,neutral or dissatisfied +8259,22555,Female,Loyal Customer,59,Business travel,Business,250,0,0,0,3,1,1,1,3,2,5,5,1,5,1,186,181.0,satisfied +8260,86403,Female,disloyal Customer,22,Business travel,Business,760,4,0,4,3,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +8261,46521,Male,Loyal Customer,38,Business travel,Business,1982,5,5,5,5,3,4,1,5,5,5,5,3,5,1,0,0.0,satisfied +8262,72682,Male,Loyal Customer,59,Personal Travel,Eco,929,3,4,3,3,5,3,4,5,5,2,5,5,4,5,0,7.0,neutral or dissatisfied +8263,53665,Male,Loyal Customer,35,Business travel,Eco,1190,4,3,3,3,4,4,4,4,2,2,3,5,4,4,0,0.0,satisfied +8264,30632,Female,Loyal Customer,21,Business travel,Business,533,4,4,4,4,4,4,4,4,1,1,3,4,5,4,0,0.0,satisfied +8265,119821,Male,Loyal Customer,31,Business travel,Business,2528,2,3,3,3,2,2,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +8266,43999,Female,Loyal Customer,51,Business travel,Business,349,0,0,0,5,5,1,5,4,4,4,4,5,4,2,0,0.0,satisfied +8267,28463,Male,Loyal Customer,56,Personal Travel,Eco,2588,1,5,1,1,1,1,1,1,2,4,3,1,2,1,10,8.0,neutral or dissatisfied +8268,62748,Female,Loyal Customer,47,Business travel,Business,2338,4,4,4,4,4,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +8269,116962,Male,Loyal Customer,56,Business travel,Business,3467,4,4,4,4,2,5,5,2,2,2,2,4,2,3,37,17.0,satisfied +8270,93575,Male,Loyal Customer,42,Business travel,Eco,159,3,4,4,4,3,3,3,3,3,2,4,2,4,3,23,38.0,neutral or dissatisfied +8271,52237,Female,disloyal Customer,25,Business travel,Eco,370,4,5,4,4,1,4,1,1,1,4,2,3,5,1,9,0.0,satisfied +8272,122153,Male,Loyal Customer,57,Business travel,Business,2579,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +8273,43404,Female,disloyal Customer,25,Business travel,Eco Plus,531,2,0,2,4,2,2,2,2,5,3,5,2,4,2,0,0.0,neutral or dissatisfied +8274,7796,Female,Loyal Customer,31,Business travel,Business,650,3,3,3,3,3,3,3,3,2,2,3,2,3,3,0,10.0,neutral or dissatisfied +8275,112971,Male,disloyal Customer,29,Business travel,Eco Plus,1497,1,1,1,4,4,1,4,4,4,4,3,2,3,4,118,107.0,neutral or dissatisfied +8276,107734,Female,Loyal Customer,68,Personal Travel,Eco,405,0,4,0,4,5,5,4,3,3,0,3,3,3,4,0,0.0,satisfied +8277,29256,Female,Loyal Customer,35,Business travel,Business,859,2,2,2,2,1,1,3,2,2,2,2,1,2,4,0,0.0,satisfied +8278,102390,Female,Loyal Customer,71,Business travel,Eco,223,3,5,5,5,3,3,4,3,3,3,3,2,3,4,31,23.0,neutral or dissatisfied +8279,64733,Male,Loyal Customer,40,Business travel,Business,247,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +8280,97714,Female,Loyal Customer,28,Personal Travel,Eco,942,2,1,2,2,4,2,4,4,1,3,1,4,2,4,34,30.0,neutral or dissatisfied +8281,1436,Female,Loyal Customer,35,Business travel,Business,772,5,5,4,5,4,4,5,4,4,4,4,5,4,5,62,46.0,satisfied +8282,98405,Female,Loyal Customer,50,Business travel,Eco,675,2,4,4,4,1,2,3,2,2,2,2,2,2,1,15,10.0,neutral or dissatisfied +8283,56981,Female,Loyal Customer,64,Personal Travel,Eco,2454,3,2,3,3,3,1,1,1,2,3,4,1,4,1,3,16.0,neutral or dissatisfied +8284,25569,Female,Loyal Customer,51,Business travel,Eco,696,5,1,1,1,1,1,1,5,5,5,5,4,5,3,4,0.0,satisfied +8285,57084,Female,Loyal Customer,25,Personal Travel,Business,1222,3,5,3,3,5,3,5,5,4,4,4,2,3,5,24,0.0,neutral or dissatisfied +8286,72684,Male,Loyal Customer,68,Personal Travel,Eco,1121,1,4,1,3,4,1,2,4,4,3,3,5,4,4,0,0.0,neutral or dissatisfied +8287,113449,Male,Loyal Customer,60,Business travel,Business,2504,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +8288,39965,Male,Loyal Customer,54,Business travel,Business,1404,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,8.0,satisfied +8289,27044,Female,Loyal Customer,14,Personal Travel,Business,1709,4,3,4,3,5,4,5,5,1,2,3,3,2,5,4,0.0,neutral or dissatisfied +8290,68073,Female,Loyal Customer,39,Business travel,Business,868,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +8291,4930,Female,Loyal Customer,44,Business travel,Eco,334,2,1,1,1,1,4,3,2,2,2,2,2,2,3,46,32.0,neutral or dissatisfied +8292,72149,Male,Loyal Customer,64,Personal Travel,Eco,731,4,4,4,3,4,3,3,5,4,2,3,3,3,3,165,146.0,satisfied +8293,38024,Male,Loyal Customer,42,Business travel,Business,1867,2,2,2,2,1,5,3,4,4,4,4,1,4,4,0,0.0,satisfied +8294,50152,Male,Loyal Customer,36,Business travel,Eco,363,5,2,2,2,5,5,5,5,1,2,4,5,3,5,0,0.0,satisfied +8295,58370,Male,Loyal Customer,60,Business travel,Business,2424,1,1,1,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +8296,38103,Female,Loyal Customer,19,Business travel,Business,1249,1,1,5,1,3,4,3,3,4,1,1,2,4,3,0,0.0,satisfied +8297,5513,Female,Loyal Customer,60,Business travel,Business,2679,3,3,3,3,4,5,5,3,3,3,3,3,3,5,6,0.0,satisfied +8298,20382,Male,Loyal Customer,43,Business travel,Eco Plus,265,4,4,5,4,4,4,4,4,4,2,3,2,4,4,0,0.0,neutral or dissatisfied +8299,73811,Female,Loyal Customer,25,Personal Travel,Eco Plus,204,3,3,3,3,3,3,3,3,4,5,3,1,3,3,0,2.0,neutral or dissatisfied +8300,14181,Female,Loyal Customer,58,Business travel,Business,3830,2,2,2,2,2,1,1,5,5,5,5,1,5,4,8,0.0,satisfied +8301,31809,Male,Loyal Customer,46,Business travel,Eco,1103,3,1,1,1,3,3,3,1,1,3,4,3,3,3,0,23.0,neutral or dissatisfied +8302,30303,Male,disloyal Customer,25,Business travel,Eco,1387,3,3,3,5,5,3,5,5,4,4,2,2,5,5,3,49.0,neutral or dissatisfied +8303,64947,Male,Loyal Customer,48,Business travel,Business,3208,1,1,1,1,2,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +8304,76266,Male,Loyal Customer,46,Business travel,Eco,1927,2,1,1,1,2,2,2,2,2,3,2,1,4,2,0,0.0,neutral or dissatisfied +8305,81420,Male,Loyal Customer,26,Business travel,Business,393,1,1,1,1,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +8306,2435,Female,Loyal Customer,11,Personal Travel,Eco,641,2,4,1,1,3,1,3,3,4,2,4,5,5,3,0,2.0,neutral or dissatisfied +8307,77643,Male,Loyal Customer,41,Business travel,Business,813,3,3,3,3,2,4,4,5,5,5,5,5,5,5,4,0.0,satisfied +8308,28400,Female,Loyal Customer,52,Business travel,Business,1489,2,3,3,3,1,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +8309,88991,Female,Loyal Customer,40,Personal Travel,Eco,1199,3,5,3,4,4,3,4,4,5,5,3,2,4,4,4,0.0,neutral or dissatisfied +8310,29863,Female,Loyal Customer,53,Business travel,Eco,31,5,3,3,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +8311,117152,Female,Loyal Customer,51,Personal Travel,Eco,338,2,4,5,1,3,4,4,2,2,5,2,3,2,5,0,0.0,neutral or dissatisfied +8312,67494,Female,disloyal Customer,22,Business travel,Eco Plus,641,4,2,4,4,5,4,5,5,1,5,3,3,4,5,3,0.0,neutral or dissatisfied +8313,40303,Male,Loyal Customer,69,Personal Travel,Eco,387,3,1,3,4,4,3,4,4,3,2,3,4,4,4,13,0.0,neutral or dissatisfied +8314,86554,Male,Loyal Customer,53,Business travel,Business,3829,4,4,3,4,4,4,4,4,4,4,4,3,4,5,9,13.0,satisfied +8315,47863,Female,disloyal Customer,24,Business travel,Eco,451,1,1,1,3,2,1,2,2,3,4,3,3,2,2,0,0.0,neutral or dissatisfied +8316,29455,Female,Loyal Customer,46,Personal Travel,Eco,421,3,2,3,4,1,3,4,5,5,3,5,3,5,4,0,10.0,neutral or dissatisfied +8317,26853,Female,Loyal Customer,27,Personal Travel,Eco,224,3,4,3,4,1,3,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +8318,13700,Male,Loyal Customer,69,Personal Travel,Eco,300,3,5,3,1,4,3,4,4,3,2,2,5,3,4,0,0.0,neutral or dissatisfied +8319,76141,Female,Loyal Customer,23,Business travel,Business,1886,3,3,3,3,4,4,4,4,4,5,5,5,4,4,4,0.0,satisfied +8320,122652,Female,Loyal Customer,60,Business travel,Business,361,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +8321,7519,Female,Loyal Customer,35,Business travel,Business,762,2,2,2,2,4,4,4,4,4,4,4,4,4,3,16,0.0,satisfied +8322,119833,Male,disloyal Customer,25,Business travel,Eco,912,3,2,2,2,5,2,5,5,1,1,1,2,1,5,107,92.0,neutral or dissatisfied +8323,96153,Male,disloyal Customer,24,Business travel,Eco,460,2,0,2,2,5,2,4,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +8324,68455,Male,Loyal Customer,54,Business travel,Business,1067,1,1,4,1,4,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +8325,82784,Female,Loyal Customer,47,Business travel,Business,231,2,2,2,2,1,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +8326,3551,Male,Loyal Customer,51,Business travel,Eco,227,2,4,4,4,2,2,2,2,4,5,4,4,4,2,0,9.0,neutral or dissatisfied +8327,49248,Male,disloyal Customer,25,Business travel,Eco,308,2,0,2,2,4,2,4,4,1,2,2,3,3,4,0,0.0,neutral or dissatisfied +8328,98110,Female,Loyal Customer,51,Business travel,Business,472,1,1,1,1,4,4,5,5,5,5,5,3,5,3,0,3.0,satisfied +8329,71965,Male,Loyal Customer,57,Business travel,Business,1440,5,5,5,5,4,5,4,4,4,4,4,5,4,4,8,10.0,satisfied +8330,2470,Female,Loyal Customer,37,Personal Travel,Eco,722,3,5,3,3,4,3,4,4,4,4,3,2,2,4,4,0.0,neutral or dissatisfied +8331,29503,Male,Loyal Customer,53,Personal Travel,Eco,1216,5,1,5,2,2,1,2,2,2,3,1,4,1,2,0,0.0,satisfied +8332,91045,Female,Loyal Customer,28,Personal Travel,Eco,594,2,5,2,1,3,2,3,3,2,2,3,4,3,3,38,39.0,neutral or dissatisfied +8333,89652,Male,Loyal Customer,37,Business travel,Business,1089,3,3,3,3,1,3,2,3,3,3,3,1,3,4,0,18.0,neutral or dissatisfied +8334,129646,Male,Loyal Customer,33,Business travel,Business,3951,4,4,4,4,4,4,4,4,3,5,4,5,4,4,0,0.0,satisfied +8335,87269,Female,Loyal Customer,50,Business travel,Business,1648,2,2,2,2,3,4,4,4,4,5,4,5,4,4,11,0.0,satisfied +8336,61667,Female,Loyal Customer,32,Business travel,Business,1635,4,1,5,1,4,4,4,4,4,1,4,3,3,4,4,0.0,neutral or dissatisfied +8337,30450,Male,Loyal Customer,49,Business travel,Business,991,4,2,2,2,5,3,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +8338,118015,Male,Loyal Customer,32,Business travel,Business,1037,2,4,4,4,2,2,2,2,1,5,3,4,3,2,18,8.0,neutral or dissatisfied +8339,105556,Male,Loyal Customer,43,Business travel,Eco Plus,611,1,3,3,3,1,1,1,1,2,1,2,3,3,1,5,0.0,neutral or dissatisfied +8340,111908,Female,disloyal Customer,28,Business travel,Business,628,4,5,5,3,2,5,2,2,5,3,5,5,5,2,9,1.0,neutral or dissatisfied +8341,33986,Male,Loyal Customer,26,Business travel,Eco,1598,4,3,2,2,4,4,5,4,2,2,5,3,2,4,13,0.0,satisfied +8342,102355,Female,Loyal Customer,54,Business travel,Business,223,2,3,3,3,3,4,4,3,3,3,2,1,3,1,0,4.0,neutral or dissatisfied +8343,61603,Female,Loyal Customer,44,Business travel,Business,1379,5,5,5,5,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +8344,116504,Male,Loyal Customer,34,Personal Travel,Eco,325,1,2,1,3,1,1,5,1,2,1,2,2,2,1,15,0.0,neutral or dissatisfied +8345,99756,Female,Loyal Customer,58,Personal Travel,Eco,255,4,4,4,4,5,1,3,3,3,4,4,2,3,1,0,10.0,neutral or dissatisfied +8346,62175,Female,disloyal Customer,34,Business travel,Eco,2454,1,2,2,3,1,1,1,1,4,1,4,3,4,1,2,0.0,neutral or dissatisfied +8347,81918,Female,Loyal Customer,50,Business travel,Business,1535,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +8348,41266,Male,Loyal Customer,31,Personal Travel,Eco,1042,1,4,1,3,3,1,4,3,3,3,5,3,4,3,2,2.0,neutral or dissatisfied +8349,39740,Female,Loyal Customer,40,Personal Travel,Eco,410,4,5,4,3,5,4,5,5,1,1,4,5,2,5,0,19.0,neutral or dissatisfied +8350,99644,Male,Loyal Customer,43,Business travel,Business,1670,4,4,4,4,4,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +8351,15791,Female,Loyal Customer,59,Business travel,Business,1819,4,4,4,4,3,4,5,5,5,5,5,4,5,4,22,0.0,satisfied +8352,75458,Male,Loyal Customer,58,Business travel,Business,1927,1,3,2,3,3,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +8353,94720,Male,Loyal Customer,53,Business travel,Business,1842,3,3,4,4,2,4,4,3,3,3,3,4,3,4,100,95.0,neutral or dissatisfied +8354,123090,Male,Loyal Customer,38,Business travel,Business,1807,4,4,5,5,4,4,4,4,4,4,4,3,4,1,39,36.0,neutral or dissatisfied +8355,49464,Male,Loyal Customer,57,Business travel,Eco,86,5,3,3,3,5,5,5,5,3,5,5,3,4,5,5,18.0,satisfied +8356,48902,Male,Loyal Customer,52,Business travel,Business,109,2,2,2,2,1,1,4,4,4,4,4,2,4,2,0,0.0,satisfied +8357,29217,Male,Loyal Customer,54,Business travel,Business,834,1,1,1,1,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +8358,100531,Female,Loyal Customer,37,Personal Travel,Eco,580,2,4,2,3,1,2,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +8359,44467,Female,Loyal Customer,38,Business travel,Eco,196,4,4,4,4,4,4,4,4,2,5,4,2,4,4,53,76.0,neutral or dissatisfied +8360,11766,Male,Loyal Customer,42,Personal Travel,Eco,429,2,2,2,3,4,2,4,4,1,3,2,2,3,4,7,0.0,neutral or dissatisfied +8361,20709,Female,Loyal Customer,44,Business travel,Business,3250,1,2,1,1,2,4,5,4,4,4,4,3,4,4,92,83.0,satisfied +8362,68988,Male,Loyal Customer,60,Business travel,Business,2422,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +8363,37082,Male,Loyal Customer,56,Business travel,Business,2203,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +8364,8583,Female,Loyal Customer,49,Personal Travel,Eco,109,4,3,4,4,4,4,4,4,1,1,5,4,2,4,148,142.0,neutral or dissatisfied +8365,35872,Female,Loyal Customer,18,Personal Travel,Eco,937,2,5,2,1,4,2,1,4,5,2,5,3,4,4,0,6.0,neutral or dissatisfied +8366,35434,Male,Loyal Customer,14,Personal Travel,Eco,1118,3,5,2,1,2,2,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +8367,75239,Male,Loyal Customer,24,Personal Travel,Eco,1744,4,1,4,4,2,4,2,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +8368,36005,Female,Loyal Customer,45,Business travel,Business,3089,4,5,4,4,2,4,4,5,5,5,5,4,5,2,0,0.0,satisfied +8369,85163,Male,Loyal Customer,49,Business travel,Business,689,1,3,1,1,5,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +8370,11015,Female,Loyal Customer,49,Business travel,Business,308,2,1,1,1,5,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +8371,71064,Male,Loyal Customer,36,Personal Travel,Eco,978,2,4,2,2,4,2,4,4,5,5,4,5,5,4,1,0.0,neutral or dissatisfied +8372,124843,Male,Loyal Customer,28,Personal Travel,Eco,280,1,5,1,4,1,1,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +8373,7449,Male,Loyal Customer,48,Personal Travel,Eco,522,5,5,5,1,1,5,1,1,3,4,4,5,5,1,6,0.0,satisfied +8374,84726,Female,Loyal Customer,48,Business travel,Business,534,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +8375,113746,Male,Loyal Customer,14,Personal Travel,Eco,397,1,5,5,3,2,5,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +8376,27474,Female,Loyal Customer,25,Business travel,Business,3647,3,3,2,3,3,3,3,3,3,4,3,2,3,3,0,3.0,neutral or dissatisfied +8377,104595,Female,Loyal Customer,52,Personal Travel,Eco,369,2,1,2,2,4,2,3,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +8378,51591,Male,Loyal Customer,37,Business travel,Eco,370,4,2,2,2,4,5,4,4,2,5,2,5,2,4,10,4.0,satisfied +8379,47935,Female,Loyal Customer,22,Personal Travel,Eco,748,2,4,2,4,5,2,5,5,3,5,3,1,2,5,0,0.0,neutral or dissatisfied +8380,15087,Male,disloyal Customer,36,Business travel,Eco,322,2,4,2,3,1,2,1,1,1,5,3,1,3,1,2,11.0,neutral or dissatisfied +8381,12994,Male,disloyal Customer,32,Business travel,Eco,374,3,3,3,2,4,3,4,4,3,3,5,2,1,4,69,59.0,neutral or dissatisfied +8382,62927,Female,Loyal Customer,51,Business travel,Business,2500,3,3,3,3,3,5,5,3,3,2,3,3,3,3,5,14.0,satisfied +8383,66492,Female,disloyal Customer,24,Business travel,Business,447,0,2,1,3,1,1,1,1,4,5,4,3,4,1,0,0.0,satisfied +8384,69811,Male,disloyal Customer,28,Business travel,Business,1055,4,4,4,1,4,4,1,4,3,5,4,5,4,4,1,0.0,neutral or dissatisfied +8385,97228,Female,Loyal Customer,56,Personal Travel,Eco Plus,1390,2,4,2,1,2,4,5,2,2,2,2,3,2,4,0,3.0,neutral or dissatisfied +8386,104020,Female,Loyal Customer,40,Business travel,Business,1262,1,0,0,3,2,3,3,1,1,0,1,2,1,1,0,6.0,neutral or dissatisfied +8387,91490,Female,disloyal Customer,21,Business travel,Eco,859,3,3,3,3,3,3,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +8388,20081,Female,Loyal Customer,8,Personal Travel,Eco Plus,738,3,5,3,1,4,3,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +8389,102671,Male,disloyal Customer,20,Business travel,Eco,255,1,4,1,3,3,1,1,3,4,5,5,4,4,3,90,82.0,neutral or dissatisfied +8390,6650,Male,Loyal Customer,53,Personal Travel,Eco,416,1,5,2,1,2,2,2,2,1,2,2,5,2,2,4,3.0,neutral or dissatisfied +8391,20104,Female,disloyal Customer,38,Business travel,Eco,416,3,3,3,1,4,3,4,4,2,4,3,3,2,4,4,1.0,neutral or dissatisfied +8392,121946,Male,Loyal Customer,41,Business travel,Business,430,1,1,1,1,3,4,4,5,5,5,5,5,5,4,64,67.0,satisfied +8393,16044,Male,Loyal Customer,56,Business travel,Business,972,5,5,5,5,5,1,3,3,3,4,3,2,3,4,0,0.0,satisfied +8394,1101,Female,Loyal Customer,46,Personal Travel,Eco,354,1,1,1,3,1,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +8395,13742,Female,disloyal Customer,25,Business travel,Eco,441,3,1,2,3,4,2,5,4,3,1,4,4,4,4,45,30.0,neutral or dissatisfied +8396,109835,Female,Loyal Customer,47,Business travel,Business,3857,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +8397,54864,Male,Loyal Customer,30,Business travel,Business,641,3,4,4,4,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +8398,102127,Male,disloyal Customer,25,Business travel,Business,407,3,0,3,1,2,3,2,2,4,3,4,4,5,2,14,12.0,neutral or dissatisfied +8399,114537,Female,Loyal Customer,49,Personal Travel,Business,308,1,4,1,4,2,3,1,2,2,1,2,5,2,1,0,11.0,neutral or dissatisfied +8400,86969,Male,Loyal Customer,67,Business travel,Business,2226,4,4,4,4,1,3,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +8401,122004,Female,disloyal Customer,24,Business travel,Business,83,4,0,4,1,5,4,5,5,3,4,4,4,5,5,0,19.0,satisfied +8402,63047,Male,Loyal Customer,52,Personal Travel,Eco,909,2,5,2,4,5,2,5,5,3,1,5,1,1,5,5,1.0,neutral or dissatisfied +8403,95024,Female,Loyal Customer,9,Personal Travel,Eco,239,5,4,5,2,1,5,1,1,3,5,2,2,3,1,1,2.0,satisfied +8404,81120,Female,Loyal Customer,53,Business travel,Business,1674,4,3,4,4,3,2,2,5,5,5,5,1,5,3,4,0.0,satisfied +8405,118543,Male,Loyal Customer,53,Business travel,Business,2149,5,5,1,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +8406,53173,Female,Loyal Customer,25,Business travel,Business,3984,5,5,5,5,5,5,5,5,4,3,5,5,2,5,8,8.0,satisfied +8407,93587,Female,Loyal Customer,36,Personal Travel,Eco,159,2,5,2,4,5,2,5,5,3,3,5,4,5,5,0,5.0,neutral or dissatisfied +8408,81074,Female,Loyal Customer,34,Business travel,Business,2461,4,4,4,4,1,3,4,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +8409,118841,Male,disloyal Customer,23,Business travel,Eco Plus,304,1,0,1,3,3,1,3,3,3,1,5,2,2,3,0,0.0,neutral or dissatisfied +8410,60996,Male,Loyal Customer,55,Business travel,Business,1884,5,5,4,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +8411,94127,Female,disloyal Customer,57,Business travel,Business,293,3,3,3,2,2,3,2,2,3,5,4,3,5,2,1,0.0,neutral or dissatisfied +8412,81799,Male,Loyal Customer,60,Business travel,Business,1416,5,5,5,5,4,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +8413,45384,Female,disloyal Customer,35,Business travel,Eco Plus,175,1,1,1,2,1,1,1,1,2,2,2,1,1,1,0,0.0,neutral or dissatisfied +8414,117542,Male,Loyal Customer,53,Business travel,Business,3993,5,5,5,5,2,4,5,4,4,4,4,4,4,3,1,6.0,satisfied +8415,17287,Male,Loyal Customer,46,Business travel,Business,403,2,2,5,2,5,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +8416,105267,Female,Loyal Customer,63,Personal Travel,Eco,2106,4,2,4,4,2,4,3,1,1,4,1,4,1,1,2,18.0,neutral or dissatisfied +8417,7963,Male,Loyal Customer,17,Personal Travel,Eco,594,1,5,1,2,4,1,2,4,1,2,3,5,2,4,0,0.0,neutral or dissatisfied +8418,44009,Female,Loyal Customer,42,Personal Travel,Eco,334,2,4,2,4,2,5,5,4,4,2,4,3,4,5,34,32.0,neutral or dissatisfied +8419,101154,Female,Loyal Customer,58,Business travel,Business,3422,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +8420,86539,Male,Loyal Customer,37,Personal Travel,Eco,762,3,4,3,3,2,3,2,2,3,3,3,2,4,2,15,9.0,neutral or dissatisfied +8421,123742,Male,Loyal Customer,57,Business travel,Eco,96,4,3,3,3,3,4,3,3,4,3,4,3,4,3,16,,neutral or dissatisfied +8422,103541,Male,Loyal Customer,31,Business travel,Business,2461,1,1,4,1,4,5,4,4,3,2,5,5,4,4,5,1.0,satisfied +8423,86363,Male,disloyal Customer,25,Business travel,Business,794,4,0,4,5,4,4,4,4,3,2,5,4,4,4,37,34.0,neutral or dissatisfied +8424,91506,Female,Loyal Customer,25,Business travel,Business,1620,1,1,1,1,4,5,4,4,4,4,3,4,4,4,79,129.0,satisfied +8425,47976,Female,Loyal Customer,60,Personal Travel,Eco,834,2,5,2,4,2,5,1,3,3,2,3,2,3,4,0,2.0,neutral or dissatisfied +8426,109777,Female,Loyal Customer,51,Business travel,Business,2766,2,1,3,1,2,2,3,2,2,2,2,3,2,3,42,38.0,neutral or dissatisfied +8427,90808,Female,Loyal Customer,45,Business travel,Business,444,1,1,1,1,5,5,4,1,1,2,1,3,1,3,16,2.0,satisfied +8428,87026,Male,Loyal Customer,30,Personal Travel,Business,645,2,4,3,1,2,3,2,2,4,2,4,3,4,2,12,0.0,neutral or dissatisfied +8429,108662,Female,disloyal Customer,31,Business travel,Business,1747,1,1,1,3,1,1,5,1,5,5,5,4,5,1,14,8.0,neutral or dissatisfied +8430,30563,Male,disloyal Customer,51,Business travel,Eco,628,2,0,2,1,4,2,4,4,3,2,1,1,2,4,8,0.0,neutral or dissatisfied +8431,116351,Male,Loyal Customer,53,Personal Travel,Eco,446,4,4,2,4,1,2,1,1,3,4,5,5,5,1,0,0.0,satisfied +8432,35699,Female,Loyal Customer,42,Personal Travel,Eco,2475,2,1,2,3,4,2,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +8433,63437,Female,Loyal Customer,18,Personal Travel,Eco,337,0,4,0,3,2,0,2,2,4,2,5,5,5,2,0,0.0,satisfied +8434,18908,Female,Loyal Customer,69,Personal Travel,Eco,448,2,4,2,3,3,4,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +8435,17534,Male,Loyal Customer,39,Business travel,Eco,297,4,2,3,2,4,4,4,4,1,3,2,2,3,4,3,0.0,satisfied +8436,101169,Male,Loyal Customer,20,Business travel,Business,1794,1,1,1,1,1,1,1,1,4,4,2,2,1,1,0,0.0,neutral or dissatisfied +8437,87531,Female,disloyal Customer,20,Business travel,Eco,321,2,2,2,3,2,2,2,2,4,1,3,3,2,2,0,0.0,neutral or dissatisfied +8438,18907,Male,Loyal Customer,25,Personal Travel,Eco,551,3,4,3,3,2,3,2,2,4,3,4,2,2,2,0,0.0,neutral or dissatisfied +8439,104866,Male,Loyal Customer,47,Business travel,Eco,327,3,3,2,3,3,3,3,3,4,4,4,2,3,3,16,1.0,neutral or dissatisfied +8440,118756,Male,Loyal Customer,44,Personal Travel,Eco,325,4,3,3,4,2,3,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +8441,109707,Male,Loyal Customer,39,Business travel,Business,2024,1,1,1,1,4,4,4,4,4,4,4,3,4,4,23,22.0,satisfied +8442,2457,Male,disloyal Customer,24,Business travel,Eco,722,2,2,2,4,4,2,4,4,2,3,3,3,4,4,0,0.0,neutral or dissatisfied +8443,109629,Female,disloyal Customer,40,Business travel,Business,802,1,1,1,1,1,1,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +8444,50461,Male,Loyal Customer,39,Business travel,Eco,421,4,5,5,5,4,4,4,4,3,2,1,2,3,4,0,0.0,satisfied +8445,95919,Male,Loyal Customer,52,Business travel,Business,1504,2,2,2,2,2,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +8446,67992,Female,Loyal Customer,64,Personal Travel,Eco Plus,1464,1,4,1,4,3,5,5,1,1,1,1,3,1,3,16,3.0,neutral or dissatisfied +8447,163,Female,Loyal Customer,64,Personal Travel,Eco,227,2,4,2,3,5,5,4,2,2,2,2,3,2,3,6,0.0,neutral or dissatisfied +8448,6475,Male,Loyal Customer,12,Personal Travel,Eco Plus,296,1,4,1,4,4,1,4,4,2,2,3,1,4,4,29,21.0,neutral or dissatisfied +8449,81654,Female,Loyal Customer,50,Business travel,Business,1653,1,1,1,1,3,4,5,5,5,5,5,3,5,4,31,37.0,satisfied +8450,73898,Male,Loyal Customer,56,Business travel,Business,2342,5,5,5,5,5,5,5,5,5,5,4,5,4,5,34,40.0,satisfied +8451,99117,Female,Loyal Customer,70,Personal Travel,Eco,453,5,5,5,1,2,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +8452,75931,Male,Loyal Customer,33,Business travel,Eco Plus,205,2,4,4,4,2,1,2,2,4,3,3,2,4,2,0,58.0,neutral or dissatisfied +8453,41933,Female,Loyal Customer,56,Personal Travel,Eco,129,2,2,2,3,4,2,3,2,2,2,1,3,2,4,9,7.0,neutral or dissatisfied +8454,116214,Male,Loyal Customer,35,Personal Travel,Eco,447,2,1,1,3,1,1,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +8455,93807,Male,Loyal Customer,54,Personal Travel,Eco Plus,1259,4,5,4,1,2,4,2,2,5,3,5,5,4,2,0,0.0,satisfied +8456,90248,Male,Loyal Customer,11,Personal Travel,Eco,1121,3,2,3,2,1,3,1,1,2,2,1,4,2,1,100,92.0,neutral or dissatisfied +8457,40835,Female,Loyal Customer,63,Business travel,Business,184,2,5,5,5,3,4,3,3,3,3,2,3,3,2,0,0.0,neutral or dissatisfied +8458,99395,Male,Loyal Customer,53,Business travel,Business,337,0,0,0,2,2,4,4,1,1,1,1,5,1,3,2,0.0,satisfied +8459,16337,Male,Loyal Customer,57,Personal Travel,Eco,594,1,3,2,1,1,2,1,1,4,1,1,3,1,1,0,16.0,neutral or dissatisfied +8460,2377,Female,Loyal Customer,8,Personal Travel,Business,767,4,2,5,3,2,5,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +8461,126984,Male,Loyal Customer,52,Business travel,Business,2615,3,3,3,3,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +8462,52253,Male,disloyal Customer,22,Business travel,Eco,455,4,4,4,5,4,4,4,4,5,4,1,1,4,4,0,0.0,satisfied +8463,32924,Female,Loyal Customer,64,Personal Travel,Eco,102,1,2,0,3,1,3,4,3,3,0,5,1,3,2,0,0.0,neutral or dissatisfied +8464,15292,Female,Loyal Customer,25,Business travel,Eco Plus,500,5,1,2,2,5,5,5,5,1,5,2,1,2,5,0,0.0,satisfied +8465,45247,Female,Loyal Customer,34,Business travel,Eco Plus,911,5,2,2,2,5,5,5,5,4,3,4,2,2,5,59,78.0,satisfied +8466,22872,Female,Loyal Customer,7,Personal Travel,Eco,302,3,1,3,4,2,3,2,2,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +8467,55211,Male,Loyal Customer,7,Personal Travel,Business,1009,1,5,1,4,2,1,2,2,4,5,5,5,4,2,2,0.0,neutral or dissatisfied +8468,5306,Male,Loyal Customer,65,Personal Travel,Eco,383,2,3,2,1,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +8469,31297,Male,Loyal Customer,41,Business travel,Business,2299,2,2,2,2,5,4,5,4,4,4,4,4,4,5,0,4.0,satisfied +8470,115265,Female,Loyal Customer,47,Business travel,Business,1816,1,1,1,1,5,5,5,5,3,5,5,5,5,5,137,135.0,satisfied +8471,129198,Male,Loyal Customer,35,Business travel,Business,2442,3,2,3,3,2,3,5,2,2,2,2,3,2,3,0,0.0,satisfied +8472,75059,Female,disloyal Customer,28,Business travel,Eco Plus,1592,1,1,1,2,1,1,1,1,2,2,3,3,2,1,0,1.0,neutral or dissatisfied +8473,14879,Male,Loyal Customer,72,Business travel,Business,2025,2,2,2,2,1,2,2,5,5,5,5,1,5,5,0,0.0,satisfied +8474,12440,Male,Loyal Customer,22,Personal Travel,Eco,262,3,3,3,2,2,3,2,2,1,5,3,4,5,2,31,11.0,neutral or dissatisfied +8475,87723,Female,Loyal Customer,61,Personal Travel,Eco Plus,606,3,5,3,1,4,5,4,1,1,3,1,3,1,5,54,67.0,neutral or dissatisfied +8476,39987,Male,Loyal Customer,24,Business travel,Business,3552,2,2,2,2,2,2,2,2,1,5,4,2,4,2,0,0.0,satisfied +8477,119223,Female,Loyal Customer,30,Personal Travel,Eco,257,2,4,2,4,1,2,1,1,2,1,3,2,3,1,0,23.0,neutral or dissatisfied +8478,122200,Female,Loyal Customer,62,Business travel,Business,603,5,5,5,5,3,4,4,4,4,5,4,3,4,4,5,0.0,satisfied +8479,55579,Male,Loyal Customer,52,Business travel,Business,1091,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +8480,5588,Male,Loyal Customer,38,Business travel,Business,3777,3,3,2,3,4,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +8481,48933,Female,disloyal Customer,22,Business travel,Business,326,5,4,5,3,1,5,1,1,3,4,1,1,3,1,0,0.0,satisfied +8482,110860,Female,Loyal Customer,55,Business travel,Business,2250,2,5,2,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +8483,81467,Female,Loyal Customer,67,Business travel,Business,2891,4,4,4,4,2,4,4,4,4,4,4,3,4,4,1,5.0,satisfied +8484,127059,Male,Loyal Customer,31,Business travel,Business,2162,1,4,2,4,1,1,1,1,1,3,4,1,4,1,27,17.0,neutral or dissatisfied +8485,55409,Female,Loyal Customer,63,Personal Travel,Eco,1558,3,4,3,2,4,5,4,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +8486,125017,Male,Loyal Customer,44,Personal Travel,Eco,184,3,4,3,1,5,3,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +8487,62684,Male,Loyal Customer,50,Business travel,Eco Plus,1846,3,3,4,3,3,3,3,3,1,2,4,2,4,3,0,17.0,neutral or dissatisfied +8488,43698,Male,disloyal Customer,22,Business travel,Eco,489,2,3,2,3,4,2,2,4,2,5,3,3,3,4,0,6.0,neutral or dissatisfied +8489,88241,Female,Loyal Customer,47,Business travel,Business,406,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +8490,17402,Male,Loyal Customer,63,Business travel,Eco,351,3,3,3,3,3,3,3,3,4,5,2,5,1,3,15,9.0,satisfied +8491,15612,Male,Loyal Customer,31,Personal Travel,Eco,229,2,4,2,1,1,2,1,1,5,3,5,3,5,1,24,16.0,neutral or dissatisfied +8492,85240,Male,Loyal Customer,33,Business travel,Business,2133,1,1,1,1,1,1,1,1,1,2,4,4,4,1,20,1.0,neutral or dissatisfied +8493,36936,Male,Loyal Customer,49,Personal Travel,Eco,867,2,4,2,3,3,2,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +8494,113328,Female,Loyal Customer,54,Business travel,Business,3063,3,3,2,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +8495,2014,Female,Loyal Customer,51,Business travel,Business,3754,5,5,5,5,5,4,4,4,4,4,4,4,4,4,12,9.0,satisfied +8496,55551,Female,Loyal Customer,16,Personal Travel,Eco,550,2,2,2,3,1,2,4,1,2,4,3,1,4,1,17,18.0,neutral or dissatisfied +8497,16226,Female,disloyal Customer,22,Business travel,Eco,266,4,5,4,1,4,1,2,3,4,4,4,2,4,2,184,179.0,satisfied +8498,88508,Female,disloyal Customer,26,Business travel,Eco,404,1,0,1,2,1,1,1,1,3,2,1,5,2,1,0,0.0,neutral or dissatisfied +8499,123666,Female,Loyal Customer,68,Business travel,Eco,214,1,4,4,4,1,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +8500,66128,Male,Loyal Customer,36,Personal Travel,Eco,583,1,5,1,3,1,1,1,1,5,4,5,3,5,1,0,12.0,neutral or dissatisfied +8501,84319,Male,Loyal Customer,19,Business travel,Business,2482,3,5,5,5,3,3,3,3,3,1,2,4,3,3,70,61.0,neutral or dissatisfied +8502,127770,Female,Loyal Customer,45,Business travel,Business,2831,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +8503,84279,Female,Loyal Customer,70,Personal Travel,Eco,334,1,2,1,4,2,3,4,5,5,1,5,2,5,2,0,0.0,neutral or dissatisfied +8504,65222,Male,Loyal Customer,56,Business travel,Business,247,0,0,0,1,4,5,5,4,4,4,4,4,4,4,9,1.0,satisfied +8505,44178,Male,Loyal Customer,58,Business travel,Business,231,3,3,3,3,1,5,4,4,4,4,4,2,4,1,0,0.0,satisfied +8506,118160,Male,Loyal Customer,51,Business travel,Business,1444,4,4,4,4,2,5,5,4,4,4,4,5,4,3,44,24.0,satisfied +8507,39038,Female,Loyal Customer,36,Personal Travel,Eco,113,1,3,0,1,2,0,2,2,5,2,3,1,2,2,0,0.0,neutral or dissatisfied +8508,80794,Female,Loyal Customer,52,Business travel,Business,2793,3,3,3,3,3,3,3,5,2,5,5,3,3,3,200,217.0,satisfied +8509,12269,Female,Loyal Customer,47,Business travel,Business,3003,1,1,1,1,1,4,3,4,4,5,4,2,4,5,0,17.0,satisfied +8510,92660,Male,disloyal Customer,39,Business travel,Business,453,1,1,1,1,4,1,2,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +8511,30424,Male,Loyal Customer,37,Business travel,Business,1872,3,1,1,1,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +8512,1104,Male,Loyal Customer,16,Personal Travel,Eco,354,2,1,4,4,5,4,5,5,2,4,3,3,4,5,0,12.0,neutral or dissatisfied +8513,49340,Female,disloyal Customer,27,Business travel,Eco,421,4,0,4,5,2,4,2,2,1,2,5,2,5,2,0,0.0,neutral or dissatisfied +8514,31559,Female,Loyal Customer,14,Personal Travel,Eco,862,3,4,2,2,3,2,3,3,5,5,4,1,4,3,0,8.0,neutral or dissatisfied +8515,5756,Female,Loyal Customer,30,Business travel,Business,642,3,2,3,2,3,3,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +8516,105991,Female,Loyal Customer,41,Personal Travel,Eco,912,1,4,1,4,4,1,4,4,2,5,5,1,2,4,11,9.0,neutral or dissatisfied +8517,8372,Female,Loyal Customer,49,Business travel,Business,674,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +8518,60117,Female,disloyal Customer,36,Business travel,Eco,1120,2,2,2,4,5,2,2,5,2,5,3,3,4,5,70,67.0,neutral or dissatisfied +8519,116241,Male,Loyal Customer,13,Personal Travel,Eco,342,4,3,4,3,2,4,2,2,3,3,3,2,2,2,0,0.0,satisfied +8520,58738,Male,Loyal Customer,41,Business travel,Business,3888,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +8521,51953,Female,Loyal Customer,56,Business travel,Eco,347,5,1,1,1,2,5,1,5,5,5,5,4,5,4,0,0.0,satisfied +8522,121274,Male,Loyal Customer,56,Business travel,Business,2075,1,1,1,1,4,5,5,4,4,4,4,3,4,3,16,19.0,satisfied +8523,25792,Male,Loyal Customer,19,Business travel,Business,1694,1,1,1,1,3,3,3,3,5,3,5,1,4,3,2,5.0,satisfied +8524,9937,Male,disloyal Customer,17,Business travel,Eco,357,1,4,1,3,1,1,1,4,4,3,3,1,4,1,163,179.0,neutral or dissatisfied +8525,70944,Male,Loyal Customer,23,Personal Travel,Eco,612,2,5,2,3,1,2,1,1,5,2,5,3,5,1,10,5.0,neutral or dissatisfied +8526,2386,Male,disloyal Customer,22,Business travel,Eco,641,4,0,4,2,3,4,3,3,3,5,4,4,4,3,42,41.0,satisfied +8527,42121,Male,Loyal Customer,7,Personal Travel,Eco,964,1,4,1,4,2,1,2,2,5,4,4,5,5,2,0,1.0,neutral or dissatisfied +8528,507,Female,Loyal Customer,36,Business travel,Business,1709,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +8529,2217,Male,Loyal Customer,30,Business travel,Business,642,2,2,2,2,5,5,5,5,3,3,4,5,4,5,34,37.0,satisfied +8530,86621,Female,Loyal Customer,29,Business travel,Business,1663,1,1,1,1,3,3,3,3,3,4,4,4,4,3,0,0.0,satisfied +8531,47381,Female,disloyal Customer,39,Business travel,Business,532,3,3,3,3,2,3,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +8532,5531,Female,Loyal Customer,35,Business travel,Eco,431,3,1,1,1,3,4,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +8533,667,Female,Loyal Customer,54,Business travel,Business,229,1,1,1,1,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +8534,28448,Female,Loyal Customer,36,Business travel,Business,2537,3,1,3,3,5,5,5,2,2,5,1,5,3,5,0,0.0,satisfied +8535,97460,Male,Loyal Customer,59,Business travel,Business,822,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +8536,77694,Female,disloyal Customer,22,Business travel,Business,731,5,0,5,2,2,5,2,2,5,3,5,5,5,2,0,0.0,satisfied +8537,7551,Female,Loyal Customer,33,Business travel,Business,3372,2,3,3,3,5,4,4,2,2,2,2,4,2,2,88,75.0,neutral or dissatisfied +8538,87071,Female,Loyal Customer,27,Business travel,Business,3162,5,5,5,5,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +8539,15001,Female,Loyal Customer,21,Personal Travel,Eco,1154,3,4,3,3,3,3,2,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +8540,89441,Female,Loyal Customer,18,Personal Travel,Eco,134,3,2,3,4,2,3,2,2,1,1,3,3,4,2,3,11.0,neutral or dissatisfied +8541,109015,Female,Loyal Customer,42,Business travel,Business,1516,5,5,5,5,5,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +8542,94535,Female,Loyal Customer,55,Business travel,Business,189,3,3,3,3,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +8543,45737,Male,Loyal Customer,24,Business travel,Eco Plus,1463,5,5,5,5,5,5,4,5,1,2,1,5,2,5,0,0.0,satisfied +8544,94888,Female,Loyal Customer,56,Business travel,Business,248,2,3,3,3,2,3,3,2,2,2,2,2,2,2,2,0.0,neutral or dissatisfied +8545,14783,Male,Loyal Customer,9,Personal Travel,Eco,694,3,4,2,1,5,2,4,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +8546,126955,Female,Loyal Customer,54,Business travel,Business,1845,5,5,4,5,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +8547,102994,Male,Loyal Customer,50,Business travel,Business,460,1,1,3,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +8548,79004,Female,Loyal Customer,56,Business travel,Business,226,5,5,2,5,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +8549,76510,Male,Loyal Customer,58,Business travel,Business,534,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +8550,100968,Female,Loyal Customer,13,Personal Travel,Eco,1204,3,2,3,3,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +8551,17077,Male,Loyal Customer,60,Personal Travel,Business,416,3,5,3,1,2,2,5,5,5,3,5,2,5,5,106,98.0,neutral or dissatisfied +8552,15179,Male,Loyal Customer,41,Personal Travel,Eco,416,3,4,3,3,3,3,3,3,2,4,3,5,2,3,0,0.0,neutral or dissatisfied +8553,75398,Female,disloyal Customer,29,Business travel,Business,2342,0,1,1,1,5,1,4,5,5,5,3,3,4,5,28,13.0,satisfied +8554,129435,Male,Loyal Customer,43,Business travel,Business,3644,3,3,2,3,5,5,5,4,2,5,5,5,5,5,226,220.0,satisfied +8555,106742,Female,disloyal Customer,25,Business travel,Eco,945,2,2,2,4,4,2,4,4,3,4,4,2,4,4,25,26.0,neutral or dissatisfied +8556,1737,Male,Loyal Customer,56,Personal Travel,Eco,364,4,2,2,2,1,2,1,1,2,4,2,2,2,1,0,0.0,satisfied +8557,26891,Female,Loyal Customer,28,Personal Travel,Eco,689,3,4,2,2,1,2,1,1,5,5,4,3,4,1,0,5.0,neutral or dissatisfied +8558,109064,Male,Loyal Customer,41,Business travel,Eco,781,4,4,2,2,4,4,4,4,3,1,2,3,3,4,10,0.0,neutral or dissatisfied +8559,66234,Female,Loyal Customer,42,Business travel,Eco,460,5,4,4,4,1,3,3,5,5,5,5,5,5,4,1,1.0,satisfied +8560,79763,Female,Loyal Customer,27,Business travel,Business,1915,1,1,1,1,5,5,5,5,4,5,4,5,4,5,2,0.0,satisfied +8561,89261,Female,disloyal Customer,30,Business travel,Eco,453,3,4,3,4,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +8562,94173,Female,Loyal Customer,28,Business travel,Business,562,4,2,2,2,4,4,4,4,2,1,3,1,3,4,0,0.0,neutral or dissatisfied +8563,2599,Female,Loyal Customer,19,Personal Travel,Eco,227,1,5,1,1,2,1,4,2,1,1,4,4,1,2,1,1.0,neutral or dissatisfied +8564,85609,Female,Loyal Customer,64,Personal Travel,Eco,192,3,5,3,4,5,5,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +8565,3095,Male,Loyal Customer,51,Personal Travel,Eco,678,2,4,2,1,4,2,1,4,3,5,5,3,4,4,19,22.0,neutral or dissatisfied +8566,47367,Female,disloyal Customer,21,Business travel,Eco,574,3,5,3,3,2,3,2,2,3,1,5,1,1,2,0,0.0,neutral or dissatisfied +8567,23317,Male,disloyal Customer,17,Business travel,Eco,979,1,1,1,3,5,1,5,5,1,3,4,3,3,5,57,52.0,neutral or dissatisfied +8568,111391,Male,Loyal Customer,33,Personal Travel,Eco,1173,3,5,4,1,2,4,2,2,4,4,3,5,4,2,0,2.0,neutral or dissatisfied +8569,37192,Female,Loyal Customer,29,Business travel,Eco Plus,1189,4,3,3,3,4,4,4,4,3,1,5,1,1,4,0,7.0,satisfied +8570,59742,Male,Loyal Customer,43,Business travel,Business,2398,2,2,5,2,3,4,4,5,5,5,5,5,5,3,15,9.0,satisfied +8571,61764,Male,Loyal Customer,11,Personal Travel,Eco,1303,2,3,2,3,4,2,4,4,1,5,2,3,4,4,3,0.0,neutral or dissatisfied +8572,39359,Male,Loyal Customer,36,Business travel,Eco,896,4,2,2,2,4,4,4,4,2,4,3,2,1,4,4,0.0,satisfied +8573,38614,Female,Loyal Customer,30,Personal Travel,Eco,231,2,1,2,3,5,2,1,5,3,4,4,4,3,5,6,0.0,neutral or dissatisfied +8574,74390,Female,Loyal Customer,56,Business travel,Business,3683,3,3,3,3,5,5,5,4,4,4,4,3,4,3,84,72.0,satisfied +8575,852,Male,Loyal Customer,49,Business travel,Business,134,2,3,1,3,3,2,2,1,1,1,2,4,1,3,0,0.0,neutral or dissatisfied +8576,87533,Female,Loyal Customer,47,Business travel,Eco Plus,373,3,3,3,3,2,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +8577,64033,Male,Loyal Customer,53,Business travel,Business,3222,1,1,1,1,2,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +8578,32133,Male,Loyal Customer,26,Business travel,Business,2314,3,3,3,3,5,5,3,5,1,1,1,4,1,5,0,0.0,satisfied +8579,128673,Female,Loyal Customer,27,Business travel,Business,2419,1,1,1,1,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +8580,123157,Male,Loyal Customer,42,Business travel,Business,1753,4,5,5,5,4,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +8581,88619,Male,Loyal Customer,42,Personal Travel,Eco,545,3,5,2,1,2,2,2,2,2,4,3,2,5,2,21,16.0,neutral or dissatisfied +8582,52644,Female,Loyal Customer,27,Personal Travel,Eco,119,4,4,4,3,5,4,5,5,5,1,4,1,2,5,0,0.0,neutral or dissatisfied +8583,70464,Female,Loyal Customer,53,Business travel,Business,867,1,1,1,1,4,5,5,2,2,2,2,3,2,5,0,19.0,satisfied +8584,66640,Male,disloyal Customer,22,Business travel,Eco,802,1,1,1,4,1,1,1,1,4,2,4,4,5,1,42,40.0,neutral or dissatisfied +8585,97125,Male,Loyal Customer,25,Business travel,Business,2744,3,3,3,3,5,4,5,5,5,5,5,4,5,5,5,0.0,satisfied +8586,3696,Female,Loyal Customer,60,Business travel,Business,2100,2,5,5,5,5,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +8587,49299,Female,Loyal Customer,48,Business travel,Business,421,5,5,5,5,1,1,5,1,1,2,1,5,1,4,21,14.0,satisfied +8588,90013,Female,Loyal Customer,52,Business travel,Business,1678,2,2,2,2,3,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +8589,5011,Male,Loyal Customer,9,Personal Travel,Eco,502,2,5,3,1,3,2,2,1,4,3,5,2,3,2,158,160.0,neutral or dissatisfied +8590,96591,Male,disloyal Customer,12,Business travel,Eco,861,2,1,1,4,4,1,4,4,4,3,3,3,4,4,13,14.0,neutral or dissatisfied +8591,5631,Female,Loyal Customer,55,Business travel,Business,2040,3,3,2,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +8592,15318,Male,Loyal Customer,57,Business travel,Business,589,2,1,1,1,1,3,4,2,2,2,2,3,2,3,0,3.0,neutral or dissatisfied +8593,107368,Male,Loyal Customer,46,Business travel,Business,3913,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +8594,70302,Female,Loyal Customer,39,Business travel,Business,334,4,4,4,4,3,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +8595,77133,Female,Loyal Customer,30,Personal Travel,Business,2105,3,0,3,4,5,3,1,5,3,2,5,4,5,5,117,85.0,neutral or dissatisfied +8596,51704,Male,Loyal Customer,49,Business travel,Business,3653,3,2,2,2,5,4,3,3,3,2,3,1,3,3,0,7.0,neutral or dissatisfied +8597,117452,Female,Loyal Customer,46,Business travel,Business,3028,1,1,1,1,1,4,4,1,1,2,1,3,1,4,26,60.0,neutral or dissatisfied +8598,104630,Female,Loyal Customer,51,Business travel,Eco,861,2,1,1,1,5,2,3,2,2,2,2,2,2,4,0,0.0,satisfied +8599,84983,Female,Loyal Customer,15,Business travel,Business,1590,5,5,5,5,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +8600,115709,Female,Loyal Customer,59,Business travel,Eco,337,3,5,5,5,2,4,4,3,3,3,3,1,3,4,9,25.0,neutral or dissatisfied +8601,119041,Female,disloyal Customer,38,Business travel,Business,2279,2,1,1,3,3,1,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +8602,72260,Female,Loyal Customer,14,Business travel,Business,2045,3,2,2,2,3,3,3,3,4,5,4,2,4,3,0,46.0,neutral or dissatisfied +8603,62921,Male,Loyal Customer,53,Business travel,Business,2456,5,5,5,5,2,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +8604,32673,Female,Loyal Customer,37,Business travel,Eco,101,3,1,1,1,3,3,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +8605,11872,Male,disloyal Customer,20,Personal Travel,Eco,1042,2,4,2,1,2,2,2,2,5,3,5,5,5,2,5,8.0,neutral or dissatisfied +8606,121399,Male,Loyal Customer,60,Business travel,Business,2991,1,1,1,1,5,5,5,4,4,4,4,5,4,4,21,18.0,satisfied +8607,62509,Female,Loyal Customer,35,Business travel,Business,1781,5,5,5,5,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +8608,115499,Female,Loyal Customer,15,Business travel,Business,1754,3,5,5,5,3,3,3,3,2,4,3,2,2,3,104,86.0,neutral or dissatisfied +8609,68324,Female,Loyal Customer,43,Business travel,Eco,2165,3,2,2,2,3,2,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +8610,8011,Female,disloyal Customer,26,Business travel,Eco,402,2,1,2,4,2,2,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +8611,112973,Female,Loyal Customer,24,Business travel,Eco Plus,1476,2,5,3,5,2,2,1,2,1,4,1,3,2,2,83,63.0,neutral or dissatisfied +8612,105744,Male,disloyal Customer,32,Business travel,Business,787,3,3,3,2,5,3,5,5,4,4,5,4,5,5,0,3.0,neutral or dissatisfied +8613,30373,Female,Loyal Customer,30,Business travel,Business,862,4,3,3,3,4,4,4,4,3,5,4,2,4,4,2,6.0,neutral or dissatisfied +8614,106781,Female,Loyal Customer,11,Personal Travel,Eco Plus,945,2,4,2,2,2,2,2,2,4,2,3,1,5,2,0,0.0,neutral or dissatisfied +8615,120036,Female,disloyal Customer,45,Business travel,Business,168,2,2,2,5,3,2,3,3,5,4,5,3,4,3,0,0.0,satisfied +8616,58272,Female,Loyal Customer,46,Business travel,Business,3332,5,5,5,5,5,4,5,4,4,4,4,3,4,4,15,21.0,satisfied +8617,2396,Female,Loyal Customer,54,Business travel,Business,1708,5,5,3,5,4,4,5,3,3,3,3,4,3,4,17,21.0,satisfied +8618,1231,Male,Loyal Customer,41,Personal Travel,Eco,102,3,4,3,4,2,3,3,2,1,5,3,2,4,2,0,0.0,neutral or dissatisfied +8619,77400,Female,Loyal Customer,14,Personal Travel,Eco,590,1,4,0,5,5,0,5,5,5,3,4,5,4,5,22,16.0,neutral or dissatisfied +8620,51856,Female,disloyal Customer,15,Business travel,Eco,438,1,1,1,4,3,1,2,3,1,2,4,4,3,3,2,6.0,neutral or dissatisfied +8621,63078,Female,Loyal Customer,49,Personal Travel,Eco,846,4,4,5,1,3,4,4,5,5,5,5,5,5,5,9,1.0,satisfied +8622,109982,Male,Loyal Customer,46,Business travel,Business,1204,2,3,2,2,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +8623,101629,Female,Loyal Customer,56,Personal Travel,Eco,1139,3,5,3,3,2,4,4,3,3,3,5,4,3,4,0,0.0,neutral or dissatisfied +8624,120522,Female,disloyal Customer,37,Business travel,Business,96,4,4,4,4,4,4,4,4,4,3,4,3,4,4,123,124.0,satisfied +8625,62471,Male,disloyal Customer,34,Business travel,Business,1723,2,2,2,1,2,2,2,2,4,3,4,4,4,2,19,1.0,neutral or dissatisfied +8626,89933,Female,disloyal Customer,63,Business travel,Eco,906,1,2,2,3,2,2,2,2,1,2,4,1,3,2,9,0.0,neutral or dissatisfied +8627,76883,Female,disloyal Customer,25,Business travel,Business,630,0,4,0,3,2,0,5,2,3,5,4,5,5,2,0,25.0,satisfied +8628,14161,Male,disloyal Customer,27,Business travel,Business,620,3,3,3,4,3,3,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +8629,123429,Female,Loyal Customer,26,Business travel,Business,2125,4,5,4,5,4,4,4,4,2,4,2,1,3,4,0,0.0,neutral or dissatisfied +8630,48116,Female,Loyal Customer,30,Business travel,Business,3800,3,3,5,3,5,5,5,5,5,4,2,3,3,5,0,0.0,satisfied +8631,33030,Male,Loyal Customer,62,Personal Travel,Eco,101,0,3,0,2,3,0,3,3,1,4,4,2,1,3,0,2.0,satisfied +8632,16912,Female,Loyal Customer,27,Business travel,Eco Plus,708,0,0,0,1,0,3,3,4,3,5,1,3,1,3,226,264.0,satisfied +8633,15196,Female,Loyal Customer,60,Business travel,Business,2063,2,4,4,4,2,2,2,1,1,4,3,2,4,2,122,164.0,neutral or dissatisfied +8634,34521,Male,Loyal Customer,36,Personal Travel,Eco,1428,2,3,2,2,1,2,1,1,1,5,3,1,3,1,0,33.0,neutral or dissatisfied +8635,25855,Female,Loyal Customer,48,Personal Travel,Eco,692,1,1,1,3,4,3,3,5,5,1,2,4,5,2,0,0.0,neutral or dissatisfied +8636,125448,Female,Loyal Customer,57,Business travel,Business,2917,1,1,5,1,2,1,1,4,5,1,2,1,1,1,17,2.0,neutral or dissatisfied +8637,17978,Female,Loyal Customer,56,Business travel,Business,332,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +8638,63240,Male,disloyal Customer,37,Business travel,Business,337,5,5,5,5,3,5,3,3,5,2,5,4,5,3,69,58.0,satisfied +8639,49158,Female,Loyal Customer,35,Business travel,Business,262,4,4,4,4,5,4,2,5,5,5,5,3,5,1,52,44.0,satisfied +8640,122438,Female,Loyal Customer,62,Personal Travel,Eco,1916,3,1,3,3,5,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +8641,101455,Female,Loyal Customer,44,Business travel,Business,3418,3,3,3,3,5,4,4,4,4,4,4,5,4,4,10,3.0,satisfied +8642,88967,Male,Loyal Customer,41,Business travel,Eco,1199,1,2,2,2,1,1,1,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +8643,13200,Male,Loyal Customer,70,Personal Travel,Eco,542,1,5,1,2,2,1,2,2,5,3,1,1,2,2,16,0.0,neutral or dissatisfied +8644,100774,Male,Loyal Customer,37,Business travel,Business,2245,4,4,4,4,2,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +8645,13827,Male,Loyal Customer,44,Business travel,Eco,628,3,1,1,1,3,3,3,3,3,3,2,4,2,3,54,40.0,satisfied +8646,16963,Female,Loyal Customer,36,Business travel,Eco,545,5,2,2,2,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +8647,92543,Female,Loyal Customer,15,Personal Travel,Eco,2139,2,5,1,1,3,1,3,3,5,5,5,5,5,3,10,0.0,neutral or dissatisfied +8648,40463,Female,Loyal Customer,49,Business travel,Business,175,5,5,5,5,1,3,4,5,5,5,3,1,5,3,0,0.0,satisfied +8649,111794,Female,Loyal Customer,42,Business travel,Business,3384,2,5,5,5,3,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +8650,116708,Male,Loyal Customer,55,Business travel,Eco Plus,296,5,5,5,5,5,5,5,5,2,4,4,1,3,5,9,6.0,satisfied +8651,83482,Male,Loyal Customer,40,Business travel,Business,3722,3,3,3,3,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +8652,67726,Female,Loyal Customer,24,Business travel,Eco,1205,4,4,4,4,4,4,1,4,2,2,4,2,4,4,1,0.0,neutral or dissatisfied +8653,65363,Female,disloyal Customer,17,Business travel,Eco,432,1,0,1,4,5,1,5,5,4,1,4,3,4,5,38,37.0,neutral or dissatisfied +8654,5402,Female,Loyal Customer,58,Personal Travel,Eco,812,4,2,4,4,5,4,3,1,1,4,1,2,1,2,0,0.0,neutral or dissatisfied +8655,84961,Male,Loyal Customer,45,Personal Travel,Eco Plus,481,2,4,2,4,5,2,5,5,2,3,3,1,3,5,70,58.0,neutral or dissatisfied +8656,35685,Female,Loyal Customer,50,Business travel,Business,2475,2,1,1,1,2,2,2,1,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +8657,44713,Male,Loyal Customer,36,Personal Travel,Eco,67,3,5,3,4,2,3,2,2,5,4,5,5,4,2,69,78.0,neutral or dissatisfied +8658,86692,Male,Loyal Customer,48,Business travel,Business,1747,3,3,3,3,2,5,5,4,4,4,4,4,4,4,2,4.0,satisfied +8659,107249,Male,Loyal Customer,59,Business travel,Business,3657,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,6.0,satisfied +8660,65293,Female,Loyal Customer,60,Personal Travel,Eco Plus,247,1,4,0,1,4,5,4,2,2,0,2,3,2,5,40,42.0,neutral or dissatisfied +8661,56238,Female,Loyal Customer,58,Personal Travel,Eco Plus,1608,1,5,1,2,5,3,5,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +8662,97873,Male,disloyal Customer,24,Business travel,Eco,391,3,5,2,2,2,2,2,2,3,4,5,4,5,2,1,0.0,neutral or dissatisfied +8663,51355,Male,disloyal Customer,43,Business travel,Eco Plus,308,3,3,3,1,1,3,1,1,3,4,1,3,2,1,0,6.0,neutral or dissatisfied +8664,97222,Female,Loyal Customer,34,Personal Travel,Eco Plus,1164,3,4,3,2,4,3,1,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +8665,74203,Female,Loyal Customer,40,Business travel,Business,3083,5,5,5,5,4,4,5,5,5,5,5,3,5,4,1,0.0,satisfied +8666,67745,Female,Loyal Customer,43,Business travel,Business,3008,2,2,2,2,2,4,5,5,5,5,5,5,5,4,5,0.0,satisfied +8667,6816,Male,Loyal Customer,49,Personal Travel,Eco,235,4,5,4,2,4,4,2,4,5,4,5,4,4,4,130,124.0,neutral or dissatisfied +8668,127325,Male,Loyal Customer,47,Business travel,Business,507,1,1,1,1,3,4,4,4,4,4,4,3,4,3,8,6.0,satisfied +8669,86364,Female,Loyal Customer,50,Business travel,Business,2120,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +8670,43080,Male,Loyal Customer,17,Personal Travel,Eco,414,2,5,4,5,2,4,2,2,4,1,2,5,1,2,0,0.0,neutral or dissatisfied +8671,95068,Female,Loyal Customer,63,Personal Travel,Eco,248,1,5,1,5,2,5,5,3,3,1,3,3,3,5,11,10.0,neutral or dissatisfied +8672,59380,Female,Loyal Customer,62,Business travel,Business,3927,2,3,3,3,4,3,3,2,2,2,2,4,2,3,9,0.0,neutral or dissatisfied +8673,93755,Female,disloyal Customer,34,Business travel,Eco,368,3,3,3,3,3,3,3,3,2,4,4,2,3,3,18,10.0,neutral or dissatisfied +8674,60895,Female,Loyal Customer,14,Personal Travel,Eco,420,3,2,3,3,2,3,2,2,3,2,4,3,4,2,5,0.0,neutral or dissatisfied +8675,102270,Female,Loyal Customer,41,Business travel,Business,258,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +8676,81990,Male,Loyal Customer,57,Business travel,Eco,1535,1,2,2,2,1,1,1,1,3,2,2,3,3,1,0,10.0,neutral or dissatisfied +8677,82659,Male,Loyal Customer,37,Business travel,Business,120,2,2,2,2,3,2,1,5,5,5,5,1,5,1,0,0.0,satisfied +8678,27721,Male,disloyal Customer,26,Business travel,Eco,775,2,2,2,3,2,2,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +8679,62023,Male,disloyal Customer,29,Business travel,Eco,2475,2,2,2,3,1,2,1,1,4,5,1,4,3,1,0,0.0,neutral or dissatisfied +8680,16273,Male,Loyal Customer,16,Personal Travel,Eco,748,3,3,2,2,3,2,3,3,3,4,2,3,2,3,32,60.0,neutral or dissatisfied +8681,82505,Female,Loyal Customer,49,Business travel,Business,1749,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +8682,59810,Female,Loyal Customer,29,Business travel,Business,1023,4,1,1,1,4,3,4,4,3,4,4,4,3,4,45,35.0,neutral or dissatisfied +8683,87183,Female,Loyal Customer,40,Business travel,Business,2960,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +8684,1235,Male,Loyal Customer,39,Personal Travel,Eco,354,3,3,3,2,1,3,1,1,3,4,2,1,2,1,3,7.0,neutral or dissatisfied +8685,70809,Female,Loyal Customer,40,Business travel,Eco,624,2,2,1,2,2,2,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +8686,34649,Male,Loyal Customer,37,Personal Travel,Eco,427,4,2,4,3,5,4,5,5,4,2,4,2,4,5,0,0.0,satisfied +8687,100677,Male,disloyal Customer,39,Business travel,Eco,628,2,4,2,3,1,2,3,1,3,5,3,2,4,1,33,26.0,neutral or dissatisfied +8688,54370,Male,disloyal Customer,25,Business travel,Business,305,4,0,4,1,1,4,1,1,5,5,5,4,4,1,44,30.0,neutral or dissatisfied +8689,106870,Female,Loyal Customer,35,Business travel,Business,2310,4,5,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +8690,43356,Female,Loyal Customer,18,Business travel,Business,387,2,2,2,2,5,5,5,5,4,4,1,3,5,5,0,0.0,satisfied +8691,57536,Male,disloyal Customer,17,Business travel,Eco,413,3,1,2,4,3,2,3,3,4,5,3,3,3,3,49,41.0,neutral or dissatisfied +8692,54790,Male,Loyal Customer,41,Personal Travel,Business,985,0,4,1,3,4,3,4,3,3,1,3,1,3,3,0,0.0,satisfied +8693,74976,Male,Loyal Customer,59,Personal Travel,Eco,2475,1,2,0,4,5,0,5,5,3,5,4,2,4,5,0,0.0,neutral or dissatisfied +8694,11490,Female,Loyal Customer,40,Personal Travel,Eco Plus,667,2,2,2,3,3,2,2,3,3,5,3,4,2,3,0,0.0,neutral or dissatisfied +8695,25247,Female,Loyal Customer,31,Business travel,Eco Plus,787,5,5,1,1,5,5,5,5,3,2,3,5,4,5,0,0.0,satisfied +8696,50890,Male,Loyal Customer,48,Personal Travel,Eco,373,2,1,2,2,5,2,5,5,3,4,2,4,3,5,18,4.0,neutral or dissatisfied +8697,809,Male,Loyal Customer,57,Business travel,Business,309,2,1,1,1,2,2,3,2,2,2,2,2,2,1,17,16.0,neutral or dissatisfied +8698,23421,Male,Loyal Customer,36,Personal Travel,Eco,541,1,4,1,1,4,1,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +8699,8694,Male,Loyal Customer,46,Business travel,Business,2771,0,0,0,2,1,3,4,3,3,3,3,3,3,1,0,0.0,satisfied +8700,94911,Male,Loyal Customer,37,Business travel,Business,2586,5,5,5,5,4,2,4,5,5,5,5,2,5,4,10,5.0,satisfied +8701,41201,Female,Loyal Customer,26,Business travel,Business,1988,4,4,4,4,4,4,4,4,5,4,1,4,3,4,37,28.0,satisfied +8702,36134,Female,Loyal Customer,64,Business travel,Business,1609,4,4,4,4,4,3,5,4,4,4,4,3,4,2,0,0.0,satisfied +8703,19704,Male,Loyal Customer,30,Business travel,Business,409,2,2,2,2,4,4,4,4,3,4,1,1,2,4,0,0.0,satisfied +8704,111903,Male,Loyal Customer,37,Personal Travel,Eco,804,2,5,2,4,1,2,1,1,5,4,3,1,2,1,10,1.0,neutral or dissatisfied +8705,10266,Male,Loyal Customer,59,Personal Travel,Business,201,2,2,0,4,3,4,4,4,4,0,4,4,4,2,0,0.0,neutral or dissatisfied +8706,88213,Male,disloyal Customer,17,Business travel,Eco,404,2,2,2,4,2,2,2,2,4,3,3,3,3,2,0,0.0,neutral or dissatisfied +8707,53037,Male,Loyal Customer,41,Business travel,Eco,1208,4,4,4,4,4,4,4,4,3,2,4,3,2,4,0,0.0,satisfied +8708,109805,Female,Loyal Customer,49,Business travel,Eco,1092,4,5,5,5,2,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +8709,11780,Female,Loyal Customer,20,Personal Travel,Eco,395,4,1,4,3,2,4,1,2,3,4,4,2,4,2,0,0.0,satisfied +8710,75245,Female,Loyal Customer,28,Personal Travel,Eco,1846,2,5,2,3,2,2,2,2,5,2,3,3,4,2,2,0.0,neutral or dissatisfied +8711,100669,Female,Loyal Customer,53,Business travel,Business,628,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +8712,100191,Male,Loyal Customer,61,Personal Travel,Eco,725,2,5,2,3,2,2,2,2,4,3,3,2,4,2,4,0.0,neutral or dissatisfied +8713,46033,Female,Loyal Customer,44,Business travel,Business,3612,3,3,3,3,3,3,3,4,5,3,2,3,4,3,105,146.0,satisfied +8714,7203,Male,Loyal Customer,34,Business travel,Business,3747,2,3,3,3,1,4,3,3,3,3,2,4,3,1,58,67.0,neutral or dissatisfied +8715,112455,Male,disloyal Customer,39,Business travel,Eco,453,1,4,1,4,4,1,4,4,2,1,4,4,3,4,42,34.0,neutral or dissatisfied +8716,108624,Male,disloyal Customer,27,Business travel,Business,696,3,3,3,5,3,1,5,4,4,4,4,5,4,5,128,152.0,neutral or dissatisfied +8717,110210,Male,Loyal Customer,31,Business travel,Business,2451,2,2,2,2,4,4,4,4,3,3,5,4,4,4,2,0.0,satisfied +8718,68819,Male,Loyal Customer,35,Business travel,Eco Plus,926,1,5,5,5,1,1,1,1,1,1,4,4,4,1,0,9.0,neutral or dissatisfied +8719,53505,Female,Loyal Customer,49,Personal Travel,Eco,2288,3,2,3,1,5,2,2,4,4,3,4,3,4,3,4,0.0,neutral or dissatisfied +8720,65998,Female,Loyal Customer,46,Business travel,Business,1502,3,3,5,3,3,4,5,3,3,4,3,4,3,4,1,6.0,satisfied +8721,91268,Male,Loyal Customer,66,Personal Travel,Eco,406,2,4,4,3,3,4,4,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +8722,38791,Male,Loyal Customer,73,Business travel,Eco,387,4,3,3,3,4,4,4,4,1,3,5,3,1,4,0,0.0,satisfied +8723,16110,Female,Loyal Customer,35,Personal Travel,Business,725,5,1,5,4,4,3,3,3,3,5,3,4,3,3,0,0.0,satisfied +8724,115042,Female,Loyal Customer,55,Business travel,Business,342,5,5,5,5,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +8725,69560,Female,disloyal Customer,42,Business travel,Eco,2475,3,3,3,3,3,5,5,1,1,4,4,5,2,5,2,0.0,neutral or dissatisfied +8726,670,Female,disloyal Customer,50,Business travel,Business,134,1,1,1,4,5,1,5,5,1,1,4,2,4,5,0,10.0,neutral or dissatisfied +8727,117722,Male,disloyal Customer,26,Business travel,Business,935,5,5,5,2,1,5,1,1,5,5,5,3,5,1,7,1.0,satisfied +8728,76662,Female,Loyal Customer,56,Personal Travel,Eco,547,4,3,4,2,1,3,5,5,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +8729,88227,Female,Loyal Customer,77,Business travel,Business,270,4,2,2,2,1,4,3,4,4,4,4,1,4,4,3,4.0,neutral or dissatisfied +8730,11288,Male,Loyal Customer,67,Personal Travel,Eco,247,1,2,1,3,4,1,3,4,2,3,4,4,4,4,74,91.0,neutral or dissatisfied +8731,60817,Female,Loyal Customer,40,Personal Travel,Eco,455,4,5,4,3,5,4,5,5,3,5,5,4,5,5,0,0.0,satisfied +8732,56261,Male,Loyal Customer,40,Business travel,Business,2753,1,1,1,1,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +8733,45962,Male,Loyal Customer,25,Business travel,Eco Plus,913,0,3,0,1,3,0,5,3,1,1,2,3,4,3,0,0.0,satisfied +8734,62093,Female,Loyal Customer,29,Business travel,Business,2565,2,2,1,2,5,4,5,5,3,5,5,3,4,5,0,0.0,satisfied +8735,27387,Female,Loyal Customer,36,Business travel,Eco,954,5,3,3,3,5,5,5,5,4,4,4,1,1,5,0,0.0,satisfied +8736,122695,Male,Loyal Customer,66,Personal Travel,Eco,361,2,4,2,4,4,2,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +8737,53308,Male,Loyal Customer,12,Personal Travel,Eco,811,3,1,3,2,2,3,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +8738,72210,Female,Loyal Customer,9,Personal Travel,Eco,2724,3,2,4,4,4,4,2,4,5,3,4,2,2,2,1,0.0,neutral or dissatisfied +8739,70203,Female,Loyal Customer,48,Personal Travel,Eco,258,2,5,2,4,4,3,4,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +8740,67351,Female,Loyal Customer,38,Personal Travel,Eco,1471,3,4,3,3,3,3,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +8741,97219,Female,Loyal Customer,16,Business travel,Eco Plus,1497,1,1,1,1,1,1,3,1,2,5,4,4,4,1,7,7.0,neutral or dissatisfied +8742,49431,Female,disloyal Customer,23,Business travel,Eco,89,4,1,4,3,3,4,4,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +8743,14616,Male,Loyal Customer,28,Personal Travel,Eco Plus,448,1,5,1,3,1,2,2,3,2,5,4,2,5,2,135,142.0,neutral or dissatisfied +8744,39569,Female,Loyal Customer,67,Business travel,Business,2828,3,3,3,3,1,2,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +8745,127928,Male,Loyal Customer,29,Business travel,Business,2300,4,4,4,4,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +8746,43315,Male,Loyal Customer,40,Business travel,Business,436,2,1,2,2,1,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +8747,12528,Male,Loyal Customer,12,Business travel,Business,871,1,4,4,4,1,1,1,1,2,4,4,2,3,1,0,0.0,neutral or dissatisfied +8748,98540,Female,Loyal Customer,66,Personal Travel,Eco,668,1,5,1,3,3,4,5,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +8749,48653,Male,Loyal Customer,57,Business travel,Business,2420,1,1,1,1,4,4,5,5,5,5,5,5,5,5,88,119.0,satisfied +8750,58811,Male,Loyal Customer,11,Personal Travel,Eco,864,2,4,2,3,2,2,2,2,3,5,4,5,4,2,47,44.0,neutral or dissatisfied +8751,126475,Female,Loyal Customer,59,Business travel,Business,1788,3,3,1,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +8752,58431,Female,Loyal Customer,41,Business travel,Eco,323,5,2,2,2,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +8753,27923,Male,Loyal Customer,34,Personal Travel,Eco,689,3,4,3,3,2,3,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +8754,20867,Female,Loyal Customer,70,Personal Travel,Eco,534,1,4,1,5,4,4,4,4,4,1,4,3,4,4,9,0.0,neutral or dissatisfied +8755,56603,Male,Loyal Customer,34,Business travel,Eco,1068,1,1,3,1,1,1,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +8756,125463,Male,Loyal Customer,26,Business travel,Business,2845,2,2,2,2,4,4,4,3,3,4,4,4,3,4,138,125.0,satisfied +8757,18167,Male,Loyal Customer,44,Business travel,Eco Plus,430,4,5,5,5,4,4,4,4,3,5,5,5,3,4,0,0.0,satisfied +8758,125523,Male,Loyal Customer,45,Business travel,Business,3914,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +8759,33573,Male,Loyal Customer,34,Business travel,Business,399,1,1,1,1,1,2,1,4,4,5,4,3,4,1,0,1.0,satisfied +8760,94560,Female,Loyal Customer,66,Business travel,Eco,528,1,4,3,4,5,3,3,1,1,1,1,4,1,3,20,11.0,neutral or dissatisfied +8761,60138,Female,Loyal Customer,30,Business travel,Business,3101,2,4,4,4,2,3,2,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +8762,63881,Male,Loyal Customer,53,Business travel,Eco,1212,2,5,5,5,2,2,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +8763,59866,Female,Loyal Customer,60,Business travel,Business,997,3,3,3,3,2,4,5,4,4,4,4,4,4,5,21,0.0,satisfied +8764,64322,Female,Loyal Customer,51,Business travel,Business,1172,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +8765,11959,Male,Loyal Customer,47,Business travel,Business,3178,2,2,2,2,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +8766,77451,Female,disloyal Customer,38,Business travel,Business,507,5,5,5,2,5,5,4,5,4,4,4,5,5,5,0,0.0,satisfied +8767,61809,Male,Loyal Customer,55,Personal Travel,Eco,1379,2,1,2,4,5,2,5,5,4,3,3,3,3,5,0,0.0,neutral or dissatisfied +8768,104804,Male,Loyal Customer,45,Personal Travel,Eco,787,1,4,1,2,3,1,3,3,1,4,4,5,2,3,2,0.0,neutral or dissatisfied +8769,95377,Female,Loyal Customer,18,Personal Travel,Eco,189,0,4,0,1,1,0,1,1,4,4,5,5,4,1,0,0.0,satisfied +8770,51,Male,Loyal Customer,44,Business travel,Business,1859,2,2,4,2,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +8771,100575,Female,Loyal Customer,30,Business travel,Business,486,2,2,2,2,4,4,4,4,4,5,5,5,5,4,4,3.0,satisfied +8772,696,Male,disloyal Customer,22,Business travel,Eco,102,1,5,1,3,4,1,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +8773,121066,Male,disloyal Customer,21,Business travel,Eco,993,4,4,4,3,5,4,5,5,5,3,5,4,4,5,0,0.0,satisfied +8774,30209,Female,Loyal Customer,62,Personal Travel,Eco Plus,123,2,4,2,4,1,1,5,5,5,2,5,1,5,4,0,0.0,neutral or dissatisfied +8775,96749,Male,Loyal Customer,40,Business travel,Business,2927,3,3,3,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +8776,25112,Female,Loyal Customer,27,Business travel,Eco,946,4,4,4,4,4,4,4,4,1,2,2,2,2,4,3,0.0,neutral or dissatisfied +8777,129844,Male,Loyal Customer,36,Personal Travel,Eco,337,2,5,3,4,5,3,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +8778,119417,Female,Loyal Customer,49,Business travel,Eco,399,5,4,4,4,2,2,4,5,5,5,5,2,5,5,0,0.0,satisfied +8779,97768,Male,disloyal Customer,63,Personal Travel,Business,471,2,3,2,4,2,1,1,3,2,3,3,1,2,1,174,172.0,neutral or dissatisfied +8780,104514,Female,Loyal Customer,25,Business travel,Business,942,4,4,4,4,5,5,5,5,4,5,4,4,4,5,0,0.0,satisfied +8781,45575,Female,Loyal Customer,43,Business travel,Business,313,4,4,4,4,2,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +8782,117794,Female,Loyal Customer,19,Business travel,Business,328,2,2,3,2,2,2,2,2,2,1,4,4,4,2,12,19.0,neutral or dissatisfied +8783,45087,Female,Loyal Customer,42,Business travel,Eco,299,5,3,3,3,2,2,4,5,5,5,5,1,5,1,0,0.0,satisfied +8784,62008,Female,Loyal Customer,56,Business travel,Business,2586,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +8785,22242,Female,Loyal Customer,54,Business travel,Business,3064,5,5,5,5,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +8786,49516,Male,Loyal Customer,39,Business travel,Eco,304,1,5,5,5,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +8787,70620,Female,Loyal Customer,49,Business travel,Business,3080,3,1,2,1,5,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +8788,110117,Male,disloyal Customer,36,Business travel,Business,634,3,3,3,1,1,3,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +8789,43358,Female,Loyal Customer,16,Business travel,Business,1725,3,1,1,1,3,3,3,3,2,3,3,1,3,3,19,10.0,neutral or dissatisfied +8790,77853,Male,Loyal Customer,8,Personal Travel,Eco Plus,874,4,4,4,5,3,4,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +8791,18198,Female,Loyal Customer,37,Business travel,Eco,224,2,4,4,4,2,2,2,2,1,1,4,3,4,2,7,0.0,neutral or dissatisfied +8792,34629,Male,Loyal Customer,33,Business travel,Business,3433,3,3,3,3,2,2,2,2,5,1,1,5,2,2,0,0.0,satisfied +8793,60871,Male,Loyal Customer,66,Business travel,Eco Plus,1491,2,1,1,1,2,2,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +8794,65792,Male,Loyal Customer,57,Business travel,Business,1389,4,4,4,4,2,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +8795,84462,Female,Loyal Customer,56,Personal Travel,Eco,290,2,4,2,3,3,4,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +8796,102081,Male,Loyal Customer,39,Business travel,Business,1679,3,3,3,3,4,5,4,4,4,4,4,4,4,5,42,34.0,satisfied +8797,10531,Female,Loyal Customer,56,Business travel,Business,2224,3,3,3,3,4,4,5,4,4,4,4,5,4,3,57,43.0,satisfied +8798,35660,Male,Loyal Customer,26,Business travel,Business,2576,2,2,2,2,4,4,4,1,1,3,4,4,4,4,48,45.0,satisfied +8799,117341,Male,disloyal Customer,39,Business travel,Business,296,5,5,5,2,3,5,2,3,5,2,4,5,4,3,0,0.0,satisfied +8800,127077,Female,Loyal Customer,22,Business travel,Eco,247,3,2,3,2,3,3,1,3,3,2,1,3,1,3,0,0.0,neutral or dissatisfied +8801,56130,Female,Loyal Customer,56,Business travel,Business,1400,5,5,5,5,5,5,5,3,3,4,3,5,3,3,31,29.0,satisfied +8802,4259,Female,Loyal Customer,50,Business travel,Eco,502,3,2,2,2,5,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +8803,17671,Male,disloyal Customer,45,Business travel,Business,282,3,4,4,3,1,3,1,1,5,5,1,2,4,1,0,0.0,neutral or dissatisfied +8804,117626,Male,Loyal Customer,40,Personal Travel,Eco,1020,3,4,3,3,2,3,2,2,5,3,4,3,4,2,7,0.0,neutral or dissatisfied +8805,49337,Male,Loyal Customer,44,Business travel,Eco,109,3,1,4,1,3,3,3,3,3,1,2,3,1,3,0,0.0,satisfied +8806,62173,Female,Loyal Customer,10,Business travel,Business,2565,1,3,3,3,1,1,1,1,1,3,4,3,3,1,6,3.0,neutral or dissatisfied +8807,55102,Female,Loyal Customer,44,Business travel,Business,903,5,5,5,5,3,1,5,5,5,5,5,2,5,3,100,75.0,satisfied +8808,30564,Female,Loyal Customer,25,Business travel,Business,3716,5,5,5,5,5,5,5,5,5,1,5,5,5,5,0,0.0,satisfied +8809,76031,Male,Loyal Customer,25,Personal Travel,Eco,311,3,4,4,3,1,4,2,1,4,2,2,5,2,1,0,10.0,neutral or dissatisfied +8810,42728,Female,Loyal Customer,25,Business travel,Eco,646,4,3,3,3,4,4,3,4,5,1,5,4,4,4,5,0.0,satisfied +8811,106910,Female,Loyal Customer,42,Business travel,Business,3512,3,3,3,3,5,5,5,4,4,4,4,5,4,3,21,11.0,satisfied +8812,14885,Female,disloyal Customer,27,Business travel,Eco,315,2,4,2,3,1,2,1,1,3,1,3,3,4,1,54,53.0,neutral or dissatisfied +8813,70356,Male,Loyal Customer,16,Personal Travel,Eco Plus,986,3,1,3,3,2,3,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +8814,19259,Female,Loyal Customer,25,Business travel,Eco,802,2,1,1,1,2,2,4,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +8815,85740,Male,Loyal Customer,54,Business travel,Business,666,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +8816,95112,Female,Loyal Customer,34,Personal Travel,Eco,458,3,5,3,2,1,3,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +8817,106055,Female,Loyal Customer,52,Business travel,Eco Plus,452,1,4,4,4,4,3,3,1,1,1,1,1,1,3,12,19.0,neutral or dissatisfied +8818,62808,Female,Loyal Customer,53,Personal Travel,Eco,2556,3,2,3,4,5,3,4,5,5,3,5,4,5,2,0,8.0,neutral or dissatisfied +8819,31649,Female,Loyal Customer,51,Business travel,Eco,844,5,2,2,2,1,5,4,4,4,5,4,4,4,3,0,77.0,satisfied +8820,11597,Female,Loyal Customer,45,Business travel,Business,3269,0,0,0,3,2,2,1,3,3,3,3,5,3,1,0,0.0,satisfied +8821,81077,Female,Loyal Customer,40,Business travel,Business,3051,3,3,3,3,2,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +8822,108075,Male,Loyal Customer,41,Business travel,Business,3750,4,4,4,4,4,4,4,4,4,4,5,4,3,4,168,185.0,satisfied +8823,92560,Male,Loyal Customer,52,Personal Travel,Eco,2139,2,4,2,3,4,2,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +8824,59909,Female,Loyal Customer,22,Business travel,Business,3907,5,5,2,5,3,3,3,3,5,2,4,3,4,3,1,0.0,satisfied +8825,58633,Female,disloyal Customer,23,Business travel,Business,867,4,5,4,4,3,4,3,3,4,2,5,5,5,3,19,2.0,satisfied +8826,29532,Male,Loyal Customer,44,Business travel,Eco,2552,5,2,2,2,5,5,5,1,5,4,2,5,2,5,0,0.0,satisfied +8827,37917,Male,Loyal Customer,39,Personal Travel,Eco,1065,3,5,3,3,2,3,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +8828,89598,Male,disloyal Customer,62,Business travel,Eco,1010,4,4,4,3,2,4,2,2,2,4,3,2,4,2,102,86.0,neutral or dissatisfied +8829,96151,Male,Loyal Customer,50,Business travel,Business,3216,3,1,4,4,5,4,3,3,3,3,3,1,3,1,0,1.0,neutral or dissatisfied +8830,18580,Female,disloyal Customer,40,Business travel,Business,201,2,2,2,4,2,2,2,2,3,3,4,3,3,2,6,6.0,neutral or dissatisfied +8831,47897,Female,disloyal Customer,27,Business travel,Eco,451,2,4,2,3,1,2,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +8832,84156,Female,Loyal Customer,28,Personal Travel,Eco Plus,1355,2,4,2,4,4,2,4,4,4,5,2,3,4,4,0,0.0,neutral or dissatisfied +8833,116790,Female,Loyal Customer,48,Personal Travel,Eco Plus,362,2,5,2,3,4,5,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +8834,119967,Male,Loyal Customer,36,Personal Travel,Eco,1009,4,4,4,3,1,4,1,1,5,4,4,3,5,1,0,0.0,satisfied +8835,80403,Female,Loyal Customer,53,Business travel,Business,1416,2,2,2,2,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +8836,99878,Male,Loyal Customer,18,Business travel,Business,1436,2,2,2,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +8837,307,Female,Loyal Customer,31,Business travel,Business,2146,5,5,5,5,5,4,5,5,5,5,4,3,4,5,0,15.0,satisfied +8838,68240,Female,disloyal Customer,23,Business travel,Eco,432,4,1,4,3,2,4,2,2,3,3,2,4,3,2,0,0.0,neutral or dissatisfied +8839,59116,Female,Loyal Customer,18,Personal Travel,Eco,1846,3,2,3,4,2,3,2,2,4,4,2,4,4,2,6,7.0,neutral or dissatisfied +8840,108348,Female,disloyal Customer,25,Business travel,Eco,1463,2,2,2,3,4,2,4,4,4,1,4,2,4,4,15,0.0,neutral or dissatisfied +8841,42733,Female,Loyal Customer,36,Business travel,Eco,536,5,2,2,2,5,5,5,5,1,1,1,5,4,5,0,4.0,satisfied +8842,2333,Male,Loyal Customer,52,Personal Travel,Eco,690,1,5,1,1,5,1,5,5,4,4,5,3,4,5,3,10.0,neutral or dissatisfied +8843,53639,Female,Loyal Customer,21,Personal Travel,Eco,1874,4,2,4,4,3,4,3,3,2,4,3,1,4,3,2,0.0,neutral or dissatisfied +8844,36573,Male,Loyal Customer,35,Business travel,Eco,1249,3,4,4,4,3,3,3,3,3,2,1,5,2,3,19,12.0,satisfied +8845,116072,Female,Loyal Customer,61,Personal Travel,Eco,342,2,1,2,4,4,3,3,4,4,2,4,2,4,1,15,8.0,neutral or dissatisfied +8846,80863,Female,Loyal Customer,34,Personal Travel,Eco,692,2,2,2,3,1,2,5,1,2,4,2,4,3,1,0,0.0,neutral or dissatisfied +8847,41723,Female,Loyal Customer,55,Business travel,Eco,695,4,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +8848,61277,Female,Loyal Customer,58,Personal Travel,Eco,862,3,5,3,5,5,4,4,3,3,3,3,4,3,5,9,7.0,neutral or dissatisfied +8849,94580,Female,disloyal Customer,23,Business travel,Eco,248,4,4,5,4,5,5,5,5,5,5,5,3,4,5,20,15.0,satisfied +8850,48121,Male,Loyal Customer,36,Business travel,Eco,259,3,4,4,4,3,4,3,3,3,5,4,2,2,3,0,0.0,satisfied +8851,70638,Female,Loyal Customer,57,Business travel,Business,1530,5,5,5,5,4,5,5,4,4,3,4,3,4,5,1,0.0,satisfied +8852,21017,Male,Loyal Customer,50,Business travel,Eco,106,4,1,1,1,4,4,4,4,4,3,3,5,5,4,3,0.0,satisfied +8853,50068,Male,Loyal Customer,53,Business travel,Eco,190,4,2,2,2,4,4,4,4,4,5,4,3,4,4,0,4.0,neutral or dissatisfied +8854,57545,Male,Loyal Customer,45,Personal Travel,Eco,413,1,4,1,4,1,1,5,1,5,4,4,3,5,1,60,51.0,neutral or dissatisfied +8855,54642,Male,Loyal Customer,48,Business travel,Eco,964,4,2,2,2,4,4,4,4,5,2,5,2,4,4,8,0.0,satisfied +8856,74053,Female,Loyal Customer,34,Business travel,Eco Plus,1194,5,3,3,3,5,5,5,5,4,2,2,2,1,5,0,0.0,satisfied +8857,55128,Female,Loyal Customer,15,Personal Travel,Eco,1608,1,4,1,4,1,1,1,1,3,3,2,2,4,1,0,0.0,neutral or dissatisfied +8858,1851,Female,Loyal Customer,59,Business travel,Business,408,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +8859,13236,Female,Loyal Customer,69,Business travel,Eco,468,5,5,5,5,5,4,5,5,5,5,5,1,5,1,0,0.0,satisfied +8860,37818,Male,disloyal Customer,24,Business travel,Eco Plus,972,4,3,4,4,3,4,3,3,1,3,4,1,3,3,0,0.0,satisfied +8861,67154,Male,Loyal Customer,34,Business travel,Business,985,1,3,3,3,4,3,3,1,1,2,1,2,1,2,1,14.0,neutral or dissatisfied +8862,34638,Male,Loyal Customer,58,Business travel,Eco,541,5,4,4,4,5,5,5,5,5,5,2,5,5,5,3,0.0,satisfied +8863,90265,Male,Loyal Customer,24,Business travel,Business,1900,3,4,3,4,3,3,3,4,3,3,4,3,2,3,236,234.0,neutral or dissatisfied +8864,4204,Male,disloyal Customer,30,Business travel,Business,888,3,3,3,3,1,3,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +8865,76773,Male,Loyal Customer,40,Business travel,Business,2323,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +8866,94914,Male,Loyal Customer,65,Business travel,Eco,293,4,1,4,4,4,4,4,4,2,2,1,2,5,4,0,0.0,satisfied +8867,63271,Male,Loyal Customer,33,Business travel,Business,447,2,2,2,2,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +8868,13767,Female,Loyal Customer,70,Personal Travel,Eco Plus,401,3,5,3,4,4,4,4,1,1,3,1,3,1,5,34,14.0,neutral or dissatisfied +8869,54382,Female,Loyal Customer,39,Business travel,Eco,305,5,2,2,2,5,5,5,5,3,5,1,4,1,5,5,0.0,satisfied +8870,98274,Male,Loyal Customer,29,Business travel,Business,3909,4,4,4,4,3,4,4,2,3,4,3,4,1,4,94,138.0,neutral or dissatisfied +8871,123251,Female,Loyal Customer,33,Personal Travel,Eco,600,2,4,1,1,3,1,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +8872,83671,Female,Loyal Customer,42,Business travel,Business,577,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +8873,26773,Female,Loyal Customer,40,Business travel,Eco,1199,4,5,5,5,4,4,4,4,5,1,2,3,5,4,0,35.0,satisfied +8874,105358,Female,Loyal Customer,50,Personal Travel,Eco,528,3,4,1,3,4,5,4,2,2,1,2,2,2,1,12,7.0,neutral or dissatisfied +8875,97983,Female,Loyal Customer,33,Personal Travel,Eco,483,3,0,3,1,5,3,5,5,5,5,4,3,4,5,96,92.0,neutral or dissatisfied +8876,88760,Female,Loyal Customer,45,Business travel,Eco Plus,581,3,4,4,4,2,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +8877,57466,Female,Loyal Customer,52,Personal Travel,Eco,334,3,1,3,4,1,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +8878,38893,Female,Loyal Customer,12,Personal Travel,Business,205,4,4,4,2,1,4,1,1,5,1,3,1,3,1,0,0.0,neutral or dissatisfied +8879,84788,Male,Loyal Customer,50,Business travel,Business,2265,3,3,3,3,2,5,4,1,1,2,1,4,1,4,1,0.0,satisfied +8880,109365,Male,Loyal Customer,35,Business travel,Business,2353,1,1,5,1,3,3,4,1,1,1,1,4,1,4,101,72.0,neutral or dissatisfied +8881,964,Female,Loyal Customer,44,Business travel,Business,3308,1,1,1,1,1,4,4,3,3,3,1,3,3,4,0,0.0,neutral or dissatisfied +8882,69652,Male,Loyal Customer,29,Business travel,Business,2601,1,1,1,1,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +8883,98526,Male,Loyal Customer,10,Personal Travel,Eco,668,4,4,4,3,1,4,1,1,5,3,5,5,4,1,19,15.0,neutral or dissatisfied +8884,126568,Female,Loyal Customer,34,Business travel,Business,1558,2,2,1,2,3,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +8885,98066,Male,Loyal Customer,43,Business travel,Business,1449,3,3,4,3,4,4,4,3,2,4,5,4,3,4,148,145.0,satisfied +8886,3599,Male,Loyal Customer,41,Business travel,Eco,599,4,5,5,5,5,4,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +8887,71212,Female,Loyal Customer,51,Business travel,Business,733,3,3,3,3,5,5,4,2,2,2,2,4,2,4,122,114.0,satisfied +8888,44770,Male,Loyal Customer,42,Business travel,Eco,1250,5,2,2,2,5,5,5,5,4,3,2,1,5,5,43,14.0,satisfied +8889,88122,Male,Loyal Customer,18,Business travel,Business,515,5,5,5,5,4,4,4,4,4,2,4,3,5,4,55,44.0,satisfied +8890,55379,Male,Loyal Customer,76,Business travel,Eco,413,1,5,5,5,1,1,1,1,1,3,4,1,4,1,13,24.0,neutral or dissatisfied +8891,86773,Male,disloyal Customer,9,Business travel,Eco,484,2,1,2,3,5,2,2,5,3,3,3,3,2,5,25,16.0,neutral or dissatisfied +8892,91030,Male,Loyal Customer,53,Personal Travel,Eco,515,4,2,2,4,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +8893,48486,Female,Loyal Customer,49,Business travel,Business,848,5,5,2,5,1,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +8894,109341,Male,disloyal Customer,26,Business travel,Business,1072,1,1,1,3,1,1,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +8895,58277,Female,Loyal Customer,38,Business travel,Business,2946,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +8896,106265,Female,Loyal Customer,29,Business travel,Business,1500,3,3,3,3,4,4,4,4,4,3,4,5,5,4,10,17.0,satisfied +8897,108176,Female,Loyal Customer,13,Personal Travel,Eco,1105,1,1,1,4,1,1,1,1,1,5,3,3,3,1,0,7.0,neutral or dissatisfied +8898,96479,Female,Loyal Customer,39,Business travel,Business,444,3,4,3,3,3,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +8899,34403,Male,Loyal Customer,42,Business travel,Eco,728,5,5,3,5,5,5,5,5,2,4,1,5,1,5,0,0.0,satisfied +8900,87148,Female,Loyal Customer,9,Personal Travel,Eco Plus,594,3,3,3,3,3,3,3,3,3,2,3,4,4,3,8,0.0,neutral or dissatisfied +8901,4186,Female,Loyal Customer,62,Business travel,Business,2990,5,5,5,5,4,4,5,5,5,4,5,3,5,3,41,29.0,satisfied +8902,25940,Female,Loyal Customer,36,Business travel,Eco Plus,594,4,2,2,2,4,4,4,4,5,1,3,3,2,4,31,7.0,satisfied +8903,129238,Male,disloyal Customer,25,Business travel,Business,1235,0,0,0,1,4,0,4,4,5,2,4,4,4,4,1,0.0,satisfied +8904,77878,Female,Loyal Customer,39,Business travel,Business,700,1,1,1,1,5,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +8905,128626,Male,disloyal Customer,21,Business travel,Business,679,4,0,4,4,5,4,5,5,4,3,5,3,5,5,0,0.0,satisfied +8906,110984,Male,Loyal Customer,32,Business travel,Business,268,3,3,3,3,5,5,5,5,5,5,4,5,4,5,25,14.0,satisfied +8907,2496,Female,Loyal Customer,8,Personal Travel,Eco,1379,3,1,3,2,5,3,5,5,3,5,2,1,1,5,7,11.0,neutral or dissatisfied +8908,101839,Female,Loyal Customer,22,Personal Travel,Eco,1521,2,3,2,4,4,2,4,4,2,5,3,1,4,4,27,16.0,neutral or dissatisfied +8909,115919,Female,Loyal Customer,22,Business travel,Eco,325,2,2,2,2,2,3,2,2,2,2,3,4,3,2,14,8.0,neutral or dissatisfied +8910,33913,Male,Loyal Customer,45,Business travel,Business,3304,4,4,5,4,2,3,2,5,5,5,5,4,5,2,0,0.0,satisfied +8911,114486,Male,Loyal Customer,53,Business travel,Business,3546,2,5,5,5,5,3,3,2,2,2,2,4,2,1,6,8.0,neutral or dissatisfied +8912,16624,Male,Loyal Customer,35,Personal Travel,Eco,1008,2,5,2,1,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +8913,101953,Male,Loyal Customer,59,Business travel,Business,3762,1,1,1,1,4,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +8914,56164,Female,Loyal Customer,18,Business travel,Business,1400,2,5,5,5,2,2,2,2,2,1,4,4,4,2,3,8.0,neutral or dissatisfied +8915,44585,Female,Loyal Customer,29,Personal Travel,Eco,157,2,5,0,4,4,0,4,4,3,5,4,5,5,4,13,18.0,neutral or dissatisfied +8916,57412,Female,Loyal Customer,17,Business travel,Business,3340,2,5,5,5,2,2,2,2,2,3,4,2,3,2,2,0.0,neutral or dissatisfied +8917,49461,Female,Loyal Customer,55,Business travel,Business,373,1,1,1,1,5,3,5,5,5,5,5,1,5,5,4,7.0,satisfied +8918,67839,Male,Loyal Customer,21,Personal Travel,Eco,1242,2,4,3,4,3,3,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +8919,70256,Female,Loyal Customer,30,Personal Travel,Eco,1592,1,4,1,2,3,1,1,3,4,4,4,5,4,3,2,5.0,neutral or dissatisfied +8920,1468,Male,Loyal Customer,34,Personal Travel,Eco,772,1,3,1,4,1,1,1,1,2,5,5,1,4,1,10,2.0,neutral or dissatisfied +8921,115638,Male,Loyal Customer,41,Business travel,Eco,325,2,5,5,5,2,3,3,4,5,2,3,3,2,3,132,118.0,neutral or dissatisfied +8922,103309,Female,Loyal Customer,51,Business travel,Business,1371,3,5,2,2,4,4,4,3,3,3,3,1,3,4,0,5.0,neutral or dissatisfied +8923,1511,Female,disloyal Customer,21,Business travel,Business,862,0,0,0,1,2,0,2,2,3,5,4,5,5,2,0,0.0,satisfied +8924,109396,Male,Loyal Customer,30,Personal Travel,Eco,1046,4,5,4,1,5,4,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +8925,97238,Female,Loyal Customer,41,Business travel,Business,1585,5,5,5,5,5,4,4,4,4,4,4,4,4,4,30,30.0,satisfied +8926,26829,Female,Loyal Customer,59,Business travel,Eco,224,4,4,4,4,3,4,2,4,4,4,4,2,4,3,0,0.0,satisfied +8927,86979,Female,disloyal Customer,35,Business travel,Eco,907,3,3,3,4,1,3,1,1,1,2,4,4,3,1,30,54.0,neutral or dissatisfied +8928,127652,Male,Loyal Customer,42,Business travel,Business,1773,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +8929,99994,Female,Loyal Customer,37,Business travel,Business,2720,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,9.0,satisfied +8930,9865,Female,disloyal Customer,27,Business travel,Business,531,2,2,2,1,1,2,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +8931,71222,Male,Loyal Customer,28,Business travel,Eco,733,3,1,1,1,3,3,3,3,4,1,2,4,2,3,15,33.0,neutral or dissatisfied +8932,68728,Female,Loyal Customer,75,Business travel,Eco Plus,175,4,2,2,2,5,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +8933,22523,Male,Loyal Customer,60,Business travel,Eco Plus,238,2,1,1,1,2,2,2,2,3,5,2,3,3,2,13,,neutral or dissatisfied +8934,13969,Female,Loyal Customer,33,Personal Travel,Eco,192,2,4,2,3,2,2,2,2,4,2,5,5,5,2,0,1.0,neutral or dissatisfied +8935,107165,Male,Loyal Customer,28,Business travel,Business,2230,1,5,5,5,1,1,1,1,4,1,3,1,4,1,32,31.0,neutral or dissatisfied +8936,28194,Female,Loyal Customer,55,Personal Travel,Eco,859,2,5,2,5,3,4,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +8937,30334,Male,Loyal Customer,44,Business travel,Eco,391,3,4,4,4,3,3,3,3,2,5,2,2,4,3,6,0.0,satisfied +8938,89853,Female,Loyal Customer,32,Business travel,Business,1487,2,1,5,1,2,2,2,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +8939,37768,Male,Loyal Customer,37,Business travel,Eco Plus,1074,1,3,3,3,1,1,1,1,1,5,4,1,3,1,25,17.0,neutral or dissatisfied +8940,110158,Female,Loyal Customer,56,Personal Travel,Eco,979,4,4,4,1,2,4,4,5,5,4,5,4,5,5,12,3.0,satisfied +8941,129385,Female,Loyal Customer,22,Personal Travel,Eco,2565,1,4,1,1,5,1,5,5,4,1,5,2,3,5,0,0.0,neutral or dissatisfied +8942,1028,Male,disloyal Customer,22,Business travel,Eco,113,4,3,4,3,2,4,2,2,3,2,3,4,2,2,0,0.0,neutral or dissatisfied +8943,8188,Male,Loyal Customer,32,Business travel,Business,335,2,2,5,2,2,2,2,2,4,5,4,3,4,2,0,4.0,neutral or dissatisfied +8944,15943,Male,Loyal Customer,13,Personal Travel,Eco,528,2,4,2,4,2,2,2,3,3,5,4,2,3,2,153,134.0,neutral or dissatisfied +8945,18924,Female,Loyal Customer,34,Personal Travel,Eco,448,1,3,1,3,3,1,3,3,2,3,5,1,1,3,0,0.0,neutral or dissatisfied +8946,43443,Male,Loyal Customer,57,Business travel,Business,2409,4,4,4,4,2,2,3,4,4,4,4,5,4,3,39,28.0,satisfied +8947,111037,Female,disloyal Customer,65,Business travel,Eco,240,1,4,1,3,5,1,5,5,3,5,3,2,4,5,0,0.0,neutral or dissatisfied +8948,32567,Female,Loyal Customer,33,Business travel,Business,163,3,3,3,3,5,5,5,5,5,5,4,2,5,5,0,0.0,satisfied +8949,92910,Female,Loyal Customer,46,Business travel,Business,3286,0,4,0,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +8950,65613,Female,Loyal Customer,60,Personal Travel,Eco,237,2,3,0,3,3,3,3,5,5,0,5,4,5,3,9,4.0,neutral or dissatisfied +8951,105508,Female,Loyal Customer,41,Business travel,Business,2047,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +8952,3266,Male,Loyal Customer,29,Business travel,Business,3945,1,2,3,2,1,1,1,1,4,5,3,2,3,1,56,53.0,neutral or dissatisfied +8953,45805,Female,disloyal Customer,30,Business travel,Eco,391,2,3,1,2,5,1,5,5,1,2,3,2,2,5,0,0.0,neutral or dissatisfied +8954,23064,Female,Loyal Customer,28,Business travel,Business,820,1,3,3,3,1,1,1,1,4,3,3,1,3,1,8,3.0,neutral or dissatisfied +8955,57974,Male,Loyal Customer,45,Business travel,Business,2949,4,4,4,4,4,4,4,4,4,4,4,2,4,1,5,8.0,neutral or dissatisfied +8956,77934,Female,Loyal Customer,60,Business travel,Business,332,0,0,0,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +8957,53700,Male,Loyal Customer,25,Business travel,Business,3477,3,3,4,3,5,5,5,5,3,5,2,4,3,5,9,3.0,satisfied +8958,35452,Female,Loyal Customer,34,Personal Travel,Eco,1076,2,5,2,1,3,2,3,3,5,5,4,4,5,3,42,47.0,neutral or dissatisfied +8959,115689,Female,Loyal Customer,60,Business travel,Eco,308,4,2,2,2,3,3,2,4,4,4,4,4,4,2,8,4.0,neutral or dissatisfied +8960,60215,Female,Loyal Customer,58,Business travel,Business,1607,3,3,3,3,2,3,5,4,4,4,4,4,4,5,2,5.0,satisfied +8961,70189,Male,Loyal Customer,54,Business travel,Eco,258,2,4,4,4,2,2,2,2,3,2,2,4,2,2,84,97.0,neutral or dissatisfied +8962,102608,Female,Loyal Customer,20,Personal Travel,Eco Plus,236,3,4,3,3,3,3,3,3,5,2,5,5,5,3,0,4.0,neutral or dissatisfied +8963,68853,Male,Loyal Customer,50,Business travel,Business,1061,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,13.0,satisfied +8964,108129,Male,Loyal Customer,59,Business travel,Eco,990,3,3,3,3,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +8965,109813,Female,Loyal Customer,28,Business travel,Business,2578,5,5,5,5,5,5,5,5,4,2,5,3,5,5,0,0.0,satisfied +8966,82048,Female,Loyal Customer,66,Personal Travel,Eco,1535,3,5,3,1,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +8967,19103,Male,Loyal Customer,42,Business travel,Business,265,1,3,3,3,3,1,1,1,1,1,1,4,1,1,70,67.0,neutral or dissatisfied +8968,39001,Female,Loyal Customer,37,Business travel,Eco,230,5,2,2,2,5,5,5,5,4,2,1,2,5,5,68,110.0,satisfied +8969,33789,Female,Loyal Customer,53,Business travel,Eco,188,5,1,1,1,5,1,4,5,5,5,5,3,5,4,0,0.0,satisfied +8970,14285,Female,Loyal Customer,53,Business travel,Eco,395,4,3,3,3,1,3,1,4,4,4,4,1,4,3,0,0.0,satisfied +8971,123789,Female,disloyal Customer,25,Business travel,Business,544,2,0,2,5,1,2,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +8972,66149,Male,Loyal Customer,17,Personal Travel,Eco Plus,583,1,3,1,4,4,1,4,4,3,4,2,5,2,4,20,14.0,neutral or dissatisfied +8973,12870,Male,Loyal Customer,13,Personal Travel,Business,927,4,5,4,3,2,4,2,2,3,5,5,4,5,2,77,71.0,neutral or dissatisfied +8974,41491,Female,Loyal Customer,40,Business travel,Eco,1428,3,3,3,3,3,3,3,3,3,1,2,1,4,3,0,0.0,neutral or dissatisfied +8975,118026,Female,Loyal Customer,32,Personal Travel,Business,1044,3,5,3,4,4,3,4,4,3,3,5,1,4,4,46,24.0,neutral or dissatisfied +8976,99855,Female,Loyal Customer,39,Personal Travel,Eco,468,1,4,1,3,5,1,5,5,4,5,5,4,4,5,6,0.0,neutral or dissatisfied +8977,52964,Female,Loyal Customer,34,Business travel,Business,2306,3,3,3,3,2,5,5,4,4,4,4,3,4,3,4,0.0,satisfied +8978,63891,Male,Loyal Customer,38,Business travel,Eco,1192,4,3,3,3,4,4,4,4,2,5,3,2,3,4,13,8.0,neutral or dissatisfied +8979,8994,Female,disloyal Customer,26,Business travel,Eco,228,1,4,1,3,4,1,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +8980,95011,Male,Loyal Customer,51,Personal Travel,Eco,248,5,4,5,2,5,5,5,5,4,2,5,5,4,5,7,5.0,satisfied +8981,103378,Male,Loyal Customer,53,Business travel,Business,3581,3,3,3,3,3,4,5,5,5,5,5,4,5,4,7,4.0,satisfied +8982,11889,Male,Loyal Customer,48,Business travel,Business,3020,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +8983,100008,Male,Loyal Customer,38,Business travel,Eco,277,2,5,5,5,2,2,2,2,2,3,4,4,4,2,0,14.0,neutral or dissatisfied +8984,64564,Male,Loyal Customer,37,Business travel,Business,3493,0,0,0,3,4,5,5,5,5,5,5,4,5,4,19,24.0,satisfied +8985,15076,Female,disloyal Customer,34,Business travel,Eco,239,2,4,2,4,1,2,1,1,4,3,3,2,2,1,0,0.0,neutral or dissatisfied +8986,26474,Female,Loyal Customer,40,Personal Travel,Eco,787,2,4,2,3,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +8987,82512,Male,disloyal Customer,39,Business travel,Eco,1749,4,4,4,3,5,4,5,5,3,2,3,1,3,5,0,0.0,neutral or dissatisfied +8988,112048,Male,Loyal Customer,48,Personal Travel,Eco,1015,4,2,4,3,3,4,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +8989,120001,Female,Loyal Customer,53,Business travel,Business,328,0,0,0,3,3,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +8990,88060,Female,Loyal Customer,57,Business travel,Business,2739,3,3,3,3,4,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +8991,70800,Female,Loyal Customer,29,Personal Travel,Eco,328,2,5,2,1,5,2,5,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +8992,65791,Male,Loyal Customer,38,Business travel,Business,1389,1,1,1,1,3,5,5,4,4,4,4,5,4,5,3,0.0,satisfied +8993,13835,Male,Loyal Customer,60,Business travel,Eco,594,2,1,1,1,2,2,2,2,1,1,2,4,1,2,8,2.0,satisfied +8994,120501,Male,Loyal Customer,57,Business travel,Business,2005,3,3,3,3,2,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +8995,10948,Female,disloyal Customer,20,Business travel,Eco,140,3,1,3,4,5,3,5,5,3,1,4,1,3,5,25,17.0,neutral or dissatisfied +8996,97472,Male,Loyal Customer,68,Business travel,Eco,670,2,5,5,5,2,2,2,2,2,1,2,4,3,2,0,0.0,neutral or dissatisfied +8997,110153,Female,Loyal Customer,41,Business travel,Business,656,2,5,5,5,3,3,3,2,2,2,2,2,2,4,0,6.0,neutral or dissatisfied +8998,95074,Female,Loyal Customer,34,Personal Travel,Eco,148,2,5,2,1,4,2,1,4,3,5,4,4,4,4,30,34.0,neutral or dissatisfied +8999,20462,Female,disloyal Customer,35,Business travel,Eco,84,4,1,4,2,5,4,5,5,3,4,2,1,2,5,0,0.0,neutral or dissatisfied +9000,40981,Female,Loyal Customer,37,Business travel,Business,3137,1,2,1,1,2,2,2,5,5,5,5,5,5,5,0,0.0,satisfied +9001,40887,Female,Loyal Customer,47,Personal Travel,Eco,584,2,5,2,3,2,4,5,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +9002,60011,Male,Loyal Customer,68,Personal Travel,Eco,1085,3,4,2,3,4,2,4,4,3,5,4,3,5,4,37,25.0,neutral or dissatisfied +9003,126978,Female,Loyal Customer,48,Business travel,Business,1866,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +9004,29447,Male,Loyal Customer,40,Business travel,Business,1849,3,3,3,3,3,1,2,5,5,5,5,1,5,3,0,0.0,satisfied +9005,129319,Female,Loyal Customer,52,Business travel,Business,2586,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +9006,108185,Female,Loyal Customer,7,Personal Travel,Eco,849,2,5,2,3,2,2,2,2,3,4,5,4,5,2,20,13.0,neutral or dissatisfied +9007,83744,Female,Loyal Customer,32,Business travel,Eco,1183,4,5,5,5,4,4,4,4,2,2,3,1,4,4,3,0.0,neutral or dissatisfied +9008,46385,Female,Loyal Customer,23,Business travel,Business,1013,5,5,5,5,4,4,4,4,2,5,2,4,2,4,0,0.0,satisfied +9009,122199,Male,disloyal Customer,27,Business travel,Business,544,4,4,4,5,2,4,2,2,4,5,5,5,5,2,0,0.0,satisfied +9010,73567,Male,disloyal Customer,23,Business travel,Eco,192,1,1,1,3,4,1,4,4,1,1,4,3,3,4,4,1.0,neutral or dissatisfied +9011,43006,Male,disloyal Customer,48,Business travel,Eco,192,2,5,2,4,2,2,2,2,1,1,1,2,2,2,0,0.0,neutral or dissatisfied +9012,116432,Male,Loyal Customer,58,Personal Travel,Eco,372,3,1,3,3,3,3,3,3,4,5,3,4,4,3,27,22.0,neutral or dissatisfied +9013,64054,Female,disloyal Customer,29,Business travel,Eco,919,3,3,3,3,1,3,1,1,3,5,4,4,4,1,0,11.0,neutral or dissatisfied +9014,102531,Male,Loyal Customer,22,Personal Travel,Eco,414,3,2,3,4,1,3,3,1,3,1,4,3,4,1,2,0.0,neutral or dissatisfied +9015,51985,Female,Loyal Customer,40,Business travel,Eco Plus,347,4,4,4,4,4,4,4,4,4,5,2,3,1,4,0,0.0,satisfied +9016,36665,Female,Loyal Customer,32,Personal Travel,Eco,1220,3,0,3,1,3,3,1,3,4,5,5,5,5,3,0,22.0,neutral or dissatisfied +9017,23483,Male,Loyal Customer,41,Personal Travel,Eco,516,2,4,2,5,4,2,4,4,5,2,4,4,3,4,0,0.0,neutral or dissatisfied +9018,62268,Male,Loyal Customer,10,Personal Travel,Eco Plus,2565,3,5,3,4,3,3,3,3,3,5,5,5,3,3,35,39.0,neutral or dissatisfied +9019,38216,Male,disloyal Customer,30,Business travel,Eco Plus,1249,3,3,3,4,1,3,2,1,3,3,4,3,4,1,29,44.0,neutral or dissatisfied +9020,106608,Male,Loyal Customer,31,Business travel,Business,589,3,4,4,4,3,3,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +9021,21551,Male,Loyal Customer,18,Personal Travel,Eco,331,4,3,4,2,4,4,4,4,3,4,5,3,3,4,0,0.0,neutral or dissatisfied +9022,109172,Female,Loyal Customer,49,Business travel,Business,2550,4,4,4,4,1,4,3,4,4,4,4,2,4,1,27,17.0,neutral or dissatisfied +9023,25674,Female,Loyal Customer,58,Personal Travel,Eco,761,4,1,3,4,5,4,4,5,5,3,5,3,5,4,7,0.0,satisfied +9024,116362,Female,Loyal Customer,21,Personal Travel,Eco,308,3,4,3,1,3,3,3,3,4,3,4,5,5,3,0,1.0,neutral or dissatisfied +9025,61344,Female,disloyal Customer,23,Business travel,Business,602,5,0,5,2,2,5,1,2,3,3,4,4,4,2,0,0.0,satisfied +9026,118051,Male,disloyal Customer,22,Business travel,Eco,1262,3,3,3,2,4,3,4,4,1,5,3,2,2,4,30,17.0,neutral or dissatisfied +9027,80134,Female,disloyal Customer,21,Business travel,Eco,1306,3,3,3,5,3,3,3,3,4,2,5,5,5,3,7,0.0,neutral or dissatisfied +9028,106855,Female,Loyal Customer,46,Business travel,Business,2031,3,3,3,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +9029,33489,Male,disloyal Customer,33,Personal Travel,Eco,2496,3,2,3,4,3,3,3,3,1,4,4,3,4,3,65,72.0,neutral or dissatisfied +9030,114659,Female,Loyal Customer,50,Business travel,Business,1703,0,0,0,2,5,5,4,2,2,2,5,4,2,4,5,0.0,satisfied +9031,128283,Female,Loyal Customer,31,Business travel,Business,1946,1,1,3,1,5,5,5,5,3,3,4,3,4,5,0,0.0,satisfied +9032,82336,Female,disloyal Customer,41,Business travel,Business,1930,4,4,4,1,1,4,1,1,3,3,5,4,5,1,0,3.0,neutral or dissatisfied +9033,56698,Male,Loyal Customer,40,Personal Travel,Eco,1068,1,5,1,2,3,1,3,3,4,4,5,4,4,3,13,26.0,neutral or dissatisfied +9034,47399,Female,Loyal Customer,25,Business travel,Eco,541,5,1,1,1,5,5,4,5,3,2,1,2,4,5,0,0.0,satisfied +9035,11967,Female,Loyal Customer,23,Business travel,Business,643,2,2,2,2,4,4,4,4,3,2,4,4,5,4,8,0.0,satisfied +9036,104953,Male,disloyal Customer,15,Business travel,Business,337,2,1,2,2,2,2,5,2,4,5,3,4,2,2,3,8.0,neutral or dissatisfied +9037,70169,Female,disloyal Customer,22,Business travel,Eco,150,4,3,4,4,5,4,5,5,1,3,3,4,4,5,6,0.0,neutral or dissatisfied +9038,15184,Male,Loyal Customer,54,Business travel,Eco,461,3,5,5,5,3,3,3,3,3,5,2,2,5,3,0,0.0,satisfied +9039,73954,Female,disloyal Customer,55,Business travel,Eco,767,2,2,2,1,1,2,5,1,3,1,1,3,3,1,0,0.0,neutral or dissatisfied +9040,113104,Female,Loyal Customer,65,Personal Travel,Eco,479,2,4,2,4,3,4,4,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +9041,47506,Male,disloyal Customer,64,Personal Travel,Eco,599,3,0,3,5,3,3,3,3,3,2,4,3,4,3,0,7.0,neutral or dissatisfied +9042,112915,Female,Loyal Customer,49,Business travel,Business,3839,3,3,3,3,4,3,5,3,3,3,3,1,3,1,18,5.0,satisfied +9043,27655,Male,Loyal Customer,50,Business travel,Business,3594,2,2,2,2,1,2,1,2,2,2,2,3,2,3,10,0.0,neutral or dissatisfied +9044,40439,Female,Loyal Customer,50,Business travel,Business,1772,4,3,3,3,2,3,4,3,3,3,4,4,3,4,66,62.0,neutral or dissatisfied +9045,42697,Male,Loyal Customer,46,Personal Travel,Eco,627,3,5,3,1,2,3,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +9046,31597,Male,Loyal Customer,54,Business travel,Business,2813,4,1,1,1,2,3,3,2,2,2,4,3,2,3,0,0.0,neutral or dissatisfied +9047,44216,Male,Loyal Customer,38,Business travel,Business,359,3,3,3,3,1,5,5,4,4,4,4,2,4,4,0,1.0,satisfied +9048,34174,Male,Loyal Customer,52,Business travel,Eco,1063,2,1,1,1,2,2,2,2,1,1,3,1,3,2,24,18.0,neutral or dissatisfied +9049,3107,Female,Loyal Customer,60,Business travel,Eco Plus,413,3,3,3,3,3,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +9050,62241,Male,Loyal Customer,69,Personal Travel,Eco,2454,3,5,3,3,4,3,4,4,5,3,3,4,5,4,0,0.0,neutral or dissatisfied +9051,40813,Female,disloyal Customer,22,Business travel,Business,558,5,0,5,5,5,5,4,5,2,5,1,4,2,5,10,9.0,satisfied +9052,3065,Male,Loyal Customer,56,Business travel,Business,594,5,5,5,5,5,5,5,4,4,5,5,5,3,5,130,138.0,satisfied +9053,59127,Male,Loyal Customer,69,Personal Travel,Eco,1744,5,5,5,4,5,5,5,5,3,2,5,4,5,5,8,0.0,satisfied +9054,47728,Female,Loyal Customer,20,Business travel,Business,1590,3,4,4,4,3,3,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +9055,19118,Female,disloyal Customer,22,Business travel,Business,323,3,4,3,3,4,3,4,4,1,4,3,3,3,4,0,0.0,neutral or dissatisfied +9056,56846,Female,Loyal Customer,41,Business travel,Business,2425,1,1,1,1,4,4,4,3,5,3,5,4,3,4,15,0.0,satisfied +9057,30589,Female,Loyal Customer,16,Personal Travel,Eco,628,3,4,3,3,5,3,3,5,4,5,4,3,4,5,27,25.0,neutral or dissatisfied +9058,102723,Female,Loyal Customer,36,Personal Travel,Eco,365,1,4,1,4,4,1,3,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +9059,100362,Male,Loyal Customer,31,Personal Travel,Eco,1101,1,5,1,3,2,1,2,2,2,3,4,5,5,2,0,7.0,neutral or dissatisfied +9060,19598,Male,Loyal Customer,51,Personal Travel,Eco,160,1,5,1,2,4,1,4,4,3,4,5,4,5,4,0,,neutral or dissatisfied +9061,108297,Male,Loyal Customer,38,Business travel,Business,1750,1,1,1,1,4,4,5,4,4,4,4,4,4,5,3,0.0,satisfied +9062,74463,Male,Loyal Customer,50,Business travel,Eco,1464,3,2,5,2,3,3,3,3,3,2,3,2,2,3,25,28.0,neutral or dissatisfied +9063,16132,Male,Loyal Customer,44,Personal Travel,Eco,725,1,5,1,3,4,1,4,4,1,3,2,4,3,4,0,5.0,neutral or dissatisfied +9064,77499,Female,Loyal Customer,65,Personal Travel,Eco,989,1,4,1,4,5,5,4,2,2,1,5,4,2,4,0,0.0,neutral or dissatisfied +9065,70568,Female,disloyal Customer,37,Business travel,Eco,858,4,3,3,4,3,3,3,3,2,2,1,4,1,3,0,3.0,satisfied +9066,93027,Male,Loyal Customer,31,Personal Travel,Eco Plus,1524,1,4,1,2,5,1,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +9067,72823,Male,disloyal Customer,22,Business travel,Business,1013,0,0,0,2,3,0,2,3,4,3,5,4,4,3,0,0.0,satisfied +9068,28783,Female,Loyal Customer,52,Business travel,Business,1050,3,3,3,3,2,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +9069,81258,Female,Loyal Customer,44,Business travel,Business,3813,2,2,5,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +9070,111217,Male,Loyal Customer,29,Business travel,Business,1703,4,3,3,3,4,3,4,4,3,1,2,4,4,4,0,19.0,neutral or dissatisfied +9071,105767,Male,Loyal Customer,59,Business travel,Business,442,5,5,5,5,2,2,1,4,4,4,4,2,4,3,8,0.0,satisfied +9072,82981,Male,Loyal Customer,46,Business travel,Business,2555,3,3,3,3,3,4,4,4,4,4,4,4,4,5,4,69.0,satisfied +9073,76124,Male,disloyal Customer,42,Business travel,Business,689,1,0,0,2,1,1,5,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +9074,127909,Female,Loyal Customer,19,Personal Travel,Eco,1671,2,3,2,4,5,2,5,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +9075,57306,Male,Loyal Customer,13,Personal Travel,Business,414,4,5,4,1,1,4,1,1,5,5,1,4,2,1,0,0.0,neutral or dissatisfied +9076,17178,Male,Loyal Customer,36,Business travel,Business,3169,3,2,2,2,2,4,3,3,3,3,3,3,3,1,0,17.0,neutral or dissatisfied +9077,46647,Female,Loyal Customer,40,Business travel,Business,125,0,5,0,4,2,1,4,4,4,3,3,2,4,4,0,0.0,satisfied +9078,86737,Female,disloyal Customer,37,Business travel,Business,821,3,3,3,2,5,3,4,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +9079,119386,Male,Loyal Customer,53,Business travel,Business,2712,2,2,2,2,3,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +9080,47404,Male,Loyal Customer,45,Business travel,Eco,584,1,1,1,1,1,1,1,1,1,5,4,4,4,1,0,0.0,neutral or dissatisfied +9081,78859,Male,Loyal Customer,52,Personal Travel,Eco Plus,447,0,5,0,1,4,0,4,4,4,3,5,5,4,4,0,0.0,satisfied +9082,57104,Female,Loyal Customer,43,Business travel,Eco,1222,3,2,2,2,2,2,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +9083,65085,Male,Loyal Customer,48,Personal Travel,Eco,282,4,1,4,4,5,4,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +9084,84444,Male,Loyal Customer,28,Personal Travel,Eco Plus,591,2,2,2,3,1,2,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +9085,100762,Male,Loyal Customer,35,Business travel,Business,1504,5,5,5,5,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +9086,52860,Female,Loyal Customer,48,Business travel,Business,3337,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +9087,123339,Male,Loyal Customer,40,Personal Travel,Eco Plus,507,3,4,5,3,5,5,5,5,2,3,1,1,2,5,44,24.0,neutral or dissatisfied +9088,42522,Male,Loyal Customer,56,Personal Travel,Eco,1187,3,4,3,3,5,3,5,5,2,5,3,4,4,5,0,0.0,neutral or dissatisfied +9089,73121,Female,Loyal Customer,43,Personal Travel,Eco,2174,2,0,2,5,3,4,5,2,2,2,2,4,2,5,0,17.0,neutral or dissatisfied +9090,103061,Male,disloyal Customer,22,Business travel,Eco,460,2,4,2,3,4,2,5,4,2,2,3,4,4,4,51,37.0,neutral or dissatisfied +9091,121325,Male,Loyal Customer,33,Personal Travel,Eco,1009,4,4,4,1,1,4,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +9092,99792,Male,Loyal Customer,31,Business travel,Business,2469,1,1,4,1,5,5,5,5,5,2,4,5,5,5,0,0.0,satisfied +9093,97071,Female,disloyal Customer,49,Business travel,Business,1211,5,5,5,1,3,5,4,3,4,3,5,3,4,3,4,0.0,satisfied +9094,64520,Male,Loyal Customer,58,Personal Travel,Business,247,3,5,3,3,5,5,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +9095,61644,Male,Loyal Customer,40,Business travel,Business,1346,5,5,5,5,3,5,4,5,5,5,5,4,5,4,10,0.0,satisfied +9096,12839,Male,Loyal Customer,60,Personal Travel,Eco,1041,5,5,5,3,3,5,3,3,5,2,5,3,5,3,0,0.0,satisfied +9097,128715,Male,Loyal Customer,23,Business travel,Business,1464,4,4,4,4,2,2,2,2,3,4,4,3,4,2,3,0.0,satisfied +9098,65186,Male,Loyal Customer,18,Personal Travel,Eco,247,2,4,2,4,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +9099,127018,Male,Loyal Customer,36,Business travel,Business,1885,4,3,3,3,2,2,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +9100,99194,Female,Loyal Customer,66,Business travel,Eco Plus,351,2,1,1,1,4,2,1,2,2,2,2,2,2,1,41,28.0,neutral or dissatisfied +9101,20829,Female,disloyal Customer,32,Business travel,Eco,457,3,1,2,3,2,2,4,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +9102,25913,Female,disloyal Customer,25,Business travel,Eco,594,2,0,2,3,1,2,1,1,3,1,5,2,2,1,11,10.0,neutral or dissatisfied +9103,1493,Female,disloyal Customer,15,Business travel,Eco,737,4,4,4,3,3,4,3,3,3,2,5,5,5,3,0,0.0,satisfied +9104,32437,Male,disloyal Customer,20,Business travel,Eco,163,2,3,2,4,5,2,5,5,3,5,2,1,3,5,0,0.0,neutral or dissatisfied +9105,101496,Female,Loyal Customer,50,Business travel,Business,3987,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +9106,108329,Male,Loyal Customer,58,Business travel,Eco,1790,2,4,5,4,2,2,2,2,1,5,2,3,3,2,6,10.0,neutral or dissatisfied +9107,32246,Female,Loyal Customer,52,Business travel,Business,2488,0,3,0,4,5,1,1,3,3,3,3,2,3,1,7,3.0,satisfied +9108,82831,Female,Loyal Customer,44,Business travel,Business,3399,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,14.0,satisfied +9109,126194,Male,Loyal Customer,33,Business travel,Business,2574,2,2,2,2,2,2,2,2,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +9110,61501,Female,Loyal Customer,45,Business travel,Eco,788,2,3,3,3,5,2,3,2,2,2,2,4,2,5,7,0.0,satisfied +9111,79214,Female,Loyal Customer,15,Personal Travel,Eco,1990,1,1,1,3,3,1,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +9112,55319,Female,disloyal Customer,23,Business travel,Business,1117,1,3,1,4,3,1,3,3,3,5,3,2,4,3,20,11.0,neutral or dissatisfied +9113,72401,Female,Loyal Customer,46,Business travel,Business,1857,1,1,1,1,2,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +9114,6227,Male,Loyal Customer,15,Business travel,Business,1582,1,1,1,1,5,5,5,5,5,3,4,4,5,5,0,1.0,satisfied +9115,44090,Male,Loyal Customer,12,Personal Travel,Business,473,4,3,4,3,2,4,2,2,1,1,3,1,3,2,0,0.0,satisfied +9116,72254,Male,Loyal Customer,32,Business travel,Business,919,4,4,4,4,4,4,4,4,3,2,5,3,5,4,5,0.0,satisfied +9117,16894,Male,Loyal Customer,31,Business travel,Eco,708,5,5,5,5,5,5,5,5,1,2,1,3,2,5,24,32.0,satisfied +9118,85890,Female,Loyal Customer,25,Personal Travel,Eco,2172,3,4,3,3,3,3,3,3,5,4,5,3,5,3,0,2.0,neutral or dissatisfied +9119,34941,Female,Loyal Customer,42,Personal Travel,Eco,187,3,4,3,2,2,4,4,1,1,3,1,4,1,4,21,32.0,neutral or dissatisfied +9120,121078,Male,Loyal Customer,35,Personal Travel,Eco Plus,951,3,4,4,4,4,4,4,4,4,5,3,2,4,4,0,21.0,neutral or dissatisfied +9121,91133,Female,Loyal Customer,25,Personal Travel,Eco,406,2,4,2,4,5,2,5,5,3,3,5,3,4,5,4,0.0,neutral or dissatisfied +9122,8594,Male,Loyal Customer,57,Personal Travel,Eco,109,3,5,3,4,4,3,4,4,1,3,5,2,1,4,0,1.0,neutral or dissatisfied +9123,62764,Male,Loyal Customer,41,Business travel,Business,2367,3,3,1,3,5,4,4,5,5,5,5,4,5,5,2,4.0,satisfied +9124,124430,Female,Loyal Customer,28,Personal Travel,Eco,1262,2,4,2,4,4,2,4,4,3,5,3,4,4,4,0,2.0,neutral or dissatisfied +9125,61597,Female,disloyal Customer,36,Business travel,Business,1635,4,4,4,3,4,4,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +9126,45381,Female,Loyal Customer,30,Business travel,Eco Plus,461,0,0,0,3,5,0,5,5,4,2,3,2,2,5,0,0.0,satisfied +9127,6553,Female,Loyal Customer,51,Business travel,Business,3091,4,4,4,4,4,5,4,4,4,4,4,5,4,3,11,8.0,satisfied +9128,78248,Male,Loyal Customer,37,Business travel,Eco Plus,259,4,4,4,4,4,4,4,4,2,4,3,2,4,4,24,26.0,neutral or dissatisfied +9129,45,Male,Loyal Customer,56,Business travel,Business,173,0,5,0,3,2,5,4,4,4,3,3,4,4,5,30,14.0,satisfied +9130,119069,Male,Loyal Customer,22,Personal Travel,Business,1107,4,4,3,4,4,3,4,4,2,1,2,1,4,4,0,0.0,satisfied +9131,108168,Male,Loyal Customer,47,Personal Travel,Eco,1166,4,5,4,5,4,4,4,4,5,3,3,5,5,4,0,0.0,neutral or dissatisfied +9132,45623,Male,disloyal Customer,61,Business travel,Eco,260,1,1,1,2,3,1,3,3,3,2,2,3,3,3,0,7.0,neutral or dissatisfied +9133,82751,Male,Loyal Customer,36,Business travel,Business,2624,2,5,5,5,2,3,2,2,2,2,2,1,2,1,7,7.0,neutral or dissatisfied +9134,112893,Male,disloyal Customer,21,Business travel,Eco,1390,1,1,1,3,2,1,4,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +9135,64712,Female,Loyal Customer,45,Business travel,Business,190,4,4,5,4,5,4,5,4,4,4,5,5,4,4,0,0.0,satisfied +9136,55832,Male,disloyal Customer,24,Business travel,Eco,1416,1,1,1,3,5,1,5,5,4,3,3,2,3,5,20,21.0,neutral or dissatisfied +9137,122822,Male,Loyal Customer,8,Personal Travel,Eco,599,3,4,3,4,3,3,3,3,2,2,3,2,4,3,5,1.0,neutral or dissatisfied +9138,2933,Female,Loyal Customer,45,Personal Travel,Eco,859,1,5,1,4,4,5,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +9139,101262,Male,Loyal Customer,70,Business travel,Business,2176,3,1,1,1,5,2,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +9140,126744,Female,Loyal Customer,34,Personal Travel,Eco,2402,0,0,0,4,2,0,2,2,3,2,5,2,5,2,0,0.0,satisfied +9141,35850,Female,disloyal Customer,27,Business travel,Eco,1065,4,4,4,3,5,4,5,5,3,4,3,1,4,5,31,33.0,neutral or dissatisfied +9142,129759,Female,disloyal Customer,19,Business travel,Eco,337,2,0,1,2,3,1,3,3,4,3,3,1,5,3,0,0.0,neutral or dissatisfied +9143,55365,Female,Loyal Customer,57,Business travel,Business,678,3,3,3,3,2,5,5,4,4,4,4,5,4,3,4,0.0,satisfied +9144,22755,Male,Loyal Customer,38,Business travel,Eco,170,5,3,3,3,5,5,5,5,2,3,2,4,5,5,0,0.0,satisfied +9145,72339,Male,disloyal Customer,27,Business travel,Business,1121,4,4,4,3,2,4,2,2,3,2,4,2,4,2,31,14.0,neutral or dissatisfied +9146,89333,Male,Loyal Customer,22,Business travel,Business,1587,1,1,5,1,4,4,4,4,5,3,3,3,4,4,0,0.0,satisfied +9147,86313,Male,Loyal Customer,41,Business travel,Eco Plus,226,4,3,3,3,4,4,4,4,1,2,5,2,3,4,0,5.0,satisfied +9148,38458,Female,Loyal Customer,50,Business travel,Eco,826,4,3,5,3,3,2,2,4,4,4,4,5,4,5,0,0.0,satisfied +9149,36477,Male,Loyal Customer,49,Business travel,Business,3433,4,2,4,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +9150,23636,Male,Loyal Customer,32,Personal Travel,Eco,911,3,2,3,2,5,3,5,5,3,3,1,1,2,5,0,0.0,neutral or dissatisfied +9151,209,Female,Loyal Customer,69,Business travel,Business,290,2,2,3,2,1,4,2,4,4,4,4,5,4,5,0,0.0,satisfied +9152,37321,Female,disloyal Customer,22,Business travel,Eco,944,5,5,5,1,5,5,5,5,4,1,5,2,5,5,11,0.0,satisfied +9153,26338,Female,Loyal Customer,41,Business travel,Business,873,3,3,3,3,5,2,2,3,3,3,3,1,3,4,5,7.0,neutral or dissatisfied +9154,41411,Male,Loyal Customer,15,Personal Travel,Eco,809,3,4,3,2,1,3,1,1,1,3,3,3,3,1,5,0.0,neutral or dissatisfied +9155,5324,Male,disloyal Customer,38,Business travel,Business,812,4,4,4,3,2,4,2,2,3,2,4,4,4,2,19,21.0,satisfied +9156,4983,Male,Loyal Customer,50,Business travel,Business,502,3,3,3,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +9157,125649,Female,Loyal Customer,57,Business travel,Business,3893,5,5,5,5,5,4,4,4,4,4,4,5,4,5,58,64.0,satisfied +9158,78784,Female,Loyal Customer,66,Business travel,Eco,432,1,1,1,1,5,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +9159,61059,Male,Loyal Customer,36,Business travel,Business,1506,2,4,4,4,3,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +9160,105490,Male,Loyal Customer,47,Business travel,Business,516,3,3,3,3,2,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +9161,98090,Male,Loyal Customer,40,Business travel,Business,445,4,4,4,4,1,4,5,4,4,4,4,1,4,2,0,0.0,satisfied +9162,25079,Female,Loyal Customer,80,Business travel,Eco,557,1,2,2,2,4,3,4,1,1,1,1,1,1,4,43,27.0,neutral or dissatisfied +9163,122662,Female,Loyal Customer,48,Business travel,Business,2664,1,1,1,1,3,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +9164,28394,Female,Loyal Customer,32,Business travel,Eco Plus,763,5,2,2,2,5,5,5,5,3,2,1,2,1,5,0,0.0,satisfied +9165,19934,Male,Loyal Customer,42,Personal Travel,Eco,343,1,5,2,5,5,2,5,5,4,3,4,5,5,5,13,12.0,neutral or dissatisfied +9166,7400,Male,disloyal Customer,32,Business travel,Business,522,4,4,4,3,1,4,1,1,5,5,5,5,5,1,5,0.0,neutral or dissatisfied +9167,97717,Female,disloyal Customer,32,Business travel,Business,942,2,2,2,2,5,2,5,5,4,2,4,4,5,5,7,0.0,neutral or dissatisfied +9168,58583,Male,disloyal Customer,45,Business travel,Business,334,2,2,2,1,5,2,5,5,3,3,5,4,5,5,40,25.0,neutral or dissatisfied +9169,92584,Male,Loyal Customer,36,Business travel,Eco Plus,419,2,5,5,5,2,2,2,2,1,2,1,3,1,2,0,0.0,satisfied +9170,86612,Female,Loyal Customer,46,Business travel,Business,3962,5,5,5,5,2,4,5,4,4,4,4,4,4,3,114,106.0,satisfied +9171,36482,Male,disloyal Customer,25,Business travel,Eco,1211,4,4,4,4,5,4,5,5,1,3,3,2,4,5,0,0.0,neutral or dissatisfied +9172,62840,Female,Loyal Customer,56,Business travel,Business,2615,5,5,5,5,4,4,4,4,4,5,5,4,3,4,0,0.0,satisfied +9173,70864,Female,Loyal Customer,39,Business travel,Business,3853,4,4,4,4,4,2,2,4,4,4,4,2,4,2,50,47.0,satisfied +9174,101,Male,Loyal Customer,44,Business travel,Business,2992,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +9175,112946,Female,Loyal Customer,43,Personal Travel,Eco,1211,1,1,0,2,5,3,2,3,3,0,4,1,3,2,0,0.0,neutral or dissatisfied +9176,23753,Female,Loyal Customer,44,Business travel,Eco,1048,2,2,2,2,3,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +9177,78061,Female,Loyal Customer,16,Personal Travel,Eco,332,4,1,4,2,4,4,4,4,1,1,2,3,2,4,0,0.0,neutral or dissatisfied +9178,102614,Female,Loyal Customer,70,Business travel,Business,1294,4,4,4,4,1,4,3,4,4,4,4,3,4,4,16,0.0,neutral or dissatisfied +9179,13628,Female,Loyal Customer,54,Business travel,Eco,1014,2,2,2,2,4,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +9180,64987,Female,Loyal Customer,30,Business travel,Business,247,5,5,5,5,4,4,4,4,3,1,2,4,2,4,0,0.0,satisfied +9181,12348,Male,Loyal Customer,32,Business travel,Eco,190,2,3,4,3,2,2,2,2,3,2,2,2,3,2,23,17.0,neutral or dissatisfied +9182,89953,Female,Loyal Customer,29,Personal Travel,Eco,1310,2,4,2,2,1,2,1,1,3,5,5,5,4,1,46,57.0,neutral or dissatisfied +9183,77691,Male,Loyal Customer,42,Business travel,Business,2721,5,5,5,5,3,4,4,1,1,2,1,4,1,4,0,0.0,satisfied +9184,19889,Female,Loyal Customer,41,Business travel,Business,2165,2,2,2,2,5,3,4,4,4,4,4,1,4,3,12,10.0,satisfied +9185,5700,Female,Loyal Customer,36,Personal Travel,Eco,147,4,4,0,4,2,0,2,2,1,5,1,4,3,2,0,3.0,satisfied +9186,92463,Female,disloyal Customer,36,Business travel,Business,1892,3,3,3,4,3,3,1,3,4,2,4,3,5,3,0,1.0,neutral or dissatisfied +9187,100153,Male,Loyal Customer,41,Business travel,Business,717,5,5,5,5,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +9188,82655,Male,Loyal Customer,47,Business travel,Business,2184,5,5,5,5,2,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +9189,76432,Male,disloyal Customer,35,Business travel,Business,405,2,1,1,1,5,1,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +9190,5778,Female,Loyal Customer,45,Business travel,Business,273,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +9191,38821,Female,Loyal Customer,51,Personal Travel,Eco,353,3,3,3,1,1,4,5,5,5,3,5,4,5,3,0,6.0,neutral or dissatisfied +9192,95397,Male,Loyal Customer,51,Personal Travel,Eco,239,3,4,3,4,4,3,4,4,4,2,4,4,5,4,1,0.0,neutral or dissatisfied +9193,111212,Male,Loyal Customer,23,Business travel,Business,1546,4,1,3,3,4,4,4,4,1,1,3,2,3,4,119,109.0,neutral or dissatisfied +9194,42841,Male,Loyal Customer,51,Business travel,Business,328,4,4,4,4,2,4,3,5,5,5,5,1,5,4,0,0.0,satisfied +9195,94371,Female,Loyal Customer,39,Business travel,Business,323,3,3,3,3,4,4,4,4,2,5,5,4,5,4,148,147.0,satisfied +9196,96250,Male,Loyal Customer,10,Personal Travel,Eco,460,3,5,3,1,3,3,3,3,1,3,4,4,2,3,6,0.0,neutral or dissatisfied +9197,117005,Female,Loyal Customer,48,Business travel,Business,3742,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +9198,33015,Male,Loyal Customer,13,Personal Travel,Eco,101,4,4,4,4,2,4,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +9199,28502,Female,Loyal Customer,28,Business travel,Business,2677,5,5,5,5,5,5,5,5,3,4,3,1,1,5,0,0.0,satisfied +9200,47876,Male,Loyal Customer,69,Business travel,Business,2558,2,5,5,5,5,2,2,2,2,2,2,4,2,3,85,80.0,neutral or dissatisfied +9201,56037,Male,Loyal Customer,19,Business travel,Business,2475,3,1,1,1,3,3,3,2,2,4,4,3,2,3,4,0.0,neutral or dissatisfied +9202,26568,Male,disloyal Customer,28,Business travel,Business,406,2,2,2,2,5,2,5,5,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +9203,33703,Male,Loyal Customer,50,Business travel,Eco,759,2,5,5,5,2,2,2,2,4,2,2,4,3,2,0,0.0,neutral or dissatisfied +9204,83474,Male,Loyal Customer,40,Business travel,Business,946,1,1,5,1,2,5,4,5,5,5,5,3,5,4,46,35.0,satisfied +9205,126889,Male,Loyal Customer,53,Personal Travel,Eco,2125,2,1,2,3,4,2,4,4,3,4,4,4,3,4,0,0.0,neutral or dissatisfied +9206,9173,Male,Loyal Customer,46,Business travel,Business,2736,3,3,3,3,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +9207,3421,Female,Loyal Customer,24,Personal Travel,Eco,240,4,5,0,4,2,0,2,2,4,2,5,3,5,2,3,0.0,neutral or dissatisfied +9208,83204,Male,Loyal Customer,59,Personal Travel,Eco,1123,4,5,4,5,2,4,2,2,3,3,3,5,5,2,22,19.0,neutral or dissatisfied +9209,126650,Female,Loyal Customer,58,Personal Travel,Eco,602,5,4,5,4,3,4,5,2,2,5,2,4,2,5,0,0.0,satisfied +9210,102863,Female,disloyal Customer,25,Business travel,Business,472,3,0,3,5,1,3,1,1,3,2,5,3,4,1,3,0.0,neutral or dissatisfied +9211,53267,Female,disloyal Customer,25,Business travel,Eco,811,0,0,0,4,2,0,2,2,2,2,1,5,5,2,0,5.0,satisfied +9212,83712,Female,Loyal Customer,39,Business travel,Business,577,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +9213,19950,Male,Loyal Customer,39,Personal Travel,Eco,315,3,5,4,3,2,4,2,2,3,3,5,3,2,2,9,6.0,neutral or dissatisfied +9214,87892,Male,disloyal Customer,26,Business travel,Business,271,3,4,3,4,5,3,5,5,4,2,5,3,5,5,4,4.0,neutral or dissatisfied +9215,118297,Female,Loyal Customer,28,Business travel,Business,2702,5,5,1,5,4,4,4,4,5,2,5,3,4,4,16,6.0,satisfied +9216,110452,Female,Loyal Customer,66,Personal Travel,Eco,842,2,4,1,4,3,4,4,5,5,1,5,5,5,4,34,39.0,neutral or dissatisfied +9217,45008,Male,disloyal Customer,20,Business travel,Eco,222,2,2,2,3,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +9218,26979,Male,Loyal Customer,31,Business travel,Business,2026,2,2,2,2,2,2,2,2,3,5,3,5,3,2,25,21.0,satisfied +9219,95234,Female,Loyal Customer,19,Personal Travel,Eco,239,3,4,3,1,5,3,5,5,5,1,5,5,5,5,34,35.0,neutral or dissatisfied +9220,103033,Male,Loyal Customer,32,Business travel,Business,3390,1,1,1,1,1,1,1,1,1,2,4,4,3,1,0,0.0,neutral or dissatisfied +9221,71898,Male,Loyal Customer,62,Personal Travel,Eco,1744,2,1,2,3,1,2,5,1,4,3,2,3,3,1,0,0.0,neutral or dissatisfied +9222,114997,Male,disloyal Customer,34,Business travel,Business,373,2,2,2,3,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +9223,117926,Male,Loyal Customer,35,Business travel,Business,2539,2,3,3,3,1,2,2,2,2,2,2,1,2,2,29,32.0,neutral or dissatisfied +9224,66582,Male,Loyal Customer,16,Business travel,Business,2655,3,3,3,3,2,2,2,2,5,5,5,4,4,2,0,50.0,satisfied +9225,59393,Female,Loyal Customer,7,Personal Travel,Eco,2486,2,5,2,2,3,2,3,3,2,5,4,1,2,3,23,17.0,neutral or dissatisfied +9226,54346,Female,Loyal Customer,20,Personal Travel,Eco Plus,1597,3,5,3,3,3,3,3,3,4,4,3,3,5,3,35,11.0,neutral or dissatisfied +9227,55309,Female,Loyal Customer,43,Business travel,Business,1325,4,3,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +9228,112934,Male,Loyal Customer,16,Personal Travel,Eco,1497,2,5,1,2,3,1,3,3,5,3,4,4,4,3,11,0.0,neutral or dissatisfied +9229,107155,Female,Loyal Customer,28,Business travel,Business,2048,3,3,3,3,4,4,4,4,3,3,5,5,5,4,21,13.0,satisfied +9230,66471,Female,Loyal Customer,59,Business travel,Business,447,5,5,5,5,4,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +9231,1374,Male,Loyal Customer,44,Business travel,Business,2401,1,1,1,1,5,4,4,4,4,4,4,3,4,4,2,2.0,satisfied +9232,89522,Female,Loyal Customer,61,Personal Travel,Business,1076,4,5,5,3,2,4,4,2,2,5,2,5,2,5,3,84.0,neutral or dissatisfied +9233,64711,Male,Loyal Customer,28,Business travel,Business,551,1,1,5,1,5,5,5,5,3,2,4,3,5,5,30,21.0,satisfied +9234,77095,Male,Loyal Customer,29,Business travel,Business,1481,5,5,5,5,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +9235,72780,Female,Loyal Customer,39,Business travel,Business,2949,2,2,5,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +9236,10419,Male,Loyal Customer,39,Business travel,Business,201,4,4,4,4,2,4,5,4,4,4,5,4,4,5,21,41.0,satisfied +9237,128892,Male,Loyal Customer,47,Business travel,Business,2565,4,2,4,4,4,4,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +9238,72871,Male,Loyal Customer,77,Business travel,Eco Plus,700,2,4,4,4,2,2,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +9239,17059,Female,Loyal Customer,33,Personal Travel,Eco,1134,1,4,1,1,1,1,1,1,4,2,3,5,5,1,39,31.0,neutral or dissatisfied +9240,68028,Female,Loyal Customer,57,Business travel,Business,3575,1,1,1,1,2,4,5,5,5,5,5,3,5,4,17,9.0,satisfied +9241,14122,Male,Loyal Customer,44,Personal Travel,Business,594,4,5,5,2,1,3,4,4,4,5,4,3,4,4,37,37.0,neutral or dissatisfied +9242,21124,Female,Loyal Customer,61,Personal Travel,Eco,106,3,4,3,4,2,1,1,5,5,3,5,1,5,1,50,51.0,neutral or dissatisfied +9243,73351,Female,Loyal Customer,29,Business travel,Business,2500,5,5,5,5,3,3,3,3,4,3,5,3,4,3,5,39.0,satisfied +9244,71362,Female,Loyal Customer,54,Business travel,Business,258,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +9245,96341,Female,Loyal Customer,45,Business travel,Business,1609,3,3,3,3,2,5,4,5,5,5,5,5,5,4,18,0.0,satisfied +9246,112653,Male,Loyal Customer,55,Business travel,Business,2237,3,3,3,3,3,4,4,5,5,5,5,3,5,4,33,25.0,satisfied +9247,110870,Male,disloyal Customer,45,Business travel,Business,406,4,4,4,1,4,4,4,4,4,3,4,5,5,4,34,27.0,neutral or dissatisfied +9248,25716,Male,Loyal Customer,57,Business travel,Business,432,4,3,3,3,5,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +9249,9473,Female,Loyal Customer,49,Business travel,Eco Plus,288,2,1,1,1,1,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +9250,25666,Female,disloyal Customer,21,Business travel,Eco,761,3,3,3,4,1,3,1,1,2,2,3,4,3,1,5,4.0,neutral or dissatisfied +9251,63146,Male,Loyal Customer,38,Business travel,Business,337,1,1,5,1,3,4,5,3,3,4,3,3,3,3,42,32.0,satisfied +9252,16640,Female,Loyal Customer,40,Business travel,Eco,488,4,2,2,2,4,4,4,4,1,2,4,2,2,4,2,0.0,satisfied +9253,116632,Male,Loyal Customer,16,Business travel,Eco Plus,371,3,1,1,1,3,3,1,3,4,1,3,4,4,3,12,7.0,neutral or dissatisfied +9254,118961,Female,Loyal Customer,64,Personal Travel,Eco Plus,682,1,4,1,3,3,5,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +9255,56138,Male,disloyal Customer,41,Business travel,Business,1400,3,3,3,3,3,3,3,3,3,4,5,3,5,3,276,265.0,neutral or dissatisfied +9256,109756,Male,Loyal Customer,40,Personal Travel,Eco Plus,587,2,4,2,2,1,2,1,1,5,3,5,5,5,1,0,3.0,neutral or dissatisfied +9257,82064,Female,Loyal Customer,49,Business travel,Business,3890,4,4,4,4,4,4,5,4,4,4,4,3,4,3,59,39.0,satisfied +9258,103460,Female,Loyal Customer,55,Personal Travel,Eco,448,1,2,1,3,4,3,4,3,3,1,3,1,3,2,3,0.0,neutral or dissatisfied +9259,107589,Female,Loyal Customer,53,Business travel,Business,1920,3,3,3,3,3,4,4,4,4,4,4,4,4,5,41,34.0,satisfied +9260,107132,Female,Loyal Customer,32,Personal Travel,Eco,842,3,5,3,1,2,3,2,2,5,5,1,4,5,2,0,9.0,neutral or dissatisfied +9261,32261,Female,Loyal Customer,43,Business travel,Business,101,1,1,1,1,4,5,5,4,4,4,3,3,4,4,5,13.0,satisfied +9262,103695,Female,Loyal Customer,27,Business travel,Business,3095,4,4,2,4,5,5,5,3,2,3,4,5,3,5,182,388.0,satisfied +9263,129273,Male,Loyal Customer,40,Business travel,Business,2402,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +9264,66560,Female,Loyal Customer,62,Personal Travel,Eco,328,3,3,3,3,5,4,3,5,5,3,5,4,5,2,32,28.0,neutral or dissatisfied +9265,21815,Male,Loyal Customer,50,Personal Travel,Eco,241,2,1,2,4,3,2,3,3,3,2,4,4,3,3,13,8.0,neutral or dissatisfied +9266,121383,Male,Loyal Customer,31,Personal Travel,Eco,2279,2,4,1,2,4,1,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +9267,9849,Female,disloyal Customer,27,Business travel,Eco,531,2,3,3,2,2,3,2,2,4,1,2,4,3,2,56,54.0,neutral or dissatisfied +9268,79151,Female,Loyal Customer,9,Personal Travel,Eco Plus,306,2,4,2,3,1,2,4,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +9269,10886,Female,disloyal Customer,61,Business travel,Eco,309,1,4,1,4,4,1,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +9270,36076,Male,disloyal Customer,29,Business travel,Eco,413,5,0,5,4,3,5,3,3,3,1,4,1,1,3,0,0.0,satisfied +9271,25448,Male,Loyal Customer,33,Personal Travel,Eco,669,4,4,4,2,3,4,3,3,5,4,4,4,4,3,14,2.0,neutral or dissatisfied +9272,4117,Male,Loyal Customer,50,Business travel,Business,2187,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,2.0,satisfied +9273,56731,Male,Loyal Customer,65,Personal Travel,Eco,937,1,4,0,4,1,0,1,1,4,2,4,3,5,1,6,1.0,neutral or dissatisfied +9274,3072,Male,Loyal Customer,51,Business travel,Business,3131,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +9275,15736,Male,Loyal Customer,64,Personal Travel,Eco,419,1,5,4,1,3,4,3,3,3,4,1,1,4,3,0,0.0,neutral or dissatisfied +9276,13303,Male,Loyal Customer,38,Personal Travel,Eco Plus,657,2,4,2,4,2,2,4,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +9277,5220,Male,disloyal Customer,64,Business travel,Business,383,3,3,3,2,2,3,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +9278,12240,Male,Loyal Customer,47,Business travel,Business,1705,2,2,2,2,4,3,5,5,5,5,5,3,5,3,0,0.0,satisfied +9279,6254,Female,Loyal Customer,49,Personal Travel,Eco,413,3,5,3,4,4,4,5,1,1,3,1,4,1,4,15,20.0,neutral or dissatisfied +9280,70037,Female,Loyal Customer,59,Business travel,Business,583,3,2,2,2,4,2,2,3,3,3,3,1,3,4,0,7.0,neutral or dissatisfied +9281,113656,Female,Loyal Customer,23,Personal Travel,Eco,488,2,5,2,4,5,2,5,5,5,5,4,3,5,5,1,0.0,neutral or dissatisfied +9282,38607,Male,Loyal Customer,39,Business travel,Business,3093,2,4,2,2,3,2,3,5,5,5,5,3,5,3,0,0.0,satisfied +9283,22287,Male,Loyal Customer,62,Business travel,Business,3517,4,4,4,4,5,5,5,3,4,1,5,5,2,5,172,171.0,satisfied +9284,12125,Male,Loyal Customer,37,Personal Travel,Eco,1034,2,5,2,5,1,2,1,1,3,4,5,3,4,1,0,0.0,neutral or dissatisfied +9285,74215,Female,Loyal Customer,56,Personal Travel,Business,1746,2,0,2,1,3,5,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +9286,86049,Female,Loyal Customer,63,Personal Travel,Eco,447,3,4,3,5,3,4,5,5,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +9287,107930,Female,Loyal Customer,42,Business travel,Eco,611,4,4,4,4,3,3,4,4,4,4,4,3,4,4,83,71.0,neutral or dissatisfied +9288,29674,Female,Loyal Customer,25,Business travel,Eco Plus,1533,4,4,4,4,4,4,5,4,2,4,1,5,1,4,0,6.0,satisfied +9289,42565,Male,Loyal Customer,46,Business travel,Eco,163,1,2,2,2,1,1,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +9290,68844,Female,Loyal Customer,49,Business travel,Business,3272,2,2,2,2,2,4,4,4,4,5,4,3,4,4,17,0.0,satisfied +9291,16688,Male,Loyal Customer,67,Personal Travel,Eco Plus,488,3,0,3,3,3,3,1,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +9292,24279,Female,Loyal Customer,25,Personal Travel,Eco,134,2,2,2,3,5,2,1,5,4,2,4,3,3,5,23,26.0,neutral or dissatisfied +9293,60995,Female,Loyal Customer,54,Business travel,Business,649,5,5,5,5,2,4,5,4,4,5,4,5,4,5,1,0.0,satisfied +9294,110881,Male,Loyal Customer,59,Business travel,Business,406,3,4,4,4,3,3,3,4,4,4,4,3,3,3,258,262.0,neutral or dissatisfied +9295,61163,Female,disloyal Customer,42,Business travel,Business,853,1,1,1,1,2,1,2,2,5,5,4,5,5,2,3,0.0,neutral or dissatisfied +9296,53057,Male,Loyal Customer,34,Personal Travel,Eco,1208,4,3,4,4,3,4,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +9297,17515,Male,Loyal Customer,20,Personal Travel,Eco,241,1,5,1,2,2,1,1,2,5,3,4,1,1,2,0,0.0,neutral or dissatisfied +9298,49806,Female,disloyal Customer,55,Business travel,Eco,109,2,4,2,1,5,2,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +9299,1321,Female,disloyal Customer,34,Business travel,Business,309,2,2,2,1,3,2,3,3,4,3,4,3,4,3,33,21.0,neutral or dissatisfied +9300,116706,Male,Loyal Customer,41,Business travel,Eco Plus,362,4,4,4,4,4,4,4,4,2,5,4,1,4,4,18,12.0,satisfied +9301,108600,Female,Loyal Customer,59,Business travel,Business,2709,1,4,4,4,1,2,2,1,1,1,1,4,1,1,43,36.0,neutral or dissatisfied +9302,91539,Male,disloyal Customer,30,Business travel,Business,680,2,2,2,3,1,2,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +9303,38595,Male,Loyal Customer,58,Business travel,Business,231,2,2,2,2,5,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +9304,28920,Female,Loyal Customer,58,Business travel,Eco,697,5,3,3,3,2,1,3,5,5,5,5,2,5,3,0,13.0,satisfied +9305,20787,Male,Loyal Customer,26,Business travel,Business,3294,5,5,3,5,4,4,4,4,1,5,4,1,2,4,19,12.0,satisfied +9306,3553,Female,disloyal Customer,24,Business travel,Business,227,4,0,4,3,3,4,2,3,3,4,4,5,4,3,21,58.0,satisfied +9307,48796,Female,Loyal Customer,36,Business travel,Business,373,3,1,1,1,1,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +9308,83661,Male,Loyal Customer,39,Business travel,Business,577,5,5,5,5,3,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +9309,96794,Female,disloyal Customer,39,Business travel,Business,957,4,4,4,4,3,4,3,3,4,2,4,5,4,3,3,0.0,neutral or dissatisfied +9310,129308,Male,disloyal Customer,39,Business travel,Business,2475,1,1,1,1,4,1,4,4,4,4,3,4,5,4,0,0.0,neutral or dissatisfied +9311,31060,Female,Loyal Customer,30,Business travel,Business,641,3,3,3,3,4,4,4,4,2,3,3,2,3,4,3,0.0,satisfied +9312,16950,Male,Loyal Customer,59,Personal Travel,Eco Plus,820,1,3,1,3,4,1,4,4,2,4,2,2,1,4,66,59.0,neutral or dissatisfied +9313,85281,Male,Loyal Customer,24,Personal Travel,Eco,813,4,2,4,2,1,4,1,1,1,1,2,4,2,1,39,42.0,neutral or dissatisfied +9314,98964,Female,Loyal Customer,40,Business travel,Eco,543,3,1,1,1,3,3,3,3,4,3,3,2,3,3,2,0.0,neutral or dissatisfied +9315,119231,Male,Loyal Customer,12,Personal Travel,Eco,331,3,5,3,3,5,3,5,5,5,3,3,5,2,5,0,0.0,neutral or dissatisfied +9316,82703,Male,Loyal Customer,45,Business travel,Eco,232,3,3,3,3,3,3,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +9317,33857,Female,Loyal Customer,16,Personal Travel,Eco,1609,3,5,3,1,1,3,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +9318,100041,Female,Loyal Customer,72,Business travel,Business,1721,2,2,2,2,5,4,5,5,5,5,4,3,5,5,0,0.0,satisfied +9319,23596,Female,Loyal Customer,52,Business travel,Business,1601,4,4,4,4,4,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +9320,14264,Male,Loyal Customer,47,Business travel,Eco,429,4,1,1,1,4,4,4,4,2,5,4,2,2,4,0,0.0,satisfied +9321,26649,Female,Loyal Customer,38,Business travel,Business,2801,2,2,2,2,5,4,4,2,2,2,2,4,2,3,0,7.0,neutral or dissatisfied +9322,8157,Female,disloyal Customer,17,Business travel,Eco,530,4,0,4,4,5,4,5,5,4,5,5,3,4,5,0,3.0,satisfied +9323,122107,Male,Loyal Customer,60,Personal Travel,Eco,185,1,1,1,2,4,1,2,4,1,3,3,1,3,4,0,14.0,neutral or dissatisfied +9324,7643,Male,Loyal Customer,31,Business travel,Business,3389,4,4,2,4,5,5,5,5,4,5,5,3,5,5,22,31.0,satisfied +9325,34902,Female,disloyal Customer,22,Business travel,Eco,187,1,5,1,4,3,1,3,3,4,2,4,1,5,3,0,0.0,neutral or dissatisfied +9326,74551,Male,disloyal Customer,44,Business travel,Business,1171,2,2,2,3,1,2,4,1,1,5,4,1,4,1,114,115.0,neutral or dissatisfied +9327,12588,Female,Loyal Customer,51,Business travel,Eco,542,5,3,2,2,3,4,5,5,5,5,5,1,5,5,0,3.0,satisfied +9328,62692,Male,Loyal Customer,15,Personal Travel,Business,2504,3,5,3,2,3,2,2,5,4,5,5,2,3,2,0,3.0,neutral or dissatisfied +9329,70239,Male,Loyal Customer,49,Business travel,Business,3696,2,2,2,2,4,4,4,4,4,4,4,4,4,5,10,0.0,satisfied +9330,115857,Male,Loyal Customer,54,Business travel,Eco,390,2,1,1,1,2,2,2,2,2,5,3,4,3,2,48,38.0,neutral or dissatisfied +9331,89531,Male,Loyal Customer,28,Business travel,Business,3081,3,4,3,4,3,3,3,3,2,3,4,3,3,3,90,80.0,neutral or dissatisfied +9332,121340,Male,Loyal Customer,50,Business travel,Business,430,3,2,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +9333,45273,Female,Loyal Customer,36,Personal Travel,Business,188,4,1,4,2,1,3,2,2,2,4,2,2,2,2,0,0.0,satisfied +9334,21330,Female,Loyal Customer,27,Business travel,Business,3955,4,4,4,4,5,5,5,5,4,5,5,5,4,5,0,4.0,satisfied +9335,129677,Male,Loyal Customer,47,Business travel,Business,3248,1,5,5,5,5,4,4,1,1,1,1,2,1,2,12,12.0,neutral or dissatisfied +9336,27220,Female,Loyal Customer,56,Business travel,Eco,1024,5,3,3,3,3,2,2,5,5,5,5,4,5,1,0,0.0,satisfied +9337,100751,Female,Loyal Customer,23,Personal Travel,Eco,328,2,0,2,3,5,2,5,5,1,2,2,2,4,5,0,0.0,neutral or dissatisfied +9338,99396,Male,disloyal Customer,44,Business travel,Eco,406,3,2,3,3,4,3,4,4,4,3,3,1,3,4,0,0.0,neutral or dissatisfied +9339,96897,Male,Loyal Customer,36,Personal Travel,Eco,781,4,5,4,5,4,5,5,3,5,5,5,5,5,5,212,221.0,neutral or dissatisfied +9340,116172,Female,Loyal Customer,26,Personal Travel,Eco,362,1,5,1,1,4,1,4,4,3,4,5,4,4,4,7,3.0,neutral or dissatisfied +9341,71315,Female,disloyal Customer,34,Business travel,Business,1671,4,4,4,3,1,4,1,1,3,5,3,3,4,1,1,2.0,neutral or dissatisfied +9342,37686,Male,Loyal Customer,7,Personal Travel,Eco,944,2,1,2,3,4,2,4,4,3,2,3,2,4,4,1,0.0,neutral or dissatisfied +9343,40050,Female,Loyal Customer,17,Personal Travel,Eco,926,5,4,5,2,4,5,4,4,1,2,2,1,5,4,0,0.0,satisfied +9344,124230,Male,Loyal Customer,47,Business travel,Business,1916,5,5,5,5,4,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +9345,111918,Male,Loyal Customer,47,Business travel,Business,3075,4,4,4,4,4,4,4,3,3,4,4,4,3,4,165,162.0,satisfied +9346,93867,Male,Loyal Customer,35,Business travel,Business,1746,2,2,2,2,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +9347,110047,Female,Loyal Customer,64,Business travel,Business,1984,2,4,4,4,2,2,2,3,1,2,3,2,4,2,152,129.0,neutral or dissatisfied +9348,35144,Female,Loyal Customer,40,Business travel,Business,2400,4,4,3,4,2,4,2,2,2,2,2,3,2,1,0,0.0,satisfied +9349,118072,Female,Loyal Customer,56,Business travel,Eco Plus,644,3,1,1,1,4,4,3,3,3,3,3,1,3,4,28,15.0,neutral or dissatisfied +9350,11823,Male,Loyal Customer,28,Business travel,Business,2680,4,4,4,4,4,5,4,4,5,4,4,4,4,4,1,0.0,satisfied +9351,87297,Female,Loyal Customer,18,Personal Travel,Eco,577,3,4,3,4,4,3,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +9352,72247,Female,Loyal Customer,30,Business travel,Business,2021,4,4,4,4,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +9353,5988,Male,Loyal Customer,44,Business travel,Business,925,1,1,4,1,4,5,5,4,4,4,4,4,4,3,20,22.0,satisfied +9354,28692,Female,disloyal Customer,23,Business travel,Eco,712,1,1,1,2,2,1,2,2,1,2,3,1,1,2,0,0.0,neutral or dissatisfied +9355,96606,Female,Loyal Customer,53,Business travel,Business,3640,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,5.0,satisfied +9356,77845,Female,Loyal Customer,22,Business travel,Business,3927,5,5,2,5,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +9357,61145,Female,disloyal Customer,30,Business travel,Business,853,3,3,3,4,4,3,4,4,3,5,5,5,4,4,12,9.0,neutral or dissatisfied +9358,108545,Female,Loyal Customer,42,Personal Travel,Eco,512,4,5,4,3,3,2,3,3,3,4,2,1,3,4,0,0.0,neutral or dissatisfied +9359,113644,Female,Loyal Customer,8,Personal Travel,Eco,197,2,4,2,3,4,2,4,4,4,3,5,4,4,4,0,1.0,neutral or dissatisfied +9360,21878,Female,Loyal Customer,20,Business travel,Business,551,1,1,1,1,3,4,3,3,2,3,3,1,2,3,0,0.0,satisfied +9361,46485,Female,Loyal Customer,71,Business travel,Business,3180,5,5,3,5,4,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +9362,27722,Female,Loyal Customer,38,Business travel,Eco,1448,3,4,4,4,3,3,3,3,4,2,5,2,2,3,0,0.0,satisfied +9363,99382,Female,Loyal Customer,49,Business travel,Business,3200,0,0,0,3,2,4,5,3,3,2,2,3,3,4,0,0.0,satisfied +9364,59360,Male,Loyal Customer,27,Business travel,Business,2486,1,0,0,3,5,0,5,5,4,4,2,1,4,5,0,0.0,neutral or dissatisfied +9365,59576,Female,disloyal Customer,22,Business travel,Eco,787,1,1,1,3,4,1,3,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +9366,110462,Male,Loyal Customer,48,Personal Travel,Eco,919,1,4,1,2,2,1,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +9367,122019,Female,disloyal Customer,22,Business travel,Eco,130,2,4,2,3,2,2,1,2,3,4,3,2,4,2,5,1.0,neutral or dissatisfied +9368,73020,Male,Loyal Customer,16,Personal Travel,Eco,1096,2,3,2,3,4,2,4,4,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +9369,30031,Male,Loyal Customer,37,Business travel,Eco,261,5,1,1,1,5,5,5,5,1,3,5,5,4,5,0,10.0,satisfied +9370,106714,Female,disloyal Customer,22,Business travel,Eco,837,2,3,3,3,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +9371,34585,Female,Loyal Customer,22,Business travel,Business,1617,2,5,5,5,2,2,2,2,2,1,3,4,3,2,78,68.0,neutral or dissatisfied +9372,103108,Female,Loyal Customer,69,Personal Travel,Eco,546,1,1,1,2,2,2,2,3,3,1,3,4,3,3,13,20.0,neutral or dissatisfied +9373,105759,Female,disloyal Customer,36,Business travel,Eco,525,1,0,1,3,3,1,3,3,2,5,2,5,4,3,7,3.0,neutral or dissatisfied +9374,23896,Male,disloyal Customer,27,Business travel,Eco,579,4,4,4,1,3,4,3,3,3,3,2,3,5,3,0,3.0,satisfied +9375,88975,Male,Loyal Customer,35,Business travel,Business,3526,2,2,2,2,2,2,2,1,3,2,2,2,4,2,178,190.0,neutral or dissatisfied +9376,7020,Male,Loyal Customer,66,Personal Travel,Eco,436,2,5,2,5,3,2,3,3,4,2,5,3,4,3,0,6.0,neutral or dissatisfied +9377,64244,Male,disloyal Customer,17,Business travel,Eco,1042,4,4,4,3,4,4,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +9378,3015,Male,Loyal Customer,41,Business travel,Business,862,2,2,2,2,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +9379,79195,Male,Loyal Customer,57,Business travel,Business,1990,4,4,3,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +9380,77521,Female,Loyal Customer,55,Personal Travel,Eco,1521,1,4,1,4,5,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +9381,665,Female,Loyal Customer,41,Business travel,Business,229,1,1,1,1,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +9382,15799,Female,disloyal Customer,22,Business travel,Eco,143,2,3,2,3,3,2,3,3,4,3,4,1,3,3,0,0.0,neutral or dissatisfied +9383,63691,Female,Loyal Customer,45,Business travel,Business,853,5,5,5,5,2,4,5,4,4,4,4,3,4,4,40,8.0,satisfied +9384,7580,Male,disloyal Customer,26,Business travel,Business,594,5,4,4,2,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +9385,89313,Male,Loyal Customer,50,Personal Travel,Eco Plus,453,3,5,3,4,2,3,2,2,3,2,1,3,4,2,0,0.0,neutral or dissatisfied +9386,120308,Female,Loyal Customer,43,Business travel,Eco,268,2,3,3,3,5,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +9387,40531,Male,Loyal Customer,34,Personal Travel,Business,391,3,5,3,4,3,4,5,1,1,3,1,3,1,4,25,25.0,neutral or dissatisfied +9388,104008,Male,Loyal Customer,49,Personal Travel,Eco,1363,3,4,3,1,5,3,5,5,4,4,3,5,5,5,2,0.0,neutral or dissatisfied +9389,90901,Female,Loyal Customer,47,Business travel,Business,515,4,4,2,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +9390,126524,Female,Loyal Customer,46,Personal Travel,Eco,196,1,5,1,3,5,4,2,4,4,1,3,1,4,1,75,76.0,neutral or dissatisfied +9391,107981,Female,Loyal Customer,43,Business travel,Business,1638,1,1,3,1,4,4,4,4,3,5,5,4,5,4,94,134.0,satisfied +9392,17436,Female,Loyal Customer,56,Personal Travel,Eco,376,1,5,5,1,2,5,5,5,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +9393,98175,Female,Loyal Customer,48,Business travel,Business,327,2,2,2,2,4,5,5,4,4,4,4,3,4,3,12,7.0,satisfied +9394,14331,Male,Loyal Customer,50,Personal Travel,Eco,429,3,0,3,5,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +9395,54063,Female,Loyal Customer,60,Business travel,Business,1416,1,1,1,1,2,2,2,1,1,1,1,4,1,4,11,0.0,neutral or dissatisfied +9396,98122,Female,Loyal Customer,7,Personal Travel,Eco,472,3,0,3,2,5,3,5,5,4,4,4,3,5,5,0,13.0,neutral or dissatisfied +9397,98746,Male,Loyal Customer,53,Personal Travel,Eco,1290,2,4,3,2,2,3,5,2,5,4,3,3,5,2,0,10.0,neutral or dissatisfied +9398,122306,Female,Loyal Customer,46,Personal Travel,Eco,544,4,5,4,2,1,1,3,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +9399,55807,Female,disloyal Customer,22,Business travel,Eco,1416,3,2,2,3,5,3,5,5,4,2,5,5,5,5,0,17.0,neutral or dissatisfied +9400,13538,Female,disloyal Customer,40,Business travel,Business,106,5,5,5,3,1,5,1,1,1,5,4,4,3,1,0,0.0,satisfied +9401,33355,Female,Loyal Customer,33,Business travel,Business,2462,2,1,2,2,3,5,2,4,4,4,4,4,4,4,0,0.0,satisfied +9402,126363,Male,Loyal Customer,28,Personal Travel,Eco,507,2,4,2,5,1,2,1,1,4,3,4,3,5,1,7,12.0,neutral or dissatisfied +9403,96247,Female,Loyal Customer,43,Personal Travel,Eco,546,2,4,2,4,5,3,3,1,1,2,3,1,1,1,41,45.0,neutral or dissatisfied +9404,87911,Male,disloyal Customer,24,Business travel,Business,271,5,0,5,1,1,5,1,1,3,2,4,3,5,1,0,0.0,satisfied +9405,43990,Male,disloyal Customer,43,Business travel,Eco,397,4,3,4,3,2,4,2,2,3,5,3,4,4,2,0,6.0,neutral or dissatisfied +9406,17412,Female,disloyal Customer,26,Business travel,Eco,376,2,0,2,4,2,2,2,2,2,1,1,2,3,2,0,0.0,neutral or dissatisfied +9407,19862,Male,Loyal Customer,34,Personal Travel,Eco,693,2,4,2,2,2,2,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +9408,38564,Male,Loyal Customer,8,Personal Travel,Eco,2586,1,4,1,1,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +9409,2855,Male,Loyal Customer,59,Business travel,Eco,409,1,4,4,4,1,1,1,1,3,4,4,1,3,1,0,7.0,neutral or dissatisfied +9410,77975,Male,disloyal Customer,22,Business travel,Eco,214,0,0,0,5,4,0,2,4,5,4,5,5,5,4,1,0.0,satisfied +9411,73581,Male,Loyal Customer,60,Business travel,Business,3657,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +9412,72169,Female,Loyal Customer,46,Business travel,Business,3540,3,3,5,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +9413,62806,Male,Loyal Customer,12,Personal Travel,Eco,2556,3,2,3,4,3,4,4,4,2,3,3,4,4,4,0,0.0,neutral or dissatisfied +9414,89916,Male,Loyal Customer,44,Business travel,Eco,1306,3,1,1,1,3,3,3,3,3,4,2,3,3,3,80,73.0,neutral or dissatisfied +9415,58892,Male,Loyal Customer,44,Business travel,Business,2069,3,3,3,3,4,5,5,2,2,2,2,3,2,5,5,47.0,satisfied +9416,15536,Male,disloyal Customer,37,Business travel,Eco,812,2,2,2,5,5,2,5,5,4,3,2,4,4,5,104,88.0,neutral or dissatisfied +9417,79390,Male,Loyal Customer,70,Business travel,Business,1696,3,3,3,3,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +9418,9803,Female,Loyal Customer,38,Business travel,Business,474,5,5,5,5,1,1,3,4,4,4,4,2,4,5,0,5.0,satisfied +9419,98445,Female,Loyal Customer,55,Personal Travel,Eco,814,3,4,3,3,2,1,4,5,5,3,5,4,5,4,13,0.0,neutral or dissatisfied +9420,91497,Female,Loyal Customer,41,Personal Travel,Eco,391,3,3,3,3,5,3,5,5,4,3,1,2,2,5,0,0.0,neutral or dissatisfied +9421,20273,Male,Loyal Customer,11,Personal Travel,Eco,235,5,5,5,3,1,5,1,1,4,4,5,3,5,1,88,73.0,satisfied +9422,2145,Male,Loyal Customer,52,Personal Travel,Eco Plus,404,2,4,5,3,4,5,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +9423,124391,Female,Loyal Customer,68,Personal Travel,Eco,808,3,5,3,4,1,3,3,5,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +9424,65886,Male,disloyal Customer,34,Business travel,Business,569,1,1,1,5,4,1,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +9425,85277,Female,Loyal Customer,53,Personal Travel,Eco,696,1,3,1,4,1,4,4,2,2,1,5,3,2,2,0,0.0,neutral or dissatisfied +9426,68322,Female,Loyal Customer,51,Business travel,Business,2165,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,5.0,satisfied +9427,9096,Female,Loyal Customer,63,Personal Travel,Eco Plus,212,1,2,1,4,2,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +9428,127797,Female,Loyal Customer,27,Business travel,Business,1044,4,4,4,4,5,5,5,5,4,2,4,3,5,5,0,0.0,satisfied +9429,123491,Female,disloyal Customer,30,Business travel,Business,2125,2,2,2,2,5,2,5,5,3,4,4,4,4,5,0,4.0,neutral or dissatisfied +9430,124510,Male,Loyal Customer,47,Personal Travel,Eco,930,1,3,0,3,5,0,5,5,2,1,3,1,2,5,0,0.0,neutral or dissatisfied +9431,50862,Female,Loyal Customer,62,Personal Travel,Eco,89,2,5,2,5,4,5,5,1,1,2,1,5,1,4,61,52.0,neutral or dissatisfied +9432,128671,Male,Loyal Customer,29,Business travel,Business,2288,4,3,3,3,4,4,4,1,5,2,4,4,2,4,2,10.0,neutral or dissatisfied +9433,45443,Female,Loyal Customer,38,Business travel,Eco Plus,458,2,4,2,4,2,1,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +9434,53281,Female,disloyal Customer,27,Business travel,Eco,811,4,3,3,3,5,3,5,5,1,4,3,4,3,5,2,0.0,neutral or dissatisfied +9435,40708,Female,Loyal Customer,58,Business travel,Eco,588,4,1,1,1,1,4,2,5,5,4,5,4,5,1,0,0.0,satisfied +9436,24736,Male,Loyal Customer,51,Business travel,Business,1597,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,31.0,satisfied +9437,108184,Male,Loyal Customer,22,Personal Travel,Eco,990,4,5,4,1,4,5,5,2,3,4,2,5,5,5,243,267.0,neutral or dissatisfied +9438,61169,Female,Loyal Customer,58,Business travel,Business,967,1,1,1,1,4,4,5,1,1,2,1,3,1,3,0,6.0,satisfied +9439,69973,Female,Loyal Customer,31,Business travel,Business,236,5,5,5,5,5,5,5,5,4,2,4,5,4,5,0,0.0,satisfied +9440,43897,Male,disloyal Customer,41,Business travel,Eco,114,3,4,3,3,4,3,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +9441,98685,Female,Loyal Customer,47,Personal Travel,Eco,861,2,5,2,3,5,4,5,4,4,2,4,3,4,5,100,120.0,neutral or dissatisfied +9442,91213,Male,Loyal Customer,10,Personal Travel,Eco,581,3,4,3,1,4,3,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +9443,65900,Female,Loyal Customer,51,Business travel,Business,569,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +9444,44420,Female,Loyal Customer,16,Personal Travel,Eco Plus,342,2,4,2,4,4,2,4,4,4,2,5,5,4,4,0,9.0,neutral or dissatisfied +9445,21958,Male,disloyal Customer,26,Business travel,Eco,448,1,1,2,3,5,2,5,5,2,5,3,3,3,5,66,59.0,neutral or dissatisfied +9446,53219,Male,disloyal Customer,40,Business travel,Eco,212,3,5,3,3,3,3,3,3,1,3,5,3,5,3,2,0.0,neutral or dissatisfied +9447,101190,Male,Loyal Customer,43,Personal Travel,Eco,758,1,5,1,2,4,1,4,4,4,4,5,4,5,4,7,3.0,neutral or dissatisfied +9448,116205,Female,Loyal Customer,7,Personal Travel,Eco,337,3,5,3,3,3,3,3,3,3,1,2,4,1,3,50,58.0,neutral or dissatisfied +9449,112348,Male,disloyal Customer,46,Business travel,Business,967,2,2,2,3,2,2,2,2,5,5,4,3,5,2,29,44.0,neutral or dissatisfied +9450,65395,Female,Loyal Customer,35,Personal Travel,Eco,631,3,3,3,2,4,3,4,4,4,5,5,2,3,4,20,11.0,neutral or dissatisfied +9451,125591,Female,Loyal Customer,54,Business travel,Business,1587,5,5,5,5,3,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +9452,57971,Male,Loyal Customer,59,Business travel,Business,3979,4,4,3,4,4,4,4,5,5,5,5,5,5,3,0,8.0,satisfied +9453,107983,Male,Loyal Customer,40,Personal Travel,Business,271,2,5,2,2,5,4,1,1,1,2,1,3,1,2,3,0.0,neutral or dissatisfied +9454,9440,Female,Loyal Customer,30,Business travel,Business,368,2,1,1,1,2,2,2,2,4,3,1,2,1,2,0,0.0,neutral or dissatisfied +9455,93232,Male,Loyal Customer,44,Business travel,Business,1460,3,1,3,3,3,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +9456,93995,Male,Loyal Customer,53,Business travel,Business,3401,2,2,4,2,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +9457,75164,Female,disloyal Customer,21,Business travel,Eco,854,1,1,1,4,5,1,5,5,4,3,4,3,4,5,0,5.0,neutral or dissatisfied +9458,27226,Female,Loyal Customer,35,Business travel,Business,2601,4,4,4,4,1,5,2,4,4,4,4,4,4,4,0,0.0,satisfied +9459,83262,Female,disloyal Customer,31,Business travel,Eco,1979,3,4,4,3,1,3,1,1,3,5,4,1,4,1,21,0.0,neutral or dissatisfied +9460,3869,Female,Loyal Customer,37,Business travel,Business,2677,5,5,5,5,2,4,4,5,5,5,4,4,5,4,0,4.0,satisfied +9461,83022,Male,Loyal Customer,39,Business travel,Business,1599,5,5,5,5,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +9462,64300,Male,Loyal Customer,34,Business travel,Business,1192,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +9463,86366,Female,disloyal Customer,49,Business travel,Business,762,3,3,3,3,5,3,4,5,4,5,5,5,4,5,0,4.0,neutral or dissatisfied +9464,28049,Female,Loyal Customer,38,Personal Travel,Eco,1739,4,4,4,1,4,4,4,4,4,5,5,5,5,4,4,0.0,neutral or dissatisfied +9465,37955,Male,Loyal Customer,50,Business travel,Business,1724,5,5,5,5,5,4,5,4,4,4,4,5,4,5,1,5.0,satisfied +9466,875,Female,Loyal Customer,31,Business travel,Business,229,2,5,5,5,2,2,2,2,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +9467,66013,Male,Loyal Customer,30,Business travel,Business,1345,4,4,3,4,4,4,4,4,4,3,4,3,5,4,0,2.0,satisfied +9468,38371,Male,Loyal Customer,45,Personal Travel,Eco,1173,2,5,2,2,3,2,3,3,5,4,3,3,4,3,5,65.0,neutral or dissatisfied +9469,52500,Female,Loyal Customer,49,Business travel,Business,1763,3,3,3,3,4,4,5,5,5,5,4,3,5,4,0,6.0,satisfied +9470,86531,Female,Loyal Customer,43,Personal Travel,Eco,762,3,4,3,4,5,4,3,4,4,3,3,4,4,2,94,76.0,neutral or dissatisfied +9471,13347,Female,Loyal Customer,48,Business travel,Business,2841,2,2,2,2,5,3,4,3,3,3,3,5,3,3,0,0.0,satisfied +9472,75282,Male,Loyal Customer,53,Personal Travel,Eco,1744,2,5,3,4,4,3,3,4,5,2,5,4,4,4,14,21.0,neutral or dissatisfied +9473,82884,Male,Loyal Customer,43,Business travel,Business,3656,4,4,4,4,3,1,1,5,5,5,5,5,5,5,0,0.0,satisfied +9474,34998,Male,disloyal Customer,38,Business travel,Business,1182,2,2,2,3,2,2,2,2,4,3,4,1,3,2,0,26.0,neutral or dissatisfied +9475,69144,Male,Loyal Customer,52,Business travel,Eco,2248,3,1,2,2,3,3,3,1,4,3,4,3,3,3,0,20.0,neutral or dissatisfied +9476,7096,Male,disloyal Customer,65,Business travel,Eco,157,3,2,3,2,1,3,1,1,2,3,1,1,2,1,38,43.0,neutral or dissatisfied +9477,80410,Male,Loyal Customer,38,Business travel,Eco Plus,1016,3,2,2,2,3,3,3,3,2,4,4,2,4,3,35,24.0,neutral or dissatisfied +9478,111492,Male,disloyal Customer,44,Business travel,Business,391,4,4,4,2,2,4,2,2,4,4,4,3,4,2,0,5.0,satisfied +9479,99747,Male,Loyal Customer,41,Business travel,Eco,255,1,0,0,4,4,1,5,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +9480,109620,Male,Loyal Customer,65,Business travel,Business,829,1,1,2,1,5,5,5,4,4,4,4,3,4,3,1,0.0,satisfied +9481,125278,Female,Loyal Customer,44,Business travel,Business,678,1,1,1,1,4,4,5,3,3,3,3,5,3,4,0,,satisfied +9482,104056,Male,Loyal Customer,12,Personal Travel,Eco,1044,1,5,1,1,1,1,1,1,5,5,1,2,1,1,0,0.0,neutral or dissatisfied +9483,31282,Male,Loyal Customer,24,Personal Travel,Eco,533,4,5,4,4,2,4,2,2,4,2,4,4,4,2,10,4.0,neutral or dissatisfied +9484,129006,Male,Loyal Customer,43,Business travel,Business,2704,3,3,3,3,5,5,5,3,4,3,4,5,5,5,0,0.0,satisfied +9485,114623,Male,Loyal Customer,58,Business travel,Business,372,4,4,4,4,2,4,4,5,5,4,5,4,5,5,58,50.0,satisfied +9486,10085,Male,Loyal Customer,54,Business travel,Business,2638,1,1,1,1,5,5,5,4,3,5,4,5,5,5,168,156.0,satisfied +9487,19481,Female,disloyal Customer,23,Business travel,Eco,177,3,3,3,1,1,3,1,1,3,4,5,4,3,1,0,0.0,neutral or dissatisfied +9488,18272,Male,Loyal Customer,58,Personal Travel,Eco,179,3,5,3,3,3,3,3,3,2,2,3,1,1,3,0,0.0,neutral or dissatisfied +9489,13288,Male,Loyal Customer,27,Business travel,Eco Plus,657,0,0,0,1,5,0,5,5,3,1,2,4,2,5,0,0.0,satisfied +9490,72762,Female,Loyal Customer,50,Business travel,Business,2616,3,3,3,3,2,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +9491,40223,Male,Loyal Customer,36,Business travel,Eco,436,2,2,2,2,2,2,2,2,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +9492,1791,Male,Loyal Customer,51,Business travel,Business,1572,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +9493,87952,Male,Loyal Customer,23,Personal Travel,Business,366,3,4,3,3,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +9494,83079,Male,Loyal Customer,52,Business travel,Business,583,3,3,3,3,5,2,3,5,5,5,5,4,5,5,0,6.0,satisfied +9495,15632,Male,Loyal Customer,48,Personal Travel,Eco,229,3,4,3,3,4,3,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +9496,126384,Male,Loyal Customer,37,Personal Travel,Eco,507,3,2,3,4,2,3,4,2,1,2,3,2,4,2,0,18.0,neutral or dissatisfied +9497,116713,Female,disloyal Customer,37,Business travel,Eco Plus,325,1,0,0,3,1,0,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +9498,100015,Female,Loyal Customer,49,Business travel,Business,1721,0,0,0,1,2,5,5,5,5,5,5,5,5,4,57,51.0,satisfied +9499,100939,Female,Loyal Customer,46,Business travel,Business,1767,3,3,3,3,3,5,5,5,5,5,5,4,5,5,28,33.0,satisfied +9500,374,Female,Loyal Customer,39,Business travel,Business,2895,3,3,2,3,4,4,5,5,5,5,5,5,5,3,27,30.0,satisfied +9501,103437,Male,Loyal Customer,22,Business travel,Eco Plus,237,2,5,2,2,2,2,2,2,4,5,1,1,1,2,19,20.0,neutral or dissatisfied +9502,103256,Male,Loyal Customer,59,Business travel,Business,888,5,5,5,5,5,4,5,5,5,5,5,4,5,4,14,14.0,satisfied +9503,97209,Male,Loyal Customer,33,Business travel,Business,2513,4,4,4,4,4,4,4,4,3,3,4,4,4,4,7,1.0,satisfied +9504,16440,Male,Loyal Customer,43,Business travel,Business,1594,4,4,4,4,2,2,4,5,5,5,5,2,5,1,0,0.0,satisfied +9505,81714,Male,Loyal Customer,54,Personal Travel,Eco Plus,907,2,4,2,3,4,2,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +9506,15714,Female,Loyal Customer,28,Business travel,Business,479,3,4,5,5,3,3,3,3,1,4,3,2,3,3,18,15.0,neutral or dissatisfied +9507,76159,Female,Loyal Customer,53,Business travel,Eco,289,3,2,2,2,3,1,1,3,3,3,3,1,3,3,117,104.0,neutral or dissatisfied +9508,69381,Female,Loyal Customer,47,Business travel,Business,1096,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +9509,77952,Female,disloyal Customer,27,Business travel,Business,332,1,1,1,3,5,1,4,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +9510,73398,Female,Loyal Customer,37,Business travel,Business,2030,2,4,1,4,2,2,2,2,2,2,2,3,2,4,12,0.0,neutral or dissatisfied +9511,99714,Male,Loyal Customer,34,Personal Travel,Eco Plus,667,1,5,1,1,5,1,5,5,4,3,5,4,4,5,3,2.0,neutral or dissatisfied +9512,114298,Male,Loyal Customer,41,Personal Travel,Eco,819,2,4,2,3,5,2,5,5,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +9513,59013,Female,disloyal Customer,49,Business travel,Business,1744,4,4,4,2,5,4,5,5,5,3,4,3,4,5,9,0.0,satisfied +9514,87328,Female,Loyal Customer,34,Personal Travel,Eco,1027,0,5,0,2,3,0,3,3,5,4,4,4,4,3,0,0.0,satisfied +9515,88534,Female,Loyal Customer,26,Personal Travel,Eco,250,2,4,0,1,5,0,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +9516,98384,Female,Loyal Customer,41,Business travel,Business,1131,3,3,3,3,3,5,4,5,5,5,5,3,5,4,2,0.0,satisfied +9517,26681,Male,Loyal Customer,52,Personal Travel,Eco,406,3,4,3,1,5,3,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +9518,80356,Male,Loyal Customer,53,Business travel,Business,2815,3,3,3,3,2,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +9519,31883,Male,disloyal Customer,18,Business travel,Business,828,5,4,5,4,4,5,2,4,2,1,3,3,5,4,0,0.0,satisfied +9520,5372,Female,Loyal Customer,47,Business travel,Business,1616,3,3,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +9521,114510,Male,Loyal Customer,43,Business travel,Business,2822,5,5,1,5,2,4,5,5,5,5,5,4,5,5,21,32.0,satisfied +9522,66476,Female,Loyal Customer,55,Business travel,Business,447,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,2.0,satisfied +9523,71911,Female,Loyal Customer,29,Personal Travel,Eco,1744,4,2,4,3,1,4,1,1,1,2,2,3,3,1,4,9.0,neutral or dissatisfied +9524,114815,Male,Loyal Customer,46,Business travel,Business,337,1,1,1,1,2,5,4,5,5,5,5,3,5,3,18,17.0,satisfied +9525,122595,Female,disloyal Customer,25,Business travel,Business,728,4,4,4,1,2,4,3,2,3,4,5,3,5,2,0,0.0,satisfied +9526,73976,Female,Loyal Customer,45,Personal Travel,Eco,2218,3,3,3,4,4,4,4,2,2,3,2,2,2,1,6,0.0,neutral or dissatisfied +9527,102177,Female,Loyal Customer,50,Business travel,Business,397,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +9528,72126,Male,disloyal Customer,38,Business travel,Business,731,3,3,3,2,5,3,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +9529,110433,Female,Loyal Customer,24,Personal Travel,Eco,919,1,4,1,4,2,1,2,2,3,4,5,3,5,2,16,10.0,neutral or dissatisfied +9530,78045,Female,Loyal Customer,34,Personal Travel,Eco,106,4,2,4,4,5,4,5,5,1,1,4,2,4,5,3,1.0,satisfied +9531,114134,Female,Loyal Customer,33,Business travel,Business,3546,4,4,4,4,5,4,4,5,5,5,5,5,5,4,3,,satisfied +9532,60118,Female,disloyal Customer,20,Business travel,Eco,1182,2,2,2,4,1,2,1,1,4,4,3,2,3,1,0,0.0,neutral or dissatisfied +9533,110027,Male,Loyal Customer,62,Personal Travel,Eco,1204,3,5,3,4,3,3,3,3,4,1,1,4,2,3,42,14.0,neutral or dissatisfied +9534,5693,Female,disloyal Customer,44,Business travel,Eco,299,4,0,4,5,1,4,1,1,1,1,3,2,4,1,0,55.0,neutral or dissatisfied +9535,14333,Female,Loyal Customer,14,Personal Travel,Eco,429,2,4,3,4,2,3,2,2,1,3,3,4,4,2,113,102.0,neutral or dissatisfied +9536,11506,Male,Loyal Customer,54,Personal Travel,Eco Plus,312,2,5,2,4,2,2,2,2,4,3,5,3,4,2,47,46.0,neutral or dissatisfied +9537,69972,Male,Loyal Customer,43,Business travel,Business,2228,0,0,0,1,3,5,4,2,2,2,5,5,2,5,0,0.0,satisfied +9538,90202,Male,Loyal Customer,35,Personal Travel,Eco,957,4,5,4,2,1,4,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +9539,97643,Male,Loyal Customer,42,Business travel,Business,1587,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +9540,15816,Female,Loyal Customer,12,Personal Travel,Eco,282,3,5,3,3,2,3,2,2,5,5,4,4,5,2,16,31.0,neutral or dissatisfied +9541,23262,Male,Loyal Customer,48,Business travel,Business,826,3,3,1,3,5,4,4,3,3,3,3,3,3,3,0,41.0,neutral or dissatisfied +9542,102078,Female,Loyal Customer,46,Business travel,Business,2014,5,5,5,5,2,5,4,4,4,4,4,4,4,5,27,43.0,satisfied +9543,34380,Male,disloyal Customer,26,Business travel,Eco,612,3,0,3,3,2,3,2,2,2,1,3,2,2,2,0,0.0,neutral or dissatisfied +9544,81605,Female,Loyal Customer,16,Business travel,Business,1975,1,4,4,4,1,1,1,1,1,4,4,2,3,1,0,26.0,neutral or dissatisfied +9545,100607,Male,Loyal Customer,55,Business travel,Business,1670,5,5,5,5,2,2,2,4,5,4,4,2,5,2,144,139.0,satisfied +9546,20746,Male,Loyal Customer,61,Business travel,Business,3937,1,1,1,1,1,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +9547,93163,Female,Loyal Customer,31,Personal Travel,Eco,1066,3,3,3,2,3,3,5,3,1,5,3,4,3,3,0,23.0,neutral or dissatisfied +9548,102268,Male,Loyal Customer,49,Business travel,Business,236,0,1,1,2,5,4,4,5,5,3,3,3,5,4,0,0.0,satisfied +9549,15475,Female,Loyal Customer,68,Personal Travel,Eco,377,1,5,1,3,2,4,5,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +9550,100795,Female,Loyal Customer,22,Business travel,Business,2525,1,1,1,1,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +9551,39734,Male,Loyal Customer,70,Personal Travel,Eco,298,2,4,2,3,1,2,1,1,3,2,4,3,5,1,0,,neutral or dissatisfied +9552,79520,Female,Loyal Customer,53,Business travel,Business,760,4,2,4,4,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +9553,2391,Male,disloyal Customer,26,Business travel,Business,641,2,2,2,5,3,2,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +9554,121208,Male,Loyal Customer,46,Personal Travel,Eco Plus,2370,2,5,2,1,2,3,3,3,2,5,4,3,5,3,0,1.0,neutral or dissatisfied +9555,30323,Female,Loyal Customer,32,Business travel,Business,2136,5,5,5,5,4,4,4,4,3,1,3,3,5,4,0,0.0,satisfied +9556,65984,Female,Loyal Customer,7,Personal Travel,Eco,1372,0,4,0,4,1,0,1,1,3,2,5,3,4,1,0,0.0,satisfied +9557,91166,Female,Loyal Customer,14,Personal Travel,Eco,250,3,5,3,4,4,3,1,4,5,2,4,5,5,4,8,17.0,neutral or dissatisfied +9558,111678,Female,Loyal Customer,61,Personal Travel,Eco,991,1,4,1,4,1,3,3,4,4,1,4,3,4,4,14,21.0,neutral or dissatisfied +9559,126120,Female,Loyal Customer,11,Business travel,Business,507,4,4,2,4,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +9560,19045,Male,Loyal Customer,52,Business travel,Business,1722,4,4,4,4,2,3,1,4,4,5,4,1,4,3,0,0.0,satisfied +9561,81039,Male,Loyal Customer,22,Business travel,Business,1399,2,1,1,1,2,2,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +9562,107139,Male,Loyal Customer,33,Personal Travel,Business,668,2,4,2,2,2,2,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +9563,33351,Male,Loyal Customer,29,Business travel,Business,2556,3,3,3,3,3,3,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +9564,46348,Female,Loyal Customer,27,Business travel,Eco Plus,692,0,1,1,2,1,1,1,1,2,1,2,5,2,1,0,51.0,satisfied +9565,37327,Female,disloyal Customer,17,Business travel,Eco,972,3,4,4,4,4,4,1,4,3,5,2,5,5,4,1,0.0,neutral or dissatisfied +9566,105521,Male,Loyal Customer,53,Business travel,Business,611,4,4,4,4,4,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +9567,124522,Female,Loyal Customer,44,Business travel,Business,1276,1,1,1,1,2,4,4,4,4,4,4,4,4,3,18,13.0,satisfied +9568,55917,Male,Loyal Customer,49,Personal Travel,Eco,723,1,3,1,4,4,1,4,4,2,3,4,5,3,4,19,4.0,neutral or dissatisfied +9569,37890,Female,Loyal Customer,31,Business travel,Business,1664,1,4,4,4,1,1,1,1,2,4,3,2,3,1,22,36.0,neutral or dissatisfied +9570,44187,Female,Loyal Customer,51,Business travel,Business,2763,2,3,3,3,5,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +9571,70364,Male,disloyal Customer,22,Business travel,Business,1145,4,0,3,3,2,3,2,2,4,2,4,3,5,2,0,0.0,satisfied +9572,55558,Female,Loyal Customer,47,Business travel,Business,550,3,3,2,3,5,5,4,5,5,4,5,3,5,4,0,4.0,satisfied +9573,53744,Male,Loyal Customer,50,Business travel,Eco Plus,1208,3,4,4,4,3,3,3,3,2,1,3,5,4,3,9,7.0,satisfied +9574,906,Female,Loyal Customer,42,Business travel,Business,247,3,4,4,4,5,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +9575,4631,Female,disloyal Customer,16,Business travel,Eco,489,2,3,2,4,4,2,4,4,1,4,4,2,3,4,36,12.0,neutral or dissatisfied +9576,39480,Male,disloyal Customer,11,Business travel,Eco,867,2,2,2,4,3,2,3,3,2,3,4,4,4,3,44,57.0,neutral or dissatisfied +9577,99183,Female,Loyal Customer,36,Business travel,Business,3087,4,4,2,4,3,1,3,4,4,4,4,3,4,5,0,0.0,satisfied +9578,32030,Male,Loyal Customer,53,Business travel,Business,216,4,4,4,4,2,2,3,4,4,5,3,1,4,4,0,0.0,satisfied +9579,120039,Male,Loyal Customer,49,Business travel,Business,2592,4,3,4,4,2,5,5,4,4,4,4,3,4,5,1,0.0,satisfied +9580,52646,Male,Loyal Customer,14,Personal Travel,Eco,119,1,2,1,3,3,1,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +9581,70265,Female,disloyal Customer,21,Business travel,Business,852,4,4,4,5,1,4,1,1,5,2,4,3,5,1,0,0.0,satisfied +9582,8686,Male,disloyal Customer,16,Business travel,Business,280,3,1,2,4,5,2,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +9583,122732,Female,Loyal Customer,36,Business travel,Business,3669,4,4,4,4,4,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +9584,19460,Female,disloyal Customer,27,Business travel,Eco,177,2,5,2,5,4,2,4,4,2,1,3,4,2,4,0,0.0,neutral or dissatisfied +9585,6656,Female,disloyal Customer,26,Business travel,Business,403,3,3,3,2,5,3,5,5,5,3,5,5,4,5,19,16.0,neutral or dissatisfied +9586,113264,Male,Loyal Customer,27,Business travel,Business,2620,1,1,1,1,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +9587,73400,Female,Loyal Customer,48,Business travel,Business,1144,3,2,2,2,2,3,2,3,3,3,3,2,3,1,29,50.0,neutral or dissatisfied +9588,64561,Male,Loyal Customer,44,Business travel,Business,2337,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +9589,54021,Male,Loyal Customer,31,Personal Travel,Eco,1091,3,5,3,1,3,3,4,3,5,3,4,1,4,3,84,78.0,neutral or dissatisfied +9590,41454,Male,Loyal Customer,42,Business travel,Business,2824,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,8.0,satisfied +9591,22651,Female,disloyal Customer,38,Business travel,Eco Plus,223,1,1,1,3,5,1,5,5,4,3,3,4,2,5,0,18.0,neutral or dissatisfied +9592,88855,Male,Loyal Customer,38,Personal Travel,Eco Plus,366,3,5,3,2,5,3,5,5,5,2,2,5,2,5,1,0.0,neutral or dissatisfied +9593,118003,Female,Loyal Customer,67,Personal Travel,Business,1037,3,4,3,3,5,4,5,2,2,3,2,5,2,3,16,11.0,neutral or dissatisfied +9594,7199,Male,Loyal Customer,55,Business travel,Business,130,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +9595,60831,Female,Loyal Customer,28,Personal Travel,Eco,680,4,1,4,2,1,4,1,1,1,4,2,2,3,1,0,0.0,satisfied +9596,64286,Male,disloyal Customer,24,Business travel,Eco,1172,4,4,4,1,3,4,3,3,3,3,4,4,5,3,0,0.0,satisfied +9597,113871,Female,Loyal Customer,50,Personal Travel,Eco,1363,1,4,1,2,2,5,5,1,1,1,3,5,1,4,0,0.0,neutral or dissatisfied +9598,117816,Female,Loyal Customer,7,Personal Travel,Eco,328,4,4,4,4,2,4,2,2,4,3,5,3,4,2,13,7.0,neutral or dissatisfied +9599,63938,Male,Loyal Customer,69,Personal Travel,Eco,1172,3,3,3,4,5,3,5,5,4,5,4,1,4,5,0,0.0,neutral or dissatisfied +9600,72948,Male,Loyal Customer,29,Business travel,Business,3300,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +9601,16257,Female,Loyal Customer,43,Business travel,Eco,946,5,3,3,3,4,1,2,5,5,5,5,2,5,2,0,0.0,satisfied +9602,53858,Male,Loyal Customer,20,Business travel,Business,191,0,3,0,1,5,4,4,5,5,5,5,4,2,5,3,0.0,satisfied +9603,33982,Female,Loyal Customer,31,Business travel,Eco,1598,3,1,4,4,3,4,3,3,1,5,3,1,2,3,19,2.0,satisfied +9604,126104,Female,disloyal Customer,21,Business travel,Eco,650,5,0,5,2,3,5,3,3,4,2,4,3,5,3,0,0.0,satisfied +9605,55069,Female,disloyal Customer,20,Business travel,Eco,1504,3,3,3,4,5,3,4,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +9606,31928,Male,Loyal Customer,44,Business travel,Business,84,5,5,5,5,5,4,5,5,5,5,4,3,5,3,3,7.0,satisfied +9607,9435,Female,disloyal Customer,48,Business travel,Business,310,3,3,3,1,5,3,5,5,5,3,5,5,5,5,3,8.0,neutral or dissatisfied +9608,129642,Female,Loyal Customer,56,Business travel,Business,3325,5,5,5,5,3,5,5,4,4,4,4,3,4,5,6,0.0,satisfied +9609,78465,Male,Loyal Customer,44,Business travel,Business,3112,5,5,5,5,5,5,4,5,5,5,5,3,5,5,0,25.0,satisfied +9610,128151,Male,Loyal Customer,49,Business travel,Business,1788,1,1,1,1,4,5,4,3,3,3,3,5,3,5,0,1.0,satisfied +9611,58797,Female,Loyal Customer,63,Business travel,Business,3991,2,2,2,2,2,4,4,2,2,2,2,2,2,2,41,33.0,neutral or dissatisfied +9612,117346,Male,disloyal Customer,25,Business travel,Business,296,5,0,5,4,2,5,2,2,4,2,5,5,4,2,54,55.0,satisfied +9613,104156,Male,disloyal Customer,24,Business travel,Eco,349,2,0,2,4,2,4,4,3,5,5,4,4,3,4,236,374.0,neutral or dissatisfied +9614,18720,Male,Loyal Customer,62,Personal Travel,Eco Plus,201,1,4,1,2,3,1,3,3,5,5,2,2,5,3,31,16.0,neutral or dissatisfied +9615,47631,Female,disloyal Customer,21,Business travel,Eco,1428,3,3,3,3,5,3,5,5,3,1,4,2,4,5,111,99.0,neutral or dissatisfied +9616,1236,Male,Loyal Customer,23,Personal Travel,Eco,158,1,5,1,3,4,1,4,4,3,2,2,3,1,4,0,0.0,neutral or dissatisfied +9617,40826,Male,Loyal Customer,44,Business travel,Eco,588,1,4,4,4,1,1,1,1,3,5,4,3,3,1,0,10.0,neutral or dissatisfied +9618,4349,Female,Loyal Customer,59,Business travel,Business,618,5,4,5,5,3,5,5,5,5,5,5,3,5,3,0,12.0,satisfied +9619,102289,Male,Loyal Customer,37,Business travel,Business,414,3,3,3,3,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +9620,36255,Male,Loyal Customer,68,Business travel,Business,2712,1,1,3,1,2,2,4,2,2,2,2,1,2,2,0,0.0,satisfied +9621,111539,Male,Loyal Customer,11,Personal Travel,Business,883,1,3,1,1,3,1,3,3,3,3,4,1,3,3,8,0.0,neutral or dissatisfied +9622,91774,Male,Loyal Customer,56,Personal Travel,Eco,626,4,5,5,3,2,5,2,2,3,3,5,3,4,2,82,92.0,satisfied +9623,118295,Female,Loyal Customer,28,Business travel,Business,602,3,3,3,3,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +9624,108272,Male,Loyal Customer,24,Personal Travel,Eco,895,3,5,3,3,1,3,1,1,2,5,3,5,2,1,69,57.0,neutral or dissatisfied +9625,75648,Female,disloyal Customer,21,Business travel,Eco,280,5,5,5,1,2,5,2,2,4,3,5,5,5,2,0,0.0,satisfied +9626,118343,Female,disloyal Customer,24,Business travel,Eco,202,4,0,4,3,3,4,3,3,1,5,1,3,2,3,0,0.0,neutral or dissatisfied +9627,14445,Male,Loyal Customer,46,Business travel,Business,3774,3,3,3,3,4,2,4,4,4,4,4,1,4,4,0,0.0,satisfied +9628,72074,Male,Loyal Customer,22,Business travel,Eco,2556,1,2,2,2,1,1,1,1,2,2,3,4,4,1,0,0.0,neutral or dissatisfied +9629,67860,Female,Loyal Customer,69,Personal Travel,Eco,1431,2,1,2,1,2,1,1,1,1,2,1,3,1,3,34,34.0,neutral or dissatisfied +9630,9655,Female,Loyal Customer,60,Business travel,Business,3602,2,2,2,2,2,4,5,4,4,4,5,4,4,4,74,78.0,satisfied +9631,45149,Male,Loyal Customer,31,Business travel,Business,3543,1,1,5,1,5,5,5,5,5,3,1,5,3,5,43,40.0,satisfied +9632,53940,Female,Loyal Customer,16,Personal Travel,Eco,2007,2,5,2,4,3,2,3,3,3,5,5,5,4,3,3,0.0,neutral or dissatisfied +9633,41703,Female,Loyal Customer,38,Personal Travel,Eco Plus,936,1,4,1,4,3,1,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +9634,44072,Female,Loyal Customer,34,Business travel,Business,1829,1,1,1,1,5,4,3,4,4,4,4,3,4,2,65,129.0,satisfied +9635,13277,Female,Loyal Customer,66,Personal Travel,Eco,657,3,1,3,3,2,4,4,1,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +9636,113668,Female,Loyal Customer,15,Personal Travel,Eco,197,4,5,4,5,2,4,2,2,3,2,4,3,4,2,63,91.0,neutral or dissatisfied +9637,28929,Male,disloyal Customer,22,Business travel,Eco,1050,4,4,4,3,5,4,5,5,3,1,4,3,3,5,0,9.0,neutral or dissatisfied +9638,45099,Female,Loyal Customer,53,Business travel,Eco,157,5,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +9639,37867,Female,Loyal Customer,42,Business travel,Eco,937,3,2,2,2,3,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +9640,21413,Male,Loyal Customer,36,Business travel,Business,377,4,4,4,4,2,3,3,4,4,4,4,4,4,3,1,0.0,satisfied +9641,13169,Female,Loyal Customer,62,Personal Travel,Eco Plus,562,2,1,2,4,2,3,3,3,3,2,3,4,3,2,16,17.0,neutral or dissatisfied +9642,97820,Male,Loyal Customer,44,Business travel,Business,2626,1,1,5,1,5,4,4,2,2,3,2,4,2,5,14,0.0,satisfied +9643,96765,Male,disloyal Customer,19,Business travel,Business,994,5,0,5,4,5,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +9644,15815,Female,Loyal Customer,68,Personal Travel,Eco,143,4,3,4,2,3,3,4,5,5,4,5,1,5,3,0,0.0,neutral or dissatisfied +9645,98005,Male,Loyal Customer,38,Personal Travel,Eco Plus,616,3,4,3,3,3,3,3,3,3,2,3,3,3,3,7,0.0,neutral or dissatisfied +9646,55253,Male,Loyal Customer,37,Personal Travel,Eco,1009,1,3,1,2,1,1,1,1,3,4,3,1,3,1,50,31.0,neutral or dissatisfied +9647,71252,Male,Loyal Customer,56,Business travel,Business,2154,4,2,4,4,5,5,2,5,5,5,5,4,5,5,0,0.0,satisfied +9648,9390,Male,Loyal Customer,39,Business travel,Business,372,3,2,2,2,3,3,4,3,3,3,3,3,3,2,56,45.0,neutral or dissatisfied +9649,98427,Male,Loyal Customer,15,Personal Travel,Eco,1910,3,5,4,2,2,4,2,2,4,5,4,3,5,2,0,6.0,neutral or dissatisfied +9650,11221,Female,Loyal Customer,67,Personal Travel,Eco,247,2,4,2,5,5,5,4,4,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +9651,18631,Female,Loyal Customer,57,Personal Travel,Eco,190,2,5,2,1,3,4,2,1,1,2,1,4,1,2,66,67.0,neutral or dissatisfied +9652,11643,Male,Loyal Customer,49,Business travel,Business,837,3,3,3,3,3,5,4,4,4,4,4,3,4,3,25,17.0,satisfied +9653,55359,Male,disloyal Customer,36,Business travel,Business,413,3,3,3,3,2,3,2,2,4,3,4,5,4,2,54,74.0,neutral or dissatisfied +9654,26300,Male,Loyal Customer,44,Personal Travel,Eco,1199,2,4,2,3,3,2,3,3,3,4,4,2,3,3,0,2.0,neutral or dissatisfied +9655,123200,Male,Loyal Customer,50,Personal Travel,Eco,507,3,4,3,2,2,3,2,2,4,2,5,3,5,2,13,6.0,neutral or dissatisfied +9656,127961,Female,Loyal Customer,13,Personal Travel,Eco,1999,2,5,2,4,5,2,1,5,3,5,5,5,5,5,1,0.0,neutral or dissatisfied +9657,90482,Female,Loyal Customer,51,Business travel,Eco,581,3,5,5,5,3,4,3,3,3,3,3,1,3,2,4,0.0,neutral or dissatisfied +9658,54219,Female,Loyal Customer,57,Personal Travel,Business,1222,3,4,3,4,5,3,3,2,2,3,2,4,2,1,16,0.0,neutral or dissatisfied +9659,32314,Male,disloyal Customer,37,Business travel,Business,216,3,3,3,4,3,3,3,3,3,2,5,2,5,3,5,0.0,satisfied +9660,71770,Male,Loyal Customer,40,Business travel,Business,1829,2,2,2,2,3,5,5,5,5,5,5,4,5,3,0,7.0,satisfied +9661,69673,Female,Loyal Customer,17,Personal Travel,Eco,569,1,4,1,3,3,1,4,3,4,4,5,3,4,3,1,0.0,neutral or dissatisfied +9662,30962,Female,Loyal Customer,67,Personal Travel,Eco,836,2,4,2,5,4,5,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +9663,2821,Male,Loyal Customer,30,Business travel,Business,1637,4,4,4,4,3,3,3,3,4,5,5,3,5,3,0,0.0,satisfied +9664,109657,Female,disloyal Customer,15,Business travel,Eco,802,2,2,2,5,2,2,2,2,4,2,5,5,5,2,2,4.0,neutral or dissatisfied +9665,48465,Female,Loyal Customer,54,Business travel,Business,3540,1,1,1,1,1,4,4,4,4,5,4,1,4,3,18,21.0,satisfied +9666,114326,Female,Loyal Customer,14,Personal Travel,Eco,862,3,4,3,4,1,3,1,1,5,5,5,5,5,1,35,23.0,neutral or dissatisfied +9667,28718,Male,Loyal Customer,40,Business travel,Eco,1054,4,1,1,1,4,4,4,5,2,5,4,4,5,4,0,0.0,satisfied +9668,66700,Female,Loyal Customer,59,Business travel,Business,3397,3,3,3,3,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +9669,52772,Male,Loyal Customer,33,Business travel,Business,1874,1,2,2,2,1,1,1,1,1,2,2,1,4,1,103,89.0,neutral or dissatisfied +9670,44657,Male,disloyal Customer,48,Business travel,Eco,173,2,0,2,4,5,2,5,5,2,2,1,5,4,5,19,27.0,neutral or dissatisfied +9671,53148,Female,Loyal Customer,49,Business travel,Eco Plus,413,4,2,2,2,5,4,4,4,4,4,4,2,4,5,2,0.0,satisfied +9672,44547,Female,Loyal Customer,51,Personal Travel,Eco,157,2,4,0,3,4,4,4,5,5,0,5,3,5,2,0,22.0,neutral or dissatisfied +9673,21481,Female,Loyal Customer,48,Business travel,Eco,164,5,5,5,5,5,1,5,4,4,5,4,3,4,3,17,8.0,satisfied +9674,107955,Male,Loyal Customer,55,Business travel,Business,825,3,3,3,3,4,4,4,5,5,5,5,3,5,3,4,10.0,satisfied +9675,67735,Male,disloyal Customer,24,Business travel,Eco,1171,2,2,2,3,1,2,5,1,5,3,5,4,4,1,7,0.0,neutral or dissatisfied +9676,86626,Male,Loyal Customer,45,Business travel,Business,3516,4,4,4,4,4,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +9677,120856,Male,disloyal Customer,18,Business travel,Eco,920,2,2,2,1,3,2,3,3,5,3,4,4,5,3,0,4.0,neutral or dissatisfied +9678,59450,Female,Loyal Customer,46,Business travel,Business,3217,2,2,2,2,4,5,4,4,4,4,4,3,4,3,5,9.0,satisfied +9679,7575,Female,disloyal Customer,43,Business travel,Business,594,4,4,4,4,4,4,4,4,5,3,5,5,4,4,11,0.0,neutral or dissatisfied +9680,21768,Female,Loyal Customer,45,Business travel,Business,3942,3,3,3,3,1,1,5,5,5,5,5,4,5,4,82,62.0,satisfied +9681,49157,Female,Loyal Customer,33,Business travel,Eco,89,0,0,0,2,5,0,5,5,3,4,1,2,1,5,0,0.0,satisfied +9682,30271,Female,Loyal Customer,33,Business travel,Business,1024,2,2,2,2,1,2,3,2,2,2,2,2,2,1,61,56.0,neutral or dissatisfied +9683,75251,Female,Loyal Customer,32,Personal Travel,Eco,1744,1,3,0,4,2,0,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +9684,40393,Male,Loyal Customer,44,Business travel,Business,3317,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +9685,77317,Male,Loyal Customer,46,Business travel,Business,3132,4,4,4,4,3,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +9686,112998,Male,disloyal Customer,24,Business travel,Eco,1797,3,3,3,3,3,3,3,3,3,2,2,1,2,3,116,104.0,neutral or dissatisfied +9687,65870,Male,Loyal Customer,59,Personal Travel,Eco,1389,2,5,2,1,2,2,2,2,2,5,5,4,2,2,0,0.0,neutral or dissatisfied +9688,34740,Female,Loyal Customer,30,Business travel,Business,2984,4,4,4,4,5,5,5,5,3,4,5,4,3,5,0,0.0,satisfied +9689,67678,Female,Loyal Customer,50,Business travel,Business,1171,4,4,3,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +9690,51149,Male,Loyal Customer,65,Personal Travel,Eco,109,3,4,3,3,2,3,2,2,4,2,4,3,5,2,0,1.0,neutral or dissatisfied +9691,43182,Female,disloyal Customer,22,Business travel,Eco,282,4,3,4,2,3,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +9692,1142,Male,Loyal Customer,36,Personal Travel,Eco,140,3,5,3,1,5,3,3,5,2,5,4,3,1,5,81,75.0,neutral or dissatisfied +9693,83970,Female,Loyal Customer,46,Business travel,Eco,321,4,4,4,4,3,3,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +9694,54529,Male,Loyal Customer,37,Personal Travel,Eco,925,3,4,3,3,4,3,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +9695,102155,Female,Loyal Customer,62,Business travel,Business,391,1,1,1,1,4,5,5,5,5,5,5,3,5,3,3,0.0,satisfied +9696,39222,Male,disloyal Customer,21,Business travel,Eco,67,3,0,3,4,4,3,2,4,4,1,5,2,3,4,8,3.0,neutral or dissatisfied +9697,6913,Male,Loyal Customer,27,Personal Travel,Eco,265,1,4,1,3,5,1,5,5,1,5,4,3,1,5,0,0.0,neutral or dissatisfied +9698,79436,Male,Loyal Customer,42,Business travel,Business,2573,0,4,0,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9699,39930,Female,Loyal Customer,42,Business travel,Business,2260,5,5,5,5,5,5,5,4,4,4,4,3,4,1,0,1.0,satisfied +9700,29524,Female,Loyal Customer,51,Business travel,Business,2577,1,1,2,1,1,3,5,4,4,4,4,5,4,1,0,1.0,satisfied +9701,128003,Male,Loyal Customer,65,Personal Travel,Eco,1488,1,5,1,2,1,1,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +9702,114509,Female,Loyal Customer,57,Business travel,Business,337,3,3,3,3,5,3,3,3,3,3,3,3,3,4,5,0.0,neutral or dissatisfied +9703,106059,Female,Loyal Customer,23,Personal Travel,Eco,903,3,3,3,3,1,3,4,1,1,1,4,4,3,1,12,13.0,neutral or dissatisfied +9704,21202,Female,Loyal Customer,28,Business travel,Business,3850,0,4,0,4,5,5,5,5,1,3,5,2,5,5,0,0.0,satisfied +9705,60004,Female,Loyal Customer,42,Personal Travel,Eco,1023,2,1,2,4,1,4,4,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +9706,124387,Male,Loyal Customer,7,Personal Travel,Eco,808,4,2,4,4,5,4,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +9707,31678,Male,Loyal Customer,58,Business travel,Business,967,2,5,5,5,3,3,3,2,2,2,2,2,2,4,47,47.0,neutral or dissatisfied +9708,70135,Female,disloyal Customer,57,Business travel,Eco,460,2,0,2,4,5,2,5,5,4,3,1,4,3,5,0,0.0,neutral or dissatisfied +9709,125625,Male,disloyal Customer,37,Business travel,Business,814,3,3,3,4,3,3,3,3,3,2,5,5,4,3,8,23.0,satisfied +9710,98101,Female,Loyal Customer,35,Personal Travel,Eco,265,2,4,2,4,4,2,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +9711,13432,Male,Loyal Customer,47,Business travel,Business,3446,2,2,2,2,4,3,2,4,4,4,4,1,4,4,0,0.0,satisfied +9712,92590,Female,disloyal Customer,44,Business travel,Business,2342,1,1,1,4,2,1,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +9713,120378,Female,Loyal Customer,59,Business travel,Business,3637,4,2,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +9714,95864,Female,Loyal Customer,29,Business travel,Business,3155,2,2,2,2,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +9715,2436,Female,Loyal Customer,49,Personal Travel,Eco,641,4,5,4,3,2,4,5,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +9716,63776,Male,Loyal Customer,32,Business travel,Business,1721,5,5,5,5,5,5,5,5,5,2,5,3,4,5,6,0.0,satisfied +9717,19990,Female,Loyal Customer,30,Business travel,Business,646,4,3,4,4,5,5,5,5,2,2,4,2,1,5,17,7.0,satisfied +9718,26424,Female,Loyal Customer,22,Business travel,Eco,842,4,2,2,2,4,4,3,4,2,5,2,3,3,4,0,0.0,satisfied +9719,67660,Female,Loyal Customer,37,Business travel,Business,1832,1,1,1,1,4,5,5,2,2,2,2,4,2,4,2,0.0,satisfied +9720,96335,Male,Loyal Customer,48,Personal Travel,Business,1609,3,2,2,3,5,2,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +9721,25814,Female,Loyal Customer,46,Business travel,Business,1747,2,4,5,4,4,3,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +9722,106658,Female,Loyal Customer,60,Business travel,Business,1590,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +9723,56433,Female,disloyal Customer,27,Business travel,Eco,719,2,2,2,4,5,2,3,5,3,1,4,3,4,5,0,5.0,neutral or dissatisfied +9724,91692,Female,Loyal Customer,52,Business travel,Business,626,5,5,5,5,2,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +9725,80735,Male,Loyal Customer,57,Business travel,Business,2033,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +9726,51458,Female,Loyal Customer,21,Personal Travel,Eco Plus,326,3,4,3,3,1,3,1,1,1,4,3,4,3,1,4,10.0,neutral or dissatisfied +9727,123866,Male,Loyal Customer,24,Business travel,Business,3480,1,4,4,4,1,1,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +9728,112260,Male,Loyal Customer,55,Business travel,Business,1506,5,5,5,5,5,5,4,5,5,5,5,3,5,3,16,6.0,satisfied +9729,111884,Male,Loyal Customer,45,Business travel,Business,2671,3,4,4,4,3,2,3,3,3,3,3,1,3,3,16,28.0,neutral or dissatisfied +9730,92111,Female,Loyal Customer,33,Personal Travel,Eco,1532,1,4,1,3,5,1,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +9731,2706,Male,Loyal Customer,46,Personal Travel,Eco,562,1,3,1,2,1,1,1,4,1,3,3,1,2,1,145,138.0,neutral or dissatisfied +9732,9146,Female,disloyal Customer,23,Business travel,Eco,227,4,4,4,3,2,4,2,2,5,3,5,4,5,2,92,86.0,satisfied +9733,47121,Female,disloyal Customer,19,Business travel,Eco Plus,784,2,2,2,4,4,2,4,4,4,1,3,2,4,4,0,4.0,neutral or dissatisfied +9734,19542,Female,disloyal Customer,43,Business travel,Eco,173,2,0,2,1,5,2,5,5,4,2,1,3,2,5,73,73.0,neutral or dissatisfied +9735,29779,Female,Loyal Customer,31,Personal Travel,Business,539,3,5,3,1,3,3,3,3,4,3,5,4,4,3,1,4.0,neutral or dissatisfied +9736,32726,Female,disloyal Customer,38,Business travel,Eco,101,4,4,4,5,3,4,3,3,4,2,5,2,3,3,0,0.0,satisfied +9737,84232,Female,Loyal Customer,11,Personal Travel,Eco,432,4,4,4,2,1,4,1,1,3,1,3,4,1,1,26,39.0,neutral or dissatisfied +9738,69601,Female,Loyal Customer,41,Personal Travel,Eco,2475,1,4,1,4,1,1,1,3,5,5,4,1,4,1,0,0.0,neutral or dissatisfied +9739,10843,Male,Loyal Customer,43,Business travel,Business,134,1,5,5,5,2,4,4,2,2,2,1,1,2,3,9,14.0,neutral or dissatisfied +9740,25884,Male,disloyal Customer,25,Business travel,Eco,907,3,3,3,4,3,3,2,3,3,4,3,3,2,3,1,0.0,neutral or dissatisfied +9741,63551,Female,Loyal Customer,58,Business travel,Business,1009,2,2,2,2,4,4,5,5,5,5,5,5,5,3,107,102.0,satisfied +9742,127553,Female,Loyal Customer,12,Personal Travel,Eco,1009,2,4,2,4,4,2,2,4,1,2,4,3,3,4,0,0.0,neutral or dissatisfied +9743,124524,Male,Loyal Customer,33,Business travel,Business,3187,5,5,5,5,4,4,4,4,4,5,4,3,5,4,0,5.0,satisfied +9744,115249,Female,Loyal Customer,22,Business travel,Business,2058,2,1,1,1,2,2,2,2,1,4,1,2,2,2,19,19.0,neutral or dissatisfied +9745,114540,Male,Loyal Customer,69,Personal Travel,Business,337,3,5,3,3,4,5,4,2,2,3,3,5,2,4,70,56.0,neutral or dissatisfied +9746,128326,Male,Loyal Customer,42,Business travel,Business,2829,1,5,1,1,2,2,2,5,5,4,4,2,3,2,198,170.0,satisfied +9747,61311,Female,Loyal Customer,53,Business travel,Business,2291,1,1,1,1,4,4,4,4,4,4,4,4,4,4,4,3.0,satisfied +9748,129817,Male,Loyal Customer,47,Personal Travel,Eco,337,4,5,4,1,2,4,2,2,4,2,5,4,4,2,77,79.0,neutral or dissatisfied +9749,29561,Male,disloyal Customer,50,Business travel,Eco,1448,4,4,4,4,3,4,3,3,3,2,5,4,1,3,0,0.0,satisfied +9750,108374,Female,Loyal Customer,23,Personal Travel,Eco,1728,5,5,4,2,4,4,4,4,3,5,5,4,4,4,0,2.0,satisfied +9751,13135,Male,Loyal Customer,40,Personal Travel,Eco,427,2,1,2,4,5,2,5,5,2,2,4,4,4,5,1,0.0,neutral or dissatisfied +9752,34342,Female,Loyal Customer,45,Personal Travel,Eco,846,2,4,2,4,5,4,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +9753,84090,Male,Loyal Customer,47,Personal Travel,Eco,773,4,4,4,3,4,4,4,4,2,1,3,4,3,4,8,0.0,neutral or dissatisfied +9754,29577,Female,Loyal Customer,42,Business travel,Eco,909,4,5,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9755,109428,Male,Loyal Customer,49,Personal Travel,Business,992,3,5,3,5,3,1,1,4,5,5,4,1,4,1,154,140.0,neutral or dissatisfied +9756,11132,Female,Loyal Customer,7,Personal Travel,Eco,458,3,4,3,1,4,3,4,4,2,1,2,4,2,4,1,10.0,neutral or dissatisfied +9757,13578,Male,Loyal Customer,14,Personal Travel,Eco,227,1,5,1,2,4,1,5,4,5,2,4,4,4,4,33,64.0,neutral or dissatisfied +9758,51350,Male,Loyal Customer,28,Business travel,Eco Plus,337,1,0,0,4,2,0,2,2,1,4,3,4,3,2,3,4.0,neutral or dissatisfied +9759,122238,Female,Loyal Customer,37,Business travel,Business,3150,1,1,1,1,1,4,3,1,1,1,1,2,1,4,0,10.0,neutral or dissatisfied +9760,23546,Female,Loyal Customer,30,Business travel,Business,3014,5,5,5,5,4,4,4,4,5,3,4,4,1,4,7,21.0,satisfied +9761,102521,Male,Loyal Customer,8,Personal Travel,Eco,236,4,3,4,3,2,4,2,2,5,5,2,4,1,2,20,12.0,neutral or dissatisfied +9762,10565,Female,Loyal Customer,58,Business travel,Business,3581,3,3,3,3,5,5,5,3,3,4,5,5,4,5,182,182.0,satisfied +9763,79574,Female,disloyal Customer,30,Business travel,Eco,762,3,3,3,3,5,3,2,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +9764,50851,Female,Loyal Customer,40,Personal Travel,Eco,421,3,3,3,3,4,3,4,4,4,2,4,2,3,4,44,42.0,neutral or dissatisfied +9765,111565,Male,Loyal Customer,37,Business travel,Business,2179,2,5,5,5,5,4,4,2,2,2,2,4,2,4,15,8.0,neutral or dissatisfied +9766,96378,Male,Loyal Customer,24,Business travel,Business,1407,2,2,2,2,4,4,4,4,4,2,4,5,5,4,35,7.0,satisfied +9767,40773,Female,disloyal Customer,23,Business travel,Eco,558,5,0,5,1,3,5,3,3,3,4,3,2,2,3,0,0.0,satisfied +9768,25985,Female,Loyal Customer,23,Business travel,Business,577,1,1,1,1,3,3,3,3,5,5,3,4,5,3,6,0.0,satisfied +9769,70310,Female,disloyal Customer,37,Business travel,Business,334,3,3,3,3,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +9770,46845,Female,disloyal Customer,49,Business travel,Eco,776,1,2,2,5,2,2,2,2,1,4,3,5,3,2,0,0.0,neutral or dissatisfied +9771,92654,Female,Loyal Customer,51,Personal Travel,Eco,453,1,5,1,4,2,5,5,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +9772,30681,Male,Loyal Customer,25,Business travel,Business,2101,2,2,2,2,5,5,5,5,1,1,3,5,1,5,98,113.0,satisfied +9773,29906,Female,disloyal Customer,38,Business travel,Eco,548,3,5,3,2,4,3,4,4,3,1,5,2,2,4,0,0.0,neutral or dissatisfied +9774,47563,Male,Loyal Customer,23,Personal Travel,Eco Plus,558,1,4,1,2,1,1,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +9775,69059,Female,disloyal Customer,25,Business travel,Eco,1389,3,3,3,3,5,3,5,5,1,2,4,3,3,5,17,0.0,neutral or dissatisfied +9776,112513,Male,Loyal Customer,62,Personal Travel,Eco,846,1,4,1,5,5,1,5,5,5,2,4,5,4,5,20,4.0,neutral or dissatisfied +9777,86645,Male,Loyal Customer,77,Business travel,Eco,346,4,4,4,4,4,4,4,4,1,2,1,4,2,4,4,0.0,satisfied +9778,113505,Male,Loyal Customer,48,Business travel,Eco,197,1,3,3,3,1,1,1,1,2,3,3,3,2,1,0,0.0,neutral or dissatisfied +9779,77115,Male,Loyal Customer,21,Business travel,Business,1481,2,2,2,2,3,5,3,3,2,3,2,4,2,3,0,0.0,satisfied +9780,36486,Female,disloyal Customer,29,Business travel,Business,1249,2,2,2,3,5,2,5,5,4,4,3,2,4,5,21,63.0,neutral or dissatisfied +9781,30368,Female,Loyal Customer,48,Business travel,Business,2996,3,5,5,5,4,3,4,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +9782,49047,Female,Loyal Customer,59,Business travel,Business,2579,1,1,1,1,3,4,1,4,4,4,5,3,4,4,0,59.0,satisfied +9783,96364,Male,Loyal Customer,25,Personal Travel,Business,1246,1,4,1,4,2,1,2,2,5,3,4,5,5,2,4,8.0,neutral or dissatisfied +9784,78374,Female,Loyal Customer,49,Business travel,Business,980,5,5,5,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +9785,21543,Female,Loyal Customer,50,Personal Travel,Eco,164,3,1,3,1,1,1,2,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +9786,16651,Male,disloyal Customer,24,Business travel,Eco,488,1,0,1,4,4,1,4,4,4,5,5,1,2,4,106,90.0,neutral or dissatisfied +9787,54798,Male,disloyal Customer,37,Business travel,Eco,862,1,1,1,3,4,1,4,4,5,3,1,3,1,4,8,0.0,neutral or dissatisfied +9788,108062,Male,Loyal Customer,45,Business travel,Business,1166,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,2.0,satisfied +9789,53764,Male,disloyal Customer,10,Business travel,Eco,1195,4,4,4,3,4,4,3,4,5,4,1,1,1,4,0,0.0,neutral or dissatisfied +9790,49514,Female,Loyal Customer,33,Business travel,Business,1804,2,2,2,2,4,3,2,5,5,4,5,3,5,2,0,1.0,satisfied +9791,46677,Female,Loyal Customer,31,Personal Travel,Eco,73,1,2,1,4,3,1,3,3,4,5,3,3,4,3,0,20.0,neutral or dissatisfied +9792,49819,Female,Loyal Customer,52,Business travel,Eco,363,5,3,3,3,4,5,2,5,5,5,5,5,5,4,0,0.0,satisfied +9793,100913,Female,Loyal Customer,9,Personal Travel,Eco,377,2,4,2,1,3,2,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +9794,25442,Female,Loyal Customer,63,Business travel,Eco,669,3,5,5,5,1,4,3,3,3,3,3,1,3,1,4,3.0,neutral or dissatisfied +9795,41746,Female,Loyal Customer,27,Personal Travel,Eco,695,3,3,3,4,4,3,4,4,4,3,4,4,3,4,7,14.0,neutral or dissatisfied +9796,78171,Female,Loyal Customer,32,Business travel,Business,2639,3,2,2,2,3,3,3,3,3,1,4,3,3,3,0,0.0,neutral or dissatisfied +9797,111575,Male,disloyal Customer,17,Business travel,Eco,794,4,4,4,3,5,4,5,5,2,3,4,3,4,5,22,7.0,neutral or dissatisfied +9798,113839,Male,Loyal Customer,47,Personal Travel,Eco Plus,397,1,5,1,2,5,1,1,5,5,2,4,4,4,5,4,0.0,neutral or dissatisfied +9799,10304,Female,Loyal Customer,52,Business travel,Business,3676,1,1,1,1,5,5,5,4,2,4,5,5,5,5,155,152.0,satisfied +9800,543,Male,Loyal Customer,53,Business travel,Business,3460,1,1,1,1,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +9801,105601,Female,Loyal Customer,36,Business travel,Business,2493,2,2,2,2,4,5,4,5,5,5,5,4,5,3,74,70.0,satisfied +9802,128991,Female,Loyal Customer,46,Business travel,Business,236,3,5,3,3,5,4,4,5,5,5,5,5,5,5,0,11.0,satisfied +9803,95765,Female,Loyal Customer,15,Personal Travel,Eco,453,1,1,1,2,1,1,1,1,2,5,2,4,2,1,13,7.0,neutral or dissatisfied +9804,71363,Female,Loyal Customer,39,Business travel,Business,258,1,1,5,1,5,5,5,4,4,4,4,5,4,5,170,174.0,satisfied +9805,62814,Male,Loyal Customer,57,Personal Travel,Eco,2504,1,5,1,5,5,1,5,5,3,3,4,3,5,5,13,0.0,neutral or dissatisfied +9806,47718,Male,Loyal Customer,67,Personal Travel,Eco Plus,1504,3,1,3,3,4,3,4,4,1,4,2,4,3,4,3,0.0,neutral or dissatisfied +9807,128590,Male,Loyal Customer,27,Business travel,Business,2552,3,5,5,5,3,3,3,3,3,4,3,1,3,3,0,13.0,neutral or dissatisfied +9808,47593,Female,disloyal Customer,37,Business travel,Eco,1482,5,5,5,1,3,5,3,3,5,4,5,4,1,3,18,13.0,satisfied +9809,19198,Female,Loyal Customer,19,Business travel,Business,542,1,5,5,5,1,1,1,1,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +9810,67288,Male,Loyal Customer,42,Personal Travel,Eco,1121,2,4,2,3,5,2,1,5,5,3,3,3,4,5,0,0.0,neutral or dissatisfied +9811,50322,Male,disloyal Customer,20,Business travel,Eco,209,4,0,4,4,4,4,4,4,1,1,2,1,2,4,0,0.0,satisfied +9812,12791,Male,Loyal Customer,40,Business travel,Business,489,5,5,5,5,3,5,3,5,5,5,5,3,5,4,0,0.0,satisfied +9813,90606,Male,Loyal Customer,49,Business travel,Business,2213,4,2,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +9814,21648,Male,Loyal Customer,52,Personal Travel,Eco Plus,780,5,4,5,5,2,5,2,2,5,2,5,4,5,2,21,12.0,satisfied +9815,119602,Male,Loyal Customer,35,Business travel,Business,1979,1,1,4,1,4,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +9816,118795,Male,Loyal Customer,16,Personal Travel,Eco,621,3,4,3,3,4,3,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +9817,3720,Female,Loyal Customer,24,Personal Travel,Eco,427,2,4,2,3,4,2,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +9818,117947,Male,disloyal Customer,28,Business travel,Eco,255,1,2,1,4,4,1,2,4,2,2,4,2,3,4,71,70.0,neutral or dissatisfied +9819,37659,Male,Loyal Customer,66,Personal Travel,Eco,1097,1,1,1,4,5,1,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +9820,21356,Female,Loyal Customer,52,Personal Travel,Eco,674,3,5,3,1,3,5,5,3,2,5,5,5,5,5,132,121.0,neutral or dissatisfied +9821,66331,Female,Loyal Customer,27,Business travel,Eco Plus,852,2,5,5,5,2,2,2,2,2,1,4,3,3,2,61,58.0,neutral or dissatisfied +9822,77648,Male,Loyal Customer,45,Business travel,Business,731,1,1,1,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +9823,3204,Female,Loyal Customer,15,Personal Travel,Eco,585,3,4,3,3,3,3,2,3,2,5,2,4,2,3,0,1.0,neutral or dissatisfied +9824,65260,Male,Loyal Customer,20,Business travel,Eco Plus,224,4,5,1,5,4,4,2,4,1,3,4,4,3,4,2,7.0,neutral or dissatisfied +9825,9623,Male,Loyal Customer,24,Business travel,Eco Plus,229,1,3,3,3,1,1,3,1,2,2,4,3,4,1,4,0.0,neutral or dissatisfied +9826,15357,Male,Loyal Customer,33,Business travel,Eco,377,4,5,5,5,4,4,4,4,4,4,1,3,2,4,0,0.0,satisfied +9827,76664,Male,Loyal Customer,29,Personal Travel,Eco,547,4,0,4,1,1,4,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +9828,78865,Male,Loyal Customer,45,Business travel,Business,1995,3,3,3,3,3,4,5,5,5,5,5,5,5,3,18,5.0,satisfied +9829,113276,Male,Loyal Customer,37,Business travel,Business,3424,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,7.0,satisfied +9830,16212,Female,Loyal Customer,32,Business travel,Eco Plus,277,5,4,4,4,5,5,5,5,3,1,2,3,3,5,0,0.0,satisfied +9831,49224,Female,disloyal Customer,33,Business travel,Eco,190,4,0,4,5,3,4,3,3,3,1,4,5,4,3,0,0.0,neutral or dissatisfied +9832,57939,Female,disloyal Customer,20,Business travel,Eco,837,4,4,4,2,5,4,5,5,3,2,5,3,4,5,2,20.0,satisfied +9833,61831,Male,Loyal Customer,33,Business travel,Business,1609,2,2,2,2,5,4,5,5,5,2,4,3,4,5,0,0.0,satisfied +9834,12040,Female,Loyal Customer,44,Business travel,Business,376,1,1,1,1,3,5,5,3,3,3,3,2,3,1,0,0.0,satisfied +9835,90920,Female,Loyal Customer,44,Business travel,Eco,246,5,5,5,5,3,4,3,5,5,5,5,3,5,5,0,7.0,satisfied +9836,83331,Male,Loyal Customer,34,Business travel,Business,2105,2,4,4,4,2,1,2,2,2,2,2,2,2,3,4,10.0,neutral or dissatisfied +9837,44825,Male,Loyal Customer,47,Business travel,Business,2306,3,5,5,5,2,4,4,3,3,3,3,4,3,1,9,41.0,neutral or dissatisfied +9838,47463,Female,Loyal Customer,63,Personal Travel,Eco,599,4,4,4,3,4,4,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +9839,31645,Female,Loyal Customer,42,Business travel,Eco,846,4,3,3,3,3,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +9840,31377,Female,disloyal Customer,30,Business travel,Eco Plus,977,4,4,4,3,4,4,4,4,2,1,5,2,4,4,0,0.0,satisfied +9841,89664,Female,Loyal Customer,58,Business travel,Business,2843,1,3,3,3,3,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +9842,48423,Female,disloyal Customer,28,Business travel,Eco,948,4,4,4,4,5,4,5,5,5,1,4,1,5,5,92,91.0,satisfied +9843,67368,Male,Loyal Customer,40,Business travel,Business,592,3,3,3,3,3,4,4,4,4,4,4,3,4,5,2,0.0,satisfied +9844,57125,Female,Loyal Customer,35,Personal Travel,Eco,1222,3,3,3,1,1,3,1,1,1,5,3,1,2,1,100,91.0,neutral or dissatisfied +9845,52379,Male,Loyal Customer,48,Personal Travel,Eco,451,3,3,3,2,5,3,5,5,3,1,2,2,2,5,0,0.0,neutral or dissatisfied +9846,72914,Male,disloyal Customer,26,Business travel,Business,1089,4,4,4,2,2,4,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +9847,34786,Male,Loyal Customer,11,Personal Travel,Eco,209,2,5,0,4,2,0,2,2,1,5,2,4,5,2,17,18.0,neutral or dissatisfied +9848,124726,Male,Loyal Customer,62,Personal Travel,Eco,399,2,4,2,2,5,2,5,5,3,2,4,4,4,5,0,11.0,neutral or dissatisfied +9849,86045,Male,Loyal Customer,48,Personal Travel,Eco,447,3,4,0,3,3,0,3,3,3,2,4,2,3,3,8,6.0,neutral or dissatisfied +9850,25741,Male,Loyal Customer,53,Business travel,Eco Plus,447,2,2,2,2,1,2,1,1,3,1,5,2,4,1,25,14.0,satisfied +9851,22970,Female,Loyal Customer,25,Business travel,Business,2926,2,4,4,4,2,2,2,2,4,1,4,1,3,2,17,16.0,neutral or dissatisfied +9852,38025,Female,Loyal Customer,33,Business travel,Business,3904,1,1,1,1,2,1,2,4,4,4,4,5,4,5,3,6.0,satisfied +9853,25382,Female,Loyal Customer,22,Personal Travel,Eco,591,1,4,1,4,2,1,2,2,4,4,5,4,4,2,1,0.0,neutral or dissatisfied +9854,42463,Male,Loyal Customer,25,Business travel,Eco Plus,926,4,3,3,3,4,4,3,4,5,4,4,5,3,4,0,0.0,satisfied +9855,110494,Female,Loyal Customer,26,Personal Travel,Eco,798,1,4,1,1,4,1,4,4,5,2,2,2,4,4,0,0.0,neutral or dissatisfied +9856,58688,Male,Loyal Customer,56,Business travel,Business,299,1,1,1,1,3,4,4,4,4,4,4,4,4,5,10,27.0,satisfied +9857,103777,Male,Loyal Customer,54,Business travel,Business,2150,5,5,5,5,5,4,4,5,5,5,5,4,5,3,82,75.0,satisfied +9858,63142,Female,Loyal Customer,10,Personal Travel,Business,447,3,5,3,1,1,3,3,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +9859,20845,Male,Loyal Customer,69,Personal Travel,Eco,357,3,1,3,3,4,3,4,4,1,2,2,2,3,4,0,8.0,neutral or dissatisfied +9860,115056,Male,disloyal Customer,25,Business travel,Business,446,2,0,2,1,3,2,3,3,4,2,5,3,4,3,31,24.0,neutral or dissatisfied +9861,7962,Male,Loyal Customer,15,Personal Travel,Eco,594,5,1,5,3,1,5,1,1,3,2,4,4,3,1,0,0.0,satisfied +9862,104418,Female,Loyal Customer,37,Business travel,Business,1138,4,4,4,4,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +9863,129364,Male,disloyal Customer,22,Business travel,Eco,1389,4,4,4,4,5,4,5,5,4,5,4,5,5,5,1,0.0,satisfied +9864,19330,Female,Loyal Customer,31,Business travel,Business,2290,4,4,4,4,4,4,4,4,2,2,4,2,3,4,9,0.0,neutral or dissatisfied +9865,114403,Female,Loyal Customer,49,Business travel,Business,2763,1,1,1,1,4,4,5,5,5,5,5,4,5,3,30,33.0,satisfied +9866,20422,Male,Loyal Customer,41,Business travel,Business,299,2,5,5,5,2,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +9867,2955,Female,Loyal Customer,48,Business travel,Business,1831,5,5,2,5,2,4,4,2,2,3,2,3,2,4,0,0.0,satisfied +9868,3462,Male,Loyal Customer,62,Business travel,Eco Plus,315,3,1,1,1,3,3,3,3,2,5,3,2,4,3,0,7.0,neutral or dissatisfied +9869,56933,Male,Loyal Customer,49,Business travel,Business,2454,2,5,5,5,2,2,2,3,1,3,2,2,2,2,2,20.0,neutral or dissatisfied +9870,23014,Male,Loyal Customer,12,Business travel,Eco Plus,817,5,1,1,1,5,5,3,5,2,1,3,4,4,5,0,0.0,satisfied +9871,41718,Female,Loyal Customer,61,Business travel,Eco Plus,1262,2,5,5,5,3,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +9872,75196,Female,Loyal Customer,53,Business travel,Business,1744,2,2,2,2,3,2,3,2,2,3,2,2,2,4,8,0.0,neutral or dissatisfied +9873,10798,Male,Loyal Customer,43,Business travel,Business,1885,2,2,5,2,2,4,5,4,4,4,4,3,4,5,32,26.0,satisfied +9874,129386,Female,Loyal Customer,10,Personal Travel,Eco,2454,2,5,2,3,5,2,1,5,3,5,3,4,4,5,0,0.0,neutral or dissatisfied +9875,2991,Male,Loyal Customer,10,Personal Travel,Business,922,5,2,5,4,5,5,5,5,1,4,3,1,4,5,0,0.0,satisfied +9876,129658,Female,disloyal Customer,24,Business travel,Eco,337,2,2,2,2,1,2,1,1,2,4,2,3,2,1,0,0.0,neutral or dissatisfied +9877,95993,Female,Loyal Customer,51,Business travel,Business,1235,3,3,3,3,4,5,5,4,4,4,4,3,4,5,1,0.0,satisfied +9878,62448,Male,Loyal Customer,20,Business travel,Business,1726,5,5,5,5,2,2,2,2,5,5,5,5,4,2,14,0.0,satisfied +9879,99985,Female,Loyal Customer,55,Business travel,Business,2576,1,1,1,1,2,4,4,4,4,4,4,5,4,3,14,18.0,satisfied +9880,58939,Male,Loyal Customer,42,Business travel,Business,888,2,2,2,2,3,5,5,5,5,5,5,3,5,3,3,0.0,satisfied +9881,13654,Female,Loyal Customer,24,Business travel,Business,196,2,1,1,1,4,3,2,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +9882,117842,Female,Loyal Customer,53,Personal Travel,Eco Plus,328,3,3,3,2,3,4,5,3,3,3,5,5,3,1,0,0.0,neutral or dissatisfied +9883,104206,Female,Loyal Customer,46,Business travel,Business,3220,1,1,1,1,5,4,5,5,5,5,5,4,5,5,32,28.0,satisfied +9884,23477,Male,Loyal Customer,7,Personal Travel,Eco,576,2,5,2,1,1,2,1,1,3,2,5,4,4,1,0,9.0,neutral or dissatisfied +9885,54396,Male,Loyal Customer,42,Business travel,Eco,305,4,2,2,2,5,4,5,5,5,1,3,3,4,5,2,0.0,satisfied +9886,18106,Female,disloyal Customer,36,Business travel,Eco Plus,610,1,1,1,1,1,1,1,1,3,1,3,4,4,1,0,0.0,neutral or dissatisfied +9887,91263,Female,Loyal Customer,12,Personal Travel,Eco,581,3,2,3,2,2,3,2,2,3,2,3,3,3,2,8,0.0,neutral or dissatisfied +9888,89884,Male,Loyal Customer,27,Business travel,Business,1310,1,4,1,1,2,2,2,2,4,3,4,5,5,2,0,1.0,satisfied +9889,86421,Male,Loyal Customer,26,Business travel,Business,762,3,5,5,5,3,3,3,3,4,5,2,2,2,3,0,7.0,neutral or dissatisfied +9890,89918,Male,disloyal Customer,27,Business travel,Eco,1501,2,2,2,2,3,2,3,3,3,1,2,1,2,3,0,0.0,neutral or dissatisfied +9891,112566,Female,Loyal Customer,9,Personal Travel,Business,602,2,4,2,1,2,2,2,2,5,3,4,4,5,2,7,2.0,neutral or dissatisfied +9892,106764,Female,Loyal Customer,44,Personal Travel,Eco,837,2,2,2,3,4,4,4,4,4,2,4,4,4,1,23,15.0,neutral or dissatisfied +9893,39116,Male,disloyal Customer,49,Business travel,Eco,190,2,4,2,4,1,2,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +9894,87153,Male,Loyal Customer,46,Business travel,Business,946,3,3,3,3,5,5,4,4,4,4,4,3,4,4,13,0.0,satisfied +9895,110782,Female,Loyal Customer,67,Business travel,Business,2359,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +9896,45560,Female,Loyal Customer,50,Business travel,Business,1199,5,5,5,5,2,5,2,4,4,4,4,3,4,2,29,27.0,satisfied +9897,105483,Female,Loyal Customer,26,Business travel,Business,516,1,5,5,5,1,2,1,1,4,5,3,4,4,1,13,23.0,neutral or dissatisfied +9898,22374,Female,Loyal Customer,37,Business travel,Business,208,3,4,4,4,3,3,4,2,2,3,3,4,2,2,0,0.0,neutral or dissatisfied +9899,117024,Male,Loyal Customer,53,Business travel,Business,325,2,2,2,2,4,4,5,4,4,4,4,5,4,3,27,24.0,satisfied +9900,12211,Male,Loyal Customer,18,Business travel,Business,2687,4,4,4,4,4,4,5,4,5,2,5,5,4,4,6,0.0,satisfied +9901,48797,Male,disloyal Customer,50,Business travel,Business,421,1,1,1,2,3,1,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +9902,18963,Male,Loyal Customer,24,Business travel,Eco Plus,448,4,1,5,1,4,4,5,4,2,4,5,5,1,4,0,0.0,satisfied +9903,99584,Female,Loyal Customer,49,Personal Travel,Eco,930,2,4,2,1,4,5,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +9904,15570,Female,disloyal Customer,37,Business travel,Eco,228,1,4,1,5,3,1,1,3,4,2,5,2,1,3,0,0.0,neutral or dissatisfied +9905,6896,Female,disloyal Customer,23,Business travel,Eco,265,1,4,1,4,2,1,4,2,1,1,4,2,3,2,33,24.0,neutral or dissatisfied +9906,44257,Female,Loyal Customer,33,Personal Travel,Eco,359,3,4,3,4,3,1,1,5,4,4,4,1,3,1,245,228.0,neutral or dissatisfied +9907,98086,Male,Loyal Customer,25,Business travel,Business,2444,1,4,4,4,1,1,1,1,3,4,4,4,3,1,0,0.0,neutral or dissatisfied +9908,64382,Male,Loyal Customer,47,Personal Travel,Eco,1158,2,4,2,1,5,2,5,5,2,3,3,4,2,5,0,10.0,neutral or dissatisfied +9909,120057,Female,Loyal Customer,20,Personal Travel,Eco,237,1,5,0,2,1,0,4,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +9910,73224,Female,Loyal Customer,55,Business travel,Eco,946,3,1,1,1,5,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +9911,55437,Male,Loyal Customer,53,Business travel,Business,2136,1,1,1,1,5,5,5,4,4,4,4,4,4,5,14,0.0,satisfied +9912,83781,Female,disloyal Customer,38,Business travel,Business,425,5,0,0,1,2,0,2,2,4,5,4,5,5,2,0,0.0,satisfied +9913,124668,Male,Loyal Customer,52,Business travel,Business,2617,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,3.0,satisfied +9914,87710,Female,Loyal Customer,11,Personal Travel,Eco,606,2,5,2,4,4,2,4,4,4,3,1,3,5,4,8,12.0,neutral or dissatisfied +9915,76678,Female,Loyal Customer,19,Personal Travel,Eco,534,4,4,4,3,3,4,3,3,3,2,5,5,4,3,0,2.0,neutral or dissatisfied +9916,68950,Male,Loyal Customer,60,Business travel,Business,3004,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +9917,111010,Male,Loyal Customer,57,Business travel,Business,319,5,5,5,5,2,5,5,5,5,5,5,3,5,4,6,38.0,satisfied +9918,79039,Female,Loyal Customer,50,Business travel,Business,3654,2,4,4,4,1,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +9919,28629,Female,disloyal Customer,28,Business travel,Eco,2409,3,3,3,5,4,3,3,4,5,1,4,5,1,4,0,0.0,neutral or dissatisfied +9920,20529,Female,Loyal Customer,42,Business travel,Eco,633,4,1,1,1,4,5,3,4,4,4,4,3,4,4,10,0.0,satisfied +9921,94007,Female,Loyal Customer,48,Business travel,Business,2115,0,4,0,4,4,4,4,3,3,4,4,5,3,5,6,0.0,satisfied +9922,122251,Female,disloyal Customer,36,Business travel,Eco,144,2,1,2,3,5,2,5,5,1,1,3,1,4,5,0,0.0,neutral or dissatisfied +9923,128915,Male,Loyal Customer,43,Business travel,Business,2248,4,2,4,4,2,3,5,5,5,5,5,3,5,3,0,12.0,satisfied +9924,29073,Female,Loyal Customer,61,Personal Travel,Eco,697,2,3,2,4,2,3,4,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +9925,35097,Female,Loyal Customer,20,Business travel,Business,3524,4,4,3,4,4,4,4,4,4,3,1,3,5,4,0,5.0,satisfied +9926,41559,Female,Loyal Customer,23,Business travel,Business,1464,1,5,1,1,5,5,5,5,3,2,2,1,4,5,0,0.0,satisfied +9927,81166,Male,Loyal Customer,41,Business travel,Business,3673,2,4,4,4,1,4,4,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +9928,98634,Male,Loyal Customer,31,Business travel,Business,873,2,1,1,1,2,2,2,2,1,3,3,2,4,2,0,6.0,neutral or dissatisfied +9929,55655,Female,Loyal Customer,42,Business travel,Business,315,3,3,5,3,4,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +9930,77195,Female,Loyal Customer,51,Personal Travel,Eco,290,1,4,1,1,2,5,4,1,1,1,4,5,1,3,4,0.0,neutral or dissatisfied +9931,69510,Female,Loyal Customer,23,Personal Travel,Eco,1746,1,4,0,3,3,0,3,3,1,1,2,2,3,3,2,0.0,neutral or dissatisfied +9932,57213,Female,disloyal Customer,25,Business travel,Business,1514,4,0,4,5,2,4,2,2,3,3,4,3,4,2,0,0.0,satisfied +9933,76508,Female,Loyal Customer,25,Business travel,Business,516,1,1,1,1,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +9934,341,Female,Loyal Customer,35,Personal Travel,Eco,821,1,5,1,3,3,1,2,3,4,4,5,3,4,3,0,6.0,neutral or dissatisfied +9935,72037,Female,Loyal Customer,11,Personal Travel,Eco,3784,4,5,4,3,4,3,3,3,5,3,5,3,4,3,0,10.0,neutral or dissatisfied +9936,33861,Male,Loyal Customer,18,Personal Travel,Eco,1562,1,5,0,3,4,0,4,4,5,5,2,3,2,4,49,39.0,neutral or dissatisfied +9937,102371,Male,Loyal Customer,47,Business travel,Eco,223,5,2,2,2,5,5,5,5,1,5,5,1,3,5,0,0.0,satisfied +9938,21962,Female,disloyal Customer,56,Business travel,Eco,448,2,0,2,3,1,2,1,1,4,4,5,5,3,1,0,1.0,neutral or dissatisfied +9939,11256,Male,Loyal Customer,7,Personal Travel,Eco,247,2,1,2,3,4,2,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +9940,16569,Female,Loyal Customer,60,Business travel,Eco,1092,2,3,3,3,2,3,3,2,2,2,2,3,2,4,16,,neutral or dissatisfied +9941,29372,Female,Loyal Customer,60,Business travel,Eco,2404,5,2,1,1,5,5,5,3,3,3,1,5,2,5,0,56.0,satisfied +9942,70072,Female,Loyal Customer,56,Business travel,Business,550,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9943,39519,Male,Loyal Customer,10,Personal Travel,Eco,852,5,4,5,1,2,5,2,2,3,3,4,3,4,2,0,0.0,satisfied +9944,29383,Female,Loyal Customer,33,Business travel,Business,2676,1,1,3,3,2,1,1,2,1,4,4,1,2,1,9,16.0,neutral or dissatisfied +9945,18294,Female,Loyal Customer,47,Personal Travel,Eco,640,2,5,2,4,5,4,4,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +9946,102973,Female,Loyal Customer,34,Personal Travel,Business,460,3,4,3,3,2,4,5,4,4,3,4,5,4,3,37,35.0,neutral or dissatisfied +9947,91158,Male,Loyal Customer,45,Personal Travel,Eco,270,1,4,1,4,4,1,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +9948,99683,Female,Loyal Customer,49,Business travel,Business,442,3,3,3,3,3,5,4,4,4,4,4,5,4,3,7,11.0,satisfied +9949,113455,Male,Loyal Customer,52,Business travel,Business,223,4,4,4,4,5,4,4,4,4,4,5,5,4,4,19,3.0,satisfied +9950,113590,Male,disloyal Customer,37,Business travel,Eco,407,2,0,2,3,4,2,2,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +9951,40545,Male,Loyal Customer,45,Business travel,Eco,391,4,2,2,2,4,4,4,4,3,2,2,5,1,4,1,14.0,satisfied +9952,95067,Male,Loyal Customer,56,Personal Travel,Eco,323,2,2,2,4,4,2,4,4,3,2,3,2,4,4,40,34.0,neutral or dissatisfied +9953,125330,Female,disloyal Customer,44,Business travel,Business,599,1,1,1,5,4,1,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +9954,93308,Male,Loyal Customer,34,Business travel,Business,1733,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +9955,115800,Female,disloyal Customer,23,Business travel,Eco,371,1,0,1,5,5,1,5,5,1,4,4,4,1,5,0,0.0,neutral or dissatisfied +9956,69178,Male,Loyal Customer,69,Personal Travel,Eco,187,3,4,3,3,5,3,4,5,5,2,5,3,4,5,5,23.0,neutral or dissatisfied +9957,123057,Male,Loyal Customer,42,Business travel,Eco,600,2,3,3,3,2,2,2,2,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +9958,35593,Male,Loyal Customer,77,Business travel,Eco Plus,1028,3,5,1,1,3,3,3,3,2,5,3,4,3,3,29,44.0,neutral or dissatisfied +9959,79087,Female,Loyal Customer,60,Personal Travel,Eco,356,4,5,4,4,4,4,4,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +9960,108057,Female,Loyal Customer,52,Personal Travel,Eco,591,3,5,2,3,4,5,5,2,2,2,2,4,2,5,23,40.0,neutral or dissatisfied +9961,19321,Male,Loyal Customer,23,Business travel,Business,1556,1,1,1,1,5,5,5,3,2,3,3,5,4,5,167,174.0,satisfied +9962,23060,Male,disloyal Customer,28,Business travel,Eco,820,4,5,5,4,4,5,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +9963,115305,Female,Loyal Customer,45,Business travel,Business,308,4,2,2,2,5,3,3,4,4,4,4,1,4,3,34,25.0,neutral or dissatisfied +9964,117272,Male,Loyal Customer,63,Personal Travel,Eco,370,2,2,2,4,1,2,1,1,3,4,4,4,3,1,12,8.0,neutral or dissatisfied +9965,103067,Female,Loyal Customer,35,Business travel,Eco,460,5,2,2,2,5,5,5,5,4,2,1,2,5,5,0,0.0,satisfied +9966,109380,Female,Loyal Customer,34,Business travel,Eco,1046,3,5,5,5,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +9967,2956,Female,disloyal Customer,27,Business travel,Business,835,2,2,2,2,2,2,2,2,3,4,5,5,5,2,15,11.0,neutral or dissatisfied +9968,60119,Male,disloyal Customer,37,Business travel,Business,1050,1,1,1,2,3,1,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +9969,72934,Male,Loyal Customer,46,Business travel,Business,3033,4,4,4,4,4,4,4,3,2,5,5,4,5,4,243,244.0,satisfied +9970,72790,Male,Loyal Customer,72,Business travel,Business,645,1,1,1,1,5,1,2,3,3,3,3,4,3,3,0,0.0,satisfied +9971,54607,Male,Loyal Customer,28,Business travel,Business,1663,1,1,1,1,4,4,4,4,5,3,1,3,3,4,0,24.0,satisfied +9972,45047,Female,Loyal Customer,53,Business travel,Eco,323,5,3,1,1,5,4,1,5,5,5,5,1,5,4,24,53.0,satisfied +9973,67513,Female,disloyal Customer,28,Business travel,Business,1171,2,2,2,3,4,2,5,4,4,2,5,4,4,4,1,4.0,neutral or dissatisfied +9974,95009,Female,Loyal Customer,26,Personal Travel,Eco,248,3,4,3,3,2,3,3,2,4,3,5,3,5,2,15,11.0,neutral or dissatisfied +9975,107489,Female,disloyal Customer,24,Business travel,Business,711,2,4,2,4,5,2,5,5,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +9976,43323,Female,Loyal Customer,37,Business travel,Business,463,1,1,1,1,2,1,4,2,2,2,2,4,2,5,0,0.0,satisfied +9977,122537,Male,disloyal Customer,37,Business travel,Business,500,1,2,2,1,5,2,5,5,5,3,5,5,4,5,4,16.0,neutral or dissatisfied +9978,90073,Female,disloyal Customer,22,Business travel,Eco,1127,5,5,5,4,4,5,3,4,5,2,5,5,4,4,0,0.0,satisfied +9979,42888,Male,Loyal Customer,36,Business travel,Eco,200,4,5,5,5,4,4,4,4,2,3,4,5,5,4,0,0.0,satisfied +9980,109107,Male,Loyal Customer,24,Business travel,Business,781,3,3,3,3,5,5,5,5,5,5,5,4,5,5,14,4.0,satisfied +9981,92311,Male,disloyal Customer,22,Business travel,Eco,1319,3,3,3,4,3,3,3,3,3,3,5,3,4,3,4,0.0,neutral or dissatisfied +9982,80580,Female,Loyal Customer,61,Personal Travel,Eco,1747,4,0,4,1,5,5,5,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +9983,1483,Male,Loyal Customer,43,Business travel,Business,737,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +9984,100443,Female,Loyal Customer,46,Business travel,Business,1180,3,2,3,3,3,4,5,4,4,4,4,5,4,4,21,0.0,satisfied +9985,65919,Male,Loyal Customer,79,Business travel,Business,3626,2,2,2,2,4,5,1,5,5,5,5,2,5,2,0,1.0,satisfied +9986,86474,Male,disloyal Customer,22,Business travel,Eco,762,5,5,5,4,1,5,1,1,5,3,2,4,1,1,0,0.0,satisfied +9987,64097,Female,Loyal Customer,41,Personal Travel,Eco,921,2,5,2,5,5,2,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +9988,106049,Female,Loyal Customer,12,Personal Travel,Eco,452,3,4,3,5,2,3,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +9989,72065,Female,Loyal Customer,23,Business travel,Business,2486,5,2,5,5,4,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +9990,45190,Male,disloyal Customer,29,Business travel,Eco,1443,2,2,2,3,2,1,1,3,1,5,3,1,3,1,187,186.0,neutral or dissatisfied +9991,91795,Male,Loyal Customer,19,Personal Travel,Eco,588,2,3,2,3,1,2,1,1,3,2,4,4,4,1,3,1.0,neutral or dissatisfied +9992,76809,Female,Loyal Customer,27,Personal Travel,Eco,689,2,5,2,2,2,2,2,2,4,5,4,3,4,2,111,110.0,neutral or dissatisfied +9993,42415,Male,Loyal Customer,35,Business travel,Eco Plus,329,5,4,4,4,5,5,5,5,4,4,5,4,1,5,0,0.0,satisfied +9994,68459,Female,Loyal Customer,56,Business travel,Business,1067,1,1,2,1,5,5,4,5,5,4,5,5,5,5,1,16.0,satisfied +9995,124365,Male,Loyal Customer,50,Business travel,Business,3599,3,3,3,3,4,5,4,5,5,5,5,5,5,4,12,24.0,satisfied +9996,22044,Male,Loyal Customer,38,Business travel,Business,3873,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +9997,14057,Female,Loyal Customer,39,Business travel,Business,319,4,4,4,4,5,4,4,4,4,4,4,3,4,2,0,0.0,satisfied +9998,113848,Male,Loyal Customer,52,Business travel,Business,1363,5,5,5,5,2,5,5,4,4,3,4,5,4,5,1,11.0,satisfied +9999,1865,Female,Loyal Customer,41,Business travel,Business,3938,4,4,4,4,2,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +10000,128155,Male,Loyal Customer,55,Business travel,Business,1788,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +10001,105927,Female,Loyal Customer,56,Business travel,Business,1491,3,3,3,3,4,4,4,3,4,5,5,4,4,4,258,247.0,satisfied +10002,222,Female,Loyal Customer,44,Personal Travel,Eco,213,4,5,4,1,1,4,1,1,1,4,1,4,1,1,0,5.0,neutral or dissatisfied +10003,92936,Female,Loyal Customer,31,Personal Travel,Eco,151,2,5,2,5,1,2,4,1,5,4,4,5,5,1,0,0.0,neutral or dissatisfied +10004,35353,Female,Loyal Customer,25,Business travel,Business,3779,4,4,4,4,4,4,4,4,1,3,4,3,5,4,0,5.0,satisfied +10005,86225,Female,disloyal Customer,36,Business travel,Eco,226,3,3,3,3,1,3,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +10006,64887,Male,disloyal Customer,23,Business travel,Eco,469,1,4,1,4,4,1,4,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +10007,64165,Male,Loyal Customer,33,Personal Travel,Eco,989,1,5,0,3,0,1,1,4,2,5,5,1,4,1,726,691.0,neutral or dissatisfied +10008,83213,Female,Loyal Customer,26,Personal Travel,Eco Plus,1123,2,5,2,1,4,2,4,4,3,2,5,4,4,4,2,0.0,neutral or dissatisfied +10009,122110,Female,Loyal Customer,65,Personal Travel,Eco,130,1,0,1,2,5,5,5,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +10010,61623,Male,Loyal Customer,42,Business travel,Eco,1346,4,5,5,5,5,4,5,5,1,5,3,3,4,5,0,0.0,neutral or dissatisfied +10011,72396,Male,Loyal Customer,56,Business travel,Business,1766,2,2,2,2,4,5,4,4,4,4,4,5,4,5,56,65.0,satisfied +10012,70312,Male,Loyal Customer,21,Personal Travel,Eco Plus,334,1,5,5,5,4,5,4,4,3,2,4,5,4,4,48,52.0,neutral or dissatisfied +10013,9981,Female,Loyal Customer,10,Personal Travel,Eco,515,2,4,4,3,4,4,4,4,4,5,5,5,4,4,0,14.0,neutral or dissatisfied +10014,120859,Female,disloyal Customer,21,Business travel,Eco,861,3,3,3,3,3,3,2,3,1,1,3,4,3,3,100,108.0,neutral or dissatisfied +10015,55157,Male,Loyal Customer,13,Personal Travel,Eco,1608,3,5,4,1,2,4,2,2,4,1,4,4,4,2,2,0.0,neutral or dissatisfied +10016,106109,Male,Loyal Customer,37,Business travel,Business,2077,2,1,1,1,1,4,3,2,2,2,2,4,2,4,37,27.0,neutral or dissatisfied +10017,26752,Male,disloyal Customer,40,Business travel,Eco,859,2,2,2,1,2,2,2,2,4,4,1,3,1,2,9,18.0,neutral or dissatisfied +10018,98476,Female,Loyal Customer,49,Personal Travel,Eco Plus,210,0,5,0,5,4,2,2,3,3,0,3,5,3,5,0,0.0,satisfied +10019,74378,Male,disloyal Customer,41,Business travel,Business,1313,3,3,3,1,5,3,1,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +10020,78372,Male,disloyal Customer,23,Business travel,Eco,726,1,1,1,1,2,1,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +10021,101711,Female,Loyal Customer,23,Personal Travel,Eco,1624,3,3,3,1,2,3,2,2,4,4,5,3,4,2,45,35.0,neutral or dissatisfied +10022,96505,Male,disloyal Customer,59,Business travel,Eco,302,1,1,1,4,1,1,1,1,2,3,3,3,3,1,38,38.0,neutral or dissatisfied +10023,104428,Female,Loyal Customer,32,Business travel,Business,2841,5,5,5,5,4,4,4,4,5,2,5,4,5,4,3,1.0,satisfied +10024,47516,Female,Loyal Customer,14,Personal Travel,Eco,599,1,4,1,3,3,1,3,3,4,5,3,2,4,3,86,88.0,neutral or dissatisfied +10025,108550,Male,Loyal Customer,25,Personal Travel,Eco Plus,511,4,4,3,4,4,3,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +10026,45953,Female,Loyal Customer,21,Personal Travel,Eco,563,2,5,2,3,5,2,5,5,3,4,4,3,5,5,62,53.0,neutral or dissatisfied +10027,98319,Female,Loyal Customer,25,Business travel,Business,1547,1,1,4,1,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +10028,76088,Female,Loyal Customer,48,Business travel,Eco,269,3,3,3,3,4,3,4,2,2,3,2,2,2,1,0,9.0,neutral or dissatisfied +10029,14284,Male,Loyal Customer,33,Business travel,Business,2140,1,1,1,1,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +10030,28302,Male,Loyal Customer,58,Business travel,Business,2265,3,5,3,3,4,1,1,3,3,3,3,4,3,3,0,0.0,satisfied +10031,71351,Female,Loyal Customer,41,Personal Travel,Eco Plus,1671,1,1,1,4,3,4,3,1,1,1,1,2,1,1,17,3.0,neutral or dissatisfied +10032,87727,Male,Loyal Customer,61,Personal Travel,Eco Plus,606,2,5,2,3,4,2,4,4,3,5,5,3,4,4,0,2.0,neutral or dissatisfied +10033,17136,Female,Loyal Customer,40,Personal Travel,Eco,423,3,5,3,1,5,3,3,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +10034,91208,Female,Loyal Customer,65,Personal Travel,Eco,270,4,0,4,1,1,5,5,5,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +10035,124112,Female,Loyal Customer,57,Business travel,Business,2568,3,3,3,3,5,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +10036,80730,Male,disloyal Customer,21,Business travel,Business,393,0,0,0,4,4,0,4,4,4,2,4,4,4,4,2,27.0,satisfied +10037,49273,Female,Loyal Customer,48,Business travel,Eco,308,5,1,1,1,2,3,2,4,4,5,4,4,4,1,0,0.0,satisfied +10038,115301,Female,Loyal Customer,41,Business travel,Business,1606,0,0,0,5,4,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +10039,38587,Male,Loyal Customer,28,Personal Travel,Eco Plus,2465,2,4,2,2,2,2,5,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +10040,87895,Male,Loyal Customer,60,Business travel,Business,515,1,1,1,1,4,4,4,4,4,4,4,4,4,3,11,31.0,satisfied +10041,85512,Female,Loyal Customer,46,Business travel,Business,332,4,4,4,4,2,5,5,4,4,4,4,4,4,4,24,30.0,satisfied +10042,33650,Female,Loyal Customer,9,Personal Travel,Eco,399,3,5,3,2,4,3,4,4,4,4,1,1,2,4,0,0.0,neutral or dissatisfied +10043,39121,Female,Loyal Customer,52,Business travel,Business,3915,3,1,1,1,2,2,2,4,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +10044,76459,Female,Loyal Customer,52,Business travel,Business,481,1,5,5,5,5,4,3,1,1,2,1,3,1,2,11,2.0,neutral or dissatisfied +10045,63517,Male,Loyal Customer,50,Business travel,Business,1009,3,3,3,3,4,5,5,1,1,2,1,5,1,4,9,0.0,satisfied +10046,32978,Male,Loyal Customer,50,Personal Travel,Eco,101,3,5,3,5,2,3,2,2,5,5,5,4,5,2,0,1.0,neutral or dissatisfied +10047,25626,Male,Loyal Customer,27,Business travel,Eco,526,4,5,5,5,4,4,4,4,1,1,2,1,3,4,6,8.0,neutral or dissatisfied +10048,45085,Male,Loyal Customer,43,Business travel,Eco,299,3,1,1,1,3,3,3,3,5,5,4,5,1,3,0,4.0,satisfied +10049,81104,Female,Loyal Customer,28,Business travel,Business,3193,5,5,5,5,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +10050,85455,Female,Loyal Customer,60,Business travel,Business,106,5,5,5,5,5,5,5,4,4,4,4,4,4,4,2,2.0,satisfied +10051,52535,Female,Loyal Customer,33,Business travel,Eco,160,5,1,1,1,5,5,5,5,5,4,3,5,4,5,0,0.0,satisfied +10052,72721,Male,Loyal Customer,30,Business travel,Eco Plus,985,3,4,5,4,3,3,3,3,1,2,3,1,4,3,0,4.0,neutral or dissatisfied +10053,38533,Male,disloyal Customer,28,Business travel,Eco,1391,1,1,1,4,3,1,3,3,1,2,4,4,3,3,31,6.0,neutral or dissatisfied +10054,75763,Male,Loyal Customer,58,Personal Travel,Eco,813,0,2,0,4,4,0,4,4,3,5,2,2,4,4,0,0.0,satisfied +10055,125885,Female,Loyal Customer,18,Personal Travel,Eco,861,3,4,3,4,2,3,2,2,3,3,4,4,3,2,14,10.0,neutral or dissatisfied +10056,9697,Female,Loyal Customer,14,Personal Travel,Eco,277,5,2,2,4,3,2,3,3,3,2,4,4,4,3,0,0.0,satisfied +10057,84424,Female,Loyal Customer,41,Personal Travel,Eco,591,3,0,3,2,4,3,5,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +10058,39713,Female,Loyal Customer,52,Business travel,Business,2661,2,2,2,2,5,4,1,5,5,5,4,4,5,5,0,0.0,satisfied +10059,125081,Male,Loyal Customer,63,Business travel,Business,1685,3,2,3,2,1,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +10060,13429,Male,Loyal Customer,37,Business travel,Business,2981,2,2,2,2,2,1,3,4,4,4,4,2,4,2,0,0.0,satisfied +10061,49169,Male,Loyal Customer,53,Business travel,Eco,372,4,2,2,2,4,4,4,4,2,3,2,2,4,4,12,3.0,satisfied +10062,58012,Male,Loyal Customer,32,Personal Travel,Eco Plus,1162,1,1,1,3,4,1,4,4,1,2,2,1,2,4,0,0.0,neutral or dissatisfied +10063,48541,Male,disloyal Customer,36,Business travel,Eco,445,4,0,5,4,3,5,1,3,1,5,4,3,2,3,0,13.0,neutral or dissatisfied +10064,9576,Female,Loyal Customer,68,Business travel,Business,288,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +10065,127620,Male,Loyal Customer,54,Business travel,Business,1773,1,1,1,1,4,5,4,2,2,2,2,4,2,5,4,0.0,satisfied +10066,362,Male,disloyal Customer,24,Business travel,Eco,134,5,3,5,3,5,5,5,5,5,4,4,4,5,5,14,14.0,satisfied +10067,116816,Male,Loyal Customer,59,Business travel,Business,3023,1,1,2,1,4,5,4,4,4,4,4,3,4,3,4,2.0,satisfied +10068,9280,Female,Loyal Customer,57,Business travel,Business,3408,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +10069,126460,Male,Loyal Customer,47,Business travel,Business,1849,4,4,4,4,4,4,5,4,4,4,4,4,4,3,9,0.0,satisfied +10070,21007,Male,Loyal Customer,30,Personal Travel,Eco Plus,689,1,4,1,4,2,1,2,2,4,4,4,5,4,2,14,11.0,neutral or dissatisfied +10071,106002,Female,Loyal Customer,66,Business travel,Business,1999,2,3,3,3,2,2,4,2,2,2,2,1,2,2,22,33.0,neutral or dissatisfied +10072,98853,Male,Loyal Customer,60,Business travel,Business,1751,5,1,5,5,3,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +10073,60466,Female,disloyal Customer,24,Business travel,Eco,775,1,1,1,4,5,1,5,5,5,5,5,3,4,5,2,0.0,neutral or dissatisfied +10074,83911,Male,disloyal Customer,70,Business travel,Eco,752,4,4,4,4,1,4,1,1,4,3,3,3,3,1,0,0.0,neutral or dissatisfied +10075,1213,Male,Loyal Customer,41,Personal Travel,Eco,282,3,4,5,4,2,5,2,2,5,5,4,5,4,2,108,98.0,neutral or dissatisfied +10076,24846,Male,Loyal Customer,54,Personal Travel,Eco,894,0,5,1,1,5,1,5,5,4,4,4,5,4,5,0,0.0,satisfied +10077,90099,Female,Loyal Customer,42,Business travel,Business,983,1,1,1,1,2,5,5,5,5,5,5,5,5,3,5,0.0,satisfied +10078,83621,Female,Loyal Customer,11,Personal Travel,Eco,409,4,1,4,3,3,4,4,3,3,4,3,4,4,3,0,0.0,satisfied +10079,3215,Female,Loyal Customer,46,Personal Travel,Eco Plus,693,2,4,2,3,3,5,5,1,1,2,1,5,1,5,3,0.0,neutral or dissatisfied +10080,75851,Male,Loyal Customer,27,Personal Travel,Eco,1440,2,5,2,1,2,2,2,2,4,5,5,3,4,2,9,7.0,neutral or dissatisfied +10081,20964,Female,disloyal Customer,37,Business travel,Eco,289,3,0,2,3,1,2,4,1,1,2,3,1,5,1,0,0.0,neutral or dissatisfied +10082,12857,Male,Loyal Customer,65,Personal Travel,Eco,817,3,2,3,4,2,3,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +10083,88182,Male,Loyal Customer,49,Business travel,Business,3713,1,1,1,1,3,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +10084,88281,Female,Loyal Customer,62,Business travel,Eco,250,2,4,4,4,1,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +10085,81892,Male,Loyal Customer,40,Business travel,Business,3050,3,3,3,3,3,4,4,4,4,5,4,4,4,4,15,4.0,satisfied +10086,16365,Male,Loyal Customer,26,Personal Travel,Eco,319,2,4,2,1,4,2,4,4,3,2,5,2,3,4,0,24.0,neutral or dissatisfied +10087,47143,Female,disloyal Customer,27,Business travel,Eco,954,3,3,3,3,3,3,3,3,5,3,3,5,3,3,0,0.0,neutral or dissatisfied +10088,17182,Female,disloyal Customer,61,Personal Travel,Eco,643,2,4,2,1,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +10089,95099,Male,Loyal Customer,23,Personal Travel,Eco,192,3,4,3,4,1,3,1,1,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +10090,77341,Female,disloyal Customer,21,Business travel,Eco,590,3,4,3,1,3,1,1,5,5,5,4,1,4,1,138,143.0,neutral or dissatisfied +10091,3422,Female,Loyal Customer,68,Personal Travel,Eco,315,3,3,3,4,3,1,1,3,5,2,1,1,4,1,169,189.0,neutral or dissatisfied +10092,129224,Male,Loyal Customer,34,Business travel,Business,1464,4,4,4,4,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10093,71699,Male,Loyal Customer,70,Personal Travel,Eco,1182,4,5,5,3,1,5,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +10094,37245,Male,Loyal Customer,20,Personal Travel,Business,1102,4,5,4,3,2,4,2,2,4,1,1,1,5,2,15,9.0,neutral or dissatisfied +10095,99182,Female,Loyal Customer,25,Business travel,Business,351,4,1,4,1,4,4,4,4,4,3,4,3,3,4,6,0.0,neutral or dissatisfied +10096,214,Male,disloyal Customer,38,Business travel,Business,213,2,2,2,3,3,2,5,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +10097,3820,Male,Loyal Customer,49,Business travel,Business,2081,2,2,2,2,2,4,5,3,3,4,3,4,3,3,21,0.0,satisfied +10098,38596,Female,Loyal Customer,53,Business travel,Eco,231,5,4,2,2,4,3,4,5,5,5,5,4,5,2,0,0.0,satisfied +10099,8770,Male,Loyal Customer,24,Personal Travel,Business,552,2,4,2,4,3,2,3,3,5,3,5,5,5,3,6,0.0,neutral or dissatisfied +10100,122252,Female,disloyal Customer,22,Business travel,Eco,141,4,4,4,2,3,4,5,3,5,3,3,3,5,3,0,0.0,satisfied +10101,31408,Female,Loyal Customer,60,Business travel,Eco,1546,4,4,4,4,3,5,3,4,4,4,4,2,4,2,4,7.0,satisfied +10102,109888,Male,Loyal Customer,23,Business travel,Business,1165,3,3,3,3,5,5,5,5,3,3,5,5,4,5,3,0.0,satisfied +10103,62782,Female,Loyal Customer,21,Business travel,Business,2447,1,4,2,4,1,1,1,1,1,1,4,1,4,1,4,3.0,neutral or dissatisfied +10104,13958,Male,Loyal Customer,61,Personal Travel,Eco,192,1,4,1,2,3,1,3,3,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +10105,32537,Male,Loyal Customer,39,Business travel,Business,102,0,5,0,1,2,2,5,5,5,5,5,1,5,3,6,4.0,satisfied +10106,129411,Female,disloyal Customer,33,Business travel,Business,414,1,1,1,1,5,1,5,5,5,5,4,3,5,5,35,32.0,neutral or dissatisfied +10107,63763,Female,Loyal Customer,25,Personal Travel,Eco Plus,2422,2,3,2,2,4,2,4,4,3,3,3,3,5,4,0,37.0,neutral or dissatisfied +10108,4561,Male,disloyal Customer,20,Business travel,Eco,161,5,2,5,3,3,5,3,3,4,1,2,4,4,3,0,0.0,satisfied +10109,4835,Male,disloyal Customer,15,Business travel,Eco,408,2,2,2,4,3,2,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +10110,18164,Female,Loyal Customer,18,Personal Travel,Eco,430,3,5,4,3,2,4,2,2,4,5,4,3,3,2,0,0.0,neutral or dissatisfied +10111,50311,Female,Loyal Customer,52,Business travel,Business,109,1,4,4,4,5,3,4,4,4,4,1,2,4,4,40,53.0,neutral or dissatisfied +10112,37466,Female,disloyal Customer,42,Business travel,Eco,1074,4,4,4,1,5,4,2,5,1,4,2,2,5,5,0,0.0,satisfied +10113,52281,Male,disloyal Customer,71,Business travel,Eco,425,4,0,4,5,2,4,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +10114,25237,Female,Loyal Customer,30,Personal Travel,Eco,925,3,4,3,3,5,3,5,5,1,3,3,1,3,5,2,15.0,neutral or dissatisfied +10115,94126,Male,disloyal Customer,38,Business travel,Business,239,5,5,5,2,3,5,3,3,5,3,5,5,4,3,21,12.0,satisfied +10116,4650,Female,Loyal Customer,47,Business travel,Business,489,3,3,3,3,2,5,4,4,4,4,4,4,4,5,47,36.0,satisfied +10117,76682,Female,Loyal Customer,18,Personal Travel,Eco,547,3,5,3,4,5,3,5,5,4,4,4,5,5,5,0,0.0,neutral or dissatisfied +10118,108951,Male,Loyal Customer,52,Business travel,Business,1516,5,5,5,5,5,4,4,5,5,4,5,5,5,3,70,55.0,satisfied +10119,68472,Male,Loyal Customer,54,Business travel,Business,2616,2,2,2,2,2,4,4,4,4,5,4,3,4,4,0,7.0,satisfied +10120,74283,Male,Loyal Customer,50,Business travel,Business,2288,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +10121,110455,Male,Loyal Customer,55,Personal Travel,Eco,925,1,5,1,3,1,1,1,1,3,2,4,3,4,1,67,58.0,neutral or dissatisfied +10122,22978,Female,disloyal Customer,17,Business travel,Eco,528,4,0,4,3,1,4,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +10123,11563,Female,Loyal Customer,60,Business travel,Business,1750,4,4,4,4,3,5,4,3,3,3,3,3,3,4,27,29.0,satisfied +10124,86356,Female,Loyal Customer,33,Business travel,Business,2540,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +10125,8735,Female,Loyal Customer,42,Business travel,Business,227,5,5,5,5,5,4,5,4,4,4,4,3,4,3,0,6.0,satisfied +10126,18739,Male,Loyal Customer,35,Business travel,Eco,1167,4,4,4,4,4,4,4,4,3,4,1,3,4,4,31,2.0,satisfied +10127,16577,Male,Loyal Customer,24,Business travel,Business,692,2,2,4,2,4,4,4,4,4,4,1,2,5,4,0,0.0,satisfied +10128,64264,Female,disloyal Customer,28,Business travel,Business,1192,5,5,5,5,4,5,4,4,4,2,5,5,4,4,12,0.0,satisfied +10129,66237,Male,Loyal Customer,39,Business travel,Eco,150,2,5,5,5,2,2,2,2,2,5,3,3,3,2,0,0.0,satisfied +10130,118419,Male,Loyal Customer,45,Business travel,Business,3919,4,2,4,4,4,4,4,2,2,2,2,3,2,4,11,6.0,satisfied +10131,71203,Male,Loyal Customer,48,Business travel,Business,733,1,1,1,1,4,5,5,5,5,5,5,3,5,3,13,7.0,satisfied +10132,105076,Male,Loyal Customer,51,Business travel,Business,3480,5,5,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +10133,75827,Male,Loyal Customer,55,Business travel,Business,1440,4,4,4,4,3,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +10134,28519,Female,Loyal Customer,49,Business travel,Business,2677,1,1,1,1,3,3,5,3,3,3,3,1,3,5,0,0.0,satisfied +10135,18590,Female,Loyal Customer,50,Business travel,Eco,190,4,1,1,1,5,3,3,4,4,4,4,1,4,1,0,0.0,satisfied +10136,119919,Male,Loyal Customer,44,Business travel,Business,1009,5,5,5,5,5,4,5,4,4,4,4,3,4,3,0,20.0,satisfied +10137,67407,Female,Loyal Customer,48,Business travel,Eco,641,3,3,3,3,5,4,3,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +10138,46316,Female,Loyal Customer,43,Business travel,Business,2205,3,3,3,3,2,1,3,1,1,2,1,1,1,4,24,30.0,satisfied +10139,120150,Female,Loyal Customer,45,Personal Travel,Eco,1475,3,2,3,4,5,2,4,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +10140,102843,Male,Loyal Customer,47,Business travel,Business,1562,4,4,4,4,3,4,5,5,5,5,5,3,5,3,5,10.0,satisfied +10141,52241,Male,Loyal Customer,42,Business travel,Eco,451,4,5,5,5,4,4,4,4,4,4,4,5,2,4,0,0.0,satisfied +10142,1756,Male,Loyal Customer,57,Business travel,Business,3303,4,4,4,4,2,4,4,4,4,4,4,3,4,4,9,3.0,satisfied +10143,90238,Female,disloyal Customer,21,Business travel,Business,983,4,0,4,3,3,4,2,3,3,3,4,3,5,3,0,0.0,satisfied +10144,88056,Male,Loyal Customer,46,Business travel,Business,2565,0,0,0,3,2,4,5,5,5,5,5,5,5,5,0,2.0,satisfied +10145,14767,Female,Loyal Customer,54,Personal Travel,Eco,533,2,4,2,1,5,5,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +10146,33715,Female,Loyal Customer,20,Personal Travel,Eco,667,1,4,1,2,3,1,3,3,5,2,4,3,5,3,0,1.0,neutral or dissatisfied +10147,104615,Male,Loyal Customer,19,Business travel,Business,1828,1,1,1,1,5,4,5,5,5,3,5,5,5,5,0,9.0,satisfied +10148,66074,Male,Loyal Customer,66,Personal Travel,Eco,1055,3,4,4,3,4,4,4,4,3,4,4,5,5,4,29,24.0,neutral or dissatisfied +10149,126500,Male,Loyal Customer,55,Personal Travel,Eco,1788,2,5,2,1,4,2,5,4,4,2,4,4,4,4,0,11.0,neutral or dissatisfied +10150,75685,Female,Loyal Customer,42,Business travel,Business,2135,3,3,5,3,5,5,5,5,5,5,5,5,5,4,0,2.0,satisfied +10151,94411,Female,disloyal Customer,21,Business travel,Eco,239,4,0,4,4,4,4,5,4,3,5,4,4,5,4,2,0.0,neutral or dissatisfied +10152,50840,Female,Loyal Customer,54,Personal Travel,Eco,156,4,2,4,4,2,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +10153,10129,Female,disloyal Customer,20,Business travel,Eco,946,2,2,2,3,2,2,2,2,1,5,3,3,4,2,0,0.0,neutral or dissatisfied +10154,84443,Male,Loyal Customer,8,Personal Travel,Eco Plus,606,3,3,3,3,5,3,5,5,1,5,3,5,1,5,0,0.0,neutral or dissatisfied +10155,35782,Female,Loyal Customer,33,Business travel,Eco,200,2,4,4,4,2,2,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +10156,22504,Female,disloyal Customer,30,Business travel,Eco Plus,83,2,3,3,1,3,3,3,3,3,2,1,3,1,3,0,0.0,neutral or dissatisfied +10157,7536,Female,disloyal Customer,14,Personal Travel,Eco,762,3,5,3,5,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +10158,55659,Male,Loyal Customer,18,Business travel,Eco Plus,296,4,1,1,1,4,4,4,4,5,1,2,2,1,4,0,0.0,satisfied +10159,7102,Male,Loyal Customer,62,Personal Travel,Eco,273,2,4,2,2,2,2,2,2,3,4,2,3,2,2,10,53.0,neutral or dissatisfied +10160,110812,Male,Loyal Customer,40,Personal Travel,Eco,1105,3,5,3,4,3,3,3,3,3,5,2,2,1,3,7,6.0,neutral or dissatisfied +10161,107707,Female,Loyal Customer,50,Business travel,Eco,405,4,1,1,1,1,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +10162,14329,Male,Loyal Customer,20,Personal Travel,Eco,429,3,3,3,2,4,3,4,4,4,1,3,2,2,4,0,0.0,neutral or dissatisfied +10163,6769,Male,disloyal Customer,65,Business travel,Business,235,4,4,4,3,3,4,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +10164,73774,Female,Loyal Customer,45,Personal Travel,Eco,192,1,5,1,4,4,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +10165,14733,Female,Loyal Customer,54,Business travel,Business,3116,2,4,2,4,2,4,3,2,2,2,2,3,2,3,55,44.0,neutral or dissatisfied +10166,89742,Female,Loyal Customer,10,Personal Travel,Eco,944,3,4,3,1,3,1,1,5,5,2,1,1,4,1,198,197.0,neutral or dissatisfied +10167,60026,Female,Loyal Customer,14,Personal Travel,Eco,1065,3,3,3,3,2,3,2,2,2,5,5,3,3,2,0,0.0,neutral or dissatisfied +10168,74777,Female,Loyal Customer,52,Business travel,Business,3896,1,1,4,1,5,4,5,4,4,4,4,4,4,3,41,25.0,satisfied +10169,48198,Male,disloyal Customer,36,Business travel,Business,236,2,2,2,2,1,2,1,1,4,4,2,5,5,1,0,0.0,neutral or dissatisfied +10170,83500,Male,disloyal Customer,38,Business travel,Eco,546,4,3,4,3,3,4,3,3,1,3,3,2,5,3,0,0.0,satisfied +10171,81191,Female,Loyal Customer,37,Personal Travel,Eco,980,2,4,2,4,2,2,2,2,5,3,4,4,5,2,11,0.0,neutral or dissatisfied +10172,85098,Male,Loyal Customer,56,Business travel,Business,2687,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +10173,54006,Male,Loyal Customer,40,Business travel,Business,395,1,1,5,1,1,5,2,5,5,5,5,2,5,3,0,0.0,satisfied +10174,532,Male,Loyal Customer,51,Business travel,Business,3462,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +10175,69498,Male,Loyal Customer,18,Personal Travel,Eco Plus,1089,3,4,3,4,1,3,1,1,1,5,1,2,5,1,0,0.0,neutral or dissatisfied +10176,83499,Female,disloyal Customer,54,Business travel,Eco,546,1,0,1,3,2,1,2,2,4,4,5,4,1,2,0,0.0,neutral or dissatisfied +10177,79484,Female,disloyal Customer,47,Business travel,Business,762,5,5,5,1,2,5,2,2,4,5,5,4,5,2,0,0.0,satisfied +10178,117536,Male,Loyal Customer,58,Business travel,Business,347,1,5,1,1,2,4,4,4,4,4,4,4,4,5,7,0.0,satisfied +10179,36296,Male,Loyal Customer,47,Business travel,Business,187,3,3,5,3,5,3,2,4,4,4,5,4,4,2,11,17.0,satisfied +10180,37763,Female,Loyal Customer,41,Business travel,Eco Plus,1069,4,5,5,5,3,1,5,4,4,4,4,1,4,4,14,0.0,satisfied +10181,39829,Female,Loyal Customer,32,Business travel,Business,2750,0,3,0,1,2,2,2,2,3,4,5,1,3,2,0,0.0,satisfied +10182,55528,Female,Loyal Customer,55,Business travel,Business,2599,5,5,4,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +10183,36178,Male,Loyal Customer,31,Personal Travel,Eco,1674,3,2,3,3,4,3,4,4,3,3,3,4,3,4,7,0.0,neutral or dissatisfied +10184,61329,Female,Loyal Customer,25,Personal Travel,Eco Plus,967,1,2,1,3,2,1,2,2,3,4,4,4,3,2,24,23.0,neutral or dissatisfied +10185,33066,Male,Loyal Customer,33,Personal Travel,Eco,163,3,4,0,1,1,0,1,1,4,1,4,4,1,1,0,1.0,neutral or dissatisfied +10186,104269,Male,Loyal Customer,22,Personal Travel,Eco,456,1,5,1,2,1,1,1,1,3,5,2,2,1,1,69,49.0,neutral or dissatisfied +10187,55638,Male,Loyal Customer,43,Business travel,Eco,563,3,4,4,4,3,3,3,3,2,2,3,3,3,3,0,35.0,neutral or dissatisfied +10188,291,Male,Loyal Customer,54,Business travel,Business,2718,1,1,3,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +10189,91861,Male,disloyal Customer,40,Business travel,Business,1995,1,1,1,3,2,1,2,2,4,3,3,5,5,2,0,0.0,neutral or dissatisfied +10190,18066,Female,Loyal Customer,44,Business travel,Eco,488,2,5,5,5,3,4,1,2,2,2,2,4,2,4,113,97.0,satisfied +10191,105611,Male,Loyal Customer,38,Personal Travel,Business,919,3,3,3,3,5,3,3,3,3,3,4,4,3,3,7,0.0,neutral or dissatisfied +10192,42301,Male,Loyal Customer,44,Personal Travel,Eco,834,5,5,5,3,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10193,60151,Female,Loyal Customer,55,Personal Travel,Eco,1012,3,3,3,3,3,1,4,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +10194,102833,Female,disloyal Customer,22,Business travel,Eco,423,2,5,2,3,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +10195,67529,Male,disloyal Customer,25,Business travel,Business,1242,1,2,1,4,4,1,4,4,1,2,4,1,4,4,0,16.0,neutral or dissatisfied +10196,21120,Female,Loyal Customer,30,Personal Travel,Eco,152,3,5,3,4,3,3,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +10197,34336,Male,Loyal Customer,43,Business travel,Business,846,3,1,1,1,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +10198,4953,Female,Loyal Customer,48,Business travel,Business,931,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +10199,42063,Female,Loyal Customer,60,Personal Travel,Eco,106,2,4,2,1,5,4,5,5,5,2,2,3,5,4,77,73.0,neutral or dissatisfied +10200,69375,Male,Loyal Customer,48,Business travel,Business,2548,2,2,2,2,5,5,5,2,2,2,2,3,2,5,0,3.0,satisfied +10201,128189,Female,disloyal Customer,18,Business travel,Eco Plus,1849,4,0,4,3,2,4,2,2,3,1,1,4,4,2,0,0.0,satisfied +10202,20090,Female,Loyal Customer,32,Business travel,Business,1722,2,2,2,2,4,4,4,4,5,5,4,5,5,4,20,6.0,satisfied +10203,999,Male,Loyal Customer,62,Business travel,Business,1637,4,4,4,4,4,4,4,5,5,5,5,1,5,3,0,0.0,satisfied +10204,49127,Male,Loyal Customer,43,Business travel,Business,209,3,3,3,3,5,1,2,4,4,4,3,2,4,2,0,3.0,satisfied +10205,53736,Male,Loyal Customer,30,Personal Travel,Eco,1208,1,3,1,3,2,1,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +10206,72955,Male,Loyal Customer,59,Business travel,Eco,1096,1,5,1,5,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +10207,21705,Female,Loyal Customer,16,Personal Travel,Eco,708,2,5,2,5,2,2,2,2,5,3,4,4,5,2,2,0.0,neutral or dissatisfied +10208,77807,Female,Loyal Customer,53,Personal Travel,Eco,689,2,4,2,3,2,4,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +10209,1819,Female,Loyal Customer,51,Business travel,Business,2478,2,2,2,2,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +10210,93043,Female,Loyal Customer,41,Business travel,Eco,436,3,2,1,2,3,3,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +10211,112253,Female,Loyal Customer,28,Business travel,Business,1703,4,4,4,4,4,4,4,4,4,5,4,5,4,4,22,2.0,satisfied +10212,88581,Female,Loyal Customer,9,Personal Travel,Eco,646,5,4,5,1,1,5,1,1,4,5,4,3,3,1,1,0.0,satisfied +10213,12895,Male,disloyal Customer,28,Business travel,Eco,809,4,4,4,5,1,4,1,1,4,5,2,2,5,1,0,0.0,neutral or dissatisfied +10214,37446,Male,Loyal Customer,38,Business travel,Business,2261,4,4,4,4,1,3,1,5,5,5,5,5,5,2,0,3.0,satisfied +10215,116275,Female,Loyal Customer,67,Personal Travel,Eco,446,2,4,2,2,4,4,4,3,3,2,3,3,3,5,20,9.0,neutral or dissatisfied +10216,41103,Male,Loyal Customer,47,Business travel,Eco,140,2,4,5,4,2,2,2,2,5,3,4,3,3,2,0,0.0,satisfied +10217,104717,Female,Loyal Customer,52,Business travel,Business,1342,5,5,5,5,2,5,4,4,4,4,4,3,4,4,6,18.0,satisfied +10218,76736,Male,Loyal Customer,53,Personal Travel,Eco Plus,481,2,4,2,1,4,2,4,4,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +10219,102110,Male,Loyal Customer,47,Business travel,Business,386,1,1,1,1,4,4,4,4,4,4,4,5,4,4,18,5.0,satisfied +10220,110849,Male,Loyal Customer,31,Business travel,Business,1951,3,3,2,3,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +10221,55516,Female,disloyal Customer,21,Business travel,Eco,991,2,2,2,4,1,2,2,1,2,5,3,2,3,1,1,4.0,neutral or dissatisfied +10222,45919,Female,Loyal Customer,71,Business travel,Business,3465,1,0,0,3,2,4,3,5,5,0,1,1,5,1,0,12.0,neutral or dissatisfied +10223,53126,Male,Loyal Customer,14,Personal Travel,Eco,2065,5,4,5,1,3,5,2,3,5,2,5,4,5,3,2,0.0,satisfied +10224,56379,Male,disloyal Customer,55,Business travel,Business,200,4,5,5,1,2,4,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +10225,23354,Male,Loyal Customer,17,Personal Travel,Eco Plus,563,5,1,4,3,1,4,1,1,2,2,2,3,2,1,85,83.0,satisfied +10226,121726,Male,disloyal Customer,30,Business travel,Business,1475,4,4,4,1,4,4,4,4,5,5,5,3,5,4,5,11.0,neutral or dissatisfied +10227,12295,Female,Loyal Customer,62,Business travel,Eco,201,4,5,5,5,1,5,5,4,4,4,4,3,4,1,0,0.0,satisfied +10228,33156,Male,Loyal Customer,57,Personal Travel,Eco,163,2,4,0,4,3,0,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +10229,8971,Female,Loyal Customer,54,Business travel,Eco,725,3,5,5,5,1,2,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +10230,83820,Female,Loyal Customer,67,Business travel,Eco,425,3,5,1,5,1,3,4,3,3,3,3,3,3,3,5,1.0,neutral or dissatisfied +10231,126588,Male,Loyal Customer,28,Business travel,Business,1337,3,3,3,3,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +10232,79412,Male,Loyal Customer,46,Personal Travel,Eco,502,1,4,1,3,2,1,5,2,4,3,4,4,3,2,7,0.0,neutral or dissatisfied +10233,69967,Male,disloyal Customer,26,Business travel,Business,236,3,4,3,1,5,3,3,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +10234,84654,Female,Loyal Customer,61,Personal Travel,Eco,363,4,2,4,4,4,3,3,2,5,4,4,3,3,3,127,133.0,neutral or dissatisfied +10235,108280,Male,Loyal Customer,8,Personal Travel,Eco,895,4,5,4,3,4,4,4,4,3,4,5,3,4,4,5,6.0,neutral or dissatisfied +10236,120826,Male,Loyal Customer,31,Personal Travel,Eco Plus,666,3,2,3,3,5,3,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +10237,1132,Female,Loyal Customer,24,Personal Travel,Eco,354,1,4,1,4,3,1,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +10238,38583,Female,Loyal Customer,28,Business travel,Eco Plus,2475,1,4,4,4,1,1,1,1,3,2,2,4,4,1,56,14.0,neutral or dissatisfied +10239,2703,Female,Loyal Customer,28,Business travel,Business,562,3,3,3,3,3,3,3,3,2,2,3,3,3,3,8,3.0,neutral or dissatisfied +10240,112988,Female,Loyal Customer,41,Business travel,Business,1797,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +10241,68287,Female,disloyal Customer,29,Business travel,Eco,806,3,3,3,3,1,3,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +10242,45251,Female,Loyal Customer,15,Personal Travel,Eco Plus,1013,4,2,4,3,4,4,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +10243,85582,Male,Loyal Customer,44,Business travel,Business,2280,5,5,5,5,5,4,4,5,5,5,4,4,5,4,9,9.0,satisfied +10244,72558,Female,Loyal Customer,46,Business travel,Eco,1121,2,4,4,4,5,3,3,2,2,2,2,1,2,3,0,9.0,neutral or dissatisfied +10245,98436,Female,disloyal Customer,22,Business travel,Business,814,0,0,0,1,4,0,1,4,3,3,5,4,4,4,0,0.0,satisfied +10246,97598,Male,Loyal Customer,38,Business travel,Business,2969,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +10247,23986,Female,disloyal Customer,23,Business travel,Eco,427,4,2,4,3,4,4,1,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +10248,40756,Female,Loyal Customer,27,Business travel,Business,588,3,3,3,3,5,5,5,5,2,2,3,3,5,5,110,93.0,satisfied +10249,76561,Female,Loyal Customer,25,Business travel,Business,3337,3,3,3,3,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +10250,20360,Female,disloyal Customer,80,Business travel,Business,265,3,4,4,4,5,3,5,2,2,3,2,2,2,1,30,15.0,neutral or dissatisfied +10251,85057,Female,disloyal Customer,22,Business travel,Eco,813,1,2,2,3,4,2,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +10252,108406,Female,Loyal Customer,41,Business travel,Business,544,3,3,3,3,4,5,5,5,5,5,5,5,5,5,3,0.0,satisfied +10253,12894,Male,Loyal Customer,29,Business travel,Business,3243,1,1,1,1,4,4,4,4,3,5,5,2,4,4,0,4.0,satisfied +10254,24461,Male,Loyal Customer,31,Business travel,Business,547,3,3,3,3,4,4,4,4,4,5,4,1,1,4,0,0.0,satisfied +10255,35641,Female,disloyal Customer,26,Business travel,Business,2586,1,1,1,2,1,2,2,4,2,3,4,2,3,2,0,27.0,neutral or dissatisfied +10256,4859,Male,disloyal Customer,63,Business travel,Eco,408,4,0,4,3,2,4,2,2,3,5,4,1,3,2,39,38.0,neutral or dissatisfied +10257,47066,Female,Loyal Customer,29,Business travel,Eco,351,0,0,0,3,5,4,5,5,5,1,5,5,1,5,0,0.0,satisfied +10258,83225,Female,Loyal Customer,53,Business travel,Business,2079,1,1,1,1,4,4,4,5,4,4,4,4,4,4,185,204.0,satisfied +10259,121336,Female,Loyal Customer,41,Business travel,Business,2231,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +10260,112573,Female,Loyal Customer,30,Business travel,Business,602,4,4,3,4,4,4,4,4,3,4,5,4,5,4,20,17.0,satisfied +10261,33282,Male,Loyal Customer,7,Personal Travel,Eco Plus,201,3,2,0,3,3,0,5,3,4,1,4,1,4,3,6,6.0,neutral or dissatisfied +10262,107352,Male,Loyal Customer,25,Business travel,Eco,632,2,3,3,3,2,2,3,2,3,2,3,4,3,2,18,4.0,neutral or dissatisfied +10263,35099,Female,Loyal Customer,45,Business travel,Eco,1069,4,5,5,5,2,4,5,4,4,4,4,4,4,5,0,27.0,satisfied +10264,74529,Male,Loyal Customer,39,Business travel,Eco,1171,3,4,4,4,3,2,3,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +10265,74872,Male,disloyal Customer,20,Business travel,Eco,1076,4,4,4,5,1,4,1,1,5,5,5,3,4,1,0,0.0,satisfied +10266,9672,Female,disloyal Customer,23,Business travel,Eco,199,4,0,5,1,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +10267,49840,Male,Loyal Customer,38,Business travel,Eco,262,5,3,3,3,5,5,5,5,5,5,1,3,5,5,0,0.0,satisfied +10268,44877,Male,Loyal Customer,54,Personal Travel,Eco,296,1,5,5,1,5,5,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +10269,30575,Male,disloyal Customer,44,Business travel,Eco,628,3,1,3,3,5,3,3,5,1,4,2,4,2,5,0,0.0,neutral or dissatisfied +10270,77602,Male,disloyal Customer,25,Business travel,Eco,1282,5,5,5,4,3,5,3,3,4,4,4,3,5,3,0,3.0,satisfied +10271,88816,Female,Loyal Customer,45,Business travel,Business,2052,2,2,2,2,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +10272,94206,Male,Loyal Customer,39,Business travel,Business,189,4,4,4,4,2,5,5,4,4,4,4,5,4,4,14,10.0,satisfied +10273,75663,Male,Loyal Customer,49,Business travel,Eco Plus,280,3,5,5,5,3,3,3,3,2,5,4,1,3,3,3,0.0,neutral or dissatisfied +10274,89681,Female,Loyal Customer,53,Business travel,Business,2398,3,3,3,3,3,2,3,2,2,2,2,4,2,3,0,0.0,satisfied +10275,55803,Female,Loyal Customer,10,Personal Travel,Business,1416,4,4,4,3,3,4,3,3,2,4,3,4,4,3,1,0.0,neutral or dissatisfied +10276,8864,Male,Loyal Customer,54,Business travel,Business,622,3,3,2,3,3,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +10277,863,Female,disloyal Customer,36,Business travel,Business,282,2,2,2,4,3,2,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +10278,113764,Female,Loyal Customer,53,Personal Travel,Eco,407,3,2,4,3,2,4,3,3,3,4,3,1,3,2,16,11.0,neutral or dissatisfied +10279,128011,Male,Loyal Customer,42,Business travel,Business,1488,2,2,2,2,2,4,5,4,4,4,4,3,4,4,84,69.0,satisfied +10280,46438,Male,disloyal Customer,20,Business travel,Eco,1199,1,1,1,5,2,1,3,2,4,2,3,5,4,2,11,0.0,neutral or dissatisfied +10281,14990,Female,Loyal Customer,42,Business travel,Business,476,5,5,4,5,5,5,4,4,4,4,4,4,4,3,21,9.0,satisfied +10282,72472,Male,disloyal Customer,26,Business travel,Business,1017,2,2,2,5,3,2,5,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +10283,60028,Female,Loyal Customer,31,Personal Travel,Eco,937,2,4,2,4,1,2,1,1,4,4,4,3,5,1,2,0.0,neutral or dissatisfied +10284,30987,Female,Loyal Customer,46,Personal Travel,Eco,1476,4,3,4,3,5,4,4,3,3,4,3,2,3,4,0,6.0,neutral or dissatisfied +10285,14701,Male,Loyal Customer,57,Business travel,Eco,419,5,1,1,1,5,5,5,5,1,3,5,4,2,5,31,13.0,satisfied +10286,14761,Male,Loyal Customer,65,Business travel,Business,463,4,4,1,4,5,1,2,5,5,4,5,5,5,2,0,0.0,satisfied +10287,41765,Female,Loyal Customer,14,Business travel,Business,872,2,2,2,2,4,4,4,4,5,1,5,4,4,4,8,8.0,satisfied +10288,80469,Female,Loyal Customer,34,Business travel,Business,1299,3,3,3,3,3,2,4,2,2,2,2,4,2,3,0,0.0,satisfied +10289,50998,Male,Loyal Customer,65,Personal Travel,Eco,373,2,0,2,5,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +10290,81851,Female,Loyal Customer,13,Personal Travel,Eco,1501,3,5,3,4,2,3,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +10291,117701,Female,Loyal Customer,58,Business travel,Business,1814,1,1,1,1,2,4,4,4,4,4,4,4,4,5,33,40.0,satisfied +10292,21055,Female,disloyal Customer,23,Business travel,Eco,214,2,2,2,3,2,2,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +10293,115183,Female,Loyal Customer,27,Business travel,Business,373,2,1,3,1,2,2,2,2,3,1,3,4,3,2,5,0.0,neutral or dissatisfied +10294,42247,Male,Loyal Customer,35,Business travel,Eco,451,2,2,2,2,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +10295,120305,Female,Loyal Customer,60,Business travel,Business,2913,1,4,1,1,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +10296,95034,Male,Loyal Customer,8,Personal Travel,Eco,319,2,3,2,5,1,2,1,1,5,5,5,5,1,1,26,16.0,neutral or dissatisfied +10297,45588,Female,Loyal Customer,49,Business travel,Eco,260,4,2,2,2,1,4,1,4,4,4,4,1,4,4,10,18.0,satisfied +10298,12374,Female,Loyal Customer,33,Business travel,Eco,253,5,3,5,3,5,5,5,5,3,2,2,1,2,5,36,29.0,satisfied +10299,69864,Female,Loyal Customer,15,Personal Travel,Eco,1055,1,5,1,4,3,1,3,3,4,2,5,3,4,3,45,22.0,neutral or dissatisfied +10300,121629,Female,Loyal Customer,67,Personal Travel,Eco,936,3,5,3,2,5,4,5,3,3,3,3,3,3,4,7,0.0,neutral or dissatisfied +10301,26639,Male,Loyal Customer,50,Business travel,Eco,515,3,1,1,1,3,3,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +10302,67550,Male,Loyal Customer,42,Personal Travel,Business,1171,2,5,2,2,5,4,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +10303,65660,Female,Loyal Customer,48,Business travel,Business,1021,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +10304,84413,Male,Loyal Customer,38,Personal Travel,Eco,591,4,2,4,3,5,4,2,5,3,1,3,3,4,5,1,0.0,satisfied +10305,25603,Male,Loyal Customer,32,Business travel,Business,1616,5,5,5,5,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +10306,38649,Female,Loyal Customer,44,Business travel,Business,2704,4,5,4,4,2,2,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +10307,82631,Female,Loyal Customer,7,Personal Travel,Eco,528,3,5,3,5,4,3,3,4,1,2,4,5,4,4,8,0.0,neutral or dissatisfied +10308,1848,Male,Loyal Customer,9,Personal Travel,Eco,500,3,2,3,3,4,3,5,4,2,4,4,4,4,4,2,0.0,neutral or dissatisfied +10309,4052,Male,Loyal Customer,28,Personal Travel,Eco,479,3,5,3,4,4,3,4,4,4,4,4,1,2,4,2,0.0,neutral or dissatisfied +10310,115951,Female,Loyal Customer,26,Personal Travel,Eco,480,2,3,2,4,3,2,3,3,4,4,4,2,4,3,16,13.0,neutral or dissatisfied +10311,39466,Female,Loyal Customer,14,Personal Travel,Eco Plus,129,5,1,5,2,3,5,2,3,3,4,1,2,3,3,0,0.0,satisfied +10312,116955,Female,Loyal Customer,50,Business travel,Business,3752,5,4,5,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +10313,49942,Male,Loyal Customer,33,Business travel,Business,190,3,3,3,3,4,4,3,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +10314,6874,Male,Loyal Customer,15,Personal Travel,Eco,622,4,3,3,3,1,3,1,1,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +10315,109711,Male,Loyal Customer,39,Business travel,Business,587,4,4,4,4,2,4,5,5,5,5,5,3,5,5,42,42.0,satisfied +10316,39924,Male,disloyal Customer,22,Business travel,Business,1087,0,3,0,4,3,3,3,3,1,2,1,5,3,3,0,0.0,satisfied +10317,53878,Female,Loyal Customer,50,Personal Travel,Eco,140,2,3,2,3,4,3,4,4,4,2,4,2,4,2,50,80.0,neutral or dissatisfied +10318,7434,Male,Loyal Customer,61,Personal Travel,Eco,522,4,5,4,4,4,4,4,4,3,4,5,4,4,4,59,147.0,neutral or dissatisfied +10319,105144,Male,Loyal Customer,53,Business travel,Eco,289,3,3,3,3,3,3,3,3,2,5,3,1,2,3,16,7.0,neutral or dissatisfied +10320,71147,Female,Loyal Customer,39,Business travel,Business,3018,3,3,3,3,4,5,5,4,4,4,4,3,4,4,1,0.0,satisfied +10321,22341,Female,disloyal Customer,62,Business travel,Eco,143,3,5,3,4,4,3,4,4,5,1,3,3,4,4,0,0.0,neutral or dissatisfied +10322,66138,Male,Loyal Customer,13,Personal Travel,Eco,583,3,4,3,3,4,3,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +10323,84167,Female,Loyal Customer,58,Business travel,Business,231,1,1,1,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +10324,90034,Male,Loyal Customer,42,Business travel,Business,2626,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +10325,51278,Male,Loyal Customer,53,Business travel,Eco Plus,373,4,1,1,1,4,4,4,4,4,2,4,1,3,4,0,0.0,satisfied +10326,116533,Male,Loyal Customer,35,Personal Travel,Eco,337,2,5,2,3,4,2,1,4,3,4,5,3,5,4,5,9.0,neutral or dissatisfied +10327,36423,Female,Loyal Customer,45,Business travel,Business,1617,2,1,2,1,3,3,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +10328,33054,Female,Loyal Customer,32,Personal Travel,Eco,101,4,5,4,2,4,4,3,4,5,4,4,1,1,4,0,0.0,neutral or dissatisfied +10329,40414,Male,Loyal Customer,37,Business travel,Eco,461,5,4,4,4,5,5,5,5,1,4,4,3,4,5,0,5.0,satisfied +10330,50627,Female,Loyal Customer,51,Personal Travel,Eco,109,1,1,0,3,3,3,3,3,3,0,3,2,3,1,0,0.0,neutral or dissatisfied +10331,80791,Female,Loyal Customer,36,Business travel,Business,3128,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +10332,80505,Male,Loyal Customer,44,Business travel,Business,1749,3,3,3,3,3,5,5,2,2,2,2,3,2,4,24,24.0,satisfied +10333,35747,Female,Loyal Customer,25,Business travel,Business,1826,3,3,3,3,4,4,4,4,2,2,5,4,5,4,0,0.0,satisfied +10334,122804,Male,Loyal Customer,40,Business travel,Business,3018,2,5,5,5,1,2,2,2,2,2,2,2,2,2,29,10.0,neutral or dissatisfied +10335,24211,Female,disloyal Customer,36,Business travel,Eco,147,3,5,3,4,4,3,4,4,1,3,5,4,1,4,0,2.0,neutral or dissatisfied +10336,73112,Female,Loyal Customer,22,Business travel,Business,2174,3,2,2,2,3,3,3,3,3,2,3,3,4,3,32,58.0,neutral or dissatisfied +10337,37338,Male,disloyal Customer,25,Business travel,Eco,1074,3,2,2,5,2,2,3,2,4,1,4,1,2,2,0,0.0,neutral or dissatisfied +10338,96718,Female,disloyal Customer,10,Business travel,Eco,696,3,3,3,1,2,3,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +10339,37715,Female,Loyal Customer,35,Personal Travel,Eco,944,2,4,2,2,5,2,5,5,2,1,4,5,1,5,28,22.0,neutral or dissatisfied +10340,33981,Male,Loyal Customer,35,Business travel,Business,1576,5,5,2,5,5,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +10341,48853,Female,Loyal Customer,18,Personal Travel,Business,158,2,5,2,5,1,2,1,1,3,4,4,5,5,1,53,49.0,neutral or dissatisfied +10342,34437,Male,disloyal Customer,30,Business travel,Eco,2422,4,5,5,2,2,4,5,2,2,5,4,5,2,2,38,28.0,neutral or dissatisfied +10343,9413,Female,Loyal Customer,45,Personal Travel,Eco,1027,4,5,3,3,3,5,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +10344,128381,Female,Loyal Customer,47,Business travel,Business,1774,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +10345,96169,Male,Loyal Customer,50,Business travel,Business,666,3,3,3,3,3,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +10346,39770,Male,disloyal Customer,35,Business travel,Eco,546,2,2,2,3,1,2,1,1,1,1,3,1,3,1,4,7.0,neutral or dissatisfied +10347,110991,Female,Loyal Customer,49,Business travel,Business,2528,0,5,0,2,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +10348,129038,Male,Loyal Customer,54,Business travel,Business,1744,4,4,4,4,5,4,4,5,4,3,5,4,4,4,302,319.0,satisfied +10349,54533,Male,Loyal Customer,54,Personal Travel,Eco,925,4,5,4,2,3,4,3,3,4,5,5,4,5,3,9,27.0,neutral or dissatisfied +10350,115115,Male,disloyal Customer,20,Business travel,Eco,337,3,0,3,5,3,3,3,3,3,4,4,5,5,3,45,63.0,neutral or dissatisfied +10351,127501,Male,Loyal Customer,28,Personal Travel,Eco,2075,1,5,1,5,4,1,3,4,2,2,4,3,5,4,7,20.0,neutral or dissatisfied +10352,13712,Male,Loyal Customer,35,Personal Travel,Business,401,1,4,1,3,5,5,4,2,2,1,2,4,2,4,57,46.0,neutral or dissatisfied +10353,65734,Female,Loyal Customer,46,Business travel,Business,1670,2,2,2,2,4,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +10354,85602,Female,Loyal Customer,42,Business travel,Business,3262,0,0,0,4,5,3,4,3,3,3,3,5,3,3,6,2.0,satisfied +10355,32392,Male,Loyal Customer,35,Business travel,Business,2578,3,3,5,3,4,1,2,4,4,4,3,5,4,5,0,0.0,satisfied +10356,30198,Male,Loyal Customer,29,Business travel,Eco Plus,234,4,5,5,5,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +10357,19826,Male,Loyal Customer,27,Business travel,Eco,528,2,3,3,3,2,2,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +10358,61448,Male,Loyal Customer,44,Business travel,Business,2442,1,1,1,1,4,4,5,4,4,4,4,4,4,5,25,11.0,satisfied +10359,56761,Male,Loyal Customer,41,Business travel,Business,997,3,3,3,3,5,4,5,5,5,5,5,5,5,5,34,13.0,satisfied +10360,47731,Male,Loyal Customer,46,Business travel,Business,2066,3,4,4,4,4,2,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +10361,103303,Male,Loyal Customer,58,Business travel,Business,3653,5,5,4,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +10362,72707,Male,Loyal Customer,40,Business travel,Business,1017,4,4,3,4,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +10363,24931,Female,Loyal Customer,22,Personal Travel,Eco,762,5,3,5,4,2,5,2,2,3,4,3,3,3,2,0,0.0,satisfied +10364,14629,Male,Loyal Customer,28,Personal Travel,Eco,541,5,3,5,1,4,5,4,4,4,2,3,1,2,4,0,0.0,satisfied +10365,107703,Male,disloyal Customer,23,Business travel,Eco,251,4,2,4,4,4,4,4,4,3,2,4,4,3,4,13,7.0,neutral or dissatisfied +10366,89418,Female,disloyal Customer,38,Business travel,Eco,151,2,1,2,4,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +10367,15582,Male,Loyal Customer,34,Business travel,Eco,283,5,4,4,4,5,5,5,5,5,2,4,2,4,5,0,0.0,satisfied +10368,15547,Female,disloyal Customer,37,Business travel,Business,296,3,3,3,4,3,3,2,3,4,4,4,3,5,3,23,16.0,neutral or dissatisfied +10369,122764,Female,Loyal Customer,58,Business travel,Eco Plus,651,1,5,5,5,2,4,4,1,1,1,1,1,1,2,0,8.0,neutral or dissatisfied +10370,24651,Female,Loyal Customer,25,Business travel,Business,3606,2,2,2,2,4,4,4,4,5,1,2,1,4,4,0,0.0,satisfied +10371,73047,Female,Loyal Customer,61,Personal Travel,Eco,1096,4,3,4,3,3,4,3,1,1,4,1,3,1,4,0,0.0,neutral or dissatisfied +10372,64305,Female,Loyal Customer,47,Business travel,Business,1172,5,5,5,5,5,4,5,4,4,4,4,3,4,5,29,16.0,satisfied +10373,124818,Male,disloyal Customer,36,Business travel,Business,280,1,1,1,2,5,1,5,5,4,1,2,3,2,5,0,25.0,neutral or dissatisfied +10374,105473,Male,Loyal Customer,7,Business travel,Business,1514,1,5,5,5,1,1,1,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +10375,37946,Female,disloyal Customer,23,Business travel,Eco,1065,4,4,4,3,1,4,1,1,1,5,5,3,1,1,0,0.0,neutral or dissatisfied +10376,34178,Male,Loyal Customer,59,Business travel,Eco,779,5,1,2,1,5,5,5,5,2,3,1,2,1,5,0,10.0,satisfied +10377,64173,Female,Loyal Customer,26,Business travel,Business,2916,2,2,2,2,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +10378,19418,Female,Loyal Customer,28,Business travel,Business,2297,1,1,4,1,4,4,4,4,2,4,4,2,3,4,0,0.0,satisfied +10379,127816,Male,Loyal Customer,46,Business travel,Business,3217,1,4,4,4,2,4,3,1,1,1,1,2,1,1,0,4.0,neutral or dissatisfied +10380,56502,Female,Loyal Customer,50,Business travel,Business,2120,1,1,1,1,5,5,5,4,4,4,4,3,4,3,31,41.0,satisfied +10381,66147,Male,Loyal Customer,25,Business travel,Business,583,4,4,4,4,4,4,4,4,4,2,5,5,5,4,7,0.0,satisfied +10382,107366,Female,Loyal Customer,46,Personal Travel,Eco,584,3,2,3,4,5,4,3,5,5,3,5,3,5,4,12,0.0,neutral or dissatisfied +10383,25379,Male,Loyal Customer,41,Business travel,Eco,591,5,4,4,4,5,5,5,5,2,3,2,2,4,5,1,2.0,satisfied +10384,53444,Male,Loyal Customer,23,Business travel,Eco,2442,2,2,2,2,2,1,2,1,2,2,4,2,2,2,283,273.0,neutral or dissatisfied +10385,26420,Female,Loyal Customer,62,Personal Travel,Business,925,2,4,2,4,2,5,4,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +10386,52827,Male,Loyal Customer,43,Business travel,Business,1721,3,3,3,3,4,4,4,3,3,3,3,4,3,4,24,35.0,satisfied +10387,55897,Female,disloyal Customer,23,Business travel,Eco,733,2,2,2,3,2,2,2,2,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +10388,21243,Male,Loyal Customer,20,Personal Travel,Eco,317,2,5,2,4,3,2,3,3,2,1,3,2,1,3,0,0.0,neutral or dissatisfied +10389,7913,Male,Loyal Customer,43,Business travel,Business,2164,1,4,4,4,2,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +10390,54970,Female,Loyal Customer,30,Business travel,Business,1609,5,5,5,5,2,2,2,2,3,3,4,4,4,2,17,18.0,satisfied +10391,27049,Male,disloyal Customer,34,Business travel,Eco,863,3,3,3,4,2,3,2,2,5,3,4,1,1,2,0,0.0,neutral or dissatisfied +10392,71958,Female,Loyal Customer,43,Business travel,Business,1440,1,1,2,1,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +10393,70871,Female,Loyal Customer,64,Personal Travel,Eco,761,2,5,2,4,4,4,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +10394,115166,Female,disloyal Customer,33,Business travel,Business,417,1,2,2,1,2,2,2,2,3,2,4,5,5,2,19,1.0,neutral or dissatisfied +10395,119027,Male,Loyal Customer,35,Business travel,Business,1460,3,2,2,2,5,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +10396,32062,Male,Loyal Customer,35,Business travel,Business,101,3,3,3,3,5,5,5,4,4,4,3,2,4,3,0,0.0,satisfied +10397,4430,Female,Loyal Customer,46,Business travel,Business,2131,2,2,2,2,2,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +10398,94801,Female,Loyal Customer,60,Business travel,Eco,239,4,5,4,4,1,3,3,4,4,4,4,3,4,2,0,4.0,neutral or dissatisfied +10399,39086,Male,Loyal Customer,18,Business travel,Business,2334,1,3,3,3,1,1,1,1,1,5,4,4,4,1,0,0.0,neutral or dissatisfied +10400,61147,Male,Loyal Customer,43,Business travel,Business,3906,3,3,3,3,2,4,4,5,5,5,5,5,5,5,7,10.0,satisfied +10401,17699,Male,Loyal Customer,8,Personal Travel,Eco,854,1,5,1,3,1,1,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +10402,112992,Male,Loyal Customer,36,Business travel,Business,1797,2,2,2,2,2,3,4,5,5,5,5,5,5,5,109,87.0,satisfied +10403,61428,Male,disloyal Customer,33,Business travel,Business,2288,2,2,2,1,2,2,2,2,4,5,4,5,4,2,20,12.0,neutral or dissatisfied +10404,74393,Male,disloyal Customer,22,Business travel,Business,1126,4,1,4,4,5,4,4,5,4,5,5,3,4,5,0,9.0,satisfied +10405,32685,Female,disloyal Customer,35,Business travel,Eco,101,1,2,1,3,2,1,2,2,4,1,3,1,4,2,14,13.0,neutral or dissatisfied +10406,54826,Female,Loyal Customer,52,Business travel,Business,3161,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +10407,37231,Male,Loyal Customer,33,Business travel,Business,1076,3,1,1,1,3,3,3,3,4,2,3,1,4,3,19,0.0,neutral or dissatisfied +10408,57043,Male,disloyal Customer,28,Business travel,Business,2133,2,2,2,3,1,2,1,1,5,2,5,5,5,1,26,41.0,neutral or dissatisfied +10409,6495,Female,Loyal Customer,69,Personal Travel,Eco,557,2,4,3,3,2,2,5,2,2,3,4,1,2,1,19,23.0,neutral or dissatisfied +10410,109997,Male,Loyal Customer,12,Personal Travel,Business,1204,4,4,4,3,2,4,2,2,2,4,3,4,4,2,37,21.0,satisfied +10411,34827,Female,disloyal Customer,35,Business travel,Eco Plus,301,2,2,2,5,3,2,3,3,1,2,4,2,2,3,0,0.0,neutral or dissatisfied +10412,9247,Male,Loyal Customer,9,Personal Travel,Eco,100,0,1,0,4,3,0,4,3,3,2,3,1,4,3,0,0.0,satisfied +10413,21637,Female,Loyal Customer,50,Personal Travel,Eco,780,3,5,3,4,2,4,5,1,1,3,1,4,1,4,21,30.0,neutral or dissatisfied +10414,76170,Female,Loyal Customer,24,Personal Travel,Eco,546,4,3,4,2,3,4,3,3,4,1,4,4,3,3,0,9.0,neutral or dissatisfied +10415,12057,Male,Loyal Customer,15,Personal Travel,Eco,351,2,1,2,3,2,2,2,2,1,5,2,4,2,2,0,0.0,neutral or dissatisfied +10416,9176,Male,Loyal Customer,63,Personal Travel,Eco,416,4,5,4,3,4,4,4,4,4,2,2,3,5,4,0,0.0,satisfied +10417,92192,Male,Loyal Customer,59,Business travel,Business,2079,5,5,5,5,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +10418,46093,Male,Loyal Customer,40,Personal Travel,Eco,495,3,5,3,1,4,3,5,4,4,4,2,1,5,4,0,0.0,neutral or dissatisfied +10419,112025,Female,Loyal Customer,41,Business travel,Business,1573,5,5,5,5,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +10420,71443,Female,disloyal Customer,26,Business travel,Business,867,3,3,3,4,5,3,2,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +10421,60303,Male,Loyal Customer,58,Business travel,Business,406,1,1,1,1,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +10422,126755,Female,Loyal Customer,36,Personal Travel,Eco,2402,3,3,2,4,5,2,3,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +10423,44925,Male,Loyal Customer,41,Business travel,Business,2733,3,3,3,3,5,5,5,5,1,3,1,5,1,5,186,209.0,satisfied +10424,96603,Female,Loyal Customer,25,Business travel,Business,3764,3,3,3,3,4,4,4,4,4,3,5,3,5,4,108,129.0,satisfied +10425,69734,Female,Loyal Customer,62,Personal Travel,Eco,1372,3,4,2,2,3,4,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +10426,78802,Male,Loyal Customer,42,Personal Travel,Eco,447,1,5,1,3,4,1,4,4,5,2,4,4,5,4,0,15.0,neutral or dissatisfied +10427,89193,Male,Loyal Customer,31,Personal Travel,Eco,1892,2,2,1,3,5,1,5,5,1,5,2,2,3,5,35,36.0,neutral or dissatisfied +10428,40102,Female,Loyal Customer,55,Business travel,Business,1948,3,4,4,4,5,4,4,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +10429,19573,Female,disloyal Customer,25,Business travel,Eco,173,2,1,2,4,2,2,2,2,1,5,3,4,3,2,37,30.0,neutral or dissatisfied +10430,74419,Female,disloyal Customer,23,Business travel,Eco,1205,1,1,1,4,1,1,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +10431,66178,Male,disloyal Customer,27,Business travel,Business,460,2,2,2,2,1,2,1,1,3,5,5,5,4,1,16,11.0,neutral or dissatisfied +10432,92270,Male,Loyal Customer,56,Business travel,Business,2036,5,5,5,5,4,3,5,5,5,5,5,3,5,3,7,11.0,satisfied +10433,78460,Female,Loyal Customer,42,Business travel,Business,3406,1,1,1,1,5,4,5,5,5,5,5,3,5,4,17,41.0,satisfied +10434,3460,Female,Loyal Customer,60,Business travel,Business,2215,2,5,5,5,3,2,2,2,2,2,2,1,2,2,6,3.0,neutral or dissatisfied +10435,74060,Female,Loyal Customer,66,Personal Travel,Eco Plus,2527,4,3,4,4,4,3,3,1,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +10436,97333,Female,Loyal Customer,58,Business travel,Business,1608,4,4,4,4,4,5,5,4,4,4,4,4,4,3,5,0.0,satisfied +10437,126187,Male,Loyal Customer,47,Business travel,Eco,328,3,4,4,4,3,3,3,3,4,2,4,1,4,3,0,14.0,neutral or dissatisfied +10438,98883,Male,Loyal Customer,56,Personal Travel,Eco,991,0,5,1,5,4,1,4,4,5,5,5,5,5,4,0,0.0,satisfied +10439,51142,Male,Loyal Customer,8,Personal Travel,Eco,86,1,4,1,5,2,1,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +10440,70666,Male,Loyal Customer,50,Business travel,Business,3704,5,5,5,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +10441,105443,Male,Loyal Customer,41,Business travel,Business,998,3,3,3,3,2,5,5,5,5,4,5,3,5,5,0,6.0,satisfied +10442,79913,Female,Loyal Customer,70,Business travel,Business,2747,4,2,2,2,2,3,2,4,4,4,4,1,4,2,19,26.0,neutral or dissatisfied +10443,51756,Male,Loyal Customer,35,Personal Travel,Eco,451,2,5,2,4,1,2,1,1,3,5,4,3,5,1,0,9.0,neutral or dissatisfied +10444,63674,Male,Loyal Customer,25,Personal Travel,Business,1047,3,4,3,2,5,3,5,5,5,4,4,3,4,5,0,6.0,neutral or dissatisfied +10445,51151,Female,Loyal Customer,55,Personal Travel,Eco,109,2,5,0,5,2,5,4,4,4,0,2,5,4,4,0,0.0,neutral or dissatisfied +10446,115603,Female,Loyal Customer,46,Business travel,Business,2398,5,5,5,5,2,5,4,4,4,4,4,3,4,4,61,53.0,satisfied +10447,22361,Male,Loyal Customer,29,Business travel,Business,143,0,4,0,4,2,3,3,2,3,5,4,4,3,2,0,0.0,satisfied +10448,97507,Female,Loyal Customer,22,Business travel,Business,756,1,1,1,1,3,4,3,3,4,2,5,5,5,3,0,0.0,satisfied +10449,59442,Female,Loyal Customer,57,Business travel,Business,206,2,2,4,2,5,1,3,5,5,5,4,4,5,2,0,0.0,satisfied +10450,15400,Male,disloyal Customer,26,Business travel,Eco,306,2,0,1,1,3,1,3,3,3,2,4,1,5,3,0,0.0,neutral or dissatisfied +10451,11749,Female,disloyal Customer,21,Business travel,Eco,429,1,2,1,3,1,1,5,1,2,4,3,2,4,1,92,96.0,neutral or dissatisfied +10452,114365,Female,disloyal Customer,57,Business travel,Business,948,2,2,2,3,5,2,5,5,5,4,5,3,5,5,24,11.0,neutral or dissatisfied +10453,66424,Male,Loyal Customer,57,Personal Travel,Eco,1562,4,4,4,3,3,4,3,3,5,4,5,3,5,3,0,0.0,satisfied +10454,33129,Male,Loyal Customer,25,Personal Travel,Eco,163,5,4,5,3,3,5,3,3,5,5,4,4,5,3,0,0.0,satisfied +10455,21039,Male,disloyal Customer,43,Business travel,Eco,106,3,4,3,4,5,3,5,5,2,5,2,1,5,5,0,2.0,neutral or dissatisfied +10456,37064,Male,Loyal Customer,32,Business travel,Business,3814,5,5,5,5,4,3,4,4,2,4,2,4,5,4,0,0.0,satisfied +10457,77843,Female,disloyal Customer,25,Business travel,Business,731,2,4,2,3,3,2,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +10458,15602,Female,Loyal Customer,47,Business travel,Business,3624,1,1,1,1,3,4,1,4,4,4,4,4,4,1,0,0.0,satisfied +10459,90122,Female,disloyal Customer,39,Business travel,Business,1084,1,2,2,4,3,2,3,3,1,2,4,1,3,3,33,30.0,neutral or dissatisfied +10460,106273,Male,disloyal Customer,28,Business travel,Business,604,1,1,1,4,1,1,1,1,3,2,5,5,4,1,31,27.0,neutral or dissatisfied +10461,28157,Female,Loyal Customer,22,Business travel,Business,859,1,5,5,5,1,1,1,1,2,5,4,2,4,1,0,0.0,neutral or dissatisfied +10462,108924,Male,Loyal Customer,51,Personal Travel,Eco,1183,1,5,1,4,2,1,2,2,4,5,3,3,4,2,12,8.0,neutral or dissatisfied +10463,32984,Female,Loyal Customer,37,Personal Travel,Eco,216,2,4,2,3,5,2,5,5,4,2,3,4,4,5,0,0.0,neutral or dissatisfied +10464,63651,Female,Loyal Customer,58,Business travel,Business,1448,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +10465,72121,Female,Loyal Customer,55,Business travel,Business,731,5,5,5,5,4,5,4,5,5,5,5,3,5,5,10,1.0,satisfied +10466,68350,Male,Loyal Customer,26,Business travel,Business,1598,2,1,1,1,2,2,2,2,1,4,2,1,3,2,0,0.0,neutral or dissatisfied +10467,46595,Female,disloyal Customer,39,Business travel,Eco,141,2,1,2,4,4,2,2,4,4,2,4,3,3,4,79,69.0,neutral or dissatisfied +10468,118952,Female,Loyal Customer,43,Business travel,Business,2482,1,1,1,1,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +10469,16437,Male,disloyal Customer,28,Business travel,Eco,416,2,2,2,3,2,2,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +10470,39981,Male,Loyal Customer,7,Personal Travel,Eco,1262,1,1,1,3,1,1,2,1,2,3,2,4,3,1,0,0.0,neutral or dissatisfied +10471,42354,Male,Loyal Customer,64,Personal Travel,Eco,329,0,3,0,4,5,0,5,5,1,3,2,4,2,5,0,0.0,satisfied +10472,64259,Female,disloyal Customer,41,Business travel,Business,1310,3,3,3,2,2,3,2,2,3,3,4,3,4,2,0,0.0,satisfied +10473,127014,Female,Loyal Customer,37,Business travel,Eco,325,2,1,3,1,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +10474,123244,Female,Loyal Customer,28,Personal Travel,Eco,600,3,2,3,3,4,3,4,4,3,4,3,2,4,4,0,0.0,neutral or dissatisfied +10475,55942,Female,Loyal Customer,45,Business travel,Business,1620,2,4,4,4,2,2,2,2,4,2,3,2,4,2,186,171.0,neutral or dissatisfied +10476,102307,Male,Loyal Customer,59,Business travel,Business,236,4,4,4,4,4,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +10477,63550,Male,Loyal Customer,33,Personal Travel,Eco,1009,0,4,0,2,2,0,2,2,3,2,5,4,5,2,0,0.0,satisfied +10478,8429,Male,disloyal Customer,37,Business travel,Eco,462,3,2,3,3,1,3,3,1,4,5,3,1,3,1,0,17.0,neutral or dissatisfied +10479,4993,Male,Loyal Customer,62,Business travel,Business,3054,4,4,4,4,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +10480,69892,Male,disloyal Customer,37,Business travel,Business,1114,3,3,3,3,1,3,1,1,3,4,4,4,4,1,19,0.0,neutral or dissatisfied +10481,73618,Male,Loyal Customer,42,Business travel,Business,3876,2,2,2,2,5,4,5,4,4,4,5,4,4,3,2,0.0,satisfied +10482,98970,Male,Loyal Customer,63,Business travel,Eco,143,4,2,2,2,4,4,4,4,1,3,5,5,5,4,0,0.0,satisfied +10483,74233,Female,Loyal Customer,41,Personal Travel,Eco,888,3,2,3,4,1,3,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +10484,8946,Female,Loyal Customer,49,Personal Travel,Eco,328,1,5,1,3,5,4,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +10485,93480,Female,disloyal Customer,38,Business travel,Business,707,4,4,4,3,3,4,3,3,5,5,5,5,4,3,0,0.0,satisfied +10486,63045,Female,Loyal Customer,53,Personal Travel,Eco,948,3,3,2,3,3,3,4,3,3,2,3,4,3,3,17,5.0,neutral or dissatisfied +10487,6670,Female,Loyal Customer,51,Business travel,Business,3629,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,40.0,satisfied +10488,85538,Male,disloyal Customer,27,Business travel,Business,153,5,5,5,1,3,5,3,3,3,3,5,3,4,3,16,9.0,satisfied +10489,64003,Male,Loyal Customer,42,Personal Travel,Eco,612,1,4,1,4,3,1,2,3,3,5,4,4,5,3,61,80.0,neutral or dissatisfied +10490,89691,Male,disloyal Customer,22,Business travel,Eco,1069,3,3,3,4,3,3,3,3,5,5,1,3,4,3,0,0.0,neutral or dissatisfied +10491,53401,Female,disloyal Customer,22,Business travel,Eco,2288,3,4,4,3,4,3,4,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +10492,55752,Male,Loyal Customer,39,Business travel,Business,237,5,5,3,5,1,4,4,5,5,5,5,5,5,5,0,3.0,satisfied +10493,114758,Male,Loyal Customer,43,Business travel,Business,390,1,1,1,1,4,5,4,4,4,4,4,4,4,5,22,19.0,satisfied +10494,1894,Female,Loyal Customer,41,Personal Travel,Business,351,2,5,2,2,4,4,5,1,1,2,1,4,1,4,13,10.0,neutral or dissatisfied +10495,10549,Male,disloyal Customer,47,Business travel,Business,74,2,2,2,2,3,2,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +10496,93187,Female,Loyal Customer,16,Personal Travel,Eco Plus,1066,2,4,2,3,5,2,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +10497,26996,Male,Loyal Customer,60,Business travel,Eco,867,5,4,4,4,5,5,5,5,3,1,4,5,2,5,3,2.0,satisfied +10498,58219,Male,Loyal Customer,62,Personal Travel,Eco,925,3,4,3,1,4,3,4,4,5,4,5,3,5,4,48,63.0,neutral or dissatisfied +10499,72280,Male,disloyal Customer,35,Business travel,Eco,919,2,2,2,5,5,2,5,5,2,1,2,5,5,5,0,0.0,neutral or dissatisfied +10500,126601,Female,Loyal Customer,46,Business travel,Business,1337,1,1,1,1,5,4,5,5,5,4,5,3,5,3,1,0.0,satisfied +10501,9592,Female,Loyal Customer,7,Personal Travel,Eco,296,2,4,2,3,5,2,5,5,4,3,4,3,4,5,3,41.0,neutral or dissatisfied +10502,56319,Female,Loyal Customer,58,Business travel,Business,3087,2,2,2,2,5,4,5,5,5,5,4,3,5,4,3,5.0,satisfied +10503,32487,Female,Loyal Customer,38,Business travel,Business,3656,1,5,5,5,1,3,4,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +10504,118001,Female,Loyal Customer,48,Personal Travel,Eco Plus,365,3,4,3,5,3,5,5,2,2,3,2,4,2,4,1,0.0,neutral or dissatisfied +10505,20837,Male,Loyal Customer,51,Business travel,Business,457,4,5,4,5,1,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +10506,120739,Female,Loyal Customer,29,Personal Travel,Eco,1089,2,3,2,2,3,2,3,3,3,5,4,2,1,3,0,16.0,neutral or dissatisfied +10507,37148,Male,disloyal Customer,9,Business travel,Eco,1189,4,4,4,3,5,4,5,5,3,2,4,2,4,5,40,31.0,neutral or dissatisfied +10508,121561,Male,Loyal Customer,50,Business travel,Business,3092,1,1,4,1,3,3,3,1,1,1,1,4,1,4,13,69.0,neutral or dissatisfied +10509,17647,Female,Loyal Customer,51,Business travel,Eco,1008,2,5,5,5,2,2,2,2,3,3,2,2,2,2,326,329.0,satisfied +10510,103979,Male,Loyal Customer,36,Business travel,Business,1363,5,5,5,5,2,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +10511,26799,Female,Loyal Customer,49,Business travel,Business,2139,2,2,2,2,3,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +10512,108351,Female,Loyal Customer,57,Business travel,Eco,1750,4,1,1,1,5,3,3,4,4,4,4,3,4,4,77,39.0,neutral or dissatisfied +10513,120520,Female,Loyal Customer,59,Business travel,Business,96,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +10514,126253,Female,disloyal Customer,73,Business travel,Eco,107,3,4,3,4,3,3,1,3,4,2,4,4,4,3,82,81.0,neutral or dissatisfied +10515,124058,Male,Loyal Customer,39,Business travel,Business,2153,3,3,3,3,2,3,4,5,5,5,5,3,5,3,0,11.0,satisfied +10516,39598,Male,Loyal Customer,26,Personal Travel,Eco,965,3,1,3,2,4,3,4,4,3,3,2,3,2,4,0,0.0,neutral or dissatisfied +10517,94504,Female,disloyal Customer,22,Business travel,Eco,248,2,0,2,3,4,2,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +10518,21802,Female,disloyal Customer,34,Business travel,Eco,341,3,2,3,4,5,3,5,5,4,2,3,4,3,5,114,103.0,neutral or dissatisfied +10519,86316,Male,Loyal Customer,25,Personal Travel,Eco Plus,226,0,5,0,3,1,0,1,1,4,3,5,3,5,1,15,7.0,satisfied +10520,39464,Female,Loyal Customer,35,Personal Travel,Eco,129,2,1,2,4,5,2,5,5,3,4,2,1,4,5,0,4.0,neutral or dissatisfied +10521,21201,Female,Loyal Customer,46,Business travel,Eco,192,2,2,2,2,4,1,4,2,2,2,2,3,2,1,0,0.0,satisfied +10522,22333,Female,Loyal Customer,35,Business travel,Business,83,1,1,1,1,5,5,5,5,4,4,2,5,5,5,0,0.0,satisfied +10523,46640,Female,Loyal Customer,42,Business travel,Business,3753,2,1,1,1,1,3,3,3,3,3,2,4,3,1,0,4.0,neutral or dissatisfied +10524,78627,Female,Loyal Customer,42,Business travel,Business,1774,2,2,2,2,3,1,4,5,5,5,5,3,5,5,0,0.0,satisfied +10525,109251,Female,Loyal Customer,15,Personal Travel,Eco,612,1,3,1,2,1,1,1,1,5,2,4,4,1,1,0,0.0,neutral or dissatisfied +10526,57110,Male,disloyal Customer,24,Business travel,Business,1222,5,0,5,2,3,5,3,3,4,2,4,5,5,3,6,13.0,satisfied +10527,627,Male,Loyal Customer,45,Business travel,Business,247,2,2,2,2,5,4,4,5,5,5,5,4,5,3,28,14.0,satisfied +10528,106078,Female,disloyal Customer,39,Business travel,Business,302,5,5,5,3,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +10529,36861,Male,Loyal Customer,31,Business travel,Eco,273,4,3,3,3,4,4,4,4,2,2,4,3,5,4,0,0.0,satisfied +10530,52272,Male,Loyal Customer,25,Business travel,Eco,493,5,4,4,4,5,5,4,5,1,5,1,2,5,5,0,1.0,satisfied +10531,29762,Male,Loyal Customer,58,Business travel,Business,2177,5,5,3,5,2,5,5,4,4,4,5,5,4,3,0,0.0,satisfied +10532,99291,Male,Loyal Customer,21,Personal Travel,Eco,935,2,5,2,4,4,2,1,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +10533,73947,Male,Loyal Customer,38,Business travel,Business,3893,3,3,3,3,4,2,2,4,4,4,4,5,4,3,11,0.0,satisfied +10534,831,Female,disloyal Customer,25,Business travel,Business,247,1,1,1,3,3,1,3,3,1,3,3,3,2,3,0,2.0,neutral or dissatisfied +10535,126314,Female,Loyal Customer,29,Personal Travel,Eco,590,4,4,4,4,4,4,4,4,4,3,4,3,3,4,33,16.0,neutral or dissatisfied +10536,65044,Female,Loyal Customer,46,Personal Travel,Eco,551,2,4,3,4,1,4,3,1,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +10537,66189,Male,Loyal Customer,33,Business travel,Business,460,3,3,3,3,3,4,3,3,3,4,5,4,4,3,53,52.0,satisfied +10538,90196,Female,Loyal Customer,52,Personal Travel,Eco,1145,1,5,1,5,3,3,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +10539,108820,Male,Loyal Customer,41,Personal Travel,Eco Plus,404,3,4,3,3,3,3,2,3,4,2,5,2,3,3,0,0.0,neutral or dissatisfied +10540,119858,Male,Loyal Customer,42,Business travel,Eco,512,5,4,4,4,5,5,5,5,2,1,3,5,2,5,0,0.0,satisfied +10541,95137,Male,Loyal Customer,26,Personal Travel,Eco,239,3,4,3,3,3,3,4,3,5,3,4,3,5,3,3,0.0,neutral or dissatisfied +10542,75055,Male,Loyal Customer,20,Personal Travel,Eco,1592,3,4,3,3,5,3,4,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +10543,127143,Male,Loyal Customer,20,Personal Travel,Eco,621,1,4,1,2,5,1,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +10544,62758,Female,Loyal Customer,56,Business travel,Business,2556,2,3,3,3,2,2,2,1,2,4,4,2,2,2,11,27.0,neutral or dissatisfied +10545,14539,Male,Loyal Customer,21,Business travel,Business,2090,1,1,1,1,5,5,5,5,4,4,4,2,1,5,0,0.0,satisfied +10546,53419,Male,Loyal Customer,55,Business travel,Business,2288,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10547,73794,Male,Loyal Customer,41,Business travel,Business,2457,2,2,2,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +10548,41406,Male,disloyal Customer,20,Business travel,Eco,809,1,1,1,3,1,1,4,1,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +10549,125033,Female,Loyal Customer,28,Business travel,Business,2300,2,2,2,2,2,2,2,2,3,3,5,5,4,2,0,0.0,satisfied +10550,30505,Female,disloyal Customer,30,Business travel,Eco Plus,484,2,2,2,5,1,2,1,1,2,5,1,2,3,1,0,0.0,neutral or dissatisfied +10551,6687,Male,Loyal Customer,29,Business travel,Business,1697,3,3,3,3,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +10552,116823,Female,disloyal Customer,39,Business travel,Business,338,3,3,3,2,5,3,5,5,3,4,4,4,4,5,25,29.0,neutral or dissatisfied +10553,97284,Male,Loyal Customer,44,Personal Travel,Business,1020,2,1,2,4,4,4,3,2,2,2,2,4,2,1,5,3.0,neutral or dissatisfied +10554,92319,Female,disloyal Customer,16,Business travel,Business,1149,0,0,0,2,0,2,2,4,4,3,4,2,3,2,11,3.0,satisfied +10555,57093,Male,Loyal Customer,42,Business travel,Business,1222,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +10556,25105,Male,Loyal Customer,23,Business travel,Business,946,4,4,4,4,4,5,4,4,4,3,5,4,4,4,0,0.0,satisfied +10557,56798,Male,Loyal Customer,30,Business travel,Business,1605,5,5,5,5,3,3,3,3,5,3,3,3,4,3,98,68.0,satisfied +10558,14901,Male,disloyal Customer,23,Business travel,Eco,240,2,0,2,1,5,2,5,5,4,4,4,4,2,5,0,0.0,neutral or dissatisfied +10559,43825,Male,disloyal Customer,50,Business travel,Eco,144,4,4,4,2,3,4,3,3,2,4,4,1,3,3,0,0.0,satisfied +10560,54763,Female,disloyal Customer,18,Business travel,Eco,964,3,3,3,1,3,3,3,3,2,2,5,4,3,3,0,0.0,neutral or dissatisfied +10561,20236,Female,disloyal Customer,20,Business travel,Eco,137,1,1,1,4,1,1,1,1,1,2,4,4,3,1,26,26.0,neutral or dissatisfied +10562,129248,Male,Loyal Customer,69,Personal Travel,Eco,1464,1,5,1,3,2,1,2,2,4,2,4,4,4,2,0,1.0,neutral or dissatisfied +10563,15370,Female,Loyal Customer,37,Business travel,Business,3779,4,4,4,4,1,3,3,4,4,4,3,5,4,3,0,0.0,satisfied +10564,101323,Male,Loyal Customer,36,Personal Travel,Eco,986,3,5,3,1,5,3,1,5,4,5,5,3,4,5,63,54.0,neutral or dissatisfied +10565,54950,Male,Loyal Customer,39,Business travel,Business,1303,4,4,4,4,5,4,4,5,5,5,5,5,5,3,4,0.0,satisfied +10566,124489,Female,Loyal Customer,21,Business travel,Business,3480,2,2,2,2,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +10567,116564,Female,Loyal Customer,41,Business travel,Business,480,3,3,3,3,5,5,5,2,2,2,2,5,2,4,1,0.0,satisfied +10568,73554,Male,disloyal Customer,24,Business travel,Eco,192,5,4,5,5,2,5,2,2,5,3,5,4,5,2,0,0.0,satisfied +10569,75727,Male,Loyal Customer,46,Business travel,Business,3765,3,3,3,3,3,5,5,4,4,3,4,3,4,5,0,0.0,satisfied +10570,67628,Female,Loyal Customer,48,Business travel,Business,3614,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,2.0,satisfied +10571,99966,Female,Loyal Customer,36,Business travel,Business,1575,5,5,2,5,4,2,3,5,5,5,5,5,5,4,3,4.0,satisfied +10572,38970,Male,Loyal Customer,39,Business travel,Business,1693,1,3,1,1,3,3,2,4,4,4,4,2,4,5,0,0.0,satisfied +10573,49500,Female,Loyal Customer,46,Business travel,Business,3849,3,3,3,3,5,3,1,4,4,3,4,5,4,1,0,0.0,satisfied +10574,46862,Female,Loyal Customer,56,Business travel,Business,3466,1,1,1,1,1,1,3,3,3,4,3,5,3,3,0,5.0,satisfied +10575,72667,Female,Loyal Customer,17,Personal Travel,Eco,918,4,1,3,2,3,3,3,3,4,4,2,4,3,3,0,0.0,neutral or dissatisfied +10576,59049,Female,Loyal Customer,43,Business travel,Eco,1744,3,1,1,1,2,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +10577,42227,Male,Loyal Customer,47,Business travel,Business,550,4,4,4,4,4,2,5,5,5,5,5,4,5,4,0,0.0,satisfied +10578,32687,Male,Loyal Customer,46,Business travel,Business,3101,1,4,4,4,1,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +10579,22320,Male,disloyal Customer,39,Business travel,Eco,238,2,0,2,4,4,2,4,4,1,3,4,3,1,4,0,0.0,neutral or dissatisfied +10580,25882,Male,Loyal Customer,32,Business travel,Business,3116,1,1,1,1,5,5,5,5,3,2,4,4,2,5,5,19.0,satisfied +10581,61558,Female,Loyal Customer,22,Business travel,Business,2288,3,3,4,3,4,4,4,4,3,3,3,5,4,4,0,0.0,satisfied +10582,27441,Female,Loyal Customer,23,Business travel,Eco,605,2,4,4,4,2,2,4,2,4,4,3,3,3,2,0,0.0,neutral or dissatisfied +10583,126339,Female,Loyal Customer,33,Personal Travel,Eco,631,3,3,3,4,1,3,1,1,1,1,2,3,1,1,16,30.0,neutral or dissatisfied +10584,86558,Female,disloyal Customer,30,Business travel,Eco Plus,760,3,3,3,4,5,3,5,5,2,1,4,2,3,5,28,11.0,neutral or dissatisfied +10585,41651,Male,Loyal Customer,28,Business travel,Business,3326,2,2,4,2,4,4,4,4,2,2,3,3,5,4,0,0.0,satisfied +10586,8585,Female,Loyal Customer,58,Personal Travel,Eco,109,5,4,0,4,2,4,5,1,1,0,1,5,1,4,0,0.0,satisfied +10587,129791,Female,Loyal Customer,66,Personal Travel,Eco,308,3,5,3,4,1,5,5,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +10588,33466,Female,Loyal Customer,28,Personal Travel,Eco Plus,2409,3,4,3,3,2,3,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +10589,103959,Female,Loyal Customer,28,Personal Travel,Eco,770,1,5,1,1,2,1,2,2,3,3,4,5,4,2,0,7.0,neutral or dissatisfied +10590,12205,Female,disloyal Customer,24,Business travel,Business,201,2,4,3,3,4,3,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +10591,29231,Male,Loyal Customer,36,Business travel,Eco,569,5,3,3,3,5,5,5,5,1,1,3,1,3,5,0,0.0,satisfied +10592,93998,Female,Loyal Customer,57,Business travel,Business,2565,4,5,4,4,2,5,4,5,5,5,5,3,5,5,25,25.0,satisfied +10593,77319,Female,Loyal Customer,51,Business travel,Business,588,5,1,5,5,5,4,5,5,5,5,5,5,5,4,13,2.0,satisfied +10594,75443,Female,disloyal Customer,25,Business travel,Eco,1027,2,2,2,2,3,2,5,3,1,3,2,1,3,3,0,0.0,neutral or dissatisfied +10595,81007,Female,Loyal Customer,57,Business travel,Business,3640,4,4,4,4,3,4,5,5,5,5,5,5,5,5,40,30.0,satisfied +10596,58096,Female,disloyal Customer,30,Business travel,Eco,589,2,1,2,4,3,2,1,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +10597,8578,Male,Loyal Customer,51,Business travel,Business,2366,1,5,4,5,2,1,1,4,4,3,1,1,4,3,0,0.0,neutral or dissatisfied +10598,60720,Male,Loyal Customer,35,Business travel,Eco,1795,2,3,3,3,2,2,2,2,2,2,3,4,5,2,26,0.0,satisfied +10599,118392,Female,disloyal Customer,27,Business travel,Business,325,1,1,1,2,4,1,4,4,4,3,3,4,2,4,16,14.0,neutral or dissatisfied +10600,13440,Female,Loyal Customer,36,Business travel,Business,2290,1,4,4,4,1,4,4,1,1,1,1,3,1,2,0,12.0,neutral or dissatisfied +10601,12407,Male,Loyal Customer,16,Business travel,Business,1978,5,5,5,5,5,4,5,5,3,2,2,2,4,5,5,0.0,satisfied +10602,67463,Male,Loyal Customer,9,Personal Travel,Eco,592,2,5,2,2,1,2,1,1,2,4,1,5,4,1,0,0.0,neutral or dissatisfied +10603,74381,Female,disloyal Customer,24,Business travel,Business,1464,4,4,4,4,4,4,4,4,5,4,4,4,4,4,11,0.0,satisfied +10604,113136,Female,Loyal Customer,46,Personal Travel,Eco Plus,479,2,5,3,4,2,3,2,1,1,3,4,3,1,2,29,14.0,neutral or dissatisfied +10605,12964,Female,Loyal Customer,38,Business travel,Eco Plus,163,4,2,2,2,4,4,4,4,4,3,5,5,1,4,12,32.0,satisfied +10606,56279,Female,Loyal Customer,64,Business travel,Eco,2227,2,3,3,3,2,2,2,4,4,3,4,2,4,2,0,29.0,neutral or dissatisfied +10607,125341,Female,Loyal Customer,33,Business travel,Business,2668,1,5,2,2,5,2,2,1,1,1,1,2,1,3,5,16.0,neutral or dissatisfied +10608,52551,Male,disloyal Customer,26,Business travel,Eco,160,3,0,3,3,5,3,5,5,4,3,5,2,4,5,0,0.0,neutral or dissatisfied +10609,39396,Male,disloyal Customer,26,Business travel,Eco,521,1,3,1,1,4,1,4,4,3,1,5,1,5,4,0,0.0,neutral or dissatisfied +10610,116083,Male,Loyal Customer,14,Personal Travel,Eco,480,4,3,4,4,3,4,3,3,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +10611,11108,Female,Loyal Customer,21,Personal Travel,Eco,201,3,1,3,4,1,3,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +10612,100334,Female,Loyal Customer,56,Business travel,Business,2342,3,2,2,2,1,4,3,3,3,3,3,2,3,4,0,4.0,neutral or dissatisfied +10613,57083,Female,disloyal Customer,24,Business travel,Eco,1222,4,4,4,3,2,4,2,2,3,5,4,1,3,2,5,0.0,neutral or dissatisfied +10614,22915,Male,Loyal Customer,33,Business travel,Eco,630,1,1,1,1,1,1,1,2,1,1,1,1,3,1,131,143.0,neutral or dissatisfied +10615,55513,Female,Loyal Customer,39,Business travel,Business,991,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,8.0,satisfied +10616,26711,Female,Loyal Customer,58,Personal Travel,Eco,406,3,5,3,1,2,4,4,3,3,3,3,5,3,5,0,14.0,neutral or dissatisfied +10617,66316,Female,Loyal Customer,11,Personal Travel,Eco,852,5,4,5,3,5,5,5,5,5,3,5,4,4,5,0,0.0,satisfied +10618,125990,Male,Loyal Customer,37,Personal Travel,Business,600,3,3,3,4,4,3,4,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +10619,45019,Male,Loyal Customer,14,Personal Travel,Eco,118,3,1,0,1,2,0,2,2,2,2,2,2,1,2,52,43.0,neutral or dissatisfied +10620,38085,Female,Loyal Customer,29,Business travel,Business,1249,3,3,3,3,3,3,3,3,4,2,4,4,3,3,55,40.0,neutral or dissatisfied +10621,22719,Male,Loyal Customer,19,Business travel,Business,170,0,4,0,5,3,3,3,3,5,4,5,3,4,3,0,3.0,satisfied +10622,27139,Female,Loyal Customer,49,Business travel,Business,2640,1,4,4,4,1,1,1,2,2,3,4,1,4,1,0,0.0,neutral or dissatisfied +10623,5760,Female,Loyal Customer,15,Personal Travel,Eco,642,2,4,2,2,5,2,5,5,4,5,4,5,5,5,0,11.0,neutral or dissatisfied +10624,59579,Female,Loyal Customer,47,Business travel,Business,2435,5,5,5,5,4,4,4,5,3,4,5,4,3,4,161,164.0,satisfied +10625,33972,Female,Loyal Customer,21,Business travel,Business,1598,2,4,3,4,2,2,2,1,2,4,4,2,1,2,148,139.0,neutral or dissatisfied +10626,126852,Female,Loyal Customer,60,Business travel,Eco,625,4,1,1,1,3,3,2,4,4,4,4,5,4,4,20,0.0,satisfied +10627,122478,Female,Loyal Customer,52,Business travel,Business,3231,3,3,3,3,4,3,5,5,5,5,4,5,5,1,0,0.0,satisfied +10628,11237,Female,Loyal Customer,42,Personal Travel,Eco,312,3,4,3,4,4,5,4,1,1,3,4,4,1,4,0,0.0,neutral or dissatisfied +10629,85856,Male,Loyal Customer,22,Personal Travel,Eco Plus,526,2,5,2,3,4,2,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +10630,128076,Male,Loyal Customer,46,Business travel,Business,2917,2,2,4,2,4,4,4,4,5,4,4,4,3,4,0,0.0,satisfied +10631,30964,Female,Loyal Customer,15,Personal Travel,Eco,1024,2,3,1,4,5,1,5,5,3,1,3,1,4,5,3,14.0,neutral or dissatisfied +10632,110086,Male,Loyal Customer,40,Business travel,Business,2694,4,4,4,4,2,4,4,4,4,5,4,4,4,5,0,1.0,satisfied +10633,85035,Female,Loyal Customer,41,Business travel,Business,1590,3,3,3,3,4,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +10634,99849,Female,Loyal Customer,26,Personal Travel,Eco,587,3,4,4,2,2,4,2,2,5,3,5,5,5,2,66,,neutral or dissatisfied +10635,18282,Female,Loyal Customer,29,Personal Travel,Eco Plus,179,2,4,2,3,4,2,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +10636,124675,Female,Loyal Customer,57,Business travel,Business,3109,3,3,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +10637,63931,Female,Loyal Customer,20,Personal Travel,Eco,1192,2,3,2,5,1,2,1,1,1,4,4,5,4,1,0,0.0,neutral or dissatisfied +10638,104639,Male,Loyal Customer,60,Personal Travel,Eco Plus,861,3,5,3,4,5,3,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +10639,16111,Female,Loyal Customer,15,Personal Travel,Business,725,2,3,2,4,4,2,4,4,3,4,1,1,1,4,0,0.0,neutral or dissatisfied +10640,94695,Female,Loyal Customer,60,Business travel,Eco,528,4,5,5,5,5,3,4,4,4,4,4,2,4,4,7,4.0,neutral or dissatisfied +10641,50486,Female,Loyal Customer,46,Business travel,Eco,308,4,5,5,5,5,4,3,4,4,4,4,4,4,2,1,0.0,neutral or dissatisfied +10642,8316,Female,Loyal Customer,47,Business travel,Eco Plus,125,4,4,4,4,3,1,4,4,4,4,4,4,4,3,118,111.0,satisfied +10643,67618,Male,disloyal Customer,35,Business travel,Business,1235,2,2,2,1,1,2,1,1,5,5,4,5,4,1,0,0.0,neutral or dissatisfied +10644,36670,Female,Loyal Customer,30,Personal Travel,Eco,1121,2,5,2,4,4,2,4,4,5,3,5,4,5,4,72,58.0,neutral or dissatisfied +10645,44157,Female,disloyal Customer,30,Business travel,Eco,229,3,0,3,4,3,3,3,3,4,4,3,3,5,3,0,4.0,neutral or dissatisfied +10646,38392,Female,disloyal Customer,48,Business travel,Eco,1626,3,3,3,4,1,3,1,1,3,3,2,2,4,1,0,0.0,neutral or dissatisfied +10647,93803,Female,Loyal Customer,65,Personal Travel,Eco,1259,1,5,1,1,2,5,5,3,3,1,4,3,3,5,0,0.0,neutral or dissatisfied +10648,52749,Female,Loyal Customer,25,Personal Travel,Eco,2306,3,5,3,3,4,3,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +10649,8272,Female,Loyal Customer,50,Personal Travel,Eco,335,3,5,3,4,5,5,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +10650,76806,Female,Loyal Customer,30,Personal Travel,Eco,546,2,3,3,3,3,3,4,3,3,4,4,2,4,3,0,0.0,neutral or dissatisfied +10651,35847,Male,Loyal Customer,45,Business travel,Business,1023,2,2,2,2,2,3,5,4,4,4,4,1,4,4,0,0.0,satisfied +10652,75064,Male,Loyal Customer,37,Business travel,Business,2611,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10653,60789,Male,Loyal Customer,20,Personal Travel,Business,472,2,2,2,4,5,2,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +10654,102639,Female,Loyal Customer,53,Business travel,Business,3995,5,5,1,5,4,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +10655,124091,Female,Loyal Customer,54,Business travel,Business,3601,4,4,4,4,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +10656,29757,Male,disloyal Customer,21,Business travel,Business,503,5,0,5,4,2,5,2,2,3,5,4,4,4,2,16,20.0,satisfied +10657,72436,Male,disloyal Customer,27,Business travel,Business,1121,4,4,4,4,4,4,4,4,5,5,5,3,4,4,6,2.0,neutral or dissatisfied +10658,32171,Female,disloyal Customer,20,Business travel,Eco,163,5,0,5,5,1,5,1,1,1,1,5,5,2,1,0,0.0,satisfied +10659,93306,Female,Loyal Customer,49,Business travel,Business,1733,1,1,1,1,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +10660,117239,Male,Loyal Customer,32,Personal Travel,Eco,651,2,2,2,2,5,2,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +10661,102538,Female,Loyal Customer,63,Personal Travel,Eco,223,2,2,0,3,1,4,3,1,1,0,1,2,1,1,33,25.0,neutral or dissatisfied +10662,3169,Male,Loyal Customer,54,Business travel,Business,585,2,2,2,2,5,4,4,4,4,4,4,3,4,5,17,40.0,satisfied +10663,3787,Male,Loyal Customer,22,Business travel,Business,2804,1,1,5,1,1,2,1,1,1,3,4,4,4,1,0,25.0,neutral or dissatisfied +10664,34592,Female,disloyal Customer,18,Business travel,Eco,1196,2,2,2,3,2,2,2,2,2,4,2,3,4,2,0,0.0,neutral or dissatisfied +10665,51709,Male,Loyal Customer,67,Business travel,Eco,370,2,4,4,4,2,2,2,2,3,5,2,3,2,2,64,61.0,neutral or dissatisfied +10666,85569,Male,Loyal Customer,36,Business travel,Business,3114,1,1,1,1,4,5,4,3,3,4,5,4,3,5,0,0.0,satisfied +10667,93331,Male,Loyal Customer,28,Business travel,Business,1024,5,5,5,5,3,3,3,3,5,5,5,3,4,3,22,26.0,satisfied +10668,441,Male,Loyal Customer,31,Personal Travel,Business,229,5,5,5,4,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +10669,33923,Female,disloyal Customer,29,Business travel,Eco,818,4,4,4,3,2,4,2,2,2,2,5,5,4,2,8,0.0,satisfied +10670,25447,Male,Loyal Customer,25,Personal Travel,Eco,669,1,5,1,3,2,1,4,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +10671,6642,Female,Loyal Customer,47,Business travel,Eco,416,2,1,3,3,1,4,3,2,2,2,2,3,2,1,8,11.0,neutral or dissatisfied +10672,97934,Male,Loyal Customer,54,Business travel,Business,684,4,4,4,4,2,4,4,5,5,5,5,4,5,3,8,11.0,satisfied +10673,9800,Female,disloyal Customer,18,Business travel,Eco,474,4,0,4,3,2,4,2,2,4,4,4,4,4,2,5,68.0,neutral or dissatisfied +10674,91858,Female,Loyal Customer,38,Personal Travel,Eco Plus,1619,2,5,2,1,1,2,1,1,3,5,3,4,5,1,0,0.0,neutral or dissatisfied +10675,106483,Female,Loyal Customer,23,Personal Travel,Eco,1624,1,2,0,4,4,0,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +10676,53596,Female,Loyal Customer,29,Business travel,Eco,3801,4,4,4,4,4,4,4,3,1,4,1,4,5,4,0,0.0,satisfied +10677,9451,Male,Loyal Customer,15,Personal Travel,Eco,368,2,5,2,4,3,2,3,3,2,1,2,3,4,3,0,0.0,neutral or dissatisfied +10678,67457,Male,Loyal Customer,22,Personal Travel,Eco,641,3,4,4,4,3,4,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +10679,41042,Male,Loyal Customer,41,Business travel,Eco,1195,5,1,1,1,5,5,5,5,2,4,1,1,4,5,0,0.0,satisfied +10680,21547,Male,Loyal Customer,30,Personal Travel,Eco,164,4,5,0,3,1,0,1,1,5,2,5,4,4,1,41,38.0,neutral or dissatisfied +10681,69003,Female,Loyal Customer,49,Business travel,Business,1391,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +10682,25567,Female,Loyal Customer,43,Business travel,Eco,874,4,2,1,2,1,1,3,4,4,4,4,2,4,2,0,0.0,satisfied +10683,51800,Female,Loyal Customer,39,Personal Travel,Eco,425,0,2,0,3,5,0,5,5,3,3,4,3,3,5,0,0.0,satisfied +10684,7802,Female,Loyal Customer,44,Business travel,Business,650,2,2,2,2,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +10685,28240,Male,Loyal Customer,19,Personal Travel,Eco,1009,2,5,2,4,2,2,5,2,5,4,4,4,4,2,0,17.0,neutral or dissatisfied +10686,4947,Male,Loyal Customer,62,Business travel,Eco Plus,268,5,5,5,5,5,5,5,5,4,1,2,4,1,5,0,3.0,satisfied +10687,39152,Male,Loyal Customer,48,Business travel,Eco Plus,190,2,5,5,5,2,2,2,2,3,3,1,4,1,2,0,0.0,satisfied +10688,30761,Female,disloyal Customer,23,Business travel,Eco,683,0,0,0,2,2,0,2,2,3,2,3,2,2,2,6,4.0,satisfied +10689,51007,Female,Loyal Customer,13,Personal Travel,Eco,109,0,5,0,4,5,0,3,5,5,3,4,5,4,5,0,0.0,satisfied +10690,106902,Female,Loyal Customer,39,Personal Travel,Eco,577,2,2,2,2,4,2,4,4,3,5,2,4,3,4,6,0.0,neutral or dissatisfied +10691,79295,Female,Loyal Customer,43,Business travel,Business,2248,2,3,2,2,4,4,4,4,2,4,5,4,3,4,23,53.0,satisfied +10692,69564,Female,Loyal Customer,40,Business travel,Business,2586,2,2,2,2,4,4,4,4,4,5,5,4,3,4,14,0.0,satisfied +10693,7366,Female,Loyal Customer,33,Business travel,Eco,783,2,5,5,5,2,2,2,2,1,1,4,1,4,2,5,0.0,neutral or dissatisfied +10694,39992,Female,disloyal Customer,25,Business travel,Eco,508,0,5,0,4,2,5,2,2,1,1,5,5,3,2,0,0.0,satisfied +10695,75286,Male,Loyal Customer,59,Business travel,Business,1723,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +10696,7836,Male,Loyal Customer,29,Business travel,Business,3064,3,3,3,3,4,5,4,4,5,5,5,4,4,4,0,0.0,satisfied +10697,34492,Male,Loyal Customer,46,Business travel,Eco,1990,5,2,2,2,5,5,5,5,2,3,4,2,1,5,2,7.0,satisfied +10698,1955,Female,disloyal Customer,33,Business travel,Business,351,2,2,2,2,4,2,4,4,4,4,5,4,4,4,0,4.0,neutral or dissatisfied +10699,5846,Male,Loyal Customer,60,Business travel,Business,1020,4,4,2,4,3,4,5,4,4,4,4,5,4,3,0,13.0,satisfied +10700,47349,Male,Loyal Customer,61,Business travel,Eco,584,4,4,4,4,3,4,3,3,3,1,5,5,2,3,0,0.0,satisfied +10701,123430,Female,Loyal Customer,44,Business travel,Business,2077,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +10702,50706,Male,Loyal Customer,62,Personal Travel,Eco,308,2,1,2,3,4,2,4,4,4,4,3,3,3,4,0,0.0,neutral or dissatisfied +10703,50532,Female,Loyal Customer,46,Personal Travel,Eco,86,3,5,3,4,2,1,5,5,5,3,5,1,5,4,55,45.0,neutral or dissatisfied +10704,128812,Male,Loyal Customer,30,Business travel,Business,2475,3,3,3,3,4,4,4,4,4,5,4,4,5,4,19,39.0,satisfied +10705,17585,Female,Loyal Customer,18,Personal Travel,Eco,852,3,5,3,2,3,3,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +10706,64298,Female,disloyal Customer,26,Business travel,Business,1192,4,4,4,1,2,4,2,2,4,4,4,5,4,2,14,0.0,satisfied +10707,93413,Female,Loyal Customer,8,Business travel,Business,697,2,2,2,2,5,5,5,5,3,4,5,5,5,5,2,2.0,satisfied +10708,5996,Female,disloyal Customer,29,Business travel,Business,672,5,4,4,4,2,4,2,2,4,5,4,4,5,2,0,0.0,satisfied +10709,56638,Male,Loyal Customer,39,Business travel,Business,1878,4,4,4,4,4,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +10710,87055,Female,Loyal Customer,48,Business travel,Business,1908,4,4,4,4,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +10711,34063,Female,disloyal Customer,36,Business travel,Eco,174,1,1,1,4,5,1,5,5,1,4,4,1,3,5,0,0.0,neutral or dissatisfied +10712,90783,Female,disloyal Customer,26,Business travel,Business,594,2,5,2,1,4,2,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +10713,104184,Male,Loyal Customer,19,Personal Travel,Eco,349,2,5,3,3,4,3,4,4,5,4,4,3,4,4,5,4.0,neutral or dissatisfied +10714,18367,Female,disloyal Customer,16,Business travel,Eco,169,2,0,1,5,2,1,2,2,2,2,1,1,5,2,0,0.0,neutral or dissatisfied +10715,36341,Male,Loyal Customer,56,Personal Travel,Eco,395,2,5,5,4,3,5,3,3,1,1,4,5,5,3,0,8.0,neutral or dissatisfied +10716,19219,Male,Loyal Customer,36,Business travel,Eco,459,1,3,3,3,2,1,1,1,5,4,4,1,2,1,89,135.0,neutral or dissatisfied +10717,32431,Female,Loyal Customer,64,Business travel,Eco,216,4,2,4,4,4,3,4,4,4,4,4,2,4,2,0,0.0,satisfied +10718,109681,Female,Loyal Customer,18,Personal Travel,Eco,802,4,2,4,3,5,4,5,5,2,3,3,3,4,5,10,4.0,neutral or dissatisfied +10719,22443,Female,Loyal Customer,23,Personal Travel,Eco,143,4,2,4,3,1,4,5,1,2,4,2,2,2,1,0,0.0,satisfied +10720,8773,Male,Loyal Customer,40,Business travel,Business,522,5,5,4,5,3,5,4,4,4,4,4,5,4,4,35,44.0,satisfied +10721,32533,Male,disloyal Customer,26,Business travel,Eco,101,2,4,2,1,3,2,3,3,5,1,3,2,5,3,0,0.0,neutral or dissatisfied +10722,45503,Female,Loyal Customer,22,Business travel,Eco Plus,749,0,3,0,1,4,0,4,4,2,4,4,4,4,4,0,0.0,satisfied +10723,15651,Male,disloyal Customer,19,Business travel,Business,258,2,3,2,3,1,2,3,1,3,5,4,2,3,1,99,87.0,neutral or dissatisfied +10724,115871,Female,disloyal Customer,26,Business travel,Eco,417,4,1,4,4,5,4,5,5,3,1,4,1,4,5,22,11.0,neutral or dissatisfied +10725,124467,Female,Loyal Customer,56,Personal Travel,Eco,980,3,5,3,1,3,4,5,2,2,3,2,5,2,5,30,69.0,neutral or dissatisfied +10726,120701,Male,Loyal Customer,29,Personal Travel,Eco,280,2,2,2,3,5,2,5,5,3,5,3,4,3,5,13,1.0,neutral or dissatisfied +10727,98072,Male,Loyal Customer,44,Business travel,Eco,1449,2,2,5,2,2,2,2,2,3,4,3,4,3,2,88,106.0,neutral or dissatisfied +10728,120861,Female,Loyal Customer,45,Business travel,Business,3652,3,3,3,3,4,4,5,4,4,4,4,5,4,3,4,0.0,satisfied +10729,108804,Male,Loyal Customer,49,Personal Travel,Eco,581,2,5,1,3,1,1,1,1,3,5,4,4,4,1,13,0.0,neutral or dissatisfied +10730,122792,Male,disloyal Customer,33,Business travel,Business,599,3,3,3,3,3,3,3,3,3,5,4,4,4,3,12,0.0,neutral or dissatisfied +10731,112168,Female,Loyal Customer,63,Personal Travel,Eco,895,4,5,4,4,2,4,5,2,2,4,2,4,2,4,0,0.0,satisfied +10732,86479,Female,Loyal Customer,53,Personal Travel,Eco,762,1,5,1,1,2,1,2,5,5,1,5,5,5,3,0,6.0,neutral or dissatisfied +10733,45131,Female,Loyal Customer,50,Business travel,Business,1842,5,5,5,5,5,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +10734,16570,Female,disloyal Customer,64,Business travel,Eco,872,2,2,2,1,1,2,2,1,4,1,1,5,3,1,0,3.0,neutral or dissatisfied +10735,18764,Female,Loyal Customer,35,Business travel,Business,2900,2,2,2,2,5,4,5,4,4,5,4,5,4,4,0,26.0,satisfied +10736,128979,Female,Loyal Customer,43,Personal Travel,Eco,414,2,4,2,3,2,2,2,2,4,3,3,2,5,2,109,132.0,neutral or dissatisfied +10737,26669,Female,disloyal Customer,39,Business travel,Eco,270,3,1,3,3,2,3,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +10738,113739,Female,Loyal Customer,34,Personal Travel,Eco,386,1,4,1,4,1,1,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +10739,10007,Female,Loyal Customer,16,Personal Travel,Eco,534,2,4,3,3,4,3,3,4,3,5,4,4,4,4,6,51.0,neutral or dissatisfied +10740,114399,Female,Loyal Customer,45,Business travel,Business,1994,2,2,1,2,2,4,5,4,4,4,4,5,4,5,7,0.0,satisfied +10741,85440,Male,Loyal Customer,45,Business travel,Business,152,3,3,3,3,3,4,4,4,4,4,5,4,4,3,74,67.0,satisfied +10742,72217,Male,Loyal Customer,49,Business travel,Business,919,3,3,4,3,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +10743,67208,Female,Loyal Customer,23,Personal Travel,Eco,929,2,4,2,4,2,2,4,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +10744,44434,Male,Loyal Customer,48,Personal Travel,Eco,542,3,2,3,4,2,3,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +10745,46745,Male,Loyal Customer,14,Personal Travel,Eco,125,4,5,4,2,5,4,5,5,2,5,5,3,3,5,0,0.0,neutral or dissatisfied +10746,108308,Female,Loyal Customer,28,Business travel,Business,1706,3,3,3,3,2,2,2,2,5,4,4,4,5,2,11,0.0,satisfied +10747,62212,Female,Loyal Customer,67,Personal Travel,Eco,2434,3,5,3,4,5,4,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +10748,104680,Female,Loyal Customer,54,Business travel,Business,2273,2,2,2,2,4,5,5,4,4,4,4,5,4,4,13,3.0,satisfied +10749,96042,Female,Loyal Customer,48,Business travel,Business,3071,1,1,1,1,3,4,4,3,3,4,3,5,3,4,15,22.0,satisfied +10750,76240,Male,Loyal Customer,38,Business travel,Eco,999,3,1,1,1,3,3,3,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +10751,74077,Male,disloyal Customer,10,Business travel,Eco,592,3,4,2,3,2,2,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +10752,58613,Female,disloyal Customer,39,Business travel,Business,137,1,1,1,2,4,1,3,4,3,4,4,5,5,4,25,12.0,neutral or dissatisfied +10753,60212,Female,disloyal Customer,30,Business travel,Business,1506,2,2,2,5,5,2,2,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +10754,79899,Female,Loyal Customer,39,Business travel,Business,3226,3,2,2,2,3,2,3,3,3,3,3,1,3,3,89,98.0,neutral or dissatisfied +10755,129283,Female,disloyal Customer,18,Business travel,Eco,550,4,0,4,4,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +10756,120468,Female,Loyal Customer,46,Personal Travel,Eco,366,3,5,3,1,2,4,4,4,4,3,2,5,4,5,0,0.0,neutral or dissatisfied +10757,110613,Male,Loyal Customer,39,Personal Travel,Eco Plus,551,3,1,4,3,2,4,2,2,1,1,4,1,4,2,0,15.0,neutral or dissatisfied +10758,6171,Female,Loyal Customer,44,Personal Travel,Eco,409,2,4,2,3,5,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +10759,29444,Female,Loyal Customer,40,Business travel,Business,3073,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +10760,63060,Male,Loyal Customer,42,Personal Travel,Eco,846,3,5,3,5,3,3,3,3,4,2,4,5,4,3,0,39.0,neutral or dissatisfied +10761,76351,Female,Loyal Customer,60,Business travel,Business,1851,5,5,5,5,5,3,4,5,5,5,5,3,5,3,75,46.0,satisfied +10762,54232,Male,Loyal Customer,37,Business travel,Business,2257,2,2,2,2,1,4,2,5,5,5,5,5,5,2,1,0.0,satisfied +10763,66630,Female,Loyal Customer,61,Personal Travel,Business,802,2,5,1,2,4,4,5,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +10764,78141,Female,Loyal Customer,57,Business travel,Business,259,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +10765,85271,Female,Loyal Customer,58,Personal Travel,Eco,874,1,4,1,2,5,5,4,5,5,1,5,4,5,4,33,26.0,neutral or dissatisfied +10766,30878,Male,Loyal Customer,11,Personal Travel,Eco,1703,2,1,2,3,3,2,3,3,3,1,2,3,3,3,42,40.0,neutral or dissatisfied +10767,72582,Female,Loyal Customer,43,Business travel,Eco,719,2,4,4,4,4,1,1,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +10768,126939,Male,Loyal Customer,51,Business travel,Business,651,3,3,3,3,5,5,5,5,5,5,5,5,4,5,134,114.0,satisfied +10769,85546,Female,Loyal Customer,55,Business travel,Business,1567,4,4,4,4,4,4,5,5,5,5,4,5,5,3,0,0.0,satisfied +10770,91793,Male,Loyal Customer,46,Personal Travel,Eco,590,2,4,2,3,4,2,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +10771,58869,Male,Loyal Customer,28,Business travel,Business,888,5,5,2,5,4,4,4,4,4,2,4,4,5,4,16,14.0,satisfied +10772,82274,Female,Loyal Customer,23,Business travel,Business,1481,2,2,2,2,5,5,5,5,3,5,5,4,4,5,4,0.0,satisfied +10773,23826,Female,Loyal Customer,58,Business travel,Eco Plus,304,2,1,1,1,5,2,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +10774,3653,Male,Loyal Customer,42,Business travel,Business,431,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +10775,9598,Female,Loyal Customer,37,Personal Travel,Eco,228,1,3,1,3,5,1,5,5,4,4,3,2,4,5,3,0.0,neutral or dissatisfied +10776,30644,Male,Loyal Customer,52,Business travel,Eco,533,4,5,3,5,4,4,4,4,4,2,4,3,1,4,6,0.0,satisfied +10777,60728,Female,Loyal Customer,24,Personal Travel,Eco,1605,2,4,2,4,3,2,3,3,4,2,5,4,4,3,8,0.0,neutral or dissatisfied +10778,32252,Female,Loyal Customer,55,Business travel,Eco,163,4,3,3,3,4,4,3,4,4,4,4,5,4,4,0,0.0,satisfied +10779,7628,Female,Loyal Customer,43,Business travel,Business,641,3,3,3,3,3,5,5,4,4,4,4,4,4,4,15,5.0,satisfied +10780,69259,Female,Loyal Customer,28,Business travel,Business,2222,3,4,4,4,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +10781,83390,Female,Loyal Customer,33,Business travel,Business,632,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +10782,32259,Female,Loyal Customer,61,Business travel,Eco,163,2,5,5,5,1,3,1,2,2,2,2,3,2,5,0,0.0,satisfied +10783,56032,Female,Loyal Customer,25,Business travel,Business,2475,2,2,2,2,5,4,4,4,3,4,5,4,4,4,8,0.0,satisfied +10784,120207,Female,Loyal Customer,44,Business travel,Business,3281,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +10785,89942,Female,Loyal Customer,65,Personal Travel,Eco,1487,3,3,3,2,3,2,2,3,2,3,1,2,5,2,150,138.0,neutral or dissatisfied +10786,106064,Female,Loyal Customer,52,Business travel,Business,3458,2,2,1,2,3,4,4,3,3,3,3,4,3,3,27,23.0,satisfied +10787,24630,Male,Loyal Customer,66,Personal Travel,Eco,526,0,5,0,5,1,0,1,1,5,5,5,4,4,1,0,5.0,satisfied +10788,59920,Female,Loyal Customer,43,Business travel,Eco,937,1,2,2,2,5,2,2,1,1,1,1,2,1,1,8,8.0,neutral or dissatisfied +10789,60223,Male,Loyal Customer,25,Business travel,Eco,1703,4,1,5,5,4,4,3,4,2,4,3,2,4,4,1,0.0,neutral or dissatisfied +10790,49291,Male,Loyal Customer,60,Business travel,Business,153,1,1,1,1,1,1,2,5,5,4,5,5,5,5,77,80.0,satisfied +10791,26610,Female,disloyal Customer,34,Business travel,Eco,270,2,1,2,4,5,2,5,5,1,2,3,4,4,5,0,1.0,neutral or dissatisfied +10792,18769,Male,Loyal Customer,59,Business travel,Business,448,5,5,5,5,2,4,5,2,2,2,2,4,2,4,0,10.0,satisfied +10793,13605,Male,Loyal Customer,30,Business travel,Eco Plus,106,5,3,3,3,5,5,5,5,1,3,5,3,3,5,0,0.0,satisfied +10794,23536,Female,Loyal Customer,18,Business travel,Eco,423,3,3,5,3,3,3,3,3,2,2,4,4,4,3,10,10.0,neutral or dissatisfied +10795,64093,Male,Loyal Customer,10,Personal Travel,Eco,919,3,4,3,4,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +10796,20584,Male,Loyal Customer,44,Personal Travel,Eco,565,4,5,4,5,3,4,2,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +10797,74320,Male,Loyal Customer,30,Business travel,Business,3486,3,5,3,3,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +10798,101907,Male,Loyal Customer,50,Personal Travel,Eco,2039,2,1,2,2,5,2,5,5,2,1,3,3,2,5,15,0.0,neutral or dissatisfied +10799,119408,Female,Loyal Customer,27,Business travel,Business,399,4,4,4,4,4,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +10800,57874,Male,disloyal Customer,23,Business travel,Business,305,2,1,2,1,4,2,4,4,3,4,2,1,2,4,33,23.0,neutral or dissatisfied +10801,116878,Female,Loyal Customer,43,Business travel,Business,3004,5,5,5,5,4,4,5,5,5,5,5,5,5,4,3,1.0,satisfied +10802,23522,Male,Loyal Customer,18,Personal Travel,Eco,349,4,4,4,1,4,4,4,4,5,4,4,5,4,4,99,93.0,neutral or dissatisfied +10803,21852,Male,Loyal Customer,20,Business travel,Business,2938,3,3,3,3,4,4,4,4,4,4,1,3,3,4,0,0.0,satisfied +10804,87848,Female,Loyal Customer,48,Personal Travel,Eco,143,3,3,3,2,1,1,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +10805,10107,Male,Loyal Customer,56,Business travel,Business,2918,4,4,4,4,2,4,5,3,3,3,3,5,3,3,11,0.0,satisfied +10806,77875,Male,Loyal Customer,49,Business travel,Eco,1016,4,1,1,1,4,4,4,4,4,2,1,4,1,4,0,34.0,neutral or dissatisfied +10807,67859,Female,Loyal Customer,20,Personal Travel,Eco,1235,2,3,2,1,3,2,3,3,2,2,4,4,2,3,0,8.0,neutral or dissatisfied +10808,93207,Female,Loyal Customer,43,Personal Travel,Eco,1756,5,2,5,3,5,3,3,4,4,5,4,4,4,1,1,22.0,satisfied +10809,94256,Male,Loyal Customer,48,Business travel,Business,3658,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10810,111629,Female,Loyal Customer,43,Business travel,Eco Plus,1014,3,1,4,1,3,3,3,3,3,3,3,3,3,3,24,23.0,neutral or dissatisfied +10811,129741,Male,disloyal Customer,36,Business travel,Business,337,3,3,3,2,5,3,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +10812,38774,Female,Loyal Customer,40,Business travel,Business,2387,1,5,5,5,1,4,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +10813,80057,Male,Loyal Customer,64,Personal Travel,Eco,1005,4,4,4,4,4,4,4,4,4,4,5,4,4,4,0,1.0,neutral or dissatisfied +10814,90899,Male,Loyal Customer,55,Business travel,Eco,270,3,1,1,1,3,3,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +10815,45167,Female,Loyal Customer,41,Personal Travel,Eco,174,5,4,5,1,2,5,2,2,3,2,5,5,4,2,0,0.0,satisfied +10816,55831,Male,Loyal Customer,29,Business travel,Business,1416,3,3,3,3,3,3,3,3,1,4,3,1,3,3,101,108.0,neutral or dissatisfied +10817,111097,Female,disloyal Customer,22,Business travel,Business,197,5,5,5,2,4,5,2,4,3,5,4,3,5,4,24,17.0,satisfied +10818,17949,Male,Loyal Customer,51,Business travel,Business,2751,2,2,3,2,2,5,5,3,3,3,3,5,3,4,66,50.0,satisfied +10819,78472,Female,Loyal Customer,37,Business travel,Business,666,1,1,4,1,2,5,5,5,5,5,5,5,5,4,0,8.0,satisfied +10820,74127,Female,Loyal Customer,59,Business travel,Business,2394,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,12.0,satisfied +10821,81027,Male,disloyal Customer,36,Business travel,Business,1175,2,2,2,3,2,2,2,5,5,5,4,2,5,2,168,195.0,neutral or dissatisfied +10822,116839,Female,disloyal Customer,20,Business travel,Business,370,4,0,4,1,3,4,3,3,3,4,4,3,4,3,5,0.0,satisfied +10823,99035,Female,Loyal Customer,8,Personal Travel,Eco,1009,3,5,3,3,4,3,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +10824,20717,Male,Loyal Customer,46,Business travel,Eco,669,2,5,5,5,2,2,2,2,4,2,4,3,3,2,8,11.0,neutral or dissatisfied +10825,1727,Male,Loyal Customer,45,Business travel,Business,489,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +10826,64332,Female,Loyal Customer,40,Business travel,Business,3181,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +10827,119798,Female,Loyal Customer,56,Business travel,Business,912,5,5,5,5,2,4,5,4,4,4,4,3,4,4,6,12.0,satisfied +10828,43970,Female,Loyal Customer,41,Personal Travel,Eco Plus,545,1,2,1,3,3,3,3,1,1,1,1,3,1,1,38,34.0,neutral or dissatisfied +10829,96404,Female,Loyal Customer,9,Personal Travel,Eco,1342,2,4,2,4,4,2,4,4,5,2,5,3,5,4,5,0.0,neutral or dissatisfied +10830,5899,Female,Loyal Customer,21,Business travel,Business,3038,4,4,4,4,4,4,5,4,3,4,4,4,5,4,2,0.0,satisfied +10831,53084,Male,Loyal Customer,28,Business travel,Business,2327,3,3,3,3,3,3,3,1,4,5,4,3,1,3,27,49.0,satisfied +10832,108039,Female,Loyal Customer,39,Personal Travel,Eco,306,3,5,3,2,5,3,5,5,4,5,5,5,4,5,37,19.0,neutral or dissatisfied +10833,2639,Female,disloyal Customer,43,Business travel,Business,539,4,4,4,4,2,4,4,2,4,5,5,5,4,2,0,0.0,satisfied +10834,3295,Male,Loyal Customer,56,Personal Travel,Eco,483,1,5,1,4,5,1,1,5,4,4,4,4,1,5,0,16.0,neutral or dissatisfied +10835,96666,Female,Loyal Customer,44,Personal Travel,Eco,937,4,5,4,2,4,3,5,4,4,4,3,2,4,5,7,1.0,neutral or dissatisfied +10836,73779,Male,Loyal Customer,52,Personal Travel,Eco,204,4,4,0,4,3,0,3,3,1,5,3,5,5,3,0,0.0,neutral or dissatisfied +10837,37573,Female,disloyal Customer,20,Business travel,Eco,641,5,0,5,5,5,1,5,4,5,3,1,5,5,5,505,486.0,satisfied +10838,100922,Female,Loyal Customer,30,Business travel,Business,1556,2,2,2,2,4,5,4,4,4,2,4,3,5,4,0,0.0,satisfied +10839,53095,Female,Loyal Customer,47,Personal Travel,Eco,224,4,5,4,2,4,2,2,3,3,4,3,5,3,3,3,0.0,satisfied +10840,63331,Female,Loyal Customer,52,Business travel,Business,3180,4,2,4,4,5,2,2,5,5,4,5,3,5,3,0,0.0,satisfied +10841,110387,Female,disloyal Customer,57,Business travel,Eco,787,1,1,1,4,4,1,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +10842,28559,Female,Loyal Customer,46,Business travel,Business,2640,5,5,5,5,2,3,5,4,4,4,4,5,4,5,50,9.0,satisfied +10843,92672,Female,Loyal Customer,33,Business travel,Business,507,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +10844,101462,Male,disloyal Customer,22,Business travel,Business,345,5,0,5,1,4,5,1,4,5,2,5,3,4,4,0,0.0,satisfied +10845,7904,Female,Loyal Customer,23,Business travel,Business,3256,1,1,1,1,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +10846,73005,Male,Loyal Customer,64,Personal Travel,Eco,1096,2,1,2,4,3,2,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +10847,110596,Male,Loyal Customer,16,Personal Travel,Eco,674,2,4,2,4,3,2,4,3,2,5,3,4,3,3,9,22.0,neutral or dissatisfied +10848,74716,Male,Loyal Customer,66,Personal Travel,Eco,1438,1,3,1,3,2,1,2,2,2,5,2,3,4,2,0,0.0,neutral or dissatisfied +10849,76473,Female,Loyal Customer,41,Business travel,Business,1867,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,6.0,satisfied +10850,118253,Female,disloyal Customer,28,Business travel,Eco,1281,3,3,3,2,2,3,4,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +10851,89162,Male,Loyal Customer,66,Personal Travel,Eco,2139,2,5,2,4,5,2,5,5,3,2,4,5,5,5,0,1.0,neutral or dissatisfied +10852,29581,Female,Loyal Customer,41,Business travel,Business,1533,2,2,2,2,5,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +10853,17319,Male,Loyal Customer,58,Personal Travel,Eco,403,3,5,3,2,3,3,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +10854,92503,Male,Loyal Customer,80,Business travel,Eco,447,3,4,4,4,3,3,3,3,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +10855,74745,Female,Loyal Customer,32,Personal Travel,Eco,1205,2,5,2,2,1,2,1,1,3,5,3,2,4,1,15,6.0,neutral or dissatisfied +10856,1079,Female,Loyal Customer,58,Personal Travel,Eco,164,3,2,3,4,5,3,4,2,2,3,1,4,2,3,19,27.0,neutral or dissatisfied +10857,21684,Female,Loyal Customer,60,Business travel,Eco,746,2,5,3,5,2,3,2,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +10858,51127,Male,Loyal Customer,39,Personal Travel,Eco,158,3,4,3,3,1,3,1,1,3,4,4,5,5,1,4,3.0,neutral or dissatisfied +10859,120665,Male,Loyal Customer,55,Business travel,Eco,280,3,1,1,1,3,3,3,3,1,4,4,1,4,3,8,14.0,neutral or dissatisfied +10860,104246,Female,Loyal Customer,26,Business travel,Business,3972,3,1,1,1,3,3,3,3,4,4,3,3,2,3,0,1.0,neutral or dissatisfied +10861,80398,Male,Loyal Customer,64,Business travel,Business,2704,5,5,2,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +10862,101048,Male,disloyal Customer,18,Business travel,Eco,368,2,1,2,4,2,2,2,2,2,2,3,4,4,2,8,0.0,neutral or dissatisfied +10863,66731,Male,Loyal Customer,14,Personal Travel,Eco,802,3,3,4,4,2,4,2,2,5,2,2,3,2,2,0,0.0,neutral or dissatisfied +10864,127639,Female,Loyal Customer,61,Personal Travel,Eco,1773,2,5,2,3,1,3,5,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +10865,31105,Female,Loyal Customer,65,Personal Travel,Eco Plus,1014,3,2,3,4,3,2,3,5,5,3,3,2,5,1,0,0.0,neutral or dissatisfied +10866,50997,Female,Loyal Customer,57,Personal Travel,Eco,337,3,3,3,4,1,4,2,3,3,3,3,5,3,1,0,4.0,neutral or dissatisfied +10867,27036,Male,Loyal Customer,37,Business travel,Eco Plus,867,4,5,5,5,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +10868,23056,Female,Loyal Customer,35,Business travel,Business,820,1,1,1,1,4,5,5,3,4,5,1,5,2,5,167,162.0,satisfied +10869,57911,Male,Loyal Customer,68,Personal Travel,Eco,305,3,5,3,4,4,3,5,4,3,3,5,4,5,4,9,0.0,neutral or dissatisfied +10870,126515,Male,Loyal Customer,34,Business travel,Business,313,0,0,0,2,2,4,5,1,1,1,1,3,1,3,0,0.0,satisfied +10871,99952,Male,Loyal Customer,54,Personal Travel,Eco,2237,1,5,1,3,4,1,4,4,5,4,3,4,4,4,3,0.0,neutral or dissatisfied +10872,24514,Female,Loyal Customer,41,Business travel,Eco Plus,516,3,5,3,5,5,4,4,3,3,3,3,1,3,4,0,16.0,satisfied +10873,24446,Female,Loyal Customer,58,Personal Travel,Business,516,1,2,1,4,3,4,4,2,2,1,2,2,2,1,0,1.0,neutral or dissatisfied +10874,64485,Male,Loyal Customer,47,Business travel,Business,224,0,0,0,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +10875,49052,Female,Loyal Customer,39,Business travel,Business,109,0,5,0,4,3,1,5,4,4,2,2,3,4,5,0,0.0,satisfied +10876,98899,Female,Loyal Customer,36,Personal Travel,Business,569,5,5,5,4,3,5,5,3,3,5,3,4,3,5,33,34.0,satisfied +10877,90928,Female,disloyal Customer,37,Business travel,Eco,404,4,0,4,4,2,4,2,2,1,1,2,5,3,2,0,0.0,neutral or dissatisfied +10878,43878,Female,Loyal Customer,39,Business travel,Business,114,1,4,4,4,3,4,3,3,3,3,1,4,3,3,0,43.0,neutral or dissatisfied +10879,120503,Female,Loyal Customer,37,Business travel,Eco Plus,449,2,3,3,3,2,2,2,2,1,2,3,3,4,2,0,6.0,neutral or dissatisfied +10880,37618,Female,Loyal Customer,58,Personal Travel,Eco,1076,1,4,1,3,2,5,4,4,4,1,5,4,4,3,0,,neutral or dissatisfied +10881,107370,Male,Loyal Customer,12,Business travel,Eco Plus,632,1,2,2,2,1,1,1,1,4,4,3,1,4,1,6,6.0,neutral or dissatisfied +10882,77982,Male,disloyal Customer,32,Business travel,Business,332,4,5,5,3,3,5,4,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +10883,91243,Female,Loyal Customer,10,Personal Travel,Eco,545,2,2,1,3,5,1,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +10884,15896,Female,Loyal Customer,24,Business travel,Eco,378,5,5,5,5,5,5,4,5,4,2,1,1,2,5,0,0.0,satisfied +10885,15302,Female,Loyal Customer,42,Personal Travel,Eco,612,3,4,3,3,5,5,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +10886,56412,Male,Loyal Customer,33,Business travel,Business,719,3,3,2,3,3,3,3,3,1,2,3,3,4,3,0,0.0,neutral or dissatisfied +10887,68002,Female,disloyal Customer,42,Business travel,Business,304,4,4,4,3,2,4,2,2,5,2,5,5,5,2,0,0.0,satisfied +10888,32927,Male,Loyal Customer,10,Personal Travel,Eco,101,2,3,2,4,3,2,3,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +10889,80284,Male,Loyal Customer,31,Business travel,Business,3188,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,3.0,satisfied +10890,100910,Female,Loyal Customer,7,Personal Travel,Eco,377,2,5,2,2,5,2,1,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +10891,40848,Female,Loyal Customer,7,Personal Travel,Eco,584,3,5,3,2,4,3,3,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +10892,181,Female,Loyal Customer,56,Business travel,Business,213,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +10893,35853,Female,Loyal Customer,60,Business travel,Eco,537,3,4,4,4,1,2,5,3,3,3,3,5,3,5,72,52.0,satisfied +10894,106965,Male,Loyal Customer,33,Business travel,Business,972,3,3,3,3,3,4,3,3,4,2,4,5,4,3,0,0.0,satisfied +10895,43371,Male,Loyal Customer,39,Personal Travel,Eco,387,4,2,4,2,4,4,4,4,3,3,2,1,2,4,0,0.0,satisfied +10896,52909,Female,disloyal Customer,21,Business travel,Eco,679,5,5,5,1,4,5,4,4,4,3,4,3,2,4,56,44.0,satisfied +10897,110806,Female,Loyal Customer,22,Personal Travel,Eco,997,3,1,3,3,2,3,1,2,3,3,3,3,2,2,0,0.0,neutral or dissatisfied +10898,18,Female,Loyal Customer,61,Personal Travel,Eco,821,2,5,2,1,4,1,5,5,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +10899,40758,Female,Loyal Customer,26,Business travel,Eco,541,4,2,2,2,4,4,5,4,4,1,4,3,1,4,0,8.0,satisfied +10900,103170,Female,Loyal Customer,46,Business travel,Eco,272,4,2,2,2,1,5,5,4,4,4,4,4,4,1,79,69.0,satisfied +10901,59633,Female,Loyal Customer,39,Business travel,Eco,787,2,5,5,5,2,2,2,2,2,1,4,3,3,2,19,10.0,neutral or dissatisfied +10902,7133,Female,Loyal Customer,52,Business travel,Business,3278,1,1,1,1,5,4,4,4,4,4,4,3,4,3,50,49.0,satisfied +10903,92699,Female,Loyal Customer,16,Personal Travel,Eco,507,4,1,2,1,4,2,4,4,1,3,1,3,2,4,0,0.0,neutral or dissatisfied +10904,68615,Male,Loyal Customer,62,Personal Travel,Business,175,3,4,3,4,2,4,5,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +10905,13789,Male,Loyal Customer,60,Personal Travel,Eco,878,3,0,3,1,4,3,4,4,5,5,3,4,5,4,0,12.0,neutral or dissatisfied +10906,79455,Male,disloyal Customer,41,Business travel,Business,1183,1,2,2,4,1,4,1,1,3,4,4,3,4,1,1,0.0,neutral or dissatisfied +10907,27122,Female,Loyal Customer,32,Business travel,Business,2715,3,3,3,3,4,5,5,3,4,5,4,5,4,5,0,14.0,satisfied +10908,127924,Female,Loyal Customer,25,Business travel,Business,2300,1,1,1,1,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +10909,74983,Male,Loyal Customer,48,Personal Travel,Eco,2475,2,5,2,3,5,2,1,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +10910,124248,Female,Loyal Customer,16,Personal Travel,Eco,1916,2,5,2,1,1,2,1,1,5,3,3,3,4,1,0,0.0,neutral or dissatisfied +10911,2170,Male,Loyal Customer,52,Business travel,Eco,624,2,3,3,3,2,2,2,2,1,3,3,4,4,2,0,20.0,neutral or dissatisfied +10912,33615,Female,disloyal Customer,45,Business travel,Eco,399,3,3,3,3,5,3,5,5,4,5,2,1,3,5,2,0.0,neutral or dissatisfied +10913,56609,Female,disloyal Customer,26,Business travel,Eco,997,2,2,2,3,5,2,3,5,3,2,4,3,3,5,63,52.0,neutral or dissatisfied +10914,30238,Male,Loyal Customer,60,Business travel,Eco,496,5,3,2,3,5,5,5,5,2,2,5,2,2,5,0,0.0,satisfied +10915,23086,Male,disloyal Customer,30,Business travel,Eco,864,1,1,1,1,2,1,2,2,2,2,2,3,1,2,0,0.0,neutral or dissatisfied +10916,79628,Male,Loyal Customer,55,Business travel,Business,3534,2,2,5,5,2,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +10917,47433,Male,Loyal Customer,67,Business travel,Eco,190,3,1,1,1,3,3,3,3,1,3,3,2,3,3,31,22.0,neutral or dissatisfied +10918,112362,Female,Loyal Customer,46,Business travel,Business,3521,2,2,2,2,3,5,4,4,4,4,4,3,4,5,5,10.0,satisfied +10919,25336,Male,Loyal Customer,8,Personal Travel,Eco,829,3,4,3,4,4,3,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +10920,79237,Female,Loyal Customer,64,Personal Travel,Eco,1521,0,5,0,4,1,1,2,1,1,0,1,1,1,4,0,0.0,satisfied +10921,7746,Male,Loyal Customer,43,Business travel,Business,3401,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,2.0,satisfied +10922,115952,Male,Loyal Customer,39,Personal Travel,Eco,446,1,5,1,4,5,1,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +10923,730,Female,Loyal Customer,41,Business travel,Business,2868,1,1,1,1,3,4,5,4,4,4,4,5,4,4,19,22.0,satisfied +10924,81303,Male,Loyal Customer,43,Business travel,Eco Plus,1020,2,5,5,5,2,2,2,2,4,3,4,2,3,2,0,0.0,neutral or dissatisfied +10925,82857,Female,Loyal Customer,49,Business travel,Business,2861,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +10926,54154,Female,Loyal Customer,31,Business travel,Business,1400,3,3,3,3,4,4,4,4,5,5,1,1,1,4,1,0.0,satisfied +10927,42360,Male,Loyal Customer,16,Personal Travel,Eco,329,4,2,4,3,5,4,5,5,2,4,3,2,4,5,0,0.0,neutral or dissatisfied +10928,34038,Female,Loyal Customer,66,Personal Travel,Eco Plus,1576,2,5,2,3,2,4,4,2,2,2,2,5,2,5,0,23.0,neutral or dissatisfied +10929,83855,Female,Loyal Customer,35,Personal Travel,Eco,425,3,4,3,3,5,3,5,5,2,4,3,2,4,5,11,22.0,neutral or dissatisfied +10930,4199,Male,disloyal Customer,22,Business travel,Eco,888,4,3,3,3,2,3,2,2,4,5,5,4,4,2,0,0.0,satisfied +10931,32563,Female,Loyal Customer,51,Business travel,Eco,101,4,4,4,4,2,5,5,4,4,4,4,3,4,2,0,9.0,satisfied +10932,107118,Male,Loyal Customer,47,Business travel,Business,842,5,5,5,5,5,4,4,4,4,4,4,3,4,3,33,17.0,satisfied +10933,74928,Male,Loyal Customer,25,Business travel,Business,2446,4,4,4,4,4,5,4,4,3,5,4,4,4,4,0,0.0,satisfied +10934,97262,Male,Loyal Customer,12,Personal Travel,Eco,296,2,5,2,4,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +10935,96281,Female,Loyal Customer,53,Personal Travel,Eco,546,4,2,4,2,3,3,2,3,3,4,4,2,3,1,15,4.0,satisfied +10936,72380,Male,Loyal Customer,52,Business travel,Business,1879,5,5,5,5,4,5,4,5,5,5,5,3,5,3,93,89.0,satisfied +10937,21147,Female,Loyal Customer,67,Personal Travel,Eco Plus,106,1,4,1,1,2,5,5,3,3,1,1,5,3,3,0,0.0,neutral or dissatisfied +10938,7805,Female,Loyal Customer,25,Business travel,Business,650,3,2,4,2,3,3,3,3,2,1,3,1,3,3,0,18.0,neutral or dissatisfied +10939,78172,Female,Loyal Customer,49,Business travel,Business,259,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10940,10618,Male,Loyal Customer,60,Business travel,Business,2111,2,2,2,2,5,4,4,5,5,5,5,4,5,4,13,12.0,satisfied +10941,15201,Male,Loyal Customer,56,Personal Travel,Eco,544,2,5,2,1,4,2,4,4,4,2,4,3,2,4,0,23.0,neutral or dissatisfied +10942,115762,Male,Loyal Customer,38,Business travel,Business,325,1,4,4,4,2,3,4,1,1,2,1,2,1,2,34,34.0,neutral or dissatisfied +10943,46801,Female,Loyal Customer,50,Business travel,Business,3377,5,5,5,5,1,4,3,4,4,4,4,5,4,3,0,0.0,satisfied +10944,30890,Female,Loyal Customer,33,Business travel,Eco,973,5,5,5,5,5,5,5,5,3,4,3,1,5,5,4,7.0,satisfied +10945,54185,Male,Loyal Customer,36,Business travel,Business,3613,5,5,5,5,4,4,4,3,3,5,3,1,3,5,0,0.0,satisfied +10946,14520,Male,disloyal Customer,27,Business travel,Eco,299,2,5,2,4,2,2,3,2,1,1,5,1,2,2,72,66.0,neutral or dissatisfied +10947,120327,Female,Loyal Customer,45,Personal Travel,Eco,268,3,2,3,5,3,5,5,3,3,3,5,4,3,3,0,1.0,neutral or dissatisfied +10948,121834,Male,Loyal Customer,58,Business travel,Business,2865,3,3,5,3,5,5,5,5,5,5,5,5,5,3,1,6.0,satisfied +10949,11134,Female,Loyal Customer,57,Personal Travel,Eco,667,3,5,2,4,2,3,3,3,3,4,5,3,5,3,189,178.0,neutral or dissatisfied +10950,26068,Female,Loyal Customer,37,Personal Travel,Business,591,2,5,2,1,4,5,5,2,2,2,2,4,2,4,1,5.0,neutral or dissatisfied +10951,57650,Male,Loyal Customer,66,Business travel,Business,2518,3,2,2,2,1,3,4,4,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +10952,76912,Male,Loyal Customer,47,Business travel,Business,630,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +10953,81048,Male,Loyal Customer,23,Business travel,Business,1399,4,3,3,3,4,4,4,4,1,4,4,4,3,4,0,8.0,neutral or dissatisfied +10954,98827,Female,Loyal Customer,23,Personal Travel,Eco,763,5,5,5,3,2,5,2,2,5,2,4,3,4,2,23,11.0,satisfied +10955,31457,Female,Loyal Customer,42,Business travel,Business,846,4,4,4,4,2,2,5,4,4,4,4,4,4,4,0,0.0,satisfied +10956,127497,Male,Loyal Customer,52,Personal Travel,Eco,2075,3,4,3,3,4,3,4,4,1,5,3,2,2,4,13,15.0,neutral or dissatisfied +10957,23046,Female,Loyal Customer,52,Personal Travel,Eco,833,3,5,3,1,3,4,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +10958,35321,Female,disloyal Customer,27,Business travel,Eco,1011,1,1,1,2,5,1,5,5,2,1,2,2,2,5,47,33.0,neutral or dissatisfied +10959,3664,Male,disloyal Customer,23,Business travel,Business,431,0,0,0,3,3,0,4,3,5,4,5,4,4,3,0,0.0,satisfied +10960,103414,Female,disloyal Customer,18,Business travel,Eco,237,5,3,5,2,4,5,4,4,4,5,4,4,5,4,0,0.0,satisfied +10961,40761,Male,Loyal Customer,48,Business travel,Business,584,2,1,1,1,4,2,3,2,2,2,2,4,2,4,9,17.0,neutral or dissatisfied +10962,67750,Male,Loyal Customer,29,Business travel,Business,1171,1,1,3,1,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +10963,77624,Male,Loyal Customer,29,Business travel,Business,689,5,5,5,5,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +10964,48765,Female,Loyal Customer,39,Business travel,Business,56,2,5,5,5,5,5,4,2,2,2,5,5,2,5,0,0.0,satisfied +10965,70655,Male,Loyal Customer,29,Business travel,Business,2258,5,5,1,5,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +10966,49173,Female,disloyal Customer,47,Business travel,Eco,447,1,5,1,4,2,1,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +10967,27543,Female,Loyal Customer,43,Personal Travel,Eco,937,5,4,5,4,2,4,4,4,4,4,4,5,4,3,0,4.0,satisfied +10968,95128,Female,Loyal Customer,27,Personal Travel,Eco,277,2,3,2,3,5,2,5,5,1,2,4,3,3,5,0,31.0,neutral or dissatisfied +10969,87046,Male,Loyal Customer,36,Business travel,Business,594,3,3,3,3,4,4,4,5,5,5,5,3,5,5,8,0.0,satisfied +10970,36388,Female,Loyal Customer,23,Personal Travel,Eco,200,1,5,1,1,4,1,4,4,3,4,3,2,2,4,0,0.0,neutral or dissatisfied +10971,72476,Male,Loyal Customer,58,Business travel,Business,1834,4,4,4,4,5,5,4,4,4,4,4,4,4,4,87,119.0,satisfied +10972,51932,Male,Loyal Customer,55,Business travel,Business,3647,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +10973,79017,Female,disloyal Customer,26,Business travel,Business,356,0,4,0,3,1,0,1,1,3,3,4,4,5,1,0,0.0,satisfied +10974,15724,Male,disloyal Customer,44,Business travel,Eco,424,1,1,1,3,4,1,4,4,3,4,4,1,4,4,4,11.0,neutral or dissatisfied +10975,23790,Male,Loyal Customer,43,Business travel,Eco,438,4,2,4,2,4,4,4,4,1,1,5,3,2,4,0,0.0,satisfied +10976,51539,Female,Loyal Customer,56,Business travel,Eco,493,5,1,1,1,3,2,5,5,5,5,5,2,5,2,0,0.0,satisfied +10977,3623,Female,Loyal Customer,18,Personal Travel,Business,431,2,5,5,2,5,5,3,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +10978,3196,Male,Loyal Customer,48,Personal Travel,Eco,585,4,5,4,5,1,4,1,1,4,5,5,4,5,1,10,24.0,neutral or dissatisfied +10979,125414,Male,disloyal Customer,34,Business travel,Business,735,1,1,1,1,4,1,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +10980,18453,Male,Loyal Customer,45,Business travel,Business,2853,4,4,3,4,4,4,3,4,4,4,4,4,4,4,10,11.0,satisfied +10981,9359,Female,Loyal Customer,66,Business travel,Business,401,3,3,3,3,2,3,2,3,3,3,3,1,3,3,20,1.0,neutral or dissatisfied +10982,64846,Male,Loyal Customer,43,Business travel,Eco,224,2,5,1,5,3,2,3,3,1,4,2,2,3,3,0,0.0,neutral or dissatisfied +10983,57928,Female,Loyal Customer,52,Business travel,Business,3041,4,4,4,4,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +10984,101422,Female,Loyal Customer,69,Business travel,Business,3571,1,1,3,1,2,4,5,4,4,4,4,5,4,5,27,25.0,satisfied +10985,36754,Female,disloyal Customer,42,Business travel,Eco,1353,3,3,3,3,3,2,2,1,1,5,2,2,5,2,242,270.0,neutral or dissatisfied +10986,43068,Female,Loyal Customer,64,Personal Travel,Eco,391,5,3,5,4,2,3,3,1,1,5,1,4,1,2,0,0.0,satisfied +10987,32992,Male,Loyal Customer,28,Personal Travel,Eco,102,1,4,1,2,5,1,5,5,5,4,4,3,4,5,10,15.0,neutral or dissatisfied +10988,64886,Female,Loyal Customer,53,Business travel,Eco,190,1,1,4,1,2,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +10989,101324,Male,Loyal Customer,40,Personal Travel,Eco,1076,2,4,2,3,4,2,4,4,5,3,5,4,4,4,18,18.0,neutral or dissatisfied +10990,49687,Male,Loyal Customer,47,Business travel,Business,153,0,4,0,1,4,5,1,5,5,5,5,1,5,3,0,0.0,satisfied +10991,31840,Male,Loyal Customer,43,Business travel,Business,2640,1,1,1,1,3,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +10992,71936,Male,Loyal Customer,7,Personal Travel,Eco Plus,1723,5,4,5,3,4,5,4,4,3,5,4,5,4,4,4,0.0,satisfied +10993,14749,Female,Loyal Customer,27,Business travel,Business,3226,1,1,1,1,2,2,2,2,5,1,4,3,5,2,26,11.0,satisfied +10994,114464,Male,Loyal Customer,48,Business travel,Business,390,5,5,4,5,5,4,4,4,4,4,4,4,4,3,19,12.0,satisfied +10995,53821,Female,disloyal Customer,33,Business travel,Eco,140,2,3,2,5,2,2,2,2,1,3,1,4,1,2,0,0.0,neutral or dissatisfied +10996,39822,Female,disloyal Customer,30,Business travel,Eco,221,2,5,2,1,4,2,4,4,2,1,2,4,3,4,0,1.0,neutral or dissatisfied +10997,87534,Male,Loyal Customer,56,Personal Travel,Eco Plus,321,4,3,4,3,5,4,4,5,1,3,4,2,3,5,66,55.0,neutral or dissatisfied +10998,73724,Male,Loyal Customer,50,Business travel,Eco,192,4,1,1,1,4,4,4,4,2,4,1,3,1,4,2,0.0,satisfied +10999,118725,Male,Loyal Customer,61,Personal Travel,Eco,370,3,5,3,4,3,3,3,3,3,4,4,1,4,3,15,4.0,neutral or dissatisfied +11000,102930,Female,Loyal Customer,29,Personal Travel,Eco,436,3,4,3,2,5,3,5,5,5,3,4,4,4,5,14,18.0,neutral or dissatisfied +11001,36373,Male,Loyal Customer,35,Business travel,Eco,200,3,1,1,1,3,3,3,3,4,5,5,2,2,3,22,16.0,satisfied +11002,25333,Male,Loyal Customer,10,Personal Travel,Eco,837,4,4,4,4,3,4,3,3,4,5,4,2,4,3,0,0.0,satisfied +11003,61252,Female,Loyal Customer,20,Personal Travel,Eco,853,0,4,0,4,5,4,5,5,5,2,4,3,4,5,0,8.0,satisfied +11004,32054,Female,disloyal Customer,56,Business travel,Eco,102,3,4,3,4,5,3,5,5,5,2,2,1,3,5,0,0.0,neutral or dissatisfied +11005,86981,Female,Loyal Customer,42,Business travel,Business,2381,1,1,2,1,2,5,3,5,5,5,5,2,5,2,9,6.0,satisfied +11006,128073,Male,Loyal Customer,56,Business travel,Business,2845,2,2,2,2,5,5,5,4,3,4,4,5,3,5,5,1.0,satisfied +11007,46101,Female,disloyal Customer,21,Business travel,Business,1154,5,4,5,2,3,5,3,3,5,4,5,3,5,3,10,3.0,satisfied +11008,71063,Female,Loyal Customer,16,Personal Travel,Eco,802,2,3,3,3,1,3,5,1,3,3,3,4,5,1,106,92.0,neutral or dissatisfied +11009,99780,Male,Loyal Customer,21,Business travel,Business,1900,4,2,2,2,4,4,4,4,2,4,4,3,4,4,0,2.0,neutral or dissatisfied +11010,40340,Male,Loyal Customer,62,Personal Travel,Eco Plus,347,3,4,3,2,3,3,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +11011,12368,Female,Loyal Customer,35,Business travel,Eco,253,3,5,5,5,3,4,3,3,4,5,3,1,5,3,0,0.0,satisfied +11012,47501,Male,Loyal Customer,12,Personal Travel,Eco,599,3,4,3,2,5,3,5,5,1,5,5,5,5,5,21,5.0,neutral or dissatisfied +11013,129428,Female,Loyal Customer,69,Business travel,Business,414,2,2,2,2,2,4,4,2,2,2,2,3,2,2,13,6.0,neutral or dissatisfied +11014,117036,Female,disloyal Customer,24,Business travel,Business,304,4,2,4,3,3,4,3,3,2,2,4,4,4,3,4,2.0,neutral or dissatisfied +11015,86285,Male,Loyal Customer,28,Personal Travel,Eco,356,3,4,5,4,2,5,2,2,2,5,4,1,4,2,42,32.0,neutral or dissatisfied +11016,39506,Female,disloyal Customer,26,Business travel,Eco,852,4,4,4,2,2,4,2,2,4,4,5,4,4,2,0,0.0,satisfied +11017,122885,Male,Loyal Customer,16,Personal Travel,Eco,226,3,4,3,1,3,3,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +11018,96051,Male,disloyal Customer,35,Business travel,Business,1069,4,3,3,5,2,3,3,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +11019,83677,Male,disloyal Customer,43,Business travel,Eco,577,3,2,3,3,1,3,1,1,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +11020,66910,Female,disloyal Customer,23,Business travel,Business,1017,0,0,1,5,4,1,4,4,5,3,4,4,5,4,85,79.0,satisfied +11021,41609,Female,Loyal Customer,46,Personal Travel,Eco,1242,2,5,3,4,3,5,5,3,3,3,5,4,3,5,0,0.0,neutral or dissatisfied +11022,68903,Female,Loyal Customer,58,Personal Travel,Eco,936,1,5,1,2,1,5,4,5,5,1,2,2,5,5,53,42.0,neutral or dissatisfied +11023,40038,Male,Loyal Customer,29,Business travel,Eco Plus,618,4,2,2,2,4,4,4,4,4,5,3,2,4,4,0,5.0,neutral or dissatisfied +11024,50749,Male,Loyal Customer,35,Personal Travel,Eco,421,2,2,2,3,1,2,1,1,3,3,2,2,2,1,51,58.0,neutral or dissatisfied +11025,15760,Male,Loyal Customer,18,Personal Travel,Eco,544,2,5,4,2,4,4,4,4,4,4,2,2,2,4,58,30.0,neutral or dissatisfied +11026,74733,Female,Loyal Customer,18,Personal Travel,Eco,1126,1,3,1,4,5,1,1,5,3,3,3,4,3,5,2,0.0,neutral or dissatisfied +11027,122258,Male,Loyal Customer,16,Personal Travel,Eco,546,3,3,3,3,4,3,4,4,2,3,3,3,1,4,0,0.0,neutral or dissatisfied +11028,88325,Female,Loyal Customer,38,Business travel,Business,406,3,3,3,3,3,4,4,3,3,3,3,3,3,2,1,0.0,neutral or dissatisfied +11029,58507,Female,Loyal Customer,48,Personal Travel,Eco,719,2,4,2,3,2,4,5,2,2,2,2,4,2,4,4,0.0,neutral or dissatisfied +11030,20722,Female,Loyal Customer,63,Personal Travel,Eco,765,3,2,3,3,3,3,4,4,4,3,4,3,4,2,0,10.0,neutral or dissatisfied +11031,123367,Male,Loyal Customer,30,Business travel,Business,1615,1,1,1,1,3,4,3,3,4,5,5,3,5,3,1,0.0,satisfied +11032,108601,Male,Loyal Customer,60,Business travel,Business,3088,5,3,5,5,3,4,5,4,4,4,4,5,4,4,8,0.0,satisfied +11033,101266,Male,Loyal Customer,59,Personal Travel,Eco,2176,4,3,4,3,4,4,4,4,1,1,3,2,3,4,0,2.0,neutral or dissatisfied +11034,6206,Female,Loyal Customer,45,Business travel,Business,462,2,3,2,2,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +11035,9091,Female,Loyal Customer,45,Personal Travel,Eco,160,1,4,1,2,3,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +11036,51632,Female,Loyal Customer,18,Business travel,Business,2420,1,0,0,4,3,0,2,3,4,1,4,3,3,3,1,0.0,neutral or dissatisfied +11037,19235,Female,Loyal Customer,28,Business travel,Business,2773,1,1,1,1,5,5,5,5,3,2,4,1,4,5,0,0.0,satisfied +11038,36686,Female,Loyal Customer,12,Personal Travel,Eco,1091,1,5,1,3,1,1,1,1,5,5,4,4,3,1,0,1.0,neutral or dissatisfied +11039,24751,Male,disloyal Customer,38,Business travel,Eco,447,5,5,5,3,4,5,4,4,4,3,5,5,4,4,0,0.0,satisfied +11040,16738,Female,Loyal Customer,46,Personal Travel,Eco,1167,3,5,3,2,5,4,1,5,5,3,5,1,5,4,6,27.0,neutral or dissatisfied +11041,29747,Male,disloyal Customer,28,Business travel,Business,571,4,4,4,1,5,4,3,5,3,4,5,4,4,5,86,76.0,satisfied +11042,23844,Female,disloyal Customer,34,Business travel,Business,552,3,3,3,4,1,3,1,1,5,2,4,5,5,1,0,0.0,neutral or dissatisfied +11043,115769,Female,Loyal Customer,30,Business travel,Business,3156,3,5,1,1,3,3,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +11044,26323,Male,Loyal Customer,24,Personal Travel,Eco,892,3,5,3,4,2,3,1,2,5,2,4,4,4,2,6,11.0,neutral or dissatisfied +11045,93926,Female,Loyal Customer,26,Business travel,Business,507,1,1,1,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +11046,38130,Male,Loyal Customer,31,Business travel,Business,1237,5,5,5,5,2,2,2,2,3,3,5,4,4,2,3,0.0,satisfied +11047,92324,Female,Loyal Customer,45,Business travel,Business,2486,5,5,5,5,4,4,4,5,5,3,4,4,3,4,6,40.0,satisfied +11048,60391,Female,Loyal Customer,59,Business travel,Business,1076,1,1,1,1,5,1,1,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +11049,12067,Male,Loyal Customer,40,Personal Travel,Eco,351,4,4,3,3,5,3,5,5,4,4,4,5,5,5,59,56.0,neutral or dissatisfied +11050,100731,Male,disloyal Customer,20,Business travel,Eco,328,1,3,1,4,1,1,1,1,1,3,4,4,4,1,25,21.0,neutral or dissatisfied +11051,81208,Female,Loyal Customer,35,Business travel,Business,1426,5,5,3,5,5,5,4,2,2,2,2,5,2,3,1,0.0,satisfied +11052,29905,Female,disloyal Customer,25,Business travel,Eco,503,2,4,2,2,3,2,3,3,3,3,4,2,4,3,7,17.0,neutral or dissatisfied +11053,50664,Female,Loyal Customer,48,Personal Travel,Eco,89,3,2,3,3,3,3,3,5,5,3,5,1,5,2,103,104.0,neutral or dissatisfied +11054,7392,Female,Loyal Customer,34,Business travel,Business,522,3,3,5,3,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +11055,88289,Male,Loyal Customer,45,Business travel,Business,3759,3,3,3,3,5,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +11056,60424,Male,disloyal Customer,25,Business travel,Business,862,2,0,2,2,3,2,3,3,4,2,5,3,5,3,2,0.0,neutral or dissatisfied +11057,56818,Male,disloyal Customer,35,Business travel,Eco,1605,2,2,2,2,3,2,4,3,1,1,2,4,3,3,114,104.0,neutral or dissatisfied +11058,105193,Male,Loyal Customer,36,Business travel,Business,1858,1,1,1,1,2,4,4,5,5,5,5,3,5,4,14,0.0,satisfied +11059,52755,Female,Loyal Customer,55,Business travel,Business,1874,2,2,2,2,5,5,4,5,5,5,5,3,5,5,10,0.0,satisfied +11060,90491,Female,Loyal Customer,42,Business travel,Business,250,2,2,2,2,5,5,4,4,4,4,4,5,4,5,0,4.0,satisfied +11061,29685,Male,Loyal Customer,40,Personal Travel,Eco Plus,1448,3,3,3,3,4,3,4,4,1,4,3,1,4,4,1,0.0,neutral or dissatisfied +11062,43920,Male,Loyal Customer,37,Personal Travel,Eco,174,4,3,4,3,2,4,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +11063,59481,Male,Loyal Customer,29,Business travel,Business,2831,2,3,3,3,2,2,2,2,1,5,2,3,2,2,0,0.0,neutral or dissatisfied +11064,78161,Male,disloyal Customer,40,Business travel,Business,259,4,4,4,2,2,4,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +11065,121832,Male,Loyal Customer,43,Business travel,Business,1570,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +11066,41237,Male,Loyal Customer,52,Business travel,Eco,1530,4,3,3,3,3,4,3,3,5,2,2,1,4,3,25,18.0,satisfied +11067,105175,Male,Loyal Customer,25,Personal Travel,Eco,277,4,1,4,3,2,4,2,2,4,2,3,1,4,2,3,0.0,neutral or dissatisfied +11068,63195,Male,disloyal Customer,65,Business travel,Business,337,4,4,4,5,4,4,4,4,5,4,5,5,5,4,0,1.0,satisfied +11069,73115,Female,Loyal Customer,8,Personal Travel,Eco,2174,0,1,0,4,4,0,4,4,2,1,3,3,4,4,1,0.0,satisfied +11070,10140,Male,Loyal Customer,14,Business travel,Business,1201,2,2,2,2,4,4,4,4,4,2,5,4,5,4,5,1.0,satisfied +11071,20140,Male,Loyal Customer,45,Personal Travel,Eco Plus,416,3,4,3,1,3,3,3,3,4,5,1,1,5,3,23,35.0,neutral or dissatisfied +11072,6159,Male,Loyal Customer,72,Business travel,Eco,501,1,1,1,1,1,1,1,1,3,4,3,1,3,1,10,10.0,neutral or dissatisfied +11073,76729,Male,disloyal Customer,38,Business travel,Eco Plus,116,2,2,2,4,3,2,3,3,2,3,4,2,3,3,8,6.0,neutral or dissatisfied +11074,120243,Male,Loyal Customer,61,Personal Travel,Eco,1496,3,2,3,4,3,3,3,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +11075,49453,Female,Loyal Customer,45,Business travel,Business,250,1,1,1,1,2,2,4,5,5,5,5,2,5,2,0,0.0,satisfied +11076,15902,Female,Loyal Customer,23,Business travel,Eco Plus,378,4,4,4,4,4,4,5,4,1,1,4,1,3,4,2,0.0,satisfied +11077,74082,Male,Loyal Customer,24,Business travel,Business,592,5,5,5,5,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +11078,48138,Male,disloyal Customer,36,Business travel,Business,236,2,2,2,2,3,2,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +11079,51276,Female,disloyal Customer,24,Business travel,Eco,109,3,1,3,3,2,3,2,2,2,2,3,3,4,2,0,5.0,neutral or dissatisfied +11080,90836,Female,disloyal Customer,32,Business travel,Eco,442,3,3,3,4,3,3,3,3,4,3,3,4,3,3,26,30.0,neutral or dissatisfied +11081,103205,Male,Loyal Customer,63,Business travel,Business,1482,4,1,2,1,1,3,3,4,4,4,4,1,4,4,83,96.0,neutral or dissatisfied +11082,62011,Female,Loyal Customer,33,Business travel,Business,2475,1,1,1,1,2,4,5,5,5,5,5,3,5,3,3,0.0,satisfied +11083,27920,Female,Loyal Customer,65,Personal Travel,Eco,689,2,5,2,2,1,4,1,3,3,2,3,5,3,1,0,0.0,neutral or dissatisfied +11084,104065,Female,Loyal Customer,72,Business travel,Business,3325,2,2,4,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +11085,30763,Male,Loyal Customer,23,Personal Travel,Eco,683,5,5,5,2,4,5,4,4,3,5,5,3,4,4,9,6.0,satisfied +11086,28098,Male,Loyal Customer,31,Business travel,Business,569,5,5,5,5,4,4,4,4,2,3,4,2,4,4,16,5.0,satisfied +11087,19779,Female,Loyal Customer,35,Business travel,Eco,578,5,4,4,4,5,5,5,5,3,5,3,1,5,5,0,1.0,satisfied +11088,2736,Male,Loyal Customer,32,Business travel,Business,2613,2,2,2,2,5,5,5,5,4,4,4,5,4,5,1,0.0,satisfied +11089,99085,Female,Loyal Customer,46,Business travel,Eco,453,2,4,1,4,2,3,4,2,2,2,2,4,2,4,73,60.0,neutral or dissatisfied +11090,10013,Female,Loyal Customer,41,Business travel,Business,3946,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +11091,89207,Male,Loyal Customer,14,Personal Travel,Eco,2139,2,5,2,1,1,2,1,1,5,2,5,3,4,1,16,7.0,neutral or dissatisfied +11092,119215,Male,Loyal Customer,26,Personal Travel,Eco,331,4,2,4,3,3,4,3,3,3,1,4,2,3,3,0,0.0,satisfied +11093,110272,Female,Loyal Customer,41,Business travel,Business,798,3,4,4,4,4,4,4,3,3,3,3,2,3,2,17,13.0,neutral or dissatisfied +11094,67108,Female,Loyal Customer,44,Business travel,Eco,1121,2,2,2,2,1,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +11095,70054,Male,Loyal Customer,19,Personal Travel,Eco,583,4,5,4,3,3,4,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +11096,118153,Female,Loyal Customer,33,Business travel,Business,1440,3,3,3,3,4,4,5,5,5,5,5,5,5,5,15,5.0,satisfied +11097,52658,Male,Loyal Customer,64,Personal Travel,Eco,119,5,1,5,3,1,5,3,1,4,1,4,4,4,1,0,0.0,satisfied +11098,45569,Female,disloyal Customer,21,Business travel,Eco,556,3,0,3,1,3,3,3,3,3,2,2,5,5,3,58,70.0,neutral or dissatisfied +11099,12862,Male,Loyal Customer,46,Business travel,Eco Plus,489,3,3,3,3,3,3,3,3,1,3,4,2,4,3,12,6.0,neutral or dissatisfied +11100,57201,Female,Loyal Customer,39,Business travel,Business,1514,2,2,2,2,5,4,5,4,4,4,4,4,4,3,14,3.0,satisfied +11101,3477,Female,Loyal Customer,52,Business travel,Business,990,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +11102,107208,Male,Loyal Customer,20,Personal Travel,Eco,668,4,4,4,3,1,4,1,1,4,4,5,5,4,1,5,0.0,satisfied +11103,79857,Male,Loyal Customer,43,Business travel,Eco,1035,3,2,2,2,3,3,3,3,2,1,3,2,4,3,54,53.0,neutral or dissatisfied +11104,36856,Male,Loyal Customer,37,Business travel,Business,3110,4,4,2,4,2,3,3,4,4,4,4,2,4,5,5,22.0,satisfied +11105,92945,Female,Loyal Customer,12,Personal Travel,Eco,151,4,5,4,1,2,4,4,2,4,2,4,5,5,2,4,0.0,neutral or dissatisfied +11106,74450,Male,Loyal Customer,40,Business travel,Business,1548,2,2,2,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +11107,76937,Male,Loyal Customer,40,Personal Travel,Eco,1823,2,5,2,2,5,2,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +11108,17331,Female,disloyal Customer,36,Business travel,Eco Plus,403,2,1,1,3,1,1,1,1,1,1,3,3,3,1,37,58.0,neutral or dissatisfied +11109,122056,Female,Loyal Customer,39,Business travel,Eco,130,2,1,1,1,2,3,2,2,4,1,4,4,3,2,9,5.0,neutral or dissatisfied +11110,42192,Female,Loyal Customer,43,Business travel,Eco,748,4,5,5,5,3,4,4,4,4,4,4,5,4,1,0,6.0,satisfied +11111,13637,Male,Loyal Customer,60,Business travel,Business,835,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11112,5640,Female,disloyal Customer,24,Business travel,Business,299,4,0,4,4,2,4,2,2,3,5,4,4,5,2,0,0.0,satisfied +11113,79636,Female,disloyal Customer,26,Business travel,Business,760,4,4,4,3,1,4,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +11114,66031,Female,Loyal Customer,42,Business travel,Business,1345,3,3,3,3,4,5,5,5,5,5,5,4,5,3,0,3.0,satisfied +11115,123888,Male,Loyal Customer,70,Personal Travel,Eco,544,2,3,3,3,3,3,3,3,3,1,2,2,2,3,0,20.0,neutral or dissatisfied +11116,74879,Male,Loyal Customer,58,Business travel,Business,2475,5,5,2,5,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +11117,49066,Female,Loyal Customer,47,Business travel,Business,3070,1,1,1,1,2,5,3,4,4,5,4,4,4,5,6,1.0,satisfied +11118,39364,Female,disloyal Customer,35,Business travel,Eco,896,1,1,1,3,4,1,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +11119,49275,Female,disloyal Customer,25,Business travel,Eco,86,2,0,1,3,1,1,1,1,5,1,4,4,2,1,0,0.0,neutral or dissatisfied +11120,90793,Male,Loyal Customer,50,Business travel,Business,271,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11121,90877,Female,Loyal Customer,65,Business travel,Eco,581,4,1,1,1,4,4,4,3,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +11122,87348,Male,Loyal Customer,50,Business travel,Business,3973,1,1,1,1,3,4,5,3,3,3,3,5,3,5,31,17.0,satisfied +11123,34774,Male,disloyal Customer,55,Business travel,Eco,301,4,0,5,2,5,5,5,5,5,1,5,1,4,5,0,10.0,satisfied +11124,33195,Female,Loyal Customer,47,Business travel,Eco Plus,163,5,2,5,2,1,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +11125,28409,Female,disloyal Customer,29,Business travel,Eco Plus,1489,2,2,2,4,4,2,4,4,3,1,3,2,3,4,0,47.0,neutral or dissatisfied +11126,13771,Male,Loyal Customer,29,Business travel,Business,2898,2,2,2,2,4,4,4,4,5,5,4,4,3,4,0,0.0,satisfied +11127,116199,Female,Loyal Customer,31,Personal Travel,Eco,417,3,1,3,2,1,3,1,1,1,4,2,4,3,1,38,28.0,neutral or dissatisfied +11128,27942,Female,Loyal Customer,44,Business travel,Eco,1774,4,5,5,5,1,3,2,4,4,4,4,5,4,3,0,2.0,satisfied +11129,188,Male,disloyal Customer,20,Business travel,Business,213,4,2,4,1,5,4,5,5,4,4,5,5,5,5,0,0.0,satisfied +11130,109598,Female,disloyal Customer,16,Business travel,Eco,861,3,3,3,3,1,3,1,1,4,5,4,4,4,1,48,56.0,neutral or dissatisfied +11131,112611,Female,Loyal Customer,19,Business travel,Business,1632,3,3,3,3,4,4,4,4,1,1,4,3,4,4,1,0.0,satisfied +11132,128933,Male,Loyal Customer,54,Business travel,Business,3808,1,1,3,1,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +11133,39024,Male,Loyal Customer,48,Personal Travel,Eco,230,0,5,0,2,4,0,4,4,4,2,5,4,4,4,0,12.0,satisfied +11134,6739,Female,Loyal Customer,8,Personal Travel,Eco Plus,268,2,4,2,1,2,2,2,2,3,5,4,3,4,2,33,28.0,neutral or dissatisfied +11135,129146,Female,disloyal Customer,28,Business travel,Business,679,2,2,2,1,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +11136,98426,Male,Loyal Customer,11,Personal Travel,Eco,1910,4,5,4,3,2,4,2,2,4,5,4,3,5,2,6,5.0,satisfied +11137,9546,Male,Loyal Customer,60,Business travel,Business,228,3,3,3,3,5,4,4,4,4,4,4,3,4,3,35,24.0,satisfied +11138,35804,Female,disloyal Customer,37,Business travel,Business,937,1,1,1,4,1,1,1,1,1,4,4,2,3,1,0,29.0,neutral or dissatisfied +11139,79115,Male,Loyal Customer,19,Personal Travel,Eco,356,3,4,3,3,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +11140,1586,Male,Loyal Customer,32,Business travel,Business,2858,2,2,2,2,2,2,2,2,4,3,2,1,3,2,34,31.0,neutral or dissatisfied +11141,56618,Male,Loyal Customer,44,Business travel,Business,997,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,2.0,satisfied +11142,44941,Female,Loyal Customer,53,Business travel,Eco,397,5,1,1,1,4,3,2,5,5,5,5,5,5,1,0,0.0,satisfied +11143,92787,Male,Loyal Customer,56,Business travel,Business,1671,1,1,1,1,3,4,5,3,3,2,3,4,3,5,0,0.0,satisfied +11144,1194,Female,Loyal Customer,51,Personal Travel,Eco,158,3,5,3,2,4,4,5,4,4,3,1,3,4,3,0,0.0,neutral or dissatisfied +11145,99808,Male,Loyal Customer,9,Personal Travel,Eco,584,3,5,3,1,1,3,2,1,5,4,2,3,1,1,0,0.0,neutral or dissatisfied +11146,4340,Female,Loyal Customer,33,Business travel,Business,1532,3,4,4,4,4,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +11147,120128,Male,Loyal Customer,44,Business travel,Business,1576,1,1,1,1,2,4,4,4,4,4,4,3,4,5,53,45.0,satisfied +11148,60706,Male,Loyal Customer,38,Business travel,Business,1605,5,5,5,5,2,3,4,5,5,5,5,3,5,4,1,0.0,satisfied +11149,105753,Female,Loyal Customer,57,Business travel,Eco,842,5,2,2,2,3,3,4,5,5,5,5,2,5,4,16,1.0,satisfied +11150,100231,Female,Loyal Customer,60,Business travel,Business,3794,3,3,3,3,1,3,2,3,3,3,3,3,3,3,10,1.0,neutral or dissatisfied +11151,112495,Male,Loyal Customer,30,Personal Travel,Eco,967,4,5,4,2,5,4,5,5,4,4,4,4,4,5,58,56.0,neutral or dissatisfied +11152,2405,Male,Loyal Customer,47,Business travel,Business,2367,2,5,3,5,3,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +11153,63769,Male,Loyal Customer,40,Business travel,Business,1721,1,1,1,1,2,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +11154,28289,Male,Loyal Customer,51,Business travel,Business,954,1,5,1,1,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +11155,122007,Female,Loyal Customer,33,Business travel,Business,1820,2,4,4,4,1,4,3,1,1,1,2,3,1,1,23,19.0,neutral or dissatisfied +11156,80008,Male,Loyal Customer,42,Personal Travel,Eco,1010,2,3,2,2,5,2,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +11157,95889,Male,Loyal Customer,44,Personal Travel,Eco,580,2,5,2,4,2,2,2,2,4,1,4,2,5,2,38,24.0,neutral or dissatisfied +11158,84362,Female,Loyal Customer,46,Business travel,Business,3704,2,4,5,5,5,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +11159,113767,Male,Loyal Customer,67,Personal Travel,Eco,488,2,0,5,2,3,5,3,3,3,5,5,4,4,3,13,19.0,neutral or dissatisfied +11160,126845,Female,Loyal Customer,57,Business travel,Business,2077,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +11161,125803,Male,disloyal Customer,34,Business travel,Business,861,1,0,0,3,1,0,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +11162,53272,Female,disloyal Customer,25,Business travel,Eco,921,5,5,5,2,5,5,5,5,4,4,4,2,3,5,8,13.0,satisfied +11163,28606,Male,Loyal Customer,27,Business travel,Business,2349,1,1,5,1,4,4,4,4,2,1,3,1,5,4,0,0.0,satisfied +11164,98512,Male,Loyal Customer,47,Business travel,Eco,402,2,4,4,4,2,2,2,2,2,1,4,2,3,2,2,0.0,neutral or dissatisfied +11165,51128,Female,Loyal Customer,39,Personal Travel,Eco,78,3,1,3,4,4,3,4,4,4,4,4,4,3,4,5,2.0,neutral or dissatisfied +11166,6207,Female,Loyal Customer,30,Business travel,Business,462,5,5,5,5,2,2,2,2,5,2,4,3,4,2,24,29.0,satisfied +11167,30988,Male,Loyal Customer,39,Business travel,Eco Plus,1476,4,1,1,1,4,4,4,4,1,4,3,5,5,4,0,0.0,satisfied +11168,30666,Female,disloyal Customer,29,Business travel,Eco Plus,770,1,0,0,3,3,0,3,3,4,5,4,2,3,3,42,41.0,neutral or dissatisfied +11169,61868,Male,Loyal Customer,43,Business travel,Business,2254,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +11170,121282,Female,Loyal Customer,31,Personal Travel,Eco Plus,2075,2,3,3,3,3,3,3,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +11171,107321,Female,disloyal Customer,20,Business travel,Eco Plus,307,3,2,3,1,3,4,4,1,2,2,1,4,4,4,71,138.0,neutral or dissatisfied +11172,6782,Male,Loyal Customer,58,Business travel,Business,235,4,4,4,4,2,5,4,5,5,4,5,4,5,5,106,92.0,satisfied +11173,43667,Male,Loyal Customer,68,Business travel,Eco,695,1,3,3,3,1,1,1,1,3,4,2,1,2,1,0,0.0,neutral or dissatisfied +11174,92490,Male,Loyal Customer,35,Business travel,Eco,1947,4,4,4,4,4,5,4,4,3,3,3,1,4,4,0,0.0,satisfied +11175,5573,Female,disloyal Customer,21,Personal Travel,Eco,501,3,5,3,3,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +11176,99260,Male,disloyal Customer,25,Business travel,Business,833,0,0,0,1,3,0,3,3,5,3,5,5,5,3,33,33.0,satisfied +11177,82748,Female,disloyal Customer,34,Business travel,Business,409,3,3,3,1,2,3,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +11178,89135,Male,Loyal Customer,19,Business travel,Business,1947,2,5,5,5,2,2,2,2,2,3,4,2,4,2,0,10.0,neutral or dissatisfied +11179,72729,Female,Loyal Customer,17,Business travel,Eco Plus,1121,5,5,5,5,5,5,4,5,5,4,5,1,5,5,0,0.0,satisfied +11180,70774,Male,Loyal Customer,48,Business travel,Business,3510,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,6.0,satisfied +11181,109963,Female,Loyal Customer,23,Personal Travel,Eco,1053,3,1,3,4,2,3,2,2,3,5,4,3,4,2,1,0.0,neutral or dissatisfied +11182,40952,Female,Loyal Customer,48,Business travel,Business,1846,3,3,3,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +11183,94267,Male,Loyal Customer,48,Business travel,Business,2121,3,3,3,3,4,4,4,4,4,4,4,3,4,4,8,8.0,satisfied +11184,57268,Female,Loyal Customer,47,Business travel,Eco,628,2,2,2,2,3,3,3,2,2,2,2,2,2,1,53,33.0,neutral or dissatisfied +11185,129485,Female,Loyal Customer,37,Business travel,Business,2004,2,1,1,1,3,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +11186,47289,Female,Loyal Customer,26,Business travel,Business,3374,3,3,3,3,5,5,5,5,3,4,3,1,3,5,0,6.0,satisfied +11187,128687,Female,Loyal Customer,28,Personal Travel,Eco,2442,2,5,2,1,2,3,3,5,4,3,4,3,4,3,116,127.0,neutral or dissatisfied +11188,9207,Female,Loyal Customer,46,Business travel,Business,2103,1,5,4,5,1,2,2,3,3,3,1,1,3,3,12,2.0,neutral or dissatisfied +11189,101897,Female,Loyal Customer,41,Business travel,Business,2173,3,2,2,2,2,2,3,3,3,3,3,3,3,3,2,8.0,neutral or dissatisfied +11190,79989,Female,Loyal Customer,54,Personal Travel,Eco,950,2,2,2,3,3,3,3,4,4,2,4,1,4,3,0,20.0,neutral or dissatisfied +11191,67173,Male,Loyal Customer,31,Personal Travel,Eco,964,2,4,2,4,3,2,5,3,5,3,4,5,4,3,94,86.0,neutral or dissatisfied +11192,12802,Male,Loyal Customer,23,Business travel,Business,3111,2,2,2,2,4,4,4,4,2,5,3,5,1,4,8,5.0,satisfied +11193,119309,Female,Loyal Customer,38,Business travel,Business,214,4,4,4,4,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +11194,129307,Female,Loyal Customer,67,Personal Travel,Business,2475,3,4,3,2,3,4,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +11195,72592,Female,Loyal Customer,46,Personal Travel,Eco,1017,5,0,5,4,5,5,4,1,1,5,1,5,1,4,0,2.0,satisfied +11196,109858,Male,Loyal Customer,60,Business travel,Business,2840,2,2,2,2,5,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +11197,21031,Female,Loyal Customer,41,Business travel,Eco,227,5,2,4,2,5,5,5,5,4,5,1,2,3,5,0,0.0,satisfied +11198,66170,Male,Loyal Customer,63,Business travel,Business,550,4,4,4,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +11199,84813,Female,Loyal Customer,45,Business travel,Business,481,3,4,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +11200,116995,Female,disloyal Customer,27,Business travel,Eco,651,3,4,3,3,5,3,5,5,3,1,4,3,4,5,77,97.0,neutral or dissatisfied +11201,56391,Female,Loyal Customer,49,Business travel,Business,719,4,4,2,4,2,5,4,3,3,3,3,5,3,3,0,23.0,satisfied +11202,119804,Female,Loyal Customer,42,Business travel,Business,2147,2,2,2,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +11203,42924,Female,disloyal Customer,37,Business travel,Eco Plus,628,3,3,3,1,5,3,3,5,5,4,5,4,3,5,0,0.0,neutral or dissatisfied +11204,83616,Female,Loyal Customer,38,Business travel,Eco,409,2,5,5,5,2,3,2,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +11205,88434,Female,Loyal Customer,45,Business travel,Business,2037,5,5,5,5,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +11206,96766,Male,Loyal Customer,47,Business travel,Business,849,2,2,2,2,4,4,4,4,5,5,4,4,5,4,139,127.0,satisfied +11207,85426,Female,Loyal Customer,49,Business travel,Business,2900,0,4,0,4,5,4,4,2,2,2,2,5,2,3,9,0.0,satisfied +11208,39290,Male,Loyal Customer,15,Personal Travel,Eco,67,1,4,1,4,3,1,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +11209,124994,Female,Loyal Customer,45,Business travel,Eco,184,2,2,2,2,2,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +11210,77522,Male,Loyal Customer,17,Personal Travel,Eco,1587,2,4,2,2,4,2,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +11211,32787,Female,Loyal Customer,39,Business travel,Eco,216,1,0,0,4,5,0,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +11212,99987,Female,disloyal Customer,55,Business travel,Business,220,5,5,5,4,5,5,4,5,3,4,5,4,4,5,0,0.0,satisfied +11213,1000,Female,Loyal Customer,63,Business travel,Eco,140,5,5,4,5,5,1,3,4,4,5,4,5,4,1,5,0.0,satisfied +11214,12129,Male,Loyal Customer,34,Business travel,Eco Plus,852,3,4,5,4,3,3,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +11215,107716,Male,Loyal Customer,19,Business travel,Business,405,3,4,1,4,3,3,3,3,4,1,3,4,4,3,24,18.0,neutral or dissatisfied +11216,25018,Male,Loyal Customer,23,Business travel,Business,3295,5,5,5,5,4,4,4,4,1,1,2,4,5,4,4,31.0,satisfied +11217,83657,Female,Loyal Customer,52,Business travel,Business,577,3,4,4,4,1,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +11218,23830,Female,Loyal Customer,41,Personal Travel,Eco,1131,2,4,2,4,4,2,2,4,4,2,4,4,5,4,34,23.0,neutral or dissatisfied +11219,108978,Female,Loyal Customer,22,Business travel,Business,972,4,4,4,4,2,2,2,2,3,4,4,5,5,2,0,0.0,satisfied +11220,56429,Female,Loyal Customer,48,Business travel,Business,719,3,5,4,5,4,3,3,3,3,3,3,4,3,3,55,41.0,neutral or dissatisfied +11221,33479,Male,Loyal Customer,36,Business travel,Eco,2422,4,2,2,2,4,4,4,4,1,1,5,5,1,4,0,0.0,satisfied +11222,63377,Male,Loyal Customer,23,Personal Travel,Eco,447,4,4,4,4,1,4,1,1,3,4,4,5,5,1,32,24.0,neutral or dissatisfied +11223,15940,Female,Loyal Customer,47,Business travel,Eco,738,3,2,2,2,3,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +11224,50397,Female,Loyal Customer,61,Business travel,Business,3805,1,1,1,1,2,3,5,5,5,5,5,4,5,2,0,4.0,satisfied +11225,36510,Female,disloyal Customer,37,Business travel,Eco,1237,2,2,2,4,2,2,3,2,5,1,4,5,2,2,9,67.0,neutral or dissatisfied +11226,99748,Male,disloyal Customer,29,Business travel,Eco,255,4,0,4,3,1,4,1,1,2,4,1,2,4,1,18,13.0,satisfied +11227,90404,Male,Loyal Customer,52,Personal Travel,Business,271,4,4,4,4,4,4,4,4,4,4,2,4,4,3,0,0.0,neutral or dissatisfied +11228,45456,Male,Loyal Customer,46,Business travel,Eco,522,5,4,4,4,5,5,5,5,1,5,5,1,3,5,0,0.0,satisfied +11229,120166,Female,Loyal Customer,35,Business travel,Eco,119,3,3,3,3,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +11230,87508,Male,Loyal Customer,51,Personal Travel,Eco,321,3,3,3,1,3,3,3,3,3,5,2,3,2,3,0,0.0,neutral or dissatisfied +11231,38419,Female,Loyal Customer,29,Business travel,Business,965,4,4,4,4,4,4,4,4,3,4,1,5,3,4,0,0.0,satisfied +11232,121716,Male,Loyal Customer,46,Personal Travel,Eco,683,1,5,1,5,4,1,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +11233,25030,Male,disloyal Customer,20,Business travel,Eco,507,1,0,1,4,3,1,3,3,3,4,4,3,1,3,3,0.0,neutral or dissatisfied +11234,20577,Male,Loyal Customer,9,Personal Travel,Eco,565,1,3,1,4,1,3,3,3,1,3,4,3,1,3,151,164.0,neutral or dissatisfied +11235,23727,Male,Loyal Customer,40,Business travel,Eco Plus,212,3,1,1,1,3,3,3,3,4,1,1,5,5,3,0,0.0,satisfied +11236,121223,Female,disloyal Customer,26,Business travel,Business,2075,4,4,4,3,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +11237,109161,Female,Loyal Customer,47,Business travel,Business,2011,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +11238,69805,Female,Loyal Customer,20,Business travel,Business,1842,1,1,5,1,3,4,3,3,5,5,5,3,5,3,0,0.0,satisfied +11239,119028,Male,Loyal Customer,51,Personal Travel,Eco,1460,3,4,3,2,2,3,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +11240,108244,Male,disloyal Customer,23,Business travel,Eco,895,1,1,1,4,3,1,3,3,3,2,4,1,3,3,9,2.0,neutral or dissatisfied +11241,14918,Male,Loyal Customer,69,Personal Travel,Eco,240,2,2,2,2,5,2,5,5,3,1,3,2,2,5,0,0.0,neutral or dissatisfied +11242,15042,Female,disloyal Customer,34,Business travel,Eco,627,2,4,2,1,5,2,5,5,5,4,2,1,4,5,0,0.0,neutral or dissatisfied +11243,43545,Female,Loyal Customer,43,Personal Travel,Eco,393,1,4,1,3,5,5,5,3,3,1,3,5,3,5,98,94.0,neutral or dissatisfied +11244,41478,Female,disloyal Customer,24,Business travel,Eco,1334,2,2,2,3,1,2,1,1,4,4,1,2,2,1,16,0.0,neutral or dissatisfied +11245,6065,Male,Loyal Customer,17,Personal Travel,Eco,630,3,5,3,3,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +11246,104309,Female,disloyal Customer,25,Business travel,Business,528,1,4,2,1,5,2,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +11247,89608,Male,Loyal Customer,55,Business travel,Business,2067,4,4,4,4,2,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +11248,56315,Female,Loyal Customer,56,Business travel,Business,3548,2,2,2,2,5,5,4,5,5,5,5,4,5,5,22,6.0,satisfied +11249,17538,Female,Loyal Customer,18,Personal Travel,Eco,252,4,5,0,3,2,0,2,2,3,1,2,1,3,2,0,0.0,neutral or dissatisfied +11250,97764,Female,Loyal Customer,56,Business travel,Business,587,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +11251,3873,Male,Loyal Customer,31,Business travel,Business,2305,3,3,3,3,5,4,5,5,4,2,4,4,5,5,0,0.0,satisfied +11252,86929,Female,Loyal Customer,69,Personal Travel,Eco,341,2,5,2,3,5,5,4,2,2,2,2,4,2,3,0,1.0,neutral or dissatisfied +11253,58899,Female,disloyal Customer,54,Business travel,Eco,888,3,4,4,3,3,4,3,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +11254,21922,Male,Loyal Customer,36,Business travel,Business,3539,1,3,1,1,4,4,4,1,5,1,5,4,3,4,133,158.0,satisfied +11255,96975,Female,Loyal Customer,46,Business travel,Business,883,1,1,1,1,3,4,4,2,2,2,2,3,2,5,39,29.0,satisfied +11256,128797,Male,Loyal Customer,69,Business travel,Business,2586,5,5,2,5,5,5,5,4,5,3,5,5,3,5,0,0.0,satisfied +11257,108209,Male,Loyal Customer,48,Business travel,Business,3881,5,5,5,5,5,4,5,5,5,5,5,4,5,4,33,38.0,satisfied +11258,92669,Male,disloyal Customer,25,Business travel,Business,507,5,5,5,2,2,5,2,2,3,4,5,3,4,2,0,0.0,satisfied +11259,104097,Male,Loyal Customer,43,Business travel,Business,2301,4,4,5,4,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +11260,79930,Female,Loyal Customer,50,Business travel,Business,1089,3,1,1,1,5,4,4,3,3,2,3,4,3,3,4,0.0,neutral or dissatisfied +11261,72370,Female,Loyal Customer,59,Business travel,Business,2592,5,5,5,5,2,4,4,5,5,4,5,4,5,4,3,7.0,satisfied +11262,119057,Female,Loyal Customer,14,Personal Travel,Eco,2279,1,4,1,3,3,1,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +11263,22323,Female,Loyal Customer,52,Business travel,Business,1847,4,4,4,4,5,2,1,5,5,5,5,1,5,5,0,1.0,satisfied +11264,71728,Female,Loyal Customer,52,Business travel,Eco Plus,1007,3,1,1,1,2,4,4,4,4,3,4,4,4,4,0,8.0,neutral or dissatisfied +11265,66684,Male,Loyal Customer,55,Business travel,Business,3098,4,4,4,4,2,5,4,3,3,4,3,5,3,4,4,0.0,satisfied +11266,72591,Female,Loyal Customer,65,Personal Travel,Eco,1102,3,4,3,4,5,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +11267,103724,Female,Loyal Customer,13,Personal Travel,Eco,405,2,4,2,1,4,2,4,4,4,1,3,4,5,4,1,0.0,neutral or dissatisfied +11268,72362,Male,Loyal Customer,43,Business travel,Business,929,5,2,5,5,5,4,5,4,4,4,4,4,4,3,1,1.0,satisfied +11269,14228,Male,Loyal Customer,25,Business travel,Eco Plus,714,5,1,1,1,5,5,4,5,5,4,4,1,2,5,0,0.0,satisfied +11270,17486,Male,Loyal Customer,48,Business travel,Business,241,0,0,0,2,1,3,2,3,3,3,3,3,3,5,67,80.0,satisfied +11271,64517,Male,Loyal Customer,44,Personal Travel,Business,551,2,0,2,5,4,5,5,1,1,2,1,3,1,4,29,18.0,neutral or dissatisfied +11272,75853,Female,Loyal Customer,13,Personal Travel,Eco,1440,3,4,3,4,5,3,5,5,5,4,4,3,4,5,62,81.0,neutral or dissatisfied +11273,99284,Male,Loyal Customer,53,Business travel,Eco,433,2,5,5,5,2,2,2,2,1,4,3,3,1,2,34,30.0,satisfied +11274,65209,Male,Loyal Customer,55,Business travel,Eco Plus,551,3,5,3,5,3,3,3,3,3,2,3,2,3,3,11,1.0,neutral or dissatisfied +11275,61411,Female,Loyal Customer,38,Personal Travel,Eco,679,3,4,3,3,1,3,1,1,2,2,4,1,4,1,104,123.0,neutral or dissatisfied +11276,57612,Female,disloyal Customer,33,Business travel,Business,200,4,4,4,1,2,4,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +11277,32732,Male,disloyal Customer,50,Business travel,Eco,163,3,5,3,4,1,3,1,1,1,5,5,1,2,1,0,0.0,neutral or dissatisfied +11278,63012,Female,Loyal Customer,47,Business travel,Business,2039,4,4,4,4,3,4,4,5,5,5,5,3,5,3,2,2.0,satisfied +11279,6456,Male,Loyal Customer,73,Business travel,Business,2265,3,2,3,3,2,4,4,4,4,4,4,3,4,3,24,22.0,satisfied +11280,54168,Male,Loyal Customer,53,Business travel,Business,1400,3,3,3,3,4,3,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +11281,28215,Female,Loyal Customer,34,Business travel,Eco Plus,933,4,5,5,5,4,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +11282,19479,Male,Loyal Customer,28,Business travel,Business,3989,2,3,3,3,3,3,2,3,3,3,4,4,4,3,62,88.0,neutral or dissatisfied +11283,4784,Male,Loyal Customer,57,Business travel,Business,2556,2,5,5,5,4,3,2,2,2,2,2,2,2,2,41,99.0,neutral or dissatisfied +11284,103886,Female,Loyal Customer,29,Personal Travel,Eco,869,3,1,3,3,4,3,2,4,4,1,3,2,3,4,11,7.0,neutral or dissatisfied +11285,44396,Male,Loyal Customer,43,Business travel,Business,1829,2,2,2,2,3,1,1,4,4,4,4,2,4,3,0,0.0,satisfied +11286,19960,Male,Loyal Customer,67,Personal Travel,Eco Plus,315,1,1,1,5,3,1,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +11287,114061,Female,disloyal Customer,29,Business travel,Business,1947,3,3,3,4,2,3,2,2,5,2,4,4,4,2,10,8.0,neutral or dissatisfied +11288,123173,Male,disloyal Customer,37,Business travel,Eco,328,2,1,2,3,1,2,4,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +11289,118694,Male,Loyal Customer,61,Personal Travel,Eco,368,3,3,1,4,2,1,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +11290,51903,Female,disloyal Customer,39,Business travel,Business,507,1,1,1,4,4,1,1,4,1,2,3,2,5,4,0,0.0,neutral or dissatisfied +11291,53711,Female,Loyal Customer,63,Personal Travel,Eco,1208,4,4,4,1,5,5,3,1,1,4,4,1,1,5,0,0.0,neutral or dissatisfied +11292,65942,Male,Loyal Customer,22,Personal Travel,Eco Plus,569,3,2,4,3,2,4,2,2,1,2,3,4,4,2,5,9.0,neutral or dissatisfied +11293,33085,Female,Loyal Customer,51,Personal Travel,Eco,216,4,4,4,3,5,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +11294,50417,Male,Loyal Customer,33,Business travel,Eco,109,4,3,3,3,4,4,4,4,2,5,1,2,3,4,0,0.0,satisfied +11295,84169,Male,Loyal Customer,54,Business travel,Business,3049,5,5,4,5,3,4,5,5,5,5,5,4,5,5,0,23.0,satisfied +11296,35514,Female,Loyal Customer,25,Personal Travel,Eco,944,2,2,2,4,2,1,1,1,5,3,3,1,3,1,126,135.0,neutral or dissatisfied +11297,107742,Female,Loyal Customer,36,Personal Travel,Eco,251,3,5,3,2,5,3,5,5,3,5,5,4,4,5,54,36.0,neutral or dissatisfied +11298,44513,Male,Loyal Customer,48,Business travel,Eco,157,5,5,5,5,5,5,5,5,2,5,2,3,2,5,0,0.0,satisfied +11299,83379,Male,Loyal Customer,35,Personal Travel,Eco,1124,2,5,2,5,3,2,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +11300,118192,Female,Loyal Customer,35,Business travel,Eco,1444,3,5,5,5,3,3,3,3,3,2,4,3,4,3,0,0.0,satisfied +11301,49790,Female,disloyal Customer,28,Business travel,Eco,421,2,3,2,2,5,2,5,5,1,2,4,4,5,5,0,1.0,neutral or dissatisfied +11302,104777,Male,Loyal Customer,9,Personal Travel,Business,587,3,4,4,1,3,4,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +11303,16590,Female,Loyal Customer,34,Personal Travel,Eco,872,3,5,3,4,2,3,1,2,4,4,3,5,5,2,0,26.0,neutral or dissatisfied +11304,7599,Male,Loyal Customer,48,Business travel,Business,1846,3,3,3,3,2,5,5,4,4,4,4,5,4,4,54,35.0,satisfied +11305,5612,Male,disloyal Customer,25,Business travel,Business,685,0,5,0,1,2,5,2,2,3,4,5,4,5,2,0,0.0,satisfied +11306,58698,Male,disloyal Customer,22,Business travel,Business,4243,5,0,5,5,5,5,5,5,5,3,5,5,4,5,14,16.0,satisfied +11307,108017,Female,Loyal Customer,44,Business travel,Business,589,2,1,2,2,2,5,5,4,4,4,4,5,4,3,3,0.0,satisfied +11308,87144,Female,disloyal Customer,19,Business travel,Business,645,5,2,5,4,4,5,3,4,4,3,4,4,4,4,0,0.0,satisfied +11309,10070,Female,Loyal Customer,21,Personal Travel,Eco,596,3,2,2,3,2,3,3,2,2,4,4,3,1,3,136,117.0,neutral or dissatisfied +11310,64040,Male,Loyal Customer,56,Business travel,Business,2981,4,4,4,4,3,4,4,5,5,5,5,3,5,4,2,0.0,satisfied +11311,30896,Male,Loyal Customer,34,Personal Travel,Eco,841,4,2,4,4,4,4,3,1,3,4,3,3,4,3,166,174.0,neutral or dissatisfied +11312,44832,Female,Loyal Customer,38,Personal Travel,Eco,462,3,3,3,3,2,3,2,2,1,1,4,1,1,2,23,50.0,neutral or dissatisfied +11313,123230,Male,Loyal Customer,42,Personal Travel,Eco,650,1,4,1,3,3,1,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +11314,119407,Female,disloyal Customer,30,Business travel,Eco,399,3,3,4,3,2,4,4,2,4,1,4,2,3,2,47,40.0,neutral or dissatisfied +11315,71691,Male,Loyal Customer,46,Personal Travel,Eco,1197,2,5,2,1,5,2,5,5,5,3,4,5,4,5,5,0.0,neutral or dissatisfied +11316,101796,Male,Loyal Customer,39,Business travel,Business,1521,4,4,4,4,2,5,4,4,4,4,4,5,4,3,7,0.0,satisfied +11317,102438,Male,Loyal Customer,21,Personal Travel,Eco,397,3,1,5,2,1,5,1,1,3,3,2,1,2,1,2,0.0,neutral or dissatisfied +11318,38296,Female,Loyal Customer,25,Business travel,Business,2583,3,2,2,2,3,3,3,1,2,1,2,3,1,3,6,125.0,neutral or dissatisfied +11319,122637,Female,Loyal Customer,71,Business travel,Eco Plus,728,3,4,3,3,2,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +11320,63559,Female,Loyal Customer,64,Personal Travel,Eco Plus,1009,3,4,3,3,3,4,5,1,1,3,1,4,1,3,5,0.0,neutral or dissatisfied +11321,20223,Female,Loyal Customer,42,Business travel,Eco,346,4,2,2,2,1,1,4,4,4,4,4,1,4,2,11,11.0,satisfied +11322,94962,Female,Loyal Customer,51,Business travel,Eco,239,5,5,5,5,3,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +11323,100647,Male,Loyal Customer,39,Personal Travel,Eco,349,2,5,2,3,5,2,5,5,3,4,4,3,5,5,45,42.0,neutral or dissatisfied +11324,79313,Male,Loyal Customer,42,Personal Travel,Eco,2248,1,5,1,4,5,1,5,5,3,5,3,3,5,5,1,0.0,neutral or dissatisfied +11325,106859,Male,disloyal Customer,27,Business travel,Business,577,3,2,2,5,3,2,3,3,3,2,5,3,5,3,28,24.0,neutral or dissatisfied +11326,18339,Female,disloyal Customer,25,Business travel,Eco,474,3,0,3,4,3,3,3,3,3,4,2,2,4,3,0,0.0,neutral or dissatisfied +11327,12821,Female,Loyal Customer,56,Business travel,Business,528,2,1,5,1,1,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +11328,121521,Female,disloyal Customer,29,Business travel,Business,1095,2,2,2,2,2,2,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +11329,32494,Female,Loyal Customer,48,Business travel,Eco,101,4,2,5,5,4,1,1,4,4,4,4,1,4,1,0,0.0,satisfied +11330,105902,Female,disloyal Customer,21,Business travel,Eco,283,4,3,4,2,5,4,5,5,2,3,2,2,2,5,0,0.0,neutral or dissatisfied +11331,128712,Female,Loyal Customer,44,Business travel,Business,1235,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +11332,62552,Female,disloyal Customer,26,Business travel,Business,1744,2,2,2,4,4,2,4,4,5,3,4,4,4,4,11,10.0,neutral or dissatisfied +11333,35397,Female,Loyal Customer,41,Business travel,Business,3195,4,4,4,4,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +11334,79376,Female,Loyal Customer,25,Business travel,Business,1816,1,1,1,1,2,2,2,2,4,4,5,3,4,2,0,0.0,satisfied +11335,96355,Female,Loyal Customer,48,Personal Travel,Eco,1609,3,5,3,2,4,4,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +11336,56417,Female,Loyal Customer,47,Business travel,Business,3975,2,2,2,2,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +11337,90934,Female,Loyal Customer,55,Business travel,Eco,581,4,5,3,5,2,2,2,4,4,4,4,3,4,4,0,0.0,satisfied +11338,64345,Male,Loyal Customer,51,Business travel,Business,3601,4,4,4,4,2,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +11339,90702,Male,Loyal Customer,34,Business travel,Business,581,2,2,2,2,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +11340,111936,Female,Loyal Customer,51,Business travel,Business,3590,4,4,4,4,2,5,4,5,5,5,5,3,5,5,4,0.0,satisfied +11341,57171,Male,Loyal Customer,53,Business travel,Business,2227,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,5.0,satisfied +11342,10079,Female,Loyal Customer,49,Business travel,Business,1851,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +11343,122322,Male,Loyal Customer,25,Business travel,Business,3939,5,5,5,5,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +11344,44166,Female,Loyal Customer,37,Personal Travel,Eco,229,3,4,0,3,5,0,3,5,4,3,5,3,4,5,2,23.0,neutral or dissatisfied +11345,9520,Male,Loyal Customer,35,Business travel,Business,1645,2,2,2,2,4,5,5,4,4,4,4,3,4,5,65,36.0,satisfied +11346,76719,Male,Loyal Customer,38,Business travel,Business,534,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,21.0,satisfied +11347,119594,Male,Loyal Customer,32,Business travel,Eco,1979,3,2,2,2,3,3,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +11348,118818,Female,disloyal Customer,24,Business travel,Eco,370,4,0,4,3,4,4,4,4,5,5,5,3,4,4,0,0.0,satisfied +11349,81853,Female,Loyal Customer,50,Business travel,Business,1416,3,3,3,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +11350,48907,Female,Loyal Customer,34,Business travel,Eco,190,5,5,5,5,5,5,5,5,5,2,1,4,1,5,0,0.0,satisfied +11351,76504,Male,Loyal Customer,23,Business travel,Business,2327,2,2,2,2,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +11352,128901,Female,Loyal Customer,18,Personal Travel,Eco,2565,3,5,2,3,2,1,5,3,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +11353,2159,Male,Loyal Customer,26,Business travel,Business,685,4,4,4,4,4,4,4,4,5,5,5,5,5,4,14,9.0,satisfied +11354,3323,Male,disloyal Customer,29,Business travel,Business,296,4,4,4,5,5,4,5,5,5,3,5,3,5,5,0,0.0,satisfied +11355,681,Female,Loyal Customer,48,Business travel,Business,3552,3,2,4,2,3,4,4,1,1,1,3,4,1,1,0,0.0,neutral or dissatisfied +11356,30499,Female,Loyal Customer,14,Personal Travel,Eco,604,2,2,2,4,5,2,5,5,1,4,3,4,3,5,0,2.0,neutral or dissatisfied +11357,62895,Male,Loyal Customer,42,Business travel,Business,2264,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +11358,122257,Female,Loyal Customer,64,Personal Travel,Eco,541,3,4,3,4,4,5,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +11359,89537,Female,Loyal Customer,40,Business travel,Business,1796,3,3,3,3,3,5,5,3,3,3,3,5,3,3,0,11.0,satisfied +11360,51585,Female,Loyal Customer,49,Business travel,Business,3606,3,4,4,4,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +11361,74351,Male,Loyal Customer,29,Business travel,Business,3883,5,5,5,5,4,5,4,4,3,3,4,5,4,4,0,0.0,satisfied +11362,100223,Male,disloyal Customer,29,Business travel,Business,1073,2,2,2,4,1,2,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +11363,5275,Female,Loyal Customer,59,Personal Travel,Eco,383,2,5,2,1,2,5,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +11364,77117,Male,Loyal Customer,32,Personal Travel,Eco,1481,3,4,2,1,3,2,3,3,4,4,1,1,5,3,0,0.0,neutral or dissatisfied +11365,22012,Female,Loyal Customer,45,Personal Travel,Eco,448,0,1,0,4,1,4,3,5,5,0,5,2,5,1,0,0.0,satisfied +11366,65065,Male,Loyal Customer,35,Personal Travel,Eco,247,3,5,3,4,1,3,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +11367,80206,Female,disloyal Customer,26,Business travel,Business,957,4,4,4,3,4,2,2,4,2,3,4,2,4,2,21,0.0,satisfied +11368,90851,Female,Loyal Customer,56,Business travel,Eco,515,3,3,3,3,1,1,2,2,2,3,2,2,2,4,20,17.0,neutral or dissatisfied +11369,21741,Female,disloyal Customer,24,Business travel,Eco,563,3,5,3,4,1,3,1,1,2,1,3,1,2,1,28,22.0,neutral or dissatisfied +11370,71522,Male,Loyal Customer,31,Business travel,Business,2914,3,3,3,3,3,3,3,3,4,4,4,5,5,3,2,18.0,satisfied +11371,89921,Male,Loyal Customer,18,Business travel,Business,1487,4,2,2,2,4,4,4,4,2,3,4,1,3,4,0,27.0,neutral or dissatisfied +11372,91462,Male,disloyal Customer,54,Business travel,Business,859,4,4,4,4,4,4,4,4,5,3,5,5,5,4,8,0.0,satisfied +11373,52461,Female,Loyal Customer,24,Business travel,Eco Plus,261,5,5,5,5,5,5,4,5,3,2,3,3,3,5,0,0.0,satisfied +11374,72034,Male,Loyal Customer,58,Personal Travel,Eco,3784,3,4,3,1,3,3,3,5,1,4,4,3,1,3,26,0.0,neutral or dissatisfied +11375,116050,Male,Loyal Customer,39,Personal Travel,Eco,342,3,5,3,3,4,3,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +11376,115176,Male,Loyal Customer,51,Business travel,Business,3652,4,4,4,4,3,4,5,4,4,4,4,3,4,3,15,12.0,satisfied +11377,106774,Female,Loyal Customer,68,Personal Travel,Eco,837,3,5,3,5,4,1,3,4,4,3,4,5,4,2,0,10.0,neutral or dissatisfied +11378,16176,Male,Loyal Customer,28,Business travel,Business,277,5,5,5,5,5,5,5,5,1,3,1,1,1,5,0,0.0,satisfied +11379,104132,Male,Loyal Customer,58,Business travel,Business,2918,5,5,5,5,5,4,4,5,5,4,5,3,5,4,4,0.0,satisfied +11380,106787,Female,Loyal Customer,65,Personal Travel,Eco Plus,829,3,2,3,2,2,2,3,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +11381,72968,Male,Loyal Customer,57,Business travel,Business,2729,4,4,5,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +11382,104591,Female,Loyal Customer,39,Personal Travel,Eco,369,3,4,3,1,2,3,2,2,4,3,4,2,4,2,34,24.0,neutral or dissatisfied +11383,15868,Male,Loyal Customer,44,Business travel,Eco,332,5,4,4,4,5,5,5,5,5,4,4,5,2,5,0,0.0,satisfied +11384,105479,Female,Loyal Customer,50,Business travel,Business,3240,3,3,3,3,5,4,5,3,3,4,3,3,3,4,91,80.0,satisfied +11385,52823,Male,disloyal Customer,22,Business travel,Eco,2402,5,5,5,3,3,5,3,3,5,4,4,2,5,3,0,0.0,satisfied +11386,88044,Male,disloyal Customer,28,Business travel,Business,515,5,5,5,4,4,5,4,4,5,3,4,5,4,4,0,0.0,satisfied +11387,83645,Female,Loyal Customer,29,Business travel,Business,577,5,5,5,5,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +11388,120170,Male,Loyal Customer,35,Business travel,Eco,335,2,5,5,5,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +11389,96044,Female,Loyal Customer,66,Business travel,Business,2986,4,2,2,2,4,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +11390,35576,Female,disloyal Customer,38,Business travel,Eco Plus,1028,1,1,1,4,3,1,5,3,1,3,3,3,4,3,0,31.0,neutral or dissatisfied +11391,82941,Male,Loyal Customer,60,Personal Travel,Eco Plus,594,3,4,3,3,5,3,5,5,5,2,5,2,2,5,0,0.0,neutral or dissatisfied +11392,126979,Male,disloyal Customer,37,Business travel,Business,621,4,4,4,4,5,4,5,5,3,3,4,5,5,5,0,0.0,satisfied +11393,36830,Male,disloyal Customer,24,Business travel,Eco,369,1,4,1,3,2,1,4,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +11394,16474,Male,Loyal Customer,70,Business travel,Eco Plus,445,3,4,1,4,3,3,3,3,4,5,4,4,3,3,0,7.0,neutral or dissatisfied +11395,63662,Female,Loyal Customer,58,Business travel,Eco,2405,3,1,1,1,3,4,3,3,3,3,3,1,3,2,32,13.0,neutral or dissatisfied +11396,6169,Male,Loyal Customer,67,Personal Travel,Eco,491,4,4,4,5,2,4,1,2,4,3,5,1,4,2,23,13.0,neutral or dissatisfied +11397,104230,Female,Loyal Customer,34,Personal Travel,Eco,680,2,4,2,4,3,2,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +11398,108916,Female,disloyal Customer,25,Business travel,Eco,666,3,3,3,4,5,3,4,5,1,4,3,1,4,5,27,18.0,neutral or dissatisfied +11399,33194,Male,Loyal Customer,44,Business travel,Eco Plus,163,4,3,4,3,5,4,5,5,1,3,1,3,3,5,0,0.0,satisfied +11400,40703,Male,Loyal Customer,53,Business travel,Eco,590,5,1,5,1,5,5,5,5,1,5,5,4,5,5,36,26.0,satisfied +11401,5648,Female,Loyal Customer,47,Personal Travel,Business,196,2,3,2,4,2,4,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +11402,90805,Male,Loyal Customer,53,Business travel,Business,581,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +11403,111181,Female,Loyal Customer,51,Business travel,Business,1506,5,5,5,5,5,4,5,5,5,5,5,5,5,5,39,59.0,satisfied +11404,80564,Male,Loyal Customer,24,Business travel,Business,1747,3,1,2,2,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +11405,26511,Female,Loyal Customer,38,Business travel,Eco Plus,829,5,3,3,3,5,5,5,5,4,1,3,3,5,5,41,36.0,satisfied +11406,63005,Male,disloyal Customer,28,Business travel,Business,862,2,3,3,5,3,1,3,4,4,5,5,3,5,3,165,155.0,neutral or dissatisfied +11407,102514,Female,Loyal Customer,15,Personal Travel,Eco,488,3,5,2,3,4,2,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +11408,61720,Female,Loyal Customer,36,Business travel,Eco,1346,2,5,5,5,2,2,2,2,4,5,3,1,2,2,11,0.0,neutral or dissatisfied +11409,1991,Male,Loyal Customer,44,Personal Travel,Eco,351,1,4,1,1,1,1,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +11410,68318,Female,disloyal Customer,27,Business travel,Business,777,5,5,5,4,3,5,3,3,3,2,3,4,5,3,0,0.0,satisfied +11411,61637,Female,Loyal Customer,44,Business travel,Business,1609,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,4.0,satisfied +11412,64786,Male,Loyal Customer,49,Business travel,Business,1947,2,4,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +11413,86478,Male,Loyal Customer,29,Personal Travel,Eco,760,2,4,2,4,4,2,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +11414,38182,Male,Loyal Customer,66,Personal Travel,Eco,1197,2,4,2,3,5,2,4,5,5,2,3,3,2,5,0,0.0,neutral or dissatisfied +11415,97378,Female,Loyal Customer,24,Personal Travel,Eco,347,3,4,3,3,2,3,2,2,5,2,5,5,4,2,14,18.0,neutral or dissatisfied +11416,99954,Male,Loyal Customer,20,Personal Travel,Eco,2237,2,2,1,4,4,1,4,4,4,3,2,2,4,4,0,0.0,neutral or dissatisfied +11417,78459,Female,Loyal Customer,43,Business travel,Business,1696,4,5,4,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +11418,92423,Male,Loyal Customer,46,Business travel,Business,1919,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11419,39007,Male,Loyal Customer,61,Business travel,Business,391,4,3,3,3,4,4,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +11420,128130,Male,Loyal Customer,14,Business travel,Business,1587,5,5,5,5,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +11421,82379,Female,Loyal Customer,51,Business travel,Business,500,3,3,3,3,4,5,4,3,3,4,3,4,3,5,24,12.0,satisfied +11422,81959,Male,Loyal Customer,48,Business travel,Business,1535,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +11423,48998,Male,disloyal Customer,21,Business travel,Eco,109,2,0,1,2,2,1,2,2,2,3,3,4,1,2,12,8.0,neutral or dissatisfied +11424,84737,Male,Loyal Customer,51,Business travel,Business,534,5,5,5,5,5,5,5,4,4,4,4,4,4,3,2,0.0,satisfied +11425,126680,Female,Loyal Customer,18,Personal Travel,Business,2402,4,1,3,4,4,3,4,4,4,4,4,1,3,4,4,0.0,satisfied +11426,57360,Male,Loyal Customer,7,Personal Travel,Eco,414,2,2,2,4,4,2,4,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +11427,53555,Male,Loyal Customer,62,Personal Travel,Eco Plus,1956,3,1,3,3,3,3,4,3,1,1,2,1,3,3,4,0.0,neutral or dissatisfied +11428,31787,Female,Loyal Customer,26,Personal Travel,Eco Plus,602,3,5,3,2,3,3,3,3,5,2,5,4,5,3,6,0.0,neutral or dissatisfied +11429,35602,Male,Loyal Customer,23,Business travel,Eco Plus,669,5,2,2,2,5,5,5,5,3,4,4,5,4,5,8,1.0,satisfied +11430,19943,Female,Loyal Customer,36,Personal Travel,Eco,343,2,5,3,4,4,3,4,4,4,4,4,5,4,4,24,20.0,neutral or dissatisfied +11431,40820,Male,Loyal Customer,27,Business travel,Eco,588,3,3,2,3,3,3,3,3,4,3,4,2,4,3,42,34.0,neutral or dissatisfied +11432,125544,Female,Loyal Customer,33,Business travel,Business,226,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +11433,105470,Male,Loyal Customer,50,Business travel,Eco,495,3,3,3,3,3,3,3,3,1,2,3,1,3,3,25,13.0,neutral or dissatisfied +11434,104523,Male,Loyal Customer,45,Business travel,Business,2104,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +11435,51230,Female,Loyal Customer,56,Business travel,Eco Plus,109,5,1,3,1,2,3,1,5,5,5,5,4,5,2,31,28.0,satisfied +11436,117742,Male,Loyal Customer,54,Personal Travel,Eco,833,4,2,4,3,2,4,2,2,1,5,2,3,2,2,32,15.0,neutral or dissatisfied +11437,126078,Male,Loyal Customer,39,Business travel,Business,507,2,1,1,1,3,3,3,2,2,2,2,4,2,2,25,22.0,neutral or dissatisfied +11438,63742,Male,Loyal Customer,18,Personal Travel,Eco,1660,2,0,2,5,1,2,1,1,4,3,4,4,5,1,81,59.0,neutral or dissatisfied +11439,16724,Male,Loyal Customer,34,Business travel,Business,2610,5,5,2,5,3,2,5,4,4,4,4,2,4,2,4,0.0,satisfied +11440,5029,Male,Loyal Customer,52,Business travel,Business,2763,0,0,0,2,3,5,4,3,3,3,3,5,3,5,0,10.0,satisfied +11441,71005,Male,Loyal Customer,50,Business travel,Business,2417,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +11442,27905,Female,Loyal Customer,47,Business travel,Business,2311,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11443,14705,Male,Loyal Customer,60,Business travel,Eco,419,5,2,2,2,5,5,5,5,4,5,1,4,1,5,0,0.0,satisfied +11444,114826,Male,disloyal Customer,42,Business travel,Business,325,5,5,5,3,2,5,2,2,4,5,4,4,4,2,46,39.0,satisfied +11445,49924,Male,disloyal Customer,41,Business travel,Eco,86,2,4,2,4,1,2,5,1,2,2,4,1,4,1,0,0.0,neutral or dissatisfied +11446,125615,Male,Loyal Customer,40,Business travel,Business,2107,2,5,5,5,2,3,4,2,2,2,2,2,2,1,36,18.0,neutral or dissatisfied +11447,30466,Male,Loyal Customer,25,Business travel,Business,495,1,2,2,2,1,1,1,1,4,4,2,1,3,1,0,0.0,neutral or dissatisfied +11448,124700,Female,Loyal Customer,36,Business travel,Business,3569,3,3,3,3,1,3,3,4,4,4,4,2,4,2,0,7.0,satisfied +11449,122321,Female,Loyal Customer,52,Business travel,Business,546,4,4,2,4,2,5,5,4,4,4,4,4,4,5,0,7.0,satisfied +11450,14144,Female,Loyal Customer,30,Personal Travel,Eco,528,2,4,2,4,4,2,4,4,3,5,4,3,4,4,0,8.0,neutral or dissatisfied +11451,117019,Female,disloyal Customer,59,Business travel,Business,451,4,4,4,1,4,4,4,4,4,5,4,3,4,4,6,0.0,satisfied +11452,129758,Female,Loyal Customer,51,Business travel,Eco,447,4,4,4,4,1,2,3,4,4,4,4,5,4,4,0,0.0,satisfied +11453,109880,Female,Loyal Customer,40,Business travel,Eco,1011,3,3,3,3,3,3,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +11454,52853,Female,Loyal Customer,27,Personal Travel,Eco,1721,2,5,2,3,2,2,2,5,4,5,5,2,5,2,150,118.0,neutral or dissatisfied +11455,90352,Male,Loyal Customer,57,Business travel,Business,581,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +11456,104351,Female,Loyal Customer,45,Personal Travel,Eco,528,3,1,3,1,1,1,1,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +11457,116957,Female,Loyal Customer,48,Business travel,Eco,647,3,1,1,1,5,3,3,3,3,3,3,1,3,1,46,44.0,neutral or dissatisfied +11458,78455,Female,Loyal Customer,59,Business travel,Business,1896,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +11459,24344,Female,Loyal Customer,48,Business travel,Business,3212,4,4,5,4,2,1,4,5,5,5,5,3,5,3,0,0.0,satisfied +11460,40423,Male,Loyal Customer,53,Business travel,Business,2280,3,3,3,3,3,3,5,4,4,5,4,1,4,3,0,0.0,satisfied +11461,46459,Male,Loyal Customer,58,Business travel,Business,125,5,5,5,5,3,4,5,4,4,4,5,5,4,3,65,67.0,satisfied +11462,109096,Male,Loyal Customer,44,Personal Travel,Eco,1041,3,4,3,3,4,3,4,4,5,2,4,5,5,4,2,4.0,neutral or dissatisfied +11463,16158,Female,Loyal Customer,33,Business travel,Business,2391,3,3,3,3,3,3,3,5,5,4,5,5,5,1,0,0.0,satisfied +11464,62014,Female,Loyal Customer,39,Business travel,Business,2586,3,2,3,3,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11465,115311,Female,disloyal Customer,24,Business travel,Business,373,5,5,5,4,4,5,4,4,3,2,5,5,5,4,0,19.0,satisfied +11466,19261,Male,Loyal Customer,59,Business travel,Business,3649,5,5,5,5,4,5,3,4,4,4,4,2,4,5,0,0.0,satisfied +11467,3191,Female,Loyal Customer,50,Business travel,Eco,185,2,4,3,3,2,3,3,2,2,2,2,3,2,1,84,106.0,neutral or dissatisfied +11468,34255,Male,Loyal Customer,49,Business travel,Business,280,1,1,1,1,4,5,4,5,5,5,5,4,5,4,10,40.0,satisfied +11469,82683,Female,Loyal Customer,51,Business travel,Eco,632,3,2,2,2,4,3,2,3,3,3,3,3,3,2,14,3.0,neutral or dissatisfied +11470,69305,Female,Loyal Customer,31,Business travel,Business,1556,2,2,2,2,5,4,5,5,5,2,5,5,4,5,0,0.0,satisfied +11471,34338,Male,disloyal Customer,28,Business travel,Eco,846,1,2,2,2,2,2,1,2,1,5,1,4,5,2,0,0.0,neutral or dissatisfied +11472,21841,Male,Loyal Customer,39,Business travel,Business,3352,5,5,5,5,2,5,4,4,4,4,4,3,4,4,111,107.0,satisfied +11473,37292,Male,disloyal Customer,23,Business travel,Eco,828,2,2,2,3,3,2,5,3,4,4,4,3,5,3,42,32.0,neutral or dissatisfied +11474,112769,Female,disloyal Customer,35,Business travel,Eco,588,1,3,1,2,4,1,4,4,2,4,3,1,3,4,2,0.0,neutral or dissatisfied +11475,50330,Female,Loyal Customer,43,Business travel,Eco,308,4,3,3,3,2,2,2,4,4,4,4,5,4,1,0,11.0,satisfied +11476,93324,Male,Loyal Customer,9,Personal Travel,Eco,287,2,4,2,4,1,2,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +11477,30468,Female,Loyal Customer,15,Personal Travel,Eco,495,4,1,4,4,3,4,3,3,4,4,4,4,3,3,19,36.0,neutral or dissatisfied +11478,129055,Male,Loyal Customer,15,Personal Travel,Eco,1744,2,5,2,1,2,2,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +11479,65367,Male,Loyal Customer,40,Business travel,Business,3296,2,5,2,2,2,4,3,2,2,2,2,2,2,2,4,8.0,neutral or dissatisfied +11480,116032,Female,Loyal Customer,45,Personal Travel,Eco,417,0,4,0,2,3,2,5,4,4,0,4,3,4,4,0,0.0,satisfied +11481,102014,Female,Loyal Customer,45,Business travel,Business,2111,1,1,1,1,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +11482,103637,Male,Loyal Customer,41,Business travel,Business,2500,2,2,2,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +11483,59028,Male,Loyal Customer,49,Business travel,Business,1846,4,2,2,2,3,1,3,4,4,3,4,3,4,1,109,119.0,neutral or dissatisfied +11484,92354,Female,Loyal Customer,21,Personal Travel,Eco,2556,4,4,4,2,5,4,5,5,2,1,3,1,1,5,3,0.0,neutral or dissatisfied +11485,60805,Male,Loyal Customer,21,Business travel,Business,3298,2,5,5,5,2,2,2,2,1,3,4,2,4,2,3,3.0,neutral or dissatisfied +11486,110225,Female,Loyal Customer,40,Business travel,Business,2807,4,4,4,4,3,4,5,5,5,5,5,4,5,3,7,0.0,satisfied +11487,17854,Male,Loyal Customer,40,Business travel,Eco Plus,615,3,1,1,1,3,3,3,3,1,2,3,1,5,3,0,0.0,satisfied +11488,126652,Male,Loyal Customer,7,Personal Travel,Eco,602,2,4,2,3,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +11489,78809,Male,Loyal Customer,68,Personal Travel,Eco,432,1,5,1,2,4,1,4,4,5,2,5,5,4,4,56,45.0,neutral or dissatisfied +11490,82174,Male,Loyal Customer,71,Business travel,Eco Plus,237,3,1,1,1,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +11491,77204,Female,Loyal Customer,44,Business travel,Eco,2994,4,2,2,2,4,4,4,2,3,4,3,4,4,4,0,0.0,neutral or dissatisfied +11492,50831,Female,Loyal Customer,29,Personal Travel,Eco,209,2,3,2,4,4,2,4,4,1,4,1,4,5,4,1,0.0,neutral or dissatisfied +11493,100946,Female,Loyal Customer,52,Business travel,Business,1142,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +11494,112099,Female,disloyal Customer,48,Business travel,Eco,1062,2,2,2,3,3,2,3,3,3,4,3,1,4,3,1,0.0,neutral or dissatisfied +11495,39511,Male,Loyal Customer,35,Business travel,Business,1068,3,3,2,3,5,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +11496,47587,Male,Loyal Customer,26,Business travel,Business,1242,2,2,2,2,4,4,4,4,2,1,1,4,4,4,10,2.0,satisfied +11497,121160,Male,disloyal Customer,22,Business travel,Business,2402,4,1,4,1,2,4,2,2,3,3,3,3,5,2,0,0.0,satisfied +11498,8149,Female,Loyal Customer,24,Business travel,Business,294,3,3,3,3,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +11499,41967,Female,Loyal Customer,25,Business travel,Business,618,5,5,4,5,5,5,5,5,2,1,1,3,1,5,0,3.0,satisfied +11500,104136,Male,Loyal Customer,47,Business travel,Business,1606,5,5,5,5,2,3,2,4,4,4,4,5,4,5,0,0.0,satisfied +11501,56281,Male,Loyal Customer,39,Business travel,Business,2227,1,1,2,1,5,4,5,5,5,5,5,3,5,4,11,0.0,satisfied +11502,34405,Male,Loyal Customer,65,Business travel,Business,3197,2,4,4,4,3,3,4,2,2,2,2,4,2,1,14,5.0,neutral or dissatisfied +11503,45206,Female,Loyal Customer,48,Business travel,Eco,1081,5,5,4,5,1,1,4,5,5,5,5,2,5,2,0,0.0,satisfied +11504,113477,Male,Loyal Customer,67,Business travel,Business,3193,3,3,3,3,4,4,5,5,5,5,5,3,5,3,75,79.0,satisfied +11505,14380,Male,disloyal Customer,29,Business travel,Eco,900,2,2,2,1,1,2,1,1,4,4,4,3,1,1,0,0.0,neutral or dissatisfied +11506,17479,Male,Loyal Customer,47,Business travel,Business,352,4,4,4,4,5,4,3,5,5,5,5,2,5,5,4,0.0,satisfied +11507,569,Female,Loyal Customer,47,Business travel,Business,2947,1,1,1,1,5,4,5,4,4,4,4,5,4,3,0,14.0,satisfied +11508,19456,Male,Loyal Customer,36,Personal Travel,Eco,363,2,5,5,2,5,5,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +11509,80803,Female,Loyal Customer,54,Business travel,Business,484,1,1,1,1,3,4,5,4,4,4,4,4,4,3,16,8.0,satisfied +11510,119900,Male,Loyal Customer,40,Business travel,Business,2479,2,2,2,2,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +11511,9233,Female,Loyal Customer,59,Business travel,Business,157,0,5,0,4,4,4,4,5,5,5,3,5,5,3,0,0.0,satisfied +11512,38128,Male,disloyal Customer,21,Business travel,Business,1185,2,4,2,3,4,2,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +11513,117922,Male,disloyal Customer,23,Business travel,Eco,255,1,4,1,1,1,1,1,1,4,3,5,3,4,1,10,2.0,neutral or dissatisfied +11514,41502,Male,Loyal Customer,27,Business travel,Eco,1211,4,4,4,4,4,4,4,4,1,2,5,3,4,4,0,0.0,satisfied +11515,102897,Female,disloyal Customer,27,Business travel,Eco,1037,3,3,3,4,4,3,4,4,2,4,4,3,3,4,7,0.0,neutral or dissatisfied +11516,65384,Male,Loyal Customer,19,Personal Travel,Eco,631,2,1,2,2,4,2,4,4,1,4,2,1,3,4,0,0.0,neutral or dissatisfied +11517,6593,Female,Loyal Customer,23,Personal Travel,Eco,528,3,2,3,4,5,3,4,5,2,4,4,2,3,5,21,7.0,neutral or dissatisfied +11518,38321,Male,Loyal Customer,50,Business travel,Business,2334,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,12.0,satisfied +11519,122094,Male,Loyal Customer,67,Personal Travel,Eco,130,2,0,2,3,4,2,4,4,3,3,3,5,4,4,94,107.0,neutral or dissatisfied +11520,8383,Male,Loyal Customer,19,Personal Travel,Eco,773,3,5,3,4,5,3,5,5,3,2,4,4,3,5,0,0.0,neutral or dissatisfied +11521,80420,Male,Loyal Customer,52,Business travel,Business,2248,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +11522,84564,Male,Loyal Customer,38,Personal Travel,Eco,2556,2,1,2,2,3,2,3,3,3,2,2,1,2,3,0,0.0,neutral or dissatisfied +11523,18765,Male,Loyal Customer,43,Business travel,Business,448,3,3,3,3,2,5,4,5,5,5,5,3,5,5,130,119.0,satisfied +11524,71018,Female,Loyal Customer,55,Business travel,Business,802,4,4,4,4,4,4,5,5,5,4,5,5,5,5,70,68.0,satisfied +11525,30617,Male,disloyal Customer,38,Business travel,Eco,524,4,5,4,2,4,4,4,4,4,3,4,1,2,4,3,0.0,neutral or dissatisfied +11526,70489,Male,Loyal Customer,49,Business travel,Business,3285,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +11527,7107,Female,Loyal Customer,66,Personal Travel,Eco,177,3,2,3,2,4,2,3,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +11528,53473,Female,disloyal Customer,44,Business travel,Eco,863,1,1,1,3,5,1,5,5,2,4,3,3,3,5,45,26.0,neutral or dissatisfied +11529,56571,Male,Loyal Customer,48,Business travel,Business,1023,1,3,1,1,3,4,5,5,5,5,5,5,5,5,8,1.0,satisfied +11530,71082,Female,Loyal Customer,57,Personal Travel,Eco,802,3,4,3,1,1,4,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +11531,18892,Female,Loyal Customer,39,Business travel,Business,3133,3,3,3,3,2,5,5,3,3,4,3,1,3,3,0,0.0,satisfied +11532,82967,Male,Loyal Customer,30,Business travel,Business,3923,5,5,5,5,3,3,3,3,5,2,5,5,4,3,0,0.0,satisfied +11533,76752,Female,Loyal Customer,50,Business travel,Business,205,0,5,0,4,5,4,5,3,3,3,3,4,3,5,2,0.0,satisfied +11534,203,Female,disloyal Customer,27,Business travel,Business,290,3,3,3,4,5,3,5,5,4,5,3,4,4,5,0,0.0,neutral or dissatisfied +11535,22087,Male,Loyal Customer,41,Business travel,Business,1983,4,4,4,4,1,5,4,3,3,3,3,4,3,2,62,49.0,satisfied +11536,81446,Male,Loyal Customer,54,Business travel,Business,2632,1,1,1,1,3,4,4,2,2,2,2,3,2,5,0,4.0,satisfied +11537,24221,Male,Loyal Customer,38,Business travel,Business,1518,2,2,2,2,3,4,2,4,4,4,4,1,4,5,0,0.0,satisfied +11538,1608,Female,Loyal Customer,17,Personal Travel,Eco Plus,140,2,3,2,4,5,2,5,5,5,3,4,1,4,5,0,0.0,neutral or dissatisfied +11539,78002,Male,Loyal Customer,72,Business travel,Business,214,2,4,4,4,5,3,3,2,2,2,2,1,2,1,10,24.0,neutral or dissatisfied +11540,98420,Female,Loyal Customer,33,Business travel,Business,2176,3,3,3,3,5,5,5,4,2,5,5,5,4,5,6,24.0,satisfied +11541,52457,Female,disloyal Customer,27,Business travel,Eco Plus,237,4,4,4,2,5,4,5,5,2,3,2,1,5,5,0,0.0,neutral or dissatisfied +11542,89428,Male,Loyal Customer,52,Personal Travel,Eco,134,5,4,5,4,5,5,5,5,4,2,3,2,3,5,88,89.0,satisfied +11543,69705,Female,Loyal Customer,55,Business travel,Business,1372,1,5,5,5,1,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +11544,29470,Male,Loyal Customer,42,Business travel,Business,2301,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +11545,85365,Male,Loyal Customer,57,Personal Travel,Eco Plus,874,1,2,1,4,1,1,1,1,1,1,3,2,4,1,11,15.0,neutral or dissatisfied +11546,97073,Female,Loyal Customer,47,Business travel,Business,1619,3,3,3,3,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +11547,51041,Female,Loyal Customer,27,Personal Travel,Eco,337,2,4,2,4,5,2,5,5,3,5,4,3,4,5,4,0.0,neutral or dissatisfied +11548,17931,Male,Loyal Customer,68,Business travel,Eco Plus,389,3,2,2,2,3,3,3,3,2,2,3,3,3,3,0,10.0,neutral or dissatisfied +11549,117041,Female,Loyal Customer,49,Business travel,Business,368,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +11550,60613,Female,Loyal Customer,22,Personal Travel,Eco,991,2,5,2,1,5,2,5,5,4,3,5,5,4,5,1,0.0,neutral or dissatisfied +11551,127078,Male,disloyal Customer,35,Business travel,Eco,647,3,2,3,4,5,3,5,5,1,2,4,2,4,5,3,0.0,neutral or dissatisfied +11552,56005,Male,Loyal Customer,53,Business travel,Business,2586,4,4,4,4,5,4,4,3,3,5,4,4,3,4,0,0.0,satisfied +11553,122745,Male,disloyal Customer,16,Business travel,Eco,651,5,5,5,4,2,5,2,2,4,3,3,3,5,2,3,0.0,satisfied +11554,52472,Female,Loyal Customer,63,Personal Travel,Eco Plus,370,4,4,4,3,4,4,5,3,3,4,3,4,3,5,0,15.0,satisfied +11555,120106,Female,Loyal Customer,29,Business travel,Business,1576,5,5,5,5,5,5,5,5,5,4,5,3,5,5,20,13.0,satisfied +11556,36208,Female,Loyal Customer,28,Business travel,Business,3202,4,4,4,4,4,4,4,4,4,2,2,3,1,4,0,0.0,satisfied +11557,17799,Female,disloyal Customer,22,Business travel,Eco,1214,3,3,3,4,4,3,2,4,1,5,3,4,4,4,14,2.0,neutral or dissatisfied +11558,105367,Female,Loyal Customer,50,Business travel,Business,369,3,3,3,3,3,5,4,4,4,4,4,4,4,5,4,0.0,satisfied +11559,83205,Female,Loyal Customer,69,Personal Travel,Eco,1123,2,5,2,1,2,4,4,1,1,2,1,4,1,4,1,0.0,neutral or dissatisfied +11560,27834,Female,Loyal Customer,13,Personal Travel,Eco,1533,2,4,2,5,3,2,5,3,3,4,3,3,5,3,10,3.0,neutral or dissatisfied +11561,8167,Female,Loyal Customer,23,Business travel,Business,3472,1,4,4,4,1,2,1,1,2,1,3,3,4,1,0,0.0,neutral or dissatisfied +11562,3490,Male,disloyal Customer,26,Business travel,Business,990,3,3,3,4,5,3,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +11563,105589,Male,Loyal Customer,45,Personal Travel,Eco,577,2,4,2,5,2,2,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +11564,105048,Female,Loyal Customer,33,Personal Travel,Eco,255,3,0,3,1,5,3,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +11565,23701,Female,Loyal Customer,53,Business travel,Business,212,5,5,5,5,2,3,1,4,4,4,3,4,4,1,0,0.0,satisfied +11566,31728,Male,Loyal Customer,52,Personal Travel,Eco,853,3,4,3,1,5,3,5,5,4,5,4,4,5,5,0,2.0,neutral or dissatisfied +11567,5962,Female,Loyal Customer,32,Business travel,Eco Plus,1250,2,2,4,2,2,2,2,1,4,3,4,2,4,2,105,155.0,neutral or dissatisfied +11568,42817,Male,Loyal Customer,28,Personal Travel,Eco,677,3,3,3,4,5,3,1,5,4,1,3,3,3,5,3,7.0,neutral or dissatisfied +11569,115956,Male,Loyal Customer,59,Personal Travel,Eco,325,2,3,2,3,3,2,3,3,3,4,4,5,2,3,0,0.0,neutral or dissatisfied +11570,124780,Female,Loyal Customer,53,Business travel,Business,3055,3,3,4,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +11571,116701,Female,Loyal Customer,44,Business travel,Business,342,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +11572,55681,Male,Loyal Customer,58,Business travel,Business,3445,1,1,1,1,5,4,5,5,5,5,5,3,5,3,9,5.0,satisfied +11573,31789,Female,Loyal Customer,46,Business travel,Eco,2640,4,3,3,3,4,4,4,2,4,5,1,4,3,4,0,23.0,satisfied +11574,96441,Female,Loyal Customer,40,Business travel,Business,436,4,4,4,4,4,4,4,5,5,5,5,3,5,3,4,1.0,satisfied +11575,86304,Male,Loyal Customer,60,Business travel,Business,331,3,3,3,3,2,5,5,4,4,4,4,4,4,3,46,51.0,satisfied +11576,41281,Female,disloyal Customer,24,Business travel,Business,812,0,0,0,2,2,0,4,2,5,5,3,4,1,2,0,0.0,satisfied +11577,39565,Male,Loyal Customer,35,Business travel,Business,3454,4,4,4,4,2,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +11578,65524,Female,Loyal Customer,17,Business travel,Business,1616,1,1,1,1,5,5,5,5,2,2,3,2,3,5,0,0.0,satisfied +11579,72092,Male,Loyal Customer,13,Personal Travel,Eco,2486,4,1,4,3,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +11580,95353,Female,Loyal Customer,28,Personal Travel,Eco,441,5,5,5,3,2,5,2,2,3,2,1,1,4,2,2,1.0,satisfied +11581,88777,Female,disloyal Customer,39,Business travel,Business,271,2,2,2,4,2,2,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +11582,109439,Female,Loyal Customer,36,Business travel,Business,1788,2,2,2,2,4,4,5,2,2,2,2,3,2,5,34,7.0,satisfied +11583,90104,Female,Loyal Customer,42,Business travel,Eco,1084,3,2,2,2,1,3,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +11584,19773,Male,Loyal Customer,15,Personal Travel,Business,578,2,4,2,5,3,2,3,3,3,2,4,4,4,3,64,107.0,neutral or dissatisfied +11585,95829,Male,Loyal Customer,19,Personal Travel,Eco,1428,4,1,4,3,3,4,3,3,2,2,2,4,3,3,10,0.0,satisfied +11586,117575,Male,Loyal Customer,36,Business travel,Business,2958,4,5,5,5,5,4,4,4,4,4,4,2,4,2,22,15.0,neutral or dissatisfied +11587,82904,Female,Loyal Customer,70,Personal Travel,Eco,645,4,5,4,2,1,1,4,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +11588,44872,Female,disloyal Customer,36,Business travel,Eco,315,4,4,4,3,4,4,4,2,1,3,4,4,4,4,215,223.0,neutral or dissatisfied +11589,16859,Female,Loyal Customer,46,Business travel,Business,708,4,4,4,4,1,4,3,5,5,5,5,4,5,1,0,0.0,satisfied +11590,11033,Female,disloyal Customer,41,Business travel,Business,267,5,5,5,3,4,5,4,4,5,4,4,2,1,4,0,0.0,satisfied +11591,54917,Female,disloyal Customer,29,Business travel,Eco Plus,862,3,3,3,3,1,3,3,1,4,2,1,5,1,1,0,0.0,neutral or dissatisfied +11592,2943,Female,Loyal Customer,60,Business travel,Business,737,3,3,1,3,4,4,4,4,4,4,4,5,4,5,0,10.0,satisfied +11593,81400,Female,Loyal Customer,52,Personal Travel,Eco,748,4,4,4,3,2,4,3,5,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +11594,59540,Female,Loyal Customer,49,Business travel,Eco,964,4,1,1,1,3,4,3,3,3,4,3,3,3,3,4,14.0,neutral or dissatisfied +11595,28361,Male,Loyal Customer,57,Personal Travel,Eco Plus,867,1,3,1,3,4,1,4,4,3,4,5,5,3,4,0,0.0,neutral or dissatisfied +11596,15120,Male,Loyal Customer,44,Business travel,Eco,1042,5,2,2,2,5,5,5,5,1,5,3,4,5,5,0,0.0,satisfied +11597,8361,Female,disloyal Customer,32,Business travel,Business,674,3,3,3,3,4,3,1,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +11598,1002,Female,disloyal Customer,45,Business travel,Eco,158,3,0,3,5,3,3,1,3,1,4,3,5,1,3,0,0.0,neutral or dissatisfied +11599,35903,Female,disloyal Customer,23,Business travel,Eco Plus,937,1,2,1,3,1,1,1,1,2,1,4,4,4,1,0,0.0,neutral or dissatisfied +11600,41004,Male,Loyal Customer,23,Personal Travel,Eco,1362,3,5,3,4,2,3,2,2,5,4,5,5,4,2,0,4.0,neutral or dissatisfied +11601,23100,Male,Loyal Customer,45,Business travel,Business,2163,3,3,3,3,1,3,4,3,3,3,3,1,3,2,5,23.0,neutral or dissatisfied +11602,106053,Male,Loyal Customer,12,Personal Travel,Eco,452,2,4,5,2,3,5,3,3,5,5,2,4,3,3,21,24.0,neutral or dissatisfied +11603,93651,Male,Loyal Customer,40,Personal Travel,Eco,547,2,5,2,1,3,2,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +11604,50512,Male,Loyal Customer,9,Personal Travel,Eco,262,2,2,0,4,5,0,5,5,4,3,3,4,3,5,124,128.0,neutral or dissatisfied +11605,122329,Male,Loyal Customer,30,Business travel,Eco Plus,546,3,2,2,2,3,3,3,3,3,5,2,3,2,3,0,0.0,neutral or dissatisfied +11606,50630,Female,Loyal Customer,43,Personal Travel,Eco,86,1,4,1,2,2,5,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +11607,82353,Female,disloyal Customer,62,Business travel,Business,201,4,4,4,3,1,4,1,1,4,5,4,3,5,1,0,0.0,satisfied +11608,25623,Female,Loyal Customer,33,Business travel,Business,2890,1,1,1,1,1,2,2,5,5,5,5,2,5,2,0,0.0,satisfied +11609,82118,Female,Loyal Customer,44,Personal Travel,Eco,1276,2,3,2,2,4,1,3,5,5,2,5,1,5,4,0,0.0,neutral or dissatisfied +11610,3530,Male,Loyal Customer,22,Business travel,Business,557,1,5,5,5,1,1,1,1,3,5,4,4,4,1,73,68.0,neutral or dissatisfied +11611,102467,Female,Loyal Customer,44,Personal Travel,Eco,226,2,2,2,4,1,4,3,4,4,2,4,4,4,4,3,0.0,neutral or dissatisfied +11612,122372,Female,disloyal Customer,45,Business travel,Business,529,5,5,5,2,1,5,1,1,3,3,5,5,4,1,0,0.0,satisfied +11613,53539,Female,Loyal Customer,17,Personal Travel,Eco Plus,2253,1,5,1,3,4,1,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +11614,58770,Female,Loyal Customer,34,Business travel,Business,1012,4,4,4,4,3,4,5,4,4,4,4,5,4,3,7,0.0,satisfied +11615,124087,Male,Loyal Customer,68,Personal Travel,Business,529,2,5,2,4,3,1,1,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +11616,25419,Female,disloyal Customer,8,Business travel,Eco Plus,990,3,2,3,4,5,3,5,5,2,3,4,4,3,5,5,0.0,neutral or dissatisfied +11617,40656,Male,Loyal Customer,33,Business travel,Business,590,5,5,5,5,5,5,5,5,4,5,5,3,4,5,1,12.0,satisfied +11618,52925,Male,disloyal Customer,22,Business travel,Eco,679,1,1,1,4,4,1,4,4,3,5,4,2,4,4,38,34.0,neutral or dissatisfied +11619,56862,Male,disloyal Customer,39,Business travel,Business,2454,2,2,2,3,2,3,5,3,4,4,5,5,5,5,6,31.0,neutral or dissatisfied +11620,107890,Female,Loyal Customer,40,Business travel,Business,861,5,5,5,5,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +11621,84248,Male,Loyal Customer,77,Business travel,Business,3883,4,4,4,4,4,1,4,3,3,3,3,1,3,4,0,0.0,satisfied +11622,89194,Female,Loyal Customer,14,Personal Travel,Eco,1947,4,4,5,3,4,5,4,4,3,4,4,4,4,4,1,12.0,neutral or dissatisfied +11623,113584,Female,Loyal Customer,58,Business travel,Business,197,1,2,2,2,5,4,4,2,2,2,1,1,2,4,35,25.0,neutral or dissatisfied +11624,123312,Male,disloyal Customer,18,Business travel,Business,507,4,4,4,3,5,4,5,5,4,4,5,5,4,5,0,0.0,satisfied +11625,129064,Male,Loyal Customer,13,Personal Travel,Eco,1846,2,4,2,3,2,2,1,2,1,4,5,1,1,2,4,0.0,neutral or dissatisfied +11626,57069,Female,Loyal Customer,28,Business travel,Business,2065,2,4,4,4,2,2,2,2,3,1,3,3,2,2,1,0.0,neutral or dissatisfied +11627,4092,Female,Loyal Customer,42,Business travel,Business,431,1,1,1,1,5,4,5,4,4,4,4,3,4,4,102,116.0,satisfied +11628,21332,Female,Loyal Customer,43,Business travel,Eco,674,5,5,5,5,2,5,3,5,5,5,5,2,5,2,0,0.0,satisfied +11629,102002,Female,Loyal Customer,38,Business travel,Business,628,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,15.0,satisfied +11630,33731,Female,Loyal Customer,65,Personal Travel,Eco,759,3,4,3,4,1,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +11631,7249,Female,Loyal Customer,43,Personal Travel,Eco,135,5,0,0,3,5,5,4,4,4,0,4,4,4,5,0,0.0,satisfied +11632,16209,Female,Loyal Customer,53,Personal Travel,Eco,212,3,1,0,2,5,3,3,5,5,0,5,4,5,1,0,0.0,neutral or dissatisfied +11633,49289,Male,Loyal Customer,35,Business travel,Business,308,4,4,4,4,1,3,2,4,4,5,4,4,4,1,0,0.0,satisfied +11634,11477,Female,Loyal Customer,16,Business travel,Eco Plus,201,5,2,2,2,5,5,4,5,4,3,4,5,2,5,0,0.0,satisfied +11635,93058,Female,Loyal Customer,45,Business travel,Business,297,0,0,0,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +11636,104172,Female,disloyal Customer,40,Business travel,Business,349,2,2,2,3,3,2,3,3,4,5,4,1,3,3,32,31.0,neutral or dissatisfied +11637,65780,Female,disloyal Customer,35,Business travel,Business,1389,2,3,3,3,2,3,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +11638,126204,Female,Loyal Customer,49,Business travel,Business,650,4,4,4,4,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +11639,84416,Male,Loyal Customer,27,Personal Travel,Eco,591,4,4,4,4,2,4,2,2,3,5,4,5,4,2,0,0.0,satisfied +11640,118467,Female,Loyal Customer,48,Business travel,Business,621,5,5,5,5,4,5,5,5,5,5,5,5,5,4,12,1.0,satisfied +11641,129139,Male,disloyal Customer,42,Business travel,Eco,679,3,3,3,3,3,3,3,3,1,3,3,2,3,3,12,21.0,neutral or dissatisfied +11642,13646,Female,Loyal Customer,45,Business travel,Business,196,4,4,4,4,2,3,5,5,5,5,5,1,5,5,0,0.0,satisfied +11643,14777,Male,Loyal Customer,31,Business travel,Business,3521,2,2,2,2,4,4,4,4,5,3,3,3,1,4,111,118.0,satisfied +11644,34625,Female,Loyal Customer,24,Business travel,Business,2177,2,2,2,2,5,5,5,5,4,2,4,5,4,5,0,0.0,satisfied +11645,23010,Female,Loyal Customer,20,Personal Travel,Eco,817,1,5,1,4,1,1,1,1,1,4,4,3,5,1,0,6.0,neutral or dissatisfied +11646,34374,Female,disloyal Customer,25,Business travel,Business,612,4,5,5,4,4,5,4,4,3,5,5,5,5,4,3,0.0,neutral or dissatisfied +11647,19776,Male,disloyal Customer,45,Business travel,Eco,578,3,0,3,4,2,3,2,2,5,4,1,5,2,2,37,32.0,neutral or dissatisfied +11648,74695,Female,Loyal Customer,34,Personal Travel,Eco,1464,1,4,2,2,3,2,3,3,4,2,3,4,5,3,0,0.0,neutral or dissatisfied +11649,41637,Male,Loyal Customer,41,Business travel,Business,3743,5,5,5,5,5,5,5,3,3,4,3,4,3,3,1,1.0,satisfied +11650,113684,Male,Loyal Customer,64,Personal Travel,Eco,386,3,4,3,4,4,3,4,4,3,3,4,5,4,4,81,79.0,neutral or dissatisfied +11651,41501,Male,Loyal Customer,30,Business travel,Business,1504,2,2,2,2,4,4,4,4,1,1,1,2,2,4,0,0.0,satisfied +11652,43204,Female,disloyal Customer,38,Business travel,Eco,466,4,1,4,4,2,4,2,2,1,4,4,1,4,2,36,27.0,neutral or dissatisfied +11653,62596,Female,Loyal Customer,45,Business travel,Business,346,1,1,1,1,2,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +11654,26346,Male,Loyal Customer,24,Business travel,Eco Plus,873,5,5,5,5,5,5,4,5,2,3,5,1,4,5,0,0.0,satisfied +11655,27715,Female,disloyal Customer,23,Business travel,Eco,1064,3,3,3,3,1,3,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +11656,42145,Female,disloyal Customer,30,Business travel,Business,846,2,2,2,3,3,2,3,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +11657,121535,Male,Loyal Customer,49,Business travel,Business,2240,4,4,4,4,2,5,4,2,2,2,2,4,2,4,0,2.0,satisfied +11658,63765,Female,Loyal Customer,32,Personal Travel,Business,1721,1,3,1,4,3,1,2,3,1,1,4,2,4,3,17,15.0,neutral or dissatisfied +11659,63311,Male,Loyal Customer,16,Business travel,Business,4000,4,5,5,5,4,4,4,4,4,1,4,3,4,4,19,29.0,neutral or dissatisfied +11660,33635,Female,Loyal Customer,43,Personal Travel,Eco,399,2,5,2,5,1,4,1,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +11661,128317,Male,Loyal Customer,54,Business travel,Business,325,0,0,0,1,3,4,4,2,2,2,3,4,2,4,0,0.0,satisfied +11662,114603,Male,Loyal Customer,48,Business travel,Business,1593,1,1,1,1,2,4,4,4,4,4,4,3,4,5,10,1.0,satisfied +11663,27197,Female,Loyal Customer,38,Business travel,Business,2516,1,1,1,1,2,2,3,4,4,4,4,4,4,1,1,0.0,satisfied +11664,1666,Male,Loyal Customer,23,Personal Travel,Eco,551,3,3,3,4,2,3,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +11665,70198,Female,Loyal Customer,32,Business travel,Business,3244,4,3,3,3,4,4,4,3,2,4,3,4,1,4,189,199.0,neutral or dissatisfied +11666,17409,Male,Loyal Customer,24,Business travel,Business,2581,1,1,1,1,4,4,4,4,1,3,5,1,1,4,0,0.0,satisfied +11667,61945,Female,Loyal Customer,64,Business travel,Business,2161,1,3,3,3,1,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +11668,70522,Female,Loyal Customer,39,Business travel,Eco Plus,467,3,1,1,1,3,3,3,3,1,4,5,2,3,3,0,0.0,satisfied +11669,62130,Female,Loyal Customer,27,Business travel,Business,2434,2,4,4,4,2,2,2,2,2,2,4,3,4,2,0,14.0,neutral or dissatisfied +11670,83608,Male,disloyal Customer,47,Business travel,Business,409,4,4,4,3,4,4,4,4,3,2,5,5,5,4,9,0.0,satisfied +11671,82756,Female,disloyal Customer,38,Business travel,Eco,409,4,3,4,4,4,4,4,4,2,4,4,3,3,4,38,27.0,neutral or dissatisfied +11672,93164,Female,Loyal Customer,59,Personal Travel,Eco,1243,3,5,3,2,3,4,4,4,4,3,4,4,4,4,0,18.0,neutral or dissatisfied +11673,119496,Male,Loyal Customer,29,Business travel,Business,814,3,3,3,3,4,4,4,4,4,2,5,4,4,4,9,6.0,satisfied +11674,492,Male,Loyal Customer,57,Business travel,Business,2884,1,1,1,1,3,5,4,4,4,4,4,3,4,4,3,21.0,satisfied +11675,56361,Male,Loyal Customer,54,Personal Travel,Eco,200,2,3,2,3,5,2,2,5,5,3,4,5,5,5,8,5.0,neutral or dissatisfied +11676,45342,Female,Loyal Customer,24,Personal Travel,Eco,222,4,0,4,5,4,4,4,4,4,5,4,4,4,4,55,47.0,satisfied +11677,11462,Female,Loyal Customer,50,Business travel,Business,166,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +11678,36947,Female,Loyal Customer,28,Personal Travel,Eco,718,1,5,1,2,1,1,1,1,3,3,1,5,3,1,0,0.0,neutral or dissatisfied +11679,71117,Female,disloyal Customer,40,Business travel,Business,278,1,1,1,2,4,1,4,4,4,4,1,4,2,4,0,0.0,neutral or dissatisfied +11680,125946,Male,Loyal Customer,55,Personal Travel,Eco,861,3,4,3,4,3,3,4,3,3,2,5,5,5,3,3,0.0,neutral or dissatisfied +11681,30980,Female,Loyal Customer,23,Business travel,Eco,1533,3,2,2,2,3,4,2,3,2,1,3,3,3,3,0,2.0,neutral or dissatisfied +11682,98043,Male,disloyal Customer,30,Business travel,Business,1797,0,0,0,3,4,0,5,4,4,3,5,5,4,4,4,17.0,satisfied +11683,19236,Male,Loyal Customer,23,Business travel,Business,2667,3,4,4,4,3,3,3,3,4,4,4,4,4,3,3,0.0,neutral or dissatisfied +11684,70985,Female,Loyal Customer,42,Business travel,Business,2822,2,2,2,2,2,5,5,2,2,2,2,5,2,3,0,8.0,satisfied +11685,107607,Male,disloyal Customer,23,Business travel,Eco,423,2,0,2,1,2,2,4,2,4,2,5,5,5,2,3,20.0,neutral or dissatisfied +11686,61878,Female,disloyal Customer,42,Business travel,Eco,928,2,2,2,3,1,2,1,1,3,3,4,4,3,1,10,0.0,neutral or dissatisfied +11687,65148,Male,disloyal Customer,51,Personal Travel,Eco,469,3,3,3,3,4,3,4,4,5,3,1,5,5,4,0,0.0,neutral or dissatisfied +11688,81661,Male,disloyal Customer,42,Business travel,Business,907,2,2,2,4,4,2,4,4,4,3,5,4,4,4,2,0.0,neutral or dissatisfied +11689,35646,Male,Loyal Customer,38,Business travel,Business,2475,5,5,2,5,4,4,4,4,1,5,5,4,4,4,10,0.0,satisfied +11690,70750,Female,Loyal Customer,50,Business travel,Business,733,5,5,5,5,2,4,4,5,5,5,5,5,5,3,12,29.0,satisfied +11691,6255,Male,Loyal Customer,10,Personal Travel,Eco,413,2,4,2,3,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +11692,118710,Female,Loyal Customer,57,Personal Travel,Eco,338,4,5,4,2,1,3,3,5,5,4,5,4,5,5,0,0.0,satisfied +11693,92741,Female,Loyal Customer,39,Business travel,Business,876,4,4,1,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11694,77397,Male,Loyal Customer,10,Personal Travel,Eco,584,4,4,4,1,1,4,1,1,5,3,4,5,4,1,18,12.0,neutral or dissatisfied +11695,23916,Male,Loyal Customer,16,Personal Travel,Eco,589,3,5,3,4,4,3,4,4,3,5,4,3,5,4,19,12.0,neutral or dissatisfied +11696,51927,Female,Loyal Customer,8,Personal Travel,Eco Plus,507,1,4,1,3,4,1,1,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +11697,101667,Male,disloyal Customer,19,Business travel,Eco,2106,3,3,3,3,2,3,2,2,2,1,4,4,3,2,13,43.0,neutral or dissatisfied +11698,114351,Male,Loyal Customer,37,Personal Travel,Eco,967,2,4,2,3,2,2,5,2,1,5,3,3,3,2,28,13.0,neutral or dissatisfied +11699,28438,Female,Loyal Customer,54,Business travel,Eco,2496,5,5,5,5,5,5,5,5,5,5,5,5,3,5,44,75.0,satisfied +11700,61466,Female,Loyal Customer,59,Business travel,Business,2253,2,2,2,2,3,5,5,3,3,4,3,5,3,4,67,54.0,satisfied +11701,119442,Male,Loyal Customer,60,Business travel,Eco Plus,399,4,5,5,5,4,4,4,4,2,4,4,2,4,4,4,39.0,neutral or dissatisfied +11702,88661,Male,Loyal Customer,47,Personal Travel,Eco,270,2,0,2,4,2,3,3,5,5,4,4,3,5,3,162,150.0,neutral or dissatisfied +11703,65371,Male,Loyal Customer,27,Business travel,Business,3437,3,3,3,3,3,3,3,3,4,1,4,1,4,3,12,13.0,neutral or dissatisfied +11704,76650,Female,Loyal Customer,39,Personal Travel,Eco,481,4,3,4,4,3,4,3,3,1,1,4,2,3,3,4,16.0,satisfied +11705,84505,Female,Loyal Customer,54,Business travel,Business,2504,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11706,68270,Male,Loyal Customer,65,Personal Travel,Eco,631,3,3,3,2,4,3,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +11707,68259,Male,Loyal Customer,22,Personal Travel,Eco,631,1,4,1,5,3,1,5,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +11708,39266,Female,disloyal Customer,21,Business travel,Eco,173,1,4,1,3,3,1,3,3,4,4,4,3,3,3,91,97.0,neutral or dissatisfied +11709,19483,Female,Loyal Customer,58,Personal Travel,Eco,177,2,5,2,3,1,4,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +11710,11397,Female,Loyal Customer,55,Business travel,Eco Plus,316,2,1,1,1,2,4,3,2,2,2,2,3,2,2,0,2.0,neutral or dissatisfied +11711,13711,Female,Loyal Customer,39,Business travel,Business,3199,4,4,4,4,4,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +11712,41877,Female,Loyal Customer,29,Business travel,Business,760,4,4,4,4,4,4,4,4,1,2,3,2,2,4,0,21.0,satisfied +11713,61974,Male,Loyal Customer,50,Business travel,Business,2586,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +11714,87023,Male,disloyal Customer,27,Business travel,Business,594,1,0,0,2,1,0,5,1,3,3,2,1,1,1,0,16.0,neutral or dissatisfied +11715,25128,Male,Loyal Customer,34,Business travel,Business,3860,5,5,5,5,1,4,1,2,2,2,2,2,2,1,0,6.0,satisfied +11716,106105,Male,disloyal Customer,20,Business travel,Eco,302,3,2,3,2,5,3,5,5,4,5,2,4,3,5,0,0.0,neutral or dissatisfied +11717,111395,Male,Loyal Customer,9,Personal Travel,Eco,1111,5,3,5,3,2,5,2,2,1,5,3,1,3,2,0,0.0,satisfied +11718,51839,Male,Loyal Customer,69,Personal Travel,Eco Plus,370,1,1,3,3,1,3,1,1,3,2,2,3,3,1,59,59.0,neutral or dissatisfied +11719,55546,Female,disloyal Customer,37,Business travel,Eco,150,3,1,3,3,4,3,4,4,1,3,3,1,4,4,4,0.0,neutral or dissatisfied +11720,27723,Female,disloyal Customer,24,Business travel,Eco,1252,2,2,2,2,1,2,1,1,1,4,4,3,5,1,0,0.0,neutral or dissatisfied +11721,70894,Female,Loyal Customer,57,Business travel,Business,1721,3,3,3,3,3,5,4,2,2,2,2,3,2,3,1,0.0,satisfied +11722,45922,Female,disloyal Customer,19,Business travel,Eco,809,2,2,2,1,5,2,5,5,5,1,1,2,2,5,65,46.0,neutral or dissatisfied +11723,120857,Male,Loyal Customer,51,Business travel,Business,3979,3,3,3,3,4,4,4,5,5,5,5,4,5,5,42,56.0,satisfied +11724,107894,Male,Loyal Customer,23,Business travel,Business,861,2,2,2,2,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +11725,16071,Female,Loyal Customer,39,Business travel,Eco,344,5,2,2,2,5,5,5,5,5,3,3,3,2,5,0,0.0,satisfied +11726,48716,Female,disloyal Customer,38,Business travel,Business,134,1,0,0,4,1,0,1,1,3,3,4,2,3,1,0,17.0,neutral or dissatisfied +11727,120924,Male,Loyal Customer,36,Business travel,Eco,951,4,5,5,5,4,4,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +11728,28197,Female,Loyal Customer,22,Personal Travel,Eco,859,4,4,3,4,5,3,5,5,3,3,4,3,4,5,0,2.0,neutral or dissatisfied +11729,23225,Male,Loyal Customer,37,Business travel,Business,3774,4,4,4,4,3,5,2,5,5,5,5,5,5,3,0,0.0,satisfied +11730,99915,Female,Loyal Customer,61,Personal Travel,Eco,1428,2,1,1,2,5,2,3,4,4,1,1,4,4,4,0,3.0,neutral or dissatisfied +11731,40105,Female,disloyal Customer,39,Business travel,Business,368,2,2,2,3,5,2,5,5,5,4,4,5,3,5,18,14.0,satisfied +11732,38004,Female,disloyal Customer,25,Business travel,Eco,1185,2,1,1,2,5,1,1,5,3,2,4,1,1,5,24,8.0,neutral or dissatisfied +11733,107847,Male,Loyal Customer,34,Personal Travel,Eco Plus,349,1,1,1,4,1,1,1,1,3,1,4,2,4,1,25,12.0,neutral or dissatisfied +11734,10793,Female,disloyal Customer,34,Business travel,Eco,247,3,0,2,4,2,2,5,2,4,3,4,3,3,2,0,0.0,neutral or dissatisfied +11735,89295,Female,disloyal Customer,24,Business travel,Eco,453,1,3,1,3,3,1,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +11736,97866,Female,Loyal Customer,50,Business travel,Business,684,3,3,3,3,2,4,5,5,5,5,5,3,5,4,15,18.0,satisfied +11737,101322,Male,Loyal Customer,67,Personal Travel,Eco,986,2,5,2,4,1,2,1,1,3,5,5,4,5,1,31,24.0,neutral or dissatisfied +11738,107839,Female,Loyal Customer,15,Personal Travel,Eco,349,2,3,2,3,1,2,1,1,2,3,3,4,4,1,24,22.0,neutral or dissatisfied +11739,108730,Male,Loyal Customer,12,Personal Travel,Eco,591,1,2,1,4,3,1,3,3,4,4,2,1,3,3,47,39.0,neutral or dissatisfied +11740,83150,Male,Loyal Customer,55,Personal Travel,Eco,983,3,4,3,1,1,3,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +11741,65087,Female,Loyal Customer,12,Personal Travel,Eco,190,3,3,0,3,5,0,5,5,4,3,3,2,4,5,0,0.0,neutral or dissatisfied +11742,25757,Female,disloyal Customer,20,Business travel,Eco,356,0,0,0,3,2,0,2,2,1,1,3,1,5,2,0,0.0,satisfied +11743,90423,Female,disloyal Customer,44,Business travel,Business,240,4,3,3,5,1,4,1,1,5,3,4,3,4,1,0,0.0,satisfied +11744,16828,Female,Loyal Customer,18,Personal Travel,Eco,645,2,4,2,3,3,2,3,3,1,5,4,3,4,3,0,7.0,neutral or dissatisfied +11745,120122,Male,Loyal Customer,59,Personal Travel,Eco,1576,2,4,2,3,2,2,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +11746,91509,Male,Loyal Customer,32,Business travel,Business,1620,2,2,2,2,5,5,5,5,3,5,5,4,5,5,15,47.0,satisfied +11747,84326,Male,Loyal Customer,46,Business travel,Business,2389,5,5,5,5,5,4,4,4,4,4,4,3,4,3,0,5.0,satisfied +11748,109367,Male,Loyal Customer,54,Business travel,Business,1189,5,5,5,5,3,5,4,4,4,4,4,3,4,4,8,1.0,satisfied +11749,53975,Male,Loyal Customer,52,Personal Travel,Eco,1117,3,4,3,4,5,3,5,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +11750,122341,Female,Loyal Customer,37,Business travel,Business,1688,3,1,1,1,5,3,3,3,3,3,3,4,3,2,3,8.0,neutral or dissatisfied +11751,52358,Male,Loyal Customer,50,Personal Travel,Eco,451,4,2,4,3,3,4,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +11752,47358,Female,Loyal Customer,36,Business travel,Business,532,3,3,3,3,2,1,2,4,4,4,4,4,4,1,0,0.0,satisfied +11753,71088,Male,Loyal Customer,21,Personal Travel,Eco,802,2,5,2,4,4,2,1,4,5,5,4,3,5,4,1,5.0,neutral or dissatisfied +11754,128956,Female,Loyal Customer,52,Business travel,Eco,414,2,4,4,4,5,4,3,2,2,2,2,3,2,1,95,106.0,neutral or dissatisfied +11755,5554,Female,Loyal Customer,47,Business travel,Business,3745,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +11756,277,Male,Loyal Customer,40,Business travel,Business,402,3,3,3,3,5,3,3,5,5,5,5,2,5,5,0,0.0,satisfied +11757,42382,Male,Loyal Customer,40,Personal Travel,Eco,748,1,4,1,5,3,1,3,3,5,5,5,3,5,3,0,5.0,neutral or dissatisfied +11758,90765,Female,disloyal Customer,25,Business travel,Eco,515,2,4,2,3,5,2,5,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +11759,58366,Female,disloyal Customer,25,Business travel,Business,646,5,0,5,3,3,5,3,3,5,2,4,3,5,3,41,65.0,satisfied +11760,97620,Male,Loyal Customer,35,Business travel,Eco,764,2,3,3,3,2,2,2,2,4,4,2,1,3,2,0,0.0,neutral or dissatisfied +11761,1792,Female,Loyal Customer,48,Business travel,Business,3103,4,4,4,4,4,4,5,4,4,4,4,5,4,4,14,15.0,satisfied +11762,109949,Male,Loyal Customer,33,Personal Travel,Eco,1052,2,5,2,4,1,2,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +11763,83157,Female,disloyal Customer,22,Business travel,Business,1084,4,0,5,2,5,5,5,5,5,2,4,3,5,5,0,0.0,satisfied +11764,22157,Female,Loyal Customer,51,Business travel,Eco,773,5,2,2,2,3,3,3,5,5,5,5,5,5,4,0,3.0,satisfied +11765,104947,Female,Loyal Customer,7,Personal Travel,Eco,1180,1,5,1,1,4,1,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +11766,34355,Female,disloyal Customer,26,Business travel,Eco,541,2,1,2,4,4,2,3,4,1,3,4,4,3,4,0,0.0,neutral or dissatisfied +11767,112900,Male,disloyal Customer,22,Business travel,Business,1313,4,0,4,5,1,4,1,1,4,2,5,3,5,1,0,0.0,satisfied +11768,12931,Male,Loyal Customer,16,Personal Travel,Eco,359,3,3,3,3,4,3,4,4,1,2,3,3,4,4,0,0.0,neutral or dissatisfied +11769,127393,Female,Loyal Customer,55,Business travel,Business,1009,4,4,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +11770,10860,Male,disloyal Customer,27,Business travel,Eco,667,2,3,2,2,5,2,5,5,4,5,2,3,3,5,0,0.0,neutral or dissatisfied +11771,1660,Male,disloyal Customer,38,Business travel,Eco,151,3,4,4,3,2,4,2,2,4,4,4,3,4,2,0,13.0,neutral or dissatisfied +11772,122816,Female,Loyal Customer,53,Personal Travel,Eco,599,3,4,3,2,2,3,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +11773,38510,Female,disloyal Customer,20,Business travel,Eco,2475,4,4,4,2,3,4,3,3,5,2,4,1,1,3,0,0.0,neutral or dissatisfied +11774,19242,Female,Loyal Customer,9,Personal Travel,Eco,782,0,4,0,2,4,0,4,4,3,3,5,5,4,4,0,1.0,satisfied +11775,89539,Male,Loyal Customer,57,Business travel,Business,944,1,1,3,1,3,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +11776,38078,Male,disloyal Customer,20,Business travel,Eco,1091,3,3,3,1,3,3,3,3,2,1,3,4,2,3,0,0.0,satisfied +11777,12437,Female,Loyal Customer,35,Personal Travel,Eco,305,1,3,1,3,1,1,1,1,5,1,5,4,4,1,5,0.0,neutral or dissatisfied +11778,12736,Female,Loyal Customer,15,Personal Travel,Eco,689,2,5,2,4,4,2,2,4,3,5,5,4,4,4,5,0.0,neutral or dissatisfied +11779,122972,Female,disloyal Customer,20,Business travel,Business,507,4,0,4,3,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +11780,22948,Male,disloyal Customer,35,Business travel,Eco,489,2,0,1,3,3,1,1,3,5,1,5,4,3,3,34,29.0,neutral or dissatisfied +11781,93240,Male,Loyal Customer,31,Personal Travel,Business,689,2,5,2,1,1,2,1,1,1,1,1,5,1,1,3,0.0,neutral or dissatisfied +11782,90497,Female,Loyal Customer,40,Business travel,Business,581,5,5,5,5,2,2,2,3,2,5,4,2,4,2,211,213.0,satisfied +11783,26698,Male,Loyal Customer,25,Personal Travel,Eco,515,1,5,1,3,4,1,4,4,5,4,4,5,5,4,76,61.0,neutral or dissatisfied +11784,70192,Female,Loyal Customer,49,Business travel,Business,2504,2,5,2,2,3,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +11785,109779,Female,Loyal Customer,60,Personal Travel,Business,1011,2,3,2,3,2,3,4,4,4,2,4,4,4,2,14,0.0,neutral or dissatisfied +11786,39125,Male,disloyal Customer,44,Business travel,Business,228,3,3,3,4,3,3,3,3,2,2,4,4,3,3,0,3.0,neutral or dissatisfied +11787,109829,Male,Loyal Customer,55,Business travel,Eco,1079,4,1,1,1,4,4,4,4,1,5,3,4,3,4,10,0.0,neutral or dissatisfied +11788,58705,Male,Loyal Customer,52,Business travel,Business,4243,2,2,2,2,4,4,4,5,2,5,4,4,3,4,52,46.0,satisfied +11789,19930,Female,Loyal Customer,70,Personal Travel,Eco,296,2,5,2,1,5,5,5,3,3,2,3,4,3,5,1,13.0,neutral or dissatisfied +11790,124138,Female,Loyal Customer,60,Personal Travel,Eco,529,2,5,2,3,3,1,4,1,1,2,1,5,1,2,0,0.0,neutral or dissatisfied +11791,5994,Female,Loyal Customer,49,Business travel,Business,925,5,5,5,5,5,5,4,4,4,4,4,3,4,4,28,20.0,satisfied +11792,56965,Male,Loyal Customer,33,Business travel,Business,2565,4,2,2,2,4,4,4,3,1,3,3,4,4,4,7,0.0,neutral or dissatisfied +11793,93110,Male,Loyal Customer,30,Business travel,Business,903,3,2,3,3,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +11794,91731,Male,Loyal Customer,28,Business travel,Business,1896,5,5,5,5,4,4,4,4,3,3,5,5,5,4,7,2.0,satisfied +11795,2561,Female,Loyal Customer,33,Business travel,Business,2924,2,1,4,1,3,1,2,2,2,2,2,2,2,1,24,27.0,neutral or dissatisfied +11796,18059,Male,Loyal Customer,40,Business travel,Eco,488,2,4,4,4,2,2,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +11797,112186,Male,Loyal Customer,28,Personal Travel,Eco,895,3,5,3,5,2,3,3,2,4,4,4,5,4,2,3,0.0,neutral or dissatisfied +11798,121175,Male,Loyal Customer,39,Personal Travel,Eco,2370,0,4,0,1,2,0,2,2,4,2,4,3,5,2,32,18.0,satisfied +11799,124373,Female,disloyal Customer,20,Business travel,Eco,575,0,0,0,5,3,0,5,3,3,5,4,4,5,3,0,0.0,satisfied +11800,32018,Male,Loyal Customer,42,Business travel,Business,101,0,3,0,1,3,4,5,3,3,3,3,2,3,1,11,17.0,satisfied +11801,4478,Male,Loyal Customer,42,Personal Travel,Business,1147,2,5,2,1,3,3,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +11802,36113,Female,Loyal Customer,17,Business travel,Business,1698,4,4,4,4,4,4,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +11803,81106,Female,Loyal Customer,57,Business travel,Business,1846,2,2,2,2,3,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +11804,27176,Male,Loyal Customer,7,Personal Travel,Eco,2688,3,3,3,3,3,4,4,3,2,4,4,4,3,4,0,23.0,neutral or dissatisfied +11805,11274,Female,Loyal Customer,7,Personal Travel,Eco,158,3,5,3,3,4,3,4,4,5,2,4,4,5,4,3,10.0,neutral or dissatisfied +11806,126240,Male,disloyal Customer,23,Business travel,Eco,507,4,0,4,1,3,4,1,3,4,5,5,2,5,3,0,0.0,satisfied +11807,49216,Female,disloyal Customer,38,Business travel,Eco,86,1,0,1,2,3,1,3,3,5,2,1,4,3,3,1,6.0,neutral or dissatisfied +11808,87073,Female,disloyal Customer,45,Business travel,Eco,594,3,4,4,4,1,4,1,1,2,3,3,1,4,1,57,56.0,neutral or dissatisfied +11809,82408,Female,Loyal Customer,70,Personal Travel,Eco Plus,500,1,5,1,1,1,1,3,1,1,1,2,1,1,4,32,14.0,neutral or dissatisfied +11810,10207,Female,Loyal Customer,51,Business travel,Business,2965,5,5,5,5,3,5,4,4,4,4,5,3,4,3,109,104.0,satisfied +11811,73062,Male,Loyal Customer,10,Personal Travel,Eco Plus,1096,3,4,2,4,1,2,1,1,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +11812,59531,Female,disloyal Customer,30,Business travel,Business,956,3,3,3,3,4,3,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +11813,26948,Male,Loyal Customer,61,Personal Travel,Eco,2402,4,5,4,2,5,4,5,5,5,4,3,3,4,5,1,0.0,neutral or dissatisfied +11814,94031,Male,Loyal Customer,43,Business travel,Business,3205,3,3,3,3,2,4,5,5,5,5,5,3,5,5,13,6.0,satisfied +11815,97498,Male,Loyal Customer,8,Personal Travel,Eco,822,2,1,2,4,1,2,1,1,3,2,3,4,3,1,1,10.0,neutral or dissatisfied +11816,42316,Male,Loyal Customer,40,Personal Travel,Eco,329,1,5,1,3,2,1,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +11817,31142,Female,Loyal Customer,67,Business travel,Eco Plus,991,3,4,4,4,3,2,2,3,3,3,3,2,3,4,27,45.0,neutral or dissatisfied +11818,10323,Male,Loyal Customer,60,Business travel,Business,2355,0,0,0,3,3,4,5,1,1,1,1,4,1,4,29,38.0,satisfied +11819,129262,Male,Loyal Customer,28,Personal Travel,Eco Plus,1504,2,4,2,4,2,2,2,2,5,3,1,1,2,2,0,0.0,neutral or dissatisfied +11820,5828,Male,Loyal Customer,39,Personal Travel,Eco,177,2,5,0,1,3,0,1,3,4,3,4,5,5,3,0,15.0,neutral or dissatisfied +11821,83238,Male,Loyal Customer,54,Business travel,Business,1979,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +11822,12633,Male,Loyal Customer,31,Business travel,Business,3748,3,2,2,2,3,3,3,3,1,4,2,4,2,3,14,12.0,neutral or dissatisfied +11823,85106,Female,disloyal Customer,28,Business travel,Business,874,5,5,5,5,3,5,3,3,4,4,5,5,5,3,1,0.0,satisfied +11824,16783,Female,Loyal Customer,51,Personal Travel,Eco,642,2,5,2,2,3,5,5,5,5,2,5,3,5,3,0,7.0,neutral or dissatisfied +11825,55658,Female,Loyal Customer,66,Personal Travel,Eco,315,3,5,3,4,4,5,4,3,3,3,3,3,3,5,27,23.0,neutral or dissatisfied +11826,2633,Male,Loyal Customer,46,Personal Travel,Eco Plus,280,1,1,1,4,1,1,1,1,4,3,4,4,4,1,20,22.0,neutral or dissatisfied +11827,11295,Female,Loyal Customer,38,Personal Travel,Eco,517,1,4,4,2,1,4,1,1,5,2,4,4,4,1,42,38.0,neutral or dissatisfied +11828,54537,Female,Loyal Customer,12,Personal Travel,Eco,925,4,1,3,3,4,3,4,4,2,3,4,1,3,4,2,0.0,neutral or dissatisfied +11829,69164,Male,Loyal Customer,45,Business travel,Business,2415,2,2,2,2,5,5,5,5,5,5,4,4,5,5,6,0.0,satisfied +11830,72319,Male,Loyal Customer,48,Business travel,Business,1905,1,1,1,1,3,5,5,4,4,4,4,4,4,4,65,55.0,satisfied +11831,65953,Female,Loyal Customer,41,Business travel,Business,1372,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11832,83706,Female,Loyal Customer,42,Personal Travel,Eco,577,2,2,2,4,1,3,4,3,3,2,3,3,3,4,20,15.0,neutral or dissatisfied +11833,120808,Female,Loyal Customer,53,Business travel,Business,2101,4,4,4,4,3,4,5,4,4,5,4,4,4,4,2,0.0,satisfied +11834,90230,Male,Loyal Customer,36,Business travel,Eco Plus,557,4,4,4,4,4,4,4,4,3,5,3,4,4,4,59,70.0,neutral or dissatisfied +11835,63020,Male,Loyal Customer,29,Business travel,Eco,967,1,4,3,3,1,1,1,1,3,1,3,3,3,1,76,63.0,neutral or dissatisfied +11836,20825,Male,Loyal Customer,39,Business travel,Eco,515,2,4,4,4,2,2,2,2,2,4,4,2,1,2,6,0.0,satisfied +11837,127930,Female,Loyal Customer,56,Business travel,Business,2300,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +11838,94403,Male,disloyal Customer,35,Business travel,Business,677,3,3,3,4,2,3,2,2,5,3,5,3,4,2,71,72.0,neutral or dissatisfied +11839,125331,Female,Loyal Customer,56,Business travel,Business,2872,1,1,5,1,3,4,4,5,5,5,5,4,5,4,44,43.0,satisfied +11840,13922,Female,Loyal Customer,53,Business travel,Business,3294,4,4,4,4,4,2,2,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +11841,95898,Male,Loyal Customer,7,Personal Travel,Eco,759,2,4,2,3,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +11842,128090,Female,Loyal Customer,39,Personal Travel,Eco,2845,5,4,5,2,5,4,4,3,4,3,4,4,5,4,3,0.0,satisfied +11843,21917,Male,disloyal Customer,28,Business travel,Eco,503,2,4,2,3,2,2,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +11844,93234,Female,Loyal Customer,53,Business travel,Business,1694,3,3,5,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +11845,73929,Female,Loyal Customer,56,Business travel,Business,2342,2,2,3,2,5,4,5,4,4,4,4,3,4,3,9,0.0,satisfied +11846,102028,Male,Loyal Customer,43,Business travel,Business,2878,2,2,2,2,4,4,4,5,5,5,5,4,5,3,28,23.0,satisfied +11847,100918,Female,Loyal Customer,47,Personal Travel,Eco Plus,377,5,4,5,5,2,5,4,2,2,5,2,3,2,5,0,0.0,satisfied +11848,16165,Female,Loyal Customer,37,Business travel,Business,199,3,2,2,2,2,4,3,3,3,3,3,4,3,2,2,0.0,neutral or dissatisfied +11849,81523,Female,Loyal Customer,47,Business travel,Business,1124,2,2,2,2,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +11850,113259,Male,Loyal Customer,45,Business travel,Business,414,2,2,3,2,3,5,5,4,4,5,4,3,4,5,5,0.0,satisfied +11851,126037,Female,Loyal Customer,46,Business travel,Business,631,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +11852,70052,Male,Loyal Customer,29,Personal Travel,Eco,583,5,5,5,2,2,5,2,2,3,5,4,3,4,2,0,0.0,satisfied +11853,56004,Male,disloyal Customer,24,Business travel,Eco,1334,2,2,2,3,2,3,3,5,3,5,4,3,3,3,40,19.0,neutral or dissatisfied +11854,18426,Female,disloyal Customer,24,Business travel,Eco,127,3,0,3,1,4,3,1,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +11855,108356,Female,Loyal Customer,65,Business travel,Eco,344,3,2,4,2,5,4,4,3,3,3,3,4,3,1,29,45.0,neutral or dissatisfied +11856,2994,Female,Loyal Customer,49,Business travel,Eco,862,2,2,2,2,1,3,4,2,2,2,2,2,2,3,0,21.0,neutral or dissatisfied +11857,56841,Male,Loyal Customer,68,Personal Travel,Eco Plus,1605,2,5,2,4,1,2,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +11858,128888,Female,disloyal Customer,26,Business travel,Eco,2454,2,2,2,3,2,5,5,1,2,3,3,5,4,5,0,0.0,neutral or dissatisfied +11859,117455,Male,Loyal Customer,25,Personal Travel,Eco,1020,1,0,1,1,1,1,5,1,5,4,5,3,4,1,0,13.0,neutral or dissatisfied +11860,64042,Male,Loyal Customer,55,Business travel,Business,3569,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +11861,40076,Female,Loyal Customer,38,Business travel,Eco,493,5,2,2,2,5,5,5,5,3,5,5,4,4,5,0,0.0,satisfied +11862,70525,Male,disloyal Customer,44,Business travel,Business,1258,3,3,3,5,3,3,3,3,5,2,5,3,5,3,30,48.0,neutral or dissatisfied +11863,32444,Male,disloyal Customer,21,Business travel,Eco,121,2,0,2,2,5,2,1,5,5,1,5,3,2,5,0,0.0,neutral or dissatisfied +11864,116316,Male,Loyal Customer,17,Personal Travel,Eco,342,3,1,3,2,3,3,3,3,2,3,2,1,1,3,12,4.0,neutral or dissatisfied +11865,51988,Male,Loyal Customer,15,Personal Travel,Eco Plus,347,4,4,4,3,3,4,3,3,3,5,5,3,5,3,7,1.0,satisfied +11866,59069,Female,disloyal Customer,29,Business travel,Eco,1482,4,4,4,3,4,4,1,4,3,3,2,1,4,4,0,0.0,neutral or dissatisfied +11867,28637,Female,disloyal Customer,10,Business travel,Eco,2417,2,2,2,3,4,2,4,4,3,4,5,4,4,4,0,0.0,satisfied +11868,38957,Female,disloyal Customer,22,Business travel,Eco,1265,2,2,2,3,4,2,4,4,3,2,4,1,3,4,69,60.0,neutral or dissatisfied +11869,38398,Male,disloyal Customer,25,Business travel,Eco,1422,3,3,3,2,4,3,4,4,2,1,3,1,2,4,0,40.0,neutral or dissatisfied +11870,67770,Female,Loyal Customer,60,Business travel,Business,1126,1,1,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +11871,101570,Male,Loyal Customer,14,Personal Travel,Eco Plus,345,2,2,2,2,1,2,1,1,2,2,3,2,2,1,19,19.0,neutral or dissatisfied +11872,60286,Female,Loyal Customer,37,Business travel,Business,1516,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +11873,93681,Female,Loyal Customer,7,Personal Travel,Eco Plus,667,2,4,2,3,1,2,4,1,4,2,3,1,4,1,26,26.0,neutral or dissatisfied +11874,105148,Female,Loyal Customer,32,Business travel,Business,281,2,4,4,4,2,2,2,2,3,4,3,3,3,2,8,3.0,neutral or dissatisfied +11875,31957,Female,Loyal Customer,42,Business travel,Business,1777,0,5,0,1,2,4,4,5,5,1,1,3,5,3,0,2.0,satisfied +11876,8689,Male,disloyal Customer,29,Business travel,Business,280,2,2,2,2,3,2,4,3,4,4,2,1,2,3,0,4.0,neutral or dissatisfied +11877,72061,Female,Loyal Customer,37,Business travel,Eco,2556,3,5,5,5,3,3,3,3,1,5,4,1,4,3,44,24.0,neutral or dissatisfied +11878,57500,Female,disloyal Customer,29,Business travel,Business,1075,0,0,0,3,3,0,3,3,5,5,4,3,4,3,0,0.0,satisfied +11879,57628,Female,disloyal Customer,24,Business travel,Eco,200,2,3,2,4,4,2,4,4,4,2,4,3,4,4,57,57.0,neutral or dissatisfied +11880,62498,Male,Loyal Customer,16,Business travel,Business,1781,3,3,3,3,5,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +11881,3120,Male,disloyal Customer,27,Business travel,Eco,613,2,1,2,4,1,2,1,1,2,1,4,1,4,1,18,5.0,neutral or dissatisfied +11882,29498,Female,Loyal Customer,51,Business travel,Eco,707,3,5,5,5,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +11883,100146,Male,Loyal Customer,22,Business travel,Business,2878,3,5,5,5,3,3,3,3,3,2,3,4,2,3,11,23.0,neutral or dissatisfied +11884,59010,Male,disloyal Customer,34,Business travel,Eco,1193,2,1,1,3,3,2,3,3,1,1,2,4,4,3,50,30.0,neutral or dissatisfied +11885,3100,Male,Loyal Customer,48,Personal Travel,Eco,594,4,3,4,3,3,4,1,3,2,1,3,1,5,3,0,26.0,neutral or dissatisfied +11886,72070,Male,disloyal Customer,39,Business travel,Business,2486,1,1,1,2,4,1,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +11887,7933,Female,Loyal Customer,41,Business travel,Business,3194,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +11888,4603,Female,Loyal Customer,17,Personal Travel,Eco Plus,416,1,3,1,1,5,1,5,5,4,3,1,5,5,5,105,108.0,neutral or dissatisfied +11889,82281,Female,Loyal Customer,41,Personal Travel,Eco,1481,1,5,1,5,2,1,2,2,3,3,3,5,4,2,19,0.0,neutral or dissatisfied +11890,49686,Male,disloyal Customer,26,Business travel,Eco,134,1,0,1,4,4,1,2,4,4,4,4,3,1,4,0,2.0,neutral or dissatisfied +11891,22045,Male,Loyal Customer,49,Business travel,Business,1923,4,4,4,4,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +11892,105802,Male,Loyal Customer,7,Personal Travel,Eco,883,3,2,3,4,5,3,5,5,3,5,3,3,4,5,125,107.0,neutral or dissatisfied +11893,12711,Male,disloyal Customer,22,Business travel,Eco,803,4,4,4,3,1,4,1,1,1,5,4,4,3,1,0,0.0,neutral or dissatisfied +11894,129775,Male,Loyal Customer,12,Personal Travel,Eco,447,2,4,3,2,3,3,3,3,5,5,4,5,5,3,80,105.0,neutral or dissatisfied +11895,57958,Male,Loyal Customer,29,Business travel,Business,1911,3,3,3,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +11896,19958,Female,disloyal Customer,15,Business travel,Eco,315,2,0,2,5,3,2,3,3,4,3,1,2,2,3,11,5.0,neutral or dissatisfied +11897,28200,Male,Loyal Customer,57,Personal Travel,Eco,834,2,5,2,2,5,2,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +11898,15180,Female,Loyal Customer,32,Personal Travel,Eco,416,2,5,2,3,5,2,5,5,5,1,3,4,5,5,0,0.0,neutral or dissatisfied +11899,111765,Male,Loyal Customer,52,Business travel,Eco Plus,1436,2,4,4,4,2,2,2,2,2,4,3,4,3,2,12,0.0,neutral or dissatisfied +11900,32674,Male,Loyal Customer,58,Business travel,Eco,102,3,4,3,4,3,3,3,3,1,5,2,3,2,3,1,0.0,neutral or dissatisfied +11901,51530,Male,Loyal Customer,48,Business travel,Business,451,5,5,5,5,5,5,5,5,5,5,3,5,1,5,154,154.0,satisfied +11902,80451,Male,Loyal Customer,30,Personal Travel,Business,1299,4,4,4,1,5,4,5,5,5,2,4,4,5,5,0,17.0,neutral or dissatisfied +11903,98662,Male,Loyal Customer,33,Personal Travel,Eco,834,1,5,1,1,4,1,4,4,3,5,5,4,4,4,0,6.0,neutral or dissatisfied +11904,18537,Male,Loyal Customer,47,Business travel,Eco,253,4,5,4,4,4,4,4,4,3,2,1,2,2,4,0,0.0,satisfied +11905,41965,Female,Loyal Customer,59,Business travel,Business,575,2,2,2,2,5,1,3,5,5,4,5,1,5,4,0,0.0,satisfied +11906,24066,Male,disloyal Customer,27,Business travel,Eco Plus,562,0,0,0,1,5,0,3,5,5,3,4,3,1,5,0,0.0,satisfied +11907,69945,Female,disloyal Customer,18,Business travel,Business,2174,5,5,5,5,5,5,4,5,3,3,4,3,5,5,0,0.0,satisfied +11908,101955,Female,Loyal Customer,23,Business travel,Business,628,2,1,3,1,2,2,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +11909,21610,Female,Loyal Customer,53,Business travel,Business,2218,3,2,2,2,2,2,2,3,3,3,3,4,3,4,43,32.0,neutral or dissatisfied +11910,89983,Female,Loyal Customer,38,Business travel,Eco Plus,1487,1,1,1,1,1,1,1,1,2,3,4,2,3,1,37,83.0,neutral or dissatisfied +11911,40450,Male,Loyal Customer,51,Business travel,Business,3033,5,5,5,5,2,3,4,4,4,4,3,1,4,4,0,0.0,satisfied +11912,125193,Male,Loyal Customer,48,Business travel,Business,651,5,5,3,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +11913,92633,Male,Loyal Customer,46,Business travel,Business,2643,3,3,3,3,2,4,4,3,3,3,3,5,3,3,0,3.0,satisfied +11914,26355,Male,Loyal Customer,34,Personal Travel,Business,828,4,2,4,3,3,4,3,4,4,4,4,3,4,1,0,3.0,neutral or dissatisfied +11915,116932,Female,disloyal Customer,26,Business travel,Business,338,1,5,1,4,2,1,4,2,4,5,5,5,4,2,18,3.0,neutral or dissatisfied +11916,9268,Male,Loyal Customer,39,Business travel,Eco,441,1,5,5,5,1,2,1,1,2,4,4,3,4,1,0,0.0,neutral or dissatisfied +11917,116007,Male,Loyal Customer,43,Personal Travel,Eco,372,1,2,1,1,5,1,5,5,3,2,3,3,5,5,0,0.0,neutral or dissatisfied +11918,14675,Female,Loyal Customer,29,Personal Travel,Eco,416,2,4,2,4,1,2,1,1,2,5,4,1,4,1,0,35.0,neutral or dissatisfied +11919,3800,Female,Loyal Customer,36,Business travel,Business,710,2,4,2,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +11920,126316,Female,Loyal Customer,41,Personal Travel,Eco,600,3,0,3,4,5,3,5,5,5,4,4,4,5,5,12,4.0,neutral or dissatisfied +11921,35066,Female,disloyal Customer,24,Business travel,Business,1076,2,2,2,2,1,2,1,1,2,2,2,2,3,1,118,96.0,neutral or dissatisfied +11922,115681,Male,Loyal Customer,52,Business travel,Business,371,4,4,1,4,2,1,2,4,4,4,4,4,4,2,46,39.0,neutral or dissatisfied +11923,107063,Male,Loyal Customer,27,Personal Travel,Eco,395,2,4,2,4,1,2,1,1,5,2,5,5,5,1,10,3.0,neutral or dissatisfied +11924,93485,Male,Loyal Customer,55,Business travel,Business,3463,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +11925,90271,Female,disloyal Customer,37,Business travel,Business,757,5,5,5,1,4,5,4,4,4,2,5,5,5,4,0,0.0,satisfied +11926,101245,Male,Loyal Customer,14,Personal Travel,Eco,1587,3,4,3,5,5,3,1,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +11927,48271,Male,Loyal Customer,38,Business travel,Eco Plus,259,5,5,5,5,5,4,5,5,1,1,4,5,2,5,0,0.0,satisfied +11928,124270,Female,disloyal Customer,28,Business travel,Business,601,3,2,2,2,1,2,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +11929,33969,Male,Loyal Customer,43,Business travel,Business,1598,4,4,4,4,5,5,3,5,5,5,5,2,5,4,0,0.0,satisfied +11930,8746,Female,Loyal Customer,52,Personal Travel,Eco Plus,280,1,5,1,4,2,4,4,5,5,1,5,3,5,3,36,103.0,neutral or dissatisfied +11931,105374,Male,Loyal Customer,51,Business travel,Business,369,1,1,1,1,3,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +11932,48188,Male,Loyal Customer,65,Business travel,Eco,259,3,3,3,3,4,3,4,4,2,3,2,3,2,4,27,13.0,neutral or dissatisfied +11933,72377,Female,disloyal Customer,27,Business travel,Business,985,2,2,2,1,2,2,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +11934,81353,Male,Loyal Customer,52,Personal Travel,Eco,1299,2,4,1,2,1,1,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +11935,48693,Female,Loyal Customer,55,Business travel,Business,2129,2,2,2,2,5,4,5,4,4,4,4,4,4,4,49,59.0,satisfied +11936,27455,Female,Loyal Customer,30,Business travel,Business,3001,4,1,4,4,4,4,4,4,2,1,3,3,3,4,0,0.0,satisfied +11937,79577,Male,Loyal Customer,58,Business travel,Business,2532,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +11938,90601,Female,Loyal Customer,52,Business travel,Business,3742,5,5,5,5,2,4,4,5,5,4,5,5,5,4,0,4.0,satisfied +11939,86806,Female,Loyal Customer,26,Business travel,Business,484,5,2,5,5,2,2,2,2,3,4,5,5,4,2,0,0.0,satisfied +11940,77863,Male,Loyal Customer,20,Personal Travel,Eco Plus,696,4,5,4,4,3,4,3,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +11941,96068,Female,Loyal Customer,42,Personal Travel,Eco,1235,1,2,1,3,5,3,3,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +11942,67129,Male,disloyal Customer,23,Business travel,Eco,1017,1,1,1,2,1,1,1,1,4,5,2,3,2,1,1,0.0,neutral or dissatisfied +11943,19251,Female,Loyal Customer,34,Business travel,Eco Plus,782,4,2,2,2,4,4,4,4,3,1,1,5,2,4,0,0.0,satisfied +11944,66853,Female,Loyal Customer,53,Personal Travel,Eco,731,1,2,1,3,2,4,4,4,4,1,4,2,4,2,73,75.0,neutral or dissatisfied +11945,46357,Male,Loyal Customer,28,Business travel,Business,1013,5,5,5,5,5,5,5,5,5,3,4,4,4,5,7,1.0,satisfied +11946,101287,Male,disloyal Customer,26,Business travel,Business,763,4,4,4,1,5,4,1,5,3,5,5,3,5,5,5,0.0,satisfied +11947,71714,Female,Loyal Customer,35,Business travel,Business,3147,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +11948,59967,Female,Loyal Customer,61,Business travel,Business,2434,4,4,4,4,4,4,4,5,5,5,5,5,5,4,7,0.0,satisfied +11949,105332,Female,Loyal Customer,45,Business travel,Business,1620,4,4,4,4,2,5,4,5,5,5,5,5,5,3,25,26.0,satisfied +11950,41010,Female,Loyal Customer,53,Personal Travel,Eco Plus,1362,4,5,4,3,4,5,5,2,2,4,5,4,2,4,0,0.0,satisfied +11951,105612,Female,Loyal Customer,47,Personal Travel,Business,925,2,5,2,2,4,4,4,5,5,2,5,3,5,4,13,0.0,neutral or dissatisfied +11952,78891,Male,Loyal Customer,45,Business travel,Business,1727,2,4,4,4,4,3,4,2,2,2,2,4,2,2,0,12.0,neutral or dissatisfied +11953,2775,Female,disloyal Customer,45,Business travel,Business,765,4,5,5,5,3,4,3,3,3,2,4,3,5,3,27,36.0,satisfied +11954,69640,Female,Loyal Customer,45,Business travel,Business,569,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,3.0,satisfied +11955,27816,Female,Loyal Customer,59,Business travel,Eco,1048,4,2,2,2,1,4,3,4,4,4,4,1,4,2,0,0.0,satisfied +11956,100537,Female,Loyal Customer,41,Personal Travel,Eco,759,2,4,2,3,5,2,5,5,3,5,5,4,5,5,35,28.0,neutral or dissatisfied +11957,44965,Female,Loyal Customer,39,Business travel,Business,1968,4,4,3,4,4,5,4,5,5,5,4,4,5,4,0,14.0,satisfied +11958,105166,Male,Loyal Customer,13,Personal Travel,Eco,289,2,5,2,3,1,2,5,1,3,4,5,3,4,1,5,0.0,neutral or dissatisfied +11959,29610,Female,Loyal Customer,32,Business travel,Business,2677,3,3,3,3,3,3,3,3,4,4,5,4,4,3,0,0.0,satisfied +11960,52213,Female,Loyal Customer,30,Business travel,Business,3377,1,3,5,3,1,1,1,1,4,1,3,2,3,1,0,0.0,neutral or dissatisfied +11961,46509,Female,Loyal Customer,32,Business travel,Eco,125,4,5,5,5,4,4,4,4,1,3,3,5,3,4,0,0.0,satisfied +11962,4996,Male,disloyal Customer,10,Business travel,Eco,502,1,2,1,3,1,1,1,1,1,1,3,2,4,1,35,44.0,neutral or dissatisfied +11963,25450,Female,Loyal Customer,35,Personal Travel,Eco,669,2,5,2,4,2,2,2,2,5,2,5,5,4,2,2,0.0,neutral or dissatisfied +11964,25737,Female,Loyal Customer,35,Personal Travel,Eco,528,4,4,4,3,1,4,3,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +11965,105158,Male,Loyal Customer,23,Business travel,Eco,289,1,3,3,3,1,1,4,1,2,3,4,4,4,1,81,81.0,neutral or dissatisfied +11966,85516,Female,disloyal Customer,22,Business travel,Eco,214,1,2,1,4,3,1,5,3,2,3,3,1,4,3,12,8.0,neutral or dissatisfied +11967,92208,Male,Loyal Customer,36,Personal Travel,Eco,1979,2,3,2,3,3,2,2,3,4,1,2,1,2,3,0,0.0,neutral or dissatisfied +11968,46487,Male,Loyal Customer,59,Business travel,Eco,125,4,5,5,5,4,4,4,4,5,4,4,4,2,4,124,127.0,satisfied +11969,108237,Male,disloyal Customer,27,Business travel,Business,895,3,3,3,4,2,3,2,2,3,5,5,3,5,2,31,22.0,neutral or dissatisfied +11970,123598,Female,Loyal Customer,15,Personal Travel,Eco,1773,3,3,3,3,3,3,3,3,5,1,4,1,2,3,3,4.0,neutral or dissatisfied +11971,49322,Female,Loyal Customer,47,Business travel,Eco,89,4,5,5,5,2,5,3,4,4,4,4,3,4,1,40,57.0,satisfied +11972,94,Male,Loyal Customer,80,Business travel,Eco Plus,108,1,4,4,4,1,1,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +11973,83174,Female,Loyal Customer,44,Business travel,Business,3620,3,3,3,3,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +11974,72686,Female,Loyal Customer,30,Personal Travel,Eco,929,4,5,4,2,3,4,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +11975,81169,Male,Loyal Customer,32,Personal Travel,Eco,196,2,4,0,3,1,0,1,1,3,3,4,3,4,1,2,3.0,neutral or dissatisfied +11976,64751,Male,Loyal Customer,41,Business travel,Business,190,3,3,3,3,4,4,5,5,5,5,4,5,5,3,0,0.0,satisfied +11977,5600,Male,Loyal Customer,48,Business travel,Business,685,2,2,2,2,4,5,4,5,5,5,5,5,5,3,0,26.0,satisfied +11978,128093,Male,Loyal Customer,56,Personal Travel,Eco,2860,3,3,4,3,4,2,2,2,1,3,2,2,4,2,0,0.0,neutral or dissatisfied +11979,117020,Female,Loyal Customer,48,Business travel,Business,369,5,5,5,5,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +11980,94626,Female,Loyal Customer,49,Business travel,Eco,187,4,5,5,5,3,3,3,3,3,4,3,3,3,2,0,9.0,neutral or dissatisfied +11981,13895,Male,Loyal Customer,20,Business travel,Eco Plus,760,1,1,1,1,1,1,2,1,1,2,2,3,2,1,0,0.0,neutral or dissatisfied +11982,43797,Male,Loyal Customer,19,Business travel,Business,3851,1,1,1,1,5,5,5,5,5,2,2,1,4,5,0,0.0,satisfied +11983,3793,Female,Loyal Customer,27,Personal Travel,Eco,599,3,3,3,3,5,3,5,5,2,5,3,2,3,5,0,1.0,neutral or dissatisfied +11984,87868,Female,disloyal Customer,44,Business travel,Business,214,5,5,5,4,3,5,3,3,3,5,5,4,4,3,0,0.0,satisfied +11985,117679,Male,Loyal Customer,41,Business travel,Business,1814,5,5,5,5,2,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +11986,13154,Female,Loyal Customer,15,Personal Travel,Eco,427,2,1,2,4,3,2,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +11987,115820,Female,Loyal Customer,50,Business travel,Business,2923,5,5,5,5,5,1,1,4,4,4,4,1,4,1,1,0.0,satisfied +11988,30599,Male,Loyal Customer,51,Business travel,Eco,472,2,4,4,4,2,2,2,2,4,5,4,4,3,2,3,23.0,satisfied +11989,54022,Male,Loyal Customer,23,Personal Travel,Eco,1091,3,4,2,3,4,2,4,4,3,1,4,2,5,4,2,0.0,neutral or dissatisfied +11990,31029,Male,Loyal Customer,47,Business travel,Business,2680,4,4,4,4,3,4,4,5,5,5,5,3,5,3,11,6.0,satisfied +11991,51679,Male,Loyal Customer,58,Business travel,Eco,509,4,1,1,1,4,4,4,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +11992,128310,Male,Loyal Customer,54,Business travel,Business,3307,5,5,5,5,5,4,5,4,4,4,4,3,4,3,95,95.0,satisfied +11993,64358,Female,disloyal Customer,24,Business travel,Eco,1192,2,2,2,4,3,2,3,3,1,3,2,3,3,3,0,3.0,neutral or dissatisfied +11994,11483,Male,Loyal Customer,33,Personal Travel,Eco Plus,166,5,4,5,4,1,5,1,1,5,2,5,3,4,1,0,0.0,satisfied +11995,41214,Male,Loyal Customer,16,Business travel,Eco,1091,3,3,3,3,3,3,2,3,1,2,4,4,3,3,15,17.0,neutral or dissatisfied +11996,23669,Female,Loyal Customer,28,Business travel,Business,3167,2,2,5,2,4,4,4,4,2,1,1,5,3,4,57,51.0,satisfied +11997,79596,Female,disloyal Customer,30,Business travel,Business,712,4,4,4,1,5,4,5,5,5,3,5,5,4,5,1,0.0,satisfied +11998,125496,Male,disloyal Customer,23,Business travel,Eco,666,5,0,4,1,4,4,4,4,5,4,5,5,4,4,3,0.0,satisfied +11999,12277,Female,disloyal Customer,25,Business travel,Eco,201,2,3,2,4,3,2,3,3,1,3,2,3,2,3,0,0.0,neutral or dissatisfied +12000,19082,Male,Loyal Customer,20,Business travel,Eco Plus,642,5,5,5,5,5,5,4,5,4,1,4,5,4,5,0,0.0,satisfied +12001,104711,Male,Loyal Customer,45,Business travel,Business,1865,5,5,5,5,3,3,5,4,4,5,4,5,4,5,14,11.0,satisfied +12002,76996,Female,Loyal Customer,59,Business travel,Business,368,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +12003,73477,Male,Loyal Customer,59,Personal Travel,Eco,1144,4,5,4,4,1,4,1,1,5,4,3,4,5,1,0,0.0,satisfied +12004,60204,Female,Loyal Customer,27,Business travel,Business,1546,1,5,1,1,5,5,5,5,5,4,4,5,5,5,25,17.0,satisfied +12005,114185,Female,Loyal Customer,35,Business travel,Business,3540,2,2,2,2,4,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +12006,96889,Female,Loyal Customer,68,Personal Travel,Eco,972,2,4,2,3,2,4,4,5,5,2,5,3,5,3,83,85.0,neutral or dissatisfied +12007,5339,Female,Loyal Customer,50,Business travel,Business,2559,5,5,5,5,5,5,4,3,3,4,3,5,3,4,2,7.0,satisfied +12008,68953,Female,Loyal Customer,48,Business travel,Business,700,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +12009,78598,Female,Loyal Customer,54,Business travel,Business,2454,1,1,1,1,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +12010,43048,Female,Loyal Customer,29,Business travel,Business,1873,2,2,4,2,5,5,4,5,1,3,1,4,5,5,7,4.0,satisfied +12011,102935,Male,Loyal Customer,31,Personal Travel,Eco,436,2,4,3,3,4,3,4,4,5,2,4,5,5,4,20,19.0,neutral or dissatisfied +12012,26800,Female,Loyal Customer,42,Business travel,Eco,2139,5,2,3,2,1,3,4,5,5,5,5,5,5,5,24,13.0,satisfied +12013,31089,Male,Loyal Customer,29,Business travel,Business,2625,4,4,4,4,5,5,5,5,1,2,5,3,4,5,35,38.0,satisfied +12014,123842,Male,Loyal Customer,52,Business travel,Business,1976,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,3.0,satisfied +12015,129832,Female,Loyal Customer,20,Personal Travel,Eco,308,2,3,2,3,4,2,4,4,4,3,4,1,3,4,0,2.0,neutral or dissatisfied +12016,68978,Female,Loyal Customer,49,Personal Travel,Eco,700,3,5,3,1,2,4,2,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +12017,51945,Female,Loyal Customer,53,Business travel,Eco,936,4,1,5,5,5,5,5,4,4,4,4,5,4,1,11,14.0,satisfied +12018,128816,Male,Loyal Customer,57,Business travel,Business,2475,1,1,3,1,4,4,5,4,4,4,4,5,4,5,1,0.0,satisfied +12019,90444,Female,Loyal Customer,27,Business travel,Business,2815,3,4,3,3,4,4,4,4,3,5,5,5,4,4,0,0.0,satisfied +12020,12263,Male,Loyal Customer,47,Business travel,Business,201,0,3,0,3,4,1,4,4,4,4,4,5,4,5,0,0.0,satisfied +12021,62491,Male,Loyal Customer,43,Business travel,Business,1744,2,2,2,2,5,5,5,4,4,5,4,3,4,3,59,52.0,satisfied +12022,22385,Female,disloyal Customer,18,Business travel,Eco,83,5,0,5,2,4,5,4,4,5,5,2,2,2,4,0,0.0,satisfied +12023,77034,Female,Loyal Customer,28,Personal Travel,Eco,422,2,3,2,4,2,2,2,2,4,3,4,1,3,2,41,33.0,neutral or dissatisfied +12024,91880,Male,Loyal Customer,11,Personal Travel,Business,2475,3,5,2,1,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +12025,26114,Male,disloyal Customer,22,Business travel,Business,515,4,3,4,4,5,4,5,5,3,4,4,5,4,5,11,0.0,satisfied +12026,582,Female,disloyal Customer,33,Business travel,Business,158,2,2,2,5,4,2,2,4,3,5,4,5,5,4,0,2.0,neutral or dissatisfied +12027,3218,Female,Loyal Customer,40,Business travel,Business,3943,5,5,5,5,2,4,5,5,5,5,5,4,5,4,26,33.0,satisfied +12028,7336,Female,Loyal Customer,46,Business travel,Business,606,3,3,3,3,3,4,5,4,4,4,4,3,4,5,13,6.0,satisfied +12029,113356,Female,Loyal Customer,49,Business travel,Business,2783,0,0,0,5,5,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +12030,26958,Male,Loyal Customer,27,Personal Travel,Business,867,2,4,2,3,4,2,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +12031,67360,Male,Loyal Customer,44,Business travel,Business,678,2,2,2,2,3,5,4,3,3,2,3,4,3,3,0,2.0,satisfied +12032,105656,Female,Loyal Customer,53,Business travel,Business,2720,2,2,2,2,2,4,4,5,5,5,5,4,5,3,13,21.0,satisfied +12033,55839,Male,disloyal Customer,36,Business travel,Eco,1016,3,3,3,2,2,3,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +12034,113415,Female,Loyal Customer,37,Business travel,Business,386,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,4.0,satisfied +12035,47182,Female,disloyal Customer,32,Business travel,Eco,679,1,1,1,2,4,1,4,4,4,4,3,4,2,4,12,7.0,neutral or dissatisfied +12036,52257,Female,Loyal Customer,21,Business travel,Business,651,2,2,2,2,2,2,2,2,1,1,3,3,4,2,12,,neutral or dissatisfied +12037,99302,Female,Loyal Customer,41,Business travel,Business,2406,5,5,5,5,3,5,5,4,4,4,4,4,4,5,5,1.0,satisfied +12038,126731,Male,disloyal Customer,24,Business travel,Eco,728,4,4,4,3,3,4,5,3,3,3,4,4,3,3,61,40.0,neutral or dissatisfied +12039,5377,Female,Loyal Customer,55,Business travel,Business,3903,2,4,4,4,4,2,1,2,2,2,2,1,2,1,0,9.0,neutral or dissatisfied +12040,120893,Female,Loyal Customer,48,Business travel,Business,3700,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +12041,41221,Female,Loyal Customer,58,Business travel,Business,2190,1,1,1,1,5,4,4,2,2,2,2,4,2,4,0,1.0,satisfied +12042,19131,Male,Loyal Customer,23,Personal Travel,Eco,265,2,3,2,1,5,2,5,5,2,1,5,5,3,5,0,0.0,neutral or dissatisfied +12043,91598,Female,disloyal Customer,15,Business travel,Eco,1352,4,4,4,2,2,4,2,2,4,3,5,3,5,2,0,0.0,satisfied +12044,102432,Female,Loyal Customer,28,Personal Travel,Eco,223,4,4,4,4,4,4,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +12045,45338,Male,disloyal Customer,80,Business travel,Eco,175,3,3,3,4,4,3,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +12046,64587,Female,Loyal Customer,43,Business travel,Business,190,2,2,2,2,2,5,5,5,5,5,4,5,5,4,5,2.0,satisfied +12047,129439,Female,disloyal Customer,72,Business travel,Eco,414,4,0,4,2,1,4,1,1,3,5,2,2,3,1,0,0.0,satisfied +12048,57728,Male,Loyal Customer,36,Business travel,Eco,1754,2,1,4,1,2,2,2,2,2,2,2,3,2,2,9,6.0,neutral or dissatisfied +12049,112678,Female,Loyal Customer,51,Business travel,Eco,605,2,5,5,5,5,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +12050,109419,Male,disloyal Customer,26,Business travel,Business,834,1,1,1,2,4,1,4,4,3,2,4,4,5,4,3,7.0,neutral or dissatisfied +12051,128518,Female,Loyal Customer,58,Personal Travel,Eco,338,3,3,3,2,1,4,5,2,2,3,2,2,2,1,28,28.0,neutral or dissatisfied +12052,33633,Male,Loyal Customer,20,Personal Travel,Eco,474,3,5,3,2,3,3,5,3,5,1,1,4,3,3,23,24.0,neutral or dissatisfied +12053,68877,Male,Loyal Customer,32,Business travel,Business,1898,3,2,2,2,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +12054,90048,Male,Loyal Customer,56,Business travel,Business,2322,1,1,1,1,4,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +12055,105405,Female,Loyal Customer,45,Personal Travel,Eco,369,3,4,1,5,4,3,5,3,3,1,3,5,3,2,0,0.0,neutral or dissatisfied +12056,41085,Female,Loyal Customer,60,Business travel,Eco,224,2,3,3,3,3,3,2,2,2,2,2,2,2,3,16,16.0,neutral or dissatisfied +12057,73001,Female,Loyal Customer,10,Personal Travel,Eco,1096,2,2,2,3,4,2,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +12058,72647,Male,Loyal Customer,14,Personal Travel,Eco,1121,2,4,2,4,2,3,3,3,3,4,2,3,1,3,198,189.0,neutral or dissatisfied +12059,81274,Female,disloyal Customer,23,Business travel,Eco,1020,2,2,2,4,4,2,4,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +12060,109674,Male,Loyal Customer,9,Personal Travel,Eco,802,1,5,1,1,5,1,5,5,1,2,4,4,2,5,16,1.0,neutral or dissatisfied +12061,11166,Female,Loyal Customer,36,Personal Travel,Eco,316,2,4,2,5,2,2,2,2,2,5,1,4,3,2,7,5.0,neutral or dissatisfied +12062,94000,Male,disloyal Customer,39,Business travel,Business,187,1,1,1,2,3,1,5,3,4,4,4,3,4,3,18,17.0,neutral or dissatisfied +12063,23364,Male,Loyal Customer,51,Business travel,Business,3383,2,1,1,1,5,4,4,2,2,2,2,3,2,2,36,27.0,neutral or dissatisfied +12064,43620,Male,Loyal Customer,17,Personal Travel,Eco,252,3,4,3,4,3,3,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +12065,68266,Male,Loyal Customer,67,Personal Travel,Eco,631,1,4,1,5,5,1,5,5,4,3,5,5,5,5,4,8.0,neutral or dissatisfied +12066,75608,Male,Loyal Customer,14,Personal Travel,Eco,337,3,4,3,3,3,3,3,3,4,5,2,2,2,3,13,0.0,neutral or dissatisfied +12067,87459,Female,disloyal Customer,46,Business travel,Eco,373,2,1,2,3,2,2,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +12068,108122,Female,Loyal Customer,45,Business travel,Business,997,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +12069,11839,Male,Loyal Customer,62,Personal Travel,Eco,986,2,4,2,4,4,2,4,4,4,2,4,3,5,4,1,0.0,neutral or dissatisfied +12070,78443,Female,disloyal Customer,32,Business travel,Business,666,2,2,2,5,4,2,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +12071,48455,Female,Loyal Customer,48,Business travel,Eco,845,5,3,3,3,2,3,2,5,5,5,5,2,5,2,10,19.0,satisfied +12072,91279,Female,Loyal Customer,31,Business travel,Business,2291,4,4,1,4,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +12073,119960,Female,Loyal Customer,45,Business travel,Eco,468,4,3,3,3,3,1,4,4,4,4,4,3,4,2,0,3.0,satisfied +12074,59024,Male,Loyal Customer,48,Business travel,Business,1846,3,3,3,3,5,3,4,5,5,5,5,5,5,5,0,19.0,satisfied +12075,81390,Male,disloyal Customer,36,Business travel,Business,748,1,1,1,5,5,1,1,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +12076,15672,Male,Loyal Customer,40,Business travel,Eco,617,4,3,3,3,4,4,4,4,4,2,2,1,5,4,0,0.0,satisfied +12077,95368,Male,Loyal Customer,68,Personal Travel,Eco,189,2,5,0,3,4,0,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +12078,50418,Female,disloyal Customer,40,Business travel,Business,78,2,2,2,3,1,2,1,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +12079,47256,Male,disloyal Customer,10,Business travel,Eco,584,3,2,3,4,2,3,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +12080,117940,Male,disloyal Customer,42,Business travel,Eco,255,3,3,3,3,5,3,5,5,3,3,4,4,3,5,0,0.0,neutral or dissatisfied +12081,6965,Female,Loyal Customer,47,Business travel,Business,234,1,1,1,1,2,5,5,4,4,4,4,4,4,4,38,34.0,satisfied +12082,114838,Female,Loyal Customer,45,Business travel,Business,373,1,1,4,1,5,5,5,4,4,4,4,4,4,5,98,105.0,satisfied +12083,76771,Male,Loyal Customer,51,Business travel,Business,3247,2,4,2,2,4,5,5,4,4,4,4,3,4,5,11,20.0,satisfied +12084,69224,Male,Loyal Customer,53,Business travel,Business,1750,5,5,4,5,2,4,4,5,5,5,5,3,5,3,56,67.0,satisfied +12085,72267,Female,Loyal Customer,62,Business travel,Business,2361,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +12086,32468,Female,disloyal Customer,59,Business travel,Eco,101,4,2,4,2,4,4,4,4,4,2,1,1,2,4,0,0.0,neutral or dissatisfied +12087,10720,Male,Loyal Customer,44,Business travel,Business,312,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +12088,8006,Female,Loyal Customer,26,Personal Travel,Business,125,3,4,3,3,2,3,2,2,4,2,1,3,5,2,0,0.0,neutral or dissatisfied +12089,15540,Female,Loyal Customer,10,Personal Travel,Eco,738,2,1,2,1,1,2,1,1,1,5,1,1,2,1,0,0.0,neutral or dissatisfied +12090,12147,Male,Loyal Customer,53,Business travel,Eco,1075,4,5,5,5,3,4,3,3,3,2,2,3,5,3,14,0.0,satisfied +12091,57937,Male,disloyal Customer,21,Business travel,Eco,837,2,2,2,3,5,2,5,5,1,4,4,4,4,5,0,0.0,neutral or dissatisfied +12092,8798,Male,Loyal Customer,49,Business travel,Eco,552,2,4,4,4,2,2,2,2,4,3,4,4,3,2,13,0.0,neutral or dissatisfied +12093,38948,Female,Loyal Customer,36,Business travel,Eco Plus,320,3,1,1,1,3,4,3,3,1,1,4,4,3,3,8,13.0,neutral or dissatisfied +12094,99828,Male,Loyal Customer,47,Business travel,Business,468,1,1,1,1,1,4,4,1,1,1,1,1,1,3,0,17.0,neutral or dissatisfied +12095,95331,Male,Loyal Customer,29,Personal Travel,Eco,239,1,5,1,3,4,1,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +12096,15227,Male,Loyal Customer,52,Business travel,Business,445,3,4,4,4,2,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +12097,128691,Male,Loyal Customer,58,Business travel,Eco Plus,942,1,2,2,2,1,1,1,2,1,3,4,1,4,1,30,15.0,neutral or dissatisfied +12098,3103,Female,Loyal Customer,34,Personal Travel,Eco,594,3,3,3,4,5,3,3,5,4,1,4,4,3,5,0,0.0,neutral or dissatisfied +12099,123349,Male,disloyal Customer,25,Business travel,Business,644,2,5,3,2,3,3,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +12100,88126,Female,Loyal Customer,47,Business travel,Business,594,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +12101,84310,Male,Loyal Customer,29,Business travel,Business,235,5,5,5,5,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +12102,2516,Male,Loyal Customer,55,Business travel,Business,181,3,3,5,3,3,5,4,5,5,5,4,5,5,5,0,9.0,satisfied +12103,24539,Female,Loyal Customer,31,Business travel,Business,2675,3,3,3,3,3,4,3,3,4,2,4,4,1,3,0,0.0,satisfied +12104,12310,Female,Loyal Customer,48,Business travel,Business,3418,3,3,5,5,3,4,3,3,3,3,3,4,3,4,0,8.0,neutral or dissatisfied +12105,81558,Female,disloyal Customer,17,Business travel,Eco,936,2,2,2,3,2,2,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +12106,53509,Male,Loyal Customer,48,Personal Travel,Eco,2419,3,4,3,5,3,2,2,3,4,4,5,2,4,2,0,26.0,neutral or dissatisfied +12107,82932,Female,disloyal Customer,24,Business travel,Business,645,4,2,3,4,1,3,1,1,4,5,4,4,4,1,0,0.0,satisfied +12108,12652,Male,disloyal Customer,45,Business travel,Eco Plus,844,3,3,3,3,2,3,2,2,1,4,4,2,1,2,4,0.0,neutral or dissatisfied +12109,12901,Female,Loyal Customer,16,Business travel,Business,359,2,3,3,3,2,2,2,2,3,5,3,4,2,2,0,0.0,neutral or dissatisfied +12110,95572,Male,Loyal Customer,59,Business travel,Business,2053,4,4,4,4,2,4,4,4,4,4,4,5,4,4,8,0.0,satisfied +12111,100409,Male,Loyal Customer,58,Business travel,Business,3266,2,2,4,2,4,5,5,5,3,5,5,5,5,5,394,383.0,satisfied +12112,71694,Female,Loyal Customer,23,Personal Travel,Eco,1120,4,5,4,2,5,4,5,5,4,3,5,5,4,5,0,0.0,satisfied +12113,80309,Male,Loyal Customer,24,Business travel,Business,1918,2,4,1,4,2,2,2,2,2,3,4,2,3,2,25,37.0,neutral or dissatisfied +12114,97174,Male,Loyal Customer,68,Personal Travel,Eco,1476,3,5,3,5,5,3,5,5,4,2,4,4,5,5,13,13.0,neutral or dissatisfied +12115,11120,Male,Loyal Customer,44,Personal Travel,Eco,308,3,4,3,4,2,3,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +12116,9232,Female,Loyal Customer,46,Business travel,Business,100,3,3,3,3,3,5,4,4,4,5,5,4,4,5,0,0.0,satisfied +12117,115454,Male,disloyal Customer,27,Business travel,Eco,446,3,2,3,3,3,4,4,3,3,2,3,4,4,4,149,139.0,neutral or dissatisfied +12118,71785,Male,Loyal Customer,59,Business travel,Business,1846,4,4,4,4,4,4,4,3,5,3,4,4,4,4,177,173.0,satisfied +12119,53534,Male,disloyal Customer,29,Business travel,Eco Plus,2358,3,3,3,3,4,3,4,4,3,5,3,4,4,4,7,0.0,neutral or dissatisfied +12120,18940,Male,Loyal Customer,27,Personal Travel,Eco,500,2,4,2,1,2,2,2,2,4,4,4,4,5,2,4,0.0,neutral or dissatisfied +12121,10411,Male,disloyal Customer,28,Business travel,Business,247,2,2,2,3,5,2,5,5,3,4,5,5,4,5,25,17.0,neutral or dissatisfied +12122,29618,Female,Loyal Customer,21,Business travel,Business,1448,3,2,3,2,3,3,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +12123,5602,Female,Loyal Customer,57,Business travel,Business,3208,2,2,2,2,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +12124,10026,Male,Loyal Customer,50,Business travel,Business,3407,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +12125,35860,Female,Loyal Customer,68,Personal Travel,Eco,1065,2,5,2,2,2,5,4,1,1,2,5,4,1,3,0,0.0,neutral or dissatisfied +12126,106402,Female,disloyal Customer,27,Business travel,Eco,674,4,4,4,3,3,4,3,3,1,4,3,2,3,3,28,26.0,neutral or dissatisfied +12127,47579,Female,Loyal Customer,69,Personal Travel,Business,1242,0,5,1,5,3,3,5,4,4,1,4,3,4,3,13,23.0,satisfied +12128,3654,Male,Loyal Customer,41,Business travel,Business,431,1,1,5,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +12129,80534,Male,Loyal Customer,29,Personal Travel,Eco,1678,1,5,1,1,3,1,3,3,2,3,2,1,2,3,33,24.0,neutral or dissatisfied +12130,81877,Male,Loyal Customer,8,Personal Travel,Business,680,5,5,5,3,3,5,3,3,4,5,4,4,5,3,0,0.0,satisfied +12131,36528,Male,Loyal Customer,22,Business travel,Business,2049,1,1,1,1,4,4,4,4,5,1,2,2,2,4,7,38.0,satisfied +12132,30650,Male,disloyal Customer,23,Business travel,Eco,133,2,2,2,3,4,2,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +12133,101572,Female,Loyal Customer,44,Business travel,Business,1099,3,3,3,3,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +12134,126572,Male,disloyal Customer,26,Business travel,Business,1158,3,3,3,3,5,3,5,5,2,5,4,2,1,5,13,5.0,neutral or dissatisfied +12135,101394,Male,disloyal Customer,36,Business travel,Eco,486,3,2,3,2,1,3,5,1,2,5,2,3,3,1,12,15.0,neutral or dissatisfied +12136,40681,Female,Loyal Customer,36,Business travel,Business,2440,5,5,5,5,3,2,5,4,4,4,4,3,4,3,0,0.0,satisfied +12137,77330,Female,Loyal Customer,46,Business travel,Business,2428,3,3,3,3,3,5,5,3,3,3,3,5,3,4,5,8.0,satisfied +12138,81190,Female,Loyal Customer,39,Personal Travel,Eco,980,2,3,2,3,2,2,2,2,2,3,4,3,3,2,6,51.0,neutral or dissatisfied +12139,18660,Female,Loyal Customer,60,Personal Travel,Eco,253,2,4,2,3,2,5,5,4,3,2,5,5,3,5,233,228.0,neutral or dissatisfied +12140,81298,Male,Loyal Customer,57,Business travel,Business,1537,4,4,4,4,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +12141,115765,Male,Loyal Customer,75,Business travel,Eco,404,4,3,5,3,4,4,4,4,1,1,2,4,3,4,48,44.0,neutral or dissatisfied +12142,73886,Female,Loyal Customer,56,Business travel,Business,2585,2,3,3,3,2,2,2,3,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +12143,98267,Male,disloyal Customer,12,Business travel,Eco,1188,5,4,4,2,5,4,1,5,5,3,4,5,4,5,0,0.0,satisfied +12144,19458,Male,Loyal Customer,35,Personal Travel,Business,84,3,2,3,3,4,4,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +12145,74004,Female,Loyal Customer,56,Personal Travel,Eco,1972,2,5,2,4,5,4,4,3,3,2,2,5,3,3,0,1.0,neutral or dissatisfied +12146,1141,Male,Loyal Customer,17,Personal Travel,Eco,309,5,5,5,2,2,5,2,2,3,4,4,1,2,2,9,1.0,satisfied +12147,124704,Male,Loyal Customer,33,Business travel,Eco,399,3,4,4,4,3,3,3,3,1,2,3,1,4,3,10,0.0,neutral or dissatisfied +12148,75223,Male,Loyal Customer,57,Business travel,Eco,1723,4,4,4,4,4,4,4,4,3,1,2,2,5,4,0,0.0,satisfied +12149,59046,Male,Loyal Customer,18,Business travel,Business,1846,4,4,4,4,4,4,4,4,3,5,4,4,3,4,64,36.0,neutral or dissatisfied +12150,53253,Female,Loyal Customer,12,Personal Travel,Eco Plus,589,4,1,4,1,4,4,4,4,2,1,1,1,1,4,0,0.0,neutral or dissatisfied +12151,116549,Female,Loyal Customer,23,Personal Travel,Eco,325,2,4,2,4,3,2,3,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +12152,98954,Female,disloyal Customer,45,Business travel,Business,479,1,1,1,4,5,1,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +12153,89024,Male,Loyal Customer,11,Personal Travel,Business,2139,1,4,0,1,2,0,2,2,3,4,4,5,5,2,21,13.0,neutral or dissatisfied +12154,95551,Female,Loyal Customer,16,Personal Travel,Eco Plus,677,2,2,2,2,4,2,4,4,3,1,1,4,2,4,9,4.0,neutral or dissatisfied +12155,115916,Female,disloyal Customer,43,Business travel,Eco,404,4,2,4,3,1,4,3,1,2,5,3,2,3,1,35,23.0,neutral or dissatisfied +12156,39307,Male,Loyal Customer,64,Personal Travel,Eco,160,1,3,1,2,5,1,5,5,2,3,3,2,2,5,29,18.0,neutral or dissatisfied +12157,34699,Male,Loyal Customer,31,Business travel,Business,3166,4,4,4,4,4,4,4,4,3,1,1,3,1,4,0,0.0,satisfied +12158,25455,Female,Loyal Customer,40,Personal Travel,Eco,669,5,4,5,5,2,5,2,2,5,3,4,5,5,2,0,0.0,satisfied +12159,42410,Female,Loyal Customer,30,Business travel,Eco Plus,834,3,5,1,5,3,3,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +12160,36346,Female,Loyal Customer,29,Personal Travel,Eco,187,1,4,1,3,4,1,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +12161,42391,Female,Loyal Customer,29,Business travel,Eco Plus,834,5,5,5,5,5,5,5,5,5,2,1,5,1,5,0,0.0,satisfied +12162,62839,Female,Loyal Customer,53,Business travel,Business,2447,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +12163,50563,Female,Loyal Customer,45,Personal Travel,Eco,209,3,1,3,3,3,3,3,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +12164,102073,Female,disloyal Customer,36,Business travel,Business,236,4,4,4,1,5,4,5,5,4,2,5,5,5,5,50,60.0,neutral or dissatisfied +12165,89789,Female,Loyal Customer,20,Personal Travel,Eco,1076,1,4,1,3,5,1,5,5,5,2,4,5,4,5,43,17.0,neutral or dissatisfied +12166,116253,Male,Loyal Customer,12,Personal Travel,Eco,446,2,5,2,5,2,2,2,2,3,4,4,4,4,2,0,2.0,neutral or dissatisfied +12167,45557,Male,disloyal Customer,54,Business travel,Eco,1304,4,3,3,4,3,4,5,3,3,3,2,2,5,3,0,0.0,neutral or dissatisfied +12168,104691,Male,Loyal Customer,51,Business travel,Business,3529,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,2.0,satisfied +12169,92508,Male,Loyal Customer,55,Personal Travel,Eco,1892,2,2,2,2,1,2,1,1,1,3,2,4,2,1,2,0.0,neutral or dissatisfied +12170,42968,Female,disloyal Customer,33,Business travel,Eco,192,3,5,3,4,4,3,3,4,5,3,3,3,4,4,64,57.0,neutral or dissatisfied +12171,16574,Male,Loyal Customer,55,Business travel,Eco,692,5,5,5,5,5,5,5,5,3,5,4,2,1,5,87,71.0,satisfied +12172,78805,Male,Loyal Customer,45,Personal Travel,Eco,447,1,4,1,3,1,1,1,1,4,3,1,4,3,1,0,0.0,neutral or dissatisfied +12173,11459,Male,Loyal Customer,39,Business travel,Business,3581,5,5,5,5,4,4,5,5,5,5,5,5,5,5,2,0.0,satisfied +12174,38811,Female,Loyal Customer,25,Personal Travel,Eco,354,2,1,2,3,5,2,5,5,1,1,3,4,4,5,57,61.0,neutral or dissatisfied +12175,124218,Female,Loyal Customer,60,Personal Travel,Eco,2176,3,5,3,1,2,4,5,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +12176,71170,Male,disloyal Customer,40,Business travel,Business,733,1,1,1,4,2,1,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +12177,75062,Male,Loyal Customer,58,Business travel,Business,2611,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +12178,24635,Male,Loyal Customer,31,Personal Travel,Eco,666,1,5,2,2,4,2,4,4,5,4,2,3,4,4,0,0.0,neutral or dissatisfied +12179,46682,Female,Loyal Customer,44,Personal Travel,Eco,152,2,4,2,2,3,5,4,2,2,2,2,3,2,5,0,3.0,neutral or dissatisfied +12180,31389,Male,Loyal Customer,36,Personal Travel,Eco,895,3,4,3,2,2,3,2,2,4,5,5,5,5,2,0,23.0,neutral or dissatisfied +12181,21688,Female,Loyal Customer,52,Business travel,Eco,708,3,1,1,1,3,3,3,1,5,4,3,3,2,3,219,214.0,neutral or dissatisfied +12182,67408,Male,Loyal Customer,46,Business travel,Eco,721,3,5,5,5,3,3,3,3,2,1,2,4,2,3,3,0.0,neutral or dissatisfied +12183,36821,Male,Loyal Customer,22,Personal Travel,Business,369,4,4,4,4,3,4,4,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +12184,322,Male,Loyal Customer,49,Business travel,Business,821,2,3,3,3,1,2,3,2,2,2,2,4,2,2,0,7.0,neutral or dissatisfied +12185,28989,Male,Loyal Customer,43,Business travel,Eco,978,2,5,5,5,3,2,3,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +12186,62674,Female,Loyal Customer,47,Business travel,Eco Plus,281,2,3,3,3,2,4,4,2,2,2,2,3,2,3,25,36.0,neutral or dissatisfied +12187,112938,Male,Loyal Customer,63,Personal Travel,Eco,1390,2,5,2,4,5,2,5,5,3,4,4,4,5,5,24,5.0,neutral or dissatisfied +12188,101924,Male,disloyal Customer,38,Business travel,Business,2297,4,4,4,2,4,4,4,4,4,2,3,3,4,4,0,0.0,satisfied +12189,58382,Female,Loyal Customer,41,Business travel,Business,733,5,5,5,5,3,5,5,3,3,3,3,4,3,4,1,0.0,satisfied +12190,24708,Female,disloyal Customer,20,Business travel,Eco,397,2,2,2,3,1,2,1,1,2,2,4,3,3,1,0,0.0,neutral or dissatisfied +12191,110071,Female,Loyal Customer,49,Business travel,Business,2695,2,3,3,3,2,2,3,2,2,2,2,4,2,4,1,0.0,neutral or dissatisfied +12192,65215,Male,Loyal Customer,48,Business travel,Business,2562,2,2,2,2,4,5,4,5,5,5,5,3,5,4,8,7.0,satisfied +12193,100834,Male,Loyal Customer,38,Business travel,Business,3223,2,5,5,5,5,3,3,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +12194,127114,Female,Loyal Customer,61,Personal Travel,Eco,304,2,2,5,3,1,3,4,5,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +12195,97932,Male,disloyal Customer,29,Business travel,Eco,684,3,2,2,2,5,2,5,5,3,5,2,1,2,5,3,0.0,neutral or dissatisfied +12196,110130,Male,Loyal Customer,26,Business travel,Business,882,3,3,3,3,3,3,3,3,1,2,4,1,3,3,6,5.0,neutral or dissatisfied +12197,44839,Female,Loyal Customer,48,Business travel,Business,760,5,5,5,5,1,4,1,5,5,5,5,3,5,1,49,56.0,satisfied +12198,56489,Female,Loyal Customer,41,Business travel,Business,3175,2,2,2,2,5,5,5,5,5,4,4,5,4,5,222,213.0,satisfied +12199,42980,Male,Loyal Customer,50,Business travel,Business,3433,5,1,5,5,3,3,1,5,5,5,3,4,5,4,45,59.0,satisfied +12200,86808,Male,disloyal Customer,34,Business travel,Business,484,4,4,4,5,1,4,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +12201,118639,Female,Loyal Customer,27,Business travel,Business,651,1,1,1,1,4,4,4,4,5,2,5,5,5,4,7,1.0,satisfied +12202,66401,Male,Loyal Customer,9,Business travel,Eco,1562,2,4,4,4,2,2,1,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +12203,14800,Male,disloyal Customer,50,Business travel,Business,214,4,4,4,3,2,4,2,2,3,2,3,5,3,2,0,4.0,satisfied +12204,99900,Female,Loyal Customer,7,Personal Travel,Eco,738,3,5,3,1,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +12205,110927,Male,Loyal Customer,42,Personal Travel,Eco,404,2,4,5,4,3,5,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +12206,67059,Male,Loyal Customer,32,Business travel,Business,2958,1,1,1,1,1,1,1,1,3,1,4,4,4,1,1,26.0,neutral or dissatisfied +12207,43777,Female,Loyal Customer,58,Personal Travel,Eco,546,3,1,3,3,3,2,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +12208,47266,Female,Loyal Customer,33,Business travel,Business,2445,5,5,5,5,5,3,1,3,3,4,3,5,3,3,1,2.0,satisfied +12209,76814,Female,Loyal Customer,32,Personal Travel,Eco,689,4,4,3,1,4,3,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +12210,21277,Male,Loyal Customer,58,Business travel,Eco,620,4,2,2,2,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +12211,115773,Female,disloyal Customer,26,Business travel,Business,333,2,4,2,4,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +12212,30855,Female,disloyal Customer,39,Business travel,Business,1506,3,2,2,3,3,2,1,3,3,3,5,4,4,3,0,2.0,neutral or dissatisfied +12213,107552,Female,disloyal Customer,35,Business travel,Eco,934,1,1,1,4,1,1,1,1,4,5,4,2,3,1,17,10.0,neutral or dissatisfied +12214,35717,Male,Loyal Customer,12,Personal Travel,Eco,2586,2,5,2,3,2,3,1,5,2,4,5,1,4,1,29,4.0,neutral or dissatisfied +12215,91979,Female,Loyal Customer,10,Personal Travel,Eco Plus,2446,4,4,4,2,2,4,2,2,4,3,4,3,5,2,0,23.0,neutral or dissatisfied +12216,400,Male,disloyal Customer,23,Business travel,Eco,134,0,0,1,1,5,1,4,5,3,4,5,3,5,5,0,0.0,satisfied +12217,59169,Male,Loyal Customer,37,Personal Travel,Eco Plus,1744,3,2,3,4,1,3,1,1,3,4,3,1,3,1,12,6.0,neutral or dissatisfied +12218,103906,Male,Loyal Customer,46,Business travel,Business,533,1,1,1,1,4,5,5,4,4,4,4,5,4,4,26,15.0,satisfied +12219,1774,Female,Loyal Customer,41,Business travel,Business,3994,1,1,1,1,3,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +12220,127834,Female,Loyal Customer,12,Personal Travel,Eco,1262,2,5,2,2,4,2,4,4,3,5,3,4,5,4,52,37.0,neutral or dissatisfied +12221,46937,Female,Loyal Customer,66,Personal Travel,Eco,737,4,5,4,3,2,2,3,3,3,4,4,3,3,1,29,22.0,satisfied +12222,17918,Female,disloyal Customer,35,Business travel,Eco,789,2,2,2,3,1,2,1,1,2,4,4,4,4,1,31,22.0,neutral or dissatisfied +12223,38545,Male,Loyal Customer,53,Business travel,Business,2475,2,2,2,2,3,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +12224,25804,Female,Loyal Customer,15,Personal Travel,Eco,762,1,4,1,3,5,1,5,5,1,4,3,4,4,5,1,0.0,neutral or dissatisfied +12225,14583,Male,Loyal Customer,46,Business travel,Business,3612,3,4,2,2,4,2,3,3,3,3,3,1,3,4,0,26.0,neutral or dissatisfied +12226,60411,Female,Loyal Customer,38,Business travel,Business,1452,2,2,2,2,3,4,5,5,5,5,5,4,5,3,41,40.0,satisfied +12227,111768,Female,Loyal Customer,59,Personal Travel,Business,1620,4,4,4,3,3,4,5,5,5,4,5,4,5,5,4,1.0,neutral or dissatisfied +12228,5130,Female,Loyal Customer,40,Personal Travel,Eco Plus,235,1,4,1,3,3,1,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +12229,89225,Female,Loyal Customer,70,Personal Travel,Eco,1919,3,4,3,3,3,5,4,2,2,3,2,4,2,5,31,29.0,neutral or dissatisfied +12230,123798,Female,Loyal Customer,49,Business travel,Business,3714,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +12231,43779,Female,Loyal Customer,18,Personal Travel,Eco,481,1,5,1,5,4,1,4,4,3,1,2,2,1,4,0,0.0,neutral or dissatisfied +12232,128685,Female,Loyal Customer,8,Personal Travel,Eco,2442,1,5,1,2,1,3,3,4,4,5,4,3,3,3,75,62.0,neutral or dissatisfied +12233,55893,Female,Loyal Customer,39,Business travel,Business,733,2,2,5,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +12234,109444,Female,disloyal Customer,26,Business travel,Business,834,4,4,4,1,2,4,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +12235,119698,Female,disloyal Customer,25,Business travel,Business,1325,3,0,3,3,5,3,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +12236,115817,Female,Loyal Customer,44,Business travel,Eco,446,2,1,1,1,1,4,1,2,2,2,2,4,2,3,43,23.0,satisfied +12237,107461,Male,Loyal Customer,41,Business travel,Business,1699,2,2,2,2,2,4,4,4,4,4,4,3,4,4,8,20.0,satisfied +12238,28221,Male,Loyal Customer,76,Business travel,Eco Plus,434,4,4,5,4,4,4,4,4,3,5,1,5,3,4,0,0.0,satisfied +12239,96520,Female,Loyal Customer,45,Personal Travel,Eco,302,1,5,1,4,4,4,5,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +12240,90045,Male,Loyal Customer,57,Business travel,Business,2529,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +12241,3472,Female,Loyal Customer,57,Business travel,Business,2554,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +12242,89388,Male,disloyal Customer,54,Business travel,Business,134,3,3,3,3,4,3,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +12243,12005,Male,Loyal Customer,63,Personal Travel,Eco Plus,643,4,5,4,3,5,4,5,5,3,5,5,3,4,5,0,0.0,satisfied +12244,91889,Female,Loyal Customer,40,Business travel,Business,2586,2,2,2,2,4,4,4,3,5,5,4,4,5,4,313,320.0,satisfied +12245,120367,Female,Loyal Customer,53,Business travel,Business,2342,4,1,4,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +12246,13774,Male,Loyal Customer,33,Business travel,Business,3791,2,2,2,2,5,5,5,5,4,1,4,2,5,5,0,0.0,satisfied +12247,127691,Female,Loyal Customer,29,Business travel,Business,2133,4,4,1,4,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +12248,73222,Male,Loyal Customer,39,Business travel,Business,946,1,1,1,1,4,3,4,1,1,1,1,1,1,4,43,28.0,neutral or dissatisfied +12249,96309,Female,Loyal Customer,68,Business travel,Eco Plus,786,1,2,2,2,2,3,4,1,1,1,1,4,1,1,11,0.0,neutral or dissatisfied +12250,82928,Female,Loyal Customer,56,Business travel,Business,3666,2,2,2,2,5,5,4,4,4,4,4,4,4,5,44,64.0,satisfied +12251,43697,Female,Loyal Customer,27,Business travel,Business,196,2,2,2,2,4,4,3,4,3,4,5,1,5,4,0,0.0,satisfied +12252,45590,Male,Loyal Customer,37,Business travel,Eco,313,5,4,4,4,5,5,5,5,1,1,4,1,5,5,0,0.0,satisfied +12253,25510,Male,Loyal Customer,29,Business travel,Business,481,1,1,3,1,5,5,5,5,5,2,4,5,2,5,0,0.0,satisfied +12254,58478,Male,Loyal Customer,60,Business travel,Business,1826,2,2,2,2,3,5,5,4,4,5,4,3,4,3,32,25.0,satisfied +12255,84690,Male,Loyal Customer,9,Personal Travel,Eco,2182,3,2,3,3,4,3,4,4,4,5,3,4,4,4,27,18.0,neutral or dissatisfied +12256,59541,Female,Loyal Customer,34,Business travel,Business,861,2,2,2,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +12257,16772,Male,disloyal Customer,22,Business travel,Eco,642,0,0,0,1,4,0,4,4,3,1,3,5,5,4,0,0.0,satisfied +12258,27487,Female,Loyal Customer,56,Business travel,Eco,671,4,4,4,4,4,3,2,4,4,4,4,3,4,4,0,7.0,neutral or dissatisfied +12259,120199,Male,Loyal Customer,32,Business travel,Business,1325,5,5,5,5,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +12260,65818,Male,Loyal Customer,44,Business travel,Business,1389,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +12261,111225,Male,Loyal Customer,20,Personal Travel,Eco,1546,1,5,1,1,3,1,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +12262,58074,Male,Loyal Customer,39,Business travel,Business,589,3,3,3,3,2,5,4,4,4,4,4,5,4,4,29,22.0,satisfied +12263,110382,Female,Loyal Customer,28,Business travel,Eco,883,3,2,2,2,3,2,3,3,2,1,4,4,4,3,17,27.0,neutral or dissatisfied +12264,480,Female,disloyal Customer,37,Business travel,Business,164,4,4,4,4,1,4,1,1,4,5,5,3,4,1,0,0.0,satisfied +12265,13846,Male,Loyal Customer,11,Personal Travel,Eco,628,3,5,3,3,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +12266,46314,Male,Loyal Customer,18,Personal Travel,Business,420,2,3,2,3,3,2,3,3,3,3,3,2,3,3,9,7.0,neutral or dissatisfied +12267,70103,Male,Loyal Customer,62,Business travel,Business,3137,3,3,3,3,3,3,3,3,3,3,3,4,3,3,4,0.0,neutral or dissatisfied +12268,96279,Male,Loyal Customer,57,Personal Travel,Eco,687,4,5,5,5,3,5,3,3,3,4,5,4,4,3,4,0.0,neutral or dissatisfied +12269,121642,Male,Loyal Customer,19,Business travel,Eco Plus,936,4,4,4,4,4,4,4,4,5,3,5,1,3,4,0,1.0,satisfied +12270,64246,Male,Loyal Customer,22,Personal Travel,Eco,1660,2,4,2,1,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +12271,81458,Male,Loyal Customer,33,Business travel,Business,3964,3,3,3,3,2,2,2,2,4,2,5,5,5,2,0,0.0,satisfied +12272,32658,Female,Loyal Customer,55,Business travel,Eco,84,4,4,4,4,2,4,2,4,4,4,4,3,4,1,0,0.0,satisfied +12273,21790,Female,Loyal Customer,41,Business travel,Eco,241,2,4,5,4,3,2,3,3,4,5,1,2,1,3,0,3.0,neutral or dissatisfied +12274,81090,Female,Loyal Customer,52,Personal Travel,Eco,931,2,5,2,3,3,4,4,5,5,2,2,4,5,5,1,0.0,neutral or dissatisfied +12275,68769,Female,Loyal Customer,48,Business travel,Business,3780,1,1,1,1,2,2,2,3,4,4,4,2,5,2,206,197.0,satisfied +12276,37351,Female,Loyal Customer,22,Business travel,Business,3611,5,5,3,5,4,4,4,4,2,3,5,3,3,4,21,11.0,satisfied +12277,2218,Male,Loyal Customer,30,Business travel,Business,2523,2,2,3,2,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +12278,72513,Male,Loyal Customer,57,Business travel,Business,2427,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,3.0,satisfied +12279,127137,Female,Loyal Customer,12,Personal Travel,Eco,647,2,1,2,3,5,2,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +12280,57044,Male,Loyal Customer,33,Business travel,Business,2133,5,5,5,5,5,5,5,5,5,5,4,3,5,5,113,106.0,satisfied +12281,65423,Female,Loyal Customer,47,Business travel,Business,2165,1,1,1,1,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +12282,14727,Female,disloyal Customer,36,Business travel,Eco Plus,419,2,3,3,4,1,3,1,1,1,4,4,4,4,1,12,14.0,neutral or dissatisfied +12283,73919,Male,Loyal Customer,41,Business travel,Business,2342,5,5,3,5,2,5,5,5,5,5,5,3,5,4,6,0.0,satisfied +12284,31229,Female,Loyal Customer,38,Personal Travel,Eco Plus,628,3,5,3,3,1,3,5,1,5,2,4,3,5,1,2,0.0,neutral or dissatisfied +12285,44882,Female,Loyal Customer,55,Business travel,Eco Plus,240,3,5,5,5,1,2,2,3,3,3,3,4,3,1,19,8.0,neutral or dissatisfied +12286,69120,Female,Loyal Customer,41,Business travel,Eco,1598,2,1,1,1,2,2,2,2,2,4,1,4,2,2,5,0.0,neutral or dissatisfied +12287,124822,Male,disloyal Customer,34,Business travel,Business,280,3,3,3,3,2,3,2,2,5,3,5,5,5,2,4,5.0,neutral or dissatisfied +12288,93217,Male,Loyal Customer,48,Business travel,Business,1460,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,3.0,satisfied +12289,110232,Male,Loyal Customer,22,Business travel,Business,3411,5,5,3,5,5,5,5,5,3,3,4,5,4,5,0,9.0,satisfied +12290,78275,Female,Loyal Customer,41,Business travel,Business,1598,1,1,1,1,4,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +12291,69348,Male,Loyal Customer,30,Business travel,Business,1096,1,1,1,1,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +12292,86515,Male,Loyal Customer,7,Personal Travel,Eco,712,2,4,2,4,3,2,4,3,2,2,1,5,2,3,0,0.0,neutral or dissatisfied +12293,49985,Female,Loyal Customer,48,Business travel,Business,2958,4,4,5,4,2,4,2,4,4,4,5,3,4,4,0,3.0,satisfied +12294,128148,Female,Loyal Customer,44,Business travel,Business,1849,2,2,3,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +12295,85326,Female,Loyal Customer,32,Personal Travel,Eco,731,3,4,3,2,5,3,5,5,4,4,4,4,3,5,3,0.0,neutral or dissatisfied +12296,50028,Male,Loyal Customer,26,Business travel,Eco,109,1,2,3,2,1,1,3,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +12297,35959,Male,disloyal Customer,37,Business travel,Business,231,4,4,4,3,5,4,5,5,3,2,1,5,1,5,0,0.0,satisfied +12298,123372,Male,Loyal Customer,56,Personal Travel,Eco,644,2,1,2,3,2,2,2,2,1,2,2,1,2,2,0,0.0,neutral or dissatisfied +12299,17943,Female,Loyal Customer,24,Personal Travel,Eco,95,4,5,4,4,2,4,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +12300,6699,Male,disloyal Customer,23,Business travel,Eco,438,2,3,2,4,3,2,3,3,1,2,3,3,4,3,10,10.0,neutral or dissatisfied +12301,31898,Male,Loyal Customer,38,Business travel,Business,2762,5,5,5,5,5,5,3,4,4,4,4,5,4,1,0,0.0,satisfied +12302,84115,Female,Loyal Customer,60,Business travel,Business,1900,4,4,4,4,5,3,5,2,2,2,2,5,2,5,0,0.0,satisfied +12303,28626,Male,Loyal Customer,27,Business travel,Business,2378,3,2,3,3,4,3,4,4,4,1,3,2,5,4,0,0.0,satisfied +12304,26441,Male,Loyal Customer,47,Business travel,Eco,925,4,3,3,3,4,4,4,4,3,3,5,5,5,4,21,26.0,satisfied +12305,128314,Male,Loyal Customer,45,Business travel,Business,651,3,3,3,3,2,4,4,4,4,4,4,3,4,4,32,16.0,satisfied +12306,89802,Female,Loyal Customer,41,Business travel,Business,3880,4,4,4,4,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +12307,126220,Female,Loyal Customer,36,Business travel,Business,650,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +12308,51860,Female,Loyal Customer,11,Business travel,Business,2608,1,1,1,1,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +12309,123407,Male,disloyal Customer,20,Business travel,Eco,1337,3,2,2,4,2,3,4,2,3,1,3,2,4,2,15,21.0,neutral or dissatisfied +12310,54975,Male,Loyal Customer,43,Business travel,Business,1635,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +12311,67317,Male,Loyal Customer,38,Personal Travel,Eco Plus,985,2,5,3,4,5,3,5,5,5,4,5,4,5,5,0,9.0,neutral or dissatisfied +12312,71896,Female,Loyal Customer,22,Personal Travel,Eco,1744,3,2,3,2,3,3,5,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +12313,4019,Male,Loyal Customer,50,Business travel,Business,2618,4,4,1,4,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +12314,11873,Female,Loyal Customer,60,Personal Travel,Eco,1042,3,4,3,1,2,5,5,4,4,3,4,3,4,5,11,0.0,neutral or dissatisfied +12315,2553,Male,disloyal Customer,27,Business travel,Business,181,2,2,2,3,4,2,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +12316,100071,Female,Loyal Customer,70,Personal Travel,Eco,281,3,3,3,1,2,3,2,2,2,3,2,4,2,3,75,86.0,neutral or dissatisfied +12317,18130,Male,Loyal Customer,31,Business travel,Business,3949,2,2,4,2,5,5,4,5,2,2,3,3,4,5,0,0.0,satisfied +12318,115168,Male,disloyal Customer,20,Business travel,Business,373,0,4,0,4,4,0,3,4,5,3,4,3,4,4,0,0.0,satisfied +12319,81608,Female,Loyal Customer,22,Business travel,Eco,334,2,5,5,5,2,2,1,2,4,4,2,1,2,2,21,21.0,neutral or dissatisfied +12320,64955,Male,disloyal Customer,37,Business travel,Business,247,4,4,4,5,2,4,2,2,3,5,5,4,5,2,0,0.0,satisfied +12321,114418,Female,Loyal Customer,49,Business travel,Business,372,3,3,2,3,5,5,5,5,5,5,5,5,5,4,1,0.0,satisfied +12322,6237,Male,Loyal Customer,12,Business travel,Business,594,1,4,4,4,1,1,1,1,4,3,2,4,2,1,0,0.0,neutral or dissatisfied +12323,49674,Female,Loyal Customer,47,Business travel,Eco,421,3,2,2,2,3,3,3,3,3,3,3,1,3,1,0,5.0,neutral or dissatisfied +12324,87890,Male,Loyal Customer,53,Business travel,Business,2349,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +12325,79094,Male,Loyal Customer,42,Personal Travel,Eco,356,1,5,1,2,3,1,3,3,5,5,4,3,5,3,8,7.0,neutral or dissatisfied +12326,34855,Male,Loyal Customer,49,Personal Travel,Eco,1826,3,5,3,3,1,3,1,1,4,2,3,3,5,1,3,0.0,neutral or dissatisfied +12327,72071,Female,Loyal Customer,48,Business travel,Business,2556,1,1,1,1,2,4,5,5,5,5,5,5,5,5,12,0.0,satisfied +12328,36865,Male,Loyal Customer,31,Personal Travel,Eco,273,3,2,3,4,3,3,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +12329,51039,Male,Loyal Customer,65,Personal Travel,Eco,266,5,3,5,4,3,5,3,3,4,4,5,4,5,3,0,0.0,satisfied +12330,96467,Male,Loyal Customer,60,Business travel,Business,302,1,1,1,1,2,5,4,5,5,5,5,4,5,5,36,27.0,satisfied +12331,107893,Male,disloyal Customer,40,Business travel,Business,861,5,5,5,5,5,5,5,5,3,2,4,4,4,5,7,3.0,satisfied +12332,123756,Female,Loyal Customer,48,Business travel,Business,541,4,4,4,4,4,4,4,4,4,4,4,3,4,3,10,16.0,satisfied +12333,35712,Female,Loyal Customer,18,Personal Travel,Eco,2475,3,3,3,1,3,4,1,4,4,3,1,1,4,1,25,32.0,neutral or dissatisfied +12334,103299,Female,disloyal Customer,39,Business travel,Business,1139,4,4,4,5,2,4,3,2,3,4,5,5,5,2,0,11.0,satisfied +12335,53300,Female,disloyal Customer,23,Business travel,Eco,758,5,4,4,2,2,4,2,2,2,1,1,4,3,2,0,0.0,satisfied +12336,82770,Female,Loyal Customer,59,Business travel,Business,409,5,5,5,5,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +12337,82195,Female,Loyal Customer,10,Personal Travel,Eco,1927,1,5,1,2,1,1,1,1,3,2,4,5,4,1,0,12.0,neutral or dissatisfied +12338,102066,Male,Loyal Customer,58,Personal Travel,Business,226,1,5,1,4,5,5,5,3,3,1,3,4,3,3,17,15.0,neutral or dissatisfied +12339,102033,Female,Loyal Customer,49,Business travel,Business,391,1,4,4,4,3,4,4,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +12340,1652,Male,Loyal Customer,24,Business travel,Business,3220,3,3,4,3,4,4,4,4,4,4,4,4,4,4,0,15.0,satisfied +12341,3254,Female,Loyal Customer,27,Business travel,Business,2295,1,1,2,1,4,4,4,4,5,2,5,4,4,4,18,15.0,satisfied +12342,83490,Female,Loyal Customer,28,Business travel,Business,946,2,5,5,5,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +12343,17628,Female,Loyal Customer,46,Business travel,Business,930,3,3,3,3,3,4,2,3,3,4,3,1,3,3,0,13.0,satisfied +12344,24533,Male,Loyal Customer,47,Business travel,Business,2098,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +12345,10705,Male,Loyal Customer,77,Business travel,Business,2659,5,5,5,5,4,5,4,3,3,3,3,3,3,4,18,9.0,satisfied +12346,124834,Female,Loyal Customer,51,Personal Travel,Eco,280,3,4,3,3,3,4,4,3,3,3,3,4,3,5,52,53.0,neutral or dissatisfied +12347,63739,Male,Loyal Customer,70,Personal Travel,Eco,1660,2,5,2,5,2,2,2,2,5,2,5,3,4,2,5,0.0,neutral or dissatisfied +12348,4245,Male,Loyal Customer,10,Personal Travel,Eco,1020,1,4,1,2,3,1,3,3,1,2,5,4,1,3,57,58.0,neutral or dissatisfied +12349,66959,Male,Loyal Customer,46,Business travel,Business,2787,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +12350,113270,Male,Loyal Customer,26,Business travel,Business,2991,0,0,0,1,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +12351,12769,Male,disloyal Customer,20,Business travel,Eco Plus,721,2,4,2,1,4,2,4,4,5,2,2,5,1,4,0,12.0,neutral or dissatisfied +12352,113990,Female,Loyal Customer,47,Business travel,Eco,1728,2,1,4,1,1,2,2,1,1,2,1,2,1,2,0,13.0,neutral or dissatisfied +12353,19702,Male,Loyal Customer,57,Business travel,Business,1578,5,5,5,5,2,5,1,4,4,4,4,3,4,5,0,5.0,satisfied +12354,70928,Male,Loyal Customer,53,Business travel,Business,3352,3,3,2,3,3,5,4,4,4,4,4,3,4,4,6,13.0,satisfied +12355,102152,Female,disloyal Customer,48,Business travel,Business,223,4,4,4,4,3,4,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +12356,77607,Male,disloyal Customer,22,Business travel,Business,874,4,5,4,1,5,4,5,5,3,2,5,3,5,5,0,0.0,satisfied +12357,17043,Female,Loyal Customer,44,Business travel,Eco,1134,5,4,4,4,5,4,2,5,5,5,5,2,5,3,75,64.0,satisfied +12358,80545,Male,disloyal Customer,21,Business travel,Eco,1385,4,3,3,4,2,4,2,2,4,5,3,3,5,2,2,0.0,satisfied +12359,59293,Male,Loyal Customer,31,Business travel,Business,2447,1,1,1,1,4,4,4,4,4,3,5,3,4,4,13,0.0,satisfied +12360,27354,Female,Loyal Customer,35,Business travel,Eco,978,4,1,1,1,4,4,4,4,4,1,4,2,5,4,0,1.0,satisfied +12361,16206,Female,Loyal Customer,55,Personal Travel,Eco,284,2,2,2,4,1,4,3,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +12362,14528,Male,Loyal Customer,66,Business travel,Eco,362,4,3,3,3,4,4,4,4,2,2,4,3,4,4,0,0.0,neutral or dissatisfied +12363,21568,Female,Loyal Customer,33,Business travel,Eco Plus,331,4,1,1,1,4,4,4,4,1,4,1,5,4,4,0,0.0,satisfied +12364,102748,Male,Loyal Customer,49,Business travel,Business,3259,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +12365,121248,Female,Loyal Customer,53,Business travel,Business,2075,2,2,2,2,4,3,5,4,4,4,4,5,4,4,1,0.0,satisfied +12366,30337,Male,disloyal Customer,21,Business travel,Eco,391,3,2,3,3,4,3,4,4,1,4,3,3,3,4,24,28.0,neutral or dissatisfied +12367,115216,Male,Loyal Customer,51,Business travel,Eco,417,4,1,1,1,4,4,4,4,1,1,3,3,4,4,28,20.0,neutral or dissatisfied +12368,30636,Male,disloyal Customer,26,Business travel,Eco,533,2,3,2,4,2,2,2,2,4,1,2,3,1,2,0,0.0,neutral or dissatisfied +12369,96738,Female,Loyal Customer,12,Personal Travel,Eco,696,3,5,3,3,2,3,3,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +12370,74982,Female,Loyal Customer,19,Personal Travel,Eco,2586,2,5,2,2,4,2,4,4,4,5,4,3,2,4,0,0.0,neutral or dissatisfied +12371,65292,Female,Loyal Customer,18,Personal Travel,Eco Plus,190,1,2,1,3,2,1,2,2,1,2,3,3,2,2,1,0.0,neutral or dissatisfied +12372,79203,Female,Loyal Customer,45,Business travel,Eco,1990,3,1,1,1,2,2,3,3,3,3,3,1,3,2,5,0.0,neutral or dissatisfied +12373,12552,Male,Loyal Customer,52,Personal Travel,Eco,788,3,3,3,3,4,3,4,4,2,3,4,3,3,4,24,20.0,neutral or dissatisfied +12374,58971,Female,Loyal Customer,29,Personal Travel,Business,1744,3,3,3,3,2,3,5,2,4,4,2,4,3,2,1,3.0,neutral or dissatisfied +12375,69241,Male,disloyal Customer,28,Business travel,Eco,733,4,4,4,4,1,4,1,1,3,2,3,2,4,1,4,0.0,neutral or dissatisfied +12376,49343,Male,Loyal Customer,54,Business travel,Eco,134,5,3,3,3,5,5,5,5,5,1,3,1,5,5,0,0.0,satisfied +12377,11965,Male,Loyal Customer,18,Personal Travel,Business,643,2,4,2,1,3,2,3,3,4,3,5,5,5,3,73,71.0,neutral or dissatisfied +12378,42377,Male,Loyal Customer,61,Personal Travel,Eco,329,2,4,2,3,2,2,3,2,2,4,3,5,3,2,0,0.0,neutral or dissatisfied +12379,87545,Female,Loyal Customer,52,Personal Travel,Eco,782,2,4,2,3,2,5,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +12380,108843,Male,Loyal Customer,60,Business travel,Business,1947,3,3,3,3,2,4,4,2,2,2,2,5,2,4,8,1.0,satisfied +12381,83307,Male,Loyal Customer,38,Business travel,Business,1671,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +12382,24580,Male,Loyal Customer,42,Business travel,Business,2539,2,3,3,3,1,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +12383,24361,Female,Loyal Customer,42,Business travel,Business,669,2,2,2,2,5,4,5,5,5,5,5,3,5,4,21,13.0,satisfied +12384,17955,Female,Loyal Customer,60,Business travel,Business,460,4,4,4,4,1,3,4,5,5,5,5,2,5,3,46,70.0,satisfied +12385,94388,Female,disloyal Customer,38,Business travel,Business,248,2,2,2,3,4,2,4,4,3,4,4,3,5,4,3,0.0,neutral or dissatisfied +12386,16317,Male,Loyal Customer,32,Business travel,Business,1512,3,4,4,4,3,3,3,3,1,4,3,1,3,3,56,70.0,neutral or dissatisfied +12387,30976,Male,Loyal Customer,16,Business travel,Eco,1476,5,3,3,3,5,5,3,5,2,1,4,2,1,5,91,74.0,satisfied +12388,28554,Male,Loyal Customer,18,Personal Travel,Eco,2640,3,4,3,4,3,3,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +12389,92286,Male,Loyal Customer,43,Personal Travel,Eco Plus,2036,3,5,2,1,4,2,4,4,3,2,3,4,5,4,1,0.0,neutral or dissatisfied +12390,90147,Female,disloyal Customer,35,Business travel,Eco,1084,4,4,4,3,4,4,4,4,3,4,4,3,2,4,0,0.0,neutral or dissatisfied +12391,36976,Male,disloyal Customer,42,Business travel,Eco,899,2,2,2,4,4,2,4,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +12392,11056,Female,Loyal Customer,20,Personal Travel,Eco,247,2,4,2,5,4,2,4,4,5,3,5,4,4,4,0,37.0,neutral or dissatisfied +12393,86340,Female,Loyal Customer,46,Business travel,Business,3113,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,14.0,satisfied +12394,115178,Female,Loyal Customer,26,Business travel,Eco,372,2,3,3,3,2,2,2,2,1,2,3,1,4,2,15,13.0,neutral or dissatisfied +12395,116594,Female,Loyal Customer,45,Business travel,Business,2113,2,2,2,2,4,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +12396,39421,Female,Loyal Customer,33,Business travel,Business,1888,2,2,2,2,2,3,4,5,5,5,4,5,5,3,0,7.0,satisfied +12397,26207,Female,disloyal Customer,16,Business travel,Eco,406,1,2,1,4,4,1,4,4,4,5,3,3,4,4,14,24.0,neutral or dissatisfied +12398,126250,Male,Loyal Customer,54,Business travel,Eco,250,5,1,1,1,5,5,5,5,4,4,1,4,3,5,1,0.0,satisfied +12399,43248,Female,Loyal Customer,52,Personal Travel,Business,347,2,4,2,3,2,4,5,2,2,2,4,4,2,5,2,21.0,neutral or dissatisfied +12400,99191,Male,Loyal Customer,32,Personal Travel,Eco,351,2,4,2,1,3,2,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +12401,32575,Male,Loyal Customer,62,Business travel,Business,216,1,1,1,1,2,1,3,5,5,5,3,5,5,5,3,2.0,satisfied +12402,109071,Male,Loyal Customer,25,Business travel,Business,781,4,1,4,4,4,4,4,4,3,2,3,1,4,4,6,9.0,neutral or dissatisfied +12403,83098,Female,Loyal Customer,50,Personal Travel,Eco,957,1,4,0,2,3,4,4,5,5,0,1,4,5,3,0,0.0,neutral or dissatisfied +12404,125314,Male,disloyal Customer,24,Business travel,Eco,678,4,4,4,1,2,4,2,2,5,1,4,1,5,2,0,0.0,neutral or dissatisfied +12405,75896,Male,Loyal Customer,60,Business travel,Business,3774,5,5,5,5,4,4,4,5,5,5,5,5,5,3,41,42.0,satisfied +12406,13095,Male,disloyal Customer,37,Business travel,Eco,562,1,4,1,1,1,1,1,1,3,4,1,5,5,1,0,0.0,neutral or dissatisfied +12407,122655,Male,disloyal Customer,25,Business travel,Business,361,5,0,4,5,1,4,1,1,4,5,4,3,5,1,7,8.0,satisfied +12408,54610,Male,Loyal Customer,46,Business travel,Eco,965,4,4,3,4,4,4,4,4,3,4,5,3,3,4,6,0.0,satisfied +12409,99485,Male,disloyal Customer,16,Business travel,Eco,307,4,3,4,3,2,4,4,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +12410,24479,Male,Loyal Customer,41,Business travel,Business,2225,4,4,4,4,2,2,1,4,4,4,4,5,4,5,0,0.0,satisfied +12411,29790,Female,disloyal Customer,28,Business travel,Eco,627,2,4,1,3,4,1,3,4,3,3,2,5,5,4,0,0.0,neutral or dissatisfied +12412,87552,Female,disloyal Customer,21,Business travel,Business,432,4,2,4,3,5,4,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +12413,91324,Female,Loyal Customer,59,Business travel,Business,3888,1,1,5,1,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +12414,12183,Female,disloyal Customer,35,Business travel,Eco,1075,2,2,2,3,4,2,4,4,1,4,4,3,3,4,0,1.0,neutral or dissatisfied +12415,19825,Male,Loyal Customer,49,Business travel,Business,3899,2,5,3,5,4,4,3,2,2,2,2,2,2,3,43,29.0,neutral or dissatisfied +12416,64518,Male,Loyal Customer,29,Personal Travel,Business,224,2,4,2,3,3,2,3,3,4,4,5,5,4,3,3,0.0,neutral or dissatisfied +12417,71706,Female,Loyal Customer,43,Personal Travel,Eco Plus,1197,2,5,2,3,3,3,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +12418,6801,Male,Loyal Customer,56,Business travel,Business,3803,1,4,4,4,5,3,2,1,1,1,1,1,1,2,3,0.0,neutral or dissatisfied +12419,101859,Male,Loyal Customer,46,Personal Travel,Eco,519,3,4,3,1,3,3,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +12420,25854,Female,Loyal Customer,66,Personal Travel,Eco,692,1,5,1,2,4,4,5,1,1,1,1,4,1,4,30,27.0,neutral or dissatisfied +12421,67075,Male,Loyal Customer,44,Business travel,Business,964,2,3,3,3,5,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +12422,115701,Female,Loyal Customer,51,Business travel,Business,2522,4,5,5,5,1,3,4,4,4,4,4,1,4,4,15,7.0,neutral or dissatisfied +12423,125751,Male,Loyal Customer,40,Business travel,Business,1803,4,4,4,4,2,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +12424,56952,Male,Loyal Customer,63,Business travel,Eco,2565,2,3,3,3,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +12425,83596,Male,Loyal Customer,42,Business travel,Business,3044,3,3,3,3,2,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +12426,56909,Male,Loyal Customer,53,Business travel,Business,2454,4,4,4,4,4,4,4,4,3,3,4,4,3,4,8,5.0,satisfied +12427,25491,Male,Loyal Customer,51,Business travel,Business,2642,2,2,2,2,3,4,3,2,2,2,2,2,2,1,26,28.0,neutral or dissatisfied +12428,98926,Male,Loyal Customer,44,Business travel,Business,2050,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,1.0,satisfied +12429,77663,Female,Loyal Customer,42,Business travel,Eco,689,4,4,4,4,2,4,4,4,4,4,4,2,4,3,83,73.0,neutral or dissatisfied +12430,105627,Male,Loyal Customer,28,Business travel,Business,1706,3,3,3,3,4,4,4,4,3,5,5,5,5,4,0,2.0,satisfied +12431,12876,Female,Loyal Customer,23,Business travel,Business,359,2,2,2,2,5,5,5,5,3,2,1,5,5,5,0,0.0,satisfied +12432,124720,Male,Loyal Customer,31,Personal Travel,Eco,399,3,5,3,3,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +12433,63625,Male,disloyal Customer,23,Business travel,Business,602,4,3,4,1,5,4,5,5,3,5,4,3,5,5,3,0.0,satisfied +12434,117233,Male,Loyal Customer,46,Personal Travel,Eco,370,2,4,2,4,2,2,2,2,4,2,3,4,4,2,4,32.0,neutral or dissatisfied +12435,78650,Male,disloyal Customer,39,Business travel,Eco,672,1,1,1,3,3,1,1,3,4,5,3,1,4,3,84,55.0,neutral or dissatisfied +12436,23720,Female,Loyal Customer,52,Personal Travel,Eco,196,1,4,1,4,3,4,4,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +12437,80096,Female,Loyal Customer,45,Business travel,Business,1620,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,20.0,satisfied +12438,21510,Male,Loyal Customer,55,Personal Travel,Eco,377,2,4,2,3,2,2,2,2,3,3,4,4,5,2,20,18.0,neutral or dissatisfied +12439,104719,Female,disloyal Customer,35,Business travel,Business,1407,3,3,3,1,3,3,3,3,3,3,4,3,5,3,22,0.0,neutral or dissatisfied +12440,114320,Male,Loyal Customer,8,Personal Travel,Eco,846,4,2,4,4,4,4,2,4,2,1,4,3,4,4,77,62.0,neutral or dissatisfied +12441,120736,Female,disloyal Customer,37,Business travel,Eco,689,3,3,3,2,3,3,3,3,3,5,1,3,2,3,0,0.0,neutral or dissatisfied +12442,69674,Male,Loyal Customer,9,Personal Travel,Eco,569,3,4,3,5,3,3,3,3,5,5,4,3,5,3,3,0.0,neutral or dissatisfied +12443,82440,Female,Loyal Customer,50,Business travel,Business,509,2,2,2,2,5,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +12444,81861,Female,Loyal Customer,39,Business travel,Eco Plus,1016,5,3,3,3,5,5,5,5,2,1,5,5,5,5,0,0.0,satisfied +12445,107745,Male,Loyal Customer,30,Personal Travel,Eco,405,2,1,0,4,4,0,3,4,3,4,3,2,4,4,3,0.0,neutral or dissatisfied +12446,10056,Female,disloyal Customer,27,Business travel,Business,326,1,1,1,4,3,1,3,3,4,3,4,5,5,3,0,4.0,neutral or dissatisfied +12447,71742,Female,Loyal Customer,33,Personal Travel,Business,1744,2,5,2,3,2,3,4,4,4,2,3,3,4,4,0,0.0,neutral or dissatisfied +12448,41355,Female,Loyal Customer,15,Personal Travel,Business,794,3,3,3,3,5,3,5,5,1,4,4,3,3,5,40,68.0,neutral or dissatisfied +12449,115380,Female,Loyal Customer,51,Business travel,Business,2598,4,3,3,3,1,4,4,4,4,4,4,3,4,2,1,0.0,neutral or dissatisfied +12450,115039,Female,disloyal Customer,50,Business travel,Business,446,4,4,4,2,3,4,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +12451,127372,Female,disloyal Customer,28,Business travel,Business,868,3,3,3,3,5,3,5,5,5,3,4,5,5,5,1,0.0,neutral or dissatisfied +12452,86931,Female,disloyal Customer,32,Business travel,Business,341,3,4,4,1,5,4,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +12453,76077,Female,Loyal Customer,47,Business travel,Eco,669,4,3,3,3,4,4,4,2,5,4,3,4,2,4,143,138.0,neutral or dissatisfied +12454,56114,Female,Loyal Customer,41,Business travel,Business,1400,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +12455,77582,Female,Loyal Customer,61,Personal Travel,Business,731,2,3,2,2,3,2,2,3,3,2,4,2,3,4,4,4.0,neutral or dissatisfied +12456,84741,Female,Loyal Customer,40,Business travel,Business,1876,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +12457,12544,Female,disloyal Customer,35,Business travel,Eco,871,3,3,3,1,4,3,1,4,2,2,5,1,2,4,14,11.0,neutral or dissatisfied +12458,46162,Female,Loyal Customer,35,Personal Travel,Eco,604,2,5,2,5,3,2,3,3,3,5,4,5,4,3,22,36.0,neutral or dissatisfied +12459,27406,Male,disloyal Customer,23,Business travel,Eco,978,4,4,4,1,1,4,1,1,2,1,2,4,2,1,0,0.0,satisfied +12460,75364,Female,Loyal Customer,65,Personal Travel,Eco Plus,2486,1,3,1,3,1,1,1,1,1,4,4,1,1,1,2,37.0,neutral or dissatisfied +12461,54097,Male,Loyal Customer,41,Business travel,Eco Plus,1416,5,5,2,5,5,5,5,5,5,1,4,2,5,5,52,16.0,satisfied +12462,39272,Female,Loyal Customer,38,Business travel,Business,2248,5,5,5,5,2,3,1,4,4,4,4,2,4,4,0,0.0,satisfied +12463,58249,Male,Loyal Customer,9,Personal Travel,Eco Plus,925,2,4,2,2,4,2,4,4,5,4,5,4,4,4,78,72.0,neutral or dissatisfied +12464,80971,Male,Loyal Customer,43,Business travel,Business,2702,0,0,0,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +12465,52949,Male,Loyal Customer,10,Personal Travel,Eco,1448,4,2,4,4,2,4,2,2,3,3,2,4,4,2,4,0.0,neutral or dissatisfied +12466,74111,Male,disloyal Customer,22,Business travel,Eco,641,3,1,2,3,2,2,3,2,4,1,3,4,3,2,5,0.0,neutral or dissatisfied +12467,28927,Female,Loyal Customer,58,Business travel,Eco,956,3,5,5,5,2,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +12468,61044,Female,Loyal Customer,39,Business travel,Eco,1709,4,4,4,4,4,4,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +12469,110628,Female,Loyal Customer,32,Personal Travel,Eco,727,4,2,3,3,4,3,1,4,2,1,3,4,3,4,0,0.0,neutral or dissatisfied +12470,124516,Male,Loyal Customer,41,Business travel,Business,3875,5,5,5,5,3,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +12471,47510,Male,Loyal Customer,67,Personal Travel,Eco,574,2,5,2,3,4,2,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +12472,31085,Female,Loyal Customer,25,Personal Travel,Business,1014,2,3,2,3,4,2,4,4,1,3,4,4,4,4,16,10.0,neutral or dissatisfied +12473,126569,Female,Loyal Customer,26,Business travel,Business,1558,1,1,5,1,1,1,1,1,3,4,3,1,3,1,0,3.0,neutral or dissatisfied +12474,91732,Male,Loyal Customer,47,Business travel,Business,2459,3,3,3,3,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +12475,40737,Male,Loyal Customer,29,Business travel,Business,501,3,3,3,3,5,5,5,5,3,5,5,5,5,5,0,5.0,satisfied +12476,119378,Male,Loyal Customer,29,Business travel,Business,399,5,5,5,5,4,4,4,4,5,2,4,5,4,4,0,0.0,satisfied +12477,73653,Female,Loyal Customer,24,Business travel,Business,192,2,5,5,5,1,1,2,1,1,5,4,4,4,1,22,29.0,neutral or dissatisfied +12478,87624,Female,Loyal Customer,51,Business travel,Business,591,3,3,3,3,5,5,5,3,3,3,3,4,3,3,110,121.0,satisfied +12479,95744,Male,Loyal Customer,33,Business travel,Business,419,1,1,5,1,4,4,4,4,1,5,3,4,5,4,89,83.0,satisfied +12480,60727,Female,Loyal Customer,45,Personal Travel,Eco,1725,4,5,4,1,3,4,4,2,2,4,2,4,2,3,19,0.0,neutral or dissatisfied +12481,83553,Female,Loyal Customer,42,Business travel,Business,1865,3,3,3,3,4,3,4,4,4,5,4,5,4,5,7,0.0,satisfied +12482,64330,Male,Loyal Customer,66,Business travel,Eco,1192,1,3,3,3,1,1,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +12483,94212,Male,Loyal Customer,49,Business travel,Business,319,0,0,0,4,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +12484,52172,Male,Loyal Customer,56,Business travel,Eco,425,4,1,1,1,4,4,4,4,3,3,4,2,4,4,0,0.0,satisfied +12485,93883,Female,Loyal Customer,42,Business travel,Business,3694,2,2,5,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +12486,38623,Female,disloyal Customer,21,Business travel,Eco,2588,2,2,2,3,2,2,5,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +12487,81580,Male,Loyal Customer,40,Business travel,Business,503,2,2,2,2,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +12488,96076,Male,Loyal Customer,27,Personal Travel,Eco,1090,2,4,2,1,5,2,5,5,1,2,5,4,3,5,0,0.0,neutral or dissatisfied +12489,42611,Female,disloyal Customer,45,Business travel,Eco,546,1,3,1,4,1,1,2,1,3,3,4,2,4,1,0,7.0,neutral or dissatisfied +12490,61084,Male,Loyal Customer,17,Personal Travel,Eco,1546,1,4,1,5,4,1,5,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +12491,63914,Male,Loyal Customer,58,Business travel,Business,772,2,2,2,2,1,4,5,5,5,4,5,5,5,1,0,2.0,satisfied +12492,52565,Female,Loyal Customer,42,Business travel,Business,3685,1,1,1,1,1,2,2,4,4,4,4,1,4,5,0,0.0,satisfied +12493,31705,Female,Loyal Customer,44,Personal Travel,Eco,846,4,5,4,2,4,4,5,1,1,4,1,3,1,5,0,0.0,satisfied +12494,122515,Female,Loyal Customer,38,Personal Travel,Eco,930,2,5,2,5,1,2,1,1,4,4,4,4,5,1,1,15.0,neutral or dissatisfied +12495,56842,Female,disloyal Customer,19,Business travel,Business,1605,4,4,4,5,1,4,1,1,5,5,5,3,4,1,5,0.0,satisfied +12496,96419,Female,Loyal Customer,47,Business travel,Business,3770,2,2,2,2,3,4,4,5,5,5,5,5,5,4,22,10.0,satisfied +12497,33991,Male,Loyal Customer,45,Business travel,Eco,1598,2,5,4,4,1,2,1,1,4,4,5,3,5,1,0,0.0,satisfied +12498,21869,Male,Loyal Customer,22,Business travel,Business,2928,2,4,2,2,4,4,4,4,4,4,1,4,2,4,133,133.0,satisfied +12499,32793,Female,Loyal Customer,39,Business travel,Business,163,1,1,1,1,1,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +12500,101863,Male,Loyal Customer,33,Business travel,Business,1747,2,2,2,2,4,4,4,4,3,3,4,3,5,4,17,0.0,satisfied +12501,56332,Female,disloyal Customer,27,Business travel,Eco,200,3,1,3,3,2,3,2,2,4,5,3,2,4,2,0,0.0,neutral or dissatisfied +12502,89413,Male,disloyal Customer,25,Business travel,Eco,134,3,3,3,4,5,3,2,5,3,2,4,1,3,5,0,0.0,neutral or dissatisfied +12503,109368,Female,Loyal Customer,59,Business travel,Business,2241,3,3,3,3,5,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +12504,85748,Male,Loyal Customer,39,Business travel,Business,526,5,5,5,5,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +12505,52219,Male,Loyal Customer,36,Business travel,Business,509,5,5,5,5,3,5,4,5,5,5,5,2,5,4,14,5.0,satisfied +12506,109833,Female,disloyal Customer,25,Business travel,Business,1011,2,0,2,4,1,2,1,1,5,5,4,5,4,1,34,25.0,neutral or dissatisfied +12507,91484,Male,Loyal Customer,14,Personal Travel,Eco,859,2,4,2,3,5,2,3,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +12508,63879,Female,Loyal Customer,54,Business travel,Business,2741,1,1,1,1,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +12509,72749,Female,Loyal Customer,43,Business travel,Business,806,5,5,5,5,5,5,4,5,5,5,5,3,5,5,123,115.0,satisfied +12510,65667,Male,disloyal Customer,14,Business travel,Eco,926,3,4,4,3,2,4,1,2,2,4,4,1,3,2,2,0.0,neutral or dissatisfied +12511,80627,Male,disloyal Customer,40,Business travel,Business,282,4,4,4,1,3,4,5,3,4,3,5,5,4,3,0,0.0,satisfied +12512,49826,Female,Loyal Customer,61,Business travel,Business,3254,1,4,4,4,3,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +12513,26500,Female,Loyal Customer,43,Business travel,Business,2089,5,5,2,5,2,3,1,4,4,4,4,2,4,3,0,0.0,satisfied +12514,115703,Female,Loyal Customer,23,Business travel,Business,3231,2,5,5,5,2,2,2,2,1,5,3,3,3,2,119,107.0,neutral or dissatisfied +12515,112084,Male,Loyal Customer,20,Personal Travel,Eco,1491,1,1,1,2,1,1,1,1,2,5,3,1,3,1,1,0.0,neutral or dissatisfied +12516,68557,Male,Loyal Customer,34,Business travel,Business,2136,4,4,5,4,1,4,4,4,4,4,4,4,4,3,5,0.0,neutral or dissatisfied +12517,90515,Female,Loyal Customer,40,Business travel,Business,250,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +12518,114671,Male,disloyal Customer,39,Business travel,Business,337,3,3,3,2,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +12519,8659,Female,Loyal Customer,49,Business travel,Business,3825,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,3.0,satisfied +12520,124564,Female,Loyal Customer,17,Personal Travel,Eco,453,1,4,1,3,3,1,5,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +12521,29502,Female,Loyal Customer,26,Personal Travel,Eco,1107,2,3,2,3,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +12522,13478,Male,Loyal Customer,41,Business travel,Business,3240,1,1,4,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +12523,64207,Male,Loyal Customer,13,Personal Travel,Eco,853,2,5,2,4,5,2,4,5,4,2,5,4,5,5,19,7.0,neutral or dissatisfied +12524,74364,Female,disloyal Customer,26,Business travel,Business,1188,2,2,2,3,3,2,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +12525,97152,Male,disloyal Customer,23,Business travel,Eco,1211,3,3,3,1,2,3,2,2,4,3,4,1,1,2,0,0.0,neutral or dissatisfied +12526,72004,Male,Loyal Customer,47,Business travel,Business,1440,5,5,5,5,3,4,4,3,3,3,3,3,3,5,0,2.0,satisfied +12527,58921,Male,Loyal Customer,22,Personal Travel,Eco,888,2,5,2,5,3,2,1,3,5,3,2,3,4,3,44,41.0,neutral or dissatisfied +12528,120125,Female,disloyal Customer,50,Business travel,Business,1576,3,3,3,2,1,3,1,1,5,2,5,5,4,1,49,43.0,neutral or dissatisfied +12529,46434,Male,Loyal Customer,13,Personal Travel,Eco Plus,458,3,4,3,3,5,3,5,5,4,4,4,3,4,5,12,3.0,neutral or dissatisfied +12530,3261,Female,Loyal Customer,57,Business travel,Business,2093,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +12531,95080,Female,Loyal Customer,66,Personal Travel,Eco,239,3,4,3,2,5,4,4,5,5,3,1,4,5,3,0,0.0,neutral or dissatisfied +12532,118169,Male,disloyal Customer,23,Business travel,Business,1444,5,0,5,1,4,0,4,4,3,3,5,4,5,4,13,0.0,satisfied +12533,92148,Female,Loyal Customer,42,Business travel,Business,1535,3,3,3,3,4,5,5,4,4,4,4,4,4,4,6,0.0,satisfied +12534,12741,Female,Loyal Customer,46,Personal Travel,Eco,721,2,5,2,2,2,4,4,4,4,2,4,4,4,3,0,7.0,neutral or dissatisfied +12535,53421,Male,Loyal Customer,47,Business travel,Business,2288,3,3,4,3,4,4,1,4,4,4,4,5,4,4,46,34.0,satisfied +12536,28591,Male,Loyal Customer,50,Business travel,Eco Plus,2607,5,1,1,1,5,5,5,5,4,3,4,1,1,5,11,0.0,satisfied +12537,99027,Male,Loyal Customer,24,Business travel,Business,3497,1,1,3,1,4,4,4,4,4,5,4,3,4,4,1,0.0,satisfied +12538,37084,Female,Loyal Customer,54,Business travel,Business,3718,3,5,5,5,5,3,3,3,3,3,3,4,3,3,78,80.0,neutral or dissatisfied +12539,31224,Female,Loyal Customer,56,Business travel,Eco Plus,628,5,3,3,3,3,3,2,5,5,5,5,2,5,2,0,0.0,satisfied +12540,51003,Male,Loyal Customer,53,Personal Travel,Eco,86,4,2,4,4,3,4,1,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +12541,126745,Male,Loyal Customer,24,Personal Travel,Eco,2370,5,4,5,4,3,5,3,3,2,2,4,1,4,3,12,0.0,satisfied +12542,120710,Female,disloyal Customer,27,Business travel,Business,280,0,0,0,3,3,0,3,3,3,2,4,4,4,3,0,0.0,satisfied +12543,92428,Female,Loyal Customer,44,Business travel,Business,2116,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +12544,43579,Male,Loyal Customer,48,Personal Travel,Eco,1499,3,2,4,4,3,4,3,3,1,1,4,2,4,3,0,6.0,neutral or dissatisfied +12545,56210,Male,Loyal Customer,47,Business travel,Business,1372,5,5,2,5,3,5,5,4,4,4,4,3,4,3,25,47.0,satisfied +12546,93180,Female,Loyal Customer,19,Personal Travel,Eco,1075,3,5,2,3,2,4,4,5,2,4,5,4,3,4,157,139.0,neutral or dissatisfied +12547,8995,Male,Loyal Customer,39,Business travel,Business,1905,0,0,0,3,2,2,2,5,5,5,4,2,5,2,202,186.0,satisfied +12548,106823,Female,Loyal Customer,59,Business travel,Business,1488,2,3,3,3,1,4,3,2,2,2,2,1,2,4,5,40.0,neutral or dissatisfied +12549,62290,Female,Loyal Customer,59,Business travel,Business,3130,1,1,1,1,5,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +12550,94364,Male,Loyal Customer,48,Business travel,Business,3380,1,1,1,1,3,4,5,5,5,5,5,4,5,5,51,50.0,satisfied +12551,89228,Female,Loyal Customer,61,Personal Travel,Eco,1892,4,3,5,4,1,3,3,3,3,5,3,2,3,2,46,32.0,neutral or dissatisfied +12552,3870,Female,Loyal Customer,57,Business travel,Business,290,4,5,4,4,2,5,5,5,5,5,5,5,5,5,15,21.0,satisfied +12553,101004,Female,Loyal Customer,44,Business travel,Business,867,2,2,2,2,5,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +12554,85670,Female,disloyal Customer,18,Business travel,Business,903,0,0,0,3,4,0,4,4,5,5,5,4,5,4,0,0.0,satisfied +12555,87133,Female,Loyal Customer,29,Personal Travel,Eco,645,3,4,3,1,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +12556,56589,Male,Loyal Customer,35,Business travel,Business,3942,1,2,2,2,2,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +12557,35947,Male,Loyal Customer,53,Business travel,Business,3533,3,4,4,4,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +12558,129719,Male,Loyal Customer,65,Business travel,Eco,337,3,4,4,4,3,3,3,3,3,4,4,4,3,3,50,36.0,neutral or dissatisfied +12559,120729,Male,Loyal Customer,40,Business travel,Business,3635,3,3,3,3,3,4,5,2,2,2,2,3,2,4,13,32.0,satisfied +12560,50502,Male,Loyal Customer,66,Personal Travel,Eco,109,5,3,5,3,3,5,1,3,2,4,2,3,5,3,0,0.0,satisfied +12561,92920,Female,Loyal Customer,41,Business travel,Business,2213,4,5,5,5,4,4,3,4,4,4,4,1,4,1,1,0.0,neutral or dissatisfied +12562,10888,Male,Loyal Customer,33,Business travel,Business,308,1,5,5,5,1,1,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +12563,120144,Male,Loyal Customer,30,Business travel,Business,1475,1,1,1,1,5,5,5,5,4,1,4,4,4,5,0,0.0,satisfied +12564,123815,Female,Loyal Customer,55,Business travel,Business,2962,2,2,2,2,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +12565,7833,Female,Loyal Customer,61,Personal Travel,Eco,650,3,5,3,1,3,3,3,5,5,3,2,5,5,4,32,24.0,neutral or dissatisfied +12566,1332,Female,Loyal Customer,47,Business travel,Business,2902,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +12567,118549,Male,Loyal Customer,41,Business travel,Business,451,1,1,1,1,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +12568,88358,Female,disloyal Customer,23,Business travel,Eco,545,4,5,3,3,2,3,2,2,5,3,5,5,4,2,0,0.0,satisfied +12569,1597,Male,Loyal Customer,50,Personal Travel,Eco,140,1,4,1,2,1,1,1,1,3,4,5,1,4,1,0,2.0,neutral or dissatisfied +12570,15390,Male,Loyal Customer,49,Business travel,Business,2377,5,5,5,5,2,3,3,4,4,4,4,5,4,4,5,1.0,satisfied +12571,42413,Female,disloyal Customer,26,Business travel,Eco Plus,550,0,0,0,5,2,0,2,2,3,1,4,2,4,2,0,0.0,satisfied +12572,89403,Female,Loyal Customer,43,Business travel,Eco,151,4,2,2,2,1,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +12573,15128,Female,Loyal Customer,25,Business travel,Eco,912,4,4,4,4,4,4,4,4,1,5,1,1,1,4,0,0.0,satisfied +12574,42246,Female,disloyal Customer,48,Business travel,Eco,817,1,1,1,2,2,1,4,2,1,5,5,3,5,2,5,4.0,neutral or dissatisfied +12575,25955,Male,Loyal Customer,23,Business travel,Business,946,1,1,1,1,4,4,4,4,1,1,4,4,3,4,2,0.0,satisfied +12576,103999,Male,disloyal Customer,22,Business travel,Eco,1363,4,4,4,1,4,4,1,4,5,4,4,3,4,4,2,1.0,satisfied +12577,25723,Female,Loyal Customer,39,Personal Travel,Eco,447,3,5,3,1,2,3,2,2,5,3,5,5,5,2,11,7.0,neutral or dissatisfied +12578,81457,Male,Loyal Customer,25,Business travel,Business,528,3,3,3,3,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +12579,37068,Male,Loyal Customer,58,Business travel,Eco,1188,2,2,2,2,2,2,2,2,3,1,2,3,2,2,8,8.0,neutral or dissatisfied +12580,99074,Male,Loyal Customer,40,Business travel,Business,453,2,5,5,5,3,3,3,2,2,2,2,4,2,1,4,0.0,neutral or dissatisfied +12581,19695,Male,Loyal Customer,48,Business travel,Business,409,3,4,4,4,3,3,4,3,3,3,3,4,3,4,19,24.0,neutral or dissatisfied +12582,90172,Female,Loyal Customer,21,Personal Travel,Eco,1084,3,5,3,4,4,3,4,4,5,5,4,3,5,4,5,11.0,neutral or dissatisfied +12583,35896,Female,Loyal Customer,29,Business travel,Eco Plus,1065,2,3,3,3,2,2,2,2,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +12584,122400,Female,Loyal Customer,50,Business travel,Business,529,4,4,4,4,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +12585,78599,Female,Loyal Customer,42,Business travel,Business,2454,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,3.0,satisfied +12586,37345,Male,Loyal Customer,72,Business travel,Eco,1069,2,4,4,4,2,2,2,2,4,2,2,2,2,2,0,0.0,neutral or dissatisfied +12587,86427,Male,Loyal Customer,24,Business travel,Business,1778,2,1,1,1,2,2,2,2,3,3,4,1,3,2,39,22.0,neutral or dissatisfied +12588,92722,Male,Loyal Customer,43,Business travel,Business,1276,2,2,3,2,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +12589,80893,Female,Loyal Customer,12,Personal Travel,Eco Plus,692,2,1,2,2,3,2,3,3,3,4,3,2,2,3,20,10.0,neutral or dissatisfied +12590,99882,Male,disloyal Customer,34,Business travel,Eco,738,3,3,3,3,2,3,2,2,1,5,3,2,3,2,0,9.0,neutral or dissatisfied +12591,102511,Female,Loyal Customer,51,Personal Travel,Eco,226,2,3,0,3,2,3,2,2,2,0,3,2,2,2,0,0.0,neutral or dissatisfied +12592,100388,Male,Loyal Customer,63,Personal Travel,Eco,1011,4,5,4,3,1,4,1,1,5,1,5,3,3,1,0,0.0,satisfied +12593,24858,Male,Loyal Customer,38,Business travel,Business,2769,1,1,1,1,2,4,3,5,5,5,5,3,5,3,13,2.0,satisfied +12594,62737,Female,Loyal Customer,47,Business travel,Business,2447,1,3,3,3,1,1,1,1,3,2,3,1,3,1,0,44.0,neutral or dissatisfied +12595,77757,Female,Loyal Customer,45,Business travel,Eco,731,5,2,2,2,2,1,1,4,4,5,4,4,4,5,4,0.0,satisfied +12596,86893,Male,disloyal Customer,26,Business travel,Business,341,4,0,4,4,4,4,4,4,4,5,5,3,5,4,23,20.0,satisfied +12597,25142,Male,Loyal Customer,13,Personal Travel,Eco,1249,3,2,3,4,5,3,1,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +12598,4961,Male,Loyal Customer,36,Personal Travel,Eco,931,4,4,4,3,5,4,5,5,4,3,5,4,5,5,0,16.0,satisfied +12599,12264,Female,Loyal Customer,28,Business travel,Business,3475,2,2,2,2,5,5,4,5,3,5,1,3,1,5,59,59.0,satisfied +12600,12137,Male,Loyal Customer,43,Business travel,Business,986,4,4,2,4,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +12601,113298,Female,Loyal Customer,51,Business travel,Business,3547,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +12602,85666,Male,Loyal Customer,31,Business travel,Business,3224,1,5,5,5,1,2,1,1,2,3,4,1,4,1,2,0.0,neutral or dissatisfied +12603,94180,Female,Loyal Customer,53,Business travel,Business,441,1,1,1,1,4,5,5,3,3,3,3,3,3,3,5,3.0,satisfied +12604,49486,Female,Loyal Customer,46,Business travel,Business,109,2,2,2,2,2,1,3,3,3,4,5,2,3,5,18,16.0,satisfied +12605,73127,Male,disloyal Customer,23,Business travel,Eco,1068,4,5,5,1,3,5,3,3,3,3,4,4,5,3,24,32.0,neutral or dissatisfied +12606,44830,Female,Loyal Customer,25,Personal Travel,Eco,462,2,4,2,2,4,2,4,4,4,5,4,2,1,4,20,27.0,neutral or dissatisfied +12607,85313,Female,Loyal Customer,60,Personal Travel,Eco,1282,1,4,1,1,5,4,5,4,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +12608,77638,Female,Loyal Customer,48,Business travel,Business,2591,1,1,2,1,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +12609,107853,Female,Loyal Customer,53,Business travel,Business,228,2,2,2,2,2,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +12610,68355,Female,Loyal Customer,51,Personal Travel,Eco,1598,0,4,0,3,4,4,5,5,5,0,5,4,5,4,0,3.0,satisfied +12611,52038,Female,Loyal Customer,47,Business travel,Eco Plus,328,5,1,1,1,1,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +12612,48981,Female,Loyal Customer,43,Business travel,Eco,373,3,4,4,4,2,5,1,2,2,3,2,4,2,2,0,0.0,satisfied +12613,53350,Male,Loyal Customer,50,Business travel,Eco,1452,5,3,3,3,4,5,4,4,1,4,4,2,2,4,0,0.0,satisfied +12614,34657,Female,Loyal Customer,44,Business travel,Business,3885,5,5,5,5,3,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +12615,48258,Male,Loyal Customer,14,Personal Travel,Eco,414,3,4,3,3,3,4,2,1,3,4,4,2,1,2,141,129.0,neutral or dissatisfied +12616,89780,Male,Loyal Customer,66,Personal Travel,Eco,944,1,2,1,3,1,1,1,1,1,4,4,4,4,1,0,0.0,neutral or dissatisfied +12617,58834,Female,Loyal Customer,51,Business travel,Business,1120,3,3,3,3,2,5,4,4,4,4,4,5,4,4,12,4.0,satisfied +12618,120526,Female,Loyal Customer,57,Business travel,Business,2531,2,5,5,5,1,4,4,4,4,4,2,4,4,1,1,0.0,neutral or dissatisfied +12619,20338,Male,Loyal Customer,33,Business travel,Business,2175,5,5,5,5,5,5,5,5,1,5,3,3,2,5,6,18.0,satisfied +12620,54028,Male,Loyal Customer,56,Business travel,Eco Plus,1091,4,4,1,4,4,4,4,4,2,4,1,2,5,4,1,0.0,satisfied +12621,74688,Male,Loyal Customer,12,Personal Travel,Eco,1235,1,4,1,4,2,1,2,2,3,2,3,4,3,2,3,0.0,neutral or dissatisfied +12622,21971,Female,Loyal Customer,35,Business travel,Eco,448,4,1,1,1,4,4,4,4,2,3,4,2,1,4,0,0.0,satisfied +12623,21690,Male,disloyal Customer,18,Business travel,Eco,746,3,2,2,4,5,2,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +12624,49421,Male,Loyal Customer,32,Business travel,Business,109,0,4,0,5,4,4,4,4,3,4,1,1,3,4,0,0.0,satisfied +12625,42784,Male,Loyal Customer,25,Business travel,Eco,1118,2,3,3,3,2,2,2,2,4,5,3,2,4,2,0,2.0,neutral or dissatisfied +12626,19737,Female,Loyal Customer,45,Personal Travel,Eco,409,2,4,2,1,4,4,4,4,4,2,3,5,4,4,0,0.0,neutral or dissatisfied +12627,80824,Male,Loyal Customer,60,Business travel,Business,2267,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +12628,28356,Male,Loyal Customer,44,Business travel,Eco Plus,867,4,3,3,3,4,4,4,4,4,3,2,4,2,4,311,319.0,satisfied +12629,44755,Male,Loyal Customer,54,Personal Travel,Eco,589,1,4,1,2,1,1,1,1,4,2,4,5,5,1,8,0.0,neutral or dissatisfied +12630,113552,Male,disloyal Customer,27,Business travel,Business,236,3,3,3,3,3,4,4,2,5,4,4,4,4,4,152,150.0,neutral or dissatisfied +12631,67533,Male,Loyal Customer,59,Business travel,Business,1235,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +12632,102708,Male,Loyal Customer,60,Business travel,Business,3118,2,2,2,2,4,4,2,5,5,5,5,3,5,2,8,3.0,satisfied +12633,118276,Male,disloyal Customer,26,Business travel,Business,639,4,4,4,5,2,4,2,2,4,4,5,3,4,2,26,22.0,neutral or dissatisfied +12634,45402,Male,disloyal Customer,18,Business travel,Eco,649,4,0,4,3,4,4,4,4,3,5,2,1,1,4,52,40.0,satisfied +12635,103124,Male,Loyal Customer,14,Personal Travel,Eco,460,1,4,1,2,5,1,4,5,4,2,5,5,5,5,29,25.0,neutral or dissatisfied +12636,80481,Female,Loyal Customer,22,Personal Travel,Eco,1299,2,4,2,1,5,2,5,5,4,5,3,3,4,5,1,0.0,neutral or dissatisfied +12637,30899,Female,Loyal Customer,45,Business travel,Business,2960,5,5,3,5,2,2,4,3,3,3,3,4,3,2,0,0.0,satisfied +12638,36314,Male,disloyal Customer,39,Business travel,Eco,395,3,3,3,3,2,3,2,2,2,2,4,1,4,2,96,89.0,neutral or dissatisfied +12639,16303,Female,Loyal Customer,33,Business travel,Business,628,5,5,5,5,4,2,3,5,5,4,5,4,5,3,0,1.0,satisfied +12640,30169,Male,Loyal Customer,16,Personal Travel,Eco,183,2,5,2,3,3,2,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +12641,95347,Female,Loyal Customer,46,Personal Travel,Eco,189,1,2,1,3,3,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +12642,28917,Female,Loyal Customer,55,Business travel,Business,954,2,3,2,3,1,3,2,2,2,2,2,1,2,2,0,10.0,neutral or dissatisfied +12643,37445,Female,Loyal Customer,50,Business travel,Eco,1076,4,3,3,3,1,4,2,4,4,4,4,2,4,3,19,0.0,satisfied +12644,108165,Male,Loyal Customer,66,Personal Travel,Eco,1105,4,5,4,4,1,4,1,1,3,3,1,2,3,1,1,1.0,neutral or dissatisfied +12645,117831,Male,Loyal Customer,56,Personal Travel,Eco,328,1,0,1,3,5,1,5,5,3,5,5,5,4,5,12,9.0,neutral or dissatisfied +12646,112298,Male,Loyal Customer,25,Business travel,Business,1671,4,2,2,2,4,4,4,4,2,5,3,2,4,4,4,0.0,neutral or dissatisfied +12647,22403,Male,Loyal Customer,54,Business travel,Eco,208,4,1,1,1,4,4,4,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +12648,61430,Female,Loyal Customer,51,Personal Travel,Business,2288,2,4,2,3,5,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +12649,35812,Male,Loyal Customer,47,Business travel,Business,1065,2,2,2,2,4,2,5,5,5,5,5,4,5,2,9,17.0,satisfied +12650,33672,Male,Loyal Customer,26,Personal Travel,Eco Plus,399,2,4,0,4,3,0,3,3,1,4,3,3,4,3,8,36.0,neutral or dissatisfied +12651,118494,Male,Loyal Customer,44,Business travel,Business,651,1,1,1,1,4,4,4,5,5,4,5,4,3,4,128,143.0,satisfied +12652,13314,Female,Loyal Customer,69,Personal Travel,Eco,448,4,5,4,1,3,4,4,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +12653,53465,Male,Loyal Customer,41,Business travel,Eco,2419,5,4,4,4,5,5,5,3,2,3,4,5,2,5,1,4.0,satisfied +12654,58424,Male,Loyal Customer,18,Business travel,Business,2829,2,3,3,3,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +12655,23897,Male,disloyal Customer,25,Business travel,Eco,589,0,0,0,3,5,0,5,5,2,2,5,5,2,5,0,0.0,satisfied +12656,64771,Male,Loyal Customer,41,Business travel,Business,551,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +12657,105910,Female,disloyal Customer,17,Business travel,Eco,283,2,4,1,3,1,1,1,1,4,4,4,4,3,1,0,0.0,neutral or dissatisfied +12658,6263,Male,Loyal Customer,44,Business travel,Business,1543,4,4,4,4,3,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +12659,63196,Female,Loyal Customer,37,Business travel,Business,1778,5,5,5,5,4,4,4,5,5,5,5,4,5,3,3,0.0,satisfied +12660,111552,Female,Loyal Customer,47,Business travel,Business,2817,1,1,1,1,5,5,5,5,5,4,5,3,5,5,54,61.0,satisfied +12661,90123,Male,Loyal Customer,41,Business travel,Business,1635,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +12662,3389,Female,Loyal Customer,37,Business travel,Business,3213,1,4,4,4,1,4,3,1,1,1,1,3,1,2,0,25.0,neutral or dissatisfied +12663,30283,Male,Loyal Customer,33,Business travel,Eco Plus,1024,5,3,3,3,5,5,5,5,2,2,3,1,1,5,2,0.0,satisfied +12664,42302,Male,Loyal Customer,33,Personal Travel,Eco,462,4,5,4,3,4,4,4,4,5,3,5,5,5,4,28,15.0,satisfied +12665,31774,Male,Loyal Customer,25,Personal Travel,Eco,602,4,5,4,2,4,4,4,4,5,1,3,1,2,4,1,0.0,neutral or dissatisfied +12666,86158,Female,Loyal Customer,40,Business travel,Business,2439,3,3,3,3,2,4,5,5,5,4,5,4,5,4,73,69.0,satisfied +12667,92163,Female,Loyal Customer,59,Personal Travel,Business,1979,2,1,2,3,2,4,3,2,2,2,3,3,2,3,0,0.0,neutral or dissatisfied +12668,97291,Male,disloyal Customer,24,Business travel,Eco,872,4,4,4,1,3,4,3,3,5,5,4,4,5,3,27,27.0,neutral or dissatisfied +12669,101015,Male,Loyal Customer,53,Business travel,Business,3979,2,2,4,4,1,3,3,2,2,2,2,2,2,1,95,74.0,neutral or dissatisfied +12670,39773,Female,Loyal Customer,31,Business travel,Business,2519,4,4,5,4,2,2,2,2,1,2,3,3,4,2,4,0.0,satisfied +12671,85509,Male,Loyal Customer,28,Personal Travel,Eco,332,2,5,2,1,2,2,2,2,3,2,5,5,5,2,14,8.0,neutral or dissatisfied +12672,127067,Male,disloyal Customer,17,Business travel,Eco,370,4,5,4,3,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +12673,87418,Female,Loyal Customer,43,Personal Travel,Eco,425,1,4,1,3,1,2,4,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +12674,29202,Male,Loyal Customer,13,Personal Travel,Eco Plus,978,2,4,2,3,2,2,1,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +12675,6533,Male,Loyal Customer,56,Business travel,Business,2432,4,4,4,4,5,4,4,4,4,4,4,5,4,3,20,19.0,satisfied +12676,48794,Female,disloyal Customer,39,Business travel,Business,199,2,2,2,4,5,2,5,5,2,2,4,1,4,5,62,59.0,neutral or dissatisfied +12677,36382,Male,Loyal Customer,46,Personal Travel,Eco,200,4,2,4,2,5,4,5,5,1,4,2,2,3,5,0,0.0,satisfied +12678,90217,Male,Loyal Customer,54,Personal Travel,Eco,1145,2,2,1,4,4,1,5,4,4,5,2,2,4,4,21,12.0,neutral or dissatisfied +12679,108939,Male,Loyal Customer,45,Personal Travel,Eco,1066,1,2,1,4,3,1,3,3,1,2,3,1,4,3,18,15.0,neutral or dissatisfied +12680,128019,Female,Loyal Customer,43,Business travel,Business,1440,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +12681,10071,Female,Loyal Customer,36,Business travel,Business,2196,3,4,5,4,3,4,3,3,3,3,3,3,3,3,29,32.0,neutral or dissatisfied +12682,5285,Female,Loyal Customer,63,Personal Travel,Eco,351,1,5,1,3,2,4,4,2,2,1,4,3,2,4,11,12.0,neutral or dissatisfied +12683,12882,Male,disloyal Customer,40,Business travel,Eco,563,5,2,5,1,4,5,4,4,3,3,3,2,3,4,77,79.0,satisfied +12684,53806,Female,Loyal Customer,33,Business travel,Eco,191,4,3,3,3,4,4,4,4,4,4,4,5,1,4,0,0.0,satisfied +12685,88131,Female,Loyal Customer,50,Business travel,Business,3221,5,5,5,5,3,4,5,4,4,4,4,3,4,5,0,17.0,satisfied +12686,46624,Male,Loyal Customer,41,Business travel,Business,2061,1,1,4,1,4,3,3,5,5,5,3,4,5,2,0,0.0,satisfied +12687,1832,Female,Loyal Customer,48,Personal Travel,Eco,408,0,2,0,4,5,4,4,4,4,0,4,4,4,3,0,0.0,satisfied +12688,64856,Male,Loyal Customer,56,Business travel,Business,3836,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +12689,31797,Female,Loyal Customer,45,Personal Travel,Eco,2640,4,4,4,3,2,4,5,4,4,4,3,4,4,4,0,,neutral or dissatisfied +12690,26532,Female,Loyal Customer,33,Business travel,Eco,990,4,5,5,5,4,4,4,4,2,3,2,4,2,4,6,8.0,neutral or dissatisfied +12691,109406,Male,Loyal Customer,12,Personal Travel,Eco Plus,1046,1,4,1,1,3,1,3,3,5,4,5,5,5,3,24,11.0,neutral or dissatisfied +12692,65677,Male,Loyal Customer,15,Personal Travel,Eco,1021,4,3,4,3,3,4,3,3,3,1,4,2,3,3,53,49.0,satisfied +12693,41782,Male,Loyal Customer,49,Personal Travel,Eco,508,3,4,3,5,5,3,5,5,5,3,5,5,5,5,0,8.0,neutral or dissatisfied +12694,91291,Male,Loyal Customer,34,Business travel,Business,2664,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +12695,24910,Female,Loyal Customer,24,Business travel,Business,1505,1,1,1,1,5,5,5,5,4,4,2,2,1,5,4,0.0,satisfied +12696,63303,Male,Loyal Customer,47,Business travel,Business,2292,2,5,5,5,4,3,4,2,2,2,2,3,2,2,5,0.0,neutral or dissatisfied +12697,51501,Male,Loyal Customer,27,Business travel,Business,370,4,4,4,4,4,4,4,4,5,1,5,3,3,4,88,105.0,satisfied +12698,1173,Female,Loyal Customer,29,Personal Travel,Eco,164,2,5,2,4,1,2,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +12699,6093,Female,Loyal Customer,16,Personal Travel,Eco Plus,691,2,4,1,4,2,1,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +12700,61108,Male,Loyal Customer,25,Personal Travel,Eco,1709,3,4,4,5,1,4,1,1,2,3,5,3,1,1,0,5.0,neutral or dissatisfied +12701,41728,Male,Loyal Customer,23,Business travel,Business,3694,2,2,3,2,4,4,4,4,1,3,2,2,3,4,0,0.0,satisfied +12702,128832,Male,Loyal Customer,31,Business travel,Business,2586,3,3,3,3,5,5,5,1,1,4,5,5,4,5,1,18.0,satisfied +12703,4210,Female,Loyal Customer,50,Business travel,Eco,888,2,4,1,1,5,3,4,1,1,2,1,1,1,3,6,0.0,neutral or dissatisfied +12704,79533,Male,Loyal Customer,25,Business travel,Business,3142,4,4,4,4,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +12705,121250,Male,Loyal Customer,57,Business travel,Business,2075,4,4,4,4,3,4,4,4,4,2,3,4,1,4,0,41.0,neutral or dissatisfied +12706,128771,Female,Loyal Customer,70,Personal Travel,Eco,550,2,4,2,3,4,2,3,4,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +12707,114888,Female,Loyal Customer,41,Business travel,Business,2229,3,3,3,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +12708,39939,Male,Loyal Customer,23,Business travel,Eco,1087,0,4,0,1,2,0,2,2,3,3,2,5,3,2,0,0.0,satisfied +12709,111162,Female,Loyal Customer,9,Personal Travel,Eco,1111,1,3,1,3,4,1,4,4,1,2,4,2,3,4,8,0.0,neutral or dissatisfied +12710,66093,Male,Loyal Customer,44,Business travel,Eco Plus,1055,2,3,3,3,2,2,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +12711,31621,Male,Loyal Customer,27,Business travel,Business,853,4,1,4,4,5,5,5,5,4,1,1,4,1,5,0,0.0,satisfied +12712,106038,Male,Loyal Customer,53,Business travel,Business,3571,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,1.0,satisfied +12713,69206,Male,Loyal Customer,61,Personal Travel,Business,733,1,3,1,3,3,4,1,5,5,1,1,4,5,2,18,40.0,neutral or dissatisfied +12714,3915,Female,Loyal Customer,55,Personal Travel,Eco,213,5,4,5,4,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +12715,114894,Male,disloyal Customer,44,Business travel,Business,337,4,4,4,1,2,4,2,2,4,5,4,3,4,2,8,8.0,satisfied +12716,19686,Female,Loyal Customer,35,Business travel,Business,409,2,2,2,2,2,1,5,4,4,4,4,3,4,4,11,0.0,satisfied +12717,62106,Female,Loyal Customer,49,Business travel,Eco,2454,1,4,5,4,5,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +12718,28183,Female,Loyal Customer,46,Personal Travel,Eco,834,0,5,0,2,4,4,2,4,4,0,4,2,4,3,0,0.0,satisfied +12719,30874,Male,Loyal Customer,15,Business travel,Business,1607,4,4,4,4,5,5,5,5,4,2,5,1,3,5,0,0.0,satisfied +12720,125517,Female,disloyal Customer,42,Business travel,Business,226,1,1,1,2,3,1,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +12721,122654,Male,Loyal Customer,54,Business travel,Business,2101,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +12722,103709,Female,Loyal Customer,53,Personal Travel,Eco,405,3,5,3,3,5,1,5,2,2,3,2,1,2,5,9,5.0,neutral or dissatisfied +12723,85263,Male,Loyal Customer,25,Personal Travel,Eco,813,1,1,1,2,5,1,5,5,4,2,2,3,3,5,2,0.0,neutral or dissatisfied +12724,85938,Female,Loyal Customer,58,Personal Travel,Business,432,2,4,2,3,4,2,4,1,1,2,1,1,1,4,27,31.0,neutral or dissatisfied +12725,71357,Female,Loyal Customer,39,Business travel,Business,2801,2,2,2,2,2,5,4,5,5,5,5,4,5,5,44,39.0,satisfied +12726,20493,Female,disloyal Customer,21,Business travel,Business,130,3,3,3,4,1,3,2,1,1,1,4,3,3,1,22,37.0,neutral or dissatisfied +12727,37023,Male,Loyal Customer,59,Personal Travel,Eco Plus,814,1,0,1,3,1,4,3,2,5,3,3,3,2,3,293,302.0,neutral or dissatisfied +12728,58354,Male,Loyal Customer,20,Business travel,Business,3360,3,3,3,3,5,4,5,5,3,2,4,4,5,5,0,0.0,satisfied +12729,44255,Female,Loyal Customer,23,Business travel,Business,222,3,3,3,3,4,4,4,4,4,5,2,5,5,4,0,12.0,satisfied +12730,129243,Male,Loyal Customer,50,Business travel,Business,2244,1,4,4,4,5,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +12731,118495,Male,Loyal Customer,57,Business travel,Business,3455,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +12732,21444,Male,Loyal Customer,43,Business travel,Eco,377,3,2,2,2,4,3,4,4,3,1,4,1,3,4,84,79.0,neutral or dissatisfied +12733,94709,Female,Loyal Customer,36,Business travel,Business,2649,4,1,1,1,1,4,3,4,4,4,4,4,4,4,2,4.0,neutral or dissatisfied +12734,65256,Female,Loyal Customer,19,Business travel,Business,3201,4,4,4,4,4,4,5,4,5,4,5,5,4,4,0,4.0,satisfied +12735,45712,Male,Loyal Customer,47,Business travel,Eco,852,3,2,2,2,3,3,3,3,3,3,1,4,4,3,18,18.0,satisfied +12736,61416,Female,Loyal Customer,41,Business travel,Business,2548,2,2,2,2,4,5,4,5,5,5,5,3,5,3,3,0.0,satisfied +12737,86975,Male,Loyal Customer,48,Business travel,Business,2932,4,3,3,3,5,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +12738,25802,Male,Loyal Customer,51,Personal Travel,Eco,762,3,5,3,1,1,3,1,1,3,4,5,4,4,1,18,46.0,neutral or dissatisfied +12739,13613,Female,Loyal Customer,37,Business travel,Eco Plus,106,4,3,3,3,4,4,4,4,4,4,5,2,3,4,0,0.0,satisfied +12740,99700,Female,Loyal Customer,49,Personal Travel,Eco,442,5,5,5,1,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +12741,123471,Male,Loyal Customer,30,Business travel,Business,2296,1,1,1,1,1,1,1,1,4,4,4,2,4,1,47,27.0,neutral or dissatisfied +12742,103856,Female,Loyal Customer,47,Personal Travel,Eco,1056,1,4,1,2,3,3,5,5,5,1,3,3,5,5,34,65.0,neutral or dissatisfied +12743,25667,Male,disloyal Customer,45,Business travel,Eco,761,3,2,2,2,3,2,3,3,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +12744,122023,Male,Loyal Customer,56,Business travel,Business,130,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +12745,35105,Male,disloyal Customer,38,Business travel,Eco,944,3,3,3,2,3,1,1,3,1,2,4,1,1,1,566,600.0,neutral or dissatisfied +12746,129246,Male,Loyal Customer,61,Personal Travel,Eco,1464,5,5,5,3,4,5,4,4,4,5,5,5,5,4,0,0.0,satisfied +12747,39225,Male,Loyal Customer,44,Business travel,Eco,268,4,5,5,5,4,3,3,5,2,4,3,3,5,3,203,203.0,satisfied +12748,96812,Male,Loyal Customer,32,Business travel,Business,1669,3,3,3,3,4,4,4,4,4,5,4,4,5,4,0,17.0,satisfied +12749,103810,Male,Loyal Customer,47,Business travel,Business,3473,4,4,4,4,2,5,4,5,5,4,5,5,5,5,1,0.0,satisfied +12750,55964,Male,Loyal Customer,40,Business travel,Business,1620,1,1,1,1,4,4,4,4,4,4,4,5,4,4,14,19.0,satisfied +12751,31062,Male,disloyal Customer,20,Business travel,Eco,241,4,3,4,1,3,4,3,3,5,4,5,5,4,3,0,6.0,neutral or dissatisfied +12752,15959,Male,Loyal Customer,62,Personal Travel,Eco,607,3,5,3,3,3,3,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +12753,57723,Female,Loyal Customer,41,Business travel,Business,1754,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,28.0,satisfied +12754,28175,Male,Loyal Customer,23,Personal Travel,Eco,834,5,5,5,1,3,5,1,3,2,5,4,1,4,3,0,0.0,satisfied +12755,28767,Male,Loyal Customer,10,Personal Travel,Eco,1024,4,5,4,3,2,4,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +12756,103113,Female,Loyal Customer,39,Personal Travel,Eco,460,3,3,3,4,2,3,2,2,4,2,3,3,3,2,0,3.0,neutral or dissatisfied +12757,39398,Male,Loyal Customer,34,Business travel,Eco,521,4,4,3,4,4,4,4,4,2,3,4,3,1,4,0,0.0,satisfied +12758,46646,Male,disloyal Customer,24,Business travel,Eco,125,3,0,4,4,5,4,5,5,4,3,4,1,2,5,0,11.0,neutral or dissatisfied +12759,73028,Male,Loyal Customer,7,Personal Travel,Eco,1089,1,3,1,5,4,1,4,4,1,2,3,4,2,4,0,0.0,neutral or dissatisfied +12760,129691,Male,Loyal Customer,29,Business travel,Business,337,3,3,3,3,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +12761,93979,Male,disloyal Customer,23,Business travel,Eco,1218,2,3,3,3,2,3,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +12762,38366,Male,Loyal Customer,52,Personal Travel,Eco,1133,4,4,4,3,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +12763,18565,Male,Loyal Customer,62,Business travel,Business,253,0,0,0,1,4,3,3,5,5,5,5,2,5,5,0,0.0,satisfied +12764,108232,Male,Loyal Customer,47,Business travel,Business,3750,3,3,5,3,4,4,4,5,5,5,5,4,5,5,76,79.0,satisfied +12765,71674,Female,Loyal Customer,59,Personal Travel,Eco,1197,2,3,2,3,2,3,4,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +12766,29008,Female,Loyal Customer,22,Business travel,Business,3683,5,5,5,5,3,3,3,3,1,2,1,1,5,3,0,0.0,satisfied +12767,12007,Female,Loyal Customer,56,Business travel,Business,2356,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +12768,69039,Male,Loyal Customer,43,Business travel,Business,1389,5,5,5,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +12769,90721,Female,Loyal Customer,54,Business travel,Business,3830,2,4,2,2,4,4,5,5,5,5,5,4,5,4,2,2.0,satisfied +12770,36833,Female,Loyal Customer,44,Business travel,Eco,369,4,4,4,4,3,2,3,4,4,4,4,1,4,1,0,0.0,satisfied +12771,56524,Female,Loyal Customer,45,Business travel,Business,937,5,5,5,5,3,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +12772,82816,Male,Loyal Customer,29,Business travel,Business,594,3,3,3,3,5,4,5,5,5,2,4,3,5,5,0,0.0,satisfied +12773,71521,Female,disloyal Customer,22,Business travel,Eco,1120,4,4,4,3,5,4,5,5,5,3,4,3,5,5,19,2.0,satisfied +12774,120943,Male,Loyal Customer,25,Business travel,Business,2727,2,2,2,2,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +12775,124317,Male,Loyal Customer,7,Personal Travel,Eco,255,4,0,4,2,5,4,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +12776,16679,Female,Loyal Customer,31,Personal Travel,Eco,488,2,5,2,3,4,2,2,4,3,3,2,1,2,4,3,19.0,neutral or dissatisfied +12777,107408,Female,Loyal Customer,26,Business travel,Business,2251,3,5,5,5,3,3,3,3,3,2,3,4,4,3,11,9.0,neutral or dissatisfied +12778,10038,Female,Loyal Customer,33,Personal Travel,Eco,630,1,3,1,3,1,1,1,1,4,3,4,1,4,1,151,158.0,neutral or dissatisfied +12779,58260,Male,Loyal Customer,18,Business travel,Business,2072,4,4,4,4,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +12780,22771,Female,Loyal Customer,36,Business travel,Business,2831,1,1,1,1,2,5,2,4,4,4,4,3,4,1,8,0.0,satisfied +12781,65041,Male,Loyal Customer,66,Personal Travel,Eco,282,4,2,4,3,2,4,2,2,1,1,4,4,4,2,0,0.0,satisfied +12782,11251,Male,Loyal Customer,11,Personal Travel,Eco,312,2,4,2,3,2,2,1,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +12783,66761,Female,Loyal Customer,59,Personal Travel,Eco,802,1,2,1,4,3,3,3,5,5,1,4,1,5,1,0,0.0,neutral or dissatisfied +12784,91556,Female,Loyal Customer,50,Personal Travel,Eco,680,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +12785,117368,Male,Loyal Customer,27,Personal Travel,Eco,296,2,4,2,3,2,2,2,2,4,5,4,4,5,2,20,15.0,neutral or dissatisfied +12786,126795,Male,Loyal Customer,50,Business travel,Business,2125,2,2,2,2,2,5,5,4,4,5,4,5,4,3,0,21.0,satisfied +12787,63434,Female,Loyal Customer,62,Personal Travel,Eco,337,1,1,4,4,4,5,4,1,2,4,3,4,3,4,185,180.0,neutral or dissatisfied +12788,46069,Male,Loyal Customer,31,Business travel,Business,3634,3,3,3,3,5,5,5,5,5,1,5,3,5,5,0,16.0,satisfied +12789,66593,Female,disloyal Customer,62,Business travel,Eco,761,2,2,2,4,1,2,1,1,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +12790,101376,Male,disloyal Customer,27,Business travel,Business,486,5,5,5,3,4,5,4,4,4,2,5,5,4,4,21,13.0,satisfied +12791,22366,Male,Loyal Customer,33,Business travel,Business,83,3,5,5,5,2,2,3,2,2,5,4,1,3,2,0,0.0,neutral or dissatisfied +12792,82420,Male,Loyal Customer,41,Business travel,Business,3429,1,1,1,1,3,5,4,4,4,4,4,4,4,5,2,0.0,satisfied +12793,122232,Female,disloyal Customer,50,Business travel,Eco,544,1,1,1,4,4,1,2,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +12794,36313,Male,Loyal Customer,33,Business travel,Business,2112,3,3,3,3,5,5,4,5,1,1,4,2,3,5,0,0.0,satisfied +12795,121310,Male,Loyal Customer,66,Business travel,Business,1880,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +12796,28123,Male,disloyal Customer,10,Business travel,Eco,550,4,0,4,1,3,4,3,3,2,2,4,4,3,3,0,0.0,satisfied +12797,96888,Female,Loyal Customer,63,Personal Travel,Eco,1041,1,4,1,2,2,5,4,2,2,1,2,5,2,3,3,28.0,neutral or dissatisfied +12798,129303,Male,Loyal Customer,51,Business travel,Business,2586,3,3,3,3,4,1,2,3,3,3,3,1,3,2,3,0.0,neutral or dissatisfied +12799,4971,Male,Loyal Customer,13,Personal Travel,Eco Plus,931,2,4,2,5,3,2,3,3,5,4,5,5,4,3,0,23.0,neutral or dissatisfied +12800,112351,Male,disloyal Customer,24,Business travel,Eco,909,5,5,5,3,5,5,5,5,4,3,5,5,5,5,22,2.0,satisfied +12801,78737,Female,Loyal Customer,58,Business travel,Business,1504,5,5,5,5,4,5,4,4,4,5,4,3,4,5,6,0.0,satisfied +12802,65829,Male,Loyal Customer,59,Business travel,Business,1389,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +12803,102483,Male,Loyal Customer,70,Personal Travel,Eco,223,2,1,0,1,3,0,1,3,3,5,1,1,2,3,60,53.0,neutral or dissatisfied +12804,27312,Male,Loyal Customer,32,Business travel,Business,3386,4,4,4,4,4,4,4,4,3,4,4,4,4,4,0,4.0,satisfied +12805,92838,Female,Loyal Customer,49,Personal Travel,Eco,1587,3,4,3,4,5,4,5,4,4,3,5,3,4,5,35,12.0,neutral or dissatisfied +12806,37861,Female,Loyal Customer,41,Business travel,Business,937,3,3,3,3,5,4,2,5,5,5,5,3,5,5,0,0.0,satisfied +12807,39861,Male,disloyal Customer,20,Business travel,Eco,272,1,5,1,4,3,1,4,3,3,4,3,1,1,3,0,0.0,neutral or dissatisfied +12808,100925,Male,Loyal Customer,48,Business travel,Business,2579,4,4,4,4,5,4,4,3,3,4,3,3,3,3,30,,satisfied +12809,52548,Female,disloyal Customer,33,Business travel,Eco,119,2,0,2,4,1,2,1,1,3,3,1,5,1,1,0,0.0,neutral or dissatisfied +12810,15275,Female,Loyal Customer,56,Business travel,Eco,460,3,1,5,1,2,3,4,3,3,3,3,4,3,2,0,7.0,neutral or dissatisfied +12811,81632,Male,disloyal Customer,19,Business travel,Eco,907,1,1,1,1,3,1,3,3,3,5,4,4,4,3,27,54.0,neutral or dissatisfied +12812,30530,Female,Loyal Customer,40,Personal Travel,Eco,532,1,4,1,3,1,1,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +12813,35112,Male,Loyal Customer,52,Business travel,Eco,944,4,2,2,2,4,4,4,4,4,4,4,4,3,4,0,0.0,satisfied +12814,119119,Male,Loyal Customer,50,Personal Travel,Eco,1020,2,4,1,3,3,1,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +12815,41011,Male,Loyal Customer,46,Business travel,Business,3930,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +12816,702,Female,Loyal Customer,34,Business travel,Business,158,4,4,4,4,3,5,4,5,5,5,4,4,5,4,6,0.0,satisfied +12817,122481,Male,Loyal Customer,39,Personal Travel,Eco,575,2,4,2,2,1,2,1,1,3,5,4,4,5,1,16,27.0,neutral or dissatisfied +12818,127823,Female,Loyal Customer,18,Personal Travel,Eco,1044,2,2,2,3,2,2,2,2,1,5,3,1,4,2,0,10.0,neutral or dissatisfied +12819,24801,Female,Loyal Customer,70,Business travel,Eco Plus,432,4,2,2,2,1,4,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +12820,46979,Male,Loyal Customer,60,Personal Travel,Eco,737,1,4,1,3,2,1,1,2,5,5,5,4,5,2,19,7.0,neutral or dissatisfied +12821,57097,Male,disloyal Customer,26,Business travel,Business,1222,2,2,2,2,2,2,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +12822,103542,Female,Loyal Customer,56,Business travel,Eco,738,2,4,4,4,2,2,2,4,4,4,4,2,3,2,225,215.0,neutral or dissatisfied +12823,56304,Male,Loyal Customer,29,Personal Travel,Eco Plus,2227,5,1,5,3,2,1,2,2,1,3,2,1,3,2,0,0.0,satisfied +12824,122339,Male,Loyal Customer,57,Business travel,Business,2636,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +12825,20115,Female,Loyal Customer,58,Business travel,Business,466,4,5,5,5,5,2,2,4,4,4,4,3,4,2,14,12.0,neutral or dissatisfied +12826,63523,Male,Loyal Customer,60,Business travel,Business,2794,2,1,1,1,1,3,4,2,2,1,2,1,2,1,3,0.0,neutral or dissatisfied +12827,11235,Male,Loyal Customer,28,Personal Travel,Eco,163,4,4,4,3,1,4,1,1,4,2,2,2,1,1,0,0.0,neutral or dissatisfied +12828,1618,Male,Loyal Customer,13,Personal Travel,Business,999,2,4,2,3,3,2,3,3,3,2,5,4,4,3,5,11.0,neutral or dissatisfied +12829,49128,Female,disloyal Customer,36,Business travel,Eco,193,3,4,3,3,5,3,5,5,4,1,1,3,4,5,0,35.0,neutral or dissatisfied +12830,116055,Female,Loyal Customer,36,Personal Travel,Eco,447,3,5,3,3,5,3,5,5,5,2,4,5,4,5,6,12.0,neutral or dissatisfied +12831,80718,Male,Loyal Customer,29,Personal Travel,Eco,920,3,5,3,3,3,3,3,3,3,4,4,5,5,3,67,85.0,neutral or dissatisfied +12832,126661,Female,Loyal Customer,67,Personal Travel,Eco,602,2,4,2,1,3,4,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +12833,65301,Female,Loyal Customer,44,Personal Travel,Eco Plus,247,2,4,2,2,4,5,4,3,3,2,3,5,3,5,9,3.0,neutral or dissatisfied +12834,72574,Male,Loyal Customer,17,Business travel,Business,3268,2,2,2,2,2,3,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +12835,105499,Male,Loyal Customer,52,Business travel,Business,3228,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +12836,119070,Male,Loyal Customer,27,Business travel,Business,2534,2,2,2,2,5,4,5,5,3,3,4,3,4,5,0,0.0,satisfied +12837,89063,Female,Loyal Customer,55,Business travel,Business,1947,3,3,3,3,4,3,4,5,5,5,5,4,5,5,23,13.0,satisfied +12838,27169,Female,Loyal Customer,66,Personal Travel,Eco,2701,3,4,2,3,2,3,3,5,4,4,5,3,4,3,0,20.0,neutral or dissatisfied +12839,9670,Male,Loyal Customer,40,Business travel,Business,199,2,2,2,2,4,5,4,5,5,5,4,5,5,4,4,0.0,satisfied +12840,36402,Female,Loyal Customer,24,Business travel,Eco,632,4,4,4,4,4,4,4,4,2,3,4,2,3,4,0,0.0,neutral or dissatisfied +12841,997,Male,Loyal Customer,56,Business travel,Eco,89,5,4,4,4,5,5,5,5,3,4,2,1,5,5,0,2.0,satisfied +12842,110581,Female,Loyal Customer,44,Business travel,Business,488,2,5,5,5,5,1,2,2,2,2,2,1,2,4,102,96.0,neutral or dissatisfied +12843,78663,Male,Loyal Customer,48,Business travel,Business,3640,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +12844,128898,Female,Loyal Customer,24,Personal Travel,Eco,2565,2,0,2,3,2,1,1,1,4,4,3,1,2,1,1,0.0,neutral or dissatisfied +12845,25223,Female,Loyal Customer,22,Business travel,Eco,842,3,3,3,3,3,3,2,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +12846,52327,Female,Loyal Customer,35,Business travel,Business,370,2,3,2,2,4,3,3,2,2,2,2,4,2,3,23,22.0,neutral or dissatisfied +12847,71533,Female,disloyal Customer,24,Business travel,Business,1012,5,0,5,2,2,5,2,2,5,3,4,5,5,2,0,0.0,satisfied +12848,18747,Female,disloyal Customer,26,Business travel,Eco,1167,4,4,4,4,1,4,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +12849,16152,Female,Loyal Customer,42,Business travel,Business,212,4,4,4,4,1,1,3,5,5,5,5,3,5,5,107,122.0,satisfied +12850,109182,Male,Loyal Customer,33,Business travel,Business,3124,3,4,4,4,3,3,3,3,1,5,4,2,3,3,21,12.0,neutral or dissatisfied +12851,104067,Female,disloyal Customer,25,Business travel,Eco Plus,1262,3,0,3,3,5,3,5,5,4,5,5,1,1,5,0,0.0,neutral or dissatisfied +12852,107320,Male,Loyal Customer,16,Personal Travel,Eco Plus,307,4,4,4,2,4,3,3,3,5,4,4,3,3,3,131,145.0,neutral or dissatisfied +12853,106383,Female,Loyal Customer,57,Business travel,Business,1978,1,1,1,1,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +12854,4135,Male,Loyal Customer,42,Business travel,Business,3757,4,4,4,4,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +12855,92795,Female,Loyal Customer,9,Personal Travel,Business,1587,3,5,3,2,1,3,1,1,5,3,4,3,4,1,7,0.0,neutral or dissatisfied +12856,81720,Female,disloyal Customer,24,Business travel,Eco,1310,3,3,3,3,4,3,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +12857,11760,Female,disloyal Customer,20,Business travel,Eco,429,3,4,3,2,4,3,4,4,4,5,2,3,5,4,0,0.0,neutral or dissatisfied +12858,25960,Female,Loyal Customer,21,Business travel,Business,2460,1,2,2,2,1,1,1,1,1,1,1,3,2,1,15,11.0,neutral or dissatisfied +12859,77583,Female,Loyal Customer,46,Business travel,Business,1773,4,4,4,4,5,5,5,4,4,4,4,3,4,4,2,0.0,satisfied +12860,70996,Male,disloyal Customer,27,Business travel,Eco,978,2,2,2,2,1,2,1,1,1,4,2,2,3,1,83,88.0,neutral or dissatisfied +12861,110344,Male,Loyal Customer,38,Business travel,Business,1674,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +12862,48462,Female,Loyal Customer,28,Business travel,Eco,853,5,2,4,2,5,5,5,5,2,5,3,1,1,5,5,2.0,satisfied +12863,123972,Male,Loyal Customer,46,Business travel,Business,2089,3,3,4,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +12864,56090,Female,Loyal Customer,18,Personal Travel,Eco Plus,2475,4,4,4,5,4,4,4,5,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +12865,99159,Female,Loyal Customer,52,Business travel,Business,986,1,1,1,1,4,4,5,5,5,5,5,5,5,4,4,0.0,satisfied +12866,10535,Male,Loyal Customer,35,Business travel,Business,2400,2,5,2,2,5,4,4,2,2,2,2,3,2,3,63,55.0,satisfied +12867,43470,Male,Loyal Customer,48,Business travel,Eco,752,5,5,3,3,5,5,5,5,1,5,4,3,4,5,45,48.0,satisfied +12868,61429,Male,Loyal Customer,13,Personal Travel,Business,2442,1,5,1,1,1,1,1,1,4,4,5,3,1,1,0,0.0,neutral or dissatisfied +12869,60083,Male,Loyal Customer,42,Business travel,Business,3259,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +12870,15811,Male,Loyal Customer,26,Personal Travel,Eco,143,2,1,2,4,5,2,2,5,3,2,4,1,4,5,1,0.0,neutral or dissatisfied +12871,5730,Male,Loyal Customer,31,Personal Travel,Eco Plus,196,2,5,2,3,2,2,2,2,5,2,3,1,4,2,0,13.0,neutral or dissatisfied +12872,70964,Male,Loyal Customer,21,Personal Travel,Business,802,2,4,2,5,5,2,5,5,2,4,3,3,4,5,14,5.0,neutral or dissatisfied +12873,74259,Male,Loyal Customer,69,Personal Travel,Eco Plus,1810,3,3,3,3,5,3,5,5,2,1,3,3,1,5,0,0.0,neutral or dissatisfied +12874,126426,Female,Loyal Customer,38,Business travel,Eco Plus,507,4,5,5,5,4,4,4,4,3,1,2,2,3,4,0,8.0,neutral or dissatisfied +12875,66597,Male,Loyal Customer,28,Business travel,Business,761,2,3,3,3,2,2,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +12876,18026,Female,Loyal Customer,68,Personal Travel,Business,488,3,0,3,2,3,4,5,5,5,3,5,3,5,3,5,0.0,neutral or dissatisfied +12877,100369,Female,Loyal Customer,7,Personal Travel,Eco,1130,2,5,2,4,5,2,5,5,3,2,3,3,5,5,0,0.0,neutral or dissatisfied +12878,51246,Female,Loyal Customer,36,Business travel,Eco Plus,308,2,2,2,2,2,2,2,2,2,1,4,5,3,2,0,0.0,satisfied +12879,67348,Male,Loyal Customer,67,Personal Travel,Eco,1471,2,5,2,5,4,2,4,4,3,5,3,5,5,4,21,1.0,neutral or dissatisfied +12880,121608,Male,Loyal Customer,49,Personal Travel,Eco,912,3,4,3,3,2,3,2,2,3,3,5,3,4,2,23,17.0,neutral or dissatisfied +12881,13747,Male,disloyal Customer,34,Business travel,Eco,401,2,3,3,5,4,3,2,4,2,3,3,4,2,4,0,0.0,neutral or dissatisfied +12882,93881,Female,Loyal Customer,41,Business travel,Business,2741,2,2,2,2,2,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +12883,98749,Female,Loyal Customer,38,Personal Travel,Eco,1558,2,5,3,3,3,3,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +12884,111853,Male,Loyal Customer,30,Business travel,Business,3386,4,4,4,4,4,4,4,4,4,2,4,4,5,4,31,10.0,satisfied +12885,88789,Male,Loyal Customer,62,Business travel,Eco Plus,404,2,3,3,3,2,2,2,2,4,1,4,4,4,2,12,15.0,neutral or dissatisfied +12886,22358,Female,Loyal Customer,35,Business travel,Eco,238,3,2,2,2,3,3,3,3,4,2,3,5,3,3,0,0.0,satisfied +12887,100577,Female,Loyal Customer,49,Business travel,Business,3598,2,2,2,2,2,5,4,4,4,4,4,3,4,3,10,5.0,satisfied +12888,92321,Male,Loyal Customer,47,Business travel,Business,2399,2,2,2,2,5,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +12889,6148,Female,Loyal Customer,50,Business travel,Business,2358,3,2,2,2,1,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +12890,108707,Female,Loyal Customer,44,Business travel,Eco,425,2,5,5,5,4,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +12891,27961,Male,Loyal Customer,19,Personal Travel,Eco,1770,2,3,2,2,5,2,5,5,1,3,3,2,3,5,8,0.0,neutral or dissatisfied +12892,76761,Female,Loyal Customer,41,Business travel,Business,689,5,5,5,5,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +12893,114068,Female,Loyal Customer,42,Business travel,Business,1947,2,2,2,2,5,5,4,3,3,4,3,5,3,5,23,0.0,satisfied +12894,95586,Male,Loyal Customer,28,Business travel,Business,670,2,5,2,5,2,2,2,2,2,4,3,3,3,2,41,43.0,neutral or dissatisfied +12895,65421,Female,Loyal Customer,43,Business travel,Business,2165,2,2,4,2,3,4,4,5,5,5,5,4,5,3,24,4.0,satisfied +12896,48507,Male,disloyal Customer,23,Business travel,Eco,776,1,0,0,5,5,0,5,5,3,2,2,5,1,5,0,0.0,neutral or dissatisfied +12897,60202,Male,Loyal Customer,24,Personal Travel,Business,1703,4,3,4,3,5,4,1,5,5,4,3,1,1,5,66,46.0,neutral or dissatisfied +12898,64672,Male,Loyal Customer,38,Business travel,Business,3078,5,4,5,5,5,5,5,4,4,4,5,5,4,5,0,4.0,satisfied +12899,48047,Male,Loyal Customer,47,Business travel,Eco,677,4,5,5,5,3,4,3,3,2,1,5,2,2,3,0,0.0,satisfied +12900,49310,Female,Loyal Customer,47,Business travel,Eco,363,4,4,4,4,2,2,5,5,5,4,5,4,5,3,87,80.0,satisfied +12901,56913,Male,Loyal Customer,33,Business travel,Business,2565,4,5,5,5,4,4,4,1,5,1,3,4,3,4,35,31.0,neutral or dissatisfied +12902,69535,Male,Loyal Customer,51,Business travel,Business,2475,3,3,4,3,4,4,4,4,4,3,4,4,3,4,2,0.0,satisfied +12903,114734,Male,Loyal Customer,30,Business travel,Business,308,5,5,3,5,4,4,4,4,5,5,4,4,5,4,62,61.0,satisfied +12904,38244,Male,Loyal Customer,47,Business travel,Business,3120,1,1,1,1,4,4,4,4,2,1,5,4,4,4,190,180.0,satisfied +12905,9248,Male,Loyal Customer,35,Personal Travel,Eco,100,4,2,4,4,4,4,4,4,3,3,3,1,4,4,126,123.0,neutral or dissatisfied +12906,56162,Female,disloyal Customer,31,Business travel,Eco,1400,3,3,3,3,4,3,4,4,1,5,3,4,3,4,75,37.0,neutral or dissatisfied +12907,58029,Female,Loyal Customer,54,Business travel,Business,1721,3,3,3,3,4,4,5,5,5,5,5,5,5,4,4,0.0,satisfied +12908,56101,Male,Loyal Customer,55,Business travel,Business,2402,2,2,2,2,2,3,3,2,2,2,2,4,2,4,102,56.0,neutral or dissatisfied +12909,55781,Female,Loyal Customer,21,Personal Travel,Eco,646,4,5,4,4,2,4,2,2,3,4,4,2,4,2,2,1.0,satisfied +12910,110167,Female,Loyal Customer,66,Personal Travel,Eco,882,1,4,1,4,2,1,4,4,4,1,4,3,4,2,0,6.0,neutral or dissatisfied +12911,56932,Male,Loyal Customer,26,Business travel,Business,2425,4,4,4,4,5,4,4,5,2,4,5,4,4,4,0,0.0,satisfied +12912,115052,Male,Loyal Customer,30,Business travel,Business,2115,0,0,0,2,5,5,5,5,3,4,4,4,5,5,2,0.0,satisfied +12913,96959,Male,Loyal Customer,28,Business travel,Business,3719,3,3,3,3,5,5,5,5,4,3,5,4,4,5,32,15.0,satisfied +12914,2620,Male,Loyal Customer,11,Personal Travel,Eco,181,2,5,2,5,4,2,4,4,2,4,3,1,3,4,0,0.0,neutral or dissatisfied +12915,98730,Male,Loyal Customer,44,Business travel,Business,1290,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +12916,35031,Male,disloyal Customer,23,Business travel,Eco,718,3,3,3,5,2,3,2,2,3,2,1,2,4,2,0,0.0,neutral or dissatisfied +12917,29776,Male,Loyal Customer,28,Personal Travel,Business,548,5,5,5,4,3,5,3,3,4,2,4,4,5,3,0,0.0,satisfied +12918,71604,Male,disloyal Customer,44,Business travel,Business,1120,4,4,4,1,3,4,3,3,3,2,4,5,4,3,0,0.0,satisfied +12919,95892,Female,Loyal Customer,41,Personal Travel,Eco,580,3,4,3,5,4,3,4,4,5,4,2,4,2,4,22,25.0,neutral or dissatisfied +12920,103190,Male,Loyal Customer,53,Business travel,Business,814,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +12921,31557,Female,Loyal Customer,38,Personal Travel,Eco,846,2,4,2,1,4,2,5,4,5,5,5,3,4,4,0,6.0,neutral or dissatisfied +12922,126276,Male,Loyal Customer,25,Personal Travel,Eco,590,2,3,2,3,3,2,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +12923,2254,Male,Loyal Customer,54,Business travel,Business,2372,3,3,2,3,3,5,4,5,5,5,5,4,5,5,32,25.0,satisfied +12924,79608,Male,Loyal Customer,30,Business travel,Business,3886,1,1,1,1,5,5,5,5,4,4,4,4,5,5,0,0.0,satisfied +12925,47927,Male,Loyal Customer,36,Personal Travel,Eco,838,3,4,3,3,4,3,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +12926,108546,Female,Loyal Customer,25,Personal Travel,Eco,512,3,4,3,1,2,3,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +12927,34937,Female,Loyal Customer,38,Personal Travel,Eco,187,5,5,0,3,2,0,2,2,4,2,5,4,4,2,0,0.0,satisfied +12928,82243,Female,Loyal Customer,38,Personal Travel,Eco,405,3,4,3,2,1,3,1,1,5,3,5,3,5,1,8,28.0,neutral or dissatisfied +12929,37832,Male,Loyal Customer,52,Business travel,Eco,937,5,4,4,4,5,5,5,5,2,5,4,5,1,5,9,18.0,satisfied +12930,59806,Female,Loyal Customer,44,Business travel,Business,3222,2,2,2,2,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +12931,114047,Female,Loyal Customer,14,Personal Travel,Eco,511,2,5,2,5,5,2,5,5,4,4,4,4,4,5,29,8.0,neutral or dissatisfied +12932,70134,Female,Loyal Customer,17,Business travel,Business,3152,2,2,2,2,2,2,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +12933,33148,Male,Loyal Customer,41,Personal Travel,Eco,163,2,5,0,3,2,0,5,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +12934,21390,Female,disloyal Customer,40,Business travel,Business,306,5,5,5,5,3,5,3,3,5,1,4,3,2,3,14,9.0,satisfied +12935,117673,Male,Loyal Customer,10,Business travel,Eco Plus,1449,2,2,4,2,2,2,1,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +12936,39922,Male,Loyal Customer,40,Business travel,Business,1965,2,2,2,2,1,1,5,4,4,4,4,2,4,5,0,0.0,satisfied +12937,54379,Female,disloyal Customer,48,Business travel,Eco,305,2,3,2,4,1,2,1,1,4,3,5,3,3,1,0,0.0,neutral or dissatisfied +12938,40039,Male,Loyal Customer,68,Personal Travel,Eco Plus,575,2,5,2,4,4,2,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +12939,99460,Female,Loyal Customer,60,Business travel,Business,2787,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +12940,72199,Female,Loyal Customer,70,Personal Travel,Eco,594,3,4,3,3,5,4,3,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +12941,64805,Female,Loyal Customer,51,Business travel,Business,3540,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,1.0,satisfied +12942,125000,Male,Loyal Customer,72,Business travel,Business,1846,1,5,3,5,1,3,3,3,3,3,1,4,3,3,0,0.0,neutral or dissatisfied +12943,24282,Male,Loyal Customer,48,Personal Travel,Eco,147,2,1,2,4,3,2,3,3,1,2,3,3,4,3,33,48.0,neutral or dissatisfied +12944,16815,Male,Loyal Customer,42,Business travel,Eco,645,5,1,1,1,3,5,3,3,5,4,1,2,5,3,0,0.0,satisfied +12945,16887,Female,disloyal Customer,30,Business travel,Eco,708,3,3,3,4,5,3,5,5,1,2,3,4,4,5,0,2.0,neutral or dissatisfied +12946,92803,Female,Loyal Customer,54,Business travel,Business,1587,2,2,2,2,5,4,4,3,3,3,3,5,3,3,2,0.0,satisfied +12947,124454,Female,Loyal Customer,40,Business travel,Business,3557,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +12948,111426,Male,Loyal Customer,24,Business travel,Business,2690,1,3,3,3,1,1,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +12949,107925,Male,Loyal Customer,22,Business travel,Business,3377,3,3,3,3,5,5,5,5,4,3,4,3,5,5,26,21.0,satisfied +12950,86565,Female,Loyal Customer,27,Personal Travel,Eco Plus,749,2,4,2,4,5,2,5,5,2,1,4,4,3,5,23,28.0,neutral or dissatisfied +12951,18144,Male,Loyal Customer,50,Personal Travel,Eco,926,3,4,2,4,1,2,1,1,3,3,4,5,5,1,2,0.0,neutral or dissatisfied +12952,81813,Female,disloyal Customer,29,Business travel,Eco,1306,2,2,2,3,5,2,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +12953,61292,Male,Loyal Customer,66,Personal Travel,Eco,967,1,5,1,4,5,1,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +12954,69462,Female,Loyal Customer,59,Personal Travel,Eco,1096,2,3,2,4,5,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +12955,70777,Female,Loyal Customer,59,Business travel,Business,328,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +12956,10794,Female,Loyal Customer,42,Business travel,Business,2344,1,1,1,1,5,5,5,4,2,4,5,5,4,5,146,151.0,satisfied +12957,44559,Female,Loyal Customer,22,Business travel,Eco Plus,157,5,5,5,5,5,5,4,5,3,5,1,4,4,5,0,0.0,satisfied +12958,80896,Female,Loyal Customer,36,Personal Travel,Eco Plus,484,3,1,3,2,1,3,1,1,3,3,2,2,3,1,5,0.0,neutral or dissatisfied +12959,27490,Male,Loyal Customer,58,Business travel,Business,954,4,1,1,1,4,3,3,4,4,4,4,2,4,1,37,21.0,neutral or dissatisfied +12960,55353,Female,Loyal Customer,42,Business travel,Business,3885,5,5,5,5,5,5,4,4,4,4,4,5,4,5,4,0.0,satisfied +12961,48406,Male,Loyal Customer,57,Business travel,Business,844,2,2,5,2,5,5,5,5,3,4,4,5,4,5,173,153.0,satisfied +12962,113774,Female,Loyal Customer,20,Personal Travel,Eco,258,4,4,4,5,1,4,1,1,4,3,4,3,1,1,7,7.0,neutral or dissatisfied +12963,16412,Female,Loyal Customer,58,Business travel,Business,2849,1,1,1,1,2,4,5,3,3,3,3,4,3,3,5,0.0,satisfied +12964,39990,Female,Loyal Customer,47,Business travel,Eco,508,4,5,5,5,2,5,5,4,4,4,4,2,4,4,0,0.0,satisfied +12965,105672,Female,Loyal Customer,12,Business travel,Business,3326,1,1,1,1,4,4,4,4,5,5,5,4,4,4,4,0.0,satisfied +12966,6072,Male,Loyal Customer,70,Personal Travel,Eco,1236,3,5,3,2,3,3,3,3,4,5,4,5,5,3,87,84.0,neutral or dissatisfied +12967,115066,Female,disloyal Customer,21,Business travel,Eco,362,2,0,2,3,1,2,1,1,3,5,5,4,5,1,9,3.0,neutral or dissatisfied +12968,55348,Male,Loyal Customer,41,Business travel,Business,594,4,4,4,4,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +12969,62805,Male,Loyal Customer,40,Personal Travel,Eco,2399,1,4,1,3,1,1,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +12970,32578,Female,Loyal Customer,66,Business travel,Business,216,2,5,5,5,3,4,3,5,5,4,2,3,5,4,0,0.0,neutral or dissatisfied +12971,108723,Female,Loyal Customer,18,Business travel,Business,591,1,5,5,5,1,1,1,1,1,4,3,4,3,1,33,35.0,neutral or dissatisfied +12972,104366,Female,Loyal Customer,44,Business travel,Business,228,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +12973,7355,Female,Loyal Customer,44,Business travel,Eco,464,4,3,3,3,1,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +12974,6733,Female,disloyal Customer,36,Business travel,Eco,268,2,1,3,3,5,3,5,5,3,1,3,1,4,5,0,10.0,neutral or dissatisfied +12975,88745,Male,Loyal Customer,16,Personal Travel,Eco,406,3,1,3,3,4,3,5,4,3,1,3,1,4,4,9,8.0,neutral or dissatisfied +12976,46098,Male,Loyal Customer,54,Personal Travel,Eco Plus,541,4,5,4,3,5,4,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +12977,10963,Male,disloyal Customer,42,Business travel,Business,267,5,5,5,4,2,5,2,2,1,1,3,5,5,2,83,69.0,satisfied +12978,18383,Male,Loyal Customer,42,Business travel,Business,3778,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +12979,102232,Female,disloyal Customer,24,Business travel,Business,258,5,0,5,3,3,5,2,3,5,5,4,4,4,3,12,0.0,satisfied +12980,50817,Female,Loyal Customer,56,Personal Travel,Eco,308,5,5,5,1,3,4,5,2,2,5,2,3,2,4,11,3.0,satisfied +12981,60080,Male,disloyal Customer,46,Business travel,Business,1005,4,4,4,3,3,4,3,3,4,4,4,5,5,3,0,8.0,satisfied +12982,41490,Male,Loyal Customer,36,Business travel,Eco,1464,4,5,5,5,4,4,4,4,3,1,5,5,1,4,63,63.0,satisfied +12983,82112,Female,Loyal Customer,23,Personal Travel,Eco,1276,1,5,1,4,4,1,4,4,5,5,4,5,4,4,54,50.0,neutral or dissatisfied +12984,29242,Male,disloyal Customer,38,Business travel,Eco,834,2,2,2,4,5,2,5,5,5,1,5,2,5,5,0,0.0,neutral or dissatisfied +12985,2097,Female,Loyal Customer,40,Personal Travel,Eco,733,4,1,4,3,5,4,4,5,2,1,3,1,2,5,0,3.0,neutral or dissatisfied +12986,93630,Male,Loyal Customer,7,Personal Travel,Eco,577,3,3,3,3,5,3,5,5,2,1,3,1,3,5,12,38.0,neutral or dissatisfied +12987,70444,Female,Loyal Customer,10,Personal Travel,Eco,187,3,4,3,2,5,3,5,5,3,2,5,5,5,5,27,28.0,neutral or dissatisfied +12988,76854,Female,Loyal Customer,50,Personal Travel,Eco,989,2,4,2,2,2,5,5,3,3,2,3,3,3,5,127,104.0,neutral or dissatisfied +12989,49833,Female,Loyal Customer,41,Business travel,Business,2770,4,5,3,5,5,3,3,1,1,1,4,3,1,2,0,0.0,neutral or dissatisfied +12990,65821,Male,Loyal Customer,42,Business travel,Business,1389,1,1,1,1,5,5,4,4,4,4,4,4,4,4,15,0.0,satisfied +12991,42875,Male,disloyal Customer,59,Business travel,Eco,467,2,2,2,4,3,2,3,3,4,1,4,4,3,3,0,8.0,neutral or dissatisfied +12992,109733,Male,Loyal Customer,17,Personal Travel,Eco,534,5,5,5,5,3,5,3,3,5,3,5,3,4,3,27,21.0,satisfied +12993,825,Female,Loyal Customer,53,Business travel,Business,1588,0,0,0,3,3,4,4,5,5,4,4,3,5,4,7,18.0,satisfied +12994,10931,Female,Loyal Customer,62,Business travel,Eco,482,4,3,3,3,4,2,3,4,4,4,4,3,4,3,15,23.0,neutral or dissatisfied +12995,5553,Male,disloyal Customer,21,Business travel,Business,501,4,1,4,2,1,4,1,1,4,4,5,3,5,1,0,0.0,satisfied +12996,83996,Male,Loyal Customer,40,Business travel,Business,2329,1,1,2,1,2,5,4,4,4,4,4,1,4,3,5,0.0,satisfied +12997,114197,Male,Loyal Customer,33,Business travel,Business,2123,2,2,2,2,4,4,4,4,4,2,5,3,5,4,21,11.0,satisfied +12998,63628,Female,Loyal Customer,37,Business travel,Business,602,5,5,4,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +12999,128015,Male,Loyal Customer,45,Business travel,Business,1440,3,5,5,5,1,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +13000,61123,Female,Loyal Customer,48,Business travel,Business,967,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +13001,23491,Female,Loyal Customer,79,Business travel,Eco Plus,116,2,2,2,2,4,4,3,2,2,2,2,1,2,4,15,4.0,neutral or dissatisfied +13002,74814,Female,Loyal Customer,46,Personal Travel,Eco Plus,1235,3,4,3,2,5,3,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +13003,42799,Male,disloyal Customer,38,Business travel,Eco,677,3,3,3,4,2,3,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +13004,100498,Male,disloyal Customer,26,Business travel,Business,580,2,2,2,4,2,2,2,2,5,3,4,3,4,2,0,1.0,neutral or dissatisfied +13005,72224,Male,Loyal Customer,58,Business travel,Business,919,1,1,1,1,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +13006,104032,Female,Loyal Customer,43,Business travel,Business,2298,2,2,3,2,5,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +13007,454,Male,Loyal Customer,59,Business travel,Business,312,1,1,1,1,2,4,4,5,5,5,5,3,5,5,26,18.0,satisfied +13008,81107,Female,Loyal Customer,53,Business travel,Business,1727,1,1,1,1,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +13009,51162,Female,Loyal Customer,35,Personal Travel,Eco,86,3,4,3,1,2,3,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +13010,63645,Male,Loyal Customer,25,Personal Travel,Eco,602,2,1,2,3,4,2,4,4,2,1,2,2,2,4,0,5.0,neutral or dissatisfied +13011,4313,Male,Loyal Customer,43,Business travel,Business,2773,4,4,4,4,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +13012,68619,Female,Loyal Customer,50,Business travel,Business,3252,5,5,3,5,5,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +13013,69985,Male,Loyal Customer,36,Business travel,Eco,236,2,1,1,1,2,2,2,2,1,5,3,2,4,2,0,7.0,neutral or dissatisfied +13014,37962,Female,Loyal Customer,35,Business travel,Business,1121,4,4,4,4,5,4,5,5,5,5,5,3,5,5,51,36.0,satisfied +13015,128783,Female,Loyal Customer,65,Business travel,Eco,748,4,5,5,5,5,4,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +13016,34911,Male,Loyal Customer,46,Business travel,Business,3095,4,1,4,4,5,5,5,5,5,4,5,5,5,5,246,242.0,satisfied +13017,76968,Female,Loyal Customer,32,Personal Travel,Eco,1990,3,3,3,1,5,3,5,5,4,4,2,3,4,5,14,26.0,neutral or dissatisfied +13018,23097,Female,Loyal Customer,72,Business travel,Business,2641,1,1,2,1,3,4,5,4,4,4,5,3,4,5,4,0.0,satisfied +13019,52756,Female,Loyal Customer,17,Business travel,Business,1874,5,5,5,5,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +13020,20748,Male,Loyal Customer,47,Personal Travel,Eco,363,4,5,4,4,4,4,4,4,5,4,4,5,5,4,6,14.0,neutral or dissatisfied +13021,17099,Female,Loyal Customer,66,Personal Travel,Eco,416,1,3,1,2,1,2,2,5,2,5,4,2,3,2,226,221.0,neutral or dissatisfied +13022,57432,Female,Loyal Customer,50,Personal Travel,Eco,533,0,5,0,2,4,4,4,2,2,0,2,4,2,5,0,0.0,satisfied +13023,20320,Female,Loyal Customer,49,Business travel,Business,265,0,0,0,2,4,4,2,4,5,4,5,2,3,2,151,138.0,satisfied +13024,126180,Female,Loyal Customer,49,Business travel,Business,631,1,1,1,1,3,5,4,3,3,3,3,4,3,4,0,10.0,satisfied +13025,7453,Male,Loyal Customer,60,Business travel,Business,3094,3,3,3,3,2,4,5,5,5,5,5,4,5,3,15,3.0,satisfied +13026,71181,Female,Loyal Customer,8,Personal Travel,Business,733,2,2,2,4,5,2,5,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +13027,37912,Male,Loyal Customer,70,Personal Travel,Eco,1065,1,3,1,3,3,1,3,3,1,1,4,4,3,3,0,3.0,neutral or dissatisfied +13028,92511,Male,Loyal Customer,48,Personal Travel,Eco,1947,3,4,3,2,4,3,4,4,4,3,5,5,5,4,1,0.0,neutral or dissatisfied +13029,94536,Male,Loyal Customer,50,Business travel,Business,3630,4,4,4,4,4,4,4,5,4,4,4,4,3,4,171,169.0,satisfied +13030,13081,Male,Loyal Customer,57,Business travel,Business,3337,3,3,3,3,2,4,4,4,4,4,4,5,4,3,48,38.0,satisfied +13031,27585,Female,Loyal Customer,8,Personal Travel,Eco,954,3,5,3,3,2,3,2,2,5,5,4,4,4,2,0,10.0,neutral or dissatisfied +13032,24626,Female,Loyal Customer,47,Personal Travel,Eco,526,5,4,5,3,2,4,4,2,2,5,2,5,2,4,0,10.0,satisfied +13033,72062,Female,Loyal Customer,25,Business travel,Business,2486,1,1,1,1,5,5,5,5,5,4,3,3,5,5,1,0.0,satisfied +13034,1271,Male,Loyal Customer,8,Personal Travel,Eco,282,4,4,4,3,2,4,3,2,5,4,4,4,5,2,5,14.0,neutral or dissatisfied +13035,48690,Male,Loyal Customer,60,Business travel,Business,372,3,3,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +13036,7421,Female,Loyal Customer,23,Business travel,Eco,522,3,2,2,2,3,3,2,3,3,1,3,2,3,3,0,34.0,neutral or dissatisfied +13037,117053,Male,Loyal Customer,36,Business travel,Business,369,3,3,3,3,4,3,3,1,3,4,4,3,1,3,153,153.0,neutral or dissatisfied +13038,5163,Male,disloyal Customer,23,Business travel,Business,383,4,0,4,3,5,4,5,5,5,5,4,3,4,5,0,0.0,satisfied +13039,65066,Female,Loyal Customer,63,Personal Travel,Eco,551,2,1,2,1,3,1,2,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +13040,21932,Female,disloyal Customer,20,Business travel,Eco,448,4,3,4,2,2,4,2,2,5,1,1,1,2,2,32,39.0,neutral or dissatisfied +13041,44595,Male,Loyal Customer,54,Business travel,Eco Plus,157,5,1,1,1,5,5,5,5,4,5,5,4,1,5,0,0.0,satisfied +13042,67126,Female,disloyal Customer,36,Business travel,Business,918,4,4,4,2,2,4,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +13043,58508,Male,Loyal Customer,12,Personal Travel,Eco,719,5,4,5,3,3,5,2,3,3,4,4,5,4,3,2,0.0,satisfied +13044,107446,Female,Loyal Customer,44,Personal Travel,Eco,717,3,4,3,3,4,2,2,5,5,3,5,3,5,5,13,10.0,neutral or dissatisfied +13045,29777,Female,Loyal Customer,37,Personal Travel,Business,95,2,3,2,1,1,4,1,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +13046,97110,Male,disloyal Customer,26,Business travel,Business,715,3,3,3,4,1,3,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +13047,70699,Female,Loyal Customer,38,Business travel,Business,3560,5,5,5,5,3,5,5,5,5,4,5,4,5,3,1,12.0,satisfied +13048,33123,Female,Loyal Customer,11,Personal Travel,Eco,163,3,5,0,2,2,0,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +13049,127556,Male,Loyal Customer,52,Personal Travel,Eco Plus,1009,2,4,2,1,5,2,5,5,2,5,1,5,2,5,0,0.0,neutral or dissatisfied +13050,66645,Female,Loyal Customer,56,Business travel,Business,2077,5,5,5,5,2,5,5,5,5,5,5,3,5,5,63,44.0,satisfied +13051,24605,Male,Loyal Customer,21,Business travel,Business,666,4,4,4,4,3,3,3,3,4,5,1,4,3,3,57,53.0,satisfied +13052,102487,Male,Loyal Customer,14,Personal Travel,Eco,414,4,4,4,4,2,4,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +13053,26484,Female,Loyal Customer,70,Personal Travel,Eco Plus,842,2,5,2,2,2,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +13054,58582,Male,Loyal Customer,53,Business travel,Business,3583,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +13055,72345,Female,disloyal Customer,22,Business travel,Eco,985,2,2,2,3,4,2,4,4,3,1,3,2,4,4,45,36.0,neutral or dissatisfied +13056,90398,Male,Loyal Customer,27,Personal Travel,Business,366,4,3,4,1,1,4,1,1,2,1,5,2,5,1,1,6.0,neutral or dissatisfied +13057,127703,Female,Loyal Customer,12,Personal Travel,Eco,2133,4,5,4,2,5,4,3,5,3,1,5,4,4,5,2,0.0,satisfied +13058,128052,Female,Loyal Customer,7,Personal Travel,Eco,735,1,4,1,2,2,1,2,2,5,5,4,5,4,2,28,22.0,neutral or dissatisfied +13059,101503,Female,disloyal Customer,24,Business travel,Eco,345,4,4,4,3,4,4,4,4,5,2,4,3,4,4,0,0.0,neutral or dissatisfied +13060,3411,Male,Loyal Customer,44,Personal Travel,Eco,315,2,5,2,4,1,2,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +13061,89215,Male,Loyal Customer,44,Personal Travel,Eco,2139,3,4,3,4,2,3,4,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +13062,7926,Male,Loyal Customer,28,Personal Travel,Eco,1020,3,1,3,4,3,3,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +13063,39168,Male,Loyal Customer,21,Business travel,Business,3991,5,5,2,5,4,4,4,4,3,3,5,5,5,4,0,4.0,satisfied +13064,72693,Male,Loyal Customer,7,Personal Travel,Eco,985,2,5,1,3,1,1,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +13065,117616,Male,disloyal Customer,39,Business travel,Business,347,4,4,4,2,3,4,3,3,2,2,1,3,2,3,0,0.0,satisfied +13066,109691,Female,Loyal Customer,39,Personal Travel,Eco,802,4,5,5,1,3,5,3,3,3,3,4,4,4,3,122,111.0,neutral or dissatisfied +13067,10244,Male,Loyal Customer,46,Personal Travel,Business,429,1,0,1,3,4,5,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +13068,81945,Female,Loyal Customer,27,Business travel,Business,1535,3,3,3,3,4,4,4,4,3,2,4,3,5,4,0,10.0,satisfied +13069,38109,Female,disloyal Customer,46,Business travel,Eco,1121,2,3,3,3,5,3,1,5,5,2,5,1,3,5,0,0.0,neutral or dissatisfied +13070,80234,Male,Loyal Customer,25,Business travel,Business,3601,3,3,3,3,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +13071,72916,Female,Loyal Customer,51,Business travel,Business,2725,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +13072,109849,Male,Loyal Customer,59,Business travel,Business,1758,2,2,2,2,3,4,5,4,4,4,4,3,4,5,10,12.0,satisfied +13073,100187,Male,Loyal Customer,41,Personal Travel,Eco,523,3,3,3,3,3,3,3,3,4,2,4,3,4,3,0,72.0,neutral or dissatisfied +13074,123638,Male,disloyal Customer,49,Business travel,Business,214,2,2,2,4,5,2,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +13075,125936,Male,Loyal Customer,18,Personal Travel,Eco,1013,3,1,3,4,5,3,5,5,3,5,4,1,3,5,32,9.0,neutral or dissatisfied +13076,87622,Female,disloyal Customer,24,Business travel,Eco,606,4,0,4,2,2,4,2,2,5,3,5,4,4,2,20,15.0,satisfied +13077,23814,Female,Loyal Customer,34,Personal Travel,Eco,374,4,2,4,3,2,4,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +13078,65278,Male,Loyal Customer,24,Personal Travel,Eco Plus,469,3,4,3,3,4,3,4,4,4,3,5,5,4,4,16,22.0,neutral or dissatisfied +13079,6831,Male,Loyal Customer,69,Personal Travel,Eco,224,2,3,2,4,2,2,1,2,2,5,2,5,1,2,0,0.0,neutral or dissatisfied +13080,114613,Male,Loyal Customer,53,Business travel,Business,3825,0,0,0,2,5,4,4,4,4,4,4,3,4,4,28,26.0,satisfied +13081,112029,Female,Loyal Customer,60,Personal Travel,Eco,680,3,5,2,2,4,5,5,2,2,2,2,5,2,4,5,6.0,neutral or dissatisfied +13082,56355,Male,Loyal Customer,19,Personal Travel,Eco,200,2,4,2,1,5,2,5,5,4,5,2,5,4,5,0,15.0,neutral or dissatisfied +13083,128633,Female,Loyal Customer,39,Personal Travel,Eco,954,1,5,1,2,3,1,5,3,4,3,5,3,5,3,18,3.0,neutral or dissatisfied +13084,113469,Female,disloyal Customer,27,Business travel,Business,236,5,5,5,2,5,5,5,5,5,3,5,5,5,5,0,3.0,satisfied +13085,58594,Male,Loyal Customer,38,Business travel,Business,334,4,2,2,2,1,3,3,4,4,4,4,3,4,2,99,80.0,neutral or dissatisfied +13086,68733,Male,Loyal Customer,21,Personal Travel,Eco Plus,175,2,5,2,5,1,2,1,1,2,4,1,5,3,1,0,20.0,neutral or dissatisfied +13087,111527,Male,Loyal Customer,45,Business travel,Business,3700,2,2,2,2,3,4,4,5,5,5,5,4,5,3,77,86.0,satisfied +13088,64432,Male,disloyal Customer,23,Business travel,Eco,989,1,1,1,2,4,1,4,4,5,3,5,5,5,4,66,75.0,neutral or dissatisfied +13089,67629,Male,disloyal Customer,25,Business travel,Eco,1235,5,5,5,1,1,5,1,1,5,5,4,3,4,1,0,0.0,satisfied +13090,17214,Female,Loyal Customer,38,Business travel,Business,3302,4,4,4,4,2,3,3,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +13091,39934,Female,Loyal Customer,40,Business travel,Business,3393,5,5,5,5,2,5,1,4,4,4,4,1,4,4,0,0.0,satisfied +13092,103517,Male,Loyal Customer,55,Personal Travel,Eco,1047,3,4,3,3,3,3,3,3,5,4,4,3,4,3,1,0.0,neutral or dissatisfied +13093,114796,Female,disloyal Customer,23,Business travel,Eco,404,1,5,1,4,2,1,2,2,3,4,4,5,5,2,6,1.0,neutral or dissatisfied +13094,66082,Female,Loyal Customer,64,Personal Travel,Eco,1055,3,4,4,3,3,5,4,4,4,4,4,3,4,5,11,17.0,neutral or dissatisfied +13095,52073,Female,Loyal Customer,25,Business travel,Business,3229,5,5,5,5,4,4,4,4,1,4,4,4,1,4,20,44.0,satisfied +13096,34997,Male,Loyal Customer,52,Business travel,Eco,1182,4,4,4,4,4,4,4,4,2,4,3,2,4,4,0,0.0,satisfied +13097,4522,Female,disloyal Customer,23,Business travel,Eco,677,1,1,1,3,2,1,2,2,4,3,5,3,5,2,0,12.0,neutral or dissatisfied +13098,78343,Male,Loyal Customer,44,Business travel,Business,1547,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +13099,45695,Female,Loyal Customer,54,Personal Travel,Eco,826,3,4,3,3,5,4,5,3,3,3,3,3,3,4,73,70.0,neutral or dissatisfied +13100,122380,Male,Loyal Customer,29,Personal Travel,Eco,529,5,5,5,5,3,5,3,3,4,4,5,3,4,3,0,2.0,satisfied +13101,1777,Male,disloyal Customer,66,Business travel,Business,408,5,5,5,1,2,5,2,2,3,2,4,3,5,2,0,0.0,satisfied +13102,104001,Male,Loyal Customer,29,Business travel,Business,1592,3,3,3,3,3,3,3,3,2,5,2,3,4,3,13,55.0,neutral or dissatisfied +13103,117957,Male,Loyal Customer,40,Business travel,Eco,365,5,1,1,1,5,5,5,5,1,3,4,4,5,5,0,0.0,satisfied +13104,30370,Female,Loyal Customer,46,Business travel,Business,2104,1,1,1,1,4,5,1,2,2,2,2,1,2,4,10,6.0,satisfied +13105,19972,Female,Loyal Customer,11,Personal Travel,Eco,557,3,4,3,1,4,3,4,4,3,5,2,3,3,4,0,0.0,neutral or dissatisfied +13106,13806,Male,Loyal Customer,23,Business travel,Business,617,2,2,2,2,4,4,4,4,1,4,1,4,5,4,78,45.0,satisfied +13107,128114,Male,disloyal Customer,35,Business travel,Business,1587,2,2,2,3,2,2,2,2,3,3,3,4,5,2,0,6.0,neutral or dissatisfied +13108,104645,Male,Loyal Customer,53,Business travel,Business,1754,1,5,1,1,1,1,1,3,2,4,3,1,2,1,199,188.0,neutral or dissatisfied +13109,15923,Female,Loyal Customer,42,Business travel,Business,607,3,3,3,3,5,3,1,4,4,4,4,3,4,4,0,0.0,satisfied +13110,119024,Male,disloyal Customer,15,Business travel,Eco,812,3,3,3,3,1,3,1,1,2,4,4,2,4,1,0,22.0,neutral or dissatisfied +13111,106579,Male,Loyal Customer,54,Personal Travel,Eco Plus,1506,4,3,4,3,4,4,4,4,4,1,2,3,3,4,0,0.0,satisfied +13112,91389,Female,Loyal Customer,39,Business travel,Business,2218,3,3,3,3,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +13113,78644,Female,Loyal Customer,48,Business travel,Business,2172,2,4,4,4,5,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +13114,122177,Female,Loyal Customer,39,Business travel,Business,541,2,2,2,2,2,4,3,2,2,2,2,3,2,4,25,24.0,neutral or dissatisfied +13115,23001,Male,Loyal Customer,22,Personal Travel,Eco,489,3,5,3,5,3,3,3,3,4,4,4,2,3,3,0,0.0,neutral or dissatisfied +13116,38563,Female,Loyal Customer,56,Personal Travel,Eco,2475,1,5,1,1,2,1,3,2,2,1,2,2,2,4,3,0.0,neutral or dissatisfied +13117,36276,Male,Loyal Customer,59,Personal Travel,Eco,612,3,5,3,1,5,3,5,5,4,4,1,1,5,5,2,0.0,neutral or dissatisfied +13118,81058,Female,Loyal Customer,70,Personal Travel,Eco,1399,4,5,4,5,3,5,3,2,2,4,2,5,2,3,11,0.0,satisfied +13119,50194,Female,Loyal Customer,37,Business travel,Eco,209,2,3,4,3,2,3,2,2,1,5,4,2,4,2,0,7.0,neutral or dissatisfied +13120,38472,Male,Loyal Customer,35,Business travel,Eco,846,3,4,4,4,3,4,3,3,4,1,1,3,2,3,0,0.0,satisfied +13121,76225,Male,Loyal Customer,48,Business travel,Business,1399,3,3,3,3,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +13122,29539,Female,Loyal Customer,53,Business travel,Business,2472,2,2,2,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +13123,100510,Female,Loyal Customer,38,Business travel,Eco,180,5,5,5,5,5,5,5,5,4,1,1,1,1,5,10,0.0,satisfied +13124,32863,Male,Loyal Customer,38,Personal Travel,Eco,101,3,4,3,4,4,3,4,4,5,2,4,4,4,4,0,7.0,neutral or dissatisfied +13125,94053,Female,Loyal Customer,55,Business travel,Business,3484,5,5,2,5,2,4,5,4,4,4,4,4,4,5,36,25.0,satisfied +13126,42778,Female,Loyal Customer,42,Business travel,Business,744,3,3,4,3,4,4,1,5,5,5,5,2,5,4,0,16.0,satisfied +13127,37110,Male,disloyal Customer,25,Business travel,Eco,1237,1,1,1,2,2,1,1,2,4,5,5,1,4,2,3,0.0,neutral or dissatisfied +13128,17153,Female,Loyal Customer,31,Business travel,Business,3917,5,5,5,5,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +13129,127281,Male,Loyal Customer,49,Personal Travel,Eco,1107,3,4,3,4,4,3,4,4,3,4,5,4,4,4,90,100.0,neutral or dissatisfied +13130,54068,Male,Loyal Customer,60,Business travel,Business,1416,3,2,4,2,2,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +13131,71314,Male,disloyal Customer,29,Business travel,Business,1514,2,2,2,3,3,2,3,3,4,5,4,5,4,3,0,1.0,neutral or dissatisfied +13132,67423,Female,disloyal Customer,21,Business travel,Eco,641,3,2,3,4,1,3,1,1,1,3,4,4,4,1,22,28.0,neutral or dissatisfied +13133,120283,Female,Loyal Customer,62,Business travel,Business,1176,4,3,3,3,1,4,4,4,4,4,4,4,4,4,7,14.0,neutral or dissatisfied +13134,89308,Male,Loyal Customer,57,Personal Travel,Eco,453,2,3,2,4,3,2,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +13135,85591,Male,Loyal Customer,42,Business travel,Business,3525,0,0,0,1,2,1,4,4,4,5,5,5,4,4,0,0.0,satisfied +13136,73953,Male,disloyal Customer,36,Business travel,Eco,718,4,4,4,3,2,4,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +13137,118966,Male,Loyal Customer,16,Personal Travel,Eco,570,4,1,4,2,4,4,4,4,2,3,2,1,3,4,0,0.0,neutral or dissatisfied +13138,88896,Male,Loyal Customer,53,Business travel,Eco,859,3,1,2,1,3,3,3,3,3,5,1,4,2,3,6,0.0,neutral or dissatisfied +13139,23213,Female,Loyal Customer,52,Business travel,Eco,326,4,4,4,4,2,1,2,4,4,4,4,1,4,3,0,0.0,satisfied +13140,78498,Female,Loyal Customer,58,Business travel,Business,666,3,5,1,1,1,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +13141,50021,Female,Loyal Customer,37,Business travel,Eco,153,4,5,5,5,4,4,4,4,4,5,4,3,4,4,73,73.0,neutral or dissatisfied +13142,15638,Male,Loyal Customer,19,Business travel,Eco Plus,325,0,4,0,2,4,0,4,4,4,1,3,1,5,4,0,0.0,satisfied +13143,123362,Male,Loyal Customer,60,Business travel,Business,644,1,1,1,1,4,5,5,5,5,5,5,4,5,4,8,15.0,satisfied +13144,66887,Male,Loyal Customer,53,Business travel,Business,3835,2,2,2,2,5,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +13145,128244,Female,Loyal Customer,58,Business travel,Business,602,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +13146,7156,Male,disloyal Customer,18,Business travel,Eco,139,2,4,2,3,3,2,3,3,3,3,4,3,4,3,84,89.0,neutral or dissatisfied +13147,11837,Male,Loyal Customer,26,Personal Travel,Eco,986,1,4,1,3,1,2,4,4,5,4,5,4,4,4,154,152.0,neutral or dissatisfied +13148,117869,Female,Loyal Customer,43,Business travel,Business,2765,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +13149,13272,Male,Loyal Customer,23,Personal Travel,Eco,657,3,1,3,2,3,3,3,3,1,5,1,3,2,3,23,12.0,neutral or dissatisfied +13150,48337,Female,disloyal Customer,30,Business travel,Eco,674,1,1,1,3,5,1,5,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +13151,97987,Male,Loyal Customer,16,Personal Travel,Eco,616,4,3,4,4,3,4,3,3,2,1,4,3,2,3,40,36.0,neutral or dissatisfied +13152,126432,Female,Loyal Customer,48,Personal Travel,Eco Plus,507,2,5,2,5,3,4,4,5,5,2,5,4,5,4,6,7.0,neutral or dissatisfied +13153,29728,Male,Loyal Customer,30,Business travel,Eco Plus,2777,4,4,4,4,4,4,4,4,1,3,4,5,1,4,0,0.0,satisfied +13154,19635,Female,disloyal Customer,45,Business travel,Eco,131,4,3,4,5,1,4,1,1,3,2,4,1,5,1,0,0.0,neutral or dissatisfied +13155,94484,Female,Loyal Customer,41,Business travel,Business,528,2,2,2,2,5,4,4,5,5,4,5,4,5,5,14,20.0,satisfied +13156,52427,Male,Loyal Customer,37,Personal Travel,Eco,451,4,2,4,4,1,4,1,1,4,4,3,4,3,1,0,0.0,neutral or dissatisfied +13157,91266,Male,Loyal Customer,49,Personal Travel,Eco,545,2,4,2,4,2,2,2,2,2,5,4,5,4,2,0,2.0,neutral or dissatisfied +13158,13934,Male,Loyal Customer,50,Business travel,Eco,192,3,3,3,3,3,3,3,3,3,2,2,2,1,3,41,47.0,neutral or dissatisfied +13159,110156,Female,Loyal Customer,29,Personal Travel,Eco,882,0,1,0,3,5,0,5,5,1,3,3,3,4,5,16,5.0,satisfied +13160,29093,Male,Loyal Customer,52,Personal Travel,Eco,605,1,4,1,1,1,1,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +13161,41565,Male,Loyal Customer,69,Business travel,Business,842,2,2,2,2,2,4,3,2,2,2,2,3,2,4,0,1.0,neutral or dissatisfied +13162,80432,Male,Loyal Customer,38,Personal Travel,Eco,2248,4,4,4,3,3,4,3,3,5,5,4,3,5,3,0,0.0,satisfied +13163,90471,Male,disloyal Customer,23,Business travel,Eco,515,5,0,5,5,2,5,2,2,3,5,4,4,4,2,2,35.0,satisfied +13164,67449,Female,Loyal Customer,52,Personal Travel,Eco,641,2,5,2,1,5,5,4,1,1,2,4,3,1,5,0,1.0,neutral or dissatisfied +13165,32700,Male,Loyal Customer,53,Business travel,Eco,101,1,2,2,2,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +13166,49917,Female,Loyal Customer,35,Business travel,Business,109,4,3,4,3,2,4,3,3,3,3,4,4,3,3,24,18.0,neutral or dissatisfied +13167,78255,Male,Loyal Customer,52,Business travel,Business,903,2,1,1,1,1,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +13168,72787,Male,Loyal Customer,50,Business travel,Business,3020,3,5,5,5,5,1,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +13169,9515,Male,Loyal Customer,48,Business travel,Business,229,5,5,5,5,5,4,5,4,4,4,4,5,4,3,24,5.0,satisfied +13170,28374,Male,Loyal Customer,42,Business travel,Business,3611,3,3,3,3,2,4,3,5,5,5,5,1,5,1,0,0.0,satisfied +13171,59255,Female,Loyal Customer,69,Personal Travel,Eco,3904,2,2,2,4,2,3,5,4,5,4,4,5,4,5,15,0.0,neutral or dissatisfied +13172,73197,Male,Loyal Customer,22,Business travel,Business,1258,2,1,1,1,2,2,2,2,1,4,4,3,4,2,0,0.0,neutral or dissatisfied +13173,53138,Male,Loyal Customer,80,Business travel,Eco,413,1,2,2,2,1,1,1,1,3,4,2,4,2,1,36,23.0,neutral or dissatisfied +13174,55178,Male,Loyal Customer,53,Business travel,Business,1346,4,4,4,4,5,5,5,5,5,5,5,5,5,4,36,13.0,satisfied +13175,18011,Male,Loyal Customer,22,Personal Travel,Eco,296,5,4,5,3,1,5,1,1,3,4,5,3,5,1,0,0.0,satisfied +13176,88142,Male,Loyal Customer,45,Business travel,Business,404,1,1,1,1,3,5,5,4,4,5,4,5,4,5,0,8.0,satisfied +13177,79784,Female,Loyal Customer,43,Personal Travel,Business,1005,3,4,3,5,5,5,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +13178,26134,Male,Loyal Customer,44,Business travel,Business,1702,3,3,3,3,2,3,5,3,3,3,3,3,3,2,19,13.0,satisfied +13179,14971,Female,Loyal Customer,25,Business travel,Business,3733,2,5,5,5,2,2,2,2,3,3,3,4,2,2,0,0.0,neutral or dissatisfied +13180,48023,Male,Loyal Customer,37,Business travel,Business,1187,2,2,2,2,4,3,3,5,5,5,5,5,5,2,8,0.0,satisfied +13181,75096,Female,Loyal Customer,22,Business travel,Business,1744,3,3,3,3,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +13182,18192,Female,Loyal Customer,56,Business travel,Eco,346,5,2,2,2,4,5,3,5,5,5,5,2,5,5,8,22.0,satisfied +13183,32202,Female,Loyal Customer,41,Business travel,Business,101,2,2,2,2,4,3,4,5,5,5,4,4,5,5,0,0.0,satisfied +13184,47549,Female,Loyal Customer,50,Business travel,Eco Plus,588,4,1,1,1,3,1,4,4,4,4,4,3,4,3,0,0.0,satisfied +13185,126493,Male,Loyal Customer,44,Personal Travel,Eco,1788,1,2,1,3,5,1,5,5,4,3,1,4,3,5,0,0.0,neutral or dissatisfied +13186,43387,Male,Loyal Customer,53,Personal Travel,Eco,402,2,4,2,2,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +13187,95506,Male,Loyal Customer,51,Business travel,Eco Plus,239,3,2,2,2,4,3,4,4,3,2,4,3,4,4,4,0.0,neutral or dissatisfied +13188,21138,Male,Loyal Customer,44,Personal Travel,Eco,214,2,0,2,2,4,2,4,4,2,4,1,1,2,4,0,0.0,neutral or dissatisfied +13189,49582,Male,Loyal Customer,56,Business travel,Business,209,5,5,5,5,2,5,1,5,5,5,5,5,5,4,0,0.0,satisfied +13190,27591,Male,Loyal Customer,20,Personal Travel,Eco,956,4,5,5,1,5,5,4,5,4,4,4,4,5,5,0,10.0,neutral or dissatisfied +13191,58327,Male,Loyal Customer,16,Personal Travel,Eco,1739,2,5,1,4,2,1,4,2,5,2,5,5,4,2,11,0.0,neutral or dissatisfied +13192,77023,Female,disloyal Customer,47,Business travel,Eco,368,1,0,1,2,5,1,5,5,3,4,5,2,5,5,2,0.0,neutral or dissatisfied +13193,81552,Male,Loyal Customer,47,Business travel,Business,936,5,5,5,5,2,4,4,5,5,5,5,5,5,4,0,6.0,satisfied +13194,121523,Female,Loyal Customer,40,Business travel,Business,936,5,5,5,5,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +13195,57987,Female,Loyal Customer,27,Personal Travel,Eco Plus,589,2,4,2,3,5,2,5,5,3,3,4,4,4,5,16,4.0,neutral or dissatisfied +13196,77300,Female,Loyal Customer,47,Business travel,Business,3913,5,5,5,5,3,5,5,5,5,5,5,5,5,3,0,1.0,satisfied +13197,105696,Female,Loyal Customer,38,Business travel,Eco,842,2,2,2,2,2,2,2,2,2,3,4,4,4,2,0,10.0,neutral or dissatisfied +13198,73889,Female,disloyal Customer,26,Business travel,Business,2342,3,3,3,2,3,2,2,4,2,5,5,2,3,2,0,0.0,neutral or dissatisfied +13199,89967,Male,Loyal Customer,31,Personal Travel,Eco,1310,2,5,2,2,5,2,5,5,5,3,4,5,5,5,0,20.0,neutral or dissatisfied +13200,63033,Female,Loyal Customer,25,Business travel,Business,462,3,4,4,4,3,3,3,3,3,5,4,2,4,3,96,78.0,neutral or dissatisfied +13201,44456,Female,Loyal Customer,13,Personal Travel,Eco,802,2,4,2,4,4,2,4,4,1,2,4,4,4,4,33,7.0,neutral or dissatisfied +13202,72140,Female,Loyal Customer,31,Business travel,Business,2468,3,3,3,3,4,5,4,4,4,2,5,3,2,4,32,41.0,satisfied +13203,79774,Male,Loyal Customer,45,Business travel,Business,3563,2,5,5,5,2,3,4,2,2,2,2,4,2,1,119,104.0,neutral or dissatisfied +13204,4381,Female,Loyal Customer,37,Business travel,Eco,207,2,5,5,5,2,2,2,2,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +13205,34494,Male,Loyal Customer,35,Business travel,Eco,1990,3,4,4,4,3,3,3,3,4,2,1,3,3,3,0,0.0,satisfied +13206,116333,Female,Loyal Customer,7,Personal Travel,Eco,308,2,4,2,2,2,2,2,2,5,2,5,4,4,2,21,13.0,neutral or dissatisfied +13207,103153,Female,Loyal Customer,52,Business travel,Business,491,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +13208,69485,Male,Loyal Customer,37,Business travel,Eco Plus,1089,3,3,3,3,3,3,3,3,3,1,3,1,3,3,0,13.0,neutral or dissatisfied +13209,111281,Female,Loyal Customer,13,Personal Travel,Eco,479,3,5,2,3,3,2,3,3,2,3,3,4,1,3,2,0.0,neutral or dissatisfied +13210,37570,Female,disloyal Customer,40,Business travel,Business,744,2,2,2,3,5,2,5,5,2,3,3,5,5,5,0,0.0,neutral or dissatisfied +13211,101433,Male,Loyal Customer,31,Personal Travel,Business,345,3,2,3,3,4,3,4,4,4,4,3,2,3,4,0,0.0,neutral or dissatisfied +13212,86938,Female,Loyal Customer,36,Business travel,Business,3657,3,5,5,5,4,3,3,3,3,3,3,3,3,1,3,0.0,neutral or dissatisfied +13213,60146,Male,Loyal Customer,56,Business travel,Eco,1197,1,4,4,4,1,1,1,1,1,2,3,3,4,1,10,13.0,neutral or dissatisfied +13214,44553,Male,Loyal Customer,56,Personal Travel,Eco,157,3,2,0,3,4,0,4,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +13215,78759,Female,Loyal Customer,38,Business travel,Business,1507,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +13216,111257,Female,Loyal Customer,19,Personal Travel,Eco,1849,4,5,4,1,4,4,1,4,4,1,1,2,2,4,0,0.0,neutral or dissatisfied +13217,58527,Female,Loyal Customer,64,Personal Travel,Eco,719,3,4,2,4,5,4,4,3,3,2,2,5,3,3,50,23.0,neutral or dissatisfied +13218,115236,Female,Loyal Customer,69,Business travel,Business,2561,4,1,5,1,1,3,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +13219,40444,Female,Loyal Customer,62,Business travel,Eco,290,5,1,1,1,3,4,4,5,5,5,5,2,5,1,0,1.0,satisfied +13220,35522,Male,Loyal Customer,50,Personal Travel,Eco,972,4,5,4,5,4,4,5,4,5,3,5,4,4,4,0,0.0,satisfied +13221,37190,Female,Loyal Customer,26,Business travel,Eco Plus,1189,4,3,3,3,4,5,4,4,4,4,1,3,1,4,0,0.0,satisfied +13222,24508,Male,Loyal Customer,12,Personal Travel,Eco,547,3,2,3,3,5,3,5,5,2,2,3,3,4,5,0,0.0,neutral or dissatisfied +13223,51297,Female,Loyal Customer,55,Business travel,Eco Plus,209,4,4,4,4,1,4,3,4,4,4,4,1,4,4,0,0.0,satisfied +13224,129515,Female,Loyal Customer,37,Personal Travel,Eco,1744,1,5,1,2,2,1,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +13225,122401,Male,Loyal Customer,31,Business travel,Business,2941,3,3,3,3,4,5,4,4,5,3,4,5,4,4,0,0.0,satisfied +13226,114738,Female,Loyal Customer,46,Business travel,Business,358,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13227,31063,Female,Loyal Customer,50,Business travel,Eco,241,4,4,4,4,5,3,4,4,4,4,4,4,4,1,29,35.0,satisfied +13228,9816,Female,Loyal Customer,33,Business travel,Business,3214,5,5,5,5,5,4,4,4,4,4,4,3,4,4,16,15.0,satisfied +13229,37874,Male,Loyal Customer,38,Business travel,Business,1578,3,4,4,4,3,3,3,2,5,2,3,3,2,3,151,137.0,neutral or dissatisfied +13230,22958,Male,Loyal Customer,44,Business travel,Business,817,1,1,1,1,5,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +13231,40087,Male,Loyal Customer,54,Personal Travel,Eco Plus,493,4,4,4,1,3,4,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +13232,82727,Female,disloyal Customer,11,Business travel,Eco,632,0,5,0,5,3,0,5,3,5,3,5,4,5,3,0,0.0,satisfied +13233,871,Male,Loyal Customer,25,Business travel,Business,2661,1,1,1,1,1,1,1,1,1,2,3,3,4,1,30,31.0,neutral or dissatisfied +13234,102231,Female,disloyal Customer,24,Business travel,Eco,223,4,4,4,4,5,4,5,5,4,2,4,3,4,5,0,4.0,neutral or dissatisfied +13235,63098,Male,disloyal Customer,30,Business travel,Eco Plus,967,4,4,4,4,3,4,3,3,2,2,3,4,4,3,1,0.0,neutral or dissatisfied +13236,91698,Female,Loyal Customer,57,Business travel,Business,590,5,5,5,5,4,4,5,5,5,5,5,3,5,4,40,40.0,satisfied +13237,20967,Male,Loyal Customer,43,Business travel,Business,2833,2,2,2,2,2,3,5,5,5,5,5,3,5,3,0,0.0,satisfied +13238,45496,Female,Loyal Customer,8,Personal Travel,Eco,674,3,4,3,4,4,3,4,4,3,3,5,5,5,4,9,13.0,neutral or dissatisfied +13239,73022,Female,Loyal Customer,25,Personal Travel,Eco,1089,3,3,3,5,5,3,4,5,4,1,2,5,2,5,0,0.0,neutral or dissatisfied +13240,50621,Male,Loyal Customer,63,Personal Travel,Eco,372,3,1,3,4,1,3,1,1,3,1,4,3,3,1,0,16.0,neutral or dissatisfied +13241,128865,Female,Loyal Customer,34,Business travel,Business,2454,4,5,4,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +13242,110189,Male,Loyal Customer,63,Personal Travel,Eco,979,4,5,3,3,1,3,1,1,5,4,4,5,4,1,7,17.0,neutral or dissatisfied +13243,97573,Female,Loyal Customer,59,Business travel,Eco,337,2,3,3,3,1,3,2,2,2,2,2,3,2,2,22,12.0,neutral or dissatisfied +13244,37661,Female,Loyal Customer,10,Personal Travel,Eco,1074,4,4,4,3,4,4,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +13245,87257,Male,Loyal Customer,40,Business travel,Business,577,4,4,5,4,3,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +13246,61500,Male,Loyal Customer,32,Business travel,Business,2419,1,4,4,4,1,1,1,1,1,1,3,1,3,1,36,13.0,neutral or dissatisfied +13247,26802,Female,Loyal Customer,59,Business travel,Business,2139,2,1,1,1,4,3,3,2,2,2,2,2,2,4,42,21.0,neutral or dissatisfied +13248,86613,Male,disloyal Customer,25,Business travel,Business,746,5,5,5,4,2,5,1,2,5,5,4,4,5,2,1,0.0,satisfied +13249,63291,Male,Loyal Customer,33,Business travel,Business,337,3,4,4,4,3,3,3,3,2,5,4,2,3,3,19,13.0,neutral or dissatisfied +13250,954,Female,Loyal Customer,56,Business travel,Business,2618,2,4,4,4,2,3,3,3,3,3,2,1,3,2,0,1.0,neutral or dissatisfied +13251,15169,Male,Loyal Customer,45,Business travel,Eco,416,4,4,4,4,4,4,4,4,1,1,1,4,5,4,2,0.0,satisfied +13252,38071,Male,disloyal Customer,48,Business travel,Eco,1249,2,1,1,3,1,1,2,1,1,1,2,2,3,1,0,0.0,neutral or dissatisfied +13253,101117,Female,disloyal Customer,27,Business travel,Business,1235,4,4,4,4,3,4,3,3,3,5,5,3,5,3,0,0.0,satisfied +13254,50827,Male,Loyal Customer,66,Personal Travel,Eco,86,3,2,3,4,3,3,3,3,1,2,4,3,4,3,6,4.0,neutral or dissatisfied +13255,36983,Male,Loyal Customer,46,Business travel,Eco,759,4,3,3,3,4,4,4,4,1,1,3,2,1,4,0,0.0,satisfied +13256,129272,Female,Loyal Customer,56,Business travel,Business,2402,5,5,5,5,3,4,4,4,4,4,4,5,4,5,6,0.0,satisfied +13257,59840,Female,disloyal Customer,38,Business travel,Business,1085,5,5,5,4,1,5,1,1,5,3,4,4,4,1,32,30.0,satisfied +13258,39651,Female,Loyal Customer,52,Business travel,Business,3005,1,0,0,4,5,3,3,4,4,0,4,2,4,4,13,11.0,neutral or dissatisfied +13259,68647,Female,Loyal Customer,45,Business travel,Business,175,4,5,4,4,5,5,4,4,4,5,4,4,4,5,61,65.0,satisfied +13260,107781,Female,Loyal Customer,34,Business travel,Business,3821,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +13261,89585,Female,disloyal Customer,23,Business travel,Business,1010,4,4,4,3,1,4,1,1,4,5,4,5,5,1,67,32.0,satisfied +13262,118354,Male,Loyal Customer,19,Personal Travel,Eco,602,4,4,4,3,5,4,5,5,5,5,5,3,5,5,0,18.0,neutral or dissatisfied +13263,32491,Male,disloyal Customer,38,Business travel,Eco,101,2,2,2,4,2,2,2,2,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +13264,15251,Male,Loyal Customer,12,Personal Travel,Eco,416,3,1,3,4,5,3,1,5,4,5,3,3,4,5,0,0.0,neutral or dissatisfied +13265,58325,Male,disloyal Customer,35,Business travel,Eco,1472,2,2,2,4,5,2,5,5,5,5,2,2,1,5,0,0.0,neutral or dissatisfied +13266,67931,Female,Loyal Customer,15,Personal Travel,Eco,1188,3,4,3,2,5,3,1,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +13267,18325,Female,Loyal Customer,16,Business travel,Eco Plus,715,4,3,3,3,4,5,3,4,2,3,1,5,2,4,0,0.0,satisfied +13268,47336,Female,Loyal Customer,29,Business travel,Business,2524,1,5,5,5,1,1,1,1,1,4,3,1,4,1,6,19.0,neutral or dissatisfied +13269,59612,Female,Loyal Customer,50,Business travel,Business,3019,1,3,1,1,2,5,5,4,4,4,4,5,4,5,0,3.0,satisfied +13270,83793,Male,Loyal Customer,48,Business travel,Business,2072,4,4,4,4,3,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +13271,1895,Male,Loyal Customer,55,Business travel,Business,2366,1,1,1,1,2,5,5,4,4,4,4,4,4,5,18,26.0,satisfied +13272,97239,Female,Loyal Customer,17,Business travel,Eco,296,1,4,4,4,1,1,1,1,2,1,2,2,3,1,14,41.0,neutral or dissatisfied +13273,25449,Male,Loyal Customer,49,Personal Travel,Eco,669,3,4,3,4,3,3,3,3,3,2,5,3,5,3,26,12.0,neutral or dissatisfied +13274,86262,Male,Loyal Customer,17,Personal Travel,Eco,226,2,4,2,3,5,2,2,5,5,1,5,4,2,5,0,0.0,neutral or dissatisfied +13275,111800,Female,Loyal Customer,51,Business travel,Business,349,1,1,1,1,4,5,5,4,4,5,4,4,4,3,10,0.0,satisfied +13276,87196,Male,Loyal Customer,43,Business travel,Business,2250,3,4,4,4,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +13277,28045,Female,disloyal Customer,38,Business travel,Business,239,4,4,4,5,2,4,2,2,5,5,5,3,4,2,5,0.0,neutral or dissatisfied +13278,41806,Female,disloyal Customer,36,Business travel,Eco,196,1,4,1,4,3,1,4,3,1,3,2,1,5,3,12,4.0,neutral or dissatisfied +13279,3302,Female,Loyal Customer,51,Business travel,Business,1964,1,4,4,4,4,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +13280,42634,Female,Loyal Customer,61,Business travel,Business,3789,5,5,4,5,4,4,4,5,2,2,3,4,1,4,218,189.0,satisfied +13281,120497,Female,Loyal Customer,45,Business travel,Business,3471,2,2,2,2,5,5,5,4,4,4,4,3,4,5,22,15.0,satisfied +13282,103654,Male,Loyal Customer,58,Business travel,Business,466,4,4,4,4,3,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +13283,86476,Female,Loyal Customer,52,Business travel,Eco,749,3,2,2,2,3,3,4,3,3,3,3,3,3,3,17,26.0,neutral or dissatisfied +13284,35521,Male,Loyal Customer,69,Personal Travel,Eco,944,3,4,2,4,3,2,1,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +13285,104607,Female,Loyal Customer,66,Personal Travel,Eco,369,1,3,1,1,1,2,2,2,1,2,4,2,3,2,145,164.0,neutral or dissatisfied +13286,23741,Male,Loyal Customer,52,Personal Travel,Eco,639,4,4,4,3,2,4,2,2,4,4,4,5,5,2,8,36.0,neutral or dissatisfied +13287,96912,Female,Loyal Customer,42,Personal Travel,Eco,571,4,5,4,3,4,1,2,1,1,4,1,5,1,1,10,3.0,neutral or dissatisfied +13288,123833,Female,Loyal Customer,53,Business travel,Eco,544,2,2,2,2,4,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +13289,61844,Female,Loyal Customer,36,Business travel,Business,1346,5,5,4,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +13290,80274,Male,disloyal Customer,48,Business travel,Business,746,2,1,1,5,1,2,1,1,3,2,5,3,5,1,0,6.0,neutral or dissatisfied +13291,8406,Male,disloyal Customer,39,Business travel,Business,862,4,5,5,3,5,1,1,1,3,4,4,1,1,1,171,167.0,neutral or dissatisfied +13292,121138,Male,Loyal Customer,55,Business travel,Business,2370,2,2,2,2,5,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +13293,52519,Male,Loyal Customer,46,Business travel,Eco,119,5,2,2,2,5,5,5,5,1,3,5,5,5,5,0,0.0,satisfied +13294,78337,Male,Loyal Customer,56,Business travel,Eco,1547,3,3,3,3,3,3,3,3,2,5,1,1,1,3,5,0.0,neutral or dissatisfied +13295,30240,Male,Loyal Customer,70,Personal Travel,Eco,896,5,5,5,4,4,5,4,4,3,4,4,5,4,4,0,0.0,satisfied +13296,9777,Male,Loyal Customer,49,Personal Travel,Eco,383,4,2,4,4,1,4,1,1,4,1,4,3,4,1,75,85.0,satisfied +13297,32655,Male,Loyal Customer,33,Business travel,Business,2591,0,4,0,4,4,4,4,4,4,2,2,2,5,4,0,0.0,satisfied +13298,68129,Female,Loyal Customer,60,Personal Travel,Eco,813,3,4,4,3,1,4,4,5,5,4,5,3,5,1,15,3.0,neutral or dissatisfied +13299,51211,Male,Loyal Customer,66,Business travel,Eco Plus,337,5,3,3,3,5,5,5,5,1,2,2,2,4,5,0,0.0,satisfied +13300,72508,Female,Loyal Customer,41,Business travel,Business,2736,4,4,2,4,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +13301,98695,Female,Loyal Customer,22,Personal Travel,Eco,992,2,4,2,4,2,2,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +13302,104149,Male,disloyal Customer,45,Business travel,Business,349,1,1,1,4,4,1,4,4,4,3,4,4,5,4,6,6.0,neutral or dissatisfied +13303,116314,Female,Loyal Customer,10,Personal Travel,Eco,337,1,5,1,2,5,1,5,5,5,3,4,5,4,5,27,37.0,neutral or dissatisfied +13304,29582,Female,Loyal Customer,57,Business travel,Eco,680,3,3,3,3,1,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +13305,17774,Female,Loyal Customer,52,Business travel,Eco,1042,4,3,5,3,4,4,4,1,4,4,5,4,1,4,227,223.0,satisfied +13306,105414,Male,Loyal Customer,36,Business travel,Business,452,1,1,1,1,4,4,4,3,3,3,3,4,3,5,23,26.0,satisfied +13307,88202,Male,Loyal Customer,57,Business travel,Business,2433,1,1,1,1,2,5,5,5,5,5,5,3,5,4,2,0.0,satisfied +13308,88605,Female,Loyal Customer,61,Personal Travel,Eco,594,1,3,1,3,5,2,4,2,2,1,2,5,2,1,24,20.0,neutral or dissatisfied +13309,110064,Female,disloyal Customer,25,Business travel,Eco Plus,2039,2,3,2,4,1,2,1,1,1,5,2,4,3,1,0,6.0,neutral or dissatisfied +13310,21021,Female,Loyal Customer,42,Business travel,Eco,332,4,5,5,5,2,4,2,4,4,4,4,5,4,2,93,115.0,satisfied +13311,93993,Female,Loyal Customer,9,Personal Travel,Eco,1315,3,5,3,4,2,3,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +13312,75273,Male,Loyal Customer,51,Personal Travel,Eco,1744,3,0,3,3,1,3,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +13313,37520,Female,Loyal Customer,34,Business travel,Business,3936,2,2,2,2,3,2,2,2,2,3,1,2,1,2,252,235.0,satisfied +13314,48726,Male,Loyal Customer,49,Business travel,Business,89,2,2,2,2,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +13315,83906,Male,disloyal Customer,26,Business travel,Business,752,0,0,0,1,5,0,5,5,4,3,4,4,4,5,0,0.0,satisfied +13316,17026,Male,Loyal Customer,56,Personal Travel,Eco,781,3,3,3,3,2,3,2,2,2,1,3,1,1,2,0,0.0,neutral or dissatisfied +13317,22645,Female,Loyal Customer,45,Personal Travel,Eco,300,3,4,3,2,2,5,4,1,1,3,1,3,1,4,3,5.0,neutral or dissatisfied +13318,28318,Female,Loyal Customer,44,Business travel,Eco,867,2,2,2,2,3,3,3,2,2,2,2,4,2,2,14,9.0,neutral or dissatisfied +13319,46515,Male,disloyal Customer,27,Business travel,Eco,73,1,0,1,4,1,1,1,2,5,1,3,1,5,1,145,143.0,neutral or dissatisfied +13320,42105,Male,disloyal Customer,47,Business travel,Eco,996,4,4,4,2,1,4,1,1,5,5,4,5,2,1,0,0.0,satisfied +13321,101719,Female,Loyal Customer,64,Personal Travel,Eco,986,4,4,4,4,4,2,4,5,2,5,4,4,5,4,134,121.0,neutral or dissatisfied +13322,88972,Female,Loyal Customer,52,Business travel,Business,1651,2,2,1,2,5,4,5,4,4,4,4,4,4,2,0,0.0,satisfied +13323,82389,Female,disloyal Customer,28,Business travel,Business,501,4,4,4,1,3,4,3,3,4,5,5,4,4,3,72,80.0,satisfied +13324,228,Female,Loyal Customer,17,Personal Travel,Eco,213,3,4,3,4,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +13325,31956,Male,Loyal Customer,32,Business travel,Business,1968,3,1,1,1,1,1,3,1,3,5,3,1,4,1,0,0.0,neutral or dissatisfied +13326,110587,Male,Loyal Customer,67,Personal Travel,Eco,551,3,1,3,2,3,3,2,3,2,5,2,1,2,3,17,13.0,neutral or dissatisfied +13327,61495,Male,Loyal Customer,31,Business travel,Business,2288,3,2,2,2,3,3,3,3,2,2,3,4,4,3,4,0.0,neutral or dissatisfied +13328,93213,Female,Loyal Customer,68,Personal Travel,Eco,1845,2,5,2,1,5,5,5,4,4,2,4,4,4,5,10,5.0,neutral or dissatisfied +13329,118907,Female,Loyal Customer,53,Business travel,Business,2363,2,2,2,2,2,1,5,5,5,5,4,2,5,5,7,0.0,satisfied +13330,41960,Female,Loyal Customer,51,Business travel,Business,2041,1,1,5,1,3,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +13331,105421,Female,Loyal Customer,39,Business travel,Business,3648,2,2,4,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +13332,107514,Male,Loyal Customer,56,Business travel,Business,838,1,1,1,1,3,4,4,4,4,4,4,3,4,4,21,17.0,satisfied +13333,83498,Male,disloyal Customer,16,Business travel,Eco,946,1,1,1,3,1,1,1,1,2,4,3,3,4,1,0,35.0,neutral or dissatisfied +13334,63844,Female,Loyal Customer,40,Business travel,Business,3507,4,4,4,4,2,5,5,4,4,4,4,4,4,5,34,30.0,satisfied +13335,104540,Male,Loyal Customer,32,Personal Travel,Eco,1047,2,5,2,1,3,2,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +13336,109212,Male,Loyal Customer,52,Business travel,Business,3426,1,1,3,1,4,1,2,4,4,5,4,2,4,1,0,1.0,satisfied +13337,93843,Female,Loyal Customer,47,Personal Travel,Eco,391,4,5,4,3,4,4,5,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +13338,44051,Male,Loyal Customer,30,Personal Travel,Eco,237,2,5,2,3,5,2,5,5,4,3,4,3,5,5,0,8.0,neutral or dissatisfied +13339,61111,Female,disloyal Customer,24,Business travel,Eco,1065,3,3,3,3,4,3,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +13340,55530,Female,Loyal Customer,77,Business travel,Eco,550,3,1,1,1,3,4,3,3,3,3,3,2,3,4,8,0.0,neutral or dissatisfied +13341,115685,Female,Loyal Customer,40,Business travel,Eco,480,2,3,3,3,2,2,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +13342,72141,Male,Loyal Customer,64,Business travel,Eco,331,2,1,3,1,2,2,2,2,5,1,4,3,2,2,0,0.0,satisfied +13343,53741,Female,Loyal Customer,33,Business travel,Eco Plus,1208,0,0,0,2,1,0,1,1,1,4,2,2,4,1,15,0.0,satisfied +13344,47681,Male,Loyal Customer,56,Personal Travel,Eco,1428,1,4,1,1,1,1,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +13345,94647,Male,disloyal Customer,38,Business travel,Business,187,2,2,2,4,3,2,3,3,4,4,5,5,5,3,17,9.0,neutral or dissatisfied +13346,34505,Male,Loyal Customer,27,Business travel,Business,1521,2,2,2,2,5,5,5,5,4,2,3,4,1,5,5,0.0,satisfied +13347,79573,Male,Loyal Customer,25,Business travel,Business,3861,1,1,3,1,4,4,4,4,4,2,5,3,4,4,70,54.0,satisfied +13348,82110,Female,Loyal Customer,48,Personal Travel,Eco,1276,1,4,1,1,4,4,5,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +13349,93269,Female,Loyal Customer,36,Business travel,Business,867,4,4,4,4,5,5,5,5,5,5,5,4,5,5,3,0.0,satisfied +13350,86166,Male,disloyal Customer,27,Business travel,Business,226,4,4,4,5,2,4,3,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +13351,3845,Male,Loyal Customer,25,Personal Travel,Eco,650,2,1,2,2,4,2,4,4,2,2,2,1,3,4,4,0.0,neutral or dissatisfied +13352,67344,Male,Loyal Customer,11,Personal Travel,Eco,1471,4,4,4,4,5,4,5,5,4,4,3,5,4,5,0,0.0,neutral or dissatisfied +13353,42780,Male,Loyal Customer,20,Personal Travel,Eco,744,2,1,1,4,5,1,2,5,2,4,3,1,3,5,52,43.0,neutral or dissatisfied +13354,93313,Male,Loyal Customer,11,Personal Travel,Eco,1733,1,4,1,1,5,1,1,5,5,4,3,3,2,5,0,0.0,neutral or dissatisfied +13355,51569,Male,Loyal Customer,23,Business travel,Eco,598,4,5,3,5,4,4,3,4,2,3,1,4,4,4,0,0.0,satisfied +13356,52286,Male,Loyal Customer,54,Business travel,Eco,370,3,4,4,4,3,3,3,3,2,4,2,4,2,3,4,0.0,neutral or dissatisfied +13357,70995,Female,Loyal Customer,57,Business travel,Business,2677,1,1,4,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +13358,121143,Male,Loyal Customer,29,Business travel,Business,2521,3,3,3,3,5,4,5,5,5,3,5,3,5,5,15,0.0,satisfied +13359,6889,Male,Loyal Customer,26,Business travel,Business,265,5,5,5,5,4,4,4,4,3,4,4,4,5,4,168,169.0,satisfied +13360,53181,Male,Loyal Customer,43,Business travel,Business,589,4,4,2,4,4,4,4,4,3,1,4,4,2,4,160,266.0,satisfied +13361,7827,Female,Loyal Customer,36,Personal Travel,Eco,650,3,5,3,2,4,3,4,4,3,3,1,5,2,4,0,0.0,neutral or dissatisfied +13362,69608,Male,Loyal Customer,11,Personal Travel,Eco,2475,2,5,2,2,2,4,4,1,3,5,1,4,1,4,0,0.0,neutral or dissatisfied +13363,105968,Male,disloyal Customer,21,Business travel,Eco,1073,1,1,1,4,1,3,3,3,1,2,4,3,3,3,0,0.0,neutral or dissatisfied +13364,12745,Male,Loyal Customer,8,Personal Travel,Eco,721,2,3,2,4,1,2,2,1,1,3,2,2,4,1,0,0.0,neutral or dissatisfied +13365,57869,Male,Loyal Customer,53,Business travel,Business,2313,3,3,3,3,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +13366,90588,Female,Loyal Customer,59,Business travel,Business,581,4,4,4,4,2,5,4,3,3,2,3,3,3,3,0,0.0,satisfied +13367,18819,Female,disloyal Customer,36,Business travel,Eco,448,1,3,1,4,2,1,2,2,2,2,4,5,5,2,51,45.0,neutral or dissatisfied +13368,93251,Male,Loyal Customer,32,Business travel,Business,1180,1,1,1,1,1,1,1,1,1,4,3,2,3,1,17,4.0,neutral or dissatisfied +13369,36063,Male,Loyal Customer,61,Business travel,Business,399,2,2,2,2,2,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +13370,39065,Female,Loyal Customer,32,Business travel,Business,3001,2,2,2,2,2,2,2,2,2,2,3,1,3,2,55,63.0,neutral or dissatisfied +13371,114587,Male,Loyal Customer,43,Business travel,Business,2998,2,2,2,2,3,4,4,2,2,2,2,5,2,3,12,10.0,satisfied +13372,111949,Male,Loyal Customer,57,Business travel,Business,533,5,5,5,5,5,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +13373,93155,Male,disloyal Customer,34,Business travel,Business,1066,2,3,3,4,3,5,5,4,5,4,3,5,1,5,291,292.0,neutral or dissatisfied +13374,115542,Female,disloyal Customer,27,Business travel,Eco,373,2,4,2,4,4,2,4,4,4,3,4,3,4,4,96,83.0,neutral or dissatisfied +13375,48886,Female,Loyal Customer,41,Business travel,Business,2529,0,5,0,1,1,2,1,5,5,3,3,4,5,4,0,0.0,satisfied +13376,110732,Female,Loyal Customer,40,Business travel,Business,3309,4,4,4,4,3,4,4,4,4,5,4,4,4,3,18,0.0,satisfied +13377,89273,Male,Loyal Customer,53,Business travel,Business,453,3,4,3,3,3,4,4,4,4,4,4,5,4,3,12,6.0,satisfied +13378,117516,Female,Loyal Customer,27,Personal Travel,Eco Plus,507,2,5,2,3,1,2,1,1,5,5,4,5,4,1,1,13.0,neutral or dissatisfied +13379,99090,Male,Loyal Customer,40,Business travel,Business,3797,2,1,1,1,1,2,2,2,2,2,2,2,2,3,1,0.0,neutral or dissatisfied +13380,18750,Male,Loyal Customer,34,Personal Travel,Eco,1167,4,4,4,3,4,2,5,3,5,3,4,5,4,5,124,141.0,satisfied +13381,42717,Female,disloyal Customer,29,Business travel,Eco,912,2,2,2,3,3,2,2,3,3,2,3,3,4,3,0,0.0,neutral or dissatisfied +13382,44502,Male,disloyal Customer,23,Business travel,Eco,411,1,3,0,5,5,0,5,5,3,1,5,2,2,5,4,2.0,neutral or dissatisfied +13383,4703,Male,Loyal Customer,18,Personal Travel,Eco,489,4,3,4,4,4,4,4,4,1,4,4,4,1,4,193,195.0,neutral or dissatisfied +13384,34261,Male,Loyal Customer,38,Business travel,Business,280,1,1,1,1,5,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +13385,71547,Male,Loyal Customer,18,Business travel,Eco,1182,2,4,5,5,2,2,2,2,2,1,3,1,4,2,0,0.0,neutral or dissatisfied +13386,77832,Male,Loyal Customer,19,Personal Travel,Eco,874,4,3,4,4,2,4,2,2,4,2,4,1,4,2,29,16.0,neutral or dissatisfied +13387,126343,Male,Loyal Customer,64,Personal Travel,Eco,590,3,4,3,3,1,3,1,1,1,1,1,1,4,1,0,6.0,neutral or dissatisfied +13388,63857,Female,Loyal Customer,56,Business travel,Business,1591,3,3,2,3,2,4,5,4,4,4,4,5,4,3,0,18.0,satisfied +13389,53957,Male,Loyal Customer,40,Business travel,Eco,1117,5,1,1,1,5,5,5,5,1,4,5,5,1,5,0,0.0,satisfied +13390,51629,Male,Loyal Customer,56,Business travel,Business,493,3,3,3,3,5,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +13391,75924,Female,Loyal Customer,48,Business travel,Business,1526,0,4,0,4,2,5,5,1,1,1,1,5,1,5,0,0.0,satisfied +13392,32211,Male,disloyal Customer,38,Business travel,Eco,163,1,5,1,1,4,1,1,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +13393,4873,Male,Loyal Customer,68,Personal Travel,Eco,408,2,5,2,3,4,2,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +13394,77478,Female,disloyal Customer,15,Business travel,Eco,2125,3,2,2,3,3,3,3,3,1,3,3,2,3,3,8,16.0,neutral or dissatisfied +13395,18684,Male,Loyal Customer,54,Personal Travel,Eco,201,4,5,4,4,4,4,4,4,1,1,2,3,5,4,0,0.0,neutral or dissatisfied +13396,37657,Female,Loyal Customer,15,Personal Travel,Eco,1035,2,1,2,2,1,2,1,1,4,1,3,2,3,1,10,0.0,neutral or dissatisfied +13397,92202,Female,Loyal Customer,46,Business travel,Business,1956,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +13398,45191,Male,Loyal Customer,26,Business travel,Business,1437,4,4,4,4,4,4,4,4,2,4,4,3,5,4,36,32.0,satisfied +13399,19967,Male,Loyal Customer,41,Business travel,Business,557,2,2,2,2,3,3,2,4,4,4,4,2,4,4,30,24.0,satisfied +13400,21630,Female,Loyal Customer,51,Personal Travel,Eco,780,3,5,3,1,3,4,4,2,2,3,2,4,2,4,1,2.0,neutral or dissatisfied +13401,58565,Male,Loyal Customer,62,Business travel,Business,416,2,2,2,2,4,5,4,5,5,5,5,5,5,5,11,2.0,satisfied +13402,120560,Male,Loyal Customer,41,Business travel,Business,2845,5,5,5,5,5,2,1,2,2,2,2,3,2,1,9,13.0,satisfied +13403,86703,Male,Loyal Customer,27,Business travel,Business,1747,5,5,2,5,5,5,5,5,4,2,3,5,4,5,10,10.0,satisfied +13404,33881,Male,disloyal Customer,11,Business travel,Business,1105,5,5,5,3,2,5,2,2,2,2,2,5,4,2,0,0.0,satisfied +13405,56991,Male,Loyal Customer,33,Personal Travel,Eco,2454,5,2,5,3,5,5,5,2,4,3,4,5,2,5,13,22.0,satisfied +13406,97448,Male,Loyal Customer,12,Business travel,Business,1633,2,1,1,1,2,2,2,2,3,3,3,2,4,2,13,29.0,neutral or dissatisfied +13407,99160,Male,Loyal Customer,34,Business travel,Business,1675,3,3,4,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +13408,33152,Female,Loyal Customer,53,Personal Travel,Eco,101,3,3,3,3,2,4,4,5,5,3,2,3,5,3,0,0.0,neutral or dissatisfied +13409,92652,Male,Loyal Customer,28,Personal Travel,Eco,453,3,5,3,3,4,3,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +13410,38633,Female,Loyal Customer,31,Business travel,Business,2588,2,2,2,2,4,4,4,4,3,3,5,3,3,4,0,8.0,satisfied +13411,19329,Female,Loyal Customer,29,Business travel,Business,2836,2,3,3,3,2,2,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +13412,50722,Female,Loyal Customer,60,Personal Travel,Eco,109,2,5,2,4,2,5,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +13413,107730,Female,Loyal Customer,51,Personal Travel,Eco,405,2,4,2,1,5,2,4,5,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +13414,26691,Male,Loyal Customer,7,Personal Travel,Eco,404,2,4,3,1,1,3,1,1,3,3,5,3,4,1,0,5.0,neutral or dissatisfied +13415,129130,Female,disloyal Customer,22,Business travel,Eco,954,3,3,3,2,3,3,4,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +13416,79486,Male,Loyal Customer,37,Business travel,Business,2978,4,5,5,5,1,2,2,4,4,4,4,2,4,1,38,45.0,neutral or dissatisfied +13417,127297,Female,disloyal Customer,40,Business travel,Business,707,2,2,2,3,1,2,1,1,4,3,1,2,5,1,5,0.0,neutral or dissatisfied +13418,21905,Male,Loyal Customer,42,Business travel,Eco,448,2,4,4,4,2,2,2,2,1,4,3,1,3,2,0,0.0,satisfied +13419,50264,Male,disloyal Customer,25,Business travel,Eco,372,2,1,2,3,1,2,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +13420,74493,Female,Loyal Customer,29,Business travel,Business,3962,2,2,2,2,4,5,4,4,5,5,4,5,5,4,14,0.0,satisfied +13421,22027,Male,Loyal Customer,15,Business travel,Eco Plus,500,4,4,4,4,4,4,4,4,2,2,4,1,3,4,0,0.0,satisfied +13422,92443,Female,Loyal Customer,39,Business travel,Business,2092,3,3,3,3,4,3,2,3,3,3,3,3,3,4,4,0.0,neutral or dissatisfied +13423,9113,Female,Loyal Customer,43,Business travel,Business,3684,1,2,2,2,1,3,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +13424,27600,Male,Loyal Customer,34,Personal Travel,Eco,937,4,5,4,5,1,4,1,1,5,2,5,5,4,1,0,0.0,satisfied +13425,24711,Female,Loyal Customer,38,Business travel,Eco Plus,397,4,5,5,5,4,4,4,4,1,2,2,1,5,4,0,0.0,satisfied +13426,61245,Male,disloyal Customer,34,Business travel,Eco,967,4,4,4,4,3,4,3,3,1,5,3,2,4,3,0,0.0,neutral or dissatisfied +13427,73826,Male,Loyal Customer,20,Personal Travel,Eco,1194,2,4,2,1,1,2,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +13428,112259,Male,disloyal Customer,46,Business travel,Eco,1546,3,3,3,3,5,3,5,5,2,1,3,2,3,5,38,52.0,neutral or dissatisfied +13429,19981,Female,Loyal Customer,52,Personal Travel,Business,589,3,4,3,4,2,3,3,2,2,3,2,2,2,2,30,22.0,neutral or dissatisfied +13430,26046,Female,Loyal Customer,27,Business travel,Business,432,3,3,3,3,3,3,3,3,3,5,3,2,4,3,14,7.0,neutral or dissatisfied +13431,15153,Female,Loyal Customer,43,Personal Travel,Eco,1042,3,5,3,2,3,2,3,1,1,3,1,3,1,2,0,38.0,neutral or dissatisfied +13432,98013,Male,disloyal Customer,29,Business travel,Business,1014,3,3,3,4,3,3,2,3,3,5,4,3,5,3,5,0.0,neutral or dissatisfied +13433,38906,Male,Loyal Customer,59,Business travel,Eco,205,4,4,4,4,4,4,4,4,5,2,4,5,2,4,0,0.0,satisfied +13434,23054,Female,Loyal Customer,43,Business travel,Business,3517,5,5,5,5,4,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +13435,38958,Male,Loyal Customer,42,Business travel,Business,2202,3,3,3,3,4,5,5,5,5,5,5,4,5,3,1,0.0,satisfied +13436,121047,Male,Loyal Customer,10,Personal Travel,Eco,992,2,1,2,1,3,2,2,3,2,4,1,2,1,3,2,3.0,neutral or dissatisfied +13437,44625,Male,Loyal Customer,20,Business travel,Business,3733,1,1,1,1,4,4,5,4,4,4,4,3,5,4,0,1.0,satisfied +13438,36980,Female,Loyal Customer,22,Business travel,Business,2091,5,5,5,5,4,4,4,4,2,5,3,5,1,4,0,0.0,satisfied +13439,13423,Female,disloyal Customer,13,Business travel,Eco,491,2,0,2,4,5,2,5,5,5,1,1,5,4,5,0,2.0,neutral or dissatisfied +13440,122001,Female,Loyal Customer,55,Business travel,Business,2023,0,4,0,3,5,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +13441,128153,Female,Loyal Customer,44,Business travel,Business,1849,2,2,2,2,5,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +13442,63056,Male,Loyal Customer,24,Personal Travel,Eco,967,1,5,1,3,5,1,5,5,5,2,5,5,5,5,65,67.0,neutral or dissatisfied +13443,67684,Male,Loyal Customer,54,Business travel,Business,1464,3,3,3,3,2,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +13444,127267,Female,Loyal Customer,55,Business travel,Business,2212,3,5,5,5,1,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +13445,57800,Female,Loyal Customer,44,Business travel,Business,1727,5,5,5,5,3,5,5,4,4,4,4,3,4,4,23,20.0,satisfied +13446,34461,Female,Loyal Customer,68,Personal Travel,Eco,228,1,4,1,1,2,4,4,1,1,1,1,4,1,5,0,0.0,neutral or dissatisfied +13447,40493,Male,Loyal Customer,31,Personal Travel,Eco,188,3,4,0,1,3,0,3,3,4,2,5,4,5,3,0,4.0,neutral or dissatisfied +13448,114311,Female,Loyal Customer,70,Personal Travel,Eco,846,3,4,3,3,4,5,5,3,3,3,3,4,3,4,19,21.0,neutral or dissatisfied +13449,80443,Female,Loyal Customer,60,Personal Travel,Eco,2248,3,4,3,2,4,4,4,1,1,3,1,5,1,5,31,129.0,neutral or dissatisfied +13450,87569,Female,Loyal Customer,46,Business travel,Business,3071,4,4,2,4,5,5,4,4,4,4,4,3,4,5,13,3.0,satisfied +13451,21235,Male,Loyal Customer,66,Personal Travel,Eco,317,3,3,3,4,2,3,2,2,5,3,4,3,3,2,28,10.0,neutral or dissatisfied +13452,68133,Male,Loyal Customer,63,Personal Travel,Eco,868,2,3,2,3,4,2,4,4,5,2,1,4,1,4,32,27.0,neutral or dissatisfied +13453,95619,Male,Loyal Customer,8,Personal Travel,Eco,756,4,4,4,1,5,4,2,5,5,4,4,5,5,5,1,0.0,satisfied +13454,11668,Female,Loyal Customer,16,Personal Travel,Eco,1117,1,2,1,4,3,1,3,3,4,4,4,4,3,3,7,0.0,neutral or dissatisfied +13455,65556,Female,Loyal Customer,56,Business travel,Business,175,4,4,4,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +13456,85853,Female,Loyal Customer,51,Business travel,Eco Plus,666,1,5,5,5,2,4,4,1,1,1,1,3,1,4,7,0.0,neutral or dissatisfied +13457,18384,Female,Loyal Customer,41,Business travel,Business,493,3,3,3,3,2,3,2,4,4,4,4,2,4,4,0,0.0,satisfied +13458,41939,Female,Loyal Customer,64,Personal Travel,Eco,129,3,1,3,4,4,3,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +13459,3414,Male,Loyal Customer,65,Personal Travel,Eco,240,2,4,2,2,1,2,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +13460,68222,Male,Loyal Customer,40,Business travel,Business,631,3,3,3,3,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +13461,12164,Female,Loyal Customer,25,Business travel,Business,986,2,2,2,2,4,4,4,4,3,3,4,4,5,4,6,0.0,satisfied +13462,6318,Female,Loyal Customer,57,Business travel,Business,3793,1,1,4,1,2,5,4,4,4,4,4,4,4,5,65,58.0,satisfied +13463,50448,Female,disloyal Customer,44,Business travel,Eco,337,1,0,1,5,2,1,2,2,2,1,4,5,3,2,0,0.0,neutral or dissatisfied +13464,69802,Male,Loyal Customer,59,Business travel,Business,1345,2,2,2,2,5,5,5,5,5,5,5,3,5,4,9,0.0,satisfied +13465,28171,Male,disloyal Customer,35,Business travel,Eco,859,1,1,1,4,3,1,2,3,4,2,3,1,4,3,94,88.0,neutral or dissatisfied +13466,60585,Female,Loyal Customer,36,Business travel,Eco,1158,5,5,5,5,5,5,5,5,2,3,3,5,4,5,0,0.0,satisfied +13467,12384,Male,disloyal Customer,65,Business travel,Eco,262,3,3,3,2,1,3,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +13468,16530,Female,Loyal Customer,42,Business travel,Eco,209,5,4,4,4,4,4,2,5,5,5,5,4,5,3,75,77.0,satisfied +13469,110695,Male,Loyal Customer,33,Personal Travel,Eco,945,2,3,2,5,5,2,5,5,4,4,1,2,3,5,0,4.0,neutral or dissatisfied +13470,112570,Male,Loyal Customer,52,Business travel,Business,3875,2,2,2,2,2,4,5,4,4,4,4,3,4,4,3,0.0,satisfied +13471,86534,Male,Loyal Customer,37,Personal Travel,Eco,762,2,5,2,2,2,2,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +13472,22276,Male,Loyal Customer,35,Business travel,Business,2123,0,5,0,4,3,5,4,2,2,2,2,2,2,1,0,0.0,satisfied +13473,108487,Male,Loyal Customer,46,Business travel,Eco,570,1,3,3,3,2,1,2,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +13474,123124,Male,Loyal Customer,60,Business travel,Business,3889,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +13475,41062,Male,disloyal Customer,21,Business travel,Business,140,0,4,0,4,3,0,3,3,5,4,4,4,4,3,42,42.0,satisfied +13476,73866,Male,disloyal Customer,34,Business travel,Business,2585,4,4,4,4,4,5,5,4,2,5,4,5,5,5,0,0.0,neutral or dissatisfied +13477,64917,Male,Loyal Customer,40,Business travel,Eco,190,1,3,3,3,1,1,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +13478,112590,Female,Loyal Customer,20,Business travel,Business,602,4,4,3,4,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +13479,119873,Male,Loyal Customer,41,Personal Travel,Eco,936,2,4,2,4,1,2,5,1,5,4,4,5,5,1,0,8.0,neutral or dissatisfied +13480,79710,Male,Loyal Customer,18,Personal Travel,Eco,760,2,5,2,3,5,2,5,5,5,2,4,5,4,5,0,4.0,neutral or dissatisfied +13481,94092,Female,Loyal Customer,27,Personal Travel,Business,248,2,4,2,2,5,2,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +13482,113265,Female,disloyal Customer,23,Business travel,Business,223,5,3,5,1,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +13483,110925,Male,Loyal Customer,36,Personal Travel,Eco,406,4,5,4,3,1,4,4,1,5,2,5,3,4,1,43,48.0,neutral or dissatisfied +13484,78120,Male,Loyal Customer,37,Personal Travel,Eco,1619,5,4,5,2,2,5,2,2,4,4,1,4,2,2,1,0.0,satisfied +13485,84056,Male,Loyal Customer,49,Business travel,Business,2590,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +13486,93916,Female,Loyal Customer,50,Business travel,Business,3720,1,1,1,1,2,5,4,4,4,4,4,3,4,5,95,93.0,satisfied +13487,7647,Male,Loyal Customer,45,Business travel,Business,2509,1,1,2,1,4,4,4,5,4,5,5,4,4,4,136,147.0,satisfied +13488,64894,Female,disloyal Customer,26,Business travel,Eco,247,1,1,1,4,1,1,1,1,3,2,4,3,4,1,13,17.0,neutral or dissatisfied +13489,11,Female,disloyal Customer,28,Business travel,Business,821,1,1,1,3,2,1,2,2,2,5,3,3,4,2,0,5.0,neutral or dissatisfied +13490,115188,Male,Loyal Customer,30,Business travel,Business,1635,0,0,0,4,5,5,5,5,3,4,5,4,5,5,16,11.0,satisfied +13491,111291,Male,Loyal Customer,50,Personal Travel,Eco Plus,479,4,3,4,4,3,4,3,3,1,5,4,4,3,3,100,83.0,neutral or dissatisfied +13492,53383,Female,Loyal Customer,57,Personal Travel,Eco,1452,2,3,2,3,3,4,4,1,1,2,1,4,1,2,0,1.0,neutral or dissatisfied +13493,78547,Male,Loyal Customer,21,Personal Travel,Eco,620,1,4,1,4,2,1,2,2,5,2,5,4,4,2,0,12.0,neutral or dissatisfied +13494,44272,Female,Loyal Customer,22,Personal Travel,Eco,222,4,2,4,3,3,4,5,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +13495,143,Female,Loyal Customer,39,Business travel,Business,227,0,0,0,5,2,5,4,2,2,2,2,4,2,4,0,18.0,satisfied +13496,45280,Male,Loyal Customer,42,Business travel,Business,1647,0,4,0,4,4,2,3,4,4,1,1,5,4,1,1,0.0,satisfied +13497,6860,Female,Loyal Customer,45,Business travel,Business,622,1,2,5,2,3,4,3,1,1,1,1,3,1,4,20,27.0,neutral or dissatisfied +13498,58000,Male,Loyal Customer,65,Personal Travel,Eco,1943,3,4,3,5,3,2,2,3,2,5,5,2,4,2,138,140.0,neutral or dissatisfied +13499,79859,Male,Loyal Customer,55,Business travel,Business,1638,1,1,1,1,5,5,5,3,2,5,5,5,5,5,120,141.0,satisfied +13500,93140,Female,disloyal Customer,21,Business travel,Eco,1066,2,2,2,4,5,2,5,5,3,3,4,3,3,5,5,0.0,neutral or dissatisfied +13501,40397,Male,Loyal Customer,56,Business travel,Business,1530,5,5,5,5,5,4,4,4,4,4,5,4,4,5,0,,satisfied +13502,41624,Female,Loyal Customer,42,Personal Travel,Eco Plus,1269,1,5,1,4,5,5,5,3,3,1,3,3,3,3,65,83.0,neutral or dissatisfied +13503,62474,Male,Loyal Customer,37,Business travel,Business,1744,3,3,3,3,2,3,4,4,4,4,4,5,4,5,22,0.0,satisfied +13504,122770,Male,Loyal Customer,51,Personal Travel,Eco,427,5,4,5,2,2,5,2,2,3,2,5,4,5,2,0,0.0,satisfied +13505,44828,Female,Loyal Customer,52,Business travel,Eco,462,3,4,5,4,3,4,3,3,3,3,3,3,3,2,7,21.0,neutral or dissatisfied +13506,18914,Male,Loyal Customer,24,Personal Travel,Eco,448,2,2,2,2,1,2,4,1,3,3,2,4,2,1,2,0.0,neutral or dissatisfied +13507,31352,Female,Loyal Customer,60,Personal Travel,Business,589,2,3,1,2,4,3,5,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +13508,86414,Male,disloyal Customer,24,Business travel,Business,762,0,5,0,5,2,0,2,2,3,4,5,3,5,2,0,5.0,satisfied +13509,74905,Female,Loyal Customer,47,Business travel,Business,2586,1,1,1,1,4,3,4,4,4,5,4,5,4,3,54,46.0,satisfied +13510,123176,Male,Loyal Customer,33,Business travel,Business,2261,2,4,4,4,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +13511,2196,Female,Loyal Customer,23,Personal Travel,Eco,624,3,5,3,4,4,3,4,4,3,4,5,3,5,4,0,22.0,neutral or dissatisfied +13512,119736,Female,Loyal Customer,10,Personal Travel,Eco,1325,3,1,3,3,5,3,5,5,3,4,4,3,3,5,0,0.0,neutral or dissatisfied +13513,17812,Female,Loyal Customer,80,Business travel,Business,675,2,3,3,3,3,4,3,2,2,2,2,2,2,4,21,18.0,neutral or dissatisfied +13514,121194,Female,Loyal Customer,67,Personal Travel,Eco,2402,3,4,4,1,4,1,1,3,2,2,3,1,5,1,110,157.0,neutral or dissatisfied +13515,66763,Male,Loyal Customer,23,Personal Travel,Eco,978,2,5,2,1,3,2,5,3,4,5,5,4,5,3,32,17.0,neutral or dissatisfied +13516,120910,Female,disloyal Customer,23,Business travel,Eco,992,1,1,1,3,3,1,5,3,3,5,5,5,5,3,40,130.0,neutral or dissatisfied +13517,54940,Female,Loyal Customer,41,Business travel,Business,1379,4,5,5,5,4,2,3,4,4,4,4,3,4,2,24,31.0,neutral or dissatisfied +13518,92373,Male,Loyal Customer,29,Business travel,Business,2139,1,1,1,1,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +13519,20043,Female,disloyal Customer,25,Business travel,Eco,607,5,5,5,3,4,5,4,4,4,2,3,3,5,4,7,0.0,satisfied +13520,34520,Female,Loyal Customer,16,Personal Travel,Eco,1521,3,3,3,4,2,3,3,2,4,3,2,4,3,2,0,7.0,neutral or dissatisfied +13521,102157,Female,Loyal Customer,38,Business travel,Business,397,5,5,2,5,5,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +13522,9549,Male,Loyal Customer,52,Business travel,Business,296,5,5,5,5,5,5,4,5,5,5,5,4,5,5,19,6.0,satisfied +13523,64945,Female,disloyal Customer,25,Business travel,Eco,190,3,2,3,4,4,3,4,4,1,1,4,1,4,4,35,29.0,neutral or dissatisfied +13524,50904,Female,Loyal Customer,44,Personal Travel,Eco,250,3,4,3,1,4,5,4,2,2,3,2,5,2,3,0,3.0,neutral or dissatisfied +13525,40548,Female,Loyal Customer,59,Business travel,Eco,411,5,1,1,1,5,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +13526,111211,Male,Loyal Customer,22,Business travel,Business,1506,2,3,3,3,2,2,2,2,2,5,2,4,3,2,1,8.0,neutral or dissatisfied +13527,70914,Male,disloyal Customer,65,Business travel,Business,212,3,3,3,3,1,3,1,1,2,4,4,2,3,1,27,19.0,neutral or dissatisfied +13528,60779,Female,Loyal Customer,53,Personal Travel,Eco,628,1,4,0,5,3,4,5,4,4,0,4,5,4,5,7,4.0,neutral or dissatisfied +13529,122285,Female,Loyal Customer,53,Personal Travel,Eco,546,2,1,2,2,4,1,1,1,1,2,1,3,1,2,26,26.0,neutral or dissatisfied +13530,65478,Female,Loyal Customer,58,Business travel,Business,1067,2,2,2,2,2,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +13531,125724,Male,Loyal Customer,25,Personal Travel,Eco,899,3,4,3,3,5,3,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +13532,36799,Male,Loyal Customer,65,Personal Travel,Eco,2704,3,4,4,3,4,4,4,2,1,3,5,4,1,4,64,92.0,neutral or dissatisfied +13533,72612,Male,Loyal Customer,21,Personal Travel,Eco,918,1,4,2,4,5,2,5,5,3,3,4,5,4,5,10,0.0,neutral or dissatisfied +13534,118605,Female,Loyal Customer,51,Business travel,Business,3212,4,4,4,4,4,4,5,5,5,5,5,5,5,5,3,0.0,satisfied +13535,122734,Female,disloyal Customer,14,Business travel,Eco,651,3,0,3,3,4,3,4,4,1,2,3,2,4,4,96,92.0,neutral or dissatisfied +13536,75255,Female,Loyal Customer,21,Personal Travel,Eco,1744,2,5,2,1,4,2,4,4,4,2,5,5,4,4,2,0.0,neutral or dissatisfied +13537,46905,Female,Loyal Customer,46,Business travel,Business,845,3,5,4,5,4,2,3,3,3,2,3,1,3,1,16,0.0,neutral or dissatisfied +13538,37995,Male,Loyal Customer,39,Business travel,Business,1237,5,5,5,5,1,3,2,5,5,5,5,1,5,3,31,10.0,satisfied +13539,122468,Male,Loyal Customer,52,Business travel,Business,2205,4,4,4,4,1,2,3,4,4,4,4,3,4,1,14,8.0,neutral or dissatisfied +13540,26863,Female,Loyal Customer,56,Business travel,Eco Plus,224,4,4,4,4,2,4,3,4,4,4,4,1,4,3,0,0.0,satisfied +13541,113197,Male,Loyal Customer,40,Business travel,Business,386,2,2,2,2,3,5,5,5,5,4,5,5,5,4,0,6.0,satisfied +13542,56225,Female,Loyal Customer,41,Business travel,Eco,1008,3,4,4,4,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +13543,12323,Male,Loyal Customer,59,Business travel,Business,2364,3,1,1,1,3,3,3,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +13544,89557,Female,disloyal Customer,22,Business travel,Eco,1096,4,4,4,2,4,5,4,3,4,4,4,4,5,4,137,105.0,satisfied +13545,61789,Female,Loyal Customer,18,Personal Travel,Eco,1379,2,2,2,3,5,2,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +13546,29466,Male,Loyal Customer,12,Personal Travel,Eco,2345,3,2,3,4,4,3,4,4,3,4,4,2,4,4,1,0.0,neutral or dissatisfied +13547,30825,Female,Loyal Customer,30,Business travel,Business,896,1,1,1,1,5,5,5,5,2,1,1,4,2,5,100,93.0,satisfied +13548,86913,Female,Loyal Customer,30,Business travel,Business,3874,4,3,3,3,4,3,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +13549,65882,Female,Loyal Customer,30,Business travel,Business,1391,1,1,1,1,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +13550,35023,Female,Loyal Customer,30,Personal Travel,Eco,740,2,5,2,3,5,2,5,5,3,2,5,4,5,5,0,2.0,neutral or dissatisfied +13551,58723,Male,Loyal Customer,42,Personal Travel,Business,1005,0,4,1,1,4,5,4,1,1,1,1,5,1,5,72,61.0,satisfied +13552,49229,Male,Loyal Customer,44,Business travel,Eco,156,2,5,5,5,2,2,2,2,1,4,2,3,1,2,0,0.0,satisfied +13553,38506,Female,Loyal Customer,31,Business travel,Business,2446,2,2,2,2,4,4,4,4,3,5,5,2,2,4,0,0.0,satisfied +13554,90642,Male,Loyal Customer,43,Business travel,Business,594,4,4,4,4,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +13555,90321,Male,Loyal Customer,37,Business travel,Business,271,0,0,0,3,2,5,4,3,3,3,3,3,3,4,1,0.0,satisfied +13556,110741,Male,Loyal Customer,47,Business travel,Business,1912,5,5,5,5,2,4,4,4,4,4,4,3,4,5,84,67.0,satisfied +13557,83832,Male,disloyal Customer,37,Business travel,Eco,425,2,1,2,3,1,2,4,1,3,5,2,3,3,1,3,15.0,neutral or dissatisfied +13558,74326,Female,disloyal Customer,21,Business travel,Eco,1235,2,2,2,2,3,2,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +13559,90146,Female,Loyal Customer,41,Business travel,Business,557,1,1,1,1,3,1,1,4,4,4,4,2,4,2,0,0.0,satisfied +13560,59666,Male,Loyal Customer,23,Personal Travel,Eco,964,4,5,3,3,4,3,4,4,4,4,5,4,4,4,2,0.0,satisfied +13561,78147,Female,Loyal Customer,40,Business travel,Business,1945,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13562,76511,Male,Loyal Customer,56,Business travel,Business,516,1,1,1,1,2,5,4,5,5,5,5,4,5,3,15,38.0,satisfied +13563,98589,Female,Loyal Customer,46,Business travel,Business,1987,5,5,5,5,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +13564,73006,Male,Loyal Customer,46,Personal Travel,Eco,1096,5,4,5,4,5,5,5,5,4,1,3,2,3,5,0,0.0,satisfied +13565,67723,Female,Loyal Customer,37,Business travel,Business,1438,2,5,4,5,5,4,4,2,2,2,2,3,2,2,0,7.0,neutral or dissatisfied +13566,51890,Male,Loyal Customer,51,Business travel,Business,507,5,5,5,5,1,5,4,4,4,4,4,1,4,2,0,9.0,satisfied +13567,17230,Male,disloyal Customer,31,Business travel,Eco,872,3,3,3,5,4,3,4,4,4,2,2,1,1,4,32,28.0,neutral or dissatisfied +13568,68535,Male,disloyal Customer,9,Business travel,Eco,1013,3,3,3,3,3,3,3,3,2,3,4,2,3,3,0,11.0,neutral or dissatisfied +13569,59022,Female,disloyal Customer,27,Business travel,Eco,1744,4,4,4,3,1,4,1,1,4,4,3,2,3,1,56,34.0,neutral or dissatisfied +13570,794,Female,disloyal Customer,22,Business travel,Business,309,0,0,1,4,2,1,3,2,3,2,4,3,4,2,0,0.0,satisfied +13571,115473,Male,Loyal Customer,47,Business travel,Business,3187,1,1,1,1,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +13572,95107,Female,Loyal Customer,69,Personal Travel,Eco,441,3,5,4,3,2,5,4,3,3,4,3,3,3,5,82,74.0,neutral or dissatisfied +13573,123682,Female,disloyal Customer,56,Business travel,Eco,214,1,2,1,2,1,1,1,1,1,2,3,2,2,1,0,0.0,neutral or dissatisfied +13574,112848,Female,Loyal Customer,53,Business travel,Business,2963,3,3,3,3,3,4,4,5,5,4,5,5,5,5,52,37.0,satisfied +13575,25862,Male,Loyal Customer,58,Personal Travel,Eco,692,3,4,3,4,4,3,4,4,4,4,3,1,4,4,1,0.0,neutral or dissatisfied +13576,21858,Female,Loyal Customer,47,Business travel,Eco,448,4,2,2,2,5,5,1,4,4,4,4,4,4,5,127,111.0,satisfied +13577,11712,Female,disloyal Customer,26,Business travel,Business,429,3,0,3,2,2,3,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +13578,45355,Male,Loyal Customer,23,Personal Travel,Eco,290,2,5,2,3,4,2,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +13579,2106,Female,Loyal Customer,63,Personal Travel,Eco,812,3,3,3,4,4,3,4,1,1,3,2,3,1,1,39,34.0,neutral or dissatisfied +13580,39022,Female,Loyal Customer,11,Personal Travel,Eco,313,5,5,5,1,2,5,2,2,3,5,4,5,4,2,81,70.0,satisfied +13581,65427,Male,Loyal Customer,49,Business travel,Eco,2165,3,3,2,3,3,3,3,3,1,4,4,4,3,3,2,0.0,neutral or dissatisfied +13582,24185,Male,Loyal Customer,34,Business travel,Eco,170,3,4,4,4,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +13583,25648,Female,Loyal Customer,22,Personal Travel,Eco,526,3,5,3,5,3,3,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +13584,77120,Male,Loyal Customer,31,Personal Travel,Eco,1481,3,2,4,3,1,4,1,1,4,2,4,2,3,1,5,0.0,neutral or dissatisfied +13585,33958,Male,Loyal Customer,14,Personal Travel,Eco,1554,1,5,1,3,3,1,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +13586,3097,Male,Loyal Customer,59,Personal Travel,Eco,594,3,5,3,3,5,3,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +13587,53797,Female,Loyal Customer,21,Business travel,Business,2241,0,3,0,5,5,1,1,5,4,2,4,4,3,5,25,14.0,satisfied +13588,99543,Male,Loyal Customer,34,Business travel,Business,2236,2,2,2,2,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +13589,56296,Female,Loyal Customer,19,Personal Travel,Eco,2227,1,2,1,4,1,2,3,4,4,4,4,3,2,3,7,14.0,neutral or dissatisfied +13590,28408,Female,Loyal Customer,51,Personal Travel,Eco,1709,2,1,3,2,2,2,3,4,4,3,1,3,4,2,37,55.0,neutral or dissatisfied +13591,11673,Male,Loyal Customer,55,Business travel,Business,395,2,2,2,2,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +13592,13454,Female,Loyal Customer,63,Personal Travel,Eco,475,4,3,4,3,5,3,4,2,2,4,4,1,2,2,0,0.0,neutral or dissatisfied +13593,51438,Female,Loyal Customer,59,Personal Travel,Eco Plus,209,2,4,2,3,4,4,4,4,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +13594,18335,Female,Loyal Customer,68,Business travel,Business,225,0,0,0,3,3,2,3,1,1,1,1,2,1,4,0,0.0,satisfied +13595,86381,Male,Loyal Customer,55,Business travel,Business,762,2,4,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +13596,127041,Female,disloyal Customer,23,Business travel,Eco,651,5,5,5,3,3,5,3,3,4,5,5,4,4,3,0,0.0,satisfied +13597,13983,Female,Loyal Customer,56,Business travel,Eco,372,4,1,1,1,2,2,3,3,3,4,3,5,3,2,2,8.0,satisfied +13598,113085,Female,Loyal Customer,50,Business travel,Eco,479,3,2,2,2,4,3,2,3,3,3,3,1,3,1,7,9.0,neutral or dissatisfied +13599,65471,Male,Loyal Customer,45,Business travel,Business,3264,3,3,3,3,5,5,4,5,5,5,5,4,5,5,4,5.0,satisfied +13600,38792,Female,Loyal Customer,42,Business travel,Business,3711,4,4,4,4,1,3,2,5,5,5,5,2,5,4,94,88.0,satisfied +13601,22494,Male,Loyal Customer,9,Personal Travel,Eco,238,3,3,3,3,1,3,1,1,3,1,4,1,3,1,0,11.0,neutral or dissatisfied +13602,7769,Female,Loyal Customer,25,Business travel,Business,1080,2,1,1,1,2,2,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +13603,73227,Female,Loyal Customer,33,Business travel,Eco,946,1,5,5,5,1,2,1,1,1,2,3,2,4,1,0,0.0,neutral or dissatisfied +13604,80708,Male,Loyal Customer,54,Business travel,Business,874,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,33.0,satisfied +13605,41535,Male,Loyal Customer,33,Business travel,Business,3967,1,1,1,1,4,4,4,4,4,4,1,1,3,4,0,0.0,satisfied +13606,127212,Female,Loyal Customer,8,Personal Travel,Eco Plus,651,2,3,2,2,5,2,5,5,4,2,4,3,3,5,0,0.0,neutral or dissatisfied +13607,51869,Female,Loyal Customer,52,Business travel,Business,3184,4,4,5,4,5,2,4,3,3,4,3,4,3,3,51,42.0,satisfied +13608,7724,Male,disloyal Customer,25,Business travel,Eco,859,2,2,2,4,1,2,1,1,3,1,4,1,3,1,11,15.0,neutral or dissatisfied +13609,101727,Female,Loyal Customer,50,Business travel,Business,1216,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +13610,113583,Female,Loyal Customer,39,Business travel,Business,1505,1,4,4,4,3,4,3,1,1,1,1,3,1,1,0,2.0,neutral or dissatisfied +13611,12808,Male,Loyal Customer,26,Business travel,Business,3875,2,3,1,3,2,2,2,2,3,3,4,3,4,2,10,16.0,neutral or dissatisfied +13612,38987,Male,Loyal Customer,57,Business travel,Business,3887,4,4,4,4,2,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +13613,116039,Male,Loyal Customer,29,Personal Travel,Eco,390,2,5,2,4,5,2,5,5,2,2,1,3,4,5,0,0.0,neutral or dissatisfied +13614,28990,Male,Loyal Customer,13,Business travel,Business,2627,3,5,5,5,3,3,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +13615,14832,Female,disloyal Customer,26,Business travel,Eco,304,1,3,1,2,4,1,4,4,4,3,5,3,2,4,0,14.0,neutral or dissatisfied +13616,85580,Female,disloyal Customer,36,Business travel,Business,259,2,2,2,1,5,2,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +13617,13369,Female,Loyal Customer,68,Personal Travel,Eco,946,3,4,2,4,3,2,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +13618,53365,Male,Loyal Customer,35,Business travel,Eco,1452,4,5,2,5,4,4,4,4,4,5,5,3,1,4,0,0.0,satisfied +13619,64783,Male,Loyal Customer,44,Business travel,Business,551,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +13620,103482,Female,Loyal Customer,52,Business travel,Business,440,2,2,3,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +13621,76802,Male,Loyal Customer,22,Personal Travel,Eco,546,4,3,4,1,1,4,1,1,2,4,1,5,1,1,0,0.0,neutral or dissatisfied +13622,42819,Male,Loyal Customer,60,Personal Travel,Eco,677,3,3,3,4,4,3,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +13623,10743,Male,disloyal Customer,33,Business travel,Business,216,3,3,3,4,5,3,5,5,1,1,4,4,3,5,0,0.0,neutral or dissatisfied +13624,18618,Female,Loyal Customer,35,Personal Travel,Eco,383,2,2,4,3,5,4,5,5,3,2,2,4,3,5,0,11.0,neutral or dissatisfied +13625,123149,Male,disloyal Customer,23,Business travel,Eco,600,5,0,5,1,1,5,1,1,4,5,4,3,4,1,0,0.0,satisfied +13626,60367,Female,disloyal Customer,23,Business travel,Eco,1452,4,4,4,4,5,4,5,5,4,4,5,3,4,5,0,0.0,satisfied +13627,107123,Female,Loyal Customer,26,Business travel,Business,3862,1,1,1,1,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +13628,77674,Female,disloyal Customer,30,Business travel,Eco,874,2,2,2,1,1,2,1,1,1,3,2,4,1,1,35,21.0,neutral or dissatisfied +13629,112195,Male,Loyal Customer,68,Personal Travel,Eco Plus,895,3,5,3,1,3,3,3,3,3,4,4,5,4,3,7,4.0,neutral or dissatisfied +13630,354,Female,Loyal Customer,51,Personal Travel,Eco Plus,821,2,5,2,4,2,5,4,2,2,2,2,5,2,4,23,10.0,neutral or dissatisfied +13631,35152,Male,Loyal Customer,30,Business travel,Eco,1010,5,3,3,3,5,5,5,5,2,2,5,5,3,5,0,1.0,satisfied +13632,122641,Female,disloyal Customer,23,Business travel,Eco,328,0,0,0,3,4,0,4,4,1,5,1,2,4,4,0,0.0,satisfied +13633,88997,Female,Loyal Customer,38,Business travel,Eco Plus,799,1,1,5,1,1,1,1,1,4,3,3,3,3,1,0,0.0,neutral or dissatisfied +13634,12276,Female,disloyal Customer,44,Business travel,Eco,190,4,5,4,2,2,4,2,2,5,2,2,5,5,2,56,58.0,satisfied +13635,47155,Female,Loyal Customer,30,Business travel,Business,1599,4,4,2,4,4,4,4,4,2,1,3,3,4,4,0,0.0,satisfied +13636,125563,Male,Loyal Customer,65,Personal Travel,Eco,226,1,4,0,1,2,0,2,2,3,5,4,3,5,2,5,0.0,neutral or dissatisfied +13637,112645,Female,Loyal Customer,58,Business travel,Business,1756,3,3,3,3,5,4,5,5,5,5,5,3,5,5,1,15.0,satisfied +13638,104193,Female,Loyal Customer,60,Business travel,Eco Plus,349,1,5,5,5,2,3,3,2,2,1,2,3,2,3,2,12.0,neutral or dissatisfied +13639,84514,Female,Loyal Customer,52,Business travel,Business,2486,1,1,2,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13640,87664,Female,disloyal Customer,17,Business travel,Business,591,4,0,4,5,2,4,2,2,3,4,5,5,5,2,0,0.0,satisfied +13641,87048,Female,disloyal Customer,24,Business travel,Business,594,0,0,0,4,5,0,5,5,3,5,4,4,5,5,21,10.0,satisfied +13642,54853,Male,Loyal Customer,48,Business travel,Business,2956,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +13643,75753,Female,disloyal Customer,19,Business travel,Eco,813,5,5,5,1,3,5,3,3,3,3,4,4,2,3,0,0.0,satisfied +13644,64994,Male,Loyal Customer,57,Business travel,Business,224,0,0,0,3,2,5,2,3,3,3,3,1,3,5,0,0.0,satisfied +13645,62172,Female,Loyal Customer,72,Business travel,Business,2454,1,4,4,4,1,2,2,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +13646,41116,Male,Loyal Customer,48,Business travel,Eco,667,3,1,1,1,3,3,3,3,1,5,1,2,1,3,0,0.0,neutral or dissatisfied +13647,3708,Female,Loyal Customer,41,Personal Travel,Eco,427,1,1,1,4,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +13648,123337,Male,Loyal Customer,55,Personal Travel,Eco Plus,328,2,1,2,1,5,2,5,5,4,4,1,2,2,5,0,0.0,neutral or dissatisfied +13649,55864,Male,Loyal Customer,44,Business travel,Business,2970,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +13650,63566,Male,Loyal Customer,46,Business travel,Business,1737,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +13651,28025,Male,Loyal Customer,36,Personal Travel,Eco,763,2,3,2,5,5,2,5,5,1,5,2,3,3,5,0,0.0,neutral or dissatisfied +13652,38986,Female,Loyal Customer,44,Business travel,Business,2048,5,5,5,5,3,1,4,5,5,5,5,4,5,3,0,0.0,satisfied +13653,53510,Female,Loyal Customer,24,Personal Travel,Eco,2288,1,3,1,4,3,1,3,3,2,1,4,4,3,3,3,0.0,neutral or dissatisfied +13654,49733,Female,Loyal Customer,35,Business travel,Eco,326,4,1,1,1,4,4,4,5,5,3,5,4,3,4,150,154.0,satisfied +13655,98111,Female,disloyal Customer,29,Business travel,Business,426,2,2,2,3,4,2,4,4,5,5,5,3,5,4,22,17.0,neutral or dissatisfied +13656,108204,Female,Loyal Customer,41,Personal Travel,Business,777,3,4,3,3,3,1,1,5,4,5,5,1,4,1,323,329.0,neutral or dissatisfied +13657,48666,Male,Loyal Customer,36,Business travel,Business,3199,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,34.0,satisfied +13658,110847,Male,Loyal Customer,60,Business travel,Business,2206,2,2,2,2,2,5,5,4,4,4,4,3,4,5,36,35.0,satisfied +13659,24087,Female,Loyal Customer,20,Business travel,Business,1985,4,2,2,2,4,4,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +13660,7388,Female,Loyal Customer,43,Business travel,Business,522,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,10.0,satisfied +13661,98438,Male,Loyal Customer,50,Business travel,Business,3726,3,3,3,3,5,5,5,2,2,3,2,5,2,4,16,0.0,satisfied +13662,3348,Female,Loyal Customer,50,Business travel,Business,3844,2,2,2,2,4,4,4,5,5,5,5,5,5,5,76,86.0,satisfied +13663,38007,Male,Loyal Customer,32,Business travel,Business,3005,3,3,3,3,4,5,4,4,2,5,4,1,1,4,108,91.0,satisfied +13664,79444,Male,Loyal Customer,20,Personal Travel,Eco,187,4,5,4,3,2,4,2,2,5,3,5,3,4,2,1,0.0,neutral or dissatisfied +13665,77358,Male,disloyal Customer,40,Business travel,Eco,626,1,1,1,4,3,1,3,3,1,4,3,1,4,3,69,53.0,neutral or dissatisfied +13666,40733,Male,Loyal Customer,46,Business travel,Eco,558,5,2,2,2,4,5,4,4,2,2,3,4,4,4,0,0.0,satisfied +13667,118958,Female,Loyal Customer,58,Personal Travel,Eco,682,4,2,4,4,3,3,4,1,1,4,1,3,1,4,0,0.0,satisfied +13668,124499,Male,Loyal Customer,28,Business travel,Business,3147,2,5,5,5,2,2,2,2,1,5,4,4,3,2,5,4.0,neutral or dissatisfied +13669,17184,Female,Loyal Customer,47,Personal Travel,Eco,643,2,5,2,3,5,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +13670,92953,Male,Loyal Customer,40,Business travel,Business,3753,3,3,4,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +13671,79778,Female,disloyal Customer,24,Business travel,Business,1035,3,1,3,2,4,3,4,4,3,3,2,4,2,4,0,0.0,neutral or dissatisfied +13672,50079,Female,Loyal Customer,33,Business travel,Business,1724,4,4,4,4,2,2,2,3,3,4,3,1,3,2,0,0.0,satisfied +13673,120237,Male,Loyal Customer,31,Personal Travel,Eco,1325,4,5,5,3,5,5,5,5,3,2,4,3,5,5,0,3.0,satisfied +13674,60514,Female,Loyal Customer,44,Personal Travel,Eco,862,2,5,2,1,5,4,4,5,5,2,5,4,5,5,13,11.0,neutral or dissatisfied +13675,103422,Female,Loyal Customer,41,Personal Travel,Eco,237,2,5,2,1,4,2,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +13676,108854,Male,Loyal Customer,46,Business travel,Business,2139,4,4,1,4,4,3,4,5,5,5,5,3,5,4,0,2.0,satisfied +13677,57000,Female,Loyal Customer,13,Personal Travel,Eco,2454,2,2,2,2,2,5,5,1,3,2,3,5,3,5,27,54.0,neutral or dissatisfied +13678,49695,Male,Loyal Customer,24,Business travel,Business,2249,0,0,0,5,2,2,2,2,4,3,2,2,2,2,0,0.0,satisfied +13679,26375,Male,Loyal Customer,38,Personal Travel,Eco,991,4,4,4,2,2,4,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +13680,78738,Male,disloyal Customer,24,Business travel,Eco,554,5,2,5,5,4,5,4,4,5,4,5,4,5,4,0,6.0,satisfied +13681,2186,Female,Loyal Customer,17,Business travel,Business,685,3,3,3,3,3,3,3,3,2,5,4,1,4,3,65,54.0,neutral or dissatisfied +13682,26079,Male,Loyal Customer,35,Business travel,Business,1717,4,4,4,4,5,1,4,4,4,4,4,1,4,4,15,15.0,satisfied +13683,26960,Female,Loyal Customer,27,Personal Travel,Business,867,4,4,4,3,5,4,5,5,2,4,5,3,5,5,0,10.0,neutral or dissatisfied +13684,128268,Female,disloyal Customer,25,Business travel,Business,621,4,0,4,3,3,4,3,3,4,2,4,5,4,3,0,0.0,satisfied +13685,23289,Male,Loyal Customer,30,Business travel,Business,2371,1,2,1,1,4,4,4,4,3,2,1,1,4,4,0,0.0,satisfied +13686,67223,Female,Loyal Customer,70,Personal Travel,Eco,964,2,1,2,3,1,4,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +13687,76598,Female,disloyal Customer,15,Business travel,Eco,547,1,4,1,2,4,1,3,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +13688,116048,Male,Loyal Customer,41,Personal Travel,Eco,362,3,4,3,4,3,3,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +13689,123943,Female,disloyal Customer,25,Business travel,Business,573,5,5,5,3,2,5,2,2,5,3,4,3,5,2,0,0.0,satisfied +13690,14593,Male,Loyal Customer,31,Personal Travel,Eco,1021,2,2,3,4,3,3,3,3,3,1,4,1,3,3,100,116.0,neutral or dissatisfied +13691,37580,Male,Loyal Customer,44,Business travel,Business,1545,1,3,1,1,5,4,1,4,4,4,4,4,4,2,19,7.0,satisfied +13692,52400,Female,Loyal Customer,53,Personal Travel,Eco,425,3,2,3,3,3,3,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +13693,7534,Male,Loyal Customer,33,Personal Travel,Eco,762,3,1,3,2,2,3,1,2,4,2,3,3,2,2,0,0.0,neutral or dissatisfied +13694,116368,Female,Loyal Customer,41,Personal Travel,Eco,404,2,4,2,3,5,2,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +13695,42209,Male,Loyal Customer,33,Business travel,Business,3141,2,2,2,2,5,5,5,5,3,2,5,1,3,5,0,0.0,satisfied +13696,59534,Female,Loyal Customer,26,Business travel,Business,2215,3,3,3,3,5,4,5,5,3,4,5,3,5,5,0,0.0,satisfied +13697,63132,Male,Loyal Customer,50,Business travel,Business,447,3,1,1,1,5,3,3,3,3,2,3,2,3,3,0,1.0,neutral or dissatisfied +13698,64682,Female,Loyal Customer,40,Business travel,Business,2257,5,5,5,5,2,5,5,4,4,4,5,5,4,3,0,0.0,satisfied +13699,16269,Male,Loyal Customer,44,Business travel,Business,2933,5,5,3,5,1,1,5,5,5,5,5,2,5,2,0,0.0,satisfied +13700,69159,Female,Loyal Customer,56,Business travel,Business,1882,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +13701,120158,Female,disloyal Customer,18,Business travel,Eco,2378,3,3,3,3,3,5,2,4,1,3,3,2,4,2,91,76.0,neutral or dissatisfied +13702,114245,Female,disloyal Customer,45,Business travel,Business,967,1,1,1,4,5,1,2,5,4,3,4,3,4,5,13,0.0,neutral or dissatisfied +13703,95247,Female,Loyal Customer,21,Personal Travel,Eco,192,2,5,2,5,2,2,2,2,3,4,5,3,5,2,3,4.0,neutral or dissatisfied +13704,45228,Male,Loyal Customer,67,Business travel,Business,1832,1,4,4,4,4,3,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +13705,72920,Male,disloyal Customer,18,Business travel,Eco,1096,2,2,2,4,3,2,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +13706,1827,Female,Loyal Customer,23,Personal Travel,Eco,408,2,4,2,1,2,2,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +13707,100907,Male,Loyal Customer,16,Personal Travel,Eco,377,2,3,2,3,3,2,3,3,4,4,3,4,2,3,0,0.0,neutral or dissatisfied +13708,18836,Male,Loyal Customer,35,Business travel,Eco,551,4,1,5,5,4,4,4,2,2,4,1,4,4,4,175,175.0,satisfied +13709,22801,Male,disloyal Customer,22,Business travel,Eco,147,3,2,3,3,4,3,5,4,2,1,3,3,4,4,0,0.0,neutral or dissatisfied +13710,37884,Female,disloyal Customer,29,Business travel,Eco,1068,4,4,4,2,1,4,1,1,1,3,4,5,3,1,14,0.0,neutral or dissatisfied +13711,17393,Female,Loyal Customer,45,Business travel,Eco,351,4,4,2,4,4,4,4,2,2,1,5,4,5,4,147,163.0,satisfied +13712,39974,Male,Loyal Customer,36,Business travel,Eco,1404,4,2,2,2,4,4,4,4,3,5,4,3,1,4,0,0.0,satisfied +13713,32315,Male,Loyal Customer,45,Business travel,Business,3511,1,1,1,1,1,2,1,4,4,4,3,1,4,1,0,0.0,satisfied +13714,69685,Male,Loyal Customer,43,Business travel,Business,1801,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +13715,58042,Male,disloyal Customer,44,Business travel,Business,589,5,5,5,3,2,5,2,2,3,5,5,3,5,2,9,15.0,satisfied +13716,36012,Male,Loyal Customer,36,Business travel,Eco,413,4,2,2,2,4,4,4,4,5,2,3,5,4,4,56,52.0,satisfied +13717,57427,Female,disloyal Customer,23,Business travel,Business,533,4,5,4,3,3,4,3,3,5,3,5,3,5,3,0,0.0,satisfied +13718,9611,Female,Loyal Customer,58,Personal Travel,Eco,288,3,4,5,1,5,4,5,5,5,5,5,4,5,3,36,20.0,neutral or dissatisfied +13719,86325,Female,Loyal Customer,44,Business travel,Business,1991,1,1,4,1,5,4,4,4,4,4,4,5,4,4,25,57.0,satisfied +13720,113445,Female,Loyal Customer,52,Business travel,Business,3930,0,0,0,2,2,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +13721,15159,Female,Loyal Customer,63,Personal Travel,Eco,912,2,2,2,3,2,3,3,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +13722,93228,Female,Loyal Customer,28,Personal Travel,Eco,1460,0,4,1,1,1,1,1,1,3,2,3,5,5,1,14,12.0,satisfied +13723,38793,Male,disloyal Customer,36,Business travel,Eco,387,2,2,1,3,5,1,5,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +13724,47346,Female,Loyal Customer,50,Business travel,Business,1741,5,5,5,5,4,1,4,3,3,4,3,4,3,3,0,0.0,satisfied +13725,44008,Male,Loyal Customer,53,Business travel,Eco,397,4,2,1,1,4,4,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +13726,83484,Male,disloyal Customer,23,Business travel,Eco,946,3,3,3,3,2,3,2,2,4,3,3,4,4,2,0,20.0,neutral or dissatisfied +13727,2669,Male,Loyal Customer,44,Personal Travel,Eco,597,5,1,5,3,2,5,2,2,4,1,1,1,3,2,0,0.0,satisfied +13728,96516,Female,Loyal Customer,12,Personal Travel,Eco,436,3,5,3,4,3,3,3,3,1,3,2,5,2,3,0,0.0,neutral or dissatisfied +13729,20531,Male,Loyal Customer,42,Business travel,Business,3868,3,3,3,3,4,3,1,4,4,4,4,1,4,3,0,0.0,satisfied +13730,53732,Female,Loyal Customer,61,Personal Travel,Eco,1208,4,3,4,1,4,5,2,3,3,4,3,5,3,5,0,0.0,satisfied +13731,14294,Male,Loyal Customer,44,Business travel,Eco,429,4,1,1,1,3,4,3,3,5,3,2,2,5,3,0,0.0,satisfied +13732,46538,Male,Loyal Customer,33,Business travel,Business,2197,0,4,0,1,5,5,5,1,4,3,2,5,1,5,281,287.0,satisfied +13733,129143,Male,Loyal Customer,51,Business travel,Business,2357,2,4,2,2,3,5,4,5,5,5,5,5,5,5,0,9.0,satisfied +13734,8575,Female,disloyal Customer,55,Business travel,Eco,109,3,2,3,3,4,3,4,4,3,4,4,1,4,4,0,0.0,neutral or dissatisfied +13735,82189,Female,Loyal Customer,47,Business travel,Business,1927,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +13736,98530,Male,Loyal Customer,26,Personal Travel,Eco,402,2,4,2,1,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +13737,74615,Female,disloyal Customer,36,Business travel,Eco,835,3,3,3,3,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +13738,20217,Male,Loyal Customer,50,Business travel,Eco,224,4,4,4,4,4,4,4,4,5,4,4,5,3,4,0,0.0,satisfied +13739,129786,Male,Loyal Customer,10,Personal Travel,Eco,337,2,4,2,4,4,2,2,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +13740,13294,Female,Loyal Customer,29,Business travel,Eco Plus,771,2,5,3,3,2,2,2,1,3,2,2,2,4,2,189,184.0,neutral or dissatisfied +13741,6503,Female,Loyal Customer,57,Business travel,Business,599,4,4,4,4,5,5,4,5,5,5,5,3,5,5,0,1.0,satisfied +13742,13609,Male,Loyal Customer,35,Business travel,Eco Plus,106,5,4,4,4,5,5,5,5,2,1,5,4,4,5,130,121.0,satisfied +13743,60150,Female,Loyal Customer,43,Personal Travel,Eco,1120,4,5,4,3,2,5,4,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +13744,46141,Male,Loyal Customer,55,Business travel,Business,604,1,1,1,1,1,1,3,5,5,5,5,3,5,3,18,5.0,satisfied +13745,106925,Male,Loyal Customer,42,Personal Travel,Eco,1259,1,5,1,4,1,1,3,1,3,2,4,3,5,1,0,2.0,neutral or dissatisfied +13746,117974,Female,Loyal Customer,32,Personal Travel,Eco,255,1,1,1,3,3,1,5,3,3,1,3,1,4,3,7,0.0,neutral or dissatisfied +13747,128233,Male,Loyal Customer,18,Personal Travel,Eco,602,3,4,4,4,1,4,1,1,4,2,1,1,2,1,0,0.0,neutral or dissatisfied +13748,127463,Female,Loyal Customer,53,Business travel,Business,2075,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,7.0,satisfied +13749,527,Male,disloyal Customer,38,Business travel,Business,134,4,4,4,1,2,4,2,2,3,2,4,3,5,2,6,1.0,neutral or dissatisfied +13750,15172,Female,disloyal Customer,36,Business travel,Eco,430,3,0,3,2,5,3,2,5,2,2,2,1,4,5,0,0.0,neutral or dissatisfied +13751,10102,Female,Loyal Customer,39,Business travel,Business,1656,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +13752,44539,Female,Loyal Customer,54,Personal Travel,Eco,157,2,1,2,4,3,4,4,2,2,2,5,4,2,3,0,0.0,neutral or dissatisfied +13753,11200,Male,Loyal Customer,47,Personal Travel,Eco,201,3,2,3,3,2,3,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +13754,47022,Male,Loyal Customer,46,Business travel,Business,1993,4,4,3,4,2,1,4,5,5,5,5,5,5,5,0,0.0,satisfied +13755,117998,Male,Loyal Customer,25,Personal Travel,Eco Plus,255,3,2,3,3,4,3,4,4,4,3,3,4,4,4,8,6.0,neutral or dissatisfied +13756,30645,Male,Loyal Customer,45,Business travel,Eco,533,1,2,2,2,1,1,1,1,4,2,2,1,3,1,0,1.0,neutral or dissatisfied +13757,62795,Male,Loyal Customer,10,Personal Travel,Eco,2556,3,2,4,3,4,3,3,1,2,4,3,3,4,3,4,0.0,neutral or dissatisfied +13758,3997,Female,disloyal Customer,58,Business travel,Business,419,3,3,3,1,2,3,5,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +13759,78327,Male,Loyal Customer,57,Business travel,Business,1547,2,2,2,2,5,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +13760,79040,Female,Loyal Customer,44,Business travel,Business,3184,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +13761,20812,Male,Loyal Customer,52,Business travel,Eco,508,5,2,2,2,5,5,5,5,3,1,5,1,3,5,7,0.0,satisfied +13762,41959,Female,Loyal Customer,26,Business travel,Business,3378,5,5,3,5,5,5,5,5,1,2,1,1,1,5,0,0.0,satisfied +13763,46221,Female,Loyal Customer,36,Business travel,Eco,752,4,3,3,3,4,4,4,4,4,4,2,4,2,4,55,59.0,satisfied +13764,59064,Male,Loyal Customer,23,Business travel,Business,1744,3,5,5,5,3,3,3,3,2,4,1,3,2,3,5,0.0,neutral or dissatisfied +13765,47555,Male,Loyal Customer,29,Business travel,Eco Plus,532,2,5,5,5,2,2,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +13766,49919,Female,Loyal Customer,33,Business travel,Business,1543,4,4,4,4,3,4,1,4,4,4,4,2,4,4,0,0.0,satisfied +13767,113834,Female,Loyal Customer,59,Personal Travel,Eco Plus,197,3,5,3,2,3,4,3,5,5,3,1,2,5,1,7,0.0,neutral or dissatisfied +13768,110114,Male,Loyal Customer,53,Business travel,Business,3021,5,5,5,5,4,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +13769,129498,Male,Loyal Customer,40,Business travel,Business,1846,2,3,3,3,2,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +13770,129614,Male,Loyal Customer,45,Business travel,Business,447,4,4,4,4,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +13771,56863,Female,disloyal Customer,49,Business travel,Business,2565,3,3,3,2,3,4,4,3,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +13772,9321,Male,Loyal Customer,41,Business travel,Business,419,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +13773,54832,Female,Loyal Customer,48,Business travel,Eco,862,3,3,3,3,2,2,2,3,3,3,3,3,3,3,10,15.0,neutral or dissatisfied +13774,41129,Male,disloyal Customer,20,Business travel,Eco,140,3,2,3,4,3,3,4,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +13775,53936,Female,Loyal Customer,24,Business travel,Business,2007,5,5,5,5,5,5,5,5,3,4,3,4,1,5,0,0.0,satisfied +13776,87742,Male,Loyal Customer,58,Business travel,Business,214,3,5,5,5,5,4,3,2,2,2,3,2,2,2,2,6.0,neutral or dissatisfied +13777,23858,Female,disloyal Customer,24,Business travel,Eco,552,2,1,2,3,1,2,1,1,2,1,2,2,3,1,0,0.0,neutral or dissatisfied +13778,15830,Male,Loyal Customer,45,Business travel,Eco,195,2,3,3,3,2,2,2,2,2,2,3,3,5,2,0,8.0,satisfied +13779,39801,Female,Loyal Customer,36,Business travel,Eco,272,4,3,3,3,4,4,4,4,3,4,4,3,2,4,49,58.0,satisfied +13780,119112,Female,Loyal Customer,18,Personal Travel,Eco,1020,3,3,4,3,3,4,2,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +13781,83266,Female,disloyal Customer,43,Business travel,Business,2079,4,4,4,3,1,4,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +13782,71041,Female,Loyal Customer,46,Business travel,Business,1826,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13783,47339,Female,Loyal Customer,27,Business travel,Eco,588,5,3,3,3,5,5,5,5,4,4,4,1,3,5,0,0.0,satisfied +13784,121074,Male,Loyal Customer,50,Business travel,Eco Plus,951,1,2,2,2,1,1,1,1,3,2,4,3,4,1,0,18.0,neutral or dissatisfied +13785,109142,Female,Loyal Customer,63,Personal Travel,Business,483,2,2,3,3,4,2,3,5,5,3,5,3,5,4,0,7.0,neutral or dissatisfied +13786,67305,Female,disloyal Customer,20,Business travel,Eco,1017,3,3,3,3,4,3,4,4,4,1,4,3,3,4,36,22.0,neutral or dissatisfied +13787,86217,Female,Loyal Customer,37,Business travel,Eco,226,5,2,2,2,5,5,5,5,1,2,2,5,3,5,3,2.0,satisfied +13788,35720,Male,Loyal Customer,54,Personal Travel,Eco,2465,1,5,1,4,1,1,4,3,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +13789,104989,Female,Loyal Customer,61,Business travel,Business,3751,2,1,1,1,1,4,3,2,2,2,2,4,2,4,29,23.0,neutral or dissatisfied +13790,2050,Male,Loyal Customer,47,Business travel,Eco,812,3,3,3,3,3,3,3,3,1,1,3,2,3,3,63,51.0,neutral or dissatisfied +13791,69795,Male,Loyal Customer,56,Business travel,Business,1738,4,4,4,4,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +13792,73853,Male,Loyal Customer,14,Personal Travel,Eco,1810,5,3,5,1,1,5,1,1,1,2,4,5,2,1,0,0.0,satisfied +13793,25576,Male,Loyal Customer,57,Business travel,Business,874,1,1,1,1,2,4,2,2,2,2,2,4,2,5,0,0.0,satisfied +13794,69301,Male,Loyal Customer,25,Business travel,Business,1096,2,2,2,2,4,5,4,4,3,4,5,3,4,4,0,0.0,satisfied +13795,84390,Female,Loyal Customer,33,Business travel,Business,1971,3,5,4,4,2,3,4,3,3,3,3,3,3,1,27,40.0,neutral or dissatisfied +13796,34634,Female,disloyal Customer,42,Business travel,Eco,427,4,3,4,3,5,4,3,5,4,3,5,5,4,5,0,0.0,satisfied +13797,74394,Female,Loyal Customer,29,Business travel,Business,3823,3,3,3,3,5,4,5,5,3,5,5,4,4,5,12,11.0,satisfied +13798,97616,Male,Loyal Customer,42,Business travel,Business,764,2,2,2,2,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +13799,8590,Female,Loyal Customer,35,Personal Travel,Eco,109,3,2,3,3,1,3,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +13800,24512,Female,disloyal Customer,24,Business travel,Eco Plus,547,2,0,1,2,1,1,1,1,1,4,1,1,4,1,0,0.0,neutral or dissatisfied +13801,67886,Male,Loyal Customer,20,Personal Travel,Eco,1464,1,5,1,4,1,1,1,1,3,5,4,4,5,1,37,68.0,neutral or dissatisfied +13802,98391,Female,Loyal Customer,54,Personal Travel,Eco,1131,2,1,2,3,3,2,3,3,3,2,3,4,3,4,46,15.0,neutral or dissatisfied +13803,90707,Male,Loyal Customer,58,Business travel,Business,1917,3,3,3,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +13804,60495,Male,Loyal Customer,37,Business travel,Eco,862,3,4,4,4,3,3,3,3,4,5,4,1,3,3,5,10.0,neutral or dissatisfied +13805,18223,Male,Loyal Customer,61,Business travel,Eco,235,3,1,1,1,3,3,3,3,2,5,4,4,4,3,26,42.0,neutral or dissatisfied +13806,61952,Male,Loyal Customer,41,Business travel,Business,2052,2,2,2,2,3,4,5,3,3,3,3,3,3,5,4,0.0,satisfied +13807,102391,Female,Loyal Customer,51,Business travel,Eco,236,2,5,5,5,1,1,2,2,2,2,2,1,2,1,6,31.0,neutral or dissatisfied +13808,99386,Male,Loyal Customer,42,Business travel,Business,337,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +13809,51464,Female,Loyal Customer,40,Personal Travel,Eco Plus,363,3,4,5,3,1,5,1,1,4,3,4,3,5,1,2,0.0,neutral or dissatisfied +13810,2385,Female,disloyal Customer,24,Business travel,Business,641,4,0,4,5,2,4,2,2,4,3,5,4,4,2,26,4.0,satisfied +13811,98448,Male,Loyal Customer,25,Personal Travel,Eco,814,4,3,4,3,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +13812,89827,Female,Loyal Customer,24,Personal Travel,Eco Plus,950,2,1,2,4,5,2,4,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +13813,34293,Male,Loyal Customer,23,Business travel,Business,280,3,4,4,4,3,3,3,3,3,4,1,2,2,3,0,0.0,neutral or dissatisfied +13814,93247,Female,Loyal Customer,30,Personal Travel,Eco,689,4,5,4,1,1,4,1,1,1,3,4,5,4,1,0,0.0,satisfied +13815,76167,Male,Loyal Customer,17,Personal Travel,Eco,689,2,4,2,3,2,2,2,2,4,3,3,3,4,2,3,0.0,neutral or dissatisfied +13816,43949,Male,Loyal Customer,49,Business travel,Business,473,2,2,2,2,3,3,2,5,5,5,5,3,5,3,49,45.0,satisfied +13817,10998,Female,disloyal Customer,23,Business travel,Eco,166,4,3,4,1,4,4,4,4,4,1,4,5,1,4,0,0.0,satisfied +13818,119767,Female,Loyal Customer,59,Business travel,Business,3298,2,2,2,2,3,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +13819,116538,Male,Loyal Customer,13,Personal Travel,Eco,337,3,5,4,3,1,4,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +13820,89880,Female,Loyal Customer,58,Business travel,Business,1416,1,1,1,1,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +13821,129609,Female,Loyal Customer,47,Business travel,Business,337,1,1,1,1,3,4,5,4,4,4,4,4,4,3,11,5.0,satisfied +13822,2118,Female,Loyal Customer,59,Business travel,Business,3391,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,1.0,satisfied +13823,95236,Male,Loyal Customer,49,Personal Travel,Eco,323,2,1,2,3,4,2,4,4,2,5,3,1,4,4,1,0.0,neutral or dissatisfied +13824,40067,Male,Loyal Customer,48,Personal Travel,Business,493,3,4,3,3,3,5,5,5,5,3,4,3,5,3,2,0.0,neutral or dissatisfied +13825,85695,Male,Loyal Customer,46,Business travel,Business,1547,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +13826,106663,Female,Loyal Customer,23,Personal Travel,Eco,1590,3,4,3,3,1,3,1,1,5,2,3,5,5,1,3,13.0,neutral or dissatisfied +13827,69330,Female,Loyal Customer,43,Business travel,Business,1089,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,2.0,satisfied +13828,66710,Female,Loyal Customer,59,Business travel,Business,402,1,5,5,5,1,1,1,1,5,4,4,1,2,1,201,186.0,neutral or dissatisfied +13829,83485,Male,Loyal Customer,44,Business travel,Business,3093,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13830,22716,Male,disloyal Customer,25,Business travel,Business,302,3,0,3,1,3,3,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +13831,92466,Female,disloyal Customer,30,Business travel,Business,1919,1,1,1,1,1,1,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +13832,4348,Female,Loyal Customer,31,Business travel,Business,2537,1,1,5,1,4,5,4,4,3,2,4,3,5,4,0,0.0,satisfied +13833,126709,Female,Loyal Customer,33,Business travel,Business,2521,3,2,2,2,2,3,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +13834,85823,Male,Loyal Customer,21,Personal Travel,Eco,666,1,3,1,4,1,1,3,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +13835,36585,Female,disloyal Customer,13,Business travel,Eco,1237,2,2,2,4,1,2,1,1,3,1,3,4,4,1,2,11.0,neutral or dissatisfied +13836,41889,Male,Loyal Customer,67,Personal Travel,Business,129,4,0,4,5,5,5,5,4,4,4,5,3,4,5,0,10.0,neutral or dissatisfied +13837,50031,Male,Loyal Customer,51,Business travel,Business,373,2,2,4,4,4,2,2,2,2,2,2,1,2,1,31,37.0,neutral or dissatisfied +13838,63023,Female,disloyal Customer,40,Business travel,Business,909,1,1,1,3,2,1,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +13839,45097,Female,Loyal Customer,53,Personal Travel,Business,157,2,4,2,4,3,4,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +13840,98609,Female,Loyal Customer,48,Business travel,Business,2877,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +13841,103547,Female,Loyal Customer,69,Personal Travel,Eco,967,3,4,3,2,5,4,5,5,5,3,5,5,5,4,1,0.0,neutral or dissatisfied +13842,14164,Male,Loyal Customer,18,Personal Travel,Business,620,4,4,4,4,3,4,3,3,4,2,5,5,5,3,0,0.0,satisfied +13843,63069,Male,Loyal Customer,49,Personal Travel,Eco,967,5,4,4,3,5,4,5,5,4,4,5,4,5,5,0,0.0,satisfied +13844,78390,Male,Loyal Customer,47,Personal Travel,Eco,726,0,5,0,5,1,0,1,1,4,5,4,4,2,1,0,0.0,satisfied +13845,75857,Female,Loyal Customer,30,Personal Travel,Eco,1440,3,4,3,2,3,3,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +13846,26496,Female,Loyal Customer,43,Business travel,Eco,829,5,1,1,1,3,1,4,4,4,5,4,2,4,5,0,0.0,satisfied +13847,71616,Female,disloyal Customer,26,Business travel,Business,1012,2,2,2,5,5,2,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +13848,57880,Male,Loyal Customer,60,Business travel,Business,305,0,0,0,1,4,5,4,3,3,3,3,5,3,4,6,0.0,satisfied +13849,25390,Male,Loyal Customer,24,Personal Travel,Eco Plus,591,3,1,3,3,1,3,1,1,4,2,4,3,4,1,107,109.0,neutral or dissatisfied +13850,64893,Female,Loyal Customer,38,Business travel,Eco,551,2,2,2,2,2,2,2,2,3,4,2,2,3,2,0,0.0,neutral or dissatisfied +13851,65381,Male,Loyal Customer,33,Personal Travel,Eco,631,2,1,2,4,1,2,1,1,3,1,3,2,4,1,3,3.0,neutral or dissatisfied +13852,80780,Male,disloyal Customer,23,Business travel,Eco,484,4,0,4,3,4,4,4,4,5,4,4,3,4,4,4,12.0,satisfied +13853,60299,Female,disloyal Customer,54,Business travel,Eco Plus,383,2,3,3,1,3,2,5,3,3,4,2,4,1,3,0,7.0,neutral or dissatisfied +13854,61880,Female,disloyal Customer,8,Business travel,Eco,1483,1,1,1,4,2,1,2,2,3,4,5,5,4,2,0,4.0,neutral or dissatisfied +13855,74109,Male,Loyal Customer,56,Business travel,Business,3133,1,1,1,1,5,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +13856,74869,Female,disloyal Customer,25,Business travel,Business,2239,3,0,3,3,5,3,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +13857,66319,Male,Loyal Customer,61,Personal Travel,Eco,852,0,5,0,5,2,0,2,2,5,5,4,4,5,2,11,2.0,satisfied +13858,119100,Female,Loyal Customer,25,Business travel,Business,1107,2,1,1,1,2,2,2,2,3,5,2,3,2,2,0,0.0,neutral or dissatisfied +13859,120238,Male,Loyal Customer,47,Personal Travel,Eco,1303,1,5,1,2,1,1,1,1,4,2,5,4,5,1,28,36.0,neutral or dissatisfied +13860,92845,Male,disloyal Customer,26,Business travel,Business,1587,3,3,3,5,2,3,2,2,4,5,4,5,4,2,0,6.0,neutral or dissatisfied +13861,81550,Female,Loyal Customer,45,Personal Travel,Business,936,5,2,5,3,3,2,3,4,4,5,2,4,4,2,16,24.0,satisfied +13862,32358,Male,Loyal Customer,55,Business travel,Eco,216,2,4,4,4,2,2,2,2,2,3,4,1,4,2,17,22.0,neutral or dissatisfied +13863,118829,Female,disloyal Customer,22,Business travel,Eco,647,0,0,0,1,2,0,2,2,5,2,5,4,4,2,9,2.0,satisfied +13864,66897,Female,Loyal Customer,46,Business travel,Business,3286,4,4,4,4,5,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +13865,9610,Male,Loyal Customer,50,Personal Travel,Eco,229,2,5,2,2,5,2,5,5,5,4,5,4,5,5,19,37.0,neutral or dissatisfied +13866,99076,Male,Loyal Customer,40,Business travel,Business,2799,4,5,4,4,5,4,4,5,5,5,4,5,5,4,10,6.0,satisfied +13867,128156,Male,Loyal Customer,59,Business travel,Business,1849,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,7.0,satisfied +13868,82208,Female,disloyal Customer,58,Business travel,Business,405,4,4,4,1,2,4,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +13869,49112,Male,Loyal Customer,44,Business travel,Eco,308,5,1,1,1,4,5,4,4,1,3,1,5,1,4,7,9.0,satisfied +13870,33990,Female,Loyal Customer,22,Business travel,Eco,1576,5,1,1,1,5,4,4,5,3,2,2,3,3,5,11,4.0,satisfied +13871,95750,Male,disloyal Customer,23,Business travel,Eco,181,2,2,2,1,5,2,5,5,4,4,2,3,2,5,3,2.0,neutral or dissatisfied +13872,126752,Male,Loyal Customer,37,Personal Travel,Eco,2370,2,4,2,4,3,2,1,3,2,1,3,1,4,3,1,0.0,neutral or dissatisfied +13873,116494,Male,Loyal Customer,62,Personal Travel,Eco,337,5,4,5,4,5,5,2,5,3,4,5,5,5,5,9,0.0,satisfied +13874,4345,Male,disloyal Customer,39,Business travel,Business,473,4,3,3,2,1,3,4,1,4,5,4,3,4,1,0,0.0,satisfied +13875,31439,Female,disloyal Customer,23,Business travel,Eco,1541,5,5,5,2,1,5,1,1,3,1,4,2,5,1,36,26.0,satisfied +13876,72807,Male,Loyal Customer,65,Personal Travel,Eco,1045,2,5,2,5,4,2,5,4,1,1,3,3,4,4,1,0.0,neutral or dissatisfied +13877,8785,Male,Loyal Customer,58,Business travel,Business,552,3,3,3,3,2,5,4,5,5,5,5,4,5,5,87,96.0,satisfied +13878,27869,Female,Loyal Customer,29,Business travel,Eco Plus,680,5,2,5,2,5,5,5,5,4,4,4,2,2,5,0,3.0,satisfied +13879,31862,Male,Loyal Customer,29,Business travel,Business,2599,2,2,2,2,4,4,4,4,2,4,4,3,5,4,0,0.0,satisfied +13880,14517,Female,Loyal Customer,39,Business travel,Eco,288,3,1,1,1,3,3,3,3,5,2,4,4,1,3,0,0.0,satisfied +13881,117751,Female,Loyal Customer,13,Personal Travel,Eco Plus,833,1,5,1,4,3,1,3,3,4,4,5,3,4,3,13,2.0,neutral or dissatisfied +13882,82638,Male,Loyal Customer,44,Business travel,Eco Plus,128,4,4,3,4,4,4,4,4,4,3,3,4,4,4,3,0.0,neutral or dissatisfied +13883,65030,Male,Loyal Customer,21,Personal Travel,Eco,551,5,5,5,1,3,5,3,3,5,2,3,2,2,3,0,0.0,satisfied +13884,25627,Male,Loyal Customer,57,Business travel,Eco,666,3,1,1,1,3,3,3,3,4,5,3,2,4,3,23,15.0,neutral or dissatisfied +13885,29174,Male,Loyal Customer,36,Business travel,Eco Plus,697,5,4,4,4,5,5,5,5,2,4,1,2,4,5,0,0.0,satisfied +13886,34335,Male,disloyal Customer,48,Business travel,Eco,846,3,3,3,3,3,3,3,3,1,4,1,2,5,3,0,0.0,neutral or dissatisfied +13887,40684,Female,disloyal Customer,24,Business travel,Eco,588,2,5,2,3,1,2,1,1,1,5,4,2,5,1,0,0.0,neutral or dissatisfied +13888,94084,Male,disloyal Customer,38,Business travel,Business,189,2,2,2,4,4,2,4,4,3,3,3,2,3,4,4,4.0,neutral or dissatisfied +13889,94287,Male,disloyal Customer,21,Business travel,Business,239,0,4,0,4,2,0,2,2,3,4,5,3,4,2,2,1.0,satisfied +13890,36396,Male,Loyal Customer,35,Business travel,Eco Plus,2381,4,2,3,2,4,4,4,4,1,4,5,5,4,4,11,0.0,satisfied +13891,115608,Female,disloyal Customer,26,Business travel,Business,337,4,3,4,3,3,4,3,3,4,3,5,5,4,3,9,4.0,satisfied +13892,4857,Female,disloyal Customer,24,Business travel,Eco,408,5,4,5,1,4,5,4,4,4,4,2,3,2,4,0,0.0,satisfied +13893,45774,Male,disloyal Customer,39,Business travel,Eco,391,2,0,2,1,5,2,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +13894,62751,Female,Loyal Customer,43,Business travel,Business,2486,2,2,2,2,5,5,5,5,3,5,5,5,4,5,0,5.0,satisfied +13895,4009,Female,Loyal Customer,48,Business travel,Business,479,4,2,2,2,4,4,4,1,1,3,2,4,1,4,245,230.0,neutral or dissatisfied +13896,17351,Female,Loyal Customer,29,Business travel,Business,563,4,4,4,4,4,4,4,4,5,1,1,1,3,4,0,0.0,satisfied +13897,55926,Male,Loyal Customer,45,Personal Travel,Eco,733,3,4,3,3,3,3,3,5,3,3,1,3,3,3,246,239.0,neutral or dissatisfied +13898,40002,Male,Loyal Customer,37,Business travel,Eco,618,4,1,1,1,4,4,4,4,4,1,2,5,4,4,0,0.0,satisfied +13899,122374,Male,disloyal Customer,37,Business travel,Eco,529,2,3,2,4,2,2,2,2,3,1,3,1,4,2,0,0.0,neutral or dissatisfied +13900,71352,Male,Loyal Customer,53,Business travel,Business,3228,5,5,4,5,3,4,4,5,5,5,5,5,5,5,2,0.0,satisfied +13901,96550,Male,Loyal Customer,60,Business travel,Business,3887,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +13902,31347,Male,Loyal Customer,14,Business travel,Business,3076,3,2,2,2,3,3,3,3,1,1,4,4,3,3,18,13.0,neutral or dissatisfied +13903,17879,Female,Loyal Customer,35,Personal Travel,Eco,371,2,4,2,3,5,2,5,5,2,2,2,5,3,5,0,0.0,neutral or dissatisfied +13904,12766,Male,Loyal Customer,21,Business travel,Eco Plus,689,0,4,0,3,0,4,3,5,5,2,3,3,4,3,190,186.0,satisfied +13905,3790,Male,Loyal Customer,37,Personal Travel,Eco,599,1,2,1,3,4,1,1,4,2,2,1,4,3,4,0,2.0,neutral or dissatisfied +13906,95340,Male,Loyal Customer,63,Personal Travel,Eco,189,4,4,4,1,4,4,4,4,5,5,5,2,3,4,20,14.0,neutral or dissatisfied +13907,56434,Male,disloyal Customer,38,Business travel,Eco,719,1,1,1,3,3,1,3,3,2,2,3,3,2,3,0,0.0,neutral or dissatisfied +13908,94006,Female,Loyal Customer,58,Business travel,Business,3407,0,4,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +13909,16619,Male,Loyal Customer,34,Personal Travel,Eco,1008,4,1,4,2,4,4,4,4,3,3,2,4,2,4,0,0.0,neutral or dissatisfied +13910,12874,Male,Loyal Customer,36,Business travel,Eco,359,5,4,4,4,5,5,5,5,3,2,2,5,1,5,0,0.0,satisfied +13911,35923,Male,Loyal Customer,42,Business travel,Business,2381,4,4,4,4,4,4,2,2,2,2,2,2,2,1,0,0.0,satisfied +13912,113688,Male,Loyal Customer,58,Personal Travel,Eco,391,2,5,2,3,3,2,3,3,5,4,1,2,3,3,0,0.0,neutral or dissatisfied +13913,125106,Female,Loyal Customer,56,Business travel,Business,2800,1,3,3,3,1,2,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +13914,52655,Male,Loyal Customer,17,Personal Travel,Eco,110,2,1,2,2,1,2,1,1,4,5,2,3,2,1,0,0.0,neutral or dissatisfied +13915,112226,Female,Loyal Customer,56,Personal Travel,Eco,1199,3,4,3,1,3,3,3,1,1,3,1,5,1,4,25,17.0,neutral or dissatisfied +13916,23449,Female,Loyal Customer,28,Business travel,Eco,576,5,4,4,4,5,5,5,5,2,3,4,1,4,5,114,123.0,satisfied +13917,120293,Female,Loyal Customer,48,Business travel,Business,1576,2,2,2,2,2,4,5,2,2,2,2,5,2,4,0,18.0,satisfied +13918,26809,Male,Loyal Customer,39,Personal Travel,Eco,2139,3,5,3,2,1,3,1,1,5,5,4,3,4,1,0,13.0,neutral or dissatisfied +13919,102726,Female,Loyal Customer,49,Personal Travel,Eco,365,1,4,4,5,3,4,4,3,3,4,3,3,3,5,14,18.0,neutral or dissatisfied +13920,72115,Male,Loyal Customer,32,Business travel,Business,731,3,3,3,3,5,5,5,5,5,4,5,3,5,5,1,0.0,satisfied +13921,28127,Female,disloyal Customer,21,Business travel,Eco,550,1,1,1,2,5,1,5,5,3,3,3,3,2,5,0,0.0,neutral or dissatisfied +13922,69261,Female,Loyal Customer,67,Business travel,Business,333,2,1,3,3,3,4,3,2,2,2,2,1,2,4,36,45.0,neutral or dissatisfied +13923,98184,Female,disloyal Customer,37,Business travel,Eco,327,1,4,1,3,1,1,1,1,2,2,4,4,4,1,0,0.0,neutral or dissatisfied +13924,88898,Female,disloyal Customer,21,Business travel,Eco,459,3,1,3,2,2,3,2,2,1,2,2,4,2,2,15,22.0,neutral or dissatisfied +13925,8187,Female,Loyal Customer,48,Business travel,Business,2225,3,1,1,1,3,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +13926,2647,Female,Loyal Customer,24,Business travel,Business,622,4,4,4,4,5,5,5,5,3,5,5,3,5,5,18,18.0,satisfied +13927,109651,Male,Loyal Customer,61,Business travel,Eco,802,3,3,3,3,3,3,3,3,1,2,4,2,3,3,38,35.0,neutral or dissatisfied +13928,114781,Female,Loyal Customer,59,Business travel,Business,2133,4,4,4,4,4,4,4,2,2,2,2,3,2,5,113,98.0,satisfied +13929,123133,Male,Loyal Customer,56,Business travel,Business,650,5,5,5,5,4,4,5,4,4,4,4,4,4,5,8,13.0,satisfied +13930,86527,Female,Loyal Customer,42,Personal Travel,Eco,749,4,5,4,2,4,5,2,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +13931,103569,Male,Loyal Customer,39,Business travel,Business,1614,4,4,4,4,5,4,4,4,4,4,4,5,4,5,3,0.0,satisfied +13932,72244,Female,Loyal Customer,43,Business travel,Business,919,4,4,4,4,5,4,5,5,5,5,5,3,5,5,22,17.0,satisfied +13933,51527,Female,Loyal Customer,40,Business travel,Business,2265,0,1,1,4,1,2,5,2,2,2,2,2,2,3,0,0.0,satisfied +13934,128993,Female,disloyal Customer,36,Business travel,Eco Plus,236,3,3,3,3,2,3,2,2,1,1,4,3,3,2,0,0.0,neutral or dissatisfied +13935,100001,Male,disloyal Customer,37,Business travel,Business,220,2,2,2,5,5,2,2,5,3,2,5,5,5,5,3,0.0,neutral or dissatisfied +13936,56950,Male,Loyal Customer,44,Business travel,Eco,2454,2,2,2,2,2,2,2,4,2,3,2,2,4,2,9,43.0,neutral or dissatisfied +13937,76833,Female,Loyal Customer,16,Business travel,Business,1851,5,5,5,5,5,5,5,5,5,3,5,1,4,5,0,0.0,satisfied +13938,100267,Male,Loyal Customer,45,Business travel,Business,3613,4,4,4,4,3,5,4,3,3,4,3,3,3,4,13,4.0,satisfied +13939,118751,Female,Loyal Customer,13,Personal Travel,Eco,646,3,4,2,3,4,2,4,4,5,4,2,3,3,4,0,0.0,neutral or dissatisfied +13940,9563,Female,Loyal Customer,36,Business travel,Business,2814,5,5,5,5,4,4,5,5,5,5,5,3,5,5,31,28.0,satisfied +13941,5356,Female,Loyal Customer,43,Business travel,Business,2335,4,4,1,4,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +13942,37637,Male,Loyal Customer,17,Personal Travel,Eco,944,3,3,3,4,5,3,1,5,1,3,4,2,3,5,33,20.0,neutral or dissatisfied +13943,110942,Male,Loyal Customer,62,Personal Travel,Eco,515,4,5,4,3,5,4,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +13944,11636,Male,disloyal Customer,25,Business travel,Business,835,2,4,2,1,1,2,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +13945,24796,Female,Loyal Customer,35,Personal Travel,Eco,447,1,4,1,4,4,1,3,4,5,2,4,4,4,4,0,11.0,neutral or dissatisfied +13946,75035,Female,Loyal Customer,10,Personal Travel,Eco,236,2,4,2,2,1,2,1,1,3,1,5,1,2,1,8,4.0,neutral or dissatisfied +13947,89675,Female,Loyal Customer,55,Business travel,Eco,1010,3,5,5,5,1,3,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +13948,73066,Male,Loyal Customer,60,Personal Travel,Eco Plus,1089,1,3,1,2,1,1,1,1,2,2,4,5,2,1,0,0.0,neutral or dissatisfied +13949,61093,Male,Loyal Customer,40,Personal Travel,Eco,1546,3,4,4,4,5,4,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +13950,34784,Male,Loyal Customer,9,Personal Travel,Eco,264,1,3,1,3,3,1,3,3,2,1,3,3,2,3,0,0.0,neutral or dissatisfied +13951,76625,Male,Loyal Customer,55,Business travel,Business,2222,4,3,4,4,1,4,3,4,4,4,3,4,4,5,0,0.0,satisfied +13952,102158,Female,Loyal Customer,58,Business travel,Business,414,1,1,1,1,4,4,5,4,4,4,4,4,4,5,17,4.0,satisfied +13953,17885,Female,Loyal Customer,55,Personal Travel,Eco,399,3,5,3,1,5,5,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +13954,13745,Male,disloyal Customer,25,Business travel,Eco,441,3,0,3,4,5,3,5,5,3,3,2,4,2,5,0,2.0,neutral or dissatisfied +13955,69035,Female,Loyal Customer,61,Business travel,Business,1389,4,1,1,1,5,2,2,4,4,4,4,1,4,4,0,4.0,neutral or dissatisfied +13956,47468,Female,Loyal Customer,33,Personal Travel,Eco,588,2,5,2,3,5,2,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +13957,49673,Male,Loyal Customer,44,Business travel,Business,373,5,5,5,5,2,4,5,4,4,4,4,5,4,2,4,22.0,satisfied +13958,72602,Female,Loyal Customer,35,Personal Travel,Eco,985,4,4,4,4,4,4,4,4,1,1,4,3,4,4,32,25.0,satisfied +13959,54620,Male,Loyal Customer,55,Business travel,Business,3834,2,2,2,2,4,3,2,5,5,5,5,1,5,5,0,0.0,satisfied +13960,1269,Male,Loyal Customer,32,Personal Travel,Eco,89,2,4,2,3,1,2,5,1,3,5,4,4,4,1,1,11.0,neutral or dissatisfied +13961,6364,Male,Loyal Customer,18,Business travel,Business,2336,2,2,4,2,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +13962,4898,Female,Loyal Customer,39,Business travel,Business,3888,4,4,1,4,3,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +13963,71717,Female,disloyal Customer,16,Business travel,Eco,1007,3,3,3,2,4,3,4,4,5,5,4,3,4,4,25,5.0,satisfied +13964,58357,Female,Loyal Customer,55,Business travel,Eco,646,3,5,5,5,5,3,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +13965,90030,Male,Loyal Customer,43,Business travel,Business,957,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +13966,11308,Female,Loyal Customer,69,Personal Travel,Eco,295,3,4,3,2,2,5,5,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +13967,26035,Female,Loyal Customer,33,Personal Travel,Eco,321,4,2,4,4,5,4,5,5,2,3,3,1,4,5,30,25.0,neutral or dissatisfied +13968,37237,Female,disloyal Customer,54,Business travel,Business,669,4,4,4,2,3,4,3,3,5,5,4,3,5,3,42,41.0,satisfied +13969,117307,Male,disloyal Customer,16,Business travel,Eco Plus,304,3,2,3,3,1,3,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +13970,68692,Female,Loyal Customer,26,Personal Travel,Eco,175,2,3,0,3,4,0,4,4,3,3,5,3,2,4,0,0.0,neutral or dissatisfied +13971,16092,Male,Loyal Customer,42,Business travel,Business,3466,3,1,1,1,4,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +13972,39942,Male,Loyal Customer,43,Business travel,Business,3081,2,2,2,2,5,4,3,4,4,4,4,1,4,1,0,0.0,satisfied +13973,43527,Female,disloyal Customer,21,Business travel,Eco,807,2,2,2,2,2,2,2,2,1,1,3,1,2,2,0,0.0,neutral or dissatisfied +13974,38902,Male,disloyal Customer,27,Business travel,Eco,298,1,0,1,2,3,1,3,3,2,1,3,5,2,3,5,0.0,neutral or dissatisfied +13975,103512,Male,Loyal Customer,59,Business travel,Business,3854,2,2,2,2,5,2,5,5,5,5,5,1,5,1,2,0.0,satisfied +13976,93367,Female,Loyal Customer,58,Personal Travel,Eco,1024,4,5,4,5,3,5,5,3,3,4,3,5,3,3,0,8.0,neutral or dissatisfied +13977,2849,Male,Loyal Customer,51,Business travel,Business,2217,4,2,2,2,3,4,3,4,4,4,4,2,4,3,27,44.0,neutral or dissatisfied +13978,27777,Female,Loyal Customer,44,Business travel,Business,680,2,1,1,1,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +13979,125878,Female,disloyal Customer,36,Business travel,Eco,520,2,1,2,3,1,2,1,1,2,1,3,4,3,1,0,10.0,neutral or dissatisfied +13980,66768,Male,Loyal Customer,36,Business travel,Business,802,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +13981,31825,Male,disloyal Customer,46,Business travel,Business,2762,5,5,5,4,5,5,5,2,2,5,4,5,3,5,0,1.0,satisfied +13982,110807,Female,Loyal Customer,20,Personal Travel,Eco,990,3,4,3,4,2,3,2,2,3,3,5,3,4,2,9,4.0,neutral or dissatisfied +13983,112,Female,disloyal Customer,11,Business travel,Eco,562,4,0,4,3,2,4,2,2,3,2,4,1,3,2,1,2.0,neutral or dissatisfied +13984,68528,Female,Loyal Customer,59,Business travel,Business,2115,4,4,4,4,3,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +13985,33641,Male,Loyal Customer,13,Personal Travel,Eco,413,3,4,3,2,5,3,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +13986,27287,Male,Loyal Customer,45,Business travel,Eco,987,4,1,1,1,4,4,4,4,3,1,4,3,2,4,0,7.0,satisfied +13987,85395,Female,Loyal Customer,43,Business travel,Business,1983,0,0,0,3,5,4,4,1,1,1,1,5,1,4,3,0.0,satisfied +13988,23611,Male,Loyal Customer,41,Personal Travel,Eco,692,1,4,1,3,1,1,1,1,3,2,4,5,5,1,110,107.0,neutral or dissatisfied +13989,27659,Female,disloyal Customer,39,Business travel,Business,1216,2,2,2,4,4,2,5,4,3,3,1,1,3,4,38,37.0,neutral or dissatisfied +13990,7709,Male,Loyal Customer,50,Business travel,Business,1701,3,3,3,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +13991,111502,Female,disloyal Customer,23,Business travel,Eco,391,1,2,1,4,5,1,5,5,1,4,4,1,4,5,13,4.0,neutral or dissatisfied +13992,107058,Female,Loyal Customer,17,Business travel,Business,395,5,5,5,5,4,4,4,4,5,5,5,2,1,4,0,0.0,satisfied +13993,57750,Male,Loyal Customer,34,Business travel,Business,2704,3,2,3,3,4,4,4,5,5,4,4,4,5,4,81,55.0,satisfied +13994,20402,Male,Loyal Customer,33,Business travel,Eco Plus,459,4,1,1,1,4,4,4,4,5,2,5,1,5,4,10,7.0,satisfied +13995,77649,Female,Loyal Customer,41,Business travel,Business,2308,1,1,1,1,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +13996,119405,Male,Loyal Customer,45,Business travel,Business,399,3,3,3,3,2,5,5,5,5,5,5,4,5,3,1,0.0,satisfied +13997,105108,Female,Loyal Customer,44,Business travel,Business,2812,5,5,5,5,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +13998,54045,Female,disloyal Customer,22,Business travel,Eco,1416,5,4,4,1,2,5,2,2,2,1,5,2,4,2,7,0.0,satisfied +13999,58617,Female,Loyal Customer,36,Business travel,Eco,235,4,3,3,3,4,4,4,2,4,3,4,4,3,4,169,155.0,neutral or dissatisfied +14000,40139,Female,Loyal Customer,47,Personal Travel,Eco Plus,200,2,4,2,1,5,2,3,1,1,2,1,1,1,5,0,6.0,neutral or dissatisfied +14001,3849,Female,Loyal Customer,14,Personal Travel,Eco,650,0,3,0,5,3,0,3,3,5,3,1,1,5,3,0,0.0,satisfied +14002,107267,Male,Loyal Customer,41,Business travel,Business,307,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +14003,1714,Female,Loyal Customer,46,Business travel,Business,364,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,1.0,satisfied +14004,48792,Male,Loyal Customer,55,Business travel,Business,2781,3,3,4,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +14005,20188,Female,Loyal Customer,60,Business travel,Eco Plus,403,2,5,5,5,2,2,2,1,3,2,3,2,1,2,191,183.0,neutral or dissatisfied +14006,104315,Female,Loyal Customer,50,Business travel,Business,2733,1,1,5,1,4,4,4,5,5,5,5,3,5,5,111,131.0,satisfied +14007,119248,Female,Loyal Customer,14,Personal Travel,Eco Plus,331,2,5,2,3,3,2,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +14008,79896,Male,disloyal Customer,22,Business travel,Business,1047,0,0,0,3,2,0,2,2,4,2,4,5,4,2,0,0.0,satisfied +14009,105807,Female,Loyal Customer,22,Personal Travel,Eco,919,2,4,2,3,4,2,3,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +14010,48997,Female,Loyal Customer,37,Business travel,Eco,421,4,2,2,2,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +14011,13861,Female,Loyal Customer,22,Business travel,Eco,760,5,4,2,2,5,5,5,5,2,1,1,5,2,5,126,206.0,satisfied +14012,17689,Female,Loyal Customer,22,Business travel,Business,2269,3,1,3,3,5,5,5,5,4,1,1,5,4,5,0,0.0,satisfied +14013,13163,Female,Loyal Customer,28,Business travel,Eco Plus,427,4,3,3,3,4,4,4,4,4,1,2,5,3,4,83,89.0,satisfied +14014,110758,Female,disloyal Customer,23,Business travel,Business,1128,5,5,5,2,5,5,5,5,5,2,4,3,5,5,38,34.0,satisfied +14015,70748,Male,Loyal Customer,37,Personal Travel,Eco Plus,675,3,5,3,4,5,3,5,5,5,5,5,3,5,5,0,7.0,neutral or dissatisfied +14016,237,Male,Loyal Customer,7,Personal Travel,Business,719,3,5,3,2,2,3,2,2,3,4,5,3,5,2,0,2.0,neutral or dissatisfied +14017,35045,Female,Loyal Customer,41,Business travel,Business,972,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +14018,32810,Female,Loyal Customer,35,Business travel,Business,1854,3,5,5,5,4,4,3,4,4,4,3,2,4,1,0,2.0,neutral or dissatisfied +14019,41584,Female,Loyal Customer,21,Personal Travel,Eco,1334,2,5,2,2,3,2,3,3,3,2,5,5,4,3,17,20.0,neutral or dissatisfied +14020,78514,Female,Loyal Customer,37,Personal Travel,Eco,526,4,4,4,1,4,4,1,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +14021,99,Female,Loyal Customer,52,Business travel,Business,562,5,5,5,5,3,4,5,4,4,4,4,4,4,3,27,18.0,satisfied +14022,52593,Female,Loyal Customer,53,Business travel,Business,119,4,1,5,5,4,3,3,4,4,3,4,1,4,2,47,42.0,neutral or dissatisfied +14023,73316,Female,Loyal Customer,32,Business travel,Business,3602,1,1,1,1,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +14024,72271,Female,Loyal Customer,25,Business travel,Business,919,4,4,1,4,4,4,4,4,2,3,2,1,3,4,0,2.0,neutral or dissatisfied +14025,86792,Female,Loyal Customer,59,Business travel,Business,3641,1,1,1,1,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +14026,82490,Female,disloyal Customer,37,Business travel,Business,488,2,1,1,1,5,1,5,5,3,2,5,4,5,5,7,2.0,neutral or dissatisfied +14027,7276,Female,Loyal Customer,45,Personal Travel,Eco,139,5,4,5,1,1,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +14028,63030,Male,disloyal Customer,29,Business travel,Eco,909,1,1,1,4,4,1,2,4,1,1,1,5,2,4,0,0.0,neutral or dissatisfied +14029,11559,Female,Loyal Customer,49,Business travel,Business,657,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +14030,53144,Female,Loyal Customer,65,Personal Travel,Eco,413,2,4,2,1,5,5,5,4,4,2,1,3,4,3,36,26.0,neutral or dissatisfied +14031,24927,Male,Loyal Customer,53,Personal Travel,Eco,762,1,3,1,3,4,1,4,4,1,2,3,1,4,4,0,0.0,neutral or dissatisfied +14032,8280,Female,Loyal Customer,44,Personal Travel,Eco,335,2,2,2,2,2,2,3,5,5,2,5,3,5,4,21,10.0,neutral or dissatisfied +14033,12734,Female,Loyal Customer,23,Personal Travel,Eco,803,3,4,3,1,1,3,1,1,2,3,5,3,3,1,0,4.0,neutral or dissatisfied +14034,87017,Female,Loyal Customer,13,Personal Travel,Eco Plus,907,1,4,1,5,4,1,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +14035,41592,Male,Loyal Customer,26,Personal Travel,Eco,1242,1,5,1,4,2,1,2,2,4,2,4,3,5,2,0,2.0,neutral or dissatisfied +14036,118943,Male,Loyal Customer,53,Business travel,Business,1619,3,3,4,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +14037,124802,Male,Loyal Customer,38,Business travel,Business,280,0,0,0,3,3,5,5,1,1,1,1,4,1,4,0,32.0,satisfied +14038,47676,Male,Loyal Customer,19,Personal Travel,Eco,1464,2,1,2,1,4,2,4,4,1,4,1,3,1,4,8,8.0,neutral or dissatisfied +14039,59405,Female,Loyal Customer,35,Personal Travel,Eco,2399,3,3,2,3,3,2,4,3,2,5,4,1,4,3,52,65.0,neutral or dissatisfied +14040,129720,Female,Loyal Customer,47,Business travel,Business,337,1,3,3,3,3,2,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +14041,63021,Female,Loyal Customer,30,Business travel,Business,967,1,1,1,1,4,5,4,4,5,3,5,5,5,4,2,0.0,satisfied +14042,8436,Female,Loyal Customer,28,Business travel,Eco Plus,862,2,2,2,2,2,2,2,4,4,3,3,2,1,2,184,173.0,neutral or dissatisfied +14043,93283,Male,Loyal Customer,25,Personal Travel,Eco,867,5,3,5,1,5,5,3,5,1,5,3,1,5,5,0,0.0,satisfied +14044,40476,Male,Loyal Customer,41,Business travel,Business,3155,3,2,2,2,4,4,4,3,3,3,3,1,3,4,0,14.0,neutral or dissatisfied +14045,47622,Male,disloyal Customer,29,Business travel,Eco,1334,4,4,4,4,3,4,3,3,1,1,4,2,3,3,0,0.0,neutral or dissatisfied +14046,97265,Male,Loyal Customer,49,Personal Travel,Eco,296,3,5,3,4,1,3,1,1,3,5,5,5,5,1,0,3.0,neutral or dissatisfied +14047,34139,Female,Loyal Customer,43,Business travel,Business,1179,5,5,5,5,4,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +14048,35428,Female,Loyal Customer,26,Personal Travel,Eco,1074,3,5,3,2,1,3,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +14049,74775,Male,Loyal Customer,30,Business travel,Business,2282,4,4,4,4,4,4,4,4,5,5,4,3,5,4,20,1.0,satisfied +14050,82726,Male,Loyal Customer,58,Business travel,Business,2591,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +14051,15810,Female,Loyal Customer,47,Personal Travel,Eco,246,1,4,1,2,5,5,5,3,3,1,3,3,3,3,29,15.0,neutral or dissatisfied +14052,118866,Male,Loyal Customer,34,Personal Travel,Eco Plus,369,3,3,4,4,2,4,2,2,1,3,1,5,4,2,0,0.0,neutral or dissatisfied +14053,75115,Male,disloyal Customer,36,Business travel,Business,1744,3,3,3,4,3,3,3,3,3,5,4,4,5,3,5,0.0,neutral or dissatisfied +14054,49320,Male,Loyal Customer,46,Business travel,Business,2407,2,2,2,2,3,3,3,4,4,4,3,2,4,1,0,8.0,satisfied +14055,77291,Female,Loyal Customer,41,Business travel,Business,391,5,5,5,5,4,4,5,4,4,4,4,4,4,3,11,34.0,satisfied +14056,41274,Female,Loyal Customer,26,Business travel,Business,2440,3,3,3,3,4,4,4,4,4,3,5,2,2,4,0,4.0,satisfied +14057,28166,Female,Loyal Customer,57,Business travel,Eco,859,2,3,3,3,3,2,3,2,2,2,2,5,2,4,0,0.0,satisfied +14058,6707,Female,Loyal Customer,15,Personal Travel,Eco,258,3,3,3,1,3,1,1,5,3,3,4,1,1,1,55,149.0,neutral or dissatisfied +14059,77951,Male,Loyal Customer,58,Business travel,Business,214,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,1.0,satisfied +14060,62362,Male,Loyal Customer,19,Personal Travel,Eco Plus,1589,2,5,2,3,3,2,3,3,3,3,3,3,4,3,34,37.0,neutral or dissatisfied +14061,12294,Male,Loyal Customer,68,Business travel,Eco,253,1,4,4,4,1,1,1,1,1,5,3,1,3,1,54,38.0,neutral or dissatisfied +14062,39999,Female,Loyal Customer,45,Business travel,Business,575,4,4,4,4,4,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +14063,76342,Female,disloyal Customer,41,Business travel,Business,554,1,1,1,1,3,1,3,3,2,5,3,1,5,3,12,23.0,neutral or dissatisfied +14064,125134,Male,Loyal Customer,31,Personal Travel,Eco,361,3,5,5,3,5,5,5,5,4,3,5,4,5,5,50,52.0,neutral or dissatisfied +14065,54478,Male,disloyal Customer,30,Business travel,Eco,802,3,3,3,4,5,3,5,5,1,2,4,2,2,5,12,8.0,neutral or dissatisfied +14066,118011,Female,Loyal Customer,31,Business travel,Business,1037,4,4,4,4,5,5,5,5,4,4,4,5,5,5,52,39.0,satisfied +14067,111804,Female,Loyal Customer,35,Business travel,Business,2603,3,4,2,2,2,3,4,3,3,3,3,1,3,2,6,24.0,neutral or dissatisfied +14068,31059,Female,Loyal Customer,42,Business travel,Eco,241,2,5,5,5,4,1,1,2,2,2,2,5,2,1,0,0.0,satisfied +14069,56442,Male,disloyal Customer,55,Business travel,Eco,319,3,2,4,3,5,4,2,5,1,3,3,2,3,5,64,51.0,neutral or dissatisfied +14070,80962,Male,Loyal Customer,39,Business travel,Business,3380,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +14071,108235,Male,disloyal Customer,36,Business travel,Business,895,2,3,3,4,1,3,1,1,5,4,5,5,5,1,106,110.0,neutral or dissatisfied +14072,127088,Female,disloyal Customer,27,Business travel,Eco,338,2,4,2,4,4,2,4,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +14073,18112,Female,Loyal Customer,39,Business travel,Business,1925,4,4,4,4,5,2,5,4,4,4,4,2,4,2,0,0.0,satisfied +14074,16395,Female,disloyal Customer,17,Business travel,Eco,404,2,1,2,4,1,2,1,1,3,4,4,3,3,1,51,63.0,neutral or dissatisfied +14075,76009,Female,Loyal Customer,54,Business travel,Business,2734,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +14076,57985,Male,Loyal Customer,44,Personal Travel,Eco,589,2,5,2,3,5,2,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +14077,69266,Female,Loyal Customer,48,Personal Travel,Eco,733,1,2,1,4,4,4,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +14078,74984,Male,Loyal Customer,70,Personal Travel,Eco,2586,3,5,3,2,4,3,4,4,3,5,2,5,5,4,0,0.0,neutral or dissatisfied +14079,48866,Male,disloyal Customer,49,Business travel,Eco,250,3,0,3,2,2,3,2,2,4,2,4,5,1,2,0,0.0,neutral or dissatisfied +14080,90859,Female,Loyal Customer,47,Business travel,Eco,270,2,4,4,4,3,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +14081,67596,Female,Loyal Customer,47,Business travel,Business,1725,5,5,5,5,3,5,4,4,4,4,4,3,4,4,10,4.0,satisfied +14082,27602,Female,Loyal Customer,62,Personal Travel,Eco,954,3,2,3,3,2,3,4,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +14083,122970,Male,Loyal Customer,43,Business travel,Business,2828,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +14084,114352,Male,Loyal Customer,12,Personal Travel,Eco,948,1,4,1,2,4,1,5,4,4,4,5,4,5,4,39,54.0,neutral or dissatisfied +14085,4514,Male,Loyal Customer,63,Personal Travel,Eco,551,3,4,3,5,5,3,5,5,5,3,1,2,2,5,46,36.0,neutral or dissatisfied +14086,18319,Male,Loyal Customer,57,Business travel,Eco,715,1,2,2,2,1,1,1,1,2,1,3,4,3,1,5,0.0,neutral or dissatisfied +14087,89015,Female,disloyal Customer,39,Business travel,Business,2116,4,4,4,3,3,4,3,3,4,4,2,3,3,3,32,25.0,neutral or dissatisfied +14088,37444,Male,disloyal Customer,42,Business travel,Eco,944,1,1,1,3,2,1,2,2,1,3,2,3,3,2,45,32.0,neutral or dissatisfied +14089,30700,Female,Loyal Customer,40,Personal Travel,Eco,680,4,4,4,3,3,4,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +14090,266,Male,Loyal Customer,44,Business travel,Business,2770,2,2,3,2,4,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +14091,108284,Male,Loyal Customer,56,Business travel,Business,1855,1,1,1,1,2,4,4,3,3,3,3,5,3,4,8,0.0,satisfied +14092,128365,Male,disloyal Customer,26,Business travel,Eco,647,2,2,2,3,5,2,5,5,1,5,2,3,2,5,19,24.0,neutral or dissatisfied +14093,97584,Male,Loyal Customer,40,Personal Travel,Eco,448,1,2,1,3,1,1,1,1,1,1,3,3,4,1,105,96.0,neutral or dissatisfied +14094,89632,Female,Loyal Customer,11,Business travel,Business,944,2,2,2,2,2,2,2,2,1,3,3,2,4,2,79,72.0,neutral or dissatisfied +14095,6765,Female,disloyal Customer,38,Business travel,Business,224,4,4,4,2,3,4,4,3,5,4,4,4,5,3,24,20.0,neutral or dissatisfied +14096,24588,Female,Loyal Customer,33,Business travel,Eco,666,3,2,2,2,3,3,3,3,4,1,3,2,4,3,11,11.0,neutral or dissatisfied +14097,94708,Male,Loyal Customer,40,Business travel,Business,3143,3,3,4,3,2,5,5,5,5,5,5,4,5,3,4,2.0,satisfied +14098,51721,Male,Loyal Customer,51,Personal Travel,Eco,370,3,5,3,3,2,3,3,2,5,1,5,2,1,2,0,0.0,neutral or dissatisfied +14099,33378,Female,Loyal Customer,53,Personal Travel,Eco,2349,3,2,3,3,4,4,3,2,2,3,3,1,2,3,10,0.0,neutral or dissatisfied +14100,61190,Female,Loyal Customer,64,Business travel,Eco,862,1,5,5,5,5,3,3,1,1,1,1,3,1,3,17,34.0,neutral or dissatisfied +14101,41581,Male,Loyal Customer,51,Personal Travel,Eco,715,0,5,0,3,2,0,2,2,4,4,5,5,5,2,0,5.0,satisfied +14102,44163,Female,disloyal Customer,68,Business travel,Eco,229,1,5,1,3,2,1,2,2,3,2,2,4,2,2,0,0.0,neutral or dissatisfied +14103,60174,Female,Loyal Customer,37,Personal Travel,Eco,1120,2,4,2,4,4,2,4,4,3,5,5,5,5,4,2,2.0,neutral or dissatisfied +14104,117529,Male,Loyal Customer,35,Personal Travel,Business,347,1,4,1,4,4,5,5,3,3,1,1,5,3,5,0,0.0,neutral or dissatisfied +14105,93661,Male,Loyal Customer,31,Business travel,Business,655,4,4,4,4,5,5,5,5,5,3,5,5,5,5,24,26.0,satisfied +14106,85394,Female,Loyal Customer,40,Business travel,Business,2502,4,4,4,4,5,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +14107,29150,Male,disloyal Customer,26,Business travel,Eco Plus,679,3,4,4,1,4,4,4,4,2,2,4,1,5,4,0,0.0,neutral or dissatisfied +14108,129057,Female,Loyal Customer,11,Personal Travel,Eco,1744,5,4,5,5,1,5,1,1,3,2,4,3,4,1,19,1.0,satisfied +14109,121779,Female,disloyal Customer,25,Business travel,Business,337,1,5,1,3,3,1,5,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +14110,84258,Male,Loyal Customer,52,Business travel,Business,1631,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14111,32175,Male,Loyal Customer,57,Business travel,Eco,102,4,3,3,3,4,4,4,4,3,5,4,2,1,4,0,0.0,satisfied +14112,17971,Female,Loyal Customer,13,Personal Travel,Eco,500,2,5,2,2,5,2,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +14113,68519,Male,Loyal Customer,41,Personal Travel,Eco,678,2,4,2,1,3,2,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +14114,27152,Female,Loyal Customer,25,Business travel,Business,2701,3,5,5,5,3,3,3,2,4,3,4,3,4,3,0,15.0,neutral or dissatisfied +14115,21535,Female,Loyal Customer,37,Personal Travel,Eco,164,2,4,2,3,4,2,4,4,5,4,4,5,5,4,2,0.0,neutral or dissatisfied +14116,120883,Male,Loyal Customer,51,Business travel,Business,2230,1,1,1,1,2,5,4,4,4,4,4,4,4,3,1,17.0,satisfied +14117,43915,Male,Loyal Customer,56,Personal Travel,Eco,114,1,4,1,1,2,1,2,2,5,5,4,5,2,2,14,1.0,neutral or dissatisfied +14118,110501,Male,Loyal Customer,51,Business travel,Eco Plus,883,3,4,4,4,3,3,3,3,3,3,4,2,3,3,25,16.0,neutral or dissatisfied +14119,1524,Female,Loyal Customer,48,Business travel,Business,3711,2,2,5,2,3,4,5,4,4,4,4,3,4,3,4,6.0,satisfied +14120,62365,Female,Loyal Customer,31,Personal Travel,Business,2611,2,2,2,4,3,2,5,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +14121,94501,Female,Loyal Customer,56,Business travel,Business,2835,1,1,1,1,4,5,5,5,5,5,4,3,5,3,19,16.0,satisfied +14122,84422,Female,Loyal Customer,35,Personal Travel,Eco,606,2,5,2,3,2,2,2,2,3,5,4,5,5,2,25,25.0,neutral or dissatisfied +14123,116332,Male,Loyal Customer,47,Personal Travel,Eco,446,1,4,1,4,1,1,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +14124,11370,Male,Loyal Customer,34,Personal Travel,Eco,247,4,4,4,1,4,4,4,4,4,5,5,5,4,4,8,6.0,neutral or dissatisfied +14125,108007,Female,Loyal Customer,9,Personal Travel,Eco,271,0,1,0,4,5,0,4,5,4,2,3,2,4,5,0,3.0,satisfied +14126,44494,Male,Loyal Customer,33,Business travel,Eco Plus,261,0,0,0,3,2,0,2,2,1,3,4,1,5,2,0,0.0,satisfied +14127,91566,Female,Loyal Customer,23,Personal Travel,Eco Plus,680,3,5,3,1,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +14128,25832,Female,Loyal Customer,46,Business travel,Business,2506,2,2,3,2,5,1,2,3,3,5,3,2,3,1,0,0.0,satisfied +14129,106098,Male,Loyal Customer,57,Business travel,Business,3751,5,5,5,5,4,4,5,2,2,2,2,3,2,5,15,4.0,satisfied +14130,37005,Female,Loyal Customer,61,Personal Travel,Eco,814,2,5,2,2,3,5,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +14131,124856,Female,Loyal Customer,43,Business travel,Business,3665,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +14132,87977,Female,Loyal Customer,33,Business travel,Business,2707,4,5,5,5,2,3,4,4,4,4,4,2,4,4,3,6.0,neutral or dissatisfied +14133,13939,Male,Loyal Customer,53,Business travel,Business,1532,2,3,3,3,1,4,4,3,3,3,2,4,3,1,0,14.0,neutral or dissatisfied +14134,75776,Male,Loyal Customer,28,Personal Travel,Eco,813,2,5,3,3,4,3,4,4,5,4,2,4,1,4,16,7.0,neutral or dissatisfied +14135,7458,Female,Loyal Customer,39,Business travel,Eco Plus,152,2,5,5,5,2,2,2,2,1,3,4,1,3,2,36,38.0,neutral or dissatisfied +14136,44974,Male,disloyal Customer,40,Business travel,Business,359,1,1,1,3,3,1,3,3,5,2,5,2,3,3,0,0.0,neutral or dissatisfied +14137,13168,Male,Loyal Customer,18,Personal Travel,Eco Plus,427,3,3,3,4,5,3,5,5,2,1,1,2,4,5,0,0.0,neutral or dissatisfied +14138,50025,Female,disloyal Customer,57,Business travel,Eco,158,2,3,2,3,1,2,1,1,4,1,3,1,3,1,0,3.0,neutral or dissatisfied +14139,66503,Female,Loyal Customer,67,Business travel,Business,3376,3,3,3,3,5,2,2,3,3,3,3,1,3,4,3,2.0,neutral or dissatisfied +14140,70929,Female,Loyal Customer,52,Business travel,Business,2411,3,3,3,3,4,4,4,3,4,4,4,4,5,4,287,289.0,satisfied +14141,10305,Male,Loyal Customer,49,Business travel,Business,3702,3,3,3,3,5,5,5,5,5,5,5,4,5,4,80,79.0,satisfied +14142,23338,Female,Loyal Customer,40,Personal Travel,Eco,563,4,4,4,4,3,4,4,3,5,4,4,3,4,3,3,0.0,neutral or dissatisfied +14143,14375,Male,Loyal Customer,39,Business travel,Eco Plus,1215,4,3,3,3,4,4,4,4,1,3,3,3,5,4,1,0.0,satisfied +14144,110148,Male,Loyal Customer,29,Business travel,Business,2752,3,5,4,5,3,3,3,3,3,2,3,4,3,3,7,0.0,neutral or dissatisfied +14145,26292,Female,disloyal Customer,28,Business travel,Eco,1199,4,3,3,3,5,3,5,5,1,1,2,2,2,5,20,18.0,satisfied +14146,37788,Male,disloyal Customer,30,Business travel,Eco Plus,989,4,4,4,4,4,4,3,4,3,1,4,2,4,4,0,9.0,neutral or dissatisfied +14147,109830,Male,Loyal Customer,37,Business travel,Business,1011,2,2,2,2,4,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +14148,15702,Female,Loyal Customer,48,Business travel,Eco,479,4,4,4,4,3,5,1,5,5,4,5,3,5,2,4,0.0,satisfied +14149,19537,Female,Loyal Customer,46,Business travel,Business,160,0,4,0,1,5,4,2,5,5,5,5,4,5,4,0,0.0,satisfied +14150,116599,Male,Loyal Customer,44,Business travel,Business,308,4,4,4,4,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +14151,49493,Male,disloyal Customer,39,Business travel,Eco,326,2,4,2,5,2,2,2,2,1,5,3,2,4,2,0,0.0,neutral or dissatisfied +14152,20069,Female,Loyal Customer,14,Personal Travel,Eco,607,1,4,1,1,5,1,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +14153,21791,Female,Loyal Customer,45,Business travel,Business,3956,0,0,0,4,1,3,5,3,3,3,3,3,3,4,2,4.0,satisfied +14154,58296,Male,Loyal Customer,49,Business travel,Business,413,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,8.0,satisfied +14155,16886,Female,disloyal Customer,45,Business travel,Eco,746,2,2,2,1,4,2,4,4,3,1,5,5,2,4,0,0.0,neutral or dissatisfied +14156,120926,Male,disloyal Customer,26,Business travel,Business,920,5,5,5,3,5,5,5,5,4,2,5,5,5,5,6,0.0,satisfied +14157,34556,Male,disloyal Customer,22,Business travel,Eco,1598,2,2,2,2,3,2,3,3,2,4,4,3,1,3,3,0.0,neutral or dissatisfied +14158,36333,Male,disloyal Customer,25,Business travel,Eco,395,2,4,2,5,1,2,1,1,2,1,5,1,5,1,0,1.0,neutral or dissatisfied +14159,102375,Male,Loyal Customer,36,Business travel,Business,2320,3,3,3,3,1,4,2,5,5,5,5,3,5,4,0,0.0,satisfied +14160,123126,Male,Loyal Customer,46,Business travel,Eco,600,3,1,5,1,2,3,2,2,1,1,3,4,3,2,8,0.0,neutral or dissatisfied +14161,65445,Male,Loyal Customer,48,Business travel,Business,2645,4,4,4,4,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +14162,79509,Male,disloyal Customer,28,Business travel,Business,762,3,2,2,2,1,2,1,1,4,4,4,3,4,1,3,0.0,neutral or dissatisfied +14163,95416,Male,Loyal Customer,56,Business travel,Business,248,4,4,4,4,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +14164,11868,Male,Loyal Customer,63,Personal Travel,Eco,912,1,4,1,4,4,1,4,4,2,2,4,4,3,4,0,0.0,neutral or dissatisfied +14165,73565,Female,Loyal Customer,60,Business travel,Business,3353,4,3,3,3,1,4,3,2,2,2,4,1,2,2,0,0.0,neutral or dissatisfied +14166,62037,Male,disloyal Customer,42,Business travel,Business,2586,4,4,4,2,5,4,2,5,4,3,4,4,4,5,35,25.0,satisfied +14167,50716,Male,Loyal Customer,9,Personal Travel,Eco,89,2,5,2,3,4,2,4,4,4,3,5,4,5,4,0,7.0,neutral or dissatisfied +14168,36479,Male,Loyal Customer,49,Business travel,Business,1010,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,34.0,satisfied +14169,39708,Male,Loyal Customer,23,Business travel,Business,2398,5,5,5,5,4,4,4,4,5,2,3,5,3,4,0,5.0,satisfied +14170,115636,Male,Loyal Customer,58,Business travel,Business,2506,1,1,1,1,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +14171,127017,Female,Loyal Customer,42,Business travel,Eco,304,2,5,5,5,5,4,3,2,2,2,2,4,2,1,0,6.0,neutral or dissatisfied +14172,100831,Female,disloyal Customer,14,Business travel,Eco,711,0,0,0,1,1,0,1,1,4,3,4,4,5,1,77,62.0,satisfied +14173,94989,Female,Loyal Customer,21,Personal Travel,Eco,562,4,4,4,3,1,4,1,1,3,2,4,5,5,1,0,0.0,satisfied +14174,127169,Female,Loyal Customer,16,Personal Travel,Eco,647,4,2,4,4,4,4,4,4,3,5,4,1,4,4,39,35.0,neutral or dissatisfied +14175,7440,Female,Loyal Customer,31,Personal Travel,Eco,522,3,2,3,3,2,3,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +14176,12158,Female,Loyal Customer,9,Business travel,Business,1214,1,0,0,3,5,0,5,5,3,3,3,1,4,5,48,27.0,neutral or dissatisfied +14177,13270,Female,Loyal Customer,59,Personal Travel,Eco,657,4,0,4,3,3,5,4,3,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +14178,66718,Male,Loyal Customer,10,Personal Travel,Eco,802,4,4,4,4,4,4,5,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +14179,129834,Male,Loyal Customer,27,Personal Travel,Eco,337,1,4,3,4,4,3,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +14180,62629,Male,Loyal Customer,39,Personal Travel,Eco,1726,4,4,4,3,5,4,5,5,4,2,3,4,4,5,2,24.0,neutral or dissatisfied +14181,1450,Female,Loyal Customer,46,Business travel,Business,3431,2,2,2,2,4,4,5,5,5,5,5,5,5,3,11,7.0,satisfied +14182,2112,Female,Loyal Customer,69,Personal Travel,Eco Plus,812,4,3,5,3,4,1,1,5,5,5,5,2,5,3,34,31.0,neutral or dissatisfied +14183,48773,Female,Loyal Customer,43,Business travel,Business,3775,4,3,4,4,3,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +14184,42712,Male,Loyal Customer,23,Business travel,Eco Plus,604,5,1,1,1,5,5,5,5,2,3,1,1,2,5,0,0.0,satisfied +14185,6557,Male,Loyal Customer,47,Business travel,Business,2022,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,,satisfied +14186,51977,Male,disloyal Customer,39,Business travel,Business,347,5,5,5,1,1,5,1,1,4,5,4,2,3,1,0,0.0,satisfied +14187,64730,Male,Loyal Customer,39,Business travel,Business,3996,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +14188,125223,Male,Loyal Customer,36,Personal Travel,Eco,651,3,1,3,4,4,3,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +14189,71046,Male,Loyal Customer,52,Business travel,Business,1593,5,5,5,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +14190,102806,Male,Loyal Customer,54,Business travel,Business,3977,2,2,2,2,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +14191,114657,Male,Loyal Customer,51,Business travel,Business,1695,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +14192,45157,Female,Loyal Customer,58,Business travel,Eco,174,4,4,4,4,5,1,5,4,4,4,4,3,4,1,0,0.0,satisfied +14193,89845,Female,Loyal Customer,21,Personal Travel,Business,1487,3,3,3,3,1,3,1,1,1,3,3,3,4,1,28,19.0,neutral or dissatisfied +14194,118049,Male,disloyal Customer,28,Business travel,Eco,1044,2,2,2,3,5,2,4,5,1,5,4,2,4,5,106,85.0,neutral or dissatisfied +14195,14938,Male,Loyal Customer,33,Business travel,Business,3891,3,3,3,3,5,5,5,5,4,4,1,1,4,5,84,79.0,satisfied +14196,38403,Female,Loyal Customer,19,Personal Travel,Eco,1754,3,2,3,4,2,3,2,2,4,3,3,1,4,2,33,20.0,neutral or dissatisfied +14197,41488,Female,Loyal Customer,38,Business travel,Eco,1464,5,4,1,4,5,5,5,5,1,1,1,5,4,5,18,47.0,satisfied +14198,123728,Female,disloyal Customer,26,Business travel,Eco Plus,214,1,4,1,1,2,1,2,2,5,1,1,1,3,2,0,0.0,neutral or dissatisfied +14199,38733,Female,Loyal Customer,59,Business travel,Eco,353,3,5,3,5,1,1,4,3,3,3,3,4,3,5,0,0.0,satisfied +14200,75476,Female,Loyal Customer,13,Personal Travel,Eco,2342,4,4,4,4,3,4,3,3,5,3,1,5,4,3,0,0.0,neutral or dissatisfied +14201,12910,Male,Loyal Customer,17,Business travel,Eco,563,1,2,2,2,1,1,3,1,1,5,4,2,3,1,54,54.0,neutral or dissatisfied +14202,80438,Female,Loyal Customer,49,Personal Travel,Eco,2248,3,5,2,2,5,3,4,1,1,2,1,3,1,5,12,0.0,neutral or dissatisfied +14203,520,Female,Loyal Customer,50,Business travel,Business,2938,1,1,1,1,5,4,5,5,5,4,5,4,5,4,0,4.0,satisfied +14204,98364,Female,disloyal Customer,55,Business travel,Eco,837,4,4,4,1,5,4,5,5,1,4,2,4,3,5,8,3.0,neutral or dissatisfied +14205,18497,Male,Loyal Customer,32,Business travel,Business,3520,3,3,3,3,4,4,4,4,2,2,1,5,5,4,0,0.0,satisfied +14206,32,Male,disloyal Customer,21,Business travel,Eco,173,4,0,4,4,3,4,3,3,5,5,4,3,4,3,0,0.0,satisfied +14207,72838,Female,Loyal Customer,17,Personal Travel,Eco,1013,3,4,3,3,1,3,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +14208,16208,Male,Loyal Customer,18,Personal Travel,Eco,212,3,2,3,3,3,1,1,3,4,4,3,1,3,1,148,151.0,neutral or dissatisfied +14209,106276,Male,Loyal Customer,30,Business travel,Business,604,1,1,1,1,1,1,1,1,4,1,3,1,4,1,0,7.0,neutral or dissatisfied +14210,92137,Female,Loyal Customer,55,Personal Travel,Eco,1535,1,5,1,1,2,4,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +14211,26620,Female,Loyal Customer,25,Business travel,Business,515,2,2,2,2,4,4,4,4,4,2,3,4,2,4,0,0.0,satisfied +14212,61549,Female,Loyal Customer,43,Business travel,Business,2419,5,5,5,5,2,4,5,4,4,4,4,5,4,4,1,1.0,satisfied +14213,91301,Female,Loyal Customer,37,Business travel,Eco Plus,404,1,1,1,1,1,1,1,1,3,3,3,3,3,1,0,7.0,neutral or dissatisfied +14214,54630,Female,disloyal Customer,27,Business travel,Eco,965,2,2,2,1,4,2,1,4,5,4,5,2,2,4,10,2.0,neutral or dissatisfied +14215,19730,Male,Loyal Customer,51,Personal Travel,Eco,475,3,5,3,1,4,3,4,4,3,1,1,4,2,4,74,82.0,neutral or dissatisfied +14216,10999,Female,disloyal Customer,55,Business travel,Eco,117,3,1,2,4,3,2,3,3,2,3,4,4,4,3,78,87.0,neutral or dissatisfied +14217,15039,Female,Loyal Customer,57,Business travel,Eco,488,3,1,1,1,3,4,3,3,3,3,3,5,3,2,0,0.0,satisfied +14218,98027,Female,disloyal Customer,26,Business travel,Eco,614,2,4,2,3,4,2,4,4,1,3,4,1,2,4,2,0.0,neutral or dissatisfied +14219,55012,Female,Loyal Customer,26,Business travel,Business,1379,1,1,5,1,4,5,4,4,5,4,4,5,5,4,0,0.0,satisfied +14220,21174,Female,Loyal Customer,61,Personal Travel,Business,192,3,2,3,4,2,3,4,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +14221,80898,Female,Loyal Customer,40,Business travel,Business,3442,4,2,2,2,2,3,4,4,4,4,4,1,4,2,7,0.0,neutral or dissatisfied +14222,32331,Male,Loyal Customer,41,Business travel,Business,163,2,2,2,2,3,3,4,1,1,2,2,3,1,1,0,0.0,neutral or dissatisfied +14223,49995,Male,disloyal Customer,39,Business travel,Eco,209,4,0,4,4,3,4,5,3,1,5,3,3,4,3,28,31.0,neutral or dissatisfied +14224,91611,Female,Loyal Customer,60,Business travel,Business,2836,1,1,1,1,2,5,4,4,4,4,4,3,4,5,6,0.0,satisfied +14225,84291,Female,Loyal Customer,36,Business travel,Business,235,0,0,0,3,3,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +14226,12193,Male,Loyal Customer,27,Business travel,Eco Plus,931,5,4,4,4,5,5,5,5,4,3,5,3,1,5,69,72.0,satisfied +14227,122944,Male,Loyal Customer,59,Business travel,Business,1595,5,5,5,5,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +14228,43008,Female,Loyal Customer,49,Business travel,Business,1684,1,1,1,1,2,3,2,4,4,4,4,3,4,4,48,54.0,satisfied +14229,129521,Female,disloyal Customer,43,Business travel,Business,718,2,2,2,3,2,2,2,2,4,5,3,3,3,2,7,0.0,neutral or dissatisfied +14230,22394,Male,Loyal Customer,45,Business travel,Business,83,2,2,3,2,1,2,4,4,4,4,4,1,4,3,0,0.0,satisfied +14231,91445,Male,disloyal Customer,47,Business travel,Business,859,2,2,2,2,5,2,2,5,3,2,5,3,5,5,20,26.0,neutral or dissatisfied +14232,86583,Male,disloyal Customer,15,Business travel,Eco,1269,3,3,3,4,3,3,3,3,3,1,3,2,3,3,0,11.0,neutral or dissatisfied +14233,88384,Male,disloyal Customer,38,Business travel,Business,270,3,3,3,2,5,3,5,5,5,4,5,5,4,5,5,3.0,neutral or dissatisfied +14234,43237,Male,disloyal Customer,21,Business travel,Business,531,5,0,5,3,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +14235,96111,Female,Loyal Customer,32,Personal Travel,Eco,795,2,4,2,3,2,2,2,2,3,3,4,4,5,2,0,3.0,neutral or dissatisfied +14236,37026,Male,Loyal Customer,43,Business travel,Business,2407,4,4,4,4,4,4,4,5,5,5,5,4,5,5,117,108.0,satisfied +14237,14465,Male,Loyal Customer,44,Personal Travel,Eco,674,1,5,1,3,4,1,3,4,3,4,5,4,4,4,32,28.0,neutral or dissatisfied +14238,393,Male,Loyal Customer,49,Business travel,Business,134,4,4,4,4,2,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +14239,56964,Female,disloyal Customer,37,Business travel,Eco,1065,1,1,1,4,1,2,2,2,3,4,3,2,4,2,3,9.0,neutral or dissatisfied +14240,6480,Male,Loyal Customer,47,Business travel,Business,3230,5,5,5,5,4,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +14241,29856,Female,disloyal Customer,25,Business travel,Eco,261,2,0,2,4,4,2,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +14242,24234,Male,Loyal Customer,59,Business travel,Business,302,3,3,3,3,5,1,2,4,4,4,4,3,4,2,0,0.0,satisfied +14243,81593,Female,disloyal Customer,26,Business travel,Eco,334,3,3,3,4,3,3,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +14244,43719,Female,Loyal Customer,10,Personal Travel,Eco,489,4,3,4,1,5,4,5,5,2,1,4,1,4,5,0,0.0,neutral or dissatisfied +14245,2982,Female,Loyal Customer,60,Personal Travel,Eco,462,1,1,1,4,2,3,3,1,1,1,1,1,1,4,59,53.0,neutral or dissatisfied +14246,100098,Male,Loyal Customer,54,Business travel,Business,468,5,5,5,5,5,4,5,3,3,3,3,3,3,4,0,1.0,satisfied +14247,11360,Male,Loyal Customer,10,Personal Travel,Eco,74,1,4,1,3,2,1,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +14248,6141,Female,Loyal Customer,47,Business travel,Business,409,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +14249,79159,Female,Loyal Customer,54,Personal Travel,Eco,2239,1,2,1,2,1,2,3,5,5,1,2,3,5,2,7,0.0,neutral or dissatisfied +14250,110393,Female,disloyal Customer,49,Business travel,Business,663,5,5,5,2,4,5,4,4,4,4,5,4,5,4,0,3.0,satisfied +14251,52780,Female,Loyal Customer,29,Business travel,Business,1874,1,1,1,1,4,4,4,4,5,1,3,3,1,4,0,0.0,satisfied +14252,128188,Female,Loyal Customer,60,Business travel,Business,1849,3,3,3,3,5,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +14253,1688,Male,Loyal Customer,55,Business travel,Business,2563,2,2,2,2,4,4,4,5,5,5,5,5,5,3,11,26.0,satisfied +14254,60063,Female,Loyal Customer,35,Business travel,Business,3268,2,2,2,2,4,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +14255,15573,Female,disloyal Customer,36,Business travel,Eco,229,4,0,4,3,2,4,2,2,5,2,4,4,3,2,107,107.0,neutral or dissatisfied +14256,55764,Female,Loyal Customer,31,Business travel,Business,1992,4,1,1,1,1,1,4,1,3,2,4,2,4,1,0,0.0,neutral or dissatisfied +14257,32403,Female,Loyal Customer,44,Business travel,Business,2083,1,1,1,1,5,1,4,4,4,4,4,1,4,1,0,0.0,satisfied +14258,99516,Female,disloyal Customer,21,Business travel,Eco,283,2,0,2,1,2,2,4,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +14259,82536,Female,disloyal Customer,23,Business travel,Eco,629,3,0,3,4,2,3,2,2,4,3,4,3,5,2,3,0.0,neutral or dissatisfied +14260,14414,Male,Loyal Customer,35,Business travel,Business,3796,3,3,3,3,1,4,4,4,4,5,4,1,4,5,3,8.0,satisfied +14261,84104,Male,Loyal Customer,60,Business travel,Eco,1069,3,5,5,5,3,3,3,3,2,1,4,4,3,3,21,6.0,neutral or dissatisfied +14262,30687,Male,Loyal Customer,34,Business travel,Business,680,1,5,5,5,3,2,2,1,1,1,1,3,1,1,50,52.0,neutral or dissatisfied +14263,112069,Male,Loyal Customer,60,Business travel,Business,1491,5,5,5,5,2,4,4,5,5,5,5,3,5,4,52,29.0,satisfied +14264,117813,Female,Loyal Customer,11,Personal Travel,Eco,328,4,4,4,3,2,4,2,2,1,5,3,4,4,2,4,4.0,satisfied +14265,120860,Male,Loyal Customer,37,Business travel,Business,2106,2,2,2,2,2,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +14266,109784,Male,Loyal Customer,30,Business travel,Business,1204,2,2,2,2,4,5,4,4,4,5,4,5,5,4,0,0.0,satisfied +14267,124998,Female,Loyal Customer,68,Business travel,Business,3817,2,1,1,1,5,3,4,4,4,4,2,1,4,1,0,0.0,neutral or dissatisfied +14268,82317,Female,disloyal Customer,24,Business travel,Business,456,0,0,0,4,2,0,2,2,5,3,4,4,5,2,0,0.0,satisfied +14269,95364,Female,Loyal Customer,15,Personal Travel,Eco,239,2,1,2,4,3,2,3,3,3,2,4,2,3,3,0,0.0,neutral or dissatisfied +14270,23464,Female,Loyal Customer,40,Business travel,Business,2799,3,2,2,2,5,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +14271,127767,Female,Loyal Customer,7,Personal Travel,Eco,255,2,4,2,5,3,2,3,3,1,3,4,3,4,3,0,0.0,neutral or dissatisfied +14272,83043,Male,Loyal Customer,52,Business travel,Business,1145,5,5,5,5,2,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +14273,37408,Female,disloyal Customer,28,Business travel,Eco,1074,5,5,5,1,2,5,2,2,2,5,3,3,4,2,0,0.0,satisfied +14274,119837,Female,Loyal Customer,38,Business travel,Eco,1095,3,1,1,1,3,3,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +14275,60900,Male,Loyal Customer,45,Personal Travel,Eco Plus,420,2,5,3,5,5,3,5,5,5,3,5,2,2,5,30,35.0,neutral or dissatisfied +14276,126193,Female,disloyal Customer,20,Business travel,Business,631,5,1,5,2,2,5,2,2,4,5,5,5,4,2,0,0.0,satisfied +14277,73402,Female,disloyal Customer,44,Business travel,Eco,1144,2,2,2,3,4,2,4,4,3,4,4,2,3,4,75,57.0,neutral or dissatisfied +14278,13438,Female,Loyal Customer,56,Business travel,Business,3294,5,5,5,5,2,1,5,4,4,4,4,2,4,5,0,0.0,satisfied +14279,32503,Male,disloyal Customer,47,Business travel,Eco,102,1,4,1,2,3,1,3,3,1,1,1,3,4,3,2,14.0,neutral or dissatisfied +14280,127759,Female,Loyal Customer,15,Personal Travel,Eco,601,2,5,2,1,1,2,1,1,1,2,1,2,3,1,0,1.0,neutral or dissatisfied +14281,72007,Male,Loyal Customer,44,Business travel,Eco Plus,1037,2,3,3,3,2,2,2,2,1,1,4,2,3,2,7,21.0,neutral or dissatisfied +14282,60639,Female,Loyal Customer,35,Business travel,Business,1620,1,1,5,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +14283,83989,Male,Loyal Customer,54,Business travel,Eco,373,4,2,2,2,4,4,4,4,1,4,2,2,3,4,0,0.0,neutral or dissatisfied +14284,32816,Male,disloyal Customer,18,Business travel,Eco,101,1,0,1,3,2,1,3,2,2,2,5,5,1,2,0,0.0,neutral or dissatisfied +14285,83227,Male,Loyal Customer,49,Business travel,Business,1979,4,4,5,4,4,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +14286,19129,Female,Loyal Customer,26,Personal Travel,Eco,323,1,4,1,2,4,1,4,4,3,5,2,3,2,4,15,0.0,neutral or dissatisfied +14287,85166,Male,Loyal Customer,40,Business travel,Business,3186,5,5,5,5,3,4,5,5,5,5,5,4,5,4,22,7.0,satisfied +14288,73769,Female,Loyal Customer,26,Personal Travel,Eco,192,2,4,2,2,3,2,5,3,3,3,4,3,4,3,4,1.0,neutral or dissatisfied +14289,47295,Male,disloyal Customer,23,Business travel,Eco,532,4,0,4,4,5,4,5,5,4,5,5,4,2,5,0,0.0,satisfied +14290,75559,Male,Loyal Customer,46,Business travel,Business,3425,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,6.0,satisfied +14291,89242,Female,Loyal Customer,41,Personal Travel,Eco Plus,1947,4,4,4,1,5,5,4,2,2,4,2,3,2,5,84,85.0,neutral or dissatisfied +14292,33708,Female,Loyal Customer,42,Business travel,Eco,805,4,4,4,4,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +14293,127563,Female,Loyal Customer,32,Business travel,Business,1670,5,5,5,5,2,2,2,2,4,2,5,3,4,2,34,18.0,satisfied +14294,101674,Male,Loyal Customer,34,Personal Travel,Eco,2106,4,2,4,4,2,4,2,2,4,1,3,4,4,2,4,0.0,satisfied +14295,104323,Female,Loyal Customer,41,Business travel,Business,1902,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +14296,50270,Female,Loyal Customer,42,Business travel,Eco,266,2,4,4,4,1,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +14297,111292,Female,Loyal Customer,52,Personal Travel,Eco Plus,459,2,4,2,5,5,4,4,2,2,2,2,5,2,3,1,0.0,neutral or dissatisfied +14298,6468,Male,Loyal Customer,73,Business travel,Eco Plus,296,5,5,3,5,5,5,5,5,2,1,3,1,1,5,0,0.0,satisfied +14299,9346,Male,Loyal Customer,40,Business travel,Business,441,5,5,5,5,4,5,5,3,3,3,3,3,3,5,0,30.0,satisfied +14300,9093,Female,disloyal Customer,26,Business travel,Business,160,3,0,3,5,1,3,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +14301,84022,Female,Loyal Customer,24,Personal Travel,Eco,321,3,2,3,4,4,3,4,4,1,2,4,3,4,4,10,,neutral or dissatisfied +14302,90595,Male,Loyal Customer,33,Business travel,Business,581,1,1,1,1,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +14303,13396,Female,Loyal Customer,60,Personal Travel,Eco,505,2,4,2,4,4,5,5,4,4,2,4,3,4,3,121,114.0,neutral or dissatisfied +14304,119712,Male,Loyal Customer,28,Business travel,Business,2530,3,3,3,3,2,2,2,2,5,3,4,3,4,2,79,70.0,satisfied +14305,5032,Male,Loyal Customer,43,Business travel,Business,1951,2,2,2,2,2,5,5,4,4,5,4,3,4,4,2,0.0,satisfied +14306,73409,Female,Loyal Customer,61,Business travel,Business,3861,3,3,3,3,5,2,5,5,5,5,5,1,5,4,42,45.0,satisfied +14307,127397,Female,disloyal Customer,22,Business travel,Eco,868,3,3,3,3,4,3,2,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +14308,128988,Male,Loyal Customer,58,Personal Travel,Eco,236,3,4,3,2,3,3,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +14309,76289,Male,Loyal Customer,42,Business travel,Business,2677,1,5,5,5,1,1,1,1,1,4,3,1,2,1,0,0.0,neutral or dissatisfied +14310,94616,Male,disloyal Customer,18,Business travel,Eco,323,1,1,1,3,2,1,3,2,4,5,4,1,4,2,7,6.0,neutral or dissatisfied +14311,57275,Male,Loyal Customer,44,Personal Travel,Eco,804,1,2,1,3,1,1,1,1,3,3,4,4,4,1,3,0.0,neutral or dissatisfied +14312,29545,Male,Loyal Customer,58,Personal Travel,Business,1448,3,4,3,3,5,3,4,3,3,3,5,3,3,3,0,0.0,neutral or dissatisfied +14313,73320,Female,disloyal Customer,37,Business travel,Business,1012,1,1,1,2,3,1,3,3,3,2,5,5,5,3,0,7.0,neutral or dissatisfied +14314,55026,Female,disloyal Customer,23,Business travel,Eco,1303,3,3,3,3,4,3,1,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +14315,8660,Female,disloyal Customer,40,Business travel,Business,304,1,1,1,2,2,1,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +14316,123706,Female,Loyal Customer,29,Personal Travel,Eco,214,1,5,0,2,3,0,3,3,2,2,2,4,1,3,0,0.0,neutral or dissatisfied +14317,91176,Male,Loyal Customer,21,Personal Travel,Eco,404,1,5,1,3,3,1,3,3,4,3,4,4,4,3,88,94.0,neutral or dissatisfied +14318,40048,Female,disloyal Customer,28,Business travel,Eco,866,3,3,3,2,3,3,3,3,3,3,2,1,2,3,15,7.0,neutral or dissatisfied +14319,44498,Male,disloyal Customer,47,Business travel,Eco,411,2,1,3,4,4,3,2,4,3,5,4,2,3,4,0,0.0,neutral or dissatisfied +14320,11241,Male,Loyal Customer,36,Personal Travel,Eco,166,4,4,4,5,2,4,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +14321,47701,Male,Loyal Customer,67,Personal Travel,Eco,1482,1,4,1,4,2,1,2,2,2,1,1,4,2,2,103,92.0,neutral or dissatisfied +14322,71922,Male,Loyal Customer,52,Business travel,Business,1723,2,2,2,2,4,4,4,5,4,4,4,4,5,4,175,185.0,satisfied +14323,95119,Female,Loyal Customer,43,Personal Travel,Eco,677,4,4,3,4,1,4,3,5,5,3,5,2,5,4,0,0.0,satisfied +14324,83966,Female,Loyal Customer,50,Business travel,Business,3056,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,10.0,satisfied +14325,37238,Male,Loyal Customer,9,Personal Travel,Business,972,5,4,5,3,3,5,1,3,3,5,4,5,5,3,0,0.0,satisfied +14326,89655,Male,Loyal Customer,62,Business travel,Business,2107,3,1,3,3,2,4,3,3,3,3,3,4,3,4,0,8.0,neutral or dissatisfied +14327,25612,Female,Loyal Customer,29,Business travel,Business,526,1,3,3,3,1,1,1,1,1,4,1,1,3,1,0,0.0,neutral or dissatisfied +14328,17398,Male,disloyal Customer,25,Business travel,Business,351,2,5,2,3,4,2,4,4,2,1,4,3,3,4,13,22.0,neutral or dissatisfied +14329,45020,Female,Loyal Customer,62,Personal Travel,Eco,224,2,4,2,4,4,5,3,5,5,2,3,4,5,3,0,0.0,neutral or dissatisfied +14330,11593,Male,Loyal Customer,52,Business travel,Eco,771,4,4,4,4,4,4,4,4,1,4,3,2,3,4,50,27.0,neutral or dissatisfied +14331,108554,Male,disloyal Customer,23,Business travel,Eco,735,3,3,3,3,3,1,1,3,3,4,5,1,5,1,339,319.0,neutral or dissatisfied +14332,102090,Male,Loyal Customer,59,Business travel,Business,226,1,1,1,1,2,5,5,5,5,4,5,4,5,5,9,6.0,satisfied +14333,92853,Female,Loyal Customer,27,Personal Travel,Eco Plus,1587,3,1,3,2,1,3,1,1,2,2,3,1,3,1,0,1.0,neutral or dissatisfied +14334,25505,Male,Loyal Customer,24,Business travel,Business,3780,1,4,4,4,1,1,1,1,3,1,2,2,2,1,1,1.0,neutral or dissatisfied +14335,2697,Female,Loyal Customer,35,Business travel,Business,3540,2,2,2,2,4,5,4,5,5,5,5,3,5,3,8,2.0,satisfied +14336,16642,Male,Loyal Customer,49,Business travel,Eco,488,4,4,4,4,4,4,4,4,3,2,5,3,4,4,52,60.0,satisfied +14337,60254,Female,Loyal Customer,56,Personal Travel,Eco,1506,3,2,3,4,1,3,4,5,5,3,5,1,5,2,0,0.0,neutral or dissatisfied +14338,86211,Female,disloyal Customer,39,Business travel,Business,377,4,4,4,3,3,4,3,3,4,5,4,1,4,3,34,33.0,neutral or dissatisfied +14339,42550,Female,Loyal Customer,68,Personal Travel,Eco,1091,1,3,1,3,4,3,3,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +14340,320,Female,disloyal Customer,21,Business travel,Business,853,2,1,3,3,3,3,3,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +14341,73269,Male,disloyal Customer,27,Business travel,Business,1144,1,1,1,4,3,1,3,3,4,3,4,5,4,3,25,16.0,neutral or dissatisfied +14342,91227,Male,Loyal Customer,27,Personal Travel,Eco,545,2,2,2,3,3,2,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +14343,41690,Male,Loyal Customer,24,Personal Travel,Eco,936,2,4,2,1,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +14344,26464,Male,Loyal Customer,38,Personal Travel,Eco,925,4,4,4,2,5,4,5,5,5,3,4,5,4,5,0,0.0,satisfied +14345,107867,Male,Loyal Customer,56,Business travel,Business,228,1,1,1,1,1,2,4,5,5,5,5,1,5,2,13,16.0,satisfied +14346,16,Male,Loyal Customer,70,Personal Travel,Eco,821,2,5,2,1,5,2,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +14347,26692,Male,Loyal Customer,21,Personal Travel,Eco,404,2,5,2,3,4,2,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +14348,29910,Female,Loyal Customer,45,Business travel,Business,2633,4,4,4,4,2,1,1,4,4,4,4,1,4,3,1,0.0,satisfied +14349,27470,Female,Loyal Customer,49,Business travel,Business,954,3,5,5,5,1,2,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +14350,104275,Male,Loyal Customer,57,Business travel,Eco,1749,2,5,5,5,2,2,2,2,2,2,1,4,3,2,0,1.0,neutral or dissatisfied +14351,122599,Male,Loyal Customer,28,Business travel,Eco,728,2,1,1,1,2,2,2,2,4,3,1,3,1,2,0,0.0,neutral or dissatisfied +14352,46052,Female,Loyal Customer,64,Personal Travel,Eco,898,3,5,3,4,2,4,5,2,2,3,2,1,2,5,13,8.0,neutral or dissatisfied +14353,48242,Female,Loyal Customer,26,Personal Travel,Eco,236,1,4,1,4,3,1,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +14354,72901,Female,Loyal Customer,33,Business travel,Business,2505,2,2,2,2,2,4,4,4,4,4,4,4,4,4,0,4.0,satisfied +14355,2478,Male,Loyal Customer,39,Business travel,Business,1379,2,2,2,2,4,4,5,4,4,5,4,3,4,3,109,99.0,satisfied +14356,105641,Female,disloyal Customer,39,Business travel,Business,925,2,3,3,3,1,3,1,1,5,3,4,3,4,1,14,12.0,satisfied +14357,96620,Female,disloyal Customer,11,Business travel,Eco,972,1,1,1,4,2,1,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +14358,79919,Male,Loyal Customer,59,Business travel,Eco,1096,3,4,4,4,3,3,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +14359,42199,Male,disloyal Customer,35,Business travel,Eco,315,2,0,3,3,2,3,4,2,1,4,2,1,3,2,0,0.0,neutral or dissatisfied +14360,16308,Female,disloyal Customer,25,Business travel,Eco,628,4,0,4,2,5,4,5,5,1,5,2,5,4,5,1,41.0,neutral or dissatisfied +14361,87166,Male,Loyal Customer,47,Business travel,Business,3182,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +14362,31724,Male,Loyal Customer,15,Personal Travel,Eco,853,3,5,3,2,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +14363,16956,Male,Loyal Customer,58,Business travel,Eco,1131,5,4,4,4,5,5,5,5,2,4,1,3,3,5,29,20.0,satisfied +14364,71253,Male,disloyal Customer,17,Business travel,Eco,733,4,4,4,3,4,4,4,4,5,1,2,1,5,4,1,0.0,satisfied +14365,103561,Male,Loyal Customer,53,Business travel,Business,738,3,3,3,3,3,4,5,4,4,5,4,3,4,5,24,22.0,satisfied +14366,122802,Male,disloyal Customer,23,Business travel,Business,599,5,4,5,3,4,5,4,4,4,2,4,5,4,4,2,0.0,satisfied +14367,9603,Male,Loyal Customer,27,Personal Travel,Eco,288,0,5,0,3,2,0,2,2,3,2,4,5,4,2,16,0.0,satisfied +14368,57313,Male,Loyal Customer,52,Business travel,Business,3492,2,2,2,2,3,4,5,4,4,4,4,4,4,4,63,51.0,satisfied +14369,42976,Male,Loyal Customer,51,Business travel,Business,236,4,4,4,4,2,4,2,4,4,5,4,5,4,4,63,67.0,satisfied +14370,5304,Male,Loyal Customer,16,Personal Travel,Eco,383,3,4,3,4,4,3,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +14371,98109,Male,disloyal Customer,25,Business travel,Business,472,4,1,4,5,2,4,5,2,4,4,4,3,5,2,0,1.0,satisfied +14372,5386,Male,Loyal Customer,21,Personal Travel,Eco,812,3,3,3,2,3,3,3,3,4,2,2,4,2,3,0,0.0,neutral or dissatisfied +14373,118102,Male,disloyal Customer,50,Business travel,Eco,1999,1,2,2,3,2,1,2,2,2,5,2,1,4,2,29,33.0,neutral or dissatisfied +14374,52242,Female,disloyal Customer,20,Business travel,Eco,237,3,4,3,3,2,3,2,2,5,4,2,3,2,2,0,0.0,neutral or dissatisfied +14375,63186,Male,Loyal Customer,57,Business travel,Business,2973,5,5,5,5,5,4,5,4,4,4,4,5,4,5,0,2.0,satisfied +14376,48464,Female,disloyal Customer,17,Business travel,Eco,853,5,5,5,3,1,5,1,1,5,5,2,3,3,1,108,114.0,satisfied +14377,2157,Female,Loyal Customer,42,Business travel,Business,2393,1,1,3,1,3,5,4,4,4,4,4,5,4,5,0,21.0,satisfied +14378,85728,Male,disloyal Customer,37,Business travel,Business,666,3,3,3,4,3,3,4,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +14379,104884,Male,Loyal Customer,33,Personal Travel,Eco,327,5,0,5,4,4,5,4,4,5,5,4,3,4,4,3,0.0,satisfied +14380,68968,Female,Loyal Customer,45,Business travel,Business,3869,1,1,1,1,4,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +14381,40810,Female,Loyal Customer,41,Business travel,Business,1872,3,5,5,5,2,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +14382,18789,Male,Loyal Customer,24,Business travel,Eco,503,5,1,5,5,5,5,5,5,4,3,3,3,4,5,0,0.0,satisfied +14383,94428,Male,Loyal Customer,40,Business travel,Business,239,2,4,2,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +14384,32955,Male,Loyal Customer,13,Personal Travel,Eco,101,3,4,3,5,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +14385,14552,Male,Loyal Customer,56,Personal Travel,Eco,362,3,5,3,3,5,3,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +14386,89362,Male,Loyal Customer,16,Personal Travel,Eco,1587,3,2,3,3,4,3,4,4,4,1,4,3,4,4,8,0.0,neutral or dissatisfied +14387,52382,Female,Loyal Customer,41,Personal Travel,Eco,370,5,5,5,3,1,5,1,1,5,4,5,2,5,1,0,0.0,satisfied +14388,51497,Female,Loyal Customer,58,Personal Travel,Business,451,1,4,1,3,4,3,3,1,1,1,1,1,1,2,0,3.0,neutral or dissatisfied +14389,115105,Female,Loyal Customer,36,Business travel,Business,358,4,4,4,4,4,4,4,5,5,5,5,3,5,5,4,2.0,satisfied +14390,92905,Male,Loyal Customer,48,Business travel,Business,2897,5,5,5,5,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +14391,38418,Male,Loyal Customer,59,Business travel,Eco,965,3,4,5,5,3,3,3,3,1,3,4,4,4,3,0,5.0,neutral or dissatisfied +14392,93012,Female,Loyal Customer,52,Business travel,Eco,1524,3,4,4,4,3,4,4,3,3,3,3,3,3,3,2,0.0,neutral or dissatisfied +14393,111130,Female,Loyal Customer,46,Business travel,Business,3145,1,1,3,1,5,5,4,5,5,5,5,4,5,4,45,24.0,satisfied +14394,92481,Female,Loyal Customer,47,Business travel,Eco,1919,1,3,3,3,5,2,4,1,1,1,1,2,1,4,0,27.0,neutral or dissatisfied +14395,26373,Male,disloyal Customer,56,Business travel,Eco,494,2,2,2,3,2,3,3,1,2,4,3,3,4,3,168,162.0,neutral or dissatisfied +14396,75837,Male,Loyal Customer,40,Business travel,Business,1440,1,5,2,5,1,3,3,1,1,1,1,3,1,4,0,11.0,neutral or dissatisfied +14397,33504,Male,Loyal Customer,37,Personal Travel,Eco,965,3,5,3,2,2,3,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +14398,53366,Male,Loyal Customer,47,Business travel,Business,1452,3,1,5,1,1,4,3,3,3,3,3,4,3,1,33,60.0,neutral or dissatisfied +14399,87278,Male,Loyal Customer,53,Business travel,Business,577,5,5,5,5,2,5,4,4,4,5,4,4,4,4,2,0.0,satisfied +14400,31368,Female,Loyal Customer,36,Business travel,Business,3500,5,5,3,5,4,3,3,5,5,5,5,4,5,5,0,0.0,satisfied +14401,12383,Male,Loyal Customer,57,Business travel,Business,2721,3,4,4,4,2,3,4,4,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +14402,11273,Female,Loyal Customer,32,Personal Travel,Eco,667,3,5,3,4,1,3,1,1,4,4,3,5,4,1,1,0.0,neutral or dissatisfied +14403,86350,Female,disloyal Customer,22,Business travel,Eco,762,0,0,0,1,5,0,5,5,5,5,5,3,4,5,19,0.0,satisfied +14404,46566,Male,disloyal Customer,25,Business travel,Eco,125,2,3,3,4,1,3,1,1,4,2,4,5,1,1,0,0.0,neutral or dissatisfied +14405,124745,Male,disloyal Customer,26,Business travel,Business,280,3,4,3,4,4,3,1,4,5,3,4,3,5,4,36,29.0,neutral or dissatisfied +14406,67896,Male,Loyal Customer,63,Personal Travel,Eco,1171,4,4,4,3,5,4,5,5,2,1,3,4,3,5,0,0.0,neutral or dissatisfied +14407,14220,Male,Loyal Customer,16,Personal Travel,Eco,620,4,4,4,4,4,4,4,4,1,5,4,3,3,4,1,0.0,satisfied +14408,12450,Male,Loyal Customer,16,Personal Travel,Eco,262,1,2,1,3,3,1,3,3,1,1,4,2,3,3,0,0.0,neutral or dissatisfied +14409,94766,Male,disloyal Customer,40,Business travel,Eco,248,3,1,3,2,1,3,1,1,4,3,2,3,2,1,17,12.0,neutral or dissatisfied +14410,64548,Male,Loyal Customer,44,Business travel,Business,2941,5,5,5,5,5,4,5,5,5,5,5,4,5,3,5,0.0,satisfied +14411,38411,Male,Loyal Customer,59,Business travel,Eco,965,4,4,1,4,4,4,4,4,1,2,1,1,5,4,0,0.0,satisfied +14412,28570,Male,disloyal Customer,29,Business travel,Eco,2603,2,2,2,4,2,2,2,2,3,2,5,2,5,2,0,19.0,neutral or dissatisfied +14413,40649,Female,disloyal Customer,22,Business travel,Business,584,5,0,5,4,2,5,3,2,4,5,4,4,5,2,0,0.0,satisfied +14414,125306,Male,Loyal Customer,51,Personal Travel,Eco,678,2,4,3,4,5,3,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +14415,44287,Female,Loyal Customer,37,Personal Travel,Business,1123,1,4,1,1,4,4,4,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +14416,27952,Male,disloyal Customer,22,Business travel,Eco,1770,2,2,2,3,4,2,4,4,4,5,5,1,5,4,0,0.0,satisfied +14417,114999,Female,disloyal Customer,26,Business travel,Business,337,4,5,4,1,5,4,5,5,5,2,5,3,4,5,112,109.0,neutral or dissatisfied +14418,11093,Male,Loyal Customer,47,Personal Travel,Eco,229,1,5,1,1,5,1,5,5,3,4,4,4,5,5,0,5.0,neutral or dissatisfied +14419,62637,Female,Loyal Customer,18,Personal Travel,Eco,1744,2,1,2,4,3,2,3,3,1,2,4,4,3,3,58,48.0,neutral or dissatisfied +14420,109565,Female,Loyal Customer,20,Personal Travel,Eco,992,4,4,4,4,3,4,3,3,3,2,3,1,4,3,20,14.0,neutral or dissatisfied +14421,41242,Female,disloyal Customer,16,Business travel,Eco,643,4,4,4,3,4,4,1,4,1,3,3,4,3,4,1,0.0,neutral or dissatisfied +14422,101488,Female,Loyal Customer,41,Business travel,Business,2964,2,2,2,2,2,5,4,4,4,4,4,5,4,5,17,13.0,satisfied +14423,69380,Female,disloyal Customer,13,Business travel,Eco,1096,3,3,3,4,3,3,3,3,2,4,3,1,3,3,0,4.0,neutral or dissatisfied +14424,101249,Female,Loyal Customer,53,Personal Travel,Eco Plus,1587,2,5,2,2,3,5,4,5,5,2,5,5,5,3,50,34.0,neutral or dissatisfied +14425,119017,Female,Loyal Customer,14,Personal Travel,Business,1460,5,5,5,1,4,5,4,4,5,2,5,4,5,4,0,19.0,satisfied +14426,74064,Male,Loyal Customer,34,Business travel,Business,3301,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +14427,6289,Female,Loyal Customer,53,Personal Travel,Eco,693,1,4,1,2,2,5,5,4,4,1,4,4,4,4,0,2.0,neutral or dissatisfied +14428,36920,Male,Loyal Customer,14,Personal Travel,Eco,740,3,5,3,3,5,3,5,5,3,5,5,4,5,5,0,4.0,neutral or dissatisfied +14429,89821,Female,disloyal Customer,23,Business travel,Eco,1096,4,4,4,5,4,4,4,4,3,1,2,1,5,4,11,0.0,neutral or dissatisfied +14430,112409,Female,disloyal Customer,29,Business travel,Eco,862,1,1,1,2,4,1,4,4,3,2,2,4,2,4,1,0.0,neutral or dissatisfied +14431,119982,Female,Loyal Customer,50,Personal Travel,Eco,1009,3,4,3,1,5,3,3,3,3,3,3,5,3,1,0,0.0,neutral or dissatisfied +14432,44795,Female,Loyal Customer,59,Business travel,Eco Plus,1250,3,1,1,1,2,1,1,3,3,3,3,3,3,3,14,4.0,neutral or dissatisfied +14433,32137,Male,Loyal Customer,55,Business travel,Eco,163,5,5,5,5,5,5,5,5,2,5,5,3,4,5,0,0.0,satisfied +14434,24845,Female,Loyal Customer,60,Personal Travel,Eco,861,2,5,2,3,4,5,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +14435,77921,Male,disloyal Customer,38,Business travel,Business,152,1,1,1,3,1,1,1,1,2,2,3,2,4,1,0,0.0,neutral or dissatisfied +14436,78580,Female,Loyal Customer,53,Personal Travel,Eco,630,3,1,4,3,3,4,3,1,1,4,1,3,1,4,0,0.0,neutral or dissatisfied +14437,94475,Female,Loyal Customer,54,Business travel,Business,3127,3,3,3,3,3,4,4,4,4,4,4,5,4,4,27,20.0,satisfied +14438,79102,Female,Loyal Customer,57,Personal Travel,Eco,226,2,4,2,3,4,5,5,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +14439,14841,Female,Loyal Customer,57,Business travel,Business,240,0,0,0,1,4,4,4,4,4,4,4,4,4,4,65,100.0,satisfied +14440,124847,Female,Loyal Customer,38,Personal Travel,Eco,280,4,5,4,2,3,4,4,3,5,4,5,4,4,3,0,0.0,satisfied +14441,112331,Female,Loyal Customer,13,Personal Travel,Business,967,1,4,1,4,5,1,5,5,3,4,5,4,4,5,17,0.0,neutral or dissatisfied +14442,6280,Female,disloyal Customer,24,Business travel,Eco,585,3,2,3,4,3,3,3,3,4,3,3,2,3,3,33,26.0,neutral or dissatisfied +14443,65627,Male,Loyal Customer,60,Personal Travel,Eco,237,4,4,0,5,1,0,1,1,4,3,4,5,5,1,0,0.0,satisfied +14444,36810,Male,disloyal Customer,15,Business travel,Eco,976,2,2,2,4,5,2,5,5,1,3,2,2,4,5,6,0.0,neutral or dissatisfied +14445,88538,Male,Loyal Customer,49,Personal Travel,Eco,270,2,1,2,3,4,2,4,4,3,4,4,1,4,4,68,66.0,neutral or dissatisfied +14446,9621,Male,Loyal Customer,54,Business travel,Business,2234,2,2,2,2,2,4,4,5,5,5,5,4,5,4,19,16.0,satisfied +14447,46857,Female,Loyal Customer,42,Business travel,Business,1844,2,2,1,2,1,4,4,2,2,2,2,2,2,4,0,0.0,satisfied +14448,28271,Male,Loyal Customer,20,Business travel,Business,2402,1,1,1,1,4,4,4,4,3,4,1,4,4,4,0,0.0,satisfied +14449,19469,Male,disloyal Customer,20,Business travel,Eco,177,2,5,2,2,3,2,3,3,2,1,4,5,1,3,0,0.0,neutral or dissatisfied +14450,105343,Male,disloyal Customer,21,Business travel,Eco,409,2,1,2,4,5,2,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +14451,128191,Female,Loyal Customer,37,Personal Travel,Eco Plus,1849,2,4,2,3,2,2,2,2,4,1,1,4,2,2,28,8.0,neutral or dissatisfied +14452,44949,Male,Loyal Customer,37,Business travel,Eco,397,5,4,4,4,5,5,5,5,5,1,3,1,1,5,0,0.0,satisfied +14453,128321,Female,disloyal Customer,40,Business travel,Business,651,3,3,3,4,4,3,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +14454,12403,Male,disloyal Customer,30,Business travel,Eco,127,4,2,4,3,3,4,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +14455,84662,Male,Loyal Customer,30,Business travel,Business,2182,4,4,4,4,4,5,5,4,4,4,4,5,3,5,0,24.0,satisfied +14456,100355,Female,Loyal Customer,49,Personal Travel,Eco,1073,3,4,3,3,5,4,4,2,2,3,2,5,2,5,53,68.0,neutral or dissatisfied +14457,126464,Female,Loyal Customer,57,Business travel,Business,1788,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,12.0,satisfied +14458,119953,Female,Loyal Customer,47,Business travel,Business,1712,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,9.0,satisfied +14459,80533,Male,Loyal Customer,38,Personal Travel,Eco,1678,3,1,3,2,2,3,2,2,4,3,2,4,2,2,0,0.0,neutral or dissatisfied +14460,64179,Male,disloyal Customer,23,Business travel,Eco,1047,3,3,3,5,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +14461,114753,Male,Loyal Customer,41,Business travel,Business,3197,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +14462,47632,Male,Loyal Customer,27,Business travel,Business,2000,4,4,4,4,3,5,3,3,1,2,3,4,4,3,5,4.0,satisfied +14463,76021,Male,Loyal Customer,39,Business travel,Eco,237,4,2,2,2,4,4,4,4,2,1,4,4,4,4,30,32.0,neutral or dissatisfied +14464,966,Male,Loyal Customer,17,Business travel,Business,2079,2,2,2,2,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +14465,86271,Female,Loyal Customer,68,Personal Travel,Eco,226,3,4,0,5,4,5,4,4,4,0,5,5,4,5,16,11.0,neutral or dissatisfied +14466,75233,Female,Loyal Customer,62,Personal Travel,Eco,1726,2,4,2,1,2,3,4,1,1,2,1,3,1,4,61,60.0,neutral or dissatisfied +14467,111531,Female,Loyal Customer,37,Business travel,Business,2797,4,4,4,4,4,5,4,4,4,4,4,3,4,5,21,24.0,satisfied +14468,1189,Female,Loyal Customer,13,Personal Travel,Eco,354,4,3,4,4,1,4,1,1,1,5,3,2,3,1,2,7.0,neutral or dissatisfied +14469,113605,Female,Loyal Customer,47,Business travel,Eco,414,3,5,5,5,5,1,2,3,3,3,3,2,3,4,62,51.0,neutral or dissatisfied +14470,18600,Female,disloyal Customer,29,Business travel,Eco,262,1,0,1,1,2,1,2,2,4,4,5,5,4,2,11,1.0,neutral or dissatisfied +14471,113628,Female,Loyal Customer,49,Personal Travel,Eco,236,3,2,3,4,2,3,4,2,2,3,2,2,2,4,15,5.0,neutral or dissatisfied +14472,114562,Female,Loyal Customer,46,Personal Travel,Business,373,2,0,2,2,1,2,3,4,4,2,4,1,4,4,15,15.0,neutral or dissatisfied +14473,84951,Female,Loyal Customer,49,Business travel,Business,481,3,3,3,3,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +14474,56080,Male,Loyal Customer,30,Personal Travel,Eco,2586,3,3,3,2,3,2,2,5,5,4,1,2,3,2,13,16.0,neutral or dissatisfied +14475,103930,Female,Loyal Customer,43,Business travel,Business,3216,2,2,2,2,2,4,4,4,4,5,4,5,4,3,11,4.0,satisfied +14476,127385,Male,Loyal Customer,51,Business travel,Business,1821,3,3,3,3,4,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +14477,27846,Female,Loyal Customer,70,Personal Travel,Eco,909,2,2,2,2,2,2,2,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +14478,84934,Male,Loyal Customer,69,Personal Travel,Eco,516,2,1,2,4,4,2,4,4,1,3,3,4,3,4,8,0.0,neutral or dissatisfied +14479,17514,Female,disloyal Customer,27,Business travel,Eco,241,3,0,3,2,3,3,2,3,5,2,1,1,3,3,0,0.0,neutral or dissatisfied +14480,44024,Male,disloyal Customer,35,Business travel,Eco,802,1,2,2,3,4,2,4,4,3,4,3,1,4,4,48,50.0,neutral or dissatisfied +14481,112106,Male,Loyal Customer,54,Personal Travel,Eco,1062,2,1,2,2,4,2,4,4,1,4,3,4,3,4,3,0.0,neutral or dissatisfied +14482,82592,Female,Loyal Customer,47,Business travel,Eco,528,3,4,5,4,5,2,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +14483,33069,Male,Loyal Customer,50,Personal Travel,Eco,216,2,0,2,5,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +14484,63344,Male,disloyal Customer,21,Business travel,Eco,447,2,2,2,2,3,2,2,3,4,2,1,4,2,3,18,11.0,neutral or dissatisfied +14485,80384,Female,Loyal Customer,43,Business travel,Eco,422,4,5,5,5,4,1,4,4,4,4,4,2,4,5,1,0.0,satisfied +14486,17195,Female,Loyal Customer,28,Personal Travel,Eco Plus,643,1,5,1,3,4,1,4,4,4,3,5,4,4,4,2,0.0,neutral or dissatisfied +14487,107666,Male,disloyal Customer,22,Business travel,Business,466,4,0,5,4,3,5,3,3,4,4,5,3,4,3,13,18.0,satisfied +14488,16195,Male,Loyal Customer,57,Personal Travel,Eco,212,3,2,3,1,2,3,2,2,3,2,2,3,1,2,0,0.0,neutral or dissatisfied +14489,73776,Male,Loyal Customer,42,Personal Travel,Eco,192,3,5,0,3,4,0,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +14490,43460,Male,Loyal Customer,22,Business travel,Business,2561,5,5,5,5,4,4,4,4,4,2,2,3,1,4,0,0.0,satisfied +14491,69644,Male,Loyal Customer,49,Business travel,Business,3187,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +14492,93705,Male,disloyal Customer,39,Business travel,Eco,689,4,4,4,3,4,4,4,4,4,5,3,1,2,4,0,0.0,neutral or dissatisfied +14493,19772,Male,Loyal Customer,59,Personal Travel,Business,578,4,4,4,2,2,5,5,1,1,4,1,5,1,3,20,21.0,neutral or dissatisfied +14494,4686,Male,Loyal Customer,58,Personal Travel,Eco,489,0,3,0,4,1,0,1,1,2,1,3,4,3,1,0,0.0,satisfied +14495,119640,Female,Loyal Customer,55,Business travel,Business,3714,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +14496,122707,Female,Loyal Customer,45,Business travel,Eco,813,2,1,1,1,1,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +14497,129776,Female,Loyal Customer,26,Personal Travel,Eco,421,2,2,2,4,3,2,3,3,3,2,4,1,4,3,125,126.0,neutral or dissatisfied +14498,57521,Female,Loyal Customer,47,Business travel,Business,3483,4,4,4,4,4,5,4,5,5,5,5,5,5,3,3,3.0,satisfied +14499,97241,Male,Loyal Customer,50,Business travel,Business,3858,0,0,0,1,2,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +14500,1601,Female,Loyal Customer,45,Personal Travel,Eco,140,3,5,3,2,2,2,3,4,4,3,4,4,4,4,31,24.0,neutral or dissatisfied +14501,90609,Male,Loyal Customer,54,Business travel,Business,3666,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,3.0,satisfied +14502,83605,Male,disloyal Customer,37,Business travel,Eco,409,2,4,2,3,4,2,4,4,3,5,3,1,3,4,0,0.0,neutral or dissatisfied +14503,45003,Female,Loyal Customer,35,Business travel,Eco,235,4,3,3,3,4,4,4,4,5,1,2,3,4,4,0,3.0,satisfied +14504,45074,Female,disloyal Customer,36,Business travel,Eco Plus,342,3,3,3,3,3,3,4,3,4,3,5,5,4,3,0,5.0,neutral or dissatisfied +14505,17277,Male,Loyal Customer,43,Business travel,Eco Plus,1092,2,3,3,3,2,2,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +14506,59511,Male,Loyal Customer,50,Business travel,Business,1815,3,3,3,3,4,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +14507,84609,Male,disloyal Customer,10,Business travel,Business,669,5,0,5,4,2,5,1,2,3,3,4,5,5,2,0,0.0,satisfied +14508,64964,Female,Loyal Customer,59,Business travel,Eco,190,4,4,3,3,2,4,1,4,4,4,4,5,4,2,0,0.0,satisfied +14509,99546,Male,disloyal Customer,23,Business travel,Business,829,5,0,5,2,1,5,3,1,4,2,5,5,4,1,0,1.0,satisfied +14510,111324,Female,Loyal Customer,51,Business travel,Eco,283,2,1,4,1,4,2,1,2,2,2,2,1,2,3,29,30.0,neutral or dissatisfied +14511,46810,Female,disloyal Customer,24,Business travel,Eco,844,4,4,4,3,5,4,2,5,3,2,3,3,1,5,39,50.0,satisfied +14512,38375,Male,Loyal Customer,21,Personal Travel,Eco,1180,3,5,3,1,3,3,3,3,3,4,5,5,4,3,0,26.0,neutral or dissatisfied +14513,15035,Female,Loyal Customer,45,Business travel,Business,3019,5,5,5,5,3,3,3,4,4,5,4,4,4,2,0,0.0,satisfied +14514,48750,Female,Loyal Customer,39,Business travel,Business,86,3,1,1,1,1,3,3,1,1,1,3,1,1,1,75,79.0,neutral or dissatisfied +14515,82877,Female,Loyal Customer,24,Business travel,Business,594,2,4,4,4,2,2,2,2,3,5,3,4,3,2,37,53.0,neutral or dissatisfied +14516,2149,Male,Loyal Customer,27,Business travel,Business,685,4,4,4,4,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +14517,90441,Female,disloyal Customer,23,Business travel,Business,240,0,0,0,4,1,0,1,1,3,5,5,3,4,1,0,11.0,satisfied +14518,31193,Female,disloyal Customer,33,Business travel,Eco,628,2,4,2,3,3,2,3,3,3,1,3,3,1,3,0,0.0,neutral or dissatisfied +14519,7161,Male,disloyal Customer,39,Business travel,Business,139,4,5,5,2,4,5,3,4,5,2,4,5,5,4,0,0.0,satisfied +14520,18827,Female,Loyal Customer,20,Business travel,Business,2652,1,1,1,1,4,4,4,4,2,4,3,1,4,4,0,0.0,satisfied +14521,68278,Female,Loyal Customer,50,Business travel,Eco Plus,432,3,3,1,3,3,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +14522,27032,Female,Loyal Customer,46,Business travel,Eco Plus,954,3,2,2,2,3,4,3,3,3,3,3,3,3,3,7,0.0,satisfied +14523,89804,Female,Loyal Customer,46,Business travel,Business,1792,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +14524,120339,Male,Loyal Customer,68,Business travel,Business,3534,1,1,1,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +14525,59577,Female,Loyal Customer,39,Business travel,Business,965,3,3,3,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +14526,126844,Male,Loyal Customer,31,Business travel,Eco,2296,1,5,5,5,1,1,1,1,2,4,4,3,4,1,9,2.0,neutral or dissatisfied +14527,43837,Male,disloyal Customer,33,Business travel,Eco,174,1,0,1,2,4,1,4,4,3,3,5,3,2,4,0,9.0,neutral or dissatisfied +14528,95642,Female,Loyal Customer,22,Personal Travel,Eco Plus,484,4,5,4,3,4,4,4,4,2,5,5,1,4,4,4,2.0,satisfied +14529,112852,Female,Loyal Customer,22,Business travel,Business,715,5,5,5,5,2,2,2,2,4,4,5,3,5,2,12,0.0,satisfied +14530,3679,Female,Loyal Customer,52,Business travel,Business,431,4,5,5,5,4,3,2,4,4,4,4,3,4,2,6,0.0,neutral or dissatisfied +14531,60419,Male,Loyal Customer,54,Business travel,Business,2913,4,4,4,4,4,4,4,4,4,4,4,4,4,4,26,9.0,satisfied +14532,114825,Female,Loyal Customer,54,Business travel,Business,342,1,1,1,1,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +14533,89422,Female,Loyal Customer,37,Business travel,Eco,151,1,4,4,4,1,2,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +14534,116831,Female,Loyal Customer,48,Business travel,Business,2848,4,4,4,4,2,5,4,5,5,5,5,3,5,5,20,26.0,satisfied +14535,50528,Male,Loyal Customer,39,Personal Travel,Eco,250,5,4,5,4,1,5,1,1,4,5,4,3,5,1,0,0.0,satisfied +14536,122406,Male,Loyal Customer,14,Personal Travel,Eco Plus,529,1,4,1,3,1,1,1,1,3,4,5,4,5,1,12,3.0,neutral or dissatisfied +14537,96616,Female,Loyal Customer,36,Business travel,Business,3058,2,5,2,2,5,4,5,4,4,4,4,3,4,4,0,1.0,satisfied +14538,85372,Male,disloyal Customer,35,Business travel,Business,332,3,3,3,5,5,3,2,5,3,3,5,3,4,5,30,23.0,neutral or dissatisfied +14539,52957,Female,Loyal Customer,42,Business travel,Business,2306,2,2,2,2,5,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +14540,70292,Female,Loyal Customer,43,Personal Travel,Eco,852,4,5,4,1,3,5,4,1,1,4,1,5,1,3,0,0.0,neutral or dissatisfied +14541,78266,Male,Loyal Customer,23,Personal Travel,Eco,903,2,4,2,3,2,2,2,2,5,5,2,3,4,2,7,0.0,neutral or dissatisfied +14542,108163,Female,Loyal Customer,60,Personal Travel,Eco,1105,1,4,1,3,5,3,1,2,2,1,2,4,2,3,20,0.0,neutral or dissatisfied +14543,366,Female,Loyal Customer,35,Business travel,Business,164,5,5,5,5,2,4,5,5,5,5,5,5,5,5,33,29.0,satisfied +14544,13765,Female,Loyal Customer,33,Business travel,Eco Plus,441,3,5,5,5,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +14545,27705,Male,Loyal Customer,29,Personal Travel,Eco Plus,1107,3,4,3,3,2,3,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +14546,59408,Male,Loyal Customer,46,Personal Travel,Eco,2367,3,5,3,2,4,3,3,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +14547,102587,Female,Loyal Customer,19,Business travel,Eco Plus,386,3,2,2,2,3,3,2,3,1,3,3,3,3,3,21,9.0,neutral or dissatisfied +14548,86239,Female,Loyal Customer,52,Personal Travel,Eco,306,0,1,0,3,5,4,3,3,3,0,3,4,3,4,0,0.0,satisfied +14549,61046,Female,Loyal Customer,55,Business travel,Business,1546,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +14550,11485,Male,Loyal Customer,49,Personal Travel,Eco Plus,429,4,5,4,1,1,4,1,1,4,5,1,3,1,1,0,3.0,neutral or dissatisfied +14551,21278,Male,disloyal Customer,25,Business travel,Eco,620,1,0,1,1,2,1,2,2,4,4,4,4,3,2,103,75.0,neutral or dissatisfied +14552,77905,Female,Loyal Customer,30,Personal Travel,Eco,456,0,2,0,3,3,0,3,3,3,1,4,3,4,3,3,0.0,satisfied +14553,7873,Male,Loyal Customer,40,Business travel,Business,2874,1,1,1,1,3,5,4,4,4,4,4,4,4,5,8,13.0,satisfied +14554,7714,Female,Loyal Customer,38,Business travel,Business,1870,5,5,5,5,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +14555,67478,Male,Loyal Customer,43,Personal Travel,Eco,592,1,3,1,1,3,1,3,3,1,3,1,4,5,3,2,0.0,neutral or dissatisfied +14556,125415,Female,Loyal Customer,47,Business travel,Business,735,2,2,2,2,4,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +14557,95808,Male,Loyal Customer,10,Personal Travel,Eco,920,1,4,2,3,2,2,2,2,1,2,3,4,3,2,7,0.0,neutral or dissatisfied +14558,78567,Female,Loyal Customer,40,Business travel,Business,630,1,1,1,1,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +14559,118645,Male,Loyal Customer,57,Business travel,Eco,304,1,3,3,3,1,1,1,1,3,2,2,1,2,1,23,38.0,neutral or dissatisfied +14560,74652,Female,Loyal Customer,40,Personal Travel,Eco,1438,4,4,4,4,5,4,4,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +14561,123924,Male,Loyal Customer,51,Personal Travel,Eco,544,4,4,4,4,4,4,4,4,3,3,5,3,1,4,53,31.0,neutral or dissatisfied +14562,114593,Female,Loyal Customer,59,Business travel,Business,333,3,5,5,5,1,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +14563,76553,Male,Loyal Customer,18,Business travel,Business,3602,2,2,2,2,2,2,2,2,5,2,5,4,4,2,0,0.0,satisfied +14564,128164,Female,Loyal Customer,18,Business travel,Eco,1849,1,5,5,5,1,2,3,1,4,2,3,4,4,1,3,0.0,neutral or dissatisfied +14565,59812,Male,disloyal Customer,31,Business travel,Business,937,1,1,1,3,5,1,5,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +14566,67597,Female,Loyal Customer,42,Business travel,Eco,1464,1,4,4,4,4,3,4,1,1,1,1,1,1,4,0,2.0,neutral or dissatisfied +14567,97103,Female,Loyal Customer,43,Business travel,Business,1521,2,5,5,5,1,3,4,2,2,2,2,3,2,4,4,0.0,neutral or dissatisfied +14568,116608,Female,Loyal Customer,25,Business travel,Business,447,2,2,2,2,4,4,4,4,5,4,4,4,5,4,19,14.0,satisfied +14569,50103,Female,Loyal Customer,39,Business travel,Eco,373,5,1,1,1,5,5,5,5,4,2,1,3,4,5,0,0.0,satisfied +14570,28432,Male,Loyal Customer,41,Business travel,Business,2496,1,1,1,1,5,4,4,4,1,3,3,4,3,4,10,0.0,satisfied +14571,58857,Female,Loyal Customer,32,Business travel,Business,888,3,2,3,3,4,4,4,4,3,3,4,4,4,4,23,1.0,satisfied +14572,82070,Male,disloyal Customer,44,Business travel,Business,1276,1,1,1,2,3,1,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +14573,1758,Female,Loyal Customer,48,Business travel,Eco Plus,327,3,3,3,3,3,1,2,3,3,3,3,3,3,3,32,31.0,neutral or dissatisfied +14574,9887,Male,Loyal Customer,32,Business travel,Business,508,3,5,3,3,4,4,4,4,5,2,4,4,5,4,0,0.0,satisfied +14575,68127,Male,Loyal Customer,34,Personal Travel,Eco,868,3,3,3,2,1,3,1,1,3,2,3,2,2,1,0,0.0,neutral or dissatisfied +14576,58746,Female,Loyal Customer,56,Business travel,Business,3185,2,2,2,2,2,5,5,3,3,4,3,3,3,5,3,0.0,satisfied +14577,15882,Male,Loyal Customer,19,Personal Travel,Eco,489,2,0,4,2,1,4,3,1,5,2,4,5,5,1,2,0.0,neutral or dissatisfied +14578,29998,Female,disloyal Customer,23,Business travel,Eco,261,3,1,3,4,1,3,1,1,3,2,3,2,3,1,28,33.0,neutral or dissatisfied +14579,14891,Male,Loyal Customer,49,Business travel,Business,296,4,4,4,4,4,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +14580,90019,Male,Loyal Customer,57,Business travel,Business,1127,4,4,2,4,4,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +14581,6721,Male,Loyal Customer,53,Personal Travel,Eco,258,3,4,3,3,3,3,3,3,3,5,3,3,4,3,18,16.0,neutral or dissatisfied +14582,9622,Male,Loyal Customer,41,Business travel,Business,3602,0,0,0,1,2,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +14583,51305,Male,Loyal Customer,25,Business travel,Eco Plus,373,2,4,1,4,2,2,1,2,3,2,4,2,4,2,0,5.0,neutral or dissatisfied +14584,26098,Male,Loyal Customer,18,Personal Travel,Eco,591,2,5,2,3,3,2,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +14585,118832,Female,Loyal Customer,62,Business travel,Eco Plus,369,3,1,1,1,3,3,3,3,3,3,3,1,3,4,15,10.0,neutral or dissatisfied +14586,94395,Female,disloyal Customer,24,Business travel,Business,458,5,0,5,4,5,5,5,5,5,3,4,5,4,5,6,4.0,satisfied +14587,59707,Female,Loyal Customer,7,Personal Travel,Eco,787,2,5,2,3,4,2,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +14588,109810,Male,Loyal Customer,57,Business travel,Business,3641,2,1,2,2,2,5,5,4,4,4,4,4,4,4,69,64.0,satisfied +14589,61406,Female,Loyal Customer,7,Personal Travel,Eco,679,2,4,2,1,4,2,1,4,3,5,5,2,5,4,16,8.0,neutral or dissatisfied +14590,123960,Male,Loyal Customer,33,Personal Travel,Business,184,3,4,3,3,1,3,1,1,3,2,4,4,3,1,11,13.0,neutral or dissatisfied +14591,91623,Male,Loyal Customer,58,Business travel,Business,1199,4,4,4,4,3,3,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +14592,125472,Male,Loyal Customer,11,Personal Travel,Eco,2845,2,5,2,1,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +14593,80789,Female,disloyal Customer,27,Business travel,Eco,484,2,4,2,4,2,2,2,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +14594,53498,Male,Loyal Customer,33,Personal Travel,Eco,2253,3,5,2,3,2,4,2,3,4,5,5,2,4,2,0,8.0,neutral or dissatisfied +14595,83472,Male,Loyal Customer,26,Business travel,Business,1900,3,4,4,4,3,3,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +14596,40890,Male,Loyal Customer,43,Personal Travel,Eco,501,2,5,2,5,3,2,3,3,4,1,3,3,5,3,9,17.0,neutral or dissatisfied +14597,98452,Female,Loyal Customer,35,Business travel,Business,2031,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +14598,3555,Male,Loyal Customer,43,Business travel,Business,2136,0,0,0,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +14599,238,Female,Loyal Customer,39,Business travel,Business,719,2,2,3,2,3,5,5,5,5,5,5,3,5,3,82,89.0,satisfied +14600,105300,Male,disloyal Customer,10,Business travel,Eco,967,3,2,2,3,5,2,2,5,3,1,3,3,3,5,29,26.0,neutral or dissatisfied +14601,50791,Male,Loyal Customer,48,Personal Travel,Eco,86,1,3,1,3,4,1,4,4,3,2,3,2,4,4,0,4.0,neutral or dissatisfied +14602,22406,Female,Loyal Customer,57,Business travel,Eco,143,4,2,2,2,2,1,4,3,3,4,3,3,3,3,0,0.0,satisfied +14603,23581,Male,Loyal Customer,47,Personal Travel,Eco,792,1,5,1,2,4,1,3,4,4,4,4,3,4,4,0,8.0,neutral or dissatisfied +14604,105915,Male,Loyal Customer,26,Personal Travel,Eco,283,2,5,2,2,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +14605,61207,Female,Loyal Customer,54,Business travel,Business,2518,4,4,4,4,4,4,5,5,5,4,5,5,5,4,25,44.0,satisfied +14606,76465,Male,Loyal Customer,36,Personal Travel,Business,547,1,4,1,3,5,3,4,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +14607,26706,Male,Loyal Customer,12,Personal Travel,Eco,515,2,4,2,5,5,2,5,5,1,2,5,4,5,5,0,0.0,neutral or dissatisfied +14608,126402,Female,Loyal Customer,46,Business travel,Business,328,0,0,0,1,5,5,5,2,2,2,2,5,2,4,0,10.0,satisfied +14609,122946,Female,Loyal Customer,41,Business travel,Business,507,3,3,3,3,3,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +14610,105256,Male,Loyal Customer,47,Business travel,Business,2106,3,3,3,3,4,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +14611,47478,Male,Loyal Customer,13,Personal Travel,Eco,532,2,4,2,4,3,2,2,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +14612,66312,Male,Loyal Customer,32,Business travel,Eco,852,4,2,2,2,4,4,4,4,3,4,3,5,5,4,40,29.0,satisfied +14613,67774,Female,Loyal Customer,35,Business travel,Eco,1242,3,1,1,1,3,3,3,3,2,1,1,1,1,3,0,0.0,neutral or dissatisfied +14614,35657,Female,disloyal Customer,29,Business travel,Eco,778,1,1,1,3,1,1,1,5,2,3,5,1,1,1,103,120.0,neutral or dissatisfied +14615,1423,Male,Loyal Customer,60,Business travel,Business,102,0,4,0,4,4,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +14616,70378,Female,Loyal Customer,60,Business travel,Business,1562,2,4,4,4,4,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +14617,16814,Male,disloyal Customer,18,Business travel,Eco,645,4,0,4,3,5,4,3,5,4,1,5,1,5,5,0,1.0,satisfied +14618,105293,Female,Loyal Customer,54,Business travel,Business,738,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +14619,72384,Male,disloyal Customer,32,Business travel,Business,929,2,2,2,5,1,2,1,1,3,4,5,5,4,1,1,9.0,neutral or dissatisfied +14620,4453,Female,Loyal Customer,18,Personal Travel,Eco Plus,762,3,3,3,3,5,3,5,5,3,2,2,4,3,5,0,8.0,neutral or dissatisfied +14621,30075,Male,Loyal Customer,27,Personal Travel,Eco,548,5,3,5,4,2,5,2,2,3,1,3,4,3,2,0,5.0,satisfied +14622,92345,Female,Loyal Customer,24,Business travel,Business,2556,3,5,5,5,3,3,3,3,4,4,1,1,1,3,0,0.0,neutral or dissatisfied +14623,49447,Female,Loyal Customer,35,Business travel,Eco,109,2,5,5,5,2,2,2,2,2,5,3,4,4,2,0,0.0,satisfied +14624,11163,Male,Loyal Customer,9,Personal Travel,Eco,224,4,5,0,3,3,0,3,3,5,2,5,4,5,3,62,68.0,neutral or dissatisfied +14625,20386,Female,Loyal Customer,46,Business travel,Eco,588,5,5,5,5,1,1,2,5,5,5,5,2,5,5,0,0.0,satisfied +14626,55660,Female,Loyal Customer,16,Personal Travel,Eco Plus,315,4,4,4,1,5,4,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +14627,35438,Female,Loyal Customer,43,Personal Travel,Eco,1056,2,4,2,3,4,4,5,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +14628,65333,Female,Loyal Customer,28,Business travel,Business,2627,5,5,5,5,2,2,2,2,4,5,4,5,5,2,6,10.0,satisfied +14629,92808,Female,Loyal Customer,51,Business travel,Business,1587,2,2,2,2,2,4,5,5,5,5,5,3,5,5,1,44.0,satisfied +14630,10048,Female,disloyal Customer,34,Business travel,Business,326,3,3,3,5,2,3,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +14631,65982,Male,Loyal Customer,32,Personal Travel,Eco,1372,1,5,1,4,1,4,4,3,3,4,5,4,3,4,141,116.0,neutral or dissatisfied +14632,88078,Male,Loyal Customer,55,Business travel,Business,406,5,5,5,5,2,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +14633,28592,Male,Loyal Customer,44,Business travel,Eco Plus,2562,4,1,3,1,4,4,4,4,1,5,3,1,5,4,0,0.0,satisfied +14634,23606,Female,Loyal Customer,26,Personal Travel,Eco,589,1,4,1,4,3,1,2,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +14635,124208,Male,Loyal Customer,57,Business travel,Eco,676,2,1,1,1,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +14636,36835,Male,Loyal Customer,39,Business travel,Business,369,5,5,5,5,4,2,1,4,4,4,4,3,4,4,0,0.0,satisfied +14637,101850,Male,Loyal Customer,59,Business travel,Business,1935,1,1,1,1,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +14638,74734,Female,Loyal Customer,7,Personal Travel,Eco,1464,3,1,3,4,4,3,4,4,2,3,2,1,3,4,73,63.0,neutral or dissatisfied +14639,122137,Female,Loyal Customer,68,Personal Travel,Business,544,1,1,1,4,3,4,4,4,4,1,4,3,4,1,42,37.0,neutral or dissatisfied +14640,74023,Male,disloyal Customer,23,Business travel,Eco,1152,4,3,3,2,4,4,4,4,3,5,4,5,4,4,11,0.0,satisfied +14641,19480,Female,disloyal Customer,23,Business travel,Business,84,3,2,3,3,2,3,2,2,3,1,4,3,4,2,61,50.0,neutral or dissatisfied +14642,102744,Female,Loyal Customer,51,Business travel,Business,2803,3,3,3,3,4,4,4,4,4,4,4,3,4,4,0,3.0,satisfied +14643,27304,Male,disloyal Customer,43,Business travel,Eco,987,3,3,3,3,5,3,5,5,1,4,5,5,3,5,0,0.0,neutral or dissatisfied +14644,72997,Male,Loyal Customer,40,Business travel,Business,2718,5,5,5,5,1,3,3,5,5,4,5,4,5,5,1,0.0,satisfied +14645,83437,Female,disloyal Customer,23,Business travel,Eco,632,3,0,3,2,2,3,2,2,3,3,5,5,5,2,0,1.0,neutral or dissatisfied +14646,65675,Male,Loyal Customer,52,Business travel,Eco,526,4,4,4,4,4,4,4,4,4,2,2,5,5,4,0,0.0,satisfied +14647,111219,Male,Loyal Customer,13,Business travel,Business,1506,4,1,1,1,4,4,4,4,2,3,3,2,4,4,0,16.0,neutral or dissatisfied +14648,19951,Male,Loyal Customer,50,Personal Travel,Eco,315,3,5,3,2,2,3,4,2,4,1,1,2,1,2,70,85.0,neutral or dissatisfied +14649,82705,Female,Loyal Customer,59,Business travel,Eco,232,4,2,2,2,3,3,3,4,4,4,4,3,4,1,0,0.0,satisfied +14650,128507,Male,Loyal Customer,69,Personal Travel,Eco,651,3,3,3,3,4,3,2,4,3,2,3,1,3,4,7,11.0,neutral or dissatisfied +14651,106066,Female,Loyal Customer,51,Business travel,Business,2807,0,0,0,5,2,4,4,3,3,2,2,3,3,3,10,3.0,satisfied +14652,41899,Female,disloyal Customer,40,Business travel,Business,129,4,4,4,3,4,4,4,4,3,4,3,3,1,4,0,8.0,satisfied +14653,29786,Male,Loyal Customer,30,Business travel,Business,3115,1,1,1,1,4,4,4,4,3,1,4,4,5,4,29,25.0,satisfied +14654,33377,Male,Loyal Customer,55,Personal Travel,Eco,2409,2,1,2,3,5,2,5,5,3,4,2,4,2,5,24,3.0,neutral or dissatisfied +14655,90589,Female,Loyal Customer,41,Business travel,Business,404,2,2,2,2,2,5,4,5,5,5,5,4,5,3,1,0.0,satisfied +14656,116751,Female,Loyal Customer,42,Personal Travel,Eco Plus,390,1,4,2,5,3,5,4,3,3,2,3,5,3,5,22,14.0,neutral or dissatisfied +14657,33465,Female,Loyal Customer,23,Personal Travel,Eco Plus,2556,5,4,5,3,5,5,4,5,4,4,4,2,1,5,15,16.0,satisfied +14658,11581,Male,Loyal Customer,62,Business travel,Business,1742,2,3,3,3,3,3,3,2,2,2,2,2,2,4,105,99.0,neutral or dissatisfied +14659,24341,Female,Loyal Customer,30,Business travel,Eco,634,4,3,5,5,4,4,4,4,5,2,2,2,3,4,0,3.0,satisfied +14660,89631,Female,disloyal Customer,25,Business travel,Eco,1076,3,3,3,4,1,3,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +14661,73595,Male,disloyal Customer,23,Business travel,Business,204,4,0,4,5,4,4,3,4,5,2,4,4,5,4,0,0.0,satisfied +14662,30698,Male,Loyal Customer,23,Personal Travel,Eco,680,1,5,0,3,3,0,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +14663,121914,Female,Loyal Customer,9,Personal Travel,Eco,449,1,1,1,4,5,1,1,5,2,3,3,3,4,5,0,8.0,neutral or dissatisfied +14664,23379,Female,Loyal Customer,49,Business travel,Eco Plus,1014,4,1,1,1,4,4,4,2,4,1,2,4,1,4,180,206.0,satisfied +14665,30824,Female,Loyal Customer,40,Business travel,Eco,1028,4,5,5,5,4,5,4,4,2,4,1,5,5,4,0,0.0,satisfied +14666,59527,Male,Loyal Customer,48,Business travel,Business,3462,2,2,2,2,4,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +14667,34873,Female,Loyal Customer,25,Business travel,Business,2248,2,4,4,4,2,2,2,4,3,4,3,2,1,2,4,21.0,neutral or dissatisfied +14668,94396,Female,disloyal Customer,32,Business travel,Business,239,3,3,3,5,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +14669,73799,Female,Loyal Customer,72,Business travel,Eco Plus,204,2,5,5,5,3,2,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +14670,28350,Female,Loyal Customer,49,Personal Travel,Eco,867,1,3,1,2,3,4,1,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +14671,34377,Male,Loyal Customer,32,Business travel,Business,2537,5,5,5,5,4,4,4,4,3,1,5,4,5,4,0,2.0,satisfied +14672,37978,Male,disloyal Customer,45,Business travel,Business,1237,2,2,2,3,2,2,2,2,1,3,4,2,4,2,40,38.0,neutral or dissatisfied +14673,108492,Male,Loyal Customer,35,Personal Travel,Eco,570,1,5,1,4,3,1,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +14674,36225,Male,Loyal Customer,7,Personal Travel,Eco,280,5,4,4,3,4,4,1,4,5,3,5,4,5,4,9,0.0,satisfied +14675,87075,Male,Loyal Customer,31,Business travel,Business,1798,2,2,2,2,4,4,4,4,4,4,4,4,5,4,0,1.0,satisfied +14676,20678,Female,Loyal Customer,47,Business travel,Business,1839,4,3,3,3,1,3,4,3,3,2,4,3,3,2,39,31.0,neutral or dissatisfied +14677,42304,Female,Loyal Customer,21,Personal Travel,Eco,817,2,2,2,3,3,2,3,3,4,3,2,4,2,3,0,0.0,neutral or dissatisfied +14678,77758,Male,Loyal Customer,38,Business travel,Business,1959,3,3,3,3,5,1,1,4,4,5,4,5,4,4,0,0.0,satisfied +14679,43567,Male,disloyal Customer,26,Business travel,Business,1499,4,4,4,3,1,4,5,1,3,5,5,4,5,1,42,24.0,neutral or dissatisfied +14680,105326,Male,Loyal Customer,47,Business travel,Business,528,5,5,5,5,5,4,4,2,2,2,2,4,2,4,64,53.0,satisfied +14681,39876,Female,Loyal Customer,57,Personal Travel,Eco,272,1,0,5,2,1,2,1,4,4,5,4,3,4,5,0,5.0,neutral or dissatisfied +14682,102139,Female,Loyal Customer,46,Business travel,Business,3319,3,3,3,3,3,4,4,4,4,4,4,5,4,3,28,15.0,satisfied +14683,105257,Female,disloyal Customer,30,Business travel,Business,2106,3,3,3,1,4,3,2,4,5,5,3,4,5,4,0,0.0,neutral or dissatisfied +14684,15050,Male,Loyal Customer,59,Business travel,Business,3036,3,4,4,4,2,2,3,3,3,3,3,3,3,2,8,9.0,neutral or dissatisfied +14685,85307,Male,Loyal Customer,69,Personal Travel,Eco,874,2,4,2,3,4,2,4,4,3,5,4,1,3,4,6,9.0,neutral or dissatisfied +14686,121681,Female,Loyal Customer,43,Personal Travel,Eco,511,2,5,2,1,3,4,5,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +14687,94079,Female,disloyal Customer,23,Business travel,Eco,273,3,0,3,4,5,3,5,5,2,4,4,4,3,5,0,0.0,neutral or dissatisfied +14688,100113,Male,Loyal Customer,30,Business travel,Business,717,3,5,5,5,3,3,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +14689,66067,Male,Loyal Customer,19,Personal Travel,Eco,1055,3,1,3,4,4,3,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +14690,104060,Female,Loyal Customer,18,Personal Travel,Eco,1044,2,4,2,3,1,2,1,1,3,5,4,2,4,1,0,0.0,neutral or dissatisfied +14691,96650,Male,disloyal Customer,39,Business travel,Eco,537,4,3,4,4,4,4,4,4,4,4,4,3,1,4,0,0.0,neutral or dissatisfied +14692,99541,Female,Loyal Customer,55,Business travel,Business,802,4,4,4,4,4,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +14693,46134,Male,Loyal Customer,58,Business travel,Eco,604,5,1,1,1,5,5,5,5,4,4,1,2,1,5,48,47.0,satisfied +14694,76670,Male,Loyal Customer,35,Personal Travel,Eco,516,3,2,3,3,5,3,5,5,2,4,3,2,4,5,4,0.0,neutral or dissatisfied +14695,18595,Female,disloyal Customer,35,Business travel,Eco,201,3,1,3,3,3,3,3,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +14696,59905,Male,Loyal Customer,45,Business travel,Business,3015,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +14697,13569,Male,Loyal Customer,13,Personal Travel,Eco,227,1,4,1,2,5,1,5,5,4,3,4,4,4,5,0,11.0,neutral or dissatisfied +14698,115167,Male,Loyal Customer,53,Business travel,Business,1663,5,5,5,5,5,5,4,5,5,5,5,4,5,5,32,24.0,satisfied +14699,4548,Female,disloyal Customer,25,Business travel,Business,719,5,0,5,3,1,5,1,1,5,4,5,4,4,1,0,1.0,satisfied +14700,100495,Male,Loyal Customer,41,Business travel,Eco,580,2,3,3,3,2,2,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +14701,45454,Female,disloyal Customer,24,Business travel,Eco,522,4,5,4,3,3,4,3,3,2,5,4,1,5,3,0,28.0,satisfied +14702,46476,Male,Loyal Customer,45,Business travel,Business,73,4,2,3,2,2,4,4,4,4,4,4,1,4,1,87,87.0,neutral or dissatisfied +14703,9791,Female,Loyal Customer,39,Business travel,Business,3399,4,4,4,4,4,5,4,5,5,5,5,3,5,3,15,22.0,satisfied +14704,24556,Female,Loyal Customer,47,Business travel,Eco,874,4,3,3,3,2,1,1,4,4,4,4,5,4,5,0,0.0,satisfied +14705,116346,Female,Loyal Customer,13,Personal Travel,Eco,371,3,3,5,2,2,5,3,2,3,4,4,1,1,2,2,15.0,neutral or dissatisfied +14706,127977,Male,disloyal Customer,28,Business travel,Business,1149,4,3,3,3,5,3,5,5,3,5,5,5,4,5,68,55.0,satisfied +14707,20890,Female,Loyal Customer,35,Personal Travel,Eco Plus,508,3,4,3,2,2,3,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +14708,97956,Female,Loyal Customer,36,Business travel,Business,2695,1,1,1,1,4,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +14709,61930,Male,Loyal Customer,45,Personal Travel,Eco,550,4,4,4,4,3,4,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +14710,102272,Female,Loyal Customer,48,Business travel,Business,258,5,5,5,5,4,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +14711,79337,Male,disloyal Customer,29,Business travel,Eco,1020,4,4,4,3,4,4,5,4,3,5,4,3,4,4,0,78.0,neutral or dissatisfied +14712,43918,Male,Loyal Customer,69,Personal Travel,Eco,144,2,3,2,3,5,2,5,5,2,2,2,1,3,5,0,0.0,neutral or dissatisfied +14713,24407,Male,disloyal Customer,20,Business travel,Eco,634,4,4,4,5,2,4,2,2,5,2,1,5,5,2,0,0.0,satisfied +14714,88339,Male,Loyal Customer,42,Business travel,Business,2973,0,0,0,3,5,5,4,5,5,5,3,5,5,4,0,0.0,satisfied +14715,24089,Male,Loyal Customer,36,Business travel,Business,2350,4,4,4,4,5,1,5,5,5,5,5,4,5,4,7,10.0,satisfied +14716,71888,Male,Loyal Customer,30,Personal Travel,Eco,1846,2,5,2,5,2,2,1,2,5,4,3,5,5,2,0,0.0,neutral or dissatisfied +14717,91840,Male,disloyal Customer,34,Business travel,Eco Plus,588,3,3,3,3,5,3,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +14718,29708,Female,Loyal Customer,56,Personal Travel,Eco,1542,2,4,2,4,2,3,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +14719,32790,Female,Loyal Customer,77,Business travel,Eco,101,4,5,2,5,4,5,4,3,3,4,3,1,3,4,0,1.0,satisfied +14720,77605,Male,Loyal Customer,59,Business travel,Business,689,1,1,1,1,3,5,4,3,3,3,3,4,3,4,6,2.0,satisfied +14721,120406,Male,disloyal Customer,39,Business travel,Business,337,5,5,5,3,3,5,3,3,5,2,5,3,5,3,0,0.0,satisfied +14722,87456,Male,Loyal Customer,45,Business travel,Business,2948,4,4,4,4,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +14723,11287,Male,Loyal Customer,30,Personal Travel,Eco,74,3,5,3,1,2,3,2,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +14724,32091,Male,disloyal Customer,44,Business travel,Eco,163,5,2,5,4,5,5,5,5,1,1,4,4,4,5,83,85.0,satisfied +14725,39699,Male,Loyal Customer,39,Business travel,Business,2738,5,5,5,5,3,4,5,4,4,4,5,1,4,3,0,3.0,satisfied +14726,90171,Male,Loyal Customer,48,Personal Travel,Eco,1145,0,5,0,3,4,0,4,4,5,4,4,4,3,4,0,0.0,satisfied +14727,57122,Female,disloyal Customer,35,Business travel,Eco,1222,3,3,3,1,2,3,4,2,1,5,2,4,2,2,0,0.0,neutral or dissatisfied +14728,116647,Female,Loyal Customer,23,Business travel,Eco Plus,337,3,1,1,1,3,3,3,3,4,1,4,4,4,3,17,15.0,neutral or dissatisfied +14729,68177,Female,Loyal Customer,34,Personal Travel,Eco,603,2,5,2,2,5,2,3,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +14730,81598,Male,disloyal Customer,21,Business travel,Eco,334,3,2,3,4,3,3,3,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +14731,118735,Female,Loyal Customer,64,Personal Travel,Eco,370,3,0,3,1,2,4,4,3,3,3,5,5,3,4,52,40.0,neutral or dissatisfied +14732,85518,Female,Loyal Customer,49,Business travel,Business,3095,0,0,0,1,5,5,4,5,5,5,5,5,5,5,4,0.0,satisfied +14733,16608,Female,Loyal Customer,43,Business travel,Business,1589,5,3,5,5,3,3,3,2,3,5,5,3,1,3,145,140.0,satisfied +14734,26431,Female,disloyal Customer,38,Business travel,Eco,919,4,4,4,3,5,4,5,5,5,4,3,4,4,5,0,0.0,satisfied +14735,41747,Female,Loyal Customer,50,Personal Travel,Eco,695,0,2,0,4,3,3,4,5,5,0,5,2,5,2,0,1.0,satisfied +14736,79165,Male,Loyal Customer,56,Business travel,Business,2422,4,4,4,4,4,4,4,5,4,4,5,4,5,4,0,3.0,satisfied +14737,70556,Male,disloyal Customer,41,Business travel,Business,1258,5,5,5,2,1,5,1,1,5,5,5,3,5,1,0,0.0,satisfied +14738,36702,Male,Loyal Customer,57,Personal Travel,Eco,1249,2,5,2,3,2,2,2,2,5,2,3,3,2,2,0,0.0,neutral or dissatisfied +14739,94065,Male,disloyal Customer,23,Business travel,Eco,293,4,0,4,3,4,4,4,4,4,4,3,3,3,4,0,0.0,neutral or dissatisfied +14740,35928,Female,Loyal Customer,60,Business travel,Business,2381,3,3,2,3,2,4,3,4,4,4,4,5,4,4,15,0.0,satisfied +14741,34109,Male,disloyal Customer,31,Business travel,Business,1189,1,0,0,2,5,0,5,5,3,1,1,2,1,5,0,0.0,neutral or dissatisfied +14742,113960,Female,Loyal Customer,60,Business travel,Business,1844,5,5,5,5,4,4,4,1,1,2,1,5,1,5,7,12.0,satisfied +14743,29927,Male,Loyal Customer,25,Business travel,Business,373,1,1,2,1,4,4,4,4,4,5,4,2,4,4,1,3.0,satisfied +14744,63498,Female,disloyal Customer,24,Business travel,Business,1208,4,4,4,2,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +14745,83938,Male,disloyal Customer,22,Business travel,Eco,373,2,4,2,1,5,2,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +14746,37668,Female,Loyal Customer,39,Personal Travel,Eco,1076,1,1,1,3,3,1,4,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +14747,98518,Male,disloyal Customer,23,Business travel,Eco,668,1,4,1,4,2,1,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +14748,421,Female,disloyal Customer,25,Business travel,Business,312,3,0,4,4,4,4,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +14749,105727,Female,Loyal Customer,29,Business travel,Business,787,2,3,3,3,2,2,2,2,3,3,4,2,4,2,12,11.0,neutral or dissatisfied +14750,39061,Male,Loyal Customer,23,Business travel,Business,784,2,2,2,2,4,4,4,4,1,5,3,4,1,4,116,160.0,satisfied +14751,23562,Female,Loyal Customer,25,Personal Travel,Eco,637,1,1,1,4,3,1,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +14752,41231,Male,Loyal Customer,46,Business travel,Business,744,1,1,1,1,4,4,1,5,5,4,5,3,5,2,10,10.0,satisfied +14753,40176,Female,Loyal Customer,41,Business travel,Business,347,3,3,3,3,5,1,3,5,5,5,5,1,5,1,0,0.0,satisfied +14754,70973,Male,disloyal Customer,27,Business travel,Business,802,3,3,3,1,4,3,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +14755,122108,Female,Loyal Customer,14,Personal Travel,Eco,130,2,5,2,4,4,2,4,4,4,1,1,5,3,4,0,19.0,neutral or dissatisfied +14756,78043,Female,Loyal Customer,70,Personal Travel,Eco,106,1,1,0,4,2,3,4,5,5,0,2,4,5,2,0,0.0,neutral or dissatisfied +14757,56790,Female,Loyal Customer,43,Business travel,Business,1725,4,4,4,4,2,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +14758,11650,Female,Loyal Customer,56,Business travel,Business,3226,5,5,5,5,3,5,4,5,5,5,5,4,5,5,20,3.0,satisfied +14759,29904,Male,disloyal Customer,38,Business travel,Eco,571,2,5,2,5,5,2,5,5,2,5,1,4,1,5,37,42.0,neutral or dissatisfied +14760,98920,Female,Loyal Customer,34,Business travel,Business,1636,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +14761,27457,Female,Loyal Customer,41,Business travel,Business,2562,2,2,2,2,3,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +14762,53939,Female,Loyal Customer,44,Personal Travel,Eco,2007,1,4,1,1,3,4,5,5,5,1,2,3,5,5,0,0.0,neutral or dissatisfied +14763,22775,Female,Loyal Customer,19,Business travel,Eco,147,2,3,3,3,2,2,4,2,1,4,4,3,3,2,112,110.0,neutral or dissatisfied +14764,20729,Female,Loyal Customer,42,Personal Travel,Eco,765,1,4,1,2,5,4,4,5,5,1,5,5,5,3,21,19.0,neutral or dissatisfied +14765,57297,Male,Loyal Customer,59,Business travel,Business,414,5,5,4,5,5,5,4,4,4,4,4,4,4,5,19,13.0,satisfied +14766,78280,Female,Loyal Customer,47,Business travel,Business,1598,1,1,1,1,4,3,5,3,3,3,3,3,3,4,0,0.0,satisfied +14767,4109,Male,Loyal Customer,53,Business travel,Business,2705,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +14768,30565,Female,Loyal Customer,38,Business travel,Business,1768,1,1,1,1,5,5,4,4,4,4,4,4,4,1,0,0.0,satisfied +14769,113015,Male,Loyal Customer,29,Business travel,Eco Plus,1751,2,4,4,4,2,2,2,2,4,4,2,3,4,2,8,10.0,neutral or dissatisfied +14770,20449,Female,Loyal Customer,53,Business travel,Eco,84,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +14771,100539,Male,Loyal Customer,31,Personal Travel,Eco,580,1,5,1,4,5,1,5,5,4,3,3,2,4,5,30,24.0,neutral or dissatisfied +14772,86165,Male,disloyal Customer,38,Business travel,Business,164,3,3,3,4,5,3,3,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +14773,95328,Female,Loyal Customer,31,Personal Travel,Eco,189,3,4,3,1,3,3,5,3,4,4,2,1,4,3,12,7.0,neutral or dissatisfied +14774,109017,Male,Loyal Customer,25,Business travel,Eco,781,4,5,5,5,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +14775,18100,Male,Loyal Customer,41,Business travel,Business,610,3,3,3,3,5,4,4,4,4,4,4,1,4,5,52,86.0,satisfied +14776,37236,Female,Loyal Customer,55,Business travel,Business,3204,2,1,1,1,2,3,4,2,2,3,2,4,2,4,57,58.0,neutral or dissatisfied +14777,82006,Female,Loyal Customer,16,Business travel,Business,1517,4,4,4,4,5,5,5,5,3,5,4,1,4,5,0,0.0,satisfied +14778,39278,Male,Loyal Customer,49,Business travel,Eco,67,4,5,5,5,4,4,4,4,4,2,2,1,1,4,0,0.0,satisfied +14779,51451,Female,Loyal Customer,34,Personal Travel,Eco Plus,447,1,1,1,2,3,1,3,3,4,1,2,2,3,3,0,0.0,neutral or dissatisfied +14780,53802,Female,Loyal Customer,44,Business travel,Business,191,1,1,4,1,1,1,5,5,5,5,3,4,5,4,0,7.0,satisfied +14781,76313,Female,Loyal Customer,21,Business travel,Business,2182,1,2,2,2,1,1,1,1,4,5,2,2,3,1,109,110.0,neutral or dissatisfied +14782,37364,Female,Loyal Customer,56,Business travel,Business,3891,4,4,4,4,2,1,1,5,5,5,5,5,5,1,0,0.0,satisfied +14783,111865,Male,Loyal Customer,15,Business travel,Business,2909,1,1,1,1,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +14784,110748,Female,Loyal Customer,60,Business travel,Business,3666,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +14785,119394,Female,disloyal Customer,41,Business travel,Business,399,1,1,1,5,4,1,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +14786,123527,Female,disloyal Customer,27,Business travel,Business,2125,5,5,5,2,5,3,5,5,3,4,5,3,5,5,0,0.0,satisfied +14787,4790,Male,Loyal Customer,33,Personal Travel,Eco,438,5,4,5,4,5,5,3,5,2,1,4,2,3,5,10,0.0,satisfied +14788,72967,Male,Loyal Customer,8,Business travel,Eco,1096,2,4,4,4,2,2,3,2,2,3,4,2,3,2,0,0.0,neutral or dissatisfied +14789,29714,Female,Loyal Customer,36,Business travel,Business,2304,1,1,1,1,3,4,4,2,2,2,2,2,2,3,0,0.0,satisfied +14790,109766,Female,Loyal Customer,34,Business travel,Business,1011,4,4,4,4,5,5,4,5,5,5,5,3,5,3,50,98.0,satisfied +14791,17599,Female,disloyal Customer,48,Business travel,Eco Plus,695,3,3,3,4,1,3,1,1,1,5,4,1,2,1,34,26.0,neutral or dissatisfied +14792,8541,Female,Loyal Customer,43,Business travel,Business,3136,3,3,3,3,5,5,4,4,4,4,4,3,4,4,60,53.0,satisfied +14793,16285,Male,disloyal Customer,8,Personal Travel,Eco,748,2,5,2,1,5,2,5,5,4,3,5,2,3,5,57,52.0,neutral or dissatisfied +14794,61580,Female,Loyal Customer,56,Business travel,Business,1346,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +14795,115266,Female,Loyal Customer,51,Business travel,Business,325,1,1,1,1,5,4,4,5,5,5,5,5,5,5,20,2.0,satisfied +14796,74759,Female,Loyal Customer,57,Personal Travel,Eco,1126,2,5,2,3,4,4,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +14797,17782,Male,disloyal Customer,22,Business travel,Eco,1214,5,5,5,2,1,5,1,1,4,1,4,2,4,1,0,0.0,satisfied +14798,31927,Female,disloyal Customer,44,Business travel,Business,102,4,3,3,1,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +14799,61410,Female,Loyal Customer,26,Personal Travel,Eco,679,2,4,2,1,1,2,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +14800,109361,Male,Loyal Customer,58,Business travel,Business,2851,2,2,2,2,2,5,5,4,4,4,4,4,4,5,7,0.0,satisfied +14801,32427,Male,Loyal Customer,33,Business travel,Eco,101,4,1,1,1,4,4,4,4,3,1,2,1,4,4,2,7.0,satisfied +14802,28060,Male,Loyal Customer,54,Business travel,Eco,2562,4,3,3,3,4,4,4,4,2,4,5,1,1,4,0,0.0,satisfied +14803,38843,Female,Loyal Customer,38,Business travel,Eco Plus,387,1,3,3,3,1,2,1,1,4,1,4,4,4,1,37,37.0,neutral or dissatisfied +14804,15367,Female,Loyal Customer,60,Business travel,Eco,331,4,5,5,5,4,1,5,4,4,4,4,5,4,3,36,18.0,satisfied +14805,117680,Female,Loyal Customer,40,Business travel,Business,1814,2,2,2,2,2,3,5,5,5,5,5,4,5,3,30,13.0,satisfied +14806,79358,Male,Loyal Customer,52,Personal Travel,Eco,1020,1,1,1,2,5,1,5,5,1,1,2,2,2,5,0,0.0,neutral or dissatisfied +14807,19144,Female,Loyal Customer,41,Business travel,Eco Plus,265,4,4,4,4,4,1,3,4,4,4,4,4,4,5,0,3.0,satisfied +14808,42907,Female,Loyal Customer,28,Personal Travel,Eco,368,5,1,5,3,4,5,4,4,4,1,4,3,3,4,0,0.0,satisfied +14809,110910,Female,Loyal Customer,63,Business travel,Business,3051,1,1,1,1,2,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +14810,29155,Female,disloyal Customer,20,Business travel,Eco Plus,1050,4,4,4,3,4,4,4,4,1,5,3,4,4,4,0,5.0,neutral or dissatisfied +14811,104284,Female,Loyal Customer,60,Business travel,Business,440,1,1,5,1,4,5,5,4,4,4,4,4,4,5,1,0.0,satisfied +14812,96387,Male,Loyal Customer,41,Business travel,Business,1407,1,1,2,1,2,5,5,2,2,2,2,5,2,3,2,0.0,satisfied +14813,54445,Female,Loyal Customer,63,Business travel,Eco Plus,305,2,5,5,5,4,5,5,1,1,2,1,4,1,3,7,8.0,satisfied +14814,43772,Female,Loyal Customer,63,Business travel,Business,481,2,2,2,2,5,5,4,4,4,4,4,1,4,2,0,0.0,satisfied +14815,128423,Male,Loyal Customer,19,Business travel,Business,2217,0,0,0,3,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +14816,105289,Male,disloyal Customer,30,Business travel,Business,967,4,5,5,2,3,5,3,3,4,3,4,4,4,3,0,6.0,satisfied +14817,110837,Female,Loyal Customer,31,Personal Travel,Eco Plus,990,2,4,2,1,5,2,3,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +14818,125691,Male,Loyal Customer,41,Business travel,Eco,359,4,1,1,1,4,4,4,4,2,1,3,2,4,4,30,28.0,neutral or dissatisfied +14819,68185,Male,Loyal Customer,37,Personal Travel,Eco,603,2,5,2,4,3,2,3,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +14820,2846,Female,Loyal Customer,48,Business travel,Business,475,3,4,3,4,4,3,3,4,2,3,3,3,4,3,240,298.0,neutral or dissatisfied +14821,56321,Female,Loyal Customer,54,Business travel,Business,2257,0,4,0,4,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +14822,17090,Male,Loyal Customer,62,Business travel,Business,416,4,4,4,4,1,1,4,2,2,2,2,5,2,3,59,57.0,satisfied +14823,33893,Female,Loyal Customer,54,Business travel,Eco,1226,4,5,2,5,4,3,2,4,4,4,4,4,4,2,3,0.0,neutral or dissatisfied +14824,84241,Female,Loyal Customer,35,Business travel,Eco Plus,432,3,5,5,5,3,3,3,3,1,2,4,2,3,3,0,0.0,satisfied +14825,127779,Female,Loyal Customer,57,Business travel,Business,2131,2,2,2,2,4,4,5,2,2,3,2,4,2,5,0,0.0,satisfied +14826,92965,Female,Loyal Customer,69,Personal Travel,Eco,1694,3,5,2,2,2,2,5,2,2,2,2,1,2,3,20,22.0,neutral or dissatisfied +14827,12100,Female,Loyal Customer,28,Business travel,Eco,1034,3,4,4,4,3,4,3,3,3,1,3,1,4,3,86,69.0,satisfied +14828,6504,Male,Loyal Customer,44,Business travel,Business,1738,5,5,5,5,3,5,5,5,5,5,5,5,5,3,8,6.0,satisfied +14829,60197,Male,Loyal Customer,25,Business travel,Business,1506,3,3,3,3,5,5,5,5,3,4,4,4,4,5,92,69.0,satisfied +14830,48306,Male,Loyal Customer,44,Business travel,Business,1499,3,1,5,1,3,4,3,3,3,3,3,4,3,2,7,0.0,neutral or dissatisfied +14831,34266,Female,Loyal Customer,60,Business travel,Business,280,3,3,3,3,1,3,4,3,3,3,3,4,3,3,67,86.0,neutral or dissatisfied +14832,83881,Female,Loyal Customer,15,Business travel,Business,1670,2,4,4,4,2,2,2,2,3,4,3,4,3,2,0,8.0,neutral or dissatisfied +14833,117365,Male,Loyal Customer,49,Personal Travel,Eco,296,2,2,2,3,2,2,5,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +14834,92725,Male,Loyal Customer,50,Business travel,Business,3279,5,5,3,5,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +14835,86235,Female,Loyal Customer,39,Personal Travel,Eco,306,2,5,2,1,4,2,4,4,5,4,5,4,5,4,85,77.0,neutral or dissatisfied +14836,11571,Female,Loyal Customer,53,Business travel,Business,468,4,3,3,3,2,2,3,4,4,3,4,1,4,1,92,84.0,neutral or dissatisfied +14837,24166,Female,Loyal Customer,41,Business travel,Business,3907,1,1,1,1,3,1,3,5,5,4,4,3,5,4,5,3.0,satisfied +14838,27003,Female,Loyal Customer,60,Business travel,Business,867,3,3,3,3,2,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +14839,97056,Female,Loyal Customer,41,Business travel,Business,1390,3,3,3,3,4,5,4,4,4,4,4,4,4,3,30,40.0,satisfied +14840,124562,Male,disloyal Customer,15,Business travel,Eco,453,2,0,2,1,4,2,4,4,3,5,1,1,2,4,2,0.0,neutral or dissatisfied +14841,87093,Male,Loyal Customer,38,Business travel,Business,2165,1,1,1,1,1,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +14842,120050,Male,Loyal Customer,48,Business travel,Business,1884,2,5,5,5,2,3,4,2,2,2,2,3,2,2,0,15.0,neutral or dissatisfied +14843,118760,Male,Loyal Customer,11,Personal Travel,Eco,338,2,4,5,4,2,5,3,2,4,4,1,2,1,2,12,11.0,neutral or dissatisfied +14844,127146,Male,Loyal Customer,36,Personal Travel,Eco,338,4,5,4,5,5,4,5,5,5,5,4,3,4,5,3,0.0,satisfied +14845,10825,Male,Loyal Customer,43,Business travel,Business,2907,0,0,0,3,2,5,4,1,1,1,1,3,1,3,0,0.0,satisfied +14846,65614,Male,Loyal Customer,64,Personal Travel,Eco,237,3,4,3,5,5,3,3,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +14847,20102,Female,disloyal Customer,30,Business travel,Eco,416,1,0,1,3,1,1,2,1,4,2,3,2,2,1,15,4.0,neutral or dissatisfied +14848,120947,Male,disloyal Customer,24,Business travel,Eco,993,5,4,4,3,4,4,4,4,3,3,4,4,5,4,22,85.0,satisfied +14849,129550,Female,disloyal Customer,20,Business travel,Eco,1083,2,3,3,5,4,3,5,4,2,4,5,3,5,4,5,23.0,neutral or dissatisfied +14850,68066,Male,Loyal Customer,44,Business travel,Business,1619,3,2,3,3,5,4,5,4,4,4,4,3,4,3,0,7.0,satisfied +14851,59997,Female,Loyal Customer,24,Personal Travel,Eco,997,1,5,1,1,2,1,1,2,4,4,4,5,4,2,72,56.0,neutral or dissatisfied +14852,31338,Male,Loyal Customer,50,Personal Travel,Eco,1062,4,3,4,3,1,4,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +14853,116081,Female,Loyal Customer,55,Personal Travel,Eco,372,1,0,1,3,2,3,4,2,2,1,2,2,2,3,30,25.0,neutral or dissatisfied +14854,26453,Male,disloyal Customer,25,Business travel,Eco,842,4,4,4,3,3,4,3,3,2,4,5,2,1,3,0,0.0,neutral or dissatisfied +14855,37816,Female,Loyal Customer,56,Personal Travel,Eco Plus,1097,4,5,4,3,2,5,3,3,3,4,3,3,3,1,3,0.0,satisfied +14856,51390,Female,Loyal Customer,57,Personal Travel,Eco Plus,372,1,3,1,4,4,2,4,2,2,1,4,3,2,1,60,54.0,neutral or dissatisfied +14857,39427,Male,Loyal Customer,58,Business travel,Business,2203,5,5,5,5,2,3,4,5,5,5,5,3,5,4,0,16.0,satisfied +14858,84329,Male,Loyal Customer,41,Business travel,Business,2808,4,4,4,4,2,5,5,5,5,5,5,4,5,5,129,124.0,satisfied +14859,14945,Male,Loyal Customer,26,Business travel,Business,554,1,4,4,4,1,1,1,1,4,5,4,1,4,1,14,10.0,neutral or dissatisfied +14860,10854,Male,Loyal Customer,27,Business travel,Eco,482,3,4,4,4,3,3,3,3,4,4,3,3,2,3,0,32.0,neutral or dissatisfied +14861,29139,Male,Loyal Customer,42,Personal Travel,Eco,954,3,4,3,4,1,3,1,1,4,2,4,3,4,1,0,9.0,neutral or dissatisfied +14862,111840,Male,Loyal Customer,50,Business travel,Business,3768,5,5,5,5,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +14863,124703,Female,Loyal Customer,49,Business travel,Business,399,5,2,5,5,2,1,4,5,5,5,5,3,5,2,0,0.0,satisfied +14864,88677,Male,Loyal Customer,35,Personal Travel,Eco,406,2,5,3,3,5,3,5,5,5,3,4,3,4,5,6,0.0,neutral or dissatisfied +14865,42305,Female,Loyal Customer,54,Personal Travel,Eco,726,2,2,2,3,4,4,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +14866,12777,Female,Loyal Customer,59,Personal Travel,Eco Plus,721,3,0,4,2,4,4,5,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +14867,37009,Male,Loyal Customer,18,Personal Travel,Eco,667,3,5,3,5,5,3,1,5,4,2,1,3,3,5,0,0.0,neutral or dissatisfied +14868,4355,Female,disloyal Customer,24,Business travel,Eco,473,3,0,3,2,4,3,4,4,3,2,4,4,5,4,0,15.0,neutral or dissatisfied +14869,47342,Female,Loyal Customer,53,Business travel,Business,626,2,2,2,2,1,3,5,5,5,5,5,5,5,5,2,0.0,satisfied +14870,102433,Female,Loyal Customer,56,Personal Travel,Eco,397,3,4,5,1,4,5,5,1,1,5,1,3,1,4,0,0.0,neutral or dissatisfied +14871,68422,Male,Loyal Customer,59,Personal Travel,Eco,1045,3,5,3,3,3,3,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +14872,50745,Female,Loyal Customer,61,Personal Travel,Eco,109,1,4,1,5,4,4,5,4,4,1,4,5,4,5,16,9.0,neutral or dissatisfied +14873,23887,Male,Loyal Customer,27,Business travel,Business,589,5,5,2,5,5,5,5,5,2,4,2,2,4,5,0,0.0,satisfied +14874,52511,Male,Loyal Customer,33,Business travel,Business,160,4,4,4,4,4,4,4,4,4,2,4,4,3,4,0,0.0,satisfied +14875,48338,Male,disloyal Customer,23,Business travel,Eco,522,5,5,5,5,5,5,2,5,2,2,4,1,3,5,0,0.0,satisfied +14876,30392,Male,Loyal Customer,65,Personal Travel,Eco,775,3,4,3,1,3,3,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +14877,67935,Male,Loyal Customer,61,Personal Travel,Eco,1205,2,2,2,3,3,2,3,3,1,5,3,3,3,3,15,21.0,neutral or dissatisfied +14878,37382,Female,Loyal Customer,58,Business travel,Eco,1069,2,5,5,5,1,3,3,2,2,2,2,3,2,3,83,68.0,neutral or dissatisfied +14879,80323,Male,Loyal Customer,19,Personal Travel,Eco,746,1,1,1,4,5,1,5,5,3,1,3,3,4,5,0,4.0,neutral or dissatisfied +14880,65963,Female,Loyal Customer,59,Business travel,Business,1372,2,2,2,2,4,4,4,4,4,4,4,3,4,4,18,0.0,satisfied +14881,58883,Female,Loyal Customer,49,Business travel,Business,888,3,3,3,3,5,4,4,4,4,4,4,4,4,4,4,0.0,satisfied +14882,26493,Male,Loyal Customer,28,Business travel,Business,837,5,5,5,5,5,5,5,5,1,1,2,4,4,5,0,0.0,satisfied +14883,80875,Male,Loyal Customer,45,Personal Travel,Eco,484,2,4,4,2,5,4,5,5,5,2,4,4,5,5,16,12.0,neutral or dissatisfied +14884,60964,Male,Loyal Customer,36,Business travel,Eco,488,2,1,1,1,2,2,2,2,3,5,3,2,4,2,71,58.0,neutral or dissatisfied +14885,23734,Female,disloyal Customer,26,Business travel,Eco,771,1,0,0,2,4,0,4,4,1,2,1,3,2,4,0,1.0,neutral or dissatisfied +14886,35028,Female,Loyal Customer,63,Business travel,Eco Plus,740,1,3,2,3,2,4,3,1,1,1,1,2,1,1,13,10.0,neutral or dissatisfied +14887,10478,Male,Loyal Customer,41,Business travel,Business,2440,4,4,4,4,4,4,4,4,4,4,4,4,4,5,71,59.0,satisfied +14888,78264,Female,Loyal Customer,50,Personal Travel,Eco,903,5,5,5,1,3,5,4,3,3,5,3,3,3,3,15,42.0,satisfied +14889,2966,Male,Loyal Customer,57,Personal Travel,Eco,737,3,5,3,1,2,3,5,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +14890,50803,Female,Loyal Customer,43,Personal Travel,Eco,209,4,5,4,4,1,4,4,2,2,4,2,5,2,1,0,1.0,satisfied +14891,37457,Male,Loyal Customer,41,Business travel,Eco,972,5,2,2,2,4,5,4,4,3,2,2,5,5,4,0,0.0,satisfied +14892,27948,Male,Loyal Customer,31,Business travel,Business,1660,4,5,5,5,4,3,4,4,1,3,3,4,3,4,0,20.0,neutral or dissatisfied +14893,38557,Female,Loyal Customer,41,Personal Travel,Eco,2475,3,3,3,2,4,3,4,4,3,2,4,5,5,4,23,0.0,neutral or dissatisfied +14894,96229,Male,Loyal Customer,53,Business travel,Eco,546,1,5,5,5,1,1,1,1,2,5,3,3,3,1,8,0.0,neutral or dissatisfied +14895,55467,Female,disloyal Customer,48,Business travel,Business,1825,4,4,4,4,4,4,4,4,4,5,4,3,4,4,2,0.0,satisfied +14896,41082,Male,disloyal Customer,33,Business travel,Eco,140,1,5,1,4,4,1,2,4,3,3,1,5,5,4,0,0.0,neutral or dissatisfied +14897,117123,Female,Loyal Customer,62,Business travel,Business,325,4,4,4,4,2,2,4,5,5,5,5,2,5,4,11,11.0,satisfied +14898,121189,Male,Loyal Customer,33,Personal Travel,Eco,2402,3,1,3,3,2,3,2,2,4,1,4,4,4,2,56,51.0,neutral or dissatisfied +14899,25914,Male,disloyal Customer,36,Business travel,Eco,594,3,5,3,4,5,3,5,5,4,4,2,4,4,5,0,0.0,neutral or dissatisfied +14900,122419,Female,Loyal Customer,29,Business travel,Business,1916,3,3,3,3,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +14901,110593,Female,Loyal Customer,46,Personal Travel,Eco,551,1,2,1,3,2,4,4,1,1,1,1,4,1,2,16,15.0,neutral or dissatisfied +14902,30990,Male,Loyal Customer,26,Personal Travel,Eco Plus,1476,3,4,3,4,2,3,1,2,2,4,3,3,4,2,12,17.0,neutral or dissatisfied +14903,82832,Female,Loyal Customer,34,Business travel,Business,594,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +14904,54081,Female,Loyal Customer,72,Business travel,Eco,1016,5,1,1,1,1,5,5,5,5,5,5,3,5,1,0,0.0,satisfied +14905,8261,Female,Loyal Customer,66,Personal Travel,Eco,335,3,1,3,4,3,3,3,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +14906,28258,Male,Loyal Customer,13,Business travel,Eco,1542,0,4,0,3,3,0,3,3,2,3,5,3,3,3,0,0.0,satisfied +14907,94264,Female,disloyal Customer,24,Business travel,Business,187,5,0,5,1,2,5,2,2,3,2,5,3,4,2,0,0.0,satisfied +14908,119170,Female,disloyal Customer,34,Business travel,Eco,257,1,1,1,3,5,1,5,5,2,5,4,4,3,5,0,0.0,neutral or dissatisfied +14909,2604,Female,Loyal Customer,33,Personal Travel,Eco,181,1,1,1,3,4,1,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +14910,66948,Female,disloyal Customer,21,Business travel,Eco,1121,5,5,5,1,4,5,4,4,3,3,5,3,4,4,0,0.0,satisfied +14911,103995,Female,Loyal Customer,54,Business travel,Business,1592,2,2,2,2,5,5,5,4,3,4,5,5,3,5,126,173.0,satisfied +14912,5290,Female,Loyal Customer,41,Personal Travel,Eco,190,3,4,3,3,4,3,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +14913,42847,Male,Loyal Customer,57,Business travel,Business,3761,4,3,3,3,4,3,2,4,4,4,4,1,4,1,29,33.0,neutral or dissatisfied +14914,36415,Female,Loyal Customer,35,Business travel,Eco,369,4,4,4,4,4,4,4,4,4,4,4,5,5,4,17,17.0,satisfied +14915,16873,Male,Loyal Customer,55,Business travel,Eco,746,4,4,4,4,4,4,4,4,1,4,2,4,5,4,18,24.0,satisfied +14916,86119,Male,Loyal Customer,39,Business travel,Business,3805,2,2,2,2,2,5,4,3,3,3,3,3,3,3,13,32.0,satisfied +14917,49679,Male,Loyal Customer,49,Business travel,Business,3437,3,3,3,3,4,3,3,4,4,4,4,1,4,2,0,1.0,satisfied +14918,15403,Male,Loyal Customer,62,Business travel,Business,377,1,5,5,5,1,3,4,1,1,1,1,1,1,3,11,8.0,neutral or dissatisfied +14919,1265,Female,Loyal Customer,52,Personal Travel,Eco,113,1,3,1,2,4,2,1,4,4,1,4,3,4,3,127,123.0,neutral or dissatisfied +14920,96013,Female,Loyal Customer,40,Business travel,Business,795,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +14921,39336,Female,disloyal Customer,17,Business travel,Eco Plus,160,3,4,3,3,4,3,5,4,1,1,4,2,4,4,0,5.0,neutral or dissatisfied +14922,106096,Female,Loyal Customer,38,Business travel,Business,3670,5,5,5,5,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +14923,52216,Female,disloyal Customer,34,Business travel,Eco,370,1,2,1,3,4,1,5,4,4,1,4,1,4,4,1,6.0,neutral or dissatisfied +14924,120261,Female,Loyal Customer,62,Business travel,Business,237,5,5,5,5,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +14925,70294,Female,Loyal Customer,33,Personal Travel,Eco,852,2,5,2,3,2,2,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +14926,11198,Male,Loyal Customer,57,Personal Travel,Eco,309,2,3,2,1,5,2,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +14927,75986,Female,Loyal Customer,58,Personal Travel,Eco,297,3,4,3,3,4,4,5,1,1,3,3,5,1,4,3,0.0,neutral or dissatisfied +14928,6530,Male,Loyal Customer,48,Personal Travel,Eco,599,2,5,2,4,3,2,3,3,5,5,3,1,2,3,0,0.0,neutral or dissatisfied +14929,41268,Female,Loyal Customer,16,Business travel,Business,1567,2,5,5,5,2,2,2,2,4,4,4,1,4,2,8,20.0,neutral or dissatisfied +14930,48300,Female,Loyal Customer,30,Business travel,Business,1499,1,4,4,4,1,1,1,1,1,5,4,4,4,1,7,3.0,neutral or dissatisfied +14931,68333,Male,Loyal Customer,69,Personal Travel,Eco,2165,2,4,1,3,3,1,3,3,3,4,3,4,4,3,4,0.0,neutral or dissatisfied +14932,102636,Female,disloyal Customer,24,Business travel,Business,255,4,0,4,4,2,4,2,2,5,4,4,4,4,2,0,0.0,satisfied +14933,70999,Male,disloyal Customer,21,Business travel,Eco,802,1,1,1,4,2,1,3,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +14934,96922,Male,Loyal Customer,47,Business travel,Business,488,5,5,2,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +14935,32513,Female,Loyal Customer,47,Business travel,Eco,101,2,3,3,3,3,3,3,2,2,2,2,4,2,2,12,8.0,neutral or dissatisfied +14936,49559,Male,Loyal Customer,63,Business travel,Eco,134,5,4,4,4,5,5,5,5,3,1,2,2,3,5,0,0.0,satisfied +14937,108016,Male,Loyal Customer,43,Business travel,Business,589,5,3,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +14938,36259,Male,disloyal Customer,10,Business travel,Eco,612,1,4,1,3,3,1,3,3,2,3,4,2,4,3,0,13.0,neutral or dissatisfied +14939,9351,Female,Loyal Customer,48,Business travel,Business,3423,1,1,2,1,5,5,5,4,4,4,4,3,4,5,1,88.0,satisfied +14940,69124,Female,Loyal Customer,58,Personal Travel,Eco,1598,3,4,2,1,5,4,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +14941,54554,Female,Loyal Customer,20,Personal Travel,Eco,925,2,1,2,3,3,2,3,3,2,1,3,3,3,3,19,8.0,neutral or dissatisfied +14942,98504,Female,Loyal Customer,50,Business travel,Business,1965,5,5,3,5,4,4,4,4,4,4,4,3,4,5,1,20.0,satisfied +14943,15589,Female,Loyal Customer,38,Business travel,Eco,229,1,1,4,1,1,1,1,1,2,2,3,3,4,1,119,109.0,neutral or dissatisfied +14944,90389,Female,Loyal Customer,31,Personal Travel,Business,404,2,4,2,5,2,2,2,2,5,3,5,4,4,2,0,1.0,neutral or dissatisfied +14945,106407,Male,Loyal Customer,8,Personal Travel,Eco,488,5,1,5,3,2,5,4,2,4,4,4,4,4,2,0,0.0,satisfied +14946,3891,Female,Loyal Customer,40,Business travel,Business,1613,2,3,3,3,3,2,2,4,4,4,2,4,4,1,0,9.0,neutral or dissatisfied +14947,129305,Female,Loyal Customer,42,Business travel,Business,1086,2,2,2,2,4,5,5,5,5,5,5,4,5,4,6,0.0,satisfied +14948,1340,Female,Loyal Customer,35,Business travel,Business,2856,0,4,0,4,2,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +14949,33601,Female,Loyal Customer,59,Business travel,Eco,399,3,1,1,1,1,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +14950,48888,Male,Loyal Customer,34,Business travel,Business,109,4,4,4,4,3,3,4,4,4,4,5,1,4,2,0,0.0,satisfied +14951,9311,Female,Loyal Customer,40,Business travel,Business,1500,3,3,3,3,3,3,3,3,3,3,3,1,3,4,0,4.0,neutral or dissatisfied +14952,44199,Male,Loyal Customer,27,Personal Travel,Eco,128,4,1,0,2,1,0,1,1,1,2,2,3,2,1,0,0.0,neutral or dissatisfied +14953,95385,Female,Loyal Customer,32,Personal Travel,Eco,248,3,5,3,1,5,3,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +14954,26637,Male,Loyal Customer,39,Business travel,Business,406,5,5,5,5,2,5,5,4,4,4,4,1,4,3,0,0.0,satisfied +14955,79127,Male,Loyal Customer,26,Personal Travel,Eco,164,1,4,1,3,3,1,3,3,5,4,3,1,2,3,8,14.0,neutral or dissatisfied +14956,35937,Female,disloyal Customer,25,Business travel,Eco Plus,2381,4,0,4,1,5,4,5,5,5,1,3,5,1,5,2,10.0,neutral or dissatisfied +14957,42096,Male,disloyal Customer,45,Business travel,Eco,996,3,3,3,1,5,3,5,5,4,5,1,4,4,5,0,0.0,neutral or dissatisfied +14958,91456,Male,Loyal Customer,47,Business travel,Business,3425,3,4,4,4,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +14959,119191,Female,disloyal Customer,25,Business travel,Business,331,5,0,5,1,3,5,3,3,3,4,4,3,5,3,0,0.0,satisfied +14960,42786,Male,disloyal Customer,28,Business travel,Business,1118,2,2,2,3,2,3,3,2,2,2,3,3,4,3,119,151.0,neutral or dissatisfied +14961,89796,Female,Loyal Customer,17,Personal Travel,Eco,1076,4,4,5,3,2,5,2,2,5,4,4,3,5,2,0,33.0,neutral or dissatisfied +14962,36234,Male,Loyal Customer,36,Personal Travel,Eco,496,3,4,3,3,3,3,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +14963,15554,Female,Loyal Customer,48,Business travel,Business,229,2,1,2,2,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +14964,23714,Female,Loyal Customer,48,Personal Travel,Eco,152,2,5,2,4,2,4,4,4,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +14965,70338,Male,Loyal Customer,49,Business travel,Business,986,1,1,1,1,3,5,5,5,5,5,5,4,5,4,8,0.0,satisfied +14966,106888,Female,disloyal Customer,35,Business travel,Eco,577,1,1,1,3,1,1,1,1,4,5,4,1,3,1,0,0.0,neutral or dissatisfied +14967,78589,Female,Loyal Customer,52,Business travel,Business,630,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +14968,61013,Female,Loyal Customer,36,Business travel,Business,3365,1,1,1,1,4,4,4,3,2,3,4,4,3,4,5,5.0,satisfied +14969,1759,Female,disloyal Customer,24,Business travel,Eco,364,3,4,3,4,2,3,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +14970,126294,Male,Loyal Customer,54,Personal Travel,Eco,631,5,3,5,1,5,5,5,5,1,1,4,1,3,5,0,0.0,satisfied +14971,34745,Male,Loyal Customer,33,Business travel,Business,301,3,2,5,2,3,3,3,3,1,1,2,2,3,3,0,0.0,neutral or dissatisfied +14972,42533,Male,disloyal Customer,22,Business travel,Eco,1091,1,1,1,1,5,1,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +14973,2973,Female,Loyal Customer,46,Business travel,Business,737,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,10.0,satisfied +14974,12927,Male,Loyal Customer,27,Personal Travel,Eco,563,5,4,5,4,2,5,4,2,4,2,4,5,4,2,0,0.0,satisfied +14975,40506,Female,Loyal Customer,62,Personal Travel,Eco,150,2,5,2,4,5,4,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +14976,107100,Male,Loyal Customer,47,Personal Travel,Eco,562,3,5,3,4,4,3,4,4,5,2,5,5,5,4,10,0.0,neutral or dissatisfied +14977,71700,Male,Loyal Customer,28,Business travel,Business,1197,1,1,1,1,5,5,5,5,5,4,5,4,4,5,1,0.0,satisfied +14978,16263,Male,Loyal Customer,29,Business travel,Business,748,2,5,3,5,2,1,2,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +14979,31331,Female,Loyal Customer,39,Business travel,Business,1062,2,2,2,2,5,4,2,3,3,4,3,2,3,2,0,0.0,satisfied +14980,62761,Male,disloyal Customer,39,Business travel,Eco,2367,1,1,1,3,2,1,3,2,4,3,3,3,3,2,45,42.0,neutral or dissatisfied +14981,55224,Male,Loyal Customer,41,Business travel,Business,2521,1,1,1,1,3,3,3,3,3,5,4,3,5,3,142,137.0,satisfied +14982,125609,Female,Loyal Customer,43,Business travel,Business,3585,4,2,4,4,5,4,4,4,4,3,4,3,4,5,0,0.0,satisfied +14983,60512,Male,Loyal Customer,42,Personal Travel,Eco,862,1,3,1,3,1,1,1,1,1,5,1,2,2,1,0,0.0,neutral or dissatisfied +14984,121710,Female,Loyal Customer,25,Business travel,Business,3030,3,3,3,3,3,3,3,3,1,5,4,3,3,3,72,64.0,neutral or dissatisfied +14985,29304,Male,Loyal Customer,50,Personal Travel,Eco,550,2,2,2,4,3,2,3,3,1,1,3,4,4,3,9,14.0,neutral or dissatisfied +14986,120469,Female,Loyal Customer,41,Personal Travel,Eco,366,2,5,4,3,2,4,2,2,3,4,1,1,4,2,0,0.0,neutral or dissatisfied +14987,88609,Male,Loyal Customer,41,Personal Travel,Eco,545,2,1,3,3,5,3,5,5,4,1,3,2,4,5,8,0.0,neutral or dissatisfied +14988,59231,Male,disloyal Customer,45,Business travel,Eco,649,2,1,2,2,5,2,5,5,3,5,1,1,1,5,6,0.0,neutral or dissatisfied +14989,32667,Female,disloyal Customer,20,Business travel,Eco,201,3,3,3,4,4,3,4,4,2,1,3,4,3,4,0,0.0,neutral or dissatisfied +14990,62822,Female,Loyal Customer,62,Personal Travel,Eco,2556,2,5,2,1,2,4,4,3,3,5,5,4,4,4,32,31.0,neutral or dissatisfied +14991,119358,Male,disloyal Customer,26,Business travel,Eco,2089,2,1,1,4,5,2,1,5,3,1,2,4,4,5,0,0.0,neutral or dissatisfied +14992,88224,Female,disloyal Customer,39,Business travel,Business,594,3,3,3,3,2,3,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +14993,76237,Male,disloyal Customer,22,Business travel,Eco,1175,4,4,4,1,1,4,1,1,4,5,4,4,5,1,18,22.0,neutral or dissatisfied +14994,108753,Female,Loyal Customer,60,Business travel,Business,406,3,5,5,5,2,4,3,3,3,3,3,3,3,1,1,0.0,neutral or dissatisfied +14995,110561,Male,disloyal Customer,22,Business travel,Eco,488,3,5,3,3,2,3,2,2,3,2,4,3,4,2,70,53.0,neutral or dissatisfied +14996,117023,Male,disloyal Customer,20,Business travel,Eco,304,2,2,2,4,5,2,5,5,3,5,3,1,4,5,0,2.0,neutral or dissatisfied +14997,107605,Female,Loyal Customer,45,Business travel,Business,2708,5,5,5,5,2,5,4,3,3,3,3,3,3,5,7,0.0,satisfied +14998,22344,Male,disloyal Customer,33,Business travel,Eco,143,2,0,2,5,4,2,3,4,3,3,4,5,1,4,0,0.0,neutral or dissatisfied +14999,115472,Female,disloyal Customer,27,Business travel,Eco,404,2,2,2,2,1,2,1,1,3,3,3,2,3,1,33,20.0,neutral or dissatisfied +15000,98563,Male,Loyal Customer,38,Personal Travel,Business,992,3,4,3,4,4,4,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +15001,51519,Male,Loyal Customer,48,Business travel,Eco,598,5,2,2,2,5,5,5,5,5,2,1,5,1,5,9,4.0,satisfied +15002,111279,Female,Loyal Customer,20,Personal Travel,Eco,459,1,5,1,3,4,1,5,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +15003,102853,Female,Loyal Customer,65,Personal Travel,Eco,423,1,5,1,1,5,5,4,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +15004,119252,Male,Loyal Customer,57,Business travel,Business,214,1,1,1,1,2,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +15005,43161,Male,Loyal Customer,45,Business travel,Business,2691,5,5,5,5,1,5,2,4,4,4,4,1,4,4,0,0.0,satisfied +15006,111944,Female,Loyal Customer,14,Business travel,Business,2373,5,5,5,5,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +15007,1671,Female,Loyal Customer,41,Business travel,Business,561,4,4,5,4,2,5,4,5,5,5,5,5,5,5,11,22.0,satisfied +15008,48019,Female,Loyal Customer,38,Business travel,Eco Plus,748,5,5,5,5,5,5,5,5,2,2,5,1,1,5,44,65.0,satisfied +15009,12049,Male,disloyal Customer,66,Business travel,Eco,376,3,3,3,2,1,3,1,1,4,4,4,2,1,1,0,0.0,neutral or dissatisfied +15010,24695,Male,Loyal Customer,39,Business travel,Business,2719,3,1,2,2,3,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +15011,115877,Female,Loyal Customer,39,Business travel,Business,308,3,3,3,3,3,4,4,3,3,3,3,4,3,1,23,15.0,neutral or dissatisfied +15012,41725,Male,disloyal Customer,22,Business travel,Eco,695,1,1,1,3,5,1,5,5,1,2,2,3,3,5,0,0.0,neutral or dissatisfied +15013,20862,Male,Loyal Customer,27,Personal Travel,Eco,534,2,4,2,1,4,2,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +15014,55040,Male,Loyal Customer,46,Business travel,Business,1379,3,3,3,3,2,4,5,4,4,4,4,5,4,5,7,2.0,satisfied +15015,52935,Female,Loyal Customer,31,Personal Travel,Eco,679,3,4,3,3,1,3,1,1,4,2,4,4,4,1,19,14.0,neutral or dissatisfied +15016,22477,Female,Loyal Customer,17,Personal Travel,Eco,83,2,4,0,2,2,0,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +15017,38588,Male,Loyal Customer,37,Personal Travel,Eco Plus,2586,2,5,2,3,4,2,4,4,3,2,4,5,4,4,1,0.0,neutral or dissatisfied +15018,17094,Male,Loyal Customer,59,Business travel,Eco,416,2,2,3,2,2,2,2,2,4,2,4,2,3,2,43,45.0,neutral or dissatisfied +15019,58516,Male,Loyal Customer,59,Personal Travel,Eco,719,1,4,1,5,2,1,5,2,5,3,5,3,4,2,16,30.0,neutral or dissatisfied +15020,113812,Male,disloyal Customer,37,Business travel,Eco Plus,197,1,1,1,4,1,1,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +15021,77541,Female,Loyal Customer,33,Business travel,Business,2000,4,4,4,4,3,4,4,3,3,4,3,3,3,4,48,25.0,satisfied +15022,11569,Male,disloyal Customer,22,Business travel,Eco,771,3,3,3,3,3,1,1,5,4,4,4,1,5,1,150,130.0,neutral or dissatisfied +15023,101547,Female,Loyal Customer,52,Personal Travel,Eco,345,3,4,3,3,5,4,4,4,4,3,4,3,4,4,39,26.0,neutral or dissatisfied +15024,62523,Male,Loyal Customer,30,Business travel,Business,1744,5,5,5,5,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +15025,73553,Female,disloyal Customer,24,Business travel,Business,204,5,0,5,4,4,5,4,4,3,4,4,5,4,4,0,3.0,satisfied +15026,63860,Female,Loyal Customer,39,Business travel,Business,2068,3,5,3,3,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +15027,63618,Male,Loyal Customer,53,Business travel,Business,1440,4,3,1,3,2,4,3,4,4,4,4,1,4,3,15,0.0,neutral or dissatisfied +15028,82097,Female,Loyal Customer,38,Business travel,Business,1843,5,5,5,5,5,2,5,4,4,4,4,2,4,5,0,0.0,satisfied +15029,41193,Male,Loyal Customer,21,Business travel,Business,1174,5,5,5,5,4,4,4,4,1,3,3,5,3,4,2,0.0,satisfied +15030,9041,Female,Loyal Customer,40,Business travel,Business,173,3,3,3,3,5,4,4,5,5,5,4,5,5,5,31,36.0,satisfied +15031,53930,Male,Loyal Customer,37,Business travel,Eco Plus,191,5,3,4,3,5,5,5,5,2,2,5,4,2,5,0,13.0,satisfied +15032,83355,Male,Loyal Customer,48,Business travel,Business,2650,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +15033,83294,Female,Loyal Customer,23,Personal Travel,Eco,2079,3,4,3,2,3,5,5,4,5,5,5,5,4,5,183,181.0,neutral or dissatisfied +15034,83940,Female,disloyal Customer,39,Business travel,Business,321,2,2,2,3,3,2,3,3,3,4,4,3,5,3,22,15.0,neutral or dissatisfied +15035,108118,Male,Loyal Customer,42,Business travel,Eco,990,1,0,0,3,5,1,5,5,4,3,2,2,2,5,0,17.0,neutral or dissatisfied +15036,53347,Male,disloyal Customer,42,Business travel,Eco,1327,4,4,4,4,1,4,5,1,4,3,3,1,1,1,7,6.0,neutral or dissatisfied +15037,47101,Female,Loyal Customer,54,Personal Travel,Eco,639,4,4,4,3,2,4,4,2,2,4,2,3,2,4,10,35.0,neutral or dissatisfied +15038,118545,Female,Loyal Customer,30,Business travel,Business,3544,4,4,4,4,5,5,5,5,4,2,5,4,5,5,2,6.0,satisfied +15039,66870,Male,Loyal Customer,60,Business travel,Eco Plus,331,4,3,2,3,4,4,4,4,3,4,3,3,5,4,2,0.0,satisfied +15040,46530,Male,disloyal Customer,23,Business travel,Eco,125,2,0,2,4,4,2,4,4,5,5,5,3,2,4,0,0.0,neutral or dissatisfied +15041,18428,Male,Loyal Customer,54,Business travel,Business,2901,2,2,2,2,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +15042,20719,Male,disloyal Customer,17,Business travel,Eco,707,4,4,4,3,5,4,5,5,2,4,3,2,3,5,52,65.0,neutral or dissatisfied +15043,33108,Male,Loyal Customer,36,Personal Travel,Eco,201,3,1,3,3,4,3,4,4,4,2,3,4,2,4,0,0.0,neutral or dissatisfied +15044,121314,Male,Loyal Customer,55,Personal Travel,Eco,1009,3,4,4,3,4,4,4,4,3,5,4,1,4,4,0,0.0,neutral or dissatisfied +15045,78966,Female,Loyal Customer,48,Business travel,Business,3553,5,5,5,5,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +15046,55663,Female,disloyal Customer,22,Business travel,Eco,1025,3,4,4,1,5,4,5,5,5,2,5,3,4,5,34,12.0,satisfied +15047,88310,Male,Loyal Customer,63,Business travel,Business,2756,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +15048,104161,Female,Loyal Customer,51,Business travel,Eco,349,1,2,2,2,4,3,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +15049,10873,Male,Loyal Customer,16,Business travel,Eco,316,2,2,2,2,2,3,2,2,1,1,4,4,4,2,1,0.0,neutral or dissatisfied +15050,15388,Female,Loyal Customer,32,Business travel,Business,2965,1,1,1,1,5,5,5,5,5,3,3,3,5,5,0,0.0,satisfied +15051,59868,Male,Loyal Customer,37,Business travel,Business,997,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +15052,72215,Female,Loyal Customer,53,Business travel,Business,919,5,5,4,5,5,4,5,2,2,2,2,4,2,4,0,56.0,satisfied +15053,75731,Male,Loyal Customer,29,Business travel,Eco,868,2,2,5,2,2,2,2,2,1,4,3,3,3,2,0,23.0,neutral or dissatisfied +15054,25695,Male,Loyal Customer,33,Business travel,Business,2542,5,5,5,5,5,5,5,5,1,4,2,4,4,5,0,0.0,satisfied +15055,1610,Male,Loyal Customer,17,Business travel,Business,1664,2,2,2,2,5,5,5,5,3,3,5,5,5,5,45,33.0,satisfied +15056,125540,Male,Loyal Customer,59,Business travel,Business,226,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +15057,16597,Female,Loyal Customer,14,Personal Travel,Business,1008,3,5,3,3,2,3,4,2,3,4,4,4,4,2,4,0.0,neutral or dissatisfied +15058,128215,Male,Loyal Customer,34,Business travel,Business,1672,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +15059,101461,Male,Loyal Customer,22,Business travel,Business,345,0,0,0,2,2,2,2,2,3,3,5,5,5,2,21,10.0,satisfied +15060,108760,Female,Loyal Customer,38,Business travel,Business,581,3,3,3,3,5,4,4,5,5,5,5,3,5,4,93,76.0,satisfied +15061,78957,Male,Loyal Customer,44,Business travel,Business,2630,3,2,2,2,1,3,4,3,3,2,3,3,3,1,20,36.0,neutral or dissatisfied +15062,3649,Female,Loyal Customer,45,Business travel,Business,431,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,25.0,satisfied +15063,116905,Male,disloyal Customer,28,Business travel,Business,646,5,5,5,2,2,5,2,2,4,4,4,4,5,2,0,0.0,satisfied +15064,88152,Female,Loyal Customer,51,Business travel,Business,3589,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +15065,15797,Male,disloyal Customer,42,Business travel,Eco,246,3,0,3,3,2,3,2,2,4,4,1,3,2,2,0,0.0,neutral or dissatisfied +15066,29585,Male,Loyal Customer,43,Business travel,Eco,1448,5,4,4,4,5,5,5,5,1,3,5,5,4,5,0,0.0,satisfied +15067,78639,Female,Loyal Customer,42,Business travel,Business,2172,4,4,3,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +15068,53805,Male,Loyal Customer,43,Business travel,Eco,191,5,2,2,2,5,5,5,5,3,3,5,1,3,5,12,4.0,satisfied +15069,13727,Female,Loyal Customer,43,Business travel,Eco,441,2,3,3,3,5,5,3,2,2,2,2,1,2,3,106,110.0,satisfied +15070,121701,Male,Loyal Customer,43,Business travel,Business,683,5,5,5,5,2,4,5,4,4,4,4,5,4,3,14,31.0,satisfied +15071,122432,Female,Loyal Customer,59,Business travel,Eco,416,4,3,2,2,2,4,3,3,3,4,3,2,3,1,1,0.0,satisfied +15072,987,Male,Loyal Customer,42,Business travel,Eco,309,5,3,3,3,5,5,5,5,1,2,2,3,4,5,0,0.0,satisfied +15073,43507,Male,Loyal Customer,60,Personal Travel,Eco,679,2,4,2,4,3,2,3,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +15074,56903,Male,Loyal Customer,46,Business travel,Business,2565,1,1,2,1,4,5,5,3,5,4,5,5,5,5,13,9.0,satisfied +15075,115467,Female,disloyal Customer,47,Business travel,Eco,446,2,4,2,4,1,2,1,1,3,1,3,4,4,1,11,13.0,neutral or dissatisfied +15076,97928,Male,disloyal Customer,29,Business travel,Eco,722,4,4,4,3,5,4,5,5,3,3,3,1,2,5,19,24.0,neutral or dissatisfied +15077,17340,Male,Loyal Customer,51,Business travel,Business,2110,1,1,1,1,2,3,4,4,4,4,4,3,4,5,3,8.0,satisfied +15078,40876,Male,Loyal Customer,15,Personal Travel,Eco,588,4,2,4,4,2,4,5,2,2,4,3,3,4,2,0,0.0,neutral or dissatisfied +15079,28798,Female,Loyal Customer,33,Personal Travel,Business,978,1,5,1,3,3,5,5,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +15080,41229,Male,Loyal Customer,59,Personal Travel,Eco,912,5,5,5,3,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +15081,109602,Female,Loyal Customer,50,Personal Travel,Eco Plus,861,1,4,1,3,5,4,4,5,5,1,1,5,5,4,28,25.0,neutral or dissatisfied +15082,19024,Male,Loyal Customer,37,Personal Travel,Eco,788,2,5,2,3,2,2,2,4,3,5,5,2,5,2,151,173.0,neutral or dissatisfied +15083,127895,Male,Loyal Customer,39,Business travel,Business,1671,4,4,4,4,5,4,5,4,4,4,4,4,4,4,2,0.0,satisfied +15084,93070,Female,Loyal Customer,51,Personal Travel,Eco,297,5,1,5,4,1,4,3,1,1,5,1,1,1,2,0,0.0,satisfied +15085,105701,Female,Loyal Customer,48,Business travel,Business,842,3,3,3,3,4,4,4,4,4,4,4,3,4,4,7,3.0,satisfied +15086,23666,Male,disloyal Customer,17,Business travel,Eco,251,3,5,3,1,3,3,3,3,1,1,5,4,4,3,0,0.0,neutral or dissatisfied +15087,8649,Male,Loyal Customer,41,Business travel,Business,304,0,0,0,3,5,4,4,2,2,5,5,3,2,3,0,0.0,satisfied +15088,56570,Male,Loyal Customer,43,Business travel,Business,2833,3,3,3,3,3,4,4,5,5,5,5,5,5,4,3,0.0,satisfied +15089,58013,Female,Loyal Customer,30,Business travel,Business,1721,3,3,5,3,4,4,4,4,5,5,4,5,4,4,4,1.0,satisfied +15090,123881,Male,disloyal Customer,16,Business travel,Eco,544,5,0,5,4,3,5,3,3,2,2,4,5,3,3,0,0.0,satisfied +15091,95590,Female,Loyal Customer,26,Business travel,Business,3657,3,3,3,3,4,4,4,4,4,5,4,4,4,4,5,8.0,satisfied +15092,93994,Female,disloyal Customer,19,Business travel,Eco Plus,1218,3,1,3,3,3,3,3,3,3,4,4,4,3,3,45,32.0,neutral or dissatisfied +15093,113711,Male,Loyal Customer,66,Personal Travel,Eco,236,3,3,3,2,2,3,2,2,1,1,2,5,1,2,0,0.0,neutral or dissatisfied +15094,28184,Female,Loyal Customer,15,Personal Travel,Eco,859,4,4,4,2,4,4,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +15095,72897,Male,Loyal Customer,39,Business travel,Business,1768,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +15096,93608,Male,Loyal Customer,17,Business travel,Business,704,2,2,2,2,2,2,2,2,4,2,5,5,4,2,0,0.0,satisfied +15097,30965,Male,Loyal Customer,26,Business travel,Eco Plus,836,5,1,1,1,5,5,5,5,3,3,1,3,3,5,26,48.0,satisfied +15098,6404,Female,Loyal Customer,70,Personal Travel,Eco,296,3,2,3,3,2,2,2,5,5,3,2,1,5,3,0,0.0,neutral or dissatisfied +15099,42189,Male,Loyal Customer,33,Business travel,Eco,329,5,4,2,2,5,4,5,5,2,4,4,2,4,5,49,37.0,satisfied +15100,50267,Female,disloyal Customer,35,Business travel,Eco,86,1,0,0,2,3,0,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +15101,41927,Female,Loyal Customer,53,Personal Travel,Eco,129,2,0,0,3,4,4,5,2,2,0,2,3,2,3,16,16.0,neutral or dissatisfied +15102,70133,Male,disloyal Customer,26,Business travel,Eco,460,1,2,2,3,1,2,1,1,3,5,4,1,3,1,17,13.0,neutral or dissatisfied +15103,54683,Male,Loyal Customer,17,Business travel,Business,854,4,4,1,4,5,5,5,5,4,5,2,4,4,5,0,0.0,satisfied +15104,38852,Female,Loyal Customer,41,Business travel,Business,2153,2,3,3,3,1,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +15105,8364,Female,Loyal Customer,39,Business travel,Business,2001,2,2,2,2,4,5,4,4,4,5,4,3,4,5,27,19.0,satisfied +15106,86610,Male,Loyal Customer,48,Business travel,Business,746,3,3,2,3,3,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +15107,51466,Male,Loyal Customer,28,Business travel,Eco Plus,89,0,0,0,4,3,0,3,3,3,5,2,1,1,3,0,0.0,satisfied +15108,25837,Female,disloyal Customer,37,Business travel,Eco,484,1,1,1,2,2,1,2,2,4,5,2,1,3,2,15,0.0,neutral or dissatisfied +15109,75136,Female,Loyal Customer,50,Business travel,Business,1726,4,4,4,4,2,5,5,4,4,4,4,5,4,4,45,19.0,satisfied +15110,97495,Female,Loyal Customer,16,Personal Travel,Eco,670,1,5,1,5,3,1,3,3,3,4,4,3,4,3,14,4.0,neutral or dissatisfied +15111,24699,Male,disloyal Customer,22,Business travel,Eco,397,2,3,2,3,5,2,5,5,2,5,5,1,2,5,87,103.0,neutral or dissatisfied +15112,72441,Male,Loyal Customer,34,Business travel,Business,3875,3,3,3,3,5,5,4,5,5,5,5,3,5,3,0,8.0,satisfied +15113,59165,Male,Loyal Customer,72,Business travel,Eco Plus,346,1,3,3,3,1,1,1,1,2,3,3,1,3,1,94,102.0,neutral or dissatisfied +15114,59009,Female,Loyal Customer,56,Business travel,Business,1846,5,5,5,5,3,3,4,2,2,3,2,5,2,3,8,14.0,satisfied +15115,97579,Female,Loyal Customer,17,Business travel,Business,448,3,1,1,1,3,3,3,3,3,5,3,4,3,3,54,46.0,neutral or dissatisfied +15116,121384,Female,Loyal Customer,67,Personal Travel,Eco,2279,2,1,2,1,2,3,3,4,2,1,1,3,2,3,0,12.0,neutral or dissatisfied +15117,67429,Male,disloyal Customer,27,Business travel,Eco,641,3,3,3,4,3,3,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +15118,52873,Female,Loyal Customer,44,Business travel,Eco,1024,1,2,2,2,4,4,4,1,1,1,1,2,1,3,8,25.0,neutral or dissatisfied +15119,24705,Female,Loyal Customer,22,Business travel,Business,397,4,5,1,1,4,4,4,4,3,4,3,1,4,4,21,9.0,neutral or dissatisfied +15120,41385,Female,disloyal Customer,33,Business travel,Eco,563,2,0,2,2,3,2,4,3,4,5,1,3,4,3,0,0.0,neutral or dissatisfied +15121,14448,Female,disloyal Customer,44,Business travel,Eco,674,4,4,4,2,4,4,4,4,5,3,5,1,1,4,0,0.0,neutral or dissatisfied +15122,113704,Male,Loyal Customer,20,Personal Travel,Eco,414,4,5,4,1,3,4,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +15123,41060,Female,disloyal Customer,33,Business travel,Business,191,3,3,3,1,5,3,5,5,3,2,4,3,4,5,1,0.0,neutral or dissatisfied +15124,58471,Male,Loyal Customer,41,Business travel,Business,1749,3,3,3,3,4,4,5,4,4,4,4,5,4,4,14,25.0,satisfied +15125,101188,Female,Loyal Customer,67,Personal Travel,Eco,1090,4,1,4,2,5,1,1,2,2,4,2,4,2,4,50,46.0,satisfied +15126,94798,Male,Loyal Customer,51,Business travel,Business,323,3,3,3,3,3,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +15127,114936,Female,Loyal Customer,59,Business travel,Business,390,4,4,4,4,5,5,5,5,5,5,5,5,5,3,1,0.0,satisfied +15128,44038,Female,Loyal Customer,36,Business travel,Eco,311,2,2,2,2,2,2,2,2,3,1,2,1,3,2,0,0.0,satisfied +15129,38855,Female,disloyal Customer,41,Business travel,Eco,2153,3,3,3,3,3,3,3,3,3,3,4,4,3,3,5,0.0,neutral or dissatisfied +15130,111372,Male,Loyal Customer,53,Business travel,Business,2447,3,3,3,3,3,5,4,4,4,4,4,5,4,4,14,30.0,satisfied +15131,67755,Male,Loyal Customer,32,Business travel,Business,1171,2,2,2,2,2,2,2,2,2,3,3,3,3,2,0,0.0,neutral or dissatisfied +15132,80012,Female,Loyal Customer,44,Personal Travel,Eco,950,4,5,4,3,1,5,5,4,4,4,4,2,4,3,0,93.0,neutral or dissatisfied +15133,91481,Female,Loyal Customer,46,Personal Travel,Eco,859,5,5,5,4,2,5,4,1,1,5,1,5,1,3,0,4.0,satisfied +15134,86143,Female,disloyal Customer,20,Business travel,Business,356,4,4,4,2,3,4,3,3,4,5,5,4,4,3,0,0.0,satisfied +15135,115745,Female,Loyal Customer,46,Business travel,Business,371,1,3,2,2,4,2,2,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +15136,87615,Male,Loyal Customer,21,Business travel,Business,3753,3,3,3,3,5,4,5,5,3,2,4,5,5,5,0,0.0,satisfied +15137,55619,Female,Loyal Customer,60,Personal Travel,Eco Plus,404,2,3,2,3,5,2,5,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +15138,23306,Female,disloyal Customer,28,Business travel,Eco,809,3,3,3,4,1,3,1,1,2,2,5,2,4,1,0,0.0,neutral or dissatisfied +15139,105942,Female,disloyal Customer,7,Business travel,Eco,1024,4,4,4,3,1,4,1,1,2,3,3,3,2,1,0,0.0,neutral or dissatisfied +15140,41433,Male,Loyal Customer,61,Personal Travel,Eco,809,3,3,3,4,4,3,4,4,1,2,1,4,2,4,82,70.0,neutral or dissatisfied +15141,49231,Male,Loyal Customer,36,Business travel,Business,2410,1,1,1,1,5,1,5,4,4,4,3,3,4,5,36,31.0,satisfied +15142,5258,Male,disloyal Customer,44,Business travel,Eco,383,3,3,3,2,4,3,4,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +15143,124056,Female,Loyal Customer,28,Business travel,Business,2153,3,3,3,3,4,4,4,4,3,4,3,5,4,4,14,0.0,satisfied +15144,51221,Female,Loyal Customer,63,Business travel,Eco Plus,337,1,4,4,4,2,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +15145,3290,Female,Loyal Customer,69,Personal Travel,Eco,479,3,4,2,1,3,3,2,5,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +15146,71271,Male,Loyal Customer,69,Personal Travel,Eco,733,3,4,3,3,1,3,1,1,1,5,5,4,5,1,0,0.0,neutral or dissatisfied +15147,21709,Male,Loyal Customer,9,Personal Travel,Eco,746,2,5,2,3,3,2,1,3,3,5,5,3,4,3,50,32.0,neutral or dissatisfied +15148,49643,Female,Loyal Customer,37,Business travel,Eco,86,3,1,5,5,3,3,3,3,2,5,5,5,5,3,0,0.0,satisfied +15149,118240,Female,Loyal Customer,23,Personal Travel,Eco,1587,4,5,4,2,2,4,2,2,3,4,5,5,5,2,7,6.0,neutral or dissatisfied +15150,104485,Male,Loyal Customer,56,Business travel,Business,3081,4,4,4,4,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +15151,12569,Male,Loyal Customer,30,Business travel,Eco Plus,871,1,0,0,3,5,0,5,5,1,3,4,1,3,5,45,41.0,neutral or dissatisfied +15152,91631,Male,Loyal Customer,29,Business travel,Business,3610,1,1,1,1,5,5,5,5,5,4,4,4,5,5,3,0.0,satisfied +15153,69866,Male,Loyal Customer,12,Personal Travel,Eco,1055,1,5,1,5,1,2,2,4,5,5,5,2,3,2,259,232.0,neutral or dissatisfied +15154,89393,Male,Loyal Customer,47,Business travel,Business,134,5,5,2,5,2,4,4,5,5,5,4,3,5,5,11,6.0,satisfied +15155,124159,Female,Loyal Customer,30,Business travel,Business,2133,4,4,4,4,5,5,5,5,5,4,4,4,4,5,0,17.0,satisfied +15156,93863,Female,Loyal Customer,31,Business travel,Business,3255,4,4,4,4,4,4,4,4,5,5,4,3,4,4,45,53.0,satisfied +15157,77244,Male,Loyal Customer,55,Business travel,Business,1590,5,5,3,5,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +15158,119879,Female,Loyal Customer,63,Personal Travel,Eco,936,2,4,2,2,4,4,5,2,2,2,2,5,2,3,7,4.0,neutral or dissatisfied +15159,7727,Female,Loyal Customer,45,Personal Travel,Eco,859,3,2,3,4,5,3,3,4,4,3,4,2,4,4,17,0.0,neutral or dissatisfied +15160,6688,Female,Loyal Customer,37,Business travel,Eco,403,4,2,2,2,4,4,4,4,1,2,3,2,3,4,75,69.0,neutral or dissatisfied +15161,37630,Male,Loyal Customer,16,Personal Travel,Eco,1102,2,4,2,4,3,2,3,3,3,5,4,5,2,3,12,3.0,neutral or dissatisfied +15162,77973,Female,Loyal Customer,58,Business travel,Business,3668,5,5,5,5,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +15163,60048,Female,Loyal Customer,58,Business travel,Eco Plus,1068,2,3,3,3,4,4,3,2,2,2,2,3,2,1,8,7.0,neutral or dissatisfied +15164,72567,Male,Loyal Customer,44,Business travel,Business,564,5,5,5,5,4,5,2,4,4,4,4,4,4,3,0,0.0,satisfied +15165,43805,Male,Loyal Customer,13,Personal Travel,Eco,448,3,4,3,1,5,3,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +15166,5920,Female,Loyal Customer,39,Personal Travel,Eco,67,5,4,5,1,5,5,5,5,4,2,5,5,4,5,2,4.0,satisfied +15167,29590,Male,Loyal Customer,11,Business travel,Eco,1448,4,4,4,4,4,4,5,4,1,1,5,1,1,4,0,0.0,satisfied +15168,63325,Male,Loyal Customer,40,Business travel,Business,3025,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +15169,105020,Male,Loyal Customer,47,Business travel,Business,3169,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +15170,5075,Male,Loyal Customer,43,Business travel,Business,223,1,3,4,3,2,2,3,2,2,2,1,3,2,1,68,124.0,neutral or dissatisfied +15171,6296,Female,disloyal Customer,30,Business travel,Eco Plus,585,1,2,2,3,5,2,5,5,2,5,4,4,3,5,59,81.0,neutral or dissatisfied +15172,112216,Female,Loyal Customer,55,Business travel,Business,1199,5,5,5,5,2,5,5,2,2,2,2,3,2,4,1,0.0,satisfied +15173,57129,Male,Loyal Customer,59,Personal Travel,Eco,1222,3,5,3,4,2,3,2,2,5,2,3,5,5,2,0,0.0,neutral or dissatisfied +15174,40746,Male,Loyal Customer,30,Business travel,Business,3066,1,1,1,1,4,4,4,4,2,1,5,1,2,4,0,0.0,satisfied +15175,46208,Female,disloyal Customer,21,Business travel,Business,594,5,0,4,4,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +15176,71592,Female,Loyal Customer,42,Business travel,Business,2945,1,1,3,1,5,4,5,5,5,5,5,5,5,4,6,5.0,satisfied +15177,20926,Male,Loyal Customer,41,Business travel,Eco,851,1,5,5,5,1,1,1,1,2,1,4,4,4,1,43,56.0,neutral or dissatisfied +15178,78587,Female,Loyal Customer,53,Personal Travel,Eco,630,3,2,4,3,3,3,4,4,4,4,4,3,4,1,32,19.0,neutral or dissatisfied +15179,8104,Female,Loyal Customer,55,Business travel,Business,530,1,1,3,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +15180,107253,Male,disloyal Customer,24,Business travel,Business,283,5,5,5,4,4,5,4,4,5,3,5,3,4,4,2,14.0,satisfied +15181,24545,Female,Loyal Customer,26,Business travel,Business,3333,3,3,1,3,5,5,5,5,2,1,1,5,5,5,0,0.0,satisfied +15182,82466,Male,Loyal Customer,37,Personal Travel,Eco,509,4,4,4,5,3,4,5,3,3,3,4,4,4,3,5,0.0,neutral or dissatisfied +15183,90083,Male,disloyal Customer,23,Business travel,Business,1145,4,0,4,2,1,4,1,1,3,2,5,4,5,1,0,0.0,satisfied +15184,94620,Male,disloyal Customer,22,Business travel,Eco,239,3,3,3,4,3,3,3,3,2,3,4,3,3,3,59,51.0,neutral or dissatisfied +15185,122295,Female,Loyal Customer,16,Personal Travel,Eco,603,2,4,2,3,2,2,2,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +15186,14017,Male,Loyal Customer,34,Business travel,Business,182,2,2,2,2,4,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +15187,128774,Female,Loyal Customer,61,Personal Travel,Eco,550,4,5,5,3,2,4,4,3,3,5,3,5,3,3,0,0.0,satisfied +15188,60165,Female,Loyal Customer,27,Personal Travel,Eco,1005,3,4,3,2,5,3,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +15189,129259,Female,disloyal Customer,22,Business travel,Eco,1235,2,2,2,4,4,2,4,4,2,1,4,2,3,4,0,0.0,neutral or dissatisfied +15190,46306,Female,Loyal Customer,33,Business travel,Business,3699,3,3,3,3,4,3,3,3,3,3,3,4,3,3,14,15.0,neutral or dissatisfied +15191,92386,Female,Loyal Customer,21,Business travel,Business,1947,4,4,4,4,4,4,4,4,5,5,5,4,4,4,74,65.0,satisfied +15192,58482,Female,disloyal Customer,33,Business travel,Business,719,2,2,2,1,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +15193,121169,Male,Loyal Customer,66,Personal Travel,Eco,2370,4,4,4,3,4,4,4,3,3,5,4,4,3,4,43,162.0,satisfied +15194,64201,Male,disloyal Customer,40,Business travel,Eco,453,2,0,1,2,3,1,3,3,3,2,5,1,3,3,5,5.0,neutral or dissatisfied +15195,1081,Male,Loyal Customer,62,Personal Travel,Eco,164,4,3,4,3,4,4,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +15196,33784,Male,disloyal Customer,41,Business travel,Eco,588,3,1,3,3,3,3,3,3,4,5,4,3,3,3,40,23.0,neutral or dissatisfied +15197,71737,Female,Loyal Customer,45,Business travel,Business,1652,3,1,1,1,1,3,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +15198,47158,Male,Loyal Customer,29,Business travel,Business,2468,4,4,4,4,3,3,3,3,5,2,5,2,4,3,0,0.0,satisfied +15199,108647,Male,Loyal Customer,48,Personal Travel,Eco,762,4,5,5,2,4,5,4,4,4,4,4,3,5,4,54,34.0,satisfied +15200,53501,Male,Loyal Customer,15,Personal Travel,Eco,2358,3,5,3,2,3,3,3,4,5,4,5,3,3,3,27,37.0,neutral or dissatisfied +15201,10862,Male,Loyal Customer,40,Business travel,Business,2822,1,1,1,1,3,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +15202,56152,Female,Loyal Customer,48,Business travel,Business,1400,3,3,2,3,4,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +15203,78517,Male,Loyal Customer,69,Personal Travel,Eco,526,0,4,0,4,1,0,1,1,3,4,5,5,5,1,14,0.0,satisfied +15204,19996,Female,Loyal Customer,45,Business travel,Eco,599,4,5,5,5,5,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +15205,16283,Male,Loyal Customer,36,Personal Travel,Eco,748,1,5,1,2,4,1,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +15206,13820,Male,disloyal Customer,23,Business travel,Eco,628,4,4,4,3,2,4,2,2,2,1,3,1,2,2,0,0.0,satisfied +15207,87577,Female,Loyal Customer,64,Personal Travel,Eco,432,1,5,2,2,1,4,1,4,4,2,4,3,4,4,12,12.0,neutral or dissatisfied +15208,18413,Male,Loyal Customer,52,Business travel,Business,750,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,6.0,satisfied +15209,29394,Male,Loyal Customer,31,Business travel,Business,2355,3,3,4,3,5,5,5,4,4,3,2,5,3,5,0,5.0,satisfied +15210,29013,Female,Loyal Customer,49,Business travel,Eco,205,1,5,5,5,4,1,1,1,1,1,1,4,1,2,21,7.0,neutral or dissatisfied +15211,49601,Female,Loyal Customer,49,Business travel,Eco,207,5,4,4,4,2,1,3,5,5,5,5,1,5,2,0,0.0,satisfied +15212,127126,Female,Loyal Customer,17,Personal Travel,Eco,304,3,5,3,3,5,3,5,5,5,2,5,4,4,5,1,0.0,neutral or dissatisfied +15213,119849,Male,Loyal Customer,38,Business travel,Business,2880,1,1,1,1,1,1,2,5,5,5,5,4,5,2,0,6.0,satisfied +15214,64769,Male,Loyal Customer,53,Business travel,Business,3680,5,5,5,5,2,5,5,4,4,4,5,5,4,4,21,20.0,satisfied +15215,38234,Female,disloyal Customer,18,Business travel,Eco,1111,5,5,5,2,4,5,4,4,5,2,5,1,4,4,39,52.0,satisfied +15216,126262,Female,disloyal Customer,34,Business travel,Eco,507,2,2,2,4,3,2,3,3,3,1,3,4,4,3,0,15.0,neutral or dissatisfied +15217,463,Female,Loyal Customer,44,Business travel,Business,2500,1,1,1,1,3,4,4,5,5,5,5,5,5,3,22,12.0,satisfied +15218,74422,Female,Loyal Customer,41,Business travel,Business,3612,1,1,1,1,4,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +15219,92256,Male,Loyal Customer,64,Personal Travel,Eco,1670,4,1,4,4,1,4,1,1,2,4,2,3,4,1,0,0.0,neutral or dissatisfied +15220,35318,Male,Loyal Customer,33,Business travel,Business,2690,5,1,5,5,2,2,2,2,2,3,2,1,5,2,35,38.0,satisfied +15221,45345,Female,Loyal Customer,17,Personal Travel,Eco,222,2,1,2,4,4,2,4,4,3,2,4,2,4,4,0,0.0,neutral or dissatisfied +15222,12004,Female,Loyal Customer,24,Personal Travel,Eco Plus,643,2,4,1,1,1,1,1,1,5,5,4,3,4,1,0,2.0,neutral or dissatisfied +15223,99162,Male,Loyal Customer,50,Business travel,Business,986,3,3,1,3,4,4,4,4,5,4,4,4,5,4,186,,satisfied +15224,102734,Female,Loyal Customer,39,Personal Travel,Eco,365,3,4,3,5,5,3,1,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +15225,8538,Male,disloyal Customer,27,Business travel,Business,109,3,3,3,1,1,3,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +15226,23118,Female,Loyal Customer,32,Business travel,Eco,300,5,2,2,2,5,5,5,5,4,4,2,4,1,5,28,21.0,satisfied +15227,57203,Female,Loyal Customer,39,Business travel,Business,1514,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +15228,17073,Male,Loyal Customer,15,Business travel,Business,651,5,5,5,5,5,5,5,5,4,4,3,5,4,5,0,0.0,satisfied +15229,91990,Female,disloyal Customer,25,Business travel,Eco,236,1,1,1,4,5,1,5,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +15230,117246,Female,Loyal Customer,25,Personal Travel,Eco,304,2,5,2,3,3,2,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +15231,36809,Female,disloyal Customer,44,Business travel,Eco,2300,1,1,1,3,2,1,2,2,1,5,5,3,1,2,17,0.0,neutral or dissatisfied +15232,62611,Female,Loyal Customer,36,Personal Travel,Eco,1726,2,5,2,1,5,2,5,5,2,4,3,2,1,5,0,0.0,neutral or dissatisfied +15233,58368,Male,Loyal Customer,62,Personal Travel,Eco Plus,599,2,3,2,3,4,2,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +15234,21241,Male,Loyal Customer,29,Personal Travel,Eco,192,4,5,4,3,5,4,5,5,5,4,3,2,4,5,15,8.0,neutral or dissatisfied +15235,56791,Female,disloyal Customer,39,Business travel,Business,1605,3,3,3,3,3,3,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +15236,6055,Female,Loyal Customer,70,Personal Travel,Eco,925,3,4,3,2,4,4,5,5,5,3,5,5,5,4,9,24.0,neutral or dissatisfied +15237,121801,Female,Loyal Customer,48,Business travel,Business,3076,2,2,2,2,2,5,5,5,5,4,5,5,5,4,62,40.0,satisfied +15238,98539,Male,Loyal Customer,50,Personal Travel,Eco,402,4,4,3,3,3,3,3,3,4,4,4,1,4,3,30,18.0,neutral or dissatisfied +15239,127299,Female,Loyal Customer,40,Business travel,Business,1979,1,1,5,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +15240,53502,Male,Loyal Customer,35,Personal Travel,Eco,2419,3,3,3,4,4,3,4,4,1,5,4,4,3,4,18,0.0,neutral or dissatisfied +15241,44821,Female,Loyal Customer,29,Business travel,Eco Plus,491,0,0,0,1,1,0,1,1,3,4,5,3,3,1,6,0.0,satisfied +15242,110951,Female,Loyal Customer,44,Personal Travel,Eco Plus,545,1,4,3,2,1,1,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +15243,77941,Male,disloyal Customer,21,Business travel,Business,332,4,0,4,2,5,4,5,5,4,2,4,5,5,5,41,27.0,satisfied +15244,118017,Female,Loyal Customer,29,Personal Travel,Eco,1037,3,5,3,4,4,3,4,4,5,5,4,3,4,4,7,2.0,neutral or dissatisfied +15245,59784,Female,Loyal Customer,63,Personal Travel,Eco,895,1,4,2,3,4,5,4,4,4,2,4,5,4,5,1,0.0,neutral or dissatisfied +15246,5309,Male,Loyal Customer,16,Personal Travel,Eco,285,2,4,2,1,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +15247,123398,Male,Loyal Customer,41,Business travel,Business,1337,1,1,2,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +15248,22765,Male,Loyal Customer,48,Business travel,Business,1665,4,4,4,4,1,3,5,3,3,4,5,3,3,5,22,7.0,satisfied +15249,86799,Male,Loyal Customer,45,Business travel,Business,3067,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +15250,63886,Female,Loyal Customer,25,Business travel,Business,3135,3,5,5,5,3,2,3,3,4,3,2,4,3,3,0,0.0,neutral or dissatisfied +15251,122925,Male,Loyal Customer,22,Personal Travel,Business,631,3,5,3,1,2,3,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +15252,33691,Female,Loyal Customer,42,Business travel,Eco,814,5,1,1,1,2,1,5,5,5,5,5,2,5,2,6,0.0,satisfied +15253,91380,Male,Loyal Customer,43,Business travel,Business,2342,3,3,3,3,5,5,5,4,4,5,4,5,5,5,5,19.0,satisfied +15254,111644,Male,Loyal Customer,61,Personal Travel,Eco,1558,4,4,4,3,2,4,5,2,3,2,4,3,5,2,6,3.0,satisfied +15255,119413,Female,Loyal Customer,58,Business travel,Business,3634,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +15256,1639,Female,Loyal Customer,8,Personal Travel,Eco Plus,999,1,4,1,4,4,1,4,4,4,1,4,2,4,4,5,11.0,neutral or dissatisfied +15257,117382,Male,Loyal Customer,49,Business travel,Business,2928,1,2,1,1,4,5,5,4,4,4,4,5,4,3,27,22.0,satisfied +15258,96687,Male,Loyal Customer,53,Business travel,Business,2989,1,1,1,1,5,5,5,2,2,2,2,3,2,3,11,1.0,satisfied +15259,54280,Female,Loyal Customer,19,Business travel,Eco Plus,1222,5,1,1,1,5,5,5,5,1,4,5,1,1,5,0,0.0,satisfied +15260,65074,Female,Loyal Customer,7,Personal Travel,Eco,190,2,3,0,2,2,0,2,2,5,2,4,2,5,2,6,0.0,neutral or dissatisfied +15261,1279,Female,Loyal Customer,37,Personal Travel,Eco,247,3,5,3,2,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +15262,93299,Male,Loyal Customer,27,Personal Travel,Eco Plus,867,2,3,2,1,2,2,2,2,4,4,4,1,1,2,0,0.0,neutral or dissatisfied +15263,95238,Female,Loyal Customer,7,Personal Travel,Eco,458,2,3,2,2,2,2,2,2,1,2,2,4,5,2,30,37.0,neutral or dissatisfied +15264,13671,Female,Loyal Customer,67,Personal Travel,Eco,462,5,5,5,4,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +15265,2363,Male,Loyal Customer,42,Business travel,Business,3043,3,3,3,3,5,4,5,4,4,5,4,5,4,5,2,0.0,satisfied +15266,88807,Male,Loyal Customer,50,Business travel,Business,2924,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +15267,124940,Male,Loyal Customer,48,Personal Travel,Eco,728,2,4,2,2,4,2,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +15268,69012,Female,Loyal Customer,41,Business travel,Business,1389,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +15269,30646,Male,disloyal Customer,23,Business travel,Eco,770,4,4,4,3,3,4,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +15270,89140,Female,Loyal Customer,28,Business travel,Business,1947,1,1,1,1,3,4,3,3,3,2,5,3,4,3,1,0.0,satisfied +15271,65551,Female,Loyal Customer,39,Business travel,Business,2477,3,3,3,3,2,4,5,5,5,5,4,5,5,5,7,7.0,satisfied +15272,121856,Female,disloyal Customer,42,Business travel,Eco,366,2,2,2,3,1,2,1,1,1,5,4,2,4,1,0,0.0,neutral or dissatisfied +15273,41859,Female,Loyal Customer,23,Business travel,Eco,483,3,1,1,1,3,3,1,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +15274,94292,Female,disloyal Customer,32,Business travel,Business,248,3,3,3,3,1,3,1,1,5,4,4,3,5,1,31,29.0,neutral or dissatisfied +15275,55407,Female,Loyal Customer,32,Business travel,Eco,1558,2,4,4,4,2,2,2,2,4,2,3,4,4,2,52,25.0,neutral or dissatisfied +15276,25923,Male,Loyal Customer,28,Business travel,Eco,594,4,4,4,4,4,4,4,4,1,2,3,1,4,4,42,15.0,neutral or dissatisfied +15277,46363,Female,Loyal Customer,36,Business travel,Business,2675,1,1,1,1,3,1,4,3,3,3,3,1,3,4,1,0.0,satisfied +15278,67757,Male,disloyal Customer,14,Business travel,Eco,1188,1,1,1,3,2,1,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +15279,107492,Male,Loyal Customer,42,Business travel,Business,1812,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +15280,6811,Male,Loyal Customer,56,Personal Travel,Eco,224,1,5,0,1,4,0,4,4,4,2,5,4,5,4,42,46.0,neutral or dissatisfied +15281,48549,Female,Loyal Customer,11,Personal Travel,Eco,850,4,5,4,1,3,4,3,3,3,3,4,5,5,3,0,19.0,neutral or dissatisfied +15282,65440,Male,Loyal Customer,44,Business travel,Business,3781,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,14.0,satisfied +15283,47291,Male,Loyal Customer,47,Business travel,Business,1957,5,5,5,5,1,4,1,3,3,3,3,2,3,5,0,3.0,satisfied +15284,94907,Male,disloyal Customer,20,Business travel,Eco,293,2,5,2,4,2,2,2,2,3,5,5,3,4,2,10,11.0,neutral or dissatisfied +15285,85643,Female,Loyal Customer,24,Business travel,Eco Plus,259,2,4,4,4,2,2,3,2,1,2,3,1,3,2,0,0.0,neutral or dissatisfied +15286,121307,Female,disloyal Customer,8,Business travel,Eco,1009,4,4,4,3,3,4,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +15287,124928,Male,Loyal Customer,19,Personal Travel,Eco,728,3,5,4,3,2,4,2,2,1,4,2,3,5,2,0,17.0,neutral or dissatisfied +15288,95139,Female,Loyal Customer,59,Personal Travel,Eco,293,4,5,4,1,3,5,5,1,1,4,4,3,1,5,42,26.0,neutral or dissatisfied +15289,95795,Male,Loyal Customer,54,Business travel,Business,3758,5,5,5,5,3,5,4,4,4,4,4,4,4,5,43,37.0,satisfied +15290,15613,Male,Loyal Customer,13,Personal Travel,Eco,292,4,5,4,3,1,4,3,1,3,2,5,3,5,1,0,0.0,satisfied +15291,111031,Female,Loyal Customer,37,Business travel,Eco,197,2,5,5,5,2,2,2,2,1,3,3,3,3,2,3,11.0,neutral or dissatisfied +15292,76482,Male,disloyal Customer,23,Business travel,Business,516,5,0,5,3,4,5,2,4,5,2,5,5,5,4,0,0.0,satisfied +15293,90705,Male,disloyal Customer,49,Business travel,Business,646,4,4,4,3,5,4,5,5,4,4,4,5,5,5,5,5.0,satisfied +15294,40925,Male,Loyal Customer,37,Business travel,Eco Plus,574,4,4,4,4,4,4,4,4,5,4,4,1,4,4,5,5.0,satisfied +15295,6023,Male,Loyal Customer,53,Business travel,Eco,690,1,0,0,3,3,1,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +15296,83734,Female,Loyal Customer,12,Personal Travel,Eco Plus,1027,2,5,2,1,3,2,3,3,4,2,4,4,5,3,17,0.0,neutral or dissatisfied +15297,52572,Male,Loyal Customer,36,Business travel,Business,3403,2,5,4,4,4,3,3,4,4,3,2,1,4,4,0,0.0,neutral or dissatisfied +15298,57733,Male,disloyal Customer,30,Business travel,Eco,867,1,1,1,3,1,1,1,1,2,4,1,4,3,1,3,16.0,neutral or dissatisfied +15299,87118,Male,Loyal Customer,22,Personal Travel,Eco,594,4,4,4,3,2,4,2,2,4,2,4,4,4,2,2,0.0,neutral or dissatisfied +15300,59681,Female,Loyal Customer,38,Personal Travel,Eco,854,3,4,3,1,3,3,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +15301,44441,Female,Loyal Customer,45,Business travel,Business,420,2,2,2,2,1,1,4,5,5,5,5,3,5,2,27,22.0,satisfied +15302,119066,Male,Loyal Customer,45,Business travel,Business,1107,3,5,5,5,3,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +15303,98682,Female,Loyal Customer,46,Personal Travel,Eco,992,1,2,1,1,1,2,2,4,4,1,2,2,4,1,28,46.0,neutral or dissatisfied +15304,53433,Male,Loyal Customer,39,Business travel,Eco,2442,4,1,2,1,5,4,4,2,4,4,5,4,2,4,5,18.0,satisfied +15305,111931,Male,disloyal Customer,25,Business travel,Business,533,1,2,1,2,4,1,4,4,1,1,2,4,2,4,17,12.0,neutral or dissatisfied +15306,83203,Female,Loyal Customer,44,Personal Travel,Eco,1123,1,4,1,4,5,4,5,3,3,1,4,4,3,5,21,0.0,neutral or dissatisfied +15307,49575,Male,Loyal Customer,48,Business travel,Business,3702,1,1,4,1,2,3,4,5,5,5,4,2,5,5,0,0.0,satisfied +15308,74648,Female,Loyal Customer,33,Personal Travel,Eco,1171,2,5,2,3,3,2,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +15309,87651,Male,disloyal Customer,29,Business travel,Business,591,0,0,0,2,3,0,3,3,3,5,5,3,4,3,0,2.0,satisfied +15310,26215,Male,Loyal Customer,23,Personal Travel,Eco,515,1,4,3,1,1,3,1,1,3,3,5,4,4,1,17,4.0,neutral or dissatisfied +15311,90732,Male,Loyal Customer,57,Business travel,Business,3282,5,5,4,5,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +15312,32848,Female,Loyal Customer,47,Personal Travel,Eco,163,0,1,0,1,5,2,1,5,5,0,5,2,5,2,40,48.0,satisfied +15313,35252,Female,disloyal Customer,42,Business travel,Eco,950,2,1,1,2,5,1,3,5,2,5,3,2,2,5,5,27.0,neutral or dissatisfied +15314,37226,Male,Loyal Customer,44,Business travel,Business,1011,3,3,3,3,4,5,5,4,4,4,4,5,4,4,5,1.0,satisfied +15315,61206,Male,Loyal Customer,33,Business travel,Business,967,3,2,3,3,5,5,5,5,3,5,5,3,4,5,17,23.0,satisfied +15316,22435,Female,Loyal Customer,42,Personal Travel,Eco,83,2,5,2,4,4,5,5,2,2,2,2,5,2,3,0,7.0,neutral or dissatisfied +15317,55064,Male,disloyal Customer,27,Business travel,Eco,1635,4,4,4,4,4,4,4,4,1,3,3,2,3,4,6,8.0,neutral or dissatisfied +15318,94500,Male,Loyal Customer,44,Business travel,Business,3723,5,5,5,5,4,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +15319,58222,Female,Loyal Customer,44,Personal Travel,Eco,925,1,5,1,3,3,5,4,5,5,1,5,2,5,4,47,33.0,neutral or dissatisfied +15320,60958,Female,Loyal Customer,43,Business travel,Business,2644,3,4,4,4,3,2,3,3,3,3,3,4,3,1,6,18.0,neutral or dissatisfied +15321,28460,Male,Loyal Customer,46,Personal Travel,Eco,2588,2,5,2,1,2,5,5,3,2,4,1,5,1,5,0,27.0,neutral or dissatisfied +15322,13046,Female,Loyal Customer,32,Personal Travel,Eco,438,2,5,2,3,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +15323,67936,Female,Loyal Customer,47,Personal Travel,Eco,1205,2,5,2,1,3,5,5,4,4,2,4,4,4,4,30,35.0,neutral or dissatisfied +15324,51457,Male,Loyal Customer,63,Personal Travel,Eco Plus,238,3,4,3,4,3,3,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +15325,33654,Female,Loyal Customer,40,Personal Travel,Eco,399,3,3,3,4,4,3,4,4,1,3,1,3,2,4,14,21.0,neutral or dissatisfied +15326,17065,Male,Loyal Customer,37,Business travel,Business,282,3,3,3,3,4,4,5,4,4,4,4,3,4,3,12,10.0,satisfied +15327,76707,Female,Loyal Customer,44,Personal Travel,Eco,547,2,4,2,3,3,3,2,3,3,2,2,4,3,5,0,0.0,neutral or dissatisfied +15328,48811,Female,Loyal Customer,47,Personal Travel,Business,304,4,4,4,5,4,4,5,1,1,4,1,3,1,5,0,0.0,satisfied +15329,22756,Male,Loyal Customer,53,Business travel,Business,302,3,3,3,3,1,3,3,4,4,4,4,5,4,1,5,2.0,satisfied +15330,14322,Male,Loyal Customer,50,Business travel,Business,429,3,3,3,3,5,3,1,4,4,4,4,5,4,3,0,0.0,satisfied +15331,91420,Male,Loyal Customer,58,Business travel,Business,549,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +15332,26951,Male,Loyal Customer,41,Business travel,Eco Plus,2402,4,2,2,2,4,4,4,4,2,4,2,2,3,4,0,1.0,neutral or dissatisfied +15333,96821,Male,Loyal Customer,44,Business travel,Business,1850,2,2,2,2,5,4,4,2,2,3,2,5,2,5,0,0.0,satisfied +15334,36644,Male,Loyal Customer,45,Personal Travel,Eco,1197,3,5,3,3,1,3,1,1,3,3,5,5,5,1,0,15.0,neutral or dissatisfied +15335,108660,Female,Loyal Customer,13,Personal Travel,Eco,1747,2,1,2,4,1,2,1,1,3,2,2,3,4,1,28,16.0,neutral or dissatisfied +15336,113261,Female,Loyal Customer,50,Business travel,Business,488,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +15337,53543,Female,Loyal Customer,49,Personal Travel,Eco Plus,2358,2,4,2,5,2,2,2,3,4,5,4,2,5,2,0,2.0,neutral or dissatisfied +15338,12355,Male,Loyal Customer,33,Business travel,Eco,253,4,4,4,4,4,3,4,4,3,3,3,1,4,4,9,3.0,neutral or dissatisfied +15339,86696,Male,Loyal Customer,45,Business travel,Business,1747,3,3,3,3,4,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +15340,114958,Male,Loyal Customer,58,Business travel,Business,3293,3,3,3,3,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +15341,33208,Male,Loyal Customer,39,Business travel,Eco Plus,216,4,5,5,5,4,4,4,4,3,2,1,4,3,4,0,2.0,satisfied +15342,113862,Male,Loyal Customer,43,Business travel,Business,963,4,4,4,4,3,5,4,4,4,4,4,4,4,1,2,3.0,satisfied +15343,41190,Male,Loyal Customer,44,Business travel,Business,1091,4,4,4,4,5,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +15344,32021,Male,Loyal Customer,32,Business travel,Business,101,3,2,3,3,4,5,5,4,2,3,3,5,5,4,0,1.0,satisfied +15345,14087,Female,Loyal Customer,34,Business travel,Eco,371,1,4,4,4,1,1,1,1,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +15346,32094,Male,Loyal Customer,37,Business travel,Business,216,4,4,4,4,3,4,1,5,5,5,4,1,5,4,0,0.0,satisfied +15347,121888,Male,Loyal Customer,46,Personal Travel,Eco,366,1,4,1,2,3,1,1,3,1,1,2,3,5,3,0,0.0,neutral or dissatisfied +15348,46118,Female,disloyal Customer,36,Business travel,Business,516,4,4,4,3,4,4,4,4,2,5,4,2,4,4,1,7.0,neutral or dissatisfied +15349,34247,Female,Loyal Customer,27,Business travel,Business,1666,1,1,1,1,3,3,3,3,4,2,3,1,1,3,65,46.0,satisfied +15350,123472,Female,disloyal Customer,24,Business travel,Eco,2296,3,3,3,3,2,3,2,2,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +15351,2641,Male,Loyal Customer,41,Business travel,Business,3906,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15352,74078,Male,disloyal Customer,16,Business travel,Eco,641,3,0,3,1,5,3,5,5,4,2,4,5,5,5,27,18.0,neutral or dissatisfied +15353,129122,Male,Loyal Customer,50,Business travel,Business,679,3,1,1,1,3,3,3,1,1,3,4,3,2,3,134,132.0,neutral or dissatisfied +15354,107239,Female,disloyal Customer,26,Business travel,Business,307,3,0,3,2,1,3,1,1,5,2,4,4,4,1,25,20.0,neutral or dissatisfied +15355,118200,Male,Loyal Customer,33,Personal Travel,Eco,1444,4,5,4,1,1,4,1,1,4,2,5,5,5,1,67,61.0,neutral or dissatisfied +15356,4496,Female,Loyal Customer,61,Business travel,Business,435,3,3,3,3,5,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +15357,69377,Female,Loyal Customer,67,Business travel,Eco,1089,3,5,5,5,3,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +15358,11953,Male,Loyal Customer,64,Personal Travel,Eco,781,1,3,1,4,2,1,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +15359,98396,Female,Loyal Customer,49,Business travel,Business,3374,2,2,2,2,2,4,5,3,3,2,3,3,3,5,1,0.0,satisfied +15360,26591,Female,Loyal Customer,40,Business travel,Eco,404,4,4,1,4,4,4,4,4,3,1,2,1,2,4,32,26.0,satisfied +15361,34610,Male,Loyal Customer,53,Personal Travel,Eco,1598,2,2,2,2,4,2,4,4,1,5,1,4,1,4,0,3.0,neutral or dissatisfied +15362,47245,Female,Loyal Customer,49,Business travel,Business,590,3,3,3,3,5,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +15363,31786,Male,Loyal Customer,41,Personal Travel,Eco Plus,602,2,2,2,3,2,2,4,2,1,4,4,3,3,2,0,0.0,neutral or dissatisfied +15364,17428,Male,Loyal Customer,67,Business travel,Eco,351,2,2,2,2,2,2,2,2,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +15365,2769,Male,Loyal Customer,42,Personal Travel,Business,764,4,4,3,2,4,5,5,2,2,3,3,5,2,5,0,0.0,neutral or dissatisfied +15366,77652,Male,Loyal Customer,26,Business travel,Business,3829,2,2,4,2,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +15367,14799,Female,Loyal Customer,51,Business travel,Eco,95,5,2,4,2,2,5,4,5,5,5,5,3,5,2,0,0.0,satisfied +15368,7782,Male,Loyal Customer,52,Business travel,Eco Plus,680,1,2,2,2,1,1,1,1,4,3,4,1,3,1,37,67.0,neutral or dissatisfied +15369,8034,Male,Loyal Customer,50,Business travel,Business,3824,2,2,2,2,5,5,4,5,5,5,5,3,5,5,23,45.0,satisfied +15370,105426,Male,Loyal Customer,37,Personal Travel,Eco,452,1,1,1,3,2,1,2,2,4,4,4,4,3,2,15,7.0,neutral or dissatisfied +15371,16371,Female,disloyal Customer,29,Business travel,Eco,1215,3,3,3,4,2,3,2,2,5,4,5,5,5,2,62,,neutral or dissatisfied +15372,727,Female,Loyal Customer,54,Business travel,Business,2509,4,4,4,4,3,5,4,5,5,5,4,4,5,4,0,3.0,satisfied +15373,52389,Female,Loyal Customer,48,Personal Travel,Eco,370,3,2,3,3,5,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +15374,38570,Male,Loyal Customer,24,Personal Travel,Eco,2446,3,0,3,5,2,3,2,2,4,3,5,3,4,2,3,0.0,neutral or dissatisfied +15375,128538,Female,Loyal Customer,31,Business travel,Business,3206,5,5,5,5,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +15376,54486,Male,Loyal Customer,43,Business travel,Business,2741,1,5,5,5,5,3,3,1,1,1,1,4,1,1,28,2.0,neutral or dissatisfied +15377,29986,Male,disloyal Customer,23,Business travel,Eco,539,2,5,2,5,5,2,5,5,4,5,3,1,2,5,0,0.0,neutral or dissatisfied +15378,122892,Female,disloyal Customer,27,Business travel,Eco Plus,226,0,0,0,3,1,0,1,1,3,1,1,5,3,1,0,0.0,satisfied +15379,72548,Male,Loyal Customer,31,Business travel,Business,3021,4,2,2,2,4,4,4,4,3,2,4,4,3,4,46,48.0,neutral or dissatisfied +15380,68494,Male,Loyal Customer,33,Personal Travel,Eco,1303,4,4,3,2,2,3,2,2,5,2,4,5,4,2,0,0.0,satisfied +15381,118450,Female,Loyal Customer,47,Business travel,Business,325,0,0,0,1,2,5,5,2,2,2,2,3,2,4,97,101.0,satisfied +15382,70227,Female,Loyal Customer,56,Business travel,Eco,668,3,3,1,1,3,3,3,3,3,3,3,1,3,1,0,6.0,neutral or dissatisfied +15383,75751,Male,disloyal Customer,28,Business travel,Eco,468,2,1,2,3,1,2,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +15384,53664,Male,Loyal Customer,55,Business travel,Business,3142,1,1,4,1,3,2,5,4,4,4,4,4,4,1,0,0.0,satisfied +15385,110408,Male,Loyal Customer,47,Business travel,Business,883,4,4,4,4,4,4,4,2,2,2,2,5,2,4,24,20.0,satisfied +15386,74768,Female,Loyal Customer,37,Personal Travel,Eco,1235,1,3,1,4,2,1,5,2,4,4,3,2,3,2,10,0.0,neutral or dissatisfied +15387,49906,Male,Loyal Customer,41,Business travel,Eco,86,4,4,4,4,4,4,4,4,2,2,1,4,2,4,2,9.0,satisfied +15388,106876,Female,disloyal Customer,28,Business travel,Eco,704,3,3,3,4,2,3,2,2,3,5,3,4,4,2,1,0.0,neutral or dissatisfied +15389,111458,Female,Loyal Customer,20,Personal Travel,Eco,836,5,5,5,5,5,5,5,5,5,2,5,5,4,5,10,2.0,satisfied +15390,36075,Male,disloyal Customer,54,Business travel,Eco,474,0,0,1,4,5,1,5,5,1,2,3,2,5,5,0,0.0,satisfied +15391,121795,Female,Loyal Customer,48,Business travel,Eco,449,2,1,1,1,2,4,3,2,2,2,2,2,2,2,35,43.0,neutral or dissatisfied +15392,129618,Male,disloyal Customer,36,Business travel,Business,337,2,3,3,4,1,3,1,1,5,5,5,3,5,1,4,0.0,neutral or dissatisfied +15393,79951,Female,Loyal Customer,13,Business travel,Business,3425,2,4,4,4,2,2,2,2,3,2,3,3,4,2,8,13.0,neutral or dissatisfied +15394,50622,Male,Loyal Customer,9,Personal Travel,Eco,207,2,1,2,3,4,2,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +15395,113329,Female,Loyal Customer,41,Business travel,Business,386,1,1,1,1,2,4,5,4,4,4,4,5,4,3,83,81.0,satisfied +15396,108383,Female,Loyal Customer,16,Personal Travel,Eco,1844,1,4,1,3,5,1,5,5,5,3,4,5,4,5,11,24.0,neutral or dissatisfied +15397,68743,Male,Loyal Customer,40,Business travel,Business,926,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +15398,80945,Male,Loyal Customer,47,Personal Travel,Eco,341,1,4,5,3,4,5,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +15399,27199,Female,Loyal Customer,17,Personal Travel,Business,2717,0,4,0,4,0,2,2,5,3,4,5,2,4,2,0,7.0,satisfied +15400,91470,Male,Loyal Customer,61,Personal Travel,Eco,859,4,5,5,2,1,5,1,1,4,5,4,4,4,1,0,0.0,satisfied +15401,52530,Female,disloyal Customer,22,Business travel,Eco,160,4,4,4,4,1,4,1,1,3,1,2,4,4,1,0,0.0,satisfied +15402,87333,Male,Loyal Customer,48,Business travel,Business,1666,1,1,1,1,5,5,4,4,4,4,4,3,4,3,51,36.0,satisfied +15403,58037,Female,Loyal Customer,44,Personal Travel,Business,589,4,4,4,4,2,4,4,3,3,4,3,4,3,5,3,0.0,satisfied +15404,62508,Female,Loyal Customer,30,Business travel,Business,1846,1,1,1,1,5,5,5,5,3,5,3,5,4,5,0,0.0,satisfied +15405,101724,Male,Loyal Customer,27,Personal Travel,Eco Plus,986,1,4,1,3,3,1,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +15406,72482,Male,Loyal Customer,43,Business travel,Eco,985,3,3,3,3,3,3,3,3,1,1,2,3,2,3,29,28.0,neutral or dissatisfied +15407,37474,Female,Loyal Customer,51,Business travel,Business,2142,1,2,2,2,3,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +15408,38771,Female,disloyal Customer,22,Business travel,Business,353,4,0,4,3,1,4,1,1,2,1,5,5,3,1,0,0.0,satisfied +15409,27770,Female,Loyal Customer,49,Business travel,Business,2952,3,3,3,3,3,4,5,2,2,2,2,4,2,1,0,1.0,satisfied +15410,6550,Male,Loyal Customer,15,Business travel,Business,2959,5,4,5,5,4,5,4,4,3,5,5,4,4,4,2,0.0,satisfied +15411,79130,Male,Loyal Customer,29,Personal Travel,Eco,356,2,5,2,4,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +15412,7897,Male,Loyal Customer,39,Business travel,Business,3733,3,3,3,3,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +15413,54406,Male,Loyal Customer,55,Business travel,Eco,305,1,1,3,1,1,1,1,1,2,4,3,1,3,1,41,36.0,neutral or dissatisfied +15414,85595,Female,disloyal Customer,26,Business travel,Eco,192,3,1,3,2,3,3,3,3,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +15415,97137,Male,Loyal Customer,39,Business travel,Business,1357,2,2,2,2,3,3,3,2,2,2,2,3,2,1,41,18.0,neutral or dissatisfied +15416,105459,Male,disloyal Customer,16,Business travel,Eco,998,3,3,3,3,5,3,2,5,1,3,3,1,3,5,15,19.0,neutral or dissatisfied +15417,16522,Male,Loyal Customer,37,Business travel,Eco,209,5,2,2,2,5,5,5,5,4,3,3,4,3,5,0,0.0,satisfied +15418,13361,Male,disloyal Customer,36,Business travel,Eco,546,2,1,2,3,1,2,1,1,1,3,3,2,4,1,0,0.0,neutral or dissatisfied +15419,32230,Female,disloyal Customer,24,Business travel,Eco,102,2,0,2,3,1,2,1,1,1,5,2,1,2,1,0,0.0,neutral or dissatisfied +15420,4402,Female,disloyal Customer,26,Business travel,Business,473,2,2,2,3,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +15421,128519,Female,Loyal Customer,9,Personal Travel,Eco,646,1,5,1,1,2,1,3,2,1,1,2,1,2,2,0,2.0,neutral or dissatisfied +15422,117981,Male,Loyal Customer,38,Personal Travel,Eco,365,3,5,4,5,4,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +15423,10847,Male,disloyal Customer,43,Business travel,Eco,667,4,1,4,3,4,4,5,4,2,1,2,4,3,4,22,20.0,neutral or dissatisfied +15424,111489,Female,Loyal Customer,28,Personal Travel,Business,391,2,5,2,4,3,2,3,3,4,4,5,3,4,3,14,6.0,neutral or dissatisfied +15425,3458,Female,disloyal Customer,58,Business travel,Business,315,2,2,2,4,5,2,5,5,3,3,4,5,5,5,73,75.0,neutral or dissatisfied +15426,23304,Female,Loyal Customer,67,Business travel,Business,2654,3,3,5,3,5,3,1,4,4,4,4,5,4,5,10,0.0,satisfied +15427,98674,Male,Loyal Customer,68,Personal Travel,Eco,920,2,4,2,4,5,2,5,5,3,1,4,3,3,5,18,0.0,neutral or dissatisfied +15428,30288,Male,Loyal Customer,16,Business travel,Business,1476,2,4,4,4,2,2,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +15429,95581,Female,Loyal Customer,12,Personal Travel,Business,670,1,4,1,3,5,1,5,5,3,5,5,4,5,5,64,63.0,neutral or dissatisfied +15430,68046,Female,Loyal Customer,43,Business travel,Business,813,1,1,1,1,3,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +15431,15355,Male,Loyal Customer,43,Business travel,Eco,331,4,4,4,4,4,4,4,4,5,2,2,5,3,4,0,2.0,satisfied +15432,101343,Male,disloyal Customer,12,Business travel,Eco,731,1,1,1,4,2,1,2,2,1,4,3,2,4,2,26,24.0,neutral or dissatisfied +15433,118089,Male,Loyal Customer,69,Personal Travel,Eco,1276,2,4,1,2,3,1,2,3,5,2,5,5,5,3,3,0.0,neutral or dissatisfied +15434,112096,Female,Loyal Customer,23,Business travel,Business,3340,1,1,1,1,4,4,4,4,4,3,4,5,4,4,15,3.0,satisfied +15435,10060,Male,Loyal Customer,27,Business travel,Business,596,2,2,2,2,4,4,4,4,5,5,5,5,5,4,68,119.0,satisfied +15436,77515,Male,Loyal Customer,32,Business travel,Business,1521,1,1,1,1,1,1,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +15437,91910,Female,Loyal Customer,54,Business travel,Business,2475,2,2,2,2,3,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +15438,11387,Female,disloyal Customer,33,Business travel,Business,191,1,1,1,5,4,1,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +15439,99715,Male,Loyal Customer,33,Personal Travel,Eco Plus,667,2,5,2,5,3,2,3,3,5,4,4,5,4,3,4,49.0,neutral or dissatisfied +15440,96683,Female,Loyal Customer,15,Personal Travel,Eco Plus,1036,2,5,2,3,1,2,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +15441,67512,Male,disloyal Customer,23,Business travel,Eco,1313,2,2,2,5,1,2,1,1,5,4,5,4,5,1,0,2.0,neutral or dissatisfied +15442,14626,Male,Loyal Customer,51,Business travel,Eco,541,4,3,3,3,4,4,4,4,1,3,2,2,1,4,0,0.0,satisfied +15443,38080,Male,Loyal Customer,30,Business travel,Business,1237,4,4,4,4,5,5,5,5,2,5,3,3,2,5,0,0.0,satisfied +15444,72641,Female,Loyal Customer,14,Personal Travel,Eco,1121,3,5,3,1,2,3,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +15445,18974,Male,Loyal Customer,39,Business travel,Business,792,2,2,2,2,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +15446,20193,Male,Loyal Customer,10,Personal Travel,Eco Plus,677,3,4,3,3,3,3,3,3,3,1,3,2,1,3,1,10.0,neutral or dissatisfied +15447,107316,Female,Loyal Customer,55,Personal Travel,Eco,307,2,4,2,5,5,4,4,2,2,2,2,5,2,4,11,11.0,neutral or dissatisfied +15448,97915,Female,Loyal Customer,38,Business travel,Eco,616,4,5,5,5,4,4,4,4,1,2,4,2,4,4,6,5.0,neutral or dissatisfied +15449,31285,Female,Loyal Customer,70,Personal Travel,Eco,770,1,4,1,1,3,5,5,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +15450,40464,Female,Loyal Customer,31,Business travel,Business,3307,0,5,0,1,2,2,2,2,5,5,3,2,2,2,0,0.0,satisfied +15451,48458,Male,disloyal Customer,24,Business travel,Eco,819,4,4,4,2,2,4,2,2,4,5,1,5,5,2,0,0.0,satisfied +15452,61473,Male,Loyal Customer,31,Business travel,Business,2253,1,5,1,1,5,5,5,5,3,5,3,4,4,5,2,2.0,satisfied +15453,32145,Female,Loyal Customer,30,Business travel,Business,2637,2,2,2,2,5,5,4,5,5,1,3,1,3,5,0,0.0,satisfied +15454,26214,Female,Loyal Customer,49,Personal Travel,Eco,406,3,4,3,4,4,4,5,5,5,3,5,5,5,5,18,11.0,neutral or dissatisfied +15455,34935,Female,Loyal Customer,9,Personal Travel,Eco,187,2,3,2,3,4,2,4,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +15456,51094,Female,Loyal Customer,31,Personal Travel,Eco,266,3,5,3,5,1,3,1,1,3,5,5,3,5,1,7,17.0,neutral or dissatisfied +15457,103003,Male,Loyal Customer,41,Business travel,Business,1861,2,2,2,2,4,4,4,4,4,4,4,3,4,4,26,23.0,satisfied +15458,13275,Female,Loyal Customer,70,Personal Travel,Eco,771,3,4,3,4,3,4,4,2,1,2,3,4,4,4,160,142.0,neutral or dissatisfied +15459,121836,Male,disloyal Customer,23,Business travel,Eco,337,2,0,2,2,4,2,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +15460,34310,Female,Loyal Customer,24,Personal Travel,Eco,280,3,2,3,4,4,3,4,4,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +15461,7972,Female,Loyal Customer,46,Business travel,Eco Plus,594,3,3,5,3,4,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +15462,30427,Female,Loyal Customer,29,Personal Travel,Eco,1014,2,3,2,3,1,2,1,1,1,2,4,4,3,1,0,4.0,neutral or dissatisfied +15463,87834,Female,Loyal Customer,31,Personal Travel,Eco,214,1,4,1,4,4,1,4,4,1,5,3,4,3,4,2,0.0,neutral or dissatisfied +15464,12107,Male,disloyal Customer,27,Business travel,Eco,1034,2,2,2,1,2,2,2,3,1,4,2,2,3,2,160,134.0,neutral or dissatisfied +15465,99084,Male,Loyal Customer,30,Business travel,Business,2835,2,2,2,2,5,5,4,5,4,3,5,5,5,5,16,22.0,satisfied +15466,20176,Male,Loyal Customer,65,Personal Travel,Eco,403,2,4,2,5,5,2,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +15467,67194,Male,Loyal Customer,10,Personal Travel,Eco,985,2,5,2,3,1,2,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +15468,56682,Female,Loyal Customer,26,Personal Travel,Eco,1068,3,5,3,3,2,3,2,2,4,5,5,3,4,2,20,13.0,neutral or dissatisfied +15469,5780,Female,Loyal Customer,69,Personal Travel,Business,177,4,3,4,3,4,4,4,1,1,4,1,4,1,4,0,23.0,neutral or dissatisfied +15470,88736,Male,Loyal Customer,69,Personal Travel,Eco,240,3,1,3,3,3,3,1,3,4,3,2,2,3,3,0,0.0,neutral or dissatisfied +15471,18701,Male,Loyal Customer,51,Business travel,Eco Plus,190,3,2,2,2,3,3,3,3,1,1,4,3,3,3,117,107.0,neutral or dissatisfied +15472,115288,Male,Loyal Customer,47,Business travel,Eco,371,3,5,5,5,3,3,3,3,1,4,3,4,3,3,52,47.0,neutral or dissatisfied +15473,110825,Male,Loyal Customer,46,Personal Travel,Eco,997,2,4,2,3,4,2,4,4,3,3,4,3,4,4,19,21.0,neutral or dissatisfied +15474,113451,Male,Loyal Customer,39,Business travel,Business,3061,0,5,0,2,4,5,4,1,1,1,1,3,1,5,0,0.0,satisfied +15475,8037,Female,Loyal Customer,59,Business travel,Business,2291,2,2,2,2,3,4,4,5,5,5,5,5,5,4,12,8.0,satisfied +15476,107471,Male,disloyal Customer,25,Business travel,Eco,1121,5,4,4,2,5,4,5,5,3,3,4,4,5,5,11,13.0,satisfied +15477,90175,Female,Loyal Customer,13,Personal Travel,Eco,983,5,4,4,5,5,4,5,5,5,3,4,4,4,5,0,0.0,satisfied +15478,74316,Male,Loyal Customer,41,Business travel,Business,1242,3,5,4,5,4,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +15479,14770,Female,Loyal Customer,20,Personal Travel,Eco Plus,533,3,4,3,2,5,3,1,5,5,3,4,3,5,5,42,24.0,neutral or dissatisfied +15480,82623,Female,Loyal Customer,59,Personal Travel,Eco,528,2,5,4,3,3,5,4,2,2,4,2,4,2,5,5,0.0,neutral or dissatisfied +15481,41523,Male,Loyal Customer,25,Business travel,Business,1334,3,1,2,2,3,3,3,3,3,1,4,3,4,3,8,13.0,neutral or dissatisfied +15482,62081,Female,Loyal Customer,45,Business travel,Business,2475,3,3,3,3,2,3,4,4,4,5,4,4,4,5,0,11.0,satisfied +15483,70948,Female,Loyal Customer,30,Personal Travel,Eco,612,2,1,2,2,1,2,1,1,1,4,2,1,2,1,4,9.0,neutral or dissatisfied +15484,61957,Male,Loyal Customer,36,Business travel,Business,552,4,2,4,4,5,1,5,4,4,4,4,3,4,5,6,0.0,satisfied +15485,14213,Female,Loyal Customer,69,Personal Travel,Eco,620,4,5,4,2,4,4,5,2,2,4,2,3,2,5,44,24.0,neutral or dissatisfied +15486,106445,Female,Loyal Customer,41,Personal Travel,Eco,1062,4,5,4,1,1,4,1,1,5,2,5,5,5,1,0,0.0,satisfied +15487,24335,Male,disloyal Customer,30,Business travel,Eco,634,4,0,4,4,3,4,3,3,5,1,2,4,1,3,0,40.0,neutral or dissatisfied +15488,95230,Male,Loyal Customer,64,Personal Travel,Eco,319,5,5,3,3,4,3,4,4,5,3,4,3,5,4,6,1.0,satisfied +15489,11588,Male,Loyal Customer,18,Business travel,Business,468,4,1,1,1,4,4,4,4,1,1,4,3,4,4,6,8.0,neutral or dissatisfied +15490,79201,Male,disloyal Customer,26,Business travel,Business,1990,2,2,2,4,4,2,1,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +15491,107121,Male,Loyal Customer,44,Business travel,Eco,842,2,4,4,4,2,2,2,2,3,4,3,3,4,2,114,98.0,neutral or dissatisfied +15492,110866,Female,Loyal Customer,45,Business travel,Business,406,4,4,4,4,5,4,5,3,3,4,3,4,3,3,11,6.0,satisfied +15493,14957,Female,Loyal Customer,23,Personal Travel,Eco,554,3,4,2,1,5,2,5,5,3,5,5,4,4,5,7,19.0,neutral or dissatisfied +15494,26108,Female,Loyal Customer,38,Business travel,Business,3799,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +15495,98666,Male,Loyal Customer,17,Personal Travel,Eco,992,4,2,4,3,2,4,2,2,1,2,3,2,3,2,30,19.0,neutral or dissatisfied +15496,107735,Female,Loyal Customer,25,Personal Travel,Eco,405,2,5,2,4,5,2,5,5,5,4,4,3,4,5,6,8.0,neutral or dissatisfied +15497,23136,Male,disloyal Customer,37,Business travel,Eco,250,3,3,3,4,5,3,5,5,3,4,1,1,2,5,0,0.0,neutral or dissatisfied +15498,36611,Female,disloyal Customer,10,Business travel,Eco,1237,3,3,3,3,5,3,5,5,4,2,3,5,4,5,0,2.0,neutral or dissatisfied +15499,105322,Female,Loyal Customer,51,Business travel,Eco,452,2,5,5,5,1,3,4,2,2,2,2,3,2,2,8,0.0,neutral or dissatisfied +15500,47303,Male,disloyal Customer,28,Business travel,Eco,590,1,4,1,3,4,1,4,4,1,2,1,2,2,4,0,0.0,neutral or dissatisfied +15501,55712,Female,Loyal Customer,30,Personal Travel,Eco,927,2,5,2,3,4,2,4,4,3,2,5,4,4,4,53,70.0,neutral or dissatisfied +15502,76069,Male,disloyal Customer,25,Business travel,Business,669,4,5,4,3,3,4,3,3,4,3,5,4,4,3,0,0.0,satisfied +15503,9961,Female,disloyal Customer,26,Business travel,Eco,515,1,0,1,3,3,1,3,3,4,1,3,2,3,3,0,4.0,neutral or dissatisfied +15504,40514,Male,Loyal Customer,59,Business travel,Eco Plus,175,5,1,1,1,5,5,5,5,3,5,3,3,5,5,0,0.0,satisfied +15505,42315,Male,Loyal Customer,37,Personal Travel,Eco,838,2,5,2,1,4,2,4,4,5,4,5,5,4,4,1,5.0,neutral or dissatisfied +15506,90699,Female,Loyal Customer,54,Business travel,Business,2948,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +15507,122410,Male,Loyal Customer,25,Business travel,Business,1916,3,3,3,3,5,5,5,5,5,2,4,5,5,5,7,16.0,satisfied +15508,77576,Female,disloyal Customer,22,Business travel,Eco,813,1,1,1,3,5,1,5,5,4,5,4,1,3,5,0,12.0,neutral or dissatisfied +15509,72732,Male,Loyal Customer,15,Personal Travel,Eco Plus,1102,4,4,4,3,1,4,1,1,1,2,4,3,3,1,0,4.0,neutral or dissatisfied +15510,82702,Female,disloyal Customer,36,Business travel,Eco,232,3,4,3,4,2,3,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +15511,4125,Female,Loyal Customer,40,Business travel,Business,3941,3,2,5,2,2,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +15512,120356,Male,Loyal Customer,42,Business travel,Business,449,5,5,5,5,4,4,5,3,3,3,3,3,3,3,47,44.0,satisfied +15513,82496,Female,Loyal Customer,55,Personal Travel,Eco,488,1,5,1,3,5,5,4,2,2,1,1,4,2,4,0,0.0,neutral or dissatisfied +15514,45772,Female,Loyal Customer,18,Business travel,Business,517,2,2,2,2,2,2,2,2,1,3,3,2,2,2,0,0.0,satisfied +15515,103824,Male,Loyal Customer,27,Business travel,Business,1072,1,5,2,2,1,1,1,1,2,3,4,4,3,1,29,13.0,neutral or dissatisfied +15516,60173,Male,Loyal Customer,56,Personal Travel,Eco,1120,2,5,1,5,1,5,1,5,5,5,5,1,4,1,192,166.0,neutral or dissatisfied +15517,89875,Male,Loyal Customer,60,Business travel,Business,2342,3,3,3,3,2,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +15518,52422,Male,Loyal Customer,49,Personal Travel,Eco,261,1,1,1,1,5,1,5,5,3,2,2,3,2,5,1,0.0,neutral or dissatisfied +15519,59097,Male,Loyal Customer,10,Personal Travel,Eco,1846,4,0,4,3,4,2,2,4,3,5,4,2,5,2,167,171.0,neutral or dissatisfied +15520,116248,Female,Loyal Customer,52,Personal Travel,Eco,480,4,2,4,3,1,3,4,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +15521,101192,Male,Loyal Customer,38,Personal Travel,Eco,775,3,5,2,4,3,2,1,3,1,5,4,4,1,3,21,12.0,neutral or dissatisfied +15522,21211,Male,Loyal Customer,22,Business travel,Business,192,2,2,2,2,4,4,5,4,1,2,4,2,3,4,0,0.0,satisfied +15523,17235,Male,Loyal Customer,35,Business travel,Business,1092,1,1,1,1,2,3,4,5,5,5,5,3,5,1,0,0.0,satisfied +15524,99075,Male,Loyal Customer,36,Business travel,Business,181,4,3,3,3,5,4,3,2,2,2,4,1,2,4,0,0.0,neutral or dissatisfied +15525,82128,Male,Loyal Customer,36,Personal Travel,Eco,2519,4,4,4,1,4,1,1,4,4,5,5,1,5,1,38,59.0,neutral or dissatisfied +15526,44027,Female,Loyal Customer,54,Business travel,Business,67,1,5,5,5,4,4,3,4,4,4,1,1,4,3,36,16.0,neutral or dissatisfied +15527,126206,Female,Loyal Customer,32,Business travel,Business,507,2,5,2,5,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +15528,10822,Female,disloyal Customer,23,Business travel,Eco,396,3,3,3,2,4,3,4,4,3,3,3,3,2,4,0,0.0,neutral or dissatisfied +15529,86,Female,Loyal Customer,27,Personal Travel,Eco,212,3,0,3,4,1,3,1,1,3,4,5,5,5,1,0,13.0,neutral or dissatisfied +15530,3884,Female,disloyal Customer,40,Business travel,Business,213,3,3,3,2,3,3,4,3,3,2,5,5,5,3,53,70.0,satisfied +15531,31174,Male,Loyal Customer,38,Business travel,Eco Plus,627,4,5,1,1,4,3,4,4,1,5,3,1,2,4,20,27.0,neutral or dissatisfied +15532,28270,Male,Loyal Customer,43,Business travel,Business,2402,5,5,5,5,4,4,4,4,5,4,2,4,5,4,0,0.0,satisfied +15533,19424,Male,Loyal Customer,29,Business travel,Business,645,2,3,1,3,2,2,2,2,1,1,3,4,3,2,0,3.0,neutral or dissatisfied +15534,19086,Male,Loyal Customer,54,Business travel,Eco,296,5,5,5,5,5,5,5,5,5,5,1,5,5,5,0,0.0,satisfied +15535,125247,Male,disloyal Customer,37,Business travel,Business,427,4,3,3,3,4,3,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +15536,13016,Female,Loyal Customer,23,Business travel,Business,374,5,5,5,5,5,5,5,5,2,1,5,5,1,5,0,0.0,satisfied +15537,30838,Female,Loyal Customer,49,Business travel,Eco Plus,1026,5,4,5,4,3,4,5,5,5,5,5,4,5,1,9,16.0,satisfied +15538,61315,Male,Loyal Customer,54,Business travel,Business,1838,3,3,3,3,5,4,5,5,5,5,5,5,5,3,16,58.0,satisfied +15539,75069,Male,Loyal Customer,60,Business travel,Business,2611,4,3,3,3,3,2,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +15540,93959,Male,Loyal Customer,27,Personal Travel,Eco Plus,507,2,1,2,4,5,2,5,5,3,3,4,4,3,5,51,40.0,neutral or dissatisfied +15541,29758,Male,disloyal Customer,27,Business travel,Business,160,3,3,3,5,5,3,1,5,4,5,4,5,4,5,11,9.0,neutral or dissatisfied +15542,72570,Male,Loyal Customer,41,Business travel,Business,3829,3,5,3,3,1,3,4,5,5,5,5,5,5,5,1,0.0,satisfied +15543,76142,Female,disloyal Customer,28,Business travel,Business,689,3,3,3,1,1,3,1,1,4,5,5,3,4,1,8,0.0,neutral or dissatisfied +15544,53298,Female,Loyal Customer,32,Business travel,Eco,921,3,2,2,2,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +15545,56480,Female,Loyal Customer,45,Business travel,Business,4963,1,1,1,1,2,1,1,3,3,5,4,1,3,1,0,13.0,satisfied +15546,25255,Male,Loyal Customer,26,Personal Travel,Business,425,3,0,3,3,1,3,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +15547,126683,Male,Loyal Customer,50,Business travel,Business,2521,5,5,5,5,2,4,4,5,5,5,5,5,5,4,5,0.0,satisfied +15548,88490,Female,disloyal Customer,25,Business travel,Eco,271,4,0,4,3,2,4,2,2,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +15549,82193,Male,disloyal Customer,43,Business travel,Eco,427,4,2,4,4,5,4,5,5,3,5,4,2,4,5,1,3.0,neutral or dissatisfied +15550,106818,Male,Loyal Customer,45,Business travel,Eco,1488,3,5,5,5,4,3,4,4,2,4,3,3,4,4,30,24.0,neutral or dissatisfied +15551,104386,Female,disloyal Customer,22,Business travel,Eco,228,4,5,4,1,4,4,4,4,5,4,4,4,4,4,0,18.0,neutral or dissatisfied +15552,44435,Female,Loyal Customer,33,Personal Travel,Eco,542,4,5,4,2,4,4,4,4,3,5,4,4,4,4,9,0.0,neutral or dissatisfied +15553,21541,Male,Loyal Customer,67,Personal Travel,Eco,399,1,5,1,3,2,1,4,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +15554,92813,Female,Loyal Customer,43,Business travel,Business,1587,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +15555,64006,Female,Loyal Customer,39,Personal Travel,Eco,612,2,4,2,2,1,2,1,1,4,3,4,2,5,1,6,3.0,neutral or dissatisfied +15556,29488,Male,disloyal Customer,37,Business travel,Business,1107,2,2,2,2,1,2,1,1,2,3,3,4,3,1,0,0.0,neutral or dissatisfied +15557,82297,Female,Loyal Customer,52,Business travel,Business,986,5,5,5,5,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +15558,126011,Female,Loyal Customer,27,Business travel,Business,3799,1,1,1,1,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +15559,25614,Female,Loyal Customer,27,Business travel,Eco,526,0,0,0,3,2,3,2,2,3,1,4,3,4,2,16,2.0,satisfied +15560,125224,Male,Loyal Customer,29,Personal Travel,Eco,651,3,3,3,3,3,3,3,3,3,5,4,3,3,3,0,0.0,neutral or dissatisfied +15561,60692,Male,Loyal Customer,19,Business travel,Business,1725,1,1,1,1,5,5,5,3,5,3,4,5,4,5,196,158.0,satisfied +15562,106877,Male,disloyal Customer,11,Business travel,Eco,704,3,3,3,3,3,3,3,3,2,3,4,2,3,3,23,12.0,neutral or dissatisfied +15563,86369,Male,disloyal Customer,30,Business travel,Business,762,5,5,5,3,2,5,2,2,4,3,4,5,5,2,5,0.0,satisfied +15564,47807,Male,Loyal Customer,48,Business travel,Business,412,1,2,2,2,4,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +15565,115349,Female,Loyal Customer,39,Business travel,Business,3587,4,4,4,4,5,5,5,4,4,4,4,4,4,3,24,17.0,satisfied +15566,115350,Female,Loyal Customer,65,Business travel,Business,1706,4,4,4,4,3,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +15567,37205,Female,disloyal Customer,22,Business travel,Eco,1046,4,4,4,4,5,4,5,5,3,1,3,2,3,5,41,32.0,satisfied +15568,15106,Female,Loyal Customer,56,Personal Travel,Eco,239,3,5,3,2,5,5,5,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +15569,86756,Male,Loyal Customer,11,Personal Travel,Eco,821,2,4,2,4,4,2,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +15570,107899,Male,Loyal Customer,34,Business travel,Business,2713,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +15571,106015,Male,disloyal Customer,37,Business travel,Business,1999,1,0,0,1,3,0,3,3,5,3,5,4,4,3,28,41.0,neutral or dissatisfied +15572,47267,Female,Loyal Customer,34,Business travel,Business,590,3,3,3,3,3,1,5,5,5,5,5,4,5,4,0,10.0,satisfied +15573,41941,Female,disloyal Customer,27,Business travel,Eco Plus,129,1,1,1,2,1,1,1,1,3,3,4,2,2,1,0,6.0,neutral or dissatisfied +15574,109929,Male,Loyal Customer,35,Personal Travel,Eco,1033,1,4,1,1,2,1,2,2,3,2,4,3,5,2,14,9.0,neutral or dissatisfied +15575,6753,Female,Loyal Customer,59,Business travel,Business,235,0,0,0,3,1,1,1,4,3,4,5,1,5,1,319,363.0,satisfied +15576,93767,Female,Loyal Customer,61,Personal Travel,Eco,368,3,4,3,3,3,4,4,4,4,3,4,2,4,1,4,1.0,neutral or dissatisfied +15577,4797,Male,Loyal Customer,36,Personal Travel,Eco,258,4,1,4,4,2,4,2,2,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +15578,38301,Male,disloyal Customer,13,Business travel,Eco,728,3,3,3,4,5,3,5,5,4,1,2,3,4,5,46,63.0,neutral or dissatisfied +15579,114895,Female,Loyal Customer,63,Business travel,Business,333,4,4,4,4,2,4,4,4,4,4,4,5,4,5,17,7.0,satisfied +15580,92476,Male,disloyal Customer,22,Business travel,Eco,825,3,2,2,3,4,3,4,4,2,2,4,2,3,4,40,30.0,neutral or dissatisfied +15581,107443,Female,Loyal Customer,9,Personal Travel,Eco,468,1,4,1,3,5,1,5,5,4,1,5,4,1,5,0,0.0,neutral or dissatisfied +15582,52078,Male,Loyal Customer,49,Business travel,Business,438,1,3,3,3,5,2,2,1,1,1,1,4,1,1,0,9.0,neutral or dissatisfied +15583,111276,Female,Loyal Customer,60,Business travel,Eco,459,5,3,3,3,2,4,2,5,5,5,5,2,5,3,0,0.0,satisfied +15584,87145,Male,Loyal Customer,23,Business travel,Eco Plus,594,2,3,3,3,2,2,2,2,2,3,3,1,3,2,15,7.0,neutral or dissatisfied +15585,2646,Female,Loyal Customer,33,Business travel,Business,622,3,3,3,3,5,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +15586,60596,Female,Loyal Customer,48,Personal Travel,Eco,1290,1,4,1,4,2,2,3,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +15587,49063,Male,Loyal Customer,51,Business travel,Eco,262,4,4,4,4,4,4,4,4,5,4,2,3,3,4,0,0.0,satisfied +15588,6624,Male,Loyal Customer,25,Business travel,Eco,719,3,4,4,4,3,4,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +15589,55997,Male,Loyal Customer,49,Business travel,Business,2475,3,4,3,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +15590,99265,Female,Loyal Customer,27,Business travel,Business,2356,2,2,2,2,4,4,4,4,3,3,5,3,5,4,25,18.0,satisfied +15591,120765,Male,disloyal Customer,21,Business travel,Business,678,5,0,5,2,4,5,4,4,5,4,4,3,4,4,0,0.0,satisfied +15592,24143,Male,Loyal Customer,32,Business travel,Business,170,2,2,5,2,4,5,4,4,3,3,3,2,3,4,44,40.0,satisfied +15593,115410,Male,disloyal Customer,32,Business travel,Eco,417,4,2,4,4,4,5,5,1,5,3,3,5,3,5,168,152.0,neutral or dissatisfied +15594,72225,Female,disloyal Customer,36,Business travel,Business,919,2,1,1,4,2,1,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +15595,66770,Female,Loyal Customer,36,Business travel,Business,3484,3,3,3,3,4,4,4,1,1,2,1,4,1,4,3,0.0,satisfied +15596,92757,Female,Loyal Customer,19,Personal Travel,Eco,1298,2,5,2,1,4,2,4,4,4,4,4,3,5,4,0,10.0,neutral or dissatisfied +15597,90923,Male,Loyal Customer,26,Business travel,Business,1779,5,5,5,5,4,4,4,4,2,2,4,4,3,4,0,1.0,satisfied +15598,49203,Female,Loyal Customer,56,Business travel,Business,1998,1,1,1,1,3,1,5,4,4,4,4,3,4,3,21,22.0,satisfied +15599,107751,Male,Loyal Customer,37,Personal Travel,Eco,251,1,4,1,3,2,1,2,2,1,1,3,4,5,2,4,6.0,neutral or dissatisfied +15600,119107,Male,Loyal Customer,23,Business travel,Business,707,4,4,4,4,4,4,4,4,1,4,2,2,5,4,6,0.0,satisfied +15601,56395,Male,disloyal Customer,28,Personal Travel,Business,719,3,4,3,4,1,3,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +15602,85565,Female,Loyal Customer,44,Business travel,Business,3340,0,0,0,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +15603,87174,Male,Loyal Customer,31,Business travel,Business,1679,2,2,5,2,2,2,2,2,5,3,4,4,5,2,1,0.0,satisfied +15604,129599,Female,disloyal Customer,22,Business travel,Business,337,5,4,5,2,2,5,4,2,4,5,4,5,4,2,1,13.0,satisfied +15605,72730,Male,Loyal Customer,29,Personal Travel,Eco Plus,929,2,2,2,2,1,2,1,1,3,1,3,4,2,1,0,0.0,neutral or dissatisfied +15606,100920,Female,Loyal Customer,56,Business travel,Business,3853,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +15607,22386,Male,Loyal Customer,57,Business travel,Business,3694,0,5,0,1,1,5,1,5,5,5,5,1,5,3,0,0.0,satisfied +15608,21773,Male,Loyal Customer,47,Business travel,Eco,352,4,2,2,2,4,4,4,4,1,4,3,3,1,4,39,30.0,satisfied +15609,112754,Female,disloyal Customer,20,Business travel,Business,590,4,0,4,2,2,4,1,2,4,3,5,3,4,2,0,0.0,satisfied +15610,59504,Female,Loyal Customer,8,Personal Travel,Eco Plus,758,2,5,3,2,4,3,4,4,5,2,4,3,4,4,38,32.0,neutral or dissatisfied +15611,90743,Female,Loyal Customer,35,Business travel,Business,240,2,2,2,2,3,3,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +15612,52174,Male,Loyal Customer,34,Business travel,Business,2035,5,5,5,5,2,3,1,5,5,5,5,5,5,1,6,0.0,satisfied +15613,52269,Female,disloyal Customer,72,Business travel,Eco,370,0,0,0,5,5,0,5,5,3,3,2,1,3,5,0,0.0,satisfied +15614,66115,Male,Loyal Customer,59,Business travel,Business,583,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,4.0,satisfied +15615,58822,Female,Loyal Customer,21,Personal Travel,Eco,1005,3,4,4,4,2,4,4,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +15616,28089,Female,Loyal Customer,41,Business travel,Business,1909,1,1,1,1,5,4,5,5,5,5,5,5,5,4,46,44.0,satisfied +15617,51063,Male,Loyal Customer,29,Personal Travel,Eco,304,3,4,2,5,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +15618,32946,Female,Loyal Customer,56,Personal Travel,Eco,101,1,4,0,2,2,2,3,4,4,0,4,4,4,2,0,3.0,neutral or dissatisfied +15619,101887,Male,disloyal Customer,41,Business travel,Business,1984,3,3,3,3,2,3,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +15620,109304,Male,Loyal Customer,49,Business travel,Business,1931,2,2,3,2,4,5,4,4,4,4,4,3,4,3,1,2.0,satisfied +15621,24215,Female,Loyal Customer,41,Business travel,Business,170,1,1,1,1,4,3,4,4,4,5,5,1,4,5,0,0.0,satisfied +15622,103238,Male,disloyal Customer,36,Business travel,Business,409,3,3,3,4,1,3,1,1,4,4,4,3,5,1,4,0.0,neutral or dissatisfied +15623,58262,Female,Loyal Customer,48,Business travel,Business,2072,1,1,1,1,2,5,4,5,5,5,5,3,5,4,95,77.0,satisfied +15624,58937,Female,Loyal Customer,12,Personal Travel,Eco,888,2,5,2,3,1,2,1,1,3,5,5,3,5,1,51,65.0,neutral or dissatisfied +15625,102167,Female,Loyal Customer,47,Business travel,Business,3946,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +15626,112202,Female,Loyal Customer,47,Business travel,Business,3715,5,5,5,5,4,4,4,5,5,5,5,4,5,3,3,3.0,satisfied +15627,99124,Male,Loyal Customer,69,Personal Travel,Eco,237,2,5,2,2,1,2,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +15628,112092,Male,Loyal Customer,39,Business travel,Business,3387,4,4,4,4,4,4,4,4,4,4,4,5,4,4,5,0.0,satisfied +15629,50037,Female,Loyal Customer,65,Business travel,Eco,337,3,2,4,4,3,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +15630,68076,Female,Loyal Customer,30,Business travel,Business,3159,3,3,3,3,5,5,5,5,4,5,4,3,4,5,14,1.0,satisfied +15631,122708,Male,Loyal Customer,10,Personal Travel,Eco,813,4,5,5,5,2,5,2,2,4,3,5,1,2,2,0,0.0,satisfied +15632,57216,Female,Loyal Customer,12,Business travel,Business,1514,2,1,1,1,2,1,2,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +15633,114088,Male,Loyal Customer,57,Personal Travel,Eco,1892,4,1,4,4,5,4,5,5,4,3,2,3,4,5,19,0.0,neutral or dissatisfied +15634,14961,Female,Loyal Customer,38,Business travel,Eco Plus,528,4,1,1,1,4,4,4,4,3,4,2,2,4,4,0,0.0,satisfied +15635,11372,Female,Loyal Customer,43,Personal Travel,Eco,309,3,5,3,1,4,4,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +15636,17728,Female,Loyal Customer,24,Business travel,Business,383,3,3,3,3,4,4,4,4,2,2,4,2,5,4,0,7.0,satisfied +15637,111119,Male,Loyal Customer,57,Business travel,Business,3054,2,2,3,2,5,5,5,5,4,5,5,5,5,5,159,155.0,satisfied +15638,48460,Female,Loyal Customer,38,Business travel,Eco,666,4,4,4,4,4,4,4,4,3,5,1,2,3,4,87,81.0,satisfied +15639,65101,Male,Loyal Customer,20,Personal Travel,Eco,354,5,3,5,3,2,5,2,2,4,5,4,4,3,2,0,1.0,satisfied +15640,27392,Female,Loyal Customer,22,Business travel,Business,3700,3,3,3,3,5,5,5,5,5,1,3,1,5,5,0,0.0,satisfied +15641,3296,Male,Loyal Customer,27,Personal Travel,Eco,479,2,2,2,4,2,2,3,4,5,3,3,3,2,3,132,185.0,neutral or dissatisfied +15642,100984,Male,Loyal Customer,27,Personal Travel,Eco,1524,3,3,2,3,1,2,1,1,4,1,2,4,3,1,0,0.0,neutral or dissatisfied +15643,69822,Female,Loyal Customer,58,Business travel,Business,1809,2,1,2,2,3,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +15644,68611,Male,Loyal Customer,40,Business travel,Business,237,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +15645,23018,Male,Loyal Customer,13,Personal Travel,Eco Plus,489,3,3,3,4,5,3,5,5,1,2,3,3,3,5,0,0.0,neutral or dissatisfied +15646,86563,Female,Loyal Customer,44,Personal Travel,Eco Plus,760,3,1,2,4,2,3,3,5,5,2,1,4,5,4,2,0.0,neutral or dissatisfied +15647,128884,Male,Loyal Customer,43,Business travel,Business,2454,4,4,4,4,4,4,4,3,2,3,4,4,5,4,0,0.0,satisfied +15648,107884,Female,disloyal Customer,42,Business travel,Business,228,2,2,2,3,3,2,3,3,4,2,4,5,4,3,21,17.0,neutral or dissatisfied +15649,119977,Female,Loyal Customer,63,Personal Travel,Eco,868,1,4,1,4,1,3,4,3,3,1,3,2,3,2,8,3.0,neutral or dissatisfied +15650,67435,Male,disloyal Customer,23,Business travel,Eco,641,3,1,3,2,5,3,5,5,2,1,3,4,3,5,0,0.0,neutral or dissatisfied +15651,10265,Female,Loyal Customer,41,Personal Travel,Business,295,1,3,1,4,2,1,2,4,4,1,4,3,4,4,2,0.0,neutral or dissatisfied +15652,21880,Male,Loyal Customer,33,Business travel,Business,500,4,4,4,4,4,4,4,4,1,1,5,1,2,4,0,13.0,satisfied +15653,37034,Female,Loyal Customer,31,Business travel,Business,2814,5,5,2,5,4,4,4,4,5,1,1,3,3,4,0,0.0,satisfied +15654,41670,Female,disloyal Customer,26,Business travel,Eco,347,3,0,2,4,3,2,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +15655,126089,Female,disloyal Customer,24,Business travel,Business,600,5,0,5,3,1,5,1,1,4,2,5,5,4,1,0,0.0,satisfied +15656,118608,Female,Loyal Customer,75,Business travel,Business,3876,1,3,3,3,3,2,2,1,1,1,1,4,1,4,2,4.0,neutral or dissatisfied +15657,64729,Female,disloyal Customer,20,Business travel,Business,190,4,0,4,5,4,4,4,4,4,4,5,3,5,4,1,0.0,satisfied +15658,14171,Male,Loyal Customer,37,Business travel,Business,620,3,2,2,2,5,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +15659,3027,Female,Loyal Customer,31,Personal Travel,Eco,862,2,4,2,2,5,2,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +15660,93188,Male,Loyal Customer,59,Personal Travel,Eco Plus,1183,2,4,2,3,4,2,4,4,5,2,3,4,4,4,19,26.0,neutral or dissatisfied +15661,98584,Male,Loyal Customer,33,Business travel,Business,994,3,3,3,3,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +15662,29614,Male,Loyal Customer,33,Business travel,Business,1448,4,4,4,4,5,5,5,5,4,1,2,2,5,5,0,0.0,satisfied +15663,22150,Female,Loyal Customer,61,Business travel,Eco,633,4,4,4,4,1,1,4,4,4,4,4,5,4,3,0,0.0,satisfied +15664,69050,Female,Loyal Customer,47,Business travel,Business,1389,4,4,4,4,4,4,5,2,2,2,2,3,2,3,0,2.0,satisfied +15665,42528,Male,Loyal Customer,42,Personal Travel,Eco,328,2,0,2,4,3,2,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +15666,106149,Female,Loyal Customer,54,Business travel,Business,302,2,1,1,1,5,4,3,2,2,2,2,4,2,3,88,87.0,neutral or dissatisfied +15667,77689,Female,Loyal Customer,27,Business travel,Eco,696,1,2,2,2,1,1,1,1,3,5,3,3,3,1,0,0.0,neutral or dissatisfied +15668,113548,Male,disloyal Customer,74,Business travel,Business,223,2,2,2,1,2,2,1,2,1,1,2,4,2,2,0,0.0,neutral or dissatisfied +15669,92884,Male,Loyal Customer,54,Business travel,Business,134,0,5,0,4,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +15670,61744,Male,disloyal Customer,33,Business travel,Eco,1345,3,3,3,3,4,3,2,4,4,1,4,3,4,4,102,85.0,neutral or dissatisfied +15671,37012,Male,Loyal Customer,24,Personal Travel,Eco,805,3,4,3,3,2,3,2,2,1,5,3,3,3,2,125,129.0,neutral or dissatisfied +15672,79821,Female,Loyal Customer,59,Business travel,Business,1076,4,4,4,4,5,5,4,5,5,4,5,3,5,4,0,2.0,satisfied +15673,74946,Female,Loyal Customer,27,Business travel,Business,2475,4,4,4,4,5,5,5,5,4,4,5,3,4,5,5,0.0,satisfied +15674,7770,Female,Loyal Customer,72,Business travel,Business,1923,3,5,5,5,3,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +15675,62276,Female,Loyal Customer,57,Business travel,Business,2717,2,2,2,2,4,5,5,4,4,4,4,5,4,3,6,0.0,satisfied +15676,91865,Male,Loyal Customer,35,Personal Travel,Eco,1995,1,1,2,3,1,2,1,1,4,2,3,3,4,1,0,0.0,neutral or dissatisfied +15677,103194,Male,Loyal Customer,50,Business travel,Business,1890,2,4,4,4,4,4,3,2,2,2,2,4,2,3,7,0.0,neutral or dissatisfied +15678,107686,Male,Loyal Customer,44,Business travel,Business,466,3,4,4,4,1,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +15679,19881,Male,disloyal Customer,25,Business travel,Business,343,3,0,3,1,5,3,1,5,3,5,4,3,1,5,0,9.0,neutral or dissatisfied +15680,58193,Male,Loyal Customer,62,Business travel,Business,925,1,3,3,3,5,3,2,1,1,1,1,4,1,4,4,16.0,neutral or dissatisfied +15681,19913,Female,Loyal Customer,24,Business travel,Eco,315,3,3,2,3,3,3,4,3,3,3,3,2,3,3,12,16.0,neutral or dissatisfied +15682,104465,Female,Loyal Customer,55,Personal Travel,Eco,1123,4,4,3,3,4,4,4,2,2,3,2,3,2,4,0,0.0,satisfied +15683,18968,Female,Loyal Customer,43,Personal Travel,Eco Plus,448,1,5,1,2,4,5,4,3,3,1,3,5,3,5,4,,neutral or dissatisfied +15684,78153,Male,Loyal Customer,41,Business travel,Business,2425,4,4,4,4,2,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +15685,36253,Male,Loyal Customer,53,Business travel,Eco,728,2,3,3,3,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +15686,55595,Female,Loyal Customer,33,Business travel,Business,2617,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,30.0,satisfied +15687,47484,Female,Loyal Customer,40,Personal Travel,Eco,558,2,5,1,1,1,1,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +15688,64323,Male,disloyal Customer,27,Business travel,Business,1172,2,1,1,4,4,1,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +15689,65944,Male,disloyal Customer,25,Business travel,Business,1372,3,2,3,4,5,3,5,5,3,2,3,4,4,5,0,0.0,neutral or dissatisfied +15690,47663,Female,Loyal Customer,38,Business travel,Eco,1334,2,1,1,1,2,1,2,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +15691,48918,Male,Loyal Customer,35,Business travel,Business,3488,0,0,0,3,4,1,1,2,2,2,2,1,2,2,0,0.0,satisfied +15692,58352,Male,Loyal Customer,64,Personal Travel,Business,646,1,3,1,1,1,3,2,4,4,1,4,3,4,1,3,0.0,neutral or dissatisfied +15693,113612,Female,Loyal Customer,32,Personal Travel,Eco,407,5,4,1,3,3,1,3,3,3,5,1,2,5,3,13,2.0,satisfied +15694,64767,Male,Loyal Customer,50,Business travel,Business,551,4,4,4,4,3,5,5,5,5,5,5,3,5,5,17,13.0,satisfied +15695,74485,Male,Loyal Customer,20,Business travel,Business,1126,3,1,5,1,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +15696,80108,Female,disloyal Customer,24,Business travel,Eco,126,4,0,4,1,4,4,4,4,1,1,2,1,4,4,0,0.0,neutral or dissatisfied +15697,83651,Female,Loyal Customer,49,Business travel,Business,577,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +15698,45331,Female,Loyal Customer,46,Business travel,Eco,290,4,2,2,2,5,3,4,4,4,4,4,1,4,3,0,0.0,satisfied +15699,121482,Female,Loyal Customer,15,Personal Travel,Eco,331,1,5,1,2,5,1,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +15700,36758,Female,Loyal Customer,31,Business travel,Business,2602,3,3,3,3,4,4,4,2,3,4,2,4,3,4,19,21.0,satisfied +15701,113172,Male,Loyal Customer,25,Personal Travel,Eco,889,4,4,4,3,2,4,2,2,4,5,5,3,5,2,9,0.0,satisfied +15702,22068,Female,Loyal Customer,25,Personal Travel,Eco,304,4,1,4,4,1,4,1,1,4,4,3,3,3,1,80,69.0,neutral or dissatisfied +15703,80365,Male,Loyal Customer,45,Business travel,Business,3559,4,4,4,4,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +15704,62298,Male,Loyal Customer,42,Business travel,Business,414,1,1,1,1,1,2,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +15705,116927,Male,Loyal Customer,45,Business travel,Eco,651,1,5,2,5,1,1,1,1,4,5,4,1,3,1,21,9.0,neutral or dissatisfied +15706,24838,Male,Loyal Customer,11,Personal Travel,Eco,991,2,4,2,4,2,1,1,1,4,3,3,1,2,1,207,205.0,neutral or dissatisfied +15707,101985,Female,Loyal Customer,20,Personal Travel,Eco,628,0,5,0,1,1,0,1,1,3,4,4,3,5,1,16,4.0,satisfied +15708,69598,Female,Loyal Customer,60,Personal Travel,Eco,2475,3,5,3,3,3,1,1,2,5,5,1,1,1,1,0,0.0,neutral or dissatisfied +15709,128754,Female,Loyal Customer,47,Business travel,Business,550,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +15710,53008,Male,Loyal Customer,26,Business travel,Business,1702,4,4,4,4,4,4,4,4,4,1,5,5,3,4,0,0.0,satisfied +15711,5936,Male,Loyal Customer,33,Personal Travel,Eco,212,2,2,2,3,5,2,5,5,3,4,2,4,2,5,18,14.0,neutral or dissatisfied +15712,58924,Male,Loyal Customer,16,Personal Travel,Eco,888,3,3,2,4,2,2,2,2,2,3,3,1,1,2,49,29.0,neutral or dissatisfied +15713,95663,Female,Loyal Customer,47,Business travel,Business,845,1,1,1,1,4,5,4,5,5,5,5,5,5,3,20,17.0,satisfied +15714,17410,Female,Loyal Customer,48,Business travel,Eco,351,5,4,2,4,3,5,2,5,5,5,5,5,5,4,0,0.0,satisfied +15715,26967,Female,disloyal Customer,26,Business travel,Eco,867,1,1,1,2,4,1,4,4,5,3,5,3,5,4,15,14.0,neutral or dissatisfied +15716,100078,Female,disloyal Customer,37,Business travel,Eco Plus,220,3,3,3,4,3,3,3,3,2,3,3,4,3,3,0,1.0,neutral or dissatisfied +15717,14133,Female,Loyal Customer,34,Business travel,Business,2365,2,5,5,5,3,3,4,2,2,2,2,4,2,2,5,2.0,neutral or dissatisfied +15718,94698,Male,Loyal Customer,49,Business travel,Business,2418,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +15719,55598,Male,Loyal Customer,44,Business travel,Business,3896,4,4,4,4,3,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +15720,82291,Female,Loyal Customer,38,Business travel,Eco Plus,1081,5,2,2,2,5,5,5,5,3,2,1,3,2,5,1,20.0,satisfied +15721,31454,Male,Loyal Customer,28,Personal Travel,Business,862,5,5,5,5,2,5,2,2,5,2,4,4,4,2,0,0.0,satisfied +15722,113263,Female,disloyal Customer,39,Business travel,Business,236,4,4,4,1,4,4,4,4,4,3,5,4,4,4,41,33.0,satisfied +15723,126446,Male,Loyal Customer,28,Business travel,Business,1849,3,3,2,3,3,3,3,3,5,2,4,4,5,3,0,0.0,satisfied +15724,127873,Female,Loyal Customer,35,Business travel,Eco,1276,3,2,2,2,3,3,3,3,3,1,4,4,3,3,55,47.0,neutral or dissatisfied +15725,45314,Female,Loyal Customer,34,Business travel,Business,188,1,2,2,2,1,4,3,3,3,3,1,3,3,3,12,9.0,neutral or dissatisfied +15726,122043,Female,Loyal Customer,56,Business travel,Business,2984,4,4,4,4,2,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +15727,80640,Male,Loyal Customer,14,Personal Travel,Eco,282,2,4,2,4,4,2,4,4,3,3,1,4,4,4,0,0.0,neutral or dissatisfied +15728,76612,Male,disloyal Customer,25,Business travel,Business,481,4,0,4,2,4,4,4,4,5,3,4,3,5,4,0,0.0,satisfied +15729,66613,Male,Loyal Customer,56,Business travel,Business,761,1,1,1,1,3,4,4,4,4,4,4,4,4,4,117,100.0,satisfied +15730,67030,Male,Loyal Customer,39,Business travel,Business,929,2,2,5,2,4,5,5,4,4,4,4,4,4,4,40,30.0,satisfied +15731,4163,Male,Loyal Customer,17,Personal Travel,Eco,427,2,3,2,4,2,2,2,2,3,3,3,2,4,2,1,0.0,neutral or dissatisfied +15732,8504,Female,Loyal Customer,44,Business travel,Business,737,3,4,3,3,3,4,5,3,3,3,3,3,3,5,14,2.0,satisfied +15733,27424,Male,Loyal Customer,36,Business travel,Business,2504,2,1,1,1,1,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +15734,88835,Male,Loyal Customer,54,Personal Travel,Eco Plus,406,4,1,4,2,1,4,1,1,3,5,3,4,3,1,0,0.0,satisfied +15735,40299,Female,Loyal Customer,24,Personal Travel,Eco,463,2,5,2,5,5,2,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +15736,94820,Female,Loyal Customer,55,Business travel,Business,2769,4,4,4,4,4,2,2,4,4,4,4,4,4,1,0,3.0,neutral or dissatisfied +15737,76092,Female,Loyal Customer,30,Personal Travel,Eco,669,3,4,3,3,4,3,2,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +15738,72932,Male,Loyal Customer,48,Business travel,Business,1096,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +15739,52391,Female,Loyal Customer,34,Personal Travel,Eco,451,3,3,3,1,3,3,3,3,5,2,5,5,1,3,0,0.0,neutral or dissatisfied +15740,19662,Male,Loyal Customer,29,Personal Travel,Eco,1236,4,5,4,4,4,4,1,4,3,2,3,4,5,4,12,0.0,neutral or dissatisfied +15741,36896,Male,Loyal Customer,16,Personal Travel,Eco,1368,2,4,2,4,1,2,4,1,4,4,4,3,5,1,4,0.0,neutral or dissatisfied +15742,95470,Male,Loyal Customer,25,Business travel,Business,192,2,2,2,2,5,5,5,5,5,3,5,4,4,5,96,86.0,satisfied +15743,129702,Female,Loyal Customer,18,Business travel,Business,337,2,1,1,1,2,2,2,2,2,4,3,2,4,2,37,31.0,neutral or dissatisfied +15744,46220,Female,Loyal Customer,48,Business travel,Business,3804,3,3,3,3,2,5,2,4,4,4,4,2,4,4,0,4.0,satisfied +15745,37432,Male,Loyal Customer,51,Business travel,Eco,944,5,4,4,4,5,5,5,5,4,2,2,3,3,5,0,0.0,satisfied +15746,59613,Female,Loyal Customer,23,Business travel,Business,3737,3,1,1,1,3,3,3,3,3,4,3,3,3,3,22,22.0,neutral or dissatisfied +15747,99666,Male,Loyal Customer,10,Personal Travel,Eco,1050,3,5,3,1,5,3,5,5,4,3,4,4,4,5,24,5.0,neutral or dissatisfied +15748,75372,Male,Loyal Customer,48,Business travel,Business,2585,3,3,3,3,1,4,4,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +15749,12555,Female,Loyal Customer,36,Personal Travel,Eco,828,1,4,2,1,4,2,4,4,4,2,5,5,5,4,84,73.0,neutral or dissatisfied +15750,101384,Male,Loyal Customer,47,Business travel,Business,486,4,4,1,4,2,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +15751,111114,Male,Loyal Customer,56,Business travel,Business,2434,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +15752,115313,Female,Loyal Customer,76,Business travel,Business,390,1,1,1,1,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +15753,99007,Female,Loyal Customer,25,Business travel,Eco Plus,569,2,1,1,1,2,2,3,2,3,3,3,3,3,2,16,19.0,neutral or dissatisfied +15754,22158,Male,disloyal Customer,26,Business travel,Eco,565,3,5,3,3,4,3,4,4,5,5,1,3,4,4,1,0.0,neutral or dissatisfied +15755,43593,Female,Loyal Customer,33,Business travel,Business,2899,2,2,2,2,4,4,4,1,1,2,4,4,3,4,157,136.0,satisfied +15756,113086,Female,Loyal Customer,46,Business travel,Business,3019,3,3,3,3,3,3,3,3,3,3,3,4,3,3,1,3.0,neutral or dissatisfied +15757,28091,Female,disloyal Customer,38,Business travel,Business,459,3,3,3,4,5,3,5,5,2,2,4,4,3,5,0,0.0,neutral or dissatisfied +15758,26605,Male,Loyal Customer,31,Business travel,Business,1975,1,1,1,1,5,5,5,5,2,4,3,3,1,5,63,66.0,satisfied +15759,90927,Male,disloyal Customer,38,Business travel,Eco,115,4,3,4,2,4,4,4,4,2,5,2,1,5,4,0,0.0,satisfied +15760,29186,Female,Loyal Customer,39,Personal Travel,Eco Plus,679,3,4,3,1,2,3,2,2,5,3,4,3,5,2,0,9.0,neutral or dissatisfied +15761,108309,Female,disloyal Customer,49,Business travel,Business,1750,2,2,2,3,2,2,3,2,5,5,5,3,4,2,13,0.0,neutral or dissatisfied +15762,82969,Male,Loyal Customer,40,Business travel,Business,2000,5,5,5,5,2,4,4,4,4,4,4,4,4,4,30,20.0,satisfied +15763,17329,Female,Loyal Customer,51,Business travel,Eco Plus,403,5,3,3,3,4,3,2,5,5,5,5,1,5,3,117,117.0,satisfied +15764,97702,Male,Loyal Customer,54,Business travel,Business,456,3,3,3,3,1,4,3,3,3,3,3,3,3,3,46,28.0,neutral or dissatisfied +15765,32493,Female,Loyal Customer,32,Business travel,Eco,163,2,3,3,3,2,2,2,2,1,2,4,3,3,2,0,6.0,neutral or dissatisfied +15766,94676,Male,Loyal Customer,41,Business travel,Business,239,1,2,2,2,4,2,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +15767,71899,Male,Loyal Customer,68,Personal Travel,Eco,1723,4,4,4,1,5,4,5,5,3,3,4,3,5,5,11,0.0,satisfied +15768,83021,Female,Loyal Customer,50,Business travel,Business,1086,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +15769,46776,Male,Loyal Customer,70,Personal Travel,Eco Plus,141,3,3,3,3,4,3,2,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +15770,69660,Male,disloyal Customer,17,Business travel,Eco,569,3,4,3,4,2,3,1,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +15771,55334,Male,Loyal Customer,68,Personal Travel,Eco,1117,4,4,4,4,4,4,5,4,3,2,5,5,5,4,12,26.0,neutral or dissatisfied +15772,86486,Male,Loyal Customer,68,Personal Travel,Eco,760,2,4,2,2,4,2,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +15773,39576,Male,disloyal Customer,30,Business travel,Eco,679,3,3,3,2,3,3,3,3,5,3,5,3,4,3,0,3.0,neutral or dissatisfied +15774,104479,Male,Loyal Customer,36,Personal Travel,Eco,1671,4,4,4,1,3,4,3,3,4,4,2,4,4,3,12,23.0,neutral or dissatisfied +15775,113185,Male,Loyal Customer,45,Business travel,Business,1924,1,1,1,1,2,4,5,4,4,3,4,5,4,4,0,0.0,satisfied +15776,37988,Female,disloyal Customer,28,Business travel,Eco,1237,2,2,2,2,2,2,2,2,2,3,4,3,2,2,39,27.0,neutral or dissatisfied +15777,101720,Female,Loyal Customer,47,Personal Travel,Eco,986,2,5,2,3,2,5,4,5,5,2,5,3,5,4,66,59.0,neutral or dissatisfied +15778,66380,Male,Loyal Customer,43,Business travel,Business,1562,1,1,1,1,3,5,4,5,5,5,5,5,5,3,95,87.0,satisfied +15779,52387,Female,Loyal Customer,21,Personal Travel,Eco,509,3,5,3,1,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +15780,15147,Female,disloyal Customer,26,Business travel,Eco,912,1,1,1,4,5,1,5,5,1,5,3,3,4,5,11,8.0,neutral or dissatisfied +15781,684,Male,Loyal Customer,32,Business travel,Business,134,2,1,1,1,1,1,2,1,4,3,4,4,3,1,3,0.0,neutral or dissatisfied +15782,15185,Male,disloyal Customer,37,Business travel,Eco,461,2,0,2,4,4,2,3,4,1,4,5,2,3,4,0,0.0,neutral or dissatisfied +15783,29438,Female,Loyal Customer,74,Business travel,Business,1569,3,3,3,3,4,3,4,4,4,4,4,2,4,2,1,0.0,satisfied +15784,87883,Male,Loyal Customer,31,Personal Travel,Eco Plus,214,1,0,1,3,1,4,5,3,4,4,4,5,3,5,145,136.0,neutral or dissatisfied +15785,91517,Female,Loyal Customer,19,Personal Travel,Eco,1626,5,4,5,4,2,5,2,2,5,3,5,5,5,2,2,0.0,satisfied +15786,31269,Male,Loyal Customer,52,Business travel,Business,533,5,5,5,5,3,5,2,4,4,4,4,2,4,4,37,33.0,satisfied +15787,34148,Female,disloyal Customer,21,Business travel,Business,1129,1,1,1,3,3,1,1,3,4,1,3,4,3,3,0,9.0,neutral or dissatisfied +15788,20649,Female,disloyal Customer,43,Business travel,Eco,552,3,4,3,5,4,3,4,4,2,1,3,2,2,4,35,25.0,neutral or dissatisfied +15789,126207,Male,Loyal Customer,43,Business travel,Eco,590,4,1,5,5,4,4,4,4,1,5,2,4,2,4,0,6.0,neutral or dissatisfied +15790,16593,Female,Loyal Customer,50,Business travel,Business,2418,2,2,2,2,4,4,4,5,5,5,5,5,5,3,86,66.0,satisfied +15791,63843,Female,Loyal Customer,23,Business travel,Business,1192,1,1,1,1,5,5,5,5,3,2,5,3,5,5,0,4.0,satisfied +15792,104767,Male,Loyal Customer,48,Personal Travel,Eco,1246,2,4,2,3,4,2,4,4,4,4,4,3,5,4,19,4.0,neutral or dissatisfied +15793,20674,Male,Loyal Customer,34,Business travel,Business,1820,1,1,1,1,1,4,5,5,5,5,5,1,5,5,0,0.0,satisfied +15794,106250,Female,Loyal Customer,35,Personal Travel,Eco,1167,4,1,5,3,3,5,3,3,1,3,2,4,3,3,0,0.0,neutral or dissatisfied +15795,52111,Female,Loyal Customer,14,Personal Travel,Eco,351,4,5,4,2,4,4,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +15796,42090,Female,Loyal Customer,11,Personal Travel,Business,964,3,5,3,1,5,3,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +15797,66119,Male,Loyal Customer,57,Business travel,Business,583,5,5,2,5,4,5,5,5,5,5,5,4,5,5,4,0.0,satisfied +15798,969,Female,disloyal Customer,66,Business travel,Business,396,3,3,3,3,3,2,2,3,4,4,4,2,4,2,195,295.0,neutral or dissatisfied +15799,70079,Male,Loyal Customer,42,Business travel,Business,3387,2,2,3,2,2,4,4,5,5,5,5,3,5,4,6,0.0,satisfied +15800,25292,Female,Loyal Customer,57,Personal Travel,Eco,321,2,2,2,4,4,4,3,2,2,2,2,2,2,2,6,9.0,neutral or dissatisfied +15801,94985,Male,Loyal Customer,34,Personal Travel,Eco,239,3,5,0,3,2,0,2,2,5,4,4,3,5,2,4,5.0,neutral or dissatisfied +15802,81956,Male,Loyal Customer,42,Business travel,Business,1589,4,4,4,4,2,4,4,5,5,5,5,4,5,5,2,0.0,satisfied +15803,54983,Male,Loyal Customer,43,Business travel,Business,1379,1,1,1,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +15804,91643,Male,Loyal Customer,44,Personal Travel,Eco,1184,3,5,3,2,2,3,1,2,5,5,3,3,5,2,84,85.0,neutral or dissatisfied +15805,52467,Female,disloyal Customer,40,Business travel,Business,109,4,4,4,2,1,4,1,1,4,3,1,1,4,1,5,3.0,satisfied +15806,21329,Male,Loyal Customer,23,Business travel,Eco,761,5,4,1,1,5,5,5,5,3,1,2,3,1,5,46,46.0,satisfied +15807,39216,Female,Loyal Customer,57,Business travel,Business,67,0,5,0,1,5,5,3,5,5,5,5,3,5,2,0,0.0,satisfied +15808,3549,Female,Loyal Customer,50,Business travel,Business,227,3,3,3,3,2,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +15809,43563,Female,Loyal Customer,24,Personal Travel,Eco,637,1,4,1,3,1,1,1,1,4,1,4,4,4,1,45,53.0,neutral or dissatisfied +15810,94738,Male,Loyal Customer,38,Business travel,Business,1678,4,5,5,5,1,3,4,4,4,3,4,3,4,3,45,40.0,neutral or dissatisfied +15811,17738,Male,Loyal Customer,18,Business travel,Eco,383,5,3,4,3,5,5,4,5,1,3,1,1,4,5,0,0.0,satisfied +15812,19102,Male,Loyal Customer,33,Business travel,Eco,323,5,2,2,2,5,5,5,5,3,2,2,1,4,5,49,116.0,satisfied +15813,17560,Male,Loyal Customer,52,Business travel,Eco,852,4,5,5,5,4,4,4,4,1,3,5,1,4,4,15,0.0,satisfied +15814,86622,Female,Loyal Customer,59,Business travel,Eco,746,1,3,3,3,1,2,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +15815,93400,Female,Loyal Customer,30,Business travel,Business,672,2,2,2,2,4,4,4,4,5,2,5,3,4,4,31,23.0,satisfied +15816,37162,Female,Loyal Customer,67,Personal Travel,Eco,1237,2,5,1,1,3,4,5,2,2,1,3,5,2,5,0,0.0,neutral or dissatisfied +15817,90461,Female,Loyal Customer,46,Business travel,Business,250,3,3,3,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +15818,94017,Male,disloyal Customer,25,Business travel,Business,192,4,5,4,1,5,4,5,5,3,5,5,5,4,5,32,20.0,satisfied +15819,32121,Female,Loyal Customer,57,Business travel,Business,2815,0,5,0,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +15820,10022,Male,Loyal Customer,16,Personal Travel,Eco Plus,457,2,5,2,3,4,2,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +15821,95733,Female,Loyal Customer,36,Business travel,Business,237,0,0,0,3,3,5,4,4,4,4,4,5,4,3,4,15.0,satisfied +15822,66368,Male,Loyal Customer,36,Personal Travel,Eco,986,4,4,4,3,4,4,4,4,5,3,5,3,5,4,40,27.0,neutral or dissatisfied +15823,57123,Female,Loyal Customer,38,Business travel,Eco,822,3,4,4,4,3,3,3,3,4,3,4,1,4,3,21,17.0,neutral or dissatisfied +15824,99106,Male,Loyal Customer,43,Business travel,Business,237,1,3,3,3,5,4,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +15825,98802,Female,Loyal Customer,14,Personal Travel,Eco Plus,1111,4,5,4,1,2,4,2,2,3,3,5,4,5,2,0,0.0,satisfied +15826,77235,Male,Loyal Customer,52,Business travel,Business,1590,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +15827,15417,Female,disloyal Customer,26,Business travel,Eco,377,2,3,2,3,3,2,3,3,3,1,4,4,3,3,20,62.0,neutral or dissatisfied +15828,72706,Female,Loyal Customer,48,Business travel,Eco Plus,1102,4,1,1,1,2,4,3,4,4,4,4,2,4,4,0,9.0,neutral or dissatisfied +15829,67693,Female,Loyal Customer,27,Business travel,Business,1464,2,2,2,2,5,5,5,5,5,4,5,3,5,5,77,102.0,satisfied +15830,33936,Male,Loyal Customer,22,Business travel,Business,1940,4,4,4,4,3,5,3,3,5,2,1,5,1,3,0,0.0,satisfied +15831,90268,Female,Loyal Customer,35,Business travel,Business,3185,2,3,2,3,3,4,3,2,2,2,2,2,2,3,9,11.0,neutral or dissatisfied +15832,46406,Female,Loyal Customer,52,Business travel,Eco,458,5,2,5,2,2,4,3,5,5,5,5,4,5,2,0,0.0,satisfied +15833,1326,Male,disloyal Customer,36,Business travel,Business,102,2,2,2,5,5,2,5,5,3,4,5,3,5,5,35,28.0,neutral or dissatisfied +15834,18342,Female,disloyal Customer,25,Business travel,Eco,563,4,5,4,4,3,4,3,3,5,1,2,1,2,3,0,0.0,neutral or dissatisfied +15835,87695,Male,Loyal Customer,67,Personal Travel,Eco,591,2,4,2,2,5,2,5,5,3,2,5,4,5,5,48,33.0,neutral or dissatisfied +15836,76906,Male,Loyal Customer,13,Personal Travel,Eco,630,2,4,2,3,1,2,1,1,4,4,4,4,4,1,23,24.0,neutral or dissatisfied +15837,54430,Male,Loyal Customer,53,Personal Travel,Eco,305,1,4,1,4,4,1,4,4,5,2,5,4,4,4,42,36.0,neutral or dissatisfied +15838,87588,Male,Loyal Customer,59,Personal Travel,Eco,432,2,3,2,4,4,2,1,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +15839,77794,Female,Loyal Customer,28,Personal Travel,Eco,813,3,0,2,3,4,2,4,4,5,4,5,3,4,4,2,9.0,neutral or dissatisfied +15840,122656,Male,Loyal Customer,46,Business travel,Business,361,3,3,3,3,4,4,5,5,5,5,5,3,5,5,18,9.0,satisfied +15841,93460,Female,Loyal Customer,61,Personal Travel,Eco,723,3,3,3,4,1,5,2,4,4,3,4,1,4,4,6,27.0,neutral or dissatisfied +15842,56151,Male,disloyal Customer,27,Business travel,Eco,1400,1,1,1,4,5,1,4,5,4,1,3,3,3,5,0,0.0,neutral or dissatisfied +15843,83335,Female,Loyal Customer,67,Personal Travel,Eco,2105,2,5,3,5,4,5,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +15844,55667,Male,disloyal Customer,27,Business travel,Business,495,2,2,2,1,2,2,2,2,4,1,1,1,2,2,0,0.0,neutral or dissatisfied +15845,21872,Male,Loyal Customer,43,Business travel,Eco,551,5,2,2,2,5,5,5,5,5,2,1,3,2,5,1,0.0,satisfied +15846,304,Female,Loyal Customer,43,Business travel,Business,1895,1,2,2,2,1,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +15847,33668,Female,Loyal Customer,34,Personal Travel,Eco Plus,399,3,3,3,4,1,3,1,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +15848,80422,Female,disloyal Customer,24,Business travel,Eco,1377,1,1,1,3,1,1,1,1,3,4,4,1,3,1,63,65.0,neutral or dissatisfied +15849,78801,Male,Loyal Customer,40,Personal Travel,Eco,447,3,4,3,4,5,3,5,5,5,4,5,3,5,5,0,1.0,neutral or dissatisfied +15850,13320,Male,disloyal Customer,27,Business travel,Eco,764,1,1,1,4,2,1,5,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +15851,46222,Female,Loyal Customer,42,Business travel,Business,3183,5,5,5,5,4,1,1,3,3,4,3,2,3,3,0,0.0,satisfied +15852,101750,Female,Loyal Customer,40,Business travel,Business,1590,1,1,3,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +15853,71829,Female,disloyal Customer,19,Business travel,Business,1411,4,5,4,5,4,4,3,4,5,2,5,5,4,4,1,0.0,satisfied +15854,76448,Female,Loyal Customer,26,Business travel,Business,516,3,3,3,3,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +15855,30703,Female,Loyal Customer,41,Business travel,Eco Plus,680,5,2,2,2,2,2,4,5,5,5,5,5,5,4,0,0.0,satisfied +15856,65444,Female,Loyal Customer,25,Personal Travel,Business,1067,2,4,2,3,1,2,1,1,3,4,4,4,4,1,0,5.0,neutral or dissatisfied +15857,42264,Male,disloyal Customer,26,Business travel,Eco,462,3,3,3,3,3,5,5,4,4,3,3,5,3,5,191,196.0,neutral or dissatisfied +15858,73756,Female,Loyal Customer,27,Personal Travel,Eco,204,3,4,0,1,4,0,4,4,5,2,4,2,3,4,0,2.0,neutral or dissatisfied +15859,66340,Male,Loyal Customer,59,Business travel,Business,986,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +15860,36677,Male,Loyal Customer,53,Personal Travel,Eco,1249,3,5,3,4,5,3,5,5,4,5,4,5,3,5,0,,neutral or dissatisfied +15861,117425,Female,disloyal Customer,23,Business travel,Eco,807,3,3,3,4,4,3,4,4,2,1,3,1,3,4,13,0.0,neutral or dissatisfied +15862,64514,Male,Loyal Customer,26,Personal Travel,Business,354,3,4,3,3,5,3,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +15863,86118,Male,Loyal Customer,43,Business travel,Business,226,3,3,3,3,3,5,5,5,5,5,5,3,5,3,3,0.0,satisfied +15864,41375,Male,Loyal Customer,39,Business travel,Business,2087,3,3,5,3,5,3,4,3,3,4,3,4,3,2,0,0.0,satisfied +15865,12957,Female,Loyal Customer,20,Business travel,Eco Plus,456,2,4,4,4,2,2,1,2,3,4,4,2,3,2,0,0.0,neutral or dissatisfied +15866,79609,Male,Loyal Customer,28,Business travel,Business,712,1,1,1,1,3,3,3,3,5,4,4,3,5,3,0,0.0,satisfied +15867,68104,Male,Loyal Customer,46,Business travel,Eco,413,4,1,1,1,4,4,4,4,4,5,2,5,2,4,0,0.0,satisfied +15868,43273,Male,Loyal Customer,40,Business travel,Business,1610,5,5,5,5,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +15869,66963,Female,Loyal Customer,48,Business travel,Business,2318,3,3,3,3,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +15870,70763,Female,Loyal Customer,32,Business travel,Business,2620,1,1,1,1,5,5,5,5,5,4,5,3,5,5,1,0.0,satisfied +15871,23278,Female,Loyal Customer,57,Business travel,Eco,809,4,2,2,2,5,1,5,4,4,4,4,5,4,3,126,111.0,satisfied +15872,113520,Male,Loyal Customer,47,Business travel,Business,3843,5,5,2,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +15873,60538,Male,Loyal Customer,40,Personal Travel,Eco,794,3,2,3,4,5,3,5,5,4,3,4,4,3,5,0,0.0,neutral or dissatisfied +15874,114050,Female,Loyal Customer,59,Business travel,Business,2139,3,5,4,5,4,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +15875,18401,Female,Loyal Customer,38,Business travel,Eco,284,4,3,3,3,4,4,4,4,2,2,3,3,3,4,57,61.0,satisfied +15876,4949,Female,Loyal Customer,40,Business travel,Business,931,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,16.0,satisfied +15877,77920,Male,Loyal Customer,47,Business travel,Business,2201,4,4,4,4,2,5,5,5,5,5,4,5,5,4,56,52.0,satisfied +15878,73884,Male,Loyal Customer,22,Business travel,Business,2342,5,5,5,5,2,2,2,3,4,4,5,2,4,2,0,0.0,satisfied +15879,35754,Female,disloyal Customer,60,Business travel,Eco,1608,1,1,1,3,1,1,1,1,3,1,4,5,1,1,0,0.0,neutral or dissatisfied +15880,17071,Female,Loyal Customer,12,Personal Travel,Eco,282,2,4,2,4,3,2,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +15881,95053,Female,Loyal Customer,25,Personal Travel,Eco,323,2,1,2,3,4,2,3,4,2,1,2,1,3,4,3,0.0,neutral or dissatisfied +15882,107480,Female,disloyal Customer,26,Business travel,Business,711,2,0,1,3,3,1,5,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +15883,9997,Male,Loyal Customer,9,Personal Travel,Eco,457,3,5,3,1,4,3,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +15884,76281,Male,Loyal Customer,45,Personal Travel,Eco,1927,3,5,3,2,2,3,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +15885,57778,Female,Loyal Customer,28,Business travel,Business,2611,1,1,1,1,1,1,1,4,3,2,2,1,1,1,48,78.0,neutral or dissatisfied +15886,90693,Female,Loyal Customer,40,Business travel,Business,3677,1,1,1,1,5,4,4,3,3,4,3,4,3,5,0,4.0,satisfied +15887,79789,Male,disloyal Customer,23,Business travel,Eco,1207,4,4,4,3,1,4,1,1,4,3,4,5,4,1,14,1.0,satisfied +15888,78311,Male,Loyal Customer,37,Personal Travel,Eco Plus,1598,4,4,4,3,5,4,5,5,4,4,4,4,4,5,0,0.0,satisfied +15889,34590,Female,disloyal Customer,12,Business travel,Eco,1333,3,3,3,4,1,3,1,1,1,4,3,5,5,1,0,0.0,neutral or dissatisfied +15890,76312,Male,Loyal Customer,42,Business travel,Business,2182,3,3,3,3,1,2,1,3,3,3,3,4,3,1,3,1.0,neutral or dissatisfied +15891,24537,Male,Loyal Customer,27,Business travel,Business,696,2,2,2,2,4,4,4,4,5,2,3,2,2,4,0,0.0,satisfied +15892,23492,Male,Loyal Customer,49,Business travel,Business,303,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +15893,19083,Female,Loyal Customer,31,Business travel,Business,296,1,1,1,1,4,5,4,4,2,2,5,5,1,4,0,0.0,satisfied +15894,86009,Male,Loyal Customer,54,Business travel,Business,432,3,3,3,3,4,4,5,5,5,5,5,5,5,3,1,0.0,satisfied +15895,116854,Female,disloyal Customer,34,Business travel,Business,304,3,3,3,2,4,3,1,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +15896,63247,Female,Loyal Customer,60,Business travel,Business,337,3,3,3,3,4,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +15897,65320,Female,Loyal Customer,41,Business travel,Business,432,3,3,2,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +15898,26154,Female,Loyal Customer,49,Business travel,Business,2103,5,5,5,5,1,5,2,5,5,5,5,3,5,1,17,8.0,satisfied +15899,7640,Female,Loyal Customer,32,Business travel,Business,604,4,4,4,4,3,3,3,3,4,3,5,3,4,3,0,0.0,satisfied +15900,78429,Female,disloyal Customer,21,Business travel,Business,666,4,4,4,1,2,4,2,2,4,5,5,3,4,2,0,23.0,satisfied +15901,95078,Female,Loyal Customer,13,Personal Travel,Eco,319,3,3,3,3,3,3,3,3,1,2,2,5,5,3,0,0.0,neutral or dissatisfied +15902,28618,Female,disloyal Customer,17,Business travel,Eco,731,4,5,5,2,2,4,2,2,2,5,5,4,2,2,0,0.0,neutral or dissatisfied +15903,82247,Female,disloyal Customer,26,Business travel,Business,405,4,4,4,4,1,4,1,1,3,3,5,5,4,1,0,0.0,satisfied +15904,10882,Female,disloyal Customer,20,Business travel,Eco,158,2,3,2,3,4,2,4,4,1,2,3,3,3,4,20,23.0,neutral or dissatisfied +15905,55280,Male,Loyal Customer,43,Business travel,Business,1608,4,4,3,4,4,4,4,3,3,5,4,4,5,4,133,103.0,satisfied +15906,11048,Male,Loyal Customer,48,Personal Travel,Eco,312,4,4,4,5,4,4,1,4,5,3,4,4,5,4,0,0.0,satisfied +15907,64489,Female,disloyal Customer,22,Business travel,Eco,247,0,4,0,2,4,0,4,4,5,5,5,3,4,4,19,16.0,satisfied +15908,63209,Female,Loyal Customer,42,Business travel,Business,337,1,1,3,1,3,4,4,4,4,4,4,5,4,3,52,46.0,satisfied +15909,23475,Male,Loyal Customer,7,Personal Travel,Eco,627,2,4,2,3,5,2,5,5,3,4,5,5,4,5,0,6.0,neutral or dissatisfied +15910,119855,Male,Loyal Customer,45,Business travel,Eco,536,2,4,4,4,2,2,2,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +15911,31854,Female,Loyal Customer,21,Personal Travel,Eco,2677,3,4,3,3,5,3,4,5,1,3,3,4,4,5,0,0.0,neutral or dissatisfied +15912,68662,Female,Loyal Customer,47,Business travel,Business,3584,4,1,1,1,4,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +15913,93815,Female,disloyal Customer,37,Business travel,Business,391,3,3,3,5,3,3,1,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +15914,20605,Female,Loyal Customer,51,Business travel,Business,1911,3,5,5,5,3,3,3,2,4,3,4,3,2,3,174,162.0,neutral or dissatisfied +15915,117032,Male,Loyal Customer,17,Business travel,Business,3841,3,3,3,3,4,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +15916,68898,Female,Loyal Customer,54,Personal Travel,Eco,936,1,1,1,3,3,4,4,5,5,1,5,2,5,2,0,0.0,neutral or dissatisfied +15917,47533,Female,Loyal Customer,46,Personal Travel,Eco,590,2,4,2,3,5,4,3,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +15918,37801,Female,Loyal Customer,59,Personal Travel,Eco Plus,1076,2,5,2,2,3,4,5,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +15919,57310,Female,disloyal Customer,44,Business travel,Business,414,2,2,2,5,3,2,1,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +15920,1912,Male,Loyal Customer,40,Business travel,Business,3504,0,1,1,4,5,5,5,4,4,4,4,3,4,4,29,32.0,satisfied +15921,37844,Male,disloyal Customer,27,Business travel,Eco,937,1,0,0,1,5,0,5,5,2,2,1,2,2,5,20,22.0,neutral or dissatisfied +15922,122520,Male,Loyal Customer,40,Personal Travel,Eco Plus,930,2,5,2,4,2,2,2,2,5,3,5,3,4,2,4,0.0,neutral or dissatisfied +15923,81433,Male,Loyal Customer,8,Personal Travel,Eco,448,2,1,2,3,2,2,2,2,4,2,3,4,3,2,1,0.0,neutral or dissatisfied +15924,61532,Male,Loyal Customer,11,Personal Travel,Eco,2419,3,4,3,3,3,3,3,3,2,4,5,4,1,3,0,0.0,neutral or dissatisfied +15925,29824,Female,disloyal Customer,23,Business travel,Eco,31,4,0,4,1,1,4,1,1,1,3,4,5,2,1,0,0.0,satisfied +15926,105756,Male,Loyal Customer,46,Business travel,Business,442,2,2,2,2,1,4,3,5,5,5,5,3,5,3,91,77.0,satisfied +15927,108277,Female,Loyal Customer,68,Personal Travel,Eco,895,2,3,2,3,4,4,4,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +15928,93059,Female,disloyal Customer,35,Business travel,Eco,297,2,1,2,3,3,2,3,3,1,5,2,3,3,3,0,6.0,neutral or dissatisfied +15929,47154,Female,Loyal Customer,25,Business travel,Business,2070,2,1,2,2,4,4,4,2,3,4,5,4,4,4,146,143.0,satisfied +15930,18726,Male,Loyal Customer,39,Personal Travel,Eco Plus,190,1,2,1,3,2,1,2,2,2,5,3,2,4,2,0,0.0,neutral or dissatisfied +15931,117160,Male,Loyal Customer,9,Personal Travel,Eco,647,3,5,3,5,4,3,4,4,2,3,3,4,3,4,20,9.0,neutral or dissatisfied +15932,41681,Female,Loyal Customer,49,Personal Travel,Eco,936,2,4,2,3,2,4,4,5,5,2,5,4,5,3,14,12.0,neutral or dissatisfied +15933,113005,Male,Loyal Customer,26,Personal Travel,Eco,1751,2,4,2,3,2,2,2,2,3,4,5,1,3,2,9,0.0,neutral or dissatisfied +15934,95507,Female,disloyal Customer,16,Business travel,Eco Plus,277,2,2,2,4,2,2,2,2,1,2,3,1,4,2,19,16.0,neutral or dissatisfied +15935,120673,Male,disloyal Customer,25,Business travel,Business,280,1,0,1,4,1,1,1,1,4,3,1,4,4,1,0,0.0,neutral or dissatisfied +15936,88592,Female,Loyal Customer,34,Personal Travel,Eco,271,1,5,1,3,1,1,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +15937,66595,Male,Loyal Customer,43,Business travel,Business,2651,4,1,1,1,3,4,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +15938,20820,Female,Loyal Customer,53,Business travel,Eco,508,2,2,4,4,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +15939,41567,Male,Loyal Customer,65,Personal Travel,Eco,1242,2,5,2,3,2,2,2,2,4,4,4,4,4,2,0,16.0,neutral or dissatisfied +15940,65393,Female,Loyal Customer,60,Personal Travel,Eco,631,4,4,4,1,2,4,2,1,1,4,1,5,1,2,0,0.0,neutral or dissatisfied +15941,120751,Male,Loyal Customer,44,Business travel,Business,3859,3,3,3,3,5,4,4,3,3,2,3,5,3,5,0,2.0,satisfied +15942,109516,Male,Loyal Customer,25,Business travel,Business,993,1,2,5,2,1,1,1,1,1,4,3,3,4,1,0,18.0,neutral or dissatisfied +15943,7026,Male,Loyal Customer,41,Personal Travel,Eco,299,3,5,3,3,3,3,3,3,4,5,5,5,5,3,23,33.0,neutral or dissatisfied +15944,79671,Male,Loyal Customer,27,Personal Travel,Eco,712,1,4,1,5,2,1,1,2,3,5,5,3,1,2,2,18.0,neutral or dissatisfied +15945,98185,Male,Loyal Customer,52,Business travel,Business,327,5,5,5,5,3,5,4,4,4,4,4,5,4,4,21,46.0,satisfied +15946,2335,Male,Loyal Customer,66,Personal Travel,Eco,691,1,4,1,1,1,1,1,1,3,5,4,4,4,1,0,1.0,neutral or dissatisfied +15947,15340,Female,disloyal Customer,26,Business travel,Business,377,4,0,4,1,5,4,5,5,4,3,4,5,4,5,0,0.0,satisfied +15948,1866,Female,Loyal Customer,46,Business travel,Business,3109,4,4,1,4,2,4,4,4,4,4,4,3,4,5,36,38.0,satisfied +15949,29621,Female,Loyal Customer,50,Business travel,Eco,1448,2,5,5,5,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +15950,89819,Female,disloyal Customer,22,Business travel,Eco,610,1,3,1,3,1,1,5,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +15951,50638,Male,Loyal Customer,68,Personal Travel,Eco,308,3,1,3,4,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +15952,28000,Male,Loyal Customer,26,Personal Travel,Business,763,1,5,1,3,5,1,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +15953,7568,Female,Loyal Customer,53,Business travel,Business,594,3,3,3,3,5,4,4,5,5,5,5,5,5,5,28,17.0,satisfied +15954,100183,Male,Loyal Customer,12,Personal Travel,Eco,468,1,4,1,4,3,1,5,3,4,1,5,1,4,3,42,41.0,neutral or dissatisfied +15955,56854,Female,Loyal Customer,48,Personal Travel,Business,2454,3,5,3,1,2,4,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +15956,40026,Male,Loyal Customer,56,Business travel,Eco,575,4,5,2,5,4,4,4,4,4,4,4,1,3,4,0,0.0,satisfied +15957,114070,Female,Loyal Customer,57,Business travel,Business,2139,3,3,2,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15958,58236,Female,Loyal Customer,49,Personal Travel,Eco,925,3,5,3,3,2,4,4,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +15959,56998,Female,Loyal Customer,21,Personal Travel,Eco,2454,2,5,2,5,2,5,5,3,2,1,4,5,3,5,0,0.0,neutral or dissatisfied +15960,114103,Male,Loyal Customer,30,Personal Travel,Eco Plus,1892,2,4,3,4,3,3,3,3,1,4,3,3,3,3,12,7.0,neutral or dissatisfied +15961,79895,Female,Loyal Customer,58,Business travel,Business,2536,1,1,1,1,5,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +15962,56243,Male,Loyal Customer,60,Business travel,Business,2434,1,1,1,1,4,4,5,4,4,4,4,5,4,3,20,0.0,satisfied +15963,111479,Female,Loyal Customer,11,Business travel,Eco,1452,4,2,2,2,4,4,4,4,3,5,4,4,4,4,6,0.0,neutral or dissatisfied +15964,119897,Male,Loyal Customer,33,Business travel,Eco Plus,912,2,1,1,1,2,2,2,2,4,3,4,2,3,2,2,5.0,neutral or dissatisfied +15965,44924,Female,Loyal Customer,44,Business travel,Business,2441,1,1,1,1,4,4,4,4,4,4,4,5,4,5,10,4.0,satisfied +15966,121512,Female,Loyal Customer,50,Personal Travel,Eco,1727,4,1,4,2,5,1,2,4,4,4,5,2,4,1,0,4.0,neutral or dissatisfied +15967,119726,Male,Loyal Customer,46,Business travel,Business,1920,1,4,4,4,2,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +15968,34137,Female,Loyal Customer,28,Business travel,Eco,1189,4,4,4,4,4,4,4,4,1,4,2,1,1,4,0,0.0,satisfied +15969,19933,Female,Loyal Customer,28,Personal Travel,Eco,240,3,4,3,2,1,3,1,1,5,3,1,3,2,1,0,0.0,neutral or dissatisfied +15970,79437,Female,Loyal Customer,60,Business travel,Business,1825,4,4,4,4,4,4,4,5,5,5,4,4,5,3,34,32.0,satisfied +15971,6824,Male,Loyal Customer,54,Personal Travel,Eco,224,4,5,0,3,1,0,1,1,3,2,5,4,4,1,0,30.0,neutral or dissatisfied +15972,32890,Male,Loyal Customer,57,Personal Travel,Eco,216,3,4,3,1,3,3,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +15973,16709,Female,Loyal Customer,48,Business travel,Business,3042,0,0,0,3,2,5,2,3,3,3,3,3,3,3,5,10.0,satisfied +15974,112366,Female,Loyal Customer,55,Business travel,Business,862,1,1,1,1,4,4,4,5,5,5,5,3,5,3,5,0.0,satisfied +15975,128613,Male,Loyal Customer,55,Business travel,Business,2357,2,2,2,2,2,5,4,4,4,4,4,4,4,5,7,0.0,satisfied +15976,19905,Male,disloyal Customer,23,Business travel,Eco,343,1,2,1,4,5,1,3,5,4,1,3,1,4,5,11,10.0,neutral or dissatisfied +15977,48711,Female,Loyal Customer,43,Business travel,Business,199,5,5,5,5,4,4,5,5,5,5,5,4,5,3,0,7.0,satisfied +15978,128837,Female,disloyal Customer,37,Business travel,Eco,975,1,1,1,3,1,3,3,3,5,4,4,3,3,3,4,0.0,neutral or dissatisfied +15979,14939,Female,Loyal Customer,40,Business travel,Eco,554,5,2,2,2,5,5,5,5,1,4,2,1,3,5,0,0.0,satisfied +15980,119427,Female,Loyal Customer,22,Personal Travel,Eco,399,3,4,3,5,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +15981,15611,Male,Loyal Customer,17,Personal Travel,Eco,292,1,4,1,2,3,1,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +15982,55257,Female,Loyal Customer,49,Business travel,Eco Plus,1009,3,2,2,2,5,4,3,4,4,3,4,2,4,1,7,14.0,neutral or dissatisfied +15983,125808,Female,Loyal Customer,36,Business travel,Business,2126,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +15984,106619,Female,Loyal Customer,49,Business travel,Eco,1216,3,5,5,5,3,3,3,1,3,4,3,3,4,3,134,137.0,neutral or dissatisfied +15985,21224,Male,Loyal Customer,35,Personal Travel,Eco,192,3,4,3,3,1,3,1,1,4,3,5,3,5,1,0,4.0,neutral or dissatisfied +15986,21149,Male,Loyal Customer,33,Personal Travel,Eco Plus,106,4,4,4,2,2,4,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +15987,79050,Male,disloyal Customer,26,Business travel,Business,356,1,2,1,3,1,1,1,1,3,4,3,1,4,1,0,0.0,neutral or dissatisfied +15988,122829,Male,Loyal Customer,47,Business travel,Business,3247,1,4,1,1,2,5,5,4,4,4,4,5,4,3,0,20.0,satisfied +15989,111869,Male,disloyal Customer,20,Business travel,Eco,804,3,3,3,3,5,3,5,5,1,1,3,2,3,5,0,20.0,neutral or dissatisfied +15990,41015,Male,Loyal Customer,36,Personal Travel,Business,1195,3,5,3,5,4,3,4,3,3,3,2,3,3,5,0,0.0,neutral or dissatisfied +15991,1980,Male,Loyal Customer,9,Personal Travel,Eco,285,4,5,4,3,2,4,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +15992,43962,Female,Loyal Customer,39,Business travel,Business,3131,4,4,4,4,2,2,3,4,4,4,4,1,4,1,0,13.0,satisfied +15993,9648,Male,Loyal Customer,32,Business travel,Business,199,5,5,5,5,5,5,4,5,4,2,5,4,5,5,24,24.0,satisfied +15994,31624,Male,disloyal Customer,39,Business travel,Eco,862,2,2,2,4,1,2,1,1,5,2,5,3,1,1,0,0.0,neutral or dissatisfied +15995,17377,Female,Loyal Customer,36,Business travel,Eco,637,4,3,3,3,4,4,4,4,4,3,1,5,1,4,0,0.0,satisfied +15996,92962,Male,Loyal Customer,43,Business travel,Eco,1694,2,5,5,5,2,2,2,2,4,5,3,1,4,2,20,9.0,neutral or dissatisfied +15997,60863,Female,Loyal Customer,52,Business travel,Business,1491,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +15998,110776,Male,Loyal Customer,45,Business travel,Business,2830,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,8.0,satisfied +15999,103459,Female,Loyal Customer,43,Business travel,Eco,393,3,2,2,2,4,5,4,3,3,3,3,1,3,5,53,47.0,satisfied +16000,51791,Female,Loyal Customer,55,Personal Travel,Eco,370,3,3,3,2,5,3,5,3,3,3,3,2,3,3,7,16.0,neutral or dissatisfied +16001,103335,Female,Loyal Customer,51,Personal Travel,Eco,1371,2,2,2,4,2,4,3,2,2,2,3,3,2,1,9,31.0,neutral or dissatisfied +16002,46628,Female,disloyal Customer,22,Business travel,Eco,125,3,2,3,3,1,3,1,1,1,5,4,1,4,1,0,1.0,neutral or dissatisfied +16003,9782,Female,Loyal Customer,35,Personal Travel,Eco,383,1,5,1,2,4,1,2,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +16004,85304,Female,Loyal Customer,37,Personal Travel,Eco,813,2,3,2,3,3,2,4,3,1,3,3,3,3,3,20,11.0,neutral or dissatisfied +16005,109327,Female,Loyal Customer,62,Personal Travel,Eco,1072,3,4,2,2,4,5,4,2,2,2,4,3,2,3,36,19.0,neutral or dissatisfied +16006,128932,Male,Loyal Customer,40,Business travel,Business,2154,4,4,4,4,2,4,5,4,4,4,4,3,4,3,15,15.0,satisfied +16007,35334,Male,Loyal Customer,28,Business travel,Business,1074,5,5,5,5,5,4,5,5,1,3,3,2,3,5,15,6.0,neutral or dissatisfied +16008,110527,Female,disloyal Customer,28,Business travel,Business,488,1,1,1,4,5,1,5,5,4,5,4,5,5,5,24,21.0,neutral or dissatisfied +16009,86664,Female,Loyal Customer,21,Personal Travel,Eco,746,2,5,1,3,1,1,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +16010,96459,Female,Loyal Customer,41,Business travel,Eco,302,4,5,5,5,3,4,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +16011,110372,Male,Loyal Customer,48,Business travel,Business,2596,2,2,2,2,2,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +16012,12737,Female,Loyal Customer,49,Personal Travel,Eco,689,3,3,2,3,1,3,2,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +16013,47008,Female,Loyal Customer,39,Business travel,Business,771,4,1,1,1,4,4,3,4,4,4,4,3,4,4,8,0.0,neutral or dissatisfied +16014,58384,Male,Loyal Customer,40,Business travel,Business,2870,5,5,3,5,5,4,4,3,3,3,3,5,3,3,1,0.0,satisfied +16015,88792,Female,disloyal Customer,49,Business travel,Business,240,5,5,5,2,3,5,3,3,5,2,4,5,5,3,10,0.0,satisfied +16016,81879,Female,Loyal Customer,31,Personal Travel,Business,680,3,5,3,2,4,3,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +16017,89550,Male,disloyal Customer,26,Business travel,Business,944,1,1,1,5,4,1,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +16018,31942,Female,Loyal Customer,54,Business travel,Business,2301,2,3,3,3,5,4,4,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +16019,44827,Female,Loyal Customer,53,Business travel,Business,462,2,2,2,2,5,1,3,5,5,5,5,2,5,4,17,9.0,satisfied +16020,56457,Female,Loyal Customer,69,Personal Travel,Eco,719,4,4,5,2,3,5,5,3,3,5,3,4,3,5,0,0.0,neutral or dissatisfied +16021,75414,Male,Loyal Customer,46,Business travel,Business,2342,4,4,4,4,2,5,4,4,4,4,4,4,4,5,9,0.0,satisfied +16022,84586,Male,Loyal Customer,42,Business travel,Business,1592,3,1,1,1,5,3,2,3,3,2,3,4,3,1,29,19.0,neutral or dissatisfied +16023,10263,Male,Loyal Customer,10,Personal Travel,Business,201,1,5,1,3,4,1,4,4,2,4,4,4,5,4,0,19.0,neutral or dissatisfied +16024,38753,Male,Loyal Customer,45,Business travel,Business,354,4,4,4,4,4,2,3,5,5,5,5,3,5,2,0,0.0,satisfied +16025,78854,Male,Loyal Customer,47,Business travel,Eco Plus,447,4,3,3,3,4,4,4,4,2,4,3,5,2,4,0,30.0,satisfied +16026,113783,Female,Loyal Customer,27,Business travel,Business,3996,3,3,3,3,4,4,4,4,3,5,4,5,4,4,0,0.0,satisfied +16027,2221,Male,Loyal Customer,57,Business travel,Business,1608,3,3,3,3,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +16028,79550,Female,Loyal Customer,46,Business travel,Business,760,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +16029,30676,Male,Loyal Customer,46,Business travel,Business,1580,1,1,2,1,1,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +16030,33394,Male,Loyal Customer,22,Business travel,Business,2917,3,3,5,3,4,4,4,4,1,4,5,5,4,4,0,0.0,satisfied +16031,15733,Female,Loyal Customer,67,Personal Travel,Eco,479,3,5,3,3,4,5,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +16032,124689,Male,Loyal Customer,55,Business travel,Business,2799,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +16033,47165,Male,Loyal Customer,46,Business travel,Business,620,5,5,5,5,1,4,1,4,4,4,4,2,4,4,30,39.0,satisfied +16034,7040,Female,Loyal Customer,19,Business travel,Eco Plus,196,5,3,4,3,5,5,5,5,3,1,5,1,5,5,0,0.0,satisfied +16035,11661,Male,Loyal Customer,59,Personal Travel,Eco,837,4,5,4,2,5,4,5,5,4,3,1,5,4,5,49,44.0,neutral or dissatisfied +16036,73063,Female,Loyal Customer,57,Personal Travel,Eco Plus,1096,3,5,3,2,2,5,5,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +16037,24762,Male,Loyal Customer,33,Business travel,Eco,447,3,4,1,1,3,3,3,3,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +16038,55821,Female,disloyal Customer,54,Business travel,Business,1416,2,2,2,3,2,2,2,2,3,3,4,4,4,2,0,26.0,neutral or dissatisfied +16039,79955,Female,Loyal Customer,50,Business travel,Eco,550,2,1,1,1,1,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +16040,109682,Male,Loyal Customer,40,Personal Travel,Eco,829,3,5,3,1,5,3,3,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +16041,69648,Female,disloyal Customer,25,Business travel,Business,569,5,4,5,1,1,5,1,1,5,4,5,4,5,1,0,0.0,satisfied +16042,90351,Female,disloyal Customer,39,Business travel,Business,404,1,1,1,3,2,1,4,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +16043,102491,Male,Loyal Customer,41,Personal Travel,Eco,236,3,4,3,1,3,3,1,3,3,2,1,2,2,3,24,24.0,neutral or dissatisfied +16044,40037,Female,Loyal Customer,26,Business travel,Eco Plus,575,3,3,2,3,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +16045,41705,Male,Loyal Customer,41,Business travel,Business,1404,3,3,5,3,3,1,3,4,4,4,4,1,4,2,3,15.0,satisfied +16046,31316,Female,Loyal Customer,59,Personal Travel,Eco,680,3,5,3,1,5,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +16047,56531,Male,Loyal Customer,38,Business travel,Business,3976,1,1,1,1,5,4,4,4,4,4,4,3,4,4,9,0.0,satisfied +16048,93336,Female,Loyal Customer,47,Business travel,Business,3310,5,5,5,5,2,5,5,5,5,5,5,5,5,4,19,0.0,satisfied +16049,31084,Male,Loyal Customer,27,Business travel,Business,2013,2,1,1,1,2,2,2,2,2,1,3,4,3,2,27,22.0,neutral or dissatisfied +16050,73734,Male,Loyal Customer,28,Personal Travel,Eco,192,0,5,0,2,3,0,3,3,4,3,5,4,5,3,0,0.0,satisfied +16051,77690,Female,Loyal Customer,51,Business travel,Business,3506,2,1,1,1,3,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +16052,5312,Female,disloyal Customer,49,Business travel,Business,190,2,2,2,2,5,2,5,5,5,3,4,4,4,5,1,0.0,neutral or dissatisfied +16053,77516,Female,Loyal Customer,47,Business travel,Business,2641,3,3,3,3,3,2,3,4,4,4,4,3,4,4,6,0.0,satisfied +16054,21301,Female,Loyal Customer,35,Personal Travel,Eco,692,3,5,3,4,5,3,5,5,3,3,5,5,4,5,78,65.0,neutral or dissatisfied +16055,125316,Male,Loyal Customer,52,Personal Travel,Eco Plus,678,3,4,3,2,2,3,2,2,3,3,5,3,5,2,55,51.0,neutral or dissatisfied +16056,24369,Female,Loyal Customer,27,Business travel,Business,669,1,1,1,1,4,4,4,4,3,2,2,3,4,4,5,0.0,satisfied +16057,64379,Female,Loyal Customer,13,Personal Travel,Eco,1192,4,4,4,2,4,4,2,4,3,2,4,3,5,4,4,0.0,neutral or dissatisfied +16058,96744,Female,disloyal Customer,49,Business travel,Eco Plus,696,3,3,3,4,2,3,1,2,1,3,3,2,3,2,22,18.0,neutral or dissatisfied +16059,111901,Male,Loyal Customer,23,Personal Travel,Eco,628,2,5,3,3,4,3,4,4,5,5,5,5,5,4,17,12.0,neutral or dissatisfied +16060,105917,Male,Loyal Customer,29,Personal Travel,Eco,283,1,5,1,2,5,1,1,5,3,3,4,4,4,5,2,0.0,neutral or dissatisfied +16061,82895,Female,Loyal Customer,69,Personal Travel,Eco,594,2,1,2,4,3,3,3,2,2,2,5,2,2,3,110,118.0,neutral or dissatisfied +16062,81006,Female,Loyal Customer,39,Personal Travel,Eco,297,3,2,3,3,1,3,1,1,1,2,4,3,3,1,0,0.0,neutral or dissatisfied +16063,92535,Female,Loyal Customer,57,Personal Travel,Eco,2116,2,2,2,4,5,3,3,4,4,2,4,2,4,4,6,0.0,neutral or dissatisfied +16064,21418,Male,Loyal Customer,47,Business travel,Business,3368,1,1,1,1,3,5,3,4,4,4,4,2,4,5,0,0.0,satisfied +16065,33717,Female,Loyal Customer,65,Personal Travel,Eco,759,4,4,4,2,3,4,4,5,5,4,5,5,5,3,72,91.0,neutral or dissatisfied +16066,48698,Male,Loyal Customer,54,Business travel,Business,199,5,5,5,5,4,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +16067,13821,Female,Loyal Customer,56,Business travel,Eco,628,4,4,4,4,1,2,3,4,4,4,4,5,4,3,0,0.0,satisfied +16068,120443,Male,disloyal Customer,36,Business travel,Eco,337,4,2,4,4,1,4,1,1,2,5,4,4,4,1,0,14.0,neutral or dissatisfied +16069,47642,Female,Loyal Customer,23,Business travel,Business,3642,1,5,5,5,1,1,1,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +16070,45326,Male,Loyal Customer,43,Business travel,Eco,175,4,1,1,1,4,4,4,4,4,5,4,1,1,4,0,0.0,satisfied +16071,14132,Female,Loyal Customer,28,Business travel,Business,632,1,1,1,1,1,1,1,1,3,3,3,1,3,1,42,41.0,neutral or dissatisfied +16072,126510,Male,Loyal Customer,34,Business travel,Eco Plus,1849,5,1,1,1,5,5,5,5,5,2,3,5,2,5,0,12.0,satisfied +16073,2423,Male,Loyal Customer,13,Personal Travel,Eco,604,3,4,3,3,3,3,3,3,5,3,5,4,5,3,63,66.0,neutral or dissatisfied +16074,85412,Male,Loyal Customer,44,Business travel,Business,227,0,0,0,3,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +16075,75735,Male,Loyal Customer,49,Business travel,Eco,813,2,4,4,4,2,2,2,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +16076,7290,Female,Loyal Customer,27,Personal Travel,Eco,130,1,5,0,3,4,0,4,4,4,5,5,3,4,4,0,1.0,neutral or dissatisfied +16077,121581,Male,disloyal Customer,25,Business travel,Eco,936,4,4,4,3,5,4,5,5,4,4,4,2,3,5,6,8.0,neutral or dissatisfied +16078,114012,Female,Loyal Customer,56,Personal Travel,Eco,1706,3,2,3,3,5,2,3,5,5,3,5,4,5,3,14,0.0,neutral or dissatisfied +16079,1867,Male,Loyal Customer,47,Business travel,Business,931,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16080,1143,Male,Loyal Customer,28,Personal Travel,Eco,229,4,5,4,2,2,4,2,2,3,3,5,5,5,2,0,2.0,neutral or dissatisfied +16081,38752,Female,Loyal Customer,65,Business travel,Business,3429,1,1,1,1,3,3,3,1,5,3,1,3,4,3,187,224.0,satisfied +16082,84960,Male,Loyal Customer,23,Personal Travel,Eco Plus,547,3,3,2,2,5,2,5,5,1,5,5,2,1,5,0,0.0,neutral or dissatisfied +16083,32216,Male,Loyal Customer,37,Business travel,Business,3431,0,5,1,4,4,3,3,4,4,3,3,3,4,2,0,0.0,satisfied +16084,30193,Male,Loyal Customer,49,Business travel,Eco Plus,261,4,3,3,3,4,4,4,4,2,1,3,2,3,4,0,0.0,satisfied +16085,101153,Female,disloyal Customer,38,Business travel,Eco,1069,1,1,1,2,5,1,5,5,1,1,1,2,2,5,8,0.0,neutral or dissatisfied +16086,105869,Male,Loyal Customer,38,Personal Travel,Eco Plus,787,2,3,2,1,2,2,5,2,1,1,4,1,1,2,0,0.0,neutral or dissatisfied +16087,25081,Male,Loyal Customer,43,Personal Travel,Eco,957,3,5,3,3,5,3,5,5,4,2,4,5,5,5,39,29.0,neutral or dissatisfied +16088,15483,Female,Loyal Customer,57,Personal Travel,Eco,164,2,4,2,1,2,5,5,4,4,2,4,3,4,3,0,11.0,neutral or dissatisfied +16089,74220,Female,disloyal Customer,22,Business travel,Eco,1746,2,2,2,3,5,2,3,5,2,5,4,2,3,5,4,0.0,neutral or dissatisfied +16090,95574,Female,disloyal Customer,25,Business travel,Business,677,3,0,3,4,4,3,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +16091,74480,Female,Loyal Customer,46,Business travel,Business,2887,4,4,4,4,2,4,4,4,4,4,4,4,4,5,9,0.0,satisfied +16092,71349,Female,Loyal Customer,39,Business travel,Business,1514,4,2,4,4,4,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +16093,105562,Female,Loyal Customer,60,Business travel,Business,3370,4,5,4,4,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +16094,71196,Female,Loyal Customer,55,Business travel,Business,733,3,3,3,3,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +16095,39047,Female,Loyal Customer,49,Business travel,Eco Plus,391,2,1,1,1,4,3,5,2,2,2,2,4,2,1,0,0.0,satisfied +16096,76899,Female,disloyal Customer,37,Business travel,Eco,230,4,5,4,2,2,4,2,2,3,4,2,5,1,2,0,0.0,neutral or dissatisfied +16097,27378,Female,Loyal Customer,50,Business travel,Business,1833,3,3,3,3,4,2,3,5,5,4,5,3,5,2,0,0.0,satisfied +16098,74038,Female,Loyal Customer,60,Business travel,Business,1194,3,3,3,3,3,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +16099,25204,Female,Loyal Customer,43,Business travel,Eco,919,5,3,3,3,4,4,3,5,5,5,5,2,5,2,24,0.0,satisfied +16100,11140,Male,Loyal Customer,55,Personal Travel,Eco,166,1,5,1,1,5,1,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +16101,69738,Male,Loyal Customer,57,Business travel,Business,1372,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16102,59216,Female,Loyal Customer,33,Personal Travel,Eco,1440,2,5,2,3,2,2,2,2,5,2,4,3,5,2,10,1.0,neutral or dissatisfied +16103,51012,Female,Loyal Customer,13,Personal Travel,Eco,89,2,4,2,3,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +16104,20580,Male,Loyal Customer,68,Personal Travel,Eco,565,2,5,2,4,4,2,4,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +16105,50961,Male,Loyal Customer,15,Personal Travel,Eco,109,3,4,3,4,3,3,3,3,5,1,4,2,3,3,65,72.0,neutral or dissatisfied +16106,111602,Female,Loyal Customer,15,Personal Travel,Eco Plus,883,1,0,1,4,5,1,4,5,3,4,5,4,4,5,0,3.0,neutral or dissatisfied +16107,113544,Male,disloyal Customer,30,Business travel,Eco,258,2,0,2,4,4,2,4,4,2,5,3,3,4,4,5,0.0,neutral or dissatisfied +16108,88114,Female,Loyal Customer,30,Business travel,Business,3359,3,3,3,3,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +16109,107330,Male,Loyal Customer,48,Business travel,Business,2825,2,2,2,2,5,5,5,5,5,5,5,3,5,5,7,0.0,satisfied +16110,16713,Female,Loyal Customer,27,Personal Travel,Eco,284,2,4,2,1,5,2,5,5,5,4,5,3,4,5,67,72.0,neutral or dissatisfied +16111,75403,Female,Loyal Customer,34,Business travel,Business,2342,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +16112,41543,Male,disloyal Customer,24,Business travel,Eco,1428,1,1,1,3,1,1,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +16113,122723,Male,Loyal Customer,49,Business travel,Business,3825,2,2,2,2,3,4,4,5,5,5,5,4,5,3,27,6.0,satisfied +16114,70365,Female,Loyal Customer,42,Business travel,Business,2955,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +16115,68376,Female,Loyal Customer,44,Business travel,Business,1045,1,1,1,1,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +16116,12111,Male,Loyal Customer,22,Business travel,Business,2107,1,1,1,1,5,5,5,5,4,2,3,4,1,5,2,26.0,satisfied +16117,46086,Female,disloyal Customer,22,Business travel,Eco,541,2,3,2,3,5,2,5,5,3,4,4,4,3,5,21,8.0,neutral or dissatisfied +16118,109800,Male,Loyal Customer,54,Business travel,Business,3968,2,2,2,2,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +16119,127926,Male,disloyal Customer,29,Business travel,Business,916,0,1,1,1,4,1,4,4,4,2,5,5,4,4,0,0.0,satisfied +16120,86081,Male,disloyal Customer,21,Business travel,Eco,306,4,0,4,5,4,4,4,4,3,4,4,5,5,4,1,0.0,satisfied +16121,69815,Male,Loyal Customer,47,Business travel,Business,1345,2,3,3,3,3,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +16122,120525,Female,disloyal Customer,59,Business travel,Eco,96,3,1,3,3,4,3,4,4,2,4,4,1,4,4,0,8.0,neutral or dissatisfied +16123,88901,Male,disloyal Customer,27,Business travel,Eco,459,1,2,1,4,4,1,4,4,2,2,3,3,4,4,3,5.0,neutral or dissatisfied +16124,81707,Female,Loyal Customer,58,Personal Travel,Eco,907,2,2,1,3,1,4,4,2,2,1,3,4,2,3,0,0.0,neutral or dissatisfied +16125,60363,Female,Loyal Customer,54,Business travel,Business,1452,5,5,5,5,2,4,5,4,4,4,4,4,4,4,14,8.0,satisfied +16126,25097,Female,Loyal Customer,48,Business travel,Eco,369,2,5,5,5,2,2,2,2,2,4,4,2,4,2,276,283.0,neutral or dissatisfied +16127,86966,Female,Loyal Customer,49,Business travel,Eco,907,2,2,2,2,5,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +16128,48292,Male,Loyal Customer,46,Business travel,Business,1499,1,5,5,5,3,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +16129,117301,Male,Loyal Customer,27,Business travel,Eco Plus,325,3,2,2,2,3,3,3,3,1,2,3,3,4,3,4,0.0,neutral or dissatisfied +16130,108853,Male,disloyal Customer,44,Business travel,Eco,1281,1,1,1,4,4,1,4,4,1,5,2,2,4,4,12,10.0,neutral or dissatisfied +16131,12576,Female,Loyal Customer,40,Personal Travel,Business,542,3,5,3,1,2,5,4,3,3,3,3,4,3,5,0,1.0,neutral or dissatisfied +16132,71867,Female,Loyal Customer,62,Personal Travel,Eco,1726,5,2,5,3,5,2,4,1,3,3,3,4,1,4,153,,satisfied +16133,101866,Female,Loyal Customer,55,Business travel,Business,1747,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +16134,23656,Female,disloyal Customer,50,Business travel,Eco,73,3,0,3,3,3,4,4,3,1,3,2,4,4,4,195,205.0,neutral or dissatisfied +16135,41880,Female,Loyal Customer,26,Business travel,Business,2941,3,3,3,3,3,3,3,3,1,4,3,3,4,3,7,16.0,neutral or dissatisfied +16136,120756,Male,disloyal Customer,25,Business travel,Business,678,1,4,1,2,2,1,2,2,4,2,4,5,4,2,5,1.0,neutral or dissatisfied +16137,112594,Female,Loyal Customer,29,Business travel,Business,2898,2,3,3,3,2,2,2,2,2,5,4,3,4,2,6,0.0,neutral or dissatisfied +16138,3792,Female,Loyal Customer,58,Personal Travel,Eco,599,2,5,2,2,5,1,2,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +16139,29384,Male,Loyal Customer,29,Business travel,Eco,2404,3,2,2,2,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +16140,70064,Male,Loyal Customer,44,Business travel,Business,550,1,1,1,1,5,4,5,4,4,4,4,3,4,4,3,3.0,satisfied +16141,116535,Male,Loyal Customer,19,Personal Travel,Eco,337,1,5,1,1,1,1,1,1,2,3,1,4,2,1,0,0.0,neutral or dissatisfied +16142,16743,Female,Loyal Customer,49,Personal Travel,Eco Plus,1167,4,3,4,4,2,3,3,1,1,4,1,2,1,2,49,38.0,neutral or dissatisfied +16143,52538,Male,Loyal Customer,53,Business travel,Eco,119,4,4,5,5,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +16144,59786,Male,Loyal Customer,7,Personal Travel,Eco,1062,4,4,4,2,1,4,1,1,4,4,4,3,4,1,5,0.0,neutral or dissatisfied +16145,106948,Female,Loyal Customer,32,Business travel,Business,3505,5,5,5,5,5,5,5,5,5,4,5,3,5,5,17,9.0,satisfied +16146,74833,Female,Loyal Customer,49,Business travel,Business,1797,2,2,2,2,4,5,4,5,5,5,5,4,5,5,11,0.0,satisfied +16147,100452,Female,Loyal Customer,45,Business travel,Business,2127,4,4,4,4,4,5,5,5,5,5,5,3,5,5,44,41.0,satisfied +16148,26986,Female,disloyal Customer,48,Business travel,Eco,867,2,2,2,3,5,2,4,5,4,5,2,4,5,5,0,0.0,neutral or dissatisfied +16149,79736,Male,Loyal Customer,63,Business travel,Eco Plus,762,4,3,3,3,4,4,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +16150,102048,Male,disloyal Customer,23,Business travel,Eco,236,2,0,2,4,4,2,4,4,3,3,4,2,3,4,0,0.0,neutral or dissatisfied +16151,92844,Female,Loyal Customer,40,Personal Travel,Eco,1587,3,4,3,5,1,3,1,1,5,2,5,3,5,1,0,6.0,neutral or dissatisfied +16152,82090,Male,disloyal Customer,7,Business travel,Eco,1276,2,2,2,3,3,2,3,3,2,4,4,1,4,3,0,0.0,neutral or dissatisfied +16153,8214,Female,Loyal Customer,40,Business travel,Eco,130,2,3,3,3,2,2,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +16154,75075,Female,Loyal Customer,61,Personal Travel,Eco,2611,1,2,1,4,3,3,3,1,1,1,4,2,1,2,0,9.0,neutral or dissatisfied +16155,99667,Male,Loyal Customer,67,Personal Travel,Eco,1050,2,4,2,4,4,2,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +16156,41919,Male,Loyal Customer,26,Business travel,Business,3137,1,3,4,4,4,4,1,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +16157,118677,Male,Loyal Customer,18,Business travel,Business,325,1,1,1,1,5,5,5,5,3,1,4,5,5,5,0,1.0,satisfied +16158,98740,Male,Loyal Customer,43,Business travel,Business,3493,2,3,4,3,3,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +16159,22050,Male,Loyal Customer,51,Business travel,Business,2740,5,5,5,5,4,4,4,5,3,3,1,4,3,4,179,166.0,satisfied +16160,28509,Female,Loyal Customer,17,Business travel,Business,2681,5,5,5,5,5,5,5,3,4,3,5,5,5,5,0,0.0,satisfied +16161,141,Female,Loyal Customer,55,Business travel,Business,227,4,4,4,4,3,4,4,4,4,4,4,3,4,4,7,1.0,satisfied +16162,64529,Male,disloyal Customer,22,Business travel,Eco,282,5,0,5,5,2,5,2,2,5,2,5,4,5,2,3,11.0,satisfied +16163,2712,Male,Loyal Customer,19,Personal Travel,Eco,562,1,5,1,1,1,1,1,1,3,2,4,3,4,1,50,44.0,neutral or dissatisfied +16164,5579,Male,Loyal Customer,38,Personal Travel,Eco,501,2,5,2,1,3,2,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +16165,25227,Female,Loyal Customer,23,Business travel,Business,925,4,4,5,4,4,4,4,4,3,4,3,3,3,4,10,18.0,neutral or dissatisfied +16166,26570,Female,Loyal Customer,58,Personal Travel,Business,515,1,2,1,3,1,4,3,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +16167,56583,Male,Loyal Customer,51,Business travel,Eco,1068,3,5,5,5,3,3,3,3,2,1,4,4,4,3,0,0.0,neutral or dissatisfied +16168,18794,Male,Loyal Customer,34,Business travel,Business,1911,5,5,4,5,4,5,5,4,4,4,4,2,4,3,6,0.0,satisfied +16169,90785,Female,Loyal Customer,46,Business travel,Business,444,3,1,1,1,4,2,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +16170,40053,Female,Loyal Customer,55,Personal Travel,Eco,866,2,4,2,4,5,4,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +16171,111799,Female,Loyal Customer,18,Business travel,Business,349,3,3,3,3,3,3,3,3,1,1,4,2,3,3,4,0.0,neutral or dissatisfied +16172,85939,Male,Loyal Customer,46,Business travel,Business,2984,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +16173,87739,Female,Loyal Customer,55,Business travel,Business,3055,0,5,0,2,2,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +16174,49110,Female,disloyal Customer,27,Business travel,Eco,109,3,0,3,2,5,3,5,5,2,3,5,5,1,5,0,0.0,neutral or dissatisfied +16175,86526,Female,Loyal Customer,42,Personal Travel,Eco,762,2,3,1,3,5,3,4,5,5,1,1,1,5,4,2,0.0,neutral or dissatisfied +16176,26128,Male,Loyal Customer,53,Business travel,Eco,270,5,1,4,1,4,5,4,4,5,4,5,5,1,4,22,0.0,satisfied +16177,73156,Male,Loyal Customer,60,Business travel,Business,2186,4,4,4,4,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +16178,104268,Female,Loyal Customer,60,Personal Travel,Eco,456,3,4,3,3,5,4,3,2,2,3,2,5,2,4,0,8.0,neutral or dissatisfied +16179,105804,Male,Loyal Customer,56,Personal Travel,Eco,925,3,4,3,1,5,3,5,5,2,2,4,1,4,5,3,0.0,neutral or dissatisfied +16180,14856,Male,Loyal Customer,42,Business travel,Business,343,3,5,3,3,4,2,5,5,5,5,5,5,5,5,0,0.0,satisfied +16181,111783,Female,disloyal Customer,43,Business travel,Eco,1620,1,1,1,4,2,1,2,2,1,2,3,2,4,2,1,0.0,neutral or dissatisfied +16182,123658,Male,disloyal Customer,50,Business travel,Business,214,1,1,1,1,5,1,5,5,3,2,4,5,4,5,0,13.0,neutral or dissatisfied +16183,1954,Female,Loyal Customer,49,Business travel,Business,295,3,3,3,3,4,2,2,3,3,3,3,4,3,1,35,34.0,neutral or dissatisfied +16184,74843,Female,Loyal Customer,47,Personal Travel,Eco,1797,4,4,4,3,4,3,4,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +16185,79043,Female,Loyal Customer,48,Business travel,Business,356,2,5,5,5,1,2,3,2,2,2,2,1,2,2,5,17.0,neutral or dissatisfied +16186,92507,Male,Loyal Customer,25,Personal Travel,Eco,1947,4,4,4,4,1,4,1,1,4,4,4,5,5,1,0,0.0,satisfied +16187,86214,Female,disloyal Customer,21,Business travel,Eco,306,1,4,1,3,5,1,5,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +16188,31722,Female,Loyal Customer,69,Personal Travel,Eco,853,2,1,2,3,1,3,4,3,3,2,5,3,3,4,0,0.0,neutral or dissatisfied +16189,116602,Male,Loyal Customer,43,Business travel,Business,2432,3,3,2,3,3,5,4,4,4,4,4,5,4,5,84,84.0,satisfied +16190,25243,Female,Loyal Customer,19,Personal Travel,Eco,842,4,4,4,3,2,4,2,2,4,2,4,3,5,2,5,0.0,neutral or dissatisfied +16191,119715,Male,Loyal Customer,43,Business travel,Business,1325,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +16192,19027,Male,Loyal Customer,34,Personal Travel,Eco,871,4,1,5,2,5,5,5,5,3,3,2,2,2,5,0,0.0,neutral or dissatisfied +16193,32594,Female,Loyal Customer,52,Business travel,Eco,101,3,3,3,3,1,2,4,3,3,3,3,4,3,3,6,10.0,satisfied +16194,50754,Female,Loyal Customer,7,Personal Travel,Eco,209,5,3,5,4,4,5,4,4,4,1,3,4,3,4,0,4.0,satisfied +16195,84351,Female,Loyal Customer,40,Business travel,Business,2919,3,3,3,3,3,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +16196,113785,Male,disloyal Customer,27,Business travel,Business,258,0,0,0,3,5,0,5,5,5,3,4,4,4,5,4,6.0,satisfied +16197,81270,Male,Loyal Customer,40,Business travel,Business,1020,3,3,3,3,5,4,4,4,4,5,4,3,4,4,0,1.0,satisfied +16198,47639,Female,Loyal Customer,53,Business travel,Business,1629,5,5,5,5,5,1,1,5,5,5,5,3,5,2,31,22.0,satisfied +16199,23405,Female,Loyal Customer,47,Business travel,Eco Plus,483,5,2,2,2,4,1,2,5,5,5,5,1,5,4,34,27.0,satisfied +16200,71217,Male,Loyal Customer,46,Business travel,Business,2934,4,4,4,4,2,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +16201,88199,Female,Loyal Customer,27,Business travel,Business,2132,2,4,4,4,2,2,2,2,3,4,3,3,4,2,28,33.0,neutral or dissatisfied +16202,71678,Female,Loyal Customer,50,Personal Travel,Eco,1197,2,4,2,1,2,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +16203,8748,Male,Loyal Customer,44,Business travel,Eco Plus,280,2,3,3,3,2,2,2,2,1,2,4,4,4,2,12,11.0,neutral or dissatisfied +16204,66921,Male,Loyal Customer,41,Business travel,Business,1102,4,4,2,4,3,4,5,4,4,4,4,4,4,5,0,1.0,satisfied +16205,50439,Male,Loyal Customer,51,Business travel,Eco,373,4,1,1,1,4,4,4,4,4,3,4,3,1,4,0,18.0,satisfied +16206,9733,Female,Loyal Customer,16,Personal Travel,Eco,926,1,4,1,2,1,1,4,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +16207,96903,Male,Loyal Customer,61,Personal Travel,Eco,972,3,4,3,4,1,3,1,1,5,4,4,4,4,1,39,23.0,neutral or dissatisfied +16208,61981,Male,Loyal Customer,15,Personal Travel,Business,2586,2,1,2,2,4,2,4,4,1,3,3,2,2,4,0,0.0,neutral or dissatisfied +16209,86933,Female,Loyal Customer,61,Business travel,Eco Plus,352,4,1,1,1,1,3,5,4,4,4,4,1,4,1,0,0.0,satisfied +16210,31016,Male,Loyal Customer,69,Personal Travel,Eco,391,4,5,4,1,2,4,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +16211,94445,Male,Loyal Customer,31,Business travel,Business,1879,1,1,1,1,5,5,5,5,3,4,4,3,4,5,37,33.0,satisfied +16212,58752,Male,disloyal Customer,48,Business travel,Business,1005,4,4,4,1,3,4,3,3,4,5,5,5,4,3,78,68.0,satisfied +16213,104354,Female,disloyal Customer,28,Business travel,Business,409,3,3,3,4,2,3,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +16214,102966,Female,disloyal Customer,38,Business travel,Business,546,1,1,1,3,4,1,4,4,3,2,3,1,2,4,4,3.0,neutral or dissatisfied +16215,94598,Female,Loyal Customer,57,Business travel,Business,562,1,1,4,1,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +16216,124105,Male,disloyal Customer,23,Business travel,Eco,529,1,5,1,4,3,1,3,3,3,5,4,4,5,3,0,1.0,neutral or dissatisfied +16217,4018,Female,Loyal Customer,60,Business travel,Eco,479,2,2,2,2,5,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +16218,20889,Male,Loyal Customer,25,Personal Travel,Eco Plus,508,3,5,3,2,2,3,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +16219,91067,Male,Loyal Customer,35,Personal Travel,Eco,404,4,2,4,4,5,4,5,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +16220,35829,Female,Loyal Customer,59,Business travel,Eco,937,3,1,1,1,1,3,4,3,3,3,3,4,3,3,17,30.0,neutral or dissatisfied +16221,115248,Male,disloyal Customer,44,Business travel,Business,417,5,5,5,2,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +16222,82164,Male,Loyal Customer,41,Business travel,Business,2572,3,3,3,3,3,1,5,5,5,5,5,2,5,5,0,0.0,satisfied +16223,62205,Male,Loyal Customer,24,Personal Travel,Eco,2454,3,5,3,1,5,3,1,5,4,5,4,3,5,5,1,0.0,neutral or dissatisfied +16224,51020,Female,Loyal Customer,14,Personal Travel,Eco,421,1,4,1,1,1,1,1,1,1,4,3,3,1,1,49,50.0,neutral or dissatisfied +16225,79019,Female,disloyal Customer,25,Business travel,Business,226,2,4,2,3,4,2,4,4,5,3,5,3,5,4,5,18.0,neutral or dissatisfied +16226,126847,Male,disloyal Customer,35,Business travel,Eco,788,3,3,3,3,2,3,2,2,5,4,3,1,3,2,0,0.0,neutral or dissatisfied +16227,27830,Female,Loyal Customer,57,Personal Travel,Eco,1533,4,5,4,2,4,5,5,1,1,4,1,4,1,5,51,44.0,satisfied +16228,77837,Male,Loyal Customer,42,Business travel,Business,3906,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16229,56688,Male,Loyal Customer,41,Personal Travel,Eco,1023,3,5,3,5,5,3,5,5,5,3,5,5,3,5,7,24.0,neutral or dissatisfied +16230,44091,Female,Loyal Customer,52,Personal Travel,Business,257,3,3,3,3,4,5,1,1,1,3,3,5,1,3,0,0.0,neutral or dissatisfied +16231,17267,Female,Loyal Customer,42,Personal Travel,Eco,872,3,5,3,3,3,1,3,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +16232,12476,Female,Loyal Customer,34,Personal Travel,Eco,305,1,5,1,2,5,1,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +16233,114927,Female,Loyal Customer,68,Business travel,Business,3379,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +16234,66212,Female,Loyal Customer,25,Business travel,Business,3604,2,2,2,2,4,4,4,4,3,3,5,3,4,4,0,0.0,satisfied +16235,108140,Male,Loyal Customer,49,Business travel,Eco,728,3,1,2,1,3,3,3,3,3,4,1,2,1,3,5,16.0,neutral or dissatisfied +16236,126581,Female,disloyal Customer,20,Business travel,Eco,1158,2,2,2,4,3,2,3,3,1,1,4,3,3,3,0,0.0,neutral or dissatisfied +16237,23326,Male,disloyal Customer,39,Business travel,Eco,579,3,0,3,3,1,3,1,1,2,3,3,2,5,1,7,1.0,neutral or dissatisfied +16238,79279,Female,disloyal Customer,24,Business travel,Eco,1428,3,3,3,4,1,3,1,1,4,3,5,3,4,1,19,0.0,neutral or dissatisfied +16239,90820,Male,Loyal Customer,56,Business travel,Business,2506,2,2,2,2,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +16240,49816,Female,Loyal Customer,30,Business travel,Business,89,4,5,4,4,4,4,3,4,3,2,5,3,3,4,0,0.0,satisfied +16241,114698,Male,Loyal Customer,46,Business travel,Business,308,2,2,2,2,4,4,4,5,5,5,5,5,5,4,8,5.0,satisfied +16242,1419,Female,Loyal Customer,66,Personal Travel,Eco Plus,113,2,5,2,4,4,5,4,3,3,2,3,3,3,5,25,24.0,neutral or dissatisfied +16243,95800,Male,Loyal Customer,31,Business travel,Business,2472,4,4,4,4,4,4,4,4,4,4,5,3,5,4,11,4.0,satisfied +16244,94923,Male,Loyal Customer,67,Business travel,Eco,187,3,1,1,1,3,3,3,3,1,5,4,3,3,3,21,21.0,neutral or dissatisfied +16245,78452,Male,Loyal Customer,50,Business travel,Business,1579,3,3,3,3,2,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +16246,65619,Male,Loyal Customer,65,Personal Travel,Eco,237,4,4,4,3,5,4,5,5,3,4,4,5,4,5,40,34.0,neutral or dissatisfied +16247,15441,Female,Loyal Customer,21,Business travel,Business,2574,3,5,5,5,3,3,3,3,4,5,3,3,3,3,13,0.0,neutral or dissatisfied +16248,102600,Male,Loyal Customer,41,Personal Travel,Eco Plus,197,3,4,0,3,5,0,5,5,4,3,4,3,4,5,64,65.0,neutral or dissatisfied +16249,72283,Male,Loyal Customer,56,Personal Travel,Eco,919,4,3,4,2,4,4,4,4,3,4,2,1,1,4,17,11.0,satisfied +16250,71002,Male,Loyal Customer,40,Business travel,Business,802,3,3,3,3,2,5,5,5,5,5,5,4,5,5,1,21.0,satisfied +16251,2195,Male,Loyal Customer,37,Personal Travel,Eco,685,1,4,1,3,1,1,1,3,3,5,4,1,5,1,124,175.0,neutral or dissatisfied +16252,55768,Male,Loyal Customer,28,Personal Travel,Business,599,2,3,3,5,4,3,4,4,4,2,2,3,3,4,35,26.0,neutral or dissatisfied +16253,86953,Female,Loyal Customer,52,Business travel,Business,2454,1,1,1,1,5,5,5,4,4,4,4,4,4,4,9,4.0,satisfied +16254,53550,Female,disloyal Customer,31,Business travel,Eco,1956,2,2,2,4,3,2,3,3,1,2,2,3,3,3,30,29.0,neutral or dissatisfied +16255,75532,Male,Loyal Customer,50,Business travel,Business,3613,4,3,3,3,1,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +16256,74569,Male,Loyal Customer,26,Business travel,Eco,1431,4,4,4,4,4,4,4,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +16257,76619,Female,Loyal Customer,44,Business travel,Eco,547,5,4,4,4,3,1,1,5,5,5,5,2,5,4,0,2.0,satisfied +16258,20866,Female,Loyal Customer,63,Personal Travel,Eco,357,5,2,5,3,3,3,4,4,4,5,1,4,4,3,5,0.0,satisfied +16259,43212,Male,disloyal Customer,36,Business travel,Business,472,3,2,2,2,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +16260,15517,Male,Loyal Customer,59,Business travel,Eco Plus,306,4,5,5,5,4,4,4,4,1,5,3,5,5,4,0,8.0,satisfied +16261,27987,Female,disloyal Customer,22,Business travel,Business,1105,5,0,5,3,5,5,5,5,5,5,3,3,2,5,0,0.0,satisfied +16262,16833,Female,Loyal Customer,36,Personal Travel,Eco,645,2,1,2,4,3,2,3,3,2,1,3,4,3,3,91,90.0,neutral or dissatisfied +16263,4183,Male,Loyal Customer,57,Personal Travel,Eco,427,1,0,2,4,4,2,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +16264,93600,Female,Loyal Customer,39,Personal Travel,Business,577,1,4,1,3,5,4,5,3,3,1,3,3,3,4,9,29.0,neutral or dissatisfied +16265,73136,Female,Loyal Customer,12,Personal Travel,Eco,1068,2,5,2,2,4,2,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +16266,129493,Female,Loyal Customer,14,Personal Travel,Eco Plus,2704,1,5,1,3,5,1,5,5,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +16267,108618,Female,Loyal Customer,13,Personal Travel,Eco,813,2,2,2,4,4,2,5,4,2,5,4,3,3,4,1,21.0,neutral or dissatisfied +16268,36910,Female,Loyal Customer,29,Business travel,Eco Plus,2072,0,0,0,1,2,0,2,2,1,3,3,5,3,2,0,0.0,satisfied +16269,122987,Male,disloyal Customer,25,Business travel,Business,631,4,0,3,5,2,3,2,2,4,3,4,5,4,2,0,0.0,satisfied +16270,2338,Male,Loyal Customer,10,Personal Travel,Eco,691,3,5,2,1,3,2,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +16271,115460,Male,Loyal Customer,54,Business travel,Business,325,2,4,2,2,3,2,2,2,2,2,2,1,2,1,11,7.0,neutral or dissatisfied +16272,110366,Male,Loyal Customer,58,Business travel,Business,2033,4,2,2,2,3,1,1,4,4,4,4,2,4,1,1,0.0,neutral or dissatisfied +16273,87765,Female,disloyal Customer,38,Business travel,Business,214,5,5,5,4,4,5,2,4,5,5,4,4,4,4,58,43.0,satisfied +16274,127310,Male,disloyal Customer,17,Business travel,Eco,1078,2,2,2,1,1,2,1,1,1,1,5,4,5,1,0,0.0,neutral or dissatisfied +16275,20358,Male,Loyal Customer,31,Business travel,Business,287,5,5,5,5,5,5,5,5,4,1,2,3,2,5,72,60.0,satisfied +16276,129694,Male,Loyal Customer,38,Business travel,Business,2785,2,5,5,5,5,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +16277,84605,Male,Loyal Customer,44,Business travel,Business,3024,4,4,4,4,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +16278,107987,Female,Loyal Customer,41,Business travel,Business,3442,4,4,4,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +16279,97976,Female,Loyal Customer,36,Personal Travel,Eco,684,3,3,3,1,1,3,1,1,1,1,2,1,2,1,8,19.0,neutral or dissatisfied +16280,15708,Female,Loyal Customer,61,Business travel,Business,1598,2,3,3,3,4,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +16281,109370,Male,Loyal Customer,10,Business travel,Business,1826,2,2,2,2,2,2,2,2,1,3,3,4,3,2,20,0.0,neutral or dissatisfied +16282,96851,Female,Loyal Customer,72,Business travel,Business,2322,2,1,1,1,2,4,4,2,2,2,2,4,2,3,0,5.0,neutral or dissatisfied +16283,100566,Female,Loyal Customer,39,Business travel,Business,486,4,4,3,4,3,4,4,2,2,2,2,3,2,3,37,42.0,satisfied +16284,87866,Female,Loyal Customer,39,Personal Travel,Eco,214,3,1,3,2,4,3,4,4,4,4,2,4,2,4,0,0.0,neutral or dissatisfied +16285,70602,Male,Loyal Customer,68,Personal Travel,Eco,2611,1,2,1,2,1,2,2,1,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +16286,15144,Male,Loyal Customer,32,Business travel,Business,1042,2,3,3,3,2,2,2,2,3,3,3,3,3,2,15,22.0,neutral or dissatisfied +16287,40123,Male,Loyal Customer,20,Personal Travel,Eco,422,3,0,3,4,3,3,3,3,1,4,3,1,3,3,0,0.0,neutral or dissatisfied +16288,107082,Male,Loyal Customer,31,Business travel,Business,1507,1,1,1,1,4,4,4,4,3,4,5,3,4,4,23,8.0,satisfied +16289,115094,Male,Loyal Customer,48,Business travel,Business,2666,4,4,4,4,3,5,5,4,4,4,4,5,4,4,4,0.0,satisfied +16290,44058,Female,Loyal Customer,35,Personal Travel,Eco Plus,67,2,4,2,4,4,2,4,4,4,4,2,4,5,4,0,0.0,neutral or dissatisfied +16291,38639,Female,disloyal Customer,25,Business travel,Eco,1020,1,1,1,3,3,1,3,3,5,4,4,4,4,3,2,0.0,neutral or dissatisfied +16292,83794,Male,disloyal Customer,20,Business travel,Eco,425,4,0,4,3,4,4,4,4,4,5,4,4,4,4,25,17.0,satisfied +16293,60746,Male,Loyal Customer,54,Business travel,Business,804,4,4,4,4,4,4,4,5,5,5,5,5,5,5,9,11.0,satisfied +16294,62501,Male,disloyal Customer,27,Business travel,Business,832,5,5,5,3,4,5,4,4,4,4,3,5,4,4,6,2.0,satisfied +16295,22688,Female,disloyal Customer,26,Business travel,Eco,579,4,2,3,3,1,3,1,1,4,3,4,3,3,1,0,0.0,neutral or dissatisfied +16296,127956,Male,Loyal Customer,56,Business travel,Business,1999,1,1,1,1,2,3,4,4,4,4,4,3,4,4,0,11.0,satisfied +16297,54796,Female,Loyal Customer,22,Business travel,Business,3677,1,1,3,1,4,5,4,4,5,3,3,5,3,4,7,0.0,satisfied +16298,118691,Female,Loyal Customer,67,Personal Travel,Eco,304,3,5,3,4,3,1,5,2,2,3,2,4,2,1,9,0.0,neutral or dissatisfied +16299,110856,Male,Loyal Customer,42,Business travel,Business,2065,3,4,3,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +16300,77274,Female,Loyal Customer,45,Business travel,Business,1931,4,4,4,4,4,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +16301,46567,Male,Loyal Customer,36,Business travel,Eco,125,3,4,4,4,3,3,3,3,3,5,3,3,3,3,38,47.0,neutral or dissatisfied +16302,70915,Female,Loyal Customer,51,Business travel,Business,2039,2,2,3,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +16303,81088,Female,Loyal Customer,29,Personal Travel,Eco,931,3,4,3,2,5,3,2,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +16304,15229,Female,Loyal Customer,43,Business travel,Business,1844,5,5,3,5,5,5,1,2,2,2,2,3,2,1,2,3.0,satisfied +16305,97803,Male,disloyal Customer,25,Business travel,Business,480,4,0,4,4,1,4,1,1,3,3,4,5,4,1,4,0.0,satisfied +16306,48111,Female,disloyal Customer,21,Business travel,Eco,236,0,3,0,4,4,0,4,4,2,3,1,1,2,4,0,0.0,satisfied +16307,113554,Male,disloyal Customer,21,Business travel,Eco,236,4,2,3,3,1,3,1,1,1,5,4,2,3,1,14,21.0,neutral or dissatisfied +16308,9627,Male,Loyal Customer,19,Personal Travel,Eco Plus,292,2,5,2,1,3,2,3,3,4,5,4,5,4,3,3,0.0,neutral or dissatisfied +16309,65385,Male,Loyal Customer,15,Personal Travel,Eco,631,1,4,0,4,2,0,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +16310,52412,Male,Loyal Customer,69,Personal Travel,Eco,598,2,0,2,2,1,2,1,1,3,4,4,4,5,1,0,2.0,neutral or dissatisfied +16311,97548,Female,Loyal Customer,41,Personal Travel,Eco,462,2,4,2,2,1,2,1,1,5,4,5,3,4,1,51,47.0,neutral or dissatisfied +16312,23603,Female,Loyal Customer,26,Business travel,Business,1699,3,3,4,3,3,3,3,3,2,1,4,3,3,3,10,0.0,neutral or dissatisfied +16313,34034,Male,Loyal Customer,26,Business travel,Eco Plus,1576,1,5,3,3,1,1,2,1,3,4,4,4,3,1,0,10.0,neutral or dissatisfied +16314,22401,Male,Loyal Customer,32,Business travel,Business,238,5,5,5,5,4,4,4,4,3,2,4,1,3,4,0,1.0,satisfied +16315,28665,Female,Loyal Customer,66,Personal Travel,Eco,2614,2,2,2,4,2,4,3,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +16316,97967,Female,Loyal Customer,16,Personal Travel,Eco,793,0,4,0,5,5,0,5,5,4,2,5,5,4,5,0,0.0,satisfied +16317,108510,Female,Loyal Customer,39,Business travel,Business,1731,1,5,5,5,1,3,3,1,1,2,1,3,1,4,77,59.0,neutral or dissatisfied +16318,4605,Female,Loyal Customer,30,Business travel,Business,3872,1,1,1,1,2,2,2,2,5,4,4,4,5,2,5,3.0,satisfied +16319,19621,Male,Loyal Customer,56,Business travel,Eco Plus,416,4,5,5,5,4,4,4,4,1,2,4,3,4,4,13,5.0,neutral or dissatisfied +16320,88116,Female,disloyal Customer,24,Business travel,Eco,404,2,0,2,5,1,2,1,1,3,3,5,4,4,1,9,6.0,neutral or dissatisfied +16321,124575,Male,Loyal Customer,49,Business travel,Business,3337,3,3,3,3,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +16322,76891,Male,Loyal Customer,55,Business travel,Business,3611,2,2,2,2,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +16323,73926,Female,Loyal Customer,35,Business travel,Business,2342,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +16324,119547,Female,Loyal Customer,45,Personal Travel,Eco,759,3,5,3,5,2,4,4,1,1,3,1,3,1,4,3,21.0,neutral or dissatisfied +16325,118556,Male,Loyal Customer,46,Business travel,Business,621,3,3,3,3,3,5,4,5,5,5,5,4,5,4,2,0.0,satisfied +16326,40355,Female,Loyal Customer,39,Business travel,Business,1250,1,1,1,1,5,4,5,4,4,4,4,5,4,5,22,46.0,satisfied +16327,35299,Female,Loyal Customer,43,Business travel,Eco,1035,2,3,3,3,4,4,4,2,2,2,2,4,2,2,2,15.0,neutral or dissatisfied +16328,81306,Female,Loyal Customer,50,Business travel,Business,1537,1,1,2,1,3,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +16329,884,Male,Loyal Customer,39,Business travel,Business,396,3,3,5,3,3,4,4,3,3,3,3,5,3,3,0,,satisfied +16330,30740,Female,Loyal Customer,23,Business travel,Business,1742,2,5,5,5,2,2,2,2,1,1,3,1,4,2,0,14.0,neutral or dissatisfied +16331,118739,Male,Loyal Customer,40,Personal Travel,Eco,368,3,2,3,3,1,3,1,1,1,3,4,3,3,1,0,0.0,neutral or dissatisfied +16332,70285,Female,Loyal Customer,31,Business travel,Business,852,5,1,3,1,5,4,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +16333,36174,Male,Loyal Customer,53,Business travel,Business,2098,1,1,1,1,4,3,3,2,2,2,1,4,2,4,10,27.0,neutral or dissatisfied +16334,18705,Male,Loyal Customer,62,Business travel,Eco Plus,201,5,3,3,3,5,5,5,5,5,4,1,4,2,5,0,0.0,satisfied +16335,20396,Female,Loyal Customer,47,Personal Travel,Eco,459,3,4,3,3,4,4,5,1,1,3,1,3,1,5,35,12.0,neutral or dissatisfied +16336,96010,Female,Loyal Customer,40,Business travel,Eco,795,4,4,5,4,4,4,4,4,4,3,4,1,3,4,0,0.0,neutral or dissatisfied +16337,42071,Male,Loyal Customer,67,Personal Travel,Eco,106,2,5,0,1,2,0,3,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +16338,65543,Male,Loyal Customer,52,Business travel,Business,237,1,3,3,3,3,3,4,1,1,1,1,4,1,4,1,0.0,neutral or dissatisfied +16339,57883,Female,disloyal Customer,39,Business travel,Business,305,3,3,3,1,3,3,3,3,3,4,5,4,5,3,4,0.0,neutral or dissatisfied +16340,64225,Male,Loyal Customer,30,Business travel,Business,1660,4,4,4,4,3,3,3,3,5,2,5,4,5,3,1,13.0,satisfied +16341,109650,Male,Loyal Customer,30,Business travel,Business,3533,2,2,2,2,2,2,2,2,4,2,3,3,3,2,15,12.0,neutral or dissatisfied +16342,54150,Male,Loyal Customer,42,Business travel,Eco,1400,2,5,5,5,2,2,2,2,3,5,4,2,5,2,0,0.0,satisfied +16343,61654,Female,disloyal Customer,48,Business travel,Business,1464,5,5,5,1,3,5,3,3,4,4,4,4,4,3,28,41.0,satisfied +16344,88828,Male,Loyal Customer,66,Personal Travel,Eco Plus,404,4,1,4,4,1,4,4,1,1,2,3,1,4,1,9,2.0,satisfied +16345,37002,Female,Loyal Customer,19,Personal Travel,Eco,899,1,2,1,4,5,1,1,5,3,1,4,4,4,5,0,0.0,neutral or dissatisfied +16346,90416,Male,disloyal Customer,20,Business travel,Eco,240,0,5,0,4,3,0,3,3,4,2,5,3,4,3,8,5.0,satisfied +16347,90027,Female,Loyal Customer,59,Business travel,Business,3272,1,1,1,1,2,5,4,4,4,4,4,3,4,5,0,38.0,satisfied +16348,58628,Male,Loyal Customer,39,Business travel,Business,3317,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,1.0,satisfied +16349,127532,Male,disloyal Customer,43,Business travel,Business,1009,3,3,3,3,3,3,3,3,5,4,5,5,4,3,0,3.0,satisfied +16350,75623,Female,Loyal Customer,44,Business travel,Business,3431,2,2,2,2,4,4,5,4,4,5,4,3,4,5,0,2.0,satisfied +16351,13564,Male,Loyal Customer,67,Personal Travel,Eco,227,4,5,4,4,3,4,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +16352,116680,Male,Loyal Customer,30,Business travel,Eco Plus,296,1,5,5,5,1,1,1,1,3,3,3,4,3,1,3,4.0,neutral or dissatisfied +16353,89856,Male,Loyal Customer,40,Business travel,Business,1487,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +16354,68213,Male,Loyal Customer,54,Business travel,Business,2602,4,4,4,4,4,4,4,2,2,2,2,3,2,5,0,31.0,satisfied +16355,52891,Female,Loyal Customer,18,Personal Travel,Eco,836,4,4,4,2,5,4,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +16356,24835,Female,Loyal Customer,35,Business travel,Business,2867,4,4,4,4,3,1,2,2,2,2,2,5,2,5,0,4.0,satisfied +16357,89712,Male,Loyal Customer,64,Personal Travel,Eco,950,2,4,2,4,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +16358,73183,Female,Loyal Customer,27,Business travel,Business,1258,3,1,1,1,3,4,3,3,1,5,3,4,3,3,29,32.0,neutral or dissatisfied +16359,36311,Female,Loyal Customer,37,Business travel,Eco,395,5,3,3,3,5,4,5,5,1,4,5,1,5,5,27,50.0,satisfied +16360,75579,Male,Loyal Customer,46,Business travel,Business,337,1,2,2,2,2,3,3,1,1,1,1,3,1,1,15,48.0,neutral or dissatisfied +16361,31982,Male,Loyal Customer,40,Business travel,Business,2530,1,5,5,5,4,2,2,2,2,3,1,3,2,2,11,14.0,neutral or dissatisfied +16362,51651,Male,Loyal Customer,70,Business travel,Business,1633,2,5,5,5,4,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +16363,9253,Female,Loyal Customer,65,Personal Travel,Eco,157,5,3,0,3,4,3,4,4,4,0,4,1,4,4,0,0.0,satisfied +16364,87484,Male,Loyal Customer,57,Business travel,Eco,321,2,1,1,1,2,2,2,2,2,3,4,2,4,2,0,0.0,neutral or dissatisfied +16365,23891,Female,Loyal Customer,39,Business travel,Eco,589,2,4,4,4,2,2,2,2,2,4,4,1,2,2,12,30.0,satisfied +16366,86162,Male,disloyal Customer,36,Business travel,Business,356,1,1,1,4,2,1,2,2,4,4,5,5,5,2,117,103.0,neutral or dissatisfied +16367,37168,Male,Loyal Customer,23,Personal Travel,Eco,1046,1,4,1,4,1,1,1,1,2,2,3,4,4,1,11,7.0,neutral or dissatisfied +16368,43786,Male,Loyal Customer,39,Business travel,Eco Plus,386,4,4,4,4,4,4,4,4,1,4,5,5,1,4,0,3.0,satisfied +16369,93599,Female,disloyal Customer,24,Business travel,Business,577,3,2,3,4,2,3,2,2,2,4,4,3,3,2,75,77.0,neutral or dissatisfied +16370,103174,Female,Loyal Customer,25,Personal Travel,Eco,491,4,3,4,1,2,4,2,2,1,4,2,1,5,2,3,54.0,neutral or dissatisfied +16371,19994,Female,Loyal Customer,48,Business travel,Eco,589,2,3,3,3,1,3,4,2,2,2,2,1,2,1,121,124.0,neutral or dissatisfied +16372,97481,Male,Loyal Customer,32,Business travel,Business,3493,4,4,4,4,4,4,4,4,3,2,4,3,5,4,65,62.0,satisfied +16373,102196,Male,Loyal Customer,40,Business travel,Business,386,5,5,5,5,4,5,4,2,2,2,2,3,2,3,3,0.0,satisfied +16374,10622,Female,disloyal Customer,25,Business travel,Business,201,5,0,5,4,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +16375,33529,Female,Loyal Customer,36,Business travel,Business,3660,1,1,1,1,1,2,2,5,5,5,5,4,5,3,0,0.0,satisfied +16376,67280,Female,Loyal Customer,18,Personal Travel,Eco,1121,0,2,1,4,1,1,1,1,2,2,2,2,3,1,13,4.0,satisfied +16377,101043,Male,disloyal Customer,34,Business travel,Business,368,2,2,2,3,4,2,4,4,4,3,4,3,4,4,22,22.0,neutral or dissatisfied +16378,47403,Male,Loyal Customer,39,Business travel,Business,3832,1,5,2,2,2,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +16379,17281,Male,Loyal Customer,35,Personal Travel,Eco Plus,872,3,4,4,4,5,4,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +16380,87293,Male,Loyal Customer,12,Personal Travel,Eco,577,5,2,5,4,2,5,2,2,3,2,4,1,4,2,13,1.0,satisfied +16381,7974,Female,Loyal Customer,58,Personal Travel,Eco Plus,594,4,5,4,4,2,4,1,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +16382,97409,Male,Loyal Customer,24,Business travel,Business,587,1,1,1,1,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +16383,33083,Female,Loyal Customer,7,Personal Travel,Eco,101,3,1,3,4,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +16384,117699,Male,Loyal Customer,48,Personal Travel,Eco,2075,1,4,1,4,2,1,2,2,5,4,5,5,5,2,0,8.0,neutral or dissatisfied +16385,101578,Female,disloyal Customer,37,Business travel,Business,1099,5,5,5,3,1,5,4,1,3,3,4,5,4,1,0,0.0,satisfied +16386,56346,Male,Loyal Customer,60,Business travel,Business,1816,3,3,3,3,4,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +16387,36039,Female,Loyal Customer,35,Business travel,Business,399,4,4,4,4,3,5,3,5,5,5,5,5,5,3,0,4.0,satisfied +16388,38220,Male,Loyal Customer,10,Personal Travel,Eco Plus,1237,2,4,1,2,5,1,5,5,3,3,5,3,4,5,0,6.0,neutral or dissatisfied +16389,36662,Male,Loyal Customer,8,Personal Travel,Eco,1185,3,4,3,3,5,3,2,5,4,3,2,2,4,5,0,0.0,neutral or dissatisfied +16390,32454,Female,disloyal Customer,48,Business travel,Eco,201,3,5,3,4,2,3,2,2,4,4,1,3,4,2,0,0.0,neutral or dissatisfied +16391,62445,Male,Loyal Customer,54,Business travel,Business,1846,2,2,5,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16392,96049,Female,disloyal Customer,45,Business travel,Eco,795,2,2,2,3,4,2,4,4,1,2,3,3,2,4,0,0.0,neutral or dissatisfied +16393,120384,Female,Loyal Customer,36,Business travel,Business,449,1,1,1,1,2,5,5,5,5,5,5,3,5,4,13,0.0,satisfied +16394,51555,Male,Loyal Customer,38,Business travel,Eco,751,2,2,2,2,2,2,2,2,2,3,2,3,5,2,87,82.0,satisfied +16395,1203,Female,Loyal Customer,44,Personal Travel,Eco,102,2,3,2,2,2,3,5,4,4,2,3,2,4,4,0,0.0,neutral or dissatisfied +16396,33325,Female,Loyal Customer,28,Business travel,Business,2399,1,1,1,1,2,2,2,2,3,5,5,4,2,2,0,0.0,satisfied +16397,25689,Female,Loyal Customer,49,Business travel,Eco,447,4,2,2,2,1,3,5,4,4,4,4,2,4,5,15,5.0,satisfied +16398,17118,Male,Loyal Customer,10,Personal Travel,Eco,821,4,3,4,4,5,4,5,5,4,3,3,2,4,5,31,39.0,satisfied +16399,8951,Female,Loyal Customer,54,Personal Travel,Eco,328,3,5,3,4,2,5,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +16400,102520,Female,Loyal Customer,49,Personal Travel,Eco,397,3,5,3,1,3,4,5,5,5,3,5,4,5,4,12,8.0,neutral or dissatisfied +16401,126606,Female,Loyal Customer,31,Business travel,Business,1337,2,3,3,3,2,2,2,2,1,4,3,3,4,2,48,46.0,neutral or dissatisfied +16402,37730,Male,Loyal Customer,7,Personal Travel,Eco,1076,2,5,1,4,4,1,2,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +16403,71741,Male,Loyal Customer,28,Personal Travel,Business,1846,1,4,1,4,2,1,2,2,5,4,4,3,5,2,0,5.0,neutral or dissatisfied +16404,54536,Female,Loyal Customer,16,Personal Travel,Eco,925,1,4,2,4,1,2,1,1,5,4,4,3,5,1,2,0.0,neutral or dissatisfied +16405,91185,Female,Loyal Customer,67,Personal Travel,Eco,406,2,5,2,3,4,5,4,2,2,2,2,3,2,5,4,14.0,neutral or dissatisfied +16406,111477,Female,Loyal Customer,23,Personal Travel,Business,1452,2,0,3,3,5,3,5,5,3,5,4,3,4,5,12,0.0,neutral or dissatisfied +16407,109793,Male,Loyal Customer,52,Business travel,Business,2987,4,4,4,4,4,4,4,5,5,5,5,5,5,4,67,61.0,satisfied +16408,76002,Male,Loyal Customer,44,Business travel,Business,2889,3,3,3,3,5,5,4,5,5,5,5,3,5,4,28,51.0,satisfied +16409,14487,Female,Loyal Customer,27,Personal Travel,Eco,541,2,2,2,4,2,3,3,4,4,4,3,3,3,3,116,146.0,neutral or dissatisfied +16410,119929,Female,disloyal Customer,39,Business travel,Business,868,4,4,4,2,4,4,4,4,3,2,4,4,4,4,2,0.0,satisfied +16411,20789,Female,disloyal Customer,52,Business travel,Eco,515,5,0,5,4,3,5,3,3,3,2,2,4,2,3,0,0.0,satisfied +16412,67346,Male,Loyal Customer,24,Personal Travel,Eco,1471,3,4,3,1,5,3,1,5,4,4,3,5,5,5,44,47.0,neutral or dissatisfied +16413,5564,Male,Loyal Customer,50,Business travel,Eco,588,1,4,3,4,1,1,1,1,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +16414,42585,Female,disloyal Customer,34,Business travel,Eco Plus,315,4,4,4,3,4,4,4,4,2,4,2,5,4,4,3,35.0,neutral or dissatisfied +16415,55491,Female,Loyal Customer,52,Business travel,Business,1739,1,1,3,1,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +16416,42183,Male,Loyal Customer,40,Business travel,Eco,817,3,4,4,4,3,3,3,3,1,5,4,1,2,3,0,0.0,satisfied +16417,117469,Female,Loyal Customer,66,Personal Travel,Business,507,1,2,1,4,4,4,4,4,4,1,4,4,4,1,113,117.0,neutral or dissatisfied +16418,47570,Female,Loyal Customer,67,Personal Travel,Eco Plus,558,2,4,2,4,4,4,4,4,4,2,4,5,4,3,25,6.0,neutral or dissatisfied +16419,22644,Male,Loyal Customer,65,Personal Travel,Eco,300,4,2,4,4,4,5,5,4,3,3,3,5,2,5,169,164.0,neutral or dissatisfied +16420,99294,Male,Loyal Customer,19,Personal Travel,Eco Plus,935,4,4,3,2,5,3,5,5,4,2,5,4,4,5,7,4.0,neutral or dissatisfied +16421,13049,Female,Loyal Customer,43,Personal Travel,Eco,438,3,5,3,3,2,5,1,5,5,3,5,1,5,1,15,3.0,neutral or dissatisfied +16422,11465,Male,disloyal Customer,18,Business travel,Business,270,0,5,0,1,5,0,5,5,3,3,4,3,4,5,0,0.0,satisfied +16423,59918,Male,Loyal Customer,47,Business travel,Business,2667,5,5,3,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +16424,34183,Female,Loyal Customer,42,Business travel,Eco,646,5,5,3,5,3,5,1,5,5,5,5,5,5,5,9,4.0,satisfied +16425,91073,Female,Loyal Customer,13,Personal Travel,Eco,240,3,4,3,1,3,3,3,3,3,2,4,5,5,3,2,0.0,neutral or dissatisfied +16426,6008,Male,disloyal Customer,19,Business travel,Business,672,4,4,4,1,4,2,2,4,4,5,5,2,3,2,1,136.0,satisfied +16427,63606,Male,Loyal Customer,47,Business travel,Business,1440,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,11.0,satisfied +16428,103815,Male,Loyal Customer,41,Business travel,Business,1587,4,4,4,4,4,4,5,4,4,4,4,5,4,5,23,48.0,satisfied +16429,17757,Male,Loyal Customer,59,Personal Travel,Eco,382,2,5,2,1,1,2,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +16430,88061,Female,Loyal Customer,22,Business travel,Business,2835,4,4,5,4,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +16431,59659,Male,Loyal Customer,46,Personal Travel,Eco,965,3,1,3,4,1,3,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +16432,121737,Male,Loyal Customer,36,Personal Travel,Eco,1475,5,4,5,3,4,5,4,4,3,3,4,5,5,4,0,0.0,satisfied +16433,39536,Female,Loyal Customer,53,Personal Travel,Business,954,2,5,2,4,4,4,4,1,1,2,1,5,1,5,0,28.0,neutral or dissatisfied +16434,32473,Female,Loyal Customer,35,Business travel,Business,3487,1,1,1,1,4,2,4,5,5,5,5,2,5,2,0,0.0,satisfied +16435,13558,Female,Loyal Customer,50,Personal Travel,Eco,106,5,2,5,3,3,4,4,2,2,5,2,1,2,2,0,0.0,satisfied +16436,56196,Female,Loyal Customer,58,Personal Travel,Eco,1400,2,4,2,5,3,5,5,2,2,2,2,5,2,4,0,7.0,neutral or dissatisfied +16437,122753,Male,Loyal Customer,47,Personal Travel,Eco,651,3,2,3,3,1,3,1,1,4,4,3,3,3,1,0,0.0,neutral or dissatisfied +16438,54069,Female,Loyal Customer,21,Business travel,Business,1416,2,2,2,2,4,4,4,4,5,1,3,3,2,4,0,0.0,satisfied +16439,111887,Male,disloyal Customer,16,Business travel,Eco,628,3,3,3,3,1,3,3,1,4,1,4,1,3,1,21,14.0,neutral or dissatisfied +16440,51319,Female,Loyal Customer,50,Business travel,Eco Plus,421,4,1,1,1,5,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +16441,81834,Female,Loyal Customer,12,Personal Travel,Eco,1416,4,1,4,2,1,4,1,1,4,3,2,2,3,1,0,0.0,satisfied +16442,37830,Male,Loyal Customer,41,Business travel,Eco,1065,5,4,4,4,5,5,5,5,5,1,5,2,4,5,5,0.0,satisfied +16443,109749,Female,Loyal Customer,58,Business travel,Business,587,4,4,5,4,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +16444,112699,Male,Loyal Customer,43,Business travel,Business,697,3,3,3,3,2,5,4,4,4,4,4,3,4,4,10,0.0,satisfied +16445,59936,Male,Loyal Customer,49,Business travel,Business,1681,3,2,2,2,5,4,3,3,3,3,3,3,3,3,18,6.0,neutral or dissatisfied +16446,103763,Male,Loyal Customer,57,Business travel,Business,2259,2,2,4,2,4,5,5,5,5,4,5,3,5,3,7,4.0,satisfied +16447,123097,Female,disloyal Customer,62,Business travel,Eco,600,1,1,1,4,1,1,1,1,4,2,4,3,4,1,0,7.0,neutral or dissatisfied +16448,93303,Female,Loyal Customer,44,Business travel,Business,1733,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +16449,37975,Female,Loyal Customer,35,Business travel,Business,1121,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +16450,18539,Male,Loyal Customer,39,Business travel,Eco,192,4,4,5,4,4,4,4,4,1,1,3,4,2,4,0,0.0,satisfied +16451,17922,Female,Loyal Customer,40,Personal Travel,Eco,900,2,5,2,1,4,2,3,4,4,5,4,1,5,4,0,0.0,neutral or dissatisfied +16452,111002,Female,Loyal Customer,50,Business travel,Business,2347,3,3,3,3,3,5,4,5,5,5,5,4,5,4,2,11.0,satisfied +16453,97341,Female,Loyal Customer,29,Business travel,Business,3831,3,4,4,4,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +16454,111779,Male,Loyal Customer,52,Business travel,Business,1620,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16455,7686,Female,Loyal Customer,34,Business travel,Business,2499,1,1,1,1,5,2,2,4,4,4,4,4,4,4,0,0.0,satisfied +16456,33695,Male,Loyal Customer,19,Business travel,Eco,899,3,2,2,2,3,3,1,3,4,1,4,4,3,3,0,10.0,neutral or dissatisfied +16457,118438,Female,disloyal Customer,22,Business travel,Business,651,4,4,4,2,1,4,1,1,3,4,4,3,5,1,29,40.0,satisfied +16458,100079,Female,Loyal Customer,36,Business travel,Eco Plus,277,1,4,4,4,1,1,1,1,1,3,3,1,4,1,8,16.0,neutral or dissatisfied +16459,17205,Male,Loyal Customer,41,Personal Travel,Eco,694,4,4,4,3,5,4,5,5,4,2,5,4,4,5,0,3.0,neutral or dissatisfied +16460,39693,Male,disloyal Customer,25,Business travel,Eco,946,2,2,2,3,3,2,4,3,4,2,3,3,3,3,52,40.0,neutral or dissatisfied +16461,86874,Female,Loyal Customer,44,Business travel,Business,692,2,2,2,2,3,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +16462,65859,Female,Loyal Customer,35,Personal Travel,Eco,1389,4,5,4,3,2,4,5,2,4,5,4,5,4,2,15,0.0,neutral or dissatisfied +16463,119480,Female,Loyal Customer,30,Business travel,Business,3232,4,4,4,4,5,5,5,5,3,2,5,5,5,5,24,9.0,satisfied +16464,3336,Male,Loyal Customer,44,Business travel,Business,240,5,5,5,5,3,5,5,5,5,5,5,4,5,4,16,11.0,satisfied +16465,45636,Male,Loyal Customer,44,Personal Travel,Eco,313,5,5,5,4,5,2,2,5,5,4,4,2,4,2,161,162.0,satisfied +16466,125529,Female,Loyal Customer,44,Business travel,Business,226,0,0,0,3,5,5,4,4,4,4,4,4,4,5,11,19.0,satisfied +16467,61005,Female,Loyal Customer,23,Business travel,Eco Plus,649,2,5,5,5,2,2,1,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +16468,118789,Male,Loyal Customer,65,Personal Travel,Eco,647,1,4,1,4,2,1,2,2,3,2,4,5,4,2,0,5.0,neutral or dissatisfied +16469,80705,Male,Loyal Customer,54,Personal Travel,Eco,748,3,4,3,4,1,3,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +16470,126668,Female,Loyal Customer,42,Business travel,Business,2276,2,3,3,3,1,1,2,2,2,2,2,2,2,3,4,0.0,neutral or dissatisfied +16471,24007,Female,disloyal Customer,34,Business travel,Eco,427,3,0,3,1,5,3,3,5,3,1,3,5,3,5,8,19.0,neutral or dissatisfied +16472,36815,Female,Loyal Customer,18,Personal Travel,Eco,2300,4,5,4,4,4,2,2,3,4,5,4,2,5,2,8,4.0,neutral or dissatisfied +16473,76001,Male,Loyal Customer,50,Business travel,Business,1822,0,0,0,2,5,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +16474,117327,Female,Loyal Customer,62,Personal Travel,Eco Plus,370,5,1,5,3,4,3,2,3,3,5,3,3,3,2,0,0.0,satisfied +16475,17521,Male,Loyal Customer,17,Personal Travel,Eco,341,3,4,3,5,2,3,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +16476,53139,Male,Loyal Customer,41,Business travel,Business,2181,1,4,5,4,2,3,3,1,1,2,1,4,1,2,53,28.0,neutral or dissatisfied +16477,119216,Male,Loyal Customer,29,Personal Travel,Eco,257,3,4,3,3,2,3,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +16478,79949,Female,Loyal Customer,48,Business travel,Eco,950,3,2,2,2,5,3,3,3,3,3,3,3,3,1,0,29.0,neutral or dissatisfied +16479,124981,Male,disloyal Customer,37,Business travel,Business,184,4,4,4,4,1,4,1,1,5,2,4,3,5,1,23,41.0,neutral or dissatisfied +16480,88814,Female,Loyal Customer,57,Business travel,Eco Plus,545,3,1,1,1,1,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +16481,113789,Male,Loyal Customer,53,Business travel,Business,386,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +16482,116025,Female,Loyal Customer,27,Personal Travel,Eco,417,2,3,2,3,4,2,4,4,4,2,3,1,4,4,32,27.0,neutral or dissatisfied +16483,13636,Male,Loyal Customer,44,Business travel,Eco Plus,1014,1,3,3,3,1,1,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +16484,39104,Male,Loyal Customer,23,Personal Travel,Business,252,5,5,5,3,2,5,2,2,4,4,1,2,1,2,0,0.0,satisfied +16485,58427,Female,Loyal Customer,39,Business travel,Eco,333,5,4,4,4,5,5,5,5,3,2,1,1,5,5,0,0.0,satisfied +16486,22965,Male,Loyal Customer,31,Business travel,Business,528,2,2,2,2,2,1,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +16487,77083,Female,Loyal Customer,40,Personal Travel,Eco,991,4,5,4,2,2,4,2,2,5,5,5,3,5,2,0,0.0,satisfied +16488,115368,Male,disloyal Customer,20,Business travel,Eco,342,4,0,4,3,3,4,3,3,3,5,5,4,5,3,0,0.0,satisfied +16489,95790,Male,Loyal Customer,47,Personal Travel,Eco,181,3,5,3,3,5,3,1,5,5,4,5,3,5,5,9,0.0,neutral or dissatisfied +16490,60382,Female,disloyal Customer,22,Business travel,Eco,704,2,2,2,3,4,2,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +16491,47846,Female,Loyal Customer,35,Business travel,Business,1848,1,4,4,4,3,4,4,1,1,1,1,2,1,2,6,2.0,neutral or dissatisfied +16492,25850,Male,disloyal Customer,38,Business travel,Eco,484,1,0,1,1,3,1,5,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +16493,43190,Male,Loyal Customer,24,Business travel,Business,3073,1,1,1,1,5,5,5,5,3,2,4,3,3,5,0,0.0,satisfied +16494,117891,Male,Loyal Customer,57,Business travel,Business,3477,5,5,5,5,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +16495,65925,Male,Loyal Customer,59,Personal Travel,Eco,569,3,2,3,3,3,3,3,3,3,5,3,3,4,3,0,1.0,neutral or dissatisfied +16496,85445,Female,Loyal Customer,57,Business travel,Business,3898,5,5,5,5,3,4,4,4,4,4,4,4,4,5,5,0.0,satisfied +16497,54335,Female,Loyal Customer,61,Personal Travel,Eco,1597,2,4,2,4,3,5,4,2,2,2,1,5,2,3,0,0.0,neutral or dissatisfied +16498,59427,Female,Loyal Customer,55,Business travel,Business,2338,4,4,4,4,3,5,4,4,4,4,4,4,4,5,10,0.0,satisfied +16499,68885,Male,disloyal Customer,62,Business travel,Business,936,1,1,1,1,3,1,5,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +16500,82191,Female,Loyal Customer,26,Business travel,Business,1927,2,5,2,5,2,2,2,2,2,2,1,2,2,2,19,19.0,neutral or dissatisfied +16501,20314,Male,Loyal Customer,34,Personal Travel,Eco,900,4,5,4,4,3,4,3,3,3,5,2,4,3,3,0,0.0,neutral or dissatisfied +16502,17444,Female,Loyal Customer,43,Personal Travel,Eco,376,5,5,5,1,4,5,5,5,5,5,3,4,5,5,0,0.0,satisfied +16503,114981,Female,Loyal Customer,56,Business travel,Business,2370,2,2,3,2,5,5,5,5,5,5,5,3,5,4,3,,satisfied +16504,99319,Male,Loyal Customer,38,Business travel,Business,448,2,2,2,2,5,4,3,2,2,1,2,1,2,2,123,115.0,neutral or dissatisfied +16505,98522,Female,Loyal Customer,66,Personal Travel,Eco,402,3,4,4,1,5,5,4,1,1,4,1,3,1,5,0,0.0,neutral or dissatisfied +16506,82544,Male,Loyal Customer,22,Personal Travel,Eco,629,3,2,3,3,4,3,1,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +16507,89881,Male,Loyal Customer,22,Business travel,Eco,1487,3,1,1,1,3,3,4,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +16508,19530,Female,Loyal Customer,49,Business travel,Business,173,4,4,1,4,3,4,2,5,5,5,4,3,5,1,0,5.0,satisfied +16509,118387,Female,Loyal Customer,49,Business travel,Business,1705,1,1,5,1,2,5,5,4,4,4,4,3,4,4,1,0.0,satisfied +16510,1687,Female,Loyal Customer,55,Business travel,Business,2541,1,0,0,4,5,3,4,5,5,0,5,4,5,2,0,3.0,neutral or dissatisfied +16511,11715,Male,Loyal Customer,58,Business travel,Business,1746,5,1,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +16512,57143,Female,disloyal Customer,36,Business travel,Business,1222,2,1,1,1,3,1,3,3,5,2,4,3,5,3,37,41.0,neutral or dissatisfied +16513,129018,Female,disloyal Customer,41,Business travel,Eco,876,3,3,3,4,3,3,3,3,2,4,4,3,3,3,39,0.0,neutral or dissatisfied +16514,17307,Male,disloyal Customer,61,Business travel,Eco,403,3,4,3,3,2,3,3,2,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +16515,114713,Female,Loyal Customer,55,Business travel,Business,404,3,3,3,3,4,5,5,3,3,3,3,3,3,5,36,36.0,satisfied +16516,111514,Male,Loyal Customer,18,Personal Travel,Eco,391,3,4,3,3,5,3,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +16517,90219,Female,Loyal Customer,67,Personal Travel,Eco,957,2,1,2,3,3,4,4,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +16518,98906,Male,disloyal Customer,28,Business travel,Business,543,0,0,0,1,1,0,1,1,5,3,5,3,5,1,14,7.0,satisfied +16519,82088,Female,disloyal Customer,25,Business travel,Eco,1276,3,3,3,2,2,3,2,2,4,1,2,3,3,2,68,59.0,neutral or dissatisfied +16520,38206,Female,disloyal Customer,35,Business travel,Eco Plus,1237,3,3,3,4,2,3,2,2,3,2,2,5,3,2,0,0.0,neutral or dissatisfied +16521,61534,Female,Loyal Customer,48,Personal Travel,Eco,2419,4,4,4,3,5,3,4,2,2,4,2,1,2,4,11,7.0,neutral or dissatisfied +16522,38927,Female,Loyal Customer,42,Business travel,Eco,298,4,3,4,4,4,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +16523,128458,Female,Loyal Customer,39,Personal Travel,Eco,370,2,4,2,4,4,2,4,4,2,4,3,2,5,4,0,0.0,neutral or dissatisfied +16524,112274,Male,disloyal Customer,21,Business travel,Eco,1272,1,1,1,3,1,1,2,1,4,1,3,1,4,1,0,0.0,neutral or dissatisfied +16525,110481,Male,Loyal Customer,50,Personal Travel,Eco,663,1,2,1,2,2,1,3,2,3,4,1,4,3,2,0,0.0,neutral or dissatisfied +16526,68180,Male,Loyal Customer,25,Personal Travel,Eco,603,2,5,2,5,4,2,4,4,5,5,4,3,4,4,1,0.0,neutral or dissatisfied +16527,128819,Male,disloyal Customer,46,Business travel,Business,2475,1,0,0,3,1,4,4,4,4,5,4,4,5,4,0,6.0,neutral or dissatisfied +16528,129074,Female,Loyal Customer,28,Personal Travel,Business,2342,3,4,3,3,3,3,3,1,3,5,5,3,3,3,0,0.0,neutral or dissatisfied +16529,18165,Female,Loyal Customer,17,Personal Travel,Eco,430,1,5,1,5,5,1,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +16530,118702,Male,Loyal Customer,8,Personal Travel,Eco,646,3,4,3,2,1,3,1,1,3,2,5,2,2,1,21,34.0,neutral or dissatisfied +16531,38290,Female,Loyal Customer,32,Personal Travel,Eco Plus,1173,2,5,2,3,3,2,3,3,4,4,4,3,4,3,57,58.0,neutral or dissatisfied +16532,24611,Male,Loyal Customer,34,Business travel,Business,3661,2,2,2,2,5,4,5,4,4,4,4,3,4,1,28,82.0,satisfied +16533,122542,Female,Loyal Customer,33,Business travel,Business,2396,2,2,2,2,2,4,5,5,5,5,5,3,5,3,27,25.0,satisfied +16534,120299,Male,disloyal Customer,34,Business travel,Business,268,3,4,4,4,3,4,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +16535,89329,Female,Loyal Customer,44,Business travel,Business,1587,5,5,5,5,5,3,4,4,4,4,4,3,4,3,7,0.0,satisfied +16536,48471,Male,Loyal Customer,36,Business travel,Eco,819,2,1,1,1,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +16537,56140,Female,Loyal Customer,32,Business travel,Business,1400,4,4,4,4,5,5,5,5,3,4,5,3,4,5,13,0.0,satisfied +16538,25571,Male,Loyal Customer,28,Business travel,Business,2840,2,4,4,4,2,2,2,2,4,2,3,3,4,2,14,17.0,neutral or dissatisfied +16539,88992,Male,Loyal Customer,54,Business travel,Business,3192,3,3,3,3,2,5,5,2,2,2,2,5,2,5,5,0.0,satisfied +16540,77021,Female,disloyal Customer,25,Business travel,Business,368,3,0,3,2,2,3,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +16541,75902,Female,Loyal Customer,26,Business travel,Business,603,3,3,3,3,5,4,5,5,4,3,4,3,1,5,0,0.0,satisfied +16542,67933,Female,Loyal Customer,65,Personal Travel,Eco,1464,1,4,2,3,3,3,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +16543,95338,Male,Loyal Customer,60,Personal Travel,Eco,239,1,5,1,2,5,1,5,5,2,1,1,3,5,5,47,54.0,neutral or dissatisfied +16544,116077,Female,Loyal Customer,38,Personal Travel,Eco,447,1,5,1,2,5,1,5,5,3,2,5,3,3,5,10,3.0,neutral or dissatisfied +16545,46957,Male,Loyal Customer,67,Personal Travel,Eco,959,2,4,2,4,3,2,3,3,5,4,4,4,4,3,1,0.0,neutral or dissatisfied +16546,57405,Female,Loyal Customer,47,Business travel,Business,455,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,16.0,satisfied +16547,113165,Male,Loyal Customer,44,Business travel,Business,1558,2,2,2,2,3,5,4,4,4,4,4,5,4,4,1,1.0,satisfied +16548,34826,Male,Loyal Customer,38,Business travel,Eco Plus,301,5,3,3,3,5,5,5,5,5,5,3,1,3,5,0,0.0,satisfied +16549,64976,Male,Loyal Customer,24,Business travel,Business,469,1,1,4,1,1,1,1,1,4,2,2,2,1,1,22,18.0,neutral or dissatisfied +16550,74297,Female,Loyal Customer,60,Business travel,Business,2288,5,5,5,5,5,4,4,5,5,5,5,3,5,3,44,14.0,satisfied +16551,32621,Female,Loyal Customer,32,Business travel,Eco,101,2,4,4,4,2,3,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +16552,13962,Female,Loyal Customer,9,Personal Travel,Eco,153,2,5,2,3,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +16553,85910,Male,Loyal Customer,59,Business travel,Business,761,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +16554,103731,Female,Loyal Customer,35,Personal Travel,Eco,251,3,5,3,4,5,3,5,5,5,2,3,1,4,5,2,0.0,neutral or dissatisfied +16555,59893,Female,Loyal Customer,60,Business travel,Business,2685,2,2,3,2,5,5,4,4,4,4,4,5,4,5,3,0.0,satisfied +16556,33411,Female,Loyal Customer,37,Business travel,Business,2556,1,1,2,1,3,3,1,4,4,4,4,2,4,3,32,23.0,satisfied +16557,45766,Female,Loyal Customer,35,Business travel,Business,3983,4,4,4,4,2,2,3,5,5,5,5,3,5,1,0,10.0,satisfied +16558,36917,Male,Loyal Customer,65,Business travel,Business,340,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16559,117200,Female,Loyal Customer,37,Personal Travel,Eco,651,1,1,2,2,4,2,4,4,1,1,2,3,2,4,26,8.0,neutral or dissatisfied +16560,115091,Female,disloyal Customer,21,Business travel,Business,337,5,0,4,2,4,4,4,4,4,3,5,4,5,4,37,32.0,satisfied +16561,28803,Male,Loyal Customer,22,Business travel,Business,954,1,1,1,1,5,5,5,5,4,1,5,5,5,5,3,0.0,satisfied +16562,119787,Male,disloyal Customer,22,Business travel,Eco,936,2,2,2,3,3,2,3,3,1,2,3,1,4,3,0,27.0,neutral or dissatisfied +16563,88115,Male,disloyal Customer,20,Business travel,Eco,240,5,0,5,2,2,5,2,2,5,3,4,4,5,2,0,0.0,satisfied +16564,95143,Male,Loyal Customer,40,Personal Travel,Eco,148,5,1,0,3,5,0,5,5,4,1,2,3,2,5,10,0.0,satisfied +16565,18185,Female,Loyal Customer,42,Business travel,Eco,235,2,2,2,2,4,3,4,2,2,2,2,4,2,1,0,8.0,neutral or dissatisfied +16566,99046,Male,Loyal Customer,52,Business travel,Business,419,2,2,2,2,5,3,3,2,2,2,2,1,2,1,29,18.0,neutral or dissatisfied +16567,41797,Male,disloyal Customer,38,Business travel,Eco,489,1,0,1,4,1,1,1,1,2,2,1,5,1,1,0,0.0,neutral or dissatisfied +16568,103030,Female,Loyal Customer,58,Business travel,Eco,687,3,4,4,4,1,3,3,4,4,3,4,4,4,2,92,103.0,neutral or dissatisfied +16569,38985,Female,Loyal Customer,33,Business travel,Business,406,2,4,4,4,3,3,4,2,2,2,2,1,2,4,31,18.0,neutral or dissatisfied +16570,82589,Male,Loyal Customer,17,Business travel,Business,528,1,5,5,5,1,1,1,1,4,3,3,1,3,1,0,0.0,neutral or dissatisfied +16571,115668,Male,disloyal Customer,25,Business travel,Eco,372,4,1,3,3,5,3,5,5,4,3,4,1,3,5,0,0.0,neutral or dissatisfied +16572,33461,Female,disloyal Customer,16,Business travel,Eco,1425,3,3,3,3,3,1,1,1,4,4,4,1,1,1,0,30.0,neutral or dissatisfied +16573,91916,Female,Loyal Customer,56,Business travel,Business,2586,3,4,4,4,3,2,4,3,3,3,3,4,3,2,29,18.0,neutral or dissatisfied +16574,103285,Male,Loyal Customer,28,Business travel,Business,2405,4,4,4,4,4,4,4,4,3,1,3,3,4,4,30,35.0,neutral or dissatisfied +16575,29952,Male,disloyal Customer,62,Business travel,Eco,95,2,3,2,3,2,2,2,2,1,5,5,4,5,2,0,0.0,neutral or dissatisfied +16576,15498,Female,Loyal Customer,12,Personal Travel,Eco,331,3,5,3,1,5,3,5,5,4,1,3,1,4,5,83,76.0,neutral or dissatisfied +16577,43372,Female,Loyal Customer,69,Personal Travel,Eco,531,1,4,1,1,3,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +16578,112774,Male,Loyal Customer,64,Personal Travel,Eco,590,3,5,3,4,3,3,3,3,3,5,4,5,2,3,15,16.0,neutral or dissatisfied +16579,57964,Female,Loyal Customer,40,Personal Travel,Eco,1911,3,5,4,1,5,4,5,5,5,2,3,5,5,5,6,21.0,neutral or dissatisfied +16580,111151,Female,Loyal Customer,19,Personal Travel,Eco,1050,1,5,1,1,5,1,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +16581,31484,Female,Loyal Customer,56,Business travel,Business,2842,3,3,3,3,4,1,5,4,4,4,4,2,4,3,9,7.0,satisfied +16582,114367,Male,Loyal Customer,59,Business travel,Business,1696,1,1,1,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +16583,53109,Female,Loyal Customer,26,Business travel,Eco,2065,5,4,4,4,5,5,5,5,1,5,4,5,5,5,0,0.0,satisfied +16584,104207,Female,Loyal Customer,40,Business travel,Business,680,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +16585,111454,Female,Loyal Customer,66,Personal Travel,Eco,1024,5,5,5,5,5,1,1,4,3,5,4,1,3,1,194,190.0,satisfied +16586,33294,Male,Loyal Customer,52,Personal Travel,Eco Plus,102,4,5,4,1,1,4,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +16587,3219,Male,Loyal Customer,11,Business travel,Business,2323,1,0,0,4,1,0,1,1,3,1,3,2,4,1,0,3.0,neutral or dissatisfied +16588,103683,Female,Loyal Customer,47,Business travel,Business,405,1,1,1,1,5,4,4,5,5,5,5,4,5,4,38,23.0,satisfied +16589,74547,Female,Loyal Customer,55,Business travel,Business,1431,5,5,5,5,4,4,4,4,4,4,4,4,4,4,24,12.0,satisfied +16590,64077,Female,Loyal Customer,34,Personal Travel,Eco,919,3,4,3,3,3,3,3,3,5,4,4,3,4,3,54,61.0,neutral or dissatisfied +16591,52395,Female,Loyal Customer,31,Personal Travel,Eco,261,3,5,3,4,1,3,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +16592,55824,Male,Loyal Customer,37,Business travel,Business,1416,1,1,1,1,5,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +16593,156,Female,disloyal Customer,49,Business travel,Business,227,2,2,2,3,3,2,5,3,1,5,4,2,3,3,4,9.0,neutral or dissatisfied +16594,68653,Male,Loyal Customer,42,Business travel,Business,237,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,2.0,satisfied +16595,33551,Male,disloyal Customer,22,Business travel,Eco,399,5,1,5,3,4,1,4,4,1,2,4,2,5,4,0,8.0,satisfied +16596,95326,Male,Loyal Customer,25,Personal Travel,Eco,293,2,5,2,3,2,2,2,2,3,5,5,3,5,2,33,34.0,neutral or dissatisfied +16597,68861,Female,disloyal Customer,37,Business travel,Business,936,4,4,4,4,4,4,2,4,4,5,5,5,5,4,25,11.0,neutral or dissatisfied +16598,76188,Male,Loyal Customer,31,Business travel,Business,2422,4,4,4,4,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +16599,88771,Male,Loyal Customer,51,Business travel,Business,2768,4,4,4,4,5,5,4,3,3,3,3,4,3,4,2,0.0,satisfied +16600,9129,Male,Loyal Customer,57,Personal Travel,Eco,765,1,4,1,3,2,1,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +16601,104080,Male,Loyal Customer,32,Personal Travel,Eco,359,4,4,4,3,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +16602,86200,Female,Loyal Customer,44,Business travel,Business,2251,2,4,4,4,4,2,3,2,2,2,2,1,2,3,3,4.0,neutral or dissatisfied +16603,57347,Male,Loyal Customer,56,Business travel,Business,1859,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +16604,22029,Male,Loyal Customer,28,Business travel,Eco Plus,503,2,4,4,4,2,1,2,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +16605,43885,Male,Loyal Customer,35,Business travel,Eco,174,4,1,1,1,4,4,4,4,1,4,3,5,5,4,0,0.0,satisfied +16606,103131,Male,Loyal Customer,57,Business travel,Business,460,1,1,3,1,5,4,4,5,5,5,5,3,5,5,8,2.0,satisfied +16607,104069,Male,Loyal Customer,57,Business travel,Business,2271,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +16608,117441,Female,disloyal Customer,24,Business travel,Eco,1107,3,3,3,4,3,3,3,3,3,5,5,4,4,3,0,17.0,neutral or dissatisfied +16609,12560,Male,Loyal Customer,42,Personal Travel,Eco,871,3,4,3,3,3,3,3,3,1,5,3,4,2,3,24,8.0,neutral or dissatisfied +16610,18913,Female,Loyal Customer,52,Personal Travel,Eco,503,2,4,4,5,3,4,4,5,5,4,5,4,5,3,73,63.0,neutral or dissatisfied +16611,61414,Female,Loyal Customer,41,Business travel,Business,2876,1,1,1,1,4,5,5,4,4,5,4,4,4,3,2,0.0,satisfied +16612,95907,Female,Loyal Customer,49,Business travel,Business,3878,2,4,2,2,3,4,5,4,4,4,4,5,4,3,1,0.0,satisfied +16613,12128,Male,Loyal Customer,33,Business travel,Eco Plus,1034,4,2,2,2,4,4,4,4,1,2,3,3,2,4,0,0.0,satisfied +16614,13390,Male,Loyal Customer,38,Business travel,Business,3809,3,3,2,3,1,5,4,4,4,4,4,4,4,2,39,15.0,satisfied +16615,120948,Female,Loyal Customer,54,Business travel,Business,861,3,3,3,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +16616,22023,Female,Loyal Customer,26,Business travel,Eco Plus,448,1,1,2,1,1,1,1,1,1,3,3,2,4,1,0,20.0,neutral or dissatisfied +16617,3425,Male,Loyal Customer,58,Personal Travel,Eco,240,3,2,3,2,3,3,3,3,1,4,3,1,3,3,1,0.0,neutral or dissatisfied +16618,110569,Female,Loyal Customer,49,Business travel,Business,2815,4,4,4,4,4,4,4,4,4,4,4,5,4,5,24,18.0,satisfied +16619,39366,Male,Loyal Customer,37,Business travel,Business,3986,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +16620,84533,Male,Loyal Customer,30,Business travel,Eco,2556,3,5,5,5,3,3,3,3,2,2,4,1,3,3,0,0.0,neutral or dissatisfied +16621,38783,Female,disloyal Customer,25,Business travel,Eco,353,1,4,1,3,2,1,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +16622,117779,Female,Loyal Customer,56,Business travel,Business,1912,2,2,2,2,2,3,5,5,5,4,5,4,5,3,36,35.0,satisfied +16623,22144,Female,Loyal Customer,54,Business travel,Business,2908,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +16624,104850,Male,Loyal Customer,52,Business travel,Business,2723,1,1,1,1,5,5,5,4,5,5,4,5,3,5,150,155.0,satisfied +16625,98671,Male,Loyal Customer,17,Personal Travel,Eco,873,2,1,2,4,2,2,2,2,4,2,3,4,4,2,2,8.0,neutral or dissatisfied +16626,21853,Male,disloyal Customer,62,Business travel,Eco,448,3,3,3,3,4,3,4,4,4,1,1,1,3,4,0,0.0,neutral or dissatisfied +16627,102383,Male,Loyal Customer,32,Business travel,Business,1985,4,1,1,1,4,4,4,4,2,5,4,3,4,4,37,23.0,neutral or dissatisfied +16628,26723,Female,Loyal Customer,30,Business travel,Eco Plus,515,5,4,4,4,5,5,5,5,2,3,1,5,3,5,0,0.0,satisfied +16629,23275,Male,Loyal Customer,43,Personal Travel,Business,979,4,1,4,3,1,2,2,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +16630,121984,Female,Loyal Customer,40,Business travel,Business,3436,4,4,4,4,3,4,4,5,5,5,5,5,5,3,8,33.0,satisfied +16631,113147,Female,disloyal Customer,48,Business travel,Business,628,5,5,5,2,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +16632,59856,Male,Loyal Customer,57,Business travel,Business,3409,3,3,3,3,4,4,4,5,5,5,5,4,5,3,110,94.0,satisfied +16633,107622,Female,Loyal Customer,59,Business travel,Eco,423,2,4,4,4,4,3,4,2,2,2,2,4,2,3,23,12.0,neutral or dissatisfied +16634,99406,Male,Loyal Customer,42,Business travel,Business,314,3,5,5,5,4,3,3,1,3,3,4,3,1,3,164,204.0,neutral or dissatisfied +16635,34517,Female,Loyal Customer,23,Personal Travel,Eco,1428,3,5,3,4,4,3,4,4,5,3,3,3,5,4,0,0.0,neutral or dissatisfied +16636,14149,Male,Loyal Customer,27,Personal Travel,Eco,654,2,5,2,3,2,2,2,2,5,3,4,4,5,2,25,16.0,neutral or dissatisfied +16637,114631,Female,disloyal Customer,26,Business travel,Eco,404,4,2,4,4,4,4,5,4,1,1,4,1,4,4,0,0.0,neutral or dissatisfied +16638,31796,Female,disloyal Customer,38,Business travel,Eco,1140,3,3,3,3,3,5,1,1,2,3,3,1,1,1,0,31.0,neutral or dissatisfied +16639,55045,Female,disloyal Customer,22,Business travel,Eco,1379,3,3,3,3,3,3,3,3,1,2,4,3,4,3,26,10.0,neutral or dissatisfied +16640,91408,Female,Loyal Customer,48,Personal Travel,Eco Plus,2218,3,2,3,4,1,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +16641,99912,Male,Loyal Customer,21,Business travel,Business,1428,2,2,2,2,5,5,5,5,3,1,5,2,4,5,0,0.0,satisfied +16642,6614,Female,Loyal Customer,36,Business travel,Business,1504,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,5.0,satisfied +16643,114471,Male,Loyal Customer,49,Business travel,Business,2961,4,4,3,4,3,5,4,4,4,4,4,5,4,5,3,0.0,satisfied +16644,57552,Female,disloyal Customer,34,Business travel,Business,1597,2,2,2,3,2,4,3,4,3,4,5,3,3,3,145,129.0,neutral or dissatisfied +16645,127474,Male,Loyal Customer,58,Business travel,Eco,2075,1,4,5,4,1,1,1,1,1,5,4,2,4,1,43,24.0,neutral or dissatisfied +16646,38160,Male,Loyal Customer,26,Personal Travel,Eco,1237,2,5,2,3,5,2,5,5,5,3,5,3,4,5,11,4.0,neutral or dissatisfied +16647,86300,Male,disloyal Customer,42,Personal Travel,Eco,331,4,0,4,3,5,4,5,5,5,5,5,4,4,5,16,13.0,neutral or dissatisfied +16648,6775,Male,Loyal Customer,50,Business travel,Business,3621,4,4,4,4,3,5,5,5,5,5,5,5,5,4,4,0.0,satisfied +16649,11603,Male,Loyal Customer,25,Personal Travel,Eco,468,2,2,1,3,2,1,5,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +16650,106942,Female,Loyal Customer,29,Business travel,Business,2704,1,1,1,1,3,3,3,3,5,3,5,4,5,3,52,54.0,satisfied +16651,31144,Female,Loyal Customer,17,Business travel,Business,3878,5,3,5,5,2,3,2,2,2,2,2,1,5,2,30,22.0,satisfied +16652,43462,Male,disloyal Customer,36,Business travel,Eco,524,3,0,4,3,3,4,3,3,1,1,3,3,3,3,49,95.0,neutral or dissatisfied +16653,23690,Female,disloyal Customer,19,Business travel,Eco,212,3,4,3,5,1,3,1,1,4,3,3,4,2,1,0,0.0,neutral or dissatisfied +16654,58283,Male,Loyal Customer,22,Personal Travel,Eco,594,1,4,1,4,4,1,4,4,2,2,2,1,5,4,12,3.0,neutral or dissatisfied +16655,16425,Female,Loyal Customer,48,Business travel,Business,529,3,3,3,3,3,5,2,5,5,5,5,5,5,4,7,3.0,satisfied +16656,14897,Female,Loyal Customer,23,Business travel,Business,2873,0,0,0,3,3,3,5,3,5,4,1,3,4,3,0,0.0,satisfied +16657,25546,Male,Loyal Customer,51,Business travel,Eco Plus,516,5,2,2,2,5,5,5,5,2,1,5,2,4,5,0,4.0,satisfied +16658,72171,Male,Loyal Customer,23,Personal Travel,Business,594,5,3,5,5,1,5,1,1,3,4,4,1,4,1,15,20.0,satisfied +16659,87430,Female,Loyal Customer,45,Personal Travel,Eco Plus,425,3,4,3,5,5,4,5,4,4,3,4,5,4,3,8,13.0,neutral or dissatisfied +16660,60042,Female,disloyal Customer,25,Business travel,Business,1065,1,0,1,5,5,1,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +16661,118879,Female,Loyal Customer,46,Personal Travel,Eco,1136,2,5,2,2,4,4,4,1,1,2,1,4,1,4,1,6.0,neutral or dissatisfied +16662,51256,Female,Loyal Customer,55,Business travel,Eco Plus,373,1,5,5,5,2,4,4,1,1,1,1,4,1,1,65,63.0,neutral or dissatisfied +16663,117681,Male,Loyal Customer,40,Business travel,Business,2075,1,1,1,1,5,4,4,4,4,4,4,4,4,4,12,15.0,satisfied +16664,26060,Male,Loyal Customer,31,Business travel,Eco Plus,432,5,1,1,1,5,5,5,5,4,3,4,4,2,5,9,2.0,satisfied +16665,112109,Female,Loyal Customer,40,Business travel,Business,3240,4,4,3,4,5,5,4,5,5,5,5,5,5,5,12,9.0,satisfied +16666,97278,Male,Loyal Customer,29,Business travel,Business,1817,1,1,1,1,5,5,5,5,4,3,4,5,4,5,0,17.0,satisfied +16667,93168,Female,Loyal Customer,13,Personal Travel,Eco,1075,3,4,3,3,2,3,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +16668,39554,Male,Loyal Customer,56,Business travel,Business,3588,3,3,3,3,3,3,2,4,4,4,4,1,4,2,20,4.0,satisfied +16669,119079,Female,Loyal Customer,60,Business travel,Business,1609,1,1,1,1,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +16670,3205,Male,Loyal Customer,38,Personal Travel,Eco,693,3,4,3,4,5,3,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +16671,43913,Male,Loyal Customer,65,Personal Travel,Eco,255,1,3,1,3,4,1,4,4,2,3,4,1,3,4,0,9.0,neutral or dissatisfied +16672,3346,Male,Loyal Customer,21,Business travel,Eco,240,4,2,2,2,3,2,4,3,2,3,3,4,1,4,537,524.0,neutral or dissatisfied +16673,94348,Female,disloyal Customer,25,Business travel,Business,293,1,0,1,1,4,1,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +16674,54257,Female,Loyal Customer,12,Personal Travel,Eco,1222,4,4,4,3,4,4,4,4,2,2,4,3,4,4,54,47.0,satisfied +16675,20511,Female,Loyal Customer,35,Business travel,Eco Plus,139,5,5,5,5,5,5,5,5,2,2,2,2,4,5,6,0.0,satisfied +16676,123116,Female,Loyal Customer,25,Business travel,Business,3828,1,1,1,1,1,1,1,1,3,2,4,1,3,1,0,1.0,neutral or dissatisfied +16677,28034,Male,disloyal Customer,12,Business travel,Business,2537,2,2,1,4,2,1,2,2,2,3,4,4,3,2,1,0.0,neutral or dissatisfied +16678,96362,Male,disloyal Customer,29,Business travel,Business,1246,4,4,4,4,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +16679,79600,Male,disloyal Customer,22,Business travel,Eco,762,3,3,3,3,2,3,2,2,5,3,5,3,5,2,10,3.0,neutral or dissatisfied +16680,95477,Female,Loyal Customer,35,Business travel,Eco Plus,189,4,4,4,4,4,4,4,4,1,3,4,3,4,4,9,6.0,neutral or dissatisfied +16681,129141,Female,Loyal Customer,40,Business travel,Business,1665,3,3,3,3,3,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +16682,10002,Female,Loyal Customer,27,Personal Travel,Eco,534,3,5,3,1,3,3,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +16683,36187,Male,Loyal Customer,47,Business travel,Business,280,5,5,5,5,3,4,5,4,4,4,4,3,4,4,35,43.0,satisfied +16684,74899,Male,Loyal Customer,43,Business travel,Business,2475,3,2,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +16685,91897,Male,disloyal Customer,49,Business travel,Business,1224,5,4,4,4,2,5,2,2,3,5,5,3,4,2,24,22.0,satisfied +16686,13814,Female,Loyal Customer,27,Business travel,Business,594,4,4,4,4,5,5,5,5,4,2,5,4,4,5,0,3.0,satisfied +16687,129752,Female,Loyal Customer,47,Business travel,Business,308,5,5,4,5,1,1,3,5,5,5,5,2,5,5,1,0.0,satisfied +16688,2464,Male,Loyal Customer,42,Business travel,Business,674,3,3,3,3,4,2,1,3,3,3,3,4,3,3,0,11.0,neutral or dissatisfied +16689,94352,Male,Loyal Customer,48,Business travel,Business,192,2,2,2,2,3,4,4,4,4,5,5,4,4,5,0,0.0,satisfied +16690,36646,Female,Loyal Customer,40,Personal Travel,Eco,1220,4,2,4,4,4,4,4,4,2,1,3,1,4,4,0,3.0,neutral or dissatisfied +16691,83668,Female,Loyal Customer,39,Business travel,Business,577,2,2,4,2,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +16692,41570,Male,Loyal Customer,59,Personal Travel,Eco,1211,3,2,3,3,1,3,1,1,1,1,3,2,3,1,44,33.0,neutral or dissatisfied +16693,98287,Female,Loyal Customer,53,Personal Travel,Eco,1148,5,4,5,4,3,5,4,2,2,5,4,3,2,4,44,41.0,satisfied +16694,125055,Female,Loyal Customer,50,Business travel,Eco Plus,2300,1,5,5,5,1,1,1,1,4,2,3,1,4,1,5,69.0,neutral or dissatisfied +16695,19771,Male,disloyal Customer,22,Business travel,Eco,267,2,4,1,3,2,1,2,2,5,2,4,4,4,2,14,8.0,neutral or dissatisfied +16696,24107,Male,Loyal Customer,43,Business travel,Eco,584,4,5,5,5,4,4,4,4,4,2,4,5,3,4,0,0.0,satisfied +16697,10603,Female,disloyal Customer,17,Business travel,Business,166,4,5,4,1,3,4,3,3,5,4,5,4,4,3,0,0.0,satisfied +16698,110078,Male,Loyal Customer,67,Personal Travel,Business,1155,3,4,3,3,3,4,4,4,3,4,5,4,5,4,141,163.0,neutral or dissatisfied +16699,14442,Female,disloyal Customer,26,Business travel,Eco,674,3,3,3,4,4,3,4,4,2,3,4,4,3,4,114,99.0,neutral or dissatisfied +16700,8873,Female,disloyal Customer,13,Business travel,Eco,622,1,1,1,3,3,1,3,3,4,1,3,4,4,3,11,2.0,neutral or dissatisfied +16701,95644,Female,Loyal Customer,32,Personal Travel,Eco Plus,670,5,4,5,4,1,5,1,1,3,3,4,3,4,1,0,0.0,satisfied +16702,33258,Male,Loyal Customer,46,Personal Travel,Eco Plus,102,0,4,0,3,1,0,1,1,4,1,4,3,4,1,2,4.0,satisfied +16703,114468,Male,Loyal Customer,49,Business travel,Business,2638,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +16704,75335,Female,Loyal Customer,45,Business travel,Business,1056,1,1,1,1,1,4,5,4,4,4,4,2,4,3,0,0.0,satisfied +16705,125921,Male,Loyal Customer,7,Personal Travel,Eco,951,4,1,4,3,2,4,2,2,1,4,2,1,2,2,0,0.0,neutral or dissatisfied +16706,60248,Female,Loyal Customer,19,Personal Travel,Eco,1709,2,3,2,4,2,2,2,2,1,5,4,3,4,2,71,52.0,neutral or dissatisfied +16707,38600,Female,Loyal Customer,32,Business travel,Business,231,0,0,0,3,5,5,5,5,5,4,2,5,3,5,76,80.0,satisfied +16708,81195,Male,Loyal Customer,60,Business travel,Business,1426,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +16709,36257,Male,Loyal Customer,48,Business travel,Eco,728,2,2,2,2,2,2,2,2,1,3,3,4,4,2,90,93.0,neutral or dissatisfied +16710,483,Female,Loyal Customer,34,Business travel,Business,2553,5,5,5,5,3,5,5,5,5,5,4,4,5,3,0,0.0,satisfied +16711,61786,Female,Loyal Customer,25,Personal Travel,Eco,1303,4,4,4,4,4,4,3,4,4,5,4,5,5,4,11,0.0,neutral or dissatisfied +16712,30891,Male,Loyal Customer,42,Business travel,Business,2117,4,4,4,4,3,1,5,3,3,3,3,2,3,1,0,9.0,satisfied +16713,2093,Female,Loyal Customer,43,Personal Travel,Eco,785,2,4,2,3,4,4,5,5,5,2,5,5,5,4,17,70.0,neutral or dissatisfied +16714,14062,Female,Loyal Customer,53,Personal Travel,Eco,319,3,2,3,3,3,3,3,3,3,3,2,3,4,3,113,158.0,neutral or dissatisfied +16715,60511,Male,Loyal Customer,32,Personal Travel,Eco,862,2,5,2,3,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +16716,2529,Female,disloyal Customer,44,Business travel,Eco,304,2,3,2,3,3,2,4,3,3,2,3,4,3,3,15,19.0,neutral or dissatisfied +16717,96101,Male,Loyal Customer,23,Personal Travel,Eco,1235,3,4,3,4,4,3,4,4,3,2,4,5,5,4,15,7.0,neutral or dissatisfied +16718,109836,Male,Loyal Customer,23,Business travel,Business,3899,1,1,1,1,4,4,4,4,4,2,5,4,4,4,24,9.0,satisfied +16719,36172,Female,disloyal Customer,25,Business travel,Eco,174,3,1,3,3,5,3,5,5,2,4,3,1,3,5,5,0.0,neutral or dissatisfied +16720,38073,Male,disloyal Customer,26,Business travel,Eco,1237,4,4,4,4,3,4,3,3,4,2,5,1,1,3,36,15.0,satisfied +16721,71544,Male,Loyal Customer,40,Business travel,Business,1866,1,1,1,1,4,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +16722,75942,Female,Loyal Customer,37,Personal Travel,Business,297,2,5,2,3,4,4,4,2,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +16723,112247,Male,Loyal Customer,46,Business travel,Business,1546,5,5,5,5,3,5,4,5,5,5,5,3,5,3,5,0.0,satisfied +16724,95084,Female,Loyal Customer,18,Personal Travel,Eco,189,2,5,2,1,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +16725,27274,Female,Loyal Customer,11,Personal Travel,Business,671,5,5,5,1,3,5,3,3,4,2,5,4,4,3,0,0.0,satisfied +16726,32855,Female,Loyal Customer,8,Personal Travel,Eco,102,1,4,1,2,1,1,1,1,2,3,4,3,5,1,0,0.0,neutral or dissatisfied +16727,77343,Male,Loyal Customer,39,Business travel,Business,2178,3,3,3,3,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +16728,118578,Female,Loyal Customer,48,Business travel,Business,3178,0,0,0,4,4,5,4,1,1,1,1,4,1,4,0,0.0,satisfied +16729,119239,Female,disloyal Customer,24,Business travel,Business,331,5,4,5,2,5,5,5,5,4,4,4,5,4,5,9,12.0,satisfied +16730,13022,Male,Loyal Customer,66,Business travel,Business,374,3,1,1,1,1,3,4,3,3,2,3,2,3,3,15,19.0,neutral or dissatisfied +16731,118544,Male,Loyal Customer,40,Business travel,Business,2587,3,3,3,3,5,5,4,4,4,4,4,3,4,5,25,23.0,satisfied +16732,101491,Female,Loyal Customer,53,Business travel,Business,345,3,3,3,3,3,5,4,4,4,4,4,5,4,5,20,21.0,satisfied +16733,94447,Female,disloyal Customer,37,Business travel,Eco,192,3,2,3,4,3,3,3,3,4,5,3,3,4,3,0,0.0,neutral or dissatisfied +16734,105523,Male,Loyal Customer,52,Business travel,Business,611,1,1,1,1,3,5,4,5,5,5,5,4,5,4,61,80.0,satisfied +16735,106496,Male,disloyal Customer,28,Business travel,Business,495,0,0,0,1,3,0,3,3,4,2,4,4,4,3,0,0.0,satisfied +16736,37277,Male,disloyal Customer,44,Business travel,Business,1074,1,0,0,3,3,1,3,3,2,3,1,3,5,3,0,0.0,neutral or dissatisfied +16737,5012,Female,Loyal Customer,39,Personal Travel,Eco,502,2,5,3,3,2,3,2,2,4,2,5,3,4,2,0,38.0,neutral or dissatisfied +16738,89771,Male,Loyal Customer,30,Personal Travel,Eco,1076,3,4,3,4,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +16739,52320,Female,Loyal Customer,51,Business travel,Business,651,5,3,5,5,4,1,1,5,5,5,5,4,5,1,0,0.0,satisfied +16740,129441,Female,Loyal Customer,67,Personal Travel,Eco,236,0,4,0,4,4,5,5,1,1,0,1,5,1,3,0,0.0,satisfied +16741,62547,Female,disloyal Customer,23,Business travel,Eco,1283,3,2,2,4,1,3,1,1,3,5,3,3,5,1,2,0.0,satisfied +16742,33846,Female,disloyal Customer,27,Business travel,Eco,1262,4,4,4,4,5,4,3,5,2,2,4,4,4,5,0,0.0,neutral or dissatisfied +16743,91890,Male,Loyal Customer,22,Business travel,Business,2475,2,2,2,2,4,4,4,4,4,3,5,4,4,4,0,10.0,satisfied +16744,128968,Female,Loyal Customer,19,Personal Travel,Eco,414,2,4,2,1,5,2,5,5,2,4,3,4,4,5,0,0.0,neutral or dissatisfied +16745,65020,Male,Loyal Customer,44,Business travel,Eco,247,2,4,4,4,3,2,3,3,3,5,2,3,2,3,0,9.0,neutral or dissatisfied +16746,13527,Female,Loyal Customer,42,Business travel,Business,3645,1,1,3,1,2,3,2,5,5,5,4,1,5,1,0,12.0,satisfied +16747,29389,Female,Loyal Customer,39,Business travel,Business,2614,5,5,4,5,3,3,3,3,2,5,5,3,2,3,0,8.0,satisfied +16748,48447,Male,Loyal Customer,41,Business travel,Business,959,3,1,3,3,5,3,4,4,4,5,4,1,4,5,0,3.0,satisfied +16749,47748,Male,disloyal Customer,27,Business travel,Eco,329,1,0,1,1,5,1,5,5,3,5,3,2,4,5,9,5.0,neutral or dissatisfied +16750,90951,Male,disloyal Customer,21,Business travel,Eco,406,2,2,2,3,1,2,1,1,1,2,3,1,4,1,5,0.0,neutral or dissatisfied +16751,25140,Female,Loyal Customer,66,Personal Travel,Eco,1249,2,4,2,3,3,5,4,3,3,2,3,4,3,4,46,44.0,neutral or dissatisfied +16752,99418,Male,Loyal Customer,36,Business travel,Eco,337,5,2,4,4,5,5,5,5,5,3,2,3,3,5,0,0.0,satisfied +16753,11799,Female,Loyal Customer,40,Business travel,Business,2676,2,2,3,2,4,4,5,4,4,4,4,5,4,5,4,2.0,satisfied +16754,100025,Male,Loyal Customer,31,Business travel,Eco,289,2,2,3,3,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +16755,44171,Male,Loyal Customer,43,Personal Travel,Business,157,3,4,0,1,2,4,5,5,5,0,5,4,5,5,40,29.0,neutral or dissatisfied +16756,61177,Female,disloyal Customer,15,Business travel,Business,967,5,0,5,2,2,5,2,2,5,3,5,5,4,2,1,11.0,satisfied +16757,50679,Male,Loyal Customer,67,Personal Travel,Eco,77,3,5,0,2,4,0,4,4,5,2,4,4,5,4,106,102.0,neutral or dissatisfied +16758,83745,Female,Loyal Customer,39,Business travel,Eco,1183,2,1,3,1,2,2,2,2,4,1,3,4,4,2,4,0.0,neutral or dissatisfied +16759,75724,Female,Loyal Customer,23,Business travel,Eco,868,2,2,2,2,2,2,4,2,2,5,3,1,3,2,2,12.0,neutral or dissatisfied +16760,84366,Female,Loyal Customer,11,Business travel,Eco,591,3,3,3,3,3,3,3,3,4,1,3,1,3,3,21,31.0,neutral or dissatisfied +16761,103713,Male,Loyal Customer,53,Personal Travel,Eco,405,4,4,2,2,2,2,2,2,5,3,4,5,4,2,1,0.0,satisfied +16762,63409,Female,Loyal Customer,46,Personal Travel,Eco,447,5,4,5,3,3,4,5,5,5,5,5,1,5,1,0,0.0,satisfied +16763,110121,Female,Loyal Customer,57,Business travel,Business,1072,1,1,1,1,2,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +16764,2301,Male,disloyal Customer,21,Business travel,Eco,690,3,2,2,4,4,2,4,4,1,3,4,1,4,4,0,0.0,neutral or dissatisfied +16765,28366,Female,Loyal Customer,36,Business travel,Eco,763,4,4,4,4,4,4,4,4,2,3,2,3,2,4,0,0.0,satisfied +16766,125684,Female,disloyal Customer,23,Business travel,Eco,857,3,3,3,4,5,3,5,5,2,3,3,3,4,5,0,0.0,neutral or dissatisfied +16767,83758,Male,Loyal Customer,57,Personal Travel,Eco Plus,1183,5,4,5,3,1,5,1,1,5,3,4,3,4,1,0,0.0,satisfied +16768,120222,Female,Loyal Customer,10,Business travel,Business,1303,3,1,3,1,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +16769,102993,Male,disloyal Customer,33,Business travel,Eco,666,2,2,2,4,2,2,2,2,2,3,4,2,3,2,5,1.0,neutral or dissatisfied +16770,22799,Female,disloyal Customer,40,Business travel,Business,302,1,1,1,3,2,1,2,2,1,3,3,2,3,2,0,7.0,neutral or dissatisfied +16771,120797,Male,Loyal Customer,65,Personal Travel,Business,666,4,0,5,5,5,5,4,5,5,5,5,5,5,3,104,101.0,neutral or dissatisfied +16772,107386,Female,Loyal Customer,39,Business travel,Business,2603,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +16773,11419,Male,Loyal Customer,47,Business travel,Business,134,3,3,3,3,2,5,4,4,4,4,4,5,4,3,30,36.0,satisfied +16774,54293,Male,Loyal Customer,55,Business travel,Eco,1075,5,1,1,1,5,5,5,5,3,2,1,2,2,5,0,0.0,satisfied +16775,54675,Female,Loyal Customer,46,Business travel,Business,2155,2,2,2,2,2,1,3,4,4,5,4,4,4,4,15,8.0,satisfied +16776,5977,Female,Loyal Customer,42,Business travel,Business,1041,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +16777,96657,Female,Loyal Customer,33,Personal Travel,Eco,937,2,3,2,4,5,2,5,5,3,2,5,5,1,5,10,0.0,neutral or dissatisfied +16778,47279,Female,Loyal Customer,51,Business travel,Eco,588,4,3,3,3,2,4,4,4,4,4,4,1,4,1,0,0.0,satisfied +16779,105700,Female,Loyal Customer,51,Business travel,Business,1875,2,2,2,2,4,4,4,3,3,5,5,4,3,4,153,160.0,satisfied +16780,104530,Female,disloyal Customer,27,Business travel,Business,1047,5,5,5,4,2,5,2,2,5,4,4,4,5,2,0,0.0,satisfied +16781,77701,Male,disloyal Customer,25,Business travel,Eco,696,3,3,3,4,2,3,2,2,3,3,3,3,3,2,13,15.0,neutral or dissatisfied +16782,63399,Male,Loyal Customer,44,Personal Travel,Eco,372,2,5,2,5,4,2,3,4,3,3,3,4,5,4,0,0.0,neutral or dissatisfied +16783,50493,Male,Loyal Customer,35,Personal Travel,Eco,110,0,5,0,2,3,0,3,3,2,3,3,2,2,3,77,74.0,satisfied +16784,121822,Male,Loyal Customer,51,Business travel,Business,2107,4,4,4,4,3,5,4,4,4,5,4,4,4,5,16,9.0,satisfied +16785,87675,Male,disloyal Customer,22,Business travel,Eco,591,2,5,2,4,3,2,4,3,4,5,5,4,5,3,3,0.0,neutral or dissatisfied +16786,109558,Male,Loyal Customer,69,Personal Travel,Eco,873,3,4,3,1,3,3,3,3,4,2,5,2,2,3,7,5.0,neutral or dissatisfied +16787,5000,Male,Loyal Customer,32,Business travel,Business,3174,2,2,2,2,5,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +16788,95673,Male,Loyal Customer,29,Personal Travel,Eco Plus,1131,1,3,1,4,1,1,1,4,1,2,3,1,1,1,181,168.0,neutral or dissatisfied +16789,50657,Female,Loyal Customer,32,Personal Travel,Eco,308,2,4,4,1,2,4,2,2,5,2,5,5,5,2,26,40.0,neutral or dissatisfied +16790,105733,Female,Loyal Customer,40,Business travel,Business,842,5,5,5,5,3,5,5,2,2,2,2,3,2,5,8,0.0,satisfied +16791,12532,Female,disloyal Customer,20,Business travel,Eco,871,2,2,2,3,4,2,4,4,4,1,1,1,2,4,0,0.0,neutral or dissatisfied +16792,37104,Male,Loyal Customer,29,Business travel,Business,1063,2,1,1,1,2,2,2,2,1,5,3,4,1,2,4,0.0,neutral or dissatisfied +16793,30380,Male,Loyal Customer,57,Business travel,Business,641,3,1,3,1,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +16794,97069,Male,disloyal Customer,25,Business travel,Business,715,4,0,5,1,4,5,4,4,3,3,4,5,4,4,0,0.0,satisfied +16795,121124,Female,Loyal Customer,42,Business travel,Business,2402,3,3,3,3,5,4,4,4,5,3,4,4,5,4,0,17.0,satisfied +16796,128995,Male,disloyal Customer,27,Business travel,Eco Plus,414,2,3,3,5,2,3,2,2,1,2,3,3,1,2,0,0.0,neutral or dissatisfied +16797,53598,Female,Loyal Customer,18,Business travel,Business,3801,4,4,4,4,4,4,4,5,2,3,2,4,5,4,0,0.0,satisfied +16798,38243,Female,Loyal Customer,44,Business travel,Business,1050,5,5,3,5,5,3,2,5,5,5,5,3,5,1,37,19.0,satisfied +16799,30829,Female,disloyal Customer,30,Business travel,Eco,955,2,2,2,4,4,2,4,4,4,1,4,4,3,4,5,5.0,neutral or dissatisfied +16800,60342,Female,disloyal Customer,22,Business travel,Eco,1024,2,2,2,2,3,2,3,3,2,1,3,1,1,3,2,0.0,neutral or dissatisfied +16801,37845,Female,disloyal Customer,39,Business travel,Business,937,1,1,1,3,3,1,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +16802,29168,Female,Loyal Customer,30,Business travel,Eco Plus,679,2,3,3,3,2,2,2,2,1,2,3,4,3,2,0,6.0,neutral or dissatisfied +16803,113611,Male,Loyal Customer,64,Personal Travel,Eco,236,4,4,0,2,5,0,5,5,5,2,1,5,3,5,2,0.0,satisfied +16804,72349,Female,disloyal Customer,80,Business travel,Business,585,3,3,3,3,4,4,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +16805,21106,Male,Loyal Customer,34,Personal Travel,Eco,106,3,4,0,5,4,0,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +16806,58540,Male,disloyal Customer,23,Business travel,Business,1514,0,3,0,4,3,0,3,3,4,3,5,5,4,3,0,0.0,satisfied +16807,29208,Female,Loyal Customer,44,Business travel,Business,2311,5,5,5,5,1,4,5,4,4,4,4,1,4,2,0,0.0,satisfied +16808,34118,Male,disloyal Customer,27,Business travel,Business,1179,3,3,3,3,5,3,5,5,1,2,4,2,2,5,0,0.0,neutral or dissatisfied +16809,24547,Male,Loyal Customer,31,Business travel,Business,696,3,2,2,2,3,3,3,3,4,2,3,3,4,3,5,12.0,neutral or dissatisfied +16810,60007,Male,Loyal Customer,37,Personal Travel,Eco,937,2,5,1,3,4,1,4,4,4,5,4,5,5,4,25,11.0,neutral or dissatisfied +16811,25661,Male,Loyal Customer,29,Business travel,Business,2889,5,5,5,5,5,5,5,5,5,4,3,5,4,5,3,0.0,satisfied +16812,89085,Female,disloyal Customer,21,Business travel,Business,1947,0,3,0,4,2,3,2,2,5,4,5,4,4,2,0,0.0,satisfied +16813,21994,Male,Loyal Customer,8,Personal Travel,Eco,500,3,4,3,5,3,3,3,3,5,5,3,4,4,3,45,29.0,neutral or dissatisfied +16814,79932,Female,Loyal Customer,56,Business travel,Eco,1010,4,4,4,4,1,4,4,4,4,4,4,2,4,2,0,7.0,neutral or dissatisfied +16815,88531,Male,Loyal Customer,35,Personal Travel,Eco,594,3,4,3,4,5,3,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +16816,69742,Female,Loyal Customer,58,Business travel,Business,2773,1,1,1,1,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +16817,70983,Male,Loyal Customer,40,Business travel,Business,802,5,5,2,5,2,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +16818,25457,Female,Loyal Customer,31,Personal Travel,Eco,669,2,2,2,2,4,2,2,4,2,5,2,1,2,4,0,0.0,neutral or dissatisfied +16819,49439,Male,Loyal Customer,57,Business travel,Eco,209,5,1,3,1,4,5,4,4,4,1,4,1,2,4,0,0.0,satisfied +16820,6524,Female,Loyal Customer,19,Personal Travel,Eco,599,2,3,2,3,3,2,4,3,4,2,3,1,2,3,0,0.0,neutral or dissatisfied +16821,66411,Female,Loyal Customer,17,Business travel,Business,1562,1,1,1,1,1,2,1,1,2,3,4,4,4,1,0,0.0,neutral or dissatisfied +16822,65693,Female,Loyal Customer,39,Business travel,Business,936,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +16823,113288,Male,disloyal Customer,23,Business travel,Business,391,4,5,4,4,5,4,5,5,4,4,5,5,4,5,6,0.0,satisfied +16824,67399,Female,Loyal Customer,58,Business travel,Business,641,3,4,4,4,3,3,3,3,3,3,3,3,3,2,2,19.0,neutral or dissatisfied +16825,49904,Male,Loyal Customer,40,Business travel,Business,1843,4,4,2,4,4,5,2,5,5,5,4,3,5,2,0,0.0,satisfied +16826,51626,Male,Loyal Customer,72,Business travel,Eco,493,5,1,4,1,5,5,5,5,3,1,1,1,2,5,0,0.0,satisfied +16827,66475,Male,Loyal Customer,51,Business travel,Business,447,2,2,5,2,2,5,4,4,4,4,4,3,4,4,34,22.0,satisfied +16828,97099,Male,disloyal Customer,39,Business travel,Eco,1357,2,2,2,2,1,2,1,1,4,4,3,1,2,1,0,23.0,neutral or dissatisfied +16829,29615,Male,Loyal Customer,46,Business travel,Eco,1448,2,2,4,2,2,2,2,2,2,4,3,3,3,2,0,13.0,neutral or dissatisfied +16830,45869,Female,Loyal Customer,24,Business travel,Business,3851,1,1,1,1,4,4,4,4,5,3,5,2,2,4,0,3.0,satisfied +16831,124664,Male,disloyal Customer,37,Business travel,Business,399,4,4,4,2,5,4,5,5,5,4,5,5,5,5,46,49.0,neutral or dissatisfied +16832,40937,Male,Loyal Customer,27,Business travel,Eco Plus,599,1,4,4,4,1,1,1,1,2,4,3,2,4,1,0,0.0,neutral or dissatisfied +16833,86555,Female,Loyal Customer,51,Business travel,Business,3080,1,5,1,1,4,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +16834,30693,Female,Loyal Customer,47,Business travel,Eco,680,3,1,4,1,5,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +16835,42934,Male,disloyal Customer,36,Business travel,Business,173,3,3,3,1,5,3,4,5,4,4,4,5,5,5,14,14.0,neutral or dissatisfied +16836,110948,Male,Loyal Customer,29,Business travel,Eco Plus,581,4,3,5,3,4,4,4,4,4,3,3,4,3,4,0,6.0,neutral or dissatisfied +16837,27217,Female,Loyal Customer,68,Personal Travel,Business,1024,3,5,3,1,4,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +16838,59456,Female,disloyal Customer,24,Business travel,Eco,811,3,3,3,3,5,3,5,5,3,2,5,4,4,5,39,33.0,neutral or dissatisfied +16839,77822,Male,Loyal Customer,58,Personal Travel,Eco,1282,4,5,4,2,2,4,2,2,5,2,4,3,4,2,26,10.0,neutral or dissatisfied +16840,7491,Male,disloyal Customer,22,Business travel,Eco,925,3,3,3,4,1,3,1,1,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +16841,62032,Male,Loyal Customer,48,Business travel,Business,2586,1,1,1,1,4,5,4,5,5,5,5,4,5,4,0,3.0,satisfied +16842,9038,Female,Loyal Customer,41,Business travel,Business,3859,1,1,1,1,3,4,4,5,5,5,5,4,5,4,9,37.0,satisfied +16843,31945,Male,disloyal Customer,25,Business travel,Business,216,3,0,3,3,5,3,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +16844,109992,Male,Loyal Customer,51,Personal Travel,Eco Plus,1052,1,4,1,3,1,1,1,1,4,4,4,4,3,1,42,39.0,neutral or dissatisfied +16845,67355,Male,Loyal Customer,21,Personal Travel,Eco,1471,1,5,1,1,5,1,5,5,4,3,5,3,5,5,8,0.0,neutral or dissatisfied +16846,125366,Female,Loyal Customer,57,Personal Travel,Eco,599,2,5,2,4,1,2,2,2,2,2,2,5,2,2,0,0.0,neutral or dissatisfied +16847,41794,Male,Loyal Customer,23,Business travel,Business,1538,0,3,0,4,4,5,5,4,5,4,4,4,3,4,0,0.0,satisfied +16848,32938,Female,Loyal Customer,60,Personal Travel,Eco,101,3,4,3,3,3,4,4,3,3,3,3,3,3,5,0,2.0,neutral or dissatisfied +16849,28710,Male,Loyal Customer,27,Business travel,Eco,2554,2,5,5,5,2,2,2,2,2,3,4,2,3,2,10,0.0,neutral or dissatisfied +16850,119151,Male,Loyal Customer,60,Business travel,Business,3841,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +16851,46281,Male,Loyal Customer,55,Business travel,Eco Plus,752,5,2,2,2,5,5,5,5,3,5,2,2,2,5,0,12.0,satisfied +16852,81939,Female,Loyal Customer,23,Business travel,Business,1532,2,2,2,2,4,4,4,4,5,3,4,4,5,4,25,50.0,satisfied +16853,123454,Male,Loyal Customer,59,Business travel,Business,2296,2,2,2,2,3,4,4,2,2,3,2,4,2,3,0,0.0,satisfied +16854,96374,Female,Loyal Customer,53,Business travel,Business,1407,5,5,5,5,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +16855,14852,Male,Loyal Customer,30,Business travel,Business,1940,0,0,0,5,1,1,1,1,5,4,2,5,3,1,0,10.0,satisfied +16856,8803,Male,disloyal Customer,33,Business travel,Business,552,3,3,3,4,3,3,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +16857,110662,Male,Loyal Customer,46,Business travel,Business,2540,1,1,1,1,3,4,4,4,4,5,4,5,4,4,9,0.0,satisfied +16858,120580,Female,Loyal Customer,34,Business travel,Business,3136,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +16859,10540,Female,Loyal Customer,48,Business travel,Business,1680,0,5,0,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +16860,100644,Male,Loyal Customer,55,Personal Travel,Eco,349,1,5,1,5,3,1,3,3,5,1,2,4,3,3,0,0.0,neutral or dissatisfied +16861,72466,Male,Loyal Customer,50,Business travel,Business,3391,5,5,5,5,4,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +16862,2919,Female,Loyal Customer,49,Business travel,Business,859,1,5,5,5,1,1,1,4,4,4,4,1,2,1,178,176.0,neutral or dissatisfied +16863,65890,Female,Loyal Customer,63,Business travel,Business,3168,1,2,2,2,4,3,3,1,1,2,1,2,1,4,2,0.0,neutral or dissatisfied +16864,127810,Female,disloyal Customer,17,Business travel,Eco,1044,4,4,4,4,4,4,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +16865,49039,Female,disloyal Customer,28,Business travel,Eco,363,1,3,1,4,5,1,5,5,5,1,2,1,4,5,14,20.0,neutral or dissatisfied +16866,53852,Male,Loyal Customer,15,Business travel,Business,3949,4,1,2,1,3,2,4,3,1,1,3,2,4,3,10,1.0,neutral or dissatisfied +16867,47428,Female,Loyal Customer,43,Business travel,Eco,574,1,3,3,3,5,3,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +16868,57982,Female,Loyal Customer,27,Business travel,Business,589,1,4,4,4,1,1,1,4,5,4,4,1,4,1,181,161.0,neutral or dissatisfied +16869,17890,Female,Loyal Customer,56,Business travel,Eco Plus,201,4,1,1,1,4,1,2,4,4,4,4,1,4,2,104,95.0,satisfied +16870,64028,Female,Loyal Customer,38,Business travel,Business,3392,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +16871,23229,Male,Loyal Customer,42,Business travel,Eco,116,5,5,5,5,5,5,5,5,3,3,4,5,3,5,42,30.0,satisfied +16872,88204,Female,Loyal Customer,44,Business travel,Business,581,4,4,4,4,5,5,4,4,4,4,4,3,4,3,50,58.0,satisfied +16873,115663,Female,Loyal Customer,38,Business travel,Eco,390,2,4,4,4,2,2,2,2,3,1,4,2,3,2,18,12.0,neutral or dissatisfied +16874,41041,Male,Loyal Customer,69,Business travel,Eco,1086,3,5,5,5,3,3,3,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +16875,19982,Female,disloyal Customer,15,Business travel,Eco,599,4,4,4,1,3,4,3,3,2,4,4,3,3,3,6,21.0,neutral or dissatisfied +16876,91543,Female,disloyal Customer,42,Business travel,Eco,680,3,3,3,2,3,3,4,3,2,5,2,4,1,3,67,86.0,neutral or dissatisfied +16877,15764,Male,disloyal Customer,26,Business travel,Eco,292,2,0,2,4,3,2,3,3,1,3,2,2,4,3,6,6.0,neutral or dissatisfied +16878,35239,Female,Loyal Customer,36,Business travel,Business,944,5,5,5,5,1,5,5,1,1,2,1,3,1,2,0,4.0,satisfied +16879,24413,Male,Loyal Customer,7,Business travel,Eco,634,3,5,5,5,3,3,2,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +16880,42499,Male,Loyal Customer,56,Business travel,Eco,541,4,5,5,5,4,4,4,4,3,4,4,4,1,4,0,0.0,satisfied +16881,34036,Male,Loyal Customer,18,Personal Travel,Eco Plus,1576,4,5,4,3,4,4,4,4,4,5,5,3,4,4,55,,satisfied +16882,51758,Male,Loyal Customer,9,Personal Travel,Eco,509,1,4,4,2,1,4,5,1,4,5,5,3,5,1,1,0.0,neutral or dissatisfied +16883,59885,Male,Loyal Customer,42,Business travel,Business,3293,3,3,3,3,4,4,5,5,5,4,5,5,5,4,0,30.0,satisfied +16884,80348,Female,disloyal Customer,37,Business travel,Business,368,3,3,3,4,2,3,2,2,3,5,3,4,3,2,2,0.0,neutral or dissatisfied +16885,77836,Female,Loyal Customer,18,Personal Travel,Eco,731,4,4,4,4,1,4,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +16886,91756,Female,Loyal Customer,45,Business travel,Eco,584,2,4,2,4,4,4,3,2,2,2,2,2,2,3,0,14.0,neutral or dissatisfied +16887,74516,Male,Loyal Customer,36,Business travel,Business,1431,2,1,1,1,3,4,4,2,2,3,2,1,2,1,91,86.0,neutral or dissatisfied +16888,128564,Female,Loyal Customer,34,Personal Travel,Eco Plus,338,2,4,2,4,1,2,1,1,1,2,4,4,4,1,0,2.0,neutral or dissatisfied +16889,121554,Male,Loyal Customer,42,Business travel,Business,3648,5,5,5,5,2,4,5,4,4,4,4,3,4,4,4,3.0,satisfied +16890,28774,Female,Loyal Customer,52,Business travel,Business,954,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +16891,7075,Female,Loyal Customer,37,Business travel,Business,273,4,4,4,4,3,4,5,5,5,5,5,5,5,4,1,4.0,satisfied +16892,108046,Male,Loyal Customer,39,Business travel,Business,591,1,1,1,1,5,4,5,5,5,5,5,5,5,4,22,16.0,satisfied +16893,51967,Male,disloyal Customer,11,Business travel,Eco,843,2,2,2,4,5,2,5,5,1,3,3,3,4,5,37,37.0,neutral or dissatisfied +16894,72710,Female,Loyal Customer,26,Business travel,Business,1121,1,1,1,1,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +16895,39918,Male,Loyal Customer,48,Business travel,Eco,1086,5,1,1,1,5,5,5,5,4,5,1,3,1,5,0,3.0,satisfied +16896,44824,Male,Loyal Customer,58,Business travel,Business,3011,2,2,2,2,1,5,3,2,2,2,2,4,2,4,12,20.0,satisfied +16897,56440,Male,disloyal Customer,24,Business travel,Eco,719,5,5,5,5,2,5,2,2,5,2,4,2,1,2,0,0.0,satisfied +16898,48405,Female,disloyal Customer,24,Business travel,Eco,846,2,2,2,1,1,2,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +16899,95775,Male,Loyal Customer,38,Personal Travel,Eco,419,1,3,4,2,2,4,2,2,5,4,1,5,5,2,21,15.0,neutral or dissatisfied +16900,40795,Female,disloyal Customer,36,Business travel,Eco,588,3,0,3,4,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +16901,47600,Male,Loyal Customer,50,Business travel,Business,1504,2,2,4,2,3,1,4,5,5,5,5,2,5,4,0,0.0,satisfied +16902,78243,Female,Loyal Customer,41,Business travel,Business,1586,0,5,0,2,3,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +16903,60997,Female,Loyal Customer,52,Business travel,Business,2336,4,4,4,4,5,5,5,5,5,5,5,3,5,3,15,9.0,satisfied +16904,116076,Male,Loyal Customer,25,Personal Travel,Eco,296,2,3,2,3,4,2,4,4,5,1,1,5,2,4,0,0.0,neutral or dissatisfied +16905,95083,Male,Loyal Customer,42,Personal Travel,Eco,248,3,5,3,2,1,3,1,1,4,3,5,4,4,1,9,4.0,neutral or dissatisfied +16906,20399,Female,Loyal Customer,59,Personal Travel,Eco,588,3,5,3,3,2,5,4,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +16907,70262,Female,disloyal Customer,27,Business travel,Business,852,0,0,0,1,2,0,2,2,4,2,4,5,5,2,32,12.0,satisfied +16908,69827,Female,Loyal Customer,43,Business travel,Business,3518,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +16909,120858,Male,Loyal Customer,34,Business travel,Business,1732,2,2,2,2,2,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +16910,17530,Female,Loyal Customer,17,Personal Travel,Eco Plus,352,2,5,2,4,3,2,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +16911,128504,Female,Loyal Customer,21,Personal Travel,Eco,304,2,4,2,2,2,2,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +16912,49800,Male,disloyal Customer,39,Business travel,Eco,421,2,3,2,3,4,2,4,4,1,3,1,4,3,4,0,0.0,neutral or dissatisfied +16913,73657,Male,Loyal Customer,60,Business travel,Business,192,0,4,0,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +16914,80033,Female,Loyal Customer,13,Personal Travel,Eco,1080,2,4,2,5,5,2,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +16915,95828,Male,Loyal Customer,30,Personal Travel,Eco,1428,2,2,2,4,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +16916,125666,Male,disloyal Customer,48,Business travel,Business,892,3,3,3,2,3,3,3,3,5,5,4,5,5,3,0,1.0,neutral or dissatisfied +16917,65177,Male,Loyal Customer,59,Personal Travel,Eco,282,1,5,1,4,5,1,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +16918,65250,Male,disloyal Customer,20,Business travel,Eco,190,2,5,2,1,2,2,1,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +16919,20726,Female,Loyal Customer,33,Personal Travel,Eco,707,3,3,2,2,2,3,3,1,5,4,3,3,1,3,151,155.0,neutral or dissatisfied +16920,75743,Male,Loyal Customer,46,Business travel,Business,2916,2,4,4,4,2,2,2,1,3,2,1,2,3,2,185,172.0,neutral or dissatisfied +16921,113388,Male,Loyal Customer,59,Business travel,Business,2908,4,1,4,4,4,4,5,5,5,5,5,5,5,5,31,27.0,satisfied +16922,16564,Male,Loyal Customer,10,Business travel,Business,3692,1,3,3,3,1,1,1,1,2,4,4,4,3,1,9,30.0,neutral or dissatisfied +16923,110584,Male,Loyal Customer,42,Business travel,Eco,151,4,3,2,3,4,4,4,4,4,1,1,3,2,4,0,0.0,satisfied +16924,69020,Female,Loyal Customer,34,Business travel,Business,1389,2,2,3,2,2,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +16925,82962,Female,Loyal Customer,45,Business travel,Business,3592,2,2,2,2,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +16926,76551,Female,Loyal Customer,39,Business travel,Business,516,4,4,4,4,3,5,4,4,4,4,4,4,4,3,9,12.0,satisfied +16927,103845,Male,Loyal Customer,13,Business travel,Business,882,5,5,5,5,3,4,3,3,4,3,4,4,5,3,0,5.0,satisfied +16928,111249,Male,disloyal Customer,42,Business travel,Business,1849,4,4,4,1,5,4,4,5,4,4,5,4,4,5,0,0.0,satisfied +16929,77977,Male,Loyal Customer,54,Business travel,Business,227,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,5.0,satisfied +16930,117528,Female,Loyal Customer,62,Personal Travel,Business,347,3,5,3,2,3,4,4,2,2,3,5,4,2,5,0,0.0,neutral or dissatisfied +16931,117989,Female,Loyal Customer,55,Business travel,Business,1730,4,4,4,4,5,4,4,5,2,4,5,4,3,4,132,124.0,satisfied +16932,5863,Male,Loyal Customer,44,Personal Travel,Eco,1020,1,4,1,4,2,1,2,2,5,4,2,5,3,2,0,0.0,neutral or dissatisfied +16933,64635,Female,Loyal Customer,51,Business travel,Business,247,0,1,1,1,2,4,4,4,4,4,4,5,4,4,0,2.0,satisfied +16934,91180,Female,Loyal Customer,30,Personal Travel,Eco,581,3,5,3,1,4,3,4,4,4,5,5,5,5,4,30,25.0,neutral or dissatisfied +16935,100444,Male,Loyal Customer,39,Business travel,Business,1900,4,4,4,4,4,4,5,4,4,4,4,4,4,3,17,1.0,satisfied +16936,22742,Male,Loyal Customer,44,Business travel,Eco,147,4,4,4,4,4,4,4,4,3,1,5,5,3,4,37,47.0,satisfied +16937,6010,Male,Loyal Customer,45,Business travel,Business,1795,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,10.0,satisfied +16938,110524,Male,Loyal Customer,60,Business travel,Business,2253,4,4,4,4,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +16939,66154,Female,Loyal Customer,61,Personal Travel,Business,550,3,0,3,2,5,5,5,1,1,3,1,5,1,3,0,51.0,neutral or dissatisfied +16940,67316,Male,Loyal Customer,60,Personal Travel,Eco Plus,918,1,4,1,1,4,1,4,4,4,4,4,3,4,4,3,5.0,neutral or dissatisfied +16941,38749,Male,disloyal Customer,34,Business travel,Business,354,3,3,3,3,2,3,2,2,5,5,3,2,2,2,0,0.0,neutral or dissatisfied +16942,4689,Male,Loyal Customer,8,Personal Travel,Eco,364,3,1,5,3,1,5,1,1,1,1,4,1,4,1,4,0.0,neutral or dissatisfied +16943,10363,Female,Loyal Customer,40,Business travel,Business,3050,3,3,3,3,3,4,5,4,4,4,4,4,4,3,68,80.0,satisfied +16944,38124,Female,disloyal Customer,38,Business travel,Eco,785,1,2,2,3,4,2,4,4,4,1,4,1,3,4,0,18.0,neutral or dissatisfied +16945,31319,Male,Loyal Customer,43,Personal Travel,Eco,680,2,5,2,3,4,2,4,4,5,4,4,4,5,4,55,69.0,neutral or dissatisfied +16946,115790,Male,Loyal Customer,58,Business travel,Business,446,1,1,5,1,5,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +16947,6871,Male,Loyal Customer,29,Personal Travel,Eco,622,3,4,3,5,4,3,4,4,5,4,5,5,5,4,61,48.0,neutral or dissatisfied +16948,124662,Female,Loyal Customer,52,Business travel,Business,2810,1,1,1,1,5,4,5,5,5,5,5,5,5,4,5,12.0,satisfied +16949,1651,Female,Loyal Customer,57,Business travel,Eco,435,1,4,4,4,3,1,2,1,1,1,1,1,1,1,4,36.0,neutral or dissatisfied +16950,31211,Male,Loyal Customer,58,Business travel,Eco,228,4,1,1,1,4,4,4,4,1,2,3,2,3,4,0,1.0,satisfied +16951,14656,Male,Loyal Customer,58,Business travel,Business,2575,2,1,1,1,5,2,2,2,2,2,2,4,2,4,36,32.0,neutral or dissatisfied +16952,16243,Female,Loyal Customer,44,Business travel,Eco,748,4,2,2,2,3,2,4,4,4,4,4,1,4,2,0,0.0,satisfied +16953,52345,Female,Loyal Customer,64,Business travel,Eco,109,4,2,2,2,5,3,5,4,4,4,4,3,4,4,33,52.0,satisfied +16954,120936,Female,Loyal Customer,72,Business travel,Business,920,4,1,1,1,1,2,2,4,4,4,4,2,4,4,0,53.0,neutral or dissatisfied +16955,22484,Female,Loyal Customer,27,Personal Travel,Eco,145,2,5,0,1,5,0,5,5,3,4,4,5,5,5,0,14.0,neutral or dissatisfied +16956,3723,Female,Loyal Customer,41,Personal Travel,Eco,544,1,5,2,1,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +16957,101019,Male,disloyal Customer,20,Business travel,Eco,467,4,4,4,2,5,4,2,5,1,5,3,3,3,5,16,9.0,satisfied +16958,15615,Male,Loyal Customer,22,Personal Travel,Eco,296,2,3,2,2,2,2,2,2,4,3,2,4,3,2,95,85.0,neutral or dissatisfied +16959,698,Male,Loyal Customer,18,Business travel,Business,2301,3,4,2,2,0,1,3,0,3,2,4,3,3,0,33,35.0,neutral or dissatisfied +16960,83904,Female,Loyal Customer,52,Business travel,Business,2338,1,1,1,1,4,4,4,1,1,1,1,3,1,2,30,26.0,neutral or dissatisfied +16961,66926,Male,Loyal Customer,59,Business travel,Business,3892,4,4,5,4,2,5,5,5,5,5,5,4,5,5,0,33.0,satisfied +16962,32343,Female,disloyal Customer,39,Business travel,Business,216,4,5,5,3,4,5,4,4,1,5,4,1,2,4,0,0.0,satisfied +16963,6457,Male,Loyal Customer,57,Business travel,Business,2456,2,2,2,2,4,5,5,5,5,5,5,3,5,4,27,31.0,satisfied +16964,47571,Male,Loyal Customer,24,Personal Travel,Eco Plus,574,2,5,3,3,5,3,4,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +16965,116517,Male,Loyal Customer,43,Personal Travel,Eco,371,1,5,1,1,3,1,3,3,3,3,5,3,4,3,3,2.0,neutral or dissatisfied +16966,56588,Male,Loyal Customer,45,Business travel,Business,2233,5,5,4,5,4,4,4,5,5,5,5,5,5,3,12,0.0,satisfied +16967,109746,Male,Loyal Customer,26,Personal Travel,Eco,468,4,4,4,4,4,4,4,4,4,2,4,3,4,4,0,18.0,neutral or dissatisfied +16968,102883,Female,Loyal Customer,40,Business travel,Business,3038,5,5,5,5,5,5,5,4,4,4,4,4,4,3,12,5.0,satisfied +16969,69538,Female,Loyal Customer,40,Business travel,Business,2475,3,3,3,3,4,5,5,3,4,4,5,5,3,5,5,0.0,satisfied +16970,47747,Female,Loyal Customer,35,Business travel,Business,2605,5,5,4,5,2,5,5,5,5,5,5,4,5,5,10,0.0,satisfied +16971,102409,Male,Loyal Customer,10,Personal Travel,Eco,236,1,3,1,2,5,1,3,5,5,4,1,3,3,5,92,100.0,neutral or dissatisfied +16972,46675,Male,Loyal Customer,51,Personal Travel,Eco,125,2,4,2,3,3,2,3,3,3,1,3,3,3,3,0,3.0,neutral or dissatisfied +16973,119665,Male,Loyal Customer,21,Personal Travel,Eco,507,3,2,3,3,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +16974,27280,Female,Loyal Customer,35,Personal Travel,Business,956,2,4,2,3,2,4,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +16975,104270,Female,Loyal Customer,26,Business travel,Business,1733,2,2,3,2,4,4,4,4,4,4,3,3,5,4,0,0.0,satisfied +16976,84878,Male,Loyal Customer,51,Personal Travel,Eco,547,2,0,3,1,3,3,2,3,5,2,5,4,5,3,7,3.0,neutral or dissatisfied +16977,41805,Female,Loyal Customer,24,Business travel,Eco,489,0,4,1,1,4,1,4,4,4,2,2,3,2,4,0,0.0,satisfied +16978,101913,Female,Loyal Customer,20,Personal Travel,Eco,1984,4,2,4,3,3,4,1,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +16979,23902,Male,Loyal Customer,58,Business travel,Business,1888,2,2,2,2,2,3,1,3,3,3,3,3,3,3,0,0.0,satisfied +16980,39751,Female,Loyal Customer,62,Personal Travel,Eco Plus,1174,3,5,4,1,3,4,4,3,3,4,3,5,3,5,0,0.0,neutral or dissatisfied +16981,77006,Male,Loyal Customer,47,Business travel,Business,2634,1,1,2,1,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +16982,1343,Female,disloyal Customer,45,Business travel,Business,309,2,1,1,2,4,2,4,4,5,3,4,5,4,4,3,1.0,neutral or dissatisfied +16983,24014,Female,disloyal Customer,27,Business travel,Eco,562,4,1,5,2,1,5,1,1,1,4,2,2,3,1,0,0.0,neutral or dissatisfied +16984,105592,Female,Loyal Customer,64,Personal Travel,Eco Plus,577,4,5,4,5,2,5,5,4,4,4,4,5,4,4,1,0.0,neutral or dissatisfied +16985,19725,Female,Loyal Customer,49,Personal Travel,Eco,491,3,4,3,3,4,4,5,3,3,3,3,5,3,3,4,8.0,neutral or dissatisfied +16986,47726,Female,Loyal Customer,49,Business travel,Business,2228,4,4,4,4,5,5,4,2,2,2,2,5,2,3,23,26.0,satisfied +16987,61296,Male,Loyal Customer,27,Personal Travel,Eco,967,3,4,2,2,4,2,1,4,3,5,5,4,4,4,30,13.0,neutral or dissatisfied +16988,83219,Female,Loyal Customer,43,Personal Travel,Business,1979,1,0,1,2,4,4,4,5,5,1,5,5,5,4,0,0.0,neutral or dissatisfied +16989,80626,Female,Loyal Customer,69,Personal Travel,Eco Plus,236,4,4,4,4,2,4,4,3,3,4,2,2,3,4,0,0.0,neutral or dissatisfied +16990,41697,Male,Loyal Customer,16,Personal Travel,Eco,347,1,4,4,3,5,4,5,5,3,3,5,4,4,5,0,10.0,neutral or dissatisfied +16991,53545,Male,Loyal Customer,63,Personal Travel,Eco Plus,2419,1,4,1,3,1,3,3,1,4,4,3,3,4,3,0,23.0,neutral or dissatisfied +16992,85828,Female,Loyal Customer,10,Personal Travel,Eco,666,3,0,3,3,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +16993,50639,Female,Loyal Customer,65,Personal Travel,Eco,421,3,2,3,4,2,4,4,5,5,3,5,2,5,3,88,88.0,neutral or dissatisfied +16994,120764,Male,Loyal Customer,46,Business travel,Business,2888,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +16995,37972,Male,Loyal Customer,54,Business travel,Business,2668,2,2,2,2,2,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +16996,43743,Male,Loyal Customer,26,Personal Travel,Eco,626,3,5,3,4,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +16997,79599,Male,disloyal Customer,29,Business travel,Eco,762,2,2,2,3,5,2,3,5,4,3,4,1,4,5,69,43.0,neutral or dissatisfied +16998,89913,Female,disloyal Customer,25,Business travel,Business,1416,2,0,2,2,3,2,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +16999,84915,Female,Loyal Customer,7,Personal Travel,Eco,547,4,4,4,4,3,4,3,3,4,4,3,4,4,3,7,0.0,neutral or dissatisfied +17000,111235,Female,Loyal Customer,19,Personal Travel,Eco,1703,1,1,1,3,4,1,4,4,2,3,3,3,2,4,14,19.0,neutral or dissatisfied +17001,16213,Male,Loyal Customer,30,Business travel,Eco Plus,277,2,2,2,2,2,2,2,2,2,1,4,1,3,2,52,47.0,neutral or dissatisfied +17002,29221,Male,Loyal Customer,22,Business travel,Business,859,5,5,5,5,5,5,5,5,4,4,5,5,5,5,11,0.0,satisfied +17003,35770,Female,Loyal Customer,37,Business travel,Eco,200,3,1,5,1,3,3,3,3,4,1,4,3,4,3,22,19.0,neutral or dissatisfied +17004,119207,Male,disloyal Customer,40,Business travel,Eco,290,2,0,2,4,5,2,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +17005,17493,Male,Loyal Customer,51,Business travel,Eco,352,2,2,2,2,2,2,2,2,3,5,2,2,2,2,17,12.0,neutral or dissatisfied +17006,41861,Female,Loyal Customer,20,Business travel,Business,2455,3,4,4,4,3,3,3,3,3,1,4,2,3,3,0,0.0,neutral or dissatisfied +17007,45023,Female,disloyal Customer,40,Business travel,Business,222,2,2,2,3,5,2,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +17008,45948,Male,Loyal Customer,56,Personal Travel,Eco,563,4,4,4,1,3,4,3,3,5,4,4,4,4,3,0,0.0,neutral or dissatisfied +17009,120612,Female,Loyal Customer,60,Business travel,Business,1533,3,2,2,2,2,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +17010,62606,Female,Loyal Customer,56,Personal Travel,Eco,1846,2,2,2,3,1,2,3,5,5,2,5,1,5,1,24,26.0,neutral or dissatisfied +17011,19904,Male,disloyal Customer,30,Business travel,Eco,296,4,4,4,2,3,4,3,3,5,3,1,2,2,3,47,53.0,neutral or dissatisfied +17012,100112,Female,Loyal Customer,50,Business travel,Business,2871,3,3,3,3,5,5,5,3,5,4,5,5,5,5,160,148.0,satisfied +17013,120731,Male,Loyal Customer,42,Business travel,Business,1089,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +17014,17638,Male,Loyal Customer,39,Business travel,Business,1930,3,3,3,3,4,4,5,5,5,5,5,4,5,3,55,47.0,satisfied +17015,78050,Female,Loyal Customer,25,Personal Travel,Eco,332,4,3,5,3,3,5,2,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +17016,63075,Male,Loyal Customer,48,Personal Travel,Eco,862,3,5,3,2,4,3,2,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +17017,27870,Female,Loyal Customer,23,Business travel,Eco Plus,1448,4,4,4,4,4,4,3,4,2,1,1,1,4,4,0,0.0,satisfied +17018,100564,Female,Loyal Customer,10,Personal Travel,Business,486,3,0,3,3,1,3,1,1,5,5,5,5,5,1,24,17.0,neutral or dissatisfied +17019,53697,Female,Loyal Customer,29,Business travel,Eco,1208,1,3,3,3,1,1,1,1,3,4,3,3,3,1,6,11.0,neutral or dissatisfied +17020,107448,Female,Loyal Customer,38,Personal Travel,Eco,468,2,2,2,4,3,2,3,3,3,1,4,1,3,3,4,2.0,neutral or dissatisfied +17021,109388,Female,Loyal Customer,62,Personal Travel,Eco,1046,2,4,2,3,3,4,5,2,2,2,2,3,2,5,27,37.0,neutral or dissatisfied +17022,103076,Male,Loyal Customer,58,Personal Travel,Eco,687,4,4,4,5,2,4,2,2,3,3,4,3,5,2,74,77.0,neutral or dissatisfied +17023,76153,Male,Loyal Customer,47,Business travel,Business,2292,3,5,5,5,4,3,4,3,3,3,3,3,3,4,2,0.0,neutral or dissatisfied +17024,48614,Female,Loyal Customer,45,Business travel,Eco Plus,844,4,5,5,5,3,5,5,4,4,4,4,1,4,2,0,0.0,satisfied +17025,19710,Female,Loyal Customer,80,Business travel,Business,475,3,4,4,4,3,4,4,3,3,3,3,2,3,4,2,0.0,neutral or dissatisfied +17026,7919,Female,Loyal Customer,55,Personal Travel,Eco,1020,1,3,1,3,3,3,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +17027,63505,Male,Loyal Customer,27,Personal Travel,Eco,1956,1,1,1,4,1,1,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +17028,31947,Female,Loyal Customer,43,Business travel,Business,101,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +17029,40268,Female,Loyal Customer,24,Personal Travel,Eco,402,1,4,1,3,1,1,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +17030,3304,Male,Loyal Customer,46,Personal Travel,Eco Plus,483,3,0,3,2,5,3,1,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +17031,24928,Male,Loyal Customer,45,Personal Travel,Eco,762,2,5,2,1,3,2,2,3,5,5,5,5,4,3,108,90.0,neutral or dissatisfied +17032,5380,Male,Loyal Customer,21,Personal Travel,Eco,733,4,4,4,1,4,4,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +17033,74352,Female,Loyal Customer,42,Business travel,Business,3188,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +17034,40081,Male,Loyal Customer,38,Personal Travel,Eco,493,3,5,3,3,3,3,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +17035,59428,Male,Loyal Customer,31,Business travel,Eco Plus,2399,3,1,1,1,3,4,3,3,4,4,2,2,3,3,0,0.0,neutral or dissatisfied +17036,74436,Female,Loyal Customer,53,Business travel,Business,1464,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +17037,69477,Female,Loyal Customer,47,Personal Travel,Eco,1035,5,5,5,3,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +17038,62284,Female,disloyal Customer,36,Business travel,Business,236,2,2,2,2,4,2,4,4,5,3,5,3,5,4,1,0.0,neutral or dissatisfied +17039,56543,Female,Loyal Customer,40,Business travel,Business,937,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,6.0,satisfied +17040,97613,Female,disloyal Customer,22,Business travel,Business,764,5,0,5,3,5,5,5,5,3,5,5,3,4,5,11,0.0,satisfied +17041,93156,Female,Loyal Customer,45,Business travel,Eco,1066,3,4,4,4,1,3,4,3,3,3,3,3,3,4,19,15.0,neutral or dissatisfied +17042,95550,Male,Loyal Customer,67,Personal Travel,Eco Plus,189,1,5,1,2,4,1,4,4,4,5,5,4,4,4,3,2.0,neutral or dissatisfied +17043,13577,Female,Loyal Customer,44,Personal Travel,Eco,106,3,4,3,5,2,4,4,4,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +17044,126944,Female,disloyal Customer,24,Business travel,Eco,338,3,0,3,1,5,3,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +17045,62787,Female,Loyal Customer,51,Personal Travel,Eco,2556,2,4,2,4,2,2,2,3,2,4,2,2,1,2,170,165.0,neutral or dissatisfied +17046,30770,Female,Loyal Customer,29,Business travel,Business,895,2,2,2,2,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +17047,121977,Female,disloyal Customer,21,Business travel,Eco,130,3,5,3,4,1,3,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +17048,123827,Female,Loyal Customer,50,Business travel,Business,544,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +17049,7180,Male,Loyal Customer,54,Business travel,Business,135,0,5,0,4,2,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +17050,51322,Female,Loyal Customer,65,Business travel,Eco Plus,373,2,5,5,5,3,3,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +17051,60807,Male,Loyal Customer,30,Business travel,Business,455,5,5,5,5,4,4,4,4,4,5,5,3,5,4,0,1.0,satisfied +17052,46184,Female,Loyal Customer,33,Business travel,Business,3850,2,2,2,2,3,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +17053,20172,Male,Loyal Customer,61,Personal Travel,Eco,258,2,1,2,2,4,2,2,4,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +17054,5566,Female,Loyal Customer,44,Personal Travel,Eco,501,4,5,4,3,4,4,3,4,5,4,4,3,3,3,147,187.0,satisfied +17055,27190,Female,Loyal Customer,34,Business travel,Eco Plus,2640,5,5,4,4,5,5,5,2,4,5,5,5,2,5,0,0.0,satisfied +17056,25777,Male,Loyal Customer,52,Business travel,Eco,762,5,1,1,1,5,5,5,5,5,1,5,2,2,5,0,0.0,satisfied +17057,24756,Female,Loyal Customer,53,Business travel,Eco,432,5,2,2,2,3,5,1,5,5,5,5,5,5,1,0,0.0,satisfied +17058,14821,Female,Loyal Customer,37,Business travel,Eco,163,5,1,1,1,5,5,5,5,1,3,3,2,2,5,7,0.0,satisfied +17059,55072,Female,Loyal Customer,18,Business travel,Business,1379,2,5,5,5,2,2,2,2,3,5,3,1,4,2,37,22.0,neutral or dissatisfied +17060,58118,Female,Loyal Customer,36,Personal Travel,Eco,612,2,5,3,5,5,3,3,5,4,3,4,4,5,5,118,97.0,neutral or dissatisfied +17061,94614,Female,disloyal Customer,21,Business travel,Eco,239,4,1,4,2,2,4,2,2,2,3,2,4,3,2,5,9.0,neutral or dissatisfied +17062,127841,Male,Loyal Customer,57,Business travel,Business,3936,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +17063,78380,Male,Loyal Customer,39,Business travel,Business,980,4,4,4,4,2,5,5,4,4,4,4,4,4,4,57,35.0,satisfied +17064,83827,Female,disloyal Customer,33,Business travel,Business,425,3,3,3,5,3,3,3,3,5,5,5,4,4,3,10,2.0,neutral or dissatisfied +17065,61491,Male,disloyal Customer,28,Business travel,Eco,2288,2,2,2,3,4,2,4,4,1,3,3,4,2,4,93,89.0,neutral or dissatisfied +17066,101352,Female,Loyal Customer,46,Business travel,Business,1986,3,3,3,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +17067,68440,Female,Loyal Customer,54,Personal Travel,Eco Plus,1045,2,5,2,3,3,5,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +17068,110959,Female,Loyal Customer,53,Business travel,Business,1582,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +17069,33848,Female,Loyal Customer,70,Business travel,Eco,1562,3,4,4,4,2,3,3,3,3,3,3,1,3,1,6,0.0,neutral or dissatisfied +17070,55689,Male,disloyal Customer,23,Business travel,Eco,1062,3,3,3,4,4,3,2,4,2,1,3,1,3,4,0,0.0,neutral or dissatisfied +17071,27904,Female,Loyal Customer,45,Business travel,Business,2311,2,2,2,2,3,4,4,5,5,5,5,3,5,3,22,5.0,satisfied +17072,101989,Female,Loyal Customer,12,Personal Travel,Eco,628,2,4,2,1,1,2,1,1,5,5,4,5,4,1,0,14.0,neutral or dissatisfied +17073,29436,Male,Loyal Customer,46,Business travel,Eco,421,4,2,2,2,4,4,4,4,4,3,5,4,2,4,0,0.0,satisfied +17074,26618,Male,Loyal Customer,39,Business travel,Business,404,3,3,3,3,2,3,3,5,5,4,5,1,5,3,37,33.0,satisfied +17075,106695,Male,Loyal Customer,47,Business travel,Business,516,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +17076,127270,Male,Loyal Customer,29,Business travel,Business,3637,3,4,3,3,4,4,4,4,5,2,2,1,3,4,0,0.0,satisfied +17077,98691,Male,Loyal Customer,13,Personal Travel,Eco,994,2,5,2,3,2,2,2,2,3,5,5,5,5,2,0,8.0,neutral or dissatisfied +17078,26569,Female,Loyal Customer,25,Business travel,Business,581,2,5,5,5,2,2,2,2,4,5,3,4,3,2,74,87.0,neutral or dissatisfied +17079,107960,Female,Loyal Customer,30,Business travel,Business,1717,5,5,5,5,4,4,4,4,3,3,5,4,5,4,36,36.0,satisfied +17080,21362,Female,Loyal Customer,45,Personal Travel,Eco,674,2,4,2,3,4,4,5,4,4,2,4,5,4,3,6,22.0,neutral or dissatisfied +17081,5761,Male,Loyal Customer,18,Personal Travel,Eco,642,3,5,3,1,4,3,1,4,4,3,4,3,5,4,0,2.0,neutral or dissatisfied +17082,53705,Male,Loyal Customer,49,Business travel,Business,3556,4,4,4,4,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +17083,12653,Male,Loyal Customer,29,Business travel,Eco Plus,844,4,1,1,1,4,4,4,4,3,5,2,2,1,4,4,0.0,satisfied +17084,18645,Male,Loyal Customer,54,Personal Travel,Eco,192,1,5,1,1,5,1,5,5,4,2,4,4,5,5,21,29.0,neutral or dissatisfied +17085,107215,Male,Loyal Customer,49,Business travel,Eco Plus,402,2,1,1,1,2,2,2,3,5,3,3,2,1,2,185,196.0,neutral or dissatisfied +17086,80089,Female,Loyal Customer,45,Personal Travel,Eco Plus,1069,2,3,2,4,5,4,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +17087,58580,Male,Loyal Customer,35,Personal Travel,Eco,403,1,4,1,3,1,1,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +17088,41895,Female,Loyal Customer,39,Business travel,Eco,129,5,5,5,5,5,5,5,5,5,3,4,5,3,5,0,1.0,satisfied +17089,127099,Male,Loyal Customer,59,Personal Travel,Eco,304,4,4,4,1,1,4,4,1,4,3,4,5,5,1,1,0.0,satisfied +17090,96399,Male,Loyal Customer,16,Business travel,Business,1246,1,2,2,2,1,1,1,1,1,1,4,1,4,1,11,0.0,neutral or dissatisfied +17091,37535,Female,disloyal Customer,25,Business travel,Eco,950,2,2,2,1,3,2,3,3,2,1,5,5,1,3,0,0.0,neutral or dissatisfied +17092,48228,Female,Loyal Customer,58,Personal Travel,Eco,391,1,5,1,2,4,4,5,1,1,1,1,3,1,5,0,16.0,neutral or dissatisfied +17093,119412,Female,Loyal Customer,54,Business travel,Eco,399,4,4,4,4,2,2,3,4,4,4,4,2,4,4,0,30.0,neutral or dissatisfied +17094,68447,Female,Loyal Customer,45,Business travel,Business,3743,2,4,4,4,3,4,4,2,2,2,2,4,2,3,0,19.0,neutral or dissatisfied +17095,99757,Female,Loyal Customer,27,Personal Travel,Eco,255,2,4,2,4,5,2,5,5,3,2,5,1,2,5,84,78.0,neutral or dissatisfied +17096,113410,Female,disloyal Customer,24,Business travel,Eco,226,0,0,0,1,2,0,5,2,5,2,5,3,5,2,8,0.0,satisfied +17097,4681,Male,Loyal Customer,44,Personal Travel,Eco,364,1,5,1,2,3,1,3,3,5,5,4,3,5,3,1,2.0,neutral or dissatisfied +17098,6336,Female,disloyal Customer,24,Business travel,Eco,296,5,0,5,2,2,5,4,2,5,4,4,5,5,2,0,0.0,satisfied +17099,66824,Male,Loyal Customer,46,Business travel,Business,3325,3,3,3,3,5,4,4,5,5,5,5,3,5,5,5,0.0,satisfied +17100,128926,Female,disloyal Customer,25,Business travel,Business,414,5,0,5,1,4,5,4,4,4,4,4,3,5,4,0,0.0,satisfied +17101,86092,Male,Loyal Customer,61,Business travel,Business,226,2,2,2,2,5,4,4,4,4,4,4,4,4,3,26,47.0,satisfied +17102,53521,Male,Loyal Customer,47,Personal Travel,Eco,2419,3,2,3,2,3,3,3,2,5,2,2,3,4,3,9,40.0,neutral or dissatisfied +17103,107086,Male,Loyal Customer,65,Personal Travel,Business,562,1,5,1,2,5,4,5,4,4,1,5,3,4,3,8,0.0,neutral or dissatisfied +17104,101414,Female,Loyal Customer,53,Personal Travel,Eco,486,4,0,4,2,3,4,4,5,5,4,5,5,5,4,12,18.0,neutral or dissatisfied +17105,4062,Male,Loyal Customer,65,Personal Travel,Eco,483,1,4,4,3,4,4,1,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +17106,55163,Female,Loyal Customer,29,Personal Travel,Eco,1609,0,5,0,1,4,0,4,4,5,3,4,4,4,4,11,5.0,satisfied +17107,81641,Female,Loyal Customer,19,Personal Travel,Business,907,1,4,1,1,2,1,5,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +17108,66381,Female,Loyal Customer,49,Business travel,Business,1562,5,5,3,5,5,5,4,4,4,4,4,3,4,3,0,6.0,satisfied +17109,39631,Female,Loyal Customer,16,Business travel,Eco Plus,620,1,1,3,1,1,2,2,1,2,4,3,4,4,1,0,1.0,neutral or dissatisfied +17110,115304,Female,Loyal Customer,35,Business travel,Business,358,2,2,5,2,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +17111,68478,Male,Loyal Customer,50,Business travel,Business,1067,2,2,2,2,3,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +17112,42284,Male,disloyal Customer,25,Business travel,Eco,838,2,2,2,1,5,2,4,5,1,3,2,5,4,5,0,1.0,neutral or dissatisfied +17113,108092,Female,Loyal Customer,40,Business travel,Business,2334,2,2,2,2,5,4,4,5,5,5,5,3,5,4,50,54.0,satisfied +17114,111448,Female,Loyal Customer,42,Business travel,Business,1024,5,5,5,5,3,5,5,5,5,4,5,5,5,5,11,5.0,satisfied +17115,69216,Female,Loyal Customer,53,Business travel,Business,733,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +17116,40145,Female,Loyal Customer,38,Business travel,Business,1937,2,2,2,2,5,5,3,5,5,5,5,3,5,1,0,0.0,satisfied +17117,21800,Male,Loyal Customer,39,Business travel,Eco,341,2,3,3,3,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +17118,7217,Male,Loyal Customer,32,Business travel,Eco,135,3,4,4,4,3,3,3,3,2,4,4,1,3,3,68,55.0,neutral or dissatisfied +17119,31960,Female,disloyal Customer,50,Business travel,Business,163,1,1,1,2,2,1,2,2,3,5,4,3,5,2,0,2.0,neutral or dissatisfied +17120,99512,Male,Loyal Customer,27,Personal Travel,Eco,307,3,5,1,5,5,1,1,5,1,2,3,3,5,5,0,0.0,neutral or dissatisfied +17121,89293,Male,disloyal Customer,20,Business travel,Business,453,4,0,4,3,5,4,5,5,5,4,5,5,5,5,8,7.0,satisfied +17122,35619,Female,Loyal Customer,26,Personal Travel,Eco Plus,1097,4,5,4,1,5,4,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +17123,31402,Female,Loyal Customer,70,Personal Travel,Eco Plus,1199,1,4,2,3,5,4,1,5,5,2,5,1,5,3,3,0.0,neutral or dissatisfied +17124,102321,Female,Loyal Customer,23,Business travel,Business,414,1,0,0,3,5,0,2,5,1,5,3,3,2,5,10,11.0,neutral or dissatisfied +17125,43624,Female,Loyal Customer,10,Personal Travel,Eco,236,3,4,3,4,1,3,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +17126,107022,Female,Loyal Customer,50,Personal Travel,Business,395,2,1,2,4,3,4,3,3,3,2,3,2,3,3,2,0.0,neutral or dissatisfied +17127,32593,Male,Loyal Customer,33,Business travel,Business,3153,0,5,0,4,3,3,3,3,3,4,1,1,2,3,0,0.0,satisfied +17128,91573,Female,Loyal Customer,58,Business travel,Business,1123,5,5,5,5,4,4,5,4,4,4,4,4,4,3,3,1.0,satisfied +17129,5869,Female,disloyal Customer,25,Business travel,Business,67,2,4,2,3,3,2,4,3,3,4,5,5,4,3,26,101.0,neutral or dissatisfied +17130,31814,Female,disloyal Customer,26,Business travel,Eco,716,3,3,3,1,3,3,3,1,2,3,3,3,2,3,5,4.0,neutral or dissatisfied +17131,37381,Male,disloyal Customer,27,Business travel,Eco,1010,2,2,2,1,1,2,2,1,3,1,4,3,1,1,27,23.0,neutral or dissatisfied +17132,88704,Female,Loyal Customer,32,Personal Travel,Eco,444,3,4,3,2,5,3,5,5,3,4,4,3,5,5,21,30.0,neutral or dissatisfied +17133,79440,Female,disloyal Customer,22,Business travel,Eco,187,2,2,2,4,5,2,5,5,2,1,3,3,3,5,98,86.0,neutral or dissatisfied +17134,127273,Female,Loyal Customer,34,Business travel,Business,2343,2,2,2,2,3,2,5,3,3,4,3,4,3,5,0,0.0,satisfied +17135,12937,Female,Loyal Customer,43,Personal Travel,Eco,456,1,1,1,3,5,3,3,4,4,1,4,3,4,1,0,10.0,neutral or dissatisfied +17136,23263,Male,Loyal Customer,27,Business travel,Eco,826,4,5,5,5,5,5,5,5,3,2,3,2,3,5,7,0.0,satisfied +17137,84660,Female,disloyal Customer,25,Business travel,Business,2182,1,0,1,3,5,1,5,5,5,5,4,4,5,5,7,5.0,neutral or dissatisfied +17138,37528,Female,Loyal Customer,10,Business travel,Eco,1069,4,1,4,1,4,4,3,4,4,5,4,2,5,4,0,0.0,satisfied +17139,99727,Female,Loyal Customer,53,Business travel,Business,361,4,4,5,4,2,4,5,4,4,4,4,3,4,4,23,15.0,satisfied +17140,60179,Male,Loyal Customer,18,Personal Travel,Eco,1005,4,5,4,5,4,4,5,4,4,5,5,4,5,4,1,8.0,neutral or dissatisfied +17141,19362,Male,Loyal Customer,13,Personal Travel,Eco Plus,692,3,5,3,1,1,3,1,1,5,5,4,3,5,1,72,64.0,neutral or dissatisfied +17142,87052,Female,disloyal Customer,29,Business travel,Business,640,2,2,2,4,2,2,3,2,5,3,5,5,4,2,12,0.0,neutral or dissatisfied +17143,106284,Male,Loyal Customer,57,Personal Travel,Eco,604,3,4,3,3,4,3,1,4,1,3,3,1,4,4,0,0.0,neutral or dissatisfied +17144,48157,Female,Loyal Customer,73,Business travel,Eco,259,2,1,1,1,1,4,3,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +17145,28505,Male,Loyal Customer,52,Business travel,Business,2640,4,4,4,4,1,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +17146,88477,Male,disloyal Customer,23,Business travel,Eco,240,3,4,3,3,4,3,3,4,3,4,4,1,4,4,0,0.0,neutral or dissatisfied +17147,105370,Male,Loyal Customer,45,Business travel,Business,2621,1,1,1,1,3,4,4,4,4,4,4,3,4,3,20,8.0,satisfied +17148,9750,Female,Loyal Customer,45,Personal Travel,Eco,970,4,4,5,1,5,4,4,3,3,5,2,3,3,5,0,0.0,neutral or dissatisfied +17149,87434,Male,Loyal Customer,46,Business travel,Business,2263,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +17150,49972,Male,Loyal Customer,53,Business travel,Eco,86,2,4,4,4,1,2,1,1,1,1,4,2,3,1,0,0.0,neutral or dissatisfied +17151,14177,Female,Loyal Customer,42,Business travel,Business,1945,5,5,5,5,4,4,4,4,2,3,3,4,5,4,152,149.0,satisfied +17152,51572,Female,Loyal Customer,44,Business travel,Eco,451,5,5,5,5,4,1,4,4,4,5,4,3,4,3,0,0.0,satisfied +17153,52302,Female,disloyal Customer,18,Business travel,Eco,261,1,4,1,4,2,1,2,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +17154,52681,Female,Loyal Customer,62,Personal Travel,Eco,119,1,4,1,4,3,2,2,3,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +17155,74341,Male,Loyal Customer,56,Personal Travel,Business,1188,4,2,3,2,3,1,2,2,2,3,2,4,2,4,21,11.0,neutral or dissatisfied +17156,79654,Female,Loyal Customer,29,Business travel,Business,1601,2,5,5,5,2,2,2,2,3,4,4,1,3,2,0,8.0,neutral or dissatisfied +17157,109239,Male,Loyal Customer,41,Personal Travel,Eco,722,0,4,0,4,3,0,3,3,1,2,1,3,5,3,0,0.0,satisfied +17158,22512,Female,Loyal Customer,47,Business travel,Eco Plus,143,5,4,3,4,5,5,5,5,5,5,5,5,5,2,36,36.0,satisfied +17159,84282,Male,Loyal Customer,16,Personal Travel,Eco,349,4,4,4,5,1,4,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +17160,40186,Male,Loyal Customer,44,Business travel,Business,2621,4,4,4,4,2,1,3,5,5,5,5,4,5,2,2,60.0,satisfied +17161,239,Male,Loyal Customer,44,Business travel,Business,719,3,3,3,3,3,5,5,4,4,4,4,5,4,3,2,11.0,satisfied +17162,45684,Female,Loyal Customer,27,Business travel,Business,2593,3,3,3,3,3,3,3,3,1,1,3,5,5,3,4,14.0,satisfied +17163,18610,Female,Loyal Customer,62,Business travel,Business,201,1,2,2,2,5,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +17164,14927,Male,Loyal Customer,57,Personal Travel,Eco Plus,315,2,4,2,2,4,2,4,4,3,4,5,2,3,4,0,0.0,neutral or dissatisfied +17165,100029,Male,Loyal Customer,36,Business travel,Business,220,1,1,1,1,5,3,3,2,2,2,1,3,2,2,30,23.0,neutral or dissatisfied +17166,102443,Male,Loyal Customer,32,Personal Travel,Eco,386,4,4,4,2,5,4,5,5,4,2,5,5,5,5,12,2.0,satisfied +17167,25262,Male,Loyal Customer,42,Business travel,Business,3737,2,4,4,4,4,3,2,2,2,2,2,3,2,4,0,15.0,neutral or dissatisfied +17168,98368,Male,Loyal Customer,44,Personal Travel,Eco,1046,3,4,3,3,3,3,3,3,4,4,3,1,3,3,7,11.0,neutral or dissatisfied +17169,107505,Male,Loyal Customer,30,Personal Travel,Eco,711,5,4,5,3,3,5,3,3,4,2,1,4,5,3,0,0.0,satisfied +17170,70786,Male,Loyal Customer,54,Business travel,Business,2470,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +17171,45956,Female,disloyal Customer,23,Business travel,Eco,563,5,0,5,2,2,5,2,2,3,1,1,4,3,2,0,0.0,satisfied +17172,90381,Male,Loyal Customer,52,Business travel,Business,1944,1,2,2,2,1,3,3,1,1,1,1,4,1,3,7,0.0,neutral or dissatisfied +17173,47592,Male,Loyal Customer,48,Business travel,Business,1504,2,4,4,4,2,1,2,2,2,2,2,3,2,4,0,2.0,neutral or dissatisfied +17174,85751,Female,Loyal Customer,44,Business travel,Business,1944,2,2,2,2,3,4,4,4,4,4,4,3,4,4,8,0.0,satisfied +17175,103356,Female,Loyal Customer,58,Business travel,Business,3862,2,2,2,2,2,4,5,5,5,5,5,4,5,5,17,21.0,satisfied +17176,121498,Female,disloyal Customer,24,Business travel,Eco,257,2,2,2,4,1,2,1,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +17177,50301,Female,Loyal Customer,30,Business travel,Business,153,3,3,3,3,5,5,5,5,1,2,2,4,1,5,0,0.0,satisfied +17178,111030,Male,Loyal Customer,39,Business travel,Business,197,4,4,4,4,3,4,5,5,5,5,5,5,5,5,25,19.0,satisfied +17179,1744,Male,Loyal Customer,30,Personal Travel,Eco,489,3,1,3,4,5,3,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +17180,115409,Female,disloyal Customer,50,Business travel,Eco,446,2,4,2,3,4,2,4,4,4,3,4,2,3,4,12,9.0,neutral or dissatisfied +17181,22926,Female,Loyal Customer,63,Personal Travel,Business,817,3,1,4,4,4,3,3,1,1,4,4,3,3,3,192,187.0,neutral or dissatisfied +17182,39719,Female,Loyal Customer,72,Business travel,Business,3637,3,3,4,3,4,4,5,5,5,5,4,4,5,1,0,0.0,satisfied +17183,49187,Male,Loyal Customer,39,Business travel,Eco,209,5,2,2,2,5,5,5,5,2,4,2,3,4,5,0,1.0,satisfied +17184,25430,Female,disloyal Customer,22,Business travel,Eco,669,1,0,1,3,5,1,5,5,1,5,4,1,3,5,2,0.0,neutral or dissatisfied +17185,56515,Male,Loyal Customer,32,Personal Travel,Business,1065,3,4,3,5,3,2,2,3,3,5,5,2,5,2,142,134.0,neutral or dissatisfied +17186,20138,Male,Loyal Customer,39,Business travel,Eco Plus,466,2,4,4,4,2,2,2,2,3,3,4,4,3,2,32,34.0,neutral or dissatisfied +17187,60799,Female,Loyal Customer,57,Business travel,Business,472,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +17188,19906,Female,disloyal Customer,37,Business travel,Eco,240,2,3,2,4,2,2,1,2,2,2,4,1,3,2,45,130.0,neutral or dissatisfied +17189,20933,Male,Loyal Customer,33,Business travel,Business,3416,5,5,5,5,2,2,2,2,5,1,2,2,3,2,0,0.0,satisfied +17190,106436,Female,disloyal Customer,21,Business travel,Eco,488,2,2,2,3,3,2,3,3,4,2,4,4,4,3,79,77.0,neutral or dissatisfied +17191,129525,Male,Loyal Customer,27,Business travel,Business,2342,5,5,5,5,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +17192,10755,Female,Loyal Customer,46,Business travel,Business,2637,2,2,3,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +17193,67313,Male,Loyal Customer,37,Business travel,Eco Plus,518,5,2,2,2,5,5,5,5,2,2,2,1,5,5,0,0.0,satisfied +17194,55762,Male,Loyal Customer,38,Business travel,Business,3894,5,5,5,5,2,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +17195,116031,Female,Loyal Customer,38,Personal Travel,Eco,333,1,5,1,2,2,1,2,2,4,3,5,5,5,2,10,4.0,neutral or dissatisfied +17196,6258,Female,disloyal Customer,24,Business travel,Eco,585,4,0,4,1,5,4,3,5,3,3,5,3,4,5,89,82.0,satisfied +17197,37261,Female,disloyal Customer,29,Business travel,Eco,1035,4,4,4,3,2,4,2,2,1,3,1,2,2,2,42,21.0,satisfied +17198,683,Male,Loyal Customer,42,Business travel,Business,134,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +17199,107493,Male,Loyal Customer,12,Business travel,Business,1589,3,3,4,3,3,3,3,3,3,5,4,3,4,3,59,51.0,neutral or dissatisfied +17200,87156,Male,disloyal Customer,15,Business travel,Eco,946,4,4,4,3,5,4,5,5,3,2,4,5,5,5,0,0.0,satisfied +17201,80499,Male,Loyal Customer,50,Business travel,Business,1749,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,4.0,satisfied +17202,108223,Female,Loyal Customer,57,Business travel,Business,895,2,2,2,2,5,4,4,5,5,5,5,5,5,5,100,76.0,satisfied +17203,20697,Female,Loyal Customer,32,Business travel,Business,2543,2,2,2,2,3,3,3,3,1,4,3,2,2,3,62,60.0,satisfied +17204,14167,Female,Loyal Customer,12,Business travel,Eco,714,4,3,4,3,4,4,5,4,4,2,5,2,4,4,33,26.0,satisfied +17205,10745,Female,disloyal Customer,32,Business travel,Business,316,3,2,2,3,4,2,4,4,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +17206,103015,Female,Loyal Customer,59,Business travel,Eco,546,1,5,5,5,5,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +17207,41752,Female,Loyal Customer,11,Business travel,Business,2625,5,3,3,3,5,4,5,5,1,2,4,2,4,5,52,46.0,neutral or dissatisfied +17208,10923,Male,Loyal Customer,47,Business travel,Eco,191,2,4,4,4,2,2,2,2,4,5,4,1,3,2,3,5.0,neutral or dissatisfied +17209,32477,Female,Loyal Customer,33,Business travel,Business,2933,0,4,0,3,5,1,2,4,4,4,4,1,4,4,0,0.0,satisfied +17210,110999,Female,disloyal Customer,20,Business travel,Eco,319,1,4,1,3,2,1,2,2,4,3,3,2,3,2,27,2.0,neutral or dissatisfied +17211,18029,Female,Loyal Customer,27,Business travel,Business,3576,2,2,1,2,4,4,4,4,3,1,3,1,5,4,57,78.0,satisfied +17212,125549,Male,Loyal Customer,37,Business travel,Eco,226,2,1,1,1,2,2,2,2,3,4,4,1,4,2,1,14.0,neutral or dissatisfied +17213,65128,Male,Loyal Customer,67,Personal Travel,Eco,190,2,5,2,3,1,2,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +17214,72421,Female,Loyal Customer,45,Business travel,Business,3059,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,24.0,satisfied +17215,127466,Female,disloyal Customer,31,Business travel,Eco,850,2,3,3,4,5,2,5,5,2,3,2,2,3,5,0,0.0,neutral or dissatisfied +17216,54501,Male,Loyal Customer,9,Business travel,Business,925,2,3,3,3,2,2,2,2,1,1,4,1,4,2,8,0.0,neutral or dissatisfied +17217,92635,Male,Loyal Customer,58,Business travel,Business,453,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +17218,83512,Female,Loyal Customer,10,Personal Travel,Eco,946,1,4,1,3,1,2,2,3,2,1,5,2,1,2,313,327.0,neutral or dissatisfied +17219,70932,Male,Loyal Customer,51,Business travel,Business,3232,1,1,1,1,3,4,5,5,5,5,5,5,5,4,13,5.0,satisfied +17220,117355,Female,Loyal Customer,16,Business travel,Business,3402,2,1,1,1,2,2,2,2,2,3,4,4,4,2,0,0.0,neutral or dissatisfied +17221,76856,Male,Loyal Customer,35,Personal Travel,Eco,1195,1,5,1,3,2,1,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +17222,7250,Female,Loyal Customer,51,Personal Travel,Eco,116,4,4,4,1,1,5,5,3,3,4,3,3,3,5,0,21.0,satisfied +17223,66426,Male,Loyal Customer,21,Personal Travel,Eco,1562,3,1,3,3,4,3,4,4,2,4,3,1,3,4,14,0.0,neutral or dissatisfied +17224,108868,Female,disloyal Customer,46,Business travel,Business,1287,4,4,4,3,3,4,3,3,4,2,5,3,4,3,0,0.0,satisfied +17225,64243,Female,Loyal Customer,61,Business travel,Eco,1660,4,2,2,2,4,1,3,4,4,4,4,2,4,1,0,19.0,neutral or dissatisfied +17226,111191,Female,Loyal Customer,54,Business travel,Business,1703,1,1,1,1,3,4,5,4,4,4,4,4,4,4,7,29.0,satisfied +17227,43172,Male,Loyal Customer,55,Business travel,Business,1916,1,1,1,1,4,4,4,2,1,2,4,4,4,4,147,145.0,satisfied +17228,84938,Female,Loyal Customer,38,Personal Travel,Eco,516,3,1,3,4,1,3,1,1,2,3,4,4,4,1,0,0.0,neutral or dissatisfied +17229,4813,Female,Loyal Customer,43,Personal Travel,Eco Plus,438,1,5,1,4,2,5,4,4,4,1,4,3,4,3,119,104.0,neutral or dissatisfied +17230,107830,Female,Loyal Customer,33,Personal Travel,Eco,349,1,4,1,4,3,1,5,3,5,4,5,5,4,3,35,30.0,neutral or dissatisfied +17231,87884,Female,Loyal Customer,49,Personal Travel,Eco Plus,214,1,4,0,1,1,2,1,1,1,0,1,3,1,3,2,0.0,neutral or dissatisfied +17232,88259,Female,Loyal Customer,55,Business travel,Business,2212,4,4,4,4,2,4,5,4,4,4,4,3,4,3,8,0.0,satisfied +17233,119550,Male,Loyal Customer,59,Personal Travel,Eco,857,3,4,3,3,5,3,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +17234,62745,Female,Loyal Customer,31,Business travel,Business,2556,1,1,1,1,4,4,4,4,3,2,4,5,5,4,26,,satisfied +17235,7882,Male,Loyal Customer,55,Business travel,Business,1941,5,5,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +17236,82476,Male,Loyal Customer,48,Personal Travel,Eco,502,4,5,4,2,5,4,5,5,3,3,4,4,5,5,0,7.0,neutral or dissatisfied +17237,89781,Female,Loyal Customer,24,Personal Travel,Eco,1010,3,4,3,1,5,3,5,5,2,3,2,1,1,5,0,6.0,neutral or dissatisfied +17238,5569,Male,Loyal Customer,51,Personal Travel,Eco,501,3,5,3,4,5,3,2,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +17239,46850,Female,Loyal Customer,21,Business travel,Eco,737,4,4,4,4,4,4,4,4,3,3,4,1,5,4,0,0.0,satisfied +17240,6991,Male,Loyal Customer,55,Business travel,Eco,299,1,3,3,3,1,1,1,1,1,1,4,2,4,1,45,51.0,neutral or dissatisfied +17241,60040,Female,disloyal Customer,25,Business travel,Eco Plus,997,4,4,4,4,5,4,5,5,2,2,3,4,3,5,5,2.0,neutral or dissatisfied +17242,31325,Male,disloyal Customer,62,Business travel,Business,1123,3,3,3,2,4,3,4,4,2,3,2,3,2,4,9,0.0,neutral or dissatisfied +17243,34292,Male,Loyal Customer,45,Business travel,Business,2191,3,4,4,4,3,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +17244,103502,Female,Loyal Customer,47,Business travel,Business,1256,3,3,3,3,3,4,4,5,5,5,5,3,5,4,47,33.0,satisfied +17245,72035,Male,Loyal Customer,41,Personal Travel,Eco,3784,1,5,1,5,1,3,5,3,3,5,4,5,3,5,5,2.0,neutral or dissatisfied +17246,108728,Female,Loyal Customer,27,Personal Travel,Eco,591,3,5,3,3,3,3,3,3,4,4,4,3,4,3,16,0.0,neutral or dissatisfied +17247,117220,Male,Loyal Customer,42,Personal Travel,Eco,304,3,4,3,4,2,3,2,2,3,2,5,3,4,2,10,9.0,neutral or dissatisfied +17248,87900,Male,disloyal Customer,26,Business travel,Business,594,2,2,2,1,4,2,3,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +17249,829,Female,Loyal Customer,57,Business travel,Business,164,3,4,4,4,3,4,3,2,2,2,3,3,2,4,25,23.0,neutral or dissatisfied +17250,66214,Female,Loyal Customer,51,Business travel,Business,2364,1,1,1,1,3,4,5,4,4,4,4,3,4,5,7,2.0,satisfied +17251,100440,Male,Loyal Customer,50,Business travel,Business,1912,1,1,5,1,4,3,4,4,4,4,4,5,4,5,1,0.0,satisfied +17252,113619,Female,Loyal Customer,44,Personal Travel,Eco,414,3,2,3,4,2,3,4,3,3,3,5,4,3,4,7,5.0,neutral or dissatisfied +17253,45096,Female,Loyal Customer,16,Personal Travel,Business,177,3,4,3,4,3,1,1,4,4,4,3,1,3,1,169,166.0,neutral or dissatisfied +17254,94073,Male,disloyal Customer,32,Business travel,Business,239,2,2,2,2,2,2,4,2,1,4,3,1,3,2,14,9.0,neutral or dissatisfied +17255,127292,Male,Loyal Customer,51,Business travel,Business,3983,2,2,2,2,3,4,5,5,5,5,5,4,5,5,36,16.0,satisfied +17256,43434,Female,disloyal Customer,10,Business travel,Eco,748,2,2,2,4,2,2,2,2,3,3,4,4,4,2,0,19.0,neutral or dissatisfied +17257,1291,Male,Loyal Customer,35,Personal Travel,Eco,158,0,4,0,1,4,0,4,4,5,4,5,3,5,4,0,0.0,satisfied +17258,41658,Male,Loyal Customer,34,Business travel,Business,3350,0,0,0,3,1,3,2,4,4,4,4,2,4,5,0,0.0,satisfied +17259,85818,Male,Loyal Customer,42,Personal Travel,Eco,666,2,5,3,3,1,3,1,1,3,2,4,3,4,1,29,5.0,neutral or dissatisfied +17260,16830,Male,Loyal Customer,68,Personal Travel,Eco,645,3,4,3,1,4,3,4,4,3,2,5,2,5,4,3,15.0,neutral or dissatisfied +17261,81963,Female,disloyal Customer,41,Business travel,Business,1535,1,1,1,4,5,1,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +17262,46197,Male,Loyal Customer,56,Personal Travel,Eco,423,2,4,4,3,1,4,1,1,2,5,1,1,5,1,11,5.0,neutral or dissatisfied +17263,92516,Male,Loyal Customer,17,Personal Travel,Eco,1947,3,2,3,4,3,3,3,3,2,4,3,1,4,3,5,6.0,neutral or dissatisfied +17264,105412,Male,Loyal Customer,62,Personal Travel,Eco Plus,369,1,2,1,4,3,1,3,3,1,3,4,2,4,3,0,0.0,neutral or dissatisfied +17265,18795,Male,Loyal Customer,55,Business travel,Eco,448,4,2,2,2,4,4,4,4,4,2,3,1,5,4,0,0.0,satisfied +17266,59708,Male,Loyal Customer,31,Personal Travel,Eco,964,2,2,2,4,3,2,3,3,1,2,4,2,4,3,14,3.0,neutral or dissatisfied +17267,109012,Female,Loyal Customer,27,Business travel,Business,2078,1,1,1,1,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +17268,10590,Female,Loyal Customer,54,Business travel,Business,2046,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +17269,75642,Male,Loyal Customer,50,Business travel,Business,3955,4,3,4,4,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +17270,112033,Female,disloyal Customer,44,Business travel,Eco Plus,680,2,2,2,3,4,2,3,4,3,3,3,2,2,4,0,5.0,neutral or dissatisfied +17271,108159,Female,Loyal Customer,54,Personal Travel,Eco,1166,1,1,0,2,5,2,3,3,3,0,3,1,3,2,0,1.0,neutral or dissatisfied +17272,2708,Male,Loyal Customer,16,Personal Travel,Eco,562,3,5,2,2,2,2,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +17273,125430,Female,Loyal Customer,31,Personal Travel,Eco,735,1,3,1,3,1,1,1,1,2,5,4,2,3,1,1,1.0,neutral or dissatisfied +17274,39658,Female,Loyal Customer,61,Personal Travel,Eco,310,2,4,2,3,5,5,4,4,4,2,4,4,4,3,85,87.0,neutral or dissatisfied +17275,84570,Female,Loyal Customer,58,Business travel,Business,2486,2,2,2,2,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +17276,52993,Male,disloyal Customer,39,Business travel,Business,1190,3,3,3,5,5,3,5,5,5,2,2,2,5,5,0,0.0,neutral or dissatisfied +17277,68912,Female,Loyal Customer,67,Personal Travel,Eco,936,3,5,3,2,2,4,3,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +17278,111732,Male,Loyal Customer,53,Business travel,Business,3616,5,5,1,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +17279,96695,Male,Loyal Customer,41,Business travel,Business,696,3,3,3,3,2,5,5,5,5,5,5,3,5,4,61,55.0,satisfied +17280,42048,Male,disloyal Customer,29,Business travel,Eco,106,3,0,3,5,5,3,5,5,4,5,3,4,5,5,0,0.0,neutral or dissatisfied +17281,126556,Female,Loyal Customer,12,Personal Travel,Eco,644,1,3,1,3,1,1,1,1,4,1,3,1,3,1,0,0.0,neutral or dissatisfied +17282,109780,Female,Loyal Customer,61,Personal Travel,Business,1034,3,4,3,3,5,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +17283,26052,Female,Loyal Customer,35,Personal Travel,Eco,432,3,4,3,1,3,3,3,3,1,1,4,4,5,3,7,0.0,neutral or dissatisfied +17284,82514,Female,Loyal Customer,57,Business travel,Business,1749,2,2,3,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +17285,118761,Female,Loyal Customer,42,Personal Travel,Eco,304,1,3,3,4,1,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +17286,42038,Female,Loyal Customer,38,Business travel,Business,1543,4,4,4,4,1,1,4,4,4,4,3,2,4,2,9,5.0,satisfied +17287,57688,Female,Loyal Customer,52,Business travel,Business,867,4,4,4,4,3,5,4,5,5,5,5,5,5,4,10,17.0,satisfied +17288,4694,Female,Loyal Customer,46,Personal Travel,Eco,364,3,3,3,3,3,3,3,4,3,3,2,3,3,3,137,119.0,neutral or dissatisfied +17289,16177,Male,Loyal Customer,39,Business travel,Eco,277,4,1,1,1,4,4,4,4,5,1,2,1,5,4,0,0.0,satisfied +17290,43394,Male,Loyal Customer,64,Personal Travel,Eco,347,1,1,3,3,3,3,3,3,1,3,2,3,3,3,0,0.0,neutral or dissatisfied +17291,37105,Female,Loyal Customer,39,Business travel,Eco,1179,5,4,4,4,5,5,5,5,3,2,2,1,1,5,5,13.0,satisfied +17292,72105,Male,Loyal Customer,50,Business travel,Eco Plus,986,2,2,2,2,2,2,2,2,3,2,1,3,2,2,18,0.0,satisfied +17293,22041,Female,Loyal Customer,10,Personal Travel,Eco Plus,448,2,4,2,5,3,2,5,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +17294,27890,Female,disloyal Customer,30,Business travel,Eco,1136,2,1,1,3,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +17295,89793,Male,Loyal Customer,52,Personal Travel,Eco,1035,3,5,3,3,2,3,2,2,5,5,5,5,4,2,9,3.0,neutral or dissatisfied +17296,108324,Female,Loyal Customer,55,Business travel,Eco,1855,2,1,1,1,3,2,3,2,2,2,2,4,2,4,2,0.0,neutral or dissatisfied +17297,95415,Female,Loyal Customer,44,Business travel,Business,189,0,4,0,1,4,5,4,1,1,1,1,3,1,3,2,0.0,satisfied +17298,103519,Male,Loyal Customer,34,Personal Travel,Eco,1256,3,5,3,1,5,3,5,5,4,2,3,3,5,5,0,0.0,neutral or dissatisfied +17299,16339,Female,Loyal Customer,16,Personal Travel,Eco,594,3,1,3,2,3,3,4,3,4,5,1,2,1,3,3,18.0,neutral or dissatisfied +17300,82467,Male,Loyal Customer,59,Personal Travel,Eco,509,3,2,3,4,2,3,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +17301,45577,Female,Loyal Customer,43,Business travel,Business,2226,2,1,1,1,3,3,3,2,2,2,2,1,2,3,5,6.0,neutral or dissatisfied +17302,97317,Female,Loyal Customer,47,Business travel,Business,3052,5,5,5,5,2,5,4,5,5,5,5,5,5,3,53,42.0,satisfied +17303,100962,Female,Loyal Customer,25,Personal Travel,Eco,1142,3,3,3,1,4,3,4,4,4,5,3,4,1,4,5,0.0,neutral or dissatisfied +17304,99813,Male,Loyal Customer,52,Business travel,Business,2178,4,4,4,4,3,5,4,5,5,5,5,5,5,5,52,63.0,satisfied +17305,90278,Female,Loyal Customer,55,Business travel,Business,2486,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,4.0,satisfied +17306,64470,Male,Loyal Customer,57,Business travel,Business,224,4,4,4,4,2,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +17307,105323,Female,Loyal Customer,54,Business travel,Business,452,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +17308,3976,Female,Loyal Customer,51,Business travel,Business,340,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +17309,63031,Female,disloyal Customer,39,Business travel,Eco,446,2,5,2,1,2,2,2,2,3,3,2,4,1,2,4,0.0,neutral or dissatisfied +17310,125727,Male,Loyal Customer,55,Business travel,Business,759,1,1,1,1,2,5,4,5,5,5,5,3,5,3,14,0.0,satisfied +17311,110485,Female,Loyal Customer,68,Personal Travel,Eco,787,3,3,4,5,2,1,1,4,4,4,4,4,4,3,49,85.0,neutral or dissatisfied +17312,63568,Female,disloyal Customer,35,Business travel,Business,1737,3,3,3,3,4,3,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +17313,53007,Male,Loyal Customer,42,Business travel,Business,3646,2,2,2,2,4,2,4,5,5,5,5,5,5,4,0,0.0,satisfied +17314,55054,Female,Loyal Customer,26,Business travel,Business,3717,1,3,3,3,1,1,1,3,1,4,4,1,4,1,140,108.0,neutral or dissatisfied +17315,66364,Male,Loyal Customer,31,Personal Travel,Eco,986,2,4,2,2,3,2,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +17316,108119,Male,Loyal Customer,53,Business travel,Business,3913,2,3,3,3,1,2,2,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +17317,101165,Female,Loyal Customer,39,Business travel,Business,3624,2,2,2,2,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +17318,44765,Male,Loyal Customer,42,Business travel,Eco,1250,4,1,4,1,3,4,3,3,3,3,3,4,5,3,0,2.0,satisfied +17319,76409,Male,Loyal Customer,64,Personal Travel,Business,405,3,4,3,2,1,3,5,4,4,3,3,2,4,2,4,0.0,neutral or dissatisfied +17320,70339,Female,Loyal Customer,57,Business travel,Eco,586,4,4,4,4,4,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +17321,57474,Male,Loyal Customer,27,Business travel,Eco,680,4,4,4,4,4,4,4,4,1,3,4,4,4,4,5,23.0,neutral or dissatisfied +17322,33624,Female,Loyal Customer,41,Business travel,Business,3544,1,1,1,1,3,1,5,5,5,4,5,1,5,2,0,0.0,satisfied +17323,82399,Male,disloyal Customer,10,Business travel,Eco,500,2,4,2,3,2,2,2,2,3,1,3,1,3,2,27,13.0,neutral or dissatisfied +17324,70971,Female,disloyal Customer,29,Business travel,Business,802,2,2,2,5,3,2,3,3,4,2,4,4,4,3,89,87.0,neutral or dissatisfied +17325,60818,Male,Loyal Customer,50,Personal Travel,Eco,524,1,1,3,3,3,3,3,3,2,1,3,2,3,3,6,6.0,neutral or dissatisfied +17326,76946,Male,Loyal Customer,43,Business travel,Business,1990,5,5,5,5,2,5,4,4,4,4,4,3,4,3,17,24.0,satisfied +17327,109434,Female,Loyal Customer,58,Business travel,Business,3620,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +17328,37934,Female,Loyal Customer,12,Personal Travel,Eco,937,2,1,2,3,2,2,2,2,4,4,4,1,3,2,30,46.0,neutral or dissatisfied +17329,44331,Male,Loyal Customer,37,Business travel,Business,230,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +17330,123971,Female,disloyal Customer,37,Business travel,Business,184,3,3,3,2,4,3,4,4,4,3,5,5,5,4,0,7.0,neutral or dissatisfied +17331,55449,Female,Loyal Customer,58,Business travel,Business,2521,1,1,1,1,2,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +17332,35722,Male,Loyal Customer,32,Personal Travel,Eco,2586,3,2,3,3,3,3,3,1,3,4,4,3,3,3,7,6.0,neutral or dissatisfied +17333,51080,Female,Loyal Customer,35,Personal Travel,Eco,89,4,4,0,1,3,0,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +17334,93793,Female,disloyal Customer,39,Business travel,Business,1259,4,4,4,3,4,4,4,4,3,2,4,4,5,4,2,22.0,neutral or dissatisfied +17335,28937,Male,disloyal Customer,36,Business travel,Eco,679,3,3,3,4,3,3,1,3,3,4,4,4,3,3,0,0.0,neutral or dissatisfied +17336,99200,Male,Loyal Customer,50,Business travel,Business,583,2,2,2,2,3,4,5,4,4,4,4,3,4,4,13,0.0,satisfied +17337,45038,Male,Loyal Customer,33,Business travel,Eco Plus,837,0,0,0,5,4,0,4,4,3,3,2,3,4,4,0,0.0,satisfied +17338,77904,Female,Loyal Customer,26,Personal Travel,Eco,610,1,5,1,4,3,1,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +17339,48040,Female,disloyal Customer,40,Business travel,Business,677,4,4,4,3,4,4,4,4,1,3,4,4,4,4,21,24.0,neutral or dissatisfied +17340,98190,Female,disloyal Customer,21,Business travel,Eco,327,4,2,4,2,1,4,1,1,4,1,2,4,3,1,0,0.0,neutral or dissatisfied +17341,21368,Female,disloyal Customer,26,Business travel,Eco,554,1,0,1,2,1,1,1,1,1,2,4,1,1,1,57,48.0,neutral or dissatisfied +17342,31765,Female,Loyal Customer,30,Business travel,Business,602,3,3,3,3,5,5,5,5,5,2,3,2,2,5,0,3.0,satisfied +17343,21047,Female,Loyal Customer,30,Business travel,Eco,227,4,5,5,5,4,4,4,4,1,3,3,1,4,4,0,0.0,neutral or dissatisfied +17344,103337,Female,Loyal Customer,11,Personal Travel,Eco,1371,2,4,2,3,5,2,2,5,5,3,4,5,4,5,0,4.0,neutral or dissatisfied +17345,28946,Female,Loyal Customer,54,Business travel,Eco,679,2,2,4,2,1,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +17346,56398,Female,Loyal Customer,40,Business travel,Business,1565,3,3,3,3,4,4,5,5,5,5,5,4,5,3,66,59.0,satisfied +17347,61187,Male,Loyal Customer,24,Business travel,Business,3849,1,5,5,5,1,1,1,1,2,1,3,3,4,1,5,4.0,neutral or dissatisfied +17348,89553,Female,Loyal Customer,53,Business travel,Business,944,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +17349,97325,Female,Loyal Customer,47,Business travel,Business,2291,2,2,2,2,4,5,5,4,4,4,4,4,4,4,4,1.0,satisfied +17350,97564,Female,Loyal Customer,43,Business travel,Business,1539,2,2,4,2,3,4,5,5,5,5,5,3,5,5,25,23.0,satisfied +17351,9111,Male,Loyal Customer,25,Business travel,Business,3152,3,4,4,4,3,3,3,3,4,5,4,2,4,3,0,16.0,neutral or dissatisfied +17352,74490,Male,Loyal Customer,46,Business travel,Business,1242,5,5,5,5,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +17353,123922,Female,Loyal Customer,21,Personal Travel,Eco,544,4,5,4,4,2,4,2,2,1,1,4,4,1,2,0,0.0,neutral or dissatisfied +17354,59584,Female,Loyal Customer,56,Business travel,Business,2349,3,3,5,3,1,3,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +17355,50674,Male,Loyal Customer,20,Personal Travel,Eco,190,2,2,0,4,3,0,1,3,1,3,4,3,4,3,62,70.0,neutral or dissatisfied +17356,278,Female,Loyal Customer,16,Personal Travel,Eco,802,2,5,1,4,4,1,4,4,3,2,3,4,1,4,0,0.0,neutral or dissatisfied +17357,29364,Male,Loyal Customer,36,Business travel,Eco,2466,5,5,5,5,5,5,5,5,4,2,3,2,2,5,0,0.0,satisfied +17358,4537,Male,Loyal Customer,42,Business travel,Business,2602,3,2,2,2,2,3,2,3,3,3,3,2,3,1,30,42.0,neutral or dissatisfied +17359,61000,Female,Loyal Customer,29,Business travel,Business,3072,3,4,2,2,3,3,3,3,4,2,3,2,3,3,3,10.0,neutral or dissatisfied +17360,93972,Female,disloyal Customer,13,Business travel,Eco,1218,2,2,2,3,2,2,2,2,3,4,4,2,3,2,18,0.0,neutral or dissatisfied +17361,84101,Male,Loyal Customer,55,Personal Travel,Eco Plus,757,2,4,2,2,4,2,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +17362,46940,Female,Loyal Customer,26,Personal Travel,Eco,844,2,2,2,3,2,2,2,2,3,2,4,3,3,2,16,13.0,neutral or dissatisfied +17363,5404,Male,Loyal Customer,61,Personal Travel,Eco,733,2,5,2,5,1,2,1,1,4,3,4,1,5,1,0,0.0,neutral or dissatisfied +17364,45879,Female,Loyal Customer,50,Business travel,Business,913,1,1,1,1,4,4,1,5,5,5,5,5,5,1,11,0.0,satisfied +17365,28812,Female,disloyal Customer,20,Business travel,Eco,954,2,2,2,4,4,2,4,4,1,3,4,2,1,4,0,15.0,neutral or dissatisfied +17366,2930,Female,Loyal Customer,44,Personal Travel,Eco,859,3,5,3,3,3,4,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +17367,105491,Female,Loyal Customer,43,Business travel,Business,516,2,2,2,2,3,4,5,5,5,5,5,5,5,4,17,19.0,satisfied +17368,88575,Female,Loyal Customer,69,Personal Travel,Eco,594,2,3,2,3,5,4,4,5,5,2,5,2,5,3,9,0.0,neutral or dissatisfied +17369,73675,Female,disloyal Customer,44,Business travel,Business,192,5,5,5,3,4,5,4,4,3,4,4,3,4,4,5,0.0,satisfied +17370,84956,Female,disloyal Customer,39,Business travel,Business,516,2,2,2,4,1,2,1,1,2,5,3,2,3,1,19,29.0,neutral or dissatisfied +17371,98865,Female,Loyal Customer,11,Personal Travel,Eco,1751,2,4,2,3,5,2,1,5,5,5,2,5,4,5,0,0.0,neutral or dissatisfied +17372,53528,Female,Loyal Customer,44,Business travel,Eco Plus,2442,5,1,1,1,5,5,5,5,1,5,2,5,5,5,1,0.0,satisfied +17373,82695,Male,Loyal Customer,72,Business travel,Business,3996,1,5,5,5,1,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +17374,113314,Female,disloyal Customer,24,Business travel,Business,258,4,4,4,3,3,4,4,3,5,4,4,5,4,3,5,9.0,satisfied +17375,17682,Male,disloyal Customer,43,Business travel,Eco,1039,1,1,1,4,4,1,4,4,3,2,4,2,3,4,33,0.0,neutral or dissatisfied +17376,113247,Female,Loyal Customer,17,Personal Travel,Business,397,3,4,3,1,5,3,5,5,2,5,1,1,4,5,50,43.0,neutral or dissatisfied +17377,6494,Male,Loyal Customer,13,Personal Travel,Eco,557,2,3,2,4,2,2,1,2,4,4,3,4,3,2,35,29.0,neutral or dissatisfied +17378,38931,Female,Loyal Customer,68,Personal Travel,Eco,162,3,5,3,3,2,4,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +17379,42392,Female,Loyal Customer,54,Business travel,Eco Plus,451,5,1,1,1,5,3,2,5,5,5,5,5,5,4,0,0.0,satisfied +17380,47666,Male,disloyal Customer,22,Business travel,Eco,1040,4,3,3,3,5,4,5,5,3,2,4,2,2,5,0,0.0,satisfied +17381,120810,Female,Loyal Customer,65,Business travel,Business,666,1,4,4,4,4,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +17382,22682,Male,Loyal Customer,36,Business travel,Business,589,5,5,1,5,2,3,3,4,4,4,3,3,4,3,142,145.0,satisfied +17383,3694,Female,Loyal Customer,60,Business travel,Eco,431,1,4,5,4,5,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +17384,71052,Male,disloyal Customer,54,Business travel,Eco,402,2,1,2,2,3,2,3,3,1,3,2,4,2,3,12,3.0,neutral or dissatisfied +17385,34104,Male,Loyal Customer,22,Business travel,Business,1189,5,5,5,5,5,5,5,5,3,2,3,5,2,5,3,0.0,satisfied +17386,65889,Female,Loyal Customer,22,Business travel,Business,569,1,0,0,4,3,0,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +17387,74732,Male,Loyal Customer,47,Personal Travel,Eco,1171,2,5,2,3,5,2,5,5,3,4,4,5,4,5,22,8.0,neutral or dissatisfied +17388,29091,Female,Loyal Customer,17,Personal Travel,Eco,605,1,5,0,3,1,0,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +17389,112443,Female,Loyal Customer,56,Business travel,Eco,909,3,4,4,4,4,2,3,3,3,3,3,4,3,1,33,52.0,neutral or dissatisfied +17390,97828,Male,Loyal Customer,45,Business travel,Business,480,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +17391,67125,Male,Loyal Customer,44,Business travel,Business,1982,5,5,5,5,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +17392,58333,Male,disloyal Customer,23,Business travel,Business,296,5,0,5,1,1,5,1,1,4,3,4,4,4,1,0,0.0,satisfied +17393,18606,Female,Loyal Customer,16,Business travel,Business,3072,1,1,1,1,4,4,5,4,4,5,5,3,4,4,0,0.0,satisfied +17394,21937,Male,Loyal Customer,43,Business travel,Business,1755,2,2,2,2,5,3,4,5,5,5,5,2,5,2,0,0.0,satisfied +17395,1515,Male,Loyal Customer,44,Business travel,Business,2644,3,3,3,3,4,5,4,4,4,3,4,4,4,3,9,8.0,satisfied +17396,12960,Female,Loyal Customer,22,Business travel,Eco Plus,641,5,5,4,5,5,5,4,5,1,2,2,1,5,5,3,0.0,satisfied +17397,75203,Female,Loyal Customer,44,Business travel,Business,1744,1,2,2,2,5,1,1,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +17398,32940,Male,Loyal Customer,51,Personal Travel,Eco,101,1,4,1,3,4,1,4,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +17399,5080,Female,disloyal Customer,42,Business travel,Eco,235,3,3,3,4,3,3,3,3,4,3,4,3,3,3,0,9.0,neutral or dissatisfied +17400,120336,Female,Loyal Customer,51,Personal Travel,Eco Plus,268,2,3,0,5,5,5,5,5,5,0,5,2,5,5,0,0.0,neutral or dissatisfied +17401,102260,Female,Loyal Customer,52,Business travel,Business,3209,0,1,1,4,4,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +17402,63557,Male,Loyal Customer,70,Personal Travel,Eco Plus,1009,3,2,3,2,1,3,1,1,4,2,2,4,2,1,0,0.0,neutral or dissatisfied +17403,35990,Male,Loyal Customer,45,Personal Travel,Eco,2496,2,4,2,3,2,4,4,4,4,2,3,4,3,4,0,0.0,neutral or dissatisfied +17404,105890,Female,disloyal Customer,37,Business travel,Business,283,4,4,4,4,1,4,2,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +17405,64667,Female,disloyal Customer,44,Business travel,Eco,190,2,2,2,4,5,2,5,5,4,4,3,3,4,5,1,0.0,neutral or dissatisfied +17406,122378,Male,disloyal Customer,37,Business travel,Eco,129,0,5,0,4,4,0,4,4,3,5,1,1,3,4,0,0.0,satisfied +17407,111466,Female,Loyal Customer,29,Personal Travel,Eco,836,3,1,3,3,4,3,1,4,2,3,2,1,3,4,0,0.0,neutral or dissatisfied +17408,113745,Female,Loyal Customer,8,Personal Travel,Eco,236,1,4,1,4,5,1,5,5,3,4,1,4,3,5,6,1.0,neutral or dissatisfied +17409,2992,Female,Loyal Customer,21,Business travel,Business,1977,3,3,3,3,5,5,5,5,3,4,4,5,4,5,0,2.0,satisfied +17410,69405,Female,Loyal Customer,14,Business travel,Business,1089,5,5,5,5,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +17411,54820,Male,Loyal Customer,32,Business travel,Business,641,2,2,2,2,4,4,4,4,4,5,3,3,3,4,0,0.0,satisfied +17412,45643,Male,Loyal Customer,27,Personal Travel,Eco,230,4,1,4,3,4,4,4,4,1,1,4,2,3,4,20,13.0,neutral or dissatisfied +17413,60673,Male,Loyal Customer,44,Business travel,Eco Plus,1620,3,1,1,1,3,3,3,3,1,5,3,4,3,3,19,64.0,neutral or dissatisfied +17414,120878,Female,Loyal Customer,48,Business travel,Business,3882,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +17415,49228,Male,Loyal Customer,32,Business travel,Business,1634,0,0,0,1,4,4,4,4,4,3,4,3,1,4,0,0.0,satisfied +17416,56242,Female,Loyal Customer,50,Business travel,Business,2434,3,3,3,3,3,4,5,4,4,5,4,3,4,3,2,0.0,satisfied +17417,15032,Female,Loyal Customer,24,Business travel,Eco,576,5,5,2,2,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +17418,118447,Male,Loyal Customer,58,Business travel,Business,338,5,4,5,5,4,5,5,5,5,5,5,4,5,5,8,3.0,satisfied +17419,18754,Female,Loyal Customer,32,Personal Travel,Eco,1167,2,5,2,5,4,2,3,4,5,2,4,3,5,4,1,0.0,neutral or dissatisfied +17420,68713,Female,Loyal Customer,10,Personal Travel,Eco,175,1,5,1,1,1,1,1,1,3,5,4,5,4,1,3,0.0,neutral or dissatisfied +17421,31069,Male,Loyal Customer,14,Personal Travel,Eco,862,4,5,3,3,5,3,5,5,3,4,5,4,5,5,47,75.0,neutral or dissatisfied +17422,125535,Male,disloyal Customer,32,Business travel,Business,226,3,3,3,2,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +17423,13407,Female,Loyal Customer,15,Personal Travel,Business,475,1,1,1,3,3,1,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +17424,74159,Male,Loyal Customer,67,Personal Travel,Eco,641,5,4,4,2,5,4,5,5,5,1,4,1,5,5,0,0.0,satisfied +17425,17391,Female,Loyal Customer,32,Business travel,Business,376,1,1,1,1,5,5,5,5,1,5,1,5,5,5,4,4.0,satisfied +17426,126862,Male,Loyal Customer,12,Personal Travel,Eco,2125,5,1,5,3,2,5,2,2,3,3,3,1,4,2,37,21.0,satisfied +17427,37847,Male,Loyal Customer,21,Business travel,Eco,937,0,4,0,3,2,0,2,2,4,2,1,4,5,2,49,29.0,satisfied +17428,129123,Male,disloyal Customer,11,Business travel,Eco,954,2,2,2,4,3,2,5,3,1,1,3,2,4,3,9,0.0,neutral or dissatisfied +17429,20941,Male,Loyal Customer,24,Business travel,Eco,689,0,4,0,5,5,0,5,5,2,3,4,5,4,5,1,13.0,satisfied +17430,99972,Male,Loyal Customer,34,Personal Travel,Eco,888,5,3,5,3,1,5,1,1,3,2,4,1,4,1,0,0.0,satisfied +17431,38836,Female,Loyal Customer,29,Business travel,Eco Plus,354,5,5,5,5,5,4,5,5,2,3,4,4,5,5,0,0.0,satisfied +17432,17400,Female,disloyal Customer,27,Business travel,Eco,351,1,0,1,2,5,1,1,5,4,2,3,1,3,5,1,8.0,neutral or dissatisfied +17433,22625,Female,Loyal Customer,29,Personal Travel,Eco,250,2,4,2,4,2,2,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +17434,112814,Male,disloyal Customer,24,Business travel,Eco,1476,3,3,3,3,2,3,2,2,5,2,4,5,5,2,1,0.0,neutral or dissatisfied +17435,37173,Male,Loyal Customer,61,Personal Travel,Eco,1288,1,5,2,3,1,2,1,1,5,4,3,3,4,1,18,20.0,neutral or dissatisfied +17436,22497,Female,Loyal Customer,36,Personal Travel,Eco,83,4,4,4,3,5,4,1,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +17437,34197,Male,Loyal Customer,65,Personal Travel,Eco,1046,4,5,4,2,3,4,4,3,4,5,5,4,5,3,31,26.0,neutral or dissatisfied +17438,80340,Female,Loyal Customer,40,Business travel,Business,952,4,4,4,4,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +17439,90396,Female,Loyal Customer,18,Personal Travel,Business,594,1,4,1,2,2,1,2,2,3,2,1,3,2,2,1,0.0,neutral or dissatisfied +17440,31222,Female,Loyal Customer,64,Personal Travel,Eco,628,3,4,2,3,4,4,4,2,2,2,2,1,2,2,41,96.0,neutral or dissatisfied +17441,40647,Female,Loyal Customer,20,Personal Travel,Eco Plus,391,2,5,2,3,2,2,2,2,1,5,5,1,4,2,48,33.0,neutral or dissatisfied +17442,33012,Male,Loyal Customer,33,Personal Travel,Eco,163,3,5,0,4,3,0,3,3,3,4,5,1,3,3,0,2.0,neutral or dissatisfied +17443,6391,Male,Loyal Customer,41,Business travel,Eco,240,4,3,3,3,4,4,4,4,5,2,3,3,2,4,0,0.0,satisfied +17444,126539,Female,disloyal Customer,22,Business travel,Eco,644,4,0,4,2,2,4,4,2,3,2,5,4,4,2,0,0.0,satisfied +17445,16327,Female,Loyal Customer,58,Business travel,Business,228,4,4,4,4,1,4,4,4,4,5,4,2,4,4,0,0.0,satisfied +17446,31255,Male,Loyal Customer,34,Personal Travel,Business,533,2,4,2,1,5,4,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +17447,47588,Female,Loyal Customer,35,Business travel,Eco,1504,4,3,5,3,4,4,4,4,5,5,1,3,5,4,23,11.0,satisfied +17448,111562,Female,disloyal Customer,40,Business travel,Business,359,3,4,4,1,5,4,5,5,4,5,4,4,4,5,35,30.0,neutral or dissatisfied +17449,43681,Male,disloyal Customer,25,Business travel,Eco,257,2,0,2,3,3,2,3,3,2,1,1,1,5,3,10,2.0,neutral or dissatisfied +17450,72877,Male,disloyal Customer,37,Business travel,Business,1096,3,3,3,2,5,3,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +17451,37307,Male,Loyal Customer,47,Business travel,Eco,1035,4,2,2,2,4,4,4,4,4,3,3,2,5,4,0,0.0,satisfied +17452,40241,Male,Loyal Customer,39,Business travel,Eco,402,1,5,5,5,1,1,1,1,4,3,3,1,4,1,0,21.0,neutral or dissatisfied +17453,124010,Female,Loyal Customer,39,Business travel,Business,3315,2,3,2,2,2,3,5,4,4,4,3,1,4,4,0,0.0,satisfied +17454,43097,Female,Loyal Customer,19,Personal Travel,Eco,236,3,5,3,4,3,3,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +17455,111487,Male,Loyal Customer,64,Personal Travel,Eco,1452,3,1,3,3,4,3,4,4,2,2,3,2,3,4,6,0.0,neutral or dissatisfied +17456,65581,Female,Loyal Customer,62,Business travel,Business,175,4,4,4,4,2,5,4,5,5,5,4,4,5,4,1,10.0,satisfied +17457,64265,Female,disloyal Customer,28,Business travel,Business,1192,5,5,5,2,3,5,3,3,4,3,4,3,5,3,0,0.0,satisfied +17458,75102,Female,Loyal Customer,15,Business travel,Business,1652,2,5,5,5,2,2,2,2,1,4,2,1,4,2,0,0.0,neutral or dissatisfied +17459,105716,Male,Loyal Customer,45,Business travel,Eco,883,2,5,5,5,2,2,2,2,1,2,4,3,3,2,22,30.0,neutral or dissatisfied +17460,82837,Female,Loyal Customer,48,Business travel,Business,2584,5,5,5,5,3,4,4,5,5,5,5,3,5,3,20,7.0,satisfied +17461,69772,Male,Loyal Customer,28,Business travel,Business,2454,3,3,3,3,5,5,5,3,4,5,4,5,3,5,1,0.0,satisfied +17462,109725,Female,disloyal Customer,14,Business travel,Eco,534,4,1,4,3,1,4,5,1,1,3,3,3,4,1,55,45.0,neutral or dissatisfied +17463,107831,Male,Loyal Customer,36,Personal Travel,Eco,349,3,5,3,3,3,3,3,3,2,3,1,1,3,3,80,74.0,neutral or dissatisfied +17464,80326,Female,Loyal Customer,29,Personal Travel,Eco,746,0,3,0,3,5,0,5,5,3,2,3,3,3,5,0,0.0,satisfied +17465,104258,Male,Loyal Customer,57,Personal Travel,Business,456,1,5,1,3,2,4,4,4,4,1,3,3,4,5,31,48.0,neutral or dissatisfied +17466,76686,Male,Loyal Customer,48,Personal Travel,Eco,547,3,5,3,4,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +17467,10074,Female,Loyal Customer,47,Business travel,Business,441,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,14.0,satisfied +17468,88610,Female,Loyal Customer,68,Personal Travel,Eco,366,2,3,2,1,5,3,4,1,1,2,2,1,1,3,0,0.0,neutral or dissatisfied +17469,113482,Female,Loyal Customer,45,Business travel,Business,258,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +17470,81011,Female,Loyal Customer,56,Personal Travel,Eco Plus,297,3,2,3,3,2,4,3,5,5,3,5,4,5,1,56,50.0,neutral or dissatisfied +17471,5867,Male,Loyal Customer,24,Personal Travel,Eco Plus,1020,2,5,2,1,3,2,3,3,3,1,4,5,1,3,0,0.0,neutral or dissatisfied +17472,85454,Female,disloyal Customer,47,Business travel,Eco,106,1,2,1,1,4,1,4,4,1,5,2,3,2,4,0,0.0,neutral or dissatisfied +17473,11031,Male,Loyal Customer,66,Business travel,Eco,224,1,1,1,1,1,1,1,1,1,3,4,4,3,1,0,0.0,neutral or dissatisfied +17474,86297,Female,Loyal Customer,61,Personal Travel,Eco,377,1,4,5,2,4,4,4,3,3,5,3,5,3,5,0,0.0,neutral or dissatisfied +17475,5004,Male,Loyal Customer,37,Business travel,Business,3004,4,3,3,3,1,4,4,1,1,1,4,2,1,4,0,0.0,neutral or dissatisfied +17476,4180,Male,Loyal Customer,27,Personal Travel,Eco,427,1,2,1,4,2,1,2,2,3,1,2,3,4,2,0,0.0,neutral or dissatisfied +17477,36123,Male,Loyal Customer,44,Business travel,Business,1609,5,5,5,5,5,4,1,4,4,3,4,1,4,4,0,0.0,satisfied +17478,110391,Female,Loyal Customer,41,Business travel,Business,3837,5,5,5,5,2,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +17479,60852,Female,Loyal Customer,32,Personal Travel,Eco,1754,4,2,4,3,5,4,5,5,4,3,2,1,3,5,3,0.0,neutral or dissatisfied +17480,4027,Male,Loyal Customer,39,Business travel,Eco,419,2,5,5,5,2,2,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +17481,27223,Female,Loyal Customer,27,Business travel,Business,2063,2,2,2,2,4,4,4,4,3,2,2,5,2,4,0,9.0,satisfied +17482,119076,Male,Loyal Customer,39,Business travel,Business,3720,5,5,5,5,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +17483,2325,Male,Loyal Customer,21,Personal Travel,Eco,691,2,5,2,3,3,2,3,3,5,4,5,4,4,3,0,3.0,neutral or dissatisfied +17484,88988,Male,Loyal Customer,40,Personal Travel,Eco,1199,1,1,1,1,1,1,1,1,3,3,2,1,1,1,0,8.0,neutral or dissatisfied +17485,121067,Male,Loyal Customer,50,Business travel,Business,861,5,5,4,5,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +17486,15004,Female,Loyal Customer,62,Personal Travel,Eco,1201,3,2,4,4,1,4,4,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +17487,107565,Female,Loyal Customer,34,Personal Travel,Eco,1521,3,3,3,3,2,3,2,2,2,3,5,1,2,2,15,10.0,neutral or dissatisfied +17488,58278,Female,Loyal Customer,40,Business travel,Eco,678,4,2,2,2,4,4,4,4,1,3,4,3,3,4,5,30.0,neutral or dissatisfied +17489,56008,Male,Loyal Customer,35,Business travel,Business,2475,5,5,5,5,4,4,4,5,5,4,4,4,5,4,40,64.0,satisfied +17490,35216,Female,Loyal Customer,48,Business travel,Eco,1069,4,1,1,1,5,2,2,4,4,4,4,2,4,5,36,39.0,satisfied +17491,108568,Male,Loyal Customer,48,Business travel,Business,3943,4,4,4,4,5,5,5,5,5,5,5,3,5,3,2,0.0,satisfied +17492,58268,Female,Loyal Customer,45,Business travel,Business,678,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +17493,66467,Female,Loyal Customer,52,Business travel,Eco Plus,817,5,3,3,3,2,4,5,5,5,5,5,5,5,1,0,4.0,satisfied +17494,7487,Female,disloyal Customer,30,Business travel,Eco,925,2,3,3,3,1,3,1,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +17495,35026,Male,Loyal Customer,48,Business travel,Eco Plus,740,4,2,2,2,4,4,4,2,1,5,5,4,4,4,125,136.0,satisfied +17496,22089,Male,Loyal Customer,27,Business travel,Business,782,2,2,2,2,4,4,4,4,3,2,2,5,4,4,55,100.0,satisfied +17497,107896,Male,Loyal Customer,57,Business travel,Business,1782,1,1,1,1,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +17498,10788,Female,disloyal Customer,39,Business travel,Business,201,2,2,2,3,1,2,1,1,4,4,3,1,3,1,2,0.0,neutral or dissatisfied +17499,34215,Female,Loyal Customer,59,Personal Travel,Eco,1237,2,5,2,5,3,4,5,4,4,2,1,3,4,3,24,12.0,neutral or dissatisfied +17500,90538,Female,Loyal Customer,51,Business travel,Business,581,3,3,5,3,3,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +17501,26483,Female,Loyal Customer,49,Business travel,Eco Plus,842,4,1,4,4,1,5,3,4,4,4,4,3,4,4,0,0.0,satisfied +17502,11404,Female,Loyal Customer,29,Business travel,Business,2739,1,1,1,1,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +17503,5713,Male,Loyal Customer,33,Personal Travel,Eco,196,1,3,1,1,4,1,4,4,3,3,4,1,1,4,7,17.0,neutral or dissatisfied +17504,33746,Female,Loyal Customer,14,Personal Travel,Eco,2277,3,5,3,3,1,3,1,1,3,5,5,3,5,1,8,3.0,neutral or dissatisfied +17505,53826,Male,disloyal Customer,26,Business travel,Eco,191,4,0,4,4,3,4,4,3,1,3,4,5,3,3,34,28.0,neutral or dissatisfied +17506,125836,Male,Loyal Customer,41,Business travel,Business,861,5,5,5,5,3,5,4,4,4,4,4,4,4,5,6,0.0,satisfied +17507,16758,Male,Loyal Customer,36,Business travel,Business,3204,2,2,2,2,2,3,2,4,4,4,4,4,4,3,42,42.0,satisfied +17508,116341,Female,Loyal Customer,18,Personal Travel,Eco,296,3,3,3,3,4,3,4,4,1,2,3,2,3,4,0,0.0,neutral or dissatisfied +17509,123457,Male,Loyal Customer,46,Business travel,Business,2296,3,3,3,3,5,5,5,4,5,5,5,5,3,5,3,22.0,satisfied +17510,118957,Female,Loyal Customer,29,Personal Travel,Eco,682,4,2,3,3,1,3,1,1,1,2,4,4,3,1,2,0.0,neutral or dissatisfied +17511,53891,Female,Loyal Customer,20,Personal Travel,Eco,191,3,5,3,1,3,3,3,3,3,4,4,5,4,3,18,10.0,neutral or dissatisfied +17512,65836,Male,Loyal Customer,45,Business travel,Business,1389,5,5,3,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +17513,55765,Female,Loyal Customer,35,Personal Travel,Eco,224,2,4,2,3,1,2,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +17514,32023,Male,Loyal Customer,42,Business travel,Business,216,4,4,4,4,1,2,5,4,4,4,5,1,4,5,0,0.0,satisfied +17515,49041,Female,Loyal Customer,61,Business travel,Business,3880,4,4,4,4,5,5,5,1,1,1,2,5,2,5,171,164.0,satisfied +17516,11742,Male,disloyal Customer,24,Business travel,Eco,429,3,4,3,4,2,3,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +17517,81407,Male,Loyal Customer,39,Business travel,Business,2211,2,2,2,2,5,5,5,4,4,4,4,4,4,3,3,2.0,satisfied +17518,33363,Male,Loyal Customer,56,Business travel,Business,2614,2,2,2,2,2,4,2,4,4,5,4,1,4,3,0,0.0,satisfied +17519,42856,Female,Loyal Customer,50,Personal Travel,Eco,328,3,0,5,2,3,4,4,4,4,5,2,4,4,3,0,0.0,neutral or dissatisfied +17520,61409,Male,Loyal Customer,66,Personal Travel,Eco,679,3,4,3,3,2,3,3,2,3,3,4,4,5,2,4,0.0,neutral or dissatisfied +17521,37284,Male,disloyal Customer,30,Business travel,Eco,944,3,3,3,2,2,3,2,2,5,3,4,1,1,2,94,73.0,neutral or dissatisfied +17522,113340,Female,Loyal Customer,60,Business travel,Business,2979,4,4,4,4,2,4,5,4,4,4,4,4,4,5,36,26.0,satisfied +17523,61378,Female,Loyal Customer,32,Business travel,Business,1760,3,3,3,3,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +17524,117206,Female,Loyal Customer,42,Personal Travel,Eco,368,4,3,4,5,5,4,4,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +17525,68625,Female,disloyal Customer,27,Business travel,Business,175,3,2,2,4,3,2,3,3,4,4,5,5,4,3,11,7.0,neutral or dissatisfied +17526,85514,Male,Loyal Customer,59,Business travel,Business,1734,3,3,4,3,2,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +17527,107442,Male,Loyal Customer,7,Personal Travel,Eco,468,1,5,1,4,5,1,5,5,5,3,5,5,5,5,1,0.0,neutral or dissatisfied +17528,99390,Male,disloyal Customer,24,Business travel,Eco,337,4,0,4,3,2,4,2,2,3,4,5,5,4,2,23,6.0,neutral or dissatisfied +17529,88008,Female,Loyal Customer,41,Business travel,Business,3942,3,3,3,3,2,4,4,4,4,4,4,4,4,5,10,7.0,satisfied +17530,124873,Male,Loyal Customer,40,Business travel,Business,728,5,5,5,5,2,4,4,5,5,5,5,4,5,5,9,18.0,satisfied +17531,73033,Male,Loyal Customer,58,Personal Travel,Eco,1035,2,1,2,3,3,2,5,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +17532,1692,Male,Loyal Customer,34,Business travel,Business,1732,2,2,2,2,5,4,5,4,4,4,4,3,4,5,1,0.0,satisfied +17533,126010,Male,disloyal Customer,25,Business travel,Business,328,4,4,4,2,1,4,1,1,4,5,5,5,5,1,0,0.0,satisfied +17534,16482,Female,Loyal Customer,38,Business travel,Business,282,2,1,5,1,4,3,4,2,2,2,2,3,2,4,94,91.0,neutral or dissatisfied +17535,59623,Female,disloyal Customer,22,Business travel,Eco,854,4,5,5,4,1,5,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +17536,107204,Male,Loyal Customer,57,Personal Travel,Eco,402,1,4,5,2,1,5,1,1,3,5,4,5,4,1,4,2.0,neutral or dissatisfied +17537,128511,Male,Loyal Customer,14,Personal Travel,Eco,647,4,4,4,3,1,4,1,1,1,1,3,3,4,1,4,0.0,satisfied +17538,93780,Male,disloyal Customer,15,Business travel,Eco,845,2,2,2,3,4,2,4,4,2,1,4,1,1,4,0,0.0,neutral or dissatisfied +17539,84563,Male,Loyal Customer,67,Personal Travel,Eco,2504,4,5,4,1,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +17540,61435,Male,Loyal Customer,41,Business travel,Business,2419,4,4,2,4,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +17541,43437,Male,Loyal Customer,57,Business travel,Business,3352,3,2,2,2,1,4,4,3,3,3,3,2,3,4,113,129.0,neutral or dissatisfied +17542,112837,Male,Loyal Customer,40,Business travel,Business,3388,2,2,2,2,4,5,4,3,3,4,3,4,3,3,1,0.0,satisfied +17543,117672,Male,Loyal Customer,30,Business travel,Business,1449,1,1,1,1,4,4,4,4,5,4,4,3,5,4,2,0.0,satisfied +17544,91129,Female,Loyal Customer,14,Personal Travel,Eco,545,3,2,3,3,1,3,1,1,4,5,4,3,3,1,6,2.0,neutral or dissatisfied +17545,25301,Female,Loyal Customer,22,Business travel,Business,432,2,2,2,2,4,4,4,4,3,2,2,5,4,4,0,0.0,satisfied +17546,106951,Female,Loyal Customer,45,Business travel,Business,972,5,5,5,5,2,4,5,4,4,4,4,3,4,3,15,25.0,satisfied +17547,16268,Male,Loyal Customer,14,Business travel,Business,1939,1,5,5,5,1,1,1,1,3,3,3,4,4,1,89,88.0,neutral or dissatisfied +17548,67107,Female,Loyal Customer,45,Business travel,Business,3367,4,4,3,4,3,5,4,4,4,4,4,3,4,5,1,0.0,satisfied +17549,61476,Female,Loyal Customer,15,Business travel,Business,2419,1,1,1,1,1,1,1,1,1,5,3,3,3,1,2,5.0,neutral or dissatisfied +17550,86483,Male,Loyal Customer,13,Personal Travel,Eco,762,2,3,3,3,3,3,3,3,4,5,3,4,3,3,3,33.0,neutral or dissatisfied +17551,125422,Male,Loyal Customer,39,Business travel,Business,1832,2,4,4,4,5,3,4,2,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +17552,20381,Male,Loyal Customer,58,Business travel,Eco Plus,287,5,2,2,2,5,5,5,5,3,4,1,1,2,5,0,0.0,satisfied +17553,106780,Female,disloyal Customer,12,Business travel,Eco Plus,837,2,2,2,4,5,2,2,5,2,1,4,3,3,5,5,0.0,neutral or dissatisfied +17554,66453,Female,Loyal Customer,37,Personal Travel,Eco,1217,2,1,2,3,5,2,5,5,3,2,4,2,3,5,3,1.0,neutral or dissatisfied +17555,6484,Female,Loyal Customer,25,Business travel,Eco,557,3,5,5,5,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +17556,30867,Male,Loyal Customer,20,Business travel,Business,1607,2,4,4,4,2,2,2,2,1,5,1,2,1,2,0,0.0,neutral or dissatisfied +17557,691,Male,disloyal Customer,37,Business travel,Business,309,2,2,2,4,1,2,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +17558,2656,Female,Loyal Customer,52,Business travel,Business,539,2,2,2,2,3,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +17559,98513,Male,Loyal Customer,53,Business travel,Business,2329,4,4,4,4,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +17560,20679,Female,Loyal Customer,47,Personal Travel,Eco,552,3,3,3,4,2,2,5,4,4,3,4,3,4,1,108,95.0,neutral or dissatisfied +17561,28156,Male,Loyal Customer,22,Business travel,Eco,569,0,5,5,5,0,1,4,0,4,5,3,3,3,0,0,0.0,neutral or dissatisfied +17562,29122,Female,Loyal Customer,16,Personal Travel,Eco,954,3,5,3,2,2,3,2,2,1,5,4,1,5,2,0,15.0,neutral or dissatisfied +17563,20663,Male,Loyal Customer,39,Business travel,Eco,552,4,5,5,5,4,4,4,4,5,2,1,5,3,4,0,0.0,satisfied +17564,76758,Female,Loyal Customer,41,Business travel,Business,3027,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +17565,122833,Male,Loyal Customer,31,Business travel,Business,599,4,4,4,4,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +17566,13975,Female,Loyal Customer,30,Business travel,Eco Plus,153,5,2,4,4,5,5,5,5,4,5,5,5,3,5,23,7.0,satisfied +17567,110125,Male,Loyal Customer,52,Business travel,Business,882,3,3,3,3,4,4,4,4,4,4,4,3,4,4,2,3.0,satisfied +17568,80216,Male,Loyal Customer,36,Business travel,Business,2153,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +17569,31609,Female,Loyal Customer,70,Personal Travel,Eco,602,1,3,1,1,2,4,3,5,5,1,5,1,5,2,0,0.0,neutral or dissatisfied +17570,101477,Female,disloyal Customer,34,Business travel,Business,345,4,4,4,2,3,4,3,3,5,2,5,3,4,3,29,23.0,neutral or dissatisfied +17571,12141,Male,disloyal Customer,24,Business travel,Eco,1075,5,5,5,3,5,5,5,5,5,5,2,4,3,5,3,0.0,satisfied +17572,28412,Male,Loyal Customer,34,Business travel,Eco Plus,1709,3,4,4,4,3,3,3,3,4,3,2,2,2,3,4,0.0,neutral or dissatisfied +17573,14233,Male,Loyal Customer,32,Business travel,Eco Plus,692,0,0,0,2,2,0,2,2,2,3,1,1,3,2,0,0.0,satisfied +17574,30338,Male,Loyal Customer,25,Business travel,Business,2085,3,2,2,2,3,3,3,3,2,3,3,4,4,3,37,32.0,neutral or dissatisfied +17575,126746,Female,Loyal Customer,30,Personal Travel,Eco,2370,3,4,3,4,2,3,2,2,5,5,4,3,5,2,13,0.0,neutral or dissatisfied +17576,83464,Male,Loyal Customer,50,Business travel,Business,3195,1,1,4,1,3,4,4,4,4,4,4,4,4,5,8,2.0,satisfied +17577,70200,Male,disloyal Customer,34,Business travel,Eco,258,2,2,2,3,2,2,2,2,2,3,4,4,3,2,0,0.0,neutral or dissatisfied +17578,93896,Male,Loyal Customer,28,Personal Travel,Eco,590,4,5,4,3,2,4,2,2,3,4,3,3,2,2,0,12.0,neutral or dissatisfied +17579,61300,Female,Loyal Customer,34,Personal Travel,Eco,967,3,5,3,3,2,3,2,2,5,4,4,4,5,2,10,31.0,neutral or dissatisfied +17580,65154,Male,Loyal Customer,22,Personal Travel,Eco,190,2,5,2,5,3,2,2,3,5,2,5,3,4,3,51,44.0,neutral or dissatisfied +17581,84628,Male,Loyal Customer,20,Personal Travel,Eco,669,1,4,1,3,4,1,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +17582,68750,Female,Loyal Customer,39,Business travel,Business,3898,2,2,2,2,3,5,4,4,4,4,4,5,4,4,8,0.0,satisfied +17583,53824,Male,Loyal Customer,37,Business travel,Business,191,3,3,3,3,4,2,3,3,3,4,3,4,3,3,16,5.0,satisfied +17584,24351,Male,Loyal Customer,28,Personal Travel,Eco,634,3,3,3,4,2,3,2,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +17585,43010,Male,Loyal Customer,63,Business travel,Eco,236,5,3,3,3,5,5,5,5,4,2,4,4,2,5,30,23.0,satisfied +17586,62138,Male,Loyal Customer,51,Business travel,Business,2565,3,3,4,3,2,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +17587,88860,Male,disloyal Customer,34,Business travel,Eco Plus,406,1,1,1,3,4,1,5,4,4,5,3,1,2,4,0,0.0,neutral or dissatisfied +17588,91868,Female,Loyal Customer,59,Business travel,Business,2239,3,3,3,3,2,4,4,5,5,5,5,4,5,5,3,0.0,satisfied +17589,106990,Female,Loyal Customer,35,Personal Travel,Eco,972,2,1,1,3,3,1,3,3,2,3,3,2,3,3,0,3.0,neutral or dissatisfied +17590,52365,Female,Loyal Customer,48,Personal Travel,Eco,237,4,4,4,4,3,4,4,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +17591,22294,Female,Loyal Customer,46,Business travel,Business,143,5,5,5,5,3,3,2,5,5,5,5,3,5,5,25,20.0,satisfied +17592,25139,Female,Loyal Customer,27,Personal Travel,Eco,1249,1,5,1,3,4,1,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +17593,159,Female,Loyal Customer,46,Business travel,Business,227,4,4,4,4,5,3,5,5,5,5,5,4,5,1,0,0.0,satisfied +17594,75498,Male,Loyal Customer,59,Business travel,Business,2330,5,5,5,5,2,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +17595,84188,Male,Loyal Customer,53,Business travel,Business,2577,1,1,1,1,2,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +17596,73587,Female,disloyal Customer,21,Business travel,Eco,192,4,4,4,1,4,4,1,4,4,5,4,5,4,4,0,0.0,satisfied +17597,39688,Female,Loyal Customer,35,Business travel,Eco,1463,4,1,1,1,4,4,4,4,5,2,1,1,2,4,0,0.0,satisfied +17598,20644,Male,Loyal Customer,50,Business travel,Business,1897,1,1,1,1,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +17599,78950,Female,Loyal Customer,57,Business travel,Business,3142,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +17600,35336,Male,Loyal Customer,49,Business travel,Eco,944,1,3,3,3,1,1,1,1,4,4,3,1,4,1,15,10.0,neutral or dissatisfied +17601,127865,Female,disloyal Customer,38,Business travel,Business,1276,3,2,2,1,3,2,3,3,4,4,5,3,5,3,0,5.0,neutral or dissatisfied +17602,30285,Female,Loyal Customer,56,Business travel,Business,1476,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,13.0,satisfied +17603,126891,Male,Loyal Customer,58,Personal Travel,Eco,2296,4,5,4,1,3,4,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +17604,60188,Female,disloyal Customer,23,Business travel,Eco Plus,1182,3,2,3,3,5,3,5,5,1,2,4,1,3,5,0,7.0,neutral or dissatisfied +17605,8293,Female,Loyal Customer,67,Personal Travel,Eco,335,3,5,3,2,3,4,4,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +17606,61871,Male,Loyal Customer,29,Business travel,Business,2521,4,4,4,4,5,5,5,5,4,4,5,4,4,5,21,8.0,satisfied +17607,121949,Female,Loyal Customer,40,Business travel,Business,2280,1,1,1,1,5,4,5,4,4,4,4,3,4,3,12,2.0,satisfied +17608,7801,Male,disloyal Customer,38,Business travel,Eco,710,2,2,2,2,5,2,5,5,2,5,3,1,2,5,110,102.0,neutral or dissatisfied +17609,90652,Male,Loyal Customer,55,Business travel,Eco,594,4,4,2,4,4,4,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +17610,16140,Male,Loyal Customer,30,Business travel,Business,1741,3,3,4,3,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +17611,49492,Male,disloyal Customer,34,Business travel,Eco,372,3,4,3,2,4,3,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +17612,126086,Male,Loyal Customer,36,Business travel,Eco,547,3,4,1,4,3,3,3,3,2,1,3,1,4,3,10,0.0,neutral or dissatisfied +17613,38949,Male,Loyal Customer,34,Personal Travel,Eco Plus,320,1,3,1,1,5,1,5,5,5,5,2,1,4,5,0,0.0,neutral or dissatisfied +17614,24018,Female,disloyal Customer,38,Business travel,Eco,427,1,0,0,3,0,5,4,3,5,4,4,4,2,4,179,178.0,neutral or dissatisfied +17615,23736,Female,Loyal Customer,36,Personal Travel,Eco,771,4,5,4,2,2,4,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +17616,12750,Male,Loyal Customer,16,Personal Travel,Eco,803,4,1,4,3,4,4,4,4,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +17617,117496,Male,Loyal Customer,42,Business travel,Business,2369,3,4,4,4,2,4,3,3,3,3,3,4,3,1,26,18.0,neutral or dissatisfied +17618,42164,Male,Loyal Customer,44,Business travel,Business,748,5,5,5,5,5,1,4,4,4,4,4,2,4,5,0,2.0,satisfied +17619,53119,Female,Loyal Customer,54,Business travel,Eco,565,2,2,2,2,4,4,4,2,2,2,2,2,2,4,6,14.0,neutral or dissatisfied +17620,61721,Male,Loyal Customer,38,Business travel,Business,1608,3,1,1,1,5,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +17621,79701,Male,Loyal Customer,67,Personal Travel,Eco,760,3,5,3,1,4,3,4,4,4,2,4,4,4,4,0,4.0,neutral or dissatisfied +17622,128177,Male,Loyal Customer,16,Personal Travel,Eco,1972,5,4,5,1,5,5,5,5,5,5,4,4,4,5,0,18.0,satisfied +17623,103633,Female,Loyal Customer,45,Business travel,Business,2671,3,3,5,3,2,4,4,4,4,4,4,5,4,3,43,57.0,satisfied +17624,42336,Female,Loyal Customer,28,Personal Travel,Eco,550,3,4,3,4,5,3,5,5,2,4,4,3,4,5,0,0.0,neutral or dissatisfied +17625,7701,Female,Loyal Customer,53,Personal Travel,Eco,767,1,5,1,2,4,5,4,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +17626,122098,Female,Loyal Customer,51,Personal Travel,Eco,130,2,5,2,4,5,5,4,1,1,2,1,5,1,4,6,0.0,neutral or dissatisfied +17627,19856,Male,disloyal Customer,25,Business travel,Eco,693,2,2,2,3,4,2,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +17628,22324,Female,Loyal Customer,48,Business travel,Business,143,4,4,4,4,4,3,4,5,5,5,5,4,5,5,7,0.0,satisfied +17629,24575,Female,Loyal Customer,29,Business travel,Eco Plus,696,0,0,0,1,4,0,4,4,2,5,3,2,1,4,0,0.0,satisfied +17630,50623,Male,Loyal Customer,58,Personal Travel,Eco,89,2,5,0,3,5,0,5,5,3,1,4,4,4,5,0,0.0,neutral or dissatisfied +17631,80632,Female,Loyal Customer,43,Business travel,Business,282,1,1,5,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +17632,40272,Female,Loyal Customer,10,Personal Travel,Eco,436,0,5,0,2,2,0,2,2,3,5,4,4,5,2,0,0.0,satisfied +17633,27577,Male,Loyal Customer,65,Personal Travel,Eco,697,2,1,2,4,3,2,3,3,1,3,4,1,3,3,0,3.0,neutral or dissatisfied +17634,90647,Male,Loyal Customer,41,Business travel,Business,3610,5,5,5,5,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +17635,70508,Female,Loyal Customer,13,Personal Travel,Eco,867,3,3,3,1,4,3,4,4,5,1,4,1,5,4,77,70.0,neutral or dissatisfied +17636,61740,Female,Loyal Customer,57,Business travel,Business,3660,2,5,5,5,4,3,3,3,3,3,2,2,3,1,3,0.0,neutral or dissatisfied +17637,58375,Male,disloyal Customer,23,Business travel,Eco,733,4,3,3,5,1,3,3,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +17638,11512,Male,Loyal Customer,32,Personal Travel,Eco Plus,308,3,4,3,3,2,3,2,2,3,2,4,5,5,2,8,2.0,neutral or dissatisfied +17639,31093,Male,Loyal Customer,46,Business travel,Business,2360,4,4,4,4,4,2,5,5,5,4,5,1,5,4,0,5.0,satisfied +17640,109469,Male,disloyal Customer,24,Business travel,Eco,920,4,4,4,3,2,4,2,2,5,4,5,4,5,2,59,58.0,satisfied +17641,13025,Female,Loyal Customer,34,Personal Travel,Eco,374,3,4,5,3,4,5,4,4,5,4,5,5,4,4,2,0.0,neutral or dissatisfied +17642,69265,Male,Loyal Customer,55,Personal Travel,Eco,733,3,3,3,3,1,3,1,1,4,3,4,3,2,1,0,0.0,neutral or dissatisfied +17643,61633,Male,Loyal Customer,34,Business travel,Business,1346,4,4,4,4,3,5,5,5,5,4,5,4,5,5,4,0.0,satisfied +17644,75261,Female,Loyal Customer,30,Personal Travel,Eco,1846,4,4,4,5,2,4,2,2,4,4,3,5,4,2,3,4.0,neutral or dissatisfied +17645,67564,Male,disloyal Customer,48,Business travel,Business,1464,4,5,5,3,4,4,4,4,3,5,4,3,4,4,15,10.0,satisfied +17646,65525,Male,Loyal Customer,27,Personal Travel,Eco,1616,1,5,1,1,3,1,5,3,3,5,4,5,4,3,64,63.0,neutral or dissatisfied +17647,111755,Male,Loyal Customer,40,Business travel,Business,1436,3,3,3,3,4,4,5,4,4,4,4,5,4,3,10,0.0,satisfied +17648,453,Male,Loyal Customer,55,Business travel,Business,134,4,4,4,4,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +17649,4497,Male,disloyal Customer,25,Business travel,Eco,435,2,2,2,3,5,2,5,5,3,5,4,1,3,5,0,0.0,neutral or dissatisfied +17650,4878,Female,Loyal Customer,40,Personal Travel,Eco,408,2,5,2,3,5,2,5,5,4,5,4,3,4,5,0,5.0,neutral or dissatisfied +17651,50430,Female,disloyal Customer,17,Business travel,Eco,109,1,2,1,4,5,1,5,5,3,4,4,4,4,5,59,69.0,neutral or dissatisfied +17652,114169,Female,Loyal Customer,51,Business travel,Business,3429,1,1,1,1,2,4,5,4,4,5,4,4,4,5,6,0.0,satisfied +17653,42130,Male,Loyal Customer,25,Business travel,Eco Plus,991,1,5,5,5,1,1,4,1,3,2,3,3,4,1,32,22.0,neutral or dissatisfied +17654,26753,Female,Loyal Customer,29,Business travel,Business,859,1,0,0,3,4,0,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +17655,87772,Male,Loyal Customer,45,Business travel,Business,2131,0,4,0,2,4,5,5,4,4,4,3,5,4,4,25,16.0,satisfied +17656,128500,Female,Loyal Customer,69,Personal Travel,Eco,621,3,4,3,4,3,5,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +17657,73584,Male,Loyal Customer,38,Business travel,Business,192,4,4,4,4,4,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +17658,68714,Male,Loyal Customer,57,Personal Travel,Eco,175,3,4,3,2,5,3,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +17659,51302,Female,Loyal Customer,50,Business travel,Eco Plus,89,4,4,4,4,3,5,3,3,3,4,3,3,3,1,0,0.0,satisfied +17660,116036,Female,Loyal Customer,49,Personal Travel,Eco,480,4,1,4,1,2,2,1,2,2,4,2,3,2,1,2,0.0,satisfied +17661,105750,Female,Loyal Customer,40,Business travel,Business,2669,4,4,4,4,3,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +17662,89897,Female,Loyal Customer,43,Business travel,Business,1310,4,4,4,4,2,4,5,5,5,5,5,4,5,4,23,4.0,satisfied +17663,40160,Male,Loyal Customer,19,Personal Travel,Business,436,1,5,5,3,5,5,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +17664,129544,Male,Loyal Customer,51,Business travel,Business,2342,5,5,5,5,2,3,4,5,5,5,5,4,5,5,2,15.0,satisfied +17665,89127,Male,Loyal Customer,40,Business travel,Business,2139,3,3,3,3,2,3,5,2,2,2,2,4,2,4,7,0.0,satisfied +17666,122648,Male,disloyal Customer,39,Business travel,Business,361,3,3,3,5,1,3,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +17667,20786,Female,Loyal Customer,46,Business travel,Eco,515,4,5,5,5,3,3,4,4,4,4,4,1,4,2,5,6.0,satisfied +17668,119067,Female,disloyal Customer,28,Business travel,Business,1107,2,2,2,3,1,2,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +17669,45602,Female,Loyal Customer,23,Business travel,Business,2567,2,4,4,4,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +17670,108631,Female,Loyal Customer,47,Business travel,Business,1547,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +17671,64175,Female,disloyal Customer,29,Business travel,Business,989,2,2,2,3,4,2,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +17672,33384,Female,Loyal Customer,69,Personal Travel,Eco,2556,2,5,2,3,3,3,4,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +17673,7370,Male,Loyal Customer,66,Personal Travel,Eco,783,2,5,2,2,5,2,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +17674,25820,Female,Loyal Customer,52,Personal Travel,Eco,1747,3,0,2,2,2,4,4,1,1,2,1,4,1,3,50,37.0,neutral or dissatisfied +17675,77157,Female,Loyal Customer,60,Business travel,Business,1450,3,3,3,3,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +17676,50812,Male,Loyal Customer,19,Personal Travel,Eco,109,3,5,0,1,5,0,5,5,5,1,2,1,1,5,86,72.0,neutral or dissatisfied +17677,849,Female,Loyal Customer,38,Business travel,Business,2885,3,1,4,1,5,3,4,3,3,3,3,4,3,1,4,8.0,neutral or dissatisfied +17678,67220,Female,Loyal Customer,21,Personal Travel,Eco,1119,2,4,2,2,5,2,5,5,3,3,5,3,4,5,0,15.0,neutral or dissatisfied +17679,119286,Male,Loyal Customer,39,Business travel,Business,214,0,4,0,2,3,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +17680,125761,Female,Loyal Customer,48,Business travel,Business,3635,5,5,5,5,5,5,4,5,5,5,5,3,5,4,56,64.0,satisfied +17681,90790,Male,Loyal Customer,24,Business travel,Business,1706,2,2,2,2,5,4,5,5,4,5,4,3,4,5,0,9.0,satisfied +17682,21071,Male,Loyal Customer,36,Business travel,Business,106,5,5,5,5,5,3,4,5,5,5,5,3,5,2,89,84.0,satisfied +17683,1372,Female,disloyal Customer,27,Business travel,Business,282,2,2,2,4,4,2,4,4,2,1,3,4,4,4,17,28.0,neutral or dissatisfied +17684,99220,Female,Loyal Customer,48,Business travel,Business,541,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +17685,36227,Female,Loyal Customer,44,Personal Travel,Eco,496,3,3,3,4,3,4,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +17686,66896,Male,Loyal Customer,44,Business travel,Business,2946,3,2,4,2,2,3,2,3,3,3,3,1,3,4,20,3.0,neutral or dissatisfied +17687,9537,Female,Loyal Customer,43,Business travel,Business,1666,2,2,2,2,2,5,5,3,3,4,3,4,3,4,0,6.0,satisfied +17688,24244,Female,Loyal Customer,30,Personal Travel,Eco,147,4,5,4,2,1,4,1,1,3,5,4,4,4,1,0,0.0,satisfied +17689,99859,Male,Loyal Customer,19,Personal Travel,Eco,587,2,4,2,3,4,2,4,4,4,2,4,4,5,4,33,39.0,neutral or dissatisfied +17690,30008,Female,Loyal Customer,30,Business travel,Business,3350,0,3,0,2,5,5,5,5,4,2,1,1,4,5,0,0.0,satisfied +17691,101682,Male,disloyal Customer,38,Business travel,Business,1500,3,3,3,2,4,3,4,4,5,4,4,3,5,4,28,25.0,neutral or dissatisfied +17692,7929,Male,Loyal Customer,32,Personal Travel,Eco,864,3,0,3,3,3,3,3,3,4,5,3,3,2,3,0,0.0,neutral or dissatisfied +17693,32718,Female,Loyal Customer,62,Business travel,Business,2808,1,5,3,5,4,3,3,3,3,3,1,3,3,1,0,0.0,neutral or dissatisfied +17694,114435,Male,disloyal Customer,38,Business travel,Business,480,4,4,4,1,5,4,5,5,5,5,4,3,4,5,0,0.0,satisfied +17695,103085,Female,Loyal Customer,48,Personal Travel,Eco,460,4,4,4,4,2,4,4,4,4,4,4,2,4,4,5,0.0,satisfied +17696,10652,Male,Loyal Customer,35,Business travel,Business,2571,3,3,3,3,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +17697,67437,Female,Loyal Customer,59,Business travel,Business,3063,2,2,2,2,2,3,3,5,5,5,5,3,5,3,47,45.0,satisfied +17698,14394,Male,disloyal Customer,37,Business travel,Eco,500,1,4,1,3,1,1,1,1,1,1,3,1,4,1,46,42.0,neutral or dissatisfied +17699,29273,Male,Loyal Customer,38,Business travel,Eco,569,4,5,5,5,4,4,4,4,1,2,4,1,4,4,120,115.0,neutral or dissatisfied +17700,51552,Female,Loyal Customer,42,Business travel,Business,2077,3,3,3,3,2,3,2,4,4,4,4,3,4,3,0,0.0,satisfied +17701,59985,Female,Loyal Customer,49,Personal Travel,Eco,937,4,5,4,3,2,5,5,2,2,4,2,5,2,4,10,0.0,satisfied +17702,84449,Female,Loyal Customer,42,Business travel,Business,1769,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +17703,95057,Female,Loyal Customer,57,Personal Travel,Eco,189,3,5,3,1,4,4,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +17704,90133,Female,disloyal Customer,18,Business travel,Business,983,4,0,4,3,1,4,1,1,4,3,4,3,5,1,5,0.0,satisfied +17705,15165,Female,Loyal Customer,48,Business travel,Business,416,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +17706,122055,Female,Loyal Customer,42,Business travel,Business,185,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +17707,8263,Female,Loyal Customer,60,Personal Travel,Eco,125,4,4,4,3,1,3,4,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +17708,122220,Female,Loyal Customer,29,Business travel,Business,3095,2,2,2,2,2,2,2,2,1,3,4,3,3,2,0,8.0,neutral or dissatisfied +17709,39604,Male,Loyal Customer,27,Personal Travel,Eco,679,3,4,3,4,2,3,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +17710,33909,Male,Loyal Customer,51,Business travel,Business,1643,1,4,4,4,5,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +17711,2504,Male,Loyal Customer,50,Business travel,Business,1691,0,0,0,1,5,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +17712,177,Female,Loyal Customer,10,Personal Travel,Eco Plus,227,1,4,1,2,1,1,1,1,4,4,4,3,5,1,39,56.0,neutral or dissatisfied +17713,3341,Female,Loyal Customer,52,Business travel,Business,296,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,6.0,satisfied +17714,41336,Female,disloyal Customer,25,Personal Travel,Eco,689,1,4,1,1,5,1,5,5,3,5,4,3,5,5,24,13.0,neutral or dissatisfied +17715,33582,Male,Loyal Customer,57,Business travel,Eco,399,4,4,4,4,4,4,4,4,5,3,4,4,3,4,0,0.0,satisfied +17716,30775,Female,Loyal Customer,22,Personal Travel,Business,895,3,4,3,5,5,3,5,5,3,3,1,3,5,5,0,0.0,neutral or dissatisfied +17717,42825,Male,Loyal Customer,61,Business travel,Business,1916,4,4,4,4,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +17718,104039,Male,Loyal Customer,62,Business travel,Business,1044,3,3,3,3,2,4,5,4,4,4,4,3,4,4,7,0.0,satisfied +17719,41481,Male,disloyal Customer,23,Business travel,Eco,1377,5,5,5,2,3,5,2,3,4,1,2,2,3,3,47,54.0,satisfied +17720,129076,Female,disloyal Customer,28,Business travel,Business,2342,2,2,2,2,2,2,2,2,5,2,4,4,5,2,70,31.0,neutral or dissatisfied +17721,5465,Female,Loyal Customer,10,Personal Travel,Eco,265,3,2,3,2,3,3,3,3,2,5,1,3,1,3,0,4.0,neutral or dissatisfied +17722,120355,Male,disloyal Customer,36,Business travel,Business,337,3,3,3,3,5,3,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +17723,109215,Male,disloyal Customer,20,Business travel,Eco,391,3,4,3,4,2,3,2,2,4,3,4,4,3,2,32,15.0,neutral or dissatisfied +17724,83070,Female,Loyal Customer,10,Business travel,Eco,983,4,5,5,5,4,4,2,4,2,5,4,1,4,4,0,8.0,neutral or dissatisfied +17725,114692,Female,disloyal Customer,42,Business travel,Business,308,2,2,2,4,5,2,5,5,3,4,4,3,4,5,0,0.0,satisfied +17726,124505,Male,Loyal Customer,24,Business travel,Business,3662,5,5,5,5,5,5,5,5,1,2,5,2,1,5,0,0.0,satisfied +17727,122820,Male,Loyal Customer,17,Personal Travel,Eco,599,4,5,4,5,3,4,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +17728,14325,Female,Loyal Customer,14,Personal Travel,Eco,395,0,3,0,3,4,0,4,4,2,3,3,4,4,4,0,0.0,satisfied +17729,64256,Male,Loyal Customer,31,Personal Travel,Eco,1660,3,4,3,4,1,3,1,1,5,4,4,4,5,1,0,13.0,neutral or dissatisfied +17730,23311,Male,disloyal Customer,26,Business travel,Business,359,5,5,5,3,5,5,5,5,4,4,4,3,4,5,11,4.0,satisfied +17731,93732,Male,Loyal Customer,48,Personal Travel,Eco Plus,630,1,1,1,2,4,1,4,4,1,4,2,4,2,4,12,22.0,neutral or dissatisfied +17732,20859,Female,Loyal Customer,27,Personal Travel,Eco,457,3,3,3,4,5,3,5,5,1,1,4,4,4,5,4,9.0,neutral or dissatisfied +17733,125755,Female,Loyal Customer,45,Business travel,Business,861,2,2,2,2,5,5,4,5,5,5,5,4,5,5,8,1.0,satisfied +17734,57996,Female,Loyal Customer,48,Business travel,Business,1943,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,24.0,satisfied +17735,112178,Female,Loyal Customer,29,Personal Travel,Eco,895,5,5,4,2,4,4,4,4,3,5,3,2,1,4,2,0.0,satisfied +17736,13466,Female,Loyal Customer,69,Personal Travel,Eco,491,1,2,1,3,3,2,3,4,4,1,4,4,4,3,119,124.0,neutral or dissatisfied +17737,19008,Male,Loyal Customer,28,Business travel,Business,2828,3,3,3,3,3,2,3,3,4,5,2,1,3,3,10,11.0,neutral or dissatisfied +17738,120070,Male,Loyal Customer,49,Business travel,Business,683,4,5,4,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +17739,84598,Male,Loyal Customer,39,Business travel,Business,3399,5,4,5,5,5,5,5,4,4,4,4,3,4,5,2,0.0,satisfied +17740,69884,Male,disloyal Customer,14,Business travel,Eco,782,1,1,1,3,2,1,1,2,1,3,2,3,4,2,0,0.0,neutral or dissatisfied +17741,25983,Female,disloyal Customer,33,Business travel,Eco,577,3,0,3,1,2,3,2,2,4,2,5,1,1,2,3,5.0,neutral or dissatisfied +17742,79592,Male,Loyal Customer,37,Business travel,Business,712,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +17743,128980,Male,Loyal Customer,68,Personal Travel,Eco,236,3,3,3,4,2,3,2,2,1,3,5,1,1,2,0,0.0,neutral or dissatisfied +17744,99408,Male,disloyal Customer,24,Business travel,Eco,337,1,5,1,3,3,1,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +17745,34443,Female,Loyal Customer,46,Personal Travel,Eco Plus,2422,2,3,2,2,2,2,2,1,1,3,4,2,4,2,92,107.0,neutral or dissatisfied +17746,94457,Female,Loyal Customer,44,Business travel,Business,2998,5,4,5,5,5,4,5,4,4,4,4,4,4,4,21,15.0,satisfied +17747,113916,Female,Loyal Customer,56,Personal Travel,Eco Plus,2295,3,5,3,4,4,4,4,2,2,3,2,5,2,4,0,13.0,neutral or dissatisfied +17748,77440,Female,Loyal Customer,50,Personal Travel,Eco Plus,588,2,4,2,5,2,4,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +17749,2653,Male,Loyal Customer,43,Business travel,Business,3084,3,3,1,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +17750,72594,Female,Loyal Customer,57,Personal Travel,Eco,1017,2,5,2,3,3,5,5,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +17751,26285,Female,Loyal Customer,27,Business travel,Eco Plus,859,4,5,5,5,4,4,4,4,1,5,1,4,3,4,23,0.0,satisfied +17752,112991,Female,Loyal Customer,59,Business travel,Business,1797,3,3,3,3,5,4,5,5,5,4,5,4,5,4,8,0.0,satisfied +17753,78858,Female,Loyal Customer,23,Personal Travel,Eco Plus,528,1,5,1,5,4,1,4,4,5,5,4,5,5,4,5,19.0,neutral or dissatisfied +17754,50183,Male,Loyal Customer,44,Business travel,Eco,193,2,4,4,4,2,2,2,2,3,5,2,3,2,2,0,0.0,neutral or dissatisfied +17755,96696,Male,Loyal Customer,45,Business travel,Business,696,5,5,5,5,3,5,4,5,5,5,5,5,5,3,56,49.0,satisfied +17756,2362,Female,Loyal Customer,57,Business travel,Business,925,2,2,2,2,5,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +17757,97929,Male,Loyal Customer,34,Business travel,Business,3531,1,1,1,1,3,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +17758,50246,Female,disloyal Customer,25,Business travel,Eco,373,3,0,3,2,4,3,4,4,1,5,2,3,2,4,7,0.0,neutral or dissatisfied +17759,48872,Male,Loyal Customer,55,Business travel,Business,89,1,1,1,1,2,4,3,3,3,4,3,3,3,2,49,59.0,satisfied +17760,85062,Male,Loyal Customer,50,Business travel,Business,689,1,1,1,1,3,4,4,5,5,5,5,3,5,4,93,73.0,satisfied +17761,85482,Female,Loyal Customer,39,Personal Travel,Eco,152,3,4,3,3,2,3,2,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +17762,30935,Female,disloyal Customer,38,Business travel,Eco,1024,2,2,2,2,4,2,5,4,4,4,4,4,3,4,46,36.0,neutral or dissatisfied +17763,96083,Male,Loyal Customer,45,Personal Travel,Eco,1235,1,4,1,2,2,1,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +17764,44474,Male,Loyal Customer,57,Personal Travel,Eco Plus,299,2,4,2,3,5,2,5,5,5,4,4,3,5,5,5,9.0,neutral or dissatisfied +17765,38076,Male,Loyal Customer,47,Business travel,Business,1220,1,1,1,1,1,1,3,4,4,4,4,4,4,2,23,1.0,satisfied +17766,113594,Female,disloyal Customer,38,Business travel,Eco,197,3,3,3,4,5,3,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +17767,38788,Female,Loyal Customer,38,Business travel,Business,1992,0,0,0,3,5,2,2,4,4,4,4,1,4,2,0,0.0,satisfied +17768,30384,Female,Loyal Customer,65,Business travel,Business,241,4,2,2,2,5,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +17769,91458,Male,disloyal Customer,23,Business travel,Eco,859,4,4,4,2,4,3,3,4,4,4,4,3,3,3,129,133.0,satisfied +17770,79541,Male,disloyal Customer,26,Business travel,Business,762,3,3,3,2,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +17771,65879,Male,Loyal Customer,35,Business travel,Eco Plus,1389,2,3,3,3,2,2,2,2,1,1,4,1,4,2,3,0.0,neutral or dissatisfied +17772,70544,Male,Loyal Customer,25,Business travel,Business,1258,5,5,5,5,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +17773,108509,Male,Loyal Customer,41,Business travel,Business,519,1,4,4,4,1,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +17774,107966,Male,disloyal Customer,23,Business travel,Eco,825,4,4,4,3,4,4,4,3,2,5,4,4,4,4,257,246.0,neutral or dissatisfied +17775,82087,Male,disloyal Customer,21,Business travel,Eco,1276,4,4,4,4,2,4,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +17776,22715,Female,Loyal Customer,49,Personal Travel,Eco Plus,589,1,4,1,1,1,5,5,5,5,1,5,2,5,3,0,0.0,neutral or dissatisfied +17777,77062,Male,Loyal Customer,34,Business travel,Business,3744,2,2,2,2,3,4,4,4,4,4,4,3,4,4,0,3.0,satisfied +17778,127636,Male,Loyal Customer,49,Personal Travel,Eco,1773,1,2,1,3,1,1,1,1,1,3,3,4,3,1,2,0.0,neutral or dissatisfied +17779,84884,Female,disloyal Customer,39,Personal Travel,Eco,481,2,4,2,5,2,2,2,2,2,3,3,5,2,2,0,0.0,neutral or dissatisfied +17780,6603,Female,Loyal Customer,69,Personal Travel,Eco,618,2,4,2,3,3,5,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +17781,80267,Male,Loyal Customer,34,Business travel,Business,488,2,2,2,2,3,4,5,5,5,5,5,4,5,5,130,114.0,satisfied +17782,116426,Male,Loyal Customer,9,Personal Travel,Eco,446,4,5,4,5,5,4,5,5,5,2,4,4,4,5,45,42.0,neutral or dissatisfied +17783,10084,Male,Loyal Customer,56,Business travel,Business,266,1,1,1,1,3,5,4,4,4,4,4,3,4,4,43,44.0,satisfied +17784,70907,Male,Loyal Customer,56,Personal Travel,Eco,1721,2,5,2,1,2,2,2,2,4,5,4,4,4,2,17,30.0,neutral or dissatisfied +17785,48673,Male,Loyal Customer,37,Business travel,Business,262,2,4,2,2,5,4,4,5,5,5,5,5,5,5,0,9.0,satisfied +17786,72374,Male,Loyal Customer,47,Business travel,Business,2582,5,5,5,5,5,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +17787,34939,Male,Loyal Customer,52,Personal Travel,Eco,395,4,4,4,2,1,4,5,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +17788,75529,Male,Loyal Customer,56,Business travel,Business,337,3,4,4,4,3,3,3,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +17789,40849,Male,Loyal Customer,11,Personal Travel,Eco,532,5,1,5,2,2,5,1,2,4,5,3,1,2,2,0,0.0,satisfied +17790,118222,Male,Loyal Customer,21,Personal Travel,Eco,735,1,4,1,1,2,1,2,2,3,3,4,4,4,2,83,82.0,neutral or dissatisfied +17791,64193,Female,Loyal Customer,57,Business travel,Business,2614,2,2,2,2,5,4,5,4,4,4,4,5,4,3,92,63.0,satisfied +17792,88549,Male,Loyal Customer,50,Personal Travel,Eco,240,1,3,1,4,3,1,3,3,3,2,4,3,4,3,0,3.0,neutral or dissatisfied +17793,118347,Male,Loyal Customer,28,Personal Travel,Eco,602,3,5,3,2,4,3,2,4,3,4,4,4,4,4,18,10.0,neutral or dissatisfied +17794,87379,Male,Loyal Customer,50,Business travel,Business,3106,4,3,2,3,2,3,4,4,4,4,4,4,4,4,0,12.0,neutral or dissatisfied +17795,34881,Male,Loyal Customer,31,Business travel,Eco Plus,2248,0,0,0,3,0,3,1,4,2,4,2,1,4,1,48,63.0,satisfied +17796,104180,Male,Loyal Customer,7,Personal Travel,Eco,349,4,5,3,4,3,3,3,3,4,2,4,4,4,3,21,100.0,neutral or dissatisfied +17797,48132,Female,Loyal Customer,35,Business travel,Eco,173,5,5,5,5,5,5,5,5,3,4,3,2,4,5,14,19.0,satisfied +17798,25838,Male,disloyal Customer,10,Business travel,Eco,484,3,3,3,3,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +17799,96069,Male,Loyal Customer,31,Personal Travel,Eco,758,3,3,4,4,1,4,1,1,2,2,2,3,5,1,15,21.0,neutral or dissatisfied +17800,48425,Male,Loyal Customer,44,Business travel,Eco,844,4,4,4,4,4,4,4,4,1,4,1,2,3,4,0,0.0,satisfied +17801,78466,Male,Loyal Customer,46,Business travel,Business,666,1,1,4,1,4,4,4,2,2,2,2,4,2,5,11,0.0,satisfied +17802,42441,Female,Loyal Customer,60,Personal Travel,Eco Plus,1119,4,5,4,1,2,5,4,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +17803,14390,Male,disloyal Customer,36,Business travel,Eco,789,3,3,3,4,5,3,5,5,2,1,1,1,3,5,42,32.0,neutral or dissatisfied +17804,22115,Male,Loyal Customer,25,Business travel,Business,2648,3,3,3,3,3,3,3,3,1,2,4,1,4,3,0,2.0,satisfied +17805,122853,Male,Loyal Customer,53,Business travel,Business,226,0,0,0,2,4,4,5,2,2,2,2,5,2,5,5,0.0,satisfied +17806,70211,Female,Loyal Customer,9,Personal Travel,Eco,258,2,4,0,1,1,0,1,1,1,4,1,3,3,1,0,0.0,neutral or dissatisfied +17807,118911,Female,Loyal Customer,42,Personal Travel,Eco,587,4,5,4,3,3,5,4,3,3,4,3,4,3,3,5,0.0,satisfied +17808,20686,Female,Loyal Customer,35,Business travel,Business,2665,1,1,1,1,2,1,2,4,4,5,4,3,4,2,0,,satisfied +17809,21558,Female,disloyal Customer,21,Business travel,Eco,164,2,0,2,3,3,2,3,3,4,5,5,2,2,3,11,6.0,neutral or dissatisfied +17810,18123,Female,disloyal Customer,21,Business travel,Eco,120,2,0,2,2,2,2,2,2,1,4,5,4,1,2,0,0.0,neutral or dissatisfied +17811,70407,Male,Loyal Customer,31,Personal Travel,Eco,1562,2,3,2,3,1,2,1,1,2,2,4,4,3,1,2,0.0,neutral or dissatisfied +17812,127406,Female,disloyal Customer,24,Business travel,Eco,872,1,1,1,4,3,1,3,3,2,4,3,4,3,3,0,1.0,neutral or dissatisfied +17813,108213,Male,disloyal Customer,40,Business travel,Eco,777,1,2,2,4,4,2,4,4,3,1,3,1,3,4,14,13.0,neutral or dissatisfied +17814,78869,Male,Loyal Customer,28,Personal Travel,Eco,1995,3,4,3,3,4,3,4,4,4,5,2,1,3,4,1,0.0,neutral or dissatisfied +17815,97419,Male,Loyal Customer,28,Business travel,Business,587,4,4,4,4,4,4,4,4,1,2,4,2,4,4,26,19.0,neutral or dissatisfied +17816,127662,Female,disloyal Customer,27,Business travel,Business,2153,3,3,3,2,1,3,1,1,4,3,5,3,4,1,0,6.0,neutral or dissatisfied +17817,28907,Male,disloyal Customer,27,Business travel,Eco,1050,2,2,2,4,5,2,5,5,1,4,1,5,2,5,0,0.0,neutral or dissatisfied +17818,26,Male,Loyal Customer,47,Business travel,Business,1676,4,4,5,4,5,4,5,5,5,5,4,5,5,5,0,15.0,satisfied +17819,114759,Male,Loyal Customer,52,Business travel,Business,3169,2,2,2,2,2,4,5,5,5,5,5,4,5,3,23,24.0,satisfied +17820,2451,Female,Loyal Customer,47,Business travel,Business,2378,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,8.0,satisfied +17821,43306,Female,Loyal Customer,36,Business travel,Business,1695,4,4,5,4,5,2,1,5,5,4,5,2,5,1,0,0.0,satisfied +17822,30834,Female,Loyal Customer,31,Personal Travel,Eco,1028,3,5,2,5,2,1,1,3,5,4,5,1,5,1,155,135.0,neutral or dissatisfied +17823,10617,Female,Loyal Customer,23,Business travel,Business,429,5,5,5,5,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +17824,36121,Female,Loyal Customer,45,Business travel,Eco,1609,5,4,4,4,3,4,4,5,5,5,5,1,5,1,0,13.0,satisfied +17825,3932,Female,Loyal Customer,18,Business travel,Business,2620,3,4,4,4,3,3,3,3,1,5,3,3,3,3,74,86.0,neutral or dissatisfied +17826,121584,Female,Loyal Customer,32,Business travel,Business,2652,3,4,4,4,3,2,3,3,3,3,3,1,4,3,13,9.0,neutral or dissatisfied +17827,101983,Male,Loyal Customer,45,Personal Travel,Eco,628,1,5,1,1,1,1,1,1,5,4,5,3,5,1,7,0.0,neutral or dissatisfied +17828,127803,Female,disloyal Customer,24,Business travel,Eco,1044,5,5,5,3,3,5,3,3,3,5,5,4,5,3,0,6.0,satisfied +17829,110318,Female,disloyal Customer,21,Business travel,Eco,842,4,4,4,2,3,4,3,3,3,2,5,5,4,3,42,42.0,satisfied +17830,64826,Female,Loyal Customer,33,Business travel,Business,3088,2,1,5,5,3,3,2,2,2,2,2,4,2,4,6,15.0,neutral or dissatisfied +17831,8936,Male,Loyal Customer,45,Business travel,Business,402,4,4,5,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +17832,63408,Female,Loyal Customer,40,Personal Travel,Eco,447,3,4,3,1,1,3,1,1,2,4,5,3,1,1,0,0.0,neutral or dissatisfied +17833,37640,Female,Loyal Customer,21,Personal Travel,Eco,1056,0,4,0,2,5,0,5,5,2,1,3,3,2,5,0,0.0,satisfied +17834,12342,Male,disloyal Customer,37,Business travel,Eco,253,3,0,3,3,2,3,2,2,1,3,2,4,3,2,0,0.0,neutral or dissatisfied +17835,49960,Female,disloyal Customer,36,Business travel,Eco,326,3,1,3,4,3,3,4,3,4,4,3,4,3,3,13,49.0,neutral or dissatisfied +17836,98925,Female,Loyal Customer,42,Business travel,Business,1803,2,2,2,2,2,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +17837,100374,Male,Loyal Customer,12,Personal Travel,Eco,1011,2,4,1,1,5,1,5,5,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +17838,75965,Male,Loyal Customer,48,Business travel,Business,3008,2,5,2,2,2,5,4,4,4,5,4,4,4,3,1,24.0,satisfied +17839,67418,Male,Loyal Customer,56,Business travel,Business,641,3,3,4,3,4,4,4,3,3,3,3,3,3,5,4,0.0,satisfied +17840,108491,Female,Loyal Customer,59,Personal Travel,Eco,570,5,5,5,4,2,5,4,1,1,5,1,5,1,4,0,0.0,satisfied +17841,14514,Female,disloyal Customer,21,Business travel,Eco Plus,328,3,4,3,4,5,3,5,5,3,3,3,3,4,5,28,18.0,neutral or dissatisfied +17842,58935,Female,Loyal Customer,42,Personal Travel,Eco,888,1,4,1,1,2,1,4,3,3,1,3,4,3,5,1,6.0,neutral or dissatisfied +17843,66795,Female,Loyal Customer,18,Personal Travel,Eco,3784,3,5,3,3,3,2,5,5,2,5,4,5,3,5,0,0.0,neutral or dissatisfied +17844,77971,Female,disloyal Customer,39,Business travel,Business,152,1,1,1,1,2,1,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +17845,8480,Male,Loyal Customer,9,Personal Travel,Eco,1187,1,5,1,4,1,1,1,1,3,5,4,4,5,1,12,18.0,neutral or dissatisfied +17846,42658,Female,Loyal Customer,19,Business travel,Eco Plus,481,4,2,2,2,4,5,5,4,5,3,5,5,5,4,13,3.0,satisfied +17847,35186,Female,Loyal Customer,28,Business travel,Eco,1032,5,5,5,5,5,5,5,5,1,5,2,4,4,5,0,11.0,satisfied +17848,2216,Male,Loyal Customer,49,Business travel,Business,859,5,5,3,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +17849,113297,Male,Loyal Customer,54,Business travel,Business,386,2,2,2,2,3,5,4,2,2,2,2,5,2,4,24,22.0,satisfied +17850,53568,Male,Loyal Customer,47,Business travel,Business,1195,3,5,5,5,1,2,2,3,3,3,3,1,3,1,10,0.0,neutral or dissatisfied +17851,10857,Male,Loyal Customer,61,Business travel,Eco,295,2,1,1,1,2,2,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +17852,123765,Female,Loyal Customer,36,Business travel,Business,541,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +17853,128182,Male,Loyal Customer,64,Personal Travel,Eco,1849,2,3,2,3,3,2,3,3,4,4,2,3,3,3,0,0.0,neutral or dissatisfied +17854,28115,Female,Loyal Customer,28,Business travel,Business,2721,3,3,4,3,2,2,2,2,3,5,1,3,3,2,0,0.0,satisfied +17855,20897,Male,Loyal Customer,50,Personal Travel,Eco Plus,961,1,5,1,4,3,1,3,3,3,2,5,4,4,3,3,7.0,neutral or dissatisfied +17856,82870,Female,disloyal Customer,21,Business travel,Eco,594,4,5,3,3,1,3,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +17857,105178,Female,Loyal Customer,29,Personal Travel,Eco,289,4,5,4,3,5,4,5,5,3,3,4,3,4,5,67,53.0,neutral or dissatisfied +17858,26678,Female,Loyal Customer,25,Personal Travel,Eco,406,2,4,2,3,2,2,4,2,4,5,4,3,5,2,0,7.0,neutral or dissatisfied +17859,83727,Female,disloyal Customer,23,Business travel,Eco Plus,269,2,4,2,4,3,2,3,3,1,4,3,1,3,3,0,11.0,neutral or dissatisfied +17860,35614,Female,Loyal Customer,10,Personal Travel,Eco Plus,1076,2,3,2,4,5,2,3,5,1,4,3,2,3,5,0,10.0,neutral or dissatisfied +17861,69642,Male,Loyal Customer,53,Business travel,Business,569,3,3,3,3,3,4,5,4,4,4,4,5,4,5,18,14.0,satisfied +17862,73681,Male,disloyal Customer,36,Business travel,Eco,204,3,2,3,4,4,3,4,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +17863,27653,Male,Loyal Customer,41,Business travel,Business,1789,3,3,2,3,5,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +17864,89737,Female,Loyal Customer,39,Personal Travel,Eco,1010,5,5,5,4,2,5,2,2,5,5,3,2,4,2,0,0.0,satisfied +17865,4816,Male,Loyal Customer,51,Business travel,Business,3179,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +17866,47955,Male,Loyal Customer,67,Personal Travel,Eco,726,3,5,4,2,5,4,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +17867,17201,Male,Loyal Customer,57,Business travel,Eco,694,5,3,3,3,5,5,5,5,3,3,2,4,1,5,0,0.0,satisfied +17868,39420,Male,Loyal Customer,58,Business travel,Eco,129,4,2,2,2,4,4,4,4,1,3,4,5,2,4,0,1.0,satisfied +17869,107188,Male,Loyal Customer,41,Business travel,Eco,402,3,5,5,5,3,3,3,3,1,3,4,2,3,3,15,27.0,neutral or dissatisfied +17870,117625,Male,Loyal Customer,49,Personal Travel,Eco,872,3,0,3,1,5,3,5,5,3,4,3,5,5,5,10,15.0,neutral or dissatisfied +17871,70962,Female,Loyal Customer,43,Business travel,Business,802,1,5,5,5,1,3,3,1,1,1,1,4,1,1,0,1.0,neutral or dissatisfied +17872,44520,Female,Loyal Customer,27,Business travel,Business,3875,0,5,0,1,5,2,2,5,3,4,4,2,3,5,60,47.0,satisfied +17873,91096,Female,Loyal Customer,38,Personal Travel,Eco,594,3,5,3,5,3,3,1,3,4,3,3,5,1,3,0,2.0,neutral or dissatisfied +17874,64365,Female,Loyal Customer,11,Personal Travel,Eco,1192,4,5,4,4,2,4,2,2,5,4,4,4,4,2,5,0.0,neutral or dissatisfied +17875,88400,Female,disloyal Customer,17,Business travel,Eco,581,1,2,1,3,1,1,1,1,1,3,3,4,4,1,0,12.0,neutral or dissatisfied +17876,104417,Male,Loyal Customer,24,Business travel,Business,3902,2,2,2,2,3,4,3,3,5,3,4,3,5,3,2,4.0,satisfied +17877,115649,Male,Loyal Customer,48,Business travel,Eco,417,3,1,1,1,3,3,3,3,1,5,4,2,4,3,4,1.0,neutral or dissatisfied +17878,51677,Female,Loyal Customer,54,Business travel,Eco,370,2,1,1,1,5,3,4,2,2,2,2,2,2,4,38,46.0,neutral or dissatisfied +17879,33448,Male,Loyal Customer,10,Personal Travel,Eco,2556,3,2,3,3,3,5,5,2,1,3,3,5,3,5,0,20.0,neutral or dissatisfied +17880,124671,Female,disloyal Customer,58,Business travel,Business,399,4,4,4,4,1,4,1,1,3,5,4,3,5,1,66,69.0,satisfied +17881,58229,Female,Loyal Customer,51,Personal Travel,Eco,925,1,4,1,5,5,5,4,3,3,1,3,4,3,4,27,28.0,neutral or dissatisfied +17882,112951,Female,Loyal Customer,20,Personal Travel,Eco,1497,4,4,4,1,3,4,1,3,1,2,5,3,4,3,0,0.0,satisfied +17883,114747,Female,Loyal Customer,48,Business travel,Business,2858,3,3,3,3,4,4,5,4,4,5,4,3,4,4,2,0.0,satisfied +17884,67406,Male,Loyal Customer,41,Business travel,Business,2730,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +17885,94858,Female,Loyal Customer,22,Business travel,Business,1724,3,4,4,4,3,3,3,3,3,3,3,1,4,3,1,0.0,neutral or dissatisfied +17886,99713,Male,Loyal Customer,15,Personal Travel,Eco,667,4,2,4,3,3,4,3,3,4,4,3,4,4,3,0,4.0,neutral or dissatisfied +17887,69192,Male,Loyal Customer,36,Personal Travel,Eco,187,2,5,2,2,4,2,5,4,5,3,5,4,4,4,74,90.0,neutral or dissatisfied +17888,64572,Male,Loyal Customer,42,Business travel,Business,3272,2,2,2,2,5,5,5,2,2,2,2,3,2,3,104,97.0,satisfied +17889,41583,Male,Loyal Customer,21,Personal Travel,Eco,1482,2,3,2,3,1,2,1,1,4,1,4,5,4,1,50,43.0,neutral or dissatisfied +17890,66165,Male,Loyal Customer,39,Business travel,Business,460,4,3,4,4,4,4,4,4,4,4,4,3,4,5,43,41.0,satisfied +17891,80296,Female,Loyal Customer,46,Business travel,Business,746,5,5,5,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +17892,120477,Male,Loyal Customer,56,Personal Travel,Eco,366,3,4,3,4,4,3,4,4,5,2,3,2,3,4,0,0.0,neutral or dissatisfied +17893,60230,Male,disloyal Customer,35,Business travel,Eco,1049,3,3,3,3,2,3,5,2,3,5,2,1,3,2,0,0.0,neutral or dissatisfied +17894,97964,Female,Loyal Customer,8,Personal Travel,Eco,612,1,5,1,3,3,1,3,3,4,5,4,3,4,3,113,101.0,neutral or dissatisfied +17895,114998,Female,Loyal Customer,58,Business travel,Business,3403,2,2,2,2,5,4,4,4,4,5,4,4,4,4,26,7.0,satisfied +17896,63211,Female,Loyal Customer,56,Business travel,Eco,337,2,2,2,2,3,3,3,2,2,2,2,2,2,1,64,52.0,neutral or dissatisfied +17897,66839,Male,Loyal Customer,51,Business travel,Eco,731,5,3,3,3,5,5,5,5,4,2,1,4,5,5,0,0.0,satisfied +17898,70311,Female,disloyal Customer,37,Business travel,Business,334,4,4,4,1,5,4,5,5,5,5,5,3,5,5,7,0.0,satisfied +17899,94558,Female,disloyal Customer,33,Business travel,Business,187,3,3,3,2,2,3,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +17900,17134,Male,Loyal Customer,28,Personal Travel,Eco,472,4,4,4,5,2,4,2,2,3,2,5,4,4,2,28,30.0,neutral or dissatisfied +17901,67857,Female,Loyal Customer,35,Personal Travel,Eco,1235,1,4,1,3,4,1,4,4,4,4,4,5,5,4,0,19.0,neutral or dissatisfied +17902,46112,Female,Loyal Customer,51,Personal Travel,Eco,1154,3,4,3,4,2,5,4,4,4,3,4,5,4,5,0,3.0,neutral or dissatisfied +17903,115429,Male,Loyal Customer,44,Business travel,Business,447,1,4,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +17904,73687,Male,disloyal Customer,25,Business travel,Business,204,4,0,4,1,1,4,1,1,4,5,5,4,4,1,0,0.0,satisfied +17905,69942,Female,disloyal Customer,29,Business travel,Eco,1033,3,3,3,4,3,3,3,3,4,3,2,2,3,3,0,0.0,neutral or dissatisfied +17906,51123,Male,Loyal Customer,68,Personal Travel,Eco,109,2,2,2,3,5,2,5,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +17907,63989,Male,disloyal Customer,19,Business travel,Eco,612,4,0,4,4,5,4,5,5,4,2,4,5,4,5,80,68.0,satisfied +17908,8574,Male,Loyal Customer,75,Business travel,Business,109,1,1,1,1,4,4,4,4,4,4,5,4,4,5,6,2.0,satisfied +17909,7027,Male,Loyal Customer,45,Personal Travel,Eco,299,5,4,5,4,1,5,1,1,4,5,4,3,4,1,0,0.0,satisfied +17910,1071,Male,Loyal Customer,24,Personal Travel,Eco,229,3,5,3,4,3,3,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +17911,35571,Female,disloyal Customer,25,Business travel,Eco Plus,1069,3,0,3,5,3,3,3,3,5,3,2,4,4,3,0,0.0,neutral or dissatisfied +17912,3124,Female,Loyal Customer,27,Personal Travel,Eco,1013,2,1,2,2,4,2,1,4,2,2,3,1,2,4,30,24.0,neutral or dissatisfied +17913,92816,Male,disloyal Customer,28,Business travel,Eco,1137,3,3,3,3,2,3,2,2,1,2,3,1,2,2,15,11.0,neutral or dissatisfied +17914,28337,Female,Loyal Customer,40,Business travel,Eco,867,4,4,4,4,4,4,4,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +17915,71608,Male,Loyal Customer,64,Business travel,Eco,1197,3,2,2,2,4,3,4,4,1,5,4,1,3,4,2,0.0,neutral or dissatisfied +17916,37685,Female,Loyal Customer,29,Personal Travel,Eco,1076,3,4,3,3,2,3,5,2,4,2,4,4,5,2,8,0.0,neutral or dissatisfied +17917,86017,Female,Loyal Customer,39,Business travel,Eco,447,4,5,5,5,4,4,4,4,2,3,4,3,4,4,0,0.0,neutral or dissatisfied +17918,45211,Male,disloyal Customer,25,Business travel,Eco,911,4,4,4,3,3,4,3,3,1,5,4,2,5,3,28,39.0,satisfied +17919,5097,Female,disloyal Customer,53,Personal Travel,Eco,235,1,3,1,4,4,1,2,4,4,3,4,1,3,4,0,7.0,neutral or dissatisfied +17920,99796,Male,Loyal Customer,53,Business travel,Eco,632,1,3,5,3,1,1,1,1,1,4,2,2,2,1,5,0.0,neutral or dissatisfied +17921,67722,Female,disloyal Customer,21,Business travel,Eco,1171,2,2,2,1,5,2,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +17922,37863,Female,disloyal Customer,31,Business travel,Eco,1023,2,2,2,4,3,2,3,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +17923,47093,Male,Loyal Customer,53,Personal Travel,Eco,639,1,4,1,2,3,1,3,3,5,3,4,5,5,3,5,0.0,neutral or dissatisfied +17924,104405,Female,disloyal Customer,23,Business travel,Eco,1138,3,3,3,1,3,3,3,3,3,5,4,4,4,3,0,0.0,satisfied +17925,82855,Female,Loyal Customer,49,Business travel,Eco,594,2,2,2,2,5,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +17926,8106,Female,disloyal Customer,22,Business travel,Eco,530,1,2,1,3,4,1,4,4,1,3,3,2,4,4,128,121.0,neutral or dissatisfied +17927,83888,Female,Loyal Customer,36,Personal Travel,Eco Plus,1670,4,5,4,4,3,4,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +17928,66540,Female,Loyal Customer,37,Business travel,Business,1940,2,2,2,2,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +17929,17064,Male,Loyal Customer,35,Business travel,Eco Plus,1134,2,1,1,1,2,2,2,2,2,5,4,1,4,2,44,36.0,neutral or dissatisfied +17930,36170,Female,disloyal Customer,43,Business travel,Eco,174,1,0,1,3,1,1,1,1,3,1,2,1,4,1,7,7.0,neutral or dissatisfied +17931,34446,Female,Loyal Customer,54,Business travel,Business,2851,1,1,1,1,3,2,2,5,5,5,5,1,5,1,0,0.0,satisfied +17932,107677,Female,Loyal Customer,38,Business travel,Business,1530,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +17933,118780,Female,Loyal Customer,52,Personal Travel,Eco,304,2,1,2,1,5,2,2,1,1,2,2,3,1,4,13,5.0,neutral or dissatisfied +17934,81055,Male,Loyal Customer,43,Personal Travel,Eco,1399,2,4,2,3,2,2,2,2,5,2,5,5,5,2,40,32.0,neutral or dissatisfied +17935,73856,Female,Loyal Customer,32,Personal Travel,Eco,1709,3,4,3,4,5,3,2,5,2,1,3,4,4,5,19,37.0,neutral or dissatisfied +17936,30124,Male,Loyal Customer,54,Personal Travel,Eco,183,2,5,2,2,1,2,4,1,4,4,3,5,3,1,0,0.0,neutral or dissatisfied +17937,37717,Female,Loyal Customer,48,Personal Travel,Eco,1069,3,4,3,3,4,4,4,3,3,3,3,5,3,4,43,24.0,neutral or dissatisfied +17938,53082,Male,disloyal Customer,27,Business travel,Eco,1106,4,4,4,1,2,4,2,2,4,2,3,2,2,2,0,0.0,neutral or dissatisfied +17939,112879,Female,Loyal Customer,56,Business travel,Business,1390,4,4,4,4,5,5,5,5,5,5,5,5,5,4,2,0.0,satisfied +17940,96413,Female,Loyal Customer,16,Personal Travel,Eco,1246,2,4,2,5,2,2,3,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +17941,52448,Male,Loyal Customer,30,Personal Travel,Eco,370,3,5,3,3,1,3,1,1,4,3,2,5,4,1,60,56.0,neutral or dissatisfied +17942,16069,Female,Loyal Customer,42,Business travel,Business,501,2,3,4,4,3,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +17943,17441,Female,Loyal Customer,38,Personal Travel,Eco,376,2,5,2,3,3,2,3,3,3,2,5,4,5,3,65,58.0,neutral or dissatisfied +17944,127709,Female,Loyal Customer,51,Business travel,Business,3111,0,0,0,1,3,5,4,2,2,2,2,5,2,4,0,5.0,satisfied +17945,77386,Male,Loyal Customer,57,Business travel,Eco,226,2,2,3,2,2,2,2,2,2,5,3,3,3,2,10,25.0,neutral or dissatisfied +17946,105027,Female,Loyal Customer,49,Business travel,Business,2567,2,5,5,5,1,2,3,2,2,2,2,3,2,1,45,40.0,neutral or dissatisfied +17947,68921,Female,Loyal Customer,21,Personal Travel,Eco,1061,4,4,4,4,3,4,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +17948,109421,Male,disloyal Customer,39,Business travel,Business,992,2,2,2,3,5,2,5,5,4,3,4,3,4,5,13,0.0,neutral or dissatisfied +17949,67214,Male,Loyal Customer,66,Personal Travel,Eco,1121,3,5,3,5,2,3,4,2,4,3,5,5,4,2,13,6.0,neutral or dissatisfied +17950,80182,Male,Loyal Customer,15,Personal Travel,Eco,2475,1,3,1,2,1,3,5,3,5,2,5,5,1,5,0,0.0,neutral or dissatisfied +17951,19476,Male,Loyal Customer,45,Business travel,Eco,84,1,4,4,4,2,1,2,2,2,3,3,2,3,2,41,53.0,neutral or dissatisfied +17952,79133,Female,Loyal Customer,60,Business travel,Business,1538,4,4,4,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +17953,83655,Female,Loyal Customer,44,Business travel,Business,2439,1,1,1,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +17954,18258,Female,Loyal Customer,51,Personal Travel,Eco,228,2,4,0,4,5,5,4,3,3,0,3,5,3,5,0,0.0,neutral or dissatisfied +17955,109995,Female,Loyal Customer,27,Personal Travel,Eco Plus,1033,3,4,2,3,5,2,5,5,3,4,4,3,4,5,6,3.0,neutral or dissatisfied +17956,45991,Female,Loyal Customer,27,Business travel,Business,2165,4,4,4,4,4,4,4,4,4,4,3,3,3,4,16,52.0,neutral or dissatisfied +17957,88170,Male,Loyal Customer,40,Business travel,Business,406,3,3,3,3,5,4,4,5,5,5,5,5,5,4,7,0.0,satisfied +17958,114086,Male,Loyal Customer,24,Personal Travel,Eco,1892,4,5,3,2,2,3,1,2,5,1,2,4,1,2,0,0.0,neutral or dissatisfied +17959,75264,Female,Loyal Customer,11,Personal Travel,Eco,1744,2,5,2,2,5,2,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +17960,57570,Male,Loyal Customer,27,Business travel,Business,1597,5,5,5,5,5,5,5,5,5,3,5,4,4,5,0,0.0,satisfied +17961,68442,Male,Loyal Customer,63,Personal Travel,Eco Plus,1045,1,5,1,1,3,1,4,3,5,1,3,4,5,3,0,0.0,neutral or dissatisfied +17962,126803,Male,disloyal Customer,23,Business travel,Eco,831,0,0,0,3,1,0,1,1,4,5,4,4,5,1,0,8.0,satisfied +17963,22142,Male,Loyal Customer,34,Business travel,Eco Plus,350,5,3,3,3,5,5,5,5,4,5,5,3,4,5,0,0.0,satisfied +17964,73686,Female,Loyal Customer,38,Business travel,Business,192,2,4,4,4,2,4,4,3,3,3,2,2,3,4,24,11.0,neutral or dissatisfied +17965,58728,Female,Loyal Customer,40,Business travel,Business,2173,1,1,1,1,4,4,4,3,4,4,5,4,3,4,225,213.0,satisfied +17966,77108,Female,Loyal Customer,27,Business travel,Eco,1481,2,3,3,3,2,2,2,2,1,3,2,2,3,2,0,0.0,neutral or dissatisfied +17967,23961,Male,disloyal Customer,37,Business travel,Eco,639,4,0,4,3,4,4,4,4,2,4,3,4,2,4,117,113.0,satisfied +17968,32291,Male,disloyal Customer,35,Business travel,Eco,102,4,0,4,3,5,4,5,5,1,5,4,1,2,5,0,0.0,neutral or dissatisfied +17969,124319,Female,Loyal Customer,32,Personal Travel,Eco,255,2,5,2,3,4,2,4,4,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +17970,56668,Female,Loyal Customer,33,Personal Travel,Eco,997,1,4,1,1,4,1,4,4,4,5,4,5,4,4,0,13.0,neutral or dissatisfied +17971,77727,Male,Loyal Customer,46,Business travel,Eco,696,2,3,3,3,2,2,2,2,2,1,4,1,3,2,8,11.0,neutral or dissatisfied +17972,9668,Female,disloyal Customer,32,Business travel,Business,284,2,2,2,2,4,2,2,4,3,3,4,5,4,4,0,3.0,neutral or dissatisfied +17973,113401,Female,disloyal Customer,22,Business travel,Eco,223,3,4,4,2,1,4,1,1,3,3,5,4,4,1,0,2.0,neutral or dissatisfied +17974,2469,Male,Loyal Customer,11,Personal Travel,Eco,773,1,1,2,1,5,2,1,5,1,4,1,2,1,5,0,1.0,neutral or dissatisfied +17975,38670,Female,Loyal Customer,9,Personal Travel,Eco,2611,3,2,3,3,2,3,2,2,1,2,3,4,3,2,62,75.0,neutral or dissatisfied +17976,54639,Male,Loyal Customer,43,Business travel,Eco,956,4,4,4,4,4,4,4,4,3,1,2,1,2,4,0,0.0,satisfied +17977,71760,Male,Loyal Customer,23,Business travel,Business,1744,1,1,2,1,3,3,3,3,4,5,3,4,4,3,0,23.0,satisfied +17978,5126,Female,Loyal Customer,51,Business travel,Business,3549,2,2,3,2,5,5,5,3,3,4,4,5,3,4,0,0.0,satisfied +17979,35595,Male,Loyal Customer,47,Business travel,Eco Plus,1010,3,1,1,1,4,3,4,4,2,5,3,3,3,4,16,19.0,neutral or dissatisfied +17980,93436,Female,Loyal Customer,38,Business travel,Business,2142,2,5,5,5,2,3,3,2,2,2,2,1,2,1,9,7.0,neutral or dissatisfied +17981,23706,Female,Loyal Customer,35,Personal Travel,Eco,152,4,5,0,1,5,0,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +17982,71164,Male,Loyal Customer,49,Personal Travel,Eco,646,2,5,2,1,2,2,2,2,4,3,5,5,1,2,3,15.0,neutral or dissatisfied +17983,85401,Female,Loyal Customer,49,Business travel,Business,2889,3,3,3,3,5,4,5,4,4,4,5,4,4,3,18,18.0,satisfied +17984,105916,Male,Loyal Customer,12,Personal Travel,Eco,283,3,1,3,1,2,3,2,2,3,3,2,4,1,2,0,0.0,neutral or dissatisfied +17985,111007,Male,Loyal Customer,47,Business travel,Business,1562,4,4,4,4,4,5,5,5,5,5,4,4,5,3,18,14.0,satisfied +17986,22335,Female,Loyal Customer,50,Business travel,Business,2686,5,5,5,5,5,3,4,4,4,4,4,5,4,1,0,0.0,satisfied +17987,52604,Male,Loyal Customer,35,Business travel,Business,3345,1,1,1,1,2,5,1,4,4,4,5,3,4,1,0,0.0,satisfied +17988,103324,Female,disloyal Customer,21,Business travel,Eco,1139,5,5,5,3,5,5,5,5,5,3,5,5,2,5,0,0.0,satisfied +17989,101116,Male,Loyal Customer,41,Business travel,Business,795,3,3,3,3,4,5,4,5,5,5,5,4,5,3,8,3.0,satisfied +17990,38662,Female,disloyal Customer,44,Business travel,Eco,1088,1,0,0,4,2,0,2,2,4,5,4,1,4,2,6,12.0,neutral or dissatisfied +17991,95485,Male,Loyal Customer,65,Business travel,Business,562,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +17992,81985,Male,disloyal Customer,24,Business travel,Eco,1338,3,3,3,3,3,3,3,3,1,4,3,4,3,3,7,15.0,neutral or dissatisfied +17993,21930,Male,disloyal Customer,26,Business travel,Eco,551,2,4,3,3,4,3,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +17994,33387,Female,disloyal Customer,24,Business travel,Eco,1038,2,2,2,3,2,2,2,2,3,3,5,1,4,2,1,0.0,neutral or dissatisfied +17995,129315,Male,Loyal Customer,36,Business travel,Business,2475,2,2,3,2,3,5,4,3,3,4,3,3,3,3,3,16.0,satisfied +17996,2968,Male,Loyal Customer,42,Business travel,Business,737,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +17997,110972,Male,disloyal Customer,25,Business travel,Business,197,3,0,3,1,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +17998,115587,Female,Loyal Customer,58,Business travel,Business,362,5,5,5,5,5,4,4,4,4,4,4,3,4,5,34,24.0,satisfied +17999,109613,Male,Loyal Customer,42,Business travel,Business,930,2,2,2,2,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +18000,22559,Male,Loyal Customer,11,Personal Travel,Business,223,1,5,0,1,3,0,3,3,4,3,4,5,4,3,47,59.0,neutral or dissatisfied +18001,111187,Female,Loyal Customer,49,Business travel,Business,1506,1,1,1,1,4,5,5,5,5,5,5,5,5,3,2,0.0,satisfied +18002,21239,Female,Loyal Customer,44,Personal Travel,Eco,153,3,4,3,3,2,5,5,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +18003,17934,Female,Loyal Customer,42,Business travel,Business,3652,0,5,0,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +18004,25504,Female,disloyal Customer,26,Business travel,Eco,481,3,1,3,2,4,3,4,4,3,4,3,4,2,4,0,0.0,neutral or dissatisfied +18005,124033,Male,Loyal Customer,20,Personal Travel,Eco,184,1,5,1,1,2,1,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +18006,95890,Female,Loyal Customer,62,Personal Travel,Eco,580,3,3,3,4,4,3,4,5,5,3,5,1,5,1,34,25.0,neutral or dissatisfied +18007,766,Female,Loyal Customer,60,Business travel,Business,354,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +18008,107787,Male,Loyal Customer,20,Personal Travel,Eco,666,1,2,1,2,1,1,2,1,1,4,2,2,2,1,41,30.0,neutral or dissatisfied +18009,23906,Female,Loyal Customer,24,Business travel,Eco,589,4,2,3,2,4,4,3,4,4,3,3,4,4,4,0,0.0,satisfied +18010,46102,Male,Loyal Customer,59,Business travel,Business,1154,5,5,5,5,4,4,5,5,5,5,5,5,5,3,19,28.0,satisfied +18011,111134,Female,Loyal Customer,34,Business travel,Business,3540,3,3,3,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +18012,87458,Male,disloyal Customer,24,Business travel,Eco,373,4,2,5,2,5,5,5,5,5,5,4,3,4,5,0,2.0,satisfied +18013,121577,Male,Loyal Customer,37,Business travel,Business,3012,1,3,3,3,1,3,4,1,1,2,1,1,1,3,2,0.0,neutral or dissatisfied +18014,44729,Female,Loyal Customer,20,Personal Travel,Eco,67,3,4,3,1,5,3,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +18015,72971,Male,Loyal Customer,29,Business travel,Business,2873,2,1,1,1,2,2,2,2,3,2,3,4,3,2,4,8.0,neutral or dissatisfied +18016,54659,Female,disloyal Customer,21,Business travel,Eco,861,2,2,2,3,3,2,3,3,2,1,5,3,2,3,0,0.0,neutral or dissatisfied +18017,78614,Male,Loyal Customer,41,Business travel,Business,1426,3,3,3,3,2,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +18018,30443,Female,Loyal Customer,34,Personal Travel,Business,991,4,5,5,1,4,4,5,4,4,5,1,4,4,3,9,11.0,neutral or dissatisfied +18019,20097,Female,Loyal Customer,61,Business travel,Eco,416,4,5,5,5,5,5,3,4,4,4,4,4,4,3,0,0.0,satisfied +18020,19125,Female,Loyal Customer,37,Personal Travel,Eco,265,4,4,4,3,1,4,1,1,5,1,5,5,2,1,26,42.0,neutral or dissatisfied +18021,8353,Female,Loyal Customer,26,Personal Travel,Eco,783,3,4,3,2,4,3,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +18022,85339,Female,Loyal Customer,50,Business travel,Business,813,4,4,4,4,4,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +18023,88373,Male,Loyal Customer,29,Business travel,Business,366,2,5,3,5,2,2,2,2,4,3,3,2,4,2,3,0.0,neutral or dissatisfied +18024,11013,Male,Loyal Customer,43,Business travel,Eco,429,3,1,1,1,3,3,3,3,1,4,4,2,4,3,28,26.0,neutral or dissatisfied +18025,16079,Male,Loyal Customer,56,Personal Travel,Eco,744,2,5,1,4,4,1,4,4,4,3,4,5,4,4,3,0.0,neutral or dissatisfied +18026,67638,Male,Loyal Customer,26,Business travel,Business,1431,1,1,1,1,5,5,5,5,3,3,5,5,5,5,116,123.0,satisfied +18027,94192,Male,Loyal Customer,43,Business travel,Business,3830,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +18028,54090,Female,Loyal Customer,57,Personal Travel,Eco,1416,3,1,3,3,4,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +18029,20324,Female,Loyal Customer,58,Business travel,Business,265,5,5,5,5,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +18030,59923,Male,Loyal Customer,53,Business travel,Business,3739,3,2,2,2,5,1,1,3,3,3,3,4,3,4,63,37.0,neutral or dissatisfied +18031,27219,Female,Loyal Customer,24,Business travel,Business,1774,1,1,1,1,4,4,4,4,1,5,1,4,4,4,0,0.0,satisfied +18032,112511,Female,Loyal Customer,19,Personal Travel,Eco,853,3,1,3,3,5,3,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +18033,2066,Female,Loyal Customer,47,Business travel,Eco,812,3,1,1,1,5,2,2,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +18034,118025,Female,Loyal Customer,59,Personal Travel,Business,1044,3,4,3,1,1,1,5,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +18035,121962,Male,Loyal Customer,52,Business travel,Eco Plus,430,4,1,1,1,4,4,4,4,2,3,2,2,2,4,0,0.0,satisfied +18036,49368,Male,Loyal Customer,30,Business travel,Eco,109,0,0,0,1,5,0,5,5,3,5,5,3,1,5,19,11.0,satisfied +18037,14545,Male,Loyal Customer,28,Personal Travel,Eco,288,3,4,3,4,3,3,3,3,4,3,4,5,4,3,0,2.0,neutral or dissatisfied +18038,14914,Male,Loyal Customer,41,Personal Travel,Eco,315,2,5,2,5,3,2,3,3,5,3,4,3,4,3,2,17.0,neutral or dissatisfied +18039,94034,Female,Loyal Customer,22,Business travel,Business,2638,3,3,3,3,4,4,4,4,5,5,4,5,4,4,15,0.0,satisfied +18040,73778,Male,Loyal Customer,17,Personal Travel,Eco,204,1,3,0,3,3,0,3,3,4,2,5,5,3,3,0,0.0,neutral or dissatisfied +18041,56299,Female,Loyal Customer,69,Personal Travel,Eco,2227,3,5,3,3,3,4,4,5,5,3,5,3,5,3,2,0.0,neutral or dissatisfied +18042,107283,Female,Loyal Customer,61,Business travel,Business,3048,2,4,4,4,4,3,4,2,2,2,2,1,2,3,18,37.0,neutral or dissatisfied +18043,114533,Female,Loyal Customer,30,Personal Travel,Business,480,5,4,5,4,4,5,4,4,4,1,3,2,3,4,4,1.0,satisfied +18044,42146,Female,Loyal Customer,41,Business travel,Business,3788,5,5,5,5,5,3,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +18045,114653,Female,Loyal Customer,65,Business travel,Business,3207,1,1,5,1,4,5,4,4,4,4,4,3,4,3,0,7.0,satisfied +18046,14981,Male,disloyal Customer,38,Business travel,Eco,680,2,2,2,2,4,2,4,4,2,2,1,3,1,4,0,7.0,neutral or dissatisfied +18047,72952,Male,Loyal Customer,42,Business travel,Business,1992,2,2,2,2,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +18048,27164,Male,Loyal Customer,71,Business travel,Eco,1177,1,2,2,2,1,1,1,4,1,4,3,1,2,1,0,0.0,neutral or dissatisfied +18049,84679,Male,Loyal Customer,39,Business travel,Business,2182,3,4,4,4,2,3,4,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +18050,50035,Male,disloyal Customer,33,Business travel,Eco,134,4,0,4,1,3,4,3,3,2,4,2,5,1,3,0,0.0,neutral or dissatisfied +18051,81902,Female,Loyal Customer,21,Personal Travel,Eco,680,3,5,3,3,1,3,1,1,5,1,3,1,5,1,0,3.0,neutral or dissatisfied +18052,108410,Male,Loyal Customer,36,Personal Travel,Eco,544,3,5,3,1,4,3,4,4,3,2,4,4,4,4,15,22.0,neutral or dissatisfied +18053,39596,Female,disloyal Customer,20,Business travel,Eco,748,2,2,2,3,3,2,3,3,3,2,4,3,4,3,0,2.0,neutral or dissatisfied +18054,45682,Female,disloyal Customer,36,Business travel,Eco,896,2,2,2,3,5,2,5,5,2,3,2,1,5,5,0,0.0,neutral or dissatisfied +18055,22220,Female,Loyal Customer,43,Business travel,Eco Plus,606,5,3,3,3,2,2,3,5,5,5,5,2,5,2,32,20.0,satisfied +18056,120511,Female,Loyal Customer,36,Personal Travel,Eco Plus,449,4,5,4,1,2,4,2,2,3,3,4,3,5,2,7,0.0,satisfied +18057,113379,Male,Loyal Customer,58,Business travel,Business,2464,4,4,4,4,4,4,4,4,4,4,4,4,4,3,18,18.0,satisfied +18058,49462,Female,Loyal Customer,41,Business travel,Business,1543,4,3,4,4,5,4,5,5,4,5,5,5,5,5,144,139.0,satisfied +18059,98564,Male,Loyal Customer,40,Personal Travel,Business,993,3,4,3,5,3,5,4,5,5,3,5,4,5,5,0,55.0,neutral or dissatisfied +18060,102392,Male,Loyal Customer,53,Business travel,Business,1592,3,4,4,4,5,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +18061,21195,Female,Loyal Customer,25,Business travel,Business,3322,1,1,1,1,4,4,4,4,5,2,3,1,2,4,0,4.0,satisfied +18062,68889,Female,disloyal Customer,29,Business travel,Business,1061,3,3,3,3,1,3,1,1,5,3,5,5,4,1,0,5.0,neutral or dissatisfied +18063,117073,Female,Loyal Customer,25,Business travel,Business,3663,1,1,1,1,1,1,1,1,2,5,3,1,3,1,25,21.0,neutral or dissatisfied +18064,71734,Male,Loyal Customer,35,Business travel,Business,1846,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +18065,53115,Female,disloyal Customer,23,Business travel,Eco,1169,5,5,5,4,2,5,2,2,4,1,4,3,5,2,0,1.0,satisfied +18066,12871,Female,disloyal Customer,30,Business travel,Eco,674,3,3,3,4,4,3,2,4,3,1,3,2,4,4,30,33.0,neutral or dissatisfied +18067,107882,Female,Loyal Customer,51,Business travel,Business,3559,0,0,0,2,3,4,5,4,4,4,4,3,4,5,12,17.0,satisfied +18068,51125,Male,Loyal Customer,18,Personal Travel,Eco,110,4,2,4,3,3,4,3,3,1,1,2,2,2,3,0,0.0,neutral or dissatisfied +18069,61352,Female,Loyal Customer,37,Business travel,Business,3497,2,3,3,3,2,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +18070,114520,Male,Loyal Customer,34,Personal Travel,Business,337,2,5,2,3,3,5,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +18071,61110,Female,disloyal Customer,42,Business travel,Eco Plus,1709,2,2,2,4,3,2,3,3,1,5,4,3,3,3,6,38.0,neutral or dissatisfied +18072,42457,Male,Loyal Customer,36,Personal Travel,Eco,866,3,4,4,5,1,4,1,1,3,2,5,5,4,1,0,18.0,neutral or dissatisfied +18073,52080,Male,Loyal Customer,61,Business travel,Business,438,3,1,1,1,2,2,2,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +18074,88888,Female,Loyal Customer,47,Business travel,Eco,859,3,5,4,5,1,2,3,3,3,3,3,2,3,3,2,7.0,neutral or dissatisfied +18075,118449,Male,Loyal Customer,55,Business travel,Business,369,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,8.0,satisfied +18076,124558,Female,Loyal Customer,38,Business travel,Business,3570,3,3,3,3,5,4,5,4,4,4,4,5,4,3,4,6.0,satisfied +18077,91970,Female,Loyal Customer,23,Personal Travel,Eco,2446,2,5,2,2,3,2,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +18078,115597,Male,disloyal Customer,21,Business travel,Business,390,5,4,5,2,3,5,3,3,5,5,4,5,4,3,12,0.0,satisfied +18079,34288,Male,disloyal Customer,29,Business travel,Eco,96,3,2,3,3,2,3,2,2,4,2,4,2,4,2,3,15.0,neutral or dissatisfied +18080,57540,Male,Loyal Customer,30,Personal Travel,Eco,413,2,4,2,2,3,2,3,3,5,4,4,3,5,3,3,0.0,neutral or dissatisfied +18081,114035,Female,Loyal Customer,51,Business travel,Business,2125,4,4,4,4,3,5,5,4,4,4,4,5,4,4,45,37.0,satisfied +18082,29417,Female,Loyal Customer,19,Business travel,Eco Plus,2378,5,4,4,4,5,5,4,5,4,1,4,2,1,5,0,0.0,satisfied +18083,55700,Female,disloyal Customer,23,Business travel,Eco,1025,4,4,4,2,2,4,2,2,4,1,1,1,4,2,0,0.0,satisfied +18084,58680,Female,Loyal Customer,49,Business travel,Business,3786,3,3,3,3,4,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +18085,65972,Male,Loyal Customer,55,Business travel,Business,1372,3,3,1,1,2,4,3,3,3,3,3,1,3,1,67,44.0,neutral or dissatisfied +18086,128668,Male,Loyal Customer,26,Business travel,Business,2419,1,2,2,2,1,2,1,1,2,1,4,3,3,1,25,13.0,neutral or dissatisfied +18087,23408,Female,Loyal Customer,43,Personal Travel,Eco Plus,300,1,4,1,3,2,1,3,3,3,1,3,3,3,5,112,98.0,neutral or dissatisfied +18088,113989,Female,Loyal Customer,51,Business travel,Eco,1750,4,4,4,4,2,2,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +18089,16987,Female,Loyal Customer,42,Personal Travel,Eco,610,3,4,3,2,1,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +18090,27928,Male,Loyal Customer,10,Business travel,Eco Plus,689,5,1,1,1,5,5,5,5,3,3,5,4,3,5,0,0.0,satisfied +18091,89171,Male,Loyal Customer,34,Personal Travel,Eco,1947,3,5,3,2,1,3,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +18092,40500,Female,Loyal Customer,56,Personal Travel,Eco,188,2,5,2,5,2,5,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +18093,28987,Male,disloyal Customer,21,Business travel,Eco,978,3,3,3,4,4,3,4,4,3,5,3,2,3,4,6,0.0,neutral or dissatisfied +18094,42792,Female,Loyal Customer,54,Personal Travel,Eco,349,4,4,4,1,2,5,4,4,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +18095,73733,Male,Loyal Customer,57,Personal Travel,Eco,204,3,4,3,5,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +18096,56653,Male,disloyal Customer,37,Business travel,Eco,668,2,0,2,3,1,2,1,1,4,2,3,1,1,1,31,25.0,neutral or dissatisfied +18097,86488,Male,Loyal Customer,46,Personal Travel,Eco,762,2,4,2,3,5,2,5,5,4,3,5,3,5,5,17,5.0,neutral or dissatisfied +18098,50571,Female,Loyal Customer,51,Personal Travel,Eco,158,3,3,3,2,1,3,3,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +18099,34186,Female,Loyal Customer,46,Personal Travel,Eco,1046,4,4,4,3,1,3,3,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +18100,110736,Male,Loyal Customer,47,Business travel,Business,3345,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +18101,64438,Male,Loyal Customer,31,Business travel,Business,1636,3,3,3,3,4,4,4,4,4,3,5,5,5,4,6,15.0,satisfied +18102,5593,Female,Loyal Customer,53,Business travel,Business,624,4,4,4,4,4,4,4,5,5,5,5,4,3,4,44,142.0,satisfied +18103,19016,Male,Loyal Customer,48,Business travel,Eco,471,3,4,4,4,4,3,4,4,1,4,3,2,4,4,0,2.0,neutral or dissatisfied +18104,3070,Female,Loyal Customer,41,Business travel,Business,2660,3,3,3,3,5,5,5,2,2,2,2,3,2,4,0,2.0,satisfied +18105,58916,Female,Loyal Customer,17,Personal Travel,Eco,888,2,5,2,3,2,3,3,2,3,3,1,3,1,3,245,273.0,neutral or dissatisfied +18106,41611,Female,Loyal Customer,30,Personal Travel,Eco,1242,4,5,4,2,2,4,2,2,4,4,3,5,5,2,5,0.0,neutral or dissatisfied +18107,123120,Male,Loyal Customer,31,Business travel,Business,2094,3,1,1,1,3,3,3,3,2,1,4,1,3,3,41,34.0,neutral or dissatisfied +18108,102064,Male,Loyal Customer,69,Personal Travel,Business,397,1,4,1,4,1,3,3,2,2,1,2,1,2,3,48,32.0,neutral or dissatisfied +18109,56143,Male,Loyal Customer,51,Business travel,Business,1400,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +18110,6037,Male,Loyal Customer,43,Business travel,Business,2163,3,2,3,3,3,3,3,3,4,3,3,3,2,3,97,134.0,neutral or dissatisfied +18111,91503,Female,disloyal Customer,21,Business travel,Eco,1216,4,4,4,3,4,4,4,4,5,2,3,4,4,4,0,0.0,neutral or dissatisfied +18112,87997,Male,disloyal Customer,26,Business travel,Business,271,4,1,4,4,2,4,2,2,4,4,5,4,4,2,0,58.0,satisfied +18113,21928,Male,Loyal Customer,40,Business travel,Business,448,3,5,5,5,4,1,2,3,3,3,3,4,3,4,43,23.0,neutral or dissatisfied +18114,31543,Female,Loyal Customer,22,Personal Travel,Eco,967,1,5,1,3,4,1,2,4,3,5,4,5,5,4,0,5.0,neutral or dissatisfied +18115,42710,Male,Loyal Customer,46,Business travel,Eco Plus,627,4,3,3,3,4,4,4,4,2,2,5,3,1,4,0,0.0,satisfied +18116,66767,Male,disloyal Customer,32,Business travel,Business,802,1,1,1,3,4,1,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +18117,54193,Male,Loyal Customer,15,Personal Travel,Eco,1400,3,5,3,5,5,3,5,5,3,2,4,4,4,5,1,3.0,neutral or dissatisfied +18118,119529,Male,Loyal Customer,62,Personal Travel,Eco,899,2,4,1,3,1,1,1,1,4,4,5,4,4,1,119,92.0,neutral or dissatisfied +18119,60539,Male,Loyal Customer,19,Personal Travel,Eco,862,3,5,3,5,3,3,2,3,5,3,4,3,4,3,110,97.0,neutral or dissatisfied +18120,995,Male,Loyal Customer,35,Business travel,Eco,102,3,4,4,4,3,4,3,3,4,5,3,2,3,3,0,5.0,satisfied +18121,104081,Female,Loyal Customer,55,Personal Travel,Business,666,1,2,1,4,5,4,3,5,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +18122,52673,Male,Loyal Customer,46,Personal Travel,Eco,119,1,2,1,4,3,1,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +18123,14708,Male,disloyal Customer,23,Business travel,Eco,479,4,3,4,4,5,4,4,5,3,4,3,3,5,5,0,0.0,satisfied +18124,36610,Male,Loyal Customer,58,Business travel,Eco,1121,2,2,5,2,2,2,2,2,2,1,4,4,4,2,1,11.0,neutral or dissatisfied +18125,80610,Female,Loyal Customer,49,Business travel,Business,3705,5,5,5,5,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +18126,84511,Male,Loyal Customer,58,Business travel,Business,2556,4,4,4,4,2,3,4,5,5,4,5,3,5,4,0,0.0,satisfied +18127,84117,Female,Loyal Customer,29,Business travel,Eco,1900,2,2,2,2,2,2,2,2,3,2,2,3,4,2,0,0.0,neutral or dissatisfied +18128,4031,Female,Loyal Customer,49,Business travel,Business,479,3,1,3,3,5,4,5,4,4,4,4,4,4,4,0,1.0,satisfied +18129,115464,Female,disloyal Customer,36,Business travel,Eco,404,3,2,3,3,4,3,4,4,1,4,4,3,3,4,5,0.0,neutral or dissatisfied +18130,89106,Female,Loyal Customer,24,Business travel,Eco,1900,2,5,5,5,2,2,2,2,3,5,2,1,3,2,97,83.0,neutral or dissatisfied +18131,71938,Female,Loyal Customer,40,Personal Travel,Eco Plus,1846,2,5,2,2,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +18132,49201,Female,Loyal Customer,43,Business travel,Business,2045,3,3,3,3,3,3,1,5,5,5,5,4,5,5,0,0.0,satisfied +18133,40365,Female,Loyal Customer,20,Business travel,Business,1250,3,3,3,3,2,2,2,2,4,1,1,2,3,2,0,7.0,satisfied +18134,128235,Female,Loyal Customer,13,Personal Travel,Eco,602,5,3,5,3,4,3,4,4,2,1,3,2,3,4,3,0.0,satisfied +18135,65216,Female,Loyal Customer,44,Business travel,Business,3025,1,1,3,1,3,4,4,4,3,4,5,4,4,4,149,149.0,satisfied +18136,75039,Female,Loyal Customer,24,Personal Travel,Eco,236,1,5,1,4,1,1,3,1,5,4,4,3,4,1,28,20.0,neutral or dissatisfied +18137,81398,Female,Loyal Customer,69,Personal Travel,Eco,874,4,0,4,1,2,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +18138,44689,Male,disloyal Customer,30,Business travel,Eco,67,3,3,3,4,4,3,4,4,5,1,3,2,1,4,10,1.0,neutral or dissatisfied +18139,23760,Female,Loyal Customer,50,Personal Travel,Eco,1083,3,4,3,1,4,1,4,5,5,3,5,5,5,2,26,44.0,neutral or dissatisfied +18140,1470,Male,Loyal Customer,19,Personal Travel,Eco,772,2,5,2,4,5,2,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +18141,39276,Female,Loyal Customer,25,Business travel,Eco,268,3,3,3,3,3,3,4,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +18142,109195,Male,disloyal Customer,26,Business travel,Business,612,3,3,3,1,3,3,3,3,5,2,4,3,5,3,17,16.0,neutral or dissatisfied +18143,67699,Female,Loyal Customer,25,Business travel,Business,1464,2,5,5,5,2,2,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +18144,17427,Female,disloyal Customer,23,Business travel,Eco,351,0,0,0,1,5,0,5,5,4,3,2,4,4,5,0,0.0,satisfied +18145,49218,Female,Loyal Customer,60,Business travel,Business,156,2,2,2,2,5,4,1,5,5,5,5,2,5,1,0,0.0,satisfied +18146,127246,Female,Loyal Customer,53,Business travel,Business,1107,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +18147,122132,Female,Loyal Customer,36,Business travel,Business,541,3,5,5,5,1,3,4,3,3,3,3,3,3,1,26,20.0,neutral or dissatisfied +18148,119832,Male,Loyal Customer,40,Business travel,Business,2070,3,3,3,3,5,5,4,5,5,5,5,4,5,5,8,0.0,satisfied +18149,51212,Male,Loyal Customer,55,Business travel,Eco Plus,109,3,3,3,3,3,3,3,3,2,2,3,3,3,3,0,0.0,satisfied +18150,126393,Female,Loyal Customer,68,Personal Travel,Eco,631,2,5,2,3,1,2,1,2,2,2,3,1,2,5,0,0.0,neutral or dissatisfied +18151,48335,Female,Loyal Customer,54,Business travel,Business,674,5,5,5,5,1,3,5,5,5,5,5,2,5,2,6,12.0,satisfied +18152,67964,Female,Loyal Customer,48,Business travel,Business,1464,5,5,2,5,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +18153,71514,Male,Loyal Customer,35,Business travel,Business,3561,1,5,5,5,1,4,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +18154,14842,Male,Loyal Customer,55,Business travel,Business,3401,2,1,1,1,5,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +18155,32803,Male,disloyal Customer,41,Business travel,Eco,101,1,4,1,4,3,1,3,3,4,5,3,1,3,3,0,1.0,neutral or dissatisfied +18156,96670,Female,disloyal Customer,32,Personal Travel,Eco,937,3,5,3,3,2,3,2,2,4,3,4,3,4,2,27,26.0,neutral or dissatisfied +18157,636,Female,Loyal Customer,57,Business travel,Business,2554,5,5,5,5,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +18158,13926,Female,Loyal Customer,53,Business travel,Business,153,1,4,4,4,2,4,4,2,2,2,1,4,2,4,35,29.0,neutral or dissatisfied +18159,37521,Male,Loyal Customer,27,Business travel,Eco,1041,1,4,4,4,1,1,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +18160,49018,Male,disloyal Customer,41,Business travel,Eco,373,3,0,3,4,1,3,1,1,4,1,2,1,5,1,0,0.0,neutral or dissatisfied +18161,3568,Female,Loyal Customer,19,Personal Travel,Eco,227,3,4,3,1,2,3,5,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +18162,70883,Female,Loyal Customer,32,Personal Travel,Eco,1814,3,4,2,1,3,2,3,3,5,3,4,4,4,3,16,56.0,neutral or dissatisfied +18163,74212,Female,Loyal Customer,21,Personal Travel,Eco Plus,769,2,1,2,3,5,2,2,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +18164,17622,Female,Loyal Customer,16,Business travel,Business,3161,1,2,2,2,1,1,1,3,1,2,2,1,4,1,213,200.0,neutral or dissatisfied +18165,92914,Female,disloyal Customer,25,Business travel,Eco,151,4,1,4,2,1,4,1,1,4,1,2,1,2,1,0,0.0,neutral or dissatisfied +18166,19636,Female,Loyal Customer,39,Personal Travel,Eco,589,3,5,3,4,3,3,3,3,3,4,4,5,5,3,7,5.0,neutral or dissatisfied +18167,99285,Male,Loyal Customer,18,Personal Travel,Eco,833,4,4,4,4,2,4,1,2,5,2,5,4,5,2,0,1.0,neutral or dissatisfied +18168,80237,Female,Loyal Customer,38,Business travel,Business,3333,2,2,2,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +18169,54010,Female,Loyal Customer,54,Business travel,Business,691,5,5,3,5,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18170,34960,Female,Loyal Customer,30,Personal Travel,Eco Plus,187,1,5,1,3,2,1,2,2,5,3,5,4,5,2,72,49.0,neutral or dissatisfied +18171,101147,Female,Loyal Customer,57,Business travel,Business,583,5,5,1,5,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +18172,75077,Male,Loyal Customer,65,Personal Travel,Eco,2611,2,4,2,2,1,2,1,1,5,3,5,3,2,1,0,0.0,neutral or dissatisfied +18173,39056,Male,Loyal Customer,65,Personal Travel,Eco Plus,260,2,1,0,2,5,0,5,5,1,2,2,4,3,5,43,55.0,neutral or dissatisfied +18174,124536,Female,Loyal Customer,72,Business travel,Business,1276,3,2,1,1,3,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +18175,85977,Female,Loyal Customer,46,Business travel,Business,528,4,4,4,4,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +18176,84469,Female,Loyal Customer,65,Personal Travel,Business,1142,1,4,2,4,4,5,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +18177,37287,Male,disloyal Customer,37,Business travel,Business,1069,3,3,3,3,5,3,5,5,4,2,2,5,1,5,0,0.0,neutral or dissatisfied +18178,93249,Male,disloyal Customer,20,Business travel,Eco,689,4,4,4,2,2,4,2,2,5,3,5,3,5,2,0,0.0,satisfied +18179,74796,Female,Loyal Customer,48,Business travel,Business,3954,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +18180,11735,Female,Loyal Customer,55,Business travel,Business,1888,2,2,2,2,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +18181,98611,Male,disloyal Customer,24,Business travel,Business,834,0,0,0,3,4,0,4,4,5,2,4,4,5,4,0,0.0,satisfied +18182,34262,Male,Loyal Customer,47,Business travel,Eco,496,4,4,4,4,4,4,4,4,2,3,4,5,2,4,0,0.0,satisfied +18183,15133,Female,disloyal Customer,29,Business travel,Eco,912,3,3,3,3,4,3,4,4,2,4,3,1,3,4,4,19.0,neutral or dissatisfied +18184,118202,Female,Loyal Customer,68,Personal Travel,Eco,1444,3,5,3,4,5,3,5,4,4,3,4,4,4,5,13,3.0,neutral or dissatisfied +18185,66748,Male,Loyal Customer,38,Personal Travel,Eco,978,1,5,1,2,5,1,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +18186,83386,Male,Loyal Customer,48,Business travel,Business,632,3,3,1,3,2,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +18187,34641,Male,Loyal Customer,20,Personal Travel,Eco,541,3,1,3,4,5,3,5,5,2,5,3,1,3,5,3,5.0,neutral or dissatisfied +18188,28831,Female,Loyal Customer,26,Business travel,Business,3798,5,5,2,5,5,5,5,5,1,1,4,1,3,5,0,0.0,satisfied +18189,74901,Female,disloyal Customer,30,Business travel,Business,2475,1,1,1,2,1,1,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +18190,37349,Male,Loyal Customer,26,Business travel,Business,2018,1,1,3,1,4,4,4,4,3,5,4,4,1,4,9,0.0,satisfied +18191,25028,Male,Loyal Customer,40,Business travel,Business,3604,1,2,2,2,3,4,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +18192,126690,Male,disloyal Customer,23,Business travel,Business,984,4,0,4,2,2,4,2,2,4,2,3,4,5,2,0,0.0,satisfied +18193,67428,Male,disloyal Customer,40,Business travel,Business,641,5,4,4,3,1,4,1,1,5,4,5,4,5,1,0,0.0,satisfied +18194,120805,Female,Loyal Customer,57,Business travel,Business,2441,2,2,2,2,5,5,5,4,2,4,5,5,3,5,172,156.0,satisfied +18195,127649,Female,Loyal Customer,19,Personal Travel,Eco,1773,2,2,2,3,4,2,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +18196,31798,Male,Loyal Customer,34,Personal Travel,Eco,2677,2,0,2,1,2,3,3,2,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +18197,116793,Male,Loyal Customer,59,Personal Travel,Eco Plus,337,3,4,4,4,3,4,3,3,2,5,3,1,3,3,11,0.0,neutral or dissatisfied +18198,72801,Male,Loyal Customer,64,Personal Travel,Eco,1045,2,4,2,5,2,2,2,2,2,2,2,5,5,2,0,0.0,neutral or dissatisfied +18199,58429,Female,Loyal Customer,41,Business travel,Eco,733,4,4,4,4,4,4,4,4,3,2,1,1,5,4,0,0.0,satisfied +18200,37984,Male,Loyal Customer,56,Personal Travel,Business,1197,3,1,3,3,3,1,1,3,3,3,4,1,1,1,132,102.0,neutral or dissatisfied +18201,44253,Female,disloyal Customer,36,Business travel,Eco,359,3,2,3,3,1,3,2,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +18202,122053,Female,Loyal Customer,15,Business travel,Business,2392,2,5,5,5,2,2,2,2,4,1,2,3,2,2,43,59.0,neutral or dissatisfied +18203,19446,Female,disloyal Customer,24,Business travel,Eco,363,2,2,2,4,1,2,1,1,1,4,4,3,3,1,73,55.0,neutral or dissatisfied +18204,106067,Male,Loyal Customer,60,Business travel,Business,444,4,2,2,2,1,3,2,4,4,4,4,3,4,1,89,105.0,neutral or dissatisfied +18205,11442,Female,Loyal Customer,37,Business travel,Business,2140,5,1,5,5,4,5,4,5,5,5,4,4,5,3,9,3.0,satisfied +18206,5375,Male,disloyal Customer,17,Business travel,Eco,812,5,5,5,4,2,5,2,2,1,5,2,4,5,2,0,0.0,satisfied +18207,96058,Female,Loyal Customer,50,Business travel,Eco,183,3,4,3,4,5,3,3,3,3,3,3,4,3,4,3,6.0,neutral or dissatisfied +18208,87843,Female,Loyal Customer,20,Personal Travel,Eco,214,4,4,4,3,1,4,1,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +18209,125484,Female,Loyal Customer,33,Business travel,Business,2917,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +18210,113396,Female,Loyal Customer,46,Business travel,Business,2701,0,1,1,5,2,4,5,4,4,4,4,4,4,5,29,28.0,satisfied +18211,37923,Male,Loyal Customer,43,Personal Travel,Eco,937,4,1,4,4,5,4,4,5,3,5,3,2,4,5,24,7.0,neutral or dissatisfied +18212,63226,Male,Loyal Customer,55,Business travel,Business,337,1,1,1,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +18213,88657,Female,Loyal Customer,52,Personal Travel,Eco,404,1,5,1,2,5,5,4,2,2,1,3,4,2,4,0,3.0,neutral or dissatisfied +18214,83943,Female,Loyal Customer,50,Business travel,Business,1793,3,3,3,3,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +18215,120234,Female,Loyal Customer,8,Personal Travel,Eco,1303,2,4,2,4,5,2,5,5,1,4,3,1,3,5,9,8.0,neutral or dissatisfied +18216,16438,Male,disloyal Customer,25,Business travel,Eco,416,2,2,1,3,5,1,5,5,2,3,4,4,3,5,39,41.0,neutral or dissatisfied +18217,109245,Male,Loyal Customer,14,Personal Travel,Eco,612,2,2,2,4,4,2,1,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +18218,59919,Male,Loyal Customer,47,Business travel,Business,3211,5,5,5,5,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +18219,42351,Female,Loyal Customer,34,Personal Travel,Eco,726,4,5,4,3,2,4,2,2,1,4,3,1,4,2,0,0.0,neutral or dissatisfied +18220,100128,Female,disloyal Customer,40,Business travel,Business,725,5,5,5,4,3,5,3,3,4,2,5,3,5,3,0,0.0,satisfied +18221,47011,Male,Loyal Customer,44,Business travel,Eco,771,5,4,4,4,5,5,5,2,3,2,1,5,4,5,183,171.0,satisfied +18222,48942,Female,Loyal Customer,46,Business travel,Business,2218,2,2,2,2,4,3,1,4,4,4,5,4,4,1,0,0.0,satisfied +18223,93353,Female,Loyal Customer,57,Business travel,Eco,836,2,3,3,3,1,4,3,3,3,2,3,3,3,1,13,14.0,neutral or dissatisfied +18224,57551,Female,disloyal Customer,23,Business travel,Eco,1133,2,2,2,2,1,2,1,1,5,3,4,3,4,1,102,83.0,neutral or dissatisfied +18225,110367,Male,Loyal Customer,47,Business travel,Eco,919,4,3,3,3,4,4,4,4,3,1,3,1,4,4,5,0.0,neutral or dissatisfied +18226,38942,Female,Loyal Customer,14,Personal Travel,Eco,162,3,5,3,3,2,3,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +18227,75790,Female,Loyal Customer,22,Personal Travel,Eco,813,2,0,2,3,1,2,5,1,3,4,3,2,2,1,11,0.0,neutral or dissatisfied +18228,22455,Male,Loyal Customer,52,Personal Travel,Eco,143,4,5,4,1,5,4,5,5,1,3,2,4,4,5,0,0.0,satisfied +18229,61829,Male,Loyal Customer,45,Business travel,Business,2284,2,1,2,2,2,4,5,4,4,4,4,5,4,4,3,2.0,satisfied +18230,37488,Female,Loyal Customer,29,Business travel,Business,3188,1,1,1,1,5,4,4,5,4,4,1,4,4,4,145,128.0,satisfied +18231,86726,Female,Loyal Customer,61,Personal Travel,Eco,1747,3,0,3,5,1,3,1,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +18232,46029,Male,Loyal Customer,50,Business travel,Business,996,4,4,5,4,3,4,3,3,3,5,3,4,3,3,10,14.0,satisfied +18233,77005,Male,disloyal Customer,33,Business travel,Eco,368,3,1,3,4,1,3,3,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +18234,99627,Female,disloyal Customer,43,Business travel,Eco,824,1,1,1,3,4,1,4,4,3,4,5,5,4,4,16,0.0,neutral or dissatisfied +18235,107179,Male,Loyal Customer,58,Business travel,Business,668,3,3,3,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +18236,110054,Male,Loyal Customer,17,Personal Travel,Eco,2039,4,5,4,2,5,4,5,5,4,4,5,4,5,5,6,14.0,neutral or dissatisfied +18237,65022,Female,Loyal Customer,38,Personal Travel,Eco,247,5,4,5,3,4,5,2,4,5,4,5,5,5,4,11,4.0,satisfied +18238,104042,Male,Loyal Customer,36,Business travel,Business,3834,5,5,4,5,2,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +18239,57793,Male,Loyal Customer,69,Personal Travel,Eco Plus,2704,3,5,3,2,3,1,1,4,5,4,5,1,3,1,24,34.0,neutral or dissatisfied +18240,10570,Male,Loyal Customer,53,Business travel,Business,316,5,5,5,5,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +18241,39431,Female,Loyal Customer,59,Business travel,Business,129,4,4,5,4,3,1,4,4,4,4,5,4,4,2,0,0.0,satisfied +18242,119776,Male,Loyal Customer,14,Business travel,Business,3457,1,1,1,1,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +18243,26200,Female,Loyal Customer,39,Business travel,Business,1717,2,2,5,2,5,1,5,3,3,4,3,2,3,4,0,0.0,satisfied +18244,111605,Female,Loyal Customer,10,Personal Travel,Eco Plus,883,5,4,5,4,3,5,3,3,5,2,3,3,4,3,0,0.0,satisfied +18245,37313,Female,disloyal Customer,32,Business travel,Eco,972,2,2,2,4,1,2,1,1,4,5,4,1,3,1,0,0.0,neutral or dissatisfied +18246,108799,Female,Loyal Customer,29,Personal Travel,Eco,406,2,5,2,4,2,2,2,2,1,3,1,2,1,2,22,10.0,neutral or dissatisfied +18247,58372,Female,disloyal Customer,21,Business travel,Eco,733,4,5,5,4,3,5,3,3,3,4,4,5,5,3,0,0.0,satisfied +18248,59739,Female,Loyal Customer,17,Personal Travel,Business,1062,1,4,1,1,1,1,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +18249,38824,Female,Loyal Customer,53,Personal Travel,Eco,354,3,3,3,3,2,5,4,5,5,3,5,1,5,2,25,23.0,neutral or dissatisfied +18250,80213,Male,disloyal Customer,23,Business travel,Eco,2153,3,3,3,1,5,3,5,5,3,4,3,5,5,5,0,0.0,neutral or dissatisfied +18251,48663,Male,Loyal Customer,58,Business travel,Business,3301,3,3,5,3,5,5,5,5,5,4,5,3,5,5,0,4.0,satisfied +18252,118280,Female,Loyal Customer,26,Business travel,Business,2413,5,5,5,5,4,4,4,4,3,3,5,5,5,4,23,8.0,satisfied +18253,98782,Male,disloyal Customer,34,Business travel,Business,630,2,2,2,3,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +18254,79963,Male,Loyal Customer,45,Business travel,Eco,669,5,1,1,1,5,5,5,5,5,1,1,4,3,5,0,0.0,satisfied +18255,36069,Male,Loyal Customer,43,Business travel,Eco,399,4,2,2,2,4,4,4,4,2,3,3,2,5,4,0,4.0,satisfied +18256,125527,Male,disloyal Customer,26,Business travel,Business,226,1,4,1,4,5,1,2,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +18257,15637,Female,disloyal Customer,25,Business travel,Eco Plus,229,0,0,0,1,4,0,4,4,5,3,4,4,2,4,0,0.0,satisfied +18258,27981,Male,Loyal Customer,28,Business travel,Eco Plus,2378,4,2,2,2,4,4,4,2,3,5,4,4,1,4,1,15.0,satisfied +18259,31405,Male,Loyal Customer,30,Business travel,Business,1546,2,3,3,3,2,2,2,2,4,2,4,1,4,2,0,4.0,neutral or dissatisfied +18260,61736,Female,Loyal Customer,75,Business travel,Business,3392,3,3,3,3,4,4,3,4,4,4,3,2,4,4,37,18.0,neutral or dissatisfied +18261,122710,Female,Loyal Customer,34,Personal Travel,Eco,813,3,5,3,1,3,3,2,3,4,4,1,4,1,3,19,8.0,neutral or dissatisfied +18262,63159,Female,disloyal Customer,37,Business travel,Business,337,1,1,1,1,2,1,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +18263,73249,Male,Loyal Customer,56,Business travel,Business,3318,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +18264,15161,Male,Loyal Customer,28,Business travel,Eco Plus,912,3,1,5,1,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +18265,98592,Male,disloyal Customer,22,Business travel,Eco,834,3,3,3,1,4,3,1,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +18266,108121,Female,Loyal Customer,49,Business travel,Business,997,1,1,1,1,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +18267,53973,Male,Loyal Customer,41,Personal Travel,Eco,1117,3,4,3,3,1,3,1,1,5,2,4,5,5,1,0,0.0,neutral or dissatisfied +18268,89784,Male,Loyal Customer,40,Personal Travel,Eco,1076,2,4,2,3,4,2,4,4,4,2,3,2,4,4,31,19.0,neutral or dissatisfied +18269,94945,Male,Loyal Customer,65,Business travel,Business,3447,2,3,1,1,4,3,4,2,2,2,2,3,2,1,73,70.0,neutral or dissatisfied +18270,89213,Female,Loyal Customer,28,Personal Travel,Eco,1947,3,3,3,4,5,3,5,5,4,3,3,2,4,5,20,37.0,neutral or dissatisfied +18271,64592,Male,Loyal Customer,45,Business travel,Business,3227,0,0,0,2,5,4,4,1,1,1,1,5,1,5,0,0.0,satisfied +18272,21392,Male,Loyal Customer,49,Business travel,Business,331,0,0,0,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +18273,69084,Female,Loyal Customer,14,Personal Travel,Eco,1389,3,4,3,4,4,3,4,4,3,1,3,4,4,4,0,6.0,neutral or dissatisfied +18274,89484,Female,Loyal Customer,50,Business travel,Business,1931,1,5,1,1,4,5,5,4,2,5,4,5,4,5,170,164.0,satisfied +18275,46133,Male,Loyal Customer,48,Business travel,Eco,604,4,3,3,3,4,4,4,4,2,3,4,1,2,4,0,0.0,satisfied +18276,65531,Male,Loyal Customer,19,Personal Travel,Eco,1616,3,2,3,4,3,3,3,3,3,3,4,1,3,3,33,39.0,neutral or dissatisfied +18277,15759,Female,Loyal Customer,64,Personal Travel,Eco,461,3,4,5,2,5,3,4,4,5,1,3,4,3,4,135,125.0,neutral or dissatisfied +18278,56749,Male,Loyal Customer,35,Business travel,Business,3498,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,5.0,satisfied +18279,29218,Male,disloyal Customer,30,Business travel,Business,859,4,4,4,2,3,4,3,3,4,5,5,3,4,3,0,4.0,neutral or dissatisfied +18280,81617,Male,Loyal Customer,79,Business travel,Eco Plus,334,3,3,3,3,3,3,3,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +18281,22538,Female,Loyal Customer,21,Personal Travel,Eco Plus,143,2,3,0,4,3,0,3,3,3,4,2,5,4,3,0,0.0,neutral or dissatisfied +18282,86082,Female,Loyal Customer,53,Business travel,Business,2130,1,1,1,1,2,4,4,5,5,5,5,5,5,4,22,20.0,satisfied +18283,536,Female,Loyal Customer,51,Business travel,Business,134,5,5,5,5,4,4,5,5,5,5,4,5,5,3,0,0.0,satisfied +18284,101744,Male,Loyal Customer,39,Business travel,Business,1590,1,1,1,1,5,5,5,4,4,5,4,3,4,5,1,0.0,satisfied +18285,51906,Female,Loyal Customer,62,Business travel,Business,2228,5,5,5,5,1,5,2,5,5,5,4,2,5,1,0,0.0,satisfied +18286,14620,Female,Loyal Customer,31,Business travel,Business,450,2,2,4,2,4,4,4,4,2,3,4,4,5,4,90,100.0,satisfied +18287,109660,Female,Loyal Customer,38,Business travel,Eco,802,3,3,3,3,3,3,3,3,1,1,3,3,4,3,30,28.0,neutral or dissatisfied +18288,112589,Female,disloyal Customer,40,Business travel,Business,602,1,1,1,2,2,1,2,2,3,4,5,5,5,2,4,0.0,neutral or dissatisfied +18289,45846,Female,Loyal Customer,9,Personal Travel,Eco,391,4,4,5,1,4,5,4,4,3,5,5,5,5,4,0,0.0,satisfied +18290,64045,Female,Loyal Customer,22,Business travel,Business,3933,1,1,2,1,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +18291,24513,Male,Loyal Customer,27,Business travel,Eco Plus,547,5,2,2,2,5,5,5,5,3,3,4,5,3,5,0,0.0,satisfied +18292,89471,Female,Loyal Customer,62,Business travel,Eco Plus,151,3,1,1,1,4,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +18293,64149,Male,disloyal Customer,46,Business travel,Business,989,3,3,3,4,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +18294,55284,Male,Loyal Customer,29,Business travel,Business,1608,4,4,4,4,4,4,4,4,3,4,4,3,4,4,11,0.0,satisfied +18295,46044,Male,disloyal Customer,25,Business travel,Eco,991,2,2,2,4,2,2,2,2,3,3,1,5,2,2,0,0.0,neutral or dissatisfied +18296,50202,Female,Loyal Customer,33,Business travel,Business,56,4,5,4,5,1,1,2,4,4,4,4,2,4,2,0,0.0,satisfied +18297,128012,Female,Loyal Customer,20,Personal Travel,Eco Plus,1488,3,1,3,3,4,3,4,4,3,2,3,3,2,4,1,21.0,neutral or dissatisfied +18298,57808,Female,Loyal Customer,21,Personal Travel,Eco,1235,1,4,1,4,5,1,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +18299,93961,Male,Loyal Customer,25,Personal Travel,Eco Plus,507,1,5,1,1,5,1,5,5,4,4,4,4,5,5,4,12.0,neutral or dissatisfied +18300,59724,Male,Loyal Customer,80,Business travel,Eco Plus,556,4,5,5,5,4,4,4,4,1,5,5,4,2,4,0,0.0,satisfied +18301,9788,Male,Loyal Customer,15,Personal Travel,Eco,383,3,4,2,2,4,2,4,4,4,2,4,3,4,4,2,0.0,neutral or dissatisfied +18302,19628,Female,Loyal Customer,24,Business travel,Business,3689,1,2,1,1,5,5,5,5,1,4,3,3,1,5,0,0.0,satisfied +18303,43626,Male,Loyal Customer,41,Personal Travel,Eco,228,3,5,3,1,1,3,1,1,5,2,4,5,4,1,0,3.0,neutral or dissatisfied +18304,66847,Male,Loyal Customer,28,Personal Travel,Eco,731,1,5,0,2,4,0,4,4,3,3,5,4,3,4,2,0.0,neutral or dissatisfied +18305,86784,Male,disloyal Customer,24,Business travel,Business,484,5,0,5,2,5,5,5,5,3,3,4,4,5,5,2,0.0,satisfied +18306,51811,Male,Loyal Customer,18,Personal Travel,Eco,261,4,3,4,2,2,4,2,2,1,4,2,1,2,2,0,2.0,neutral or dissatisfied +18307,54973,Male,Loyal Customer,24,Business travel,Business,3979,3,3,3,3,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +18308,51652,Female,Loyal Customer,39,Business travel,Business,2633,5,5,2,5,1,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +18309,128434,Female,Loyal Customer,59,Business travel,Eco,338,2,1,1,1,4,3,3,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +18310,94621,Male,Loyal Customer,36,Business travel,Business,239,3,3,3,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +18311,107256,Female,Loyal Customer,55,Business travel,Business,3143,3,3,3,3,2,5,4,4,4,4,4,5,4,4,13,12.0,satisfied +18312,108832,Female,Loyal Customer,39,Business travel,Business,2617,3,4,2,4,4,3,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +18313,46865,Male,disloyal Customer,25,Business travel,Eco,819,3,3,3,2,3,1,1,5,2,5,3,1,4,1,150,165.0,neutral or dissatisfied +18314,77519,Female,Loyal Customer,35,Personal Travel,Eco,1521,1,3,1,3,3,1,3,3,1,4,3,1,2,3,0,0.0,neutral or dissatisfied +18315,38173,Female,Loyal Customer,50,Personal Travel,Eco,1237,0,4,1,1,3,3,5,4,4,1,4,3,4,3,0,0.0,satisfied +18316,5883,Female,disloyal Customer,55,Business travel,Business,173,4,4,4,1,1,4,1,1,4,3,5,4,5,1,6,10.0,satisfied +18317,44174,Female,Loyal Customer,34,Business travel,Business,157,1,1,1,1,1,2,2,5,5,5,3,1,5,5,0,30.0,satisfied +18318,6870,Female,Loyal Customer,30,Personal Travel,Eco,622,2,3,2,4,2,2,2,2,2,5,3,1,4,2,0,6.0,neutral or dissatisfied +18319,23715,Female,Loyal Customer,24,Personal Travel,Eco,73,3,5,0,2,3,0,1,3,2,3,3,1,2,3,7,0.0,neutral or dissatisfied +18320,114728,Female,Loyal Customer,36,Business travel,Business,373,2,2,2,2,2,5,4,5,5,4,5,5,5,3,14,11.0,satisfied +18321,98056,Female,Loyal Customer,21,Personal Travel,Eco,1751,2,5,2,1,1,2,1,1,3,3,3,3,2,1,0,22.0,neutral or dissatisfied +18322,55915,Female,Loyal Customer,34,Personal Travel,Eco,733,2,3,3,3,1,3,1,1,2,4,4,3,3,1,0,0.0,neutral or dissatisfied +18323,46505,Male,Loyal Customer,42,Business travel,Business,141,1,1,2,1,2,1,2,4,4,4,4,3,4,1,5,10.0,satisfied +18324,10895,Male,Loyal Customer,27,Business travel,Business,1796,1,3,3,3,2,2,1,2,4,2,3,4,3,2,25,40.0,neutral or dissatisfied +18325,103885,Male,Loyal Customer,67,Personal Travel,Eco,882,1,4,1,1,1,5,5,3,2,5,1,5,2,5,204,188.0,neutral or dissatisfied +18326,65857,Female,Loyal Customer,49,Personal Travel,Eco,1389,3,4,3,3,5,3,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +18327,15578,Female,Loyal Customer,54,Business travel,Business,292,2,5,5,5,3,3,2,2,2,2,2,2,2,4,117,105.0,neutral or dissatisfied +18328,83627,Female,Loyal Customer,43,Personal Travel,Eco,409,3,4,3,3,5,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +18329,26548,Male,Loyal Customer,14,Personal Travel,Eco,1105,1,1,1,3,3,1,3,3,1,1,3,1,2,3,16,51.0,neutral or dissatisfied +18330,128063,Male,Loyal Customer,56,Business travel,Business,2845,4,4,4,4,4,4,4,3,5,3,4,4,5,4,0,8.0,satisfied +18331,91530,Female,Loyal Customer,46,Business travel,Business,2633,5,5,5,5,4,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +18332,74606,Male,Loyal Customer,47,Business travel,Eco,1235,2,3,3,3,2,2,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +18333,43938,Male,Loyal Customer,40,Personal Travel,Eco Plus,114,1,2,1,3,1,2,3,1,1,2,3,3,3,3,127,148.0,neutral or dissatisfied +18334,121824,Male,disloyal Customer,42,Business travel,Business,449,3,3,3,2,5,3,5,5,5,2,5,4,4,5,42,44.0,neutral or dissatisfied +18335,72792,Male,Loyal Customer,80,Business travel,Eco,645,5,1,1,1,4,5,4,4,4,5,4,5,2,4,0,0.0,satisfied +18336,94522,Male,Loyal Customer,36,Business travel,Business,2634,3,3,3,3,4,4,4,4,4,4,4,3,4,5,8,0.0,satisfied +18337,12971,Male,Loyal Customer,17,Business travel,Business,374,4,1,1,1,4,4,4,4,1,3,3,4,3,4,4,8.0,neutral or dissatisfied +18338,59988,Male,Loyal Customer,45,Personal Travel,Eco,937,3,4,3,4,2,3,2,2,2,1,4,2,3,2,86,61.0,neutral or dissatisfied +18339,26229,Male,Loyal Customer,42,Personal Travel,Eco,406,2,4,2,2,4,2,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +18340,34493,Female,Loyal Customer,30,Business travel,Business,1990,2,4,4,4,2,2,2,2,2,4,3,4,2,2,20,9.0,neutral or dissatisfied +18341,109817,Female,Loyal Customer,53,Business travel,Business,1033,1,1,1,1,4,4,4,2,2,2,2,5,2,4,0,3.0,satisfied +18342,94328,Female,Loyal Customer,51,Business travel,Business,1975,0,4,0,4,2,4,5,1,1,1,1,5,1,3,9,0.0,satisfied +18343,33111,Male,Loyal Customer,44,Personal Travel,Eco,216,1,5,1,5,5,1,5,5,3,2,5,3,4,5,7,15.0,neutral or dissatisfied +18344,88135,Female,Loyal Customer,56,Business travel,Business,545,4,4,5,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +18345,97327,Female,Loyal Customer,9,Business travel,Business,2227,4,1,1,1,4,4,4,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +18346,56260,Male,disloyal Customer,40,Business travel,Business,404,1,1,1,5,4,1,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +18347,112586,Female,Loyal Customer,31,Business travel,Business,602,4,4,3,4,4,4,4,4,4,2,4,3,4,4,13,8.0,satisfied +18348,100690,Female,Loyal Customer,37,Personal Travel,Eco,677,1,4,1,3,5,1,5,5,4,1,4,3,4,5,0,14.0,neutral or dissatisfied +18349,23909,Female,Loyal Customer,41,Business travel,Eco,589,4,5,5,5,4,4,4,4,4,1,5,2,4,4,0,0.0,satisfied +18350,73948,Male,disloyal Customer,16,Business travel,Eco,731,4,4,4,4,1,4,1,1,3,4,4,3,4,1,27,29.0,neutral or dissatisfied +18351,30398,Female,Loyal Customer,60,Personal Travel,Eco,862,3,4,3,2,5,4,4,4,4,3,5,4,4,5,30,38.0,neutral or dissatisfied +18352,26714,Male,Loyal Customer,55,Personal Travel,Eco,404,4,5,4,3,1,4,1,1,4,2,5,5,4,1,0,2.0,neutral or dissatisfied +18353,27498,Male,Loyal Customer,39,Business travel,Business,1935,5,5,5,5,4,1,2,4,4,4,4,3,4,2,0,0.0,satisfied +18354,42024,Male,Loyal Customer,65,Business travel,Business,106,2,4,4,4,1,3,4,1,1,1,2,1,1,4,0,0.0,neutral or dissatisfied +18355,68674,Female,disloyal Customer,22,Business travel,Business,237,5,4,4,5,5,4,5,5,4,2,5,3,4,5,0,0.0,satisfied +18356,41961,Female,disloyal Customer,30,Business travel,Eco,575,2,3,2,3,2,2,5,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +18357,74923,Male,disloyal Customer,30,Business travel,Eco,1375,1,1,1,2,5,1,5,5,2,4,2,1,3,5,32,18.0,neutral or dissatisfied +18358,27550,Female,Loyal Customer,14,Personal Travel,Eco,978,1,5,1,3,3,1,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +18359,60327,Female,Loyal Customer,59,Business travel,Business,3237,3,3,2,3,3,4,4,5,5,5,5,5,5,4,40,31.0,satisfied +18360,119180,Male,disloyal Customer,35,Business travel,Business,331,3,3,3,2,4,3,1,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +18361,119983,Female,Loyal Customer,41,Personal Travel,Eco,868,4,5,4,1,3,4,3,3,2,1,5,1,5,3,0,0.0,neutral or dissatisfied +18362,18576,Female,disloyal Customer,39,Business travel,Business,190,3,3,3,2,4,3,1,4,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +18363,32908,Male,Loyal Customer,38,Personal Travel,Eco,101,2,3,2,1,3,2,5,3,5,5,5,3,2,3,0,0.0,neutral or dissatisfied +18364,16369,Female,Loyal Customer,50,Business travel,Business,1325,5,5,2,5,4,5,5,5,5,5,5,4,5,4,0,23.0,satisfied +18365,836,Male,Loyal Customer,39,Business travel,Business,2879,3,5,5,5,1,4,3,2,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +18366,52344,Male,Loyal Customer,58,Business travel,Eco,493,4,2,2,2,4,4,4,4,4,1,1,1,5,4,0,0.0,satisfied +18367,54854,Male,Loyal Customer,40,Business travel,Eco,775,4,3,3,3,4,4,4,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +18368,116725,Male,Loyal Customer,56,Business travel,Eco Plus,417,4,1,1,1,4,4,4,4,1,1,4,2,1,4,0,0.0,satisfied +18369,16449,Male,Loyal Customer,74,Business travel,Eco,416,1,1,1,1,1,1,1,1,4,1,4,1,3,1,98,81.0,neutral or dissatisfied +18370,96267,Female,Loyal Customer,58,Personal Travel,Eco,546,5,3,5,2,1,2,5,4,4,5,4,3,4,4,2,0.0,satisfied +18371,124790,Female,Loyal Customer,53,Business travel,Business,280,3,5,5,5,1,4,4,3,3,3,3,2,3,1,74,100.0,neutral or dissatisfied +18372,30000,Male,Loyal Customer,43,Business travel,Eco,399,4,3,3,3,5,4,5,5,3,1,4,2,3,5,0,0.0,satisfied +18373,103132,Male,Loyal Customer,21,Business travel,Eco Plus,460,2,4,4,4,2,2,3,2,3,1,4,4,4,2,5,3.0,neutral or dissatisfied +18374,129207,Male,Loyal Customer,46,Business travel,Business,1563,1,3,3,3,1,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +18375,95915,Male,Loyal Customer,49,Business travel,Business,1504,1,3,3,3,4,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +18376,103046,Male,Loyal Customer,38,Business travel,Business,3615,2,2,2,2,2,3,3,2,2,2,2,4,2,4,84,78.0,neutral or dissatisfied +18377,123269,Female,Loyal Customer,27,Personal Travel,Eco,468,1,3,4,4,2,4,2,2,4,3,3,4,4,2,41,48.0,neutral or dissatisfied +18378,60532,Female,Loyal Customer,14,Personal Travel,Eco,934,2,5,3,2,1,3,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +18379,46740,Male,Loyal Customer,9,Personal Travel,Eco,125,1,5,1,5,1,1,1,1,1,3,1,3,2,1,0,0.0,neutral or dissatisfied +18380,44360,Female,Loyal Customer,51,Business travel,Business,1632,2,5,5,5,4,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +18381,70977,Female,Loyal Customer,34,Business travel,Business,2212,1,1,1,1,5,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +18382,19372,Female,Loyal Customer,52,Personal Travel,Eco,476,3,4,2,3,2,1,1,3,3,4,3,1,1,1,176,177.0,neutral or dissatisfied +18383,94414,Female,disloyal Customer,36,Business travel,Business,458,2,2,2,2,2,2,2,2,3,4,4,5,5,2,8,5.0,neutral or dissatisfied +18384,14021,Male,Loyal Customer,60,Personal Travel,Eco,182,3,3,3,4,2,3,4,2,2,3,1,4,4,2,0,0.0,neutral or dissatisfied +18385,115621,Female,disloyal Customer,25,Business travel,Business,325,3,5,3,2,5,3,5,5,3,4,5,5,4,5,1,0.0,neutral or dissatisfied +18386,48247,Male,Loyal Customer,31,Personal Travel,Eco,259,2,5,2,5,3,2,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +18387,34039,Female,Loyal Customer,26,Business travel,Eco Plus,1598,2,3,3,3,2,2,3,2,4,3,2,4,3,2,5,0.0,neutral or dissatisfied +18388,39603,Male,Loyal Customer,60,Personal Travel,Eco,954,2,3,2,2,2,2,2,2,5,3,5,3,5,2,6,0.0,neutral or dissatisfied +18389,37348,Female,disloyal Customer,28,Business travel,Eco,1074,2,2,2,1,5,2,5,5,2,3,2,5,4,5,26,21.0,satisfied +18390,59319,Male,Loyal Customer,48,Business travel,Business,2338,4,4,4,4,2,5,4,5,5,5,5,3,5,4,12,3.0,satisfied +18391,112717,Male,Loyal Customer,10,Personal Travel,Eco,671,2,5,2,3,3,2,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +18392,41542,Male,Loyal Customer,10,Business travel,Business,1269,4,4,1,1,4,4,4,4,1,2,3,2,2,4,0,8.0,neutral or dissatisfied +18393,21887,Male,disloyal Customer,40,Business travel,Eco,551,1,0,1,3,5,1,5,5,4,5,1,5,4,5,73,80.0,neutral or dissatisfied +18394,110711,Male,disloyal Customer,20,Business travel,Eco,990,2,2,2,3,1,2,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +18395,4924,Male,Loyal Customer,52,Personal Travel,Eco,1020,4,0,4,3,5,4,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +18396,64851,Male,Loyal Customer,50,Business travel,Business,247,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +18397,87495,Male,Loyal Customer,48,Business travel,Business,1621,2,1,1,1,5,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +18398,47568,Female,Loyal Customer,66,Personal Travel,Eco Plus,599,3,3,3,1,5,1,4,1,1,3,2,1,1,2,7,19.0,neutral or dissatisfied +18399,10661,Female,Loyal Customer,46,Business travel,Business,201,5,5,5,5,5,4,5,5,5,5,5,5,5,5,5,6.0,satisfied +18400,32988,Male,Loyal Customer,37,Personal Travel,Eco,163,2,4,2,3,3,2,4,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +18401,61773,Male,Loyal Customer,50,Personal Travel,Eco,1303,2,5,2,3,3,2,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +18402,15633,Female,disloyal Customer,21,Business travel,Eco,296,3,0,3,3,3,3,3,3,5,1,2,3,2,3,113,82.0,neutral or dissatisfied +18403,63953,Male,Loyal Customer,50,Personal Travel,Eco,1172,4,2,3,2,3,4,4,1,5,3,3,4,4,4,180,187.0,neutral or dissatisfied +18404,122458,Female,Loyal Customer,40,Business travel,Business,575,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +18405,34562,Male,Loyal Customer,33,Business travel,Business,1598,3,3,3,3,2,2,2,2,1,3,3,2,5,2,9,5.0,satisfied +18406,127298,Male,Loyal Customer,37,Personal Travel,Eco Plus,1107,3,3,3,2,3,3,3,3,1,3,4,2,1,3,6,0.0,neutral or dissatisfied +18407,56777,Female,Loyal Customer,50,Personal Travel,Eco Plus,1065,2,5,2,4,5,5,4,5,5,2,1,5,5,4,0,0.0,neutral or dissatisfied +18408,102471,Female,Loyal Customer,16,Personal Travel,Eco,414,4,3,4,1,5,4,5,5,2,1,4,4,2,5,0,0.0,satisfied +18409,73444,Male,Loyal Customer,52,Personal Travel,Eco,1012,2,1,1,2,5,1,5,5,3,3,2,2,2,5,5,6.0,neutral or dissatisfied +18410,42511,Male,Loyal Customer,37,Business travel,Eco,1384,4,5,5,5,4,4,4,4,3,3,5,4,5,4,0,29.0,satisfied +18411,119424,Male,Loyal Customer,13,Personal Travel,Eco,399,3,4,3,2,1,3,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +18412,14581,Female,Loyal Customer,42,Business travel,Eco,986,2,3,3,3,1,3,3,2,2,2,2,3,2,3,26,12.0,neutral or dissatisfied +18413,67950,Female,Loyal Customer,47,Personal Travel,Eco,1235,2,5,2,3,2,4,4,3,3,2,4,4,3,5,0,0.0,neutral or dissatisfied +18414,76837,Male,Loyal Customer,47,Business travel,Business,1701,3,3,3,3,3,5,5,4,4,4,4,5,4,4,17,10.0,satisfied +18415,127806,Male,Loyal Customer,46,Business travel,Business,3436,4,4,4,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +18416,85465,Female,disloyal Customer,38,Business travel,Business,214,4,4,4,3,3,4,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +18417,119999,Female,Loyal Customer,43,Business travel,Business,3235,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +18418,5690,Female,Loyal Customer,35,Business travel,Business,3991,3,5,5,5,3,3,3,3,3,3,3,2,3,1,7,11.0,neutral or dissatisfied +18419,52643,Male,Loyal Customer,11,Personal Travel,Eco,160,4,4,0,2,2,0,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +18420,116268,Male,Loyal Customer,41,Personal Travel,Eco,390,5,4,3,3,3,3,3,3,4,2,5,4,4,3,0,0.0,satisfied +18421,117688,Female,Loyal Customer,21,Business travel,Business,1814,4,1,1,1,4,4,4,4,3,2,1,2,2,4,129,112.0,neutral or dissatisfied +18422,116544,Female,Loyal Customer,36,Personal Travel,Eco,373,3,4,3,3,3,3,4,3,4,4,4,1,2,3,16,28.0,neutral or dissatisfied +18423,14467,Male,Loyal Customer,35,Personal Travel,Eco,761,3,5,3,1,3,3,4,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +18424,24517,Female,Loyal Customer,50,Business travel,Eco Plus,516,5,1,1,1,1,1,2,5,5,5,5,4,5,1,7,0.0,satisfied +18425,1115,Male,Loyal Customer,15,Personal Travel,Eco,113,3,5,3,3,1,3,1,1,3,5,5,3,1,1,0,0.0,neutral or dissatisfied +18426,77579,Male,Loyal Customer,59,Business travel,Business,331,1,1,4,1,4,3,3,1,1,1,1,3,1,3,53,46.0,neutral or dissatisfied +18427,23383,Male,Loyal Customer,23,Personal Travel,Eco Plus,1014,3,3,3,3,4,3,4,4,4,5,2,3,3,4,53,44.0,neutral or dissatisfied +18428,67157,Female,Loyal Customer,58,Business travel,Business,529,3,3,3,3,5,2,1,4,4,4,4,1,4,3,0,0.0,satisfied +18429,39959,Male,Loyal Customer,56,Personal Travel,Eco,1087,3,1,3,3,2,3,2,2,1,2,3,2,3,2,0,,neutral or dissatisfied +18430,46179,Male,Loyal Customer,58,Business travel,Eco Plus,604,4,1,2,1,4,4,4,4,3,5,3,2,4,4,0,0.0,satisfied +18431,58603,Female,Loyal Customer,57,Personal Travel,Eco,334,1,5,2,4,2,4,4,4,4,2,4,4,4,3,16,6.0,neutral or dissatisfied +18432,112615,Female,Loyal Customer,58,Personal Travel,Eco,639,1,4,1,5,4,5,5,4,4,1,4,4,4,4,14,13.0,neutral or dissatisfied +18433,121933,Male,Loyal Customer,69,Personal Travel,Eco Plus,449,2,4,2,1,1,2,1,1,4,5,4,3,5,1,57,41.0,neutral or dissatisfied +18434,31876,Female,Loyal Customer,31,Business travel,Eco,4983,4,3,3,3,4,4,4,3,2,5,2,4,1,4,18,0.0,satisfied +18435,3781,Male,Loyal Customer,59,Business travel,Business,3566,3,5,5,5,3,2,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +18436,34469,Female,Loyal Customer,32,Business travel,Eco,266,4,4,4,4,4,4,4,4,3,5,3,5,3,4,0,0.0,satisfied +18437,109986,Female,disloyal Customer,43,Business travel,Eco Plus,1011,4,4,4,4,3,4,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +18438,47078,Male,Loyal Customer,62,Personal Travel,Eco,438,2,1,2,4,5,2,3,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +18439,2156,Male,disloyal Customer,44,Business travel,Business,685,3,3,3,5,1,3,1,1,5,4,5,5,4,1,18,43.0,neutral or dissatisfied +18440,111243,Female,Loyal Customer,57,Business travel,Business,1849,5,5,5,5,4,4,5,4,4,4,4,3,4,4,112,109.0,satisfied +18441,11467,Male,Loyal Customer,58,Business travel,Eco Plus,191,3,3,3,3,3,3,3,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +18442,60372,Male,Loyal Customer,44,Business travel,Business,1452,5,5,5,5,4,4,4,2,2,2,2,5,2,3,1,3.0,satisfied +18443,92334,Female,Loyal Customer,58,Business travel,Business,2486,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +18444,51066,Female,Loyal Customer,62,Personal Travel,Eco,109,3,5,3,3,4,4,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +18445,80753,Male,Loyal Customer,15,Personal Travel,Eco,393,3,1,3,4,3,3,3,3,4,3,3,3,3,3,0,0.0,neutral or dissatisfied +18446,59525,Male,disloyal Customer,40,Business travel,Business,787,3,3,3,3,3,3,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +18447,20393,Male,Loyal Customer,33,Business travel,Eco,459,4,2,2,2,4,4,4,4,3,1,3,2,4,4,35,67.0,neutral or dissatisfied +18448,94826,Female,disloyal Customer,20,Business travel,Eco,187,4,4,4,3,1,4,1,1,2,5,3,4,4,1,0,1.0,neutral or dissatisfied +18449,112476,Male,Loyal Customer,57,Personal Travel,Eco,846,2,5,2,4,3,2,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +18450,90867,Male,Loyal Customer,45,Business travel,Eco,270,3,1,1,1,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +18451,94390,Female,Loyal Customer,56,Business travel,Business,2724,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +18452,26168,Female,Loyal Customer,59,Business travel,Business,1819,4,4,4,4,3,1,3,4,4,4,4,3,4,5,32,14.0,satisfied +18453,14622,Female,Loyal Customer,39,Personal Travel,Eco,450,3,4,3,5,2,3,2,2,3,4,4,4,4,2,85,93.0,neutral or dissatisfied +18454,90333,Female,Loyal Customer,41,Business travel,Business,1973,3,3,3,3,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +18455,51896,Male,Loyal Customer,63,Business travel,Business,601,4,5,5,5,4,3,2,4,4,4,4,2,4,2,1,1.0,neutral or dissatisfied +18456,95003,Male,Loyal Customer,57,Personal Travel,Eco,239,1,4,1,3,2,1,2,2,3,4,4,4,5,2,8,3.0,neutral or dissatisfied +18457,102818,Female,Loyal Customer,33,Business travel,Business,342,1,4,1,1,1,4,3,5,5,5,5,1,5,3,4,0.0,satisfied +18458,122999,Female,Loyal Customer,39,Business travel,Business,3372,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +18459,50291,Male,Loyal Customer,51,Business travel,Business,86,3,3,4,3,2,3,2,1,1,1,3,3,1,4,21,16.0,neutral or dissatisfied +18460,27536,Female,Loyal Customer,65,Personal Travel,Eco,605,2,4,3,4,4,4,5,4,4,3,4,4,4,3,0,5.0,neutral or dissatisfied +18461,123331,Female,Loyal Customer,62,Personal Travel,Eco Plus,590,3,3,2,3,5,4,4,2,2,2,2,2,2,4,0,3.0,neutral or dissatisfied +18462,118498,Male,Loyal Customer,40,Business travel,Business,2554,4,4,3,4,2,4,4,5,5,5,5,5,5,5,44,36.0,satisfied +18463,47225,Male,Loyal Customer,28,Business travel,Eco Plus,748,4,3,3,3,4,4,4,4,4,1,2,2,2,4,120,112.0,satisfied +18464,54160,Male,Loyal Customer,33,Business travel,Business,1569,3,5,5,5,3,3,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +18465,33546,Male,Loyal Customer,56,Business travel,Eco,413,5,1,1,1,5,5,5,5,5,3,4,2,4,5,0,0.0,satisfied +18466,125752,Female,Loyal Customer,44,Business travel,Business,3749,5,5,5,5,4,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +18467,65658,Male,Loyal Customer,38,Business travel,Business,861,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +18468,83059,Female,Loyal Customer,33,Business travel,Business,3716,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +18469,50707,Male,Loyal Customer,59,Personal Travel,Eco,262,4,5,4,3,4,2,2,5,4,5,5,2,1,2,180,172.0,neutral or dissatisfied +18470,44414,Male,Loyal Customer,61,Personal Travel,Eco,323,2,5,2,2,4,2,4,4,4,4,3,5,4,4,0,0.0,neutral or dissatisfied +18471,96273,Female,Loyal Customer,53,Personal Travel,Eco,546,3,3,3,2,5,3,2,3,3,3,3,5,3,1,0,0.0,neutral or dissatisfied +18472,82132,Female,Loyal Customer,54,Business travel,Business,2519,2,2,3,2,5,5,5,5,2,5,5,5,5,5,0,16.0,satisfied +18473,327,Female,Loyal Customer,39,Business travel,Business,821,1,3,3,3,1,4,4,1,1,1,1,1,1,3,12,32.0,neutral or dissatisfied +18474,127432,Female,Loyal Customer,13,Personal Travel,Eco,868,1,2,1,3,2,1,5,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +18475,113788,Female,Loyal Customer,48,Business travel,Business,2084,2,2,2,2,4,5,4,4,4,4,5,5,4,3,0,0.0,satisfied +18476,42409,Male,Loyal Customer,17,Business travel,Eco Plus,462,2,5,5,5,2,2,3,2,2,1,3,2,3,2,22,21.0,neutral or dissatisfied +18477,26929,Male,Loyal Customer,52,Personal Travel,Eco,1874,5,3,5,3,2,5,2,2,2,4,4,4,4,2,0,0.0,satisfied +18478,13203,Female,Loyal Customer,12,Business travel,Eco Plus,542,2,4,4,4,2,2,4,2,2,1,3,2,3,2,35,32.0,neutral or dissatisfied +18479,54688,Female,Loyal Customer,32,Business travel,Business,2391,1,3,3,3,1,1,1,1,3,2,3,3,3,1,5,0.0,neutral or dissatisfied +18480,76697,Female,Loyal Customer,50,Personal Travel,Eco,481,2,2,2,2,2,3,3,5,5,2,5,2,5,2,5,0.0,neutral or dissatisfied +18481,87007,Male,Loyal Customer,46,Personal Travel,Eco,907,4,5,4,2,2,4,2,2,5,2,5,5,4,2,32,29.0,neutral or dissatisfied +18482,31657,Female,Loyal Customer,26,Business travel,Business,846,5,5,4,5,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +18483,95050,Female,Loyal Customer,40,Personal Travel,Eco,496,3,5,3,1,3,3,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +18484,67605,Male,disloyal Customer,22,Business travel,Business,1242,0,0,0,2,3,0,3,3,3,4,4,3,5,3,0,2.0,satisfied +18485,129285,Male,Loyal Customer,42,Business travel,Business,550,3,3,3,3,2,3,3,3,5,1,2,3,2,3,135,134.0,neutral or dissatisfied +18486,41034,Male,disloyal Customer,38,Business travel,Business,1087,3,3,3,3,2,3,2,2,2,3,2,2,3,2,0,0.0,neutral or dissatisfied +18487,116847,Male,Loyal Customer,68,Personal Travel,Business,370,2,4,2,1,3,2,4,2,2,2,2,1,2,2,12,10.0,neutral or dissatisfied +18488,28005,Male,Loyal Customer,25,Business travel,Business,2239,2,2,2,2,5,5,5,5,5,2,3,1,5,5,0,0.0,satisfied +18489,116781,Female,Loyal Customer,18,Personal Travel,Eco Plus,446,3,5,3,1,5,3,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +18490,19914,Female,Loyal Customer,23,Business travel,Business,3204,1,3,3,3,1,1,1,1,2,1,3,4,2,1,76,90.0,neutral or dissatisfied +18491,83854,Male,Loyal Customer,66,Personal Travel,Eco,425,1,0,3,2,3,3,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +18492,55506,Female,Loyal Customer,40,Business travel,Business,1739,3,3,3,3,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +18493,95630,Female,Loyal Customer,31,Personal Travel,Eco,756,2,3,2,3,2,2,2,2,3,1,3,4,2,2,27,27.0,neutral or dissatisfied +18494,7127,Male,Loyal Customer,41,Business travel,Business,2231,2,2,2,2,2,4,5,5,5,5,5,5,5,4,12,4.0,satisfied +18495,51366,Female,Loyal Customer,12,Personal Travel,Eco Plus,89,1,4,1,3,3,1,3,3,4,5,5,2,3,3,0,0.0,neutral or dissatisfied +18496,10229,Female,Loyal Customer,61,Business travel,Business,458,4,4,4,4,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +18497,36222,Male,Loyal Customer,41,Business travel,Business,280,2,3,3,3,5,4,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +18498,57158,Female,Loyal Customer,26,Personal Travel,Eco,1824,3,4,3,4,4,3,5,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +18499,92170,Female,Loyal Customer,36,Business travel,Eco,2079,3,1,1,1,3,3,3,3,1,1,2,2,4,3,2,6.0,neutral or dissatisfied +18500,87584,Male,Loyal Customer,46,Personal Travel,Eco,432,1,4,1,4,4,1,4,4,4,1,4,1,4,4,4,0.0,neutral or dissatisfied +18501,120415,Male,Loyal Customer,20,Business travel,Business,2800,1,1,1,1,5,5,5,5,3,5,5,4,5,5,0,0.0,satisfied +18502,7918,Male,Loyal Customer,36,Personal Travel,Eco,1020,1,5,1,3,4,1,4,4,5,3,5,5,3,4,11,2.0,neutral or dissatisfied +18503,36087,Male,Loyal Customer,50,Personal Travel,Eco,399,2,4,2,3,2,1,1,5,3,4,5,1,3,1,202,219.0,neutral or dissatisfied +18504,28470,Male,Loyal Customer,27,Business travel,Eco,1721,5,5,5,5,5,5,5,5,2,5,3,3,2,5,0,0.0,satisfied +18505,52878,Male,Loyal Customer,22,Business travel,Business,3294,3,4,1,4,3,3,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +18506,106821,Female,Loyal Customer,34,Business travel,Business,1488,1,1,1,1,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +18507,71887,Male,Loyal Customer,8,Personal Travel,Eco,1744,1,5,0,3,5,0,4,5,3,2,5,4,4,5,1,0.0,neutral or dissatisfied +18508,20395,Male,Loyal Customer,12,Personal Travel,Eco,588,1,4,1,2,2,1,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +18509,110386,Female,Loyal Customer,9,Business travel,Business,3814,2,3,4,3,2,2,2,2,3,1,4,1,3,2,83,83.0,neutral or dissatisfied +18510,13907,Female,disloyal Customer,44,Business travel,Eco,192,3,4,3,1,3,3,3,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +18511,49292,Male,Loyal Customer,35,Business travel,Eco,156,3,4,4,4,3,3,3,3,4,1,3,2,2,3,0,0.0,neutral or dissatisfied +18512,31658,Male,Loyal Customer,59,Business travel,Eco,844,4,3,3,3,4,4,4,4,2,2,4,1,3,4,0,0.0,satisfied +18513,32944,Female,Loyal Customer,64,Personal Travel,Eco,101,2,5,2,2,3,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +18514,15925,Male,Loyal Customer,31,Business travel,Business,1846,1,5,5,5,1,1,1,1,4,3,4,4,4,1,0,8.0,neutral or dissatisfied +18515,6182,Female,Loyal Customer,49,Personal Travel,Eco,409,3,5,3,1,2,4,5,1,1,3,3,5,1,5,0,15.0,neutral or dissatisfied +18516,114476,Male,Loyal Customer,54,Business travel,Business,325,2,3,3,3,4,3,3,2,2,2,2,1,2,2,2,1.0,neutral or dissatisfied +18517,96573,Female,disloyal Customer,26,Business travel,Eco,333,3,2,3,3,2,3,2,2,1,3,4,2,4,2,19,18.0,neutral or dissatisfied +18518,19020,Female,Loyal Customer,10,Personal Travel,Eco,871,1,1,2,2,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +18519,112403,Female,Loyal Customer,42,Business travel,Business,2020,2,2,2,2,3,5,5,4,4,4,4,4,4,5,29,44.0,satisfied +18520,78952,Male,Loyal Customer,38,Business travel,Business,3402,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18521,38678,Female,Loyal Customer,36,Personal Travel,Eco,2704,4,3,4,4,1,4,1,1,2,4,4,3,4,1,0,0.0,neutral or dissatisfied +18522,103518,Male,Loyal Customer,34,Personal Travel,Eco,1047,2,4,2,4,5,2,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +18523,80595,Female,Loyal Customer,8,Business travel,Business,1747,3,3,3,3,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +18524,17611,Male,Loyal Customer,17,Personal Travel,Eco,196,2,5,2,4,3,2,1,3,5,4,5,3,5,3,65,75.0,neutral or dissatisfied +18525,60933,Male,Loyal Customer,53,Business travel,Business,3339,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,14.0,satisfied +18526,114427,Male,Loyal Customer,39,Business travel,Business,2460,0,1,1,5,5,5,4,3,3,3,3,5,3,5,45,45.0,satisfied +18527,115727,Female,Loyal Customer,25,Business travel,Business,3355,2,4,4,4,2,2,2,2,4,2,3,1,2,2,41,34.0,neutral or dissatisfied +18528,100212,Female,Loyal Customer,23,Business travel,Business,762,2,1,1,1,2,2,2,2,2,3,3,4,4,2,0,12.0,neutral or dissatisfied +18529,36418,Female,disloyal Customer,43,Business travel,Eco,369,4,3,4,4,4,4,4,4,5,4,2,4,4,4,0,0.0,neutral or dissatisfied +18530,22747,Female,Loyal Customer,37,Business travel,Business,2157,1,1,1,1,1,2,3,5,5,5,5,4,5,1,0,0.0,satisfied +18531,53862,Male,disloyal Customer,22,Business travel,Eco,140,4,0,3,2,2,3,2,2,5,4,4,5,5,2,0,0.0,satisfied +18532,10091,Female,Loyal Customer,24,Business travel,Business,2841,4,5,5,5,4,3,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +18533,78279,Female,Loyal Customer,49,Business travel,Business,1598,4,4,3,4,2,2,2,3,2,5,4,2,4,2,201,186.0,satisfied +18534,8481,Female,Loyal Customer,14,Personal Travel,Eco,1187,4,4,4,3,1,4,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +18535,106170,Female,Loyal Customer,19,Personal Travel,Eco,444,1,4,1,4,3,1,3,3,4,2,5,4,4,3,4,4.0,neutral or dissatisfied +18536,46614,Male,Loyal Customer,38,Business travel,Eco,125,3,5,5,5,3,3,3,3,4,5,3,3,2,3,29,24.0,neutral or dissatisfied +18537,65239,Female,disloyal Customer,23,Business travel,Eco,224,2,4,2,4,1,2,1,1,4,1,3,3,4,1,56,45.0,neutral or dissatisfied +18538,108575,Male,Loyal Customer,55,Business travel,Business,1719,4,4,4,4,3,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +18539,499,Female,Loyal Customer,57,Business travel,Business,2541,2,2,4,2,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +18540,38965,Female,Loyal Customer,29,Personal Travel,Business,313,3,4,3,3,2,3,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +18541,121081,Female,Loyal Customer,62,Personal Travel,Eco Plus,993,2,5,2,1,5,5,5,2,2,2,2,5,2,5,79,71.0,neutral or dissatisfied +18542,76880,Male,Loyal Customer,59,Business travel,Business,2095,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +18543,43506,Male,Loyal Customer,47,Personal Travel,Eco,679,1,4,1,2,2,1,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +18544,36555,Male,disloyal Customer,12,Business travel,Business,1121,5,0,5,1,3,0,3,3,2,4,5,3,5,3,22,3.0,satisfied +18545,33206,Male,Loyal Customer,67,Business travel,Eco Plus,216,5,1,1,1,5,5,5,5,1,2,3,4,2,5,0,0.0,satisfied +18546,36681,Female,Loyal Customer,45,Personal Travel,Eco,1121,1,4,1,3,2,5,4,4,4,1,2,3,4,5,0,13.0,neutral or dissatisfied +18547,110498,Female,Loyal Customer,43,Business travel,Business,787,2,2,2,2,2,4,5,5,5,5,5,4,5,3,33,31.0,satisfied +18548,73324,Male,Loyal Customer,44,Business travel,Business,2190,4,4,4,4,5,4,5,4,4,4,4,3,4,4,54,43.0,satisfied +18549,122751,Male,Loyal Customer,67,Personal Travel,Eco,651,2,2,2,4,5,2,5,5,4,4,3,4,3,5,0,0.0,neutral or dissatisfied +18550,51304,Female,Loyal Customer,40,Business travel,Eco Plus,190,2,3,3,3,2,2,2,2,2,5,3,4,3,2,0,0.0,satisfied +18551,32997,Female,Loyal Customer,8,Personal Travel,Eco,102,0,4,0,1,1,0,1,1,4,3,4,3,4,1,1,2.0,satisfied +18552,114267,Female,Loyal Customer,43,Business travel,Business,2538,3,1,1,1,5,4,3,3,3,3,3,1,3,2,128,130.0,neutral or dissatisfied +18553,7726,Female,Loyal Customer,11,Personal Travel,Eco,859,1,4,0,1,5,0,5,5,3,5,5,5,4,5,0,6.0,neutral or dissatisfied +18554,127891,Female,Loyal Customer,52,Business travel,Business,1671,5,5,5,5,5,4,4,4,4,4,4,4,4,3,22,14.0,satisfied +18555,49596,Male,Loyal Customer,46,Business travel,Business,326,5,5,5,5,5,1,2,4,4,4,4,1,4,4,0,5.0,satisfied +18556,56505,Male,Loyal Customer,50,Business travel,Business,3926,3,3,3,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +18557,73237,Female,Loyal Customer,41,Personal Travel,Eco Plus,946,3,2,3,2,5,2,3,4,4,3,3,3,4,3,0,1.0,neutral or dissatisfied +18558,1438,Female,Loyal Customer,37,Personal Travel,Business,772,2,5,2,3,1,1,1,5,5,2,5,2,5,4,0,2.0,neutral or dissatisfied +18559,57332,Male,Loyal Customer,60,Business travel,Business,3028,3,3,3,3,3,4,4,5,5,4,5,4,5,5,30,44.0,satisfied +18560,103595,Female,Loyal Customer,50,Personal Travel,Eco,451,2,4,2,1,3,4,5,5,5,2,1,3,5,3,0,0.0,neutral or dissatisfied +18561,112980,Male,Loyal Customer,8,Personal Travel,Eco Plus,1642,5,5,5,1,4,5,4,4,5,3,3,4,4,4,0,0.0,satisfied +18562,39762,Male,Loyal Customer,27,Business travel,Eco,546,5,1,1,1,5,5,5,5,5,5,2,1,3,5,0,0.0,satisfied +18563,99995,Female,Loyal Customer,44,Business travel,Business,281,0,0,0,2,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +18564,22002,Male,Loyal Customer,29,Personal Travel,Eco,448,5,2,1,4,3,1,3,3,3,5,4,3,4,3,0,0.0,satisfied +18565,9681,Female,Loyal Customer,32,Business travel,Business,2445,2,4,4,4,2,3,2,2,1,5,3,2,3,2,14,21.0,neutral or dissatisfied +18566,127057,Female,Loyal Customer,65,Business travel,Business,2552,2,2,2,2,4,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +18567,60798,Male,Loyal Customer,53,Business travel,Business,1711,2,2,2,2,2,5,4,5,5,5,5,4,5,4,3,0.0,satisfied +18568,95188,Female,Loyal Customer,46,Personal Travel,Eco,239,2,5,2,5,5,4,5,2,2,2,3,2,2,4,4,0.0,neutral or dissatisfied +18569,24617,Female,Loyal Customer,41,Business travel,Business,2441,0,1,1,2,2,3,4,2,2,2,2,3,2,4,0,0.0,satisfied +18570,68093,Male,Loyal Customer,37,Business travel,Business,1815,1,2,2,2,5,3,4,1,1,1,1,2,1,2,23,14.0,neutral or dissatisfied +18571,87831,Male,Loyal Customer,21,Personal Travel,Eco,214,2,4,2,4,4,2,1,4,3,1,2,5,4,4,4,0.0,neutral or dissatisfied +18572,13426,Male,Loyal Customer,45,Business travel,Business,1788,3,3,3,3,1,1,5,5,5,5,5,1,5,2,99,94.0,satisfied +18573,92165,Female,Loyal Customer,49,Business travel,Business,1979,1,4,1,1,4,5,5,5,5,5,5,5,5,5,32,5.0,satisfied +18574,121255,Male,Loyal Customer,50,Business travel,Eco,575,5,3,3,3,5,5,5,5,1,3,5,4,3,5,8,52.0,satisfied +18575,14160,Male,Loyal Customer,58,Business travel,Business,3041,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +18576,37438,Female,disloyal Customer,25,Business travel,Eco,1053,2,2,2,3,2,2,2,2,4,2,3,1,2,2,6,1.0,neutral or dissatisfied +18577,52200,Male,Loyal Customer,40,Business travel,Eco,425,5,5,5,5,5,5,5,5,1,3,2,3,1,5,0,7.0,satisfied +18578,128927,Male,Loyal Customer,54,Business travel,Business,414,2,2,2,2,3,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +18579,47842,Male,disloyal Customer,25,Business travel,Eco,550,1,4,1,2,5,1,5,5,5,4,5,2,4,5,0,0.0,neutral or dissatisfied +18580,9364,Male,disloyal Customer,15,Business travel,Eco,401,2,3,2,3,4,2,4,4,3,2,4,2,3,4,5,12.0,neutral or dissatisfied +18581,76457,Male,disloyal Customer,22,Business travel,Business,547,4,0,4,5,1,4,5,1,5,5,5,4,4,1,0,0.0,satisfied +18582,126300,Male,Loyal Customer,35,Personal Travel,Eco,631,3,5,3,4,3,3,3,3,5,3,5,4,4,3,7,13.0,neutral or dissatisfied +18583,23069,Male,Loyal Customer,38,Personal Travel,Eco,820,2,2,2,4,5,2,5,5,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +18584,93385,Male,Loyal Customer,25,Business travel,Eco,605,1,5,5,5,1,1,3,1,1,5,4,3,4,1,1,4.0,neutral or dissatisfied +18585,31056,Female,Loyal Customer,30,Business travel,Business,641,2,1,4,1,2,2,2,2,3,1,3,1,3,2,7,12.0,neutral or dissatisfied +18586,52704,Female,Loyal Customer,35,Business travel,Eco Plus,562,3,5,5,5,3,3,3,3,4,2,4,4,4,3,0,0.0,satisfied +18587,23367,Male,Loyal Customer,24,Business travel,Business,2691,5,5,5,5,5,5,5,5,3,3,1,3,1,5,34,21.0,satisfied +18588,82039,Female,Loyal Customer,36,Personal Travel,Eco,1535,2,3,2,4,3,2,3,3,2,2,3,3,3,3,0,3.0,neutral or dissatisfied +18589,40010,Male,Loyal Customer,23,Business travel,Eco,575,4,4,4,4,4,4,2,4,4,2,3,2,2,4,25,32.0,neutral or dissatisfied +18590,86315,Female,Loyal Customer,69,Business travel,Eco Plus,306,2,2,2,2,2,3,4,2,2,2,2,3,2,3,7,14.0,neutral or dissatisfied +18591,15542,Female,Loyal Customer,29,Personal Travel,Eco,812,2,4,2,1,1,2,1,1,2,1,1,5,1,1,129,92.0,neutral or dissatisfied +18592,96494,Female,Loyal Customer,20,Business travel,Business,436,3,2,2,2,3,2,3,3,2,1,4,2,4,3,50,33.0,neutral or dissatisfied +18593,107467,Female,Loyal Customer,15,Personal Travel,Eco,1121,3,4,3,3,3,3,3,3,4,3,5,5,4,3,16,25.0,neutral or dissatisfied +18594,31508,Female,Loyal Customer,46,Business travel,Eco,853,2,5,5,5,3,4,5,2,2,2,2,5,2,1,51,58.0,satisfied +18595,49163,Female,Loyal Customer,66,Business travel,Eco,326,5,2,2,2,2,4,1,5,5,5,5,2,5,3,0,0.0,satisfied +18596,20629,Female,Loyal Customer,55,Business travel,Eco Plus,783,5,1,1,1,3,1,3,5,5,5,5,5,5,3,0,5.0,satisfied +18597,112436,Female,disloyal Customer,29,Business travel,Eco,967,3,3,3,4,4,3,4,4,3,4,3,1,3,4,52,23.0,neutral or dissatisfied +18598,100784,Male,Loyal Customer,64,Personal Travel,Eco,1411,2,4,2,1,1,2,1,1,5,1,3,3,1,1,0,0.0,neutral or dissatisfied +18599,78214,Female,Loyal Customer,16,Personal Travel,Eco,153,3,4,3,3,5,3,5,5,3,2,5,4,5,5,33,33.0,neutral or dissatisfied +18600,7415,Female,Loyal Customer,42,Business travel,Business,1742,1,1,1,1,4,5,5,4,4,4,4,5,4,4,108,107.0,satisfied +18601,16223,Male,Loyal Customer,61,Personal Travel,Business,266,4,0,0,4,2,4,4,1,1,0,1,3,1,5,0,0.0,satisfied +18602,112189,Female,Loyal Customer,60,Business travel,Business,895,4,4,4,4,5,4,4,3,3,2,3,3,3,4,0,0.0,satisfied +18603,96369,Female,disloyal Customer,25,Business travel,Business,1342,5,0,5,4,4,5,4,4,5,3,4,4,5,4,23,18.0,satisfied +18604,109226,Female,Loyal Customer,27,Personal Travel,Eco,401,3,1,3,3,1,3,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +18605,103833,Female,Loyal Customer,29,Business travel,Eco,1242,4,5,5,5,4,3,4,4,2,2,3,1,4,4,12,16.0,neutral or dissatisfied +18606,75682,Female,Loyal Customer,50,Business travel,Business,868,4,4,1,4,2,5,5,3,3,3,3,4,3,5,4,0.0,satisfied +18607,15557,Female,Loyal Customer,55,Business travel,Eco,229,4,1,1,1,1,2,2,4,4,4,4,2,4,3,61,53.0,satisfied +18608,48282,Male,Loyal Customer,9,Personal Travel,Eco Plus,259,0,4,0,3,1,0,1,1,5,3,2,2,5,1,0,0.0,satisfied +18609,23980,Female,Loyal Customer,47,Business travel,Business,2309,4,4,2,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +18610,127271,Female,Loyal Customer,40,Business travel,Eco,1107,2,5,5,5,2,2,2,2,1,5,4,1,1,2,0,0.0,satisfied +18611,40655,Female,disloyal Customer,23,Business travel,Business,532,4,0,4,3,4,4,3,4,4,4,4,3,4,4,0,0.0,satisfied +18612,84372,Male,Loyal Customer,28,Business travel,Business,606,1,1,1,1,1,1,1,1,4,4,4,1,3,1,58,64.0,neutral or dissatisfied +18613,43684,Male,Loyal Customer,49,Business travel,Business,489,1,1,1,1,3,2,5,5,5,5,5,2,5,4,0,43.0,satisfied +18614,46725,Female,Loyal Customer,53,Personal Travel,Eco,73,4,4,0,1,4,4,4,1,1,0,1,4,1,5,0,0.0,neutral or dissatisfied +18615,32792,Female,disloyal Customer,23,Business travel,Eco,216,3,3,3,4,5,3,5,5,1,1,4,1,4,5,0,4.0,neutral or dissatisfied +18616,127872,Female,Loyal Customer,30,Business travel,Business,3959,3,3,3,3,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +18617,28562,Female,Loyal Customer,30,Business travel,Eco Plus,2681,5,3,3,3,5,5,5,5,5,1,3,1,2,5,1,0.0,satisfied +18618,4369,Male,disloyal Customer,22,Business travel,Eco,528,1,0,1,3,2,1,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +18619,43262,Female,Loyal Customer,33,Business travel,Business,347,1,1,1,1,3,1,2,5,5,5,5,1,5,5,0,0.0,satisfied +18620,71751,Female,Loyal Customer,50,Business travel,Business,1723,2,2,2,2,5,4,5,5,5,5,5,4,5,5,19,,satisfied +18621,85321,Female,Loyal Customer,17,Personal Travel,Eco,813,2,3,2,4,2,2,2,2,1,2,2,3,4,2,0,0.0,neutral or dissatisfied +18622,105540,Female,disloyal Customer,39,Business travel,Eco,211,5,0,5,3,4,5,4,4,3,5,4,3,5,4,7,0.0,satisfied +18623,11351,Male,Loyal Customer,17,Personal Travel,Eco,396,2,4,2,1,1,2,1,1,1,5,1,4,1,1,0,0.0,neutral or dissatisfied +18624,12859,Female,Loyal Customer,51,Business travel,Eco Plus,817,2,5,5,5,5,5,3,2,2,2,2,1,2,4,1,0.0,satisfied +18625,37368,Female,Loyal Customer,42,Business travel,Eco,944,5,2,2,2,1,2,1,4,4,5,4,1,4,1,0,0.0,satisfied +18626,91953,Male,Loyal Customer,57,Personal Travel,Eco,2475,3,4,4,3,2,4,2,2,5,3,3,5,5,2,1,19.0,neutral or dissatisfied +18627,29380,Female,disloyal Customer,37,Business travel,Eco,1342,1,1,1,1,1,4,4,2,4,3,4,4,4,4,0,13.0,neutral or dissatisfied +18628,39118,Female,Loyal Customer,33,Business travel,Business,3107,2,4,4,4,3,4,4,1,1,1,2,1,1,1,0,7.0,neutral or dissatisfied +18629,34040,Male,disloyal Customer,34,Business travel,Eco,1608,2,3,3,3,1,2,1,1,1,2,5,2,2,1,0,0.0,neutral or dissatisfied +18630,86700,Male,Loyal Customer,38,Business travel,Eco,1747,3,4,4,4,3,3,3,3,3,2,2,2,3,3,15,17.0,neutral or dissatisfied +18631,58247,Female,Loyal Customer,9,Personal Travel,Eco Plus,925,2,4,2,3,4,2,3,4,4,4,5,4,5,4,2,20.0,neutral or dissatisfied +18632,48317,Female,Loyal Customer,41,Business travel,Business,2807,3,3,3,3,2,5,2,5,5,5,5,4,5,3,0,0.0,satisfied +18633,87872,Female,disloyal Customer,40,Business travel,Business,214,1,0,0,4,5,0,2,5,3,4,4,3,4,5,11,6.0,neutral or dissatisfied +18634,11363,Male,Loyal Customer,57,Personal Travel,Eco,201,3,5,3,3,1,3,3,1,1,5,5,3,3,1,70,67.0,neutral or dissatisfied +18635,28292,Male,Loyal Customer,38,Personal Travel,Business,867,4,3,4,4,3,4,4,2,2,4,2,3,2,4,0,0.0,satisfied +18636,76992,Male,Loyal Customer,50,Business travel,Business,2891,5,5,5,5,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +18637,16174,Male,disloyal Customer,35,Business travel,Eco,212,4,1,4,2,4,4,4,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +18638,6104,Male,Loyal Customer,32,Business travel,Business,409,1,4,4,4,1,1,1,1,4,4,4,2,4,1,83,125.0,neutral or dissatisfied +18639,55201,Female,Loyal Customer,40,Personal Travel,Eco Plus,1609,4,5,4,3,3,4,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +18640,48079,Female,Loyal Customer,16,Personal Travel,Business,236,2,5,2,2,4,2,4,4,3,3,4,4,5,4,78,73.0,neutral or dissatisfied +18641,40218,Male,Loyal Customer,47,Business travel,Eco,402,4,2,2,2,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +18642,112889,Male,Loyal Customer,44,Business travel,Eco,1313,2,2,2,2,2,2,2,2,2,4,2,2,3,2,0,0.0,neutral or dissatisfied +18643,67147,Female,Loyal Customer,67,Business travel,Business,564,2,3,3,3,1,3,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +18644,98120,Female,Loyal Customer,40,Personal Travel,Eco,472,2,3,1,4,2,1,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +18645,104176,Female,Loyal Customer,74,Business travel,Eco,349,2,2,2,2,5,3,4,2,2,2,2,3,2,1,24,17.0,neutral or dissatisfied +18646,122073,Female,Loyal Customer,7,Personal Travel,Eco,130,2,5,2,1,1,2,3,1,3,3,5,3,3,1,0,0.0,neutral or dissatisfied +18647,12499,Male,Loyal Customer,50,Business travel,Eco Plus,201,5,1,1,1,5,5,5,5,4,3,3,5,1,5,1,0.0,satisfied +18648,35040,Female,disloyal Customer,46,Business travel,Business,1076,2,2,2,2,4,2,4,4,4,4,5,3,5,4,0,0.0,satisfied +18649,17952,Female,Loyal Customer,38,Business travel,Eco,460,4,1,1,1,4,4,4,4,5,1,3,2,4,4,0,0.0,satisfied +18650,95650,Female,disloyal Customer,20,Business travel,Eco,928,3,3,3,3,2,3,2,2,4,4,4,5,5,2,31,12.0,neutral or dissatisfied +18651,67443,Female,disloyal Customer,34,Business travel,Eco,721,4,4,4,4,2,4,2,2,4,1,4,3,4,2,35,38.0,neutral or dissatisfied +18652,111878,Female,Loyal Customer,40,Business travel,Business,628,4,4,4,4,5,2,3,4,4,4,4,2,4,3,20,21.0,neutral or dissatisfied +18653,125802,Female,disloyal Customer,35,Business travel,Eco,992,2,1,1,4,2,1,2,2,4,4,3,2,3,2,42,34.0,neutral or dissatisfied +18654,89177,Female,Loyal Customer,48,Personal Travel,Eco,1919,3,3,3,2,4,4,4,2,2,3,2,5,2,2,0,0.0,neutral or dissatisfied +18655,80942,Female,Loyal Customer,29,Personal Travel,Eco,341,3,2,3,3,2,3,5,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +18656,34623,Female,Loyal Customer,41,Business travel,Business,2454,2,2,2,2,5,5,5,3,1,5,1,5,2,5,71,65.0,satisfied +18657,94110,Female,Loyal Customer,67,Personal Travel,Business,341,2,5,2,3,2,5,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +18658,113672,Male,Loyal Customer,59,Personal Travel,Eco,236,2,5,2,4,4,2,4,4,3,4,5,5,4,4,6,0.0,neutral or dissatisfied +18659,95771,Female,Loyal Customer,22,Personal Travel,Eco,419,3,5,3,5,1,3,1,1,1,4,2,5,3,1,38,45.0,neutral or dissatisfied +18660,117612,Male,Loyal Customer,35,Business travel,Business,1647,2,3,5,3,2,3,4,2,2,2,2,1,2,4,40,31.0,neutral or dissatisfied +18661,82959,Male,Loyal Customer,50,Business travel,Business,983,1,1,1,1,2,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +18662,106612,Male,Loyal Customer,20,Business travel,Eco Plus,589,2,1,1,1,2,2,3,2,2,4,4,2,4,2,17,8.0,neutral or dissatisfied +18663,107530,Female,Loyal Customer,44,Business travel,Business,1521,4,4,4,4,3,4,4,4,4,4,4,3,4,4,101,97.0,satisfied +18664,79809,Female,Loyal Customer,34,Business travel,Business,2038,5,5,5,5,5,5,5,2,2,2,2,4,2,4,0,16.0,satisfied +18665,128347,Male,Loyal Customer,25,Business travel,Business,338,4,4,4,4,5,5,5,5,5,4,5,5,4,5,0,0.0,satisfied +18666,93348,Female,Loyal Customer,43,Business travel,Business,1024,4,4,4,4,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +18667,48113,Male,Loyal Customer,34,Business travel,Business,391,4,4,4,4,1,3,3,4,4,4,4,1,4,2,4,0.0,satisfied +18668,14400,Male,Loyal Customer,9,Personal Travel,Eco,789,3,4,3,1,2,3,2,2,3,3,4,5,4,2,14,0.0,neutral or dissatisfied +18669,125722,Female,Loyal Customer,46,Personal Travel,Eco,814,2,0,2,3,1,3,3,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +18670,123940,Female,Loyal Customer,61,Personal Travel,Eco,573,3,4,3,1,5,5,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +18671,62355,Female,disloyal Customer,22,Business travel,Business,1312,5,3,5,2,5,5,5,5,5,2,3,5,5,5,0,0.0,satisfied +18672,82696,Female,Loyal Customer,59,Business travel,Business,632,3,3,3,3,3,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +18673,97365,Male,Loyal Customer,39,Personal Travel,Eco,347,3,5,3,3,1,3,1,1,4,5,5,3,4,1,32,19.0,neutral or dissatisfied +18674,55773,Female,Loyal Customer,50,Business travel,Business,599,4,4,4,4,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +18675,19729,Male,Loyal Customer,28,Personal Travel,Eco,475,3,3,3,2,2,3,2,2,5,4,2,1,1,2,4,44.0,neutral or dissatisfied +18676,112657,Male,Loyal Customer,40,Business travel,Business,605,2,4,4,4,4,3,4,2,2,2,2,3,2,2,1,7.0,neutral or dissatisfied +18677,72930,Male,Loyal Customer,53,Business travel,Business,1035,2,2,2,2,2,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +18678,84483,Male,Loyal Customer,27,Personal Travel,Eco,2677,3,3,3,2,4,3,4,4,1,1,3,2,2,4,0,0.0,neutral or dissatisfied +18679,104051,Female,Loyal Customer,16,Personal Travel,Eco,1262,3,4,3,2,2,3,1,2,4,5,3,3,4,2,5,13.0,neutral or dissatisfied +18680,100307,Female,Loyal Customer,49,Business travel,Business,1034,4,4,4,4,2,5,5,2,2,2,2,4,2,5,5,16.0,satisfied +18681,99058,Male,Loyal Customer,61,Business travel,Eco,237,2,2,3,2,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +18682,2080,Male,disloyal Customer,18,Business travel,Eco,785,0,0,0,4,2,0,2,2,3,5,4,2,4,2,3,0.0,satisfied +18683,44097,Male,Loyal Customer,50,Business travel,Business,2751,4,4,4,4,1,3,5,3,3,4,3,5,3,5,0,0.0,satisfied +18684,39102,Female,Loyal Customer,68,Personal Travel,Eco Plus,328,2,3,2,3,1,4,4,4,4,2,4,3,4,3,4,3.0,neutral or dissatisfied +18685,58339,Male,Loyal Customer,54,Business travel,Business,1936,3,3,3,3,4,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +18686,33097,Female,Loyal Customer,70,Personal Travel,Eco,101,1,5,1,4,3,5,1,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +18687,117577,Male,Loyal Customer,60,Business travel,Business,3402,4,4,4,4,4,4,5,2,2,2,2,4,2,4,5,0.0,satisfied +18688,107996,Male,disloyal Customer,55,Business travel,Business,271,5,4,4,2,1,5,1,1,2,1,3,3,5,1,26,4.0,satisfied +18689,110836,Female,Loyal Customer,23,Personal Travel,Eco Plus,997,2,1,2,3,5,2,5,5,2,1,4,4,4,5,18,16.0,neutral or dissatisfied +18690,90254,Female,disloyal Customer,25,Business travel,Business,879,4,2,4,4,4,4,4,4,1,4,4,2,3,4,3,0.0,neutral or dissatisfied +18691,13230,Female,Loyal Customer,28,Business travel,Business,1794,1,1,1,1,5,5,5,5,4,3,5,2,3,5,0,0.0,satisfied +18692,43281,Male,Loyal Customer,44,Business travel,Business,3660,3,3,4,3,4,2,3,5,5,5,5,1,5,5,0,0.0,satisfied +18693,63863,Male,Loyal Customer,55,Business travel,Business,3730,2,2,2,2,5,4,4,4,4,4,4,3,4,5,32,20.0,satisfied +18694,75519,Female,Loyal Customer,60,Business travel,Business,2479,1,1,1,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +18695,40156,Male,Loyal Customer,23,Personal Travel,Business,436,1,5,1,4,1,1,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +18696,93650,Female,Loyal Customer,37,Personal Travel,Eco,547,3,0,3,3,1,3,5,1,5,2,5,3,4,1,84,77.0,neutral or dissatisfied +18697,106376,Female,disloyal Customer,34,Business travel,Business,488,2,3,3,2,3,3,3,3,4,4,4,4,5,3,25,32.0,neutral or dissatisfied +18698,102047,Female,Loyal Customer,41,Business travel,Business,1576,2,1,1,1,1,4,4,2,2,2,2,2,2,2,0,10.0,neutral or dissatisfied +18699,84841,Male,Loyal Customer,29,Business travel,Business,481,1,2,2,2,1,1,1,1,2,1,4,3,4,1,22,23.0,neutral or dissatisfied +18700,10136,Female,Loyal Customer,39,Business travel,Business,1201,5,2,5,5,4,5,5,4,4,4,4,3,4,3,5,1.0,satisfied +18701,61031,Female,Loyal Customer,31,Business travel,Business,1546,3,3,3,3,2,2,2,2,5,2,5,3,4,2,0,0.0,satisfied +18702,123484,Female,disloyal Customer,18,Business travel,Eco,2296,2,2,2,4,2,4,4,3,4,2,3,4,2,4,4,8.0,neutral or dissatisfied +18703,95212,Female,Loyal Customer,62,Personal Travel,Eco,677,1,2,1,4,4,3,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +18704,56046,Male,disloyal Customer,24,Business travel,Eco,1130,2,2,2,4,2,5,1,4,2,3,4,1,1,1,0,0.0,neutral or dissatisfied +18705,12287,Male,Loyal Customer,50,Business travel,Business,2682,0,5,0,5,4,5,3,5,5,5,5,5,5,3,2,0.0,satisfied +18706,16101,Female,Loyal Customer,41,Personal Travel,Eco,303,3,4,3,4,5,3,2,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +18707,101909,Female,Loyal Customer,12,Personal Travel,Eco,2039,4,5,4,3,3,4,3,3,3,2,3,5,4,3,3,0.0,neutral or dissatisfied +18708,51871,Female,Loyal Customer,55,Business travel,Eco,771,4,2,2,2,2,4,1,3,3,4,3,5,3,1,0,0.0,satisfied +18709,23385,Male,Loyal Customer,39,Business travel,Business,2514,4,4,4,4,3,2,1,3,3,4,3,5,3,1,4,6.0,satisfied +18710,25935,Female,Loyal Customer,35,Personal Travel,Eco,594,1,3,1,3,4,1,4,4,2,5,4,3,4,4,26,18.0,neutral or dissatisfied +18711,40677,Female,Loyal Customer,23,Business travel,Business,3759,1,1,4,1,5,5,5,5,3,4,3,4,3,5,0,0.0,satisfied +18712,110713,Male,Loyal Customer,40,Business travel,Business,3173,2,5,5,5,1,4,3,2,2,2,2,1,2,4,3,0.0,neutral or dissatisfied +18713,21388,Male,Loyal Customer,29,Personal Travel,Business,331,2,1,2,4,2,2,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +18714,63734,Female,Loyal Customer,18,Personal Travel,Eco,1660,3,3,3,5,3,3,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +18715,16349,Female,Loyal Customer,21,Business travel,Eco,160,4,2,2,2,4,4,4,4,3,4,4,3,4,4,83,78.0,neutral or dissatisfied +18716,118084,Male,Loyal Customer,26,Business travel,Business,1276,2,5,4,5,2,2,2,2,2,3,4,2,3,2,37,23.0,neutral or dissatisfied +18717,80694,Male,disloyal Customer,24,Business travel,Eco,874,3,3,3,3,3,3,3,3,4,3,3,1,2,3,0,0.0,neutral or dissatisfied +18718,81761,Male,disloyal Customer,28,Business travel,Business,1310,2,2,2,2,1,2,1,1,3,3,4,5,4,1,36,50.0,neutral or dissatisfied +18719,81336,Male,Loyal Customer,29,Business travel,Business,2306,1,4,4,4,1,1,1,1,4,3,4,4,4,1,3,1.0,neutral or dissatisfied +18720,97917,Male,Loyal Customer,40,Business travel,Business,3837,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +18721,59214,Male,Loyal Customer,27,Personal Travel,Eco,1440,0,5,0,4,4,0,4,4,3,4,5,4,4,4,3,0.0,satisfied +18722,25776,Male,disloyal Customer,29,Business travel,Eco,762,4,4,4,4,5,4,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +18723,103704,Female,Loyal Customer,31,Personal Travel,Eco,251,5,5,5,1,3,5,3,3,4,5,5,3,4,3,0,0.0,satisfied +18724,40434,Male,Loyal Customer,44,Business travel,Business,3383,2,2,3,2,2,2,4,5,5,5,5,5,5,4,70,,satisfied +18725,109372,Female,disloyal Customer,22,Business travel,Business,1189,4,4,4,1,5,4,5,5,3,5,4,4,4,5,6,0.0,satisfied +18726,80645,Male,disloyal Customer,25,Business travel,Business,821,2,3,2,3,5,2,5,5,1,5,4,4,3,5,16,9.0,neutral or dissatisfied +18727,121407,Female,Loyal Customer,43,Business travel,Business,3323,5,5,5,5,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +18728,74550,Female,Loyal Customer,25,Business travel,Business,1464,3,3,3,3,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +18729,107428,Female,Loyal Customer,11,Personal Travel,Eco,717,4,1,4,3,5,4,4,5,1,1,3,2,2,5,20,13.0,neutral or dissatisfied +18730,97857,Male,Loyal Customer,31,Business travel,Business,3774,1,5,2,5,1,1,1,1,4,4,4,1,3,1,0,17.0,neutral or dissatisfied +18731,10316,Male,Loyal Customer,53,Business travel,Business,1589,5,5,5,5,3,5,4,4,4,4,4,5,4,3,13,9.0,satisfied +18732,67713,Male,disloyal Customer,26,Business travel,Business,1171,3,3,3,3,3,3,3,3,1,1,3,4,3,3,124,117.0,neutral or dissatisfied +18733,24561,Female,disloyal Customer,43,Business travel,Eco,474,2,0,2,4,1,2,1,1,1,3,2,2,5,1,0,0.0,neutral or dissatisfied +18734,123077,Female,disloyal Customer,38,Business travel,Business,590,5,5,5,3,5,5,5,5,4,4,5,3,5,5,0,0.0,satisfied +18735,52923,Female,Loyal Customer,24,Business travel,Business,679,4,4,4,4,5,5,5,5,4,1,5,4,4,5,39,24.0,satisfied +18736,110404,Female,Loyal Customer,48,Business travel,Business,1625,1,2,2,2,3,3,4,1,1,1,1,1,1,2,9,25.0,neutral or dissatisfied +18737,21633,Male,Loyal Customer,60,Personal Travel,Eco,780,1,4,1,4,3,1,3,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +18738,49941,Male,Loyal Customer,39,Business travel,Business,1530,2,1,5,1,3,4,3,1,1,1,2,3,1,4,1,1.0,neutral or dissatisfied +18739,117446,Female,Loyal Customer,77,Business travel,Business,2859,3,3,3,3,3,3,2,3,3,3,3,4,3,1,0,4.0,neutral or dissatisfied +18740,37736,Female,Loyal Customer,37,Personal Travel,Eco,972,1,1,1,2,2,1,2,2,1,4,2,4,3,2,0,0.0,neutral or dissatisfied +18741,76576,Female,Loyal Customer,47,Business travel,Business,2793,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +18742,57649,Female,disloyal Customer,16,Business travel,Eco,200,3,2,3,4,4,3,4,4,2,1,4,1,3,4,4,0.0,neutral or dissatisfied +18743,105330,Male,disloyal Customer,22,Business travel,Business,528,5,0,5,4,2,5,2,2,4,4,5,3,5,2,10,1.0,satisfied +18744,91017,Male,Loyal Customer,7,Personal Travel,Eco,240,4,4,4,5,3,4,3,3,5,3,5,4,2,3,39,68.0,satisfied +18745,117959,Male,Loyal Customer,31,Business travel,Business,1944,2,3,2,2,4,4,4,4,1,4,3,5,4,4,0,1.0,satisfied +18746,65061,Male,Loyal Customer,10,Personal Travel,Eco,247,2,5,2,5,4,2,4,4,4,5,4,3,5,4,4,0.0,neutral or dissatisfied +18747,25216,Female,Loyal Customer,9,Business travel,Eco,842,2,2,3,2,2,2,1,2,2,4,4,3,3,2,10,25.0,neutral or dissatisfied +18748,21919,Male,disloyal Customer,20,Business travel,Eco,551,2,0,2,2,2,2,5,2,1,4,5,3,4,2,0,0.0,neutral or dissatisfied +18749,121394,Male,Loyal Customer,64,Business travel,Business,3399,3,3,3,3,4,3,3,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +18750,91960,Male,Loyal Customer,36,Personal Travel,Eco,2586,2,4,2,5,1,2,1,1,5,4,3,4,4,1,4,0.0,neutral or dissatisfied +18751,84908,Female,Loyal Customer,43,Personal Travel,Eco,547,2,5,2,3,4,5,3,1,1,2,1,5,1,4,6,0.0,neutral or dissatisfied +18752,84696,Female,Loyal Customer,45,Business travel,Business,2182,2,2,5,2,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +18753,25944,Male,Loyal Customer,38,Personal Travel,Eco Plus,594,2,2,2,4,4,2,4,4,4,4,4,2,3,4,32,24.0,neutral or dissatisfied +18754,53666,Male,Loyal Customer,60,Business travel,Business,2825,2,2,2,2,1,2,5,5,5,5,5,1,5,4,5,0.0,satisfied +18755,34510,Female,Loyal Customer,39,Business travel,Eco,1521,1,4,4,4,1,1,1,1,1,5,4,2,4,1,21,21.0,neutral or dissatisfied +18756,68018,Female,Loyal Customer,61,Business travel,Eco,304,4,4,4,4,4,1,5,5,5,4,5,1,5,2,0,0.0,satisfied +18757,98816,Male,Loyal Customer,55,Business travel,Business,3987,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +18758,821,Female,Loyal Customer,52,Business travel,Business,2236,2,3,3,3,3,4,4,2,2,2,2,4,2,3,27,28.0,neutral or dissatisfied +18759,112482,Female,Loyal Customer,58,Personal Travel,Eco,846,1,5,1,2,5,3,3,3,3,1,2,4,3,4,43,30.0,neutral or dissatisfied +18760,70269,Female,disloyal Customer,62,Business travel,Business,852,3,3,3,1,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +18761,119945,Male,Loyal Customer,44,Business travel,Business,3050,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,3.0,satisfied +18762,1088,Male,Loyal Customer,35,Personal Travel,Eco,102,2,4,0,1,4,0,5,4,1,4,3,3,3,4,3,0.0,neutral or dissatisfied +18763,82812,Male,Loyal Customer,53,Personal Travel,Eco,235,3,5,3,3,3,3,3,3,5,2,5,3,4,3,64,93.0,neutral or dissatisfied +18764,66944,Male,Loyal Customer,49,Business travel,Business,929,2,2,2,2,2,4,5,5,5,5,5,5,5,5,32,20.0,satisfied +18765,121502,Male,Loyal Customer,26,Personal Travel,Eco Plus,331,3,4,3,1,5,3,5,5,4,4,5,3,2,5,3,0.0,neutral or dissatisfied +18766,58005,Female,Loyal Customer,55,Business travel,Business,1162,1,1,1,1,2,5,4,5,5,5,5,3,5,3,2,19.0,satisfied +18767,44753,Female,Loyal Customer,63,Personal Travel,Eco,717,4,4,4,4,2,5,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +18768,98442,Male,Loyal Customer,54,Business travel,Business,2063,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +18769,40549,Male,Loyal Customer,53,Business travel,Business,391,1,1,1,1,4,3,1,5,5,5,5,5,5,5,4,0.0,satisfied +18770,16366,Male,Loyal Customer,69,Personal Travel,Eco,319,4,2,4,4,4,3,3,2,4,4,3,3,4,3,192,190.0,neutral or dissatisfied +18771,110149,Male,Loyal Customer,41,Business travel,Eco,1048,1,4,4,4,1,1,1,1,2,2,3,3,2,1,15,11.0,neutral or dissatisfied +18772,65855,Male,Loyal Customer,31,Personal Travel,Eco,1521,4,4,4,3,3,4,3,3,4,3,4,2,1,3,0,0.0,neutral or dissatisfied +18773,74933,Female,Loyal Customer,37,Business travel,Business,2446,5,5,5,5,2,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +18774,101372,Male,Loyal Customer,61,Personal Travel,Eco,1986,4,1,4,3,3,4,3,3,2,3,3,2,4,3,16,0.0,neutral or dissatisfied +18775,13804,Male,Loyal Customer,52,Business travel,Eco Plus,450,4,4,4,4,4,4,4,4,5,2,2,2,1,4,13,8.0,satisfied +18776,114604,Male,disloyal Customer,61,Business travel,Business,362,5,3,3,1,3,5,3,3,5,2,4,5,4,3,3,0.0,satisfied +18777,26515,Female,Loyal Customer,52,Business travel,Business,2827,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +18778,35605,Female,Loyal Customer,51,Personal Travel,Eco Plus,972,3,5,3,4,2,4,4,5,5,3,5,3,5,5,61,52.0,neutral or dissatisfied +18779,39749,Male,Loyal Customer,52,Business travel,Eco,1174,1,2,2,2,1,1,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +18780,39108,Female,Loyal Customer,43,Business travel,Business,190,3,3,4,3,3,2,3,4,4,4,4,4,4,4,0,0.0,satisfied +18781,92127,Male,Loyal Customer,56,Personal Travel,Eco,1522,2,5,2,3,1,2,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +18782,66512,Male,Loyal Customer,10,Personal Travel,Eco,447,2,4,2,1,5,2,5,5,5,2,4,3,5,5,27,28.0,neutral or dissatisfied +18783,66872,Male,Loyal Customer,46,Personal Travel,Eco Plus,731,1,4,1,4,5,1,5,5,1,2,3,2,3,5,113,103.0,neutral or dissatisfied +18784,26663,Male,disloyal Customer,30,Business travel,Eco,545,1,0,1,4,3,1,1,3,5,3,2,4,1,3,0,0.0,neutral or dissatisfied +18785,127927,Male,Loyal Customer,43,Business travel,Business,2300,4,3,3,3,5,4,4,4,4,4,4,1,4,2,3,0.0,neutral or dissatisfied +18786,111419,Male,Loyal Customer,50,Business travel,Business,3898,3,3,3,3,5,5,5,4,4,4,4,3,4,4,46,33.0,satisfied +18787,25756,Male,Loyal Customer,33,Business travel,Business,2829,2,2,2,2,4,4,4,4,2,3,4,1,2,4,17,19.0,satisfied +18788,59332,Female,Loyal Customer,44,Business travel,Business,2556,2,2,2,2,3,4,4,5,5,5,5,3,5,5,6,0.0,satisfied +18789,49003,Male,Loyal Customer,55,Business travel,Eco,447,4,3,5,5,4,4,4,4,1,4,1,4,4,4,0,0.0,satisfied +18790,59799,Female,disloyal Customer,21,Business travel,Eco,997,2,2,2,3,5,2,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +18791,125031,Male,Loyal Customer,40,Business travel,Business,2300,5,5,4,5,2,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +18792,80617,Female,Loyal Customer,17,Business travel,Business,236,4,4,1,4,4,4,4,4,3,3,3,1,1,4,0,0.0,satisfied +18793,95413,Male,Loyal Customer,45,Personal Travel,Eco,189,1,5,0,1,5,0,2,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +18794,66039,Female,Loyal Customer,32,Business travel,Business,3629,2,2,5,2,5,5,5,5,5,4,5,5,4,5,1,1.0,satisfied +18795,85953,Male,Loyal Customer,53,Business travel,Business,447,2,2,2,2,2,4,4,2,2,2,2,5,2,3,0,3.0,satisfied +18796,41391,Female,disloyal Customer,21,Business travel,Eco,913,2,2,2,2,2,2,2,2,3,3,5,1,3,2,9,,neutral or dissatisfied +18797,37000,Male,Loyal Customer,15,Personal Travel,Eco,899,2,3,2,2,2,2,2,2,2,1,3,2,5,2,12,1.0,neutral or dissatisfied +18798,128123,Female,disloyal Customer,38,Business travel,Eco,1187,5,4,4,3,2,4,2,2,1,2,2,4,3,2,0,0.0,satisfied +18799,99752,Female,Loyal Customer,13,Personal Travel,Eco,255,4,5,4,3,2,4,2,2,1,2,5,3,5,2,0,0.0,satisfied +18800,16662,Male,Loyal Customer,54,Business travel,Business,3509,4,4,4,4,5,4,5,2,2,2,2,5,2,1,0,0.0,satisfied +18801,95488,Female,Loyal Customer,47,Business travel,Eco Plus,323,2,1,1,1,5,4,3,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +18802,96445,Male,Loyal Customer,49,Business travel,Business,436,3,3,3,3,4,5,5,4,4,4,4,4,4,5,49,62.0,satisfied +18803,110608,Female,Loyal Customer,45,Business travel,Eco Plus,551,2,5,5,5,1,3,2,2,2,2,2,3,2,2,21,8.0,neutral or dissatisfied +18804,13245,Male,disloyal Customer,23,Business travel,Eco,657,4,4,4,3,3,4,3,3,4,1,2,2,4,3,0,0.0,satisfied +18805,46423,Female,Loyal Customer,39,Business travel,Eco,458,2,3,3,3,2,2,2,2,4,2,4,1,3,2,8,11.0,neutral or dissatisfied +18806,48474,Female,Loyal Customer,38,Business travel,Business,916,5,2,5,5,5,4,2,2,2,2,2,2,2,2,0,0.0,satisfied +18807,21833,Male,Loyal Customer,44,Personal Travel,Eco,640,3,5,3,1,2,3,2,2,5,3,4,4,5,2,95,94.0,neutral or dissatisfied +18808,125248,Male,Loyal Customer,47,Business travel,Business,427,3,1,1,1,1,4,3,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +18809,36452,Female,Loyal Customer,38,Business travel,Eco,867,3,2,2,2,3,4,3,3,1,5,3,4,2,3,19,115.0,satisfied +18810,115648,Male,Loyal Customer,41,Business travel,Business,2531,3,2,4,4,3,4,4,3,3,3,3,1,3,4,29,33.0,neutral or dissatisfied +18811,129417,Male,Loyal Customer,49,Business travel,Business,3637,4,4,4,4,2,4,5,5,5,5,5,3,5,3,10,8.0,satisfied +18812,55723,Male,Loyal Customer,53,Business travel,Business,1751,1,1,4,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +18813,98969,Female,Loyal Customer,39,Business travel,Eco,479,3,3,3,3,3,3,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +18814,6328,Female,Loyal Customer,38,Business travel,Business,3737,0,4,0,1,3,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +18815,60049,Male,Loyal Customer,41,Business travel,Business,2992,2,2,2,2,5,5,5,5,5,5,5,4,5,4,4,0.0,satisfied +18816,77750,Female,Loyal Customer,66,Business travel,Eco,331,4,5,5,5,2,3,3,3,3,4,3,2,3,3,0,0.0,satisfied +18817,96590,Male,Loyal Customer,72,Business travel,Business,2241,4,4,4,4,3,2,2,4,4,4,4,1,4,4,61,60.0,neutral or dissatisfied +18818,95469,Female,disloyal Customer,38,Business travel,Eco Plus,319,4,4,4,4,4,4,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +18819,40864,Female,Loyal Customer,67,Personal Travel,Eco,574,1,5,1,2,5,5,4,1,1,1,4,4,1,3,30,38.0,neutral or dissatisfied +18820,108249,Female,disloyal Customer,22,Business travel,Eco,895,1,1,1,2,4,1,4,4,5,4,5,5,4,4,47,52.0,neutral or dissatisfied +18821,36166,Male,Loyal Customer,39,Business travel,Eco,1674,5,1,1,1,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +18822,77074,Female,Loyal Customer,47,Business travel,Business,3245,1,1,5,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +18823,80289,Male,Loyal Customer,28,Business travel,Business,1709,2,2,2,2,4,4,4,4,5,3,5,5,5,4,0,14.0,satisfied +18824,39194,Male,disloyal Customer,34,Business travel,Eco,318,2,4,2,5,3,2,3,3,4,4,4,3,4,3,0,11.0,neutral or dissatisfied +18825,49952,Male,Loyal Customer,53,Business travel,Eco,86,2,1,3,1,2,2,2,2,4,4,4,1,4,2,42,48.0,neutral or dissatisfied +18826,37142,Male,Loyal Customer,27,Business travel,Business,2230,4,3,3,3,4,4,4,4,1,3,3,3,3,4,47,48.0,neutral or dissatisfied +18827,60046,Male,disloyal Customer,28,Business travel,Business,1065,5,5,5,1,3,5,3,3,4,3,5,5,4,3,9,12.0,satisfied +18828,50540,Male,Loyal Customer,52,Personal Travel,Eco,110,0,1,0,3,2,0,2,2,1,5,2,2,3,2,0,7.0,satisfied +18829,122561,Male,Loyal Customer,35,Personal Travel,Eco,500,4,5,4,3,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +18830,89944,Female,Loyal Customer,50,Personal Travel,Eco,1416,3,5,3,3,5,3,4,1,1,3,1,5,1,4,0,14.0,neutral or dissatisfied +18831,97170,Female,Loyal Customer,68,Personal Travel,Eco,1164,2,5,2,1,2,4,4,1,1,2,1,3,1,5,38,43.0,neutral or dissatisfied +18832,97904,Female,Loyal Customer,50,Business travel,Business,3556,3,3,3,3,5,5,4,2,2,2,2,4,2,5,2,0.0,satisfied +18833,88830,Male,Loyal Customer,29,Personal Travel,Eco Plus,270,4,5,4,5,1,4,1,1,5,2,4,3,4,1,7,11.0,neutral or dissatisfied +18834,40889,Male,Loyal Customer,19,Personal Travel,Eco,588,1,5,1,1,2,1,2,2,5,5,5,4,5,2,6,0.0,neutral or dissatisfied +18835,93884,Male,disloyal Customer,24,Business travel,Eco,590,1,1,1,2,1,1,1,1,1,4,2,4,3,1,15,7.0,neutral or dissatisfied +18836,97382,Male,Loyal Customer,68,Personal Travel,Eco,1020,2,2,2,2,3,2,3,3,3,2,2,1,2,3,5,5.0,neutral or dissatisfied +18837,36350,Male,Loyal Customer,50,Business travel,Eco Plus,187,3,2,2,2,2,3,2,2,5,3,4,3,4,2,0,0.0,satisfied +18838,14499,Male,Loyal Customer,28,Business travel,Eco,402,5,5,5,5,5,5,5,5,1,2,4,3,2,5,0,0.0,satisfied +18839,90402,Male,Loyal Customer,70,Personal Travel,Business,366,2,5,2,1,1,1,5,3,3,2,3,1,3,5,0,0.0,neutral or dissatisfied +18840,89075,Male,disloyal Customer,27,Business travel,Business,1947,5,5,5,2,1,5,1,1,5,2,4,5,5,1,0,0.0,satisfied +18841,17384,Male,Loyal Customer,67,Personal Travel,Eco,637,2,4,2,1,3,2,3,3,3,2,5,5,4,3,17,28.0,neutral or dissatisfied +18842,26976,Male,Loyal Customer,32,Business travel,Business,3278,4,5,5,5,4,4,4,4,4,4,3,4,4,4,0,3.0,neutral or dissatisfied +18843,97292,Female,Loyal Customer,45,Business travel,Business,347,4,4,4,4,2,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +18844,116736,Male,Loyal Customer,34,Personal Travel,Eco Plus,417,2,2,2,3,5,2,5,5,4,5,4,1,3,5,5,0.0,neutral or dissatisfied +18845,117621,Male,disloyal Customer,18,Business travel,Eco,872,3,3,3,3,3,5,5,1,2,3,3,5,2,5,168,165.0,neutral or dissatisfied +18846,123248,Male,Loyal Customer,46,Personal Travel,Eco,468,2,3,2,4,4,2,4,4,1,2,3,2,4,4,2,0.0,neutral or dissatisfied +18847,93622,Female,Loyal Customer,62,Business travel,Business,577,5,5,1,5,2,5,5,5,5,5,5,3,5,5,0,3.0,satisfied +18848,5902,Male,Loyal Customer,30,Business travel,Business,3470,2,2,2,2,4,4,4,4,5,2,4,4,5,4,0,0.0,satisfied +18849,33590,Male,Loyal Customer,33,Business travel,Business,1909,5,5,5,5,3,4,3,3,4,4,2,4,5,3,0,0.0,satisfied +18850,69352,Female,disloyal Customer,28,Business travel,Business,1096,2,2,2,1,4,2,2,4,4,4,5,5,5,4,0,7.0,neutral or dissatisfied +18851,121541,Male,Loyal Customer,31,Business travel,Business,3492,2,3,3,3,2,2,2,2,4,3,3,3,3,2,0,0.0,neutral or dissatisfied +18852,78826,Male,Loyal Customer,62,Personal Travel,Eco,432,2,4,2,2,2,2,1,2,4,5,4,5,5,2,1,0.0,neutral or dissatisfied +18853,46734,Female,Loyal Customer,31,Personal Travel,Eco,125,1,1,1,1,3,1,3,3,4,3,2,4,1,3,5,0.0,neutral or dissatisfied +18854,62771,Female,disloyal Customer,39,Business travel,Business,2556,4,4,4,3,3,4,3,3,2,2,3,1,3,3,1,0.0,neutral or dissatisfied +18855,44798,Female,Loyal Customer,53,Business travel,Business,802,4,4,4,4,5,5,5,5,5,5,5,4,5,5,45,37.0,satisfied +18856,21836,Male,disloyal Customer,28,Business travel,Business,448,2,2,2,1,5,2,5,5,3,3,4,3,5,5,30,13.0,neutral or dissatisfied +18857,98028,Female,Loyal Customer,24,Personal Travel,Eco,1014,2,4,2,1,1,2,4,1,4,1,4,1,2,1,0,0.0,neutral or dissatisfied +18858,109641,Male,Loyal Customer,58,Business travel,Eco,802,3,2,2,2,4,3,4,4,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +18859,109957,Female,Loyal Customer,8,Personal Travel,Eco,1092,3,5,3,4,4,3,4,4,5,2,3,1,3,4,35,34.0,neutral or dissatisfied +18860,86007,Female,Loyal Customer,36,Business travel,Business,3341,3,2,2,2,2,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +18861,13316,Male,Loyal Customer,9,Personal Travel,Eco Plus,448,2,4,2,2,2,2,2,2,5,4,4,5,4,2,34,25.0,neutral or dissatisfied +18862,16789,Female,Loyal Customer,62,Personal Travel,Eco Plus,569,2,5,2,3,2,3,3,4,4,2,4,3,4,5,1,0.0,neutral or dissatisfied +18863,12852,Female,Loyal Customer,33,Personal Travel,Eco,641,4,4,4,4,4,4,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +18864,5849,Female,Loyal Customer,27,Business travel,Business,1527,5,5,5,5,4,3,4,4,5,3,4,3,4,4,0,45.0,satisfied +18865,46596,Female,Loyal Customer,41,Business travel,Business,125,2,2,2,2,1,1,3,3,3,4,4,3,3,1,16,10.0,satisfied +18866,81015,Female,Loyal Customer,53,Business travel,Business,1399,1,1,1,1,3,2,2,1,1,1,1,3,1,2,72,68.0,neutral or dissatisfied +18867,50878,Male,Loyal Customer,22,Personal Travel,Eco,89,2,4,2,1,4,2,4,4,3,5,4,5,5,4,30,38.0,neutral or dissatisfied +18868,81622,Female,disloyal Customer,60,Business travel,Business,1142,4,4,4,2,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +18869,78833,Female,Loyal Customer,55,Personal Travel,Eco,447,2,4,2,3,5,3,1,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +18870,7103,Female,Loyal Customer,49,Personal Travel,Eco,273,1,1,1,4,1,3,3,4,4,1,4,1,4,2,10,8.0,neutral or dissatisfied +18871,2862,Male,Loyal Customer,72,Business travel,Business,475,3,4,3,3,4,2,2,3,3,3,3,4,3,1,15,,neutral or dissatisfied +18872,100847,Male,Loyal Customer,7,Personal Travel,Eco,711,1,5,1,4,5,1,5,5,3,3,4,1,3,5,13,16.0,neutral or dissatisfied +18873,2890,Male,Loyal Customer,63,Personal Travel,Eco,491,2,4,2,3,2,2,2,2,4,5,4,2,3,2,6,0.0,neutral or dissatisfied +18874,125996,Female,Loyal Customer,46,Personal Travel,Business,468,5,5,5,2,4,4,4,3,3,5,2,5,3,5,0,0.0,satisfied +18875,32441,Female,Loyal Customer,40,Business travel,Eco,163,3,4,4,4,3,2,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +18876,87687,Male,Loyal Customer,38,Personal Travel,Eco,591,2,3,1,5,3,1,4,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +18877,109452,Female,Loyal Customer,58,Business travel,Business,2714,1,1,2,1,2,5,4,4,4,4,4,3,4,4,1,0.0,satisfied +18878,120121,Male,Loyal Customer,61,Personal Travel,Eco,1576,4,5,4,1,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +18879,52043,Male,Loyal Customer,36,Business travel,Business,1613,4,4,4,4,1,2,2,5,5,5,5,2,5,4,108,99.0,satisfied +18880,13042,Female,Loyal Customer,66,Personal Travel,Eco,438,1,5,1,1,5,5,5,3,3,1,3,4,3,3,2,0.0,neutral or dissatisfied +18881,96714,Female,Loyal Customer,57,Business travel,Business,2665,2,2,2,2,3,3,3,2,2,2,2,1,2,1,22,11.0,neutral or dissatisfied +18882,125551,Female,disloyal Customer,42,Business travel,Eco,226,3,1,3,2,1,3,1,1,4,5,3,2,3,1,0,0.0,neutral or dissatisfied +18883,83894,Male,Loyal Customer,48,Business travel,Business,1450,5,5,5,5,5,4,4,4,4,4,4,4,4,3,0,8.0,satisfied +18884,91382,Female,Loyal Customer,57,Business travel,Business,2218,2,2,4,2,4,4,4,5,5,5,5,5,5,4,0,5.0,satisfied +18885,6269,Female,Loyal Customer,46,Business travel,Business,585,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,3.0,satisfied +18886,75450,Male,Loyal Customer,61,Business travel,Eco,842,5,4,4,4,5,5,5,5,5,3,1,1,4,5,0,4.0,satisfied +18887,126980,Female,Loyal Customer,57,Business travel,Business,2303,3,3,3,3,5,4,5,5,5,5,5,5,5,5,9,2.0,satisfied +18888,44957,Female,Loyal Customer,12,Personal Travel,Eco,334,4,5,4,3,5,4,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +18889,9432,Female,Loyal Customer,53,Business travel,Business,310,1,1,1,1,5,4,4,4,4,5,4,5,4,5,55,70.0,satisfied +18890,95803,Male,Loyal Customer,40,Business travel,Business,2544,3,3,3,3,5,4,5,4,4,4,4,3,4,4,17,0.0,satisfied +18891,62982,Male,Loyal Customer,27,Business travel,Business,2341,3,5,5,5,3,3,3,3,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +18892,111018,Female,Loyal Customer,36,Business travel,Business,2501,3,3,3,3,3,3,4,3,3,3,3,4,3,1,12,11.0,neutral or dissatisfied +18893,12505,Male,Loyal Customer,10,Personal Travel,Eco Plus,201,2,5,2,2,4,2,3,4,5,5,5,5,4,4,0,4.0,neutral or dissatisfied +18894,52024,Male,Loyal Customer,46,Business travel,Business,328,0,0,0,3,1,5,4,3,3,3,5,4,3,2,0,0.0,satisfied +18895,56367,Male,Loyal Customer,26,Personal Travel,Eco,200,2,1,2,2,2,2,2,2,4,3,2,2,2,2,37,37.0,neutral or dissatisfied +18896,51933,Male,Loyal Customer,49,Business travel,Business,2403,3,2,3,3,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +18897,83243,Female,Loyal Customer,33,Business travel,Business,2079,1,1,4,1,3,3,5,3,3,4,3,5,3,5,0,0.0,satisfied +18898,47614,Male,Loyal Customer,45,Business travel,Business,1242,3,3,3,3,5,5,5,3,3,2,5,5,4,5,126,134.0,satisfied +18899,44438,Female,Loyal Customer,31,Business travel,Business,3087,2,5,5,5,2,1,2,2,1,2,3,1,4,2,27,44.0,neutral or dissatisfied +18900,108758,Female,disloyal Customer,38,Business travel,Business,404,4,4,4,4,5,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +18901,73291,Female,disloyal Customer,27,Business travel,Business,1182,4,4,4,4,3,4,4,3,5,3,4,5,4,3,0,0.0,satisfied +18902,16135,Male,Loyal Customer,27,Business travel,Eco Plus,799,4,1,4,1,4,4,4,4,3,4,4,5,1,4,0,0.0,satisfied +18903,115283,Female,Loyal Customer,39,Business travel,Business,480,3,3,3,3,2,4,5,4,4,4,4,3,4,5,2,12.0,satisfied +18904,34985,Female,Loyal Customer,65,Personal Travel,Eco,273,1,5,2,3,3,1,5,4,4,2,1,3,4,2,2,0.0,neutral or dissatisfied +18905,85878,Female,Loyal Customer,59,Business travel,Business,2172,2,2,2,2,4,4,4,4,4,5,4,3,4,3,3,0.0,satisfied +18906,104703,Female,Loyal Customer,31,Personal Travel,Eco,159,1,5,1,3,4,1,4,4,4,3,4,5,4,4,2,5.0,neutral or dissatisfied +18907,91888,Male,Loyal Customer,36,Business travel,Business,2586,2,2,2,2,2,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +18908,32883,Male,Loyal Customer,61,Personal Travel,Eco,201,3,4,3,3,3,3,1,3,2,3,3,2,3,3,0,5.0,neutral or dissatisfied +18909,10218,Female,Loyal Customer,48,Business travel,Business,3822,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,6.0,satisfied +18910,101583,Female,Loyal Customer,53,Business travel,Eco,1099,3,2,2,2,4,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +18911,13807,Female,Loyal Customer,32,Business travel,Business,641,2,2,2,2,5,5,5,5,1,3,5,2,1,5,15,0.0,satisfied +18912,72882,Male,disloyal Customer,28,Business travel,Business,1035,0,0,0,3,2,0,3,2,4,4,5,3,4,2,0,4.0,satisfied +18913,62678,Female,Loyal Customer,69,Personal Travel,Eco Plus,1846,2,3,1,4,5,4,2,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +18914,16239,Female,Loyal Customer,45,Business travel,Eco,748,4,5,5,5,3,1,3,4,4,4,4,4,4,4,76,71.0,satisfied +18915,104654,Male,Loyal Customer,33,Personal Travel,Business,641,2,4,2,2,2,2,2,2,3,5,5,4,4,2,48,55.0,neutral or dissatisfied +18916,432,Female,Loyal Customer,46,Personal Travel,Business,247,2,5,2,3,3,4,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +18917,947,Female,Loyal Customer,45,Business travel,Business,2215,2,1,1,1,5,2,2,2,2,2,2,4,2,3,14,16.0,neutral or dissatisfied +18918,62487,Male,Loyal Customer,28,Business travel,Business,1744,1,1,1,1,5,4,5,5,5,3,4,3,5,5,0,0.0,satisfied +18919,124932,Male,Loyal Customer,65,Personal Travel,Eco,728,1,2,1,4,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +18920,56302,Female,Loyal Customer,10,Personal Travel,Eco,2227,2,3,2,3,4,2,4,4,1,4,2,3,3,4,0,4.0,neutral or dissatisfied +18921,3825,Male,Loyal Customer,54,Business travel,Business,2775,1,2,2,2,2,2,2,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +18922,53634,Female,Loyal Customer,63,Personal Travel,Eco,1874,4,3,4,3,2,4,4,2,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +18923,85668,Male,Loyal Customer,56,Business travel,Business,3602,2,2,2,2,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +18924,86078,Male,Loyal Customer,56,Business travel,Business,356,4,4,4,4,2,5,4,4,4,4,4,3,4,3,45,27.0,satisfied +18925,35081,Female,Loyal Customer,44,Business travel,Business,2081,4,4,4,4,5,5,5,3,2,5,1,5,2,5,126,133.0,satisfied +18926,27089,Male,Loyal Customer,55,Personal Travel,Eco,2496,2,2,2,3,2,2,2,2,3,1,2,4,3,2,5,2.0,neutral or dissatisfied +18927,127555,Female,disloyal Customer,38,Business travel,Business,1009,2,2,2,3,2,2,3,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +18928,47482,Male,Loyal Customer,60,Personal Travel,Eco,584,3,5,3,3,3,3,2,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +18929,85923,Female,disloyal Customer,26,Business travel,Business,761,5,5,5,2,4,5,4,4,4,5,5,3,5,4,50,53.0,satisfied +18930,118531,Male,Loyal Customer,35,Business travel,Eco,369,4,4,4,4,4,4,4,4,3,1,4,1,4,4,17,6.0,neutral or dissatisfied +18931,49319,Male,Loyal Customer,52,Business travel,Business,421,2,2,2,2,5,3,2,4,4,4,4,5,4,3,1,10.0,satisfied +18932,108640,Female,Loyal Customer,54,Business travel,Business,2100,3,3,3,3,4,4,4,4,4,5,4,4,4,3,25,13.0,satisfied +18933,2572,Male,Loyal Customer,51,Business travel,Business,3185,1,1,1,1,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +18934,13741,Male,disloyal Customer,27,Business travel,Eco,401,1,4,2,4,3,2,3,3,1,3,5,3,1,3,0,0.0,neutral or dissatisfied +18935,29050,Female,Loyal Customer,31,Personal Travel,Eco,956,2,5,2,1,5,2,5,5,4,5,5,5,4,5,0,8.0,neutral or dissatisfied +18936,2204,Male,Loyal Customer,15,Personal Travel,Eco,685,4,4,4,3,1,4,1,1,2,3,4,4,4,1,0,0.0,neutral or dissatisfied +18937,81745,Male,Loyal Customer,55,Business travel,Business,2132,4,4,4,4,2,5,5,5,5,5,5,4,5,3,3,0.0,satisfied +18938,39626,Male,Loyal Customer,14,Personal Travel,Eco,748,1,5,1,4,4,1,4,4,3,2,1,5,3,4,0,0.0,neutral or dissatisfied +18939,77736,Male,Loyal Customer,41,Business travel,Business,731,2,2,2,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +18940,83885,Male,Loyal Customer,26,Personal Travel,Eco,1670,1,0,1,2,1,1,1,1,3,2,5,5,5,1,0,3.0,neutral or dissatisfied +18941,72139,Male,Loyal Customer,23,Business travel,Eco,331,5,3,3,3,5,5,4,5,1,5,4,4,4,5,48,43.0,satisfied +18942,96810,Male,Loyal Customer,42,Business travel,Eco,816,2,5,5,5,3,2,3,3,2,2,3,3,4,3,85,81.0,neutral or dissatisfied +18943,52651,Female,Loyal Customer,61,Personal Travel,Eco,160,4,4,4,3,2,4,4,4,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +18944,52639,Female,Loyal Customer,69,Personal Travel,Eco,160,3,3,3,3,3,4,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +18945,45537,Male,disloyal Customer,24,Business travel,Eco,566,0,5,0,2,5,0,3,5,3,5,4,5,1,5,1,0.0,satisfied +18946,40142,Male,disloyal Customer,25,Business travel,Business,840,5,0,4,2,5,4,5,5,4,3,4,5,5,5,0,0.0,satisfied +18947,117230,Male,Loyal Customer,61,Personal Travel,Eco,647,5,5,5,5,3,5,4,3,1,1,5,5,3,3,0,0.0,satisfied +18948,15752,Female,Loyal Customer,62,Business travel,Business,461,3,4,4,4,3,3,4,3,3,3,3,4,3,2,45,52.0,neutral or dissatisfied +18949,128261,Female,Loyal Customer,35,Business travel,Business,3528,1,5,5,5,1,3,3,1,1,1,1,2,1,1,0,6.0,neutral or dissatisfied +18950,119196,Male,Loyal Customer,37,Business travel,Business,290,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +18951,127120,Male,Loyal Customer,61,Personal Travel,Eco,651,2,5,2,4,3,2,3,3,5,3,1,5,4,3,0,0.0,neutral or dissatisfied +18952,21868,Female,disloyal Customer,26,Business travel,Eco,448,2,3,2,1,1,2,1,1,2,4,5,2,2,1,0,0.0,neutral or dissatisfied +18953,93696,Male,Loyal Customer,43,Business travel,Business,2355,3,3,4,3,4,1,5,5,5,5,5,2,5,2,47,51.0,satisfied +18954,65715,Female,Loyal Customer,47,Business travel,Eco,1061,4,5,5,5,1,3,4,4,4,4,4,2,4,1,0,2.0,neutral or dissatisfied +18955,123068,Male,disloyal Customer,25,Business travel,Business,468,2,0,2,4,5,2,5,5,4,5,4,3,5,5,22,22.0,neutral or dissatisfied +18956,73399,Male,disloyal Customer,23,Business travel,Eco,1182,2,2,2,3,5,2,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +18957,107145,Female,Loyal Customer,50,Business travel,Business,1646,2,2,2,2,4,5,5,5,5,5,5,5,5,3,35,36.0,satisfied +18958,120424,Male,Loyal Customer,48,Business travel,Business,2437,1,5,5,5,3,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +18959,20117,Female,Loyal Customer,41,Business travel,Eco,416,5,2,2,2,5,5,5,5,4,1,1,4,4,5,10,5.0,satisfied +18960,91397,Male,Loyal Customer,23,Business travel,Eco,658,5,5,2,2,5,5,4,5,2,2,5,4,1,5,0,4.0,satisfied +18961,123297,Male,Loyal Customer,37,Business travel,Business,2946,5,5,4,5,3,5,5,4,4,4,4,5,4,3,4,3.0,satisfied +18962,30042,Male,disloyal Customer,30,Business travel,Eco,95,2,5,2,4,3,2,2,3,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +18963,46574,Female,Loyal Customer,66,Business travel,Business,196,2,3,3,3,4,3,2,3,3,2,2,1,3,3,82,71.0,neutral or dissatisfied +18964,79962,Male,Loyal Customer,18,Business travel,Business,1096,4,4,4,4,4,4,4,4,2,2,4,4,3,4,0,0.0,satisfied +18965,56708,Male,Loyal Customer,46,Personal Travel,Eco,1085,3,4,3,3,2,3,2,2,3,1,4,4,3,2,2,0.0,neutral or dissatisfied +18966,24525,Male,Loyal Customer,44,Business travel,Eco,892,2,2,2,2,1,2,1,1,3,5,4,3,3,1,0,8.0,neutral or dissatisfied +18967,6930,Male,Loyal Customer,47,Business travel,Business,588,5,5,4,5,3,4,5,4,4,4,4,3,4,5,63,120.0,satisfied +18968,93345,Female,Loyal Customer,35,Business travel,Business,836,3,3,3,3,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18969,15646,Male,Loyal Customer,30,Personal Travel,Eco Plus,228,2,4,2,3,3,2,3,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +18970,101277,Female,Loyal Customer,60,Business travel,Business,444,2,2,3,2,5,4,5,4,4,4,4,4,4,3,0,7.0,satisfied +18971,108394,Male,disloyal Customer,50,Business travel,Eco Plus,1844,1,1,1,4,4,1,4,4,3,5,4,3,4,4,11,18.0,neutral or dissatisfied +18972,18562,Female,disloyal Customer,25,Business travel,Eco,192,1,3,1,3,5,1,5,5,4,3,2,1,2,5,0,0.0,neutral or dissatisfied +18973,124987,Male,Loyal Customer,20,Business travel,Business,3836,2,2,2,2,5,5,4,5,3,4,4,5,5,5,0,0.0,satisfied +18974,103693,Male,disloyal Customer,23,Business travel,Eco,405,2,2,2,3,2,2,2,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +18975,95865,Female,Loyal Customer,41,Business travel,Business,580,2,2,2,2,4,4,4,3,3,4,3,3,3,3,3,7.0,satisfied +18976,106305,Male,Loyal Customer,35,Business travel,Business,3799,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +18977,53260,Female,Loyal Customer,42,Business travel,Eco Plus,4817,2,2,2,2,2,2,2,2,4,1,3,2,3,2,17,14.0,neutral or dissatisfied +18978,49867,Female,Loyal Customer,29,Business travel,Business,209,5,5,4,5,5,5,5,5,3,3,5,4,2,5,0,2.0,satisfied +18979,116593,Male,Loyal Customer,47,Business travel,Business,3485,2,2,3,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +18980,92657,Female,Loyal Customer,7,Personal Travel,Eco,453,3,1,3,4,4,3,4,4,3,5,4,2,3,4,13,5.0,neutral or dissatisfied +18981,11579,Female,Loyal Customer,49,Business travel,Business,3417,4,4,2,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +18982,117648,Male,disloyal Customer,25,Business travel,Eco,1020,1,1,1,4,3,1,3,3,1,5,4,2,3,3,0,10.0,neutral or dissatisfied +18983,68428,Male,Loyal Customer,45,Personal Travel,Eco,1045,1,4,1,4,5,1,5,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +18984,97113,Female,Loyal Customer,31,Business travel,Business,1390,3,2,2,2,3,3,3,3,4,4,4,3,4,3,7,12.0,neutral or dissatisfied +18985,33348,Female,disloyal Customer,44,Business travel,Eco,1073,1,1,1,2,2,1,2,2,5,3,3,4,5,2,0,0.0,neutral or dissatisfied +18986,36963,Female,Loyal Customer,39,Business travel,Eco,805,4,3,3,3,4,4,4,4,5,2,2,5,2,4,94,104.0,satisfied +18987,51295,Female,disloyal Customer,48,Business travel,Eco Plus,199,2,2,2,3,3,2,5,3,2,4,3,3,2,3,55,49.0,neutral or dissatisfied +18988,90145,Male,Loyal Customer,38,Business travel,Eco,583,5,1,1,1,5,5,5,2,2,1,4,5,3,5,300,290.0,satisfied +18989,84145,Female,Loyal Customer,31,Business travel,Business,1782,5,4,5,5,5,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +18990,57257,Female,disloyal Customer,23,Business travel,Eco,628,2,0,2,3,4,2,4,4,4,5,5,3,4,4,35,22.0,neutral or dissatisfied +18991,61843,Male,Loyal Customer,9,Business travel,Eco Plus,1635,4,2,2,2,4,4,3,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +18992,71299,Female,Loyal Customer,46,Business travel,Business,1514,3,3,3,3,5,5,5,4,4,4,4,4,4,5,1,0.0,satisfied +18993,85016,Male,Loyal Customer,38,Business travel,Eco,1190,5,3,3,3,5,4,5,5,3,1,3,2,4,5,10,9.0,satisfied +18994,108461,Female,Loyal Customer,29,Personal Travel,Eco,1444,1,0,2,2,5,2,2,5,5,4,4,5,4,5,19,36.0,neutral or dissatisfied +18995,33245,Female,disloyal Customer,39,Business travel,Eco Plus,201,3,3,3,1,4,3,4,4,2,2,2,2,5,4,0,0.0,neutral or dissatisfied +18996,44345,Female,Loyal Customer,54,Business travel,Business,2053,4,5,4,4,2,5,3,4,4,4,4,2,4,3,0,0.0,satisfied +18997,41954,Female,Loyal Customer,43,Business travel,Business,618,4,4,4,4,1,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +18998,82603,Male,Loyal Customer,12,Business travel,Business,528,3,3,3,3,3,3,3,3,2,4,3,2,3,3,0,0.0,neutral or dissatisfied +18999,116970,Male,Loyal Customer,42,Business travel,Business,2514,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +19000,50253,Female,Loyal Customer,49,Business travel,Eco,209,3,1,1,1,4,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +19001,96490,Male,disloyal Customer,24,Business travel,Eco,436,4,3,4,3,4,4,5,4,3,3,3,2,4,4,0,0.0,neutral or dissatisfied +19002,129853,Female,Loyal Customer,30,Personal Travel,Eco,447,1,2,1,4,1,4,4,3,3,4,4,4,3,4,145,138.0,neutral or dissatisfied +19003,115400,Female,disloyal Customer,24,Business travel,Eco,337,3,5,3,5,1,3,1,1,3,5,4,4,5,1,79,88.0,neutral or dissatisfied +19004,3826,Female,disloyal Customer,34,Business travel,Eco,650,2,1,2,3,4,2,4,4,1,4,3,2,4,4,6,0.0,neutral or dissatisfied +19005,26143,Male,Loyal Customer,76,Business travel,Business,270,0,0,0,3,3,4,3,2,2,2,2,4,2,1,0,0.0,satisfied +19006,54103,Female,Loyal Customer,29,Business travel,Eco Plus,1416,0,0,0,2,3,0,2,3,4,1,1,5,4,3,0,0.0,satisfied +19007,28321,Male,Loyal Customer,30,Business travel,Business,3441,1,1,1,1,4,4,4,4,2,4,2,3,1,4,0,0.0,satisfied +19008,62679,Male,Loyal Customer,56,Personal Travel,Eco Plus,1846,4,5,4,1,4,4,4,4,2,3,5,1,5,4,0,0.0,satisfied +19009,59651,Female,Loyal Customer,38,Business travel,Business,3242,5,5,4,5,4,1,1,3,3,5,3,5,3,1,0,0.0,satisfied +19010,104281,Female,Loyal Customer,24,Business travel,Eco Plus,1733,4,4,4,4,4,3,1,4,4,5,1,2,3,4,7,15.0,neutral or dissatisfied +19011,53676,Male,Loyal Customer,49,Business travel,Eco,1208,3,5,5,5,3,3,3,3,4,1,5,3,3,3,0,2.0,satisfied +19012,84991,Male,disloyal Customer,24,Business travel,Eco,1590,4,4,4,1,3,4,3,3,3,3,5,3,4,3,0,7.0,satisfied +19013,12838,Female,Loyal Customer,35,Personal Travel,Eco,528,4,4,4,4,4,4,4,4,5,3,4,3,4,4,1,0.0,satisfied +19014,24567,Male,Loyal Customer,60,Personal Travel,Eco,696,2,4,2,1,3,2,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +19015,67232,Male,Loyal Customer,40,Personal Travel,Eco,964,2,4,2,1,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +19016,6042,Male,Loyal Customer,23,Business travel,Business,2805,1,4,4,4,1,1,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +19017,60281,Female,Loyal Customer,12,Personal Travel,Eco,2446,1,4,1,2,1,1,1,1,5,4,4,5,4,1,8,0.0,neutral or dissatisfied +19018,19457,Male,Loyal Customer,60,Business travel,Business,84,2,2,1,2,5,5,4,5,5,5,5,3,5,5,46,57.0,satisfied +19019,127015,Female,disloyal Customer,25,Business travel,Business,304,3,0,3,3,1,3,1,1,4,5,5,5,4,1,0,27.0,neutral or dissatisfied +19020,125152,Male,Loyal Customer,34,Personal Travel,Eco,1999,5,5,5,5,5,5,5,5,4,2,5,5,5,5,34,26.0,satisfied +19021,94615,Female,Loyal Customer,24,Business travel,Business,3666,3,2,2,2,3,3,3,3,4,3,2,2,1,3,0,0.0,neutral or dissatisfied +19022,128388,Male,Loyal Customer,51,Business travel,Business,338,2,2,2,2,1,2,3,2,2,2,2,2,2,3,43,38.0,neutral or dissatisfied +19023,86864,Female,Loyal Customer,55,Personal Travel,Eco,484,2,0,2,4,4,4,4,5,5,2,5,4,5,5,3,0.0,neutral or dissatisfied +19024,94563,Male,Loyal Customer,57,Business travel,Business,2576,5,5,5,5,5,5,5,4,2,4,5,5,3,5,146,135.0,satisfied +19025,13056,Female,Loyal Customer,47,Business travel,Business,3384,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +19026,65783,Male,Loyal Customer,41,Business travel,Business,1521,5,3,5,5,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +19027,95203,Male,Loyal Customer,47,Personal Travel,Eco,293,3,3,3,1,1,3,4,1,3,1,1,5,4,1,0,16.0,neutral or dissatisfied +19028,7869,Male,Loyal Customer,57,Business travel,Business,910,4,4,4,4,4,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +19029,113373,Female,Loyal Customer,40,Business travel,Business,236,0,0,0,1,5,5,4,1,1,1,1,5,1,4,1,10.0,satisfied +19030,55756,Male,Loyal Customer,22,Personal Travel,Eco,1737,3,4,3,4,1,3,1,1,4,3,3,4,5,1,0,1.0,neutral or dissatisfied +19031,13718,Female,Loyal Customer,41,Business travel,Eco,401,2,2,5,2,2,2,2,2,1,5,2,4,4,2,6,0.0,satisfied +19032,19734,Male,Loyal Customer,62,Personal Travel,Eco,409,3,5,3,1,4,3,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +19033,46187,Female,disloyal Customer,65,Business travel,Business,472,5,5,5,1,5,5,5,5,3,2,4,4,4,5,2,10.0,satisfied +19034,30084,Male,Loyal Customer,63,Personal Travel,Eco,571,4,4,4,5,5,4,5,5,4,5,5,3,5,5,3,2.0,satisfied +19035,71702,Female,Loyal Customer,72,Business travel,Eco Plus,1197,4,4,4,4,4,3,2,4,4,4,4,3,4,2,24,12.0,neutral or dissatisfied +19036,128759,Male,disloyal Customer,26,Business travel,Business,550,2,3,3,2,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +19037,112584,Female,Loyal Customer,23,Business travel,Business,639,4,5,5,5,4,4,4,4,4,3,4,1,4,4,90,87.0,neutral or dissatisfied +19038,60899,Female,disloyal Customer,22,Business travel,Eco,420,4,4,4,5,1,4,1,1,4,3,5,5,5,1,0,0.0,satisfied +19039,104361,Male,Loyal Customer,42,Business travel,Business,452,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,15.0,satisfied +19040,37930,Male,Loyal Customer,14,Personal Travel,Eco,1065,3,4,3,3,3,3,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +19041,108542,Male,Loyal Customer,38,Business travel,Business,3559,4,5,5,5,1,1,2,4,4,4,4,2,4,1,34,34.0,neutral or dissatisfied +19042,6190,Female,Loyal Customer,22,Personal Travel,Eco,409,0,1,0,3,2,0,2,2,2,2,3,1,3,2,0,0.0,satisfied +19043,67296,Female,Loyal Customer,43,Business travel,Eco Plus,964,3,4,4,4,1,3,3,3,3,3,3,4,3,4,23,16.0,neutral or dissatisfied +19044,47302,Male,Loyal Customer,49,Business travel,Business,3752,4,2,2,2,4,3,2,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +19045,109656,Female,Loyal Customer,59,Business travel,Eco,802,1,4,4,4,1,1,1,3,2,4,4,1,4,1,138,119.0,neutral or dissatisfied +19046,34000,Female,disloyal Customer,26,Business travel,Eco,1598,2,2,2,2,3,2,3,3,5,1,4,2,4,3,1,0.0,neutral or dissatisfied +19047,41202,Male,Loyal Customer,35,Business travel,Business,1656,2,2,2,2,5,5,3,4,4,4,4,2,4,4,1,0.0,satisfied +19048,107199,Female,Loyal Customer,30,Personal Travel,Eco,402,3,4,3,5,5,3,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +19049,16452,Male,Loyal Customer,16,Personal Travel,Eco,445,3,4,3,3,3,3,3,3,5,4,5,2,4,3,43,26.0,neutral or dissatisfied +19050,36657,Male,Loyal Customer,45,Personal Travel,Eco,1249,3,5,3,5,4,3,4,4,3,5,3,5,5,4,0,10.0,neutral or dissatisfied +19051,92171,Male,Loyal Customer,44,Business travel,Business,1979,5,5,5,5,4,4,5,4,4,4,4,4,4,3,13,24.0,satisfied +19052,66164,Female,Loyal Customer,64,Business travel,Business,1725,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,2.0,satisfied +19053,37931,Male,Loyal Customer,18,Personal Travel,Eco,937,2,3,2,4,1,2,1,1,5,2,1,5,2,1,6,1.0,neutral or dissatisfied +19054,124943,Female,Loyal Customer,13,Personal Travel,Eco,728,3,3,3,5,4,3,1,4,2,3,2,2,2,4,17,48.0,neutral or dissatisfied +19055,104574,Male,Loyal Customer,55,Business travel,Business,369,5,5,5,5,2,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +19056,112383,Female,Loyal Customer,49,Business travel,Business,2161,3,4,3,3,5,5,4,5,5,5,5,4,5,5,65,59.0,satisfied +19057,98025,Male,Loyal Customer,44,Business travel,Eco,1014,4,4,4,4,4,4,4,4,1,2,4,4,3,4,0,13.0,neutral or dissatisfied +19058,74089,Female,Loyal Customer,51,Business travel,Business,1692,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +19059,88918,Male,Loyal Customer,43,Personal Travel,Eco,859,3,3,3,3,4,3,4,4,2,1,4,2,3,4,32,17.0,neutral or dissatisfied +19060,102005,Female,disloyal Customer,8,Business travel,Eco,628,3,1,3,3,3,3,3,3,1,1,3,4,3,3,37,34.0,neutral or dissatisfied +19061,112116,Female,Loyal Customer,23,Business travel,Eco Plus,1024,3,5,5,5,3,2,3,3,3,1,4,1,4,3,20,13.0,neutral or dissatisfied +19062,78072,Male,Loyal Customer,45,Business travel,Business,332,2,2,2,2,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +19063,108052,Male,Loyal Customer,63,Personal Travel,Eco,591,2,5,2,1,2,2,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +19064,29683,Female,Loyal Customer,45,Personal Travel,Eco Plus,1448,2,4,3,4,5,2,1,5,5,3,5,4,5,3,24,59.0,neutral or dissatisfied +19065,49359,Male,Loyal Customer,43,Business travel,Eco,421,4,3,3,3,4,4,4,4,5,5,5,5,4,4,42,68.0,satisfied +19066,54466,Male,disloyal Customer,25,Business travel,Eco,925,2,2,2,3,3,2,3,3,3,1,1,1,4,3,16,24.0,neutral or dissatisfied +19067,15017,Male,Loyal Customer,14,Personal Travel,Eco,557,4,2,4,4,1,4,1,1,4,3,3,2,4,1,92,86.0,satisfied +19068,65650,Male,disloyal Customer,23,Business travel,Eco,926,0,0,0,2,3,0,3,3,5,4,4,4,4,3,46,52.0,satisfied +19069,119783,Male,disloyal Customer,21,Business travel,Eco,912,4,4,4,3,1,4,5,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +19070,97025,Male,Loyal Customer,39,Business travel,Business,1996,5,5,5,5,2,5,5,5,5,5,5,3,5,5,28,28.0,satisfied +19071,117729,Male,Loyal Customer,56,Business travel,Business,2941,1,1,1,1,3,5,5,4,4,4,4,5,4,5,31,14.0,satisfied +19072,46619,Female,Loyal Customer,43,Business travel,Business,125,0,3,0,5,2,3,4,2,2,2,2,3,2,4,2,0.0,satisfied +19073,112239,Male,Loyal Customer,45,Business travel,Business,1546,4,2,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +19074,58908,Female,Loyal Customer,24,Business travel,Eco,888,2,4,4,4,2,2,2,2,1,2,4,2,4,2,17,7.0,neutral or dissatisfied +19075,92051,Male,Loyal Customer,44,Business travel,Business,1589,2,2,2,2,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +19076,64862,Female,Loyal Customer,54,Business travel,Business,247,1,5,5,5,5,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +19077,47597,Female,Loyal Customer,48,Business travel,Eco,1504,5,2,2,2,5,4,5,5,5,5,5,5,5,4,3,0.0,satisfied +19078,104766,Male,Loyal Customer,43,Personal Travel,Eco,1407,1,5,1,4,5,1,5,5,3,1,4,5,1,5,16,22.0,neutral or dissatisfied +19079,62497,Male,Loyal Customer,37,Business travel,Business,1846,2,2,2,2,3,5,4,5,5,5,5,5,5,5,19,0.0,satisfied +19080,8814,Female,Loyal Customer,36,Personal Travel,Eco,522,2,4,2,1,2,2,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +19081,17461,Female,Loyal Customer,21,Business travel,Eco,677,1,4,1,4,1,1,2,1,4,4,4,1,3,1,0,24.0,neutral or dissatisfied +19082,35848,Female,Loyal Customer,50,Business travel,Eco,1023,3,1,1,1,5,3,4,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +19083,279,Female,Loyal Customer,23,Personal Travel,Eco,825,3,3,3,4,1,3,1,1,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +19084,123181,Female,Loyal Customer,59,Personal Travel,Eco,650,5,1,4,3,1,3,4,5,5,4,5,4,5,4,0,0.0,satisfied +19085,65840,Male,Loyal Customer,51,Business travel,Business,1389,1,1,1,1,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +19086,15626,Male,Loyal Customer,33,Personal Travel,Eco,296,2,2,2,2,4,2,4,4,1,1,3,1,2,4,0,0.0,neutral or dissatisfied +19087,24851,Female,Loyal Customer,35,Business travel,Eco Plus,894,3,1,1,1,3,4,3,3,1,1,5,1,4,3,0,0.0,satisfied +19088,50490,Male,Loyal Customer,57,Personal Travel,Eco,363,5,5,5,3,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +19089,54814,Female,Loyal Customer,31,Business travel,Business,862,1,1,1,1,4,3,4,4,4,4,5,5,4,4,26,29.0,satisfied +19090,7776,Female,Loyal Customer,25,Personal Travel,Eco,990,2,5,3,4,4,3,4,4,4,3,4,4,5,4,0,12.0,neutral or dissatisfied +19091,5776,Female,Loyal Customer,49,Business travel,Business,273,0,0,0,2,3,3,3,5,3,5,5,3,3,3,191,173.0,satisfied +19092,58376,Male,Loyal Customer,53,Business travel,Business,2579,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +19093,20446,Male,Loyal Customer,42,Business travel,Eco,177,3,2,2,2,3,3,3,3,1,3,4,1,4,3,69,58.0,neutral or dissatisfied +19094,42788,Male,Loyal Customer,64,Personal Travel,Eco,1118,3,4,3,3,1,3,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +19095,19921,Female,disloyal Customer,16,Business travel,Eco,240,1,0,1,1,4,1,4,4,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +19096,26366,Female,Loyal Customer,69,Business travel,Business,3842,2,2,2,2,5,4,4,2,2,2,2,4,2,3,34,22.0,neutral or dissatisfied +19097,455,Male,Loyal Customer,47,Business travel,Business,3145,5,5,5,5,4,5,5,5,5,5,5,4,5,3,51,34.0,satisfied +19098,56720,Female,Loyal Customer,64,Personal Travel,Eco,1023,4,0,4,2,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +19099,58566,Male,Loyal Customer,35,Business travel,Business,1687,2,1,1,1,3,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +19100,109594,Female,disloyal Customer,39,Business travel,Business,993,2,2,2,4,2,2,2,2,3,1,3,4,4,2,88,102.0,neutral or dissatisfied +19101,77261,Male,Loyal Customer,65,Personal Travel,Eco,1590,1,1,1,3,4,1,4,4,4,4,3,2,2,4,1,0.0,neutral or dissatisfied +19102,34779,Male,Loyal Customer,29,Personal Travel,Eco,301,2,5,2,4,3,2,3,3,5,3,5,4,4,3,30,17.0,neutral or dissatisfied +19103,107174,Male,Loyal Customer,48,Business travel,Business,1907,1,1,1,1,3,4,4,5,5,5,5,5,5,4,10,0.0,satisfied +19104,73711,Male,Loyal Customer,30,Business travel,Business,192,2,2,2,2,5,5,5,5,4,2,5,5,5,5,0,0.0,satisfied +19105,126804,Male,Loyal Customer,41,Business travel,Business,2077,3,3,3,3,3,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +19106,62659,Female,Loyal Customer,37,Business travel,Business,1726,3,3,3,3,4,4,4,3,4,5,5,4,4,4,136,110.0,satisfied +19107,40246,Female,Loyal Customer,43,Business travel,Business,387,4,4,4,4,2,1,2,4,4,4,4,5,4,2,0,0.0,satisfied +19108,55212,Female,Loyal Customer,33,Personal Travel,Business,1009,1,3,1,2,2,2,2,1,1,1,1,4,1,2,3,9.0,neutral or dissatisfied +19109,83101,Male,Loyal Customer,16,Personal Travel,Eco,1084,4,3,3,3,3,3,3,3,4,4,3,1,2,3,0,0.0,neutral or dissatisfied +19110,18494,Female,disloyal Customer,26,Business travel,Eco,201,1,1,0,3,2,0,2,2,3,5,3,3,3,2,20,9.0,neutral or dissatisfied +19111,65931,Male,Loyal Customer,53,Personal Travel,Eco,569,1,2,0,3,3,0,3,3,3,4,3,1,3,3,7,0.0,neutral or dissatisfied +19112,84753,Female,Loyal Customer,53,Business travel,Business,481,1,1,3,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +19113,120598,Female,Loyal Customer,29,Personal Travel,Eco,980,2,5,2,3,3,2,3,3,4,1,3,2,1,3,0,0.0,neutral or dissatisfied +19114,110214,Female,disloyal Customer,80,Business travel,Business,910,3,3,3,3,4,2,3,3,3,3,2,1,3,3,4,0.0,neutral or dissatisfied +19115,36432,Female,Loyal Customer,16,Personal Travel,Eco,369,2,3,3,3,2,3,2,2,2,4,1,5,4,2,0,0.0,neutral or dissatisfied +19116,43197,Male,Loyal Customer,26,Personal Travel,Eco,651,1,1,1,3,3,1,3,3,3,4,3,1,4,3,0,10.0,neutral or dissatisfied +19117,104848,Female,Loyal Customer,57,Business travel,Business,3599,1,1,1,1,5,4,5,3,3,4,3,4,3,4,60,56.0,satisfied +19118,40152,Male,Loyal Customer,55,Business travel,Business,2554,2,3,2,2,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +19119,94167,Female,Loyal Customer,34,Business travel,Business,2550,0,0,0,5,2,4,5,2,2,2,2,5,2,4,4,5.0,satisfied +19120,54351,Female,Loyal Customer,40,Business travel,Eco,1235,3,3,4,4,3,4,3,3,5,1,4,2,1,3,0,0.0,satisfied +19121,69505,Female,Loyal Customer,53,Business travel,Business,1746,2,2,4,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +19122,115344,Female,Loyal Customer,39,Business travel,Business,325,4,2,4,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +19123,99169,Female,Loyal Customer,24,Personal Travel,Eco,1076,3,4,3,5,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +19124,30280,Male,Loyal Customer,56,Personal Travel,Eco,1024,3,5,3,3,3,3,3,3,5,3,4,5,4,3,11,5.0,neutral or dissatisfied +19125,10730,Female,disloyal Customer,17,Business travel,Eco,301,2,2,2,3,2,2,4,2,1,2,4,2,4,2,19,17.0,neutral or dissatisfied +19126,94737,Female,Loyal Customer,58,Business travel,Business,189,2,2,5,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +19127,12338,Male,Loyal Customer,40,Business travel,Business,192,4,2,2,2,2,4,2,2,5,4,3,2,4,2,104,177.0,neutral or dissatisfied +19128,88445,Female,Loyal Customer,42,Business travel,Business,515,4,4,4,4,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +19129,45333,Female,Loyal Customer,16,Business travel,Business,1713,0,3,0,4,3,3,3,3,1,2,3,5,4,3,0,0.0,satisfied +19130,84924,Male,Loyal Customer,50,Personal Travel,Eco,516,3,4,3,2,4,3,2,4,4,4,4,1,1,4,0,0.0,neutral or dissatisfied +19131,91903,Male,Loyal Customer,29,Business travel,Eco,2586,4,4,4,4,4,4,4,4,3,5,4,4,3,4,0,0.0,neutral or dissatisfied +19132,84738,Female,Loyal Customer,48,Business travel,Business,481,1,1,1,1,2,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +19133,89367,Male,disloyal Customer,22,Business travel,Business,1541,0,4,0,4,2,0,1,2,5,4,4,4,4,2,72,63.0,satisfied +19134,7975,Female,Loyal Customer,49,Personal Travel,Eco Plus,594,3,4,3,4,3,3,5,1,1,3,1,2,1,5,0,0.0,neutral or dissatisfied +19135,93347,Female,Loyal Customer,38,Business travel,Business,1570,2,1,2,2,2,5,4,5,5,5,5,3,5,5,8,0.0,satisfied +19136,59078,Female,disloyal Customer,26,Business travel,Eco,346,4,1,4,1,3,4,5,3,4,1,1,4,2,3,0,0.0,neutral or dissatisfied +19137,81776,Male,Loyal Customer,25,Business travel,Business,1487,1,1,3,1,5,4,5,5,4,4,4,3,4,5,0,0.0,satisfied +19138,123568,Female,Loyal Customer,60,Business travel,Business,1773,2,2,2,2,4,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +19139,89109,Male,Loyal Customer,58,Business travel,Eco,1947,2,2,2,2,2,2,2,2,2,1,3,1,2,2,5,8.0,neutral or dissatisfied +19140,29551,Female,Loyal Customer,64,Business travel,Business,1533,2,2,2,2,4,3,5,2,2,2,2,1,2,1,0,12.0,satisfied +19141,4411,Male,Loyal Customer,32,Personal Travel,Business,762,3,3,3,3,3,3,3,3,1,3,5,3,4,3,38,44.0,neutral or dissatisfied +19142,124126,Male,Loyal Customer,53,Business travel,Eco,529,5,2,2,2,5,5,5,5,5,4,5,2,4,5,0,0.0,satisfied +19143,52070,Female,Loyal Customer,29,Business travel,Business,3821,2,2,2,2,4,4,4,4,5,3,5,4,2,4,0,35.0,satisfied +19144,112801,Male,Loyal Customer,49,Business travel,Business,3664,2,3,3,3,1,3,3,2,2,2,2,2,2,2,30,12.0,neutral or dissatisfied +19145,32892,Female,Loyal Customer,65,Personal Travel,Eco,163,5,4,5,4,4,4,4,5,5,5,5,4,5,4,0,4.0,satisfied +19146,112244,Male,Loyal Customer,39,Business travel,Business,1447,2,2,2,2,2,5,4,4,4,5,4,4,4,5,71,63.0,satisfied +19147,89107,Female,disloyal Customer,21,Business travel,Eco,2139,1,2,2,2,2,1,2,2,4,1,2,3,3,2,35,35.0,neutral or dissatisfied +19148,124400,Male,Loyal Customer,36,Business travel,Business,1262,2,2,5,2,4,5,4,5,5,5,5,4,5,3,14,0.0,satisfied +19149,22681,Female,disloyal Customer,21,Business travel,Business,589,5,4,5,4,3,4,3,3,2,4,1,2,2,3,0,0.0,satisfied +19150,129662,Female,disloyal Customer,27,Business travel,Business,308,2,2,2,1,4,2,4,4,5,2,4,3,5,4,0,4.0,neutral or dissatisfied +19151,112446,Male,disloyal Customer,11,Business travel,Business,862,4,0,3,1,3,3,4,3,5,5,5,4,4,3,5,1.0,satisfied +19152,5875,Female,Loyal Customer,43,Business travel,Business,212,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +19153,22288,Female,disloyal Customer,27,Business travel,Eco,238,4,0,4,3,2,4,2,2,2,5,4,2,1,2,0,0.0,neutral or dissatisfied +19154,3055,Male,Loyal Customer,55,Business travel,Business,2503,3,3,3,3,2,5,4,5,5,5,5,5,5,5,18,9.0,satisfied +19155,126135,Female,Loyal Customer,56,Business travel,Business,2770,5,1,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +19156,105090,Male,Loyal Customer,42,Business travel,Business,2681,0,0,0,3,3,4,4,4,4,4,4,4,4,4,19,19.0,satisfied +19157,126245,Male,Loyal Customer,39,Business travel,Business,328,0,0,0,3,5,1,1,5,5,5,5,3,5,2,0,0.0,satisfied +19158,60806,Male,Loyal Customer,50,Business travel,Business,3002,2,3,2,2,5,4,5,5,5,5,5,4,5,5,73,68.0,satisfied +19159,68416,Male,Loyal Customer,57,Personal Travel,Eco,1045,5,5,5,3,4,5,4,4,3,3,1,2,4,4,0,4.0,satisfied +19160,111027,Female,Loyal Customer,55,Business travel,Eco,197,1,4,4,4,2,3,4,1,1,1,1,2,1,2,14,9.0,neutral or dissatisfied +19161,52154,Female,Loyal Customer,23,Personal Travel,Business,370,2,4,2,3,1,2,1,1,2,2,3,4,4,1,0,0.0,neutral or dissatisfied +19162,127156,Male,Loyal Customer,9,Personal Travel,Eco,338,2,5,2,1,3,2,3,3,4,2,4,4,1,3,0,0.0,neutral or dissatisfied +19163,29770,Male,disloyal Customer,80,Business travel,Business,373,1,1,1,5,2,5,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +19164,116801,Female,Loyal Customer,9,Personal Travel,Eco Plus,447,2,2,2,3,2,2,2,2,3,2,3,1,4,2,13,4.0,neutral or dissatisfied +19165,35680,Male,disloyal Customer,25,Business travel,Eco,1408,4,4,4,2,4,5,5,5,2,3,1,5,5,5,0,0.0,satisfied +19166,7779,Male,Loyal Customer,12,Personal Travel,Eco,990,1,4,1,1,3,1,3,3,4,5,5,3,5,3,13,16.0,neutral or dissatisfied +19167,91601,Female,disloyal Customer,24,Business travel,Eco,1199,5,5,5,3,5,5,5,5,5,2,4,3,4,5,130,131.0,satisfied +19168,71723,Male,Loyal Customer,34,Business travel,Business,888,1,1,3,1,4,4,3,1,1,1,1,4,1,3,1,7.0,neutral or dissatisfied +19169,38186,Male,Loyal Customer,54,Personal Travel,Eco,1091,1,4,1,4,4,1,4,4,1,5,2,5,5,4,0,0.0,neutral or dissatisfied +19170,92930,Female,Loyal Customer,32,Business travel,Business,151,0,5,0,4,3,3,3,3,1,2,1,4,2,3,48,64.0,satisfied +19171,57055,Male,Loyal Customer,59,Personal Travel,Eco,2133,3,3,3,1,1,3,1,1,5,2,3,3,1,1,83,62.0,neutral or dissatisfied +19172,68375,Male,Loyal Customer,39,Business travel,Business,1045,2,2,2,2,4,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +19173,93839,Male,Loyal Customer,46,Business travel,Eco,391,5,5,5,5,5,5,5,5,1,1,4,5,5,5,173,150.0,satisfied +19174,125942,Female,Loyal Customer,68,Personal Travel,Eco,861,3,5,2,2,2,4,5,5,5,2,5,5,5,4,0,33.0,neutral or dissatisfied +19175,79111,Female,Loyal Customer,38,Personal Travel,Eco,356,2,5,2,4,3,2,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +19176,44426,Female,Loyal Customer,32,Business travel,Business,542,3,3,3,3,4,4,4,4,2,4,4,3,5,4,0,0.0,satisfied +19177,126251,Female,Loyal Customer,72,Business travel,Business,200,0,3,0,5,5,3,3,2,2,2,2,2,2,5,0,0.0,satisfied +19178,51087,Male,Loyal Customer,43,Personal Travel,Eco,156,2,5,2,4,4,2,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +19179,62251,Female,disloyal Customer,25,Business travel,Business,2565,1,0,0,4,3,0,2,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +19180,43869,Female,Loyal Customer,57,Business travel,Eco,199,4,3,3,3,4,5,4,4,4,4,4,3,4,1,0,0.0,satisfied +19181,97704,Male,Loyal Customer,56,Personal Travel,Eco,456,1,5,1,2,3,1,3,3,3,2,4,4,3,3,72,111.0,neutral or dissatisfied +19182,102362,Male,disloyal Customer,33,Business travel,Eco,397,2,1,2,3,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +19183,82107,Female,Loyal Customer,59,Personal Travel,Eco,1276,4,2,4,2,5,3,2,4,4,4,4,2,4,1,22,5.0,satisfied +19184,84170,Female,Loyal Customer,54,Business travel,Business,2790,3,2,3,3,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +19185,101686,Male,Loyal Customer,25,Business travel,Business,1500,2,2,2,2,2,2,2,2,2,4,2,4,1,2,53,44.0,neutral or dissatisfied +19186,37306,Male,Loyal Customer,35,Business travel,Business,2963,1,1,1,1,2,5,4,4,4,4,4,3,4,3,91,92.0,satisfied +19187,69074,Male,Loyal Customer,85,Business travel,Business,3732,3,4,4,4,3,3,3,3,3,3,3,3,3,3,1,0.0,neutral or dissatisfied +19188,97966,Male,Loyal Customer,55,Personal Travel,Eco,655,2,2,2,3,3,2,3,3,3,4,2,4,3,3,27,50.0,neutral or dissatisfied +19189,96910,Male,Loyal Customer,7,Personal Travel,Eco,488,2,5,5,3,3,5,3,3,5,3,4,4,4,3,47,41.0,neutral or dissatisfied +19190,63144,Female,Loyal Customer,54,Business travel,Business,2137,3,3,3,3,2,5,5,5,5,5,5,4,5,5,79,62.0,satisfied +19191,14935,Female,Loyal Customer,51,Business travel,Eco,554,4,5,5,5,2,1,1,4,4,4,4,4,4,2,7,0.0,satisfied +19192,31895,Male,Loyal Customer,26,Personal Travel,Eco,2762,2,0,2,3,5,2,1,5,4,4,4,4,1,5,0,0.0,neutral or dissatisfied +19193,100765,Male,Loyal Customer,38,Business travel,Business,1504,1,1,1,1,3,4,4,4,4,4,4,5,4,4,22,3.0,satisfied +19194,92553,Male,Loyal Customer,28,Personal Travel,Eco,1892,1,2,1,3,4,1,4,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +19195,83272,Female,disloyal Customer,41,Business travel,Business,479,4,4,4,4,1,3,5,1,2,3,3,4,4,1,3,3.0,neutral or dissatisfied +19196,99212,Male,Loyal Customer,35,Business travel,Business,3988,3,3,3,3,3,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +19197,114644,Male,Loyal Customer,43,Business travel,Eco,333,3,1,1,1,3,3,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +19198,129714,Female,disloyal Customer,20,Business travel,Eco,421,2,0,2,3,3,2,3,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +19199,43408,Female,Loyal Customer,47,Business travel,Eco Plus,463,4,2,2,2,1,1,5,4,4,4,4,2,4,2,0,0.0,satisfied +19200,82868,Female,disloyal Customer,20,Business travel,Eco,645,3,2,3,2,1,3,1,1,2,2,2,2,1,1,0,18.0,neutral or dissatisfied +19201,28908,Female,disloyal Customer,27,Business travel,Eco,937,2,2,2,2,1,2,1,1,5,1,3,5,5,1,0,0.0,neutral or dissatisfied +19202,69883,Male,Loyal Customer,56,Business travel,Eco,2248,2,4,2,4,2,2,2,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +19203,103171,Female,Loyal Customer,16,Business travel,Eco,491,4,5,5,5,4,4,5,4,3,4,5,4,2,4,0,0.0,satisfied +19204,81333,Female,disloyal Customer,26,Business travel,Business,1299,2,2,2,4,4,2,4,4,5,3,4,5,5,4,3,0.0,neutral or dissatisfied +19205,102182,Male,disloyal Customer,27,Business travel,Business,414,5,5,5,1,2,5,1,2,3,2,5,4,5,2,15,12.0,satisfied +19206,88803,Male,Loyal Customer,40,Business travel,Eco Plus,271,1,1,2,1,1,1,1,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +19207,33397,Female,Loyal Customer,41,Business travel,Eco,1417,3,1,1,1,3,3,3,3,3,2,2,5,2,3,0,0.0,neutral or dissatisfied +19208,111772,Male,Loyal Customer,60,Business travel,Business,1620,3,3,3,3,4,5,4,5,5,5,5,3,5,5,40,46.0,satisfied +19209,74369,Female,Loyal Customer,29,Business travel,Business,1431,5,5,5,5,3,4,3,3,3,3,5,5,4,3,110,93.0,satisfied +19210,11199,Female,Loyal Customer,67,Personal Travel,Eco,295,1,5,1,4,3,4,5,1,1,1,1,4,1,3,10,3.0,neutral or dissatisfied +19211,87994,Male,Loyal Customer,39,Business travel,Business,2694,4,4,4,4,4,5,5,4,4,4,4,3,4,3,18,29.0,satisfied +19212,61327,Male,Loyal Customer,53,Personal Travel,Eco Plus,967,0,5,0,1,3,0,3,3,5,4,4,3,4,3,0,0.0,satisfied +19213,32462,Female,disloyal Customer,36,Business travel,Eco,216,2,0,1,4,4,1,4,4,4,2,5,2,1,4,0,0.0,neutral or dissatisfied +19214,105239,Female,Loyal Customer,35,Personal Travel,Eco,377,2,5,2,3,4,2,5,4,4,5,5,5,5,4,17,11.0,neutral or dissatisfied +19215,11326,Female,Loyal Customer,33,Personal Travel,Eco,247,4,4,0,4,1,0,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +19216,128031,Female,Loyal Customer,28,Business travel,Business,1440,1,1,1,1,2,2,2,2,5,4,5,4,5,2,0,17.0,satisfied +19217,123214,Male,Loyal Customer,48,Personal Travel,Eco,631,4,5,4,3,1,4,1,1,5,3,5,2,4,1,0,0.0,neutral or dissatisfied +19218,45076,Male,Loyal Customer,43,Business travel,Eco,588,4,3,3,3,4,4,4,4,2,4,4,1,4,4,24,25.0,satisfied +19219,116415,Female,Loyal Customer,11,Personal Travel,Eco,404,2,4,2,3,2,2,2,2,2,1,4,1,3,2,6,0.0,neutral or dissatisfied +19220,74884,Female,Loyal Customer,41,Business travel,Business,2586,1,1,1,1,2,5,5,5,5,4,5,5,5,4,2,0.0,satisfied +19221,75527,Female,Loyal Customer,41,Business travel,Business,3619,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +19222,124947,Female,Loyal Customer,49,Business travel,Business,728,5,5,2,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +19223,65079,Female,Loyal Customer,9,Personal Travel,Eco,282,0,4,0,2,1,0,1,1,5,2,5,3,4,1,0,0.0,satisfied +19224,29021,Male,disloyal Customer,39,Business travel,Eco,578,2,5,2,3,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +19225,29274,Female,Loyal Customer,52,Business travel,Eco,873,1,5,5,5,1,1,1,3,4,2,2,1,3,1,295,314.0,neutral or dissatisfied +19226,12519,Male,disloyal Customer,11,Business travel,Eco,871,3,3,3,3,5,3,5,5,4,4,5,2,1,5,0,0.0,neutral or dissatisfied +19227,88022,Male,Loyal Customer,41,Business travel,Business,581,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +19228,33008,Male,Loyal Customer,21,Personal Travel,Eco,101,2,3,2,2,4,2,4,4,1,1,1,4,2,4,0,0.0,neutral or dissatisfied +19229,42493,Female,Loyal Customer,40,Business travel,Eco Plus,585,4,4,4,4,4,4,4,4,5,2,1,1,5,4,11,25.0,satisfied +19230,6920,Female,Loyal Customer,21,Personal Travel,Eco,287,2,2,2,3,5,2,5,5,2,1,4,4,3,5,0,0.0,neutral or dissatisfied +19231,32041,Male,Loyal Customer,50,Business travel,Business,101,1,4,1,1,1,5,2,4,4,4,5,3,4,4,4,16.0,satisfied +19232,80651,Male,Loyal Customer,29,Business travel,Business,2091,1,1,1,1,3,4,3,3,4,4,5,4,4,3,0,13.0,satisfied +19233,1785,Female,Loyal Customer,40,Business travel,Business,1744,3,3,3,3,5,4,5,4,4,4,4,4,4,3,63,63.0,satisfied +19234,52307,Female,disloyal Customer,33,Business travel,Eco,370,3,2,3,3,4,3,4,4,1,3,3,2,4,4,0,8.0,neutral or dissatisfied +19235,54824,Male,Loyal Customer,40,Business travel,Business,794,4,4,4,4,3,4,1,5,5,5,5,1,5,4,0,0.0,satisfied +19236,128752,Male,Loyal Customer,41,Business travel,Business,550,2,5,5,5,4,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +19237,95342,Female,Loyal Customer,50,Personal Travel,Eco,239,2,4,2,1,2,2,3,4,4,2,4,1,4,2,6,0.0,neutral or dissatisfied +19238,104785,Female,Loyal Customer,51,Business travel,Business,2187,2,2,2,2,3,5,4,4,4,4,4,5,4,5,20,16.0,satisfied +19239,127701,Female,Loyal Customer,23,Personal Travel,Eco,2133,1,1,1,2,4,1,4,4,3,5,3,1,3,4,10,0.0,neutral or dissatisfied +19240,102154,Male,Loyal Customer,54,Business travel,Business,3727,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +19241,98463,Male,Loyal Customer,42,Business travel,Business,210,0,4,0,5,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +19242,113069,Male,disloyal Customer,23,Business travel,Eco,479,1,4,1,3,2,1,2,2,4,5,5,4,5,2,33,25.0,neutral or dissatisfied +19243,36955,Female,Loyal Customer,20,Personal Travel,Business,759,4,4,4,4,2,4,2,2,3,4,4,4,3,2,0,0.0,satisfied +19244,86407,Female,disloyal Customer,26,Business travel,Eco,794,1,1,1,3,5,1,5,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +19245,76480,Female,Loyal Customer,33,Business travel,Business,3700,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +19246,48926,Female,Loyal Customer,38,Business travel,Business,337,2,2,2,2,4,3,1,4,4,4,4,4,4,5,0,0.0,satisfied +19247,84069,Male,disloyal Customer,24,Business travel,Eco,757,4,4,4,2,1,4,1,1,4,3,5,4,4,1,0,0.0,satisfied +19248,109131,Male,Loyal Customer,48,Business travel,Business,3085,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +19249,94742,Female,disloyal Customer,23,Business travel,Eco,148,2,2,2,4,4,2,4,4,2,3,3,4,3,4,15,23.0,neutral or dissatisfied +19250,50810,Male,Loyal Customer,23,Personal Travel,Eco,110,2,3,0,1,1,0,2,1,5,5,5,4,2,1,88,81.0,neutral or dissatisfied +19251,94211,Female,Loyal Customer,58,Business travel,Business,1841,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +19252,81482,Female,Loyal Customer,45,Business travel,Eco,528,2,5,5,5,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +19253,7106,Male,Loyal Customer,15,Personal Travel,Eco,273,2,4,2,2,1,2,1,1,4,2,4,4,4,1,9,11.0,neutral or dissatisfied +19254,106429,Male,Loyal Customer,29,Business travel,Business,551,4,4,4,4,5,5,5,5,5,4,5,5,4,5,7,9.0,satisfied +19255,94724,Male,disloyal Customer,33,Business travel,Eco,323,2,3,2,3,5,2,2,5,3,5,3,3,3,5,0,0.0,neutral or dissatisfied +19256,67455,Female,Loyal Customer,35,Personal Travel,Eco,641,3,4,3,1,5,3,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +19257,88577,Male,Loyal Customer,45,Personal Travel,Eco,545,4,5,4,5,4,4,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +19258,49059,Female,disloyal Customer,21,Business travel,Eco,109,4,5,5,4,3,5,3,3,3,4,1,4,5,3,34,35.0,neutral or dissatisfied +19259,92683,Female,Loyal Customer,45,Business travel,Business,507,3,4,4,4,2,4,4,3,3,3,3,1,3,4,38,25.0,neutral or dissatisfied +19260,106541,Male,Loyal Customer,60,Business travel,Business,1917,2,2,2,2,3,5,4,4,4,4,4,5,4,3,14,11.0,satisfied +19261,67111,Male,disloyal Customer,13,Business travel,Business,1121,2,4,2,4,4,2,4,4,2,3,4,4,3,4,10,0.0,neutral or dissatisfied +19262,10301,Female,disloyal Customer,23,Business travel,Business,163,0,0,0,1,4,0,4,4,4,4,4,5,4,4,0,6.0,satisfied +19263,2628,Female,Loyal Customer,51,Business travel,Eco Plus,227,4,2,2,2,4,4,4,4,4,4,4,1,4,1,0,3.0,neutral or dissatisfied +19264,3238,Male,Loyal Customer,59,Business travel,Business,2130,3,3,5,3,2,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +19265,127687,Female,Loyal Customer,44,Business travel,Business,2133,4,4,4,4,5,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +19266,76048,Female,Loyal Customer,45,Business travel,Business,2339,5,5,5,5,5,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +19267,98416,Male,disloyal Customer,40,Business travel,Business,410,5,5,5,4,1,5,1,1,3,5,5,5,5,1,0,0.0,satisfied +19268,95343,Female,Loyal Customer,46,Personal Travel,Eco,319,1,5,1,2,1,2,5,5,5,1,2,5,5,1,0,0.0,neutral or dissatisfied +19269,32119,Male,Loyal Customer,39,Business travel,Business,163,1,1,4,1,2,3,5,5,5,5,3,4,5,4,0,0.0,satisfied +19270,103276,Female,disloyal Customer,22,Business travel,Eco,888,1,1,1,2,3,1,3,3,3,4,4,3,4,3,2,0.0,neutral or dissatisfied +19271,95723,Male,Loyal Customer,49,Business travel,Business,3424,1,1,1,1,4,5,4,4,4,4,4,3,4,3,12,10.0,satisfied +19272,107651,Female,Loyal Customer,69,Personal Travel,Business,405,3,4,3,4,4,3,3,3,3,3,3,4,3,2,2,0.0,neutral or dissatisfied +19273,36307,Female,Loyal Customer,32,Business travel,Eco,187,4,2,2,2,4,4,4,4,4,4,3,1,1,4,14,49.0,satisfied +19274,57100,Male,Loyal Customer,26,Business travel,Business,1222,1,1,1,1,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +19275,3235,Female,Loyal Customer,9,Personal Travel,Business,479,5,5,5,1,5,5,5,5,4,5,1,3,2,5,27,51.0,satisfied +19276,84631,Male,Loyal Customer,44,Personal Travel,Eco,669,3,5,3,3,4,3,5,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +19277,37633,Female,Loyal Customer,13,Personal Travel,Eco,1056,4,5,4,2,3,4,3,3,3,2,4,3,5,3,89,89.0,neutral or dissatisfied +19278,89907,Male,Loyal Customer,59,Business travel,Business,2698,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +19279,104938,Female,disloyal Customer,29,Business travel,Business,1180,2,2,2,1,4,2,4,4,4,5,5,3,5,4,33,33.0,neutral or dissatisfied +19280,73825,Male,Loyal Customer,41,Personal Travel,Eco,1194,4,4,4,4,3,4,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +19281,66063,Female,Loyal Customer,30,Personal Travel,Eco,1055,3,4,3,4,3,3,3,3,5,2,4,3,4,3,13,9.0,neutral or dissatisfied +19282,50213,Female,Loyal Customer,25,Business travel,Business,308,1,2,2,2,1,1,1,1,3,1,4,3,4,1,11,17.0,neutral or dissatisfied +19283,68704,Male,Loyal Customer,24,Personal Travel,Eco,175,1,4,1,3,2,1,2,2,1,5,4,4,3,2,0,14.0,neutral or dissatisfied +19284,15149,Male,Loyal Customer,21,Personal Travel,Eco,912,2,5,3,1,5,3,5,5,4,2,4,5,5,5,63,52.0,neutral or dissatisfied +19285,80672,Male,Loyal Customer,15,Personal Travel,Eco,821,2,4,2,4,5,2,5,5,1,2,4,4,4,5,0,0.0,neutral or dissatisfied +19286,45075,Female,disloyal Customer,24,Business travel,Eco,265,0,2,0,1,2,0,2,2,5,5,2,5,5,2,5,22.0,satisfied +19287,68649,Female,Loyal Customer,60,Business travel,Eco,175,3,2,2,2,2,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +19288,39211,Female,Loyal Customer,51,Business travel,Business,67,3,3,3,3,2,4,4,4,4,4,5,5,4,4,10,0.0,satisfied +19289,31836,Female,Loyal Customer,28,Personal Travel,Eco,2762,3,1,3,4,3,1,1,2,2,3,4,1,3,1,0,3.0,neutral or dissatisfied +19290,37007,Male,Loyal Customer,31,Personal Travel,Eco,814,3,3,3,4,1,3,1,1,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +19291,51666,Female,Loyal Customer,41,Business travel,Business,3970,1,3,3,3,5,2,2,1,1,2,1,3,1,4,0,6.0,neutral or dissatisfied +19292,51033,Female,Loyal Customer,29,Personal Travel,Eco,266,0,3,0,4,1,0,1,1,3,4,3,4,4,1,0,1.0,satisfied +19293,57117,Male,Loyal Customer,52,Business travel,Business,1222,3,3,2,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +19294,81732,Male,disloyal Customer,24,Business travel,Eco,1501,2,2,2,5,4,2,5,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +19295,48081,Female,Loyal Customer,54,Business travel,Eco,192,5,1,1,1,3,3,3,5,5,5,5,1,5,2,0,0.0,satisfied +19296,61898,Female,Loyal Customer,49,Business travel,Business,550,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +19297,40859,Female,Loyal Customer,40,Personal Travel,Eco,599,2,5,3,5,5,3,1,5,4,3,4,5,2,5,26,18.0,neutral or dissatisfied +19298,80294,Female,Loyal Customer,53,Business travel,Business,3946,3,3,3,3,4,4,4,4,4,5,4,4,4,4,262,316.0,satisfied +19299,107513,Male,Loyal Customer,53,Business travel,Business,838,4,4,4,4,3,5,4,5,5,5,5,5,5,5,15,0.0,satisfied +19300,22995,Female,Loyal Customer,14,Personal Travel,Eco,817,2,4,2,4,1,2,1,1,4,1,5,2,5,1,2,7.0,neutral or dissatisfied +19301,127150,Male,Loyal Customer,19,Personal Travel,Eco,338,2,3,2,3,5,2,2,5,4,5,3,4,3,5,0,0.0,neutral or dissatisfied +19302,94323,Female,Loyal Customer,63,Business travel,Business,2906,3,3,3,3,2,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +19303,11212,Male,Loyal Customer,17,Personal Travel,Eco,458,4,4,4,4,2,4,2,2,3,2,4,3,5,2,4,9.0,neutral or dissatisfied +19304,97925,Male,Loyal Customer,26,Business travel,Business,483,2,1,2,1,2,2,2,2,1,3,4,4,3,2,10,14.0,neutral or dissatisfied +19305,128773,Male,Loyal Customer,51,Personal Travel,Eco,550,1,4,1,5,4,1,4,4,4,3,5,4,5,4,0,2.0,neutral or dissatisfied +19306,9765,Male,disloyal Customer,36,Business travel,Business,383,1,1,1,3,3,1,3,3,5,2,5,5,4,3,1,6.0,neutral or dissatisfied +19307,47527,Female,Loyal Customer,34,Personal Travel,Eco,599,3,5,3,3,4,3,4,4,1,5,1,3,1,4,23,20.0,neutral or dissatisfied +19308,91507,Male,Loyal Customer,53,Business travel,Business,1620,2,2,4,2,2,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +19309,97882,Female,disloyal Customer,24,Business travel,Business,616,4,4,4,1,1,4,1,1,5,3,5,3,4,1,0,0.0,satisfied +19310,53006,Female,disloyal Customer,55,Business travel,Eco,1208,2,3,3,5,2,3,2,2,1,2,3,2,4,2,5,3.0,neutral or dissatisfied +19311,110690,Female,Loyal Customer,56,Personal Travel,Eco,945,2,2,2,4,5,4,4,2,2,2,2,4,2,2,7,0.0,neutral or dissatisfied +19312,80524,Male,Loyal Customer,23,Business travel,Eco Plus,249,1,2,2,2,1,1,4,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +19313,82344,Male,disloyal Customer,28,Business travel,Business,453,5,5,5,1,3,4,2,3,4,2,4,5,4,3,13,8.0,satisfied +19314,43591,Male,Loyal Customer,47,Business travel,Eco,190,4,5,5,5,5,4,5,5,1,1,1,3,4,5,0,0.0,satisfied +19315,28822,Male,Loyal Customer,49,Business travel,Eco,671,5,4,5,4,5,5,5,5,4,3,4,2,5,5,62,55.0,satisfied +19316,75888,Female,disloyal Customer,20,Business travel,Business,597,5,0,5,1,3,5,3,3,4,4,5,5,5,3,0,10.0,satisfied +19317,39543,Female,disloyal Customer,20,Business travel,Eco,679,3,3,3,3,2,3,2,2,1,1,2,1,4,2,0,44.0,neutral or dissatisfied +19318,68052,Female,Loyal Customer,58,Business travel,Business,813,2,2,2,2,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +19319,47253,Male,Loyal Customer,31,Business travel,Business,590,2,2,2,2,3,3,3,3,5,5,5,4,5,3,2,13.0,satisfied +19320,10314,Male,disloyal Customer,37,Business travel,Business,163,2,3,3,4,3,3,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +19321,115710,Female,Loyal Customer,63,Business travel,Eco,342,4,3,3,3,4,3,3,4,4,4,4,4,4,3,4,0.0,neutral or dissatisfied +19322,19255,Male,Loyal Customer,24,Business travel,Business,1783,1,1,1,1,4,4,4,4,1,4,2,4,4,4,0,0.0,satisfied +19323,125,Male,Loyal Customer,21,Personal Travel,Eco,562,3,5,3,3,5,3,5,5,4,3,1,4,5,5,103,117.0,neutral or dissatisfied +19324,122072,Female,Loyal Customer,29,Personal Travel,Eco,83,5,5,5,3,1,5,1,1,5,5,4,5,4,1,0,0.0,satisfied +19325,29701,Male,Loyal Customer,51,Personal Travel,Eco,1542,5,4,5,2,4,5,4,4,4,3,5,3,5,4,0,0.0,satisfied +19326,12563,Male,Loyal Customer,66,Personal Travel,Eco,788,1,2,1,4,2,1,2,2,2,5,3,4,3,2,1,0.0,neutral or dissatisfied +19327,10264,Female,Loyal Customer,13,Personal Travel,Business,201,1,1,1,3,3,1,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +19328,55022,Male,Loyal Customer,57,Business travel,Business,1635,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +19329,101862,Female,Loyal Customer,22,Business travel,Business,519,5,5,5,5,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +19330,58791,Male,Loyal Customer,12,Business travel,Business,2800,4,4,4,4,4,4,4,4,2,3,3,1,4,4,24,18.0,neutral or dissatisfied +19331,68503,Male,Loyal Customer,63,Personal Travel,Eco,1303,3,4,3,4,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +19332,123096,Male,Loyal Customer,59,Business travel,Business,600,3,3,3,3,3,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +19333,48662,Female,Loyal Customer,59,Business travel,Business,373,2,2,2,2,4,4,5,5,5,5,5,5,5,5,16,4.0,satisfied +19334,91315,Female,Loyal Customer,23,Business travel,Business,3482,4,5,4,4,4,4,4,5,4,5,4,4,5,4,299,304.0,satisfied +19335,110171,Male,Loyal Customer,32,Personal Travel,Eco,1072,1,2,1,4,3,1,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +19336,110026,Female,Loyal Customer,23,Personal Travel,Eco,1142,2,4,2,5,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +19337,100553,Female,Loyal Customer,55,Personal Travel,Eco Plus,580,3,4,2,2,2,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +19338,861,Male,disloyal Customer,20,Business travel,Eco,113,2,0,2,1,4,2,2,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +19339,42837,Female,Loyal Customer,32,Business travel,Business,1864,3,3,3,3,4,5,4,4,2,5,3,3,3,4,0,0.0,satisfied +19340,48538,Female,disloyal Customer,35,Business travel,Eco,959,4,4,4,3,3,4,1,3,4,1,4,2,2,3,10,2.0,neutral or dissatisfied +19341,43809,Male,Loyal Customer,50,Business travel,Business,1960,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +19342,87306,Female,Loyal Customer,46,Personal Travel,Eco,577,1,4,1,2,2,5,5,5,5,1,5,5,5,4,31,31.0,neutral or dissatisfied +19343,8548,Male,Loyal Customer,44,Business travel,Business,2982,3,3,3,3,4,4,5,5,5,5,4,3,5,4,2,17.0,satisfied +19344,22722,Male,Loyal Customer,53,Business travel,Business,2949,0,0,0,4,5,4,4,1,1,1,1,4,1,5,0,0.0,satisfied +19345,65039,Female,Loyal Customer,46,Personal Travel,Eco,247,3,5,3,4,4,4,5,5,5,3,5,3,5,5,13,10.0,neutral or dissatisfied +19346,81406,Male,Loyal Customer,22,Personal Travel,Business,448,2,4,2,1,3,2,5,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +19347,71909,Male,Loyal Customer,55,Personal Travel,Eco,1723,4,3,4,3,5,4,5,5,1,1,1,2,2,5,11,27.0,neutral or dissatisfied +19348,8813,Male,disloyal Customer,26,Business travel,Eco,122,2,2,2,3,4,2,4,4,3,2,3,4,3,4,3,6.0,neutral or dissatisfied +19349,89740,Male,Loyal Customer,49,Personal Travel,Eco,1069,4,5,4,1,5,4,5,5,5,4,4,4,5,5,4,0.0,neutral or dissatisfied +19350,107876,Female,Loyal Customer,19,Personal Travel,Eco,228,2,1,2,4,2,2,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +19351,27255,Male,Loyal Customer,45,Business travel,Business,954,3,3,4,3,2,3,3,3,3,3,3,4,3,3,0,12.0,neutral or dissatisfied +19352,94719,Male,Loyal Customer,20,Business travel,Eco,239,2,3,3,3,2,2,2,2,3,2,3,2,3,2,1,0.0,neutral or dissatisfied +19353,89758,Female,Loyal Customer,66,Personal Travel,Eco,1089,2,3,2,3,2,1,4,4,5,3,4,4,3,4,179,187.0,neutral or dissatisfied +19354,93194,Female,disloyal Customer,25,Business travel,Business,896,2,0,2,5,1,2,2,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +19355,121016,Female,Loyal Customer,35,Personal Travel,Eco,992,3,4,3,3,5,3,5,5,3,5,4,5,4,5,13,23.0,neutral or dissatisfied +19356,100110,Male,Loyal Customer,31,Business travel,Business,717,3,3,3,3,5,4,5,5,5,3,4,4,4,5,0,0.0,satisfied +19357,56559,Male,Loyal Customer,48,Business travel,Business,937,2,2,2,2,4,5,4,4,4,4,4,4,4,4,17,13.0,satisfied +19358,85825,Female,Loyal Customer,16,Personal Travel,Eco,666,3,5,3,3,3,3,3,3,4,2,2,3,4,3,37,10.0,neutral or dissatisfied +19359,62314,Female,Loyal Customer,38,Business travel,Business,414,3,3,5,3,3,4,2,5,5,5,5,3,5,4,0,5.0,satisfied +19360,109708,Female,Loyal Customer,36,Business travel,Business,468,5,5,5,5,2,4,5,4,4,4,4,5,4,3,3,0.0,satisfied +19361,6897,Male,disloyal Customer,30,Business travel,Eco,265,2,3,2,2,5,2,5,5,3,3,2,1,3,5,0,0.0,neutral or dissatisfied +19362,46558,Male,Loyal Customer,46,Business travel,Eco,125,5,1,1,1,5,5,5,5,4,4,2,4,1,5,12,0.0,satisfied +19363,34228,Female,Loyal Customer,27,Business travel,Eco Plus,1046,4,5,5,5,4,5,4,4,2,4,2,4,2,4,32,30.0,satisfied +19364,41479,Female,Loyal Customer,27,Business travel,Business,3157,2,2,2,2,3,3,3,3,2,2,1,2,4,3,0,0.0,satisfied +19365,102932,Female,Loyal Customer,52,Personal Travel,Eco,436,1,4,1,1,5,4,5,5,5,1,5,3,5,3,8,6.0,neutral or dissatisfied +19366,19531,Male,Loyal Customer,38,Business travel,Business,3578,5,5,1,5,2,4,1,5,5,4,5,2,5,4,68,81.0,satisfied +19367,61567,Male,Loyal Customer,21,Personal Travel,Eco,599,1,3,0,1,1,0,1,1,5,3,1,5,1,1,1,0.0,neutral or dissatisfied +19368,75547,Male,Loyal Customer,51,Business travel,Business,3578,1,1,1,1,2,4,5,5,5,5,5,4,5,5,6,0.0,satisfied +19369,55900,Female,Loyal Customer,10,Business travel,Business,2226,3,1,5,1,3,3,3,3,2,5,4,4,3,3,0,3.0,neutral or dissatisfied +19370,61085,Male,Loyal Customer,17,Personal Travel,Eco,1703,2,2,2,3,5,2,5,5,2,3,3,3,3,5,10,0.0,neutral or dissatisfied +19371,28242,Female,Loyal Customer,70,Personal Travel,Eco,1009,0,5,0,1,4,4,4,2,2,0,3,5,2,4,0,0.0,satisfied +19372,48310,Female,Loyal Customer,63,Personal Travel,Eco,1499,4,5,3,3,5,3,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +19373,49245,Female,disloyal Customer,37,Business travel,Eco,250,2,0,2,2,2,2,2,2,5,3,2,5,5,2,39,33.0,neutral or dissatisfied +19374,120032,Female,Loyal Customer,36,Personal Travel,Eco Plus,328,1,0,1,3,1,1,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +19375,29020,Male,disloyal Customer,24,Business travel,Eco,650,3,2,3,4,5,3,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +19376,73597,Male,Loyal Customer,55,Business travel,Business,204,2,1,2,2,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +19377,32383,Female,Loyal Customer,62,Business travel,Business,1642,0,4,0,5,5,1,1,5,5,5,5,3,5,4,0,2.0,satisfied +19378,33920,Male,Loyal Customer,66,Personal Travel,Eco,636,3,5,3,4,1,3,1,1,5,2,5,4,5,1,18,26.0,neutral or dissatisfied +19379,70123,Male,disloyal Customer,24,Business travel,Eco,550,2,1,2,3,4,2,4,4,4,5,4,1,3,4,35,31.0,neutral or dissatisfied +19380,6330,Male,Loyal Customer,47,Business travel,Business,1741,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,30.0,satisfied +19381,106601,Female,Loyal Customer,37,Business travel,Business,3491,1,1,5,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +19382,115420,Male,Loyal Customer,68,Business travel,Business,404,2,5,3,5,1,4,3,2,2,2,2,1,2,4,18,10.0,neutral or dissatisfied +19383,120211,Male,Loyal Customer,53,Business travel,Eco,1430,2,4,4,4,2,2,2,2,2,4,4,3,4,2,23,31.0,neutral or dissatisfied +19384,90393,Male,Loyal Customer,65,Personal Travel,Business,250,2,4,0,3,2,4,4,3,3,0,3,5,3,5,0,0.0,neutral or dissatisfied +19385,24345,Male,Loyal Customer,38,Personal Travel,Eco,634,1,5,1,4,4,1,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +19386,126656,Female,Loyal Customer,59,Personal Travel,Eco,602,2,4,2,2,3,4,4,4,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +19387,125954,Male,Loyal Customer,33,Business travel,Business,1013,4,4,4,4,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +19388,6662,Female,Loyal Customer,47,Personal Travel,Business,438,1,4,5,4,3,3,4,1,1,5,4,1,1,3,70,66.0,neutral or dissatisfied +19389,65706,Male,Loyal Customer,29,Business travel,Business,936,4,4,4,4,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +19390,45789,Male,Loyal Customer,48,Business travel,Eco,411,5,2,2,2,4,5,4,4,5,3,1,2,2,4,20,10.0,satisfied +19391,111890,Male,disloyal Customer,67,Business travel,Business,228,4,4,4,2,1,4,1,1,1,1,5,2,4,1,0,0.0,satisfied +19392,90397,Male,Loyal Customer,29,Personal Travel,Business,545,1,3,1,3,1,4,4,2,1,3,4,4,4,4,92,150.0,neutral or dissatisfied +19393,33067,Female,Loyal Customer,15,Personal Travel,Eco,201,3,5,3,3,4,3,4,4,3,2,4,5,2,4,0,0.0,neutral or dissatisfied +19394,30428,Male,Loyal Customer,26,Business travel,Eco Plus,872,5,2,2,2,5,5,5,5,1,5,2,1,1,5,0,2.0,satisfied +19395,128450,Male,Loyal Customer,49,Personal Travel,Eco,304,4,4,4,4,3,4,3,3,3,2,4,4,5,3,0,0.0,satisfied +19396,105526,Male,Loyal Customer,49,Business travel,Business,2018,4,4,4,4,3,5,4,5,5,5,5,4,5,3,35,27.0,satisfied +19397,80555,Male,Loyal Customer,54,Business travel,Business,1747,3,2,3,3,3,5,5,4,4,4,4,3,4,5,29,4.0,satisfied +19398,75709,Female,Loyal Customer,72,Business travel,Business,1674,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +19399,45625,Male,Loyal Customer,41,Business travel,Eco,313,3,1,1,1,2,3,2,2,3,5,4,1,4,2,0,4.0,neutral or dissatisfied +19400,27843,Male,Loyal Customer,37,Personal Travel,Eco,1448,3,1,3,4,2,3,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +19401,42488,Female,disloyal Customer,24,Business travel,Business,585,4,3,4,4,2,4,2,2,3,3,4,3,5,2,7,34.0,satisfied +19402,90716,Female,Loyal Customer,42,Business travel,Business,404,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +19403,127610,Male,Loyal Customer,53,Business travel,Business,1773,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +19404,24043,Female,Loyal Customer,29,Personal Travel,Eco,562,3,4,2,4,5,2,4,5,4,2,4,4,4,5,9,23.0,neutral or dissatisfied +19405,34396,Female,Loyal Customer,25,Business travel,Business,1867,2,2,2,2,2,2,2,2,1,1,2,1,3,2,0,0.0,neutral or dissatisfied +19406,40729,Female,Loyal Customer,43,Business travel,Eco,588,2,1,2,1,3,3,5,2,2,2,2,2,2,3,0,0.0,satisfied +19407,121532,Female,Loyal Customer,43,Business travel,Business,2381,2,5,5,5,3,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +19408,86586,Male,Loyal Customer,55,Personal Travel,Eco,1269,4,4,4,2,2,4,2,2,4,5,5,3,5,2,0,0.0,satisfied +19409,37072,Male,disloyal Customer,36,Business travel,Business,1072,3,3,3,4,5,3,5,5,1,5,1,4,2,5,0,0.0,neutral or dissatisfied +19410,16151,Female,Loyal Customer,39,Business travel,Eco,212,5,4,2,4,5,5,5,2,3,1,4,5,1,5,276,262.0,satisfied +19411,124771,Female,Loyal Customer,48,Business travel,Business,2820,5,5,5,5,5,4,4,5,5,5,5,3,5,5,73,55.0,satisfied +19412,71047,Female,Loyal Customer,41,Business travel,Business,3945,1,1,1,1,4,4,5,5,5,5,5,3,5,3,14,0.0,satisfied +19413,80478,Female,Loyal Customer,36,Personal Travel,Eco,1299,3,4,2,3,4,2,4,4,5,5,5,3,5,4,2,3.0,neutral or dissatisfied +19414,34576,Female,Loyal Customer,22,Business travel,Business,1598,4,4,5,4,5,5,5,5,4,5,3,4,1,5,42,20.0,satisfied +19415,72951,Male,Loyal Customer,50,Business travel,Business,944,1,1,4,1,2,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +19416,42425,Female,Loyal Customer,17,Personal Travel,Eco Plus,550,4,0,4,3,1,4,5,1,4,5,4,4,4,1,21,37.0,neutral or dissatisfied +19417,105333,Female,Loyal Customer,34,Business travel,Business,528,5,5,5,5,5,5,4,4,4,4,4,5,4,3,5,0.0,satisfied +19418,15207,Male,Loyal Customer,8,Personal Travel,Business,529,3,4,3,1,1,3,1,1,4,5,5,3,4,1,9,5.0,neutral or dissatisfied +19419,114256,Female,Loyal Customer,47,Business travel,Eco,453,4,2,3,2,1,3,3,4,4,4,4,5,4,2,10,0.0,satisfied +19420,41645,Female,Loyal Customer,33,Business travel,Business,2150,5,5,5,5,1,2,4,5,5,5,5,2,5,1,0,0.0,satisfied +19421,9394,Female,Loyal Customer,46,Personal Travel,Eco,372,2,5,2,3,2,5,5,3,3,2,3,1,3,2,0,2.0,neutral or dissatisfied +19422,68588,Male,Loyal Customer,31,Personal Travel,Eco,1616,3,4,3,3,2,3,1,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +19423,31980,Female,disloyal Customer,45,Business travel,Business,101,2,2,2,2,5,2,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +19424,92353,Female,Loyal Customer,33,Personal Travel,Eco,2556,1,4,1,5,1,5,5,5,5,5,5,5,5,5,0,12.0,neutral or dissatisfied +19425,65767,Male,disloyal Customer,20,Business travel,Business,936,4,4,4,3,4,4,4,4,3,2,5,4,5,4,1,0.0,satisfied +19426,97282,Male,Loyal Customer,26,Personal Travel,Business,872,1,1,1,2,4,1,4,4,3,2,1,2,2,4,22,38.0,neutral or dissatisfied +19427,76632,Male,Loyal Customer,52,Business travel,Business,2731,4,4,4,4,5,1,3,5,5,5,3,5,5,2,2,0.0,satisfied +19428,8710,Male,Loyal Customer,53,Personal Travel,Eco,280,2,4,2,4,2,2,1,2,3,4,5,4,1,2,2,0.0,neutral or dissatisfied +19429,123533,Male,Loyal Customer,52,Business travel,Eco Plus,2125,2,3,4,3,2,2,2,2,3,5,2,4,4,2,4,0.0,neutral or dissatisfied +19430,16756,Male,Loyal Customer,26,Business travel,Business,569,5,5,5,5,4,4,4,4,4,5,4,4,3,4,1,3.0,satisfied +19431,31324,Female,Loyal Customer,42,Business travel,Business,3167,2,3,3,3,1,2,2,2,2,2,2,4,2,4,99,113.0,neutral or dissatisfied +19432,69431,Male,Loyal Customer,36,Personal Travel,Eco,1096,2,1,2,3,2,2,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +19433,26859,Female,Loyal Customer,46,Business travel,Eco Plus,224,4,3,3,3,3,4,1,4,4,4,4,1,4,4,0,14.0,satisfied +19434,56578,Male,disloyal Customer,24,Business travel,Eco,997,2,2,2,3,1,2,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +19435,50860,Female,Loyal Customer,15,Personal Travel,Eco,262,2,5,2,3,1,2,4,1,5,2,4,1,3,1,0,0.0,neutral or dissatisfied +19436,11176,Female,Loyal Customer,21,Personal Travel,Eco,201,3,4,3,3,3,3,1,3,3,3,2,1,4,3,0,0.0,neutral or dissatisfied +19437,129214,Female,Loyal Customer,31,Personal Travel,Eco Plus,2442,2,1,2,4,4,2,3,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +19438,68363,Female,Loyal Customer,41,Business travel,Business,2072,2,3,3,3,1,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +19439,89378,Male,Loyal Customer,43,Business travel,Business,3547,0,5,0,4,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +19440,72309,Female,Loyal Customer,40,Business travel,Business,3526,3,3,3,3,3,4,4,4,4,4,4,3,4,5,8,0.0,satisfied +19441,11570,Female,disloyal Customer,24,Business travel,Eco,657,4,0,5,3,1,5,1,1,5,5,5,5,4,1,15,9.0,neutral or dissatisfied +19442,64815,Female,Loyal Customer,68,Business travel,Eco,224,3,3,5,3,4,3,3,3,3,3,3,3,3,4,13,6.0,neutral or dissatisfied +19443,103827,Male,Loyal Customer,48,Business travel,Business,2001,3,3,3,3,3,4,4,2,2,2,2,4,2,4,2,0.0,satisfied +19444,24146,Male,Loyal Customer,38,Business travel,Business,2173,3,5,5,5,5,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +19445,5895,Female,Loyal Customer,36,Business travel,Eco,173,1,4,4,4,1,1,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +19446,67331,Female,Loyal Customer,60,Business travel,Business,1471,4,4,4,4,4,5,4,4,4,5,4,4,4,3,22,10.0,satisfied +19447,45580,Female,Loyal Customer,39,Personal Travel,Business,313,4,5,4,3,4,5,4,3,3,4,3,5,3,5,62,58.0,neutral or dissatisfied +19448,7849,Male,Loyal Customer,30,Business travel,Business,1005,2,2,2,2,2,2,2,2,3,5,2,3,2,2,54,35.0,neutral or dissatisfied +19449,119325,Male,Loyal Customer,32,Personal Travel,Eco,214,4,0,4,1,4,4,4,4,3,5,5,3,5,4,0,2.0,neutral or dissatisfied +19450,42750,Male,Loyal Customer,28,Personal Travel,Business,607,2,4,2,4,4,2,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +19451,79167,Male,Loyal Customer,16,Personal Travel,Business,2422,2,5,2,4,2,3,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +19452,98570,Male,Loyal Customer,54,Business travel,Business,834,1,1,5,1,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +19453,123066,Female,disloyal Customer,17,Business travel,Eco,631,1,3,1,3,2,1,1,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +19454,94547,Male,disloyal Customer,44,Business travel,Eco,239,2,0,2,4,3,2,3,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +19455,98475,Male,Loyal Customer,40,Personal Travel,Eco Plus,210,4,4,4,4,1,4,1,1,3,5,3,4,4,1,0,0.0,satisfied +19456,65003,Male,Loyal Customer,71,Business travel,Business,3540,2,3,3,3,2,4,4,4,4,4,2,2,4,3,28,21.0,neutral or dissatisfied +19457,99376,Female,Loyal Customer,69,Personal Travel,Business,337,2,5,2,3,2,5,5,2,2,2,2,5,2,5,0,17.0,neutral or dissatisfied +19458,80142,Male,Loyal Customer,46,Business travel,Business,2586,5,5,5,5,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +19459,77859,Male,Loyal Customer,47,Personal Travel,Eco Plus,689,3,5,3,1,4,3,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +19460,31896,Male,Loyal Customer,34,Personal Travel,Eco,2762,1,0,1,4,4,1,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +19461,117932,Male,Loyal Customer,67,Business travel,Eco,365,3,1,1,1,3,3,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +19462,87847,Male,Loyal Customer,16,Personal Travel,Eco,214,1,2,1,4,3,1,5,3,4,3,4,4,3,3,80,85.0,neutral or dissatisfied +19463,82854,Male,Loyal Customer,48,Business travel,Business,594,4,4,4,4,3,5,5,5,5,4,5,3,5,4,7,17.0,satisfied +19464,118963,Male,Loyal Customer,33,Business travel,Business,3012,3,3,3,3,3,3,3,3,4,5,3,3,4,3,5,0.0,neutral or dissatisfied +19465,62401,Male,Loyal Customer,40,Personal Travel,Eco,2704,5,1,5,4,3,5,3,3,1,5,3,2,3,3,21,0.0,satisfied +19466,68365,Female,Loyal Customer,33,Personal Travel,Eco,2072,2,4,2,4,1,2,1,1,4,4,3,5,4,1,15,0.0,neutral or dissatisfied +19467,61599,Female,Loyal Customer,54,Business travel,Business,1346,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +19468,67887,Male,Loyal Customer,65,Personal Travel,Eco,1235,1,5,1,1,4,1,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +19469,70008,Female,Loyal Customer,57,Business travel,Business,236,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +19470,128923,Female,Loyal Customer,52,Business travel,Business,414,3,3,3,3,2,5,4,5,5,5,5,4,5,3,6,0.0,satisfied +19471,77933,Male,disloyal Customer,57,Business travel,Business,106,4,4,4,5,3,4,3,3,3,4,4,4,4,3,0,0.0,satisfied +19472,80615,Male,Loyal Customer,60,Business travel,Business,236,3,3,3,3,5,5,5,5,5,5,5,5,5,4,3,0.0,satisfied +19473,128399,Male,Loyal Customer,47,Business travel,Business,2357,4,2,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +19474,74245,Male,disloyal Customer,24,Business travel,Business,1810,0,4,0,1,0,2,2,5,5,5,4,2,3,2,236,202.0,satisfied +19475,18667,Male,Loyal Customer,41,Personal Travel,Eco,190,5,5,5,3,4,5,4,4,3,2,5,5,4,4,0,0.0,satisfied +19476,119348,Female,Loyal Customer,49,Business travel,Business,214,2,2,2,2,4,4,4,5,5,5,4,3,5,5,0,0.0,satisfied +19477,29657,Female,Loyal Customer,33,Personal Travel,Eco,909,1,3,1,3,1,1,1,1,2,1,5,2,2,1,0,0.0,neutral or dissatisfied +19478,97562,Female,Loyal Customer,43,Business travel,Business,448,1,1,1,1,2,5,5,5,5,5,5,5,5,4,28,28.0,satisfied +19479,58574,Female,Loyal Customer,48,Business travel,Business,3612,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +19480,26553,Female,Loyal Customer,64,Personal Travel,Eco Plus,990,2,3,2,4,4,2,5,1,1,2,1,2,1,5,4,0.0,neutral or dissatisfied +19481,113018,Female,Loyal Customer,54,Business travel,Business,479,4,4,4,4,2,5,4,5,5,5,5,4,5,4,34,21.0,satisfied +19482,119369,Female,Loyal Customer,32,Business travel,Business,399,1,1,1,1,4,4,4,4,3,3,5,4,5,4,0,25.0,satisfied +19483,22739,Female,Loyal Customer,55,Business travel,Business,2314,5,5,5,5,3,1,1,4,4,4,4,3,4,2,9,19.0,satisfied +19484,52354,Female,Loyal Customer,68,Personal Travel,Eco,370,5,1,5,3,5,2,2,4,4,5,4,3,4,1,0,0.0,satisfied +19485,103063,Male,Loyal Customer,68,Business travel,Eco,266,5,2,2,2,5,5,5,5,4,5,3,5,3,5,0,0.0,satisfied +19486,58800,Female,Loyal Customer,40,Business travel,Eco,605,5,2,2,2,5,5,5,5,2,2,3,3,5,5,7,1.0,satisfied +19487,76218,Female,Loyal Customer,52,Business travel,Business,1399,4,4,4,4,3,4,4,3,3,4,3,3,3,3,20,14.0,satisfied +19488,86505,Female,Loyal Customer,38,Personal Travel,Eco,762,3,4,3,1,1,3,1,1,3,4,5,5,4,1,1,0.0,neutral or dissatisfied +19489,31492,Female,Loyal Customer,47,Business travel,Business,2268,1,1,1,1,5,4,3,5,5,5,5,5,5,4,0,0.0,satisfied +19490,55412,Male,Loyal Customer,67,Personal Travel,Eco,1558,2,4,2,4,5,2,5,5,3,3,4,5,4,5,27,13.0,neutral or dissatisfied +19491,98180,Female,Loyal Customer,45,Business travel,Business,3474,0,1,1,5,5,5,4,4,4,1,1,5,4,4,14,12.0,satisfied +19492,62439,Female,Loyal Customer,44,Business travel,Business,1943,2,2,2,2,3,5,5,4,4,4,4,3,4,5,7,0.0,satisfied +19493,35175,Male,disloyal Customer,23,Business travel,Eco,950,2,2,2,5,4,2,1,4,3,3,4,5,1,4,0,0.0,neutral or dissatisfied +19494,3811,Female,Loyal Customer,40,Business travel,Business,3611,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +19495,52152,Male,Loyal Customer,66,Personal Travel,Business,451,1,5,4,1,2,3,4,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +19496,98167,Female,Loyal Customer,50,Business travel,Business,562,2,2,2,2,3,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +19497,57725,Female,disloyal Customer,29,Business travel,Eco,1016,3,3,3,4,4,3,4,4,2,1,4,4,3,4,9,11.0,neutral or dissatisfied +19498,32478,Female,disloyal Customer,21,Business travel,Eco,216,1,2,1,2,4,1,4,4,1,5,3,4,3,4,0,,neutral or dissatisfied +19499,106703,Female,Loyal Customer,28,Personal Travel,Eco,516,2,4,2,1,5,2,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +19500,42525,Female,disloyal Customer,45,Business travel,Eco,328,0,0,0,4,1,0,1,1,3,3,4,1,2,1,0,0.0,satisfied +19501,121965,Female,Loyal Customer,36,Business travel,Business,2391,2,1,1,1,5,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +19502,225,Male,Loyal Customer,29,Personal Travel,Eco,290,4,5,4,2,3,4,3,3,4,3,4,3,2,3,0,0.0,neutral or dissatisfied +19503,66791,Male,Loyal Customer,60,Personal Travel,Eco,3784,3,5,3,3,3,4,4,3,3,3,5,4,3,4,9,20.0,neutral or dissatisfied +19504,27326,Male,Loyal Customer,45,Business travel,Business,2237,1,1,1,1,1,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +19505,50172,Male,Loyal Customer,58,Business travel,Business,266,2,2,2,2,2,3,3,2,2,2,2,4,2,4,99,88.0,neutral or dissatisfied +19506,4912,Male,Loyal Customer,50,Business travel,Business,3459,1,1,1,1,3,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +19507,29860,Male,Loyal Customer,43,Business travel,Eco,571,4,4,4,4,4,4,4,4,4,1,1,5,3,4,6,16.0,satisfied +19508,31985,Female,Loyal Customer,39,Personal Travel,Business,163,3,5,3,2,3,4,5,5,5,3,5,3,5,3,2,7.0,neutral or dissatisfied +19509,128356,Female,Loyal Customer,49,Business travel,Business,1955,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +19510,95496,Female,disloyal Customer,27,Business travel,Eco Plus,562,2,2,2,3,1,2,1,1,2,3,4,3,3,1,1,0.0,neutral or dissatisfied +19511,112344,Female,Loyal Customer,53,Business travel,Business,846,2,2,2,2,5,4,4,4,4,4,4,4,4,4,4,3.0,satisfied +19512,122369,Female,Loyal Customer,25,Business travel,Business,3400,3,3,4,3,3,3,3,3,5,2,4,3,4,3,5,0.0,satisfied +19513,65804,Female,Loyal Customer,26,Business travel,Eco,1389,4,2,2,2,4,4,2,4,2,4,3,1,2,4,0,0.0,neutral or dissatisfied +19514,57876,Male,Loyal Customer,65,Personal Travel,Business,305,4,5,4,2,5,1,5,3,3,4,1,2,3,5,18,7.0,neutral or dissatisfied +19515,93820,Male,Loyal Customer,59,Business travel,Business,2639,2,2,5,2,4,4,5,4,4,4,4,4,4,3,90,80.0,satisfied +19516,75464,Male,Loyal Customer,37,Personal Travel,Eco,2585,1,5,1,3,2,1,1,2,5,2,5,5,3,2,4,0.0,neutral or dissatisfied +19517,92821,Female,Loyal Customer,12,Business travel,Business,1587,5,5,5,5,4,4,4,4,5,3,3,4,5,4,0,0.0,satisfied +19518,128253,Male,Loyal Customer,40,Business travel,Business,2250,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,4.0,satisfied +19519,117348,Male,disloyal Customer,27,Business travel,Business,296,2,2,2,5,2,2,2,2,4,2,5,4,5,2,8,18.0,neutral or dissatisfied +19520,74017,Female,Loyal Customer,52,Business travel,Business,1471,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +19521,62285,Female,Loyal Customer,46,Business travel,Business,414,5,5,5,5,2,5,5,5,5,5,5,3,5,3,48,39.0,satisfied +19522,101781,Male,Loyal Customer,49,Business travel,Business,1521,5,5,5,5,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +19523,23968,Male,disloyal Customer,22,Business travel,Eco,596,3,5,3,2,3,3,3,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +19524,14923,Male,Loyal Customer,30,Business travel,Eco Plus,315,5,5,5,5,5,5,5,5,1,1,2,3,5,5,0,0.0,satisfied +19525,22570,Female,Loyal Customer,55,Business travel,Business,300,5,5,3,5,4,5,4,4,4,4,4,2,4,3,0,0.0,satisfied +19526,50725,Female,Loyal Customer,62,Personal Travel,Eco,109,3,5,3,1,5,5,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +19527,90584,Male,Loyal Customer,26,Business travel,Business,2020,3,3,3,3,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +19528,61462,Female,Loyal Customer,24,Business travel,Business,2419,1,5,5,5,1,1,1,1,3,1,2,2,4,1,13,0.0,neutral or dissatisfied +19529,119584,Female,Loyal Customer,30,Business travel,Business,2276,4,4,4,4,4,5,4,4,3,5,5,3,4,4,0,0.0,satisfied +19530,47392,Male,disloyal Customer,24,Business travel,Eco,501,3,3,3,2,5,3,5,5,5,2,4,5,1,5,0,0.0,neutral or dissatisfied +19531,74313,Male,disloyal Customer,20,Business travel,Eco,1235,3,3,3,2,4,3,1,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +19532,28632,Female,Loyal Customer,25,Business travel,Business,2614,3,3,3,3,4,4,4,4,4,3,5,3,2,4,0,0.0,satisfied +19533,39709,Male,Loyal Customer,51,Business travel,Eco,320,4,2,2,2,4,4,4,4,4,3,5,5,1,4,0,6.0,satisfied +19534,97869,Male,Loyal Customer,51,Business travel,Business,2520,3,3,3,3,4,5,4,3,3,4,3,5,3,3,4,2.0,satisfied +19535,13184,Male,Loyal Customer,57,Business travel,Business,419,4,4,3,4,5,2,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +19536,48582,Male,Loyal Customer,58,Personal Travel,Eco,853,2,4,3,4,3,3,3,3,4,3,5,5,4,3,0,6.0,neutral or dissatisfied +19537,1540,Male,Loyal Customer,39,Business travel,Business,3505,4,5,2,2,3,3,4,4,4,4,4,3,4,1,78,69.0,neutral or dissatisfied +19538,125880,Male,disloyal Customer,19,Business travel,Eco,1013,2,2,2,4,4,2,4,4,5,1,5,5,5,4,3,0.0,satisfied +19539,70954,Female,Loyal Customer,25,Business travel,Eco Plus,612,2,3,3,3,2,3,2,2,3,3,4,4,3,2,6,0.0,neutral or dissatisfied +19540,503,Male,Loyal Customer,38,Business travel,Business,3598,4,5,4,4,5,4,4,5,5,5,4,4,5,3,0,4.0,satisfied +19541,11893,Female,Loyal Customer,57,Business travel,Business,3528,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +19542,105598,Female,disloyal Customer,20,Business travel,Eco,663,1,0,1,3,3,1,4,3,2,1,4,2,4,3,13,9.0,neutral or dissatisfied +19543,83615,Female,Loyal Customer,25,Business travel,Business,3377,4,4,4,4,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +19544,113621,Female,Loyal Customer,67,Personal Travel,Eco,223,1,5,1,3,5,3,5,4,4,1,4,1,4,2,5,8.0,neutral or dissatisfied +19545,32328,Female,Loyal Customer,37,Business travel,Eco,216,4,4,4,4,4,4,4,4,5,4,1,4,2,4,0,0.0,satisfied +19546,64267,Female,Loyal Customer,43,Business travel,Business,2575,1,1,1,1,2,4,5,5,5,5,5,5,5,5,44,54.0,satisfied +19547,111126,Male,Loyal Customer,22,Business travel,Business,1173,1,1,1,1,5,5,5,5,3,4,4,5,5,5,28,24.0,satisfied +19548,48301,Female,Loyal Customer,44,Business travel,Business,1499,4,4,3,4,4,3,3,5,5,5,5,2,5,5,3,14.0,satisfied +19549,10883,Female,Loyal Customer,46,Business travel,Business,2650,4,4,4,4,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +19550,42591,Female,Loyal Customer,35,Business travel,Business,1201,1,3,3,3,5,4,4,1,1,1,1,4,1,3,14,14.0,neutral or dissatisfied +19551,34476,Female,disloyal Customer,36,Business travel,Eco,266,4,4,4,3,3,4,3,3,2,4,4,4,3,3,2,0.0,neutral or dissatisfied +19552,98808,Male,disloyal Customer,25,Business travel,Business,763,1,0,1,2,1,1,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +19553,54614,Male,Loyal Customer,47,Business travel,Business,1508,3,3,3,3,2,2,2,4,4,4,4,5,4,4,25,18.0,satisfied +19554,10736,Female,Loyal Customer,56,Business travel,Business,2103,0,5,0,4,2,5,4,1,1,1,1,5,1,3,0,0.0,satisfied +19555,85442,Female,Loyal Customer,59,Business travel,Business,1572,3,3,3,3,2,4,4,3,3,3,3,2,3,1,9,3.0,neutral or dissatisfied +19556,13929,Male,disloyal Customer,26,Business travel,Eco,192,2,2,2,2,5,2,5,5,4,3,2,3,1,5,0,9.0,neutral or dissatisfied +19557,78713,Male,disloyal Customer,24,Business travel,Eco,528,4,0,4,1,5,4,5,5,3,2,4,3,4,5,2,0.0,satisfied +19558,75765,Male,Loyal Customer,18,Personal Travel,Eco,868,2,3,2,4,1,2,1,1,2,5,3,2,1,1,0,0.0,neutral or dissatisfied +19559,107415,Female,Loyal Customer,40,Business travel,Business,717,3,4,3,4,1,3,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +19560,116262,Female,Loyal Customer,68,Personal Travel,Eco,296,2,4,2,1,2,4,5,4,4,2,5,5,4,5,1,0.0,neutral or dissatisfied +19561,6771,Female,disloyal Customer,37,Business travel,Business,235,2,2,2,3,2,2,2,2,3,3,5,3,4,2,43,40.0,neutral or dissatisfied +19562,124413,Female,Loyal Customer,47,Business travel,Business,1917,3,3,3,3,2,4,5,3,3,2,3,5,3,3,0,0.0,satisfied +19563,37120,Male,Loyal Customer,52,Business travel,Business,3502,5,5,5,5,4,2,4,5,5,5,5,1,5,2,0,7.0,satisfied +19564,128542,Female,Loyal Customer,55,Business travel,Business,3607,1,1,5,1,4,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +19565,31044,Male,Loyal Customer,42,Business travel,Business,2396,3,3,3,3,4,4,3,3,3,3,3,2,3,2,0,0.0,satisfied +19566,71666,Male,Loyal Customer,27,Personal Travel,Eco,1012,4,4,4,1,5,4,5,5,4,2,2,3,1,5,63,84.0,neutral or dissatisfied +19567,43187,Female,Loyal Customer,59,Personal Travel,Eco,282,3,4,3,2,2,4,5,2,2,3,2,3,2,4,3,3.0,neutral or dissatisfied +19568,78408,Female,Loyal Customer,58,Business travel,Business,3663,5,5,1,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +19569,87826,Male,Loyal Customer,67,Business travel,Business,1558,1,2,2,2,4,1,2,2,2,3,1,3,2,4,12,4.0,neutral or dissatisfied +19570,89545,Male,disloyal Customer,23,Business travel,Eco,950,2,2,2,3,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +19571,29787,Female,disloyal Customer,32,Business travel,Eco,261,2,0,2,2,4,2,4,4,4,5,2,2,4,4,0,0.0,neutral or dissatisfied +19572,112640,Female,Loyal Customer,34,Personal Travel,Eco Plus,602,3,5,2,2,3,2,3,3,4,2,4,5,5,3,11,0.0,neutral or dissatisfied +19573,13104,Male,Loyal Customer,25,Business travel,Business,595,5,5,5,5,4,4,4,4,5,4,3,2,4,4,0,0.0,satisfied +19574,89120,Female,Loyal Customer,56,Business travel,Business,2139,2,2,2,2,2,3,5,5,5,5,5,5,5,4,3,0.0,satisfied +19575,34921,Male,disloyal Customer,25,Business travel,Eco,187,2,4,2,3,2,2,2,3,2,4,4,2,4,2,129,142.0,neutral or dissatisfied +19576,56836,Female,Loyal Customer,58,Business travel,Business,1605,4,4,4,4,2,4,5,4,4,4,4,4,4,5,44,17.0,satisfied +19577,9847,Female,Loyal Customer,48,Business travel,Business,3497,3,3,3,3,3,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +19578,92157,Male,Loyal Customer,48,Personal Travel,Eco Plus,1532,2,3,2,2,3,2,3,3,4,1,3,3,2,3,0,0.0,neutral or dissatisfied +19579,75459,Male,Loyal Customer,46,Personal Travel,Eco,2342,1,1,1,2,4,1,2,4,1,2,3,4,3,4,0,0.0,neutral or dissatisfied +19580,30098,Male,Loyal Customer,30,Personal Travel,Eco,253,2,1,2,4,1,2,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +19581,111867,Female,disloyal Customer,11,Business travel,Eco,804,3,3,3,1,5,3,2,5,4,4,4,5,4,5,8,0.0,neutral or dissatisfied +19582,38889,Female,Loyal Customer,52,Business travel,Business,205,0,5,0,2,5,5,4,5,5,5,5,4,5,4,0,3.0,satisfied +19583,109636,Female,Loyal Customer,46,Business travel,Business,3874,1,1,1,1,4,3,3,5,5,5,4,3,4,3,312,296.0,satisfied +19584,124051,Female,Loyal Customer,7,Personal Travel,Business,2153,3,4,3,3,1,3,3,1,4,2,3,5,4,1,0,6.0,neutral or dissatisfied +19585,96754,Female,Loyal Customer,59,Business travel,Business,2163,3,1,3,3,2,4,4,5,5,5,5,5,5,3,6,0.0,satisfied +19586,87362,Female,Loyal Customer,38,Business travel,Business,425,4,4,4,4,5,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +19587,126952,Female,disloyal Customer,37,Business travel,Business,325,2,2,2,3,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +19588,47916,Female,Loyal Customer,14,Personal Travel,Eco,834,4,5,5,4,4,5,4,4,5,4,4,3,4,4,0,18.0,satisfied +19589,54352,Male,Loyal Customer,22,Business travel,Business,1235,1,1,1,1,4,4,4,4,4,3,4,1,4,4,0,0.0,satisfied +19590,115801,Female,disloyal Customer,39,Business travel,Eco,372,1,1,1,2,2,1,2,2,1,5,1,4,1,2,18,12.0,neutral or dissatisfied +19591,73815,Female,Loyal Customer,58,Personal Travel,Eco Plus,204,2,3,2,4,1,3,1,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +19592,122743,Male,Loyal Customer,47,Business travel,Eco,651,2,2,2,2,2,2,2,2,2,1,2,2,2,2,0,5.0,neutral or dissatisfied +19593,108172,Male,Loyal Customer,36,Personal Travel,Eco,990,4,5,4,3,2,4,2,2,5,5,4,5,5,2,5,0.0,neutral or dissatisfied +19594,88783,Male,Loyal Customer,58,Business travel,Business,3714,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,1.0,satisfied +19595,56041,Female,Loyal Customer,35,Business travel,Business,2586,3,2,2,2,3,3,3,4,5,3,2,3,4,3,0,0.0,neutral or dissatisfied +19596,120561,Male,Loyal Customer,60,Personal Travel,Eco,2176,2,3,2,4,1,2,1,1,1,4,3,4,3,1,58,33.0,neutral or dissatisfied +19597,12982,Female,Loyal Customer,36,Business travel,Eco,374,4,4,4,4,4,4,4,4,3,1,5,3,2,4,24,20.0,satisfied +19598,127072,Female,Loyal Customer,45,Business travel,Business,1583,4,2,2,2,4,3,3,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +19599,104451,Male,Loyal Customer,47,Personal Travel,Business,1015,1,2,1,2,1,3,3,3,3,1,3,4,3,4,24,39.0,neutral or dissatisfied +19600,26196,Male,disloyal Customer,27,Business travel,Eco,581,4,1,4,4,3,4,3,3,1,3,3,3,4,3,20,21.0,neutral or dissatisfied +19601,75135,Female,Loyal Customer,42,Business travel,Business,1723,3,3,3,3,2,4,4,2,2,3,2,3,2,5,19,0.0,satisfied +19602,53742,Female,Loyal Customer,46,Business travel,Eco Plus,1190,5,1,1,1,4,5,5,5,5,5,5,5,5,2,0,0.0,satisfied +19603,9292,Female,Loyal Customer,7,Personal Travel,Eco,1157,3,4,3,2,5,3,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +19604,22259,Male,Loyal Customer,38,Business travel,Business,2695,5,5,2,5,4,5,4,4,4,4,4,5,4,2,0,2.0,satisfied +19605,128059,Female,Loyal Customer,61,Personal Travel,Eco Plus,735,2,4,2,4,4,3,3,1,1,2,5,2,1,4,0,9.0,neutral or dissatisfied +19606,18283,Male,Loyal Customer,10,Personal Travel,Eco Plus,179,2,4,2,2,5,2,5,5,5,4,4,4,4,5,63,82.0,neutral or dissatisfied +19607,6286,Female,Loyal Customer,53,Personal Travel,Eco,693,3,2,3,4,1,4,4,5,5,3,5,3,5,4,0,1.0,neutral or dissatisfied +19608,21664,Female,Loyal Customer,48,Business travel,Business,746,3,3,3,3,4,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +19609,13679,Male,disloyal Customer,24,Business travel,Eco,954,3,2,2,5,5,2,5,5,3,3,3,1,1,5,0,2.0,neutral or dissatisfied +19610,69835,Female,disloyal Customer,57,Business travel,Eco,945,4,4,4,4,3,4,1,3,2,4,4,1,4,3,37,12.0,neutral or dissatisfied +19611,118296,Female,Loyal Customer,59,Business travel,Business,2718,4,4,4,4,3,4,4,4,4,4,4,5,4,3,25,9.0,satisfied +19612,91661,Female,Loyal Customer,18,Personal Travel,Eco,1184,1,5,1,4,5,1,4,5,5,5,5,4,4,5,0,12.0,neutral or dissatisfied +19613,96977,Female,Loyal Customer,52,Business travel,Eco,359,2,5,5,5,2,3,3,2,2,2,2,4,2,2,6,0.0,neutral or dissatisfied +19614,41250,Male,Loyal Customer,46,Business travel,Business,2837,1,1,3,1,3,2,2,3,3,4,3,2,3,3,7,17.0,satisfied +19615,40192,Male,Loyal Customer,29,Business travel,Business,2387,3,3,4,3,3,3,3,3,4,1,2,2,5,3,0,0.0,satisfied +19616,78911,Male,disloyal Customer,21,Business travel,Business,930,5,0,5,3,5,5,5,5,3,2,5,4,4,5,47,38.0,satisfied +19617,43164,Male,Loyal Customer,30,Business travel,Business,2013,4,4,4,4,4,4,4,4,2,1,2,4,2,4,0,0.0,satisfied +19618,111620,Male,disloyal Customer,23,Business travel,Eco,1014,4,4,4,4,3,4,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +19619,28802,Female,Loyal Customer,22,Business travel,Eco,954,3,2,2,2,3,4,4,3,5,4,5,2,2,3,0,0.0,satisfied +19620,21158,Male,Loyal Customer,32,Business travel,Eco,954,2,1,1,1,2,2,2,2,4,1,3,3,2,2,15,12.0,neutral or dissatisfied +19621,57923,Female,Loyal Customer,21,Personal Travel,Eco,305,3,5,3,4,1,3,1,1,3,4,5,5,5,1,18,7.0,neutral or dissatisfied +19622,15068,Male,Loyal Customer,10,Personal Travel,Eco,488,2,0,2,2,4,2,2,4,4,2,5,5,4,4,11,11.0,neutral or dissatisfied +19623,78356,Male,Loyal Customer,38,Business travel,Business,1927,1,5,5,5,3,3,3,1,1,1,1,2,1,1,5,0.0,neutral or dissatisfied +19624,78201,Female,Loyal Customer,67,Business travel,Eco,192,2,1,1,1,4,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +19625,119393,Male,Loyal Customer,53,Business travel,Business,1614,1,0,0,2,4,3,3,5,5,0,5,1,5,4,0,0.0,neutral or dissatisfied +19626,121874,Male,Loyal Customer,41,Business travel,Business,3467,1,1,1,1,3,3,3,4,4,4,4,2,4,5,1,0.0,satisfied +19627,1478,Male,Loyal Customer,28,Personal Travel,Eco Plus,772,4,3,4,4,1,4,1,1,5,3,3,5,4,1,8,0.0,neutral or dissatisfied +19628,28788,Male,Loyal Customer,44,Business travel,Business,3866,3,5,5,5,3,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +19629,64430,Male,Loyal Customer,34,Business travel,Business,1506,3,3,3,3,4,4,4,3,3,4,3,5,3,3,27,26.0,satisfied +19630,82766,Male,Loyal Customer,65,Personal Travel,Eco,409,2,4,2,3,4,2,4,4,3,1,2,5,3,4,7,0.0,neutral or dissatisfied +19631,16785,Male,Loyal Customer,20,Personal Travel,Eco,569,3,3,3,2,2,3,2,2,2,5,2,4,3,2,0,0.0,neutral or dissatisfied +19632,119892,Male,Loyal Customer,39,Business travel,Business,3904,5,5,1,5,4,4,5,4,4,4,4,5,4,4,0,9.0,satisfied +19633,94294,Female,Loyal Customer,45,Business travel,Business,3770,0,0,0,3,3,4,4,2,2,2,2,3,2,3,7,10.0,satisfied +19634,106270,Male,Loyal Customer,29,Business travel,Business,689,1,3,3,3,1,1,1,1,2,2,3,1,3,1,0,4.0,neutral or dissatisfied +19635,121474,Female,Loyal Customer,47,Personal Travel,Eco,331,4,5,4,4,5,4,5,5,5,4,5,4,5,3,6,0.0,neutral or dissatisfied +19636,98303,Female,Loyal Customer,27,Business travel,Eco Plus,1136,3,4,4,4,3,3,3,3,3,5,4,2,4,3,2,10.0,neutral or dissatisfied +19637,59934,Male,Loyal Customer,45,Business travel,Business,2402,1,1,1,1,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +19638,119058,Female,Loyal Customer,24,Personal Travel,Eco,2279,2,5,2,2,2,2,2,2,3,4,4,3,4,2,74,65.0,neutral or dissatisfied +19639,97825,Female,Loyal Customer,35,Business travel,Business,395,4,4,4,4,4,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +19640,91997,Male,Loyal Customer,8,Personal Travel,Eco,236,2,5,0,1,4,0,5,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +19641,129252,Female,Loyal Customer,47,Personal Travel,Eco,1504,3,5,4,1,5,3,4,2,2,4,1,3,2,5,0,0.0,neutral or dissatisfied +19642,56608,Female,Loyal Customer,48,Business travel,Business,3256,4,4,4,4,4,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +19643,35564,Male,Loyal Customer,44,Business travel,Eco Plus,1053,4,5,5,5,4,4,4,4,5,5,2,5,3,4,4,0.0,satisfied +19644,129837,Male,Loyal Customer,66,Personal Travel,Eco,337,2,4,2,3,2,5,5,5,2,4,5,5,4,5,199,213.0,neutral or dissatisfied +19645,65309,Female,disloyal Customer,42,Business travel,Business,432,2,2,2,3,3,2,3,3,4,4,4,4,4,3,6,0.0,neutral or dissatisfied +19646,36235,Female,Loyal Customer,59,Personal Travel,Eco,280,2,1,2,3,3,3,3,5,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +19647,32281,Male,Loyal Customer,33,Business travel,Business,2632,0,5,0,4,1,1,1,1,4,1,1,4,1,1,0,0.0,satisfied +19648,123548,Male,Loyal Customer,27,Business travel,Business,1773,3,3,3,3,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +19649,31272,Male,disloyal Customer,26,Business travel,Eco,533,1,3,1,3,4,1,4,4,4,4,4,3,4,4,55,56.0,neutral or dissatisfied +19650,23549,Male,Loyal Customer,43,Business travel,Business,1511,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,30.0,satisfied +19651,50698,Male,Loyal Customer,29,Personal Travel,Eco,110,3,2,0,2,2,0,2,2,3,1,3,1,3,2,12,0.0,neutral or dissatisfied +19652,101404,Male,Loyal Customer,50,Personal Travel,Eco,486,4,4,2,2,5,2,5,5,4,3,4,4,4,5,34,17.0,satisfied +19653,42179,Female,disloyal Customer,21,Business travel,Eco,817,4,4,4,3,4,4,4,4,3,4,2,1,5,4,84,109.0,satisfied +19654,31659,Male,Loyal Customer,59,Business travel,Business,846,3,1,4,1,5,3,2,3,3,3,3,1,3,3,3,8.0,neutral or dissatisfied +19655,6541,Female,disloyal Customer,20,Business travel,Business,207,1,4,1,3,3,1,3,3,1,5,3,1,4,3,0,4.0,neutral or dissatisfied +19656,22346,Female,Loyal Customer,48,Business travel,Business,2545,1,1,1,1,3,1,5,5,5,5,5,1,5,2,13,13.0,satisfied +19657,76364,Female,disloyal Customer,24,Business travel,Eco,931,4,4,4,1,1,4,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +19658,96811,Male,disloyal Customer,44,Business travel,Business,781,3,3,3,1,3,3,3,3,4,5,4,4,5,3,19,7.0,satisfied +19659,15471,Female,Loyal Customer,66,Personal Travel,Eco,164,4,4,4,5,3,4,4,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +19660,109537,Female,Loyal Customer,60,Personal Travel,Eco,861,2,3,2,4,1,4,3,3,3,2,3,3,3,4,23,38.0,neutral or dissatisfied +19661,51235,Female,Loyal Customer,60,Business travel,Eco Plus,372,5,5,4,5,5,3,3,5,5,5,5,1,5,5,38,31.0,satisfied +19662,24506,Male,Loyal Customer,36,Personal Travel,Eco,547,3,1,2,2,5,2,5,5,3,1,3,2,2,5,15,21.0,neutral or dissatisfied +19663,10916,Female,disloyal Customer,21,Business travel,Eco,308,5,2,5,1,2,5,2,2,4,3,5,3,5,2,0,0.0,satisfied +19664,108362,Female,Loyal Customer,40,Business travel,Eco,250,1,2,1,2,1,1,1,1,2,3,3,2,4,1,20,9.0,neutral or dissatisfied +19665,25790,Male,disloyal Customer,23,Business travel,Eco,762,2,2,2,3,4,2,4,4,4,3,5,2,1,4,12,41.0,neutral or dissatisfied +19666,18830,Female,disloyal Customer,50,Business travel,Eco,500,4,0,4,3,5,4,5,5,3,1,3,1,5,5,61,64.0,neutral or dissatisfied +19667,82850,Female,Loyal Customer,26,Business travel,Business,3117,1,5,5,5,1,1,1,1,3,2,3,4,3,1,31,67.0,neutral or dissatisfied +19668,80946,Male,Loyal Customer,31,Personal Travel,Eco,352,3,4,4,2,3,4,3,3,4,3,4,3,5,3,0,6.0,neutral or dissatisfied +19669,9494,Female,Loyal Customer,43,Business travel,Business,3267,3,3,3,3,1,3,3,3,3,3,3,4,3,4,29,22.0,neutral or dissatisfied +19670,104561,Female,disloyal Customer,24,Business travel,Eco,369,3,0,3,2,4,3,3,4,3,4,4,5,4,4,69,71.0,neutral or dissatisfied +19671,7357,Male,Loyal Customer,15,Personal Travel,Eco,864,3,5,3,5,1,3,1,1,3,4,4,3,4,1,40,70.0,neutral or dissatisfied +19672,96707,Male,Loyal Customer,39,Business travel,Business,696,2,2,3,2,2,5,4,4,4,4,4,5,4,4,9,13.0,satisfied +19673,117165,Male,Loyal Customer,38,Personal Travel,Eco,647,3,4,2,5,4,2,4,4,1,2,2,1,4,4,0,0.0,neutral or dissatisfied +19674,110605,Female,Loyal Customer,47,Business travel,Business,1790,5,5,5,5,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +19675,53100,Female,Loyal Customer,50,Business travel,Business,1628,2,2,2,2,3,4,4,5,5,5,5,4,5,1,22,2.0,satisfied +19676,67815,Male,disloyal Customer,29,Business travel,Eco,1064,4,3,3,4,5,3,5,5,2,5,3,2,3,5,29,29.0,neutral or dissatisfied +19677,56738,Male,Loyal Customer,50,Personal Travel,Eco,937,3,5,3,2,1,3,1,1,1,1,5,4,4,1,0,6.0,neutral or dissatisfied +19678,11975,Male,Loyal Customer,53,Business travel,Business,643,5,5,5,5,4,5,4,5,5,5,5,3,5,3,2,0.0,satisfied +19679,108964,Male,disloyal Customer,37,Business travel,Eco,255,3,5,2,3,1,2,1,1,1,4,4,1,1,1,37,28.0,neutral or dissatisfied +19680,96958,Female,Loyal Customer,57,Business travel,Business,3132,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +19681,95613,Female,Loyal Customer,46,Business travel,Business,1773,1,4,4,4,2,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +19682,38779,Female,Loyal Customer,44,Business travel,Business,2145,3,3,3,3,4,1,1,5,5,5,5,1,5,4,0,0.0,satisfied +19683,82237,Female,Loyal Customer,40,Personal Travel,Eco,405,3,4,3,3,1,3,1,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +19684,15299,Female,Loyal Customer,34,Business travel,Business,612,2,2,2,2,1,2,1,4,4,4,4,1,4,5,0,0.0,satisfied +19685,23818,Male,Loyal Customer,23,Personal Travel,Eco,438,4,3,4,3,2,4,2,2,2,4,3,3,5,2,128,121.0,neutral or dissatisfied +19686,57456,Male,Loyal Customer,51,Business travel,Business,3104,2,2,3,2,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +19687,125378,Female,Loyal Customer,54,Business travel,Business,1440,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +19688,8622,Male,disloyal Customer,38,Business travel,Business,304,3,3,3,3,4,3,4,4,5,4,5,5,5,4,87,96.0,neutral or dissatisfied +19689,53302,Male,Loyal Customer,40,Business travel,Eco,811,4,1,4,1,4,4,4,4,4,5,4,5,2,4,2,0.0,satisfied +19690,94462,Male,Loyal Customer,41,Business travel,Business,192,2,2,2,2,3,4,4,4,4,4,4,3,4,5,0,4.0,satisfied +19691,28853,Male,Loyal Customer,25,Business travel,Business,2635,5,5,5,5,3,3,3,3,5,5,2,4,2,3,0,11.0,satisfied +19692,18655,Female,Loyal Customer,60,Personal Travel,Eco,201,4,1,4,3,4,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +19693,88279,Male,Loyal Customer,53,Business travel,Eco,404,2,2,2,2,2,2,2,2,3,1,3,3,4,2,7,2.0,neutral or dissatisfied +19694,118618,Male,Loyal Customer,51,Business travel,Business,2246,2,4,4,4,3,4,3,2,2,2,2,4,2,1,9,11.0,neutral or dissatisfied +19695,62013,Female,Loyal Customer,27,Business travel,Business,2586,3,3,3,3,5,4,5,5,5,3,4,4,5,5,0,0.0,satisfied +19696,92873,Male,Loyal Customer,58,Business travel,Business,3412,0,4,0,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +19697,3457,Male,Loyal Customer,55,Business travel,Business,240,2,1,1,1,2,3,3,2,2,2,2,1,2,3,11,6.0,neutral or dissatisfied +19698,98453,Male,Loyal Customer,49,Business travel,Business,210,5,5,5,5,4,5,5,4,4,4,4,5,4,4,23,14.0,satisfied +19699,12985,Male,disloyal Customer,36,Business travel,Eco,438,3,0,3,2,1,3,2,1,2,5,3,3,1,1,1,16.0,neutral or dissatisfied +19700,67163,Male,Loyal Customer,7,Personal Travel,Eco,985,5,4,5,4,4,5,4,4,3,2,5,3,4,4,0,0.0,satisfied +19701,22402,Male,Loyal Customer,48,Business travel,Eco,83,2,5,5,5,2,2,2,2,1,4,2,2,2,2,0,0.0,neutral or dissatisfied +19702,63867,Male,Loyal Customer,47,Business travel,Business,2519,3,3,3,3,4,5,4,5,5,5,5,5,5,5,83,65.0,satisfied +19703,123951,Male,Loyal Customer,35,Business travel,Eco Plus,544,3,1,1,1,3,3,3,3,3,4,3,3,4,3,0,18.0,neutral or dissatisfied +19704,60351,Male,Loyal Customer,51,Personal Travel,Eco,1024,1,5,1,1,2,1,2,2,3,5,3,4,1,2,0,5.0,neutral or dissatisfied +19705,106041,Male,Loyal Customer,60,Business travel,Business,2575,2,2,2,2,3,4,4,4,4,4,4,4,4,3,20,29.0,satisfied +19706,91950,Female,Loyal Customer,68,Personal Travel,Eco,2586,2,4,2,4,2,4,2,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +19707,120895,Female,Loyal Customer,27,Business travel,Business,3984,2,2,2,2,5,5,5,5,4,2,5,3,5,5,0,0.0,satisfied +19708,94297,Male,Loyal Customer,47,Business travel,Business,1635,1,1,4,1,4,5,5,4,4,4,4,4,4,4,6,11.0,satisfied +19709,111850,Male,Loyal Customer,52,Business travel,Business,3947,3,3,3,3,5,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +19710,45663,Female,Loyal Customer,37,Business travel,Eco Plus,230,4,2,2,2,4,4,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +19711,101807,Female,Loyal Customer,39,Business travel,Business,1521,5,5,5,5,2,4,4,4,4,4,4,5,4,5,32,23.0,satisfied +19712,34668,Female,Loyal Customer,52,Business travel,Business,1841,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +19713,49607,Male,disloyal Customer,24,Business travel,Eco,156,1,1,1,3,4,1,4,4,4,2,4,3,3,4,48,47.0,neutral or dissatisfied +19714,129226,Male,Loyal Customer,32,Business travel,Business,1504,3,3,3,3,3,3,3,3,3,2,4,4,4,3,3,0.0,satisfied +19715,123496,Male,Loyal Customer,44,Business travel,Business,2125,4,4,4,4,5,5,4,3,3,3,3,5,3,4,5,0.0,satisfied +19716,24137,Female,Loyal Customer,72,Business travel,Business,134,5,5,5,5,3,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +19717,57056,Female,Loyal Customer,10,Personal Travel,Eco,2133,2,2,2,2,4,2,4,4,4,1,3,4,3,4,1,0.0,neutral or dissatisfied +19718,42152,Female,Loyal Customer,57,Personal Travel,Business,550,3,1,3,2,3,3,3,3,3,1,2,3,1,3,131,126.0,neutral or dissatisfied +19719,10556,Female,Loyal Customer,39,Business travel,Business,1533,2,2,2,2,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +19720,109534,Female,disloyal Customer,20,Business travel,Eco,966,2,2,2,1,4,2,4,4,2,3,2,3,2,4,32,15.0,neutral or dissatisfied +19721,22933,Female,Loyal Customer,36,Business travel,Business,3007,1,1,1,1,1,2,4,4,4,4,4,2,4,5,0,0.0,satisfied +19722,95423,Female,disloyal Customer,36,Business travel,Business,319,3,4,4,2,5,4,5,5,4,2,5,3,4,5,43,33.0,neutral or dissatisfied +19723,21449,Female,disloyal Customer,39,Business travel,Business,164,2,2,2,4,5,2,5,5,2,2,4,1,4,5,0,0.0,neutral or dissatisfied +19724,573,Female,Loyal Customer,27,Business travel,Business,89,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +19725,84544,Male,Loyal Customer,19,Personal Travel,Eco,2556,1,3,2,4,1,2,1,1,3,5,3,1,4,1,3,5.0,neutral or dissatisfied +19726,33760,Male,disloyal Customer,53,Personal Travel,Eco,266,2,4,2,5,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +19727,30071,Male,Loyal Customer,23,Personal Travel,Eco,95,5,2,0,4,2,0,2,2,4,5,4,4,4,2,0,11.0,satisfied +19728,124346,Male,Loyal Customer,54,Business travel,Business,1037,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,2.0,satisfied +19729,58274,Male,Loyal Customer,22,Business travel,Eco,678,3,3,1,3,3,3,1,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +19730,38943,Female,Loyal Customer,31,Personal Travel,Eco,205,3,5,3,4,2,3,2,2,2,3,3,1,4,2,0,7.0,neutral or dissatisfied +19731,64210,Female,Loyal Customer,33,Personal Travel,Eco Plus,853,2,5,2,4,5,2,5,5,4,2,5,3,5,5,35,35.0,neutral or dissatisfied +19732,102265,Male,Loyal Customer,62,Business travel,Business,3430,3,5,5,5,3,4,3,3,3,3,3,1,3,2,11,0.0,neutral or dissatisfied +19733,93934,Male,Loyal Customer,42,Business travel,Eco,507,3,2,2,2,3,3,3,3,4,2,2,3,3,3,23,22.0,neutral or dissatisfied +19734,129162,Male,disloyal Customer,15,Business travel,Eco,954,3,2,2,3,3,2,4,3,1,5,4,3,3,3,13,0.0,neutral or dissatisfied +19735,29007,Female,disloyal Customer,26,Business travel,Eco,987,2,2,2,4,1,2,1,1,3,1,2,3,5,1,2,0.0,neutral or dissatisfied +19736,81906,Female,Loyal Customer,37,Personal Travel,Eco,680,2,5,2,1,2,2,2,2,3,2,4,5,5,2,5,3.0,neutral or dissatisfied +19737,73462,Male,Loyal Customer,49,Personal Travel,Eco,1120,2,4,2,2,3,2,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +19738,97878,Male,Loyal Customer,33,Business travel,Business,1972,2,2,2,2,5,4,5,5,4,3,4,5,4,5,0,0.0,satisfied +19739,16983,Male,Loyal Customer,19,Business travel,Eco,610,4,2,2,2,4,4,4,4,4,4,1,2,5,4,0,0.0,satisfied +19740,24646,Female,Loyal Customer,21,Personal Travel,Eco Plus,526,4,4,4,3,2,4,2,2,3,5,4,3,5,2,0,0.0,satisfied +19741,49712,Male,Loyal Customer,42,Business travel,Business,3967,3,3,3,3,1,5,2,5,5,5,5,1,5,2,0,0.0,satisfied +19742,122493,Male,Loyal Customer,53,Business travel,Business,3690,3,3,3,3,2,5,5,3,3,3,3,5,3,3,3,0.0,satisfied +19743,26612,Female,Loyal Customer,49,Business travel,Business,2477,5,5,5,5,3,5,1,4,4,4,4,1,4,2,0,0.0,satisfied +19744,44663,Female,Loyal Customer,43,Business travel,Business,2500,1,3,3,3,4,1,2,3,3,3,1,1,3,1,0,0.0,neutral or dissatisfied +19745,100554,Female,Loyal Customer,12,Personal Travel,Eco Plus,580,4,5,4,4,3,4,3,3,3,4,4,5,5,3,14,8.0,neutral or dissatisfied +19746,41109,Male,Loyal Customer,38,Business travel,Business,1752,2,1,1,1,1,3,4,2,2,2,2,2,2,4,7,14.0,neutral or dissatisfied +19747,105041,Female,Loyal Customer,70,Personal Travel,Eco,255,2,4,0,3,4,5,5,4,4,0,4,4,4,4,21,19.0,neutral or dissatisfied +19748,24998,Female,Loyal Customer,62,Personal Travel,Eco,692,3,5,2,2,3,5,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +19749,125292,Female,Loyal Customer,19,Business travel,Business,678,1,1,1,1,1,1,1,1,3,5,2,4,3,1,0,0.0,neutral or dissatisfied +19750,118613,Male,Loyal Customer,60,Business travel,Business,1706,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +19751,65766,Female,Loyal Customer,43,Business travel,Eco Plus,936,2,3,3,3,4,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +19752,17407,Male,Loyal Customer,27,Business travel,Eco,376,4,2,2,2,4,4,4,4,2,2,5,1,2,4,4,6.0,satisfied +19753,67479,Female,Loyal Customer,46,Personal Travel,Eco,641,2,5,2,4,3,2,4,2,2,2,2,5,2,2,8,9.0,neutral or dissatisfied +19754,78500,Female,Loyal Customer,61,Business travel,Business,126,5,5,5,5,3,2,5,5,5,4,3,5,5,5,0,0.0,satisfied +19755,31871,Female,Loyal Customer,50,Business travel,Business,4983,5,4,5,5,5,1,5,3,2,4,3,5,5,5,0,0.0,satisfied +19756,24799,Female,Loyal Customer,57,Personal Travel,Eco Plus,447,3,4,3,1,5,5,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +19757,25598,Male,Loyal Customer,53,Personal Travel,Eco,696,3,4,3,1,5,3,5,5,3,2,4,5,5,5,2,0.0,neutral or dissatisfied +19758,66224,Female,Loyal Customer,52,Business travel,Business,1997,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +19759,91236,Female,Loyal Customer,38,Personal Travel,Eco,581,2,4,2,2,3,2,1,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +19760,90011,Male,Loyal Customer,52,Business travel,Business,3366,2,2,2,2,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +19761,116742,Male,Loyal Customer,49,Personal Travel,Eco Plus,337,3,4,4,4,2,4,2,2,1,3,2,2,3,2,2,0.0,neutral or dissatisfied +19762,106450,Female,Loyal Customer,31,Business travel,Business,1670,1,1,1,1,3,4,3,3,5,5,4,5,5,3,4,0.0,satisfied +19763,84259,Female,Loyal Customer,42,Business travel,Business,334,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +19764,64136,Male,Loyal Customer,68,Personal Travel,Business,989,1,5,0,5,4,4,4,4,4,0,4,5,4,4,0,10.0,neutral or dissatisfied +19765,98376,Male,Loyal Customer,22,Business travel,Business,1046,2,2,2,2,5,5,5,5,5,4,5,3,4,5,4,0.0,satisfied +19766,25926,Male,Loyal Customer,46,Business travel,Business,3536,4,4,4,4,3,3,2,5,5,5,5,3,5,5,0,4.0,satisfied +19767,128053,Male,Loyal Customer,67,Personal Travel,Eco,735,3,5,3,2,1,3,1,1,3,2,4,3,5,1,0,9.0,neutral or dissatisfied +19768,69155,Male,Loyal Customer,57,Personal Travel,Business,187,5,5,5,3,4,4,4,1,1,5,1,4,1,4,0,20.0,satisfied +19769,44269,Female,Loyal Customer,47,Personal Travel,Eco,359,2,5,2,3,4,5,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +19770,102812,Male,Loyal Customer,20,Business travel,Eco,342,3,5,1,1,3,3,3,3,2,4,4,3,3,3,31,28.0,neutral or dissatisfied +19771,27613,Female,Loyal Customer,27,Personal Travel,Eco,954,4,5,4,2,4,4,4,4,3,2,4,5,5,4,15,0.0,satisfied +19772,99522,Male,Loyal Customer,35,Personal Travel,Eco Plus,283,1,2,1,3,4,1,4,4,2,2,3,4,4,4,5,18.0,neutral or dissatisfied +19773,10417,Female,Loyal Customer,60,Business travel,Business,1959,3,3,3,3,5,5,4,3,3,4,3,3,3,5,22,21.0,satisfied +19774,14509,Female,Loyal Customer,36,Personal Travel,Eco,402,3,4,3,4,5,3,5,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +19775,57554,Male,Loyal Customer,17,Personal Travel,Business,1597,2,4,2,3,2,2,2,2,1,2,2,4,3,2,48,42.0,neutral or dissatisfied +19776,17828,Female,Loyal Customer,64,Personal Travel,Eco,1075,1,5,1,1,2,5,5,2,2,1,5,4,2,4,0,11.0,neutral or dissatisfied +19777,33392,Female,Loyal Customer,27,Personal Travel,Eco Plus,2349,2,4,2,3,2,2,2,2,3,1,4,4,5,2,0,0.0,neutral or dissatisfied +19778,57961,Male,Loyal Customer,41,Business travel,Business,1670,1,1,1,1,4,4,4,3,3,4,3,3,3,5,0,8.0,satisfied +19779,83382,Female,Loyal Customer,66,Personal Travel,Eco,1124,3,5,3,2,5,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +19780,49991,Male,Loyal Customer,35,Business travel,Eco,207,2,5,4,5,2,2,2,2,3,3,4,2,3,2,0,13.0,neutral or dissatisfied +19781,29772,Male,Loyal Customer,55,Business travel,Business,2276,2,3,4,3,2,4,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +19782,43818,Male,Loyal Customer,35,Personal Travel,Business,114,3,3,3,2,5,1,5,4,4,3,4,5,4,5,0,2.0,neutral or dissatisfied +19783,78860,Female,Loyal Customer,10,Personal Travel,Eco Plus,447,4,4,4,4,5,4,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +19784,88714,Female,Loyal Customer,37,Personal Travel,Eco,404,2,5,2,4,4,2,4,4,4,2,5,4,5,4,25,14.0,neutral or dissatisfied +19785,116116,Female,Loyal Customer,58,Personal Travel,Eco,337,2,4,2,2,5,5,4,1,1,2,1,4,1,4,19,15.0,neutral or dissatisfied +19786,55661,Male,disloyal Customer,60,Business travel,Business,1062,5,5,5,3,5,5,5,5,3,5,4,3,4,5,0,35.0,satisfied +19787,14159,Female,Loyal Customer,43,Business travel,Business,620,5,5,5,5,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +19788,18695,Female,Loyal Customer,35,Business travel,Eco Plus,127,5,1,4,4,5,5,5,5,2,3,5,3,1,5,0,0.0,satisfied +19789,112363,Male,Loyal Customer,49,Business travel,Business,2448,3,3,3,3,5,4,5,4,4,4,4,3,4,3,60,47.0,satisfied +19790,125464,Female,Loyal Customer,50,Business travel,Business,2917,1,2,2,2,1,1,1,3,3,3,4,1,1,1,0,0.0,neutral or dissatisfied +19791,81003,Female,Loyal Customer,33,Personal Travel,Eco,228,3,3,3,4,2,3,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +19792,95861,Male,Loyal Customer,59,Business travel,Business,580,2,1,2,2,3,4,5,4,4,4,4,5,4,5,9,4.0,satisfied +19793,4820,Male,Loyal Customer,47,Personal Travel,Business,408,3,4,3,1,5,5,5,1,1,3,1,4,1,4,9,3.0,neutral or dissatisfied +19794,87217,Male,Loyal Customer,27,Personal Travel,Eco,946,2,3,2,3,4,2,4,4,1,4,4,2,4,4,14,5.0,neutral or dissatisfied +19795,25774,Male,Loyal Customer,41,Business travel,Eco,762,4,3,3,3,4,4,4,4,5,3,3,1,5,4,0,0.0,satisfied +19796,50069,Male,Loyal Customer,19,Business travel,Business,1522,5,5,5,5,4,4,4,4,5,3,1,5,2,4,0,5.0,satisfied +19797,50609,Female,Loyal Customer,48,Personal Travel,Eco,89,3,5,3,4,2,5,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +19798,87206,Male,disloyal Customer,21,Business travel,Eco,546,2,4,3,3,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +19799,5743,Male,Loyal Customer,45,Business travel,Business,642,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,6.0,satisfied +19800,62308,Female,Loyal Customer,40,Business travel,Eco,414,3,5,5,5,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +19801,75495,Male,Loyal Customer,56,Business travel,Eco Plus,2342,1,5,5,5,1,1,1,1,3,2,3,4,4,1,101,92.0,neutral or dissatisfied +19802,70077,Female,Loyal Customer,40,Business travel,Eco,460,1,1,5,5,1,1,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +19803,49393,Male,Loyal Customer,42,Business travel,Eco,337,4,1,1,1,4,4,4,4,4,1,1,3,5,4,0,0.0,satisfied +19804,3889,Female,Loyal Customer,62,Business travel,Eco,213,1,4,4,4,1,4,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +19805,58018,Female,disloyal Customer,41,Business travel,Eco,1443,3,3,3,4,3,3,4,3,4,3,2,4,4,3,1,9.0,neutral or dissatisfied +19806,10858,Female,Loyal Customer,39,Business travel,Business,2302,3,5,5,5,5,3,3,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +19807,1702,Female,Loyal Customer,59,Business travel,Business,1677,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +19808,112595,Female,Loyal Customer,46,Business travel,Business,2125,3,4,4,4,5,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +19809,30734,Male,Loyal Customer,30,Business travel,Business,1069,2,1,1,1,2,2,2,2,3,2,3,4,3,2,0,14.0,neutral or dissatisfied +19810,38719,Female,Loyal Customer,58,Business travel,Business,2053,5,5,5,5,2,5,5,5,5,5,5,4,5,3,10,8.0,satisfied +19811,104534,Male,Loyal Customer,59,Business travel,Business,647,4,4,4,4,2,1,2,4,4,4,4,3,4,4,91,74.0,satisfied +19812,128547,Male,Loyal Customer,49,Business travel,Business,1818,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +19813,11431,Male,Loyal Customer,36,Business travel,Eco Plus,301,2,1,1,1,2,2,2,2,2,1,4,4,4,2,0,22.0,neutral or dissatisfied +19814,39549,Female,Loyal Customer,29,Business travel,Business,620,5,5,5,5,5,5,5,5,2,4,1,3,1,5,0,0.0,satisfied +19815,16211,Female,Loyal Customer,32,Personal Travel,Eco,199,2,4,2,3,3,2,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +19816,49407,Female,Loyal Customer,37,Business travel,Business,3710,1,1,1,1,4,3,4,4,4,4,4,1,4,5,0,0.0,satisfied +19817,15528,Male,Loyal Customer,42,Personal Travel,Eco Plus,306,3,4,3,4,5,3,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +19818,122370,Female,Loyal Customer,52,Business travel,Business,3136,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +19819,25780,Female,Loyal Customer,23,Business travel,Business,2665,1,1,1,1,4,5,4,4,5,1,2,5,1,4,0,0.0,satisfied +19820,120483,Male,Loyal Customer,20,Personal Travel,Eco,449,4,1,4,4,5,4,5,5,3,2,3,3,3,5,122,102.0,neutral or dissatisfied +19821,66146,Female,Loyal Customer,64,Personal Travel,Eco,583,1,5,1,1,4,5,5,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +19822,13027,Female,Loyal Customer,58,Personal Travel,Eco,374,2,4,2,4,3,4,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +19823,33805,Male,Loyal Customer,32,Business travel,Eco,1521,5,2,2,2,5,5,5,5,4,1,4,4,5,5,1,4.0,satisfied +19824,93257,Male,Loyal Customer,9,Personal Travel,Eco Plus,1180,4,4,4,5,2,4,2,2,3,5,3,5,5,2,26,11.0,neutral or dissatisfied +19825,14709,Female,Loyal Customer,44,Personal Travel,Eco,419,5,4,5,3,5,3,4,4,4,5,4,2,4,4,30,23.0,satisfied +19826,75088,Female,Loyal Customer,58,Personal Travel,Eco,1814,3,2,3,4,5,4,4,5,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +19827,49443,Female,Loyal Customer,36,Business travel,Eco,156,4,2,2,2,4,4,4,4,3,4,5,3,2,4,0,0.0,satisfied +19828,53228,Female,Loyal Customer,54,Personal Travel,Eco,612,1,4,1,3,4,4,4,2,2,1,2,5,2,5,3,6.0,neutral or dissatisfied +19829,36682,Female,Loyal Customer,58,Personal Travel,Eco,1249,2,5,2,2,3,3,4,3,3,2,3,3,3,5,3,57.0,neutral or dissatisfied +19830,116458,Female,Loyal Customer,55,Personal Travel,Eco,362,1,5,1,2,3,5,4,2,2,1,2,5,2,4,9,0.0,neutral or dissatisfied +19831,119423,Female,Loyal Customer,49,Personal Travel,Eco,399,0,3,0,1,2,4,3,1,1,0,1,2,1,3,0,0.0,satisfied +19832,46977,Female,Loyal Customer,21,Personal Travel,Eco,844,2,5,2,2,2,2,2,2,4,4,5,5,4,2,77,67.0,neutral or dissatisfied +19833,23171,Male,Loyal Customer,52,Personal Travel,Eco,250,5,5,5,4,3,5,3,3,5,2,5,3,4,3,0,3.0,satisfied +19834,55376,Female,disloyal Customer,8,Business travel,Eco,678,3,3,3,3,5,3,4,5,2,1,3,2,3,5,27,20.0,neutral or dissatisfied +19835,66430,Male,Loyal Customer,12,Personal Travel,Eco Plus,1562,0,4,0,1,2,0,2,2,1,4,5,3,4,2,12,0.0,satisfied +19836,63246,Female,Loyal Customer,31,Business travel,Business,2741,2,2,2,2,3,4,3,3,5,2,5,4,5,3,3,0.0,satisfied +19837,27998,Female,Loyal Customer,38,Business travel,Business,2235,1,1,3,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +19838,114902,Female,Loyal Customer,52,Business travel,Business,373,2,5,2,2,3,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +19839,53894,Female,Loyal Customer,44,Personal Travel,Eco,191,3,5,0,4,4,5,4,3,3,0,3,4,3,5,2,6.0,neutral or dissatisfied +19840,57627,Male,Loyal Customer,52,Business travel,Business,3588,1,1,4,1,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +19841,94517,Female,Loyal Customer,56,Business travel,Business,562,3,3,3,3,3,4,4,1,1,2,1,5,1,5,0,0.0,satisfied +19842,19747,Male,Loyal Customer,37,Business travel,Eco Plus,475,3,2,2,2,3,3,3,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +19843,67042,Female,Loyal Customer,56,Business travel,Business,3419,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +19844,43658,Male,Loyal Customer,59,Business travel,Eco,695,5,4,4,4,5,5,5,5,3,4,3,3,3,5,0,4.0,satisfied +19845,695,Male,disloyal Customer,20,Business travel,Eco,89,1,4,1,5,3,1,1,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +19846,108994,Male,disloyal Customer,24,Business travel,Eco,1105,4,4,4,3,3,4,3,3,4,2,5,4,4,3,29,28.0,satisfied +19847,58041,Female,disloyal Customer,52,Business travel,Business,589,1,1,1,3,2,1,2,2,5,3,4,4,5,2,58,43.0,neutral or dissatisfied +19848,50718,Female,Loyal Customer,31,Personal Travel,Eco,110,2,5,2,4,3,2,4,3,5,5,1,3,5,3,0,0.0,neutral or dissatisfied +19849,106163,Male,Loyal Customer,31,Personal Travel,Eco,302,1,4,1,3,4,1,5,4,5,4,4,5,4,4,10,0.0,neutral or dissatisfied +19850,33308,Male,Loyal Customer,43,Business travel,Eco Plus,121,2,4,4,4,2,2,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +19851,78857,Female,Loyal Customer,7,Personal Travel,Eco Plus,432,1,4,1,4,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +19852,62485,Female,disloyal Customer,35,Business travel,Business,1846,3,3,3,4,3,3,3,3,5,2,4,3,4,3,21,2.0,neutral or dissatisfied +19853,127340,Female,disloyal Customer,23,Business travel,Eco,507,0,4,1,4,4,1,4,4,3,2,4,5,5,4,0,0.0,satisfied +19854,110769,Female,Loyal Customer,38,Business travel,Business,2004,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +19855,77504,Female,Loyal Customer,18,Personal Travel,Eco,1195,2,4,2,5,4,2,4,4,2,5,5,1,2,4,0,8.0,neutral or dissatisfied +19856,123322,Male,Loyal Customer,37,Business travel,Eco Plus,328,3,5,5,5,3,3,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +19857,99019,Male,Loyal Customer,44,Business travel,Business,1009,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,3.0,satisfied +19858,73484,Male,Loyal Customer,49,Personal Travel,Eco,1012,2,1,2,3,3,2,3,3,3,2,2,2,2,3,0,0.0,neutral or dissatisfied +19859,91174,Male,Loyal Customer,9,Personal Travel,Eco,545,3,5,3,3,2,3,2,2,3,5,5,3,3,2,0,0.0,neutral or dissatisfied +19860,76801,Female,Loyal Customer,56,Personal Travel,Eco,689,4,5,5,3,5,4,4,2,2,5,2,5,2,3,8,0.0,neutral or dissatisfied +19861,16382,Female,Loyal Customer,56,Business travel,Business,2865,5,5,5,5,2,3,1,4,4,4,4,5,4,3,0,0.0,satisfied +19862,78193,Male,Loyal Customer,58,Business travel,Business,2240,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +19863,45631,Male,Loyal Customer,62,Business travel,Business,113,3,1,1,1,5,4,4,3,3,3,3,2,3,3,0,36.0,neutral or dissatisfied +19864,124743,Male,Loyal Customer,49,Personal Travel,Eco Plus,399,3,4,3,2,1,3,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +19865,114310,Female,Loyal Customer,30,Personal Travel,Eco,909,4,4,4,3,3,4,3,3,4,2,3,3,4,3,54,80.0,neutral or dissatisfied +19866,103526,Female,Loyal Customer,52,Personal Travel,Business,738,3,5,3,2,5,4,4,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +19867,96868,Male,Loyal Customer,52,Business travel,Business,381,4,4,4,4,4,2,1,3,3,3,3,1,3,5,0,0.0,satisfied +19868,66759,Female,Loyal Customer,67,Personal Travel,Eco,802,2,2,2,3,3,3,4,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +19869,59952,Male,Loyal Customer,53,Business travel,Business,1085,2,5,5,5,4,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +19870,23583,Female,Loyal Customer,15,Personal Travel,Business,1024,1,5,1,5,1,1,1,1,3,5,5,4,4,1,30,33.0,neutral or dissatisfied +19871,111803,Female,Loyal Customer,73,Business travel,Business,349,2,2,3,3,2,3,4,2,2,3,2,4,2,2,5,0.0,neutral or dissatisfied +19872,79092,Female,Loyal Customer,54,Personal Travel,Eco,331,2,5,2,1,4,4,4,3,3,2,3,5,3,3,28,17.0,neutral or dissatisfied +19873,35756,Female,Loyal Customer,13,Business travel,Eco,1608,4,5,5,5,4,4,5,4,3,3,5,4,2,4,2,0.0,satisfied +19874,122998,Male,Loyal Customer,46,Business travel,Business,2357,3,3,3,3,4,4,4,4,4,3,4,4,4,4,0,0.0,satisfied +19875,55553,Female,Loyal Customer,70,Personal Travel,Eco,550,3,4,3,4,2,4,4,4,4,3,4,4,4,3,37,19.0,neutral or dissatisfied +19876,93899,Male,Loyal Customer,38,Personal Travel,Eco,588,1,5,1,4,1,1,3,1,3,5,4,4,5,1,10,9.0,neutral or dissatisfied +19877,98336,Male,Loyal Customer,35,Business travel,Business,3449,5,5,5,5,2,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +19878,102640,Female,Loyal Customer,48,Business travel,Business,1703,1,1,1,1,3,4,4,5,5,5,5,4,5,5,37,25.0,satisfied +19879,757,Female,disloyal Customer,38,Business travel,Business,113,3,3,3,4,5,3,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +19880,100116,Male,disloyal Customer,22,Business travel,Eco,725,4,4,4,2,3,4,3,3,5,3,5,5,4,3,0,0.0,satisfied +19881,22777,Male,Loyal Customer,27,Business travel,Business,3746,2,2,4,2,4,4,5,4,5,1,3,4,5,4,10,13.0,satisfied +19882,105935,Male,Loyal Customer,64,Business travel,Business,1491,4,3,3,3,4,4,4,4,4,4,4,4,4,4,133,158.0,neutral or dissatisfied +19883,121788,Female,disloyal Customer,21,Business travel,Business,449,4,0,4,4,4,2,2,3,2,4,4,2,4,2,185,180.0,satisfied +19884,56700,Female,Loyal Customer,27,Personal Travel,Eco,1068,3,4,3,3,5,3,5,5,5,2,4,5,5,5,34,17.0,neutral or dissatisfied +19885,104407,Female,Loyal Customer,44,Business travel,Business,1011,3,3,3,3,2,4,5,4,4,4,4,3,4,4,39,24.0,satisfied +19886,22565,Male,Loyal Customer,39,Business travel,Eco,300,4,5,5,5,4,4,4,4,1,2,4,3,4,4,0,0.0,satisfied +19887,127370,Female,disloyal Customer,29,Business travel,Business,868,4,4,4,4,5,4,5,5,5,5,5,4,5,5,37,19.0,satisfied +19888,92724,Female,Loyal Customer,41,Business travel,Business,1276,1,1,1,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +19889,89451,Female,Loyal Customer,43,Personal Travel,Eco,134,1,1,1,4,3,4,4,4,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +19890,20881,Male,Loyal Customer,52,Business travel,Eco Plus,508,4,4,1,4,3,4,3,3,5,5,5,5,3,3,0,0.0,satisfied +19891,18226,Female,Loyal Customer,68,Business travel,Eco,235,4,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +19892,57651,Female,disloyal Customer,37,Business travel,Eco,200,3,1,3,1,4,3,4,4,4,2,2,1,1,4,0,3.0,neutral or dissatisfied +19893,110729,Female,disloyal Customer,25,Business travel,Business,849,4,0,4,2,5,4,5,5,5,5,4,3,4,5,0,22.0,satisfied +19894,41867,Female,Loyal Customer,43,Personal Travel,Eco,483,2,1,2,3,3,3,2,2,2,2,2,1,2,2,51,66.0,neutral or dissatisfied +19895,16804,Male,Loyal Customer,65,Personal Travel,Business,645,0,2,0,3,3,4,4,3,3,0,3,1,3,2,0,0.0,satisfied +19896,87594,Female,Loyal Customer,46,Personal Travel,Eco,432,3,4,3,4,3,4,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +19897,77502,Male,Loyal Customer,33,Personal Travel,Eco,1087,2,1,3,4,2,3,5,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +19898,102236,Female,disloyal Customer,39,Business travel,Business,226,3,3,3,3,2,3,1,2,1,4,4,4,3,2,0,0.0,neutral or dissatisfied +19899,62087,Female,Loyal Customer,32,Personal Travel,Eco Plus,2586,3,4,3,3,1,3,1,1,5,3,4,3,4,1,0,3.0,neutral or dissatisfied +19900,117602,Male,Loyal Customer,31,Business travel,Business,3413,4,1,1,1,4,4,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +19901,12616,Female,Loyal Customer,50,Business travel,Eco,802,4,5,5,5,3,4,4,4,4,4,4,3,4,4,15,6.0,satisfied +19902,9076,Male,Loyal Customer,44,Personal Travel,Eco,108,2,4,0,4,5,0,5,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +19903,11183,Male,Loyal Customer,15,Personal Travel,Eco,316,1,5,1,3,5,1,1,5,2,2,4,2,4,5,50,42.0,neutral or dissatisfied +19904,90049,Female,disloyal Customer,23,Business travel,Business,1086,5,2,5,1,4,5,3,4,5,2,5,3,5,4,13,27.0,satisfied +19905,108817,Female,Loyal Customer,11,Personal Travel,Eco Plus,404,1,2,1,4,4,1,4,4,3,2,3,2,4,4,2,0.0,neutral or dissatisfied +19906,12017,Female,Loyal Customer,48,Business travel,Business,2408,4,4,4,4,2,1,4,2,2,2,2,2,2,5,0,0.0,satisfied +19907,65157,Female,Loyal Customer,56,Personal Travel,Eco,190,2,4,2,1,2,4,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +19908,100364,Male,Loyal Customer,47,Personal Travel,Eco,1073,2,4,2,1,1,2,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +19909,59085,Male,Loyal Customer,41,Business travel,Eco,244,4,5,5,5,3,4,3,3,5,3,4,3,2,3,25,15.0,satisfied +19910,60233,Male,disloyal Customer,40,Business travel,Eco,209,2,0,2,2,4,2,2,4,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +19911,92273,Male,Loyal Customer,32,Business travel,Business,1900,3,3,3,3,3,3,3,3,3,1,2,3,3,3,0,0.0,neutral or dissatisfied +19912,122996,Male,Loyal Customer,40,Business travel,Business,3070,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +19913,53283,Female,Loyal Customer,47,Business travel,Business,3484,4,4,4,4,5,4,1,4,4,4,4,5,4,1,29,5.0,satisfied +19914,125771,Female,Loyal Customer,60,Business travel,Business,992,3,3,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +19915,74360,Female,Loyal Customer,59,Business travel,Business,1235,3,3,1,3,5,5,5,4,4,4,4,3,4,5,17,13.0,satisfied +19916,93380,Male,Loyal Customer,50,Business travel,Business,1638,2,2,2,2,3,4,5,4,4,4,4,3,4,5,7,6.0,satisfied +19917,51218,Male,Loyal Customer,52,Business travel,Eco Plus,308,2,3,3,3,2,2,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +19918,78173,Female,Loyal Customer,43,Business travel,Business,153,5,5,5,5,4,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +19919,72203,Female,disloyal Customer,20,Business travel,Business,768,0,5,0,5,0,3,3,5,5,4,4,3,5,3,0,0.0,satisfied +19920,20302,Male,Loyal Customer,31,Business travel,Eco Plus,224,5,4,4,4,5,5,5,5,3,2,2,3,1,5,7,9.0,satisfied +19921,107282,Male,Loyal Customer,45,Business travel,Business,283,5,5,5,5,5,5,5,5,5,5,5,5,5,5,28,81.0,satisfied +19922,69207,Female,disloyal Customer,22,Business travel,Eco,733,0,0,0,1,5,0,5,5,4,4,4,5,4,5,10,19.0,satisfied +19923,60983,Male,Loyal Customer,39,Personal Travel,Eco,888,2,5,2,1,5,2,5,5,3,5,5,3,1,5,0,0.0,neutral or dissatisfied +19924,117270,Female,Loyal Customer,9,Personal Travel,Eco,370,4,0,4,5,3,4,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +19925,128238,Female,Loyal Customer,11,Personal Travel,Eco,602,2,1,2,2,4,2,4,4,4,3,2,3,2,4,0,1.0,neutral or dissatisfied +19926,127900,Female,disloyal Customer,50,Business travel,Business,1671,4,3,3,4,4,4,4,4,4,2,5,5,5,4,3,28.0,neutral or dissatisfied +19927,74291,Female,disloyal Customer,22,Business travel,Eco,811,5,5,5,5,3,0,3,3,1,4,5,2,2,3,0,7.0,satisfied +19928,15402,Male,Loyal Customer,38,Business travel,Eco,331,3,2,2,2,3,3,3,3,1,4,3,5,3,3,0,0.0,satisfied +19929,10956,Male,Loyal Customer,34,Business travel,Eco,140,2,2,2,2,2,2,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +19930,20287,Male,Loyal Customer,63,Personal Travel,Eco,228,2,4,2,1,5,2,5,5,5,3,4,5,4,5,0,30.0,neutral or dissatisfied +19931,10853,Male,Loyal Customer,24,Business travel,Business,396,3,3,3,3,5,5,5,5,4,5,5,3,5,5,0,0.0,satisfied +19932,76507,Male,Loyal Customer,52,Business travel,Business,2886,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +19933,123341,Male,Loyal Customer,55,Personal Travel,Eco Plus,631,3,2,3,2,3,3,2,3,1,4,1,2,2,3,0,0.0,neutral or dissatisfied +19934,27098,Female,Loyal Customer,35,Business travel,Eco,1721,5,4,4,4,5,5,5,5,2,5,4,4,5,5,0,0.0,satisfied +19935,81434,Male,Loyal Customer,39,Personal Travel,Eco,448,3,3,3,3,5,3,5,5,1,5,2,1,2,5,100,81.0,neutral or dissatisfied +19936,99658,Female,Loyal Customer,35,Business travel,Eco,1050,3,4,4,4,3,5,3,3,2,4,4,3,3,3,3,0.0,satisfied +19937,73388,Female,Loyal Customer,21,Business travel,Eco,1197,5,2,2,2,4,2,5,2,3,2,3,5,3,5,107,141.0,neutral or dissatisfied +19938,99843,Male,Loyal Customer,48,Business travel,Business,468,5,5,5,5,1,3,4,3,3,4,3,2,3,5,28,30.0,satisfied +19939,3403,Female,disloyal Customer,23,Business travel,Eco,240,5,0,5,2,1,5,1,1,2,3,5,2,1,1,2,27.0,satisfied +19940,55602,Female,Loyal Customer,36,Business travel,Business,1749,1,5,5,5,2,3,3,1,1,1,1,4,1,2,16,12.0,neutral or dissatisfied +19941,83424,Female,Loyal Customer,39,Personal Travel,Eco,632,4,3,4,4,5,4,2,5,4,2,4,1,4,5,0,0.0,satisfied +19942,110651,Male,Loyal Customer,44,Business travel,Business,3372,4,4,4,4,4,5,5,5,5,5,5,3,5,3,10,0.0,satisfied +19943,47695,Male,Loyal Customer,22,Personal Travel,Eco,1334,0,5,0,5,5,0,5,5,5,2,4,5,4,5,0,0.0,satisfied +19944,113070,Male,Loyal Customer,27,Business travel,Business,2559,2,3,3,3,2,2,2,2,2,3,3,1,4,2,19,17.0,neutral or dissatisfied +19945,97724,Male,disloyal Customer,37,Business travel,Business,787,5,5,5,5,1,5,5,1,4,3,5,5,5,1,43,41.0,satisfied +19946,58788,Female,Loyal Customer,60,Business travel,Business,1908,4,4,4,4,5,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +19947,11721,Male,Loyal Customer,45,Business travel,Business,1847,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,5.0,satisfied +19948,115137,Female,Loyal Customer,30,Business travel,Business,2254,1,1,1,1,5,5,5,5,3,3,4,3,4,5,39,34.0,satisfied +19949,54114,Male,Loyal Customer,12,Personal Travel,Business,1400,2,5,2,1,2,2,2,2,3,5,5,4,4,2,30,12.0,neutral or dissatisfied +19950,44078,Male,Loyal Customer,40,Personal Travel,Eco,651,2,3,2,3,3,2,5,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +19951,96945,Female,Loyal Customer,45,Business travel,Business,3767,2,2,2,2,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +19952,12565,Male,Loyal Customer,29,Personal Travel,Eco,871,4,5,4,3,3,4,3,3,3,5,3,5,3,3,64,81.0,neutral or dissatisfied +19953,124937,Female,Loyal Customer,8,Personal Travel,Eco,728,2,3,1,3,3,1,3,3,1,1,3,2,3,3,0,0.0,neutral or dissatisfied +19954,77019,Female,Loyal Customer,23,Business travel,Business,1717,3,3,5,3,3,3,3,3,2,3,4,2,3,3,31,15.0,neutral or dissatisfied +19955,30808,Female,Loyal Customer,31,Business travel,Eco,1199,3,5,5,5,3,3,3,3,2,4,3,3,4,3,22,25.0,neutral or dissatisfied +19956,91410,Male,Loyal Customer,51,Business travel,Business,1939,4,4,4,4,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +19957,44098,Female,Loyal Customer,57,Business travel,Eco,408,2,2,2,2,4,3,3,2,2,2,2,3,2,1,20,39.0,neutral or dissatisfied +19958,66419,Female,Loyal Customer,41,Personal Travel,Eco,1562,2,4,3,4,3,3,3,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +19959,109020,Male,Loyal Customer,55,Business travel,Business,3680,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,23.0,satisfied +19960,119758,Female,Loyal Customer,54,Business travel,Business,1303,2,2,2,2,3,4,4,3,3,3,3,3,3,4,0,4.0,satisfied +19961,119172,Female,Loyal Customer,36,Business travel,Business,3721,0,0,0,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +19962,94066,Male,Loyal Customer,46,Business travel,Business,2507,1,1,1,1,5,4,5,5,5,5,5,5,5,4,12,12.0,satisfied +19963,27801,Male,disloyal Customer,26,Business travel,Eco,1533,3,3,3,3,2,3,5,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +19964,42978,Female,Loyal Customer,30,Business travel,Eco,259,4,3,3,3,4,4,4,4,2,3,1,2,3,4,0,0.0,satisfied +19965,51233,Female,disloyal Customer,23,Business travel,Eco,373,4,0,4,3,3,4,3,3,3,5,1,2,5,3,0,0.0,neutral or dissatisfied +19966,119711,Female,Loyal Customer,55,Business travel,Business,1430,3,3,3,3,3,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +19967,22667,Male,Loyal Customer,52,Personal Travel,Business,589,4,5,4,3,4,1,1,1,1,4,1,1,1,4,0,0.0,satisfied +19968,10290,Female,Loyal Customer,49,Business travel,Business,224,4,4,4,4,5,4,4,5,5,5,5,4,5,3,0,3.0,satisfied +19969,122913,Female,disloyal Customer,23,Business travel,Eco,468,1,2,1,1,5,1,5,5,3,3,2,4,1,5,0,0.0,neutral or dissatisfied +19970,82561,Female,Loyal Customer,46,Business travel,Business,528,3,3,3,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +19971,21900,Female,disloyal Customer,20,Business travel,Eco,551,5,0,5,1,5,5,5,5,5,4,5,5,2,5,0,,satisfied +19972,31732,Male,Loyal Customer,41,Personal Travel,Eco,853,3,5,3,2,1,3,1,1,3,4,4,4,5,1,115,111.0,neutral or dissatisfied +19973,8422,Male,Loyal Customer,60,Business travel,Business,2589,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +19974,101094,Female,Loyal Customer,55,Business travel,Business,1069,4,4,4,4,5,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +19975,54694,Male,disloyal Customer,26,Business travel,Eco,965,2,2,2,4,2,2,1,2,4,2,4,1,4,2,39,35.0,neutral or dissatisfied +19976,52265,Female,Loyal Customer,38,Business travel,Business,3121,3,2,2,2,3,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +19977,98918,Female,disloyal Customer,27,Business travel,Eco,569,3,2,3,3,1,3,1,1,1,4,3,3,4,1,20,4.0,neutral or dissatisfied +19978,66703,Female,Loyal Customer,43,Business travel,Business,3038,4,4,4,4,5,4,4,5,5,5,5,3,5,4,12,4.0,satisfied +19979,100667,Male,Loyal Customer,45,Business travel,Eco,677,2,2,2,2,3,2,3,3,2,1,3,1,4,3,51,55.0,neutral or dissatisfied +19980,108116,Female,Loyal Customer,38,Business travel,Business,1166,3,5,3,3,2,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +19981,115252,Male,Loyal Customer,32,Business travel,Business,373,4,4,4,4,4,4,4,4,4,3,4,4,5,4,77,63.0,satisfied +19982,116943,Male,disloyal Customer,36,Business travel,Eco,304,3,0,3,3,4,3,1,4,1,4,3,2,3,4,0,0.0,neutral or dissatisfied +19983,55078,Male,Loyal Customer,65,Business travel,Business,1379,2,1,1,1,1,2,3,2,2,3,2,2,2,3,0,7.0,neutral or dissatisfied +19984,100080,Male,Loyal Customer,60,Personal Travel,Eco Plus,289,4,4,4,1,5,4,5,5,4,4,4,4,4,5,14,0.0,neutral or dissatisfied +19985,125797,Male,Loyal Customer,49,Business travel,Business,2491,2,2,2,2,5,4,5,2,2,2,2,5,2,4,44,25.0,satisfied +19986,94953,Female,Loyal Customer,65,Business travel,Business,2457,3,3,3,3,2,3,5,4,4,4,4,3,4,1,1,0.0,satisfied +19987,8724,Male,Loyal Customer,15,Personal Travel,Eco,280,1,5,1,3,3,1,1,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +19988,7425,Male,Loyal Customer,37,Business travel,Eco,522,2,2,2,2,2,2,2,2,4,1,3,2,4,2,4,27.0,neutral or dissatisfied +19989,69148,Female,Loyal Customer,57,Personal Travel,Eco,2248,2,4,2,2,2,3,3,3,5,5,5,3,4,3,0,49.0,neutral or dissatisfied +19990,72805,Female,Loyal Customer,11,Personal Travel,Eco,1045,4,5,4,4,1,4,1,1,5,3,3,2,2,1,10,4.0,neutral or dissatisfied +19991,55396,Female,Loyal Customer,43,Business travel,Eco Plus,413,2,2,2,2,3,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +19992,31442,Female,Loyal Customer,53,Business travel,Eco,1541,2,5,5,5,2,2,3,2,2,2,2,4,2,3,4,0.0,neutral or dissatisfied +19993,94043,Female,Loyal Customer,49,Business travel,Business,562,3,3,3,3,4,5,4,5,5,5,5,4,5,4,15,9.0,satisfied +19994,104016,Male,Loyal Customer,29,Business travel,Eco Plus,1363,1,5,5,5,1,1,1,1,5,3,3,1,3,1,160,154.0,neutral or dissatisfied +19995,78185,Female,Loyal Customer,29,Business travel,Business,259,3,3,2,3,5,5,5,5,5,5,4,3,5,5,0,2.0,satisfied +19996,124766,Male,disloyal Customer,26,Business travel,Business,280,2,5,2,3,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +19997,121293,Female,Loyal Customer,63,Business travel,Business,2987,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,9.0,satisfied +19998,83357,Female,disloyal Customer,23,Business travel,Eco,1124,1,1,1,4,4,1,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +19999,75499,Female,Loyal Customer,49,Business travel,Business,2585,3,3,2,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +20000,66203,Male,Loyal Customer,63,Business travel,Business,1639,4,3,3,3,5,2,2,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +20001,71698,Female,Loyal Customer,19,Personal Travel,Eco,1144,2,2,2,2,5,2,5,5,2,5,2,3,3,5,0,0.0,neutral or dissatisfied +20002,98346,Male,Loyal Customer,25,Business travel,Business,1046,4,4,4,4,4,3,4,4,2,2,3,3,3,4,20,22.0,neutral or dissatisfied +20003,99851,Male,Loyal Customer,29,Personal Travel,Eco,680,1,2,1,3,5,1,5,5,4,2,3,1,4,5,1,0.0,neutral or dissatisfied +20004,117540,Male,Loyal Customer,46,Business travel,Business,1020,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +20005,87207,Female,Loyal Customer,36,Personal Travel,Eco,946,5,3,5,3,1,5,1,1,2,3,4,4,4,1,0,0.0,satisfied +20006,12477,Male,Loyal Customer,17,Personal Travel,Eco,201,1,4,1,4,2,1,2,2,3,2,4,2,4,2,0,1.0,neutral or dissatisfied +20007,102317,Male,Loyal Customer,56,Business travel,Business,258,5,5,4,5,5,4,4,4,4,4,4,5,4,3,65,55.0,satisfied +20008,42621,Male,Loyal Customer,46,Business travel,Eco,546,3,3,3,3,3,3,3,3,3,3,2,4,4,3,0,0.0,satisfied +20009,62269,Female,Loyal Customer,27,Personal Travel,Eco Plus,2565,1,1,0,3,1,0,1,1,4,1,4,1,3,1,6,0.0,neutral or dissatisfied +20010,9056,Female,disloyal Customer,57,Business travel,Business,108,3,3,3,4,4,3,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +20011,10394,Male,Loyal Customer,52,Business travel,Business,2092,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +20012,36705,Male,Loyal Customer,62,Personal Travel,Eco,1249,3,4,3,3,3,4,4,4,4,4,5,4,3,4,130,133.0,neutral or dissatisfied +20013,15595,Male,Loyal Customer,39,Business travel,Business,296,4,1,3,3,1,3,2,4,4,3,4,4,4,3,0,4.0,neutral or dissatisfied +20014,78752,Male,Loyal Customer,54,Business travel,Business,554,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20015,44945,Female,Loyal Customer,49,Business travel,Business,397,1,1,1,1,3,4,4,1,1,1,1,3,1,1,23,18.0,neutral or dissatisfied +20016,19706,Female,Loyal Customer,44,Business travel,Business,1575,3,3,3,3,2,2,1,5,5,5,5,4,5,2,91,91.0,satisfied +20017,27320,Male,Loyal Customer,41,Business travel,Eco,954,5,4,5,4,5,5,5,5,1,4,5,1,3,5,0,0.0,satisfied +20018,32683,Male,disloyal Customer,36,Business travel,Business,216,1,1,1,3,4,1,1,4,3,1,3,4,4,4,5,13.0,neutral or dissatisfied +20019,121206,Female,Loyal Customer,61,Personal Travel,Eco Plus,2402,1,2,2,4,2,4,4,1,1,3,4,4,4,4,0,0.0,neutral or dissatisfied +20020,54433,Female,Loyal Customer,56,Personal Travel,Eco,305,3,5,5,3,2,5,4,4,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +20021,39184,Female,Loyal Customer,67,Personal Travel,Eco,237,4,5,0,3,5,5,5,2,2,0,2,5,2,3,0,0.0,neutral or dissatisfied +20022,51336,Female,Loyal Customer,52,Business travel,Eco Plus,308,3,1,1,1,3,4,4,3,3,3,3,2,3,4,37,52.0,neutral or dissatisfied +20023,34756,Male,disloyal Customer,34,Business travel,Eco,301,2,1,2,2,4,2,4,4,4,5,3,2,3,4,0,4.0,neutral or dissatisfied +20024,6502,Female,Loyal Customer,27,Business travel,Business,2306,5,5,1,5,5,5,5,5,4,5,4,5,5,5,0,0.0,satisfied +20025,14493,Male,Loyal Customer,46,Business travel,Eco Plus,495,4,5,2,5,4,4,4,4,3,5,4,1,4,4,0,0.0,neutral or dissatisfied +20026,43509,Male,Loyal Customer,50,Personal Travel,Eco,679,4,5,4,3,4,4,4,4,4,5,5,3,5,4,0,1.0,neutral or dissatisfied +20027,71525,Male,Loyal Customer,58,Business travel,Business,1500,1,1,1,1,3,4,4,4,4,4,4,4,4,4,24,16.0,satisfied +20028,116651,Female,Loyal Customer,47,Business travel,Business,2941,1,1,1,1,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20029,34471,Male,Loyal Customer,30,Business travel,Business,266,3,1,1,1,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +20030,26274,Male,Loyal Customer,40,Business travel,Business,2372,3,5,5,5,4,4,3,3,3,3,3,4,3,3,22,33.0,neutral or dissatisfied +20031,102630,Male,disloyal Customer,22,Business travel,Eco,255,4,0,4,2,3,4,1,3,3,3,4,3,4,3,24,19.0,satisfied +20032,13658,Male,Loyal Customer,43,Business travel,Business,3769,1,1,1,1,2,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +20033,76532,Female,Loyal Customer,28,Business travel,Eco,547,3,5,2,5,3,2,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +20034,109645,Male,Loyal Customer,45,Business travel,Business,3831,4,1,4,4,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +20035,47604,Male,Loyal Customer,27,Business travel,Business,1773,2,2,2,2,4,4,4,4,3,2,2,5,3,4,32,15.0,satisfied +20036,85835,Female,Loyal Customer,20,Personal Travel,Eco,526,2,4,2,3,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +20037,24151,Male,Loyal Customer,43,Business travel,Eco,147,3,4,4,4,3,3,3,3,2,2,5,5,5,3,13,11.0,satisfied +20038,34624,Female,disloyal Customer,30,Business travel,Eco Plus,2454,1,1,1,3,1,5,5,1,1,4,5,5,4,5,6,36.0,neutral or dissatisfied +20039,107945,Female,Loyal Customer,46,Personal Travel,Eco,611,3,3,3,3,3,2,1,4,4,3,4,5,4,4,1,0.0,neutral or dissatisfied +20040,5823,Female,Loyal Customer,58,Personal Travel,Eco,273,2,2,2,3,5,3,3,4,4,2,4,4,4,1,33,73.0,neutral or dissatisfied +20041,45235,Male,Loyal Customer,52,Business travel,Eco,613,4,1,1,1,4,4,4,4,5,2,4,2,4,4,0,0.0,satisfied +20042,117219,Female,Loyal Customer,32,Personal Travel,Eco,646,3,3,3,4,5,3,5,5,1,5,1,4,1,5,1,0.0,neutral or dissatisfied +20043,9752,Female,Loyal Customer,42,Business travel,Business,1045,4,4,4,4,4,4,4,5,2,4,5,4,5,4,266,248.0,satisfied +20044,60864,Female,Loyal Customer,36,Business travel,Business,1491,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +20045,125290,Male,disloyal Customer,33,Business travel,Eco,678,3,3,3,4,1,3,2,1,4,4,3,2,4,1,4,9.0,neutral or dissatisfied +20046,38569,Female,Loyal Customer,40,Personal Travel,Eco,2586,2,3,2,3,4,2,4,4,1,1,4,2,3,4,0,17.0,neutral or dissatisfied +20047,47196,Male,Loyal Customer,58,Business travel,Eco,279,4,5,5,5,4,4,4,4,3,1,5,1,4,4,6,5.0,satisfied +20048,28100,Male,Loyal Customer,15,Business travel,Eco,569,5,5,5,5,5,5,4,5,4,3,1,2,5,5,0,8.0,satisfied +20049,121192,Female,Loyal Customer,7,Personal Travel,Eco,2521,3,2,4,2,1,4,1,1,1,5,1,1,2,1,0,,neutral or dissatisfied +20050,81302,Male,Loyal Customer,11,Personal Travel,Eco Plus,1029,4,2,3,3,5,3,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +20051,26845,Male,Loyal Customer,56,Business travel,Eco,224,5,3,3,3,5,5,5,5,5,5,3,1,3,5,0,0.0,satisfied +20052,72079,Male,Loyal Customer,39,Business travel,Business,3404,3,4,4,4,1,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +20053,46480,Male,Loyal Customer,49,Personal Travel,Business,125,1,5,1,4,3,4,3,5,5,1,1,5,5,4,0,0.0,neutral or dissatisfied +20054,56881,Female,disloyal Customer,23,Business travel,Eco,2565,5,4,4,2,5,4,4,3,4,4,5,4,4,4,0,28.0,satisfied +20055,112340,Female,Loyal Customer,52,Business travel,Business,2304,3,3,3,3,4,4,4,5,5,5,5,3,5,5,30,35.0,satisfied +20056,125067,Female,Loyal Customer,39,Business travel,Business,3683,5,5,2,5,5,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +20057,7018,Male,Loyal Customer,7,Personal Travel,Eco,234,3,5,3,4,3,3,3,3,1,5,4,5,4,3,0,0.0,neutral or dissatisfied +20058,55910,Male,Loyal Customer,7,Personal Travel,Eco,733,2,4,2,4,5,2,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +20059,13161,Female,Loyal Customer,54,Personal Travel,Eco,427,3,5,3,4,5,3,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +20060,24741,Female,Loyal Customer,49,Business travel,Eco,447,2,2,2,2,3,4,2,2,2,2,2,2,2,5,0,0.0,satisfied +20061,25789,Female,Loyal Customer,38,Business travel,Business,2388,1,3,3,3,3,4,2,1,1,1,1,2,1,2,2,0.0,neutral or dissatisfied +20062,116885,Male,disloyal Customer,21,Business travel,Eco,368,5,5,5,4,4,5,4,4,4,2,5,3,5,4,43,41.0,satisfied +20063,28932,Male,Loyal Customer,25,Business travel,Eco,605,1,4,4,4,1,1,2,1,2,3,4,3,3,1,0,0.0,neutral or dissatisfied +20064,58714,Female,disloyal Customer,15,Business travel,Eco,606,3,2,3,3,3,3,3,3,2,1,4,3,4,3,64,89.0,neutral or dissatisfied +20065,60776,Male,Loyal Customer,8,Personal Travel,Eco,628,1,5,0,1,3,0,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +20066,102425,Female,Loyal Customer,54,Personal Travel,Eco,391,1,2,1,3,3,4,4,5,5,1,5,3,5,4,13,3.0,neutral or dissatisfied +20067,72312,Male,Loyal Customer,60,Business travel,Eco Plus,919,1,4,4,4,1,1,1,1,4,4,2,4,3,1,0,0.0,neutral or dissatisfied +20068,45912,Female,disloyal Customer,39,Business travel,Business,641,2,2,2,4,4,2,1,4,1,2,3,3,3,4,58,45.0,neutral or dissatisfied +20069,73419,Male,disloyal Customer,20,Business travel,Eco,797,3,3,3,2,5,3,5,5,2,2,1,1,2,5,37,33.0,neutral or dissatisfied +20070,55392,Female,Loyal Customer,10,Personal Travel,Eco,678,3,5,4,2,5,4,5,5,3,2,4,4,4,5,23,28.0,neutral or dissatisfied +20071,119981,Male,Loyal Customer,8,Personal Travel,Eco,1009,1,3,1,4,4,1,2,4,2,2,4,3,3,4,0,0.0,neutral or dissatisfied +20072,43093,Female,Loyal Customer,15,Personal Travel,Eco,391,3,4,3,4,5,3,1,5,3,4,3,2,4,5,21,15.0,neutral or dissatisfied +20073,102611,Male,disloyal Customer,36,Business travel,Business,236,3,3,3,4,1,3,1,1,4,1,3,1,3,1,23,37.0,neutral or dissatisfied +20074,113471,Male,Loyal Customer,47,Business travel,Eco,223,1,3,3,3,1,1,1,1,4,5,2,4,2,1,2,0.0,neutral or dissatisfied +20075,37003,Female,Loyal Customer,33,Personal Travel,Eco,899,4,4,4,3,5,4,2,5,5,4,5,4,5,5,0,0.0,satisfied +20076,108530,Female,disloyal Customer,56,Business travel,Eco,249,3,0,3,3,2,3,2,2,2,3,1,3,1,2,1,3.0,neutral or dissatisfied +20077,111679,Male,Loyal Customer,15,Personal Travel,Eco,991,1,3,0,2,4,0,4,4,2,3,2,4,3,4,20,33.0,neutral or dissatisfied +20078,29014,Female,Loyal Customer,70,Business travel,Business,3405,5,5,5,5,4,5,3,4,4,4,4,5,4,1,0,0.0,satisfied +20079,63080,Female,Loyal Customer,66,Personal Travel,Eco,948,3,2,3,3,1,2,3,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +20080,29999,Male,Loyal Customer,30,Business travel,Eco,160,4,2,4,2,4,4,4,4,3,1,2,5,2,4,0,0.0,satisfied +20081,26939,Male,Loyal Customer,14,Personal Travel,Eco,2378,2,5,2,2,2,2,2,2,4,4,4,5,4,2,30,40.0,neutral or dissatisfied +20082,87776,Male,Loyal Customer,39,Business travel,Business,143,4,4,2,4,3,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +20083,66530,Male,Loyal Customer,46,Business travel,Business,2688,1,1,1,1,3,5,5,4,4,5,4,4,4,5,3,0.0,satisfied +20084,33268,Male,Loyal Customer,25,Personal Travel,Eco Plus,101,2,1,2,3,5,2,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +20085,40364,Male,Loyal Customer,51,Business travel,Business,1250,1,1,1,1,2,1,1,2,2,2,2,4,2,4,0,0.0,satisfied +20086,35992,Female,Loyal Customer,47,Personal Travel,Eco,2496,2,2,2,4,2,3,3,2,2,3,3,3,1,3,0,0.0,neutral or dissatisfied +20087,47246,Female,Loyal Customer,48,Business travel,Business,2728,3,2,3,3,4,4,4,3,3,4,3,5,3,5,12,4.0,satisfied +20088,55031,Male,Loyal Customer,52,Business travel,Business,1379,1,1,2,1,5,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +20089,896,Female,Loyal Customer,39,Business travel,Business,1976,1,2,2,2,3,2,2,1,1,1,1,3,1,1,0,13.0,neutral or dissatisfied +20090,87530,Male,Loyal Customer,51,Business travel,Business,1627,2,2,2,2,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +20091,50268,Male,Loyal Customer,51,Business travel,Business,308,1,1,1,1,5,4,4,3,3,4,3,4,3,2,0,0.0,satisfied +20092,47861,Female,disloyal Customer,22,Business travel,Eco,834,2,2,2,5,5,2,5,5,4,1,3,2,5,5,9,1.0,neutral or dissatisfied +20093,111444,Male,Loyal Customer,58,Business travel,Eco,1024,2,3,3,3,2,2,2,2,3,3,3,4,4,2,65,40.0,neutral or dissatisfied +20094,86319,Male,Loyal Customer,46,Personal Travel,Eco Plus,226,1,4,1,3,1,1,1,1,5,4,4,3,5,1,22,34.0,neutral or dissatisfied +20095,111065,Female,Loyal Customer,16,Personal Travel,Eco,319,4,5,5,5,2,5,4,2,5,5,2,5,3,2,0,0.0,neutral or dissatisfied +20096,91913,Male,Loyal Customer,26,Business travel,Eco,2586,3,2,5,2,3,3,2,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +20097,74846,Male,Loyal Customer,39,Personal Travel,Eco Plus,1797,3,5,3,3,1,3,1,1,4,3,4,3,5,1,0,2.0,neutral or dissatisfied +20098,31453,Male,Loyal Customer,68,Personal Travel,Business,853,2,4,2,3,5,5,5,5,5,2,5,4,5,3,19,34.0,neutral or dissatisfied +20099,69659,Female,Loyal Customer,41,Business travel,Business,3787,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +20100,106256,Female,Loyal Customer,53,Business travel,Business,1500,5,5,5,5,4,5,4,4,4,5,4,3,4,5,0,9.0,satisfied +20101,56306,Male,Loyal Customer,40,Business travel,Business,1882,3,3,3,3,5,3,5,4,4,4,4,4,4,3,1,0.0,satisfied +20102,56848,Male,Loyal Customer,38,Business travel,Business,2425,5,5,5,5,4,4,4,4,2,5,5,4,3,4,0,0.0,satisfied +20103,116403,Female,Loyal Customer,11,Personal Travel,Eco,447,2,5,2,3,1,2,1,1,5,2,5,5,5,1,36,34.0,neutral or dissatisfied +20104,60833,Female,disloyal Customer,36,Business travel,Eco,1015,3,2,2,3,4,2,4,4,4,3,4,1,3,4,50,46.0,neutral or dissatisfied +20105,24021,Male,Loyal Customer,44,Business travel,Business,562,2,3,3,3,2,2,2,4,4,2,3,2,1,2,383,386.0,neutral or dissatisfied +20106,105892,Male,Loyal Customer,54,Business travel,Business,283,5,5,5,5,4,4,5,5,5,5,5,5,5,4,21,0.0,satisfied +20107,36567,Female,Loyal Customer,33,Business travel,Business,1185,1,1,1,1,5,3,2,5,5,4,5,2,5,5,52,115.0,satisfied +20108,96679,Female,Loyal Customer,59,Personal Travel,Eco Plus,937,2,4,1,3,2,1,4,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +20109,121177,Male,Loyal Customer,68,Personal Travel,Eco,2402,4,5,4,2,4,4,4,5,3,4,5,4,5,4,28,30.0,neutral or dissatisfied +20110,120204,Female,Loyal Customer,38,Business travel,Business,1430,5,5,5,5,2,4,5,5,5,5,5,3,5,4,13,9.0,satisfied +20111,18354,Male,Loyal Customer,47,Business travel,Business,3605,1,0,0,3,1,4,4,1,1,0,1,2,1,1,39,39.0,neutral or dissatisfied +20112,25748,Female,Loyal Customer,39,Business travel,Business,2847,1,1,1,1,3,4,5,2,2,2,2,1,2,3,15,7.0,satisfied +20113,113083,Female,Loyal Customer,50,Business travel,Eco,479,1,3,3,3,1,3,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +20114,68119,Male,Loyal Customer,26,Personal Travel,Eco,813,2,0,2,2,5,2,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +20115,34569,Female,Loyal Customer,41,Business travel,Business,1598,1,5,1,1,4,4,2,5,5,5,5,2,5,4,0,0.0,satisfied +20116,101410,Female,Loyal Customer,56,Personal Travel,Eco,486,3,2,3,3,3,3,3,5,5,3,5,2,5,2,11,0.0,neutral or dissatisfied +20117,83873,Male,Loyal Customer,56,Business travel,Business,1670,1,1,1,1,4,4,5,4,4,4,4,5,4,5,4,19.0,satisfied +20118,62736,Male,Loyal Customer,29,Business travel,Business,2556,1,1,1,1,2,2,2,4,2,3,4,2,5,2,9,0.0,satisfied +20119,65414,Female,Loyal Customer,60,Business travel,Business,2170,1,1,1,1,2,4,5,2,2,2,2,4,2,5,52,54.0,satisfied +20120,73478,Male,Loyal Customer,66,Personal Travel,Eco,1197,3,4,3,2,2,3,2,2,5,2,1,5,4,2,0,21.0,neutral or dissatisfied +20121,59871,Male,Loyal Customer,29,Business travel,Business,2332,2,1,2,2,4,4,4,4,3,2,5,5,5,4,47,32.0,satisfied +20122,2838,Female,Loyal Customer,59,Business travel,Business,1832,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +20123,30137,Male,Loyal Customer,47,Personal Travel,Eco,548,2,0,2,2,3,2,3,3,2,2,5,4,1,3,0,0.0,neutral or dissatisfied +20124,116780,Female,Loyal Customer,53,Personal Travel,Eco Plus,447,1,3,1,1,1,4,4,5,3,4,2,4,4,4,138,158.0,neutral or dissatisfied +20125,122395,Male,Loyal Customer,12,Personal Travel,Eco,529,4,4,4,3,4,4,4,4,4,5,4,5,5,4,1,7.0,neutral or dissatisfied +20126,122353,Female,Loyal Customer,41,Business travel,Business,1973,1,1,1,1,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +20127,58556,Female,Loyal Customer,62,Personal Travel,Eco,1514,2,4,2,4,2,3,3,3,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +20128,65443,Female,Loyal Customer,40,Business travel,Business,1303,3,5,2,2,4,4,4,3,3,3,3,3,3,3,0,1.0,neutral or dissatisfied +20129,20765,Male,Loyal Customer,9,Business travel,Business,534,1,1,1,1,1,1,1,1,4,5,3,1,4,1,0,0.0,neutral or dissatisfied +20130,60739,Male,Loyal Customer,69,Personal Travel,Eco Plus,1605,3,3,2,4,2,2,2,2,4,5,2,2,3,2,0,0.0,neutral or dissatisfied +20131,85340,Male,Loyal Customer,45,Business travel,Business,874,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +20132,66955,Female,Loyal Customer,54,Business travel,Business,3331,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +20133,60101,Female,disloyal Customer,57,Business travel,Business,1182,3,3,3,2,5,3,5,5,5,3,5,3,4,5,0,0.0,satisfied +20134,30395,Male,Loyal Customer,62,Personal Travel,Eco,862,2,1,2,3,1,2,1,1,2,1,2,4,3,1,7,10.0,neutral or dissatisfied +20135,115772,Female,disloyal Customer,24,Business travel,Eco,308,1,0,1,3,4,1,4,4,3,4,5,3,5,4,2,0.0,neutral or dissatisfied +20136,83400,Male,disloyal Customer,52,Business travel,Business,632,5,5,5,3,1,5,1,1,3,5,4,5,4,1,0,0.0,satisfied +20137,95149,Female,Loyal Customer,36,Personal Travel,Eco,192,3,5,0,4,4,0,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +20138,61765,Male,Loyal Customer,50,Personal Travel,Eco,1635,1,5,1,5,5,1,5,5,2,5,5,1,5,5,22,16.0,neutral or dissatisfied +20139,13032,Male,Loyal Customer,57,Personal Travel,Eco,374,4,4,4,4,5,4,5,5,5,5,5,3,5,5,4,0.0,neutral or dissatisfied +20140,129655,Female,Loyal Customer,42,Business travel,Business,337,5,5,3,5,5,5,5,4,4,4,4,4,4,5,36,38.0,satisfied +20141,8284,Male,Loyal Customer,25,Personal Travel,Eco,530,3,1,3,3,5,3,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +20142,9083,Male,Loyal Customer,17,Personal Travel,Eco,173,1,5,1,1,5,1,5,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +20143,45808,Female,disloyal Customer,37,Business travel,Eco,391,3,2,3,3,3,3,5,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +20144,62785,Male,Loyal Customer,18,Personal Travel,Eco,2504,5,5,5,1,5,5,5,1,3,3,5,5,1,5,0,37.0,satisfied +20145,102664,Male,Loyal Customer,45,Business travel,Business,365,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20146,41507,Female,disloyal Customer,21,Business travel,Eco,715,3,4,4,2,3,4,3,3,1,5,1,4,5,3,4,11.0,neutral or dissatisfied +20147,125104,Female,disloyal Customer,24,Business travel,Eco,361,4,0,5,5,5,5,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +20148,3442,Female,Loyal Customer,40,Personal Travel,Eco,296,2,2,2,4,5,2,4,5,4,1,4,2,3,5,0,0.0,neutral or dissatisfied +20149,25993,Male,Loyal Customer,28,Personal Travel,Eco,577,5,2,5,4,4,2,4,4,4,2,4,3,4,4,0,0.0,satisfied +20150,28780,Male,disloyal Customer,25,Business travel,Business,679,4,0,4,5,3,4,3,3,3,5,5,4,5,3,77,77.0,neutral or dissatisfied +20151,118809,Female,Loyal Customer,8,Personal Travel,Eco,368,3,1,3,2,1,3,1,1,1,5,2,1,1,1,0,0.0,neutral or dissatisfied +20152,73275,Male,Loyal Customer,37,Business travel,Business,2045,5,5,5,5,4,4,5,4,4,4,4,3,4,4,16,0.0,satisfied +20153,36854,Female,Loyal Customer,57,Business travel,Business,273,2,2,2,2,2,5,4,5,5,5,5,3,5,2,0,1.0,satisfied +20154,19554,Female,disloyal Customer,16,Business travel,Eco,173,2,4,2,3,2,2,2,2,2,1,3,4,3,2,105,97.0,neutral or dissatisfied +20155,25067,Male,Loyal Customer,46,Personal Travel,Eco,594,3,1,3,4,2,3,2,2,3,4,3,2,3,2,26,27.0,neutral or dissatisfied +20156,78384,Female,Loyal Customer,45,Business travel,Business,980,2,2,2,2,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +20157,47005,Male,Loyal Customer,24,Personal Travel,Eco Plus,845,2,4,2,4,4,2,4,4,4,2,5,5,5,4,28,31.0,neutral or dissatisfied +20158,123508,Female,Loyal Customer,17,Personal Travel,Eco,2077,2,3,2,4,2,2,2,2,4,3,4,4,3,2,0,0.0,neutral or dissatisfied +20159,57343,Male,Loyal Customer,36,Business travel,Business,2257,4,4,4,4,4,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +20160,77733,Female,Loyal Customer,59,Business travel,Business,731,3,5,5,5,5,4,3,3,3,3,3,1,3,1,17,1.0,neutral or dissatisfied +20161,27384,Male,Loyal Customer,36,Business travel,Business,679,4,1,4,1,5,2,3,4,4,4,4,3,4,1,0,7.0,neutral or dissatisfied +20162,8313,Male,Loyal Customer,29,Business travel,Eco Plus,335,4,5,5,5,4,4,4,4,2,5,3,2,3,4,0,0.0,neutral or dissatisfied +20163,32623,Male,Loyal Customer,79,Business travel,Business,163,3,1,1,1,2,3,3,1,1,2,3,3,1,3,0,0.0,neutral or dissatisfied +20164,17517,Female,Loyal Customer,32,Personal Travel,Eco,341,4,5,4,2,2,4,3,2,4,4,5,3,5,2,118,108.0,neutral or dissatisfied +20165,56600,Male,Loyal Customer,54,Business travel,Business,3706,4,4,4,4,3,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +20166,4158,Female,Loyal Customer,31,Personal Travel,Eco,431,3,4,3,3,3,3,3,3,4,4,5,3,4,3,26,9.0,neutral or dissatisfied +20167,31157,Female,Loyal Customer,48,Personal Travel,Eco,495,5,4,5,3,3,4,5,1,1,5,1,4,1,3,0,0.0,satisfied +20168,83185,Male,Loyal Customer,26,Business travel,Eco Plus,549,3,1,1,1,3,3,3,3,2,4,4,2,4,3,28,14.0,neutral or dissatisfied +20169,81898,Male,disloyal Customer,27,Business travel,Eco,680,2,2,2,4,5,2,5,5,1,3,4,2,3,5,1,0.0,neutral or dissatisfied +20170,55779,Male,Loyal Customer,36,Personal Travel,Eco,599,3,4,3,4,3,3,3,3,4,2,1,4,5,3,0,8.0,neutral or dissatisfied +20171,26941,Female,disloyal Customer,25,Business travel,Eco,1076,5,5,5,3,2,5,1,2,4,5,4,4,5,2,0,0.0,satisfied +20172,29254,Male,disloyal Customer,37,Business travel,Eco,834,2,2,2,1,1,2,1,1,3,1,5,1,4,1,7,6.0,neutral or dissatisfied +20173,54929,Female,Loyal Customer,53,Business travel,Business,1635,2,2,2,2,2,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +20174,122519,Female,disloyal Customer,11,Business travel,Eco,930,3,3,3,3,2,3,3,2,2,5,3,3,4,2,21,15.0,neutral or dissatisfied +20175,6830,Female,Loyal Customer,66,Personal Travel,Eco,235,3,1,3,4,2,3,3,2,2,3,2,1,2,3,26,56.0,neutral or dissatisfied +20176,110565,Female,Loyal Customer,41,Business travel,Business,488,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +20177,123053,Female,Loyal Customer,29,Business travel,Business,1992,3,3,3,3,4,5,4,4,3,5,5,4,4,4,0,0.0,satisfied +20178,9814,Female,Loyal Customer,48,Business travel,Business,1653,3,5,5,5,2,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +20179,2910,Female,disloyal Customer,27,Business travel,Business,409,4,5,5,3,2,5,2,2,3,4,5,5,4,2,0,32.0,neutral or dissatisfied +20180,59583,Male,Loyal Customer,41,Business travel,Business,2733,5,5,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +20181,46877,Female,Loyal Customer,16,Business travel,Eco,848,4,4,4,4,4,4,3,4,1,3,5,3,5,4,0,0.0,satisfied +20182,70350,Male,Loyal Customer,49,Personal Travel,Eco,986,2,5,2,5,2,2,2,2,3,4,4,5,5,2,65,69.0,neutral or dissatisfied +20183,123516,Female,Loyal Customer,69,Personal Travel,Eco,2296,3,5,4,3,4,5,5,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +20184,79144,Male,Loyal Customer,46,Personal Travel,Eco Plus,226,1,1,1,4,2,1,2,2,4,2,4,2,4,2,19,16.0,neutral or dissatisfied +20185,99814,Male,Loyal Customer,58,Business travel,Business,2366,4,3,2,2,2,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +20186,35260,Female,Loyal Customer,48,Business travel,Business,2859,1,4,4,4,3,2,2,1,1,1,1,4,1,1,0,39.0,neutral or dissatisfied +20187,55648,Female,Loyal Customer,54,Business travel,Business,1782,0,0,0,1,5,5,5,1,1,1,1,5,1,3,5,21.0,satisfied +20188,102666,Female,Loyal Customer,36,Business travel,Business,255,5,5,5,5,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +20189,3388,Female,disloyal Customer,21,Business travel,Eco,315,2,0,2,3,4,2,3,4,3,1,4,2,4,4,16,29.0,neutral or dissatisfied +20190,102647,Male,Loyal Customer,47,Business travel,Business,255,0,0,0,4,2,4,5,1,1,1,1,5,1,5,36,27.0,satisfied +20191,53667,Female,disloyal Customer,50,Business travel,Eco,1190,3,3,3,3,5,3,5,5,1,3,1,5,3,5,0,0.0,neutral or dissatisfied +20192,110978,Male,Loyal Customer,47,Business travel,Business,197,3,3,3,3,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +20193,91597,Male,Loyal Customer,18,Personal Travel,Business,1199,3,5,3,1,5,3,5,5,2,2,4,4,1,5,0,0.0,neutral or dissatisfied +20194,124453,Female,disloyal Customer,24,Business travel,Eco,980,4,4,4,3,5,4,5,5,5,2,5,4,5,5,0,0.0,satisfied +20195,105063,Female,Loyal Customer,55,Business travel,Business,1816,2,2,2,2,5,5,5,4,4,4,4,3,4,5,19,7.0,satisfied +20196,116186,Male,Loyal Customer,37,Personal Travel,Eco,372,2,4,3,4,5,3,5,5,2,3,3,4,4,5,2,4.0,neutral or dissatisfied +20197,53128,Male,Loyal Customer,16,Personal Travel,Eco,2065,1,5,2,4,1,2,1,1,4,4,3,5,4,1,2,12.0,neutral or dissatisfied +20198,41844,Female,Loyal Customer,36,Business travel,Eco Plus,462,3,4,4,4,3,5,3,3,1,1,5,4,5,3,0,0.0,satisfied +20199,86900,Male,Loyal Customer,44,Business travel,Business,3489,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,6.0,satisfied +20200,41037,Female,Loyal Customer,30,Business travel,Business,1513,2,2,2,2,5,5,5,5,4,1,1,3,3,5,0,0.0,satisfied +20201,27099,Male,Loyal Customer,51,Business travel,Eco,1721,2,3,3,3,2,2,2,2,4,1,2,3,3,2,0,0.0,neutral or dissatisfied +20202,51740,Female,Loyal Customer,23,Personal Travel,Eco,455,2,4,5,3,2,5,1,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +20203,104064,Female,Loyal Customer,49,Business travel,Business,1262,4,4,1,4,5,5,4,4,4,4,4,3,4,3,13,0.0,satisfied +20204,56245,Male,Loyal Customer,42,Business travel,Eco,2434,3,3,4,4,3,3,3,4,5,4,4,3,1,3,0,0.0,neutral or dissatisfied +20205,95930,Female,Loyal Customer,60,Business travel,Eco,1011,4,1,1,1,5,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +20206,26782,Male,Loyal Customer,71,Business travel,Business,2243,4,1,1,1,5,3,3,4,4,4,4,4,4,3,50,31.0,neutral or dissatisfied +20207,44769,Male,Loyal Customer,46,Business travel,Business,1250,3,2,2,2,3,4,4,3,3,3,3,1,3,3,8,15.0,neutral or dissatisfied +20208,108240,Male,disloyal Customer,45,Business travel,Business,895,2,2,2,4,4,2,4,4,4,3,4,4,4,4,73,63.0,neutral or dissatisfied +20209,19151,Female,Loyal Customer,23,Business travel,Business,3287,0,0,0,5,4,1,1,4,5,3,5,2,5,4,6,0.0,satisfied +20210,660,Male,Loyal Customer,57,Business travel,Business,2360,5,5,5,5,5,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +20211,120348,Female,Loyal Customer,25,Personal Travel,Business,366,3,1,3,4,3,3,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +20212,5262,Female,disloyal Customer,79,Business travel,Eco,351,2,0,2,3,5,2,5,5,4,2,2,5,5,5,0,0.0,neutral or dissatisfied +20213,106485,Male,Loyal Customer,45,Business travel,Business,254,1,1,1,1,5,5,4,5,5,5,5,5,5,3,25,38.0,satisfied +20214,16917,Male,Loyal Customer,41,Business travel,Eco Plus,346,4,3,3,3,4,4,4,4,2,4,4,3,1,4,38,17.0,satisfied +20215,129128,Female,disloyal Customer,25,Business travel,Business,679,5,4,5,1,1,5,1,1,3,5,4,3,5,1,0,9.0,satisfied +20216,6095,Male,Loyal Customer,44,Personal Travel,Eco Plus,690,2,5,2,3,5,2,5,5,2,1,3,5,5,5,3,6.0,neutral or dissatisfied +20217,73869,Female,Loyal Customer,41,Business travel,Business,2342,4,2,4,4,3,3,5,5,5,5,5,5,5,4,2,0.0,satisfied +20218,102300,Male,Loyal Customer,44,Business travel,Business,391,2,2,2,2,2,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +20219,75217,Female,disloyal Customer,33,Business travel,Eco,1442,1,1,1,1,2,1,2,2,4,1,3,3,1,2,95,104.0,neutral or dissatisfied +20220,80983,Female,Loyal Customer,38,Business travel,Business,3228,0,0,0,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20221,35192,Male,disloyal Customer,35,Business travel,Business,1074,2,2,2,2,2,2,3,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +20222,129826,Male,Loyal Customer,9,Personal Travel,Eco,308,4,5,4,3,5,4,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +20223,52613,Male,Loyal Customer,76,Business travel,Eco,160,2,4,4,4,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +20224,54451,Female,Loyal Customer,36,Personal Travel,Eco,844,2,4,2,1,5,2,3,5,5,3,5,4,4,5,48,48.0,neutral or dissatisfied +20225,1378,Female,disloyal Customer,36,Business travel,Eco Plus,134,3,3,3,4,2,3,2,2,2,2,3,4,4,2,0,13.0,neutral or dissatisfied +20226,45909,Male,Loyal Customer,43,Business travel,Business,3183,1,1,1,1,5,4,3,1,1,1,1,3,1,1,102,100.0,neutral or dissatisfied +20227,84817,Male,Loyal Customer,30,Business travel,Business,3596,2,3,3,3,2,2,2,2,1,3,2,2,1,2,0,0.0,neutral or dissatisfied +20228,27267,Male,Loyal Customer,54,Business travel,Business,2937,3,1,1,1,4,4,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +20229,99732,Female,Loyal Customer,40,Business travel,Business,1544,1,1,1,1,4,4,5,5,5,5,5,4,5,3,21,19.0,satisfied +20230,91347,Female,Loyal Customer,39,Personal Travel,Eco Plus,515,1,5,1,4,1,2,2,4,3,5,5,2,3,2,103,137.0,neutral or dissatisfied +20231,94644,Male,Loyal Customer,36,Business travel,Business,1771,3,4,2,4,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +20232,90390,Female,Loyal Customer,70,Personal Travel,Business,240,3,4,3,1,4,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +20233,80106,Female,Loyal Customer,31,Business travel,Business,1626,3,5,5,5,3,3,3,3,2,4,2,3,2,3,4,0.0,neutral or dissatisfied +20234,76278,Male,disloyal Customer,37,Business travel,Eco,427,1,0,1,3,3,1,3,3,4,3,5,4,1,3,0,0.0,neutral or dissatisfied +20235,2649,Female,Loyal Customer,53,Business travel,Business,3525,4,4,4,4,4,5,4,4,4,4,4,3,4,4,63,61.0,satisfied +20236,61050,Male,disloyal Customer,34,Business travel,Eco,1302,3,3,3,3,4,3,3,4,4,1,4,3,4,4,110,100.0,neutral or dissatisfied +20237,115561,Male,Loyal Customer,47,Business travel,Business,2772,3,3,2,2,2,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +20238,27959,Female,Loyal Customer,31,Business travel,Eco,1774,1,5,5,5,1,1,1,1,2,3,1,2,3,1,0,0.0,neutral or dissatisfied +20239,922,Female,Loyal Customer,60,Business travel,Business,309,3,4,3,4,1,3,3,3,3,3,3,1,3,4,0,2.0,neutral or dissatisfied +20240,87805,Male,Loyal Customer,58,Business travel,Business,3952,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +20241,38885,Female,Loyal Customer,7,Personal Travel,Eco,261,2,1,2,4,4,2,4,4,4,2,3,1,4,4,0,0.0,neutral or dissatisfied +20242,34917,Female,Loyal Customer,38,Business travel,Eco,395,5,3,3,3,5,5,5,5,3,5,1,3,3,5,0,0.0,satisfied +20243,104098,Male,Loyal Customer,8,Personal Travel,Business,297,1,4,1,1,4,1,4,4,4,3,5,5,4,4,7,0.0,neutral or dissatisfied +20244,60944,Male,disloyal Customer,20,Business travel,Eco,888,2,2,2,4,3,2,3,3,1,4,4,4,3,3,0,0.0,neutral or dissatisfied +20245,77915,Female,Loyal Customer,46,Business travel,Business,3065,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +20246,96878,Female,Loyal Customer,44,Personal Travel,Eco,849,2,4,2,1,5,5,4,1,1,2,1,4,1,5,45,44.0,neutral or dissatisfied +20247,116439,Female,Loyal Customer,34,Personal Travel,Eco,308,2,5,4,3,4,4,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +20248,62581,Male,Loyal Customer,44,Business travel,Eco,1744,2,1,2,2,2,2,2,2,1,4,4,2,4,2,0,0.0,neutral or dissatisfied +20249,18711,Female,Loyal Customer,33,Personal Travel,Eco Plus,192,5,4,5,4,4,5,3,4,5,3,4,4,4,4,0,0.0,satisfied +20250,21281,Female,Loyal Customer,41,Business travel,Eco,620,5,3,3,3,5,5,5,5,1,2,1,3,5,5,1,0.0,satisfied +20251,65389,Male,Loyal Customer,7,Personal Travel,Eco,631,0,3,0,3,5,0,5,5,1,5,3,1,4,5,0,0.0,satisfied +20252,84086,Female,Loyal Customer,53,Personal Travel,Eco,757,1,4,1,3,4,5,5,3,3,1,5,5,3,4,0,26.0,neutral or dissatisfied +20253,41358,Female,disloyal Customer,24,Business travel,Eco,641,1,0,1,5,3,1,3,3,3,2,1,3,1,3,0,0.0,neutral or dissatisfied +20254,54339,Male,Loyal Customer,57,Personal Travel,Eco,1597,2,1,2,3,3,2,1,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +20255,18594,Female,Loyal Customer,39,Business travel,Business,192,3,3,3,3,1,4,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +20256,83384,Female,Loyal Customer,54,Business travel,Eco Plus,1124,3,3,3,3,5,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +20257,19541,Male,Loyal Customer,38,Business travel,Eco,173,5,3,3,3,5,5,5,5,3,2,3,4,5,5,36,33.0,satisfied +20258,379,Female,Loyal Customer,42,Business travel,Business,247,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +20259,123332,Male,Loyal Customer,25,Personal Travel,Eco Plus,631,3,5,2,1,3,2,3,3,3,4,4,4,4,3,3,7.0,neutral or dissatisfied +20260,31379,Male,Loyal Customer,35,Business travel,Business,2105,3,3,3,3,1,3,2,5,5,5,5,1,5,1,11,5.0,satisfied +20261,34096,Female,Loyal Customer,56,Business travel,Business,1046,4,5,5,5,1,3,4,4,4,4,4,1,4,3,52,53.0,neutral or dissatisfied +20262,16771,Female,Loyal Customer,44,Business travel,Business,642,2,2,2,2,4,4,4,2,2,2,2,1,2,4,0,2.0,neutral or dissatisfied +20263,125333,Female,Loyal Customer,46,Business travel,Business,599,3,3,3,3,2,4,4,4,4,5,4,4,4,4,42,30.0,satisfied +20264,53923,Female,disloyal Customer,38,Business travel,Eco Plus,140,2,2,2,1,4,2,4,4,1,1,5,3,4,4,0,0.0,neutral or dissatisfied +20265,75436,Female,disloyal Customer,14,Business travel,Eco,1498,3,3,3,4,1,3,1,1,5,3,3,5,4,1,0,0.0,neutral or dissatisfied +20266,49981,Female,Loyal Customer,26,Business travel,Business,110,5,5,5,5,5,5,3,5,5,5,2,1,2,5,3,6.0,satisfied +20267,115017,Female,Loyal Customer,47,Business travel,Business,1516,3,3,3,3,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +20268,8805,Male,Loyal Customer,19,Business travel,Eco,522,1,2,2,2,1,1,1,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +20269,98811,Female,Loyal Customer,42,Business travel,Business,763,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +20270,121571,Female,disloyal Customer,35,Business travel,Business,912,2,2,2,1,3,2,4,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +20271,68616,Female,Loyal Customer,41,Business travel,Business,237,5,5,4,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20272,76496,Female,Loyal Customer,44,Business travel,Business,516,4,4,4,4,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +20273,48897,Female,Loyal Customer,23,Business travel,Business,77,2,2,2,2,4,4,5,4,5,1,3,1,4,4,0,0.0,satisfied +20274,11952,Male,Loyal Customer,43,Personal Travel,Eco,781,2,3,2,3,3,2,3,3,3,3,4,4,3,3,38,48.0,neutral or dissatisfied +20275,127039,Female,Loyal Customer,66,Business travel,Business,2323,2,3,3,3,3,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +20276,104006,Female,Loyal Customer,56,Personal Travel,Eco,1363,3,4,2,4,3,3,3,5,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +20277,54318,Female,disloyal Customer,22,Business travel,Business,1597,2,2,2,3,5,2,5,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +20278,121412,Male,Loyal Customer,50,Business travel,Business,2600,1,2,1,1,3,5,4,4,4,4,4,5,4,3,16,22.0,satisfied +20279,79101,Female,Loyal Customer,26,Personal Travel,Eco,226,1,5,1,3,2,1,3,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +20280,32218,Male,Loyal Customer,44,Business travel,Eco,216,5,3,4,3,5,5,5,5,3,2,2,2,1,5,0,0.0,satisfied +20281,47511,Female,Loyal Customer,24,Personal Travel,Eco,599,1,5,1,2,2,1,2,2,3,4,3,4,5,2,41,27.0,neutral or dissatisfied +20282,90662,Male,Loyal Customer,60,Business travel,Business,2912,1,4,4,4,5,3,4,1,1,1,1,4,1,1,1,8.0,neutral or dissatisfied +20283,47139,Female,Loyal Customer,18,Business travel,Business,3711,2,2,2,2,4,4,4,4,3,4,4,3,2,4,0,0.0,satisfied +20284,87661,Female,Loyal Customer,49,Business travel,Business,3747,1,1,5,1,5,5,5,4,3,5,5,5,5,5,159,149.0,satisfied +20285,24136,Male,Loyal Customer,49,Business travel,Business,2000,1,1,2,1,4,4,5,5,5,5,5,5,5,5,64,56.0,satisfied +20286,80303,Female,Loyal Customer,20,Business travel,Business,2209,1,1,1,1,5,5,5,5,3,3,5,5,4,5,0,23.0,satisfied +20287,108540,Female,Loyal Customer,48,Business travel,Business,512,1,1,1,1,5,4,4,4,4,5,4,3,4,4,1,0.0,satisfied +20288,58637,Male,Loyal Customer,52,Business travel,Business,2455,3,3,3,3,2,4,4,4,4,4,4,4,4,5,5,0.0,satisfied +20289,6982,Female,Loyal Customer,55,Business travel,Business,3571,2,4,4,4,5,4,3,2,2,2,2,4,2,2,25,18.0,neutral or dissatisfied +20290,121746,Male,Loyal Customer,36,Business travel,Eco Plus,1475,3,4,4,4,3,3,3,3,3,3,4,1,4,3,72,55.0,neutral or dissatisfied +20291,60098,Male,Loyal Customer,27,Business travel,Business,1867,1,1,5,1,5,5,5,5,3,3,5,4,4,5,4,9.0,satisfied +20292,103057,Male,disloyal Customer,39,Business travel,Eco,546,3,2,3,2,4,3,4,4,1,1,2,2,3,4,22,42.0,neutral or dissatisfied +20293,53079,Male,Loyal Customer,58,Personal Travel,Eco Plus,1190,1,5,1,2,1,1,1,1,5,3,5,3,4,1,4,1.0,neutral or dissatisfied +20294,88871,Female,disloyal Customer,27,Business travel,Business,859,1,2,2,2,1,2,1,1,3,3,5,4,4,1,0,4.0,neutral or dissatisfied +20295,5389,Male,Loyal Customer,13,Personal Travel,Eco,785,1,4,1,2,5,1,5,5,3,2,4,5,5,5,13,11.0,neutral or dissatisfied +20296,26578,Male,Loyal Customer,27,Business travel,Eco,581,4,1,1,1,4,4,4,4,3,3,3,2,1,4,0,0.0,satisfied +20297,120380,Male,Loyal Customer,54,Business travel,Business,366,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,34.0,satisfied +20298,40407,Female,Loyal Customer,50,Business travel,Business,3951,1,1,5,1,1,5,2,4,4,4,5,3,4,4,0,3.0,satisfied +20299,109797,Male,Loyal Customer,48,Business travel,Business,3141,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +20300,78812,Female,Loyal Customer,45,Personal Travel,Eco,528,2,4,2,4,4,3,4,3,3,2,3,1,3,4,0,8.0,neutral or dissatisfied +20301,3558,Female,disloyal Customer,39,Business travel,Business,227,2,2,2,2,3,2,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +20302,53963,Male,disloyal Customer,38,Business travel,Eco,925,2,2,2,4,4,2,4,4,1,3,4,4,4,4,0,0.0,neutral or dissatisfied +20303,24640,Female,Loyal Customer,26,Business travel,Eco Plus,526,4,2,2,2,4,4,5,4,5,1,1,2,2,4,1,1.0,satisfied +20304,119434,Male,Loyal Customer,8,Personal Travel,Eco,399,1,3,1,3,3,1,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +20305,22553,Male,Loyal Customer,59,Business travel,Business,223,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +20306,75752,Male,disloyal Customer,22,Business travel,Eco,868,1,1,1,4,4,1,4,4,2,2,1,5,1,4,0,0.0,neutral or dissatisfied +20307,126295,Male,Loyal Customer,13,Personal Travel,Eco,631,2,4,2,5,5,2,5,5,1,4,4,5,5,5,0,0.0,neutral or dissatisfied +20308,25632,Female,Loyal Customer,60,Business travel,Business,666,1,1,1,1,1,1,1,4,4,4,4,4,4,2,0,0.0,satisfied +20309,125558,Male,Loyal Customer,58,Business travel,Eco,226,2,3,3,3,3,2,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +20310,75885,Female,Loyal Customer,26,Business travel,Business,603,2,2,2,2,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +20311,45906,Male,Loyal Customer,36,Business travel,Business,3901,3,1,1,1,3,2,2,3,3,3,3,1,3,2,75,71.0,neutral or dissatisfied +20312,43420,Female,Loyal Customer,12,Personal Travel,Eco Plus,436,3,4,3,1,3,3,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +20313,66264,Female,Loyal Customer,61,Personal Travel,Eco,550,2,0,2,4,2,4,4,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +20314,83649,Male,disloyal Customer,25,Business travel,Business,577,1,4,1,2,5,1,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +20315,104642,Female,Loyal Customer,50,Business travel,Business,1754,1,1,5,1,4,5,5,2,2,2,2,3,2,3,7,0.0,satisfied +20316,1066,Male,Loyal Customer,28,Personal Travel,Eco,89,4,5,4,3,1,4,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +20317,66314,Male,Loyal Customer,46,Business travel,Business,2798,4,5,5,5,2,3,3,4,4,4,4,4,4,2,0,37.0,neutral or dissatisfied +20318,29459,Male,Loyal Customer,19,Personal Travel,Eco,421,4,4,4,1,3,4,1,3,5,3,5,3,3,3,0,3.0,neutral or dissatisfied +20319,86614,Male,Loyal Customer,57,Business travel,Business,2035,1,1,1,1,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +20320,57062,Female,Loyal Customer,8,Personal Travel,Eco,2133,3,5,3,1,2,3,3,2,4,3,4,3,5,2,2,28.0,neutral or dissatisfied +20321,90318,Female,disloyal Customer,22,Business travel,Business,442,4,0,4,2,1,4,1,1,4,3,5,5,5,1,39,37.0,satisfied +20322,58861,Female,Loyal Customer,47,Business travel,Business,1955,3,3,3,3,2,4,5,4,4,4,4,3,4,3,14,6.0,satisfied +20323,80063,Male,Loyal Customer,18,Personal Travel,Eco,1076,3,4,3,4,4,3,4,4,4,2,4,3,4,4,104,124.0,neutral or dissatisfied +20324,6131,Male,Loyal Customer,33,Business travel,Business,1637,5,5,3,5,5,5,5,5,4,2,5,5,4,5,5,0.0,satisfied +20325,99024,Female,Loyal Customer,57,Business travel,Business,2977,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20326,128476,Male,Loyal Customer,25,Personal Travel,Eco,651,3,3,3,3,4,3,4,4,1,2,4,4,3,4,36,50.0,neutral or dissatisfied +20327,71366,Male,Loyal Customer,32,Business travel,Business,2962,1,1,4,1,5,5,5,5,4,5,5,5,4,5,5,0.0,satisfied +20328,52057,Female,disloyal Customer,38,Business travel,Eco,351,3,0,3,3,1,3,3,1,3,1,4,1,3,1,0,0.0,neutral or dissatisfied +20329,30684,Male,disloyal Customer,42,Business travel,Eco,680,5,5,5,2,4,5,4,4,4,3,5,2,5,4,0,0.0,satisfied +20330,53504,Female,Loyal Customer,17,Personal Travel,Eco,2419,5,2,5,3,5,1,1,4,5,3,4,1,3,1,0,3.0,satisfied +20331,28126,Female,Loyal Customer,45,Business travel,Business,550,3,2,2,2,5,3,3,3,3,3,3,3,3,3,67,49.0,neutral or dissatisfied +20332,101481,Female,Loyal Customer,38,Business travel,Business,345,2,2,2,2,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +20333,60313,Male,Loyal Customer,36,Personal Travel,Eco Plus,406,1,5,1,1,2,1,2,2,3,2,4,3,5,2,5,9.0,neutral or dissatisfied +20334,88479,Female,disloyal Customer,17,Business travel,Eco,270,4,3,4,4,3,4,3,3,2,4,3,2,3,3,0,3.0,neutral or dissatisfied +20335,48924,Male,Loyal Customer,36,Business travel,Business,266,3,3,3,3,5,5,2,5,5,5,5,3,5,5,3,6.0,satisfied +20336,57844,Male,Loyal Customer,66,Personal Travel,Eco,1491,3,5,3,1,5,3,5,5,3,2,4,4,1,5,15,29.0,neutral or dissatisfied +20337,8872,Male,disloyal Customer,20,Business travel,Eco,622,4,5,3,1,1,3,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +20338,23134,Male,Loyal Customer,37,Business travel,Business,1680,2,2,2,2,3,1,3,4,4,4,5,4,4,2,0,0.0,satisfied +20339,5376,Male,disloyal Customer,22,Business travel,Eco,812,3,3,3,4,5,3,3,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +20340,22229,Male,Loyal Customer,36,Business travel,Business,3378,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +20341,96037,Female,Loyal Customer,51,Business travel,Business,1687,3,1,5,1,4,4,3,3,3,3,3,1,3,2,89,74.0,neutral or dissatisfied +20342,6710,Female,Loyal Customer,17,Personal Travel,Eco,438,3,5,3,3,5,3,5,5,5,3,5,5,4,5,0,7.0,neutral or dissatisfied +20343,38944,Male,Loyal Customer,26,Personal Travel,Eco,162,5,5,5,5,1,5,4,1,4,5,5,5,5,1,0,0.0,satisfied +20344,46235,Male,Loyal Customer,26,Business travel,Business,752,5,5,5,5,3,4,3,3,4,2,3,3,3,3,13,4.0,satisfied +20345,111855,Male,Loyal Customer,57,Business travel,Business,1965,3,3,3,3,3,4,5,2,2,2,2,3,2,4,18,15.0,satisfied +20346,109852,Female,Loyal Customer,49,Business travel,Business,1653,1,1,3,1,3,4,3,1,1,1,1,1,1,3,51,17.0,neutral or dissatisfied +20347,26724,Male,Loyal Customer,31,Business travel,Eco Plus,581,5,4,3,4,5,5,5,5,3,3,3,3,3,5,0,0.0,satisfied +20348,34789,Female,Loyal Customer,64,Personal Travel,Eco,264,1,1,1,3,5,2,2,2,2,1,2,1,2,4,28,31.0,neutral or dissatisfied +20349,7522,Male,Loyal Customer,26,Business travel,Business,3578,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +20350,81582,Female,Loyal Customer,56,Business travel,Business,503,4,5,4,4,5,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +20351,12282,Female,Loyal Customer,35,Business travel,Eco,253,5,5,5,5,5,5,5,5,4,1,2,2,1,5,5,27.0,satisfied +20352,71618,Male,Loyal Customer,47,Business travel,Business,1005,3,5,5,5,5,2,2,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +20353,2512,Female,Loyal Customer,12,Personal Travel,Business,280,3,5,3,3,2,3,2,2,5,5,5,4,5,2,42,45.0,neutral or dissatisfied +20354,66391,Female,disloyal Customer,30,Business travel,Business,1562,5,5,5,3,5,5,5,5,3,5,5,3,5,5,0,0.0,satisfied +20355,129582,Female,Loyal Customer,46,Business travel,Business,308,0,0,0,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +20356,104939,Male,Loyal Customer,40,Business travel,Business,3662,1,1,1,1,4,5,5,5,5,5,5,5,5,3,3,0.0,satisfied +20357,107772,Male,Loyal Customer,38,Business travel,Eco Plus,251,3,2,2,2,3,3,3,4,3,4,3,3,4,3,189,239.0,neutral or dissatisfied +20358,31162,Female,disloyal Customer,27,Business travel,Eco,1201,4,4,4,3,2,4,2,2,3,3,2,4,4,2,6,6.0,neutral or dissatisfied +20359,92380,Male,Loyal Customer,15,Personal Travel,Business,2139,4,4,4,1,1,4,1,1,3,3,4,5,4,1,0,0.0,satisfied +20360,99167,Male,Loyal Customer,30,Personal Travel,Eco,986,4,5,4,1,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +20361,10151,Female,Loyal Customer,51,Personal Travel,Eco,1157,3,4,3,2,2,4,5,1,1,3,4,4,1,5,0,0.0,neutral or dissatisfied +20362,53987,Female,Loyal Customer,30,Business travel,Eco,1825,4,5,4,5,4,4,4,4,2,1,5,2,5,4,0,0.0,satisfied +20363,95848,Female,disloyal Customer,52,Business travel,Business,759,2,2,2,3,4,2,1,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +20364,69402,Male,Loyal Customer,24,Business travel,Business,3480,4,4,4,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +20365,126541,Female,disloyal Customer,29,Business travel,Business,644,5,5,5,2,4,5,4,4,5,2,5,4,4,4,0,0.0,satisfied +20366,15226,Male,disloyal Customer,27,Business travel,Eco,529,4,5,4,2,2,4,2,2,1,3,4,5,4,2,0,0.0,satisfied +20367,18407,Female,Loyal Customer,59,Business travel,Business,284,3,2,2,2,1,4,4,3,3,3,3,1,3,3,24,35.0,neutral or dissatisfied +20368,74443,Male,Loyal Customer,25,Business travel,Business,1171,1,1,1,1,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +20369,37550,Female,Loyal Customer,22,Business travel,Business,1069,1,2,2,2,1,1,1,1,1,2,3,4,4,1,21,32.0,neutral or dissatisfied +20370,120730,Male,disloyal Customer,22,Business travel,Eco,1089,5,5,5,5,5,5,3,5,4,4,4,5,5,5,0,0.0,satisfied +20371,27840,Female,Loyal Customer,36,Personal Travel,Eco,1448,2,1,2,2,3,2,3,3,1,2,2,2,3,3,37,28.0,neutral or dissatisfied +20372,6988,Female,disloyal Customer,32,Business travel,Eco,436,1,3,1,3,1,1,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +20373,25815,Male,disloyal Customer,37,Business travel,Eco,1010,3,3,3,3,3,3,3,3,3,5,4,3,3,3,0,22.0,neutral or dissatisfied +20374,77166,Male,Loyal Customer,12,Personal Travel,Eco,1450,2,2,2,2,1,2,1,1,3,5,2,3,3,1,0,0.0,neutral or dissatisfied +20375,58647,Male,Loyal Customer,45,Business travel,Eco,867,1,4,4,4,1,1,1,1,1,4,4,4,4,1,86,68.0,neutral or dissatisfied +20376,88050,Female,disloyal Customer,27,Business travel,Business,581,5,5,5,5,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +20377,33403,Male,Loyal Customer,42,Business travel,Business,2614,2,2,2,2,4,4,4,4,2,3,5,4,5,4,31,45.0,satisfied +20378,5278,Male,Loyal Customer,57,Personal Travel,Eco,351,3,2,3,4,2,3,4,2,3,2,4,3,3,2,18,8.0,neutral or dissatisfied +20379,69896,Female,Loyal Customer,56,Business travel,Business,1514,4,2,4,4,3,5,5,5,5,5,5,3,5,3,3,4.0,satisfied +20380,84573,Female,Loyal Customer,33,Business travel,Eco Plus,2556,4,3,2,3,4,4,4,4,1,5,5,5,1,4,43,22.0,satisfied +20381,56484,Male,Loyal Customer,63,Business travel,Business,746,2,3,3,3,2,2,2,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +20382,78393,Male,Loyal Customer,34,Personal Travel,Eco,726,0,1,0,3,4,0,4,4,1,1,2,3,2,4,0,0.0,satisfied +20383,118828,Female,disloyal Customer,36,Business travel,Eco Plus,325,3,4,4,3,4,4,5,4,2,1,3,2,4,4,8,0.0,neutral or dissatisfied +20384,53377,Female,disloyal Customer,19,Business travel,Eco,1452,3,3,3,4,3,5,5,1,1,3,3,5,3,5,174,162.0,neutral or dissatisfied +20385,127153,Female,Loyal Customer,17,Personal Travel,Eco,304,4,4,4,3,3,4,3,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +20386,10717,Female,Loyal Customer,55,Business travel,Business,429,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +20387,102513,Male,Loyal Customer,38,Personal Travel,Eco,236,3,5,3,3,5,3,5,5,4,2,4,4,4,5,11,2.0,neutral or dissatisfied +20388,96693,Female,disloyal Customer,34,Business travel,Business,696,2,2,2,1,1,2,1,1,3,2,4,3,4,1,3,1.0,neutral or dissatisfied +20389,111215,Male,Loyal Customer,27,Business travel,Business,1546,3,1,1,1,3,3,3,4,3,3,3,3,3,3,173,169.0,neutral or dissatisfied +20390,79128,Female,Loyal Customer,29,Personal Travel,Eco,356,2,2,2,4,5,2,5,5,4,3,4,1,4,5,0,0.0,neutral or dissatisfied +20391,98406,Male,Loyal Customer,44,Business travel,Business,2649,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +20392,66708,Male,Loyal Customer,24,Business travel,Business,402,1,4,2,4,1,1,1,1,3,5,2,4,1,1,18,27.0,neutral or dissatisfied +20393,83728,Male,Loyal Customer,28,Business travel,Eco Plus,269,3,1,4,4,3,3,3,3,4,3,2,2,3,3,3,12.0,neutral or dissatisfied +20394,15310,Female,Loyal Customer,30,Business travel,Business,2205,2,2,2,2,2,2,2,2,5,5,4,5,3,2,0,0.0,satisfied +20395,21765,Male,Loyal Customer,45,Business travel,Business,3878,1,1,1,1,3,3,4,4,4,4,4,1,4,1,0,0.0,satisfied +20396,21874,Male,Loyal Customer,55,Business travel,Eco,503,4,5,5,5,4,4,4,4,3,4,5,1,4,4,0,0.0,satisfied +20397,104396,Male,Loyal Customer,47,Business travel,Business,3116,1,3,1,1,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +20398,87599,Female,Loyal Customer,60,Personal Travel,Eco,432,3,4,4,3,4,5,5,3,3,4,3,3,3,4,37,25.0,neutral or dissatisfied +20399,24205,Female,Loyal Customer,39,Business travel,Eco,147,4,5,4,4,4,4,4,4,5,4,1,5,4,4,0,0.0,satisfied +20400,115411,Female,Loyal Customer,28,Business travel,Business,480,5,2,5,5,5,5,5,5,3,3,4,4,5,5,2,0.0,satisfied +20401,19448,Female,Loyal Customer,59,Business travel,Eco,363,2,4,4,4,1,3,3,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +20402,108654,Female,Loyal Customer,51,Business travel,Business,1747,5,5,5,5,3,5,5,4,4,4,4,4,4,4,58,47.0,satisfied +20403,117058,Female,disloyal Customer,34,Business travel,Eco,338,1,3,2,4,3,2,3,3,2,2,3,4,3,3,0,0.0,neutral or dissatisfied +20404,101747,Male,disloyal Customer,21,Business travel,Eco,1590,4,4,4,1,5,4,1,5,3,2,3,3,5,5,0,0.0,satisfied +20405,91863,Female,disloyal Customer,35,Business travel,Eco,731,3,3,3,3,1,3,1,1,1,1,5,2,5,1,0,0.0,neutral or dissatisfied +20406,109821,Male,Loyal Customer,46,Business travel,Business,2444,2,2,2,2,5,5,4,5,5,5,5,5,5,4,6,0.0,satisfied +20407,69174,Female,Loyal Customer,51,Business travel,Eco,187,3,5,5,5,2,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +20408,109710,Male,disloyal Customer,24,Business travel,Eco,587,4,5,4,5,1,4,1,1,5,4,4,3,4,1,45,46.0,neutral or dissatisfied +20409,33171,Male,Loyal Customer,36,Personal Travel,Eco,101,4,5,4,4,2,4,4,2,5,5,5,5,4,2,9,15.0,neutral or dissatisfied +20410,25918,Male,Loyal Customer,37,Business travel,Business,3925,5,5,5,5,5,1,3,4,4,4,4,1,4,2,2,5.0,satisfied +20411,70562,Male,Loyal Customer,52,Business travel,Eco,858,4,4,4,4,5,4,5,5,1,2,2,4,4,5,0,0.0,satisfied +20412,71670,Female,Loyal Customer,22,Personal Travel,Eco,1182,3,4,2,5,4,2,4,4,5,5,4,4,4,4,9,4.0,neutral or dissatisfied +20413,1171,Female,Loyal Customer,70,Personal Travel,Eco,164,3,5,3,4,2,5,4,1,1,3,1,5,1,3,0,9.0,neutral or dissatisfied +20414,70736,Male,Loyal Customer,33,Personal Travel,Eco,675,4,4,4,1,1,4,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +20415,68578,Male,Loyal Customer,63,Business travel,Eco,1016,3,4,4,4,3,3,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +20416,1280,Female,Loyal Customer,42,Personal Travel,Eco,113,3,2,3,4,4,3,4,3,3,3,3,3,3,1,28,22.0,neutral or dissatisfied +20417,65696,Female,Loyal Customer,30,Business travel,Business,936,3,4,4,4,3,3,3,3,2,1,2,2,2,3,20,20.0,neutral or dissatisfied +20418,14500,Male,disloyal Customer,25,Business travel,Eco,328,4,4,4,4,1,4,1,1,5,2,4,3,2,1,0,0.0,satisfied +20419,56636,Female,disloyal Customer,31,Business travel,Eco,1068,3,3,3,3,5,3,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +20420,94756,Male,Loyal Customer,70,Business travel,Business,458,4,4,4,4,3,4,5,4,4,5,4,4,4,5,0,4.0,satisfied +20421,70209,Male,Loyal Customer,28,Personal Travel,Eco,403,2,5,2,4,4,2,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +20422,1706,Female,Loyal Customer,48,Business travel,Business,2460,3,3,3,3,5,5,5,3,3,3,3,3,3,5,55,66.0,satisfied +20423,73760,Male,Loyal Customer,62,Personal Travel,Eco,204,4,5,4,1,2,4,2,2,3,1,1,4,2,2,0,0.0,neutral or dissatisfied +20424,29931,Female,Loyal Customer,36,Business travel,Business,571,1,1,1,1,4,2,5,5,5,5,5,2,5,3,0,6.0,satisfied +20425,49282,Male,Loyal Customer,37,Business travel,Business,3932,1,1,1,1,5,2,5,5,5,5,5,5,5,5,0,0.0,satisfied +20426,25625,Male,Loyal Customer,32,Business travel,Business,666,5,4,4,4,5,4,5,5,1,3,2,4,3,5,72,53.0,neutral or dissatisfied +20427,106000,Male,Loyal Customer,29,Business travel,Business,1999,1,3,3,3,1,1,1,1,1,4,3,1,2,1,0,15.0,neutral or dissatisfied +20428,83089,Female,Loyal Customer,44,Business travel,Eco,727,2,1,1,1,4,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +20429,10212,Female,Loyal Customer,59,Business travel,Business,2392,5,5,5,5,5,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +20430,87532,Female,Loyal Customer,17,Business travel,Eco Plus,321,2,5,5,5,2,2,3,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +20431,46724,Female,Loyal Customer,60,Personal Travel,Eco,125,3,2,3,2,2,3,3,1,1,3,1,2,1,1,66,63.0,neutral or dissatisfied +20432,96079,Male,Loyal Customer,60,Personal Travel,Eco,795,1,5,1,2,2,1,5,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +20433,45692,Female,Loyal Customer,17,Business travel,Eco,896,4,2,2,2,4,4,5,4,4,5,2,1,2,4,0,0.0,satisfied +20434,74195,Male,Loyal Customer,65,Personal Travel,Eco,641,2,5,2,3,4,2,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +20435,88924,Male,disloyal Customer,29,Business travel,Business,1312,4,4,4,3,1,4,1,1,5,3,4,4,5,1,11,4.0,satisfied +20436,97356,Female,Loyal Customer,73,Business travel,Business,1697,3,3,3,3,4,3,4,5,5,5,5,1,5,1,3,0.0,satisfied +20437,64192,Male,Loyal Customer,45,Business travel,Business,853,1,1,1,1,4,5,4,3,3,4,3,4,3,4,67,78.0,satisfied +20438,42480,Female,Loyal Customer,47,Business travel,Eco Plus,429,2,5,5,5,2,2,2,2,5,3,4,2,3,2,155,173.0,neutral or dissatisfied +20439,28398,Male,Loyal Customer,33,Business travel,Business,1709,3,3,3,3,5,5,5,5,4,2,3,1,3,5,0,0.0,satisfied +20440,40599,Female,Loyal Customer,15,Personal Travel,Eco,216,1,1,1,3,4,1,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +20441,37088,Male,Loyal Customer,41,Personal Travel,Business,1189,3,5,3,3,4,3,5,5,5,3,5,5,5,5,0,8.0,neutral or dissatisfied +20442,52989,Female,Loyal Customer,36,Business travel,Business,1208,3,3,3,3,5,5,5,5,5,4,5,4,5,4,2,15.0,satisfied +20443,65622,Female,Loyal Customer,20,Personal Travel,Eco,175,3,5,3,1,4,3,4,4,4,2,4,3,5,4,50,45.0,neutral or dissatisfied +20444,60358,Male,Loyal Customer,45,Business travel,Business,1452,5,4,5,5,5,5,5,5,5,5,5,5,5,3,7,0.0,satisfied +20445,127369,Male,Loyal Customer,47,Business travel,Business,1009,2,2,1,2,5,4,4,2,2,2,2,5,2,4,10,0.0,satisfied +20446,95013,Male,Loyal Customer,29,Personal Travel,Eco,239,3,5,0,2,1,0,1,1,3,1,4,4,5,1,0,0.0,neutral or dissatisfied +20447,4185,Female,Loyal Customer,49,Business travel,Business,1781,5,5,5,5,3,4,4,4,4,4,4,3,4,4,96,113.0,satisfied +20448,47352,Male,Loyal Customer,28,Business travel,Business,3324,3,3,3,3,4,4,4,4,5,1,1,5,1,4,32,28.0,satisfied +20449,57847,Female,disloyal Customer,24,Business travel,Business,2457,0,4,0,1,0,2,2,3,2,3,4,2,3,2,0,0.0,satisfied +20450,48636,Male,disloyal Customer,29,Business travel,Business,110,2,2,2,4,4,2,1,4,3,2,5,3,4,4,16,20.0,neutral or dissatisfied +20451,55907,Male,Loyal Customer,32,Business travel,Business,733,1,4,4,4,1,1,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +20452,78677,Female,Loyal Customer,16,Business travel,Business,761,4,4,4,4,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +20453,95555,Male,Loyal Customer,42,Personal Travel,Eco Plus,239,4,1,4,4,2,4,2,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +20454,38973,Female,disloyal Customer,36,Business travel,Eco,260,2,0,2,5,1,2,4,1,2,5,1,1,3,1,28,37.0,neutral or dissatisfied +20455,43425,Male,Loyal Customer,64,Personal Travel,Eco Plus,347,1,4,1,3,5,1,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +20456,24720,Male,Loyal Customer,56,Business travel,Business,406,5,5,5,5,4,2,3,4,4,4,4,2,4,2,0,0.0,satisfied +20457,69680,Male,Loyal Customer,25,Personal Travel,Eco,569,1,4,1,1,2,1,2,2,4,3,5,5,4,2,0,11.0,neutral or dissatisfied +20458,22078,Male,disloyal Customer,17,Business travel,Eco,304,2,0,2,4,2,2,2,2,1,5,4,3,4,2,41,39.0,neutral or dissatisfied +20459,9736,Female,Loyal Customer,60,Personal Travel,Eco,926,4,5,3,4,4,5,5,2,2,3,2,4,2,5,48,40.0,neutral or dissatisfied +20460,30882,Female,Loyal Customer,19,Personal Travel,Eco,1546,2,4,2,2,5,2,4,5,5,2,5,3,4,5,0,7.0,neutral or dissatisfied +20461,27353,Male,Loyal Customer,29,Business travel,Business,697,5,5,5,5,2,2,2,2,3,4,3,4,5,2,0,0.0,satisfied +20462,53670,Male,Loyal Customer,39,Business travel,Business,1208,2,2,2,2,4,3,3,5,5,5,5,3,5,2,0,0.0,satisfied +20463,84003,Female,Loyal Customer,43,Personal Travel,Eco,321,2,1,2,3,2,2,2,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +20464,76105,Female,Loyal Customer,59,Business travel,Business,3041,3,3,3,3,5,4,5,3,3,2,3,5,3,3,0,0.0,satisfied +20465,36715,Male,Loyal Customer,8,Business travel,Eco Plus,1185,0,3,0,4,2,0,2,2,4,4,2,4,5,2,7,0.0,satisfied +20466,93226,Female,Loyal Customer,51,Business travel,Eco,1060,5,1,1,1,3,4,4,5,5,5,5,5,5,4,7,3.0,satisfied +20467,4277,Female,Loyal Customer,39,Business travel,Business,502,5,5,3,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +20468,71614,Female,Loyal Customer,26,Business travel,Business,3604,1,4,4,4,1,1,1,1,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +20469,65083,Female,Loyal Customer,65,Personal Travel,Eco,247,1,5,1,2,5,4,5,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +20470,85947,Female,Loyal Customer,45,Business travel,Business,447,2,2,2,2,2,5,5,4,4,4,4,5,4,3,7,0.0,satisfied +20471,125530,Male,Loyal Customer,58,Business travel,Business,1960,4,4,4,4,4,4,4,5,5,5,5,3,5,5,27,20.0,satisfied +20472,11491,Male,Loyal Customer,67,Personal Travel,Eco Plus,482,2,5,2,3,2,2,2,2,2,2,3,2,5,2,0,0.0,neutral or dissatisfied +20473,49832,Male,Loyal Customer,51,Business travel,Eco,86,4,4,4,4,4,4,4,4,4,2,1,2,3,4,14,1.0,satisfied +20474,13300,Male,Loyal Customer,42,Personal Travel,Eco Plus,468,2,5,3,4,5,3,5,5,4,3,5,5,4,5,38,34.0,neutral or dissatisfied +20475,73253,Male,Loyal Customer,26,Business travel,Business,675,2,2,2,2,2,2,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +20476,20566,Male,Loyal Customer,46,Business travel,Business,2799,3,5,2,5,3,4,3,3,3,2,3,3,3,4,0,20.0,neutral or dissatisfied +20477,61358,Male,Loyal Customer,54,Business travel,Business,3235,2,2,2,2,4,5,5,4,4,4,4,4,4,3,108,80.0,satisfied +20478,83774,Male,Loyal Customer,56,Business travel,Business,3643,3,3,3,3,4,5,4,5,5,5,5,3,5,3,49,36.0,satisfied +20479,43839,Female,Loyal Customer,32,Business travel,Eco,114,0,0,0,1,1,0,1,1,4,5,2,3,1,1,0,10.0,satisfied +20480,89687,Female,Loyal Customer,49,Business travel,Business,2551,3,5,5,5,2,3,3,2,4,3,4,3,4,3,123,133.0,neutral or dissatisfied +20481,34653,Female,Loyal Customer,41,Business travel,Eco Plus,427,4,4,4,4,2,2,1,4,4,4,4,4,4,4,0,0.0,satisfied +20482,49171,Female,Loyal Customer,24,Business travel,Eco,447,5,5,5,5,5,5,3,5,2,1,3,5,3,5,43,44.0,satisfied +20483,70963,Male,disloyal Customer,36,Business travel,Business,402,4,4,4,4,4,4,2,4,2,4,4,2,4,4,2,0.0,neutral or dissatisfied +20484,108225,Female,disloyal Customer,38,Business travel,Business,495,4,4,4,4,3,4,3,3,1,5,4,1,3,3,8,34.0,neutral or dissatisfied +20485,128489,Male,Loyal Customer,48,Personal Travel,Eco,338,0,5,0,3,4,0,3,4,4,4,5,5,4,4,0,3.0,satisfied +20486,24105,Male,Loyal Customer,48,Business travel,Business,584,1,1,1,1,5,4,3,4,4,4,4,5,4,5,0,0.0,satisfied +20487,57169,Female,Loyal Customer,46,Business travel,Business,2227,1,1,1,1,5,5,5,5,5,5,5,4,5,3,12,12.0,satisfied +20488,20278,Male,Loyal Customer,67,Personal Travel,Eco,137,4,0,0,5,4,0,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +20489,38189,Male,Loyal Customer,45,Personal Travel,Eco,1121,4,5,4,2,5,4,5,5,4,3,5,5,5,5,0,0.0,satisfied +20490,23515,Female,Loyal Customer,58,Business travel,Business,1679,3,2,2,2,4,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +20491,68205,Female,disloyal Customer,24,Business travel,Eco,432,4,0,4,5,2,4,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +20492,121035,Male,Loyal Customer,18,Personal Travel,Eco,920,5,5,4,3,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +20493,124238,Male,disloyal Customer,43,Business travel,Business,1916,2,2,2,1,4,2,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +20494,32120,Female,Loyal Customer,37,Business travel,Eco,163,4,2,3,2,4,5,4,4,1,4,3,5,2,4,11,14.0,satisfied +20495,49553,Female,disloyal Customer,38,Business travel,Eco,363,3,0,3,2,4,3,4,4,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +20496,8542,Female,Loyal Customer,38,Business travel,Business,3461,0,4,0,2,5,5,5,2,2,2,2,5,2,5,45,36.0,satisfied +20497,78163,Female,Loyal Customer,56,Business travel,Business,192,0,4,0,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20498,39849,Male,Loyal Customer,48,Business travel,Business,184,1,1,1,1,5,3,3,5,5,5,3,2,5,1,0,0.0,satisfied +20499,22296,Female,Loyal Customer,53,Business travel,Business,238,0,0,0,4,3,5,4,1,1,1,1,1,1,1,0,0.0,satisfied +20500,128056,Male,Loyal Customer,68,Personal Travel,Eco Plus,735,3,4,3,4,1,3,1,1,4,3,5,5,4,1,0,4.0,neutral or dissatisfied +20501,89398,Male,disloyal Customer,27,Business travel,Business,134,2,1,1,2,2,1,3,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +20502,46261,Male,Loyal Customer,36,Personal Travel,Eco,679,2,3,2,4,2,1,5,3,4,3,4,5,1,5,133,143.0,neutral or dissatisfied +20503,41822,Female,Loyal Customer,27,Personal Travel,Eco,257,5,4,5,4,5,5,1,5,4,2,5,3,5,5,0,0.0,satisfied +20504,17523,Male,Loyal Customer,29,Personal Travel,Eco,352,1,5,1,5,3,1,1,3,3,3,5,4,5,3,77,70.0,neutral or dissatisfied +20505,4599,Male,Loyal Customer,19,Personal Travel,Eco,416,2,4,2,4,4,2,4,4,1,1,1,2,3,4,0,25.0,neutral or dissatisfied +20506,93790,Female,Loyal Customer,52,Business travel,Business,3145,5,5,5,5,3,5,5,2,2,2,2,3,2,3,61,45.0,satisfied +20507,113828,Male,Loyal Customer,29,Personal Travel,Eco Plus,223,4,4,4,4,1,4,1,1,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +20508,83556,Male,Loyal Customer,67,Business travel,Business,365,3,2,2,2,5,3,4,3,3,3,3,2,3,4,0,7.0,neutral or dissatisfied +20509,43554,Male,Loyal Customer,10,Personal Travel,Eco,438,1,2,3,3,5,3,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +20510,25987,Female,disloyal Customer,26,Business travel,Eco,577,2,0,2,4,1,2,1,1,2,3,1,1,5,1,3,0.0,neutral or dissatisfied +20511,21409,Female,Loyal Customer,65,Business travel,Business,2996,1,1,1,1,5,1,1,5,5,5,5,3,5,3,16,21.0,satisfied +20512,14937,Female,Loyal Customer,49,Business travel,Business,2808,3,3,3,3,3,3,4,5,5,4,5,4,5,5,4,27.0,satisfied +20513,100427,Female,Loyal Customer,27,Business travel,Business,1620,4,5,4,4,4,4,4,4,3,5,3,4,4,4,52,13.0,neutral or dissatisfied +20514,49953,Male,Loyal Customer,40,Business travel,Eco,421,2,4,4,4,2,2,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +20515,92605,Female,Loyal Customer,68,Personal Travel,Eco,2342,3,1,3,4,5,4,4,4,4,3,4,4,4,4,1,0.0,neutral or dissatisfied +20516,99645,Male,Loyal Customer,54,Business travel,Business,1670,4,4,4,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +20517,112562,Male,Loyal Customer,40,Personal Travel,Eco Plus,853,1,1,1,2,5,1,5,5,1,1,2,4,3,5,20,18.0,neutral or dissatisfied +20518,45845,Female,Loyal Customer,67,Personal Travel,Eco,216,1,0,1,3,2,4,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +20519,48210,Female,Loyal Customer,25,Personal Travel,Eco,173,4,5,4,2,3,4,3,3,1,2,1,5,5,3,0,0.0,satisfied +20520,52618,Female,disloyal Customer,17,Business travel,Eco,110,1,1,1,3,5,1,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +20521,70137,Female,Loyal Customer,55,Personal Travel,Eco,460,3,2,3,3,2,2,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +20522,8932,Female,Loyal Customer,53,Personal Travel,Eco,984,1,4,1,1,4,4,5,2,2,1,2,4,2,3,49,34.0,neutral or dissatisfied +20523,10864,Female,Loyal Customer,51,Business travel,Business,74,1,1,1,1,5,4,4,1,1,1,1,4,1,4,27,25.0,neutral or dissatisfied +20524,26765,Female,Loyal Customer,44,Personal Travel,Eco,859,3,3,3,1,5,3,2,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +20525,107542,Female,disloyal Customer,21,Business travel,Business,761,4,0,5,3,5,5,1,5,5,3,4,4,5,5,0,0.0,satisfied +20526,95235,Male,Loyal Customer,19,Personal Travel,Eco,248,4,5,4,4,3,4,3,3,5,5,5,5,5,3,19,16.0,neutral or dissatisfied +20527,59773,Female,disloyal Customer,24,Business travel,Business,927,0,0,0,2,5,0,5,5,3,1,3,3,3,5,0,0.0,satisfied +20528,29291,Female,Loyal Customer,57,Business travel,Business,859,1,1,1,1,2,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +20529,64974,Male,Loyal Customer,39,Business travel,Business,247,3,3,3,3,1,1,2,4,4,4,4,1,4,2,58,57.0,satisfied +20530,50565,Female,Loyal Customer,36,Personal Travel,Eco,109,4,5,4,2,5,4,5,5,3,2,4,4,4,5,0,0.0,satisfied +20531,48468,Male,disloyal Customer,27,Business travel,Eco,844,1,1,1,2,2,1,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +20532,102441,Female,Loyal Customer,36,Personal Travel,Eco,236,3,4,3,2,5,3,5,5,5,4,4,2,1,5,0,0.0,neutral or dissatisfied +20533,80677,Male,Loyal Customer,25,Personal Travel,Eco,821,1,4,1,4,2,1,1,2,3,2,3,3,3,2,17,3.0,neutral or dissatisfied +20534,52312,Male,Loyal Customer,18,Business travel,Business,3389,3,4,4,4,3,3,3,3,3,4,3,1,4,3,35,21.0,neutral or dissatisfied +20535,100934,Female,Loyal Customer,63,Business travel,Business,838,4,4,2,4,4,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +20536,54856,Female,disloyal Customer,26,Business travel,Business,862,3,2,2,2,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +20537,30094,Male,Loyal Customer,24,Personal Travel,Eco,261,1,5,1,1,4,1,3,4,2,4,3,4,2,4,0,0.0,neutral or dissatisfied +20538,35942,Female,Loyal Customer,45,Business travel,Business,3989,2,2,2,2,1,4,4,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +20539,125966,Female,Loyal Customer,23,Business travel,Business,2560,2,4,4,4,2,2,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +20540,83222,Female,disloyal Customer,39,Business travel,Business,1979,2,2,2,3,1,2,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +20541,99436,Female,Loyal Customer,48,Personal Travel,Eco,337,2,5,4,2,4,4,5,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +20542,21697,Female,Loyal Customer,9,Personal Travel,Eco,746,2,1,3,1,4,3,4,4,4,1,1,3,1,4,20,7.0,neutral or dissatisfied +20543,39148,Female,Loyal Customer,69,Personal Travel,Eco,119,2,5,2,2,2,5,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +20544,11423,Female,Loyal Customer,60,Business travel,Business,3130,4,4,4,4,4,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +20545,8332,Male,Loyal Customer,51,Business travel,Business,2690,5,5,5,5,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +20546,28704,Male,Loyal Customer,48,Personal Travel,Eco,2172,1,1,1,1,4,1,4,4,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +20547,126326,Male,Loyal Customer,28,Personal Travel,Eco,507,4,1,4,2,3,4,3,3,2,3,3,1,3,3,6,4.0,neutral or dissatisfied +20548,122783,Female,Loyal Customer,48,Business travel,Business,2897,4,4,4,4,5,5,4,4,4,4,4,4,4,3,7,26.0,satisfied +20549,91474,Female,Loyal Customer,36,Personal Travel,Eco,859,4,3,3,3,4,3,4,4,2,5,5,4,3,4,4,8.0,neutral or dissatisfied +20550,80684,Male,disloyal Customer,28,Business travel,Business,874,5,5,5,5,5,5,2,5,4,5,4,5,5,5,7,5.0,satisfied +20551,24850,Female,Loyal Customer,41,Business travel,Eco Plus,829,4,1,1,1,1,1,1,4,4,4,4,1,4,4,0,5.0,satisfied +20552,103755,Male,disloyal Customer,9,Business travel,Eco,484,2,2,1,4,2,1,2,2,3,4,4,4,4,2,0,1.0,neutral or dissatisfied +20553,58289,Male,Loyal Customer,11,Personal Travel,Eco,678,2,4,3,2,5,3,5,5,5,4,4,4,4,5,4,8.0,neutral or dissatisfied +20554,129212,Female,Loyal Customer,28,Personal Travel,Eco,2419,3,4,3,3,2,3,2,2,3,4,3,5,5,2,0,0.0,neutral or dissatisfied +20555,23039,Female,Loyal Customer,57,Personal Travel,Eco,1020,2,5,2,1,1,4,2,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +20556,75882,Male,Loyal Customer,55,Personal Travel,Eco Plus,1972,3,2,3,2,5,3,5,5,1,3,2,4,3,5,1,0.0,neutral or dissatisfied +20557,20955,Male,disloyal Customer,13,Business travel,Eco,721,2,2,2,4,4,2,4,4,1,2,4,3,3,4,0,0.0,neutral or dissatisfied +20558,67410,Male,Loyal Customer,55,Business travel,Business,3452,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20559,48302,Male,disloyal Customer,39,Business travel,Eco,1499,4,4,4,4,4,4,4,4,5,4,4,5,2,4,0,12.0,satisfied +20560,774,Female,Loyal Customer,56,Business travel,Business,3886,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +20561,42690,Female,Loyal Customer,48,Business travel,Business,2079,1,1,1,1,3,5,3,5,5,5,5,1,5,3,0,0.0,satisfied +20562,55945,Male,Loyal Customer,54,Business travel,Business,1536,5,5,4,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +20563,66190,Female,Loyal Customer,43,Business travel,Business,460,3,3,3,3,5,4,5,4,4,4,4,4,4,4,33,28.0,satisfied +20564,85368,Male,Loyal Customer,15,Personal Travel,Eco Plus,1282,1,4,1,4,3,1,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +20565,66985,Male,Loyal Customer,19,Business travel,Business,1121,5,5,5,5,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +20566,33047,Male,Loyal Customer,34,Personal Travel,Eco,101,1,3,1,4,2,1,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +20567,77101,Male,Loyal Customer,56,Business travel,Business,1481,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +20568,38712,Male,Loyal Customer,56,Personal Travel,Eco,2583,5,4,5,4,5,5,5,5,4,3,3,2,2,5,0,2.0,satisfied +20569,19059,Male,Loyal Customer,56,Business travel,Business,1852,2,2,2,2,5,1,4,4,4,5,4,4,4,1,66,56.0,satisfied +20570,56595,Female,Loyal Customer,42,Business travel,Eco,937,3,2,2,2,1,4,4,3,3,3,3,2,3,2,23,24.0,neutral or dissatisfied +20571,120281,Female,Loyal Customer,45,Business travel,Eco,1176,4,3,3,3,3,1,4,4,4,4,4,4,4,3,61,49.0,satisfied +20572,64825,Female,Loyal Customer,58,Business travel,Business,2163,4,3,3,3,2,2,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +20573,108250,Female,Loyal Customer,52,Business travel,Business,2654,4,5,4,4,2,4,5,4,4,4,4,5,4,5,14,10.0,satisfied +20574,79069,Male,disloyal Customer,36,Business travel,Eco,306,1,1,1,3,3,1,3,3,2,1,4,4,3,3,36,20.0,neutral or dissatisfied +20575,105058,Male,Loyal Customer,42,Business travel,Business,1797,0,0,0,4,4,4,5,2,2,2,2,5,2,3,19,24.0,satisfied +20576,66562,Female,Loyal Customer,14,Personal Travel,Eco,328,3,4,3,3,5,3,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +20577,106621,Female,Loyal Customer,49,Personal Travel,Business,306,2,5,2,1,2,5,4,1,1,2,1,5,1,4,9,5.0,neutral or dissatisfied +20578,123550,Female,Loyal Customer,25,Business travel,Eco,1773,2,5,5,5,2,2,2,2,3,2,4,3,4,2,61,33.0,neutral or dissatisfied +20579,21683,Female,Loyal Customer,35,Business travel,Business,2122,3,3,3,3,3,4,1,4,4,4,4,5,4,2,0,0.0,satisfied +20580,73703,Female,disloyal Customer,23,Business travel,Eco,204,3,3,4,3,1,4,1,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +20581,5889,Male,Loyal Customer,47,Business travel,Business,67,5,5,4,5,2,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +20582,122034,Male,Loyal Customer,41,Business travel,Eco,130,4,1,1,1,4,4,4,4,3,1,3,3,2,4,51,38.0,neutral or dissatisfied +20583,102901,Male,Loyal Customer,42,Personal Travel,Eco,1037,4,5,4,1,5,4,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +20584,8298,Male,Loyal Customer,44,Business travel,Business,2408,2,5,2,2,5,4,4,5,5,5,5,4,5,5,0,2.0,satisfied +20585,28051,Male,Loyal Customer,42,Personal Travel,Eco,1739,4,5,4,5,5,4,1,5,3,3,3,4,5,5,0,49.0,satisfied +20586,47047,Male,Loyal Customer,47,Business travel,Eco,438,4,4,4,4,4,4,4,4,2,2,4,1,3,4,0,0.0,neutral or dissatisfied +20587,36668,Female,Loyal Customer,21,Personal Travel,Eco,1249,3,5,3,2,5,3,3,5,5,4,4,5,4,5,81,109.0,neutral or dissatisfied +20588,73945,Male,disloyal Customer,30,Business travel,Eco,883,1,1,1,4,2,1,2,2,2,1,3,3,3,2,23,6.0,neutral or dissatisfied +20589,126846,Female,Loyal Customer,41,Business travel,Business,2125,2,4,5,4,4,2,3,2,2,2,2,1,2,3,19,0.0,neutral or dissatisfied +20590,25636,Female,Loyal Customer,39,Business travel,Eco,266,3,1,1,1,3,4,3,3,5,4,3,1,3,3,0,0.0,satisfied +20591,88715,Male,Loyal Customer,26,Personal Travel,Eco,250,3,4,0,4,5,0,5,5,4,5,4,3,4,5,27,27.0,neutral or dissatisfied +20592,33916,Female,disloyal Customer,29,Business travel,Eco,636,1,0,1,4,3,1,3,3,5,2,1,5,4,3,0,0.0,neutral or dissatisfied +20593,60152,Female,Loyal Customer,37,Personal Travel,Eco,1005,2,5,2,4,1,2,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +20594,15806,Female,Loyal Customer,63,Personal Travel,Eco,282,5,5,5,5,2,2,3,1,1,5,1,3,1,1,55,45.0,satisfied +20595,14378,Female,Loyal Customer,52,Business travel,Business,1670,5,5,5,5,5,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +20596,41598,Male,Loyal Customer,7,Personal Travel,Eco,1235,3,0,3,3,1,3,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +20597,75784,Female,Loyal Customer,46,Personal Travel,Eco,868,0,4,0,4,5,1,3,1,1,0,1,2,1,4,0,0.0,satisfied +20598,108301,Male,Loyal Customer,29,Business travel,Business,1728,1,1,1,1,5,4,5,5,5,4,5,3,4,5,52,36.0,satisfied +20599,12815,Female,disloyal Customer,28,Business travel,Eco,817,1,1,1,5,4,1,4,4,5,2,4,1,5,4,0,0.0,neutral or dissatisfied +20600,29176,Female,disloyal Customer,29,Business travel,Eco Plus,1050,1,1,1,3,4,1,4,4,5,1,5,2,4,4,0,0.0,neutral or dissatisfied +20601,24391,Male,Loyal Customer,65,Personal Travel,Eco,669,3,4,4,2,1,4,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +20602,64428,Female,Loyal Customer,45,Business travel,Business,3502,5,5,4,5,3,4,4,4,4,5,4,4,4,3,93,87.0,satisfied +20603,84149,Male,Loyal Customer,54,Business travel,Business,1355,4,4,4,4,5,4,5,5,5,5,5,5,5,5,46,53.0,satisfied +20604,10105,Female,Loyal Customer,36,Business travel,Business,391,2,2,2,2,3,5,5,4,4,4,4,3,4,3,5,0.0,satisfied +20605,89646,Female,Loyal Customer,53,Business travel,Business,950,1,0,0,4,4,4,4,3,3,0,3,4,3,2,38,37.0,neutral or dissatisfied +20606,111929,Male,disloyal Customer,20,Business travel,Eco,770,2,2,2,2,4,2,5,4,3,2,5,3,5,4,5,0.0,neutral or dissatisfied +20607,6400,Male,Loyal Customer,12,Personal Travel,Eco,240,4,4,0,1,2,0,5,2,4,3,4,4,4,2,10,3.0,satisfied +20608,115819,Female,Loyal Customer,51,Business travel,Business,446,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +20609,60208,Male,Loyal Customer,60,Business travel,Business,1703,2,2,2,2,4,4,5,3,3,3,3,5,3,4,26,25.0,satisfied +20610,83960,Male,Loyal Customer,53,Business travel,Business,321,4,4,4,4,3,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +20611,99131,Female,Loyal Customer,38,Personal Travel,Eco,237,2,5,2,2,5,2,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +20612,40196,Male,Loyal Customer,57,Business travel,Eco,347,5,2,2,2,5,5,5,5,2,5,3,1,3,5,0,0.0,satisfied +20613,19187,Male,Loyal Customer,39,Business travel,Business,2633,3,3,3,3,1,1,5,5,5,5,5,4,5,1,71,75.0,satisfied +20614,125453,Male,disloyal Customer,30,Business travel,Business,2979,1,1,1,2,1,5,3,4,5,3,5,3,3,3,0,0.0,neutral or dissatisfied +20615,68747,Male,disloyal Customer,26,Business travel,Business,461,1,1,1,3,2,1,5,2,2,4,4,4,4,2,1,0.0,neutral or dissatisfied +20616,81051,Male,Loyal Customer,37,Personal Travel,Eco,1399,1,5,1,3,3,1,3,3,3,2,5,5,4,3,3,0.0,neutral or dissatisfied +20617,111634,Female,Loyal Customer,58,Business travel,Business,1558,1,1,1,1,4,5,5,4,4,5,4,5,4,5,47,28.0,satisfied +20618,97133,Female,Loyal Customer,56,Business travel,Business,1390,3,3,3,3,2,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +20619,58517,Female,Loyal Customer,15,Personal Travel,Eco,719,3,5,3,4,1,3,2,1,4,2,5,4,5,1,6,0.0,neutral or dissatisfied +20620,34328,Female,Loyal Customer,40,Business travel,Eco,846,4,1,5,1,4,4,4,4,2,3,5,5,5,4,0,0.0,satisfied +20621,46422,Female,Loyal Customer,69,Business travel,Business,458,5,5,5,5,3,2,4,4,4,4,4,3,4,4,0,0.0,satisfied +20622,14080,Female,disloyal Customer,39,Business travel,Business,399,3,3,3,1,3,3,3,3,2,3,5,1,5,3,0,0.0,neutral or dissatisfied +20623,13013,Female,Loyal Customer,34,Business travel,Business,2091,2,2,5,2,2,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +20624,10955,Female,Loyal Customer,60,Business travel,Eco,316,1,2,2,2,5,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +20625,98804,Female,disloyal Customer,30,Business travel,Business,763,5,5,5,1,1,5,1,1,3,4,5,5,4,1,2,0.0,satisfied +20626,37774,Female,Loyal Customer,27,Business travel,Eco Plus,950,3,5,5,5,3,3,3,3,2,5,3,4,3,3,57,41.0,neutral or dissatisfied +20627,70462,Male,Loyal Customer,39,Business travel,Business,3861,5,5,5,5,5,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +20628,68823,Male,disloyal Customer,34,Business travel,Business,1995,3,3,3,5,3,3,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +20629,14778,Female,Loyal Customer,42,Business travel,Business,2277,1,1,2,1,4,2,4,5,5,5,5,3,5,5,0,2.0,satisfied +20630,83239,Female,Loyal Customer,58,Business travel,Business,1979,5,5,5,5,2,3,5,5,5,5,5,3,5,4,51,45.0,satisfied +20631,92054,Male,Loyal Customer,34,Business travel,Business,1589,4,4,4,4,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +20632,18503,Female,Loyal Customer,37,Business travel,Eco,305,3,1,1,1,3,4,3,3,4,3,2,5,3,3,0,0.0,satisfied +20633,51544,Male,Loyal Customer,38,Business travel,Business,3996,4,4,4,4,1,3,2,4,4,3,4,4,4,1,6,2.0,satisfied +20634,64552,Male,Loyal Customer,45,Business travel,Business,469,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +20635,123721,Female,Loyal Customer,55,Business travel,Business,2004,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +20636,105926,Female,Loyal Customer,39,Business travel,Business,1491,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +20637,36554,Male,disloyal Customer,22,Business travel,Eco,1249,4,4,4,4,2,4,2,2,5,1,5,4,5,2,0,0.0,satisfied +20638,82013,Female,disloyal Customer,39,Business travel,Eco,1135,2,2,2,3,1,2,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +20639,40576,Male,disloyal Customer,44,Business travel,Eco,391,1,3,1,4,3,1,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +20640,40710,Female,Loyal Customer,24,Business travel,Business,3216,2,3,3,3,2,2,2,2,5,1,1,2,2,2,10,0.0,neutral or dissatisfied +20641,122994,Male,Loyal Customer,31,Business travel,Business,3652,1,0,0,3,1,0,1,1,3,5,3,3,4,1,0,7.0,neutral or dissatisfied +20642,124595,Female,Loyal Customer,37,Personal Travel,Eco,500,1,5,1,2,3,1,3,3,5,2,4,5,4,3,1,0.0,neutral or dissatisfied +20643,117656,Male,Loyal Customer,51,Business travel,Business,1449,3,3,3,3,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +20644,21052,Female,disloyal Customer,48,Business travel,Eco,214,4,4,4,3,4,4,4,4,5,1,1,2,5,4,0,0.0,satisfied +20645,102797,Male,Loyal Customer,55,Personal Travel,Business,342,5,1,2,3,2,4,3,4,4,4,4,3,4,3,138,127.0,satisfied +20646,10237,Female,Loyal Customer,43,Business travel,Business,3149,4,4,4,4,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +20647,61592,Male,Loyal Customer,53,Business travel,Business,1635,2,2,2,2,5,4,4,5,5,5,5,4,5,3,29,13.0,satisfied +20648,90982,Male,Loyal Customer,40,Business travel,Business,1846,3,5,5,5,2,4,4,3,3,3,3,4,3,2,0,14.0,neutral or dissatisfied +20649,91144,Female,Loyal Customer,67,Personal Travel,Eco,594,4,2,5,3,2,3,3,3,3,5,4,4,3,1,1,0.0,neutral or dissatisfied +20650,69950,Female,Loyal Customer,40,Personal Travel,Eco,2174,2,4,1,2,2,1,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +20651,35143,Female,disloyal Customer,24,Business travel,Business,828,0,0,1,2,5,1,5,5,3,1,4,3,4,5,0,0.0,satisfied +20652,45363,Female,Loyal Customer,37,Personal Travel,Eco,150,1,4,1,3,4,1,4,4,4,2,4,3,4,4,49,109.0,neutral or dissatisfied +20653,54567,Male,Loyal Customer,39,Business travel,Eco Plus,925,3,2,2,2,3,5,3,3,3,1,2,2,3,3,92,75.0,satisfied +20654,127550,Female,Loyal Customer,41,Personal Travel,Eco,1009,3,4,3,4,5,3,5,5,5,5,5,3,4,5,0,3.0,neutral or dissatisfied +20655,26743,Male,Loyal Customer,57,Personal Travel,Eco,319,4,3,4,5,1,4,1,1,1,4,1,4,2,1,49,45.0,neutral or dissatisfied +20656,96896,Male,Loyal Customer,35,Personal Travel,Eco,994,3,5,3,3,2,3,2,2,5,3,5,4,5,2,66,35.0,neutral or dissatisfied +20657,113669,Male,Loyal Customer,41,Personal Travel,Eco,397,3,5,3,4,1,3,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +20658,118959,Male,Loyal Customer,30,Personal Travel,Eco,682,2,2,2,3,1,2,5,1,3,4,3,4,3,1,61,63.0,neutral or dissatisfied +20659,66957,Female,Loyal Customer,55,Business travel,Business,2147,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +20660,42985,Male,Loyal Customer,57,Business travel,Business,2009,3,3,3,3,2,2,2,5,5,5,4,4,5,4,29,26.0,satisfied +20661,85805,Female,disloyal Customer,47,Business travel,Eco,266,2,0,3,4,5,3,4,5,1,1,5,3,3,5,1,0.0,neutral or dissatisfied +20662,30971,Female,Loyal Customer,36,Business travel,Eco,1476,2,5,5,5,2,2,2,2,1,4,5,1,5,2,0,0.0,satisfied +20663,43903,Female,Loyal Customer,49,Personal Travel,Eco,144,1,1,1,3,4,2,3,3,3,1,3,2,3,1,65,77.0,neutral or dissatisfied +20664,81970,Male,disloyal Customer,55,Business travel,Business,1576,5,5,5,1,2,5,2,2,4,4,5,4,5,2,0,0.0,satisfied +20665,103297,Female,disloyal Customer,37,Business travel,Business,1371,4,5,5,3,3,5,4,3,4,3,4,3,5,3,46,,satisfied +20666,128741,Male,Loyal Customer,42,Business travel,Business,2521,5,5,1,5,5,5,5,3,4,5,4,5,5,5,0,6.0,satisfied +20667,60134,Male,Loyal Customer,42,Business travel,Business,3463,2,2,2,2,4,4,4,3,4,4,4,4,5,4,184,175.0,satisfied +20668,39259,Female,Loyal Customer,49,Business travel,Eco,268,2,5,5,5,1,3,3,2,2,2,2,1,2,2,6,0.0,neutral or dissatisfied +20669,80454,Male,Loyal Customer,36,Business travel,Business,1299,2,2,2,2,5,4,5,5,5,5,5,3,5,5,45,29.0,satisfied +20670,68434,Male,disloyal Customer,25,Business travel,Eco,1045,3,2,2,3,5,2,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +20671,36589,Female,Loyal Customer,35,Business travel,Eco,1091,5,2,2,2,5,5,5,5,1,3,3,4,2,5,0,0.0,satisfied +20672,3342,Male,Loyal Customer,47,Business travel,Business,3250,3,3,2,3,4,5,5,4,4,4,4,5,4,5,0,9.0,satisfied +20673,46512,Male,Loyal Customer,39,Business travel,Business,3337,3,3,3,3,3,3,5,5,5,4,5,1,5,5,0,0.0,satisfied +20674,81023,Female,Loyal Customer,42,Business travel,Business,1399,1,1,1,1,3,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +20675,53916,Male,Loyal Customer,59,Personal Travel,Eco,191,1,4,1,4,5,1,5,5,1,1,3,1,3,5,7,0.0,neutral or dissatisfied +20676,122044,Female,Loyal Customer,39,Business travel,Business,2923,3,5,4,5,4,3,3,2,2,2,3,3,2,4,0,6.0,neutral or dissatisfied +20677,28105,Female,Loyal Customer,39,Business travel,Business,2838,4,4,4,4,2,1,5,4,4,4,4,1,4,3,0,0.0,satisfied +20678,48130,Female,Loyal Customer,36,Business travel,Business,3169,1,1,1,1,4,2,5,4,4,4,4,5,4,2,0,0.0,satisfied +20679,19153,Female,Loyal Customer,36,Business travel,Business,3065,4,4,4,4,2,1,2,4,4,4,4,4,4,3,0,27.0,satisfied +20680,129748,Male,Loyal Customer,15,Business travel,Business,337,5,5,5,5,5,5,5,5,4,1,3,1,4,5,0,0.0,satisfied +20681,39931,Male,disloyal Customer,37,Business travel,Business,1086,2,2,2,3,1,2,2,1,4,5,4,3,3,1,12,0.0,neutral or dissatisfied +20682,37476,Female,Loyal Customer,48,Business travel,Eco,950,1,3,3,3,1,4,4,1,1,1,1,1,1,1,78,65.0,neutral or dissatisfied +20683,68443,Female,Loyal Customer,39,Business travel,Business,2853,3,1,1,1,4,4,3,3,3,3,3,3,3,3,9,15.0,neutral or dissatisfied +20684,117756,Female,Loyal Customer,45,Business travel,Eco,1670,4,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +20685,70972,Male,Loyal Customer,46,Business travel,Business,802,4,4,4,4,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20686,109276,Female,Loyal Customer,43,Business travel,Business,1072,4,4,4,4,4,4,4,4,4,4,4,3,4,4,37,12.0,satisfied +20687,50360,Female,Loyal Customer,55,Business travel,Eco,250,4,5,5,5,1,1,1,4,4,4,4,5,4,2,6,0.0,satisfied +20688,30378,Female,Loyal Customer,28,Business travel,Eco,641,2,4,4,4,2,2,2,2,1,3,3,2,3,2,12,21.0,neutral or dissatisfied +20689,84717,Female,Loyal Customer,50,Personal Travel,Business,516,2,3,2,3,2,4,4,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +20690,73930,Male,disloyal Customer,8,Business travel,Eco,2342,3,3,3,3,2,3,2,2,1,4,2,3,3,2,0,0.0,neutral or dissatisfied +20691,36517,Male,Loyal Customer,26,Business travel,Business,2640,4,4,4,4,5,5,5,5,5,4,3,2,4,5,16,44.0,satisfied +20692,2084,Male,Loyal Customer,15,Personal Travel,Eco,785,1,5,1,5,1,1,4,1,5,5,4,5,4,1,0,0.0,neutral or dissatisfied +20693,58595,Female,Loyal Customer,36,Business travel,Eco,334,5,1,1,1,5,5,5,5,3,3,2,4,2,5,5,0.0,satisfied +20694,107684,Female,disloyal Customer,68,Business travel,Eco,251,3,2,3,3,3,3,2,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +20695,75940,Male,Loyal Customer,46,Business travel,Business,1572,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +20696,73572,Male,Loyal Customer,42,Business travel,Business,2476,3,3,3,3,3,5,4,4,4,4,4,3,4,5,27,44.0,satisfied +20697,34730,Male,disloyal Customer,49,Business travel,Eco,264,4,1,4,4,5,4,4,5,1,3,3,1,3,5,51,51.0,neutral or dissatisfied +20698,98157,Female,disloyal Customer,26,Business travel,Eco,562,4,4,4,3,2,4,2,2,1,2,4,2,3,2,17,15.0,neutral or dissatisfied +20699,92436,Male,Loyal Customer,48,Business travel,Business,1947,4,4,4,4,3,4,5,5,5,5,5,4,5,4,10,2.0,satisfied +20700,102713,Female,Loyal Customer,61,Business travel,Eco,255,4,3,3,3,3,1,1,4,4,4,4,2,4,3,18,7.0,satisfied +20701,99911,Male,disloyal Customer,36,Business travel,Eco,1028,2,2,2,3,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +20702,24275,Male,Loyal Customer,20,Personal Travel,Eco,147,3,5,3,3,2,3,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +20703,75935,Male,Loyal Customer,41,Business travel,Business,1572,4,4,4,4,5,5,5,4,4,4,4,3,4,5,3,1.0,satisfied +20704,129349,Male,Loyal Customer,60,Personal Travel,Eco,2586,3,5,3,2,2,3,2,2,5,3,4,4,1,2,0,0.0,neutral or dissatisfied +20705,512,Male,disloyal Customer,36,Business travel,Business,247,2,2,2,2,4,2,4,4,3,4,5,4,4,4,15,32.0,neutral or dissatisfied +20706,63833,Male,Loyal Customer,46,Business travel,Business,1172,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,26.0,satisfied +20707,129845,Female,Loyal Customer,47,Personal Travel,Eco,421,3,3,3,3,2,3,3,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +20708,39674,Male,Loyal Customer,39,Business travel,Eco,612,4,5,2,5,4,4,4,4,5,3,3,3,5,4,0,3.0,satisfied +20709,5446,Male,Loyal Customer,38,Business travel,Business,265,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20710,79751,Male,Loyal Customer,24,Personal Travel,Eco Plus,762,3,4,3,2,3,3,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +20711,91998,Male,Loyal Customer,19,Personal Travel,Eco,236,3,3,0,3,1,0,1,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +20712,126868,Female,Loyal Customer,14,Personal Travel,Eco,2077,4,0,4,3,3,4,3,3,5,2,5,4,5,3,0,14.0,neutral or dissatisfied +20713,4982,Male,disloyal Customer,18,Business travel,Eco,502,1,2,1,3,1,4,4,3,1,4,3,4,2,4,148,155.0,neutral or dissatisfied +20714,121334,Male,Loyal Customer,52,Business travel,Business,430,2,1,1,1,3,3,4,2,2,2,2,4,2,1,124,108.0,neutral or dissatisfied +20715,16306,Male,disloyal Customer,21,Business travel,Eco,628,2,4,2,4,1,2,1,1,1,4,1,4,2,1,0,5.0,neutral or dissatisfied +20716,125832,Female,Loyal Customer,40,Business travel,Business,920,1,1,1,1,2,5,4,4,4,4,4,5,4,5,10,3.0,satisfied +20717,27115,Male,Loyal Customer,20,Personal Travel,Business,2677,5,2,5,3,5,5,5,3,3,2,2,5,1,5,7,53.0,satisfied +20718,122135,Male,disloyal Customer,37,Business travel,Business,144,4,4,4,5,1,4,1,1,4,5,5,3,4,1,0,0.0,satisfied +20719,34840,Male,Loyal Customer,64,Personal Travel,Eco Plus,301,2,3,2,3,5,2,5,5,3,2,3,4,4,5,0,0.0,neutral or dissatisfied +20720,83216,Male,Loyal Customer,57,Business travel,Business,2079,4,1,1,1,2,4,3,4,4,4,4,4,4,4,30,13.0,neutral or dissatisfied +20721,78791,Male,disloyal Customer,55,Business travel,Eco,154,1,1,2,2,1,2,1,1,3,2,1,2,1,1,13,22.0,neutral or dissatisfied +20722,70450,Female,Loyal Customer,55,Business travel,Business,3151,3,3,3,3,4,5,5,4,4,4,5,5,4,3,0,0.0,satisfied +20723,111963,Female,Loyal Customer,26,Business travel,Business,3717,2,2,4,2,4,4,4,4,5,3,4,5,4,4,13,17.0,satisfied +20724,74645,Male,Loyal Customer,35,Personal Travel,Eco,1431,4,5,4,5,5,4,5,5,5,5,4,4,5,5,107,97.0,neutral or dissatisfied +20725,16573,Male,Loyal Customer,32,Business travel,Business,872,3,3,3,3,4,4,4,4,1,1,5,1,5,4,0,0.0,satisfied +20726,94837,Female,Loyal Customer,61,Business travel,Eco,187,2,4,4,4,5,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +20727,94666,Female,Loyal Customer,32,Business travel,Business,562,2,2,2,2,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +20728,95904,Male,Loyal Customer,53,Personal Travel,Eco,580,3,1,3,4,5,3,5,5,4,1,4,2,4,5,50,49.0,neutral or dissatisfied +20729,127305,Male,Loyal Customer,40,Business travel,Business,1979,2,2,2,2,5,5,5,2,2,2,2,4,2,3,4,0.0,satisfied +20730,23330,Female,Loyal Customer,50,Business travel,Business,1825,1,1,1,1,4,1,5,5,5,5,3,3,5,4,0,0.0,satisfied +20731,16535,Female,Loyal Customer,54,Personal Travel,Eco,209,1,2,1,3,3,4,3,5,5,1,5,4,5,2,26,19.0,neutral or dissatisfied +20732,85376,Female,Loyal Customer,30,Business travel,Business,3563,5,5,5,5,4,4,4,4,4,2,4,5,5,4,0,20.0,satisfied +20733,16246,Male,Loyal Customer,34,Business travel,Business,2010,1,1,1,1,1,3,3,1,1,1,1,2,1,3,8,0.0,neutral or dissatisfied +20734,65794,Female,disloyal Customer,27,Business travel,Business,1389,3,3,3,3,4,3,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +20735,11682,Female,Loyal Customer,68,Personal Travel,Business,175,4,3,4,5,4,1,4,3,3,4,5,4,3,3,0,1.0,neutral or dissatisfied +20736,30584,Female,Loyal Customer,40,Personal Travel,Eco,628,2,4,2,5,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +20737,61572,Female,Loyal Customer,46,Business travel,Business,1635,1,1,3,1,5,5,4,4,4,4,4,5,4,4,16,0.0,satisfied +20738,123060,Male,Loyal Customer,15,Business travel,Business,3300,5,1,5,5,4,4,4,4,3,3,5,5,4,4,0,0.0,satisfied +20739,88510,Male,Loyal Customer,38,Business travel,Eco,404,3,4,4,4,3,4,3,3,2,5,5,2,1,3,1,14.0,satisfied +20740,35846,Male,Loyal Customer,53,Business travel,Eco,1065,4,5,5,5,3,4,3,3,5,1,2,2,5,3,0,4.0,satisfied +20741,90893,Male,Loyal Customer,25,Business travel,Business,250,2,3,3,3,2,2,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +20742,91595,Male,Loyal Customer,11,Personal Travel,Business,1184,3,5,3,3,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +20743,9901,Male,Loyal Customer,42,Business travel,Business,2979,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +20744,20184,Female,Loyal Customer,42,Business travel,Eco Plus,403,4,1,1,1,1,5,2,4,4,4,4,3,4,2,50,72.0,satisfied +20745,67132,Male,Loyal Customer,39,Business travel,Eco,985,2,3,3,3,2,2,2,2,2,2,2,3,3,2,21,29.0,neutral or dissatisfied +20746,73088,Female,Loyal Customer,70,Personal Travel,Eco,1085,2,4,2,3,3,5,4,1,1,2,2,5,1,4,0,0.0,neutral or dissatisfied +20747,18393,Female,Loyal Customer,55,Business travel,Eco,378,4,2,2,2,3,3,2,4,4,4,4,5,4,3,0,0.0,satisfied +20748,61905,Male,Loyal Customer,32,Business travel,Business,2515,2,2,2,2,5,5,5,5,3,5,5,3,4,5,3,5.0,satisfied +20749,65283,Female,Loyal Customer,12,Personal Travel,Eco Plus,247,3,2,3,3,1,3,1,1,4,5,4,3,4,1,11,13.0,neutral or dissatisfied +20750,94507,Female,Loyal Customer,33,Business travel,Business,1966,5,5,4,5,4,4,5,4,4,4,4,4,4,4,10,10.0,satisfied +20751,27768,Female,disloyal Customer,27,Business travel,Eco,1448,2,3,3,4,2,2,2,2,1,2,4,1,4,2,0,0.0,neutral or dissatisfied +20752,42230,Female,Loyal Customer,30,Business travel,Business,834,2,1,5,1,2,2,2,2,2,3,3,3,4,2,44,77.0,neutral or dissatisfied +20753,29315,Female,Loyal Customer,32,Personal Travel,Eco,933,3,3,3,4,1,3,1,1,2,2,4,4,4,1,0,0.0,neutral or dissatisfied +20754,54218,Male,disloyal Customer,20,Business travel,Business,1222,5,4,5,2,1,5,5,1,3,3,4,4,4,1,5,15.0,satisfied +20755,76041,Male,Loyal Customer,42,Business travel,Business,669,1,1,1,1,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +20756,8370,Male,Loyal Customer,43,Business travel,Business,773,3,4,3,3,3,5,4,5,5,5,5,4,5,4,15,18.0,satisfied +20757,67347,Male,Loyal Customer,38,Personal Travel,Eco,1471,3,4,3,2,3,3,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +20758,110194,Male,Loyal Customer,28,Personal Travel,Eco,882,3,5,3,3,4,3,3,4,4,5,5,4,5,4,62,66.0,neutral or dissatisfied +20759,42878,Female,Loyal Customer,36,Personal Travel,Eco,867,2,3,2,1,4,2,4,4,4,5,2,3,4,4,0,6.0,neutral or dissatisfied +20760,56576,Female,Loyal Customer,43,Business travel,Business,997,4,3,4,4,4,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +20761,24661,Female,Loyal Customer,60,Personal Travel,Eco,834,4,2,4,3,5,3,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +20762,129500,Female,Loyal Customer,46,Business travel,Business,1846,2,2,2,2,2,4,5,4,4,4,4,4,4,3,80,73.0,satisfied +20763,77818,Female,Loyal Customer,40,Personal Travel,Eco,1282,2,4,1,1,2,1,2,2,3,3,5,5,5,2,19,2.0,neutral or dissatisfied +20764,110717,Female,Loyal Customer,55,Personal Travel,Business,990,4,4,4,2,4,4,4,4,4,4,4,4,4,5,0,1.0,neutral or dissatisfied +20765,128597,Male,Loyal Customer,45,Personal Travel,Business,679,1,4,1,3,3,4,4,3,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +20766,94933,Female,disloyal Customer,24,Business travel,Eco,319,2,2,2,4,2,2,2,2,1,5,4,1,3,2,17,16.0,neutral or dissatisfied +20767,61366,Female,Loyal Customer,43,Business travel,Business,2232,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +20768,68013,Female,Loyal Customer,47,Business travel,Business,2886,4,4,4,4,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +20769,72124,Female,Loyal Customer,46,Business travel,Business,2240,2,2,2,2,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +20770,115,Female,disloyal Customer,12,Business travel,Business,562,3,2,3,3,2,3,2,2,3,4,3,3,3,2,11,25.0,neutral or dissatisfied +20771,349,Female,Loyal Customer,33,Personal Travel,Eco,821,3,3,4,4,4,4,4,4,4,5,3,3,3,4,0,0.0,neutral or dissatisfied +20772,43600,Female,Loyal Customer,47,Business travel,Business,190,1,1,1,1,2,1,1,5,5,5,4,1,5,4,0,0.0,satisfied +20773,44092,Male,Loyal Customer,45,Business travel,Eco,257,4,3,3,3,3,4,3,3,1,3,3,3,4,3,1,5.0,satisfied +20774,52063,Female,Loyal Customer,44,Business travel,Eco,438,5,1,2,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +20775,31723,Male,Loyal Customer,16,Personal Travel,Eco,967,1,2,1,4,1,1,1,1,2,2,4,3,4,1,0,0.0,neutral or dissatisfied +20776,81753,Female,Loyal Customer,44,Business travel,Business,2521,5,5,5,5,5,4,4,5,5,5,5,4,5,3,37,47.0,satisfied +20777,7623,Male,Loyal Customer,42,Business travel,Business,641,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +20778,2746,Female,Loyal Customer,33,Business travel,Business,772,4,4,2,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +20779,771,Male,Loyal Customer,44,Business travel,Business,312,3,3,5,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +20780,65399,Male,Loyal Customer,61,Personal Travel,Eco,432,3,1,3,1,5,3,5,5,3,5,2,4,1,5,0,0.0,neutral or dissatisfied +20781,91299,Female,Loyal Customer,53,Business travel,Eco Plus,404,3,5,4,5,1,3,3,3,3,3,3,1,3,2,18,37.0,neutral or dissatisfied +20782,11983,Male,Loyal Customer,55,Business travel,Eco,643,4,3,4,3,4,4,4,4,4,2,1,5,4,4,1,1.0,satisfied +20783,88590,Male,Loyal Customer,47,Personal Travel,Eco,406,3,4,3,5,4,3,4,4,3,2,5,2,2,4,0,0.0,neutral or dissatisfied +20784,62286,Male,Loyal Customer,49,Business travel,Business,236,1,1,1,1,5,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +20785,114926,Female,Loyal Customer,58,Business travel,Business,2249,5,5,5,5,5,5,5,4,4,4,4,4,4,4,13,8.0,satisfied +20786,118604,Male,Loyal Customer,38,Business travel,Eco,647,2,3,3,3,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +20787,90731,Female,Loyal Customer,42,Business travel,Business,404,2,2,3,2,4,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +20788,84547,Female,Loyal Customer,12,Personal Travel,Eco,2504,4,5,5,3,5,5,5,5,3,2,5,4,1,5,1,0.0,neutral or dissatisfied +20789,30015,Female,disloyal Customer,49,Business travel,Eco,1192,3,3,3,3,4,3,4,4,2,2,3,1,4,4,11,18.0,neutral or dissatisfied +20790,83281,Male,Loyal Customer,44,Personal Travel,Eco,1979,3,3,3,4,3,3,3,5,5,4,5,3,2,3,164,152.0,neutral or dissatisfied +20791,57457,Female,Loyal Customer,48,Business travel,Business,3895,3,5,5,5,5,4,4,3,3,3,3,3,3,4,13,18.0,neutral or dissatisfied +20792,13261,Female,Loyal Customer,24,Business travel,Eco,257,3,1,1,1,3,3,4,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +20793,95344,Female,disloyal Customer,64,Personal Travel,Eco,239,1,5,1,3,3,1,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +20794,85517,Female,Loyal Customer,30,Business travel,Eco Plus,152,3,1,4,4,3,3,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +20795,97035,Female,disloyal Customer,22,Business travel,Business,1129,0,0,0,3,5,0,5,5,3,2,5,5,4,5,50,36.0,satisfied +20796,70621,Female,Loyal Customer,15,Business travel,Business,2152,3,4,4,4,3,3,3,3,2,5,4,4,3,3,12,6.0,neutral or dissatisfied +20797,75214,Male,Loyal Customer,29,Business travel,Eco,1846,2,1,1,1,2,2,2,2,3,2,2,3,3,2,0,4.0,neutral or dissatisfied +20798,21653,Female,Loyal Customer,59,Business travel,Business,746,1,1,1,1,4,4,4,4,4,4,4,5,4,3,53,63.0,satisfied +20799,104563,Female,Loyal Customer,31,Business travel,Business,369,1,5,5,5,1,1,1,1,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +20800,74837,Female,Loyal Customer,30,Business travel,Business,1797,4,3,3,3,4,4,4,4,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +20801,129370,Female,Loyal Customer,57,Business travel,Business,2454,2,2,2,2,5,4,4,4,4,4,4,3,4,4,9,0.0,satisfied +20802,112070,Male,Loyal Customer,40,Business travel,Business,1491,3,3,3,3,4,4,4,4,4,4,4,4,4,3,36,11.0,satisfied +20803,112583,Male,disloyal Customer,25,Business travel,Business,602,1,5,1,5,4,1,4,4,5,4,5,5,4,4,50,37.0,neutral or dissatisfied +20804,105279,Female,Loyal Customer,57,Business travel,Business,2765,5,5,5,5,4,5,5,4,4,4,4,5,4,4,0,1.0,satisfied +20805,74663,Female,Loyal Customer,42,Personal Travel,Eco,1438,4,4,4,1,3,4,5,1,1,4,1,5,1,3,0,0.0,neutral or dissatisfied +20806,11551,Male,Loyal Customer,44,Business travel,Business,2596,4,3,4,4,2,5,4,4,4,4,4,5,4,3,0,6.0,satisfied +20807,82279,Female,Loyal Customer,45,Personal Travel,Eco,1481,2,2,2,2,1,3,2,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +20808,110875,Female,Loyal Customer,43,Business travel,Business,1956,2,2,4,2,5,5,5,4,4,4,4,4,4,5,6,0.0,satisfied +20809,70868,Female,Loyal Customer,18,Personal Travel,Eco,761,2,4,2,1,5,2,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +20810,56370,Female,Loyal Customer,31,Personal Travel,Eco,200,3,2,3,4,2,3,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +20811,29775,Male,Loyal Customer,18,Personal Travel,Business,183,4,4,4,3,1,4,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +20812,43814,Female,Loyal Customer,40,Business travel,Business,199,2,3,5,3,4,3,3,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +20813,104108,Male,Loyal Customer,32,Personal Travel,Eco,297,1,4,2,3,1,2,1,1,5,5,5,3,4,1,20,24.0,neutral or dissatisfied +20814,265,Female,Loyal Customer,49,Business travel,Business,825,3,3,4,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20815,127884,Male,Loyal Customer,46,Business travel,Business,1603,2,2,2,2,3,4,4,4,4,4,4,5,4,5,4,0.0,satisfied +20816,115121,Male,Loyal Customer,68,Business travel,Business,325,0,0,0,1,4,4,4,1,1,1,1,5,1,5,81,76.0,satisfied +20817,115694,Female,disloyal Customer,26,Business travel,Eco,342,1,2,1,3,3,1,3,3,4,4,2,3,3,3,9,0.0,neutral or dissatisfied +20818,15656,Male,Loyal Customer,41,Business travel,Eco Plus,258,3,3,3,3,3,3,3,3,2,3,1,4,3,3,0,0.0,satisfied +20819,66079,Female,Loyal Customer,42,Personal Travel,Eco,1055,4,4,4,2,5,4,5,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +20820,4226,Female,Loyal Customer,30,Business travel,Business,1020,2,2,2,2,4,4,4,4,3,4,4,5,4,4,0,3.0,satisfied +20821,32725,Male,Loyal Customer,48,Business travel,Business,101,3,5,5,5,2,4,3,1,1,1,3,2,1,2,0,0.0,neutral or dissatisfied +20822,117802,Female,Loyal Customer,32,Business travel,Business,3758,1,1,1,1,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +20823,99953,Female,disloyal Customer,54,Personal Travel,Eco,1986,3,5,3,1,1,3,1,1,4,2,1,2,1,1,41,41.0,neutral or dissatisfied +20824,24966,Male,Loyal Customer,13,Personal Travel,Eco,226,2,3,2,3,2,2,2,2,4,1,1,4,2,2,4,0.0,neutral or dissatisfied +20825,113102,Male,Loyal Customer,21,Personal Travel,Eco,479,3,2,3,4,1,3,1,1,1,2,4,3,4,1,0,0.0,neutral or dissatisfied +20826,110428,Female,Loyal Customer,52,Business travel,Business,387,5,5,3,5,2,1,1,5,5,5,5,2,5,5,24,15.0,satisfied +20827,74307,Male,Loyal Customer,51,Business travel,Business,1928,4,4,4,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20828,73335,Female,Loyal Customer,29,Business travel,Business,1144,4,4,4,4,4,4,4,4,3,2,5,4,4,4,0,3.0,satisfied +20829,49583,Male,Loyal Customer,39,Business travel,Eco,308,5,2,2,2,5,5,5,5,3,5,1,2,2,5,0,3.0,satisfied +20830,117126,Female,Loyal Customer,58,Personal Travel,Eco,370,5,2,5,3,3,2,3,3,3,5,3,1,3,3,9,0.0,satisfied +20831,93120,Male,Loyal Customer,48,Personal Travel,Business,1066,2,5,1,1,3,4,4,5,5,1,5,5,5,5,8,21.0,neutral or dissatisfied +20832,72828,Male,Loyal Customer,25,Business travel,Business,3048,2,2,2,2,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +20833,51935,Male,Loyal Customer,45,Business travel,Business,1889,5,5,5,5,3,3,1,4,4,4,4,4,4,3,0,0.0,satisfied +20834,118997,Male,disloyal Customer,22,Business travel,Eco,479,3,0,4,2,1,4,2,1,3,5,4,3,4,1,22,14.0,neutral or dissatisfied +20835,10310,Female,Loyal Customer,60,Business travel,Business,247,2,2,2,2,3,5,5,4,4,4,4,5,4,5,27,14.0,satisfied +20836,128780,Female,Loyal Customer,40,Business travel,Business,2248,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +20837,57422,Female,Loyal Customer,18,Personal Travel,Eco,403,1,5,4,3,1,4,1,1,5,4,4,3,5,1,18,24.0,neutral or dissatisfied +20838,98847,Male,Loyal Customer,40,Business travel,Business,1482,4,4,3,4,3,4,5,4,4,4,4,5,4,3,5,0.0,satisfied +20839,59138,Male,Loyal Customer,67,Personal Travel,Eco,1744,2,5,2,4,2,2,2,2,5,3,3,4,5,2,0,0.0,neutral or dissatisfied +20840,57240,Female,Loyal Customer,68,Personal Travel,Business,804,4,2,4,3,1,3,3,4,4,4,4,1,4,4,0,0.0,satisfied +20841,10221,Female,Loyal Customer,19,Business travel,Business,2538,1,2,2,2,1,1,1,1,4,5,3,2,3,1,2,3.0,neutral or dissatisfied +20842,120541,Female,Loyal Customer,54,Business travel,Business,2176,2,2,4,2,2,3,5,4,4,4,4,3,4,4,100,124.0,satisfied +20843,121562,Female,Loyal Customer,67,Business travel,Business,2871,2,3,3,3,2,3,2,2,2,3,2,2,2,1,4,0.0,neutral or dissatisfied +20844,44875,Male,disloyal Customer,27,Business travel,Eco,315,2,2,2,2,4,2,4,4,1,3,2,2,1,4,29,27.0,neutral or dissatisfied +20845,129527,Male,Loyal Customer,45,Business travel,Business,2342,4,4,3,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +20846,33485,Male,Loyal Customer,26,Business travel,Business,2496,1,1,1,1,5,5,5,5,3,4,3,1,1,5,0,0.0,satisfied +20847,128745,Female,disloyal Customer,26,Business travel,Business,2521,3,3,3,4,3,1,1,3,3,4,4,1,4,1,30,84.0,neutral or dissatisfied +20848,20325,Male,disloyal Customer,27,Business travel,Business,323,3,3,3,4,3,5,5,4,4,4,5,5,3,5,163,173.0,neutral or dissatisfied +20849,12665,Male,Loyal Customer,47,Business travel,Eco,721,4,3,3,3,4,4,4,4,3,3,5,5,2,4,0,0.0,satisfied +20850,93453,Male,Loyal Customer,21,Personal Travel,Eco,723,2,2,2,4,4,2,3,4,4,1,4,2,3,4,0,0.0,neutral or dissatisfied +20851,42650,Male,Loyal Customer,40,Personal Travel,Eco,546,2,4,2,5,4,2,4,4,5,3,1,5,3,4,4,0.0,neutral or dissatisfied +20852,113645,Female,Loyal Customer,50,Personal Travel,Eco,226,3,5,3,1,5,4,5,5,5,3,5,5,5,3,19,14.0,neutral or dissatisfied +20853,116786,Female,Loyal Customer,37,Personal Travel,Eco Plus,337,3,5,3,4,2,3,1,2,3,2,4,5,5,2,10,3.0,neutral or dissatisfied +20854,25502,Male,Loyal Customer,48,Business travel,Eco,481,1,5,5,5,2,1,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +20855,84644,Female,Loyal Customer,51,Personal Travel,Eco Plus,669,3,5,3,2,3,5,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +20856,29376,Female,Loyal Customer,47,Business travel,Eco,2349,4,4,4,4,3,5,5,4,4,4,4,5,4,2,0,0.0,satisfied +20857,77217,Female,Loyal Customer,43,Business travel,Business,1590,1,1,1,1,4,4,5,4,4,4,4,4,4,3,3,0.0,satisfied +20858,32390,Male,disloyal Customer,23,Business travel,Eco,163,3,0,3,2,1,3,1,1,3,3,3,3,2,1,42,44.0,neutral or dissatisfied +20859,46444,Male,Loyal Customer,52,Personal Travel,Eco,1199,3,3,3,3,2,3,2,2,3,5,4,3,3,2,40,50.0,neutral or dissatisfied +20860,31534,Female,Loyal Customer,67,Personal Travel,Eco,967,4,4,4,3,3,4,4,4,4,4,4,4,4,4,11,7.0,neutral or dissatisfied +20861,79614,Male,disloyal Customer,30,Business travel,Eco,762,1,1,1,4,3,1,3,3,2,5,3,4,4,3,0,0.0,neutral or dissatisfied +20862,11836,Female,Loyal Customer,42,Personal Travel,Eco,1091,3,4,3,3,1,3,4,2,2,3,2,1,2,3,64,48.0,neutral or dissatisfied +20863,93986,Male,Loyal Customer,15,Personal Travel,Eco,1315,2,5,2,1,1,2,5,1,3,4,5,5,4,1,14,0.0,neutral or dissatisfied +20864,45316,Female,Loyal Customer,56,Business travel,Business,461,1,4,4,4,1,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +20865,93182,Female,Loyal Customer,12,Personal Travel,Eco,1243,5,5,5,2,4,5,4,4,5,5,3,3,4,4,10,0.0,satisfied +20866,52159,Male,Loyal Customer,36,Business travel,Business,425,1,1,1,1,3,5,5,5,5,5,5,2,5,3,0,0.0,satisfied +20867,14946,Male,Loyal Customer,40,Business travel,Business,2907,4,4,5,4,4,3,3,5,2,3,3,3,1,3,392,381.0,satisfied +20868,50388,Female,disloyal Customer,40,Business travel,Business,308,4,5,5,3,2,5,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +20869,72766,Female,Loyal Customer,50,Business travel,Eco,1045,2,5,5,5,4,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +20870,11155,Male,Loyal Customer,36,Personal Travel,Eco,312,1,4,1,2,4,1,5,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +20871,89952,Female,Loyal Customer,45,Personal Travel,Eco,1416,2,2,2,3,2,4,3,4,4,2,4,4,4,1,0,31.0,neutral or dissatisfied +20872,97610,Male,Loyal Customer,23,Personal Travel,Eco,442,1,5,2,3,5,2,5,5,3,2,5,4,4,5,9,4.0,neutral or dissatisfied +20873,117050,Male,disloyal Customer,45,Business travel,Eco,304,4,1,3,3,2,3,2,2,4,4,2,3,2,2,14,0.0,neutral or dissatisfied +20874,3250,Male,Loyal Customer,41,Business travel,Business,425,2,2,2,2,5,5,5,5,5,5,5,4,5,4,4,12.0,satisfied +20875,86074,Female,Loyal Customer,19,Personal Travel,Eco Plus,554,2,1,2,2,4,2,4,4,4,3,3,2,3,4,15,0.0,neutral or dissatisfied +20876,106135,Male,Loyal Customer,37,Business travel,Business,2306,1,2,2,2,5,3,3,1,1,1,1,3,1,4,40,35.0,neutral or dissatisfied +20877,38162,Female,Loyal Customer,66,Personal Travel,Eco,1237,3,4,3,5,2,3,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +20878,46327,Female,Loyal Customer,60,Personal Travel,Eco,420,5,2,5,3,2,4,3,1,1,5,1,2,1,1,0,0.0,satisfied +20879,19518,Male,Loyal Customer,59,Business travel,Business,577,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20880,100908,Male,Loyal Customer,16,Personal Travel,Eco,377,1,4,1,1,1,1,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +20881,105457,Male,Loyal Customer,10,Personal Travel,Eco,998,3,5,3,3,4,3,4,4,5,5,5,5,5,4,4,0.0,neutral or dissatisfied +20882,61969,Male,Loyal Customer,53,Business travel,Eco,2400,1,3,3,3,2,1,2,2,1,1,1,4,2,2,0,0.0,neutral or dissatisfied +20883,54857,Male,Loyal Customer,32,Business travel,Business,862,2,2,2,2,4,4,4,4,3,2,4,5,5,4,2,0.0,satisfied +20884,82963,Female,Loyal Customer,31,Business travel,Business,957,3,3,5,3,5,5,5,5,4,3,4,4,5,5,2,12.0,satisfied +20885,45969,Female,Loyal Customer,25,Business travel,Eco,872,5,2,2,2,5,5,3,5,5,4,4,5,4,5,6,0.0,satisfied +20886,7376,Male,Loyal Customer,28,Business travel,Business,1791,2,2,2,2,4,4,4,4,3,4,4,4,5,4,16,36.0,satisfied +20887,43277,Female,Loyal Customer,48,Business travel,Eco,387,4,3,3,3,2,1,3,4,4,4,4,1,4,2,0,0.0,satisfied +20888,22636,Male,Loyal Customer,38,Personal Travel,Eco,223,3,4,3,2,2,3,2,2,5,5,4,4,5,2,0,7.0,neutral or dissatisfied +20889,100844,Male,Loyal Customer,28,Personal Travel,Eco,711,1,3,1,2,5,1,5,5,1,4,3,1,3,5,0,0.0,neutral or dissatisfied +20890,113712,Female,Loyal Customer,27,Personal Travel,Eco,236,2,1,0,4,5,0,5,5,4,4,4,1,3,5,12,15.0,neutral or dissatisfied +20891,65455,Female,Loyal Customer,30,Business travel,Business,1303,1,1,1,1,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +20892,70875,Female,Loyal Customer,40,Personal Travel,Eco,761,1,4,1,4,5,1,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +20893,44646,Female,Loyal Customer,57,Business travel,Eco,173,4,2,2,2,5,4,1,4,4,4,4,2,4,1,0,0.0,satisfied +20894,48411,Male,Loyal Customer,30,Business travel,Business,3306,1,1,1,1,4,4,4,4,5,4,4,3,4,4,0,33.0,satisfied +20895,10470,Male,Loyal Customer,50,Business travel,Business,3757,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20896,55381,Female,Loyal Customer,53,Business travel,Business,2157,4,3,3,3,3,3,3,4,4,4,4,1,4,2,5,0.0,neutral or dissatisfied +20897,25618,Female,disloyal Customer,15,Business travel,Eco,666,5,5,5,3,5,5,5,5,4,5,3,2,5,5,0,0.0,satisfied +20898,107029,Female,Loyal Customer,32,Business travel,Business,480,1,1,1,1,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +20899,93062,Male,Loyal Customer,49,Business travel,Business,1614,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +20900,67661,Male,Loyal Customer,45,Business travel,Business,1464,3,3,3,3,2,5,4,5,5,5,5,4,5,4,2,4.0,satisfied +20901,122867,Male,Loyal Customer,30,Business travel,Business,226,1,1,1,1,3,4,3,3,4,5,5,5,4,3,7,0.0,satisfied +20902,25370,Female,Loyal Customer,36,Business travel,Eco,591,2,3,3,3,2,2,2,2,4,4,2,4,2,2,7,2.0,neutral or dissatisfied +20903,76157,Female,disloyal Customer,24,Business travel,Eco,689,4,4,4,4,5,4,5,5,1,4,4,4,4,5,0,0.0,neutral or dissatisfied +20904,67183,Female,Loyal Customer,30,Personal Travel,Eco,929,1,5,1,1,3,1,3,3,3,3,4,5,5,3,45,40.0,neutral or dissatisfied +20905,59313,Male,Loyal Customer,43,Business travel,Business,2367,3,3,3,3,2,5,5,5,5,5,5,5,5,3,6,3.0,satisfied +20906,1767,Female,Loyal Customer,48,Business travel,Business,100,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +20907,116931,Female,Loyal Customer,32,Business travel,Business,325,0,0,0,2,3,3,3,3,4,3,5,5,4,3,50,43.0,satisfied +20908,52523,Male,Loyal Customer,37,Business travel,Business,3405,5,5,3,5,3,4,1,4,4,4,4,2,4,3,0,0.0,satisfied +20909,35779,Female,Loyal Customer,56,Business travel,Business,200,5,5,5,5,1,5,1,5,5,5,3,2,5,4,0,0.0,satisfied +20910,106782,Female,Loyal Customer,54,Personal Travel,Eco Plus,837,3,4,3,5,5,5,5,3,3,3,3,4,3,3,1,19.0,neutral or dissatisfied +20911,58535,Female,disloyal Customer,32,Business travel,Eco Plus,719,3,2,2,4,2,2,2,2,2,3,3,2,3,2,3,8.0,neutral or dissatisfied +20912,13259,Male,Loyal Customer,22,Business travel,Business,468,2,5,5,5,2,2,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +20913,11177,Female,Loyal Customer,61,Personal Travel,Eco,312,1,3,1,4,4,3,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +20914,73426,Male,Loyal Customer,25,Personal Travel,Eco,1197,3,5,3,1,3,3,3,3,4,4,4,4,4,3,17,11.0,neutral or dissatisfied +20915,108137,Female,Loyal Customer,29,Business travel,Business,849,3,3,3,3,3,3,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +20916,101045,Female,Loyal Customer,52,Business travel,Business,3712,5,5,5,5,4,4,4,4,4,4,4,3,4,5,17,11.0,satisfied +20917,77139,Female,Loyal Customer,52,Personal Travel,Eco,2105,4,3,4,4,3,3,4,5,5,4,5,1,5,1,0,0.0,neutral or dissatisfied +20918,62680,Male,Loyal Customer,35,Personal Travel,Eco Plus,1846,4,4,4,4,4,4,4,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +20919,728,Male,disloyal Customer,16,Business travel,Eco,309,4,4,4,4,5,4,5,5,2,1,4,2,4,5,0,0.0,neutral or dissatisfied +20920,54296,Male,Loyal Customer,27,Personal Travel,Eco,1075,3,3,3,3,2,3,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +20921,37164,Female,Loyal Customer,59,Personal Travel,Eco,1046,4,5,4,1,5,4,5,2,2,4,3,5,2,4,12,3.0,neutral or dissatisfied +20922,42238,Male,Loyal Customer,30,Business travel,Business,3775,2,2,2,2,2,2,2,2,4,1,4,2,5,2,0,0.0,satisfied +20923,42434,Female,disloyal Customer,24,Business travel,Eco,1119,3,3,3,3,2,3,2,2,4,1,2,1,1,2,0,0.0,neutral or dissatisfied +20924,38491,Male,Loyal Customer,58,Business travel,Business,2586,1,1,1,1,3,4,1,3,3,2,3,3,3,2,0,0.0,satisfied +20925,105955,Male,disloyal Customer,22,Business travel,Eco,2295,4,4,4,4,3,4,3,3,3,2,3,4,4,3,3,0.0,neutral or dissatisfied +20926,93451,Male,Loyal Customer,24,Personal Travel,Eco,697,4,5,4,3,4,4,5,4,5,5,5,3,4,4,42,33.0,neutral or dissatisfied +20927,28577,Male,Loyal Customer,26,Business travel,Business,2603,4,5,5,5,4,4,4,4,1,1,1,2,3,4,73,51.0,neutral or dissatisfied +20928,45986,Female,Loyal Customer,51,Business travel,Business,3972,3,3,3,3,1,1,2,5,5,5,5,1,5,5,0,0.0,satisfied +20929,50870,Female,Loyal Customer,17,Personal Travel,Eco,134,0,0,0,1,1,0,1,1,3,4,5,5,5,1,0,4.0,satisfied +20930,129186,Male,Loyal Customer,38,Business travel,Business,2288,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +20931,86435,Male,Loyal Customer,41,Business travel,Business,712,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +20932,42437,Male,Loyal Customer,50,Personal Travel,Eco,1119,3,4,3,2,5,3,1,5,3,5,5,5,4,5,81,63.0,neutral or dissatisfied +20933,75360,Female,Loyal Customer,75,Business travel,Eco Plus,986,5,1,3,1,3,5,4,5,5,5,5,2,5,1,0,0.0,satisfied +20934,84339,Female,Loyal Customer,54,Business travel,Business,2613,4,4,4,4,3,5,5,5,5,5,5,5,5,5,2,7.0,satisfied +20935,128931,Male,Loyal Customer,40,Business travel,Business,3177,5,5,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +20936,84112,Male,Loyal Customer,31,Business travel,Business,1900,4,4,4,4,5,5,5,5,5,3,5,4,5,5,0,4.0,satisfied +20937,6368,Female,disloyal Customer,20,Business travel,Business,213,3,4,3,4,3,3,3,3,3,2,3,1,4,3,32,32.0,neutral or dissatisfied +20938,37146,Female,disloyal Customer,28,Business travel,Eco,1189,3,3,3,3,5,3,5,5,2,1,3,3,4,5,57,46.0,neutral or dissatisfied +20939,129408,Male,Loyal Customer,55,Business travel,Business,2056,1,1,1,1,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +20940,38620,Male,disloyal Customer,19,Business travel,Eco,1184,2,2,2,3,2,2,4,2,1,3,3,1,4,2,31,22.0,neutral or dissatisfied +20941,15527,Female,Loyal Customer,44,Personal Travel,Eco Plus,306,1,5,1,4,4,4,5,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +20942,92325,Male,Loyal Customer,54,Business travel,Business,2556,3,3,3,3,4,4,4,3,2,5,4,4,5,4,0,9.0,satisfied +20943,82480,Male,Loyal Customer,60,Personal Travel,Eco,502,3,5,3,2,3,3,3,3,5,5,5,5,5,3,10,62.0,neutral or dissatisfied +20944,22643,Male,Loyal Customer,58,Personal Travel,Eco,300,3,5,3,5,1,3,4,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +20945,87417,Male,Loyal Customer,18,Personal Travel,Eco,425,2,0,2,3,3,2,3,3,5,5,4,5,4,3,0,1.0,neutral or dissatisfied +20946,85430,Male,Loyal Customer,40,Business travel,Eco,227,3,3,3,3,3,3,3,3,1,4,3,3,4,3,0,0.0,neutral or dissatisfied +20947,55076,Female,Loyal Customer,35,Business travel,Business,1609,4,4,4,4,4,3,3,4,4,4,4,3,4,2,23,14.0,neutral or dissatisfied +20948,28804,Female,Loyal Customer,51,Business travel,Business,1809,1,1,1,1,2,1,1,4,4,4,4,5,4,3,0,0.0,satisfied +20949,90168,Female,Loyal Customer,38,Personal Travel,Eco,1127,2,5,2,4,3,2,1,3,5,4,5,3,4,3,41,56.0,neutral or dissatisfied +20950,61806,Female,Loyal Customer,23,Personal Travel,Eco,1303,1,4,1,2,1,1,1,1,4,5,4,4,4,1,25,6.0,neutral or dissatisfied +20951,27013,Female,Loyal Customer,54,Personal Travel,Eco,867,1,5,1,3,2,5,5,5,5,1,5,4,5,3,25,35.0,neutral or dissatisfied +20952,13937,Female,Loyal Customer,53,Business travel,Business,3492,1,1,1,1,2,1,1,1,1,1,1,2,1,1,3,7.0,neutral or dissatisfied +20953,93266,Female,Loyal Customer,39,Business travel,Business,2660,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +20954,97551,Male,Loyal Customer,45,Business travel,Eco Plus,675,1,0,0,4,2,1,5,2,2,5,3,2,4,2,84,74.0,neutral or dissatisfied +20955,204,Female,Loyal Customer,71,Business travel,Business,2376,2,3,3,3,2,3,3,4,4,4,2,1,4,1,9,8.0,neutral or dissatisfied +20956,90638,Female,Loyal Customer,53,Business travel,Business,581,2,2,2,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +20957,91413,Male,Loyal Customer,48,Business travel,Business,1050,5,5,4,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +20958,14286,Female,Loyal Customer,40,Business travel,Business,3247,5,5,5,5,3,4,2,4,4,4,4,2,4,2,0,0.0,satisfied +20959,16555,Male,Loyal Customer,32,Business travel,Eco,1092,0,0,0,3,1,0,1,1,3,1,1,1,2,1,0,0.0,satisfied +20960,51064,Female,Loyal Customer,64,Personal Travel,Eco,89,2,4,2,2,3,4,4,2,2,2,1,5,2,5,0,0.0,neutral or dissatisfied +20961,125716,Male,Loyal Customer,39,Personal Travel,Eco,759,5,3,5,4,5,5,3,5,4,3,4,4,3,5,0,0.0,satisfied +20962,98503,Female,disloyal Customer,21,Business travel,Eco,668,3,5,4,3,1,4,1,1,3,5,5,4,5,1,6,0.0,neutral or dissatisfied +20963,45883,Female,Loyal Customer,23,Business travel,Business,1505,3,3,3,3,4,4,4,4,4,3,1,1,2,4,4,3.0,satisfied +20964,75504,Male,Loyal Customer,13,Personal Travel,Eco Plus,2218,3,2,3,3,3,3,3,3,3,2,4,2,3,3,0,0.0,neutral or dissatisfied +20965,64455,Female,Loyal Customer,12,Personal Travel,Eco,989,3,3,3,3,1,3,1,1,2,4,4,4,3,1,5,4.0,neutral or dissatisfied +20966,83682,Female,disloyal Customer,21,Business travel,Eco,577,1,1,1,3,3,1,3,3,4,5,3,3,4,3,0,0.0,neutral or dissatisfied +20967,75219,Male,disloyal Customer,38,Business travel,Eco,244,2,0,2,3,4,2,3,4,4,3,1,1,3,4,0,0.0,neutral or dissatisfied +20968,88406,Female,Loyal Customer,53,Business travel,Business,2258,0,0,0,3,3,5,4,1,1,1,1,4,1,3,0,0.0,satisfied +20969,46335,Male,disloyal Customer,25,Business travel,Eco,589,1,3,1,4,3,1,3,3,2,1,3,4,5,3,34,25.0,neutral or dissatisfied +20970,72118,Male,Loyal Customer,31,Business travel,Business,2645,5,5,4,5,3,3,3,3,4,3,5,3,5,3,0,0.0,satisfied +20971,37052,Male,Loyal Customer,34,Personal Travel,Eco Plus,994,5,4,5,4,3,5,3,3,4,4,5,3,4,3,0,0.0,satisfied +20972,26042,Female,Loyal Customer,59,Business travel,Eco,432,2,1,1,1,4,1,2,2,2,2,2,5,2,3,11,29.0,satisfied +20973,127744,Female,Loyal Customer,44,Business travel,Eco,255,2,1,1,1,3,2,3,3,3,2,3,2,3,4,10,11.0,neutral or dissatisfied +20974,125007,Female,Loyal Customer,42,Business travel,Eco,184,2,1,1,1,5,2,4,2,2,2,2,3,2,1,0,0.0,satisfied +20975,115527,Male,Loyal Customer,45,Business travel,Business,1803,2,3,3,3,3,4,3,2,2,2,2,2,2,3,66,60.0,neutral or dissatisfied +20976,88665,Female,Loyal Customer,10,Personal Travel,Eco,406,4,4,4,3,1,4,1,1,5,3,4,5,5,1,0,9.0,neutral or dissatisfied +20977,45017,Male,Loyal Customer,43,Personal Travel,Eco,137,4,0,0,3,4,0,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +20978,8684,Female,Loyal Customer,29,Business travel,Business,181,0,4,0,4,4,5,5,4,3,5,5,3,5,4,0,0.0,satisfied +20979,16282,Female,Loyal Customer,12,Personal Travel,Eco,748,1,4,1,1,2,1,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +20980,82036,Male,Loyal Customer,48,Personal Travel,Eco,1535,4,4,4,4,5,4,5,5,2,3,5,1,4,5,0,0.0,neutral or dissatisfied +20981,103964,Male,Loyal Customer,41,Personal Travel,Eco,533,3,4,3,2,1,3,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +20982,129343,Male,Loyal Customer,37,Personal Travel,Eco,2475,2,4,2,4,1,2,1,1,4,5,5,2,4,1,10,36.0,neutral or dissatisfied +20983,15330,Male,Loyal Customer,51,Personal Travel,Eco,599,5,4,5,3,3,5,3,3,2,4,4,1,5,3,0,0.0,satisfied +20984,41389,Female,Loyal Customer,54,Business travel,Eco,913,5,5,4,5,4,1,2,5,5,5,5,4,5,4,4,0.0,satisfied +20985,75651,Male,Loyal Customer,38,Business travel,Business,304,3,4,3,4,4,4,3,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +20986,25708,Male,disloyal Customer,52,Business travel,Eco,528,4,4,4,4,2,4,1,2,2,4,3,2,4,2,0,0.0,neutral or dissatisfied +20987,64580,Female,Loyal Customer,54,Business travel,Business,282,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +20988,6955,Male,Loyal Customer,51,Business travel,Business,3931,1,1,1,1,4,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +20989,15665,Female,Loyal Customer,60,Business travel,Eco,764,4,1,1,1,1,5,4,4,4,4,4,3,4,1,47,7.0,satisfied +20990,107973,Female,disloyal Customer,25,Business travel,Eco,825,2,2,2,4,1,2,5,1,3,4,3,3,4,1,0,0.0,neutral or dissatisfied +20991,118247,Male,Loyal Customer,40,Business travel,Business,1849,5,5,5,5,5,4,4,3,3,4,3,4,3,5,17,0.0,satisfied +20992,121500,Male,Loyal Customer,55,Personal Travel,Eco Plus,331,4,1,4,3,2,4,2,2,1,5,3,2,3,2,0,0.0,satisfied +20993,77236,Female,Loyal Customer,51,Business travel,Business,1590,3,1,1,1,4,4,4,3,3,3,3,4,3,1,0,2.0,neutral or dissatisfied +20994,79283,Female,Loyal Customer,43,Business travel,Business,2248,3,3,3,3,5,5,4,4,4,4,4,5,4,5,5,0.0,satisfied +20995,93361,Female,Loyal Customer,39,Business travel,Eco,624,4,1,1,1,4,4,4,4,5,2,3,4,3,4,4,0.0,satisfied +20996,41887,Female,Loyal Customer,58,Business travel,Business,129,3,3,3,3,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20997,95435,Female,Loyal Customer,49,Business travel,Business,2890,5,5,4,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +20998,26766,Male,Loyal Customer,14,Personal Travel,Eco,859,2,5,2,2,4,2,4,4,3,1,3,4,2,4,5,16.0,neutral or dissatisfied +20999,97095,Male,Loyal Customer,40,Business travel,Business,1242,2,2,2,2,3,4,4,5,5,5,5,5,5,5,29,37.0,satisfied +21000,126591,Male,Loyal Customer,52,Business travel,Business,1337,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +21001,63433,Male,Loyal Customer,40,Personal Travel,Eco,337,2,4,2,1,4,2,4,4,5,5,5,5,5,4,11,10.0,neutral or dissatisfied +21002,12110,Male,Loyal Customer,24,Business travel,Business,1034,5,5,5,5,4,4,4,4,5,4,1,5,5,4,0,0.0,satisfied +21003,15171,Female,Loyal Customer,44,Business travel,Eco,430,5,3,3,3,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +21004,29598,Female,Loyal Customer,31,Business travel,Eco,1448,4,1,1,1,4,4,4,4,4,2,1,2,4,4,0,0.0,satisfied +21005,112369,Male,disloyal Customer,22,Business travel,Eco,957,2,2,2,3,1,2,1,1,4,2,4,3,4,1,12,1.0,neutral or dissatisfied +21006,89915,Female,disloyal Customer,27,Business travel,Eco,1369,3,3,3,4,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +21007,56228,Female,Loyal Customer,52,Personal Travel,Eco,1608,2,2,2,1,1,1,2,5,5,2,5,4,5,4,0,37.0,neutral or dissatisfied +21008,78377,Male,Loyal Customer,31,Business travel,Business,980,1,1,1,1,4,4,4,4,4,4,5,4,4,4,0,5.0,satisfied +21009,44610,Female,Loyal Customer,8,Business travel,Eco,508,1,3,3,3,1,1,1,1,2,4,3,4,2,1,0,8.0,neutral or dissatisfied +21010,112500,Female,Loyal Customer,21,Personal Travel,Eco,819,3,3,3,3,5,3,5,5,3,5,5,5,5,5,17,1.0,neutral or dissatisfied +21011,282,Male,Loyal Customer,25,Personal Travel,Eco,825,4,5,4,4,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +21012,98729,Female,Loyal Customer,42,Business travel,Business,1558,4,4,4,4,4,5,5,5,5,5,5,5,5,4,8,19.0,satisfied +21013,18947,Female,Loyal Customer,43,Personal Travel,Eco,448,2,4,2,5,2,5,4,1,1,2,1,4,1,4,0,1.0,neutral or dissatisfied +21014,36155,Male,Loyal Customer,37,Business travel,Business,1674,4,4,4,4,2,5,5,4,4,4,4,3,4,3,4,0.0,satisfied +21015,58720,Male,Loyal Customer,31,Business travel,Business,1012,5,5,5,5,4,4,4,4,3,3,5,3,4,4,8,4.0,satisfied +21016,9888,Female,disloyal Customer,59,Business travel,Business,457,3,3,3,4,1,3,1,1,4,2,5,3,5,1,34,37.0,neutral or dissatisfied +21017,2350,Female,Loyal Customer,62,Personal Travel,Eco Plus,925,3,4,3,2,4,5,4,2,2,3,2,5,2,3,17,19.0,neutral or dissatisfied +21018,22107,Female,disloyal Customer,52,Business travel,Eco,694,1,1,1,3,1,1,1,1,3,4,1,1,4,1,10,0.0,neutral or dissatisfied +21019,97601,Male,Loyal Customer,38,Business travel,Eco,442,2,3,3,3,2,2,2,2,3,2,3,3,3,2,5,3.0,neutral or dissatisfied +21020,34734,Male,Loyal Customer,65,Business travel,Business,2849,3,5,4,5,3,3,2,3,3,3,3,2,3,4,0,4.0,neutral or dissatisfied +21021,63983,Female,disloyal Customer,26,Business travel,Business,1158,3,0,3,3,2,3,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +21022,61553,Male,Loyal Customer,66,Business travel,Eco Plus,2288,2,2,2,2,2,2,2,2,3,4,4,2,4,2,9,4.0,neutral or dissatisfied +21023,15565,Female,Loyal Customer,48,Business travel,Eco,292,4,2,5,2,4,4,4,5,1,5,2,4,4,4,207,226.0,satisfied +21024,66906,Male,Loyal Customer,39,Personal Travel,Business,1119,4,5,4,4,2,4,5,2,2,4,2,3,2,3,86,88.0,neutral or dissatisfied +21025,104419,Male,disloyal Customer,43,Business travel,Business,1036,4,4,4,3,2,4,2,2,4,4,5,5,5,2,0,0.0,satisfied +21026,47299,Male,Loyal Customer,30,Business travel,Business,558,1,1,1,1,5,5,5,5,5,2,3,2,5,5,44,26.0,satisfied +21027,72156,Female,Loyal Customer,29,Personal Travel,Eco,731,3,3,3,4,5,3,5,5,5,1,5,4,2,5,0,2.0,neutral or dissatisfied +21028,121893,Male,Loyal Customer,26,Personal Travel,Eco,337,2,4,2,3,3,2,5,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +21029,41429,Male,Loyal Customer,17,Personal Travel,Eco,809,3,3,3,3,4,3,5,4,3,2,3,4,2,4,21,6.0,neutral or dissatisfied +21030,127756,Male,Loyal Customer,48,Personal Travel,Eco,255,3,5,0,3,1,0,1,1,2,4,2,2,4,1,3,4.0,neutral or dissatisfied +21031,82066,Female,Loyal Customer,48,Business travel,Business,2336,2,2,2,2,4,5,5,5,5,5,5,3,5,3,35,25.0,satisfied +21032,116668,Female,Loyal Customer,47,Business travel,Eco Plus,371,2,1,1,1,3,4,3,2,2,2,2,3,2,4,34,25.0,neutral or dissatisfied +21033,19444,Male,Loyal Customer,21,Personal Travel,Eco,503,3,2,3,3,5,3,5,5,4,3,4,1,3,5,41,42.0,neutral or dissatisfied +21034,62457,Male,Loyal Customer,32,Business travel,Business,1726,4,4,4,4,4,4,4,4,5,5,3,4,4,4,93,96.0,satisfied +21035,69806,Male,Loyal Customer,42,Business travel,Business,1055,4,4,4,4,2,4,5,5,5,5,5,3,5,4,19,23.0,satisfied +21036,49756,Female,disloyal Customer,30,Business travel,Eco,110,3,5,3,3,5,3,5,5,3,5,3,1,3,5,0,0.0,neutral or dissatisfied +21037,65036,Male,Loyal Customer,70,Personal Travel,Eco,190,1,2,1,3,1,1,1,3,1,3,4,1,4,1,161,195.0,neutral or dissatisfied +21038,127607,Female,Loyal Customer,55,Business travel,Eco,1773,3,2,5,2,3,2,3,3,3,3,3,4,3,4,2,0.0,neutral or dissatisfied +21039,129208,Female,Loyal Customer,20,Personal Travel,Eco,2288,2,2,2,3,2,2,2,2,4,1,3,4,4,2,0,11.0,neutral or dissatisfied +21040,9320,Female,Loyal Customer,22,Business travel,Eco,542,4,4,4,4,4,4,2,4,4,1,4,3,3,4,3,0.0,neutral or dissatisfied +21041,57380,Male,Loyal Customer,45,Personal Travel,Eco Plus,236,2,5,0,4,4,0,4,4,4,4,4,4,5,4,3,0.0,neutral or dissatisfied +21042,43465,Male,Loyal Customer,58,Business travel,Eco,624,3,3,5,5,3,3,3,3,3,1,4,3,4,3,0,44.0,neutral or dissatisfied +21043,77255,Female,Loyal Customer,21,Personal Travel,Eco,1590,1,4,1,1,5,1,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +21044,23773,Male,Loyal Customer,37,Business travel,Business,438,5,5,5,5,2,3,4,3,3,4,3,3,3,2,2,0.0,satisfied +21045,15139,Male,Loyal Customer,23,Business travel,Business,912,3,4,5,4,3,2,3,3,3,4,2,4,3,3,3,12.0,neutral or dissatisfied +21046,2523,Female,Loyal Customer,40,Business travel,Business,280,5,5,5,5,4,4,5,5,5,5,5,3,5,4,48,74.0,satisfied +21047,336,Female,Loyal Customer,40,Business travel,Eco,421,4,4,4,4,4,4,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +21048,7308,Female,Loyal Customer,48,Business travel,Business,135,5,5,5,5,3,4,5,3,3,4,5,4,3,3,0,0.0,satisfied +21049,41804,Female,Loyal Customer,60,Business travel,Eco,196,2,1,2,1,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +21050,23665,Male,disloyal Customer,25,Business travel,Eco,152,2,0,2,2,1,2,1,1,2,1,4,5,2,1,0,0.0,neutral or dissatisfied +21051,39418,Female,disloyal Customer,22,Business travel,Eco,129,4,5,4,1,2,4,2,2,1,3,5,5,2,2,14,22.0,satisfied +21052,52574,Female,Loyal Customer,40,Business travel,Eco,119,5,3,4,3,5,5,5,5,1,4,2,4,1,5,0,0.0,satisfied +21053,119051,Female,Loyal Customer,51,Business travel,Business,2279,1,1,1,1,5,3,4,3,3,4,3,5,3,4,0,0.0,satisfied +21054,82908,Male,Loyal Customer,20,Personal Travel,Eco,594,4,4,4,2,2,4,1,2,3,5,4,2,3,2,11,13.0,neutral or dissatisfied +21055,129754,Male,disloyal Customer,36,Business travel,Eco,337,3,3,3,3,3,3,4,3,4,5,3,1,4,3,0,0.0,neutral or dissatisfied +21056,114904,Female,Loyal Customer,60,Business travel,Business,446,1,1,1,1,2,4,4,3,3,3,3,5,3,4,15,13.0,satisfied +21057,26603,Male,Loyal Customer,40,Business travel,Business,2555,1,1,3,1,3,2,2,5,5,5,5,1,5,2,3,0.0,satisfied +21058,42959,Male,disloyal Customer,25,Business travel,Business,236,5,5,5,2,3,5,2,3,1,1,3,4,1,3,0,0.0,satisfied +21059,29433,Female,Loyal Customer,45,Personal Travel,Eco,2149,2,4,2,4,5,4,4,5,5,2,2,4,5,4,7,0.0,neutral or dissatisfied +21060,4460,Female,Loyal Customer,59,Business travel,Business,1005,1,1,1,1,2,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +21061,7733,Female,Loyal Customer,47,Business travel,Business,2354,1,1,1,1,4,5,4,4,4,4,4,3,4,5,25,26.0,satisfied +21062,61965,Female,Loyal Customer,46,Business travel,Business,2052,1,3,1,1,2,4,5,5,5,5,5,4,5,5,0,4.0,satisfied +21063,67904,Male,Loyal Customer,21,Personal Travel,Eco,1171,2,4,2,2,4,2,4,4,5,2,3,3,4,4,0,0.0,neutral or dissatisfied +21064,26306,Male,Loyal Customer,27,Personal Travel,Business,2139,4,5,4,3,3,4,3,3,5,5,4,3,5,3,2,0.0,neutral or dissatisfied +21065,71757,Male,Loyal Customer,47,Business travel,Business,1726,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +21066,120615,Female,disloyal Customer,28,Business travel,Business,453,3,3,3,5,2,3,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +21067,96427,Female,disloyal Customer,26,Business travel,Business,436,4,4,4,5,4,4,4,4,4,2,5,4,5,4,31,36.0,satisfied +21068,37599,Male,disloyal Customer,21,Business travel,Eco,944,1,1,1,3,5,1,5,5,1,2,2,4,1,5,0,0.0,neutral or dissatisfied +21069,121578,Female,Loyal Customer,31,Business travel,Business,912,3,5,5,5,3,3,3,3,2,4,4,3,4,3,0,0.0,neutral or dissatisfied +21070,27761,Female,Loyal Customer,56,Business travel,Eco,1448,5,5,5,5,5,3,1,5,5,5,5,5,5,2,0,0.0,satisfied +21071,26446,Male,Loyal Customer,36,Business travel,Business,2127,4,1,1,1,1,1,2,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +21072,57271,Male,Loyal Customer,12,Personal Travel,Eco,804,2,4,2,4,4,2,4,4,1,1,3,1,4,4,0,0.0,neutral or dissatisfied +21073,45448,Male,Loyal Customer,60,Business travel,Business,2596,4,4,4,4,5,4,4,4,4,4,4,5,4,5,2,1.0,satisfied +21074,86390,Male,disloyal Customer,24,Business travel,Eco,762,2,2,2,3,5,2,4,5,2,5,4,2,4,5,0,0.0,neutral or dissatisfied +21075,5748,Female,disloyal Customer,27,Business travel,Business,642,4,4,4,2,3,4,2,3,3,3,4,3,5,3,0,17.0,satisfied +21076,114920,Male,Loyal Customer,59,Business travel,Business,308,0,0,0,1,4,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +21077,121149,Male,disloyal Customer,49,Business travel,Business,2402,1,1,1,1,1,5,5,4,5,4,4,5,3,5,294,284.0,neutral or dissatisfied +21078,51244,Female,Loyal Customer,52,Business travel,Eco Plus,326,5,5,5,5,2,1,4,5,5,5,5,4,5,5,7,5.0,satisfied +21079,118283,Male,Loyal Customer,40,Business travel,Business,2889,5,5,5,5,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +21080,62207,Female,Loyal Customer,47,Personal Travel,Eco,2454,3,1,3,2,3,2,2,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +21081,8516,Female,disloyal Customer,24,Business travel,Eco,462,1,1,1,1,3,1,3,3,4,2,1,1,1,3,83,61.0,neutral or dissatisfied +21082,125841,Female,Loyal Customer,41,Business travel,Eco,992,3,4,4,4,3,3,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +21083,113534,Male,disloyal Customer,21,Business travel,Eco,258,2,1,2,2,5,2,5,5,2,4,2,2,3,5,1,0.0,neutral or dissatisfied +21084,54411,Female,Loyal Customer,41,Business travel,Eco,305,4,5,5,5,4,4,4,4,2,1,3,3,3,4,3,3.0,satisfied +21085,1135,Female,Loyal Customer,36,Personal Travel,Eco,134,3,2,0,4,1,0,1,1,4,3,4,4,3,1,0,0.0,neutral or dissatisfied +21086,43467,Female,Loyal Customer,38,Business travel,Eco,624,2,3,2,3,2,2,2,2,4,2,2,2,3,2,0,0.0,neutral or dissatisfied +21087,124972,Male,Loyal Customer,37,Business travel,Business,1585,4,4,4,4,2,4,3,2,2,2,4,2,2,2,6,49.0,neutral or dissatisfied +21088,3650,Female,Loyal Customer,37,Business travel,Business,2003,1,1,1,1,4,5,4,5,5,5,5,3,5,4,0,10.0,satisfied +21089,17360,Female,Loyal Customer,65,Personal Travel,Eco,563,1,4,2,2,4,5,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +21090,110897,Male,Loyal Customer,79,Business travel,Business,1771,3,2,2,2,5,4,4,3,3,3,3,3,3,3,16,16.0,neutral or dissatisfied +21091,39204,Female,Loyal Customer,55,Business travel,Business,173,0,4,0,1,3,4,4,5,5,5,5,5,5,5,29,25.0,satisfied +21092,43338,Female,Loyal Customer,76,Business travel,Business,2552,1,4,4,4,3,2,2,1,1,1,1,2,1,3,0,3.0,neutral or dissatisfied +21093,60543,Male,Loyal Customer,21,Personal Travel,Eco,862,2,4,2,3,1,2,1,1,4,2,4,3,5,1,0,0.0,neutral or dissatisfied +21094,81328,Male,Loyal Customer,70,Business travel,Eco,1299,1,2,2,2,1,1,1,1,4,4,3,3,3,1,0,3.0,neutral or dissatisfied +21095,48490,Female,Loyal Customer,25,Business travel,Eco,776,4,5,3,3,4,4,1,4,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +21096,29759,Male,Loyal Customer,54,Business travel,Business,548,3,1,1,1,5,3,4,3,3,3,3,3,3,2,0,3.0,neutral or dissatisfied +21097,72160,Female,Loyal Customer,28,Personal Travel,Eco,731,1,5,1,3,5,1,5,5,4,3,5,1,1,5,0,0.0,neutral or dissatisfied +21098,40292,Female,Loyal Customer,21,Personal Travel,Eco,531,1,4,1,3,3,1,4,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +21099,30264,Female,disloyal Customer,27,Business travel,Eco,1024,1,1,1,3,1,1,1,1,3,2,2,3,2,1,35,45.0,neutral or dissatisfied +21100,126147,Male,Loyal Customer,62,Business travel,Business,3038,3,1,1,1,2,3,3,3,3,3,3,4,3,4,2,0.0,neutral or dissatisfied +21101,80799,Female,Loyal Customer,59,Business travel,Business,692,4,4,4,4,3,5,4,5,5,5,5,3,5,4,22,29.0,satisfied +21102,100824,Female,Loyal Customer,30,Business travel,Business,2636,5,5,5,5,4,4,4,4,5,2,5,3,4,4,1,0.0,satisfied +21103,68566,Female,Loyal Customer,43,Business travel,Business,1616,5,5,5,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +21104,87548,Male,Loyal Customer,23,Personal Travel,Business,743,3,5,3,2,1,3,1,1,3,3,5,4,5,1,25,25.0,neutral or dissatisfied +21105,66757,Female,Loyal Customer,32,Personal Travel,Eco,978,2,5,2,1,2,2,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +21106,52098,Female,Loyal Customer,29,Personal Travel,Eco,438,1,5,2,1,1,2,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +21107,78967,Male,disloyal Customer,34,Business travel,Business,356,2,2,2,5,2,2,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +21108,69569,Male,disloyal Customer,28,Business travel,Eco,1474,4,5,5,3,4,1,1,3,2,2,3,1,1,1,0,2.0,neutral or dissatisfied +21109,118989,Male,Loyal Customer,45,Business travel,Business,459,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,2.0,satisfied +21110,10987,Female,disloyal Customer,37,Business travel,Eco,140,1,2,1,3,3,1,3,3,1,5,3,1,3,3,31,17.0,neutral or dissatisfied +21111,6178,Male,Loyal Customer,43,Personal Travel,Eco,491,3,4,3,3,3,3,3,5,1,1,5,3,5,3,167,159.0,neutral or dissatisfied +21112,86675,Male,Loyal Customer,42,Business travel,Business,3035,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +21113,123478,Male,Loyal Customer,45,Business travel,Business,2077,1,2,2,2,2,2,2,1,1,1,1,4,1,3,13,0.0,neutral or dissatisfied +21114,89837,Female,Loyal Customer,45,Business travel,Business,539,2,2,2,2,3,3,3,3,3,3,3,2,3,5,0,3.0,satisfied +21115,27689,Male,Loyal Customer,41,Business travel,Business,2821,5,5,5,5,4,1,1,4,4,4,4,4,4,3,4,0.0,satisfied +21116,32416,Female,Loyal Customer,48,Business travel,Eco,201,5,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +21117,60291,Female,Loyal Customer,8,Business travel,Business,3678,4,4,4,4,4,4,4,4,5,4,5,5,4,4,2,0.0,satisfied +21118,87096,Female,Loyal Customer,26,Business travel,Business,3043,2,2,2,2,2,2,2,2,4,4,1,2,2,2,8,8.0,neutral or dissatisfied +21119,100158,Male,Loyal Customer,47,Business travel,Business,325,1,1,1,1,2,1,3,4,4,4,4,3,4,2,4,0.0,satisfied +21120,121687,Male,Loyal Customer,56,Personal Travel,Eco,328,3,4,3,3,5,3,5,5,3,2,4,1,3,5,0,0.0,neutral or dissatisfied +21121,7057,Female,Loyal Customer,54,Business travel,Business,1503,0,5,0,4,2,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +21122,109996,Female,disloyal Customer,44,Business travel,Business,1204,2,2,2,3,5,2,5,5,2,4,2,1,2,5,24,0.0,neutral or dissatisfied +21123,124852,Male,Loyal Customer,18,Personal Travel,Eco,280,2,4,2,2,5,2,5,5,3,2,4,3,5,5,15,20.0,neutral or dissatisfied +21124,8906,Female,Loyal Customer,34,Business travel,Business,510,1,5,5,5,1,3,3,1,1,1,1,4,1,4,0,23.0,neutral or dissatisfied +21125,18854,Female,Loyal Customer,37,Business travel,Eco,448,4,1,1,1,4,4,4,4,5,4,2,1,2,4,0,0.0,satisfied +21126,38233,Male,Loyal Customer,30,Business travel,Business,3863,4,4,4,4,3,4,3,3,1,4,3,1,2,3,0,0.0,satisfied +21127,67979,Female,disloyal Customer,15,Business travel,Eco,1188,1,1,1,3,2,1,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +21128,43709,Female,Loyal Customer,21,Personal Travel,Eco,489,2,1,2,3,1,2,2,1,3,3,3,2,3,1,0,11.0,neutral or dissatisfied +21129,98605,Male,Loyal Customer,45,Business travel,Business,2155,4,5,4,4,2,4,4,5,5,5,5,5,5,5,37,56.0,satisfied +21130,126155,Female,Loyal Customer,44,Business travel,Eco,468,4,5,5,5,2,2,1,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +21131,62262,Female,disloyal Customer,24,Business travel,Eco,2454,2,2,2,4,2,2,2,2,1,1,2,2,3,2,5,8.0,neutral or dissatisfied +21132,129777,Female,Loyal Customer,64,Personal Travel,Eco,308,2,4,5,4,2,4,4,2,2,5,2,4,2,4,0,2.0,neutral or dissatisfied +21133,116466,Female,Loyal Customer,34,Personal Travel,Eco,308,3,4,3,2,2,3,2,2,4,4,5,5,4,2,25,36.0,neutral or dissatisfied +21134,45661,Female,Loyal Customer,51,Business travel,Eco Plus,313,2,2,2,2,4,3,3,2,2,2,2,1,2,3,12,48.0,neutral or dissatisfied +21135,65892,Male,Loyal Customer,41,Personal Travel,Business,569,3,5,3,3,2,5,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +21136,52908,Male,Loyal Customer,25,Business travel,Business,3327,2,2,2,2,5,5,5,4,5,5,3,5,1,5,250,270.0,satisfied +21137,70610,Male,Loyal Customer,17,Personal Travel,Eco Plus,2611,1,4,1,1,1,3,3,3,4,4,4,3,4,3,10,0.0,neutral or dissatisfied +21138,35223,Female,disloyal Customer,50,Business travel,Eco,1005,1,1,1,5,4,1,4,4,1,3,2,4,2,4,0,4.0,neutral or dissatisfied +21139,28250,Male,Loyal Customer,59,Business travel,Eco,1542,5,3,3,3,5,5,5,5,4,5,2,4,1,5,23,30.0,satisfied +21140,17288,Female,Loyal Customer,38,Business travel,Eco,403,3,5,5,5,3,3,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +21141,80687,Male,disloyal Customer,38,Business travel,Business,874,4,4,4,4,2,4,2,2,3,4,5,4,4,2,16,15.0,satisfied +21142,48953,Female,disloyal Customer,22,Business travel,Eco,89,2,0,2,2,3,2,3,3,4,2,1,1,1,3,0,1.0,neutral or dissatisfied +21143,108966,Male,Loyal Customer,31,Personal Travel,Eco,667,2,4,2,4,2,2,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +21144,43091,Female,Loyal Customer,38,Personal Travel,Eco,236,1,2,1,3,5,1,5,5,4,5,4,3,4,5,0,39.0,neutral or dissatisfied +21145,128611,Male,Loyal Customer,45,Business travel,Eco,679,2,3,3,3,2,2,2,2,3,5,3,4,4,2,68,60.0,neutral or dissatisfied +21146,73251,Male,Loyal Customer,28,Business travel,Business,2711,2,2,1,1,2,2,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +21147,37525,Male,disloyal Customer,17,Business travel,Eco,1011,4,4,4,3,4,3,3,2,3,3,3,3,4,3,330,322.0,neutral or dissatisfied +21148,97727,Male,Loyal Customer,60,Business travel,Business,1758,4,4,4,4,3,5,4,4,4,4,4,3,4,4,10,0.0,satisfied +21149,115728,Female,Loyal Customer,53,Business travel,Business,3430,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +21150,29318,Male,Loyal Customer,55,Personal Travel,Eco,834,1,5,1,3,3,1,3,3,2,5,5,4,5,3,0,0.0,neutral or dissatisfied +21151,81555,Male,disloyal Customer,27,Business travel,Business,936,4,5,5,1,3,5,4,3,4,3,5,4,4,3,9,0.0,neutral or dissatisfied +21152,47529,Male,Loyal Customer,19,Personal Travel,Eco,574,1,5,1,3,4,1,4,4,2,5,5,3,3,4,64,53.0,neutral or dissatisfied +21153,40072,Male,Loyal Customer,56,Business travel,Eco,493,5,2,5,5,5,5,5,5,2,3,3,5,1,5,0,0.0,satisfied +21154,80143,Male,Loyal Customer,55,Business travel,Business,2475,2,2,2,2,5,4,4,3,3,4,5,4,3,4,67,77.0,satisfied +21155,36565,Male,Loyal Customer,56,Business travel,Business,2273,1,1,1,1,4,3,4,4,4,4,4,3,4,5,0,6.0,satisfied +21156,86386,Male,Loyal Customer,50,Business travel,Business,2965,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +21157,79145,Male,Loyal Customer,16,Personal Travel,Eco Plus,356,2,1,2,3,2,2,2,2,2,3,3,4,3,2,0,0.0,neutral or dissatisfied +21158,90209,Male,Loyal Customer,67,Personal Travel,Eco,1127,1,5,1,1,1,1,1,1,5,3,3,3,5,1,23,3.0,neutral or dissatisfied +21159,9669,Female,disloyal Customer,22,Business travel,Eco,199,2,0,2,5,1,2,1,1,4,3,4,5,5,1,101,100.0,neutral or dissatisfied +21160,121575,Male,Loyal Customer,47,Business travel,Business,2655,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +21161,119794,Male,Loyal Customer,41,Business travel,Business,1605,5,5,5,5,5,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +21162,126447,Male,Loyal Customer,53,Business travel,Business,1972,1,1,4,1,3,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +21163,117261,Female,Loyal Customer,13,Personal Travel,Eco,325,3,3,3,4,5,3,2,5,3,5,3,3,3,5,79,75.0,neutral or dissatisfied +21164,101792,Female,Loyal Customer,48,Business travel,Eco,1521,1,2,2,2,5,2,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +21165,27621,Female,Loyal Customer,25,Business travel,Eco Plus,987,5,5,3,5,5,5,4,5,5,5,1,5,5,5,0,0.0,satisfied +21166,85251,Female,Loyal Customer,14,Personal Travel,Eco,813,4,3,3,4,2,3,2,2,1,4,3,2,4,2,14,7.0,neutral or dissatisfied +21167,16487,Female,Loyal Customer,50,Business travel,Business,3502,2,2,2,2,4,3,1,4,4,4,5,1,4,2,0,0.0,satisfied +21168,107494,Male,Loyal Customer,42,Business travel,Business,711,2,5,5,5,3,4,4,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +21169,91869,Female,disloyal Customer,24,Business travel,Eco,780,4,5,5,4,5,5,5,5,5,4,4,5,5,5,11,10.0,satisfied +21170,43955,Male,Loyal Customer,25,Personal Travel,Eco,257,4,1,0,4,2,0,2,2,2,3,4,4,3,2,0,0.0,satisfied +21171,31955,Male,Loyal Customer,39,Business travel,Business,2448,2,2,2,2,4,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +21172,38345,Male,Loyal Customer,31,Business travel,Business,1050,4,2,4,4,4,4,4,4,4,3,3,5,5,4,0,18.0,satisfied +21173,13086,Female,Loyal Customer,56,Business travel,Eco,427,2,2,2,2,5,1,4,2,2,2,2,1,2,2,0,0.0,satisfied +21174,47476,Female,Loyal Customer,68,Personal Travel,Eco,584,4,4,4,3,2,5,5,2,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +21175,73195,Male,Loyal Customer,43,Business travel,Business,2749,4,2,2,2,1,4,4,4,4,4,4,3,4,1,9,5.0,neutral or dissatisfied +21176,43610,Female,Loyal Customer,60,Business travel,Business,3956,3,1,4,1,1,4,4,1,1,1,3,1,1,1,0,0.0,neutral or dissatisfied +21177,40437,Male,Loyal Customer,45,Business travel,Eco,188,4,4,4,4,4,4,4,4,4,1,2,3,2,4,0,0.0,satisfied +21178,33555,Female,Loyal Customer,47,Business travel,Business,4000,2,2,3,2,5,3,2,5,5,5,5,5,5,2,0,0.0,satisfied +21179,28367,Female,Loyal Customer,52,Business travel,Business,2714,3,3,3,3,5,4,4,3,1,3,3,4,4,4,129,135.0,satisfied +21180,118836,Female,Loyal Customer,57,Business travel,Business,646,5,5,5,5,5,5,4,4,4,3,4,3,4,5,14,0.0,satisfied +21181,75607,Male,Loyal Customer,68,Personal Travel,Eco,337,3,5,3,3,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +21182,56986,Female,Loyal Customer,11,Personal Travel,Eco,2454,3,2,3,3,3,3,3,3,4,2,3,1,4,3,17,0.0,neutral or dissatisfied +21183,119020,Female,Loyal Customer,60,Business travel,Business,1460,3,4,2,4,4,4,3,3,3,3,3,2,3,4,0,17.0,neutral or dissatisfied +21184,61698,Female,disloyal Customer,26,Business travel,Eco,1303,3,3,3,4,1,3,1,1,1,4,3,1,4,1,0,0.0,neutral or dissatisfied +21185,17430,Male,Loyal Customer,46,Business travel,Eco,351,4,5,5,5,4,4,4,4,3,3,4,2,5,4,17,6.0,satisfied +21186,38671,Male,Loyal Customer,10,Personal Travel,Eco,2602,1,4,1,2,5,1,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +21187,110714,Female,Loyal Customer,52,Business travel,Business,1105,2,2,2,2,1,2,3,2,2,2,2,3,2,2,16,6.0,neutral or dissatisfied +21188,88794,Female,disloyal Customer,38,Business travel,Eco Plus,270,3,3,3,3,2,3,4,2,1,5,4,1,3,2,0,0.0,neutral or dissatisfied +21189,110523,Female,disloyal Customer,29,Business travel,Business,551,4,4,4,4,5,4,1,5,3,4,5,4,5,5,64,63.0,satisfied +21190,38110,Female,Loyal Customer,29,Business travel,Eco,1091,3,3,3,3,3,3,3,3,2,2,3,4,3,3,2,0.0,neutral or dissatisfied +21191,74135,Female,Loyal Customer,45,Business travel,Business,3897,1,5,5,5,1,1,1,4,2,4,3,1,1,1,123,134.0,neutral or dissatisfied +21192,10945,Female,disloyal Customer,35,Business travel,Eco,201,3,3,3,4,1,3,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +21193,25088,Female,disloyal Customer,26,Business travel,Eco,149,4,0,5,2,3,5,3,3,1,3,5,3,1,3,1,1.0,neutral or dissatisfied +21194,38612,Female,Loyal Customer,67,Personal Travel,Eco,231,4,1,4,4,5,3,3,3,3,4,4,2,3,4,0,0.0,satisfied +21195,110444,Male,Loyal Customer,18,Personal Travel,Eco,919,5,3,4,3,1,4,1,1,4,1,4,3,4,1,0,0.0,satisfied +21196,12554,Male,Loyal Customer,14,Personal Travel,Eco,788,1,2,1,3,1,4,4,4,2,4,4,4,1,4,232,242.0,neutral or dissatisfied +21197,49762,Female,Loyal Customer,43,Business travel,Eco,262,3,3,3,3,1,1,3,3,3,3,3,2,3,1,0,0.0,satisfied +21198,58492,Female,Loyal Customer,52,Business travel,Business,719,5,5,5,5,4,5,5,5,5,5,5,5,5,3,32,21.0,satisfied +21199,38576,Male,Loyal Customer,36,Personal Travel,Eco,2465,3,5,2,2,1,2,1,1,3,5,5,4,3,1,5,0.0,neutral or dissatisfied +21200,15267,Female,Loyal Customer,55,Business travel,Business,3126,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +21201,124110,Male,Loyal Customer,23,Business travel,Eco,529,2,4,4,4,2,2,1,2,4,3,3,2,2,2,0,7.0,neutral or dissatisfied +21202,10348,Male,disloyal Customer,20,Business travel,Business,158,4,0,4,3,4,4,4,4,3,5,5,5,5,4,0,0.0,satisfied +21203,91053,Female,Loyal Customer,69,Personal Travel,Eco,406,4,4,3,1,4,4,4,4,4,3,1,4,4,4,0,0.0,neutral or dissatisfied +21204,41114,Male,Loyal Customer,58,Business travel,Eco,191,2,2,5,2,1,2,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +21205,29616,Female,Loyal Customer,39,Business travel,Business,1448,2,1,1,1,5,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +21206,101738,Male,Loyal Customer,51,Personal Travel,Business,1590,1,3,1,4,2,4,4,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +21207,11070,Female,Loyal Customer,7,Personal Travel,Eco,224,3,2,0,4,4,0,4,4,2,3,3,3,3,4,0,0.0,neutral or dissatisfied +21208,5072,Male,Loyal Customer,40,Business travel,Business,235,2,2,5,2,2,4,5,5,5,4,5,4,5,4,24,21.0,satisfied +21209,113024,Male,Loyal Customer,21,Personal Travel,Business,569,2,4,2,1,2,2,2,2,5,3,4,5,5,2,14,13.0,neutral or dissatisfied +21210,4732,Male,Loyal Customer,46,Business travel,Business,888,5,5,2,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +21211,121631,Female,disloyal Customer,30,Business travel,Business,912,0,0,0,5,3,0,3,3,3,2,4,3,5,3,0,0.0,satisfied +21212,37583,Male,Loyal Customer,37,Business travel,Eco,428,3,4,4,4,3,3,3,3,4,3,3,2,4,3,36,23.0,neutral or dissatisfied +21213,83040,Female,Loyal Customer,55,Business travel,Business,3221,2,2,2,2,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +21214,11424,Female,Loyal Customer,48,Business travel,Business,3688,4,4,4,4,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +21215,108652,Female,disloyal Customer,43,Business travel,Eco,940,1,1,1,4,1,1,1,1,2,5,4,2,3,1,23,27.0,neutral or dissatisfied +21216,13953,Female,Loyal Customer,13,Personal Travel,Eco,192,3,5,0,3,4,0,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +21217,84388,Male,Loyal Customer,44,Business travel,Business,3037,4,1,1,1,2,3,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +21218,69291,Female,Loyal Customer,43,Business travel,Business,733,2,2,4,2,2,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +21219,15125,Male,Loyal Customer,24,Business travel,Eco,1042,5,2,2,2,5,5,4,5,2,1,2,1,1,5,0,0.0,satisfied +21220,117592,Male,Loyal Customer,29,Business travel,Business,2049,4,4,4,4,3,3,3,3,3,5,4,3,4,3,0,0.0,satisfied +21221,126867,Female,Loyal Customer,21,Personal Travel,Eco,2077,2,0,2,4,3,2,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +21222,103239,Male,disloyal Customer,37,Business travel,Eco,409,3,1,3,4,1,3,1,1,4,5,4,4,4,1,9,2.0,neutral or dissatisfied +21223,120236,Male,Loyal Customer,52,Personal Travel,Eco,1325,2,4,2,3,3,2,3,3,3,3,3,5,4,3,0,7.0,neutral or dissatisfied +21224,100421,Female,Loyal Customer,50,Personal Travel,Eco Plus,1034,3,2,3,4,2,3,3,5,5,3,5,3,5,4,55,100.0,neutral or dissatisfied +21225,110335,Female,Loyal Customer,47,Business travel,Business,925,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21226,57383,Male,Loyal Customer,25,Personal Travel,Eco,416,2,3,2,3,2,2,2,2,3,2,3,1,5,2,42,45.0,neutral or dissatisfied +21227,32127,Male,Loyal Customer,37,Business travel,Business,101,4,4,4,4,2,4,4,5,5,5,3,3,5,5,0,0.0,satisfied +21228,105397,Male,Loyal Customer,66,Personal Travel,Eco,369,3,5,3,3,1,3,2,1,4,1,2,2,3,1,20,8.0,neutral or dissatisfied +21229,72,Male,Loyal Customer,53,Business travel,Business,3201,3,2,2,2,3,3,3,2,2,1,3,3,2,1,7,24.0,neutral or dissatisfied +21230,78760,Female,disloyal Customer,26,Business travel,Business,432,4,4,4,3,2,4,2,2,4,4,5,5,5,2,0,0.0,satisfied +21231,25779,Female,Loyal Customer,35,Business travel,Business,3498,2,2,2,2,2,4,5,5,5,5,5,2,5,5,22,8.0,satisfied +21232,7462,Male,Loyal Customer,56,Business travel,Business,2136,3,3,5,3,2,4,5,5,5,5,5,3,5,4,21,55.0,satisfied +21233,43546,Female,Loyal Customer,32,Personal Travel,Eco,440,2,4,2,4,3,2,1,3,2,2,4,2,3,3,20,26.0,neutral or dissatisfied +21234,9614,Female,Loyal Customer,10,Personal Travel,Eco,283,1,4,1,1,2,1,2,2,3,2,4,3,4,2,19,16.0,neutral or dissatisfied +21235,72608,Male,Loyal Customer,54,Personal Travel,Eco,985,5,5,5,5,4,5,4,4,5,4,4,4,5,4,0,0.0,satisfied +21236,104395,Male,Loyal Customer,57,Business travel,Business,1041,2,1,1,1,5,4,3,2,2,2,2,4,2,1,50,35.0,neutral or dissatisfied +21237,126964,Female,Loyal Customer,48,Business travel,Business,3587,3,3,3,3,4,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +21238,6743,Male,disloyal Customer,22,Business travel,Eco,224,2,0,2,2,3,2,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +21239,111593,Female,Loyal Customer,34,Personal Travel,Eco,794,4,5,4,4,5,4,5,5,3,2,4,3,5,5,35,29.0,neutral or dissatisfied +21240,74676,Female,Loyal Customer,43,Personal Travel,Eco,1171,3,5,3,4,4,3,5,4,4,3,4,5,4,3,9,0.0,neutral or dissatisfied +21241,123670,Male,Loyal Customer,50,Business travel,Business,214,3,3,3,3,2,4,5,4,4,4,5,5,4,4,47,38.0,satisfied +21242,60334,Male,disloyal Customer,25,Business travel,Eco,1024,1,1,1,3,2,1,2,2,4,5,4,3,4,2,93,86.0,neutral or dissatisfied +21243,18190,Female,Loyal Customer,46,Business travel,Eco,235,5,1,1,1,3,1,1,5,5,5,5,3,5,1,14,0.0,satisfied +21244,24380,Female,Loyal Customer,45,Business travel,Eco,669,3,1,1,1,4,3,4,3,3,3,3,3,3,3,19,32.0,neutral or dissatisfied +21245,58389,Female,disloyal Customer,20,Business travel,Eco,733,2,2,2,5,5,2,4,5,3,2,4,3,4,5,39,25.0,neutral or dissatisfied +21246,116807,Female,Loyal Customer,55,Business travel,Eco Plus,362,4,1,1,1,4,4,4,4,4,4,4,1,4,4,24,10.0,neutral or dissatisfied +21247,10173,Male,disloyal Customer,21,Business travel,Eco,140,2,0,2,3,3,2,3,3,4,2,4,5,5,3,3,38.0,neutral or dissatisfied +21248,101805,Female,Loyal Customer,54,Business travel,Business,1521,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +21249,117573,Male,Loyal Customer,43,Business travel,Business,1722,1,1,1,1,3,5,4,4,4,4,4,4,4,4,1,2.0,satisfied +21250,68601,Female,disloyal Customer,22,Business travel,Eco,1084,3,3,3,3,3,3,5,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +21251,3605,Male,Loyal Customer,63,Personal Travel,Eco,999,5,2,5,4,3,5,3,3,4,4,4,3,4,3,0,4.0,satisfied +21252,11214,Male,Loyal Customer,53,Personal Travel,Eco,74,2,5,2,2,4,2,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +21253,120899,Male,Loyal Customer,48,Business travel,Business,3991,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +21254,120423,Female,Loyal Customer,58,Business travel,Business,366,1,1,2,1,5,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +21255,5670,Male,disloyal Customer,22,Business travel,Eco,299,3,0,3,3,1,3,1,1,5,4,4,4,4,1,2,16.0,neutral or dissatisfied +21256,112233,Female,disloyal Customer,49,Business travel,Business,1506,4,5,5,1,1,4,1,1,4,3,4,3,5,1,12,8.0,satisfied +21257,21745,Female,Loyal Customer,47,Business travel,Eco,563,4,1,1,1,1,4,4,4,4,4,4,5,4,2,0,0.0,satisfied +21258,20253,Female,Loyal Customer,18,Business travel,Business,2013,2,3,3,3,2,2,2,2,1,3,3,3,4,2,2,0.0,neutral or dissatisfied +21259,47082,Male,Loyal Customer,22,Personal Travel,Eco,639,1,5,1,1,2,1,2,2,3,3,1,1,3,2,0,0.0,neutral or dissatisfied +21260,106243,Male,Loyal Customer,57,Business travel,Business,3936,2,2,2,2,3,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +21261,71531,Female,disloyal Customer,25,Business travel,Business,1144,2,0,2,3,1,2,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +21262,13078,Male,Loyal Customer,53,Business travel,Business,3445,3,3,5,3,5,5,4,4,4,4,4,4,4,5,64,57.0,satisfied +21263,44239,Female,Loyal Customer,64,Business travel,Eco,118,4,3,3,3,3,4,3,4,4,4,4,3,4,1,0,0.0,satisfied +21264,11245,Male,Loyal Customer,17,Personal Travel,Eco,216,3,5,3,4,4,3,4,4,5,2,4,4,4,4,4,23.0,neutral or dissatisfied +21265,117631,Female,Loyal Customer,47,Personal Travel,Eco,872,1,1,0,3,4,3,2,1,1,0,1,1,1,4,0,0.0,neutral or dissatisfied +21266,2667,Female,disloyal Customer,29,Business travel,Eco,622,3,2,3,4,1,3,5,1,1,1,4,1,3,1,3,0.0,neutral or dissatisfied +21267,62703,Male,disloyal Customer,46,Business travel,Business,2504,2,3,3,3,4,2,4,4,5,5,3,4,4,4,0,0.0,neutral or dissatisfied +21268,25462,Male,Loyal Customer,47,Business travel,Business,2874,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +21269,79479,Male,Loyal Customer,40,Business travel,Business,2629,2,2,2,2,3,4,5,4,4,4,4,4,4,4,38,35.0,satisfied +21270,27814,Female,Loyal Customer,70,Business travel,Business,1448,2,3,3,3,4,3,4,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +21271,116729,Male,Loyal Customer,37,Personal Travel,Eco Plus,296,0,4,0,2,4,0,4,4,4,5,5,5,4,4,7,3.0,satisfied +21272,123563,Female,Loyal Customer,46,Business travel,Business,1773,1,1,1,1,4,4,4,5,5,5,5,4,5,4,3,0.0,satisfied +21273,90363,Male,Loyal Customer,54,Business travel,Business,3658,3,1,1,1,5,3,4,3,3,3,3,1,3,2,43,55.0,neutral or dissatisfied +21274,121875,Female,disloyal Customer,36,Business travel,Eco,366,4,5,4,4,5,4,5,5,4,2,4,4,4,5,7,1.0,neutral or dissatisfied +21275,74916,Female,Loyal Customer,45,Business travel,Business,2586,2,2,1,2,3,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +21276,128598,Female,Loyal Customer,35,Personal Travel,Business,679,3,4,3,3,4,5,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +21277,5980,Male,Loyal Customer,48,Business travel,Business,672,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +21278,111868,Male,disloyal Customer,12,Business travel,Eco,628,2,0,1,4,3,1,3,3,1,2,3,4,4,3,22,17.0,neutral or dissatisfied +21279,92636,Male,Loyal Customer,50,Business travel,Business,453,2,1,1,1,4,4,3,2,2,2,2,3,2,2,7,17.0,neutral or dissatisfied +21280,39013,Female,Loyal Customer,33,Business travel,Eco,230,3,2,2,2,3,3,3,3,3,2,1,1,1,3,62,80.0,neutral or dissatisfied +21281,118967,Female,Loyal Customer,60,Personal Travel,Eco,570,4,4,4,3,4,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +21282,47280,Male,Loyal Customer,31,Business travel,Business,590,2,2,2,2,5,5,5,5,1,3,5,3,5,5,0,0.0,satisfied +21283,110257,Female,Loyal Customer,60,Business travel,Business,3416,5,5,5,5,5,4,5,3,3,3,3,3,3,3,3,0.0,satisfied +21284,77347,Female,disloyal Customer,26,Business travel,Business,590,0,0,0,3,1,0,5,1,5,4,5,5,5,1,0,0.0,satisfied +21285,1978,Male,Loyal Customer,62,Personal Travel,Eco,351,2,5,2,1,2,2,2,2,4,2,5,3,4,2,50,106.0,neutral or dissatisfied +21286,24535,Female,Loyal Customer,55,Business travel,Business,2348,5,5,3,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +21287,32741,Female,Loyal Customer,65,Business travel,Business,101,1,1,1,1,2,3,3,3,3,3,1,2,3,3,0,0.0,neutral or dissatisfied +21288,119201,Female,Loyal Customer,37,Business travel,Eco,257,2,4,4,4,2,3,2,2,2,5,4,3,3,2,0,0.0,neutral or dissatisfied +21289,47788,Male,disloyal Customer,40,Business travel,Eco,412,3,5,3,1,3,3,3,3,1,3,2,5,2,3,3,0.0,neutral or dissatisfied +21290,74337,Male,Loyal Customer,62,Personal Travel,Business,1188,4,4,4,4,3,2,3,3,3,4,1,2,3,4,0,0.0,neutral or dissatisfied +21291,88779,Female,disloyal Customer,35,Business travel,Business,545,1,1,1,2,3,1,5,3,3,2,4,4,5,3,26,24.0,neutral or dissatisfied +21292,49529,Female,Loyal Customer,50,Business travel,Business,3595,2,2,2,2,4,2,4,5,5,5,5,4,5,2,0,0.0,satisfied +21293,5657,Female,Loyal Customer,48,Business travel,Business,2073,2,2,3,2,2,5,5,4,4,4,4,3,4,5,19,26.0,satisfied +21294,126410,Male,Loyal Customer,53,Business travel,Business,328,2,2,2,2,5,5,4,5,5,5,5,5,5,4,1,0.0,satisfied +21295,52350,Male,Loyal Customer,47,Personal Travel,Eco,493,4,4,4,4,2,4,3,2,5,2,5,4,4,2,2,2.0,satisfied +21296,121897,Female,Loyal Customer,33,Personal Travel,Eco,449,5,4,5,3,2,5,2,2,4,3,4,4,4,2,0,0.0,satisfied +21297,8707,Male,Loyal Customer,8,Personal Travel,Eco,227,1,3,1,5,3,1,3,3,2,4,2,4,1,3,0,0.0,neutral or dissatisfied +21298,104398,Male,Loyal Customer,46,Business travel,Business,2370,5,5,5,5,5,5,4,5,5,5,5,4,5,3,111,108.0,satisfied +21299,20296,Female,Loyal Customer,36,Personal Travel,Eco,228,4,4,4,3,5,4,5,5,3,3,5,3,4,5,0,8.0,neutral or dissatisfied +21300,119165,Male,Loyal Customer,60,Business travel,Business,331,3,3,3,3,2,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +21301,34478,Female,Loyal Customer,33,Personal Travel,Eco,266,0,5,0,3,2,0,2,2,3,3,5,4,5,2,0,0.0,satisfied +21302,89698,Female,Loyal Customer,31,Business travel,Eco,1096,1,3,5,3,1,2,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +21303,91489,Male,Loyal Customer,36,Business travel,Eco Plus,859,1,3,3,3,1,1,1,1,2,4,3,3,4,1,0,18.0,neutral or dissatisfied +21304,77983,Male,Loyal Customer,45,Business travel,Business,152,2,2,2,2,4,5,5,4,4,4,4,5,4,3,35,25.0,satisfied +21305,116297,Male,Loyal Customer,12,Personal Travel,Eco,308,1,5,1,3,5,1,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +21306,68949,Male,Loyal Customer,38,Personal Travel,Eco,646,3,5,3,4,4,3,4,4,5,1,4,3,1,4,0,0.0,neutral or dissatisfied +21307,62587,Male,Loyal Customer,45,Business travel,Eco,1723,3,4,2,4,3,3,3,3,3,2,3,2,3,3,15,14.0,neutral or dissatisfied +21308,59082,Female,disloyal Customer,39,Business travel,Eco,346,4,3,4,3,2,4,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +21309,124563,Male,Loyal Customer,35,Personal Travel,Eco,453,1,5,3,3,2,3,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +21310,94439,Male,Loyal Customer,42,Business travel,Business,2453,2,2,4,2,4,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +21311,83514,Male,Loyal Customer,18,Personal Travel,Eco,946,3,5,3,2,3,3,3,3,4,5,1,3,2,3,3,0.0,neutral or dissatisfied +21312,50552,Female,Loyal Customer,58,Personal Travel,Eco,421,3,5,3,1,4,4,5,2,2,3,2,5,2,1,9,14.0,neutral or dissatisfied +21313,68827,Female,Loyal Customer,53,Business travel,Business,1995,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,23.0,satisfied +21314,89080,Female,Loyal Customer,53,Business travel,Business,2092,5,5,2,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21315,72772,Female,disloyal Customer,47,Business travel,Business,1045,3,3,3,4,3,3,1,3,5,2,5,4,4,3,4,0.0,neutral or dissatisfied +21316,102609,Female,Loyal Customer,66,Personal Travel,Eco Plus,386,0,5,0,2,2,4,4,1,1,0,1,4,1,3,0,0.0,satisfied +21317,60436,Female,Loyal Customer,60,Business travel,Business,862,4,4,4,4,2,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +21318,39827,Male,Loyal Customer,24,Business travel,Business,272,1,1,1,1,5,5,5,5,4,5,3,2,2,5,0,0.0,satisfied +21319,29271,Male,Loyal Customer,38,Business travel,Business,859,3,1,1,1,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +21320,128525,Female,Loyal Customer,24,Personal Travel,Eco,355,2,4,2,5,3,2,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +21321,913,Female,Loyal Customer,41,Business travel,Business,2743,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +21322,69936,Male,Loyal Customer,35,Business travel,Business,2174,2,1,2,2,2,3,5,5,5,5,5,5,5,3,17,0.0,satisfied +21323,41863,Female,Loyal Customer,63,Personal Travel,Eco,483,2,4,2,5,2,5,1,5,5,2,5,2,5,5,0,16.0,neutral or dissatisfied +21324,53395,Male,Loyal Customer,51,Business travel,Business,2442,2,2,3,2,4,4,4,5,4,4,5,4,4,4,0,1.0,satisfied +21325,56034,Male,Loyal Customer,28,Business travel,Eco,2586,1,5,2,5,1,1,1,2,1,4,3,1,1,1,0,0.0,neutral or dissatisfied +21326,26232,Male,Loyal Customer,31,Personal Travel,Eco,406,2,2,2,3,1,2,1,1,1,3,2,4,3,1,43,54.0,neutral or dissatisfied +21327,25109,Male,Loyal Customer,40,Business travel,Eco,946,4,1,1,1,4,4,4,4,1,5,4,2,2,4,0,19.0,satisfied +21328,52233,Female,disloyal Customer,46,Business travel,Eco,370,1,5,1,4,3,1,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +21329,118010,Male,disloyal Customer,19,Business travel,Eco,1037,3,4,4,3,4,4,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +21330,123916,Female,Loyal Customer,39,Personal Travel,Eco,544,2,2,2,2,4,2,4,4,3,2,2,1,2,4,12,5.0,neutral or dissatisfied +21331,32762,Female,disloyal Customer,36,Business travel,Eco,163,3,3,3,4,5,3,5,5,3,5,4,2,3,5,0,0.0,neutral or dissatisfied +21332,55216,Female,Loyal Customer,52,Business travel,Business,1662,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +21333,2351,Male,disloyal Customer,24,Business travel,Business,925,5,1,5,3,3,5,3,3,3,4,5,5,4,3,4,0.0,satisfied +21334,74838,Male,disloyal Customer,24,Business travel,Eco,816,1,1,1,2,4,1,4,4,3,4,1,2,3,4,0,0.0,neutral or dissatisfied +21335,93912,Male,Loyal Customer,55,Business travel,Business,2272,2,2,2,2,2,4,5,2,2,2,2,4,2,4,2,6.0,satisfied +21336,48974,Male,disloyal Customer,33,Business travel,Eco,326,3,3,3,4,2,3,2,2,2,1,3,2,3,2,36,30.0,neutral or dissatisfied +21337,86205,Male,Loyal Customer,44,Business travel,Business,306,4,4,4,4,3,5,5,5,5,5,5,4,5,5,29,28.0,satisfied +21338,59439,Female,Loyal Customer,43,Business travel,Business,3789,5,5,5,5,4,5,5,3,3,4,3,5,3,4,0,1.0,satisfied +21339,58137,Female,Loyal Customer,59,Business travel,Business,3222,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +21340,81852,Male,Loyal Customer,55,Personal Travel,Eco,1416,1,4,2,3,5,2,5,5,2,4,2,1,3,5,0,0.0,neutral or dissatisfied +21341,36706,Female,Loyal Customer,30,Personal Travel,Eco,1249,2,4,2,2,1,2,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +21342,82145,Male,disloyal Customer,21,Business travel,Eco,237,1,5,1,4,1,5,4,3,3,5,5,4,4,4,419,460.0,neutral or dissatisfied +21343,120267,Female,Loyal Customer,53,Business travel,Business,1576,3,3,3,3,4,4,4,5,5,5,5,3,5,3,3,8.0,satisfied +21344,11857,Female,Loyal Customer,37,Business travel,Business,1042,3,3,3,3,5,5,5,4,2,5,5,5,5,5,136,120.0,satisfied +21345,99893,Male,Loyal Customer,25,Business travel,Business,1723,4,3,3,3,4,4,4,4,1,4,4,3,3,4,9,0.0,neutral or dissatisfied +21346,115159,Male,Loyal Customer,33,Business travel,Business,371,3,2,3,3,5,4,5,5,5,5,5,4,5,5,10,1.0,satisfied +21347,65126,Male,Loyal Customer,41,Personal Travel,Eco,190,4,4,4,4,3,4,3,3,4,5,5,3,5,3,0,0.0,satisfied +21348,109680,Male,Loyal Customer,31,Personal Travel,Eco,802,2,3,2,2,3,2,3,3,2,2,2,1,2,3,70,62.0,neutral or dissatisfied +21349,68228,Female,Loyal Customer,14,Business travel,Eco,631,2,2,2,2,2,2,1,2,2,1,3,4,4,2,5,9.0,neutral or dissatisfied +21350,80853,Female,disloyal Customer,39,Business travel,Eco,292,2,0,2,5,5,2,5,5,1,2,4,4,2,5,5,0.0,neutral or dissatisfied +21351,110567,Male,Loyal Customer,40,Business travel,Business,2455,2,2,2,2,2,4,4,4,4,4,4,5,4,3,5,0.0,satisfied +21352,116683,Female,disloyal Customer,30,Business travel,Eco Plus,372,2,2,2,3,5,2,5,5,2,5,4,2,4,5,0,0.0,neutral or dissatisfied +21353,62232,Male,Loyal Customer,37,Personal Travel,Eco,2454,3,5,3,2,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +21354,16621,Female,Loyal Customer,34,Personal Travel,Eco,1008,1,4,1,2,2,1,2,2,4,3,4,5,4,2,3,0.0,neutral or dissatisfied +21355,73081,Male,disloyal Customer,50,Business travel,Business,1085,4,4,4,3,1,4,1,1,1,5,4,1,4,1,0,0.0,neutral or dissatisfied +21356,52690,Male,Loyal Customer,57,Business travel,Eco Plus,119,5,4,4,4,5,5,5,5,5,3,3,2,5,5,0,4.0,satisfied +21357,45425,Female,Loyal Customer,49,Business travel,Business,2711,3,3,3,3,3,1,2,5,5,5,5,3,5,1,0,0.0,satisfied +21358,18225,Male,disloyal Customer,18,Business travel,Business,235,4,0,4,4,3,4,4,3,4,3,4,1,4,3,44,87.0,neutral or dissatisfied +21359,40785,Male,Loyal Customer,49,Business travel,Business,599,5,5,5,5,3,5,2,3,3,3,3,5,3,3,0,0.0,satisfied +21360,112267,Female,Loyal Customer,29,Business travel,Business,1703,1,2,2,2,1,1,1,1,3,4,3,1,3,1,36,26.0,neutral or dissatisfied +21361,22665,Female,Loyal Customer,49,Personal Travel,Business,589,1,5,1,2,4,4,5,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +21362,33719,Female,Loyal Customer,70,Personal Travel,Eco,759,2,4,2,2,2,1,1,5,3,5,5,1,5,1,243,247.0,neutral or dissatisfied +21363,70394,Male,Loyal Customer,30,Business travel,Business,1562,3,3,3,3,3,3,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +21364,42459,Female,Loyal Customer,7,Personal Travel,Eco,866,2,4,2,3,4,2,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +21365,8109,Female,Loyal Customer,46,Business travel,Business,3286,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +21366,83450,Female,Loyal Customer,49,Business travel,Business,3739,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21367,49180,Male,Loyal Customer,31,Business travel,Eco,77,5,4,4,4,5,4,5,5,4,2,5,4,4,5,0,0.0,satisfied +21368,78901,Female,Loyal Customer,45,Personal Travel,Eco,2026,4,4,4,5,5,5,4,2,2,4,2,3,2,4,0,0.0,satisfied +21369,12989,Male,Loyal Customer,51,Business travel,Business,2531,5,5,5,5,1,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +21370,82215,Female,Loyal Customer,34,Business travel,Business,3920,3,3,3,3,5,4,4,4,4,4,4,4,4,3,17,26.0,satisfied +21371,89732,Female,Loyal Customer,20,Personal Travel,Eco,950,2,2,2,3,2,2,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +21372,27590,Female,Loyal Customer,68,Personal Travel,Eco,671,4,4,5,4,1,4,4,4,4,5,4,4,4,1,0,10.0,neutral or dissatisfied +21373,9799,Female,Loyal Customer,40,Business travel,Business,474,1,1,1,1,2,5,5,4,4,4,4,3,4,5,65,78.0,satisfied +21374,100298,Female,disloyal Customer,60,Business travel,Business,1092,2,2,2,1,1,2,1,1,4,2,5,5,5,1,1,3.0,neutral or dissatisfied +21375,5724,Female,Loyal Customer,36,Business travel,Business,2956,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,30.0,satisfied +21376,111003,Female,Loyal Customer,32,Business travel,Business,1633,3,2,2,2,1,2,3,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +21377,19124,Male,Loyal Customer,33,Business travel,Business,3036,3,3,3,3,3,2,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +21378,62163,Male,disloyal Customer,12,Business travel,Eco,815,2,2,2,3,1,2,1,1,1,5,3,2,4,1,0,14.0,neutral or dissatisfied +21379,823,Male,Loyal Customer,60,Business travel,Business,102,1,1,5,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +21380,28498,Female,Loyal Customer,63,Personal Travel,Business,2677,1,5,1,1,4,1,2,2,2,1,2,3,2,4,43,0.0,neutral or dissatisfied +21381,91828,Female,Loyal Customer,34,Business travel,Business,1750,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21382,106236,Female,Loyal Customer,47,Personal Travel,Eco,471,4,3,4,3,4,3,5,3,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +21383,84748,Female,Loyal Customer,45,Business travel,Business,1645,4,4,4,4,2,4,5,5,5,5,5,3,5,5,7,0.0,satisfied +21384,125959,Female,Loyal Customer,69,Personal Travel,Eco Plus,992,2,5,2,2,4,4,5,4,4,2,4,3,4,3,0,3.0,neutral or dissatisfied +21385,42845,Male,Loyal Customer,52,Business travel,Business,3429,4,2,2,2,4,3,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +21386,23672,Female,disloyal Customer,24,Business travel,Eco,212,2,0,2,4,1,2,1,1,1,2,4,4,3,1,0,0.0,neutral or dissatisfied +21387,107941,Male,Loyal Customer,21,Personal Travel,Eco,611,2,4,2,2,2,2,2,2,4,2,5,2,5,2,10,0.0,neutral or dissatisfied +21388,20304,Female,Loyal Customer,65,Business travel,Eco Plus,228,5,1,1,1,2,3,3,5,5,5,5,1,5,1,0,0.0,satisfied +21389,14178,Male,disloyal Customer,23,Business travel,Eco,620,3,0,3,3,3,3,3,3,5,1,3,1,5,3,15,23.0,neutral or dissatisfied +21390,83575,Female,disloyal Customer,27,Business travel,Business,936,4,4,4,5,3,4,3,3,3,2,4,5,4,3,0,0.0,satisfied +21391,68176,Female,Loyal Customer,30,Personal Travel,Eco,597,3,4,3,4,1,3,1,1,4,5,5,5,4,1,48,116.0,neutral or dissatisfied +21392,39483,Male,disloyal Customer,38,Business travel,Eco,467,3,0,3,2,1,3,1,1,3,4,5,5,4,1,0,4.0,neutral or dissatisfied +21393,107680,Male,Loyal Customer,35,Business travel,Business,2558,5,5,5,5,5,5,4,4,4,4,4,4,4,5,45,35.0,satisfied +21394,108030,Male,disloyal Customer,36,Business travel,Eco,306,3,2,4,2,4,4,4,1,5,2,3,4,4,4,216,314.0,neutral or dissatisfied +21395,42879,Male,Loyal Customer,60,Personal Travel,Eco,867,1,2,1,4,4,1,3,4,1,3,3,1,3,4,0,4.0,neutral or dissatisfied +21396,46964,Male,Loyal Customer,44,Personal Travel,Eco,846,3,4,3,2,3,3,3,3,4,4,4,4,5,3,2,55.0,neutral or dissatisfied +21397,67422,Female,Loyal Customer,50,Business travel,Eco,769,3,4,4,4,1,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +21398,36201,Female,disloyal Customer,22,Business travel,Eco,496,3,0,3,4,1,3,1,1,5,2,1,3,5,1,0,0.0,neutral or dissatisfied +21399,5651,Female,Loyal Customer,40,Business travel,Business,3519,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +21400,80761,Male,Loyal Customer,57,Business travel,Business,3617,3,4,3,3,3,5,5,4,4,4,4,5,4,5,30,17.0,satisfied +21401,46027,Female,disloyal Customer,25,Business travel,Eco,898,3,3,3,2,2,3,1,2,2,3,2,3,1,2,0,36.0,neutral or dissatisfied +21402,102306,Male,disloyal Customer,77,Business travel,Business,236,4,4,4,2,1,3,3,5,5,4,5,1,5,2,36,21.0,neutral or dissatisfied +21403,94166,Female,Loyal Customer,33,Business travel,Business,189,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21404,28284,Male,disloyal Customer,35,Business travel,Business,867,1,1,1,5,1,1,2,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +21405,103598,Female,disloyal Customer,27,Business travel,Business,405,0,0,0,3,2,0,2,2,3,5,4,3,4,2,6,7.0,satisfied +21406,85249,Male,Loyal Customer,57,Personal Travel,Eco,874,5,2,5,3,5,5,5,5,2,1,4,3,4,5,14,20.0,satisfied +21407,100245,Female,Loyal Customer,51,Business travel,Eco,1165,4,3,3,3,4,3,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +21408,87940,Female,Loyal Customer,37,Personal Travel,Business,646,3,2,2,3,4,3,3,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +21409,119227,Female,Loyal Customer,64,Personal Travel,Eco,290,1,2,1,4,2,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +21410,6413,Female,Loyal Customer,35,Personal Travel,Eco,296,4,5,4,1,1,4,1,1,5,3,5,4,5,1,8,13.0,neutral or dissatisfied +21411,113492,Male,Loyal Customer,43,Business travel,Business,236,5,5,5,5,3,5,5,4,4,4,4,4,4,5,3,9.0,satisfied +21412,41732,Female,Loyal Customer,53,Business travel,Business,695,4,4,4,4,4,3,2,3,3,4,3,3,3,1,0,0.0,satisfied +21413,59520,Female,Loyal Customer,64,Personal Travel,Business,965,3,5,3,3,5,5,5,1,1,3,1,5,1,5,11,4.0,neutral or dissatisfied +21414,67159,Female,disloyal Customer,26,Business travel,Eco,721,2,2,2,5,4,2,4,4,5,5,4,1,5,4,25,1.0,neutral or dissatisfied +21415,45759,Male,Loyal Customer,38,Business travel,Eco,391,4,3,1,3,4,4,4,4,5,1,5,3,4,4,0,0.0,satisfied +21416,97285,Female,Loyal Customer,42,Business travel,Business,3982,4,4,4,4,4,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +21417,92828,Female,Loyal Customer,57,Business travel,Eco,1587,5,4,4,4,1,4,3,5,5,5,5,2,5,3,0,0.0,satisfied +21418,11864,Male,Loyal Customer,48,Business travel,Eco,912,3,2,2,2,3,3,3,3,4,1,3,1,2,3,19,7.0,neutral or dissatisfied +21419,31667,Male,Loyal Customer,29,Business travel,Business,3027,4,4,4,4,2,2,2,2,4,2,2,4,4,2,0,0.0,satisfied +21420,41914,Male,Loyal Customer,40,Business travel,Business,129,4,4,4,4,5,2,3,5,5,5,4,3,5,2,0,2.0,satisfied +21421,14327,Female,Loyal Customer,64,Personal Travel,Eco,429,2,5,2,4,2,2,2,1,2,2,2,2,5,2,308,329.0,neutral or dissatisfied +21422,117238,Male,Loyal Customer,7,Personal Travel,Eco,304,3,2,3,3,1,3,1,1,4,5,3,2,4,1,15,14.0,neutral or dissatisfied +21423,124514,Female,Loyal Customer,48,Business travel,Business,1276,2,2,2,2,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +21424,47207,Female,Loyal Customer,39,Personal Travel,Eco,954,3,4,3,4,3,3,3,4,3,4,4,3,3,3,423,418.0,neutral or dissatisfied +21425,102353,Male,disloyal Customer,17,Business travel,Business,236,4,0,5,2,4,5,4,4,4,4,5,3,5,4,0,0.0,satisfied +21426,41146,Female,Loyal Customer,16,Personal Travel,Eco,140,3,2,3,5,4,3,4,4,3,4,5,3,5,4,1,0.0,neutral or dissatisfied +21427,100285,Female,Loyal Customer,30,Business travel,Business,971,2,2,2,2,5,5,5,5,5,3,4,5,4,5,18,0.0,satisfied +21428,85738,Male,Loyal Customer,39,Business travel,Business,3874,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +21429,71851,Male,Loyal Customer,55,Business travel,Eco,226,2,5,5,5,2,2,2,2,3,4,1,5,2,2,0,29.0,satisfied +21430,10795,Male,Loyal Customer,58,Business travel,Business,458,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +21431,41983,Female,Loyal Customer,56,Business travel,Business,1827,2,3,4,3,2,4,3,3,3,3,2,2,3,2,0,0.0,neutral or dissatisfied +21432,27107,Female,Loyal Customer,28,Personal Travel,Eco,1721,3,4,3,2,3,3,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +21433,93967,Male,Loyal Customer,41,Business travel,Business,1776,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +21434,118320,Female,Loyal Customer,50,Business travel,Business,602,2,1,1,1,1,4,3,2,2,2,2,2,2,4,19,9.0,neutral or dissatisfied +21435,72450,Male,Loyal Customer,51,Business travel,Business,918,4,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +21436,77262,Male,Loyal Customer,50,Personal Travel,Eco,1590,2,5,2,4,5,2,5,5,5,2,5,4,1,5,0,4.0,neutral or dissatisfied +21437,26655,Male,Loyal Customer,54,Business travel,Business,270,2,2,2,2,4,5,1,4,4,4,4,3,4,4,0,0.0,satisfied +21438,66991,Female,Loyal Customer,45,Business travel,Business,3420,2,2,4,2,2,5,5,2,2,2,2,4,2,5,0,8.0,satisfied +21439,126766,Female,Loyal Customer,24,Personal Travel,Eco,2402,2,2,2,2,5,2,5,5,2,3,3,4,2,5,0,0.0,neutral or dissatisfied +21440,38736,Female,Loyal Customer,33,Business travel,Business,354,1,1,5,1,3,4,5,5,5,4,5,1,5,2,0,0.0,satisfied +21441,30014,Female,Loyal Customer,42,Business travel,Business,539,4,4,4,4,5,4,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +21442,41767,Female,disloyal Customer,22,Business travel,Eco,872,5,4,4,2,2,4,2,2,1,1,4,3,4,2,0,0.0,satisfied +21443,70603,Male,Loyal Customer,40,Personal Travel,Eco,2611,0,1,1,1,1,4,4,4,4,1,2,4,3,4,0,0.0,satisfied +21444,31110,Female,Loyal Customer,10,Business travel,Eco Plus,483,4,4,4,4,4,4,4,4,2,5,3,2,4,4,10,6.0,neutral or dissatisfied +21445,84481,Male,Loyal Customer,72,Business travel,Business,2677,3,1,3,1,3,3,3,3,3,3,3,2,3,3,37,6.0,neutral or dissatisfied +21446,101622,Male,Loyal Customer,47,Personal Travel,Eco,1139,2,3,2,3,1,2,1,1,3,5,4,2,5,1,2,0.0,neutral or dissatisfied +21447,12908,Male,Loyal Customer,22,Business travel,Business,3613,2,4,4,4,2,3,2,2,1,3,1,2,2,2,23,29.0,neutral or dissatisfied +21448,88698,Female,Loyal Customer,41,Personal Travel,Eco,404,3,3,3,3,4,3,4,4,4,1,5,4,3,4,8,16.0,neutral or dissatisfied +21449,28484,Female,disloyal Customer,25,Business travel,Eco,1069,3,4,4,3,3,3,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +21450,19112,Male,Loyal Customer,60,Business travel,Eco,265,2,1,2,2,2,2,2,2,3,4,5,3,1,2,0,2.0,satisfied +21451,41059,Female,Loyal Customer,58,Personal Travel,Eco Plus,1087,1,3,1,3,4,3,3,4,4,1,4,4,4,1,0,1.0,neutral or dissatisfied +21452,58073,Female,Loyal Customer,29,Business travel,Business,1890,1,1,1,1,4,5,5,3,5,4,5,5,3,5,157,152.0,satisfied +21453,21812,Male,Loyal Customer,53,Personal Travel,Eco,352,4,5,4,3,1,4,1,1,4,2,4,4,4,1,30,,neutral or dissatisfied +21454,53726,Female,Loyal Customer,20,Personal Travel,Eco,1208,3,5,3,4,3,3,3,3,1,4,3,3,5,3,0,0.0,neutral or dissatisfied +21455,6121,Female,disloyal Customer,28,Business travel,Business,409,4,4,4,1,4,4,4,4,3,2,4,5,4,4,36,41.0,satisfied +21456,22217,Female,Loyal Customer,37,Personal Travel,Eco,633,2,5,2,4,1,2,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +21457,94161,Male,Loyal Customer,45,Business travel,Business,3671,1,1,3,1,4,5,4,5,5,5,5,5,5,4,55,43.0,satisfied +21458,98863,Male,Loyal Customer,68,Personal Travel,Eco,1751,3,5,3,4,5,3,5,5,4,1,1,5,3,5,0,11.0,neutral or dissatisfied +21459,89906,Female,Loyal Customer,48,Business travel,Eco,1487,3,2,2,2,1,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +21460,127655,Female,Loyal Customer,30,Business travel,Eco Plus,1773,4,2,4,2,4,4,4,4,1,2,4,4,4,4,20,16.0,neutral or dissatisfied +21461,77315,Male,Loyal Customer,43,Business travel,Business,3399,2,2,5,2,4,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +21462,79640,Female,Loyal Customer,55,Business travel,Business,2408,3,3,3,3,2,3,1,5,5,5,5,5,5,5,0,0.0,satisfied +21463,27021,Male,Loyal Customer,14,Personal Travel,Eco,867,3,5,3,5,4,3,4,4,2,2,4,4,5,4,0,0.0,neutral or dissatisfied +21464,68413,Male,Loyal Customer,23,Business travel,Business,2517,1,0,0,3,5,0,5,5,1,3,4,4,4,5,0,0.0,neutral or dissatisfied +21465,56886,Female,disloyal Customer,36,Business travel,Eco,1038,1,1,1,4,1,3,4,1,1,3,4,4,1,4,6,0.0,neutral or dissatisfied +21466,92098,Female,Loyal Customer,49,Business travel,Eco,1132,4,5,5,5,1,2,2,4,4,4,4,3,4,5,0,12.0,satisfied +21467,98538,Female,Loyal Customer,30,Personal Travel,Eco,668,1,5,1,4,2,1,2,2,3,5,4,5,5,2,1,0.0,neutral or dissatisfied +21468,25740,Male,Loyal Customer,36,Business travel,Eco Plus,528,3,5,2,2,3,3,3,3,1,1,2,2,1,3,0,0.0,satisfied +21469,124175,Male,Loyal Customer,21,Business travel,Eco Plus,2133,1,1,1,1,1,1,2,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +21470,34176,Female,Loyal Customer,22,Business travel,Business,2247,4,2,4,4,4,4,4,4,2,2,5,2,2,4,0,0.0,satisfied +21471,69525,Male,Loyal Customer,37,Business travel,Business,2586,3,3,3,3,5,5,5,3,4,5,5,5,5,5,27,14.0,satisfied +21472,75661,Female,Loyal Customer,46,Business travel,Eco Plus,304,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,4.0,neutral or dissatisfied +21473,114910,Female,Loyal Customer,54,Business travel,Business,2334,3,3,3,3,3,4,5,2,2,3,2,4,2,4,21,22.0,satisfied +21474,4146,Male,disloyal Customer,21,Business travel,Eco,431,3,2,2,4,3,2,1,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +21475,74395,Male,Loyal Customer,40,Business travel,Business,1235,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21476,127193,Female,Loyal Customer,51,Business travel,Business,325,4,4,5,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +21477,122884,Male,Loyal Customer,64,Personal Travel,Eco,226,0,5,0,5,5,0,5,5,4,5,5,3,5,5,0,0.0,satisfied +21478,35666,Female,disloyal Customer,24,Business travel,Eco,722,2,2,2,3,2,3,3,1,2,5,3,3,5,3,0,9.0,neutral or dissatisfied +21479,14268,Female,Loyal Customer,44,Business travel,Eco,395,2,5,5,5,5,2,2,2,2,2,2,1,2,2,0,0.0,satisfied +21480,13337,Male,Loyal Customer,42,Business travel,Eco,946,4,1,1,1,4,4,4,4,5,3,4,4,3,4,0,0.0,satisfied +21481,26590,Female,Loyal Customer,40,Business travel,Eco,406,4,5,5,5,4,4,4,2,3,2,5,4,3,4,346,349.0,satisfied +21482,93762,Female,Loyal Customer,50,Personal Travel,Eco,368,2,1,2,3,2,3,3,3,3,2,3,4,3,4,65,71.0,neutral or dissatisfied +21483,68563,Female,Loyal Customer,39,Business travel,Business,1616,4,4,1,4,4,4,5,5,5,5,5,4,5,4,0,4.0,satisfied +21484,85423,Male,Loyal Customer,42,Business travel,Business,3123,0,0,0,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +21485,87692,Female,Loyal Customer,25,Personal Travel,Eco,606,2,5,2,4,1,2,1,1,4,5,4,5,4,1,8,12.0,neutral or dissatisfied +21486,126857,Female,Loyal Customer,25,Personal Travel,Eco,2296,3,5,3,1,3,3,3,3,3,4,5,5,4,3,0,1.0,neutral or dissatisfied +21487,107449,Male,Loyal Customer,49,Business travel,Business,725,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,8.0,satisfied +21488,98372,Male,Loyal Customer,62,Personal Travel,Eco,1189,3,4,3,4,3,1,1,5,4,4,5,1,5,1,151,145.0,neutral or dissatisfied +21489,18962,Female,Loyal Customer,35,Business travel,Eco Plus,448,2,4,4,4,2,2,2,2,4,3,2,2,2,2,0,0.0,neutral or dissatisfied +21490,44011,Female,Loyal Customer,52,Personal Travel,Eco,397,3,5,3,2,2,4,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +21491,41566,Male,disloyal Customer,21,Business travel,Eco,1104,3,3,3,3,5,3,5,5,3,1,4,2,3,5,0,9.0,neutral or dissatisfied +21492,88480,Female,Loyal Customer,40,Business travel,Eco,404,3,1,3,1,3,3,3,3,2,1,2,4,2,3,7,11.0,neutral or dissatisfied +21493,62696,Male,Loyal Customer,43,Business travel,Business,2399,4,4,4,4,5,5,5,3,3,4,5,5,3,5,0,20.0,satisfied +21494,52115,Male,Loyal Customer,56,Personal Travel,Eco,639,3,4,3,4,1,3,4,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +21495,70212,Male,Loyal Customer,21,Personal Travel,Eco,258,4,4,4,1,3,4,3,3,3,1,4,5,2,3,0,0.0,neutral or dissatisfied +21496,45070,Female,Loyal Customer,25,Personal Travel,Eco,265,4,4,4,3,3,4,3,3,1,1,3,1,3,3,77,88.0,neutral or dissatisfied +21497,87539,Male,Loyal Customer,44,Business travel,Business,3169,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +21498,129304,Male,disloyal Customer,34,Business travel,Business,2475,3,3,3,3,3,1,1,1,1,2,4,1,4,1,272,270.0,neutral or dissatisfied +21499,107223,Female,Loyal Customer,32,Business travel,Eco,1751,2,2,2,2,2,2,2,2,4,2,2,4,4,2,3,0.0,neutral or dissatisfied +21500,54000,Female,Loyal Customer,25,Business travel,Eco Plus,1825,5,1,1,1,5,5,4,5,4,3,4,4,5,5,0,0.0,satisfied +21501,124896,Male,disloyal Customer,25,Business travel,Business,728,3,5,3,1,2,3,4,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +21502,11524,Female,Loyal Customer,57,Personal Travel,Eco Plus,247,2,4,2,4,2,5,4,4,4,2,4,5,4,3,79,69.0,neutral or dissatisfied +21503,69781,Male,Loyal Customer,55,Business travel,Business,3626,4,4,4,4,4,5,4,4,4,4,4,3,4,3,11,0.0,satisfied +21504,122956,Female,Loyal Customer,50,Business travel,Business,328,3,3,3,3,5,4,4,5,5,5,5,5,5,3,2,9.0,satisfied +21505,116798,Male,Loyal Customer,19,Personal Travel,Eco Plus,373,4,2,1,3,1,1,1,1,3,1,4,2,4,1,17,8.0,neutral or dissatisfied +21506,119475,Male,Loyal Customer,49,Business travel,Business,759,2,2,2,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +21507,102050,Male,Loyal Customer,39,Business travel,Business,414,3,3,4,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +21508,126657,Female,Loyal Customer,58,Personal Travel,Eco,602,1,4,1,3,5,4,4,5,5,1,5,1,5,4,0,0.0,neutral or dissatisfied +21509,2322,Male,Loyal Customer,59,Personal Travel,Eco,925,3,4,3,3,4,3,4,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +21510,34200,Male,Loyal Customer,43,Personal Travel,Eco,1179,2,4,1,3,4,1,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +21511,100135,Female,Loyal Customer,34,Business travel,Business,2965,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,63.0,satisfied +21512,12773,Male,Loyal Customer,70,Personal Travel,Eco Plus,689,3,5,3,2,3,3,3,3,3,3,5,3,4,3,12,2.0,neutral or dissatisfied +21513,81129,Female,Loyal Customer,12,Personal Travel,Eco,991,3,5,3,4,2,3,2,2,5,5,4,3,5,2,2,4.0,neutral or dissatisfied +21514,116388,Female,Loyal Customer,21,Personal Travel,Eco,480,4,3,4,3,3,4,3,3,4,5,4,2,3,3,0,3.0,neutral or dissatisfied +21515,102569,Female,Loyal Customer,72,Business travel,Eco Plus,223,2,1,1,1,3,4,4,2,2,2,2,2,2,2,16,9.0,neutral or dissatisfied +21516,62568,Male,disloyal Customer,46,Business travel,Business,1846,4,4,4,4,5,4,5,5,5,2,5,4,5,5,3,0.0,neutral or dissatisfied +21517,1786,Male,Loyal Customer,54,Business travel,Business,2283,4,4,4,4,5,5,4,4,4,5,4,4,4,4,3,0.0,satisfied +21518,72488,Male,Loyal Customer,53,Business travel,Business,1848,2,2,2,2,3,4,5,4,4,4,4,3,4,3,5,5.0,satisfied +21519,88074,Male,Loyal Customer,44,Business travel,Business,515,2,2,5,2,5,5,5,5,5,5,5,3,5,4,6,3.0,satisfied +21520,40078,Male,Loyal Customer,50,Business travel,Eco,493,5,3,3,3,5,5,5,5,4,5,5,3,5,5,11,0.0,satisfied +21521,87147,Female,Loyal Customer,8,Personal Travel,Eco Plus,645,3,5,2,5,2,5,5,4,5,1,1,5,5,5,119,161.0,neutral or dissatisfied +21522,114791,Male,disloyal Customer,36,Business travel,Business,333,2,2,2,2,4,2,2,4,3,5,4,3,4,4,4,0.0,neutral or dissatisfied +21523,86499,Female,Loyal Customer,63,Personal Travel,Eco,762,2,2,2,4,4,4,4,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +21524,113661,Female,Loyal Customer,37,Personal Travel,Eco,197,4,5,4,3,3,4,3,3,3,2,4,3,4,3,12,4.0,neutral or dissatisfied +21525,74544,Female,Loyal Customer,8,Business travel,Business,1188,4,2,2,2,4,4,4,4,1,1,3,1,4,4,6,0.0,neutral or dissatisfied +21526,79885,Male,Loyal Customer,56,Business travel,Business,1645,5,5,5,5,3,5,4,4,4,4,4,3,4,5,16,22.0,satisfied +21527,43982,Female,Loyal Customer,20,Personal Travel,Eco,411,3,4,3,4,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +21528,127016,Female,disloyal Customer,25,Business travel,Business,338,1,0,1,3,3,1,3,3,3,2,5,4,5,3,0,6.0,neutral or dissatisfied +21529,99344,Male,Loyal Customer,46,Business travel,Eco,1771,1,3,3,3,1,1,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +21530,6354,Female,Loyal Customer,55,Business travel,Business,3824,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +21531,94337,Female,Loyal Customer,23,Business travel,Business,562,1,1,1,1,4,4,4,4,3,2,5,3,4,4,0,0.0,satisfied +21532,72300,Female,Loyal Customer,19,Personal Travel,Eco,921,4,5,4,3,5,4,5,5,3,2,4,4,4,5,24,9.0,neutral or dissatisfied +21533,106234,Male,Loyal Customer,38,Personal Travel,Eco,471,3,5,3,3,4,3,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +21534,13268,Male,Loyal Customer,53,Personal Travel,Eco,771,2,1,2,3,1,2,1,1,1,5,3,4,3,1,0,22.0,neutral or dissatisfied +21535,46212,Female,disloyal Customer,27,Business travel,Eco,752,2,2,2,4,5,2,5,5,5,1,5,5,2,5,113,106.0,neutral or dissatisfied +21536,106223,Female,Loyal Customer,43,Business travel,Eco,471,2,2,2,2,3,3,4,2,2,2,2,2,2,4,20,5.0,neutral or dissatisfied +21537,74680,Female,Loyal Customer,25,Personal Travel,Eco,1126,2,2,2,3,5,2,5,5,2,4,4,1,4,5,0,0.0,neutral or dissatisfied +21538,128644,Male,Loyal Customer,36,Business travel,Eco Plus,679,3,1,1,1,3,3,3,3,4,1,3,2,4,3,12,0.0,neutral or dissatisfied +21539,43645,Male,Loyal Customer,33,Business travel,Business,1609,3,5,3,3,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +21540,23910,Female,Loyal Customer,44,Business travel,Eco,189,5,3,3,3,4,5,1,5,5,5,5,1,5,2,0,0.0,satisfied +21541,112587,Female,disloyal Customer,27,Business travel,Business,639,5,5,5,3,3,5,3,3,5,4,5,5,4,3,10,0.0,satisfied +21542,76829,Male,disloyal Customer,37,Business travel,Business,1851,3,3,3,1,3,3,3,3,5,4,5,3,4,3,69,44.0,neutral or dissatisfied +21543,122476,Male,disloyal Customer,21,Business travel,Eco,808,4,5,5,4,1,5,1,1,2,4,3,1,4,1,5,4.0,neutral or dissatisfied +21544,28494,Female,disloyal Customer,29,Business travel,Business,2640,2,2,2,4,1,2,1,1,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +21545,22384,Female,Loyal Customer,37,Business travel,Eco,83,4,2,2,2,4,4,4,4,4,2,3,1,3,4,0,0.0,neutral or dissatisfied +21546,6308,Male,Loyal Customer,60,Business travel,Business,315,1,1,1,1,4,4,4,4,4,4,4,3,4,5,25,65.0,satisfied +21547,65877,Female,Loyal Customer,42,Business travel,Business,1389,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +21548,47543,Male,Loyal Customer,38,Business travel,Eco Plus,558,5,1,1,1,5,5,5,5,5,5,1,4,1,5,11,0.0,satisfied +21549,28962,Female,disloyal Customer,24,Business travel,Eco,1050,3,3,3,3,2,3,2,2,1,3,3,1,4,2,13,24.0,neutral or dissatisfied +21550,13928,Male,Loyal Customer,37,Business travel,Eco,192,5,5,5,5,5,4,5,5,1,1,5,5,4,5,0,0.0,satisfied +21551,40522,Male,Loyal Customer,45,Personal Travel,Eco Plus,290,4,4,4,3,3,4,3,3,3,5,5,4,5,3,0,3.0,neutral or dissatisfied +21552,78355,Female,Loyal Customer,52,Business travel,Business,1927,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,3.0,satisfied +21553,64831,Male,Loyal Customer,35,Business travel,Business,3744,2,4,4,4,5,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +21554,55616,Female,Loyal Customer,65,Personal Travel,Eco,404,3,4,3,1,5,4,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +21555,70208,Male,Loyal Customer,34,Personal Travel,Eco,403,5,5,5,3,1,5,1,1,3,4,4,3,5,1,0,3.0,satisfied +21556,114592,Female,Loyal Customer,74,Business travel,Business,390,4,4,4,4,2,4,5,5,5,5,5,5,5,3,14,15.0,satisfied +21557,102761,Male,Loyal Customer,50,Business travel,Business,1618,3,3,3,3,4,3,5,4,4,4,4,3,4,4,45,40.0,satisfied +21558,7316,Female,Loyal Customer,69,Personal Travel,Eco Plus,139,4,5,4,1,3,5,4,2,2,4,2,5,2,3,0,0.0,satisfied +21559,48829,Male,Loyal Customer,18,Personal Travel,Business,308,3,5,3,2,1,3,1,1,4,2,4,5,5,1,14,8.0,neutral or dissatisfied +21560,128592,Male,Loyal Customer,62,Personal Travel,Eco,2552,4,5,4,2,5,4,5,5,5,1,4,4,5,5,6,7.0,neutral or dissatisfied +21561,128621,Female,Loyal Customer,17,Business travel,Business,3083,1,1,1,1,4,4,4,4,5,3,4,3,5,4,0,0.0,satisfied +21562,92640,Male,disloyal Customer,41,Business travel,Eco,453,3,0,3,3,2,3,2,2,3,1,4,2,3,2,6,2.0,neutral or dissatisfied +21563,5718,Female,Loyal Customer,66,Personal Travel,Eco,436,3,5,3,3,3,4,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +21564,90426,Female,Loyal Customer,41,Business travel,Business,2434,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +21565,502,Male,Loyal Customer,41,Business travel,Business,1549,0,4,1,1,4,4,4,1,1,1,1,4,1,3,37,32.0,satisfied +21566,18885,Female,disloyal Customer,40,Business travel,Business,448,3,3,3,2,5,3,5,5,3,1,3,1,3,5,0,0.0,neutral or dissatisfied +21567,37498,Female,Loyal Customer,54,Business travel,Business,2740,3,5,5,5,4,4,3,3,3,3,3,2,3,3,34,33.0,neutral or dissatisfied +21568,105160,Female,disloyal Customer,27,Business travel,Eco,289,0,5,0,2,3,0,3,3,3,1,2,4,1,3,9,2.0,satisfied +21569,119589,Male,disloyal Customer,35,Business travel,Business,2276,3,3,3,4,2,3,3,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +21570,1426,Female,Loyal Customer,54,Business travel,Business,158,1,1,1,1,4,4,4,2,2,2,1,1,2,4,24,27.0,neutral or dissatisfied +21571,7092,Female,Loyal Customer,56,Business travel,Business,3296,3,1,1,1,1,3,2,3,3,3,3,2,3,1,24,20.0,neutral or dissatisfied +21572,11928,Male,Loyal Customer,49,Business travel,Business,2391,2,2,2,2,5,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +21573,13374,Female,Loyal Customer,8,Personal Travel,Eco,748,2,4,2,3,1,2,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +21574,62507,Female,disloyal Customer,38,Business travel,Business,1463,4,4,4,3,5,4,1,5,4,4,3,3,4,5,0,0.0,satisfied +21575,102414,Female,Loyal Customer,43,Personal Travel,Eco,197,3,5,3,1,2,5,5,2,2,3,2,3,2,3,1,0.0,neutral or dissatisfied +21576,29110,Male,Loyal Customer,33,Personal Travel,Eco,672,0,5,0,2,1,0,1,1,5,5,5,5,5,1,0,0.0,satisfied +21577,25990,Female,disloyal Customer,30,Business travel,Eco,577,1,4,1,4,5,1,3,5,2,1,3,4,4,5,9,11.0,neutral or dissatisfied +21578,71292,Male,Loyal Customer,28,Personal Travel,Eco Plus,733,1,4,1,4,3,1,4,3,1,2,3,4,3,3,1,0.0,neutral or dissatisfied +21579,102575,Female,Loyal Customer,37,Business travel,Eco Plus,197,3,3,4,4,3,3,3,3,2,1,3,1,3,3,75,58.0,neutral or dissatisfied +21580,84190,Male,Loyal Customer,56,Business travel,Business,432,2,2,2,2,3,5,5,4,4,4,4,5,4,3,96,84.0,satisfied +21581,87140,Male,disloyal Customer,8,Business travel,Eco Plus,594,3,1,3,4,4,3,4,4,2,3,4,3,4,4,0,0.0,neutral or dissatisfied +21582,85378,Male,Loyal Customer,48,Business travel,Business,3423,4,4,1,4,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +21583,36728,Female,Loyal Customer,21,Personal Travel,Eco Plus,1249,3,5,3,1,1,3,1,1,3,2,4,4,5,1,1,18.0,neutral or dissatisfied +21584,112644,Male,Loyal Customer,58,Business travel,Business,1845,4,4,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +21585,33422,Female,disloyal Customer,29,Business travel,Eco,737,4,4,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +21586,114741,Female,Loyal Customer,55,Business travel,Business,296,2,2,2,2,5,5,5,4,4,4,5,5,5,5,172,168.0,satisfied +21587,70870,Male,Loyal Customer,32,Personal Travel,Eco,761,5,3,5,4,4,5,5,4,2,2,4,3,3,4,2,0.0,satisfied +21588,120344,Female,Loyal Customer,38,Business travel,Business,1884,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +21589,125641,Female,Loyal Customer,39,Business travel,Business,2984,4,2,4,4,3,5,5,4,4,4,4,3,4,4,5,0.0,satisfied +21590,460,Female,Loyal Customer,38,Business travel,Business,1911,0,0,0,1,3,5,5,1,1,2,2,4,1,5,0,0.0,satisfied +21591,13249,Female,Loyal Customer,34,Business travel,Business,2558,3,1,3,1,4,3,4,3,3,3,3,4,3,2,77,78.0,neutral or dissatisfied +21592,50807,Female,Loyal Customer,69,Personal Travel,Eco,363,1,5,1,1,5,5,5,4,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +21593,24915,Female,disloyal Customer,23,Business travel,Eco,762,1,1,1,3,4,1,4,4,3,4,2,5,2,4,0,0.0,neutral or dissatisfied +21594,15127,Male,Loyal Customer,26,Business travel,Business,2519,5,5,5,5,5,5,5,5,4,2,4,5,3,5,0,0.0,satisfied +21595,124059,Male,Loyal Customer,46,Business travel,Business,2153,4,4,4,4,5,3,4,4,4,4,4,5,4,4,0,0.0,satisfied +21596,36726,Female,Loyal Customer,51,Personal Travel,Eco Plus,1185,1,3,1,4,1,3,4,2,2,1,2,4,2,1,86,95.0,neutral or dissatisfied +21597,106461,Male,Loyal Customer,16,Personal Travel,Eco Plus,1670,2,1,2,3,1,2,1,1,1,1,3,1,3,1,8,0.0,neutral or dissatisfied +21598,85239,Female,disloyal Customer,27,Business travel,Eco,413,1,5,1,4,1,1,1,1,1,5,1,4,3,1,0,0.0,neutral or dissatisfied +21599,129615,Male,Loyal Customer,44,Business travel,Business,337,4,3,4,4,5,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +21600,2948,Male,Loyal Customer,36,Business travel,Business,2369,4,4,4,4,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +21601,89336,Female,Loyal Customer,51,Business travel,Business,1541,2,2,2,2,5,4,5,5,5,5,5,3,5,3,19,0.0,satisfied +21602,79761,Female,disloyal Customer,27,Business travel,Business,1096,2,2,2,4,4,2,4,4,1,2,3,3,4,4,0,0.0,neutral or dissatisfied +21603,4863,Female,Loyal Customer,66,Personal Travel,Eco,500,3,5,3,1,3,2,2,4,2,5,4,2,4,2,152,142.0,neutral or dissatisfied +21604,115620,Male,disloyal Customer,65,Business travel,Eco,342,1,1,1,3,4,1,4,4,3,4,3,1,3,4,1,0.0,neutral or dissatisfied +21605,109862,Female,Loyal Customer,39,Business travel,Business,2291,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +21606,34181,Male,Loyal Customer,58,Business travel,Eco,779,2,4,4,4,2,2,2,2,3,4,2,4,2,2,0,8.0,neutral or dissatisfied +21607,117179,Female,Loyal Customer,45,Personal Travel,Eco,369,3,5,3,3,2,2,2,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +21608,73428,Female,Loyal Customer,60,Personal Travel,Eco,1197,2,1,2,2,4,3,2,4,4,2,3,1,4,2,5,0.0,neutral or dissatisfied +21609,70446,Female,Loyal Customer,38,Personal Travel,Eco,187,2,4,2,3,2,5,5,3,4,4,4,5,3,5,197,203.0,neutral or dissatisfied +21610,35211,Male,Loyal Customer,28,Business travel,Business,1028,3,3,4,3,5,5,5,5,4,2,1,4,5,5,0,0.0,satisfied +21611,118983,Female,Loyal Customer,36,Business travel,Business,459,3,1,1,1,1,4,4,3,3,3,3,4,3,4,14,2.0,neutral or dissatisfied +21612,106849,Male,Loyal Customer,70,Personal Travel,Eco,1733,5,4,5,1,5,5,5,5,3,2,5,3,5,5,4,0.0,satisfied +21613,84639,Female,disloyal Customer,22,Business travel,Eco,707,2,2,2,3,1,2,3,1,2,4,4,4,3,1,2,0.0,neutral or dissatisfied +21614,71007,Male,disloyal Customer,25,Business travel,Business,802,2,0,3,3,5,3,5,5,5,2,5,3,5,5,31,26.0,neutral or dissatisfied +21615,34222,Male,Loyal Customer,32,Personal Travel,Eco,1129,5,4,5,2,1,4,1,1,4,4,5,5,4,1,0,0.0,satisfied +21616,73299,Female,Loyal Customer,57,Business travel,Business,1005,1,1,1,1,4,4,5,5,5,5,5,3,5,4,14,23.0,satisfied +21617,119277,Female,disloyal Customer,50,Business travel,Business,214,2,2,2,4,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +21618,2117,Male,disloyal Customer,20,Business travel,Business,431,4,0,4,1,3,4,3,3,4,3,5,5,4,3,5,0.0,satisfied +21619,115786,Male,Loyal Customer,25,Business travel,Eco,390,1,3,5,5,1,1,2,1,3,1,2,1,3,1,17,10.0,neutral or dissatisfied +21620,63768,Male,Loyal Customer,24,Business travel,Business,1721,2,2,2,2,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +21621,7389,Male,disloyal Customer,25,Business travel,Business,522,2,0,2,2,1,2,1,1,4,5,4,3,4,1,76,82.0,neutral or dissatisfied +21622,101167,Male,Loyal Customer,45,Business travel,Eco,1069,2,3,5,3,2,2,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +21623,10992,Male,Loyal Customer,37,Business travel,Eco,140,3,1,1,1,3,2,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +21624,16755,Female,Loyal Customer,52,Business travel,Business,2604,2,2,2,2,3,1,5,3,3,3,3,2,3,4,4,0.0,satisfied +21625,92730,Male,Loyal Customer,47,Business travel,Business,1276,3,3,3,3,4,4,4,4,4,4,4,3,4,3,5,0.0,satisfied +21626,80452,Female,Loyal Customer,40,Personal Travel,Business,1299,1,5,1,4,4,3,5,2,2,1,3,4,2,3,0,0.0,neutral or dissatisfied +21627,60105,Female,Loyal Customer,48,Business travel,Business,3305,1,4,1,1,4,4,4,5,5,4,5,5,5,4,52,23.0,satisfied +21628,73210,Male,Loyal Customer,48,Personal Travel,Eco,1258,2,5,2,2,3,2,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +21629,81159,Female,disloyal Customer,36,Business travel,Eco,300,1,0,2,3,5,2,5,5,1,4,3,2,5,5,0,0.0,neutral or dissatisfied +21630,58126,Female,Loyal Customer,46,Personal Travel,Eco,612,3,4,3,1,3,1,2,5,5,3,5,2,5,1,58,43.0,neutral or dissatisfied +21631,29317,Female,Loyal Customer,20,Personal Travel,Eco,569,3,5,3,2,3,3,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +21632,36038,Male,disloyal Customer,46,Business travel,Eco,413,2,0,2,4,4,2,4,4,4,4,5,3,1,4,114,119.0,neutral or dissatisfied +21633,70308,Male,Loyal Customer,26,Personal Travel,Eco,334,4,5,3,3,4,3,4,4,5,2,4,4,4,4,87,71.0,neutral or dissatisfied +21634,85523,Male,Loyal Customer,39,Business travel,Business,2102,4,4,5,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +21635,80502,Male,Loyal Customer,46,Business travel,Business,1749,2,2,2,2,2,4,5,3,3,3,3,5,3,4,7,0.0,satisfied +21636,34253,Male,disloyal Customer,46,Business travel,Eco,1666,4,4,4,4,3,4,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +21637,87473,Male,disloyal Customer,22,Business travel,Business,373,5,0,4,2,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +21638,42440,Female,Loyal Customer,53,Personal Travel,Eco Plus,1119,4,4,3,4,5,5,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +21639,31340,Female,Loyal Customer,19,Personal Travel,Eco,1062,2,2,2,4,2,2,2,2,2,3,4,1,3,2,11,10.0,neutral or dissatisfied +21640,57305,Male,Loyal Customer,39,Personal Travel,Business,236,5,5,5,3,3,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +21641,113922,Male,Loyal Customer,67,Personal Travel,Eco,1670,3,2,3,3,4,3,3,4,2,3,3,3,3,4,8,5.0,neutral or dissatisfied +21642,32968,Male,Loyal Customer,14,Personal Travel,Eco,201,1,3,1,4,2,1,5,2,5,5,4,1,5,2,4,8.0,neutral or dissatisfied +21643,124095,Male,Loyal Customer,38,Business travel,Eco,529,4,1,1,1,4,4,4,4,4,1,2,1,2,4,0,0.0,neutral or dissatisfied +21644,79762,Male,Loyal Customer,47,Business travel,Business,3736,2,2,2,2,2,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +21645,5121,Female,Loyal Customer,38,Business travel,Business,3055,1,1,4,1,4,5,5,5,5,5,5,5,5,3,0,70.0,satisfied +21646,9308,Male,Loyal Customer,49,Business travel,Business,2873,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,3.0,satisfied +21647,51026,Male,Loyal Customer,59,Personal Travel,Eco,89,1,4,1,3,3,1,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +21648,102593,Female,disloyal Customer,21,Business travel,Eco,197,2,1,2,4,1,2,1,1,2,3,3,4,3,1,13,10.0,neutral or dissatisfied +21649,70230,Female,Loyal Customer,39,Personal Travel,Eco,1068,2,4,2,2,2,1,1,3,4,5,4,1,5,1,205,190.0,neutral or dissatisfied +21650,82138,Female,disloyal Customer,36,Business travel,Business,311,3,3,3,1,4,3,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +21651,107906,Male,Loyal Customer,59,Business travel,Business,3180,5,5,5,5,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +21652,113500,Female,Loyal Customer,52,Business travel,Business,3270,5,5,5,5,4,4,5,4,4,4,4,5,4,4,5,0.0,satisfied +21653,84724,Male,Loyal Customer,57,Business travel,Business,357,1,1,1,1,4,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +21654,34221,Female,Loyal Customer,20,Personal Travel,Eco,1189,2,5,1,5,5,1,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +21655,122473,Female,Loyal Customer,69,Business travel,Eco,575,3,1,1,1,3,4,4,3,3,3,3,3,3,3,53,45.0,neutral or dissatisfied +21656,58238,Female,Loyal Customer,33,Personal Travel,Eco,802,3,3,2,3,2,2,2,2,1,2,4,4,3,2,0,5.0,neutral or dissatisfied +21657,54239,Male,Loyal Customer,41,Business travel,Business,3299,2,5,5,5,4,3,3,2,2,2,2,3,2,2,0,5.0,neutral or dissatisfied +21658,40814,Male,Loyal Customer,26,Business travel,Business,2684,1,1,1,1,1,1,1,1,2,3,2,2,4,1,15,2.0,neutral or dissatisfied +21659,11972,Female,Loyal Customer,40,Business travel,Business,643,4,4,4,4,3,4,4,4,4,4,4,3,4,4,4,18.0,satisfied +21660,93093,Male,Loyal Customer,48,Business travel,Business,3396,5,5,4,5,4,4,5,4,4,4,4,3,4,4,17,4.0,satisfied +21661,127198,Male,Loyal Customer,56,Business travel,Business,2180,1,1,3,1,3,4,5,5,5,4,5,5,5,5,1,0.0,satisfied +21662,44308,Male,Loyal Customer,44,Personal Travel,Eco Plus,1428,3,4,3,2,3,3,3,3,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +21663,47040,Male,Loyal Customer,51,Business travel,Business,3266,4,4,4,4,3,2,2,4,4,4,4,4,4,5,0,0.0,satisfied +21664,2152,Male,disloyal Customer,36,Business travel,Business,285,4,4,4,4,1,4,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +21665,21339,Female,Loyal Customer,28,Business travel,Eco,674,4,2,2,2,4,4,4,4,2,4,2,2,1,4,23,7.0,satisfied +21666,60579,Male,Loyal Customer,47,Business travel,Business,1558,3,5,5,5,3,3,3,3,3,4,3,2,3,4,24,24.0,neutral or dissatisfied +21667,85068,Male,disloyal Customer,22,Business travel,Eco,731,2,2,2,1,4,2,2,4,5,4,5,4,5,4,2,0.0,neutral or dissatisfied +21668,61606,Female,disloyal Customer,28,Business travel,Business,1379,1,1,1,4,1,2,2,5,2,4,4,2,4,2,153,147.0,neutral or dissatisfied +21669,107162,Female,Loyal Customer,58,Business travel,Eco,668,1,3,3,3,5,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +21670,5252,Male,Loyal Customer,43,Business travel,Business,3836,1,3,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +21671,22907,Male,disloyal Customer,33,Business travel,Business,630,3,3,3,2,2,3,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +21672,27674,Female,disloyal Customer,54,Business travel,Eco,1216,2,2,2,4,3,2,2,3,3,2,4,2,2,3,0,0.0,neutral or dissatisfied +21673,31518,Female,disloyal Customer,24,Business travel,Eco,846,4,4,4,3,4,4,4,4,4,3,4,5,3,4,1,0.0,neutral or dissatisfied +21674,119429,Female,Loyal Customer,27,Personal Travel,Eco,399,3,5,3,2,1,3,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +21675,10280,Male,Loyal Customer,26,Business travel,Business,2890,4,2,4,4,4,4,4,4,4,4,5,4,4,4,2,2.0,satisfied +21676,50920,Male,Loyal Customer,58,Personal Travel,Eco,158,3,4,3,2,5,3,5,5,3,3,4,5,5,5,0,37.0,neutral or dissatisfied +21677,114749,Male,disloyal Customer,26,Business travel,Business,337,5,0,5,3,1,5,1,1,4,5,4,5,4,1,0,0.0,satisfied +21678,14611,Male,Loyal Customer,21,Business travel,Business,2679,2,2,2,2,3,3,3,3,3,2,3,2,1,3,0,0.0,satisfied +21679,5317,Female,disloyal Customer,17,Business travel,Business,383,4,0,4,1,4,4,5,4,3,3,5,4,4,4,0,0.0,satisfied +21680,118627,Male,Loyal Customer,57,Business travel,Business,1870,3,3,2,3,2,3,4,3,3,3,3,4,3,1,20,16.0,neutral or dissatisfied +21681,116117,Male,Loyal Customer,25,Personal Travel,Eco,417,1,3,1,2,2,1,2,2,5,1,3,2,2,2,0,0.0,neutral or dissatisfied +21682,35140,Male,Loyal Customer,41,Business travel,Eco,1076,5,5,5,5,5,5,5,5,3,1,5,5,5,5,0,1.0,satisfied +21683,29604,Male,disloyal Customer,15,Business travel,Eco,680,2,2,2,3,5,2,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +21684,49560,Female,Loyal Customer,58,Business travel,Business,3810,3,4,4,4,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +21685,96359,Female,Loyal Customer,44,Personal Travel,Eco Plus,1609,1,1,1,3,4,2,3,4,4,1,4,3,4,1,18,0.0,neutral or dissatisfied +21686,43871,Male,Loyal Customer,58,Business travel,Eco,174,4,4,4,4,4,4,4,4,2,5,3,4,2,4,0,0.0,neutral or dissatisfied +21687,32222,Female,Loyal Customer,41,Business travel,Business,163,0,5,0,3,4,5,5,5,5,5,5,1,5,2,0,0.0,satisfied +21688,126036,Male,disloyal Customer,32,Business travel,Business,507,4,4,4,1,5,4,5,5,3,3,4,5,4,5,9,1.0,neutral or dissatisfied +21689,103559,Female,Loyal Customer,30,Personal Travel,Eco,738,4,4,4,1,2,4,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +21690,10016,Male,Loyal Customer,25,Business travel,Eco Plus,534,2,2,2,2,2,2,1,2,4,3,3,2,3,2,2,56.0,neutral or dissatisfied +21691,49872,Female,Loyal Customer,39,Business travel,Eco,156,5,2,2,2,5,5,5,5,4,1,3,4,1,5,0,0.0,satisfied +21692,61870,Male,disloyal Customer,19,Business travel,Business,1221,4,0,4,3,2,4,2,2,3,4,3,4,5,2,78,56.0,satisfied +21693,2732,Female,Loyal Customer,31,Business travel,Business,695,2,2,2,2,3,3,3,3,4,3,5,4,4,3,0,17.0,satisfied +21694,129282,Male,disloyal Customer,22,Business travel,Business,550,4,3,4,2,2,4,2,2,5,4,5,3,5,2,0,0.0,satisfied +21695,47908,Female,Loyal Customer,65,Business travel,Eco,329,1,3,3,3,5,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +21696,44669,Female,Loyal Customer,45,Business travel,Eco,268,4,4,4,4,2,5,3,4,4,4,4,3,4,2,0,3.0,satisfied +21697,96525,Female,disloyal Customer,32,Personal Travel,Eco,436,2,1,2,4,1,2,1,1,1,5,3,4,3,1,71,63.0,neutral or dissatisfied +21698,6968,Male,Loyal Customer,59,Business travel,Business,1659,5,5,5,5,2,4,4,4,4,4,4,5,4,5,16,9.0,satisfied +21699,45172,Female,Loyal Customer,66,Personal Travel,Eco,174,2,1,2,4,5,3,3,2,2,2,2,1,2,1,58,54.0,neutral or dissatisfied +21700,95294,Male,Loyal Customer,56,Personal Travel,Eco,239,4,5,4,1,4,4,4,4,4,5,2,5,3,4,0,0.0,neutral or dissatisfied +21701,11384,Female,Loyal Customer,38,Business travel,Business,2625,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +21702,122828,Female,Loyal Customer,53,Business travel,Business,3372,3,3,3,3,5,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +21703,42516,Male,Loyal Customer,32,Business travel,Business,1384,5,2,5,5,2,2,2,2,4,2,4,2,3,2,0,0.0,satisfied +21704,11151,Male,Loyal Customer,64,Personal Travel,Eco,316,1,4,1,2,1,1,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +21705,53572,Female,Loyal Customer,24,Business travel,Business,1195,3,3,3,3,5,5,5,5,1,5,1,3,2,5,16,4.0,satisfied +21706,53249,Male,Loyal Customer,24,Business travel,Eco Plus,612,0,1,4,4,0,1,4,0,3,5,4,1,3,0,0,0.0,neutral or dissatisfied +21707,12167,Male,Loyal Customer,52,Business travel,Business,3920,2,1,1,1,3,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +21708,42367,Male,Loyal Customer,20,Personal Travel,Eco,817,3,4,3,4,2,3,2,2,1,3,4,4,4,2,0,6.0,neutral or dissatisfied +21709,57340,Female,Loyal Customer,46,Business travel,Business,1626,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +21710,21810,Female,Loyal Customer,31,Personal Travel,Eco,241,1,5,1,4,3,1,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +21711,121792,Female,disloyal Customer,37,Business travel,Business,366,4,4,4,1,1,4,1,1,4,4,5,4,5,1,0,0.0,satisfied +21712,121060,Female,Loyal Customer,57,Personal Travel,Eco,1013,1,1,1,2,5,3,2,2,2,1,2,1,2,3,35,60.0,neutral or dissatisfied +21713,79251,Female,Loyal Customer,27,Business travel,Business,1598,2,2,2,2,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +21714,28352,Male,Loyal Customer,55,Personal Travel,Eco,867,2,4,2,4,1,2,1,1,4,3,2,4,4,1,0,0.0,neutral or dissatisfied +21715,32973,Male,Loyal Customer,32,Personal Travel,Eco,163,1,4,1,4,5,1,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +21716,65142,Male,Loyal Customer,33,Personal Travel,Eco,190,2,5,2,3,2,2,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +21717,26333,Female,Loyal Customer,29,Business travel,Business,834,5,5,5,5,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +21718,41421,Female,Loyal Customer,21,Personal Travel,Eco,913,2,5,3,3,5,3,1,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +21719,114786,Female,Loyal Customer,26,Business travel,Business,371,3,3,3,3,4,4,4,4,4,2,4,5,5,4,38,36.0,satisfied +21720,57535,Female,disloyal Customer,33,Business travel,Eco,413,1,4,1,4,5,1,5,5,1,3,4,4,3,5,4,12.0,neutral or dissatisfied +21721,14297,Female,disloyal Customer,34,Business travel,Eco,429,3,1,3,3,2,3,2,2,1,5,3,4,3,2,16,20.0,neutral or dissatisfied +21722,77452,Female,disloyal Customer,23,Business travel,Business,507,0,4,0,2,4,0,4,4,5,3,5,5,5,4,0,0.0,satisfied +21723,63026,Male,Loyal Customer,54,Business travel,Eco,967,1,2,2,2,1,1,1,1,3,4,3,4,3,1,16,3.0,neutral or dissatisfied +21724,35573,Male,Loyal Customer,50,Business travel,Eco Plus,1069,5,2,2,2,5,5,5,5,2,1,1,4,1,5,0,5.0,satisfied +21725,13935,Male,disloyal Customer,26,Business travel,Eco,192,2,5,2,4,4,2,2,4,3,1,1,1,4,4,0,3.0,neutral or dissatisfied +21726,99484,Female,disloyal Customer,21,Business travel,Business,283,4,0,4,1,3,4,3,3,2,5,5,3,5,3,14,10.0,satisfied +21727,120972,Female,disloyal Customer,22,Business travel,Eco,993,2,3,3,3,5,3,5,5,5,2,4,3,4,5,0,3.0,neutral or dissatisfied +21728,118771,Female,Loyal Customer,21,Personal Travel,Eco,646,1,5,1,5,5,1,5,5,4,1,1,1,1,5,5,8.0,neutral or dissatisfied +21729,55469,Male,Loyal Customer,36,Business travel,Eco,1825,2,2,2,2,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +21730,122696,Female,Loyal Customer,51,Personal Travel,Eco,361,3,5,3,3,3,5,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +21731,20606,Female,Loyal Customer,59,Business travel,Eco,794,5,3,3,3,5,5,4,5,5,5,5,4,5,3,14,8.0,satisfied +21732,2695,Male,Loyal Customer,50,Business travel,Business,2996,3,3,3,3,2,4,4,3,3,3,3,5,3,5,93,89.0,satisfied +21733,3093,Female,Loyal Customer,14,Business travel,Business,2255,2,2,3,2,2,2,2,2,4,4,3,1,3,2,5,8.0,neutral or dissatisfied +21734,105705,Female,Loyal Customer,27,Business travel,Business,3883,4,2,2,2,4,3,4,4,1,5,3,1,4,4,59,69.0,neutral or dissatisfied +21735,91274,Male,Loyal Customer,32,Business travel,Business,581,2,2,2,2,3,3,3,3,3,3,4,3,5,3,5,11.0,satisfied +21736,15168,Female,Loyal Customer,48,Business travel,Eco,416,4,2,2,2,5,3,4,4,4,4,4,5,4,1,21,6.0,satisfied +21737,15462,Female,Loyal Customer,51,Business travel,Eco,164,5,3,3,3,1,1,1,4,4,5,4,1,4,2,17,29.0,satisfied +21738,6846,Female,disloyal Customer,38,Business travel,Business,235,1,1,1,3,1,1,4,1,3,4,5,4,5,1,1,0.0,neutral or dissatisfied +21739,113568,Female,disloyal Customer,27,Business travel,Eco,407,2,1,2,4,1,2,1,1,3,3,4,2,3,1,23,20.0,neutral or dissatisfied +21740,46736,Male,Loyal Customer,53,Personal Travel,Eco,73,2,5,0,1,3,0,1,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +21741,67263,Female,Loyal Customer,46,Personal Travel,Eco,1119,2,5,2,4,3,5,5,1,1,2,1,3,1,4,14,21.0,neutral or dissatisfied +21742,43689,Female,Loyal Customer,65,Business travel,Eco,257,5,5,4,4,3,3,3,5,5,5,5,4,5,3,8,11.0,satisfied +21743,109588,Male,Loyal Customer,60,Business travel,Business,3823,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +21744,65603,Male,Loyal Customer,27,Business travel,Business,237,4,3,3,3,4,4,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +21745,8287,Male,Loyal Customer,49,Personal Travel,Eco,125,3,5,0,3,5,0,5,5,4,3,5,2,1,5,58,45.0,neutral or dissatisfied +21746,96956,Male,Loyal Customer,28,Business travel,Business,2172,1,1,1,1,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +21747,17996,Male,Loyal Customer,61,Business travel,Business,332,4,4,4,4,3,5,1,5,5,5,5,5,5,3,11,2.0,satisfied +21748,13216,Male,disloyal Customer,22,Business travel,Eco,771,3,3,3,2,2,3,3,2,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +21749,74093,Male,disloyal Customer,26,Business travel,Business,721,2,2,2,3,2,1,1,4,5,4,4,1,5,1,193,174.0,neutral or dissatisfied +21750,1800,Male,Loyal Customer,55,Business travel,Business,500,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,10.0,satisfied +21751,37803,Female,Loyal Customer,68,Personal Travel,Eco Plus,950,2,1,2,1,3,1,1,3,3,2,5,2,3,3,28,22.0,neutral or dissatisfied +21752,75412,Female,disloyal Customer,24,Business travel,Business,1092,5,5,5,2,5,5,1,5,5,5,5,4,4,5,0,0.0,satisfied +21753,65091,Female,Loyal Customer,11,Personal Travel,Eco,247,5,3,5,2,5,5,5,5,3,1,2,4,2,5,0,1.0,satisfied +21754,27306,Male,Loyal Customer,23,Business travel,Business,2010,5,5,5,5,4,4,4,4,2,4,2,1,2,4,0,0.0,satisfied +21755,117711,Female,Loyal Customer,50,Business travel,Business,3279,1,1,5,1,4,4,4,4,4,4,4,4,4,5,26,11.0,satisfied +21756,93932,Male,disloyal Customer,28,Business travel,Business,507,5,5,5,4,1,5,1,1,3,2,5,3,4,1,1,0.0,satisfied +21757,61811,Female,Loyal Customer,30,Personal Travel,Eco,1379,2,3,2,1,1,2,1,1,3,5,3,3,5,1,0,0.0,neutral or dissatisfied +21758,17080,Female,Loyal Customer,46,Business travel,Business,2513,1,1,1,1,3,2,3,2,2,2,2,2,2,3,0,0.0,satisfied +21759,20233,Female,Loyal Customer,33,Business travel,Business,2153,2,2,5,2,1,2,5,5,5,5,4,2,5,5,0,0.0,satisfied +21760,84963,Male,Loyal Customer,16,Personal Travel,Eco Plus,547,3,2,3,4,3,3,5,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +21761,92748,Female,Loyal Customer,37,Personal Travel,Eco,1276,2,4,2,4,2,2,2,2,5,3,3,5,5,2,0,0.0,neutral or dissatisfied +21762,22737,Female,Loyal Customer,50,Business travel,Business,151,2,2,2,2,3,3,2,4,4,4,3,2,4,1,25,26.0,satisfied +21763,72791,Male,disloyal Customer,20,Business travel,Eco,645,2,0,2,4,5,2,1,5,4,1,3,1,4,5,0,0.0,neutral or dissatisfied +21764,5342,Female,Loyal Customer,60,Business travel,Business,3277,3,3,4,3,2,5,4,4,4,4,4,4,4,5,11,21.0,satisfied +21765,75449,Female,disloyal Customer,29,Business travel,Business,1135,4,4,4,4,2,4,2,2,3,2,4,5,4,2,0,0.0,satisfied +21766,29983,Female,Loyal Customer,54,Business travel,Eco,548,4,5,5,5,3,4,1,4,4,4,4,2,4,2,0,0.0,satisfied +21767,20266,Female,disloyal Customer,38,Business travel,Eco,346,2,4,2,3,3,2,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +21768,112827,Male,Loyal Customer,34,Business travel,Business,2369,1,1,1,1,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21769,21719,Male,Loyal Customer,45,Business travel,Business,2108,3,3,3,3,2,3,3,3,3,3,3,4,3,5,15,0.0,satisfied +21770,53803,Female,Loyal Customer,42,Business travel,Business,3767,2,2,2,2,3,4,2,5,5,5,5,3,5,1,17,21.0,satisfied +21771,111971,Female,Loyal Customer,59,Business travel,Eco,533,5,4,2,4,4,2,3,5,5,5,5,5,5,5,8,5.0,satisfied +21772,34828,Male,Loyal Customer,28,Business travel,Eco Plus,209,4,1,1,1,4,4,4,4,3,1,3,1,3,4,0,0.0,satisfied +21773,118132,Male,disloyal Customer,28,Business travel,Business,1488,4,4,4,5,2,4,2,2,3,5,4,3,4,2,47,47.0,satisfied +21774,45964,Female,disloyal Customer,38,Business travel,Business,872,4,5,5,4,2,5,2,2,5,5,4,4,4,2,19,22.0,satisfied +21775,105860,Male,Loyal Customer,35,Business travel,Business,1650,1,1,1,1,4,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +21776,33366,Male,Loyal Customer,47,Personal Travel,Eco,2556,4,2,4,3,5,4,5,5,1,5,4,1,3,5,2,0.0,satisfied +21777,125613,Female,Loyal Customer,47,Business travel,Business,899,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21778,64834,Male,Loyal Customer,49,Business travel,Business,224,0,0,0,3,2,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +21779,99420,Female,Loyal Customer,35,Personal Travel,Eco,314,4,5,4,4,3,4,3,3,3,3,5,5,5,3,31,13.0,neutral or dissatisfied +21780,9302,Male,Loyal Customer,52,Business travel,Business,3942,4,4,4,4,1,4,3,4,4,4,4,4,4,2,38,26.0,neutral or dissatisfied +21781,83546,Male,Loyal Customer,17,Personal Travel,Eco,1121,3,4,3,1,4,3,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +21782,129102,Male,Loyal Customer,58,Personal Travel,Eco,2342,2,1,2,2,2,4,4,4,3,2,2,4,4,4,0,7.0,neutral or dissatisfied +21783,51929,Male,Loyal Customer,55,Business travel,Business,936,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +21784,111874,Female,disloyal Customer,27,Business travel,Eco,628,4,1,4,3,5,4,5,5,4,4,3,4,3,5,18,38.0,neutral or dissatisfied +21785,81756,Male,Loyal Customer,54,Business travel,Business,1487,5,5,5,5,4,5,4,4,4,4,4,5,4,5,10,11.0,satisfied +21786,123667,Female,Loyal Customer,48,Business travel,Business,214,5,5,5,5,2,4,4,3,3,4,4,4,3,3,0,0.0,satisfied +21787,120715,Female,Loyal Customer,60,Business travel,Business,3014,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21788,48331,Male,Loyal Customer,28,Business travel,Business,522,1,1,1,1,3,3,3,3,1,2,3,3,2,3,26,29.0,satisfied +21789,33200,Female,disloyal Customer,24,Business travel,Eco,101,2,5,2,4,3,2,3,3,4,5,1,3,4,3,32,36.0,neutral or dissatisfied +21790,3801,Male,disloyal Customer,42,Business travel,Business,710,3,3,3,4,2,3,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +21791,98030,Female,Loyal Customer,67,Personal Travel,Eco,1014,2,4,2,3,2,3,4,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +21792,33513,Female,Loyal Customer,12,Personal Travel,Eco Plus,965,5,4,5,4,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +21793,8616,Male,Loyal Customer,33,Personal Travel,Eco,1371,4,5,4,2,1,4,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +21794,54075,Male,disloyal Customer,24,Business travel,Eco,1416,2,2,2,4,4,2,4,4,1,1,4,1,4,4,0,,neutral or dissatisfied +21795,32279,Female,Loyal Customer,47,Business travel,Business,3922,1,1,1,1,5,4,1,5,5,5,3,1,5,3,0,0.0,satisfied +21796,117290,Male,Loyal Customer,51,Business travel,Business,621,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,2.0,satisfied +21797,567,Male,Loyal Customer,57,Business travel,Business,309,4,2,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21798,129480,Female,disloyal Customer,30,Business travel,Business,722,4,4,4,1,2,4,2,2,4,2,4,5,5,2,0,0.0,satisfied +21799,5157,Female,Loyal Customer,52,Personal Travel,Eco,622,2,4,2,3,2,5,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +21800,44469,Female,Loyal Customer,38,Business travel,Business,2268,1,1,1,1,4,4,5,5,5,5,5,5,5,2,0,0.0,satisfied +21801,98136,Female,Loyal Customer,32,Personal Travel,Eco,472,3,4,3,1,2,3,2,2,1,4,1,1,1,2,33,26.0,neutral or dissatisfied +21802,120889,Male,Loyal Customer,50,Business travel,Business,2251,4,4,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +21803,76989,Male,disloyal Customer,37,Business travel,Business,368,2,2,2,3,4,2,3,4,3,3,2,1,2,4,120,122.0,neutral or dissatisfied +21804,118913,Female,Loyal Customer,41,Personal Travel,Eco,587,2,4,2,3,5,2,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +21805,18689,Female,Loyal Customer,29,Personal Travel,Eco,190,2,4,2,1,2,2,2,2,3,4,4,2,5,2,49,49.0,neutral or dissatisfied +21806,79378,Female,Loyal Customer,40,Business travel,Business,2430,5,5,5,5,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +21807,34290,Male,Loyal Customer,62,Business travel,Business,96,2,2,2,2,3,3,5,5,5,5,4,5,5,2,0,0.0,satisfied +21808,92024,Female,disloyal Customer,30,Business travel,Business,1522,1,1,1,3,3,1,2,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +21809,31622,Female,Loyal Customer,22,Business travel,Business,3580,3,3,3,3,3,3,3,3,1,4,3,2,5,3,0,0.0,satisfied +21810,39539,Female,Loyal Customer,41,Business travel,Eco,954,5,5,5,5,4,5,4,4,2,5,4,5,1,4,0,4.0,satisfied +21811,19659,Male,Loyal Customer,38,Business travel,Business,3053,1,1,1,1,4,5,2,4,4,4,4,4,4,2,18,0.0,satisfied +21812,98714,Female,Loyal Customer,30,Business travel,Eco Plus,834,4,3,3,3,4,4,4,4,4,1,2,4,2,4,0,0.0,neutral or dissatisfied +21813,126779,Male,Loyal Customer,58,Business travel,Business,2125,2,2,4,2,2,3,4,5,5,4,5,3,5,3,0,0.0,satisfied +21814,23555,Male,disloyal Customer,22,Business travel,Eco,637,5,0,5,4,5,5,5,5,1,5,2,1,5,5,0,0.0,satisfied +21815,114122,Male,Loyal Customer,62,Personal Travel,Business,862,3,4,3,3,1,4,4,5,5,3,5,2,5,4,1,6.0,neutral or dissatisfied +21816,57041,Male,Loyal Customer,32,Personal Travel,Eco Plus,2565,0,4,0,3,0,5,5,1,4,3,5,5,4,5,0,0.0,satisfied +21817,4236,Female,disloyal Customer,24,Business travel,Eco,1020,4,4,4,2,2,4,2,2,3,2,5,3,4,2,0,0.0,satisfied +21818,115268,Female,disloyal Customer,21,Business travel,Business,373,4,0,4,5,1,4,1,1,5,5,5,4,5,1,0,2.0,satisfied +21819,43521,Male,Loyal Customer,49,Business travel,Eco Plus,524,4,2,2,2,4,4,4,4,2,3,4,3,3,4,13,9.0,neutral or dissatisfied +21820,80835,Female,disloyal Customer,37,Business travel,Eco,692,2,2,2,3,1,2,1,1,3,3,4,3,4,1,103,93.0,neutral or dissatisfied +21821,46290,Female,Loyal Customer,25,Business travel,Business,637,2,1,2,2,2,2,2,2,1,5,3,2,3,2,0,8.0,neutral or dissatisfied +21822,68412,Female,Loyal Customer,41,Business travel,Eco,1045,5,5,5,5,5,5,5,5,5,5,1,2,2,5,0,0.0,satisfied +21823,49077,Female,Loyal Customer,32,Business travel,Eco,109,5,5,5,5,5,5,5,5,4,4,2,3,5,5,0,0.0,satisfied +21824,109420,Female,Loyal Customer,57,Business travel,Business,834,5,5,5,5,5,5,4,5,5,5,5,5,5,4,9,0.0,satisfied +21825,105732,Male,Loyal Customer,68,Business travel,Eco,925,3,3,3,3,4,3,4,4,2,1,2,2,3,4,3,8.0,neutral or dissatisfied +21826,28396,Male,Loyal Customer,44,Personal Travel,Eco,2304,4,2,4,4,5,4,5,5,3,4,3,1,3,5,5,3.0,satisfied +21827,3933,Female,Loyal Customer,22,Business travel,Business,3770,1,3,1,1,5,5,5,5,4,4,4,4,5,5,0,0.0,satisfied +21828,82599,Female,disloyal Customer,22,Business travel,Eco,528,1,3,1,3,5,1,5,5,4,2,4,1,4,5,0,20.0,neutral or dissatisfied +21829,108532,Female,Loyal Customer,63,Personal Travel,Eco,649,3,5,3,3,2,2,4,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +21830,18738,Female,Loyal Customer,38,Business travel,Eco,1167,1,1,4,1,1,1,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +21831,65754,Female,Loyal Customer,32,Personal Travel,Eco,936,2,4,3,3,3,3,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +21832,77598,Female,Loyal Customer,58,Business travel,Business,731,2,2,2,2,4,5,4,5,5,5,5,4,5,4,0,31.0,satisfied +21833,87245,Female,Loyal Customer,40,Business travel,Business,577,3,3,3,3,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +21834,11425,Female,Loyal Customer,43,Business travel,Business,247,5,5,5,5,5,4,5,4,4,4,4,3,4,3,0,3.0,satisfied +21835,79401,Female,disloyal Customer,20,Business travel,Eco,502,1,3,1,3,1,1,1,1,2,1,4,3,3,1,0,0.0,neutral or dissatisfied +21836,18588,Male,Loyal Customer,43,Business travel,Eco,190,2,4,4,4,2,2,2,2,4,1,3,1,3,2,17,25.0,neutral or dissatisfied +21837,62843,Male,Loyal Customer,13,Personal Travel,Eco Plus,2556,4,2,4,3,4,5,5,4,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +21838,106987,Female,Loyal Customer,63,Personal Travel,Eco,937,3,3,3,4,5,3,3,3,3,3,3,5,3,1,0,0.0,neutral or dissatisfied +21839,80190,Male,Loyal Customer,55,Personal Travel,Eco,2475,3,0,3,2,3,1,5,3,4,2,5,5,1,5,0,1.0,neutral or dissatisfied +21840,6564,Female,Loyal Customer,30,Business travel,Business,607,3,3,2,3,3,3,3,3,2,1,2,3,3,3,25,18.0,neutral or dissatisfied +21841,128064,Male,Loyal Customer,40,Business travel,Business,2917,3,5,5,5,3,3,3,3,3,2,3,3,4,3,0,8.0,neutral or dissatisfied +21842,13536,Male,disloyal Customer,29,Business travel,Eco,152,3,1,3,3,2,3,2,2,3,1,4,2,4,2,17,20.0,neutral or dissatisfied +21843,112321,Female,Loyal Customer,69,Business travel,Business,862,2,5,5,5,5,3,4,2,2,2,2,4,2,1,6,9.0,neutral or dissatisfied +21844,64491,Female,disloyal Customer,22,Business travel,Eco,247,3,1,3,4,1,3,1,1,1,4,4,1,4,1,65,68.0,neutral or dissatisfied +21845,114589,Male,Loyal Customer,53,Business travel,Business,3574,5,5,5,5,5,5,5,5,5,5,5,5,5,5,29,23.0,satisfied +21846,66713,Female,disloyal Customer,38,Business travel,Eco,402,2,2,1,4,5,1,5,5,1,5,4,1,4,5,6,1.0,neutral or dissatisfied +21847,12377,Female,disloyal Customer,39,Business travel,Business,305,1,1,1,4,3,1,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +21848,126873,Female,Loyal Customer,61,Personal Travel,Eco,2125,1,1,1,3,3,3,4,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +21849,81132,Male,Loyal Customer,68,Personal Travel,Eco,991,0,4,1,2,5,1,5,5,4,2,5,4,4,5,0,0.0,satisfied +21850,50880,Female,Loyal Customer,54,Personal Travel,Eco,190,0,5,0,1,4,4,5,3,3,0,5,3,3,4,0,0.0,satisfied +21851,25549,Female,Loyal Customer,32,Business travel,Eco Plus,481,5,5,5,5,5,4,5,5,3,4,2,4,1,5,5,0.0,satisfied +21852,10163,Female,disloyal Customer,42,Business travel,Business,301,4,4,4,5,5,4,5,5,4,4,4,5,5,5,0,0.0,satisfied +21853,1342,Male,Loyal Customer,38,Business travel,Business,158,0,5,0,1,5,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +21854,682,Female,disloyal Customer,27,Business travel,Business,247,2,2,2,2,1,2,1,1,3,2,4,3,4,1,9,8.0,neutral or dissatisfied +21855,127616,Female,Loyal Customer,40,Business travel,Business,1773,5,5,5,5,3,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +21856,55806,Male,disloyal Customer,22,Business travel,Eco,1416,3,3,3,4,2,3,1,2,5,5,5,4,4,2,50,42.0,neutral or dissatisfied +21857,111991,Female,Loyal Customer,20,Personal Travel,Eco,770,1,4,2,3,2,2,2,2,4,2,4,4,5,2,0,8.0,neutral or dissatisfied +21858,57382,Female,Loyal Customer,57,Business travel,Business,416,5,5,5,5,4,5,5,4,4,5,4,5,4,3,42,44.0,satisfied +21859,114010,Male,Loyal Customer,46,Personal Travel,Eco,1750,1,3,0,3,3,0,3,3,5,1,1,1,3,3,32,27.0,neutral or dissatisfied +21860,71468,Male,Loyal Customer,65,Personal Travel,Eco Plus,867,4,5,4,1,1,4,1,1,4,3,5,4,4,1,0,0.0,satisfied +21861,87654,Female,Loyal Customer,56,Business travel,Business,3592,2,4,4,4,1,4,3,2,2,2,2,1,2,2,18,19.0,neutral or dissatisfied +21862,83300,Male,Loyal Customer,49,Business travel,Business,1979,2,2,2,2,3,4,5,2,2,2,2,3,2,3,0,2.0,satisfied +21863,108552,Male,Loyal Customer,47,Business travel,Business,3635,2,2,2,2,4,4,5,5,5,5,5,3,5,3,1,0.0,satisfied +21864,102644,Female,disloyal Customer,65,Business travel,Business,365,4,4,4,3,4,2,2,3,2,5,5,2,4,2,154,143.0,satisfied +21865,114809,Male,Loyal Customer,38,Business travel,Business,2293,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,4.0,satisfied +21866,75444,Male,Loyal Customer,60,Business travel,Eco,2267,2,2,2,2,2,2,2,2,2,5,4,1,3,2,0,0.0,neutral or dissatisfied +21867,18129,Female,Loyal Customer,74,Business travel,Eco,120,3,3,3,3,4,4,3,3,3,3,3,2,3,4,16,1.0,neutral or dissatisfied +21868,7638,Female,Loyal Customer,47,Business travel,Business,604,5,5,5,5,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21869,106032,Female,Loyal Customer,35,Personal Travel,Eco,682,2,5,2,3,2,2,2,2,5,4,5,5,4,2,9,2.0,neutral or dissatisfied +21870,121330,Male,disloyal Customer,22,Business travel,Eco Plus,1009,2,1,2,3,2,2,2,2,1,2,2,1,3,2,0,0.0,neutral or dissatisfied +21871,81729,Female,Loyal Customer,56,Business travel,Business,1306,4,4,2,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +21872,29442,Female,disloyal Customer,47,Business travel,Eco,421,2,0,2,1,2,2,4,2,2,5,4,1,1,2,15,13.0,neutral or dissatisfied +21873,106428,Female,disloyal Customer,22,Business travel,Business,551,4,5,4,3,3,4,3,3,4,3,5,3,5,3,0,0.0,satisfied +21874,79452,Male,Loyal Customer,49,Business travel,Business,2099,1,1,2,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21875,69404,Female,Loyal Customer,32,Business travel,Business,3483,1,2,2,2,1,1,1,4,2,4,3,1,3,1,178,175.0,neutral or dissatisfied +21876,1658,Female,disloyal Customer,51,Business travel,Business,551,4,4,4,4,4,4,2,4,1,2,3,4,4,4,30,38.0,neutral or dissatisfied +21877,90177,Male,Loyal Customer,70,Personal Travel,Eco,1145,3,4,3,2,5,3,3,5,4,5,3,5,5,5,13,1.0,neutral or dissatisfied +21878,14628,Male,Loyal Customer,44,Business travel,Business,541,2,4,4,4,5,4,3,2,2,2,2,2,2,2,0,13.0,neutral or dissatisfied +21879,97151,Male,Loyal Customer,60,Business travel,Eco,1097,5,3,3,3,5,5,5,5,4,3,4,2,1,5,0,0.0,satisfied +21880,126992,Male,disloyal Customer,64,Business travel,Business,338,5,5,5,4,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +21881,25391,Male,Loyal Customer,35,Personal Travel,Eco Plus,591,1,0,1,2,3,1,1,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +21882,8751,Male,Loyal Customer,58,Business travel,Business,1670,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +21883,102484,Male,Loyal Customer,39,Personal Travel,Eco,197,2,5,2,1,4,2,4,4,5,2,4,3,5,4,25,18.0,neutral or dissatisfied +21884,40253,Female,Loyal Customer,33,Business travel,Business,2021,4,4,4,4,1,5,2,2,2,2,2,2,2,1,0,1.0,satisfied +21885,37331,Female,Loyal Customer,35,Business travel,Eco,1069,4,1,1,1,4,5,4,4,2,5,5,3,1,4,54,41.0,satisfied +21886,68938,Male,disloyal Customer,22,Business travel,Eco,646,3,4,3,3,2,3,2,2,2,5,3,2,3,2,5,18.0,neutral or dissatisfied +21887,53660,Male,Loyal Customer,69,Personal Travel,Business,1208,4,4,4,4,2,2,4,1,1,4,1,5,1,1,0,0.0,satisfied +21888,51300,Male,Loyal Customer,47,Business travel,Eco Plus,373,4,5,5,5,4,4,4,4,2,2,2,5,5,4,4,5.0,satisfied +21889,113509,Male,disloyal Customer,26,Business travel,Business,258,3,5,3,4,4,3,3,4,3,5,5,4,5,4,2,0.0,neutral or dissatisfied +21890,101830,Male,Loyal Customer,12,Personal Travel,Eco,1521,5,4,5,1,1,5,1,1,3,5,4,5,4,1,3,0.0,satisfied +21891,25268,Female,Loyal Customer,37,Business travel,Business,425,3,3,3,3,3,5,2,5,5,5,5,5,5,4,0,0.0,satisfied +21892,23310,Male,Loyal Customer,31,Business travel,Eco,359,0,0,0,4,3,0,3,3,5,1,4,2,3,3,1,0.0,satisfied +21893,98269,Male,Loyal Customer,28,Business travel,Business,1960,4,4,4,4,4,4,4,4,1,4,3,4,4,4,1,0.0,neutral or dissatisfied +21894,69307,Female,Loyal Customer,60,Business travel,Business,2725,2,4,3,3,1,3,2,2,2,2,2,2,2,4,0,14.0,neutral or dissatisfied +21895,88719,Male,Loyal Customer,67,Personal Travel,Eco,406,2,5,4,2,3,4,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +21896,120661,Female,Loyal Customer,70,Business travel,Business,280,1,2,3,2,5,4,4,1,1,1,1,1,1,4,56,45.0,neutral or dissatisfied +21897,82825,Male,Loyal Customer,51,Business travel,Eco,640,2,3,3,3,2,2,2,2,2,3,3,3,4,2,0,6.0,neutral or dissatisfied +21898,8079,Female,disloyal Customer,24,Business travel,Business,402,3,1,2,3,5,2,5,5,2,2,2,4,3,5,0,9.0,neutral or dissatisfied +21899,5649,Male,Loyal Customer,42,Business travel,Business,234,3,4,3,3,2,5,5,4,4,4,4,5,4,4,0,2.0,satisfied +21900,43242,Female,Loyal Customer,52,Business travel,Business,2589,4,3,3,3,4,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +21901,58790,Male,disloyal Customer,49,Business travel,Business,1182,1,1,1,5,4,1,4,4,4,5,5,5,5,4,0,2.0,neutral or dissatisfied +21902,54261,Male,Loyal Customer,33,Personal Travel,Eco,1222,4,5,4,1,3,4,3,3,2,2,2,4,3,3,1,0.0,neutral or dissatisfied +21903,101849,Male,Loyal Customer,35,Business travel,Business,2905,5,5,1,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +21904,129078,Female,Loyal Customer,48,Business travel,Business,2583,1,1,1,1,4,4,4,4,3,4,5,4,5,4,0,10.0,satisfied +21905,26110,Male,disloyal Customer,38,Business travel,Business,404,2,2,2,3,3,2,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +21906,87010,Male,Loyal Customer,16,Personal Travel,Eco,907,3,4,4,3,4,4,3,4,4,2,5,5,4,4,55,28.0,neutral or dissatisfied +21907,15114,Female,Loyal Customer,30,Business travel,Eco,912,4,5,5,5,4,4,4,4,4,5,1,1,3,4,0,10.0,satisfied +21908,57103,Female,Loyal Customer,46,Business travel,Eco,1222,2,2,2,2,5,3,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +21909,103144,Female,Loyal Customer,47,Personal Travel,Eco Plus,460,3,4,1,3,2,1,3,5,5,1,1,4,5,2,1,0.0,neutral or dissatisfied +21910,114482,Male,Loyal Customer,55,Business travel,Business,2275,4,4,2,4,5,4,4,4,4,4,4,5,4,3,10,3.0,satisfied +21911,116547,Female,Loyal Customer,28,Personal Travel,Eco,480,3,2,4,2,1,4,1,1,1,2,3,3,2,1,67,60.0,neutral or dissatisfied +21912,48358,Female,disloyal Customer,25,Business travel,Eco,522,2,5,2,1,5,2,5,5,3,1,1,2,3,5,0,0.0,neutral or dissatisfied +21913,21751,Male,Loyal Customer,7,Personal Travel,Eco,563,3,0,3,4,4,3,4,4,5,3,5,4,4,4,51,39.0,neutral or dissatisfied +21914,9102,Female,disloyal Customer,24,Business travel,Business,707,4,0,4,2,2,4,2,2,5,4,4,5,5,2,74,73.0,satisfied +21915,105655,Female,disloyal Customer,20,Business travel,Eco,919,1,2,2,3,1,2,1,1,3,4,4,5,4,1,3,18.0,neutral or dissatisfied +21916,105940,Female,Loyal Customer,42,Personal Travel,Eco,1491,1,3,1,2,3,3,3,4,4,1,4,1,4,2,20,12.0,neutral or dissatisfied +21917,90109,Male,disloyal Customer,24,Business travel,Eco,1127,2,2,2,3,1,2,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +21918,11705,Female,Loyal Customer,60,Business travel,Business,3694,4,4,4,4,4,5,4,5,5,5,5,4,5,3,35,27.0,satisfied +21919,13421,Male,Loyal Customer,41,Business travel,Business,409,4,4,3,4,2,5,5,4,4,4,4,5,4,4,0,5.0,satisfied +21920,59171,Male,Loyal Customer,60,Personal Travel,Eco Plus,1726,1,4,1,1,1,1,1,1,4,2,5,4,4,1,39,3.0,neutral or dissatisfied +21921,55728,Female,Loyal Customer,12,Personal Travel,Eco,1201,3,2,4,4,5,4,5,5,3,1,4,2,3,5,0,0.0,neutral or dissatisfied +21922,88422,Male,Loyal Customer,59,Business travel,Eco,240,1,3,3,3,1,1,1,1,1,3,1,3,2,1,0,0.0,neutral or dissatisfied +21923,116235,Female,Loyal Customer,59,Personal Travel,Eco,446,4,1,4,3,2,4,4,3,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +21924,91537,Male,disloyal Customer,20,Business travel,Eco,680,3,4,4,5,4,1,5,5,2,4,5,5,3,5,330,349.0,neutral or dissatisfied +21925,103538,Male,Loyal Customer,40,Business travel,Business,2432,3,3,3,3,4,4,5,4,4,4,4,5,4,3,5,0.0,satisfied +21926,39339,Male,Loyal Customer,46,Business travel,Eco,774,3,5,5,5,3,3,3,3,4,2,4,1,3,3,0,5.0,neutral or dissatisfied +21927,76084,Male,Loyal Customer,36,Business travel,Business,3891,0,0,0,1,3,5,4,3,3,3,3,4,3,1,0,0.0,satisfied +21928,73761,Male,Loyal Customer,24,Personal Travel,Eco,204,3,5,3,1,4,3,4,4,5,2,3,1,5,4,0,0.0,neutral or dissatisfied +21929,41227,Male,Loyal Customer,35,Personal Travel,Eco,912,2,4,2,1,4,2,4,4,5,4,5,5,4,4,72,60.0,neutral or dissatisfied +21930,123519,Male,Loyal Customer,15,Personal Travel,Eco,2296,4,5,3,4,4,3,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +21931,127632,Male,Loyal Customer,26,Business travel,Eco,1773,3,4,4,4,3,3,2,3,4,5,3,3,3,3,7,14.0,neutral or dissatisfied +21932,122926,Male,Loyal Customer,50,Business travel,Business,3128,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +21933,101813,Female,Loyal Customer,44,Business travel,Business,1521,4,2,2,2,1,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +21934,51371,Male,Loyal Customer,70,Personal Travel,Eco Plus,110,3,1,0,4,3,0,1,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +21935,102977,Female,Loyal Customer,44,Business travel,Business,460,2,2,2,2,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +21936,95612,Female,Loyal Customer,43,Business travel,Business,3764,2,2,2,2,4,4,5,5,5,5,5,4,5,4,18,4.0,satisfied +21937,84895,Female,Loyal Customer,11,Personal Travel,Eco,534,3,5,2,3,2,2,5,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +21938,9801,Female,Loyal Customer,56,Business travel,Business,3123,5,5,5,5,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +21939,3320,Male,Loyal Customer,60,Business travel,Business,213,4,4,4,4,2,4,5,4,4,4,5,5,4,4,0,1.0,satisfied +21940,90939,Female,Loyal Customer,49,Business travel,Business,1950,5,5,5,5,4,3,2,4,4,4,5,1,4,3,0,0.0,satisfied +21941,45824,Female,Loyal Customer,7,Personal Travel,Eco,391,1,5,1,1,3,1,1,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +21942,33086,Male,Loyal Customer,70,Personal Travel,Eco,163,2,2,0,4,3,0,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +21943,12731,Male,Loyal Customer,32,Personal Travel,Eco,721,2,3,2,3,4,2,4,4,4,5,4,2,2,4,20,9.0,neutral or dissatisfied +21944,113792,Female,disloyal Customer,23,Business travel,Eco,258,1,3,1,3,1,1,1,1,4,3,4,2,4,1,25,18.0,neutral or dissatisfied +21945,92902,Male,Loyal Customer,57,Business travel,Business,3837,3,3,4,3,2,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +21946,48554,Female,Loyal Customer,56,Personal Travel,Eco,844,1,4,1,2,4,4,4,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +21947,28546,Female,Loyal Customer,27,Personal Travel,Eco,2688,5,1,5,2,1,5,1,1,1,5,1,4,2,1,0,0.0,satisfied +21948,112171,Female,Loyal Customer,67,Personal Travel,Eco,895,3,1,4,4,2,3,4,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +21949,126087,Male,Loyal Customer,51,Business travel,Business,631,4,4,4,4,2,5,5,4,4,4,4,4,4,5,71,65.0,satisfied +21950,100576,Female,Loyal Customer,58,Business travel,Eco,486,3,4,4,4,4,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +21951,24080,Female,disloyal Customer,24,Business travel,Eco,866,2,2,2,4,5,2,5,5,3,4,1,5,4,5,0,0.0,neutral or dissatisfied +21952,59526,Female,Loyal Customer,46,Business travel,Business,2851,1,1,1,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +21953,38871,Male,disloyal Customer,26,Business travel,Business,261,1,5,1,5,4,1,4,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +21954,33683,Female,Loyal Customer,39,Business travel,Business,899,3,3,3,3,4,3,3,3,2,4,4,3,2,3,233,256.0,satisfied +21955,37541,Male,disloyal Customer,27,Business travel,Business,1069,4,4,4,4,2,4,2,2,2,5,3,4,3,2,60,44.0,neutral or dissatisfied +21956,9617,Female,Loyal Customer,16,Personal Travel,Eco,296,2,4,2,1,5,2,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +21957,101528,Male,Loyal Customer,39,Personal Travel,Eco,345,2,1,2,2,2,2,2,2,2,2,3,4,2,2,6,0.0,neutral or dissatisfied +21958,77172,Male,Loyal Customer,31,Business travel,Eco,1355,4,1,4,1,4,4,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +21959,92750,Male,Loyal Customer,34,Personal Travel,Eco,1276,2,1,2,3,2,2,2,2,3,3,3,2,2,2,0,5.0,neutral or dissatisfied +21960,37807,Female,Loyal Customer,61,Personal Travel,Eco Plus,1069,4,5,5,2,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21961,55466,Female,disloyal Customer,50,Business travel,Eco,1400,4,4,4,3,2,4,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +21962,69720,Male,Loyal Customer,32,Personal Travel,Eco,1372,5,4,5,2,4,5,4,4,5,5,5,4,4,4,0,1.0,satisfied +21963,65491,Male,Loyal Customer,49,Personal Travel,Eco,1303,3,4,4,2,3,4,3,3,5,2,5,5,5,3,79,61.0,neutral or dissatisfied +21964,14608,Male,Loyal Customer,37,Business travel,Business,3023,1,1,1,1,4,3,3,5,3,2,2,3,1,3,303,324.0,satisfied +21965,612,Female,Loyal Customer,48,Business travel,Business,2311,4,4,2,4,2,4,4,5,5,5,5,5,5,3,8,12.0,satisfied +21966,73700,Male,Loyal Customer,43,Business travel,Business,204,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +21967,54878,Female,Loyal Customer,49,Personal Travel,Eco,794,3,2,3,4,3,4,3,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +21968,31322,Female,Loyal Customer,59,Business travel,Eco Plus,680,4,1,1,1,1,4,3,4,4,4,4,2,4,2,0,1.0,satisfied +21969,58751,Female,Loyal Customer,50,Business travel,Business,3837,5,5,5,5,3,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +21970,11596,Female,Loyal Customer,59,Business travel,Business,257,3,3,3,3,2,1,5,5,5,5,5,3,5,2,0,4.0,satisfied +21971,41407,Female,Loyal Customer,40,Business travel,Eco,241,1,3,3,3,1,1,1,1,2,5,3,4,3,1,0,10.0,neutral or dissatisfied +21972,127022,Male,Loyal Customer,39,Business travel,Business,325,0,0,0,3,4,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +21973,94218,Male,disloyal Customer,20,Business travel,Eco,189,3,4,3,3,5,3,5,5,3,2,4,4,4,5,3,1.0,neutral or dissatisfied +21974,13292,Female,Loyal Customer,29,Business travel,Eco Plus,657,3,1,1,1,3,3,3,3,1,1,4,2,3,3,0,0.0,neutral or dissatisfied +21975,110921,Male,Loyal Customer,45,Personal Travel,Eco,545,4,2,4,1,2,4,2,2,1,1,1,3,2,2,0,0.0,neutral or dissatisfied +21976,124259,Female,Loyal Customer,43,Business travel,Business,1916,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21977,40341,Female,Loyal Customer,52,Business travel,Eco,920,4,1,1,1,3,3,3,4,4,4,4,1,4,4,0,3.0,satisfied +21978,96209,Male,Loyal Customer,29,Business travel,Business,3926,3,5,5,5,3,3,3,3,3,2,2,4,2,3,1,0.0,neutral or dissatisfied +21979,71452,Male,Loyal Customer,26,Business travel,Business,867,1,2,2,2,1,1,1,1,2,5,3,1,2,1,24,25.0,neutral or dissatisfied +21980,81301,Male,Loyal Customer,36,Personal Travel,Eco Plus,1020,2,0,2,3,4,2,4,4,5,3,5,3,4,4,6,5.0,neutral or dissatisfied +21981,10275,Male,Loyal Customer,52,Personal Travel,Business,191,2,2,2,3,2,4,3,1,1,2,1,3,1,2,97,91.0,neutral or dissatisfied +21982,48386,Female,Loyal Customer,9,Personal Travel,Eco,522,3,4,3,2,4,3,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +21983,68661,Male,Loyal Customer,64,Business travel,Eco,237,2,2,2,2,2,2,2,2,4,1,2,1,2,2,0,0.0,neutral or dissatisfied +21984,102813,Male,Loyal Customer,35,Business travel,Eco,342,3,3,3,3,3,3,3,2,1,4,4,3,3,3,251,249.0,neutral or dissatisfied +21985,71302,Male,Loyal Customer,55,Business travel,Business,1114,1,1,1,1,5,4,4,3,5,4,5,4,4,4,213,194.0,satisfied +21986,105259,Male,Loyal Customer,29,Business travel,Business,2106,4,4,5,4,4,4,4,4,4,4,2,4,4,4,0,0.0,neutral or dissatisfied +21987,79853,Female,Loyal Customer,51,Business travel,Business,1076,5,5,4,5,3,4,5,3,3,4,3,5,3,3,11,0.0,satisfied +21988,97876,Female,Loyal Customer,55,Business travel,Business,793,4,4,3,4,5,4,4,5,5,5,5,3,5,3,13,24.0,satisfied +21989,37843,Female,Loyal Customer,31,Business travel,Business,2933,1,1,1,1,4,4,4,4,1,1,1,1,4,4,0,2.0,satisfied +21990,910,Male,Loyal Customer,35,Business travel,Business,89,2,3,3,3,4,4,4,1,1,1,2,1,1,4,0,2.0,neutral or dissatisfied +21991,84949,Female,Loyal Customer,57,Business travel,Business,3483,4,4,4,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +21992,78029,Female,Loyal Customer,20,Business travel,Eco,332,1,2,2,2,2,4,1,4,3,3,3,1,3,1,138,135.0,neutral or dissatisfied +21993,59792,Female,Loyal Customer,40,Business travel,Business,3361,3,3,3,3,4,4,4,5,2,5,5,4,3,4,344,331.0,satisfied +21994,78550,Female,Loyal Customer,52,Personal Travel,Eco,526,1,4,4,1,5,4,5,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +21995,121627,Male,Loyal Customer,30,Personal Travel,Eco,912,2,4,2,3,2,2,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +21996,10994,Female,Loyal Customer,61,Business travel,Business,458,3,2,4,2,1,4,3,3,3,2,3,4,3,4,10,8.0,neutral or dissatisfied +21997,87129,Female,Loyal Customer,54,Personal Travel,Eco,594,3,5,3,4,2,1,1,3,3,3,3,1,3,2,10,0.0,neutral or dissatisfied +21998,69132,Female,Loyal Customer,50,Business travel,Eco Plus,1598,2,3,3,3,2,3,3,2,2,2,2,3,2,1,6,18.0,neutral or dissatisfied +21999,29094,Male,Loyal Customer,52,Personal Travel,Eco,954,1,4,2,3,5,2,5,5,2,3,4,4,3,5,35,47.0,neutral or dissatisfied +22000,111286,Male,Loyal Customer,27,Personal Travel,Eco,459,3,5,3,3,2,3,2,2,3,4,5,4,4,2,7,4.0,neutral or dissatisfied +22001,6215,Male,Loyal Customer,45,Personal Travel,Eco,462,2,2,2,3,3,2,3,3,4,3,2,2,3,3,1,13.0,neutral or dissatisfied +22002,44238,Female,Loyal Customer,61,Business travel,Business,3227,4,4,4,4,3,3,5,5,5,5,5,2,5,4,0,0.0,satisfied +22003,17830,Female,Loyal Customer,24,Business travel,Eco Plus,931,5,1,1,1,5,5,4,5,1,4,2,1,4,5,4,0.0,satisfied +22004,95783,Male,Loyal Customer,57,Personal Travel,Eco,453,4,4,4,4,4,4,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +22005,111497,Female,Loyal Customer,54,Business travel,Eco,391,3,2,2,2,4,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +22006,88780,Male,disloyal Customer,27,Business travel,Business,515,3,3,3,2,4,3,4,4,3,4,5,5,4,4,30,42.0,neutral or dissatisfied +22007,99765,Female,Loyal Customer,10,Personal Travel,Eco,255,4,0,4,1,5,4,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +22008,83572,Male,disloyal Customer,30,Business travel,Business,936,5,5,5,3,3,5,3,3,5,2,4,5,5,3,23,11.0,satisfied +22009,121165,Male,Loyal Customer,61,Business travel,Business,1021,2,2,2,2,5,5,5,5,3,3,4,5,1,5,0,11.0,satisfied +22010,5970,Male,disloyal Customer,25,Business travel,Business,925,3,3,2,3,4,2,4,4,2,3,4,2,4,4,0,0.0,neutral or dissatisfied +22011,57661,Male,Loyal Customer,16,Personal Travel,Eco,200,1,1,1,4,2,1,2,2,3,4,4,1,3,2,35,50.0,neutral or dissatisfied +22012,94247,Male,Loyal Customer,48,Business travel,Business,239,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +22013,75899,Female,Loyal Customer,55,Business travel,Business,603,3,3,3,3,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +22014,32017,Male,Loyal Customer,37,Business travel,Business,3493,3,3,3,3,4,5,3,5,5,5,4,1,5,2,0,0.0,satisfied +22015,31841,Male,Loyal Customer,38,Business travel,Eco,2677,5,3,3,3,5,5,5,5,2,4,4,5,2,5,0,0.0,satisfied +22016,91469,Male,disloyal Customer,26,Business travel,Eco,459,2,2,3,4,4,3,4,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +22017,112281,Male,Loyal Customer,27,Personal Travel,Eco,1703,4,3,4,4,2,4,2,2,3,1,3,5,3,2,0,0.0,satisfied +22018,35622,Female,Loyal Customer,35,Personal Travel,Eco Plus,1056,3,4,3,4,5,3,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +22019,42874,Male,Loyal Customer,56,Business travel,Eco,467,4,1,1,1,4,4,4,4,1,3,4,2,3,4,0,0.0,neutral or dissatisfied +22020,53946,Male,Loyal Customer,29,Business travel,Eco,1117,5,4,4,4,5,5,5,5,5,5,5,4,3,5,9,0.0,satisfied +22021,112360,Male,Loyal Customer,31,Business travel,Business,853,4,4,4,4,5,5,5,5,3,3,4,4,4,5,0,14.0,satisfied +22022,25426,Female,Loyal Customer,19,Business travel,Business,1717,2,3,3,3,2,2,2,2,3,5,4,2,3,2,16,13.0,neutral or dissatisfied +22023,89830,Female,Loyal Customer,45,Personal Travel,Eco Plus,944,1,3,1,5,5,2,1,3,3,1,5,3,3,2,0,0.0,neutral or dissatisfied +22024,72290,Female,Loyal Customer,15,Personal Travel,Eco,919,2,3,1,4,4,1,4,4,4,2,3,1,3,4,6,0.0,neutral or dissatisfied +22025,74145,Female,disloyal Customer,25,Business travel,Eco,592,3,4,3,4,3,3,3,3,2,1,4,3,3,3,28,14.0,neutral or dissatisfied +22026,75167,Female,disloyal Customer,13,Business travel,Eco,1744,4,4,4,4,3,4,3,3,1,4,2,3,4,3,9,0.0,neutral or dissatisfied +22027,63215,Female,disloyal Customer,36,Business travel,Business,337,3,3,3,2,5,3,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +22028,28864,Male,Loyal Customer,34,Business travel,Business,697,3,3,2,3,1,4,3,5,5,5,5,2,5,5,0,0.0,satisfied +22029,33199,Male,Loyal Customer,53,Business travel,Eco Plus,101,4,3,3,3,5,4,5,5,1,5,3,4,3,5,2,10.0,satisfied +22030,98755,Female,Loyal Customer,53,Business travel,Business,2075,2,2,2,2,5,4,4,4,4,4,4,5,4,5,40,47.0,satisfied +22031,12429,Female,Loyal Customer,49,Personal Travel,Eco,201,1,3,0,4,0,2,2,3,2,4,4,2,2,2,165,155.0,neutral or dissatisfied +22032,91454,Male,Loyal Customer,39,Business travel,Business,2915,5,5,5,5,5,5,4,4,4,4,4,4,4,4,2,0.0,satisfied +22033,17686,Male,Loyal Customer,28,Business travel,Business,503,4,3,4,4,5,5,5,5,3,4,4,4,5,5,7,0.0,satisfied +22034,93882,Male,disloyal Customer,24,Business travel,Eco,590,3,4,3,5,4,3,4,4,5,5,4,3,4,4,0,12.0,neutral or dissatisfied +22035,101401,Male,Loyal Customer,16,Personal Travel,Eco,486,4,2,4,4,2,4,2,2,4,2,3,1,3,2,30,17.0,satisfied +22036,43760,Female,disloyal Customer,29,Business travel,Eco,386,1,0,1,4,5,1,5,5,2,2,4,1,3,5,39,30.0,neutral or dissatisfied +22037,11422,Male,Loyal Customer,42,Business travel,Business,2298,2,2,2,2,4,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +22038,27011,Female,Loyal Customer,33,Business travel,Business,867,3,3,3,3,2,2,5,4,4,4,4,4,4,4,0,0.0,satisfied +22039,67687,Male,Loyal Customer,29,Business travel,Business,1188,1,3,3,3,1,1,1,1,4,3,3,4,4,1,40,35.0,neutral or dissatisfied +22040,90583,Female,disloyal Customer,23,Business travel,Business,581,5,5,5,4,3,5,2,3,5,4,5,4,5,3,0,19.0,satisfied +22041,62960,Female,disloyal Customer,29,Business travel,Business,776,4,4,4,4,4,2,2,3,2,5,4,2,4,2,153,172.0,neutral or dissatisfied +22042,38856,Female,Loyal Customer,59,Business travel,Business,2153,3,2,2,2,1,2,3,3,3,3,3,2,3,4,0,9.0,neutral or dissatisfied +22043,107779,Female,Loyal Customer,34,Personal Travel,Eco Plus,251,3,3,3,2,3,4,4,2,4,2,2,4,1,4,87,133.0,neutral or dissatisfied +22044,109309,Female,Loyal Customer,41,Business travel,Business,2618,2,2,2,2,1,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +22045,91354,Female,Loyal Customer,35,Personal Travel,Eco Plus,515,2,5,2,4,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +22046,118878,Female,Loyal Customer,56,Personal Travel,Eco,1136,2,5,2,1,4,3,5,5,5,2,5,1,5,3,8,0.0,neutral or dissatisfied +22047,101400,Male,disloyal Customer,36,Business travel,Eco,486,4,4,4,3,2,4,5,2,4,1,3,4,3,2,34,23.0,neutral or dissatisfied +22048,62572,Male,Loyal Customer,45,Business travel,Eco,1846,3,2,2,2,3,3,3,3,2,3,1,2,3,3,0,0.0,neutral or dissatisfied +22049,12281,Female,disloyal Customer,22,Business travel,Business,253,4,0,4,5,5,4,5,5,5,4,2,5,1,5,0,4.0,satisfied +22050,108943,Female,Loyal Customer,53,Business travel,Business,3652,3,3,3,3,4,4,4,3,2,4,4,4,3,4,167,172.0,satisfied +22051,115644,Female,Loyal Customer,41,Business travel,Eco,337,2,5,5,5,2,2,2,2,3,2,3,1,3,2,29,18.0,neutral or dissatisfied +22052,91375,Female,Loyal Customer,56,Business travel,Business,1875,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +22053,11564,Male,Loyal Customer,49,Business travel,Business,3424,5,5,5,5,5,4,4,4,4,4,4,5,4,5,13,0.0,satisfied +22054,119645,Female,Loyal Customer,23,Business travel,Business,3375,1,1,1,1,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +22055,18630,Male,Loyal Customer,33,Personal Travel,Eco,190,2,5,2,4,5,2,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +22056,29782,Female,Loyal Customer,26,Business travel,Business,571,1,1,1,1,5,5,5,5,2,4,4,5,1,5,204,185.0,satisfied +22057,16798,Male,Loyal Customer,46,Business travel,Eco,1017,5,5,4,4,5,5,5,5,4,5,3,2,5,5,113,121.0,satisfied +22058,27813,Male,disloyal Customer,14,Business travel,Eco,1409,3,3,3,3,2,3,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +22059,67870,Female,Loyal Customer,62,Personal Travel,Eco,1188,1,3,1,2,4,3,2,5,5,1,5,4,5,2,0,6.0,neutral or dissatisfied +22060,34542,Female,Loyal Customer,43,Business travel,Business,1598,4,3,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +22061,80642,Female,disloyal Customer,27,Business travel,Eco Plus,282,2,2,2,4,3,2,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +22062,11791,Female,Loyal Customer,21,Personal Travel,Eco,395,2,5,2,4,3,2,3,3,3,5,5,3,4,3,19,23.0,neutral or dissatisfied +22063,75723,Male,Loyal Customer,57,Business travel,Business,2135,1,1,1,1,5,4,5,5,5,5,5,5,5,5,6,2.0,satisfied +22064,62738,Female,Loyal Customer,17,Business travel,Business,2486,5,5,5,5,2,2,2,5,5,4,5,2,5,2,0,33.0,satisfied +22065,84262,Male,Loyal Customer,63,Business travel,Business,334,5,5,5,5,2,5,4,5,5,5,5,4,5,5,45,27.0,satisfied +22066,63664,Female,disloyal Customer,29,Business travel,Business,2405,3,3,3,4,1,3,2,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +22067,32323,Female,Loyal Customer,44,Business travel,Eco,102,4,2,2,2,5,4,1,4,4,4,4,4,4,2,0,0.0,satisfied +22068,60677,Male,Loyal Customer,11,Personal Travel,Eco Plus,1620,2,5,2,3,2,2,2,2,4,2,4,5,4,2,21,0.0,neutral or dissatisfied +22069,33961,Male,Loyal Customer,56,Business travel,Business,1598,4,4,4,4,3,3,5,5,5,5,5,4,5,3,58,47.0,satisfied +22070,18846,Female,disloyal Customer,50,Business travel,Eco,448,2,5,2,3,2,2,2,2,2,5,2,2,4,2,16,9.0,neutral or dissatisfied +22071,49483,Female,disloyal Customer,44,Business travel,Eco,109,2,2,2,3,3,2,3,3,3,2,3,2,4,3,19,13.0,neutral or dissatisfied +22072,45828,Male,Loyal Customer,41,Personal Travel,Eco,391,2,5,2,4,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +22073,19342,Female,Loyal Customer,67,Personal Travel,Eco,743,1,4,1,5,3,4,4,1,1,1,1,5,1,3,29,15.0,neutral or dissatisfied +22074,18546,Female,Loyal Customer,35,Business travel,Eco,253,1,0,0,4,1,0,1,1,3,3,3,1,3,1,6,0.0,neutral or dissatisfied +22075,58121,Male,Loyal Customer,24,Personal Travel,Eco,589,3,4,3,1,2,3,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +22076,111179,Male,Loyal Customer,42,Business travel,Business,1447,1,1,1,1,2,5,5,2,2,2,2,5,2,5,68,56.0,satisfied +22077,102100,Female,Loyal Customer,42,Business travel,Business,258,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +22078,12663,Female,Loyal Customer,29,Business travel,Business,3637,4,3,3,3,4,4,4,4,3,5,4,2,4,4,23,12.0,neutral or dissatisfied +22079,24112,Male,Loyal Customer,60,Business travel,Eco,510,3,2,2,2,4,3,4,4,2,5,4,1,3,4,0,0.0,neutral or dissatisfied +22080,113359,Male,Loyal Customer,46,Business travel,Business,2698,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22081,7980,Male,Loyal Customer,43,Business travel,Business,1505,5,5,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +22082,85332,Female,Loyal Customer,23,Business travel,Business,3529,5,5,5,5,4,4,4,4,3,3,4,4,5,4,50,53.0,satisfied +22083,116327,Female,Loyal Customer,33,Personal Travel,Eco,342,1,4,1,3,5,1,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +22084,30502,Male,Loyal Customer,62,Business travel,Business,2859,2,4,4,4,5,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +22085,61794,Male,Loyal Customer,59,Personal Travel,Eco,1379,1,5,0,2,5,0,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +22086,33257,Female,Loyal Customer,27,Personal Travel,Eco Plus,163,3,4,3,2,1,3,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +22087,88354,Female,disloyal Customer,27,Business travel,Eco,240,1,2,1,4,4,1,2,4,1,1,3,4,4,4,5,1.0,neutral or dissatisfied +22088,128647,Female,Loyal Customer,37,Business travel,Business,2347,4,4,4,4,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +22089,3689,Female,Loyal Customer,59,Business travel,Business,2827,1,5,5,5,1,1,1,3,2,3,4,1,3,1,303,315.0,neutral or dissatisfied +22090,45620,Male,Loyal Customer,44,Business travel,Business,2515,1,3,5,3,4,4,3,1,1,2,1,3,1,2,34,26.0,neutral or dissatisfied +22091,64183,Female,disloyal Customer,42,Business travel,Business,1047,5,5,5,3,4,5,4,4,4,5,5,3,4,4,0,0.0,satisfied +22092,99691,Female,Loyal Customer,33,Business travel,Business,2475,1,1,1,1,3,1,3,4,4,4,4,2,4,4,0,0.0,satisfied +22093,45052,Female,Loyal Customer,44,Business travel,Eco,265,4,3,3,3,1,5,3,4,4,4,4,3,4,2,0,0.0,satisfied +22094,105463,Male,Loyal Customer,44,Business travel,Business,2461,5,5,5,5,4,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +22095,121480,Female,Loyal Customer,38,Personal Travel,Eco,331,3,0,3,4,2,3,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +22096,70349,Female,Loyal Customer,22,Personal Travel,Eco,986,3,4,3,3,2,3,2,2,3,3,5,3,4,2,8,66.0,neutral or dissatisfied +22097,79146,Male,Loyal Customer,29,Personal Travel,Eco Plus,356,4,4,4,4,3,4,3,3,3,2,5,4,5,3,39,30.0,neutral or dissatisfied +22098,116267,Male,Loyal Customer,12,Personal Travel,Eco,446,1,4,1,3,4,1,4,4,5,5,5,5,4,4,124,111.0,neutral or dissatisfied +22099,109980,Female,Loyal Customer,46,Personal Travel,Eco,1092,2,4,2,2,1,5,3,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +22100,23117,Male,Loyal Customer,41,Business travel,Business,300,3,2,2,2,4,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +22101,35229,Female,Loyal Customer,27,Business travel,Business,1980,5,5,5,5,1,2,1,1,3,2,3,2,1,1,79,83.0,satisfied +22102,35346,Female,Loyal Customer,30,Business travel,Business,2654,2,1,1,1,2,2,2,2,4,3,4,3,3,2,12,11.0,neutral or dissatisfied +22103,112961,Female,Loyal Customer,61,Personal Travel,Eco,1497,2,3,2,5,5,5,5,3,3,2,3,5,3,5,11,0.0,neutral or dissatisfied +22104,70220,Male,Loyal Customer,42,Business travel,Business,3713,5,5,5,5,4,5,4,4,4,4,4,5,4,4,0,12.0,satisfied +22105,89812,Male,Loyal Customer,47,Business travel,Business,2970,2,2,2,2,5,5,5,4,4,4,4,3,4,4,56,51.0,satisfied +22106,27136,Male,Loyal Customer,49,Business travel,Business,2701,2,2,2,2,4,4,4,2,4,5,4,4,3,4,0,0.0,satisfied +22107,23863,Male,Loyal Customer,36,Personal Travel,Eco,522,1,5,4,3,5,4,5,5,3,5,4,5,4,5,125,114.0,neutral or dissatisfied +22108,4476,Female,Loyal Customer,50,Business travel,Business,1005,4,4,4,4,2,5,5,3,3,3,3,5,3,4,0,14.0,satisfied +22109,74217,Female,disloyal Customer,22,Business travel,Business,1746,0,0,0,2,3,0,3,3,5,5,5,4,4,3,0,0.0,satisfied +22110,111138,Female,disloyal Customer,26,Business travel,Business,1180,4,4,4,5,1,4,1,1,5,3,4,4,4,1,0,0.0,satisfied +22111,113884,Male,Loyal Customer,54,Personal Travel,Eco Plus,1592,3,5,3,3,3,3,3,3,5,2,4,3,4,3,10,0.0,neutral or dissatisfied +22112,25619,Male,Loyal Customer,24,Business travel,Eco,666,4,2,2,2,4,4,5,4,1,1,5,5,5,4,17,4.0,satisfied +22113,34751,Male,Loyal Customer,46,Business travel,Eco,264,3,2,2,2,3,3,3,3,1,3,4,4,3,3,0,1.0,neutral or dissatisfied +22114,19783,Male,Loyal Customer,26,Business travel,Business,667,4,2,3,2,4,4,4,3,5,4,4,4,3,4,193,208.0,neutral or dissatisfied +22115,114617,Female,disloyal Customer,40,Business travel,Business,404,4,4,4,2,4,4,4,4,5,3,4,5,5,4,0,0.0,satisfied +22116,29028,Female,Loyal Customer,18,Business travel,Business,954,1,1,2,1,4,4,4,4,1,1,4,5,2,4,0,0.0,satisfied +22117,16013,Female,Loyal Customer,37,Business travel,Business,3488,4,4,4,4,1,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +22118,78637,Male,Loyal Customer,15,Personal Travel,Business,2172,3,4,3,4,1,3,4,1,4,3,4,4,4,1,0,1.0,neutral or dissatisfied +22119,71671,Female,Loyal Customer,48,Personal Travel,Eco,1120,1,5,1,1,2,5,3,3,3,1,4,4,3,2,10,9.0,neutral or dissatisfied +22120,67402,Male,Loyal Customer,51,Business travel,Business,3422,3,1,1,1,4,2,2,3,3,3,3,3,3,1,28,26.0,neutral or dissatisfied +22121,34781,Female,Loyal Customer,14,Personal Travel,Eco,209,4,5,4,4,4,4,1,4,1,2,2,3,4,4,11,3.0,neutral or dissatisfied +22122,87799,Female,Loyal Customer,44,Business travel,Business,2665,5,5,5,5,2,4,5,5,5,5,4,5,5,4,2,0.0,satisfied +22123,19760,Male,Loyal Customer,30,Personal Travel,Eco,462,4,5,5,4,4,5,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +22124,25224,Female,Loyal Customer,32,Business travel,Eco,842,0,0,0,1,4,0,4,4,4,4,4,2,1,4,0,7.0,satisfied +22125,47517,Female,Loyal Customer,53,Personal Travel,Eco,588,3,2,3,3,3,4,3,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +22126,79918,Male,Loyal Customer,37,Business travel,Business,1069,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +22127,62465,Female,Loyal Customer,29,Business travel,Business,1726,1,1,1,1,5,5,5,3,5,5,5,5,5,5,139,139.0,satisfied +22128,63899,Male,Loyal Customer,46,Business travel,Eco,1212,4,1,1,1,4,4,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +22129,39962,Female,Loyal Customer,57,Personal Travel,Eco Plus,1195,4,5,4,4,4,4,5,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +22130,55812,Male,Loyal Customer,41,Business travel,Business,1416,1,1,1,1,2,5,4,2,2,2,2,5,2,4,5,0.0,satisfied +22131,31431,Male,Loyal Customer,51,Personal Travel,Eco,1546,2,5,3,3,1,3,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +22132,50107,Male,Loyal Customer,46,Business travel,Eco,250,4,1,1,1,4,4,4,4,5,2,5,1,1,4,0,0.0,satisfied +22133,953,Male,Loyal Customer,56,Business travel,Business,89,3,4,4,4,1,4,4,1,1,2,3,3,1,1,0,0.0,neutral or dissatisfied +22134,32210,Female,Loyal Customer,34,Business travel,Eco,163,5,3,3,3,5,5,5,5,1,2,3,5,5,5,0,2.0,satisfied +22135,37805,Female,Loyal Customer,13,Personal Travel,Eco Plus,1165,4,5,4,4,3,4,3,3,3,2,5,3,5,3,121,109.0,neutral or dissatisfied +22136,38177,Male,Loyal Customer,17,Personal Travel,Eco,1237,1,4,1,3,1,1,1,1,5,2,4,4,5,1,22,8.0,neutral or dissatisfied +22137,89493,Female,disloyal Customer,30,Business travel,Business,1931,1,1,1,3,1,1,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +22138,41052,Male,Loyal Customer,25,Personal Travel,Eco,1086,1,5,1,2,2,1,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +22139,73738,Male,Loyal Customer,11,Personal Travel,Eco,192,4,5,4,4,3,4,2,3,5,5,4,3,5,3,10,0.0,satisfied +22140,16290,Male,Loyal Customer,14,Personal Travel,Eco,748,3,4,3,5,3,3,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +22141,107540,Female,Loyal Customer,42,Business travel,Business,1680,4,1,4,4,5,4,4,4,4,4,4,3,4,5,33,18.0,satisfied +22142,114703,Male,Loyal Customer,52,Business travel,Business,337,0,0,0,2,3,4,4,2,2,3,3,5,2,4,7,1.0,satisfied +22143,113099,Male,Loyal Customer,29,Personal Travel,Eco,479,4,1,4,4,5,4,5,5,3,1,3,1,3,5,0,0.0,neutral or dissatisfied +22144,123345,Male,Loyal Customer,37,Personal Travel,Eco Plus,507,1,4,1,3,5,1,5,5,5,4,5,5,5,5,19,23.0,neutral or dissatisfied +22145,101900,Male,Loyal Customer,24,Business travel,Business,2039,1,2,4,2,1,1,1,1,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +22146,69557,Female,Loyal Customer,57,Business travel,Business,2475,3,3,3,3,5,5,5,4,3,4,5,5,4,5,0,0.0,satisfied +22147,2419,Male,Loyal Customer,52,Personal Travel,Eco,767,2,5,2,3,2,2,2,2,4,4,3,5,5,2,0,5.0,neutral or dissatisfied +22148,121905,Male,Loyal Customer,36,Personal Travel,Eco,449,2,5,2,1,2,2,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +22149,126028,Male,Loyal Customer,45,Business travel,Eco,590,2,4,1,4,3,2,3,3,1,1,4,1,4,3,2,4.0,neutral or dissatisfied +22150,10804,Male,Loyal Customer,50,Business travel,Eco,667,2,2,2,2,2,2,2,2,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +22151,34458,Female,Loyal Customer,48,Personal Travel,Eco,228,3,4,3,3,3,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +22152,107170,Male,Loyal Customer,52,Business travel,Business,3907,1,1,5,1,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +22153,111192,Male,Loyal Customer,33,Business travel,Eco,1703,2,1,1,1,2,2,2,2,4,5,3,4,4,2,1,0.0,neutral or dissatisfied +22154,128055,Female,Loyal Customer,66,Personal Travel,Eco,735,2,1,1,3,2,3,2,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +22155,23570,Female,disloyal Customer,17,Business travel,Eco,1015,2,2,2,3,1,2,1,1,1,1,3,3,4,1,48,35.0,neutral or dissatisfied +22156,96879,Male,Loyal Customer,16,Personal Travel,Eco,957,1,4,1,3,3,1,3,3,3,2,3,3,3,3,50,35.0,neutral or dissatisfied +22157,77040,Female,Loyal Customer,68,Personal Travel,Eco Plus,368,3,3,3,4,3,4,3,1,1,3,1,1,1,1,0,22.0,neutral or dissatisfied +22158,109736,Male,Loyal Customer,31,Personal Travel,Eco,534,2,4,2,4,4,2,4,4,3,5,4,4,4,4,72,71.0,neutral or dissatisfied +22159,61141,Male,disloyal Customer,42,Business travel,Business,862,3,3,3,2,1,3,1,1,3,2,5,4,4,1,0,0.0,satisfied +22160,59163,Female,disloyal Customer,25,Business travel,Business,928,4,0,4,2,1,4,4,1,4,5,3,3,4,1,11,0.0,satisfied +22161,55714,Female,Loyal Customer,43,Personal Travel,Eco,1062,4,5,4,4,2,4,4,2,2,4,2,5,2,5,1,12.0,neutral or dissatisfied +22162,61700,Male,Loyal Customer,45,Business travel,Business,2930,2,5,5,5,5,4,3,2,2,2,2,1,2,4,12,3.0,neutral or dissatisfied +22163,47727,Male,Loyal Customer,44,Business travel,Business,834,3,3,5,3,5,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +22164,120684,Female,Loyal Customer,39,Personal Travel,Eco,280,4,4,4,1,4,4,1,4,5,5,4,5,5,4,0,8.0,neutral or dissatisfied +22165,120277,Male,Loyal Customer,29,Business travel,Eco,1576,3,3,3,3,3,3,3,3,2,1,4,4,4,3,1,0.0,neutral or dissatisfied +22166,45583,Female,Loyal Customer,30,Business travel,Eco,260,4,4,4,4,4,4,4,4,2,4,1,3,4,4,0,0.0,satisfied +22167,12048,Male,disloyal Customer,28,Business travel,Business,351,2,2,2,3,3,2,1,3,1,4,2,1,3,3,0,0.0,neutral or dissatisfied +22168,63205,Female,disloyal Customer,64,Business travel,Eco,372,4,2,4,4,4,4,4,4,3,2,4,3,3,4,0,4.0,neutral or dissatisfied +22169,95518,Male,Loyal Customer,30,Business travel,Eco Plus,248,2,2,2,2,2,2,2,2,4,1,4,3,3,2,28,28.0,neutral or dissatisfied +22170,123534,Female,Loyal Customer,7,Personal Travel,Eco Plus,2125,5,3,5,4,4,5,2,4,4,5,4,1,4,4,64,69.0,satisfied +22171,12523,Female,disloyal Customer,25,Business travel,Eco,871,2,2,2,3,3,2,3,3,4,5,3,3,3,3,60,81.0,neutral or dissatisfied +22172,21024,Female,Loyal Customer,43,Business travel,Eco,106,5,2,2,2,5,3,3,5,5,5,5,1,5,3,0,0.0,satisfied +22173,39273,Female,disloyal Customer,36,Business travel,Eco,67,1,2,1,3,1,1,1,1,4,1,3,1,4,1,0,0.0,neutral or dissatisfied +22174,2035,Male,Loyal Customer,42,Business travel,Business,3809,4,4,4,4,4,4,4,4,2,5,4,4,4,4,133,193.0,satisfied +22175,97521,Female,Loyal Customer,55,Business travel,Business,2193,3,5,5,5,4,3,3,3,3,3,3,3,3,3,14,13.0,neutral or dissatisfied +22176,37265,Male,disloyal Customer,37,Business travel,Eco,944,5,5,5,3,2,5,2,2,4,3,2,3,1,2,0,0.0,satisfied +22177,46216,Female,Loyal Customer,53,Business travel,Business,3129,2,2,5,2,3,3,4,5,5,4,5,2,5,5,38,48.0,satisfied +22178,1582,Male,disloyal Customer,26,Business travel,Business,140,1,2,0,3,4,0,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +22179,50342,Female,Loyal Customer,64,Business travel,Business,308,3,3,3,3,1,5,5,4,4,4,4,1,4,4,0,0.0,satisfied +22180,108880,Male,Loyal Customer,51,Business travel,Business,2258,2,2,2,2,3,4,5,5,5,5,5,4,5,4,20,11.0,satisfied +22181,97018,Male,Loyal Customer,17,Personal Travel,Eco,883,1,4,1,4,2,1,3,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +22182,52970,Female,Loyal Customer,16,Personal Travel,Eco,2306,2,4,1,1,4,1,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +22183,117298,Female,disloyal Customer,30,Business travel,Business,370,0,0,0,1,1,0,1,1,5,4,4,3,5,1,0,0.0,satisfied +22184,12311,Female,Loyal Customer,56,Business travel,Business,3194,5,5,3,5,3,4,3,5,5,5,5,4,5,4,0,0.0,satisfied +22185,44372,Female,Loyal Customer,22,Personal Travel,Eco,596,3,1,3,3,2,3,2,2,2,4,1,4,2,2,0,0.0,neutral or dissatisfied +22186,56916,Male,Loyal Customer,43,Business travel,Business,2454,2,2,2,2,3,4,5,4,4,4,4,3,4,5,13,0.0,satisfied +22187,23854,Male,Loyal Customer,25,Business travel,Business,552,3,2,2,2,3,3,3,3,3,4,3,3,4,3,5,16.0,neutral or dissatisfied +22188,126706,Female,Loyal Customer,59,Business travel,Business,2402,5,5,5,5,3,3,4,3,3,4,3,3,3,4,0,0.0,satisfied +22189,6671,Male,Loyal Customer,54,Business travel,Business,1585,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22190,104259,Female,Loyal Customer,58,Personal Travel,Business,456,2,4,4,1,5,5,4,5,5,4,5,4,5,5,29,21.0,neutral or dissatisfied +22191,53312,Male,Loyal Customer,60,Personal Travel,Eco,921,4,5,4,2,1,4,1,1,5,5,4,5,4,1,0,0.0,satisfied +22192,82944,Male,Loyal Customer,56,Business travel,Business,1084,1,1,1,1,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +22193,76213,Male,Loyal Customer,57,Business travel,Business,3101,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +22194,71414,Male,Loyal Customer,8,Personal Travel,Eco,334,4,2,4,3,3,4,3,3,3,3,4,4,4,3,0,0.0,satisfied +22195,10877,Male,Loyal Customer,49,Business travel,Eco,247,2,4,4,4,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +22196,62189,Female,disloyal Customer,23,Business travel,Eco,925,5,5,5,3,4,5,1,4,5,2,2,5,5,4,4,3.0,satisfied +22197,24747,Female,disloyal Customer,39,Business travel,Business,432,2,2,2,3,2,2,2,2,3,1,5,2,4,2,0,4.0,neutral or dissatisfied +22198,123100,Male,Loyal Customer,66,Business travel,Eco,600,3,1,1,1,3,3,3,3,2,4,4,1,3,3,6,1.0,neutral or dissatisfied +22199,25582,Female,disloyal Customer,18,Business travel,Eco,874,3,2,2,4,1,2,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +22200,23155,Male,Loyal Customer,22,Personal Travel,Eco,646,5,5,5,3,1,5,1,1,5,2,5,3,1,1,0,0.0,satisfied +22201,110872,Male,Loyal Customer,53,Business travel,Business,404,5,5,5,5,4,5,5,4,4,4,4,4,4,4,35,38.0,satisfied +22202,36329,Female,Loyal Customer,34,Business travel,Business,3303,5,5,5,5,2,1,4,4,4,4,4,2,4,3,33,,satisfied +22203,42782,Female,Loyal Customer,44,Business travel,Eco,1118,5,2,1,2,5,5,5,5,2,1,2,5,4,5,333,371.0,satisfied +22204,105623,Male,Loyal Customer,52,Business travel,Business,3836,5,5,5,5,5,5,5,4,4,4,4,4,4,3,8,10.0,satisfied +22205,42765,Female,Loyal Customer,31,Business travel,Business,493,2,4,5,5,2,2,2,2,4,1,3,2,4,2,0,0.0,neutral or dissatisfied +22206,79270,Female,Loyal Customer,36,Business travel,Business,2454,1,2,2,2,2,1,1,3,3,1,2,1,2,1,7,6.0,neutral or dissatisfied +22207,121820,Female,Loyal Customer,41,Business travel,Business,366,4,4,4,4,5,4,4,4,4,4,4,3,4,4,6,0.0,satisfied +22208,3625,Female,disloyal Customer,42,Business travel,Business,427,5,5,5,1,1,5,1,1,3,5,4,3,4,1,57,50.0,satisfied +22209,98822,Male,Loyal Customer,39,Business travel,Eco,763,3,2,2,2,3,3,3,3,3,3,2,3,1,3,5,0.0,neutral or dissatisfied +22210,74050,Female,Loyal Customer,28,Personal Travel,Eco,1194,3,1,3,1,5,3,5,5,4,2,2,2,2,5,3,0.0,neutral or dissatisfied +22211,21404,Male,disloyal Customer,33,Business travel,Eco,331,1,0,0,4,3,0,3,3,3,3,2,5,4,3,0,10.0,neutral or dissatisfied +22212,2528,Male,Loyal Customer,49,Business travel,Business,1545,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +22213,88077,Male,disloyal Customer,25,Business travel,Business,404,5,0,5,1,5,5,5,5,5,5,4,5,4,5,0,3.0,satisfied +22214,83375,Female,Loyal Customer,7,Personal Travel,Eco,1124,4,4,3,1,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +22215,24395,Male,Loyal Customer,31,Business travel,Eco Plus,669,4,2,2,2,4,4,4,4,2,4,1,1,1,4,0,0.0,satisfied +22216,43657,Male,Loyal Customer,22,Business travel,Business,1620,1,1,4,1,1,1,1,1,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +22217,14792,Female,Loyal Customer,65,Personal Travel,Eco,622,4,4,3,3,4,5,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +22218,51059,Male,Loyal Customer,21,Personal Travel,Eco,110,2,4,2,1,3,2,3,3,3,2,1,3,4,3,22,10.0,neutral or dissatisfied +22219,34475,Female,Loyal Customer,61,Business travel,Business,3218,4,4,4,4,2,4,2,4,4,4,4,5,4,4,0,3.0,satisfied +22220,63732,Male,Loyal Customer,22,Personal Travel,Eco,1660,3,4,3,3,1,3,1,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +22221,71434,Male,disloyal Customer,45,Business travel,Business,867,4,4,4,2,4,4,4,4,4,3,4,3,5,4,7,0.0,satisfied +22222,112601,Female,Loyal Customer,50,Business travel,Business,1759,2,2,5,2,2,3,3,2,2,2,2,4,2,2,106,86.0,neutral or dissatisfied +22223,21009,Male,Loyal Customer,68,Personal Travel,Eco Plus,689,3,5,3,3,2,3,2,2,4,3,2,4,5,2,0,0.0,neutral or dissatisfied +22224,15238,Male,Loyal Customer,78,Business travel,Eco,129,1,0,0,3,4,1,3,4,3,4,4,2,3,4,26,40.0,neutral or dissatisfied +22225,70033,Female,Loyal Customer,34,Business travel,Business,3939,2,1,1,1,5,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +22226,72910,Male,Loyal Customer,31,Business travel,Business,1763,3,3,3,3,4,5,4,4,5,2,4,3,4,4,0,0.0,satisfied +22227,123221,Male,Loyal Customer,9,Personal Travel,Eco,631,4,4,4,3,1,4,1,1,4,2,5,3,5,1,30,17.0,neutral or dissatisfied +22228,125800,Male,Loyal Customer,51,Business travel,Business,1973,1,1,1,1,4,4,5,2,2,2,2,5,2,4,43,40.0,satisfied +22229,116175,Male,Loyal Customer,61,Personal Travel,Eco,296,3,5,3,4,3,3,5,3,5,3,5,5,4,3,49,55.0,neutral or dissatisfied +22230,312,Male,Loyal Customer,22,Business travel,Business,3206,2,2,2,2,5,5,5,4,2,5,4,5,4,5,41,133.0,satisfied +22231,86005,Female,Loyal Customer,40,Business travel,Eco,432,4,2,2,2,4,4,4,4,3,5,3,4,4,4,51,86.0,neutral or dissatisfied +22232,52017,Female,disloyal Customer,22,Business travel,Eco,328,1,4,1,5,1,1,1,1,2,4,1,4,1,1,0,0.0,neutral or dissatisfied +22233,41719,Male,disloyal Customer,45,Business travel,Eco,468,1,1,1,4,1,1,4,1,2,1,3,1,3,1,0,0.0,neutral or dissatisfied +22234,116042,Male,Loyal Customer,48,Personal Travel,Eco,404,3,4,5,2,1,5,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +22235,30002,Male,Loyal Customer,33,Business travel,Business,261,3,5,5,5,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +22236,98133,Female,Loyal Customer,14,Personal Travel,Eco,472,2,0,2,4,3,2,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +22237,29866,Male,Loyal Customer,40,Business travel,Eco,539,4,3,3,3,4,4,4,4,5,4,1,4,4,4,0,0.0,satisfied +22238,114285,Female,Loyal Customer,40,Personal Travel,Eco,853,2,5,2,2,3,2,1,3,4,4,5,3,4,3,34,9.0,neutral or dissatisfied +22239,84378,Male,Loyal Customer,25,Business travel,Business,591,3,4,4,4,3,3,3,3,2,1,3,1,3,3,0,39.0,neutral or dissatisfied +22240,37293,Male,Loyal Customer,30,Business travel,Business,944,3,3,3,3,5,5,5,5,4,3,3,3,5,5,0,0.0,satisfied +22241,68027,Female,Loyal Customer,37,Business travel,Eco Plus,304,2,5,5,5,2,2,2,2,3,3,3,2,3,2,6,5.0,neutral or dissatisfied +22242,116570,Female,disloyal Customer,34,Business travel,Business,390,3,3,3,3,4,3,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +22243,35110,Male,Loyal Customer,34,Business travel,Business,2716,4,1,4,4,3,1,5,3,3,3,3,2,3,5,0,13.0,satisfied +22244,76699,Female,Loyal Customer,48,Personal Travel,Eco,534,3,4,3,3,3,5,5,2,2,3,2,3,2,3,14,21.0,neutral or dissatisfied +22245,64444,Female,disloyal Customer,12,Business travel,Business,989,0,0,0,1,3,0,3,3,5,4,4,4,5,3,0,0.0,satisfied +22246,75342,Male,Loyal Customer,69,Personal Travel,Eco,2556,1,5,1,3,1,1,1,3,2,3,5,1,5,1,8,18.0,neutral or dissatisfied +22247,128667,Female,Loyal Customer,51,Business travel,Business,2419,5,5,2,5,5,5,5,3,5,3,4,5,3,5,0,0.0,satisfied +22248,58854,Female,disloyal Customer,40,Business travel,Business,888,2,3,3,3,2,3,5,2,4,3,3,3,3,2,0,0.0,neutral or dissatisfied +22249,64661,Female,disloyal Customer,25,Business travel,Business,190,2,0,2,4,1,2,1,1,4,3,5,4,4,1,6,9.0,neutral or dissatisfied +22250,12518,Female,Loyal Customer,27,Business travel,Business,3686,2,2,2,2,4,4,4,4,4,4,3,1,3,4,5,3.0,satisfied +22251,4854,Female,Loyal Customer,38,Business travel,Business,3969,3,5,5,5,2,3,3,3,3,3,3,3,3,4,11,24.0,neutral or dissatisfied +22252,50814,Male,Loyal Customer,29,Personal Travel,Eco,337,1,5,1,2,3,1,3,3,3,1,5,3,1,3,0,28.0,neutral or dissatisfied +22253,8696,Female,Loyal Customer,42,Business travel,Business,280,1,1,1,1,5,4,5,5,5,5,5,3,5,5,16,7.0,satisfied +22254,52583,Female,Loyal Customer,43,Business travel,Business,160,1,1,1,1,4,5,3,4,4,4,5,3,4,5,0,0.0,satisfied +22255,123431,Female,Loyal Customer,40,Business travel,Business,2077,4,4,1,4,2,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +22256,43781,Male,Loyal Customer,51,Personal Travel,Eco,546,1,5,2,5,1,2,1,1,4,4,1,2,2,1,20,14.0,neutral or dissatisfied +22257,59777,Male,Loyal Customer,10,Personal Travel,Eco,895,2,4,2,3,5,2,5,5,5,5,4,5,4,5,93,75.0,neutral or dissatisfied +22258,55199,Male,Loyal Customer,42,Personal Travel,Eco Plus,1635,1,4,1,3,5,1,5,5,3,5,4,5,4,5,14,9.0,neutral or dissatisfied +22259,86590,Male,Loyal Customer,25,Business travel,Eco Plus,1269,2,2,2,2,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +22260,103520,Female,Loyal Customer,9,Personal Travel,Eco,1047,3,5,3,4,5,3,5,5,3,3,5,4,5,5,3,0.0,neutral or dissatisfied +22261,25844,Female,Loyal Customer,60,Business travel,Eco,484,1,2,1,2,4,4,3,1,1,1,1,2,1,3,0,33.0,neutral or dissatisfied +22262,22859,Male,Loyal Customer,9,Personal Travel,Eco,134,5,4,5,4,4,5,4,4,3,2,3,1,3,4,12,0.0,satisfied +22263,65570,Female,Loyal Customer,57,Business travel,Business,175,3,5,5,5,4,2,3,1,1,2,3,3,1,4,8,0.0,neutral or dissatisfied +22264,54468,Male,Loyal Customer,38,Business travel,Eco,925,5,3,3,3,5,5,5,5,5,5,1,5,3,5,36,30.0,satisfied +22265,68832,Male,Loyal Customer,69,Business travel,Business,2810,4,4,4,4,5,5,4,4,4,5,4,5,4,3,0,9.0,satisfied +22266,83555,Female,Loyal Customer,52,Business travel,Business,1865,3,3,3,3,5,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +22267,66054,Female,Loyal Customer,49,Business travel,Business,655,3,3,3,3,2,1,3,2,2,2,2,3,2,5,7,0.0,satisfied +22268,120062,Female,disloyal Customer,16,Business travel,Eco,683,3,3,3,1,3,1,1,4,5,4,4,1,3,1,150,135.0,neutral or dissatisfied +22269,109200,Male,Loyal Customer,32,Business travel,Business,612,1,1,1,1,4,4,4,4,4,5,5,5,4,4,10,2.0,satisfied +22270,64078,Female,Loyal Customer,31,Personal Travel,Eco,919,3,3,3,3,1,3,1,1,2,2,3,3,4,1,11,0.0,neutral or dissatisfied +22271,3138,Female,Loyal Customer,51,Business travel,Business,3762,3,4,3,3,5,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +22272,61073,Male,Loyal Customer,71,Business travel,Business,1546,2,2,2,2,5,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +22273,8248,Male,Loyal Customer,60,Personal Travel,Eco,294,1,4,1,4,4,1,4,4,5,2,4,5,4,4,0,4.0,neutral or dissatisfied +22274,118792,Male,Loyal Customer,11,Personal Travel,Eco,369,1,2,1,4,5,1,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +22275,33158,Female,Loyal Customer,50,Personal Travel,Eco,101,1,5,1,2,4,2,2,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +22276,102343,Female,Loyal Customer,58,Business travel,Business,236,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +22277,55089,Female,disloyal Customer,22,Business travel,Eco,1303,2,2,2,4,3,2,2,3,3,3,4,2,4,3,13,29.0,neutral or dissatisfied +22278,3514,Male,Loyal Customer,55,Business travel,Business,557,4,4,4,4,3,3,3,4,4,5,5,3,4,3,120,229.0,satisfied +22279,26105,Male,disloyal Customer,10,Business travel,Eco,591,4,0,4,3,2,4,3,2,4,4,5,4,5,2,0,3.0,satisfied +22280,104299,Male,Loyal Customer,34,Personal Travel,Eco,440,2,5,2,5,5,2,3,5,4,4,5,5,5,5,63,55.0,neutral or dissatisfied +22281,125088,Female,Loyal Customer,60,Business travel,Business,2162,4,4,4,4,3,4,4,4,4,4,4,4,4,4,4,1.0,satisfied +22282,24503,Female,Loyal Customer,7,Personal Travel,Eco,547,1,4,1,3,4,1,4,4,2,2,4,5,5,4,0,0.0,neutral or dissatisfied +22283,97895,Female,Loyal Customer,55,Business travel,Business,3635,3,3,5,3,4,5,5,4,4,4,4,3,4,5,4,22.0,satisfied +22284,107780,Female,Loyal Customer,44,Business travel,Business,2253,0,0,0,4,3,5,4,5,5,5,5,5,5,3,13,4.0,satisfied +22285,50808,Female,Loyal Customer,58,Personal Travel,Eco,266,2,2,2,1,5,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +22286,40337,Female,Loyal Customer,50,Personal Travel,Eco Plus,463,3,4,3,2,3,2,4,4,5,5,4,4,5,4,176,161.0,neutral or dissatisfied +22287,49740,Male,disloyal Customer,26,Business travel,Eco,250,2,5,1,1,4,1,4,4,3,4,5,1,4,4,112,106.0,neutral or dissatisfied +22288,20151,Female,Loyal Customer,63,Business travel,Eco,403,3,3,4,4,2,2,1,3,3,3,3,2,3,1,3,17.0,neutral or dissatisfied +22289,74162,Male,Loyal Customer,57,Personal Travel,Eco,592,1,5,1,1,5,1,2,5,5,1,2,2,4,5,25,27.0,neutral or dissatisfied +22290,90637,Female,Loyal Customer,60,Business travel,Business,1921,3,3,3,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +22291,13367,Male,Loyal Customer,12,Personal Travel,Eco,946,4,4,4,4,3,4,2,3,2,4,4,2,1,3,0,0.0,neutral or dissatisfied +22292,16189,Male,Loyal Customer,40,Business travel,Business,1912,4,4,4,4,4,1,4,4,4,5,4,4,4,2,0,0.0,satisfied +22293,90738,Male,Loyal Customer,46,Business travel,Eco,545,1,3,3,3,1,1,1,1,4,3,4,1,3,1,19,25.0,neutral or dissatisfied +22294,52654,Female,Loyal Customer,39,Personal Travel,Eco,119,3,3,3,3,2,3,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +22295,5774,Male,Loyal Customer,53,Business travel,Business,1985,3,3,3,3,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +22296,20656,Female,Loyal Customer,26,Business travel,Business,552,2,2,2,2,4,4,4,4,2,1,4,4,3,4,0,0.0,satisfied +22297,15758,Male,Loyal Customer,69,Personal Travel,Eco,544,3,2,3,4,5,3,5,5,2,1,4,1,4,5,0,0.0,neutral or dissatisfied +22298,83165,Female,Loyal Customer,9,Personal Travel,Eco Plus,1145,3,5,3,2,4,3,4,4,5,2,5,3,5,4,40,19.0,neutral or dissatisfied +22299,67686,Female,disloyal Customer,38,Business travel,Business,1464,1,0,0,3,3,0,3,3,4,2,5,5,4,3,4,0.0,neutral or dissatisfied +22300,50051,Male,disloyal Customer,32,Business travel,Business,363,2,2,2,4,4,2,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +22301,96252,Female,Loyal Customer,10,Personal Travel,Eco,546,3,3,3,3,3,3,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +22302,51175,Female,Loyal Customer,49,Personal Travel,Eco,209,3,5,3,1,5,4,2,1,1,3,1,2,1,2,6,3.0,neutral or dissatisfied +22303,79721,Female,Loyal Customer,37,Personal Travel,Eco,760,1,4,1,4,2,1,2,2,5,2,4,1,3,2,0,4.0,neutral or dissatisfied +22304,49350,Female,Loyal Customer,24,Business travel,Business,308,0,0,0,2,5,5,1,5,1,4,2,2,2,5,0,3.0,satisfied +22305,72996,Female,Loyal Customer,49,Business travel,Business,2455,4,4,4,4,5,1,4,4,4,4,4,2,4,3,2,0.0,satisfied +22306,6781,Male,disloyal Customer,24,Business travel,Business,223,5,5,5,2,3,5,5,3,4,4,4,3,5,3,39,37.0,satisfied +22307,64311,Male,Loyal Customer,42,Business travel,Business,1192,5,5,5,5,3,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +22308,15049,Male,Loyal Customer,51,Business travel,Eco,576,2,5,5,5,2,2,2,2,2,5,3,2,3,2,2,25.0,neutral or dissatisfied +22309,129131,Male,Loyal Customer,40,Business travel,Business,954,3,5,3,3,2,5,4,4,4,4,4,5,4,4,9,4.0,satisfied +22310,71730,Male,Loyal Customer,57,Personal Travel,Eco Plus,888,3,3,3,3,4,3,1,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +22311,19105,Male,Loyal Customer,45,Business travel,Business,287,4,4,4,4,1,1,2,5,5,5,5,1,5,4,0,0.0,satisfied +22312,56794,Female,disloyal Customer,24,Business travel,Eco,763,2,2,2,4,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +22313,8774,Male,Loyal Customer,50,Business travel,Business,2202,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +22314,92843,Male,Loyal Customer,67,Personal Travel,Eco,1541,3,5,3,3,4,3,4,4,1,5,5,4,4,4,0,0.0,neutral or dissatisfied +22315,4201,Male,Loyal Customer,21,Business travel,Business,888,5,5,5,5,4,4,4,4,5,5,5,3,4,4,27,14.0,satisfied +22316,101752,Female,Loyal Customer,41,Business travel,Business,1590,1,1,2,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +22317,108083,Female,Loyal Customer,31,Business travel,Business,2281,4,4,4,4,5,5,5,5,3,5,5,4,5,5,23,17.0,satisfied +22318,59649,Female,Loyal Customer,72,Business travel,Eco,387,4,3,3,3,1,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +22319,120708,Female,Loyal Customer,39,Personal Travel,Eco,280,2,4,2,1,3,2,5,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +22320,126544,Male,Loyal Customer,55,Business travel,Business,1683,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22321,35550,Male,Loyal Customer,33,Personal Travel,Eco,1076,3,5,3,1,1,3,1,1,3,2,4,4,4,1,59,72.0,neutral or dissatisfied +22322,125308,Female,Loyal Customer,39,Personal Travel,Eco,678,4,4,4,1,3,4,3,3,4,4,4,4,5,3,34,33.0,neutral or dissatisfied +22323,94320,Male,Loyal Customer,54,Business travel,Business,2636,0,0,0,3,4,5,5,4,4,4,4,4,4,5,57,52.0,satisfied +22324,57399,Male,Loyal Customer,55,Business travel,Business,1739,5,3,5,5,4,5,5,5,5,5,5,3,5,3,0,1.0,satisfied +22325,7354,Male,disloyal Customer,19,Business travel,Eco,864,4,4,4,4,4,5,2,4,5,3,3,2,2,2,103,171.0,neutral or dissatisfied +22326,120776,Female,Loyal Customer,31,Personal Travel,Eco,678,4,4,4,3,5,4,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +22327,73939,Female,disloyal Customer,48,Business travel,Eco,894,4,4,4,4,2,4,2,2,4,4,4,1,3,2,43,17.0,neutral or dissatisfied +22328,118567,Male,disloyal Customer,20,Business travel,Eco,370,4,2,4,4,1,4,1,1,1,2,3,2,3,1,1,5.0,neutral or dissatisfied +22329,87660,Female,Loyal Customer,56,Business travel,Business,591,3,1,1,1,4,3,4,3,3,3,3,2,3,3,29,20.0,neutral or dissatisfied +22330,115104,Male,Loyal Customer,36,Business travel,Business,1655,2,2,2,2,4,3,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +22331,77625,Female,Loyal Customer,72,Business travel,Business,2077,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,1.0,satisfied +22332,103775,Male,Loyal Customer,52,Business travel,Business,3661,2,2,2,2,2,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +22333,54360,Male,Loyal Customer,21,Personal Travel,Eco,1235,1,2,1,4,4,1,4,4,3,5,3,1,4,4,7,0.0,neutral or dissatisfied +22334,43103,Male,Loyal Customer,43,Personal Travel,Eco,192,3,4,0,3,1,0,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +22335,54553,Female,Loyal Customer,64,Personal Travel,Eco,925,4,4,4,3,3,4,5,4,4,4,4,3,4,3,20,41.0,neutral or dissatisfied +22336,46491,Female,Loyal Customer,30,Business travel,Business,1757,2,2,3,2,5,4,3,5,2,3,3,2,3,5,23,31.0,satisfied +22337,121241,Male,Loyal Customer,27,Business travel,Business,2075,1,4,4,4,1,1,1,1,2,3,3,3,3,1,0,16.0,neutral or dissatisfied +22338,25772,Female,Loyal Customer,69,Business travel,Eco,762,5,4,4,4,4,2,3,4,4,5,4,2,4,3,5,0.0,satisfied +22339,104790,Male,disloyal Customer,20,Business travel,Eco,587,3,5,3,5,3,3,2,3,3,2,4,5,5,3,3,4.0,neutral or dissatisfied +22340,50692,Male,Loyal Customer,50,Personal Travel,Eco,78,3,5,3,3,5,3,4,5,3,1,3,3,4,5,0,0.0,neutral or dissatisfied +22341,77886,Male,Loyal Customer,31,Personal Travel,Eco,700,4,4,3,5,3,3,3,3,4,2,4,4,2,3,10,0.0,neutral or dissatisfied +22342,123738,Female,Loyal Customer,52,Business travel,Business,3645,0,4,0,4,5,5,5,1,1,1,1,3,1,3,0,0.0,satisfied +22343,79985,Female,Loyal Customer,13,Personal Travel,Eco,950,5,2,5,3,4,5,4,4,4,5,3,4,3,4,0,13.0,satisfied +22344,50072,Female,Loyal Customer,38,Business travel,Business,3672,1,5,4,5,5,3,3,2,2,2,1,3,2,3,0,0.0,neutral or dissatisfied +22345,64113,Male,Loyal Customer,55,Business travel,Business,2288,4,4,4,4,4,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +22346,36521,Male,disloyal Customer,36,Business travel,Eco,1220,2,3,3,3,1,3,1,1,1,1,5,3,3,1,24,10.0,neutral or dissatisfied +22347,39995,Male,Loyal Customer,27,Business travel,Eco,508,4,2,2,2,4,4,4,4,4,1,1,1,1,4,0,5.0,satisfied +22348,94459,Female,Loyal Customer,52,Business travel,Business,192,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +22349,47068,Male,Loyal Customer,17,Personal Travel,Eco,639,2,4,2,2,5,2,4,5,5,2,4,5,5,5,0,4.0,neutral or dissatisfied +22350,89121,Female,disloyal Customer,27,Business travel,Eco,1087,2,2,2,3,4,2,4,4,2,3,1,3,3,4,1,14.0,neutral or dissatisfied +22351,42271,Female,Loyal Customer,72,Business travel,Business,550,4,1,4,4,3,2,1,2,2,2,2,4,2,5,41,49.0,satisfied +22352,68518,Female,disloyal Customer,24,Business travel,Eco,678,3,3,3,2,3,5,5,2,5,3,2,5,3,5,74,147.0,neutral or dissatisfied +22353,102283,Male,Loyal Customer,50,Business travel,Eco,407,1,2,2,2,1,1,1,1,3,1,1,4,2,1,76,75.0,neutral or dissatisfied +22354,47320,Female,disloyal Customer,27,Business travel,Eco,501,4,3,4,2,3,4,3,3,3,4,1,2,2,3,0,0.0,satisfied +22355,106134,Female,Loyal Customer,60,Business travel,Business,2801,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +22356,12772,Female,Loyal Customer,9,Personal Travel,Eco Plus,689,3,4,3,2,4,3,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +22357,35938,Female,disloyal Customer,24,Business travel,Eco Plus,881,1,4,1,3,5,1,5,5,3,1,3,2,2,5,2,0.0,neutral or dissatisfied +22358,109905,Female,Loyal Customer,30,Business travel,Business,1011,1,1,1,1,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +22359,82845,Male,Loyal Customer,48,Business travel,Business,1576,2,2,4,2,4,5,4,5,5,5,5,4,5,5,9,2.0,satisfied +22360,51092,Male,Loyal Customer,21,Personal Travel,Eco,373,2,3,1,1,3,1,3,3,4,4,5,2,3,3,0,0.0,neutral or dissatisfied +22361,39069,Male,Loyal Customer,25,Business travel,Business,784,1,3,3,3,1,1,1,1,4,3,3,2,4,1,3,12.0,neutral or dissatisfied +22362,112660,Male,disloyal Customer,33,Business travel,Business,605,4,4,4,2,2,4,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +22363,43520,Male,Loyal Customer,24,Business travel,Eco Plus,624,4,4,4,4,4,3,4,5,3,4,2,4,4,4,202,216.0,satisfied +22364,75926,Male,Loyal Customer,62,Business travel,Business,1835,2,1,1,1,1,2,2,3,3,3,2,2,3,1,10,28.0,neutral or dissatisfied +22365,81286,Female,Loyal Customer,15,Personal Travel,Eco,1020,1,3,1,4,4,1,4,4,1,4,4,1,4,4,0,0.0,neutral or dissatisfied +22366,78308,Female,Loyal Customer,55,Business travel,Eco Plus,1598,4,2,1,2,2,2,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +22367,24945,Male,Loyal Customer,23,Business travel,Eco,1747,0,4,0,3,2,0,2,2,2,2,5,3,2,2,71,45.0,satisfied +22368,77437,Male,Loyal Customer,43,Business travel,Eco Plus,588,2,4,4,4,2,2,2,2,4,3,3,2,4,2,4,0.0,neutral or dissatisfied +22369,99136,Male,Loyal Customer,69,Personal Travel,Eco,237,2,5,2,3,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +22370,640,Male,Loyal Customer,40,Business travel,Business,282,0,0,0,4,4,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +22371,22429,Female,Loyal Customer,30,Personal Travel,Eco,238,3,2,3,4,2,3,2,2,2,1,3,2,4,2,40,30.0,neutral or dissatisfied +22372,8389,Male,Loyal Customer,19,Personal Travel,Eco Plus,722,2,3,3,4,3,3,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +22373,78700,Female,Loyal Customer,39,Business travel,Business,432,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +22374,72917,Male,Loyal Customer,47,Business travel,Business,2278,5,5,5,5,2,5,4,5,5,5,5,4,5,3,11,5.0,satisfied +22375,91229,Female,Loyal Customer,69,Personal Travel,Eco,270,1,5,1,4,2,5,5,4,4,1,2,4,4,4,0,0.0,neutral or dissatisfied +22376,33354,Male,Loyal Customer,53,Business travel,Business,2614,2,2,2,2,3,5,2,4,4,4,4,2,4,1,0,0.0,satisfied +22377,54599,Male,disloyal Customer,60,Business travel,Business,965,2,1,1,3,4,2,1,4,2,1,3,1,2,4,15,8.0,neutral or dissatisfied +22378,16039,Female,disloyal Customer,47,Business travel,Eco Plus,780,2,2,2,3,4,2,4,4,4,2,2,5,3,4,3,4.0,neutral or dissatisfied +22379,97117,Female,Loyal Customer,24,Business travel,Eco,715,3,4,4,4,3,3,1,3,4,2,3,2,3,3,0,7.0,neutral or dissatisfied +22380,11353,Female,Loyal Customer,63,Personal Travel,Eco,247,2,5,2,1,2,5,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +22381,32489,Male,disloyal Customer,55,Business travel,Eco,163,3,2,3,2,3,3,3,3,1,3,1,1,2,3,0,0.0,neutral or dissatisfied +22382,77114,Male,disloyal Customer,72,Business travel,Business,1081,2,2,2,1,4,2,3,4,1,2,1,2,2,4,0,0.0,neutral or dissatisfied +22383,92357,Male,Loyal Customer,14,Personal Travel,Eco,2486,4,1,4,4,4,3,3,4,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +22384,69618,Female,disloyal Customer,42,Business travel,Business,2475,2,3,3,3,2,5,5,3,4,4,4,5,3,5,0,0.0,neutral or dissatisfied +22385,3391,Female,Loyal Customer,55,Business travel,Business,3471,2,4,4,4,3,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +22386,102712,Female,Loyal Customer,76,Business travel,Business,2295,3,5,5,5,1,4,3,3,3,3,3,3,3,3,22,15.0,neutral or dissatisfied +22387,80273,Female,Loyal Customer,52,Business travel,Business,746,3,3,3,3,2,5,5,5,5,5,5,5,5,5,24,23.0,satisfied +22388,75501,Female,Loyal Customer,61,Personal Travel,Eco Plus,2342,2,5,2,4,5,5,1,2,2,2,2,1,2,5,0,2.0,neutral or dissatisfied +22389,81626,Female,disloyal Customer,48,Business travel,Business,1142,4,3,3,1,2,4,2,2,5,3,5,4,4,2,0,0.0,satisfied +22390,79318,Female,disloyal Customer,34,Business travel,Business,2248,1,0,0,3,1,0,1,1,4,3,5,4,4,1,23,10.0,neutral or dissatisfied +22391,65542,Female,Loyal Customer,54,Business travel,Business,237,2,3,2,2,2,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +22392,22421,Male,Loyal Customer,42,Business travel,Business,3546,3,3,4,3,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +22393,55904,Female,Loyal Customer,27,Business travel,Business,2531,1,1,1,1,5,5,5,5,3,5,4,5,5,5,0,4.0,satisfied +22394,22927,Female,Loyal Customer,37,Personal Travel,Business,528,1,2,3,4,3,3,4,1,1,3,1,1,1,2,1,6.0,neutral or dissatisfied +22395,115922,Female,disloyal Customer,36,Business travel,Eco,308,4,0,4,4,1,4,1,1,3,4,4,5,1,1,0,0.0,neutral or dissatisfied +22396,114480,Female,Loyal Customer,41,Business travel,Business,417,1,1,1,1,2,4,4,4,4,4,4,5,4,4,49,53.0,satisfied +22397,89584,Female,disloyal Customer,42,Business travel,Business,1069,1,2,2,1,3,1,3,3,4,4,4,3,4,3,54,21.0,neutral or dissatisfied +22398,119072,Male,Loyal Customer,59,Business travel,Business,1107,1,1,1,1,3,5,4,5,5,5,5,3,5,4,2,0.0,satisfied +22399,116784,Female,Loyal Customer,19,Personal Travel,Eco Plus,296,4,4,4,3,3,4,4,3,3,2,5,3,4,3,0,0.0,satisfied +22400,121014,Male,Loyal Customer,18,Personal Travel,Eco,861,3,4,3,3,1,3,1,1,4,2,5,5,5,1,0,12.0,neutral or dissatisfied +22401,110598,Female,Loyal Customer,39,Personal Travel,Eco,643,2,4,2,4,2,2,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +22402,107134,Female,Loyal Customer,49,Business travel,Business,842,1,1,1,1,5,4,5,5,5,5,5,4,5,3,10,5.0,satisfied +22403,1685,Male,Loyal Customer,42,Business travel,Business,3281,4,4,4,4,2,4,5,5,5,5,5,5,5,5,46,48.0,satisfied +22404,73180,Female,Loyal Customer,46,Business travel,Eco,1258,3,5,5,5,2,1,1,2,2,3,2,1,2,1,14,0.0,neutral or dissatisfied +22405,39587,Male,Loyal Customer,53,Business travel,Eco,954,1,4,4,4,1,1,1,1,3,5,2,4,3,1,124,107.0,neutral or dissatisfied +22406,78727,Female,Loyal Customer,56,Business travel,Business,432,2,2,2,2,3,5,4,4,4,5,4,3,4,4,22,27.0,satisfied +22407,116109,Female,Loyal Customer,64,Personal Travel,Eco,333,5,5,2,1,2,5,4,3,3,2,3,4,3,3,0,0.0,satisfied +22408,97561,Female,disloyal Customer,23,Business travel,Business,337,0,0,0,1,5,0,4,5,5,3,5,5,4,5,3,0.0,satisfied +22409,71211,Female,disloyal Customer,40,Business travel,Business,733,3,3,3,1,4,3,5,4,3,4,4,3,4,4,60,55.0,neutral or dissatisfied +22410,68451,Male,disloyal Customer,35,Business travel,Business,1303,3,3,3,3,4,3,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +22411,75565,Female,Loyal Customer,54,Business travel,Business,337,4,4,4,4,4,4,4,5,5,4,4,4,4,4,119,133.0,satisfied +22412,41774,Female,Loyal Customer,39,Personal Travel,Eco,872,3,2,3,2,3,3,3,3,2,3,2,3,3,3,88,78.0,neutral or dissatisfied +22413,65285,Male,Loyal Customer,60,Personal Travel,Eco Plus,247,4,5,4,4,5,4,2,5,5,3,5,4,4,5,47,38.0,neutral or dissatisfied +22414,80902,Female,Loyal Customer,45,Personal Travel,Business,341,3,2,4,3,3,3,3,2,2,4,2,1,2,1,9,28.0,neutral or dissatisfied +22415,35393,Male,disloyal Customer,35,Business travel,Business,1074,3,3,3,2,1,3,5,1,3,5,2,2,2,1,0,0.0,neutral or dissatisfied +22416,111158,Female,Loyal Customer,63,Personal Travel,Eco,1173,4,4,4,5,3,4,4,2,2,4,2,2,2,2,0,0.0,neutral or dissatisfied +22417,9438,Female,Loyal Customer,41,Business travel,Business,1822,5,5,2,5,2,5,5,4,4,5,4,3,4,3,0,13.0,satisfied +22418,78060,Male,Loyal Customer,34,Personal Travel,Eco,214,2,2,2,3,2,2,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +22419,40343,Male,Loyal Customer,22,Business travel,Eco,1156,5,2,2,2,5,5,4,5,3,5,2,3,1,5,0,0.0,satisfied +22420,21723,Male,Loyal Customer,23,Business travel,Business,563,5,5,5,5,5,5,5,5,5,4,4,3,4,5,10,0.0,satisfied +22421,127950,Male,Loyal Customer,47,Business travel,Business,1999,1,1,1,1,5,4,4,4,4,4,4,3,4,5,8,0.0,satisfied +22422,79812,Female,Loyal Customer,50,Business travel,Business,1096,5,5,5,5,4,4,4,4,4,4,4,4,4,5,29,2.0,satisfied +22423,47736,Female,Loyal Customer,52,Personal Travel,Business,817,4,0,4,4,2,2,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +22424,41279,Female,Loyal Customer,23,Business travel,Business,3177,4,4,5,4,5,5,5,5,3,3,4,4,2,5,0,0.0,satisfied +22425,33146,Female,Loyal Customer,10,Personal Travel,Eco,163,1,4,0,2,5,0,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +22426,18641,Female,Loyal Customer,43,Personal Travel,Eco,383,2,4,2,2,2,5,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +22427,92038,Male,disloyal Customer,34,Business travel,Business,1589,2,2,2,3,1,2,1,1,4,2,3,5,5,1,0,0.0,neutral or dissatisfied +22428,32339,Female,Loyal Customer,38,Business travel,Eco,84,5,2,2,2,5,5,5,5,3,5,2,2,2,5,0,0.0,satisfied +22429,78399,Male,Loyal Customer,68,Personal Travel,Eco Plus,980,2,5,2,1,1,2,1,1,3,3,3,2,1,1,0,29.0,neutral or dissatisfied +22430,90231,Female,Loyal Customer,29,Personal Travel,Eco Plus,1086,1,4,1,4,2,1,2,2,4,4,4,3,5,2,2,0.0,neutral or dissatisfied +22431,76812,Female,Loyal Customer,67,Personal Travel,Eco,689,1,5,2,2,5,4,5,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +22432,68164,Female,Loyal Customer,37,Business travel,Business,1837,2,2,2,2,2,5,4,4,4,4,4,3,4,4,5,0.0,satisfied +22433,67827,Female,Loyal Customer,79,Business travel,Business,2727,5,1,1,1,4,4,4,5,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +22434,49600,Female,Loyal Customer,59,Business travel,Eco,262,5,5,4,4,5,5,5,5,5,5,5,1,5,5,12,14.0,satisfied +22435,102757,Male,Loyal Customer,63,Personal Travel,Eco Plus,365,3,5,3,4,2,3,2,2,4,5,5,5,5,2,69,55.0,neutral or dissatisfied +22436,35948,Male,disloyal Customer,27,Business travel,Business,231,2,2,2,3,3,2,4,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +22437,68802,Male,Loyal Customer,32,Personal Travel,Eco,861,4,4,4,4,4,4,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +22438,27263,Female,disloyal Customer,26,Business travel,Business,671,1,4,1,3,5,1,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +22439,112111,Male,Loyal Customer,35,Business travel,Business,3299,2,2,2,2,2,5,5,5,5,5,5,3,5,3,9,4.0,satisfied +22440,109356,Male,Loyal Customer,54,Business travel,Business,1544,5,5,5,5,5,4,5,4,4,4,4,4,4,5,36,19.0,satisfied +22441,66161,Male,Loyal Customer,41,Business travel,Business,2071,1,1,1,1,5,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +22442,37478,Female,Loyal Customer,34,Business travel,Business,2099,5,5,5,5,1,2,1,5,5,4,5,3,5,3,0,0.0,satisfied +22443,86088,Male,disloyal Customer,40,Business travel,Business,306,4,4,4,2,2,4,2,2,3,3,4,4,5,2,0,0.0,satisfied +22444,59521,Female,Loyal Customer,30,Personal Travel,Business,854,2,1,2,3,5,2,5,5,1,4,3,2,3,5,15,14.0,neutral or dissatisfied +22445,25959,Female,Loyal Customer,40,Business travel,Eco,946,5,5,5,5,5,4,5,5,2,5,3,4,1,5,3,0.0,satisfied +22446,112813,Male,disloyal Customer,30,Business travel,Business,715,3,3,3,5,5,3,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +22447,101861,Female,Loyal Customer,26,Personal Travel,Eco,519,4,2,3,3,4,3,4,4,2,2,3,4,2,4,19,14.0,neutral or dissatisfied +22448,125846,Male,disloyal Customer,14,Business travel,Eco,920,3,3,3,3,1,3,1,1,1,1,3,1,3,1,53,54.0,neutral or dissatisfied +22449,30012,Female,Loyal Customer,41,Business travel,Business,160,2,3,3,3,1,3,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +22450,117376,Female,Loyal Customer,51,Business travel,Business,1778,1,1,4,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +22451,9388,Male,Loyal Customer,15,Personal Travel,Eco,401,3,3,3,3,5,3,5,5,1,1,3,3,3,5,72,67.0,neutral or dissatisfied +22452,75738,Male,Loyal Customer,56,Business travel,Eco,868,2,4,4,4,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +22453,75769,Male,Loyal Customer,8,Personal Travel,Eco,813,3,2,3,4,5,3,5,5,1,1,4,4,3,5,0,0.0,neutral or dissatisfied +22454,48225,Female,Loyal Customer,36,Personal Travel,Eco,259,4,4,0,3,5,0,5,5,3,5,5,5,3,5,0,0.0,satisfied +22455,55604,Male,Loyal Customer,64,Business travel,Business,404,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,2.0,satisfied +22456,13442,Female,disloyal Customer,38,Business travel,Eco,491,2,4,1,4,3,1,3,3,1,3,3,3,3,3,17,21.0,neutral or dissatisfied +22457,15875,Male,disloyal Customer,23,Business travel,Eco,296,3,0,3,4,5,3,5,5,2,1,5,2,4,5,0,0.0,neutral or dissatisfied +22458,128818,Male,Loyal Customer,32,Business travel,Business,2586,1,1,1,1,4,4,4,5,2,5,4,4,5,4,0,0.0,satisfied +22459,29101,Female,Loyal Customer,48,Personal Travel,Eco,697,2,4,2,3,2,4,3,4,4,2,4,3,4,2,0,10.0,neutral or dissatisfied +22460,84775,Female,disloyal Customer,26,Business travel,Business,516,3,4,3,3,2,3,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +22461,13738,Female,Loyal Customer,51,Business travel,Eco,401,5,1,1,1,5,5,5,4,4,5,4,2,4,1,117,97.0,satisfied +22462,95070,Female,Loyal Customer,61,Personal Travel,Eco,341,2,4,2,4,4,5,4,4,4,2,4,5,4,5,0,17.0,neutral or dissatisfied +22463,79580,Male,disloyal Customer,21,Business travel,Eco,762,3,3,3,3,5,3,5,5,2,1,3,2,3,5,2,0.0,neutral or dissatisfied +22464,66750,Male,Loyal Customer,31,Personal Travel,Eco,802,3,3,2,4,2,2,2,2,1,2,2,5,5,2,0,3.0,neutral or dissatisfied +22465,102216,Male,Loyal Customer,47,Business travel,Business,3830,4,4,4,4,5,5,4,2,2,2,2,3,2,3,2,0.0,satisfied +22466,108369,Female,Loyal Customer,33,Personal Travel,Eco,1750,2,5,2,3,5,2,5,5,3,4,1,1,4,5,18,19.0,neutral or dissatisfied +22467,37211,Male,Loyal Customer,29,Personal Travel,Eco Plus,680,3,4,3,1,1,3,1,1,3,4,4,3,5,1,21,24.0,neutral or dissatisfied +22468,93087,Female,Loyal Customer,26,Business travel,Eco,860,4,1,1,1,4,4,3,4,4,5,3,4,2,4,15,10.0,satisfied +22469,15572,Male,Loyal Customer,56,Business travel,Business,229,1,1,1,1,5,3,4,5,5,5,5,1,5,2,0,0.0,satisfied +22470,123874,Female,Loyal Customer,51,Business travel,Business,541,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +22471,107763,Male,Loyal Customer,54,Personal Travel,Eco,405,3,5,3,5,2,3,2,2,5,3,4,3,4,2,62,34.0,neutral or dissatisfied +22472,41568,Male,Loyal Customer,59,Personal Travel,Eco,1428,5,4,5,2,4,5,1,4,3,2,5,5,4,4,0,0.0,satisfied +22473,102858,Male,Loyal Customer,39,Business travel,Business,1884,3,3,3,3,5,5,5,4,4,4,4,3,4,5,14,33.0,satisfied +22474,44914,Male,Loyal Customer,40,Business travel,Business,3410,2,2,2,2,5,1,5,5,5,5,5,3,5,3,0,0.0,satisfied +22475,83999,Male,Loyal Customer,10,Personal Travel,Eco,321,2,2,2,4,5,2,5,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +22476,85616,Female,Loyal Customer,31,Personal Travel,Eco,153,3,4,3,1,3,1,1,5,5,4,4,1,3,1,183,165.0,neutral or dissatisfied +22477,128112,Male,Loyal Customer,58,Business travel,Business,1587,2,2,4,2,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +22478,4850,Female,disloyal Customer,37,Business travel,Eco,408,2,3,2,3,4,2,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +22479,37456,Female,Loyal Customer,50,Business travel,Eco,1069,2,4,4,4,2,3,4,2,2,2,2,3,2,3,19,19.0,neutral or dissatisfied +22480,84289,Female,Loyal Customer,68,Personal Travel,Eco Plus,334,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,24.0,neutral or dissatisfied +22481,94498,Female,Loyal Customer,55,Business travel,Business,2518,2,2,2,2,5,5,5,4,3,5,4,5,3,5,179,172.0,satisfied +22482,128841,Female,Loyal Customer,25,Personal Travel,Eco,2586,5,4,5,4,5,3,3,3,4,3,5,3,4,3,0,12.0,satisfied +22483,2155,Female,Loyal Customer,30,Business travel,Business,2859,3,3,3,3,5,5,5,5,3,4,5,3,4,5,16,16.0,satisfied +22484,43456,Female,disloyal Customer,22,Business travel,Eco,752,3,3,3,1,1,3,1,1,2,5,1,4,2,1,0,0.0,neutral or dissatisfied +22485,109753,Male,Loyal Customer,56,Business travel,Business,2303,1,1,1,1,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +22486,121647,Male,Loyal Customer,50,Personal Travel,Eco Plus,936,1,3,1,2,2,1,2,2,3,3,1,5,3,2,35,17.0,neutral or dissatisfied +22487,23430,Female,disloyal Customer,20,Business travel,Eco,488,5,0,5,1,3,0,3,3,3,5,5,3,4,3,5,2.0,satisfied +22488,66132,Male,Loyal Customer,64,Personal Travel,Eco,583,1,1,1,2,2,1,2,2,4,4,2,3,2,2,0,0.0,neutral or dissatisfied +22489,38782,Female,disloyal Customer,26,Business travel,Eco,353,3,5,3,3,2,3,2,2,4,1,1,3,5,2,0,0.0,neutral or dissatisfied +22490,27984,Female,Loyal Customer,20,Personal Travel,Eco,2350,2,4,2,4,5,2,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +22491,55739,Female,Loyal Customer,62,Personal Travel,Eco,2026,1,4,1,2,3,3,4,2,2,1,2,4,2,4,33,25.0,neutral or dissatisfied +22492,12197,Male,Loyal Customer,38,Business travel,Business,201,0,4,0,1,3,4,5,5,5,5,5,4,5,4,0,8.0,satisfied +22493,38364,Male,Loyal Customer,11,Personal Travel,Eco,1180,4,4,4,4,3,4,3,3,3,3,5,4,5,3,22,42.0,neutral or dissatisfied +22494,48136,Male,Loyal Customer,50,Business travel,Eco,236,4,3,3,3,4,4,4,4,2,1,2,5,2,4,0,0.0,satisfied +22495,5235,Female,disloyal Customer,39,Business travel,Business,351,3,3,3,3,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +22496,35547,Female,Loyal Customer,30,Personal Travel,Eco,1032,2,5,2,2,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +22497,48944,Male,Loyal Customer,49,Business travel,Eco,209,4,5,5,5,4,4,4,4,2,3,1,1,5,4,0,2.0,satisfied +22498,57433,Female,Loyal Customer,52,Personal Travel,Eco,533,2,4,3,3,5,5,4,5,5,3,5,5,5,3,6,1.0,neutral or dissatisfied +22499,53189,Male,disloyal Customer,24,Business travel,Eco,589,3,3,4,4,4,4,4,4,3,1,2,4,5,4,4,0.0,neutral or dissatisfied +22500,79886,Male,Loyal Customer,54,Business travel,Business,1735,4,4,1,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22501,16386,Female,Loyal Customer,45,Business travel,Business,463,2,2,2,2,1,4,3,5,5,5,5,3,5,1,0,4.0,satisfied +22502,92279,Male,Loyal Customer,62,Personal Travel,Eco,2036,2,4,2,3,1,2,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +22503,74385,Female,Loyal Customer,53,Business travel,Business,1464,4,4,4,4,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +22504,33606,Female,Loyal Customer,52,Business travel,Eco,399,4,4,4,4,1,1,4,4,4,4,4,4,4,5,0,0.0,satisfied +22505,102795,Male,Loyal Customer,51,Personal Travel,Eco Plus,1099,4,0,4,4,3,4,2,3,3,2,3,1,4,3,2,20.0,neutral or dissatisfied +22506,40208,Female,disloyal Customer,27,Business travel,Eco,402,1,0,1,5,4,1,4,4,2,5,1,2,1,4,0,5.0,neutral or dissatisfied +22507,80423,Female,disloyal Customer,40,Business travel,Business,2248,3,3,3,2,4,3,5,4,3,3,3,5,4,4,0,0.0,neutral or dissatisfied +22508,55171,Female,Loyal Customer,17,Personal Travel,Eco,1608,3,5,3,2,4,3,3,4,4,4,5,1,3,4,34,38.0,neutral or dissatisfied +22509,8017,Female,disloyal Customer,37,Business travel,Business,335,1,1,1,4,4,1,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +22510,27964,Female,Loyal Customer,52,Personal Travel,Eco,1874,3,4,3,4,3,3,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +22511,54091,Male,Loyal Customer,15,Personal Travel,Eco,1416,3,2,3,4,5,3,5,5,3,4,2,3,3,5,0,0.0,neutral or dissatisfied +22512,95431,Male,Loyal Customer,52,Business travel,Business,3309,5,5,5,5,2,4,4,5,5,5,5,3,5,3,11,5.0,satisfied +22513,24017,Female,disloyal Customer,26,Business travel,Eco,427,1,1,1,3,5,1,4,5,3,1,3,4,3,5,1,0.0,neutral or dissatisfied +22514,68654,Female,Loyal Customer,56,Business travel,Business,2862,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +22515,45900,Female,disloyal Customer,28,Business travel,Eco,775,2,2,2,4,2,2,2,1,3,4,4,2,2,2,355,391.0,neutral or dissatisfied +22516,96863,Female,Loyal Customer,61,Business travel,Business,705,3,3,3,3,5,2,1,5,5,5,5,2,5,1,5,0.0,satisfied +22517,59877,Male,Loyal Customer,45,Business travel,Business,1798,5,5,5,5,5,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +22518,27050,Female,Loyal Customer,25,Business travel,Eco,1709,3,3,3,3,3,3,3,3,2,4,4,4,4,3,8,9.0,neutral or dissatisfied +22519,67146,Female,Loyal Customer,37,Business travel,Business,3490,3,3,3,3,5,3,4,4,4,4,4,1,4,5,7,0.0,satisfied +22520,37827,Female,Loyal Customer,26,Personal Travel,Business,997,1,4,1,1,2,1,2,2,5,5,5,3,4,2,33,18.0,neutral or dissatisfied +22521,37689,Male,Loyal Customer,41,Personal Travel,Eco,1076,2,4,2,2,5,2,5,5,5,2,5,3,5,5,23,0.0,neutral or dissatisfied +22522,37367,Female,Loyal Customer,32,Business travel,Business,3831,1,1,1,1,5,5,5,5,3,5,5,3,4,5,97,94.0,satisfied +22523,82078,Female,Loyal Customer,39,Business travel,Business,2263,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +22524,16603,Female,disloyal Customer,43,Business travel,Eco,1008,4,4,4,5,4,4,4,4,3,1,3,4,2,4,51,46.0,satisfied +22525,125036,Female,Loyal Customer,40,Business travel,Business,2300,2,1,1,1,2,2,2,1,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +22526,129682,Male,Loyal Customer,38,Business travel,Business,3585,3,2,3,3,5,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +22527,72402,Male,Loyal Customer,46,Business travel,Business,1548,1,3,1,1,2,4,4,5,5,4,5,3,5,4,74,85.0,satisfied +22528,88120,Male,Loyal Customer,64,Business travel,Business,406,1,1,1,1,3,4,4,5,5,5,5,3,5,3,23,17.0,satisfied +22529,54871,Male,Loyal Customer,43,Business travel,Business,241,3,3,3,3,2,2,2,5,5,5,5,1,5,3,0,19.0,satisfied +22530,33725,Female,Loyal Customer,47,Personal Travel,Eco,667,2,4,1,2,3,4,4,2,2,1,2,5,2,3,0,7.0,neutral or dissatisfied +22531,48746,Male,Loyal Customer,36,Business travel,Business,3499,3,1,1,1,1,4,3,1,1,1,3,4,1,2,119,126.0,neutral or dissatisfied +22532,115733,Female,Loyal Customer,45,Business travel,Business,3328,3,5,5,5,3,3,3,1,1,3,3,3,4,3,160,146.0,neutral or dissatisfied +22533,98986,Female,Loyal Customer,33,Personal Travel,Eco,569,2,4,2,3,5,2,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +22534,97068,Female,Loyal Customer,51,Business travel,Business,715,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +22535,3406,Female,Loyal Customer,18,Personal Travel,Eco,315,4,5,4,4,2,4,2,2,1,3,2,2,4,2,0,22.0,satisfied +22536,19946,Female,Loyal Customer,52,Personal Travel,Eco,296,2,5,2,4,2,3,3,5,4,5,5,3,3,3,211,213.0,neutral or dissatisfied +22537,74719,Male,Loyal Customer,69,Personal Travel,Eco,1205,4,4,4,4,3,4,3,3,2,1,4,3,4,3,8,2.0,neutral or dissatisfied +22538,60555,Female,Loyal Customer,42,Business travel,Business,2675,4,4,4,4,3,4,4,5,5,5,5,3,5,3,6,23.0,satisfied +22539,45864,Male,disloyal Customer,38,Business travel,Business,163,4,4,4,3,5,4,4,5,4,5,5,4,4,5,17,11.0,neutral or dissatisfied +22540,7073,Male,Loyal Customer,48,Business travel,Business,273,0,0,0,5,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +22541,4206,Female,Loyal Customer,8,Business travel,Business,888,4,1,1,1,4,4,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +22542,102122,Female,Loyal Customer,27,Business travel,Business,2501,4,4,4,4,5,5,5,5,4,2,4,5,5,5,14,3.0,satisfied +22543,29933,Male,Loyal Customer,52,Business travel,Business,183,2,1,1,1,3,4,4,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +22544,110089,Female,Loyal Customer,22,Business travel,Business,1056,4,4,4,4,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +22545,95747,Male,Loyal Customer,44,Business travel,Eco,181,3,3,3,3,3,3,3,3,4,3,3,1,3,3,1,0.0,neutral or dissatisfied +22546,44938,Male,Loyal Customer,51,Business travel,Business,334,1,1,1,1,5,5,3,4,4,4,4,1,4,1,16,13.0,satisfied +22547,58964,Female,Loyal Customer,60,Business travel,Business,1846,3,3,3,3,5,5,5,5,5,5,5,3,5,4,22,22.0,satisfied +22548,107231,Female,disloyal Customer,9,Business travel,Eco,583,1,3,1,4,3,1,2,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +22549,123978,Female,Loyal Customer,56,Business travel,Business,184,2,2,2,2,5,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +22550,66867,Male,Loyal Customer,52,Business travel,Business,2390,3,3,3,3,2,4,5,4,4,4,4,5,4,4,46,45.0,satisfied +22551,113831,Female,Loyal Customer,60,Personal Travel,Eco Plus,223,1,3,0,3,4,3,3,3,3,0,3,1,3,4,31,46.0,neutral or dissatisfied +22552,112285,Female,Loyal Customer,38,Personal Travel,Eco,1447,3,1,3,3,5,3,5,5,2,2,3,3,4,5,7,0.0,neutral or dissatisfied +22553,114986,Female,Loyal Customer,36,Business travel,Business,2512,3,3,5,3,2,5,5,3,3,4,3,4,3,3,11,0.0,satisfied +22554,32124,Female,Loyal Customer,48,Business travel,Business,84,0,4,0,4,2,3,5,4,4,5,5,3,4,5,0,0.0,satisfied +22555,93946,Female,Loyal Customer,15,Personal Travel,Eco,507,2,4,2,3,4,2,4,4,3,2,4,3,5,4,6,0.0,neutral or dissatisfied +22556,11234,Male,Loyal Customer,21,Personal Travel,Eco,301,4,4,4,3,3,4,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +22557,22015,Male,Loyal Customer,32,Personal Travel,Eco,448,1,1,1,3,4,1,4,4,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +22558,45671,Male,Loyal Customer,42,Business travel,Business,896,3,3,5,3,2,4,5,4,4,4,4,3,4,5,0,3.0,satisfied +22559,125747,Male,Loyal Customer,40,Personal Travel,Business,1013,3,1,3,4,1,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +22560,118506,Female,Loyal Customer,35,Business travel,Business,3572,4,4,4,4,4,4,4,3,2,5,4,4,3,4,154,139.0,satisfied +22561,108813,Male,Loyal Customer,40,Business travel,Business,2009,5,5,5,5,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +22562,75105,Female,Loyal Customer,65,Personal Travel,Business,1726,4,5,4,1,3,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +22563,6938,Female,Loyal Customer,54,Business travel,Business,588,3,3,3,3,4,5,5,5,5,5,5,4,5,4,1,14.0,satisfied +22564,33542,Female,Loyal Customer,51,Personal Travel,Business,474,3,3,3,4,4,2,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +22565,109584,Male,Loyal Customer,50,Business travel,Business,992,2,2,2,2,3,5,4,5,5,5,5,4,5,5,16,22.0,satisfied +22566,101282,Male,disloyal Customer,18,Business travel,Business,763,5,0,5,2,5,5,5,5,3,3,5,5,5,5,17,0.0,satisfied +22567,113779,Male,Loyal Customer,55,Business travel,Business,2752,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +22568,109301,Male,Loyal Customer,55,Business travel,Business,2235,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +22569,73901,Male,Loyal Customer,49,Business travel,Business,2342,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +22570,101892,Male,disloyal Customer,22,Business travel,Business,1110,4,0,4,3,4,1,5,5,5,5,4,5,3,5,293,265.0,satisfied +22571,38484,Female,Loyal Customer,56,Business travel,Business,2465,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +22572,108002,Female,Loyal Customer,16,Personal Travel,Eco,271,4,2,3,4,3,3,2,3,2,4,4,2,3,3,77,120.0,neutral or dissatisfied +22573,91764,Male,Loyal Customer,15,Business travel,Eco,626,4,2,2,2,4,4,3,4,1,2,4,4,4,4,0,0.0,neutral or dissatisfied +22574,83493,Male,Loyal Customer,54,Business travel,Business,2306,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,2.0,satisfied +22575,8252,Male,Loyal Customer,8,Personal Travel,Eco,402,5,4,5,1,2,5,2,2,5,2,4,3,4,2,0,0.0,satisfied +22576,42253,Male,Loyal Customer,33,Business travel,Business,1776,2,2,2,2,4,4,4,4,1,3,3,1,4,4,0,0.0,satisfied +22577,64957,Female,Loyal Customer,41,Business travel,Business,190,2,3,3,3,2,4,4,1,1,1,2,1,1,1,0,0.0,neutral or dissatisfied +22578,8330,Male,Loyal Customer,32,Business travel,Business,661,3,3,3,3,5,5,5,5,3,3,4,5,4,5,8,6.0,satisfied +22579,44032,Male,disloyal Customer,40,Business travel,Business,287,3,2,2,3,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +22580,8858,Female,Loyal Customer,53,Business travel,Business,3451,5,5,5,5,4,4,5,4,4,4,4,4,4,3,9,16.0,satisfied +22581,47764,Female,disloyal Customer,42,Business travel,Eco,329,3,4,3,2,1,3,1,1,5,4,2,5,2,1,0,0.0,neutral or dissatisfied +22582,125602,Female,Loyal Customer,50,Personal Travel,Eco,1587,3,4,3,1,5,3,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +22583,71106,Male,disloyal Customer,43,Business travel,Business,2072,3,3,3,4,2,3,2,2,3,4,4,5,5,2,36,27.0,neutral or dissatisfied +22584,21668,Male,Loyal Customer,9,Business travel,Business,708,1,1,1,1,1,1,1,1,2,3,4,1,3,1,20,14.0,neutral or dissatisfied +22585,100528,Female,Loyal Customer,19,Personal Travel,Eco,759,3,5,3,2,1,3,1,1,3,2,5,4,4,1,2,0.0,neutral or dissatisfied +22586,118136,Male,Loyal Customer,62,Personal Travel,Eco,1488,3,5,3,4,5,3,5,5,1,1,5,1,2,5,0,0.0,neutral or dissatisfied +22587,90308,Female,Loyal Customer,50,Personal Travel,Eco,932,2,5,2,2,3,4,4,2,2,2,2,5,2,4,82,71.0,neutral or dissatisfied +22588,20927,Female,Loyal Customer,22,Business travel,Business,2513,4,4,1,4,5,5,5,5,3,2,4,2,5,5,2,0.0,satisfied +22589,35473,Male,Loyal Customer,14,Personal Travel,Eco,1011,3,1,2,3,1,2,1,1,3,3,3,3,2,1,15,57.0,neutral or dissatisfied +22590,45749,Male,disloyal Customer,27,Business travel,Eco,391,1,0,0,5,4,0,4,4,5,5,2,2,2,4,0,2.0,neutral or dissatisfied +22591,54660,Male,disloyal Customer,12,Business travel,Eco,861,3,3,3,3,1,3,1,1,2,5,3,4,4,1,0,0.0,neutral or dissatisfied +22592,20783,Female,Loyal Customer,63,Business travel,Business,357,5,5,5,5,4,1,4,5,5,5,5,2,5,1,0,0.0,satisfied +22593,66827,Female,Loyal Customer,58,Business travel,Business,731,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +22594,92855,Male,Loyal Customer,22,Business travel,Business,2125,1,1,1,1,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +22595,88273,Female,disloyal Customer,47,Business travel,Business,444,4,4,4,4,1,4,1,1,4,3,4,5,5,1,7,0.0,neutral or dissatisfied +22596,126109,Male,Loyal Customer,60,Business travel,Business,3374,3,5,2,2,2,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +22597,128285,Male,Loyal Customer,60,Business travel,Business,1668,1,1,1,1,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +22598,11744,Male,disloyal Customer,16,Business travel,Eco,429,1,2,2,3,2,2,2,2,3,3,3,4,3,2,13,13.0,neutral or dissatisfied +22599,105359,Female,Loyal Customer,31,Personal Travel,Eco,528,2,4,4,2,4,4,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +22600,63289,Female,Loyal Customer,43,Business travel,Business,3518,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +22601,125137,Female,Loyal Customer,50,Personal Travel,Eco,361,4,5,4,3,4,4,4,1,1,4,1,3,1,3,0,12.0,neutral or dissatisfied +22602,44726,Male,Loyal Customer,25,Personal Travel,Eco,67,4,4,4,1,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +22603,112687,Male,Loyal Customer,47,Business travel,Business,3741,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,1.0,satisfied +22604,15992,Female,Loyal Customer,45,Business travel,Business,780,4,3,3,3,1,3,2,4,4,4,4,1,4,2,0,12.0,neutral or dissatisfied +22605,96139,Male,Loyal Customer,47,Personal Travel,Business,460,2,3,2,4,5,2,1,3,3,2,3,1,3,2,30,29.0,neutral or dissatisfied +22606,23011,Female,Loyal Customer,50,Business travel,Eco Plus,489,4,4,4,4,5,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +22607,64658,Male,disloyal Customer,65,Business travel,Business,247,2,2,2,5,5,2,5,5,3,4,4,5,4,5,20,10.0,satisfied +22608,78246,Male,Loyal Customer,18,Personal Travel,Eco Plus,259,2,2,2,4,5,2,5,5,4,2,4,2,4,5,0,5.0,neutral or dissatisfied +22609,78139,Female,Loyal Customer,43,Business travel,Business,259,2,2,2,2,5,4,4,5,5,5,5,4,5,4,6,1.0,satisfied +22610,26652,Male,Loyal Customer,54,Business travel,Eco,581,4,2,2,2,4,4,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +22611,73641,Female,Loyal Customer,35,Business travel,Business,2037,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +22612,41538,Female,disloyal Customer,21,Business travel,Eco,1235,2,1,1,4,1,1,1,1,1,5,3,4,4,1,8,20.0,neutral or dissatisfied +22613,49651,Male,disloyal Customer,36,Business travel,Eco,304,2,0,1,1,5,1,5,5,1,5,2,4,3,5,42,47.0,neutral or dissatisfied +22614,74435,Female,Loyal Customer,14,Business travel,Business,2521,3,3,3,3,5,4,5,5,5,2,4,3,5,5,0,0.0,satisfied +22615,26796,Female,Loyal Customer,22,Business travel,Eco,1947,5,5,5,5,5,5,5,5,5,2,3,4,4,5,25,0.0,satisfied +22616,64260,Male,Loyal Customer,32,Business travel,Business,1660,5,5,2,5,4,4,4,4,5,3,3,3,4,4,1,4.0,satisfied +22617,121017,Male,Loyal Customer,38,Personal Travel,Eco,951,4,5,4,5,2,4,2,2,4,3,5,5,4,2,27,13.0,neutral or dissatisfied +22618,87498,Male,Loyal Customer,25,Business travel,Business,2822,2,1,4,1,2,2,2,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +22619,16021,Male,Loyal Customer,59,Personal Travel,Eco,722,3,4,3,4,3,3,3,3,2,3,2,3,5,3,0,0.0,neutral or dissatisfied +22620,43082,Male,Loyal Customer,55,Personal Travel,Eco,391,3,5,3,5,5,3,5,5,2,5,1,5,4,5,0,0.0,neutral or dissatisfied +22621,17684,Female,Loyal Customer,39,Personal Travel,Eco,1039,1,5,1,2,2,1,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +22622,90362,Male,Loyal Customer,30,Business travel,Business,1884,5,5,5,5,4,4,4,4,3,3,4,5,5,4,0,0.0,satisfied +22623,14659,Male,Loyal Customer,60,Personal Travel,Eco,112,3,5,3,2,3,2,2,3,1,3,4,2,5,2,154,176.0,neutral or dissatisfied +22624,13915,Female,Loyal Customer,48,Business travel,Business,192,2,2,2,2,2,2,2,4,4,4,5,2,4,2,0,0.0,satisfied +22625,44571,Male,Loyal Customer,37,Business travel,Eco,84,2,5,4,5,2,1,2,2,3,2,3,1,3,2,2,0.0,neutral or dissatisfied +22626,115902,Male,Loyal Customer,48,Business travel,Eco,446,3,1,1,1,3,3,3,3,5,4,4,3,3,3,156,146.0,neutral or dissatisfied +22627,32449,Female,Loyal Customer,76,Business travel,Business,3902,3,1,1,1,3,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +22628,123581,Female,disloyal Customer,37,Personal Travel,Eco,1773,1,1,1,4,2,1,2,2,2,5,3,3,3,2,5,4.0,neutral or dissatisfied +22629,71894,Female,Loyal Customer,38,Personal Travel,Eco,1744,1,3,1,4,4,1,4,4,1,1,4,2,4,4,0,3.0,neutral or dissatisfied +22630,107306,Male,Loyal Customer,18,Personal Travel,Eco,283,3,4,3,4,5,3,5,5,5,4,4,4,4,5,86,82.0,neutral or dissatisfied +22631,45518,Female,Loyal Customer,29,Business travel,Business,2377,3,3,3,3,3,3,3,3,3,3,2,1,5,3,6,5.0,satisfied +22632,73106,Female,Loyal Customer,45,Business travel,Business,2174,3,3,3,3,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +22633,12196,Male,Loyal Customer,40,Business travel,Business,127,0,5,1,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +22634,85219,Female,disloyal Customer,27,Business travel,Eco,696,1,1,1,3,1,1,1,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +22635,79086,Male,Loyal Customer,58,Personal Travel,Eco,306,1,2,1,4,1,1,1,1,4,3,3,2,4,1,3,7.0,neutral or dissatisfied +22636,125501,Female,Loyal Customer,72,Business travel,Business,3579,2,1,5,5,2,2,2,2,2,2,2,1,2,4,16,16.0,neutral or dissatisfied +22637,53052,Male,Loyal Customer,59,Personal Travel,Eco,1190,2,5,1,1,5,1,4,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +22638,33808,Male,disloyal Customer,15,Business travel,Eco,1322,2,2,2,1,3,2,3,3,3,5,1,1,4,3,27,10.0,neutral or dissatisfied +22639,15624,Male,Loyal Customer,21,Personal Travel,Eco,288,2,5,2,1,4,2,4,4,5,5,5,3,4,4,1,0.0,neutral or dissatisfied +22640,70690,Female,Loyal Customer,19,Personal Travel,Eco,447,1,5,1,2,5,1,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +22641,120180,Male,Loyal Customer,43,Business travel,Business,1927,3,1,1,1,2,1,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +22642,94990,Male,Loyal Customer,35,Personal Travel,Eco,248,5,5,5,4,2,5,2,2,3,5,4,4,5,2,2,3.0,satisfied +22643,96624,Female,Loyal Customer,44,Business travel,Business,2064,2,2,2,2,2,5,4,4,4,4,4,5,4,3,51,42.0,satisfied +22644,65704,Female,Loyal Customer,34,Business travel,Business,3994,5,5,5,5,5,4,4,3,3,3,3,4,3,4,4,0.0,satisfied +22645,36164,Male,Loyal Customer,22,Business travel,Business,1674,5,5,5,5,5,5,5,5,1,2,4,5,4,5,1,29.0,satisfied +22646,85012,Male,Loyal Customer,22,Business travel,Business,1590,2,1,5,5,2,2,2,2,4,4,3,1,4,2,1,3.0,neutral or dissatisfied +22647,39008,Male,Loyal Customer,39,Business travel,Business,3875,1,1,1,1,3,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +22648,120686,Female,Loyal Customer,53,Personal Travel,Eco,280,3,4,3,5,4,4,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +22649,99004,Male,Loyal Customer,47,Business travel,Eco Plus,569,2,1,1,1,2,2,2,2,2,5,3,2,3,2,20,28.0,neutral or dissatisfied +22650,111125,Male,Loyal Customer,20,Business travel,Business,1111,2,1,1,1,2,2,2,2,3,3,3,3,4,2,89,71.0,neutral or dissatisfied +22651,23021,Male,Loyal Customer,28,Personal Travel,Business,1025,2,5,3,1,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +22652,45036,Female,Loyal Customer,39,Personal Travel,Eco,837,2,4,1,4,5,1,5,5,1,3,3,4,3,5,3,0.0,neutral or dissatisfied +22653,30325,Female,Loyal Customer,66,Business travel,Business,3740,1,1,1,1,4,5,3,5,5,5,5,5,5,5,0,0.0,satisfied +22654,52997,Female,Loyal Customer,41,Business travel,Business,2691,5,5,5,5,2,4,4,5,5,5,5,2,5,1,13,0.0,satisfied +22655,34083,Male,Loyal Customer,14,Personal Travel,Eco Plus,1674,3,3,4,3,2,4,2,2,4,3,4,3,3,2,56,53.0,neutral or dissatisfied +22656,80588,Male,Loyal Customer,54,Personal Travel,Eco,1747,1,2,1,4,5,1,5,5,2,3,4,3,4,5,2,0.0,neutral or dissatisfied +22657,10732,Male,Loyal Customer,33,Business travel,Eco,158,2,4,4,4,2,2,2,2,4,3,4,2,4,2,92,84.0,neutral or dissatisfied +22658,40630,Male,Loyal Customer,20,Personal Travel,Eco,391,4,3,4,4,5,4,5,5,4,1,2,2,5,5,30,2.0,satisfied +22659,51910,Male,Loyal Customer,34,Personal Travel,Eco,601,3,4,3,3,3,3,3,3,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +22660,22021,Male,Loyal Customer,19,Business travel,Eco Plus,551,4,5,5,5,4,4,3,4,2,1,1,1,5,4,0,0.0,satisfied +22661,3239,Female,Loyal Customer,39,Business travel,Business,3115,2,2,2,2,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +22662,106368,Male,Loyal Customer,47,Business travel,Business,643,2,2,2,2,2,5,5,4,4,4,4,4,4,4,8,0.0,satisfied +22663,117325,Male,Loyal Customer,23,Personal Travel,Eco Plus,368,2,2,2,3,5,2,5,5,4,4,4,1,4,5,8,4.0,neutral or dissatisfied +22664,64134,Male,Loyal Customer,46,Business travel,Business,2571,1,5,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +22665,77405,Female,Loyal Customer,51,Personal Travel,Eco,590,4,4,4,4,3,4,4,1,1,4,1,4,1,3,0,0.0,satisfied +22666,41998,Male,Loyal Customer,56,Business travel,Business,241,2,2,2,2,5,1,2,4,4,4,4,3,4,1,0,0.0,satisfied +22667,112535,Female,Loyal Customer,59,Personal Travel,Eco,853,2,4,2,4,2,5,4,2,2,2,2,4,2,3,45,37.0,neutral or dissatisfied +22668,39764,Male,Loyal Customer,45,Business travel,Business,2590,2,4,4,4,2,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +22669,64224,Male,disloyal Customer,31,Business travel,Business,1660,3,3,3,4,5,3,5,5,4,2,3,4,4,5,1,30.0,neutral or dissatisfied +22670,46032,Male,Loyal Customer,45,Business travel,Eco,898,2,5,5,5,2,2,2,2,2,1,3,1,4,2,0,0.0,neutral or dissatisfied +22671,76027,Male,disloyal Customer,22,Business travel,Eco,311,0,0,0,3,2,0,2,2,2,5,3,2,5,2,0,0.0,satisfied +22672,31605,Male,Loyal Customer,11,Personal Travel,Eco,602,1,4,1,1,3,1,3,3,3,4,5,4,4,3,3,2.0,neutral or dissatisfied +22673,5100,Male,Loyal Customer,28,Personal Travel,Eco,235,3,5,3,2,3,3,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +22674,127279,Female,Loyal Customer,30,Personal Travel,Eco,1020,1,2,0,3,5,0,5,5,4,1,3,4,3,5,50,35.0,neutral or dissatisfied +22675,109427,Male,Loyal Customer,21,Personal Travel,Business,992,1,5,1,4,1,1,1,1,4,2,5,3,5,1,8,0.0,neutral or dissatisfied +22676,37531,Female,Loyal Customer,52,Business travel,Eco,1028,3,3,3,3,4,4,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +22677,62922,Female,disloyal Customer,20,Business travel,Business,967,5,0,5,1,1,0,5,1,5,2,5,3,5,1,74,62.0,satisfied +22678,98498,Female,disloyal Customer,27,Business travel,Business,668,0,0,0,5,5,0,5,5,5,5,5,5,5,5,1,0.0,satisfied +22679,15533,Male,Loyal Customer,22,Business travel,Business,534,3,3,3,3,5,5,5,5,5,2,2,3,5,5,0,0.0,satisfied +22680,78726,Female,disloyal Customer,24,Business travel,Eco,447,3,4,2,3,3,2,3,3,4,4,4,3,4,3,42,64.0,neutral or dissatisfied +22681,41462,Female,disloyal Customer,55,Business travel,Eco,1504,4,4,4,1,2,4,5,2,3,1,5,1,5,2,8,35.0,satisfied +22682,71240,Male,Loyal Customer,54,Business travel,Business,2608,3,2,2,2,1,4,3,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +22683,13682,Female,disloyal Customer,25,Business travel,Eco,954,1,1,1,4,5,1,5,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +22684,28368,Male,Loyal Customer,45,Business travel,Business,3317,2,5,5,5,2,3,4,2,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +22685,43120,Female,Loyal Customer,49,Personal Travel,Eco,236,4,4,4,2,4,5,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +22686,26277,Female,Loyal Customer,40,Personal Travel,Eco,859,3,3,3,3,3,3,3,3,2,1,3,1,4,3,22,0.0,neutral or dissatisfied +22687,91667,Female,Loyal Customer,45,Personal Travel,Eco Plus,1199,0,4,0,3,5,3,3,2,2,0,2,5,2,5,0,0.0,satisfied +22688,115591,Female,Loyal Customer,24,Business travel,Eco,371,3,3,3,3,3,3,3,3,2,5,3,2,4,3,19,10.0,neutral or dissatisfied +22689,113087,Female,Loyal Customer,49,Business travel,Eco,543,2,2,2,2,5,4,4,1,1,2,1,3,1,3,20,13.0,neutral or dissatisfied +22690,115141,Male,Loyal Customer,60,Business travel,Business,2577,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +22691,4954,Female,Loyal Customer,59,Business travel,Business,3817,2,2,2,2,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +22692,76796,Male,Loyal Customer,27,Business travel,Eco,689,3,1,1,1,3,4,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +22693,59245,Female,Loyal Customer,29,Business travel,Business,3801,3,3,3,3,4,4,4,4,3,4,5,4,3,4,6,0.0,satisfied +22694,47652,Male,Loyal Customer,47,Business travel,Business,2858,2,2,2,2,3,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +22695,39652,Male,Loyal Customer,10,Business travel,Business,1633,4,4,4,4,4,4,4,4,5,5,1,3,2,4,0,0.0,satisfied +22696,72740,Female,Loyal Customer,45,Personal Travel,Eco Plus,1119,2,5,2,4,2,4,4,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +22697,127252,Male,Loyal Customer,59,Business travel,Business,3115,2,2,2,2,2,5,4,4,4,4,4,5,4,3,4,13.0,satisfied +22698,102552,Male,Loyal Customer,55,Personal Travel,Eco,236,5,2,0,4,4,0,4,4,1,2,3,3,4,4,1,4.0,satisfied +22699,74522,Female,disloyal Customer,30,Business travel,Business,1464,5,5,5,4,5,5,4,5,4,4,5,3,5,5,0,0.0,satisfied +22700,110542,Male,Loyal Customer,51,Business travel,Business,2468,3,3,4,3,2,5,5,5,5,5,5,5,5,5,82,104.0,satisfied +22701,41132,Male,Loyal Customer,31,Business travel,Eco,224,4,5,5,5,4,4,4,4,2,4,4,2,3,4,4,11.0,neutral or dissatisfied +22702,61275,Female,Loyal Customer,62,Personal Travel,Eco,853,2,5,3,3,2,4,4,2,2,3,2,5,2,4,32,74.0,neutral or dissatisfied +22703,62727,Female,disloyal Customer,29,Business travel,Eco,2486,2,2,2,3,1,2,1,1,3,1,2,1,3,1,0,0.0,neutral or dissatisfied +22704,3996,Male,Loyal Customer,40,Business travel,Business,3925,1,1,1,1,2,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +22705,57870,Female,Loyal Customer,37,Business travel,Business,1908,5,5,5,5,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +22706,109433,Male,Loyal Customer,45,Business travel,Business,3331,5,5,5,5,3,4,5,4,4,4,4,5,4,5,17,0.0,satisfied +22707,23578,Male,Loyal Customer,53,Business travel,Eco,792,5,2,2,2,5,5,5,5,4,5,5,5,2,5,0,11.0,satisfied +22708,59112,Male,Loyal Customer,57,Personal Travel,Eco,1726,3,1,3,3,5,3,5,5,3,2,3,2,4,5,5,12.0,neutral or dissatisfied +22709,7874,Female,Loyal Customer,58,Business travel,Business,3141,1,1,5,1,2,4,4,5,5,5,5,4,5,3,0,8.0,satisfied +22710,15534,Female,Loyal Customer,14,Personal Travel,Eco,534,3,2,3,4,3,3,3,4,5,4,4,3,3,3,154,164.0,neutral or dissatisfied +22711,38991,Female,disloyal Customer,37,Business travel,Eco,230,3,3,3,2,4,3,4,4,4,1,3,4,3,4,72,99.0,neutral or dissatisfied +22712,14204,Female,Loyal Customer,26,Business travel,Eco,526,4,1,1,1,4,4,3,4,4,5,4,3,3,4,37,23.0,neutral or dissatisfied +22713,97387,Female,Loyal Customer,56,Business travel,Business,2099,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +22714,16134,Male,Loyal Customer,33,Personal Travel,Eco,725,3,1,3,3,3,3,3,3,2,2,2,4,2,3,3,0.0,neutral or dissatisfied +22715,22370,Female,disloyal Customer,20,Business travel,Eco,143,2,1,2,3,5,2,5,5,2,4,3,4,3,5,0,0.0,neutral or dissatisfied +22716,20730,Male,Loyal Customer,56,Personal Travel,Eco,707,3,5,3,5,1,3,1,1,5,5,1,5,3,1,0,9.0,neutral or dissatisfied +22717,55099,Male,Loyal Customer,45,Business travel,Eco,135,3,2,2,2,2,3,2,2,2,1,3,2,4,2,0,13.0,neutral or dissatisfied +22718,43473,Female,Loyal Customer,51,Business travel,Eco,679,4,4,4,4,1,2,1,4,4,4,4,3,4,5,0,1.0,satisfied +22719,111992,Male,Loyal Customer,46,Personal Travel,Eco,770,4,4,4,1,5,4,1,5,5,5,4,3,4,5,0,0.0,satisfied +22720,41755,Male,disloyal Customer,21,Business travel,Eco,230,5,3,5,5,1,5,1,1,4,4,4,1,1,1,2,0.0,satisfied +22721,41550,Male,disloyal Customer,54,Business travel,Eco,1211,3,3,3,3,1,3,1,1,4,4,2,1,3,1,0,0.0,neutral or dissatisfied +22722,11869,Male,Loyal Customer,34,Personal Travel,Eco,912,3,4,3,2,5,3,5,5,5,5,4,5,5,5,10,0.0,neutral or dissatisfied +22723,37719,Male,Loyal Customer,66,Personal Travel,Eco,1097,3,5,3,4,4,3,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +22724,73814,Male,Loyal Customer,36,Personal Travel,Eco Plus,204,2,5,2,1,4,2,4,4,2,2,4,5,4,4,0,0.0,neutral or dissatisfied +22725,81410,Female,Loyal Customer,46,Business travel,Business,1906,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +22726,41056,Male,Loyal Customer,60,Business travel,Eco Plus,1087,4,2,2,2,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +22727,124965,Male,disloyal Customer,24,Business travel,Business,184,0,0,0,5,2,0,2,2,3,2,4,4,4,2,0,0.0,satisfied +22728,17425,Male,Loyal Customer,40,Business travel,Eco,351,2,1,4,1,2,2,2,2,1,1,3,4,3,2,0,37.0,neutral or dissatisfied +22729,76376,Female,Loyal Customer,54,Business travel,Business,1705,2,2,2,2,4,3,4,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +22730,14314,Male,Loyal Customer,73,Business travel,Eco,429,4,3,2,2,4,4,4,4,1,3,3,4,2,4,76,64.0,neutral or dissatisfied +22731,42851,Female,disloyal Customer,37,Business travel,Eco,328,4,2,4,3,5,4,2,5,2,5,3,1,3,5,0,3.0,neutral or dissatisfied +22732,78065,Female,Loyal Customer,7,Personal Travel,Eco,152,3,4,3,3,5,3,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +22733,19942,Female,Loyal Customer,22,Personal Travel,Eco,343,2,5,2,3,4,2,4,4,2,3,3,3,5,4,9,0.0,neutral or dissatisfied +22734,53113,Male,Loyal Customer,34,Business travel,Business,2065,5,5,5,5,3,5,4,5,5,5,5,2,5,1,5,0.0,satisfied +22735,18069,Female,Loyal Customer,28,Personal Travel,Eco,488,3,5,3,3,4,3,4,4,3,4,4,5,5,4,28,27.0,neutral or dissatisfied +22736,124151,Female,Loyal Customer,45,Business travel,Business,2133,2,2,2,2,4,3,5,4,4,4,4,5,4,4,53,43.0,satisfied +22737,33385,Male,Loyal Customer,42,Personal Travel,Eco,2556,4,3,4,2,4,4,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +22738,36631,Male,Loyal Customer,53,Business travel,Eco,837,5,4,4,4,5,5,5,5,3,1,2,3,1,5,0,0.0,satisfied +22739,76185,Female,Loyal Customer,49,Business travel,Business,2422,1,1,1,1,5,4,5,5,5,5,5,4,5,4,16,1.0,satisfied +22740,58966,Male,Loyal Customer,48,Business travel,Business,1723,4,4,4,4,4,4,5,2,2,2,2,4,2,5,20,3.0,satisfied +22741,113850,Male,Loyal Customer,32,Business travel,Business,1363,1,1,2,1,4,4,4,4,3,2,4,3,5,4,58,48.0,satisfied +22742,45427,Female,disloyal Customer,25,Business travel,Eco,649,1,5,2,2,4,2,4,4,2,5,4,4,1,4,0,5.0,neutral or dissatisfied +22743,14864,Male,Loyal Customer,51,Business travel,Business,315,2,4,4,4,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +22744,118335,Male,Loyal Customer,25,Business travel,Business,3500,3,4,4,4,3,3,3,3,2,3,3,2,2,3,0,0.0,neutral or dissatisfied +22745,3277,Male,disloyal Customer,23,Business travel,Eco,479,3,4,3,3,2,3,2,2,5,1,1,4,4,2,0,0.0,neutral or dissatisfied +22746,73438,Female,Loyal Customer,10,Personal Travel,Eco,1182,1,5,1,4,4,1,3,4,3,1,3,1,3,4,30,22.0,neutral or dissatisfied +22747,81359,Female,Loyal Customer,31,Personal Travel,Eco,1299,2,4,2,3,5,2,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +22748,1039,Male,disloyal Customer,27,Business travel,Eco,247,1,0,1,3,5,1,5,5,2,1,1,5,3,5,0,0.0,neutral or dissatisfied +22749,14112,Female,Loyal Customer,38,Business travel,Eco Plus,371,5,4,4,4,5,5,5,5,4,3,5,4,5,5,0,0.0,satisfied +22750,90857,Female,Loyal Customer,64,Business travel,Eco,270,3,1,1,1,2,4,4,3,3,3,3,3,3,2,28,25.0,neutral or dissatisfied +22751,23692,Male,Loyal Customer,39,Business travel,Business,3164,3,2,2,2,2,2,3,2,2,1,3,4,2,1,74,73.0,neutral or dissatisfied +22752,31204,Female,Loyal Customer,21,Business travel,Business,628,2,5,5,5,2,2,2,2,1,1,4,4,4,2,1,8.0,neutral or dissatisfied +22753,60570,Female,Loyal Customer,23,Business travel,Business,1558,5,5,5,5,3,3,3,3,4,5,5,5,5,3,86,93.0,satisfied +22754,48795,Female,disloyal Customer,17,Business travel,Eco,109,4,2,4,3,4,4,4,4,2,5,3,3,3,4,60,49.0,neutral or dissatisfied +22755,88921,Male,Loyal Customer,33,Personal Travel,Eco Plus,859,2,5,2,4,5,2,3,5,4,3,4,5,4,5,14,0.0,neutral or dissatisfied +22756,80181,Female,Loyal Customer,41,Personal Travel,Eco,2586,2,1,2,3,2,4,4,2,4,2,2,4,1,4,0,0.0,neutral or dissatisfied +22757,72601,Male,Loyal Customer,44,Personal Travel,Eco,1119,2,3,2,1,2,2,1,2,1,3,5,1,4,2,3,1.0,neutral or dissatisfied +22758,14387,Male,Loyal Customer,44,Business travel,Eco,900,5,3,3,3,5,5,5,5,5,2,1,2,2,5,0,0.0,satisfied +22759,120876,Female,Loyal Customer,45,Business travel,Business,1013,5,5,5,5,3,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +22760,49433,Female,Loyal Customer,68,Business travel,Eco,89,2,5,5,5,2,2,5,1,1,2,1,4,1,1,13,12.0,satisfied +22761,96508,Male,Loyal Customer,56,Business travel,Business,436,2,2,2,2,1,3,3,2,2,2,2,1,2,1,20,9.0,neutral or dissatisfied +22762,84229,Female,Loyal Customer,31,Personal Travel,Eco,432,1,5,1,4,4,1,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +22763,124967,Male,disloyal Customer,40,Business travel,Eco,184,3,3,3,4,3,3,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +22764,9602,Male,Loyal Customer,15,Personal Travel,Eco,228,3,1,3,2,5,3,5,5,3,3,1,2,1,5,21,14.0,neutral or dissatisfied +22765,75330,Female,Loyal Customer,47,Business travel,Business,2615,5,5,5,5,4,4,4,3,4,4,4,4,3,4,0,0.0,satisfied +22766,72205,Female,Loyal Customer,45,Business travel,Business,2724,5,5,5,5,4,3,3,5,4,4,5,3,3,3,0,0.0,satisfied +22767,32146,Female,Loyal Customer,30,Business travel,Eco,163,4,4,4,4,4,4,4,4,3,5,1,4,2,4,0,0.0,satisfied +22768,49604,Female,Loyal Customer,36,Business travel,Business,158,2,2,2,2,3,1,3,4,4,4,5,4,4,3,3,1.0,satisfied +22769,87918,Male,Loyal Customer,30,Business travel,Business,2210,5,5,5,5,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +22770,3634,Female,disloyal Customer,23,Business travel,Eco,427,2,0,1,3,3,1,5,3,3,5,5,4,5,3,7,0.0,neutral or dissatisfied +22771,10433,Male,Loyal Customer,60,Business travel,Business,2496,3,3,5,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +22772,26702,Male,Loyal Customer,36,Personal Travel,Eco,404,5,5,5,3,1,5,1,1,5,2,4,3,4,1,16,0.0,satisfied +22773,80747,Female,Loyal Customer,9,Personal Travel,Eco,393,4,4,4,4,1,4,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +22774,62242,Female,Loyal Customer,53,Personal Travel,Eco,2565,2,4,2,1,5,5,5,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +22775,103268,Female,Loyal Customer,35,Personal Travel,Eco,888,4,4,4,3,1,4,1,1,4,3,2,4,3,1,10,29.0,satisfied +22776,70258,Female,Loyal Customer,35,Business travel,Business,1592,2,2,2,2,5,3,4,3,3,4,3,3,3,3,0,0.0,satisfied +22777,103557,Male,Loyal Customer,56,Personal Travel,Eco,738,4,5,4,3,1,4,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +22778,79382,Female,Loyal Customer,47,Business travel,Business,502,4,4,4,4,5,4,5,4,4,4,4,5,4,3,26,4.0,satisfied +22779,124731,Male,Loyal Customer,49,Personal Travel,Eco,399,4,3,4,4,5,4,5,5,1,2,3,1,4,5,0,1.0,neutral or dissatisfied +22780,10477,Female,disloyal Customer,24,Business travel,Eco,163,4,4,4,2,3,4,3,3,3,4,5,3,4,3,0,0.0,satisfied +22781,53547,Female,Loyal Customer,31,Business travel,Eco,1956,3,5,5,5,3,4,3,3,2,3,5,2,4,3,5,0.0,satisfied +22782,106202,Female,disloyal Customer,71,Business travel,Eco Plus,436,4,4,4,4,2,4,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +22783,19798,Male,Loyal Customer,32,Personal Travel,Eco Plus,578,2,1,3,3,3,3,3,3,3,1,4,1,3,3,39,36.0,neutral or dissatisfied +22784,34303,Male,Loyal Customer,66,Personal Travel,Eco,496,1,4,1,2,2,1,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +22785,104694,Female,Loyal Customer,46,Business travel,Business,159,2,2,2,2,4,4,4,5,5,5,5,3,5,3,35,30.0,satisfied +22786,103663,Female,disloyal Customer,24,Business travel,Eco,405,1,5,1,5,3,1,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +22787,75250,Female,Loyal Customer,44,Personal Travel,Eco,1744,3,4,3,1,3,5,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +22788,39229,Male,Loyal Customer,32,Business travel,Eco,67,4,4,4,4,4,4,4,4,5,2,5,3,4,4,68,72.0,satisfied +22789,24682,Male,Loyal Customer,46,Business travel,Business,3422,4,3,3,3,3,3,2,4,4,4,4,4,4,4,20,3.0,neutral or dissatisfied +22790,49586,Male,Loyal Customer,47,Business travel,Eco,337,5,1,4,4,5,5,5,5,4,2,3,4,4,5,0,0.0,satisfied +22791,66187,Female,Loyal Customer,42,Business travel,Business,3954,1,5,5,5,1,2,2,1,1,1,1,1,1,4,5,0.0,neutral or dissatisfied +22792,44079,Female,Loyal Customer,58,Personal Travel,Eco,651,1,3,1,1,2,5,2,1,1,1,1,2,1,2,0,7.0,neutral or dissatisfied +22793,119305,Male,Loyal Customer,54,Business travel,Business,214,3,3,5,3,5,5,5,5,5,5,5,4,5,3,0,4.0,satisfied +22794,82571,Female,disloyal Customer,20,Business travel,Business,408,4,4,4,2,2,4,2,2,5,4,4,4,4,2,0,5.0,satisfied +22795,18261,Male,Loyal Customer,53,Personal Travel,Eco,228,3,3,3,4,2,3,3,2,4,5,4,2,4,2,0,0.0,neutral or dissatisfied +22796,47776,Female,disloyal Customer,39,Business travel,Business,817,2,2,2,4,1,2,1,1,3,1,3,2,4,1,0,0.0,neutral or dissatisfied +22797,122334,Female,Loyal Customer,62,Personal Travel,Eco Plus,546,3,4,3,3,2,4,3,4,4,3,4,1,4,4,42,36.0,neutral or dissatisfied +22798,107054,Female,disloyal Customer,23,Business travel,Eco,395,3,1,3,3,4,3,4,4,3,1,3,4,3,4,32,22.0,neutral or dissatisfied +22799,77792,Female,Loyal Customer,66,Personal Travel,Eco,696,2,5,2,1,4,5,5,1,1,2,1,5,1,3,0,2.0,neutral or dissatisfied +22800,2499,Female,Loyal Customer,57,Business travel,Business,3242,3,3,3,3,3,4,5,5,5,5,5,3,5,5,11,5.0,satisfied +22801,82839,Male,Loyal Customer,49,Business travel,Business,2288,2,2,4,2,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +22802,117000,Male,Loyal Customer,50,Business travel,Business,3242,4,4,4,4,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +22803,22048,Male,disloyal Customer,16,Business travel,Eco,304,3,0,3,1,2,3,2,2,4,4,4,2,2,2,0,0.0,neutral or dissatisfied +22804,118259,Female,disloyal Customer,20,Business travel,Eco,1849,2,2,2,4,2,2,2,2,1,1,3,3,4,2,10,13.0,neutral or dissatisfied +22805,57879,Female,disloyal Customer,27,Business travel,Eco,305,3,1,3,4,1,3,1,1,3,3,4,3,3,1,11,4.0,neutral or dissatisfied +22806,33358,Male,disloyal Customer,26,Business travel,Eco,1135,2,2,2,4,4,2,4,4,1,2,3,2,4,4,2,0.0,neutral or dissatisfied +22807,103002,Female,disloyal Customer,24,Business travel,Business,546,0,4,0,3,2,0,2,2,4,3,4,4,5,2,9,56.0,satisfied +22808,34152,Male,Loyal Customer,29,Business travel,Eco,1129,3,1,1,1,3,2,3,3,2,1,2,1,2,3,0,12.0,neutral or dissatisfied +22809,33326,Female,Loyal Customer,51,Business travel,Eco,2399,5,3,3,3,2,3,3,5,5,5,5,5,5,1,0,0.0,satisfied +22810,7546,Female,disloyal Customer,23,Business travel,Eco,606,4,0,4,2,5,4,4,5,3,2,4,3,4,5,64,68.0,satisfied +22811,383,Female,Loyal Customer,58,Business travel,Business,3442,4,4,4,4,5,5,5,5,5,5,4,4,5,3,13,16.0,satisfied +22812,3283,Male,Loyal Customer,24,Personal Travel,Eco,479,3,5,3,3,2,3,2,2,4,4,2,4,2,2,6,0.0,neutral or dissatisfied +22813,44271,Female,Loyal Customer,40,Personal Travel,Eco,118,2,3,2,2,1,2,1,1,3,3,2,2,2,1,0,0.0,neutral or dissatisfied +22814,75025,Male,Loyal Customer,51,Business travel,Business,2519,0,1,1,1,3,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +22815,81532,Male,Loyal Customer,14,Business travel,Eco,1124,3,1,1,1,3,3,4,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +22816,92522,Male,Loyal Customer,13,Personal Travel,Eco,2092,2,0,2,5,2,2,2,5,3,4,4,2,5,2,454,454.0,neutral or dissatisfied +22817,7474,Female,Loyal Customer,37,Personal Travel,Eco,510,2,4,2,3,3,2,5,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +22818,19396,Female,disloyal Customer,21,Business travel,Eco,261,1,4,1,3,1,3,3,2,2,3,1,3,4,3,135,136.0,neutral or dissatisfied +22819,48552,Female,Loyal Customer,42,Personal Travel,Eco,845,4,4,4,3,3,4,4,4,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +22820,92864,Male,Loyal Customer,48,Business travel,Business,2519,4,4,4,4,3,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +22821,58085,Female,Loyal Customer,26,Business travel,Business,2596,2,1,1,1,2,1,2,2,3,5,2,1,2,2,10,0.0,neutral or dissatisfied +22822,86669,Female,Loyal Customer,21,Personal Travel,Eco,746,5,5,5,3,2,5,2,2,1,4,5,4,5,2,0,0.0,satisfied +22823,100710,Male,disloyal Customer,22,Business travel,Business,328,5,0,5,1,2,5,1,2,5,4,4,4,4,2,29,26.0,satisfied +22824,77860,Male,Loyal Customer,62,Personal Travel,Eco Plus,696,2,2,3,2,1,3,1,1,3,1,1,3,2,1,0,14.0,neutral or dissatisfied +22825,30868,Female,Loyal Customer,32,Business travel,Business,1546,4,4,4,4,4,4,4,4,3,5,4,3,5,4,39,55.0,satisfied +22826,18688,Male,Loyal Customer,24,Personal Travel,Eco,190,2,2,2,3,4,2,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +22827,69929,Male,disloyal Customer,24,Business travel,Eco,171,4,0,4,3,1,4,1,1,1,3,1,4,2,1,0,0.0,satisfied +22828,129213,Female,Loyal Customer,61,Business travel,Eco Plus,788,5,2,2,2,1,5,3,5,5,5,5,4,5,4,15,8.0,satisfied +22829,125559,Female,Loyal Customer,36,Business travel,Eco,226,5,2,2,2,5,5,5,5,2,3,3,5,2,5,0,0.0,satisfied +22830,124749,Female,Loyal Customer,49,Business travel,Business,2435,2,2,2,2,1,4,3,2,2,2,2,3,2,4,2,28.0,neutral or dissatisfied +22831,58397,Female,disloyal Customer,23,Business travel,Eco,733,2,2,2,3,3,2,5,3,4,2,4,2,4,3,44,44.0,neutral or dissatisfied +22832,87725,Male,Loyal Customer,14,Personal Travel,Eco Plus,591,3,5,3,4,3,3,5,3,3,3,5,3,4,3,3,6.0,neutral or dissatisfied +22833,31682,Male,Loyal Customer,37,Business travel,Business,862,5,5,5,5,4,4,4,5,5,5,5,5,5,2,0,0.0,satisfied +22834,75295,Male,Loyal Customer,41,Personal Travel,Eco Plus,1744,4,5,4,3,5,4,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +22835,79613,Male,Loyal Customer,22,Business travel,Business,712,2,2,2,2,4,4,4,4,4,4,4,3,5,4,0,3.0,satisfied +22836,97918,Male,disloyal Customer,22,Business travel,Business,616,4,2,4,2,4,4,4,4,5,4,5,4,4,4,5,3.0,satisfied +22837,102931,Female,Loyal Customer,64,Personal Travel,Eco,317,4,4,4,4,5,3,4,5,5,4,5,1,5,4,0,0.0,neutral or dissatisfied +22838,69852,Male,Loyal Customer,70,Personal Travel,Eco,1055,3,4,3,3,2,3,2,2,5,3,4,4,5,2,79,71.0,neutral or dissatisfied +22839,128214,Female,Loyal Customer,43,Business travel,Business,3277,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +22840,98485,Male,Loyal Customer,50,Business travel,Business,668,3,3,3,3,2,5,4,5,5,5,5,5,5,3,4,,satisfied +22841,121050,Male,Loyal Customer,38,Personal Travel,Eco,1013,5,2,5,2,5,5,5,5,1,4,3,1,3,5,0,0.0,satisfied +22842,90655,Female,Loyal Customer,39,Business travel,Business,515,1,1,1,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +22843,65784,Female,Loyal Customer,26,Business travel,Business,1389,3,3,3,3,4,4,4,4,5,3,5,3,5,4,10,0.0,satisfied +22844,102134,Male,Loyal Customer,44,Business travel,Business,3097,1,1,3,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +22845,3152,Female,Loyal Customer,8,Personal Travel,Eco,140,3,1,3,4,4,3,4,4,1,5,4,1,4,4,11,6.0,neutral or dissatisfied +22846,126275,Female,Loyal Customer,16,Personal Travel,Eco,600,2,4,2,2,3,2,3,3,5,3,5,4,5,3,10,18.0,neutral or dissatisfied +22847,39390,Female,Loyal Customer,46,Business travel,Business,521,1,1,1,1,2,1,5,3,3,3,3,3,3,1,0,0.0,satisfied +22848,6852,Female,Loyal Customer,49,Business travel,Business,622,5,5,5,5,2,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +22849,53378,Female,Loyal Customer,46,Business travel,Eco,1052,3,4,4,4,2,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +22850,111021,Female,Loyal Customer,43,Business travel,Business,319,1,1,4,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +22851,129293,Female,Loyal Customer,13,Personal Travel,Eco,550,4,5,4,4,4,4,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +22852,72885,Male,Loyal Customer,51,Business travel,Business,1884,2,2,2,2,5,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +22853,750,Male,Loyal Customer,55,Business travel,Business,164,4,4,4,4,3,4,4,4,4,4,5,4,4,3,61,66.0,satisfied +22854,61076,Female,disloyal Customer,21,Business travel,Eco,1506,2,1,1,4,4,2,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +22855,90138,Female,Loyal Customer,71,Business travel,Business,2605,2,5,5,5,1,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +22856,58801,Male,Loyal Customer,36,Personal Travel,Eco,1005,2,1,2,2,2,2,2,2,4,2,2,1,2,2,0,0.0,neutral or dissatisfied +22857,34566,Female,Loyal Customer,26,Business travel,Business,1598,2,2,2,2,3,2,3,3,1,3,5,3,2,3,0,42.0,satisfied +22858,57101,Female,Loyal Customer,34,Business travel,Business,3389,1,1,1,1,3,5,5,5,5,5,5,5,5,5,40,24.0,satisfied +22859,123976,Male,disloyal Customer,59,Business travel,Business,184,4,4,4,3,1,4,1,1,4,5,4,5,4,1,0,0.0,satisfied +22860,12204,Male,Loyal Customer,57,Business travel,Business,190,0,5,0,4,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +22861,35914,Male,disloyal Customer,22,Business travel,Eco,768,2,1,1,1,3,1,3,3,5,5,4,5,2,3,39,13.0,neutral or dissatisfied +22862,69399,Female,Loyal Customer,46,Business travel,Business,1096,3,2,2,2,2,2,3,3,3,3,3,4,3,2,47,41.0,neutral or dissatisfied +22863,70773,Male,Loyal Customer,58,Business travel,Business,2349,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +22864,123644,Female,Loyal Customer,60,Business travel,Business,2863,2,2,2,2,3,5,4,5,5,5,4,5,5,3,9,5.0,satisfied +22865,74495,Male,Loyal Customer,52,Business travel,Business,1235,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +22866,7093,Male,disloyal Customer,22,Business travel,Eco,273,1,0,1,3,1,1,1,1,4,3,4,5,5,1,1,0.0,neutral or dissatisfied +22867,97645,Male,disloyal Customer,8,Business travel,Business,1587,3,4,3,2,2,3,2,2,4,2,4,4,4,2,1,0.0,neutral or dissatisfied +22868,75786,Male,Loyal Customer,63,Personal Travel,Eco,813,2,1,2,4,4,2,4,4,4,4,3,4,4,4,8,5.0,neutral or dissatisfied +22869,10636,Female,Loyal Customer,46,Business travel,Business,2467,5,5,5,5,3,5,4,3,3,4,4,5,3,4,0,0.0,satisfied +22870,61097,Male,Loyal Customer,35,Personal Travel,Eco,1709,4,3,4,2,1,4,1,1,3,2,3,3,2,1,4,10.0,neutral or dissatisfied +22871,64596,Male,disloyal Customer,50,Business travel,Business,551,3,3,3,1,3,3,4,3,4,3,4,3,4,3,1,16.0,neutral or dissatisfied +22872,97954,Male,Loyal Customer,29,Business travel,Business,2768,2,5,3,3,2,2,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +22873,62055,Male,Loyal Customer,32,Personal Travel,Eco,2586,1,2,1,3,4,1,4,4,2,2,2,3,3,4,0,0.0,neutral or dissatisfied +22874,126443,Female,Loyal Customer,64,Personal Travel,Eco Plus,650,1,2,1,3,3,4,3,4,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +22875,81115,Female,Loyal Customer,50,Business travel,Eco,991,2,4,5,4,3,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +22876,77881,Female,Loyal Customer,39,Business travel,Business,700,1,1,1,1,5,5,4,3,3,3,3,4,3,4,21,16.0,satisfied +22877,68373,Male,Loyal Customer,25,Business travel,Business,2335,4,4,4,4,4,4,4,4,3,3,4,4,5,4,28,30.0,satisfied +22878,26104,Female,Loyal Customer,28,Business travel,Eco Plus,591,4,3,3,3,4,4,4,4,3,3,5,4,4,4,23,27.0,satisfied +22879,111255,Female,Loyal Customer,38,Business travel,Eco,288,4,1,1,1,4,4,4,4,2,2,4,1,3,4,10,0.0,satisfied +22880,120460,Male,Loyal Customer,42,Personal Travel,Eco,366,2,3,2,2,1,2,1,1,5,1,2,3,4,1,0,2.0,neutral or dissatisfied +22881,79695,Female,Loyal Customer,70,Personal Travel,Eco,853,2,2,2,3,4,4,4,1,1,2,1,1,1,4,11,61.0,neutral or dissatisfied +22882,13917,Male,Loyal Customer,38,Business travel,Eco,192,3,1,4,1,3,3,3,3,4,1,4,3,3,3,0,0.0,neutral or dissatisfied +22883,127799,Female,disloyal Customer,22,Business travel,Eco,1262,5,5,5,2,1,5,1,1,5,5,4,4,4,1,0,0.0,satisfied +22884,50733,Male,Loyal Customer,38,Personal Travel,Eco,266,4,0,4,1,2,4,2,2,5,5,4,5,4,2,0,3.0,satisfied +22885,3432,Male,Loyal Customer,48,Personal Travel,Eco,240,2,5,2,1,4,2,4,4,5,2,5,3,5,4,25,33.0,neutral or dissatisfied +22886,4316,Male,Loyal Customer,50,Business travel,Business,184,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +22887,75936,Male,Loyal Customer,51,Business travel,Business,1572,5,5,5,5,3,4,5,4,4,5,4,3,4,5,16,2.0,satisfied +22888,76573,Male,Loyal Customer,25,Business travel,Eco,547,1,1,5,5,1,1,2,1,1,4,3,2,3,1,44,39.0,neutral or dissatisfied +22889,91009,Female,Loyal Customer,29,Personal Travel,Eco,442,2,2,3,2,2,3,3,2,2,4,3,3,2,2,15,21.0,neutral or dissatisfied +22890,97059,Female,disloyal Customer,22,Business travel,Business,1242,4,0,4,4,3,4,1,3,4,2,5,5,4,3,25,41.0,satisfied +22891,101841,Male,Loyal Customer,36,Personal Travel,Eco Plus,1521,4,4,4,3,2,4,3,2,2,2,1,1,4,2,13,0.0,neutral or dissatisfied +22892,119262,Male,Loyal Customer,40,Business travel,Business,214,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,16.0,satisfied +22893,63380,Female,Loyal Customer,29,Personal Travel,Eco,337,3,3,1,3,3,1,3,3,3,3,2,1,5,3,3,0.0,neutral or dissatisfied +22894,6402,Female,Loyal Customer,40,Personal Travel,Eco,296,2,3,4,4,1,4,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +22895,82741,Female,Loyal Customer,46,Business travel,Business,1819,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +22896,115904,Female,Loyal Customer,16,Business travel,Business,337,3,3,3,3,4,4,4,4,1,3,2,2,3,4,2,0.0,satisfied +22897,31663,Female,disloyal Customer,22,Business travel,Eco,967,3,3,3,4,4,3,4,4,2,4,5,4,5,4,1,0.0,neutral or dissatisfied +22898,44566,Female,Loyal Customer,52,Business travel,Eco,157,5,4,4,4,3,3,4,3,3,5,3,2,3,1,0,0.0,satisfied +22899,72738,Female,Loyal Customer,16,Personal Travel,Eco Plus,1119,2,4,2,4,5,2,5,5,3,2,4,5,5,5,0,4.0,neutral or dissatisfied +22900,5106,Male,Loyal Customer,66,Personal Travel,Eco,223,4,5,4,1,1,4,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +22901,80937,Male,Loyal Customer,33,Personal Travel,Eco,352,1,4,1,5,1,1,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +22902,86130,Female,Loyal Customer,36,Business travel,Eco,356,2,5,5,5,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +22903,31206,Male,Loyal Customer,38,Business travel,Eco,628,3,1,3,1,3,3,3,3,1,2,3,3,3,3,15,14.0,neutral or dissatisfied +22904,96634,Male,Loyal Customer,31,Business travel,Business,1913,3,1,3,3,4,4,4,4,4,4,5,5,4,4,9,0.0,satisfied +22905,18441,Female,Loyal Customer,41,Business travel,Business,201,0,5,0,4,2,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +22906,55948,Female,Loyal Customer,42,Business travel,Business,1620,1,1,1,1,3,4,4,4,4,5,4,3,4,4,19,17.0,satisfied +22907,47833,Female,Loyal Customer,39,Business travel,Eco,451,3,5,4,5,3,3,3,3,4,3,4,4,3,3,48,39.0,neutral or dissatisfied +22908,118208,Male,Loyal Customer,11,Personal Travel,Eco,1444,1,2,1,4,4,1,4,4,3,1,4,3,3,4,0,0.0,neutral or dissatisfied +22909,51972,Male,Loyal Customer,39,Business travel,Eco,347,3,2,2,2,3,3,3,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +22910,38829,Male,Loyal Customer,45,Personal Travel,Eco,354,4,1,4,3,3,4,2,3,1,3,4,3,4,3,4,16.0,neutral or dissatisfied +22911,13208,Female,disloyal Customer,10,Business travel,Eco,657,4,2,4,3,1,4,1,1,3,4,3,4,4,1,45,31.0,neutral or dissatisfied +22912,111905,Male,Loyal Customer,60,Business travel,Business,2870,2,2,2,2,5,4,5,5,5,5,5,3,5,4,18,27.0,satisfied +22913,43956,Female,Loyal Customer,68,Personal Travel,Eco,408,3,4,3,4,5,5,4,5,5,3,3,5,5,3,0,33.0,neutral or dissatisfied +22914,40120,Male,Loyal Customer,66,Personal Travel,Eco,200,4,3,0,2,2,0,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +22915,24223,Male,Loyal Customer,31,Business travel,Eco,302,1,5,5,5,1,1,1,1,3,4,3,3,3,1,0,0.0,neutral or dissatisfied +22916,91520,Male,Loyal Customer,18,Personal Travel,Eco,1620,3,4,3,1,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +22917,22422,Female,Loyal Customer,38,Personal Travel,Eco,83,5,4,5,2,3,5,3,3,5,1,1,2,1,3,39,69.0,satisfied +22918,103560,Female,Loyal Customer,70,Personal Travel,Eco,738,3,4,3,2,2,5,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +22919,96737,Female,Loyal Customer,44,Personal Travel,Eco,696,2,4,2,2,3,5,5,3,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +22920,24739,Female,Loyal Customer,26,Personal Travel,Business,528,0,4,0,3,5,0,5,5,5,3,5,5,5,5,10,0.0,satisfied +22921,108408,Male,disloyal Customer,25,Business travel,Eco,544,3,2,3,4,5,3,3,5,1,3,4,1,4,5,20,6.0,neutral or dissatisfied +22922,103696,Male,Loyal Customer,56,Business travel,Eco,251,1,5,5,5,1,1,1,1,2,3,3,3,4,1,69,78.0,neutral or dissatisfied +22923,50379,Female,Loyal Customer,52,Business travel,Eco,209,2,1,1,1,1,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +22924,104993,Female,Loyal Customer,66,Personal Travel,Eco,337,2,5,2,4,5,4,5,5,5,2,5,5,5,4,1,0.0,neutral or dissatisfied +22925,84685,Male,Loyal Customer,62,Personal Travel,Eco,2182,4,4,4,1,2,4,2,2,2,2,4,3,1,2,7,0.0,satisfied +22926,31644,Female,disloyal Customer,26,Business travel,Eco,862,3,3,3,4,5,3,5,5,5,2,3,4,3,5,27,24.0,neutral or dissatisfied +22927,6264,Male,Loyal Customer,28,Business travel,Business,693,4,4,4,4,4,5,4,4,3,3,5,4,4,4,0,38.0,satisfied +22928,43058,Female,disloyal Customer,26,Business travel,Eco,391,2,3,2,4,2,2,3,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +22929,77887,Male,Loyal Customer,60,Business travel,Business,700,3,3,3,3,3,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +22930,100117,Male,Loyal Customer,51,Business travel,Business,2777,4,4,4,4,3,4,5,4,4,5,4,5,4,5,27,11.0,satisfied +22931,96128,Female,Loyal Customer,38,Business travel,Business,328,1,1,1,1,3,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +22932,4704,Male,Loyal Customer,40,Personal Travel,Eco,364,3,5,3,1,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +22933,94734,Female,Loyal Customer,33,Business travel,Eco,323,2,4,4,4,2,2,2,2,3,5,4,2,4,2,110,112.0,neutral or dissatisfied +22934,125111,Male,disloyal Customer,18,Business travel,Eco,361,3,4,3,3,2,3,2,2,2,1,5,3,3,2,0,0.0,neutral or dissatisfied +22935,58380,Female,Loyal Customer,26,Business travel,Business,3015,4,4,2,4,2,2,2,2,4,4,4,4,4,2,15,4.0,satisfied +22936,40249,Male,Loyal Customer,37,Business travel,Business,463,5,5,4,5,4,2,3,4,4,4,4,5,4,2,1,0.0,satisfied +22937,76190,Male,Loyal Customer,15,Business travel,Business,2422,4,4,4,4,2,2,2,2,3,5,4,4,4,2,0,5.0,satisfied +22938,80731,Male,Loyal Customer,40,Business travel,Eco,393,3,3,3,3,3,2,3,3,1,4,3,4,3,3,2,0.0,neutral or dissatisfied +22939,99446,Male,Loyal Customer,60,Business travel,Business,283,0,0,0,2,5,5,5,2,2,2,2,3,2,5,36,,satisfied +22940,38382,Male,Loyal Customer,42,Business travel,Eco Plus,1133,5,1,1,1,4,5,4,4,4,5,2,2,2,4,80,100.0,satisfied +22941,20464,Male,Loyal Customer,32,Personal Travel,Eco,177,3,4,0,4,2,0,1,2,4,3,4,4,5,2,25,17.0,neutral or dissatisfied +22942,87736,Male,Loyal Customer,42,Business travel,Eco,3002,3,5,5,5,3,3,3,2,4,3,4,3,1,3,0,0.0,neutral or dissatisfied +22943,61874,Male,Loyal Customer,53,Business travel,Business,2521,1,1,4,1,2,3,4,4,4,4,4,5,4,4,0,9.0,satisfied +22944,105198,Female,Loyal Customer,66,Business travel,Eco Plus,281,4,3,3,3,4,5,5,4,4,4,4,2,4,5,81,83.0,satisfied +22945,122363,Female,Loyal Customer,59,Business travel,Business,3765,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,1.0,satisfied +22946,22660,Female,disloyal Customer,12,Business travel,Eco,859,4,4,4,2,5,4,5,5,1,1,5,2,2,5,0,0.0,satisfied +22947,1920,Female,Loyal Customer,35,Business travel,Business,3607,0,0,0,2,3,4,4,3,3,3,3,4,3,4,0,12.0,satisfied +22948,39320,Female,Loyal Customer,55,Personal Travel,Eco,67,2,4,0,2,3,4,4,3,3,0,3,5,3,5,0,0.0,neutral or dissatisfied +22949,56590,Female,disloyal Customer,28,Business travel,Eco,937,1,1,1,3,1,5,5,3,1,4,4,5,4,5,151,186.0,neutral or dissatisfied +22950,27911,Male,Loyal Customer,33,Personal Travel,Eco,2311,4,4,4,2,1,4,1,1,4,2,4,3,5,1,0,0.0,satisfied +22951,97896,Male,disloyal Customer,36,Business travel,Business,401,4,4,4,3,3,4,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +22952,36700,Male,Loyal Customer,48,Personal Travel,Eco,1197,1,5,1,2,4,1,4,4,5,2,1,2,4,4,9,0.0,neutral or dissatisfied +22953,87300,Female,Loyal Customer,66,Personal Travel,Eco,577,3,5,3,4,2,4,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +22954,5240,Female,disloyal Customer,33,Business travel,Eco,383,1,1,1,2,1,1,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +22955,37746,Female,Loyal Customer,53,Business travel,Eco Plus,1010,4,1,2,1,4,4,4,4,1,2,3,4,4,4,92,167.0,satisfied +22956,70055,Female,Loyal Customer,49,Business travel,Eco Plus,583,3,3,3,3,5,3,4,3,3,3,3,1,3,3,0,2.0,neutral or dissatisfied +22957,81912,Male,Loyal Customer,67,Personal Travel,Eco Plus,680,3,4,3,4,3,3,3,3,3,1,3,2,5,3,6,4.0,neutral or dissatisfied +22958,61609,Female,Loyal Customer,29,Business travel,Business,1635,5,5,5,5,5,5,5,5,4,5,3,4,4,5,0,0.0,satisfied +22959,38634,Female,Loyal Customer,51,Business travel,Business,2611,5,5,5,5,1,5,1,5,5,5,5,5,5,2,0,0.0,satisfied +22960,27858,Male,Loyal Customer,14,Personal Travel,Eco,1533,3,4,3,2,1,3,1,1,4,5,5,4,5,1,25,31.0,neutral or dissatisfied +22961,21781,Female,Loyal Customer,60,Business travel,Eco,241,5,5,5,5,5,5,2,5,5,5,5,2,5,5,0,0.0,satisfied +22962,120289,Male,Loyal Customer,10,Personal Travel,Eco,1576,2,5,1,3,3,1,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +22963,120532,Female,Loyal Customer,7,Personal Travel,Eco Plus,96,1,4,1,1,4,1,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +22964,21859,Male,Loyal Customer,41,Business travel,Business,1689,4,4,4,4,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +22965,10763,Female,disloyal Customer,27,Business travel,Business,482,1,1,1,4,2,1,4,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +22966,38303,Male,Loyal Customer,72,Business travel,Eco,2583,2,4,4,4,2,2,2,3,1,2,3,2,1,2,0,5.0,neutral or dissatisfied +22967,110832,Female,Loyal Customer,27,Business travel,Eco Plus,1128,3,3,3,3,3,3,3,3,2,1,3,2,4,3,0,0.0,neutral or dissatisfied +22968,120545,Female,disloyal Customer,25,Business travel,Eco,1014,3,3,3,4,4,3,4,4,4,2,3,3,3,4,0,35.0,neutral or dissatisfied +22969,60471,Male,Loyal Customer,54,Business travel,Business,2897,3,3,3,3,5,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +22970,106359,Female,Loyal Customer,40,Business travel,Business,674,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +22971,18665,Female,Loyal Customer,42,Personal Travel,Eco,253,4,2,4,3,5,4,3,5,5,4,5,4,5,2,37,28.0,neutral or dissatisfied +22972,91402,Male,Loyal Customer,62,Personal Travel,Eco,2158,2,5,2,3,5,2,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +22973,127366,Male,Loyal Customer,28,Business travel,Business,1009,1,1,1,1,1,1,1,1,3,1,2,3,2,1,2,6.0,neutral or dissatisfied +22974,25314,Female,Loyal Customer,66,Business travel,Business,3974,3,2,2,2,4,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +22975,59986,Male,Loyal Customer,43,Personal Travel,Eco,937,1,4,1,1,1,1,5,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +22976,363,Female,Loyal Customer,39,Business travel,Business,1869,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +22977,115722,Male,disloyal Customer,21,Business travel,Eco,372,2,0,2,3,5,2,5,5,1,5,3,2,4,5,14,6.0,neutral or dissatisfied +22978,14075,Male,Loyal Customer,59,Business travel,Eco,371,4,2,2,2,4,4,4,4,5,3,5,3,3,4,0,9.0,satisfied +22979,85145,Male,Loyal Customer,49,Business travel,Business,3677,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +22980,84836,Female,disloyal Customer,27,Business travel,Eco,547,1,1,1,3,4,1,4,4,2,2,3,2,4,4,0,1.0,neutral or dissatisfied +22981,101595,Male,disloyal Customer,25,Business travel,Eco,1139,3,3,3,3,2,3,3,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +22982,104553,Male,Loyal Customer,46,Business travel,Business,369,5,5,5,5,3,5,4,4,4,4,4,5,4,4,1,3.0,satisfied +22983,116103,Female,Loyal Customer,58,Personal Travel,Eco,390,2,5,2,5,3,5,4,5,5,2,5,4,5,3,3,3.0,neutral or dissatisfied +22984,3611,Male,Loyal Customer,59,Personal Travel,Eco Plus,999,3,4,3,3,4,3,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +22985,95720,Female,Loyal Customer,44,Business travel,Business,3511,5,5,5,5,4,5,5,4,4,4,4,3,4,3,13,6.0,satisfied +22986,127638,Male,Loyal Customer,8,Personal Travel,Eco,1773,1,3,0,3,1,0,1,1,2,4,3,1,3,1,0,,neutral or dissatisfied +22987,89797,Male,Loyal Customer,67,Personal Travel,Eco,944,2,1,2,4,4,2,4,4,2,3,4,1,4,4,0,0.0,neutral or dissatisfied +22988,70263,Female,Loyal Customer,28,Business travel,Business,3045,3,3,3,3,4,4,4,4,5,5,4,5,5,4,7,0.0,satisfied +22989,111876,Male,disloyal Customer,23,Business travel,Eco,628,0,4,0,3,5,0,5,5,5,2,4,5,4,5,0,0.0,satisfied +22990,61769,Female,Loyal Customer,42,Personal Travel,Eco,1379,3,5,3,2,2,5,4,2,2,3,2,2,2,5,5,0.0,neutral or dissatisfied +22991,76922,Female,Loyal Customer,59,Business travel,Business,1823,1,1,1,1,4,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +22992,36081,Female,Loyal Customer,17,Personal Travel,Eco,399,2,5,2,4,4,2,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +22993,69912,Female,Loyal Customer,45,Personal Travel,Eco,1514,2,4,2,4,5,1,3,5,5,2,5,1,5,3,1,0.0,neutral or dissatisfied +22994,61625,Female,Loyal Customer,47,Business travel,Business,3119,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +22995,72795,Female,Loyal Customer,40,Personal Travel,Eco,1045,4,5,4,4,2,4,3,2,5,4,5,5,4,2,0,0.0,satisfied +22996,50465,Female,Loyal Customer,54,Business travel,Eco,262,2,2,2,2,4,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +22997,105653,Female,Loyal Customer,51,Business travel,Business,1803,3,3,3,3,2,5,4,5,5,5,5,4,5,3,50,24.0,satisfied +22998,70183,Male,Loyal Customer,49,Business travel,Business,1756,2,3,4,3,3,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +22999,80920,Female,Loyal Customer,76,Business travel,Business,3095,4,5,4,5,4,2,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +23000,86780,Male,Loyal Customer,54,Business travel,Business,692,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +23001,124916,Male,Loyal Customer,55,Business travel,Business,2728,2,1,1,1,2,4,4,2,2,2,2,4,2,3,0,33.0,neutral or dissatisfied +23002,36558,Male,Loyal Customer,41,Business travel,Business,3463,4,4,4,4,5,3,3,4,4,4,4,2,4,4,0,18.0,neutral or dissatisfied +23003,101748,Female,disloyal Customer,39,Business travel,Business,1590,3,2,2,1,2,2,2,2,5,3,5,5,4,2,89,81.0,neutral or dissatisfied +23004,127902,Male,Loyal Customer,36,Business travel,Eco,171,3,3,3,3,3,3,3,3,4,2,5,4,2,3,0,0.0,satisfied +23005,112448,Female,Loyal Customer,41,Business travel,Business,1673,4,3,3,3,4,1,2,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +23006,85712,Male,Loyal Customer,34,Business travel,Business,1547,1,1,3,1,2,4,4,5,5,5,5,4,5,4,8,13.0,satisfied +23007,58388,Male,disloyal Customer,22,Business travel,Eco,733,3,3,3,1,5,3,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +23008,128996,Male,Loyal Customer,33,Personal Travel,Eco Plus,236,4,4,0,1,4,0,4,4,3,2,4,4,5,4,0,0.0,satisfied +23009,61881,Male,Loyal Customer,60,Business travel,Eco,2521,3,5,5,5,3,3,3,3,2,2,2,1,4,3,0,0.0,neutral or dissatisfied +23010,68010,Male,Loyal Customer,52,Business travel,Business,280,0,0,0,5,2,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +23011,32520,Male,Loyal Customer,38,Business travel,Eco,101,5,1,1,1,5,5,5,5,1,5,1,5,1,5,0,12.0,satisfied +23012,74807,Male,Loyal Customer,41,Business travel,Eco Plus,1171,3,1,1,1,3,3,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +23013,128417,Male,Loyal Customer,60,Business travel,Business,651,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +23014,118424,Female,disloyal Customer,38,Business travel,Business,370,2,1,1,3,3,1,2,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +23015,38312,Female,Loyal Customer,63,Personal Travel,Eco Plus,2342,3,4,3,3,4,2,3,2,2,3,2,1,2,2,15,0.0,neutral or dissatisfied +23016,28109,Female,Loyal Customer,42,Business travel,Business,1551,3,3,3,3,1,1,2,3,3,4,3,1,3,4,0,0.0,satisfied +23017,77340,Female,Loyal Customer,41,Business travel,Business,3874,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +23018,35273,Male,Loyal Customer,28,Business travel,Business,950,2,2,2,2,2,2,2,2,4,5,4,3,3,2,8,21.0,neutral or dissatisfied +23019,36964,Female,disloyal Customer,21,Business travel,Eco,814,3,3,3,3,1,3,1,1,4,4,3,3,2,1,67,55.0,neutral or dissatisfied +23020,47996,Male,Loyal Customer,45,Business travel,Eco Plus,817,4,4,4,4,4,4,4,4,4,2,4,4,3,4,0,0.0,satisfied +23021,55424,Male,disloyal Customer,13,Business travel,Eco,2521,1,1,1,3,1,4,4,4,2,3,4,4,3,4,38,42.0,neutral or dissatisfied +23022,80668,Female,Loyal Customer,46,Business travel,Business,2574,5,5,5,5,2,5,3,5,5,5,5,5,5,4,0,0.0,satisfied +23023,4215,Male,Loyal Customer,19,Personal Travel,Eco,888,4,1,3,4,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +23024,84784,Female,disloyal Customer,25,Business travel,Business,481,5,3,5,5,2,5,2,2,4,4,4,5,4,2,7,0.0,satisfied +23025,39176,Female,disloyal Customer,26,Business travel,Eco,67,3,2,3,4,5,3,5,5,1,3,4,4,4,5,0,0.0,neutral or dissatisfied +23026,63512,Female,Loyal Customer,20,Business travel,Business,2628,4,4,5,4,4,4,4,4,3,5,5,4,4,4,10,0.0,satisfied +23027,68908,Male,Loyal Customer,16,Personal Travel,Eco,1061,2,4,2,3,5,2,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +23028,81927,Female,Loyal Customer,33,Personal Travel,Business,1535,3,4,3,1,3,4,5,1,1,3,2,3,1,5,0,0.0,neutral or dissatisfied +23029,92420,Male,disloyal Customer,38,Business travel,Business,1892,1,1,1,1,1,1,1,1,4,4,4,4,4,1,5,15.0,neutral or dissatisfied +23030,116269,Female,Loyal Customer,39,Personal Travel,Eco,372,1,4,1,1,2,1,2,2,3,3,5,5,5,2,87,90.0,neutral or dissatisfied +23031,36574,Male,disloyal Customer,37,Business travel,Eco,1237,2,2,2,4,5,2,5,5,2,4,3,4,3,5,0,0.0,neutral or dissatisfied +23032,98866,Male,Loyal Customer,42,Personal Travel,Eco,1751,2,3,2,3,4,2,4,4,4,4,3,4,3,4,1,0.0,neutral or dissatisfied +23033,13660,Male,Loyal Customer,24,Business travel,Business,462,5,5,5,5,5,5,5,5,4,5,5,4,2,5,46,,satisfied +23034,85065,Female,Loyal Customer,39,Business travel,Business,2976,5,5,4,5,3,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +23035,123019,Male,Loyal Customer,28,Business travel,Business,600,3,3,3,3,4,4,4,4,4,2,4,4,4,4,0,4.0,satisfied +23036,124951,Male,Loyal Customer,12,Personal Travel,Eco Plus,728,3,3,3,2,4,3,4,4,4,2,2,5,5,4,64,77.0,neutral or dissatisfied +23037,26606,Male,disloyal Customer,46,Business travel,Eco,406,3,4,3,4,4,3,2,4,1,2,1,2,1,4,94,99.0,neutral or dissatisfied +23038,46493,Male,Loyal Customer,39,Business travel,Eco,73,5,1,1,1,5,5,5,5,2,1,2,1,1,5,0,0.0,satisfied +23039,74721,Male,Loyal Customer,15,Personal Travel,Eco,1464,3,5,3,3,1,3,2,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +23040,126598,Female,Loyal Customer,31,Business travel,Business,1337,5,5,5,5,5,5,5,5,3,3,4,4,4,5,34,33.0,satisfied +23041,68894,Male,disloyal Customer,25,Business travel,Eco,936,3,3,3,4,1,3,1,1,4,3,1,5,5,1,2,3.0,neutral or dissatisfied +23042,41432,Female,Loyal Customer,50,Personal Travel,Eco,641,1,5,1,2,4,4,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +23043,69584,Male,Loyal Customer,38,Personal Travel,Eco,2475,2,5,2,1,2,1,1,3,2,5,5,1,3,1,2,22.0,neutral or dissatisfied +23044,12320,Male,Loyal Customer,36,Business travel,Business,253,1,4,4,4,4,2,3,1,1,2,1,4,1,2,0,12.0,neutral or dissatisfied +23045,21606,Female,disloyal Customer,22,Business travel,Eco,853,2,3,3,3,2,3,2,2,2,3,3,2,4,2,130,109.0,neutral or dissatisfied +23046,27022,Female,Loyal Customer,44,Personal Travel,Eco,867,1,4,1,3,4,5,4,4,4,1,4,4,4,3,6,0.0,neutral or dissatisfied +23047,93621,Male,Loyal Customer,36,Business travel,Business,577,1,5,5,5,1,4,4,1,1,1,1,3,1,1,2,0.0,neutral or dissatisfied +23048,109561,Female,Loyal Customer,25,Personal Travel,Eco,951,3,3,3,3,3,3,3,3,4,3,3,4,1,3,0,0.0,neutral or dissatisfied +23049,51792,Male,Loyal Customer,58,Personal Travel,Eco,237,1,4,1,1,5,1,5,5,3,3,2,1,4,5,0,0.0,neutral or dissatisfied +23050,27137,Male,Loyal Customer,40,Business travel,Business,2688,4,4,4,4,4,4,4,1,1,4,5,4,3,4,0,22.0,satisfied +23051,98333,Female,Loyal Customer,57,Business travel,Business,1697,3,3,3,3,4,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +23052,128945,Male,Loyal Customer,25,Business travel,Business,2881,3,3,2,2,3,3,3,3,1,4,2,3,3,3,0,0.0,neutral or dissatisfied +23053,56840,Female,Loyal Customer,50,Personal Travel,Eco Plus,1605,3,5,3,4,3,3,5,5,5,3,1,4,5,5,8,0.0,neutral or dissatisfied +23054,26562,Male,Loyal Customer,46,Business travel,Business,2751,4,4,1,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +23055,50110,Male,disloyal Customer,25,Business travel,Eco,86,1,1,1,4,1,5,5,3,2,3,3,5,4,5,459,445.0,neutral or dissatisfied +23056,115165,Male,Loyal Customer,39,Business travel,Business,1818,1,1,1,1,3,5,4,5,5,5,5,4,5,5,8,2.0,satisfied +23057,123449,Male,Loyal Customer,52,Business travel,Business,2077,4,4,4,4,4,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +23058,109230,Female,Loyal Customer,70,Personal Travel,Eco,616,2,2,1,4,1,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +23059,93885,Male,disloyal Customer,23,Business travel,Eco,590,3,2,3,3,1,3,1,1,1,3,2,4,3,1,16,7.0,neutral or dissatisfied +23060,19388,Female,Loyal Customer,65,Personal Travel,Eco,844,3,4,3,1,4,4,4,4,4,3,4,3,4,5,10,26.0,neutral or dissatisfied +23061,108437,Female,disloyal Customer,13,Business travel,Eco,860,2,2,2,4,5,2,5,5,3,1,3,2,3,5,13,0.0,neutral or dissatisfied +23062,20488,Female,Loyal Customer,45,Business travel,Eco,139,3,3,4,3,1,4,1,3,3,3,3,5,3,1,2,26.0,satisfied +23063,127969,Female,Loyal Customer,37,Personal Travel,Eco Plus,1999,3,2,3,2,2,3,2,2,2,3,1,3,2,2,6,0.0,neutral or dissatisfied +23064,60084,Female,Loyal Customer,21,Business travel,Business,1182,1,1,1,1,3,4,3,3,4,3,5,4,4,3,41,43.0,satisfied +23065,126008,Male,disloyal Customer,33,Business travel,Business,631,3,3,3,1,5,3,5,5,5,3,4,5,4,5,17,10.0,neutral or dissatisfied +23066,4552,Female,Loyal Customer,51,Business travel,Business,561,4,4,2,4,3,5,4,4,4,4,4,4,4,3,25,7.0,satisfied +23067,34334,Male,disloyal Customer,24,Business travel,Eco,846,1,1,1,3,1,1,1,1,3,4,3,2,5,1,0,2.0,neutral or dissatisfied +23068,19440,Female,Loyal Customer,40,Personal Travel,Eco Plus,645,3,3,3,4,2,3,2,2,5,3,3,3,3,2,0,2.0,neutral or dissatisfied +23069,5907,Female,Loyal Customer,67,Business travel,Eco,108,3,2,2,2,4,1,2,3,3,3,3,4,3,3,10,0.0,satisfied +23070,22563,Male,Loyal Customer,51,Business travel,Business,2067,4,4,1,4,5,3,2,4,4,4,5,4,4,4,0,0.0,satisfied +23071,2631,Male,Loyal Customer,29,Personal Travel,Eco Plus,181,1,2,1,3,3,1,4,3,3,3,3,3,3,3,19,23.0,neutral or dissatisfied +23072,25808,Male,Loyal Customer,28,Business travel,Eco Plus,762,5,4,4,4,5,5,5,5,1,3,3,1,2,5,0,0.0,satisfied +23073,50650,Male,Loyal Customer,9,Personal Travel,Eco,109,1,0,1,2,5,1,5,5,3,1,5,5,3,5,9,14.0,neutral or dissatisfied +23074,107887,Female,disloyal Customer,42,Business travel,Eco Plus,228,1,1,1,3,5,1,5,5,2,2,3,1,3,5,0,0.0,neutral or dissatisfied +23075,58756,Male,Loyal Customer,44,Business travel,Business,1732,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +23076,40869,Male,Loyal Customer,57,Personal Travel,Eco,599,3,3,3,3,4,3,4,4,4,5,4,1,4,4,0,8.0,neutral or dissatisfied +23077,107931,Male,Loyal Customer,20,Business travel,Eco,611,1,4,4,4,1,1,2,1,4,2,4,2,3,1,8,0.0,neutral or dissatisfied +23078,9332,Female,Loyal Customer,28,Personal Travel,Eco Plus,542,4,2,4,3,3,4,3,3,4,2,3,2,3,3,0,0.0,satisfied +23079,115559,Male,Loyal Customer,49,Business travel,Business,2444,2,2,2,2,1,3,3,2,2,2,2,2,2,2,36,36.0,neutral or dissatisfied +23080,5898,Female,Loyal Customer,52,Business travel,Business,2540,1,1,2,1,5,5,4,5,5,5,4,3,5,5,4,0.0,satisfied +23081,100438,Female,Loyal Customer,66,Personal Travel,Eco,1912,4,4,4,1,3,3,4,1,1,4,1,4,1,4,5,13.0,neutral or dissatisfied +23082,123147,Female,Loyal Customer,28,Business travel,Business,3897,4,4,4,4,4,4,4,4,5,4,5,4,5,4,8,0.0,satisfied +23083,74651,Male,Loyal Customer,61,Personal Travel,Eco,1205,2,3,2,4,4,2,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +23084,107731,Female,Loyal Customer,50,Personal Travel,Eco,405,1,3,1,3,2,3,4,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +23085,11487,Female,Loyal Customer,62,Personal Travel,Eco Plus,517,4,5,4,1,3,5,5,3,3,4,4,4,3,5,51,47.0,neutral or dissatisfied +23086,79819,Male,Loyal Customer,40,Business travel,Business,2165,4,4,5,4,5,5,5,4,4,4,4,4,4,5,75,58.0,satisfied +23087,29653,Female,Loyal Customer,15,Personal Travel,Eco,1533,3,5,3,5,5,3,5,5,4,4,5,4,5,5,5,0.0,neutral or dissatisfied +23088,34213,Male,Loyal Customer,30,Personal Travel,Eco,1189,2,4,2,1,3,2,3,3,5,2,3,4,5,3,0,0.0,neutral or dissatisfied +23089,58294,Male,Loyal Customer,29,Personal Travel,Eco,413,3,2,3,2,5,3,5,5,1,4,3,4,3,5,38,31.0,neutral or dissatisfied +23090,42256,Male,Loyal Customer,43,Business travel,Business,462,4,3,3,3,3,2,2,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +23091,4099,Male,Loyal Customer,39,Business travel,Business,431,3,3,3,3,3,4,4,4,4,4,4,3,4,5,13,37.0,satisfied +23092,76865,Male,Loyal Customer,45,Business travel,Business,1927,5,5,4,5,5,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +23093,11320,Female,Loyal Customer,32,Personal Travel,Eco,316,2,4,2,2,2,2,2,2,1,1,4,4,3,2,0,0.0,neutral or dissatisfied +23094,67505,Male,disloyal Customer,49,Business travel,Business,1188,3,3,3,3,5,3,5,5,3,4,5,3,5,5,2,19.0,neutral or dissatisfied +23095,127224,Male,Loyal Customer,51,Business travel,Business,1460,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +23096,5793,Female,Loyal Customer,56,Business travel,Business,177,4,4,4,4,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +23097,72314,Male,Loyal Customer,14,Personal Travel,Eco Plus,919,2,5,2,3,3,2,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +23098,84077,Male,Loyal Customer,44,Business travel,Business,1543,5,5,5,5,3,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +23099,24265,Female,Loyal Customer,23,Personal Travel,Eco,302,1,3,2,4,4,2,4,4,4,5,1,4,3,4,0,0.0,neutral or dissatisfied +23100,89108,Female,Loyal Customer,47,Business travel,Business,1892,5,5,5,5,3,4,4,4,4,4,4,4,4,5,8,0.0,satisfied +23101,13460,Male,Loyal Customer,11,Personal Travel,Eco,409,1,4,4,1,2,4,2,2,5,5,1,3,1,2,0,0.0,neutral or dissatisfied +23102,32560,Female,disloyal Customer,29,Business travel,Eco,216,1,1,1,3,4,1,4,4,4,3,3,3,2,4,0,0.0,neutral or dissatisfied +23103,69891,Male,Loyal Customer,40,Business travel,Business,1514,1,1,1,1,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +23104,104450,Male,Loyal Customer,24,Business travel,Business,1123,3,3,3,3,3,3,3,3,3,1,4,2,4,3,0,15.0,neutral or dissatisfied +23105,105220,Female,Loyal Customer,40,Business travel,Business,377,5,5,5,5,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +23106,56614,Male,Loyal Customer,30,Business travel,Business,1967,3,1,5,1,3,3,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +23107,13341,Male,disloyal Customer,37,Business travel,Eco,631,4,0,4,1,2,4,2,2,5,2,2,2,4,2,0,0.0,neutral or dissatisfied +23108,85982,Male,Loyal Customer,65,Business travel,Business,447,2,1,5,1,4,3,4,2,2,2,2,1,2,3,2,0.0,neutral or dissatisfied +23109,100879,Male,disloyal Customer,41,Business travel,Eco,739,4,4,4,2,2,4,1,2,1,2,3,1,2,2,15,7.0,neutral or dissatisfied +23110,34711,Female,Loyal Customer,57,Business travel,Business,3103,4,4,4,4,2,5,1,4,4,4,4,2,4,5,0,0.0,satisfied +23111,129663,Male,Loyal Customer,48,Business travel,Business,337,1,5,1,1,3,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +23112,128426,Female,disloyal Customer,25,Business travel,Eco,338,4,4,4,3,3,4,3,3,3,1,4,2,3,3,20,8.0,neutral or dissatisfied +23113,71118,Female,Loyal Customer,43,Personal Travel,Eco,678,3,5,3,3,3,5,5,2,2,3,2,5,2,4,15,49.0,neutral or dissatisfied +23114,125637,Male,disloyal Customer,38,Business travel,Business,814,2,2,2,4,3,2,3,3,4,2,4,3,5,3,4,13.0,neutral or dissatisfied +23115,101409,Male,Loyal Customer,68,Personal Travel,Eco,486,2,4,4,3,2,4,2,2,3,2,4,4,4,2,49,34.0,neutral or dissatisfied +23116,96731,Female,disloyal Customer,52,Personal Travel,Eco,696,2,4,2,3,5,2,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +23117,49305,Male,Loyal Customer,53,Business travel,Business,1886,4,4,4,4,2,3,1,4,4,4,4,1,4,1,0,0.0,satisfied +23118,90464,Female,Loyal Customer,26,Business travel,Business,646,5,3,5,5,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +23119,60091,Male,disloyal Customer,39,Business travel,Business,1005,4,3,3,1,5,3,3,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +23120,57185,Female,Loyal Customer,20,Personal Travel,Eco,2227,3,3,3,3,3,3,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +23121,99924,Male,Loyal Customer,50,Business travel,Business,3938,4,4,4,4,2,4,5,3,3,4,3,3,3,3,55,49.0,satisfied +23122,91359,Female,Loyal Customer,58,Personal Travel,Eco Plus,581,3,5,3,2,2,4,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +23123,30690,Female,Loyal Customer,22,Business travel,Business,3082,5,5,5,5,4,4,4,4,1,4,3,3,5,4,3,0.0,satisfied +23124,34757,Male,disloyal Customer,23,Business travel,Eco,264,5,4,5,4,3,5,3,3,4,3,4,4,4,3,9,0.0,satisfied +23125,23726,Male,Loyal Customer,26,Business travel,Eco Plus,196,4,5,5,5,4,3,1,4,1,4,4,1,3,4,3,0.0,neutral or dissatisfied +23126,91742,Male,Loyal Customer,29,Business travel,Business,3938,5,5,5,5,5,5,5,5,3,2,4,4,4,5,0,0.0,satisfied +23127,77318,Female,Loyal Customer,27,Business travel,Business,588,5,5,5,5,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +23128,87413,Female,Loyal Customer,58,Personal Travel,Eco,425,1,5,1,3,3,4,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +23129,126234,Female,disloyal Customer,30,Business travel,Eco,600,1,4,1,3,2,1,2,2,3,1,3,3,3,2,45,35.0,neutral or dissatisfied +23130,30938,Male,disloyal Customer,27,Business travel,Eco,1024,1,1,1,4,3,1,3,3,5,4,2,5,4,3,8,1.0,neutral or dissatisfied +23131,33772,Female,Loyal Customer,61,Personal Travel,Eco,1990,3,2,3,3,4,4,3,2,2,3,2,1,2,1,51,58.0,neutral or dissatisfied +23132,36781,Female,Loyal Customer,19,Business travel,Business,2611,1,3,3,3,2,1,1,3,1,3,4,1,4,1,0,6.0,neutral or dissatisfied +23133,10005,Male,Loyal Customer,22,Personal Travel,Eco,515,1,5,1,3,5,1,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +23134,69448,Female,Loyal Customer,23,Personal Travel,Eco,1096,4,4,4,3,3,4,3,3,4,5,4,3,3,3,0,0.0,satisfied +23135,102528,Female,Loyal Customer,53,Personal Travel,Eco,236,2,4,0,3,3,5,4,3,3,0,3,4,3,3,10,9.0,neutral or dissatisfied +23136,96307,Female,Loyal Customer,49,Business travel,Business,3399,4,4,4,4,2,5,5,5,5,4,5,5,5,3,3,14.0,satisfied +23137,56795,Female,disloyal Customer,38,Business travel,Business,1605,3,3,3,2,2,3,2,2,4,2,4,3,5,2,2,0.0,neutral or dissatisfied +23138,89724,Male,Loyal Customer,64,Personal Travel,Eco,1035,2,4,2,1,4,2,1,4,3,5,4,3,5,4,4,0.0,neutral or dissatisfied +23139,51091,Female,Loyal Customer,48,Personal Travel,Eco,238,3,5,3,3,4,5,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +23140,106681,Female,disloyal Customer,32,Business travel,Eco,451,2,2,2,3,3,2,3,3,2,5,3,4,4,3,33,17.0,neutral or dissatisfied +23141,125699,Male,Loyal Customer,53,Personal Travel,Eco,857,3,4,3,4,3,3,2,3,3,1,2,1,2,3,22,15.0,neutral or dissatisfied +23142,71625,Female,Loyal Customer,59,Business travel,Business,3894,4,4,4,4,5,2,2,4,4,4,4,3,4,1,0,0.0,satisfied +23143,109697,Male,Loyal Customer,55,Business travel,Eco Plus,530,2,3,3,3,2,2,2,2,3,3,4,1,4,2,39,22.0,neutral or dissatisfied +23144,105031,Male,disloyal Customer,32,Business travel,Eco,255,3,1,3,2,3,3,2,3,2,1,3,3,2,3,42,40.0,neutral or dissatisfied +23145,6963,Female,disloyal Customer,26,Business travel,Business,196,1,1,1,1,5,1,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +23146,44525,Male,disloyal Customer,22,Business travel,Eco,157,4,4,4,2,1,4,1,1,5,3,4,1,5,1,0,0.0,satisfied +23147,27944,Male,Loyal Customer,54,Business travel,Eco,1770,4,4,4,4,3,4,3,3,4,4,5,3,1,3,0,0.0,satisfied +23148,29848,Male,disloyal Customer,25,Business travel,Eco,261,0,3,0,3,4,0,4,4,4,3,5,1,4,4,2,3.0,satisfied +23149,48782,Male,Loyal Customer,67,Business travel,Business,250,0,0,0,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +23150,116982,Female,Loyal Customer,57,Business travel,Business,2347,2,2,2,2,5,5,4,5,5,5,5,3,5,5,11,3.0,satisfied +23151,60144,Female,Loyal Customer,39,Business travel,Eco,605,2,5,5,5,2,2,2,2,3,1,4,3,3,2,0,0.0,neutral or dissatisfied +23152,1153,Female,Loyal Customer,63,Personal Travel,Eco,309,1,5,1,4,2,4,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +23153,126322,Male,Loyal Customer,49,Personal Travel,Eco,507,1,5,1,3,5,1,5,5,5,4,5,3,4,5,44,41.0,neutral or dissatisfied +23154,24411,Male,Loyal Customer,36,Business travel,Eco,634,4,1,1,1,4,4,4,4,3,1,1,5,2,4,0,0.0,satisfied +23155,6681,Female,Loyal Customer,36,Business travel,Business,1769,5,5,5,5,5,4,4,4,4,4,4,3,4,4,15,95.0,satisfied +23156,88401,Male,Loyal Customer,29,Business travel,Eco,545,1,5,5,5,1,1,1,1,3,5,4,1,4,1,9,40.0,neutral or dissatisfied +23157,58148,Female,Loyal Customer,34,Business travel,Business,1808,1,1,1,1,3,4,4,5,5,5,5,3,5,4,6,0.0,satisfied +23158,26883,Male,Loyal Customer,38,Business travel,Eco,689,5,1,1,1,5,5,5,5,2,4,3,1,3,5,0,0.0,satisfied +23159,49351,Female,disloyal Customer,27,Business travel,Eco,209,3,0,3,2,4,3,4,4,5,5,4,3,1,4,0,0.0,neutral or dissatisfied +23160,49044,Female,Loyal Customer,44,Business travel,Eco,158,4,5,5,5,2,1,2,4,4,4,4,2,4,3,0,6.0,satisfied +23161,38336,Female,Loyal Customer,24,Business travel,Business,2700,3,3,3,3,5,5,5,5,3,2,4,5,2,5,0,20.0,satisfied +23162,94924,Male,Loyal Customer,27,Business travel,Business,248,4,5,5,5,4,4,4,4,1,2,4,3,4,4,4,0.0,neutral or dissatisfied +23163,7901,Female,Loyal Customer,59,Business travel,Business,1020,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +23164,32805,Female,Loyal Customer,60,Business travel,Eco,216,4,5,5,5,1,3,3,4,4,4,4,5,4,5,0,3.0,satisfied +23165,99228,Female,Loyal Customer,30,Business travel,Business,1914,4,4,4,4,4,4,4,4,5,4,4,5,5,4,0,21.0,satisfied +23166,90735,Male,Loyal Customer,42,Business travel,Eco,515,2,2,2,2,2,2,2,2,2,2,2,2,1,2,0,0.0,neutral or dissatisfied +23167,16430,Male,disloyal Customer,23,Business travel,Eco,416,3,4,2,3,3,2,3,3,2,2,5,3,4,3,2,17.0,neutral or dissatisfied +23168,61839,Male,Loyal Customer,54,Business travel,Business,1379,1,1,1,1,2,4,4,4,4,4,4,3,4,5,4,0.0,satisfied +23169,31488,Female,Loyal Customer,41,Business travel,Business,1676,5,5,5,5,3,1,2,4,4,4,4,3,4,3,11,2.0,satisfied +23170,51472,Male,Loyal Customer,37,Business travel,Eco Plus,109,4,5,5,5,4,4,4,4,3,1,3,4,4,4,31,47.0,neutral or dissatisfied +23171,3112,Male,Loyal Customer,68,Personal Travel,Eco Plus,594,3,4,3,2,1,3,1,1,2,4,1,3,1,1,0,0.0,neutral or dissatisfied +23172,27366,Female,Loyal Customer,60,Business travel,Eco,978,3,5,5,5,2,1,5,3,3,3,3,3,3,3,0,4.0,satisfied +23173,93852,Female,Loyal Customer,12,Personal Travel,Eco,391,1,4,1,1,4,1,4,4,3,3,4,5,4,4,46,38.0,neutral or dissatisfied +23174,38251,Female,Loyal Customer,49,Business travel,Eco,1050,2,4,4,4,1,3,4,2,2,2,2,4,2,2,71,60.0,neutral or dissatisfied +23175,44551,Male,Loyal Customer,60,Personal Travel,Eco,157,2,3,2,4,3,2,2,3,3,1,4,4,3,3,4,0.0,neutral or dissatisfied +23176,109647,Female,Loyal Customer,40,Business travel,Business,2377,1,1,2,1,2,5,4,2,2,2,2,5,2,4,32,31.0,satisfied +23177,49951,Male,Loyal Customer,40,Business travel,Business,2933,0,5,0,3,4,4,1,3,3,3,3,2,3,2,0,0.0,satisfied +23178,11379,Male,Loyal Customer,63,Business travel,Business,2046,2,2,2,2,5,5,4,4,4,4,4,4,4,4,3,0.0,satisfied +23179,129690,Male,Loyal Customer,60,Business travel,Business,2007,3,3,3,3,2,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +23180,111404,Male,Loyal Customer,12,Personal Travel,Eco,1050,3,1,3,4,4,3,3,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +23181,111893,Female,Loyal Customer,25,Personal Travel,Eco,628,2,4,2,1,1,2,1,1,3,3,4,3,5,1,83,75.0,neutral or dissatisfied +23182,103668,Male,disloyal Customer,25,Business travel,Business,251,4,4,3,3,1,3,1,1,4,5,5,5,5,1,10,6.0,neutral or dissatisfied +23183,114251,Male,Loyal Customer,46,Business travel,Eco,819,4,3,3,3,4,4,4,4,1,3,4,1,3,4,14,4.0,neutral or dissatisfied +23184,86395,Female,disloyal Customer,48,Business travel,Business,712,3,3,3,2,5,3,5,5,4,2,4,3,4,5,0,0.0,satisfied +23185,68605,Male,disloyal Customer,19,Business travel,Eco,1404,3,3,3,3,4,3,4,4,3,3,4,4,4,4,16,0.0,neutral or dissatisfied +23186,74937,Male,Loyal Customer,30,Business travel,Business,2475,3,3,3,3,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +23187,24297,Female,Loyal Customer,34,Business travel,Eco Plus,170,5,5,5,5,5,5,5,5,3,2,2,2,4,5,0,0.0,satisfied +23188,39530,Male,Loyal Customer,58,Personal Travel,Eco Plus,852,1,4,1,4,1,1,1,1,5,3,5,3,5,1,0,2.0,neutral or dissatisfied +23189,8322,Female,Loyal Customer,53,Personal Travel,Eco Plus,402,3,4,3,4,2,4,4,5,5,3,5,5,5,4,0,6.0,neutral or dissatisfied +23190,51606,Female,Loyal Customer,49,Business travel,Eco,261,3,2,2,2,3,2,2,3,3,3,3,5,3,1,0,0.0,satisfied +23191,164,Male,Loyal Customer,12,Personal Travel,Eco,227,4,4,4,1,4,4,4,5,5,4,4,4,5,4,134,133.0,neutral or dissatisfied +23192,65501,Female,Loyal Customer,47,Business travel,Business,3700,3,3,3,3,2,5,4,4,4,4,4,3,4,4,61,64.0,satisfied +23193,75402,Male,Loyal Customer,42,Business travel,Business,2267,1,1,1,1,2,3,5,3,3,3,3,5,3,5,0,0.0,satisfied +23194,34748,Male,disloyal Customer,27,Business travel,Eco,264,2,2,2,4,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +23195,121269,Male,Loyal Customer,61,Personal Travel,Eco,2075,2,3,1,2,5,1,5,5,4,2,4,1,4,5,3,0.0,neutral or dissatisfied +23196,74577,Male,Loyal Customer,48,Business travel,Eco,1235,3,1,1,1,3,3,3,3,1,3,3,2,4,3,34,12.0,neutral or dissatisfied +23197,118037,Female,Loyal Customer,54,Business travel,Business,2633,1,1,1,1,3,5,4,4,4,4,4,3,4,3,54,35.0,satisfied +23198,33249,Female,disloyal Customer,22,Business travel,Business,101,3,2,3,1,5,3,5,5,2,1,1,4,1,5,0,0.0,neutral or dissatisfied +23199,5925,Male,Loyal Customer,9,Personal Travel,Eco,173,4,4,4,5,4,4,2,4,5,3,4,4,5,4,11,5.0,neutral or dissatisfied +23200,14744,Female,disloyal Customer,28,Business travel,Eco,533,3,2,3,3,5,3,5,5,4,5,3,4,2,5,0,0.0,neutral or dissatisfied +23201,16397,Male,Loyal Customer,66,Personal Travel,Eco,533,5,5,5,1,1,5,1,1,4,2,5,4,4,1,10,0.0,satisfied +23202,67461,Female,Loyal Customer,20,Personal Travel,Eco,592,2,4,2,5,4,2,5,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +23203,97040,Female,disloyal Customer,44,Business travel,Business,715,3,3,3,1,5,3,5,5,5,4,5,4,5,5,50,44.0,satisfied +23204,4848,Female,disloyal Customer,27,Business travel,Eco,408,2,3,2,3,1,2,1,1,1,4,4,4,4,1,0,0.0,neutral or dissatisfied +23205,107608,Male,Loyal Customer,39,Business travel,Business,423,2,1,1,1,4,3,4,2,2,2,2,2,2,4,53,52.0,neutral or dissatisfied +23206,116716,Female,disloyal Customer,22,Business travel,Business,342,2,1,2,4,3,2,4,3,3,5,3,3,4,3,49,45.0,neutral or dissatisfied +23207,35936,Male,Loyal Customer,65,Personal Travel,Eco,2381,1,2,1,3,3,1,3,3,1,5,3,4,3,3,0,0.0,neutral or dissatisfied +23208,56945,Female,Loyal Customer,43,Business travel,Business,2565,2,3,3,3,1,2,2,2,2,4,3,2,3,2,2,16.0,neutral or dissatisfied +23209,103718,Male,Loyal Customer,65,Personal Travel,Eco,405,3,5,3,2,2,3,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +23210,41090,Male,disloyal Customer,27,Business travel,Eco,295,1,0,1,1,5,1,5,5,1,5,4,5,4,5,19,22.0,neutral or dissatisfied +23211,940,Male,disloyal Customer,39,Business travel,Business,247,1,1,1,1,1,1,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +23212,108629,Female,Loyal Customer,47,Business travel,Eco,1547,4,2,2,2,4,3,3,4,4,4,4,2,4,1,23,0.0,neutral or dissatisfied +23213,32154,Female,disloyal Customer,39,Business travel,Eco,102,4,0,4,1,4,4,4,4,3,1,2,1,5,4,0,0.0,satisfied +23214,86339,Male,Loyal Customer,58,Business travel,Business,762,4,4,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +23215,97499,Female,Loyal Customer,45,Personal Travel,Eco,822,3,4,3,5,4,5,5,2,2,3,2,4,2,4,9,0.0,neutral or dissatisfied +23216,26662,Female,disloyal Customer,26,Business travel,Eco,406,2,3,2,3,5,2,5,5,1,1,3,2,4,5,0,10.0,neutral or dissatisfied +23217,96195,Female,Loyal Customer,50,Business travel,Business,2875,2,2,4,2,5,4,4,5,5,4,5,5,5,5,2,0.0,satisfied +23218,77901,Male,Loyal Customer,76,Business travel,Business,3257,3,2,2,2,1,1,2,3,3,3,3,1,3,4,0,18.0,neutral or dissatisfied +23219,18004,Male,Loyal Customer,31,Business travel,Eco,332,1,3,3,3,1,1,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +23220,14216,Male,Loyal Customer,8,Personal Travel,Eco,620,2,5,2,3,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +23221,105059,Male,Loyal Customer,60,Business travel,Eco Plus,361,2,2,2,2,2,2,2,2,4,2,4,3,3,2,74,55.0,neutral or dissatisfied +23222,78508,Male,disloyal Customer,26,Business travel,Eco,620,4,0,4,1,2,4,2,2,1,5,3,2,1,2,0,0.0,neutral or dissatisfied +23223,74271,Female,disloyal Customer,43,Business travel,Business,2311,4,3,3,1,5,4,5,5,4,5,5,3,4,5,0,0.0,satisfied +23224,67800,Female,Loyal Customer,21,Business travel,Business,3301,1,3,3,3,1,1,1,1,1,5,4,2,3,1,0,1.0,neutral or dissatisfied +23225,36524,Male,Loyal Customer,38,Business travel,Business,1121,5,5,5,5,4,4,4,4,1,5,1,4,3,4,269,260.0,satisfied +23226,105373,Male,Loyal Customer,52,Business travel,Business,2904,3,3,3,3,5,4,5,5,5,5,5,5,5,4,12,6.0,satisfied +23227,3496,Female,Loyal Customer,31,Personal Travel,Eco,1080,1,5,1,2,4,1,1,4,3,4,5,3,5,4,6,0.0,neutral or dissatisfied +23228,32768,Female,disloyal Customer,17,Business travel,Eco,163,2,2,2,3,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +23229,51368,Female,Loyal Customer,8,Personal Travel,Eco Plus,110,4,5,4,4,1,4,1,1,5,4,4,4,5,1,0,0.0,satisfied +23230,123936,Female,Loyal Customer,61,Personal Travel,Eco,541,4,2,4,4,2,4,3,4,4,4,1,1,4,2,0,0.0,neutral or dissatisfied +23231,18931,Female,Loyal Customer,70,Personal Travel,Eco,448,3,5,3,3,2,5,5,5,5,3,5,3,5,4,34,28.0,neutral or dissatisfied +23232,700,Female,Loyal Customer,61,Business travel,Business,1701,2,2,2,2,4,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +23233,98507,Female,Loyal Customer,39,Business travel,Business,402,3,3,3,3,3,5,4,5,5,4,5,3,5,5,58,51.0,satisfied +23234,110223,Male,Loyal Customer,44,Business travel,Business,1011,5,5,5,5,3,4,4,5,5,5,5,3,5,4,5,20.0,satisfied +23235,61124,Female,Loyal Customer,39,Business travel,Business,967,5,5,5,5,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +23236,125187,Female,Loyal Customer,43,Business travel,Eco,651,2,5,5,5,2,2,2,3,4,4,3,2,3,2,222,223.0,neutral or dissatisfied +23237,83460,Male,disloyal Customer,37,Business travel,Business,946,5,5,5,2,2,5,2,2,3,2,4,4,5,2,37,37.0,satisfied +23238,121461,Female,Loyal Customer,7,Personal Travel,Eco,257,3,3,3,3,3,3,1,3,1,5,2,4,2,3,0,0.0,neutral or dissatisfied +23239,93184,Male,Loyal Customer,52,Business travel,Business,3274,2,2,1,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +23240,18806,Female,Loyal Customer,25,Business travel,Business,551,3,3,3,3,4,4,4,4,2,3,5,4,3,4,0,0.0,satisfied +23241,126555,Female,Loyal Customer,7,Personal Travel,Eco,644,1,4,1,4,5,1,5,5,3,2,4,5,4,5,94,104.0,neutral or dissatisfied +23242,30845,Female,Loyal Customer,59,Personal Travel,Eco,936,2,4,2,4,5,3,4,3,3,2,3,2,3,2,0,9.0,neutral or dissatisfied +23243,34240,Female,Loyal Customer,41,Personal Travel,Eco Plus,1189,3,5,3,3,2,4,4,2,2,3,2,3,2,4,120,99.0,neutral or dissatisfied +23244,59362,Male,Loyal Customer,57,Business travel,Business,2367,1,3,1,1,4,3,5,2,2,2,2,5,2,4,8,0.0,satisfied +23245,96911,Female,Loyal Customer,25,Personal Travel,Eco,781,3,3,3,4,3,3,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +23246,92001,Male,Loyal Customer,75,Business travel,Eco Plus,236,2,2,2,2,3,2,3,3,4,2,4,3,4,3,6,3.0,neutral or dissatisfied +23247,53161,Female,Loyal Customer,62,Business travel,Business,2555,0,5,0,1,5,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +23248,72733,Male,Loyal Customer,18,Personal Travel,Eco Plus,918,2,5,2,1,4,2,4,4,4,3,2,1,1,4,71,82.0,neutral or dissatisfied +23249,3164,Male,Loyal Customer,7,Personal Travel,Business,585,1,5,1,3,4,1,4,4,4,5,4,3,5,4,44,37.0,neutral or dissatisfied +23250,69761,Male,Loyal Customer,36,Personal Travel,Eco,1085,3,5,3,5,4,3,3,4,5,5,5,4,4,4,17,22.0,neutral or dissatisfied +23251,119443,Male,Loyal Customer,51,Business travel,Eco Plus,399,4,5,2,5,3,4,3,3,1,4,5,3,2,3,0,0.0,satisfied +23252,55114,Female,Loyal Customer,13,Personal Travel,Eco,1346,3,4,3,4,2,3,3,2,5,4,3,5,5,2,0,0.0,neutral or dissatisfied +23253,91192,Male,Loyal Customer,67,Personal Travel,Eco,270,1,4,1,5,3,1,3,3,4,3,5,4,4,3,0,2.0,neutral or dissatisfied +23254,98983,Male,Loyal Customer,20,Personal Travel,Eco,569,3,4,3,4,5,3,5,5,3,2,4,4,5,5,2,0.0,neutral or dissatisfied +23255,1091,Male,Loyal Customer,65,Personal Travel,Eco,158,3,4,3,1,5,3,5,5,3,4,5,4,4,5,8,8.0,neutral or dissatisfied +23256,24923,Female,Loyal Customer,17,Business travel,Eco,762,3,1,1,1,3,4,4,3,3,5,4,3,3,3,0,0.0,satisfied +23257,115360,Male,Loyal Customer,52,Business travel,Business,2637,1,5,5,5,1,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +23258,5710,Female,Loyal Customer,63,Personal Travel,Eco,299,0,4,0,4,3,4,4,1,1,0,1,3,1,4,12,0.0,satisfied +23259,35302,Female,disloyal Customer,21,Business travel,Business,944,0,0,0,1,4,0,4,4,5,5,5,5,5,4,0,5.0,satisfied +23260,14389,Female,Loyal Customer,46,Business travel,Business,3927,3,3,3,3,2,4,4,4,4,4,4,2,4,2,0,0.0,satisfied +23261,19097,Male,Loyal Customer,23,Business travel,Business,323,3,3,3,3,4,4,4,4,5,4,5,4,5,4,0,5.0,satisfied +23262,68237,Female,Loyal Customer,51,Business travel,Business,3384,3,3,2,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +23263,51673,Male,Loyal Customer,28,Business travel,Business,493,2,4,4,4,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +23264,80607,Male,Loyal Customer,44,Business travel,Business,236,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +23265,23349,Female,Loyal Customer,36,Business travel,Eco Plus,456,3,2,2,2,3,4,3,3,3,3,3,5,5,3,0,0.0,satisfied +23266,103729,Female,Loyal Customer,58,Personal Travel,Eco,466,4,4,4,4,4,5,2,4,4,4,4,1,4,5,90,90.0,neutral or dissatisfied +23267,88758,Male,Loyal Customer,54,Business travel,Business,1629,4,4,4,4,3,5,4,5,5,5,5,3,5,5,7,4.0,satisfied +23268,51641,Male,Loyal Customer,60,Business travel,Business,370,2,3,3,3,1,4,3,2,2,2,2,2,2,3,6,0.0,neutral or dissatisfied +23269,44450,Female,Loyal Customer,67,Personal Travel,Eco,1203,1,4,1,4,1,4,4,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +23270,45513,Male,Loyal Customer,10,Personal Travel,Eco Plus,774,5,2,5,3,4,5,2,4,2,4,3,2,3,4,0,0.0,satisfied +23271,118713,Female,Loyal Customer,15,Personal Travel,Eco,325,2,3,2,4,4,2,4,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +23272,67801,Female,Loyal Customer,48,Business travel,Eco,1188,2,3,3,3,2,4,3,2,2,2,2,4,2,2,0,5.0,neutral or dissatisfied +23273,87260,Female,disloyal Customer,25,Business travel,Business,577,3,5,3,4,2,3,2,2,4,5,4,4,4,2,11,7.0,neutral or dissatisfied +23274,100805,Male,Loyal Customer,45,Business travel,Business,872,5,5,5,5,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +23275,107596,Female,Loyal Customer,41,Business travel,Business,423,3,3,3,3,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +23276,106141,Female,Loyal Customer,46,Business travel,Eco,302,1,5,5,5,1,3,2,1,1,1,1,3,1,3,1,0.0,neutral or dissatisfied +23277,89161,Female,Loyal Customer,39,Personal Travel,Eco,2092,4,2,4,2,3,4,3,3,2,2,1,1,2,3,0,0.0,neutral or dissatisfied +23278,36250,Female,disloyal Customer,36,Business travel,Eco,612,1,0,1,2,2,1,4,2,3,3,2,5,5,2,0,1.0,neutral or dissatisfied +23279,121284,Male,Loyal Customer,22,Personal Travel,Eco Plus,2075,3,4,3,3,5,3,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +23280,66056,Female,disloyal Customer,36,Business travel,Eco,655,2,2,2,4,1,2,1,1,1,3,4,2,3,1,14,16.0,neutral or dissatisfied +23281,16120,Male,Loyal Customer,34,Business travel,Business,1747,3,3,3,3,2,5,5,3,3,5,3,3,3,2,50,72.0,satisfied +23282,9519,Female,Loyal Customer,52,Business travel,Business,2603,0,0,0,5,5,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +23283,48316,Female,Loyal Customer,55,Business travel,Business,1670,5,5,5,5,5,5,4,5,5,5,5,5,5,3,1,11.0,satisfied +23284,18603,Male,Loyal Customer,72,Business travel,Business,1582,4,4,4,4,5,3,4,4,4,4,4,2,4,2,14,6.0,neutral or dissatisfied +23285,24125,Male,Loyal Customer,14,Personal Travel,Eco,584,3,4,3,3,2,3,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +23286,77593,Female,Loyal Customer,39,Business travel,Business,3053,2,2,1,2,3,4,5,4,4,5,4,3,4,4,9,24.0,satisfied +23287,12109,Female,Loyal Customer,31,Business travel,Business,2265,3,3,3,3,5,5,5,5,2,5,5,5,2,5,0,0.0,satisfied +23288,103047,Female,Loyal Customer,38,Business travel,Business,2373,4,2,2,2,4,4,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +23289,96783,Male,Loyal Customer,57,Business travel,Business,781,2,2,3,2,2,5,5,4,4,4,4,5,4,3,9,0.0,satisfied +23290,71451,Male,Loyal Customer,54,Business travel,Business,2187,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +23291,17983,Female,Loyal Customer,17,Personal Travel,Business,332,3,5,3,3,4,3,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +23292,116806,Female,Loyal Customer,40,Business travel,Business,337,4,4,4,4,5,4,4,5,5,5,5,5,5,4,37,17.0,satisfied +23293,128373,Female,disloyal Customer,35,Business travel,Business,304,3,2,2,1,5,2,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +23294,4733,Male,disloyal Customer,49,Business travel,Business,888,2,2,2,3,5,2,1,5,3,4,4,5,4,5,96,76.0,neutral or dissatisfied +23295,102564,Male,Loyal Customer,43,Business travel,Business,3598,2,2,2,2,5,5,5,5,4,5,4,5,4,5,109,137.0,satisfied +23296,66954,Male,disloyal Customer,29,Business travel,Business,985,4,4,4,5,1,4,5,1,3,2,5,3,5,1,0,9.0,neutral or dissatisfied +23297,97812,Female,disloyal Customer,33,Business travel,Business,395,3,3,3,5,4,3,5,4,3,4,5,4,5,4,2,0.0,neutral or dissatisfied +23298,20942,Female,Loyal Customer,27,Business travel,Business,2654,3,2,4,2,3,2,3,3,4,2,4,4,3,3,26,13.0,neutral or dissatisfied +23299,110983,Female,Loyal Customer,55,Business travel,Business,2307,3,5,5,5,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +23300,42850,Female,disloyal Customer,27,Business travel,Eco,328,3,1,3,3,5,3,5,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +23301,68078,Male,Loyal Customer,31,Business travel,Eco,868,2,4,4,4,2,2,2,2,1,4,4,4,4,2,18,16.0,neutral or dissatisfied +23302,22055,Male,disloyal Customer,65,Business travel,Eco,304,2,0,2,1,2,2,2,2,1,4,2,5,4,2,0,0.0,neutral or dissatisfied +23303,70796,Male,Loyal Customer,60,Personal Travel,Eco,328,4,0,3,1,5,3,5,5,4,2,3,4,5,5,0,0.0,satisfied +23304,55408,Male,Loyal Customer,53,Personal Travel,Eco,1290,1,5,1,1,2,1,2,2,5,5,5,4,5,2,106,71.0,neutral or dissatisfied +23305,4899,Female,Loyal Customer,39,Business travel,Business,1020,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +23306,108993,Male,Loyal Customer,39,Business travel,Business,2098,3,3,3,3,5,5,5,3,3,2,3,3,3,3,4,0.0,satisfied +23307,12352,Female,disloyal Customer,27,Business travel,Eco,127,3,3,3,3,3,3,3,3,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +23308,111442,Male,Loyal Customer,59,Business travel,Business,1024,1,3,2,2,5,3,4,1,1,1,1,2,1,4,22,15.0,neutral or dissatisfied +23309,57478,Female,Loyal Customer,36,Business travel,Business,2862,2,2,2,2,4,1,5,4,4,4,4,4,4,2,0,0.0,satisfied +23310,66412,Female,Loyal Customer,58,Personal Travel,Eco,1562,2,4,1,1,5,3,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +23311,5132,Male,Loyal Customer,41,Personal Travel,Eco Plus,235,1,2,1,2,2,1,1,2,3,5,2,1,2,2,0,3.0,neutral or dissatisfied +23312,76993,Male,Loyal Customer,50,Business travel,Business,2748,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,1.0,satisfied +23313,32622,Female,Loyal Customer,38,Business travel,Business,2256,2,2,2,2,3,4,1,5,5,5,5,4,5,2,0,0.0,satisfied +23314,82998,Male,disloyal Customer,18,Business travel,Business,957,0,0,0,1,2,0,2,2,3,3,5,4,5,2,0,0.0,satisfied +23315,78813,Female,Loyal Customer,65,Personal Travel,Eco,432,4,4,2,2,5,5,5,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +23316,33828,Male,Loyal Customer,38,Business travel,Business,1562,4,4,2,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +23317,112603,Female,disloyal Customer,21,Business travel,Business,639,3,3,3,4,4,3,4,4,4,2,4,1,4,4,39,16.0,neutral or dissatisfied +23318,108913,Female,Loyal Customer,51,Business travel,Eco,1066,2,5,5,5,2,2,2,1,1,2,1,3,1,2,0,13.0,neutral or dissatisfied +23319,76293,Female,Loyal Customer,39,Personal Travel,Eco,2677,2,2,2,3,2,1,1,3,5,2,3,1,2,1,0,20.0,neutral or dissatisfied +23320,65960,Female,disloyal Customer,25,Business travel,Business,1372,4,4,4,4,4,4,1,4,5,3,4,3,4,4,8,0.0,satisfied +23321,91076,Male,Loyal Customer,35,Personal Travel,Eco,240,3,4,3,1,2,3,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +23322,62524,Female,Loyal Customer,58,Business travel,Business,1846,2,2,2,2,2,3,5,3,3,4,3,3,3,4,2,5.0,satisfied +23323,32986,Female,Loyal Customer,35,Personal Travel,Eco,163,5,3,5,4,5,5,5,5,4,4,3,3,3,5,0,5.0,satisfied +23324,81774,Female,Loyal Customer,44,Business travel,Business,1310,4,4,4,4,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +23325,70744,Female,Loyal Customer,53,Personal Travel,Eco,675,3,5,3,1,3,4,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +23326,123207,Male,Loyal Customer,46,Personal Travel,Eco,328,3,4,4,3,5,4,5,5,2,5,4,2,5,5,0,10.0,neutral or dissatisfied +23327,114300,Male,Loyal Customer,31,Personal Travel,Eco,819,1,5,1,4,5,1,5,5,2,3,4,2,1,5,1,0.0,neutral or dissatisfied +23328,3130,Male,Loyal Customer,58,Business travel,Business,237,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,24.0,satisfied +23329,100208,Male,Loyal Customer,29,Business travel,Business,3024,1,1,1,1,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +23330,45587,Female,Loyal Customer,45,Business travel,Eco,260,4,4,4,4,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +23331,102458,Female,Loyal Customer,40,Personal Travel,Eco,386,4,3,4,2,3,4,3,3,2,1,5,4,3,3,38,43.0,neutral or dissatisfied +23332,41917,Male,Loyal Customer,67,Business travel,Business,129,3,1,1,1,5,4,3,4,4,4,3,1,4,4,19,26.0,neutral or dissatisfied +23333,21581,Male,Loyal Customer,70,Personal Travel,Eco Plus,331,2,5,2,4,5,2,5,5,3,5,5,3,4,5,22,12.0,neutral or dissatisfied +23334,106655,Female,Loyal Customer,52,Business travel,Business,1590,4,4,4,4,4,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +23335,19442,Female,Loyal Customer,48,Business travel,Business,1818,1,1,1,1,5,5,5,5,5,4,5,3,5,3,0,4.0,satisfied +23336,127324,Male,Loyal Customer,53,Business travel,Business,2810,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +23337,78731,Male,Loyal Customer,41,Business travel,Business,432,5,5,5,5,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +23338,246,Male,Loyal Customer,50,Business travel,Business,719,3,2,2,2,3,3,3,3,2,4,3,3,4,3,116,140.0,neutral or dissatisfied +23339,36217,Male,Loyal Customer,17,Business travel,Eco,280,2,5,1,1,2,2,1,2,1,5,4,3,4,2,0,0.0,neutral or dissatisfied +23340,112575,Female,Loyal Customer,41,Business travel,Business,602,2,2,2,2,4,5,5,5,5,5,5,5,5,3,14,13.0,satisfied +23341,24277,Male,Loyal Customer,12,Personal Travel,Eco,134,2,0,2,5,1,2,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +23342,60129,Male,Loyal Customer,25,Business travel,Business,2503,3,1,1,1,3,3,3,1,4,4,3,3,2,3,140,150.0,neutral or dissatisfied +23343,50271,Female,Loyal Customer,57,Business travel,Business,110,3,1,1,1,2,2,3,2,2,2,3,2,2,1,0,0.0,neutral or dissatisfied +23344,13023,Female,Loyal Customer,20,Business travel,Business,374,1,1,1,1,5,5,5,5,3,2,3,1,3,5,0,0.0,satisfied +23345,82288,Female,Loyal Customer,55,Personal Travel,Eco,1481,0,5,0,3,3,4,5,2,2,0,2,4,2,3,0,0.0,satisfied +23346,52708,Female,disloyal Customer,21,Business travel,Eco,1361,4,4,4,3,1,4,1,1,4,3,4,3,3,1,36,17.0,satisfied +23347,93513,Male,Loyal Customer,51,Business travel,Eco Plus,1020,2,4,4,4,2,2,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +23348,34131,Female,disloyal Customer,26,Business travel,Eco,1237,4,4,4,5,4,4,4,4,2,5,2,5,4,4,36,44.0,satisfied +23349,98581,Male,Loyal Customer,45,Business travel,Business,3955,3,3,4,3,2,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +23350,106824,Female,Loyal Customer,43,Business travel,Business,1488,2,2,2,2,3,4,5,4,4,4,4,5,4,3,20,0.0,satisfied +23351,78655,Female,Loyal Customer,46,Personal Travel,Eco,2172,3,5,3,2,3,4,5,5,5,3,5,5,5,4,3,0.0,neutral or dissatisfied +23352,3318,Female,Loyal Customer,48,Business travel,Business,296,1,1,1,1,2,5,4,5,5,5,5,4,5,4,15,25.0,satisfied +23353,7398,Female,disloyal Customer,19,Business travel,Eco,522,0,4,0,1,3,0,3,3,4,5,5,3,4,3,15,0.0,satisfied +23354,22372,Female,disloyal Customer,54,Business travel,Eco,83,2,3,2,4,3,2,3,3,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +23355,127940,Female,Loyal Customer,67,Personal Travel,Eco,2300,4,4,3,3,3,3,2,2,2,3,2,2,2,3,12,0.0,satisfied +23356,36522,Male,Loyal Customer,44,Business travel,Business,3023,5,5,5,5,2,5,2,5,5,4,5,4,5,3,11,15.0,satisfied +23357,104082,Female,disloyal Customer,37,Business travel,Business,666,2,2,2,3,1,2,1,1,3,4,4,4,5,1,12,0.0,neutral or dissatisfied +23358,89850,Female,Loyal Customer,39,Personal Travel,Business,1310,2,3,2,3,2,4,2,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +23359,36406,Female,Loyal Customer,44,Business travel,Business,2623,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +23360,91079,Male,Loyal Customer,33,Personal Travel,Eco,240,2,5,2,5,3,2,3,3,4,2,5,5,4,3,2,3.0,neutral or dissatisfied +23361,76025,Female,Loyal Customer,54,Business travel,Business,237,1,3,4,3,2,3,4,1,1,1,1,3,1,4,49,64.0,neutral or dissatisfied +23362,58409,Male,disloyal Customer,20,Business travel,Business,733,5,5,5,3,3,5,3,3,3,3,4,4,4,3,0,0.0,satisfied +23363,109574,Female,Loyal Customer,16,Personal Travel,Eco,834,0,5,0,4,4,0,4,4,5,3,5,3,5,4,15,0.0,satisfied +23364,19514,Female,Loyal Customer,65,Personal Travel,Eco,350,3,5,3,1,3,4,5,5,5,3,5,3,5,3,0,15.0,neutral or dissatisfied +23365,80413,Male,Loyal Customer,44,Business travel,Business,2248,4,2,4,4,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +23366,118210,Female,Loyal Customer,55,Business travel,Eco Plus,1444,1,1,1,1,2,3,4,1,1,1,1,3,1,3,22,0.0,neutral or dissatisfied +23367,58604,Female,Loyal Customer,54,Personal Travel,Eco,334,2,5,2,5,2,2,2,5,2,5,4,2,3,2,205,213.0,neutral or dissatisfied +23368,112218,Female,Loyal Customer,41,Business travel,Eco,1199,4,5,5,5,4,4,4,4,3,3,4,4,4,4,96,95.0,neutral or dissatisfied +23369,127262,Female,disloyal Customer,15,Business travel,Eco,1107,1,0,0,3,4,0,3,4,4,5,4,2,4,4,1,0.0,neutral or dissatisfied +23370,90072,Male,disloyal Customer,25,Business travel,Business,1145,0,0,0,4,3,0,3,3,3,2,4,5,5,3,0,0.0,satisfied +23371,26690,Female,Loyal Customer,33,Personal Travel,Eco,270,2,2,2,3,2,2,4,2,2,5,3,3,3,2,0,2.0,neutral or dissatisfied +23372,11350,Male,Loyal Customer,64,Personal Travel,Eco,247,1,1,1,2,4,1,4,4,4,5,3,1,3,4,0,2.0,neutral or dissatisfied +23373,57011,Female,Loyal Customer,28,Personal Travel,Eco,2565,1,5,1,1,1,5,5,1,4,3,1,5,3,5,4,0.0,neutral or dissatisfied +23374,98506,Female,Loyal Customer,35,Business travel,Business,402,5,5,5,5,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +23375,60067,Female,Loyal Customer,48,Business travel,Business,1012,5,5,5,5,5,4,5,4,4,4,4,4,4,4,10,6.0,satisfied +23376,98889,Male,Loyal Customer,51,Business travel,Business,991,4,4,4,4,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +23377,66450,Male,Loyal Customer,58,Business travel,Business,3030,1,3,5,5,3,3,3,1,1,1,1,3,1,3,0,1.0,neutral or dissatisfied +23378,102576,Female,disloyal Customer,24,Business travel,Business,258,4,4,4,1,5,4,5,5,3,2,4,4,5,5,0,0.0,satisfied +23379,30771,Female,Loyal Customer,39,Business travel,Business,895,3,5,5,5,5,3,3,3,3,3,3,2,3,1,21,3.0,neutral or dissatisfied +23380,75029,Female,Loyal Customer,73,Business travel,Business,236,1,1,4,1,2,1,5,4,4,4,4,5,4,2,0,0.0,satisfied +23381,117707,Male,disloyal Customer,35,Business travel,Eco,1009,3,3,3,4,4,3,4,4,2,5,3,2,4,4,112,118.0,neutral or dissatisfied +23382,97583,Male,Loyal Customer,16,Personal Travel,Eco,337,3,3,3,1,4,3,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +23383,10454,Female,Loyal Customer,55,Business travel,Business,191,1,1,3,1,2,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +23384,63572,Male,Loyal Customer,10,Personal Travel,Eco,1737,2,5,2,5,3,2,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +23385,30214,Male,Loyal Customer,31,Personal Travel,Eco Plus,571,3,5,3,3,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +23386,93115,Male,Loyal Customer,52,Business travel,Business,1183,2,2,2,2,2,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +23387,37431,Female,Loyal Customer,24,Business travel,Eco,1010,0,5,0,1,2,0,2,2,1,5,1,3,1,2,0,0.0,satisfied +23388,114869,Female,disloyal Customer,40,Business travel,Business,446,4,4,4,4,2,4,2,2,4,5,5,4,4,2,22,23.0,neutral or dissatisfied +23389,116450,Male,Loyal Customer,67,Personal Travel,Eco,480,1,3,1,2,2,1,2,2,2,2,5,3,1,2,50,36.0,neutral or dissatisfied +23390,61397,Male,disloyal Customer,25,Business travel,Business,279,3,3,3,3,3,3,3,3,1,2,4,1,3,3,42,12.0,neutral or dissatisfied +23391,14464,Female,Loyal Customer,49,Personal Travel,Eco,761,3,5,3,5,5,5,5,4,4,3,3,4,4,4,96,107.0,neutral or dissatisfied +23392,68194,Male,Loyal Customer,41,Personal Travel,Eco Plus,603,3,4,3,4,5,3,4,5,5,5,5,3,5,5,0,1.0,neutral or dissatisfied +23393,48270,Female,Loyal Customer,32,Business travel,Eco Plus,236,5,1,3,1,5,5,5,5,1,4,3,4,2,5,39,32.0,satisfied +23394,45031,Male,Loyal Customer,10,Personal Travel,Eco,867,2,1,2,3,4,2,4,4,2,3,3,1,4,4,55,61.0,neutral or dissatisfied +23395,115046,Female,Loyal Customer,52,Business travel,Business,325,4,4,4,4,3,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +23396,102320,Male,Loyal Customer,60,Business travel,Business,223,2,1,1,1,5,2,3,4,4,3,2,4,4,2,16,19.0,neutral or dissatisfied +23397,6325,Male,disloyal Customer,24,Business travel,Business,315,5,4,5,1,4,5,4,4,4,4,5,5,5,4,0,8.0,satisfied +23398,118133,Female,Loyal Customer,29,Business travel,Eco,1488,2,3,3,3,2,2,2,2,1,3,4,1,3,2,7,0.0,neutral or dissatisfied +23399,73188,Female,Loyal Customer,25,Business travel,Business,1635,1,2,2,2,1,1,1,1,4,1,3,2,3,1,0,0.0,neutral or dissatisfied +23400,89558,Female,Loyal Customer,53,Business travel,Business,3736,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +23401,93038,Male,Loyal Customer,46,Business travel,Business,1733,2,2,2,2,2,4,4,5,5,5,5,4,5,4,74,64.0,satisfied +23402,7218,Male,Loyal Customer,60,Business travel,Business,135,5,5,5,5,5,5,4,4,4,4,5,5,4,5,14,30.0,satisfied +23403,25061,Male,Loyal Customer,20,Personal Travel,Eco,594,4,5,4,4,4,4,4,3,3,2,5,4,4,4,170,158.0,neutral or dissatisfied +23404,34463,Male,Loyal Customer,63,Personal Travel,Eco Plus,228,2,2,2,2,3,2,2,3,3,5,3,4,3,3,0,0.0,neutral or dissatisfied +23405,77721,Male,Loyal Customer,32,Business travel,Eco,874,1,2,2,2,1,1,1,1,1,1,3,2,3,1,30,100.0,neutral or dissatisfied +23406,38744,Female,Loyal Customer,41,Business travel,Eco,354,4,5,5,5,4,4,4,4,5,3,4,1,2,4,0,0.0,satisfied +23407,55007,Male,disloyal Customer,37,Business travel,Eco,1346,1,1,1,3,4,1,4,4,2,2,4,1,3,4,0,0.0,neutral or dissatisfied +23408,49474,Female,Loyal Customer,42,Business travel,Business,3854,3,5,5,5,5,3,3,1,1,1,3,1,1,3,38,33.0,neutral or dissatisfied +23409,54985,Female,Loyal Customer,39,Business travel,Business,1635,5,5,5,5,2,4,5,4,4,4,4,3,4,3,5,4.0,satisfied +23410,98676,Female,Loyal Customer,65,Personal Travel,Eco,920,2,4,2,5,3,4,5,4,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +23411,107503,Female,Loyal Customer,9,Personal Travel,Eco,711,1,4,0,2,2,0,2,2,5,5,5,4,4,2,26,19.0,neutral or dissatisfied +23412,20457,Female,Loyal Customer,42,Business travel,Business,2743,3,5,4,4,3,4,4,4,4,4,3,4,4,2,48,39.0,neutral or dissatisfied +23413,37704,Male,Loyal Customer,14,Personal Travel,Eco,1097,2,3,2,4,2,2,2,2,3,5,4,4,3,2,20,12.0,neutral or dissatisfied +23414,111624,Male,Loyal Customer,56,Personal Travel,Eco,1014,2,2,2,3,2,2,2,2,4,3,4,1,3,2,25,9.0,neutral or dissatisfied +23415,2563,Male,disloyal Customer,32,Business travel,Business,181,2,2,2,1,5,2,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +23416,74957,Female,disloyal Customer,17,Business travel,Eco,1345,1,1,1,4,3,1,3,3,1,3,2,1,3,3,0,2.0,neutral or dissatisfied +23417,61039,Female,Loyal Customer,54,Business travel,Business,1709,2,2,2,2,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +23418,34797,Male,Loyal Customer,24,Personal Travel,Eco,209,4,1,4,2,2,4,2,2,2,5,2,1,2,2,0,4.0,satisfied +23419,50542,Female,Loyal Customer,18,Personal Travel,Eco,109,3,1,3,3,2,3,2,2,1,4,2,2,3,2,71,83.0,neutral or dissatisfied +23420,75921,Male,Loyal Customer,56,Business travel,Business,3616,5,5,5,5,2,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +23421,80010,Male,Loyal Customer,59,Personal Travel,Eco,944,1,5,1,3,3,1,2,3,3,2,3,2,2,3,26,10.0,neutral or dissatisfied +23422,41006,Female,Loyal Customer,50,Personal Travel,Eco,1362,4,3,4,3,4,3,5,2,2,4,2,3,2,3,8,0.0,neutral or dissatisfied +23423,81341,Male,Loyal Customer,53,Business travel,Business,2789,4,3,4,4,3,4,4,4,4,4,4,2,4,2,0,7.0,neutral or dissatisfied +23424,78027,Male,Loyal Customer,45,Business travel,Business,1501,2,2,2,2,2,3,4,2,2,2,2,3,2,4,3,0.0,neutral or dissatisfied +23425,101312,Female,Loyal Customer,53,Business travel,Business,3157,5,5,5,5,4,4,5,4,4,4,4,4,4,4,27,1.0,satisfied +23426,81177,Male,Loyal Customer,39,Business travel,Business,2765,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +23427,54510,Female,Loyal Customer,45,Business travel,Eco,525,4,3,4,4,2,3,1,4,4,4,4,5,4,5,0,0.0,satisfied +23428,66830,Female,Loyal Customer,42,Business travel,Business,1753,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +23429,95781,Male,Loyal Customer,18,Personal Travel,Eco,181,2,4,2,3,3,2,3,3,4,3,5,5,5,3,12,4.0,neutral or dissatisfied +23430,60220,Male,Loyal Customer,69,Business travel,Business,1506,2,5,5,5,5,2,2,2,2,2,2,3,2,1,0,15.0,neutral or dissatisfied +23431,62900,Female,Loyal Customer,44,Business travel,Business,862,5,5,5,5,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +23432,60380,Male,disloyal Customer,31,Business travel,Eco,782,4,4,4,4,4,4,3,4,4,2,3,3,3,4,13,0.0,neutral or dissatisfied +23433,12968,Male,Loyal Customer,66,Personal Travel,Eco Plus,456,3,4,3,5,5,3,5,5,5,1,5,3,2,5,0,5.0,neutral or dissatisfied +23434,5529,Male,disloyal Customer,39,Business travel,Eco,431,3,3,3,4,2,3,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +23435,51794,Female,Loyal Customer,41,Personal Travel,Eco,355,2,4,2,5,5,2,5,5,2,4,2,3,5,5,0,0.0,neutral or dissatisfied +23436,124556,Female,Loyal Customer,53,Business travel,Business,453,4,1,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +23437,125667,Female,Loyal Customer,56,Business travel,Business,3086,5,5,5,5,4,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +23438,1994,Female,Loyal Customer,62,Personal Travel,Eco,383,2,4,2,5,5,5,4,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +23439,37055,Male,Loyal Customer,39,Business travel,Business,1188,3,2,3,3,2,4,4,3,3,2,3,5,3,1,18,3.0,satisfied +23440,75546,Male,disloyal Customer,21,Business travel,Business,337,5,0,4,4,3,4,3,3,5,3,4,4,4,3,0,0.0,satisfied +23441,81092,Female,Loyal Customer,9,Personal Travel,Eco,931,1,3,1,3,2,1,2,2,1,3,3,1,1,2,0,0.0,neutral or dissatisfied +23442,100767,Male,Loyal Customer,37,Business travel,Business,1411,1,1,1,1,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +23443,113245,Female,Loyal Customer,46,Personal Travel,Business,258,1,5,1,2,5,5,3,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +23444,54580,Female,Loyal Customer,53,Business travel,Business,3904,1,1,4,1,4,4,4,2,3,5,1,4,5,4,10,0.0,satisfied +23445,39369,Male,Loyal Customer,38,Business travel,Eco Plus,826,4,3,3,3,4,4,4,4,4,1,5,1,1,4,9,20.0,satisfied +23446,40838,Male,Loyal Customer,16,Business travel,Eco,588,5,1,1,1,5,5,5,5,2,4,2,5,2,5,0,0.0,satisfied +23447,55147,Female,Loyal Customer,40,Personal Travel,Eco,1379,1,5,0,3,3,0,3,3,5,5,3,3,5,3,0,14.0,neutral or dissatisfied +23448,39704,Female,Loyal Customer,37,Business travel,Eco,162,5,4,4,4,5,5,5,5,5,5,4,2,5,5,0,8.0,satisfied +23449,109669,Female,Loyal Customer,36,Business travel,Business,1812,1,1,1,1,5,4,5,5,5,5,5,3,5,1,1,0.0,satisfied +23450,13794,Female,Loyal Customer,25,Business travel,Eco Plus,837,2,4,4,4,2,2,2,2,1,3,4,1,4,2,0,2.0,neutral or dissatisfied +23451,14024,Male,Loyal Customer,26,Business travel,Business,3656,2,2,2,2,4,4,4,4,2,5,4,5,1,4,0,0.0,satisfied +23452,59776,Female,Loyal Customer,36,Business travel,Eco,495,5,2,2,2,4,5,5,1,4,4,3,5,3,5,266,266.0,neutral or dissatisfied +23453,58248,Male,Loyal Customer,24,Personal Travel,Eco Plus,925,2,2,2,3,1,2,1,1,3,5,3,3,3,1,107,120.0,neutral or dissatisfied +23454,33965,Male,Loyal Customer,45,Personal Travel,Business,1598,3,5,4,4,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +23455,26272,Male,Loyal Customer,34,Business travel,Business,2716,2,4,4,4,3,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +23456,58180,Male,Loyal Customer,32,Business travel,Business,925,4,4,4,4,3,3,3,3,3,5,4,4,4,3,21,0.0,satisfied +23457,18055,Male,Loyal Customer,25,Business travel,Business,605,2,2,2,2,2,2,2,4,5,3,3,2,3,2,153,163.0,neutral or dissatisfied +23458,86682,Male,Loyal Customer,45,Business travel,Business,1747,1,2,2,2,1,1,1,3,3,2,4,1,3,1,204,205.0,neutral or dissatisfied +23459,116753,Male,Loyal Customer,60,Personal Travel,Eco Plus,480,5,3,5,3,5,5,5,5,4,4,3,2,3,5,0,0.0,satisfied +23460,66729,Male,Loyal Customer,64,Personal Travel,Eco,802,3,2,3,4,3,3,3,3,4,5,3,3,3,3,11,29.0,neutral or dissatisfied +23461,12185,Female,Loyal Customer,58,Personal Travel,Eco,931,4,5,5,1,4,4,4,2,2,5,2,5,2,3,44,44.0,satisfied +23462,80305,Female,disloyal Customer,25,Business travel,Eco,746,2,1,1,3,4,1,4,4,2,1,3,2,4,4,10,19.0,neutral or dissatisfied +23463,18060,Male,Loyal Customer,23,Business travel,Business,488,4,4,4,4,4,4,4,4,1,5,1,2,4,4,0,0.0,satisfied +23464,77692,Male,Loyal Customer,16,Business travel,Eco,689,3,4,4,4,3,3,1,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +23465,88899,Male,Loyal Customer,23,Business travel,Business,3155,2,2,2,2,2,2,2,2,1,2,4,1,3,2,12,14.0,neutral or dissatisfied +23466,102550,Female,Loyal Customer,49,Personal Travel,Eco,258,1,2,1,4,5,3,4,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +23467,97774,Male,Loyal Customer,53,Business travel,Business,3398,2,2,2,2,2,5,4,4,4,5,4,5,4,5,4,6.0,satisfied +23468,61178,Female,Loyal Customer,60,Business travel,Business,2483,5,5,5,5,2,4,4,4,4,4,4,4,4,4,3,0.0,satisfied +23469,107303,Female,Loyal Customer,15,Personal Travel,Eco,283,3,4,3,1,5,3,1,5,3,4,4,5,4,5,2,0.0,neutral or dissatisfied +23470,36213,Female,Loyal Customer,55,Business travel,Business,280,3,5,4,5,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +23471,64469,Male,disloyal Customer,21,Business travel,Eco,469,4,0,4,5,1,4,1,1,3,2,4,5,5,1,0,0.0,satisfied +23472,29987,Female,Loyal Customer,34,Business travel,Eco,199,0,0,0,4,5,0,5,5,3,5,1,4,4,5,0,0.0,satisfied +23473,53156,Male,Loyal Customer,37,Business travel,Business,2249,5,5,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +23474,55366,Female,Loyal Customer,64,Business travel,Eco,678,2,5,5,5,4,4,3,2,2,2,2,4,2,1,14,0.0,neutral or dissatisfied +23475,127931,Female,Loyal Customer,28,Personal Travel,Eco,2300,4,5,4,5,1,4,1,1,5,2,3,3,4,1,0,0.0,satisfied +23476,48545,Female,disloyal Customer,50,Business travel,Eco,453,3,1,3,4,3,3,3,3,2,2,4,3,4,3,3,5.0,neutral or dissatisfied +23477,61431,Female,Loyal Customer,13,Personal Travel,Business,2253,2,1,2,4,2,2,4,2,3,4,2,2,4,2,0,0.0,neutral or dissatisfied +23478,13532,Female,disloyal Customer,21,Business travel,Eco,227,3,3,3,3,1,3,1,1,1,1,4,4,4,1,0,0.0,neutral or dissatisfied +23479,26707,Female,Loyal Customer,41,Personal Travel,Eco,270,0,4,0,4,3,0,3,3,3,2,5,3,5,3,0,0.0,satisfied +23480,43934,Male,Loyal Customer,38,Business travel,Eco Plus,114,5,2,5,5,5,5,5,5,4,2,3,4,1,5,58,48.0,satisfied +23481,56514,Male,Loyal Customer,17,Personal Travel,Business,1065,1,4,1,3,3,1,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +23482,28680,Female,disloyal Customer,21,Business travel,Eco,2777,5,5,5,4,2,5,2,2,5,1,5,1,1,2,0,0.0,satisfied +23483,93045,Male,Loyal Customer,14,Personal Travel,Eco,317,1,3,1,2,3,1,3,3,2,2,3,3,5,3,0,0.0,neutral or dissatisfied +23484,125627,Female,Loyal Customer,58,Business travel,Business,2116,3,3,3,3,5,4,4,3,3,3,3,5,3,5,28,30.0,satisfied +23485,25925,Female,Loyal Customer,34,Business travel,Business,594,5,5,5,5,2,2,2,5,5,5,5,1,5,1,3,1.0,satisfied +23486,16191,Female,Loyal Customer,55,Business travel,Business,199,1,4,4,4,1,1,2,3,5,3,3,2,1,2,210,206.0,neutral or dissatisfied +23487,97810,Male,Loyal Customer,39,Business travel,Business,3064,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +23488,54345,Female,disloyal Customer,22,Business travel,Eco,997,3,3,3,5,1,3,1,1,5,4,5,4,2,1,0,0.0,neutral or dissatisfied +23489,10926,Male,disloyal Customer,30,Business travel,Business,216,2,2,2,4,3,2,3,3,3,4,3,4,4,3,12,4.0,neutral or dissatisfied +23490,9631,Male,Loyal Customer,44,Business travel,Business,2638,0,0,0,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +23491,113122,Female,Loyal Customer,47,Business travel,Business,479,4,4,4,4,4,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +23492,95426,Male,Loyal Customer,50,Business travel,Business,248,0,0,0,4,4,4,5,5,5,5,5,4,5,3,13,20.0,satisfied +23493,25201,Male,Loyal Customer,29,Business travel,Business,787,1,4,4,4,1,1,1,4,5,3,4,1,1,1,212,210.0,neutral or dissatisfied +23494,37209,Male,Loyal Customer,24,Business travel,Eco,680,3,1,1,1,4,4,3,1,3,3,4,3,5,3,254,246.0,satisfied +23495,8407,Male,Loyal Customer,48,Business travel,Business,2278,5,5,5,5,3,5,5,5,5,5,5,4,5,5,70,85.0,satisfied +23496,51650,Male,Loyal Customer,15,Business travel,Business,451,1,4,1,4,1,2,1,1,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +23497,92006,Female,Loyal Customer,54,Business travel,Business,1532,3,2,3,3,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +23498,12213,Male,Loyal Customer,48,Business travel,Business,190,0,4,0,4,2,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +23499,17042,Female,Loyal Customer,27,Business travel,Business,3497,1,1,1,1,4,4,4,4,2,2,4,3,3,4,0,0.0,satisfied +23500,4471,Male,Loyal Customer,49,Personal Travel,Eco,1005,2,4,2,4,3,2,3,3,1,4,3,2,3,3,119,114.0,neutral or dissatisfied +23501,24188,Male,disloyal Customer,27,Business travel,Eco,147,1,2,1,3,4,1,4,4,1,4,4,2,3,4,41,27.0,neutral or dissatisfied +23502,87665,Female,Loyal Customer,27,Business travel,Business,3070,1,3,3,3,1,1,1,1,3,1,4,1,3,1,17,24.0,neutral or dissatisfied +23503,52026,Male,Loyal Customer,29,Personal Travel,Eco,328,3,0,3,5,2,3,2,2,3,5,1,5,3,2,0,0.0,neutral or dissatisfied +23504,74107,Female,disloyal Customer,27,Business travel,Eco,721,1,1,1,3,4,1,3,4,4,1,4,1,3,4,0,0.0,neutral or dissatisfied +23505,102803,Male,Loyal Customer,41,Business travel,Business,2472,3,3,3,3,5,5,5,4,4,4,4,4,4,3,86,,satisfied +23506,105983,Male,Loyal Customer,67,Personal Travel,Eco,2295,2,3,2,3,2,2,4,2,5,4,3,4,2,4,13,16.0,neutral or dissatisfied +23507,12679,Male,disloyal Customer,23,Business travel,Eco,721,3,3,3,3,3,5,3,1,3,3,1,3,2,3,197,189.0,neutral or dissatisfied +23508,59629,Male,disloyal Customer,11,Business travel,Eco,854,4,4,4,3,4,4,4,4,1,1,4,2,4,4,0,0.0,neutral or dissatisfied +23509,114496,Male,Loyal Customer,25,Business travel,Business,3657,2,5,5,5,2,2,2,2,4,5,4,2,3,2,36,30.0,neutral or dissatisfied +23510,47323,Female,Loyal Customer,49,Business travel,Eco,532,4,4,4,4,4,1,2,4,4,4,4,2,4,4,0,0.0,satisfied +23511,76819,Male,Loyal Customer,60,Business travel,Business,1851,2,2,2,2,2,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +23512,27873,Female,Loyal Customer,61,Business travel,Eco Plus,1448,5,3,3,3,3,3,1,5,5,5,5,3,5,2,21,0.0,satisfied +23513,64436,Female,Loyal Customer,36,Business travel,Business,2419,5,5,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23514,114411,Male,Loyal Customer,51,Business travel,Business,308,3,2,3,3,2,4,5,5,5,5,5,4,5,5,18,25.0,satisfied +23515,121673,Male,Loyal Customer,61,Personal Travel,Eco,511,4,4,4,1,1,4,1,1,4,5,5,4,4,1,0,0.0,satisfied +23516,105302,Male,Loyal Customer,30,Business travel,Business,3684,3,3,3,3,4,4,4,4,2,2,2,5,5,4,15,4.0,satisfied +23517,79729,Female,Loyal Customer,17,Personal Travel,Eco,762,3,5,2,4,3,2,3,3,3,3,5,4,5,3,79,74.0,neutral or dissatisfied +23518,31522,Male,disloyal Customer,40,Business travel,Eco,462,2,1,2,3,1,2,2,1,3,1,4,3,3,1,95,114.0,neutral or dissatisfied +23519,29002,Female,Loyal Customer,30,Business travel,Business,697,1,4,3,4,1,1,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +23520,60032,Male,Loyal Customer,69,Personal Travel,Eco,1023,3,5,3,1,2,3,2,2,5,4,1,1,5,2,0,0.0,neutral or dissatisfied +23521,81451,Male,Loyal Customer,51,Business travel,Business,3989,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +23522,28190,Female,Loyal Customer,48,Personal Travel,Eco,550,2,0,2,4,4,5,5,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +23523,6205,Male,Loyal Customer,7,Personal Travel,Eco Plus,491,3,5,3,2,4,3,1,4,4,1,1,1,4,4,0,1.0,neutral or dissatisfied +23524,44103,Male,Loyal Customer,51,Business travel,Business,408,5,5,5,5,4,2,1,5,5,5,5,2,5,1,0,0.0,satisfied +23525,87202,Male,Loyal Customer,33,Business travel,Business,2153,4,2,2,2,4,4,4,4,1,3,3,1,2,4,0,0.0,neutral or dissatisfied +23526,32734,Male,disloyal Customer,33,Business travel,Eco,163,3,0,3,4,1,3,1,1,2,3,4,5,4,1,0,0.0,neutral or dissatisfied +23527,88395,Female,disloyal Customer,22,Business travel,Business,581,4,0,4,1,1,4,1,1,4,2,4,3,5,1,4,0.0,satisfied +23528,5964,Male,disloyal Customer,25,Business travel,Business,691,2,2,2,3,4,2,4,4,3,1,3,2,3,4,0,26.0,neutral or dissatisfied +23529,30924,Male,Loyal Customer,21,Personal Travel,Eco,896,3,5,3,2,2,3,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +23530,111238,Female,Loyal Customer,62,Business travel,Eco Plus,1703,1,4,4,4,4,2,4,1,1,1,1,3,1,3,6,33.0,neutral or dissatisfied +23531,102499,Male,Loyal Customer,30,Personal Travel,Eco,386,2,4,2,3,1,2,1,1,3,4,4,3,5,1,24,26.0,neutral or dissatisfied +23532,102657,Female,Loyal Customer,34,Business travel,Business,255,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +23533,86113,Male,Loyal Customer,37,Business travel,Business,2490,3,3,3,3,2,5,5,5,5,5,5,5,5,4,0,25.0,satisfied +23534,48641,Female,Loyal Customer,40,Business travel,Business,250,5,5,5,5,5,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +23535,46780,Female,Loyal Customer,57,Business travel,Business,737,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,15.0,satisfied +23536,39903,Female,Loyal Customer,45,Business travel,Eco Plus,221,5,5,5,5,5,5,5,5,1,1,5,5,4,5,105,171.0,satisfied +23537,21308,Female,Loyal Customer,32,Personal Travel,Eco,714,4,4,4,3,1,4,1,1,5,3,5,4,5,1,3,3.0,satisfied +23538,50076,Female,Loyal Customer,54,Business travel,Business,1698,2,2,2,2,2,2,4,5,5,4,3,5,5,1,1,0.0,satisfied +23539,115548,Female,Loyal Customer,50,Business travel,Business,404,5,5,1,5,2,4,5,5,5,5,5,5,5,5,13,3.0,satisfied +23540,70301,Female,Loyal Customer,54,Business travel,Business,2986,0,0,0,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +23541,110184,Male,Loyal Customer,18,Personal Travel,Eco,1056,1,3,1,4,4,1,4,4,3,5,3,1,1,4,1,0.0,neutral or dissatisfied +23542,4332,Female,Loyal Customer,40,Business travel,Business,3851,2,3,3,3,2,2,2,2,4,3,3,2,3,2,212,168.0,neutral or dissatisfied +23543,224,Male,Loyal Customer,35,Personal Travel,Eco,290,3,4,3,1,2,3,2,2,4,3,4,4,5,2,0,24.0,neutral or dissatisfied +23544,111143,Male,Loyal Customer,55,Business travel,Business,1577,4,4,5,4,3,5,1,5,5,5,5,3,5,5,72,52.0,satisfied +23545,108729,Male,Loyal Customer,49,Personal Travel,Eco,591,2,0,2,3,2,2,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +23546,35773,Male,disloyal Customer,38,Business travel,Eco,200,3,3,3,2,3,3,3,3,3,5,3,1,2,3,0,0.0,neutral or dissatisfied +23547,46384,Male,Loyal Customer,26,Business travel,Eco,1013,1,2,2,2,1,1,2,1,2,4,3,1,4,1,0,0.0,neutral or dissatisfied +23548,86484,Female,Loyal Customer,62,Personal Travel,Eco,853,1,4,1,3,3,4,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +23549,10408,Female,disloyal Customer,23,Business travel,Eco,429,4,5,4,4,4,4,4,4,4,2,5,4,5,4,0,1.0,neutral or dissatisfied +23550,86902,Male,Loyal Customer,40,Business travel,Business,352,4,4,4,4,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +23551,118708,Female,Loyal Customer,28,Personal Travel,Eco,621,2,2,1,3,1,1,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +23552,17896,Male,Loyal Customer,40,Personal Travel,Eco Plus,425,3,0,3,3,5,3,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +23553,415,Female,disloyal Customer,38,Business travel,Business,229,4,4,4,3,2,4,5,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +23554,124828,Female,Loyal Customer,60,Personal Travel,Eco,280,2,1,2,3,4,4,3,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +23555,82711,Female,Loyal Customer,19,Personal Travel,Eco,632,4,4,4,3,4,4,4,4,3,2,5,4,4,4,1,3.0,satisfied +23556,889,Male,disloyal Customer,17,Business travel,Eco,309,2,1,2,3,2,2,5,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +23557,68200,Male,Loyal Customer,52,Business travel,Business,3298,2,2,2,2,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +23558,57132,Male,Loyal Customer,27,Personal Travel,Eco,1530,3,4,3,1,3,3,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +23559,92807,Female,disloyal Customer,41,Business travel,Business,1541,3,3,3,5,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +23560,113218,Male,Loyal Customer,51,Business travel,Business,414,4,1,3,1,5,4,3,4,4,4,4,3,4,4,4,5.0,neutral or dissatisfied +23561,56607,Male,Loyal Customer,26,Business travel,Business,3106,5,4,4,4,5,4,5,5,3,2,4,4,3,5,43,75.0,neutral or dissatisfied +23562,45233,Female,Loyal Customer,43,Business travel,Business,613,4,5,5,5,2,3,3,4,4,4,4,4,4,1,6,19.0,neutral or dissatisfied +23563,101890,Male,disloyal Customer,21,Business travel,Business,2039,5,5,5,3,5,4,4,4,2,3,4,4,3,4,131,98.0,satisfied +23564,9637,Female,Loyal Customer,38,Business travel,Business,2554,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +23565,26210,Male,Loyal Customer,45,Business travel,Business,181,5,5,5,5,4,1,5,5,5,4,5,2,5,2,0,0.0,satisfied +23566,109557,Female,Loyal Customer,33,Personal Travel,Eco,834,2,2,2,4,4,2,4,4,3,2,3,3,3,4,33,32.0,neutral or dissatisfied +23567,26088,Male,disloyal Customer,25,Business travel,Eco,591,3,0,4,3,1,4,1,1,3,4,4,3,1,1,0,0.0,neutral or dissatisfied +23568,30723,Male,Loyal Customer,50,Business travel,Business,2499,2,2,2,2,2,3,3,3,5,4,5,3,4,3,160,164.0,satisfied +23569,79873,Female,Loyal Customer,16,Business travel,Business,3327,2,2,2,2,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +23570,125438,Female,Loyal Customer,43,Business travel,Eco Plus,735,3,1,1,1,1,1,2,3,3,3,3,4,3,4,0,6.0,neutral or dissatisfied +23571,115672,Female,Loyal Customer,61,Business travel,Eco,373,2,4,4,4,5,4,4,2,2,2,2,3,2,1,10,12.0,neutral or dissatisfied +23572,127695,Female,disloyal Customer,11,Business travel,Eco,2133,3,3,3,4,1,3,1,1,4,3,4,4,3,1,2,13.0,neutral or dissatisfied +23573,72493,Male,Loyal Customer,44,Business travel,Business,929,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +23574,119478,Male,disloyal Customer,15,Business travel,Eco,759,4,4,4,2,1,4,3,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +23575,107011,Male,Loyal Customer,26,Business travel,Eco Plus,937,2,4,4,4,2,4,2,1,3,4,3,2,3,2,147,151.0,neutral or dissatisfied +23576,17818,Male,Loyal Customer,40,Personal Travel,Eco,1214,3,1,3,3,1,3,1,1,1,3,4,3,3,1,0,0.0,neutral or dissatisfied +23577,79938,Male,Loyal Customer,7,Business travel,Business,1076,3,5,5,5,3,3,3,3,1,5,4,4,3,3,9,7.0,neutral or dissatisfied +23578,68251,Female,Loyal Customer,10,Personal Travel,Eco,631,5,5,5,2,5,5,5,5,4,5,4,5,5,5,0,0.0,satisfied +23579,25936,Male,Loyal Customer,28,Personal Travel,Eco,594,4,2,4,4,4,4,4,4,3,5,4,3,3,4,2,0.0,satisfied +23580,41342,Male,Loyal Customer,36,Business travel,Eco Plus,689,3,3,3,3,3,3,3,3,2,1,4,3,3,3,14,4.0,neutral or dissatisfied +23581,31938,Female,Loyal Customer,47,Business travel,Business,121,5,5,5,5,2,4,4,4,4,5,4,5,4,5,0,2.0,satisfied +23582,62065,Male,Loyal Customer,15,Personal Travel,Eco,2586,1,5,1,3,5,1,5,5,5,5,3,3,5,5,0,0.0,neutral or dissatisfied +23583,84758,Male,Loyal Customer,39,Business travel,Business,2195,4,4,3,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +23584,40388,Male,Loyal Customer,41,Business travel,Business,175,4,4,4,4,3,5,5,5,5,5,5,4,5,4,60,68.0,satisfied +23585,103552,Male,Loyal Customer,11,Personal Travel,Eco,738,2,4,2,3,4,2,4,4,3,3,4,5,5,4,8,4.0,neutral or dissatisfied +23586,62732,Male,Loyal Customer,39,Business travel,Business,2399,5,3,5,5,4,3,4,5,5,5,5,5,5,4,43,29.0,satisfied +23587,20831,Female,Loyal Customer,37,Business travel,Eco,508,4,1,1,1,4,4,4,4,2,2,5,4,5,4,0,0.0,satisfied +23588,42339,Male,Loyal Customer,31,Personal Travel,Eco,315,4,5,4,1,3,4,3,3,2,2,5,4,2,3,0,0.0,neutral or dissatisfied +23589,63037,Male,disloyal Customer,38,Business travel,Eco,453,1,4,1,3,3,1,3,3,2,3,4,1,4,3,8,2.0,neutral or dissatisfied +23590,21839,Female,Loyal Customer,55,Business travel,Business,3799,5,5,5,5,4,4,5,2,2,2,2,4,2,3,6,11.0,satisfied +23591,2672,Female,Loyal Customer,62,Personal Travel,Eco,539,3,2,3,3,3,4,4,3,3,3,2,4,3,2,42,39.0,neutral or dissatisfied +23592,53933,Male,Loyal Customer,33,Personal Travel,Eco Plus,191,2,3,2,3,5,2,5,5,1,2,2,1,2,5,0,0.0,neutral or dissatisfied +23593,79948,Female,disloyal Customer,60,Business travel,Eco,1005,3,3,3,4,3,2,2,3,3,4,3,2,4,2,142,171.0,neutral or dissatisfied +23594,70717,Female,disloyal Customer,42,Business travel,Business,675,3,3,3,5,3,3,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +23595,53849,Female,Loyal Customer,27,Business travel,Business,3018,1,1,1,1,5,5,3,5,5,1,2,3,4,5,0,0.0,satisfied +23596,38011,Female,Loyal Customer,29,Business travel,Business,3534,5,5,5,5,4,4,4,4,4,3,5,4,1,4,65,52.0,satisfied +23597,77848,Male,Loyal Customer,47,Business travel,Eco Plus,289,5,2,2,2,5,5,5,5,2,5,5,5,1,5,0,0.0,satisfied +23598,87743,Female,disloyal Customer,22,Business travel,Business,214,4,0,4,1,2,4,2,2,4,4,5,4,4,2,0,7.0,satisfied +23599,35247,Female,Loyal Customer,49,Business travel,Business,2784,3,3,3,3,3,3,4,4,4,4,4,5,4,3,5,0.0,satisfied +23600,25887,Male,Loyal Customer,64,Business travel,Business,2694,2,3,3,3,1,2,2,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +23601,44842,Female,Loyal Customer,52,Business travel,Business,3731,4,4,4,4,5,5,1,5,5,5,5,4,5,4,0,2.0,satisfied +23602,20916,Female,Loyal Customer,24,Business travel,Business,3798,1,2,2,2,1,1,1,2,5,3,4,1,1,1,177,167.0,neutral or dissatisfied +23603,89946,Male,Loyal Customer,23,Personal Travel,Eco,1416,4,4,4,1,4,4,4,4,3,2,5,4,5,4,0,11.0,neutral or dissatisfied +23604,50750,Female,Loyal Customer,62,Personal Travel,Eco,337,4,4,4,1,4,5,3,4,4,4,4,3,4,2,0,8.0,neutral or dissatisfied +23605,97109,Male,disloyal Customer,29,Business travel,Business,1476,5,5,5,4,4,5,4,4,4,5,4,4,4,4,3,0.0,satisfied +23606,77482,Female,disloyal Customer,24,Business travel,Business,1195,4,5,4,4,5,4,5,5,3,5,5,5,4,5,0,0.0,satisfied +23607,34721,Female,disloyal Customer,21,Business travel,Eco,264,4,0,4,1,1,4,1,1,4,5,2,5,4,1,0,0.0,satisfied +23608,50767,Female,Loyal Customer,56,Personal Travel,Eco,77,2,5,2,2,5,5,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +23609,15369,Male,Loyal Customer,32,Business travel,Business,1544,5,5,5,5,2,2,2,2,3,3,3,1,3,2,0,0.0,satisfied +23610,120500,Female,Loyal Customer,22,Business travel,Business,449,5,5,5,5,4,4,4,4,4,4,5,3,4,4,0,14.0,satisfied +23611,40997,Female,disloyal Customer,21,Business travel,Eco,1362,3,3,3,3,4,3,4,4,3,3,5,2,1,4,0,2.0,neutral or dissatisfied +23612,121434,Male,disloyal Customer,25,Business travel,Business,331,4,5,4,1,5,4,5,5,3,5,4,3,4,5,0,2.0,neutral or dissatisfied +23613,16958,Female,Loyal Customer,30,Business travel,Business,1131,4,4,4,4,5,5,5,4,1,3,2,5,3,5,231,268.0,satisfied +23614,83159,Female,Loyal Customer,57,Business travel,Business,1127,2,2,2,2,3,5,5,4,4,4,4,5,4,3,58,54.0,satisfied +23615,59556,Male,Loyal Customer,40,Business travel,Business,1879,5,5,5,5,4,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +23616,59648,Male,Loyal Customer,38,Business travel,Business,564,1,2,2,2,5,4,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +23617,54245,Female,Loyal Customer,56,Business travel,Business,1222,4,2,2,2,3,3,2,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +23618,87367,Female,disloyal Customer,28,Business travel,Business,448,1,1,1,4,3,1,3,3,5,4,4,3,5,3,9,6.0,neutral or dissatisfied +23619,46031,Female,Loyal Customer,29,Business travel,Business,991,1,1,1,1,4,4,4,4,4,1,4,2,3,4,0,0.0,satisfied +23620,72881,Male,Loyal Customer,51,Business travel,Business,1731,3,3,4,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +23621,16845,Female,Loyal Customer,46,Business travel,Eco Plus,645,5,2,2,2,3,4,4,5,5,5,5,4,5,2,0,0.0,satisfied +23622,10758,Male,Loyal Customer,48,Business travel,Business,3175,1,2,2,2,5,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +23623,60987,Female,disloyal Customer,39,Business travel,Eco Plus,488,1,1,1,3,2,1,2,2,1,2,3,4,4,2,9,11.0,neutral or dissatisfied +23624,93569,Male,Loyal Customer,47,Business travel,Business,3318,5,5,5,5,4,5,5,3,3,4,4,5,3,5,0,0.0,satisfied +23625,43606,Male,Loyal Customer,70,Business travel,Business,3768,2,3,3,3,3,3,2,2,2,2,2,4,2,3,0,8.0,neutral or dissatisfied +23626,49799,Male,Loyal Customer,60,Business travel,Eco,158,2,4,4,4,2,2,2,2,1,2,2,3,3,2,26,20.0,neutral or dissatisfied +23627,74866,Male,disloyal Customer,17,Business travel,Business,2239,5,3,5,5,1,5,1,1,4,5,4,4,5,1,0,0.0,satisfied +23628,66716,Female,Loyal Customer,36,Personal Travel,Eco,978,2,5,3,1,3,3,2,3,4,4,5,4,4,3,37,37.0,neutral or dissatisfied +23629,36162,Male,Loyal Customer,27,Business travel,Business,1674,3,3,3,3,4,4,4,4,4,1,3,4,4,4,0,0.0,satisfied +23630,89189,Female,Loyal Customer,45,Personal Travel,Eco,2139,0,4,0,1,2,5,5,1,1,0,1,5,1,4,0,0.0,satisfied +23631,112541,Female,Loyal Customer,46,Business travel,Business,3455,3,3,3,3,5,4,4,4,4,4,4,4,4,3,17,0.0,satisfied +23632,93162,Male,Loyal Customer,54,Personal Travel,Eco,1183,3,4,3,4,4,3,4,4,4,5,4,4,5,4,17,16.0,neutral or dissatisfied +23633,109329,Female,Loyal Customer,60,Personal Travel,Eco,1072,3,1,3,1,2,2,1,5,5,3,5,2,5,4,49,36.0,neutral or dissatisfied +23634,95284,Female,Loyal Customer,22,Personal Travel,Eco,248,0,5,0,3,4,0,4,4,3,3,4,5,4,4,6,5.0,satisfied +23635,122358,Male,Loyal Customer,50,Business travel,Eco,529,3,2,3,3,2,3,2,2,1,2,2,3,2,2,0,0.0,neutral or dissatisfied +23636,77770,Female,Loyal Customer,13,Personal Travel,Eco,874,2,2,2,4,2,2,2,2,2,1,3,3,3,2,4,0.0,neutral or dissatisfied +23637,73362,Female,Loyal Customer,50,Business travel,Eco,1012,3,1,1,1,2,4,4,3,3,3,3,1,3,4,128,121.0,neutral or dissatisfied +23638,35329,Female,Loyal Customer,43,Business travel,Eco,972,1,2,2,2,4,3,3,1,1,1,1,4,1,3,7,17.0,neutral or dissatisfied +23639,42274,Male,Loyal Customer,25,Business travel,Eco,817,4,3,3,3,4,4,3,4,4,4,2,5,3,4,0,0.0,satisfied +23640,27516,Female,Loyal Customer,45,Personal Travel,Eco,954,3,4,4,3,5,4,5,2,2,4,2,3,2,4,0,1.0,neutral or dissatisfied +23641,93602,Male,Loyal Customer,29,Business travel,Business,3382,4,4,4,4,5,5,5,5,3,5,5,3,5,5,19,7.0,satisfied +23642,87850,Male,Loyal Customer,53,Personal Travel,Eco,214,2,4,2,3,1,2,1,1,3,5,5,4,5,1,3,0.0,neutral or dissatisfied +23643,94183,Male,disloyal Customer,23,Business travel,Eco,562,3,0,4,3,4,4,4,4,5,5,4,5,4,4,12,11.0,neutral or dissatisfied +23644,83002,Male,disloyal Customer,35,Business travel,Business,1084,4,5,5,2,4,5,2,4,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +23645,98586,Male,Loyal Customer,39,Business travel,Business,1614,2,2,2,2,5,5,5,4,4,4,4,3,4,3,17,0.0,satisfied +23646,39347,Female,Loyal Customer,46,Business travel,Business,1739,1,1,1,1,2,4,5,5,5,5,5,4,5,4,34,96.0,satisfied +23647,115232,Female,disloyal Customer,39,Business travel,Business,417,5,0,0,5,5,0,5,5,4,3,5,4,4,5,2,0.0,satisfied +23648,116930,Female,Loyal Customer,53,Business travel,Business,304,5,5,5,5,5,4,4,5,5,5,5,3,5,5,3,0.0,satisfied +23649,16696,Male,Loyal Customer,63,Business travel,Business,2441,4,4,4,4,2,1,4,5,5,5,5,1,5,3,32,22.0,satisfied +23650,112417,Male,Loyal Customer,43,Business travel,Business,862,3,3,3,3,2,5,4,4,4,5,4,3,4,3,9,12.0,satisfied +23651,35956,Female,Loyal Customer,61,Business travel,Business,231,4,4,5,4,5,5,5,5,2,5,2,5,4,5,172,168.0,satisfied +23652,89511,Female,Loyal Customer,52,Business travel,Business,2853,5,5,2,5,3,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +23653,17160,Female,disloyal Customer,27,Business travel,Eco,643,2,0,2,2,3,2,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +23654,43468,Female,Loyal Customer,34,Business travel,Business,1975,2,2,2,2,3,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +23655,75382,Female,Loyal Customer,49,Business travel,Business,2342,2,2,2,2,5,3,5,5,5,5,5,4,5,5,0,10.0,satisfied +23656,126840,Female,Loyal Customer,50,Business travel,Business,2125,5,4,5,5,5,5,4,3,3,4,3,4,3,3,3,0.0,satisfied +23657,96702,Male,Loyal Customer,33,Business travel,Business,696,2,1,2,1,2,3,2,2,3,5,2,1,2,2,11,5.0,neutral or dissatisfied +23658,64255,Male,Loyal Customer,30,Personal Travel,Eco,1660,2,3,1,3,2,1,2,2,2,2,3,4,4,2,0,12.0,neutral or dissatisfied +23659,86688,Female,Loyal Customer,43,Business travel,Business,1747,2,2,2,2,5,3,4,4,4,4,4,5,4,3,1,0.0,satisfied +23660,61286,Female,Loyal Customer,61,Personal Travel,Eco,853,1,5,1,3,3,4,4,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +23661,2207,Female,Loyal Customer,57,Business travel,Business,3032,1,1,1,1,5,4,4,5,5,5,5,3,5,3,18,18.0,satisfied +23662,47939,Female,Loyal Customer,12,Personal Travel,Eco,726,1,3,1,3,3,1,3,3,5,4,5,4,2,3,0,0.0,neutral or dissatisfied +23663,52319,Female,disloyal Customer,30,Business travel,Business,493,4,4,4,1,1,4,1,1,2,2,1,2,2,1,0,0.0,neutral or dissatisfied +23664,74789,Male,Loyal Customer,33,Business travel,Business,3217,3,3,2,3,4,5,4,4,3,3,4,5,4,4,0,0.0,satisfied +23665,108090,Female,Loyal Customer,44,Business travel,Business,1166,3,3,3,3,2,4,5,4,4,4,4,5,4,4,5,27.0,satisfied +23666,35055,Male,disloyal Customer,23,Business travel,Eco,972,1,1,1,1,4,1,1,4,4,2,5,3,5,4,37,49.0,neutral or dissatisfied +23667,34639,Female,Loyal Customer,49,Business travel,Business,2023,3,5,5,5,3,3,4,3,3,3,3,2,3,3,0,19.0,neutral or dissatisfied +23668,78781,Male,disloyal Customer,23,Business travel,Eco,554,1,2,2,4,5,2,5,5,3,5,3,1,4,5,0,0.0,neutral or dissatisfied +23669,121767,Male,Loyal Customer,58,Business travel,Business,337,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,28.0,satisfied +23670,123002,Female,Loyal Customer,31,Business travel,Business,2788,3,3,2,3,5,5,5,5,3,2,4,4,4,5,0,5.0,satisfied +23671,50458,Female,Loyal Customer,30,Business travel,Business,110,0,5,0,4,4,4,4,4,3,3,1,5,3,4,0,3.0,satisfied +23672,25687,Male,disloyal Customer,33,Business travel,Eco,432,2,0,2,2,1,2,1,1,4,2,2,3,4,1,0,0.0,neutral or dissatisfied +23673,1183,Male,Loyal Customer,60,Personal Travel,Eco,158,0,4,0,3,2,0,2,2,3,4,5,4,4,2,0,5.0,satisfied +23674,5419,Male,Loyal Customer,19,Business travel,Business,1787,2,5,5,5,2,2,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +23675,48699,Female,Loyal Customer,51,Business travel,Business,158,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +23676,102017,Male,Loyal Customer,47,Business travel,Business,1833,4,4,4,4,3,4,5,4,4,5,4,4,4,5,2,0.0,satisfied +23677,84730,Male,disloyal Customer,22,Business travel,Eco,481,1,0,1,2,4,1,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +23678,81943,Female,Loyal Customer,55,Business travel,Business,1535,3,5,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +23679,115443,Male,Loyal Customer,42,Business travel,Business,2023,3,3,3,3,4,4,4,3,3,3,3,1,3,4,51,51.0,neutral or dissatisfied +23680,27850,Male,Loyal Customer,49,Personal Travel,Eco,680,2,5,2,1,5,2,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +23681,72595,Female,Loyal Customer,20,Personal Travel,Eco,964,4,5,4,3,2,4,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +23682,107273,Male,Loyal Customer,43,Business travel,Business,2018,3,2,2,2,4,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +23683,28211,Male,Loyal Customer,47,Personal Travel,Eco,550,4,0,4,1,4,4,4,4,3,3,5,3,4,4,0,0.0,satisfied +23684,53426,Female,Loyal Customer,32,Business travel,Business,2253,4,4,5,4,5,5,5,5,5,5,4,3,4,5,0,26.0,satisfied +23685,34352,Female,Loyal Customer,17,Business travel,Business,2576,5,1,5,5,4,4,4,4,3,3,5,5,4,4,0,0.0,satisfied +23686,34243,Male,Loyal Customer,63,Personal Travel,Eco Plus,1189,1,4,2,3,3,2,3,3,3,4,5,3,5,3,16,6.0,neutral or dissatisfied +23687,43090,Male,Loyal Customer,26,Personal Travel,Eco,391,3,5,3,3,2,3,2,2,5,5,3,3,4,2,4,0.0,neutral or dissatisfied +23688,58541,Male,disloyal Customer,21,Business travel,Eco,737,2,2,2,2,1,2,1,1,3,2,3,4,2,1,10,29.0,neutral or dissatisfied +23689,90024,Male,Loyal Customer,40,Business travel,Business,2561,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +23690,92391,Female,Loyal Customer,23,Business travel,Business,1947,1,1,1,1,5,5,5,5,5,5,4,3,4,5,96,92.0,satisfied +23691,91531,Female,Loyal Customer,54,Business travel,Business,3295,3,3,3,3,4,4,5,5,5,5,5,3,5,5,3,0.0,satisfied +23692,59104,Male,Loyal Customer,16,Personal Travel,Eco,1846,3,4,3,4,4,3,4,4,4,2,3,4,5,4,37,17.0,neutral or dissatisfied +23693,56602,Male,Loyal Customer,26,Business travel,Business,3454,2,2,2,2,2,2,2,2,2,3,2,3,1,2,2,24.0,neutral or dissatisfied +23694,67287,Male,Loyal Customer,13,Personal Travel,Eco,985,1,4,1,5,4,1,3,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +23695,124343,Male,disloyal Customer,41,Business travel,Eco,637,3,0,2,4,5,2,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +23696,124450,Male,disloyal Customer,29,Business travel,Business,980,4,4,4,5,1,4,1,1,5,3,4,4,5,1,0,0.0,satisfied +23697,4273,Female,disloyal Customer,29,Business travel,Eco,502,2,3,1,3,1,1,1,1,4,5,3,3,3,1,38,41.0,neutral or dissatisfied +23698,86617,Male,Loyal Customer,52,Business travel,Business,2861,4,4,4,4,4,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +23699,68904,Male,Loyal Customer,29,Personal Travel,Eco,1061,3,5,3,3,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +23700,45606,Male,disloyal Customer,24,Business travel,Eco,113,5,0,4,1,5,4,5,5,4,4,4,5,1,5,30,37.0,satisfied +23701,79611,Female,Loyal Customer,51,Business travel,Business,3364,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +23702,55521,Female,Loyal Customer,29,Personal Travel,Eco,991,1,1,1,2,5,1,5,5,3,4,2,2,3,5,0,0.0,neutral or dissatisfied +23703,20309,Male,Loyal Customer,49,Business travel,Eco Plus,622,5,2,2,2,5,5,5,5,1,5,1,2,3,5,4,11.0,satisfied +23704,17620,Male,Loyal Customer,25,Business travel,Eco,622,2,3,3,3,2,2,3,2,3,4,4,2,4,2,0,24.0,neutral or dissatisfied +23705,125998,Male,Loyal Customer,52,Personal Travel,Business,468,3,5,3,3,2,5,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +23706,12189,Male,Loyal Customer,68,Personal Travel,Eco,1075,1,4,0,3,2,0,2,2,3,1,3,3,4,2,2,0.0,neutral or dissatisfied +23707,64709,Male,Loyal Customer,54,Business travel,Business,469,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +23708,7785,Female,Loyal Customer,28,Personal Travel,Business,710,4,5,4,4,2,4,1,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +23709,1823,Female,Loyal Customer,58,Business travel,Business,3585,5,5,5,5,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +23710,122046,Female,disloyal Customer,17,Business travel,Eco,130,0,0,0,3,5,0,5,5,4,5,4,4,5,5,0,0.0,satisfied +23711,93496,Female,Loyal Customer,60,Business travel,Business,1107,5,5,5,5,4,4,4,5,5,5,5,3,5,5,80,83.0,satisfied +23712,71908,Female,Loyal Customer,59,Personal Travel,Eco,1744,1,1,1,2,4,2,3,2,2,1,5,2,2,1,5,0.0,neutral or dissatisfied +23713,31446,Female,Loyal Customer,45,Business travel,Business,1823,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +23714,126114,Female,Loyal Customer,24,Business travel,Eco,650,2,2,2,2,2,3,3,2,2,2,3,1,4,2,0,6.0,neutral or dissatisfied +23715,118520,Female,Loyal Customer,49,Business travel,Business,3797,3,2,2,2,5,3,3,3,3,3,3,4,3,2,2,2.0,neutral or dissatisfied +23716,37079,Female,Loyal Customer,50,Business travel,Business,1237,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +23717,53356,Male,Loyal Customer,27,Business travel,Business,1452,1,1,5,1,2,2,2,2,2,4,2,2,4,2,99,89.0,satisfied +23718,4343,Female,Loyal Customer,36,Business travel,Business,3131,4,4,4,4,4,4,4,5,5,5,5,3,5,4,41,116.0,satisfied +23719,107451,Female,disloyal Customer,23,Business travel,Business,468,0,4,0,1,2,0,2,2,3,3,5,4,5,2,0,1.0,satisfied +23720,19952,Female,Loyal Customer,41,Personal Travel,Eco,315,4,1,2,2,3,2,3,3,4,3,2,3,2,3,8,0.0,satisfied +23721,21879,Male,Loyal Customer,35,Business travel,Business,2381,2,2,2,2,2,2,3,4,4,5,4,2,4,4,0,0.0,satisfied +23722,70317,Male,Loyal Customer,41,Business travel,Business,1501,1,1,1,1,3,5,4,5,5,5,5,4,5,3,5,33.0,satisfied +23723,81869,Female,Loyal Customer,46,Business travel,Business,1050,3,3,3,3,5,5,5,4,4,4,4,5,4,3,27,53.0,satisfied +23724,63917,Male,Loyal Customer,55,Business travel,Business,3267,3,3,3,3,4,4,4,4,4,4,4,2,4,4,0,0.0,satisfied +23725,100759,Female,Loyal Customer,13,Personal Travel,Business,1411,2,2,2,3,5,2,5,5,4,5,3,4,3,5,5,12.0,neutral or dissatisfied +23726,74613,Male,Loyal Customer,41,Business travel,Business,3594,1,1,1,1,2,5,2,5,5,5,5,2,5,1,0,0.0,satisfied +23727,21365,Female,Loyal Customer,62,Personal Travel,Eco Plus,761,3,5,3,1,2,5,5,3,3,3,2,4,3,5,105,117.0,neutral or dissatisfied +23728,117691,Male,disloyal Customer,50,Business travel,Eco,575,3,3,3,4,4,3,4,4,5,3,4,2,1,4,6,0.0,neutral or dissatisfied +23729,125043,Male,Loyal Customer,13,Personal Travel,Eco,2300,5,5,4,4,3,4,3,3,4,5,4,3,4,3,2,0.0,satisfied +23730,31998,Male,Loyal Customer,21,Personal Travel,Business,101,2,4,2,2,1,2,1,1,2,2,5,2,1,1,0,0.0,neutral or dissatisfied +23731,76028,Male,Loyal Customer,55,Personal Travel,Eco,237,4,5,4,3,4,4,2,4,5,4,5,4,4,4,10,0.0,neutral or dissatisfied +23732,27953,Male,Loyal Customer,46,Business travel,Business,1660,2,5,5,5,5,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +23733,47372,Male,Loyal Customer,28,Business travel,Business,2024,4,4,2,4,5,5,5,5,2,5,2,3,4,5,0,0.0,satisfied +23734,82806,Female,Loyal Customer,42,Business travel,Eco,235,3,5,5,5,3,4,4,3,3,3,3,3,3,2,0,8.0,neutral or dissatisfied +23735,123694,Female,Loyal Customer,11,Personal Travel,Eco,214,5,0,5,4,4,5,4,4,4,3,4,4,4,4,0,0.0,satisfied +23736,7587,Male,Loyal Customer,27,Personal Travel,Eco,594,1,4,2,3,5,2,5,5,2,1,1,5,1,5,0,0.0,neutral or dissatisfied +23737,39454,Male,Loyal Customer,40,Personal Travel,Eco,129,1,0,1,1,1,1,1,1,4,5,5,4,4,1,0,1.0,neutral or dissatisfied +23738,110269,Female,Loyal Customer,41,Business travel,Business,3380,3,3,3,3,5,4,4,4,4,4,4,5,4,5,28,32.0,satisfied +23739,44883,Male,Loyal Customer,62,Personal Travel,Eco Plus,315,2,4,2,5,4,2,4,4,5,2,4,5,3,4,11,6.0,neutral or dissatisfied +23740,129631,Female,disloyal Customer,35,Business travel,Business,337,2,1,1,2,2,1,2,2,3,2,4,4,4,2,61,53.0,neutral or dissatisfied +23741,71307,Female,disloyal Customer,30,Business travel,Business,1514,4,4,4,4,2,4,5,2,3,4,5,3,5,2,0,0.0,satisfied +23742,26520,Female,Loyal Customer,54,Business travel,Business,2936,3,3,3,3,5,3,1,5,5,5,5,3,5,4,0,0.0,satisfied +23743,19075,Female,Loyal Customer,38,Business travel,Eco,169,5,2,2,2,5,5,5,5,2,4,1,5,2,5,0,0.0,satisfied +23744,17786,Female,Loyal Customer,36,Business travel,Eco,1075,2,5,5,5,2,2,2,2,5,1,4,1,1,2,0,0.0,satisfied +23745,84896,Male,Loyal Customer,63,Personal Travel,Eco,516,4,4,3,3,3,3,5,3,4,4,4,3,4,3,3,0.0,neutral or dissatisfied +23746,13498,Male,Loyal Customer,59,Business travel,Business,2268,5,5,5,5,5,1,2,4,4,4,4,5,4,2,87,85.0,satisfied +23747,59035,Female,disloyal Customer,36,Business travel,Business,1846,2,2,2,4,4,2,4,4,3,2,3,3,4,4,2,15.0,neutral or dissatisfied +23748,98354,Male,Loyal Customer,12,Business travel,Eco,1189,4,1,1,1,4,4,3,4,4,4,4,1,3,4,0,0.0,neutral or dissatisfied +23749,17862,Male,disloyal Customer,25,Business travel,Eco,399,2,0,2,1,5,2,3,5,3,4,2,2,5,5,0,0.0,neutral or dissatisfied +23750,106809,Female,Loyal Customer,35,Business travel,Business,1488,4,4,4,4,3,4,5,5,5,5,5,4,5,5,2,0.0,satisfied +23751,103808,Female,disloyal Customer,18,Business travel,Business,979,4,0,4,3,2,4,5,2,3,4,4,5,5,2,29,21.0,satisfied +23752,59051,Female,disloyal Customer,39,Business travel,Business,907,5,5,5,2,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +23753,71231,Female,Loyal Customer,25,Business travel,Business,733,4,4,4,4,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +23754,31305,Female,Loyal Customer,44,Business travel,Eco,680,3,5,1,5,3,1,3,3,3,3,3,4,3,4,0,0.0,satisfied +23755,123877,Male,disloyal Customer,24,Business travel,Eco,141,1,4,1,1,4,1,4,4,2,4,5,2,4,4,0,0.0,neutral or dissatisfied +23756,74199,Female,Loyal Customer,40,Business travel,Business,3821,4,4,4,4,5,5,5,3,3,3,3,4,3,3,0,4.0,satisfied +23757,83864,Female,Loyal Customer,10,Personal Travel,Eco,425,5,0,5,2,4,5,4,4,4,5,5,5,4,4,0,0.0,satisfied +23758,8277,Female,Loyal Customer,45,Personal Travel,Eco,335,5,5,5,3,3,4,4,2,2,5,2,4,2,5,0,0.0,satisfied +23759,61447,Female,disloyal Customer,30,Business travel,Business,832,4,3,3,4,2,3,2,2,4,2,4,4,5,2,0,0.0,satisfied +23760,92944,Female,Loyal Customer,13,Personal Travel,Eco,151,2,5,2,4,5,2,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +23761,32951,Female,Loyal Customer,70,Personal Travel,Eco,101,2,5,2,5,3,5,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +23762,11614,Male,Loyal Customer,60,Personal Travel,Eco,657,3,5,3,4,1,3,1,1,3,2,5,3,2,1,0,0.0,neutral or dissatisfied +23763,22204,Male,Loyal Customer,70,Personal Travel,Eco,533,3,4,3,5,3,3,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +23764,127862,Male,Loyal Customer,47,Business travel,Business,1276,5,5,5,5,5,5,5,4,4,4,4,5,4,5,0,7.0,satisfied +23765,101279,Female,Loyal Customer,40,Business travel,Business,1612,4,4,2,4,4,4,4,4,4,5,4,3,4,3,1,1.0,satisfied +23766,36027,Female,Loyal Customer,46,Business travel,Eco,399,2,2,2,2,1,2,3,2,2,2,2,4,2,2,0,0.0,satisfied +23767,80378,Male,Loyal Customer,44,Business travel,Business,2950,3,1,1,1,4,3,3,3,3,3,3,3,3,2,2,3.0,neutral or dissatisfied +23768,3516,Female,Loyal Customer,32,Business travel,Business,1763,2,2,2,2,4,4,4,4,3,2,5,4,5,4,0,0.0,satisfied +23769,70768,Female,Loyal Customer,40,Business travel,Business,328,0,0,0,3,3,5,4,2,2,2,2,5,2,3,16,16.0,satisfied +23770,101833,Female,Loyal Customer,27,Personal Travel,Eco,1521,3,1,3,4,3,3,3,3,4,3,2,1,3,3,44,36.0,neutral or dissatisfied +23771,88466,Female,Loyal Customer,27,Business travel,Eco,270,4,2,2,2,4,4,4,4,2,3,2,2,4,4,0,17.0,satisfied +23772,71791,Female,disloyal Customer,24,Business travel,Eco,1265,3,3,3,2,5,3,4,5,5,5,5,5,5,5,4,29.0,neutral or dissatisfied +23773,60920,Male,disloyal Customer,39,Business travel,Business,888,1,1,1,1,5,1,5,5,5,3,4,5,4,5,0,4.0,neutral or dissatisfied +23774,45212,Female,Loyal Customer,50,Business travel,Eco,1013,2,3,5,3,2,2,1,2,2,2,2,3,2,5,0,3.0,satisfied +23775,12551,Female,Loyal Customer,29,Personal Travel,Eco,788,2,5,1,1,5,1,5,5,5,3,5,4,5,5,31,24.0,neutral or dissatisfied +23776,30318,Female,Loyal Customer,49,Business travel,Eco,391,5,4,4,4,4,1,1,5,5,5,5,4,5,3,6,0.0,satisfied +23777,14638,Female,Loyal Customer,41,Business travel,Eco,948,2,2,2,2,2,2,2,2,1,1,3,1,3,2,74,55.0,neutral or dissatisfied +23778,22992,Male,Loyal Customer,10,Personal Travel,Eco,489,2,5,2,3,1,2,1,1,5,2,3,1,3,1,0,6.0,neutral or dissatisfied +23779,44194,Male,Loyal Customer,31,Business travel,Eco,157,3,1,1,1,3,3,3,3,1,4,2,4,2,3,9,10.0,neutral or dissatisfied +23780,8913,Female,disloyal Customer,39,Business travel,Business,510,5,5,5,1,4,5,4,4,3,5,4,5,4,4,0,0.0,satisfied +23781,31706,Female,Loyal Customer,37,Personal Travel,Eco,862,3,4,3,1,4,3,4,4,4,4,2,3,4,4,0,0.0,neutral or dissatisfied +23782,69939,Male,Loyal Customer,57,Business travel,Business,2174,4,4,4,4,4,5,4,2,2,2,2,3,2,5,8,0.0,satisfied +23783,12177,Male,Loyal Customer,50,Business travel,Eco,1075,2,3,3,3,2,1,1,4,4,4,4,1,3,1,172,154.0,neutral or dissatisfied +23784,65961,Male,Loyal Customer,41,Business travel,Business,1372,2,2,2,2,3,5,4,3,3,4,3,5,3,4,6,0.0,satisfied +23785,32141,Male,Loyal Customer,37,Business travel,Eco,102,4,1,1,1,4,4,4,4,3,1,3,3,2,4,0,8.0,satisfied +23786,106245,Male,disloyal Customer,21,Business travel,Eco,1167,2,2,2,3,5,2,5,5,4,4,4,5,4,5,0,0.0,satisfied +23787,20432,Male,Loyal Customer,33,Business travel,Eco Plus,196,0,0,0,4,1,0,1,1,2,5,2,5,4,1,0,0.0,satisfied +23788,56292,Male,disloyal Customer,27,Business travel,Eco,727,2,2,2,5,4,2,4,4,1,2,5,3,5,4,0,0.0,neutral or dissatisfied +23789,127068,Male,disloyal Customer,23,Business travel,Eco,647,3,3,3,3,5,3,5,5,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +23790,96320,Female,Loyal Customer,45,Business travel,Business,2605,3,3,5,3,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +23791,47286,Female,Loyal Customer,25,Business travel,Business,1793,3,3,3,3,5,4,5,5,3,1,2,3,5,5,0,1.0,satisfied +23792,119796,Male,disloyal Customer,9,Business travel,Eco,936,4,4,4,3,3,4,3,3,1,2,3,2,3,3,7,30.0,neutral or dissatisfied +23793,91044,Male,Loyal Customer,9,Personal Travel,Eco,515,3,4,3,4,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +23794,107025,Female,disloyal Customer,36,Business travel,Eco,395,1,2,1,3,3,1,3,3,3,5,3,4,3,3,12,21.0,neutral or dissatisfied +23795,7631,Female,Loyal Customer,57,Business travel,Business,604,1,1,1,1,3,4,4,5,5,5,5,5,5,3,30,30.0,satisfied +23796,36788,Female,disloyal Customer,26,Business travel,Eco,1026,2,2,2,2,2,5,5,3,2,2,4,5,1,5,0,0.0,neutral or dissatisfied +23797,121660,Male,Loyal Customer,39,Business travel,Business,328,1,1,1,1,4,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +23798,77000,Female,Loyal Customer,45,Business travel,Business,3948,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +23799,36372,Female,Loyal Customer,55,Business travel,Business,200,1,1,1,1,4,3,4,4,4,4,5,3,4,3,37,31.0,satisfied +23800,113048,Female,disloyal Customer,23,Business travel,Eco,543,1,0,1,4,1,1,1,1,4,5,5,4,4,1,11,8.0,neutral or dissatisfied +23801,5442,Female,disloyal Customer,23,Business travel,Business,265,0,0,0,5,3,0,1,3,3,2,5,4,4,3,0,0.0,satisfied +23802,45136,Male,Loyal Customer,56,Business travel,Eco,174,5,5,5,5,5,5,5,5,4,4,2,2,3,5,0,1.0,satisfied +23803,56250,Male,Loyal Customer,47,Business travel,Business,404,1,1,1,1,4,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +23804,86273,Female,Loyal Customer,34,Personal Travel,Eco,356,2,4,2,4,1,2,1,1,3,4,4,3,4,1,14,34.0,neutral or dissatisfied +23805,84608,Female,Loyal Customer,9,Business travel,Business,2672,3,4,4,4,3,3,3,3,4,1,4,2,4,3,19,12.0,neutral or dissatisfied +23806,89549,Male,disloyal Customer,36,Business travel,Business,1076,2,2,2,1,4,2,4,4,3,4,5,4,5,4,83,67.0,neutral or dissatisfied +23807,5253,Male,disloyal Customer,26,Business travel,Eco,383,2,2,2,3,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +23808,1109,Female,Loyal Customer,20,Personal Travel,Eco,113,1,2,1,3,3,1,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +23809,16711,Female,Loyal Customer,47,Personal Travel,Eco,284,1,5,1,2,4,4,4,5,5,1,5,4,5,3,3,1.0,neutral or dissatisfied +23810,80485,Female,Loyal Customer,41,Business travel,Eco Plus,1299,2,4,4,4,2,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +23811,20364,Male,Loyal Customer,31,Personal Travel,Eco,265,3,5,3,4,4,3,4,4,3,2,5,4,2,4,0,0.0,neutral or dissatisfied +23812,34605,Female,Loyal Customer,30,Personal Travel,Eco,1598,5,5,5,4,4,5,4,4,4,4,5,4,5,4,0,0.0,satisfied +23813,75386,Female,Loyal Customer,55,Business travel,Business,2585,4,4,4,4,5,5,4,3,3,4,3,5,3,4,19,0.0,satisfied +23814,55504,Male,Loyal Customer,69,Business travel,Eco Plus,239,3,4,4,4,3,3,3,3,3,4,3,4,2,3,18,1.0,satisfied +23815,93669,Female,Loyal Customer,51,Business travel,Eco,655,2,5,5,5,5,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +23816,31422,Male,Loyal Customer,60,Business travel,Business,1703,2,4,4,4,4,3,4,2,2,2,2,2,2,1,6,42.0,neutral or dissatisfied +23817,63556,Male,Loyal Customer,55,Business travel,Eco Plus,1009,1,3,3,3,1,1,1,1,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +23818,49856,Male,disloyal Customer,41,Business travel,Eco,304,4,0,4,2,5,4,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +23819,40225,Female,Loyal Customer,70,Business travel,Business,2816,1,1,2,1,2,2,2,4,4,4,4,5,4,2,0,0.0,satisfied +23820,112144,Male,Loyal Customer,48,Business travel,Business,895,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +23821,97600,Male,disloyal Customer,23,Business travel,Eco,442,2,2,2,4,4,2,4,4,4,3,4,3,3,4,0,0.0,neutral or dissatisfied +23822,13015,Female,Loyal Customer,53,Business travel,Business,374,3,1,1,1,2,3,4,3,3,3,3,4,3,3,0,7.0,neutral or dissatisfied +23823,28381,Female,disloyal Customer,26,Business travel,Eco,763,3,3,3,4,1,3,2,1,1,5,3,4,2,1,0,0.0,neutral or dissatisfied +23824,37250,Male,Loyal Customer,22,Personal Travel,Business,1069,2,5,2,2,4,2,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +23825,105106,Male,Loyal Customer,54,Business travel,Business,1866,0,0,0,3,3,4,5,4,4,1,1,5,4,3,6,0.0,satisfied +23826,57908,Female,Loyal Customer,9,Personal Travel,Eco,305,5,5,5,5,3,5,2,3,3,5,5,4,4,3,0,0.0,satisfied +23827,51656,Female,disloyal Customer,22,Business travel,Eco,598,2,5,2,2,4,2,4,4,3,3,3,2,5,4,0,0.0,neutral or dissatisfied +23828,35093,Female,Loyal Customer,50,Business travel,Eco,1080,4,4,4,4,4,2,3,4,4,4,4,2,4,2,0,0.0,satisfied +23829,22818,Female,disloyal Customer,40,Business travel,Business,170,2,2,2,3,1,2,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +23830,50524,Male,Loyal Customer,45,Personal Travel,Eco,373,2,4,2,3,4,2,4,4,2,1,4,2,3,4,0,0.0,neutral or dissatisfied +23831,68215,Male,Loyal Customer,49,Business travel,Business,432,5,5,5,5,3,4,4,3,3,4,3,4,3,3,23,4.0,satisfied +23832,114618,Female,Loyal Customer,39,Business travel,Business,3415,5,5,5,5,5,5,5,5,5,5,5,3,5,5,28,25.0,satisfied +23833,125092,Male,Loyal Customer,53,Business travel,Business,361,3,2,2,2,1,3,3,3,3,3,3,4,3,2,19,24.0,neutral or dissatisfied +23834,42424,Female,Loyal Customer,14,Personal Travel,Eco Plus,834,3,5,3,4,3,3,3,3,5,5,4,3,5,3,2,4.0,neutral or dissatisfied +23835,99254,Female,disloyal Customer,25,Business travel,Business,495,5,3,5,3,1,5,1,1,4,2,4,3,5,1,5,0.0,satisfied +23836,114665,Female,Loyal Customer,55,Business travel,Business,325,2,2,2,2,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +23837,103247,Female,Loyal Customer,42,Business travel,Business,2678,3,3,3,3,2,5,5,3,3,3,3,4,3,4,6,0.0,satisfied +23838,67153,Female,Loyal Customer,44,Business travel,Eco,1119,3,4,2,4,1,3,3,3,3,3,3,1,3,4,0,48.0,neutral or dissatisfied +23839,891,Female,Loyal Customer,51,Business travel,Business,134,1,1,1,1,3,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +23840,22617,Male,Loyal Customer,10,Personal Travel,Eco,646,3,4,3,3,2,3,2,2,3,2,1,2,1,2,93,88.0,neutral or dissatisfied +23841,68166,Female,Loyal Customer,47,Business travel,Business,2946,3,3,3,3,2,5,5,2,2,3,2,4,2,3,0,0.0,satisfied +23842,56713,Female,Loyal Customer,13,Personal Travel,Eco,1065,5,5,5,1,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +23843,113494,Female,Loyal Customer,42,Business travel,Business,2408,1,1,1,1,5,5,4,5,5,5,5,5,5,3,5,0.0,satisfied +23844,10947,Male,Loyal Customer,66,Business travel,Business,312,1,3,3,3,4,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +23845,58313,Female,Loyal Customer,30,Business travel,Business,1739,1,1,1,1,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +23846,86572,Male,Loyal Customer,52,Business travel,Business,1718,3,3,1,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +23847,108906,Female,Loyal Customer,48,Business travel,Business,3216,1,2,2,2,3,4,3,1,1,1,1,1,1,1,4,0.0,neutral or dissatisfied +23848,104858,Male,Loyal Customer,38,Business travel,Business,3845,5,1,5,5,4,5,5,4,3,4,4,5,4,5,253,253.0,satisfied +23849,9553,Female,Loyal Customer,47,Business travel,Business,3782,5,5,5,5,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +23850,53438,Female,disloyal Customer,23,Business travel,Eco,964,4,4,4,5,2,4,2,2,2,4,4,2,3,2,0,0.0,satisfied +23851,34514,Male,Loyal Customer,70,Personal Travel,Eco,1428,2,4,2,4,5,2,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +23852,124160,Female,disloyal Customer,26,Business travel,Business,2133,3,3,3,1,2,3,4,2,3,5,5,3,5,2,0,1.0,neutral or dissatisfied +23853,62513,Male,Loyal Customer,29,Business travel,Business,1846,4,4,4,4,5,5,5,5,5,2,4,3,4,5,6,1.0,satisfied +23854,21130,Female,Loyal Customer,46,Personal Travel,Eco,152,3,4,3,4,3,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +23855,96802,Male,Loyal Customer,33,Business travel,Business,1847,3,3,3,3,4,4,4,4,3,3,4,5,5,4,9,0.0,satisfied +23856,84955,Male,Loyal Customer,25,Business travel,Business,1519,4,4,4,4,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +23857,81537,Female,Loyal Customer,48,Personal Travel,Eco,1124,4,5,4,2,4,4,5,2,2,4,2,4,2,4,0,2.0,satisfied +23858,116044,Male,Loyal Customer,28,Personal Travel,Eco,371,2,5,5,1,1,5,2,1,4,2,3,3,2,1,49,30.0,neutral or dissatisfied +23859,50782,Female,Loyal Customer,44,Personal Travel,Eco,153,2,4,2,3,5,5,4,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +23860,12935,Male,Loyal Customer,42,Personal Travel,Eco,359,1,5,1,2,4,1,5,4,3,3,4,4,5,4,7,2.0,neutral or dissatisfied +23861,72617,Male,Loyal Customer,7,Personal Travel,Eco,985,3,4,2,4,2,2,2,2,3,3,5,3,5,2,42,47.0,neutral or dissatisfied +23862,21296,Male,Loyal Customer,27,Business travel,Business,692,4,4,4,4,4,4,4,4,2,1,4,4,4,4,0,0.0,neutral or dissatisfied +23863,103950,Female,Loyal Customer,56,Business travel,Business,370,4,4,4,4,2,2,2,5,5,5,5,5,5,3,7,6.0,satisfied +23864,66933,Male,disloyal Customer,38,Business travel,Business,1121,4,4,4,4,3,4,3,3,3,4,4,3,4,3,5,0.0,satisfied +23865,59383,Male,Loyal Customer,47,Personal Travel,Eco,2367,3,4,3,1,4,3,1,4,3,2,4,4,5,4,19,0.0,neutral or dissatisfied +23866,112075,Female,disloyal Customer,23,Business travel,Eco,1491,4,5,5,1,3,4,3,3,5,2,4,3,4,3,33,26.0,neutral or dissatisfied +23867,86249,Male,Loyal Customer,31,Personal Travel,Eco,226,3,4,3,1,2,3,2,2,4,2,5,4,4,2,18,14.0,neutral or dissatisfied +23868,104853,Male,Loyal Customer,32,Business travel,Business,1740,2,2,2,2,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +23869,104570,Female,Loyal Customer,39,Business travel,Business,369,2,2,2,2,5,5,4,3,3,3,3,5,3,4,20,20.0,satisfied +23870,21893,Male,Loyal Customer,51,Business travel,Business,3060,5,5,5,5,5,2,3,5,5,5,5,4,5,2,0,0.0,satisfied +23871,75405,Male,disloyal Customer,71,Business travel,Business,2330,4,4,4,2,5,4,1,5,4,2,5,5,5,5,4,5.0,satisfied +23872,77552,Male,Loyal Customer,51,Personal Travel,Eco,986,5,5,5,5,3,5,3,3,5,5,5,5,4,3,0,2.0,satisfied +23873,70609,Male,Loyal Customer,60,Business travel,Business,2611,4,4,4,4,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +23874,110164,Female,Loyal Customer,59,Personal Travel,Eco,869,3,1,3,1,1,1,1,3,3,3,3,2,3,1,16,12.0,neutral or dissatisfied +23875,82898,Male,Loyal Customer,46,Personal Travel,Eco,645,1,4,1,3,4,1,4,4,3,4,4,5,3,4,0,6.0,neutral or dissatisfied +23876,13805,Female,Loyal Customer,49,Business travel,Business,3528,4,4,4,4,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +23877,23642,Male,disloyal Customer,45,Business travel,Eco Plus,793,3,3,3,2,5,3,5,5,4,2,1,4,1,5,17,1.0,neutral or dissatisfied +23878,97502,Female,Loyal Customer,32,Personal Travel,Eco,822,1,5,1,4,2,1,2,2,4,4,4,3,4,2,21,34.0,neutral or dissatisfied +23879,18682,Male,Loyal Customer,53,Personal Travel,Eco,262,3,5,3,3,3,3,3,3,3,2,1,4,1,3,0,0.0,neutral or dissatisfied +23880,38844,Male,Loyal Customer,33,Business travel,Eco Plus,353,0,0,0,4,5,0,5,5,1,4,4,3,2,5,0,0.0,satisfied +23881,57515,Male,Loyal Customer,14,Personal Travel,Eco,137,2,0,2,1,3,2,3,3,4,5,3,1,5,3,0,0.0,neutral or dissatisfied +23882,6083,Female,Loyal Customer,57,Business travel,Business,630,4,4,4,4,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +23883,82407,Male,Loyal Customer,54,Personal Travel,Eco,500,2,2,2,3,4,2,4,4,4,4,3,1,3,4,7,0.0,neutral or dissatisfied +23884,69082,Male,Loyal Customer,50,Personal Travel,Eco,1389,1,3,1,4,2,1,2,2,2,5,2,4,4,2,0,0.0,neutral or dissatisfied +23885,53089,Female,Loyal Customer,55,Personal Travel,Eco,2327,0,5,0,1,3,5,5,5,5,5,3,3,5,3,0,0.0,satisfied +23886,47835,Female,disloyal Customer,26,Business travel,Eco,834,2,2,2,1,5,2,5,5,2,3,1,1,2,5,0,0.0,neutral or dissatisfied +23887,118982,Female,Loyal Customer,42,Business travel,Business,2773,2,2,2,2,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +23888,117262,Female,Loyal Customer,52,Personal Travel,Eco,304,2,5,2,4,5,4,4,4,4,2,4,5,4,4,42,50.0,neutral or dissatisfied +23889,19205,Male,Loyal Customer,51,Business travel,Eco,588,5,2,2,2,5,5,5,5,4,2,4,3,2,5,0,0.0,satisfied +23890,76529,Female,Loyal Customer,40,Business travel,Business,516,5,5,5,5,3,5,4,4,4,4,4,4,4,5,0,1.0,satisfied +23891,62133,Female,Loyal Customer,42,Business travel,Business,2454,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +23892,106905,Male,Loyal Customer,30,Business travel,Business,704,3,3,3,3,5,5,5,5,4,2,4,5,4,5,17,0.0,satisfied +23893,114908,Female,Loyal Customer,56,Business travel,Business,373,1,1,1,1,2,5,5,5,5,5,5,5,5,5,3,4.0,satisfied +23894,33882,Male,Loyal Customer,60,Business travel,Eco,705,4,2,2,2,4,4,4,4,2,2,4,2,3,4,0,0.0,neutral or dissatisfied +23895,102310,Female,Loyal Customer,52,Business travel,Business,3772,3,2,2,2,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +23896,26873,Male,Loyal Customer,28,Business travel,Eco,2329,4,3,5,3,4,4,4,4,3,2,3,3,2,4,0,15.0,satisfied +23897,90828,Male,Loyal Customer,59,Business travel,Business,594,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +23898,73184,Male,Loyal Customer,39,Business travel,Business,1258,2,1,1,1,3,4,4,2,2,1,2,3,2,3,125,128.0,neutral or dissatisfied +23899,110385,Female,disloyal Customer,28,Business travel,Eco,925,3,3,3,4,3,3,3,3,1,1,3,4,4,3,96,90.0,neutral or dissatisfied +23900,88353,Female,Loyal Customer,41,Business travel,Eco,271,4,5,5,5,4,4,4,4,1,5,3,1,3,4,1,0.0,neutral or dissatisfied +23901,114504,Male,disloyal Customer,17,Business travel,Eco,296,3,3,3,2,5,3,5,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +23902,5061,Female,disloyal Customer,23,Business travel,Business,235,0,0,0,2,2,0,2,2,5,3,4,5,5,2,0,0.0,satisfied +23903,91142,Male,Loyal Customer,33,Personal Travel,Eco,250,2,5,2,1,1,2,1,1,3,5,4,3,4,1,13,9.0,neutral or dissatisfied +23904,63955,Female,Loyal Customer,14,Personal Travel,Eco,1172,2,4,2,3,4,2,1,4,4,2,1,3,2,4,0,0.0,neutral or dissatisfied +23905,13331,Male,Loyal Customer,32,Business travel,Eco,946,4,4,4,4,4,4,4,4,2,5,1,2,4,4,0,0.0,satisfied +23906,97344,Male,disloyal Customer,24,Business travel,Business,1020,4,0,5,2,1,5,1,1,3,5,5,3,4,1,0,0.0,satisfied +23907,2607,Male,Loyal Customer,28,Personal Travel,Eco,304,4,5,4,1,5,4,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +23908,68652,Female,disloyal Customer,23,Business travel,Business,175,5,0,5,1,4,5,4,4,3,4,4,4,4,4,0,0.0,satisfied +23909,15623,Male,Loyal Customer,13,Personal Travel,Eco,229,3,2,3,4,4,3,4,4,1,2,4,1,4,4,127,108.0,neutral or dissatisfied +23910,85063,Male,Loyal Customer,49,Business travel,Business,2580,5,5,5,5,5,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +23911,105247,Female,Loyal Customer,33,Personal Travel,Eco Plus,377,2,3,2,4,5,2,5,5,1,1,3,1,4,5,37,17.0,neutral or dissatisfied +23912,95072,Female,Loyal Customer,18,Personal Travel,Eco,189,3,5,0,1,2,0,1,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +23913,31186,Female,Loyal Customer,53,Business travel,Business,628,3,3,3,3,4,4,5,4,4,4,4,3,4,5,12,6.0,satisfied +23914,97630,Female,Loyal Customer,45,Business travel,Business,3083,1,1,4,1,2,5,5,4,4,4,4,4,4,4,30,18.0,satisfied +23915,91482,Male,Loyal Customer,54,Personal Travel,Eco,859,1,5,1,3,1,1,1,1,5,2,5,5,4,1,12,5.0,neutral or dissatisfied +23916,79687,Female,Loyal Customer,31,Personal Travel,Eco,762,2,5,1,4,1,1,1,1,4,3,4,4,4,1,0,9.0,neutral or dissatisfied +23917,106009,Female,Loyal Customer,45,Business travel,Eco,499,4,2,2,2,2,3,3,4,4,4,4,4,4,4,0,12.0,neutral or dissatisfied +23918,53710,Female,Loyal Customer,49,Business travel,Business,808,1,5,4,4,2,2,1,1,1,1,1,1,1,2,15,0.0,neutral or dissatisfied +23919,129497,Female,Loyal Customer,44,Business travel,Business,1744,1,1,3,1,2,4,5,5,5,5,5,3,5,3,12,4.0,satisfied +23920,88267,Female,Loyal Customer,42,Business travel,Business,2765,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,6.0,satisfied +23921,79155,Male,Loyal Customer,38,Personal Travel,Business,2239,1,4,1,3,3,4,4,3,3,1,1,4,3,3,60,37.0,neutral or dissatisfied +23922,67446,Male,Loyal Customer,19,Personal Travel,Eco,592,3,3,2,1,5,2,5,5,4,3,2,5,1,5,3,16.0,neutral or dissatisfied +23923,3953,Male,Loyal Customer,36,Business travel,Business,764,3,3,3,3,3,4,3,3,3,3,3,2,3,2,13,15.0,neutral or dissatisfied +23924,92393,Female,disloyal Customer,28,Business travel,Business,2139,3,3,3,4,2,3,3,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +23925,89317,Male,Loyal Customer,47,Business travel,Business,1587,3,3,3,3,3,4,4,4,4,4,4,4,4,4,12,35.0,satisfied +23926,15145,Male,Loyal Customer,49,Business travel,Business,2649,1,1,1,1,2,2,3,2,2,2,2,3,2,1,0,0.0,satisfied +23927,120163,Male,Loyal Customer,43,Business travel,Business,2736,5,5,5,5,4,4,4,4,4,4,5,3,4,4,33,34.0,satisfied +23928,33895,Male,Loyal Customer,70,Personal Travel,Eco,1226,3,5,3,5,5,3,2,5,5,5,1,2,1,5,3,6.0,neutral or dissatisfied +23929,125416,Male,Loyal Customer,30,Business travel,Business,3100,3,3,3,3,2,2,2,2,4,5,5,3,4,2,7,4.0,satisfied +23930,90077,Female,Loyal Customer,51,Business travel,Business,957,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +23931,83908,Female,Loyal Customer,45,Business travel,Business,752,4,4,4,4,3,4,4,5,5,5,5,5,5,4,11,0.0,satisfied +23932,127953,Male,Loyal Customer,22,Business travel,Eco,1999,3,1,1,1,3,3,4,3,2,2,2,4,4,3,0,10.0,neutral or dissatisfied +23933,117744,Female,Loyal Customer,52,Personal Travel,Eco,833,1,3,1,3,1,3,2,3,3,1,4,2,3,4,17,3.0,neutral or dissatisfied +23934,127441,Male,Loyal Customer,41,Business travel,Business,868,2,2,2,2,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +23935,36870,Male,Loyal Customer,69,Personal Travel,Eco,273,4,2,4,3,2,4,2,2,3,3,3,1,2,2,0,0.0,neutral or dissatisfied +23936,81267,Male,Loyal Customer,60,Business travel,Business,2892,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +23937,100119,Female,disloyal Customer,39,Business travel,Business,725,4,4,4,4,2,4,2,2,2,2,4,4,4,2,0,0.0,neutral or dissatisfied +23938,95010,Female,Loyal Customer,58,Personal Travel,Eco,239,3,4,3,3,4,5,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +23939,37056,Male,disloyal Customer,18,Business travel,Eco,1072,3,3,3,3,3,3,4,3,5,5,1,5,5,3,6,0.0,neutral or dissatisfied +23940,12950,Male,Loyal Customer,52,Personal Travel,Eco,359,3,4,3,4,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +23941,27233,Female,disloyal Customer,36,Business travel,Eco,624,2,2,2,4,5,2,3,5,2,1,3,2,3,5,0,15.0,neutral or dissatisfied +23942,6647,Female,Loyal Customer,61,Business travel,Eco,416,2,2,2,2,3,4,3,2,2,2,2,4,2,3,0,0.0,satisfied +23943,103039,Male,disloyal Customer,8,Business travel,Eco,546,2,1,2,2,1,2,1,1,4,3,2,4,3,1,6,8.0,neutral or dissatisfied +23944,78370,Female,disloyal Customer,29,Business travel,Business,980,5,4,4,3,3,4,3,3,4,2,5,3,4,3,0,0.0,satisfied +23945,88739,Female,Loyal Customer,53,Personal Travel,Eco,545,1,4,1,5,2,5,5,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +23946,27670,Female,Loyal Customer,39,Business travel,Business,1107,4,4,4,4,3,4,4,5,5,5,5,3,5,2,0,0.0,satisfied +23947,65973,Female,Loyal Customer,60,Business travel,Business,1372,3,1,3,3,1,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +23948,84862,Female,Loyal Customer,17,Business travel,Business,1860,5,5,2,5,3,3,3,3,2,1,4,4,3,3,3,0.0,satisfied +23949,73015,Male,Loyal Customer,14,Personal Travel,Eco,1089,4,4,4,4,3,4,3,3,3,4,3,2,4,3,26,18.0,neutral or dissatisfied +23950,31415,Male,Loyal Customer,39,Business travel,Eco,1703,5,2,2,2,5,5,5,5,3,1,5,3,3,5,0,0.0,satisfied +23951,96983,Male,Loyal Customer,39,Business travel,Business,359,1,1,2,1,5,5,5,4,4,4,4,3,4,4,0,2.0,satisfied +23952,62864,Male,Loyal Customer,53,Business travel,Business,2218,3,2,2,2,5,2,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +23953,31520,Male,disloyal Customer,16,Business travel,Eco,862,3,3,3,3,5,3,5,5,2,5,3,3,3,5,21,25.0,neutral or dissatisfied +23954,118742,Female,Loyal Customer,66,Personal Travel,Eco,338,2,5,5,4,5,4,5,5,5,5,5,5,5,5,46,41.0,neutral or dissatisfied +23955,124379,Male,Loyal Customer,39,Personal Travel,Eco,808,5,1,5,4,5,5,5,5,1,1,3,1,4,5,0,0.0,satisfied +23956,30039,Male,Loyal Customer,41,Business travel,Business,2677,3,5,5,5,3,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +23957,122290,Male,Loyal Customer,21,Personal Travel,Eco,544,3,4,1,4,3,1,2,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +23958,67554,Female,Loyal Customer,9,Personal Travel,Business,1188,2,5,2,2,1,2,1,1,5,4,3,3,4,1,7,7.0,neutral or dissatisfied +23959,108391,Male,Loyal Customer,29,Personal Travel,Eco,1750,1,2,1,2,5,1,5,5,2,2,3,1,2,5,0,0.0,neutral or dissatisfied +23960,78850,Male,Loyal Customer,45,Business travel,Eco Plus,554,3,2,2,2,3,3,3,3,1,5,4,4,4,3,1,0.0,neutral or dissatisfied +23961,49116,Female,disloyal Customer,35,Business travel,Eco,421,1,0,1,1,5,1,5,5,5,2,5,3,5,5,0,5.0,neutral or dissatisfied +23962,11921,Female,Loyal Customer,30,Personal Travel,Eco,744,2,2,2,3,4,2,3,4,3,3,3,1,4,4,0,0.0,neutral or dissatisfied +23963,35980,Female,Loyal Customer,49,Business travel,Eco,632,4,2,2,2,4,1,1,4,4,4,4,3,4,3,0,0.0,satisfied +23964,15586,Male,Loyal Customer,64,Business travel,Eco,229,1,3,4,3,1,1,1,1,2,5,2,1,3,1,115,123.0,neutral or dissatisfied +23965,129803,Female,Loyal Customer,41,Personal Travel,Eco,308,4,4,4,1,1,4,1,1,4,2,5,4,5,1,1,0.0,neutral or dissatisfied +23966,120401,Male,disloyal Customer,18,Business travel,Eco,449,4,4,4,4,2,4,2,2,4,2,3,2,3,2,11,3.0,neutral or dissatisfied +23967,3533,Female,Loyal Customer,46,Personal Travel,Eco,557,3,4,3,5,4,4,5,4,4,3,4,4,4,5,0,10.0,neutral or dissatisfied +23968,44761,Female,Loyal Customer,30,Business travel,Eco,1250,4,2,2,2,4,4,4,4,3,3,2,2,4,4,18,8.0,satisfied +23969,101051,Female,Loyal Customer,40,Business travel,Business,368,5,5,5,5,5,4,5,5,5,5,5,5,5,4,13,16.0,satisfied +23970,122938,Female,Loyal Customer,59,Business travel,Business,507,5,5,3,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +23971,60350,Male,Loyal Customer,24,Personal Travel,Eco,1024,3,5,3,1,5,3,5,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +23972,123022,Female,disloyal Customer,22,Business travel,Business,507,0,5,0,2,3,0,3,3,3,2,5,4,5,3,0,0.0,satisfied +23973,7506,Male,Loyal Customer,34,Business travel,Business,762,1,1,1,1,4,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +23974,53696,Female,Loyal Customer,41,Business travel,Eco,1190,2,4,4,4,2,2,2,2,4,1,5,1,3,2,0,0.0,satisfied +23975,91063,Male,Loyal Customer,58,Personal Travel,Eco,406,4,4,4,1,2,4,2,2,4,4,4,3,5,2,34,28.0,neutral or dissatisfied +23976,90843,Female,disloyal Customer,29,Business travel,Eco,404,3,1,3,4,1,3,1,1,3,2,4,2,4,1,0,0.0,neutral or dissatisfied +23977,104789,Female,Loyal Customer,59,Business travel,Business,587,5,5,5,5,5,5,5,3,2,4,4,5,3,5,144,128.0,satisfied +23978,104847,Female,Loyal Customer,51,Business travel,Business,2901,1,5,5,5,4,2,1,1,1,1,1,2,1,1,29,12.0,neutral or dissatisfied +23979,85902,Female,Loyal Customer,51,Business travel,Eco,761,4,3,3,3,5,2,2,4,4,4,4,2,4,1,0,20.0,neutral or dissatisfied +23980,81260,Female,disloyal Customer,50,Business travel,Business,1029,5,5,5,1,2,5,2,2,5,4,4,4,5,2,14,27.0,satisfied +23981,125707,Female,Loyal Customer,65,Personal Travel,Eco,814,1,2,2,4,4,2,4,2,2,2,3,4,2,4,19,19.0,neutral or dissatisfied +23982,43450,Female,Loyal Customer,58,Business travel,Eco,594,4,3,2,3,5,2,3,5,5,4,5,2,5,2,0,1.0,satisfied +23983,75161,Male,Loyal Customer,27,Business travel,Business,1846,4,4,4,4,3,3,3,3,3,2,5,5,5,3,0,0.0,satisfied +23984,7003,Female,Loyal Customer,35,Business travel,Eco,234,3,5,5,5,3,4,3,3,1,5,1,1,3,3,0,0.0,satisfied +23985,66834,Female,Loyal Customer,26,Business travel,Eco,731,1,1,1,1,1,2,4,1,4,3,3,3,4,1,14,7.0,neutral or dissatisfied +23986,38559,Female,Loyal Customer,59,Personal Travel,Eco,2446,1,5,1,3,2,4,4,2,2,1,2,5,2,4,87,89.0,neutral or dissatisfied +23987,25746,Female,Loyal Customer,53,Business travel,Business,2346,1,1,1,1,5,3,3,4,4,4,4,5,4,4,4,0.0,satisfied +23988,54748,Female,Loyal Customer,14,Personal Travel,Eco,964,2,5,2,1,1,2,3,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +23989,99517,Female,disloyal Customer,23,Business travel,Eco,283,2,0,2,5,4,2,1,4,4,3,5,3,4,4,0,1.0,neutral or dissatisfied +23990,90091,Female,Loyal Customer,24,Business travel,Business,2634,5,5,5,5,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +23991,120993,Female,Loyal Customer,69,Business travel,Eco,861,3,4,2,4,3,3,4,2,2,3,2,4,2,4,6,16.0,neutral or dissatisfied +23992,7812,Male,Loyal Customer,8,Business travel,Business,2220,4,4,4,4,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +23993,66673,Male,disloyal Customer,26,Business travel,Eco,978,2,2,2,3,3,2,3,3,1,3,4,3,3,3,0,0.0,neutral or dissatisfied +23994,122270,Male,Loyal Customer,17,Personal Travel,Eco,541,0,3,0,3,2,0,4,2,5,3,1,5,2,2,0,0.0,satisfied +23995,37855,Male,Loyal Customer,24,Business travel,Business,1023,3,3,3,3,4,5,4,4,4,2,5,3,5,4,0,0.0,satisfied +23996,32716,Female,Loyal Customer,48,Business travel,Eco,216,5,3,3,3,3,1,3,5,5,5,5,4,5,5,0,0.0,satisfied +23997,26402,Male,Loyal Customer,26,Personal Travel,Eco,957,3,1,4,2,1,4,1,1,3,2,3,4,3,1,0,1.0,neutral or dissatisfied +23998,96651,Male,Loyal Customer,47,Personal Travel,Eco,937,1,4,1,1,5,1,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +23999,72709,Female,Loyal Customer,40,Business travel,Eco Plus,985,3,5,5,5,3,3,3,3,1,5,4,2,3,3,0,6.0,neutral or dissatisfied +24000,91638,Female,Loyal Customer,58,Personal Travel,Eco,1184,4,4,4,4,4,4,3,2,5,4,4,3,3,3,186,186.0,neutral or dissatisfied +24001,93771,Female,Loyal Customer,30,Business travel,Eco Plus,368,3,4,2,4,3,3,3,3,4,4,4,2,3,3,27,34.0,neutral or dissatisfied +24002,129075,Male,disloyal Customer,43,Business travel,Business,2342,5,5,5,3,5,2,2,4,3,5,5,2,3,2,0,0.0,satisfied +24003,83601,Male,Loyal Customer,41,Business travel,Business,409,4,4,4,4,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +24004,97763,Male,Loyal Customer,47,Business travel,Business,587,2,2,2,2,3,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +24005,112708,Female,disloyal Customer,25,Business travel,Eco,671,1,0,0,3,1,0,1,1,3,5,4,2,3,1,32,35.0,neutral or dissatisfied +24006,16926,Male,disloyal Customer,37,Business travel,Eco,820,4,4,4,3,2,4,2,2,5,4,5,2,3,2,5,12.0,satisfied +24007,122752,Female,Loyal Customer,24,Personal Travel,Eco,651,2,1,2,4,5,2,5,5,2,4,4,1,4,5,0,0.0,neutral or dissatisfied +24008,48414,Male,Loyal Customer,16,Personal Travel,Business,850,1,4,1,1,4,1,4,4,2,5,1,5,2,4,0,0.0,neutral or dissatisfied +24009,106279,Female,Loyal Customer,32,Business travel,Business,1798,3,3,2,3,5,5,5,5,5,3,4,5,4,5,12,21.0,satisfied +24010,105434,Male,Loyal Customer,50,Personal Travel,Eco,452,1,5,1,3,4,1,4,4,4,2,4,4,5,4,20,14.0,neutral or dissatisfied +24011,105945,Female,disloyal Customer,15,Business travel,Eco,2295,2,2,2,3,2,1,5,4,1,4,3,5,2,5,21,36.0,neutral or dissatisfied +24012,42281,Female,Loyal Customer,43,Business travel,Eco,846,1,3,3,3,3,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +24013,73445,Female,Loyal Customer,53,Personal Travel,Eco,1182,4,5,4,2,2,4,5,5,5,4,5,5,5,3,4,13.0,neutral or dissatisfied +24014,77037,Female,disloyal Customer,43,Business travel,Business,368,4,4,4,4,3,4,3,3,5,3,4,3,4,3,0,0.0,satisfied +24015,5610,Female,Loyal Customer,47,Business travel,Business,2196,3,2,2,2,1,3,4,3,3,3,3,2,3,2,26,27.0,neutral or dissatisfied +24016,66665,Male,disloyal Customer,39,Business travel,Business,802,2,2,2,3,3,2,3,3,3,2,4,3,5,3,0,0.0,satisfied +24017,101467,Male,Loyal Customer,54,Business travel,Business,3207,0,0,0,4,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +24018,6019,Female,Loyal Customer,61,Business travel,Eco,691,2,4,2,4,3,3,4,2,2,2,2,3,2,1,1,0.0,neutral or dissatisfied +24019,83107,Female,Loyal Customer,11,Personal Travel,Eco,1127,3,4,3,5,5,3,5,5,5,3,5,3,4,5,0,11.0,neutral or dissatisfied +24020,100853,Male,Loyal Customer,37,Personal Travel,Eco,711,2,1,2,2,5,2,5,5,4,5,2,4,3,5,0,4.0,neutral or dissatisfied +24021,46080,Male,disloyal Customer,38,Business travel,Eco,495,3,4,3,2,4,3,4,4,5,1,3,4,3,4,10,26.0,neutral or dissatisfied +24022,257,Male,Loyal Customer,58,Business travel,Business,612,2,2,2,2,3,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +24023,83217,Male,Loyal Customer,28,Business travel,Business,1979,3,4,4,4,3,3,3,3,1,3,3,2,3,3,2,16.0,neutral or dissatisfied +24024,52016,Male,Loyal Customer,31,Business travel,Eco,328,0,0,0,2,4,0,4,4,4,2,4,2,1,4,0,6.0,satisfied +24025,72373,Female,Loyal Customer,41,Business travel,Business,3731,3,3,3,3,4,4,4,3,5,4,4,4,4,4,245,245.0,satisfied +24026,127771,Female,Loyal Customer,18,Personal Travel,Eco Plus,255,1,3,0,4,3,0,4,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +24027,19303,Female,Loyal Customer,52,Personal Travel,Eco,196,3,5,3,3,3,5,5,3,4,4,5,5,4,5,150,149.0,neutral or dissatisfied +24028,4177,Male,Loyal Customer,53,Personal Travel,Eco,431,3,4,3,2,2,3,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +24029,6910,Female,Loyal Customer,56,Personal Travel,Eco,265,2,5,2,2,3,1,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +24030,9286,Male,Loyal Customer,15,Personal Travel,Eco,1190,2,5,3,4,1,3,1,1,4,4,5,4,4,1,69,119.0,neutral or dissatisfied +24031,82559,Male,disloyal Customer,51,Business travel,Business,528,2,2,2,2,5,2,2,5,5,3,4,5,4,5,19,44.0,neutral or dissatisfied +24032,84734,Female,Loyal Customer,51,Business travel,Business,2943,2,2,2,2,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +24033,41604,Male,Loyal Customer,62,Personal Travel,Eco,1504,1,5,1,3,5,1,5,5,4,3,4,5,1,5,57,59.0,neutral or dissatisfied +24034,86650,Female,Loyal Customer,29,Personal Travel,Eco,746,0,5,0,1,4,0,5,4,5,5,4,4,4,4,0,0.0,satisfied +24035,35971,Female,Loyal Customer,44,Personal Travel,Eco,231,2,5,0,5,2,4,4,2,2,0,2,5,2,4,0,0.0,neutral or dissatisfied +24036,113793,Female,Loyal Customer,58,Business travel,Business,1873,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +24037,56344,Male,Loyal Customer,35,Business travel,Eco,200,2,2,2,2,2,2,2,2,3,4,1,2,2,2,29,21.0,neutral or dissatisfied +24038,59246,Male,Loyal Customer,49,Business travel,Business,3801,1,1,1,1,5,5,5,5,5,4,5,5,3,5,39,25.0,satisfied +24039,81371,Female,Loyal Customer,26,Business travel,Business,282,3,2,2,2,3,3,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +24040,45842,Female,Loyal Customer,32,Personal Travel,Eco,391,3,5,3,5,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +24041,98700,Female,Loyal Customer,25,Personal Travel,Eco,920,2,5,2,2,4,2,4,4,3,5,4,3,5,4,32,56.0,neutral or dissatisfied +24042,103457,Female,Loyal Customer,30,Business travel,Business,3732,3,2,2,2,3,2,3,3,3,2,4,1,3,3,8,20.0,neutral or dissatisfied +24043,26345,Female,Loyal Customer,40,Business travel,Eco Plus,834,5,3,3,3,5,5,5,5,4,5,5,2,1,5,0,0.0,satisfied +24044,75462,Male,Loyal Customer,60,Personal Travel,Eco,2342,3,2,3,3,5,3,5,5,1,3,3,1,4,5,6,4.0,neutral or dissatisfied +24045,37405,Female,Loyal Customer,59,Business travel,Eco,1053,4,4,3,3,5,4,3,4,4,4,4,2,4,1,3,0.0,satisfied +24046,70238,Male,Loyal Customer,44,Business travel,Business,1592,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +24047,34218,Female,Loyal Customer,34,Personal Travel,Eco,1237,0,5,1,4,3,1,3,3,5,4,5,4,4,3,0,0.0,satisfied +24048,95719,Female,Loyal Customer,44,Business travel,Business,237,1,1,1,1,2,5,4,4,4,4,4,3,4,4,7,4.0,satisfied +24049,92822,Male,disloyal Customer,30,Business travel,Eco,1541,4,4,4,4,4,3,5,2,2,4,3,5,4,5,167,156.0,neutral or dissatisfied +24050,105430,Male,Loyal Customer,67,Personal Travel,Eco,452,4,4,4,5,5,4,1,5,3,1,1,1,2,5,13,1.0,neutral or dissatisfied +24051,86152,Female,Loyal Customer,51,Business travel,Business,2126,1,1,1,1,3,5,4,5,5,5,5,3,5,3,4,29.0,satisfied +24052,129071,Male,Loyal Customer,58,Business travel,Business,2218,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +24053,53078,Female,Loyal Customer,49,Business travel,Eco Plus,1190,4,3,2,3,5,4,3,4,4,4,4,4,4,1,0,0.0,satisfied +24054,90812,Female,Loyal Customer,54,Business travel,Business,515,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,1.0,satisfied +24055,80367,Male,Loyal Customer,47,Business travel,Business,1748,2,2,2,2,5,4,4,2,2,2,2,5,2,4,3,0.0,satisfied +24056,98273,Female,Loyal Customer,22,Business travel,Business,1200,1,0,0,2,3,0,5,3,3,4,3,3,3,3,67,60.0,neutral or dissatisfied +24057,83903,Male,Loyal Customer,60,Personal Travel,Eco,1678,4,3,4,4,1,4,1,1,2,2,4,2,3,1,15,0.0,satisfied +24058,113859,Female,disloyal Customer,22,Business travel,Business,1592,2,1,1,3,2,1,2,2,2,1,4,1,4,2,30,15.0,neutral or dissatisfied +24059,95622,Female,Loyal Customer,15,Personal Travel,Eco,484,3,1,3,2,2,3,2,2,3,4,3,2,2,2,1,0.0,neutral or dissatisfied +24060,108917,Female,Loyal Customer,47,Business travel,Business,675,3,2,2,2,4,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +24061,122846,Female,disloyal Customer,42,Business travel,Business,226,4,4,4,5,2,4,2,2,4,4,5,3,5,2,0,5.0,satisfied +24062,55272,Female,Loyal Customer,36,Business travel,Business,2007,3,3,3,3,2,5,5,4,4,4,4,5,4,5,47,28.0,satisfied +24063,22136,Female,Loyal Customer,44,Business travel,Business,1859,0,0,0,3,4,4,2,1,1,1,1,1,1,5,8,3.0,satisfied +24064,18015,Female,Loyal Customer,33,Personal Travel,Eco,332,3,5,1,1,4,1,4,4,2,1,1,3,2,4,6,0.0,neutral or dissatisfied +24065,115209,Female,Loyal Customer,48,Business travel,Business,3662,4,4,4,4,2,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +24066,82793,Female,Loyal Customer,40,Business travel,Business,231,3,3,3,3,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +24067,119878,Female,Loyal Customer,22,Personal Travel,Eco,912,4,4,4,2,3,4,3,3,4,4,5,4,2,3,31,19.0,neutral or dissatisfied +24068,54519,Female,Loyal Customer,20,Personal Travel,Eco,925,0,5,0,3,2,0,2,2,3,5,4,3,5,2,0,0.0,satisfied +24069,101121,Female,Loyal Customer,40,Business travel,Business,758,2,2,2,2,4,5,5,5,5,5,5,5,5,3,10,0.0,satisfied +24070,92696,Female,Loyal Customer,48,Personal Travel,Eco,507,3,1,3,2,3,2,2,2,2,3,1,2,2,2,0,0.0,neutral or dissatisfied +24071,99861,Male,Loyal Customer,25,Personal Travel,Eco,534,3,5,3,3,4,3,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +24072,88820,Female,Loyal Customer,46,Business travel,Eco Plus,194,5,1,1,1,1,2,4,5,5,5,5,5,5,3,22,26.0,satisfied +24073,64127,Female,Loyal Customer,48,Personal Travel,Eco,2288,4,4,3,3,2,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +24074,49599,Female,Loyal Customer,37,Business travel,Business,373,5,5,5,5,4,5,4,4,4,4,4,1,4,2,2,3.0,satisfied +24075,63736,Female,Loyal Customer,12,Personal Travel,Eco,1660,2,4,2,4,4,2,4,4,4,3,3,1,3,4,14,31.0,neutral or dissatisfied +24076,77505,Female,Loyal Customer,44,Personal Travel,Eco,1087,1,2,1,3,5,4,3,5,5,1,5,1,5,3,0,0.0,neutral or dissatisfied +24077,112080,Female,disloyal Customer,26,Business travel,Eco,1491,3,3,3,4,3,3,3,3,3,5,4,3,3,3,39,33.0,neutral or dissatisfied +24078,62861,Male,disloyal Customer,12,Business travel,Eco,842,2,2,2,4,3,2,1,3,1,5,3,4,3,3,39,12.0,neutral or dissatisfied +24079,57135,Male,Loyal Customer,14,Personal Travel,Eco,1222,2,2,2,3,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +24080,88724,Male,Loyal Customer,59,Personal Travel,Eco,594,3,4,4,4,2,4,5,2,3,5,4,2,2,2,26,13.0,neutral or dissatisfied +24081,41076,Female,disloyal Customer,38,Business travel,Eco,191,2,0,2,3,1,2,1,1,2,1,2,1,3,1,42,39.0,neutral or dissatisfied +24082,14152,Female,Loyal Customer,14,Personal Travel,Eco,413,4,4,2,4,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +24083,97467,Male,disloyal Customer,47,Business travel,Business,484,2,2,2,1,2,2,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +24084,47989,Female,Loyal Customer,55,Business travel,Eco Plus,726,4,2,2,2,3,4,4,4,4,4,4,5,4,2,0,0.0,satisfied +24085,11803,Male,Loyal Customer,45,Personal Travel,Eco Plus,429,2,3,2,2,3,2,3,3,3,1,3,2,2,3,110,110.0,neutral or dissatisfied +24086,9974,Male,Loyal Customer,14,Personal Travel,Eco,357,3,2,5,3,2,5,2,2,1,1,2,1,3,2,74,73.0,neutral or dissatisfied +24087,50320,Female,Loyal Customer,29,Business travel,Business,2972,4,4,4,4,4,4,4,4,2,5,1,2,5,4,0,0.0,satisfied +24088,48816,Female,Loyal Customer,50,Personal Travel,Business,250,3,5,3,1,2,4,5,2,2,3,3,4,2,4,0,0.0,neutral or dissatisfied +24089,100411,Male,Loyal Customer,23,Business travel,Eco Plus,1073,1,1,1,1,1,1,3,1,2,3,4,1,3,1,11,14.0,neutral or dissatisfied +24090,121437,Male,disloyal Customer,35,Business travel,Eco,331,2,1,2,2,3,2,3,3,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +24091,119367,Female,Loyal Customer,58,Business travel,Business,3980,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +24092,117124,Female,disloyal Customer,35,Business travel,Eco,647,4,4,4,2,5,4,5,5,4,1,3,1,4,5,45,34.0,neutral or dissatisfied +24093,100302,Female,Loyal Customer,41,Business travel,Business,3596,3,3,5,3,2,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +24094,73174,Female,Loyal Customer,40,Business travel,Business,1258,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +24095,73757,Male,Loyal Customer,66,Personal Travel,Eco,192,2,4,2,3,3,2,3,3,4,4,5,4,5,3,15,4.0,neutral or dissatisfied +24096,92226,Female,Loyal Customer,23,Personal Travel,Eco,1979,2,2,2,2,2,2,2,2,3,3,3,4,2,2,0,0.0,neutral or dissatisfied +24097,5056,Male,disloyal Customer,27,Business travel,Business,223,0,0,0,3,3,0,3,3,4,2,5,4,5,3,0,0.0,satisfied +24098,19320,Female,Loyal Customer,34,Business travel,Business,3338,3,3,3,3,3,1,4,2,2,2,2,4,2,5,1,9.0,satisfied +24099,30043,Male,Loyal Customer,57,Business travel,Eco,139,4,1,1,1,4,4,4,4,2,2,2,5,2,4,0,0.0,satisfied +24100,21074,Male,Loyal Customer,66,Business travel,Eco,106,1,5,5,5,1,1,1,1,4,5,3,1,3,1,0,0.0,neutral or dissatisfied +24101,56499,Female,disloyal Customer,22,Business travel,Business,1085,5,0,5,4,3,0,3,3,3,2,5,5,5,3,25,0.0,satisfied +24102,49004,Female,disloyal Customer,38,Business travel,Eco,337,4,5,4,1,1,4,1,1,1,1,4,5,5,1,0,3.0,neutral or dissatisfied +24103,78047,Male,Loyal Customer,23,Personal Travel,Eco,214,1,1,1,1,1,3,4,3,4,2,1,4,1,4,265,245.0,neutral or dissatisfied +24104,49992,Male,Loyal Customer,47,Business travel,Business,3766,1,1,1,1,3,5,3,4,4,4,4,1,4,5,0,0.0,satisfied +24105,112712,Female,disloyal Customer,47,Business travel,Eco,271,4,1,5,1,2,5,2,2,1,2,2,2,1,2,8,16.0,neutral or dissatisfied +24106,12135,Female,Loyal Customer,41,Business travel,Business,3781,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,7.0,satisfied +24107,20564,Female,Loyal Customer,47,Business travel,Eco,633,3,4,4,4,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +24108,56641,Female,disloyal Customer,48,Business travel,Business,1085,2,2,2,4,5,2,5,5,4,3,4,5,4,5,0,0.0,satisfied +24109,17110,Male,Loyal Customer,34,Personal Travel,Eco,416,4,1,4,3,3,4,3,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +24110,81312,Male,Loyal Customer,55,Personal Travel,Business,1299,2,4,2,1,4,3,4,1,1,2,1,5,1,5,20,40.0,neutral or dissatisfied +24111,42823,Male,Loyal Customer,53,Business travel,Eco Plus,677,5,1,4,1,5,5,5,5,1,3,3,3,3,5,0,0.0,satisfied +24112,122620,Female,Loyal Customer,57,Personal Travel,Eco,728,2,5,2,2,2,1,1,4,4,2,4,3,4,3,0,7.0,neutral or dissatisfied +24113,91115,Female,Loyal Customer,54,Personal Travel,Eco,581,2,5,2,4,5,5,4,5,5,2,5,4,5,3,0,94.0,neutral or dissatisfied +24114,47,Male,disloyal Customer,24,Business travel,Business,108,0,4,0,4,4,4,2,4,4,2,5,5,5,4,0,0.0,satisfied +24115,106617,Male,Loyal Customer,27,Business travel,Business,2766,2,3,3,3,2,2,2,2,2,1,3,3,3,2,121,127.0,neutral or dissatisfied +24116,91453,Male,Loyal Customer,32,Business travel,Eco,859,3,2,5,2,3,3,3,3,1,1,4,2,4,3,65,53.0,neutral or dissatisfied +24117,24155,Female,disloyal Customer,23,Business travel,Eco,302,3,0,3,2,5,3,5,5,1,4,4,4,1,5,0,0.0,neutral or dissatisfied +24118,5491,Male,Loyal Customer,42,Business travel,Business,3314,3,3,5,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +24119,24908,Male,Loyal Customer,30,Business travel,Eco,762,4,5,5,5,4,4,4,4,3,3,2,5,5,4,0,0.0,satisfied +24120,41222,Female,disloyal Customer,54,Business travel,Eco,1042,3,3,3,3,2,3,2,2,5,3,1,4,1,2,24,13.0,neutral or dissatisfied +24121,80930,Female,Loyal Customer,32,Business travel,Business,352,2,2,2,2,2,2,2,2,4,5,4,2,4,2,0,10.0,neutral or dissatisfied +24122,29832,Female,Loyal Customer,61,Business travel,Business,1619,2,2,2,2,2,2,3,5,5,5,5,5,5,2,0,0.0,satisfied +24123,104865,Male,disloyal Customer,22,Business travel,Eco,327,4,2,3,3,1,3,1,1,3,1,4,3,4,1,0,1.0,neutral or dissatisfied +24124,67069,Female,Loyal Customer,47,Business travel,Business,2653,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +24125,27053,Male,Loyal Customer,46,Business travel,Eco,1489,4,3,3,3,4,4,4,4,1,1,2,3,2,4,0,0.0,satisfied +24126,99029,Female,disloyal Customer,43,Business travel,Business,1009,2,2,2,4,1,2,1,1,3,5,5,3,4,1,91,113.0,neutral or dissatisfied +24127,54268,Male,Loyal Customer,66,Personal Travel,Eco,1222,5,1,5,4,4,5,4,4,4,2,4,1,3,4,4,0.0,satisfied +24128,32724,Male,Loyal Customer,56,Business travel,Business,3131,3,3,3,3,1,5,5,4,4,4,3,5,4,3,4,4.0,satisfied +24129,104090,Female,Loyal Customer,59,Business travel,Eco,588,2,4,4,4,1,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +24130,120680,Male,Loyal Customer,36,Business travel,Eco,280,4,1,1,1,4,4,4,4,1,3,1,4,2,4,10,10.0,satisfied +24131,161,Male,Loyal Customer,20,Personal Travel,Eco,227,2,5,2,5,5,2,5,5,3,2,5,4,4,5,49,63.0,neutral or dissatisfied +24132,124406,Male,Loyal Customer,44,Business travel,Business,1044,1,1,1,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +24133,93887,Female,disloyal Customer,24,Business travel,Eco,588,4,1,4,3,3,4,1,3,2,3,2,4,3,3,0,0.0,neutral or dissatisfied +24134,19233,Female,Loyal Customer,36,Personal Travel,Business,782,1,3,1,2,1,2,2,1,1,1,1,1,1,3,100,91.0,neutral or dissatisfied +24135,122066,Female,Loyal Customer,49,Business travel,Business,130,2,2,2,2,4,2,2,3,3,3,2,2,3,1,14,18.0,neutral or dissatisfied +24136,117214,Female,Loyal Customer,47,Personal Travel,Eco,369,4,2,4,3,1,3,3,5,5,4,1,1,5,4,4,2.0,satisfied +24137,129169,Male,Loyal Customer,56,Personal Travel,Eco,679,1,2,0,3,2,0,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +24138,28312,Female,Loyal Customer,42,Business travel,Eco,867,5,5,5,5,3,5,1,5,5,5,5,4,5,2,0,0.0,satisfied +24139,31999,Male,Loyal Customer,56,Personal Travel,Business,101,2,4,2,2,4,5,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +24140,88998,Female,Loyal Customer,55,Personal Travel,Eco Plus,1199,2,4,2,3,2,3,3,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +24141,100214,Female,Loyal Customer,69,Business travel,Eco,362,4,3,3,3,1,3,3,4,4,4,4,5,4,3,0,0.0,satisfied +24142,97163,Male,Loyal Customer,23,Personal Travel,Eco,1313,4,4,3,3,1,3,1,1,3,3,3,3,4,1,6,0.0,satisfied +24143,103957,Female,Loyal Customer,12,Personal Travel,Eco,533,3,5,3,3,1,3,1,1,3,5,5,5,4,1,0,4.0,neutral or dissatisfied +24144,80952,Male,Loyal Customer,8,Business travel,Business,2053,2,2,2,2,2,2,2,2,1,1,2,1,2,2,0,0.0,neutral or dissatisfied +24145,44554,Female,Loyal Customer,21,Personal Travel,Eco,231,2,5,2,3,5,2,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +24146,117011,Female,Loyal Customer,52,Business travel,Business,2873,5,5,5,5,3,4,5,5,5,5,5,4,5,4,2,2.0,satisfied +24147,40070,Female,Loyal Customer,29,Business travel,Business,493,3,3,3,3,5,5,5,5,3,4,2,3,4,5,0,0.0,satisfied +24148,106944,Female,Loyal Customer,27,Business travel,Business,3853,5,5,5,5,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +24149,58279,Female,Loyal Customer,75,Business travel,Business,2188,2,4,4,4,3,4,3,2,2,2,2,2,2,3,3,0.0,neutral or dissatisfied +24150,86522,Female,Loyal Customer,54,Personal Travel,Eco,762,1,4,1,4,5,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +24151,31750,Male,Loyal Customer,43,Personal Travel,Eco Plus,853,2,5,2,3,2,2,2,2,5,4,4,4,5,2,76,82.0,neutral or dissatisfied +24152,128358,Female,Loyal Customer,35,Business travel,Business,3093,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +24153,41325,Female,Loyal Customer,14,Personal Travel,Eco Plus,802,3,5,3,4,5,3,3,5,4,3,5,2,2,5,0,0.0,neutral or dissatisfied +24154,116940,Female,Loyal Customer,55,Business travel,Business,647,4,4,4,4,2,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +24155,65787,Male,Loyal Customer,27,Business travel,Business,1391,4,4,2,4,4,4,4,4,4,2,5,3,5,4,0,17.0,satisfied +24156,82842,Male,disloyal Customer,29,Business travel,Business,645,1,1,1,3,5,1,5,5,5,3,4,5,4,5,3,36.0,neutral or dissatisfied +24157,77932,Female,disloyal Customer,23,Business travel,Eco,332,2,0,2,2,2,3,4,3,5,4,4,4,4,4,301,283.0,neutral or dissatisfied +24158,96557,Male,Loyal Customer,19,Personal Travel,Eco Plus,302,2,3,2,3,3,2,3,3,2,3,2,2,2,3,5,0.0,neutral or dissatisfied +24159,102026,Male,Loyal Customer,62,Business travel,Business,397,1,1,1,1,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +24160,123146,Female,Loyal Customer,46,Business travel,Business,328,2,2,4,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +24161,88257,Female,Loyal Customer,42,Business travel,Business,3713,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +24162,104909,Male,Loyal Customer,49,Personal Travel,Eco,1565,2,1,2,1,2,2,2,2,1,2,2,2,2,2,3,35.0,neutral or dissatisfied +24163,56054,Male,disloyal Customer,37,Business travel,Eco,975,2,2,2,3,2,1,3,4,3,3,4,3,1,3,29,32.0,neutral or dissatisfied +24164,103730,Male,Loyal Customer,46,Personal Travel,Eco,405,3,4,3,5,4,3,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +24165,29400,Male,Loyal Customer,36,Business travel,Eco,904,1,2,2,2,1,1,1,3,5,4,3,1,2,1,2,26.0,neutral or dissatisfied +24166,36224,Female,disloyal Customer,29,Business travel,Eco,496,2,1,2,4,5,2,4,5,1,5,4,3,3,5,5,19.0,neutral or dissatisfied +24167,44680,Female,Loyal Customer,26,Business travel,Business,1981,4,5,4,4,3,3,4,3,3,4,4,2,3,3,22,44.0,neutral or dissatisfied +24168,12363,Female,Loyal Customer,45,Business travel,Business,253,4,3,3,3,2,3,3,4,4,3,4,3,4,2,24,25.0,neutral or dissatisfied +24169,84655,Female,Loyal Customer,57,Business travel,Business,2182,1,1,1,1,5,5,5,3,3,3,3,4,3,4,39,31.0,satisfied +24170,103681,Female,disloyal Customer,19,Business travel,Eco,251,3,0,3,3,4,3,4,4,3,5,3,3,4,4,25,20.0,neutral or dissatisfied +24171,47923,Female,Loyal Customer,49,Personal Travel,Eco,834,1,1,1,3,2,4,3,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +24172,106218,Female,Loyal Customer,62,Business travel,Business,471,2,3,2,3,5,4,4,2,2,2,2,3,2,4,7,0.0,neutral or dissatisfied +24173,77711,Male,Loyal Customer,47,Business travel,Business,731,3,3,3,3,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +24174,1900,Male,disloyal Customer,39,Business travel,Business,190,2,2,2,3,1,2,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +24175,31718,Female,Loyal Customer,52,Personal Travel,Eco,846,1,1,1,3,5,4,4,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +24176,22721,Female,Loyal Customer,51,Business travel,Business,3651,2,2,5,2,3,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +24177,24750,Female,disloyal Customer,45,Business travel,Eco,432,3,3,3,1,4,3,4,4,3,5,3,5,1,4,1,7.0,neutral or dissatisfied +24178,123576,Female,disloyal Customer,37,Business travel,Eco,273,0,3,0,4,3,0,3,3,3,5,5,1,2,3,96,100.0,satisfied +24179,32001,Male,Loyal Customer,47,Personal Travel,Business,101,3,3,3,4,1,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +24180,8960,Female,Loyal Customer,48,Business travel,Business,738,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,,satisfied +24181,48992,Female,Loyal Customer,50,Business travel,Business,110,2,2,2,2,4,1,2,4,4,4,3,4,4,4,0,1.0,satisfied +24182,106437,Female,Loyal Customer,26,Personal Travel,Eco Plus,674,2,4,2,2,3,2,3,3,3,5,5,4,5,3,8,11.0,neutral or dissatisfied +24183,75730,Female,Loyal Customer,46,Business travel,Eco,813,2,1,1,1,5,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +24184,102566,Male,Loyal Customer,27,Business travel,Business,236,4,3,4,4,5,5,5,5,3,3,5,3,5,5,1,7.0,satisfied +24185,91608,Female,Loyal Customer,50,Business travel,Business,3148,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +24186,67788,Female,disloyal Customer,27,Business travel,Eco,1205,4,4,4,3,4,4,4,4,2,4,3,2,4,4,32,22.0,neutral or dissatisfied +24187,13250,Female,Loyal Customer,36,Business travel,Business,3402,2,2,2,2,4,1,2,4,4,4,4,3,4,3,0,0.0,satisfied +24188,70728,Female,Loyal Customer,48,Business travel,Business,2163,5,5,5,5,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +24189,5591,Male,Loyal Customer,15,Personal Travel,Business,624,1,5,1,2,1,1,1,1,5,3,5,4,5,1,8,0.0,neutral or dissatisfied +24190,20608,Female,Loyal Customer,54,Business travel,Eco,864,5,2,2,2,4,4,5,5,5,5,5,3,5,4,0,33.0,satisfied +24191,88861,Female,Loyal Customer,47,Business travel,Business,859,4,4,4,4,2,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +24192,83361,Female,Loyal Customer,45,Business travel,Business,1124,4,4,4,4,4,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +24193,95515,Male,disloyal Customer,15,Business travel,Eco Plus,441,3,3,4,4,4,4,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +24194,30806,Male,Loyal Customer,41,Business travel,Eco,1199,4,4,4,4,4,4,4,4,3,4,5,5,2,4,0,0.0,satisfied +24195,86862,Male,Loyal Customer,7,Personal Travel,Eco,692,2,4,2,1,2,1,1,3,4,5,4,1,4,1,142,119.0,neutral or dissatisfied +24196,90847,Male,Loyal Customer,28,Business travel,Business,406,3,2,2,2,3,3,3,3,2,4,3,4,3,3,0,2.0,neutral or dissatisfied +24197,74036,Male,Loyal Customer,22,Personal Travel,Eco Plus,1471,4,5,4,3,5,4,5,5,3,5,4,4,4,5,0,12.0,neutral or dissatisfied +24198,30667,Male,Loyal Customer,25,Business travel,Eco Plus,533,3,1,3,3,3,3,2,3,1,5,4,3,3,3,41,37.0,neutral or dissatisfied +24199,93964,Male,Loyal Customer,37,Personal Travel,Business,1218,3,4,3,4,2,5,4,4,4,3,3,3,4,5,4,0.0,neutral or dissatisfied +24200,50112,Female,disloyal Customer,38,Business travel,Eco,110,4,2,3,3,3,3,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +24201,61437,Female,Loyal Customer,42,Business travel,Business,2419,3,3,3,3,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +24202,114209,Male,Loyal Customer,45,Business travel,Business,3037,5,5,5,5,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +24203,85039,Female,Loyal Customer,46,Personal Travel,Eco Plus,1590,2,5,2,2,4,3,4,3,3,2,3,3,3,5,13,24.0,neutral or dissatisfied +24204,15929,Female,Loyal Customer,42,Business travel,Eco,723,2,3,3,3,3,3,2,2,2,2,2,2,2,4,26,12.0,neutral or dissatisfied +24205,33099,Female,Loyal Customer,18,Personal Travel,Eco,163,3,3,3,1,2,3,2,2,4,3,4,2,5,2,0,0.0,neutral or dissatisfied +24206,122501,Male,Loyal Customer,59,Business travel,Business,930,3,3,4,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +24207,128295,Female,Loyal Customer,40,Business travel,Business,304,1,1,1,1,5,4,4,4,4,4,4,5,4,4,6,0.0,satisfied +24208,89658,Male,Loyal Customer,45,Business travel,Business,3965,4,4,4,4,3,5,5,2,2,2,2,4,2,5,2,0.0,satisfied +24209,51416,Female,Loyal Customer,50,Personal Travel,Eco Plus,109,2,0,2,2,4,4,5,4,4,2,4,4,4,3,13,13.0,neutral or dissatisfied +24210,58823,Male,Loyal Customer,31,Personal Travel,Eco,1120,2,4,2,2,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +24211,35581,Male,Loyal Customer,37,Business travel,Eco Plus,1069,5,1,1,1,5,5,5,5,5,2,1,4,5,5,10,26.0,satisfied +24212,36405,Female,Loyal Customer,54,Business travel,Business,2084,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +24213,13704,Male,Loyal Customer,21,Personal Travel,Eco,300,1,4,1,1,2,1,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +24214,87244,Female,Loyal Customer,52,Business travel,Business,1785,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +24215,63261,Male,Loyal Customer,39,Business travel,Business,337,1,4,4,4,3,3,3,1,1,1,1,3,1,4,36,19.0,neutral or dissatisfied +24216,29533,Male,Loyal Customer,52,Business travel,Business,2552,3,3,3,3,4,5,5,4,4,5,1,5,2,5,0,0.0,satisfied +24217,3260,Female,Loyal Customer,40,Business travel,Business,479,3,4,4,4,4,2,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +24218,77181,Female,Loyal Customer,64,Business travel,Eco,290,2,2,3,2,1,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +24219,96331,Female,Loyal Customer,41,Business travel,Eco,359,3,5,5,5,3,3,3,3,4,1,2,1,2,3,4,0.0,neutral or dissatisfied +24220,38045,Female,Loyal Customer,25,Business travel,Eco,1121,4,3,2,3,4,4,4,4,1,4,4,2,5,4,0,0.0,satisfied +24221,86734,Female,Loyal Customer,42,Business travel,Business,1747,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +24222,5134,Female,Loyal Customer,34,Personal Travel,Eco Plus,303,4,5,4,2,3,4,3,3,5,5,5,3,5,3,49,50.0,neutral or dissatisfied +24223,77185,Female,Loyal Customer,27,Business travel,Business,290,3,1,1,1,3,3,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +24224,125413,Female,Loyal Customer,43,Business travel,Business,735,2,2,2,2,5,4,5,4,4,4,4,5,4,4,2,1.0,satisfied +24225,106971,Male,Loyal Customer,58,Business travel,Business,2024,3,2,2,2,2,2,3,3,3,3,3,4,3,3,51,52.0,neutral or dissatisfied +24226,71447,Male,Loyal Customer,44,Business travel,Eco,867,2,5,5,5,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +24227,48326,Male,Loyal Customer,59,Business travel,Business,674,5,5,4,5,3,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +24228,79022,Female,disloyal Customer,62,Business travel,Eco,356,2,4,2,4,5,2,5,5,3,2,3,1,4,5,2,0.0,neutral or dissatisfied +24229,12122,Male,Loyal Customer,29,Personal Travel,Eco,1034,2,2,2,2,4,2,4,4,1,3,1,2,1,4,17,3.0,neutral or dissatisfied +24230,128578,Female,Loyal Customer,51,Business travel,Eco,2552,3,1,1,1,3,2,2,4,2,1,3,2,2,2,5,56.0,neutral or dissatisfied +24231,122848,Male,Loyal Customer,44,Business travel,Business,2221,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +24232,96067,Male,Loyal Customer,18,Personal Travel,Eco,775,4,4,4,3,2,4,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +24233,20445,Female,Loyal Customer,38,Business travel,Business,177,5,5,5,5,4,4,5,4,4,4,5,1,4,4,0,20.0,satisfied +24234,64486,Female,disloyal Customer,26,Business travel,Business,469,5,5,5,4,3,5,3,3,3,3,4,3,5,3,6,0.0,satisfied +24235,128955,Male,Loyal Customer,59,Business travel,Business,414,2,2,3,2,5,5,4,5,5,5,5,5,5,4,1,0.0,satisfied +24236,27224,Female,Loyal Customer,49,Business travel,Business,1024,2,2,1,2,1,5,4,4,4,4,4,1,4,4,0,3.0,satisfied +24237,67411,Male,Loyal Customer,60,Business travel,Eco,592,2,4,1,1,3,2,3,3,2,2,3,2,3,3,0,7.0,neutral or dissatisfied +24238,108516,Male,Loyal Customer,57,Personal Travel,Eco,519,4,4,4,1,2,4,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +24239,94949,Female,Loyal Customer,38,Business travel,Business,248,3,4,4,4,1,4,3,3,3,3,3,4,3,1,27,23.0,neutral or dissatisfied +24240,104549,Male,Loyal Customer,65,Business travel,Business,1256,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,1.0,satisfied +24241,104334,Female,disloyal Customer,29,Business travel,Eco,452,1,4,1,3,1,1,1,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +24242,31851,Female,disloyal Customer,25,Business travel,Eco,1140,2,2,2,3,1,2,1,1,3,1,3,3,4,1,6,13.0,neutral or dissatisfied +24243,94552,Male,Loyal Customer,18,Business travel,Business,1752,4,1,1,1,4,4,4,4,1,2,3,2,3,4,5,0.0,neutral or dissatisfied +24244,110829,Male,Loyal Customer,56,Business travel,Business,1811,5,5,5,5,3,5,5,4,4,4,4,5,4,4,3,5.0,satisfied +24245,82633,Male,Loyal Customer,42,Personal Travel,Eco,528,3,5,3,3,3,3,3,3,3,3,5,3,4,3,0,8.0,neutral or dissatisfied +24246,56710,Male,Loyal Customer,31,Personal Travel,Eco,937,4,4,4,3,4,4,4,4,5,5,5,4,5,4,3,1.0,neutral or dissatisfied +24247,65933,Male,Loyal Customer,13,Personal Travel,Eco,569,2,3,2,4,4,2,1,4,1,5,1,5,3,4,0,1.0,neutral or dissatisfied +24248,40027,Male,Loyal Customer,25,Business travel,Business,525,1,5,5,5,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +24249,45840,Male,Loyal Customer,21,Personal Travel,Eco,411,1,4,3,3,4,3,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +24250,109323,Female,Loyal Customer,23,Personal Travel,Eco,1072,1,5,1,4,5,1,5,5,5,5,5,5,5,5,29,11.0,neutral or dissatisfied +24251,51638,Male,disloyal Customer,23,Business travel,Eco,751,3,3,3,2,3,3,3,3,2,5,2,3,2,3,18,16.0,neutral or dissatisfied +24252,34548,Female,Loyal Customer,29,Business travel,Business,1576,4,3,4,4,4,4,4,4,3,4,1,5,1,4,0,0.0,satisfied +24253,519,Female,Loyal Customer,34,Business travel,Business,396,2,2,2,2,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +24254,63150,Male,Loyal Customer,47,Business travel,Business,3019,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +24255,3081,Female,Loyal Customer,46,Business travel,Eco,678,2,2,2,2,1,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +24256,68677,Male,Loyal Customer,57,Business travel,Business,3952,0,0,0,3,3,4,5,1,1,1,1,4,1,3,0,0.0,satisfied +24257,103082,Female,Loyal Customer,15,Personal Travel,Eco,546,4,1,4,2,2,4,2,2,1,5,3,4,3,2,0,0.0,neutral or dissatisfied +24258,29153,Female,Loyal Customer,45,Business travel,Eco Plus,697,3,3,3,3,4,3,5,3,3,3,3,3,3,2,0,8.0,satisfied +24259,63082,Female,Loyal Customer,23,Personal Travel,Eco,862,3,2,3,3,2,3,2,2,2,3,3,3,3,2,7,0.0,neutral or dissatisfied +24260,34862,Female,disloyal Customer,28,Business travel,Business,2248,2,2,2,1,5,2,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +24261,113602,Female,Loyal Customer,46,Business travel,Eco,407,4,4,4,4,3,5,5,4,4,4,4,1,4,3,0,2.0,satisfied +24262,32070,Male,Loyal Customer,51,Business travel,Business,216,3,3,3,3,1,3,4,4,4,5,4,2,4,5,71,67.0,satisfied +24263,49574,Male,Loyal Customer,61,Business travel,Eco,109,5,4,4,4,5,5,5,5,2,5,2,2,5,5,29,29.0,satisfied +24264,48218,Female,Loyal Customer,69,Personal Travel,Eco,391,1,5,5,2,3,4,4,1,1,5,1,3,1,3,56,46.0,neutral or dissatisfied +24265,64525,Male,Loyal Customer,48,Business travel,Business,2355,5,5,5,5,4,4,5,5,5,5,5,4,5,3,73,63.0,satisfied +24266,32579,Male,Loyal Customer,45,Business travel,Business,163,4,3,4,4,2,5,4,4,4,4,4,2,4,5,7,5.0,satisfied +24267,31725,Female,Loyal Customer,11,Personal Travel,Eco,967,4,4,3,3,4,3,4,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +24268,116121,Female,Loyal Customer,62,Personal Travel,Eco,342,1,3,1,3,1,3,2,5,5,1,5,3,5,1,0,0.0,neutral or dissatisfied +24269,38850,Female,Loyal Customer,37,Personal Travel,Eco Plus,353,3,4,3,3,2,3,2,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +24270,97055,Female,Loyal Customer,39,Business travel,Business,1642,3,3,3,3,5,4,4,5,4,3,5,4,3,4,136,116.0,satisfied +24271,69093,Male,Loyal Customer,48,Personal Travel,Eco,1389,2,2,2,3,4,2,4,4,1,2,2,4,2,4,28,16.0,neutral or dissatisfied +24272,66005,Female,disloyal Customer,35,Business travel,Business,1055,3,3,3,2,4,3,4,4,4,2,5,5,4,4,18,33.0,neutral or dissatisfied +24273,73867,Female,Loyal Customer,30,Business travel,Business,2585,3,5,3,3,4,4,4,5,2,3,5,4,3,4,0,33.0,satisfied +24274,37922,Male,Loyal Customer,17,Personal Travel,Eco,1065,2,5,1,3,3,1,3,3,4,5,5,3,5,3,14,1.0,neutral or dissatisfied +24275,85217,Female,Loyal Customer,56,Business travel,Business,813,1,1,1,1,2,5,4,4,4,4,4,4,4,5,7,0.0,satisfied +24276,21206,Female,Loyal Customer,51,Business travel,Eco,192,1,0,0,3,2,3,3,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +24277,102211,Female,disloyal Customer,39,Business travel,Business,223,3,3,3,3,1,3,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +24278,62381,Male,disloyal Customer,25,Business travel,Business,2704,0,4,0,1,2,0,2,2,5,2,4,3,4,2,8,10.0,satisfied +24279,76811,Female,Loyal Customer,25,Personal Travel,Eco,689,2,4,2,5,1,2,1,1,5,3,4,3,4,1,5,0.0,neutral or dissatisfied +24280,127182,Female,Loyal Customer,42,Business travel,Business,3112,2,1,2,2,3,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +24281,120240,Female,Loyal Customer,55,Personal Travel,Eco,1325,2,3,2,3,5,4,4,4,4,2,3,1,4,1,0,0.0,neutral or dissatisfied +24282,64516,Female,Loyal Customer,8,Personal Travel,Business,247,1,1,1,4,3,1,3,3,1,1,4,3,3,3,3,0.0,neutral or dissatisfied +24283,129829,Male,Loyal Customer,26,Personal Travel,Eco,447,4,4,4,4,2,4,2,2,5,2,5,3,5,2,0,0.0,satisfied +24284,58621,Male,Loyal Customer,70,Personal Travel,Eco,137,2,0,2,3,1,2,1,1,2,3,1,2,3,1,8,2.0,neutral or dissatisfied +24285,46540,Male,disloyal Customer,56,Business travel,Eco,125,2,0,2,2,5,2,5,5,4,4,3,2,4,5,27,36.0,neutral or dissatisfied +24286,10294,Female,Loyal Customer,51,Business travel,Business,1930,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24287,111127,Male,Loyal Customer,59,Business travel,Business,3648,5,5,5,5,3,5,4,4,4,5,4,4,4,4,32,19.0,satisfied +24288,3735,Male,Loyal Customer,11,Personal Travel,Eco,544,2,4,2,3,3,2,3,3,4,4,4,2,4,3,0,13.0,neutral or dissatisfied +24289,40858,Female,Loyal Customer,68,Personal Travel,Eco,574,3,5,3,2,5,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +24290,21992,Male,Loyal Customer,18,Personal Travel,Eco,503,4,5,4,2,4,4,3,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +24291,48669,Female,Loyal Customer,60,Business travel,Business,3809,2,2,2,2,5,5,4,5,5,5,5,3,5,3,0,10.0,satisfied +24292,118016,Male,Loyal Customer,25,Personal Travel,Eco,1037,4,5,5,1,5,5,5,5,5,2,5,5,5,5,19,3.0,satisfied +24293,41756,Male,Loyal Customer,27,Business travel,Business,2862,1,1,1,1,5,5,5,5,4,1,1,3,1,5,10,24.0,satisfied +24294,26523,Female,Loyal Customer,35,Business travel,Eco,990,4,3,3,3,4,4,4,4,1,5,1,1,1,4,0,11.0,satisfied +24295,102537,Male,Loyal Customer,65,Personal Travel,Eco,223,1,5,0,3,3,0,3,3,5,4,5,4,5,3,5,4.0,neutral or dissatisfied +24296,35439,Male,Loyal Customer,47,Personal Travel,Eco,1074,2,4,2,3,3,2,3,3,4,2,4,5,5,3,3,30.0,neutral or dissatisfied +24297,99399,Male,Loyal Customer,22,Business travel,Business,1643,3,1,4,4,3,3,3,3,1,1,2,2,2,3,31,30.0,neutral or dissatisfied +24298,61515,Male,Loyal Customer,8,Personal Travel,Eco,2253,2,1,2,4,2,2,1,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +24299,114521,Female,Loyal Customer,33,Personal Travel,Business,325,3,5,3,3,5,2,2,3,3,3,3,2,3,5,46,39.0,neutral or dissatisfied +24300,119312,Male,Loyal Customer,45,Business travel,Eco,214,2,1,1,1,2,2,2,2,1,3,4,3,4,2,72,100.0,neutral or dissatisfied +24301,68623,Female,Loyal Customer,52,Business travel,Business,1539,0,0,0,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +24302,68116,Male,Loyal Customer,64,Personal Travel,Eco,813,3,2,3,2,4,3,1,4,2,3,1,3,2,4,18,16.0,neutral or dissatisfied +24303,24896,Male,Loyal Customer,48,Personal Travel,Eco,397,2,3,2,3,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +24304,18800,Female,Loyal Customer,23,Business travel,Eco,503,3,4,3,4,3,4,4,3,1,2,5,4,3,3,7,10.0,satisfied +24305,99773,Female,Loyal Customer,25,Business travel,Business,2220,3,3,3,3,5,5,5,5,5,5,4,4,5,5,6,1.0,satisfied +24306,15008,Male,Loyal Customer,29,Business travel,Business,2463,5,5,5,5,5,5,5,5,5,3,4,3,5,5,30,18.0,satisfied +24307,69283,Male,Loyal Customer,34,Personal Travel,Eco,733,3,3,3,3,3,1,1,4,1,4,3,1,2,1,140,132.0,neutral or dissatisfied +24308,87523,Female,Loyal Customer,19,Personal Travel,Eco,321,1,3,1,3,4,1,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +24309,71632,Female,disloyal Customer,21,Business travel,Business,720,0,0,0,4,5,0,5,5,5,4,5,4,3,5,0,0.0,satisfied +24310,111330,Male,Loyal Customer,42,Personal Travel,Eco,283,2,5,2,1,3,2,3,3,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +24311,43951,Male,disloyal Customer,36,Business travel,Business,473,4,4,4,3,1,4,1,1,3,3,3,4,3,1,0,14.0,neutral or dissatisfied +24312,12313,Male,Loyal Customer,47,Business travel,Business,190,2,1,1,1,4,2,3,4,4,4,2,3,4,4,49,55.0,neutral or dissatisfied +24313,3128,Male,Loyal Customer,57,Business travel,Business,3428,1,1,5,1,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +24314,120368,Male,Loyal Customer,43,Business travel,Business,2248,0,0,0,2,3,4,5,4,4,4,4,3,4,3,0,7.0,satisfied +24315,9276,Female,Loyal Customer,19,Business travel,Business,2417,4,4,5,4,4,4,4,4,5,4,4,5,4,4,32,15.0,satisfied +24316,42863,Male,Loyal Customer,57,Business travel,Business,2252,1,1,1,1,4,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +24317,46823,Male,Loyal Customer,27,Business travel,Business,2425,3,3,3,3,4,4,4,4,4,5,2,1,3,4,0,0.0,satisfied +24318,528,Female,Loyal Customer,49,Business travel,Business,134,3,3,3,3,4,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +24319,79064,Female,Loyal Customer,60,Business travel,Eco,356,4,5,5,5,3,2,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +24320,62310,Female,disloyal Customer,38,Business travel,Eco,414,3,1,3,4,2,3,2,2,1,2,3,1,3,2,12,7.0,neutral or dissatisfied +24321,121469,Female,Loyal Customer,54,Personal Travel,Eco,257,4,5,4,2,5,5,4,5,5,4,5,2,5,1,51,41.0,neutral or dissatisfied +24322,33211,Male,Loyal Customer,49,Business travel,Eco Plus,102,3,5,3,3,3,3,3,3,3,4,3,4,3,3,15,30.0,neutral or dissatisfied +24323,49616,Male,Loyal Customer,55,Business travel,Eco,337,2,4,5,5,2,2,2,2,2,3,2,4,1,2,0,0.0,satisfied +24324,108061,Female,Loyal Customer,45,Business travel,Business,1868,4,4,4,4,4,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +24325,102097,Male,Loyal Customer,31,Business travel,Business,1768,5,5,4,5,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +24326,33563,Male,disloyal Customer,47,Business travel,Eco,399,4,5,4,1,5,4,5,5,1,3,5,2,5,5,0,0.0,neutral or dissatisfied +24327,108808,Female,Loyal Customer,22,Personal Travel,Eco,581,2,4,2,1,3,2,5,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +24328,31317,Female,Loyal Customer,25,Personal Travel,Eco,680,2,5,2,2,2,2,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +24329,107126,Female,Loyal Customer,10,Personal Travel,Eco,842,4,5,4,2,4,4,4,4,3,3,5,4,5,4,32,27.0,satisfied +24330,5515,Male,Loyal Customer,49,Business travel,Business,431,4,5,3,3,5,3,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +24331,83824,Male,Loyal Customer,43,Business travel,Business,425,2,4,4,4,1,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +24332,55860,Female,Loyal Customer,65,Personal Travel,Eco,419,4,4,4,4,3,5,2,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +24333,97754,Male,Loyal Customer,69,Personal Travel,Eco,587,1,3,1,2,1,1,1,1,4,2,2,4,2,1,34,26.0,neutral or dissatisfied +24334,18910,Male,Loyal Customer,16,Personal Travel,Eco,503,3,1,3,1,3,3,3,3,1,1,2,4,2,3,0,0.0,neutral or dissatisfied +24335,83705,Male,Loyal Customer,36,Personal Travel,Eco,577,2,5,2,2,2,2,2,2,4,2,5,4,4,2,19,10.0,neutral or dissatisfied +24336,117652,Female,Loyal Customer,70,Personal Travel,Eco Plus,1020,2,4,1,4,5,5,1,4,4,1,2,2,4,2,30,12.0,neutral or dissatisfied +24337,22752,Male,Loyal Customer,43,Business travel,Business,2324,5,5,5,5,2,2,3,5,5,5,4,2,5,1,48,39.0,satisfied +24338,19496,Female,Loyal Customer,57,Business travel,Eco,350,3,4,4,4,5,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +24339,12676,Female,disloyal Customer,26,Business travel,Eco,689,3,3,3,1,3,3,3,3,2,1,3,5,5,3,0,0.0,neutral or dissatisfied +24340,73987,Female,Loyal Customer,16,Personal Travel,Eco Plus,2330,2,4,2,1,2,2,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +24341,17960,Male,disloyal Customer,15,Business travel,Eco,501,4,0,4,2,3,4,2,3,3,4,2,5,3,3,0,0.0,satisfied +24342,111101,Female,Loyal Customer,27,Business travel,Business,3454,2,2,2,2,4,4,4,4,4,2,5,3,5,4,9,8.0,satisfied +24343,71951,Female,Loyal Customer,58,Business travel,Business,1440,4,4,4,4,3,5,4,3,3,3,3,4,3,3,10,11.0,satisfied +24344,33730,Male,Loyal Customer,51,Personal Travel,Eco,805,2,3,2,4,3,2,5,3,1,4,3,3,1,3,47,46.0,neutral or dissatisfied +24345,28581,Male,disloyal Customer,16,Business travel,Eco,802,2,2,2,4,5,2,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +24346,2042,Male,Loyal Customer,56,Business travel,Business,3987,3,3,3,3,2,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +24347,52899,Female,Loyal Customer,25,Business travel,Eco Plus,836,5,3,3,3,5,5,5,5,3,4,5,3,5,5,2,0.0,satisfied +24348,59108,Female,Loyal Customer,49,Personal Travel,Eco,1846,2,4,3,3,2,5,5,3,3,3,3,3,3,5,16,7.0,neutral or dissatisfied +24349,37333,Male,Loyal Customer,32,Business travel,Business,2429,5,5,5,5,4,4,4,4,3,4,5,4,2,4,0,0.0,satisfied +24350,101211,Female,Loyal Customer,52,Personal Travel,Eco,1090,3,5,3,2,2,2,3,2,2,3,2,5,2,2,35,56.0,neutral or dissatisfied +24351,107314,Female,Loyal Customer,52,Personal Travel,Eco,307,2,5,2,5,5,4,5,2,2,2,2,3,2,5,20,2.0,neutral or dissatisfied +24352,23794,Male,Loyal Customer,29,Business travel,Business,2493,5,2,5,5,5,5,5,5,2,5,2,5,4,5,0,0.0,satisfied +24353,63273,Female,Loyal Customer,27,Business travel,Business,3315,3,5,5,5,3,3,3,3,3,4,3,2,2,3,102,98.0,neutral or dissatisfied +24354,103515,Male,Loyal Customer,9,Personal Travel,Eco,1047,2,5,2,2,2,2,3,2,3,2,5,5,5,2,18,13.0,neutral or dissatisfied +24355,65153,Female,Loyal Customer,65,Personal Travel,Eco,469,3,3,3,3,4,3,3,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +24356,80774,Male,Loyal Customer,54,Business travel,Business,1844,4,4,4,4,2,5,5,3,3,4,3,5,3,5,3,0.0,satisfied +24357,41969,Female,Loyal Customer,56,Business travel,Eco,125,2,2,2,2,4,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +24358,11945,Female,Loyal Customer,25,Business travel,Business,781,2,3,5,3,2,2,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +24359,99101,Male,Loyal Customer,40,Business travel,Business,419,3,3,3,3,5,5,5,5,5,5,5,4,5,5,5,0.0,satisfied +24360,94485,Male,Loyal Customer,40,Business travel,Business,248,0,0,0,3,3,4,4,5,5,5,5,5,5,4,0,1.0,satisfied +24361,129367,Female,Loyal Customer,59,Personal Travel,Business,2454,4,2,4,3,5,3,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +24362,71087,Male,Loyal Customer,12,Personal Travel,Eco,802,4,2,4,4,1,4,1,1,1,2,4,1,4,1,0,11.0,neutral or dissatisfied +24363,44260,Female,Loyal Customer,67,Personal Travel,Eco,222,2,5,2,1,3,4,1,5,5,2,5,4,5,4,20,1.0,neutral or dissatisfied +24364,425,Male,Loyal Customer,59,Business travel,Business,3800,0,4,0,3,5,4,4,1,1,1,1,5,1,5,0,0.0,satisfied +24365,127391,Male,Loyal Customer,38,Business travel,Business,1585,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +24366,57724,Female,Loyal Customer,60,Business travel,Business,1754,2,5,2,2,5,3,5,5,5,5,5,3,5,3,5,0.0,satisfied +24367,105841,Female,Loyal Customer,37,Business travel,Business,2452,5,5,5,5,4,5,4,5,5,5,5,5,5,4,121,106.0,satisfied +24368,44751,Female,Loyal Customer,40,Personal Travel,Eco,612,4,5,4,2,3,4,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +24369,95885,Female,Loyal Customer,12,Personal Travel,Eco,580,3,2,3,3,4,3,4,4,1,5,4,2,4,4,0,0.0,neutral or dissatisfied +24370,63565,Male,disloyal Customer,50,Business travel,Business,1737,1,1,1,4,5,1,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +24371,107612,Female,disloyal Customer,24,Business travel,Business,423,5,0,5,5,4,5,1,4,4,3,5,5,4,4,0,0.0,satisfied +24372,33103,Male,Loyal Customer,16,Personal Travel,Eco,216,3,0,3,4,1,3,1,1,3,4,5,4,5,1,1,0.0,neutral or dissatisfied +24373,26837,Male,disloyal Customer,59,Business travel,Business,224,2,2,2,2,4,2,4,4,1,5,3,2,2,4,0,2.0,neutral or dissatisfied +24374,6779,Female,Loyal Customer,41,Business travel,Business,303,1,1,3,1,3,5,5,4,4,4,4,4,4,3,25,18.0,satisfied +24375,598,Male,Loyal Customer,56,Business travel,Business,247,2,2,3,2,4,4,5,5,5,5,5,5,5,3,1,8.0,satisfied +24376,16244,Male,Loyal Customer,60,Business travel,Eco,946,4,5,5,5,4,4,4,4,5,2,1,1,1,4,0,0.0,satisfied +24377,33278,Male,Loyal Customer,31,Personal Travel,Eco Plus,101,2,4,0,1,3,0,3,3,3,5,5,5,4,3,12,18.0,neutral or dissatisfied +24378,50680,Male,Loyal Customer,40,Personal Travel,Eco,158,3,5,0,3,3,0,3,3,5,2,5,3,4,3,1,0.0,neutral or dissatisfied +24379,63542,Female,Loyal Customer,19,Personal Travel,Eco,1009,2,4,2,1,3,2,2,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +24380,4102,Female,Loyal Customer,39,Business travel,Business,544,3,3,3,3,2,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +24381,77097,Female,disloyal Customer,22,Business travel,Business,1481,4,4,4,2,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +24382,6848,Male,Loyal Customer,30,Personal Travel,Eco Plus,224,1,5,1,4,3,1,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +24383,116523,Female,Loyal Customer,11,Personal Travel,Eco,446,2,4,2,4,1,2,1,1,5,5,5,4,4,1,7,2.0,neutral or dissatisfied +24384,47127,Female,Loyal Customer,48,Business travel,Business,945,5,5,5,5,5,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +24385,58682,Male,Loyal Customer,58,Personal Travel,Eco,837,3,5,3,3,5,3,5,5,1,3,4,5,1,5,0,0.0,neutral or dissatisfied +24386,45460,Male,Loyal Customer,44,Business travel,Business,522,5,5,3,5,5,3,4,4,4,4,4,3,4,5,8,0.0,satisfied +24387,81442,Female,Loyal Customer,24,Business travel,Business,528,4,5,4,4,4,4,4,4,3,5,4,4,4,4,2,0.0,satisfied +24388,25398,Male,disloyal Customer,37,Business travel,Business,1105,2,2,2,5,3,2,1,3,4,1,2,4,1,3,5,0.0,neutral or dissatisfied +24389,6435,Female,Loyal Customer,35,Personal Travel,Eco,240,3,5,0,1,3,0,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +24390,39558,Male,disloyal Customer,24,Business travel,Eco,620,5,0,5,2,4,5,5,4,5,5,4,5,5,4,0,0.0,satisfied +24391,20265,Female,disloyal Customer,40,Business travel,Business,228,4,4,4,3,4,4,4,4,2,3,5,4,1,4,30,3.0,satisfied +24392,111910,Male,Loyal Customer,34,Business travel,Eco Plus,628,2,1,1,1,2,2,2,2,2,2,4,1,4,2,3,15.0,neutral or dissatisfied +24393,108727,Male,disloyal Customer,38,Business travel,Eco,191,3,3,3,4,3,5,5,1,1,3,4,5,3,5,128,337.0,neutral or dissatisfied +24394,126638,Female,Loyal Customer,32,Business travel,Business,1566,3,3,1,3,3,3,3,3,5,3,4,4,4,3,0,0.0,satisfied +24395,10600,Male,Loyal Customer,48,Business travel,Business,3761,5,5,5,5,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +24396,53244,Male,Loyal Customer,25,Business travel,Eco Plus,612,0,3,0,3,5,0,5,5,1,2,3,2,1,5,0,18.0,satisfied +24397,2484,Male,Loyal Customer,21,Business travel,Business,1379,1,1,1,1,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +24398,46278,Male,Loyal Customer,15,Personal Travel,Eco,679,2,4,2,1,3,2,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +24399,67037,Male,Loyal Customer,22,Business travel,Business,929,3,3,3,3,4,4,4,4,4,3,4,5,5,4,21,14.0,satisfied +24400,72089,Male,Loyal Customer,13,Personal Travel,Eco,2504,5,3,5,2,3,5,3,3,1,5,3,3,2,3,10,0.0,satisfied +24401,57465,Male,Loyal Customer,36,Personal Travel,Eco,334,3,4,3,1,3,3,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +24402,91753,Female,disloyal Customer,17,Business travel,Business,590,5,0,5,2,3,5,3,3,4,5,4,4,4,3,0,0.0,satisfied +24403,111721,Female,Loyal Customer,70,Personal Travel,Eco,495,2,1,2,2,5,2,3,4,4,2,4,2,4,1,20,16.0,neutral or dissatisfied +24404,1237,Female,Loyal Customer,51,Personal Travel,Eco,354,4,4,3,2,3,4,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +24405,26257,Female,Loyal Customer,33,Personal Travel,Eco Plus,406,3,4,3,2,3,3,3,3,3,4,5,4,5,3,71,65.0,neutral or dissatisfied +24406,125843,Female,disloyal Customer,30,Business travel,Business,992,1,0,0,5,2,0,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +24407,20713,Female,disloyal Customer,24,Business travel,Eco,707,5,5,5,5,4,5,4,4,1,5,4,1,5,4,0,0.0,satisfied +24408,68977,Male,Loyal Customer,47,Personal Travel,Eco,700,1,5,1,1,4,1,4,4,5,2,5,5,4,4,0,8.0,neutral or dissatisfied +24409,118561,Male,Loyal Customer,38,Business travel,Business,3904,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +24410,35838,Female,Loyal Customer,38,Business travel,Business,1068,3,5,5,5,2,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +24411,53133,Male,Loyal Customer,53,Personal Travel,Eco Plus,2065,2,5,2,3,2,1,1,3,4,4,4,1,5,1,203,190.0,neutral or dissatisfied +24412,25722,Female,disloyal Customer,20,Business travel,Eco,528,0,1,0,4,1,0,1,1,1,2,2,5,1,1,0,0.0,satisfied +24413,49314,Male,disloyal Customer,27,Business travel,Eco,421,1,5,1,5,1,1,1,1,2,4,3,1,5,1,2,0.0,neutral or dissatisfied +24414,68892,Female,Loyal Customer,51,Business travel,Business,3526,2,5,5,5,2,3,4,2,2,2,2,3,2,4,0,11.0,neutral or dissatisfied +24415,55474,Female,Loyal Customer,59,Personal Travel,Eco,1825,2,4,2,4,3,2,4,3,3,2,5,4,3,4,0,0.0,neutral or dissatisfied +24416,3240,Male,Loyal Customer,58,Business travel,Business,483,3,3,3,3,5,5,4,4,4,4,4,4,4,3,12,23.0,satisfied +24417,98105,Female,Loyal Customer,43,Business travel,Business,1561,0,0,0,2,4,4,4,2,2,2,2,3,2,4,1,3.0,satisfied +24418,35763,Female,Loyal Customer,34,Business travel,Business,3755,0,5,0,3,5,2,4,3,3,3,3,4,3,2,0,0.0,satisfied +24419,14931,Female,Loyal Customer,64,Personal Travel,Business,554,4,5,4,1,2,5,5,5,5,4,5,5,5,5,0,8.0,neutral or dissatisfied +24420,93536,Male,Loyal Customer,56,Personal Travel,Eco,1218,3,4,3,4,3,3,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +24421,79758,Female,Loyal Customer,25,Business travel,Business,1005,2,2,3,2,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +24422,106300,Male,disloyal Customer,25,Business travel,Eco,998,1,1,1,5,5,1,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +24423,72668,Male,Loyal Customer,30,Personal Travel,Eco,985,2,3,1,4,5,1,5,5,2,2,3,1,4,5,11,5.0,neutral or dissatisfied +24424,44283,Male,Loyal Customer,16,Personal Travel,Eco Plus,359,1,2,1,3,1,1,1,1,3,1,3,2,2,1,0,0.0,neutral or dissatisfied +24425,53218,Female,Loyal Customer,56,Business travel,Eco,189,5,2,2,2,1,2,3,5,5,5,5,3,5,2,58,52.0,satisfied +24426,39941,Male,Loyal Customer,49,Business travel,Eco,795,5,3,3,3,5,5,5,5,4,1,5,4,2,5,9,0.0,satisfied +24427,66326,Male,Loyal Customer,63,Personal Travel,Eco,852,3,5,3,1,4,3,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +24428,10458,Female,Loyal Customer,61,Business travel,Business,3114,3,3,3,3,4,5,5,3,3,4,3,5,3,4,66,67.0,satisfied +24429,96380,Male,Loyal Customer,59,Business travel,Business,1342,2,2,2,2,4,5,4,4,4,4,4,4,4,3,22,23.0,satisfied +24430,39051,Male,Loyal Customer,23,Personal Travel,Eco Plus,230,3,4,3,5,5,3,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +24431,115263,Female,Loyal Customer,43,Business travel,Business,373,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +24432,676,Female,Loyal Customer,52,Business travel,Business,229,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +24433,120123,Male,Loyal Customer,11,Personal Travel,Eco,1576,1,5,1,2,1,1,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +24434,35002,Female,Loyal Customer,67,Business travel,Business,2754,1,1,4,1,1,4,3,4,4,4,4,1,4,4,2,0.0,satisfied +24435,98314,Male,Loyal Customer,26,Personal Travel,Eco,1565,2,4,3,3,5,3,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +24436,98680,Female,Loyal Customer,17,Personal Travel,Eco,834,2,4,2,4,2,2,2,4,5,4,5,2,5,2,263,247.0,neutral or dissatisfied +24437,102221,Female,Loyal Customer,59,Business travel,Eco,391,1,5,5,5,3,3,4,1,1,1,1,3,1,2,0,4.0,neutral or dissatisfied +24438,36691,Female,Loyal Customer,35,Personal Travel,Eco,1121,3,4,3,3,5,3,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +24439,68544,Male,Loyal Customer,48,Personal Travel,Eco,1013,3,5,3,4,2,3,4,2,2,2,3,2,5,2,0,0.0,neutral or dissatisfied +24440,48851,Female,Loyal Customer,24,Personal Travel,Business,199,2,4,2,4,2,2,2,2,4,5,5,5,5,2,10,22.0,neutral or dissatisfied +24441,69200,Male,disloyal Customer,45,Business travel,Business,733,2,3,3,3,1,2,1,1,5,3,4,4,4,1,108,121.0,neutral or dissatisfied +24442,79776,Male,disloyal Customer,29,Business travel,Business,944,3,3,3,3,4,3,4,4,2,4,4,2,4,4,48,51.0,neutral or dissatisfied +24443,90542,Male,Loyal Customer,57,Business travel,Business,3228,1,1,1,1,5,5,4,5,5,5,5,3,5,5,15,49.0,satisfied +24444,29805,Female,Loyal Customer,25,Business travel,Business,3532,4,4,4,4,4,4,4,4,4,5,1,4,1,4,0,0.0,satisfied +24445,106693,Male,Loyal Customer,52,Business travel,Business,516,5,5,5,5,4,4,4,4,4,4,4,5,4,3,20,18.0,satisfied +24446,105145,Male,Loyal Customer,48,Business travel,Business,3360,2,5,3,5,4,3,3,2,2,2,2,4,2,3,31,11.0,neutral or dissatisfied +24447,25348,Male,disloyal Customer,18,Business travel,Eco,691,1,1,1,1,1,3,3,4,1,3,4,3,5,3,315,297.0,neutral or dissatisfied +24448,7735,Male,disloyal Customer,24,Business travel,Business,489,0,0,0,2,3,0,3,3,4,4,5,3,4,3,0,0.0,satisfied +24449,77987,Male,disloyal Customer,41,Business travel,Eco,332,4,2,4,3,4,4,4,4,3,1,4,3,3,4,43,22.0,neutral or dissatisfied +24450,123847,Female,Loyal Customer,42,Business travel,Business,541,1,1,1,1,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +24451,67717,Male,Loyal Customer,56,Business travel,Business,1235,4,4,4,4,4,4,4,4,4,4,4,3,4,3,10,15.0,satisfied +24452,106834,Male,Loyal Customer,60,Business travel,Business,1733,4,4,4,4,4,4,4,3,5,3,4,4,5,4,381,436.0,satisfied +24453,128746,Female,disloyal Customer,46,Business travel,Eco,2402,2,3,3,3,2,5,5,3,4,4,3,5,3,5,0,6.0,neutral or dissatisfied +24454,22433,Male,Loyal Customer,44,Personal Travel,Eco,238,4,4,4,1,3,4,3,3,3,4,5,3,4,3,13,7.0,neutral or dissatisfied +24455,119308,Female,Loyal Customer,49,Business travel,Business,2233,4,1,1,1,2,4,3,1,1,1,4,2,1,2,13,0.0,neutral or dissatisfied +24456,87541,Female,Loyal Customer,31,Business travel,Business,1980,4,3,3,3,4,4,4,1,5,4,3,4,1,4,324,307.0,neutral or dissatisfied +24457,13544,Male,Loyal Customer,59,Business travel,Business,3808,1,5,5,5,2,1,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +24458,59991,Male,Loyal Customer,26,Personal Travel,Eco,1023,3,1,3,3,2,3,2,2,2,4,4,3,4,2,18,7.0,neutral or dissatisfied +24459,15086,Male,Loyal Customer,60,Business travel,Business,2644,3,3,3,3,2,4,3,3,3,3,3,2,3,3,22,27.0,neutral or dissatisfied +24460,111013,Male,disloyal Customer,22,Business travel,Eco,240,2,0,2,3,5,2,5,5,3,3,5,3,5,5,20,20.0,neutral or dissatisfied +24461,46662,Female,disloyal Customer,25,Business travel,Eco,125,2,0,2,4,2,2,2,2,2,4,2,5,3,2,0,0.0,neutral or dissatisfied +24462,127464,Male,Loyal Customer,42,Business travel,Eco,2075,2,2,2,2,2,2,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +24463,72512,Female,disloyal Customer,24,Business travel,Eco,1017,4,4,4,2,3,4,3,3,5,4,5,3,5,3,8,0.0,neutral or dissatisfied +24464,84771,Male,Loyal Customer,25,Business travel,Business,1506,2,2,2,2,4,4,4,4,5,5,5,5,4,4,23,12.0,satisfied +24465,21875,Female,Loyal Customer,32,Business travel,Business,3678,5,5,5,5,4,4,4,4,2,4,3,1,1,4,0,0.0,satisfied +24466,69509,Male,Loyal Customer,20,Personal Travel,Eco,1746,3,0,4,3,4,4,4,4,4,2,4,2,3,4,1,0.0,neutral or dissatisfied +24467,28133,Male,Loyal Customer,53,Business travel,Business,3886,3,1,1,1,4,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +24468,24843,Female,Loyal Customer,24,Personal Travel,Eco,894,3,5,2,1,5,2,5,5,4,2,5,3,5,5,68,75.0,neutral or dissatisfied +24469,88462,Male,Loyal Customer,37,Business travel,Business,240,1,1,1,1,1,4,5,4,4,4,4,2,4,4,0,0.0,satisfied +24470,87234,Male,Loyal Customer,45,Personal Travel,Eco Plus,946,1,5,1,2,5,1,4,5,2,5,1,1,2,5,0,0.0,neutral or dissatisfied +24471,46511,Female,Loyal Customer,44,Business travel,Eco,125,5,1,1,1,3,3,2,5,5,5,5,2,5,2,0,0.0,satisfied +24472,74918,Female,Loyal Customer,32,Business travel,Business,2475,1,1,1,1,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +24473,86744,Male,Loyal Customer,29,Business travel,Business,821,5,5,3,5,4,4,4,4,3,4,4,3,5,4,62,63.0,satisfied +24474,97607,Female,disloyal Customer,30,Business travel,Eco,442,2,0,1,1,4,1,2,4,1,3,3,3,2,4,2,1.0,neutral or dissatisfied +24475,10525,Female,disloyal Customer,26,Business travel,Business,316,3,0,3,1,1,3,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +24476,110128,Female,Loyal Customer,59,Business travel,Business,3225,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,1.0,satisfied +24477,90211,Female,Loyal Customer,23,Personal Travel,Eco,1127,2,4,2,2,3,2,1,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +24478,104655,Male,Loyal Customer,58,Business travel,Business,2608,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,4.0,satisfied +24479,115463,Male,Loyal Customer,33,Business travel,Business,308,2,2,2,2,4,4,4,4,3,4,5,5,5,4,0,27.0,satisfied +24480,90355,Male,Loyal Customer,59,Business travel,Business,2853,2,1,1,1,2,2,2,2,2,1,2,2,2,4,0,19.0,neutral or dissatisfied +24481,47621,Female,Loyal Customer,49,Business travel,Business,1504,1,1,5,1,4,1,5,4,4,5,4,2,4,2,85,66.0,satisfied +24482,122986,Female,Loyal Customer,53,Business travel,Business,600,5,5,5,5,5,5,4,5,5,5,5,4,5,4,18,37.0,satisfied +24483,45455,Male,Loyal Customer,30,Business travel,Business,522,5,5,5,5,4,5,4,4,2,3,1,3,5,4,0,0.0,satisfied +24484,56934,Female,disloyal Customer,15,Business travel,Eco,998,3,3,3,2,3,5,5,2,2,2,3,5,3,5,51,31.0,neutral or dissatisfied +24485,124746,Male,Loyal Customer,66,Business travel,Business,280,4,4,4,4,5,4,5,4,4,4,4,5,4,4,60,50.0,satisfied +24486,17592,Female,Loyal Customer,45,Personal Travel,Eco Plus,1034,1,5,0,5,2,5,4,5,5,0,5,3,5,4,1,0.0,neutral or dissatisfied +24487,111090,Female,Loyal Customer,66,Personal Travel,Eco,319,1,2,1,3,4,2,2,2,2,1,4,1,2,3,0,0.0,neutral or dissatisfied +24488,66087,Female,disloyal Customer,26,Business travel,Business,1055,5,5,5,2,2,5,2,2,3,2,4,5,5,2,0,0.0,satisfied +24489,3900,Male,Loyal Customer,30,Personal Travel,Eco,290,4,4,2,1,4,2,4,4,3,4,5,3,4,4,0,0.0,satisfied +24490,115421,Female,Loyal Customer,49,Business travel,Business,3721,1,1,1,1,4,5,4,4,4,4,4,3,4,5,44,36.0,satisfied +24491,129697,Female,disloyal Customer,26,Business travel,Business,337,0,5,0,4,5,0,5,5,5,5,5,5,5,5,16,14.0,satisfied +24492,86046,Female,Loyal Customer,43,Personal Travel,Eco,447,4,5,4,3,5,4,4,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +24493,4506,Female,Loyal Customer,42,Personal Travel,Eco,435,3,5,3,1,2,4,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +24494,9640,Female,Loyal Customer,20,Personal Travel,Business,212,3,1,3,4,4,3,4,4,4,5,5,5,4,4,1,0.0,neutral or dissatisfied +24495,56670,Male,Loyal Customer,14,Personal Travel,Eco,937,2,5,2,1,4,2,4,4,3,2,4,1,2,4,0,0.0,neutral or dissatisfied +24496,24360,Male,Loyal Customer,16,Business travel,Eco Plus,634,0,3,0,4,2,0,1,2,4,2,1,5,5,2,0,0.0,satisfied +24497,14801,Female,disloyal Customer,22,Business travel,Eco,133,4,0,5,4,3,5,3,3,1,2,4,3,1,3,0,0.0,satisfied +24498,5269,Male,Loyal Customer,41,Personal Travel,Eco,351,5,5,5,3,3,5,2,3,3,3,5,3,5,3,0,0.0,satisfied +24499,124164,Female,Loyal Customer,43,Business travel,Business,2133,5,2,5,5,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +24500,99346,Male,Loyal Customer,40,Business travel,Eco,1771,4,3,3,3,4,4,4,4,3,4,4,2,3,4,0,17.0,neutral or dissatisfied +24501,89619,Female,disloyal Customer,27,Business travel,Business,1005,4,4,4,1,4,4,5,4,5,4,5,4,5,4,0,0.0,satisfied +24502,125102,Male,Loyal Customer,54,Business travel,Eco,361,2,4,4,4,2,2,2,2,3,5,3,1,3,2,0,6.0,neutral or dissatisfied +24503,26241,Male,Loyal Customer,70,Personal Travel,Eco,581,3,5,3,4,2,3,2,2,3,4,4,4,5,2,7,0.0,neutral or dissatisfied +24504,56632,Female,Loyal Customer,29,Business travel,Business,3294,4,1,1,1,4,4,4,4,1,4,4,4,3,4,7,7.0,neutral or dissatisfied +24505,128737,Male,Loyal Customer,46,Business travel,Business,2521,4,2,2,2,4,4,4,4,1,3,2,4,1,4,20,22.0,neutral or dissatisfied +24506,37091,Female,Loyal Customer,31,Business travel,Business,1851,5,5,5,5,4,4,4,4,2,3,4,4,4,4,21,15.0,satisfied +24507,89659,Male,disloyal Customer,43,Business travel,Business,1035,4,4,4,2,1,4,1,1,3,2,4,4,4,1,59,51.0,neutral or dissatisfied +24508,89156,Female,Loyal Customer,43,Personal Travel,Eco,2139,4,4,4,3,3,5,5,3,3,4,3,4,3,3,0,11.0,satisfied +24509,74528,Male,disloyal Customer,20,Business travel,Eco,1235,2,2,2,3,5,2,1,5,3,5,4,4,5,5,1,0.0,neutral or dissatisfied +24510,69783,Male,Loyal Customer,39,Business travel,Business,3993,4,4,4,4,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +24511,476,Female,Loyal Customer,62,Business travel,Business,3490,3,3,3,3,2,4,5,4,4,4,5,5,4,3,22,19.0,satisfied +24512,77628,Male,Loyal Customer,40,Business travel,Business,689,4,4,4,4,4,4,4,4,3,5,5,4,4,4,179,181.0,satisfied +24513,9859,Female,Loyal Customer,7,Personal Travel,Eco,642,1,3,1,4,5,1,5,5,2,5,4,1,4,5,0,0.0,neutral or dissatisfied +24514,101161,Female,disloyal Customer,24,Business travel,Eco,775,1,2,2,4,3,2,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +24515,108794,Female,disloyal Customer,50,Business travel,Eco,181,2,4,2,5,1,2,1,1,1,4,4,1,1,1,0,0.0,neutral or dissatisfied +24516,30948,Male,Loyal Customer,50,Business travel,Eco,1024,4,1,3,1,4,4,4,4,4,5,4,2,5,4,2,29.0,satisfied +24517,46933,Male,disloyal Customer,24,Business travel,Eco,819,4,4,4,4,1,4,1,1,4,5,2,3,5,1,19,10.0,satisfied +24518,78205,Female,Loyal Customer,69,Personal Travel,Eco,317,3,2,3,3,2,4,3,4,4,3,5,4,4,1,0,2.0,neutral or dissatisfied +24519,17907,Female,disloyal Customer,26,Business travel,Eco,900,2,2,2,4,4,2,4,4,5,4,5,5,3,4,92,72.0,neutral or dissatisfied +24520,1892,Male,Loyal Customer,45,Business travel,Business,3923,2,3,3,3,4,3,4,2,2,2,2,4,2,3,59,55.0,neutral or dissatisfied +24521,81847,Female,Loyal Customer,8,Personal Travel,Eco,1501,2,4,2,3,2,2,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +24522,18068,Male,Loyal Customer,51,Personal Travel,Eco,488,3,2,3,3,5,3,5,5,1,1,4,3,4,5,0,0.0,neutral or dissatisfied +24523,123832,Male,disloyal Customer,25,Business travel,Business,544,3,0,3,2,1,3,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +24524,104750,Female,Loyal Customer,41,Business travel,Eco,846,4,3,3,3,4,4,4,4,4,5,5,2,5,4,0,0.0,satisfied +24525,59463,Male,Loyal Customer,23,Business travel,Business,2858,5,5,5,5,4,4,4,4,5,4,5,3,5,4,7,0.0,satisfied +24526,30773,Male,Loyal Customer,55,Personal Travel,Business,834,3,4,3,1,3,4,4,1,1,3,1,3,1,4,43,39.0,neutral or dissatisfied +24527,107336,Female,Loyal Customer,57,Business travel,Business,2023,2,2,2,2,2,5,5,5,5,5,5,4,5,5,5,0.0,satisfied +24528,18944,Female,Loyal Customer,42,Personal Travel,Eco,448,2,5,3,3,2,5,4,4,4,3,4,5,4,3,16,14.0,neutral or dissatisfied +24529,71095,Male,Loyal Customer,58,Personal Travel,Eco Plus,802,2,5,2,4,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +24530,57431,Male,Loyal Customer,40,Business travel,Business,3347,3,3,3,3,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +24531,107995,Male,Loyal Customer,63,Business travel,Business,271,0,0,0,1,3,2,4,3,3,3,3,2,3,3,20,0.0,satisfied +24532,68362,Female,disloyal Customer,18,Business travel,Eco,1231,2,2,2,3,2,2,2,2,5,4,3,3,5,2,0,0.0,neutral or dissatisfied +24533,13295,Female,Loyal Customer,16,Business travel,Eco Plus,771,2,2,2,2,2,2,4,2,1,4,4,2,4,2,0,0.0,neutral or dissatisfied +24534,69052,Female,disloyal Customer,8,Business travel,Eco,1389,3,3,3,4,5,3,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +24535,429,Female,Loyal Customer,52,Personal Travel,Business,309,2,5,2,5,2,5,4,2,2,2,2,3,2,4,6,16.0,neutral or dissatisfied +24536,77567,Male,disloyal Customer,29,Business travel,Business,731,5,5,5,3,4,5,4,4,3,4,4,4,5,4,27,21.0,satisfied +24537,32282,Female,Loyal Customer,34,Business travel,Business,102,5,5,5,5,2,3,5,5,5,5,3,2,5,5,0,4.0,satisfied +24538,117209,Male,Loyal Customer,65,Personal Travel,Eco,651,3,2,3,3,2,3,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +24539,75087,Female,Loyal Customer,43,Personal Travel,Eco,1814,3,4,3,1,4,4,4,3,3,3,3,3,3,3,10,6.0,neutral or dissatisfied +24540,49609,Female,Loyal Customer,59,Business travel,Business,304,1,1,1,1,1,2,4,4,4,4,4,1,4,5,0,0.0,satisfied +24541,35189,Female,Loyal Customer,42,Business travel,Eco,828,4,1,1,1,2,2,2,4,4,4,4,2,4,5,0,21.0,satisfied +24542,48977,Male,Loyal Customer,63,Business travel,Business,2780,5,5,5,5,3,3,4,5,5,5,5,3,5,3,100,90.0,satisfied +24543,5016,Male,Loyal Customer,58,Personal Travel,Eco Plus,502,1,5,2,2,2,2,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +24544,64282,Female,Loyal Customer,56,Business travel,Business,2414,3,3,3,3,2,5,4,5,5,5,5,4,5,5,25,11.0,satisfied +24545,108215,Male,Loyal Customer,53,Business travel,Eco,777,2,5,5,5,2,2,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +24546,42185,Female,disloyal Customer,28,Business travel,Eco,834,5,5,5,3,4,5,3,4,1,3,3,4,5,4,0,10.0,satisfied +24547,7154,Female,Loyal Customer,27,Business travel,Business,1970,0,5,0,4,1,1,1,1,4,4,4,4,4,1,0,4.0,satisfied +24548,53752,Female,Loyal Customer,22,Business travel,Eco,1195,5,4,4,4,5,5,4,5,1,2,1,4,5,5,47,43.0,satisfied +24549,129242,Male,disloyal Customer,39,Business travel,Eco,1064,3,3,3,1,1,3,1,1,2,5,5,4,4,1,0,0.0,neutral or dissatisfied +24550,64522,Male,disloyal Customer,43,Business travel,Business,551,1,1,1,3,4,1,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +24551,42082,Male,Loyal Customer,29,Personal Travel,Eco Plus,106,2,4,0,3,5,0,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +24552,23728,Male,Loyal Customer,28,Personal Travel,Eco Plus,73,4,3,4,4,3,4,3,3,3,5,4,2,4,3,42,37.0,neutral or dissatisfied +24553,77854,Female,Loyal Customer,33,Personal Travel,Eco Plus,689,2,4,2,3,5,2,4,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +24554,129412,Female,disloyal Customer,37,Business travel,Eco,414,2,2,3,4,3,3,3,4,1,4,4,3,2,3,143,131.0,neutral or dissatisfied +24555,125985,Male,Loyal Customer,58,Personal Travel,Business,650,3,3,3,4,3,3,4,2,2,3,2,1,2,2,9,13.0,neutral or dissatisfied +24556,80847,Male,disloyal Customer,13,Business travel,Eco,484,1,2,1,4,1,1,1,1,3,1,3,2,4,1,8,3.0,neutral or dissatisfied +24557,9703,Female,Loyal Customer,51,Personal Travel,Eco,277,1,5,1,5,4,2,2,1,1,1,1,1,1,5,0,0.0,neutral or dissatisfied +24558,39089,Female,disloyal Customer,49,Business travel,Eco,984,1,1,1,1,1,1,1,1,2,2,1,3,5,1,0,0.0,neutral or dissatisfied +24559,46638,Male,Loyal Customer,37,Business travel,Eco,125,5,1,1,1,5,5,5,5,1,2,1,4,5,5,3,0.0,satisfied +24560,119922,Female,Loyal Customer,58,Business travel,Business,1507,2,2,2,2,4,5,4,5,5,5,5,3,5,4,3,6.0,satisfied +24561,6788,Male,Loyal Customer,64,Business travel,Eco,223,4,3,3,3,4,4,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +24562,54685,Female,Loyal Customer,10,Business travel,Eco,964,4,1,1,1,4,4,3,4,1,2,4,4,5,4,2,0.0,satisfied +24563,118619,Male,disloyal Customer,9,Business travel,Eco,651,3,4,3,3,1,3,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +24564,69955,Female,Loyal Customer,52,Personal Travel,Eco,2174,4,1,4,3,2,4,3,2,2,4,2,3,2,1,1,16.0,neutral or dissatisfied +24565,96782,Female,disloyal Customer,47,Business travel,Business,781,1,1,1,3,1,1,1,1,3,5,5,5,4,1,44,32.0,neutral or dissatisfied +24566,17655,Male,disloyal Customer,43,Business travel,Eco,1008,1,1,1,4,3,1,4,3,1,1,4,3,5,3,0,13.0,neutral or dissatisfied +24567,83145,Male,Loyal Customer,33,Personal Travel,Eco,1084,2,5,2,4,4,2,1,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +24568,18514,Female,Loyal Customer,42,Business travel,Business,1907,0,5,0,3,1,1,1,5,2,1,2,1,2,1,186,179.0,satisfied +24569,82622,Female,Loyal Customer,42,Personal Travel,Eco,528,3,4,3,4,3,4,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +24570,15950,Male,Loyal Customer,60,Personal Travel,Eco,607,2,5,2,3,4,2,4,4,4,4,4,3,4,4,0,40.0,neutral or dissatisfied +24571,55706,Male,Loyal Customer,48,Personal Travel,Eco,895,2,1,2,2,4,2,4,4,2,5,3,4,3,4,0,37.0,neutral or dissatisfied +24572,29623,Female,disloyal Customer,40,Business travel,Business,1448,3,2,2,4,1,2,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +24573,36889,Female,Loyal Customer,21,Personal Travel,Eco,1182,3,4,3,3,5,3,5,5,4,5,3,4,4,5,0,0.0,neutral or dissatisfied +24574,91163,Male,Loyal Customer,9,Personal Travel,Eco,594,1,5,1,1,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +24575,129180,Female,Loyal Customer,25,Business travel,Eco Plus,954,1,4,4,4,1,1,1,1,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +24576,44727,Female,Loyal Customer,54,Personal Travel,Eco,173,2,4,0,3,5,4,4,1,1,0,4,3,1,3,52,58.0,neutral or dissatisfied +24577,5873,Male,Loyal Customer,47,Business travel,Business,212,3,3,3,3,5,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +24578,117334,Male,Loyal Customer,54,Business travel,Business,393,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +24579,39701,Female,Loyal Customer,35,Business travel,Business,298,0,0,0,3,2,3,3,1,1,1,1,3,1,1,0,0.0,satisfied +24580,55133,Male,Loyal Customer,27,Personal Travel,Eco,1379,1,5,1,4,3,1,3,3,3,4,3,4,5,3,0,0.0,neutral or dissatisfied +24581,70583,Male,Loyal Customer,68,Personal Travel,Eco,1258,2,3,2,2,2,2,2,2,3,5,1,4,2,2,0,0.0,neutral or dissatisfied +24582,23687,Female,Loyal Customer,48,Business travel,Business,1836,5,5,5,5,2,3,5,4,4,4,5,4,4,5,7,12.0,satisfied +24583,119840,Male,disloyal Customer,45,Business travel,Eco,912,3,3,3,4,5,3,5,5,3,1,4,4,3,5,0,0.0,neutral or dissatisfied +24584,9230,Male,Loyal Customer,51,Business travel,Business,3848,1,2,2,2,1,2,2,3,3,3,1,1,3,4,0,26.0,neutral or dissatisfied +24585,56500,Female,Loyal Customer,60,Business travel,Business,1664,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +24586,36153,Female,Loyal Customer,40,Business travel,Eco Plus,818,5,2,2,2,5,5,5,5,4,3,2,5,2,5,0,23.0,satisfied +24587,45657,Male,Loyal Customer,39,Personal Travel,Eco,260,2,3,2,4,5,2,5,5,4,1,4,3,3,5,0,0.0,neutral or dissatisfied +24588,58589,Male,disloyal Customer,24,Business travel,Eco,334,4,0,4,2,4,4,4,4,5,2,5,4,5,4,4,0.0,satisfied +24589,59506,Male,disloyal Customer,36,Business travel,Business,787,3,3,3,4,1,3,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +24590,119115,Male,Loyal Customer,14,Personal Travel,Eco,1107,4,3,3,4,4,3,4,4,4,4,3,3,2,4,0,0.0,neutral or dissatisfied +24591,89344,Male,disloyal Customer,43,Business travel,Business,1587,2,2,2,4,5,2,5,5,4,2,5,5,4,5,1,0.0,neutral or dissatisfied +24592,9284,Male,disloyal Customer,26,Business travel,Eco,757,4,3,3,3,4,3,4,4,3,4,4,2,3,4,0,23.0,neutral or dissatisfied +24593,47464,Female,Loyal Customer,30,Personal Travel,Eco,590,1,4,2,3,2,2,3,2,5,3,4,4,4,2,17,28.0,neutral or dissatisfied +24594,35237,Male,Loyal Customer,35,Business travel,Business,1808,5,5,3,5,2,5,2,5,5,5,5,1,5,3,12,9.0,satisfied +24595,63152,Male,Loyal Customer,46,Business travel,Business,3046,0,0,0,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +24596,31811,Female,Loyal Customer,44,Personal Travel,Eco,2603,4,2,4,4,4,1,1,2,5,2,3,1,4,1,0,34.0,neutral or dissatisfied +24597,96311,Female,disloyal Customer,66,Business travel,Eco Plus,460,2,2,2,3,2,2,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +24598,51401,Female,Loyal Customer,45,Personal Travel,Eco Plus,109,3,5,3,2,3,4,5,3,3,5,5,5,4,5,175,165.0,neutral or dissatisfied +24599,103977,Female,Loyal Customer,36,Business travel,Business,1592,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +24600,76113,Female,disloyal Customer,23,Business travel,Eco,689,3,4,4,3,4,4,4,4,3,3,4,3,3,4,0,29.0,neutral or dissatisfied +24601,17882,Female,Loyal Customer,21,Personal Travel,Eco,399,2,5,2,3,4,2,4,4,5,4,5,5,4,4,1,5.0,neutral or dissatisfied +24602,27698,Male,Loyal Customer,47,Personal Travel,Eco,1107,2,1,2,1,3,2,3,3,1,5,2,3,2,3,0,0.0,neutral or dissatisfied +24603,82223,Female,Loyal Customer,46,Business travel,Business,405,2,1,1,1,2,4,3,2,2,2,2,1,2,4,60,64.0,neutral or dissatisfied +24604,44302,Female,Loyal Customer,46,Business travel,Business,1428,4,1,1,1,1,3,3,4,4,4,4,3,4,1,87,80.0,neutral or dissatisfied +24605,21476,Female,disloyal Customer,25,Business travel,Eco,399,2,0,2,1,5,2,5,5,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +24606,38143,Female,Loyal Customer,24,Personal Travel,Eco,1249,4,5,4,5,3,4,3,3,3,4,3,3,4,3,10,8.0,neutral or dissatisfied +24607,101234,Male,Loyal Customer,51,Personal Travel,Eco Plus,1090,3,5,3,5,1,3,1,1,4,5,4,1,5,1,110,126.0,neutral or dissatisfied +24608,93057,Male,Loyal Customer,51,Business travel,Business,297,3,3,3,3,5,4,5,4,4,4,4,5,4,4,49,34.0,satisfied +24609,81130,Male,Loyal Customer,10,Personal Travel,Eco,991,3,4,3,5,5,3,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +24610,114293,Male,Loyal Customer,30,Personal Travel,Eco,948,1,3,1,4,4,1,4,4,2,1,4,2,4,4,9,16.0,neutral or dissatisfied +24611,20612,Female,disloyal Customer,23,Business travel,Eco,864,3,3,3,4,3,3,3,3,4,4,4,1,3,3,1,0.0,neutral or dissatisfied +24612,57321,Female,disloyal Customer,42,Business travel,Business,414,1,0,0,4,3,1,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +24613,126507,Male,Loyal Customer,46,Business travel,Business,1972,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,6.0,satisfied +24614,55297,Male,Loyal Customer,37,Personal Travel,Eco,1585,1,4,1,1,4,1,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +24615,99411,Male,Loyal Customer,49,Business travel,Business,3111,5,5,5,5,5,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +24616,16508,Male,Loyal Customer,57,Personal Travel,Eco,143,3,5,3,3,1,3,1,1,5,5,4,5,1,1,0,0.0,neutral or dissatisfied +24617,64487,Female,Loyal Customer,34,Business travel,Business,3293,3,3,3,3,2,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +24618,62186,Male,disloyal Customer,35,Business travel,Eco,1491,4,4,4,4,4,4,4,4,5,1,1,2,4,4,0,0.0,neutral or dissatisfied +24619,57818,Male,Loyal Customer,53,Business travel,Business,622,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +24620,68742,Female,disloyal Customer,52,Business travel,Business,585,2,2,2,3,2,2,2,2,5,4,5,5,4,2,5,39.0,neutral or dissatisfied +24621,120795,Male,Loyal Customer,27,Business travel,Business,2916,3,3,3,3,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +24622,44229,Female,Loyal Customer,19,Business travel,Business,359,4,4,5,4,4,4,4,4,2,1,1,2,3,4,0,11.0,satisfied +24623,93947,Female,Loyal Customer,64,Personal Travel,Eco,507,3,5,3,5,2,5,5,2,2,3,2,5,2,5,65,66.0,neutral or dissatisfied +24624,106364,Male,Loyal Customer,27,Business travel,Business,3339,1,1,1,1,3,3,3,3,5,2,4,3,5,3,25,15.0,satisfied +24625,20739,Male,Loyal Customer,43,Business travel,Business,363,2,2,2,2,3,4,1,5,5,5,5,4,5,2,0,23.0,satisfied +24626,39818,Female,Loyal Customer,49,Business travel,Business,2811,1,1,1,1,5,2,1,5,5,5,5,2,5,4,0,0.0,satisfied +24627,63052,Female,Loyal Customer,29,Personal Travel,Eco,909,3,4,3,2,4,3,4,4,2,3,4,2,1,4,19,17.0,neutral or dissatisfied +24628,76733,Male,Loyal Customer,11,Personal Travel,Eco Plus,534,1,4,4,5,3,4,3,3,4,3,5,4,5,3,16,17.0,neutral or dissatisfied +24629,79553,Female,Loyal Customer,30,Business travel,Business,2773,1,1,1,1,4,4,4,4,4,4,5,4,4,4,65,65.0,satisfied +24630,87778,Male,Loyal Customer,28,Business travel,Business,2986,1,5,5,5,3,3,1,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +24631,69195,Male,Loyal Customer,60,Business travel,Eco Plus,187,5,2,2,2,5,5,5,5,2,1,1,4,2,5,0,0.0,satisfied +24632,75934,Male,Loyal Customer,69,Personal Travel,Eco,872,2,4,2,3,3,2,3,3,1,2,1,3,3,3,8,2.0,neutral or dissatisfied +24633,67534,Female,disloyal Customer,23,Business travel,Eco,1171,3,3,3,3,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +24634,48990,Male,Loyal Customer,40,Business travel,Eco,209,2,4,4,4,2,2,2,2,5,5,4,2,3,2,0,0.0,satisfied +24635,116787,Male,Loyal Customer,28,Personal Travel,Eco Plus,342,4,4,4,3,1,4,2,1,3,5,3,1,3,1,9,3.0,neutral or dissatisfied +24636,28699,Male,Loyal Customer,32,Business travel,Eco,2172,3,3,3,3,3,4,3,3,1,4,4,4,1,3,0,0.0,satisfied +24637,71929,Female,Loyal Customer,42,Business travel,Eco Plus,1846,3,2,2,2,1,4,3,3,3,3,3,3,3,2,10,12.0,neutral or dissatisfied +24638,112592,Female,Loyal Customer,7,Business travel,Business,2390,1,4,4,4,1,1,1,1,2,3,3,2,2,1,47,30.0,neutral or dissatisfied +24639,47740,Male,Loyal Customer,47,Personal Travel,Business,834,3,4,3,1,3,1,5,4,4,5,5,5,5,5,214,217.0,neutral or dissatisfied +24640,90660,Male,Loyal Customer,39,Business travel,Business,581,1,1,1,1,3,4,5,4,4,4,4,5,4,3,38,33.0,satisfied +24641,94868,Male,disloyal Customer,20,Business travel,Eco,323,2,2,2,4,5,2,3,5,4,5,3,1,3,5,0,1.0,neutral or dissatisfied +24642,52297,Male,Loyal Customer,72,Business travel,Eco,237,4,2,3,3,4,4,4,4,3,3,3,1,4,4,0,0.0,neutral or dissatisfied +24643,92338,Male,Loyal Customer,47,Business travel,Business,2486,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +24644,25917,Male,disloyal Customer,26,Business travel,Eco,594,2,0,2,5,2,2,2,2,1,3,3,1,1,2,6,5.0,neutral or dissatisfied +24645,93855,Male,Loyal Customer,42,Business travel,Business,3242,3,3,3,3,4,4,5,4,4,4,4,5,4,5,21,8.0,satisfied +24646,117804,Male,disloyal Customer,17,Business travel,Business,328,0,0,0,5,1,0,1,1,5,3,4,4,5,1,0,0.0,satisfied +24647,69656,Female,Loyal Customer,25,Business travel,Business,569,4,2,2,2,4,4,4,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +24648,34763,Male,disloyal Customer,39,Business travel,Eco,301,2,3,2,2,1,2,1,1,3,4,5,4,1,1,0,0.0,neutral or dissatisfied +24649,41674,Female,Loyal Customer,52,Business travel,Business,2673,3,3,3,3,1,3,5,5,5,5,5,2,5,4,0,0.0,satisfied +24650,70357,Male,Loyal Customer,13,Personal Travel,Eco Plus,986,2,5,2,3,4,2,5,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +24651,68473,Male,Loyal Customer,17,Business travel,Business,1303,2,2,2,2,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +24652,15166,Male,Loyal Customer,22,Business travel,Eco,416,5,3,1,3,5,5,5,5,3,3,2,1,4,5,0,0.0,satisfied +24653,118330,Female,Loyal Customer,30,Business travel,Business,3822,4,5,2,5,4,4,4,2,5,4,3,4,1,4,242,223.0,neutral or dissatisfied +24654,124808,Female,Loyal Customer,25,Business travel,Business,1648,1,2,2,2,1,1,1,1,1,3,4,1,3,1,70,62.0,neutral or dissatisfied +24655,61432,Male,Loyal Customer,26,Business travel,Business,2419,1,1,1,1,5,5,5,5,4,3,5,3,4,5,10,2.0,satisfied +24656,81652,Female,Loyal Customer,41,Business travel,Business,907,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,8.0,satisfied +24657,43254,Male,Loyal Customer,30,Business travel,Business,1926,4,4,2,4,4,4,4,4,5,5,1,5,3,4,0,0.0,satisfied +24658,117588,Female,Loyal Customer,23,Business travel,Business,1020,3,5,5,5,3,3,3,3,2,2,3,2,4,3,75,53.0,neutral or dissatisfied +24659,47255,Male,Loyal Customer,47,Business travel,Business,590,1,4,4,4,1,2,2,1,1,1,1,1,1,1,75,72.0,neutral or dissatisfied +24660,59315,Male,Loyal Customer,51,Business travel,Business,2449,1,1,5,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +24661,49237,Female,Loyal Customer,47,Business travel,Business,86,1,1,4,1,1,5,3,5,5,5,4,3,5,4,43,39.0,satisfied +24662,79639,Male,Loyal Customer,45,Business travel,Business,1898,2,3,3,3,5,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +24663,28743,Female,Loyal Customer,45,Business travel,Eco,1024,2,1,1,1,2,4,3,2,2,2,2,1,2,3,0,13.0,neutral or dissatisfied +24664,95937,Male,Loyal Customer,59,Business travel,Business,1411,3,3,3,3,5,4,4,4,4,4,4,3,4,4,7,0.0,satisfied +24665,80969,Male,disloyal Customer,22,Business travel,Eco,297,2,4,1,4,4,1,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +24666,75952,Female,Loyal Customer,40,Business travel,Business,297,3,3,3,3,4,4,4,5,5,5,5,3,5,5,21,20.0,satisfied +24667,51561,Male,disloyal Customer,26,Business travel,Eco,651,3,5,3,3,3,3,3,3,5,5,1,5,4,3,0,0.0,neutral or dissatisfied +24668,127716,Female,Loyal Customer,58,Business travel,Business,3262,2,2,2,2,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +24669,71628,Female,Loyal Customer,36,Business travel,Business,2873,4,4,3,4,4,1,5,5,5,5,5,2,5,2,0,0.0,satisfied +24670,90572,Male,Loyal Customer,40,Business travel,Business,3230,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +24671,74611,Male,disloyal Customer,38,Business travel,Business,1235,5,5,5,4,5,5,5,5,3,2,4,5,4,5,0,0.0,satisfied +24672,13802,Male,Loyal Customer,66,Personal Travel,Eco,450,2,5,5,3,4,5,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +24673,109098,Male,Loyal Customer,70,Personal Travel,Eco,928,3,5,3,3,2,3,2,2,1,4,3,4,5,2,37,30.0,neutral or dissatisfied +24674,120531,Female,Loyal Customer,32,Personal Travel,Eco,96,3,5,0,2,5,0,2,5,4,2,4,5,4,5,0,9.0,neutral or dissatisfied +24675,65287,Female,Loyal Customer,68,Personal Travel,Eco Plus,224,3,4,3,3,3,4,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +24676,15420,Female,Loyal Customer,28,Business travel,Business,3965,5,5,5,5,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +24677,52493,Female,Loyal Customer,34,Personal Travel,Eco Plus,370,4,2,4,3,3,4,2,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +24678,91014,Male,Loyal Customer,35,Personal Travel,Eco,366,1,2,1,3,3,1,1,3,1,4,2,2,2,3,0,0.0,neutral or dissatisfied +24679,51741,Female,Loyal Customer,65,Personal Travel,Eco,598,0,2,0,3,4,5,5,2,2,0,2,4,2,3,90,80.0,satisfied +24680,41630,Female,disloyal Customer,36,Business travel,Eco,374,2,1,2,1,2,2,2,2,4,3,2,4,1,2,49,57.0,neutral or dissatisfied +24681,113961,Female,Loyal Customer,60,Business travel,Business,1844,1,1,1,1,5,3,5,3,3,4,3,4,3,4,42,38.0,satisfied +24682,22762,Male,disloyal Customer,39,Business travel,Eco,147,4,0,4,1,4,4,4,4,2,1,4,2,1,4,0,0.0,neutral or dissatisfied +24683,118748,Male,Loyal Customer,19,Personal Travel,Eco,304,4,4,4,3,1,4,1,1,3,5,5,3,5,1,14,9.0,neutral or dissatisfied +24684,122893,Female,Loyal Customer,60,Personal Travel,Eco Plus,226,2,2,2,4,4,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +24685,5913,Male,Loyal Customer,15,Personal Travel,Eco,67,4,4,4,3,2,4,2,2,1,5,3,2,4,2,0,12.0,satisfied +24686,81881,Female,Loyal Customer,39,Business travel,Business,680,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +24687,95285,Female,Loyal Customer,69,Personal Travel,Eco,248,3,4,3,2,5,4,4,4,4,3,4,5,4,3,9,10.0,neutral or dissatisfied +24688,12691,Female,Loyal Customer,48,Business travel,Eco,689,4,2,2,2,4,2,3,4,4,4,4,1,4,3,27,11.0,satisfied +24689,109308,Male,Loyal Customer,44,Business travel,Business,1188,5,2,5,5,2,4,4,2,2,2,2,3,2,5,9,0.0,satisfied +24690,128523,Female,Loyal Customer,44,Personal Travel,Eco,646,2,2,2,3,3,3,3,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +24691,19894,Male,Loyal Customer,32,Business travel,Eco,315,5,5,5,5,5,5,5,5,3,5,3,4,4,5,0,0.0,satisfied +24692,42948,Male,Loyal Customer,55,Business travel,Eco,391,4,3,3,3,4,4,4,4,1,4,4,2,3,4,0,10.0,satisfied +24693,122114,Male,Loyal Customer,66,Business travel,Business,130,3,3,3,3,4,4,4,3,3,4,4,3,3,4,0,0.0,satisfied +24694,61505,Male,Loyal Customer,54,Business travel,Eco,2419,2,4,4,4,2,2,2,2,1,2,3,3,4,2,4,0.0,neutral or dissatisfied +24695,69686,Male,Loyal Customer,42,Business travel,Business,569,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +24696,90573,Female,Loyal Customer,39,Business travel,Eco,545,1,5,5,5,1,1,1,1,2,1,3,4,2,1,15,15.0,neutral or dissatisfied +24697,13665,Male,Loyal Customer,48,Business travel,Business,2758,2,3,3,3,3,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +24698,7077,Female,Loyal Customer,36,Business travel,Eco,177,1,5,5,5,1,1,1,1,4,4,3,3,3,1,17,8.0,neutral or dissatisfied +24699,67820,Female,Loyal Customer,38,Business travel,Eco,771,3,3,5,5,3,3,3,3,1,1,3,2,4,3,83,89.0,neutral or dissatisfied +24700,77222,Female,disloyal Customer,23,Business travel,Business,1590,4,3,4,1,4,1,1,4,4,4,5,1,5,1,290,279.0,satisfied +24701,7008,Male,Loyal Customer,45,Business travel,Eco,299,2,3,5,3,3,2,3,3,3,3,3,3,4,3,20,26.0,neutral or dissatisfied +24702,31118,Female,Loyal Customer,51,Business travel,Eco,991,3,5,4,5,3,2,2,3,3,3,3,2,3,4,0,32.0,satisfied +24703,20986,Female,Loyal Customer,43,Personal Travel,Eco,689,2,5,2,3,3,4,4,5,5,2,5,5,5,4,10,16.0,neutral or dissatisfied +24704,7064,Male,Loyal Customer,49,Business travel,Business,1699,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +24705,47145,Male,Loyal Customer,30,Business travel,Business,3683,3,3,1,3,4,4,4,4,2,2,1,4,5,4,86,77.0,satisfied +24706,87563,Female,Loyal Customer,50,Business travel,Eco,432,2,1,3,1,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +24707,42405,Female,Loyal Customer,44,Business travel,Eco Plus,838,1,3,3,3,5,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +24708,3495,Female,Loyal Customer,32,Personal Travel,Eco,1080,4,4,4,3,2,4,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +24709,100850,Female,Loyal Customer,52,Personal Travel,Eco,711,3,4,3,1,2,5,4,5,5,3,5,2,5,1,0,0.0,neutral or dissatisfied +24710,71845,Female,Loyal Customer,66,Business travel,Business,1744,4,1,3,1,1,1,2,4,4,4,4,3,4,1,0,1.0,neutral or dissatisfied +24711,22893,Male,Loyal Customer,37,Business travel,Eco Plus,170,5,2,5,2,5,5,5,5,5,5,1,4,5,5,0,0.0,satisfied +24712,121029,Female,Loyal Customer,46,Personal Travel,Eco,1013,2,2,2,3,5,3,3,2,2,2,2,4,2,1,3,0.0,neutral or dissatisfied +24713,20149,Male,disloyal Customer,33,Business travel,Eco,403,3,0,3,5,3,3,3,3,3,5,5,5,1,3,0,0.0,neutral or dissatisfied +24714,61307,Female,Loyal Customer,37,Personal Travel,Eco,862,2,4,2,4,1,2,1,1,5,5,4,3,5,1,4,0.0,neutral or dissatisfied +24715,82468,Female,Loyal Customer,36,Personal Travel,Eco,502,2,4,2,4,3,2,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +24716,1407,Male,Loyal Customer,49,Personal Travel,Eco Plus,113,3,3,3,3,4,3,4,4,2,5,4,1,4,4,0,5.0,neutral or dissatisfied +24717,91594,Female,Loyal Customer,63,Personal Travel,Business,1312,2,4,2,1,3,4,4,4,4,2,4,3,4,4,5,0.0,neutral or dissatisfied +24718,22807,Female,Loyal Customer,53,Business travel,Business,1505,2,3,3,3,3,2,3,3,3,3,2,1,3,4,0,0.0,neutral or dissatisfied +24719,114321,Female,Loyal Customer,34,Personal Travel,Eco,948,1,3,1,3,1,1,1,1,2,1,4,4,3,1,0,0.0,neutral or dissatisfied +24720,99909,Male,Loyal Customer,34,Business travel,Business,1428,2,2,2,2,4,4,5,4,4,4,4,4,4,4,17,26.0,satisfied +24721,14576,Male,disloyal Customer,23,Business travel,Eco,986,1,1,1,3,2,1,2,2,2,4,4,1,3,2,15,4.0,neutral or dissatisfied +24722,25342,Male,disloyal Customer,28,Business travel,Eco Plus,829,2,2,2,2,1,2,1,1,1,4,2,1,3,1,0,8.0,neutral or dissatisfied +24723,72076,Male,Loyal Customer,60,Business travel,Eco,2615,4,1,1,1,4,4,4,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +24724,46714,Female,Loyal Customer,57,Personal Travel,Eco,125,4,1,4,2,5,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +24725,115907,Male,Loyal Customer,49,Business travel,Eco,337,1,2,2,2,2,1,2,2,2,4,1,1,2,2,0,6.0,neutral or dissatisfied +24726,127864,Female,Loyal Customer,39,Business travel,Business,2840,3,3,3,3,3,5,4,4,4,4,4,5,4,5,5,2.0,satisfied +24727,386,Female,Loyal Customer,58,Business travel,Business,2759,2,2,2,2,2,5,4,4,4,4,4,3,4,4,59,51.0,satisfied +24728,35762,Female,Loyal Customer,16,Business travel,Business,200,0,4,0,4,3,3,4,3,5,4,4,5,4,3,0,0.0,satisfied +24729,31560,Male,Loyal Customer,69,Personal Travel,Eco,853,5,1,5,2,3,5,3,3,4,1,2,4,2,3,0,0.0,satisfied +24730,111188,Female,disloyal Customer,22,Business travel,Business,1546,5,0,5,4,1,0,5,1,5,2,5,4,4,1,18,13.0,satisfied +24731,96894,Male,Loyal Customer,15,Personal Travel,Eco,488,2,4,5,1,3,5,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +24732,57516,Male,Loyal Customer,22,Personal Travel,Eco,235,2,5,2,4,4,2,4,4,4,5,5,4,5,4,22,2.0,neutral or dissatisfied +24733,58241,Female,Loyal Customer,41,Business travel,Business,3646,5,5,5,5,5,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +24734,125226,Female,disloyal Customer,24,Business travel,Eco,651,4,0,4,1,2,4,2,2,4,2,4,5,5,2,0,0.0,satisfied +24735,101490,Male,disloyal Customer,64,Business travel,Business,345,2,2,2,3,5,2,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +24736,8433,Female,Loyal Customer,12,Personal Travel,Eco,737,1,5,1,2,2,1,2,2,4,5,5,4,4,2,3,1.0,neutral or dissatisfied +24737,18604,Female,Loyal Customer,58,Business travel,Eco,190,3,4,4,4,5,4,4,3,3,3,3,2,3,1,28,9.0,neutral or dissatisfied +24738,127863,Female,Loyal Customer,39,Business travel,Business,1276,5,5,5,5,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +24739,127162,Female,Loyal Customer,15,Personal Travel,Eco,646,2,3,2,2,4,2,4,4,5,1,1,3,1,4,0,0.0,neutral or dissatisfied +24740,31707,Female,Loyal Customer,22,Personal Travel,Eco,967,1,5,2,4,3,2,1,3,4,3,4,4,4,3,66,57.0,neutral or dissatisfied +24741,118141,Female,Loyal Customer,59,Business travel,Business,1444,1,1,1,1,4,5,5,3,3,4,3,3,3,4,15,24.0,satisfied +24742,127753,Male,Loyal Customer,61,Personal Travel,Eco,255,1,5,1,1,5,1,5,5,2,2,1,3,2,5,0,0.0,neutral or dissatisfied +24743,37547,Female,Loyal Customer,30,Business travel,Business,1069,5,5,5,5,4,4,4,4,2,5,3,2,2,4,0,0.0,satisfied +24744,21338,Female,disloyal Customer,25,Business travel,Eco,761,2,3,3,1,3,3,1,3,3,2,2,2,4,3,0,0.0,neutral or dissatisfied +24745,46387,Female,Loyal Customer,23,Business travel,Business,681,5,5,5,5,5,5,5,5,1,2,1,3,1,5,0,0.0,satisfied +24746,11240,Male,Loyal Customer,18,Personal Travel,Eco,667,2,5,2,4,4,2,3,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +24747,85289,Male,Loyal Customer,50,Personal Travel,Eco,813,1,1,1,3,3,1,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +24748,10914,Male,Loyal Customer,56,Business travel,Business,429,2,4,4,4,2,4,4,2,2,2,2,4,2,3,1,0.0,neutral or dissatisfied +24749,71183,Male,Loyal Customer,43,Business travel,Business,733,5,5,1,5,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +24750,50773,Female,Loyal Customer,18,Personal Travel,Eco,156,3,5,3,5,3,3,3,3,3,2,4,5,4,3,1,0.0,neutral or dissatisfied +24751,64809,Male,disloyal Customer,25,Business travel,Business,247,2,4,2,4,3,2,3,3,5,3,5,4,5,3,6,0.0,neutral or dissatisfied +24752,122516,Female,Loyal Customer,59,Personal Travel,Eco,930,1,5,1,4,5,3,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +24753,46506,Male,disloyal Customer,22,Business travel,Eco,141,5,5,5,1,4,5,1,4,1,4,2,4,3,4,0,0.0,satisfied +24754,15468,Male,Loyal Customer,16,Personal Travel,Eco,331,4,4,2,5,3,2,3,3,4,2,5,3,5,3,0,2.0,neutral or dissatisfied +24755,115194,Female,Loyal Customer,60,Business travel,Business,296,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +24756,81615,Female,disloyal Customer,25,Business travel,Business,334,2,4,2,3,3,2,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +24757,48999,Male,disloyal Customer,37,Business travel,Eco,190,3,0,3,3,5,3,5,5,3,4,4,5,2,5,4,13.0,neutral or dissatisfied +24758,79021,Male,Loyal Customer,45,Business travel,Business,1612,1,1,4,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +24759,24520,Female,Loyal Customer,51,Personal Travel,Eco Plus,547,3,3,3,3,2,2,3,4,4,3,4,3,4,3,0,10.0,neutral or dissatisfied +24760,5021,Male,Loyal Customer,39,Business travel,Business,2890,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +24761,30871,Male,Loyal Customer,24,Business travel,Eco,1546,4,3,3,3,4,4,5,4,2,4,2,3,1,4,0,0.0,satisfied +24762,4089,Male,Loyal Customer,22,Personal Travel,Business,431,1,3,1,4,3,1,3,3,3,2,4,4,3,3,71,57.0,neutral or dissatisfied +24763,106907,Male,disloyal Customer,18,Business travel,Eco,577,4,3,4,4,5,4,5,5,4,5,4,3,3,5,13,12.0,neutral or dissatisfied +24764,104177,Male,Loyal Customer,79,Business travel,Business,1889,2,2,2,2,1,1,2,5,5,5,5,4,5,1,0,0.0,satisfied +24765,39448,Female,Loyal Customer,35,Personal Travel,Eco,129,1,1,1,3,4,1,4,4,2,3,3,1,3,4,0,6.0,neutral or dissatisfied +24766,2648,Male,Loyal Customer,48,Business travel,Business,2844,1,1,1,1,4,5,5,4,4,4,4,3,4,3,18,111.0,satisfied +24767,118478,Male,disloyal Customer,37,Business travel,Business,647,3,3,3,3,3,3,3,3,4,3,4,4,5,3,0,1.0,neutral or dissatisfied +24768,70852,Female,Loyal Customer,42,Business travel,Business,3682,3,3,3,3,4,5,4,5,5,5,5,3,5,5,18,11.0,satisfied +24769,77569,Male,disloyal Customer,22,Business travel,Eco,1282,5,5,5,4,4,5,4,4,4,3,4,3,5,4,0,0.0,satisfied +24770,1915,Female,Loyal Customer,43,Business travel,Business,351,2,2,2,2,3,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +24771,42465,Female,disloyal Customer,46,Business travel,Business,395,2,2,2,3,3,2,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +24772,25747,Female,Loyal Customer,77,Business travel,Eco,356,4,4,4,4,4,3,5,3,3,4,3,4,3,1,8,9.0,satisfied +24773,11380,Female,disloyal Customer,27,Business travel,Business,429,4,4,4,3,3,4,3,3,5,3,5,5,4,3,4,9.0,satisfied +24774,103453,Male,Loyal Customer,45,Business travel,Business,448,4,4,4,4,5,4,4,3,3,3,3,3,3,4,5,1.0,satisfied +24775,60670,Female,Loyal Customer,27,Personal Travel,Eco,1620,3,4,3,2,1,3,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +24776,64007,Female,Loyal Customer,66,Personal Travel,Eco,612,2,4,2,3,2,5,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +24777,20978,Male,Loyal Customer,12,Personal Travel,Eco,721,1,4,1,4,1,1,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +24778,90711,Male,disloyal Customer,22,Business travel,Eco,250,0,4,0,4,2,0,2,2,5,3,4,3,4,2,0,0.0,satisfied +24779,43737,Female,Loyal Customer,31,Personal Travel,Business,626,3,5,3,4,2,3,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +24780,47761,Male,disloyal Customer,22,Business travel,Eco,784,4,4,4,1,2,4,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +24781,107919,Male,Loyal Customer,47,Business travel,Business,2939,1,1,1,1,2,4,4,3,3,3,3,5,3,4,17,6.0,satisfied +24782,54443,Male,Loyal Customer,36,Personal Travel,Eco Plus,305,3,5,4,3,3,4,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +24783,71808,Male,Loyal Customer,52,Business travel,Business,1846,3,3,3,3,5,4,4,4,4,4,4,4,4,3,35,37.0,satisfied +24784,88956,Male,disloyal Customer,27,Business travel,Business,1199,1,1,1,3,3,1,3,3,4,5,5,3,4,3,0,2.0,neutral or dissatisfied +24785,18816,Female,Loyal Customer,32,Business travel,Business,551,4,4,4,4,4,4,4,4,5,5,3,4,1,4,0,0.0,satisfied +24786,93315,Male,Loyal Customer,44,Business travel,Business,2053,4,4,4,4,3,5,5,4,4,4,4,3,4,3,45,37.0,satisfied +24787,16753,Male,Loyal Customer,40,Business travel,Business,3904,5,5,5,5,1,2,1,4,4,4,4,4,4,4,0,0.0,satisfied +24788,27338,Male,Loyal Customer,32,Business travel,Eco,954,5,2,2,2,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +24789,74744,Female,Loyal Customer,64,Personal Travel,Eco,1205,2,1,2,4,2,3,4,4,4,2,4,2,4,4,6,0.0,neutral or dissatisfied +24790,94496,Female,Loyal Customer,23,Business travel,Business,2579,4,4,4,4,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +24791,101704,Male,Loyal Customer,35,Business travel,Business,1624,2,2,2,2,5,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +24792,107096,Male,disloyal Customer,29,Business travel,Business,745,0,0,0,1,2,0,2,2,5,2,5,4,5,2,1,5.0,satisfied +24793,49196,Male,Loyal Customer,42,Business travel,Eco,134,4,5,5,5,4,4,4,4,3,3,4,2,5,4,0,0.0,satisfied +24794,49535,Male,Loyal Customer,37,Business travel,Business,2599,4,4,4,4,4,4,2,4,4,4,4,3,4,4,0,0.0,satisfied +24795,112624,Female,Loyal Customer,38,Personal Travel,Eco,602,4,5,4,1,5,4,1,5,5,2,5,3,5,5,0,0.0,satisfied +24796,76300,Female,disloyal Customer,24,Business travel,Business,1473,4,0,4,3,4,5,4,5,3,4,5,4,3,4,133,114.0,satisfied +24797,40845,Male,disloyal Customer,25,Business travel,Eco,590,2,2,2,4,2,2,2,2,2,1,3,1,3,2,36,26.0,neutral or dissatisfied +24798,54880,Male,Loyal Customer,23,Personal Travel,Eco,862,3,4,3,3,2,3,2,2,3,4,4,3,4,2,26,28.0,neutral or dissatisfied +24799,95337,Female,Loyal Customer,59,Personal Travel,Eco,192,5,4,5,3,5,4,5,1,1,5,1,5,1,4,0,0.0,satisfied +24800,85915,Female,Loyal Customer,35,Business travel,Business,761,2,3,3,3,2,2,2,1,3,1,2,2,4,2,131,118.0,neutral or dissatisfied +24801,111726,Male,Loyal Customer,66,Business travel,Eco Plus,495,1,4,2,4,1,1,1,1,4,5,3,4,4,1,46,38.0,neutral or dissatisfied +24802,43979,Female,Loyal Customer,52,Business travel,Eco,411,4,4,4,4,1,1,1,4,4,4,4,5,4,5,7,0.0,satisfied +24803,41929,Female,Loyal Customer,28,Personal Travel,Eco,129,1,3,1,3,3,1,5,3,3,1,3,1,4,3,0,18.0,neutral or dissatisfied +24804,26812,Female,Loyal Customer,49,Personal Travel,Eco Plus,2139,3,4,3,3,5,5,5,3,3,3,3,3,3,3,56,34.0,neutral or dissatisfied +24805,41850,Female,Loyal Customer,45,Business travel,Business,483,2,2,2,2,4,4,2,4,4,4,4,1,4,5,92,84.0,satisfied +24806,62862,Female,Loyal Customer,53,Business travel,Business,2446,1,1,1,1,4,4,5,3,3,3,3,5,3,3,0,36.0,satisfied +24807,103544,Female,disloyal Customer,34,Business travel,Eco,738,4,4,4,3,5,4,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +24808,30125,Female,Loyal Customer,54,Personal Travel,Eco,31,2,1,2,3,4,4,4,5,5,2,5,3,5,2,18,22.0,neutral or dissatisfied +24809,120642,Female,disloyal Customer,34,Business travel,Business,280,3,3,3,3,2,3,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +24810,121983,Male,disloyal Customer,44,Business travel,Business,130,5,5,5,1,4,5,5,4,5,4,4,3,5,4,0,0.0,satisfied +24811,90895,Female,Loyal Customer,38,Business travel,Eco,545,2,3,3,3,2,2,2,2,4,1,3,1,3,2,52,48.0,neutral or dissatisfied +24812,17856,Female,disloyal Customer,17,Business travel,Eco,399,2,4,1,3,5,1,5,5,1,1,3,1,3,5,0,0.0,neutral or dissatisfied +24813,92392,Male,disloyal Customer,34,Business travel,Business,2139,3,3,3,1,5,3,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +24814,29119,Male,Loyal Customer,47,Personal Travel,Eco,954,2,1,2,3,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +24815,102488,Female,Loyal Customer,13,Personal Travel,Eco,226,3,5,3,1,4,3,4,4,4,3,5,5,5,4,11,9.0,neutral or dissatisfied +24816,79256,Male,Loyal Customer,38,Business travel,Business,3655,2,2,2,2,2,2,3,5,5,5,5,2,5,1,0,0.0,satisfied +24817,13150,Male,Loyal Customer,22,Personal Travel,Eco,427,1,4,1,1,4,1,1,4,3,1,3,2,4,4,16,5.0,neutral or dissatisfied +24818,30826,Male,Loyal Customer,51,Business travel,Business,1028,3,3,3,3,2,2,4,5,5,5,5,4,5,5,37,17.0,satisfied +24819,68157,Male,Loyal Customer,31,Business travel,Business,3360,3,3,3,3,4,4,4,4,3,2,4,3,5,4,0,7.0,satisfied +24820,21708,Female,Loyal Customer,48,Personal Travel,Eco,746,3,2,3,3,2,4,4,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +24821,41270,Male,Loyal Customer,19,Personal Travel,Eco,305,3,5,3,3,2,3,2,2,4,2,4,5,5,2,107,110.0,neutral or dissatisfied +24822,120303,Female,Loyal Customer,29,Business travel,Business,3973,2,2,3,2,4,4,4,4,5,5,4,4,4,4,2,0.0,satisfied +24823,60140,Male,disloyal Customer,21,Business travel,Business,1120,1,4,1,3,3,1,5,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +24824,125542,Female,disloyal Customer,25,Business travel,Business,226,2,4,3,3,3,3,3,3,3,3,5,3,4,3,0,8.0,neutral or dissatisfied +24825,28386,Male,Loyal Customer,43,Personal Travel,Eco,763,2,5,3,1,4,3,4,4,1,3,2,4,4,4,0,0.0,neutral or dissatisfied +24826,10962,Female,Loyal Customer,47,Business travel,Business,308,0,0,0,3,5,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +24827,108106,Female,Loyal Customer,37,Business travel,Business,3674,4,4,5,4,5,5,5,5,5,5,5,3,5,5,38,21.0,satisfied +24828,63925,Female,Loyal Customer,17,Personal Travel,Eco,1192,2,5,2,1,2,2,2,2,5,5,3,4,4,2,0,12.0,neutral or dissatisfied +24829,43031,Male,disloyal Customer,37,Business travel,Eco,192,3,0,3,4,3,3,3,3,2,4,2,3,5,3,0,0.0,neutral or dissatisfied +24830,22507,Male,Loyal Customer,36,Business travel,Eco Plus,143,4,5,5,5,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +24831,63216,Male,Loyal Customer,53,Business travel,Business,2180,4,4,4,4,3,5,5,5,5,5,5,3,5,3,0,11.0,satisfied +24832,111625,Male,Loyal Customer,25,Personal Travel,Eco,1014,1,1,1,3,5,1,5,5,3,2,3,4,4,5,0,0.0,neutral or dissatisfied +24833,96775,Female,Loyal Customer,50,Business travel,Business,2993,4,4,4,4,4,4,4,4,4,4,4,5,4,5,3,0.0,satisfied +24834,62842,Female,disloyal Customer,21,Business travel,Business,2504,3,4,3,4,3,3,3,3,4,4,4,3,2,3,21,26.0,neutral or dissatisfied +24835,102783,Female,Loyal Customer,27,Business travel,Eco,1099,3,4,4,4,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +24836,34528,Female,Loyal Customer,30,Personal Travel,Business,636,1,4,1,3,3,1,3,3,3,4,5,4,4,3,7,6.0,neutral or dissatisfied +24837,119174,Male,disloyal Customer,39,Business travel,Business,331,2,2,2,3,4,2,3,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +24838,52614,Female,disloyal Customer,59,Business travel,Eco,160,1,4,1,4,1,1,1,1,3,1,4,2,3,1,0,0.0,neutral or dissatisfied +24839,113442,Female,Loyal Customer,66,Business travel,Business,223,2,2,4,2,4,5,5,4,4,4,5,4,4,4,0,0.0,satisfied +24840,35071,Male,Loyal Customer,50,Personal Travel,Business,1069,2,2,2,3,2,1,1,2,3,3,4,1,2,1,79,135.0,neutral or dissatisfied +24841,100473,Female,disloyal Customer,19,Business travel,Eco,580,1,1,1,3,3,1,3,3,4,2,3,2,3,3,0,4.0,neutral or dissatisfied +24842,63841,Male,disloyal Customer,14,Business travel,Business,1172,5,0,5,2,3,5,3,3,3,3,4,3,4,3,0,0.0,satisfied +24843,16468,Female,Loyal Customer,35,Personal Travel,Eco,416,2,3,2,4,1,2,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +24844,63683,Male,Loyal Customer,7,Personal Travel,Eco,1047,1,5,1,1,1,1,1,1,5,2,5,4,5,1,0,13.0,neutral or dissatisfied +24845,11970,Female,disloyal Customer,44,Business travel,Business,667,2,2,2,3,5,2,5,5,3,2,5,4,5,5,83,74.0,neutral or dissatisfied +24846,52863,Female,disloyal Customer,27,Business travel,Eco,836,4,4,4,3,4,4,3,5,2,2,3,3,3,3,170,161.0,satisfied +24847,81638,Male,Loyal Customer,48,Business travel,Business,3791,1,1,2,1,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +24848,85962,Female,Loyal Customer,48,Business travel,Business,447,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +24849,108022,Male,Loyal Customer,43,Personal Travel,Eco,589,2,5,2,1,3,2,3,3,3,4,5,5,5,3,10,16.0,neutral or dissatisfied +24850,3025,Male,Loyal Customer,26,Personal Travel,Eco,922,1,4,1,2,4,1,4,4,4,1,5,5,3,4,63,67.0,neutral or dissatisfied +24851,14386,Male,Loyal Customer,30,Business travel,Business,2462,2,2,2,2,4,4,4,4,3,3,5,2,3,4,0,0.0,satisfied +24852,56908,Male,disloyal Customer,34,Business travel,Business,2565,4,4,4,1,4,3,3,4,3,3,4,3,3,3,0,45.0,neutral or dissatisfied +24853,58161,Male,Loyal Customer,50,Business travel,Business,925,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +24854,9243,Female,disloyal Customer,30,Business travel,Eco,100,1,2,2,3,1,2,1,1,1,2,4,1,3,1,13,38.0,neutral or dissatisfied +24855,71512,Male,Loyal Customer,50,Business travel,Business,3587,2,2,2,2,2,5,4,5,5,5,5,4,5,4,7,1.0,satisfied +24856,24885,Male,Loyal Customer,28,Business travel,Business,2226,1,1,1,1,5,5,5,5,1,5,1,5,1,5,1,0.0,satisfied +24857,105237,Female,Loyal Customer,69,Personal Travel,Eco,377,5,5,5,2,4,5,4,1,1,5,1,4,1,5,0,0.0,satisfied +24858,92621,Male,Loyal Customer,59,Business travel,Business,3601,3,3,3,3,3,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +24859,89381,Female,Loyal Customer,53,Business travel,Business,151,2,2,2,2,4,5,5,5,5,5,4,4,5,4,0,6.0,satisfied +24860,109330,Male,Loyal Customer,51,Personal Travel,Eco,1136,3,5,3,1,2,3,2,2,3,3,4,4,5,2,2,0.0,neutral or dissatisfied +24861,94740,Male,Loyal Customer,57,Business travel,Business,2619,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +24862,60073,Female,Loyal Customer,57,Business travel,Business,3501,4,4,2,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24863,102386,Female,Loyal Customer,32,Business travel,Eco,236,1,3,3,3,1,1,1,1,3,3,3,3,4,1,10,14.0,neutral or dissatisfied +24864,50240,Female,disloyal Customer,21,Business travel,Business,373,3,2,3,4,2,3,2,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +24865,123081,Female,disloyal Customer,36,Business travel,Business,631,1,1,1,4,1,1,1,1,4,3,4,5,4,1,0,4.0,neutral or dissatisfied +24866,99397,Male,Loyal Customer,58,Business travel,Business,3334,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +24867,43826,Male,Loyal Customer,40,Business travel,Eco,199,4,3,3,3,4,5,4,4,5,5,4,3,4,4,0,0.0,satisfied +24868,68962,Female,Loyal Customer,44,Business travel,Business,2572,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +24869,86491,Female,Loyal Customer,23,Personal Travel,Eco,762,3,2,3,4,5,3,2,5,4,5,3,4,4,5,8,0.0,neutral or dissatisfied +24870,25466,Male,disloyal Customer,36,Business travel,Business,547,3,3,3,5,2,3,5,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +24871,107257,Male,Loyal Customer,39,Business travel,Business,1640,0,0,0,3,5,4,5,1,1,1,1,3,1,4,0,0.0,satisfied +24872,23866,Male,Loyal Customer,39,Personal Travel,Eco,552,1,5,1,3,5,1,3,5,2,2,4,3,4,5,0,0.0,neutral or dissatisfied +24873,70530,Female,Loyal Customer,46,Business travel,Business,3003,1,1,1,1,1,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +24874,84173,Female,Loyal Customer,40,Business travel,Business,2885,2,3,2,2,4,4,5,5,5,5,5,3,5,3,4,1.0,satisfied +24875,66553,Female,Loyal Customer,60,Business travel,Eco,328,5,3,4,4,1,1,3,5,5,5,5,3,5,5,0,0.0,satisfied +24876,53651,Male,Loyal Customer,44,Business travel,Eco Plus,1874,5,5,5,5,4,5,4,4,2,1,4,2,2,4,0,20.0,satisfied +24877,121052,Female,Loyal Customer,52,Personal Travel,Eco,861,1,5,1,4,4,4,4,5,5,1,5,5,5,4,5,0.0,neutral or dissatisfied +24878,12349,Male,disloyal Customer,22,Business travel,Eco,190,3,5,3,3,1,3,1,1,5,1,3,1,1,1,0,0.0,neutral or dissatisfied +24879,20652,Male,disloyal Customer,22,Business travel,Eco,522,2,5,3,5,2,3,2,2,5,5,2,2,2,2,0,0.0,neutral or dissatisfied +24880,47012,Male,Loyal Customer,26,Business travel,Business,3267,3,1,1,1,3,3,3,3,3,2,2,1,3,3,30,32.0,neutral or dissatisfied +24881,66934,Female,Loyal Customer,17,Business travel,Business,3808,3,3,2,3,5,4,5,5,4,5,4,3,5,5,0,11.0,satisfied +24882,97594,Female,Loyal Customer,59,Business travel,Business,1675,3,3,3,3,5,4,5,3,3,2,3,5,3,3,2,0.0,satisfied +24883,115852,Male,disloyal Customer,26,Business travel,Eco,447,4,0,4,1,5,4,5,5,1,3,3,1,3,5,0,11.0,neutral or dissatisfied +24884,59904,Female,Loyal Customer,49,Business travel,Business,1068,5,5,5,5,3,4,5,5,5,5,5,3,5,5,42,61.0,satisfied +24885,26633,Male,Loyal Customer,57,Business travel,Business,2747,3,2,2,2,3,3,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +24886,124867,Female,Loyal Customer,53,Personal Travel,Eco Plus,280,4,4,4,4,3,4,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +24887,23061,Male,Loyal Customer,63,Business travel,Business,820,3,1,1,1,1,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +24888,54354,Male,Loyal Customer,54,Business travel,Eco,1235,3,3,4,3,3,3,3,3,4,4,1,1,2,3,0,0.0,neutral or dissatisfied +24889,87612,Male,Loyal Customer,14,Personal Travel,Business,591,2,3,3,2,3,3,3,3,2,3,1,4,1,3,0,0.0,neutral or dissatisfied +24890,50778,Male,Loyal Customer,65,Personal Travel,Eco,109,2,3,2,5,3,2,2,3,3,4,1,4,2,3,0,0.0,neutral or dissatisfied +24891,3314,Male,Loyal Customer,43,Business travel,Business,213,3,5,5,5,1,4,4,4,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +24892,128721,Male,Loyal Customer,39,Business travel,Business,1064,3,2,2,2,2,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +24893,56180,Male,Loyal Customer,65,Personal Travel,Eco,1400,3,4,3,1,3,3,3,3,5,4,3,5,4,3,8,24.0,neutral or dissatisfied +24894,114335,Male,Loyal Customer,20,Personal Travel,Eco,909,4,5,5,4,1,5,1,1,5,4,5,4,4,1,41,32.0,neutral or dissatisfied +24895,86803,Female,Loyal Customer,47,Business travel,Business,2854,2,2,2,2,5,5,4,5,5,5,5,4,5,4,10,1.0,satisfied +24896,68102,Male,disloyal Customer,36,Business travel,Eco,413,3,4,2,3,5,2,4,5,4,3,3,4,3,5,48,42.0,neutral or dissatisfied +24897,77838,Male,Loyal Customer,41,Business travel,Business,1601,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +24898,58302,Female,Loyal Customer,54,Business travel,Business,1739,3,3,2,3,3,5,4,4,4,5,4,4,4,4,56,77.0,satisfied +24899,38390,Male,Loyal Customer,41,Business travel,Business,1626,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +24900,103122,Female,Loyal Customer,43,Personal Travel,Eco,687,3,5,3,3,4,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +24901,84918,Male,Loyal Customer,51,Personal Travel,Eco,516,2,4,2,4,5,2,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +24902,108665,Female,Loyal Customer,23,Personal Travel,Business,484,3,0,3,3,2,3,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +24903,33967,Male,Loyal Customer,40,Business travel,Eco,1598,2,1,1,1,2,2,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +24904,34298,Female,Loyal Customer,42,Personal Travel,Eco,280,2,5,2,2,5,5,5,3,3,2,1,2,3,2,0,0.0,neutral or dissatisfied +24905,34057,Female,Loyal Customer,38,Business travel,Eco,1674,3,1,1,1,3,3,3,3,1,3,2,2,2,3,3,0.0,neutral or dissatisfied +24906,74766,Male,Loyal Customer,26,Personal Travel,Eco,1235,3,5,3,4,3,3,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +24907,8428,Female,disloyal Customer,37,Business travel,Eco,462,2,2,2,4,5,2,5,5,1,4,4,3,4,5,3,8.0,neutral or dissatisfied +24908,97302,Female,Loyal Customer,54,Business travel,Business,3879,4,4,4,4,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +24909,41125,Male,disloyal Customer,18,Business travel,Eco,429,2,3,2,2,4,2,3,4,2,1,5,4,1,4,0,0.0,neutral or dissatisfied +24910,37586,Female,Loyal Customer,48,Business travel,Eco,1069,3,5,5,5,3,3,4,3,3,3,3,3,3,2,56,47.0,neutral or dissatisfied +24911,45027,Male,Loyal Customer,44,Business travel,Eco,867,4,4,4,4,4,4,4,4,4,2,3,4,1,4,2,21.0,satisfied +24912,49676,Male,Loyal Customer,37,Business travel,Eco,134,1,3,3,3,1,1,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +24913,23607,Female,Loyal Customer,25,Personal Travel,Eco,589,3,4,3,3,2,3,1,2,4,3,5,5,5,2,88,88.0,neutral or dissatisfied +24914,91688,Female,Loyal Customer,68,Personal Travel,Business,626,4,5,4,4,5,5,4,1,1,4,1,5,1,4,22,23.0,neutral or dissatisfied +24915,76847,Female,Loyal Customer,40,Business travel,Business,3393,1,1,1,1,5,5,4,2,2,2,2,5,2,4,15,5.0,satisfied +24916,85211,Male,Loyal Customer,53,Business travel,Business,813,3,3,3,3,2,5,5,4,4,4,4,3,4,3,18,2.0,satisfied +24917,8247,Female,Loyal Customer,17,Personal Travel,Eco,402,2,3,2,4,5,2,5,5,4,2,3,2,3,5,16,21.0,neutral or dissatisfied +24918,18552,Female,Loyal Customer,49,Business travel,Business,2749,2,5,5,5,2,2,2,4,4,3,2,4,4,1,0,0.0,neutral or dissatisfied +24919,109687,Male,Loyal Customer,44,Personal Travel,Eco,829,2,3,2,3,5,2,5,5,3,3,2,4,2,5,16,1.0,neutral or dissatisfied +24920,1427,Female,disloyal Customer,30,Business travel,Business,312,4,4,4,3,2,4,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +24921,113797,Female,Loyal Customer,50,Business travel,Business,397,4,4,4,4,5,4,5,4,4,4,4,5,4,4,29,29.0,satisfied +24922,88804,Female,Loyal Customer,37,Business travel,Eco Plus,406,3,3,3,3,3,3,3,3,4,3,3,1,4,3,0,5.0,neutral or dissatisfied +24923,116280,Female,Loyal Customer,23,Personal Travel,Eco,446,1,5,1,3,2,1,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +24924,32649,Female,disloyal Customer,38,Business travel,Eco,102,3,0,3,1,3,3,3,3,4,1,2,3,3,3,0,0.0,neutral or dissatisfied +24925,129523,Male,Loyal Customer,41,Personal Travel,Business,2342,2,2,2,3,3,4,4,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +24926,42140,Female,disloyal Customer,22,Business travel,Eco,315,4,5,4,4,3,4,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +24927,121163,Male,Loyal Customer,57,Business travel,Business,870,3,5,5,5,2,3,4,3,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +24928,66781,Male,Loyal Customer,40,Business travel,Business,3784,2,2,2,2,4,4,4,5,3,4,5,4,4,4,4,0.0,satisfied +24929,100224,Male,disloyal Customer,25,Business travel,Eco,1053,3,4,4,3,3,4,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +24930,42911,Male,Loyal Customer,55,Personal Travel,Eco,422,3,0,3,1,2,3,2,2,4,5,5,4,5,2,0,9.0,neutral or dissatisfied +24931,24982,Female,disloyal Customer,24,Business travel,Eco,484,5,4,5,2,1,5,1,1,1,4,3,1,1,1,0,0.0,satisfied +24932,97822,Male,disloyal Customer,44,Business travel,Business,395,2,2,2,4,4,2,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +24933,18048,Female,Loyal Customer,26,Business travel,Eco,488,3,3,3,3,3,3,1,3,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +24934,79083,Male,Loyal Customer,70,Personal Travel,Eco,306,4,4,4,5,5,4,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +24935,129241,Female,Loyal Customer,41,Business travel,Business,3928,2,2,2,2,4,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +24936,20327,Male,Loyal Customer,18,Personal Travel,Business,323,2,2,2,3,1,2,1,1,3,3,3,3,4,1,101,112.0,neutral or dissatisfied +24937,68308,Female,Loyal Customer,39,Personal Travel,Eco,1797,3,5,3,1,3,3,3,3,4,2,4,5,3,3,10,15.0,neutral or dissatisfied +24938,3633,Female,Loyal Customer,37,Business travel,Eco,431,3,4,4,4,3,2,3,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +24939,42358,Male,Loyal Customer,21,Personal Travel,Eco,838,2,4,2,1,5,2,5,5,5,4,4,3,4,5,9,0.0,neutral or dissatisfied +24940,63175,Male,disloyal Customer,37,Business travel,Business,372,4,4,4,1,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +24941,121833,Male,Loyal Customer,40,Business travel,Business,3896,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24942,119822,Male,disloyal Customer,38,Business travel,Business,936,3,3,3,3,3,3,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +24943,100220,Male,disloyal Customer,16,Business travel,Eco,1011,5,5,5,1,2,5,2,2,4,5,4,4,5,2,0,0.0,satisfied +24944,124241,Male,Loyal Customer,40,Business travel,Business,1916,4,4,4,4,3,4,5,5,5,5,5,4,5,3,46,44.0,satisfied +24945,116461,Female,Loyal Customer,39,Personal Travel,Eco,447,1,5,5,3,2,5,2,2,5,2,5,3,5,2,26,16.0,neutral or dissatisfied +24946,12903,Female,disloyal Customer,38,Business travel,Eco,456,2,1,1,2,3,1,4,3,2,4,3,3,2,3,103,120.0,neutral or dissatisfied +24947,56501,Male,disloyal Customer,62,Business travel,Business,1065,2,2,2,4,3,2,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +24948,114899,Female,Loyal Customer,40,Business travel,Business,390,1,1,5,1,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +24949,14231,Male,Loyal Customer,23,Business travel,Eco Plus,692,5,4,2,2,5,5,3,5,5,5,4,3,1,5,0,0.0,satisfied +24950,12030,Female,Loyal Customer,37,Business travel,Business,2788,3,3,3,3,2,1,3,5,5,5,5,4,5,3,37,50.0,satisfied +24951,118775,Male,Loyal Customer,27,Personal Travel,Eco,621,3,5,3,5,1,3,1,1,4,5,4,3,5,1,10,6.0,neutral or dissatisfied +24952,70887,Male,Loyal Customer,38,Personal Travel,Business,1721,5,4,5,2,5,5,5,2,2,5,2,3,2,3,6,0.0,satisfied +24953,57633,Male,Loyal Customer,48,Business travel,Business,3465,2,2,2,2,3,5,5,5,5,5,4,4,5,3,10,0.0,satisfied +24954,111912,Male,Loyal Customer,49,Personal Travel,Eco Plus,628,1,4,1,3,5,1,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +24955,123961,Female,Loyal Customer,37,Personal Travel,Business,184,3,5,3,1,1,1,2,3,3,3,3,5,3,2,13,14.0,neutral or dissatisfied +24956,48194,Male,disloyal Customer,23,Business travel,Eco,259,3,4,3,4,3,3,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +24957,112682,Male,Loyal Customer,30,Business travel,Business,1689,4,4,4,4,5,4,5,5,4,5,5,5,5,5,29,15.0,satisfied +24958,122041,Female,disloyal Customer,20,Business travel,Eco,130,4,5,4,1,5,4,5,5,5,2,5,4,4,5,0,0.0,satisfied +24959,122905,Female,disloyal Customer,26,Business travel,Business,631,3,0,4,3,1,4,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +24960,28623,Male,Loyal Customer,45,Business travel,Business,2614,4,4,4,4,3,3,2,5,5,5,5,1,5,5,12,0.0,satisfied +24961,81461,Female,Loyal Customer,53,Business travel,Business,2865,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +24962,19210,Female,Loyal Customer,43,Business travel,Eco,459,3,4,5,4,3,4,4,3,3,3,3,4,3,2,0,4.0,neutral or dissatisfied +24963,5433,Female,Loyal Customer,47,Business travel,Business,2509,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,25.0,satisfied +24964,60729,Female,Loyal Customer,48,Personal Travel,Eco,1605,2,2,1,4,5,2,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +24965,56825,Male,Loyal Customer,14,Personal Travel,Eco,1605,5,5,5,3,4,5,1,4,4,3,3,5,4,4,6,13.0,satisfied +24966,42776,Male,Loyal Customer,33,Personal Travel,Eco Plus,493,1,5,1,3,2,1,2,2,3,2,5,5,5,2,49,38.0,neutral or dissatisfied +24967,60472,Female,Loyal Customer,53,Business travel,Business,794,4,4,4,4,4,4,5,5,5,5,5,3,5,4,20,0.0,satisfied +24968,14360,Female,Loyal Customer,8,Personal Travel,Eco Plus,175,2,5,2,4,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +24969,116689,Female,disloyal Customer,36,Business travel,Eco Plus,337,1,2,2,3,4,2,4,4,2,5,4,2,4,4,15,24.0,neutral or dissatisfied +24970,82137,Male,Loyal Customer,59,Business travel,Business,1795,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +24971,59326,Male,disloyal Customer,22,Business travel,Eco,912,4,4,4,5,4,4,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +24972,48788,Female,disloyal Customer,24,Business travel,Eco,421,3,1,3,4,3,3,3,3,3,1,4,3,3,3,11,14.0,neutral or dissatisfied +24973,80417,Female,disloyal Customer,25,Business travel,Business,2248,2,5,2,1,3,2,3,3,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +24974,85253,Female,Loyal Customer,22,Personal Travel,Eco,731,2,5,2,4,1,2,1,1,5,1,5,2,2,1,0,0.0,neutral or dissatisfied +24975,120139,Male,Loyal Customer,64,Business travel,Eco,1475,4,1,1,1,4,4,4,4,4,4,4,4,4,4,0,2.0,neutral or dissatisfied +24976,36082,Male,Loyal Customer,22,Personal Travel,Eco,399,3,5,3,3,4,3,4,4,3,4,5,4,4,4,47,36.0,neutral or dissatisfied +24977,108013,Male,Loyal Customer,47,Business travel,Business,3431,3,3,2,3,5,5,4,5,5,5,5,4,5,4,27,23.0,satisfied +24978,75300,Male,Loyal Customer,7,Personal Travel,Eco Plus,1846,4,1,4,3,2,4,4,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +24979,63266,Female,Loyal Customer,63,Business travel,Business,337,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,16.0,satisfied +24980,47953,Female,Loyal Customer,35,Personal Travel,Eco,550,2,2,2,4,2,2,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +24981,99245,Male,Loyal Customer,67,Personal Travel,Eco,495,3,3,4,4,4,4,4,4,4,5,2,4,4,4,0,0.0,neutral or dissatisfied +24982,126215,Male,Loyal Customer,49,Business travel,Business,2951,4,5,5,5,1,2,2,4,4,4,4,3,4,2,2,0.0,neutral or dissatisfied +24983,116619,Female,Loyal Customer,40,Business travel,Business,2600,5,5,5,5,4,4,4,5,5,5,5,5,5,5,26,9.0,satisfied +24984,59590,Female,disloyal Customer,23,Business travel,Business,854,4,0,4,4,3,4,3,3,5,3,4,5,5,3,8,0.0,satisfied +24985,11793,Female,Loyal Customer,43,Personal Travel,Eco,429,3,3,3,2,5,1,4,1,1,3,1,5,1,5,39,29.0,neutral or dissatisfied +24986,110422,Male,disloyal Customer,24,Business travel,Eco,925,2,2,2,4,4,2,4,4,4,2,4,1,3,4,9,0.0,neutral or dissatisfied +24987,119543,Male,Loyal Customer,15,Personal Travel,Eco,814,3,4,2,4,3,2,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +24988,63652,Male,disloyal Customer,25,Business travel,Eco,760,2,2,2,3,3,2,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +24989,129625,Female,Loyal Customer,55,Business travel,Business,2265,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +24990,78093,Male,Loyal Customer,60,Business travel,Business,684,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,25.0,satisfied +24991,5123,Female,Loyal Customer,35,Business travel,Business,122,4,4,4,4,2,5,5,4,4,4,5,3,4,4,84,83.0,satisfied +24992,15920,Male,disloyal Customer,24,Business travel,Eco,566,4,4,4,5,2,4,2,2,2,5,3,5,2,2,5,10.0,satisfied +24993,1824,Male,Loyal Customer,32,Business travel,Business,3324,2,4,3,4,2,2,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +24994,15922,Male,Loyal Customer,47,Business travel,Business,738,4,3,3,3,2,4,3,4,4,4,4,2,4,2,0,13.0,neutral or dissatisfied +24995,72425,Female,Loyal Customer,50,Business travel,Business,3809,1,1,1,1,5,4,4,5,5,5,5,5,5,5,39,37.0,satisfied +24996,106089,Female,disloyal Customer,23,Business travel,Eco,302,5,5,5,1,1,5,1,1,3,3,4,3,4,1,28,22.0,satisfied +24997,104621,Female,Loyal Customer,39,Business travel,Business,3811,1,1,1,1,4,4,4,4,3,4,5,4,4,4,310,300.0,satisfied +24998,8469,Male,Loyal Customer,47,Business travel,Business,1187,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +24999,16990,Male,Loyal Customer,67,Personal Travel,Eco Plus,610,4,5,4,2,1,4,1,1,5,3,4,3,5,1,103,106.0,neutral or dissatisfied +25000,51770,Female,Loyal Customer,56,Personal Travel,Eco,370,3,4,3,4,4,4,3,3,3,3,3,2,3,1,0,9.0,neutral or dissatisfied +25001,18093,Male,Loyal Customer,22,Business travel,Eco Plus,605,0,4,0,3,2,0,3,2,5,3,3,2,4,2,35,25.0,satisfied +25002,3729,Female,Loyal Customer,49,Personal Travel,Eco,544,3,3,3,4,3,2,2,4,5,4,4,2,1,2,128,161.0,neutral or dissatisfied +25003,85338,Female,Loyal Customer,46,Business travel,Business,731,5,5,5,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +25004,46793,Male,Loyal Customer,41,Business travel,Business,845,2,3,3,3,2,2,3,2,2,2,2,1,2,1,31,13.0,neutral or dissatisfied +25005,111692,Female,disloyal Customer,35,Business travel,Business,495,3,3,3,2,5,3,5,5,5,3,5,4,5,5,16,12.0,neutral or dissatisfied +25006,108573,Female,disloyal Customer,25,Business travel,Business,696,3,5,3,3,1,3,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +25007,122455,Male,Loyal Customer,42,Business travel,Business,575,2,2,2,2,5,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +25008,128730,Female,Loyal Customer,43,Personal Travel,Eco,1235,2,2,2,4,3,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +25009,121321,Male,Loyal Customer,13,Personal Travel,Eco,1009,3,3,3,2,5,3,5,5,2,3,3,3,2,5,9,12.0,neutral or dissatisfied +25010,57179,Male,Loyal Customer,23,Personal Travel,Eco,2227,2,3,2,4,1,2,2,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +25011,23563,Female,disloyal Customer,20,Business travel,Eco Plus,637,3,0,3,3,2,3,2,2,4,1,1,1,4,2,3,5.0,neutral or dissatisfied +25012,74483,Male,disloyal Customer,12,Business travel,Eco,1188,3,3,3,3,3,3,3,3,1,5,3,1,3,3,22,29.0,neutral or dissatisfied +25013,96486,Male,Loyal Customer,59,Business travel,Business,302,4,4,4,4,5,5,4,4,4,5,4,3,4,4,15,8.0,satisfied +25014,30648,Male,Loyal Customer,35,Business travel,Business,3786,1,1,3,1,5,4,4,3,3,3,3,1,3,2,0,12.0,satisfied +25015,41846,Male,Loyal Customer,35,Business travel,Business,483,1,1,1,1,4,2,2,3,3,3,3,4,3,1,37,45.0,satisfied +25016,91671,Male,disloyal Customer,48,Business travel,Business,954,3,3,3,2,1,3,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +25017,96428,Male,Loyal Customer,59,Business travel,Business,3027,4,4,4,4,2,5,4,5,5,5,5,4,5,5,7,0.0,satisfied +25018,37916,Female,Loyal Customer,29,Personal Travel,Eco,1023,2,3,2,3,4,2,4,4,3,5,4,3,1,4,0,73.0,neutral or dissatisfied +25019,55473,Female,Loyal Customer,38,Personal Travel,Eco,1825,1,5,1,1,2,1,2,2,3,3,5,3,4,2,1,0.0,neutral or dissatisfied +25020,49542,Male,Loyal Customer,36,Business travel,Business,3996,1,1,3,1,2,3,3,3,3,3,3,2,3,1,0,0.0,satisfied +25021,119533,Female,Loyal Customer,70,Personal Travel,Eco,814,3,0,4,3,5,4,4,2,2,4,1,3,2,4,0,0.0,neutral or dissatisfied +25022,65219,Male,Loyal Customer,54,Business travel,Business,3861,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,8.0,satisfied +25023,102132,Male,Loyal Customer,33,Business travel,Business,386,5,5,5,5,4,4,4,4,5,3,4,5,5,4,3,0.0,satisfied +25024,98057,Female,Loyal Customer,44,Personal Travel,Eco,1797,3,5,3,2,2,5,2,3,3,3,3,3,3,5,21,2.0,neutral or dissatisfied +25025,26314,Male,Loyal Customer,21,Personal Travel,Eco,1947,2,5,2,3,1,2,1,1,4,4,5,5,1,1,18,13.0,neutral or dissatisfied +25026,15506,Male,Loyal Customer,14,Personal Travel,Eco,164,3,4,3,4,2,3,4,2,3,1,4,2,3,2,0,0.0,neutral or dissatisfied +25027,24924,Female,Loyal Customer,28,Personal Travel,Eco,762,5,4,5,3,3,5,3,3,3,4,3,2,4,3,0,0.0,satisfied +25028,32192,Female,Loyal Customer,31,Business travel,Eco,101,5,3,3,3,5,5,5,5,2,2,1,4,2,5,6,12.0,satisfied +25029,39142,Male,Loyal Customer,14,Personal Travel,Eco,119,4,3,4,5,5,4,5,5,4,1,4,5,4,5,123,123.0,neutral or dissatisfied +25030,129674,Female,Loyal Customer,60,Business travel,Business,337,4,4,2,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +25031,48452,Female,Loyal Customer,23,Business travel,Business,1513,4,4,4,4,4,4,4,4,1,3,3,2,4,4,3,0.0,satisfied +25032,106298,Female,Loyal Customer,18,Business travel,Business,2901,4,4,4,4,4,4,4,4,5,4,5,5,5,4,15,4.0,satisfied +25033,122036,Female,disloyal Customer,27,Business travel,Business,130,2,2,2,4,4,2,2,4,5,5,4,4,5,4,0,1.0,neutral or dissatisfied +25034,124380,Male,Loyal Customer,68,Personal Travel,Eco,575,0,5,0,1,2,0,2,2,4,5,4,3,4,2,0,0.0,satisfied +25035,114431,Male,Loyal Customer,50,Business travel,Business,1589,4,4,2,4,5,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +25036,107424,Female,Loyal Customer,32,Personal Travel,Eco,725,3,3,3,1,4,3,4,4,1,2,1,3,2,4,6,0.0,neutral or dissatisfied +25037,51640,Male,Loyal Customer,48,Business travel,Business,3630,3,1,1,1,1,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +25038,80726,Male,Loyal Customer,49,Business travel,Business,3323,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +25039,124167,Male,Loyal Customer,61,Personal Travel,Eco,2133,2,5,3,3,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +25040,24504,Male,Loyal Customer,47,Personal Travel,Eco,547,2,4,2,1,3,2,4,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +25041,34479,Male,Loyal Customer,42,Personal Travel,Eco,266,3,4,0,4,2,0,2,2,4,4,3,5,5,2,0,0.0,neutral or dissatisfied +25042,86950,Female,Loyal Customer,28,Business travel,Business,2198,3,3,3,3,4,4,4,4,4,5,5,3,5,4,0,0.0,satisfied +25043,46155,Female,Loyal Customer,54,Business travel,Eco,204,1,0,0,4,5,4,3,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +25044,54070,Male,Loyal Customer,41,Business travel,Eco,1416,3,2,2,2,3,3,3,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +25045,48615,Male,Loyal Customer,24,Business travel,Eco Plus,737,5,5,5,5,5,5,4,5,1,2,2,2,5,5,0,0.0,satisfied +25046,7300,Male,Loyal Customer,51,Business travel,Business,3554,5,5,4,5,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +25047,71011,Male,Loyal Customer,29,Business travel,Business,2999,5,4,5,5,5,5,5,5,3,4,4,5,5,5,0,9.0,satisfied +25048,124088,Female,disloyal Customer,45,Business travel,Business,529,5,4,4,1,4,5,4,4,5,4,5,3,4,4,0,0.0,satisfied +25049,45612,Male,Loyal Customer,47,Business travel,Business,1996,3,3,3,3,4,2,1,5,5,5,5,2,5,5,0,0.0,satisfied +25050,12491,Female,Loyal Customer,28,Business travel,Eco Plus,253,3,5,4,5,3,3,3,3,1,5,4,2,4,3,14,7.0,neutral or dissatisfied +25051,28148,Male,Loyal Customer,43,Business travel,Eco,569,3,3,3,3,3,3,3,3,1,5,4,2,4,3,0,1.0,neutral or dissatisfied +25052,26647,Female,Loyal Customer,41,Business travel,Eco,270,4,5,5,5,4,4,4,4,1,5,2,2,4,4,0,0.0,satisfied +25053,88722,Female,Loyal Customer,19,Personal Travel,Eco,270,2,0,2,4,5,2,1,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +25054,14410,Female,Loyal Customer,31,Business travel,Business,585,5,5,5,5,4,4,4,4,1,5,1,4,4,4,0,8.0,satisfied +25055,43030,Female,Loyal Customer,41,Business travel,Business,1896,1,4,4,4,1,3,3,1,1,1,1,2,1,4,0,9.0,neutral or dissatisfied +25056,22530,Male,Loyal Customer,13,Personal Travel,Eco Plus,145,1,5,1,4,1,1,1,1,5,2,3,2,3,1,0,0.0,neutral or dissatisfied +25057,97862,Female,Loyal Customer,56,Business travel,Business,3309,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,2.0,satisfied +25058,100423,Male,Loyal Customer,42,Personal Travel,Eco Plus,1073,2,5,2,2,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +25059,58112,Male,Loyal Customer,40,Personal Travel,Eco,589,5,5,5,2,3,5,3,3,5,3,3,4,1,3,0,0.0,satisfied +25060,42775,Female,Loyal Customer,58,Business travel,Eco Plus,493,2,4,4,4,2,3,2,2,2,2,2,4,2,5,0,0.0,satisfied +25061,105548,Male,Loyal Customer,7,Personal Travel,Eco,611,1,1,1,4,1,2,2,2,5,3,4,2,1,2,132,131.0,neutral or dissatisfied +25062,31261,Male,Loyal Customer,44,Business travel,Business,2299,3,3,3,3,4,4,4,2,4,1,1,4,1,4,163,181.0,satisfied +25063,66962,Male,disloyal Customer,25,Business travel,Eco,1121,2,3,3,3,4,3,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +25064,75388,Female,Loyal Customer,31,Business travel,Business,2330,2,2,2,2,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +25065,9294,Male,Loyal Customer,41,Business travel,Business,1157,2,2,2,2,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +25066,43774,Female,Loyal Customer,67,Personal Travel,Eco,223,2,5,2,2,3,5,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +25067,6481,Male,Loyal Customer,48,Business travel,Business,2817,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +25068,104295,Female,Loyal Customer,11,Personal Travel,Eco,440,4,5,5,4,1,5,1,1,3,2,5,3,5,1,12,4.0,neutral or dissatisfied +25069,43514,Male,Loyal Customer,27,Personal Travel,Eco,455,2,4,2,2,2,2,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +25070,106964,Male,Loyal Customer,54,Business travel,Business,937,5,5,5,5,2,5,5,4,4,4,4,3,4,4,11,0.0,satisfied +25071,115944,Female,Loyal Customer,69,Personal Travel,Eco,337,1,4,1,4,4,5,5,4,4,1,4,3,4,5,0,8.0,neutral or dissatisfied +25072,57935,Female,disloyal Customer,30,Business travel,Business,837,4,4,4,1,2,4,2,2,3,4,4,4,4,2,0,0.0,satisfied +25073,49878,Female,disloyal Customer,25,Business travel,Eco,363,3,2,3,2,5,3,5,5,4,3,3,2,2,5,0,0.0,neutral or dissatisfied +25074,3836,Female,Loyal Customer,66,Personal Travel,Eco,650,1,4,1,3,2,3,4,4,4,1,4,4,4,2,0,3.0,neutral or dissatisfied +25075,48576,Female,Loyal Customer,48,Personal Travel,Eco,948,3,2,3,3,2,4,4,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +25076,62311,Female,Loyal Customer,49,Business travel,Eco,414,1,1,1,1,3,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +25077,58206,Male,disloyal Customer,24,Business travel,Eco,925,1,1,1,1,1,1,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +25078,122598,Male,Loyal Customer,62,Business travel,Business,2212,1,0,0,3,1,3,2,1,1,0,1,3,1,2,10,18.0,neutral or dissatisfied +25079,116929,Male,Loyal Customer,55,Business travel,Business,3477,3,3,3,3,4,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +25080,6292,Female,Loyal Customer,10,Personal Travel,Eco,693,4,4,4,3,4,4,4,4,4,2,4,4,5,4,66,57.0,neutral or dissatisfied +25081,4178,Female,Loyal Customer,22,Personal Travel,Eco,427,2,3,0,3,2,0,2,2,4,2,2,2,4,2,0,0.0,neutral or dissatisfied +25082,72961,Female,disloyal Customer,24,Business travel,Eco,1096,4,4,4,5,5,4,5,5,5,2,5,3,4,5,0,0.0,satisfied +25083,119676,Male,disloyal Customer,22,Business travel,Eco,1430,3,3,3,4,4,3,4,4,4,4,4,3,5,4,27,15.0,neutral or dissatisfied +25084,116270,Female,Loyal Customer,8,Personal Travel,Eco,373,1,3,1,2,4,1,4,4,1,1,2,5,2,4,0,0.0,neutral or dissatisfied +25085,14790,Female,Loyal Customer,28,Business travel,Business,1824,3,3,3,3,3,3,3,3,2,2,3,3,3,3,0,6.0,neutral or dissatisfied +25086,126901,Male,Loyal Customer,21,Personal Travel,Eco Plus,2296,3,4,3,5,3,3,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +25087,82890,Female,Loyal Customer,43,Personal Travel,Eco,640,3,5,4,4,5,4,5,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +25088,4098,Male,Loyal Customer,41,Business travel,Business,544,1,1,2,1,4,4,5,5,5,5,5,4,5,3,0,9.0,satisfied +25089,27315,Female,disloyal Customer,25,Business travel,Eco,1050,2,2,2,2,5,2,5,5,1,3,1,1,4,5,0,0.0,neutral or dissatisfied +25090,129639,Male,Loyal Customer,48,Business travel,Business,337,1,1,2,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +25091,63003,Female,Loyal Customer,52,Business travel,Eco,909,2,5,5,5,5,4,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +25092,119449,Female,disloyal Customer,23,Business travel,Eco,759,5,5,5,2,4,5,4,4,5,4,4,3,5,4,0,1.0,satisfied +25093,39768,Female,disloyal Customer,22,Business travel,Business,521,4,0,4,1,5,4,5,5,5,1,1,3,3,5,0,0.0,satisfied +25094,50352,Female,Loyal Customer,35,Business travel,Eco,363,2,2,2,2,2,2,2,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +25095,51824,Male,Loyal Customer,25,Business travel,Eco Plus,370,4,4,4,4,4,3,2,4,2,4,3,1,4,4,0,13.0,neutral or dissatisfied +25096,17548,Male,Loyal Customer,59,Business travel,Eco,908,3,1,1,1,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +25097,106112,Male,disloyal Customer,40,Business travel,Business,436,3,3,3,5,3,4,4,4,3,5,5,4,4,4,244,240.0,neutral or dissatisfied +25098,62897,Male,disloyal Customer,26,Business travel,Business,862,2,2,2,3,3,2,3,3,4,5,4,5,5,3,0,2.0,neutral or dissatisfied +25099,94715,Female,Loyal Customer,45,Business travel,Business,2666,3,3,3,3,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +25100,54172,Female,Loyal Customer,38,Business travel,Business,3668,5,5,5,5,1,4,2,4,4,4,4,1,4,4,7,0.0,satisfied +25101,39614,Male,Loyal Customer,53,Personal Travel,Eco,954,2,5,2,5,5,2,5,5,1,1,1,2,4,5,0,8.0,neutral or dissatisfied +25102,60253,Male,Loyal Customer,53,Personal Travel,Eco,1506,2,4,2,4,5,2,4,5,1,4,2,3,1,5,0,0.0,neutral or dissatisfied +25103,96608,Male,Loyal Customer,46,Business travel,Business,3073,2,2,1,2,4,5,5,5,5,5,5,4,5,4,3,0.0,satisfied +25104,39794,Female,Loyal Customer,66,Personal Travel,Business,221,4,0,4,3,5,4,5,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +25105,62561,Female,Loyal Customer,40,Business travel,Business,1846,1,1,1,1,5,3,4,5,5,5,5,4,5,3,1,3.0,satisfied +25106,57703,Male,Loyal Customer,47,Personal Travel,Eco,867,4,4,4,4,2,4,2,2,2,2,3,5,1,2,0,0.0,neutral or dissatisfied +25107,21512,Male,Loyal Customer,55,Personal Travel,Eco,306,1,4,1,4,2,1,3,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +25108,45105,Male,Loyal Customer,49,Business travel,Business,84,4,4,3,4,1,2,5,5,5,5,3,4,5,3,0,0.0,satisfied +25109,18416,Male,Loyal Customer,47,Business travel,Eco,750,4,1,4,1,4,4,4,4,4,3,1,1,1,4,0,0.0,satisfied +25110,87987,Male,disloyal Customer,34,Business travel,Business,270,1,0,0,3,5,0,5,5,3,5,4,5,5,5,56,57.0,neutral or dissatisfied +25111,29310,Male,Loyal Customer,66,Personal Travel,Eco,933,4,4,4,1,2,4,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +25112,105433,Male,Loyal Customer,63,Personal Travel,Eco,452,3,2,3,3,3,3,1,3,2,1,4,1,4,3,6,0.0,neutral or dissatisfied +25113,8534,Male,Loyal Customer,51,Personal Travel,Eco Plus,862,2,5,2,1,3,2,3,3,3,3,4,5,5,3,78,70.0,neutral or dissatisfied +25114,35177,Male,Loyal Customer,48,Business travel,Eco,1005,5,2,2,2,5,5,5,5,4,2,2,3,5,5,0,12.0,satisfied +25115,127745,Male,Loyal Customer,37,Business travel,Eco,255,5,2,2,2,5,5,5,5,1,3,4,4,2,5,0,0.0,satisfied +25116,11539,Male,Loyal Customer,43,Business travel,Business,2606,4,1,4,4,4,4,5,5,5,5,5,5,5,3,5,7.0,satisfied +25117,74940,Female,disloyal Customer,34,Business travel,Eco,1405,2,2,2,4,5,2,2,5,3,3,2,4,4,5,1,0.0,neutral or dissatisfied +25118,39774,Male,Loyal Customer,55,Business travel,Eco,521,5,5,5,5,5,5,5,5,4,4,1,2,3,5,0,2.0,satisfied +25119,97403,Female,Loyal Customer,44,Business travel,Business,2211,1,1,1,1,3,5,5,3,3,3,3,3,3,5,57,44.0,satisfied +25120,109120,Male,Loyal Customer,65,Personal Travel,Eco Plus,849,2,4,2,1,1,2,1,1,4,2,5,3,5,1,1,0.0,neutral or dissatisfied +25121,93698,Female,Loyal Customer,59,Personal Travel,Eco,1452,4,5,4,4,3,5,3,4,4,4,4,2,4,2,29,27.0,neutral or dissatisfied +25122,97640,Female,Loyal Customer,51,Business travel,Business,1587,4,4,4,4,5,4,5,4,4,4,4,4,4,4,1,17.0,satisfied +25123,88402,Male,Loyal Customer,55,Business travel,Business,545,3,3,1,3,3,4,4,5,5,5,5,5,5,3,3,0.0,satisfied +25124,118484,Female,Loyal Customer,29,Business travel,Business,3487,2,2,3,2,5,5,5,5,5,4,5,4,5,5,93,81.0,satisfied +25125,878,Female,disloyal Customer,37,Business travel,Business,312,4,4,4,1,2,4,2,2,5,2,5,5,4,2,0,0.0,satisfied +25126,110144,Male,disloyal Customer,47,Business travel,Business,1072,1,1,1,2,4,1,4,4,1,4,3,3,2,4,6,13.0,neutral or dissatisfied +25127,31839,Female,Loyal Customer,39,Business travel,Business,2677,4,5,5,5,4,4,4,1,4,4,4,4,3,4,0,18.0,neutral or dissatisfied +25128,113366,Male,Loyal Customer,52,Business travel,Business,3977,5,5,2,5,4,5,4,3,3,3,3,5,3,4,35,30.0,satisfied +25129,20791,Female,disloyal Customer,45,Business travel,Eco,457,3,0,3,5,4,3,4,4,2,5,4,1,5,4,1,0.0,neutral or dissatisfied +25130,92797,Male,Loyal Customer,33,Business travel,Business,1541,3,3,3,3,4,4,4,4,4,4,5,3,5,4,2,0.0,satisfied +25131,16791,Male,Loyal Customer,47,Personal Travel,Eco Plus,569,4,4,3,1,1,3,1,1,5,2,5,5,5,1,0,0.0,satisfied +25132,82820,Female,Loyal Customer,58,Business travel,Business,2052,4,1,5,1,2,3,3,4,4,4,4,2,4,3,20,51.0,neutral or dissatisfied +25133,61340,Female,disloyal Customer,36,Business travel,Business,602,3,3,3,2,3,3,5,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +25134,67892,Male,Loyal Customer,16,Personal Travel,Eco,1431,0,5,0,1,1,0,1,1,5,2,4,4,4,1,0,0.0,satisfied +25135,111919,Male,disloyal Customer,23,Business travel,Eco,472,1,4,1,3,4,1,5,4,1,1,4,4,4,4,17,2.0,neutral or dissatisfied +25136,93135,Female,Loyal Customer,53,Business travel,Business,1183,2,2,2,2,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +25137,112269,Female,Loyal Customer,52,Business travel,Business,1703,3,3,3,3,4,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +25138,112175,Female,Loyal Customer,18,Personal Travel,Eco,895,2,3,2,4,5,2,5,5,3,2,4,2,3,5,0,0.0,neutral or dissatisfied +25139,108972,Male,Loyal Customer,56,Personal Travel,Eco Plus,655,2,3,2,2,2,2,2,2,4,2,4,4,4,2,46,37.0,neutral or dissatisfied +25140,9258,Male,Loyal Customer,49,Business travel,Business,157,1,1,1,1,5,5,5,4,4,4,4,5,4,4,29,13.0,satisfied +25141,74682,Male,Loyal Customer,40,Personal Travel,Eco,1235,2,4,2,4,2,2,2,2,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +25142,7119,Female,disloyal Customer,24,Business travel,Eco,177,3,2,3,4,3,3,3,3,1,1,4,4,4,3,0,17.0,neutral or dissatisfied +25143,43718,Male,Loyal Customer,49,Personal Travel,Eco,489,2,3,2,3,1,2,4,1,4,3,4,4,3,1,0,3.0,neutral or dissatisfied +25144,128921,Male,Loyal Customer,15,Personal Travel,Business,414,0,3,0,2,2,0,2,2,4,4,2,4,3,2,0,0.0,satisfied +25145,61763,Female,Loyal Customer,56,Personal Travel,Eco,1379,5,5,5,3,5,4,4,1,1,5,1,4,1,4,0,0.0,satisfied +25146,55523,Female,Loyal Customer,61,Personal Travel,Eco,991,1,2,1,4,2,3,3,5,5,1,5,4,5,1,4,0.0,neutral or dissatisfied +25147,34698,Female,Loyal Customer,51,Business travel,Business,301,5,5,5,5,4,3,3,5,5,5,5,5,5,5,1,0.0,satisfied +25148,89025,Male,Loyal Customer,40,Business travel,Business,1947,4,4,4,4,4,5,5,4,4,4,4,5,4,3,5,22.0,satisfied +25149,58968,Male,Loyal Customer,24,Personal Travel,Business,1846,3,0,3,2,3,3,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +25150,74633,Male,Loyal Customer,42,Business travel,Business,2921,2,2,2,2,3,4,3,4,4,4,4,5,4,4,0,0.0,satisfied +25151,128218,Male,disloyal Customer,26,Business travel,Business,602,3,3,3,1,4,3,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +25152,101220,Male,Loyal Customer,37,Personal Travel,Eco,1235,4,5,4,1,4,4,4,4,3,2,3,5,4,4,0,0.0,neutral or dissatisfied +25153,18829,Female,Loyal Customer,52,Business travel,Business,3442,3,2,2,2,4,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +25154,123911,Female,Loyal Customer,8,Personal Travel,Eco,544,4,4,4,4,4,4,4,4,1,3,4,2,3,4,0,5.0,satisfied +25155,123252,Male,Loyal Customer,40,Personal Travel,Eco,600,2,5,2,3,1,2,1,1,2,5,2,4,3,1,0,0.0,neutral or dissatisfied +25156,109095,Female,Loyal Customer,56,Personal Travel,Eco,957,3,5,3,2,2,5,5,4,4,3,1,4,4,3,0,0.0,neutral or dissatisfied +25157,15063,Female,Loyal Customer,64,Personal Travel,Eco,576,2,4,2,2,2,1,1,3,2,5,4,1,5,1,248,270.0,neutral or dissatisfied +25158,87912,Female,disloyal Customer,33,Business travel,Business,594,2,2,2,2,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +25159,7751,Female,Loyal Customer,44,Business travel,Business,613,2,2,2,2,5,2,1,5,5,5,5,5,5,4,0,0.0,satisfied +25160,125971,Male,Loyal Customer,45,Business travel,Business,2960,3,3,2,3,3,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +25161,113904,Male,Loyal Customer,30,Business travel,Business,2329,1,1,1,1,5,5,5,5,5,2,4,3,1,5,2,2.0,satisfied +25162,41466,Male,Loyal Customer,60,Business travel,Eco,1464,4,3,3,3,4,4,4,4,4,1,4,3,4,4,58,87.0,satisfied +25163,36819,Male,Loyal Customer,11,Personal Travel,Eco Plus,2300,4,5,3,3,3,3,3,3,4,1,4,3,5,3,0,0.0,satisfied +25164,95339,Male,Loyal Customer,39,Personal Travel,Eco,293,3,4,3,3,5,3,5,5,5,5,4,5,5,5,0,10.0,neutral or dissatisfied +25165,74972,Male,Loyal Customer,47,Personal Travel,Eco,2475,1,3,1,4,2,1,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +25166,120409,Female,disloyal Customer,24,Business travel,Eco,449,1,5,1,3,5,1,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +25167,94052,Male,disloyal Customer,20,Business travel,Eco,239,5,0,5,3,4,5,4,4,3,4,5,5,5,4,0,0.0,satisfied +25168,114359,Female,disloyal Customer,21,Business travel,Eco,957,2,2,2,3,5,2,3,5,3,4,4,5,5,5,20,4.0,neutral or dissatisfied +25169,41123,Male,Loyal Customer,45,Business travel,Eco,667,1,2,3,2,1,1,1,1,3,2,4,2,3,1,24,11.0,neutral or dissatisfied +25170,122823,Female,Loyal Customer,56,Personal Travel,Eco,599,5,3,5,3,2,2,3,3,3,5,3,5,3,1,0,0.0,satisfied +25171,31521,Female,Loyal Customer,55,Business travel,Business,567,1,3,3,3,5,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +25172,23659,Male,disloyal Customer,54,Business travel,Eco,152,4,0,4,5,3,4,3,3,1,2,1,4,2,3,0,0.0,neutral or dissatisfied +25173,27034,Female,Loyal Customer,31,Business travel,Eco Plus,954,5,4,4,4,5,5,5,5,5,2,4,1,1,5,0,4.0,satisfied +25174,113968,Female,Loyal Customer,58,Business travel,Business,1838,3,3,3,3,4,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +25175,115732,Male,Loyal Customer,23,Business travel,Eco,337,5,2,2,2,5,4,2,5,1,2,3,4,3,5,0,0.0,neutral or dissatisfied +25176,48055,Female,Loyal Customer,58,Personal Travel,Eco,677,3,4,3,2,5,4,4,2,2,3,2,4,2,3,11,6.0,neutral or dissatisfied +25177,30913,Female,Loyal Customer,30,Business travel,Business,2405,5,5,5,5,5,5,5,5,5,2,2,1,4,5,0,0.0,satisfied +25178,85384,Female,Loyal Customer,43,Personal Travel,Business,332,2,4,3,2,4,5,5,5,5,3,3,4,5,5,3,0.0,neutral or dissatisfied +25179,57976,Female,Loyal Customer,27,Personal Travel,Eco,420,1,1,1,4,2,1,2,2,3,3,3,4,4,2,57,67.0,neutral or dissatisfied +25180,65504,Male,Loyal Customer,14,Personal Travel,Eco Plus,1303,1,5,1,1,4,1,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +25181,21617,Female,Loyal Customer,28,Business travel,Eco,780,3,2,2,2,3,3,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +25182,27865,Male,Loyal Customer,27,Business travel,Eco Plus,1448,0,0,0,4,1,4,1,1,1,2,4,4,1,1,5,0.0,satisfied +25183,127355,Female,Loyal Customer,67,Personal Travel,Eco,507,2,5,2,1,5,5,4,5,5,2,3,4,5,5,0,0.0,neutral or dissatisfied +25184,30329,Male,Loyal Customer,39,Business travel,Eco,391,4,1,5,1,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +25185,18381,Female,Loyal Customer,63,Business travel,Business,2849,3,3,3,3,2,4,4,4,4,4,4,3,4,4,39,55.0,satisfied +25186,34965,Male,Loyal Customer,42,Business travel,Business,3977,2,2,2,2,3,3,4,2,2,2,2,2,2,2,6,7.0,neutral or dissatisfied +25187,84028,Male,Loyal Customer,18,Personal Travel,Eco Plus,321,2,4,2,4,5,2,5,5,3,2,1,4,2,5,0,0.0,neutral or dissatisfied +25188,59161,Female,Loyal Customer,29,Business travel,Eco Plus,1726,1,5,5,5,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +25189,31965,Female,Loyal Customer,49,Business travel,Business,102,4,4,4,4,5,4,5,3,3,4,5,4,3,4,0,0.0,satisfied +25190,97215,Female,disloyal Customer,31,Business travel,Eco Plus,1497,3,2,2,3,1,2,1,1,2,4,4,3,3,1,11,11.0,neutral or dissatisfied +25191,46471,Female,Loyal Customer,56,Business travel,Business,1988,4,4,4,4,3,4,3,1,1,1,4,2,1,1,0,0.0,neutral or dissatisfied +25192,87643,Male,Loyal Customer,44,Business travel,Business,606,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,1.0,satisfied +25193,34743,Female,Loyal Customer,59,Business travel,Business,1892,2,1,3,1,3,3,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +25194,108229,Male,Loyal Customer,40,Business travel,Business,895,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,7.0,satisfied +25195,96005,Female,Loyal Customer,36,Business travel,Business,2901,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +25196,78008,Female,disloyal Customer,26,Business travel,Eco,152,3,4,3,4,5,3,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +25197,49428,Male,disloyal Customer,32,Business travel,Eco,209,2,5,2,4,4,2,4,4,5,5,1,1,1,4,0,11.0,neutral or dissatisfied +25198,1259,Male,Loyal Customer,47,Personal Travel,Eco,229,1,4,1,4,1,1,1,1,4,5,4,3,5,1,2,6.0,neutral or dissatisfied +25199,84367,Female,Loyal Customer,11,Business travel,Business,1694,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +25200,105427,Female,Loyal Customer,28,Personal Travel,Eco,452,2,5,2,2,2,2,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +25201,66289,Female,Loyal Customer,9,Personal Travel,Business,852,2,4,3,2,5,3,5,5,4,5,4,4,4,5,0,4.0,neutral or dissatisfied +25202,123089,Male,Loyal Customer,44,Business travel,Business,2076,2,3,2,2,5,5,5,5,5,5,5,5,5,5,22,14.0,satisfied +25203,98051,Female,Loyal Customer,20,Business travel,Business,1751,2,2,2,2,4,4,4,4,4,4,5,3,4,4,14,0.0,satisfied +25204,34823,Male,Loyal Customer,35,Personal Travel,Eco,264,2,3,2,1,5,2,5,5,1,5,2,3,5,5,27,27.0,neutral or dissatisfied +25205,29995,Male,Loyal Customer,38,Business travel,Eco,95,5,2,2,2,5,5,5,5,4,4,3,1,3,5,0,0.0,satisfied +25206,112614,Female,Loyal Customer,68,Personal Travel,Eco,602,3,3,3,4,3,4,3,5,5,3,5,3,5,3,12,6.0,neutral or dissatisfied +25207,45618,Male,Loyal Customer,35,Business travel,Eco,230,2,5,5,5,2,2,2,2,2,1,2,5,3,2,0,0.0,satisfied +25208,77110,Female,disloyal Customer,44,Business travel,Eco,1295,3,3,3,3,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +25209,120779,Female,Loyal Customer,30,Personal Travel,Eco,678,2,4,2,3,3,2,3,3,3,3,5,5,4,3,100,98.0,neutral or dissatisfied +25210,113532,Male,disloyal Customer,29,Business travel,Eco,391,3,2,2,4,1,2,1,1,4,4,4,1,4,1,70,73.0,neutral or dissatisfied +25211,113735,Male,Loyal Customer,29,Personal Travel,Eco,414,1,4,4,2,3,4,3,3,2,2,3,1,1,3,0,0.0,neutral or dissatisfied +25212,1479,Male,Loyal Customer,49,Business travel,Business,3053,1,1,1,1,2,4,4,5,5,5,5,5,5,5,7,0.0,satisfied +25213,42326,Male,Loyal Customer,59,Personal Travel,Eco,550,1,5,0,4,5,0,3,5,3,5,5,3,4,5,43,67.0,neutral or dissatisfied +25214,106873,Male,disloyal Customer,30,Business travel,Eco,577,4,1,4,4,5,4,5,5,4,2,4,2,3,5,0,3.0,neutral or dissatisfied +25215,122404,Male,Loyal Customer,37,Personal Travel,Eco Plus,529,3,5,3,3,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +25216,46565,Female,Loyal Customer,53,Business travel,Business,125,4,4,4,4,2,3,1,5,5,5,3,5,5,5,0,0.0,satisfied +25217,50135,Female,Loyal Customer,48,Business travel,Business,2967,2,2,2,2,5,4,5,4,4,4,4,5,4,1,0,0.0,satisfied +25218,51796,Male,Loyal Customer,30,Personal Travel,Eco,369,3,5,3,2,3,3,3,3,2,2,5,3,1,3,0,0.0,neutral or dissatisfied +25219,27769,Female,disloyal Customer,57,Business travel,Eco,909,3,3,3,3,2,3,2,2,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +25220,129046,Male,Loyal Customer,44,Business travel,Business,1744,1,1,1,1,1,1,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +25221,39251,Female,Loyal Customer,60,Business travel,Business,67,4,2,2,2,5,4,3,3,3,3,4,3,3,3,9,6.0,neutral or dissatisfied +25222,86189,Female,Loyal Customer,39,Business travel,Eco,356,2,3,3,3,2,2,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +25223,118179,Female,Loyal Customer,45,Business travel,Business,1444,5,5,5,5,4,4,4,1,1,2,1,5,1,4,0,0.0,satisfied +25224,46362,Male,Loyal Customer,47,Business travel,Business,2138,3,3,3,3,3,1,5,5,5,5,5,3,5,2,33,9.0,satisfied +25225,97684,Male,Loyal Customer,57,Business travel,Business,3136,5,5,4,5,3,5,5,3,3,4,3,4,3,3,3,2.0,satisfied +25226,117805,Male,Loyal Customer,38,Business travel,Eco,328,4,4,4,4,4,4,4,4,2,1,3,2,3,4,53,63.0,neutral or dissatisfied +25227,6679,Male,Loyal Customer,57,Business travel,Business,438,5,5,5,5,5,4,4,4,4,4,4,3,4,4,35,51.0,satisfied +25228,87299,Female,Loyal Customer,9,Personal Travel,Eco,577,1,5,1,5,1,3,3,4,2,4,5,3,5,3,150,144.0,neutral or dissatisfied +25229,30145,Female,Loyal Customer,46,Personal Travel,Eco,204,2,3,2,3,5,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +25230,46551,Male,Loyal Customer,42,Business travel,Eco,125,4,5,5,5,4,4,4,4,3,3,5,2,1,4,20,17.0,satisfied +25231,39967,Female,Loyal Customer,43,Business travel,Business,1404,1,1,1,1,3,1,4,2,2,3,2,5,2,1,0,0.0,satisfied +25232,42085,Male,Loyal Customer,56,Business travel,Eco,344,4,2,2,2,5,4,5,5,1,1,2,3,2,5,0,0.0,satisfied +25233,91491,Female,Loyal Customer,11,Personal Travel,Eco Plus,859,2,5,2,2,3,2,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +25234,15677,Male,disloyal Customer,55,Business travel,Business,217,2,2,2,1,3,2,3,3,4,2,5,2,2,3,0,0.0,neutral or dissatisfied +25235,88562,Male,Loyal Customer,55,Personal Travel,Eco,581,2,2,2,3,4,2,4,4,2,2,2,2,3,4,0,8.0,neutral or dissatisfied +25236,116501,Male,Loyal Customer,62,Personal Travel,Eco,337,3,4,4,4,5,4,5,5,3,4,4,4,5,5,12,22.0,neutral or dissatisfied +25237,126477,Male,Loyal Customer,27,Business travel,Business,1972,2,3,3,3,2,2,2,2,1,1,1,4,2,2,0,0.0,neutral or dissatisfied +25238,30961,Female,Loyal Customer,31,Personal Travel,Eco,1024,2,4,2,3,5,2,5,5,4,3,1,4,5,5,0,2.0,neutral or dissatisfied +25239,14042,Male,disloyal Customer,34,Business travel,Business,363,3,4,4,1,1,4,1,1,1,5,5,3,2,1,0,0.0,neutral or dissatisfied +25240,2693,Female,Loyal Customer,45,Business travel,Business,2079,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +25241,22556,Male,disloyal Customer,45,Business travel,Business,223,1,1,1,1,4,1,2,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +25242,29700,Female,disloyal Customer,19,Business travel,Eco,1542,5,5,5,1,1,5,2,1,5,3,4,3,3,1,0,0.0,satisfied +25243,105435,Male,Loyal Customer,43,Personal Travel,Eco,452,1,5,3,1,5,3,3,5,5,5,5,3,5,5,32,13.0,neutral or dissatisfied +25244,2619,Female,Loyal Customer,67,Personal Travel,Eco,227,2,5,2,1,4,4,4,5,5,2,5,3,5,4,0,4.0,neutral or dissatisfied +25245,87591,Male,Loyal Customer,51,Personal Travel,Eco,432,2,1,2,2,4,2,4,4,1,2,2,3,3,4,16,9.0,neutral or dissatisfied +25246,48521,Female,Loyal Customer,54,Business travel,Eco,737,2,4,4,4,3,3,3,2,2,2,2,1,2,1,0,26.0,neutral or dissatisfied +25247,23945,Female,Loyal Customer,68,Business travel,Business,936,3,4,4,4,3,2,2,3,3,3,3,1,3,2,24,33.0,neutral or dissatisfied +25248,58269,Female,Loyal Customer,56,Business travel,Business,2809,4,4,4,4,2,4,4,5,5,5,5,4,5,3,11,25.0,satisfied +25249,97728,Male,Loyal Customer,49,Business travel,Business,2307,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +25250,70660,Male,Loyal Customer,44,Business travel,Business,447,3,3,3,3,2,4,4,2,2,2,2,4,2,3,2,0.0,satisfied +25251,18681,Female,Loyal Customer,47,Personal Travel,Eco,262,1,2,1,3,4,3,4,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +25252,120584,Male,Loyal Customer,50,Business travel,Business,980,1,1,1,1,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +25253,18959,Female,Loyal Customer,12,Business travel,Eco Plus,503,4,3,3,3,4,4,3,4,3,4,1,5,5,4,4,4.0,satisfied +25254,107198,Female,Loyal Customer,50,Personal Travel,Eco,402,5,4,5,3,4,4,5,5,5,5,5,5,5,5,91,90.0,satisfied +25255,73951,Female,Loyal Customer,53,Business travel,Business,2455,1,0,0,3,2,3,3,2,2,0,2,1,2,1,17,7.0,neutral or dissatisfied +25256,63727,Male,disloyal Customer,26,Business travel,Eco,160,5,0,5,2,3,5,3,3,2,4,1,4,4,3,11,0.0,satisfied +25257,40314,Female,Loyal Customer,28,Personal Travel,Eco,358,1,5,1,5,2,1,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +25258,126781,Female,Loyal Customer,42,Business travel,Business,2296,2,2,2,2,2,3,5,3,3,3,3,3,3,4,0,0.0,satisfied +25259,63784,Male,disloyal Customer,27,Business travel,Business,1721,3,3,3,5,4,3,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +25260,27468,Male,Loyal Customer,33,Business travel,Business,3549,4,4,4,4,3,5,3,3,2,4,1,3,1,3,0,0.0,satisfied +25261,25346,Female,Loyal Customer,28,Business travel,Business,2362,5,2,5,5,5,5,5,5,2,3,5,3,3,5,0,0.0,satisfied +25262,100051,Female,Loyal Customer,35,Personal Travel,Eco,289,3,4,3,2,4,3,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +25263,124961,Male,Loyal Customer,50,Business travel,Business,2345,1,1,1,1,5,4,5,4,4,4,5,3,4,3,1,0.0,satisfied +25264,97146,Female,Loyal Customer,40,Business travel,Eco,1390,1,2,2,2,1,1,1,1,2,2,3,2,3,1,0,6.0,neutral or dissatisfied +25265,14281,Female,Loyal Customer,53,Business travel,Business,395,3,3,3,3,3,2,3,3,3,3,3,5,3,3,63,93.0,satisfied +25266,40359,Female,disloyal Customer,26,Business travel,Eco,1250,1,1,1,2,3,1,4,3,2,2,3,4,5,3,5,0.0,neutral or dissatisfied +25267,38268,Female,disloyal Customer,25,Business travel,Eco,1111,2,2,2,3,1,2,1,1,5,3,3,4,2,1,1,0.0,neutral or dissatisfied +25268,68090,Female,Loyal Customer,26,Business travel,Business,813,3,5,3,3,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +25269,106073,Female,Loyal Customer,40,Business travel,Business,302,4,4,4,4,3,4,5,5,5,5,5,5,5,4,22,11.0,satisfied +25270,104565,Female,Loyal Customer,28,Business travel,Business,369,3,3,3,3,5,5,5,5,4,3,4,4,5,5,5,0.0,satisfied +25271,1025,Female,Loyal Customer,31,Business travel,Business,2202,4,1,1,1,2,2,4,2,2,2,4,3,4,2,0,0.0,neutral or dissatisfied +25272,51801,Female,Loyal Customer,21,Personal Travel,Eco,451,4,4,4,1,3,4,3,3,3,5,1,3,3,3,0,0.0,satisfied +25273,55038,Female,Loyal Customer,59,Business travel,Business,1379,2,2,2,2,2,5,5,5,5,5,5,5,5,5,10,2.0,satisfied +25274,111686,Male,Loyal Customer,33,Business travel,Business,1796,2,2,5,2,5,4,5,5,3,5,5,5,4,5,31,37.0,satisfied +25275,128135,Male,disloyal Customer,25,Business travel,Eco,1026,3,3,3,4,3,3,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +25276,63206,Male,disloyal Customer,22,Business travel,Business,447,4,0,4,2,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +25277,5073,Female,Loyal Customer,52,Business travel,Business,2315,5,5,5,5,3,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +25278,45156,Male,Loyal Customer,49,Business travel,Business,174,4,4,4,4,4,1,3,5,5,5,4,2,5,3,20,9.0,satisfied +25279,84470,Female,disloyal Customer,21,Business travel,Business,1142,0,0,0,5,1,0,1,1,5,5,5,4,5,1,57,46.0,satisfied +25280,112049,Female,Loyal Customer,24,Personal Travel,Eco,1015,3,1,3,3,2,3,2,2,1,4,2,3,3,2,0,0.0,neutral or dissatisfied +25281,6388,Female,disloyal Customer,20,Business travel,Business,213,3,3,3,3,4,3,4,4,1,5,2,2,3,4,10,11.0,neutral or dissatisfied +25282,70822,Female,disloyal Customer,29,Business travel,Business,624,2,2,2,3,5,2,3,5,3,2,5,4,5,5,5,0.0,neutral or dissatisfied +25283,83787,Male,Loyal Customer,55,Business travel,Business,425,1,1,1,1,3,4,5,4,4,4,4,5,4,5,6,9.0,satisfied +25284,118850,Male,Loyal Customer,23,Personal Travel,Eco Plus,621,3,2,3,3,3,3,1,3,4,5,3,2,3,3,31,17.0,neutral or dissatisfied +25285,25871,Female,Loyal Customer,67,Personal Travel,Eco Plus,692,1,5,1,2,3,4,4,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +25286,61104,Male,Loyal Customer,32,Personal Travel,Eco,1607,3,5,4,3,4,4,4,4,3,4,4,4,4,4,4,6.0,neutral or dissatisfied +25287,15493,Female,Loyal Customer,21,Personal Travel,Eco,377,3,5,3,3,4,3,3,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +25288,75820,Female,Loyal Customer,48,Business travel,Business,1437,3,3,3,3,5,5,5,5,3,5,5,5,4,5,156,146.0,satisfied +25289,88298,Male,Loyal Customer,57,Business travel,Eco,223,1,5,5,5,1,1,1,1,4,3,2,2,3,1,22,17.0,neutral or dissatisfied +25290,74026,Female,Loyal Customer,25,Business travel,Business,1471,5,5,5,5,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +25291,88178,Female,Loyal Customer,60,Business travel,Eco,270,2,1,1,1,2,3,4,2,2,2,2,4,2,3,38,34.0,neutral or dissatisfied +25292,34598,Female,Loyal Customer,43,Personal Travel,Eco,1576,2,5,2,4,2,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +25293,102838,Female,Loyal Customer,44,Business travel,Business,2238,4,4,5,4,4,5,5,4,4,5,4,5,4,5,13,13.0,satisfied +25294,30732,Female,Loyal Customer,37,Business travel,Business,1069,1,2,2,2,3,4,3,1,1,1,1,4,1,1,2,26.0,neutral or dissatisfied +25295,92643,Female,Loyal Customer,40,Personal Travel,Eco,453,3,5,3,2,1,3,1,1,2,5,4,2,2,1,0,0.0,neutral or dissatisfied +25296,30481,Male,Loyal Customer,63,Personal Travel,Eco,1201,4,4,4,4,1,4,2,1,1,4,4,4,3,1,77,81.0,satisfied +25297,29263,Male,Loyal Customer,36,Business travel,Eco,550,3,4,4,4,4,3,3,4,5,4,3,3,2,3,212,222.0,satisfied +25298,112371,Female,Loyal Customer,72,Business travel,Business,853,1,1,1,1,5,5,4,5,5,5,5,5,5,5,2,3.0,satisfied +25299,77417,Male,Loyal Customer,33,Personal Travel,Eco,588,2,5,2,3,1,2,1,1,3,5,4,4,4,1,0,3.0,neutral or dissatisfied +25300,126575,Male,Loyal Customer,13,Personal Travel,Eco,1558,4,4,4,3,3,4,3,3,1,2,2,1,3,3,0,0.0,satisfied +25301,4252,Female,Loyal Customer,42,Business travel,Business,1020,1,1,1,1,4,4,5,4,4,4,4,4,4,4,0,5.0,satisfied +25302,78794,Male,Loyal Customer,34,Business travel,Business,3965,2,2,1,2,5,4,2,5,5,5,5,1,5,4,0,18.0,satisfied +25303,60494,Male,Loyal Customer,22,Business travel,Eco,641,4,3,3,3,4,4,3,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +25304,94668,Male,Loyal Customer,42,Business travel,Business,3130,5,5,5,5,3,5,4,4,4,4,4,5,4,4,0,16.0,satisfied +25305,21941,Female,Loyal Customer,39,Business travel,Business,448,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +25306,87160,Female,Loyal Customer,42,Business travel,Business,3388,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +25307,94169,Female,Loyal Customer,45,Business travel,Business,2747,3,3,3,3,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +25308,89230,Female,Loyal Customer,25,Business travel,Eco Plus,1892,2,2,2,2,2,2,2,2,3,4,3,1,3,2,26,0.0,neutral or dissatisfied +25309,62470,Male,Loyal Customer,46,Business travel,Business,1846,1,1,3,1,4,3,4,3,3,4,3,4,3,4,25,0.0,satisfied +25310,96825,Male,Loyal Customer,44,Business travel,Business,3054,5,5,5,5,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +25311,14908,Male,Loyal Customer,34,Personal Travel,Eco,315,0,5,0,3,4,0,4,4,5,3,4,5,4,4,0,0.0,satisfied +25312,92528,Male,Loyal Customer,57,Personal Travel,Eco,1947,3,4,3,2,2,3,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +25313,52714,Female,disloyal Customer,37,Business travel,Eco Plus,1162,1,1,1,3,2,1,5,2,4,4,5,4,5,2,9,13.0,neutral or dissatisfied +25314,114864,Male,Loyal Customer,47,Business travel,Business,308,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +25315,7678,Male,Loyal Customer,39,Business travel,Eco,241,4,1,1,1,4,5,4,4,4,1,4,2,1,4,0,13.0,satisfied +25316,37372,Male,disloyal Customer,38,Business travel,Business,1074,4,4,4,5,2,4,1,2,3,4,2,3,4,2,5,16.0,satisfied +25317,14776,Female,Loyal Customer,28,Business travel,Business,694,3,3,3,3,5,5,5,5,1,4,3,4,2,5,0,0.0,satisfied +25318,46026,Female,Loyal Customer,28,Business travel,Business,898,2,2,5,2,4,4,4,4,4,1,5,3,3,4,5,0.0,satisfied +25319,73747,Female,Loyal Customer,10,Personal Travel,Eco,204,4,1,4,4,2,4,2,2,2,1,3,2,3,2,0,13.0,neutral or dissatisfied +25320,121990,Male,Loyal Customer,37,Business travel,Business,1714,3,3,3,3,3,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +25321,47067,Female,Loyal Customer,30,Personal Travel,Eco,438,2,5,2,4,1,2,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +25322,118452,Male,Loyal Customer,57,Business travel,Business,3232,3,3,3,3,2,5,5,5,5,5,5,3,5,3,13,7.0,satisfied +25323,69063,Male,Loyal Customer,52,Business travel,Business,1389,3,2,3,2,4,1,1,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +25324,112786,Male,Loyal Customer,26,Business travel,Business,1497,4,4,2,4,5,5,5,5,3,4,4,5,4,5,52,32.0,satisfied +25325,75905,Female,Loyal Customer,63,Business travel,Business,203,4,4,4,4,1,4,1,5,5,5,4,3,5,3,0,0.0,satisfied +25326,125773,Male,Loyal Customer,30,Business travel,Business,2030,3,3,3,3,5,5,5,5,5,4,4,4,4,5,14,10.0,satisfied +25327,34097,Male,Loyal Customer,56,Business travel,Business,2917,5,3,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +25328,97709,Female,Loyal Customer,59,Business travel,Business,3841,5,5,5,5,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +25329,126267,Female,disloyal Customer,38,Business travel,Eco,200,2,4,2,4,5,2,5,5,1,4,4,1,3,5,39,25.0,neutral or dissatisfied +25330,60743,Male,Loyal Customer,52,Business travel,Business,2273,2,1,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +25331,79118,Male,Loyal Customer,38,Personal Travel,Eco,356,3,5,3,5,3,3,3,3,4,2,3,5,5,3,68,59.0,neutral or dissatisfied +25332,115749,Female,Loyal Customer,60,Business travel,Business,337,3,3,3,3,2,5,5,5,5,5,5,4,5,5,10,4.0,satisfied +25333,74571,Male,Loyal Customer,40,Business travel,Business,1548,2,2,2,2,2,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +25334,35360,Female,Loyal Customer,28,Business travel,Eco,950,3,4,4,4,3,4,3,3,2,1,1,3,1,3,0,0.0,satisfied +25335,63812,Female,Loyal Customer,58,Business travel,Eco Plus,1224,5,2,2,2,4,5,1,4,4,5,4,2,4,4,52,56.0,satisfied +25336,29546,Female,Loyal Customer,37,Business travel,Eco,1448,4,4,3,3,4,4,4,4,3,5,1,2,5,4,0,0.0,satisfied +25337,2921,Female,Loyal Customer,42,Personal Travel,Business,806,3,5,3,4,1,5,4,4,4,3,4,3,4,4,26,21.0,neutral or dissatisfied +25338,118559,Female,Loyal Customer,35,Business travel,Business,1702,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +25339,55385,Male,Loyal Customer,38,Personal Travel,Eco,678,3,2,3,3,4,3,4,4,2,4,4,4,4,4,1,15.0,neutral or dissatisfied +25340,84607,Male,Loyal Customer,29,Business travel,Business,669,2,2,2,2,5,5,5,5,3,4,5,4,5,5,3,0.0,satisfied +25341,94987,Female,Loyal Customer,10,Personal Travel,Eco,187,0,3,0,3,2,0,2,2,4,5,3,1,4,2,13,7.0,satisfied +25342,91578,Female,disloyal Customer,47,Business travel,Eco,723,5,5,5,3,5,5,5,5,3,2,2,5,4,5,0,0.0,satisfied +25343,67897,Female,Loyal Customer,43,Personal Travel,Eco,1235,2,4,2,4,5,3,4,4,4,2,5,1,4,2,4,1.0,neutral or dissatisfied +25344,13071,Male,Loyal Customer,54,Business travel,Business,609,2,2,2,2,4,5,3,5,5,5,5,5,5,3,0,0.0,satisfied +25345,18206,Female,Loyal Customer,39,Business travel,Business,1967,5,5,5,5,3,1,2,5,5,5,5,5,5,1,71,57.0,satisfied +25346,41970,Female,disloyal Customer,22,Business travel,Eco,575,2,0,2,1,3,2,3,3,3,2,4,2,5,3,0,0.0,neutral or dissatisfied +25347,85641,Female,disloyal Customer,36,Business travel,Business,259,4,5,5,3,3,5,3,3,4,3,4,4,5,3,84,69.0,neutral or dissatisfied +25348,98706,Male,Loyal Customer,41,Business travel,Business,1582,1,1,1,1,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +25349,103625,Female,Loyal Customer,42,Business travel,Business,405,1,1,1,1,3,5,4,4,4,4,4,5,4,3,6,0.0,satisfied +25350,30414,Female,Loyal Customer,45,Business travel,Eco Plus,641,3,4,4,4,5,5,4,3,3,3,3,5,3,2,0,0.0,satisfied +25351,100903,Male,Loyal Customer,37,Business travel,Eco,377,1,2,2,2,1,1,1,1,2,1,4,2,4,1,105,99.0,neutral or dissatisfied +25352,38604,Male,Loyal Customer,32,Business travel,Eco,231,3,3,2,3,3,4,3,3,5,4,4,4,2,3,0,0.0,satisfied +25353,30026,Male,Loyal Customer,30,Business travel,Business,1975,4,4,4,4,4,4,4,4,4,5,3,4,1,4,0,4.0,satisfied +25354,36859,Female,Loyal Customer,54,Business travel,Eco,273,1,0,0,4,5,4,4,4,4,1,4,4,4,3,0,9.0,neutral or dissatisfied +25355,58742,Female,Loyal Customer,58,Business travel,Business,1012,4,4,4,4,2,4,4,4,4,4,4,3,4,3,21,21.0,satisfied +25356,80118,Male,Loyal Customer,38,Business travel,Eco Plus,120,5,5,5,5,5,5,5,5,5,5,3,1,3,5,0,0.0,satisfied +25357,109506,Female,Loyal Customer,49,Business travel,Eco,873,4,2,2,2,3,3,3,4,4,4,4,3,4,2,11,1.0,neutral or dissatisfied +25358,46477,Male,Loyal Customer,44,Business travel,Business,125,2,2,2,2,3,3,3,3,3,3,2,4,3,2,0,0.0,neutral or dissatisfied +25359,110600,Male,Loyal Customer,35,Personal Travel,Eco,488,2,0,3,2,5,3,4,5,5,4,5,5,4,5,21,35.0,neutral or dissatisfied +25360,9774,Male,Loyal Customer,39,Business travel,Business,3437,3,3,3,3,1,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +25361,97159,Male,Loyal Customer,36,Business travel,Business,2474,3,3,3,3,1,3,3,3,3,3,3,2,3,4,21,23.0,neutral or dissatisfied +25362,11040,Male,Loyal Customer,52,Personal Travel,Eco,166,5,5,5,3,4,5,4,4,4,3,5,4,5,4,25,35.0,satisfied +25363,10226,Male,Loyal Customer,45,Business travel,Business,3728,5,5,5,5,4,5,5,5,5,5,5,3,5,3,4,1.0,satisfied +25364,930,Female,disloyal Customer,26,Business travel,Business,354,1,2,1,3,4,1,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +25365,87560,Male,Loyal Customer,43,Business travel,Eco,432,1,2,2,2,1,1,1,1,3,5,4,1,3,1,19,22.0,neutral or dissatisfied +25366,64421,Male,Loyal Customer,17,Personal Travel,Business,989,2,5,2,4,1,2,1,1,3,4,2,5,3,1,2,0.0,neutral or dissatisfied +25367,21806,Female,disloyal Customer,23,Business travel,Eco,341,3,0,3,3,4,3,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +25368,46842,Male,Loyal Customer,26,Business travel,Business,948,4,4,4,4,4,5,4,4,1,4,2,2,5,4,12,5.0,satisfied +25369,1812,Female,Loyal Customer,57,Business travel,Business,408,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +25370,23621,Female,Loyal Customer,27,Business travel,Eco,977,1,2,2,2,1,1,1,1,4,3,4,1,3,1,56,48.0,neutral or dissatisfied +25371,45521,Male,Loyal Customer,13,Personal Travel,Eco,689,4,4,5,1,1,5,1,1,4,3,5,4,4,1,0,0.0,satisfied +25372,120350,Male,Loyal Customer,56,Personal Travel,Business,366,2,4,2,1,3,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +25373,103182,Male,Loyal Customer,57,Business travel,Business,272,1,1,1,1,5,5,5,3,2,4,4,5,4,5,184,180.0,satisfied +25374,60449,Male,Loyal Customer,51,Business travel,Business,2542,1,1,1,1,2,4,5,5,5,5,5,5,5,3,7,0.0,satisfied +25375,82381,Male,Loyal Customer,45,Business travel,Business,500,1,1,1,1,2,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +25376,68906,Female,Loyal Customer,14,Personal Travel,Eco,936,2,4,2,3,4,2,5,4,1,4,4,4,3,4,45,41.0,neutral or dissatisfied +25377,19181,Male,Loyal Customer,43,Business travel,Business,1024,2,2,2,2,3,4,3,2,2,2,2,4,2,3,9,0.0,neutral or dissatisfied +25378,10611,Female,Loyal Customer,57,Business travel,Business,158,3,5,5,5,1,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +25379,84370,Female,Loyal Customer,65,Business travel,Business,2216,3,1,1,1,4,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +25380,70409,Female,disloyal Customer,13,Personal Travel,Eco,1562,1,5,1,2,4,1,4,4,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +25381,80316,Female,Loyal Customer,63,Personal Travel,Eco,746,3,4,3,3,1,4,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +25382,11929,Female,Loyal Customer,42,Business travel,Eco Plus,744,1,2,2,2,1,3,4,1,1,1,1,3,1,3,3,14.0,neutral or dissatisfied +25383,103,Male,Loyal Customer,44,Business travel,Business,1964,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +25384,10658,Male,Loyal Customer,54,Business travel,Business,3171,5,5,5,5,3,4,5,3,3,3,3,3,3,5,0,4.0,satisfied +25385,47943,Female,Loyal Customer,12,Personal Travel,Eco,817,4,3,4,5,1,4,1,1,1,2,4,1,5,1,0,0.0,satisfied +25386,81,Female,Loyal Customer,19,Personal Travel,Eco,215,2,3,2,3,1,2,1,1,5,2,2,5,5,1,0,0.0,neutral or dissatisfied +25387,85764,Male,Loyal Customer,44,Business travel,Eco,666,3,3,2,3,3,3,3,3,4,5,3,4,3,3,17,1.0,neutral or dissatisfied +25388,98788,Female,Loyal Customer,53,Business travel,Business,2852,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +25389,99530,Female,Loyal Customer,54,Business travel,Business,829,2,2,2,2,5,3,2,2,2,2,2,2,2,1,26,31.0,neutral or dissatisfied +25390,125594,Male,Loyal Customer,40,Business travel,Business,1587,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +25391,108500,Female,Loyal Customer,41,Business travel,Eco,287,2,4,5,4,2,2,2,2,2,2,2,3,3,2,0,0.0,neutral or dissatisfied +25392,29823,Male,disloyal Customer,40,Business travel,Eco,261,1,0,1,4,5,1,5,5,3,5,4,5,1,5,0,0.0,neutral or dissatisfied +25393,124023,Male,Loyal Customer,28,Personal Travel,Eco,184,4,5,4,3,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +25394,103269,Female,Loyal Customer,61,Personal Travel,Eco,888,3,5,4,4,2,5,5,5,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +25395,102434,Male,Loyal Customer,11,Personal Travel,Eco,414,1,4,4,3,1,4,1,1,3,3,1,2,1,1,6,0.0,neutral or dissatisfied +25396,66513,Female,Loyal Customer,16,Personal Travel,Eco,447,2,5,2,1,3,2,4,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +25397,89540,Male,Loyal Customer,56,Business travel,Business,950,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,3.0,satisfied +25398,82310,Female,Loyal Customer,65,Business travel,Business,2180,2,2,2,2,3,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +25399,14713,Female,Loyal Customer,40,Personal Travel,Eco,317,2,3,2,3,5,2,1,5,5,3,4,2,2,5,0,0.0,neutral or dissatisfied +25400,118402,Male,Loyal Customer,59,Personal Travel,Business,369,2,4,2,2,2,5,1,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +25401,30739,Female,Loyal Customer,27,Business travel,Eco,589,3,5,5,5,3,3,3,3,2,4,1,2,2,3,0,8.0,neutral or dissatisfied +25402,63265,Male,Loyal Customer,48,Business travel,Business,337,2,2,2,2,3,5,4,4,4,4,4,3,4,5,2,2.0,satisfied +25403,87945,Male,Loyal Customer,13,Personal Travel,Business,444,4,4,4,5,1,4,4,1,4,2,4,4,4,1,0,0.0,satisfied +25404,84891,Male,Loyal Customer,63,Personal Travel,Eco,516,4,4,4,2,4,4,4,4,5,3,5,5,5,4,46,52.0,neutral or dissatisfied +25405,56869,Male,Loyal Customer,41,Business travel,Business,2434,4,4,4,4,5,5,5,4,2,4,5,5,5,5,17,0.0,satisfied +25406,72851,Male,disloyal Customer,39,Business travel,Business,700,5,4,4,2,1,4,1,1,5,4,5,3,5,1,15,0.0,satisfied +25407,59992,Male,Loyal Customer,58,Personal Travel,Eco,1023,3,3,2,3,5,2,5,5,1,3,5,2,3,5,0,0.0,neutral or dissatisfied +25408,109209,Female,Loyal Customer,16,Business travel,Eco,793,3,4,4,4,3,3,1,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +25409,74311,Female,disloyal Customer,30,Business travel,Business,1205,3,3,3,1,1,3,1,1,4,3,4,3,5,1,47,34.0,neutral or dissatisfied +25410,9706,Male,Loyal Customer,46,Personal Travel,Eco,284,1,4,1,1,5,1,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +25411,104256,Female,Loyal Customer,55,Business travel,Business,2313,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +25412,88770,Female,Loyal Customer,57,Business travel,Business,2190,5,5,5,5,4,4,5,4,4,4,4,3,4,4,5,0.0,satisfied +25413,101173,Female,disloyal Customer,54,Business travel,Eco,375,3,0,3,3,4,3,4,4,5,1,5,1,3,4,9,0.0,neutral or dissatisfied +25414,95155,Female,Loyal Customer,21,Personal Travel,Eco,248,3,5,3,2,3,3,3,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +25415,59488,Male,Loyal Customer,37,Personal Travel,Eco,758,2,4,2,3,2,2,1,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +25416,128997,Male,Loyal Customer,21,Personal Travel,Eco Plus,414,3,1,3,2,2,3,2,2,2,5,1,4,2,2,0,0.0,neutral or dissatisfied +25417,105369,Female,Loyal Customer,49,Business travel,Business,369,3,2,2,2,1,3,3,3,3,3,3,1,3,1,22,16.0,neutral or dissatisfied +25418,14371,Male,Loyal Customer,24,Business travel,Business,1325,5,2,2,2,5,4,5,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +25419,129457,Female,disloyal Customer,24,Business travel,Business,414,4,4,4,2,5,4,5,5,3,2,5,5,4,5,0,0.0,satisfied +25420,107266,Female,disloyal Customer,45,Business travel,Business,307,4,4,4,4,1,4,1,1,4,3,4,5,4,1,69,62.0,satisfied +25421,119306,Male,Loyal Customer,46,Business travel,Eco,214,2,1,1,1,2,2,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +25422,35941,Male,Loyal Customer,18,Personal Travel,Eco Plus,2381,1,5,1,1,2,1,2,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +25423,24242,Male,Loyal Customer,24,Business travel,Business,3437,3,3,3,3,3,4,4,3,3,5,2,3,1,3,0,0.0,satisfied +25424,26867,Female,disloyal Customer,20,Business travel,Eco,1073,2,2,2,3,5,2,1,5,4,5,4,3,3,5,0,0.0,satisfied +25425,5078,Male,Loyal Customer,39,Business travel,Eco,235,2,3,3,3,2,2,2,2,1,3,2,1,2,2,50,65.0,neutral or dissatisfied +25426,39889,Female,Loyal Customer,37,Personal Travel,Eco,272,2,4,2,4,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +25427,108084,Female,Loyal Customer,36,Business travel,Business,1166,2,2,2,2,3,4,4,4,4,4,4,5,4,3,7,4.0,satisfied +25428,101221,Female,Loyal Customer,56,Personal Travel,Eco,795,3,5,3,3,4,4,4,2,2,3,2,5,2,3,19,2.0,neutral or dissatisfied +25429,4419,Female,disloyal Customer,13,Business travel,Eco,762,3,3,3,4,2,3,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +25430,126040,Male,disloyal Customer,37,Business travel,Business,328,4,4,4,3,3,4,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +25431,124623,Male,Loyal Customer,31,Business travel,Eco,1671,4,2,2,2,4,4,4,4,5,1,3,4,4,4,0,0.0,satisfied +25432,16460,Female,Loyal Customer,55,Personal Travel,Eco,416,4,2,4,4,2,3,3,5,5,4,3,3,5,3,0,0.0,neutral or dissatisfied +25433,113652,Male,Loyal Customer,43,Personal Travel,Eco,386,2,5,2,2,2,2,4,2,3,4,4,3,4,2,54,47.0,neutral or dissatisfied +25434,126090,Male,disloyal Customer,22,Business travel,Eco,631,4,0,4,5,2,4,2,2,5,4,5,5,5,2,0,6.0,satisfied +25435,39322,Female,Loyal Customer,33,Personal Travel,Eco,67,2,5,2,4,4,2,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +25436,30148,Male,Loyal Customer,11,Personal Travel,Eco,261,3,1,3,3,2,3,2,2,4,3,3,2,3,2,51,53.0,neutral or dissatisfied +25437,11416,Male,disloyal Customer,23,Business travel,Eco,295,4,0,4,3,2,4,2,2,5,4,4,4,4,2,58,52.0,satisfied +25438,90116,Male,Loyal Customer,55,Business travel,Business,2771,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +25439,109250,Female,Loyal Customer,48,Personal Travel,Eco,401,2,1,2,1,1,2,1,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +25440,68444,Male,Loyal Customer,52,Business travel,Business,3646,1,1,1,1,5,5,5,4,3,4,4,5,4,5,186,183.0,satisfied +25441,55534,Male,Loyal Customer,52,Business travel,Business,2016,1,1,2,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +25442,117967,Female,Loyal Customer,55,Personal Travel,Eco,365,2,4,2,2,5,4,5,4,4,2,4,3,4,5,3,0.0,neutral or dissatisfied +25443,118749,Male,Loyal Customer,62,Personal Travel,Eco,647,3,4,4,4,4,5,3,2,1,2,3,3,4,3,140,127.0,neutral or dissatisfied +25444,128799,Male,Loyal Customer,23,Business travel,Business,2475,4,4,4,4,2,2,2,5,2,3,5,2,3,2,0,0.0,satisfied +25445,28459,Female,Loyal Customer,15,Personal Travel,Eco,2588,3,5,3,1,3,5,4,5,4,4,5,4,3,4,0,31.0,neutral or dissatisfied +25446,40975,Male,Loyal Customer,50,Personal Travel,Eco,601,4,5,4,4,1,4,1,1,4,5,1,3,2,1,0,0.0,neutral or dissatisfied +25447,75205,Female,Loyal Customer,44,Business travel,Business,1744,2,2,4,2,4,1,2,2,2,2,2,1,2,2,5,12.0,neutral or dissatisfied +25448,47193,Male,disloyal Customer,36,Business travel,Eco,565,3,0,3,3,4,3,1,4,3,5,3,2,1,4,0,0.0,neutral or dissatisfied +25449,124463,Male,Loyal Customer,44,Business travel,Business,2899,3,2,4,2,5,4,4,3,3,2,3,3,3,4,60,30.0,neutral or dissatisfied +25450,53103,Male,Loyal Customer,29,Business travel,Business,1628,4,4,5,4,5,5,5,5,3,5,3,1,2,5,0,0.0,satisfied +25451,29009,Female,Loyal Customer,56,Business travel,Business,2196,1,2,2,2,2,1,2,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +25452,98913,Male,Loyal Customer,54,Business travel,Business,1840,4,4,5,4,2,4,4,5,5,5,5,5,5,5,69,81.0,satisfied +25453,25736,Male,Loyal Customer,33,Personal Travel,Eco,528,3,4,3,2,2,3,2,2,3,2,5,4,5,2,25,77.0,neutral or dissatisfied +25454,30035,Male,disloyal Customer,27,Business travel,Business,234,2,2,2,4,2,2,5,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +25455,95125,Female,Loyal Customer,26,Personal Travel,Eco,192,3,4,3,3,5,3,5,5,4,3,5,5,5,5,17,30.0,neutral or dissatisfied +25456,114511,Female,disloyal Customer,20,Business travel,Eco,404,1,3,1,3,2,1,4,2,4,3,4,3,3,2,1,0.0,neutral or dissatisfied +25457,65835,Female,disloyal Customer,27,Business travel,Eco,1389,2,2,2,4,1,2,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +25458,84265,Male,Loyal Customer,75,Business travel,Business,2940,0,0,0,2,3,5,5,1,1,1,1,4,1,4,1,0.0,satisfied +25459,13075,Female,Loyal Customer,44,Business travel,Eco Plus,936,3,5,5,5,4,5,1,3,3,3,3,5,3,4,13,37.0,satisfied +25460,120067,Female,Loyal Customer,23,Business travel,Business,3164,2,5,2,2,4,4,4,4,5,4,5,5,5,4,16,15.0,satisfied +25461,27882,Female,Loyal Customer,68,Personal Travel,Eco Plus,1448,3,2,3,3,5,4,4,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +25462,58122,Male,Loyal Customer,69,Personal Travel,Eco,612,4,4,4,2,4,4,4,4,2,1,3,3,4,4,0,0.0,satisfied +25463,93501,Male,Loyal Customer,13,Personal Travel,Eco,1107,2,4,2,1,3,2,1,3,4,2,4,4,4,3,45,26.0,neutral or dissatisfied +25464,109704,Female,disloyal Customer,24,Business travel,Business,587,4,0,4,3,3,4,3,3,4,2,4,3,5,3,28,29.0,satisfied +25465,3418,Male,Loyal Customer,7,Personal Travel,Eco,213,3,4,0,4,4,0,4,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +25466,123722,Female,disloyal Customer,37,Business travel,Eco Plus,214,4,4,4,3,5,4,5,5,2,3,4,2,4,5,0,0.0,neutral or dissatisfied +25467,21417,Male,disloyal Customer,42,Business travel,Eco,331,3,4,3,4,1,3,4,1,4,1,3,5,4,1,91,83.0,neutral or dissatisfied +25468,69153,Male,Loyal Customer,58,Business travel,Business,187,5,5,5,5,3,5,5,4,4,4,5,5,4,5,0,0.0,satisfied +25469,105651,Male,Loyal Customer,49,Business travel,Business,3615,3,3,3,3,4,4,5,4,4,5,4,5,4,3,2,0.0,satisfied +25470,52594,Female,Loyal Customer,50,Business travel,Business,2229,1,1,1,1,3,3,2,5,5,5,5,5,5,4,0,0.0,satisfied +25471,80268,Male,Loyal Customer,28,Personal Travel,Eco Plus,488,3,0,3,1,5,3,5,5,5,2,4,5,4,5,0,0.0,neutral or dissatisfied +25472,127733,Male,Loyal Customer,38,Business travel,Business,3650,2,3,5,3,2,2,2,2,2,2,2,3,2,4,6,14.0,neutral or dissatisfied +25473,96932,Male,Loyal Customer,26,Personal Travel,Eco Plus,781,2,1,2,3,3,2,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +25474,125070,Female,Loyal Customer,47,Business travel,Business,2113,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +25475,83314,Male,Loyal Customer,28,Business travel,Business,1671,3,3,3,3,4,4,4,4,5,5,5,5,5,4,34,13.0,satisfied +25476,41495,Female,Loyal Customer,24,Business travel,Business,1464,3,3,3,3,4,4,4,4,5,1,5,4,1,4,0,0.0,satisfied +25477,110680,Female,Loyal Customer,27,Personal Travel,Eco,829,3,4,3,1,2,3,2,2,4,5,4,5,4,2,4,19.0,neutral or dissatisfied +25478,88932,Female,Loyal Customer,54,Business travel,Business,2726,4,4,4,4,5,4,4,4,4,4,4,4,4,5,9,5.0,satisfied +25479,10138,Male,Loyal Customer,14,Business travel,Business,2786,5,5,5,5,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +25480,102835,Female,disloyal Customer,36,Business travel,Business,423,3,3,3,3,1,3,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +25481,114080,Female,Loyal Customer,34,Business travel,Business,1892,3,5,3,5,3,2,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +25482,29907,Female,Loyal Customer,15,Business travel,Business,2669,0,3,0,4,4,4,3,4,1,1,3,2,4,4,0,0.0,satisfied +25483,120486,Female,Loyal Customer,32,Personal Travel,Eco,449,2,4,2,3,3,2,2,3,3,3,4,4,5,3,7,1.0,neutral or dissatisfied +25484,24122,Female,Loyal Customer,48,Personal Travel,Eco,510,1,4,1,4,4,3,4,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +25485,36893,Female,Loyal Customer,39,Business travel,Business,1368,4,2,2,2,1,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +25486,37177,Female,Loyal Customer,22,Personal Travel,Eco,1189,3,5,3,1,1,3,1,1,5,4,5,3,4,1,0,1.0,neutral or dissatisfied +25487,82882,Male,Loyal Customer,30,Business travel,Business,2456,2,2,2,2,4,4,4,4,4,2,2,2,5,4,110,104.0,satisfied +25488,6619,Male,Loyal Customer,56,Business travel,Business,3178,1,1,1,1,3,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +25489,117122,Female,Loyal Customer,38,Business travel,Business,3144,0,0,0,2,2,2,2,3,3,3,2,5,3,4,2,0.0,satisfied +25490,71081,Male,Loyal Customer,27,Personal Travel,Eco,802,2,4,2,4,2,2,2,2,4,5,4,3,4,2,13,36.0,neutral or dissatisfied +25491,46121,Male,Loyal Customer,30,Business travel,Business,2548,2,2,2,2,4,4,4,4,2,5,3,2,1,4,75,83.0,satisfied +25492,109887,Male,Loyal Customer,48,Business travel,Business,3386,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +25493,101109,Male,Loyal Customer,57,Business travel,Business,1090,5,5,5,5,2,5,5,4,4,4,4,5,4,4,19,0.0,satisfied +25494,76164,Female,Loyal Customer,34,Personal Travel,Eco,546,4,5,4,4,1,4,5,1,5,3,1,1,2,1,0,0.0,neutral or dissatisfied +25495,101142,Female,Loyal Customer,59,Business travel,Business,583,4,4,4,4,4,4,4,2,2,2,2,5,2,5,10,8.0,satisfied +25496,79773,Male,Loyal Customer,56,Business travel,Business,950,1,1,1,1,2,5,5,4,4,3,4,4,4,3,0,0.0,satisfied +25497,18410,Male,Loyal Customer,14,Personal Travel,Eco,284,3,4,3,4,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +25498,85573,Male,Loyal Customer,32,Business travel,Business,153,2,2,2,2,5,5,5,5,3,3,4,5,5,5,14,1.0,satisfied +25499,108429,Male,Loyal Customer,24,Business travel,Business,1444,2,2,5,2,3,4,3,3,4,4,4,4,5,3,46,64.0,satisfied +25500,57376,Female,disloyal Customer,28,Business travel,Business,414,5,5,5,4,5,5,2,5,4,5,4,3,4,5,0,0.0,satisfied +25501,34948,Female,Loyal Customer,59,Personal Travel,Eco,187,3,4,3,3,3,4,1,2,2,3,2,3,2,1,31,51.0,neutral or dissatisfied +25502,42722,Male,Loyal Customer,48,Personal Travel,Eco,1042,1,4,1,4,2,1,2,2,3,4,3,2,3,2,4,6.0,neutral or dissatisfied +25503,21574,Male,Loyal Customer,39,Personal Travel,Eco Plus,399,3,4,3,4,1,3,1,1,5,5,2,3,1,1,10,3.0,neutral or dissatisfied +25504,99174,Female,Loyal Customer,42,Personal Travel,Eco Plus,986,1,4,2,2,1,5,3,3,3,2,3,3,3,2,23,14.0,neutral or dissatisfied +25505,55827,Female,Loyal Customer,37,Business travel,Business,1416,3,3,3,3,2,4,4,5,5,5,5,5,5,5,17,22.0,satisfied +25506,80725,Female,Loyal Customer,39,Business travel,Business,2193,2,2,2,2,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +25507,118868,Male,Loyal Customer,68,Personal Travel,Eco Plus,651,2,5,2,3,1,2,1,1,3,1,2,4,4,1,89,92.0,neutral or dissatisfied +25508,46831,Female,Loyal Customer,46,Business travel,Business,3892,2,2,2,2,2,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +25509,17894,Female,disloyal Customer,46,Business travel,Eco Plus,371,4,4,4,3,2,4,2,2,3,2,3,3,1,2,0,0.0,satisfied +25510,25053,Male,Loyal Customer,40,Business travel,Business,3788,2,2,2,2,2,1,1,4,4,4,4,4,4,3,0,0.0,satisfied +25511,100953,Female,Loyal Customer,23,Business travel,Business,3758,2,3,3,3,2,2,2,2,4,3,4,3,3,2,0,3.0,neutral or dissatisfied +25512,93811,Female,Loyal Customer,60,Business travel,Business,2051,5,5,2,5,3,4,5,4,4,4,4,4,4,5,33,61.0,satisfied +25513,43025,Male,Loyal Customer,58,Business travel,Business,259,3,3,3,3,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +25514,119350,Female,Loyal Customer,70,Personal Travel,Eco Plus,214,3,0,3,3,4,5,5,4,4,3,4,3,4,5,0,17.0,neutral or dissatisfied +25515,19993,Male,disloyal Customer,36,Business travel,Eco,599,2,4,2,3,5,2,5,5,5,3,5,1,2,5,127,121.0,neutral or dissatisfied +25516,10324,Female,Loyal Customer,50,Business travel,Business,295,0,0,0,3,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +25517,25231,Female,Loyal Customer,49,Business travel,Eco,925,4,2,2,2,5,4,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +25518,104690,Male,Loyal Customer,70,Business travel,Business,3615,2,2,2,2,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +25519,102333,Female,disloyal Customer,40,Business travel,Business,197,2,2,2,3,5,2,5,5,1,3,4,4,3,5,11,10.0,neutral or dissatisfied +25520,81367,Male,Loyal Customer,37,Business travel,Business,3570,4,5,4,4,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +25521,97214,Male,Loyal Customer,39,Business travel,Eco Plus,1390,1,1,1,1,1,1,1,1,1,1,4,1,4,1,0,0.0,neutral or dissatisfied +25522,76365,Female,Loyal Customer,54,Business travel,Business,1744,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +25523,13340,Male,Loyal Customer,27,Business travel,Business,2902,5,5,5,5,4,4,4,4,3,5,4,5,4,4,11,27.0,satisfied +25524,46312,Female,disloyal Customer,38,Business travel,Eco Plus,1069,2,2,2,3,1,2,1,1,1,3,1,5,1,1,0,0.0,neutral or dissatisfied +25525,76352,Male,Loyal Customer,64,Business travel,Business,1851,4,4,4,4,3,5,5,4,4,4,4,3,4,3,9,0.0,satisfied +25526,7323,Male,Loyal Customer,32,Personal Travel,Eco Plus,116,1,3,1,4,3,1,4,3,4,2,1,3,1,3,0,0.0,neutral or dissatisfied +25527,93117,Male,Loyal Customer,50,Business travel,Business,3681,5,3,2,2,3,3,3,5,5,4,5,4,5,3,8,0.0,neutral or dissatisfied +25528,61317,Male,Loyal Customer,42,Business travel,Business,862,4,4,4,4,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +25529,16909,Male,disloyal Customer,20,Personal Travel,Eco,746,4,4,4,4,1,4,1,1,4,3,4,2,3,1,0,0.0,satisfied +25530,43627,Male,Loyal Customer,9,Personal Travel,Eco,190,2,4,2,1,3,2,4,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +25531,5689,Male,Loyal Customer,36,Business travel,Business,3700,3,4,4,4,3,3,3,4,3,4,3,3,3,3,108,140.0,neutral or dissatisfied +25532,19094,Male,Loyal Customer,43,Business travel,Business,265,0,0,0,5,4,5,4,5,5,3,3,4,5,3,11,0.0,satisfied +25533,32906,Male,Loyal Customer,52,Personal Travel,Eco,102,4,4,4,4,4,4,4,4,3,2,4,3,4,4,0,2.0,neutral or dissatisfied +25534,106269,Female,Loyal Customer,56,Business travel,Business,689,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +25535,44787,Male,Loyal Customer,35,Business travel,Business,3237,3,3,3,3,1,1,5,5,5,5,5,3,5,1,0,0.0,satisfied +25536,8220,Female,Loyal Customer,63,Personal Travel,Eco,335,3,4,3,2,4,2,5,4,4,3,4,3,4,3,21,20.0,neutral or dissatisfied +25537,41251,Male,Loyal Customer,31,Business travel,Business,2691,2,2,2,2,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +25538,45377,Female,Loyal Customer,39,Business travel,Eco Plus,461,4,1,2,1,4,4,4,4,5,4,5,1,4,4,0,0.0,satisfied +25539,33919,Male,Loyal Customer,67,Personal Travel,Eco,636,3,5,3,4,3,3,1,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +25540,117477,Female,Loyal Customer,29,Business travel,Business,2968,2,2,2,2,5,5,5,5,5,2,5,3,4,5,72,77.0,satisfied +25541,47130,Female,disloyal Customer,27,Business travel,Business,954,4,4,4,3,3,4,3,3,2,4,3,2,4,3,0,0.0,neutral or dissatisfied +25542,13286,Male,Loyal Customer,19,Personal Travel,Eco,771,4,3,4,2,3,4,3,3,1,4,2,4,3,3,0,0.0,neutral or dissatisfied +25543,111154,Female,Loyal Customer,14,Personal Travel,Eco,1173,2,5,2,3,3,2,3,3,5,2,4,4,4,3,88,106.0,neutral or dissatisfied +25544,120045,Male,Loyal Customer,65,Personal Travel,Eco,168,2,5,0,4,5,0,5,5,1,3,5,1,5,5,0,0.0,neutral or dissatisfied +25545,83184,Female,Loyal Customer,41,Business travel,Business,3967,3,3,5,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +25546,35555,Female,Loyal Customer,14,Personal Travel,Eco,944,2,3,3,5,1,3,1,1,5,2,1,5,5,1,0,0.0,neutral or dissatisfied +25547,7948,Male,Loyal Customer,58,Business travel,Business,2279,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +25548,21458,Female,disloyal Customer,32,Business travel,Eco,377,3,3,3,3,3,3,3,3,1,4,4,3,3,3,26,21.0,neutral or dissatisfied +25549,119220,Female,Loyal Customer,43,Personal Travel,Eco,331,2,3,2,2,1,2,2,3,3,2,3,1,3,3,5,60.0,neutral or dissatisfied +25550,64363,Female,Loyal Customer,43,Business travel,Business,2278,3,4,4,4,1,2,1,3,3,3,3,3,3,2,13,8.0,neutral or dissatisfied +25551,41343,Female,Loyal Customer,38,Business travel,Eco Plus,289,4,1,4,4,4,4,4,4,4,5,2,1,4,4,15,0.0,satisfied +25552,115428,Male,disloyal Customer,64,Business travel,Business,404,4,4,4,2,1,4,1,1,5,3,5,4,4,1,20,9.0,neutral or dissatisfied +25553,115050,Female,Loyal Customer,57,Business travel,Business,1604,0,0,0,5,4,5,5,5,5,5,5,5,5,3,12,10.0,satisfied +25554,62857,Male,Loyal Customer,42,Business travel,Business,2446,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +25555,56705,Female,Loyal Customer,63,Personal Travel,Eco,1065,2,5,2,3,4,4,4,1,1,2,1,4,1,5,5,30.0,neutral or dissatisfied +25556,104624,Female,disloyal Customer,18,Business travel,Eco,861,4,4,4,3,5,4,5,5,3,2,4,2,3,5,0,0.0,neutral or dissatisfied +25557,124651,Male,Loyal Customer,13,Personal Travel,Business,399,2,5,2,4,5,2,5,5,1,5,4,2,2,5,0,2.0,neutral or dissatisfied +25558,17293,Female,Loyal Customer,25,Business travel,Eco,403,0,3,0,4,3,0,3,3,2,5,5,3,2,3,0,0.0,satisfied +25559,8923,Female,Loyal Customer,22,Personal Travel,Eco,661,1,5,1,2,3,1,2,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +25560,118518,Male,Loyal Customer,57,Business travel,Business,3218,1,2,1,1,3,4,4,4,4,4,4,4,4,4,37,44.0,satisfied +25561,129311,Female,disloyal Customer,27,Business travel,Business,2475,3,3,3,1,1,3,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +25562,6166,Male,Loyal Customer,30,Business travel,Business,501,1,0,0,1,2,0,2,2,1,3,1,2,2,2,0,0.0,neutral or dissatisfied +25563,21151,Female,Loyal Customer,32,Business travel,Eco Plus,227,4,4,4,4,4,4,4,4,1,3,4,5,3,4,0,0.0,satisfied +25564,61968,Male,disloyal Customer,22,Business travel,Business,2400,5,0,5,1,2,5,2,2,3,2,4,4,4,2,23,11.0,satisfied +25565,48268,Female,disloyal Customer,45,Business travel,Eco Plus,414,3,3,3,2,1,3,1,1,4,5,5,4,5,1,0,0.0,satisfied +25566,92115,Female,Loyal Customer,61,Personal Travel,Eco,1532,1,5,2,5,3,3,4,5,5,2,5,5,5,3,0,3.0,neutral or dissatisfied +25567,35043,Female,Loyal Customer,26,Business travel,Business,1056,3,3,2,3,4,4,4,4,3,3,5,4,5,4,8,12.0,satisfied +25568,15886,Male,Loyal Customer,70,Personal Travel,Eco,332,4,4,4,3,1,4,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +25569,43623,Male,Loyal Customer,31,Personal Travel,Eco,252,2,4,2,3,2,2,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +25570,84569,Male,Loyal Customer,69,Personal Travel,Eco,2556,1,1,0,1,4,0,4,4,2,3,1,1,2,4,1,0.0,neutral or dissatisfied +25571,83263,Female,Loyal Customer,25,Business travel,Business,1979,2,4,2,4,2,2,2,2,4,4,1,4,3,2,86,63.0,neutral or dissatisfied +25572,81510,Female,Loyal Customer,53,Personal Travel,Eco Plus,528,3,3,3,3,1,4,3,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +25573,60186,Female,Loyal Customer,41,Business travel,Business,1515,3,3,3,3,5,4,4,5,5,5,5,5,5,4,14,16.0,satisfied +25574,84402,Male,Loyal Customer,56,Business travel,Eco,206,2,4,4,4,2,2,2,2,2,4,3,2,1,2,4,0.0,satisfied +25575,31372,Male,disloyal Customer,41,Business travel,Eco,577,5,3,5,3,3,5,5,3,2,5,4,3,5,3,9,21.0,satisfied +25576,96701,Male,disloyal Customer,30,Business travel,Business,696,1,1,1,2,4,1,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +25577,45652,Female,Loyal Customer,58,Personal Travel,Eco,113,3,1,3,3,2,3,3,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +25578,74678,Female,Loyal Customer,34,Personal Travel,Eco,1205,2,3,2,3,3,2,3,3,3,5,4,1,3,3,0,0.0,neutral or dissatisfied +25579,26157,Female,disloyal Customer,61,Business travel,Eco,270,5,0,5,4,3,5,3,3,2,4,3,5,1,3,43,74.0,satisfied +25580,51999,Male,Loyal Customer,26,Business travel,Eco,1119,5,4,4,4,5,5,3,5,2,2,2,5,4,5,0,0.0,satisfied +25581,1410,Female,Loyal Customer,38,Personal Travel,Eco Plus,482,3,4,3,3,1,3,1,1,1,5,2,4,1,1,33,27.0,neutral or dissatisfied +25582,40577,Male,Loyal Customer,49,Business travel,Eco,411,1,4,4,4,1,1,1,1,4,1,3,1,2,1,5,0.0,neutral or dissatisfied +25583,28486,Female,disloyal Customer,19,Business travel,Eco,1422,5,5,5,1,5,5,5,5,3,1,5,4,2,5,0,0.0,satisfied +25584,14067,Female,Loyal Customer,30,Business travel,Business,3022,1,4,4,4,1,1,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +25585,126340,Female,Loyal Customer,40,Personal Travel,Eco,507,2,5,2,5,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +25586,91931,Male,Loyal Customer,50,Business travel,Business,2586,4,5,4,4,1,4,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +25587,2213,Female,Loyal Customer,35,Personal Travel,Business,859,1,5,1,4,2,4,5,4,4,1,4,5,4,5,0,11.0,neutral or dissatisfied +25588,25084,Male,disloyal Customer,30,Business travel,Eco,549,2,5,2,2,5,2,5,5,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +25589,40706,Female,Loyal Customer,55,Business travel,Eco,558,5,1,2,2,3,1,2,5,5,5,5,3,5,3,28,21.0,satisfied +25590,59363,Male,Loyal Customer,49,Business travel,Business,2338,3,3,3,3,5,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +25591,25704,Male,Loyal Customer,27,Business travel,Business,528,2,2,2,2,5,5,5,5,3,4,1,1,5,5,0,0.0,satisfied +25592,8860,Female,Loyal Customer,44,Business travel,Business,1690,5,5,5,5,4,4,5,5,5,4,5,4,5,3,28,28.0,satisfied +25593,56263,Female,disloyal Customer,33,Business travel,Eco,404,4,1,4,3,3,4,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +25594,63039,Male,Loyal Customer,59,Personal Travel,Eco,862,3,4,3,3,5,3,5,5,5,3,5,5,4,5,13,0.0,neutral or dissatisfied +25595,121618,Female,Loyal Customer,65,Personal Travel,Eco,936,2,4,2,2,3,4,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +25596,83969,Male,Loyal Customer,54,Business travel,Business,321,3,4,4,4,2,2,2,3,3,3,3,2,3,4,2,0.0,neutral or dissatisfied +25597,109316,Male,Loyal Customer,51,Business travel,Business,1200,4,4,4,4,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +25598,78878,Female,Loyal Customer,30,Business travel,Eco,223,4,1,1,1,4,3,4,4,1,3,4,1,4,4,8,7.0,neutral or dissatisfied +25599,95259,Male,Loyal Customer,20,Personal Travel,Eco,319,1,3,1,3,3,1,3,3,2,3,3,3,3,3,5,0.0,neutral or dissatisfied +25600,67381,Male,Loyal Customer,60,Business travel,Business,1902,2,2,2,2,2,5,5,4,4,4,4,5,4,5,52,49.0,satisfied +25601,24731,Male,Loyal Customer,7,Personal Travel,Eco Plus,406,1,5,1,2,3,1,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +25602,8478,Female,Loyal Customer,45,Business travel,Business,2084,5,5,5,5,4,4,5,4,4,4,4,5,4,2,19,22.0,satisfied +25603,23973,Male,Loyal Customer,46,Business travel,Eco,596,2,3,3,3,2,2,2,2,1,2,3,2,3,2,138,115.0,neutral or dissatisfied +25604,16761,Male,Loyal Customer,67,Business travel,Business,642,3,5,4,5,3,3,3,2,3,2,2,3,3,3,146,154.0,neutral or dissatisfied +25605,8968,Female,Loyal Customer,58,Business travel,Business,3274,5,5,5,5,5,4,5,4,4,4,4,4,4,5,37,44.0,satisfied +25606,69248,Male,Loyal Customer,51,Business travel,Business,2573,5,5,5,5,2,5,5,4,4,4,4,3,4,4,24,3.0,satisfied +25607,90401,Male,Loyal Customer,59,Personal Travel,Business,271,1,0,1,3,5,4,4,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +25608,12966,Male,Loyal Customer,53,Personal Travel,Eco Plus,359,2,3,2,4,5,2,2,5,3,2,3,4,4,5,23,27.0,neutral or dissatisfied +25609,80570,Male,Loyal Customer,29,Business travel,Business,1747,3,5,5,5,3,3,3,3,1,2,3,3,4,3,0,0.0,neutral or dissatisfied +25610,126236,Male,Loyal Customer,58,Business travel,Eco,231,4,5,5,5,4,4,4,4,1,1,3,5,4,4,0,0.0,satisfied +25611,38245,Male,Loyal Customer,29,Business travel,Eco,1180,5,1,1,1,5,5,5,5,3,3,3,2,2,5,40,15.0,satisfied +25612,117372,Female,disloyal Customer,72,Business travel,Business,393,3,3,3,4,4,3,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +25613,29942,Male,disloyal Customer,25,Business travel,Eco,261,3,0,3,1,2,3,5,2,3,4,1,2,2,2,0,0.0,neutral or dissatisfied +25614,26513,Male,Loyal Customer,64,Business travel,Business,3308,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +25615,103697,Male,Loyal Customer,52,Business travel,Business,3644,0,1,1,4,3,4,1,3,3,3,3,2,3,2,0,0.0,satisfied +25616,73528,Male,Loyal Customer,42,Business travel,Business,1887,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +25617,106246,Male,Loyal Customer,47,Business travel,Business,3003,4,4,4,4,5,4,4,4,4,4,4,5,4,3,3,0.0,satisfied +25618,75996,Female,disloyal Customer,34,Business travel,Business,297,1,1,1,1,2,1,2,2,3,2,5,4,4,2,13,3.0,neutral or dissatisfied +25619,87889,Female,Loyal Customer,53,Business travel,Business,3105,2,2,2,2,2,4,4,3,3,3,3,5,3,5,8,15.0,satisfied +25620,10722,Male,Loyal Customer,33,Business travel,Business,312,1,2,2,2,1,1,1,1,2,4,3,2,3,1,11,52.0,neutral or dissatisfied +25621,21884,Male,Loyal Customer,41,Business travel,Business,3340,1,1,1,1,5,3,5,4,4,4,4,2,4,5,0,0.0,satisfied +25622,8146,Male,Loyal Customer,58,Business travel,Eco,530,1,2,2,2,1,1,1,1,2,3,4,3,4,1,84,78.0,neutral or dissatisfied +25623,40911,Female,Loyal Customer,35,Personal Travel,Eco,584,2,5,2,3,3,2,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +25624,12285,Male,Loyal Customer,36,Business travel,Business,127,0,5,0,4,3,1,3,1,1,1,1,1,1,1,0,0.0,satisfied +25625,53851,Female,Loyal Customer,51,Business travel,Business,140,4,1,1,1,4,4,3,1,1,1,4,4,1,1,46,40.0,neutral or dissatisfied +25626,106442,Male,Loyal Customer,12,Business travel,Business,2012,1,1,1,1,1,2,1,1,2,5,4,3,4,1,0,0.0,neutral or dissatisfied +25627,72008,Male,Loyal Customer,16,Business travel,Eco Plus,1437,5,5,5,5,5,5,3,5,5,2,1,5,4,5,7,0.0,satisfied +25628,77970,Female,Loyal Customer,31,Business travel,Eco,214,3,4,5,4,3,3,3,3,1,3,2,1,3,3,8,13.0,neutral or dissatisfied +25629,68074,Female,Loyal Customer,39,Business travel,Business,2251,3,1,1,1,4,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +25630,47097,Female,Loyal Customer,33,Personal Travel,Eco,602,2,3,2,3,4,2,4,4,4,4,4,4,4,4,1,0.0,neutral or dissatisfied +25631,53040,Female,Loyal Customer,42,Business travel,Eco,790,5,2,2,2,5,2,3,5,5,5,5,3,5,1,37,73.0,satisfied +25632,41634,Male,Loyal Customer,31,Business travel,Eco Plus,374,1,5,2,2,1,1,1,1,4,3,4,1,4,1,109,109.0,neutral or dissatisfied +25633,116820,Male,Loyal Customer,63,Business travel,Business,338,4,4,2,4,5,4,4,5,5,5,5,5,5,3,0,20.0,satisfied +25634,89532,Male,Loyal Customer,28,Business travel,Business,3413,3,3,3,3,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +25635,96109,Male,Loyal Customer,65,Personal Travel,Eco,795,3,4,3,3,3,3,3,3,3,3,4,5,4,3,0,13.0,neutral or dissatisfied +25636,49632,Male,Loyal Customer,54,Business travel,Business,3764,5,5,5,5,1,5,4,4,4,4,5,4,4,1,0,0.0,satisfied +25637,55142,Male,Loyal Customer,10,Personal Travel,Eco,1346,2,5,2,1,5,2,5,5,3,4,5,3,4,5,4,0.0,neutral or dissatisfied +25638,109648,Male,Loyal Customer,56,Business travel,Business,1738,5,5,5,5,2,4,4,4,4,4,4,3,4,5,23,10.0,satisfied +25639,44716,Female,Loyal Customer,22,Personal Travel,Eco,108,4,3,4,3,5,4,5,5,1,2,2,3,2,5,0,0.0,neutral or dissatisfied +25640,110742,Female,disloyal Customer,47,Business travel,Business,990,5,4,4,4,3,5,3,3,4,5,4,4,5,3,13,10.0,satisfied +25641,38170,Male,Loyal Customer,20,Personal Travel,Eco,1121,3,4,3,4,1,3,5,1,2,2,2,3,4,1,68,53.0,neutral or dissatisfied +25642,44204,Male,Loyal Customer,15,Personal Travel,Eco,157,3,4,0,1,4,0,4,4,5,5,5,4,4,4,55,71.0,neutral or dissatisfied +25643,45218,Female,disloyal Customer,21,Business travel,Eco,1013,4,4,4,4,1,4,1,1,1,4,5,2,4,1,12,64.0,satisfied +25644,55601,Female,disloyal Customer,20,Business travel,Business,404,4,0,4,5,5,4,5,5,3,2,5,5,4,5,0,0.0,satisfied +25645,123630,Female,Loyal Customer,49,Business travel,Business,2265,0,4,0,5,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +25646,64756,Female,Loyal Customer,50,Business travel,Eco,469,2,4,4,4,5,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +25647,91843,Female,disloyal Customer,25,Business travel,Business,1299,5,3,5,1,2,5,2,2,3,2,4,3,5,2,0,0.0,satisfied +25648,2038,Female,Loyal Customer,56,Business travel,Business,1936,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +25649,31240,Female,Loyal Customer,36,Business travel,Eco,472,3,2,2,2,3,4,3,3,1,3,2,2,2,3,2,4.0,satisfied +25650,26309,Female,Loyal Customer,50,Business travel,Business,2139,1,4,4,4,1,3,4,1,1,2,1,1,1,2,2,18.0,neutral or dissatisfied +25651,126348,Female,Loyal Customer,23,Personal Travel,Eco,468,3,2,3,2,5,3,5,5,1,4,2,1,3,5,4,0.0,neutral or dissatisfied +25652,12035,Female,Loyal Customer,36,Business travel,Business,3199,2,2,2,2,2,3,1,5,5,5,5,3,5,4,0,0.0,satisfied +25653,13381,Male,Loyal Customer,32,Personal Travel,Eco Plus,748,1,4,1,1,3,1,3,3,1,5,1,3,4,3,0,0.0,neutral or dissatisfied +25654,45983,Female,Loyal Customer,32,Business travel,Business,1502,2,2,2,2,4,4,4,4,4,1,5,1,5,4,1,0.0,satisfied +25655,15445,Female,Loyal Customer,53,Business travel,Business,2953,2,4,4,4,1,3,3,2,2,2,2,2,2,4,2,2.0,neutral or dissatisfied +25656,118944,Male,Loyal Customer,54,Business travel,Business,3569,1,1,1,1,4,4,4,4,4,5,4,3,4,3,9,0.0,satisfied +25657,97428,Male,Loyal Customer,43,Personal Travel,Eco,587,3,5,3,4,4,3,4,4,3,3,5,3,5,4,25,7.0,neutral or dissatisfied +25658,118987,Female,disloyal Customer,23,Business travel,Eco,479,3,0,3,2,1,3,1,1,4,4,5,3,5,1,0,1.0,neutral or dissatisfied +25659,11365,Female,Loyal Customer,22,Personal Travel,Eco,224,3,3,3,3,5,3,5,5,1,5,4,1,4,5,79,67.0,neutral or dissatisfied +25660,114620,Male,Loyal Customer,57,Business travel,Business,3121,2,2,2,2,4,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +25661,87699,Male,Loyal Customer,21,Personal Travel,Eco,606,1,5,1,2,4,1,4,4,4,2,4,5,5,4,9,5.0,neutral or dissatisfied +25662,48429,Male,Loyal Customer,39,Business travel,Eco,845,5,4,1,4,5,5,5,5,1,5,5,5,4,5,0,0.0,satisfied +25663,4475,Female,Loyal Customer,28,Personal Travel,Eco,1005,2,5,1,2,1,1,1,1,3,2,4,5,4,1,53,46.0,neutral or dissatisfied +25664,72186,Male,Loyal Customer,35,Business travel,Business,594,4,5,5,5,3,3,2,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +25665,76828,Male,Loyal Customer,32,Business travel,Eco,1851,1,5,5,5,1,1,1,1,4,5,3,2,3,1,0,0.0,neutral or dissatisfied +25666,124772,Male,Loyal Customer,44,Business travel,Business,3557,3,3,3,3,2,4,5,4,4,4,4,3,4,3,0,21.0,satisfied +25667,78816,Male,Loyal Customer,17,Personal Travel,Eco,528,1,5,1,3,3,1,3,3,3,4,5,3,4,3,0,3.0,neutral or dissatisfied +25668,119921,Male,Loyal Customer,29,Business travel,Business,2798,5,5,5,5,4,5,4,4,3,3,4,3,4,4,0,3.0,satisfied +25669,104331,Female,Loyal Customer,42,Business travel,Eco,452,3,1,1,1,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +25670,60901,Male,Loyal Customer,68,Personal Travel,Business,589,3,3,3,5,3,1,5,3,3,3,3,1,3,4,37,62.0,neutral or dissatisfied +25671,109658,Male,Loyal Customer,41,Business travel,Business,3457,4,5,5,5,2,3,4,4,4,4,4,3,4,3,20,21.0,neutral or dissatisfied +25672,112357,Male,Loyal Customer,28,Business travel,Business,862,5,5,5,5,4,4,4,4,4,4,5,3,5,4,7,0.0,satisfied +25673,116343,Male,Loyal Customer,41,Personal Travel,Eco,325,2,5,2,1,4,2,4,4,4,4,2,4,3,4,0,0.0,neutral or dissatisfied +25674,10117,Female,Loyal Customer,46,Business travel,Eco,984,2,4,4,4,4,3,3,2,2,2,2,3,2,3,58,62.0,neutral or dissatisfied +25675,38722,Male,Loyal Customer,43,Business travel,Business,3376,2,2,2,2,2,4,4,4,4,4,4,5,4,4,0,9.0,satisfied +25676,64823,Male,Loyal Customer,47,Business travel,Business,190,0,4,0,3,5,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +25677,52893,Female,Loyal Customer,44,Personal Travel,Eco,1024,1,4,1,1,5,5,4,4,4,1,4,4,4,5,14,6.0,neutral or dissatisfied +25678,23904,Female,Loyal Customer,58,Business travel,Eco,589,3,3,3,3,1,5,1,4,4,3,4,3,4,1,0,4.0,satisfied +25679,41517,Male,Loyal Customer,48,Business travel,Eco,1464,2,5,5,5,2,2,2,2,5,4,5,5,2,2,50,66.0,satisfied +25680,107926,Female,disloyal Customer,26,Business travel,Business,611,2,5,2,3,1,2,1,1,5,2,4,5,5,1,42,40.0,neutral or dissatisfied +25681,22174,Female,Loyal Customer,26,Business travel,Business,533,3,3,4,3,3,2,3,3,1,1,2,1,4,3,42,43.0,satisfied +25682,116028,Male,Loyal Customer,52,Personal Travel,Eco,308,2,4,2,3,1,2,1,1,3,2,3,3,4,1,54,40.0,neutral or dissatisfied +25683,63251,Female,Loyal Customer,34,Business travel,Business,2208,3,3,3,3,5,4,5,5,5,5,5,3,5,5,5,4.0,satisfied +25684,43927,Male,Loyal Customer,34,Personal Travel,Eco,174,1,4,1,3,1,1,1,1,3,3,1,2,4,1,0,0.0,neutral or dissatisfied +25685,78133,Male,Loyal Customer,47,Business travel,Business,153,3,2,2,2,4,3,4,2,2,2,3,4,2,4,0,15.0,neutral or dissatisfied +25686,3393,Male,disloyal Customer,26,Business travel,Eco,296,2,2,2,3,3,2,3,3,3,1,4,3,3,3,2,0.0,neutral or dissatisfied +25687,66248,Female,Loyal Customer,9,Personal Travel,Eco,550,2,1,2,4,5,2,5,5,2,3,2,2,3,5,0,0.0,neutral or dissatisfied +25688,79880,Male,Loyal Customer,55,Business travel,Business,1911,2,3,2,2,2,4,4,3,3,3,3,3,3,4,0,4.0,satisfied +25689,80382,Male,Loyal Customer,40,Business travel,Eco,368,3,3,3,3,3,3,3,3,3,2,4,4,3,3,22,11.0,neutral or dissatisfied +25690,97978,Female,Loyal Customer,59,Personal Travel,Eco,612,2,5,2,3,2,5,2,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +25691,50484,Female,disloyal Customer,28,Business travel,Eco,156,4,3,4,1,3,4,3,3,4,1,3,2,1,3,0,2.0,satisfied +25692,71121,Female,Loyal Customer,31,Business travel,Business,1739,4,5,4,4,3,3,3,3,4,3,3,3,4,3,0,6.0,satisfied +25693,100433,Male,Loyal Customer,22,Personal Travel,Eco,1620,2,5,2,4,3,2,3,3,3,2,3,4,5,3,6,41.0,neutral or dissatisfied +25694,113555,Female,Loyal Customer,36,Business travel,Business,3832,0,4,0,3,5,4,5,2,2,5,5,5,2,3,0,0.0,satisfied +25695,56598,Male,Loyal Customer,34,Business travel,Eco,937,2,4,4,4,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +25696,25058,Male,Loyal Customer,27,Business travel,Eco,594,3,3,3,3,3,3,3,3,3,2,3,3,4,3,35,36.0,neutral or dissatisfied +25697,85719,Male,disloyal Customer,24,Business travel,Business,620,5,4,5,1,4,5,1,4,4,4,5,5,5,4,0,0.0,satisfied +25698,57899,Male,Loyal Customer,30,Business travel,Business,305,0,0,0,1,5,5,5,5,3,5,5,5,5,5,17,17.0,satisfied +25699,121190,Male,Loyal Customer,35,Personal Travel,Eco,2521,2,1,2,2,2,4,4,3,3,1,3,4,2,4,32,27.0,neutral or dissatisfied +25700,70765,Male,Loyal Customer,35,Personal Travel,Business,328,1,1,1,4,5,5,5,3,3,1,3,5,3,4,17,17.0,neutral or dissatisfied +25701,67234,Male,Loyal Customer,27,Personal Travel,Eco,985,2,4,2,4,2,4,4,5,3,4,4,4,5,4,135,135.0,neutral or dissatisfied +25702,84677,Female,disloyal Customer,25,Business travel,Eco,1432,4,4,4,3,3,4,3,3,3,1,2,4,3,3,19,31.0,neutral or dissatisfied +25703,38036,Female,Loyal Customer,36,Business travel,Business,1607,2,2,2,2,3,2,2,5,5,5,5,5,5,5,5,0.0,satisfied +25704,21497,Female,Loyal Customer,33,Personal Travel,Eco,331,1,4,1,1,2,1,2,2,3,5,5,2,3,2,21,21.0,neutral or dissatisfied +25705,29893,Male,Loyal Customer,46,Business travel,Business,2562,1,1,1,1,2,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +25706,111687,Male,Loyal Customer,53,Business travel,Business,541,2,2,2,2,4,5,4,4,4,4,4,5,4,4,24,20.0,satisfied +25707,8836,Male,Loyal Customer,45,Business travel,Business,3783,2,2,2,2,4,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +25708,90599,Male,Loyal Customer,43,Business travel,Business,404,4,4,4,4,3,4,5,5,5,5,5,5,5,4,3,0.0,satisfied +25709,76330,Female,Loyal Customer,68,Personal Travel,Eco,2182,1,4,1,4,5,3,3,4,4,1,4,2,4,2,15,0.0,neutral or dissatisfied +25710,17703,Male,Loyal Customer,34,Business travel,Business,3636,3,3,4,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +25711,67225,Male,Loyal Customer,28,Personal Travel,Eco,929,3,4,3,4,3,3,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +25712,55794,Female,Loyal Customer,53,Business travel,Eco,900,1,2,2,2,1,1,1,1,1,4,3,1,3,1,1,7.0,neutral or dissatisfied +25713,12623,Male,Loyal Customer,29,Personal Travel,Eco Plus,802,1,5,1,2,4,1,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +25714,108774,Female,Loyal Customer,48,Business travel,Business,1790,2,2,2,2,2,4,4,4,4,5,4,5,4,5,11,4.0,satisfied +25715,91673,Female,Loyal Customer,55,Business travel,Business,954,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,2.0,satisfied +25716,90594,Male,disloyal Customer,25,Business travel,Business,404,2,4,2,2,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +25717,19373,Female,Loyal Customer,33,Personal Travel,Eco,476,1,3,1,5,4,1,4,4,2,2,4,3,4,4,91,82.0,neutral or dissatisfied +25718,68449,Female,Loyal Customer,44,Business travel,Business,2241,2,2,2,2,2,4,5,5,5,5,5,5,5,5,2,0.0,satisfied +25719,125431,Male,Loyal Customer,15,Personal Travel,Eco,735,2,5,2,2,2,2,2,2,5,3,1,4,3,2,0,8.0,neutral or dissatisfied +25720,117199,Male,Loyal Customer,16,Personal Travel,Eco,370,1,5,1,4,5,1,5,5,4,3,4,5,4,5,10,0.0,neutral or dissatisfied +25721,74981,Female,Loyal Customer,45,Personal Travel,Eco,2475,2,5,2,3,1,4,2,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +25722,36232,Female,Loyal Customer,48,Personal Travel,Eco,280,2,3,2,1,4,2,4,3,3,2,3,4,3,3,0,5.0,neutral or dissatisfied +25723,67213,Male,Loyal Customer,8,Personal Travel,Eco,985,3,5,3,5,5,3,1,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +25724,78618,Male,Loyal Customer,43,Business travel,Business,1426,1,1,2,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +25725,60337,Male,Loyal Customer,29,Business travel,Business,3391,1,4,1,1,3,2,3,3,4,5,4,3,5,3,0,0.0,satisfied +25726,109961,Female,Loyal Customer,45,Personal Travel,Eco,1073,5,5,5,4,3,4,4,2,2,5,2,5,2,4,1,0.0,satisfied +25727,83234,Female,Loyal Customer,35,Business travel,Business,1956,1,1,1,1,2,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +25728,73699,Male,Loyal Customer,62,Business travel,Eco,204,4,2,2,2,4,4,4,4,3,1,3,4,4,4,8,0.0,neutral or dissatisfied +25729,21983,Female,Loyal Customer,44,Personal Travel,Eco,551,1,2,1,3,3,4,4,3,3,1,3,2,3,2,30,53.0,neutral or dissatisfied +25730,37968,Female,Loyal Customer,52,Business travel,Business,2067,2,1,1,1,3,3,3,2,2,2,2,1,2,1,19,17.0,neutral or dissatisfied +25731,75189,Female,Loyal Customer,44,Business travel,Business,1723,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +25732,43551,Female,Loyal Customer,52,Business travel,Eco,438,4,3,3,3,2,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +25733,26865,Male,disloyal Customer,23,Business travel,Eco,2329,3,3,3,1,1,3,4,1,4,1,4,1,2,1,0,16.0,neutral or dissatisfied +25734,36491,Male,Loyal Customer,34,Business travel,Business,2681,3,1,1,1,1,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +25735,101986,Female,Loyal Customer,10,Personal Travel,Eco,628,3,3,3,4,3,3,2,3,4,1,3,4,3,3,10,1.0,neutral or dissatisfied +25736,80186,Male,Loyal Customer,19,Personal Travel,Eco,2475,2,5,2,4,2,5,5,2,5,3,3,5,2,5,139,151.0,neutral or dissatisfied +25737,61089,Female,Loyal Customer,65,Personal Travel,Eco,1607,2,4,3,3,2,5,4,5,5,3,5,4,5,5,37,18.0,neutral or dissatisfied +25738,44649,Male,disloyal Customer,24,Business travel,Eco,268,3,5,3,4,3,3,4,3,5,2,2,2,4,3,0,1.0,neutral or dissatisfied +25739,15942,Male,Loyal Customer,26,Personal Travel,Eco,738,4,5,4,1,1,4,1,1,4,4,5,5,4,1,0,5.0,neutral or dissatisfied +25740,129415,Male,disloyal Customer,25,Business travel,Business,414,0,2,0,1,3,0,3,3,4,2,5,5,5,3,0,0.0,satisfied +25741,7009,Female,Loyal Customer,77,Business travel,Business,2342,0,0,0,4,5,2,1,1,1,1,1,3,1,2,2,0.0,satisfied +25742,67362,Male,Loyal Customer,46,Business travel,Business,592,2,4,4,4,1,3,4,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +25743,25563,Female,Loyal Customer,49,Business travel,Business,1649,1,1,1,1,2,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +25744,53462,Male,Loyal Customer,32,Business travel,Eco,2288,2,4,4,4,2,2,2,2,2,3,1,4,2,2,0,0.0,neutral or dissatisfied +25745,25753,Female,disloyal Customer,24,Business travel,Eco,356,3,0,3,3,3,3,3,3,1,2,2,4,2,3,0,0.0,neutral or dissatisfied +25746,50908,Male,Loyal Customer,32,Personal Travel,Eco,110,1,5,1,5,3,1,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +25747,69858,Male,Loyal Customer,26,Personal Travel,Eco,1055,2,4,3,1,3,3,3,3,3,3,5,3,5,3,0,0.0,neutral or dissatisfied +25748,22014,Female,Loyal Customer,55,Personal Travel,Eco,503,2,5,2,3,2,4,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +25749,62871,Female,Loyal Customer,44,Personal Travel,Eco,2446,2,4,1,4,2,4,4,2,2,1,1,4,2,4,6,0.0,neutral or dissatisfied +25750,56660,Female,disloyal Customer,36,Business travel,Eco,537,3,2,3,3,3,3,3,3,2,2,4,3,3,3,29,18.0,neutral or dissatisfied +25751,7997,Female,Loyal Customer,35,Business travel,Business,530,3,5,2,2,1,4,3,3,3,4,3,3,3,1,0,1.0,neutral or dissatisfied +25752,11582,Female,Loyal Customer,46,Business travel,Business,2485,2,2,2,2,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +25753,65457,Male,disloyal Customer,25,Business travel,Eco,1067,3,3,3,3,3,3,3,3,3,2,5,3,5,3,6,0.0,neutral or dissatisfied +25754,49249,Male,Loyal Customer,25,Business travel,Eco,158,4,5,5,5,4,4,1,4,2,2,3,3,3,4,59,65.0,neutral or dissatisfied +25755,93856,Male,disloyal Customer,25,Business travel,Business,590,4,0,4,3,4,3,3,4,2,4,5,3,4,3,184,173.0,satisfied +25756,95541,Male,Loyal Customer,36,Personal Travel,Eco Plus,458,1,5,1,1,2,1,5,2,3,5,5,5,4,2,2,5.0,neutral or dissatisfied +25757,11915,Male,Loyal Customer,23,Personal Travel,Eco,501,4,4,5,3,5,5,4,5,5,4,5,3,5,5,11,0.0,neutral or dissatisfied +25758,109070,Female,disloyal Customer,34,Business travel,Eco,781,3,3,3,1,1,3,1,1,4,4,5,1,5,1,0,0.0,neutral or dissatisfied +25759,28614,Female,Loyal Customer,54,Business travel,Business,2378,2,2,2,2,1,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +25760,17467,Male,Loyal Customer,53,Business travel,Business,3530,3,3,2,3,2,5,4,5,5,5,5,3,5,3,0,7.0,satisfied +25761,43824,Male,disloyal Customer,38,Business travel,Eco,153,2,0,1,4,4,1,4,4,5,2,5,2,1,4,12,24.0,neutral or dissatisfied +25762,67356,Male,Loyal Customer,46,Business travel,Business,1929,3,3,3,3,3,4,4,3,3,3,3,5,3,3,26,26.0,satisfied +25763,80029,Female,Loyal Customer,58,Personal Travel,Eco,950,3,0,3,4,3,5,5,5,5,3,5,4,5,3,2,0.0,neutral or dissatisfied +25764,109621,Male,Loyal Customer,41,Business travel,Business,829,2,2,2,2,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +25765,129295,Female,Loyal Customer,19,Personal Travel,Eco,550,2,3,2,4,1,2,1,1,4,4,4,1,3,1,35,34.0,neutral or dissatisfied +25766,19876,Female,Loyal Customer,23,Personal Travel,Business,315,1,4,1,1,5,1,5,5,5,5,2,4,2,5,9,0.0,neutral or dissatisfied +25767,125644,Female,Loyal Customer,25,Business travel,Business,2391,2,2,2,2,5,4,5,5,3,2,5,5,4,5,0,0.0,satisfied +25768,119702,Female,Loyal Customer,23,Business travel,Business,1430,3,5,5,5,3,3,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +25769,90745,Female,Loyal Customer,32,Business travel,Business,1613,1,1,4,1,3,4,3,3,5,3,4,4,5,3,0,0.0,satisfied +25770,105863,Male,disloyal Customer,22,Business travel,Eco,842,3,3,3,4,4,3,2,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +25771,101716,Male,Loyal Customer,26,Business travel,Business,986,2,3,4,4,2,2,2,2,4,2,3,4,4,2,17,30.0,neutral or dissatisfied +25772,117900,Female,disloyal Customer,44,Business travel,Business,255,3,3,3,1,5,3,4,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +25773,4041,Male,Loyal Customer,54,Business travel,Business,479,3,5,4,4,4,4,3,3,3,3,3,4,3,1,9,17.0,neutral or dissatisfied +25774,25012,Female,disloyal Customer,23,Business travel,Eco,907,4,4,4,3,3,4,3,3,1,1,4,2,3,3,0,2.0,neutral or dissatisfied +25775,70578,Male,Loyal Customer,70,Personal Travel,Eco,1258,2,1,2,2,1,2,1,1,2,1,1,2,2,1,0,0.0,neutral or dissatisfied +25776,93641,Male,Loyal Customer,51,Business travel,Business,2799,2,2,2,2,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +25777,53408,Female,disloyal Customer,23,Business travel,Eco,1109,2,2,2,1,2,1,4,3,2,5,4,4,4,4,71,73.0,neutral or dissatisfied +25778,129661,Male,Loyal Customer,45,Business travel,Eco,447,2,4,4,4,2,2,2,2,2,3,3,2,3,2,31,35.0,neutral or dissatisfied +25779,340,Male,Loyal Customer,16,Personal Travel,Eco,853,3,5,3,1,2,3,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +25780,115107,Female,disloyal Customer,23,Business travel,Eco,337,2,2,2,3,4,2,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +25781,111900,Female,Loyal Customer,7,Personal Travel,Eco,628,4,3,3,1,2,3,2,2,5,4,2,2,2,2,0,0.0,neutral or dissatisfied +25782,109010,Female,Loyal Customer,17,Business travel,Business,1681,2,2,2,2,4,4,4,4,3,3,4,5,4,4,37,46.0,satisfied +25783,23168,Female,Loyal Customer,52,Personal Travel,Eco,646,1,5,1,3,4,3,1,3,3,1,4,1,3,1,0,0.0,neutral or dissatisfied +25784,98347,Female,disloyal Customer,20,Business travel,Eco,1046,3,2,2,3,5,2,5,5,2,2,2,2,2,5,0,0.0,neutral or dissatisfied +25785,101385,Male,Loyal Customer,55,Business travel,Business,486,5,5,5,5,5,4,5,4,4,4,4,5,4,5,9,4.0,satisfied +25786,97234,Male,Loyal Customer,47,Business travel,Business,2318,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +25787,127772,Male,Loyal Customer,64,Personal Travel,Eco Plus,255,2,5,2,4,5,2,3,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +25788,101675,Male,Loyal Customer,50,Personal Travel,Eco,2106,2,2,2,4,5,2,5,5,1,1,3,1,3,5,9,0.0,neutral or dissatisfied +25789,19390,Female,Loyal Customer,20,Personal Travel,Eco,844,3,4,3,5,3,3,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +25790,123380,Male,Loyal Customer,54,Business travel,Business,644,1,1,1,1,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +25791,43833,Female,Loyal Customer,51,Business travel,Business,3664,4,4,4,4,3,1,2,5,5,5,5,2,5,1,0,10.0,satisfied +25792,3573,Male,Loyal Customer,49,Personal Travel,Eco,227,2,2,2,4,5,2,5,5,1,1,3,3,3,5,0,0.0,neutral or dissatisfied +25793,106836,Female,disloyal Customer,50,Business travel,Business,1733,2,3,3,1,3,2,3,3,3,5,4,3,4,3,80,71.0,neutral or dissatisfied +25794,864,Female,disloyal Customer,39,Business travel,Business,312,3,3,3,3,3,3,3,3,3,4,4,3,4,3,9,3.0,neutral or dissatisfied +25795,14436,Female,disloyal Customer,32,Business travel,Eco,674,2,3,3,3,1,3,1,1,3,3,1,2,4,1,0,0.0,neutral or dissatisfied +25796,119406,Female,Loyal Customer,19,Business travel,Business,1566,1,1,1,1,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +25797,39367,Male,Loyal Customer,15,Personal Travel,Eco,896,4,4,4,4,5,4,5,5,5,4,5,3,4,5,6,0.0,neutral or dissatisfied +25798,15352,Male,Loyal Customer,45,Personal Travel,Business,306,3,4,3,3,3,5,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +25799,102772,Female,Loyal Customer,22,Business travel,Eco Plus,1618,2,5,5,5,2,2,2,2,1,2,3,3,4,2,25,18.0,neutral or dissatisfied +25800,81791,Male,Loyal Customer,30,Business travel,Eco,1310,2,4,4,4,2,2,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +25801,110767,Female,Loyal Customer,24,Business travel,Business,1660,2,2,2,2,2,2,2,2,1,2,3,1,4,2,1,7.0,neutral or dissatisfied +25802,84126,Female,Loyal Customer,10,Personal Travel,Eco Plus,1900,1,5,1,1,5,1,2,5,3,4,4,3,4,5,0,11.0,neutral or dissatisfied +25803,29192,Female,Loyal Customer,59,Personal Travel,Eco Plus,605,2,3,2,1,5,3,4,2,2,2,2,2,2,5,0,0.0,neutral or dissatisfied +25804,82303,Male,disloyal Customer,60,Business travel,Eco,986,1,1,1,3,1,1,1,1,1,1,3,4,3,1,0,0.0,neutral or dissatisfied +25805,51577,Female,Loyal Customer,49,Business travel,Business,2854,5,5,5,5,1,4,5,5,5,5,5,5,5,1,0,0.0,satisfied +25806,858,Male,Loyal Customer,40,Business travel,Business,2845,1,5,3,5,4,4,4,3,3,3,1,3,3,3,3,8.0,neutral or dissatisfied +25807,128608,Female,disloyal Customer,45,Business travel,Business,679,4,5,5,5,4,4,4,4,4,4,4,3,4,4,1,0.0,satisfied +25808,57900,Female,Loyal Customer,52,Business travel,Eco,305,4,2,2,2,4,3,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +25809,105209,Male,Loyal Customer,43,Business travel,Business,2539,1,1,3,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +25810,109510,Male,Loyal Customer,29,Business travel,Business,2162,2,4,4,4,2,2,2,2,2,1,3,3,2,2,18,8.0,neutral or dissatisfied +25811,36421,Female,disloyal Customer,21,Business travel,Eco,369,3,5,3,1,4,3,4,4,2,2,1,3,1,4,0,0.0,neutral or dissatisfied +25812,55268,Female,Loyal Customer,44,Business travel,Business,507,5,5,5,5,4,2,4,4,4,4,4,4,4,5,2,0.0,satisfied +25813,91072,Male,Loyal Customer,34,Personal Travel,Eco,646,2,4,2,3,2,2,2,2,2,5,2,1,3,2,3,0.0,neutral or dissatisfied +25814,85,Male,Loyal Customer,53,Personal Travel,Eco,173,3,1,3,1,2,3,2,2,3,1,1,4,1,2,0,0.0,neutral or dissatisfied +25815,16591,Female,Loyal Customer,39,Personal Travel,Eco Plus,872,4,3,4,3,2,4,2,2,2,2,2,2,3,2,0,0.0,neutral or dissatisfied +25816,56510,Male,Loyal Customer,42,Business travel,Business,1664,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +25817,73213,Female,Loyal Customer,28,Personal Travel,Eco,1258,1,4,1,3,4,1,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +25818,55091,Female,Loyal Customer,51,Business travel,Business,135,1,1,1,1,2,4,2,4,4,4,5,1,4,1,0,0.0,satisfied +25819,12603,Female,Loyal Customer,65,Personal Travel,Eco,542,2,4,3,3,5,5,5,1,1,3,1,4,1,5,0,1.0,neutral or dissatisfied +25820,87789,Female,disloyal Customer,38,Business travel,Eco,214,2,4,2,4,2,2,2,2,3,2,4,3,4,2,4,6.0,neutral or dissatisfied +25821,33995,Female,Loyal Customer,34,Business travel,Business,1598,5,5,3,5,5,5,3,3,3,3,3,4,3,5,0,0.0,satisfied +25822,91082,Male,Loyal Customer,50,Personal Travel,Eco,581,0,3,0,4,4,0,4,4,4,1,3,3,4,4,0,5.0,satisfied +25823,118936,Female,disloyal Customer,42,Business travel,Eco,1618,1,1,1,4,2,1,2,2,3,1,4,3,4,2,9,3.0,neutral or dissatisfied +25824,54259,Female,Loyal Customer,40,Personal Travel,Eco,1222,2,2,2,3,1,2,1,1,3,1,4,4,4,1,56,28.0,neutral or dissatisfied +25825,41359,Female,disloyal Customer,26,Business travel,Eco,563,0,0,0,3,3,0,3,3,5,2,4,4,3,3,2,0.0,satisfied +25826,117063,Female,disloyal Customer,25,Business travel,Business,304,4,0,4,2,5,4,5,5,3,5,4,5,4,5,10,0.0,neutral or dissatisfied +25827,46532,Female,Loyal Customer,47,Business travel,Eco,125,3,1,1,1,1,3,1,3,3,3,3,3,3,5,26,35.0,satisfied +25828,104601,Female,Loyal Customer,14,Personal Travel,Eco,369,4,4,4,4,2,4,2,2,1,2,4,1,4,2,4,7.0,neutral or dissatisfied +25829,6756,Female,disloyal Customer,43,Business travel,Business,122,4,4,4,3,2,4,2,2,3,5,4,4,4,2,0,0.0,satisfied +25830,115434,Male,Loyal Customer,52,Business travel,Business,1718,2,2,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +25831,1481,Male,Loyal Customer,61,Personal Travel,Business,737,2,4,2,2,3,5,4,4,4,2,4,5,4,4,44,53.0,neutral or dissatisfied +25832,32344,Female,Loyal Customer,40,Business travel,Business,163,5,5,5,5,3,5,4,5,5,5,3,4,5,1,0,0.0,satisfied +25833,101443,Female,disloyal Customer,26,Business travel,Business,345,4,4,4,2,1,4,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +25834,83718,Male,Loyal Customer,18,Personal Travel,Eco Plus,577,3,5,4,2,4,4,4,4,3,3,4,4,4,4,28,51.0,neutral or dissatisfied +25835,64257,Female,Loyal Customer,17,Personal Travel,Eco,1660,1,4,1,4,3,1,4,3,4,3,5,4,5,3,2,6.0,neutral or dissatisfied +25836,17455,Female,Loyal Customer,51,Personal Travel,Eco Plus,351,2,4,2,3,4,4,4,4,4,2,4,5,4,3,4,9.0,neutral or dissatisfied +25837,124886,Female,Loyal Customer,23,Business travel,Business,728,2,2,2,2,3,3,3,3,3,2,5,3,5,3,0,0.0,satisfied +25838,79617,Male,Loyal Customer,55,Business travel,Business,762,2,4,4,4,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +25839,56776,Male,Loyal Customer,39,Personal Travel,Eco Plus,937,1,4,1,3,1,1,1,1,3,3,3,1,1,1,186,163.0,neutral or dissatisfied +25840,87550,Female,Loyal Customer,24,Business travel,Business,743,4,4,4,4,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +25841,115112,Female,disloyal Customer,46,Business travel,Business,390,5,5,5,3,5,5,5,5,5,5,5,4,4,5,6,0.0,satisfied +25842,58608,Female,disloyal Customer,47,Business travel,Eco Plus,334,4,5,5,3,5,4,5,5,3,2,5,3,3,5,12,18.0,satisfied +25843,4515,Female,Loyal Customer,49,Personal Travel,Eco,435,2,5,4,1,4,4,4,1,1,4,1,3,1,4,5,0.0,neutral or dissatisfied +25844,37258,Female,disloyal Customer,21,Business travel,Eco,1010,4,4,4,3,2,4,2,2,1,1,5,4,1,2,32,24.0,satisfied +25845,42661,Female,Loyal Customer,39,Personal Travel,Eco,557,2,4,2,3,2,2,2,2,3,4,5,3,4,2,0,16.0,neutral or dissatisfied +25846,63147,Female,Loyal Customer,60,Business travel,Business,2310,3,3,3,3,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +25847,3502,Male,Loyal Customer,7,Personal Travel,Eco,990,1,4,1,2,3,1,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +25848,125389,Male,Loyal Customer,29,Business travel,Business,1440,5,2,5,5,5,4,5,5,3,2,4,5,4,5,0,0.0,satisfied +25849,89849,Female,Loyal Customer,56,Personal Travel,Business,1310,4,4,4,3,4,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +25850,19363,Female,Loyal Customer,33,Personal Travel,Eco Plus,692,2,4,2,3,2,2,2,2,4,3,5,4,4,2,23,22.0,neutral or dissatisfied +25851,103332,Male,Loyal Customer,45,Personal Travel,Eco,1371,2,5,2,1,2,2,2,2,5,3,5,5,4,2,19,21.0,neutral or dissatisfied +25852,73730,Male,Loyal Customer,52,Personal Travel,Eco,192,3,4,3,3,1,3,1,1,5,2,4,4,5,1,1,0.0,neutral or dissatisfied +25853,31546,Female,Loyal Customer,33,Personal Travel,Eco,862,4,5,4,3,1,4,2,1,4,3,5,5,4,1,0,39.0,neutral or dissatisfied +25854,43331,Male,Loyal Customer,26,Business travel,Business,3134,4,4,4,4,4,4,4,4,3,3,1,5,1,4,0,0.0,satisfied +25855,34353,Male,disloyal Customer,36,Business travel,Eco,427,2,3,2,3,1,2,1,1,1,5,3,2,3,1,0,0.0,neutral or dissatisfied +25856,33104,Female,Loyal Customer,36,Personal Travel,Eco,101,4,3,4,5,5,4,5,5,4,1,2,2,5,5,0,0.0,neutral or dissatisfied +25857,67470,Male,Loyal Customer,50,Personal Travel,Eco,641,1,5,1,1,5,1,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +25858,124086,Female,Loyal Customer,57,Personal Travel,Business,529,1,3,1,3,5,2,5,5,5,1,5,2,5,5,0,0.0,neutral or dissatisfied +25859,106427,Male,Loyal Customer,52,Personal Travel,Eco,551,1,4,1,4,2,1,4,2,1,3,1,1,3,2,17,7.0,neutral or dissatisfied +25860,29441,Male,Loyal Customer,58,Business travel,Eco,421,5,3,1,3,5,5,5,5,2,1,4,2,4,5,0,0.0,satisfied +25861,13721,Female,Loyal Customer,45,Business travel,Business,1559,2,2,2,2,3,2,2,4,4,4,4,2,4,1,0,0.0,satisfied +25862,52732,Female,Loyal Customer,32,Business travel,Business,2306,3,2,1,2,3,3,3,3,1,3,2,1,3,3,0,0.0,neutral or dissatisfied +25863,28255,Female,Loyal Customer,22,Business travel,Business,1542,3,5,3,3,4,4,4,4,3,1,2,4,4,4,0,0.0,satisfied +25864,48520,Male,disloyal Customer,22,Business travel,Eco,916,2,2,2,2,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +25865,29454,Female,Loyal Customer,70,Personal Travel,Eco,421,1,3,1,5,2,5,3,3,3,1,3,1,3,5,7,3.0,neutral or dissatisfied +25866,55283,Female,Loyal Customer,55,Business travel,Business,1608,4,4,4,4,4,4,5,2,2,2,2,5,2,5,13,17.0,satisfied +25867,111836,Male,Loyal Customer,39,Business travel,Business,3085,4,4,4,4,3,5,5,4,4,4,4,5,4,4,6,1.0,satisfied +25868,92691,Female,Loyal Customer,9,Personal Travel,Eco,507,2,5,2,3,1,2,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +25869,17850,Male,Loyal Customer,39,Business travel,Business,2374,2,2,2,2,4,2,4,4,4,4,4,3,4,5,0,0.0,satisfied +25870,39489,Female,Loyal Customer,26,Personal Travel,Eco,867,2,5,2,4,1,2,1,1,5,4,4,4,5,1,7,0.0,neutral or dissatisfied +25871,14812,Male,Loyal Customer,29,Personal Travel,Eco,95,4,1,4,4,1,4,2,1,3,1,4,2,4,1,0,8.0,neutral or dissatisfied +25872,112225,Female,Loyal Customer,25,Personal Travel,Eco,1199,4,3,4,3,2,4,4,2,1,1,3,3,3,2,7,2.0,neutral or dissatisfied +25873,93171,Female,Loyal Customer,13,Personal Travel,Eco,1075,2,5,3,2,5,3,5,5,4,4,5,3,4,5,18,13.0,neutral or dissatisfied +25874,69400,Female,Loyal Customer,28,Business travel,Eco,1096,1,0,0,4,5,0,5,5,4,3,4,1,3,5,23,35.0,neutral or dissatisfied +25875,125481,Male,Loyal Customer,9,Personal Travel,Eco,2917,2,3,2,4,1,2,1,1,1,5,4,2,4,1,9,2.0,neutral or dissatisfied +25876,40806,Female,Loyal Customer,61,Business travel,Business,584,1,1,1,1,2,2,1,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +25877,72017,Male,disloyal Customer,34,Business travel,Business,3784,3,3,3,3,3,1,1,3,5,3,4,1,4,1,239,226.0,neutral or dissatisfied +25878,10561,Male,disloyal Customer,23,Business travel,Eco,308,0,0,1,3,1,1,1,1,4,4,5,5,5,1,0,0.0,satisfied +25879,6879,Male,disloyal Customer,38,Business travel,Business,265,1,1,1,3,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +25880,36245,Male,disloyal Customer,45,Business travel,Eco,612,4,1,4,3,3,4,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +25881,38424,Female,disloyal Customer,25,Business travel,Eco,965,1,1,1,1,3,1,3,3,2,3,2,4,2,3,4,0.0,neutral or dissatisfied +25882,1648,Female,Loyal Customer,41,Business travel,Business,435,1,1,5,1,4,4,5,4,4,4,4,3,4,3,0,3.0,satisfied +25883,95674,Male,disloyal Customer,26,Business travel,Business,419,4,4,4,5,3,4,3,3,4,4,4,4,4,3,102,101.0,satisfied +25884,14126,Male,disloyal Customer,38,Business travel,Eco,413,2,3,2,1,1,2,1,1,2,4,5,5,3,1,17,31.0,neutral or dissatisfied +25885,8781,Male,Loyal Customer,34,Business travel,Business,522,3,5,3,3,3,5,5,5,5,5,5,5,5,5,0,2.0,satisfied +25886,26899,Male,Loyal Customer,65,Personal Travel,Business,1874,4,4,4,3,2,3,2,3,3,4,3,1,3,3,0,11.0,neutral or dissatisfied +25887,84824,Female,Loyal Customer,42,Business travel,Business,547,1,4,4,4,2,4,3,1,1,1,1,3,1,1,14,1.0,neutral or dissatisfied +25888,119540,Male,Loyal Customer,21,Personal Travel,Eco,759,3,4,2,2,3,2,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +25889,53022,Male,disloyal Customer,29,Business travel,Eco,1208,4,5,5,2,2,5,2,2,5,1,2,2,2,2,0,0.0,satisfied +25890,2277,Female,disloyal Customer,18,Business travel,Eco,672,1,1,1,3,2,1,3,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +25891,115889,Female,disloyal Customer,37,Business travel,Eco,480,4,0,4,5,3,4,3,3,2,2,5,2,5,3,0,0.0,neutral or dissatisfied +25892,126769,Female,disloyal Customer,22,Business travel,Business,985,5,0,5,5,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +25893,90486,Female,Loyal Customer,38,Business travel,Business,1999,3,3,5,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +25894,54904,Male,Loyal Customer,42,Personal Travel,Eco,862,3,4,3,5,3,3,3,3,4,2,5,4,4,3,8,0.0,neutral or dissatisfied +25895,25713,Male,Loyal Customer,59,Business travel,Business,447,2,2,2,2,5,1,2,5,5,5,5,3,5,5,13,4.0,satisfied +25896,17469,Female,Loyal Customer,52,Business travel,Business,241,2,1,1,1,3,3,2,2,2,2,2,4,2,4,0,2.0,neutral or dissatisfied +25897,114637,Male,Loyal Customer,44,Business travel,Business,337,3,3,3,3,2,4,5,4,4,5,4,3,4,5,8,0.0,satisfied +25898,79865,Male,Loyal Customer,43,Business travel,Business,2720,4,4,4,4,4,4,4,3,4,4,5,4,5,4,138,137.0,satisfied +25899,90946,Male,disloyal Customer,39,Business travel,Eco,181,0,0,0,1,4,0,4,4,2,4,2,3,2,4,0,0.0,satisfied +25900,113431,Female,Loyal Customer,44,Business travel,Business,2824,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +25901,68690,Female,Loyal Customer,8,Personal Travel,Eco,237,2,4,2,3,2,5,5,3,5,5,5,5,3,5,97,178.0,neutral or dissatisfied +25902,66664,Female,disloyal Customer,22,Business travel,Eco,802,3,3,3,2,3,3,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +25903,34343,Male,Loyal Customer,25,Personal Travel,Eco,846,4,5,4,1,3,4,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +25904,1289,Male,disloyal Customer,68,Personal Travel,Eco,396,1,4,1,3,2,1,5,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +25905,118284,Female,Loyal Customer,44,Business travel,Business,3866,3,3,3,3,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +25906,57324,Female,Loyal Customer,50,Business travel,Business,414,5,5,5,5,4,4,4,5,5,5,5,3,5,5,10,33.0,satisfied +25907,4721,Male,Loyal Customer,49,Business travel,Business,2269,3,3,1,3,3,4,5,4,4,4,4,4,4,3,48,40.0,satisfied +25908,117456,Male,Loyal Customer,25,Personal Travel,Eco,1107,3,5,3,4,5,3,5,5,4,3,4,4,5,5,10,0.0,neutral or dissatisfied +25909,42542,Male,Loyal Customer,43,Business travel,Business,2718,1,1,1,1,4,4,4,1,1,2,1,3,1,3,6,0.0,neutral or dissatisfied +25910,32704,Female,Loyal Customer,55,Business travel,Business,2133,1,1,1,1,2,3,3,3,3,3,1,3,3,2,0,0.0,neutral or dissatisfied +25911,77301,Female,Loyal Customer,44,Business travel,Business,532,1,1,1,1,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +25912,99034,Male,Loyal Customer,57,Personal Travel,Eco,1009,3,4,3,2,3,3,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +25913,6057,Female,Loyal Customer,25,Personal Travel,Eco,630,3,3,3,3,1,3,5,1,2,5,1,4,3,1,54,53.0,neutral or dissatisfied +25914,74936,Male,Loyal Customer,58,Business travel,Business,2475,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +25915,47220,Female,Loyal Customer,42,Personal Travel,Eco,954,3,2,3,4,3,2,4,1,1,3,1,3,1,1,21,13.0,neutral or dissatisfied +25916,104743,Male,Loyal Customer,38,Business travel,Eco,1342,1,5,5,5,1,1,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +25917,78531,Female,Loyal Customer,30,Personal Travel,Eco,526,3,4,3,4,4,3,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +25918,129676,Female,Loyal Customer,40,Business travel,Business,1918,4,5,4,4,5,5,4,5,5,5,5,5,5,4,23,28.0,satisfied +25919,45434,Male,Loyal Customer,33,Business travel,Business,3714,2,2,2,2,5,5,5,5,2,1,1,5,1,5,0,0.0,satisfied +25920,9704,Female,Loyal Customer,29,Personal Travel,Eco,277,1,3,1,3,5,1,3,5,5,1,1,5,5,5,0,0.0,neutral or dissatisfied +25921,8130,Male,Loyal Customer,31,Business travel,Business,125,1,5,5,5,3,3,1,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +25922,67872,Female,Loyal Customer,35,Personal Travel,Eco,1235,4,4,4,4,3,4,3,3,3,5,4,5,5,3,1,1.0,neutral or dissatisfied +25923,38532,Male,Loyal Customer,47,Business travel,Business,2521,2,3,3,3,5,2,3,2,2,2,2,3,2,2,72,46.0,neutral or dissatisfied +25924,1157,Male,Loyal Customer,26,Personal Travel,Eco,158,3,5,3,1,2,3,1,2,3,2,4,4,5,2,8,1.0,neutral or dissatisfied +25925,75922,Female,Loyal Customer,42,Business travel,Business,2090,4,4,4,4,3,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +25926,62305,Male,Loyal Customer,69,Business travel,Business,2206,1,1,1,1,4,3,4,1,1,1,1,4,1,4,1,11.0,neutral or dissatisfied +25927,20033,Male,Loyal Customer,55,Business travel,Eco,738,4,1,1,1,4,4,4,4,3,3,4,2,5,4,0,0.0,satisfied +25928,37268,Female,Loyal Customer,38,Business travel,Business,1005,2,2,2,2,5,4,2,4,4,4,4,5,4,1,0,0.0,satisfied +25929,54520,Female,Loyal Customer,7,Personal Travel,Eco,925,2,5,3,4,3,3,3,3,1,2,1,5,5,3,9,1.0,neutral or dissatisfied +25930,66971,Male,disloyal Customer,23,Business travel,Eco,929,1,1,1,1,2,1,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +25931,47831,Female,Loyal Customer,51,Business travel,Business,550,3,3,3,3,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +25932,78117,Male,Loyal Customer,29,Business travel,Business,1619,3,3,3,3,5,5,5,5,4,2,3,3,4,5,0,0.0,satisfied +25933,76919,Male,Loyal Customer,52,Personal Travel,Business,1727,2,4,2,3,3,2,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +25934,27125,Female,Loyal Customer,49,Business travel,Eco,2677,4,1,1,1,4,4,4,4,4,5,3,4,5,4,0,0.0,satisfied +25935,99959,Female,Loyal Customer,43,Personal Travel,Eco Plus,2237,2,4,2,3,5,4,5,1,1,2,5,5,1,5,0,0.0,neutral or dissatisfied +25936,72893,Male,disloyal Customer,16,Business travel,Eco,1096,5,5,5,5,2,5,2,2,3,5,5,3,5,2,9,1.0,satisfied +25937,45644,Male,Loyal Customer,35,Personal Travel,Eco,230,2,3,2,4,3,2,2,3,1,4,3,1,3,3,0,23.0,neutral or dissatisfied +25938,92729,Female,disloyal Customer,25,Business travel,Business,1276,3,0,3,3,3,3,3,3,5,4,5,5,4,3,0,4.0,neutral or dissatisfied +25939,77530,Female,Loyal Customer,34,Personal Travel,Eco,1310,2,1,2,2,1,2,1,1,4,4,2,2,2,1,18,31.0,neutral or dissatisfied +25940,90224,Male,Loyal Customer,23,Business travel,Business,1127,4,4,4,4,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +25941,30423,Female,Loyal Customer,35,Business travel,Business,1014,3,3,3,3,1,4,1,4,4,4,4,5,4,1,0,0.0,satisfied +25942,5452,Male,disloyal Customer,20,Business travel,Eco,265,2,4,2,4,2,2,2,2,1,4,4,1,4,2,25,72.0,neutral or dissatisfied +25943,11210,Male,Loyal Customer,12,Personal Travel,Eco,224,1,3,1,3,5,1,4,5,3,4,2,4,5,5,78,110.0,neutral or dissatisfied +25944,13327,Male,disloyal Customer,25,Business travel,Eco,748,0,0,0,1,2,0,2,2,5,5,3,5,1,2,5,2.0,satisfied +25945,82012,Female,disloyal Customer,26,Business travel,Eco,1135,3,3,3,1,4,3,2,4,3,1,1,1,2,4,0,0.0,neutral or dissatisfied +25946,110425,Female,disloyal Customer,37,Business travel,Eco,263,1,5,1,3,1,1,1,4,1,3,3,1,5,1,228,237.0,neutral or dissatisfied +25947,100761,Female,Loyal Customer,53,Business travel,Business,1504,5,5,5,5,2,4,4,5,5,5,5,3,5,3,82,100.0,satisfied +25948,69090,Male,Loyal Customer,24,Personal Travel,Eco,1389,5,4,5,5,2,5,2,2,1,5,1,3,1,2,0,0.0,satisfied +25949,59945,Male,Loyal Customer,61,Business travel,Business,2868,2,5,5,5,4,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +25950,61337,Male,disloyal Customer,26,Business travel,Business,602,4,4,4,4,5,4,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +25951,3194,Male,Loyal Customer,39,Business travel,Eco,293,5,1,1,1,5,5,5,5,3,3,5,1,3,5,0,1.0,satisfied +25952,24001,Male,Loyal Customer,30,Business travel,Business,1797,4,4,4,4,3,4,3,3,3,2,2,5,2,3,0,0.0,satisfied +25953,92629,Female,Loyal Customer,51,Business travel,Eco,453,3,5,5,5,4,3,2,3,3,3,3,2,3,3,9,0.0,neutral or dissatisfied +25954,60470,Male,Loyal Customer,30,Business travel,Business,3893,3,1,1,1,3,3,3,3,1,4,3,2,3,3,38,20.0,neutral or dissatisfied +25955,113536,Male,Loyal Customer,44,Business travel,Business,3341,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +25956,68286,Male,Loyal Customer,44,Business travel,Business,1856,3,5,5,5,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +25957,51048,Male,Loyal Customer,51,Personal Travel,Eco,209,4,4,4,1,1,4,1,1,4,4,3,5,1,1,0,0.0,neutral or dissatisfied +25958,64251,Female,Loyal Customer,65,Personal Travel,Eco,1660,2,0,2,5,4,4,4,1,1,2,1,3,1,5,10,6.0,neutral or dissatisfied +25959,26928,Male,Loyal Customer,34,Personal Travel,Eco,1874,4,5,4,4,2,4,2,2,5,2,1,5,3,2,0,0.0,neutral or dissatisfied +25960,986,Male,Loyal Customer,38,Business travel,Business,1998,5,5,5,5,4,3,1,5,5,5,5,3,5,1,0,0.0,satisfied +25961,92052,Female,disloyal Customer,39,Business travel,Business,1522,2,2,2,4,2,2,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +25962,59136,Male,Loyal Customer,62,Personal Travel,Eco,1846,3,3,4,4,2,4,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +25963,50788,Female,Loyal Customer,36,Personal Travel,Eco,373,3,1,3,2,4,3,4,4,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +25964,91684,Female,Loyal Customer,52,Business travel,Business,2759,1,2,2,2,5,2,3,1,1,1,1,1,1,3,5,6.0,neutral or dissatisfied +25965,20957,Female,Loyal Customer,25,Business travel,Business,3506,2,5,5,5,2,2,2,2,4,5,2,1,2,2,44,46.0,neutral or dissatisfied +25966,55027,Male,Loyal Customer,50,Business travel,Business,1346,5,5,2,5,5,5,4,4,4,5,4,5,4,3,3,0.0,satisfied +25967,15080,Female,Loyal Customer,75,Business travel,Business,1504,3,4,4,4,3,3,3,1,2,4,4,3,4,3,255,246.0,neutral or dissatisfied +25968,89956,Female,Loyal Customer,31,Personal Travel,Eco,1501,2,5,2,1,3,2,2,3,5,5,5,1,4,3,7,0.0,neutral or dissatisfied +25969,128679,Male,Loyal Customer,18,Personal Travel,Eco,2419,4,2,4,3,4,4,4,1,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +25970,24530,Female,disloyal Customer,29,Business travel,Eco Plus,892,2,2,2,4,2,1,1,3,1,3,4,1,2,1,148,131.0,neutral or dissatisfied +25971,9742,Female,disloyal Customer,32,Business travel,Eco,908,4,4,4,2,2,4,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +25972,103168,Male,Loyal Customer,49,Business travel,Business,272,4,4,4,4,3,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +25973,105120,Male,Loyal Customer,55,Business travel,Business,277,5,5,4,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +25974,127189,Male,Loyal Customer,39,Business travel,Business,325,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +25975,93981,Male,Loyal Customer,34,Business travel,Business,3694,3,3,3,3,2,4,5,4,4,4,4,4,4,3,5,0.0,satisfied +25976,28120,Male,Loyal Customer,34,Business travel,Business,834,4,4,4,4,4,3,5,3,3,3,3,2,3,3,0,0.0,satisfied +25977,40776,Female,Loyal Customer,38,Business travel,Business,501,4,4,4,4,5,5,4,4,4,4,4,3,4,2,0,0.0,satisfied +25978,113108,Female,Loyal Customer,70,Personal Travel,Eco,569,2,5,2,1,4,4,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +25979,106637,Female,Loyal Customer,48,Personal Travel,Eco,306,1,4,1,3,5,4,4,2,2,1,2,4,2,4,0,2.0,neutral or dissatisfied +25980,12039,Female,disloyal Customer,26,Business travel,Eco,376,4,2,4,4,3,4,3,3,3,3,4,1,3,3,12,2.0,satisfied +25981,105826,Female,Loyal Customer,10,Personal Travel,Eco,883,2,4,2,5,2,2,2,2,5,1,1,2,4,2,3,4.0,neutral or dissatisfied +25982,49556,Female,Loyal Customer,39,Business travel,Business,3177,3,3,3,3,2,3,5,5,5,4,5,3,5,4,0,0.0,satisfied +25983,90944,Female,Loyal Customer,62,Business travel,Eco,404,4,5,5,5,1,2,4,4,4,4,4,1,4,1,0,0.0,satisfied +25984,10775,Female,Loyal Customer,77,Business travel,Business,308,2,5,5,5,5,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +25985,85071,Male,Loyal Customer,45,Business travel,Business,1705,5,5,5,5,4,5,4,4,4,5,4,5,4,4,3,0.0,satisfied +25986,67991,Male,Loyal Customer,70,Personal Travel,Eco Plus,1205,1,4,1,4,1,1,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +25987,44845,Male,Loyal Customer,32,Personal Travel,Eco,760,3,4,3,4,2,3,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +25988,72021,Female,disloyal Customer,39,Business travel,Business,3784,2,2,2,2,2,4,4,3,2,4,5,4,3,4,0,0.0,neutral or dissatisfied +25989,6063,Female,Loyal Customer,18,Personal Travel,Eco,630,2,5,2,1,4,2,5,4,1,3,4,1,2,4,0,4.0,neutral or dissatisfied +25990,104130,Male,Loyal Customer,72,Business travel,Eco,393,3,4,4,4,3,3,3,3,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +25991,44894,Female,Loyal Customer,41,Business travel,Eco,536,2,3,3,3,2,2,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +25992,55645,Male,Loyal Customer,45,Business travel,Business,315,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,28.0,satisfied +25993,76513,Male,disloyal Customer,28,Business travel,Business,516,4,4,4,2,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +25994,103413,Female,disloyal Customer,21,Business travel,Business,237,4,3,4,3,5,4,5,5,4,2,5,5,5,5,0,0.0,satisfied +25995,85757,Male,disloyal Customer,25,Business travel,Business,526,5,2,5,3,3,5,3,3,5,5,5,5,4,3,1,14.0,satisfied +25996,57391,Male,Loyal Customer,52,Business travel,Business,2202,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +25997,76913,Female,Loyal Customer,48,Business travel,Business,630,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +25998,8314,Female,Loyal Customer,48,Business travel,Business,3489,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +25999,117331,Female,Loyal Customer,31,Personal Travel,Business,296,1,1,1,3,2,1,2,2,1,2,4,4,3,2,38,42.0,neutral or dissatisfied +26000,61465,Male,Loyal Customer,49,Business travel,Business,2419,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,2.0,satisfied +26001,95633,Female,Loyal Customer,14,Personal Travel,Eco,670,2,4,2,4,4,2,4,4,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +26002,94653,Male,Loyal Customer,52,Business travel,Eco,323,2,1,1,1,2,2,2,2,1,4,3,4,2,2,35,33.0,neutral or dissatisfied +26003,84739,Female,Loyal Customer,57,Business travel,Business,2438,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +26004,9069,Male,Loyal Customer,63,Business travel,Eco,173,3,2,2,2,3,3,3,3,2,2,1,3,2,3,3,10.0,neutral or dissatisfied +26005,34366,Female,Loyal Customer,14,Personal Travel,Eco,541,3,4,3,4,3,3,3,3,3,2,4,3,4,3,74,66.0,neutral or dissatisfied +26006,65822,Male,Loyal Customer,29,Business travel,Business,1389,2,2,2,2,4,4,4,4,3,2,4,4,4,4,0,0.0,satisfied +26007,67266,Male,Loyal Customer,37,Personal Travel,Eco,929,3,5,2,4,4,2,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +26008,28604,Male,Loyal Customer,48,Business travel,Eco,2417,4,3,3,3,4,4,4,4,5,1,4,2,5,4,0,0.0,satisfied +26009,110267,Female,Loyal Customer,49,Business travel,Business,3837,2,2,2,2,3,4,4,4,4,4,4,3,4,3,8,0.0,satisfied +26010,105484,Female,Loyal Customer,9,Business travel,Business,516,1,3,3,3,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +26011,56711,Female,Loyal Customer,30,Personal Travel,Eco,1023,3,3,3,5,2,3,5,2,1,4,1,5,4,2,1,0.0,neutral or dissatisfied +26012,47841,Female,Loyal Customer,46,Business travel,Eco,834,4,2,2,2,3,2,4,4,4,4,4,3,4,1,0,1.0,satisfied +26013,113802,Female,Loyal Customer,67,Business travel,Eco Plus,236,2,4,4,4,5,3,3,2,2,2,2,3,2,1,1,17.0,neutral or dissatisfied +26014,127130,Male,Loyal Customer,35,Personal Travel,Eco,370,4,4,4,3,5,4,5,5,1,3,4,2,3,5,0,0.0,neutral or dissatisfied +26015,34365,Male,Loyal Customer,51,Personal Travel,Eco,541,1,3,3,4,5,3,5,5,1,3,3,3,4,5,36,92.0,neutral or dissatisfied +26016,43139,Male,Loyal Customer,67,Personal Travel,Eco Plus,192,1,4,0,3,1,0,1,1,4,3,5,5,4,1,28,21.0,neutral or dissatisfied +26017,61070,Male,Loyal Customer,42,Business travel,Eco,1506,4,3,3,3,4,4,4,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +26018,106130,Female,Loyal Customer,44,Business travel,Business,436,2,2,2,2,3,4,4,2,2,2,2,3,2,3,7,11.0,satisfied +26019,105176,Male,Loyal Customer,44,Personal Travel,Eco,220,1,4,1,3,2,1,2,2,4,5,3,1,4,2,63,46.0,neutral or dissatisfied +26020,124587,Male,Loyal Customer,43,Business travel,Eco,500,3,2,2,2,3,3,3,3,2,3,3,2,4,3,0,3.0,neutral or dissatisfied +26021,104049,Female,Loyal Customer,31,Personal Travel,Eco,1044,4,3,4,5,3,4,4,3,1,5,2,5,5,3,31,32.0,satisfied +26022,113344,Female,Loyal Customer,39,Business travel,Eco,223,3,5,5,5,3,3,3,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +26023,79261,Female,Loyal Customer,11,Personal Travel,Eco,1598,2,3,2,3,2,2,2,2,3,2,3,3,4,2,3,0.0,neutral or dissatisfied +26024,110723,Female,disloyal Customer,45,Business travel,Business,990,5,4,4,2,3,5,3,3,4,5,5,4,5,3,32,125.0,satisfied +26025,77009,Male,Loyal Customer,50,Business travel,Business,2177,1,1,1,1,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +26026,114953,Male,Loyal Customer,30,Business travel,Business,480,1,1,1,1,3,4,3,3,4,3,4,3,4,3,19,17.0,satisfied +26027,58910,Female,disloyal Customer,35,Business travel,Eco,888,2,2,2,3,2,2,2,2,1,3,3,1,3,2,87,99.0,neutral or dissatisfied +26028,8139,Female,disloyal Customer,20,Business travel,Business,125,0,5,0,1,1,0,1,1,4,5,4,5,5,1,0,0.0,satisfied +26029,114117,Female,Loyal Customer,46,Business travel,Business,909,4,4,1,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +26030,53998,Female,Loyal Customer,17,Personal Travel,Eco,1825,3,5,3,2,5,3,5,5,4,5,4,3,4,5,0,1.0,neutral or dissatisfied +26031,92518,Female,Loyal Customer,39,Personal Travel,Eco,1947,3,4,3,5,1,3,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +26032,16939,Male,Loyal Customer,16,Business travel,Business,3835,2,3,3,3,2,2,2,2,2,4,3,2,3,2,140,149.0,neutral or dissatisfied +26033,14037,Male,Loyal Customer,51,Personal Travel,Eco,1117,2,5,3,1,4,3,4,4,4,3,5,4,4,4,26,2.0,neutral or dissatisfied +26034,31642,Female,Loyal Customer,56,Business travel,Business,967,4,4,4,4,3,3,3,5,5,5,5,1,5,4,80,67.0,satisfied +26035,17231,Female,disloyal Customer,24,Business travel,Eco,1092,4,5,5,4,2,5,2,2,5,5,1,5,1,2,0,0.0,neutral or dissatisfied +26036,18259,Female,Loyal Customer,33,Personal Travel,Eco,235,2,5,2,1,4,2,4,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +26037,98096,Male,Loyal Customer,39,Business travel,Business,1719,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +26038,51075,Female,Loyal Customer,42,Personal Travel,Eco,86,2,5,2,5,5,1,1,5,5,2,1,1,5,4,6,3.0,neutral or dissatisfied +26039,129391,Female,Loyal Customer,47,Business travel,Business,2552,2,2,2,2,2,4,5,4,4,4,4,5,4,4,1,1.0,satisfied +26040,89892,Female,disloyal Customer,29,Business travel,Business,1416,3,3,3,1,3,3,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +26041,34170,Female,Loyal Customer,52,Business travel,Business,2013,3,3,3,3,1,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +26042,28827,Male,Loyal Customer,40,Business travel,Eco,1050,4,3,3,3,4,4,4,4,1,2,5,2,2,4,0,0.0,satisfied +26043,88928,Female,Loyal Customer,50,Business travel,Business,1199,5,5,5,5,5,4,5,4,4,4,4,4,4,3,20,19.0,satisfied +26044,72456,Female,Loyal Customer,41,Business travel,Business,3336,3,3,3,3,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +26045,40811,Male,Loyal Customer,25,Business travel,Business,2202,4,4,4,4,5,5,5,5,3,4,2,2,2,5,0,0.0,satisfied +26046,55678,Male,Loyal Customer,41,Business travel,Business,895,2,2,2,2,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +26047,109631,Male,Loyal Customer,40,Business travel,Business,3613,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +26048,111414,Female,Loyal Customer,25,Business travel,Eco,1671,2,5,5,5,2,1,4,2,3,3,2,4,4,2,0,21.0,neutral or dissatisfied +26049,126219,Female,Loyal Customer,29,Business travel,Business,1757,3,3,3,3,3,3,3,3,1,4,2,3,2,3,0,0.0,neutral or dissatisfied +26050,94797,Female,disloyal Customer,36,Business travel,Eco,192,4,1,4,3,4,4,4,4,2,5,3,1,3,4,95,82.0,neutral or dissatisfied +26051,11010,Male,Loyal Customer,28,Business travel,Business,3558,5,5,5,5,5,5,3,5,1,1,4,4,5,5,0,0.0,satisfied +26052,93789,Male,Loyal Customer,39,Business travel,Business,1549,3,3,3,3,4,5,5,4,4,4,4,4,4,4,11,13.0,satisfied +26053,20750,Male,Loyal Customer,27,Personal Travel,Eco,363,1,5,1,4,1,1,1,1,4,5,4,5,5,1,36,25.0,neutral or dissatisfied +26054,8889,Female,Loyal Customer,29,Personal Travel,Eco,622,2,5,2,2,2,2,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +26055,129794,Female,Loyal Customer,8,Personal Travel,Eco,337,4,5,4,5,5,4,1,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +26056,19973,Female,Loyal Customer,39,Personal Travel,Eco,557,4,4,4,3,4,4,4,4,1,4,4,1,3,4,1,5.0,neutral or dissatisfied +26057,122218,Male,Loyal Customer,58,Business travel,Business,541,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +26058,92342,Male,Loyal Customer,36,Business travel,Business,2486,4,1,2,1,3,3,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +26059,65097,Female,Loyal Customer,49,Personal Travel,Eco,354,3,5,3,1,3,5,1,4,4,3,4,2,4,1,41,50.0,neutral or dissatisfied +26060,50429,Female,Loyal Customer,42,Business travel,Business,86,0,5,0,3,3,2,5,2,2,2,2,3,2,5,0,0.0,satisfied +26061,105590,Male,Loyal Customer,40,Business travel,Business,3467,1,1,1,1,5,4,5,5,5,5,5,4,5,5,29,30.0,satisfied +26062,128825,Female,Loyal Customer,58,Business travel,Business,2475,2,3,3,3,2,2,2,1,2,4,3,2,1,2,0,0.0,neutral or dissatisfied +26063,6418,Female,Loyal Customer,42,Personal Travel,Eco,213,3,0,3,2,5,4,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +26064,129014,Male,disloyal Customer,11,Business travel,Business,2611,4,4,4,4,4,1,1,2,4,3,4,1,1,1,4,32.0,neutral or dissatisfied +26065,22096,Male,Loyal Customer,64,Personal Travel,Eco,782,3,4,3,2,4,3,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +26066,33177,Female,Loyal Customer,70,Personal Travel,Eco,163,1,5,1,1,3,3,5,4,4,1,2,4,4,2,0,0.0,neutral or dissatisfied +26067,22655,Female,Loyal Customer,59,Personal Travel,Eco Plus,300,3,5,3,4,5,4,5,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +26068,112810,Male,Loyal Customer,17,Business travel,Business,1390,2,2,2,2,4,4,4,4,5,5,5,5,5,4,7,0.0,satisfied +26069,5576,Female,Loyal Customer,15,Personal Travel,Eco,588,1,4,1,1,4,1,4,4,3,3,5,4,4,4,0,42.0,neutral or dissatisfied +26070,113973,Male,Loyal Customer,49,Business travel,Business,1728,1,1,4,1,2,5,4,5,5,5,5,4,5,5,51,33.0,satisfied +26071,41696,Female,Loyal Customer,11,Personal Travel,Eco,347,2,5,3,4,4,3,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +26072,117407,Male,Loyal Customer,36,Business travel,Business,1136,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,10.0,satisfied +26073,105818,Male,Loyal Customer,56,Personal Travel,Eco,787,1,3,1,2,1,1,1,1,3,1,3,3,3,1,77,93.0,neutral or dissatisfied +26074,13606,Female,Loyal Customer,57,Business travel,Eco Plus,227,2,3,3,3,1,4,3,2,2,2,2,1,2,4,3,27.0,neutral or dissatisfied +26075,46185,Male,disloyal Customer,23,Business travel,Business,349,5,0,5,3,1,5,1,1,5,2,3,5,5,1,86,73.0,satisfied +26076,115179,Male,Loyal Customer,34,Business travel,Business,308,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +26077,103162,Male,Loyal Customer,51,Business travel,Business,3805,0,0,0,1,4,5,5,1,1,1,1,5,1,4,13,1.0,satisfied +26078,85002,Male,Loyal Customer,10,Business travel,Business,1590,1,2,2,2,1,1,1,1,1,3,2,3,3,1,20,26.0,neutral or dissatisfied +26079,39994,Male,Loyal Customer,45,Business travel,Eco,508,3,1,1,1,3,3,3,3,1,1,3,4,3,3,0,0.0,neutral or dissatisfied +26080,41838,Male,Loyal Customer,33,Business travel,Business,2404,5,5,5,5,4,4,4,4,3,3,1,2,5,4,0,0.0,satisfied +26081,69672,Female,Loyal Customer,23,Personal Travel,Eco,569,2,3,2,4,3,2,3,3,1,3,4,2,3,3,2,8.0,neutral or dissatisfied +26082,15098,Female,Loyal Customer,30,Personal Travel,Eco,239,4,4,4,1,2,4,2,2,5,3,4,5,5,2,14,0.0,neutral or dissatisfied +26083,93167,Male,Loyal Customer,25,Personal Travel,Eco,1183,3,4,3,4,2,3,3,2,3,5,3,5,4,2,11,21.0,neutral or dissatisfied +26084,105861,Male,disloyal Customer,16,Business travel,Eco,663,4,3,3,4,3,3,3,3,1,3,1,5,4,3,6,3.0,satisfied +26085,78749,Female,disloyal Customer,22,Business travel,Business,554,4,0,4,2,5,4,5,5,4,3,5,4,5,5,0,0.0,satisfied +26086,26153,Female,Loyal Customer,31,Business travel,Business,3368,3,3,3,3,4,4,4,4,5,5,5,3,2,4,1,0.0,satisfied +26087,90080,Male,Loyal Customer,53,Business travel,Eco,1127,1,4,4,4,1,1,1,1,1,3,4,1,3,1,0,0.0,neutral or dissatisfied +26088,126351,Male,Loyal Customer,42,Personal Travel,Eco,631,3,3,2,2,3,2,3,3,4,3,2,4,3,3,26,26.0,neutral or dissatisfied +26089,19179,Female,Loyal Customer,29,Business travel,Business,3682,4,4,4,4,4,4,4,4,5,1,1,2,2,4,0,0.0,satisfied +26090,55651,Male,Loyal Customer,34,Business travel,Business,2813,0,0,0,3,2,4,5,2,2,4,4,4,2,4,0,0.0,satisfied +26091,35538,Male,Loyal Customer,57,Personal Travel,Eco,1144,3,5,3,4,4,3,4,4,5,3,3,4,4,4,0,13.0,neutral or dissatisfied +26092,23291,Female,disloyal Customer,44,Business travel,Eco,674,1,1,1,1,2,1,2,2,4,1,3,4,1,2,55,62.0,neutral or dissatisfied +26093,79049,Female,disloyal Customer,37,Business travel,Business,306,5,4,4,4,3,4,2,3,3,3,5,3,4,3,0,0.0,satisfied +26094,102810,Female,Loyal Customer,61,Business travel,Business,1724,4,4,4,4,4,5,4,5,5,5,5,4,5,3,84,80.0,satisfied +26095,89150,Female,disloyal Customer,33,Business travel,Eco,1919,3,3,3,4,4,3,4,4,5,4,4,4,5,4,13,2.0,neutral or dissatisfied +26096,53669,Male,Loyal Customer,38,Business travel,Business,3273,5,5,3,5,2,1,4,2,2,2,2,5,2,3,0,0.0,satisfied +26097,98357,Male,Loyal Customer,7,Business travel,Business,1927,2,4,2,2,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +26098,13874,Female,disloyal Customer,38,Business travel,Eco,667,3,3,3,2,3,3,3,3,3,3,2,2,2,3,0,0.0,neutral or dissatisfied +26099,129022,Female,Loyal Customer,17,Personal Travel,Eco,2611,2,4,1,3,1,1,1,2,2,4,4,1,5,1,0,0.0,neutral or dissatisfied +26100,126590,Female,Loyal Customer,44,Business travel,Eco,1337,3,1,5,1,1,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +26101,53151,Female,Loyal Customer,28,Business travel,Business,1678,4,4,4,4,5,5,5,5,1,3,1,1,3,5,2,21.0,satisfied +26102,16629,Female,Loyal Customer,48,Business travel,Business,1571,2,2,5,5,4,3,2,2,2,2,2,2,2,1,56,59.0,neutral or dissatisfied +26103,63687,Female,Loyal Customer,45,Business travel,Business,2610,1,1,4,1,2,4,5,5,5,5,5,3,5,4,9,0.0,satisfied +26104,78932,Male,Loyal Customer,72,Business travel,Business,500,3,1,2,1,1,3,4,3,3,3,3,1,3,1,4,0.0,neutral or dissatisfied +26105,57454,Male,Loyal Customer,65,Business travel,Business,1843,3,3,3,3,3,3,3,2,2,2,3,3,4,3,168,191.0,neutral or dissatisfied +26106,30852,Female,Loyal Customer,26,Personal Travel,Eco,841,2,4,2,4,4,2,4,4,1,2,4,3,4,4,25,30.0,neutral or dissatisfied +26107,95313,Male,Loyal Customer,60,Personal Travel,Eco,239,4,5,4,2,1,4,1,1,4,1,1,2,2,1,0,0.0,neutral or dissatisfied +26108,49912,Female,disloyal Customer,38,Business travel,Eco,199,2,2,2,4,1,2,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +26109,15047,Male,Loyal Customer,13,Business travel,Business,576,3,3,3,3,4,4,4,4,4,1,2,3,1,4,10,0.0,satisfied +26110,14585,Female,Loyal Customer,42,Business travel,Business,2867,4,2,2,2,5,1,1,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +26111,19867,Male,Loyal Customer,33,Personal Travel,Eco Plus,585,3,4,3,2,2,3,2,2,5,5,5,3,4,2,5,5.0,neutral or dissatisfied +26112,34093,Male,Loyal Customer,59,Business travel,Business,1046,1,1,1,1,5,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +26113,83285,Female,Loyal Customer,36,Personal Travel,Eco,2079,5,2,5,3,5,5,5,5,3,4,3,2,3,5,2,0.0,satisfied +26114,69414,Female,Loyal Customer,47,Business travel,Eco,1089,3,4,4,4,1,4,3,3,3,3,3,2,3,2,55,24.0,neutral or dissatisfied +26115,86485,Female,Loyal Customer,58,Personal Travel,Eco,712,2,5,2,4,3,4,5,1,1,2,4,3,1,4,0,7.0,neutral or dissatisfied +26116,82649,Female,Loyal Customer,41,Business travel,Business,120,0,4,0,1,5,4,5,1,1,1,1,5,1,3,50,41.0,satisfied +26117,117833,Male,Loyal Customer,34,Personal Travel,Eco,328,3,3,3,4,4,3,3,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +26118,96858,Male,Loyal Customer,56,Business travel,Business,1845,4,3,3,3,5,4,3,4,4,4,4,1,4,2,3,0.0,neutral or dissatisfied +26119,129299,Female,Loyal Customer,44,Business travel,Business,550,3,3,3,3,5,4,4,5,5,5,5,4,5,3,2,0.0,satisfied +26120,47659,Male,Loyal Customer,20,Business travel,Business,1464,4,4,4,4,2,2,2,2,4,5,3,1,4,2,3,0.0,satisfied +26121,29886,Female,Loyal Customer,44,Business travel,Business,123,2,2,2,2,1,4,1,4,4,5,5,3,4,4,0,0.0,satisfied +26122,62475,Male,Loyal Customer,51,Business travel,Business,1846,4,4,3,4,4,3,4,4,4,4,4,3,4,3,1,1.0,satisfied +26123,74761,Male,Loyal Customer,7,Personal Travel,Eco,1464,3,5,3,1,3,3,3,3,5,3,4,3,5,3,142,118.0,neutral or dissatisfied +26124,38630,Male,Loyal Customer,37,Business travel,Eco,2704,5,4,4,4,5,5,5,5,3,3,5,1,3,5,4,17.0,satisfied +26125,73742,Female,Loyal Customer,21,Personal Travel,Eco,192,2,4,2,3,5,2,5,5,3,5,4,5,4,5,8,6.0,neutral or dissatisfied +26126,22598,Female,disloyal Customer,17,Business travel,Eco,300,1,2,1,4,5,1,1,5,1,5,3,1,3,5,50,44.0,neutral or dissatisfied +26127,63479,Female,Loyal Customer,67,Personal Travel,Eco Plus,447,2,4,2,3,2,5,2,4,4,2,4,3,4,3,0,22.0,neutral or dissatisfied +26128,29469,Male,Loyal Customer,59,Business travel,Business,1107,3,4,4,4,4,4,4,3,3,3,3,1,3,2,0,1.0,neutral or dissatisfied +26129,19052,Female,disloyal Customer,22,Business travel,Eco,604,4,3,4,5,4,4,4,4,3,4,4,4,3,4,0,0.0,neutral or dissatisfied +26130,67749,Male,Loyal Customer,29,Business travel,Business,1188,5,5,5,5,5,5,5,5,3,4,5,3,5,5,7,11.0,satisfied +26131,12790,Male,Loyal Customer,69,Business travel,Eco,528,4,2,2,2,4,4,4,4,4,5,4,5,3,4,10,,satisfied +26132,116663,Male,Loyal Customer,36,Business travel,Eco Plus,446,4,3,3,3,4,4,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +26133,59880,Female,Loyal Customer,43,Business travel,Business,2477,5,5,2,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +26134,66479,Female,Loyal Customer,40,Business travel,Business,447,1,1,1,1,3,4,5,5,5,5,5,4,5,5,50,50.0,satisfied +26135,67695,Male,Loyal Customer,58,Business travel,Business,1431,4,4,5,4,5,4,4,4,4,4,4,3,4,3,7,11.0,satisfied +26136,20560,Female,disloyal Customer,14,Business travel,Eco,533,4,0,4,5,1,4,1,1,3,1,2,4,3,1,0,0.0,neutral or dissatisfied +26137,90420,Male,disloyal Customer,40,Business travel,Eco,250,3,1,3,1,3,2,2,3,3,1,2,2,2,2,152,144.0,neutral or dissatisfied +26138,91320,Male,Loyal Customer,57,Business travel,Eco Plus,404,3,1,1,1,3,3,3,3,3,1,2,3,2,3,0,7.0,neutral or dissatisfied +26139,126501,Female,Loyal Customer,68,Personal Travel,Eco,1788,3,4,3,4,4,5,5,4,4,3,2,5,4,3,0,0.0,neutral or dissatisfied +26140,78095,Female,Loyal Customer,41,Business travel,Business,684,4,4,4,4,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +26141,74211,Male,Loyal Customer,14,Personal Travel,Eco Plus,592,3,5,3,4,2,3,2,2,2,3,4,2,2,2,0,0.0,neutral or dissatisfied +26142,49202,Female,Loyal Customer,35,Business travel,Business,2592,5,5,5,5,4,2,4,5,5,5,5,5,5,4,0,0.0,satisfied +26143,33118,Male,Loyal Customer,46,Personal Travel,Eco,163,4,3,4,2,5,4,5,5,5,4,3,2,5,5,0,0.0,neutral or dissatisfied +26144,74069,Female,disloyal Customer,41,Business travel,Business,641,4,4,4,3,4,4,4,4,2,5,3,3,3,4,4,0.0,neutral or dissatisfied +26145,75949,Male,Loyal Customer,23,Business travel,Business,1716,2,2,2,2,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +26146,30456,Male,Loyal Customer,46,Personal Travel,Eco,991,3,4,3,4,1,3,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +26147,84020,Male,Loyal Customer,38,Personal Travel,Eco,304,1,5,1,4,1,1,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +26148,70581,Male,Loyal Customer,22,Personal Travel,Eco,1258,4,4,4,4,2,4,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +26149,119586,Male,Loyal Customer,28,Personal Travel,Eco,2276,2,5,2,3,1,2,2,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +26150,27106,Female,Loyal Customer,53,Personal Travel,Eco,1721,3,5,3,3,5,4,4,5,5,3,5,4,5,4,20,5.0,neutral or dissatisfied +26151,88826,Male,Loyal Customer,34,Business travel,Eco Plus,406,2,1,1,1,2,2,2,2,4,3,4,4,4,2,34,26.0,neutral or dissatisfied +26152,28380,Female,disloyal Customer,21,Business travel,Business,763,1,4,1,4,5,1,5,5,4,3,3,4,3,5,25,33.0,neutral or dissatisfied +26153,17476,Female,Loyal Customer,33,Business travel,Business,241,4,4,4,4,1,1,5,5,5,5,5,4,5,3,0,13.0,satisfied +26154,11394,Male,Loyal Customer,42,Business travel,Business,458,3,3,3,3,4,4,5,5,5,5,5,3,5,3,1,8.0,satisfied +26155,28673,Male,Loyal Customer,46,Personal Travel,Eco Plus,2404,4,1,4,4,3,4,3,3,3,2,3,2,3,3,16,0.0,neutral or dissatisfied +26156,119241,Female,Loyal Customer,57,Business travel,Business,331,1,1,5,1,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +26157,14869,Female,Loyal Customer,47,Business travel,Business,1559,5,5,5,5,1,1,3,4,4,4,4,5,4,4,13,6.0,satisfied +26158,8732,Female,disloyal Customer,22,Business travel,Eco,181,5,2,5,3,5,5,4,5,3,4,4,4,4,5,0,0.0,satisfied +26159,10964,Female,Loyal Customer,45,Business travel,Eco,229,5,5,5,5,3,2,3,5,5,5,5,3,5,1,0,0.0,satisfied +26160,60838,Male,Loyal Customer,59,Business travel,Business,1754,3,3,3,3,5,4,4,4,4,5,4,4,4,3,12,0.0,satisfied +26161,33310,Female,disloyal Customer,25,Business travel,Eco Plus,101,1,0,1,3,3,1,3,3,1,2,5,3,4,3,0,1.0,neutral or dissatisfied +26162,88935,Male,Loyal Customer,53,Business travel,Business,1340,5,1,5,5,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +26163,129638,Male,Loyal Customer,59,Business travel,Business,2552,1,1,1,1,4,5,4,5,5,5,5,4,5,3,10,8.0,satisfied +26164,104887,Male,Loyal Customer,44,Business travel,Business,1939,1,1,3,1,5,4,5,5,5,5,5,5,5,5,32,19.0,satisfied +26165,103156,Male,disloyal Customer,27,Business travel,Business,272,2,2,2,1,1,0,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +26166,108765,Female,Loyal Customer,31,Business travel,Business,2964,5,5,5,5,4,4,4,4,5,3,5,4,5,4,12,0.0,satisfied +26167,44970,Female,Loyal Customer,46,Business travel,Business,359,4,4,4,4,5,1,5,5,5,5,5,4,5,4,0,0.0,satisfied +26168,105304,Male,Loyal Customer,28,Personal Travel,Eco,738,3,5,2,3,2,4,4,5,3,4,5,4,4,4,214,207.0,neutral or dissatisfied +26169,99585,Male,Loyal Customer,15,Personal Travel,Eco,973,5,4,5,3,2,4,2,2,4,3,3,1,3,2,0,0.0,satisfied +26170,95220,Female,Loyal Customer,33,Personal Travel,Eco,239,1,4,1,3,2,1,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +26171,104493,Male,Loyal Customer,14,Personal Travel,Eco,860,3,3,3,4,3,3,3,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +26172,62662,Female,Loyal Customer,51,Business travel,Business,1781,5,4,5,5,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +26173,85507,Male,Loyal Customer,37,Personal Travel,Eco,332,4,5,4,3,2,4,5,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +26174,23085,Female,Loyal Customer,40,Business travel,Eco,464,1,0,0,4,5,0,5,5,1,3,4,4,3,5,0,19.0,neutral or dissatisfied +26175,86923,Female,Loyal Customer,42,Personal Travel,Eco,341,1,4,1,3,3,5,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +26176,87463,Male,Loyal Customer,46,Business travel,Business,3963,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +26177,81962,Female,Loyal Customer,26,Business travel,Business,1589,3,3,3,3,5,4,5,5,3,5,5,3,5,5,0,0.0,satisfied +26178,23488,Female,Loyal Customer,38,Business travel,Eco Plus,488,4,4,4,4,4,4,4,4,1,2,5,4,2,4,12,19.0,satisfied +26179,31497,Female,disloyal Customer,25,Business travel,Eco,846,3,3,3,3,5,3,5,5,5,2,2,3,5,5,4,0.0,neutral or dissatisfied +26180,105113,Male,Loyal Customer,53,Business travel,Business,281,1,1,1,1,5,4,5,4,4,4,4,4,4,3,47,44.0,satisfied +26181,119769,Female,disloyal Customer,48,Business travel,Business,936,1,1,1,5,2,1,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +26182,27828,Female,Loyal Customer,48,Personal Travel,Eco,1448,0,1,0,3,3,3,2,2,2,1,2,4,2,2,0,2.0,satisfied +26183,44515,Female,Loyal Customer,36,Business travel,Business,2351,0,4,0,4,1,2,1,2,2,2,2,2,2,1,13,2.0,satisfied +26184,5453,Male,disloyal Customer,26,Business travel,Eco,265,4,3,4,3,2,4,2,2,2,4,3,2,3,2,0,12.0,neutral or dissatisfied +26185,121359,Female,Loyal Customer,56,Personal Travel,Business,1670,1,4,1,2,2,2,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +26186,53016,Male,Loyal Customer,31,Business travel,Eco,1190,1,5,5,5,1,1,1,1,4,1,3,2,2,1,19,26.0,neutral or dissatisfied +26187,37283,Female,Loyal Customer,44,Business travel,Business,3625,4,4,4,4,2,3,2,4,4,4,4,4,4,4,0,0.0,satisfied +26188,115084,Female,disloyal Customer,44,Business travel,Business,308,1,1,1,4,3,1,1,3,4,4,4,5,5,3,100,92.0,neutral or dissatisfied +26189,57319,Female,disloyal Customer,38,Business travel,Business,414,5,4,4,3,4,4,4,4,5,2,4,3,5,4,2,0.0,satisfied +26190,84911,Male,Loyal Customer,51,Personal Travel,Eco,481,1,5,2,4,4,2,4,4,5,4,2,1,4,4,31,33.0,neutral or dissatisfied +26191,63514,Male,Loyal Customer,56,Business travel,Business,1009,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +26192,25646,Female,Loyal Customer,53,Personal Travel,Eco,526,2,4,2,5,2,5,4,3,3,2,1,5,3,3,0,11.0,neutral or dissatisfied +26193,14694,Female,Loyal Customer,43,Business travel,Eco,419,5,4,4,4,2,3,4,5,5,5,5,3,5,1,0,0.0,satisfied +26194,115759,Male,Loyal Customer,56,Business travel,Business,3243,2,2,3,2,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +26195,81668,Female,disloyal Customer,21,Business travel,Eco,907,2,2,2,5,2,2,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +26196,108562,Male,disloyal Customer,24,Business travel,Eco,735,2,2,2,1,3,2,3,3,5,4,5,5,4,3,0,11.0,neutral or dissatisfied +26197,7492,Female,Loyal Customer,38,Business travel,Business,925,3,5,5,5,1,2,1,3,3,3,3,4,3,4,10,8.0,neutral or dissatisfied +26198,18867,Male,Loyal Customer,39,Business travel,Eco,448,5,4,4,4,5,5,5,5,1,2,4,4,1,5,0,0.0,satisfied +26199,31090,Female,disloyal Customer,25,Business travel,Eco,1014,4,4,4,2,5,4,5,5,4,3,2,2,1,5,0,0.0,neutral or dissatisfied +26200,117750,Female,Loyal Customer,29,Personal Travel,Eco,935,1,4,1,2,1,1,4,1,5,3,4,4,4,1,34,23.0,neutral or dissatisfied +26201,104168,Male,Loyal Customer,22,Business travel,Business,349,2,3,3,3,2,3,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +26202,11007,Female,Loyal Customer,46,Business travel,Business,267,5,5,5,5,5,2,4,5,5,5,5,3,5,4,0,4.0,satisfied +26203,79563,Female,disloyal Customer,48,Business travel,Business,762,3,3,3,5,3,3,3,3,4,4,5,5,4,3,9,0.0,neutral or dissatisfied +26204,19047,Female,Loyal Customer,24,Business travel,Business,1601,2,5,5,5,2,3,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +26205,92046,Female,Loyal Customer,33,Business travel,Business,1589,1,1,1,1,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +26206,120077,Male,Loyal Customer,56,Business travel,Business,683,5,5,5,5,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +26207,866,Male,Loyal Customer,44,Business travel,Business,1644,2,4,4,4,5,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +26208,118794,Male,Loyal Customer,33,Personal Travel,Eco,370,1,2,1,4,1,5,5,1,2,4,3,5,4,5,161,177.0,neutral or dissatisfied +26209,26130,Male,disloyal Customer,26,Business travel,Eco,545,2,3,2,4,3,2,3,3,2,3,2,2,4,3,53,44.0,neutral or dissatisfied +26210,53185,Female,disloyal Customer,40,Business travel,Business,589,3,3,3,3,3,3,3,4,5,1,5,3,2,3,93,142.0,neutral or dissatisfied +26211,81219,Male,Loyal Customer,67,Personal Travel,Eco,1426,2,4,2,2,5,2,5,5,3,1,1,3,4,5,6,0.0,neutral or dissatisfied +26212,42131,Female,disloyal Customer,30,Business travel,Eco Plus,991,1,1,1,3,4,1,2,4,4,2,3,3,4,4,13,12.0,neutral or dissatisfied +26213,25252,Male,Loyal Customer,28,Personal Travel,Eco Plus,925,4,4,4,3,5,4,2,5,4,1,4,2,5,5,5,5.0,satisfied +26214,116421,Female,Loyal Customer,67,Personal Travel,Eco,446,2,3,2,4,4,3,4,3,3,2,3,4,3,3,13,0.0,neutral or dissatisfied +26215,77778,Female,Loyal Customer,54,Personal Travel,Eco,731,1,3,1,4,3,4,3,5,5,1,5,1,5,2,18,1.0,neutral or dissatisfied +26216,86821,Female,Loyal Customer,25,Business travel,Business,692,3,1,5,1,3,3,3,3,2,3,3,3,3,3,3,8.0,neutral or dissatisfied +26217,533,Female,disloyal Customer,38,Business travel,Business,309,3,3,3,4,5,3,1,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +26218,121890,Male,Loyal Customer,24,Personal Travel,Eco,366,1,3,2,4,4,2,4,4,1,4,2,1,2,4,0,0.0,neutral or dissatisfied +26219,116246,Male,Loyal Customer,23,Personal Travel,Eco,296,2,2,2,4,2,2,2,2,4,2,3,4,4,2,26,22.0,neutral or dissatisfied +26220,36719,Male,Loyal Customer,65,Business travel,Eco Plus,1010,3,5,5,5,3,3,3,3,3,2,3,3,4,3,0,11.0,neutral or dissatisfied +26221,29763,Female,Loyal Customer,37,Business travel,Business,1973,4,4,4,4,2,4,5,5,5,5,5,3,5,3,8,0.0,satisfied +26222,109218,Male,disloyal Customer,36,Business travel,Eco,391,3,0,3,4,5,3,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +26223,51560,Male,Loyal Customer,54,Business travel,Business,370,4,1,4,4,4,3,3,5,5,4,5,4,5,1,70,58.0,satisfied +26224,10861,Female,Loyal Customer,49,Business travel,Business,3534,2,2,2,2,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +26225,64901,Male,Loyal Customer,54,Business travel,Business,1698,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +26226,39933,Male,Loyal Customer,47,Business travel,Business,2222,1,3,3,3,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +26227,61413,Male,Loyal Customer,27,Personal Travel,Eco,679,4,4,5,1,4,5,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +26228,40787,Female,Loyal Customer,43,Business travel,Eco,558,3,5,5,5,5,2,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +26229,12239,Male,Loyal Customer,62,Business travel,Business,2483,0,4,0,4,1,2,4,4,4,4,4,1,4,3,0,0.0,satisfied +26230,25478,Male,Loyal Customer,28,Business travel,Business,481,4,1,4,4,2,2,2,2,4,4,5,4,2,2,0,0.0,satisfied +26231,126001,Female,Loyal Customer,17,Personal Travel,Business,507,2,2,2,3,2,2,2,2,4,2,3,1,3,2,1,0.0,neutral or dissatisfied +26232,6812,Male,Loyal Customer,40,Personal Travel,Eco,235,2,5,0,4,3,0,1,3,4,3,5,4,4,3,0,2.0,neutral or dissatisfied +26233,6716,Male,Loyal Customer,39,Personal Travel,Eco,438,2,4,2,3,1,2,1,1,3,2,3,3,4,1,35,45.0,neutral or dissatisfied +26234,24233,Male,Loyal Customer,30,Business travel,Business,2628,3,5,5,5,2,2,3,2,2,2,3,2,3,2,41,40.0,neutral or dissatisfied +26235,56009,Female,Loyal Customer,54,Business travel,Business,2586,3,3,3,3,4,4,4,4,5,5,4,4,4,4,25,6.0,satisfied +26236,17629,Female,Loyal Customer,31,Business travel,Business,980,4,1,1,1,4,3,4,4,4,4,3,2,4,4,0,0.0,neutral or dissatisfied +26237,56548,Male,Loyal Customer,19,Business travel,Business,3596,3,3,3,3,2,2,2,2,3,5,4,4,4,2,19,16.0,satisfied +26238,86501,Female,Loyal Customer,61,Personal Travel,Eco,762,2,1,2,3,4,4,3,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +26239,100815,Male,Loyal Customer,48,Business travel,Business,711,4,4,4,4,2,5,4,5,5,5,5,4,5,5,11,0.0,satisfied +26240,78115,Female,Loyal Customer,43,Business travel,Business,1797,1,1,1,1,2,3,5,5,5,5,5,5,5,3,36,42.0,satisfied +26241,60377,Male,disloyal Customer,40,Business travel,Business,1476,4,4,4,3,5,4,5,5,3,4,4,4,5,5,0,1.0,satisfied +26242,92559,Female,Loyal Customer,19,Personal Travel,Eco,2116,4,1,3,2,1,3,1,1,4,2,2,3,1,1,3,0.0,satisfied +26243,36168,Male,disloyal Customer,15,Business travel,Eco,1674,2,2,2,4,1,2,1,1,3,2,3,3,4,1,18,8.0,neutral or dissatisfied +26244,35264,Female,Loyal Customer,53,Business travel,Business,2248,2,2,2,2,2,4,1,3,3,3,3,1,3,2,0,2.0,satisfied +26245,105165,Female,Loyal Customer,57,Personal Travel,Eco,220,4,1,4,1,2,2,2,2,2,4,2,4,2,2,9,0.0,satisfied +26246,2699,Male,Loyal Customer,56,Business travel,Business,2704,3,3,3,3,5,5,4,2,2,2,2,5,2,3,0,3.0,satisfied +26247,47261,Male,Loyal Customer,66,Personal Travel,Business,588,3,5,4,4,5,2,5,5,5,4,2,1,5,2,0,0.0,neutral or dissatisfied +26248,79661,Female,Loyal Customer,54,Personal Travel,Eco,762,2,5,3,5,3,4,5,4,5,4,5,5,4,5,131,122.0,neutral or dissatisfied +26249,76786,Female,Loyal Customer,60,Business travel,Business,3821,3,1,1,1,1,4,4,3,3,3,3,1,3,1,3,4.0,neutral or dissatisfied +26250,7396,Female,Loyal Customer,49,Business travel,Business,552,5,5,5,5,2,4,4,3,3,3,3,3,3,5,8,1.0,satisfied +26251,69476,Male,Loyal Customer,42,Personal Travel,Eco,1035,1,2,1,4,5,1,5,5,4,2,3,1,3,5,0,0.0,neutral or dissatisfied +26252,34619,Female,Loyal Customer,12,Personal Travel,Eco Plus,1598,1,5,1,3,5,1,5,5,4,5,3,3,5,5,21,7.0,neutral or dissatisfied +26253,40591,Female,disloyal Customer,55,Business travel,Eco,391,1,0,1,5,1,1,1,1,3,4,1,4,3,1,0,0.0,neutral or dissatisfied +26254,30709,Male,disloyal Customer,37,Business travel,Eco,464,2,2,2,2,2,2,2,2,3,5,3,4,2,2,41,32.0,neutral or dissatisfied +26255,58051,Male,disloyal Customer,29,Business travel,Business,642,2,2,2,1,5,2,2,5,5,4,4,4,4,5,19,13.0,neutral or dissatisfied +26256,111885,Male,Loyal Customer,34,Business travel,Business,2257,4,4,5,4,2,1,2,4,4,4,4,1,4,5,16,15.0,satisfied +26257,87422,Female,Loyal Customer,53,Personal Travel,Eco,425,2,0,2,4,4,5,4,1,1,2,1,5,1,3,3,0.0,neutral or dissatisfied +26258,94632,Female,Loyal Customer,52,Business travel,Business,2596,3,3,3,3,5,5,5,5,5,5,4,5,5,3,50,46.0,satisfied +26259,57920,Male,Loyal Customer,26,Personal Travel,Eco,305,3,5,3,4,1,3,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +26260,51518,Female,disloyal Customer,25,Business travel,Eco,651,5,0,5,2,2,5,2,2,1,1,2,3,1,2,0,0.0,satisfied +26261,19590,Female,Loyal Customer,14,Personal Travel,Eco,212,4,3,4,2,2,4,2,2,4,3,2,3,3,2,0,0.0,satisfied +26262,91864,Male,Loyal Customer,57,Personal Travel,Eco,1995,5,3,5,2,2,5,2,2,4,3,4,5,5,2,0,0.0,satisfied +26263,99554,Female,Loyal Customer,36,Business travel,Business,802,2,5,5,5,5,4,3,2,2,2,2,4,2,2,36,30.0,neutral or dissatisfied +26264,81769,Female,Loyal Customer,33,Business travel,Business,1487,1,5,1,1,4,5,5,4,4,4,4,5,4,3,16,1.0,satisfied +26265,84834,Male,Loyal Customer,44,Business travel,Business,481,4,4,4,4,5,3,4,4,4,4,4,1,4,2,18,13.0,neutral or dissatisfied +26266,98179,Male,Loyal Customer,44,Business travel,Business,327,5,5,2,5,5,4,5,5,5,5,5,3,5,4,0,12.0,satisfied +26267,72639,Male,Loyal Customer,46,Personal Travel,Eco,964,2,4,2,1,1,2,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +26268,128348,Female,Loyal Customer,28,Business travel,Business,1849,1,1,1,1,2,2,2,2,5,4,4,5,4,2,6,4.0,satisfied +26269,74386,Female,Loyal Customer,48,Business travel,Business,1313,4,4,4,4,2,5,5,3,3,2,3,4,3,3,48,31.0,satisfied +26270,74726,Female,Loyal Customer,60,Personal Travel,Eco,1171,2,4,2,1,5,5,4,5,5,2,5,3,5,4,0,9.0,neutral or dissatisfied +26271,119940,Female,Loyal Customer,40,Business travel,Business,1009,5,5,5,5,4,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +26272,18420,Female,Loyal Customer,45,Business travel,Eco,900,4,3,4,3,2,1,1,4,4,4,4,4,4,4,0,0.0,satisfied +26273,27413,Female,Loyal Customer,47,Business travel,Eco,954,4,3,3,3,2,3,4,4,4,4,4,3,4,1,0,0.0,satisfied +26274,120956,Female,Loyal Customer,25,Business travel,Business,992,3,4,4,4,3,3,3,3,1,2,3,1,4,3,86,72.0,neutral or dissatisfied +26275,123323,Female,disloyal Customer,22,Business travel,Eco,468,3,0,3,4,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +26276,15789,Male,Loyal Customer,30,Personal Travel,Eco Plus,198,2,5,2,2,3,2,3,3,3,3,4,3,5,3,16,0.0,neutral or dissatisfied +26277,41950,Male,Loyal Customer,29,Business travel,Business,575,4,4,4,4,4,4,4,4,3,5,2,4,5,4,0,0.0,satisfied +26278,57801,Male,Loyal Customer,45,Business travel,Business,1235,2,2,2,2,4,5,4,5,5,4,5,5,5,4,4,0.0,satisfied +26279,101643,Male,Loyal Customer,41,Business travel,Business,1733,2,2,2,2,2,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +26280,15378,Male,Loyal Customer,34,Business travel,Business,164,2,2,2,2,4,5,3,4,4,4,3,5,4,5,0,0.0,satisfied +26281,108988,Male,disloyal Customer,45,Business travel,Business,849,1,1,1,3,3,1,3,3,4,5,5,3,4,3,19,18.0,neutral or dissatisfied +26282,119093,Male,Loyal Customer,25,Business travel,Business,1673,3,3,3,3,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +26283,37613,Male,Loyal Customer,27,Personal Travel,Eco,944,2,3,2,3,2,2,2,2,1,4,3,2,3,2,29,17.0,neutral or dissatisfied +26284,16201,Male,Loyal Customer,9,Personal Travel,Eco,212,2,1,2,3,1,2,1,1,3,2,3,2,4,1,41,49.0,neutral or dissatisfied +26285,31380,Female,disloyal Customer,32,Business travel,Eco,895,2,3,3,3,3,3,3,3,2,5,2,1,3,3,3,0.0,neutral or dissatisfied +26286,67776,Male,Loyal Customer,32,Business travel,Eco,1438,5,3,4,4,5,4,5,5,3,2,3,1,3,5,38,56.0,neutral or dissatisfied +26287,110190,Male,Loyal Customer,18,Personal Travel,Eco,869,1,1,1,4,1,1,1,1,2,3,4,2,3,1,8,0.0,neutral or dissatisfied +26288,96112,Female,Loyal Customer,61,Personal Travel,Eco,1235,3,5,3,3,2,3,4,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +26289,10423,Male,Loyal Customer,51,Business travel,Business,158,0,5,0,1,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +26290,11769,Female,Loyal Customer,44,Personal Travel,Eco,429,5,4,5,1,3,3,1,3,3,5,3,3,3,1,15,25.0,satisfied +26291,3234,Female,Loyal Customer,58,Business travel,Business,479,2,2,4,2,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +26292,40214,Female,disloyal Customer,23,Business travel,Eco,358,4,4,4,4,1,4,1,1,2,4,3,3,1,1,0,0.0,satisfied +26293,43940,Male,Loyal Customer,48,Personal Travel,Eco Plus,174,3,5,3,3,4,3,4,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +26294,61658,Female,Loyal Customer,42,Business travel,Business,1609,4,4,4,4,3,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +26295,97101,Male,disloyal Customer,28,Business travel,Eco,1242,1,1,1,3,4,1,4,4,4,1,4,1,3,4,0,20.0,neutral or dissatisfied +26296,123448,Male,Loyal Customer,59,Business travel,Business,2296,1,1,5,1,4,4,4,4,4,4,4,5,4,4,8,0.0,satisfied +26297,7001,Male,Loyal Customer,52,Business travel,Business,3774,1,1,1,1,5,3,3,3,3,3,1,2,3,3,10,40.0,neutral or dissatisfied +26298,63426,Female,Loyal Customer,22,Personal Travel,Eco,447,4,3,4,3,2,4,2,2,1,4,3,1,3,2,2,0.0,neutral or dissatisfied +26299,26231,Male,Loyal Customer,10,Personal Travel,Eco,270,2,0,2,1,3,2,3,3,3,5,1,1,4,3,24,26.0,neutral or dissatisfied +26300,85524,Male,Loyal Customer,40,Business travel,Business,259,0,0,0,2,3,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +26301,73119,Male,Loyal Customer,11,Personal Travel,Eco,2174,2,1,2,3,1,2,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +26302,10492,Female,Loyal Customer,60,Business travel,Business,2014,2,2,2,2,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +26303,93983,Female,Loyal Customer,29,Business travel,Business,3217,3,3,3,3,3,4,3,3,4,5,3,1,4,3,11,2.0,neutral or dissatisfied +26304,37430,Female,disloyal Customer,9,Business travel,Eco,1005,3,3,3,2,2,3,2,2,2,2,2,4,4,2,2,0.0,neutral or dissatisfied +26305,96700,Male,Loyal Customer,42,Business travel,Business,1773,2,5,2,2,5,4,4,4,4,4,4,4,4,5,79,80.0,satisfied +26306,82450,Female,disloyal Customer,19,Business travel,Eco,502,1,5,1,2,3,1,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +26307,31613,Female,Loyal Customer,52,Business travel,Business,853,4,4,2,4,2,4,5,4,4,4,4,5,4,5,12,7.0,satisfied +26308,88158,Male,Loyal Customer,39,Business travel,Business,3057,2,2,2,2,4,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +26309,124398,Male,Loyal Customer,70,Personal Travel,Eco Plus,808,3,1,3,2,3,3,3,3,1,4,2,2,2,3,20,43.0,neutral or dissatisfied +26310,28658,Male,Loyal Customer,31,Personal Travel,Eco,2541,3,2,3,3,3,3,3,3,1,3,2,2,3,3,0,,neutral or dissatisfied +26311,116417,Male,Loyal Customer,66,Personal Travel,Eco,337,2,4,2,2,5,2,4,5,3,5,5,5,4,5,5,0.0,neutral or dissatisfied +26312,34650,Male,Loyal Customer,66,Personal Travel,Eco,427,4,5,4,3,5,4,5,5,5,4,1,1,5,5,0,0.0,neutral or dissatisfied +26313,84210,Female,Loyal Customer,31,Business travel,Business,2881,3,4,4,4,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +26314,10702,Male,disloyal Customer,24,Business travel,Eco,295,1,2,1,2,2,1,4,2,4,4,2,4,3,2,0,0.0,neutral or dissatisfied +26315,103911,Male,Loyal Customer,52,Business travel,Business,2310,4,4,4,4,4,5,4,4,4,4,4,4,4,5,10,10.0,satisfied +26316,4319,Male,Loyal Customer,57,Business travel,Business,589,2,2,4,2,4,4,4,4,4,4,4,5,4,5,4,0.0,satisfied +26317,124307,Female,Loyal Customer,46,Business travel,Business,3130,0,0,0,3,4,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +26318,104183,Male,Loyal Customer,57,Personal Travel,Eco,349,3,4,3,4,3,2,5,4,3,4,3,5,4,5,129,134.0,neutral or dissatisfied +26319,6728,Male,disloyal Customer,26,Business travel,Business,268,2,0,2,4,2,2,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +26320,29562,Male,disloyal Customer,27,Business travel,Eco,1464,4,4,4,4,5,4,5,5,5,2,3,2,3,5,12,12.0,neutral or dissatisfied +26321,28373,Female,Loyal Customer,24,Business travel,Eco,763,0,3,0,4,5,0,5,5,2,1,4,2,4,5,0,16.0,satisfied +26322,93396,Male,Loyal Customer,53,Business travel,Business,605,4,3,4,4,4,4,5,4,4,4,4,4,4,3,51,38.0,satisfied +26323,121882,Male,Loyal Customer,8,Personal Travel,Eco,366,2,4,2,3,3,2,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +26324,43983,Female,Loyal Customer,48,Personal Travel,Eco,411,3,5,3,1,3,5,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +26325,20412,Male,disloyal Customer,42,Business travel,Eco,299,4,5,4,2,3,4,3,3,2,2,2,2,2,3,92,98.0,neutral or dissatisfied +26326,123806,Male,disloyal Customer,38,Business travel,Business,544,5,5,5,2,4,5,4,4,3,4,5,5,5,4,0,0.0,satisfied +26327,29520,Male,Loyal Customer,41,Business travel,Business,1009,2,2,2,2,3,1,3,4,4,4,4,1,4,5,0,0.0,satisfied +26328,39843,Female,Loyal Customer,28,Business travel,Business,221,1,1,1,1,5,5,5,5,2,4,5,3,5,5,0,0.0,satisfied +26329,55938,Male,Loyal Customer,7,Personal Travel,Eco Plus,733,1,2,1,4,4,1,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +26330,91900,Female,Loyal Customer,58,Business travel,Business,2586,3,3,3,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +26331,29074,Female,Loyal Customer,52,Personal Travel,Eco,956,3,2,3,3,3,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +26332,13739,Male,Loyal Customer,35,Business travel,Business,441,2,2,2,2,4,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +26333,89870,Male,Loyal Customer,42,Business travel,Business,1416,2,2,2,2,4,5,4,3,3,4,3,5,3,4,23,39.0,satisfied +26334,87993,Male,Loyal Customer,51,Business travel,Business,442,3,3,3,3,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +26335,99073,Male,Loyal Customer,40,Business travel,Business,2842,3,3,3,3,5,4,5,5,5,5,5,3,5,5,4,0.0,satisfied +26336,62813,Male,Loyal Customer,23,Personal Travel,Eco,2367,1,5,1,4,2,1,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +26337,82528,Female,Loyal Customer,10,Personal Travel,Eco,1749,2,5,2,5,4,2,5,4,4,1,3,4,5,4,8,6.0,neutral or dissatisfied +26338,3449,Male,Loyal Customer,34,Personal Travel,Eco,213,2,4,2,4,3,2,3,3,5,4,5,4,5,3,0,,neutral or dissatisfied +26339,121900,Male,Loyal Customer,34,Personal Travel,Eco,449,3,4,3,4,1,3,1,1,2,2,4,2,3,1,3,1.0,neutral or dissatisfied +26340,120097,Female,Loyal Customer,10,Personal Travel,Business,1576,4,4,4,3,2,4,2,2,4,3,3,5,5,2,18,3.0,neutral or dissatisfied +26341,92396,Female,Loyal Customer,42,Business travel,Business,1947,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +26342,89409,Male,disloyal Customer,57,Business travel,Business,134,1,2,2,4,1,1,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +26343,55210,Male,Loyal Customer,45,Business travel,Business,1919,3,5,5,5,3,3,4,3,3,3,3,3,3,3,10,0.0,neutral or dissatisfied +26344,13097,Male,Loyal Customer,36,Business travel,Business,562,5,5,5,5,3,3,2,5,5,4,5,4,5,4,0,0.0,satisfied +26345,86704,Male,Loyal Customer,38,Business travel,Business,1747,2,4,4,4,4,2,2,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +26346,80743,Female,disloyal Customer,22,Personal Travel,Eco,393,1,2,1,3,2,1,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +26347,66978,Male,Loyal Customer,38,Business travel,Business,1774,3,3,3,3,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +26348,94807,Female,Loyal Customer,17,Business travel,Business,2515,4,4,4,4,4,4,4,4,3,2,4,2,3,4,12,14.0,neutral or dissatisfied +26349,60961,Female,Loyal Customer,15,Business travel,Business,888,2,3,3,3,2,2,2,2,2,1,3,4,4,2,3,0.0,neutral or dissatisfied +26350,65358,Male,Loyal Customer,44,Business travel,Eco,631,1,1,1,1,1,1,1,1,1,2,3,1,4,1,0,0.0,neutral or dissatisfied +26351,73946,Male,Loyal Customer,32,Business travel,Business,2585,4,4,4,4,4,5,5,2,1,3,1,5,3,5,64,58.0,satisfied +26352,70408,Female,disloyal Customer,70,Personal Travel,Eco,1562,2,1,2,2,4,2,4,4,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +26353,127411,Male,Loyal Customer,69,Personal Travel,Eco,868,3,1,3,3,2,3,2,2,4,5,3,4,2,2,0,0.0,neutral or dissatisfied +26354,122605,Male,Loyal Customer,59,Business travel,Eco,728,3,3,3,3,3,3,3,3,1,4,3,4,3,3,1,9.0,neutral or dissatisfied +26355,29749,Male,Loyal Customer,42,Business travel,Business,571,3,3,2,3,3,4,5,2,2,2,2,5,2,5,54,52.0,satisfied +26356,107114,Female,disloyal Customer,30,Business travel,Business,842,3,3,3,4,4,3,4,4,3,4,5,5,5,4,14,3.0,neutral or dissatisfied +26357,114948,Female,Loyal Customer,38,Business travel,Business,342,5,5,5,5,4,4,5,4,4,4,4,3,4,5,13,4.0,satisfied +26358,57872,Female,disloyal Customer,21,Business travel,Eco,305,4,0,4,1,4,5,5,3,4,5,5,5,4,5,239,219.0,neutral or dissatisfied +26359,26233,Female,Loyal Customer,14,Personal Travel,Eco,270,3,2,3,3,3,3,2,3,1,1,3,1,3,3,51,50.0,neutral or dissatisfied +26360,62505,Male,Loyal Customer,53,Business travel,Business,1723,2,2,2,2,3,4,4,4,4,4,4,5,4,4,5,0.0,satisfied +26361,115441,Male,disloyal Customer,61,Business travel,Business,390,2,2,2,3,5,2,5,5,4,3,5,5,4,5,56,51.0,neutral or dissatisfied +26362,40906,Female,Loyal Customer,14,Personal Travel,Eco,588,2,4,3,5,3,3,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +26363,32140,Female,Loyal Customer,56,Business travel,Eco,101,4,5,5,5,2,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +26364,70974,Female,Loyal Customer,53,Business travel,Business,802,5,5,3,5,5,4,5,3,3,3,3,3,3,3,86,78.0,satisfied +26365,105714,Male,Loyal Customer,39,Business travel,Business,842,2,2,3,2,3,3,3,3,5,4,4,3,5,3,77,139.0,satisfied +26366,24827,Female,disloyal Customer,20,Business travel,Eco,894,4,4,4,5,3,4,3,3,5,5,2,3,5,3,1,0.0,satisfied +26367,75378,Male,Loyal Customer,48,Business travel,Business,2342,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +26368,6445,Male,Loyal Customer,46,Personal Travel,Eco,315,4,1,4,3,4,4,4,4,2,4,3,1,2,4,0,0.0,neutral or dissatisfied +26369,76137,Female,disloyal Customer,32,Business travel,Business,689,2,2,2,2,3,2,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +26370,4058,Female,Loyal Customer,23,Personal Travel,Eco,483,2,4,2,4,1,2,1,1,2,2,4,3,3,1,0,0.0,neutral or dissatisfied +26371,129772,Female,Loyal Customer,44,Personal Travel,Eco,337,3,4,4,1,3,5,4,5,5,4,3,3,5,5,0,0.0,neutral or dissatisfied +26372,77404,Female,Loyal Customer,58,Personal Travel,Eco,599,4,3,4,2,4,3,2,3,3,4,5,5,3,5,7,0.0,neutral or dissatisfied +26373,31039,Male,Loyal Customer,33,Business travel,Business,1745,3,3,3,3,4,4,4,4,2,4,5,2,5,4,0,0.0,satisfied +26374,111323,Female,Loyal Customer,47,Business travel,Eco,283,1,2,2,2,5,3,3,1,1,1,1,2,1,1,8,0.0,neutral or dissatisfied +26375,79988,Female,Loyal Customer,11,Personal Travel,Eco,1076,2,5,2,1,1,2,1,1,5,5,4,4,4,1,46,73.0,neutral or dissatisfied +26376,45014,Female,Loyal Customer,42,Personal Travel,Eco,118,2,3,2,2,3,4,4,1,1,2,1,1,1,1,91,84.0,neutral or dissatisfied +26377,3687,Male,disloyal Customer,34,Business travel,Eco,427,3,2,3,3,4,3,4,4,4,4,3,4,3,4,68,39.0,neutral or dissatisfied +26378,54348,Male,Loyal Customer,48,Business travel,Eco Plus,1597,5,1,1,1,5,5,5,5,4,4,4,4,1,5,3,0.0,satisfied +26379,73429,Female,Loyal Customer,17,Personal Travel,Eco,1182,3,1,3,2,2,3,2,2,4,1,1,3,3,2,31,18.0,neutral or dissatisfied +26380,61499,Female,Loyal Customer,28,Business travel,Eco,2419,1,2,2,2,1,1,1,1,3,1,2,4,4,1,0,7.0,neutral or dissatisfied +26381,33405,Male,Loyal Customer,37,Business travel,Business,2556,5,5,5,5,4,4,4,4,4,4,4,2,4,5,0,0.0,satisfied +26382,321,Male,Loyal Customer,42,Business travel,Business,3109,2,1,1,1,2,3,4,2,2,2,2,1,2,3,0,8.0,neutral or dissatisfied +26383,79968,Female,disloyal Customer,21,Business travel,Eco,1096,3,3,3,4,5,3,5,5,3,2,3,4,4,5,54,67.0,neutral or dissatisfied +26384,34901,Male,Loyal Customer,50,Business travel,Eco,187,4,1,1,1,4,4,4,3,2,2,3,4,5,4,218,229.0,satisfied +26385,19355,Male,Loyal Customer,25,Business travel,Business,692,1,3,3,3,1,1,1,1,1,2,3,2,3,1,24,29.0,neutral or dissatisfied +26386,43997,Female,Loyal Customer,55,Business travel,Eco,397,4,2,2,2,1,2,2,5,5,4,5,2,5,3,0,12.0,neutral or dissatisfied +26387,41286,Male,Loyal Customer,10,Business travel,Eco,542,3,2,3,2,3,3,4,3,3,1,3,4,3,3,2,5.0,neutral or dissatisfied +26388,78588,Male,Loyal Customer,30,Personal Travel,Eco,630,3,5,3,5,2,3,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +26389,40582,Male,Loyal Customer,41,Business travel,Eco,411,4,1,1,1,4,4,4,4,1,2,3,4,3,4,78,66.0,neutral or dissatisfied +26390,63772,Female,Loyal Customer,60,Business travel,Business,1721,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +26391,36061,Female,Loyal Customer,45,Business travel,Eco,413,3,2,2,2,5,1,5,3,3,3,3,4,3,4,7,6.0,satisfied +26392,64714,Male,Loyal Customer,61,Business travel,Business,3403,2,2,2,2,5,5,4,5,5,5,5,3,5,5,10,5.0,satisfied +26393,51287,Female,disloyal Customer,23,Business travel,Eco,153,4,0,4,4,4,4,4,4,1,4,5,1,1,4,0,0.0,satisfied +26394,11260,Female,Loyal Customer,56,Personal Travel,Eco,216,1,0,1,5,4,2,5,4,4,1,5,4,4,2,0,3.0,neutral or dissatisfied +26395,27732,Male,Loyal Customer,42,Business travel,Business,1448,5,5,5,5,3,4,3,5,5,5,5,2,5,3,0,28.0,satisfied +26396,95482,Female,Loyal Customer,72,Business travel,Eco Plus,192,4,5,4,5,1,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +26397,6216,Female,Loyal Customer,9,Personal Travel,Business,594,3,4,3,3,1,3,1,1,4,1,3,3,1,1,0,0.0,neutral or dissatisfied +26398,67792,Male,Loyal Customer,26,Business travel,Business,1235,1,4,4,4,1,1,1,1,3,2,3,1,4,1,105,111.0,neutral or dissatisfied +26399,64523,Male,Loyal Customer,49,Business travel,Business,247,2,2,2,2,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +26400,58369,Male,Loyal Customer,17,Personal Travel,Eco Plus,599,2,2,2,3,1,2,1,1,1,4,4,4,3,1,0,0.0,neutral or dissatisfied +26401,96033,Female,disloyal Customer,22,Business travel,Eco,1235,1,1,1,3,2,1,5,2,4,5,4,2,4,2,25,38.0,neutral or dissatisfied +26402,81468,Female,Loyal Customer,23,Business travel,Business,3541,4,4,4,4,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +26403,93850,Female,Loyal Customer,18,Personal Travel,Eco,391,3,5,3,2,4,3,3,4,5,2,5,2,4,4,0,0.0,neutral or dissatisfied +26404,8281,Male,Loyal Customer,56,Personal Travel,Eco,335,2,4,3,1,1,3,1,1,2,1,2,4,1,1,0,0.0,neutral or dissatisfied +26405,121869,Female,disloyal Customer,62,Business travel,Eco,366,2,2,2,3,3,2,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +26406,71886,Female,Loyal Customer,65,Personal Travel,Eco,1846,1,3,1,1,2,3,3,3,3,1,5,2,3,4,11,34.0,neutral or dissatisfied +26407,90232,Male,Loyal Customer,55,Personal Travel,Eco Plus,1084,4,4,4,3,5,4,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +26408,120622,Male,Loyal Customer,57,Business travel,Business,2050,3,3,3,3,4,4,5,4,4,4,4,5,4,5,0,34.0,satisfied +26409,49024,Female,Loyal Customer,32,Business travel,Eco,373,5,2,4,4,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +26410,4600,Female,Loyal Customer,47,Personal Travel,Eco,416,3,3,3,4,3,3,3,5,5,3,5,2,5,3,11,10.0,neutral or dissatisfied +26411,78203,Female,Loyal Customer,69,Business travel,Business,2395,1,1,1,1,5,1,2,5,5,5,5,4,5,1,0,0.0,satisfied +26412,81863,Male,Loyal Customer,34,Personal Travel,Eco Plus,1310,1,4,1,3,2,1,2,2,2,2,3,4,4,2,1,6.0,neutral or dissatisfied +26413,41025,Female,Loyal Customer,52,Business travel,Eco,989,4,3,3,3,1,5,1,4,4,4,4,4,4,4,0,15.0,satisfied +26414,109672,Male,Loyal Customer,7,Personal Travel,Eco,973,1,4,0,4,5,0,2,5,3,4,4,3,4,5,1,0.0,neutral or dissatisfied +26415,23177,Female,Loyal Customer,57,Personal Travel,Eco,223,2,4,2,1,3,5,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +26416,94274,Male,Loyal Customer,60,Business travel,Business,248,0,0,0,1,5,4,5,1,1,1,1,3,1,4,0,5.0,satisfied +26417,106592,Female,Loyal Customer,48,Personal Travel,Eco Plus,333,2,4,2,3,5,4,4,1,1,2,1,5,1,4,20,14.0,neutral or dissatisfied +26418,108599,Male,Loyal Customer,48,Business travel,Business,2676,3,4,4,4,4,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +26419,47854,Male,Loyal Customer,38,Business travel,Business,451,2,2,2,2,2,2,2,3,4,4,4,2,3,2,130,135.0,neutral or dissatisfied +26420,74563,Male,Loyal Customer,55,Business travel,Eco,1188,1,4,2,4,1,1,1,4,5,2,3,1,2,1,281,284.0,neutral or dissatisfied +26421,37670,Female,Loyal Customer,64,Personal Travel,Eco,944,1,2,1,4,1,2,2,2,5,3,4,2,4,2,111,133.0,neutral or dissatisfied +26422,20592,Female,Loyal Customer,42,Business travel,Eco Plus,773,4,1,3,1,2,3,5,4,4,4,4,1,4,4,16,9.0,satisfied +26423,89036,Female,Loyal Customer,24,Business travel,Business,1919,1,1,4,1,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +26424,37401,Male,Loyal Customer,39,Business travel,Business,944,3,3,3,3,4,4,4,2,2,5,5,4,2,4,123,171.0,satisfied +26425,100431,Female,Loyal Customer,50,Business travel,Eco,120,5,1,1,1,1,5,2,5,5,5,5,3,5,2,0,31.0,satisfied +26426,115431,Male,disloyal Customer,30,Business travel,Eco,373,1,2,1,3,1,1,1,1,1,3,4,4,3,1,0,0.0,neutral or dissatisfied +26427,33470,Male,Loyal Customer,46,Business travel,Business,2917,2,2,2,2,4,4,4,4,1,3,3,4,5,4,0,25.0,satisfied +26428,92969,Male,Loyal Customer,50,Business travel,Eco Plus,1694,3,3,3,3,3,3,3,3,1,2,4,1,3,3,10,0.0,neutral or dissatisfied +26429,89695,Male,Loyal Customer,57,Business travel,Eco,647,2,5,5,5,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +26430,62084,Female,disloyal Customer,24,Business travel,Business,1481,4,0,3,3,3,3,5,3,5,5,3,4,4,3,0,0.0,satisfied +26431,109939,Female,Loyal Customer,66,Personal Travel,Eco,971,2,5,2,3,4,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +26432,37343,Female,Loyal Customer,26,Business travel,Eco,1011,4,5,5,5,4,4,3,4,5,3,4,3,4,4,0,0.0,satisfied +26433,80221,Female,Loyal Customer,50,Business travel,Business,2153,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +26434,61421,Male,Loyal Customer,47,Business travel,Business,2288,4,4,2,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +26435,12762,Male,Loyal Customer,57,Personal Travel,Eco,721,2,4,2,4,3,2,3,3,2,3,2,5,1,3,0,0.0,neutral or dissatisfied +26436,71610,Male,Loyal Customer,58,Business travel,Business,1182,3,4,4,4,3,3,4,3,3,3,3,3,3,4,5,0.0,neutral or dissatisfied +26437,59982,Male,Loyal Customer,16,Personal Travel,Eco,937,1,4,1,3,1,1,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +26438,68299,Female,Loyal Customer,47,Business travel,Business,1797,1,1,5,1,2,5,4,3,3,4,3,5,3,4,7,16.0,satisfied +26439,88568,Female,Loyal Customer,33,Personal Travel,Eco,271,4,0,4,3,2,4,2,2,3,5,4,4,5,2,17,10.0,neutral or dissatisfied +26440,81910,Female,Loyal Customer,65,Business travel,Eco Plus,280,2,5,5,5,5,4,1,2,2,2,2,4,2,5,13,0.0,satisfied +26441,108206,Male,disloyal Customer,34,Business travel,Eco,777,1,1,1,4,3,1,3,3,2,3,3,4,3,3,12,9.0,neutral or dissatisfied +26442,13775,Female,disloyal Customer,20,Business travel,Eco,878,3,3,3,3,3,3,3,3,5,4,2,1,4,3,0,0.0,neutral or dissatisfied +26443,54749,Female,Loyal Customer,15,Personal Travel,Eco,965,2,5,2,4,2,2,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +26444,129120,Male,Loyal Customer,56,Business travel,Business,2619,1,1,1,1,5,4,3,1,1,1,1,1,1,4,0,1.0,neutral or dissatisfied +26445,111473,Male,Loyal Customer,43,Business travel,Business,3653,5,5,5,5,5,4,4,4,4,5,4,4,4,3,14,20.0,satisfied +26446,44908,Male,Loyal Customer,48,Business travel,Eco,1118,4,1,1,1,4,4,4,4,1,4,2,4,4,4,104,102.0,satisfied +26447,50663,Female,Loyal Customer,38,Personal Travel,Eco,250,1,5,1,5,5,1,1,5,4,2,4,5,4,5,36,44.0,neutral or dissatisfied +26448,45082,Female,disloyal Customer,20,Business travel,Eco,299,2,0,2,4,1,2,1,1,1,2,4,1,3,1,13,3.0,neutral or dissatisfied +26449,117764,Female,Loyal Customer,52,Business travel,Eco,1670,2,2,2,2,1,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +26450,104138,Female,Loyal Customer,58,Personal Travel,Eco,448,5,5,5,1,3,4,5,1,1,5,1,3,1,3,0,0.0,satisfied +26451,23723,Female,Loyal Customer,59,Business travel,Eco Plus,196,5,2,2,2,2,1,1,5,5,5,5,5,5,1,78,80.0,satisfied +26452,12399,Female,disloyal Customer,25,Business travel,Eco,383,3,2,3,4,4,3,4,4,1,4,4,1,3,4,24,9.0,neutral or dissatisfied +26453,7593,Male,Loyal Customer,54,Business travel,Business,1900,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +26454,93636,Female,Loyal Customer,45,Personal Travel,Eco,577,1,4,1,2,3,5,5,4,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +26455,91957,Female,Loyal Customer,45,Personal Travel,Eco,2475,2,2,2,3,5,4,3,4,4,2,3,2,4,3,23,2.0,neutral or dissatisfied +26456,2124,Male,Loyal Customer,45,Business travel,Business,3059,5,5,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +26457,2627,Male,Loyal Customer,39,Business travel,Eco Plus,304,1,1,5,1,1,1,1,1,1,5,3,4,4,1,29,26.0,neutral or dissatisfied +26458,73282,Male,disloyal Customer,24,Business travel,Business,1144,4,0,4,2,5,4,5,5,4,4,5,3,4,5,0,0.0,satisfied +26459,34719,Female,disloyal Customer,25,Business travel,Eco,264,2,4,2,2,3,2,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +26460,69294,Female,Loyal Customer,28,Personal Travel,Eco Plus,733,1,5,1,4,1,3,4,4,1,2,3,4,1,4,205,198.0,neutral or dissatisfied +26461,65905,Male,Loyal Customer,32,Business travel,Business,3020,2,3,3,3,2,2,2,2,2,1,4,4,4,2,20,22.0,neutral or dissatisfied +26462,94643,Female,Loyal Customer,48,Business travel,Business,239,1,2,4,4,2,3,3,1,1,1,1,4,1,2,0,7.0,neutral or dissatisfied +26463,42478,Male,Loyal Customer,33,Business travel,Eco Plus,395,3,4,3,4,3,2,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +26464,61709,Female,Loyal Customer,55,Business travel,Business,1635,1,1,1,1,3,3,4,4,4,5,4,4,4,5,0,0.0,satisfied +26465,82533,Male,disloyal Customer,20,Business travel,Business,440,0,5,0,1,5,0,5,5,4,4,4,5,4,5,0,5.0,satisfied +26466,104950,Male,disloyal Customer,38,Business travel,Business,337,5,5,5,4,1,5,1,1,3,3,5,4,5,1,0,0.0,satisfied +26467,36857,Male,disloyal Customer,25,Business travel,Business,273,1,5,1,3,5,1,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +26468,18174,Male,Loyal Customer,37,Business travel,Eco Plus,363,5,5,5,5,5,5,5,5,4,4,2,3,1,5,0,0.0,satisfied +26469,102407,Female,Loyal Customer,45,Personal Travel,Eco,197,1,5,1,1,5,2,1,5,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +26470,122014,Female,Loyal Customer,46,Business travel,Business,3261,4,4,4,4,4,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +26471,3114,Male,disloyal Customer,45,Business travel,Business,1013,5,0,0,3,2,5,2,2,3,3,4,3,5,2,0,0.0,satisfied +26472,85131,Female,Loyal Customer,53,Business travel,Business,1815,5,5,5,5,3,5,5,2,2,2,2,5,2,4,10,0.0,satisfied +26473,31941,Female,Loyal Customer,53,Business travel,Business,1654,5,5,5,5,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +26474,58825,Female,Loyal Customer,69,Personal Travel,Eco,1012,1,3,1,4,2,4,3,2,2,1,2,1,2,4,36,22.0,neutral or dissatisfied +26475,9786,Male,Loyal Customer,56,Personal Travel,Eco,383,0,4,0,3,5,0,5,5,5,4,4,4,4,5,0,0.0,satisfied +26476,64971,Female,disloyal Customer,30,Business travel,Eco,190,2,1,2,4,4,2,4,4,1,4,4,2,4,4,0,0.0,neutral or dissatisfied +26477,44512,Male,Loyal Customer,11,Personal Travel,Business,157,1,4,0,4,2,0,1,2,5,2,4,3,4,2,72,73.0,neutral or dissatisfied +26478,46301,Male,Loyal Customer,39,Business travel,Eco Plus,533,5,1,1,1,5,5,5,5,4,1,4,3,5,5,39,41.0,satisfied +26479,118630,Male,Loyal Customer,54,Business travel,Business,304,2,2,2,2,2,5,5,5,5,5,5,5,5,5,15,0.0,satisfied +26480,123636,Female,Loyal Customer,43,Business travel,Business,1635,3,3,3,3,2,4,5,4,4,4,4,5,4,4,31,32.0,satisfied +26481,99321,Female,Loyal Customer,59,Business travel,Business,3133,1,5,5,5,4,4,4,1,1,1,1,1,1,3,14,9.0,neutral or dissatisfied +26482,26276,Female,Loyal Customer,34,Personal Travel,Eco,859,3,5,3,5,5,3,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +26483,109580,Female,Loyal Customer,28,Personal Travel,Eco,994,4,4,4,2,2,4,2,2,5,5,5,4,4,2,55,42.0,neutral or dissatisfied +26484,22744,Female,disloyal Customer,23,Business travel,Eco,302,4,4,4,1,4,4,4,4,3,5,1,5,4,4,87,81.0,neutral or dissatisfied +26485,57094,Male,Loyal Customer,32,Business travel,Business,2682,5,5,5,5,5,5,5,5,3,5,4,4,4,5,0,0.0,satisfied +26486,95121,Female,Loyal Customer,46,Personal Travel,Eco,677,2,5,3,4,4,4,3,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +26487,79759,Female,disloyal Customer,24,Business travel,Eco,1076,4,5,5,3,3,5,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +26488,38360,Male,disloyal Customer,21,Business travel,Eco,1111,2,2,2,4,2,2,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +26489,32631,Male,Loyal Customer,50,Business travel,Eco,216,5,2,2,2,5,5,5,5,3,2,3,4,1,5,0,0.0,satisfied +26490,113545,Female,Loyal Customer,47,Business travel,Business,3524,2,2,2,2,3,2,2,3,5,4,3,2,2,2,175,160.0,neutral or dissatisfied +26491,104985,Male,disloyal Customer,21,Business travel,Eco,314,3,1,3,4,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +26492,104449,Female,disloyal Customer,66,Business travel,Business,1123,2,2,2,3,2,2,2,2,3,2,2,2,3,2,89,60.0,neutral or dissatisfied +26493,27460,Female,Loyal Customer,29,Business travel,Business,978,1,3,3,3,1,1,1,1,4,3,2,4,3,1,0,0.0,neutral or dissatisfied +26494,3864,Male,Loyal Customer,33,Personal Travel,Business,213,4,1,4,5,4,4,4,4,5,3,4,3,4,4,10,15.0,satisfied +26495,10471,Male,Loyal Customer,51,Business travel,Business,312,0,0,0,2,2,5,4,1,1,1,1,3,1,3,0,0.0,satisfied +26496,114136,Female,disloyal Customer,32,Business travel,Business,957,2,2,2,1,1,2,1,1,4,2,4,5,4,1,76,83.0,neutral or dissatisfied +26497,45593,Female,Loyal Customer,41,Business travel,Eco,313,5,4,4,4,5,5,5,5,2,1,2,4,2,5,0,0.0,satisfied +26498,18329,Male,Loyal Customer,40,Business travel,Business,3954,3,3,3,3,2,2,2,4,4,4,4,1,4,3,0,7.0,satisfied +26499,129406,Male,disloyal Customer,24,Business travel,Business,236,4,0,4,1,1,4,1,1,3,5,5,5,5,1,0,0.0,satisfied +26500,1364,Male,Loyal Customer,49,Business travel,Business,2906,0,0,0,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +26501,118176,Male,Loyal Customer,22,Business travel,Business,1440,2,2,2,2,2,2,2,2,4,2,5,3,5,2,8,0.0,satisfied +26502,8076,Female,Loyal Customer,58,Business travel,Business,125,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +26503,73285,Male,disloyal Customer,25,Business travel,Business,1182,4,4,4,2,4,5,5,5,3,5,4,5,5,5,155,150.0,satisfied +26504,739,Female,disloyal Customer,39,Business travel,Business,482,2,2,2,4,1,2,1,1,4,2,5,3,4,1,11,7.0,neutral or dissatisfied +26505,17603,Male,Loyal Customer,50,Business travel,Business,2224,2,2,2,2,3,3,3,4,4,5,3,4,4,4,0,0.0,satisfied +26506,91651,Male,Loyal Customer,32,Personal Travel,Eco,1184,1,5,1,2,1,1,1,1,3,2,3,5,4,1,0,0.0,neutral or dissatisfied +26507,102364,Male,disloyal Customer,33,Business travel,Eco,386,2,4,2,4,1,2,1,1,2,3,4,4,4,1,16,9.0,neutral or dissatisfied +26508,98245,Female,disloyal Customer,18,Business travel,Eco,1072,5,5,5,1,5,5,4,5,3,4,5,3,4,5,0,2.0,satisfied +26509,53229,Male,disloyal Customer,40,Personal Travel,Eco,612,2,3,2,3,1,2,1,1,2,1,1,1,3,1,4,0.0,neutral or dissatisfied +26510,125346,Female,Loyal Customer,40,Business travel,Eco,599,3,3,5,3,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +26511,63930,Female,Loyal Customer,24,Personal Travel,Eco,1158,1,3,1,3,2,1,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +26512,118155,Male,disloyal Customer,18,Business travel,Business,1440,0,2,1,1,4,1,4,4,5,2,4,3,4,4,11,3.0,satisfied +26513,66772,Male,Loyal Customer,52,Business travel,Business,3528,4,4,2,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +26514,27282,Female,Loyal Customer,61,Personal Travel,Business,679,3,4,3,3,3,4,5,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +26515,27702,Female,Loyal Customer,20,Personal Travel,Eco Plus,1107,4,4,4,4,3,4,1,3,2,4,3,2,2,3,0,14.0,neutral or dissatisfied +26516,106499,Female,disloyal Customer,37,Business travel,Eco,495,2,0,2,1,5,2,5,5,4,5,1,2,3,5,0,0.0,neutral or dissatisfied +26517,8926,Male,disloyal Customer,43,Business travel,Business,984,2,2,2,2,2,2,2,2,4,5,5,5,4,2,10,0.0,neutral or dissatisfied +26518,89448,Male,Loyal Customer,26,Personal Travel,Eco,151,2,5,2,3,2,2,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +26519,62451,Male,Loyal Customer,42,Business travel,Business,1744,4,4,4,4,1,4,4,4,4,4,4,4,4,1,0,10.0,neutral or dissatisfied +26520,5112,Female,Loyal Customer,44,Personal Travel,Eco,122,1,5,1,1,4,5,2,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +26521,24117,Female,Loyal Customer,61,Business travel,Business,3355,0,5,0,2,1,1,5,3,3,3,3,2,3,4,7,0.0,satisfied +26522,104569,Male,Loyal Customer,58,Business travel,Business,369,5,5,5,5,5,5,4,4,4,5,4,3,4,5,19,11.0,satisfied +26523,5797,Male,disloyal Customer,59,Business travel,Business,273,2,2,2,1,1,2,1,1,5,4,5,5,4,1,0,6.0,neutral or dissatisfied +26524,100851,Female,Loyal Customer,15,Personal Travel,Eco,711,3,5,3,4,2,3,2,2,1,1,3,4,3,2,0,2.0,neutral or dissatisfied +26525,2562,Female,Loyal Customer,39,Business travel,Business,3701,4,5,5,5,3,2,2,4,4,4,4,4,4,1,42,41.0,neutral or dissatisfied +26526,127578,Female,Loyal Customer,51,Business travel,Business,1773,5,5,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +26527,121530,Female,Loyal Customer,47,Business travel,Business,912,1,1,1,1,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +26528,92205,Male,disloyal Customer,15,Business travel,Eco,838,1,1,1,5,1,1,1,1,2,5,2,3,3,1,0,0.0,neutral or dissatisfied +26529,94611,Male,disloyal Customer,21,Business travel,Business,248,4,4,3,4,5,3,5,5,5,3,5,5,4,5,65,61.0,satisfied +26530,28954,Male,Loyal Customer,68,Business travel,Business,697,1,2,1,2,3,4,3,1,1,1,1,3,1,4,0,2.0,neutral or dissatisfied +26531,125865,Male,Loyal Customer,50,Business travel,Business,1872,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +26532,37593,Male,Loyal Customer,56,Business travel,Business,2740,2,2,2,2,4,3,5,5,5,5,5,5,5,1,0,0.0,satisfied +26533,115758,Female,Loyal Customer,47,Business travel,Business,337,4,2,2,2,2,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +26534,46347,Male,Loyal Customer,21,Personal Travel,Eco,589,2,5,3,3,1,3,1,1,5,3,5,3,5,1,0,33.0,neutral or dissatisfied +26535,107807,Male,disloyal Customer,23,Business travel,Eco,349,1,4,1,2,1,1,4,1,3,2,4,5,5,1,7,0.0,neutral or dissatisfied +26536,86066,Female,disloyal Customer,20,Business travel,Eco,432,2,0,2,4,3,2,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +26537,15372,Male,Loyal Customer,43,Business travel,Eco,331,5,4,4,4,5,5,5,5,1,3,4,4,5,5,0,2.0,satisfied +26538,32452,Female,Loyal Customer,63,Business travel,Business,3795,1,5,5,5,3,4,3,2,2,2,1,3,2,2,0,0.0,neutral or dissatisfied +26539,121827,Male,Loyal Customer,46,Business travel,Business,366,2,2,2,2,2,5,5,4,4,4,4,3,4,3,0,4.0,satisfied +26540,95854,Female,Loyal Customer,20,Business travel,Business,1929,4,4,3,4,3,4,3,3,4,5,5,5,5,3,0,0.0,satisfied +26541,106730,Male,Loyal Customer,55,Business travel,Business,3768,3,3,5,3,4,4,4,4,4,4,4,4,4,3,18,2.0,satisfied +26542,4133,Female,Loyal Customer,62,Business travel,Business,431,3,2,2,2,4,4,3,3,3,3,3,4,3,2,0,16.0,neutral or dissatisfied +26543,113630,Male,Loyal Customer,39,Personal Travel,Eco,258,2,3,2,1,4,2,4,4,2,5,2,2,4,4,0,0.0,neutral or dissatisfied +26544,95884,Female,Loyal Customer,59,Personal Travel,Eco,580,2,4,2,3,5,5,4,3,3,2,3,4,3,3,3,0.0,neutral or dissatisfied +26545,46302,Female,Loyal Customer,43,Business travel,Eco,680,1,3,3,3,4,2,3,1,1,1,1,4,1,4,0,13.0,neutral or dissatisfied +26546,115317,Female,Loyal Customer,41,Business travel,Business,308,1,5,5,5,4,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +26547,124018,Male,Loyal Customer,56,Personal Travel,Eco,184,3,5,3,4,3,3,3,3,5,4,1,2,2,3,0,0.0,neutral or dissatisfied +26548,52800,Female,Loyal Customer,29,Personal Travel,Eco,1874,3,4,3,5,2,3,2,2,1,3,5,1,1,2,6,0.0,neutral or dissatisfied +26549,5140,Female,disloyal Customer,48,Business travel,Business,622,5,4,4,2,5,5,2,5,4,3,5,3,4,5,0,0.0,satisfied +26550,104710,Female,Loyal Customer,56,Business travel,Business,1865,2,2,2,2,2,5,4,5,5,5,5,3,5,5,87,85.0,satisfied +26551,55006,Female,Loyal Customer,52,Business travel,Business,1635,2,2,2,2,5,5,5,5,5,5,5,4,5,5,45,50.0,satisfied +26552,98894,Male,disloyal Customer,47,Business travel,Business,479,1,1,1,4,1,1,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +26553,49986,Male,Loyal Customer,23,Business travel,Business,199,4,5,5,5,3,3,4,3,2,5,3,4,3,3,32,32.0,neutral or dissatisfied +26554,42449,Male,disloyal Customer,30,Business travel,Eco,866,1,1,1,1,1,1,1,1,5,4,2,3,1,1,0,0.0,neutral or dissatisfied +26555,11964,Female,Loyal Customer,65,Personal Travel,Business,643,3,5,2,3,5,4,4,3,3,2,3,5,3,4,81,90.0,neutral or dissatisfied +26556,43555,Female,Loyal Customer,8,Personal Travel,Eco,438,2,4,2,1,2,5,5,4,3,5,5,5,4,5,328,404.0,neutral or dissatisfied +26557,71508,Male,Loyal Customer,41,Business travel,Business,3940,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +26558,20238,Male,disloyal Customer,21,Business travel,Business,235,4,0,4,5,3,4,2,3,4,5,4,3,5,3,2,0.0,satisfied +26559,103097,Female,Loyal Customer,26,Personal Travel,Eco,786,2,4,2,2,1,2,1,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +26560,89200,Female,Loyal Customer,27,Personal Travel,Eco,1947,4,2,4,1,1,4,1,1,1,4,1,4,2,1,3,0.0,neutral or dissatisfied +26561,96167,Male,Loyal Customer,55,Business travel,Business,460,3,3,3,3,3,5,5,5,5,5,5,5,5,3,21,21.0,satisfied +26562,35594,Female,Loyal Customer,45,Business travel,Eco Plus,944,2,4,4,4,3,3,3,2,2,2,2,1,2,3,1,7.0,neutral or dissatisfied +26563,70970,Female,Loyal Customer,49,Business travel,Business,1873,1,1,1,1,3,4,5,4,4,4,4,3,4,5,4,0.0,satisfied +26564,19133,Female,Loyal Customer,39,Personal Travel,Eco,287,4,4,4,1,5,4,5,5,5,4,4,5,1,5,46,81.0,neutral or dissatisfied +26565,90632,Male,Loyal Customer,43,Business travel,Business,3610,4,4,4,4,3,5,4,3,3,3,3,3,3,5,0,1.0,satisfied +26566,71738,Male,Loyal Customer,41,Business travel,Business,2189,4,2,4,4,5,4,5,4,4,5,4,5,4,3,4,28.0,satisfied +26567,58867,Female,Loyal Customer,31,Business travel,Business,2068,3,4,4,4,3,3,3,3,4,4,3,1,4,3,19,12.0,neutral or dissatisfied +26568,125279,Female,Loyal Customer,52,Business travel,Business,2427,3,3,3,3,3,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +26569,8420,Female,Loyal Customer,24,Business travel,Business,862,1,3,3,3,2,1,1,4,1,3,4,1,2,1,129,140.0,neutral or dissatisfied +26570,111839,Female,Loyal Customer,17,Personal Travel,Business,804,1,1,1,4,5,1,5,5,1,1,3,2,3,5,27,19.0,neutral or dissatisfied +26571,65368,Female,Loyal Customer,69,Business travel,Eco,432,4,3,3,3,3,2,3,4,4,4,4,4,4,4,21,27.0,neutral or dissatisfied +26572,45547,Male,Loyal Customer,35,Personal Travel,Eco,566,1,3,1,4,5,1,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +26573,58017,Female,Loyal Customer,34,Business travel,Eco,1721,4,1,1,1,4,4,4,4,2,1,2,4,4,4,0,0.0,neutral or dissatisfied +26574,57623,Female,Loyal Customer,46,Business travel,Business,3536,3,3,3,3,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +26575,40233,Male,Loyal Customer,52,Business travel,Eco,358,5,3,3,3,5,5,5,5,5,4,1,5,2,5,0,0.0,satisfied +26576,118299,Female,Loyal Customer,53,Business travel,Business,2759,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +26577,11882,Male,Loyal Customer,50,Personal Travel,Eco,912,2,5,2,2,5,2,5,5,3,1,1,3,3,5,2,0.0,neutral or dissatisfied +26578,28540,Male,disloyal Customer,24,Business travel,Eco,1201,5,5,5,3,1,5,2,1,2,3,3,5,2,1,0,0.0,satisfied +26579,10779,Male,Loyal Customer,43,Business travel,Business,2493,2,4,4,4,1,4,4,2,2,2,2,3,2,4,70,72.0,neutral or dissatisfied +26580,108132,Female,disloyal Customer,49,Business travel,Eco,1105,4,4,4,3,5,4,1,5,4,3,3,4,4,5,0,0.0,neutral or dissatisfied +26581,120529,Female,Loyal Customer,28,Personal Travel,Eco,96,2,5,0,2,1,0,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +26582,44781,Female,disloyal Customer,27,Business travel,Eco,1250,3,3,3,4,5,3,5,5,2,3,4,2,3,5,42,70.0,neutral or dissatisfied +26583,32132,Female,Loyal Customer,47,Business travel,Business,163,2,2,2,2,3,5,2,5,5,5,4,2,5,5,18,16.0,satisfied +26584,65380,Female,Loyal Customer,59,Business travel,Eco,432,5,1,5,1,5,1,1,5,5,5,5,5,5,2,0,0.0,satisfied +26585,107733,Male,Loyal Customer,51,Personal Travel,Eco,405,3,3,3,3,4,3,4,4,5,5,2,1,2,4,0,0.0,neutral or dissatisfied +26586,39381,Female,Loyal Customer,33,Business travel,Business,2471,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +26587,99639,Female,Loyal Customer,18,Personal Travel,Eco Plus,1154,2,4,3,3,1,3,1,1,4,3,5,4,4,1,18,41.0,neutral or dissatisfied +26588,38454,Male,Loyal Customer,39,Business travel,Business,1781,5,5,5,5,3,1,4,3,3,3,3,4,3,2,0,0.0,satisfied +26589,103128,Female,Loyal Customer,32,Business travel,Eco Plus,460,3,3,3,3,3,3,3,3,2,2,4,1,4,3,0,0.0,neutral or dissatisfied +26590,4374,Male,Loyal Customer,9,Business travel,Business,618,3,4,3,4,3,3,3,3,1,2,4,4,4,3,27,50.0,neutral or dissatisfied +26591,100886,Male,Loyal Customer,47,Business travel,Business,377,4,4,4,4,4,4,5,5,5,5,5,4,5,5,4,0.0,satisfied +26592,70483,Female,Loyal Customer,30,Business travel,Business,3481,4,4,4,4,4,4,4,4,3,2,4,2,4,4,0,0.0,neutral or dissatisfied +26593,67202,Female,Loyal Customer,21,Personal Travel,Eco,1119,1,3,0,4,4,0,4,4,2,5,3,2,3,4,0,2.0,neutral or dissatisfied +26594,5608,Male,Loyal Customer,33,Business travel,Business,3781,5,5,2,5,4,4,4,4,3,4,5,3,4,4,12,0.0,satisfied +26595,9985,Female,Loyal Customer,23,Personal Travel,Eco,508,5,5,5,2,2,5,2,2,4,2,4,4,4,2,0,0.0,satisfied +26596,30747,Male,disloyal Customer,25,Business travel,Eco,977,3,3,3,4,3,3,3,3,4,2,5,3,1,3,0,0.0,neutral or dissatisfied +26597,74472,Female,Loyal Customer,36,Business travel,Business,2572,4,4,4,4,2,4,5,5,5,5,5,3,5,4,15,11.0,satisfied +26598,16703,Male,Loyal Customer,44,Business travel,Eco,284,5,5,5,5,5,5,5,5,4,4,1,4,2,5,0,11.0,satisfied +26599,67282,Female,Loyal Customer,10,Personal Travel,Eco,1121,2,5,1,4,2,1,2,2,3,5,3,4,5,2,104,90.0,neutral or dissatisfied +26600,32811,Female,Loyal Customer,31,Business travel,Business,163,1,1,1,1,5,5,4,5,2,2,2,5,1,5,0,0.0,satisfied +26601,39447,Female,Loyal Customer,15,Personal Travel,Eco,129,3,5,3,2,2,3,3,2,4,3,4,3,4,2,0,7.0,neutral or dissatisfied +26602,122955,Female,Loyal Customer,29,Business travel,Business,2206,2,2,2,2,4,4,4,4,3,5,4,5,4,4,0,8.0,satisfied +26603,58546,Male,Loyal Customer,49,Business travel,Business,1514,2,2,2,2,1,3,4,2,2,2,2,3,2,3,0,7.0,neutral or dissatisfied +26604,5731,Male,Loyal Customer,51,Personal Travel,Eco Plus,299,2,4,2,3,2,2,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +26605,14720,Female,Loyal Customer,66,Personal Travel,Eco,479,4,1,4,4,5,4,4,4,4,4,4,3,4,3,6,,satisfied +26606,600,Female,Loyal Customer,56,Business travel,Business,134,5,5,5,5,5,4,4,5,5,5,4,5,5,4,0,2.0,satisfied +26607,76344,Female,Loyal Customer,17,Business travel,Business,954,1,3,3,3,1,1,1,4,2,4,4,1,2,1,136,155.0,neutral or dissatisfied +26608,100169,Female,Loyal Customer,68,Personal Travel,Eco,523,3,5,3,2,2,3,5,2,2,3,3,5,2,5,10,0.0,neutral or dissatisfied +26609,78225,Female,Loyal Customer,27,Personal Travel,Eco,259,1,5,0,3,3,0,3,3,2,2,1,5,5,3,2,0.0,neutral or dissatisfied +26610,6658,Female,Loyal Customer,59,Business travel,Business,1524,3,5,5,5,5,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +26611,18781,Male,disloyal Customer,23,Business travel,Eco,448,4,4,4,4,3,4,3,3,5,1,4,4,5,3,1,0.0,satisfied +26612,10966,Female,Loyal Customer,61,Business travel,Eco,216,5,2,2,2,2,1,2,5,5,5,5,2,5,1,0,0.0,satisfied +26613,104956,Male,Loyal Customer,50,Business travel,Business,337,4,4,4,4,3,5,4,5,5,5,5,5,5,4,3,8.0,satisfied +26614,32967,Female,Loyal Customer,70,Personal Travel,Eco,102,2,3,2,1,1,2,1,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +26615,107657,Female,Loyal Customer,31,Business travel,Business,3765,3,3,3,3,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +26616,118249,Male,Loyal Customer,43,Business travel,Business,1849,1,1,1,1,2,4,4,4,4,4,4,3,4,3,3,2.0,satisfied +26617,83099,Male,Loyal Customer,63,Personal Travel,Eco,957,4,4,4,4,3,4,3,3,4,4,5,5,4,3,0,24.0,neutral or dissatisfied +26618,21361,Male,Loyal Customer,61,Personal Travel,Eco,674,1,4,1,1,3,1,3,3,5,3,4,5,4,3,12,0.0,neutral or dissatisfied +26619,121356,Male,Loyal Customer,25,Personal Travel,Eco Plus,347,1,4,2,3,5,2,5,5,4,4,5,3,5,5,62,57.0,neutral or dissatisfied +26620,89330,Male,Loyal Customer,44,Business travel,Business,1587,1,1,1,1,3,5,4,4,4,5,4,4,4,4,5,1.0,satisfied +26621,103669,Female,disloyal Customer,32,Business travel,Business,405,2,2,2,5,4,2,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +26622,64247,Female,Loyal Customer,43,Personal Travel,Eco,1660,4,5,4,2,2,3,1,2,2,4,2,3,2,5,7,11.0,neutral or dissatisfied +26623,69731,Female,Loyal Customer,55,Personal Travel,Eco,1372,3,5,3,2,3,3,3,3,5,5,5,3,4,3,127,136.0,neutral or dissatisfied +26624,76848,Male,Loyal Customer,45,Business travel,Eco,1195,1,2,2,2,1,1,1,1,1,1,3,2,4,1,0,10.0,neutral or dissatisfied +26625,68030,Female,disloyal Customer,46,Business travel,Business,868,3,3,3,2,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +26626,124693,Female,Loyal Customer,22,Business travel,Business,3361,2,4,4,4,2,2,2,2,4,1,4,4,3,2,51,59.0,neutral or dissatisfied +26627,82453,Female,disloyal Customer,20,Business travel,Eco,502,1,0,1,3,2,1,2,2,5,4,4,5,5,2,1,0.0,neutral or dissatisfied +26628,70688,Female,Loyal Customer,26,Personal Travel,Eco,447,1,4,5,4,4,5,4,4,5,4,5,5,5,4,18,14.0,neutral or dissatisfied +26629,105024,Male,Loyal Customer,63,Business travel,Eco,255,3,1,2,2,3,3,3,3,3,5,4,1,3,3,14,7.0,neutral or dissatisfied +26630,53959,Male,Loyal Customer,53,Business travel,Eco,1325,4,2,2,2,4,4,4,4,2,5,2,1,4,4,0,0.0,satisfied +26631,88264,Female,Loyal Customer,22,Business travel,Business,1726,2,2,2,2,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +26632,5238,Male,Loyal Customer,63,Business travel,Eco,293,4,5,2,5,4,4,4,4,4,3,4,1,3,4,0,0.0,neutral or dissatisfied +26633,112016,Male,Loyal Customer,46,Business travel,Business,1689,3,3,3,3,4,5,5,4,4,4,4,4,4,5,37,32.0,satisfied +26634,115290,Female,Loyal Customer,51,Business travel,Business,337,0,0,0,3,3,4,4,4,4,5,5,5,4,3,0,0.0,satisfied +26635,38861,Male,Loyal Customer,9,Personal Travel,Business,2300,5,4,5,4,2,5,4,2,3,5,3,3,3,2,0,0.0,satisfied +26636,122525,Male,Loyal Customer,13,Personal Travel,Business,500,1,3,1,3,4,1,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +26637,58853,Female,disloyal Customer,26,Business travel,Business,888,4,4,4,4,5,4,5,5,3,3,4,5,5,5,40,56.0,satisfied +26638,81574,Male,Loyal Customer,33,Personal Travel,Eco,936,3,5,4,4,3,4,3,3,4,1,5,4,2,3,52,30.0,neutral or dissatisfied +26639,95768,Female,Loyal Customer,17,Personal Travel,Eco,419,1,4,1,4,5,1,5,5,4,3,4,2,2,5,0,0.0,neutral or dissatisfied +26640,59674,Female,Loyal Customer,60,Personal Travel,Eco,965,5,5,5,3,3,4,5,1,1,5,1,3,1,3,0,0.0,satisfied +26641,17151,Female,Loyal Customer,27,Business travel,Eco Plus,696,4,4,4,4,4,4,4,4,3,5,1,4,3,4,0,0.0,satisfied +26642,116579,Female,disloyal Customer,33,Business travel,Business,362,1,2,2,5,1,2,1,1,4,5,4,5,5,1,13,8.0,neutral or dissatisfied +26643,6441,Female,Loyal Customer,59,Personal Travel,Eco,296,5,4,5,3,2,4,4,3,3,5,3,4,3,3,0,0.0,satisfied +26644,97908,Male,Loyal Customer,47,Business travel,Business,1992,1,1,1,1,5,5,4,2,2,2,2,4,2,3,42,31.0,satisfied +26645,111233,Male,Loyal Customer,37,Personal Travel,Eco,1607,3,2,3,3,4,3,4,4,4,2,3,1,4,4,12,19.0,neutral or dissatisfied +26646,39798,Female,Loyal Customer,24,Business travel,Eco,272,0,5,0,5,2,5,2,2,4,4,4,1,2,2,0,0.0,satisfied +26647,76675,Male,Loyal Customer,8,Personal Travel,Eco,516,1,5,1,1,1,1,1,1,4,4,5,5,1,1,0,0.0,neutral or dissatisfied +26648,108224,Male,Loyal Customer,46,Business travel,Business,2871,3,4,1,4,2,4,3,3,3,3,3,2,3,2,9,0.0,neutral or dissatisfied +26649,714,Female,disloyal Customer,37,Business travel,Business,89,4,4,4,3,3,4,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +26650,72216,Female,Loyal Customer,44,Business travel,Business,921,2,2,2,2,3,5,5,3,3,4,3,5,3,5,1,0.0,satisfied +26651,66555,Male,Loyal Customer,66,Personal Travel,Eco,328,3,1,3,3,2,3,2,2,4,3,4,3,4,2,11,20.0,neutral or dissatisfied +26652,33939,Male,disloyal Customer,28,Business travel,Business,1072,4,4,4,3,4,4,4,4,5,3,5,4,1,4,0,0.0,satisfied +26653,49592,Female,disloyal Customer,41,Business travel,Business,304,2,3,3,4,4,2,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +26654,13599,Female,Loyal Customer,54,Personal Travel,Eco,214,2,1,2,3,4,3,3,1,1,2,1,3,1,4,52,46.0,neutral or dissatisfied +26655,92473,Female,Loyal Customer,39,Business travel,Business,2139,1,1,5,1,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +26656,106321,Male,Loyal Customer,53,Business travel,Business,2233,1,1,1,1,3,4,5,5,5,5,5,5,5,4,39,35.0,satisfied +26657,3556,Male,Loyal Customer,39,Business travel,Business,2185,3,1,1,1,2,3,4,3,3,3,3,2,3,2,2,6.0,neutral or dissatisfied +26658,23737,Female,Loyal Customer,23,Personal Travel,Eco Plus,616,2,5,2,4,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +26659,9191,Male,Loyal Customer,43,Personal Travel,Eco,363,1,5,1,5,2,1,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +26660,59529,Male,Loyal Customer,33,Business travel,Business,965,5,4,5,5,4,4,4,4,5,2,5,4,5,4,5,15.0,satisfied +26661,1773,Female,Loyal Customer,53,Business travel,Business,2478,4,4,4,4,5,5,5,3,3,2,3,5,3,3,44,55.0,satisfied +26662,90463,Male,Loyal Customer,41,Business travel,Business,581,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +26663,97383,Male,Loyal Customer,35,Personal Travel,Eco,347,2,4,2,3,1,2,1,1,3,2,4,5,5,1,18,19.0,neutral or dissatisfied +26664,66543,Male,Loyal Customer,42,Business travel,Business,3478,0,1,1,2,5,4,4,5,5,5,5,3,5,3,55,56.0,satisfied +26665,9250,Male,Loyal Customer,24,Personal Travel,Eco,100,3,5,3,3,5,3,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +26666,120412,Male,Loyal Customer,57,Business travel,Business,366,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +26667,84989,Female,disloyal Customer,40,Business travel,Business,1590,5,0,0,1,0,3,3,3,5,4,4,3,5,3,150,134.0,satisfied +26668,54116,Male,Loyal Customer,65,Personal Travel,Business,1400,3,4,2,3,2,1,2,1,1,2,1,4,1,2,41,27.0,neutral or dissatisfied +26669,79419,Male,Loyal Customer,41,Personal Travel,Eco,502,2,5,2,3,3,2,3,3,4,5,5,4,5,3,34,14.0,neutral or dissatisfied +26670,122317,Female,disloyal Customer,22,Business travel,Eco,546,0,4,0,4,5,0,5,5,4,3,4,4,4,5,0,0.0,satisfied +26671,120539,Male,Loyal Customer,48,Business travel,Business,2176,2,4,2,2,2,4,4,5,5,5,5,4,5,4,65,54.0,satisfied +26672,88728,Female,Loyal Customer,45,Personal Travel,Eco,444,3,4,5,2,5,4,4,5,4,5,4,4,3,4,212,213.0,neutral or dissatisfied +26673,51478,Male,Loyal Customer,44,Business travel,Business,3887,5,5,5,5,3,5,4,4,4,4,4,3,4,3,43,21.0,satisfied +26674,87788,Female,Loyal Customer,48,Business travel,Eco,214,2,5,5,5,1,3,3,2,2,2,2,3,2,2,33,26.0,neutral or dissatisfied +26675,52408,Male,Loyal Customer,17,Personal Travel,Eco,455,1,5,1,4,1,1,1,1,3,4,5,5,4,1,0,5.0,neutral or dissatisfied +26676,48789,Female,Loyal Customer,50,Business travel,Business,1822,1,1,1,1,4,4,4,5,5,4,5,5,5,4,7,3.0,satisfied +26677,15240,Female,Loyal Customer,35,Personal Travel,Eco,445,4,4,4,4,1,4,4,1,3,4,5,3,4,1,0,0.0,satisfied +26678,60930,Male,Loyal Customer,49,Business travel,Business,888,4,4,4,4,2,4,5,5,5,5,5,3,5,5,14,8.0,satisfied +26679,113301,Female,disloyal Customer,42,Business travel,Business,407,4,4,4,3,3,4,3,3,4,2,4,4,4,3,6,0.0,neutral or dissatisfied +26680,100268,Male,Loyal Customer,57,Business travel,Business,971,4,4,4,4,4,4,5,3,3,4,3,4,3,3,8,0.0,satisfied +26681,50503,Male,Loyal Customer,12,Personal Travel,Eco,308,4,5,5,2,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +26682,125119,Male,Loyal Customer,36,Personal Travel,Eco,361,1,5,4,3,2,4,2,2,4,2,5,4,4,2,0,3.0,neutral or dissatisfied +26683,57065,Male,Loyal Customer,26,Personal Travel,Business,2065,3,5,3,5,1,3,1,1,5,5,5,5,1,1,0,0.0,neutral or dissatisfied +26684,85515,Female,Loyal Customer,40,Business travel,Business,3276,0,4,0,2,5,4,4,4,4,4,2,4,4,3,3,1.0,satisfied +26685,51570,Female,Loyal Customer,51,Business travel,Business,3058,3,3,3,3,2,4,2,4,4,4,4,3,4,5,0,0.0,satisfied +26686,80265,Male,Loyal Customer,56,Personal Travel,Eco,488,4,0,4,5,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +26687,72270,Female,Loyal Customer,32,Business travel,Business,919,4,4,4,4,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +26688,121590,Male,Loyal Customer,40,Business travel,Eco,632,4,2,3,2,4,4,4,4,5,4,1,3,4,4,0,7.0,satisfied +26689,65360,Male,Loyal Customer,44,Business travel,Business,631,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,3.0,satisfied +26690,100276,Female,Loyal Customer,53,Business travel,Business,2753,3,3,3,3,3,5,4,4,4,4,4,5,4,4,38,50.0,satisfied +26691,9732,Female,Loyal Customer,44,Business travel,Business,926,3,3,3,3,2,4,5,5,5,5,5,4,5,3,8,4.0,satisfied +26692,87243,Female,Loyal Customer,42,Business travel,Business,2055,3,3,3,3,5,5,4,4,4,4,4,5,4,4,0,1.0,satisfied +26693,122209,Male,Loyal Customer,49,Business travel,Business,544,5,5,2,5,2,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +26694,78772,Female,disloyal Customer,22,Business travel,Eco,554,4,4,4,4,5,4,5,5,5,4,5,4,4,5,0,0.0,satisfied +26695,97524,Male,Loyal Customer,58,Business travel,Business,3306,0,0,0,2,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +26696,118013,Female,Loyal Customer,34,Business travel,Business,3676,2,1,1,1,3,4,3,2,2,2,2,3,2,1,5,0.0,neutral or dissatisfied +26697,75678,Female,Loyal Customer,40,Business travel,Business,868,1,1,1,1,3,5,4,4,4,4,4,5,4,3,2,4.0,satisfied +26698,57440,Female,Loyal Customer,46,Business travel,Eco,1735,4,4,4,4,3,1,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +26699,46139,Female,Loyal Customer,44,Business travel,Eco,516,1,5,5,5,4,3,4,2,2,1,2,4,2,1,0,26.0,neutral or dissatisfied +26700,19712,Female,Loyal Customer,48,Business travel,Business,2258,3,3,3,3,4,1,2,5,5,5,5,5,5,5,0,0.0,satisfied +26701,128376,Female,disloyal Customer,35,Business travel,Business,304,1,0,0,2,1,0,1,1,3,3,5,3,4,1,0,18.0,neutral or dissatisfied +26702,124969,Female,Loyal Customer,45,Business travel,Business,3312,3,3,3,3,4,5,4,5,5,5,5,4,5,5,28,34.0,satisfied +26703,22780,Female,Loyal Customer,39,Business travel,Eco,170,4,2,2,2,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +26704,20535,Male,Loyal Customer,57,Business travel,Business,2238,4,4,4,4,4,5,5,5,5,5,5,3,5,3,2,1.0,satisfied +26705,85607,Male,Loyal Customer,31,Personal Travel,Eco,192,2,5,0,5,4,0,4,4,4,2,5,3,5,4,8,4.0,neutral or dissatisfied +26706,112486,Female,Loyal Customer,42,Personal Travel,Eco,850,2,5,2,5,4,4,5,3,3,2,3,3,3,4,1,0.0,neutral or dissatisfied +26707,68336,Female,Loyal Customer,51,Business travel,Business,1598,4,4,4,4,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +26708,32827,Male,Loyal Customer,37,Business travel,Eco,102,5,1,1,1,5,5,5,5,3,3,1,1,2,5,0,0.0,satisfied +26709,84917,Female,Loyal Customer,66,Personal Travel,Eco,547,3,5,3,2,5,5,5,5,5,3,5,3,5,5,37,40.0,neutral or dissatisfied +26710,93428,Female,Loyal Customer,58,Business travel,Business,3273,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +26711,82071,Female,disloyal Customer,46,Business travel,Business,1276,4,4,4,1,4,1,1,5,4,4,5,1,4,1,348,329.0,satisfied +26712,118857,Female,Loyal Customer,67,Personal Travel,Eco Plus,338,3,5,3,3,3,5,5,4,4,3,4,3,4,4,42,54.0,neutral or dissatisfied +26713,38875,Female,Loyal Customer,36,Business travel,Eco,261,4,3,3,3,4,4,4,4,2,3,5,1,2,4,0,2.0,satisfied +26714,78619,Male,Loyal Customer,56,Business travel,Business,1426,4,4,4,4,2,4,5,4,4,3,4,4,4,3,0,11.0,satisfied +26715,27135,Male,Loyal Customer,21,Business travel,Business,2688,2,2,2,2,2,2,2,2,5,4,1,2,4,2,0,11.0,satisfied +26716,118077,Male,Loyal Customer,47,Business travel,Business,1276,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +26717,49124,Male,Loyal Customer,55,Business travel,Eco,109,5,1,1,1,5,5,5,5,4,4,4,3,5,5,8,14.0,satisfied +26718,40968,Female,Loyal Customer,56,Business travel,Business,2692,4,5,5,5,2,4,3,3,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +26719,117085,Male,Loyal Customer,38,Business travel,Business,368,4,4,4,4,3,5,5,4,4,4,4,5,4,4,12,1.0,satisfied +26720,120369,Male,disloyal Customer,74,Business travel,Eco,449,4,0,4,3,3,4,3,3,2,1,4,1,4,3,2,68.0,neutral or dissatisfied +26721,31416,Female,Loyal Customer,27,Business travel,Eco,1546,1,4,4,4,1,1,1,1,3,1,4,3,4,1,6,14.0,neutral or dissatisfied +26722,1776,Male,disloyal Customer,22,Business travel,Eco,408,1,0,1,2,4,1,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +26723,48186,Female,Loyal Customer,55,Business travel,Business,3390,2,4,4,4,5,4,3,2,2,2,2,3,2,2,0,4.0,neutral or dissatisfied +26724,17256,Male,Loyal Customer,63,Business travel,Business,472,4,4,4,4,4,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +26725,100114,Female,Loyal Customer,48,Business travel,Business,523,4,4,4,4,2,5,4,2,2,2,2,4,2,3,0,31.0,satisfied +26726,41935,Female,Loyal Customer,67,Personal Travel,Eco,129,4,5,4,3,3,5,3,4,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +26727,81831,Male,Loyal Customer,64,Personal Travel,Eco,1306,3,5,4,2,3,4,3,3,4,5,5,3,5,3,68,47.0,neutral or dissatisfied +26728,100981,Female,disloyal Customer,27,Business travel,Eco,1162,2,2,2,3,4,2,4,4,2,3,3,1,4,4,43,22.0,neutral or dissatisfied +26729,55514,Male,disloyal Customer,27,Business travel,Business,991,2,2,2,5,3,2,3,3,4,5,5,3,4,3,1,0.0,neutral or dissatisfied +26730,93721,Female,Loyal Customer,20,Business travel,Business,630,3,1,1,1,3,3,3,3,2,4,4,2,4,3,11,3.0,neutral or dissatisfied +26731,28333,Female,disloyal Customer,9,Business travel,Eco,867,2,2,2,4,1,2,1,1,1,2,4,2,3,1,9,4.0,neutral or dissatisfied +26732,38021,Female,Loyal Customer,49,Business travel,Eco,1237,5,2,2,2,4,5,4,5,5,5,5,3,5,2,0,0.0,satisfied +26733,56884,Male,Loyal Customer,52,Business travel,Business,2434,4,4,4,4,4,4,4,4,4,4,4,4,3,4,7,0.0,satisfied +26734,38546,Female,Loyal Customer,43,Business travel,Eco,2586,2,5,5,5,5,3,3,2,2,2,2,4,2,1,0,21.0,neutral or dissatisfied +26735,127027,Male,disloyal Customer,23,Business travel,Eco,355,1,5,1,1,2,1,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +26736,20111,Male,disloyal Customer,23,Business travel,Eco,416,0,1,0,2,3,0,3,3,1,2,2,4,4,3,0,0.0,satisfied +26737,126949,Male,disloyal Customer,41,Business travel,Business,325,5,5,5,3,4,5,4,4,4,4,4,5,5,4,0,11.0,satisfied +26738,19248,Male,Loyal Customer,18,Personal Travel,Eco,782,2,4,2,4,3,2,3,3,4,3,5,3,4,3,7,0.0,neutral or dissatisfied +26739,64865,Female,Loyal Customer,59,Business travel,Eco,551,3,1,1,1,5,4,3,3,3,3,3,1,3,4,52,41.0,neutral or dissatisfied +26740,55786,Male,Loyal Customer,37,Business travel,Business,2400,5,5,5,5,4,4,4,5,4,4,5,4,3,4,0,0.0,satisfied +26741,73649,Male,Loyal Customer,39,Business travel,Business,204,1,1,1,1,3,5,5,4,4,4,5,4,4,4,9,2.0,satisfied +26742,125818,Male,Loyal Customer,30,Business travel,Eco,993,4,4,4,4,4,4,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +26743,79684,Male,Loyal Customer,65,Personal Travel,Eco,749,1,4,0,5,2,0,2,2,4,2,4,5,5,2,1,0.0,neutral or dissatisfied +26744,6185,Male,Loyal Customer,68,Personal Travel,Eco,409,1,2,1,3,3,1,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +26745,96180,Female,disloyal Customer,30,Business travel,Eco,546,1,3,1,3,1,1,1,1,1,5,3,4,3,1,2,6.0,neutral or dissatisfied +26746,44480,Male,disloyal Customer,24,Business travel,Eco,692,2,2,2,3,4,2,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +26747,83200,Male,Loyal Customer,17,Business travel,Business,1939,1,1,1,1,4,4,4,4,3,4,5,4,5,4,43,52.0,satisfied +26748,49628,Female,Loyal Customer,56,Business travel,Eco,109,5,1,1,1,5,4,3,5,5,5,5,5,5,1,47,46.0,satisfied +26749,40977,Female,Loyal Customer,33,Business travel,Eco Plus,601,5,1,4,4,5,5,5,5,4,2,1,1,3,5,0,0.0,satisfied +26750,58851,Male,Loyal Customer,37,Business travel,Business,3034,1,1,1,1,5,4,5,5,5,5,5,3,5,4,127,129.0,satisfied +26751,9671,Male,Loyal Customer,52,Business travel,Eco,277,4,5,5,5,4,4,4,4,4,4,4,3,4,4,68,42.0,neutral or dissatisfied +26752,112257,Female,disloyal Customer,19,Business travel,Business,1447,4,4,4,1,2,4,2,2,3,3,5,4,4,2,39,13.0,satisfied +26753,8681,Male,Loyal Customer,74,Business travel,Business,1940,4,4,4,4,5,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +26754,107940,Female,Loyal Customer,69,Personal Travel,Eco,611,3,5,3,3,2,3,2,5,5,3,5,4,5,1,2,11.0,neutral or dissatisfied +26755,6777,Male,Loyal Customer,55,Business travel,Business,235,1,1,1,1,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +26756,14083,Female,Loyal Customer,39,Business travel,Eco,399,5,3,3,3,5,5,5,5,3,4,2,1,2,5,0,0.0,satisfied +26757,40513,Male,Loyal Customer,16,Business travel,Eco Plus,175,5,4,4,4,5,5,5,5,4,1,2,1,5,5,0,0.0,satisfied +26758,98625,Female,Loyal Customer,49,Business travel,Business,834,2,1,1,1,2,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +26759,95327,Female,Loyal Customer,53,Personal Travel,Eco,187,4,4,0,3,3,4,4,4,4,0,4,3,4,4,6,3.0,neutral or dissatisfied +26760,103626,Female,Loyal Customer,41,Business travel,Business,1516,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +26761,97577,Female,Loyal Customer,59,Business travel,Business,448,4,4,4,4,2,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +26762,104693,Female,disloyal Customer,36,Business travel,Business,159,1,0,0,5,5,0,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +26763,52819,Male,Loyal Customer,66,Personal Travel,Eco,2402,3,4,2,3,5,2,5,5,1,4,3,2,4,5,0,0.0,neutral or dissatisfied +26764,114616,Female,Loyal Customer,34,Business travel,Business,2588,5,5,5,5,5,5,5,4,3,4,5,5,3,5,160,146.0,satisfied +26765,52236,Male,Loyal Customer,60,Business travel,Business,237,5,5,5,5,2,2,4,5,5,5,5,5,5,4,27,24.0,satisfied +26766,73137,Female,Loyal Customer,34,Personal Travel,Eco,1068,4,5,4,4,5,4,5,5,5,2,5,4,4,5,0,9.0,neutral or dissatisfied +26767,85975,Female,Loyal Customer,55,Business travel,Business,2669,1,1,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +26768,56648,Male,disloyal Customer,59,Business travel,Eco,623,3,0,3,1,1,3,1,1,4,4,3,1,4,1,54,46.0,neutral or dissatisfied +26769,40862,Male,Loyal Customer,46,Personal Travel,Eco,588,5,5,5,2,1,5,1,1,5,4,5,5,4,1,10,0.0,satisfied +26770,395,Female,Loyal Customer,54,Business travel,Business,3325,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +26771,24867,Male,Loyal Customer,25,Business travel,Business,356,1,5,5,5,1,2,1,1,2,4,4,2,4,1,0,0.0,neutral or dissatisfied +26772,4567,Female,Loyal Customer,48,Personal Travel,Eco,561,2,4,2,2,2,5,4,1,1,2,1,4,1,4,17,3.0,neutral or dissatisfied +26773,61656,Male,Loyal Customer,65,Business travel,Business,1379,1,4,4,4,3,2,3,1,1,1,1,2,1,4,14,17.0,neutral or dissatisfied +26774,124949,Female,disloyal Customer,23,Business travel,Eco Plus,728,2,1,3,3,3,5,5,3,2,4,4,5,1,5,133,127.0,neutral or dissatisfied +26775,44704,Male,Loyal Customer,70,Personal Travel,Eco,67,3,5,3,2,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +26776,22792,Female,Loyal Customer,56,Business travel,Business,170,0,4,0,4,2,1,2,4,4,5,5,4,4,4,0,5.0,satisfied +26777,46177,Male,Loyal Customer,47,Personal Travel,Eco,627,2,5,2,3,1,2,1,1,3,3,5,3,4,1,0,7.0,neutral or dissatisfied +26778,75595,Female,Loyal Customer,37,Business travel,Business,337,4,2,2,2,5,3,3,4,4,3,4,2,4,4,30,21.0,neutral or dissatisfied +26779,103079,Male,Loyal Customer,14,Personal Travel,Eco,546,3,3,3,1,4,3,1,4,3,1,5,4,3,4,24,8.0,neutral or dissatisfied +26780,59839,Female,disloyal Customer,25,Business travel,Business,1023,4,0,4,5,3,4,5,3,4,2,5,5,4,3,5,0.0,satisfied +26781,61118,Female,Loyal Customer,29,Business travel,Business,846,3,3,3,3,4,4,4,4,4,2,4,5,4,4,0,4.0,satisfied +26782,81338,Male,Loyal Customer,41,Business travel,Business,1299,3,3,3,3,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +26783,59564,Female,Loyal Customer,28,Business travel,Business,964,3,3,3,3,4,4,4,4,5,4,5,3,5,4,4,0.0,satisfied +26784,99749,Female,disloyal Customer,29,Business travel,Eco,255,2,1,2,2,5,2,5,5,3,3,1,3,2,5,33,19.0,neutral or dissatisfied +26785,65604,Female,Loyal Customer,16,Business travel,Business,2150,1,1,1,1,5,5,5,5,2,1,1,2,4,5,0,0.0,satisfied +26786,117571,Male,Loyal Customer,27,Business travel,Eco,347,2,1,2,1,2,2,2,2,2,5,3,1,4,2,8,0.0,neutral or dissatisfied +26787,47275,Female,Loyal Customer,50,Business travel,Eco,584,4,4,2,2,3,1,2,4,4,4,4,1,4,2,0,0.0,satisfied +26788,122532,Male,Loyal Customer,29,Business travel,Business,3265,4,4,2,4,5,4,5,5,5,3,5,3,5,5,4,1.0,satisfied +26789,100822,Female,Loyal Customer,39,Business travel,Business,711,5,5,5,5,2,4,4,5,5,4,5,3,5,3,7,0.0,satisfied +26790,104310,Male,Loyal Customer,38,Personal Travel,Business,409,3,4,2,1,2,5,4,5,5,2,4,4,5,4,1,13.0,neutral or dissatisfied +26791,30557,Male,Loyal Customer,52,Business travel,Business,2014,3,1,1,1,5,4,3,3,3,3,3,1,3,3,56,55.0,neutral or dissatisfied +26792,59011,Male,Loyal Customer,45,Business travel,Business,1744,1,4,4,4,5,1,3,1,1,1,1,3,1,1,5,16.0,neutral or dissatisfied +26793,92069,Female,Loyal Customer,29,Business travel,Eco,1535,2,1,1,1,2,2,2,2,2,2,3,3,2,2,0,0.0,neutral or dissatisfied +26794,9264,Male,Loyal Customer,49,Business travel,Business,2508,5,5,5,5,4,5,5,4,4,4,4,5,4,3,55,38.0,satisfied +26795,16677,Female,Loyal Customer,67,Personal Travel,Eco,488,2,3,2,4,3,4,4,5,5,2,5,3,5,4,0,33.0,neutral or dissatisfied +26796,107485,Female,Loyal Customer,33,Business travel,Business,2232,3,3,2,3,5,5,5,5,5,5,5,5,5,5,7,0.0,satisfied +26797,16838,Male,Loyal Customer,59,Personal Travel,Eco,645,2,3,2,4,4,2,4,4,4,3,5,2,5,4,6,9.0,neutral or dissatisfied +26798,103828,Female,Loyal Customer,56,Business travel,Eco,882,1,5,4,5,5,4,3,1,1,1,1,3,1,1,40,25.0,neutral or dissatisfied +26799,84843,Female,Loyal Customer,31,Business travel,Business,3389,3,1,1,1,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +26800,121557,Female,Loyal Customer,56,Business travel,Business,2689,4,2,2,2,2,2,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +26801,91781,Male,Loyal Customer,40,Personal Travel,Eco,626,4,5,4,2,5,4,4,5,5,4,4,3,5,5,0,0.0,satisfied +26802,116441,Male,Loyal Customer,52,Personal Travel,Eco,308,3,5,3,3,1,3,1,1,3,2,4,4,4,1,93,83.0,neutral or dissatisfied +26803,58139,Female,disloyal Customer,16,Business travel,Eco,925,2,2,2,4,4,2,4,4,5,5,5,4,4,4,4,0.0,neutral or dissatisfied +26804,129204,Female,Loyal Customer,39,Business travel,Eco,2419,2,2,2,2,2,2,2,2,2,4,2,2,3,2,4,0.0,neutral or dissatisfied +26805,23680,Female,disloyal Customer,54,Business travel,Eco,212,2,5,2,3,3,2,3,3,4,5,2,2,4,3,0,0.0,neutral or dissatisfied +26806,119005,Male,Loyal Customer,32,Personal Travel,Eco,459,1,4,1,3,4,1,4,4,2,5,1,4,4,4,0,0.0,neutral or dissatisfied +26807,45989,Female,Loyal Customer,20,Business travel,Business,483,2,4,1,4,2,2,2,2,2,1,4,3,4,2,79,88.0,neutral or dissatisfied +26808,74835,Female,Loyal Customer,11,Business travel,Eco,1797,2,1,1,1,2,2,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +26809,73602,Male,Loyal Customer,49,Business travel,Business,204,4,4,4,4,2,4,5,3,3,4,4,3,3,3,0,0.0,satisfied +26810,73232,Female,Loyal Customer,50,Personal Travel,Eco,946,3,1,3,4,2,2,3,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +26811,51584,Male,Loyal Customer,47,Business travel,Eco,451,2,4,4,4,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +26812,79804,Male,Loyal Customer,49,Business travel,Business,3629,1,1,3,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +26813,121068,Female,Loyal Customer,25,Business travel,Business,861,2,2,2,2,2,2,2,2,5,4,4,5,5,2,0,0.0,satisfied +26814,19572,Male,Loyal Customer,27,Business travel,Business,3891,1,1,1,1,5,5,4,5,4,5,4,5,1,5,3,0.0,satisfied +26815,8479,Female,Loyal Customer,20,Personal Travel,Eco,1187,2,4,2,2,1,2,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +26816,103954,Female,Loyal Customer,33,Business travel,Business,3101,3,1,3,3,4,3,4,3,3,3,3,3,3,3,27,27.0,neutral or dissatisfied +26817,110731,Male,Loyal Customer,58,Business travel,Business,3033,4,4,4,4,2,4,5,4,4,5,4,5,4,5,19,27.0,satisfied +26818,21160,Female,Loyal Customer,59,Personal Travel,Eco,954,2,5,2,4,3,4,5,1,1,2,1,5,1,5,23,13.0,neutral or dissatisfied +26819,23824,Male,Loyal Customer,65,Business travel,Eco Plus,374,4,2,2,2,4,4,4,4,4,2,3,3,4,4,0,0.0,satisfied +26820,129665,Female,disloyal Customer,49,Business travel,Business,308,4,4,4,4,5,4,5,5,3,2,4,4,5,5,0,6.0,satisfied +26821,75689,Female,Loyal Customer,50,Business travel,Business,3001,5,5,3,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +26822,126987,Male,Loyal Customer,57,Business travel,Business,2815,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +26823,80245,Male,disloyal Customer,54,Business travel,Eco,869,1,1,1,3,1,1,1,1,5,1,3,2,5,1,0,0.0,neutral or dissatisfied +26824,33832,Male,disloyal Customer,22,Business travel,Business,1162,0,0,0,2,5,0,4,5,5,4,5,5,5,5,1,0.0,satisfied +26825,19605,Female,Loyal Customer,33,Business travel,Eco Plus,108,4,4,5,5,4,4,4,4,2,5,1,4,3,4,21,17.0,satisfied +26826,101411,Male,Loyal Customer,13,Personal Travel,Eco,486,2,4,2,3,1,2,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +26827,56018,Male,Loyal Customer,23,Business travel,Business,2475,5,5,5,5,4,4,4,3,2,4,5,4,3,4,0,31.0,satisfied +26828,6315,Male,Loyal Customer,38,Business travel,Business,2173,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +26829,17709,Male,Loyal Customer,39,Personal Travel,Eco,311,4,4,4,4,1,4,1,1,3,2,4,4,5,1,0,0.0,satisfied +26830,8476,Male,Loyal Customer,65,Business travel,Eco,1187,3,2,2,2,3,3,3,3,3,1,4,1,3,3,25,18.0,neutral or dissatisfied +26831,83189,Male,Loyal Customer,11,Personal Travel,Business,1123,3,4,2,1,1,2,2,1,5,4,4,5,5,1,3,1.0,neutral or dissatisfied +26832,22918,Female,Loyal Customer,13,Personal Travel,Eco,630,5,4,5,5,4,5,4,4,1,5,4,3,5,4,0,0.0,satisfied +26833,24307,Female,Loyal Customer,25,Business travel,Eco Plus,302,5,4,4,4,5,4,4,5,3,5,4,3,3,5,0,0.0,satisfied +26834,109624,Male,Loyal Customer,45,Business travel,Business,2042,4,4,4,4,2,5,5,5,5,5,5,3,5,3,23,16.0,satisfied +26835,10024,Female,Loyal Customer,46,Business travel,Business,3975,1,1,1,1,3,4,5,4,4,4,4,4,4,4,0,11.0,satisfied +26836,44869,Female,Loyal Customer,34,Business travel,Business,315,5,5,5,5,2,5,1,5,5,5,5,1,5,5,39,26.0,satisfied +26837,49084,Female,disloyal Customer,26,Business travel,Eco,77,1,1,1,3,2,1,2,2,3,4,3,3,3,2,111,117.0,neutral or dissatisfied +26838,42378,Female,Loyal Customer,34,Personal Travel,Eco,462,3,2,3,3,4,3,4,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +26839,15119,Female,disloyal Customer,22,Business travel,Eco,912,1,1,1,1,5,1,5,5,2,3,3,3,2,5,0,0.0,neutral or dissatisfied +26840,37149,Female,disloyal Customer,37,Business travel,Eco,1046,3,3,3,3,3,3,3,3,3,1,4,5,3,3,0,0.0,satisfied +26841,37377,Male,Loyal Customer,21,Business travel,Business,1041,1,1,1,1,4,4,4,4,2,5,4,4,4,4,0,12.0,satisfied +26842,107329,Male,disloyal Customer,43,Business travel,Business,584,5,5,5,4,5,5,5,5,5,2,5,4,4,5,13,3.0,satisfied +26843,116696,Female,Loyal Customer,39,Business travel,Eco Plus,404,2,3,3,3,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +26844,81850,Female,Loyal Customer,16,Personal Travel,Eco,1306,2,5,2,4,1,2,1,1,5,5,5,4,4,1,1,0.0,neutral or dissatisfied +26845,76602,Female,Loyal Customer,38,Business travel,Eco,481,3,4,4,4,3,4,3,3,3,2,3,1,3,3,0,19.0,neutral or dissatisfied +26846,76702,Male,Loyal Customer,15,Personal Travel,Eco,481,3,4,3,3,1,3,1,1,3,2,3,3,3,1,6,7.0,neutral or dissatisfied +26847,46269,Male,Loyal Customer,23,Personal Travel,Eco,752,3,4,2,4,2,2,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +26848,36447,Female,disloyal Customer,9,Business travel,Eco,1368,2,2,2,4,5,2,3,5,2,1,4,1,3,5,0,4.0,neutral or dissatisfied +26849,46813,Female,Loyal Customer,33,Business travel,Business,819,4,4,4,4,4,4,3,2,2,2,2,2,2,2,0,18.0,satisfied +26850,104408,Female,Loyal Customer,23,Business travel,Business,2848,1,1,1,1,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +26851,125016,Male,Loyal Customer,64,Personal Travel,Eco,184,4,4,4,2,5,4,5,5,4,5,5,5,5,5,3,0.0,neutral or dissatisfied +26852,56954,Male,Loyal Customer,59,Business travel,Business,2454,4,4,3,4,5,5,5,4,3,5,4,5,3,5,0,0.0,satisfied +26853,6822,Female,Loyal Customer,50,Personal Travel,Eco,224,1,5,1,2,2,4,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +26854,60012,Male,Loyal Customer,55,Personal Travel,Eco,1065,4,4,4,1,5,4,2,5,4,2,4,5,5,5,30,0.0,neutral or dissatisfied +26855,2341,Female,disloyal Customer,30,Business travel,Eco Plus,672,4,3,3,4,4,3,4,4,2,3,4,3,3,4,0,0.0,neutral or dissatisfied +26856,48838,Female,Loyal Customer,60,Personal Travel,Business,308,2,3,2,1,1,3,5,5,5,2,5,2,5,2,30,16.0,neutral or dissatisfied +26857,8102,Male,Loyal Customer,33,Business travel,Business,2967,2,2,2,2,5,5,5,5,3,5,4,5,4,5,0,11.0,satisfied +26858,9501,Female,Loyal Customer,22,Business travel,Business,322,3,3,3,3,4,4,4,4,2,4,2,3,5,4,2,0.0,satisfied +26859,78646,Female,Loyal Customer,27,Business travel,Business,2172,2,2,2,2,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +26860,4021,Female,disloyal Customer,27,Business travel,Business,479,2,2,2,2,2,2,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +26861,37958,Female,Loyal Customer,56,Business travel,Business,1121,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +26862,18051,Female,Loyal Customer,29,Business travel,Eco,488,4,2,2,2,4,4,4,4,2,4,3,3,2,4,2,34.0,satisfied +26863,111405,Male,Loyal Customer,42,Personal Travel,Eco,1050,2,5,3,2,5,3,5,5,4,5,5,3,4,5,2,21.0,neutral or dissatisfied +26864,79467,Female,Loyal Customer,31,Personal Travel,Eco,1183,3,4,3,5,3,3,3,3,5,5,5,4,5,3,120,88.0,neutral or dissatisfied +26865,80982,Female,disloyal Customer,72,Business travel,Eco,297,2,4,2,3,3,2,5,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +26866,90884,Male,Loyal Customer,23,Business travel,Business,1654,4,4,4,4,2,2,2,2,3,3,5,4,5,2,0,0.0,satisfied +26867,121270,Male,Loyal Customer,11,Personal Travel,Eco,2075,3,4,3,2,3,3,3,3,1,4,4,4,4,3,4,65.0,neutral or dissatisfied +26868,44626,Female,Loyal Customer,39,Business travel,Business,3361,3,3,5,3,5,5,5,4,2,4,5,5,5,5,133,124.0,satisfied +26869,55151,Female,Loyal Customer,65,Personal Travel,Eco,1635,1,5,1,3,3,5,5,3,3,1,3,4,3,4,1,27.0,neutral or dissatisfied +26870,108819,Female,Loyal Customer,15,Personal Travel,Eco Plus,581,3,4,3,5,5,3,5,5,5,4,2,3,1,5,36,60.0,neutral or dissatisfied +26871,117583,Male,Loyal Customer,54,Business travel,Business,347,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +26872,10935,Male,Loyal Customer,60,Business travel,Business,2360,3,3,3,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +26873,33584,Male,Loyal Customer,43,Business travel,Business,3288,5,5,5,5,2,4,2,4,4,4,4,3,4,4,11,0.0,satisfied +26874,30208,Female,Loyal Customer,26,Personal Travel,Eco Plus,539,3,4,3,4,3,3,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +26875,68546,Female,Loyal Customer,26,Personal Travel,Eco,1013,2,2,2,2,3,2,1,3,1,5,2,2,2,3,0,0.0,neutral or dissatisfied +26876,103487,Female,Loyal Customer,17,Personal Travel,Eco,382,1,5,3,4,2,3,2,2,5,5,4,4,5,2,17,13.0,neutral or dissatisfied +26877,46689,Female,Loyal Customer,36,Personal Travel,Eco,125,2,3,2,2,1,2,1,1,1,5,2,1,2,1,71,78.0,neutral or dissatisfied +26878,65124,Female,Loyal Customer,10,Personal Travel,Eco,247,2,1,2,3,5,2,5,5,4,4,2,3,3,5,1,2.0,neutral or dissatisfied +26879,116197,Male,Loyal Customer,65,Personal Travel,Eco,446,2,5,2,4,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +26880,78697,Male,Loyal Customer,60,Business travel,Business,2016,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +26881,49188,Female,Loyal Customer,57,Business travel,Business,86,1,1,1,1,1,1,2,5,5,5,3,3,5,5,0,0.0,satisfied +26882,77835,Female,Loyal Customer,62,Personal Travel,Eco,874,1,5,2,4,3,5,4,4,4,2,4,5,4,5,19,13.0,neutral or dissatisfied +26883,37123,Female,Loyal Customer,52,Business travel,Business,3740,5,5,5,5,1,5,2,4,4,4,4,2,4,5,0,0.0,satisfied +26884,72094,Female,Loyal Customer,67,Personal Travel,Eco,2556,2,3,2,3,5,3,2,2,2,2,3,1,2,2,0,0.0,neutral or dissatisfied +26885,97459,Female,disloyal Customer,25,Business travel,Business,822,3,5,3,3,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +26886,127838,Male,disloyal Customer,21,Business travel,Business,1044,4,0,5,2,3,5,3,3,4,5,5,3,4,3,0,0.0,satisfied +26887,119861,Male,Loyal Customer,30,Personal Travel,Eco,912,3,5,3,3,1,3,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +26888,85682,Male,Loyal Customer,40,Business travel,Business,1547,5,5,5,5,5,4,5,5,5,5,5,4,5,4,7,0.0,satisfied +26889,58305,Female,Loyal Customer,52,Business travel,Business,1739,5,5,5,5,2,3,4,5,5,5,5,5,5,4,1,26.0,satisfied +26890,80848,Female,Loyal Customer,23,Business travel,Business,484,3,5,2,5,3,2,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +26891,4459,Male,Loyal Customer,25,Personal Travel,Business,1005,1,4,2,4,2,2,4,2,5,4,4,3,4,2,36,24.0,neutral or dissatisfied +26892,4333,Female,Loyal Customer,18,Business travel,Business,3648,5,5,5,5,3,3,3,3,4,5,4,4,4,3,0,0.0,satisfied +26893,46524,Male,disloyal Customer,55,Business travel,Eco,73,5,0,5,4,5,2,2,4,4,3,2,2,3,2,151,136.0,satisfied +26894,99769,Female,Loyal Customer,26,Business travel,Business,255,5,5,5,5,4,4,4,4,5,4,5,4,4,4,16,11.0,satisfied +26895,93025,Female,Loyal Customer,49,Personal Travel,Eco,1524,2,4,2,4,4,3,4,3,3,2,5,4,3,5,12,0.0,neutral or dissatisfied +26896,100199,Male,Loyal Customer,56,Business travel,Business,2590,1,1,1,1,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +26897,128072,Male,Loyal Customer,52,Business travel,Business,2979,5,5,5,5,2,2,2,4,5,4,4,2,5,2,0,0.0,satisfied +26898,77544,Female,disloyal Customer,37,Business travel,Eco,986,2,3,3,3,2,3,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +26899,18998,Female,Loyal Customer,53,Business travel,Business,788,5,5,5,5,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +26900,70027,Male,disloyal Customer,26,Business travel,Business,583,1,1,1,3,2,1,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +26901,81896,Male,disloyal Customer,27,Business travel,Business,680,4,4,4,3,4,4,4,4,4,5,4,4,5,4,2,7.0,satisfied +26902,46095,Male,Loyal Customer,29,Business travel,Eco Plus,541,2,4,4,4,2,2,2,2,3,5,2,3,2,2,12,44.0,neutral or dissatisfied +26903,68948,Male,Loyal Customer,34,Personal Travel,Eco,646,3,3,3,3,2,3,2,2,1,2,3,2,3,2,0,0.0,neutral or dissatisfied +26904,29261,Female,Loyal Customer,41,Business travel,Business,550,3,2,2,2,3,3,3,3,3,3,3,2,3,3,0,25.0,neutral or dissatisfied +26905,106238,Female,disloyal Customer,20,Business travel,Eco Plus,471,3,4,3,3,4,3,4,4,1,3,3,4,4,4,36,28.0,neutral or dissatisfied +26906,67535,Female,Loyal Customer,47,Business travel,Business,1464,2,1,1,1,4,4,3,2,2,3,2,4,2,4,2,21.0,neutral or dissatisfied +26907,127494,Male,Loyal Customer,21,Personal Travel,Eco,1814,1,4,1,3,4,1,3,4,4,5,4,4,4,4,10,0.0,neutral or dissatisfied +26908,39015,Female,Loyal Customer,32,Business travel,Eco,113,4,1,1,1,4,5,4,4,1,1,1,5,1,4,0,0.0,satisfied +26909,32717,Female,disloyal Customer,43,Business travel,Eco,101,3,4,3,2,5,3,5,5,2,3,2,4,2,5,0,4.0,neutral or dissatisfied +26910,89986,Female,Loyal Customer,26,Business travel,Eco Plus,1501,1,2,2,2,1,1,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +26911,123134,Female,Loyal Customer,27,Business travel,Eco,468,2,4,4,4,2,2,2,2,2,1,2,4,2,2,0,0.0,neutral or dissatisfied +26912,75655,Male,disloyal Customer,22,Business travel,Eco,304,2,3,2,3,2,2,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +26913,100785,Female,Loyal Customer,30,Personal Travel,Eco,1411,2,3,3,1,3,3,3,4,2,4,5,3,2,3,183,,neutral or dissatisfied +26914,125260,Female,Loyal Customer,39,Personal Travel,Business,1488,2,3,2,3,3,3,4,4,4,2,5,3,4,1,0,11.0,neutral or dissatisfied +26915,119774,Male,disloyal Customer,24,Business travel,Eco,936,4,4,4,3,2,4,2,2,4,2,3,3,3,2,0,13.0,neutral or dissatisfied +26916,46190,Female,Loyal Customer,49,Business travel,Eco,472,2,1,1,1,3,4,4,2,2,2,2,1,2,4,28,48.0,neutral or dissatisfied +26917,4002,Female,Loyal Customer,52,Business travel,Business,3484,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +26918,69607,Male,Loyal Customer,33,Personal Travel,Eco,2475,4,5,4,1,4,2,2,1,3,4,2,2,4,2,0,0.0,neutral or dissatisfied +26919,20147,Male,disloyal Customer,17,Business travel,Eco,403,2,3,2,3,3,2,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +26920,17557,Female,Loyal Customer,40,Business travel,Eco,852,5,4,4,4,5,4,5,5,5,4,2,3,4,5,0,0.0,satisfied +26921,17880,Female,Loyal Customer,10,Personal Travel,Eco,425,1,2,1,4,4,1,4,4,1,3,3,2,3,4,0,0.0,neutral or dissatisfied +26922,105056,Male,Loyal Customer,62,Personal Travel,Eco,255,3,3,3,3,2,3,2,2,4,5,4,2,3,2,7,0.0,neutral or dissatisfied +26923,77031,Female,Loyal Customer,49,Personal Travel,Eco,368,1,3,1,4,4,2,5,5,5,1,5,2,5,2,1,0.0,neutral or dissatisfied +26924,26688,Male,Loyal Customer,58,Personal Travel,Eco,406,0,4,0,4,3,0,3,3,5,5,4,4,5,3,0,0.0,satisfied +26925,124842,Male,Loyal Customer,63,Personal Travel,Eco,280,2,5,2,2,5,2,5,5,4,5,4,3,5,5,1,7.0,neutral or dissatisfied +26926,49396,Male,disloyal Customer,40,Business travel,Eco,109,2,0,2,4,4,2,4,4,3,4,5,3,2,4,0,0.0,neutral or dissatisfied +26927,45871,Male,Loyal Customer,25,Business travel,Business,2674,2,2,2,2,5,5,5,5,1,2,5,3,5,5,0,0.0,satisfied +26928,119311,Female,Loyal Customer,54,Business travel,Business,214,0,3,0,2,5,1,5,5,5,5,5,3,5,2,0,0.0,satisfied +26929,14405,Female,Loyal Customer,56,Business travel,Eco Plus,789,4,4,4,4,1,1,5,4,4,4,4,4,4,2,0,0.0,satisfied +26930,69103,Female,disloyal Customer,41,Business travel,Eco Plus,1389,3,3,3,3,4,3,4,4,3,1,3,3,3,4,0,11.0,neutral or dissatisfied +26931,41292,Male,Loyal Customer,19,Business travel,Business,3436,4,4,4,4,3,3,3,3,3,1,2,2,4,3,0,0.0,satisfied +26932,74339,Female,Loyal Customer,54,Personal Travel,Business,1235,1,5,1,4,2,1,5,4,4,1,4,1,4,1,1,0.0,neutral or dissatisfied +26933,82043,Female,Loyal Customer,22,Personal Travel,Eco,1589,3,4,3,4,3,3,3,3,4,2,3,4,5,3,0,0.0,neutral or dissatisfied +26934,60020,Female,Loyal Customer,61,Personal Travel,Eco,1068,2,4,2,1,3,1,2,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +26935,32460,Female,Loyal Customer,40,Business travel,Business,1700,0,3,0,3,4,2,5,3,3,5,5,3,3,2,0,0.0,satisfied +26936,30707,Male,disloyal Customer,25,Business travel,Eco,464,1,2,1,3,1,4,4,2,5,3,2,4,4,4,245,243.0,neutral or dissatisfied +26937,97567,Female,Loyal Customer,42,Business travel,Business,448,1,1,4,1,3,5,5,2,2,2,2,5,2,5,2,0.0,satisfied +26938,41595,Male,Loyal Customer,66,Personal Travel,Eco,1464,2,4,2,4,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +26939,71857,Female,Loyal Customer,75,Business travel,Business,1892,1,1,5,1,3,2,4,5,5,5,5,4,5,1,4,0.0,satisfied +26940,95911,Male,disloyal Customer,22,Business travel,Eco,359,2,1,2,4,3,2,3,3,4,1,3,1,4,3,3,0.0,neutral or dissatisfied +26941,23358,Male,Loyal Customer,35,Business travel,Eco Plus,563,4,1,1,1,4,4,4,4,2,4,2,4,5,4,0,24.0,satisfied +26942,113339,Male,Loyal Customer,46,Business travel,Business,386,5,5,5,5,4,4,4,5,5,5,5,3,5,4,13,7.0,satisfied +26943,15395,Male,disloyal Customer,44,Business travel,Eco,306,2,4,2,3,1,2,1,1,2,3,4,2,5,1,0,0.0,neutral or dissatisfied +26944,23113,Female,Loyal Customer,49,Business travel,Business,2976,3,3,3,3,3,4,2,4,4,4,4,4,4,3,1,37.0,satisfied +26945,122480,Female,Loyal Customer,48,Business travel,Business,2338,5,5,5,5,3,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +26946,104509,Male,Loyal Customer,28,Personal Travel,Eco,1609,3,5,3,3,3,3,2,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +26947,105400,Female,Loyal Customer,30,Personal Travel,Eco,369,2,2,2,3,5,2,5,5,3,1,3,4,4,5,76,81.0,neutral or dissatisfied +26948,33417,Male,Loyal Customer,25,Business travel,Eco,2349,1,5,5,5,1,1,3,1,2,5,2,2,3,1,0,0.0,neutral or dissatisfied +26949,39501,Female,disloyal Customer,45,Business travel,Eco,852,2,2,2,3,5,2,5,5,5,2,1,3,1,5,0,2.0,neutral or dissatisfied +26950,114808,Female,Loyal Customer,46,Business travel,Business,404,3,3,3,3,3,5,4,3,3,4,3,5,3,4,7,2.0,satisfied +26951,124677,Female,Loyal Customer,30,Business travel,Business,399,5,5,5,5,4,4,4,4,5,2,4,4,5,4,0,0.0,satisfied +26952,78107,Female,Loyal Customer,53,Personal Travel,Eco,655,3,2,3,2,4,3,2,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +26953,55279,Male,Loyal Customer,35,Personal Travel,Business,1608,4,5,4,2,2,3,4,2,2,4,2,4,2,3,3,2.0,neutral or dissatisfied +26954,12084,Female,Loyal Customer,62,Personal Travel,Eco Plus,351,3,5,3,3,5,5,4,1,1,3,3,3,1,4,1,5.0,neutral or dissatisfied +26955,7755,Male,Loyal Customer,10,Personal Travel,Eco,1013,1,2,1,3,3,1,3,3,1,3,3,1,3,3,0,0.0,neutral or dissatisfied +26956,7402,Female,disloyal Customer,24,Business travel,Eco,522,3,0,3,1,4,3,5,4,5,2,4,5,5,4,2,0.0,neutral or dissatisfied +26957,62458,Female,Loyal Customer,25,Business travel,Business,1723,3,3,3,3,3,2,3,3,1,5,2,2,4,3,59,47.0,neutral or dissatisfied +26958,63916,Female,Loyal Customer,24,Business travel,Business,3521,3,3,3,3,3,4,3,3,5,2,4,3,1,3,0,0.0,satisfied +26959,55179,Female,Loyal Customer,46,Business travel,Business,1346,4,4,4,4,3,5,5,3,3,2,3,5,3,3,0,0.0,satisfied +26960,114373,Male,Loyal Customer,49,Business travel,Business,2017,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +26961,17078,Female,Loyal Customer,11,Personal Travel,Business,416,3,5,5,2,5,5,5,5,2,2,4,1,5,5,0,0.0,neutral or dissatisfied +26962,67861,Female,Loyal Customer,16,Personal Travel,Eco,1126,3,4,3,1,4,3,2,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +26963,70924,Male,Loyal Customer,30,Business travel,Business,612,4,4,4,4,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +26964,65088,Male,Loyal Customer,53,Personal Travel,Eco,190,3,3,3,3,4,3,4,4,2,1,3,4,4,4,0,0.0,neutral or dissatisfied +26965,107486,Female,disloyal Customer,32,Business travel,Eco,711,3,3,3,4,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +26966,51732,Female,Loyal Customer,61,Personal Travel,Eco,509,3,4,4,1,2,4,4,1,1,4,1,4,1,4,35,19.0,neutral or dissatisfied +26967,81386,Male,Loyal Customer,54,Business travel,Business,2238,2,2,2,2,5,4,4,4,4,4,4,5,4,5,8,0.0,satisfied +26968,88113,Male,disloyal Customer,25,Business travel,Business,223,5,0,5,1,4,5,4,4,3,3,4,4,5,4,8,14.0,satisfied +26969,79095,Male,Loyal Customer,38,Personal Travel,Eco,356,1,5,1,2,5,1,5,5,4,3,4,3,4,5,0,1.0,neutral or dissatisfied +26970,64541,Male,Loyal Customer,39,Business travel,Business,3308,3,3,3,3,5,5,4,4,4,5,5,4,4,3,0,0.0,satisfied +26971,39077,Male,Loyal Customer,26,Personal Travel,Eco,1174,5,5,5,5,2,5,2,2,3,5,5,5,5,2,0,0.0,satisfied +26972,117143,Female,Loyal Customer,30,Personal Travel,Eco,451,3,4,3,3,2,3,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +26973,72167,Female,Loyal Customer,26,Personal Travel,Eco Plus,731,2,2,2,4,4,2,4,4,4,3,3,3,4,4,0,0.0,neutral or dissatisfied +26974,87128,Female,Loyal Customer,34,Personal Travel,Eco,645,2,5,2,3,3,2,3,3,3,4,4,4,5,3,122,118.0,neutral or dissatisfied +26975,54217,Female,Loyal Customer,48,Business travel,Business,2537,3,1,2,1,5,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +26976,73993,Male,Loyal Customer,26,Business travel,Business,1972,1,1,1,1,5,5,5,5,3,5,4,3,4,5,20,0.0,satisfied +26977,65024,Female,Loyal Customer,7,Personal Travel,Eco,247,1,4,1,1,3,1,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +26978,91206,Female,Loyal Customer,65,Personal Travel,Eco,406,3,4,3,2,2,4,5,2,2,3,2,5,2,4,6,0.0,neutral or dissatisfied +26979,125124,Female,Loyal Customer,20,Personal Travel,Eco,361,5,5,1,3,1,1,1,1,4,1,4,1,5,1,0,0.0,satisfied +26980,105471,Female,Loyal Customer,47,Business travel,Business,3285,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,1.0,satisfied +26981,114880,Male,disloyal Customer,47,Business travel,Business,480,3,3,3,5,3,3,3,3,5,2,5,3,4,3,34,27.0,neutral or dissatisfied +26982,117343,Female,Loyal Customer,42,Business travel,Business,296,2,2,2,2,2,5,4,5,5,5,5,4,5,4,4,1.0,satisfied +26983,99332,Female,Loyal Customer,22,Personal Travel,Eco,337,2,5,2,5,2,1,1,5,5,1,1,1,5,1,148,229.0,neutral or dissatisfied +26984,77163,Male,Loyal Customer,58,Personal Travel,Eco,1450,5,4,5,1,3,5,3,3,4,1,4,3,4,3,0,0.0,satisfied +26985,11627,Female,Loyal Customer,60,Business travel,Business,657,2,2,2,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +26986,89226,Male,Loyal Customer,49,Personal Travel,Eco,2116,2,4,2,3,5,2,5,5,4,5,4,5,1,5,0,0.0,neutral or dissatisfied +26987,99495,Female,Loyal Customer,69,Personal Travel,Eco,307,5,5,5,2,5,4,5,4,4,5,4,5,4,3,13,16.0,satisfied +26988,26740,Male,Loyal Customer,43,Personal Travel,Eco Plus,270,4,4,4,1,5,4,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +26989,113813,Female,Loyal Customer,46,Business travel,Eco Plus,386,4,2,1,2,2,5,5,4,4,4,4,3,4,1,3,0.0,satisfied +26990,22196,Female,Loyal Customer,18,Personal Travel,Eco,533,0,5,0,2,1,0,1,1,4,2,4,4,4,1,106,90.0,satisfied +26991,120335,Female,Loyal Customer,22,Business travel,Eco Plus,268,3,2,2,2,3,3,4,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +26992,82615,Female,Loyal Customer,73,Business travel,Business,1567,4,4,4,4,5,4,1,4,4,4,5,4,4,5,0,0.0,satisfied +26993,12956,Female,disloyal Customer,38,Business travel,Eco Plus,456,4,4,4,4,3,4,3,3,5,1,5,3,1,3,28,22.0,neutral or dissatisfied +26994,95018,Male,Loyal Customer,28,Personal Travel,Eco,239,3,4,0,3,3,0,3,3,1,5,5,1,4,3,0,0.0,neutral or dissatisfied +26995,31196,Male,Loyal Customer,39,Business travel,Business,3070,3,3,2,3,4,3,2,5,5,5,5,2,5,3,0,0.0,satisfied +26996,100346,Female,Loyal Customer,17,Personal Travel,Eco,1079,2,4,2,1,3,2,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +26997,106686,Female,Loyal Customer,37,Business travel,Eco Plus,451,3,2,2,2,3,3,3,3,4,2,3,4,3,3,84,78.0,neutral or dissatisfied +26998,97342,Male,Loyal Customer,37,Business travel,Business,347,2,2,2,2,1,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +26999,98447,Female,Loyal Customer,49,Personal Travel,Eco,814,2,0,2,1,5,4,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +27000,4750,Female,Loyal Customer,22,Business travel,Business,888,5,5,5,5,4,4,4,4,5,5,5,5,5,4,88,98.0,satisfied +27001,60210,Male,Loyal Customer,35,Business travel,Business,1703,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +27002,62194,Female,Loyal Customer,22,Business travel,Business,2454,2,3,3,3,2,2,2,2,3,3,1,2,2,2,2,0.0,neutral or dissatisfied +27003,72328,Male,Loyal Customer,59,Business travel,Business,1939,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +27004,73980,Female,Loyal Customer,41,Business travel,Business,2342,5,2,5,5,4,5,5,4,4,4,4,5,4,3,5,4.0,satisfied +27005,69277,Male,Loyal Customer,20,Personal Travel,Eco,733,2,4,2,4,1,2,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +27006,80127,Male,disloyal Customer,37,Business travel,Business,2586,3,3,3,3,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +27007,34491,Male,disloyal Customer,28,Business travel,Eco,700,1,1,1,2,4,1,4,4,2,2,3,3,5,4,95,90.0,neutral or dissatisfied +27008,4989,Male,disloyal Customer,25,Business travel,Business,502,3,0,3,5,2,3,2,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +27009,68756,Male,Loyal Customer,45,Business travel,Business,3565,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,4.0,satisfied +27010,102348,Female,Loyal Customer,54,Business travel,Business,236,1,3,3,3,4,2,2,1,1,1,1,2,1,4,16,15.0,neutral or dissatisfied +27011,36044,Male,Loyal Customer,55,Business travel,Business,2939,5,5,5,5,3,4,4,4,4,4,4,1,4,1,0,0.0,satisfied +27012,74470,Female,Loyal Customer,42,Business travel,Business,2206,4,4,4,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +27013,87470,Male,Loyal Customer,48,Business travel,Business,2692,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +27014,67637,Male,Loyal Customer,30,Business travel,Business,1438,2,2,5,2,5,5,5,5,5,5,4,4,5,5,1,7.0,satisfied +27015,124210,Male,Loyal Customer,16,Personal Travel,Eco,2176,4,2,5,3,2,5,2,2,3,1,3,1,4,2,34,25.0,neutral or dissatisfied +27016,83275,Female,Loyal Customer,65,Personal Travel,Eco,1979,4,4,4,4,3,1,4,4,4,4,4,1,4,3,0,5.0,satisfied +27017,112107,Male,Loyal Customer,43,Personal Travel,Eco,1062,3,1,3,2,2,3,2,2,2,4,2,2,3,2,14,9.0,neutral or dissatisfied +27018,48334,Female,Loyal Customer,37,Business travel,Business,522,1,1,1,1,2,1,5,2,2,2,2,2,2,3,0,0.0,satisfied +27019,106310,Male,Loyal Customer,32,Business travel,Eco,998,4,4,4,4,4,4,4,4,2,2,4,1,3,4,7,18.0,neutral or dissatisfied +27020,41130,Male,disloyal Customer,39,Business travel,Eco,191,2,0,2,4,4,2,4,4,2,3,4,1,4,4,0,0.0,neutral or dissatisfied +27021,79716,Male,Loyal Customer,29,Personal Travel,Eco,762,2,5,2,4,4,2,4,4,3,4,4,4,5,4,6,0.0,neutral or dissatisfied +27022,89247,Male,Loyal Customer,39,Personal Travel,Eco Plus,1947,5,4,5,3,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +27023,46749,Female,Loyal Customer,70,Personal Travel,Eco,73,2,5,2,2,1,5,3,2,2,2,1,5,2,2,113,124.0,neutral or dissatisfied +27024,104536,Male,Loyal Customer,53,Business travel,Eco,856,2,2,2,2,2,2,2,2,2,1,3,1,3,2,13,12.0,neutral or dissatisfied +27025,34075,Female,Loyal Customer,60,Personal Travel,Eco,1674,3,4,3,4,4,4,3,5,5,3,5,2,5,4,66,43.0,neutral or dissatisfied +27026,9716,Male,Loyal Customer,36,Personal Travel,Eco,199,2,5,0,1,1,0,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +27027,69984,Male,disloyal Customer,40,Business travel,Business,236,3,3,3,3,3,3,3,3,4,2,3,1,3,3,4,20.0,neutral or dissatisfied +27028,22736,Male,Loyal Customer,56,Business travel,Business,3611,2,4,2,2,3,5,3,5,5,5,5,1,5,5,16,7.0,satisfied +27029,4317,Male,disloyal Customer,22,Business travel,Eco,589,1,0,1,3,5,1,5,5,3,5,5,4,5,5,14,12.0,neutral or dissatisfied +27030,79183,Male,Loyal Customer,32,Personal Travel,Eco,2422,2,4,2,2,2,1,2,4,3,4,5,2,5,2,1,0.0,neutral or dissatisfied +27031,56316,Male,Loyal Customer,56,Business travel,Business,3090,0,5,0,4,2,4,5,4,4,3,3,5,4,4,0,0.0,satisfied +27032,82864,Male,Loyal Customer,29,Business travel,Business,2435,1,1,1,1,5,5,5,5,3,3,5,3,4,5,8,0.0,satisfied +27033,95410,Male,Loyal Customer,40,Personal Travel,Eco,677,3,4,3,4,3,3,3,3,4,3,5,5,4,3,49,26.0,neutral or dissatisfied +27034,11378,Female,Loyal Customer,33,Business travel,Business,2097,0,4,0,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +27035,89473,Male,Loyal Customer,48,Business travel,Business,2191,5,5,5,5,2,4,5,5,5,5,4,4,5,3,12,12.0,satisfied +27036,77484,Male,Loyal Customer,48,Business travel,Business,989,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,10.0,satisfied +27037,68745,Male,disloyal Customer,24,Business travel,Business,926,4,0,4,4,2,4,2,2,4,5,4,3,4,2,0,0.0,satisfied +27038,98324,Male,Loyal Customer,54,Business travel,Business,1960,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +27039,128029,Female,Loyal Customer,52,Business travel,Business,1440,2,1,1,1,2,3,3,2,2,2,2,4,2,4,4,1.0,neutral or dissatisfied +27040,86698,Female,Loyal Customer,39,Business travel,Business,1747,3,3,3,3,3,5,5,4,4,5,4,3,4,5,23,15.0,satisfied +27041,108769,Male,Loyal Customer,44,Business travel,Business,2600,5,5,5,5,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +27042,14209,Female,disloyal Customer,16,Business travel,Eco,620,1,3,1,3,2,1,2,2,3,4,3,4,4,2,0,4.0,neutral or dissatisfied +27043,16517,Male,Loyal Customer,52,Personal Travel,Eco Plus,246,1,4,1,3,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +27044,53028,Male,Loyal Customer,39,Business travel,Eco,1208,5,3,4,3,5,5,5,5,5,4,3,2,4,5,14,0.0,satisfied +27045,34411,Male,Loyal Customer,64,Personal Travel,Eco,728,2,3,2,3,3,2,3,3,1,1,1,5,4,3,19,5.0,neutral or dissatisfied +27046,10912,Female,disloyal Customer,37,Business travel,Eco,224,4,1,4,4,5,4,5,5,4,4,4,1,3,5,22,11.0,neutral or dissatisfied +27047,82643,Male,Loyal Customer,16,Personal Travel,Eco Plus,528,2,5,2,2,3,2,3,3,5,3,5,4,5,3,3,0.0,neutral or dissatisfied +27048,58063,Male,disloyal Customer,24,Business travel,Eco,589,4,5,4,5,4,4,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +27049,8743,Male,Loyal Customer,15,Personal Travel,Eco Plus,227,3,4,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +27050,102697,Male,Loyal Customer,52,Business travel,Business,365,2,2,2,2,5,4,5,4,4,3,4,4,4,5,0,0.0,satisfied +27051,66949,Male,Loyal Customer,48,Business travel,Business,1017,4,4,4,4,5,5,4,4,4,4,4,5,4,3,68,67.0,satisfied +27052,101693,Female,disloyal Customer,37,Business travel,Eco,1100,1,1,1,1,4,1,4,4,4,1,2,2,1,4,0,0.0,neutral or dissatisfied +27053,47637,Male,disloyal Customer,38,Business travel,Eco,1242,4,4,4,2,2,4,2,2,4,1,2,4,3,2,0,0.0,neutral or dissatisfied +27054,54573,Male,Loyal Customer,9,Personal Travel,Eco Plus,925,3,2,3,3,5,3,5,5,4,3,2,4,3,5,15,0.0,neutral or dissatisfied +27055,51773,Male,Loyal Customer,16,Personal Travel,Eco,493,3,4,3,4,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +27056,106397,Male,Loyal Customer,32,Business travel,Business,2278,1,3,3,3,1,1,1,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +27057,25617,Female,Loyal Customer,34,Business travel,Business,666,1,1,1,1,3,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +27058,9119,Male,disloyal Customer,15,Business travel,Eco,765,4,4,4,5,2,4,2,2,4,1,4,1,5,2,0,0.0,satisfied +27059,38413,Male,Loyal Customer,55,Business travel,Business,2929,3,3,3,3,5,1,4,4,4,4,4,4,4,3,0,0.0,satisfied +27060,87729,Female,Loyal Customer,55,Personal Travel,Eco Plus,591,2,4,2,2,2,5,4,3,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +27061,105985,Female,Loyal Customer,17,Personal Travel,Eco Plus,2295,2,1,2,3,5,2,5,5,2,2,3,4,4,5,31,21.0,neutral or dissatisfied +27062,38751,Male,disloyal Customer,24,Business travel,Eco,353,4,5,4,1,1,4,1,1,2,4,4,1,4,1,0,0.0,satisfied +27063,43102,Male,Loyal Customer,28,Personal Travel,Eco,192,1,4,1,4,1,5,5,5,3,4,5,5,4,5,152,149.0,neutral or dissatisfied +27064,26451,Female,Loyal Customer,37,Business travel,Eco,925,4,4,4,4,4,5,4,4,2,2,2,4,5,4,0,0.0,satisfied +27065,79077,Male,Loyal Customer,50,Personal Travel,Eco,356,5,5,5,2,4,5,4,4,3,5,5,4,5,4,10,9.0,satisfied +27066,123292,Female,Loyal Customer,16,Personal Travel,Eco,468,4,2,4,2,4,4,5,4,1,5,2,4,3,4,35,34.0,neutral or dissatisfied +27067,35413,Female,Loyal Customer,46,Business travel,Eco,544,4,3,3,3,4,4,3,4,4,4,4,1,4,2,0,0.0,satisfied +27068,111715,Female,Loyal Customer,61,Personal Travel,Eco,541,3,5,3,2,2,4,4,3,3,3,3,3,3,3,2,0.0,neutral or dissatisfied +27069,23041,Male,Loyal Customer,28,Personal Travel,Eco Plus,1025,4,4,4,2,4,4,5,4,5,2,4,3,4,4,0,0.0,satisfied +27070,97251,Male,disloyal Customer,26,Business travel,Business,296,2,5,1,1,1,1,1,1,5,4,5,5,4,1,2,2.0,neutral or dissatisfied +27071,39083,Male,Loyal Customer,40,Business travel,Eco,984,5,2,2,2,5,5,5,5,1,4,4,5,3,5,0,18.0,satisfied +27072,26734,Female,Loyal Customer,40,Business travel,Eco Plus,404,3,1,1,1,3,4,3,3,2,5,3,5,4,3,0,0.0,satisfied +27073,117706,Male,disloyal Customer,39,Business travel,Business,1009,3,4,4,4,5,4,5,5,5,2,4,3,5,5,0,4.0,neutral or dissatisfied +27074,124860,Female,disloyal Customer,44,Business travel,Eco Plus,280,2,2,2,3,1,2,1,1,4,1,3,4,3,1,36,34.0,neutral or dissatisfied +27075,29082,Male,Loyal Customer,44,Personal Travel,Eco,954,3,4,4,2,5,4,5,5,3,2,4,3,5,5,0,7.0,neutral or dissatisfied +27076,97225,Female,Loyal Customer,50,Personal Travel,Eco Plus,1211,4,0,4,1,2,5,4,4,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +27077,117538,Female,Loyal Customer,59,Business travel,Business,347,5,5,5,5,3,4,5,4,4,4,4,3,4,3,7,6.0,satisfied +27078,77954,Female,Loyal Customer,42,Business travel,Business,332,3,3,5,3,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +27079,73143,Male,Loyal Customer,42,Personal Travel,Eco,1068,3,2,3,2,1,3,1,1,4,4,3,3,3,1,0,6.0,neutral or dissatisfied +27080,8266,Female,Loyal Customer,53,Personal Travel,Eco,335,5,5,5,2,5,4,5,2,2,5,2,4,2,4,0,0.0,satisfied +27081,74683,Female,Loyal Customer,20,Personal Travel,Eco,1438,2,4,2,4,1,2,1,1,4,1,4,2,4,1,15,11.0,neutral or dissatisfied +27082,70899,Male,disloyal Customer,24,Business travel,Business,965,5,0,5,2,3,5,3,3,3,5,5,4,5,3,27,30.0,satisfied +27083,118901,Female,Loyal Customer,29,Business travel,Business,3513,3,3,3,3,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +27084,88290,Female,Loyal Customer,41,Business travel,Business,406,3,1,3,1,3,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +27085,103993,Female,Loyal Customer,31,Business travel,Business,1592,3,3,3,3,3,3,3,3,3,5,3,3,4,3,0,0.0,satisfied +27086,95031,Male,Loyal Customer,42,Personal Travel,Eco,273,3,3,3,3,4,3,4,4,4,5,4,3,4,4,0,4.0,neutral or dissatisfied +27087,93185,Male,Loyal Customer,33,Business travel,Eco Plus,1066,2,2,2,2,2,2,2,2,2,3,3,2,3,2,51,125.0,neutral or dissatisfied +27088,79726,Male,Loyal Customer,23,Personal Travel,Eco,712,3,5,3,2,4,3,4,4,3,2,5,4,5,4,4,3.0,neutral or dissatisfied +27089,13971,Female,Loyal Customer,32,Personal Travel,Eco,153,2,5,0,4,1,0,1,1,3,5,4,5,4,1,0,10.0,neutral or dissatisfied +27090,42662,Female,Loyal Customer,59,Personal Travel,Eco Plus,557,2,2,2,4,3,3,3,2,2,2,2,2,2,3,0,9.0,neutral or dissatisfied +27091,52291,Male,Loyal Customer,56,Business travel,Eco,370,2,2,3,2,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +27092,119706,Male,Loyal Customer,24,Business travel,Business,1496,4,4,4,4,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +27093,128658,Female,Loyal Customer,39,Business travel,Business,2442,4,4,4,4,4,3,4,2,2,2,2,5,2,5,6,0.0,satisfied +27094,35801,Female,Loyal Customer,51,Business travel,Business,3921,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,5.0,satisfied +27095,96644,Female,Loyal Customer,14,Business travel,Business,972,2,2,2,2,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +27096,107104,Male,Loyal Customer,52,Business travel,Business,1764,3,3,3,3,5,4,5,5,5,5,5,5,5,5,14,12.0,satisfied +27097,97669,Female,disloyal Customer,32,Business travel,Eco,491,2,0,3,4,2,3,2,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +27098,32592,Female,Loyal Customer,18,Business travel,Business,3640,0,3,1,2,2,2,2,2,4,5,4,2,3,2,3,2.0,satisfied +27099,3588,Female,Loyal Customer,56,Business travel,Business,3177,1,1,1,1,4,5,5,5,5,5,5,3,5,3,11,2.0,satisfied +27100,123336,Male,Loyal Customer,63,Personal Travel,Eco Plus,650,2,5,3,2,5,3,5,5,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +27101,41012,Male,disloyal Customer,54,Business travel,Business,1087,4,4,4,4,5,4,5,5,4,4,5,4,4,5,0,0.0,satisfied +27102,55483,Male,Loyal Customer,26,Business travel,Business,2434,2,2,2,2,5,5,5,5,5,4,4,3,4,5,2,0.0,satisfied +27103,112606,Male,Loyal Customer,58,Business travel,Eco,639,4,5,2,5,4,4,4,4,2,1,2,5,3,4,89,68.0,satisfied +27104,49700,Male,Loyal Customer,52,Business travel,Business,308,1,1,1,1,4,4,4,5,5,5,5,2,5,1,22,17.0,satisfied +27105,4724,Male,disloyal Customer,35,Business travel,Business,888,3,3,3,1,5,3,5,5,4,3,4,4,5,5,27,0.0,neutral or dissatisfied +27106,109035,Female,Loyal Customer,59,Business travel,Business,781,3,3,3,3,2,4,4,4,4,4,4,4,4,5,20,0.0,satisfied +27107,55708,Female,Loyal Customer,59,Personal Travel,Eco,1025,4,4,4,3,3,5,4,4,4,4,1,3,4,3,0,0.0,neutral or dissatisfied +27108,104267,Female,Loyal Customer,21,Personal Travel,Eco,456,3,4,3,3,3,3,1,3,5,4,5,5,5,3,1,0.0,neutral or dissatisfied +27109,88381,Female,disloyal Customer,39,Business travel,Business,366,2,2,2,3,2,2,2,2,2,5,3,2,3,2,90,89.0,neutral or dissatisfied +27110,112964,Female,Loyal Customer,28,Personal Travel,Eco,1476,4,5,4,1,5,4,5,5,4,3,2,4,3,5,0,0.0,neutral or dissatisfied +27111,85674,Male,Loyal Customer,57,Personal Travel,Eco,903,3,4,3,2,5,3,5,5,4,5,4,4,4,5,60,51.0,neutral or dissatisfied +27112,105316,Female,Loyal Customer,55,Business travel,Business,3111,1,1,1,1,4,5,4,2,2,2,2,4,2,5,30,28.0,satisfied +27113,59148,Female,disloyal Customer,50,Personal Travel,Eco,1726,2,5,2,2,3,2,3,3,2,5,2,4,5,3,0,0.0,neutral or dissatisfied +27114,100235,Female,Loyal Customer,45,Business travel,Business,1757,2,2,2,2,2,2,2,4,5,4,5,2,4,2,193,194.0,satisfied +27115,63985,Male,disloyal Customer,41,Business travel,Business,612,4,4,4,4,2,4,4,2,3,2,5,4,5,2,78,127.0,satisfied +27116,122280,Male,Loyal Customer,59,Personal Travel,Eco,544,4,1,3,4,2,3,5,2,2,5,3,2,4,2,0,3.0,neutral or dissatisfied +27117,66415,Male,Loyal Customer,69,Personal Travel,Eco,1562,4,4,4,5,1,4,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +27118,101096,Male,disloyal Customer,37,Business travel,Business,1090,3,3,3,3,3,3,3,3,4,3,5,4,4,3,19,0.0,neutral or dissatisfied +27119,116648,Male,disloyal Customer,11,Business travel,Eco,480,1,1,1,4,3,1,3,3,4,4,4,1,3,3,32,34.0,neutral or dissatisfied +27120,73727,Female,Loyal Customer,17,Personal Travel,Eco,192,4,5,4,1,3,4,3,3,5,3,4,4,4,3,0,3.0,satisfied +27121,111734,Female,Loyal Customer,26,Business travel,Business,2218,1,1,1,1,5,5,5,5,5,3,4,4,4,5,3,19.0,satisfied +27122,61142,Male,disloyal Customer,30,Business travel,Business,862,3,3,3,4,1,3,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +27123,55727,Female,Loyal Customer,39,Business travel,Business,3829,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +27124,3636,Male,disloyal Customer,40,Business travel,Business,427,2,3,3,3,4,3,4,4,4,5,4,3,4,4,26,41.0,neutral or dissatisfied +27125,126238,Female,disloyal Customer,22,Business travel,Eco,468,3,1,3,3,4,3,4,4,2,4,3,1,4,4,1,0.0,neutral or dissatisfied +27126,43685,Male,Loyal Customer,39,Business travel,Eco,257,5,3,4,4,5,5,5,5,3,5,5,2,5,5,83,70.0,satisfied +27127,89298,Female,Loyal Customer,63,Personal Travel,Eco,453,2,4,2,5,3,5,5,3,3,2,3,3,3,5,50,54.0,neutral or dissatisfied +27128,72576,Female,Loyal Customer,47,Business travel,Eco,585,5,5,5,5,3,4,2,4,4,5,4,4,4,2,0,0.0,satisfied +27129,65744,Female,Loyal Customer,37,Personal Travel,Eco,936,2,5,2,1,5,2,3,5,5,1,4,3,1,5,1,0.0,neutral or dissatisfied +27130,61903,Male,Loyal Customer,56,Business travel,Business,550,3,3,3,3,3,4,4,2,2,2,2,3,2,3,18,2.0,satisfied +27131,1650,Female,Loyal Customer,42,Business travel,Business,3908,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,2.0,satisfied +27132,6027,Male,Loyal Customer,57,Business travel,Business,2426,3,2,4,2,4,2,2,3,3,2,3,4,3,2,3,4.0,neutral or dissatisfied +27133,109037,Female,disloyal Customer,22,Business travel,Eco,781,5,5,5,2,1,5,1,1,5,4,4,4,5,1,0,0.0,satisfied +27134,114157,Male,Loyal Customer,41,Business travel,Business,2995,1,1,1,1,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +27135,40798,Male,Loyal Customer,32,Business travel,Business,1737,3,2,2,2,3,3,3,3,1,4,4,1,3,3,42,,neutral or dissatisfied +27136,110585,Female,Loyal Customer,67,Personal Travel,Eco,551,4,4,5,3,2,4,4,2,2,5,2,1,2,3,0,0.0,neutral or dissatisfied +27137,48427,Female,Loyal Customer,46,Business travel,Eco,776,4,2,2,2,3,3,1,4,4,4,4,3,4,5,4,5.0,satisfied +27138,41614,Female,Loyal Customer,51,Business travel,Eco Plus,1482,5,1,1,1,4,3,1,5,5,5,5,3,5,1,61,50.0,satisfied +27139,83280,Female,Loyal Customer,51,Personal Travel,Eco,1979,0,4,0,3,5,3,3,4,4,0,4,1,4,2,8,0.0,satisfied +27140,93056,Female,Loyal Customer,56,Business travel,Business,3916,0,0,0,3,4,5,4,2,2,2,2,3,2,4,0,10.0,satisfied +27141,72984,Male,Loyal Customer,55,Business travel,Business,1089,1,1,1,1,4,5,5,4,4,4,4,4,4,3,20,0.0,satisfied +27142,81490,Female,Loyal Customer,28,Personal Travel,Eco,528,2,4,2,1,5,2,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +27143,112626,Male,Loyal Customer,7,Personal Travel,Eco,602,2,1,2,4,4,2,4,4,4,2,3,2,4,4,1,0.0,neutral or dissatisfied +27144,87676,Male,Loyal Customer,47,Business travel,Eco,591,4,1,1,1,4,4,4,4,4,4,2,3,3,4,0,0.0,neutral or dissatisfied +27145,65544,Male,Loyal Customer,33,Business travel,Business,237,3,3,3,3,4,4,4,4,3,4,4,3,5,4,0,3.0,satisfied +27146,33106,Female,Loyal Customer,17,Personal Travel,Eco,102,3,2,3,4,3,3,3,3,2,1,4,2,3,3,0,5.0,neutral or dissatisfied +27147,93275,Male,Loyal Customer,31,Business travel,Eco,806,1,3,1,3,1,1,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +27148,61946,Male,disloyal Customer,23,Business travel,Eco,2052,4,4,4,3,3,4,3,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +27149,18869,Male,disloyal Customer,18,Business travel,Eco,551,2,4,2,4,4,2,4,4,1,1,4,3,4,4,71,79.0,neutral or dissatisfied +27150,77746,Male,disloyal Customer,39,Business travel,Eco,413,2,3,2,4,3,2,1,3,5,5,1,5,4,3,1,0.0,neutral or dissatisfied +27151,85103,Male,disloyal Customer,21,Business travel,Eco,731,2,2,2,3,5,2,4,5,5,5,4,4,5,5,2,0.0,neutral or dissatisfied +27152,84125,Female,disloyal Customer,36,Business travel,Eco Plus,1900,3,3,3,4,2,3,2,2,4,5,3,2,4,2,4,27.0,neutral or dissatisfied +27153,21911,Male,disloyal Customer,27,Business travel,Eco,503,1,2,1,4,2,1,2,2,4,4,3,3,4,2,0,0.0,neutral or dissatisfied +27154,50933,Male,Loyal Customer,34,Personal Travel,Eco,156,2,5,2,3,2,2,2,2,3,2,3,3,1,2,39,33.0,neutral or dissatisfied +27155,67028,Female,Loyal Customer,45,Business travel,Business,3163,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +27156,105002,Male,Loyal Customer,34,Personal Travel,Eco Plus,337,3,4,3,3,3,3,3,3,5,3,5,3,4,3,15,3.0,neutral or dissatisfied +27157,50721,Female,Loyal Customer,58,Personal Travel,Eco,110,3,1,3,3,2,3,4,5,5,3,5,3,5,2,0,2.0,neutral or dissatisfied +27158,40055,Female,Loyal Customer,32,Business travel,Eco Plus,866,0,0,0,1,5,0,3,5,3,5,2,1,3,5,2,0.0,satisfied +27159,41215,Female,Loyal Customer,51,Personal Travel,Eco,1091,0,4,0,4,5,4,4,2,2,0,2,2,2,1,35,36.0,satisfied +27160,17332,Female,Loyal Customer,65,Personal Travel,Eco Plus,438,2,4,2,1,4,3,1,2,2,2,2,4,2,4,7,30.0,neutral or dissatisfied +27161,101229,Female,Loyal Customer,43,Business travel,Eco Plus,583,3,5,5,5,1,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +27162,78222,Male,Loyal Customer,50,Personal Travel,Eco,259,3,5,3,3,2,3,2,2,3,3,2,5,3,2,0,0.0,neutral or dissatisfied +27163,50688,Female,Loyal Customer,24,Personal Travel,Eco,337,4,1,4,3,1,4,5,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +27164,123712,Male,Loyal Customer,46,Personal Travel,Eco,214,3,1,3,4,1,3,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +27165,56690,Male,Loyal Customer,62,Personal Travel,Eco,1068,3,5,3,4,3,3,1,3,4,5,4,5,1,3,40,33.0,neutral or dissatisfied +27166,31506,Female,Loyal Customer,8,Business travel,Business,2355,2,4,4,4,2,2,2,2,1,4,3,4,2,2,12,45.0,neutral or dissatisfied +27167,111346,Male,disloyal Customer,25,Business travel,Business,777,2,3,2,3,5,2,5,5,1,4,3,2,3,5,76,75.0,neutral or dissatisfied +27168,45616,Male,Loyal Customer,30,Business travel,Eco,230,3,2,2,2,3,3,3,3,3,5,4,3,3,3,2,0.0,neutral or dissatisfied +27169,52040,Male,Loyal Customer,9,Personal Travel,Eco Plus,328,2,4,2,4,4,2,4,4,3,3,3,2,4,4,0,0.0,neutral or dissatisfied +27170,16250,Female,Loyal Customer,21,Business travel,Business,748,1,1,2,1,4,4,4,4,1,4,4,5,3,4,29,17.0,satisfied +27171,115329,Female,Loyal Customer,61,Business travel,Eco,373,1,5,5,5,4,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +27172,26421,Male,Loyal Customer,25,Personal Travel,Business,925,2,4,2,1,5,2,2,5,3,3,4,4,5,5,25,14.0,neutral or dissatisfied +27173,18984,Male,Loyal Customer,38,Business travel,Business,3918,1,1,1,1,5,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +27174,20554,Female,disloyal Customer,36,Business travel,Eco,533,3,2,2,3,5,2,1,5,1,5,3,2,4,5,0,0.0,neutral or dissatisfied +27175,38026,Male,Loyal Customer,59,Business travel,Eco,1249,4,3,3,3,4,4,4,4,4,5,3,1,3,4,59,51.0,satisfied +27176,79871,Male,Loyal Customer,54,Business travel,Business,2477,2,2,1,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +27177,73158,Male,Loyal Customer,46,Business travel,Business,2548,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +27178,28832,Male,Loyal Customer,33,Business travel,Eco,671,0,0,0,2,1,3,1,1,1,2,2,2,1,1,0,0.0,satisfied +27179,33748,Female,disloyal Customer,44,Business travel,Business,266,2,2,2,4,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +27180,99463,Female,Loyal Customer,40,Business travel,Business,283,4,4,4,4,2,5,4,4,4,4,4,4,4,4,30,31.0,satisfied +27181,20437,Male,Loyal Customer,35,Business travel,Business,2137,1,1,1,1,5,4,5,4,4,4,4,4,4,5,3,5.0,satisfied +27182,66068,Male,Loyal Customer,30,Personal Travel,Eco,1055,3,4,3,4,5,3,1,5,3,3,5,4,4,5,38,52.0,neutral or dissatisfied +27183,52144,Male,Loyal Customer,41,Business travel,Business,493,5,5,5,5,3,5,4,4,4,4,4,5,4,3,47,42.0,satisfied +27184,67662,Male,Loyal Customer,57,Business travel,Business,1464,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +27185,26383,Female,Loyal Customer,23,Business travel,Eco Plus,991,5,4,4,4,5,5,3,5,1,4,1,5,4,5,0,1.0,satisfied +27186,13991,Male,disloyal Customer,37,Business travel,Eco,160,4,0,3,2,3,3,3,3,5,4,3,2,5,3,55,51.0,neutral or dissatisfied +27187,7941,Female,Loyal Customer,51,Business travel,Business,594,3,3,3,3,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +27188,123907,Female,Loyal Customer,42,Personal Travel,Eco,541,2,3,2,1,1,5,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +27189,35001,Female,disloyal Customer,23,Business travel,Eco,782,2,2,2,1,2,2,2,2,3,5,2,2,2,2,20,30.0,neutral or dissatisfied +27190,96149,Female,Loyal Customer,45,Business travel,Business,3169,4,4,3,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +27191,48744,Male,Loyal Customer,44,Business travel,Business,1905,4,4,2,4,4,5,5,4,4,4,4,3,4,5,53,84.0,satisfied +27192,11665,Male,disloyal Customer,23,Business travel,Business,1117,2,3,3,4,1,3,1,1,3,3,3,4,3,1,5,7.0,neutral or dissatisfied +27193,74934,Female,Loyal Customer,53,Business travel,Eco,2586,2,1,3,1,5,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +27194,52505,Male,Loyal Customer,30,Personal Travel,Business,110,5,4,5,3,5,5,5,5,3,5,3,1,4,5,0,0.0,satisfied +27195,49767,Male,Loyal Customer,58,Business travel,Business,1532,2,2,2,2,2,3,5,4,4,4,4,2,4,5,0,0.0,satisfied +27196,108313,Male,Loyal Customer,51,Business travel,Business,1750,1,1,1,1,4,3,4,5,5,5,5,5,5,5,22,24.0,satisfied +27197,106275,Female,Loyal Customer,43,Business travel,Business,1641,1,1,1,1,4,5,5,4,4,4,4,4,4,4,22,15.0,satisfied +27198,81216,Male,Loyal Customer,38,Business travel,Business,1026,1,1,1,1,5,5,5,5,3,3,2,5,5,5,187,187.0,satisfied +27199,72663,Female,Loyal Customer,35,Personal Travel,Eco,964,1,4,1,4,3,1,3,3,5,3,5,5,4,3,0,1.0,neutral or dissatisfied +27200,44578,Male,disloyal Customer,20,Business travel,Eco,157,5,1,5,3,2,5,2,2,5,5,1,4,2,2,0,0.0,satisfied +27201,11585,Male,Loyal Customer,54,Business travel,Eco,657,4,5,5,5,3,4,3,3,1,2,3,4,4,3,39,27.0,neutral or dissatisfied +27202,61659,Female,Loyal Customer,51,Business travel,Business,1635,2,2,4,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +27203,103548,Female,Loyal Customer,10,Personal Travel,Eco,967,3,4,3,3,1,3,4,1,5,5,4,3,5,1,2,0.0,neutral or dissatisfied +27204,12710,Female,Loyal Customer,33,Business travel,Business,3613,2,3,3,3,4,4,3,2,2,2,2,4,2,2,0,1.0,neutral or dissatisfied +27205,64289,Female,Loyal Customer,46,Business travel,Business,1212,1,1,3,1,5,4,4,5,5,5,5,5,5,4,0,5.0,satisfied +27206,37167,Male,Loyal Customer,55,Personal Travel,Eco,1129,4,4,4,5,3,4,3,3,4,2,5,5,5,3,11,7.0,neutral or dissatisfied +27207,71043,Female,Loyal Customer,40,Business travel,Business,2634,1,5,4,5,5,2,1,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +27208,116477,Female,Loyal Customer,24,Personal Travel,Eco,325,3,2,3,3,1,3,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +27209,87117,Female,Loyal Customer,50,Personal Travel,Eco,594,2,4,2,3,5,4,2,5,5,2,4,4,5,2,5,0.0,neutral or dissatisfied +27210,48289,Male,disloyal Customer,35,Business travel,Eco,807,2,2,2,3,5,2,1,5,4,1,4,4,2,5,80,57.0,neutral or dissatisfied +27211,76377,Male,Loyal Customer,40,Business travel,Business,2596,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +27212,117167,Female,Loyal Customer,51,Personal Travel,Eco,338,3,5,3,1,5,4,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +27213,103914,Female,Loyal Customer,56,Business travel,Business,533,3,3,3,3,4,4,4,4,4,4,4,4,4,5,43,46.0,satisfied +27214,118152,Male,Loyal Customer,44,Business travel,Business,1444,2,2,2,2,2,4,5,4,4,4,4,5,4,4,5,17.0,satisfied +27215,71923,Female,Loyal Customer,59,Business travel,Business,1846,1,1,1,1,5,3,4,4,4,4,4,4,4,4,3,0.0,satisfied +27216,129421,Male,Loyal Customer,33,Business travel,Business,3698,1,1,1,1,4,4,4,4,4,4,5,5,4,4,1,0.0,satisfied +27217,37395,Male,Loyal Customer,59,Business travel,Eco,972,3,4,4,4,3,3,3,3,5,5,5,5,2,3,10,0.0,satisfied +27218,66657,Male,Loyal Customer,31,Business travel,Eco,802,3,1,2,1,4,3,3,2,3,4,3,3,1,3,144,144.0,neutral or dissatisfied +27219,31419,Female,Loyal Customer,52,Business travel,Business,1506,3,1,1,1,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +27220,127605,Female,Loyal Customer,41,Business travel,Business,1773,4,4,4,4,3,3,4,4,4,5,4,4,4,3,0,0.0,satisfied +27221,71861,Male,disloyal Customer,37,Business travel,Eco,244,4,1,4,3,3,4,3,3,3,3,3,4,3,3,2,0.0,neutral or dissatisfied +27222,66490,Male,Loyal Customer,52,Business travel,Business,447,3,3,3,3,4,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +27223,14055,Female,Loyal Customer,24,Business travel,Eco,319,3,2,2,2,3,4,4,3,1,5,2,1,1,3,0,0.0,satisfied +27224,13455,Female,Loyal Customer,44,Personal Travel,Eco,409,3,5,5,4,1,3,1,5,5,5,5,5,5,4,10,33.0,neutral or dissatisfied +27225,85305,Male,Loyal Customer,67,Personal Travel,Eco,1282,3,5,3,1,3,3,2,3,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +27226,59158,Male,Loyal Customer,12,Business travel,Business,1846,4,4,4,4,5,4,5,5,4,3,3,4,5,5,0,28.0,satisfied +27227,20406,Male,Loyal Customer,59,Personal Travel,Eco Plus,588,4,4,3,2,3,3,4,3,5,5,5,5,5,3,0,26.0,neutral or dissatisfied +27228,106766,Male,Loyal Customer,26,Personal Travel,Eco,829,2,4,2,4,5,2,3,5,3,2,5,3,5,5,9,4.0,neutral or dissatisfied +27229,125489,Female,Loyal Customer,50,Personal Travel,Eco Plus,2979,3,4,3,1,3,1,1,2,3,5,1,1,5,1,0,0.0,neutral or dissatisfied +27230,95434,Male,Loyal Customer,43,Business travel,Eco Plus,562,3,2,2,2,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +27231,124251,Female,Loyal Customer,49,Personal Travel,Eco,1916,1,5,1,5,3,4,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +27232,64875,Male,Loyal Customer,22,Business travel,Business,190,2,1,1,1,2,2,2,2,3,4,3,2,3,2,0,13.0,neutral or dissatisfied +27233,7135,Male,Loyal Customer,54,Business travel,Business,2569,4,2,2,2,3,3,4,3,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +27234,111773,Male,Loyal Customer,46,Business travel,Business,1620,5,5,5,5,5,4,5,4,4,4,4,3,4,3,13,24.0,satisfied +27235,14105,Female,Loyal Customer,23,Personal Travel,Eco,425,2,0,5,3,5,5,5,5,3,2,5,4,5,5,57,49.0,neutral or dissatisfied +27236,45026,Female,Loyal Customer,56,Personal Travel,Eco Plus,222,2,1,0,2,1,3,2,4,4,0,4,3,4,2,0,6.0,neutral or dissatisfied +27237,113491,Male,Loyal Customer,51,Business travel,Business,407,5,5,5,5,5,4,5,4,4,4,4,3,4,5,10,2.0,satisfied +27238,40000,Male,Loyal Customer,8,Business travel,Business,575,2,1,1,1,2,2,2,2,1,2,3,1,3,2,0,,neutral or dissatisfied +27239,74831,Male,Loyal Customer,44,Business travel,Business,1797,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +27240,72577,Male,Loyal Customer,80,Business travel,Eco,617,4,2,2,2,4,4,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +27241,7067,Male,Loyal Customer,34,Business travel,Business,273,4,4,3,4,4,4,4,4,4,4,4,5,4,3,36,58.0,satisfied +27242,120134,Female,Loyal Customer,29,Business travel,Business,1475,1,5,5,5,1,1,1,1,1,3,3,3,3,1,0,0.0,neutral or dissatisfied +27243,29871,Male,disloyal Customer,49,Business travel,Eco,204,3,0,3,5,1,3,1,1,4,3,1,1,2,1,29,23.0,neutral or dissatisfied +27244,13446,Male,Loyal Customer,37,Personal Travel,Eco,475,1,2,1,4,4,1,2,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +27245,107578,Male,Loyal Customer,64,Personal Travel,Eco,1521,2,5,2,4,5,2,5,5,4,4,4,3,4,5,68,57.0,neutral or dissatisfied +27246,126057,Female,Loyal Customer,24,Business travel,Business,1952,5,5,5,5,4,4,4,4,4,3,5,4,4,4,2,0.0,satisfied +27247,35755,Male,Loyal Customer,23,Business travel,Business,1608,3,2,2,2,3,3,3,3,1,3,3,4,4,3,4,26.0,neutral or dissatisfied +27248,109118,Female,disloyal Customer,34,Business travel,Eco Plus,816,1,1,1,3,5,1,5,5,3,1,4,3,3,5,119,121.0,neutral or dissatisfied +27249,118412,Female,Loyal Customer,41,Business travel,Business,3732,2,2,2,2,4,5,4,5,5,5,5,3,5,4,20,13.0,satisfied +27250,29295,Male,Loyal Customer,35,Business travel,Business,2049,4,5,5,5,2,3,4,4,4,4,4,2,4,1,0,6.0,neutral or dissatisfied +27251,84006,Female,Loyal Customer,13,Personal Travel,Eco,321,5,4,5,4,3,5,3,3,5,4,4,4,1,3,0,0.0,satisfied +27252,30750,Female,Loyal Customer,57,Personal Travel,Eco,977,4,4,4,5,3,4,4,5,5,4,5,3,5,4,2,5.0,neutral or dissatisfied +27253,36508,Male,Loyal Customer,40,Business travel,Business,2484,2,2,3,2,1,2,1,4,4,4,4,3,4,5,3,3.0,satisfied +27254,62817,Female,Loyal Customer,56,Personal Travel,Eco,2486,2,2,2,2,2,3,3,4,1,1,3,3,1,3,4,28.0,neutral or dissatisfied +27255,126974,Male,disloyal Customer,25,Business travel,Business,338,4,0,4,3,4,4,4,4,5,3,5,3,5,4,0,3.0,satisfied +27256,8609,Male,Loyal Customer,30,Personal Travel,Business,1371,3,4,3,3,4,3,4,4,4,5,4,5,4,4,20,12.0,neutral or dissatisfied +27257,112789,Female,Loyal Customer,44,Business travel,Business,2219,5,5,5,5,4,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +27258,20276,Female,Loyal Customer,12,Personal Travel,Eco,179,1,4,1,4,3,1,3,3,3,2,3,3,3,3,10,7.0,neutral or dissatisfied +27259,109566,Female,Loyal Customer,64,Personal Travel,Eco,873,1,0,1,3,4,5,4,2,2,1,1,1,2,5,95,93.0,neutral or dissatisfied +27260,19539,Male,Loyal Customer,52,Business travel,Business,1901,5,5,5,5,4,4,2,4,4,4,5,3,4,5,0,0.0,satisfied +27261,92988,Female,Loyal Customer,45,Business travel,Business,738,5,5,5,5,5,4,4,4,4,4,4,3,4,5,2,,satisfied +27262,15617,Male,Loyal Customer,49,Personal Travel,Eco,229,4,4,4,3,4,4,5,4,3,5,4,3,4,4,72,75.0,neutral or dissatisfied +27263,56703,Female,Loyal Customer,31,Personal Travel,Eco,1068,2,3,2,2,4,2,4,4,3,5,2,3,2,4,0,0.0,neutral or dissatisfied +27264,106743,Female,Loyal Customer,55,Business travel,Business,1694,3,3,3,3,2,5,4,4,4,4,4,3,4,5,9,15.0,satisfied +27265,43603,Male,disloyal Customer,38,Business travel,Eco,190,4,2,4,3,4,4,4,4,1,3,3,1,3,4,7,0.0,neutral or dissatisfied +27266,129459,Female,Loyal Customer,54,Business travel,Business,414,4,4,5,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +27267,57145,Female,Loyal Customer,52,Business travel,Business,1562,1,1,2,1,4,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +27268,34225,Male,Loyal Customer,24,Personal Travel,Eco,1179,2,5,2,1,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +27269,101536,Male,Loyal Customer,43,Personal Travel,Eco,345,1,4,1,3,4,1,4,4,1,4,2,2,5,4,5,9.0,neutral or dissatisfied +27270,9662,Male,Loyal Customer,47,Business travel,Business,1885,4,4,4,4,5,5,5,5,5,5,5,5,5,4,15,11.0,satisfied +27271,7667,Female,disloyal Customer,32,Business travel,Eco,767,3,3,3,3,4,3,4,4,3,4,3,2,4,4,124,108.0,neutral or dissatisfied +27272,40885,Female,Loyal Customer,62,Personal Travel,Eco,590,3,3,3,3,4,4,4,1,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +27273,40754,Male,Loyal Customer,32,Business travel,Business,588,5,5,1,5,5,4,5,5,1,3,3,2,4,5,6,8.0,satisfied +27274,36999,Male,Loyal Customer,18,Personal Travel,Eco,814,5,1,5,3,1,5,5,1,4,1,3,1,4,1,0,1.0,satisfied +27275,82526,Female,disloyal Customer,59,Personal Travel,Eco,1749,4,5,4,3,2,4,2,2,1,5,2,3,3,2,5,0.0,satisfied +27276,124187,Female,Loyal Customer,59,Business travel,Business,2176,3,3,4,3,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +27277,88486,Male,Loyal Customer,39,Business travel,Eco,404,4,5,5,5,4,4,4,4,3,2,1,4,4,4,0,0.0,satisfied +27278,47426,Male,Loyal Customer,61,Business travel,Business,1871,2,5,5,5,4,4,4,2,2,2,2,4,2,2,64,56.0,neutral or dissatisfied +27279,13777,Female,disloyal Customer,22,Business travel,Eco,878,2,2,2,2,1,2,1,1,2,3,5,2,1,1,4,,neutral or dissatisfied +27280,63436,Female,Loyal Customer,19,Personal Travel,Eco,372,2,5,2,1,3,2,3,3,3,2,5,3,5,3,3,17.0,neutral or dissatisfied +27281,106025,Female,Loyal Customer,56,Business travel,Business,682,3,3,3,3,2,4,5,4,4,4,4,3,4,3,48,57.0,satisfied +27282,8618,Female,Loyal Customer,44,Business travel,Business,1973,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +27283,12426,Female,Loyal Customer,13,Personal Travel,Eco,383,1,4,1,5,1,1,1,1,4,3,4,5,4,1,25,18.0,neutral or dissatisfied +27284,111585,Male,Loyal Customer,52,Personal Travel,Eco,359,3,4,3,3,3,3,3,3,5,4,5,3,5,3,7,0.0,neutral or dissatisfied +27285,56874,Male,Loyal Customer,53,Business travel,Business,2565,2,2,2,2,4,4,4,3,5,4,5,4,3,4,0,0.0,satisfied +27286,65155,Male,Loyal Customer,59,Personal Travel,Eco,190,1,4,0,4,5,0,5,5,1,4,4,4,4,5,1,0.0,neutral or dissatisfied +27287,98599,Female,Loyal Customer,37,Business travel,Business,966,2,2,2,2,3,4,4,5,5,5,5,4,5,4,6,0.0,satisfied +27288,90532,Female,Loyal Customer,41,Business travel,Business,2714,3,4,3,3,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +27289,20917,Female,Loyal Customer,25,Business travel,Eco,689,4,1,1,1,4,4,5,4,5,1,2,2,1,4,0,0.0,satisfied +27290,75206,Male,disloyal Customer,50,Business travel,Eco,1466,3,3,3,4,5,3,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +27291,106124,Male,Loyal Customer,46,Business travel,Business,1759,2,2,2,2,3,4,4,5,5,5,5,4,5,3,6,3.0,satisfied +27292,99337,Female,Loyal Customer,55,Personal Travel,Eco Plus,337,2,3,3,3,5,1,4,3,3,3,3,1,3,4,7,3.0,neutral or dissatisfied +27293,129196,Female,Loyal Customer,31,Business travel,Business,2288,1,1,1,1,1,1,1,1,2,3,4,4,3,1,1,10.0,neutral or dissatisfied +27294,43557,Male,Loyal Customer,21,Personal Travel,Business,637,4,4,4,4,3,4,3,3,3,4,4,4,4,3,5,0.0,neutral or dissatisfied +27295,96276,Male,Loyal Customer,61,Personal Travel,Eco,546,3,4,3,1,4,3,4,4,2,1,4,1,4,4,37,29.0,neutral or dissatisfied +27296,91428,Male,Loyal Customer,55,Personal Travel,Eco,549,2,3,1,3,2,1,2,2,4,4,4,5,2,2,0,0.0,neutral or dissatisfied +27297,48850,Male,Loyal Customer,20,Personal Travel,Business,109,4,4,4,4,4,4,4,4,5,3,1,5,2,4,0,0.0,neutral or dissatisfied +27298,47645,Female,Loyal Customer,16,Business travel,Business,1504,1,1,1,1,4,4,4,4,5,1,2,2,5,4,0,0.0,satisfied +27299,59855,Female,disloyal Customer,25,Business travel,Business,937,4,0,4,3,3,4,4,3,3,3,5,4,4,3,0,0.0,satisfied +27300,85699,Female,Loyal Customer,42,Business travel,Eco,1147,4,5,5,5,2,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +27301,82355,Male,Loyal Customer,48,Business travel,Business,3254,2,1,1,1,3,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +27302,60366,Female,Loyal Customer,56,Business travel,Business,1476,5,5,5,5,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +27303,79001,Female,Loyal Customer,39,Business travel,Business,3968,5,5,3,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +27304,109173,Male,disloyal Customer,23,Business travel,Business,616,0,3,0,1,3,0,3,3,3,5,5,5,5,3,5,0.0,satisfied +27305,59327,Female,Loyal Customer,60,Business travel,Business,2486,5,5,5,5,5,3,5,3,3,3,3,3,3,3,1,0.0,satisfied +27306,56517,Male,disloyal Customer,45,Business travel,Business,997,5,5,5,4,2,5,2,2,5,5,5,3,5,2,18,36.0,satisfied +27307,82235,Female,Loyal Customer,18,Personal Travel,Eco,405,3,1,3,3,2,3,2,2,2,3,3,4,3,2,25,10.0,neutral or dissatisfied +27308,461,Male,Loyal Customer,41,Business travel,Business,2227,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +27309,107051,Male,Loyal Customer,31,Business travel,Business,1962,3,4,1,4,3,3,3,3,2,1,3,4,3,3,19,7.0,neutral or dissatisfied +27310,111259,Female,Loyal Customer,52,Personal Travel,Eco,1788,4,5,5,4,5,5,5,2,2,5,2,3,2,3,2,0.0,satisfied +27311,102504,Male,Loyal Customer,60,Personal Travel,Eco,236,4,4,4,3,1,4,1,1,3,5,5,5,5,1,21,17.0,neutral or dissatisfied +27312,59372,Male,Loyal Customer,53,Business travel,Business,2556,2,1,3,1,1,3,4,2,2,2,2,2,2,1,1,0.0,neutral or dissatisfied +27313,7945,Male,disloyal Customer,25,Business travel,Eco,594,2,1,2,3,1,2,1,1,3,4,4,2,3,1,0,9.0,neutral or dissatisfied +27314,15295,Female,Loyal Customer,56,Personal Travel,Eco Plus,500,3,4,3,3,3,5,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +27315,77633,Female,disloyal Customer,23,Business travel,Eco,696,2,2,2,2,5,2,5,5,3,3,2,2,1,5,18,2.0,neutral or dissatisfied +27316,27662,Female,disloyal Customer,35,Business travel,Eco,1107,1,1,1,2,3,1,3,3,1,5,2,1,2,3,4,6.0,neutral or dissatisfied +27317,61131,Female,disloyal Customer,21,Business travel,Eco,567,2,3,2,4,3,2,1,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +27318,49915,Female,Loyal Customer,56,Business travel,Business,308,1,4,4,4,5,4,3,1,1,1,1,2,1,1,13,31.0,neutral or dissatisfied +27319,56003,Female,disloyal Customer,25,Business travel,Business,2475,3,0,3,1,3,5,4,4,4,5,4,4,4,4,23,0.0,neutral or dissatisfied +27320,8080,Male,Loyal Customer,53,Business travel,Business,2930,3,3,3,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +27321,120512,Male,Loyal Customer,41,Personal Travel,Eco Plus,337,3,2,3,3,1,3,1,1,3,3,4,4,3,1,9,7.0,neutral or dissatisfied +27322,63630,Female,Loyal Customer,43,Business travel,Business,602,3,4,4,4,1,3,2,3,3,3,3,4,3,3,0,2.0,neutral or dissatisfied +27323,42502,Female,Loyal Customer,55,Business travel,Business,1971,2,3,3,3,2,4,4,2,2,2,2,4,2,3,18,7.0,neutral or dissatisfied +27324,78227,Male,Loyal Customer,35,Personal Travel,Eco,259,3,1,3,4,3,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +27325,88430,Male,disloyal Customer,38,Business travel,Business,250,3,3,3,3,5,3,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +27326,86247,Male,Loyal Customer,33,Personal Travel,Eco,356,2,4,2,1,3,2,3,3,5,5,4,4,4,3,36,21.0,neutral or dissatisfied +27327,117226,Male,Loyal Customer,14,Personal Travel,Eco,370,1,3,1,1,4,1,4,4,3,2,2,5,3,4,54,44.0,neutral or dissatisfied +27328,39611,Male,Loyal Customer,44,Personal Travel,Eco,954,4,4,4,3,2,4,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +27329,119727,Female,Loyal Customer,48,Business travel,Business,3778,4,2,2,2,4,2,3,4,4,4,4,1,4,4,0,12.0,neutral or dissatisfied +27330,107041,Male,disloyal Customer,33,Business travel,Eco,395,2,3,2,3,5,2,5,5,4,1,4,2,4,5,23,18.0,neutral or dissatisfied +27331,85336,Male,Loyal Customer,39,Business travel,Business,689,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +27332,120009,Male,Loyal Customer,35,Business travel,Business,2907,4,4,4,4,1,2,2,4,4,4,4,4,4,2,0,0.0,satisfied +27333,119382,Female,Loyal Customer,60,Business travel,Business,2467,3,3,3,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +27334,19244,Male,Loyal Customer,8,Personal Travel,Eco,782,2,5,2,4,3,2,3,3,5,1,3,1,1,3,1,0.0,neutral or dissatisfied +27335,62356,Male,Loyal Customer,26,Business travel,Eco Plus,1735,2,1,1,1,2,2,1,2,2,1,2,4,4,2,44,21.0,neutral or dissatisfied +27336,115391,Female,disloyal Customer,30,Business travel,Eco,342,1,4,1,3,2,1,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +27337,44871,Male,disloyal Customer,39,Business travel,Eco,296,3,3,3,3,5,3,5,5,2,2,4,4,4,5,0,8.0,neutral or dissatisfied +27338,96729,Male,Loyal Customer,37,Personal Travel,Eco,696,5,4,5,4,2,5,2,2,3,2,4,3,4,2,0,0.0,satisfied +27339,12511,Male,Loyal Customer,58,Personal Travel,Eco Plus,127,3,3,3,1,4,3,4,4,1,3,3,1,4,4,40,36.0,neutral or dissatisfied +27340,97744,Male,Loyal Customer,65,Business travel,Business,587,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +27341,129050,Female,disloyal Customer,36,Business travel,Eco,742,2,3,3,4,5,2,5,5,3,1,3,4,4,5,0,0.0,neutral or dissatisfied +27342,20925,Male,disloyal Customer,28,Business travel,Eco,851,3,3,3,5,1,3,1,1,1,1,3,5,5,1,37,32.0,neutral or dissatisfied +27343,82942,Male,Loyal Customer,56,Business travel,Business,3519,3,3,3,3,4,5,4,5,5,5,5,3,5,4,19,19.0,satisfied +27344,88166,Male,Loyal Customer,40,Business travel,Business,444,5,5,5,5,3,5,5,5,5,5,5,4,5,3,14,3.0,satisfied +27345,42181,Male,Loyal Customer,50,Business travel,Eco,817,4,2,2,2,4,4,4,4,4,2,4,4,5,4,1,0.0,satisfied +27346,45927,Male,Loyal Customer,57,Personal Travel,Eco,641,3,5,3,2,2,3,2,2,3,5,4,3,4,2,8,1.0,neutral or dissatisfied +27347,25403,Male,Loyal Customer,43,Business travel,Eco,990,4,1,5,1,4,4,4,4,5,4,1,4,1,4,37,42.0,satisfied +27348,112612,Female,Loyal Customer,31,Business travel,Business,3616,1,1,1,1,5,5,5,5,2,2,3,4,5,5,13,13.0,satisfied +27349,94036,Female,Loyal Customer,53,Business travel,Business,248,5,5,5,5,3,4,4,4,4,4,4,3,4,3,54,42.0,satisfied +27350,78033,Female,Loyal Customer,45,Personal Travel,Eco,214,5,0,0,1,3,5,4,5,5,0,4,3,5,4,0,0.0,satisfied +27351,60881,Male,Loyal Customer,53,Business travel,Business,1522,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +27352,69917,Male,Loyal Customer,16,Personal Travel,Eco,1514,2,3,2,1,4,2,4,4,5,1,5,1,3,4,0,0.0,neutral or dissatisfied +27353,32696,Male,Loyal Customer,56,Business travel,Business,3133,4,3,3,3,5,4,3,1,1,1,4,1,1,3,3,4.0,neutral or dissatisfied +27354,56492,Female,Loyal Customer,31,Business travel,Business,3644,2,2,3,2,4,4,4,4,4,4,5,4,5,4,10,0.0,satisfied +27355,18099,Female,disloyal Customer,29,Business travel,Eco,610,4,5,3,2,5,3,5,5,3,5,2,2,1,5,0,0.0,neutral or dissatisfied +27356,66563,Female,Loyal Customer,50,Personal Travel,Eco,328,3,4,3,3,3,5,5,5,5,3,3,5,5,3,0,7.0,neutral or dissatisfied +27357,31757,Male,Loyal Customer,31,Business travel,Business,602,3,3,3,3,4,4,4,4,4,4,5,3,3,4,41,44.0,satisfied +27358,119463,Male,Loyal Customer,59,Business travel,Business,899,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,36.0,satisfied +27359,99614,Male,Loyal Customer,41,Business travel,Business,1224,2,4,4,4,2,2,2,3,1,4,3,2,1,2,146,159.0,neutral or dissatisfied +27360,86855,Male,Loyal Customer,32,Personal Travel,Eco,692,1,3,1,3,3,1,3,3,2,5,2,4,4,3,27,9.0,neutral or dissatisfied +27361,91835,Female,Loyal Customer,7,Personal Travel,Eco Plus,590,4,2,4,3,3,4,1,3,3,5,4,3,3,3,0,0.0,neutral or dissatisfied +27362,120437,Female,Loyal Customer,30,Business travel,Business,449,5,5,5,5,4,4,4,4,4,3,4,5,1,4,3,3.0,satisfied +27363,29975,Male,Loyal Customer,41,Business travel,Eco,213,5,1,1,1,5,5,5,5,5,1,2,2,4,5,0,0.0,satisfied +27364,46071,Male,Loyal Customer,49,Business travel,Business,541,4,4,4,4,4,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +27365,58034,Male,Loyal Customer,41,Business travel,Business,3390,3,3,2,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +27366,112984,Female,Loyal Customer,51,Business travel,Business,1797,1,1,3,1,2,3,4,4,4,4,4,3,4,4,1,0.0,satisfied +27367,83538,Female,Loyal Customer,52,Business travel,Business,1847,5,5,2,5,5,5,5,4,4,4,4,3,4,4,4,0.0,satisfied +27368,118233,Male,Loyal Customer,47,Business travel,Business,1587,5,5,5,5,5,5,4,3,3,4,3,3,3,3,0,10.0,satisfied +27369,72433,Female,Loyal Customer,46,Business travel,Business,1585,2,2,2,2,4,5,4,4,4,4,4,4,4,5,24,1.0,satisfied +27370,107245,Female,Loyal Customer,70,Personal Travel,Business,283,3,1,5,3,2,4,4,4,4,5,4,4,4,3,20,31.0,neutral or dissatisfied +27371,11693,Female,disloyal Customer,66,Business travel,Business,429,4,4,4,4,3,4,5,3,5,3,5,4,4,3,60,59.0,satisfied +27372,31308,Female,Loyal Customer,45,Business travel,Eco,680,3,3,3,3,1,4,4,3,3,3,3,2,3,4,13,16.0,neutral or dissatisfied +27373,121002,Female,Loyal Customer,59,Personal Travel,Eco,861,4,5,4,2,4,5,5,3,4,5,4,5,5,5,231,341.0,satisfied +27374,75043,Male,Loyal Customer,26,Personal Travel,Eco,236,3,3,0,2,2,0,2,2,4,3,5,3,3,2,0,3.0,neutral or dissatisfied +27375,89842,Female,disloyal Customer,23,Business travel,Business,1310,4,0,4,4,1,4,1,1,3,5,4,3,4,1,0,0.0,satisfied +27376,90947,Male,Loyal Customer,38,Business travel,Eco,366,5,1,1,1,5,5,5,5,3,1,1,2,2,5,0,0.0,satisfied +27377,99403,Male,Loyal Customer,29,Business travel,Business,3726,4,4,4,4,4,4,4,4,3,3,5,4,5,4,2,2.0,satisfied +27378,61802,Female,Loyal Customer,55,Personal Travel,Eco,1379,3,4,3,4,3,5,4,5,5,3,5,4,5,5,0,21.0,neutral or dissatisfied +27379,33854,Female,Loyal Customer,10,Personal Travel,Eco,1562,3,4,3,1,4,3,4,4,5,5,3,4,5,4,0,0.0,neutral or dissatisfied +27380,23237,Female,Loyal Customer,50,Business travel,Business,549,4,4,4,4,3,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +27381,25094,Male,disloyal Customer,20,Business travel,Eco,369,3,3,3,1,2,3,2,2,5,2,1,3,4,2,0,0.0,neutral or dissatisfied +27382,110347,Female,Loyal Customer,49,Business travel,Business,3623,3,3,5,3,2,4,5,5,5,5,5,3,5,4,56,40.0,satisfied +27383,94699,Female,Loyal Customer,50,Business travel,Business,1894,2,2,2,2,2,2,2,2,2,2,2,4,2,3,15,4.0,neutral or dissatisfied +27384,85935,Male,disloyal Customer,36,Business travel,Business,447,2,1,1,2,4,1,5,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +27385,43783,Male,Loyal Customer,40,Personal Travel,Eco,546,3,1,3,3,3,3,3,3,1,2,4,2,3,3,0,2.0,neutral or dissatisfied +27386,109242,Female,Loyal Customer,33,Personal Travel,Eco,616,3,4,3,1,2,3,2,2,5,3,5,5,4,2,3,0.0,neutral or dissatisfied +27387,8666,Male,Loyal Customer,38,Business travel,Business,3382,2,1,1,1,4,2,3,2,2,2,2,2,2,2,5,12.0,neutral or dissatisfied +27388,69075,Female,disloyal Customer,15,Business travel,Eco,1389,1,1,1,3,4,1,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +27389,18489,Male,Loyal Customer,57,Business travel,Eco,201,5,2,2,2,5,5,5,5,4,3,3,2,1,5,0,0.0,satisfied +27390,95118,Female,Loyal Customer,19,Personal Travel,Eco,239,1,5,1,2,5,1,4,5,3,4,5,5,4,5,18,7.0,neutral or dissatisfied +27391,66059,Male,Loyal Customer,49,Business travel,Eco,1055,4,1,1,1,5,4,5,5,4,3,5,1,4,5,0,0.0,satisfied +27392,101080,Male,Loyal Customer,40,Personal Travel,Business,1090,3,4,3,2,1,1,3,2,2,3,2,2,2,2,102,114.0,neutral or dissatisfied +27393,124609,Female,Loyal Customer,49,Business travel,Business,1671,1,1,5,1,5,3,4,5,5,4,5,3,5,3,0,6.0,satisfied +27394,43647,Male,Loyal Customer,50,Personal Travel,Business,695,2,4,2,3,2,4,4,1,1,2,1,3,1,5,11,0.0,neutral or dissatisfied +27395,59981,Female,Loyal Customer,19,Personal Travel,Eco,937,3,4,3,2,3,3,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +27396,85164,Female,Loyal Customer,51,Business travel,Eco,689,2,1,1,1,4,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +27397,87524,Female,Loyal Customer,57,Personal Travel,Eco,373,3,5,3,2,2,2,5,4,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +27398,28096,Male,Loyal Customer,38,Business travel,Business,834,1,1,1,1,1,1,2,5,5,5,5,3,5,1,0,6.0,satisfied +27399,29233,Male,Loyal Customer,27,Business travel,Eco,834,2,2,2,2,2,2,2,2,1,4,2,1,1,2,0,0.0,neutral or dissatisfied +27400,49007,Female,Loyal Customer,47,Business travel,Business,3114,5,5,5,5,4,3,1,5,5,5,5,4,5,4,0,0.0,satisfied +27401,54608,Female,Loyal Customer,28,Business travel,Business,2034,2,2,2,2,3,4,3,3,5,2,3,1,2,3,2,0.0,satisfied +27402,62169,Female,Loyal Customer,9,Business travel,Business,2454,4,2,5,2,4,4,4,4,1,1,3,3,4,4,10,0.0,neutral or dissatisfied +27403,81160,Male,Loyal Customer,37,Personal Travel,Eco,700,2,4,2,4,4,2,4,4,3,4,4,4,5,4,10,0.0,neutral or dissatisfied +27404,92209,Male,Loyal Customer,65,Personal Travel,Eco,2079,5,3,5,4,4,5,4,4,1,2,4,4,3,4,0,0.0,satisfied +27405,21282,Female,Loyal Customer,36,Business travel,Business,2570,3,3,3,3,5,2,2,4,4,4,4,4,4,2,0,17.0,satisfied +27406,36459,Female,Loyal Customer,26,Personal Travel,Eco,867,2,4,2,4,5,2,5,5,5,1,1,1,2,5,0,0.0,neutral or dissatisfied +27407,58777,Male,disloyal Customer,22,Business travel,Eco,1005,3,3,3,4,3,3,3,3,4,3,3,2,4,3,10,9.0,neutral or dissatisfied +27408,20684,Male,Loyal Customer,58,Business travel,Eco Plus,552,1,2,2,2,1,1,1,1,4,1,3,2,4,1,8,14.0,neutral or dissatisfied +27409,22855,Male,Loyal Customer,21,Personal Travel,Eco,147,2,4,2,3,5,2,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +27410,28979,Female,Loyal Customer,56,Business travel,Business,2279,3,5,5,5,2,3,2,3,3,3,3,4,3,2,0,14.0,neutral or dissatisfied +27411,27734,Female,Loyal Customer,56,Business travel,Business,2952,1,1,1,1,2,4,3,4,4,4,4,4,4,1,0,0.0,satisfied +27412,53845,Male,Loyal Customer,18,Business travel,Business,3028,3,2,2,2,3,3,3,3,1,5,2,2,3,3,0,0.0,neutral or dissatisfied +27413,15576,Male,Loyal Customer,28,Business travel,Business,296,2,2,3,2,4,5,4,4,1,5,5,2,2,4,0,0.0,satisfied +27414,24654,Female,Loyal Customer,51,Business travel,Business,2672,5,5,5,5,3,5,1,4,4,4,4,5,4,3,0,0.0,satisfied +27415,39517,Male,Loyal Customer,48,Business travel,Business,1868,2,3,3,3,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +27416,60622,Female,Loyal Customer,57,Business travel,Eco,801,4,1,1,1,2,2,3,4,4,4,4,1,4,2,11,2.0,satisfied +27417,24141,Female,Loyal Customer,61,Personal Travel,Business,147,4,5,4,4,2,5,3,4,4,4,4,2,4,2,0,0.0,satisfied +27418,48984,Female,disloyal Customer,48,Business travel,Eco,308,0,0,0,3,2,0,2,2,2,5,5,1,5,2,10,3.0,satisfied +27419,63520,Female,disloyal Customer,19,Business travel,Eco,1009,2,1,1,3,3,1,3,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +27420,92781,Female,Loyal Customer,67,Personal Travel,Eco,1671,4,1,4,3,5,3,3,1,1,4,3,2,1,2,0,0.0,neutral or dissatisfied +27421,11057,Female,Loyal Customer,70,Personal Travel,Eco,517,2,5,2,1,2,5,4,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +27422,36769,Female,Loyal Customer,25,Business travel,Business,2704,1,1,1,1,4,4,4,5,2,5,3,4,5,4,0,1.0,satisfied +27423,30232,Female,Loyal Customer,46,Business travel,Business,826,3,3,4,3,1,4,1,5,5,5,5,1,5,2,6,40.0,satisfied +27424,50636,Female,Loyal Customer,50,Personal Travel,Eco,77,3,5,3,3,3,4,4,4,4,3,2,5,4,5,0,0.0,neutral or dissatisfied +27425,62264,Male,Loyal Customer,34,Business travel,Eco Plus,2565,0,1,1,1,1,4,4,3,1,4,2,4,2,4,278,278.0,satisfied +27426,117763,Female,Loyal Customer,31,Business travel,Eco,1670,1,1,1,1,1,1,1,1,2,4,4,3,4,1,10,3.0,neutral or dissatisfied +27427,59578,Male,Loyal Customer,33,Business travel,Business,2291,3,4,5,5,3,3,3,3,2,5,2,1,3,3,0,0.0,neutral or dissatisfied +27428,50009,Female,Loyal Customer,55,Business travel,Eco,337,4,1,5,1,3,4,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +27429,109229,Female,Loyal Customer,31,Personal Travel,Eco,616,3,5,3,3,4,3,4,4,2,2,4,1,3,4,3,0.0,neutral or dissatisfied +27430,3910,Male,Loyal Customer,63,Personal Travel,Eco,213,3,0,3,1,5,3,5,5,5,4,4,3,5,5,0,5.0,neutral or dissatisfied +27431,4659,Male,disloyal Customer,19,Business travel,Eco,364,1,4,0,1,3,0,2,3,5,3,5,4,4,3,0,3.0,neutral or dissatisfied +27432,2143,Female,Loyal Customer,22,Business travel,Eco Plus,431,5,2,2,2,5,5,5,5,1,1,4,4,5,5,0,0.0,satisfied +27433,21261,Male,disloyal Customer,24,Business travel,Eco,903,0,0,0,1,2,0,2,2,2,1,2,4,2,2,0,0.0,satisfied +27434,99620,Female,Loyal Customer,41,Business travel,Business,3600,5,5,5,5,4,5,4,4,4,4,4,5,4,4,50,48.0,satisfied +27435,125194,Female,Loyal Customer,49,Business travel,Business,2322,3,3,3,3,2,4,4,4,4,3,4,3,4,3,0,0.0,satisfied +27436,13355,Female,Loyal Customer,63,Business travel,Eco,748,2,4,4,4,3,3,3,2,2,2,2,5,2,1,0,0.0,satisfied +27437,8088,Female,Loyal Customer,62,Business travel,Business,1616,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +27438,118123,Male,Loyal Customer,37,Business travel,Business,1506,3,3,5,3,4,5,4,4,4,4,4,4,4,5,47,43.0,satisfied +27439,63790,Female,Loyal Customer,44,Business travel,Eco,221,5,5,5,5,5,2,5,5,5,5,5,5,5,3,7,27.0,satisfied +27440,121954,Male,Loyal Customer,46,Business travel,Business,3234,3,3,3,3,5,4,4,4,4,4,4,3,4,5,16,15.0,satisfied +27441,1581,Female,disloyal Customer,36,Business travel,Business,140,2,2,2,1,1,2,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +27442,62898,Male,Loyal Customer,30,Business travel,Business,1970,5,5,5,5,5,5,5,5,4,4,5,3,5,5,0,0.0,satisfied +27443,88300,Male,disloyal Customer,27,Business travel,Business,581,4,4,4,2,2,4,2,2,4,4,5,3,4,2,2,0.0,satisfied +27444,91001,Male,Loyal Customer,23,Personal Travel,Eco,404,3,1,3,4,3,3,3,3,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +27445,71280,Male,Loyal Customer,26,Personal Travel,Eco,740,2,4,2,2,4,2,4,4,4,4,5,3,4,4,43,29.0,neutral or dissatisfied +27446,43466,Male,Loyal Customer,52,Business travel,Eco,524,5,1,4,1,5,5,5,5,4,5,4,1,1,5,86,100.0,satisfied +27447,48220,Female,Loyal Customer,57,Personal Travel,Eco,259,4,4,4,4,4,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +27448,56252,Female,Loyal Customer,54,Business travel,Business,404,2,2,2,2,4,4,5,4,4,4,4,3,4,4,77,76.0,satisfied +27449,34663,Female,Loyal Customer,50,Business travel,Business,301,3,1,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +27450,85898,Male,Loyal Customer,54,Business travel,Business,2222,4,4,2,4,4,4,4,4,4,4,4,3,4,4,29,24.0,satisfied +27451,118372,Female,Loyal Customer,46,Business travel,Business,3665,0,0,0,1,3,5,5,3,3,5,5,4,3,4,53,43.0,satisfied +27452,873,Female,Loyal Customer,35,Business travel,Business,3587,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +27453,73451,Male,Loyal Customer,26,Personal Travel,Eco,1197,1,4,1,2,4,1,5,4,1,4,4,5,2,4,0,0.0,neutral or dissatisfied +27454,83423,Male,Loyal Customer,19,Personal Travel,Eco,632,2,4,2,3,2,2,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +27455,49853,Female,Loyal Customer,66,Business travel,Eco,326,2,5,5,5,4,4,4,2,2,2,2,3,2,2,39,46.0,neutral or dissatisfied +27456,100356,Female,Loyal Customer,22,Personal Travel,Eco,1011,3,5,3,1,4,3,4,4,1,1,4,3,3,4,18,31.0,neutral or dissatisfied +27457,32921,Female,Loyal Customer,25,Personal Travel,Eco,163,2,1,2,2,3,2,3,3,4,2,2,3,3,3,0,0.0,neutral or dissatisfied +27458,40744,Male,Loyal Customer,49,Business travel,Eco,584,5,3,3,3,5,5,5,5,1,4,3,3,4,5,0,0.0,satisfied +27459,1708,Male,disloyal Customer,21,Business travel,Eco,364,3,0,3,2,4,3,4,4,5,3,5,4,5,4,0,1.0,neutral or dissatisfied +27460,125232,Male,Loyal Customer,27,Business travel,Business,1149,3,3,3,3,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +27461,688,Female,Loyal Customer,42,Business travel,Business,1988,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +27462,81577,Female,disloyal Customer,24,Business travel,Eco,1039,2,2,2,4,2,2,2,2,2,1,4,1,4,2,112,97.0,neutral or dissatisfied +27463,56532,Female,Loyal Customer,35,Business travel,Business,1065,5,5,5,5,4,4,5,5,5,5,5,5,5,5,65,59.0,satisfied +27464,8776,Male,Loyal Customer,33,Business travel,Business,3961,1,1,5,1,4,4,4,4,5,3,5,4,5,4,0,11.0,satisfied +27465,121549,Female,disloyal Customer,27,Business travel,Business,936,1,1,1,3,3,1,3,3,5,4,5,5,4,3,7,8.0,neutral or dissatisfied +27466,2374,Female,Loyal Customer,51,Business travel,Business,767,5,5,5,5,4,5,5,5,5,5,5,5,5,4,9,5.0,satisfied +27467,64960,Female,Loyal Customer,50,Business travel,Eco,151,4,2,2,2,1,4,4,4,4,4,4,3,4,5,13,0.0,satisfied +27468,28790,Male,Loyal Customer,10,Personal Travel,Business,954,4,3,4,4,4,4,4,4,2,4,3,4,4,4,0,0.0,neutral or dissatisfied +27469,47244,Male,Loyal Customer,59,Business travel,Business,3886,2,4,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +27470,62562,Male,disloyal Customer,21,Business travel,Eco,721,3,3,3,3,4,3,4,4,2,5,2,4,4,4,1,2.0,neutral or dissatisfied +27471,41787,Male,Loyal Customer,22,Business travel,Business,2275,2,2,2,2,4,4,4,4,5,3,5,4,4,4,0,5.0,satisfied +27472,44807,Female,Loyal Customer,69,Business travel,Business,2638,2,1,1,1,1,1,2,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +27473,1809,Male,disloyal Customer,59,Business travel,Business,500,1,2,2,3,2,1,2,2,1,1,2,4,3,2,4,0.0,neutral or dissatisfied +27474,24176,Female,Loyal Customer,36,Business travel,Business,151,4,4,4,4,4,2,1,5,5,5,5,3,5,1,12,14.0,satisfied +27475,9334,Female,Loyal Customer,48,Personal Travel,Eco Plus,419,3,5,3,5,4,1,5,2,2,3,2,5,2,4,26,22.0,neutral or dissatisfied +27476,119615,Female,Loyal Customer,30,Business travel,Eco Plus,1979,3,3,3,3,3,3,3,3,2,2,3,1,3,3,2,10.0,neutral or dissatisfied +27477,95332,Male,Loyal Customer,51,Personal Travel,Eco,496,1,2,1,3,1,1,1,1,2,4,4,1,3,1,9,10.0,neutral or dissatisfied +27478,68502,Female,Loyal Customer,36,Personal Travel,Eco,1303,3,4,3,5,4,3,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +27479,27960,Female,Loyal Customer,60,Personal Travel,Eco,1660,1,5,1,3,3,5,4,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +27480,44994,Female,Loyal Customer,16,Business travel,Eco,222,4,5,5,5,4,4,3,4,2,4,4,2,3,4,21,15.0,neutral or dissatisfied +27481,108319,Male,Loyal Customer,48,Business travel,Business,1750,5,5,5,5,5,3,4,5,5,5,5,4,5,3,0,2.0,satisfied +27482,65336,Female,disloyal Customer,26,Business travel,Business,432,0,0,0,4,3,0,3,3,4,5,4,4,4,3,0,0.0,satisfied +27483,41715,Male,Loyal Customer,62,Personal Travel,Eco,1404,4,3,3,5,1,3,1,1,5,4,1,3,2,1,0,0.0,satisfied +27484,14025,Female,disloyal Customer,39,Business travel,Business,1117,1,1,1,4,3,1,3,3,5,5,3,5,1,3,99,110.0,neutral or dissatisfied +27485,64235,Female,disloyal Customer,23,Business travel,Eco,836,4,4,4,3,4,4,1,4,1,4,4,2,3,4,35,24.0,neutral or dissatisfied +27486,122459,Female,Loyal Customer,41,Business travel,Business,1636,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +27487,99305,Male,Loyal Customer,45,Business travel,Business,3906,1,1,1,1,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +27488,97001,Female,Loyal Customer,61,Personal Travel,Eco,883,1,4,1,1,2,5,4,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +27489,61127,Female,Loyal Customer,34,Business travel,Business,1638,1,1,1,1,5,4,4,5,5,5,5,4,5,3,32,25.0,satisfied +27490,92150,Female,Loyal Customer,44,Business travel,Eco Plus,1535,3,5,5,5,5,3,4,3,3,3,3,3,3,2,13,1.0,neutral or dissatisfied +27491,112474,Female,Loyal Customer,31,Personal Travel,Eco,909,5,3,5,3,5,5,5,5,1,1,2,1,2,5,4,4.0,satisfied +27492,63225,Female,Loyal Customer,56,Business travel,Business,3627,4,2,3,2,4,4,4,4,4,4,4,4,4,1,20,39.0,neutral or dissatisfied +27493,91848,Female,disloyal Customer,18,Business travel,Eco,1797,1,1,1,4,1,1,1,1,4,2,2,1,4,1,10,29.0,neutral or dissatisfied +27494,13698,Female,Loyal Customer,9,Personal Travel,Eco,483,2,4,2,3,2,2,4,2,3,5,4,5,4,2,48,48.0,neutral or dissatisfied +27495,76331,Male,Loyal Customer,34,Personal Travel,Eco,2182,2,5,2,3,5,2,5,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +27496,51956,Male,Loyal Customer,25,Business travel,Business,2807,3,3,3,3,4,5,4,4,3,2,5,2,2,4,0,0.0,satisfied +27497,94468,Male,disloyal Customer,48,Business travel,Eco,239,2,1,2,1,2,2,5,2,3,3,1,2,2,2,14,6.0,neutral or dissatisfied +27498,19034,Female,Loyal Customer,29,Personal Travel,Eco,871,1,4,1,3,4,1,4,4,5,3,2,3,2,4,0,0.0,neutral or dissatisfied +27499,79149,Male,Loyal Customer,58,Personal Travel,Eco Plus,226,2,4,2,3,5,2,5,5,4,5,5,4,5,5,0,10.0,neutral or dissatisfied +27500,37666,Female,Loyal Customer,11,Personal Travel,Eco,944,3,4,3,3,3,3,3,3,2,4,3,2,3,3,0,2.0,neutral or dissatisfied +27501,20680,Male,Loyal Customer,42,Personal Travel,Eco,552,4,0,4,1,1,4,1,1,5,2,5,3,5,1,42,23.0,satisfied +27502,18772,Male,Loyal Customer,49,Business travel,Business,3513,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +27503,86174,Female,disloyal Customer,44,Business travel,Business,356,3,2,2,2,4,3,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +27504,44397,Female,Loyal Customer,47,Business travel,Eco,342,3,2,2,2,3,3,3,3,3,3,3,4,3,2,55,47.0,neutral or dissatisfied +27505,117969,Male,Loyal Customer,67,Personal Travel,Eco,255,2,5,0,1,4,0,4,4,2,5,2,1,1,4,13,11.0,neutral or dissatisfied +27506,19637,Male,Loyal Customer,10,Personal Travel,Eco,642,3,3,3,2,4,3,4,4,4,5,2,2,3,4,0,0.0,neutral or dissatisfied +27507,27855,Male,Loyal Customer,10,Personal Travel,Eco,680,2,5,2,3,1,2,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +27508,18114,Male,disloyal Customer,24,Business travel,Eco,629,3,2,3,4,4,3,4,4,3,5,4,3,3,4,23,2.0,neutral or dissatisfied +27509,74497,Female,Loyal Customer,36,Business travel,Business,1431,5,5,2,5,4,5,5,2,2,2,2,3,2,3,21,12.0,satisfied +27510,99233,Male,Loyal Customer,26,Business travel,Business,2048,3,2,2,2,3,3,3,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +27511,93920,Female,Loyal Customer,20,Business travel,Business,507,2,2,2,2,2,2,2,2,5,3,4,5,5,2,0,7.0,satisfied +27512,29529,Female,Loyal Customer,27,Personal Travel,Eco,1009,2,5,2,1,3,2,3,3,3,5,4,4,2,3,0,0.0,neutral or dissatisfied +27513,31844,Male,Loyal Customer,39,Business travel,Business,2640,2,2,2,2,4,5,1,3,3,3,3,5,3,4,0,0.0,satisfied +27514,44129,Male,Loyal Customer,73,Business travel,Business,120,5,5,5,5,3,4,1,4,4,4,3,2,4,3,4,1.0,satisfied +27515,62483,Female,Loyal Customer,59,Business travel,Business,1726,5,1,5,5,5,4,4,4,4,5,4,3,4,4,9,0.0,satisfied +27516,70471,Male,Loyal Customer,41,Business travel,Business,2293,1,1,1,1,3,5,4,4,4,4,4,3,4,5,0,5.0,satisfied +27517,35357,Male,Loyal Customer,35,Business travel,Business,2038,2,4,4,4,3,2,2,2,2,2,2,4,2,2,17,39.0,neutral or dissatisfied +27518,50594,Female,Loyal Customer,11,Personal Travel,Eco,326,4,2,4,2,5,4,1,5,2,5,2,4,3,5,0,0.0,satisfied +27519,81449,Male,disloyal Customer,52,Business travel,Business,528,1,1,1,2,4,1,4,4,4,3,4,5,4,4,1,0.0,neutral or dissatisfied +27520,110551,Male,disloyal Customer,25,Business travel,Eco,488,3,1,3,2,3,3,3,3,3,2,1,3,1,3,14,3.0,neutral or dissatisfied +27521,111100,Female,disloyal Customer,39,Business travel,Business,197,3,3,3,3,5,3,5,5,5,4,4,3,4,5,8,40.0,neutral or dissatisfied +27522,7548,Female,Loyal Customer,38,Business travel,Business,1705,3,4,3,3,3,4,5,4,4,4,4,5,4,5,0,1.0,satisfied +27523,75123,Female,Loyal Customer,49,Business travel,Business,1723,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +27524,9696,Female,Loyal Customer,8,Personal Travel,Eco,199,2,5,2,4,3,2,3,3,1,4,5,4,1,3,45,29.0,neutral or dissatisfied +27525,64881,Male,Loyal Customer,17,Business travel,Business,190,3,3,3,3,2,2,3,2,1,3,4,1,4,2,34,21.0,neutral or dissatisfied +27526,101965,Male,Loyal Customer,36,Business travel,Business,3958,1,1,1,1,2,4,4,5,5,5,5,3,5,4,4,3.0,satisfied +27527,2524,Female,Loyal Customer,48,Business travel,Business,3093,0,0,0,1,5,5,4,5,5,5,3,5,5,4,93,102.0,satisfied +27528,18157,Male,disloyal Customer,34,Business travel,Eco,430,1,4,1,4,5,1,5,5,4,5,4,3,3,5,0,0.0,neutral or dissatisfied +27529,100322,Female,disloyal Customer,24,Business travel,Eco,1092,2,2,2,4,1,2,1,1,4,1,4,3,3,1,17,7.0,neutral or dissatisfied +27530,95483,Female,Loyal Customer,50,Business travel,Eco Plus,562,4,2,2,2,2,4,4,4,4,4,4,4,4,4,6,1.0,neutral or dissatisfied +27531,11612,Male,Loyal Customer,55,Personal Travel,Eco,468,2,2,2,4,1,2,1,1,4,1,3,1,4,1,0,0.0,neutral or dissatisfied +27532,30411,Male,Loyal Customer,41,Business travel,Eco Plus,641,5,1,2,2,5,5,5,5,3,5,4,2,5,5,0,4.0,satisfied +27533,90442,Male,disloyal Customer,22,Business travel,Business,250,5,4,5,3,3,5,3,3,4,5,5,3,5,3,0,0.0,satisfied +27534,14846,Female,Loyal Customer,29,Personal Travel,Business,343,1,4,1,2,2,1,2,2,4,4,2,3,1,2,3,0.0,neutral or dissatisfied +27535,92434,Female,disloyal Customer,55,Business travel,Business,1133,4,4,4,4,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +27536,3579,Male,Loyal Customer,34,Personal Travel,Eco Plus,227,4,5,4,4,3,4,3,3,5,2,4,5,4,3,0,3.0,neutral or dissatisfied +27537,21808,Male,Loyal Customer,14,Personal Travel,Eco,241,1,2,1,3,4,1,4,4,1,2,2,1,2,4,0,0.0,neutral or dissatisfied +27538,63106,Male,Loyal Customer,25,Business travel,Eco Plus,862,4,3,5,3,4,4,4,4,4,5,3,2,5,4,2,0.0,satisfied +27539,84752,Female,Loyal Customer,53,Business travel,Business,2077,4,4,4,4,4,4,5,3,3,4,3,3,3,5,19,13.0,satisfied +27540,94592,Male,Loyal Customer,43,Business travel,Business,148,5,5,4,5,2,4,5,4,4,4,5,3,4,4,0,13.0,satisfied +27541,41691,Male,Loyal Customer,29,Personal Travel,Eco,347,3,5,3,2,3,3,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +27542,66217,Male,disloyal Customer,21,Business travel,Eco,550,4,0,4,4,1,4,1,1,4,2,3,2,3,1,20,14.0,neutral or dissatisfied +27543,114818,Female,Loyal Customer,42,Business travel,Business,2986,2,2,2,2,3,4,5,3,3,4,3,4,3,4,13,0.0,satisfied +27544,43335,Male,disloyal Customer,29,Business travel,Eco,531,4,4,4,3,1,4,3,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +27545,125020,Male,Loyal Customer,22,Personal Travel,Eco,184,2,4,2,1,4,2,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +27546,93456,Male,Loyal Customer,58,Personal Travel,Eco,697,3,4,4,3,5,4,5,5,4,2,5,5,5,5,0,7.0,neutral or dissatisfied +27547,47235,Female,Loyal Customer,42,Personal Travel,Eco Plus,965,3,5,3,4,5,5,5,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +27548,64920,Male,Loyal Customer,64,Business travel,Business,190,2,2,2,2,5,3,3,4,4,3,2,4,4,4,0,33.0,neutral or dissatisfied +27549,91656,Male,Loyal Customer,50,Personal Travel,Eco,1199,3,4,2,3,3,2,3,3,3,5,3,1,3,3,0,13.0,neutral or dissatisfied +27550,113565,Female,Loyal Customer,68,Business travel,Business,226,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,4.0,satisfied +27551,35953,Female,Loyal Customer,38,Business travel,Business,2395,5,5,5,5,1,4,3,4,4,4,4,4,4,5,0,0.0,satisfied +27552,46788,Female,disloyal Customer,42,Business travel,Business,776,2,2,2,4,5,2,5,5,2,3,3,4,3,5,0,1.0,neutral or dissatisfied +27553,8447,Female,Loyal Customer,43,Business travel,Business,979,2,1,1,1,1,3,4,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +27554,101888,Female,disloyal Customer,43,Business travel,Business,2173,2,2,2,5,1,2,1,1,4,4,4,4,5,1,19,0.0,neutral or dissatisfied +27555,98457,Female,Loyal Customer,59,Business travel,Business,3757,1,1,4,1,5,4,5,4,4,4,4,5,4,5,18,26.0,satisfied +27556,72842,Male,Loyal Customer,8,Personal Travel,Eco,1013,1,5,1,3,1,1,4,1,2,4,1,2,5,1,0,0.0,neutral or dissatisfied +27557,98282,Female,Loyal Customer,45,Business travel,Eco,736,4,2,2,2,1,4,4,4,4,4,4,1,4,3,0,6.0,neutral or dissatisfied +27558,126249,Female,disloyal Customer,38,Business travel,Eco,107,3,0,2,3,4,2,4,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +27559,25178,Female,disloyal Customer,28,Business travel,Business,577,2,2,2,1,2,2,2,2,1,4,5,3,1,2,0,29.0,neutral or dissatisfied +27560,97938,Female,disloyal Customer,34,Business travel,Eco,655,1,1,1,4,5,1,5,5,4,1,3,2,4,5,0,0.0,neutral or dissatisfied +27561,36912,Female,Loyal Customer,39,Business travel,Business,740,2,2,2,2,4,2,3,4,4,4,4,5,4,4,0,0.0,satisfied +27562,46691,Male,Loyal Customer,16,Personal Travel,Eco,73,3,5,3,1,3,3,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +27563,78685,Female,Loyal Customer,39,Business travel,Business,2380,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +27564,25192,Female,Loyal Customer,70,Personal Travel,Eco,577,3,2,3,4,1,4,3,1,1,3,1,3,1,2,6,7.0,neutral or dissatisfied +27565,129043,Male,disloyal Customer,29,Business travel,Business,1376,4,4,4,1,3,4,3,3,3,4,4,5,4,3,0,0.0,satisfied +27566,38190,Male,Loyal Customer,13,Personal Travel,Eco,1121,4,5,4,1,1,4,1,1,4,4,5,5,4,1,10,0.0,neutral or dissatisfied +27567,95964,Female,Loyal Customer,39,Business travel,Business,2736,5,5,5,5,2,5,4,5,5,5,5,5,5,3,38,36.0,satisfied +27568,117295,Female,Loyal Customer,25,Business travel,Business,304,0,0,0,4,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +27569,33429,Female,Loyal Customer,12,Business travel,Business,2399,4,5,5,5,4,3,4,4,3,5,4,2,4,4,0,0.0,neutral or dissatisfied +27570,67582,Male,disloyal Customer,26,Business travel,Business,1235,5,5,5,3,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +27571,5227,Male,Loyal Customer,36,Business travel,Eco,293,4,5,5,5,4,4,4,4,1,5,3,3,3,4,2,0.0,neutral or dissatisfied +27572,126232,Male,Loyal Customer,38,Business travel,Business,328,3,3,3,3,3,4,5,5,5,5,5,4,5,3,10,5.0,satisfied +27573,42568,Male,Loyal Customer,46,Business travel,Business,240,2,2,2,2,3,1,4,5,5,5,5,2,5,4,0,3.0,satisfied +27574,71788,Female,Loyal Customer,17,Business travel,Business,1846,3,3,3,3,3,2,3,3,3,5,2,4,4,3,90,90.0,neutral or dissatisfied +27575,117504,Female,Loyal Customer,15,Personal Travel,Eco,507,4,5,4,3,3,4,3,3,5,5,4,4,5,3,4,0.0,neutral or dissatisfied +27576,723,Female,disloyal Customer,50,Business travel,Business,140,3,3,3,4,5,3,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +27577,121886,Female,Loyal Customer,45,Personal Travel,Eco,366,1,4,1,2,3,5,4,3,3,1,3,4,3,5,1,2.0,neutral or dissatisfied +27578,69785,Female,disloyal Customer,54,Business travel,Business,655,1,1,1,3,1,1,1,1,4,3,5,3,4,1,0,2.0,neutral or dissatisfied +27579,18694,Male,disloyal Customer,20,Business travel,Eco Plus,192,0,0,1,4,3,1,1,3,1,1,4,4,4,3,123,117.0,satisfied +27580,90930,Female,Loyal Customer,25,Business travel,Business,366,4,4,1,4,3,3,3,3,5,2,2,1,1,3,0,0.0,satisfied +27581,110624,Male,Loyal Customer,49,Business travel,Business,3716,4,4,4,4,2,4,4,3,3,4,3,3,3,5,0,1.0,satisfied +27582,68243,Female,Loyal Customer,59,Business travel,Business,2121,3,3,4,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +27583,66421,Male,Loyal Customer,24,Personal Travel,Eco,1562,3,5,3,4,1,3,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +27584,78085,Male,Loyal Customer,10,Personal Travel,Eco Plus,332,4,5,2,1,5,2,5,5,4,2,4,5,4,5,0,7.0,neutral or dissatisfied +27585,3186,Female,Loyal Customer,29,Business travel,Business,2560,2,4,4,4,2,2,2,2,4,4,2,2,2,2,0,0.0,neutral or dissatisfied +27586,123619,Female,Loyal Customer,51,Business travel,Business,214,3,3,3,3,4,4,5,4,4,4,4,3,4,3,0,14.0,satisfied +27587,116393,Male,Loyal Customer,64,Personal Travel,Eco,358,2,4,2,3,3,2,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +27588,21394,Male,Loyal Customer,69,Business travel,Business,164,3,3,1,3,5,4,1,4,4,4,5,5,4,5,0,0.0,satisfied +27589,63791,Male,disloyal Customer,35,Business travel,Eco,1721,4,4,4,4,4,4,4,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +27590,59830,Male,Loyal Customer,53,Business travel,Business,2748,2,2,2,2,3,5,5,4,4,5,4,5,4,4,31,12.0,satisfied +27591,12585,Male,Loyal Customer,51,Business travel,Eco,542,5,3,3,3,5,5,5,5,5,2,2,4,3,5,8,8.0,satisfied +27592,116586,Female,Loyal Customer,41,Business travel,Business,3307,4,4,4,4,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +27593,73516,Male,disloyal Customer,23,Business travel,Eco,594,5,0,5,2,2,5,2,2,5,5,5,5,4,2,9,1.0,satisfied +27594,110291,Male,Loyal Customer,54,Business travel,Business,2394,4,4,4,4,3,4,4,5,5,5,5,5,5,5,61,50.0,satisfied +27595,64478,Male,disloyal Customer,27,Business travel,Business,551,5,5,5,3,1,5,1,1,3,3,4,4,4,1,0,0.0,satisfied +27596,52822,Female,Loyal Customer,16,Personal Travel,Eco,2402,2,1,1,2,1,1,1,1,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +27597,23700,Male,Loyal Customer,48,Business travel,Eco,212,3,4,4,4,3,3,3,3,1,4,4,1,4,3,107,104.0,neutral or dissatisfied +27598,97642,Female,Loyal Customer,33,Business travel,Business,1587,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +27599,48635,Female,disloyal Customer,24,Business travel,Business,110,4,5,4,4,2,4,2,2,5,4,5,4,4,2,4,14.0,satisfied +27600,20258,Female,disloyal Customer,44,Business travel,Eco,137,1,1,1,3,2,1,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +27601,2387,Female,disloyal Customer,25,Business travel,Business,604,3,0,3,4,5,3,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +27602,127881,Female,Loyal Customer,43,Personal Travel,Eco,1276,1,2,1,2,1,4,4,4,3,3,2,4,3,4,138,105.0,neutral or dissatisfied +27603,29514,Female,Loyal Customer,68,Personal Travel,Eco Plus,1107,1,0,0,4,3,4,4,5,5,0,5,4,5,3,0,0.0,neutral or dissatisfied +27604,118802,Female,Loyal Customer,54,Personal Travel,Eco,368,1,2,1,4,1,4,4,2,2,1,2,3,2,3,4,3.0,neutral or dissatisfied +27605,86290,Male,Loyal Customer,53,Personal Travel,Eco,356,2,4,2,2,5,2,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +27606,96375,Male,Loyal Customer,37,Business travel,Eco,1407,1,1,1,1,1,1,1,1,3,5,4,1,4,1,49,71.0,neutral or dissatisfied +27607,5248,Female,Loyal Customer,55,Business travel,Eco,190,3,3,5,5,1,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +27608,94630,Female,Loyal Customer,25,Business travel,Eco,189,3,2,2,2,3,3,2,3,1,3,2,1,2,3,0,0.0,neutral or dissatisfied +27609,108419,Female,Loyal Customer,45,Business travel,Business,1444,4,4,3,4,2,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +27610,92950,Male,Loyal Customer,54,Business travel,Business,151,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,3.0,satisfied +27611,9179,Female,Loyal Customer,46,Business travel,Business,3868,4,4,4,4,4,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +27612,67940,Male,Loyal Customer,13,Personal Travel,Eco,1235,3,4,3,2,3,3,4,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +27613,54231,Male,Loyal Customer,32,Business travel,Eco,1222,5,2,2,2,5,5,5,5,3,1,5,1,2,5,0,0.0,satisfied +27614,68770,Male,Loyal Customer,28,Business travel,Eco,1021,3,2,2,2,3,3,3,3,2,5,4,2,3,3,6,0.0,neutral or dissatisfied +27615,25454,Female,Loyal Customer,52,Personal Travel,Eco,669,4,4,4,4,5,4,5,1,1,4,1,4,1,3,9,8.0,neutral or dissatisfied +27616,108247,Male,disloyal Customer,27,Business travel,Business,895,5,5,5,4,4,5,4,4,3,3,5,5,4,4,5,2.0,satisfied +27617,56665,Female,Loyal Customer,13,Personal Travel,Eco,937,0,5,0,1,1,0,1,1,5,3,5,5,4,1,0,4.0,satisfied +27618,101599,Female,Loyal Customer,49,Business travel,Business,1371,1,1,1,1,5,4,5,4,4,4,4,5,4,5,40,,satisfied +27619,93966,Male,disloyal Customer,36,Business travel,Business,1315,3,3,3,3,2,3,2,2,5,2,4,3,5,2,3,0.0,neutral or dissatisfied +27620,24971,Female,disloyal Customer,32,Business travel,Eco,484,3,0,3,5,5,3,5,5,5,4,1,5,4,5,21,16.0,neutral or dissatisfied +27621,91303,Female,Loyal Customer,43,Business travel,Business,406,5,5,5,5,5,4,4,5,5,4,5,5,5,5,0,18.0,satisfied +27622,83007,Male,Loyal Customer,51,Business travel,Business,3749,2,2,2,2,5,5,4,4,4,4,4,3,4,5,0,15.0,satisfied +27623,28451,Male,Loyal Customer,36,Business travel,Eco,2537,3,5,5,5,3,3,3,4,1,3,3,3,3,3,0,0.0,neutral or dissatisfied +27624,63700,Female,Loyal Customer,21,Personal Travel,Eco,853,2,3,2,5,2,2,2,2,2,2,1,3,2,2,16,15.0,neutral or dissatisfied +27625,47340,Male,disloyal Customer,30,Business travel,Eco,532,3,5,3,5,3,3,5,3,5,1,1,3,3,3,0,0.0,neutral or dissatisfied +27626,76199,Female,disloyal Customer,26,Business travel,Eco,2422,1,1,1,4,3,1,3,3,4,5,3,3,4,3,0,0.0,neutral or dissatisfied +27627,127755,Male,Loyal Customer,44,Personal Travel,Eco,255,3,2,3,3,2,3,2,2,3,2,3,3,3,2,5,8.0,neutral or dissatisfied +27628,67511,Female,disloyal Customer,28,Business travel,Business,1171,3,3,3,4,2,3,2,2,3,2,4,3,5,2,10,16.0,neutral or dissatisfied +27629,119376,Male,Loyal Customer,41,Business travel,Business,3931,5,5,5,5,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +27630,126616,Female,Loyal Customer,50,Business travel,Business,1337,4,4,4,4,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +27631,33954,Female,Loyal Customer,22,Personal Travel,Eco Plus,1072,2,4,2,3,4,2,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +27632,75240,Male,Loyal Customer,26,Personal Travel,Eco,1744,3,0,3,2,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +27633,2941,Female,Loyal Customer,60,Business travel,Business,737,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +27634,56022,Male,Loyal Customer,59,Business travel,Business,2475,1,1,2,1,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +27635,36193,Male,disloyal Customer,35,Business travel,Eco,496,3,5,3,1,2,3,4,2,2,2,4,3,1,2,0,7.0,neutral or dissatisfied +27636,39610,Female,Loyal Customer,18,Personal Travel,Eco,908,3,5,4,4,3,4,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +27637,74475,Male,Loyal Customer,45,Business travel,Business,2257,5,5,1,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +27638,81439,Female,Loyal Customer,36,Personal Travel,Eco Plus,393,1,4,1,3,2,1,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +27639,18977,Female,Loyal Customer,40,Business travel,Business,1709,3,5,3,3,1,1,4,3,3,5,3,1,3,3,16,15.0,satisfied +27640,100363,Male,Loyal Customer,10,Personal Travel,Eco,1011,2,2,2,4,4,2,4,4,4,4,4,4,3,4,30,13.0,neutral or dissatisfied +27641,66270,Female,Loyal Customer,63,Personal Travel,Eco,460,2,4,2,4,3,5,2,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +27642,98952,Female,disloyal Customer,45,Business travel,Business,569,3,3,3,3,5,3,5,5,5,5,5,3,5,5,7,0.0,neutral or dissatisfied +27643,45462,Male,Loyal Customer,51,Business travel,Eco,674,4,3,3,3,4,4,4,4,5,5,1,4,2,4,3,4.0,satisfied +27644,11679,Female,Loyal Customer,48,Business travel,Business,3111,5,5,4,5,4,5,4,4,4,4,4,4,4,3,2,1.0,satisfied +27645,88708,Female,Loyal Customer,51,Personal Travel,Eco,404,3,4,3,3,5,4,5,4,4,3,4,5,4,5,18,4.0,neutral or dissatisfied +27646,82194,Female,Loyal Customer,29,Personal Travel,Eco,1927,2,4,2,4,3,2,3,3,3,4,3,3,5,3,0,21.0,neutral or dissatisfied +27647,102098,Female,disloyal Customer,38,Business travel,Business,407,1,1,1,3,4,1,4,4,5,2,4,4,4,4,78,74.0,neutral or dissatisfied +27648,24415,Male,Loyal Customer,49,Business travel,Eco,634,4,4,4,4,4,4,4,4,4,5,2,5,4,4,0,0.0,satisfied +27649,108591,Female,Loyal Customer,26,Business travel,Business,696,4,4,4,4,5,5,5,5,3,3,5,4,5,5,9,0.0,satisfied +27650,5973,Female,Loyal Customer,24,Personal Travel,Business,690,1,1,1,3,1,1,1,1,2,2,2,3,3,1,0,0.0,neutral or dissatisfied +27651,87120,Male,Loyal Customer,58,Personal Travel,Eco,640,3,4,3,4,5,3,5,5,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +27652,17790,Female,Loyal Customer,43,Business travel,Eco,1075,3,1,1,1,5,5,3,2,2,3,2,1,2,2,0,0.0,satisfied +27653,98161,Female,Loyal Customer,31,Personal Travel,Eco,562,0,4,1,2,1,1,5,1,4,4,5,3,5,1,31,35.0,satisfied +27654,65759,Female,Loyal Customer,46,Personal Travel,Eco,936,3,2,2,3,1,4,3,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +27655,105043,Male,Loyal Customer,69,Personal Travel,Eco,255,3,4,3,3,1,3,1,1,4,4,1,1,5,1,2,7.0,neutral or dissatisfied +27656,96506,Male,Loyal Customer,36,Business travel,Business,2332,1,2,1,1,5,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +27657,55028,Male,Loyal Customer,41,Business travel,Business,1635,4,4,2,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +27658,9529,Female,disloyal Customer,23,Business travel,Eco,229,5,4,5,4,3,5,3,3,3,5,5,3,5,3,0,0.0,satisfied +27659,100109,Female,Loyal Customer,49,Business travel,Business,3796,2,2,1,2,5,4,5,5,5,5,5,5,5,5,43,60.0,satisfied +27660,2841,Female,Loyal Customer,57,Business travel,Business,2403,2,3,3,3,1,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +27661,55249,Female,Loyal Customer,8,Personal Travel,Eco,1009,2,5,2,1,5,2,5,5,3,2,3,3,4,5,0,0.0,neutral or dissatisfied +27662,103961,Male,Loyal Customer,61,Personal Travel,Eco,533,3,5,3,3,4,3,4,4,4,4,5,3,4,4,10,0.0,neutral or dissatisfied +27663,60748,Female,Loyal Customer,50,Business travel,Business,1825,5,5,5,5,5,4,4,5,5,5,5,4,5,3,4,26.0,satisfied +27664,6471,Male,Loyal Customer,27,Personal Travel,Eco Plus,213,2,5,2,3,3,2,3,3,5,4,5,5,4,3,25,76.0,neutral or dissatisfied +27665,97733,Female,Loyal Customer,23,Business travel,Business,2740,2,2,2,2,3,3,3,3,3,4,5,4,5,3,0,0.0,satisfied +27666,45369,Female,Loyal Customer,40,Personal Travel,Eco,175,2,4,0,1,0,4,4,3,3,5,4,4,4,4,167,169.0,neutral or dissatisfied +27667,90700,Male,Loyal Customer,49,Business travel,Business,270,5,5,4,5,4,4,5,4,4,4,4,5,4,5,4,21.0,satisfied +27668,107568,Female,Loyal Customer,43,Personal Travel,Eco,1521,2,5,2,1,2,5,4,5,5,2,5,5,5,5,57,97.0,neutral or dissatisfied +27669,13385,Female,Loyal Customer,20,Personal Travel,Business,505,4,4,3,3,3,3,5,3,3,3,4,4,4,3,0,8.0,satisfied +27670,99634,Male,Loyal Customer,33,Personal Travel,Eco,1224,2,4,1,4,5,1,5,5,4,5,4,4,3,5,18,15.0,neutral or dissatisfied +27671,102877,Female,Loyal Customer,31,Personal Travel,Eco,472,1,0,1,5,1,1,1,1,5,3,5,3,5,1,12,21.0,neutral or dissatisfied +27672,79745,Female,Loyal Customer,28,Business travel,Eco Plus,760,1,1,1,1,1,1,1,1,1,2,2,1,1,1,22,27.0,neutral or dissatisfied +27673,61676,Female,Loyal Customer,30,Business travel,Business,1635,4,4,4,4,4,4,4,4,5,5,4,4,4,4,18,25.0,satisfied +27674,92867,Female,Loyal Customer,63,Personal Travel,Eco,2519,3,1,3,3,2,4,4,1,1,3,1,4,1,2,26,24.0,neutral or dissatisfied +27675,110938,Male,Loyal Customer,31,Personal Travel,Eco,406,4,5,4,3,1,4,1,1,4,2,4,3,4,1,27,27.0,neutral or dissatisfied +27676,42348,Female,Loyal Customer,34,Personal Travel,Eco,834,3,5,3,1,4,3,4,4,4,3,4,5,5,4,23,28.0,neutral or dissatisfied +27677,76221,Male,Loyal Customer,37,Business travel,Business,1399,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +27678,17310,Female,Loyal Customer,46,Business travel,Eco,403,2,5,5,5,4,2,2,2,2,2,2,4,2,4,56,52.0,satisfied +27679,12319,Female,disloyal Customer,24,Business travel,Eco,190,2,2,2,3,1,2,1,1,4,5,3,4,3,1,35,41.0,neutral or dissatisfied +27680,61622,Male,Loyal Customer,51,Business travel,Business,1346,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +27681,72890,Female,disloyal Customer,57,Business travel,Business,1089,4,4,4,2,5,4,5,5,1,1,2,2,2,5,0,0.0,neutral or dissatisfied +27682,71497,Female,Loyal Customer,23,Personal Travel,Business,1182,3,2,3,3,4,3,3,4,1,3,4,3,3,4,4,1.0,neutral or dissatisfied +27683,64604,Female,Loyal Customer,40,Business travel,Business,3505,0,0,0,4,2,4,4,1,1,1,1,4,1,3,0,0.0,satisfied +27684,48729,Female,Loyal Customer,43,Business travel,Business,2969,0,4,0,5,2,5,5,1,1,1,1,5,1,4,0,9.0,satisfied +27685,27557,Female,Loyal Customer,20,Personal Travel,Eco,978,3,4,3,1,4,3,5,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +27686,81215,Male,Loyal Customer,50,Business travel,Eco,1426,2,4,4,4,2,2,2,2,2,1,3,4,3,2,18,24.0,neutral or dissatisfied +27687,32565,Male,Loyal Customer,37,Business travel,Eco,201,4,4,4,4,4,4,4,4,1,1,3,2,1,4,0,1.0,satisfied +27688,18270,Female,Loyal Customer,49,Personal Travel,Eco,179,2,5,2,4,4,2,3,1,1,2,1,3,1,5,18,7.0,neutral or dissatisfied +27689,96356,Male,Loyal Customer,28,Personal Travel,Eco,1609,3,4,3,1,5,3,5,5,4,2,5,3,5,5,54,16.0,neutral or dissatisfied +27690,41311,Male,Loyal Customer,36,Business travel,Eco,802,5,2,2,2,5,5,5,5,2,2,2,5,1,5,0,0.0,satisfied +27691,65522,Male,Loyal Customer,49,Business travel,Business,1616,3,1,1,1,1,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +27692,115199,Female,disloyal Customer,62,Business travel,Business,446,5,5,5,4,5,5,5,5,3,4,4,4,5,5,0,4.0,satisfied +27693,29111,Male,Loyal Customer,30,Personal Travel,Eco,978,2,4,1,2,3,1,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +27694,125337,Female,Loyal Customer,45,Business travel,Business,1649,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +27695,53980,Female,disloyal Customer,22,Business travel,Eco,1325,4,4,4,3,1,4,1,1,1,4,2,2,2,1,0,0.0,neutral or dissatisfied +27696,15057,Male,Loyal Customer,23,Personal Travel,Eco,576,2,5,2,3,1,2,1,1,3,3,5,4,4,1,5,18.0,neutral or dissatisfied +27697,32641,Male,Loyal Customer,18,Business travel,Eco,102,5,1,4,1,5,5,5,5,4,2,1,4,4,5,0,0.0,satisfied +27698,76015,Male,Loyal Customer,41,Business travel,Business,3474,2,2,2,2,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +27699,97396,Female,Loyal Customer,37,Business travel,Eco Plus,443,3,4,4,4,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +27700,89868,Male,Loyal Customer,45,Business travel,Business,1632,4,4,4,4,2,4,5,4,4,4,4,5,4,3,25,25.0,satisfied +27701,84320,Female,Loyal Customer,58,Business travel,Business,606,4,1,1,1,4,2,3,4,4,4,4,1,4,3,3,0.0,neutral or dissatisfied +27702,67021,Female,Loyal Customer,25,Business travel,Business,1119,4,4,4,4,5,5,5,5,5,3,5,5,5,5,29,11.0,satisfied +27703,68876,Male,Loyal Customer,33,Business travel,Business,1544,3,3,3,3,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +27704,124616,Male,Loyal Customer,49,Business travel,Business,1671,2,4,4,4,1,4,4,2,2,2,2,1,2,2,0,6.0,neutral or dissatisfied +27705,65489,Female,Loyal Customer,68,Personal Travel,Eco,1067,2,4,2,4,2,4,5,3,3,2,3,5,3,3,120,110.0,neutral or dissatisfied +27706,55450,Female,disloyal Customer,55,Business travel,Business,1462,5,5,5,3,5,3,3,4,4,3,5,3,3,3,0,0.0,satisfied +27707,125758,Male,Loyal Customer,57,Business travel,Business,951,4,4,4,4,2,5,5,5,5,5,5,5,5,5,0,12.0,satisfied +27708,107555,Male,disloyal Customer,24,Business travel,Eco,1275,2,3,3,4,3,2,3,3,2,2,4,4,3,3,25,35.0,neutral or dissatisfied +27709,67740,Female,disloyal Customer,15,Business travel,Eco,1205,1,1,1,3,3,1,2,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +27710,82534,Female,Loyal Customer,59,Business travel,Business,3533,3,4,3,3,5,5,5,5,5,5,5,5,5,4,0,3.0,satisfied +27711,122933,Male,Loyal Customer,39,Business travel,Business,650,3,3,3,3,2,4,5,5,5,5,5,3,5,5,3,35.0,satisfied +27712,116614,Female,Loyal Customer,46,Business travel,Business,2679,3,3,3,3,3,4,4,4,4,4,4,5,4,3,2,4.0,satisfied +27713,5833,Female,disloyal Customer,32,Personal Travel,Eco,157,3,4,3,4,4,3,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +27714,40409,Male,disloyal Customer,20,Business travel,Eco,150,0,4,1,2,1,1,1,1,2,4,5,4,1,1,0,0.0,satisfied +27715,107632,Female,Loyal Customer,45,Business travel,Business,2334,1,1,3,1,2,5,5,4,4,4,4,3,4,3,2,0.0,satisfied +27716,34081,Female,Loyal Customer,38,Personal Travel,Eco Plus,1674,3,1,4,3,2,4,2,2,2,5,2,3,2,2,39,17.0,neutral or dissatisfied +27717,101030,Female,disloyal Customer,26,Business travel,Eco Plus,867,2,2,2,4,4,2,4,4,3,3,4,4,3,4,1,0.0,neutral or dissatisfied +27718,110278,Male,Loyal Customer,47,Personal Travel,Business,883,0,0,0,3,0,2,2,3,4,4,4,2,3,2,310,305.0,satisfied +27719,41159,Female,Loyal Customer,24,Personal Travel,Eco,667,1,4,1,1,4,1,5,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +27720,49843,Female,Loyal Customer,30,Business travel,Business,3425,3,3,3,3,4,5,4,4,4,2,2,4,4,4,1,5.0,satisfied +27721,84344,Female,Loyal Customer,55,Business travel,Business,591,2,2,2,2,3,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +27722,43994,Female,disloyal Customer,40,Business travel,Business,397,5,5,5,5,3,5,3,3,1,1,1,4,2,3,0,0.0,satisfied +27723,45013,Male,Loyal Customer,66,Personal Travel,Eco,235,2,5,2,3,3,2,3,3,3,5,4,5,4,3,4,15.0,neutral or dissatisfied +27724,103476,Male,Loyal Customer,41,Business travel,Business,2858,1,1,1,1,4,5,4,2,2,2,2,3,2,5,3,2.0,satisfied +27725,37594,Female,disloyal Customer,23,Business travel,Eco,605,3,2,3,3,3,3,3,3,1,4,4,2,3,3,25,19.0,neutral or dissatisfied +27726,66712,Female,disloyal Customer,25,Business travel,Eco,802,3,3,3,3,5,3,5,5,4,2,1,1,3,5,17,0.0,neutral or dissatisfied +27727,74653,Female,Loyal Customer,12,Personal Travel,Eco,1235,2,5,2,2,5,2,4,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +27728,82847,Female,Loyal Customer,46,Business travel,Business,645,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +27729,2479,Male,disloyal Customer,20,Business travel,Eco,1379,3,4,4,1,2,3,2,2,3,5,4,3,4,2,0,9.0,neutral or dissatisfied +27730,43447,Male,Loyal Customer,24,Business travel,Eco,679,5,2,2,2,5,5,4,5,4,5,2,4,3,5,0,12.0,satisfied +27731,86332,Female,Loyal Customer,8,Personal Travel,Business,762,1,5,1,5,3,1,3,3,5,5,4,4,5,3,4,22.0,neutral or dissatisfied +27732,69504,Male,Loyal Customer,27,Business travel,Business,1746,1,1,4,1,4,5,5,4,3,5,4,5,4,5,859,860.0,satisfied +27733,107491,Female,disloyal Customer,27,Business travel,Eco,711,1,1,1,4,1,1,2,1,4,1,3,2,3,1,0,0.0,neutral or dissatisfied +27734,13797,Male,Loyal Customer,39,Business travel,Business,3402,3,1,1,1,1,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +27735,107937,Female,Loyal Customer,43,Business travel,Business,211,4,5,5,5,2,3,3,3,3,3,4,3,3,3,39,30.0,neutral or dissatisfied +27736,48108,Female,Loyal Customer,64,Business travel,Business,1602,3,3,3,3,3,2,5,5,5,5,5,5,5,3,0,0.0,satisfied +27737,59941,Female,Loyal Customer,60,Business travel,Business,1085,2,1,4,1,1,3,3,2,2,2,2,3,2,3,4,9.0,neutral or dissatisfied +27738,78005,Female,Loyal Customer,56,Business travel,Business,332,5,5,5,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +27739,35056,Male,Loyal Customer,44,Business travel,Business,1047,4,4,4,4,3,4,5,5,5,5,5,5,5,4,56,81.0,satisfied +27740,119975,Female,Loyal Customer,47,Personal Travel,Eco,868,1,5,1,2,1,1,4,5,5,1,5,2,5,5,0,0.0,neutral or dissatisfied +27741,7188,Female,Loyal Customer,47,Business travel,Business,1643,2,4,3,4,4,3,3,3,3,3,2,4,3,2,0,0.0,neutral or dissatisfied +27742,33340,Female,Loyal Customer,47,Business travel,Business,2556,3,3,3,3,5,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +27743,124376,Female,disloyal Customer,28,Business travel,Business,408,1,0,0,1,1,0,1,1,3,5,1,2,3,1,0,0.0,neutral or dissatisfied +27744,75341,Female,Loyal Customer,33,Personal Travel,Eco,2504,3,4,3,2,3,3,3,3,3,4,4,3,5,3,0,11.0,neutral or dissatisfied +27745,45647,Male,Loyal Customer,19,Personal Travel,Eco,260,4,5,0,2,3,0,3,3,1,1,4,2,2,3,0,0.0,neutral or dissatisfied +27746,111475,Female,Loyal Customer,27,Personal Travel,Eco Plus,1024,3,1,3,2,5,3,5,5,3,1,2,4,2,5,0,0.0,neutral or dissatisfied +27747,67853,Female,Loyal Customer,13,Personal Travel,Eco,1205,2,1,2,4,1,2,1,1,1,1,3,1,4,1,1,0.0,neutral or dissatisfied +27748,110040,Male,Loyal Customer,49,Business travel,Business,1984,2,2,2,2,4,4,4,2,2,2,2,4,2,4,29,6.0,satisfied +27749,93008,Female,Loyal Customer,43,Business travel,Business,1524,2,2,2,2,4,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +27750,26924,Female,Loyal Customer,28,Personal Travel,Eco,1774,4,4,3,5,3,3,3,3,3,4,4,4,4,3,0,0.0,satisfied +27751,67498,Female,Loyal Customer,19,Personal Travel,Eco Plus,641,1,4,0,4,4,0,4,4,2,1,3,1,3,4,0,2.0,neutral or dissatisfied +27752,109668,Female,disloyal Customer,59,Business travel,Eco,408,3,1,2,4,4,2,4,4,2,4,3,4,3,4,18,20.0,neutral or dissatisfied +27753,43594,Male,Loyal Customer,44,Business travel,Eco,119,4,3,4,3,4,4,4,4,3,4,3,5,5,4,32,40.0,satisfied +27754,28032,Male,Loyal Customer,70,Personal Travel,Eco Plus,763,3,5,3,5,1,3,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +27755,65453,Female,Loyal Customer,60,Business travel,Business,1772,2,5,5,5,5,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +27756,90251,Female,Loyal Customer,53,Personal Travel,Eco Plus,1121,3,5,3,3,4,5,5,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +27757,107373,Female,Loyal Customer,42,Personal Travel,Eco Plus,584,0,4,0,4,2,5,5,2,2,0,2,5,2,5,0,0.0,satisfied +27758,30455,Male,Loyal Customer,31,Business travel,Eco,991,0,0,0,3,4,0,4,4,1,3,3,4,2,4,0,0.0,satisfied +27759,61774,Male,Loyal Customer,53,Personal Travel,Eco,1504,1,3,1,4,4,1,3,4,4,3,4,2,3,4,0,0.0,neutral or dissatisfied +27760,29241,Female,Loyal Customer,29,Business travel,Business,873,3,3,3,3,5,5,5,5,5,4,3,2,4,5,0,0.0,satisfied +27761,117090,Female,Loyal Customer,79,Business travel,Business,325,3,3,3,3,1,2,2,3,3,3,3,4,3,1,16,13.0,neutral or dissatisfied +27762,270,Female,Loyal Customer,59,Business travel,Business,802,2,2,2,2,2,5,5,4,4,4,4,5,4,4,0,14.0,satisfied +27763,59552,Male,disloyal Customer,29,Business travel,Business,854,4,5,5,3,1,5,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +27764,11671,Male,Loyal Customer,41,Personal Travel,Eco Plus,1117,2,4,2,3,1,2,1,1,4,2,4,1,3,1,24,0.0,neutral or dissatisfied +27765,84881,Male,Loyal Customer,29,Personal Travel,Eco,481,1,3,1,4,5,1,5,5,1,5,3,4,4,5,0,0.0,neutral or dissatisfied +27766,119515,Female,Loyal Customer,40,Business travel,Eco,899,3,1,1,1,3,3,3,3,4,5,3,1,4,3,0,8.0,neutral or dissatisfied +27767,3005,Male,Loyal Customer,52,Business travel,Business,922,3,3,3,3,2,4,4,5,5,5,5,4,5,3,34,48.0,satisfied +27768,28076,Female,Loyal Customer,45,Business travel,Eco Plus,2562,4,5,5,5,4,4,4,5,5,3,5,4,1,4,0,0.0,satisfied +27769,65,Male,disloyal Customer,24,Business travel,Eco,108,0,0,0,1,5,0,5,5,5,5,4,3,5,5,0,0.0,satisfied +27770,75571,Male,Loyal Customer,30,Business travel,Eco,337,4,3,3,3,4,4,4,4,1,2,2,2,1,4,0,1.0,neutral or dissatisfied +27771,27259,Female,Loyal Customer,40,Business travel,Business,954,3,3,3,3,5,5,5,5,5,5,5,5,5,3,0,10.0,satisfied +27772,118572,Male,Loyal Customer,43,Business travel,Business,2334,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +27773,120354,Female,Loyal Customer,57,Business travel,Business,449,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +27774,59416,Male,Loyal Customer,69,Personal Travel,Eco,2399,1,4,1,3,3,1,3,3,4,3,3,4,5,3,7,0.0,neutral or dissatisfied +27775,98023,Female,disloyal Customer,23,Business travel,Eco,1014,4,3,3,3,5,3,5,5,4,4,3,3,3,5,15,43.0,neutral or dissatisfied +27776,98149,Female,disloyal Customer,22,Business travel,Eco,745,3,3,3,2,4,3,4,4,4,4,3,2,2,4,118,113.0,neutral or dissatisfied +27777,66736,Female,Loyal Customer,23,Personal Travel,Eco,802,3,4,3,5,4,3,4,4,4,3,2,5,2,4,7,0.0,neutral or dissatisfied +27778,26704,Male,Loyal Customer,48,Personal Travel,Eco,406,3,4,3,5,5,3,5,5,4,5,4,5,1,5,0,0.0,neutral or dissatisfied +27779,124410,Male,Loyal Customer,49,Business travel,Business,2765,3,3,3,3,2,5,4,4,4,4,4,5,4,3,24,17.0,satisfied +27780,48137,Male,disloyal Customer,26,Business travel,Eco,173,0,0,0,5,4,0,4,4,2,4,3,3,4,4,0,0.0,satisfied +27781,92291,Female,disloyal Customer,39,Business travel,Business,1814,1,1,1,5,5,1,5,5,3,5,3,3,5,5,33,30.0,neutral or dissatisfied +27782,101012,Male,Loyal Customer,69,Business travel,Business,1822,1,3,3,3,3,2,2,1,1,1,1,4,1,4,0,3.0,neutral or dissatisfied +27783,90018,Male,disloyal Customer,21,Business travel,Eco,1145,4,5,5,1,2,5,2,2,3,2,4,5,5,2,5,15.0,satisfied +27784,62396,Male,Loyal Customer,23,Personal Travel,Eco,2704,2,4,2,4,3,2,3,3,4,5,4,5,4,3,5,0.0,neutral or dissatisfied +27785,92167,Male,Loyal Customer,56,Business travel,Business,2079,5,5,5,5,2,4,5,3,3,2,3,3,3,3,0,0.0,satisfied +27786,47212,Male,Loyal Customer,8,Personal Travel,Eco,954,3,3,3,3,3,3,3,3,3,2,4,3,3,3,4,0.0,neutral or dissatisfied +27787,99787,Male,Loyal Customer,54,Business travel,Business,3252,5,5,2,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +27788,26247,Male,Loyal Customer,39,Business travel,Eco Plus,404,5,2,2,2,5,5,5,5,3,5,3,3,4,5,0,0.0,satisfied +27789,10970,Female,Loyal Customer,75,Business travel,Eco,74,2,4,4,4,5,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +27790,41150,Female,Loyal Customer,25,Personal Travel,Eco,667,2,4,1,2,1,1,1,1,3,4,4,4,4,1,4,6.0,neutral or dissatisfied +27791,65777,Male,disloyal Customer,41,Business travel,Business,1389,4,4,4,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +27792,55882,Male,Loyal Customer,42,Business travel,Business,473,1,1,3,1,2,5,5,5,5,5,5,3,5,3,3,0.0,satisfied +27793,87784,Male,Loyal Customer,59,Business travel,Business,214,4,4,2,4,3,5,5,3,3,4,4,3,3,5,9,0.0,satisfied +27794,89743,Male,Loyal Customer,68,Personal Travel,Eco,950,4,3,4,4,4,4,4,4,3,4,2,2,3,4,0,0.0,neutral or dissatisfied +27795,112675,Female,Loyal Customer,57,Business travel,Business,672,2,2,2,2,3,4,4,5,5,5,5,3,5,5,18,0.0,satisfied +27796,52674,Male,Loyal Customer,40,Personal Travel,Eco,160,2,5,0,1,4,0,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +27797,49905,Male,Loyal Customer,52,Business travel,Eco,308,5,3,3,3,4,5,4,4,3,5,2,2,2,4,0,0.0,satisfied +27798,83466,Female,Loyal Customer,13,Business travel,Business,946,1,4,4,4,1,1,1,1,4,3,4,4,4,1,49,35.0,neutral or dissatisfied +27799,80701,Female,Loyal Customer,52,Personal Travel,Eco,748,2,3,2,3,5,3,4,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +27800,27640,Female,disloyal Customer,37,Business travel,Eco Plus,554,1,1,1,4,3,1,3,3,1,5,4,3,4,3,0,6.0,neutral or dissatisfied +27801,9086,Male,Loyal Customer,7,Personal Travel,Eco,212,3,3,0,4,2,0,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +27802,38172,Female,Loyal Customer,70,Personal Travel,Eco,1091,2,1,2,3,5,4,3,5,5,2,5,2,5,1,72,53.0,neutral or dissatisfied +27803,63386,Male,Loyal Customer,15,Personal Travel,Eco,372,2,3,2,2,1,2,1,1,3,3,2,3,3,1,4,6.0,neutral or dissatisfied +27804,78071,Male,Loyal Customer,37,Business travel,Business,2310,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +27805,38405,Female,disloyal Customer,38,Business travel,Eco Plus,1754,2,1,1,4,2,1,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +27806,5096,Female,Loyal Customer,41,Personal Travel,Eco,223,2,2,2,3,4,2,4,4,1,2,3,2,3,4,2,0.0,neutral or dissatisfied +27807,76886,Female,Loyal Customer,51,Business travel,Business,2422,5,5,5,5,2,5,5,2,2,2,2,5,2,5,0,8.0,satisfied +27808,53920,Male,Loyal Customer,33,Business travel,Eco Plus,191,4,1,1,1,4,4,4,4,1,1,5,4,3,4,12,0.0,satisfied +27809,120321,Male,Loyal Customer,23,Personal Travel,Eco,268,4,4,4,2,3,4,3,3,4,5,2,5,3,3,0,0.0,neutral or dissatisfied +27810,113589,Female,Loyal Customer,16,Business travel,Eco,407,2,1,1,1,2,2,1,2,4,1,4,1,3,2,16,9.0,neutral or dissatisfied +27811,66480,Male,disloyal Customer,25,Business travel,Business,447,1,4,1,3,2,1,2,2,5,3,5,3,4,2,11,2.0,neutral or dissatisfied +27812,5427,Female,Loyal Customer,63,Business travel,Business,1733,0,0,0,3,3,5,5,5,5,2,2,4,5,4,0,0.0,satisfied +27813,97070,Female,disloyal Customer,29,Business travel,Business,1211,1,2,2,2,4,2,2,4,5,2,4,3,4,4,41,38.0,neutral or dissatisfied +27814,13956,Male,Loyal Customer,41,Personal Travel,Eco,192,2,5,2,3,4,2,3,4,5,5,5,3,4,4,2,0.0,neutral or dissatisfied +27815,8582,Female,Loyal Customer,19,Business travel,Business,109,3,1,1,1,3,3,3,3,3,2,4,3,3,3,0,13.0,neutral or dissatisfied +27816,107840,Female,Loyal Customer,20,Personal Travel,Eco,349,3,3,3,4,4,3,4,4,4,5,3,3,3,4,34,17.0,neutral or dissatisfied +27817,81460,Male,Loyal Customer,10,Business travel,Business,2544,2,2,2,2,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +27818,46962,Female,Loyal Customer,21,Personal Travel,Eco,850,4,5,4,4,5,4,5,5,3,5,5,3,4,5,61,44.0,neutral or dissatisfied +27819,40480,Male,Loyal Customer,28,Personal Travel,Eco,222,0,3,0,4,2,0,4,2,1,1,3,4,3,2,0,,satisfied +27820,78743,Female,Loyal Customer,52,Business travel,Business,554,1,1,1,1,2,5,4,4,4,4,4,5,4,4,0,16.0,satisfied +27821,94407,Female,Loyal Customer,60,Business travel,Business,496,4,4,4,4,2,5,5,5,5,5,5,3,5,3,12,2.0,satisfied +27822,79380,Male,Loyal Customer,46,Business travel,Business,2853,4,4,4,4,3,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +27823,66361,Female,Loyal Customer,22,Business travel,Business,2230,3,1,1,1,3,3,3,1,4,3,3,3,3,3,140,135.0,neutral or dissatisfied +27824,19134,Male,Loyal Customer,35,Personal Travel,Eco,287,3,5,3,3,5,3,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +27825,29323,Female,Loyal Customer,56,Personal Travel,Eco,859,2,3,2,1,5,2,1,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +27826,76000,Male,disloyal Customer,61,Business travel,Business,237,5,5,5,5,3,5,3,3,3,5,5,3,4,3,0,0.0,satisfied +27827,42939,Male,disloyal Customer,25,Business travel,Business,173,5,5,5,2,4,5,3,4,4,3,4,5,5,4,0,0.0,satisfied +27828,76463,Male,Loyal Customer,42,Personal Travel,Business,547,4,2,4,3,1,3,4,2,2,4,5,2,2,2,35,49.0,neutral or dissatisfied +27829,55852,Male,Loyal Customer,12,Personal Travel,Eco,1416,2,5,2,2,2,2,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +27830,88651,Female,Loyal Customer,28,Personal Travel,Eco,545,1,5,1,1,4,1,4,4,1,1,5,4,4,4,0,2.0,neutral or dissatisfied +27831,25533,Female,Loyal Customer,50,Personal Travel,Eco,481,2,5,2,3,1,1,2,2,2,2,2,4,2,4,3,0.0,neutral or dissatisfied +27832,79755,Male,Loyal Customer,58,Business travel,Business,944,1,1,1,1,4,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +27833,99570,Female,disloyal Customer,9,Business travel,Eco,802,1,1,1,3,1,1,1,1,2,1,4,2,4,1,0,0.0,neutral or dissatisfied +27834,58606,Female,Loyal Customer,67,Personal Travel,Eco,334,3,4,3,1,4,5,5,2,2,3,5,5,2,5,11,9.0,neutral or dissatisfied +27835,78798,Female,disloyal Customer,17,Business travel,Eco,447,3,4,2,3,4,2,4,4,2,2,4,2,3,4,0,6.0,neutral or dissatisfied +27836,68014,Male,Loyal Customer,34,Business travel,Business,3392,2,2,4,2,4,2,2,2,2,2,2,3,2,1,9,9.0,neutral or dissatisfied +27837,33711,Female,Loyal Customer,33,Business travel,Business,2364,3,2,2,2,2,3,3,3,3,3,3,1,3,3,89,111.0,neutral or dissatisfied +27838,113443,Female,Loyal Customer,33,Business travel,Eco,226,3,2,2,2,3,3,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +27839,112004,Female,Loyal Customer,24,Business travel,Business,2630,4,4,4,4,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +27840,56360,Female,Loyal Customer,34,Personal Travel,Eco,200,3,1,3,3,3,3,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +27841,107862,Female,Loyal Customer,30,Business travel,Eco,228,3,1,3,3,3,3,3,3,3,1,4,3,4,3,9,7.0,neutral or dissatisfied +27842,91378,Female,disloyal Customer,38,Business travel,Business,2342,4,4,4,2,1,4,5,1,3,5,4,4,5,1,0,14.0,neutral or dissatisfied +27843,1753,Male,Loyal Customer,62,Business travel,Eco Plus,327,3,4,4,4,3,3,3,3,1,4,3,4,4,3,0,0.0,neutral or dissatisfied +27844,49741,Female,disloyal Customer,33,Business travel,Eco,373,4,5,4,4,2,4,2,2,5,2,4,4,2,2,0,0.0,neutral or dissatisfied +27845,88123,Female,disloyal Customer,39,Business travel,Business,515,4,4,4,4,5,4,5,5,4,4,5,3,5,5,52,43.0,satisfied +27846,124610,Female,Loyal Customer,40,Business travel,Business,1671,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +27847,55743,Female,disloyal Customer,27,Business travel,Eco Plus,2052,1,1,1,3,4,1,4,4,3,5,2,1,2,4,3,23.0,neutral or dissatisfied +27848,53624,Female,Loyal Customer,50,Business travel,Business,1874,2,1,5,1,1,2,4,2,2,2,2,2,2,3,105,105.0,neutral or dissatisfied +27849,94586,Male,Loyal Customer,31,Business travel,Business,2463,4,4,4,4,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +27850,61705,Female,Loyal Customer,31,Business travel,Business,3786,1,1,1,1,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +27851,110898,Male,Loyal Customer,59,Business travel,Business,545,2,1,1,1,4,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +27852,6678,Female,Loyal Customer,55,Business travel,Business,438,5,5,5,5,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +27853,47716,Male,Loyal Customer,20,Personal Travel,Eco Plus,1428,2,1,2,2,4,2,4,4,4,4,2,4,2,4,0,0.0,neutral or dissatisfied +27854,36242,Female,Loyal Customer,21,Personal Travel,Business,728,1,5,0,1,2,0,2,2,5,2,2,5,3,2,0,0.0,neutral or dissatisfied +27855,120484,Female,Loyal Customer,33,Personal Travel,Eco,449,2,4,2,3,2,2,2,2,3,2,4,3,4,2,64,84.0,neutral or dissatisfied +27856,30847,Female,Loyal Customer,32,Business travel,Business,841,2,2,2,2,4,4,4,4,1,2,2,4,5,4,0,2.0,satisfied +27857,3532,Female,Loyal Customer,38,Business travel,Business,3059,0,4,0,1,1,4,4,3,3,2,2,1,3,1,0,2.0,satisfied +27858,57024,Female,disloyal Customer,18,Business travel,Eco,913,2,2,2,3,2,3,3,2,4,2,3,3,4,3,41,87.0,neutral or dissatisfied +27859,69814,Female,Loyal Customer,42,Business travel,Business,1055,1,1,1,1,2,5,4,3,3,4,3,5,3,5,0,1.0,satisfied +27860,72572,Male,Loyal Customer,33,Business travel,Business,929,3,2,2,2,3,3,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +27861,92240,Male,disloyal Customer,24,Business travel,Eco,710,4,4,4,1,3,4,3,3,4,5,4,3,5,3,0,0.0,satisfied +27862,51949,Female,Loyal Customer,35,Business travel,Business,347,4,4,4,4,5,3,2,4,4,4,4,2,4,5,0,0.0,satisfied +27863,21789,Male,disloyal Customer,26,Business travel,Eco,341,1,5,1,3,2,1,2,2,4,2,5,1,1,2,0,0.0,neutral or dissatisfied +27864,108571,Female,Loyal Customer,57,Business travel,Business,696,4,4,4,4,3,5,4,4,4,4,4,4,4,3,26,24.0,satisfied +27865,45755,Female,disloyal Customer,47,Business travel,Eco,391,1,0,1,4,3,1,3,3,1,1,1,4,4,3,0,0.0,neutral or dissatisfied +27866,71772,Female,disloyal Customer,20,Business travel,Eco,1442,3,3,3,3,2,3,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +27867,113833,Male,Loyal Customer,27,Personal Travel,Eco Plus,236,1,1,1,3,1,1,1,1,2,3,3,2,3,1,2,2.0,neutral or dissatisfied +27868,108373,Male,Loyal Customer,49,Personal Travel,Eco,1855,3,4,3,4,3,4,4,3,5,3,3,4,4,4,165,224.0,neutral or dissatisfied +27869,14063,Female,Loyal Customer,11,Personal Travel,Eco,319,3,2,3,4,2,3,2,2,3,4,4,1,3,2,30,4.0,neutral or dissatisfied +27870,101715,Female,Loyal Customer,51,Business travel,Business,2272,1,1,1,1,4,2,2,1,1,2,1,3,1,4,34,27.0,neutral or dissatisfied +27871,2793,Female,disloyal Customer,17,Business travel,Eco,764,2,2,2,4,5,2,5,5,4,4,3,2,3,5,0,0.0,neutral or dissatisfied +27872,107594,Male,disloyal Customer,23,Business travel,Eco,423,3,4,3,2,4,3,4,4,5,5,4,3,5,4,38,32.0,neutral or dissatisfied +27873,46635,Female,disloyal Customer,18,Business travel,Eco,125,1,3,1,3,4,1,4,4,4,5,3,3,4,4,2,2.0,neutral or dissatisfied +27874,106172,Male,Loyal Customer,20,Personal Travel,Eco,436,2,4,2,3,5,2,5,5,5,2,5,5,4,5,31,25.0,neutral or dissatisfied +27875,68746,Male,Loyal Customer,40,Business travel,Business,3292,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +27876,64213,Female,Loyal Customer,47,Business travel,Business,1660,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +27877,41299,Male,Loyal Customer,13,Personal Travel,Eco,844,2,4,2,1,1,2,5,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +27878,58284,Male,Loyal Customer,53,Personal Travel,Eco,678,2,4,2,5,5,2,5,5,5,2,4,4,4,5,16,0.0,neutral or dissatisfied +27879,41991,Female,Loyal Customer,61,Business travel,Business,116,0,4,0,4,4,3,2,2,2,2,2,4,2,4,14,10.0,satisfied +27880,100095,Female,Loyal Customer,45,Business travel,Business,2060,2,2,2,2,5,4,4,2,2,2,2,2,2,1,1,0.0,neutral or dissatisfied +27881,21829,Male,Loyal Customer,38,Business travel,Business,3282,4,5,5,5,3,3,3,4,4,4,4,1,4,3,2,0.0,neutral or dissatisfied +27882,112974,Male,disloyal Customer,27,Business travel,Eco Plus,715,3,2,2,4,3,2,3,3,1,1,4,3,4,3,7,0.0,neutral or dissatisfied +27883,52507,Male,Loyal Customer,8,Personal Travel,Business,160,2,4,2,4,3,2,3,3,4,3,5,3,4,3,0,2.0,neutral or dissatisfied +27884,57246,Female,Loyal Customer,58,Business travel,Business,628,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,10.0,satisfied +27885,124748,Female,disloyal Customer,24,Business travel,Business,280,4,2,4,3,2,4,4,2,3,3,4,4,3,2,0,7.0,neutral or dissatisfied +27886,69156,Male,Loyal Customer,54,Business travel,Business,187,5,5,5,5,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +27887,107220,Male,Loyal Customer,47,Personal Travel,Business,1751,3,1,3,3,3,4,3,4,4,3,4,3,4,1,9,2.0,neutral or dissatisfied +27888,98095,Male,disloyal Customer,17,Business travel,Eco Plus,928,3,2,3,4,2,3,2,2,4,5,3,3,3,2,7,14.0,neutral or dissatisfied +27889,35973,Male,Loyal Customer,66,Business travel,Eco Plus,231,4,1,1,1,4,4,4,4,4,4,3,4,3,4,0,0.0,satisfied +27890,42319,Female,Loyal Customer,68,Personal Travel,Eco,550,1,0,2,2,4,4,5,4,4,2,4,3,4,4,0,3.0,neutral or dissatisfied +27891,91842,Female,Loyal Customer,37,Business travel,Business,1797,3,3,3,3,5,5,5,4,4,4,4,3,4,4,16,4.0,satisfied +27892,125920,Male,Loyal Customer,15,Personal Travel,Eco,992,1,4,1,1,4,1,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +27893,104031,Female,disloyal Customer,25,Business travel,Business,1262,5,4,5,3,2,5,2,2,5,2,4,5,5,2,0,1.0,satisfied +27894,107759,Female,Loyal Customer,70,Personal Travel,Eco,405,4,4,4,4,3,4,4,2,2,4,3,3,2,4,6,0.0,satisfied +27895,9526,Male,Loyal Customer,68,Personal Travel,Business,292,4,4,5,4,5,4,5,4,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +27896,14320,Female,disloyal Customer,26,Business travel,Eco,429,2,2,2,4,4,2,4,4,4,4,3,1,3,4,16,7.0,neutral or dissatisfied +27897,48715,Male,Loyal Customer,40,Business travel,Business,266,4,4,4,4,3,4,4,5,5,5,5,3,5,3,2,7.0,satisfied +27898,74675,Female,Loyal Customer,10,Personal Travel,Eco,1188,4,4,4,1,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +27899,65220,Female,Loyal Customer,56,Business travel,Business,224,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +27900,39872,Female,Loyal Customer,23,Personal Travel,Eco,221,2,5,2,3,1,2,1,1,4,4,3,2,3,1,0,1.0,neutral or dissatisfied +27901,53542,Female,Loyal Customer,67,Personal Travel,Eco Plus,2442,3,5,3,3,3,3,3,5,4,5,5,3,3,3,0,0.0,neutral or dissatisfied +27902,56788,Female,Loyal Customer,24,Business travel,Business,1605,5,5,5,5,5,4,5,5,5,2,5,5,4,5,4,0.0,satisfied +27903,21515,Female,Loyal Customer,36,Personal Travel,Eco,399,2,5,2,4,3,2,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +27904,8752,Female,Loyal Customer,50,Business travel,Business,1147,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,,satisfied +27905,33917,Male,Loyal Customer,44,Business travel,Eco,236,3,2,2,2,4,3,4,4,2,2,3,4,4,4,0,0.0,neutral or dissatisfied +27906,105366,Male,Loyal Customer,52,Business travel,Business,369,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +27907,95608,Male,Loyal Customer,8,Business travel,Business,2296,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +27908,105449,Female,Loyal Customer,40,Business travel,Business,2519,5,5,5,5,3,4,5,5,5,4,5,3,5,3,28,36.0,satisfied +27909,102497,Female,Loyal Customer,49,Personal Travel,Eco,488,3,4,3,3,1,3,4,5,5,3,5,3,5,3,34,24.0,neutral or dissatisfied +27910,64107,Female,Loyal Customer,41,Business travel,Business,788,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +27911,28044,Male,Loyal Customer,40,Business travel,Business,1739,1,1,1,1,2,4,4,4,4,4,4,5,4,5,12,18.0,satisfied +27912,100155,Male,Loyal Customer,26,Business travel,Business,3322,1,2,2,2,1,1,1,1,3,5,3,4,3,1,0,0.0,neutral or dissatisfied +27913,127700,Male,disloyal Customer,29,Business travel,Business,2133,1,2,2,5,2,2,2,2,4,3,4,4,5,2,15,0.0,neutral or dissatisfied +27914,26038,Male,Loyal Customer,37,Business travel,Eco,432,5,3,3,3,5,5,5,5,1,3,1,3,1,5,36,28.0,satisfied +27915,91729,Male,Loyal Customer,46,Business travel,Business,3422,1,1,1,1,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +27916,26631,Female,Loyal Customer,34,Business travel,Business,270,1,0,0,4,5,4,4,5,5,0,5,1,5,4,4,,neutral or dissatisfied +27917,63638,Female,Loyal Customer,38,Business travel,Business,2542,2,1,3,1,5,3,4,2,2,2,2,3,2,2,17,13.0,neutral or dissatisfied +27918,63032,Male,disloyal Customer,23,Business travel,Eco,967,4,5,5,3,4,5,4,4,4,1,4,2,3,4,17,8.0,neutral or dissatisfied +27919,34679,Female,Loyal Customer,55,Business travel,Business,3457,4,4,4,4,1,4,3,4,4,4,4,4,4,2,0,0.0,satisfied +27920,44458,Female,disloyal Customer,42,Business travel,Eco,299,4,0,4,1,3,4,4,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +27921,98108,Female,Loyal Customer,58,Business travel,Business,3068,1,1,1,1,2,5,5,4,4,5,4,4,4,5,2,1.0,satisfied +27922,10015,Male,Loyal Customer,57,Business travel,Business,534,2,2,2,2,4,5,4,5,5,4,5,4,5,5,4,6.0,satisfied +27923,75658,Female,Loyal Customer,36,Personal Travel,Eco,304,5,5,5,4,4,5,4,4,3,4,4,4,4,4,0,0.0,satisfied +27924,110370,Female,disloyal Customer,21,Business travel,Business,787,4,0,5,1,2,5,2,2,4,3,5,4,4,2,14,7.0,satisfied +27925,53136,Female,Loyal Customer,47,Business travel,Business,413,4,4,4,4,2,3,1,3,3,4,3,3,3,3,0,0.0,satisfied +27926,46956,Male,Loyal Customer,44,Personal Travel,Eco,819,3,0,3,2,3,3,3,3,3,3,5,5,5,3,28,22.0,neutral or dissatisfied +27927,123236,Female,Loyal Customer,38,Personal Travel,Eco,631,2,4,2,1,1,2,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +27928,61983,Female,Loyal Customer,39,Personal Travel,Business,2475,4,5,4,3,3,2,4,3,3,4,3,3,3,4,0,14.0,neutral or dissatisfied +27929,37552,Female,Loyal Customer,35,Business travel,Eco,1010,5,5,5,5,5,5,5,5,2,3,2,1,5,5,2,0.0,satisfied +27930,13965,Male,Loyal Customer,46,Personal Travel,Eco,317,3,2,3,3,2,3,2,2,3,5,3,2,4,2,110,118.0,neutral or dissatisfied +27931,18923,Female,Loyal Customer,44,Personal Travel,Eco,448,4,4,4,1,4,5,4,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +27932,14040,Male,Loyal Customer,31,Personal Travel,Eco Plus,1117,1,5,1,3,4,1,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +27933,102234,Female,Loyal Customer,33,Business travel,Business,2275,2,3,3,3,4,3,4,2,2,2,2,1,2,1,14,7.0,neutral or dissatisfied +27934,43275,Male,disloyal Customer,36,Business travel,Eco,463,3,0,3,1,3,3,3,3,2,1,4,5,2,3,4,16.0,neutral or dissatisfied +27935,114715,Female,Loyal Customer,46,Business travel,Business,1815,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +27936,35125,Female,Loyal Customer,20,Business travel,Business,3274,4,5,3,5,4,4,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +27937,85556,Female,Loyal Customer,48,Business travel,Business,153,5,5,5,5,5,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +27938,3848,Female,Loyal Customer,39,Personal Travel,Eco,650,3,1,3,3,2,3,3,2,2,3,3,3,4,2,0,16.0,neutral or dissatisfied +27939,74345,Male,Loyal Customer,57,Personal Travel,Business,1126,0,2,0,3,5,4,4,2,2,0,3,2,2,3,0,0.0,satisfied +27940,119116,Male,Loyal Customer,27,Personal Travel,Eco,1107,1,5,2,4,1,2,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +27941,109057,Female,disloyal Customer,23,Business travel,Eco,1041,2,2,2,3,2,2,2,2,3,5,4,2,4,2,61,65.0,neutral or dissatisfied +27942,18301,Female,Loyal Customer,56,Business travel,Business,2704,3,3,3,3,2,5,4,1,1,2,1,4,1,4,0,0.0,satisfied +27943,123890,Male,Loyal Customer,57,Personal Travel,Eco,544,4,5,4,4,2,4,2,2,2,1,3,3,3,2,0,0.0,satisfied +27944,75270,Female,Loyal Customer,66,Personal Travel,Eco,1846,3,2,3,3,3,2,3,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +27945,43083,Female,Loyal Customer,28,Personal Travel,Eco,236,1,5,1,2,2,1,3,2,5,5,4,5,5,2,8,17.0,neutral or dissatisfied +27946,25429,Male,Loyal Customer,17,Personal Travel,Business,669,2,2,2,4,2,2,2,2,1,3,4,1,4,2,16,15.0,neutral or dissatisfied +27947,86778,Male,Loyal Customer,60,Business travel,Business,3235,4,4,4,4,2,5,4,5,5,5,5,3,5,5,10,1.0,satisfied +27948,127141,Male,Loyal Customer,67,Personal Travel,Eco,621,2,4,2,3,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +27949,33362,Female,Loyal Customer,34,Business travel,Business,2355,2,2,2,2,4,2,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +27950,58963,Male,Loyal Customer,49,Business travel,Business,1744,1,5,5,5,1,4,3,1,1,1,1,4,1,1,67,62.0,neutral or dissatisfied +27951,105390,Female,Loyal Customer,45,Personal Travel,Eco,369,3,4,1,1,2,4,1,2,2,1,2,4,2,5,25,10.0,neutral or dissatisfied +27952,113382,Male,Loyal Customer,46,Business travel,Business,2664,2,2,2,2,5,4,4,5,5,5,5,3,5,3,6,0.0,satisfied +27953,73854,Female,Loyal Customer,16,Personal Travel,Eco,1810,1,5,1,3,4,1,4,4,4,4,4,4,5,4,22,10.0,neutral or dissatisfied +27954,12801,Male,Loyal Customer,25,Business travel,Eco,641,5,4,4,4,5,5,4,5,2,1,4,1,5,5,5,24.0,satisfied +27955,56613,Male,Loyal Customer,29,Business travel,Business,3324,5,5,5,5,4,4,4,4,4,3,4,3,4,4,22,0.0,satisfied +27956,96274,Male,Loyal Customer,43,Personal Travel,Eco,490,1,2,1,2,1,1,1,1,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +27957,93618,Male,Loyal Customer,15,Business travel,Business,577,4,4,4,4,4,3,4,4,2,3,3,1,4,4,0,12.0,neutral or dissatisfied +27958,96519,Male,Loyal Customer,19,Personal Travel,Eco,302,2,5,2,2,1,2,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +27959,125689,Male,Loyal Customer,23,Business travel,Business,759,3,2,2,2,3,3,3,3,4,5,3,3,3,3,2,0.0,neutral or dissatisfied +27960,80101,Male,Loyal Customer,66,Business travel,Business,1620,5,5,5,5,2,3,5,4,4,4,4,3,4,5,0,5.0,satisfied +27961,34289,Female,disloyal Customer,24,Business travel,Eco,96,2,0,1,1,1,1,1,1,3,4,1,1,2,1,0,0.0,neutral or dissatisfied +27962,12003,Female,Loyal Customer,46,Personal Travel,Eco Plus,643,4,4,4,3,2,5,4,1,1,4,1,5,1,3,86,85.0,neutral or dissatisfied +27963,32742,Male,Loyal Customer,32,Business travel,Business,2172,2,3,3,3,3,3,2,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +27964,6113,Male,Loyal Customer,33,Business travel,Business,409,3,3,3,3,4,4,4,4,3,5,5,3,5,4,41,29.0,satisfied +27965,55358,Male,disloyal Customer,30,Business travel,Business,678,4,4,4,2,5,4,1,5,4,4,4,5,4,5,0,0.0,satisfied +27966,116359,Female,Loyal Customer,9,Personal Travel,Eco,446,2,5,2,4,5,2,5,5,5,5,5,5,5,5,8,9.0,neutral or dissatisfied +27967,73381,Female,Loyal Customer,24,Business travel,Eco,1197,4,5,5,5,4,4,2,4,3,3,3,1,3,4,16,9.0,neutral or dissatisfied +27968,28535,Female,Loyal Customer,42,Business travel,Eco,2677,2,3,4,3,3,5,3,2,2,2,2,1,2,3,7,0.0,satisfied +27969,125616,Male,Loyal Customer,58,Business travel,Business,414,2,5,5,5,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +27970,5755,Female,Loyal Customer,54,Business travel,Business,3743,3,5,2,5,2,3,3,3,3,3,3,4,3,2,51,36.0,neutral or dissatisfied +27971,60474,Female,Loyal Customer,32,Business travel,Business,3457,3,3,4,3,3,3,3,3,2,4,4,3,4,3,266,258.0,neutral or dissatisfied +27972,122277,Male,Loyal Customer,39,Personal Travel,Eco,544,4,5,4,4,2,4,2,2,5,3,2,1,2,2,2,15.0,neutral or dissatisfied +27973,124976,Female,Loyal Customer,49,Business travel,Business,3992,5,5,5,5,2,4,5,4,4,4,5,4,4,3,0,0.0,satisfied +27974,33084,Female,Loyal Customer,34,Personal Travel,Eco,102,2,5,0,5,5,0,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +27975,89577,Male,disloyal Customer,21,Business travel,Eco,1207,4,4,4,2,3,4,3,3,3,3,5,5,4,3,6,15.0,neutral or dissatisfied +27976,112073,Female,Loyal Customer,44,Business travel,Business,1491,5,5,5,5,2,5,4,4,4,4,4,5,4,3,41,22.0,satisfied +27977,37677,Female,Loyal Customer,53,Personal Travel,Eco,944,1,2,1,4,1,3,4,3,3,1,5,4,3,2,0,0.0,neutral or dissatisfied +27978,9467,Female,Loyal Customer,63,Personal Travel,Eco,288,2,4,2,3,4,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +27979,74738,Female,Loyal Customer,62,Personal Travel,Eco,1235,2,4,2,3,5,3,4,4,4,2,4,2,4,3,26,4.0,neutral or dissatisfied +27980,99352,Female,Loyal Customer,28,Personal Travel,Eco,1771,0,1,0,2,3,0,3,3,2,5,2,3,2,3,0,0.0,satisfied +27981,18917,Female,Loyal Customer,24,Personal Travel,Eco,448,2,5,2,3,3,2,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +27982,112209,Female,Loyal Customer,34,Business travel,Business,1813,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +27983,69223,Male,Loyal Customer,48,Business travel,Business,3921,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +27984,124231,Male,Loyal Customer,51,Business travel,Business,1916,4,4,4,4,3,5,4,5,5,5,5,3,5,5,11,0.0,satisfied +27985,103157,Female,Loyal Customer,45,Business travel,Business,491,4,4,4,4,2,4,5,5,5,5,5,3,5,3,3,17.0,satisfied +27986,12782,Male,Loyal Customer,41,Business travel,Business,528,4,4,4,4,4,5,4,3,3,3,3,3,3,4,15,2.0,satisfied +27987,112237,Female,Loyal Customer,41,Business travel,Business,1506,1,1,1,1,4,4,4,4,4,4,4,4,4,4,7,0.0,satisfied +27988,1503,Male,Loyal Customer,62,Personal Travel,Eco,737,4,4,4,4,5,4,5,5,5,3,4,4,4,5,74,87.0,neutral or dissatisfied +27989,74699,Female,Loyal Customer,14,Personal Travel,Eco,1431,2,1,2,2,4,2,5,4,3,2,2,1,2,4,32,23.0,neutral or dissatisfied +27990,41890,Female,Loyal Customer,37,Business travel,Eco,129,3,3,5,3,3,3,3,3,1,3,1,5,1,3,0,1.0,satisfied +27991,81581,Female,Loyal Customer,30,Business travel,Business,3178,4,4,5,4,3,3,3,3,3,2,5,5,4,3,13,0.0,satisfied +27992,63854,Male,Loyal Customer,45,Business travel,Business,1172,4,4,4,4,5,4,5,4,4,4,4,5,4,5,17,,satisfied +27993,70004,Male,Loyal Customer,48,Personal Travel,Eco,236,1,4,0,2,3,0,2,3,5,5,4,4,4,3,19,38.0,neutral or dissatisfied +27994,74478,Female,Loyal Customer,57,Business travel,Business,2603,1,1,3,1,5,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +27995,87947,Female,Loyal Customer,69,Personal Travel,Business,442,4,2,4,4,5,4,3,2,2,4,2,2,2,4,9,9.0,neutral or dissatisfied +27996,10355,Male,disloyal Customer,27,Business travel,Business,134,1,1,1,4,4,1,4,4,5,3,4,4,5,4,74,81.0,neutral or dissatisfied +27997,126674,Female,Loyal Customer,40,Business travel,Business,2276,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +27998,65027,Female,Loyal Customer,68,Personal Travel,Eco,247,2,5,2,1,3,4,4,1,1,2,1,5,1,3,87,78.0,neutral or dissatisfied +27999,101877,Female,Loyal Customer,48,Personal Travel,Eco,1747,3,4,3,3,3,4,4,4,2,3,4,4,3,4,178,149.0,neutral or dissatisfied +28000,31949,Female,Loyal Customer,42,Business travel,Business,2221,3,4,4,4,5,2,3,4,4,4,3,2,4,4,0,0.0,neutral or dissatisfied +28001,17654,Female,Loyal Customer,25,Business travel,Eco,1008,2,5,2,2,2,2,2,2,4,2,3,2,2,2,20,14.0,neutral or dissatisfied +28002,33427,Female,disloyal Customer,29,Business travel,Eco,702,1,1,1,3,1,1,1,1,2,5,4,4,4,1,0,15.0,neutral or dissatisfied +28003,474,Female,Loyal Customer,39,Business travel,Business,1681,4,4,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +28004,28176,Male,Loyal Customer,29,Personal Travel,Eco,569,1,5,2,2,4,2,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +28005,44168,Male,disloyal Customer,22,Business travel,Eco,157,5,4,5,2,4,5,4,4,5,5,5,3,4,4,0,2.0,satisfied +28006,108627,Male,Loyal Customer,29,Business travel,Eco,1547,4,3,3,3,4,4,4,4,1,4,4,4,3,4,5,6.0,neutral or dissatisfied +28007,4682,Male,Loyal Customer,17,Personal Travel,Eco,489,4,4,4,4,4,4,4,3,4,5,5,4,4,4,187,194.0,neutral or dissatisfied +28008,21792,Male,Loyal Customer,29,Business travel,Eco,241,4,2,2,2,4,4,4,4,2,2,1,4,5,4,0,0.0,satisfied +28009,36645,Female,Loyal Customer,7,Personal Travel,Eco,1121,1,4,1,2,5,1,5,5,5,2,4,3,4,5,56,86.0,neutral or dissatisfied +28010,112339,Female,Loyal Customer,55,Business travel,Business,3660,4,4,4,4,2,5,4,4,4,4,4,5,4,5,9,0.0,satisfied +28011,55972,Male,Loyal Customer,53,Personal Travel,Eco,1620,4,4,4,2,2,4,3,2,3,2,4,4,5,2,0,0.0,satisfied +28012,73624,Female,disloyal Customer,32,Business travel,Business,192,4,4,4,2,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +28013,82924,Male,Loyal Customer,21,Business travel,Business,2193,2,2,2,2,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +28014,37620,Male,Loyal Customer,55,Personal Travel,Eco,1032,2,5,2,1,2,2,5,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +28015,29769,Female,Loyal Customer,53,Business travel,Business,399,3,3,3,3,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +28016,128940,Female,Loyal Customer,52,Business travel,Business,414,2,2,2,2,3,4,4,5,5,5,5,3,5,3,9,5.0,satisfied +28017,61911,Male,Loyal Customer,46,Business travel,Business,2304,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,9.0,satisfied +28018,81841,Male,Loyal Customer,70,Personal Travel,Eco,1416,2,3,1,4,4,1,2,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +28019,106272,Male,Loyal Customer,25,Business travel,Business,689,5,5,5,5,4,4,4,4,3,5,5,3,4,4,17,13.0,satisfied +28020,22030,Female,Loyal Customer,11,Personal Travel,Eco Plus,503,1,3,1,3,2,1,2,2,4,4,2,2,3,2,0,0.0,neutral or dissatisfied +28021,116870,Female,disloyal Customer,27,Business travel,Business,338,3,3,3,5,2,3,2,2,4,2,5,3,5,2,10,0.0,neutral or dissatisfied +28022,100616,Male,Loyal Customer,31,Business travel,Business,1121,3,3,3,3,4,4,4,4,5,4,5,4,5,4,1,12.0,satisfied +28023,34239,Male,Loyal Customer,28,Personal Travel,Eco Plus,1189,1,4,1,3,4,1,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +28024,6994,Male,Loyal Customer,19,Business travel,Business,3757,4,1,1,1,4,4,4,4,2,3,4,3,3,4,0,0.0,neutral or dissatisfied +28025,66121,Male,Loyal Customer,58,Business travel,Business,2286,3,1,1,1,4,3,3,3,3,3,3,4,3,1,36,25.0,neutral or dissatisfied +28026,5055,Female,disloyal Customer,33,Business travel,Business,223,3,3,3,1,2,3,2,2,3,4,4,4,4,2,1,0.0,neutral or dissatisfied +28027,37638,Female,Loyal Customer,30,Personal Travel,Eco,1056,2,5,2,2,4,2,4,4,4,4,5,4,5,4,9,0.0,neutral or dissatisfied +28028,111399,Male,Loyal Customer,51,Personal Travel,Eco,1111,4,4,4,1,4,4,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +28029,60258,Male,Loyal Customer,42,Personal Travel,Eco,1607,1,2,1,2,1,1,1,1,3,3,1,1,2,1,0,0.0,neutral or dissatisfied +28030,18303,Female,Loyal Customer,42,Business travel,Business,813,4,4,4,4,4,2,2,3,3,3,3,4,3,5,50,35.0,satisfied +28031,40188,Female,Loyal Customer,37,Business travel,Eco,347,5,3,3,3,5,5,5,5,3,1,5,5,5,5,0,0.0,satisfied +28032,65218,Male,Loyal Customer,45,Business travel,Business,469,3,3,3,3,3,4,5,5,5,5,5,4,5,5,4,4.0,satisfied +28033,80001,Female,Loyal Customer,55,Personal Travel,Eco,1010,2,4,2,4,3,4,3,4,4,2,4,4,4,3,41,12.0,neutral or dissatisfied +28034,60029,Female,Loyal Customer,68,Personal Travel,Eco,1085,4,2,4,3,3,4,4,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +28035,49909,Male,Loyal Customer,25,Business travel,Eco,363,4,5,3,5,4,4,4,4,5,2,1,2,3,4,43,36.0,satisfied +28036,103135,Male,Loyal Customer,59,Business travel,Business,3619,4,4,4,4,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +28037,12192,Male,disloyal Customer,26,Business travel,Business,1075,4,4,4,2,2,4,3,2,5,5,4,1,3,2,25,7.0,satisfied +28038,103278,Female,Loyal Customer,38,Personal Travel,Eco Plus,888,0,1,0,3,5,0,5,5,3,5,3,3,2,5,0,0.0,satisfied +28039,30815,Male,Loyal Customer,26,Personal Travel,Eco,1109,2,4,2,3,2,2,2,2,4,3,4,3,5,2,4,0.0,neutral or dissatisfied +28040,117322,Female,Loyal Customer,44,Personal Travel,Eco Plus,325,3,4,3,4,5,3,4,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +28041,65194,Female,Loyal Customer,24,Personal Travel,Eco,190,2,5,2,5,3,2,5,3,4,4,1,5,2,3,27,24.0,neutral or dissatisfied +28042,83210,Male,Loyal Customer,50,Business travel,Business,1895,5,5,5,5,2,5,5,5,5,5,5,4,5,4,62,81.0,satisfied +28043,77666,Female,Loyal Customer,47,Business travel,Business,874,3,3,3,3,3,3,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +28044,123702,Male,Loyal Customer,26,Personal Travel,Eco,214,3,0,3,3,5,3,5,5,4,4,1,3,3,5,0,5.0,neutral or dissatisfied +28045,71564,Female,Loyal Customer,48,Business travel,Business,3090,3,3,2,3,2,4,4,4,4,4,4,3,4,3,1,0.0,satisfied +28046,41883,Male,disloyal Customer,21,Business travel,Eco,1117,3,3,3,1,3,3,3,3,3,4,4,3,3,3,9,28.0,neutral or dissatisfied +28047,25264,Female,disloyal Customer,39,Business travel,Business,425,2,2,2,2,2,2,2,2,5,5,1,5,4,2,0,0.0,neutral or dissatisfied +28048,47710,Female,disloyal Customer,24,Business travel,Business,1334,4,0,4,3,3,4,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +28049,32013,Female,Loyal Customer,70,Business travel,Eco,101,4,4,5,4,3,2,1,3,3,4,3,5,3,2,0,0.0,satisfied +28050,70561,Male,Loyal Customer,27,Business travel,Business,3754,3,4,4,4,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +28051,49050,Female,disloyal Customer,50,Business travel,Eco,199,2,0,2,1,3,2,3,3,5,5,1,2,1,3,0,0.0,neutral or dissatisfied +28052,100250,Female,Loyal Customer,56,Business travel,Business,3280,4,4,4,4,2,4,5,3,3,3,3,3,3,3,55,74.0,satisfied +28053,44224,Female,Loyal Customer,33,Business travel,Business,2225,1,1,1,1,1,4,5,4,4,4,3,1,4,5,0,0.0,satisfied +28054,108693,Male,Loyal Customer,36,Personal Travel,Eco,577,2,5,3,3,1,3,2,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +28055,16075,Male,Loyal Customer,53,Personal Travel,Eco,744,2,5,2,3,4,2,4,4,5,5,2,4,5,4,102,101.0,neutral or dissatisfied +28056,42540,Male,Loyal Customer,34,Business travel,Business,1091,2,2,2,2,4,3,3,5,1,4,5,3,4,3,191,258.0,satisfied +28057,35994,Male,Loyal Customer,50,Business travel,Eco Plus,2496,5,5,5,5,5,5,5,5,1,5,5,5,4,5,0,0.0,satisfied +28058,110517,Female,Loyal Customer,53,Personal Travel,Eco Plus,787,1,4,1,2,5,5,5,4,4,1,4,4,4,4,4,21.0,neutral or dissatisfied +28059,104121,Female,Loyal Customer,42,Personal Travel,Business,448,3,4,3,3,1,4,1,3,3,3,3,1,3,2,25,8.0,neutral or dissatisfied +28060,51321,Female,disloyal Customer,42,Business travel,Eco Plus,421,2,2,2,3,5,2,5,5,1,5,3,4,4,5,43,32.0,neutral or dissatisfied +28061,92530,Female,Loyal Customer,48,Personal Travel,Eco,1947,1,4,1,3,5,2,4,3,3,1,3,1,3,2,11,0.0,neutral or dissatisfied +28062,14287,Female,Loyal Customer,48,Business travel,Business,2546,4,4,4,4,4,5,5,5,5,5,3,3,5,1,0,0.0,satisfied +28063,75716,Female,Loyal Customer,39,Business travel,Business,868,3,5,5,5,2,2,3,3,3,3,3,4,3,3,11,8.0,neutral or dissatisfied +28064,116808,Male,Loyal Customer,51,Business travel,Eco Plus,308,3,3,3,3,3,3,3,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +28065,4972,Female,Loyal Customer,46,Business travel,Eco Plus,531,4,3,3,3,3,5,5,4,4,4,4,4,4,5,3,0.0,satisfied +28066,115528,Female,disloyal Customer,22,Business travel,Eco,417,2,3,2,3,5,2,5,5,1,5,2,3,3,5,5,7.0,neutral or dissatisfied +28067,46087,Male,disloyal Customer,40,Business travel,Eco,495,4,5,4,5,4,4,4,4,3,3,2,1,2,4,0,0.0,neutral or dissatisfied +28068,21769,Male,Loyal Customer,33,Business travel,Business,352,2,2,2,2,5,5,5,5,4,2,2,5,2,5,0,0.0,satisfied +28069,84649,Male,Loyal Customer,60,Business travel,Business,363,2,2,2,2,3,5,5,4,4,4,4,5,4,4,1,4.0,satisfied +28070,66687,Female,Loyal Customer,49,Business travel,Business,2434,5,5,5,5,3,5,5,4,4,4,4,4,4,5,8,0.0,satisfied +28071,72275,Female,Loyal Customer,54,Business travel,Business,919,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +28072,4632,Female,Loyal Customer,53,Business travel,Business,2457,2,2,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +28073,24653,Male,Loyal Customer,50,Business travel,Eco,834,5,2,2,2,5,5,5,5,3,1,1,2,1,5,0,0.0,satisfied +28074,5799,Female,Loyal Customer,55,Business travel,Business,3640,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +28075,110499,Female,disloyal Customer,28,Business travel,Business,925,3,3,3,2,5,3,5,5,5,3,4,3,4,5,31,6.0,neutral or dissatisfied +28076,80648,Male,Loyal Customer,34,Business travel,Business,821,5,5,5,5,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +28077,5173,Female,Loyal Customer,42,Personal Travel,Business,351,2,3,2,2,2,3,3,1,3,3,2,3,3,3,692,702.0,neutral or dissatisfied +28078,94746,Female,Loyal Customer,36,Business travel,Eco,192,4,4,4,4,4,4,4,4,2,1,3,1,4,4,30,25.0,neutral or dissatisfied +28079,101978,Female,Loyal Customer,21,Personal Travel,Eco,628,2,5,1,4,1,1,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +28080,7024,Female,Loyal Customer,59,Personal Travel,Eco,196,3,5,3,2,4,5,5,5,5,3,5,5,5,4,2,0.0,neutral or dissatisfied +28081,70766,Female,Loyal Customer,66,Personal Travel,Business,328,2,4,5,3,5,5,4,2,2,5,3,4,2,3,0,0.0,neutral or dissatisfied +28082,64314,Male,Loyal Customer,29,Business travel,Business,2543,4,4,4,4,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +28083,94434,Male,Loyal Customer,52,Business travel,Business,1568,4,4,4,4,5,5,5,5,5,4,5,3,5,5,2,0.0,satisfied +28084,38565,Male,Loyal Customer,34,Personal Travel,Eco,2475,2,3,2,4,1,2,1,1,5,3,4,1,1,1,0,0.0,neutral or dissatisfied +28085,31571,Male,Loyal Customer,49,Business travel,Eco,771,5,4,2,2,4,5,4,4,2,1,4,1,4,4,0,0.0,satisfied +28086,108396,Female,Loyal Customer,45,Business travel,Eco Plus,290,2,4,4,4,3,4,3,2,2,2,2,2,2,3,3,21.0,neutral or dissatisfied +28087,44227,Male,disloyal Customer,32,Business travel,Business,222,1,1,1,4,5,1,5,5,5,5,3,1,3,5,0,5.0,neutral or dissatisfied +28088,128397,Female,Loyal Customer,48,Business travel,Eco,370,4,3,3,3,2,4,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +28089,53943,Female,Loyal Customer,32,Business travel,Business,3391,3,3,3,3,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +28090,11265,Male,Loyal Customer,8,Personal Travel,Eco,517,1,5,1,2,5,1,5,5,3,4,5,3,5,5,30,27.0,neutral or dissatisfied +28091,65707,Female,disloyal Customer,26,Business travel,Business,1061,0,0,0,4,3,0,1,3,5,2,4,4,5,3,0,3.0,satisfied +28092,56737,Male,Loyal Customer,35,Personal Travel,Eco,937,3,5,2,5,1,2,1,1,3,4,5,5,4,1,22,24.0,neutral or dissatisfied +28093,56001,Female,disloyal Customer,24,Business travel,Business,931,5,2,5,3,5,1,1,4,3,5,4,1,3,1,0,0.0,satisfied +28094,34934,Male,Loyal Customer,23,Personal Travel,Eco,187,2,5,2,3,2,2,2,2,5,3,5,3,4,2,23,14.0,neutral or dissatisfied +28095,128565,Male,Loyal Customer,67,Personal Travel,Eco Plus,370,3,0,3,5,4,3,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +28096,6200,Female,Loyal Customer,30,Personal Travel,Eco Plus,409,2,5,2,1,2,2,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +28097,24426,Male,Loyal Customer,58,Personal Travel,Eco,634,2,3,2,3,5,2,3,5,2,1,3,4,3,5,0,0.0,neutral or dissatisfied +28098,44135,Female,Loyal Customer,38,Business travel,Business,2432,4,5,5,5,4,3,3,1,1,1,4,2,1,1,0,38.0,neutral or dissatisfied +28099,47769,Male,Loyal Customer,37,Business travel,Business,3508,1,1,2,1,5,1,2,5,5,5,5,4,5,4,0,0.0,satisfied +28100,45189,Female,disloyal Customer,39,Business travel,Business,1437,5,5,5,3,4,5,4,4,4,5,2,4,5,4,40,64.0,satisfied +28101,95651,Male,disloyal Customer,36,Business travel,Business,928,2,2,2,5,1,2,3,1,5,3,5,5,4,1,12,9.0,neutral or dissatisfied +28102,67530,Male,Loyal Customer,39,Business travel,Business,1235,5,1,5,5,4,4,5,4,4,4,4,3,4,5,73,60.0,satisfied +28103,29030,Female,Loyal Customer,37,Business travel,Business,2401,2,2,2,2,4,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +28104,107447,Male,Loyal Customer,29,Personal Travel,Eco,717,3,5,3,2,4,3,1,4,4,2,4,5,4,4,97,86.0,neutral or dissatisfied +28105,33432,Male,disloyal Customer,29,Business travel,Eco,886,2,2,2,2,2,2,5,2,1,4,3,4,3,2,0,3.0,neutral or dissatisfied +28106,16316,Female,Loyal Customer,24,Business travel,Business,628,5,5,5,5,4,4,4,4,1,1,2,5,2,4,49,60.0,satisfied +28107,106301,Male,Loyal Customer,8,Business travel,Business,998,4,2,2,2,4,4,4,4,2,3,4,3,4,4,4,11.0,neutral or dissatisfied +28108,86172,Female,Loyal Customer,55,Business travel,Business,3810,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,2.0,satisfied +28109,125037,Male,Loyal Customer,45,Business travel,Business,2300,3,3,3,3,4,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +28110,14027,Female,disloyal Customer,13,Business travel,Eco,1117,5,5,5,1,3,5,1,3,2,3,2,2,3,3,0,3.0,satisfied +28111,76303,Male,Loyal Customer,63,Business travel,Eco,2182,3,5,5,5,3,3,3,3,4,3,2,3,4,3,1,0.0,neutral or dissatisfied +28112,83982,Female,Loyal Customer,20,Business travel,Eco,373,3,2,3,2,3,3,1,3,1,3,3,3,4,3,59,62.0,neutral or dissatisfied +28113,117822,Female,Loyal Customer,17,Personal Travel,Eco,328,2,4,2,3,5,2,5,5,3,1,2,4,5,5,3,11.0,neutral or dissatisfied +28114,109159,Female,Loyal Customer,44,Business travel,Business,616,2,2,2,2,5,4,4,4,4,4,4,4,4,4,3,5.0,satisfied +28115,58522,Male,Loyal Customer,70,Personal Travel,Eco,719,1,4,1,3,5,1,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +28116,48755,Male,disloyal Customer,33,Business travel,Business,373,4,4,4,4,5,4,5,5,1,3,3,3,4,5,0,3.0,neutral or dissatisfied +28117,92197,Female,Loyal Customer,43,Business travel,Business,2079,5,5,4,5,3,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +28118,9625,Male,Loyal Customer,38,Business travel,Eco Plus,288,2,4,3,4,2,2,2,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +28119,42741,Female,Loyal Customer,16,Personal Travel,Eco,536,1,5,1,2,5,1,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +28120,9513,Female,Loyal Customer,30,Personal Travel,Eco Plus,239,5,5,5,3,4,5,4,4,4,3,4,3,4,4,2,0.0,satisfied +28121,121799,Female,Loyal Customer,50,Business travel,Business,2461,3,4,3,3,4,5,4,5,5,5,5,3,5,5,24,52.0,satisfied +28122,119674,Male,Loyal Customer,35,Personal Travel,Eco Plus,507,3,5,3,1,2,3,4,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +28123,11926,Female,Loyal Customer,64,Personal Travel,Eco,744,2,4,2,1,3,4,5,4,4,2,1,2,4,4,0,6.0,neutral or dissatisfied +28124,55763,Male,Loyal Customer,38,Business travel,Business,2182,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +28125,21229,Female,Loyal Customer,61,Personal Travel,Eco,153,3,5,3,2,3,5,4,4,4,3,4,5,4,4,66,65.0,neutral or dissatisfied +28126,72473,Male,Loyal Customer,28,Business travel,Business,3267,1,1,1,1,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +28127,52791,Male,Loyal Customer,59,Personal Travel,Eco,1874,2,1,2,1,3,2,3,3,1,4,2,1,1,3,0,0.0,neutral or dissatisfied +28128,40530,Male,disloyal Customer,24,Business travel,Business,391,5,0,5,4,1,5,1,1,5,4,4,5,5,1,0,0.0,satisfied +28129,18663,Male,Loyal Customer,53,Personal Travel,Eco,192,1,4,0,3,4,0,4,4,4,4,5,3,4,4,71,72.0,neutral or dissatisfied +28130,126357,Male,Loyal Customer,35,Personal Travel,Eco,600,2,3,2,3,2,2,2,2,4,4,2,5,2,2,9,5.0,neutral or dissatisfied +28131,108911,Male,Loyal Customer,42,Business travel,Eco,1243,2,5,5,5,1,2,1,1,4,5,3,1,4,1,57,33.0,neutral or dissatisfied +28132,73012,Female,Loyal Customer,52,Personal Travel,Eco,944,3,4,3,3,4,3,3,2,2,3,2,2,2,4,7,3.0,neutral or dissatisfied +28133,47643,Female,Loyal Customer,46,Business travel,Eco,1428,4,4,3,4,4,4,2,5,5,4,5,3,5,3,0,4.0,satisfied +28134,91645,Male,Loyal Customer,18,Personal Travel,Eco,1199,2,3,2,1,3,2,3,3,3,3,3,2,5,3,5,0.0,neutral or dissatisfied +28135,104846,Male,Loyal Customer,31,Business travel,Business,1810,5,5,5,5,3,4,3,3,4,2,4,4,4,3,98,95.0,satisfied +28136,50766,Male,Loyal Customer,35,Personal Travel,Eco,373,3,1,1,2,2,1,2,2,2,4,1,4,2,2,0,4.0,neutral or dissatisfied +28137,75350,Male,Loyal Customer,8,Personal Travel,Eco,2615,2,4,2,2,2,5,3,5,3,3,5,3,3,3,0,0.0,neutral or dissatisfied +28138,113531,Female,Loyal Customer,38,Business travel,Business,2259,3,4,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +28139,108565,Male,Loyal Customer,15,Personal Travel,Eco Plus,735,4,2,4,3,1,4,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +28140,97198,Female,Loyal Customer,65,Personal Travel,Eco,1390,2,2,2,4,3,4,3,3,3,2,1,1,3,4,55,47.0,neutral or dissatisfied +28141,43529,Male,Loyal Customer,47,Business travel,Eco,920,4,2,2,2,4,4,4,4,2,1,3,3,2,4,0,0.0,satisfied +28142,80161,Female,disloyal Customer,27,Business travel,Eco,959,4,3,3,4,4,5,5,4,4,4,4,5,4,5,6,40.0,neutral or dissatisfied +28143,93726,Male,Loyal Customer,12,Personal Travel,Eco,630,2,1,2,3,3,2,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +28144,112064,Male,Loyal Customer,11,Business travel,Eco Plus,1754,4,1,1,1,4,3,2,4,1,2,2,4,4,4,10,0.0,neutral or dissatisfied +28145,116928,Male,disloyal Customer,33,Business travel,Business,370,3,4,4,2,3,4,3,3,4,3,5,3,5,3,41,76.0,neutral or dissatisfied +28146,64375,Male,Loyal Customer,59,Personal Travel,Eco,1192,3,4,3,3,5,3,5,5,2,1,4,4,1,5,0,0.0,neutral or dissatisfied +28147,55844,Female,Loyal Customer,57,Personal Travel,Eco,1416,2,2,1,4,3,4,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +28148,121210,Female,disloyal Customer,29,Business travel,Business,2075,5,5,5,1,3,5,3,3,3,4,5,5,4,3,0,18.0,satisfied +28149,15337,Male,Loyal Customer,31,Business travel,Eco Plus,589,4,4,4,4,4,4,4,4,5,1,4,1,4,4,0,0.0,satisfied +28150,127223,Female,Loyal Customer,38,Business travel,Business,1460,2,2,2,2,3,4,5,3,3,3,3,5,3,4,6,0.0,satisfied +28151,37433,Male,disloyal Customer,30,Business travel,Eco,944,2,1,1,3,1,1,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +28152,2809,Female,Loyal Customer,47,Business travel,Business,409,5,5,1,5,4,5,4,4,4,4,4,3,4,3,0,28.0,satisfied +28153,48798,Male,Loyal Customer,47,Business travel,Business,421,2,4,2,2,4,3,3,2,2,2,2,3,2,1,60,50.0,neutral or dissatisfied +28154,86410,Female,Loyal Customer,57,Business travel,Business,762,2,2,2,2,2,4,4,4,4,4,4,4,4,3,11,1.0,satisfied +28155,69524,Male,Loyal Customer,56,Business travel,Business,2475,3,3,3,3,5,5,5,4,5,4,5,5,3,5,24,29.0,satisfied +28156,11300,Female,Loyal Customer,21,Personal Travel,Eco,191,1,5,1,2,3,1,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +28157,54123,Female,Loyal Customer,16,Business travel,Eco,1504,4,2,2,2,4,4,3,4,4,2,5,4,1,4,2,14.0,satisfied +28158,89439,Male,Loyal Customer,26,Personal Travel,Eco,134,2,4,2,1,5,2,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +28159,109572,Male,Loyal Customer,24,Personal Travel,Eco,920,5,5,5,1,4,5,1,4,3,2,5,4,5,4,9,1.0,satisfied +28160,28010,Female,disloyal Customer,14,Business travel,Eco,763,4,4,4,2,4,4,4,4,3,5,1,4,5,4,0,0.0,satisfied +28161,66892,Male,disloyal Customer,12,Business travel,Eco,1119,3,3,3,3,4,3,4,4,4,2,4,3,4,4,0,17.0,neutral or dissatisfied +28162,25683,Male,Loyal Customer,27,Business travel,Business,3455,4,4,2,4,4,4,4,4,4,3,5,5,5,4,9,0.0,satisfied +28163,97309,Female,disloyal Customer,45,Business travel,Business,1020,5,5,5,1,1,5,1,1,4,5,5,5,5,1,10,14.0,satisfied +28164,62612,Female,Loyal Customer,47,Personal Travel,Eco,1744,1,2,1,4,2,4,3,3,3,1,3,1,3,4,8,6.0,neutral or dissatisfied +28165,35552,Female,Loyal Customer,51,Personal Travel,Eco,1005,2,4,2,3,5,4,4,2,2,2,2,3,2,4,6,21.0,neutral or dissatisfied +28166,2489,Female,Loyal Customer,42,Business travel,Business,1379,4,4,4,4,3,5,4,4,4,4,4,3,4,5,37,22.0,satisfied +28167,128870,Female,Loyal Customer,52,Business travel,Business,2454,4,4,5,4,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +28168,107393,Female,Loyal Customer,43,Business travel,Business,468,5,5,5,5,5,5,5,4,5,4,4,5,5,5,321,360.0,satisfied +28169,79717,Female,Loyal Customer,46,Personal Travel,Eco,712,4,3,4,1,2,5,4,1,1,4,1,5,1,3,0,14.0,neutral or dissatisfied +28170,104695,Female,disloyal Customer,77,Business travel,Eco,159,2,1,2,2,3,2,3,3,1,5,3,2,3,3,3,0.0,neutral or dissatisfied +28171,58684,Female,Loyal Customer,58,Personal Travel,Eco,837,3,5,3,2,4,5,5,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +28172,28793,Male,Loyal Customer,59,Personal Travel,Business,605,1,5,1,5,4,4,5,3,3,1,3,3,3,5,0,7.0,neutral or dissatisfied +28173,97880,Female,Loyal Customer,41,Business travel,Business,2010,2,2,2,2,4,4,5,4,4,4,4,3,4,4,41,29.0,satisfied +28174,115507,Male,disloyal Customer,24,Business travel,Business,325,4,2,4,3,2,4,4,2,4,3,5,3,4,2,1,3.0,satisfied +28175,48908,Male,Loyal Customer,30,Business travel,Business,2115,1,1,5,1,4,4,5,4,3,5,1,1,1,4,2,0.0,satisfied +28176,57108,Male,Loyal Customer,52,Business travel,Business,2944,4,4,4,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +28177,52721,Male,Loyal Customer,31,Business travel,Business,406,1,1,1,1,4,4,4,4,1,1,3,4,4,4,0,0.0,satisfied +28178,82429,Female,Loyal Customer,46,Business travel,Business,1565,3,3,3,3,3,5,5,5,5,5,5,3,5,4,4,0.0,satisfied +28179,81249,Male,Loyal Customer,32,Business travel,Business,1922,2,2,2,2,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +28180,108543,Male,disloyal Customer,59,Business travel,Eco,511,1,2,2,2,2,2,2,2,4,4,2,1,2,2,44,35.0,neutral or dissatisfied +28181,6348,Male,Loyal Customer,44,Business travel,Business,315,5,5,3,5,5,4,4,4,4,4,4,5,4,4,69,72.0,satisfied +28182,37094,Male,Loyal Customer,22,Business travel,Business,1046,1,1,1,1,5,5,5,5,5,3,3,5,3,5,0,0.0,satisfied +28183,93471,Male,Loyal Customer,45,Business travel,Business,2414,5,5,5,5,3,4,4,4,4,4,4,5,4,5,15,13.0,satisfied +28184,60908,Male,Loyal Customer,36,Personal Travel,Eco,589,4,4,4,2,2,4,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +28185,122068,Male,disloyal Customer,36,Business travel,Eco,130,1,1,1,3,2,1,2,2,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +28186,92755,Male,Loyal Customer,34,Personal Travel,Eco,1276,1,5,1,5,4,1,2,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +28187,24926,Female,Loyal Customer,19,Personal Travel,Eco,762,3,4,3,3,1,3,1,1,5,4,5,2,3,1,0,0.0,neutral or dissatisfied +28188,117651,Female,Loyal Customer,70,Personal Travel,Eco Plus,347,3,5,3,3,4,5,5,1,1,3,1,3,1,3,21,12.0,neutral or dissatisfied +28189,104555,Female,Loyal Customer,43,Business travel,Business,3652,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +28190,26070,Male,Loyal Customer,42,Business travel,Business,3945,5,5,3,5,4,2,4,4,4,4,4,4,4,1,0,0.0,satisfied +28191,92376,Female,Loyal Customer,29,Personal Travel,Business,1947,4,5,4,1,2,4,4,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +28192,84223,Female,Loyal Customer,12,Personal Travel,Eco,432,5,5,5,4,5,5,5,5,1,1,5,2,2,5,0,0.0,satisfied +28193,69565,Male,Loyal Customer,42,Business travel,Business,2586,1,1,1,1,5,5,5,4,2,4,4,5,5,5,0,0.0,satisfied +28194,83258,Female,Loyal Customer,27,Business travel,Eco,2079,1,5,5,5,1,1,1,1,3,5,1,4,2,1,7,53.0,neutral or dissatisfied +28195,113023,Female,Loyal Customer,11,Personal Travel,Business,543,2,5,2,1,1,2,1,1,4,3,5,4,5,1,7,0.0,neutral or dissatisfied +28196,91191,Male,Loyal Customer,56,Personal Travel,Eco,581,2,4,2,3,4,2,1,4,5,4,5,5,5,4,4,0.0,neutral or dissatisfied +28197,10576,Female,Loyal Customer,36,Business travel,Business,312,4,2,2,2,4,3,3,4,4,4,4,4,4,3,71,67.0,neutral or dissatisfied +28198,27433,Female,Loyal Customer,31,Business travel,Business,3252,4,4,3,3,4,4,4,4,1,2,3,1,4,4,0,0.0,neutral or dissatisfied +28199,12466,Male,Loyal Customer,25,Personal Travel,Eco,192,3,5,3,2,5,3,5,5,3,5,5,5,4,5,37,34.0,neutral or dissatisfied +28200,43073,Male,Loyal Customer,58,Personal Travel,Eco,236,2,5,2,2,4,2,4,4,5,2,5,5,5,4,5,0.0,neutral or dissatisfied +28201,128517,Male,Loyal Customer,16,Personal Travel,Eco,651,2,3,2,2,1,2,1,1,5,3,4,3,5,1,40,19.0,neutral or dissatisfied +28202,90917,Male,Loyal Customer,51,Business travel,Eco,404,4,1,1,1,4,4,4,4,3,5,1,5,4,4,62,62.0,satisfied +28203,87132,Male,Loyal Customer,14,Personal Travel,Eco,640,1,4,1,3,4,1,4,4,5,3,5,4,5,4,4,1.0,neutral or dissatisfied +28204,30247,Female,Loyal Customer,25,Business travel,Eco Plus,826,4,4,4,4,4,4,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +28205,18751,Male,Loyal Customer,64,Personal Travel,Eco,1167,3,4,3,2,2,3,2,2,5,5,5,5,5,2,4,0.0,neutral or dissatisfied +28206,40711,Male,Loyal Customer,40,Business travel,Business,501,3,1,3,3,5,4,3,3,3,3,3,3,3,5,0,0.0,satisfied +28207,86596,Female,Loyal Customer,49,Business travel,Business,1961,4,4,3,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +28208,32385,Male,disloyal Customer,22,Business travel,Eco,101,4,0,5,5,3,5,3,3,4,1,2,3,5,3,0,3.0,satisfied +28209,118588,Male,disloyal Customer,23,Business travel,Business,370,4,5,4,5,4,1,5,3,2,4,4,5,4,5,205,193.0,satisfied +28210,118727,Male,Loyal Customer,34,Personal Travel,Eco,651,2,2,2,4,5,2,5,5,2,5,3,3,3,5,24,28.0,neutral or dissatisfied +28211,6717,Female,Loyal Customer,43,Personal Travel,Eco,258,2,4,0,1,1,3,3,3,3,0,2,5,3,5,14,12.0,neutral or dissatisfied +28212,14952,Male,Loyal Customer,57,Personal Travel,Eco,528,2,4,2,2,4,2,4,4,3,4,5,3,4,4,5,0.0,neutral or dissatisfied +28213,19563,Female,disloyal Customer,30,Business travel,Eco,173,2,0,2,4,1,2,2,1,1,5,3,3,1,1,0,0.0,neutral or dissatisfied +28214,44785,Male,Loyal Customer,15,Business travel,Business,2330,5,5,5,5,4,4,4,4,1,3,3,3,3,4,0,3.0,satisfied +28215,1129,Female,Loyal Customer,36,Personal Travel,Eco,134,3,3,0,3,3,0,3,3,1,4,3,3,5,3,0,0.0,neutral or dissatisfied +28216,84491,Male,Loyal Customer,33,Personal Travel,Eco,2994,3,4,3,3,4,3,5,4,2,2,4,4,3,4,0,0.0,neutral or dissatisfied +28217,18347,Female,Loyal Customer,51,Personal Travel,Eco,612,2,5,1,3,4,5,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +28218,24457,Male,Loyal Customer,39,Business travel,Eco,481,4,1,5,5,4,4,4,4,5,3,3,3,5,4,0,0.0,satisfied +28219,37859,Male,Loyal Customer,43,Business travel,Business,1068,3,1,1,1,4,2,3,3,3,3,3,3,3,1,33,37.0,neutral or dissatisfied +28220,118146,Male,Loyal Customer,43,Personal Travel,Business,1440,4,4,5,1,5,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +28221,78577,Female,Loyal Customer,40,Business travel,Business,630,4,5,5,5,1,2,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +28222,2998,Female,disloyal Customer,35,Business travel,Business,862,3,3,3,5,4,3,3,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +28223,33523,Male,Loyal Customer,34,Business travel,Business,2643,5,5,5,5,3,2,5,3,3,4,3,2,3,1,0,0.0,satisfied +28224,78628,Male,disloyal Customer,26,Business travel,Eco,1342,4,4,4,3,1,4,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +28225,98696,Female,Loyal Customer,65,Personal Travel,Eco,834,2,4,2,4,2,3,3,4,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +28226,25981,Male,Loyal Customer,17,Business travel,Business,1953,3,4,3,3,3,4,3,3,2,2,5,2,3,3,0,0.0,satisfied +28227,84869,Male,Loyal Customer,43,Personal Travel,Eco,516,3,4,3,4,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +28228,99454,Male,Loyal Customer,54,Business travel,Business,1783,0,0,0,4,2,4,4,3,3,3,3,5,3,5,0,4.0,satisfied +28229,59606,Male,Loyal Customer,33,Business travel,Business,2640,2,2,2,2,2,2,2,2,1,4,4,4,3,2,66,87.0,neutral or dissatisfied +28230,127615,Male,Loyal Customer,47,Business travel,Eco,1773,2,2,2,2,2,2,2,2,1,3,4,4,3,2,0,0.0,neutral or dissatisfied +28231,68543,Male,Loyal Customer,53,Business travel,Eco,613,4,5,5,5,4,4,4,4,2,2,3,1,4,4,0,0.0,neutral or dissatisfied +28232,7230,Male,Loyal Customer,48,Business travel,Business,2157,4,4,4,4,3,2,4,5,5,5,4,5,5,2,35,35.0,satisfied +28233,70095,Female,Loyal Customer,56,Business travel,Business,3534,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +28234,7023,Male,Loyal Customer,31,Personal Travel,Eco,196,3,2,3,4,5,3,5,5,4,4,3,2,3,5,0,11.0,neutral or dissatisfied +28235,30407,Male,Loyal Customer,57,Personal Travel,Eco,862,3,4,4,2,5,4,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +28236,88021,Female,Loyal Customer,57,Business travel,Business,594,2,2,3,2,4,5,5,4,4,4,4,5,4,5,3,10.0,satisfied +28237,915,Female,disloyal Customer,24,Business travel,Eco,247,5,0,5,2,2,5,2,2,5,5,4,5,4,2,3,0.0,satisfied +28238,24101,Male,Loyal Customer,39,Business travel,Business,2415,2,2,2,2,2,2,5,5,5,5,5,1,5,5,0,6.0,satisfied +28239,97652,Female,Loyal Customer,35,Personal Travel,Eco,1587,4,4,4,4,5,4,5,5,5,4,3,4,5,5,21,25.0,neutral or dissatisfied +28240,50489,Female,Loyal Customer,7,Personal Travel,Eco,373,4,0,4,4,5,4,5,5,5,2,4,4,4,5,0,0.0,satisfied +28241,109526,Male,Loyal Customer,50,Business travel,Eco,966,5,2,2,2,5,5,5,5,4,3,4,2,2,5,0,0.0,satisfied +28242,110448,Female,Loyal Customer,49,Personal Travel,Eco,798,3,5,3,1,4,1,3,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +28243,23513,Female,disloyal Customer,36,Business travel,Eco,349,3,3,4,4,2,4,2,2,3,3,1,1,5,2,0,0.0,neutral or dissatisfied +28244,101318,Female,disloyal Customer,25,Business travel,Eco,986,3,3,3,3,3,4,4,2,4,4,4,4,2,4,156,152.0,neutral or dissatisfied +28245,11903,Female,Loyal Customer,49,Business travel,Business,1818,1,1,1,1,4,5,5,3,3,3,3,3,3,4,11,8.0,satisfied +28246,108802,Female,Loyal Customer,42,Personal Travel,Eco,404,3,5,3,4,2,5,4,4,4,3,4,4,4,5,39,35.0,neutral or dissatisfied +28247,125827,Female,Loyal Customer,59,Business travel,Business,951,4,4,4,4,2,2,2,5,3,5,4,2,4,2,143,128.0,satisfied +28248,34900,Female,disloyal Customer,25,Business travel,Business,395,0,4,0,4,1,0,1,1,4,2,2,1,1,1,0,0.0,satisfied +28249,107844,Male,Loyal Customer,45,Business travel,Business,1683,2,3,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +28250,54762,Male,disloyal Customer,26,Business travel,Eco Plus,787,3,3,3,3,3,3,5,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +28251,100416,Female,Loyal Customer,56,Personal Travel,Eco Plus,1073,3,4,3,1,3,4,5,2,2,3,2,4,2,5,1,11.0,neutral or dissatisfied +28252,101906,Female,Loyal Customer,32,Personal Travel,Eco,1984,3,4,3,3,4,3,5,4,3,5,4,3,4,4,46,43.0,neutral or dissatisfied +28253,78992,Female,disloyal Customer,21,Business travel,Eco,356,1,0,1,3,5,1,5,5,4,3,4,3,4,5,2,20.0,neutral or dissatisfied +28254,57209,Male,disloyal Customer,11,Business travel,Eco,1352,1,1,1,4,5,1,5,5,3,1,4,4,3,5,0,0.0,neutral or dissatisfied +28255,120104,Female,Loyal Customer,56,Business travel,Business,1576,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,8.0,satisfied +28256,85051,Male,Loyal Customer,53,Business travel,Business,2142,2,2,2,2,4,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +28257,88436,Female,Loyal Customer,23,Business travel,Business,1802,4,1,1,1,4,4,4,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +28258,65523,Male,Loyal Customer,25,Business travel,Eco,1616,2,4,4,4,2,2,1,2,1,1,4,2,3,2,10,15.0,neutral or dissatisfied +28259,28307,Female,Loyal Customer,32,Business travel,Business,3140,4,4,5,4,4,4,4,4,4,4,1,2,5,4,0,0.0,satisfied +28260,128554,Female,Loyal Customer,60,Business travel,Business,3117,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +28261,112308,Male,disloyal Customer,29,Business travel,Business,909,1,1,1,5,5,1,5,5,3,4,5,5,5,5,42,40.0,neutral or dissatisfied +28262,96842,Male,Loyal Customer,32,Business travel,Business,2639,3,5,5,5,3,3,3,3,3,5,4,3,3,3,9,7.0,neutral or dissatisfied +28263,42590,Male,Loyal Customer,32,Business travel,Eco,1154,4,4,4,4,4,4,4,4,3,4,3,4,4,4,0,0.0,satisfied +28264,72704,Female,Loyal Customer,53,Business travel,Business,2054,2,2,1,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +28265,4083,Male,Loyal Customer,58,Business travel,Business,1826,3,5,5,5,2,4,3,3,3,3,3,2,3,3,22,8.0,neutral or dissatisfied +28266,54860,Male,disloyal Customer,26,Business travel,Eco,862,2,2,2,3,4,2,4,4,4,4,3,1,4,4,29,13.0,neutral or dissatisfied +28267,4752,Male,disloyal Customer,22,Business travel,Eco,403,2,5,2,5,5,2,1,5,3,2,4,3,4,5,1,57.0,neutral or dissatisfied +28268,105305,Male,Loyal Customer,37,Personal Travel,Eco,738,3,2,3,4,3,3,3,3,2,4,4,1,3,3,34,25.0,neutral or dissatisfied +28269,83117,Female,Loyal Customer,18,Personal Travel,Eco,1086,0,4,0,3,1,0,1,1,2,1,4,5,1,1,0,0.0,satisfied +28270,10159,Female,Loyal Customer,59,Personal Travel,Eco,1195,2,5,2,4,3,4,4,4,4,2,4,5,4,4,9,9.0,neutral or dissatisfied +28271,124692,Male,disloyal Customer,25,Business travel,Business,399,1,4,1,1,4,1,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +28272,47888,Male,Loyal Customer,43,Business travel,Business,1842,3,5,5,5,1,2,2,3,3,3,3,2,3,1,103,93.0,neutral or dissatisfied +28273,126586,Female,Loyal Customer,44,Business travel,Business,1337,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +28274,88266,Female,disloyal Customer,65,Business travel,Business,444,2,2,2,1,3,2,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +28275,69440,Male,Loyal Customer,60,Personal Travel,Eco,1096,1,1,1,3,1,1,1,1,2,5,4,4,4,1,0,0.0,neutral or dissatisfied +28276,3842,Male,Loyal Customer,64,Personal Travel,Eco,650,2,4,2,4,1,2,1,1,4,2,4,1,5,1,0,5.0,neutral or dissatisfied +28277,54732,Female,Loyal Customer,69,Personal Travel,Eco,964,3,2,3,3,4,3,2,5,5,3,5,1,5,3,0,0.0,neutral or dissatisfied +28278,71583,Female,Loyal Customer,56,Business travel,Business,1012,2,2,2,2,2,4,5,5,5,5,5,3,5,3,1,0.0,satisfied +28279,48960,Female,Loyal Customer,46,Business travel,Business,3068,0,4,0,4,5,1,3,2,2,2,2,1,2,2,0,0.0,satisfied +28280,16334,Male,Loyal Customer,13,Personal Travel,Eco,628,2,5,2,3,2,5,5,3,3,5,4,5,5,5,204,193.0,neutral or dissatisfied +28281,64668,Female,Loyal Customer,53,Business travel,Business,1597,1,1,1,1,2,5,5,3,3,4,3,4,3,4,7,5.0,satisfied +28282,119807,Female,Loyal Customer,37,Business travel,Business,936,3,2,3,2,5,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +28283,112079,Female,disloyal Customer,31,Business travel,Eco,911,1,1,1,3,2,1,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +28284,72358,Female,Loyal Customer,16,Personal Travel,Business,964,4,5,4,2,1,4,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +28285,123963,Female,Loyal Customer,47,Business travel,Business,184,5,5,5,5,3,5,4,3,3,4,4,3,3,3,0,0.0,satisfied +28286,59788,Female,Loyal Customer,11,Personal Travel,Eco,895,1,1,1,1,3,1,4,3,3,1,2,3,1,3,16,3.0,neutral or dissatisfied +28287,109079,Male,Loyal Customer,65,Personal Travel,Eco,781,2,2,2,4,5,2,5,5,1,5,4,3,4,5,0,0.0,neutral or dissatisfied +28288,55991,Male,Loyal Customer,56,Business travel,Business,1504,5,1,4,4,4,5,5,4,3,3,3,5,3,5,0,17.0,neutral or dissatisfied +28289,75691,Female,disloyal Customer,27,Business travel,Business,868,3,3,3,4,2,3,2,2,5,5,4,4,4,2,1,6.0,neutral or dissatisfied +28290,17088,Female,Loyal Customer,60,Business travel,Business,466,1,1,1,1,2,1,2,5,5,5,5,5,5,5,4,0.0,satisfied +28291,15437,Male,disloyal Customer,27,Business travel,Eco,164,1,3,1,3,4,1,4,4,3,3,3,2,4,4,0,0.0,neutral or dissatisfied +28292,91694,Male,Loyal Customer,52,Business travel,Business,532,1,1,1,1,2,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +28293,125565,Male,Loyal Customer,32,Personal Travel,Eco,226,4,1,4,3,3,4,3,3,2,2,3,2,3,3,23,9.0,neutral or dissatisfied +28294,125810,Female,Loyal Customer,19,Business travel,Business,2271,4,4,4,4,5,4,5,5,4,4,4,3,4,5,18,28.0,satisfied +28295,55393,Female,Loyal Customer,32,Personal Travel,Eco,678,3,5,3,2,1,3,3,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +28296,119383,Male,Loyal Customer,58,Business travel,Business,2507,3,5,3,3,5,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +28297,69480,Female,Loyal Customer,57,Business travel,Business,1096,2,2,2,2,3,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +28298,27740,Male,Loyal Customer,15,Business travel,Business,1448,3,3,3,3,5,5,5,5,4,1,4,2,4,5,0,0.0,satisfied +28299,51173,Female,Loyal Customer,12,Personal Travel,Eco,190,2,5,0,5,3,0,5,3,4,5,1,1,2,3,0,0.0,neutral or dissatisfied +28300,41002,Female,Loyal Customer,53,Business travel,Business,1362,3,5,5,5,2,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +28301,119971,Female,Loyal Customer,34,Personal Travel,Eco,1009,1,4,1,2,1,1,1,1,5,5,4,1,3,1,0,0.0,neutral or dissatisfied +28302,37165,Male,Loyal Customer,10,Personal Travel,Eco,1179,4,5,4,4,2,4,2,2,4,5,3,4,4,2,4,6.0,satisfied +28303,20357,Female,disloyal Customer,44,Business travel,Eco,323,2,0,2,1,3,2,3,3,2,5,1,1,1,3,0,1.0,neutral or dissatisfied +28304,47809,Male,Loyal Customer,27,Business travel,Business,748,5,5,5,5,2,2,2,2,5,3,4,5,5,2,0,10.0,satisfied +28305,90336,Male,disloyal Customer,33,Business travel,Business,404,3,3,3,4,5,3,5,5,4,3,4,4,5,5,46,94.0,neutral or dissatisfied +28306,8809,Male,Loyal Customer,20,Business travel,Business,522,4,2,2,2,4,4,4,4,4,5,4,3,4,4,22,17.0,neutral or dissatisfied +28307,40812,Male,Loyal Customer,38,Business travel,Eco,588,3,1,1,1,3,3,3,3,4,3,3,4,3,3,1,0.0,neutral or dissatisfied +28308,88744,Male,Loyal Customer,26,Personal Travel,Eco,515,3,4,4,4,5,4,5,5,2,4,1,3,4,5,2,12.0,neutral or dissatisfied +28309,13817,Male,Loyal Customer,55,Business travel,Business,628,1,1,1,1,3,4,1,3,3,3,3,5,3,1,0,0.0,satisfied +28310,49356,Female,Loyal Customer,47,Business travel,Eco,109,5,3,3,3,5,4,5,5,5,5,5,2,5,5,0,0.0,satisfied +28311,86817,Female,Loyal Customer,22,Business travel,Business,692,2,1,1,1,2,2,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +28312,41898,Male,Loyal Customer,53,Business travel,Eco,129,5,1,1,1,4,5,4,4,4,3,4,2,1,4,0,0.0,satisfied +28313,389,Female,disloyal Customer,27,Business travel,Business,102,2,2,2,3,1,2,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +28314,69561,Female,disloyal Customer,20,Business travel,Eco,2475,2,2,2,3,3,2,3,3,2,2,3,1,2,3,0,0.0,neutral or dissatisfied +28315,86090,Male,Loyal Customer,49,Business travel,Business,226,1,3,3,3,5,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +28316,34470,Male,Loyal Customer,37,Business travel,Business,266,3,1,1,1,2,4,4,3,3,3,3,3,3,1,90,85.0,neutral or dissatisfied +28317,2012,Male,Loyal Customer,35,Business travel,Eco Plus,190,4,1,1,1,4,4,4,4,3,2,3,2,3,4,0,0.0,satisfied +28318,22874,Female,Loyal Customer,7,Personal Travel,Eco,302,1,5,5,1,4,5,3,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +28319,3773,Female,Loyal Customer,45,Business travel,Business,2815,5,5,5,5,4,5,4,4,4,4,4,5,4,5,54,102.0,satisfied +28320,22221,Female,Loyal Customer,32,Business travel,Eco Plus,773,4,5,5,5,4,4,4,4,5,1,3,4,4,4,12,14.0,satisfied +28321,71218,Male,Loyal Customer,48,Business travel,Business,2734,5,5,5,5,2,4,5,5,5,5,5,5,5,3,8,43.0,satisfied +28322,112165,Male,disloyal Customer,20,Business travel,Eco,495,4,3,4,2,5,4,4,5,1,2,3,3,3,5,0,0.0,satisfied +28323,91119,Female,Loyal Customer,65,Personal Travel,Eco,404,0,4,0,2,5,4,4,4,4,0,4,5,4,3,1,0.0,satisfied +28324,14207,Female,Loyal Customer,49,Business travel,Eco,714,2,5,5,5,4,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +28325,8007,Female,disloyal Customer,20,Business travel,Business,335,5,2,5,4,3,5,3,3,4,3,5,3,5,3,6,0.0,satisfied +28326,86663,Female,Loyal Customer,16,Personal Travel,Eco,746,2,3,1,3,3,1,3,3,3,3,4,3,3,3,1,4.0,neutral or dissatisfied +28327,29867,Female,Loyal Customer,54,Business travel,Eco,373,5,5,4,5,4,1,5,5,5,5,5,5,5,1,20,25.0,satisfied +28328,45572,Female,Loyal Customer,44,Business travel,Business,230,2,2,3,2,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +28329,86606,Female,Loyal Customer,51,Business travel,Business,2334,3,3,3,3,2,5,4,5,5,5,5,3,5,4,28,12.0,satisfied +28330,92071,Male,disloyal Customer,39,Business travel,Eco,896,2,2,2,2,5,2,5,5,4,4,3,1,3,5,0,0.0,neutral or dissatisfied +28331,52437,Male,Loyal Customer,22,Personal Travel,Eco,451,1,4,1,1,1,1,1,1,5,4,4,3,5,1,0,1.0,neutral or dissatisfied +28332,1154,Male,Loyal Customer,52,Personal Travel,Eco,354,3,4,3,1,2,3,1,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +28333,31501,Male,Loyal Customer,49,Business travel,Eco,967,2,2,2,2,2,2,2,2,4,2,3,2,2,2,0,0.0,satisfied +28334,69868,Female,Loyal Customer,53,Business travel,Business,1055,1,1,5,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +28335,38911,Male,Loyal Customer,52,Business travel,Business,298,0,0,0,3,2,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +28336,81762,Male,Loyal Customer,46,Business travel,Business,1416,1,1,1,1,4,5,5,5,5,5,5,5,5,3,59,30.0,satisfied +28337,21474,Female,Loyal Customer,72,Business travel,Eco,164,1,5,5,5,2,3,3,1,1,1,1,3,1,3,31,17.0,neutral or dissatisfied +28338,74847,Female,Loyal Customer,13,Personal Travel,Eco Plus,1797,3,4,3,4,5,3,5,5,2,4,4,2,4,5,0,0.0,neutral or dissatisfied +28339,67620,Male,disloyal Customer,24,Business travel,Business,1313,5,2,5,3,4,5,4,4,5,4,4,4,5,4,24,22.0,satisfied +28340,117079,Female,disloyal Customer,18,Business travel,Business,621,5,0,5,3,3,0,2,3,3,4,5,4,5,3,0,0.0,satisfied +28341,23967,Male,disloyal Customer,25,Business travel,Eco,596,2,3,2,2,2,2,2,2,3,2,2,1,3,2,0,0.0,neutral or dissatisfied +28342,126968,Male,Loyal Customer,39,Business travel,Business,647,4,4,4,4,2,5,4,3,3,3,3,4,3,3,3,2.0,satisfied +28343,38010,Male,Loyal Customer,37,Business travel,Business,2222,1,1,1,1,5,5,4,5,5,5,5,5,5,4,59,62.0,satisfied +28344,88755,Male,Loyal Customer,23,Personal Travel,Eco,240,4,1,4,2,4,4,2,4,1,3,3,3,2,4,0,0.0,neutral or dissatisfied +28345,92770,Male,Loyal Customer,59,Business travel,Business,1671,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +28346,109628,Female,Loyal Customer,37,Business travel,Business,973,4,4,4,4,2,5,4,5,5,5,5,4,5,5,7,0.0,satisfied +28347,114739,Male,Loyal Customer,59,Business travel,Business,2407,5,5,5,5,3,5,5,3,3,4,3,4,3,3,26,30.0,satisfied +28348,67181,Female,Loyal Customer,56,Personal Travel,Eco,1121,2,2,3,4,1,4,3,5,5,3,5,4,5,4,20,12.0,neutral or dissatisfied +28349,85520,Male,Loyal Customer,16,Personal Travel,Eco Plus,332,2,5,2,2,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +28350,31971,Female,Loyal Customer,40,Business travel,Business,101,2,5,5,5,1,3,3,3,3,3,2,2,3,1,0,0.0,neutral or dissatisfied +28351,43484,Male,Loyal Customer,25,Business travel,Business,3397,4,4,4,4,5,5,5,5,5,2,1,2,3,5,14,5.0,satisfied +28352,114031,Male,Loyal Customer,54,Personal Travel,Eco Plus,1750,1,3,0,4,3,0,3,3,5,1,5,4,3,3,1,,neutral or dissatisfied +28353,24213,Female,disloyal Customer,25,Business travel,Eco,170,4,4,5,4,5,5,5,5,1,2,2,3,4,5,0,0.0,satisfied +28354,70935,Female,Loyal Customer,56,Business travel,Business,612,2,1,1,1,2,2,2,2,2,2,2,2,2,1,30,20.0,neutral or dissatisfied +28355,78877,Male,Loyal Customer,46,Business travel,Eco,223,3,4,4,4,3,3,3,4,4,3,4,3,3,3,202,177.0,neutral or dissatisfied +28356,40670,Female,Loyal Customer,39,Personal Travel,Business,574,1,4,0,1,5,4,4,3,3,0,3,4,3,5,0,0.0,neutral or dissatisfied +28357,23207,Female,disloyal Customer,23,Business travel,Eco,125,3,4,3,3,4,3,3,4,4,3,4,3,4,4,73,91.0,neutral or dissatisfied +28358,98334,Female,Loyal Customer,53,Business travel,Business,1189,3,3,5,3,3,4,5,5,5,5,5,3,5,4,0,7.0,satisfied +28359,101760,Female,Loyal Customer,62,Personal Travel,Eco,1590,2,4,3,1,1,4,3,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +28360,51358,Female,Loyal Customer,19,Business travel,Eco Plus,250,2,4,3,4,2,2,3,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +28361,40551,Male,Loyal Customer,38,Business travel,Business,2661,3,3,3,3,2,1,2,5,5,5,5,4,5,3,22,13.0,satisfied +28362,52660,Female,Loyal Customer,65,Personal Travel,Eco,160,4,5,4,5,4,4,4,4,4,4,1,4,4,5,0,0.0,neutral or dissatisfied +28363,39831,Female,disloyal Customer,39,Business travel,Business,272,3,3,3,2,1,3,1,1,5,5,3,1,5,1,2,0.0,neutral or dissatisfied +28364,22823,Male,disloyal Customer,24,Business travel,Eco,134,3,3,3,3,3,3,3,3,3,3,2,1,2,3,71,65.0,neutral or dissatisfied +28365,12063,Female,Loyal Customer,8,Personal Travel,Eco,351,2,5,2,1,3,2,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +28366,68882,Female,Loyal Customer,9,Business travel,Business,3302,4,4,4,4,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +28367,91040,Male,Loyal Customer,45,Personal Travel,Eco,406,4,5,4,2,4,4,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +28368,48577,Female,Loyal Customer,31,Personal Travel,Eco,964,1,1,0,4,3,0,3,3,1,1,3,2,3,3,0,0.0,neutral or dissatisfied +28369,100752,Female,Loyal Customer,14,Personal Travel,Eco,328,4,3,4,2,3,4,2,3,4,3,5,4,2,3,20,23.0,neutral or dissatisfied +28370,112536,Female,Loyal Customer,34,Personal Travel,Eco,862,2,5,2,4,5,2,5,5,3,5,4,3,5,5,33,18.0,neutral or dissatisfied +28371,47607,Female,Loyal Customer,47,Business travel,Eco,1211,5,3,3,3,3,2,1,5,5,5,5,3,5,2,0,0.0,satisfied +28372,92360,Male,Loyal Customer,52,Business travel,Business,1947,3,3,3,3,4,4,4,4,4,4,4,4,4,4,3,0.0,satisfied +28373,18218,Male,Loyal Customer,47,Business travel,Business,2756,3,1,4,4,4,4,4,3,3,2,3,1,3,1,93,88.0,neutral or dissatisfied +28374,27006,Female,Loyal Customer,40,Business travel,Business,954,2,3,3,3,5,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +28375,19391,Male,Loyal Customer,46,Personal Travel,Eco,844,3,5,2,2,2,2,2,2,4,3,5,4,5,2,10,10.0,neutral or dissatisfied +28376,98753,Female,Loyal Customer,48,Business travel,Business,1814,5,5,5,5,2,4,4,4,4,5,4,5,4,5,36,52.0,satisfied +28377,96843,Male,disloyal Customer,30,Business travel,Business,816,4,4,4,2,2,4,2,2,4,3,4,3,5,2,0,0.0,satisfied +28378,52770,Male,Loyal Customer,40,Business travel,Business,1874,2,2,2,2,2,5,4,4,4,4,4,2,4,4,20,10.0,satisfied +28379,72599,Male,Loyal Customer,10,Personal Travel,Eco,985,2,5,2,5,2,2,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +28380,107264,Male,Loyal Customer,40,Business travel,Business,307,0,0,0,4,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +28381,103778,Female,Loyal Customer,38,Business travel,Business,2716,1,1,1,1,4,4,5,3,3,4,3,3,3,4,0,4.0,satisfied +28382,93620,Male,Loyal Customer,52,Business travel,Business,2523,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +28383,25113,Female,Loyal Customer,29,Business travel,Eco,946,5,4,4,4,5,5,5,5,5,3,1,4,1,5,1,0.0,satisfied +28384,57698,Male,Loyal Customer,31,Personal Travel,Eco,867,1,5,1,3,4,1,4,4,4,4,4,5,4,4,0,6.0,neutral or dissatisfied +28385,100686,Male,Loyal Customer,25,Business travel,Business,1786,1,1,2,1,4,4,4,4,4,2,4,2,1,4,31,30.0,satisfied +28386,127878,Female,Loyal Customer,59,Personal Travel,Eco,1276,4,4,4,3,4,5,4,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +28387,34157,Female,Loyal Customer,52,Business travel,Eco,1046,2,1,4,4,4,3,3,1,1,2,1,1,1,4,0,12.0,neutral or dissatisfied +28388,115230,Male,Loyal Customer,43,Business travel,Business,3945,1,1,1,1,2,4,4,5,5,5,5,3,5,3,44,41.0,satisfied +28389,74692,Female,Loyal Customer,17,Personal Travel,Eco,1235,3,4,3,4,4,3,4,4,3,5,5,3,4,4,3,0.0,neutral or dissatisfied +28390,3782,Male,Loyal Customer,42,Business travel,Eco,646,2,1,1,1,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +28391,50990,Male,Loyal Customer,55,Personal Travel,Eco,110,3,3,3,3,2,3,2,2,1,3,3,1,4,2,11,19.0,neutral or dissatisfied +28392,71879,Male,Loyal Customer,9,Personal Travel,Eco,1744,1,5,1,2,2,1,2,2,3,4,3,5,5,2,0,0.0,neutral or dissatisfied +28393,80590,Male,Loyal Customer,62,Personal Travel,Eco,1747,2,0,2,5,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +28394,113411,Male,disloyal Customer,24,Business travel,Eco,386,2,3,1,4,3,1,4,3,3,4,3,2,4,3,0,0.0,neutral or dissatisfied +28395,90952,Female,Loyal Customer,40,Business travel,Business,1746,0,5,0,2,3,2,4,3,3,5,5,5,3,2,0,0.0,satisfied +28396,48011,Female,Loyal Customer,43,Personal Travel,Eco Plus,834,1,5,1,2,5,1,5,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +28397,104218,Male,Loyal Customer,36,Business travel,Business,3003,4,4,4,4,2,3,2,4,4,4,4,3,4,2,8,9.0,neutral or dissatisfied +28398,100728,Male,disloyal Customer,20,Business travel,Eco,328,1,2,1,2,5,1,5,5,2,4,2,4,2,5,21,9.0,neutral or dissatisfied +28399,8391,Male,Loyal Customer,41,Business travel,Business,888,2,2,2,2,3,5,4,4,4,4,4,4,4,4,14,0.0,satisfied +28400,106361,Male,Loyal Customer,53,Business travel,Business,643,1,1,3,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +28401,10518,Female,Loyal Customer,33,Business travel,Business,224,5,5,5,5,3,4,4,4,4,4,5,3,4,5,16,14.0,satisfied +28402,82802,Female,Loyal Customer,46,Business travel,Business,3123,2,2,2,2,2,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +28403,11393,Female,Loyal Customer,51,Business travel,Business,3947,5,5,5,5,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +28404,117554,Female,Loyal Customer,43,Business travel,Business,2421,1,1,5,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +28405,99742,Female,Loyal Customer,51,Business travel,Eco,255,3,3,3,3,5,2,3,3,3,3,3,4,3,2,10,10.0,neutral or dissatisfied +28406,69426,Female,Loyal Customer,16,Business travel,Business,3081,3,5,1,1,3,3,3,3,1,2,4,4,4,3,8,0.0,neutral or dissatisfied +28407,53594,Female,disloyal Customer,42,Business travel,Eco,802,1,1,1,3,1,5,5,1,3,4,2,5,5,5,0,17.0,neutral or dissatisfied +28408,53931,Female,Loyal Customer,57,Business travel,Eco Plus,140,3,5,5,5,2,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +28409,42900,Male,Loyal Customer,36,Business travel,Business,3810,0,4,0,3,1,5,3,2,2,2,2,2,2,1,0,0.0,satisfied +28410,89747,Female,disloyal Customer,56,Personal Travel,Eco,1047,3,4,3,4,2,3,2,2,3,3,4,4,4,2,42,27.0,neutral or dissatisfied +28411,120518,Female,Loyal Customer,68,Business travel,Business,3623,4,5,4,5,2,3,4,3,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +28412,70707,Female,Loyal Customer,22,Business travel,Business,3422,5,5,5,5,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +28413,84614,Female,Loyal Customer,43,Business travel,Business,669,3,4,4,4,4,3,2,3,3,3,3,3,3,3,52,56.0,neutral or dissatisfied +28414,102730,Female,Loyal Customer,26,Personal Travel,Eco,601,2,4,3,2,3,3,3,3,4,3,3,3,5,3,0,0.0,neutral or dissatisfied +28415,107509,Male,Loyal Customer,20,Personal Travel,Eco,711,2,4,2,3,4,2,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +28416,80431,Male,Loyal Customer,43,Business travel,Eco,748,5,2,2,2,5,5,5,5,4,1,4,5,2,5,0,0.0,satisfied +28417,22106,Male,Loyal Customer,40,Business travel,Eco,694,4,5,5,5,4,4,4,4,3,4,2,1,2,4,0,0.0,satisfied +28418,112888,Female,Loyal Customer,32,Business travel,Business,1812,2,3,3,3,2,2,2,2,1,4,3,3,4,2,78,75.0,neutral or dissatisfied +28419,87656,Male,Loyal Customer,8,Business travel,Business,606,2,2,2,2,2,2,2,2,4,2,2,2,2,2,4,0.0,neutral or dissatisfied +28420,117915,Female,Loyal Customer,51,Business travel,Eco,365,3,4,3,4,2,3,4,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +28421,103022,Female,Loyal Customer,48,Business travel,Business,460,2,2,2,2,3,5,5,4,4,4,4,3,4,4,19,2.0,satisfied +28422,46108,Male,Loyal Customer,25,Business travel,Business,2421,1,1,1,1,5,4,5,5,2,3,2,4,2,5,13,17.0,satisfied +28423,104763,Female,Loyal Customer,20,Personal Travel,Eco,1342,4,5,4,3,5,4,5,5,3,3,5,4,4,5,7,0.0,satisfied +28424,34824,Female,Loyal Customer,21,Personal Travel,Eco,301,3,4,4,4,2,4,4,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +28425,44510,Male,disloyal Customer,24,Business travel,Business,157,0,3,0,1,5,3,5,5,4,2,5,5,4,5,14,44.0,satisfied +28426,70226,Male,disloyal Customer,19,Business travel,Eco,1068,4,3,3,2,3,3,3,3,1,1,5,2,1,3,0,0.0,satisfied +28427,80865,Female,Loyal Customer,55,Personal Travel,Eco,484,1,4,1,1,5,5,5,2,2,1,2,5,2,3,1,44.0,neutral or dissatisfied +28428,22856,Female,disloyal Customer,24,Personal Travel,Eco,151,4,5,4,2,2,4,2,2,4,5,5,5,4,2,0,0.0,satisfied +28429,94723,Female,disloyal Customer,40,Business travel,Business,189,2,1,1,4,2,1,2,2,2,2,4,1,4,2,0,1.0,neutral or dissatisfied +28430,41916,Male,disloyal Customer,40,Business travel,Eco,129,4,0,3,4,1,3,1,1,1,3,1,2,5,1,0,3.0,neutral or dissatisfied +28431,6946,Male,Loyal Customer,59,Business travel,Business,588,4,4,4,4,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +28432,47027,Male,Loyal Customer,51,Business travel,Eco,639,3,3,3,3,2,3,2,2,4,4,1,2,3,2,0,0.0,satisfied +28433,45809,Male,Loyal Customer,55,Business travel,Eco,391,5,1,4,1,5,5,5,5,1,3,4,2,5,5,0,0.0,satisfied +28434,118788,Female,Loyal Customer,62,Personal Travel,Eco,370,3,4,3,4,1,3,4,1,1,3,1,3,1,1,15,10.0,neutral or dissatisfied +28435,19545,Female,Loyal Customer,34,Business travel,Business,3032,1,1,1,1,4,5,4,3,5,2,1,4,5,4,117,149.0,satisfied +28436,52835,Female,Loyal Customer,21,Business travel,Eco,1721,2,5,5,5,2,2,4,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +28437,3365,Female,Loyal Customer,58,Business travel,Business,3760,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +28438,10153,Male,Loyal Customer,64,Personal Travel,Eco,1201,2,1,2,2,4,2,4,4,3,4,2,1,2,4,19,18.0,neutral or dissatisfied +28439,240,Female,Loyal Customer,49,Business travel,Business,3477,5,5,5,5,2,5,5,5,5,5,5,3,5,5,7,26.0,satisfied +28440,77842,Female,Loyal Customer,28,Business travel,Business,1698,3,3,3,3,1,2,1,1,4,3,4,4,4,1,2,0.0,satisfied +28441,127248,Male,Loyal Customer,57,Business travel,Business,1107,3,3,3,3,3,4,4,5,5,4,5,3,5,4,1,0.0,satisfied +28442,35117,Male,Loyal Customer,33,Business travel,Business,1971,3,3,3,3,5,5,5,4,3,2,2,5,3,5,465,493.0,satisfied +28443,55522,Female,Loyal Customer,13,Personal Travel,Eco,991,1,4,1,4,3,1,3,3,5,2,4,5,5,3,1,0.0,neutral or dissatisfied +28444,113224,Male,disloyal Customer,42,Business travel,Business,414,1,1,1,3,4,1,4,4,1,3,4,4,4,4,12,14.0,neutral or dissatisfied +28445,112376,Male,Loyal Customer,50,Business travel,Business,2568,4,4,4,4,2,4,4,4,4,4,4,4,4,5,24,12.0,satisfied +28446,67345,Female,Loyal Customer,64,Personal Travel,Eco,1471,5,4,5,3,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +28447,87855,Female,Loyal Customer,51,Personal Travel,Eco,214,3,0,3,2,4,4,5,1,1,3,1,1,1,3,0,3.0,neutral or dissatisfied +28448,125828,Female,Loyal Customer,50,Business travel,Business,742,1,1,1,1,4,5,5,4,4,4,4,4,4,4,6,3.0,satisfied +28449,9290,Male,Loyal Customer,39,Personal Travel,Eco,1157,3,5,3,3,5,3,2,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +28450,59221,Male,disloyal Customer,16,Business travel,Business,1440,5,4,5,1,5,5,3,5,5,5,4,4,4,5,26,27.0,satisfied +28451,100282,Male,Loyal Customer,60,Business travel,Business,1809,2,2,4,2,3,4,4,2,2,2,2,4,2,4,12,7.0,satisfied +28452,21564,Male,Loyal Customer,30,Business travel,Eco Plus,164,3,5,5,5,3,3,3,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +28453,21599,Male,Loyal Customer,30,Business travel,Business,3448,3,3,4,3,5,5,5,2,5,1,5,5,3,5,219,237.0,satisfied +28454,126842,Female,disloyal Customer,20,Business travel,Eco,716,1,1,1,1,5,1,5,5,2,3,1,3,1,5,2,10.0,neutral or dissatisfied +28455,73824,Female,Loyal Customer,11,Personal Travel,Eco,1194,4,5,4,1,4,4,4,4,5,4,3,5,5,4,2,0.0,satisfied +28456,14413,Male,Loyal Customer,47,Business travel,Business,3268,4,1,4,4,3,5,5,4,4,5,4,1,4,5,37,31.0,satisfied +28457,39563,Female,Loyal Customer,23,Business travel,Business,3639,5,5,4,5,5,5,5,5,5,3,1,4,3,5,0,0.0,satisfied +28458,30054,Female,Loyal Customer,38,Business travel,Business,1927,1,1,1,1,1,1,1,1,4,3,3,1,2,1,167,170.0,neutral or dissatisfied +28459,41931,Male,Loyal Customer,31,Personal Travel,Eco,129,1,0,0,4,4,0,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +28460,82120,Female,disloyal Customer,50,Business travel,Eco Plus,876,1,1,1,3,5,1,5,5,4,4,4,3,3,5,0,10.0,neutral or dissatisfied +28461,102395,Female,Loyal Customer,35,Business travel,Eco,223,3,3,3,3,3,5,3,3,3,2,3,1,3,3,19,16.0,satisfied +28462,48652,Female,Loyal Customer,52,Business travel,Business,1889,1,1,1,1,3,4,4,4,4,4,5,3,4,4,1,12.0,satisfied +28463,97937,Male,Loyal Customer,47,Business travel,Business,2878,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +28464,115760,Male,Loyal Customer,71,Business travel,Eco,325,3,1,1,1,4,3,4,4,2,5,3,2,4,4,0,0.0,neutral or dissatisfied +28465,7597,Female,Loyal Customer,54,Business travel,Business,825,5,5,4,5,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +28466,94379,Male,disloyal Customer,24,Business travel,Eco,239,3,2,3,3,3,3,3,3,3,1,4,1,4,3,0,0.0,neutral or dissatisfied +28467,116673,Female,Loyal Customer,41,Business travel,Business,373,4,4,4,4,3,5,4,3,3,4,3,4,3,4,5,0.0,satisfied +28468,17558,Female,Loyal Customer,28,Business travel,Eco,1034,4,5,5,5,4,4,4,4,1,5,1,3,1,4,10,0.0,satisfied +28469,60866,Male,disloyal Customer,18,Business travel,Eco,1491,4,4,4,1,2,4,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +28470,63758,Female,disloyal Customer,26,Business travel,Eco,2422,3,4,4,3,1,3,1,1,4,4,3,1,3,1,0,1.0,neutral or dissatisfied +28471,129300,Female,Loyal Customer,50,Business travel,Business,2475,3,3,3,3,5,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +28472,58930,Male,Loyal Customer,41,Personal Travel,Eco,1081,1,5,1,5,1,4,4,1,2,4,4,4,5,4,150,171.0,neutral or dissatisfied +28473,82489,Male,Loyal Customer,47,Business travel,Business,488,2,4,4,4,2,3,3,2,2,2,2,2,2,2,17,4.0,neutral or dissatisfied +28474,103624,Female,Loyal Customer,38,Business travel,Eco,251,3,4,4,4,3,3,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +28475,49392,Male,Loyal Customer,39,Business travel,Eco,209,5,3,3,3,5,5,5,5,3,3,3,3,4,5,0,0.0,satisfied +28476,9312,Female,disloyal Customer,22,Business travel,Eco,542,2,2,2,4,5,2,5,5,4,4,4,4,4,5,0,1.0,neutral or dissatisfied +28477,6459,Female,Loyal Customer,50,Business travel,Business,3128,2,5,2,2,2,5,5,5,5,5,5,3,5,4,3,0.0,satisfied +28478,128971,Female,Loyal Customer,44,Personal Travel,Eco,414,2,4,2,1,1,4,2,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +28479,23063,Male,disloyal Customer,24,Business travel,Eco,820,4,4,4,4,4,4,4,4,5,3,3,4,4,4,0,0.0,neutral or dissatisfied +28480,108739,Female,Loyal Customer,52,Business travel,Business,515,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +28481,39341,Male,Loyal Customer,63,Business travel,Eco,374,4,2,2,2,4,4,4,4,4,1,1,1,2,4,0,0.0,satisfied +28482,11777,Female,Loyal Customer,45,Personal Travel,Eco,429,2,1,2,2,2,2,2,5,5,2,5,4,5,2,21,7.0,neutral or dissatisfied +28483,63286,Male,Loyal Customer,27,Business travel,Business,3127,2,4,5,4,2,2,2,4,3,2,3,2,4,2,131,122.0,neutral or dissatisfied +28484,95888,Male,Loyal Customer,52,Personal Travel,Eco,759,2,4,3,4,3,3,3,3,4,4,5,5,4,3,83,79.0,neutral or dissatisfied +28485,36045,Female,Loyal Customer,37,Business travel,Eco,399,2,1,1,1,2,3,2,2,5,1,2,5,3,2,0,0.0,satisfied +28486,54464,Female,disloyal Customer,38,Business travel,Eco,925,3,3,3,4,2,3,4,2,1,1,4,1,5,2,56,42.0,neutral or dissatisfied +28487,47070,Male,Loyal Customer,34,Personal Travel,Eco,639,2,5,1,1,5,1,5,5,3,5,5,4,5,5,7,5.0,neutral or dissatisfied +28488,3904,Female,Loyal Customer,46,Personal Travel,Eco,213,3,4,3,3,4,5,5,2,2,3,3,5,2,5,0,0.0,neutral or dissatisfied +28489,39599,Male,Loyal Customer,42,Personal Travel,Eco,954,3,4,2,3,3,2,3,3,3,1,1,1,5,3,3,12.0,neutral or dissatisfied +28490,14697,Female,Loyal Customer,41,Business travel,Business,419,3,5,3,3,1,4,1,4,4,4,4,2,4,2,0,0.0,satisfied +28491,24824,Male,Loyal Customer,21,Business travel,Business,861,3,3,3,3,5,5,5,5,4,1,3,3,5,5,0,0.0,satisfied +28492,52091,Male,disloyal Customer,50,Business travel,Eco,202,3,1,3,3,1,3,1,1,4,5,3,3,3,1,30,45.0,neutral or dissatisfied +28493,9006,Male,Loyal Customer,58,Personal Travel,Eco,287,2,5,2,1,2,2,2,2,3,5,4,3,5,2,0,11.0,neutral or dissatisfied +28494,48017,Female,Loyal Customer,68,Personal Travel,Eco Plus,748,5,4,5,3,3,5,4,3,3,5,3,4,3,5,0,,satisfied +28495,100127,Female,Loyal Customer,15,Business travel,Business,3709,5,5,5,5,5,5,5,5,4,3,4,5,5,5,0,22.0,satisfied +28496,38350,Male,disloyal Customer,46,Business travel,Eco,1050,2,2,2,3,3,2,3,3,1,5,4,3,4,3,43,28.0,neutral or dissatisfied +28497,101485,Female,Loyal Customer,44,Business travel,Business,345,3,3,3,3,3,3,4,3,3,3,3,2,3,2,15,3.0,neutral or dissatisfied +28498,122796,Male,Loyal Customer,25,Business travel,Business,599,2,2,3,3,2,2,2,2,3,4,4,1,3,2,0,28.0,neutral or dissatisfied +28499,105686,Male,Loyal Customer,54,Business travel,Business,1671,5,5,5,5,3,5,4,5,5,5,5,3,5,3,12,7.0,satisfied +28500,80871,Male,Loyal Customer,22,Personal Travel,Eco,484,2,0,4,3,3,4,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +28501,33512,Male,Loyal Customer,18,Personal Travel,Eco Plus,965,5,5,4,1,4,4,1,4,3,5,5,4,5,4,15,1.0,satisfied +28502,3372,Male,Loyal Customer,40,Business travel,Eco,240,2,5,5,5,2,2,2,2,1,4,3,3,4,2,0,8.0,neutral or dissatisfied +28503,71569,Male,Loyal Customer,52,Business travel,Eco,1182,4,3,3,3,4,4,4,4,2,5,3,3,3,4,0,19.0,neutral or dissatisfied +28504,71152,Male,Loyal Customer,44,Business travel,Business,2602,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +28505,112154,Female,Loyal Customer,48,Business travel,Business,3745,3,1,2,2,2,4,4,3,3,3,3,2,3,3,60,47.0,neutral or dissatisfied +28506,50279,Female,Loyal Customer,69,Business travel,Eco,109,4,4,4,4,1,3,4,4,4,4,4,3,4,2,14,36.0,neutral or dissatisfied +28507,15780,Female,Loyal Customer,31,Personal Travel,Eco,254,5,3,5,1,1,5,1,1,4,1,3,4,3,1,0,0.0,satisfied +28508,7121,Female,Loyal Customer,33,Personal Travel,Eco Plus,273,2,4,2,2,3,2,3,3,4,2,1,4,1,3,0,6.0,neutral or dissatisfied +28509,126502,Female,Loyal Customer,41,Personal Travel,Eco,1849,3,3,3,3,2,3,2,2,3,5,1,2,5,2,5,0.0,neutral or dissatisfied +28510,74499,Female,disloyal Customer,26,Business travel,Eco,1313,2,3,3,3,4,2,1,4,3,2,3,4,4,4,0,0.0,neutral or dissatisfied +28511,112548,Female,Loyal Customer,49,Business travel,Eco Plus,850,2,1,1,1,5,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +28512,50534,Female,Loyal Customer,59,Personal Travel,Eco,156,3,4,3,3,3,4,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +28513,6378,Male,Loyal Customer,55,Business travel,Business,3375,2,1,1,1,2,2,2,4,4,3,2,4,4,1,11,8.0,neutral or dissatisfied +28514,41692,Female,Loyal Customer,12,Personal Travel,Eco,347,1,4,1,3,1,1,5,1,4,1,2,3,4,1,0,0.0,neutral or dissatisfied +28515,5381,Female,Loyal Customer,49,Personal Travel,Eco,785,5,5,5,5,3,5,4,1,1,5,1,4,1,5,6,13.0,satisfied +28516,28178,Male,Loyal Customer,64,Personal Travel,Eco,933,2,4,2,2,1,2,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +28517,75230,Female,Loyal Customer,53,Personal Travel,Eco,1744,5,4,5,4,4,4,5,5,5,5,5,3,5,5,18,31.0,satisfied +28518,41795,Male,Loyal Customer,42,Business travel,Eco,257,5,3,3,3,5,5,5,5,2,3,3,2,2,5,0,0.0,satisfied +28519,79255,Male,disloyal Customer,63,Business travel,Eco,998,2,2,2,3,2,2,2,2,1,5,3,3,3,2,22,0.0,neutral or dissatisfied +28520,42553,Female,Loyal Customer,33,Personal Travel,Eco,1174,4,5,4,1,1,4,1,1,3,3,5,5,5,1,0,32.0,neutral or dissatisfied +28521,25655,Female,Loyal Customer,59,Business travel,Business,761,4,4,4,4,4,4,5,5,5,5,5,3,5,3,22,15.0,satisfied +28522,49102,Male,Loyal Customer,39,Business travel,Eco,110,4,2,2,2,4,4,4,4,4,5,1,4,1,4,22,18.0,satisfied +28523,11852,Male,disloyal Customer,17,Business travel,Eco,912,4,4,4,4,4,2,2,3,2,3,4,2,4,2,139,117.0,neutral or dissatisfied +28524,33043,Male,Loyal Customer,66,Personal Travel,Eco,216,2,3,2,1,3,2,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +28525,68057,Female,Loyal Customer,44,Business travel,Business,2588,3,3,3,3,2,5,5,5,5,5,5,4,5,3,0,7.0,satisfied +28526,54361,Male,Loyal Customer,26,Personal Travel,Eco,1235,4,4,4,1,5,4,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +28527,29039,Male,Loyal Customer,38,Personal Travel,Eco,987,2,4,2,1,4,2,4,4,2,3,3,2,1,4,0,0.0,neutral or dissatisfied +28528,22919,Female,Loyal Customer,65,Personal Travel,Eco,630,4,1,5,4,5,3,4,3,3,5,1,3,3,3,0,0.0,neutral or dissatisfied +28529,54861,Male,disloyal Customer,47,Business travel,Eco,862,3,3,3,3,3,3,3,3,4,4,2,4,2,3,0,0.0,neutral or dissatisfied +28530,126437,Male,Loyal Customer,27,Personal Travel,Eco Plus,631,2,5,2,2,5,2,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +28531,43028,Female,Loyal Customer,53,Business travel,Eco,391,4,2,2,2,2,3,5,3,3,4,3,5,3,1,0,0.0,satisfied +28532,18820,Male,Loyal Customer,61,Business travel,Eco,503,3,2,2,2,3,3,3,3,5,1,3,2,3,3,0,4.0,satisfied +28533,8692,Female,disloyal Customer,23,Business travel,Eco,280,2,0,2,1,1,2,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +28534,14169,Female,Loyal Customer,42,Business travel,Business,526,1,1,1,1,3,4,1,5,5,5,5,3,5,1,0,15.0,satisfied +28535,67034,Male,Loyal Customer,48,Business travel,Business,2928,1,1,2,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +28536,72103,Female,disloyal Customer,28,Business travel,Business,2504,1,2,2,3,4,2,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +28537,77539,Male,Loyal Customer,51,Business travel,Business,2199,1,1,1,1,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +28538,125099,Female,Loyal Customer,72,Business travel,Business,361,3,3,3,3,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +28539,101419,Female,Loyal Customer,8,Personal Travel,Eco Plus,486,2,5,5,5,3,5,3,3,4,4,4,5,4,3,19,1.0,neutral or dissatisfied +28540,34356,Male,disloyal Customer,29,Business travel,Eco,541,4,4,4,4,5,4,2,5,3,3,4,4,4,5,14,31.0,neutral or dissatisfied +28541,84615,Female,disloyal Customer,25,Business travel,Business,669,0,4,0,2,4,0,4,4,4,4,5,5,5,4,0,0.0,satisfied +28542,128629,Female,disloyal Customer,17,Business travel,Eco,954,4,4,4,4,1,4,1,1,2,4,2,1,4,1,1,0.0,neutral or dissatisfied +28543,77490,Male,Loyal Customer,31,Business travel,Business,1558,5,5,5,5,5,5,5,5,5,2,4,4,5,5,1,0.0,satisfied +28544,16231,Male,Loyal Customer,58,Personal Travel,Eco,266,1,2,1,4,1,1,1,1,1,3,3,2,4,1,65,53.0,neutral or dissatisfied +28545,124980,Male,Loyal Customer,54,Business travel,Business,184,1,1,1,1,3,5,4,3,3,4,5,4,3,5,7,0.0,satisfied +28546,73421,Male,Loyal Customer,35,Business travel,Eco,1144,1,1,1,1,1,1,1,1,3,4,4,2,3,1,0,15.0,neutral or dissatisfied +28547,30539,Female,Loyal Customer,25,Personal Travel,Eco,701,2,4,2,3,4,2,2,4,5,4,4,3,5,4,63,71.0,neutral or dissatisfied +28548,58701,Female,Loyal Customer,45,Business travel,Business,4243,1,1,1,1,4,4,4,5,5,4,4,4,5,4,103,111.0,satisfied +28549,98647,Female,Loyal Customer,60,Business travel,Eco,551,4,3,3,3,5,5,4,4,4,4,4,3,4,1,65,47.0,satisfied +28550,95373,Male,Loyal Customer,58,Personal Travel,Eco,458,3,3,3,4,5,3,1,5,4,2,2,5,2,5,0,0.0,neutral or dissatisfied +28551,90218,Female,Loyal Customer,15,Personal Travel,Eco,1086,1,4,1,4,1,1,1,1,3,2,5,5,5,1,3,4.0,neutral or dissatisfied +28552,109101,Male,Loyal Customer,43,Personal Travel,Eco,994,1,5,1,4,5,1,4,5,5,5,5,4,4,5,52,40.0,neutral or dissatisfied +28553,123975,Female,Loyal Customer,41,Business travel,Business,1555,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,21.0,satisfied +28554,87688,Female,Loyal Customer,57,Personal Travel,Eco,606,3,1,3,4,4,4,4,5,5,3,3,4,5,2,9,0.0,neutral or dissatisfied +28555,91600,Female,disloyal Customer,27,Business travel,Business,1199,2,2,2,3,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +28556,46770,Male,Loyal Customer,40,Personal Travel,Eco Plus,196,3,5,3,1,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +28557,15359,Female,Loyal Customer,35,Business travel,Business,2449,5,5,5,5,3,3,3,5,1,2,5,3,2,3,139,113.0,satisfied +28558,5705,Male,Loyal Customer,39,Personal Travel,Eco,299,1,4,1,4,5,1,2,5,5,2,5,5,5,5,55,42.0,neutral or dissatisfied +28559,79291,Male,Loyal Customer,45,Business travel,Business,2248,1,1,1,1,5,5,5,4,4,3,4,5,5,5,223,237.0,satisfied +28560,73578,Female,disloyal Customer,24,Business travel,Business,192,4,0,4,4,5,4,5,5,3,3,5,3,5,5,0,0.0,satisfied +28561,97139,Female,Loyal Customer,14,Business travel,Eco,1476,2,4,4,4,2,2,3,2,4,5,4,1,3,2,5,7.0,neutral or dissatisfied +28562,7953,Female,disloyal Customer,22,Business travel,Eco,594,2,0,2,2,4,2,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +28563,71915,Male,Loyal Customer,56,Personal Travel,Eco,1723,2,4,2,2,1,2,1,1,3,2,3,4,4,1,4,0.0,neutral or dissatisfied +28564,5916,Male,Loyal Customer,40,Personal Travel,Eco,173,3,3,3,1,2,3,2,2,4,1,4,3,3,2,4,0.0,neutral or dissatisfied +28565,99641,Female,Loyal Customer,19,Personal Travel,Business,1670,3,3,3,4,3,3,3,3,3,5,3,2,4,3,42,7.0,neutral or dissatisfied +28566,103878,Male,Loyal Customer,69,Personal Travel,Eco,979,1,4,1,1,5,1,3,5,5,5,4,3,5,5,20,18.0,neutral or dissatisfied +28567,124498,Female,Loyal Customer,12,Business travel,Eco,930,2,1,1,1,2,3,1,2,4,3,3,3,3,2,14,10.0,neutral or dissatisfied +28568,42704,Female,Loyal Customer,26,Personal Travel,Eco,604,2,5,2,5,2,2,5,3,5,4,5,5,4,5,426,427.0,neutral or dissatisfied +28569,128781,Female,Loyal Customer,63,Business travel,Business,2248,3,5,4,5,3,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +28570,47903,Female,Loyal Customer,35,Business travel,Business,3416,1,1,1,1,3,1,1,4,4,4,4,5,4,4,0,0.0,satisfied +28571,51660,Male,Loyal Customer,41,Business travel,Business,1520,3,5,2,2,3,4,3,3,3,3,3,1,3,2,77,70.0,neutral or dissatisfied +28572,18850,Female,disloyal Customer,43,Business travel,Eco,551,2,3,2,2,4,2,5,4,4,2,1,2,5,4,0,0.0,neutral or dissatisfied +28573,82738,Female,Loyal Customer,54,Business travel,Business,409,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +28574,104821,Female,Loyal Customer,50,Business travel,Business,1617,2,2,2,2,4,5,4,5,5,5,5,4,5,4,6,14.0,satisfied +28575,98270,Male,Loyal Customer,61,Business travel,Business,3305,3,5,5,5,5,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +28576,58019,Male,Loyal Customer,45,Business travel,Eco,1721,2,3,3,3,2,2,2,2,3,4,1,3,3,2,0,0.0,neutral or dissatisfied +28577,51210,Female,disloyal Customer,33,Business travel,Eco Plus,77,3,3,3,5,5,3,5,5,2,4,3,2,2,5,0,0.0,neutral or dissatisfied +28578,72529,Male,disloyal Customer,26,Business travel,Eco,1017,3,2,2,4,5,2,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +28579,106159,Female,Loyal Customer,10,Personal Travel,Eco,436,4,5,4,3,4,4,4,4,5,2,5,5,4,4,31,26.0,neutral or dissatisfied +28580,63990,Male,disloyal Customer,40,Business travel,Business,612,5,4,4,4,2,4,2,2,4,5,5,4,5,2,0,0.0,satisfied +28581,85700,Male,Loyal Customer,37,Business travel,Business,3425,3,3,3,3,1,2,5,4,4,4,4,1,4,2,8,0.0,satisfied +28582,28640,Female,disloyal Customer,55,Business travel,Eco,2355,2,2,2,4,2,2,2,2,2,4,3,2,4,2,0,0.0,neutral or dissatisfied +28583,123786,Male,Loyal Customer,56,Business travel,Business,2921,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +28584,4935,Male,Loyal Customer,39,Business travel,Business,334,5,5,3,5,3,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +28585,96095,Male,Loyal Customer,27,Personal Travel,Eco,758,1,4,1,5,4,1,4,4,3,2,5,3,5,4,1,1.0,neutral or dissatisfied +28586,120853,Female,Loyal Customer,63,Personal Travel,Business,992,1,4,1,3,3,5,4,5,5,1,5,3,5,3,99,71.0,neutral or dissatisfied +28587,39913,Female,Loyal Customer,50,Business travel,Business,1087,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +28588,54337,Male,Loyal Customer,21,Personal Travel,Eco,1597,3,2,3,4,3,3,1,3,4,3,4,4,3,3,3,0.0,neutral or dissatisfied +28589,86299,Female,Loyal Customer,61,Personal Travel,Eco,306,2,4,2,5,3,5,5,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +28590,116185,Female,Loyal Customer,64,Personal Travel,Eco,404,3,5,3,4,5,2,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +28591,82625,Male,Loyal Customer,54,Personal Travel,Eco,528,2,3,2,4,3,2,3,3,2,4,4,1,3,3,27,35.0,neutral or dissatisfied +28592,109322,Male,Loyal Customer,39,Personal Travel,Eco,1072,1,5,2,3,3,2,3,3,3,4,4,3,5,3,24,25.0,neutral or dissatisfied +28593,19925,Male,Loyal Customer,57,Business travel,Business,315,0,0,0,1,2,2,1,5,5,5,5,2,5,2,73,65.0,satisfied +28594,35866,Male,Loyal Customer,35,Personal Travel,Eco,1065,1,3,1,4,2,1,2,2,2,2,3,4,4,2,6,0.0,neutral or dissatisfied +28595,81194,Male,Loyal Customer,29,Personal Travel,Eco Plus,980,4,5,4,3,1,4,1,1,5,5,4,5,4,1,0,0.0,satisfied +28596,13657,Male,disloyal Customer,23,Business travel,Eco,462,5,0,5,1,3,5,3,3,2,4,5,4,2,3,30,16.0,satisfied +28597,122647,Male,disloyal Customer,38,Business travel,Business,361,5,5,5,1,2,5,1,2,3,3,5,5,5,2,28,10.0,satisfied +28598,21873,Female,disloyal Customer,37,Business travel,Eco,448,3,5,3,2,4,3,1,4,3,1,1,2,3,4,31,25.0,neutral or dissatisfied +28599,96703,Female,Loyal Customer,38,Business travel,Eco,696,4,3,4,3,4,4,4,4,2,3,4,1,4,4,6,16.0,neutral or dissatisfied +28600,18220,Female,Loyal Customer,53,Business travel,Business,3137,4,4,4,4,4,5,1,4,4,4,4,2,4,5,0,0.0,satisfied +28601,64795,Male,disloyal Customer,44,Business travel,Business,190,5,5,5,2,3,5,3,3,3,3,4,4,5,3,0,0.0,satisfied +28602,20766,Female,Loyal Customer,44,Personal Travel,Business,508,3,4,3,3,5,4,5,2,2,3,5,4,2,5,25,12.0,neutral or dissatisfied +28603,57609,Female,Loyal Customer,47,Business travel,Business,200,3,5,5,5,4,3,4,2,2,2,3,2,2,4,0,0.0,neutral or dissatisfied +28604,41871,Female,Loyal Customer,59,Business travel,Eco Plus,483,5,4,4,4,1,5,2,5,5,5,5,1,5,4,0,4.0,satisfied +28605,10119,Female,Loyal Customer,53,Personal Travel,Eco,984,2,4,2,3,5,3,3,5,5,2,5,4,5,3,1,0.0,neutral or dissatisfied +28606,5794,Female,disloyal Customer,36,Business travel,Business,273,2,1,1,4,5,1,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +28607,57028,Male,Loyal Customer,33,Business travel,Business,2454,2,2,2,2,4,4,4,5,5,4,4,4,5,4,0,0.0,satisfied +28608,97511,Male,Loyal Customer,42,Personal Travel,Eco Plus,822,4,4,4,2,1,4,2,1,3,4,5,4,5,1,66,51.0,neutral or dissatisfied +28609,51028,Female,Loyal Customer,37,Personal Travel,Eco,262,4,3,0,3,3,0,3,3,1,1,4,1,4,3,0,3.0,neutral or dissatisfied +28610,123250,Male,Loyal Customer,18,Personal Travel,Eco,631,2,3,2,3,4,2,4,4,3,4,3,1,3,4,52,46.0,neutral or dissatisfied +28611,123270,Male,Loyal Customer,50,Personal Travel,Eco,507,1,4,1,4,4,1,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +28612,115481,Female,Loyal Customer,37,Business travel,Eco,325,2,2,2,2,2,2,2,2,2,4,3,4,4,2,0,0.0,neutral or dissatisfied +28613,26997,Female,Loyal Customer,41,Business travel,Business,2960,2,4,4,4,2,3,2,2,2,2,2,2,2,4,0,3.0,neutral or dissatisfied +28614,102166,Female,Loyal Customer,60,Business travel,Business,3679,1,1,1,1,3,5,4,4,4,4,4,3,4,4,9,2.0,satisfied +28615,56276,Female,Loyal Customer,33,Business travel,Business,2227,2,2,5,2,5,5,5,4,5,4,4,5,4,5,7,6.0,satisfied +28616,18725,Female,Loyal Customer,37,Personal Travel,Eco Plus,192,0,4,0,4,3,0,3,3,5,3,5,4,4,3,0,0.0,satisfied +28617,29607,Female,Loyal Customer,13,Business travel,Business,3397,2,3,3,3,2,2,2,2,1,3,3,1,4,2,17,7.0,neutral or dissatisfied +28618,18113,Female,Loyal Customer,72,Business travel,Business,629,2,2,2,2,3,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +28619,114361,Male,Loyal Customer,27,Business travel,Business,1565,4,4,3,4,5,5,5,5,5,4,5,4,5,5,29,20.0,satisfied +28620,14258,Male,Loyal Customer,55,Business travel,Business,429,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +28621,4033,Female,Loyal Customer,42,Business travel,Business,419,3,3,4,3,1,4,4,2,2,2,2,1,2,1,18,59.0,satisfied +28622,64898,Male,Loyal Customer,22,Business travel,Business,247,1,1,1,1,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +28623,3867,Male,Loyal Customer,37,Personal Travel,Business,213,2,3,2,2,3,3,2,1,1,2,1,2,1,5,128,131.0,neutral or dissatisfied +28624,11457,Female,Loyal Customer,50,Business travel,Eco Plus,201,1,2,2,2,3,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +28625,18255,Female,Loyal Customer,47,Personal Travel,Eco,346,3,5,3,1,5,5,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +28626,17306,Male,disloyal Customer,22,Business travel,Eco,403,4,2,4,3,3,4,3,3,1,1,4,1,4,3,0,14.0,neutral or dissatisfied +28627,46888,Female,Loyal Customer,20,Business travel,Business,3376,4,4,4,4,5,5,5,5,1,4,5,5,2,5,18,16.0,satisfied +28628,15771,Female,Loyal Customer,40,Business travel,Eco,254,3,5,5,5,3,3,3,3,3,4,2,1,3,3,29,32.0,neutral or dissatisfied +28629,7028,Male,Loyal Customer,14,Personal Travel,Eco,299,3,5,3,4,4,3,4,4,4,2,5,3,5,4,1,27.0,neutral or dissatisfied +28630,118752,Female,Loyal Customer,19,Personal Travel,Eco,338,3,2,3,4,3,3,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +28631,11478,Female,Loyal Customer,36,Business travel,Eco Plus,458,4,3,1,3,4,4,4,4,5,4,3,5,4,4,9,13.0,satisfied +28632,128814,Male,Loyal Customer,11,Business travel,Eco,2475,1,2,2,2,1,2,1,4,5,3,4,1,3,1,0,0.0,neutral or dissatisfied +28633,30017,Female,disloyal Customer,58,Business travel,Eco,399,3,2,3,4,5,3,5,5,1,2,3,4,4,5,0,0.0,neutral or dissatisfied +28634,125655,Female,Loyal Customer,58,Business travel,Business,3137,4,4,5,4,3,4,5,5,5,5,5,4,5,3,85,76.0,satisfied +28635,110537,Male,Loyal Customer,70,Business travel,Business,488,1,3,1,1,5,4,5,4,4,4,4,4,4,4,2,17.0,satisfied +28636,4491,Male,disloyal Customer,44,Business travel,Business,435,4,4,4,4,4,4,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +28637,51884,Male,Loyal Customer,58,Business travel,Business,1946,3,3,3,3,5,3,2,4,4,4,4,5,4,4,0,0.0,satisfied +28638,82068,Male,disloyal Customer,48,Business travel,Business,1298,3,3,3,1,2,3,1,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +28639,15426,Female,Loyal Customer,45,Business travel,Business,2241,3,3,3,3,3,3,3,2,1,3,3,3,2,3,141,136.0,neutral or dissatisfied +28640,22826,Female,Loyal Customer,62,Business travel,Eco,147,4,5,5,5,3,3,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +28641,49100,Male,Loyal Customer,58,Business travel,Business,238,5,5,5,5,2,3,2,5,5,5,5,4,5,3,37,30.0,satisfied +28642,29415,Female,Loyal Customer,31,Personal Travel,Eco,2541,3,4,3,3,3,4,1,4,3,4,5,1,5,1,1,0.0,neutral or dissatisfied +28643,55129,Male,Loyal Customer,67,Personal Travel,Eco,1635,2,4,2,1,4,2,4,4,3,5,5,5,5,4,1,0.0,neutral or dissatisfied +28644,61710,Male,Loyal Customer,53,Business travel,Business,1635,2,2,2,2,5,2,3,2,2,2,2,1,2,3,0,16.0,neutral or dissatisfied +28645,25988,Female,Loyal Customer,24,Business travel,Eco,577,4,5,5,5,4,5,4,4,4,4,3,3,3,4,0,0.0,satisfied +28646,94575,Male,Loyal Customer,46,Business travel,Business,2286,3,3,3,3,3,5,4,4,4,4,4,4,4,3,28,11.0,satisfied +28647,22439,Female,Loyal Customer,46,Personal Travel,Eco,143,2,2,2,4,1,4,3,1,1,2,1,1,1,4,0,4.0,neutral or dissatisfied +28648,43360,Male,Loyal Customer,24,Personal Travel,Eco,347,2,5,2,4,2,2,2,2,5,4,4,5,4,2,0,1.0,neutral or dissatisfied +28649,97380,Female,Loyal Customer,25,Personal Travel,Eco,347,1,4,1,2,2,1,2,2,5,5,4,5,5,2,20,13.0,neutral or dissatisfied +28650,121039,Male,Loyal Customer,45,Personal Travel,Eco,993,2,4,2,4,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +28651,36629,Female,disloyal Customer,22,Business travel,Eco,1249,2,2,2,3,4,2,4,4,3,3,3,3,4,4,0,15.0,neutral or dissatisfied +28652,115629,Male,Loyal Customer,57,Business travel,Eco,373,2,2,2,2,2,2,2,2,3,2,3,4,3,2,24,33.0,neutral or dissatisfied +28653,72243,Male,disloyal Customer,22,Business travel,Eco,919,3,3,3,3,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +28654,5282,Female,Loyal Customer,66,Personal Travel,Eco,383,2,5,2,3,4,5,5,5,5,2,3,3,5,3,0,17.0,neutral or dissatisfied +28655,40661,Male,disloyal Customer,24,Business travel,Eco,558,3,0,3,3,1,3,1,1,5,4,4,5,5,1,0,4.0,neutral or dissatisfied +28656,110066,Male,disloyal Customer,14,Business travel,Business,1072,5,0,5,5,5,5,1,5,4,2,4,3,4,5,12,10.0,satisfied +28657,44370,Male,Loyal Customer,21,Personal Travel,Eco,596,3,3,3,3,1,3,1,1,4,3,2,4,3,1,0,0.0,neutral or dissatisfied +28658,96571,Male,Loyal Customer,55,Business travel,Business,333,2,2,2,2,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +28659,71458,Female,Loyal Customer,15,Personal Travel,Eco,867,1,3,1,1,3,1,3,3,2,3,4,2,2,3,0,0.0,neutral or dissatisfied +28660,64736,Male,Loyal Customer,45,Business travel,Business,1590,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +28661,122635,Female,Loyal Customer,50,Business travel,Eco Plus,728,4,5,3,5,1,3,2,4,4,4,4,1,4,3,6,0.0,neutral or dissatisfied +28662,116587,Male,Loyal Customer,49,Business travel,Business,371,2,2,2,2,2,4,4,4,4,4,4,4,4,4,0,3.0,satisfied +28663,19291,Male,Loyal Customer,36,Business travel,Business,2113,2,4,4,4,2,3,4,2,2,2,2,3,2,1,0,15.0,neutral or dissatisfied +28664,1595,Female,Loyal Customer,25,Personal Travel,Eco,140,2,5,2,1,4,2,4,4,4,3,5,5,5,4,41,42.0,neutral or dissatisfied +28665,47538,Male,Loyal Customer,59,Personal Travel,Eco,541,4,5,2,1,2,2,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +28666,54487,Male,Loyal Customer,34,Business travel,Business,3655,1,1,1,1,5,2,2,5,5,5,5,5,5,2,44,61.0,satisfied +28667,9115,Female,Loyal Customer,42,Business travel,Business,2287,4,5,5,5,3,3,2,4,4,4,4,3,4,3,0,10.0,neutral or dissatisfied +28668,59355,Female,Loyal Customer,49,Business travel,Business,2556,2,2,2,2,4,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +28669,39906,Male,disloyal Customer,18,Business travel,Eco,272,2,2,3,4,3,3,3,3,4,1,3,1,4,3,0,3.0,neutral or dissatisfied +28670,19121,Female,Loyal Customer,45,Business travel,Eco,323,4,2,2,2,1,5,2,3,3,4,3,2,3,5,0,0.0,satisfied +28671,24271,Female,Loyal Customer,40,Personal Travel,Eco,147,3,5,3,2,5,3,5,5,5,5,5,4,4,5,65,60.0,neutral or dissatisfied +28672,79353,Male,Loyal Customer,35,Personal Travel,Eco,1020,3,3,2,3,5,2,5,5,2,3,3,4,3,5,31,11.0,neutral or dissatisfied +28673,94333,Female,Loyal Customer,34,Business travel,Business,187,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +28674,80464,Male,Loyal Customer,35,Business travel,Business,1299,3,3,3,3,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +28675,27902,Male,Loyal Customer,29,Personal Travel,Eco,2350,1,3,1,4,1,3,3,3,2,3,4,3,4,3,0,0.0,neutral or dissatisfied +28676,51670,Female,Loyal Customer,30,Business travel,Business,509,3,1,1,1,3,3,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +28677,68569,Male,Loyal Customer,29,Business travel,Business,1616,2,2,2,2,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +28678,1022,Male,disloyal Customer,23,Business travel,Eco,158,2,4,2,3,2,2,2,2,2,4,4,4,4,2,93,102.0,neutral or dissatisfied +28679,83741,Male,Loyal Customer,60,Business travel,Business,3198,5,5,5,5,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +28680,67921,Male,Loyal Customer,50,Personal Travel,Eco,1235,2,4,2,5,4,2,4,4,3,2,3,5,4,4,6,4.0,neutral or dissatisfied +28681,14853,Female,disloyal Customer,20,Business travel,Eco,240,1,5,1,1,1,3,3,3,4,5,1,3,5,3,340,335.0,neutral or dissatisfied +28682,34105,Male,Loyal Customer,24,Business travel,Business,1179,4,3,4,4,2,2,2,2,2,5,5,1,1,2,0,0.0,satisfied +28683,7294,Female,Loyal Customer,40,Personal Travel,Eco,139,1,4,1,3,4,1,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +28684,59226,Male,Loyal Customer,40,Business travel,Business,649,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +28685,115108,Female,Loyal Customer,55,Business travel,Business,342,2,2,2,2,5,4,5,5,5,5,5,3,5,5,36,18.0,satisfied +28686,78184,Male,Loyal Customer,70,Business travel,Business,2813,0,0,0,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +28687,36440,Female,Loyal Customer,59,Personal Travel,Eco,369,3,4,3,3,3,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +28688,12369,Male,disloyal Customer,24,Business travel,Eco,253,5,4,5,3,2,5,2,2,5,3,4,5,5,2,2,0.0,satisfied +28689,98943,Female,Loyal Customer,57,Business travel,Business,1784,4,3,3,3,2,3,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +28690,31716,Female,Loyal Customer,39,Personal Travel,Eco,862,5,4,5,3,3,5,5,3,2,3,4,2,4,3,3,0.0,satisfied +28691,46687,Female,Loyal Customer,68,Personal Travel,Eco,125,2,4,0,2,2,1,5,1,1,0,1,2,1,2,2,6.0,neutral or dissatisfied +28692,81709,Female,Loyal Customer,51,Business travel,Business,3895,1,1,1,1,5,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +28693,97563,Female,disloyal Customer,21,Business travel,Eco,448,3,0,3,4,1,3,1,1,4,4,4,5,4,1,7,2.0,neutral or dissatisfied +28694,126369,Female,Loyal Customer,56,Personal Travel,Eco,507,3,5,3,1,5,5,4,4,4,3,4,5,4,3,3,1.0,neutral or dissatisfied +28695,98277,Male,Loyal Customer,53,Business travel,Business,1200,2,1,1,1,3,3,4,2,2,2,2,3,2,2,0,9.0,neutral or dissatisfied +28696,71054,Female,Loyal Customer,36,Business travel,Business,402,1,1,1,1,2,4,5,4,4,4,4,2,4,4,0,0.0,satisfied +28697,15109,Female,Loyal Customer,33,Business travel,Business,3195,1,1,1,1,2,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +28698,89996,Male,Loyal Customer,52,Business travel,Business,1084,5,5,5,5,5,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +28699,31909,Male,disloyal Customer,32,Business travel,Business,216,2,2,2,1,4,2,4,4,3,2,4,4,4,4,0,6.0,neutral or dissatisfied +28700,49139,Female,Loyal Customer,57,Business travel,Business,110,5,5,5,5,4,3,2,5,5,5,5,5,5,3,1,0.0,satisfied +28701,69867,Male,Loyal Customer,19,Business travel,Business,3634,5,5,2,5,4,4,4,4,5,3,5,3,5,4,3,9.0,satisfied +28702,77756,Male,Loyal Customer,70,Business travel,Business,413,4,4,4,4,4,3,5,5,5,5,5,1,5,5,0,0.0,satisfied +28703,100654,Male,Loyal Customer,41,Business travel,Business,2129,2,2,4,2,4,4,5,4,4,4,4,4,4,5,0,5.0,satisfied +28704,33561,Male,disloyal Customer,47,Business travel,Eco,399,3,4,3,1,4,3,3,4,4,4,1,3,2,4,28,13.0,neutral or dissatisfied +28705,12526,Male,Loyal Customer,43,Business travel,Business,2536,4,4,4,4,2,3,3,4,4,4,4,2,4,5,102,99.0,satisfied +28706,80608,Female,Loyal Customer,28,Business travel,Business,236,3,3,3,3,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +28707,66169,Male,Loyal Customer,52,Business travel,Business,2105,5,5,5,5,5,4,5,5,5,5,5,4,5,3,0,4.0,satisfied +28708,38554,Female,Loyal Customer,40,Personal Travel,Eco,2446,4,5,4,1,5,4,2,5,3,2,3,3,5,5,42,7.0,neutral or dissatisfied +28709,41399,Male,Loyal Customer,32,Business travel,Business,563,1,1,1,1,4,4,4,4,1,3,4,1,1,4,0,0.0,satisfied +28710,110473,Female,Loyal Customer,49,Personal Travel,Eco,787,2,5,2,3,2,5,5,4,4,2,4,5,4,3,88,94.0,neutral or dissatisfied +28711,114034,Male,Loyal Customer,63,Personal Travel,Business,511,0,5,0,4,3,5,5,5,5,0,5,4,5,5,4,3.0,satisfied +28712,23568,Male,Loyal Customer,26,Business travel,Business,1743,2,2,2,2,5,5,5,5,1,5,2,2,5,5,0,4.0,satisfied +28713,78321,Female,Loyal Customer,46,Business travel,Business,1547,1,1,1,1,4,5,5,4,4,4,4,5,4,3,3,6.0,satisfied +28714,106546,Male,disloyal Customer,27,Business travel,Business,727,3,3,3,4,4,3,3,4,5,3,5,3,4,4,17,2.0,neutral or dissatisfied +28715,36379,Female,Loyal Customer,51,Business travel,Eco,200,3,3,3,3,4,4,5,3,3,3,3,2,3,1,0,0.0,satisfied +28716,94032,Male,Loyal Customer,52,Business travel,Business,3482,3,3,2,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +28717,18425,Male,Loyal Customer,17,Personal Travel,Eco,955,3,4,3,3,5,3,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +28718,4739,Male,Loyal Customer,77,Business travel,Business,2506,3,3,3,3,5,1,2,4,4,4,4,1,4,5,0,0.0,satisfied +28719,103423,Female,Loyal Customer,58,Personal Travel,Eco,237,3,4,3,3,2,5,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +28720,124362,Female,Loyal Customer,55,Business travel,Business,3049,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +28721,88082,Female,Loyal Customer,44,Business travel,Business,223,5,5,5,5,4,4,4,3,3,4,4,3,3,4,14,22.0,satisfied +28722,35361,Female,Loyal Customer,42,Business travel,Eco,1041,5,4,4,4,3,4,2,5,5,5,5,1,5,1,0,0.0,satisfied +28723,19526,Female,Loyal Customer,58,Business travel,Business,2280,4,2,2,2,3,4,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +28724,33453,Male,Loyal Customer,21,Personal Travel,Eco,2349,1,2,1,3,1,4,4,4,3,3,2,4,4,4,0,19.0,neutral or dissatisfied +28725,71786,Female,disloyal Customer,35,Business travel,Business,1744,2,2,2,4,4,2,4,4,3,3,4,4,4,4,0,4.0,neutral or dissatisfied +28726,100259,Male,disloyal Customer,24,Business travel,Eco,1033,2,2,2,3,3,2,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +28727,1010,Female,Loyal Customer,53,Business travel,Business,3993,1,1,1,1,5,1,1,5,5,5,4,5,5,5,0,0.0,satisfied +28728,69919,Male,Loyal Customer,52,Personal Travel,Eco,1514,1,4,1,4,2,1,4,2,1,2,4,3,4,2,100,64.0,neutral or dissatisfied +28729,127623,Female,disloyal Customer,36,Business travel,Business,1773,1,1,1,3,3,1,3,3,5,2,3,5,4,3,0,2.0,neutral or dissatisfied +28730,68991,Female,Loyal Customer,46,Business travel,Business,2422,5,5,5,5,4,4,4,4,5,5,5,4,5,4,0,12.0,satisfied +28731,27895,Male,Loyal Customer,51,Business travel,Eco Plus,2329,3,4,4,4,3,3,3,3,4,2,4,2,1,3,0,0.0,satisfied +28732,112661,Male,Loyal Customer,53,Business travel,Business,723,1,1,3,1,2,5,4,4,4,4,4,3,4,3,17,9.0,satisfied +28733,87984,Female,Loyal Customer,40,Business travel,Business,2276,4,4,4,4,2,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +28734,7832,Male,Loyal Customer,63,Personal Travel,Eco,650,4,4,3,4,2,3,2,2,4,4,3,1,4,2,0,0.0,satisfied +28735,79374,Male,disloyal Customer,45,Business travel,Business,502,5,5,5,4,2,5,2,2,5,5,4,4,5,2,0,0.0,satisfied +28736,93908,Male,Loyal Customer,44,Business travel,Business,2234,5,3,5,5,4,5,4,5,5,5,5,3,5,4,37,31.0,satisfied +28737,34535,Female,Loyal Customer,28,Business travel,Eco,636,3,5,5,5,3,3,3,3,4,2,4,4,3,3,15,56.0,neutral or dissatisfied +28738,57704,Female,Loyal Customer,35,Personal Travel,Eco,867,3,4,3,1,4,3,3,4,4,5,4,3,4,4,70,90.0,neutral or dissatisfied +28739,125441,Male,disloyal Customer,27,Business travel,Business,2845,4,4,4,3,1,4,1,1,4,4,2,2,3,1,0,0.0,neutral or dissatisfied +28740,29035,Female,Loyal Customer,7,Personal Travel,Eco,672,4,2,4,4,1,4,1,1,3,2,4,1,4,1,0,0.0,satisfied +28741,35455,Male,Loyal Customer,9,Personal Travel,Eco,1035,2,4,2,3,5,2,5,5,3,3,4,5,4,5,12,0.0,neutral or dissatisfied +28742,17531,Female,Loyal Customer,59,Personal Travel,Eco Plus,341,3,5,3,1,4,4,5,3,3,3,3,5,3,5,115,106.0,neutral or dissatisfied +28743,41187,Male,Loyal Customer,28,Personal Travel,Eco,395,3,4,3,3,5,3,5,5,5,4,5,3,5,5,42,34.0,neutral or dissatisfied +28744,60473,Female,Loyal Customer,57,Business travel,Business,1512,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +28745,78250,Male,Loyal Customer,21,Personal Travel,Business,903,4,5,4,2,3,4,1,3,3,2,4,5,5,3,0,9.0,neutral or dissatisfied +28746,9705,Male,Loyal Customer,12,Personal Travel,Eco,212,2,1,2,3,5,2,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +28747,115439,Female,Loyal Customer,55,Business travel,Business,1576,3,3,3,3,5,5,4,4,4,4,4,3,4,3,3,0.0,satisfied +28748,63403,Female,Loyal Customer,54,Personal Travel,Eco,337,0,4,0,5,3,4,4,5,5,0,5,4,5,4,0,3.0,satisfied +28749,88541,Female,Loyal Customer,46,Personal Travel,Eco,515,3,5,3,5,5,5,4,2,2,3,2,5,2,3,14,20.0,neutral or dissatisfied +28750,103925,Male,disloyal Customer,29,Business travel,Business,770,5,4,4,3,2,4,1,2,5,5,5,3,4,2,10,14.0,satisfied +28751,40563,Male,Loyal Customer,46,Business travel,Eco,216,4,4,5,5,4,4,4,4,5,5,3,2,4,4,0,0.0,satisfied +28752,40619,Male,Loyal Customer,41,Personal Travel,Eco,216,3,2,3,3,3,3,2,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +28753,74340,Female,Loyal Customer,39,Personal Travel,Business,1188,1,4,1,3,3,3,5,2,2,1,2,4,2,5,0,9.0,neutral or dissatisfied +28754,37726,Male,Loyal Customer,28,Personal Travel,Eco,1069,1,5,1,1,3,1,3,3,3,4,4,4,4,3,6,0.0,neutral or dissatisfied +28755,14657,Male,Loyal Customer,52,Personal Travel,Eco,162,2,5,0,1,2,0,2,2,5,5,5,3,4,2,0,13.0,neutral or dissatisfied +28756,32369,Male,Loyal Customer,59,Business travel,Business,2340,5,5,5,5,2,1,4,5,5,5,3,4,5,3,2,3.0,satisfied +28757,86509,Male,Loyal Customer,27,Personal Travel,Eco,762,3,4,2,1,1,2,1,1,4,2,4,4,4,1,51,57.0,neutral or dissatisfied +28758,92562,Female,Loyal Customer,43,Business travel,Business,1947,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +28759,59040,Female,disloyal Customer,29,Business travel,Eco,941,1,1,1,4,3,1,3,3,2,1,2,1,4,3,39,24.0,neutral or dissatisfied +28760,98434,Female,Loyal Customer,56,Personal Travel,Eco,1910,3,5,3,3,3,4,4,3,5,4,5,4,4,4,132,116.0,neutral or dissatisfied +28761,77335,Female,Loyal Customer,49,Business travel,Business,588,2,2,2,2,2,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +28762,63442,Male,Loyal Customer,11,Personal Travel,Eco,337,4,5,2,5,2,2,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +28763,56122,Female,Loyal Customer,56,Business travel,Business,1372,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,12.0,satisfied +28764,113805,Female,Loyal Customer,41,Business travel,Business,414,2,2,2,2,5,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +28765,51975,Male,Loyal Customer,68,Business travel,Eco,443,4,2,5,2,4,4,4,4,2,4,4,5,4,4,0,6.0,satisfied +28766,6573,Female,Loyal Customer,41,Business travel,Business,3423,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +28767,103023,Male,Loyal Customer,54,Business travel,Business,460,5,5,2,5,5,4,5,4,4,4,4,3,4,5,9,0.0,satisfied +28768,74285,Female,Loyal Customer,11,Business travel,Business,2288,4,4,4,4,3,4,3,3,5,5,5,3,5,3,0,0.0,satisfied +28769,110668,Female,Loyal Customer,36,Business travel,Eco,945,3,2,2,2,3,3,3,3,2,2,2,2,3,3,6,13.0,neutral or dissatisfied +28770,114952,Female,disloyal Customer,21,Business travel,Business,296,0,0,0,3,3,0,3,3,3,5,5,3,5,3,40,34.0,satisfied +28771,78635,Female,Loyal Customer,47,Business travel,Business,1953,1,1,1,1,4,4,5,5,5,5,5,4,5,4,14,5.0,satisfied +28772,116271,Male,Loyal Customer,28,Personal Travel,Eco,296,4,4,4,4,3,4,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +28773,104107,Male,Loyal Customer,53,Personal Travel,Eco,297,2,2,2,2,5,2,5,5,3,4,2,2,3,5,2,0.0,neutral or dissatisfied +28774,122701,Male,Loyal Customer,53,Personal Travel,Eco,361,2,4,2,3,2,2,2,2,4,2,4,5,4,2,60,39.0,neutral or dissatisfied +28775,21309,Female,Loyal Customer,12,Personal Travel,Eco,620,3,1,3,4,4,3,4,4,2,1,3,2,3,4,25,18.0,neutral or dissatisfied +28776,97732,Male,Loyal Customer,57,Business travel,Business,587,3,4,4,4,4,4,4,3,3,3,3,4,3,4,60,51.0,neutral or dissatisfied +28777,112421,Female,Loyal Customer,46,Business travel,Eco,957,3,1,1,1,3,4,4,3,3,3,3,4,3,1,16,14.0,neutral or dissatisfied +28778,79631,Male,Loyal Customer,17,Business travel,Eco,762,2,5,5,5,2,2,3,2,4,5,3,4,3,2,5,36.0,neutral or dissatisfied +28779,41588,Female,Loyal Customer,28,Personal Travel,Eco,1211,2,5,2,4,2,2,2,2,3,4,4,3,5,2,13,16.0,neutral or dissatisfied +28780,82141,Male,Loyal Customer,30,Business travel,Business,2901,3,3,3,3,5,5,5,5,5,4,5,3,5,5,0,20.0,satisfied +28781,40507,Female,Loyal Customer,17,Personal Travel,Eco,175,1,4,1,4,1,1,1,1,5,2,4,2,5,1,0,0.0,neutral or dissatisfied +28782,9785,Male,Loyal Customer,9,Personal Travel,Eco,456,3,5,3,4,1,3,1,1,5,4,4,3,1,1,9,0.0,neutral or dissatisfied +28783,36840,Female,disloyal Customer,44,Business travel,Eco,369,2,3,2,1,3,2,3,3,5,4,2,1,2,3,0,0.0,neutral or dissatisfied +28784,62058,Female,Loyal Customer,18,Personal Travel,Eco,2475,2,1,2,4,5,2,5,5,2,3,3,4,4,5,0,0.0,neutral or dissatisfied +28785,96668,Male,Loyal Customer,63,Personal Travel,Eco,937,1,1,1,1,5,1,5,5,1,5,2,1,2,5,25,25.0,neutral or dissatisfied +28786,30462,Female,Loyal Customer,49,Business travel,Eco Plus,991,4,3,3,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +28787,10921,Male,Loyal Customer,52,Business travel,Business,1868,2,2,2,2,3,4,5,3,3,4,5,5,3,4,16,5.0,satisfied +28788,49880,Male,Loyal Customer,53,Business travel,Eco,89,4,4,4,4,4,4,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +28789,64378,Male,Loyal Customer,51,Personal Travel,Eco,1172,1,2,1,3,4,1,4,4,1,2,3,2,3,4,13,2.0,neutral or dissatisfied +28790,109563,Female,Loyal Customer,56,Personal Travel,Eco,834,1,2,1,3,3,3,4,3,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +28791,12868,Male,Loyal Customer,69,Personal Travel,Eco Plus,817,2,4,1,3,1,1,1,1,1,2,4,4,4,1,0,0.0,neutral or dissatisfied +28792,115208,Male,Loyal Customer,50,Business travel,Business,333,5,5,5,5,2,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +28793,126843,Male,Loyal Customer,49,Business travel,Eco,2077,1,4,4,4,1,1,1,1,2,3,3,4,2,1,0,38.0,neutral or dissatisfied +28794,115764,Female,disloyal Customer,36,Business travel,Eco,308,1,3,1,3,5,1,5,5,1,5,3,4,3,5,0,3.0,neutral or dissatisfied +28795,78493,Male,Loyal Customer,59,Business travel,Business,3640,3,3,3,3,2,3,2,3,3,3,3,2,3,1,0,19.0,neutral or dissatisfied +28796,45715,Female,Loyal Customer,45,Business travel,Eco,852,4,5,1,1,1,2,2,4,4,4,4,2,4,2,0,42.0,neutral or dissatisfied +28797,10656,Female,Loyal Customer,37,Business travel,Business,1749,5,5,5,5,4,4,5,5,5,5,4,5,5,4,15,11.0,satisfied +28798,88504,Female,Loyal Customer,61,Business travel,Business,240,1,1,1,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +28799,77460,Female,Loyal Customer,56,Business travel,Eco,507,3,4,3,3,4,4,3,3,3,3,3,4,3,1,1,0.0,neutral or dissatisfied +28800,43836,Female,Loyal Customer,44,Business travel,Business,2879,5,5,5,5,4,3,4,4,4,4,4,5,4,1,0,3.0,satisfied +28801,52303,Male,Loyal Customer,50,Business travel,Eco,451,1,2,2,2,1,1,1,1,2,5,1,3,1,1,0,0.0,neutral or dissatisfied +28802,62786,Male,Loyal Customer,20,Personal Travel,Eco,2399,5,5,5,4,2,5,2,2,3,5,5,3,5,2,14,14.0,satisfied +28803,90142,Male,Loyal Customer,52,Business travel,Business,2277,1,1,1,1,1,4,1,5,5,5,5,4,5,4,12,11.0,satisfied +28804,30785,Female,Loyal Customer,35,Business travel,Business,2978,3,3,3,3,1,4,3,4,4,4,4,5,4,3,0,0.0,satisfied +28805,30527,Female,Loyal Customer,60,Business travel,Eco,532,5,4,4,4,1,5,4,5,5,5,5,5,5,4,0,4.0,satisfied +28806,14222,Male,Loyal Customer,27,Personal Travel,Eco,692,4,5,4,5,5,4,1,5,4,4,4,5,5,5,4,42.0,neutral or dissatisfied +28807,93033,Female,Loyal Customer,41,Business travel,Business,2683,3,3,1,3,5,5,4,4,4,4,4,5,4,4,31,39.0,satisfied +28808,79669,Female,Loyal Customer,36,Personal Travel,Eco,749,4,5,4,3,5,4,5,5,2,3,5,3,3,5,0,8.0,neutral or dissatisfied +28809,43692,Female,Loyal Customer,33,Business travel,Eco,257,5,2,3,2,5,5,5,5,5,5,2,2,1,5,0,0.0,satisfied +28810,123862,Male,Loyal Customer,49,Business travel,Business,2552,3,1,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +28811,68012,Female,Loyal Customer,47,Business travel,Business,3150,2,2,2,2,4,5,5,5,5,5,5,4,5,4,109,109.0,satisfied +28812,79982,Female,Loyal Customer,38,Personal Travel,Eco,950,4,0,4,3,2,4,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +28813,82953,Male,disloyal Customer,25,Business travel,Business,1145,5,0,5,1,2,5,2,2,3,3,5,5,4,2,0,0.0,satisfied +28814,109894,Female,Loyal Customer,54,Business travel,Eco,744,3,1,1,1,2,1,4,3,3,3,3,4,3,4,20,5.0,satisfied +28815,102848,Male,Loyal Customer,27,Business travel,Eco,423,5,3,3,3,5,5,5,5,1,1,2,3,2,5,0,0.0,satisfied +28816,7981,Female,Loyal Customer,46,Business travel,Business,402,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +28817,114057,Male,disloyal Customer,31,Business travel,Business,1892,3,4,4,1,3,4,2,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +28818,82276,Male,Loyal Customer,72,Business travel,Business,1481,2,4,1,4,3,3,4,2,2,2,2,3,2,1,85,61.0,neutral or dissatisfied +28819,94687,Female,Loyal Customer,51,Business travel,Business,2962,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +28820,77171,Female,Loyal Customer,47,Business travel,Business,1355,1,1,1,1,4,5,5,4,4,4,4,4,4,4,20,39.0,satisfied +28821,65940,Male,Loyal Customer,56,Business travel,Eco Plus,569,2,2,3,2,2,2,2,2,3,4,4,1,4,2,14,34.0,neutral or dissatisfied +28822,126132,Male,Loyal Customer,53,Business travel,Business,2256,5,5,5,5,4,4,4,4,4,4,4,3,4,3,0,1.0,satisfied +28823,124041,Female,disloyal Customer,38,Business travel,Business,184,4,4,4,2,4,4,3,4,3,5,5,4,5,4,0,0.0,satisfied +28824,129429,Female,disloyal Customer,46,Business travel,Eco,414,1,4,1,3,2,1,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +28825,63357,Female,Loyal Customer,21,Personal Travel,Eco,372,3,4,3,4,1,3,1,1,3,2,5,2,5,1,40,23.0,neutral or dissatisfied +28826,122694,Female,Loyal Customer,56,Personal Travel,Eco,361,2,5,2,3,4,5,4,1,1,2,1,5,1,3,0,3.0,neutral or dissatisfied +28827,79124,Male,Loyal Customer,52,Personal Travel,Eco,356,2,5,2,4,1,2,1,1,3,5,5,4,5,1,8,7.0,neutral or dissatisfied +28828,16936,Female,Loyal Customer,59,Business travel,Business,3127,3,3,3,3,3,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +28829,77491,Female,Loyal Customer,25,Business travel,Business,1717,4,4,3,4,3,3,3,3,3,2,5,4,5,3,0,0.0,satisfied +28830,14094,Female,Loyal Customer,33,Business travel,Business,1920,4,4,4,4,3,5,5,5,5,5,5,1,5,3,95,99.0,satisfied +28831,31043,Female,disloyal Customer,44,Business travel,Eco,775,3,2,2,1,1,2,4,1,1,1,5,3,4,1,0,0.0,neutral or dissatisfied +28832,7619,Male,Loyal Customer,77,Business travel,Eco Plus,802,2,2,2,2,3,2,3,3,3,2,2,1,2,3,0,0.0,neutral or dissatisfied +28833,78548,Female,Loyal Customer,12,Personal Travel,Eco,526,2,4,2,1,1,2,1,1,5,4,5,3,5,1,10,0.0,neutral or dissatisfied +28834,5153,Female,Loyal Customer,24,Personal Travel,Eco,622,2,4,2,4,3,2,3,3,4,2,5,4,5,3,1,2.0,neutral or dissatisfied +28835,41577,Male,Loyal Customer,12,Personal Travel,Eco,1211,3,1,3,2,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +28836,118006,Female,disloyal Customer,21,Business travel,Eco,1037,4,4,4,4,1,4,1,1,5,3,4,4,4,1,10,18.0,neutral or dissatisfied +28837,3669,Female,Loyal Customer,30,Business travel,Business,3255,3,3,3,3,3,3,3,3,1,3,4,3,3,3,8,1.0,neutral or dissatisfied +28838,1930,Male,disloyal Customer,26,Business travel,Business,351,2,4,2,4,4,2,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +28839,75520,Male,Loyal Customer,60,Business travel,Business,337,3,3,3,3,4,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +28840,34938,Female,Loyal Customer,38,Personal Travel,Eco,395,2,4,2,5,5,2,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +28841,56125,Male,Loyal Customer,38,Business travel,Business,1400,1,1,1,1,4,5,4,5,5,5,5,4,5,3,0,21.0,satisfied +28842,5872,Female,Loyal Customer,47,Business travel,Business,108,5,3,5,5,3,4,5,4,4,4,4,3,4,5,20,20.0,satisfied +28843,80727,Male,Loyal Customer,42,Business travel,Business,448,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +28844,30749,Male,Loyal Customer,47,Business travel,Eco,577,3,3,3,3,3,3,3,3,1,2,3,1,4,3,103,110.0,neutral or dissatisfied +28845,7990,Female,disloyal Customer,23,Business travel,Eco,335,2,3,2,4,5,2,5,5,1,1,4,2,3,5,0,0.0,neutral or dissatisfied +28846,85489,Female,Loyal Customer,26,Personal Travel,Eco,214,1,5,1,5,3,1,5,3,3,3,5,4,4,3,0,2.0,neutral or dissatisfied +28847,102762,Male,Loyal Customer,50,Business travel,Business,1618,4,1,4,4,5,4,5,4,4,4,4,5,4,5,19,12.0,satisfied +28848,24715,Male,disloyal Customer,23,Business travel,Eco,149,2,2,2,3,4,2,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +28849,19992,Female,Loyal Customer,12,Business travel,Business,3024,1,1,2,1,3,4,3,3,3,1,1,3,3,3,0,0.0,satisfied +28850,63307,Male,Loyal Customer,37,Business travel,Eco,337,3,5,5,5,3,2,3,3,3,3,3,4,4,3,28,19.0,neutral or dissatisfied +28851,46439,Male,Loyal Customer,30,Business travel,Eco,1304,5,2,2,2,5,5,5,5,3,3,1,3,3,5,25,27.0,satisfied +28852,68660,Male,Loyal Customer,74,Business travel,Business,1561,4,5,5,5,4,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +28853,7078,Male,Loyal Customer,34,Business travel,Eco,157,4,4,4,4,4,4,4,4,3,3,3,3,2,4,0,19.0,neutral or dissatisfied +28854,113804,Male,Loyal Customer,23,Business travel,Business,1596,4,4,4,4,5,5,5,5,3,4,5,4,4,5,16,0.0,satisfied +28855,105112,Female,Loyal Customer,58,Business travel,Business,2441,1,1,5,1,3,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +28856,60345,Female,Loyal Customer,62,Personal Travel,Eco,1024,4,5,4,4,5,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +28857,92760,Female,Loyal Customer,60,Business travel,Business,2171,1,4,1,1,4,5,5,5,5,5,5,4,5,4,0,1.0,satisfied +28858,15743,Male,Loyal Customer,31,Business travel,Business,544,3,3,3,3,5,5,5,5,1,4,1,1,3,5,118,109.0,satisfied +28859,31859,Female,Loyal Customer,36,Business travel,Business,2640,2,2,2,2,2,4,3,4,4,4,4,3,4,4,0,9.0,satisfied +28860,46814,Male,Loyal Customer,37,Business travel,Business,964,2,2,2,2,2,5,5,5,5,4,5,1,5,3,0,16.0,satisfied +28861,128435,Male,Loyal Customer,40,Business travel,Eco,651,3,2,2,2,3,3,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +28862,56619,Male,Loyal Customer,33,Business travel,Eco,1023,4,1,1,1,4,4,4,4,1,5,3,1,3,4,0,0.0,neutral or dissatisfied +28863,37233,Male,Loyal Customer,85,Business travel,Business,2078,1,1,5,1,5,4,4,3,4,5,5,4,4,4,82,76.0,satisfied +28864,127073,Female,Loyal Customer,23,Business travel,Eco,338,2,3,3,3,2,2,3,2,2,1,3,3,4,2,0,0.0,neutral or dissatisfied +28865,50473,Male,disloyal Customer,26,Business travel,Eco,109,4,0,4,4,3,4,3,3,2,5,3,5,2,3,0,0.0,neutral or dissatisfied +28866,24483,Female,Loyal Customer,30,Business travel,Business,481,1,4,5,4,1,2,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +28867,54755,Female,Loyal Customer,26,Business travel,Eco Plus,854,3,5,5,5,3,4,3,3,3,3,2,5,2,3,10,3.0,satisfied +28868,93026,Female,Loyal Customer,25,Personal Travel,Eco,1524,3,2,3,3,5,3,5,5,1,1,2,2,3,5,4,0.0,neutral or dissatisfied +28869,124809,Male,Loyal Customer,58,Business travel,Business,2744,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +28870,115803,Female,Loyal Customer,30,Business travel,Business,1560,2,4,3,4,2,2,2,2,2,2,4,3,3,2,18,9.0,neutral or dissatisfied +28871,37891,Female,Loyal Customer,36,Business travel,Business,1065,2,2,2,2,3,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +28872,106018,Female,Loyal Customer,48,Personal Travel,Business,682,1,1,1,4,5,3,4,3,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +28873,8602,Male,Loyal Customer,55,Business travel,Business,2744,0,5,0,1,4,5,5,2,2,2,2,5,2,3,10,4.0,satisfied +28874,103841,Female,Loyal Customer,22,Business travel,Business,3081,2,3,3,3,2,2,2,2,1,5,4,3,3,2,129,122.0,neutral or dissatisfied +28875,9186,Male,disloyal Customer,23,Business travel,Business,363,3,2,3,4,2,3,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +28876,69073,Male,Loyal Customer,65,Business travel,Business,2865,1,1,1,1,3,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +28877,30132,Female,Loyal Customer,18,Personal Travel,Eco,160,5,5,5,2,3,5,3,3,4,4,5,3,5,3,0,0.0,satisfied +28878,117485,Male,Loyal Customer,27,Business travel,Business,507,3,5,5,5,3,3,3,3,3,1,4,1,3,3,25,20.0,neutral or dissatisfied +28879,70815,Male,Loyal Customer,60,Personal Travel,Eco,624,4,4,4,3,3,4,3,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +28880,73506,Female,Loyal Customer,55,Business travel,Business,2360,1,1,1,1,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +28881,19164,Male,Loyal Customer,48,Business travel,Eco,304,4,1,1,1,4,4,4,4,5,1,5,5,5,4,3,0.0,satisfied +28882,119372,Male,Loyal Customer,51,Business travel,Business,3472,3,3,3,3,5,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +28883,36760,Male,disloyal Customer,25,Business travel,Eco,777,3,3,3,1,3,3,3,4,2,5,2,3,2,3,5,0.0,neutral or dissatisfied +28884,23786,Female,Loyal Customer,40,Business travel,Business,374,2,2,2,2,2,1,4,5,5,5,5,3,5,4,0,0.0,satisfied +28885,51255,Male,Loyal Customer,38,Business travel,Eco Plus,89,4,1,1,1,4,4,4,4,3,3,5,3,1,4,0,31.0,satisfied +28886,57059,Female,Loyal Customer,40,Personal Travel,Eco,2133,2,4,2,4,2,2,2,2,1,4,4,3,4,2,0,0.0,neutral or dissatisfied +28887,100826,Male,Loyal Customer,45,Business travel,Business,711,3,3,3,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +28888,45391,Female,Loyal Customer,32,Business travel,Business,1905,3,3,3,3,5,5,5,5,1,5,4,2,3,5,0,0.0,satisfied +28889,28472,Female,disloyal Customer,25,Business travel,Eco,1352,2,2,2,4,2,5,5,3,2,2,4,5,3,5,214,258.0,neutral or dissatisfied +28890,106933,Female,disloyal Customer,49,Business travel,Business,937,1,0,0,3,3,1,3,3,4,3,5,3,4,3,10,32.0,neutral or dissatisfied +28891,61745,Male,Loyal Customer,48,Business travel,Business,2503,3,5,5,5,2,3,3,4,4,4,3,4,4,1,114,111.0,neutral or dissatisfied +28892,12667,Male,Loyal Customer,34,Business travel,Business,3808,4,4,4,4,1,3,3,4,4,4,4,3,4,5,46,41.0,satisfied +28893,260,Male,Loyal Customer,62,Business travel,Business,612,2,5,5,5,2,4,3,2,2,2,2,2,2,2,29,22.0,neutral or dissatisfied +28894,12500,Female,Loyal Customer,52,Business travel,Eco Plus,190,5,2,2,2,4,5,4,5,5,5,5,3,5,2,27,23.0,satisfied +28895,5201,Male,Loyal Customer,51,Business travel,Business,2917,3,3,5,3,5,4,5,5,5,5,5,5,5,5,4,2.0,satisfied +28896,23479,Male,Loyal Customer,16,Personal Travel,Eco,488,4,4,4,4,1,4,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +28897,82210,Female,Loyal Customer,46,Business travel,Business,2148,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +28898,52348,Female,Loyal Customer,49,Business travel,Eco,451,5,5,5,5,1,4,4,5,5,5,5,2,5,1,0,0.0,satisfied +28899,5485,Male,Loyal Customer,48,Business travel,Business,3331,1,1,1,1,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +28900,30854,Male,Loyal Customer,39,Business travel,Eco Plus,973,1,4,4,4,1,1,1,1,1,5,3,1,4,1,13,1.0,neutral or dissatisfied +28901,107270,Female,Loyal Customer,36,Business travel,Eco,307,2,4,5,4,2,2,2,2,4,1,4,2,3,2,31,27.0,neutral or dissatisfied +28902,71980,Male,disloyal Customer,24,Business travel,Eco,1068,2,2,2,4,1,2,1,1,1,5,1,3,2,1,98,74.0,neutral or dissatisfied +28903,103773,Female,Loyal Customer,16,Personal Travel,Business,634,3,1,3,4,4,3,3,4,4,5,4,2,3,4,0,0.0,neutral or dissatisfied +28904,123319,Male,Loyal Customer,52,Business travel,Eco Plus,631,1,5,5,5,1,1,1,1,3,3,3,3,2,1,11,18.0,neutral or dissatisfied +28905,105929,Male,Loyal Customer,31,Business travel,Business,1491,3,4,3,3,3,4,3,3,5,3,4,3,4,3,24,10.0,satisfied +28906,93244,Male,Loyal Customer,58,Business travel,Business,689,5,5,5,5,4,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +28907,23694,Male,disloyal Customer,37,Business travel,Eco,196,3,1,3,1,2,3,2,2,3,3,1,2,1,2,0,0.0,neutral or dissatisfied +28908,92538,Male,Loyal Customer,62,Personal Travel,Eco,1947,0,5,0,4,2,0,2,2,5,5,5,3,5,2,5,4.0,satisfied +28909,73961,Female,Loyal Customer,68,Personal Travel,Eco,2267,4,5,4,1,4,3,4,2,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +28910,66354,Female,Loyal Customer,42,Business travel,Business,986,1,4,4,4,1,3,3,1,1,2,1,2,1,1,102,101.0,neutral or dissatisfied +28911,56213,Female,disloyal Customer,50,Business travel,Business,1585,4,4,4,2,4,4,4,4,4,3,4,3,4,4,67,51.0,satisfied +28912,10108,Female,disloyal Customer,23,Business travel,Eco,391,2,4,2,4,2,4,4,2,4,4,4,4,4,4,274,273.0,neutral or dissatisfied +28913,38608,Male,Loyal Customer,34,Business travel,Business,3789,3,5,5,5,2,3,4,3,3,3,3,4,3,4,114,119.0,neutral or dissatisfied +28914,125074,Male,Loyal Customer,51,Business travel,Business,3006,4,4,4,4,5,5,5,4,4,4,4,4,4,3,22,20.0,satisfied +28915,96385,Male,Loyal Customer,49,Business travel,Business,1407,1,1,1,1,3,4,5,4,4,4,4,5,4,5,87,91.0,satisfied +28916,5191,Male,Loyal Customer,48,Business travel,Business,293,2,2,2,2,3,4,5,5,5,5,5,4,5,3,52,59.0,satisfied +28917,33402,Female,Loyal Customer,61,Personal Travel,Business,2556,2,2,2,3,1,2,4,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +28918,64570,Male,disloyal Customer,22,Business travel,Eco,247,0,0,0,3,3,0,2,3,3,4,4,3,5,3,21,11.0,satisfied +28919,61305,Male,Loyal Customer,47,Personal Travel,Eco,853,3,1,2,3,1,2,1,1,1,4,3,4,3,1,3,0.0,neutral or dissatisfied +28920,75089,Female,Loyal Customer,18,Personal Travel,Eco,1814,3,5,3,4,5,3,5,5,4,5,3,5,4,5,3,0.0,neutral or dissatisfied +28921,125726,Female,Loyal Customer,57,Business travel,Business,2004,1,1,1,1,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +28922,11109,Male,Loyal Customer,11,Personal Travel,Eco,308,0,5,0,1,5,0,5,5,5,3,5,4,5,5,0,0.0,satisfied +28923,121271,Male,Loyal Customer,52,Personal Travel,Eco,2075,3,5,3,2,2,3,2,2,3,4,3,4,5,2,0,0.0,neutral or dissatisfied +28924,107337,Female,disloyal Customer,18,Business travel,Eco,632,0,0,0,2,3,0,3,3,5,3,5,5,5,3,0,0.0,satisfied +28925,125607,Male,Loyal Customer,39,Business travel,Business,759,4,4,4,4,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +28926,86344,Male,Loyal Customer,50,Business travel,Business,2048,1,1,1,1,4,4,4,2,2,2,2,4,2,3,18,36.0,satisfied +28927,98593,Female,Loyal Customer,39,Business travel,Business,861,2,2,2,2,2,4,4,5,5,5,5,5,5,3,16,21.0,satisfied +28928,45876,Male,Loyal Customer,44,Business travel,Business,563,1,1,1,1,3,5,2,3,3,4,3,1,3,2,0,0.0,satisfied +28929,26609,Female,Loyal Customer,58,Business travel,Business,270,4,1,4,4,2,4,2,5,5,4,5,2,5,4,65,71.0,satisfied +28930,26757,Male,Loyal Customer,50,Business travel,Business,459,2,2,2,2,5,3,4,2,2,2,2,4,2,4,28,28.0,neutral or dissatisfied +28931,122470,Male,Loyal Customer,25,Business travel,Business,808,3,3,3,3,3,3,3,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +28932,52826,Female,Loyal Customer,52,Business travel,Business,1721,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,33.0,satisfied +28933,68818,Female,Loyal Customer,25,Business travel,Eco Plus,1021,4,2,2,2,4,4,4,4,1,4,4,4,4,4,8,79.0,neutral or dissatisfied +28934,34718,Male,Loyal Customer,43,Business travel,Business,2992,3,3,2,3,3,1,4,4,4,4,4,4,4,4,0,0.0,satisfied +28935,56270,Male,Loyal Customer,46,Business travel,Business,1828,3,2,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +28936,116858,Female,disloyal Customer,37,Business travel,Business,370,2,2,2,1,5,2,5,5,4,4,5,3,4,5,111,102.0,neutral or dissatisfied +28937,108874,Male,Loyal Customer,54,Business travel,Eco,1587,3,5,5,5,3,3,3,3,2,4,2,4,3,3,44,50.0,neutral or dissatisfied +28938,100304,Female,Loyal Customer,33,Business travel,Business,3875,1,1,1,1,2,4,5,5,5,4,5,4,5,3,0,6.0,satisfied +28939,50926,Male,Loyal Customer,66,Personal Travel,Eco,337,3,4,3,3,4,3,4,4,2,2,3,1,4,4,3,0.0,neutral or dissatisfied +28940,60522,Male,Loyal Customer,25,Personal Travel,Eco,862,2,3,2,4,4,2,4,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +28941,54198,Female,Loyal Customer,9,Personal Travel,Eco,1400,2,4,2,1,4,2,5,4,4,3,2,2,2,4,41,6.0,neutral or dissatisfied +28942,50312,Male,Loyal Customer,54,Business travel,Eco,86,3,1,5,1,3,3,3,3,1,3,4,3,3,3,94,118.0,neutral or dissatisfied +28943,59212,Female,Loyal Customer,33,Personal Travel,Eco,1440,4,4,5,3,3,5,3,3,3,5,5,5,4,3,27,22.0,neutral or dissatisfied +28944,54417,Female,Loyal Customer,64,Business travel,Business,1904,1,2,2,2,2,3,3,1,1,1,1,3,1,2,6,1.0,neutral or dissatisfied +28945,36357,Female,Loyal Customer,43,Business travel,Business,200,5,5,5,5,5,3,1,4,4,4,5,2,4,1,0,0.0,satisfied +28946,79023,Male,Loyal Customer,38,Business travel,Eco,306,2,1,5,5,2,2,2,2,3,1,3,3,3,2,14,26.0,neutral or dissatisfied +28947,99272,Female,Loyal Customer,56,Business travel,Business,3334,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +28948,82022,Male,Loyal Customer,65,Personal Travel,Eco,1589,2,4,2,3,4,2,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +28949,13643,Female,Loyal Customer,36,Personal Travel,Eco Plus,835,4,5,4,3,3,4,4,3,4,4,4,5,4,3,50,62.0,neutral or dissatisfied +28950,112509,Male,Loyal Customer,16,Personal Travel,Eco,862,2,3,2,4,3,2,3,3,3,3,3,2,3,3,50,37.0,neutral or dissatisfied +28951,22338,Male,Loyal Customer,77,Business travel,Business,2435,4,4,4,4,1,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +28952,66501,Female,Loyal Customer,47,Business travel,Eco,447,1,4,4,4,1,2,2,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +28953,62535,Female,disloyal Customer,23,Business travel,Business,1726,4,0,4,5,2,4,2,2,3,3,3,3,5,2,7,7.0,satisfied +28954,22634,Female,Loyal Customer,43,Personal Travel,Eco,300,2,4,2,2,3,5,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +28955,26803,Male,disloyal Customer,20,Business travel,Eco,2139,3,3,3,2,2,3,5,2,1,5,2,3,2,2,21,1.0,neutral or dissatisfied +28956,111135,Female,disloyal Customer,25,Business travel,Eco,1173,2,2,2,3,3,2,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +28957,50544,Male,Loyal Customer,56,Personal Travel,Eco,209,2,3,2,3,3,2,3,3,4,1,3,3,3,3,0,6.0,neutral or dissatisfied +28958,124228,Female,Loyal Customer,47,Business travel,Business,1916,4,4,2,4,2,3,4,4,4,4,4,3,4,4,4,0.0,satisfied +28959,96667,Male,Loyal Customer,60,Personal Travel,Eco,937,3,5,3,2,1,3,1,1,5,2,5,3,4,1,0,,neutral or dissatisfied +28960,69615,Female,Loyal Customer,43,Business travel,Business,2446,5,5,5,5,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +28961,110157,Male,Loyal Customer,61,Personal Travel,Eco,1242,3,5,3,1,2,3,2,2,5,3,4,5,5,2,20,29.0,neutral or dissatisfied +28962,13441,Male,Loyal Customer,55,Business travel,Business,475,1,1,1,1,2,2,3,1,1,1,1,2,1,4,0,7.0,neutral or dissatisfied +28963,7309,Male,disloyal Customer,18,Business travel,Eco Plus,130,1,4,1,3,1,1,1,1,1,5,4,3,3,1,0,0.0,neutral or dissatisfied +28964,108810,Male,Loyal Customer,43,Business travel,Business,3346,3,3,3,3,4,4,4,5,5,5,5,3,5,5,12,22.0,satisfied +28965,111185,Female,disloyal Customer,60,Business travel,Business,1546,3,3,3,2,5,3,3,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +28966,39037,Male,Loyal Customer,25,Personal Travel,Eco,113,2,1,2,4,3,2,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +28967,49222,Male,Loyal Customer,57,Business travel,Eco,308,4,2,2,2,4,4,4,4,1,1,3,3,4,4,0,0.0,satisfied +28968,116296,Female,Loyal Customer,63,Personal Travel,Eco,308,2,4,2,2,2,4,4,5,5,5,5,4,4,4,141,128.0,neutral or dissatisfied +28969,59657,Female,Loyal Customer,37,Personal Travel,Eco,787,1,5,1,2,1,1,2,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +28970,34121,Male,Loyal Customer,36,Business travel,Eco,1046,2,4,5,4,2,2,2,2,2,1,2,3,2,2,0,0.0,satisfied +28971,37412,Female,disloyal Customer,54,Business travel,Eco,1028,2,2,2,4,5,2,5,5,3,1,3,1,3,5,76,62.0,neutral or dissatisfied +28972,104163,Male,Loyal Customer,42,Business travel,Business,3992,4,4,4,4,2,4,4,4,4,5,4,5,4,3,35,18.0,satisfied +28973,58664,Male,Loyal Customer,32,Personal Travel,Eco,867,1,4,1,3,5,1,5,5,4,1,4,4,3,5,35,19.0,neutral or dissatisfied +28974,47131,Female,Loyal Customer,65,Business travel,Business,2282,2,3,3,3,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +28975,122269,Female,Loyal Customer,48,Personal Travel,Eco,603,3,4,3,3,5,5,4,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +28976,92174,Male,Loyal Customer,46,Business travel,Business,1956,1,1,1,1,5,5,4,4,4,4,4,4,4,4,82,57.0,satisfied +28977,58010,Male,Loyal Customer,39,Personal Travel,Eco,1162,1,5,1,2,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +28978,100857,Female,disloyal Customer,10,Business travel,Eco,711,2,1,1,3,1,1,1,1,3,2,4,2,4,1,76,77.0,neutral or dissatisfied +28979,59307,Male,Loyal Customer,45,Business travel,Business,2556,4,4,4,4,4,5,4,4,4,4,4,3,4,4,26,0.0,satisfied +28980,127642,Female,Loyal Customer,9,Personal Travel,Eco,1773,2,5,2,5,2,2,2,2,1,3,4,3,3,2,1,28.0,neutral or dissatisfied +28981,74668,Male,Loyal Customer,8,Personal Travel,Eco,1431,3,1,3,2,5,3,5,5,2,5,2,2,1,5,0,0.0,neutral or dissatisfied +28982,80165,Female,Loyal Customer,50,Business travel,Business,2475,2,2,2,2,2,2,2,2,2,3,4,2,4,2,41,35.0,neutral or dissatisfied +28983,101478,Male,Loyal Customer,47,Business travel,Business,1647,0,0,0,2,3,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +28984,62875,Female,Loyal Customer,28,Personal Travel,Eco,2446,3,4,3,3,4,3,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +28985,47959,Female,Loyal Customer,63,Personal Travel,Eco,329,1,1,1,3,3,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +28986,73277,Female,Loyal Customer,44,Personal Travel,Business,1197,5,3,5,3,2,4,2,5,5,5,5,3,5,2,0,0.0,satisfied +28987,71765,Male,disloyal Customer,37,Business travel,Business,1726,1,1,1,4,1,1,1,1,3,3,3,4,4,1,4,6.0,neutral or dissatisfied +28988,101853,Female,Loyal Customer,42,Business travel,Business,3916,4,4,4,4,2,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +28989,588,Female,Loyal Customer,40,Business travel,Business,3424,1,1,1,1,3,5,4,5,5,5,5,3,5,4,36,37.0,satisfied +28990,40305,Male,Loyal Customer,48,Personal Travel,Eco,436,3,2,3,4,4,3,4,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +28991,112098,Female,Loyal Customer,33,Business travel,Business,1062,2,2,2,2,4,5,4,4,4,4,4,3,4,5,40,31.0,satisfied +28992,74232,Male,Loyal Customer,30,Business travel,Business,1535,2,2,2,2,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +28993,111589,Female,Loyal Customer,43,Personal Travel,Eco,883,2,2,2,4,2,4,4,1,1,2,1,3,1,2,1,0.0,neutral or dissatisfied +28994,107389,Female,Loyal Customer,45,Business travel,Business,3136,3,3,3,3,3,5,4,4,4,4,4,5,4,3,16,0.0,satisfied +28995,79362,Female,Loyal Customer,27,Business travel,Eco Plus,1020,4,2,2,2,4,3,4,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +28996,39908,Male,Loyal Customer,48,Personal Travel,Eco Plus,272,2,4,2,3,1,2,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +28997,71368,Female,Loyal Customer,58,Business travel,Business,1651,3,3,3,3,5,4,4,4,4,4,4,4,4,3,32,25.0,satisfied +28998,48169,Male,Loyal Customer,60,Business travel,Eco,173,5,3,1,1,5,5,5,5,1,4,5,3,5,5,0,4.0,satisfied +28999,84822,Male,Loyal Customer,20,Business travel,Business,2007,2,3,3,3,2,2,2,2,3,3,4,1,4,2,0,32.0,neutral or dissatisfied +29000,63753,Female,Loyal Customer,40,Business travel,Business,1660,1,1,1,1,2,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +29001,61440,Female,Loyal Customer,43,Business travel,Eco,2253,2,5,5,5,1,2,3,2,2,2,2,1,2,2,4,4.0,neutral or dissatisfied +29002,43270,Male,disloyal Customer,39,Business travel,Eco,463,5,0,5,4,4,5,4,4,5,5,3,4,1,4,0,0.0,satisfied +29003,118634,Female,Loyal Customer,34,Business travel,Business,2871,3,3,3,3,3,4,4,3,3,3,3,3,3,3,1,23.0,neutral or dissatisfied +29004,29696,Female,Loyal Customer,45,Business travel,Eco,1542,4,2,2,2,1,3,5,4,4,4,4,5,4,3,0,3.0,satisfied +29005,74254,Male,Loyal Customer,67,Personal Travel,Eco,1709,2,2,2,4,3,2,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +29006,21717,Female,disloyal Customer,24,Business travel,Eco,952,3,3,3,2,2,3,2,2,4,1,2,5,2,2,7,0.0,neutral or dissatisfied +29007,31362,Male,Loyal Customer,25,Business travel,Business,692,4,4,1,4,5,5,5,5,3,1,1,1,3,5,8,3.0,satisfied +29008,43166,Female,Loyal Customer,34,Personal Travel,Eco,840,3,5,3,3,5,3,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +29009,128894,Female,Loyal Customer,46,Business travel,Eco,1065,5,3,3,3,5,5,5,4,1,3,2,5,5,5,0,0.0,satisfied +29010,12402,Female,Loyal Customer,22,Business travel,Business,2426,1,1,1,1,3,4,1,3,3,4,3,3,3,3,6,26.0,neutral or dissatisfied +29011,57226,Female,Loyal Customer,62,Personal Travel,Eco,1514,3,3,3,3,5,3,3,5,5,3,5,1,5,3,0,0.0,neutral or dissatisfied +29012,51657,Female,disloyal Customer,25,Business travel,Eco,598,4,3,4,2,3,4,3,3,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +29013,79530,Female,disloyal Customer,24,Business travel,Eco,712,3,3,3,2,1,3,1,1,2,2,2,4,2,1,2,1.0,neutral or dissatisfied +29014,94141,Female,disloyal Customer,25,Business travel,Eco,323,3,2,4,3,5,4,4,5,3,4,3,3,4,5,0,0.0,neutral or dissatisfied +29015,25212,Male,Loyal Customer,40,Business travel,Eco,842,4,1,1,1,4,4,4,4,3,4,3,2,5,4,0,9.0,satisfied +29016,53448,Male,Loyal Customer,20,Business travel,Business,2253,2,3,3,3,2,2,2,2,2,1,3,2,3,2,0,2.0,neutral or dissatisfied +29017,8577,Female,disloyal Customer,35,Business travel,Eco,109,3,0,3,3,4,3,4,4,4,5,1,4,2,4,75,85.0,neutral or dissatisfied +29018,59915,Male,Loyal Customer,36,Business travel,Business,1023,1,1,1,1,2,5,5,4,4,5,4,5,4,3,17,0.0,satisfied +29019,73053,Male,disloyal Customer,23,Business travel,Business,1096,5,0,5,4,1,5,1,1,4,3,4,4,4,1,3,0.0,satisfied +29020,115774,Male,Loyal Customer,53,Business travel,Business,3767,4,4,1,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +29021,105965,Female,disloyal Customer,14,Business travel,Eco,2295,4,4,4,4,3,4,3,3,3,3,2,4,3,3,5,0.0,neutral or dissatisfied +29022,99978,Female,Loyal Customer,45,Business travel,Business,2964,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +29023,81485,Female,Loyal Customer,61,Business travel,Business,3711,0,4,0,2,5,3,2,4,4,4,4,5,4,1,0,0.0,satisfied +29024,89600,Female,disloyal Customer,29,Business travel,Business,1035,0,0,0,3,2,0,2,2,5,3,4,5,4,2,25,0.0,satisfied +29025,16377,Male,disloyal Customer,62,Business travel,Eco,1325,4,4,4,3,5,4,5,5,2,5,5,2,3,5,0,0.0,neutral or dissatisfied +29026,64591,Female,Loyal Customer,49,Business travel,Business,282,0,0,0,1,3,5,4,3,3,2,2,5,3,3,67,64.0,satisfied +29027,12160,Female,Loyal Customer,50,Business travel,Eco,986,4,2,1,1,5,4,2,4,4,4,4,5,4,2,0,0.0,satisfied +29028,95995,Male,Loyal Customer,22,Business travel,Business,2086,3,3,2,3,3,3,3,3,1,2,4,1,4,3,14,10.0,neutral or dissatisfied +29029,52459,Female,disloyal Customer,34,Business travel,Eco Plus,370,4,4,4,3,5,4,5,5,1,2,5,5,2,5,12,1.0,neutral or dissatisfied +29030,126721,Male,Loyal Customer,52,Business travel,Business,2521,3,3,3,3,2,2,3,3,3,3,3,1,3,1,77,62.0,neutral or dissatisfied +29031,22706,Female,Loyal Customer,17,Personal Travel,Eco,589,1,4,1,2,4,1,3,4,3,4,3,3,4,4,19,7.0,neutral or dissatisfied +29032,36434,Male,Loyal Customer,16,Personal Travel,Eco,369,4,1,4,3,3,4,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +29033,58106,Male,Loyal Customer,18,Personal Travel,Eco,589,2,5,2,3,3,2,3,3,4,5,5,5,4,3,54,64.0,neutral or dissatisfied +29034,79150,Female,Loyal Customer,17,Personal Travel,Eco Plus,306,4,4,4,1,5,4,5,5,4,3,4,4,5,5,26,102.0,neutral or dissatisfied +29035,114512,Male,Loyal Customer,68,Business travel,Business,2328,3,2,2,2,1,3,4,3,3,3,3,3,3,4,45,38.0,neutral or dissatisfied +29036,9950,Female,disloyal Customer,34,Business travel,Eco,515,2,3,2,2,3,2,3,3,4,4,2,1,3,3,28,14.0,neutral or dissatisfied +29037,93067,Female,Loyal Customer,54,Personal Travel,Eco,297,3,4,3,2,5,5,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +29038,127564,Female,Loyal Customer,25,Business travel,Business,1670,5,5,5,5,5,5,5,5,3,2,4,4,4,5,0,0.0,satisfied +29039,70025,Female,Loyal Customer,12,Business travel,Business,583,3,3,3,3,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +29040,125694,Male,Loyal Customer,8,Personal Travel,Eco,899,2,5,2,2,2,2,2,2,4,2,5,4,4,2,0,10.0,neutral or dissatisfied +29041,38416,Female,Loyal Customer,42,Business travel,Eco,965,4,1,1,1,2,2,5,3,3,4,3,2,3,3,0,0.0,satisfied +29042,129551,Female,Loyal Customer,61,Business travel,Business,2045,3,3,3,3,5,3,4,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +29043,3301,Female,Loyal Customer,78,Business travel,Business,2963,4,4,4,4,4,4,5,3,3,3,3,3,3,4,34,17.0,satisfied +29044,14998,Male,Loyal Customer,53,Business travel,Eco,1201,2,2,2,2,1,2,1,1,1,5,3,1,4,1,3,0.0,neutral or dissatisfied +29045,43905,Male,Loyal Customer,35,Personal Travel,Eco,199,4,5,4,3,3,4,3,3,3,5,5,3,4,3,0,0.0,satisfied +29046,92923,Female,Loyal Customer,57,Business travel,Business,134,0,4,0,3,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +29047,124332,Male,Loyal Customer,34,Personal Travel,Eco Plus,601,4,4,4,3,4,4,4,4,4,2,1,1,5,4,0,0.0,neutral or dissatisfied +29048,11086,Male,Loyal Customer,56,Personal Travel,Eco,309,3,4,4,1,5,4,5,5,5,3,5,4,5,5,34,29.0,neutral or dissatisfied +29049,112220,Male,disloyal Customer,29,Business travel,Eco,1199,3,3,3,4,2,3,5,2,1,1,3,3,3,2,31,58.0,neutral or dissatisfied +29050,66431,Male,Loyal Customer,69,Personal Travel,Eco Plus,1562,1,3,1,2,4,1,5,4,1,1,2,4,2,4,0,0.0,neutral or dissatisfied +29051,96728,Female,Loyal Customer,56,Personal Travel,Eco,813,3,2,3,4,1,2,4,3,3,3,4,2,3,3,14,6.0,neutral or dissatisfied +29052,116092,Female,Loyal Customer,19,Personal Travel,Eco,480,1,4,1,3,2,1,3,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +29053,76781,Male,disloyal Customer,23,Business travel,Business,689,5,0,5,2,2,5,3,2,4,4,4,4,4,2,1,0.0,satisfied +29054,82648,Male,Loyal Customer,46,Business travel,Business,120,5,5,5,5,4,5,5,4,4,4,4,5,4,5,9,1.0,satisfied +29055,9548,Female,Loyal Customer,31,Business travel,Business,3863,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +29056,97457,Male,Loyal Customer,52,Business travel,Business,484,5,5,5,5,5,5,5,3,3,3,3,4,3,3,1,0.0,satisfied +29057,22584,Male,disloyal Customer,45,Business travel,Eco,300,2,0,2,2,4,2,5,4,5,3,1,4,1,4,4,2.0,neutral or dissatisfied +29058,32251,Male,disloyal Customer,33,Business travel,Business,216,3,2,2,4,5,2,3,5,3,5,3,3,1,5,0,7.0,neutral or dissatisfied +29059,101171,Female,Loyal Customer,53,Business travel,Business,1662,2,5,1,5,1,3,3,2,2,2,2,4,2,4,13,8.0,neutral or dissatisfied +29060,39769,Female,Loyal Customer,40,Business travel,Eco,521,2,2,5,5,2,2,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +29061,3760,Male,Loyal Customer,58,Business travel,Business,3361,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +29062,64140,Male,Loyal Customer,50,Business travel,Business,2719,1,2,1,1,3,5,4,5,5,4,5,3,5,5,3,0.0,satisfied +29063,87616,Female,Loyal Customer,56,Business travel,Business,1791,2,2,2,2,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +29064,38849,Female,Loyal Customer,45,Personal Travel,Eco Plus,353,1,1,1,4,3,4,3,4,4,1,4,1,4,1,80,96.0,neutral or dissatisfied +29065,94515,Male,Loyal Customer,39,Business travel,Business,248,5,5,5,5,2,5,4,5,5,5,5,5,5,5,18,34.0,satisfied +29066,17144,Female,Loyal Customer,45,Business travel,Eco,696,5,3,3,3,1,4,1,5,5,5,5,4,5,5,8,0.0,satisfied +29067,1844,Female,Loyal Customer,13,Personal Travel,Eco,408,2,5,4,1,2,4,2,2,5,5,5,5,5,2,0,1.0,neutral or dissatisfied +29068,51265,Male,Loyal Customer,61,Business travel,Eco Plus,109,3,3,3,3,3,3,3,3,4,1,3,2,2,3,0,0.0,neutral or dissatisfied +29069,128603,Female,Loyal Customer,52,Business travel,Business,679,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +29070,126050,Male,Loyal Customer,49,Business travel,Business,328,0,0,0,3,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +29071,40931,Female,disloyal Customer,9,Business travel,Eco,584,4,4,4,3,5,4,5,5,2,3,5,3,1,5,0,0.0,satisfied +29072,93241,Male,Loyal Customer,45,Business travel,Business,689,2,2,2,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +29073,69133,Female,Loyal Customer,30,Business travel,Eco Plus,1598,2,2,2,2,2,2,2,2,4,5,3,3,4,2,9,28.0,neutral or dissatisfied +29074,6961,Male,Loyal Customer,36,Business travel,Business,2054,2,5,4,5,1,3,3,1,1,1,2,2,1,4,0,0.0,neutral or dissatisfied +29075,93137,Male,Loyal Customer,58,Business travel,Business,2437,1,1,1,1,2,4,4,4,4,4,4,3,4,5,3,45.0,satisfied +29076,85233,Male,Loyal Customer,30,Business travel,Business,3050,1,1,1,1,1,1,1,1,4,2,2,4,1,1,9,10.0,neutral or dissatisfied +29077,95847,Male,Loyal Customer,50,Business travel,Business,3829,4,4,4,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +29078,28181,Female,Loyal Customer,34,Personal Travel,Eco,834,1,5,1,4,2,1,2,2,3,4,4,4,4,2,37,42.0,neutral or dissatisfied +29079,73622,Male,Loyal Customer,56,Business travel,Business,2595,0,4,0,5,5,5,5,5,5,1,1,4,5,3,0,0.0,satisfied +29080,90008,Female,Loyal Customer,47,Personal Travel,Business,1084,4,4,4,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +29081,8001,Female,disloyal Customer,28,Business travel,Business,402,1,1,1,5,1,1,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +29082,29334,Female,Loyal Customer,69,Personal Travel,Eco,933,4,4,5,4,3,4,4,4,4,5,5,4,4,3,0,20.0,neutral or dissatisfied +29083,19497,Female,Loyal Customer,35,Business travel,Eco,508,5,4,2,4,5,5,5,5,3,4,4,1,2,5,0,0.0,satisfied +29084,37606,Male,Loyal Customer,8,Personal Travel,Eco,828,2,5,2,1,1,2,1,1,3,5,4,3,5,1,24,16.0,neutral or dissatisfied +29085,16353,Male,Loyal Customer,11,Personal Travel,Eco,160,1,4,1,2,2,1,1,2,3,5,4,3,4,2,20,4.0,neutral or dissatisfied +29086,119567,Female,Loyal Customer,31,Business travel,Business,814,4,4,2,4,5,5,5,5,3,5,4,3,4,5,0,0.0,satisfied +29087,93005,Male,disloyal Customer,23,Business travel,Business,1524,0,0,0,4,4,0,4,4,4,4,5,5,5,4,0,0.0,satisfied +29088,126633,Female,Loyal Customer,49,Business travel,Business,602,3,3,3,3,3,5,4,4,4,4,4,4,4,3,0,7.0,satisfied +29089,109097,Female,Loyal Customer,27,Personal Travel,Eco,781,1,4,2,5,5,2,1,5,4,1,4,1,5,5,23,21.0,neutral or dissatisfied +29090,115885,Male,disloyal Customer,29,Business travel,Eco,373,3,2,4,4,2,4,2,2,1,1,3,4,4,2,27,34.0,neutral or dissatisfied +29091,13535,Male,Loyal Customer,60,Business travel,Business,106,4,1,2,1,5,3,3,2,2,2,4,4,2,3,0,0.0,neutral or dissatisfied +29092,26977,Female,Loyal Customer,29,Business travel,Eco,867,5,2,2,2,5,5,5,5,1,4,5,1,5,5,0,0.0,satisfied +29093,123316,Male,Loyal Customer,44,Business travel,Eco Plus,328,2,1,1,1,2,2,2,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +29094,27496,Male,Loyal Customer,57,Business travel,Business,2173,2,2,2,2,2,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +29095,81656,Female,Loyal Customer,57,Business travel,Business,2047,2,2,2,2,5,5,5,4,4,4,4,5,4,5,0,12.0,satisfied +29096,113681,Female,Loyal Customer,39,Personal Travel,Eco,386,3,2,3,3,3,3,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +29097,31846,Female,disloyal Customer,42,Business travel,Eco,1163,4,4,4,4,4,4,4,4,4,4,4,4,3,4,12,1.0,neutral or dissatisfied +29098,74584,Male,Loyal Customer,10,Business travel,Business,1431,3,1,1,1,3,3,3,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +29099,38710,Female,Loyal Customer,28,Business travel,Eco,2583,5,2,2,2,5,5,5,5,1,5,4,4,5,5,8,0.0,satisfied +29100,43041,Female,Loyal Customer,26,Business travel,Business,236,2,4,4,4,2,3,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +29101,16660,Female,Loyal Customer,47,Business travel,Eco,488,4,2,2,2,5,4,3,4,4,4,4,1,4,1,0,9.0,neutral or dissatisfied +29102,86541,Female,Loyal Customer,41,Personal Travel,Eco,762,1,5,1,1,3,1,4,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +29103,87497,Female,Loyal Customer,44,Business travel,Business,3339,3,5,5,5,3,4,3,3,3,2,3,1,3,2,28,22.0,neutral or dissatisfied +29104,98632,Female,Loyal Customer,50,Business travel,Eco,861,4,5,5,5,2,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +29105,100126,Female,Loyal Customer,51,Business travel,Business,1857,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +29106,84865,Male,Loyal Customer,41,Personal Travel,Eco,534,3,5,3,3,5,3,5,5,5,3,5,3,5,5,6,0.0,neutral or dissatisfied +29107,19917,Female,disloyal Customer,25,Business travel,Eco,343,3,1,3,4,2,3,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +29108,7932,Female,Loyal Customer,61,Personal Travel,Eco Plus,864,2,4,2,5,2,4,4,1,1,2,1,4,1,5,0,10.0,neutral or dissatisfied +29109,123900,Female,Loyal Customer,54,Personal Travel,Eco,544,2,4,2,3,2,4,3,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +29110,95280,Female,Loyal Customer,60,Personal Travel,Eco,239,3,3,3,3,2,2,3,4,4,3,4,3,4,2,39,36.0,neutral or dissatisfied +29111,23082,Female,Loyal Customer,44,Business travel,Business,864,4,4,4,4,5,3,4,4,4,4,4,4,4,2,1,0.0,satisfied +29112,94216,Male,Loyal Customer,41,Business travel,Business,248,1,1,1,1,3,4,5,5,5,5,5,3,5,3,12,12.0,satisfied +29113,104527,Female,Loyal Customer,28,Business travel,Business,1842,2,2,5,2,5,5,5,5,5,3,4,5,4,5,2,0.0,satisfied +29114,32935,Female,Loyal Customer,22,Personal Travel,Eco,84,3,4,3,3,2,3,2,2,4,4,4,4,5,2,0,2.0,neutral or dissatisfied +29115,119552,Male,Loyal Customer,35,Personal Travel,Eco,814,4,0,4,1,3,4,3,3,1,3,1,3,5,3,0,0.0,neutral or dissatisfied +29116,117337,Female,Loyal Customer,50,Business travel,Business,296,1,1,1,1,4,4,4,5,5,5,5,5,5,3,7,0.0,satisfied +29117,48697,Female,Loyal Customer,57,Business travel,Business,3811,4,2,2,2,4,3,3,4,4,4,4,1,4,1,19,6.0,neutral or dissatisfied +29118,87201,Male,Loyal Customer,55,Business travel,Business,946,3,3,3,3,4,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +29119,99897,Male,Loyal Customer,48,Personal Travel,Eco,738,1,5,1,4,2,1,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +29120,53279,Male,Loyal Customer,53,Business travel,Eco,811,4,5,5,5,4,4,4,4,2,3,5,2,3,4,9,0.0,satisfied +29121,34113,Female,Loyal Customer,32,Business travel,Eco,1046,4,5,5,5,4,4,4,4,3,4,4,3,1,4,0,0.0,satisfied +29122,21861,Female,Loyal Customer,37,Business travel,Eco,500,4,1,1,1,4,4,4,4,2,2,5,4,1,4,52,47.0,satisfied +29123,14703,Female,Loyal Customer,44,Business travel,Eco,419,5,3,2,3,1,1,4,5,5,5,5,4,5,2,0,0.0,satisfied +29124,52224,Male,disloyal Customer,33,Business travel,Eco,370,3,0,3,4,3,3,3,3,4,1,2,2,2,3,0,0.0,neutral or dissatisfied +29125,18005,Female,Loyal Customer,21,Business travel,Business,332,0,0,0,1,5,2,2,5,1,1,5,4,1,5,0,4.0,satisfied +29126,33147,Female,Loyal Customer,49,Personal Travel,Eco,201,1,2,1,2,1,3,3,2,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +29127,127736,Female,Loyal Customer,41,Business travel,Business,3607,5,5,1,5,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +29128,9171,Female,Loyal Customer,52,Business travel,Business,416,5,5,5,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +29129,8317,Female,Loyal Customer,52,Business travel,Eco Plus,335,3,5,5,5,3,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +29130,63518,Male,Loyal Customer,22,Business travel,Business,3042,3,3,3,3,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +29131,16994,Male,Loyal Customer,53,Business travel,Business,843,2,2,2,2,5,1,5,5,5,5,5,4,5,2,0,29.0,satisfied +29132,85920,Female,Loyal Customer,19,Personal Travel,Eco,674,3,5,2,1,4,2,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +29133,99712,Female,Loyal Customer,68,Personal Travel,Eco,667,3,5,3,3,3,4,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +29134,119668,Female,Loyal Customer,58,Personal Travel,Eco,507,5,5,5,3,3,5,4,4,4,5,4,5,4,3,4,0.0,satisfied +29135,124853,Male,Loyal Customer,54,Personal Travel,Eco,280,1,2,1,2,1,1,4,1,4,5,1,2,2,1,0,0.0,neutral or dissatisfied +29136,107582,Female,Loyal Customer,25,Personal Travel,Eco Plus,1521,2,2,2,3,5,2,5,5,2,2,3,4,3,5,47,41.0,neutral or dissatisfied +29137,28948,Male,Loyal Customer,58,Business travel,Eco,671,3,1,1,1,3,3,3,3,3,1,2,1,2,3,0,0.0,neutral or dissatisfied +29138,10068,Male,Loyal Customer,51,Personal Travel,Eco,596,3,2,3,4,2,3,2,2,4,2,4,4,4,2,0,38.0,neutral or dissatisfied +29139,85604,Female,Loyal Customer,38,Business travel,Business,192,3,3,3,3,3,2,2,1,1,1,3,3,1,1,0,0.0,neutral or dissatisfied +29140,45707,Female,Loyal Customer,43,Business travel,Eco,836,4,4,4,4,4,4,4,4,4,1,5,4,1,4,115,167.0,satisfied +29141,93716,Male,disloyal Customer,33,Business travel,Business,630,1,1,1,4,1,3,3,3,4,5,5,3,4,3,145,152.0,neutral or dissatisfied +29142,57366,Male,Loyal Customer,53,Personal Travel,Eco,414,1,0,2,5,1,2,1,1,4,4,4,4,5,1,10,0.0,neutral or dissatisfied +29143,25869,Female,Loyal Customer,28,Business travel,Eco Plus,692,2,3,3,3,2,2,2,2,1,2,2,4,2,2,0,0.0,neutral or dissatisfied +29144,9333,Male,Loyal Customer,32,Personal Travel,Eco Plus,419,1,4,1,3,5,1,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +29145,75525,Male,Loyal Customer,48,Business travel,Business,337,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +29146,104754,Female,Loyal Customer,22,Personal Travel,Eco,1246,4,5,4,2,4,4,5,4,4,5,4,4,4,4,77,83.0,neutral or dissatisfied +29147,84214,Male,Loyal Customer,52,Business travel,Business,3477,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +29148,98223,Female,Loyal Customer,61,Personal Travel,Eco Plus,842,0,5,0,3,5,5,5,5,5,0,5,3,5,5,13,17.0,satisfied +29149,604,Male,Loyal Customer,47,Business travel,Business,396,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +29150,5373,Female,disloyal Customer,8,Business travel,Eco,812,3,4,4,3,4,4,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +29151,108736,Male,Loyal Customer,41,Business travel,Business,545,4,4,4,4,2,5,5,5,5,5,5,3,5,5,0,1.0,satisfied +29152,22843,Male,Loyal Customer,16,Personal Travel,Eco,147,2,5,0,4,5,0,5,5,5,5,5,5,5,5,18,19.0,neutral or dissatisfied +29153,64102,Female,Loyal Customer,51,Business travel,Business,919,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,15.0,satisfied +29154,11930,Male,Loyal Customer,28,Personal Travel,Eco Plus,744,2,5,2,4,4,2,4,4,5,5,3,2,1,4,0,0.0,neutral or dissatisfied +29155,59366,Male,Loyal Customer,33,Business travel,Business,2486,3,3,3,3,2,2,2,2,5,5,3,3,5,2,9,0.0,satisfied +29156,118088,Male,Loyal Customer,44,Business travel,Eco,876,3,1,1,1,3,3,3,3,1,2,2,3,5,3,67,56.0,neutral or dissatisfied +29157,119255,Female,Loyal Customer,49,Business travel,Business,2240,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,13.0,satisfied +29158,78423,Male,Loyal Customer,52,Business travel,Eco Plus,453,4,4,4,4,4,4,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +29159,18181,Male,Loyal Customer,61,Personal Travel,Business,228,3,5,3,3,2,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +29160,14311,Female,disloyal Customer,25,Business travel,Eco,175,4,3,4,4,2,4,2,2,1,2,2,4,3,2,0,0.0,satisfied +29161,125295,Male,Loyal Customer,49,Business travel,Business,678,3,4,4,4,4,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +29162,91041,Male,Loyal Customer,35,Personal Travel,Eco,366,2,5,2,2,5,2,1,5,4,4,2,4,1,5,5,18.0,neutral or dissatisfied +29163,37897,Male,Loyal Customer,63,Business travel,Eco,937,3,3,3,3,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +29164,52368,Male,Loyal Customer,12,Personal Travel,Eco,451,1,3,1,2,5,1,5,5,2,2,5,4,2,5,0,7.0,neutral or dissatisfied +29165,16879,Male,Loyal Customer,65,Business travel,Eco,746,2,4,1,4,2,2,2,2,4,5,3,1,4,2,0,8.0,neutral or dissatisfied +29166,82182,Female,Loyal Customer,41,Business travel,Business,1927,3,3,3,3,2,4,4,4,4,4,4,5,4,4,0,30.0,satisfied +29167,124388,Male,Loyal Customer,27,Personal Travel,Eco,808,4,1,4,3,5,4,5,5,1,5,3,3,4,5,0,0.0,satisfied +29168,87950,Male,Loyal Customer,38,Personal Travel,Business,240,2,4,2,4,2,4,4,4,4,2,1,3,4,3,0,0.0,neutral or dissatisfied +29169,38868,Male,Loyal Customer,47,Personal Travel,Eco,2300,2,4,2,2,5,2,5,5,3,4,3,4,4,5,0,0.0,neutral or dissatisfied +29170,79978,Male,Loyal Customer,44,Business travel,Business,1790,2,4,4,4,2,2,2,1,4,4,4,2,1,2,267,255.0,neutral or dissatisfied +29171,59756,Male,disloyal Customer,26,Business travel,Business,895,4,3,3,4,4,3,4,4,3,3,4,5,5,4,0,0.0,satisfied +29172,57106,Male,Loyal Customer,39,Business travel,Business,1222,2,2,2,2,3,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +29173,25639,Female,Loyal Customer,40,Personal Travel,Eco,666,2,4,2,3,3,2,5,3,2,5,4,4,3,3,41,40.0,neutral or dissatisfied +29174,8018,Female,Loyal Customer,50,Business travel,Business,2938,4,4,4,4,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +29175,28056,Male,Loyal Customer,43,Business travel,Business,2603,1,1,2,1,5,5,5,2,1,5,3,5,2,5,0,0.0,satisfied +29176,22487,Male,Loyal Customer,52,Personal Travel,Eco,238,1,4,1,4,4,1,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +29177,11528,Female,Loyal Customer,45,Personal Travel,Eco Plus,295,3,4,3,3,2,4,4,3,3,3,3,5,3,3,31,39.0,neutral or dissatisfied +29178,66330,Female,Loyal Customer,35,Business travel,Business,852,4,5,4,4,3,5,4,4,4,4,4,4,4,5,5,3.0,satisfied +29179,91325,Male,disloyal Customer,21,Business travel,Business,270,4,3,4,1,3,4,4,3,5,4,1,4,2,3,0,22.0,satisfied +29180,22668,Female,Loyal Customer,33,Business travel,Business,3413,2,2,2,2,1,4,5,4,4,4,4,1,4,4,57,65.0,satisfied +29181,79028,Male,disloyal Customer,33,Business travel,Business,356,2,2,2,1,1,2,1,1,5,4,5,5,4,1,3,5.0,neutral or dissatisfied +29182,52703,Female,Loyal Customer,25,Business travel,Eco Plus,562,0,4,0,3,4,0,5,4,1,4,3,3,5,4,0,3.0,satisfied +29183,29200,Male,Loyal Customer,21,Personal Travel,Eco Plus,954,3,4,3,1,1,3,1,1,2,5,3,2,1,1,0,0.0,neutral or dissatisfied +29184,107469,Male,Loyal Customer,51,Personal Travel,Eco,1121,2,5,2,3,2,2,2,2,3,4,4,3,4,2,7,0.0,neutral or dissatisfied +29185,95089,Male,Loyal Customer,37,Personal Travel,Eco,192,3,4,3,3,1,3,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +29186,10059,Male,Loyal Customer,47,Business travel,Business,1745,5,5,5,5,3,5,5,5,5,5,5,5,5,4,11,15.0,satisfied +29187,84828,Female,Loyal Customer,17,Business travel,Business,3567,4,4,4,4,4,4,4,4,4,4,4,4,4,4,21,17.0,neutral or dissatisfied +29188,81213,Male,Loyal Customer,38,Business travel,Eco,1426,3,3,3,3,3,4,3,3,1,4,3,2,2,3,54,32.0,neutral or dissatisfied +29189,8944,Male,Loyal Customer,51,Business travel,Eco,328,3,1,1,1,3,3,3,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +29190,101791,Female,disloyal Customer,30,Business travel,Business,1521,2,2,2,3,4,2,4,4,4,2,4,5,5,4,10,0.0,neutral or dissatisfied +29191,82811,Female,Loyal Customer,36,Personal Travel,Eco,235,1,4,0,1,5,0,5,5,3,5,4,5,5,5,0,7.0,neutral or dissatisfied +29192,59090,Female,Loyal Customer,42,Personal Travel,Eco,1723,2,4,2,3,5,5,5,3,3,2,3,3,3,4,32,21.0,neutral or dissatisfied +29193,28038,Female,Loyal Customer,29,Business travel,Business,2537,3,3,3,3,4,3,4,4,1,2,5,5,4,4,2,0.0,satisfied +29194,65437,Female,disloyal Customer,14,Business travel,Eco Plus,2165,3,2,3,4,5,3,5,5,4,2,2,3,3,5,0,0.0,neutral or dissatisfied +29195,96710,Male,Loyal Customer,53,Business travel,Business,2368,4,4,4,4,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +29196,84433,Female,Loyal Customer,39,Business travel,Business,3284,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,19.0,satisfied +29197,107004,Female,disloyal Customer,21,Business travel,Eco,972,3,3,3,3,2,3,2,2,5,2,5,4,4,2,6,0.0,neutral or dissatisfied +29198,14174,Female,Loyal Customer,36,Business travel,Eco,692,3,2,2,2,3,3,3,3,2,1,4,4,4,3,0,0.0,neutral or dissatisfied +29199,42384,Male,Loyal Customer,25,Personal Travel,Eco,834,3,4,3,4,5,3,5,5,3,4,4,4,4,5,49,39.0,neutral or dissatisfied +29200,30319,Female,Loyal Customer,41,Business travel,Business,1799,5,5,5,5,4,2,1,5,5,5,5,4,5,4,95,88.0,satisfied +29201,70873,Female,Loyal Customer,29,Personal Travel,Eco,761,3,5,3,3,4,3,4,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +29202,26008,Female,disloyal Customer,34,Business travel,Eco,425,4,1,3,1,4,3,4,4,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29203,127903,Male,disloyal Customer,25,Business travel,Eco,171,3,1,3,2,4,3,4,4,3,4,1,3,2,4,0,0.0,neutral or dissatisfied +29204,16862,Male,Loyal Customer,23,Business travel,Business,3573,5,5,5,5,4,4,4,4,3,1,2,3,1,4,3,0.0,satisfied +29205,107905,Male,Loyal Customer,54,Business travel,Business,2940,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +29206,26194,Female,Loyal Customer,38,Business travel,Business,2367,2,3,3,3,2,3,3,2,2,3,2,2,2,3,22,12.0,neutral or dissatisfied +29207,117475,Male,Loyal Customer,44,Business travel,Business,507,4,4,4,4,4,5,5,5,5,5,5,5,5,4,22,41.0,satisfied +29208,80856,Male,Loyal Customer,64,Personal Travel,Eco,484,0,3,0,4,4,0,4,4,4,3,2,4,4,4,0,0.0,satisfied +29209,69727,Female,Loyal Customer,60,Personal Travel,Eco,1372,4,5,5,2,3,4,4,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +29210,112067,Male,Loyal Customer,25,Personal Travel,Business,1491,4,4,4,4,3,4,1,3,4,2,4,4,4,3,22,21.0,neutral or dissatisfied +29211,78194,Male,Loyal Customer,42,Business travel,Eco,259,1,1,3,1,1,1,1,1,4,5,2,3,2,1,0,0.0,neutral or dissatisfied +29212,70814,Female,Loyal Customer,31,Business travel,Business,624,2,2,2,2,2,2,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +29213,83443,Female,Loyal Customer,32,Personal Travel,Eco,752,4,4,4,3,1,4,1,1,5,3,5,4,4,1,0,0.0,satisfied +29214,74717,Female,Loyal Customer,44,Personal Travel,Eco,1235,1,2,1,2,2,2,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +29215,103916,Female,Loyal Customer,52,Business travel,Business,533,3,3,3,3,5,5,4,5,5,5,5,3,5,4,7,3.0,satisfied +29216,11520,Female,Loyal Customer,33,Personal Travel,Eco Plus,667,3,5,3,1,1,3,1,1,5,4,4,3,4,1,47,53.0,neutral or dissatisfied +29217,55292,Male,Loyal Customer,32,Personal Travel,Eco,1608,3,5,4,3,3,4,3,3,5,4,5,3,4,3,8,4.0,neutral or dissatisfied +29218,72208,Male,Loyal Customer,15,Personal Travel,Eco,2724,4,4,4,2,4,4,4,4,5,3,4,4,3,4,0,0.0,satisfied +29219,19048,Male,disloyal Customer,20,Business travel,Eco,304,3,2,3,3,2,3,2,2,2,3,3,4,2,2,91,119.0,neutral or dissatisfied +29220,95938,Male,Loyal Customer,39,Business travel,Business,1411,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +29221,6677,Female,Loyal Customer,61,Business travel,Business,403,4,4,4,4,3,5,4,5,5,4,5,5,5,3,0,16.0,satisfied +29222,122948,Male,Loyal Customer,25,Business travel,Business,2307,3,3,3,3,5,5,5,5,3,5,4,4,4,5,27,26.0,satisfied +29223,86878,Male,Loyal Customer,34,Business travel,Eco Plus,484,4,2,2,2,4,4,4,4,5,4,5,1,5,4,0,0.0,satisfied +29224,19626,Female,Loyal Customer,29,Business travel,Business,2118,3,3,2,3,5,5,5,1,2,2,5,5,5,5,158,164.0,satisfied +29225,45112,Male,disloyal Customer,80,Business travel,Eco,157,1,1,1,2,1,4,4,3,1,2,2,4,1,4,144,130.0,neutral or dissatisfied +29226,106394,Male,Loyal Customer,22,Business travel,Business,551,1,3,3,3,1,1,1,1,3,5,4,2,4,1,6,5.0,neutral or dissatisfied +29227,75809,Female,disloyal Customer,25,Business travel,Business,813,3,0,3,1,1,3,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +29228,124318,Female,Loyal Customer,20,Personal Travel,Eco,255,4,3,0,3,3,0,3,3,5,4,4,2,1,3,0,0.0,neutral or dissatisfied +29229,96823,Male,Loyal Customer,52,Business travel,Business,849,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,6.0,satisfied +29230,20619,Male,Loyal Customer,48,Personal Travel,Eco,864,2,5,2,1,1,2,2,1,4,4,4,4,5,1,40,62.0,neutral or dissatisfied +29231,106891,Male,Loyal Customer,10,Personal Travel,Eco,577,2,4,2,4,4,2,4,4,5,3,5,4,5,4,43,34.0,neutral or dissatisfied +29232,123894,Male,Loyal Customer,23,Personal Travel,Eco,544,3,1,3,4,5,3,5,5,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +29233,121864,Male,disloyal Customer,45,Business travel,Eco,449,3,2,3,2,2,3,2,2,4,3,2,3,2,2,64,52.0,neutral or dissatisfied +29234,9951,Male,disloyal Customer,17,Business travel,Eco,457,2,3,2,3,4,2,4,4,1,5,3,2,3,4,112,113.0,neutral or dissatisfied +29235,90737,Female,Loyal Customer,59,Business travel,Business,404,3,3,3,3,4,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +29236,42028,Female,Loyal Customer,42,Business travel,Business,106,4,4,4,4,4,2,5,5,5,5,4,1,5,4,0,0.0,satisfied +29237,80166,Female,Loyal Customer,29,Business travel,Business,2446,2,3,2,2,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +29238,103787,Female,Loyal Customer,45,Business travel,Business,1056,5,5,5,5,2,5,4,5,5,5,5,4,5,5,38,37.0,satisfied +29239,84842,Male,disloyal Customer,29,Business travel,Eco,516,3,1,3,4,1,3,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +29240,53714,Female,Loyal Customer,29,Personal Travel,Eco,1208,2,1,2,2,2,2,2,2,4,1,2,4,2,2,7,3.0,neutral or dissatisfied +29241,2375,Female,disloyal Customer,16,Business travel,Eco,604,4,3,3,4,2,3,2,2,1,1,3,4,3,2,0,0.0,neutral or dissatisfied +29242,81264,Female,disloyal Customer,29,Business travel,Business,1020,3,3,3,3,4,3,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +29243,11624,Female,Loyal Customer,28,Personal Travel,Eco,468,4,5,4,4,4,4,5,4,5,4,2,3,2,4,0,0.0,satisfied +29244,56428,Female,Loyal Customer,37,Business travel,Business,1500,2,2,2,2,3,4,4,2,2,2,2,3,2,5,6,0.0,satisfied +29245,61914,Female,Loyal Customer,43,Business travel,Business,2940,1,1,1,1,3,5,5,5,5,5,5,5,5,5,13,3.0,satisfied +29246,45711,Female,Loyal Customer,39,Business travel,Business,3879,1,1,2,1,2,5,5,5,5,5,5,2,5,2,0,0.0,satisfied +29247,110307,Male,Loyal Customer,49,Business travel,Business,2600,5,5,5,5,2,5,5,2,2,2,2,4,2,5,9,1.0,satisfied +29248,63924,Male,Loyal Customer,59,Personal Travel,Eco,1172,3,4,3,2,2,3,2,2,4,5,5,3,4,2,0,8.0,neutral or dissatisfied +29249,53187,Male,Loyal Customer,43,Business travel,Business,2732,2,2,2,2,5,2,1,4,4,4,4,5,4,2,12,2.0,satisfied +29250,62380,Male,disloyal Customer,11,Business travel,Eco,1210,2,2,2,4,4,2,4,4,3,3,2,3,4,4,91,61.0,neutral or dissatisfied +29251,74858,Female,Loyal Customer,56,Business travel,Business,1995,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,14.0,satisfied +29252,54546,Female,Loyal Customer,8,Personal Travel,Eco,925,4,4,4,3,3,4,4,3,5,5,5,3,1,3,0,0.0,neutral or dissatisfied +29253,123952,Female,Loyal Customer,17,Business travel,Eco Plus,646,2,3,3,3,2,2,4,2,4,1,3,4,4,2,0,2.0,neutral or dissatisfied +29254,80014,Female,Loyal Customer,59,Personal Travel,Eco,944,2,4,3,2,5,5,4,4,4,3,4,2,4,1,3,0.0,neutral or dissatisfied +29255,68077,Male,disloyal Customer,36,Business travel,Eco,868,2,2,2,3,2,2,1,2,2,3,4,3,3,2,0,2.0,neutral or dissatisfied +29256,114211,Female,Loyal Customer,48,Business travel,Business,853,3,3,3,3,2,4,5,1,1,2,1,3,1,3,0,0.0,satisfied +29257,52402,Female,Loyal Customer,41,Personal Travel,Eco,425,4,1,4,4,2,4,3,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +29258,123282,Male,Loyal Customer,55,Personal Travel,Eco,468,1,4,1,3,4,1,3,4,5,4,4,5,4,4,9,14.0,neutral or dissatisfied +29259,14529,Female,Loyal Customer,43,Business travel,Business,2150,3,5,3,3,3,2,1,5,5,5,5,1,5,5,25,15.0,satisfied +29260,66894,Female,disloyal Customer,29,Business travel,Business,918,4,4,4,3,4,4,4,4,4,1,2,2,2,4,0,0.0,neutral or dissatisfied +29261,112863,Male,Loyal Customer,52,Business travel,Business,1242,1,1,1,1,3,5,4,5,5,5,5,5,5,5,5,0.0,satisfied +29262,73140,Female,Loyal Customer,29,Personal Travel,Eco,1068,4,5,4,1,5,4,5,5,3,2,4,4,4,5,40,44.0,neutral or dissatisfied +29263,114527,Male,Loyal Customer,7,Personal Travel,Business,342,4,4,4,3,4,4,4,4,5,5,5,3,5,4,3,0.0,neutral or dissatisfied +29264,1781,Female,disloyal Customer,42,Business travel,Business,408,5,5,5,2,5,1,1,3,5,4,4,1,3,1,184,217.0,satisfied +29265,101212,Female,Loyal Customer,32,Personal Travel,Eco,1069,4,5,4,1,2,4,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +29266,126433,Female,Loyal Customer,34,Personal Travel,Eco Plus,600,2,3,2,2,5,2,4,5,3,4,2,4,2,5,0,0.0,neutral or dissatisfied +29267,28599,Male,Loyal Customer,48,Business travel,Business,1845,4,4,4,4,4,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +29268,59087,Female,Loyal Customer,76,Business travel,Eco,346,5,3,3,3,1,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +29269,40456,Female,Loyal Customer,71,Business travel,Business,2939,1,1,1,1,5,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +29270,22233,Male,Loyal Customer,46,Business travel,Business,3053,1,1,1,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +29271,97685,Male,Loyal Customer,37,Business travel,Business,2282,5,5,5,5,3,4,4,2,2,2,2,5,2,5,20,8.0,satisfied +29272,79007,Female,disloyal Customer,61,Business travel,Business,226,4,4,4,2,1,4,1,1,3,2,5,5,5,1,0,0.0,satisfied +29273,11939,Female,disloyal Customer,29,Business travel,Business,781,4,4,4,5,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +29274,92355,Female,Loyal Customer,27,Personal Travel,Eco,2556,4,4,4,3,5,4,5,5,4,5,5,4,5,5,3,0.0,neutral or dissatisfied +29275,19835,Female,Loyal Customer,51,Personal Travel,Eco,632,4,3,4,3,5,3,3,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +29276,8518,Female,disloyal Customer,45,Personal Travel,Eco,737,5,2,5,3,2,5,2,2,2,5,4,3,4,2,0,0.0,satisfied +29277,58591,Female,Loyal Customer,43,Business travel,Eco,334,1,5,5,5,5,3,4,1,1,1,1,4,1,4,46,40.0,neutral or dissatisfied +29278,114478,Female,disloyal Customer,33,Business travel,Business,342,2,2,2,3,5,2,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +29279,121588,Female,Loyal Customer,40,Business travel,Eco,512,4,3,3,3,4,4,4,4,4,3,1,5,3,4,0,0.0,satisfied +29280,82074,Female,Loyal Customer,38,Business travel,Business,2281,3,3,3,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +29281,104871,Female,Loyal Customer,61,Business travel,Eco,327,2,2,5,5,2,4,4,2,2,2,2,2,2,2,37,30.0,neutral or dissatisfied +29282,67540,Male,Loyal Customer,60,Business travel,Business,1703,4,5,5,5,5,4,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +29283,56786,Male,Loyal Customer,48,Personal Travel,Eco Plus,937,0,2,0,4,1,0,1,1,3,1,3,3,4,1,0,0.0,satisfied +29284,95164,Male,Loyal Customer,69,Personal Travel,Eco,458,1,4,1,1,5,1,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +29285,115965,Male,Loyal Customer,11,Personal Travel,Eco,404,2,5,2,3,2,2,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +29286,76604,Male,Loyal Customer,11,Business travel,Business,3338,5,5,5,5,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +29287,63233,Male,disloyal Customer,58,Business travel,Business,372,4,4,4,4,5,4,5,5,4,3,4,3,4,5,0,0.0,satisfied +29288,129284,Female,Loyal Customer,56,Business travel,Business,1581,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +29289,106670,Female,Loyal Customer,43,Business travel,Business,451,3,3,3,3,5,4,3,3,3,3,3,1,3,2,109,99.0,neutral or dissatisfied +29290,81858,Male,Loyal Customer,17,Business travel,Eco Plus,1306,1,3,3,3,1,1,2,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +29291,123839,Female,Loyal Customer,29,Business travel,Business,1855,2,5,5,5,2,2,2,2,3,3,4,1,4,2,7,1.0,neutral or dissatisfied +29292,105026,Male,Loyal Customer,36,Business travel,Business,255,5,1,5,5,2,4,4,4,4,4,4,4,4,4,12,0.0,satisfied +29293,89910,Male,disloyal Customer,12,Business travel,Business,1310,4,4,4,5,3,4,3,3,4,4,4,5,5,3,0,0.0,satisfied +29294,76624,Female,disloyal Customer,25,Business travel,Eco,481,3,3,3,4,1,3,3,1,1,3,3,2,2,1,71,62.0,neutral or dissatisfied +29295,55627,Male,Loyal Customer,33,Business travel,Business,1824,1,2,2,2,1,1,1,1,4,2,1,1,2,1,0,0.0,neutral or dissatisfied +29296,34363,Male,Loyal Customer,32,Personal Travel,Eco,541,2,4,2,3,2,2,5,2,4,4,3,3,5,2,0,0.0,neutral or dissatisfied +29297,18793,Male,disloyal Customer,21,Business travel,Eco,500,4,0,4,2,2,4,2,2,4,3,3,2,5,2,0,0.0,satisfied +29298,10952,Male,Loyal Customer,44,Business travel,Business,312,5,5,5,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +29299,114545,Female,Loyal Customer,48,Personal Travel,Business,404,1,5,1,3,5,5,4,4,4,1,4,3,4,4,1,0.0,neutral or dissatisfied +29300,116237,Male,Loyal Customer,47,Personal Travel,Eco,446,2,5,2,2,2,2,2,2,4,3,5,4,5,2,40,34.0,neutral or dissatisfied +29301,60163,Male,Loyal Customer,10,Personal Travel,Eco,1050,4,5,3,2,3,3,4,3,5,5,4,3,5,3,0,0.0,satisfied +29302,54963,Male,Loyal Customer,56,Business travel,Business,1379,5,5,4,5,3,4,4,4,4,4,4,5,4,4,0,13.0,satisfied +29303,67496,Female,Loyal Customer,60,Personal Travel,Eco Plus,592,3,5,3,4,3,5,3,2,2,3,4,3,2,1,0,0.0,neutral or dissatisfied +29304,75967,Female,Loyal Customer,54,Business travel,Eco,297,2,5,5,5,1,4,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +29305,7331,Male,Loyal Customer,42,Business travel,Business,3499,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +29306,60660,Male,Loyal Customer,61,Personal Travel,Eco,1620,4,4,4,3,2,4,2,2,5,5,5,5,4,2,2,5.0,satisfied +29307,43423,Female,Loyal Customer,63,Personal Travel,Eco Plus,402,1,5,1,3,5,4,4,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +29308,126083,Male,disloyal Customer,20,Business travel,Eco,507,3,4,3,4,4,3,3,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +29309,58027,Male,Loyal Customer,54,Personal Travel,Eco,1721,3,1,3,3,2,3,2,2,2,4,1,1,3,2,6,9.0,neutral or dissatisfied +29310,9358,Female,disloyal Customer,39,Business travel,Business,384,5,5,5,3,3,5,1,3,5,3,4,4,4,3,14,2.0,satisfied +29311,90371,Female,Loyal Customer,51,Business travel,Business,270,2,4,4,4,1,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29312,15843,Female,Loyal Customer,30,Business travel,Business,1761,3,1,1,1,3,3,3,3,4,4,4,2,3,3,0,0.0,neutral or dissatisfied +29313,59432,Female,Loyal Customer,59,Personal Travel,Eco Plus,2447,2,0,2,4,3,5,5,5,5,2,5,5,5,5,8,0.0,neutral or dissatisfied +29314,8153,Male,Loyal Customer,44,Business travel,Business,1609,3,2,2,2,5,2,3,3,3,2,3,1,3,4,22,19.0,neutral or dissatisfied +29315,17911,Male,Loyal Customer,36,Business travel,Business,789,4,3,3,3,4,3,2,4,4,3,4,1,4,3,0,13.0,neutral or dissatisfied +29316,64401,Female,Loyal Customer,46,Business travel,Business,2154,5,5,5,5,4,4,4,3,3,4,3,4,3,4,2,0.0,satisfied +29317,67893,Female,Loyal Customer,41,Personal Travel,Eco,1188,4,1,5,3,1,5,1,1,4,4,4,2,3,1,1,0.0,satisfied +29318,28993,Female,Loyal Customer,26,Business travel,Business,605,1,1,2,1,5,5,5,5,4,2,1,2,3,5,0,0.0,satisfied +29319,59418,Female,Loyal Customer,28,Personal Travel,Eco,2447,3,5,3,2,2,3,2,2,3,5,4,1,1,2,0,0.0,neutral or dissatisfied +29320,28955,Male,disloyal Customer,23,Business travel,Eco,987,3,3,3,3,5,3,5,5,2,5,4,2,3,5,24,14.0,neutral or dissatisfied +29321,43191,Male,disloyal Customer,25,Business travel,Eco,651,3,2,3,3,5,3,5,5,3,2,3,2,3,5,0,3.0,neutral or dissatisfied +29322,73520,Female,disloyal Customer,36,Business travel,Business,194,2,3,3,4,2,3,2,2,3,4,3,2,3,2,57,48.0,neutral or dissatisfied +29323,58201,Female,disloyal Customer,20,Business travel,Eco,925,4,4,4,3,5,4,5,5,4,1,4,4,4,5,38,62.0,neutral or dissatisfied +29324,108920,Male,Loyal Customer,18,Personal Travel,Eco,1243,4,1,4,3,2,4,4,2,2,5,1,3,2,2,2,0.0,neutral or dissatisfied +29325,62210,Male,Loyal Customer,21,Personal Travel,Eco,2454,1,3,1,3,1,1,1,1,2,3,3,2,4,1,30,23.0,neutral or dissatisfied +29326,23387,Female,disloyal Customer,24,Business travel,Eco,300,4,3,4,3,4,4,4,4,3,4,3,1,5,4,0,0.0,neutral or dissatisfied +29327,12794,Female,disloyal Customer,20,Business travel,Eco,641,1,3,0,2,2,0,2,2,2,4,1,3,5,2,17,16.0,neutral or dissatisfied +29328,123683,Female,disloyal Customer,42,Business travel,Eco,214,3,2,3,3,4,3,1,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +29329,32083,Female,Loyal Customer,28,Business travel,Business,1706,0,4,0,3,5,5,5,5,1,5,4,1,2,5,0,0.0,satisfied +29330,118723,Female,Loyal Customer,70,Personal Travel,Eco,368,2,4,2,4,3,2,3,4,4,2,2,2,4,4,19,21.0,neutral or dissatisfied +29331,109502,Male,Loyal Customer,53,Business travel,Business,3146,4,4,4,4,2,5,4,4,4,4,4,5,4,3,55,50.0,satisfied +29332,12842,Female,Loyal Customer,70,Personal Travel,Eco,817,2,5,2,4,4,5,4,4,4,2,2,3,4,3,0,0.0,neutral or dissatisfied +29333,38781,Female,Loyal Customer,45,Business travel,Business,2326,5,5,5,5,5,4,3,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +29334,113057,Male,Loyal Customer,59,Business travel,Business,1722,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +29335,83356,Female,Loyal Customer,58,Business travel,Business,3677,1,1,1,1,4,4,5,5,5,5,5,4,5,4,0,4.0,satisfied +29336,109975,Male,disloyal Customer,45,Personal Travel,Eco,1052,3,5,3,2,2,3,2,2,4,4,4,5,5,2,16,4.0,neutral or dissatisfied +29337,6759,Male,Loyal Customer,46,Business travel,Business,2989,0,0,0,2,3,4,4,3,3,3,3,5,3,5,31,34.0,satisfied +29338,30409,Female,Loyal Customer,23,Personal Travel,Eco,641,4,5,4,2,2,4,2,2,3,3,4,4,4,2,0,1.0,neutral or dissatisfied +29339,102677,Male,disloyal Customer,21,Business travel,Eco,601,3,0,3,2,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +29340,125173,Female,Loyal Customer,16,Personal Travel,Eco,1089,2,2,2,3,5,2,5,5,2,4,4,2,4,5,0,0.0,neutral or dissatisfied +29341,81621,Male,Loyal Customer,41,Business travel,Business,1142,2,2,2,2,4,5,5,5,5,5,5,5,5,4,13,19.0,satisfied +29342,115549,Female,disloyal Customer,36,Business travel,Eco,308,2,2,1,4,3,1,5,3,4,5,4,2,3,3,51,44.0,neutral or dissatisfied +29343,34872,Female,Loyal Customer,58,Business travel,Business,2248,4,4,4,4,2,4,1,4,4,4,4,4,4,4,0,0.0,satisfied +29344,39373,Male,disloyal Customer,26,Business travel,Business,521,4,4,4,1,5,4,5,5,5,3,5,5,5,5,0,0.0,satisfied +29345,110099,Male,disloyal Customer,29,Business travel,Business,1072,3,3,3,3,3,3,3,3,4,5,4,5,5,3,8,0.0,neutral or dissatisfied +29346,120229,Male,disloyal Customer,38,Business travel,Eco,925,1,1,1,4,1,5,5,1,4,4,4,5,2,5,203,152.0,neutral or dissatisfied +29347,77377,Male,Loyal Customer,39,Business travel,Business,599,5,5,3,5,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +29348,39902,Female,disloyal Customer,44,Business travel,Eco Plus,272,1,0,0,2,3,1,3,3,5,1,4,2,1,3,4,3.0,neutral or dissatisfied +29349,29206,Male,Loyal Customer,44,Business travel,Business,2311,2,2,2,2,4,4,3,5,5,5,5,4,5,5,14,0.0,satisfied +29350,82670,Female,Loyal Customer,47,Business travel,Business,2801,4,4,4,4,2,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +29351,53754,Female,disloyal Customer,39,Business travel,Business,1195,4,5,5,5,1,5,1,1,1,4,3,3,5,1,10,6.0,neutral or dissatisfied +29352,11374,Male,Loyal Customer,29,Personal Travel,Eco,74,3,4,3,4,2,3,2,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +29353,77012,Male,Loyal Customer,53,Business travel,Business,2528,5,5,5,5,2,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +29354,101539,Female,Loyal Customer,49,Personal Travel,Eco,345,2,4,2,3,3,4,4,5,5,2,3,3,5,3,6,0.0,neutral or dissatisfied +29355,27532,Female,Loyal Customer,28,Personal Travel,Eco,954,2,4,2,3,3,2,3,3,5,2,5,5,4,3,0,1.0,neutral or dissatisfied +29356,3416,Male,Loyal Customer,9,Personal Travel,Eco,296,2,1,2,4,4,2,5,4,2,5,4,1,3,4,0,0.0,neutral or dissatisfied +29357,37266,Male,Loyal Customer,25,Business travel,Business,1056,1,1,1,1,4,4,4,4,2,2,2,3,5,4,14,11.0,satisfied +29358,70205,Female,Loyal Customer,13,Personal Travel,Eco,403,2,3,2,2,1,2,1,1,5,2,1,2,5,1,0,4.0,neutral or dissatisfied +29359,67606,Female,Loyal Customer,29,Business travel,Business,2410,5,1,5,5,3,4,3,3,5,3,5,4,5,3,30,56.0,satisfied +29360,79933,Male,Loyal Customer,53,Business travel,Business,1096,5,5,5,5,4,5,4,5,5,5,5,5,5,4,1,0.0,satisfied +29361,19343,Male,Loyal Customer,24,Personal Travel,Eco,694,3,5,2,1,3,2,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +29362,96340,Male,Loyal Customer,28,Business travel,Business,1609,2,2,2,2,2,2,2,2,5,5,5,5,4,2,11,0.0,satisfied +29363,107135,Female,Loyal Customer,32,Business travel,Eco Plus,842,3,1,1,1,3,3,3,3,3,4,3,3,2,3,25,10.0,neutral or dissatisfied +29364,69208,Female,Loyal Customer,55,Business travel,Business,2861,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +29365,23942,Male,Loyal Customer,22,Business travel,Business,2891,4,4,4,4,5,5,5,5,4,1,1,4,3,5,38,20.0,satisfied +29366,92519,Male,Loyal Customer,24,Personal Travel,Eco,1947,2,4,2,4,1,2,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +29367,121610,Male,Loyal Customer,13,Personal Travel,Eco,912,2,5,2,3,1,2,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +29368,126612,Female,Loyal Customer,49,Personal Travel,Eco,1337,1,5,2,3,3,5,4,4,4,2,1,5,4,5,0,15.0,neutral or dissatisfied +29369,178,Male,Loyal Customer,28,Personal Travel,Eco Plus,227,2,1,2,4,4,2,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +29370,67200,Female,Loyal Customer,69,Personal Travel,Eco,1017,4,4,5,4,4,4,4,1,1,5,2,1,1,2,0,0.0,neutral or dissatisfied +29371,4571,Male,Loyal Customer,37,Business travel,Business,561,3,3,3,3,3,4,4,4,4,4,4,4,4,4,7,0.0,satisfied +29372,127617,Female,Loyal Customer,40,Business travel,Eco,1773,3,3,3,3,3,3,3,3,2,1,1,2,2,3,0,0.0,neutral or dissatisfied +29373,57862,Male,Loyal Customer,52,Business travel,Business,2457,4,4,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +29374,6472,Male,Loyal Customer,62,Personal Travel,Eco Plus,213,2,4,2,4,3,2,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +29375,101348,Female,Loyal Customer,26,Personal Travel,Eco,2026,3,4,3,5,2,3,4,2,4,4,4,5,4,2,5,0.0,neutral or dissatisfied +29376,127402,Female,Loyal Customer,52,Business travel,Business,2655,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +29377,92913,Male,Loyal Customer,68,Business travel,Eco,134,1,1,1,1,1,1,1,1,2,4,3,4,2,1,0,20.0,neutral or dissatisfied +29378,89970,Male,Loyal Customer,37,Personal Travel,Eco,1416,3,4,3,5,4,3,4,4,4,3,4,5,5,4,0,6.0,neutral or dissatisfied +29379,125266,Male,Loyal Customer,23,Business travel,Business,1488,3,4,4,4,3,3,3,3,1,2,3,4,2,3,7,14.0,neutral or dissatisfied +29380,3737,Female,Loyal Customer,51,Personal Travel,Eco,427,4,4,4,2,5,4,5,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +29381,122975,Female,Loyal Customer,40,Business travel,Business,1710,1,1,5,1,4,5,5,3,3,3,3,4,3,3,7,49.0,satisfied +29382,46183,Male,Loyal Customer,34,Personal Travel,Eco Plus,604,5,5,5,2,3,5,2,3,3,3,4,3,4,3,0,0.0,satisfied +29383,39281,Male,Loyal Customer,27,Business travel,Business,67,0,5,0,3,3,1,1,3,2,2,1,2,1,3,0,8.0,satisfied +29384,7163,Male,Loyal Customer,41,Business travel,Business,135,2,2,4,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +29385,75645,Male,Loyal Customer,21,Business travel,Business,3379,1,2,3,3,1,1,1,1,1,3,4,1,3,1,0,0.0,neutral or dissatisfied +29386,31381,Male,Loyal Customer,43,Business travel,Eco,834,4,5,5,5,4,4,4,4,1,1,2,3,1,4,5,33.0,satisfied +29387,76354,Female,Loyal Customer,33,Business travel,Business,1851,3,3,3,3,4,1,1,3,3,3,3,2,3,3,10,19.0,neutral or dissatisfied +29388,3727,Male,Loyal Customer,24,Personal Travel,Eco,431,1,5,1,4,5,1,3,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +29389,59671,Female,Loyal Customer,22,Personal Travel,Eco,965,1,4,2,5,3,2,3,3,5,5,4,4,4,3,26,8.0,neutral or dissatisfied +29390,99567,Male,Loyal Customer,59,Business travel,Business,2270,5,5,5,5,2,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +29391,118337,Female,Loyal Customer,52,Business travel,Business,2978,4,5,5,5,3,4,4,2,2,2,4,2,2,3,12,11.0,neutral or dissatisfied +29392,2151,Female,Loyal Customer,12,Business travel,Business,2199,3,2,4,2,3,3,3,3,4,4,4,1,3,3,12,27.0,neutral or dissatisfied +29393,39073,Male,Loyal Customer,30,Business travel,Business,2474,4,4,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +29394,62317,Female,disloyal Customer,26,Business travel,Eco,414,3,2,3,1,1,3,1,1,2,5,2,3,1,1,3,0.0,neutral or dissatisfied +29395,47623,Male,Loyal Customer,48,Business travel,Business,1464,5,5,3,5,3,3,1,5,5,5,5,3,5,4,59,44.0,satisfied +29396,81894,Male,Loyal Customer,26,Business travel,Business,2408,1,1,1,1,1,1,1,1,4,1,4,2,3,1,88,82.0,neutral or dissatisfied +29397,28042,Male,Loyal Customer,34,Business travel,Eco Plus,2537,5,4,4,4,5,5,5,5,2,1,5,2,2,5,0,0.0,satisfied +29398,106353,Female,disloyal Customer,23,Business travel,Eco,551,2,0,2,3,2,2,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +29399,69872,Male,Loyal Customer,30,Personal Travel,Eco Plus,1345,2,2,3,2,5,3,5,5,3,3,3,4,2,5,3,0.0,neutral or dissatisfied +29400,91709,Female,Loyal Customer,48,Business travel,Business,3409,3,2,3,3,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +29401,52695,Male,Loyal Customer,54,Personal Travel,Eco Plus,119,1,3,1,4,2,1,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +29402,54743,Female,Loyal Customer,47,Personal Travel,Eco,787,2,1,2,3,2,4,4,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +29403,87410,Male,Loyal Customer,27,Personal Travel,Eco,425,1,3,1,2,5,1,5,5,3,3,3,1,2,5,0,0.0,neutral or dissatisfied +29404,73636,Male,Loyal Customer,57,Business travel,Business,204,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +29405,26914,Male,Loyal Customer,45,Business travel,Eco,1774,4,5,5,5,4,4,4,4,2,4,4,2,4,4,0,0.0,satisfied +29406,77067,Female,disloyal Customer,28,Business travel,Eco,991,3,3,3,3,4,3,5,4,1,1,3,4,4,4,6,0.0,neutral or dissatisfied +29407,24566,Female,Loyal Customer,19,Personal Travel,Eco,874,4,1,4,3,2,4,2,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +29408,92043,Male,disloyal Customer,46,Business travel,Business,1589,2,2,2,4,4,2,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +29409,60834,Female,Loyal Customer,48,Business travel,Business,1754,5,3,5,5,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +29410,71998,Male,Loyal Customer,48,Personal Travel,Eco,1437,3,4,4,3,2,4,3,2,3,5,3,5,5,2,53,50.0,neutral or dissatisfied +29411,70138,Female,Loyal Customer,30,Personal Travel,Eco,460,3,2,1,3,2,1,2,2,4,5,3,4,4,2,0,1.0,neutral or dissatisfied +29412,1855,Female,Loyal Customer,67,Personal Travel,Business,931,2,5,2,2,2,4,5,2,2,2,2,5,2,4,47,52.0,neutral or dissatisfied +29413,42649,Male,Loyal Customer,35,Personal Travel,Eco,546,1,4,1,5,3,1,3,3,2,5,3,3,4,3,10,0.0,neutral or dissatisfied +29414,117827,Male,Loyal Customer,55,Personal Travel,Eco,328,4,1,3,4,4,3,4,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +29415,49998,Female,Loyal Customer,32,Business travel,Business,2643,2,3,1,3,2,2,2,2,1,2,2,3,2,2,0,26.0,neutral or dissatisfied +29416,83918,Male,Loyal Customer,39,Business travel,Business,2481,2,2,2,2,4,5,5,5,5,5,5,3,5,4,15,0.0,satisfied +29417,61269,Female,Loyal Customer,28,Personal Travel,Eco,967,3,5,3,1,3,3,3,3,4,4,4,4,5,3,13,20.0,neutral or dissatisfied +29418,69554,Female,Loyal Customer,53,Business travel,Business,2475,3,3,5,3,2,3,3,4,4,4,5,3,4,3,0,3.0,satisfied +29419,45835,Male,Loyal Customer,25,Personal Travel,Eco,391,2,2,2,4,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +29420,33138,Female,Loyal Customer,19,Personal Travel,Eco,101,1,5,1,3,1,1,1,1,1,2,4,3,4,1,0,0.0,neutral or dissatisfied +29421,20247,Female,Loyal Customer,45,Business travel,Business,1886,3,5,5,5,5,3,2,3,3,3,3,1,3,2,9,14.0,neutral or dissatisfied +29422,6117,Female,Loyal Customer,58,Business travel,Business,3085,5,5,5,5,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +29423,67412,Female,Loyal Customer,57,Business travel,Business,3282,1,1,1,1,2,4,4,4,4,4,4,3,4,4,1,2.0,satisfied +29424,2853,Female,Loyal Customer,60,Business travel,Business,409,1,1,4,1,4,4,4,5,4,5,4,4,4,4,105,136.0,satisfied +29425,34489,Male,Loyal Customer,40,Business travel,Business,1990,4,4,4,4,1,5,3,5,5,5,5,5,5,1,11,5.0,satisfied +29426,43663,Male,Loyal Customer,24,Business travel,Eco,695,4,4,4,4,4,4,3,4,1,2,5,1,4,4,0,1.0,satisfied +29427,120882,Male,disloyal Customer,39,Business travel,Business,920,4,3,3,1,3,1,5,3,2,4,4,5,5,5,113,171.0,neutral or dissatisfied +29428,128444,Female,disloyal Customer,23,Business travel,Eco,647,1,4,1,3,4,1,4,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +29429,49614,Female,Loyal Customer,42,Business travel,Business,89,0,4,0,1,4,4,5,3,3,3,3,5,3,1,0,0.0,satisfied +29430,70720,Male,Loyal Customer,46,Business travel,Business,675,3,3,3,3,2,5,5,4,4,4,4,5,4,3,18,20.0,satisfied +29431,20182,Male,Loyal Customer,17,Personal Travel,Eco,403,2,4,2,4,1,2,1,1,4,2,4,3,4,1,7,3.0,neutral or dissatisfied +29432,40671,Male,Loyal Customer,36,Personal Travel,Business,588,2,4,3,1,5,1,3,3,3,3,3,4,3,2,2,0.0,neutral or dissatisfied +29433,42787,Female,Loyal Customer,54,Business travel,Business,2833,3,3,3,3,1,2,3,5,5,5,5,5,5,4,0,0.0,satisfied +29434,47954,Female,Loyal Customer,49,Personal Travel,Eco,838,2,4,2,3,2,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +29435,28952,Female,Loyal Customer,23,Business travel,Business,697,3,2,3,3,5,5,5,5,3,3,3,2,2,5,0,0.0,satisfied +29436,50284,Male,Loyal Customer,37,Business travel,Business,1706,3,3,3,3,3,3,5,4,4,4,3,1,4,4,0,0.0,satisfied +29437,121693,Female,Loyal Customer,48,Business travel,Eco Plus,511,1,1,1,1,2,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +29438,108454,Female,Loyal Customer,43,Business travel,Eco,1444,2,1,3,1,5,3,4,2,2,2,2,2,2,1,1,6.0,neutral or dissatisfied +29439,41662,Male,Loyal Customer,32,Business travel,Business,347,2,2,2,2,4,4,4,4,3,1,4,3,4,4,0,0.0,satisfied +29440,26472,Female,Loyal Customer,60,Personal Travel,Eco,842,3,5,3,5,2,1,5,1,1,3,1,4,1,4,89,94.0,neutral or dissatisfied +29441,43581,Female,Loyal Customer,42,Personal Travel,Eco,1499,3,3,3,2,4,1,1,5,5,3,5,1,5,1,2,0.0,neutral or dissatisfied +29442,116752,Male,Loyal Customer,38,Personal Travel,Eco Plus,372,2,0,2,2,2,2,2,2,3,3,3,3,5,2,7,0.0,neutral or dissatisfied +29443,69296,Male,Loyal Customer,45,Personal Travel,Eco Plus,733,3,4,3,1,2,3,2,2,4,3,3,1,2,2,43,43.0,neutral or dissatisfied +29444,67916,Male,Loyal Customer,21,Personal Travel,Eco,1235,2,5,2,5,1,2,1,1,4,5,5,5,4,1,6,0.0,neutral or dissatisfied +29445,41337,Male,Loyal Customer,33,Personal Travel,Eco,689,2,2,2,3,3,2,3,3,4,1,2,2,2,3,0,0.0,neutral or dissatisfied +29446,95025,Male,Loyal Customer,59,Personal Travel,Eco,293,3,3,3,4,3,3,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +29447,334,Male,disloyal Customer,26,Business travel,Eco,421,3,5,3,2,1,3,1,1,4,4,1,1,4,1,0,0.0,neutral or dissatisfied +29448,123596,Female,Loyal Customer,52,Personal Travel,Eco,1773,3,4,3,4,4,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +29449,92812,Male,Loyal Customer,44,Business travel,Business,1587,4,4,4,4,2,3,5,1,1,2,1,4,1,3,0,0.0,satisfied +29450,929,Male,Loyal Customer,34,Business travel,Business,158,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +29451,68939,Female,disloyal Customer,7,Business travel,Eco,646,2,5,2,3,2,2,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +29452,61478,Female,disloyal Customer,27,Business travel,Business,805,0,0,0,2,1,0,1,1,5,3,3,4,4,1,0,5.0,satisfied +29453,113013,Female,disloyal Customer,35,Business travel,Business,1751,4,3,3,4,2,3,2,2,3,2,3,4,4,2,10,0.0,neutral or dissatisfied +29454,39803,Female,disloyal Customer,22,Business travel,Eco,221,2,0,2,4,4,2,5,4,1,3,5,3,5,4,0,11.0,neutral or dissatisfied +29455,95093,Female,Loyal Customer,20,Personal Travel,Eco,239,1,5,1,5,5,1,3,5,3,3,5,4,4,5,30,31.0,neutral or dissatisfied +29456,123091,Male,Loyal Customer,26,Business travel,Eco,590,1,5,5,5,1,1,3,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +29457,80535,Male,Loyal Customer,26,Business travel,Eco Plus,1678,3,1,1,1,3,3,1,3,4,2,3,4,3,3,24,13.0,neutral or dissatisfied +29458,57320,Male,disloyal Customer,25,Business travel,Business,414,2,5,2,3,1,2,1,1,4,4,5,3,5,1,5,4.0,neutral or dissatisfied +29459,117906,Male,Loyal Customer,42,Business travel,Business,3267,2,2,2,2,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +29460,48950,Female,Loyal Customer,42,Business travel,Eco,308,5,3,3,3,3,2,3,5,5,5,5,1,5,1,0,0.0,satisfied +29461,115172,Male,Loyal Customer,52,Business travel,Business,3826,2,2,2,2,4,5,4,4,4,4,4,5,4,3,25,28.0,satisfied +29462,106633,Male,Loyal Customer,44,Business travel,Business,1613,4,1,1,1,4,4,3,4,4,4,4,3,4,3,8,15.0,neutral or dissatisfied +29463,12214,Male,Loyal Customer,50,Business travel,Business,192,3,5,5,5,1,3,3,2,2,2,3,2,2,3,0,17.0,neutral or dissatisfied +29464,4575,Female,Loyal Customer,31,Business travel,Business,416,1,2,2,2,1,1,1,1,1,2,3,4,4,1,0,4.0,neutral or dissatisfied +29465,30536,Female,Loyal Customer,53,Personal Travel,Eco,683,2,4,2,1,2,5,5,4,4,2,4,3,4,5,0,9.0,neutral or dissatisfied +29466,68790,Male,Loyal Customer,58,Business travel,Business,1021,2,1,1,1,1,1,2,2,2,2,2,3,2,3,0,2.0,neutral or dissatisfied +29467,120681,Female,disloyal Customer,37,Business travel,Eco,280,2,5,2,2,1,2,1,1,2,5,1,5,2,1,0,0.0,neutral or dissatisfied +29468,53557,Male,Loyal Customer,60,Personal Travel,Business,1195,2,5,2,4,4,5,5,5,5,2,5,4,5,4,6,0.0,neutral or dissatisfied +29469,5263,Female,Loyal Customer,56,Business travel,Business,1580,2,5,4,5,2,3,3,2,2,3,2,1,2,1,34,25.0,neutral or dissatisfied +29470,117889,Male,Loyal Customer,58,Business travel,Business,3587,2,3,2,2,4,5,4,4,4,4,4,5,4,5,5,8.0,satisfied +29471,78223,Male,Loyal Customer,10,Personal Travel,Eco,153,2,2,2,3,4,2,4,4,4,1,3,4,3,4,1,20.0,neutral or dissatisfied +29472,115744,Male,Loyal Customer,40,Business travel,Business,3105,2,2,2,2,5,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +29473,102824,Female,disloyal Customer,26,Business travel,Business,342,3,5,2,2,5,2,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +29474,120194,Female,Loyal Customer,34,Business travel,Business,1325,4,4,4,4,3,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +29475,42417,Female,disloyal Customer,37,Business travel,Eco Plus,462,4,4,4,2,3,4,3,3,5,5,1,4,2,3,0,0.0,neutral or dissatisfied +29476,80032,Male,Loyal Customer,49,Personal Travel,Eco,1010,2,5,2,3,2,2,2,2,3,3,5,5,2,2,17,8.0,neutral or dissatisfied +29477,107569,Female,Loyal Customer,21,Personal Travel,Eco,1521,1,2,1,3,4,1,1,4,3,5,3,2,3,4,10,25.0,neutral or dissatisfied +29478,37790,Female,disloyal Customer,19,Business travel,Eco,1102,3,3,3,3,2,3,5,2,1,5,4,1,3,2,25,15.0,neutral or dissatisfied +29479,125209,Female,Loyal Customer,34,Business travel,Business,2429,5,5,5,5,1,1,4,4,4,5,4,5,4,3,0,2.0,satisfied +29480,109060,Male,Loyal Customer,51,Business travel,Eco,957,2,2,2,2,2,2,2,2,2,2,3,1,3,2,5,0.0,neutral or dissatisfied +29481,87099,Female,Loyal Customer,47,Personal Travel,Eco,640,1,4,2,5,2,4,4,3,5,4,5,4,3,4,7,137.0,neutral or dissatisfied +29482,27630,Male,Loyal Customer,45,Business travel,Eco Plus,697,2,3,3,3,2,2,2,2,5,1,2,4,4,2,0,0.0,satisfied +29483,24024,Female,disloyal Customer,22,Business travel,Business,427,2,2,2,3,2,2,2,2,1,5,3,2,3,2,88,91.0,neutral or dissatisfied +29484,70895,Female,disloyal Customer,44,Business travel,Eco,1721,2,2,2,4,4,2,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +29485,445,Female,Loyal Customer,41,Business travel,Business,3060,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +29486,2615,Male,Loyal Customer,46,Personal Travel,Eco,181,2,4,2,3,5,2,5,5,4,4,4,4,3,5,0,,neutral or dissatisfied +29487,24009,Female,disloyal Customer,25,Business travel,Eco,595,3,0,3,1,4,3,4,4,2,1,5,4,3,4,0,0.0,neutral or dissatisfied +29488,39743,Male,Loyal Customer,59,Business travel,Eco Plus,205,4,2,2,2,4,4,4,4,1,5,1,3,1,4,0,0.0,satisfied +29489,126176,Female,Loyal Customer,34,Business travel,Business,468,1,2,2,2,5,2,2,1,1,1,1,3,1,1,7,5.0,neutral or dissatisfied +29490,100804,Male,disloyal Customer,20,Business travel,Eco,872,3,3,3,4,5,3,5,5,3,3,4,2,3,5,0,4.0,neutral or dissatisfied +29491,84562,Female,Loyal Customer,58,Personal Travel,Eco,2556,4,5,4,1,3,3,5,3,3,4,3,3,3,4,0,1.0,neutral or dissatisfied +29492,27167,Male,Loyal Customer,36,Business travel,Eco,1177,5,5,5,5,5,5,5,1,2,3,4,5,5,5,0,0.0,satisfied +29493,74727,Male,Loyal Customer,49,Personal Travel,Eco,1235,1,4,1,5,2,1,2,2,5,2,3,3,4,2,0,0.0,neutral or dissatisfied +29494,119809,Female,disloyal Customer,32,Business travel,Business,912,3,3,3,2,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +29495,71949,Male,Loyal Customer,59,Business travel,Business,1440,5,5,5,5,2,5,5,5,5,5,5,5,5,5,24,29.0,satisfied +29496,11999,Female,Loyal Customer,42,Personal Travel,Eco,643,4,5,4,1,2,5,5,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +29497,110226,Female,Loyal Customer,43,Business travel,Business,1011,3,3,3,3,2,4,5,4,4,4,4,4,4,4,8,8.0,satisfied +29498,72545,Female,disloyal Customer,49,Business travel,Eco,964,4,4,4,4,3,4,3,3,1,2,3,4,4,3,0,7.0,neutral or dissatisfied +29499,83199,Male,Loyal Customer,25,Business travel,Business,1123,1,1,1,1,3,3,3,3,4,3,5,4,4,3,0,4.0,satisfied +29500,70423,Female,Loyal Customer,57,Business travel,Business,3190,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +29501,85537,Female,disloyal Customer,32,Business travel,Business,153,1,1,1,2,5,1,5,5,5,5,5,4,4,5,43,37.0,neutral or dissatisfied +29502,119699,Male,Loyal Customer,48,Business travel,Business,3403,2,2,5,2,3,4,5,5,5,5,5,5,5,4,13,39.0,satisfied +29503,11325,Female,Loyal Customer,29,Personal Travel,Eco,429,1,5,1,2,2,1,3,2,3,4,5,3,3,2,0,0.0,neutral or dissatisfied +29504,70065,Female,Loyal Customer,59,Business travel,Business,550,2,5,4,5,2,3,3,2,2,2,2,3,2,4,29,28.0,neutral or dissatisfied +29505,84657,Male,Loyal Customer,28,Personal Travel,Business,2182,3,5,3,5,3,3,3,3,5,2,3,1,1,3,0,0.0,neutral or dissatisfied +29506,29124,Female,Loyal Customer,51,Personal Travel,Eco,697,1,4,1,3,2,4,3,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +29507,39662,Female,Loyal Customer,30,Personal Travel,Eco,224,1,4,0,3,5,0,5,5,2,5,3,4,4,5,0,0.0,neutral or dissatisfied +29508,42994,Female,Loyal Customer,40,Business travel,Business,1585,2,2,2,2,3,2,3,5,5,4,5,1,5,4,0,0.0,satisfied +29509,2169,Female,Loyal Customer,27,Business travel,Business,2815,4,1,1,1,4,4,4,4,2,5,3,2,3,4,59,57.0,neutral or dissatisfied +29510,24201,Female,Loyal Customer,41,Business travel,Business,147,5,5,5,5,3,2,4,4,4,5,3,4,4,2,0,0.0,satisfied +29511,63304,Female,Loyal Customer,58,Business travel,Business,2470,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +29512,54308,Male,disloyal Customer,38,Business travel,Eco,1342,3,3,3,3,2,3,2,2,3,1,3,3,3,2,1,0.0,neutral or dissatisfied +29513,107982,Male,disloyal Customer,25,Business travel,Business,271,5,0,5,4,2,5,2,2,3,2,4,4,4,2,0,5.0,satisfied +29514,53373,Male,disloyal Customer,22,Business travel,Eco,1452,3,3,3,4,3,3,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +29515,80771,Male,Loyal Customer,43,Business travel,Eco Plus,629,1,4,3,4,1,1,1,1,1,1,3,1,3,1,4,0.0,neutral or dissatisfied +29516,93941,Female,Loyal Customer,41,Personal Travel,Eco,507,4,4,5,4,5,5,5,5,4,3,4,1,4,5,0,0.0,satisfied +29517,111491,Female,Loyal Customer,35,Business travel,Business,2947,1,1,1,1,5,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +29518,59029,Female,Loyal Customer,50,Business travel,Business,1723,1,1,4,1,5,5,5,5,2,4,4,5,5,5,159,168.0,satisfied +29519,52929,Female,Loyal Customer,68,Personal Travel,Eco,679,5,4,5,2,2,2,3,2,2,5,2,1,2,5,11,10.0,satisfied +29520,93563,Female,Loyal Customer,12,Business travel,Eco Plus,719,3,3,3,3,3,3,2,3,3,1,4,2,4,3,40,43.0,neutral or dissatisfied +29521,45287,Male,Loyal Customer,56,Business travel,Business,150,1,1,1,1,5,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +29522,48733,Female,disloyal Customer,58,Business travel,Business,262,4,5,5,4,4,2,2,3,5,5,5,2,5,2,180,174.0,satisfied +29523,40472,Male,disloyal Customer,25,Business travel,Eco,175,3,0,3,2,2,3,2,2,3,3,3,4,1,2,0,0.0,neutral or dissatisfied +29524,80061,Female,Loyal Customer,23,Personal Travel,Eco,1010,3,4,3,4,5,3,5,5,4,1,4,4,4,5,0,8.0,neutral or dissatisfied +29525,79239,Male,disloyal Customer,23,Business travel,Business,1598,3,2,3,1,1,3,1,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +29526,93145,Male,Loyal Customer,17,Business travel,Eco,1066,2,4,4,4,2,2,2,2,1,2,4,1,4,2,0,0.0,neutral or dissatisfied +29527,119505,Female,disloyal Customer,8,Business travel,Eco,759,2,2,2,2,2,2,2,2,2,4,3,4,2,2,65,72.0,neutral or dissatisfied +29528,20538,Male,Loyal Customer,34,Business travel,Business,3335,3,3,2,3,4,4,4,1,3,2,4,4,2,4,177,179.0,satisfied +29529,50611,Female,Loyal Customer,67,Personal Travel,Eco,134,2,2,2,3,3,4,4,4,4,2,4,3,4,3,7,8.0,neutral or dissatisfied +29530,64950,Male,disloyal Customer,20,Business travel,Eco,469,3,3,3,3,4,3,4,4,3,3,2,1,3,4,29,13.0,neutral or dissatisfied +29531,127776,Male,Loyal Customer,54,Business travel,Business,3583,4,4,4,4,3,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +29532,80148,Male,Loyal Customer,54,Business travel,Business,2586,1,1,1,1,4,4,4,3,3,5,5,4,3,4,0,5.0,satisfied +29533,58672,Male,Loyal Customer,45,Business travel,Business,2730,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +29534,58599,Male,Loyal Customer,36,Personal Travel,Eco,334,3,1,3,3,5,3,5,5,2,1,3,2,4,5,61,35.0,neutral or dissatisfied +29535,33501,Male,Loyal Customer,39,Business travel,Eco,965,5,1,3,1,5,5,5,5,3,3,1,1,2,5,8,0.0,satisfied +29536,107724,Female,Loyal Customer,31,Business travel,Eco,405,4,1,1,1,4,4,4,4,4,1,5,4,5,4,2,1.0,satisfied +29537,62195,Female,Loyal Customer,43,Business travel,Business,1506,5,5,5,5,3,2,2,4,4,4,4,5,4,3,1,0.0,satisfied +29538,42328,Female,Loyal Customer,36,Personal Travel,Eco,817,1,0,1,4,4,1,4,4,5,3,5,5,4,4,0,3.0,neutral or dissatisfied +29539,124384,Female,Loyal Customer,8,Personal Travel,Eco,808,3,2,4,4,3,4,3,3,2,1,4,3,4,3,0,16.0,neutral or dissatisfied +29540,56951,Female,Loyal Customer,49,Business travel,Eco,2565,3,2,2,2,3,3,3,3,5,2,3,3,1,3,9,22.0,neutral or dissatisfied +29541,105781,Female,Loyal Customer,10,Personal Travel,Eco,787,3,4,3,3,5,3,5,5,5,5,4,3,5,5,18,28.0,neutral or dissatisfied +29542,3026,Female,Loyal Customer,11,Personal Travel,Eco,987,4,4,4,3,5,4,5,5,3,2,5,5,5,5,23,25.0,neutral or dissatisfied +29543,125131,Female,Loyal Customer,7,Personal Travel,Eco,361,1,5,4,2,4,4,4,4,3,3,4,3,5,4,17,13.0,neutral or dissatisfied +29544,11703,Male,disloyal Customer,47,Business travel,Business,429,4,4,4,2,3,4,3,3,3,2,4,5,4,3,6,12.0,satisfied +29545,113729,Male,Loyal Customer,49,Personal Travel,Eco,397,3,1,3,1,5,3,5,5,2,2,2,2,1,5,46,32.0,neutral or dissatisfied +29546,27077,Female,Loyal Customer,50,Business travel,Business,2496,1,1,1,1,4,4,3,2,2,2,2,4,2,3,0,0.0,satisfied +29547,123439,Female,Loyal Customer,39,Business travel,Business,2125,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,18.0,satisfied +29548,101426,Female,Loyal Customer,39,Business travel,Business,345,2,2,2,2,2,5,5,5,5,5,5,5,5,4,21,18.0,satisfied +29549,33173,Male,Loyal Customer,52,Personal Travel,Eco,102,3,5,3,5,2,3,3,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +29550,73556,Male,Loyal Customer,45,Business travel,Business,1684,0,5,0,4,3,5,5,5,5,5,5,4,5,5,0,8.0,satisfied +29551,108991,Male,Loyal Customer,53,Business travel,Business,849,2,2,2,2,5,4,4,5,5,5,5,4,5,4,16,19.0,satisfied +29552,26607,Male,disloyal Customer,22,Business travel,Eco,545,2,3,2,4,4,2,4,4,4,4,3,2,3,4,2,0.0,neutral or dissatisfied +29553,40620,Male,Loyal Customer,54,Personal Travel,Eco,216,3,3,3,4,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +29554,41486,Female,Loyal Customer,41,Business travel,Eco,1211,5,2,2,2,5,5,5,5,2,3,3,4,5,5,0,9.0,satisfied +29555,57219,Male,Loyal Customer,50,Business travel,Eco,1114,5,2,2,2,5,5,5,5,4,1,2,3,1,5,5,28.0,satisfied +29556,44870,Male,disloyal Customer,25,Business travel,Eco,315,2,0,2,5,5,2,5,5,4,3,3,1,2,5,0,15.0,neutral or dissatisfied +29557,634,Female,Loyal Customer,39,Business travel,Business,113,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +29558,20906,Male,Loyal Customer,45,Business travel,Eco,721,5,2,4,4,5,5,5,5,5,1,2,1,1,5,39,32.0,satisfied +29559,125410,Male,Loyal Customer,40,Business travel,Business,2741,1,1,1,1,3,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +29560,116174,Female,Loyal Customer,57,Personal Travel,Eco,308,2,4,2,3,5,5,5,4,4,2,1,4,4,4,0,0.0,neutral or dissatisfied +29561,36398,Male,Loyal Customer,37,Personal Travel,Eco Plus,2381,3,1,3,3,3,5,5,4,2,3,3,5,1,5,0,0.0,neutral or dissatisfied +29562,62573,Male,Loyal Customer,47,Business travel,Business,1846,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +29563,55332,Female,Loyal Customer,56,Personal Travel,Eco,1117,2,3,2,4,3,3,4,1,1,2,2,3,1,4,0,14.0,neutral or dissatisfied +29564,49798,Female,disloyal Customer,54,Business travel,Eco,156,5,0,5,5,4,5,4,4,3,3,1,4,3,4,0,0.0,satisfied +29565,88971,Male,disloyal Customer,26,Business travel,Business,1340,3,3,3,2,4,3,3,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +29566,10055,Male,Loyal Customer,27,Personal Travel,Eco Plus,326,1,3,1,5,4,1,2,4,3,3,1,4,2,4,0,37.0,neutral or dissatisfied +29567,63258,Female,Loyal Customer,60,Business travel,Eco,372,4,3,3,3,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +29568,32603,Female,Loyal Customer,45,Business travel,Eco,101,2,1,1,1,2,4,4,2,2,2,2,1,2,3,2,5.0,neutral or dissatisfied +29569,61587,Male,Loyal Customer,37,Personal Travel,Business,1346,3,4,3,2,4,5,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +29570,129843,Female,Loyal Customer,68,Personal Travel,Eco,337,3,4,3,2,2,4,1,3,3,3,1,1,3,1,0,4.0,neutral or dissatisfied +29571,44568,Female,Loyal Customer,48,Business travel,Business,157,5,5,4,5,1,4,5,4,4,4,3,4,4,2,0,0.0,satisfied +29572,47344,Female,Loyal Customer,21,Business travel,Business,588,3,3,3,3,2,2,2,2,1,3,4,1,2,2,0,0.0,satisfied +29573,33684,Male,Loyal Customer,34,Business travel,Eco,759,5,2,2,2,5,5,5,5,4,5,4,2,5,5,16,24.0,satisfied +29574,100323,Male,Loyal Customer,42,Business travel,Business,1053,5,5,5,5,5,5,4,4,4,4,4,5,4,4,29,8.0,satisfied +29575,67373,Male,Loyal Customer,41,Business travel,Business,2850,5,5,5,5,5,4,5,4,4,4,4,4,4,4,19,18.0,satisfied +29576,80160,Male,Loyal Customer,43,Business travel,Business,2475,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +29577,52882,Male,disloyal Customer,18,Business travel,Eco,1024,3,3,3,4,2,3,2,2,4,5,4,1,4,2,5,0.0,neutral or dissatisfied +29578,109504,Female,Loyal Customer,60,Business travel,Business,2751,5,5,1,5,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +29579,53441,Male,disloyal Customer,23,Business travel,Eco,2288,1,1,1,1,1,5,5,4,2,3,4,5,2,5,3,0.0,neutral or dissatisfied +29580,73758,Male,Loyal Customer,66,Personal Travel,Eco,204,4,3,0,1,2,0,2,2,5,3,1,5,5,2,0,3.0,neutral or dissatisfied +29581,14313,Male,Loyal Customer,17,Business travel,Eco,175,4,2,2,2,4,4,2,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +29582,111965,Female,Loyal Customer,55,Business travel,Eco,533,2,1,1,1,4,3,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29583,107624,Female,Loyal Customer,43,Personal Travel,Eco,423,2,0,2,1,5,4,5,2,2,2,2,5,2,4,34,29.0,neutral or dissatisfied +29584,71776,Male,Loyal Customer,53,Business travel,Business,1744,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +29585,14340,Male,Loyal Customer,14,Personal Travel,Eco,395,1,5,2,1,2,2,2,4,4,5,4,2,4,2,519,516.0,neutral or dissatisfied +29586,22069,Female,Loyal Customer,64,Personal Travel,Eco,304,2,5,2,4,3,5,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +29587,117317,Female,Loyal Customer,11,Personal Travel,Eco Plus,325,3,4,3,1,5,3,5,5,5,3,2,1,3,5,0,0.0,neutral or dissatisfied +29588,74949,Male,Loyal Customer,34,Business travel,Business,2586,1,5,3,5,4,1,1,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +29589,110477,Female,Loyal Customer,30,Personal Travel,Eco,787,3,4,3,1,4,3,4,4,4,2,5,4,5,4,6,0.0,neutral or dissatisfied +29590,90969,Male,Loyal Customer,67,Business travel,Business,3732,0,5,0,3,2,2,3,1,1,4,4,2,1,5,0,0.0,satisfied +29591,35516,Female,Loyal Customer,9,Personal Travel,Eco,1118,2,5,3,2,4,3,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +29592,58048,Male,disloyal Customer,37,Business travel,Business,612,5,4,4,2,2,4,2,2,3,2,4,5,5,2,0,0.0,satisfied +29593,20950,Male,Loyal Customer,13,Business travel,Business,689,3,3,3,3,4,4,4,4,2,5,5,4,4,4,0,0.0,satisfied +29594,101308,Male,Loyal Customer,48,Personal Travel,Eco Plus,444,3,4,3,2,3,3,3,3,5,4,4,5,4,3,12,7.0,neutral or dissatisfied +29595,85838,Male,Loyal Customer,31,Personal Travel,Eco,666,3,4,3,3,1,3,4,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +29596,77685,Male,Loyal Customer,16,Business travel,Business,731,3,2,4,4,3,3,3,3,1,1,3,3,4,3,7,0.0,neutral or dissatisfied +29597,120386,Male,Loyal Customer,48,Business travel,Business,3201,0,0,0,1,2,4,5,2,2,2,2,4,2,3,0,2.0,satisfied +29598,116456,Male,Loyal Customer,54,Personal Travel,Eco,446,3,5,3,2,2,3,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +29599,18445,Male,Loyal Customer,40,Business travel,Business,262,4,1,1,1,3,3,2,4,4,4,4,2,4,3,0,2.0,neutral or dissatisfied +29600,121142,Female,Loyal Customer,54,Business travel,Business,2370,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +29601,50155,Female,disloyal Customer,37,Business travel,Eco,199,2,4,2,4,3,2,3,3,2,2,4,4,4,3,4,2.0,neutral or dissatisfied +29602,97058,Female,Loyal Customer,46,Business travel,Business,1476,5,5,5,5,5,5,5,3,3,3,3,5,3,3,54,59.0,satisfied +29603,96390,Female,Loyal Customer,30,Business travel,Business,1342,2,2,2,2,5,5,5,5,3,5,5,3,4,5,41,31.0,satisfied +29604,3268,Female,disloyal Customer,22,Business travel,Business,479,1,2,2,3,2,2,2,2,4,5,3,2,3,2,122,106.0,neutral or dissatisfied +29605,15571,Male,Loyal Customer,33,Business travel,Eco,229,5,5,5,5,5,5,5,5,4,1,3,2,3,5,4,0.0,satisfied +29606,30551,Female,Loyal Customer,44,Personal Travel,Eco,1028,1,4,2,3,3,4,4,5,5,2,5,3,5,4,61,51.0,neutral or dissatisfied +29607,7528,Female,Loyal Customer,35,Business travel,Eco,762,4,3,3,3,4,4,4,4,4,3,4,1,4,4,0,7.0,neutral or dissatisfied +29608,50321,Male,Loyal Customer,50,Business travel,Business,77,3,3,5,3,1,4,4,4,4,4,3,2,4,2,15,9.0,neutral or dissatisfied +29609,47950,Female,Loyal Customer,12,Personal Travel,Eco,550,3,2,3,3,2,3,4,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +29610,35461,Male,Loyal Customer,17,Personal Travel,Eco,950,3,2,3,4,3,5,5,3,1,3,3,5,1,5,118,134.0,neutral or dissatisfied +29611,56430,Female,Loyal Customer,36,Business travel,Business,3783,3,5,5,5,2,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +29612,58525,Male,Loyal Customer,27,Personal Travel,Eco,719,2,5,2,4,4,2,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +29613,51746,Male,Loyal Customer,56,Personal Travel,Eco,370,1,4,4,2,1,4,1,1,1,1,3,4,5,1,0,0.0,neutral or dissatisfied +29614,93834,Male,Loyal Customer,44,Business travel,Business,2965,4,4,4,4,5,4,5,5,5,5,5,3,5,2,0,0.0,satisfied +29615,125850,Male,Loyal Customer,54,Business travel,Business,3432,2,2,2,2,3,4,4,2,2,2,2,3,2,5,5,0.0,satisfied +29616,116553,Female,Loyal Customer,32,Personal Travel,Eco,337,2,3,2,2,2,2,2,2,2,2,1,3,5,2,11,8.0,neutral or dissatisfied +29617,76718,Female,Loyal Customer,33,Business travel,Eco Plus,547,3,3,3,3,3,3,3,3,4,4,3,4,2,3,0,0.0,neutral or dissatisfied +29618,106030,Male,Loyal Customer,14,Personal Travel,Eco,682,3,2,3,3,3,3,3,3,2,1,4,4,4,3,23,22.0,neutral or dissatisfied +29619,97130,Female,Loyal Customer,57,Business travel,Eco,1211,4,1,1,1,2,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +29620,76250,Female,Loyal Customer,50,Personal Travel,Eco,1399,2,4,2,3,3,4,4,1,1,2,1,4,1,1,5,0.0,neutral or dissatisfied +29621,17748,Male,Loyal Customer,53,Personal Travel,Eco,529,3,1,3,4,3,2,2,2,5,4,3,2,4,2,218,220.0,neutral or dissatisfied +29622,120652,Female,Loyal Customer,31,Business travel,Business,280,3,4,5,5,3,3,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +29623,120173,Male,Loyal Customer,15,Personal Travel,Eco,335,1,4,1,4,4,1,4,4,3,2,5,4,4,4,5,5.0,neutral or dissatisfied +29624,112646,Male,disloyal Customer,27,Business travel,Business,1177,4,4,4,3,3,4,3,3,4,5,4,5,4,3,31,44.0,satisfied +29625,114935,Male,disloyal Customer,35,Business travel,Business,342,3,3,3,3,1,3,1,1,4,5,4,3,5,1,2,5.0,neutral or dissatisfied +29626,128559,Female,Loyal Customer,35,Business travel,Eco Plus,325,5,4,4,4,5,5,5,5,5,2,5,1,2,5,0,0.0,satisfied +29627,98544,Female,Loyal Customer,59,Business travel,Business,1525,1,1,1,1,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +29628,55050,Female,Loyal Customer,49,Business travel,Business,1379,2,4,5,4,1,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29629,50737,Male,Loyal Customer,37,Personal Travel,Eco,109,4,0,4,2,1,4,1,1,3,5,4,3,4,1,13,14.0,neutral or dissatisfied +29630,7911,Female,Loyal Customer,47,Business travel,Business,2970,2,2,2,2,2,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +29631,3446,Female,Loyal Customer,10,Personal Travel,Eco,240,2,5,2,1,5,2,5,5,3,5,5,5,5,5,17,9.0,neutral or dissatisfied +29632,127358,Male,Loyal Customer,51,Personal Travel,Eco,507,3,4,2,3,5,2,2,5,5,2,3,2,5,5,2,0.0,neutral or dissatisfied +29633,112271,Male,Loyal Customer,53,Business travel,Business,1106,3,3,3,3,1,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +29634,61289,Male,Loyal Customer,16,Personal Travel,Eco,967,2,4,2,4,4,2,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +29635,79426,Female,Loyal Customer,63,Personal Travel,Eco,502,4,4,4,1,4,4,4,1,1,4,1,5,1,5,0,0.0,satisfied +29636,101769,Female,Loyal Customer,33,Personal Travel,Eco Plus,1590,4,4,4,1,2,4,2,2,4,3,4,3,5,2,0,0.0,satisfied +29637,5759,Male,Loyal Customer,65,Personal Travel,Eco,859,5,5,5,4,2,5,2,2,5,4,2,1,3,2,2,0.0,satisfied +29638,93825,Female,Loyal Customer,49,Business travel,Business,3879,3,3,3,3,5,5,5,4,4,4,4,5,4,4,8,0.0,satisfied +29639,111819,Female,Loyal Customer,44,Personal Travel,Eco Plus,349,2,2,2,2,5,2,3,3,3,2,4,3,3,3,71,68.0,neutral or dissatisfied +29640,11642,Female,Loyal Customer,22,Personal Travel,Business,925,2,5,2,4,1,2,1,1,5,3,4,2,5,1,0,3.0,neutral or dissatisfied +29641,73762,Male,Loyal Customer,8,Personal Travel,Eco,192,1,5,1,2,3,1,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +29642,88838,Female,Loyal Customer,11,Personal Travel,Eco Plus,406,2,4,2,4,2,2,2,2,3,4,5,3,5,2,24,16.0,neutral or dissatisfied +29643,76568,Male,Loyal Customer,31,Business travel,Business,3531,1,3,3,3,1,1,1,1,3,4,3,2,4,1,27,26.0,neutral or dissatisfied +29644,16705,Male,Loyal Customer,31,Business travel,Business,2609,3,5,3,3,5,5,5,5,3,4,3,2,2,5,18,12.0,satisfied +29645,10205,Female,Loyal Customer,60,Business travel,Business,2574,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +29646,119468,Female,Loyal Customer,55,Business travel,Business,759,2,2,2,2,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +29647,47451,Female,Loyal Customer,29,Personal Travel,Eco,599,5,4,5,4,3,5,3,3,3,5,5,5,4,3,0,0.0,satisfied +29648,79120,Male,Loyal Customer,9,Personal Travel,Eco,164,1,4,1,1,2,1,2,2,1,4,3,1,4,2,0,0.0,neutral or dissatisfied +29649,53731,Female,Loyal Customer,35,Personal Travel,Eco,1208,2,3,2,3,5,2,2,5,1,1,3,1,5,5,0,0.0,neutral or dissatisfied +29650,103289,Female,Loyal Customer,56,Business travel,Business,1608,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +29651,67681,Female,Loyal Customer,19,Business travel,Business,1438,2,2,2,2,4,4,4,4,5,2,5,3,4,4,2,0.0,satisfied +29652,44421,Female,Loyal Customer,70,Personal Travel,Eco Plus,323,4,4,4,3,4,5,2,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +29653,40743,Female,Loyal Customer,52,Business travel,Business,3979,1,1,1,1,4,1,2,4,4,4,4,2,4,4,21,7.0,satisfied +29654,100006,Female,disloyal Customer,25,Business travel,Business,277,3,0,3,5,5,3,5,5,3,3,5,5,4,5,47,51.0,neutral or dissatisfied +29655,39410,Female,Loyal Customer,55,Personal Travel,Eco,521,4,5,4,4,2,5,4,3,3,4,3,5,3,3,0,0.0,neutral or dissatisfied +29656,30498,Female,Loyal Customer,8,Personal Travel,Eco,516,3,5,3,4,4,3,4,4,4,5,3,2,4,4,0,13.0,neutral or dissatisfied +29657,66394,Male,Loyal Customer,45,Business travel,Business,1562,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +29658,25306,Female,Loyal Customer,44,Business travel,Business,2544,3,1,1,1,5,3,4,3,3,3,3,4,3,1,25,21.0,neutral or dissatisfied +29659,65779,Female,Loyal Customer,30,Personal Travel,Business,1389,3,5,2,1,3,2,2,3,5,5,4,3,4,3,17,0.0,neutral or dissatisfied +29660,85197,Male,Loyal Customer,39,Business travel,Business,813,3,3,3,3,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +29661,112313,Female,Loyal Customer,59,Business travel,Business,1544,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +29662,112760,Female,Loyal Customer,35,Business travel,Business,588,3,3,3,3,2,3,3,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +29663,33247,Male,Loyal Customer,53,Business travel,Eco Plus,101,1,4,4,4,2,1,2,2,3,2,3,1,4,2,7,7.0,neutral or dissatisfied +29664,119176,Male,Loyal Customer,60,Business travel,Business,1745,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +29665,119338,Female,Loyal Customer,8,Personal Travel,Eco,214,3,0,3,3,2,3,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +29666,76022,Male,Loyal Customer,41,Business travel,Business,2079,4,1,4,4,1,3,3,4,4,4,4,2,4,4,69,53.0,neutral or dissatisfied +29667,122689,Female,disloyal Customer,80,Business travel,Business,361,4,4,4,4,1,4,4,5,5,4,5,1,5,2,63,47.0,neutral or dissatisfied +29668,28417,Female,Loyal Customer,30,Business travel,Business,1399,1,1,1,1,4,4,4,4,4,1,5,2,1,4,0,3.0,satisfied +29669,91984,Male,Loyal Customer,61,Personal Travel,Eco Plus,2475,4,4,3,4,5,3,5,5,2,4,5,4,1,5,0,0.0,neutral or dissatisfied +29670,3868,Male,Loyal Customer,41,Business travel,Business,3146,3,3,3,3,4,4,4,5,5,5,5,5,5,5,33,33.0,satisfied +29671,98698,Female,Loyal Customer,12,Personal Travel,Eco,861,2,5,2,5,1,2,1,1,5,5,4,4,5,1,34,60.0,neutral or dissatisfied +29672,52158,Female,Loyal Customer,12,Business travel,Business,2629,3,3,4,3,2,2,2,2,3,4,5,1,5,2,0,0.0,satisfied +29673,60905,Male,Loyal Customer,54,Business travel,Business,3023,5,5,4,5,3,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +29674,39340,Male,disloyal Customer,26,Business travel,Eco,374,3,2,3,3,5,3,5,5,4,4,3,4,3,5,0,30.0,neutral or dissatisfied +29675,125875,Male,Loyal Customer,32,Business travel,Business,2031,4,4,4,4,4,5,4,4,4,3,2,1,4,4,0,4.0,satisfied +29676,22400,Female,Loyal Customer,57,Business travel,Eco,238,3,3,3,3,4,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +29677,3087,Male,disloyal Customer,28,Business travel,Business,413,3,3,3,1,3,3,2,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +29678,18719,Male,Loyal Customer,58,Personal Travel,Eco Plus,305,1,5,1,3,1,1,1,1,3,2,2,3,4,1,0,0.0,neutral or dissatisfied +29679,117567,Male,Loyal Customer,46,Business travel,Business,347,4,4,4,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +29680,78299,Female,Loyal Customer,21,Personal Travel,Eco,1598,4,5,4,5,4,4,3,4,4,5,5,3,5,4,2,0.0,neutral or dissatisfied +29681,29660,Male,Loyal Customer,8,Personal Travel,Eco,909,2,4,2,3,5,2,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +29682,68190,Male,Loyal Customer,58,Business travel,Business,1642,1,1,1,1,2,5,5,5,5,5,5,5,5,4,18,14.0,satisfied +29683,33797,Female,Loyal Customer,25,Business travel,Eco,1521,0,4,0,3,2,0,2,2,3,5,5,3,1,2,0,6.0,satisfied +29684,760,Female,disloyal Customer,37,Business travel,Business,309,1,1,1,3,2,1,2,2,5,2,4,5,4,2,71,61.0,neutral or dissatisfied +29685,70517,Female,Loyal Customer,21,Business travel,Business,2319,5,5,5,5,4,4,4,4,4,2,5,4,5,4,0,0.0,satisfied +29686,12646,Female,Loyal Customer,40,Personal Travel,Eco,844,1,5,2,3,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +29687,109568,Female,Loyal Customer,47,Personal Travel,Eco,861,3,5,3,2,2,1,1,1,1,3,1,4,1,5,7,0.0,neutral or dissatisfied +29688,19720,Male,Loyal Customer,51,Personal Travel,Eco,475,4,2,4,3,3,4,3,3,2,4,3,1,4,3,3,22.0,satisfied +29689,66249,Female,Loyal Customer,32,Personal Travel,Eco,550,1,1,1,2,3,1,3,3,2,2,1,1,2,3,4,0.0,neutral or dissatisfied +29690,123330,Female,Loyal Customer,15,Personal Travel,Eco Plus,507,5,4,5,3,2,5,2,2,5,2,5,5,4,2,0,0.0,satisfied +29691,2068,Female,disloyal Customer,26,Business travel,Business,812,2,2,2,4,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +29692,8024,Male,Loyal Customer,43,Business travel,Business,2244,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +29693,93284,Male,Loyal Customer,19,Personal Travel,Eco,867,2,5,2,3,3,2,3,3,2,5,5,1,1,3,3,0.0,neutral or dissatisfied +29694,123993,Male,Loyal Customer,44,Business travel,Eco,184,2,1,1,1,2,2,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +29695,85425,Male,disloyal Customer,38,Business travel,Business,152,4,4,4,4,5,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +29696,4524,Female,disloyal Customer,28,Business travel,Business,677,4,4,4,3,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +29697,119366,Female,disloyal Customer,39,Business travel,Business,399,5,5,5,4,2,5,2,2,5,2,4,5,5,2,0,0.0,satisfied +29698,16622,Female,Loyal Customer,12,Personal Travel,Eco,1008,3,4,3,1,4,3,4,4,3,4,4,5,5,4,3,8.0,neutral or dissatisfied +29699,64326,Female,disloyal Customer,27,Business travel,Eco,1158,1,1,1,3,5,1,4,5,4,3,3,3,2,5,8,4.0,neutral or dissatisfied +29700,93798,Female,Loyal Customer,56,Business travel,Business,3308,1,1,1,1,2,4,4,4,4,4,4,5,4,4,1,0.0,satisfied +29701,3110,Male,Loyal Customer,34,Personal Travel,Eco Plus,413,3,5,3,5,2,3,1,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +29702,33839,Female,Loyal Customer,31,Business travel,Business,1562,1,1,1,1,4,4,4,4,1,3,5,1,4,4,3,0.0,satisfied +29703,44122,Female,Loyal Customer,69,Business travel,Eco,198,4,2,2,2,4,1,3,3,3,4,3,2,3,2,0,0.0,satisfied +29704,124020,Male,Loyal Customer,7,Personal Travel,Eco,184,3,4,3,1,1,3,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +29705,99588,Female,Loyal Customer,69,Personal Travel,Eco,808,2,3,2,3,1,3,4,4,4,2,2,3,4,1,23,17.0,neutral or dissatisfied +29706,84588,Female,disloyal Customer,24,Business travel,Eco,269,4,4,4,2,4,4,3,4,3,5,5,4,4,4,102,85.0,neutral or dissatisfied +29707,23870,Female,Loyal Customer,65,Personal Travel,Eco,552,1,0,1,4,2,5,4,5,5,1,5,3,5,3,14,18.0,neutral or dissatisfied +29708,39103,Female,Loyal Customer,56,Business travel,Business,252,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +29709,106237,Male,Loyal Customer,58,Business travel,Business,2713,3,3,3,3,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +29710,78440,Male,disloyal Customer,39,Business travel,Business,666,2,2,2,4,2,2,2,2,5,5,5,3,4,2,30,31.0,neutral or dissatisfied +29711,105706,Male,Loyal Customer,48,Business travel,Business,2488,1,1,1,1,3,4,4,5,5,5,5,4,5,5,6,3.0,satisfied +29712,110658,Female,Loyal Customer,60,Business travel,Business,2255,2,2,2,2,4,4,4,5,5,5,5,3,5,4,11,0.0,satisfied +29713,93102,Male,Loyal Customer,49,Personal Travel,Eco,641,2,4,3,5,5,3,5,5,3,5,4,5,4,5,1,12.0,neutral or dissatisfied +29714,63388,Female,Loyal Customer,59,Personal Travel,Eco,447,2,5,2,4,5,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +29715,79259,Male,Loyal Customer,41,Personal Travel,Eco,1598,3,5,3,1,3,3,3,3,5,4,4,3,4,3,31,13.0,neutral or dissatisfied +29716,112135,Male,Loyal Customer,31,Business travel,Business,895,3,3,5,3,4,4,4,4,3,3,5,5,4,4,10,0.0,satisfied +29717,43729,Female,Loyal Customer,36,Business travel,Eco Plus,196,4,5,5,5,4,4,4,4,1,1,3,2,2,4,0,0.0,satisfied +29718,22088,Female,Loyal Customer,56,Business travel,Eco,782,4,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +29719,111001,Female,Loyal Customer,42,Business travel,Business,240,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +29720,13627,Female,Loyal Customer,51,Business travel,Business,1162,1,1,1,1,5,5,5,2,5,1,2,5,1,5,113,146.0,satisfied +29721,127795,Male,Loyal Customer,51,Personal Travel,Business,1044,1,5,1,3,5,1,5,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +29722,106155,Male,disloyal Customer,20,Business travel,Eco,436,2,1,2,3,5,2,5,5,1,1,4,3,4,5,2,0.0,neutral or dissatisfied +29723,58411,Male,Loyal Customer,24,Business travel,Business,723,2,4,4,4,2,2,2,2,1,3,4,1,4,2,0,6.0,neutral or dissatisfied +29724,41016,Male,Loyal Customer,20,Personal Travel,Business,1086,4,5,4,3,5,4,5,5,3,3,5,3,4,5,0,3.0,neutral or dissatisfied +29725,95844,Male,Loyal Customer,40,Business travel,Business,580,1,1,1,1,3,4,4,4,4,4,4,3,4,3,6,0.0,satisfied +29726,129297,Female,Loyal Customer,51,Personal Travel,Eco,550,2,0,2,4,4,5,4,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +29727,68223,Female,Loyal Customer,51,Business travel,Business,3664,2,2,2,2,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +29728,120683,Male,disloyal Customer,35,Business travel,Business,280,4,4,4,3,1,4,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +29729,70876,Female,Loyal Customer,44,Personal Travel,Eco,761,2,1,2,2,1,2,2,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +29730,33814,Female,Loyal Customer,47,Business travel,Eco,1521,3,1,1,1,1,3,4,3,3,3,3,2,3,2,0,25.0,neutral or dissatisfied +29731,26823,Male,Loyal Customer,38,Business travel,Business,2549,3,3,3,3,3,4,4,5,5,5,5,1,5,1,0,3.0,satisfied +29732,110752,Male,Loyal Customer,12,Business travel,Eco,990,1,5,5,5,1,1,3,1,2,3,4,2,4,1,10,11.0,neutral or dissatisfied +29733,94966,Male,Loyal Customer,33,Business travel,Eco,319,2,2,2,2,2,2,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +29734,84202,Male,disloyal Customer,37,Business travel,Eco,432,1,2,2,2,1,2,1,1,4,3,3,4,2,1,0,16.0,neutral or dissatisfied +29735,42723,Female,Loyal Customer,55,Personal Travel,Eco,1042,2,3,2,3,3,3,2,1,1,2,1,5,1,1,0,9.0,neutral or dissatisfied +29736,114886,Male,Loyal Customer,32,Business travel,Business,3456,4,3,4,4,3,3,3,3,4,4,5,3,5,3,1,0.0,satisfied +29737,81721,Male,disloyal Customer,20,Business travel,Business,1487,5,0,5,3,1,5,1,1,4,2,5,4,5,1,0,0.0,satisfied +29738,86149,Female,Loyal Customer,49,Business travel,Business,3910,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +29739,102435,Male,Loyal Customer,43,Personal Travel,Eco,258,3,5,0,4,3,0,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +29740,91111,Male,Loyal Customer,22,Personal Travel,Eco,444,1,4,5,4,1,5,1,1,3,5,5,5,5,1,55,43.0,neutral or dissatisfied +29741,54919,Male,Loyal Customer,27,Personal Travel,Eco Plus,862,2,5,2,2,4,2,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +29742,75960,Male,Loyal Customer,54,Business travel,Business,2432,1,3,3,3,5,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +29743,51797,Male,Loyal Customer,70,Personal Travel,Eco,493,3,2,3,4,5,3,5,5,3,5,4,4,3,5,0,0.0,neutral or dissatisfied +29744,104305,Female,Loyal Customer,39,Business travel,Business,2153,2,2,2,2,2,5,5,5,5,5,5,3,5,4,21,5.0,satisfied +29745,7430,Male,disloyal Customer,23,Business travel,Eco,522,2,3,2,4,5,2,5,5,2,4,3,3,4,5,23,13.0,neutral or dissatisfied +29746,81005,Male,Loyal Customer,13,Personal Travel,Eco,228,4,5,4,4,2,4,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +29747,67718,Male,Loyal Customer,55,Business travel,Business,2257,3,1,3,3,4,4,5,4,4,4,4,4,4,4,130,127.0,satisfied +29748,114549,Male,Loyal Customer,44,Personal Travel,Business,362,1,5,1,4,3,5,5,3,3,1,3,3,3,5,22,29.0,neutral or dissatisfied +29749,90221,Female,Loyal Customer,25,Personal Travel,Eco,1145,1,5,1,3,4,1,4,4,4,3,3,3,5,4,0,0.0,neutral or dissatisfied +29750,43310,Female,disloyal Customer,33,Business travel,Eco,347,2,0,2,1,4,2,4,4,3,4,1,4,3,4,0,0.0,neutral or dissatisfied +29751,25321,Female,Loyal Customer,24,Business travel,Business,2719,2,4,2,4,2,2,2,2,1,4,4,3,3,2,30,33.0,neutral or dissatisfied +29752,54295,Male,Loyal Customer,57,Personal Travel,Eco,1075,1,5,1,1,1,1,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +29753,63579,Male,disloyal Customer,25,Business travel,Business,2133,5,4,5,3,5,5,5,4,5,3,5,5,5,5,286,272.0,satisfied +29754,14964,Male,Loyal Customer,51,Business travel,Business,3196,3,3,3,3,4,4,2,4,4,4,4,2,4,2,0,0.0,satisfied +29755,27300,Male,Loyal Customer,42,Business travel,Eco,679,4,1,2,1,3,4,3,3,1,3,1,1,4,3,0,0.0,satisfied +29756,45204,Male,Loyal Customer,20,Personal Travel,Business,911,4,4,4,4,5,4,1,5,3,4,3,3,4,5,0,3.0,satisfied +29757,61395,Female,Loyal Customer,58,Business travel,Eco,279,5,1,1,1,4,5,2,5,5,5,5,3,5,3,1,0.0,satisfied +29758,10880,Male,disloyal Customer,20,Business travel,Eco,429,1,4,1,3,1,1,1,3,3,4,4,1,4,1,184,193.0,neutral or dissatisfied +29759,121586,Female,Loyal Customer,36,Business travel,Eco,512,4,1,1,1,4,5,4,4,5,1,3,5,3,4,4,0.0,satisfied +29760,37067,Male,disloyal Customer,25,Business travel,Business,1188,4,4,4,2,3,4,3,3,1,1,2,3,1,3,0,0.0,satisfied +29761,13867,Female,disloyal Customer,45,Business travel,Eco,760,1,1,1,1,3,1,4,3,2,5,1,4,4,3,0,0.0,neutral or dissatisfied +29762,59115,Female,Loyal Customer,17,Personal Travel,Eco,1744,3,0,3,1,4,3,1,4,4,2,5,4,5,4,7,39.0,neutral or dissatisfied +29763,128470,Male,Loyal Customer,12,Personal Travel,Eco,304,3,4,3,4,4,3,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +29764,18937,Male,Loyal Customer,22,Personal Travel,Eco,503,3,1,2,2,4,2,1,4,3,5,3,3,2,4,67,65.0,neutral or dissatisfied +29765,11978,Male,Loyal Customer,50,Business travel,Business,667,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +29766,40612,Male,Loyal Customer,67,Personal Travel,Eco,216,3,0,3,4,5,3,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +29767,54146,Male,Loyal Customer,37,Business travel,Eco,1400,4,2,2,2,4,4,4,4,5,5,1,3,2,4,14,0.0,satisfied +29768,74246,Female,disloyal Customer,41,Business travel,Business,1014,5,5,5,3,2,5,2,2,3,5,3,4,4,2,0,0.0,satisfied +29769,48859,Female,Loyal Customer,34,Business travel,Business,2950,5,5,5,5,5,1,5,4,4,4,5,2,4,1,0,0.0,satisfied +29770,86341,Male,disloyal Customer,20,Business travel,Business,762,4,0,4,3,2,4,2,2,3,4,4,3,4,2,0,0.0,satisfied +29771,68400,Female,Loyal Customer,25,Business travel,Eco,1045,2,4,4,4,2,2,2,1,1,2,3,2,1,2,148,149.0,neutral or dissatisfied +29772,92716,Male,disloyal Customer,25,Business travel,Eco,1276,1,1,1,4,5,1,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +29773,22836,Female,disloyal Customer,25,Business travel,Eco,147,2,3,2,1,5,2,5,5,1,1,2,5,4,5,0,0.0,neutral or dissatisfied +29774,52468,Male,Loyal Customer,36,Business travel,Eco Plus,198,2,4,4,4,2,2,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +29775,108136,Male,Loyal Customer,25,Business travel,Business,1166,1,5,5,5,1,2,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +29776,125538,Female,Loyal Customer,42,Business travel,Business,226,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +29777,12174,Male,Loyal Customer,49,Business travel,Business,3121,5,5,5,5,3,1,3,4,4,4,4,3,4,4,0,0.0,satisfied +29778,20822,Male,Loyal Customer,58,Business travel,Eco,457,1,1,2,2,1,1,1,1,2,1,4,3,3,1,20,3.0,neutral or dissatisfied +29779,49313,Male,Loyal Customer,58,Business travel,Eco,447,4,5,5,5,5,4,5,5,3,5,1,5,4,5,0,0.0,satisfied +29780,128824,Male,Loyal Customer,50,Business travel,Eco,2475,2,4,4,4,2,2,2,4,3,3,3,2,2,2,0,0.0,neutral or dissatisfied +29781,11312,Female,Loyal Customer,32,Personal Travel,Eco,247,2,4,0,1,0,2,2,5,4,5,4,2,3,2,143,141.0,neutral or dissatisfied +29782,106142,Female,disloyal Customer,20,Business travel,Eco,302,2,4,2,3,2,2,2,2,2,1,3,1,4,2,0,0.0,neutral or dissatisfied +29783,25273,Female,Loyal Customer,48,Business travel,Business,425,1,1,1,1,5,2,1,4,4,4,4,5,4,4,4,0.0,satisfied +29784,75679,Male,disloyal Customer,24,Business travel,Eco,813,2,2,2,3,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +29785,125842,Female,Loyal Customer,48,Business travel,Eco,993,2,4,4,4,3,2,2,2,2,2,2,1,2,1,0,21.0,neutral or dissatisfied +29786,89310,Male,Loyal Customer,49,Business travel,Business,1807,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +29787,77585,Female,Loyal Customer,23,Business travel,Business,731,2,2,2,2,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +29788,9931,Female,Loyal Customer,72,Business travel,Eco,357,3,3,3,3,1,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +29789,106187,Male,Loyal Customer,23,Personal Travel,Eco,302,1,5,4,4,3,4,3,3,3,3,5,3,4,3,12,8.0,neutral or dissatisfied +29790,99385,Male,Loyal Customer,57,Business travel,Business,2727,4,4,4,4,2,5,4,5,5,5,5,3,5,3,14,7.0,satisfied +29791,78241,Female,Loyal Customer,37,Business travel,Business,3711,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +29792,43747,Female,Loyal Customer,56,Personal Travel,Business,546,2,2,2,3,5,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +29793,16716,Male,Loyal Customer,63,Business travel,Eco Plus,284,3,2,2,2,3,3,3,3,1,4,3,4,3,3,96,97.0,neutral or dissatisfied +29794,17725,Male,disloyal Customer,20,Business travel,Eco,456,1,0,1,4,4,1,4,4,2,5,4,4,2,4,14,6.0,neutral or dissatisfied +29795,66537,Male,Loyal Customer,47,Personal Travel,Eco,733,2,1,2,2,3,2,3,3,2,3,2,3,3,3,61,72.0,neutral or dissatisfied +29796,32009,Male,Loyal Customer,56,Personal Travel,Business,101,3,3,3,1,2,1,1,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +29797,20771,Female,Loyal Customer,51,Business travel,Business,2208,4,4,4,4,1,3,1,5,5,5,5,3,5,4,0,1.0,satisfied +29798,58256,Male,Loyal Customer,53,Business travel,Business,2072,1,1,5,1,3,3,5,4,4,4,4,4,4,3,66,53.0,satisfied +29799,129189,Male,Loyal Customer,33,Business travel,Business,2288,2,2,5,2,5,5,5,5,5,3,5,5,4,5,18,1.0,satisfied +29800,76623,Female,Loyal Customer,39,Business travel,Business,147,1,1,1,1,1,4,3,4,4,4,3,1,4,5,0,0.0,satisfied +29801,110945,Male,Loyal Customer,50,Personal Travel,Eco,406,4,5,4,3,1,4,1,1,2,3,1,3,2,1,0,0.0,neutral or dissatisfied +29802,28915,Female,disloyal Customer,23,Business travel,Eco,954,2,2,2,3,4,2,4,4,2,1,1,3,5,4,0,0.0,neutral or dissatisfied +29803,92536,Female,Loyal Customer,18,Personal Travel,Eco,1919,1,4,1,1,5,1,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +29804,58972,Female,Loyal Customer,43,Business travel,Business,1846,5,5,5,5,5,3,4,5,5,5,5,4,5,3,2,5.0,satisfied +29805,78623,Male,Loyal Customer,51,Business travel,Business,1426,2,1,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +29806,29676,Female,Loyal Customer,50,Business travel,Eco Plus,680,2,2,2,2,3,5,1,2,2,2,2,4,2,5,0,0.0,satisfied +29807,54849,Male,disloyal Customer,36,Business travel,Eco,862,4,4,4,3,4,4,3,4,4,1,4,3,3,4,11,9.0,neutral or dissatisfied +29808,109378,Female,disloyal Customer,27,Business travel,Eco,1189,3,3,3,4,4,3,4,4,1,4,3,1,4,4,108,103.0,neutral or dissatisfied +29809,6692,Male,Loyal Customer,66,Business travel,Business,3672,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +29810,5922,Female,Loyal Customer,33,Personal Travel,Eco,173,2,5,2,3,2,2,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +29811,80072,Female,disloyal Customer,22,Business travel,Business,1096,5,5,4,4,2,4,2,2,4,4,4,5,5,2,0,0.0,satisfied +29812,64426,Female,Loyal Customer,42,Business travel,Business,989,1,1,1,1,5,4,5,5,5,5,5,4,5,3,4,0.0,satisfied +29813,93243,Male,disloyal Customer,28,Business travel,Business,689,4,5,5,1,3,5,3,3,3,5,5,5,4,3,4,2.0,satisfied +29814,39375,Male,Loyal Customer,47,Business travel,Eco,521,5,5,5,5,5,5,5,5,5,5,2,4,5,5,6,0.0,satisfied +29815,27339,Male,Loyal Customer,43,Business travel,Business,1604,4,4,3,4,3,4,3,5,5,5,5,4,5,3,10,14.0,satisfied +29816,62246,Male,Loyal Customer,36,Personal Travel,Eco,2454,3,4,3,3,5,3,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +29817,119997,Female,Loyal Customer,38,Business travel,Business,1582,2,1,1,1,3,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +29818,126279,Female,Loyal Customer,62,Personal Travel,Eco,468,3,4,3,3,5,4,5,3,3,3,3,3,3,3,0,6.0,neutral or dissatisfied +29819,75438,Male,Loyal Customer,25,Business travel,Business,2585,3,5,5,5,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +29820,102546,Male,Loyal Customer,30,Personal Travel,Eco,258,4,3,4,4,2,4,3,2,2,3,4,3,4,2,0,0.0,satisfied +29821,8199,Male,disloyal Customer,37,Business travel,Eco,335,4,3,4,1,1,4,1,1,3,2,5,1,4,1,1,2.0,satisfied +29822,11158,Female,Loyal Customer,51,Personal Travel,Eco,163,3,4,3,3,3,3,4,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +29823,80204,Male,disloyal Customer,27,Business travel,Business,2586,5,5,5,1,0,5,1,3,3,4,5,1,3,1,0,0.0,satisfied +29824,13113,Female,disloyal Customer,25,Business travel,Eco,562,3,4,3,3,5,3,2,5,2,3,2,2,1,5,2,0.0,neutral or dissatisfied +29825,102415,Male,Loyal Customer,64,Personal Travel,Eco,397,2,4,2,3,3,2,4,3,5,2,4,5,5,3,3,0.0,neutral or dissatisfied +29826,34936,Male,Loyal Customer,43,Personal Travel,Eco,187,3,4,3,3,2,3,3,2,5,5,5,3,4,2,74,79.0,neutral or dissatisfied +29827,34125,Female,Loyal Customer,24,Business travel,Eco,1237,5,2,2,2,5,5,5,5,5,3,2,3,4,5,6,0.0,satisfied +29828,101875,Male,Loyal Customer,34,Personal Travel,Eco,1747,4,1,4,3,1,4,1,1,4,2,4,4,3,1,0,0.0,neutral or dissatisfied +29829,45717,Female,disloyal Customer,38,Business travel,Eco,452,2,3,2,3,3,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +29830,120554,Female,Loyal Customer,57,Business travel,Eco,2176,4,1,1,1,2,4,4,4,4,4,4,4,4,1,17,12.0,neutral or dissatisfied +29831,43725,Female,Loyal Customer,47,Business travel,Eco Plus,489,4,2,4,4,4,4,3,4,4,4,4,3,4,4,0,0.0,satisfied +29832,10756,Male,Loyal Customer,46,Business travel,Eco,201,4,1,1,1,4,4,4,4,4,5,3,2,2,4,30,32.0,neutral or dissatisfied +29833,127493,Male,Loyal Customer,31,Personal Travel,Eco,2075,3,3,3,4,1,3,1,1,4,3,5,4,2,1,0,0.0,neutral or dissatisfied +29834,91223,Female,Loyal Customer,49,Personal Travel,Eco,594,2,2,2,4,2,3,3,4,4,2,4,3,4,1,88,82.0,neutral or dissatisfied +29835,111246,Male,Loyal Customer,45,Business travel,Business,1972,3,3,3,3,2,4,4,4,4,4,4,3,4,4,46,59.0,satisfied +29836,95355,Female,Loyal Customer,28,Personal Travel,Eco,293,4,5,4,1,2,4,2,2,3,3,5,4,4,2,14,11.0,neutral or dissatisfied +29837,109688,Male,Loyal Customer,28,Personal Travel,Eco,802,4,4,4,4,2,4,2,2,1,4,2,4,2,2,0,0.0,neutral or dissatisfied +29838,37579,Female,Loyal Customer,37,Business travel,Eco,610,2,3,3,3,2,2,2,4,2,3,3,2,2,2,161,155.0,neutral or dissatisfied +29839,40947,Male,Loyal Customer,12,Personal Travel,Eco Plus,588,4,1,4,3,2,4,2,2,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +29840,13125,Female,Loyal Customer,24,Business travel,Business,2124,4,2,3,3,4,4,4,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +29841,33391,Female,Loyal Customer,41,Personal Travel,Eco Plus,2614,2,5,2,2,4,5,4,5,5,2,5,4,5,5,9,0.0,neutral or dissatisfied +29842,10381,Male,Loyal Customer,39,Business travel,Business,429,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +29843,68406,Female,Loyal Customer,50,Business travel,Business,3988,3,2,4,2,4,1,1,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +29844,41556,Female,disloyal Customer,44,Business travel,Eco,1104,3,3,3,4,4,3,4,4,3,5,1,1,2,4,16,6.0,neutral or dissatisfied +29845,49409,Female,Loyal Customer,38,Business travel,Business,1960,4,4,5,4,1,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +29846,11296,Male,Loyal Customer,58,Personal Travel,Eco,482,4,3,4,4,2,4,4,2,3,5,5,1,3,2,0,0.0,neutral or dissatisfied +29847,42477,Female,Loyal Customer,8,Personal Travel,Eco,429,1,1,1,3,2,1,4,2,3,4,3,3,4,2,0,4.0,neutral or dissatisfied +29848,68789,Female,disloyal Customer,30,Business travel,Business,861,2,2,2,3,1,2,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +29849,72130,Male,disloyal Customer,33,Business travel,Eco,731,3,3,3,2,1,3,2,1,1,2,2,1,2,1,11,16.0,neutral or dissatisfied +29850,11358,Female,Loyal Customer,7,Personal Travel,Eco,429,3,3,3,1,3,3,3,3,2,5,4,4,2,3,0,0.0,neutral or dissatisfied +29851,43738,Male,Loyal Customer,46,Business travel,Business,622,1,1,1,1,4,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +29852,44881,Female,Loyal Customer,48,Business travel,Eco Plus,240,5,4,4,4,1,2,2,5,5,5,5,2,5,1,0,0.0,satisfied +29853,100084,Female,Loyal Customer,17,Personal Travel,Eco Plus,289,3,5,3,3,4,3,4,4,5,3,4,3,5,4,9,3.0,neutral or dissatisfied +29854,11691,Male,Loyal Customer,47,Business travel,Business,395,5,5,5,5,3,5,5,5,5,5,5,4,5,4,69,52.0,satisfied +29855,120147,Male,Loyal Customer,55,Personal Travel,Eco,1475,3,5,3,2,4,3,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +29856,8093,Female,Loyal Customer,60,Business travel,Business,125,4,1,4,4,3,5,4,4,4,4,4,4,4,5,0,2.0,satisfied +29857,104,Male,Loyal Customer,42,Business travel,Business,3227,3,3,1,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +29858,61155,Male,Loyal Customer,39,Business travel,Business,776,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +29859,63715,Male,Loyal Customer,21,Business travel,Business,1660,3,2,2,2,3,3,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +29860,113867,Female,Loyal Customer,25,Business travel,Business,1363,1,5,3,5,1,1,1,1,3,4,3,2,4,1,39,44.0,neutral or dissatisfied +29861,108681,Female,Loyal Customer,42,Business travel,Business,577,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +29862,21032,Male,Loyal Customer,43,Business travel,Business,3054,2,2,2,2,3,1,3,5,5,5,4,2,5,4,0,7.0,satisfied +29863,16720,Female,Loyal Customer,51,Business travel,Business,1167,4,4,3,4,5,5,5,5,5,5,5,5,5,5,12,0.0,satisfied +29864,97246,Female,disloyal Customer,21,Business travel,Business,296,4,2,4,2,1,4,1,1,5,3,5,3,5,1,0,0.0,satisfied +29865,75630,Female,Loyal Customer,57,Personal Travel,Eco Plus,337,2,5,2,4,5,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29866,48836,Male,Loyal Customer,9,Personal Travel,Business,109,4,5,4,2,5,4,5,5,3,4,5,4,5,5,7,4.0,neutral or dissatisfied +29867,29042,Male,Loyal Customer,53,Personal Travel,Eco,679,4,4,4,1,4,4,4,4,4,3,5,4,5,4,72,74.0,satisfied +29868,11511,Female,Loyal Customer,69,Personal Travel,Eco Plus,429,3,3,3,4,2,2,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +29869,84306,Male,Loyal Customer,25,Personal Travel,Eco,235,3,4,0,3,4,0,4,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +29870,118632,Female,Loyal Customer,50,Business travel,Eco,451,4,1,1,1,1,4,3,4,4,4,4,3,4,2,23,11.0,neutral or dissatisfied +29871,24231,Female,Loyal Customer,46,Business travel,Business,2350,4,4,4,4,1,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +29872,36597,Male,Loyal Customer,37,Business travel,Eco,1237,5,1,1,1,5,5,5,5,3,1,5,1,1,5,0,0.0,satisfied +29873,13972,Male,Loyal Customer,64,Personal Travel,Eco,317,2,2,2,4,4,2,5,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +29874,46762,Male,Loyal Customer,40,Business travel,Eco Plus,125,5,5,5,5,5,5,5,5,5,5,2,3,3,5,0,0.0,satisfied +29875,29929,Male,Loyal Customer,34,Business travel,Business,3890,5,5,5,5,5,3,2,5,5,5,5,4,5,1,5,33.0,satisfied +29876,13952,Male,Loyal Customer,15,Personal Travel,Eco,192,1,4,1,4,1,1,1,1,3,4,5,4,4,1,0,3.0,neutral or dissatisfied +29877,115979,Female,Loyal Customer,11,Personal Travel,Eco,337,2,5,2,5,4,2,4,4,3,4,4,3,4,4,35,24.0,neutral or dissatisfied +29878,110127,Female,Loyal Customer,44,Business travel,Business,1621,2,4,4,4,4,4,4,2,2,2,2,2,2,1,0,5.0,neutral or dissatisfied +29879,55137,Male,Loyal Customer,61,Personal Travel,Eco,1635,1,1,1,2,5,1,3,5,2,1,1,3,2,5,0,7.0,neutral or dissatisfied +29880,124445,Female,Loyal Customer,61,Personal Travel,Business,980,2,3,1,1,1,3,2,1,1,1,3,3,1,5,0,0.0,neutral or dissatisfied +29881,124465,Male,Loyal Customer,31,Personal Travel,Eco,980,4,5,4,3,4,4,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +29882,49151,Male,Loyal Customer,50,Business travel,Eco,109,4,3,3,3,5,4,5,5,4,5,2,3,5,5,0,0.0,satisfied +29883,74124,Male,disloyal Customer,34,Business travel,Eco,721,3,3,3,4,4,3,4,4,2,2,4,3,3,4,0,6.0,neutral or dissatisfied +29884,14810,Female,Loyal Customer,40,Personal Travel,Eco,95,5,3,0,4,1,0,1,1,5,2,3,2,5,1,0,0.0,satisfied +29885,92549,Female,Loyal Customer,12,Personal Travel,Eco,1892,2,3,2,2,1,2,1,1,3,1,2,3,2,1,0,0.0,neutral or dissatisfied +29886,62036,Male,Loyal Customer,26,Business travel,Business,2586,4,4,4,4,5,5,5,5,4,5,4,5,5,5,35,9.0,satisfied +29887,112000,Male,Loyal Customer,8,Business travel,Eco Plus,770,2,1,1,1,2,2,2,2,3,1,3,2,3,2,103,120.0,neutral or dissatisfied +29888,91800,Female,Loyal Customer,13,Personal Travel,Eco,532,1,5,1,4,1,1,1,1,5,4,4,3,5,1,0,7.0,neutral or dissatisfied +29889,72091,Male,disloyal Customer,49,Personal Travel,Eco,2486,0,2,1,4,2,1,3,2,1,1,4,4,3,2,0,0.0,satisfied +29890,71487,Female,disloyal Customer,26,Business travel,Business,1012,3,2,2,4,3,2,1,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +29891,1418,Female,Loyal Customer,12,Personal Travel,Eco Plus,354,1,5,1,2,3,1,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +29892,2439,Female,Loyal Customer,49,Personal Travel,Eco,641,2,4,2,2,2,5,5,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +29893,115319,Female,Loyal Customer,41,Business travel,Business,371,5,5,5,5,5,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +29894,14275,Male,Loyal Customer,47,Business travel,Eco,429,5,2,2,2,5,5,5,5,3,4,2,3,4,5,0,0.0,satisfied +29895,18703,Male,Loyal Customer,47,Business travel,Eco Plus,190,2,4,4,4,2,2,2,4,4,3,2,2,5,2,414,410.0,satisfied +29896,72179,Male,Loyal Customer,26,Business travel,Business,3484,2,2,2,2,5,5,5,5,3,5,4,4,4,5,0,0.0,satisfied +29897,113387,Male,Loyal Customer,57,Business travel,Business,3482,5,5,2,5,3,4,4,4,4,4,5,4,4,5,21,12.0,satisfied +29898,97555,Male,disloyal Customer,40,Business travel,Business,448,3,3,3,5,4,3,5,4,3,2,4,4,4,4,14,7.0,neutral or dissatisfied +29899,50625,Female,Loyal Customer,49,Personal Travel,Eco,86,2,2,2,3,5,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +29900,17504,Female,Loyal Customer,68,Business travel,Business,352,3,5,5,5,3,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +29901,41335,Female,Loyal Customer,39,Personal Travel,Eco,689,2,4,3,5,3,3,3,3,5,5,5,3,4,3,3,0.0,neutral or dissatisfied +29902,40430,Female,Loyal Customer,29,Business travel,Eco,222,0,1,1,3,1,1,1,1,3,5,3,1,5,1,0,0.0,satisfied +29903,106842,Male,Loyal Customer,53,Business travel,Eco,233,3,3,3,3,3,3,3,3,2,1,3,2,3,3,40,44.0,neutral or dissatisfied +29904,121884,Male,Loyal Customer,27,Personal Travel,Eco,366,2,4,2,4,1,2,1,1,1,2,1,4,3,1,0,0.0,neutral or dissatisfied +29905,126574,Female,Loyal Customer,31,Personal Travel,Eco,1558,4,5,4,5,3,4,3,3,4,4,5,3,5,3,0,14.0,satisfied +29906,96086,Female,Loyal Customer,34,Personal Travel,Eco,583,4,4,4,3,4,4,4,4,4,3,5,5,5,4,6,13.0,neutral or dissatisfied +29907,113349,Female,disloyal Customer,38,Business travel,Business,223,4,4,4,3,2,4,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +29908,59744,Female,Loyal Customer,52,Business travel,Business,927,5,5,5,5,2,5,5,4,4,4,4,5,4,5,5,0.0,satisfied +29909,20705,Female,Loyal Customer,40,Personal Travel,Eco,584,2,4,2,4,4,2,2,4,2,3,4,4,4,4,5,0.0,neutral or dissatisfied +29910,122900,Male,Loyal Customer,56,Business travel,Business,2418,1,1,1,1,2,5,4,4,4,4,4,3,4,5,14,5.0,satisfied +29911,113975,Male,Loyal Customer,38,Business travel,Business,1728,1,1,1,1,3,3,5,5,5,5,5,4,5,4,2,0.0,satisfied +29912,110159,Female,Loyal Customer,14,Personal Travel,Eco,869,3,1,3,2,2,3,2,2,1,3,2,4,3,2,79,78.0,neutral or dissatisfied +29913,61755,Male,Loyal Customer,62,Personal Travel,Eco,1635,3,5,3,1,5,3,5,5,5,5,3,4,4,5,3,0.0,neutral or dissatisfied +29914,16023,Male,Loyal Customer,52,Personal Travel,Eco,780,2,4,2,5,3,2,3,3,1,1,3,5,5,3,15,22.0,neutral or dissatisfied +29915,75696,Female,Loyal Customer,39,Business travel,Business,1952,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +29916,102146,Female,Loyal Customer,41,Business travel,Business,3556,1,1,1,1,5,5,5,5,5,5,5,4,5,3,19,17.0,satisfied +29917,21756,Female,Loyal Customer,49,Personal Travel,Eco Plus,563,2,1,2,3,4,3,4,1,1,2,1,4,1,2,6,0.0,neutral or dissatisfied +29918,46989,Male,Loyal Customer,58,Personal Travel,Eco,833,2,5,2,4,2,2,2,2,5,4,4,3,4,2,119,,neutral or dissatisfied +29919,7473,Female,Loyal Customer,58,Personal Travel,Eco,510,4,1,4,2,5,3,2,2,2,4,2,4,2,1,12,14.0,neutral or dissatisfied +29920,64072,Female,Loyal Customer,36,Business travel,Eco,519,1,5,5,5,1,1,1,1,2,4,1,3,2,1,104,97.0,neutral or dissatisfied +29921,21786,Male,disloyal Customer,25,Business travel,Eco,241,3,2,3,3,2,3,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +29922,65656,Female,disloyal Customer,26,Business travel,Business,926,4,0,3,3,2,3,2,2,4,3,4,5,5,2,8,3.0,neutral or dissatisfied +29923,90305,Female,Loyal Customer,33,Personal Travel,Eco,773,4,5,4,4,2,4,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +29924,5995,Female,Loyal Customer,19,Business travel,Business,2756,2,5,5,5,2,2,2,2,3,3,4,3,4,2,12,19.0,neutral or dissatisfied +29925,72378,Female,Loyal Customer,44,Business travel,Business,1608,2,2,2,2,5,5,5,4,4,4,4,4,4,4,2,0.0,satisfied +29926,6199,Female,Loyal Customer,62,Personal Travel,Eco Plus,409,3,4,3,5,3,3,3,5,2,5,5,3,3,3,178,172.0,neutral or dissatisfied +29927,65632,Male,Loyal Customer,52,Personal Travel,Eco,175,2,4,2,5,3,2,3,3,3,4,5,3,4,3,4,0.0,neutral or dissatisfied +29928,76194,Male,Loyal Customer,40,Business travel,Business,2422,4,2,2,2,5,2,4,4,4,3,4,1,4,2,11,3.0,neutral or dissatisfied +29929,105630,Female,Loyal Customer,40,Business travel,Business,2724,1,1,1,1,3,5,5,4,4,4,4,4,4,5,17,10.0,satisfied +29930,85056,Female,Loyal Customer,33,Business travel,Business,2747,1,4,1,1,4,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +29931,103403,Female,disloyal Customer,48,Business travel,Eco,237,1,3,1,3,2,1,2,2,2,1,4,2,3,2,24,20.0,neutral or dissatisfied +29932,3728,Male,Loyal Customer,65,Personal Travel,Eco,544,2,2,2,3,2,2,2,2,3,4,3,2,4,2,10,0.0,neutral or dissatisfied +29933,16218,Female,Loyal Customer,25,Business travel,Eco Plus,277,5,3,2,2,5,5,5,5,4,1,4,1,5,5,0,0.0,satisfied +29934,61521,Female,Loyal Customer,15,Personal Travel,Eco,2253,3,4,3,5,3,3,3,3,5,2,5,5,4,3,72,57.0,neutral or dissatisfied +29935,51480,Female,Loyal Customer,41,Business travel,Business,3257,5,5,2,5,5,4,4,3,3,3,3,5,3,4,15,22.0,satisfied +29936,94024,Male,Loyal Customer,55,Business travel,Business,189,0,5,0,1,5,5,5,4,4,4,4,4,4,5,14,12.0,satisfied +29937,105989,Male,disloyal Customer,27,Business travel,Business,912,2,2,2,1,1,2,1,1,4,4,4,4,4,1,0,4.0,neutral or dissatisfied +29938,101502,Male,Loyal Customer,44,Business travel,Eco,345,2,2,4,2,1,2,1,1,1,1,3,1,2,1,56,48.0,neutral or dissatisfied +29939,21699,Female,Loyal Customer,17,Personal Travel,Eco,708,1,5,1,4,5,1,3,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +29940,49817,Male,Loyal Customer,32,Business travel,Business,3713,0,3,0,4,5,4,4,5,4,1,4,3,3,5,0,0.0,satisfied +29941,945,Female,Loyal Customer,61,Business travel,Business,3093,3,1,1,1,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +29942,11368,Female,Loyal Customer,55,Personal Travel,Eco,429,2,5,2,1,2,4,4,4,4,2,2,4,4,4,0,6.0,neutral or dissatisfied +29943,118415,Male,Loyal Customer,44,Business travel,Business,2738,4,4,3,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +29944,73913,Male,Loyal Customer,35,Business travel,Business,2330,5,5,5,5,2,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +29945,81206,Male,Loyal Customer,42,Business travel,Business,1426,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +29946,87481,Male,Loyal Customer,66,Business travel,Business,3705,4,2,4,2,4,2,3,4,4,4,4,4,4,2,12,8.0,neutral or dissatisfied +29947,83364,Male,Loyal Customer,38,Business travel,Business,1124,2,2,5,2,2,5,4,4,4,4,4,3,4,3,10,14.0,satisfied +29948,47294,Female,Loyal Customer,50,Business travel,Eco,541,5,3,5,5,2,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +29949,44725,Female,Loyal Customer,70,Personal Travel,Eco,67,5,4,5,1,3,5,4,1,1,5,1,4,1,5,0,0.0,satisfied +29950,106696,Female,Loyal Customer,47,Business travel,Business,516,5,4,5,5,2,4,4,5,5,5,5,5,5,3,17,9.0,satisfied +29951,344,Male,Loyal Customer,8,Personal Travel,Eco,821,2,1,2,4,1,2,1,1,2,5,4,4,4,1,18,13.0,neutral or dissatisfied +29952,64959,Female,Loyal Customer,48,Business travel,Eco,224,3,2,2,2,3,3,2,3,3,3,3,4,3,1,87,84.0,neutral or dissatisfied +29953,98239,Male,Loyal Customer,20,Business travel,Business,1850,4,3,4,4,4,4,4,4,3,3,4,3,5,4,4,11.0,satisfied +29954,86745,Female,Loyal Customer,38,Business travel,Business,3806,5,5,5,5,3,4,4,4,4,4,4,4,4,3,8,0.0,satisfied +29955,121290,Male,Loyal Customer,42,Personal Travel,Eco,2282,1,3,1,4,5,1,5,5,4,5,4,3,3,5,0,0.0,neutral or dissatisfied +29956,31738,Female,Loyal Customer,39,Business travel,Eco Plus,967,4,2,2,2,4,4,4,4,4,3,2,2,2,4,0,0.0,satisfied +29957,88649,Male,Loyal Customer,53,Personal Travel,Eco,404,2,3,2,3,2,2,3,2,1,2,3,4,4,2,88,95.0,neutral or dissatisfied +29958,113437,Female,disloyal Customer,22,Business travel,Eco,223,5,0,5,1,1,5,1,1,4,3,4,4,4,1,0,2.0,satisfied +29959,23407,Female,Loyal Customer,19,Personal Travel,Eco Plus,483,2,1,4,3,2,4,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +29960,89118,Male,Loyal Customer,24,Business travel,Eco,1892,2,1,1,1,2,4,2,2,1,3,4,2,1,2,141,135.0,neutral or dissatisfied +29961,66447,Male,disloyal Customer,50,Business travel,Eco,1217,2,2,2,3,3,2,4,3,4,3,3,4,3,3,107,96.0,neutral or dissatisfied +29962,38946,Female,Loyal Customer,35,Business travel,Eco Plus,298,3,5,4,4,3,3,3,3,4,5,4,2,3,3,25,23.0,neutral or dissatisfied +29963,26781,Female,Loyal Customer,37,Business travel,Business,799,2,2,2,2,5,5,4,4,4,4,4,5,4,4,16,0.0,satisfied +29964,102922,Female,Loyal Customer,39,Business travel,Business,317,5,5,5,5,2,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +29965,39784,Female,Loyal Customer,41,Business travel,Business,221,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,2.0,satisfied +29966,63627,Male,Loyal Customer,57,Business travel,Eco,602,4,2,2,2,5,4,5,5,4,5,2,3,2,5,0,0.0,neutral or dissatisfied +29967,49398,Male,Loyal Customer,38,Business travel,Business,89,5,5,3,5,3,5,4,5,5,5,4,2,5,3,0,0.0,satisfied +29968,110333,Female,Loyal Customer,31,Business travel,Business,2737,5,5,5,5,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +29969,50872,Male,Loyal Customer,41,Personal Travel,Eco,372,4,0,4,1,4,4,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +29970,81228,Female,disloyal Customer,44,Business travel,Business,223,2,2,2,1,3,2,3,3,5,4,4,5,5,3,0,13.0,neutral or dissatisfied +29971,23949,Male,Loyal Customer,27,Business travel,Business,936,4,4,4,4,5,5,5,5,1,4,4,3,2,5,16,6.0,satisfied +29972,71026,Male,Loyal Customer,58,Business travel,Business,1998,2,4,4,4,5,3,3,2,2,2,2,1,2,4,3,0.0,neutral or dissatisfied +29973,87366,Male,Loyal Customer,54,Business travel,Business,1749,5,5,5,5,2,4,4,3,3,3,3,3,3,4,11,3.0,satisfied +29974,57437,Male,Loyal Customer,33,Business travel,Eco,1735,2,1,4,4,2,2,2,2,2,2,3,3,3,2,12,0.0,neutral or dissatisfied +29975,78365,Male,Loyal Customer,15,Personal Travel,Business,726,3,2,3,3,1,3,1,1,2,2,4,3,4,1,0,0.0,neutral or dissatisfied +29976,65621,Female,Loyal Customer,18,Personal Travel,Eco,175,3,3,3,4,1,3,1,1,4,2,4,1,3,1,29,24.0,neutral or dissatisfied +29977,125199,Male,Loyal Customer,11,Business travel,Business,3230,2,2,2,2,2,3,2,2,4,5,4,4,5,2,0,0.0,satisfied +29978,110516,Male,Loyal Customer,58,Personal Travel,Eco Plus,787,3,4,3,2,4,3,3,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +29979,105559,Female,Loyal Customer,47,Business travel,Business,3232,0,4,0,3,4,4,4,1,1,5,5,3,1,4,0,0.0,satisfied +29980,35477,Female,Loyal Customer,61,Personal Travel,Eco,950,1,4,1,4,3,4,4,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +29981,46397,Female,Loyal Customer,40,Personal Travel,Eco,911,2,4,2,1,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +29982,121398,Male,disloyal Customer,34,Business travel,Business,331,3,3,3,3,2,3,2,2,4,5,4,3,4,2,20,25.0,neutral or dissatisfied +29983,35649,Female,disloyal Customer,24,Business travel,Eco,1178,4,4,4,1,4,1,2,5,3,5,5,2,5,2,0,0.0,satisfied +29984,3148,Male,disloyal Customer,25,Business travel,Business,140,3,5,4,2,2,4,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +29985,102939,Male,Loyal Customer,50,Business travel,Business,436,3,3,3,3,4,4,5,4,4,4,4,3,4,3,68,72.0,satisfied +29986,44826,Male,Loyal Customer,23,Business travel,Eco,462,3,5,3,5,3,3,2,3,4,3,2,2,2,3,0,0.0,neutral or dissatisfied +29987,36921,Female,Loyal Customer,52,Personal Travel,Eco,740,3,5,3,5,4,4,5,5,5,3,5,3,5,5,11,40.0,neutral or dissatisfied +29988,43486,Male,Loyal Customer,61,Business travel,Business,2683,4,3,4,4,2,2,3,4,4,4,3,2,4,3,0,3.0,satisfied +29989,121410,Female,Loyal Customer,57,Business travel,Business,1937,5,5,5,5,5,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +29990,2925,Female,disloyal Customer,20,Business travel,Eco,806,3,3,3,4,5,3,5,5,4,5,4,2,3,5,0,0.0,neutral or dissatisfied +29991,61699,Female,Loyal Customer,59,Business travel,Business,1379,3,3,4,4,4,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +29992,52094,Male,Loyal Customer,45,Personal Travel,Eco,438,3,2,3,2,2,3,2,2,3,3,2,1,3,2,0,0.0,neutral or dissatisfied +29993,62288,Female,Loyal Customer,37,Business travel,Business,414,4,4,4,4,5,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +29994,124592,Female,Loyal Customer,39,Business travel,Business,500,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +29995,24439,Male,Loyal Customer,29,Business travel,Business,1517,4,5,5,5,4,4,4,4,3,3,3,1,4,4,0,2.0,neutral or dissatisfied +29996,106377,Female,Loyal Customer,51,Business travel,Eco,674,3,2,2,2,1,3,3,3,3,3,3,4,3,3,14,17.0,neutral or dissatisfied +29997,57599,Female,disloyal Customer,66,Business travel,Eco,563,3,1,4,2,2,4,2,2,3,3,3,2,2,2,18,0.0,neutral or dissatisfied +29998,117832,Female,Loyal Customer,33,Personal Travel,Eco,328,3,3,3,3,5,3,5,5,1,1,4,2,2,5,13,10.0,neutral or dissatisfied +29999,28108,Female,Loyal Customer,51,Business travel,Eco,569,4,4,4,4,3,5,1,4,4,4,4,1,4,3,0,0.0,satisfied +30000,128149,Female,disloyal Customer,24,Business travel,Business,1080,5,0,5,1,1,5,5,1,5,3,4,5,5,1,2,8.0,satisfied +30001,82717,Male,Loyal Customer,43,Personal Travel,Eco,632,2,5,2,2,3,2,5,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +30002,95463,Female,Loyal Customer,52,Business travel,Business,239,5,5,5,5,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +30003,45792,Female,Loyal Customer,40,Business travel,Business,3051,1,1,1,1,1,4,2,4,4,4,4,2,4,1,31,61.0,satisfied +30004,3474,Female,Loyal Customer,53,Business travel,Business,2049,5,5,5,5,5,5,5,5,2,5,4,5,5,5,137,113.0,satisfied +30005,100221,Male,Loyal Customer,40,Business travel,Business,2011,5,5,3,5,3,4,5,3,3,4,3,5,3,4,0,4.0,satisfied +30006,49753,Male,disloyal Customer,26,Business travel,Eco,250,2,0,2,4,2,4,4,2,3,2,2,4,3,4,173,177.0,neutral or dissatisfied +30007,129375,Female,Loyal Customer,16,Business travel,Business,2454,2,2,2,2,2,2,2,2,2,5,3,3,3,2,4,7.0,neutral or dissatisfied +30008,117971,Female,Loyal Customer,65,Personal Travel,Eco,365,2,5,2,2,5,5,4,5,5,2,5,4,5,3,1,1.0,neutral or dissatisfied +30009,116528,Male,Loyal Customer,40,Personal Travel,Eco,337,0,4,0,3,5,0,5,5,4,4,5,3,5,5,0,0.0,satisfied +30010,120981,Male,disloyal Customer,45,Business travel,Eco,992,2,2,2,3,3,2,3,3,2,5,3,1,2,3,1,19.0,neutral or dissatisfied +30011,107554,Female,Loyal Customer,36,Business travel,Business,1521,3,4,2,4,3,3,3,3,3,3,3,4,3,4,2,22.0,neutral or dissatisfied +30012,36133,Male,Loyal Customer,42,Business travel,Business,1562,2,4,4,4,2,3,4,2,2,2,2,3,2,2,19,6.0,neutral or dissatisfied +30013,101879,Female,Loyal Customer,19,Personal Travel,Eco,1747,4,1,4,4,2,4,2,2,3,1,3,4,4,2,0,0.0,satisfied +30014,27276,Male,Loyal Customer,36,Personal Travel,Business,605,2,2,1,3,4,3,3,3,3,1,3,1,3,1,1,13.0,neutral or dissatisfied +30015,69004,Female,Loyal Customer,61,Business travel,Business,1521,2,1,1,1,1,2,3,2,2,2,2,3,2,2,0,31.0,neutral or dissatisfied +30016,17535,Female,Loyal Customer,25,Business travel,Business,297,1,5,1,5,1,1,1,1,1,2,2,3,2,1,0,0.0,neutral or dissatisfied +30017,50372,Male,Loyal Customer,31,Business travel,Business,3119,3,3,3,3,5,5,5,5,3,5,3,5,5,5,3,0.0,satisfied +30018,16523,Female,Loyal Customer,60,Business travel,Business,209,0,3,0,2,4,2,5,3,3,3,3,5,3,5,25,18.0,satisfied +30019,34188,Female,Loyal Customer,59,Personal Travel,Eco,1046,5,5,5,3,5,4,4,5,5,5,5,4,5,3,10,4.0,satisfied +30020,60406,Female,Loyal Customer,28,Personal Travel,Eco,1452,2,5,2,2,4,2,4,4,2,5,4,1,5,4,97,93.0,neutral or dissatisfied +30021,50050,Male,Loyal Customer,54,Business travel,Business,3280,1,1,1,1,1,4,5,5,5,5,5,2,5,1,0,3.0,satisfied +30022,71801,Female,Loyal Customer,68,Business travel,Business,1723,1,1,1,1,3,2,4,1,1,1,1,3,1,3,1,0.0,neutral or dissatisfied +30023,75200,Male,Loyal Customer,54,Business travel,Eco,1829,2,3,4,3,2,2,2,2,2,5,2,1,3,2,0,0.0,neutral or dissatisfied +30024,90229,Male,Loyal Customer,19,Business travel,Business,3800,5,5,5,5,3,3,3,3,3,4,4,4,5,3,0,0.0,satisfied +30025,96758,Female,Loyal Customer,51,Business travel,Business,849,2,3,3,3,1,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +30026,81235,Female,Loyal Customer,55,Personal Travel,Eco,223,1,4,1,2,5,1,3,1,1,1,1,5,1,1,0,0.0,neutral or dissatisfied +30027,67012,Female,Loyal Customer,53,Business travel,Business,1121,2,2,3,2,5,5,4,5,5,5,5,5,5,4,0,42.0,satisfied +30028,61304,Male,Loyal Customer,18,Personal Travel,Eco,862,3,4,3,3,5,3,5,5,4,1,3,3,3,5,43,36.0,neutral or dissatisfied +30029,106241,Male,Loyal Customer,70,Personal Travel,Eco Plus,471,5,3,5,4,4,5,4,4,4,1,3,1,4,4,0,0.0,satisfied +30030,41296,Female,Loyal Customer,38,Business travel,Eco,444,5,5,5,5,5,5,5,5,3,4,4,4,3,5,0,0.0,satisfied +30031,83853,Male,Loyal Customer,50,Personal Travel,Eco,425,1,1,2,3,3,2,3,3,4,1,3,2,4,3,22,31.0,neutral or dissatisfied +30032,44490,Male,Loyal Customer,43,Business travel,Business,844,2,2,2,2,5,3,4,2,2,3,2,4,2,4,5,0.0,neutral or dissatisfied +30033,6450,Male,Loyal Customer,68,Business travel,Business,2992,5,5,5,5,5,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +30034,31361,Male,Loyal Customer,60,Business travel,Business,589,4,3,3,3,1,2,3,4,4,4,4,4,4,2,19,44.0,neutral or dissatisfied +30035,62001,Female,Loyal Customer,47,Business travel,Business,2586,1,1,1,1,3,3,5,5,5,5,5,4,5,3,2,0.0,satisfied +30036,43329,Male,Loyal Customer,48,Business travel,Business,463,2,2,2,2,3,4,3,2,2,2,2,4,2,1,2,8.0,neutral or dissatisfied +30037,114189,Male,Loyal Customer,32,Business travel,Business,2111,2,1,1,1,2,2,2,2,1,2,3,4,3,2,0,0.0,neutral or dissatisfied +30038,24068,Female,Loyal Customer,11,Personal Travel,Eco Plus,427,1,0,1,4,3,1,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +30039,44018,Female,Loyal Customer,36,Business travel,Eco Plus,397,5,3,3,3,5,5,5,5,2,2,3,1,2,5,0,0.0,satisfied +30040,97653,Male,Loyal Customer,36,Business travel,Business,1587,1,1,1,1,4,3,4,5,5,5,5,4,5,3,0,21.0,satisfied +30041,116837,Male,Loyal Customer,44,Business travel,Business,451,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +30042,127908,Male,Loyal Customer,34,Personal Travel,Eco,1671,3,5,3,4,3,3,3,3,4,1,3,5,5,3,22,14.0,neutral or dissatisfied +30043,42569,Female,Loyal Customer,54,Business travel,Business,315,1,1,1,1,3,5,2,4,4,4,4,3,4,2,0,0.0,satisfied +30044,104873,Female,disloyal Customer,21,Business travel,Eco,327,2,0,2,3,5,2,5,5,2,5,4,2,4,5,26,35.0,neutral or dissatisfied +30045,79108,Female,Loyal Customer,51,Personal Travel,Eco,226,3,5,3,1,3,1,1,5,5,5,5,1,4,1,165,167.0,neutral or dissatisfied +30046,73139,Female,Loyal Customer,12,Personal Travel,Eco,1068,2,4,2,3,2,2,5,2,5,4,5,3,4,2,0,3.0,neutral or dissatisfied +30047,35228,Male,Loyal Customer,45,Business travel,Eco,1005,5,3,5,3,5,5,5,5,2,5,2,5,2,5,0,24.0,satisfied +30048,71924,Female,Loyal Customer,25,Business travel,Business,1744,5,5,5,5,4,4,4,4,4,3,4,4,4,4,0,0.0,satisfied +30049,87793,Female,Loyal Customer,48,Business travel,Business,3740,2,2,5,2,2,4,5,5,5,5,4,5,5,4,0,9.0,satisfied +30050,4061,Male,Loyal Customer,60,Personal Travel,Eco,419,3,5,3,1,3,3,2,3,1,5,4,5,1,3,0,1.0,neutral or dissatisfied +30051,82730,Male,Loyal Customer,55,Personal Travel,Business,409,4,5,4,2,5,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +30052,42507,Female,disloyal Customer,8,Business travel,Business,541,2,2,2,3,4,2,4,4,3,4,4,1,4,4,0,9.0,neutral or dissatisfied +30053,37585,Male,Loyal Customer,50,Business travel,Eco,544,5,2,2,2,5,5,5,5,5,3,3,1,4,5,0,0.0,satisfied +30054,68634,Female,Loyal Customer,46,Business travel,Business,2608,3,3,3,3,5,3,3,4,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +30055,45159,Male,Loyal Customer,51,Business travel,Business,3892,4,3,3,3,3,3,3,3,3,3,4,4,3,2,74,101.0,neutral or dissatisfied +30056,91505,Male,Loyal Customer,37,Business travel,Business,1626,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +30057,48396,Male,Loyal Customer,52,Personal Travel,Eco,587,4,4,4,4,5,4,5,5,4,4,3,4,3,5,10,0.0,neutral or dissatisfied +30058,20153,Male,disloyal Customer,26,Business travel,Eco,403,3,4,3,3,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +30059,69938,Male,Loyal Customer,27,Business travel,Business,2174,2,2,2,2,3,3,3,3,5,5,4,5,5,3,1,0.0,satisfied +30060,23078,Male,Loyal Customer,22,Personal Travel,Eco,1174,2,4,2,5,4,2,4,4,4,2,3,3,4,4,0,7.0,neutral or dissatisfied +30061,16883,Female,Loyal Customer,41,Business travel,Eco,708,3,3,2,3,3,3,3,3,4,4,3,3,2,3,0,0.0,neutral or dissatisfied +30062,78467,Female,disloyal Customer,36,Business travel,Business,526,2,2,2,2,5,2,5,5,3,4,4,3,5,5,0,12.0,neutral or dissatisfied +30063,52263,Male,Loyal Customer,33,Business travel,Business,493,1,1,1,1,2,2,2,2,5,5,4,4,2,2,0,5.0,satisfied +30064,1890,Male,Loyal Customer,29,Business travel,Business,295,1,1,1,1,4,4,4,4,5,3,4,3,5,4,3,2.0,satisfied +30065,128368,Male,Loyal Customer,55,Business travel,Business,621,2,2,2,2,3,4,4,5,5,5,5,3,5,3,23,17.0,satisfied +30066,52807,Male,disloyal Customer,46,Business travel,Eco,1312,3,3,3,3,4,3,4,4,4,2,5,3,4,4,1,0.0,neutral or dissatisfied +30067,14019,Female,Loyal Customer,50,Personal Travel,Eco,182,1,3,0,3,2,2,3,5,5,0,3,3,5,2,0,0.0,neutral or dissatisfied +30068,70507,Female,Loyal Customer,64,Personal Travel,Eco,867,3,5,3,2,3,2,3,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +30069,101476,Male,disloyal Customer,37,Business travel,Business,345,2,2,2,5,5,2,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +30070,57735,Female,disloyal Customer,23,Business travel,Eco,1046,4,4,4,4,3,4,3,3,1,3,5,4,4,3,2,0.0,satisfied +30071,36529,Male,disloyal Customer,44,Business travel,Business,1121,1,1,1,2,3,1,3,3,2,3,1,1,2,3,0,0.0,neutral or dissatisfied +30072,105533,Male,disloyal Customer,36,Business travel,Eco,611,4,1,4,3,1,4,1,1,3,5,2,3,2,1,0,0.0,neutral or dissatisfied +30073,34254,Male,Loyal Customer,37,Business travel,Eco,166,5,1,1,1,5,5,5,5,4,3,1,4,5,5,0,0.0,satisfied +30074,73908,Female,Loyal Customer,52,Business travel,Business,2218,3,3,3,3,5,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +30075,11481,Female,Loyal Customer,29,Personal Travel,Eco Plus,482,2,5,2,3,2,2,2,2,3,1,2,5,1,2,0,0.0,neutral or dissatisfied +30076,67322,Male,Loyal Customer,33,Personal Travel,Eco Plus,1121,0,4,0,2,4,0,5,4,5,3,3,4,5,4,2,0.0,satisfied +30077,11545,Female,Loyal Customer,37,Business travel,Business,372,4,4,1,4,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +30078,78444,Male,Loyal Customer,47,Business travel,Business,3732,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,3.0,satisfied +30079,121339,Male,Loyal Customer,49,Business travel,Business,2909,2,2,2,2,5,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +30080,48556,Male,Loyal Customer,38,Personal Travel,Eco,846,1,4,1,1,1,1,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +30081,48025,Female,Loyal Customer,25,Business travel,Eco,1384,0,4,0,1,3,0,1,3,5,4,2,5,5,3,51,33.0,satisfied +30082,14531,Male,Loyal Customer,60,Business travel,Eco,368,1,1,2,1,1,1,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +30083,119364,Female,Loyal Customer,62,Personal Travel,Business,399,2,4,2,3,2,5,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +30084,35899,Male,Loyal Customer,42,Business travel,Eco Plus,1065,2,1,5,1,2,2,2,2,2,5,4,2,3,2,45,50.0,neutral or dissatisfied +30085,77935,Female,Loyal Customer,46,Business travel,Business,2995,2,2,2,2,3,4,5,5,5,5,4,5,5,4,18,34.0,satisfied +30086,122466,Male,Loyal Customer,66,Business travel,Business,575,2,3,5,5,3,4,3,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +30087,67682,Female,Loyal Customer,47,Business travel,Business,1464,1,2,2,2,5,1,1,1,1,1,1,3,1,1,13,11.0,neutral or dissatisfied +30088,466,Female,Loyal Customer,48,Business travel,Business,102,3,3,3,3,5,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +30089,98021,Female,Loyal Customer,35,Business travel,Business,1014,3,3,3,3,1,3,3,3,3,3,3,4,3,1,13,11.0,neutral or dissatisfied +30090,64126,Female,Loyal Customer,52,Personal Travel,Eco,2311,1,5,1,3,3,4,5,2,2,1,2,1,2,1,0,0.0,neutral or dissatisfied +30091,95200,Female,Loyal Customer,49,Personal Travel,Eco,239,4,4,4,3,3,4,4,2,2,4,2,4,2,3,22,32.0,neutral or dissatisfied +30092,30189,Male,Loyal Customer,48,Business travel,Eco Plus,725,4,4,4,4,4,4,4,4,2,2,3,3,3,4,0,0.0,satisfied +30093,86892,Female,Loyal Customer,11,Personal Travel,Business,341,2,3,2,3,2,2,2,2,3,1,4,1,4,2,3,3.0,neutral or dissatisfied +30094,85149,Female,disloyal Customer,25,Business travel,Business,813,0,0,0,1,2,0,2,2,3,3,4,4,4,2,0,0.0,satisfied +30095,48128,Male,Loyal Customer,46,Business travel,Business,236,0,0,0,2,2,1,4,3,3,3,3,2,3,4,0,0.0,satisfied +30096,89679,Female,Loyal Customer,48,Business travel,Business,550,3,3,3,3,4,5,5,5,5,5,5,1,5,4,3,0.0,satisfied +30097,80347,Female,Loyal Customer,58,Business travel,Business,422,5,1,1,1,5,3,3,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +30098,129806,Female,Loyal Customer,13,Personal Travel,Eco,308,0,4,0,3,4,0,4,4,2,1,2,3,3,4,0,0.0,satisfied +30099,102738,Male,Loyal Customer,52,Personal Travel,Eco,255,2,0,2,1,1,2,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +30100,74852,Male,Loyal Customer,56,Personal Travel,Eco,2136,2,3,2,3,2,2,3,2,3,1,4,1,1,2,0,0.0,neutral or dissatisfied +30101,19273,Male,Loyal Customer,26,Business travel,Business,430,5,5,5,5,4,5,4,4,2,2,3,2,5,4,0,0.0,satisfied +30102,110785,Female,disloyal Customer,26,Business travel,Eco,1166,3,4,4,4,5,4,5,5,1,5,4,1,3,5,2,33.0,neutral or dissatisfied +30103,82712,Male,Loyal Customer,38,Personal Travel,Eco,632,1,1,1,3,4,1,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +30104,118282,Female,Loyal Customer,24,Business travel,Business,3706,3,3,4,3,3,4,3,3,5,4,4,5,4,3,4,0.0,satisfied +30105,72434,Female,Loyal Customer,44,Business travel,Business,929,4,4,4,4,4,4,5,4,4,5,4,3,4,3,1,18.0,satisfied +30106,68351,Female,Loyal Customer,60,Business travel,Business,1598,3,3,5,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +30107,116430,Male,Loyal Customer,45,Personal Travel,Eco,417,3,2,3,3,5,3,5,5,2,1,2,3,2,5,0,8.0,neutral or dissatisfied +30108,115854,Male,Loyal Customer,68,Business travel,Business,2177,2,2,2,2,4,4,5,4,4,4,4,4,4,5,25,15.0,satisfied +30109,16723,Female,disloyal Customer,26,Business travel,Eco,1167,4,3,3,1,3,1,1,4,2,3,1,1,1,1,174,164.0,neutral or dissatisfied +30110,55899,Female,disloyal Customer,34,Business travel,Eco,473,1,2,1,4,1,1,5,1,2,1,3,3,4,1,100,96.0,neutral or dissatisfied +30111,81955,Female,Loyal Customer,42,Business travel,Business,1589,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +30112,93743,Female,Loyal Customer,42,Business travel,Business,368,5,5,5,5,4,4,4,5,5,5,5,3,5,5,17,9.0,satisfied +30113,94381,Female,Loyal Customer,41,Business travel,Business,2737,4,5,4,4,4,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +30114,79483,Female,Loyal Customer,24,Business travel,Business,762,4,4,1,4,5,4,5,5,4,4,4,4,4,5,0,0.0,satisfied +30115,84087,Male,Loyal Customer,46,Personal Travel,Eco,757,3,5,3,2,5,3,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +30116,109456,Male,Loyal Customer,51,Business travel,Business,2859,4,4,4,4,2,5,5,5,5,5,5,4,5,3,3,27.0,satisfied +30117,128594,Male,Loyal Customer,40,Business travel,Business,954,3,3,3,3,4,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +30118,17154,Male,Loyal Customer,43,Business travel,Business,2753,1,2,2,2,2,2,2,1,1,1,1,2,1,4,53,38.0,neutral or dissatisfied +30119,87580,Male,Loyal Customer,55,Personal Travel,Eco,432,3,4,3,3,1,3,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +30120,81093,Female,Loyal Customer,31,Personal Travel,Eco,931,2,4,2,2,1,2,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +30121,10581,Male,Loyal Customer,38,Business travel,Business,1639,2,2,2,2,4,4,5,3,3,4,3,3,3,3,11,7.0,satisfied +30122,88781,Female,Loyal Customer,32,Business travel,Eco Plus,404,2,1,1,1,2,1,2,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +30123,16205,Female,Loyal Customer,26,Personal Travel,Eco,199,3,4,3,1,1,3,1,1,5,5,5,3,4,1,15,16.0,neutral or dissatisfied +30124,60412,Male,Loyal Customer,24,Business travel,Eco Plus,1452,2,3,3,3,2,3,3,2,2,1,4,1,4,2,18,10.0,neutral or dissatisfied +30125,83620,Male,Loyal Customer,49,Personal Travel,Eco,409,2,2,1,4,2,1,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +30126,87506,Female,Loyal Customer,53,Personal Travel,Eco,321,4,5,3,4,5,1,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +30127,79523,Female,Loyal Customer,47,Business travel,Business,1865,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +30128,7935,Female,Loyal Customer,41,Personal Travel,Business,594,3,5,3,1,5,5,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +30129,19651,Female,Loyal Customer,35,Business travel,Eco,763,5,3,3,3,5,5,5,5,2,2,2,1,2,5,59,66.0,satisfied +30130,106219,Female,Loyal Customer,46,Business travel,Eco,471,3,4,4,4,4,3,4,3,3,3,3,2,3,4,38,30.0,neutral or dissatisfied +30131,115511,Male,Loyal Customer,73,Business travel,Business,3532,3,1,1,1,4,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +30132,84591,Male,Loyal Customer,47,Business travel,Business,669,5,5,2,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +30133,353,Female,Loyal Customer,37,Personal Travel,Eco Plus,821,4,5,3,3,5,3,4,5,3,4,1,2,1,5,0,15.0,neutral or dissatisfied +30134,109232,Male,Loyal Customer,29,Personal Travel,Eco,793,2,5,2,3,3,2,4,3,3,5,5,5,5,3,7,8.0,neutral or dissatisfied +30135,114524,Female,Loyal Customer,67,Personal Travel,Business,390,3,4,3,3,4,3,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +30136,4834,Female,disloyal Customer,25,Business travel,Business,408,5,3,4,5,1,4,4,1,5,2,5,3,5,1,0,0.0,satisfied +30137,73726,Female,Loyal Customer,32,Business travel,Eco,204,2,2,2,2,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +30138,74358,Male,disloyal Customer,28,Business travel,Business,1205,0,0,0,1,5,0,5,5,3,3,4,3,5,5,49,41.0,satisfied +30139,74939,Female,Loyal Customer,37,Business travel,Business,2475,4,4,4,4,3,4,4,4,4,4,4,4,4,5,17,0.0,satisfied +30140,36148,Male,Loyal Customer,24,Business travel,Business,2745,1,1,1,1,5,5,5,5,3,3,2,1,2,5,39,38.0,satisfied +30141,129425,Female,Loyal Customer,58,Business travel,Business,3155,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +30142,3332,Female,Loyal Customer,28,Business travel,Business,3306,5,5,5,5,5,5,5,5,5,3,4,5,5,5,13,5.0,satisfied +30143,34820,Male,Loyal Customer,65,Personal Travel,Eco,209,3,4,3,2,1,3,1,1,1,5,3,2,2,1,12,15.0,neutral or dissatisfied +30144,19394,Female,Loyal Customer,64,Personal Travel,Eco Plus,844,3,4,3,3,3,5,4,4,4,3,4,3,4,5,17,10.0,neutral or dissatisfied +30145,108755,Male,Loyal Customer,42,Business travel,Business,404,4,4,4,4,2,4,4,5,5,5,5,4,5,3,79,79.0,satisfied +30146,23739,Female,disloyal Customer,23,Business travel,Eco,639,3,0,3,1,1,3,1,1,4,1,3,2,5,1,4,10.0,neutral or dissatisfied +30147,16605,Male,Loyal Customer,33,Business travel,Business,3605,5,1,5,5,3,3,3,3,3,4,1,2,1,3,0,6.0,satisfied +30148,61210,Male,Loyal Customer,37,Business travel,Business,967,2,5,5,5,4,2,2,2,2,2,2,3,2,3,42,37.0,neutral or dissatisfied +30149,43108,Female,Loyal Customer,45,Personal Travel,Eco,192,2,5,2,3,4,5,4,3,3,2,3,3,3,3,99,104.0,neutral or dissatisfied +30150,56233,Female,Loyal Customer,37,Personal Travel,Eco,1608,4,1,4,4,5,4,5,5,4,2,3,2,4,5,5,24.0,neutral or dissatisfied +30151,83327,Male,Loyal Customer,46,Business travel,Business,2105,3,3,3,3,2,4,4,3,3,2,3,3,3,4,0,6.0,satisfied +30152,127967,Male,Loyal Customer,18,Personal Travel,Eco,1999,3,5,3,4,2,3,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +30153,110557,Female,Loyal Customer,45,Business travel,Business,3826,3,1,1,1,1,3,4,3,3,3,3,3,3,3,39,24.0,neutral or dissatisfied +30154,14549,Female,Loyal Customer,35,Personal Travel,Eco,368,3,1,2,3,2,2,2,2,4,2,2,3,3,2,111,117.0,neutral or dissatisfied +30155,42526,Male,Loyal Customer,29,Business travel,Business,2507,2,1,1,1,2,2,2,2,2,2,2,1,1,2,0,0.0,neutral or dissatisfied +30156,93877,Male,Loyal Customer,50,Business travel,Business,1521,3,3,3,3,2,4,4,4,4,5,4,3,4,5,35,42.0,satisfied +30157,100933,Male,Loyal Customer,67,Personal Travel,Eco,838,3,5,3,5,2,3,2,2,4,2,5,5,4,2,0,5.0,neutral or dissatisfied +30158,52155,Female,Loyal Customer,8,Personal Travel,Business,651,3,3,3,3,1,3,1,1,3,3,5,2,3,1,0,7.0,neutral or dissatisfied +30159,118979,Female,Loyal Customer,51,Business travel,Business,3542,4,4,4,4,3,4,5,3,3,3,3,4,3,4,7,5.0,satisfied +30160,77898,Female,disloyal Customer,26,Business travel,Business,610,1,0,1,4,3,1,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +30161,6305,Female,Loyal Customer,14,Personal Travel,Business,315,3,4,3,3,5,3,1,5,3,5,4,5,4,5,11,7.0,neutral or dissatisfied +30162,59276,Female,Loyal Customer,22,Personal Travel,Business,3302,3,3,3,3,3,3,3,3,1,4,3,3,3,3,1,0.0,neutral or dissatisfied +30163,112475,Male,Loyal Customer,70,Personal Travel,Eco,819,3,0,3,3,4,3,1,4,3,4,5,4,5,4,2,0.0,neutral or dissatisfied +30164,32278,Male,Loyal Customer,69,Business travel,Business,163,0,5,0,3,5,3,4,5,5,5,5,4,5,4,47,57.0,satisfied +30165,25877,Female,disloyal Customer,49,Business travel,Eco,907,4,4,4,3,4,4,4,4,4,1,3,1,2,4,15,0.0,neutral or dissatisfied +30166,79005,Male,Loyal Customer,39,Business travel,Business,226,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +30167,64995,Female,disloyal Customer,26,Business travel,Eco,551,3,4,3,5,2,3,2,2,4,1,2,5,5,2,0,0.0,neutral or dissatisfied +30168,28537,Male,Loyal Customer,37,Business travel,Business,2640,2,4,4,4,3,1,2,2,2,2,2,2,2,1,5,0.0,neutral or dissatisfied +30169,124330,Female,Loyal Customer,20,Personal Travel,Eco Plus,255,1,5,1,1,2,1,2,2,4,1,1,4,5,2,0,3.0,neutral or dissatisfied +30170,23453,Male,Loyal Customer,27,Business travel,Business,576,2,2,2,2,5,5,5,5,2,4,5,1,4,5,14,32.0,satisfied +30171,115776,Male,disloyal Customer,33,Business travel,Business,362,1,1,1,3,2,1,3,2,3,4,3,1,3,2,82,86.0,neutral or dissatisfied +30172,94145,Male,Loyal Customer,52,Business travel,Business,277,4,4,4,4,3,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +30173,90388,Female,Loyal Customer,24,Personal Travel,Business,515,1,2,2,4,1,2,1,1,2,4,4,3,3,1,69,57.0,neutral or dissatisfied +30174,60631,Male,Loyal Customer,32,Business travel,Business,1620,1,1,1,1,4,5,4,4,5,2,3,3,4,4,0,0.0,satisfied +30175,30741,Female,Loyal Customer,50,Business travel,Eco,589,1,2,2,2,5,3,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +30176,15994,Male,Loyal Customer,28,Business travel,Eco,780,4,1,1,1,4,4,4,4,5,1,5,1,3,4,0,0.0,satisfied +30177,14882,Male,Loyal Customer,54,Business travel,Eco,343,1,4,4,4,1,1,1,1,1,5,3,4,4,1,78,70.0,neutral or dissatisfied +30178,106949,Female,Loyal Customer,44,Business travel,Business,937,5,5,5,5,4,4,4,5,5,5,5,5,5,3,0,13.0,satisfied +30179,56686,Male,Loyal Customer,66,Personal Travel,Eco,997,1,3,1,2,3,1,5,3,2,4,3,3,3,3,7,0.0,neutral or dissatisfied +30180,26874,Female,disloyal Customer,25,Business travel,Eco,722,3,3,3,4,2,3,2,2,1,5,4,1,4,2,31,18.0,neutral or dissatisfied +30181,55104,Male,Loyal Customer,38,Business travel,Eco,1104,4,5,5,5,4,4,4,4,5,5,3,3,5,4,4,2.0,satisfied +30182,4065,Male,Loyal Customer,20,Personal Travel,Eco,479,3,2,3,3,4,3,4,4,4,2,2,4,3,4,18,10.0,neutral or dissatisfied +30183,46644,Male,Loyal Customer,32,Business travel,Business,125,0,4,0,4,1,1,1,1,1,3,3,1,4,1,0,0.0,satisfied +30184,41729,Female,disloyal Customer,40,Business travel,Business,695,4,4,4,3,2,4,1,2,1,4,5,5,4,2,0,4.0,neutral or dissatisfied +30185,76977,Female,Loyal Customer,45,Business travel,Business,469,2,1,1,1,1,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +30186,66019,Female,Loyal Customer,43,Business travel,Business,1055,2,2,2,2,4,4,4,3,3,3,3,5,3,4,2,0.0,satisfied +30187,92493,Male,Loyal Customer,45,Business travel,Eco,447,5,2,2,2,5,3,3,3,2,4,3,3,3,3,559,555.0,satisfied +30188,111685,Female,Loyal Customer,27,Personal Travel,Business,495,2,4,2,4,5,2,5,5,2,4,4,2,4,5,3,6.0,neutral or dissatisfied +30189,100247,Female,Loyal Customer,28,Business travel,Business,1053,1,2,2,2,1,1,1,1,4,2,3,1,4,1,0,0.0,neutral or dissatisfied +30190,78462,Male,Loyal Customer,38,Business travel,Business,666,2,2,2,2,3,5,4,4,4,4,4,4,4,4,83,81.0,satisfied +30191,62518,Female,disloyal Customer,37,Business travel,Business,1846,1,1,1,4,4,1,2,4,5,5,5,4,4,4,0,16.0,neutral or dissatisfied +30192,26656,Male,disloyal Customer,45,Business travel,Eco,115,2,5,2,1,4,2,4,4,3,2,5,2,4,4,0,0.0,neutral or dissatisfied +30193,100924,Female,disloyal Customer,21,Business travel,Eco,838,3,3,3,3,5,3,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +30194,103065,Female,Loyal Customer,65,Business travel,Eco,386,4,4,4,4,3,1,1,4,4,4,4,2,4,2,55,22.0,satisfied +30195,81592,Male,Loyal Customer,45,Business travel,Business,334,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,2.0,satisfied +30196,54648,Female,Loyal Customer,23,Business travel,Business,964,2,2,2,2,5,5,5,5,2,2,1,3,5,5,12,10.0,satisfied +30197,71420,Female,Loyal Customer,43,Business travel,Business,867,4,4,4,4,4,5,5,5,5,5,5,5,5,4,7,6.0,satisfied +30198,61201,Female,Loyal Customer,55,Business travel,Business,3021,5,5,5,5,4,4,4,4,4,4,4,5,4,4,15,0.0,satisfied +30199,98343,Female,Loyal Customer,30,Business travel,Business,1046,1,1,1,1,3,3,3,3,5,2,5,5,5,3,3,0.0,satisfied +30200,122782,Female,Loyal Customer,45,Business travel,Business,2539,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,4.0,satisfied +30201,66788,Male,Loyal Customer,26,Personal Travel,Eco,3784,2,5,2,1,2,2,2,5,3,4,5,2,3,2,75,84.0,neutral or dissatisfied +30202,46,Female,disloyal Customer,23,Business travel,Eco,173,3,0,3,1,4,3,4,4,3,2,5,3,4,4,16,13.0,neutral or dissatisfied +30203,19886,Male,disloyal Customer,49,Business travel,Eco,240,3,4,3,1,3,3,1,3,3,1,1,4,1,3,0,0.0,neutral or dissatisfied +30204,84113,Male,Loyal Customer,16,Business travel,Business,1900,1,1,1,1,5,4,5,5,4,3,5,5,4,5,0,1.0,satisfied +30205,83432,Female,Loyal Customer,37,Personal Travel,Eco,632,1,4,2,1,1,2,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +30206,66683,Female,Loyal Customer,24,Business travel,Business,978,3,1,2,1,3,3,3,3,1,1,3,4,2,3,22,17.0,neutral or dissatisfied +30207,108800,Female,Loyal Customer,54,Personal Travel,Eco,404,3,4,3,2,5,4,4,5,5,3,5,4,5,5,20,15.0,neutral or dissatisfied +30208,30404,Male,Loyal Customer,62,Personal Travel,Eco,641,3,5,3,3,3,3,3,3,4,4,4,3,4,3,2,5.0,neutral or dissatisfied +30209,31781,Female,Loyal Customer,52,Personal Travel,Eco,602,4,1,4,2,3,2,3,1,1,4,1,3,1,1,26,25.0,neutral or dissatisfied +30210,52076,Male,disloyal Customer,24,Business travel,Business,351,5,0,5,1,2,5,2,2,5,2,5,3,1,2,0,0.0,satisfied +30211,24046,Female,Loyal Customer,28,Personal Travel,Eco,595,1,4,1,2,5,1,1,5,2,2,2,5,4,5,0,9.0,neutral or dissatisfied +30212,67257,Female,Loyal Customer,60,Personal Travel,Eco,1121,3,5,3,4,5,4,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +30213,127929,Male,Loyal Customer,40,Business travel,Business,2300,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +30214,9506,Male,Loyal Customer,52,Personal Travel,Eco,239,1,4,1,3,1,1,1,1,1,5,4,3,4,1,0,6.0,neutral or dissatisfied +30215,3073,Female,Loyal Customer,58,Business travel,Business,413,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +30216,1442,Male,Loyal Customer,43,Business travel,Business,2907,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +30217,92573,Female,Loyal Customer,38,Business travel,Eco Plus,1947,2,1,1,1,2,2,2,2,3,1,1,1,2,2,0,0.0,neutral or dissatisfied +30218,112930,Female,Loyal Customer,45,Personal Travel,Eco,1390,1,5,1,4,5,3,5,5,5,1,5,4,5,4,23,13.0,neutral or dissatisfied +30219,16964,Female,disloyal Customer,25,Business travel,Eco,195,3,4,3,3,3,4,4,3,1,3,4,4,3,4,382,392.0,neutral or dissatisfied +30220,10234,Female,Loyal Customer,35,Business travel,Business,309,2,2,2,2,3,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +30221,80653,Male,Loyal Customer,40,Business travel,Business,821,3,3,3,3,2,5,5,2,2,2,2,3,2,4,3,0.0,satisfied +30222,9406,Female,Loyal Customer,26,Business travel,Business,1136,1,1,1,1,4,4,4,4,4,2,5,4,5,4,3,16.0,satisfied +30223,97872,Female,Loyal Customer,37,Business travel,Business,483,2,2,1,2,3,4,5,2,2,2,2,5,2,3,17,5.0,satisfied +30224,67668,Male,Loyal Customer,35,Business travel,Business,1464,3,3,3,3,2,5,5,4,4,4,4,4,4,3,4,0.0,satisfied +30225,51503,Male,Loyal Customer,32,Business travel,Business,2262,2,2,2,2,4,4,4,4,2,4,5,1,1,4,42,33.0,satisfied +30226,36370,Male,disloyal Customer,49,Business travel,Eco,200,3,0,3,5,5,3,5,5,2,5,2,1,2,5,0,0.0,neutral or dissatisfied +30227,43553,Female,disloyal Customer,24,Business travel,Eco,403,3,1,3,3,4,3,4,4,2,2,4,4,3,4,23,36.0,neutral or dissatisfied +30228,22878,Male,Loyal Customer,58,Personal Travel,Eco,147,2,4,2,1,5,2,5,5,5,3,4,3,2,5,13,16.0,neutral or dissatisfied +30229,12418,Male,Loyal Customer,15,Personal Travel,Eco,253,1,5,1,3,3,1,3,3,1,4,2,3,1,3,0,0.0,neutral or dissatisfied +30230,79198,Male,Loyal Customer,41,Business travel,Business,1990,3,3,3,3,3,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +30231,49768,Male,Loyal Customer,35,Business travel,Business,3259,1,5,1,1,3,5,1,4,4,4,4,4,4,5,0,0.0,satisfied +30232,19114,Male,Loyal Customer,32,Business travel,Business,265,2,2,3,2,5,5,5,5,5,3,4,1,3,5,0,0.0,satisfied +30233,49092,Male,disloyal Customer,22,Business travel,Eco,262,2,2,2,3,3,2,4,3,1,2,3,3,4,3,0,0.0,neutral or dissatisfied +30234,28279,Female,Loyal Customer,39,Personal Travel,Eco,2402,2,2,2,3,2,2,5,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +30235,75417,Female,Loyal Customer,58,Business travel,Business,2585,3,3,2,3,3,3,4,5,5,5,5,3,5,4,10,0.0,satisfied +30236,20965,Male,Loyal Customer,36,Business travel,Business,321,3,2,2,2,4,4,3,3,3,3,3,4,3,2,54,29.0,neutral or dissatisfied +30237,61265,Male,Loyal Customer,50,Personal Travel,Eco,967,4,1,4,3,4,4,4,4,3,1,4,4,3,4,4,0.0,neutral or dissatisfied +30238,33553,Female,Loyal Customer,39,Business travel,Business,3084,2,2,2,2,1,4,3,3,3,5,3,1,3,4,44,42.0,satisfied +30239,14746,Male,Loyal Customer,25,Business travel,Business,463,1,1,1,1,3,4,3,3,1,2,3,1,1,3,0,0.0,satisfied +30240,127581,Male,disloyal Customer,25,Business travel,Eco,902,3,3,3,3,4,3,4,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +30241,59413,Female,Loyal Customer,31,Personal Travel,Eco,2447,3,4,3,1,4,3,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +30242,79032,Female,disloyal Customer,48,Business travel,Business,226,3,2,2,3,5,3,5,5,5,3,4,5,5,5,19,5.0,neutral or dissatisfied +30243,115326,Female,Loyal Customer,33,Business travel,Business,362,4,4,4,4,3,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +30244,98959,Female,Loyal Customer,30,Business travel,Business,2366,1,1,3,1,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +30245,122131,Male,disloyal Customer,26,Business travel,Business,541,3,3,3,4,1,3,1,1,3,4,4,4,3,1,0,0.0,neutral or dissatisfied +30246,61370,Female,Loyal Customer,58,Business travel,Business,679,3,3,5,3,5,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +30247,112303,Male,Loyal Customer,17,Personal Travel,Eco,1671,4,2,3,4,2,3,2,2,1,3,4,4,3,2,6,0.0,neutral or dissatisfied +30248,87638,Female,Loyal Customer,47,Business travel,Business,591,3,3,4,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +30249,16141,Female,Loyal Customer,47,Business travel,Business,277,3,3,3,3,4,4,4,4,4,5,5,4,3,4,157,143.0,satisfied +30250,42372,Female,Loyal Customer,43,Personal Travel,Eco,550,4,2,3,4,5,3,3,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +30251,36721,Female,Loyal Customer,26,Business travel,Eco Plus,1197,2,5,5,5,2,1,1,2,3,4,3,3,4,2,0,4.0,neutral or dissatisfied +30252,83056,Female,Loyal Customer,17,Business travel,Eco,957,3,5,5,5,3,3,3,3,4,3,4,3,3,3,0,4.0,neutral or dissatisfied +30253,41834,Male,disloyal Customer,20,Business travel,Eco,462,4,0,4,3,3,4,1,3,2,2,3,2,1,3,0,0.0,satisfied +30254,59284,Male,Loyal Customer,39,Business travel,Business,1865,2,3,3,3,2,2,2,4,5,3,4,2,3,2,0,3.0,neutral or dissatisfied +30255,63966,Male,Loyal Customer,58,Business travel,Business,1889,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +30256,9325,Female,Loyal Customer,23,Personal Travel,Eco,419,3,1,3,3,2,3,2,2,1,3,3,4,3,2,6,0.0,neutral or dissatisfied +30257,5882,Male,Loyal Customer,51,Business travel,Eco,212,3,5,5,5,3,3,3,3,1,3,3,4,3,3,25,25.0,neutral or dissatisfied +30258,39428,Male,Loyal Customer,46,Business travel,Business,3712,2,2,2,2,4,4,3,4,4,4,5,2,4,1,22,24.0,satisfied +30259,112836,Male,Loyal Customer,55,Business travel,Business,1390,4,4,5,4,3,5,5,2,2,2,2,3,2,5,5,0.0,satisfied +30260,120027,Female,Loyal Customer,38,Business travel,Business,1756,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +30261,49940,Female,disloyal Customer,40,Business travel,Business,250,3,3,3,4,1,3,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +30262,46038,Female,disloyal Customer,22,Business travel,Business,996,4,0,4,4,2,4,2,2,2,3,4,5,3,2,37,31.0,satisfied +30263,4520,Female,Loyal Customer,15,Personal Travel,Eco Plus,435,5,5,5,3,3,5,3,3,5,2,5,4,5,3,0,0.0,satisfied +30264,124107,Female,disloyal Customer,22,Business travel,Eco,529,1,0,1,3,2,1,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +30265,128023,Male,Loyal Customer,33,Business travel,Business,1440,5,5,1,5,5,5,5,5,4,5,5,4,4,5,0,1.0,satisfied +30266,99120,Female,Loyal Customer,13,Personal Travel,Eco,453,4,5,4,2,3,4,3,3,3,5,5,5,4,3,3,0.0,neutral or dissatisfied +30267,88837,Male,Loyal Customer,47,Personal Travel,Eco Plus,594,2,1,2,3,1,2,1,1,3,1,4,4,4,1,45,46.0,neutral or dissatisfied +30268,82809,Female,disloyal Customer,16,Business travel,Eco,235,3,4,3,4,3,3,3,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +30269,65376,Male,Loyal Customer,52,Business travel,Business,3374,5,5,5,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +30270,82044,Male,Loyal Customer,23,Personal Travel,Eco,1517,3,2,3,4,1,3,1,1,4,1,4,1,3,1,0,0.0,neutral or dissatisfied +30271,46264,Male,Loyal Customer,22,Personal Travel,Eco,752,2,5,2,1,1,2,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +30272,48078,Female,Loyal Customer,59,Personal Travel,Business,236,4,5,4,2,3,4,5,3,3,4,3,3,3,3,16,22.0,satisfied +30273,48631,Female,Loyal Customer,38,Business travel,Business,3085,2,2,2,2,5,5,5,5,5,5,5,3,5,5,17,27.0,satisfied +30274,58736,Female,disloyal Customer,29,Business travel,Business,1120,2,2,2,1,5,2,5,5,5,3,5,5,4,5,62,73.0,neutral or dissatisfied +30275,22094,Male,Loyal Customer,56,Business travel,Business,782,3,2,4,4,1,3,3,3,3,3,3,1,3,4,0,17.0,neutral or dissatisfied +30276,46606,Female,Loyal Customer,52,Business travel,Eco,125,1,0,0,3,1,4,3,5,5,1,5,3,5,3,18,13.0,neutral or dissatisfied +30277,77408,Male,Loyal Customer,8,Personal Travel,Eco,590,1,3,1,3,4,1,4,4,2,3,2,3,3,4,30,16.0,neutral or dissatisfied +30278,124944,Male,Loyal Customer,24,Personal Travel,Eco,728,2,4,2,4,4,2,4,4,3,3,4,2,3,4,9,9.0,neutral or dissatisfied +30279,52856,Female,Loyal Customer,12,Personal Travel,Eco,1721,1,3,2,4,5,2,5,5,1,3,4,2,3,5,0,4.0,neutral or dissatisfied +30280,44954,Female,Loyal Customer,42,Personal Travel,Eco,397,4,4,4,5,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +30281,78537,Male,Loyal Customer,29,Personal Travel,Eco,666,2,5,2,1,2,2,1,2,5,3,1,1,2,2,0,0.0,neutral or dissatisfied +30282,53698,Male,Loyal Customer,72,Business travel,Eco,1208,3,3,3,3,3,3,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +30283,75355,Female,disloyal Customer,26,Business travel,Business,2556,1,1,1,3,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +30284,49152,Female,Loyal Customer,48,Business travel,Business,337,2,2,2,2,3,4,4,4,4,4,4,1,4,2,0,0.0,satisfied +30285,11828,Male,Loyal Customer,55,Business travel,Business,1743,4,4,4,4,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +30286,61695,Female,Loyal Customer,42,Business travel,Business,1609,1,1,5,1,3,5,4,4,4,4,4,4,4,5,14,14.0,satisfied +30287,84638,Female,Loyal Customer,58,Business travel,Business,3436,5,5,4,5,2,5,4,4,4,4,4,4,4,4,81,67.0,satisfied +30288,24254,Female,Loyal Customer,9,Personal Travel,Eco,302,2,3,2,2,5,2,5,5,2,4,3,1,2,5,20,29.0,neutral or dissatisfied +30289,91794,Male,Loyal Customer,45,Personal Travel,Eco,588,1,5,1,4,4,1,3,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +30290,117164,Male,Loyal Customer,69,Personal Travel,Eco,451,2,4,2,1,4,2,4,4,2,4,3,3,5,4,50,34.0,neutral or dissatisfied +30291,83411,Male,disloyal Customer,21,Business travel,Eco,632,4,4,4,4,5,4,4,5,4,5,4,1,4,5,0,14.0,neutral or dissatisfied +30292,6360,Female,Loyal Customer,59,Business travel,Business,296,1,1,3,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +30293,13834,Male,Loyal Customer,49,Business travel,Eco,594,3,1,1,1,3,3,3,3,1,5,5,3,3,3,0,0.0,satisfied +30294,4904,Male,Loyal Customer,26,Business travel,Business,1020,3,3,3,3,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +30295,56887,Male,disloyal Customer,41,Business travel,Business,714,4,3,3,3,5,4,5,5,4,3,4,4,5,5,10,5.0,satisfied +30296,95408,Female,Loyal Customer,42,Personal Travel,Eco,319,2,5,2,1,3,1,3,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +30297,35269,Male,disloyal Customer,11,Business travel,Eco,944,3,3,3,4,2,3,2,2,3,3,4,2,3,2,0,2.0,neutral or dissatisfied +30298,125621,Male,Loyal Customer,69,Personal Travel,Business,892,3,3,4,3,4,3,4,2,2,4,2,1,2,4,31,37.0,neutral or dissatisfied +30299,4833,Male,Loyal Customer,59,Business travel,Business,1892,4,4,3,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +30300,109289,Female,Loyal Customer,27,Business travel,Business,1072,3,3,3,3,3,4,3,3,3,4,5,5,5,3,0,0.0,satisfied +30301,91884,Male,Loyal Customer,55,Business travel,Business,2475,5,5,5,5,4,5,5,3,3,3,3,4,3,3,0,2.0,satisfied +30302,67209,Male,Loyal Customer,56,Personal Travel,Eco,918,3,1,3,3,5,3,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +30303,102745,Male,Loyal Customer,30,Business travel,Business,3400,2,5,2,2,5,5,5,5,4,4,4,3,5,5,54,48.0,satisfied +30304,2546,Female,disloyal Customer,64,Business travel,Business,227,4,4,4,3,2,4,2,2,5,5,5,3,5,2,0,0.0,satisfied +30305,38104,Male,Loyal Customer,27,Business travel,Eco,1237,2,1,1,1,2,2,2,2,3,1,2,4,3,2,17,41.0,neutral or dissatisfied +30306,102120,Male,disloyal Customer,24,Business travel,Eco,258,2,5,2,1,4,2,4,4,4,2,5,3,5,4,68,60.0,neutral or dissatisfied +30307,21485,Female,Loyal Customer,37,Business travel,Eco,164,5,2,2,2,5,5,5,5,5,4,4,4,2,5,0,0.0,satisfied +30308,31650,Male,disloyal Customer,21,Business travel,Eco,853,3,3,3,4,2,3,3,2,5,4,1,1,1,2,0,0.0,neutral or dissatisfied +30309,100407,Male,Loyal Customer,44,Business travel,Business,3055,1,1,2,1,2,5,5,4,4,4,4,5,4,5,25,22.0,satisfied +30310,128807,Male,Loyal Customer,28,Business travel,Business,2586,2,2,2,2,5,5,5,4,2,4,4,5,5,5,10,0.0,satisfied +30311,103159,Female,Loyal Customer,27,Business travel,Business,2420,1,1,1,1,5,5,5,5,4,3,4,4,5,5,5,0.0,satisfied +30312,76316,Male,Loyal Customer,29,Business travel,Business,2182,3,5,5,5,3,3,3,3,3,5,3,4,3,3,0,0.0,neutral or dissatisfied +30313,118149,Female,Loyal Customer,42,Business travel,Business,1444,2,2,2,2,2,4,4,5,5,5,5,5,5,5,11,0.0,satisfied +30314,10696,Male,Loyal Customer,25,Business travel,Eco,308,2,2,2,2,2,2,4,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +30315,88198,Female,Loyal Customer,25,Business travel,Business,1982,3,3,3,3,2,2,2,2,4,2,5,3,5,2,0,0.0,satisfied +30316,88348,Female,Loyal Customer,38,Business travel,Business,3113,2,5,1,5,5,2,3,2,2,2,2,2,2,2,2,0.0,neutral or dissatisfied +30317,45300,Male,Loyal Customer,33,Business travel,Eco,188,3,3,3,3,3,2,3,3,4,1,3,1,3,3,0,4.0,neutral or dissatisfied +30318,10625,Male,Loyal Customer,62,Business travel,Eco,458,3,1,1,1,2,3,2,2,3,4,3,1,3,2,5,3.0,neutral or dissatisfied +30319,32595,Female,Loyal Customer,45,Business travel,Eco,101,5,4,4,4,2,2,1,4,4,5,4,5,4,3,0,0.0,satisfied +30320,128048,Male,Loyal Customer,32,Business travel,Business,735,1,1,1,1,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +30321,51548,Male,Loyal Customer,42,Business travel,Eco,493,2,3,3,3,2,2,2,2,3,2,5,3,4,2,75,68.0,satisfied +30322,91834,Male,Loyal Customer,37,Business travel,Eco Plus,188,4,1,1,1,4,4,4,4,1,1,2,5,4,4,1,4.0,satisfied +30323,58450,Male,Loyal Customer,44,Personal Travel,Eco,733,3,3,2,3,3,2,3,3,5,2,2,1,4,3,113,94.0,neutral or dissatisfied +30324,3058,Female,Loyal Customer,57,Business travel,Business,340,3,3,3,3,3,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +30325,2347,Female,Loyal Customer,68,Personal Travel,Eco Plus,672,3,1,3,4,2,3,4,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +30326,119063,Male,Loyal Customer,70,Personal Travel,Eco Plus,2279,1,4,0,3,3,0,3,3,3,4,3,5,4,3,95,57.0,neutral or dissatisfied +30327,102988,Female,Loyal Customer,45,Business travel,Business,666,4,4,4,4,2,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +30328,123685,Male,disloyal Customer,38,Business travel,Business,214,1,2,2,3,4,2,4,4,1,4,4,2,4,4,0,15.0,neutral or dissatisfied +30329,50227,Female,Loyal Customer,61,Business travel,Business,421,4,4,4,4,3,5,2,3,3,3,3,5,3,5,0,0.0,satisfied +30330,92871,Female,Loyal Customer,54,Business travel,Business,3894,0,5,1,3,1,1,1,5,5,4,4,1,3,1,237,228.0,satisfied +30331,113196,Female,disloyal Customer,25,Business travel,Business,226,5,0,5,2,2,5,2,2,4,2,5,5,5,2,30,61.0,satisfied +30332,32747,Male,Loyal Customer,58,Business travel,Business,163,4,4,4,4,5,3,5,4,4,4,5,1,4,3,0,0.0,satisfied +30333,119096,Female,Loyal Customer,48,Business travel,Business,2047,3,3,3,3,2,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +30334,90253,Male,Loyal Customer,30,Business travel,Business,3773,1,1,1,1,4,4,4,4,5,3,5,4,4,4,28,19.0,satisfied +30335,6040,Male,disloyal Customer,19,Business travel,Eco,925,4,3,3,2,5,3,5,5,5,4,5,3,5,5,4,0.0,satisfied +30336,110191,Female,Loyal Customer,36,Personal Travel,Eco,979,2,5,2,1,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +30337,16706,Female,Loyal Customer,39,Business travel,Business,3261,3,4,3,3,2,2,2,5,5,5,5,4,5,4,88,78.0,satisfied +30338,57285,Male,Loyal Customer,26,Business travel,Business,3556,5,5,5,5,5,5,5,5,3,4,5,5,5,5,2,0.0,satisfied +30339,60157,Male,Loyal Customer,65,Personal Travel,Eco,1005,3,4,3,2,3,3,3,3,3,2,5,5,4,3,0,8.0,neutral or dissatisfied +30340,73035,Female,Loyal Customer,43,Personal Travel,Eco,1035,2,5,2,3,3,4,4,1,1,2,1,4,1,5,1,0.0,neutral or dissatisfied +30341,91546,Male,Loyal Customer,44,Business travel,Eco,680,2,3,3,3,2,2,2,2,1,1,4,1,4,2,0,0.0,neutral or dissatisfied +30342,74321,Male,Loyal Customer,50,Business travel,Business,3210,5,5,5,5,5,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +30343,29148,Female,Loyal Customer,39,Personal Travel,Eco,679,1,4,2,4,4,2,1,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +30344,65781,Male,Loyal Customer,23,Business travel,Business,1389,2,2,2,2,5,5,5,5,4,5,5,4,4,5,0,0.0,satisfied +30345,99674,Female,Loyal Customer,53,Business travel,Business,442,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,3.0,satisfied +30346,73306,Female,Loyal Customer,49,Business travel,Business,2027,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +30347,79975,Male,disloyal Customer,36,Business travel,Eco,676,2,1,1,3,1,1,1,1,3,3,3,1,3,1,199,192.0,neutral or dissatisfied +30348,23557,Male,Loyal Customer,25,Business travel,Business,2110,1,1,1,1,1,1,1,1,3,5,4,3,3,1,8,2.0,neutral or dissatisfied +30349,99631,Female,Loyal Customer,64,Personal Travel,Eco,1085,2,5,2,3,2,5,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +30350,86857,Male,Loyal Customer,30,Personal Travel,Eco,692,1,5,1,2,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +30351,78329,Female,disloyal Customer,35,Business travel,Business,1547,2,2,2,2,1,2,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +30352,5276,Male,Loyal Customer,47,Personal Travel,Eco,351,2,4,4,4,4,4,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +30353,47596,Female,disloyal Customer,30,Business travel,Eco,1211,2,2,2,1,2,2,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +30354,67417,Female,disloyal Customer,15,Business travel,Eco,641,2,3,2,4,5,2,3,5,2,1,3,4,4,5,0,0.0,neutral or dissatisfied +30355,81731,Female,Loyal Customer,57,Business travel,Business,1416,3,3,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +30356,10960,Female,Loyal Customer,34,Business travel,Business,3149,2,2,2,2,4,4,5,5,5,5,5,2,5,1,0,3.0,satisfied +30357,38937,Male,Loyal Customer,11,Personal Travel,Eco,162,2,3,2,3,1,2,1,1,5,1,2,3,5,1,0,0.0,neutral or dissatisfied +30358,53621,Male,Loyal Customer,36,Business travel,Eco,1874,2,4,4,4,2,2,2,2,2,1,4,4,4,2,4,2.0,neutral or dissatisfied +30359,52951,Male,Loyal Customer,29,Personal Travel,Eco,1448,1,3,1,4,1,1,1,1,1,3,5,5,1,1,0,0.0,neutral or dissatisfied +30360,3938,Male,Loyal Customer,60,Business travel,Business,764,4,4,4,4,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +30361,19765,Female,Loyal Customer,35,Business travel,Eco Plus,462,2,5,5,5,2,2,2,2,3,1,3,3,4,2,53,70.0,neutral or dissatisfied +30362,93325,Female,Loyal Customer,11,Personal Travel,Eco,287,2,5,2,2,3,2,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +30363,58772,Male,disloyal Customer,25,Business travel,Eco,1012,1,1,1,4,3,1,3,3,3,5,4,2,3,3,9,0.0,neutral or dissatisfied +30364,92697,Female,Loyal Customer,30,Personal Travel,Eco,507,3,4,2,3,1,2,1,1,1,1,1,1,4,1,0,1.0,neutral or dissatisfied +30365,53348,Male,Loyal Customer,46,Business travel,Business,1476,3,3,3,3,1,2,3,4,4,4,4,1,4,1,1,0.0,satisfied +30366,34244,Male,Loyal Customer,50,Personal Travel,Eco Plus,1046,1,5,2,2,2,2,2,2,4,5,5,5,4,2,36,28.0,neutral or dissatisfied +30367,5224,Female,Loyal Customer,52,Business travel,Business,2499,4,4,4,4,4,5,5,5,5,5,4,5,5,5,107,126.0,satisfied +30368,93022,Male,Loyal Customer,54,Personal Travel,Eco,1524,2,5,3,3,3,3,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +30369,55517,Male,Loyal Customer,23,Personal Travel,Eco,991,2,2,2,3,5,2,1,5,3,1,4,2,3,5,0,0.0,neutral or dissatisfied +30370,11376,Female,Loyal Customer,30,Personal Travel,Eco,301,2,5,2,3,4,2,4,4,5,4,4,3,4,4,0,18.0,neutral or dissatisfied +30371,59458,Male,Loyal Customer,48,Business travel,Business,1827,5,5,5,5,2,5,4,3,3,3,3,3,3,5,5,0.0,satisfied +30372,89206,Male,Loyal Customer,9,Personal Travel,Eco,2116,3,4,3,3,1,3,1,1,2,2,1,2,5,1,42,46.0,neutral or dissatisfied +30373,15236,Female,Loyal Customer,53,Business travel,Eco,416,2,4,4,4,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +30374,63582,Female,disloyal Customer,21,Business travel,Eco,840,1,1,1,5,5,1,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +30375,114934,Male,Loyal Customer,38,Business travel,Eco,362,3,1,1,1,3,3,3,3,2,4,3,2,2,3,0,7.0,neutral or dissatisfied +30376,37398,Male,Loyal Customer,43,Business travel,Business,944,1,1,1,1,2,1,2,4,4,4,4,4,4,1,0,5.0,satisfied +30377,50114,Female,Loyal Customer,61,Business travel,Business,109,4,5,5,5,2,3,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +30378,14645,Female,Loyal Customer,40,Personal Travel,Eco,948,1,0,1,3,4,1,2,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +30379,99746,Male,Loyal Customer,32,Business travel,Business,255,2,3,4,4,2,3,2,2,2,3,2,1,3,2,0,0.0,neutral or dissatisfied +30380,88624,Female,Loyal Customer,58,Personal Travel,Eco,646,4,3,4,3,4,3,3,2,2,4,2,1,2,3,0,2.0,neutral or dissatisfied +30381,104335,Female,Loyal Customer,30,Business travel,Business,409,1,5,1,1,4,4,4,4,3,3,1,5,3,4,0,2.0,satisfied +30382,75140,Male,Loyal Customer,28,Business travel,Business,1846,3,3,3,3,3,3,3,3,5,2,5,5,5,3,0,0.0,satisfied +30383,11220,Male,Loyal Customer,61,Personal Travel,Eco,308,0,5,0,3,3,0,3,3,4,4,5,5,5,3,0,0.0,satisfied +30384,81965,Female,Loyal Customer,52,Business travel,Eco,1589,2,3,2,3,4,1,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +30385,34179,Male,Loyal Customer,21,Business travel,Business,1720,4,4,2,4,5,5,5,5,2,2,2,4,2,5,0,0.0,satisfied +30386,100076,Female,disloyal Customer,16,Business travel,Eco,277,3,1,3,4,4,3,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +30387,27476,Female,Loyal Customer,62,Business travel,Eco,954,3,2,2,2,4,2,1,3,3,3,3,1,3,3,5,19.0,neutral or dissatisfied +30388,8767,Female,disloyal Customer,32,Business travel,Business,522,3,3,3,1,3,3,3,3,3,5,4,3,4,3,6,18.0,neutral or dissatisfied +30389,100736,Male,disloyal Customer,43,Business travel,Eco,328,4,0,4,5,3,4,3,3,5,2,4,2,4,3,1,0.0,satisfied +30390,4737,Female,Loyal Customer,72,Business travel,Business,888,4,2,2,2,3,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +30391,66182,Male,Loyal Customer,22,Business travel,Business,2883,3,3,3,3,5,5,5,5,4,3,4,4,4,5,22,21.0,satisfied +30392,71157,Male,disloyal Customer,18,Business travel,Eco,646,4,1,4,4,5,4,5,5,2,1,4,2,3,5,6,12.0,neutral or dissatisfied +30393,112232,Male,Loyal Customer,52,Business travel,Business,1506,2,2,2,2,5,5,5,5,5,5,5,3,5,5,125,119.0,satisfied +30394,22798,Female,Loyal Customer,21,Business travel,Business,3362,1,1,4,1,5,5,5,5,5,3,1,2,4,5,0,0.0,satisfied +30395,12463,Female,Loyal Customer,42,Personal Travel,Eco,201,3,5,0,2,4,2,3,5,5,0,5,5,5,1,17,8.0,neutral or dissatisfied +30396,24899,Female,Loyal Customer,35,Business travel,Business,1918,5,5,5,5,4,4,5,4,4,4,4,4,4,5,45,62.0,satisfied +30397,74906,Female,Loyal Customer,46,Business travel,Business,2475,3,3,3,3,2,5,4,5,5,5,5,3,5,3,54,31.0,satisfied +30398,120069,Male,Loyal Customer,58,Business travel,Business,2450,3,1,3,3,2,5,4,4,4,4,4,4,4,5,9,36.0,satisfied +30399,102169,Male,Loyal Customer,35,Business travel,Business,407,2,2,2,2,3,4,4,4,4,4,4,5,4,5,4,3.0,satisfied +30400,56758,Male,Loyal Customer,46,Business travel,Business,997,2,2,2,2,5,4,4,5,5,5,5,5,5,3,3,48.0,satisfied +30401,55625,Male,Loyal Customer,51,Business travel,Eco,1824,2,5,2,5,2,2,2,2,4,1,1,1,1,2,8,0.0,neutral or dissatisfied +30402,36747,Male,Loyal Customer,66,Personal Travel,Business,2588,1,4,1,3,1,4,4,5,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +30403,37075,Female,Loyal Customer,10,Personal Travel,Eco,1072,3,2,3,4,1,3,4,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +30404,99377,Male,Loyal Customer,55,Business travel,Business,314,4,4,4,4,5,4,4,5,5,5,5,4,5,4,55,48.0,satisfied +30405,74357,Female,disloyal Customer,14,Business travel,Business,1431,4,0,4,3,4,4,4,4,3,4,4,4,5,4,44,18.0,satisfied +30406,96182,Male,Loyal Customer,51,Business travel,Business,2693,1,1,1,1,5,4,5,4,4,4,4,3,4,3,39,35.0,satisfied +30407,127217,Male,Loyal Customer,44,Personal Travel,Eco Plus,651,1,2,1,3,5,1,1,5,2,3,3,4,4,5,0,0.0,neutral or dissatisfied +30408,9539,Female,disloyal Customer,38,Business travel,Business,229,5,4,4,3,4,1,5,4,2,5,4,5,5,5,206,209.0,satisfied +30409,37877,Female,Loyal Customer,37,Business travel,Business,3730,2,4,1,4,5,3,3,2,2,2,2,2,2,4,60,50.0,neutral or dissatisfied +30410,4140,Male,disloyal Customer,21,Business travel,Eco,431,3,4,3,4,3,3,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +30411,97907,Male,disloyal Customer,15,Business travel,Business,483,4,4,4,5,5,4,5,5,4,3,5,3,4,5,40,45.0,satisfied +30412,94876,Male,Loyal Customer,32,Business travel,Eco,239,5,5,5,5,5,4,5,5,4,1,3,3,3,5,31,23.0,neutral or dissatisfied +30413,103926,Female,Loyal Customer,31,Business travel,Business,770,4,4,4,4,4,4,4,4,3,3,5,3,5,4,15,6.0,satisfied +30414,23009,Female,Loyal Customer,38,Personal Travel,Eco,817,1,1,1,1,3,1,3,3,1,2,1,4,2,3,70,54.0,neutral or dissatisfied +30415,113211,Male,disloyal Customer,66,Business travel,Business,407,1,2,2,5,2,1,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +30416,11243,Male,Loyal Customer,26,Personal Travel,Eco,429,3,4,3,4,3,3,3,3,3,4,4,3,4,3,22,42.0,neutral or dissatisfied +30417,65158,Male,Loyal Customer,32,Personal Travel,Eco,190,3,5,3,3,5,3,1,5,3,5,5,4,5,5,10,13.0,neutral or dissatisfied +30418,33795,Male,Loyal Customer,50,Business travel,Business,1428,1,3,3,3,3,2,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +30419,67793,Female,disloyal Customer,8,Business travel,Business,1313,4,4,4,1,5,4,5,5,4,5,4,5,5,5,3,0.0,neutral or dissatisfied +30420,76704,Male,Loyal Customer,15,Personal Travel,Eco,534,3,4,3,4,2,3,3,2,3,5,5,3,4,2,18,47.0,neutral or dissatisfied +30421,68775,Female,disloyal Customer,36,Business travel,Eco,926,3,3,3,4,1,3,1,1,1,5,3,2,3,1,3,16.0,neutral or dissatisfied +30422,127486,Male,disloyal Customer,43,Business travel,Eco,575,2,4,2,4,1,2,1,1,1,3,4,3,4,1,0,13.0,neutral or dissatisfied +30423,13661,Female,Loyal Customer,52,Business travel,Business,2703,4,4,4,4,3,3,2,5,5,5,5,1,5,3,9,8.0,satisfied +30424,81343,Female,disloyal Customer,15,Business travel,Eco,1299,1,1,1,3,3,1,3,3,4,3,2,3,3,3,7,14.0,neutral or dissatisfied +30425,65845,Male,disloyal Customer,37,Business travel,Business,1389,2,1,1,1,1,1,1,1,5,3,4,4,4,1,2,5.0,neutral or dissatisfied +30426,117259,Male,Loyal Customer,22,Personal Travel,Eco,621,4,5,4,5,2,4,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +30427,46205,Male,Loyal Customer,37,Business travel,Business,3709,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +30428,41168,Female,Loyal Customer,34,Business travel,Eco Plus,429,4,5,5,5,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +30429,9802,Male,Loyal Customer,60,Business travel,Business,3873,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +30430,9262,Male,Loyal Customer,66,Personal Travel,Eco Plus,100,3,1,3,1,3,3,2,3,4,3,2,2,1,3,0,0.0,neutral or dissatisfied +30431,24841,Male,Loyal Customer,41,Personal Travel,Eco,861,3,5,3,4,3,3,3,3,4,5,5,5,4,3,0,1.0,neutral or dissatisfied +30432,59558,Male,Loyal Customer,59,Business travel,Business,787,4,4,4,4,2,4,4,1,1,2,1,4,1,3,0,0.0,satisfied +30433,44648,Male,Loyal Customer,60,Business travel,Business,160,1,1,1,1,4,1,2,4,4,5,4,2,4,3,15,26.0,satisfied +30434,30613,Female,Loyal Customer,32,Business travel,Business,1798,2,4,5,5,2,2,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +30435,69553,Female,Loyal Customer,53,Business travel,Business,2475,1,1,5,1,5,5,5,3,2,5,5,5,4,5,8,0.0,satisfied +30436,39371,Male,Loyal Customer,49,Business travel,Eco Plus,896,4,2,5,2,3,4,3,3,1,4,1,1,3,3,6,0.0,satisfied +30437,110882,Female,Loyal Customer,59,Business travel,Business,2363,2,2,2,2,2,4,4,4,4,4,4,4,4,4,14,22.0,satisfied +30438,118063,Male,Loyal Customer,24,Personal Travel,Eco,1262,0,4,0,1,4,0,4,4,4,4,3,5,5,4,8,0.0,satisfied +30439,113045,Female,Loyal Customer,25,Business travel,Business,3806,3,3,4,3,4,4,4,4,5,3,5,4,4,4,2,0.0,satisfied +30440,100036,Female,disloyal Customer,16,Business travel,Eco,289,0,0,0,3,2,0,2,2,3,5,4,5,4,2,0,0.0,satisfied +30441,88511,Female,Loyal Customer,53,Business travel,Business,3426,4,4,4,4,5,1,5,5,5,5,5,1,5,4,1,2.0,satisfied +30442,7798,Male,disloyal Customer,39,Business travel,Eco,650,2,3,2,3,3,2,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +30443,1598,Male,Loyal Customer,7,Personal Travel,Eco,140,3,3,0,3,3,0,3,3,2,4,3,1,2,3,45,46.0,neutral or dissatisfied +30444,109987,Male,Loyal Customer,39,Business travel,Business,2074,1,1,1,1,2,4,5,1,1,2,1,4,1,4,0,0.0,satisfied +30445,85536,Female,disloyal Customer,29,Business travel,Business,192,5,5,5,4,4,5,4,4,5,4,5,3,4,4,0,6.0,satisfied +30446,49680,Female,Loyal Customer,31,Business travel,Business,1560,2,2,2,2,5,5,4,5,3,4,4,4,1,5,0,0.0,satisfied +30447,18338,Male,disloyal Customer,47,Business travel,Eco,474,2,0,3,4,3,3,4,3,3,2,4,4,3,3,113,105.0,neutral or dissatisfied +30448,8448,Male,Loyal Customer,70,Personal Travel,Business,1379,4,5,4,4,3,3,4,5,5,4,5,5,5,3,0,14.0,neutral or dissatisfied +30449,58056,Male,Loyal Customer,45,Business travel,Business,642,5,5,5,5,3,4,5,4,4,4,4,3,4,3,41,35.0,satisfied +30450,25278,Male,Loyal Customer,10,Personal Travel,Eco,425,2,0,2,2,5,2,5,5,5,2,4,5,4,5,0,0.0,neutral or dissatisfied +30451,87477,Male,Loyal Customer,41,Business travel,Business,373,3,3,3,3,1,3,3,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +30452,54966,Male,Loyal Customer,41,Business travel,Business,1635,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +30453,56475,Female,Loyal Customer,57,Business travel,Business,4963,1,1,1,1,4,4,4,3,4,5,5,4,3,4,12,0.0,satisfied +30454,114600,Male,Loyal Customer,59,Business travel,Business,3466,4,4,5,4,4,5,4,2,2,2,2,5,2,5,3,0.0,satisfied +30455,110673,Female,Loyal Customer,59,Business travel,Business,837,3,3,3,3,2,5,4,4,4,4,4,3,4,4,4,4.0,satisfied +30456,126436,Male,Loyal Customer,60,Personal Travel,Eco Plus,507,3,4,3,4,1,3,1,1,5,4,4,4,5,1,0,3.0,neutral or dissatisfied +30457,59597,Female,disloyal Customer,35,Business travel,Business,964,4,4,4,5,1,4,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +30458,1891,Male,Loyal Customer,51,Business travel,Business,1668,0,5,0,1,3,4,5,5,5,5,5,4,5,5,15,21.0,satisfied +30459,116140,Female,Loyal Customer,23,Personal Travel,Eco,371,3,2,3,2,5,3,5,5,4,5,1,2,2,5,9,6.0,neutral or dissatisfied +30460,23919,Male,Loyal Customer,25,Personal Travel,Eco,589,4,5,4,2,2,4,4,2,2,2,2,3,5,2,65,52.0,neutral or dissatisfied +30461,29958,Female,Loyal Customer,18,Business travel,Business,1658,2,2,2,2,4,4,4,4,5,5,2,3,4,4,0,0.0,satisfied +30462,46346,Male,Loyal Customer,16,Personal Travel,Eco,589,3,5,3,1,2,3,2,2,5,3,5,4,4,2,58,50.0,neutral or dissatisfied +30463,83202,Male,Loyal Customer,68,Personal Travel,Eco,1123,3,5,3,1,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +30464,117867,Male,disloyal Customer,25,Business travel,Business,255,4,0,5,1,4,5,4,4,4,4,5,5,5,4,24,17.0,neutral or dissatisfied +30465,63141,Male,Loyal Customer,70,Personal Travel,Business,337,2,4,2,2,5,5,4,1,1,2,3,3,1,4,34,21.0,neutral or dissatisfied +30466,63745,Male,Loyal Customer,43,Personal Travel,Eco,1660,4,5,4,2,3,4,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +30467,24985,Male,Loyal Customer,46,Business travel,Business,692,3,3,3,3,4,3,5,5,5,5,5,4,5,1,2,1.0,satisfied +30468,55282,Male,disloyal Customer,21,Business travel,Business,1608,0,0,1,3,3,1,3,3,4,3,4,4,5,3,4,2.0,satisfied +30469,60479,Female,Loyal Customer,23,Business travel,Business,2186,3,3,3,3,3,3,3,3,2,3,3,1,3,3,5,12.0,neutral or dissatisfied +30470,58528,Male,Loyal Customer,18,Personal Travel,Eco,719,3,5,3,1,5,3,5,5,4,4,5,5,5,5,39,28.0,neutral or dissatisfied +30471,25950,Male,disloyal Customer,35,Business travel,Eco,946,2,1,1,3,5,1,5,5,1,5,1,4,5,5,6,1.0,neutral or dissatisfied +30472,26099,Male,Loyal Customer,62,Personal Travel,Eco,591,1,4,1,4,4,1,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +30473,2098,Male,Loyal Customer,42,Personal Travel,Eco,785,1,5,2,2,1,2,1,1,4,3,4,5,5,1,22,23.0,neutral or dissatisfied +30474,82682,Male,Loyal Customer,46,Business travel,Business,3402,4,4,3,4,3,5,5,5,5,5,5,4,5,4,5,0.0,satisfied +30475,98619,Female,disloyal Customer,30,Business travel,Business,993,2,2,2,2,3,2,3,3,5,3,5,4,4,3,10,13.0,neutral or dissatisfied +30476,58444,Female,Loyal Customer,29,Personal Travel,Eco,733,5,4,5,4,5,5,5,5,5,1,2,2,5,5,3,0.0,satisfied +30477,53694,Male,Loyal Customer,51,Business travel,Business,2468,1,1,1,1,1,1,3,5,5,5,5,3,5,2,32,29.0,satisfied +30478,81136,Male,Loyal Customer,45,Personal Travel,Eco,991,4,4,4,1,5,4,4,5,4,3,4,4,5,5,0,0.0,satisfied +30479,90615,Male,Loyal Customer,42,Business travel,Business,444,2,2,2,2,3,4,4,4,4,4,4,5,4,5,111,115.0,satisfied +30480,50535,Male,Loyal Customer,7,Personal Travel,Eco,86,2,5,2,3,3,2,3,3,4,4,1,1,4,3,0,0.0,neutral or dissatisfied +30481,127817,Male,Loyal Customer,59,Business travel,Eco,862,3,5,5,5,3,3,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +30482,116950,Female,Loyal Customer,56,Business travel,Eco,621,2,4,4,4,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +30483,101605,Male,Loyal Customer,27,Business travel,Business,1371,5,5,5,5,5,5,5,5,3,2,5,3,5,5,70,38.0,satisfied +30484,49435,Female,Loyal Customer,56,Business travel,Eco,209,4,1,1,1,2,5,1,4,4,4,4,4,4,2,0,0.0,satisfied +30485,86832,Female,disloyal Customer,35,Business travel,Business,484,3,2,2,1,3,2,3,3,3,3,5,3,5,3,0,4.0,neutral or dissatisfied +30486,76076,Female,Loyal Customer,49,Business travel,Business,2809,4,2,2,2,2,4,4,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +30487,60141,Female,Loyal Customer,26,Business travel,Business,1005,2,1,1,1,2,2,2,2,3,5,4,1,4,2,10,10.0,neutral or dissatisfied +30488,39777,Female,Loyal Customer,21,Personal Travel,Eco,521,3,4,3,4,5,3,5,5,2,2,4,3,3,5,0,3.0,neutral or dissatisfied +30489,47552,Female,Loyal Customer,37,Business travel,Eco Plus,588,4,5,5,5,4,4,4,4,4,5,4,4,2,4,0,0.0,satisfied +30490,128536,Female,Loyal Customer,13,Personal Travel,Eco,338,3,4,3,5,4,3,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +30491,34707,Male,Loyal Customer,40,Business travel,Eco,209,4,5,5,5,4,4,4,4,5,5,3,1,4,4,0,0.0,satisfied +30492,51341,Male,Loyal Customer,20,Business travel,Eco Plus,109,3,4,4,4,3,3,2,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +30493,35134,Female,Loyal Customer,40,Business travel,Eco,1165,4,2,2,2,4,4,4,4,2,5,4,5,4,4,0,0.0,satisfied +30494,28967,Female,disloyal Customer,22,Business travel,Eco,679,2,2,2,3,4,2,4,4,5,1,5,4,2,4,0,0.0,neutral or dissatisfied +30495,54170,Female,Loyal Customer,48,Business travel,Business,1400,4,4,4,4,5,3,2,4,4,5,4,3,4,2,0,0.0,satisfied +30496,118445,Female,Loyal Customer,45,Business travel,Business,338,5,5,5,5,3,4,4,5,5,5,5,4,5,3,7,0.0,satisfied +30497,77964,Female,Loyal Customer,44,Business travel,Business,1914,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,4.0,satisfied +30498,57459,Male,Loyal Customer,48,Personal Travel,Eco,334,2,4,2,2,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +30499,100698,Female,Loyal Customer,66,Personal Travel,Eco,677,4,3,4,1,1,5,2,1,1,4,1,1,1,1,61,48.0,neutral or dissatisfied +30500,128035,Male,disloyal Customer,44,Business travel,Eco,1440,3,3,3,4,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +30501,107194,Female,Loyal Customer,26,Personal Travel,Eco,668,2,4,2,3,1,2,1,1,2,2,4,2,4,1,8,10.0,neutral or dissatisfied +30502,95913,Male,Loyal Customer,31,Business travel,Eco Plus,580,3,3,3,3,3,3,3,3,3,4,3,3,4,3,2,1.0,neutral or dissatisfied +30503,93668,Female,Loyal Customer,22,Business travel,Eco,717,1,1,0,3,4,0,4,4,4,5,3,1,2,4,0,0.0,neutral or dissatisfied +30504,8507,Male,Loyal Customer,57,Business travel,Business,737,4,4,4,4,3,4,5,4,4,4,4,3,4,5,12,,satisfied +30505,103196,Male,Loyal Customer,27,Personal Travel,Eco,814,4,5,4,3,3,4,3,3,3,5,4,3,4,3,18,2.0,satisfied +30506,84975,Female,Loyal Customer,39,Business travel,Business,1590,5,1,5,5,2,3,5,2,2,2,2,5,2,3,7,0.0,satisfied +30507,57790,Female,disloyal Customer,33,Business travel,Business,2611,2,2,2,3,3,2,3,3,4,4,5,5,5,3,1,0.0,neutral or dissatisfied +30508,1096,Female,Loyal Customer,25,Personal Travel,Eco,309,3,3,3,5,5,3,5,5,1,4,2,3,1,5,48,49.0,neutral or dissatisfied +30509,107190,Female,disloyal Customer,25,Business travel,Eco,402,2,0,2,3,1,2,1,1,4,3,1,2,1,1,0,0.0,neutral or dissatisfied +30510,64791,Male,disloyal Customer,38,Business travel,Business,247,5,5,5,3,1,5,1,1,4,3,4,4,4,1,43,30.0,satisfied +30511,15906,Male,disloyal Customer,45,Business travel,Business,607,4,4,4,2,5,4,5,5,3,4,5,5,4,5,36,34.0,satisfied +30512,59762,Male,disloyal Customer,24,Business travel,Business,895,5,0,5,1,4,5,4,4,3,5,4,4,5,4,21,10.0,satisfied +30513,125158,Female,disloyal Customer,22,Business travel,Eco,813,1,1,1,4,3,1,3,3,1,3,3,2,4,3,0,83.0,neutral or dissatisfied +30514,100980,Male,Loyal Customer,8,Business travel,Business,1524,4,4,5,4,4,5,4,4,5,3,5,4,4,4,12,3.0,satisfied +30515,99566,Male,Loyal Customer,39,Business travel,Business,2275,1,1,1,1,2,5,4,2,2,2,2,4,2,3,7,9.0,satisfied +30516,70161,Male,Loyal Customer,23,Personal Travel,Eco,550,3,5,3,1,5,3,5,5,4,3,3,3,5,5,0,0.0,neutral or dissatisfied +30517,67748,Male,disloyal Customer,28,Business travel,Business,1235,3,3,3,3,2,3,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +30518,37673,Female,Loyal Customer,27,Personal Travel,Eco,1097,2,0,2,4,5,2,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +30519,66362,Male,disloyal Customer,37,Business travel,Eco,586,2,0,2,1,1,2,1,1,1,1,5,4,3,1,0,1.0,neutral or dissatisfied +30520,4429,Male,Loyal Customer,52,Business travel,Business,2861,3,3,3,3,3,5,4,5,5,5,5,3,5,4,28,50.0,satisfied +30521,56572,Male,Loyal Customer,44,Business travel,Business,1992,5,5,5,5,4,4,5,4,4,4,4,4,4,5,2,0.0,satisfied +30522,107664,Male,Loyal Customer,48,Business travel,Business,2762,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +30523,64700,Male,Loyal Customer,44,Business travel,Business,1510,1,1,4,1,3,5,4,4,4,4,4,3,4,4,21,20.0,satisfied +30524,54389,Male,Loyal Customer,29,Business travel,Business,2968,2,2,2,2,4,4,4,4,1,3,4,5,2,4,1,1.0,satisfied +30525,63839,Female,disloyal Customer,35,Business travel,Business,1212,2,2,2,5,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +30526,77517,Male,disloyal Customer,23,Business travel,Eco,1121,3,4,4,3,2,4,2,2,3,4,4,2,4,2,25,0.0,neutral or dissatisfied +30527,104448,Male,Loyal Customer,44,Business travel,Business,2959,4,4,5,4,2,4,5,4,4,4,4,5,4,3,34,20.0,satisfied +30528,62484,Female,disloyal Customer,39,Business travel,Business,1283,5,5,5,5,2,5,2,2,4,3,5,5,5,2,9,4.0,satisfied +30529,98162,Female,Loyal Customer,23,Personal Travel,Eco,562,2,4,3,2,2,3,1,2,3,4,4,3,5,2,2,,neutral or dissatisfied +30530,113660,Male,Loyal Customer,8,Personal Travel,Eco,236,3,4,3,5,4,3,4,4,5,3,1,1,3,4,22,3.0,neutral or dissatisfied +30531,95540,Female,Loyal Customer,49,Personal Travel,Eco Plus,148,2,2,2,4,2,3,4,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +30532,76591,Male,disloyal Customer,29,Business travel,Eco,534,3,2,3,3,5,3,5,5,2,3,4,4,3,5,0,0.0,neutral or dissatisfied +30533,6577,Male,Loyal Customer,39,Business travel,Eco,607,1,2,2,2,1,1,1,1,4,1,3,2,4,1,0,0.0,neutral or dissatisfied +30534,48741,Male,Loyal Customer,32,Business travel,Business,2522,1,0,0,3,4,0,4,4,1,5,4,3,3,4,8,6.0,neutral or dissatisfied +30535,84387,Male,Loyal Customer,27,Business travel,Business,3344,3,5,5,5,3,3,3,3,2,5,4,3,4,3,10,0.0,neutral or dissatisfied +30536,35187,Female,Loyal Customer,43,Business travel,Eco,1028,4,1,1,1,2,2,4,4,4,4,4,1,4,3,75,105.0,satisfied +30537,69233,Female,Loyal Customer,41,Business travel,Business,733,2,2,2,2,5,5,5,2,2,2,2,4,2,5,0,3.0,satisfied +30538,34602,Male,Loyal Customer,31,Personal Travel,Eco,1598,3,5,3,5,1,3,5,1,3,3,4,3,4,1,3,17.0,neutral or dissatisfied +30539,6390,Female,disloyal Customer,50,Business travel,Eco,296,2,3,2,3,2,1,1,2,2,3,3,1,3,1,155,237.0,neutral or dissatisfied +30540,129679,Male,Loyal Customer,42,Business travel,Business,337,5,5,5,5,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +30541,9196,Female,Loyal Customer,52,Business travel,Business,2844,3,4,4,4,5,3,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +30542,37782,Male,Loyal Customer,34,Business travel,Eco Plus,944,4,5,5,5,4,4,4,4,2,5,2,3,3,4,14,0.0,neutral or dissatisfied +30543,65319,Female,Loyal Customer,22,Business travel,Business,432,3,3,3,3,3,3,3,3,2,2,3,1,3,3,0,6.0,neutral or dissatisfied +30544,49931,Male,disloyal Customer,44,Business travel,Eco,77,0,0,0,2,5,0,5,5,1,5,1,3,3,5,13,14.0,satisfied +30545,87962,Male,Loyal Customer,34,Business travel,Business,1678,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +30546,124665,Female,Loyal Customer,74,Business travel,Business,399,1,1,1,1,3,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +30547,115936,Female,Loyal Customer,46,Business travel,Business,371,2,2,2,2,2,5,4,4,4,4,4,1,4,4,0,3.0,satisfied +30548,1918,Male,Loyal Customer,48,Business travel,Business,351,0,0,0,3,5,5,4,3,3,3,3,5,3,3,80,76.0,satisfied +30549,36399,Female,Loyal Customer,56,Business travel,Business,632,2,2,2,2,2,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +30550,92876,Male,Loyal Customer,51,Business travel,Business,3720,1,3,3,3,2,3,3,2,2,2,1,1,2,4,0,0.0,neutral or dissatisfied +30551,22720,Female,Loyal Customer,46,Business travel,Business,170,0,4,0,4,4,4,4,4,4,4,4,3,4,3,0,15.0,satisfied +30552,41897,Male,Loyal Customer,46,Business travel,Business,129,0,5,0,3,2,5,3,2,2,2,2,2,2,4,0,3.0,satisfied +30553,70649,Male,Loyal Customer,54,Business travel,Business,3995,2,2,5,2,5,4,5,3,3,3,3,4,3,3,0,4.0,satisfied +30554,41671,Female,Loyal Customer,31,Business travel,Eco,347,3,5,5,5,3,3,3,3,1,1,2,4,3,3,0,8.0,neutral or dissatisfied +30555,12637,Female,Loyal Customer,29,Business travel,Eco,844,5,1,1,1,5,4,5,5,4,4,2,2,1,5,0,0.0,neutral or dissatisfied +30556,49788,Male,Loyal Customer,30,Business travel,Eco,199,5,4,3,4,5,5,5,5,3,4,3,1,1,5,14,1.0,satisfied +30557,53331,Female,Loyal Customer,22,Business travel,Eco Plus,811,4,3,3,3,4,4,2,4,1,4,4,2,4,4,0,0.0,neutral or dissatisfied +30558,70552,Male,disloyal Customer,24,Business travel,Eco,1258,2,2,2,2,2,2,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +30559,129398,Female,Loyal Customer,53,Personal Travel,Business,414,3,2,3,3,3,3,3,1,1,3,1,4,1,2,0,0.0,neutral or dissatisfied +30560,117202,Female,Loyal Customer,53,Personal Travel,Eco,647,1,4,1,3,3,2,1,3,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +30561,109008,Female,disloyal Customer,26,Business travel,Business,781,0,0,0,2,3,0,3,3,5,5,5,3,5,3,15,15.0,satisfied +30562,102718,Male,Loyal Customer,33,Personal Travel,Eco,255,0,5,0,5,3,0,3,3,3,4,4,4,5,3,0,0.0,satisfied +30563,118732,Male,Loyal Customer,42,Personal Travel,Eco,451,3,1,3,3,2,3,2,2,4,5,2,4,2,2,2,0.0,neutral or dissatisfied +30564,123405,Female,Loyal Customer,43,Business travel,Business,1337,1,1,1,1,2,4,5,4,4,4,4,4,4,4,38,30.0,satisfied +30565,27389,Male,disloyal Customer,15,Business travel,Eco,679,2,2,2,2,3,2,3,3,1,5,1,1,1,3,43,87.0,neutral or dissatisfied +30566,42641,Male,Loyal Customer,37,Personal Travel,Eco,481,1,2,1,3,3,1,3,3,3,5,4,3,4,3,110,112.0,neutral or dissatisfied +30567,40716,Male,Loyal Customer,18,Business travel,Business,584,5,5,5,5,4,4,4,4,2,1,2,5,2,4,0,0.0,satisfied +30568,23192,Male,Loyal Customer,44,Personal Travel,Eco,300,0,4,0,1,1,0,5,1,5,3,5,3,5,1,0,0.0,satisfied +30569,39996,Male,Loyal Customer,65,Personal Travel,Eco,508,3,4,3,4,3,3,4,3,4,4,5,4,5,3,13,12.0,neutral or dissatisfied +30570,58994,Male,Loyal Customer,56,Business travel,Business,1726,3,3,3,3,3,4,4,4,4,4,4,5,4,4,6,0.0,satisfied +30571,31615,Female,Loyal Customer,49,Business travel,Business,3375,3,1,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +30572,21258,Female,Loyal Customer,54,Personal Travel,Eco Plus,192,2,5,2,2,3,4,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +30573,124513,Male,Loyal Customer,35,Business travel,Business,2586,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,5.0,satisfied +30574,119683,Male,Loyal Customer,56,Personal Travel,Business,1325,1,5,1,4,2,4,5,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +30575,84024,Male,Loyal Customer,45,Business travel,Business,321,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,1.0,satisfied +30576,92854,Female,Loyal Customer,52,Business travel,Business,2125,1,1,1,1,3,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +30577,47186,Female,Loyal Customer,49,Business travel,Business,1926,2,2,2,2,5,1,3,4,4,4,4,5,4,4,0,0.0,satisfied +30578,1341,Female,Loyal Customer,44,Business travel,Business,2886,1,2,2,2,1,4,4,1,1,1,1,4,1,1,0,3.0,neutral or dissatisfied +30579,41801,Male,Loyal Customer,36,Business travel,Eco,257,5,2,3,2,5,5,5,5,4,2,1,4,5,5,0,0.0,satisfied +30580,13358,Male,Loyal Customer,59,Business travel,Business,2664,2,5,5,5,3,3,4,2,2,3,2,1,2,3,21,18.0,neutral or dissatisfied +30581,111046,Female,Loyal Customer,30,Business travel,Business,268,3,3,3,3,3,3,3,3,1,2,3,2,4,3,13,10.0,neutral or dissatisfied +30582,15750,Female,Loyal Customer,45,Business travel,Eco,461,2,3,3,3,1,3,3,2,2,2,2,2,2,2,1,7.0,neutral or dissatisfied +30583,58087,Female,disloyal Customer,37,Business travel,Business,612,4,4,4,4,1,4,1,1,3,5,4,4,5,1,0,0.0,satisfied +30584,61716,Female,Loyal Customer,7,Business travel,Business,3651,2,1,1,1,2,2,2,2,4,2,4,2,3,2,97,85.0,neutral or dissatisfied +30585,48868,Female,Loyal Customer,34,Business travel,Business,3686,5,5,5,5,3,4,5,5,5,5,5,3,5,1,0,0.0,satisfied +30586,107093,Female,Loyal Customer,39,Business travel,Business,745,1,1,1,1,2,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +30587,104175,Male,Loyal Customer,47,Business travel,Business,2307,0,0,0,4,5,3,3,4,4,4,4,3,4,4,0,0.0,satisfied +30588,7446,Female,Loyal Customer,34,Personal Travel,Eco,552,3,3,3,5,2,3,2,2,1,3,4,4,1,2,0,1.0,neutral or dissatisfied +30589,55121,Male,Loyal Customer,69,Personal Travel,Eco,1346,4,4,4,1,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +30590,126354,Female,Loyal Customer,68,Personal Travel,Eco,328,3,5,3,3,3,2,4,2,2,3,2,3,2,1,19,12.0,neutral or dissatisfied +30591,84794,Male,Loyal Customer,51,Business travel,Business,2861,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +30592,26382,Female,Loyal Customer,36,Business travel,Eco Plus,861,5,4,4,4,5,5,5,5,4,5,4,3,1,5,0,0.0,satisfied +30593,125375,Male,Loyal Customer,31,Personal Travel,Business,1440,3,4,3,1,3,3,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +30594,120342,Female,Loyal Customer,53,Business travel,Business,366,5,5,2,5,5,5,4,5,5,5,5,3,5,4,15,24.0,satisfied +30595,4046,Female,Loyal Customer,9,Personal Travel,Eco,483,2,3,2,4,5,2,5,5,3,1,3,5,4,5,0,0.0,neutral or dissatisfied +30596,73466,Male,Loyal Customer,41,Personal Travel,Eco,1005,3,4,3,2,3,3,3,3,4,2,5,4,5,3,76,116.0,neutral or dissatisfied +30597,129019,Male,disloyal Customer,20,Business travel,Business,2611,3,2,3,4,3,3,2,2,2,4,3,2,2,2,193,185.0,neutral or dissatisfied +30598,107088,Male,Loyal Customer,57,Business travel,Business,562,4,4,4,4,4,4,4,4,4,4,4,3,4,3,12,0.0,satisfied +30599,117755,Male,disloyal Customer,38,Business travel,Business,1670,3,3,3,4,2,3,2,2,3,2,4,4,5,2,10,32.0,neutral or dissatisfied +30600,59833,Female,disloyal Customer,23,Business travel,Eco,1085,5,5,5,3,2,5,2,2,3,5,5,3,4,2,12,3.0,satisfied +30601,48402,Female,Loyal Customer,14,Personal Travel,Eco Plus,522,1,4,1,4,5,1,5,5,4,2,4,3,4,5,0,5.0,neutral or dissatisfied +30602,112501,Male,Loyal Customer,54,Personal Travel,Eco,957,2,5,2,1,2,2,5,2,4,3,5,4,5,2,1,4.0,neutral or dissatisfied +30603,27481,Male,Loyal Customer,50,Business travel,Eco,679,4,3,3,3,4,4,4,4,2,2,4,2,1,4,0,0.0,satisfied +30604,90469,Female,disloyal Customer,36,Business travel,Business,240,4,4,4,2,4,4,4,4,4,5,4,3,5,4,6,0.0,neutral or dissatisfied +30605,67007,Male,disloyal Customer,47,Business travel,Business,1017,3,3,3,1,4,3,4,4,3,2,4,3,4,4,18,7.0,neutral or dissatisfied +30606,40270,Female,Loyal Customer,18,Personal Travel,Eco,402,3,1,3,3,5,3,5,5,4,3,4,1,3,5,1,0.0,neutral or dissatisfied +30607,19065,Female,Loyal Customer,38,Business travel,Business,3949,5,5,1,5,1,1,4,4,4,4,4,1,4,2,0,0.0,satisfied +30608,129547,Female,disloyal Customer,20,Business travel,Business,1474,4,0,3,1,2,3,2,2,4,3,5,5,5,2,0,0.0,satisfied +30609,49109,Male,Loyal Customer,35,Business travel,Business,3158,3,3,4,3,1,2,2,5,5,5,5,5,5,1,0,0.0,satisfied +30610,22864,Male,Loyal Customer,41,Personal Travel,Eco,302,4,4,5,1,4,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +30611,4817,Female,disloyal Customer,30,Business travel,Business,408,2,2,2,4,4,2,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +30612,3754,Female,Loyal Customer,33,Personal Travel,Eco Plus,431,1,5,1,3,5,1,1,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +30613,77469,Male,Loyal Customer,32,Personal Travel,Eco,507,2,1,2,3,4,2,4,4,4,3,3,3,4,4,5,10.0,neutral or dissatisfied +30614,26180,Female,disloyal Customer,8,Business travel,Eco,545,3,1,3,4,1,3,1,1,1,5,4,3,4,1,0,0.0,neutral or dissatisfied +30615,24819,Male,Loyal Customer,48,Business travel,Business,991,4,5,5,5,4,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +30616,45567,Male,disloyal Customer,26,Business travel,Eco,861,2,2,2,1,5,2,5,5,1,4,3,5,1,5,0,0.0,neutral or dissatisfied +30617,108402,Male,Loyal Customer,61,Personal Travel,Eco Plus,1844,3,5,3,5,4,3,4,4,4,3,5,5,4,4,25,40.0,neutral or dissatisfied +30618,55158,Male,Loyal Customer,34,Personal Travel,Eco,1504,3,5,3,2,3,2,2,5,5,2,4,2,1,2,146,148.0,neutral or dissatisfied +30619,87263,Male,Loyal Customer,19,Business travel,Eco,577,3,4,4,4,3,3,3,3,4,1,4,3,3,3,0,0.0,neutral or dissatisfied +30620,119136,Male,disloyal Customer,57,Business travel,Business,119,1,1,1,4,2,1,2,2,5,5,5,4,5,2,0,13.0,neutral or dissatisfied +30621,111798,Female,Loyal Customer,51,Business travel,Business,3807,0,0,0,2,5,5,5,2,2,4,4,5,2,3,1,0.0,satisfied +30622,26793,Male,Loyal Customer,16,Personal Travel,Eco,226,1,4,1,3,2,1,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +30623,19829,Male,Loyal Customer,51,Business travel,Business,3563,2,2,2,2,2,3,4,2,2,2,2,3,2,1,0,19.0,neutral or dissatisfied +30624,15356,Female,disloyal Customer,20,Business travel,Eco,433,4,1,4,2,2,4,2,2,3,4,2,1,5,2,0,11.0,satisfied +30625,88461,Male,Loyal Customer,49,Business travel,Eco,145,3,4,4,4,2,3,2,2,4,2,4,2,4,2,19,7.0,neutral or dissatisfied +30626,96990,Female,disloyal Customer,34,Business travel,Eco,775,2,1,1,5,2,1,3,2,1,4,4,4,3,2,0,0.0,neutral or dissatisfied +30627,39045,Male,Loyal Customer,57,Business travel,Eco Plus,113,2,4,5,4,2,2,2,2,4,1,2,5,2,2,0,4.0,satisfied +30628,58681,Male,Loyal Customer,47,Business travel,Business,3110,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +30629,19119,Male,Loyal Customer,78,Business travel,Eco,323,2,3,3,3,2,2,2,2,2,3,3,1,4,2,50,61.0,neutral or dissatisfied +30630,51447,Male,Loyal Customer,69,Personal Travel,Eco Plus,86,3,2,3,3,4,3,4,4,2,3,4,2,3,4,1,3.0,neutral or dissatisfied +30631,115617,Female,disloyal Customer,34,Business travel,Eco,390,1,3,2,3,4,2,4,4,4,2,4,3,4,4,12,10.0,neutral or dissatisfied +30632,73693,Female,Loyal Customer,41,Business travel,Business,192,3,3,3,3,1,3,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +30633,107529,Female,Loyal Customer,47,Business travel,Business,1521,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +30634,27480,Female,disloyal Customer,39,Business travel,Business,697,3,3,3,4,1,3,1,1,3,5,3,1,4,1,0,0.0,neutral or dissatisfied +30635,11447,Female,Loyal Customer,51,Business travel,Business,2784,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +30636,112471,Male,Loyal Customer,63,Business travel,Business,557,3,2,2,2,1,3,4,3,3,3,3,1,3,1,66,70.0,neutral or dissatisfied +30637,82290,Female,Loyal Customer,41,Business travel,Business,1481,5,3,5,5,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +30638,15463,Female,disloyal Customer,37,Business travel,Eco,306,3,1,3,4,3,3,3,3,4,4,3,3,4,3,0,13.0,neutral or dissatisfied +30639,92623,Male,Loyal Customer,58,Business travel,Business,453,5,5,5,5,5,4,5,4,4,5,4,3,4,4,0,9.0,satisfied +30640,114024,Male,Loyal Customer,44,Business travel,Eco Plus,1855,3,2,2,2,3,3,3,3,3,2,3,1,2,3,12,18.0,neutral or dissatisfied +30641,116289,Male,Loyal Customer,51,Personal Travel,Eco,446,3,5,4,3,3,4,3,3,3,2,5,3,5,3,23,50.0,neutral or dissatisfied +30642,125574,Female,Loyal Customer,64,Personal Travel,Eco,226,4,1,4,4,2,3,3,5,5,4,2,4,5,2,0,0.0,neutral or dissatisfied +30643,59664,Female,Loyal Customer,29,Personal Travel,Eco,965,1,1,1,2,2,1,2,2,3,4,3,1,2,2,0,0.0,neutral or dissatisfied +30644,88654,Male,Loyal Customer,37,Personal Travel,Eco,594,3,4,3,3,1,3,5,1,1,4,3,5,5,1,0,0.0,neutral or dissatisfied +30645,61664,Male,Loyal Customer,42,Business travel,Business,1379,1,4,4,4,2,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +30646,85996,Male,Loyal Customer,79,Business travel,Eco,447,4,2,3,2,3,4,3,3,3,2,4,2,3,3,15,12.0,neutral or dissatisfied +30647,126854,Male,Loyal Customer,30,Personal Travel,Eco,2125,4,2,5,4,1,5,1,1,3,5,3,4,3,1,69,48.0,satisfied +30648,71441,Male,disloyal Customer,39,Business travel,Eco,867,1,1,1,2,5,1,2,5,4,1,2,1,3,5,1,0.0,neutral or dissatisfied +30649,42094,Female,Loyal Customer,32,Business travel,Business,1787,3,3,3,3,5,5,5,5,1,5,3,2,4,5,0,0.0,satisfied +30650,111553,Male,Loyal Customer,51,Business travel,Business,1870,2,2,2,2,5,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +30651,121120,Female,disloyal Customer,29,Business travel,Business,2402,4,4,4,1,1,4,2,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +30652,120249,Female,Loyal Customer,13,Personal Travel,Eco,1303,5,4,5,4,5,5,3,5,5,5,5,5,4,5,0,0.0,satisfied +30653,40257,Female,Loyal Customer,30,Business travel,Business,2946,3,3,3,3,4,4,4,4,1,4,2,5,2,4,0,0.0,satisfied +30654,56797,Male,Loyal Customer,38,Business travel,Business,1605,5,5,5,5,4,5,5,4,4,4,4,3,4,4,33,42.0,satisfied +30655,83754,Female,Loyal Customer,36,Personal Travel,Eco,1183,5,4,5,3,3,5,3,3,5,5,4,4,4,3,0,0.0,satisfied +30656,179,Female,Loyal Customer,36,Business travel,Business,213,0,4,0,3,3,4,4,1,1,1,1,5,1,5,0,0.0,satisfied +30657,10681,Female,Loyal Customer,66,Business travel,Business,2727,3,1,1,1,3,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +30658,95753,Male,Loyal Customer,46,Business travel,Business,237,3,3,3,3,4,3,3,3,3,3,3,4,3,4,13,6.0,neutral or dissatisfied +30659,84281,Female,Loyal Customer,7,Personal Travel,Eco,334,3,5,3,2,5,3,5,5,5,2,4,3,5,5,0,8.0,neutral or dissatisfied +30660,126966,Male,Loyal Customer,41,Business travel,Business,1590,4,4,4,4,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +30661,67222,Male,Loyal Customer,15,Personal Travel,Eco,985,3,4,2,3,3,2,3,3,5,2,4,4,5,3,130,125.0,neutral or dissatisfied +30662,86766,Male,Loyal Customer,33,Personal Travel,Eco Plus,821,2,4,2,3,1,2,1,1,1,5,4,3,4,1,25,23.0,neutral or dissatisfied +30663,24040,Female,Loyal Customer,47,Personal Travel,Eco,562,4,5,4,1,2,4,5,4,4,4,2,3,4,3,2,2.0,neutral or dissatisfied +30664,57314,Male,Loyal Customer,57,Business travel,Business,3380,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +30665,52238,Female,Loyal Customer,27,Business travel,Business,2372,1,1,1,1,5,5,5,5,4,4,1,4,4,5,0,4.0,satisfied +30666,76427,Female,Loyal Customer,67,Business travel,Business,405,2,2,2,2,3,2,2,2,2,2,2,3,2,1,56,30.0,neutral or dissatisfied +30667,111173,Female,Loyal Customer,23,Personal Travel,Business,1703,4,1,5,2,3,5,3,3,4,1,2,2,3,3,10,0.0,satisfied +30668,113832,Female,Loyal Customer,22,Personal Travel,Eco Plus,414,3,3,3,1,5,3,5,5,4,4,1,5,3,5,27,20.0,neutral or dissatisfied +30669,2629,Female,disloyal Customer,25,Business travel,Eco Plus,227,1,4,2,3,1,2,2,1,2,5,3,4,4,1,0,0.0,neutral or dissatisfied +30670,115855,Male,Loyal Customer,46,Business travel,Business,1832,3,4,1,1,4,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +30671,26923,Male,Loyal Customer,12,Personal Travel,Eco,1874,5,1,5,3,4,5,4,4,1,3,2,4,2,4,18,2.0,satisfied +30672,22215,Male,Loyal Customer,42,Personal Travel,Eco,606,3,3,3,1,5,3,5,5,5,1,1,5,1,5,26,11.0,neutral or dissatisfied +30673,124574,Female,Loyal Customer,55,Business travel,Business,3744,2,2,2,2,2,4,4,3,3,4,3,4,3,4,7,1.0,satisfied +30674,80209,Female,Loyal Customer,26,Personal Travel,Eco Plus,2475,4,3,5,4,5,1,1,3,3,3,5,1,5,1,119,99.0,neutral or dissatisfied +30675,103921,Male,Loyal Customer,43,Business travel,Business,533,2,2,2,2,2,5,4,5,5,4,5,4,5,4,36,27.0,satisfied +30676,32808,Male,disloyal Customer,22,Business travel,Eco,102,3,3,4,1,2,4,2,2,4,3,4,2,1,2,0,0.0,neutral or dissatisfied +30677,26885,Female,disloyal Customer,34,Business travel,Eco,689,3,3,3,3,3,3,1,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +30678,111253,Female,Loyal Customer,43,Business travel,Business,1788,1,1,5,1,4,2,2,1,1,1,1,4,1,2,18,16.0,neutral or dissatisfied +30679,56338,Male,Loyal Customer,40,Business travel,Eco,200,3,2,2,2,3,3,3,3,2,2,3,3,4,3,69,64.0,neutral or dissatisfied +30680,56144,Female,disloyal Customer,45,Business travel,Business,1400,1,1,1,2,1,1,1,1,4,4,4,5,4,1,2,15.0,neutral or dissatisfied +30681,18105,Female,Loyal Customer,42,Personal Travel,Eco,610,3,2,3,3,1,2,3,2,2,3,3,2,2,4,0,0.0,neutral or dissatisfied +30682,86055,Female,Loyal Customer,60,Personal Travel,Eco,447,1,5,1,3,5,4,5,3,3,1,3,3,3,5,0,5.0,neutral or dissatisfied +30683,71571,Female,disloyal Customer,20,Business travel,Business,1144,4,0,4,2,2,4,2,2,5,5,5,5,5,2,75,129.0,satisfied +30684,69361,Female,Loyal Customer,51,Business travel,Business,944,4,5,5,5,2,4,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +30685,97788,Female,Loyal Customer,80,Business travel,Business,3825,4,1,1,1,5,3,3,4,4,4,4,1,4,4,1,0.0,neutral or dissatisfied +30686,72944,Male,Loyal Customer,27,Business travel,Business,2839,4,5,4,4,5,5,5,5,3,3,5,5,5,5,78,56.0,satisfied +30687,23147,Female,Loyal Customer,30,Business travel,Business,223,2,2,3,2,4,4,4,4,5,4,2,3,3,4,0,0.0,satisfied +30688,88883,Male,Loyal Customer,60,Business travel,Business,2725,2,2,4,2,3,5,4,4,4,4,4,4,4,4,79,54.0,satisfied +30689,129857,Male,disloyal Customer,21,Business travel,Business,337,4,4,4,1,5,4,5,5,5,2,4,5,4,5,46,43.0,satisfied +30690,8156,Female,Loyal Customer,58,Business travel,Business,3554,2,1,1,1,4,4,3,2,2,2,2,4,2,3,0,6.0,neutral or dissatisfied +30691,10688,Male,Loyal Customer,57,Business travel,Business,201,4,3,4,4,2,5,5,5,5,5,4,4,5,3,0,0.0,satisfied +30692,107732,Male,Loyal Customer,50,Personal Travel,Eco,405,3,5,3,1,4,3,5,4,5,4,4,5,5,4,15,7.0,neutral or dissatisfied +30693,108181,Male,Loyal Customer,28,Personal Travel,Eco,1166,3,4,3,3,3,3,5,3,3,2,4,4,4,3,28,25.0,neutral or dissatisfied +30694,2343,Female,Loyal Customer,16,Business travel,Eco Plus,690,4,4,4,4,4,4,3,4,3,1,4,4,4,4,38,46.0,neutral or dissatisfied +30695,115923,Male,Loyal Customer,63,Business travel,Business,3947,0,0,0,3,4,1,2,2,2,2,2,4,2,4,0,0.0,satisfied +30696,65533,Male,Loyal Customer,24,Business travel,Eco Plus,1616,3,1,1,1,3,3,2,3,3,3,2,3,3,3,38,79.0,neutral or dissatisfied +30697,49543,Male,Loyal Customer,53,Business travel,Business,3552,3,3,2,3,2,2,3,4,4,4,4,1,4,2,0,5.0,satisfied +30698,117055,Female,Loyal Customer,62,Business travel,Business,3689,3,3,3,3,2,2,2,3,3,3,3,3,3,4,37,23.0,neutral or dissatisfied +30699,53549,Male,Loyal Customer,40,Business travel,Eco,1956,5,2,4,2,5,5,5,5,3,2,4,5,3,5,0,0.0,satisfied +30700,109123,Female,Loyal Customer,45,Personal Travel,Eco Plus,816,5,0,5,4,2,5,5,3,3,5,3,5,3,5,0,0.0,satisfied +30701,24448,Male,Loyal Customer,46,Business travel,Eco,516,5,2,2,2,5,5,5,5,5,1,1,2,3,5,6,29.0,satisfied +30702,60715,Male,disloyal Customer,8,Business travel,Eco,756,2,1,1,4,4,2,4,4,1,3,3,3,4,4,40,30.0,neutral or dissatisfied +30703,41868,Female,Loyal Customer,43,Personal Travel,Eco,483,1,3,1,5,4,5,2,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +30704,69745,Female,disloyal Customer,27,Business travel,Eco,1085,2,2,2,4,2,2,2,2,3,1,3,1,4,2,21,10.0,neutral or dissatisfied +30705,122790,Female,disloyal Customer,24,Business travel,Business,599,2,1,1,2,3,1,3,3,2,5,2,4,2,3,23,9.0,neutral or dissatisfied +30706,128740,Female,Loyal Customer,48,Business travel,Business,2402,1,1,5,1,4,4,4,4,3,3,4,4,3,4,0,0.0,satisfied +30707,93358,Female,Loyal Customer,42,Business travel,Eco,1024,4,3,3,3,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +30708,108738,Female,Loyal Customer,40,Business travel,Business,406,1,1,1,1,4,4,4,5,5,5,5,5,5,4,13,20.0,satisfied +30709,87904,Male,Loyal Customer,39,Business travel,Business,581,4,4,4,4,2,4,4,4,4,4,4,3,4,4,3,0.0,satisfied +30710,36263,Male,Loyal Customer,37,Business travel,Eco,612,2,1,1,1,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +30711,102719,Male,Loyal Customer,29,Personal Travel,Eco,255,2,4,2,4,4,2,4,4,3,3,3,2,4,4,0,0.0,neutral or dissatisfied +30712,39605,Female,Loyal Customer,51,Personal Travel,Eco,679,4,4,4,1,2,5,4,1,1,4,1,5,1,5,0,0.0,neutral or dissatisfied +30713,37881,Male,Loyal Customer,30,Business travel,Business,1912,1,5,5,5,1,1,1,1,3,5,4,4,4,1,91,123.0,neutral or dissatisfied +30714,91247,Male,Loyal Customer,62,Personal Travel,Eco,406,2,5,2,1,1,2,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +30715,88447,Female,disloyal Customer,25,Business travel,Eco,271,2,2,3,3,5,3,5,5,4,3,3,2,4,5,0,0.0,neutral or dissatisfied +30716,107203,Female,Loyal Customer,10,Personal Travel,Eco,402,1,5,1,1,2,1,2,2,2,4,5,2,3,2,0,0.0,neutral or dissatisfied +30717,118103,Female,Loyal Customer,32,Business travel,Eco,1999,4,2,2,2,4,4,4,4,3,1,2,3,3,4,0,19.0,neutral or dissatisfied +30718,123946,Male,Loyal Customer,49,Business travel,Business,3183,2,2,2,2,3,4,4,5,5,5,5,3,5,4,7,7.0,satisfied +30719,15870,Female,Loyal Customer,47,Business travel,Business,2098,3,3,3,3,2,2,5,4,4,4,4,3,4,5,5,0.0,satisfied +30720,20807,Female,disloyal Customer,24,Business travel,Eco,357,4,0,4,2,4,4,4,4,3,3,1,3,2,4,12,2.0,satisfied +30721,122418,Male,Loyal Customer,54,Business travel,Business,1916,4,4,4,4,3,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +30722,5864,Female,Loyal Customer,55,Personal Travel,Eco,1020,1,1,2,4,3,3,4,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +30723,67155,Female,disloyal Customer,85,Business travel,Business,617,3,3,3,4,3,1,1,3,1,3,3,1,2,1,58,59.0,neutral or dissatisfied +30724,122398,Female,Loyal Customer,8,Personal Travel,Eco,529,2,5,2,2,2,2,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +30725,108449,Male,Loyal Customer,40,Business travel,Business,1444,2,4,3,3,1,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +30726,82008,Male,disloyal Customer,17,Business travel,Eco,1535,1,1,1,4,3,1,3,3,4,2,3,4,4,3,0,16.0,neutral or dissatisfied +30727,25236,Female,Loyal Customer,55,Personal Travel,Eco,787,2,1,2,3,1,2,2,2,2,2,2,1,2,2,51,68.0,neutral or dissatisfied +30728,19269,Female,Loyal Customer,11,Personal Travel,Eco,1017,2,4,2,4,5,2,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +30729,36519,Female,Loyal Customer,49,Business travel,Business,2866,3,4,3,3,1,1,5,3,3,3,3,4,3,5,0,13.0,satisfied +30730,81782,Female,disloyal Customer,23,Business travel,Eco,1360,2,2,2,1,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +30731,108343,Female,Loyal Customer,77,Business travel,Business,1844,3,5,5,5,4,4,4,3,3,2,3,1,3,1,11,25.0,neutral or dissatisfied +30732,127249,Male,Loyal Customer,50,Business travel,Business,3706,5,5,5,5,4,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +30733,119624,Female,Loyal Customer,60,Personal Travel,Business,1927,1,4,1,3,2,4,5,4,4,1,4,4,4,5,18,0.0,neutral or dissatisfied +30734,125867,Female,disloyal Customer,27,Business travel,Eco,1013,1,1,1,3,1,1,1,1,3,3,2,4,2,1,53,47.0,neutral or dissatisfied +30735,125196,Female,Loyal Customer,31,Business travel,Business,2146,3,1,1,1,3,3,3,3,1,2,4,3,3,3,3,0.0,neutral or dissatisfied +30736,3918,Female,Loyal Customer,40,Personal Travel,Eco,213,3,0,3,3,2,3,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +30737,36965,Female,Loyal Customer,30,Business travel,Business,899,3,3,4,3,5,5,5,5,3,2,2,3,5,5,0,0.0,satisfied +30738,119195,Male,Loyal Customer,37,Business travel,Business,331,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +30739,60292,Male,Loyal Customer,24,Business travel,Business,3742,3,4,4,4,3,3,3,3,2,4,4,4,3,3,0,0.0,neutral or dissatisfied +30740,82668,Female,Loyal Customer,52,Personal Travel,Eco,120,4,2,0,3,2,3,3,5,5,0,5,4,5,4,0,0.0,satisfied +30741,45359,Female,Loyal Customer,58,Personal Travel,Eco,188,3,4,3,4,4,4,4,1,1,3,5,3,1,3,0,0.0,neutral or dissatisfied +30742,15465,Male,Loyal Customer,27,Personal Travel,Eco,331,4,2,4,4,1,4,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +30743,26755,Female,Loyal Customer,50,Business travel,Eco,859,3,2,2,2,5,5,5,3,3,3,3,2,3,5,0,0.0,satisfied +30744,86120,Male,Loyal Customer,30,Business travel,Business,306,3,3,3,3,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +30745,111556,Female,Loyal Customer,45,Business travel,Business,883,1,1,1,1,5,4,5,4,4,5,4,3,4,5,18,2.0,satisfied +30746,91398,Female,Loyal Customer,23,Business travel,Business,2982,3,3,3,3,5,5,5,5,1,1,2,3,5,5,0,0.0,satisfied +30747,16423,Female,Loyal Customer,28,Business travel,Business,3094,3,3,3,3,4,4,4,4,1,5,1,3,4,4,0,0.0,satisfied +30748,105542,Male,Loyal Customer,42,Business travel,Eco,211,3,4,4,4,4,3,4,4,3,5,4,4,3,4,0,0.0,neutral or dissatisfied +30749,76775,Male,disloyal Customer,21,Business travel,Eco,689,1,1,1,4,4,1,4,4,4,1,3,2,3,4,11,18.0,neutral or dissatisfied +30750,23397,Female,Loyal Customer,38,Business travel,Eco,300,1,1,1,1,1,1,1,1,1,4,3,3,4,1,40,30.0,neutral or dissatisfied +30751,66271,Female,Loyal Customer,21,Personal Travel,Eco,460,2,3,2,1,2,2,2,2,3,2,1,4,3,2,0,0.0,neutral or dissatisfied +30752,39870,Female,Loyal Customer,57,Personal Travel,Eco,272,4,0,4,1,3,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +30753,33159,Female,Loyal Customer,22,Personal Travel,Eco,102,0,3,0,3,5,0,5,5,1,3,4,3,2,5,0,0.0,satisfied +30754,35335,Female,Loyal Customer,59,Business travel,Business,2990,2,5,5,5,5,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +30755,71198,Male,Loyal Customer,56,Business travel,Business,733,5,5,5,5,5,5,5,4,4,4,4,3,4,5,21,9.0,satisfied +30756,108961,Female,disloyal Customer,38,Business travel,Eco,667,3,4,3,3,2,3,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +30757,48318,Female,Loyal Customer,53,Business travel,Eco,1203,4,3,3,3,1,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +30758,53316,Female,Loyal Customer,54,Personal Travel,Eco,758,3,4,3,1,2,5,5,3,3,3,3,4,3,4,0,3.0,neutral or dissatisfied +30759,43432,Female,Loyal Customer,43,Personal Travel,Eco,913,3,4,3,4,3,5,4,1,1,3,1,3,1,5,0,13.0,neutral or dissatisfied +30760,34773,Female,Loyal Customer,43,Business travel,Business,264,1,2,2,2,3,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +30761,99625,Male,Loyal Customer,55,Business travel,Eco,1224,2,3,3,3,2,2,2,2,2,2,2,1,2,2,0,2.0,neutral or dissatisfied +30762,97587,Male,Loyal Customer,42,Business travel,Business,2363,2,2,3,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +30763,79217,Female,Loyal Customer,30,Personal Travel,Eco,1990,2,3,2,2,1,2,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +30764,78848,Male,Loyal Customer,56,Business travel,Business,2530,5,5,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +30765,122930,Male,disloyal Customer,36,Business travel,Business,468,4,4,4,4,2,4,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +30766,49373,Male,disloyal Customer,34,Business travel,Eco,262,2,4,2,2,2,2,4,2,1,2,3,5,2,2,0,0.0,neutral or dissatisfied +30767,8958,Female,Loyal Customer,34,Business travel,Business,1981,3,5,1,5,3,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +30768,34550,Female,Loyal Customer,50,Business travel,Business,1598,1,1,1,1,2,3,2,4,4,4,4,3,4,5,0,0.0,satisfied +30769,49527,Female,disloyal Customer,38,Business travel,Eco,337,5,4,5,3,2,5,2,2,4,3,4,2,3,2,0,8.0,satisfied +30770,114278,Male,Loyal Customer,68,Personal Travel,Eco,850,3,3,3,3,5,3,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +30771,48370,Male,Loyal Customer,51,Business travel,Eco,122,2,5,3,5,2,2,2,2,5,2,5,2,3,2,0,0.0,satisfied +30772,129003,Female,Loyal Customer,44,Business travel,Business,2704,4,4,4,4,5,5,5,4,4,4,5,5,4,5,0,0.0,satisfied +30773,107696,Female,disloyal Customer,25,Business travel,Business,251,3,0,3,2,4,3,1,4,5,4,4,5,5,4,16,15.0,neutral or dissatisfied +30774,70331,Female,Loyal Customer,51,Business travel,Business,2049,1,1,1,1,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +30775,25900,Female,Loyal Customer,19,Personal Travel,Eco,907,4,4,4,4,5,4,4,5,3,3,5,5,5,5,0,0.0,satisfied +30776,87368,Female,disloyal Customer,27,Business travel,Business,425,0,0,0,2,3,0,3,3,4,4,5,4,5,3,21,15.0,satisfied +30777,54368,Female,Loyal Customer,33,Business travel,Eco Plus,1235,4,2,2,2,4,4,4,4,2,2,3,2,5,4,0,0.0,satisfied +30778,1180,Male,Loyal Customer,28,Personal Travel,Eco,158,3,5,3,5,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +30779,78135,Male,Loyal Customer,10,Personal Travel,Business,259,4,5,4,2,5,4,5,5,3,3,1,5,1,5,0,0.0,satisfied +30780,844,Male,Loyal Customer,52,Business travel,Business,1959,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +30781,12881,Female,disloyal Customer,22,Business travel,Eco,456,4,0,4,5,1,4,1,1,1,5,4,2,5,1,0,0.0,satisfied +30782,102051,Male,disloyal Customer,38,Business travel,Business,407,4,4,4,3,5,4,5,5,2,1,4,1,4,5,0,0.0,neutral or dissatisfied +30783,116459,Female,Loyal Customer,10,Personal Travel,Eco,296,1,5,1,3,1,2,2,3,5,4,4,2,5,2,252,255.0,neutral or dissatisfied +30784,80200,Male,Loyal Customer,61,Personal Travel,Eco,2475,1,1,1,3,4,1,4,4,2,4,3,3,4,4,4,0.0,neutral or dissatisfied +30785,108706,Male,Loyal Customer,56,Business travel,Business,1717,2,2,2,2,2,5,4,5,5,5,5,5,5,3,11,0.0,satisfied +30786,20752,Male,Loyal Customer,36,Personal Travel,Eco,363,3,4,3,4,5,3,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +30787,15291,Male,Loyal Customer,14,Personal Travel,Eco,500,2,4,2,4,2,3,3,3,3,4,4,3,4,3,131,114.0,neutral or dissatisfied +30788,72022,Female,Loyal Customer,62,Business travel,Business,3784,2,2,2,2,5,5,5,4,2,5,4,5,3,5,260,279.0,satisfied +30789,84432,Female,Loyal Customer,48,Business travel,Business,3230,4,4,4,4,4,5,5,3,3,3,3,3,3,4,14,16.0,satisfied +30790,25251,Female,Loyal Customer,42,Personal Travel,Eco Plus,919,4,5,4,4,4,2,1,3,3,4,3,3,3,2,12,0.0,neutral or dissatisfied +30791,1201,Female,Loyal Customer,35,Personal Travel,Eco,134,3,0,3,4,4,3,4,4,4,5,5,3,4,4,58,59.0,neutral or dissatisfied +30792,33663,Male,Loyal Customer,60,Business travel,Eco Plus,399,5,4,4,4,5,5,5,5,2,4,3,2,3,5,0,0.0,satisfied +30793,53376,Female,disloyal Customer,22,Business travel,Eco,1052,4,4,4,1,1,4,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +30794,24251,Male,Loyal Customer,67,Personal Travel,Eco,147,5,5,0,4,4,0,4,4,3,5,5,4,5,4,0,0.0,satisfied +30795,49096,Male,Loyal Customer,44,Business travel,Business,2035,3,3,5,3,1,2,3,4,4,5,5,4,4,3,3,0.0,satisfied +30796,36051,Female,Loyal Customer,55,Business travel,Business,2034,2,3,3,3,3,4,4,2,2,2,2,4,2,4,0,6.0,neutral or dissatisfied +30797,100756,Female,disloyal Customer,44,Business travel,Eco Plus,328,2,3,3,3,5,2,5,5,1,2,4,4,4,5,49,44.0,neutral or dissatisfied +30798,65401,Female,Loyal Customer,25,Personal Travel,Eco,432,2,2,2,4,1,2,1,1,2,5,4,4,4,1,3,0.0,neutral or dissatisfied +30799,57877,Female,Loyal Customer,50,Business travel,Business,2798,4,4,5,4,2,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +30800,126009,Male,Loyal Customer,53,Business travel,Business,1691,5,5,3,5,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +30801,12863,Female,Loyal Customer,8,Business travel,Eco Plus,817,4,5,5,5,4,4,4,4,5,1,2,5,5,4,0,0.0,satisfied +30802,66626,Female,Loyal Customer,31,Personal Travel,Business,802,2,3,2,2,3,2,1,3,5,5,5,4,5,3,14,0.0,neutral or dissatisfied +30803,115730,Male,Loyal Customer,25,Business travel,Eco,373,1,2,2,2,1,1,2,1,4,1,4,3,4,1,1,9.0,neutral or dissatisfied +30804,100464,Female,disloyal Customer,39,Business travel,Business,580,4,4,4,4,5,4,1,5,3,4,4,3,5,5,44,38.0,satisfied +30805,26411,Male,Loyal Customer,18,Personal Travel,Eco,1249,1,1,1,3,3,1,5,3,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +30806,99560,Female,Loyal Customer,44,Business travel,Eco,829,2,2,2,2,1,2,3,2,2,2,2,1,2,2,50,61.0,neutral or dissatisfied +30807,41246,Female,Loyal Customer,16,Business travel,Eco,643,1,1,1,1,1,1,4,1,1,5,3,3,4,1,0,6.0,neutral or dissatisfied +30808,37621,Female,Loyal Customer,14,Personal Travel,Eco,972,2,5,2,2,5,2,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +30809,4364,Female,disloyal Customer,33,Business travel,Business,607,3,3,3,4,2,3,2,2,5,2,5,4,5,2,73,125.0,neutral or dissatisfied +30810,17742,Male,disloyal Customer,15,Business travel,Eco,456,4,2,4,4,5,4,5,5,1,2,4,4,3,5,4,66.0,neutral or dissatisfied +30811,52678,Male,Loyal Customer,32,Personal Travel,Eco,119,2,1,2,3,3,2,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +30812,70718,Female,disloyal Customer,37,Business travel,Eco,675,2,2,2,3,2,2,2,2,1,2,3,2,3,2,0,0.0,neutral or dissatisfied +30813,58537,Female,Loyal Customer,61,Personal Travel,Eco Plus,719,3,4,3,1,5,4,5,3,3,3,3,5,3,3,56,58.0,neutral or dissatisfied +30814,17002,Male,Loyal Customer,53,Business travel,Business,3919,2,3,3,3,1,2,3,2,2,2,2,2,2,4,0,6.0,neutral or dissatisfied +30815,66303,Male,Loyal Customer,25,Business travel,Business,3142,5,5,5,5,5,5,5,5,3,2,4,5,4,5,6,0.0,satisfied +30816,128713,Female,Loyal Customer,56,Business travel,Business,1504,2,4,4,4,1,3,3,2,2,2,2,3,2,2,0,5.0,neutral or dissatisfied +30817,25822,Female,Loyal Customer,37,Personal Travel,Eco,1747,1,2,1,4,4,1,1,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +30818,120365,Female,Loyal Customer,47,Business travel,Business,2836,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +30819,71221,Male,Loyal Customer,62,Business travel,Business,3005,3,4,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +30820,34525,Male,Loyal Customer,20,Personal Travel,Eco Plus,1521,2,2,2,4,3,2,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +30821,23556,Female,Loyal Customer,35,Business travel,Eco,533,5,1,2,1,5,5,5,5,1,1,5,5,4,5,69,71.0,satisfied +30822,128501,Male,Loyal Customer,61,Personal Travel,Eco,304,4,1,4,3,2,4,2,2,3,4,3,2,3,2,0,0.0,satisfied +30823,126573,Female,Loyal Customer,59,Business travel,Business,1158,3,3,3,3,3,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +30824,84905,Female,Loyal Customer,45,Personal Travel,Eco,547,3,2,3,4,1,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +30825,99470,Male,Loyal Customer,33,Business travel,Business,3801,1,0,0,4,5,0,5,5,2,2,3,4,4,5,19,10.0,neutral or dissatisfied +30826,23643,Male,Loyal Customer,59,Business travel,Business,73,3,5,3,3,5,4,4,3,3,4,5,4,3,4,13,18.0,satisfied +30827,22797,Female,disloyal Customer,23,Business travel,Eco,302,1,5,1,3,2,1,5,2,4,1,2,3,1,2,3,0.0,neutral or dissatisfied +30828,39588,Female,Loyal Customer,8,Business travel,Business,3183,2,5,5,5,2,2,2,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +30829,63458,Female,Loyal Customer,35,Business travel,Business,3203,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +30830,51559,Female,Loyal Customer,52,Business travel,Business,370,1,1,2,1,4,5,4,2,2,2,2,4,2,4,23,22.0,satisfied +30831,39044,Male,Loyal Customer,49,Personal Travel,Eco,113,3,1,3,4,2,3,2,2,1,2,3,1,3,2,3,5.0,neutral or dissatisfied +30832,5860,Female,Loyal Customer,62,Personal Travel,Eco,1020,2,4,2,1,2,3,1,1,1,2,1,4,1,4,0,2.0,neutral or dissatisfied +30833,122513,Female,Loyal Customer,26,Personal Travel,Eco,930,2,4,3,1,2,3,1,2,3,4,5,3,5,2,23,22.0,neutral or dissatisfied +30834,62682,Male,Loyal Customer,38,Personal Travel,Eco Plus,1846,3,0,3,2,2,3,2,2,5,3,3,4,5,2,25,27.0,neutral or dissatisfied +30835,122452,Male,disloyal Customer,22,Business travel,Business,808,0,5,0,1,3,0,3,3,3,4,4,3,5,3,0,7.0,satisfied +30836,32197,Female,Loyal Customer,58,Business travel,Business,2070,2,2,2,2,3,1,5,5,5,5,4,5,5,4,0,0.0,satisfied +30837,12146,Male,Loyal Customer,38,Business travel,Business,986,1,1,1,1,1,1,4,2,2,2,2,2,2,2,0,0.0,satisfied +30838,129815,Female,Loyal Customer,66,Personal Travel,Eco,337,3,3,3,2,3,5,5,1,2,3,1,5,4,5,132,140.0,neutral or dissatisfied +30839,68111,Female,Loyal Customer,30,Personal Travel,Eco,813,3,0,3,2,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +30840,121406,Male,Loyal Customer,30,Business travel,Business,2439,2,2,3,2,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +30841,100333,Male,Loyal Customer,40,Business travel,Business,3620,4,4,4,4,2,4,3,5,5,5,5,5,5,5,0,0.0,satisfied +30842,3157,Female,Loyal Customer,41,Business travel,Business,2217,0,5,0,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +30843,50804,Male,Loyal Customer,33,Personal Travel,Eco,156,4,4,4,2,5,4,5,5,5,1,2,2,3,5,6,7.0,neutral or dissatisfied +30844,113332,Female,disloyal Customer,25,Business travel,Eco,414,1,1,1,3,5,1,5,5,4,3,3,1,4,5,0,0.0,neutral or dissatisfied +30845,9437,Male,Loyal Customer,44,Business travel,Business,3819,3,3,3,3,3,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +30846,87252,Male,Loyal Customer,56,Business travel,Business,2836,4,5,4,4,4,4,4,4,4,5,4,4,4,4,1,0.0,satisfied +30847,110031,Female,Loyal Customer,64,Personal Travel,Eco Plus,1142,1,3,1,3,3,2,3,3,3,1,3,1,3,3,31,32.0,neutral or dissatisfied +30848,39630,Female,Loyal Customer,45,Business travel,Eco Plus,908,4,4,4,4,3,3,1,4,4,4,4,2,4,2,0,0.0,satisfied +30849,82632,Female,Loyal Customer,32,Personal Travel,Eco,528,2,4,2,1,1,2,1,1,3,3,4,3,5,1,0,19.0,neutral or dissatisfied +30850,55795,Female,Loyal Customer,18,Personal Travel,Eco,2400,3,5,3,2,3,2,2,3,4,4,5,2,4,2,0,0.0,neutral or dissatisfied +30851,93516,Male,Loyal Customer,66,Business travel,Eco Plus,707,4,3,3,3,4,4,4,4,2,4,4,5,5,4,0,0.0,satisfied +30852,123226,Female,Loyal Customer,25,Personal Travel,Eco,468,2,4,2,4,3,2,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +30853,21069,Male,Loyal Customer,67,Business travel,Business,3069,3,3,4,3,2,3,4,3,3,3,3,1,3,4,1,7.0,neutral or dissatisfied +30854,48887,Male,Loyal Customer,27,Business travel,Eco,308,5,4,4,4,5,5,5,5,5,5,1,5,3,5,0,0.0,satisfied +30855,65450,Male,disloyal Customer,26,Business travel,Business,1067,3,3,3,1,2,3,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +30856,9420,Male,Loyal Customer,42,Business travel,Business,2630,3,3,3,3,2,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +30857,96543,Female,Loyal Customer,13,Personal Travel,Eco,302,2,2,2,4,5,2,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +30858,21335,Female,Loyal Customer,40,Business travel,Eco,674,3,5,5,5,3,4,3,3,4,3,5,1,2,3,4,7.0,satisfied +30859,30917,Female,Loyal Customer,31,Business travel,Business,1747,2,2,2,2,2,2,2,2,4,2,3,4,3,2,24,17.0,neutral or dissatisfied +30860,54102,Female,Loyal Customer,55,Business travel,Eco Plus,1416,2,4,5,4,4,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +30861,110566,Female,Loyal Customer,30,Business travel,Business,674,3,4,4,4,3,3,3,3,2,2,4,3,4,3,15,11.0,neutral or dissatisfied +30862,84870,Female,Loyal Customer,11,Personal Travel,Eco,547,4,2,4,3,5,4,5,5,1,3,4,4,4,5,4,0.0,neutral or dissatisfied +30863,73151,Male,disloyal Customer,35,Business travel,Business,1501,3,3,3,3,4,3,4,4,3,3,4,3,5,4,13,19.0,neutral or dissatisfied +30864,123602,Female,Loyal Customer,67,Personal Travel,Eco,1773,3,5,3,2,5,5,4,5,5,3,5,3,5,5,0,13.0,neutral or dissatisfied +30865,63595,Female,Loyal Customer,47,Business travel,Business,2133,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,1.0,satisfied +30866,15600,Male,disloyal Customer,38,Business travel,Eco,288,3,3,3,4,5,3,5,5,4,4,4,1,4,5,7,6.0,neutral or dissatisfied +30867,58783,Male,disloyal Customer,25,Business travel,Eco,1012,2,2,2,4,2,2,2,2,4,3,3,4,4,2,10,13.0,neutral or dissatisfied +30868,33435,Male,Loyal Customer,60,Business travel,Eco,2399,4,3,3,3,4,3,3,3,5,1,2,3,1,3,0,19.0,neutral or dissatisfied +30869,80056,Female,Loyal Customer,59,Personal Travel,Eco,950,4,3,4,5,4,1,1,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +30870,60409,Male,Loyal Customer,43,Personal Travel,Eco,1452,4,4,4,4,4,4,2,4,3,3,4,3,4,4,0,2.0,satisfied +30871,103940,Male,Loyal Customer,42,Business travel,Business,533,4,4,4,4,3,5,4,4,4,4,4,5,4,4,2,0.0,satisfied +30872,40126,Male,Loyal Customer,37,Personal Travel,Eco,422,2,5,3,1,2,3,4,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +30873,22492,Female,Loyal Customer,66,Personal Travel,Eco,238,2,2,2,3,5,3,4,2,2,2,2,2,2,1,0,10.0,neutral or dissatisfied +30874,47879,Female,Loyal Customer,55,Business travel,Business,2517,4,3,3,3,3,4,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +30875,40276,Male,Loyal Customer,51,Personal Travel,Eco,358,1,5,1,2,2,1,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +30876,92915,Female,disloyal Customer,39,Business travel,Eco,134,1,4,1,4,5,1,1,5,1,2,4,1,4,5,23,29.0,neutral or dissatisfied +30877,97061,Female,disloyal Customer,24,Business travel,Business,1390,5,0,5,1,4,5,4,4,4,4,5,4,4,4,34,19.0,satisfied +30878,117879,Female,Loyal Customer,29,Business travel,Business,3355,3,3,3,3,4,3,4,4,3,3,4,3,4,4,3,0.0,satisfied +30879,97102,Female,disloyal Customer,43,Business travel,Business,1642,2,2,2,1,4,2,4,4,5,3,5,5,4,4,10,21.0,neutral or dissatisfied +30880,107670,Female,Loyal Customer,49,Business travel,Business,1873,4,4,4,4,3,4,4,5,5,5,5,5,5,3,8,6.0,satisfied +30881,34379,Male,Loyal Customer,29,Business travel,Business,3775,2,2,2,2,4,4,4,4,4,1,3,1,5,4,9,0.0,satisfied +30882,73146,Female,Loyal Customer,41,Business travel,Business,2189,1,1,1,1,5,5,5,3,3,4,3,4,3,4,0,1.0,satisfied +30883,45506,Male,disloyal Customer,43,Business travel,Eco Plus,122,4,3,3,4,3,4,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +30884,27178,Female,Loyal Customer,66,Personal Travel,Eco,2681,1,4,1,3,1,2,2,3,1,3,5,2,4,2,0,0.0,neutral or dissatisfied +30885,126223,Male,Loyal Customer,49,Business travel,Eco,590,2,2,2,2,2,2,2,2,4,1,3,2,4,2,0,0.0,neutral or dissatisfied +30886,22595,Female,Loyal Customer,27,Business travel,Business,3658,2,4,5,4,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +30887,92572,Female,Loyal Customer,49,Business travel,Business,2139,1,1,1,1,2,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +30888,77709,Female,disloyal Customer,24,Business travel,Eco,874,2,2,2,3,5,2,5,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +30889,39947,Female,Loyal Customer,25,Personal Travel,Eco,1195,2,2,2,2,5,2,5,5,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +30890,57948,Male,Loyal Customer,25,Business travel,Business,1062,2,2,2,2,4,5,4,4,3,4,4,4,5,4,84,78.0,satisfied +30891,70251,Male,Loyal Customer,48,Business travel,Business,1592,4,1,1,1,4,2,3,4,4,4,4,1,4,3,10,0.0,neutral or dissatisfied +30892,113155,Female,Loyal Customer,21,Business travel,Business,628,4,4,4,4,5,5,5,5,3,4,5,5,4,5,0,5.0,satisfied +30893,87018,Female,Loyal Customer,58,Personal Travel,Eco Plus,907,1,2,1,4,5,3,4,5,5,1,5,1,5,4,0,1.0,neutral or dissatisfied +30894,32585,Female,Loyal Customer,31,Business travel,Business,1617,1,2,2,2,2,2,1,2,2,4,3,2,2,2,15,19.0,neutral or dissatisfied +30895,21005,Male,Loyal Customer,48,Business travel,Eco Plus,289,5,3,3,3,5,5,5,5,4,1,5,5,3,5,0,0.0,satisfied +30896,50003,Female,Loyal Customer,45,Business travel,Eco,109,4,2,2,2,2,2,5,4,4,4,4,4,4,1,3,1.0,satisfied +30897,33619,Female,Loyal Customer,22,Business travel,Eco,399,4,1,1,1,4,4,4,4,2,5,2,5,4,4,0,0.0,satisfied +30898,10287,Female,disloyal Customer,24,Business travel,Eco,316,2,4,2,2,5,2,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +30899,37037,Male,Loyal Customer,26,Business travel,Business,1777,3,3,3,3,4,5,4,4,4,5,5,2,2,4,0,0.0,satisfied +30900,97718,Male,Loyal Customer,49,Personal Travel,Eco Plus,942,2,5,2,2,4,2,1,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +30901,29492,Female,Loyal Customer,28,Business travel,Eco,1107,0,0,0,4,5,0,4,5,1,4,5,5,3,5,0,0.0,satisfied +30902,91267,Male,Loyal Customer,45,Personal Travel,Eco,270,3,0,3,4,2,3,2,2,5,2,4,5,5,2,10,7.0,neutral or dissatisfied +30903,72888,Female,Loyal Customer,45,Business travel,Business,3979,2,2,2,2,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +30904,29955,Female,disloyal Customer,17,Business travel,Eco,95,4,3,4,4,2,4,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +30905,119213,Female,disloyal Customer,52,Personal Travel,Eco,257,4,5,4,2,4,4,3,4,3,2,2,2,1,4,0,0.0,satisfied +30906,60036,Male,Loyal Customer,48,Business travel,Business,1564,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +30907,71793,Male,Loyal Customer,56,Business travel,Business,1744,1,1,1,1,2,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +30908,125640,Female,Loyal Customer,31,Business travel,Business,1670,3,3,3,3,5,4,5,5,3,3,4,3,4,5,0,0.0,satisfied +30909,22837,Female,Loyal Customer,33,Business travel,Business,2691,3,1,1,1,3,3,3,1,1,3,4,3,1,3,135,128.0,neutral or dissatisfied +30910,24429,Male,Loyal Customer,11,Personal Travel,Eco,634,4,4,4,4,1,4,1,1,3,2,4,3,4,1,0,4.0,satisfied +30911,50863,Male,Loyal Customer,18,Personal Travel,Eco,308,1,5,1,1,2,1,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +30912,36699,Male,Loyal Customer,38,Personal Travel,Eco,1121,4,4,4,1,3,4,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +30913,79769,Male,Loyal Customer,53,Business travel,Business,1005,3,2,2,2,3,2,2,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +30914,33346,Male,Loyal Customer,51,Business travel,Business,2556,2,2,2,2,1,5,1,5,5,5,5,3,5,1,1,0.0,satisfied +30915,44341,Male,Loyal Customer,58,Personal Travel,Eco,230,1,4,0,3,3,0,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +30916,52517,Female,Loyal Customer,63,Business travel,Business,119,1,1,1,1,2,2,2,5,5,5,5,5,5,5,61,55.0,satisfied +30917,70912,Female,Loyal Customer,31,Business travel,Business,1721,5,5,2,5,5,5,5,5,4,4,3,3,5,5,0,4.0,satisfied +30918,107553,Female,disloyal Customer,25,Business travel,Business,1521,5,5,5,3,5,4,4,5,4,5,4,4,5,4,315,302.0,satisfied +30919,33495,Male,Loyal Customer,46,Personal Travel,Eco,2496,1,3,1,5,5,1,1,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +30920,116791,Male,Loyal Customer,56,Personal Travel,Eco Plus,480,4,2,4,3,3,4,5,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +30921,106513,Male,disloyal Customer,22,Business travel,Eco,271,4,0,4,3,2,4,3,2,5,2,4,3,4,2,10,3.0,neutral or dissatisfied +30922,91037,Female,Loyal Customer,15,Personal Travel,Eco,406,3,1,3,3,2,3,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +30923,110771,Female,disloyal Customer,31,Business travel,Eco,1105,3,4,4,4,3,4,2,3,1,5,3,1,4,3,6,16.0,neutral or dissatisfied +30924,80908,Female,Loyal Customer,56,Business travel,Business,341,2,2,2,2,5,5,5,4,4,4,4,5,4,3,7,15.0,satisfied +30925,28590,Female,Loyal Customer,25,Personal Travel,Eco,2607,0,2,0,3,2,0,2,2,4,3,3,1,4,2,0,0.0,satisfied +30926,687,Male,Loyal Customer,32,Business travel,Business,282,3,3,5,3,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +30927,55111,Female,Loyal Customer,54,Personal Travel,Eco,1504,4,5,4,5,2,3,5,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +30928,61215,Male,Loyal Customer,55,Business travel,Eco,853,2,5,5,5,2,2,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +30929,85966,Male,disloyal Customer,42,Business travel,Business,432,1,1,1,4,3,1,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +30930,120447,Female,Loyal Customer,36,Personal Travel,Eco,366,4,4,4,3,3,4,3,3,4,2,3,1,4,3,0,15.0,neutral or dissatisfied +30931,81344,Male,Loyal Customer,24,Business travel,Business,1299,3,1,1,1,3,3,3,3,3,5,3,2,3,3,32,9.0,neutral or dissatisfied +30932,45870,Female,Loyal Customer,46,Business travel,Eco,563,5,4,4,4,5,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +30933,128952,Male,disloyal Customer,40,Business travel,Business,236,5,5,5,2,4,5,4,4,4,4,4,5,5,4,0,5.0,satisfied +30934,63338,Male,Loyal Customer,30,Business travel,Business,337,5,5,5,5,4,4,4,4,5,1,5,1,5,4,0,0.0,satisfied +30935,64923,Female,disloyal Customer,32,Business travel,Business,190,3,3,3,4,5,3,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +30936,66535,Female,Loyal Customer,34,Personal Travel,Eco,733,1,2,2,3,5,2,5,5,2,2,4,3,3,5,14,10.0,neutral or dissatisfied +30937,107681,Male,Loyal Customer,61,Business travel,Eco,251,1,1,1,1,1,1,1,1,2,1,3,4,3,1,32,32.0,neutral or dissatisfied +30938,91941,Female,Loyal Customer,37,Business travel,Business,2388,4,4,4,4,5,2,3,3,3,3,3,5,3,2,0,0.0,satisfied +30939,18822,Male,Loyal Customer,51,Business travel,Business,551,3,3,3,3,1,1,1,4,4,4,4,5,4,2,0,0.0,satisfied +30940,45677,Female,Loyal Customer,53,Business travel,Business,896,3,3,3,3,1,4,1,4,4,4,4,1,4,2,6,5.0,satisfied +30941,51805,Female,Loyal Customer,46,Personal Travel,Eco,751,1,2,2,2,5,2,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +30942,57720,Female,disloyal Customer,37,Business travel,Business,1754,3,3,3,2,2,3,1,2,3,2,3,3,4,2,67,62.0,neutral or dissatisfied +30943,104545,Male,Loyal Customer,35,Personal Travel,Eco,1047,3,5,3,1,5,3,5,5,4,3,4,4,5,5,0,2.0,neutral or dissatisfied +30944,117026,Female,Loyal Customer,44,Business travel,Eco,304,2,2,2,2,4,3,3,2,2,2,2,4,2,4,82,60.0,neutral or dissatisfied +30945,113310,Female,Loyal Customer,30,Business travel,Business,407,1,1,1,1,5,5,5,5,3,5,5,3,5,5,13,23.0,satisfied +30946,53577,Male,Loyal Customer,56,Personal Travel,Eco,1195,3,5,3,2,2,3,2,2,5,5,3,5,4,2,0,0.0,neutral or dissatisfied +30947,42902,Male,disloyal Customer,34,Business travel,Eco,200,1,4,1,3,3,1,3,3,4,5,3,3,4,3,0,0.0,neutral or dissatisfied +30948,61807,Female,Loyal Customer,63,Personal Travel,Eco,1346,3,5,3,1,4,4,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +30949,42657,Female,Loyal Customer,61,Personal Travel,Eco Plus,546,1,5,4,3,4,1,3,2,2,4,2,1,2,1,24,13.0,neutral or dissatisfied +30950,22829,Female,Loyal Customer,47,Business travel,Eco,170,4,1,1,1,3,1,3,4,4,4,4,4,4,3,0,0.0,satisfied +30951,29353,Male,Loyal Customer,44,Business travel,Business,2466,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +30952,99609,Male,Loyal Customer,69,Personal Travel,Eco Plus,930,1,2,1,4,2,1,2,2,2,3,3,3,4,2,9,11.0,neutral or dissatisfied +30953,29277,Male,disloyal Customer,35,Business travel,Eco,569,3,3,3,4,4,3,4,4,1,3,4,1,3,4,0,0.0,neutral or dissatisfied +30954,101421,Female,Loyal Customer,53,Business travel,Business,3882,3,3,3,3,2,5,5,4,4,4,4,5,4,5,40,36.0,satisfied +30955,22063,Female,disloyal Customer,18,Business travel,Eco,304,5,3,5,4,4,5,4,4,5,1,5,4,1,4,0,0.0,satisfied +30956,126439,Male,Loyal Customer,65,Personal Travel,Eco Plus,468,1,1,4,3,2,4,4,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +30957,86080,Male,Loyal Customer,46,Business travel,Business,3173,3,3,3,3,4,4,5,5,5,5,5,5,5,3,35,38.0,satisfied +30958,15944,Female,Loyal Customer,28,Personal Travel,Eco,723,1,2,1,4,4,1,1,4,2,1,3,3,4,4,0,0.0,neutral or dissatisfied +30959,99107,Female,disloyal Customer,26,Business travel,Eco,181,3,1,3,4,5,3,5,5,1,5,4,4,4,5,64,51.0,neutral or dissatisfied +30960,68182,Female,Loyal Customer,43,Personal Travel,Eco,603,3,5,3,3,4,5,4,1,1,3,1,5,1,4,43,34.0,neutral or dissatisfied +30961,128462,Male,Loyal Customer,17,Personal Travel,Eco,325,4,5,4,1,4,4,4,4,5,1,4,3,5,4,5,6.0,neutral or dissatisfied +30962,128171,Male,disloyal Customer,21,Business travel,Eco,1788,3,2,2,2,4,3,4,4,2,1,3,2,3,4,23,20.0,neutral or dissatisfied +30963,41458,Male,Loyal Customer,50,Personal Travel,Business,1334,4,4,3,1,4,5,5,1,1,3,1,3,1,4,5,0.0,satisfied +30964,25903,Female,disloyal Customer,22,Business travel,Eco Plus,907,5,0,5,3,5,5,5,5,2,2,3,4,1,5,1,7.0,satisfied +30965,73264,Female,disloyal Customer,30,Business travel,Eco Plus,675,1,1,1,4,4,1,4,4,1,1,3,2,4,4,24,22.0,neutral or dissatisfied +30966,56328,Male,Loyal Customer,41,Business travel,Business,2410,4,4,4,4,3,4,4,5,5,5,4,5,5,3,0,0.0,satisfied +30967,3310,Female,disloyal Customer,22,Business travel,Business,315,0,0,0,1,4,0,3,4,5,2,5,3,4,4,0,12.0,satisfied +30968,115905,Female,Loyal Customer,54,Business travel,Eco,337,1,2,2,2,5,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +30969,86416,Female,Loyal Customer,71,Business travel,Eco,760,4,4,4,4,2,4,3,4,4,4,4,4,4,1,16,4.0,neutral or dissatisfied +30970,90970,Male,disloyal Customer,59,Business travel,Eco,404,2,2,2,3,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +30971,41733,Male,disloyal Customer,19,Business travel,Eco,695,4,4,4,1,4,4,3,4,3,3,2,4,2,4,0,0.0,neutral or dissatisfied +30972,65272,Male,Loyal Customer,59,Personal Travel,Eco Plus,247,3,4,0,4,3,0,3,3,5,5,4,3,5,3,13,11.0,neutral or dissatisfied +30973,115955,Male,Loyal Customer,30,Personal Travel,Eco,362,0,5,0,1,2,0,3,2,3,5,4,5,4,2,0,0.0,satisfied +30974,1963,Male,Loyal Customer,26,Business travel,Business,383,4,4,4,4,4,5,4,4,5,4,5,5,2,4,0,0.0,satisfied +30975,68800,Female,Loyal Customer,31,Personal Travel,Eco,926,1,2,1,4,1,1,1,1,1,2,3,3,3,1,0,11.0,neutral or dissatisfied +30976,122810,Female,Loyal Customer,53,Personal Travel,Eco,599,4,5,4,2,2,2,4,4,4,4,1,5,4,2,0,19.0,neutral or dissatisfied +30977,31,Male,disloyal Customer,35,Business travel,Business,212,2,2,2,1,2,2,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +30978,127431,Male,Loyal Customer,55,Personal Travel,Eco,1009,3,4,3,4,1,3,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +30979,48436,Female,Loyal Customer,45,Business travel,Business,776,1,1,1,1,3,1,2,4,4,4,4,2,4,3,0,0.0,satisfied +30980,66981,Male,Loyal Customer,39,Business travel,Business,1713,2,2,2,2,5,4,5,4,4,4,4,4,4,5,7,0.0,satisfied +30981,36566,Female,Loyal Customer,50,Business travel,Eco,1121,2,2,2,2,2,4,3,1,1,2,1,2,1,3,0,7.0,neutral or dissatisfied +30982,103661,Female,Loyal Customer,72,Business travel,Eco,251,2,2,2,2,2,2,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +30983,83371,Male,Loyal Customer,28,Personal Travel,Eco,1124,3,5,3,2,2,3,4,2,3,5,3,5,5,2,6,0.0,neutral or dissatisfied +30984,10887,Female,disloyal Customer,39,Business travel,Business,316,4,4,4,2,4,4,4,4,4,5,4,4,5,4,0,2.0,satisfied +30985,129478,Female,disloyal Customer,29,Business travel,Eco,2704,1,1,1,4,1,1,1,1,4,5,2,2,3,1,15,7.0,neutral or dissatisfied +30986,4326,Female,Loyal Customer,33,Personal Travel,Eco,589,2,4,2,2,2,2,2,2,5,4,5,4,4,2,10,3.0,neutral or dissatisfied +30987,42600,Female,Loyal Customer,45,Business travel,Eco,866,4,5,5,5,1,5,3,4,4,4,4,1,4,1,32,36.0,satisfied +30988,85754,Female,Loyal Customer,23,Business travel,Business,526,5,5,5,5,4,4,4,4,5,2,4,5,4,4,4,6.0,satisfied +30989,53392,Male,Loyal Customer,56,Personal Travel,Eco Plus,1476,2,5,2,3,4,2,4,4,3,2,3,3,5,4,22,20.0,neutral or dissatisfied +30990,54813,Female,Loyal Customer,41,Business travel,Eco,862,4,2,2,2,4,4,4,4,4,5,1,2,1,4,4,0.0,satisfied +30991,44365,Female,Loyal Customer,22,Personal Travel,Eco,596,2,3,2,2,3,2,3,3,4,4,3,2,2,3,0,0.0,neutral or dissatisfied +30992,86460,Female,disloyal Customer,9,Business travel,Eco,762,2,2,2,2,3,2,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +30993,57035,Female,Loyal Customer,27,Business travel,Eco Plus,2454,0,0,0,3,5,0,5,5,5,2,2,4,4,5,5,0.0,satisfied +30994,53178,Female,Loyal Customer,22,Business travel,Business,3076,2,2,3,2,4,4,4,4,3,1,4,4,3,4,14,6.0,satisfied +30995,124534,Female,disloyal Customer,26,Business travel,Eco,1276,2,1,1,4,5,1,5,5,1,2,4,4,4,5,5,0.0,neutral or dissatisfied +30996,87426,Female,disloyal Customer,36,Business travel,Business,425,1,1,1,3,3,1,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +30997,49241,Female,Loyal Customer,62,Business travel,Business,1608,4,4,4,4,5,2,5,4,4,4,5,1,4,2,0,0.0,satisfied +30998,66313,Female,disloyal Customer,29,Business travel,Eco,852,3,3,3,3,4,3,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +30999,30768,Male,Loyal Customer,72,Business travel,Eco,936,2,3,3,3,2,2,2,3,3,3,3,2,3,2,81,135.0,neutral or dissatisfied +31000,16921,Male,Loyal Customer,13,Personal Travel,Business,820,1,4,1,5,5,1,5,5,3,5,2,2,5,5,0,0.0,neutral or dissatisfied +31001,51114,Male,Loyal Customer,48,Personal Travel,Eco,190,2,4,2,3,5,2,5,5,3,3,4,2,4,5,0,0.0,neutral or dissatisfied +31002,56612,Male,disloyal Customer,29,Business travel,Business,997,3,3,3,3,4,3,4,4,4,3,5,4,4,4,10,0.0,neutral or dissatisfied +31003,55866,Male,Loyal Customer,28,Business travel,Business,2968,2,2,2,2,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +31004,103947,Female,Loyal Customer,48,Business travel,Business,3790,3,5,5,5,4,2,3,3,3,3,3,2,3,1,25,25.0,neutral or dissatisfied +31005,77719,Female,Loyal Customer,22,Business travel,Business,1746,1,2,2,2,1,1,1,1,4,3,3,2,2,1,9,0.0,neutral or dissatisfied +31006,91854,Female,Loyal Customer,23,Personal Travel,Eco,1797,3,4,3,2,3,3,1,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +31007,117421,Male,Loyal Customer,39,Business travel,Business,1460,2,2,2,2,2,4,4,2,2,2,2,4,2,2,19,13.0,neutral or dissatisfied +31008,44724,Female,Loyal Customer,16,Personal Travel,Eco,67,3,5,3,1,5,3,5,5,4,5,5,5,4,5,18,14.0,neutral or dissatisfied +31009,101551,Female,Loyal Customer,43,Personal Travel,Eco,345,3,5,3,2,3,2,2,4,2,5,3,2,2,2,136,154.0,neutral or dissatisfied +31010,27421,Male,Loyal Customer,52,Business travel,Eco,978,3,2,2,2,3,3,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +31011,26836,Female,Loyal Customer,38,Business travel,Business,3033,3,4,4,4,2,3,4,3,3,3,3,3,3,4,0,2.0,neutral or dissatisfied +31012,18250,Female,Loyal Customer,56,Personal Travel,Eco,235,3,5,3,4,5,4,3,1,1,3,1,5,1,5,105,96.0,neutral or dissatisfied +31013,100799,Female,disloyal Customer,24,Business travel,Eco,348,3,1,3,3,3,3,3,3,3,5,3,1,3,3,11,27.0,neutral or dissatisfied +31014,93393,Female,Loyal Customer,58,Business travel,Business,723,5,5,5,5,4,4,4,4,2,5,4,4,5,4,401,404.0,satisfied +31015,15997,Female,Loyal Customer,54,Business travel,Eco,780,3,3,3,3,2,3,3,3,3,3,3,3,3,4,16,33.0,neutral or dissatisfied +31016,128242,Female,disloyal Customer,38,Business travel,Business,602,2,2,2,1,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +31017,113284,Male,Loyal Customer,56,Business travel,Business,414,2,2,2,2,5,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +31018,20877,Male,Loyal Customer,47,Business travel,Eco Plus,457,4,5,4,5,4,4,4,4,4,4,5,5,1,4,0,0.0,satisfied +31019,124620,Male,Loyal Customer,48,Business travel,Business,1671,1,5,5,5,4,3,3,1,1,1,1,1,1,2,0,10.0,neutral or dissatisfied +31020,3136,Male,Loyal Customer,49,Business travel,Business,140,0,4,0,2,5,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +31021,112643,Female,Loyal Customer,39,Business travel,Business,1756,2,2,2,2,2,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +31022,81153,Male,Loyal Customer,56,Business travel,Business,2899,5,5,5,5,3,5,4,5,5,5,5,4,5,4,3,0.0,satisfied +31023,98560,Male,disloyal Customer,22,Business travel,Eco,920,3,3,3,3,3,3,3,3,3,4,3,4,3,3,50,51.0,neutral or dissatisfied +31024,100671,Female,Loyal Customer,49,Business travel,Business,2986,4,1,4,4,3,5,5,5,5,5,5,3,5,3,37,39.0,satisfied +31025,7403,Male,Loyal Customer,55,Business travel,Business,2795,4,4,4,4,2,4,4,5,5,5,5,5,5,3,9,0.0,satisfied +31026,125018,Female,Loyal Customer,16,Personal Travel,Eco,184,1,5,1,2,4,1,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +31027,68465,Female,Loyal Customer,43,Business travel,Business,2043,3,3,3,3,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +31028,37921,Male,Loyal Customer,23,Personal Travel,Eco,1023,3,3,3,2,4,3,4,4,3,3,3,3,3,4,1,0.0,neutral or dissatisfied +31029,4390,Female,Loyal Customer,9,Personal Travel,Eco,473,1,5,1,4,5,1,5,5,4,3,1,4,4,5,16,12.0,neutral or dissatisfied +31030,80112,Male,Loyal Customer,28,Personal Travel,Eco,1626,2,2,2,4,5,2,5,5,4,2,3,2,3,5,120,125.0,neutral or dissatisfied +31031,18693,Female,Loyal Customer,59,Business travel,Eco Plus,253,2,3,3,3,1,5,4,2,2,2,2,3,2,3,0,10.0,satisfied +31032,81037,Male,Loyal Customer,36,Business travel,Business,1399,3,3,3,3,4,5,4,3,3,2,3,3,3,4,0,0.0,satisfied +31033,12090,Female,Loyal Customer,30,Business travel,Business,2584,2,2,5,2,2,2,2,2,3,4,3,4,3,2,76,87.0,neutral or dissatisfied +31034,124158,Female,Loyal Customer,44,Business travel,Business,2133,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +31035,127274,Female,Loyal Customer,26,Personal Travel,Eco,1020,3,5,3,5,4,3,4,4,2,2,1,1,2,4,0,8.0,neutral or dissatisfied +31036,96933,Male,Loyal Customer,47,Personal Travel,Eco Plus,957,1,5,2,3,3,2,2,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +31037,83434,Male,disloyal Customer,49,Business travel,Business,632,1,0,0,5,4,1,4,4,5,3,5,4,4,4,0,1.0,neutral or dissatisfied +31038,16117,Male,Loyal Customer,42,Business travel,Eco,799,5,1,1,1,5,5,5,5,2,1,3,5,4,5,11,26.0,satisfied +31039,82567,Male,disloyal Customer,26,Business travel,Business,528,0,0,0,4,4,0,4,4,5,3,4,3,5,4,0,0.0,satisfied +31040,58061,Female,Loyal Customer,42,Business travel,Business,2248,3,3,3,3,1,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +31041,52542,Female,Loyal Customer,63,Business travel,Eco,119,4,4,4,4,3,5,5,4,4,4,4,2,4,1,0,0.0,satisfied +31042,39812,Male,Loyal Customer,72,Business travel,Business,272,2,2,2,2,5,5,4,4,4,4,4,3,4,5,3,7.0,satisfied +31043,66446,Male,Loyal Customer,29,Business travel,Business,1857,1,1,1,1,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +31044,65046,Male,Loyal Customer,32,Personal Travel,Eco,247,2,5,2,4,2,2,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +31045,21430,Male,Loyal Customer,45,Business travel,Business,2989,3,3,3,3,4,4,4,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +31046,41166,Male,disloyal Customer,44,Business travel,Eco Plus,140,4,4,4,4,5,4,5,5,1,5,3,4,1,5,36,25.0,neutral or dissatisfied +31047,16902,Male,Loyal Customer,24,Personal Travel,Eco,746,1,5,2,4,4,2,4,4,5,3,4,4,5,4,4,0.0,neutral or dissatisfied +31048,113765,Male,Loyal Customer,9,Personal Travel,Eco,236,3,1,3,2,3,3,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +31049,105334,Male,Loyal Customer,55,Business travel,Business,452,3,3,2,3,3,5,5,4,4,4,4,4,4,5,12,7.0,satisfied +31050,123920,Male,Loyal Customer,40,Personal Travel,Eco,546,1,5,1,5,3,1,2,3,5,1,5,1,4,3,7,5.0,neutral or dissatisfied +31051,26003,Male,disloyal Customer,21,Business travel,Eco,425,2,5,2,3,5,2,5,5,5,4,5,5,4,5,0,2.0,neutral or dissatisfied +31052,11064,Male,Loyal Customer,16,Personal Travel,Eco,166,1,5,0,2,3,0,4,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +31053,75474,Female,Loyal Customer,49,Personal Travel,Eco,2218,3,4,4,4,5,4,3,3,3,4,2,1,3,4,0,0.0,neutral or dissatisfied +31054,84312,Male,Loyal Customer,62,Personal Travel,Eco Plus,235,2,4,2,5,1,2,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +31055,90771,Male,Loyal Customer,40,Business travel,Business,270,1,0,0,3,4,4,4,5,5,0,1,1,5,1,0,0.0,neutral or dissatisfied +31056,62476,Female,Loyal Customer,56,Business travel,Business,1846,3,3,3,3,2,4,5,3,3,3,3,3,3,4,28,3.0,satisfied +31057,83028,Male,Loyal Customer,40,Business travel,Business,2128,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,20.0,satisfied +31058,4095,Male,Loyal Customer,54,Business travel,Business,2872,3,3,3,3,5,5,4,4,4,4,4,5,4,5,0,53.0,satisfied +31059,31984,Female,Loyal Customer,49,Personal Travel,Business,101,4,5,4,2,5,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +31060,108803,Female,Loyal Customer,62,Personal Travel,Eco,406,3,5,3,3,2,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +31061,78262,Male,Loyal Customer,29,Business travel,Business,2085,3,1,1,1,3,3,3,3,4,3,4,4,3,3,0,0.0,neutral or dissatisfied +31062,104911,Female,Loyal Customer,38,Business travel,Business,1565,4,4,2,4,5,4,4,5,5,5,5,5,5,3,14,14.0,satisfied +31063,27778,Female,Loyal Customer,30,Business travel,Business,1448,4,4,4,4,4,4,4,4,1,5,4,2,1,4,0,0.0,satisfied +31064,126577,Female,Loyal Customer,49,Personal Travel,Eco,1558,3,2,3,2,1,3,3,1,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +31065,46109,Female,Loyal Customer,51,Business travel,Business,3353,3,3,3,3,2,5,4,4,4,4,4,4,4,4,57,62.0,satisfied +31066,53611,Male,Loyal Customer,25,Business travel,Eco,1874,5,1,1,1,5,5,5,5,4,2,4,5,3,5,1,0.0,satisfied +31067,79249,Female,Loyal Customer,47,Business travel,Business,1598,4,4,4,4,4,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +31068,112944,Female,Loyal Customer,63,Personal Travel,Eco,1242,4,3,3,4,3,3,4,5,5,3,5,1,5,4,35,32.0,neutral or dissatisfied +31069,105015,Female,Loyal Customer,47,Business travel,Business,2783,2,2,2,2,3,4,4,4,4,4,4,5,4,3,15,1.0,satisfied +31070,98230,Female,Loyal Customer,11,Business travel,Business,2666,2,3,3,3,2,2,2,2,3,2,3,4,4,2,50,52.0,neutral or dissatisfied +31071,18422,Female,Loyal Customer,38,Business travel,Business,3470,1,1,1,1,1,3,1,5,5,5,5,2,5,2,0,0.0,satisfied +31072,35449,Male,Loyal Customer,47,Personal Travel,Eco,1056,3,4,3,3,4,3,4,4,4,1,4,4,3,4,0,0.0,neutral or dissatisfied +31073,102855,Male,Loyal Customer,49,Personal Travel,Eco,423,2,2,2,3,5,2,5,5,1,1,4,1,4,5,0,2.0,neutral or dissatisfied +31074,56403,Male,Loyal Customer,40,Business travel,Business,1993,3,3,3,3,2,4,5,1,1,2,1,3,1,5,0,5.0,satisfied +31075,78359,Female,Loyal Customer,58,Business travel,Business,1927,3,3,3,3,4,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +31076,61815,Male,Loyal Customer,59,Personal Travel,Eco,1379,1,4,1,1,3,1,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +31077,30809,Male,disloyal Customer,39,Business travel,Eco,799,1,1,1,4,5,1,5,5,5,2,2,1,2,5,7,5.0,neutral or dissatisfied +31078,104371,Female,Loyal Customer,50,Business travel,Business,1509,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +31079,61486,Male,Loyal Customer,40,Business travel,Eco,2288,2,1,3,3,2,2,2,2,2,2,2,3,3,2,2,0.0,neutral or dissatisfied +31080,107835,Female,Loyal Customer,24,Personal Travel,Eco,349,3,4,3,3,3,3,3,3,5,2,5,4,5,3,8,2.0,neutral or dissatisfied +31081,28149,Female,Loyal Customer,52,Business travel,Eco,933,5,2,2,2,4,2,5,5,5,5,5,4,5,1,0,0.0,satisfied +31082,20127,Male,Loyal Customer,63,Personal Travel,Eco,416,2,2,2,4,1,2,1,1,1,5,4,2,4,1,125,121.0,neutral or dissatisfied +31083,46550,Female,Loyal Customer,31,Business travel,Business,3965,2,2,2,2,4,4,3,4,4,5,3,3,3,4,0,0.0,satisfied +31084,126112,Male,Loyal Customer,44,Business travel,Eco,507,1,0,0,4,1,1,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +31085,83648,Male,Loyal Customer,53,Business travel,Business,577,3,3,3,3,2,4,5,3,3,3,3,5,3,4,13,8.0,satisfied +31086,97835,Female,Loyal Customer,35,Personal Travel,Eco,395,5,5,2,2,2,2,2,2,3,5,4,3,5,2,0,4.0,satisfied +31087,82432,Female,Loyal Customer,43,Business travel,Business,1651,4,4,4,4,5,4,5,4,4,4,4,4,4,4,9,16.0,satisfied +31088,15933,Male,Loyal Customer,30,Business travel,Business,607,2,4,4,4,2,2,2,2,2,5,3,4,3,2,0,29.0,neutral or dissatisfied +31089,77082,Male,Loyal Customer,25,Personal Travel,Eco,991,2,4,2,4,3,2,3,3,4,2,4,3,4,3,25,17.0,neutral or dissatisfied +31090,51362,Male,Loyal Customer,75,Business travel,Eco Plus,262,4,1,5,1,4,4,4,4,4,1,3,1,3,4,0,0.0,satisfied +31091,53499,Female,Loyal Customer,26,Personal Travel,Eco,2419,3,2,3,3,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +31092,59573,Female,disloyal Customer,20,Business travel,Eco,965,1,0,0,2,2,0,2,2,4,4,5,5,4,2,35,34.0,neutral or dissatisfied +31093,101219,Male,Loyal Customer,14,Personal Travel,Eco,795,3,5,3,3,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +31094,94196,Male,Loyal Customer,48,Business travel,Business,323,4,4,4,4,2,5,5,4,4,4,4,4,4,5,4,3.0,satisfied +31095,23017,Male,Loyal Customer,61,Personal Travel,Eco Plus,528,3,4,3,1,4,3,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +31096,58717,Female,disloyal Customer,28,Business travel,Business,1182,4,4,4,3,1,4,1,1,5,4,4,5,5,1,11,6.0,neutral or dissatisfied +31097,29509,Female,Loyal Customer,22,Personal Travel,Eco,1216,3,0,3,4,4,3,4,4,5,1,1,2,4,4,0,0.0,neutral or dissatisfied +31098,79686,Female,Loyal Customer,57,Personal Travel,Eco,762,3,5,3,4,5,4,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +31099,67093,Female,Loyal Customer,26,Business travel,Business,1903,4,5,4,4,5,5,5,5,5,2,4,5,5,5,0,0.0,satisfied +31100,59102,Male,Loyal Customer,57,Personal Travel,Eco,1846,3,2,3,3,2,3,2,2,3,2,3,3,4,2,0,11.0,neutral or dissatisfied +31101,69295,Female,Loyal Customer,12,Personal Travel,Eco Plus,733,2,4,2,4,4,2,3,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +31102,100917,Female,Loyal Customer,60,Business travel,Business,2214,4,4,4,4,3,4,5,5,5,5,5,4,5,5,5,0.0,satisfied +31103,43291,Female,Loyal Customer,42,Business travel,Eco,387,4,1,1,1,5,5,1,4,4,4,4,3,4,3,0,4.0,satisfied +31104,117527,Male,Loyal Customer,47,Personal Travel,Business,347,3,5,3,1,4,4,4,4,4,3,4,3,4,4,15,12.0,neutral or dissatisfied +31105,40893,Female,Loyal Customer,33,Personal Travel,Eco,501,3,5,3,4,2,3,2,2,5,4,5,4,5,2,4,0.0,neutral or dissatisfied +31106,16445,Male,disloyal Customer,23,Business travel,Eco,416,5,3,5,3,2,5,2,2,1,2,4,1,3,2,0,0.0,satisfied +31107,62603,Male,Loyal Customer,26,Personal Travel,Eco,1744,3,3,3,3,2,3,2,2,4,3,2,4,4,2,5,0.0,neutral or dissatisfied +31108,22815,Male,Loyal Customer,45,Business travel,Business,1752,3,3,4,3,1,1,4,4,4,4,4,2,4,3,0,0.0,satisfied +31109,18511,Male,disloyal Customer,22,Business travel,Eco,190,4,0,3,1,5,3,5,5,1,2,1,3,5,5,0,0.0,satisfied +31110,91285,Female,Loyal Customer,52,Business travel,Business,223,1,1,1,1,5,5,5,4,4,4,5,4,4,3,4,0.0,satisfied +31111,23988,Male,Loyal Customer,30,Business travel,Business,427,1,1,1,1,5,5,5,5,1,1,2,1,4,5,0,0.0,satisfied +31112,52433,Male,Loyal Customer,24,Personal Travel,Eco,370,3,0,3,3,5,3,5,5,5,2,5,5,4,5,72,57.0,neutral or dissatisfied +31113,117148,Male,Loyal Customer,24,Personal Travel,Eco,370,1,2,1,3,5,1,5,5,3,3,3,4,4,5,40,37.0,neutral or dissatisfied +31114,115834,Female,Loyal Customer,45,Business travel,Business,2898,4,1,1,1,5,4,4,4,4,4,4,2,4,2,47,34.0,neutral or dissatisfied +31115,30482,Female,Loyal Customer,31,Personal Travel,Eco,1201,3,2,3,1,2,3,1,2,2,4,2,2,2,2,99,92.0,neutral or dissatisfied +31116,129620,Female,Loyal Customer,26,Business travel,Business,1788,2,2,1,2,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +31117,108227,Male,disloyal Customer,24,Business travel,Business,895,0,5,0,4,3,0,3,3,5,2,4,5,4,3,0,0.0,satisfied +31118,37942,Male,Loyal Customer,35,Business travel,Eco Plus,937,4,4,4,4,4,4,4,4,1,3,4,1,3,4,0,0.0,satisfied +31119,102556,Male,Loyal Customer,42,Personal Travel,Eco,236,2,5,2,3,3,2,4,3,1,3,2,2,2,3,47,56.0,neutral or dissatisfied +31120,31991,Male,Loyal Customer,11,Personal Travel,Business,102,1,4,1,1,5,1,5,5,3,1,5,1,2,5,0,0.0,neutral or dissatisfied +31121,33751,Male,Loyal Customer,58,Business travel,Eco,266,5,3,5,3,5,5,5,5,3,1,1,4,2,5,0,0.0,satisfied +31122,8852,Female,disloyal Customer,23,Business travel,Business,622,5,0,5,3,2,5,4,2,3,4,5,3,4,2,56,72.0,satisfied +31123,26623,Female,Loyal Customer,52,Business travel,Eco,515,5,2,2,2,4,2,3,5,5,5,5,3,5,5,4,6.0,satisfied +31124,127593,Male,Loyal Customer,41,Business travel,Business,1773,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,8.0,satisfied +31125,75588,Female,Loyal Customer,40,Business travel,Business,3312,5,5,2,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +31126,6228,Female,Loyal Customer,57,Business travel,Business,1942,1,1,1,1,3,4,4,4,4,4,4,5,4,4,22,5.0,satisfied +31127,65951,Male,Loyal Customer,51,Business travel,Business,1372,5,5,5,5,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +31128,71579,Male,disloyal Customer,23,Business travel,Eco,1012,5,5,5,4,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +31129,58530,Female,Loyal Customer,31,Personal Travel,Eco,719,1,5,1,1,5,1,5,5,4,5,5,4,5,5,3,0.0,neutral or dissatisfied +31130,84709,Female,Loyal Customer,49,Business travel,Business,1791,3,3,3,3,5,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +31131,95043,Female,Loyal Customer,15,Personal Travel,Eco,248,1,4,1,1,5,1,5,5,4,2,5,4,4,5,18,12.0,neutral or dissatisfied +31132,48611,Male,Loyal Customer,39,Business travel,Eco Plus,964,4,5,5,5,4,4,4,4,3,3,3,2,5,4,96,95.0,satisfied +31133,36847,Female,Loyal Customer,21,Personal Travel,Eco,369,3,1,3,3,4,3,4,4,2,5,3,1,2,4,48,45.0,neutral or dissatisfied +31134,110439,Female,Loyal Customer,9,Personal Travel,Eco,919,1,2,1,3,2,1,2,2,3,5,4,1,4,2,42,46.0,neutral or dissatisfied +31135,11667,Female,Loyal Customer,35,Business travel,Business,3725,1,2,2,2,1,2,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +31136,112697,Male,Loyal Customer,39,Business travel,Business,697,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +31137,53570,Female,disloyal Customer,24,Business travel,Eco,1195,3,3,3,4,1,3,1,1,3,4,4,1,3,1,10,0.0,neutral or dissatisfied +31138,89601,Male,Loyal Customer,31,Business travel,Business,2690,4,4,4,4,3,3,3,3,5,3,5,5,5,3,11,2.0,satisfied +31139,86956,Female,Loyal Customer,39,Business travel,Business,2541,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +31140,111091,Male,Loyal Customer,49,Personal Travel,Eco,197,2,1,2,3,5,2,5,5,2,2,3,4,2,5,25,30.0,neutral or dissatisfied +31141,32025,Female,Loyal Customer,58,Business travel,Business,102,2,2,2,2,4,3,4,5,5,5,4,5,5,4,0,0.0,satisfied +31142,128473,Female,Loyal Customer,51,Personal Travel,Eco,646,3,1,3,3,1,3,2,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +31143,121570,Female,Loyal Customer,55,Business travel,Business,1095,4,4,4,4,5,5,5,5,5,5,5,5,5,3,0,5.0,satisfied +31144,41196,Male,Loyal Customer,29,Business travel,Business,3334,3,3,3,3,3,3,3,3,3,2,3,4,4,3,21,25.0,neutral or dissatisfied +31145,106482,Male,Loyal Customer,18,Personal Travel,Eco,1624,3,2,3,4,4,3,5,4,1,3,3,3,4,4,5,0.0,neutral or dissatisfied +31146,63541,Male,Loyal Customer,52,Personal Travel,Eco,1009,5,5,5,5,4,5,4,4,4,2,4,5,4,4,0,0.0,satisfied +31147,37669,Male,Loyal Customer,59,Personal Travel,Eco,950,3,3,3,3,3,4,4,2,4,4,4,4,2,4,134,129.0,neutral or dissatisfied +31148,99122,Male,Loyal Customer,28,Personal Travel,Eco,237,2,5,2,4,1,2,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +31149,26405,Male,Loyal Customer,16,Personal Travel,Eco,957,5,3,4,3,4,4,4,4,1,2,3,2,2,4,4,0.0,satisfied +31150,26811,Male,Loyal Customer,58,Personal Travel,Eco Plus,2139,2,5,2,3,4,2,4,4,4,3,5,5,4,4,17,3.0,neutral or dissatisfied +31151,58948,Male,Loyal Customer,9,Personal Travel,Eco Plus,888,3,2,4,4,1,4,1,1,3,1,3,1,4,1,0,0.0,neutral or dissatisfied +31152,86327,Female,disloyal Customer,28,Business travel,Business,749,3,2,2,3,2,2,2,2,4,4,4,2,4,2,0,11.0,neutral or dissatisfied +31153,99845,Female,disloyal Customer,39,Business travel,Eco,468,2,1,2,4,5,2,5,5,2,5,3,1,4,5,1,4.0,neutral or dissatisfied +31154,20810,Male,Loyal Customer,23,Business travel,Business,357,1,5,5,5,1,1,1,1,1,3,3,2,3,1,27,23.0,neutral or dissatisfied +31155,112159,Female,disloyal Customer,25,Business travel,Eco,895,1,1,1,4,3,1,3,3,2,4,4,1,3,3,0,2.0,neutral or dissatisfied +31156,109448,Male,Loyal Customer,49,Business travel,Business,834,2,2,2,2,4,4,5,4,4,4,4,4,4,3,23,5.0,satisfied +31157,242,Male,disloyal Customer,38,Business travel,Business,719,4,4,4,5,1,4,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +31158,49240,Female,Loyal Customer,32,Business travel,Business,3276,0,5,0,2,2,2,2,2,1,4,1,5,2,2,0,0.0,satisfied +31159,110851,Female,Loyal Customer,37,Business travel,Business,2894,3,3,3,3,4,4,5,4,4,4,4,4,4,3,21,28.0,satisfied +31160,55724,Male,Loyal Customer,32,Business travel,Business,1700,5,5,5,5,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +31161,84153,Male,Loyal Customer,8,Personal Travel,Eco,1355,0,1,0,4,3,0,3,3,3,5,2,4,4,3,0,0.0,satisfied +31162,22573,Male,disloyal Customer,40,Business travel,Eco,300,4,4,3,4,4,3,4,4,3,2,2,2,4,4,0,7.0,neutral or dissatisfied +31163,28253,Male,Loyal Customer,33,Business travel,Business,1542,1,1,1,1,4,4,4,4,3,5,1,2,4,4,0,0.0,satisfied +31164,65508,Male,Loyal Customer,48,Personal Travel,Eco Plus,1303,2,2,2,4,5,2,5,5,4,3,3,2,4,5,0,1.0,neutral or dissatisfied +31165,51961,Female,Loyal Customer,27,Business travel,Business,3209,2,3,5,3,2,2,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +31166,26579,Male,Loyal Customer,21,Business travel,Business,545,1,1,3,1,5,5,5,5,2,2,2,4,4,5,0,0.0,satisfied +31167,123704,Female,Loyal Customer,17,Personal Travel,Eco,214,1,3,1,3,4,1,4,4,4,4,3,3,3,4,0,0.0,neutral or dissatisfied +31168,14793,Female,Loyal Customer,8,Personal Travel,Eco Plus,622,2,4,2,3,1,2,2,1,5,4,4,3,4,1,7,0.0,neutral or dissatisfied +31169,122875,Female,Loyal Customer,68,Personal Travel,Eco,226,4,4,4,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +31170,89312,Female,Loyal Customer,47,Personal Travel,Eco Plus,453,3,4,3,3,2,5,5,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +31171,79595,Male,Loyal Customer,44,Business travel,Business,760,3,3,3,3,5,5,4,4,4,4,4,4,4,5,8,0.0,satisfied +31172,124170,Female,Loyal Customer,23,Personal Travel,Eco,2133,1,2,1,3,3,1,3,3,2,3,1,4,3,3,0,0.0,neutral or dissatisfied +31173,42680,Female,Loyal Customer,28,Business travel,Business,1581,4,4,4,4,4,4,4,4,4,4,1,1,3,4,0,0.0,satisfied +31174,110469,Female,Loyal Customer,67,Personal Travel,Eco,798,1,2,1,4,4,3,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +31175,51015,Female,Loyal Customer,58,Personal Travel,Eco,86,2,4,2,1,5,4,4,3,3,2,4,3,3,5,0,4.0,neutral or dissatisfied +31176,52494,Male,disloyal Customer,26,Business travel,Business,160,1,4,1,2,1,1,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +31177,105263,Male,Loyal Customer,78,Business travel,Business,1775,5,5,5,5,3,1,2,5,5,5,5,3,5,5,0,19.0,satisfied +31178,76521,Female,Loyal Customer,46,Business travel,Business,3281,3,3,5,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +31179,31633,Male,Loyal Customer,49,Business travel,Business,1691,5,5,5,5,1,1,4,5,5,5,5,4,5,3,0,0.0,satisfied +31180,58157,Male,Loyal Customer,54,Business travel,Business,1896,5,5,5,5,2,5,4,3,3,4,3,4,3,4,29,25.0,satisfied +31181,96330,Male,Loyal Customer,49,Business travel,Business,359,3,3,3,3,4,5,5,5,5,5,5,4,5,3,16,0.0,satisfied +31182,119283,Male,Loyal Customer,44,Business travel,Business,214,3,3,3,3,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +31183,64673,Female,Loyal Customer,46,Business travel,Business,2749,3,3,4,3,5,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +31184,100377,Female,Loyal Customer,12,Personal Travel,Eco,971,1,2,1,4,3,1,5,3,1,5,4,4,3,3,11,0.0,neutral or dissatisfied +31185,80884,Male,disloyal Customer,44,Business travel,Business,692,4,4,4,2,1,4,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +31186,53241,Male,Loyal Customer,36,Personal Travel,Eco,589,3,3,3,3,3,3,2,3,4,5,3,4,3,3,19,25.0,neutral or dissatisfied +31187,19592,Male,Loyal Customer,52,Personal Travel,Eco,173,3,2,3,4,5,3,5,5,1,2,3,1,4,5,0,0.0,neutral or dissatisfied +31188,76456,Male,Loyal Customer,51,Business travel,Business,481,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +31189,63988,Male,Loyal Customer,46,Business travel,Business,2583,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +31190,115437,Female,Loyal Customer,41,Business travel,Business,1731,0,0,0,5,5,5,4,2,2,2,2,4,2,5,24,6.0,satisfied +31191,21863,Female,Loyal Customer,61,Business travel,Eco,500,4,2,2,2,2,2,5,4,4,4,4,1,4,3,28,13.0,satisfied +31192,50257,Male,Loyal Customer,46,Business travel,Eco,134,1,3,3,3,1,1,1,1,4,2,3,3,4,1,0,0.0,neutral or dissatisfied +31193,105664,Female,Loyal Customer,40,Business travel,Business,925,5,5,5,5,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +31194,126640,Female,Loyal Customer,60,Business travel,Business,602,1,2,2,2,4,3,4,1,1,1,1,4,1,2,0,18.0,neutral or dissatisfied +31195,62906,Male,Loyal Customer,16,Personal Travel,Business,862,2,4,2,4,3,2,1,3,4,5,5,5,5,3,100,82.0,neutral or dissatisfied +31196,53898,Female,Loyal Customer,66,Personal Travel,Eco,191,1,4,0,3,2,2,1,4,4,0,5,3,4,2,4,8.0,neutral or dissatisfied +31197,44451,Male,Loyal Customer,53,Personal Travel,Eco,1203,4,4,4,2,1,4,1,1,4,5,1,4,5,1,50,39.0,neutral or dissatisfied +31198,53386,Female,Loyal Customer,54,Personal Travel,Eco,1452,1,2,1,4,1,4,4,4,5,3,3,4,1,4,162,156.0,neutral or dissatisfied +31199,127995,Female,Loyal Customer,33,Business travel,Business,1488,2,1,4,1,3,1,2,2,2,2,2,2,2,3,0,6.0,neutral or dissatisfied +31200,123076,Female,Loyal Customer,59,Business travel,Business,631,5,5,3,5,5,5,5,4,4,4,4,5,4,4,22,26.0,satisfied +31201,6284,Female,Loyal Customer,56,Personal Travel,Eco,585,2,4,1,1,3,4,4,1,1,1,1,4,1,5,86,109.0,neutral or dissatisfied +31202,8754,Female,disloyal Customer,23,Business travel,Eco,1147,4,4,4,4,5,4,5,5,5,5,4,3,5,5,0,0.0,satisfied +31203,74647,Male,Loyal Customer,7,Personal Travel,Eco,1464,4,4,4,3,1,4,1,1,4,5,4,1,3,1,8,0.0,neutral or dissatisfied +31204,49075,Male,Loyal Customer,35,Business travel,Business,209,2,2,2,2,1,1,2,5,5,5,5,5,5,4,1,1.0,satisfied +31205,15477,Female,Loyal Customer,32,Personal Travel,Eco,399,1,4,1,4,1,1,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +31206,129848,Female,Loyal Customer,56,Personal Travel,Eco,337,2,5,2,4,2,4,4,4,5,4,4,4,5,4,236,255.0,neutral or dissatisfied +31207,72918,Male,Loyal Customer,21,Business travel,Business,1834,5,5,5,5,3,3,3,3,4,4,5,4,5,3,0,2.0,satisfied +31208,81679,Female,Loyal Customer,23,Business travel,Business,907,1,4,4,4,1,1,1,4,2,4,4,1,2,1,187,177.0,neutral or dissatisfied +31209,94845,Female,Loyal Customer,63,Business travel,Eco,319,3,4,4,4,1,2,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +31210,9298,Male,Loyal Customer,39,Business travel,Business,2734,3,3,3,3,2,4,4,5,5,5,5,5,5,3,4,0.0,satisfied +31211,116070,Male,Loyal Customer,66,Personal Travel,Eco,358,2,1,2,3,4,2,4,4,3,1,2,1,2,4,0,0.0,neutral or dissatisfied +31212,112012,Female,Loyal Customer,18,Personal Travel,Business,680,4,5,4,3,2,4,2,2,4,5,5,5,4,2,11,5.0,satisfied +31213,109043,Male,Loyal Customer,40,Business travel,Eco,488,2,3,3,3,2,3,2,2,1,5,2,3,3,2,0,0.0,neutral or dissatisfied +31214,28815,Female,disloyal Customer,41,Business travel,Eco,605,2,5,2,3,1,2,1,1,5,2,1,4,2,1,0,8.0,neutral or dissatisfied +31215,8083,Male,Loyal Customer,60,Business travel,Business,2610,0,0,0,3,5,5,4,2,2,2,2,3,2,4,0,1.0,satisfied +31216,22646,Male,Loyal Customer,25,Personal Travel,Eco,300,3,4,3,1,5,3,5,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +31217,24593,Female,Loyal Customer,28,Business travel,Business,526,3,3,3,3,4,4,4,4,2,5,4,4,4,4,0,0.0,satisfied +31218,22519,Male,disloyal Customer,22,Business travel,Eco Plus,143,4,1,3,4,3,3,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +31219,47304,Female,Loyal Customer,23,Business travel,Business,2816,2,2,2,2,5,5,5,5,2,1,3,2,2,5,0,0.0,satisfied +31220,23209,Male,Loyal Customer,51,Business travel,Business,1594,3,2,2,2,5,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +31221,71021,Male,Loyal Customer,54,Business travel,Eco,802,2,2,2,2,2,2,2,2,3,3,2,2,3,2,3,0.0,neutral or dissatisfied +31222,19849,Male,disloyal Customer,30,Business travel,Eco,693,3,3,3,4,4,3,5,4,2,5,4,3,2,4,0,0.0,neutral or dissatisfied +31223,31731,Female,Loyal Customer,13,Personal Travel,Eco,862,2,4,2,3,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +31224,34014,Female,Loyal Customer,13,Personal Travel,Eco,1576,3,5,3,5,2,3,2,2,5,2,5,3,5,2,33,27.0,neutral or dissatisfied +31225,67127,Male,disloyal Customer,28,Business travel,Business,1121,4,4,4,3,2,4,2,2,5,4,4,5,4,2,3,0.0,satisfied +31226,104078,Female,disloyal Customer,10,Personal Travel,Eco,359,2,5,2,2,1,2,1,1,5,1,4,1,2,1,13,5.0,neutral or dissatisfied +31227,72281,Female,Loyal Customer,75,Business travel,Business,519,5,4,5,5,5,5,1,5,5,5,5,1,5,5,0,0.0,satisfied +31228,20103,Female,Loyal Customer,43,Business travel,Business,416,4,4,4,4,5,5,2,5,5,5,5,5,5,2,52,40.0,satisfied +31229,23552,Female,Loyal Customer,40,Business travel,Eco,637,5,5,4,5,5,5,5,5,3,1,2,1,5,5,7,1.0,satisfied +31230,12789,Male,disloyal Customer,32,Business travel,Eco,489,1,4,1,1,1,1,4,3,4,5,1,4,3,4,157,154.0,neutral or dissatisfied +31231,95729,Female,disloyal Customer,72,Business travel,Eco,181,2,2,2,1,3,2,3,3,2,5,1,3,2,3,4,2.0,neutral or dissatisfied +31232,67910,Female,Loyal Customer,10,Personal Travel,Eco,1464,2,4,1,3,1,1,1,1,4,5,3,2,3,1,3,0.0,neutral or dissatisfied +31233,7382,Female,Loyal Customer,12,Business travel,Business,3322,5,4,4,4,5,4,5,5,4,3,3,1,4,5,38,39.0,neutral or dissatisfied +31234,112702,Female,Loyal Customer,48,Business travel,Business,2401,1,2,1,1,1,3,3,1,1,2,1,2,1,3,12,0.0,neutral or dissatisfied +31235,82139,Female,Loyal Customer,57,Business travel,Business,1678,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +31236,98942,Female,disloyal Customer,8,Business travel,Business,569,1,2,1,4,3,1,3,3,4,5,3,4,3,3,87,95.0,neutral or dissatisfied +31237,71071,Male,Loyal Customer,10,Personal Travel,Eco,802,1,4,1,3,5,1,5,5,3,4,4,3,2,5,7,10.0,neutral or dissatisfied +31238,64607,Male,disloyal Customer,50,Business travel,Business,190,3,3,3,4,2,3,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +31239,33189,Female,Loyal Customer,56,Business travel,Eco Plus,102,4,3,5,3,5,3,3,4,4,4,4,2,4,1,10,8.0,satisfied +31240,22633,Male,Loyal Customer,57,Personal Travel,Eco,300,1,4,1,1,2,1,2,2,5,5,4,5,4,2,9,5.0,neutral or dissatisfied +31241,59859,Male,Loyal Customer,58,Business travel,Business,1023,4,4,4,4,5,4,5,5,5,5,5,3,5,3,18,0.0,satisfied +31242,123505,Female,disloyal Customer,24,Business travel,Eco,625,2,1,2,3,5,2,3,5,2,4,3,2,3,5,36,35.0,neutral or dissatisfied +31243,20312,Female,Loyal Customer,36,Business travel,Eco,900,5,4,4,4,5,5,5,5,2,5,4,4,5,5,88,62.0,satisfied +31244,81087,Female,Loyal Customer,64,Personal Travel,Eco,931,2,5,2,3,3,4,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +31245,98454,Male,Loyal Customer,41,Business travel,Business,3892,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +31246,10293,Female,Loyal Customer,55,Business travel,Business,3504,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +31247,6772,Female,Loyal Customer,55,Business travel,Business,137,0,5,1,1,3,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +31248,65182,Male,Loyal Customer,25,Personal Travel,Eco,190,2,5,2,3,5,2,1,5,5,4,4,3,4,5,4,0.0,neutral or dissatisfied +31249,66980,Male,Loyal Customer,41,Business travel,Business,2003,4,4,4,4,3,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +31250,77375,Female,Loyal Customer,49,Business travel,Business,590,3,5,3,3,5,4,4,5,5,5,5,3,5,5,0,1.0,satisfied +31251,83887,Male,Loyal Customer,14,Personal Travel,Eco,1670,1,5,1,3,2,1,2,2,5,1,5,1,4,2,0,3.0,neutral or dissatisfied +31252,125385,Female,disloyal Customer,37,Business travel,Business,1440,3,4,4,2,1,4,1,1,3,2,5,5,5,1,0,2.0,neutral or dissatisfied +31253,17466,Male,Loyal Customer,48,Business travel,Business,3481,2,2,2,2,3,5,4,5,5,5,5,5,5,5,44,35.0,satisfied +31254,57344,Male,Loyal Customer,51,Business travel,Business,3913,2,1,1,1,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +31255,93191,Male,Loyal Customer,50,Business travel,Business,2353,1,1,1,1,5,5,5,4,4,4,4,5,4,3,2,50.0,satisfied +31256,128778,Male,Loyal Customer,30,Business travel,Business,2248,3,3,3,3,5,5,5,5,3,5,4,3,4,5,29,11.0,satisfied +31257,106517,Male,Loyal Customer,45,Business travel,Business,271,2,2,4,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +31258,90193,Male,Loyal Customer,9,Personal Travel,Eco,983,1,5,2,2,1,2,1,1,3,2,5,4,4,1,60,51.0,neutral or dissatisfied +31259,50875,Female,Loyal Customer,35,Personal Travel,Eco,158,1,4,0,4,5,0,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +31260,69318,Male,Loyal Customer,59,Business travel,Business,1805,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +31261,80778,Male,Loyal Customer,30,Business travel,Business,2212,4,4,4,4,5,5,5,5,5,4,5,3,4,5,0,0.0,satisfied +31262,53846,Female,Loyal Customer,57,Business travel,Business,2940,2,1,4,4,1,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +31263,113967,Male,Loyal Customer,31,Business travel,Business,1844,5,5,5,5,5,5,5,5,5,2,3,4,5,5,1,0.0,satisfied +31264,68927,Male,Loyal Customer,49,Personal Travel,Eco Plus,1061,3,5,2,3,5,2,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +31265,12723,Male,Loyal Customer,56,Business travel,Eco,803,4,5,5,5,4,4,4,4,1,5,4,2,4,4,0,0.0,satisfied +31266,48134,Male,Loyal Customer,39,Business travel,Business,1679,4,1,4,4,1,5,4,5,5,5,4,2,5,1,0,0.0,satisfied +31267,52438,Male,Loyal Customer,36,Personal Travel,Eco,451,2,4,2,5,4,2,4,4,3,2,4,3,5,4,57,52.0,neutral or dissatisfied +31268,79712,Female,Loyal Customer,15,Personal Travel,Eco,762,3,5,3,3,1,3,1,1,5,2,5,3,3,1,0,0.0,neutral or dissatisfied +31269,100139,Male,Loyal Customer,29,Business travel,Business,3309,3,2,2,2,3,3,3,1,5,4,3,3,1,3,294,278.0,neutral or dissatisfied +31270,30541,Male,Loyal Customer,29,Business travel,Eco Plus,701,0,0,0,2,5,0,5,5,1,2,1,2,2,5,0,0.0,satisfied +31271,20912,Female,Loyal Customer,23,Business travel,Business,1646,2,2,2,2,5,5,5,5,1,4,1,1,5,5,0,0.0,satisfied +31272,35745,Male,Loyal Customer,28,Business travel,Eco Plus,2153,2,2,2,2,2,2,2,2,3,4,2,4,3,2,0,0.0,neutral or dissatisfied +31273,93984,Female,Loyal Customer,35,Personal Travel,Eco,1315,0,5,0,1,4,0,4,4,5,4,4,5,4,4,0,19.0,satisfied +31274,65749,Female,Loyal Customer,33,Personal Travel,Eco,1061,2,5,2,3,2,2,2,2,4,4,5,4,4,2,7,0.0,neutral or dissatisfied +31275,127526,Male,disloyal Customer,24,Business travel,Eco,1009,2,2,2,2,5,2,5,5,5,3,4,3,4,5,34,43.0,neutral or dissatisfied +31276,50774,Female,Loyal Customer,51,Personal Travel,Eco,308,2,1,4,2,2,2,2,5,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +31277,76540,Female,Loyal Customer,38,Business travel,Business,516,5,5,3,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +31278,32482,Male,disloyal Customer,80,Business travel,Eco,163,3,1,3,3,4,3,4,4,2,1,3,1,3,4,2,3.0,neutral or dissatisfied +31279,13234,Female,Loyal Customer,43,Business travel,Business,1614,3,3,3,3,2,3,3,4,4,4,4,3,4,4,0,48.0,satisfied +31280,116120,Female,Loyal Customer,39,Personal Travel,Eco,342,2,2,2,2,4,2,1,4,3,4,2,3,2,4,0,0.0,neutral or dissatisfied +31281,108975,Male,Loyal Customer,49,Business travel,Business,2055,4,4,4,4,3,4,5,4,4,4,4,4,4,4,112,102.0,satisfied +31282,21886,Female,Loyal Customer,43,Business travel,Business,2949,3,2,2,2,3,3,2,3,3,3,3,3,3,2,28,13.0,neutral or dissatisfied +31283,100741,Female,Loyal Customer,39,Personal Travel,Eco,328,0,4,0,4,1,0,5,1,4,4,2,3,2,1,12,0.0,satisfied +31284,96753,Female,Loyal Customer,57,Business travel,Business,781,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +31285,85924,Male,Loyal Customer,62,Business travel,Eco Plus,674,2,5,5,5,2,2,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +31286,72542,Female,disloyal Customer,40,Business travel,Business,964,2,2,2,4,4,2,4,4,1,4,4,4,3,4,0,0.0,neutral or dissatisfied +31287,60568,Female,Loyal Customer,62,Personal Travel,Business,1290,4,1,3,2,5,1,3,3,3,3,3,3,3,2,0,0.0,satisfied +31288,49214,Female,Loyal Customer,33,Business travel,Eco,86,5,2,4,2,5,5,5,5,4,1,1,3,3,5,0,0.0,satisfied +31289,74196,Male,Loyal Customer,67,Personal Travel,Eco,592,1,3,1,5,1,1,1,1,4,5,2,4,3,1,18,4.0,neutral or dissatisfied +31290,72829,Male,Loyal Customer,48,Business travel,Business,2636,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +31291,21420,Male,Loyal Customer,51,Business travel,Eco,433,5,2,2,2,5,5,5,5,2,4,3,1,1,5,11,10.0,satisfied +31292,78734,Female,Loyal Customer,58,Business travel,Business,447,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +31293,8300,Female,Loyal Customer,35,Business travel,Business,2063,2,2,2,2,4,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +31294,120288,Male,Loyal Customer,24,Personal Travel,Eco,1576,4,4,4,1,2,4,5,2,3,3,3,3,5,2,0,12.0,neutral or dissatisfied +31295,95905,Male,Loyal Customer,28,Personal Travel,Eco,580,3,1,2,4,2,2,2,2,4,2,4,2,4,2,7,12.0,neutral or dissatisfied +31296,107089,Female,disloyal Customer,24,Business travel,Eco,562,1,0,1,1,4,1,4,4,3,5,5,4,5,4,12,10.0,neutral or dissatisfied +31297,43823,Male,Loyal Customer,52,Business travel,Eco,144,4,3,3,3,4,4,4,4,5,4,4,4,4,4,0,42.0,satisfied +31298,96704,Female,Loyal Customer,40,Business travel,Eco,696,1,4,4,4,1,1,1,1,1,1,3,3,2,1,0,15.0,neutral or dissatisfied +31299,36722,Male,Loyal Customer,35,Personal Travel,Eco Plus,1121,1,4,1,4,2,1,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +31300,74718,Male,Loyal Customer,50,Personal Travel,Eco,1205,5,3,5,4,2,5,3,2,2,3,4,1,3,2,21,4.0,satisfied +31301,122832,Female,Loyal Customer,49,Business travel,Eco Plus,599,2,2,2,2,3,4,4,2,2,2,2,1,2,3,18,77.0,neutral or dissatisfied +31302,4080,Female,disloyal Customer,40,Business travel,Business,427,2,2,2,3,2,2,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +31303,74428,Female,Loyal Customer,39,Business travel,Business,1464,4,4,5,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +31304,101534,Female,Loyal Customer,50,Personal Travel,Eco,345,3,4,3,3,5,3,3,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +31305,89041,Female,Loyal Customer,53,Business travel,Business,2092,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,9.0,satisfied +31306,103900,Male,Loyal Customer,30,Business travel,Eco Plus,882,4,1,1,1,4,4,4,4,3,5,3,2,2,4,48,52.0,neutral or dissatisfied +31307,66273,Female,Loyal Customer,41,Business travel,Business,2688,3,3,5,3,5,4,5,4,4,4,4,5,4,3,4,0.0,satisfied +31308,59998,Male,Loyal Customer,17,Personal Travel,Eco,937,2,5,2,3,2,2,2,2,4,4,2,4,3,2,0,0.0,neutral or dissatisfied +31309,59294,Female,Loyal Customer,59,Business travel,Business,2556,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +31310,89588,Female,Loyal Customer,47,Business travel,Business,2339,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +31311,5478,Female,Loyal Customer,42,Business travel,Eco Plus,265,2,3,3,3,2,2,2,2,3,3,3,2,3,2,215,189.0,neutral or dissatisfied +31312,43750,Male,Loyal Customer,43,Business travel,Eco,481,4,1,1,1,4,4,4,4,2,3,1,1,3,4,0,0.0,satisfied +31313,115359,Female,Loyal Customer,38,Business travel,Business,446,3,3,5,3,3,4,5,4,4,4,4,3,4,4,4,5.0,satisfied +31314,94860,Female,disloyal Customer,25,Business travel,Eco,248,2,0,2,3,4,2,4,4,1,1,4,3,4,4,0,0.0,neutral or dissatisfied +31315,53458,Male,Loyal Customer,44,Business travel,Business,2288,2,2,2,2,4,3,3,5,5,4,5,2,5,4,0,0.0,satisfied +31316,128697,Male,Loyal Customer,41,Business travel,Business,2923,3,3,3,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +31317,73613,Male,Loyal Customer,55,Business travel,Business,1539,4,4,4,4,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +31318,123032,Female,Loyal Customer,46,Business travel,Business,631,5,5,5,5,2,5,4,5,5,5,5,4,5,4,6,0.0,satisfied +31319,106591,Male,Loyal Customer,54,Business travel,Business,333,4,4,4,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +31320,71529,Male,disloyal Customer,21,Business travel,Eco,1197,5,5,5,1,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +31321,7031,Female,Loyal Customer,22,Personal Travel,Eco,234,1,5,1,4,4,1,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +31322,81096,Male,disloyal Customer,21,Business travel,Eco,931,3,3,3,3,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +31323,76256,Female,Loyal Customer,54,Business travel,Eco Plus,1399,4,1,1,1,2,3,3,4,4,4,4,1,4,4,34,21.0,neutral or dissatisfied +31324,94179,Female,Loyal Customer,50,Business travel,Business,248,3,3,3,3,4,5,5,5,5,5,5,5,5,3,57,48.0,satisfied +31325,110560,Male,Loyal Customer,55,Business travel,Business,488,3,4,3,3,4,5,4,4,4,4,4,3,4,5,11,15.0,satisfied +31326,60560,Female,Loyal Customer,19,Business travel,Eco Plus,985,3,3,3,3,3,3,2,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +31327,100865,Female,disloyal Customer,14,Business travel,Eco,702,4,4,4,3,1,4,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +31328,48735,Female,Loyal Customer,46,Business travel,Business,372,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,1.0,satisfied +31329,11298,Male,Loyal Customer,56,Personal Travel,Eco,191,1,5,1,3,2,1,2,2,5,2,5,5,1,2,16,6.0,neutral or dissatisfied +31330,36907,Female,Loyal Customer,53,Personal Travel,Eco,2072,2,2,3,3,1,2,2,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +31331,59469,Female,Loyal Customer,43,Business travel,Business,811,3,3,2,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +31332,90155,Female,Loyal Customer,74,Business travel,Eco,557,5,5,5,5,1,1,4,5,5,5,5,3,5,1,0,0.0,satisfied +31333,84080,Female,Loyal Customer,56,Business travel,Business,373,2,2,2,2,2,5,2,2,2,2,2,3,2,2,0,0.0,satisfied +31334,116159,Male,Loyal Customer,53,Personal Travel,Eco,371,2,4,2,3,3,2,3,3,3,2,3,3,4,3,20,8.0,neutral or dissatisfied +31335,98055,Female,Loyal Customer,70,Personal Travel,Eco,1751,3,2,3,1,5,1,1,3,3,3,1,2,3,4,0,15.0,neutral or dissatisfied +31336,78098,Female,disloyal Customer,33,Business travel,Business,684,3,3,3,3,1,3,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +31337,45337,Male,disloyal Customer,30,Business travel,Eco,188,1,3,1,3,3,1,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +31338,37494,Male,Loyal Customer,63,Business travel,Eco,1069,4,1,1,1,4,4,4,4,5,1,2,4,1,4,0,0.0,satisfied +31339,55342,Female,Loyal Customer,29,Personal Travel,Eco,1117,2,5,2,3,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +31340,2007,Male,Loyal Customer,66,Personal Travel,Eco Plus,351,2,5,2,2,1,2,1,1,4,4,4,5,4,1,0,1.0,neutral or dissatisfied +31341,51590,Female,Loyal Customer,54,Business travel,Eco,370,5,5,5,5,1,4,4,5,5,5,5,1,5,1,0,0.0,satisfied +31342,125795,Female,Loyal Customer,27,Business travel,Business,2903,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +31343,84578,Male,Loyal Customer,59,Personal Travel,Eco,1572,2,4,2,1,4,2,1,4,4,2,3,5,5,4,11,23.0,neutral or dissatisfied +31344,11773,Male,Loyal Customer,15,Personal Travel,Eco,429,3,1,4,2,4,4,4,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +31345,94097,Male,Loyal Customer,9,Personal Travel,Business,248,2,4,0,4,5,0,5,5,5,2,4,4,5,5,25,27.0,neutral or dissatisfied +31346,1528,Female,disloyal Customer,38,Business travel,Business,862,3,3,3,4,4,3,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +31347,10776,Female,disloyal Customer,22,Business travel,Business,140,4,3,4,2,5,4,5,5,1,5,3,2,2,5,0,0.0,neutral or dissatisfied +31348,76904,Female,Loyal Customer,30,Personal Travel,Eco,630,2,3,2,5,1,2,1,1,3,2,4,1,3,1,3,1.0,neutral or dissatisfied +31349,106080,Male,Loyal Customer,59,Business travel,Business,436,2,2,2,2,3,5,4,5,5,5,5,4,5,5,47,37.0,satisfied +31350,30114,Female,Loyal Customer,55,Personal Travel,Eco,571,2,5,2,2,4,4,5,4,4,2,4,3,4,4,7,5.0,neutral or dissatisfied +31351,93220,Male,Loyal Customer,55,Business travel,Business,1460,4,4,4,4,4,4,5,4,4,4,4,4,4,4,18,4.0,satisfied +31352,123262,Female,Loyal Customer,63,Personal Travel,Eco,590,1,4,1,4,5,5,4,4,4,1,4,3,4,5,47,29.0,neutral or dissatisfied +31353,46432,Male,Loyal Customer,44,Business travel,Eco Plus,458,3,1,1,1,3,3,3,3,4,2,2,1,2,3,106,98.0,neutral or dissatisfied +31354,113219,Female,disloyal Customer,48,Business travel,Business,236,1,1,1,4,4,1,4,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +31355,35761,Female,Loyal Customer,36,Business travel,Business,200,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +31356,118485,Male,Loyal Customer,48,Business travel,Business,2384,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +31357,87081,Female,Loyal Customer,71,Business travel,Business,2289,3,2,2,2,5,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +31358,106459,Male,Loyal Customer,24,Business travel,Eco Plus,1670,2,1,1,1,2,2,4,2,3,5,3,3,4,2,0,3.0,neutral or dissatisfied +31359,66551,Female,disloyal Customer,33,Business travel,Business,328,4,4,4,1,4,4,4,4,5,5,4,5,4,4,2,1.0,neutral or dissatisfied +31360,89469,Male,Loyal Customer,51,Business travel,Business,134,4,4,4,4,5,5,4,5,5,5,4,4,5,4,0,4.0,satisfied +31361,105065,Male,disloyal Customer,21,Business travel,Eco,289,3,4,2,1,3,2,3,3,3,4,4,5,4,3,44,76.0,neutral or dissatisfied +31362,55745,Male,Loyal Customer,56,Business travel,Business,1737,1,1,1,1,4,3,5,5,5,5,5,5,5,4,17,20.0,satisfied +31363,66438,Female,Loyal Customer,38,Business travel,Business,1217,5,5,5,5,5,5,5,4,4,4,4,5,4,4,30,17.0,satisfied +31364,24116,Male,Loyal Customer,11,Business travel,Business,3427,3,1,1,1,3,2,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +31365,121750,Female,Loyal Customer,41,Business travel,Business,1509,2,2,2,2,4,5,4,5,5,5,5,3,5,4,107,104.0,satisfied +31366,24609,Male,disloyal Customer,28,Business travel,Eco,666,4,2,4,2,3,4,3,3,3,5,3,2,3,3,0,45.0,neutral or dissatisfied +31367,65731,Female,disloyal Customer,60,Business travel,Eco,1061,2,2,2,3,5,2,1,5,3,3,4,3,3,5,10,5.0,neutral or dissatisfied +31368,20806,Male,Loyal Customer,41,Business travel,Business,2257,5,5,5,5,2,1,1,2,2,2,2,1,2,3,0,0.0,satisfied +31369,98117,Female,Loyal Customer,41,Business travel,Business,3877,4,4,4,4,5,5,5,3,3,5,5,5,5,5,222,243.0,satisfied +31370,54759,Male,Loyal Customer,25,Business travel,Eco Plus,787,1,1,1,1,1,2,2,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +31371,48786,Female,Loyal Customer,53,Business travel,Business,2532,1,3,3,3,2,2,2,1,1,2,1,3,1,1,91,79.0,neutral or dissatisfied +31372,98042,Female,Loyal Customer,52,Business travel,Business,1797,1,1,1,1,2,5,4,4,4,4,4,3,4,5,3,0.0,satisfied +31373,34203,Male,Loyal Customer,37,Personal Travel,Eco,1179,2,4,2,4,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +31374,94378,Male,Loyal Customer,40,Business travel,Business,189,1,1,1,1,4,5,5,3,3,4,4,5,3,3,12,7.0,satisfied +31375,63693,Male,Loyal Customer,35,Business travel,Eco,853,2,2,2,2,2,1,2,2,3,2,3,4,4,2,0,15.0,neutral or dissatisfied +31376,93694,Female,disloyal Customer,45,Business travel,Business,1452,2,2,2,4,4,2,4,4,4,3,4,3,5,4,13,0.0,neutral or dissatisfied +31377,14960,Female,Loyal Customer,68,Personal Travel,Eco,554,3,5,3,2,3,5,4,4,4,3,4,3,4,4,1,0.0,neutral or dissatisfied +31378,34816,Female,Loyal Customer,31,Personal Travel,Eco,264,3,4,3,3,5,3,4,5,4,3,2,2,4,5,0,0.0,neutral or dissatisfied +31379,116016,Female,Loyal Customer,70,Personal Travel,Eco,296,3,5,3,2,3,4,5,4,4,3,4,3,4,5,47,47.0,neutral or dissatisfied +31380,129193,Female,disloyal Customer,20,Business travel,Business,1063,5,5,4,5,2,4,2,2,5,2,3,4,4,2,0,0.0,satisfied +31381,25149,Female,Loyal Customer,17,Business travel,Business,1866,1,1,1,1,5,5,5,5,1,5,2,4,4,5,0,0.0,satisfied +31382,97682,Male,Loyal Customer,30,Personal Travel,Eco,491,3,1,3,3,4,3,4,4,4,1,3,3,3,4,6,8.0,neutral or dissatisfied +31383,117686,Female,disloyal Customer,25,Business travel,Business,1059,0,1,0,3,3,1,4,3,5,5,5,5,4,3,0,0.0,satisfied +31384,122686,Male,Loyal Customer,62,Business travel,Eco,361,4,2,2,2,4,4,4,4,3,4,5,1,3,4,2,0.0,satisfied +31385,80308,Male,disloyal Customer,32,Business travel,Business,746,3,3,3,5,4,3,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +31386,17187,Female,Loyal Customer,10,Personal Travel,Eco,643,4,5,4,2,2,4,1,2,4,2,4,3,4,2,0,0.0,satisfied +31387,16411,Male,Loyal Customer,64,Personal Travel,Eco Plus,533,5,2,5,2,3,5,3,3,3,4,3,4,3,3,0,0.0,satisfied +31388,125006,Female,Loyal Customer,39,Business travel,Business,3937,1,1,1,1,5,2,5,4,4,4,3,5,4,2,68,105.0,satisfied +31389,36390,Female,Loyal Customer,36,Business travel,Business,2381,2,2,3,2,4,4,4,3,3,5,5,4,3,4,4,3.0,satisfied +31390,124656,Female,Loyal Customer,36,Business travel,Business,399,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,46.0,satisfied +31391,88000,Female,disloyal Customer,26,Business travel,Eco,404,2,2,2,4,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +31392,3182,Male,Loyal Customer,28,Business travel,Business,3482,2,2,1,2,4,4,4,4,5,2,5,3,4,4,0,56.0,satisfied +31393,18177,Female,Loyal Customer,55,Business travel,Business,179,0,4,0,4,5,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +31394,40792,Male,Loyal Customer,46,Business travel,Eco,588,4,1,5,5,4,4,4,4,4,4,1,5,1,4,0,0.0,satisfied +31395,89470,Female,Loyal Customer,20,Business travel,Eco Plus,151,1,3,3,3,1,1,4,1,2,1,4,2,4,1,0,17.0,neutral or dissatisfied +31396,79103,Male,Loyal Customer,70,Personal Travel,Eco,356,4,5,4,3,1,4,1,1,4,2,5,5,5,1,0,0.0,satisfied +31397,66427,Female,Loyal Customer,14,Personal Travel,Eco,1562,3,4,3,4,2,3,2,2,3,5,3,5,4,2,11,5.0,neutral or dissatisfied +31398,43170,Female,Loyal Customer,34,Business travel,Business,781,1,1,1,1,1,1,4,4,4,4,4,2,4,1,0,0.0,satisfied +31399,46504,Female,Loyal Customer,31,Business travel,Business,141,1,1,4,1,4,4,4,4,4,1,1,5,4,4,0,0.0,satisfied +31400,125483,Female,Loyal Customer,50,Personal Travel,Eco,2845,3,0,3,4,1,3,2,3,3,3,5,3,3,3,110,75.0,neutral or dissatisfied +31401,16869,Male,Loyal Customer,36,Business travel,Business,746,3,3,3,3,4,5,5,2,2,2,2,1,2,5,20,56.0,satisfied +31402,28635,Female,disloyal Customer,17,Business travel,Eco,1276,3,3,3,3,2,3,2,2,1,2,4,4,4,2,0,0.0,neutral or dissatisfied +31403,70775,Female,Loyal Customer,41,Business travel,Business,328,2,2,2,2,2,5,5,4,4,4,4,5,4,4,2,0.0,satisfied +31404,98602,Male,Loyal Customer,33,Business travel,Business,3581,2,2,2,2,2,2,2,2,2,5,2,1,2,2,11,11.0,neutral or dissatisfied +31405,10831,Female,Loyal Customer,36,Business travel,Business,2504,3,2,3,3,2,1,1,3,3,3,3,2,3,4,68,61.0,neutral or dissatisfied +31406,102065,Female,Loyal Customer,51,Personal Travel,Business,397,3,5,3,3,2,2,1,2,2,3,2,1,2,4,9,0.0,neutral or dissatisfied +31407,109941,Male,Loyal Customer,70,Personal Travel,Eco,971,5,4,5,4,4,5,4,4,5,4,5,5,4,4,4,0.0,satisfied +31408,97162,Female,Loyal Customer,23,Personal Travel,Eco,1642,4,5,4,3,5,4,2,5,3,2,5,4,4,5,6,14.0,neutral or dissatisfied +31409,94262,Male,Loyal Customer,30,Business travel,Business,239,5,5,5,5,4,4,4,4,3,3,5,5,5,4,5,10.0,satisfied +31410,128591,Male,Loyal Customer,22,Business travel,Business,2552,1,1,1,1,5,5,5,5,1,2,4,2,1,5,0,0.0,satisfied +31411,99682,Female,Loyal Customer,50,Business travel,Eco,442,2,4,4,4,1,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +31412,65798,Male,disloyal Customer,35,Business travel,Business,1389,3,3,3,3,2,3,2,2,3,4,5,5,4,2,32,31.0,neutral or dissatisfied +31413,122318,Female,disloyal Customer,25,Business travel,Business,544,3,4,3,4,3,3,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +31414,129623,Female,Loyal Customer,56,Business travel,Business,3517,3,3,3,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +31415,88094,Male,Loyal Customer,27,Business travel,Business,515,1,1,1,1,4,4,4,4,3,4,4,3,4,4,0,8.0,satisfied +31416,75887,Female,Loyal Customer,32,Business travel,Business,597,3,1,1,1,3,3,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +31417,57266,Female,disloyal Customer,39,Business travel,Business,628,2,2,2,4,4,2,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +31418,102462,Female,Loyal Customer,32,Personal Travel,Eco,397,1,5,4,2,2,4,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +31419,29729,Male,disloyal Customer,63,Business travel,Eco Plus,1297,4,4,4,2,4,2,2,1,1,4,4,2,4,2,0,19.0,satisfied +31420,21015,Male,Loyal Customer,13,Personal Travel,Business,106,3,1,3,3,2,3,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +31421,116178,Female,Loyal Customer,11,Personal Travel,Eco,404,2,5,2,2,2,2,2,2,5,2,4,4,4,2,10,8.0,neutral or dissatisfied +31422,111218,Male,Loyal Customer,50,Business travel,Business,1506,3,3,5,3,4,5,5,4,4,4,4,3,4,3,3,3.0,satisfied +31423,100125,Male,Loyal Customer,57,Business travel,Business,1763,1,1,1,1,3,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +31424,76939,Female,disloyal Customer,20,Business travel,Eco,874,1,1,1,4,5,1,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +31425,85458,Female,Loyal Customer,60,Business travel,Eco,332,4,3,3,3,1,4,4,4,4,4,4,1,4,2,54,53.0,neutral or dissatisfied +31426,118667,Female,disloyal Customer,20,Business travel,Eco,338,1,3,1,3,3,1,3,3,2,1,4,4,4,3,1,0.0,neutral or dissatisfied +31427,5598,Male,Loyal Customer,41,Business travel,Business,2358,3,3,3,3,5,5,5,4,4,4,4,3,4,5,14,0.0,satisfied +31428,94672,Male,Loyal Customer,46,Business travel,Eco,319,2,3,3,3,2,2,2,2,3,5,4,2,4,2,9,14.0,neutral or dissatisfied +31429,78842,Male,Loyal Customer,48,Personal Travel,Eco,447,2,4,2,4,5,2,5,5,5,3,2,3,3,5,0,0.0,neutral or dissatisfied +31430,107800,Female,Loyal Customer,48,Business travel,Business,2927,4,4,4,4,2,5,5,5,5,5,5,4,5,5,17,1.0,satisfied +31431,61777,Male,Loyal Customer,14,Personal Travel,Eco,1379,1,4,1,3,5,1,5,5,5,4,4,4,2,5,2,0.0,neutral or dissatisfied +31432,57497,Female,Loyal Customer,61,Business travel,Business,2787,2,2,4,2,5,4,5,4,4,4,4,3,4,4,81,73.0,satisfied +31433,36321,Male,Loyal Customer,42,Business travel,Eco,187,3,2,2,2,3,3,3,3,1,4,2,2,3,3,0,14.0,neutral or dissatisfied +31434,27364,Male,Loyal Customer,51,Business travel,Eco,978,4,3,3,3,4,4,4,4,5,2,2,1,3,4,0,0.0,satisfied +31435,13138,Female,Loyal Customer,56,Personal Travel,Eco,427,1,0,1,4,5,4,5,3,3,1,3,4,3,3,98,104.0,neutral or dissatisfied +31436,6261,Male,disloyal Customer,51,Business travel,Business,585,3,3,3,5,3,3,3,3,3,2,4,3,4,3,21,49.0,neutral or dissatisfied +31437,42220,Female,Loyal Customer,56,Business travel,Eco,329,3,2,2,2,4,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +31438,30426,Male,Loyal Customer,52,Personal Travel,Eco,1014,4,4,4,3,4,4,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +31439,70425,Male,Loyal Customer,40,Business travel,Business,3595,5,5,5,5,3,5,5,5,5,5,4,4,5,3,1,0.0,satisfied +31440,47644,Male,Loyal Customer,29,Business travel,Business,1211,2,2,2,2,2,2,2,2,2,3,4,1,4,2,27,23.0,neutral or dissatisfied +31441,80035,Female,Loyal Customer,33,Personal Travel,Eco,1080,4,4,4,3,3,4,3,3,3,3,5,5,4,3,1,0.0,satisfied +31442,67621,Female,disloyal Customer,22,Business travel,Business,1235,5,0,5,2,4,0,4,4,3,3,4,5,4,4,0,0.0,satisfied +31443,104229,Female,Loyal Customer,44,Personal Travel,Eco,680,1,5,1,1,4,5,5,3,3,1,3,4,3,3,6,0.0,neutral or dissatisfied +31444,76358,Female,Loyal Customer,40,Business travel,Business,1851,5,5,5,5,4,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +31445,95584,Female,Loyal Customer,60,Business travel,Business,1883,1,1,2,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +31446,87786,Female,disloyal Customer,24,Business travel,Business,214,5,5,5,1,4,5,4,4,5,3,5,4,4,4,10,0.0,satisfied +31447,58988,Female,disloyal Customer,50,Business travel,Business,1846,3,3,3,4,4,3,4,4,4,4,3,4,5,4,15,11.0,neutral or dissatisfied +31448,61255,Male,Loyal Customer,59,Personal Travel,Eco,948,3,2,3,3,4,3,4,4,4,4,1,1,3,4,25,15.0,neutral or dissatisfied +31449,63755,Male,Loyal Customer,25,Business travel,Eco Plus,1660,3,5,5,5,3,2,1,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +31450,38255,Female,Loyal Customer,36,Business travel,Business,3155,2,2,2,2,1,5,2,5,5,5,5,5,5,2,0,0.0,satisfied +31451,58796,Male,Loyal Customer,53,Business travel,Business,2455,5,5,3,5,4,4,4,4,3,4,3,4,5,4,170,175.0,satisfied +31452,17749,Female,Loyal Customer,31,Personal Travel,Eco,405,0,4,0,3,1,0,1,1,4,3,5,3,5,1,1,0.0,satisfied +31453,11998,Male,Loyal Customer,53,Personal Travel,Eco,643,2,5,3,3,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +31454,27774,Male,disloyal Customer,48,Business travel,Eco,722,3,3,3,4,3,3,1,3,5,2,4,2,5,3,0,0.0,neutral or dissatisfied +31455,89272,Male,Loyal Customer,57,Business travel,Business,2030,2,2,2,2,4,4,5,3,3,4,3,4,3,4,0,3.0,satisfied +31456,33950,Female,Loyal Customer,12,Personal Travel,Eco,1072,2,4,2,4,4,2,2,4,1,5,1,5,1,4,0,0.0,neutral or dissatisfied +31457,3144,Male,Loyal Customer,60,Business travel,Business,140,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +31458,112770,Female,disloyal Customer,39,Business travel,Eco,188,3,2,3,3,5,3,2,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +31459,109716,Female,Loyal Customer,35,Business travel,Business,2714,3,3,3,3,1,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +31460,39434,Male,Loyal Customer,46,Business travel,Eco,129,2,3,3,3,2,2,2,2,1,5,3,3,4,2,8,15.0,neutral or dissatisfied +31461,17956,Female,Loyal Customer,60,Business travel,Eco,501,3,2,2,2,2,3,3,3,3,3,3,1,3,4,12,7.0,neutral or dissatisfied +31462,827,Male,Loyal Customer,43,Business travel,Business,3120,3,3,3,3,5,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +31463,67988,Male,Loyal Customer,41,Personal Travel,Eco Plus,1171,5,5,5,5,1,5,2,1,1,5,4,1,4,1,11,3.0,satisfied +31464,40171,Female,Loyal Customer,67,Business travel,Eco,463,4,1,5,5,1,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +31465,16693,Male,Loyal Customer,33,Business travel,Business,2791,4,2,4,4,4,4,4,4,5,2,4,2,4,4,0,0.0,satisfied +31466,116961,Male,Loyal Customer,58,Business travel,Business,370,5,5,5,5,5,5,4,4,4,4,4,3,4,5,16,7.0,satisfied +31467,111124,Female,disloyal Customer,54,Business travel,Business,1111,2,2,2,3,2,2,2,2,4,5,5,5,5,2,38,36.0,neutral or dissatisfied +31468,60508,Female,Loyal Customer,26,Personal Travel,Eco,862,3,4,3,4,4,3,1,4,5,5,4,4,5,4,106,85.0,neutral or dissatisfied +31469,123139,Female,Loyal Customer,51,Business travel,Business,2464,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,5.0,satisfied +31470,107133,Male,Loyal Customer,57,Business travel,Business,842,4,4,2,4,5,5,5,2,2,2,2,3,2,5,6,0.0,satisfied +31471,55675,Male,Loyal Customer,32,Business travel,Business,2000,3,3,3,3,2,2,2,2,5,5,5,3,4,2,0,0.0,satisfied +31472,106029,Male,Loyal Customer,62,Personal Travel,Eco,682,2,2,2,4,4,2,4,4,3,3,4,2,3,4,3,5.0,neutral or dissatisfied +31473,13589,Male,Loyal Customer,61,Personal Travel,Eco,227,1,5,1,2,5,1,4,5,2,2,2,1,3,5,0,2.0,neutral or dissatisfied +31474,4001,Male,Loyal Customer,53,Business travel,Business,419,1,1,1,1,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +31475,59329,Male,Loyal Customer,51,Business travel,Business,2367,4,4,4,4,2,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +31476,16427,Male,Loyal Customer,54,Business travel,Eco,529,4,3,3,3,4,4,4,4,3,5,3,4,5,4,0,0.0,satisfied +31477,61130,Male,disloyal Customer,37,Business travel,Business,509,1,1,1,3,3,1,3,3,3,3,4,4,4,3,4,0.0,neutral or dissatisfied +31478,28992,Male,disloyal Customer,28,Business travel,Eco,1050,3,3,3,2,4,3,4,4,1,2,2,3,3,4,22,32.0,neutral or dissatisfied +31479,36238,Male,disloyal Customer,36,Business travel,Business,280,2,2,2,4,1,2,1,1,1,1,2,3,3,1,0,0.0,neutral or dissatisfied +31480,102539,Female,Loyal Customer,24,Personal Travel,Eco,236,3,3,3,3,3,3,3,3,5,1,4,2,4,3,42,20.0,neutral or dissatisfied +31481,74039,Male,Loyal Customer,44,Business travel,Business,3913,4,4,4,4,4,5,5,5,5,5,5,5,5,3,0,34.0,satisfied +31482,73111,Female,Loyal Customer,57,Business travel,Business,2174,1,1,1,1,2,4,5,4,4,4,4,3,4,4,4,0.0,satisfied +31483,72655,Male,Loyal Customer,15,Personal Travel,Eco,918,3,5,3,4,5,3,5,5,5,5,5,3,5,5,13,12.0,neutral or dissatisfied +31484,76043,Male,Loyal Customer,60,Business travel,Business,669,3,3,3,3,5,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +31485,8198,Male,Loyal Customer,38,Business travel,Eco,335,3,4,4,4,3,3,3,3,4,1,4,3,3,3,43,45.0,neutral or dissatisfied +31486,10232,Female,Loyal Customer,48,Business travel,Business,301,5,5,5,5,2,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +31487,123574,Male,Loyal Customer,44,Business travel,Business,1773,1,3,3,3,3,2,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +31488,126190,Female,Loyal Customer,9,Business travel,Business,2537,2,3,3,3,2,2,2,2,2,2,3,1,3,2,5,14.0,neutral or dissatisfied +31489,87856,Female,Loyal Customer,46,Personal Travel,Eco,214,2,0,2,3,4,5,5,3,3,2,3,5,3,2,15,13.0,neutral or dissatisfied +31490,1046,Male,disloyal Customer,37,Business travel,Eco,134,3,1,3,3,4,3,4,4,1,2,3,2,4,4,93,98.0,neutral or dissatisfied +31491,78519,Female,Loyal Customer,61,Personal Travel,Eco,666,3,2,3,3,5,4,4,1,1,3,1,3,1,1,0,13.0,neutral or dissatisfied +31492,84403,Female,disloyal Customer,18,Business travel,Eco,606,1,4,1,4,1,4,4,4,1,3,4,4,3,4,127,165.0,neutral or dissatisfied +31493,128828,Male,Loyal Customer,31,Business travel,Business,2475,1,1,1,1,5,5,5,3,2,3,5,5,3,5,0,0.0,satisfied +31494,78665,Male,Loyal Customer,52,Business travel,Business,761,3,3,2,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +31495,117806,Female,Loyal Customer,25,Business travel,Business,328,3,4,4,4,3,3,3,3,1,5,2,3,1,3,15,15.0,neutral or dissatisfied +31496,102610,Female,disloyal Customer,38,Business travel,Business,386,3,3,3,3,4,3,4,4,4,4,5,4,5,4,0,5.0,neutral or dissatisfied +31497,57671,Female,Loyal Customer,43,Personal Travel,Eco Plus,200,5,0,0,1,4,4,4,2,2,0,2,3,2,5,2,1.0,satisfied +31498,82548,Male,Loyal Customer,63,Personal Travel,Eco,629,3,4,3,2,3,3,3,3,3,5,5,3,5,3,183,181.0,neutral or dissatisfied +31499,77923,Female,Loyal Customer,25,Personal Travel,Business,214,4,4,4,2,1,4,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +31500,58553,Female,Loyal Customer,62,Personal Travel,Eco,1514,3,4,3,2,1,1,1,3,3,3,2,5,3,3,6,9.0,neutral or dissatisfied +31501,38329,Female,Loyal Customer,30,Business travel,Business,2281,2,2,2,2,2,3,2,2,5,4,2,1,3,2,93,112.0,satisfied +31502,59292,Female,Loyal Customer,52,Business travel,Business,2486,1,1,5,1,2,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +31503,46090,Female,Loyal Customer,70,Personal Travel,Eco,495,2,5,2,1,5,2,3,2,2,2,2,2,2,1,60,61.0,neutral or dissatisfied +31504,32029,Female,disloyal Customer,35,Business travel,Eco,101,2,0,2,4,2,2,2,2,3,5,1,1,2,2,0,0.0,neutral or dissatisfied +31505,82168,Female,Loyal Customer,32,Personal Travel,Eco,237,3,5,3,4,2,3,2,2,5,2,4,4,4,2,9,0.0,neutral or dissatisfied +31506,68255,Female,Loyal Customer,29,Personal Travel,Eco,432,3,5,3,4,5,3,5,5,4,4,5,5,4,5,38,20.0,neutral or dissatisfied +31507,113516,Female,Loyal Customer,61,Business travel,Business,1679,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +31508,90359,Female,Loyal Customer,34,Business travel,Business,2499,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +31509,97881,Female,disloyal Customer,33,Business travel,Business,722,2,2,2,5,4,2,4,4,5,2,5,5,5,4,0,3.0,neutral or dissatisfied +31510,27664,Female,disloyal Customer,27,Business travel,Eco,1216,4,4,4,3,3,4,3,3,4,2,3,5,5,3,0,0.0,satisfied +31511,1967,Female,Loyal Customer,51,Business travel,Business,295,2,4,4,4,2,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +31512,122243,Female,Loyal Customer,42,Business travel,Eco,573,2,3,3,3,2,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +31513,69197,Female,Loyal Customer,40,Business travel,Business,733,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +31514,81047,Female,Loyal Customer,25,Business travel,Business,1641,3,1,1,1,3,3,3,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +31515,69695,Female,Loyal Customer,57,Business travel,Business,1372,5,5,1,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +31516,36743,Female,disloyal Customer,23,Business travel,Eco,1426,1,1,1,2,1,1,4,4,2,4,5,4,4,4,0,0.0,neutral or dissatisfied +31517,121365,Female,Loyal Customer,33,Personal Travel,Eco,1670,2,5,2,3,5,2,5,5,5,1,1,3,5,5,0,10.0,neutral or dissatisfied +31518,108940,Female,Loyal Customer,54,Personal Travel,Eco,1075,5,5,5,1,5,4,4,3,3,5,3,3,3,5,2,0.0,satisfied +31519,97410,Male,Loyal Customer,50,Business travel,Business,570,5,5,5,5,5,4,5,2,2,2,2,3,2,5,10,0.0,satisfied +31520,14226,Male,Loyal Customer,18,Personal Travel,Eco,526,1,4,1,3,3,1,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +31521,51050,Male,Loyal Customer,57,Personal Travel,Eco,238,4,4,0,3,5,0,5,5,5,4,4,3,5,5,0,0.0,satisfied +31522,125442,Male,Loyal Customer,55,Business travel,Business,2860,1,1,1,1,1,1,1,4,5,2,4,1,4,1,10,13.0,neutral or dissatisfied +31523,9817,Female,Loyal Customer,41,Business travel,Business,1799,2,2,2,2,3,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +31524,5093,Male,disloyal Customer,36,Business travel,Business,224,4,4,4,1,4,4,4,4,2,1,4,2,5,4,0,4.0,neutral or dissatisfied +31525,10725,Male,Loyal Customer,58,Business travel,Business,201,1,1,1,1,4,5,5,4,4,4,5,3,4,4,0,0.0,satisfied +31526,121433,Female,Loyal Customer,22,Business travel,Business,2109,1,1,1,1,1,1,1,1,4,2,4,2,3,1,9,36.0,neutral or dissatisfied +31527,51550,Female,Loyal Customer,56,Business travel,Business,3405,5,4,5,5,5,5,4,3,3,4,3,5,3,3,0,11.0,satisfied +31528,13921,Male,disloyal Customer,32,Business travel,Eco,192,3,0,2,4,5,2,5,5,5,4,2,2,4,5,40,32.0,neutral or dissatisfied +31529,55984,Male,Loyal Customer,54,Business travel,Business,1620,3,3,3,3,3,5,4,4,4,4,4,4,4,4,15,2.0,satisfied +31530,82414,Female,disloyal Customer,26,Business travel,Business,502,4,4,4,4,2,4,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +31531,110395,Male,Loyal Customer,50,Business travel,Eco,787,3,4,4,4,3,3,3,3,2,3,3,3,4,3,0,8.0,neutral or dissatisfied +31532,113072,Male,disloyal Customer,27,Business travel,Business,543,4,4,4,1,1,4,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +31533,36188,Female,Loyal Customer,42,Business travel,Business,2139,3,3,2,3,2,3,4,3,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +31534,17320,Male,Loyal Customer,25,Personal Travel,Eco,258,2,4,2,2,2,2,2,4,3,3,2,2,3,2,247,307.0,neutral or dissatisfied +31535,105037,Female,Loyal Customer,8,Personal Travel,Eco,361,1,4,1,1,3,1,3,3,5,4,5,3,5,3,1,10.0,neutral or dissatisfied +31536,65267,Male,Loyal Customer,59,Business travel,Eco Plus,190,4,2,2,2,3,4,3,3,1,1,1,3,4,3,0,4.0,satisfied +31537,109611,Male,Loyal Customer,57,Business travel,Business,3575,1,1,5,1,2,5,5,4,4,4,4,3,4,3,17,17.0,satisfied +31538,37441,Male,Loyal Customer,35,Business travel,Business,1825,2,3,3,3,2,3,2,2,2,3,2,4,2,3,9,4.0,neutral or dissatisfied +31539,21257,Female,Loyal Customer,22,Personal Travel,Eco Plus,192,1,5,1,4,4,1,4,4,4,5,5,4,5,4,42,33.0,neutral or dissatisfied +31540,58569,Male,Loyal Customer,57,Business travel,Business,1186,3,3,5,3,3,5,5,5,5,5,5,3,5,3,41,12.0,satisfied +31541,48931,Female,Loyal Customer,39,Business travel,Business,89,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +31542,98029,Male,Loyal Customer,10,Personal Travel,Eco,1014,1,2,1,4,1,1,1,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +31543,74555,Male,Loyal Customer,22,Business travel,Business,2806,4,1,1,1,4,4,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +31544,1387,Male,Loyal Customer,49,Personal Travel,Eco Plus,312,4,4,4,2,3,4,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +31545,118004,Male,Loyal Customer,29,Business travel,Business,1037,1,1,1,1,4,5,4,4,5,5,4,4,4,4,30,33.0,satisfied +31546,17753,Female,Loyal Customer,14,Personal Travel,Eco,383,2,5,2,4,1,2,1,1,5,2,1,4,1,1,0,0.0,neutral or dissatisfied +31547,41107,Female,Loyal Customer,37,Business travel,Business,224,1,3,3,3,2,4,4,4,4,4,1,3,4,3,22,27.0,neutral or dissatisfied +31548,16754,Male,disloyal Customer,25,Business travel,Eco,569,2,3,2,3,5,2,1,5,1,3,3,2,4,5,51,60.0,neutral or dissatisfied +31549,52532,Male,Loyal Customer,44,Business travel,Business,160,3,3,3,3,5,1,3,4,4,5,5,2,4,1,0,0.0,satisfied +31550,44745,Male,Loyal Customer,31,Business travel,Business,2984,1,1,1,1,4,4,4,4,3,4,2,5,3,4,72,100.0,satisfied +31551,53938,Male,Loyal Customer,12,Personal Travel,Eco,2007,2,5,2,2,1,2,1,1,5,3,3,4,5,1,0,0.0,neutral or dissatisfied +31552,57804,Male,Loyal Customer,53,Business travel,Business,3606,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +31553,1637,Female,disloyal Customer,35,Business travel,Eco Plus,999,3,3,3,3,3,3,1,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +31554,127828,Male,Loyal Customer,25,Personal Travel,Eco,1262,1,4,1,2,2,1,2,2,3,2,4,5,5,2,6,19.0,neutral or dissatisfied +31555,53853,Male,Loyal Customer,66,Business travel,Eco,224,4,4,4,4,4,4,4,4,3,4,2,4,1,4,0,0.0,satisfied +31556,18102,Female,Loyal Customer,51,Personal Travel,Eco,610,4,4,4,2,4,4,5,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +31557,52724,Female,Loyal Customer,38,Business travel,Business,2187,2,5,5,5,4,4,3,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +31558,125597,Male,disloyal Customer,43,Business travel,Business,1587,2,2,2,3,2,2,3,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +31559,73848,Female,Loyal Customer,60,Business travel,Eco,1709,2,1,1,1,2,4,4,2,2,2,2,4,2,1,0,25.0,neutral or dissatisfied +31560,20809,Female,Loyal Customer,24,Business travel,Business,357,3,4,4,4,3,3,3,3,4,2,3,4,4,3,43,32.0,neutral or dissatisfied +31561,43378,Female,Loyal Customer,43,Personal Travel,Eco,402,4,4,5,4,3,4,4,3,3,5,3,3,3,2,8,4.0,satisfied +31562,87898,Female,Loyal Customer,37,Business travel,Business,2957,3,3,3,3,2,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +31563,129353,Male,Loyal Customer,11,Personal Travel,Eco,2475,3,4,3,4,4,3,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +31564,7100,Female,Loyal Customer,54,Personal Travel,Eco,273,4,0,4,3,5,4,4,5,5,4,2,4,5,4,2,5.0,satisfied +31565,44042,Male,Loyal Customer,45,Business travel,Eco,237,3,3,3,3,3,3,3,3,4,3,3,3,2,3,0,0.0,neutral or dissatisfied +31566,109282,Male,disloyal Customer,27,Business travel,Business,1136,1,1,1,4,2,1,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +31567,48027,Female,Loyal Customer,36,Business travel,Business,1384,1,5,1,1,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +31568,116491,Male,Loyal Customer,51,Personal Travel,Eco,417,2,5,1,4,2,1,2,2,1,4,1,4,2,2,0,0.0,neutral or dissatisfied +31569,109977,Male,Loyal Customer,53,Personal Travel,Eco,1079,1,5,1,5,2,1,2,2,5,3,5,5,4,2,21,17.0,neutral or dissatisfied +31570,53656,Female,Loyal Customer,54,Business travel,Business,1208,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +31571,81172,Female,disloyal Customer,24,Business travel,Eco,980,3,3,3,4,4,3,4,4,5,4,4,4,5,4,32,17.0,neutral or dissatisfied +31572,63169,Female,Loyal Customer,47,Business travel,Business,447,2,2,2,2,5,4,4,4,4,4,4,4,4,4,112,102.0,satisfied +31573,69387,Male,Loyal Customer,55,Business travel,Eco,1096,3,3,3,3,3,3,3,3,3,5,4,1,3,3,22,36.0,neutral or dissatisfied +31574,91365,Female,Loyal Customer,27,Personal Travel,Eco Plus,515,2,5,2,3,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +31575,84317,Male,Loyal Customer,36,Business travel,Business,3148,5,5,2,5,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +31576,49448,Female,disloyal Customer,34,Business travel,Eco,262,1,0,1,1,3,1,3,3,2,1,4,2,4,3,6,0.0,neutral or dissatisfied +31577,75326,Male,Loyal Customer,47,Business travel,Business,2615,3,3,3,3,5,5,5,4,3,3,5,5,3,5,0,0.0,satisfied +31578,34300,Female,Loyal Customer,10,Personal Travel,Eco,280,2,4,2,2,3,2,3,3,1,5,3,3,2,3,59,54.0,neutral or dissatisfied +31579,78076,Male,Loyal Customer,38,Business travel,Business,332,0,0,0,4,4,4,5,1,1,1,1,4,1,3,0,7.0,satisfied +31580,4826,Male,Loyal Customer,59,Business travel,Eco,408,2,1,1,1,3,2,3,3,3,1,3,3,4,3,28,28.0,neutral or dissatisfied +31581,32760,Female,disloyal Customer,72,Business travel,Eco,101,3,1,3,2,3,3,5,3,4,1,1,1,2,3,0,0.0,neutral or dissatisfied +31582,123647,Female,Loyal Customer,41,Business travel,Business,214,4,4,4,4,4,4,4,4,4,4,5,3,4,5,2,10.0,satisfied +31583,93688,Male,Loyal Customer,51,Business travel,Business,1452,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +31584,95534,Female,Loyal Customer,11,Personal Travel,Eco Plus,187,2,5,2,3,5,2,5,5,3,4,5,5,5,5,1,0.0,neutral or dissatisfied +31585,44487,Female,Loyal Customer,41,Personal Travel,Eco,476,2,1,2,3,1,2,1,1,4,4,3,3,3,1,14,0.0,neutral or dissatisfied +31586,6000,Male,Loyal Customer,8,Business travel,Business,2580,2,1,1,1,2,3,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +31587,121806,Female,disloyal Customer,20,Business travel,Business,449,5,1,5,4,5,5,5,5,5,4,5,5,5,5,112,117.0,satisfied +31588,17817,Female,Loyal Customer,39,Personal Travel,Eco,1075,2,4,2,4,1,2,1,1,5,5,4,5,5,1,0,3.0,neutral or dissatisfied +31589,55753,Female,Loyal Customer,42,Business travel,Business,1582,1,1,1,1,1,4,1,5,5,5,5,3,5,5,2,0.0,satisfied +31590,42833,Female,Loyal Customer,40,Business travel,Eco,328,2,5,5,5,2,2,2,2,2,5,4,1,1,2,0,0.0,satisfied +31591,56560,Female,Loyal Customer,57,Business travel,Business,2223,2,2,2,2,5,4,4,5,5,5,5,3,5,5,32,59.0,satisfied +31592,63842,Female,disloyal Customer,27,Business travel,Business,1192,1,2,2,3,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +31593,36858,Female,Loyal Customer,41,Business travel,Eco,273,4,2,2,2,4,4,4,4,2,2,1,2,3,4,0,0.0,satisfied +31594,51582,Male,Loyal Customer,35,Business travel,Business,2162,3,3,3,3,3,4,1,2,2,3,2,4,2,1,0,0.0,satisfied +31595,83366,Male,Loyal Customer,25,Business travel,Business,2814,5,5,5,5,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +31596,98403,Male,Loyal Customer,31,Business travel,Business,675,4,4,4,4,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +31597,38406,Female,Loyal Customer,26,Business travel,Eco Plus,1754,5,5,2,2,5,5,4,5,4,5,5,3,4,5,0,0.0,satisfied +31598,104369,Female,Loyal Customer,46,Business travel,Business,3057,3,3,3,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +31599,1377,Male,disloyal Customer,38,Business travel,Eco Plus,247,4,4,4,2,3,4,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +31600,35577,Male,Loyal Customer,33,Business travel,Eco Plus,1028,5,5,5,5,5,5,5,5,4,2,1,4,4,5,0,7.0,satisfied +31601,116877,Male,Loyal Customer,50,Business travel,Business,370,5,5,5,5,4,5,5,4,4,4,4,4,4,5,28,4.0,satisfied +31602,44477,Male,Loyal Customer,26,Business travel,Business,2462,4,4,4,4,4,4,4,4,2,5,4,2,3,4,6,19.0,satisfied +31603,116051,Female,Loyal Customer,7,Personal Travel,Eco,337,1,4,1,2,1,1,1,1,5,4,5,1,1,1,0,0.0,neutral or dissatisfied +31604,48367,Male,disloyal Customer,24,Business travel,Eco,522,3,4,3,2,4,3,4,4,3,3,5,1,5,4,69,66.0,neutral or dissatisfied +31605,105432,Male,Loyal Customer,28,Personal Travel,Eco,452,3,2,3,3,4,3,1,4,4,4,3,1,3,4,44,42.0,neutral or dissatisfied +31606,92850,Male,disloyal Customer,27,Business travel,Business,1187,3,3,3,3,3,3,5,3,2,4,4,1,3,3,0,1.0,neutral or dissatisfied +31607,97836,Female,Loyal Customer,22,Personal Travel,Eco,395,3,5,3,3,4,3,4,4,1,5,3,1,2,4,0,0.0,neutral or dissatisfied +31608,94077,Male,Loyal Customer,53,Business travel,Business,341,2,4,4,4,1,2,3,2,2,2,2,1,2,2,68,73.0,neutral or dissatisfied +31609,84539,Female,disloyal Customer,40,Business travel,Business,986,4,4,4,2,1,4,2,1,2,2,2,3,1,1,0,0.0,neutral or dissatisfied +31610,12915,Female,Loyal Customer,23,Business travel,Business,1537,3,4,4,4,3,3,3,3,3,5,3,1,4,3,0,0.0,neutral or dissatisfied +31611,125931,Female,Loyal Customer,65,Personal Travel,Eco,920,4,4,4,1,3,4,5,1,1,4,1,4,1,5,0,0.0,satisfied +31612,50245,Female,Loyal Customer,46,Business travel,Business,3558,4,4,4,4,3,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +31613,40995,Male,Loyal Customer,58,Business travel,Business,1201,4,4,2,4,4,1,2,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +31614,111846,Female,Loyal Customer,42,Business travel,Business,1902,2,2,2,2,3,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +31615,115967,Female,Loyal Customer,42,Personal Travel,Eco,325,2,5,2,3,5,5,2,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +31616,28805,Female,disloyal Customer,22,Business travel,Eco,1050,2,2,2,1,1,2,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +31617,96298,Female,Loyal Customer,12,Personal Travel,Eco,490,5,5,4,4,3,4,3,3,1,4,1,3,2,3,0,0.0,satisfied +31618,121655,Male,disloyal Customer,27,Business travel,Business,511,4,4,4,5,5,4,1,5,3,4,5,4,5,5,35,24.0,neutral or dissatisfied +31619,3272,Female,Loyal Customer,66,Business travel,Business,479,2,2,2,2,3,3,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +31620,42481,Female,Loyal Customer,47,Business travel,Business,585,1,1,1,1,5,5,5,5,5,5,5,5,5,5,0,4.0,satisfied +31621,43959,Male,Loyal Customer,50,Business travel,Eco Plus,408,5,4,4,4,5,5,5,5,2,3,5,4,5,5,43,37.0,satisfied +31622,27690,Male,Loyal Customer,38,Business travel,Eco,707,5,5,5,5,5,5,5,5,2,3,1,5,2,5,0,0.0,satisfied +31623,75715,Male,Loyal Customer,47,Business travel,Business,2718,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +31624,116112,Male,Loyal Customer,64,Personal Travel,Eco,390,3,1,3,4,4,3,4,4,2,3,3,2,3,4,16,15.0,neutral or dissatisfied +31625,54441,Male,Loyal Customer,32,Business travel,Eco Plus,305,5,2,5,2,5,5,5,5,2,1,3,5,1,5,0,0.0,satisfied +31626,21104,Male,Loyal Customer,50,Business travel,Business,3973,3,2,2,2,3,1,1,3,3,3,3,2,3,5,5,4.0,neutral or dissatisfied +31627,95949,Female,disloyal Customer,24,Business travel,Business,1090,4,4,4,3,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +31628,123298,Male,Loyal Customer,47,Business travel,Eco Plus,468,3,2,4,2,3,3,3,3,4,1,3,3,3,3,1,0.0,neutral or dissatisfied +31629,84057,Female,Loyal Customer,41,Business travel,Eco,757,3,3,3,3,3,3,3,3,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +31630,77057,Female,Loyal Customer,44,Business travel,Business,2865,5,5,5,5,2,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +31631,101728,Female,Loyal Customer,42,Business travel,Business,1216,4,4,4,4,3,4,5,4,4,4,4,3,4,3,15,0.0,satisfied +31632,85252,Male,Loyal Customer,50,Personal Travel,Eco,689,2,5,2,3,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +31633,107130,Male,Loyal Customer,31,Personal Travel,Eco,842,3,5,3,1,1,3,1,1,4,3,5,5,4,1,35,16.0,neutral or dissatisfied +31634,11574,Male,Loyal Customer,17,Business travel,Eco,468,2,4,4,4,2,1,2,4,1,3,3,2,4,2,141,156.0,neutral or dissatisfied +31635,26301,Female,Loyal Customer,24,Personal Travel,Eco,1199,3,5,2,4,1,2,1,1,5,1,5,4,1,1,0,18.0,neutral or dissatisfied +31636,89602,Female,Loyal Customer,25,Business travel,Business,3619,2,2,2,2,2,2,2,2,3,5,2,2,2,2,0,0.0,neutral or dissatisfied +31637,90718,Female,Loyal Customer,44,Business travel,Business,404,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +31638,107720,Female,Loyal Customer,37,Business travel,Business,3179,2,1,1,1,2,3,4,2,2,2,2,4,2,1,66,80.0,neutral or dissatisfied +31639,77753,Male,Loyal Customer,56,Business travel,Eco,331,4,3,3,3,4,4,4,4,1,5,4,5,5,4,0,0.0,satisfied +31640,124327,Male,Loyal Customer,26,Personal Travel,Eco,601,2,2,2,3,5,2,5,5,4,1,3,3,4,5,0,0.0,neutral or dissatisfied +31641,107353,Male,Loyal Customer,46,Business travel,Eco,632,1,3,3,3,2,1,2,2,4,5,2,3,1,2,0,8.0,neutral or dissatisfied +31642,41635,Male,Loyal Customer,25,Personal Travel,Eco Plus,374,3,5,3,5,4,3,4,4,4,3,5,5,5,4,20,33.0,neutral or dissatisfied +31643,44740,Female,Loyal Customer,27,Personal Travel,Eco Plus,268,1,1,1,4,1,1,1,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +31644,79243,Male,Loyal Customer,60,Business travel,Business,1598,1,1,1,1,2,3,4,5,5,5,5,5,5,4,0,6.0,satisfied +31645,122298,Female,Loyal Customer,8,Personal Travel,Eco,544,2,3,1,3,2,1,2,2,4,3,4,2,3,2,21,23.0,neutral or dissatisfied +31646,45951,Female,Loyal Customer,66,Personal Travel,Eco,563,3,5,3,1,3,5,5,2,2,3,1,4,2,3,0,0.0,neutral or dissatisfied +31647,62495,Male,disloyal Customer,43,Business travel,Business,1744,2,2,2,3,1,2,1,1,4,3,4,3,4,1,12,9.0,satisfied +31648,50936,Female,Loyal Customer,38,Personal Travel,Eco,109,4,3,4,4,5,4,5,5,1,1,4,5,1,5,0,2.0,satisfied +31649,10076,Male,Loyal Customer,40,Business travel,Business,258,3,2,2,2,3,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +31650,83890,Male,Loyal Customer,58,Business travel,Business,1450,2,2,2,2,5,5,4,2,2,2,2,4,2,5,6,21.0,satisfied +31651,11770,Female,Loyal Customer,55,Personal Travel,Eco,395,3,3,3,3,5,4,4,2,2,3,2,4,2,3,126,127.0,neutral or dissatisfied +31652,4940,Male,Loyal Customer,10,Personal Travel,Eco,268,2,3,2,3,3,2,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +31653,120641,Female,disloyal Customer,23,Business travel,Eco,280,4,4,4,5,2,4,2,2,3,4,5,3,4,2,3,2.0,satisfied +31654,116049,Male,Loyal Customer,32,Personal Travel,Eco,296,2,4,2,3,4,2,4,4,4,4,4,3,4,4,0,4.0,neutral or dissatisfied +31655,80881,Female,Loyal Customer,30,Business travel,Business,2482,2,2,2,2,4,4,4,4,4,4,5,3,4,4,3,0.0,satisfied +31656,86031,Male,Loyal Customer,11,Personal Travel,Eco,528,4,4,4,5,3,4,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +31657,110301,Female,disloyal Customer,29,Business travel,Business,883,3,3,3,5,2,3,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +31658,63978,Male,Loyal Customer,28,Personal Travel,Eco Plus,1158,3,4,3,3,2,3,5,2,3,2,5,3,4,2,0,15.0,neutral or dissatisfied +31659,113936,Male,Loyal Customer,39,Business travel,Business,1706,1,1,1,1,2,3,5,5,5,5,5,4,5,3,2,1.0,satisfied +31660,44118,Male,disloyal Customer,20,Business travel,Eco,120,1,0,1,2,5,1,5,5,3,2,3,1,4,5,46,36.0,neutral or dissatisfied +31661,51301,Female,disloyal Customer,38,Business travel,Eco Plus,86,4,4,4,2,2,4,2,2,5,2,3,2,4,2,0,0.0,satisfied +31662,52858,Male,Loyal Customer,40,Business travel,Eco Plus,1721,2,4,4,4,2,2,2,2,1,5,3,1,3,2,0,0.0,satisfied +31663,18863,Female,Loyal Customer,57,Business travel,Business,503,2,4,4,4,1,4,4,2,2,2,2,4,2,4,0,8.0,neutral or dissatisfied +31664,32329,Male,Loyal Customer,54,Business travel,Eco,102,3,5,4,5,3,3,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +31665,106969,Female,Loyal Customer,48,Business travel,Business,3037,4,4,4,4,2,5,5,4,4,4,4,3,4,5,25,0.0,satisfied +31666,100360,Male,Loyal Customer,67,Personal Travel,Eco,1052,4,5,5,3,1,5,1,1,4,3,4,4,5,1,0,4.0,satisfied +31667,124233,Female,Loyal Customer,59,Business travel,Business,1916,4,4,2,4,2,5,4,5,5,5,5,3,5,3,35,4.0,satisfied +31668,25693,Female,Loyal Customer,14,Business travel,Business,2053,4,4,4,4,5,5,5,5,3,2,3,1,3,5,0,0.0,satisfied +31669,115580,Female,Loyal Customer,43,Business travel,Business,371,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +31670,34540,Male,Loyal Customer,18,Personal Travel,Eco,636,3,4,3,3,1,3,5,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +31671,13540,Female,Loyal Customer,51,Business travel,Business,1972,2,4,4,4,5,3,3,2,2,1,2,4,2,1,96,116.0,neutral or dissatisfied +31672,8143,Male,Loyal Customer,38,Business travel,Business,3974,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +31673,42596,Male,Loyal Customer,22,Personal Travel,Eco,1201,1,5,1,4,4,1,4,4,4,1,5,2,2,4,0,0.0,neutral or dissatisfied +31674,68682,Female,Loyal Customer,44,Business travel,Business,237,2,2,2,2,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +31675,18903,Female,Loyal Customer,59,Personal Travel,Eco,500,2,1,2,2,1,2,3,4,4,2,4,1,4,1,18,20.0,neutral or dissatisfied +31676,59260,Female,disloyal Customer,12,Business travel,Eco Plus,3904,3,2,3,3,3,4,4,1,4,3,4,4,2,4,12,0.0,neutral or dissatisfied +31677,120691,Male,Loyal Customer,13,Personal Travel,Eco,280,1,5,5,1,5,5,4,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +31678,9425,Female,disloyal Customer,39,Business travel,Business,288,2,2,2,3,1,2,1,1,2,4,3,1,3,1,50,43.0,neutral or dissatisfied +31679,76418,Female,Loyal Customer,44,Business travel,Business,405,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +31680,100914,Male,Loyal Customer,18,Personal Travel,Eco,377,2,5,2,3,4,2,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +31681,11405,Female,Loyal Customer,51,Business travel,Business,247,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +31682,84385,Male,disloyal Customer,36,Business travel,Eco,591,1,0,1,4,1,1,1,1,4,2,4,4,3,1,7,1.0,neutral or dissatisfied +31683,97254,Male,Loyal Customer,22,Business travel,Business,3282,4,4,4,4,4,4,4,4,5,3,4,4,1,4,8,0.0,satisfied +31684,43590,Female,disloyal Customer,36,Business travel,Eco,252,3,0,3,4,2,3,2,2,1,3,1,1,2,2,0,5.0,neutral or dissatisfied +31685,104672,Male,Loyal Customer,70,Personal Travel,Eco,641,1,5,1,1,5,1,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +31686,116498,Female,Loyal Customer,10,Personal Travel,Eco,417,3,2,3,2,5,3,5,5,4,5,2,3,3,5,0,0.0,neutral or dissatisfied +31687,49737,Male,Loyal Customer,45,Business travel,Business,2848,3,3,3,3,3,5,4,4,4,4,3,1,4,4,0,0.0,satisfied +31688,52737,Female,Loyal Customer,44,Business travel,Eco,2306,4,5,5,5,4,5,1,4,4,4,4,2,4,5,0,0.0,satisfied +31689,104043,Female,Loyal Customer,55,Business travel,Eco,1044,4,2,2,2,5,2,3,4,4,4,4,2,4,3,0,15.0,neutral or dissatisfied +31690,113914,Female,Loyal Customer,28,Business travel,Business,2295,5,5,5,5,4,4,4,4,4,5,4,4,4,4,1,0.0,satisfied +31691,92831,Male,Loyal Customer,62,Personal Travel,Eco,1587,4,5,4,1,2,4,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +31692,49315,Male,Loyal Customer,54,Business travel,Business,89,4,3,4,4,1,5,5,5,5,5,4,1,5,3,76,70.0,satisfied +31693,58956,Male,disloyal Customer,37,Business travel,Business,1744,1,1,1,4,1,1,1,1,3,2,4,5,4,1,45,16.0,neutral or dissatisfied +31694,127534,Female,disloyal Customer,24,Business travel,Eco,1009,2,2,2,2,1,2,1,1,4,2,4,4,5,1,0,2.0,neutral or dissatisfied +31695,126542,Female,Loyal Customer,38,Business travel,Eco,644,2,3,3,3,2,2,2,2,2,4,2,1,1,2,6,37.0,neutral or dissatisfied +31696,110858,Male,disloyal Customer,26,Business travel,Business,581,1,1,1,1,5,1,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +31697,29751,Male,Loyal Customer,50,Business travel,Business,1604,5,5,5,5,4,5,4,5,5,5,4,3,5,3,0,4.0,satisfied +31698,24874,Female,Loyal Customer,52,Personal Travel,Eco,356,1,4,1,3,4,4,4,2,2,1,5,3,2,3,0,7.0,neutral or dissatisfied +31699,42789,Male,Loyal Customer,56,Business travel,Eco Plus,1118,5,5,5,5,4,5,4,4,2,5,5,4,3,4,0,3.0,satisfied +31700,84131,Male,Loyal Customer,50,Business travel,Business,1569,3,3,4,3,4,4,5,4,4,4,4,4,4,5,0,8.0,satisfied +31701,85592,Female,disloyal Customer,25,Business travel,Eco,153,2,0,2,1,3,2,3,3,2,4,5,1,4,3,0,0.0,neutral or dissatisfied +31702,65238,Male,Loyal Customer,60,Business travel,Eco Plus,551,1,2,2,2,1,1,1,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +31703,104928,Female,Loyal Customer,53,Personal Travel,Eco,210,3,5,3,5,3,5,4,4,4,3,4,1,4,5,14,12.0,neutral or dissatisfied +31704,54187,Male,Loyal Customer,17,Personal Travel,Eco,1400,2,4,2,1,4,2,4,4,5,2,2,5,5,4,0,0.0,neutral or dissatisfied +31705,71424,Female,Loyal Customer,47,Business travel,Business,867,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +31706,37159,Male,Loyal Customer,53,Personal Travel,Eco,1189,2,5,2,3,5,2,5,5,5,2,4,5,4,5,3,6.0,neutral or dissatisfied +31707,119237,Female,Loyal Customer,26,Personal Travel,Eco,257,2,2,2,4,5,2,2,5,1,5,4,3,3,5,0,0.0,neutral or dissatisfied +31708,42142,Female,Loyal Customer,27,Business travel,Business,834,1,1,1,1,4,4,4,4,5,2,4,4,5,4,0,11.0,satisfied +31709,22521,Male,Loyal Customer,64,Business travel,Eco Plus,143,1,4,3,4,1,1,1,1,2,1,4,3,3,1,13,14.0,neutral or dissatisfied +31710,5154,Male,Loyal Customer,60,Personal Travel,Eco,622,2,3,2,2,2,2,2,2,1,2,5,3,5,2,0,0.0,neutral or dissatisfied +31711,85894,Female,Loyal Customer,50,Business travel,Business,761,2,2,2,2,5,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +31712,25441,Male,Loyal Customer,31,Business travel,Business,2950,1,2,2,2,1,1,1,1,2,3,4,4,4,1,13,3.0,neutral or dissatisfied +31713,35390,Male,disloyal Customer,25,Business travel,Eco,1028,5,5,5,1,5,5,5,5,5,3,4,5,3,5,0,0.0,satisfied +31714,20299,Female,Loyal Customer,48,Personal Travel,Eco,346,3,2,3,4,5,3,3,5,5,3,5,1,5,4,0,0.0,neutral or dissatisfied +31715,106193,Male,Loyal Customer,63,Personal Travel,Eco,302,2,4,2,1,5,2,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +31716,58172,Male,disloyal Customer,23,Business travel,Business,978,5,0,5,1,3,5,1,3,5,3,5,4,4,3,0,0.0,satisfied +31717,51437,Male,Loyal Customer,69,Personal Travel,Eco Plus,304,2,4,1,3,3,1,2,3,3,5,4,3,4,3,1,0.0,neutral or dissatisfied +31718,9760,Male,Loyal Customer,57,Business travel,Business,3252,4,4,4,4,3,5,4,4,4,4,4,5,4,3,7,0.0,satisfied +31719,36132,Female,Loyal Customer,53,Business travel,Eco,1609,3,3,4,3,1,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +31720,78654,Female,Loyal Customer,19,Personal Travel,Eco,2172,3,5,2,5,3,2,5,3,5,3,4,5,4,3,8,3.0,neutral or dissatisfied +31721,117445,Female,Loyal Customer,27,Business travel,Business,3169,2,4,4,4,2,2,2,2,1,5,1,3,2,2,38,29.0,neutral or dissatisfied +31722,97038,Male,Loyal Customer,48,Business travel,Business,1497,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +31723,111025,Female,disloyal Customer,27,Business travel,Eco,197,3,3,3,4,3,3,1,3,1,3,4,2,4,3,0,0.0,neutral or dissatisfied +31724,54282,Female,Loyal Customer,26,Business travel,Business,3503,4,1,1,1,4,4,4,4,2,3,4,4,4,4,111,103.0,neutral or dissatisfied +31725,44890,Female,disloyal Customer,25,Business travel,Eco,536,1,4,1,3,1,1,1,1,3,1,4,2,2,1,1,0.0,neutral or dissatisfied +31726,71460,Male,Loyal Customer,54,Personal Travel,Eco,867,1,4,1,3,4,1,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +31727,99475,Female,Loyal Customer,17,Business travel,Eco,307,2,1,1,1,2,2,1,2,2,3,3,2,3,2,39,28.0,neutral or dissatisfied +31728,84256,Male,Loyal Customer,38,Business travel,Eco,314,1,3,3,3,1,1,1,1,4,3,4,1,4,1,0,9.0,neutral or dissatisfied +31729,45892,Male,Loyal Customer,52,Business travel,Business,913,3,3,3,3,4,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +31730,4372,Female,disloyal Customer,26,Business travel,Business,473,1,1,1,4,2,1,5,2,4,2,3,3,4,2,0,1.0,neutral or dissatisfied +31731,97464,Female,disloyal Customer,22,Business travel,Eco,484,5,0,5,1,1,5,1,1,3,2,4,5,4,1,0,0.0,satisfied +31732,110059,Female,Loyal Customer,7,Personal Travel,Eco,2173,2,5,2,2,3,2,3,3,4,5,4,3,5,3,1,0.0,neutral or dissatisfied +31733,93050,Male,Loyal Customer,78,Business travel,Eco Plus,317,1,2,2,2,1,1,1,1,3,3,4,3,3,1,4,0.0,neutral or dissatisfied +31734,99244,Male,Loyal Customer,22,Personal Travel,Eco,495,4,4,4,4,5,4,5,5,2,4,3,4,4,5,15,6.0,neutral or dissatisfied +31735,103036,Male,disloyal Customer,30,Business travel,Eco,546,1,2,1,4,1,1,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +31736,127245,Male,disloyal Customer,21,Business travel,Business,1107,4,0,4,1,1,4,1,1,3,3,4,3,5,1,0,0.0,satisfied +31737,97772,Female,disloyal Customer,26,Business travel,Business,471,2,2,2,1,4,2,4,4,4,4,5,3,5,4,35,18.0,neutral or dissatisfied +31738,51602,Female,Loyal Customer,63,Business travel,Eco,370,3,3,5,3,3,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +31739,8360,Female,Loyal Customer,46,Business travel,Business,1525,1,1,1,1,3,5,4,4,4,4,4,4,4,4,20,17.0,satisfied +31740,72715,Male,Loyal Customer,39,Business travel,Eco Plus,1119,3,2,2,2,3,4,3,3,1,3,2,1,3,3,1,2.0,neutral or dissatisfied +31741,34770,Male,disloyal Customer,27,Business travel,Eco,301,4,5,4,3,2,4,4,2,3,3,3,2,5,2,0,0.0,neutral or dissatisfied +31742,39021,Male,Loyal Customer,47,Business travel,Eco,230,4,3,3,3,4,4,4,4,3,1,4,2,4,4,0,0.0,satisfied +31743,116399,Female,Loyal Customer,13,Personal Travel,Eco,337,1,5,1,4,3,1,3,3,3,2,4,3,4,3,25,26.0,neutral or dissatisfied +31744,74586,Male,Loyal Customer,46,Business travel,Business,1464,2,5,4,5,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +31745,47062,Male,Loyal Customer,55,Business travel,Business,239,2,2,3,2,2,2,3,5,5,5,5,5,5,3,35,62.0,satisfied +31746,106826,Female,Loyal Customer,52,Personal Travel,Eco,1488,4,5,3,4,2,5,5,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +31747,94131,Female,disloyal Customer,25,Business travel,Business,528,3,5,3,4,3,3,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +31748,39991,Male,Loyal Customer,34,Business travel,Business,3953,3,3,3,3,5,2,2,3,3,3,3,3,3,2,77,108.0,neutral or dissatisfied +31749,82970,Female,disloyal Customer,25,Business travel,Business,1084,2,0,2,5,2,2,1,2,3,4,4,5,5,2,81,86.0,neutral or dissatisfied +31750,31094,Female,disloyal Customer,26,Business travel,Eco,1014,1,1,1,4,3,1,3,3,2,4,3,3,4,3,8,36.0,neutral or dissatisfied +31751,93329,Male,Loyal Customer,29,Business travel,Business,1024,4,4,4,4,5,5,5,5,3,4,4,4,5,5,83,65.0,satisfied +31752,102365,Female,Loyal Customer,53,Business travel,Business,2859,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +31753,78856,Male,Loyal Customer,46,Personal Travel,Eco Plus,528,3,1,3,3,5,3,3,5,2,2,2,1,3,5,0,0.0,neutral or dissatisfied +31754,37812,Female,Loyal Customer,58,Personal Travel,Eco Plus,1028,2,4,3,1,5,2,1,5,5,3,5,3,5,4,8,9.0,neutral or dissatisfied +31755,17519,Female,Loyal Customer,39,Personal Travel,Eco,352,2,3,2,4,5,2,3,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +31756,77299,Female,Loyal Customer,47,Business travel,Business,391,3,3,3,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +31757,33811,Male,Loyal Customer,24,Business travel,Eco,1521,5,2,2,2,5,5,5,5,1,1,5,3,2,5,14,0.0,satisfied +31758,124970,Male,Loyal Customer,38,Business travel,Business,2030,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +31759,61576,Male,disloyal Customer,39,Business travel,Business,1346,2,3,3,2,1,3,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +31760,111261,Female,Loyal Customer,59,Business travel,Business,1652,2,2,4,4,3,4,4,2,2,2,2,2,2,3,93,84.0,neutral or dissatisfied +31761,73304,Female,Loyal Customer,49,Business travel,Business,1182,1,1,1,1,3,4,5,4,4,5,4,4,4,5,4,11.0,satisfied +31762,73542,Female,Loyal Customer,51,Personal Travel,Eco,594,2,2,2,1,1,1,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +31763,26085,Male,Loyal Customer,20,Business travel,Business,2184,5,5,4,5,4,4,4,4,3,1,3,2,3,4,5,0.0,satisfied +31764,61904,Male,Loyal Customer,47,Business travel,Business,550,2,2,3,2,4,4,5,5,5,5,5,4,5,3,22,24.0,satisfied +31765,128873,Female,Loyal Customer,55,Business travel,Business,2565,2,2,2,2,5,4,4,5,4,3,5,4,3,4,0,0.0,satisfied +31766,28885,Female,disloyal Customer,27,Business travel,Eco,1050,3,3,3,4,1,3,1,1,4,4,3,4,2,1,0,0.0,neutral or dissatisfied +31767,97298,Male,Loyal Customer,55,Business travel,Business,2525,5,5,5,5,2,4,5,5,5,5,5,5,5,3,114,120.0,satisfied +31768,113503,Female,Loyal Customer,54,Business travel,Business,236,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +31769,106709,Female,Loyal Customer,11,Personal Travel,Eco,516,2,2,2,4,1,2,1,1,4,4,3,3,3,1,11,16.0,neutral or dissatisfied +31770,110814,Female,Loyal Customer,50,Personal Travel,Eco,1128,3,4,3,3,4,3,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +31771,79063,Male,Loyal Customer,31,Business travel,Business,3229,5,5,5,5,5,5,5,5,3,5,4,4,5,5,15,0.0,satisfied +31772,6230,Male,Loyal Customer,42,Business travel,Business,413,5,5,5,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +31773,3390,Female,Loyal Customer,59,Business travel,Business,1550,5,1,1,1,4,4,4,5,5,4,5,3,5,4,51,36.0,neutral or dissatisfied +31774,121030,Female,Loyal Customer,12,Personal Travel,Eco,951,3,2,2,3,5,2,4,5,2,1,4,2,4,5,0,2.0,neutral or dissatisfied +31775,75832,Male,Loyal Customer,56,Business travel,Business,1440,2,2,2,2,5,4,4,3,3,3,3,5,3,5,115,100.0,satisfied +31776,1229,Female,Loyal Customer,42,Personal Travel,Eco,164,2,4,2,2,3,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +31777,99456,Female,disloyal Customer,24,Business travel,Eco,283,5,4,5,2,4,5,4,4,3,3,4,5,4,4,0,0.0,satisfied +31778,78067,Male,Loyal Customer,52,Personal Travel,Eco,214,1,4,0,4,4,0,4,4,3,5,3,3,4,4,14,18.0,neutral or dissatisfied +31779,26901,Female,Loyal Customer,41,Business travel,Business,1660,2,2,2,2,2,3,3,5,5,4,5,4,5,2,0,0.0,satisfied +31780,124408,Female,Loyal Customer,55,Business travel,Business,2102,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +31781,117531,Male,Loyal Customer,41,Personal Travel,Business,843,5,5,5,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +31782,64284,Female,disloyal Customer,26,Business travel,Business,1192,1,1,1,3,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +31783,81124,Male,Loyal Customer,53,Personal Travel,Eco,991,1,5,1,3,2,1,2,2,4,5,5,4,4,2,60,60.0,neutral or dissatisfied +31784,102025,Male,Loyal Customer,25,Business travel,Business,3277,2,2,2,2,5,5,5,5,4,2,4,3,5,5,124,113.0,satisfied +31785,81196,Female,Loyal Customer,41,Business travel,Business,1426,3,3,3,3,5,5,4,4,4,4,4,3,4,5,7,0.0,satisfied +31786,48510,Female,Loyal Customer,12,Business travel,Business,2667,3,2,2,2,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +31787,129787,Female,Loyal Customer,19,Personal Travel,Eco,337,3,2,3,3,1,3,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +31788,81540,Female,Loyal Customer,66,Personal Travel,Eco,1124,3,4,3,5,3,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +31789,97806,Female,disloyal Customer,16,Business travel,Eco,395,1,2,1,3,1,1,1,1,1,5,3,1,3,1,4,12.0,neutral or dissatisfied +31790,110594,Female,Loyal Customer,46,Personal Travel,Eco,488,3,4,3,3,2,4,4,2,2,3,2,3,2,5,15,11.0,neutral or dissatisfied +31791,15518,Female,Loyal Customer,31,Business travel,Eco Plus,399,0,1,1,5,4,1,4,4,2,1,4,5,4,4,19,7.0,satisfied +31792,99962,Male,Loyal Customer,41,Business travel,Business,888,1,1,1,1,2,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +31793,125370,Male,Loyal Customer,60,Business travel,Business,2573,2,2,2,2,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +31794,71517,Male,Loyal Customer,54,Business travel,Business,3730,1,1,2,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +31795,74725,Male,Loyal Customer,40,Personal Travel,Eco,1235,4,2,4,4,1,4,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +31796,36603,Female,Loyal Customer,19,Business travel,Business,3699,3,1,1,1,3,3,3,3,1,3,2,1,2,3,46,52.0,neutral or dissatisfied +31797,63189,Male,Loyal Customer,50,Business travel,Business,337,0,0,0,1,4,5,5,3,3,3,3,3,3,5,4,0.0,satisfied +31798,32114,Male,Loyal Customer,37,Business travel,Eco,101,3,3,3,3,3,3,3,3,3,1,5,3,4,3,0,0.0,satisfied +31799,17741,Male,Loyal Customer,49,Business travel,Eco,383,3,2,2,2,3,3,3,3,1,1,1,3,2,3,0,37.0,neutral or dissatisfied +31800,55374,Male,Loyal Customer,56,Business travel,Eco,678,2,5,3,5,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +31801,150,Male,disloyal Customer,21,Business travel,Eco,227,2,1,2,3,2,3,3,4,3,4,4,3,2,3,166,185.0,neutral or dissatisfied +31802,30083,Male,Loyal Customer,27,Personal Travel,Eco,399,3,5,3,2,5,3,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +31803,72056,Female,disloyal Customer,27,Business travel,Business,1235,0,0,0,3,2,0,2,2,3,4,4,5,4,2,0,0.0,satisfied +31804,116590,Female,Loyal Customer,34,Business travel,Business,3524,5,5,5,5,3,4,5,5,5,5,5,5,5,3,7,2.0,satisfied +31805,42676,Female,Loyal Customer,26,Business travel,Business,627,2,2,2,2,5,5,5,5,1,5,3,1,3,5,0,0.0,satisfied +31806,66561,Female,Loyal Customer,21,Personal Travel,Eco,328,3,2,3,4,3,3,3,3,1,5,3,1,3,3,28,41.0,neutral or dissatisfied +31807,59782,Male,Loyal Customer,68,Personal Travel,Eco,1025,3,5,3,2,4,3,4,4,5,2,5,4,5,4,3,8.0,neutral or dissatisfied +31808,93381,Female,Loyal Customer,53,Business travel,Business,3170,1,1,1,1,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +31809,121800,Female,Loyal Customer,47,Business travel,Business,2011,4,4,4,4,4,4,4,4,3,5,5,4,3,4,181,174.0,satisfied +31810,39010,Male,Loyal Customer,42,Business travel,Eco,113,2,3,3,3,3,2,3,3,4,3,3,4,3,3,93,121.0,neutral or dissatisfied +31811,91772,Male,Loyal Customer,35,Business travel,Eco,584,5,3,3,3,5,4,5,5,2,1,1,4,2,5,0,0.0,satisfied +31812,32399,Female,Loyal Customer,33,Business travel,Business,163,1,1,3,1,4,1,1,4,4,4,4,4,4,4,0,6.0,satisfied +31813,48200,Male,Loyal Customer,18,Business travel,Business,391,1,1,1,1,2,2,2,2,2,2,5,5,3,2,0,0.0,satisfied +31814,56692,Female,Loyal Customer,23,Personal Travel,Eco,1065,2,4,2,3,2,2,2,2,4,3,5,4,5,2,12,0.0,neutral or dissatisfied +31815,33196,Female,Loyal Customer,63,Business travel,Eco Plus,163,4,2,2,2,5,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +31816,37016,Male,Loyal Customer,11,Personal Travel,Eco,814,3,2,3,3,4,3,4,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +31817,58750,Male,disloyal Customer,9,Business travel,Eco,1005,1,2,2,3,4,2,4,4,2,4,4,1,3,4,100,76.0,neutral or dissatisfied +31818,92582,Female,Loyal Customer,52,Business travel,Business,2139,1,1,2,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +31819,52170,Female,Loyal Customer,43,Business travel,Business,451,1,1,1,1,2,1,2,5,5,5,5,4,5,4,0,2.0,satisfied +31820,22114,Male,Loyal Customer,53,Business travel,Business,2349,3,3,3,3,5,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +31821,444,Male,Loyal Customer,48,Personal Travel,Business,247,5,5,5,1,3,5,4,3,3,5,3,4,3,4,27,32.0,satisfied +31822,129418,Female,Loyal Customer,39,Business travel,Business,414,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,4.0,satisfied +31823,117720,Female,Loyal Customer,45,Business travel,Business,3343,5,5,5,5,2,5,4,4,4,4,4,3,4,3,27,29.0,satisfied +31824,121714,Male,Loyal Customer,29,Personal Travel,Eco,683,2,1,2,3,4,2,4,4,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +31825,24390,Male,Loyal Customer,35,Personal Travel,Eco,669,2,5,2,5,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +31826,62100,Male,disloyal Customer,20,Business travel,Business,2454,4,4,5,4,3,5,3,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +31827,9839,Male,Loyal Customer,49,Business travel,Business,2778,2,2,2,2,3,5,4,5,5,5,5,5,5,3,5,0.0,satisfied +31828,31689,Female,Loyal Customer,14,Business travel,Eco,846,3,5,2,2,3,3,1,3,4,2,3,4,4,3,16,10.0,neutral or dissatisfied +31829,99394,Female,Loyal Customer,52,Business travel,Business,2794,0,0,0,3,3,5,5,5,5,5,5,5,5,3,0,8.0,satisfied +31830,68080,Male,Loyal Customer,60,Business travel,Business,2131,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +31831,83265,Female,Loyal Customer,31,Business travel,Business,1956,1,2,2,2,1,1,1,1,3,1,3,3,3,1,22,27.0,neutral or dissatisfied +31832,13204,Male,Loyal Customer,34,Business travel,Eco Plus,419,3,3,2,3,3,2,3,3,2,4,2,1,3,3,3,0.0,neutral or dissatisfied +31833,69789,Male,Loyal Customer,44,Business travel,Business,1055,3,3,1,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +31834,110981,Male,Loyal Customer,60,Business travel,Business,3570,5,5,5,5,3,5,5,5,5,5,5,4,5,4,0,20.0,satisfied +31835,11782,Female,Loyal Customer,34,Personal Travel,Eco,429,2,4,2,2,4,2,4,4,3,3,5,2,1,4,0,18.0,neutral or dissatisfied +31836,85501,Male,Loyal Customer,60,Personal Travel,Eco,332,1,4,1,5,3,1,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +31837,28388,Male,Loyal Customer,32,Personal Travel,Eco,763,3,4,3,2,2,3,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +31838,121513,Female,Loyal Customer,25,Personal Travel,Eco,1727,2,1,2,3,1,2,1,1,2,1,2,4,3,1,2,11.0,neutral or dissatisfied +31839,4931,Female,Loyal Customer,43,Business travel,Business,1870,0,0,0,4,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +31840,79618,Female,Loyal Customer,57,Business travel,Business,3131,1,1,1,1,2,5,5,5,5,5,5,3,5,4,24,0.0,satisfied +31841,55493,Male,Loyal Customer,36,Business travel,Business,1739,3,4,4,4,1,3,3,3,3,2,3,3,3,2,126,92.0,neutral or dissatisfied +31842,56685,Male,Loyal Customer,34,Personal Travel,Eco,1065,3,4,2,3,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +31843,129051,Male,Loyal Customer,44,Business travel,Business,1846,4,2,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +31844,125243,Female,disloyal Customer,22,Business travel,Eco Plus,1149,1,1,0,2,4,0,4,4,2,2,2,2,3,4,0,6.0,neutral or dissatisfied +31845,67193,Female,Loyal Customer,10,Personal Travel,Eco,929,3,5,3,4,5,3,5,5,3,2,5,5,5,5,6,0.0,neutral or dissatisfied +31846,78247,Female,disloyal Customer,61,Business travel,Eco Plus,259,3,3,3,4,5,3,5,5,2,1,4,2,3,5,0,0.0,neutral or dissatisfied +31847,108332,Male,Loyal Customer,56,Business travel,Business,1750,3,3,3,3,4,5,4,4,4,4,4,5,4,4,44,26.0,satisfied +31848,75424,Male,disloyal Customer,22,Business travel,Eco,844,4,4,4,4,5,4,1,5,4,3,5,4,5,5,0,0.0,satisfied +31849,77132,Male,Loyal Customer,53,Personal Travel,Business,2105,3,1,2,1,3,1,2,5,5,2,5,2,5,3,21,33.0,neutral or dissatisfied +31850,77443,Male,Loyal Customer,40,Personal Travel,Eco Plus,590,3,5,3,3,4,3,4,4,3,5,4,4,4,4,1,12.0,neutral or dissatisfied +31851,31907,Female,Loyal Customer,34,Business travel,Business,3803,5,5,5,5,3,4,4,5,5,5,4,4,5,5,9,8.0,satisfied +31852,84257,Female,Loyal Customer,36,Personal Travel,Eco,1814,2,4,2,1,2,2,2,2,5,5,3,5,4,2,0,5.0,neutral or dissatisfied +31853,1567,Female,Loyal Customer,52,Business travel,Business,3841,5,5,5,5,2,5,4,5,5,5,5,3,5,3,39,42.0,satisfied +31854,27073,Female,Loyal Customer,29,Business travel,Eco Plus,1399,5,4,4,4,5,5,5,5,5,4,1,1,3,5,0,0.0,satisfied +31855,86914,Male,disloyal Customer,29,Business travel,Eco,341,4,3,4,4,1,4,1,1,3,4,1,5,1,1,10,0.0,satisfied +31856,45693,Female,Loyal Customer,31,Personal Travel,Eco,896,4,1,4,2,2,4,2,2,4,4,3,4,2,2,0,0.0,satisfied +31857,28493,Male,Loyal Customer,27,Business travel,Business,2677,2,2,2,2,5,5,5,5,5,3,4,5,4,5,33,0.0,satisfied +31858,63038,Female,Loyal Customer,55,Business travel,Business,3860,5,5,5,5,1,3,2,4,4,5,4,1,4,2,0,0.0,satisfied +31859,51077,Female,Loyal Customer,43,Personal Travel,Eco,86,2,4,2,5,4,5,4,1,1,2,3,5,1,3,0,0.0,neutral or dissatisfied +31860,26491,Male,Loyal Customer,27,Business travel,Business,3325,4,4,4,4,4,4,4,4,5,1,3,2,5,4,0,0.0,satisfied +31861,10371,Female,Loyal Customer,41,Business travel,Business,247,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +31862,43289,Male,Loyal Customer,31,Business travel,Business,1858,2,2,5,2,3,4,3,3,2,2,1,3,1,3,0,0.0,satisfied +31863,62742,Female,disloyal Customer,26,Business travel,Eco,2615,3,3,3,3,3,5,5,1,1,2,2,5,4,5,0,7.0,neutral or dissatisfied +31864,104819,Male,disloyal Customer,42,Business travel,Business,426,3,3,3,2,4,3,5,4,4,4,2,4,3,4,2,0.0,neutral or dissatisfied +31865,42643,Male,Loyal Customer,22,Personal Travel,Eco,481,1,1,5,4,4,5,4,4,2,2,3,2,3,4,120,122.0,neutral or dissatisfied +31866,4171,Female,Loyal Customer,53,Personal Travel,Eco,427,3,4,3,4,3,2,3,4,4,3,4,1,4,4,0,11.0,neutral or dissatisfied +31867,96136,Male,disloyal Customer,40,Business travel,Business,460,1,2,2,3,5,2,5,5,4,1,4,4,3,5,0,0.0,neutral or dissatisfied +31868,22899,Female,Loyal Customer,85,Business travel,Eco Plus,147,4,4,4,4,4,4,4,2,1,3,4,4,1,4,3,0.0,neutral or dissatisfied +31869,33064,Female,Loyal Customer,11,Personal Travel,Eco,101,3,5,3,2,2,3,2,2,5,3,1,3,4,2,0,0.0,neutral or dissatisfied +31870,114196,Male,Loyal Customer,53,Business travel,Eco,819,2,1,1,1,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +31871,111578,Female,Loyal Customer,22,Personal Travel,Eco,359,4,5,4,4,3,4,3,3,5,3,4,3,4,3,34,38.0,neutral or dissatisfied +31872,19299,Female,Loyal Customer,28,Business travel,Business,3024,0,0,0,3,3,3,1,3,1,4,5,4,4,3,0,0.0,satisfied +31873,50693,Male,Loyal Customer,15,Personal Travel,Eco,326,3,3,3,1,3,3,3,3,2,3,4,3,5,3,0,24.0,neutral or dissatisfied +31874,7210,Male,Loyal Customer,49,Business travel,Business,135,2,2,2,2,2,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +31875,66098,Male,Loyal Customer,57,Business travel,Business,583,1,1,1,1,2,5,5,4,4,4,4,4,4,4,0,9.0,satisfied +31876,40460,Female,Loyal Customer,53,Business travel,Eco,188,2,4,4,4,1,3,3,2,2,2,2,2,2,1,0,16.0,neutral or dissatisfied +31877,63730,Female,Loyal Customer,36,Business travel,Business,160,1,1,4,1,2,4,3,2,2,2,1,4,2,4,0,6.0,neutral or dissatisfied +31878,126307,Female,Loyal Customer,56,Personal Travel,Eco,468,3,5,3,3,3,4,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +31879,5122,Female,Loyal Customer,49,Business travel,Eco Plus,235,1,1,1,1,3,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +31880,94897,Male,Loyal Customer,36,Business travel,Business,162,1,1,1,1,1,1,1,3,5,3,4,1,1,1,232,232.0,neutral or dissatisfied +31881,62743,Female,Loyal Customer,47,Business travel,Business,2504,2,5,2,2,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +31882,122768,Female,Loyal Customer,57,Business travel,Business,1801,3,3,3,3,2,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +31883,107390,Female,disloyal Customer,23,Business travel,Business,717,5,0,5,1,4,5,4,4,4,5,5,3,5,4,5,0.0,satisfied +31884,20010,Female,Loyal Customer,18,Personal Travel,Eco,599,2,5,2,3,4,2,4,4,4,2,3,5,4,4,1,7.0,neutral or dissatisfied +31885,5429,Male,Loyal Customer,43,Business travel,Business,265,5,5,5,5,4,4,4,3,3,5,4,4,3,4,209,224.0,satisfied +31886,122214,Male,Loyal Customer,43,Business travel,Eco,541,3,5,5,5,3,3,3,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +31887,31477,Male,Loyal Customer,30,Business travel,Business,3980,3,3,1,3,3,3,3,3,3,2,4,1,2,3,15,17.0,satisfied +31888,72393,Female,disloyal Customer,25,Business travel,Business,1121,3,0,3,2,1,3,1,1,4,3,5,4,4,1,23,12.0,neutral or dissatisfied +31889,23948,Female,Loyal Customer,56,Business travel,Eco,936,3,1,1,1,1,4,3,3,3,3,3,1,3,1,66,57.0,satisfied +31890,99686,Male,disloyal Customer,34,Business travel,Business,442,2,2,2,3,2,2,2,2,3,5,5,4,5,2,0,2.0,neutral or dissatisfied +31891,114493,Female,Loyal Customer,54,Business travel,Business,2217,5,5,5,5,2,5,4,3,3,4,3,4,3,4,9,11.0,satisfied +31892,6796,Male,Loyal Customer,20,Business travel,Business,235,4,2,2,2,4,4,4,4,1,5,4,3,4,4,26,16.0,neutral or dissatisfied +31893,51155,Female,Loyal Customer,15,Personal Travel,Eco,209,2,3,2,3,4,2,3,4,4,4,2,2,2,4,12,0.0,neutral or dissatisfied +31894,81911,Female,Loyal Customer,49,Business travel,Eco Plus,280,4,2,2,2,5,4,5,4,4,4,4,2,4,1,22,3.0,satisfied +31895,27140,Female,disloyal Customer,25,Business travel,Eco,1260,2,2,2,4,2,1,1,3,1,4,3,1,5,1,0,0.0,neutral or dissatisfied +31896,95948,Female,Loyal Customer,52,Business travel,Business,1549,1,1,1,1,2,5,4,5,5,5,5,4,5,3,22,22.0,satisfied +31897,14283,Male,Loyal Customer,39,Business travel,Eco,395,4,2,2,2,4,4,4,4,1,4,3,1,3,4,1,0.0,satisfied +31898,29672,Female,Loyal Customer,28,Business travel,Eco Plus,680,5,2,2,2,5,5,5,5,5,5,4,2,3,5,7,2.0,satisfied +31899,113183,Male,disloyal Customer,24,Business travel,Eco,277,4,2,4,1,2,4,2,2,1,3,2,3,1,2,0,0.0,neutral or dissatisfied +31900,71131,Male,disloyal Customer,36,Business travel,Eco,239,3,5,3,4,3,3,4,3,4,3,2,1,3,3,2,0.0,neutral or dissatisfied +31901,51192,Female,disloyal Customer,26,Business travel,Eco Plus,337,3,3,3,2,3,3,3,3,5,4,5,1,2,3,0,8.0,neutral or dissatisfied +31902,6974,Male,disloyal Customer,27,Business travel,Business,436,1,1,1,4,4,1,5,4,4,4,5,5,4,4,6,79.0,neutral or dissatisfied +31903,31276,Female,Loyal Customer,16,Business travel,Business,1721,1,4,4,4,1,1,1,1,3,2,4,4,3,1,45,39.0,neutral or dissatisfied +31904,102186,Female,Loyal Customer,34,Business travel,Business,236,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +31905,13173,Male,Loyal Customer,41,Business travel,Business,542,2,2,2,2,3,4,4,4,4,5,4,3,4,3,53,59.0,satisfied +31906,78420,Female,Loyal Customer,49,Personal Travel,Eco,453,3,3,1,4,2,1,2,2,2,1,4,2,2,5,0,3.0,neutral or dissatisfied +31907,112338,Male,disloyal Customer,45,Business travel,Business,909,5,5,5,1,3,5,3,3,3,4,5,5,5,3,0,6.0,satisfied +31908,63444,Male,Loyal Customer,56,Personal Travel,Eco,337,3,5,3,3,3,3,4,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +31909,15690,Female,Loyal Customer,38,Personal Travel,Eco,335,5,5,5,3,1,5,1,1,4,3,4,4,5,1,0,0.0,satisfied +31910,82829,Male,disloyal Customer,20,Business travel,Eco,594,0,0,0,4,5,0,5,5,5,2,5,5,5,5,11,2.0,satisfied +31911,106917,Female,Loyal Customer,24,Business travel,Business,3675,3,3,2,2,3,3,3,3,1,2,4,4,4,3,10,15.0,neutral or dissatisfied +31912,106291,Male,Loyal Customer,50,Business travel,Eco Plus,689,1,0,0,3,3,1,1,3,2,3,4,1,4,3,24,13.0,neutral or dissatisfied +31913,44524,Female,Loyal Customer,33,Business travel,Business,157,2,4,4,4,1,4,4,1,1,2,2,3,1,4,0,0.0,neutral or dissatisfied +31914,54367,Female,Loyal Customer,49,Business travel,Eco Plus,1235,5,3,3,3,5,2,3,5,5,5,5,1,5,3,1,0.0,satisfied +31915,86212,Female,Loyal Customer,27,Business travel,Eco,356,2,4,4,4,2,2,2,2,4,1,4,2,3,2,1,6.0,neutral or dissatisfied +31916,37060,Male,disloyal Customer,47,Business travel,Business,1072,2,2,2,5,5,2,2,5,3,3,5,2,1,5,0,0.0,neutral or dissatisfied +31917,46934,Female,disloyal Customer,38,Business travel,Eco,266,2,4,3,3,2,3,2,2,4,2,3,3,3,2,42,22.0,neutral or dissatisfied +31918,125639,Male,Loyal Customer,31,Business travel,Business,2525,2,5,5,5,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +31919,43352,Male,disloyal Customer,36,Business travel,Business,347,3,4,4,3,5,4,5,5,3,4,4,3,4,5,0,20.0,neutral or dissatisfied +31920,52197,Female,Loyal Customer,53,Business travel,Eco,598,4,2,2,2,4,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +31921,115920,Male,Loyal Customer,47,Business travel,Eco,446,4,2,2,2,4,4,4,4,5,3,4,4,2,4,0,0.0,satisfied +31922,2039,Female,Loyal Customer,38,Business travel,Business,812,1,1,5,1,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +31923,60695,Male,disloyal Customer,25,Business travel,Eco,1605,1,1,1,4,2,1,1,2,4,2,3,3,4,2,9,0.0,neutral or dissatisfied +31924,12280,Female,disloyal Customer,25,Business travel,Eco,127,2,0,2,5,3,2,3,3,3,1,5,5,1,3,0,0.0,neutral or dissatisfied +31925,119605,Male,Loyal Customer,28,Personal Travel,Eco,1979,3,3,3,3,3,3,3,3,5,3,1,2,4,3,31,15.0,neutral or dissatisfied +31926,72994,Female,Loyal Customer,42,Business travel,Business,3593,2,2,2,2,1,4,5,5,5,5,5,2,5,1,1,13.0,satisfied +31927,15792,Female,disloyal Customer,27,Business travel,Eco,143,3,5,3,4,3,3,3,3,5,1,1,4,2,3,8,0.0,neutral or dissatisfied +31928,60520,Female,Loyal Customer,70,Personal Travel,Eco,862,3,5,3,5,4,4,4,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +31929,102962,Female,Loyal Customer,51,Business travel,Business,687,3,3,3,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +31930,31805,Female,Loyal Customer,33,Business travel,Business,2603,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +31931,27189,Female,disloyal Customer,38,Business travel,Eco Plus,2640,1,2,2,5,2,5,5,4,5,3,3,5,2,5,2,7.0,neutral or dissatisfied +31932,83604,Male,Loyal Customer,44,Business travel,Business,3797,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +31933,119375,Male,disloyal Customer,32,Business travel,Business,399,2,2,2,4,3,2,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +31934,125588,Male,Loyal Customer,44,Personal Travel,Business,1587,3,4,4,3,5,3,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +31935,80016,Male,Loyal Customer,48,Personal Travel,Eco,944,2,5,2,3,3,2,3,3,4,3,5,4,2,3,0,0.0,neutral or dissatisfied +31936,47194,Female,Loyal Customer,47,Business travel,Eco,554,3,3,3,3,5,3,3,3,3,3,3,4,3,1,0,0.0,satisfied +31937,119080,Male,Loyal Customer,39,Business travel,Business,2406,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +31938,102822,Male,Loyal Customer,22,Personal Travel,Eco,342,2,5,2,4,4,2,1,4,3,3,4,3,4,4,0,2.0,neutral or dissatisfied +31939,27397,Male,Loyal Customer,44,Business travel,Business,3031,3,3,3,3,4,3,3,5,5,5,5,3,5,4,0,2.0,satisfied +31940,41045,Male,Loyal Customer,57,Business travel,Eco,686,4,1,1,1,4,4,4,4,5,4,4,3,1,4,0,9.0,satisfied +31941,110937,Female,Loyal Customer,48,Personal Travel,Eco,581,2,4,2,1,2,5,5,3,3,2,3,4,3,3,9,9.0,neutral or dissatisfied +31942,30171,Female,Loyal Customer,13,Personal Travel,Eco,261,3,2,0,3,3,0,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +31943,75938,Male,Loyal Customer,59,Business travel,Business,1572,1,1,1,1,5,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +31944,28523,Female,disloyal Customer,40,Business travel,Business,2688,3,3,3,3,1,3,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +31945,479,Male,disloyal Customer,28,Business travel,Business,309,4,4,4,1,1,4,1,1,5,3,4,3,5,1,0,11.0,neutral or dissatisfied +31946,17145,Male,Loyal Customer,23,Business travel,Eco,926,4,5,2,5,4,4,5,4,1,5,2,4,5,4,0,0.0,satisfied +31947,47962,Female,Loyal Customer,36,Personal Travel,Eco,846,1,4,1,2,5,1,5,5,1,4,1,1,2,5,0,0.0,neutral or dissatisfied +31948,7247,Female,Loyal Customer,9,Personal Travel,Eco,135,3,1,3,3,4,3,4,4,4,5,2,3,3,4,15,12.0,neutral or dissatisfied +31949,116899,Female,disloyal Customer,25,Business travel,Eco,646,2,3,2,4,4,2,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +31950,87237,Female,disloyal Customer,26,Business travel,Business,577,2,4,2,3,5,2,4,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +31951,91226,Male,Loyal Customer,44,Personal Travel,Eco,406,2,4,5,3,3,5,3,3,5,2,5,5,5,3,8,12.0,neutral or dissatisfied +31952,53523,Male,Loyal Customer,68,Personal Travel,Eco,2253,3,3,3,3,3,2,2,2,2,3,4,2,2,2,0,3.0,neutral or dissatisfied +31953,5048,Female,Loyal Customer,44,Business travel,Business,2937,0,0,0,4,2,4,4,1,1,1,1,5,1,4,20,71.0,satisfied +31954,9675,Male,disloyal Customer,23,Business travel,Business,277,3,4,3,3,4,3,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +31955,69044,Female,Loyal Customer,34,Business travel,Business,1391,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,3.0,satisfied +31956,101706,Female,Loyal Customer,54,Business travel,Business,1624,2,2,2,2,4,4,4,4,4,4,4,3,4,5,21,0.0,satisfied +31957,71398,Female,Loyal Customer,42,Business travel,Business,3019,3,3,3,3,5,4,4,4,4,4,4,3,4,5,1,4.0,satisfied +31958,47816,Female,disloyal Customer,36,Business travel,Eco,451,1,0,2,1,2,2,2,2,5,5,5,4,2,2,7,0.0,neutral or dissatisfied +31959,126563,Female,Loyal Customer,14,Business travel,Business,1558,3,3,3,3,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +31960,77251,Male,disloyal Customer,30,Business travel,Eco,1590,3,3,3,4,1,3,1,1,4,3,1,1,1,1,5,0.0,neutral or dissatisfied +31961,3134,Male,Loyal Customer,44,Business travel,Business,237,1,1,1,1,5,4,4,5,5,4,5,4,5,4,42,40.0,satisfied +31962,86763,Female,Loyal Customer,8,Personal Travel,Eco,821,1,5,1,3,1,1,1,1,4,5,4,5,4,1,5,5.0,neutral or dissatisfied +31963,26161,Female,Loyal Customer,50,Business travel,Eco,581,4,3,5,5,4,2,1,4,4,4,4,3,4,1,22,19.0,satisfied +31964,50200,Female,Loyal Customer,36,Business travel,Business,373,3,3,3,3,1,1,1,5,5,5,5,5,5,1,0,0.0,satisfied +31965,42445,Male,disloyal Customer,30,Business travel,Business,926,2,2,2,3,4,2,2,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +31966,68067,Female,Loyal Customer,59,Business travel,Business,1585,1,1,4,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +31967,66142,Female,Loyal Customer,7,Personal Travel,Eco,583,2,1,2,2,3,2,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +31968,72972,Female,Loyal Customer,26,Business travel,Business,1089,2,5,5,5,2,2,2,2,2,4,4,3,4,2,0,0.0,neutral or dissatisfied +31969,123805,Male,Loyal Customer,44,Business travel,Business,3346,2,2,2,2,4,5,5,5,5,5,5,3,5,3,10,26.0,satisfied +31970,107978,Male,Loyal Customer,42,Personal Travel,Eco,825,2,5,2,4,4,2,4,4,5,5,5,4,5,4,14,0.0,neutral or dissatisfied +31971,92940,Male,Loyal Customer,35,Personal Travel,Eco,151,3,5,3,4,4,3,1,4,4,3,5,3,5,4,0,7.0,neutral or dissatisfied +31972,56824,Female,Loyal Customer,56,Personal Travel,Eco,1728,3,5,3,2,1,4,5,5,5,3,5,1,5,2,18,14.0,neutral or dissatisfied +31973,58378,Female,Loyal Customer,36,Business travel,Business,1509,2,1,1,1,3,3,4,2,2,2,2,1,2,3,7,0.0,neutral or dissatisfied +31974,77035,Female,Loyal Customer,31,Personal Travel,Eco,368,4,4,4,4,3,4,3,3,3,5,4,2,4,3,0,0.0,satisfied +31975,96982,Male,disloyal Customer,35,Business travel,Eco,794,1,1,1,3,1,1,3,1,3,2,2,4,2,1,59,62.0,neutral or dissatisfied +31976,91737,Female,Loyal Customer,32,Business travel,Business,3301,5,5,5,5,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +31977,25861,Male,Loyal Customer,51,Personal Travel,Eco,692,1,4,1,2,3,1,3,3,5,5,4,5,4,3,13,29.0,neutral or dissatisfied +31978,107522,Female,Loyal Customer,50,Personal Travel,Eco,838,2,5,1,4,3,5,4,2,2,1,2,5,2,3,35,26.0,neutral or dissatisfied +31979,122260,Female,Loyal Customer,12,Personal Travel,Eco,546,4,4,4,4,1,4,1,1,5,5,5,2,4,1,0,0.0,neutral or dissatisfied +31980,13899,Female,disloyal Customer,21,Business travel,Eco,153,1,3,1,4,2,1,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +31981,54162,Male,Loyal Customer,19,Business travel,Business,1400,2,4,4,4,2,2,2,2,1,4,3,4,3,2,83,83.0,neutral or dissatisfied +31982,31710,Female,Loyal Customer,22,Personal Travel,Eco,853,3,5,3,3,4,3,4,4,3,3,5,3,4,4,2,4.0,neutral or dissatisfied +31983,77197,Female,disloyal Customer,49,Business travel,Business,290,4,4,4,5,5,4,5,5,4,5,5,4,4,5,0,0.0,satisfied +31984,122763,Female,disloyal Customer,22,Business travel,Eco,651,4,0,4,1,2,4,2,2,3,4,5,3,5,2,0,0.0,satisfied +31985,40023,Female,disloyal Customer,51,Business travel,Eco,525,3,1,3,3,4,3,4,4,4,2,2,3,3,4,0,0.0,neutral or dissatisfied +31986,35072,Male,Loyal Customer,37,Personal Travel,Business,828,1,5,1,1,4,5,5,4,4,1,4,3,4,3,4,18.0,neutral or dissatisfied +31987,19041,Female,Loyal Customer,55,Personal Travel,Eco Plus,788,2,4,2,4,3,4,4,5,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +31988,104322,Female,Loyal Customer,55,Business travel,Business,409,3,3,3,3,4,5,5,4,4,4,4,5,4,4,7,13.0,satisfied +31989,32179,Male,Loyal Customer,46,Business travel,Eco,102,4,4,4,4,4,4,4,4,2,1,4,2,1,4,0,1.0,satisfied +31990,114817,Male,Loyal Customer,41,Business travel,Business,372,5,5,4,5,2,4,4,4,4,5,4,4,4,5,25,19.0,satisfied +31991,23123,Female,Loyal Customer,23,Business travel,Business,3463,0,0,0,4,3,3,3,3,5,1,3,5,5,3,0,0.0,satisfied +31992,121003,Male,Loyal Customer,13,Personal Travel,Eco,951,3,4,3,4,3,4,1,1,3,3,1,1,2,1,255,252.0,neutral or dissatisfied +31993,81609,Male,Loyal Customer,65,Personal Travel,Eco,334,3,5,3,2,4,3,4,4,5,5,5,5,5,4,25,27.0,neutral or dissatisfied +31994,42535,Male,Loyal Customer,39,Personal Travel,Business,1091,4,2,4,3,2,3,2,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +31995,59938,Female,disloyal Customer,29,Business travel,Eco,1085,3,3,3,4,5,3,5,5,2,1,4,4,3,5,0,4.0,neutral or dissatisfied +31996,59618,Female,Loyal Customer,28,Business travel,Business,1575,2,1,1,1,2,1,2,2,4,5,4,2,3,2,27,28.0,neutral or dissatisfied +31997,27422,Female,Loyal Customer,23,Business travel,Business,2438,1,5,4,5,1,1,1,1,4,1,3,2,4,1,1,0.0,neutral or dissatisfied +31998,11310,Female,Loyal Customer,51,Personal Travel,Eco,247,1,5,1,4,5,4,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +31999,18801,Male,Loyal Customer,36,Business travel,Eco,551,4,3,4,4,4,4,4,4,5,1,2,5,2,4,0,0.0,satisfied +32000,110336,Male,Loyal Customer,43,Business travel,Business,787,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +32001,38215,Male,Loyal Customer,20,Business travel,Eco Plus,1091,3,1,1,1,3,3,2,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +32002,16615,Male,Loyal Customer,59,Personal Travel,Eco,1008,2,5,2,3,5,2,5,5,3,4,5,3,5,5,27,17.0,neutral or dissatisfied +32003,113664,Female,Loyal Customer,37,Personal Travel,Eco,391,2,1,2,2,3,2,3,3,1,2,2,2,2,3,8,0.0,neutral or dissatisfied +32004,113473,Female,Loyal Customer,62,Business travel,Business,1695,2,2,2,2,2,5,4,5,5,5,5,5,5,3,119,126.0,satisfied +32005,61885,Male,Loyal Customer,30,Business travel,Eco,2521,0,0,0,3,3,0,3,3,2,4,5,5,4,3,2,0.0,satisfied +32006,126315,Male,Loyal Customer,50,Personal Travel,Eco,328,1,0,1,4,4,1,4,4,5,4,5,4,4,4,19,29.0,neutral or dissatisfied +32007,100161,Female,disloyal Customer,27,Business travel,Eco,717,3,3,3,4,4,3,4,4,1,3,4,2,1,4,0,0.0,neutral or dissatisfied +32008,29309,Male,Loyal Customer,67,Personal Travel,Eco,550,1,4,0,4,2,0,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +32009,41463,Female,disloyal Customer,22,Business travel,Eco,1027,5,5,5,2,4,5,4,4,4,1,1,3,4,4,22,19.0,satisfied +32010,50785,Female,Loyal Customer,41,Personal Travel,Eco,190,4,5,4,3,2,4,2,2,4,5,5,5,4,2,4,0.0,neutral or dissatisfied +32011,91361,Female,Loyal Customer,60,Personal Travel,Eco Plus,250,3,4,3,4,4,4,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +32012,80623,Female,Loyal Customer,41,Business travel,Eco Plus,236,1,2,2,2,3,3,3,1,1,1,1,2,1,3,0,17.0,neutral or dissatisfied +32013,47365,Female,Loyal Customer,25,Business travel,Business,3815,4,4,4,4,5,5,5,5,3,5,2,4,2,5,0,0.0,satisfied +32014,22318,Female,Loyal Customer,34,Business travel,Business,1644,0,4,0,3,1,4,2,5,5,5,5,5,5,5,0,0.0,satisfied +32015,79333,Male,Loyal Customer,56,Business travel,Business,3750,5,5,5,5,2,5,4,3,3,3,3,3,3,3,0,1.0,satisfied +32016,31128,Female,Loyal Customer,32,Business travel,Eco,991,2,1,1,1,2,2,2,2,3,2,2,3,2,2,86,117.0,neutral or dissatisfied +32017,104653,Female,Loyal Customer,23,Personal Travel,Eco Plus,1754,3,4,4,2,3,4,4,3,4,2,4,4,3,3,7,1.0,neutral or dissatisfied +32018,21726,Female,Loyal Customer,51,Business travel,Business,2199,5,5,5,5,4,2,1,5,5,5,5,1,5,1,0,0.0,satisfied +32019,4867,Male,Loyal Customer,54,Personal Travel,Eco,408,2,1,2,3,4,2,4,4,4,4,4,4,4,4,6,11.0,neutral or dissatisfied +32020,111635,Male,Loyal Customer,50,Business travel,Business,1558,1,1,1,1,4,5,5,4,4,4,4,5,4,5,73,63.0,satisfied +32021,40164,Female,Loyal Customer,43,Business travel,Business,1729,0,0,0,2,1,2,2,1,1,1,1,5,1,1,0,0.0,satisfied +32022,100535,Female,Loyal Customer,9,Personal Travel,Eco,580,2,4,2,4,2,2,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +32023,118920,Male,Loyal Customer,61,Personal Travel,Eco,587,4,2,4,3,5,4,5,5,3,4,4,1,3,5,42,41.0,neutral or dissatisfied +32024,26592,Male,Loyal Customer,36,Business travel,Business,515,1,1,1,1,2,3,5,5,5,4,5,4,5,2,0,0.0,satisfied +32025,65574,Female,disloyal Customer,21,Business travel,Eco,175,1,0,1,4,1,1,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +32026,126545,Female,Loyal Customer,52,Business travel,Business,3096,4,4,4,4,4,2,5,4,4,4,4,5,4,3,0,0.0,satisfied +32027,40116,Female,Loyal Customer,51,Business travel,Business,2924,2,2,2,2,5,5,1,5,5,5,4,2,5,1,0,0.0,satisfied +32028,116821,Female,Loyal Customer,42,Business travel,Business,1689,4,4,4,4,2,5,4,4,4,4,4,5,4,3,58,52.0,satisfied +32029,7987,Male,disloyal Customer,26,Business travel,Business,125,4,0,4,1,1,4,1,1,3,4,4,5,5,1,0,0.0,satisfied +32030,56190,Male,Loyal Customer,36,Personal Travel,Eco,1400,4,3,4,3,4,4,4,4,1,4,2,1,2,4,26,3.0,neutral or dissatisfied +32031,62887,Male,Loyal Customer,41,Business travel,Business,846,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +32032,84065,Female,disloyal Customer,20,Business travel,Eco,773,2,2,2,4,3,2,3,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +32033,106500,Female,Loyal Customer,40,Business travel,Business,1630,2,2,2,2,4,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +32034,89009,Female,Loyal Customer,36,Business travel,Business,1892,5,5,5,5,3,5,5,4,4,4,4,4,4,4,0,8.0,satisfied +32035,101170,Male,disloyal Customer,19,Business travel,Eco,1235,2,2,2,2,4,2,3,4,1,5,2,1,2,4,82,59.0,neutral or dissatisfied +32036,93510,Female,disloyal Customer,25,Business travel,Eco Plus,1107,2,3,2,3,5,2,5,5,2,2,3,4,3,5,32,32.0,neutral or dissatisfied +32037,8338,Female,Loyal Customer,15,Business travel,Business,661,2,2,2,2,5,5,5,5,5,3,5,3,5,5,0,0.0,satisfied +32038,20703,Male,Loyal Customer,49,Personal Travel,Eco,584,2,5,2,3,4,2,4,4,3,5,4,4,4,4,2,2.0,neutral or dissatisfied +32039,31417,Female,Loyal Customer,45,Business travel,Business,1546,1,1,1,1,3,5,5,5,5,5,5,2,5,2,38,30.0,satisfied +32040,93434,Male,disloyal Customer,21,Business travel,Eco,605,2,4,2,4,5,2,5,5,4,2,3,3,4,5,23,19.0,neutral or dissatisfied +32041,12799,Female,Loyal Customer,28,Business travel,Business,3102,5,5,5,5,3,4,3,3,3,2,5,3,3,3,38,36.0,satisfied +32042,39570,Male,Loyal Customer,18,Business travel,Business,3581,2,2,2,2,5,5,5,5,1,5,2,3,4,5,0,2.0,satisfied +32043,50593,Female,Loyal Customer,36,Personal Travel,Eco,110,3,1,3,2,2,3,2,2,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +32044,7085,Male,disloyal Customer,44,Business travel,Business,273,2,2,2,4,5,2,5,5,3,3,4,3,4,5,11,11.0,neutral or dissatisfied +32045,105023,Female,disloyal Customer,22,Business travel,Business,255,0,0,0,1,5,0,5,5,5,3,4,3,5,5,0,0.0,satisfied +32046,4709,Female,disloyal Customer,24,Business travel,Business,364,5,0,5,5,4,5,4,4,3,3,5,3,4,4,64,76.0,satisfied +32047,107804,Female,Loyal Customer,55,Business travel,Business,349,0,0,0,5,2,5,4,1,1,1,1,3,1,4,1,0.0,satisfied +32048,3955,Female,Loyal Customer,59,Business travel,Business,2914,4,4,4,4,1,1,5,5,5,5,5,5,5,3,0,0.0,satisfied +32049,89198,Male,Loyal Customer,23,Personal Travel,Eco,1919,3,4,3,2,1,3,1,1,4,4,4,3,4,1,0,7.0,neutral or dissatisfied +32050,64509,Female,disloyal Customer,23,Business travel,Eco,354,2,4,2,4,5,2,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +32051,64362,Female,Loyal Customer,59,Business travel,Business,1192,2,2,2,2,2,4,3,2,2,2,2,1,2,1,1,0.0,neutral or dissatisfied +32052,113750,Male,Loyal Customer,30,Personal Travel,Eco,386,4,1,4,3,2,4,2,2,3,5,4,2,4,2,8,1.0,neutral or dissatisfied +32053,35856,Female,disloyal Customer,19,Business travel,Eco,937,4,4,4,3,1,4,1,1,3,3,3,3,4,1,0,30.0,neutral or dissatisfied +32054,65657,Male,disloyal Customer,26,Business travel,Business,1021,0,0,0,1,3,0,5,3,3,5,4,3,4,3,0,0.0,satisfied +32055,64663,Female,Loyal Customer,56,Business travel,Business,3756,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +32056,23110,Female,Loyal Customer,58,Business travel,Business,300,4,4,3,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +32057,76430,Female,disloyal Customer,36,Business travel,Eco,405,2,3,2,3,1,2,1,1,2,2,4,2,4,1,0,0.0,neutral or dissatisfied +32058,530,Female,Loyal Customer,54,Business travel,Business,1665,0,0,0,4,3,5,5,1,1,1,1,4,1,4,0,0.0,satisfied +32059,60145,Female,disloyal Customer,21,Business travel,Eco,1005,2,2,2,1,2,2,2,2,2,5,4,3,4,2,1,0.0,neutral or dissatisfied +32060,16338,Female,Loyal Customer,58,Personal Travel,Eco,628,1,4,1,3,2,3,5,2,2,1,2,5,2,5,95,88.0,neutral or dissatisfied +32061,980,Male,Loyal Customer,53,Business travel,Business,3852,1,5,5,5,1,3,3,2,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +32062,118071,Female,Loyal Customer,68,Business travel,Eco Plus,1044,3,2,5,2,2,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +32063,106539,Male,Loyal Customer,66,Personal Travel,Eco,321,2,4,1,3,3,1,3,3,1,1,3,3,4,3,6,0.0,neutral or dissatisfied +32064,120310,Female,Loyal Customer,48,Business travel,Eco,268,3,2,2,2,5,3,3,3,3,3,3,3,3,2,2,9.0,neutral or dissatisfied +32065,105866,Male,Loyal Customer,14,Personal Travel,Eco Plus,787,1,3,1,1,5,1,2,5,2,1,1,5,5,5,3,23.0,neutral or dissatisfied +32066,2617,Female,Loyal Customer,32,Personal Travel,Eco,304,1,4,1,2,2,1,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +32067,88564,Female,Loyal Customer,58,Personal Travel,Eco,406,1,2,5,4,5,4,4,5,5,5,5,3,5,4,10,0.0,neutral or dissatisfied +32068,42646,Male,Loyal Customer,18,Personal Travel,Eco,546,1,4,1,3,5,1,5,5,2,2,3,3,4,5,44,16.0,neutral or dissatisfied +32069,110302,Male,Loyal Customer,41,Business travel,Business,3455,2,2,2,2,4,4,5,5,5,5,5,4,5,5,18,7.0,satisfied +32070,58760,Female,Loyal Customer,44,Business travel,Business,3464,5,5,4,5,2,5,4,5,5,5,5,4,5,3,8,0.0,satisfied +32071,95219,Female,Loyal Customer,28,Personal Travel,Eco,319,1,5,2,1,4,2,4,4,1,1,5,5,4,4,0,0.0,neutral or dissatisfied +32072,70293,Female,Loyal Customer,33,Personal Travel,Eco,852,5,4,5,3,3,5,3,3,4,2,4,4,4,3,0,0.0,satisfied +32073,113881,Female,Loyal Customer,38,Personal Travel,Eco Plus,1592,1,5,0,3,4,0,4,4,3,5,4,5,5,4,26,21.0,neutral or dissatisfied +32074,6307,Female,Loyal Customer,12,Personal Travel,Business,296,3,3,3,3,4,3,4,4,2,1,4,2,3,4,0,0.0,neutral or dissatisfied +32075,59430,Male,Loyal Customer,56,Personal Travel,Eco Plus,2504,2,2,2,4,1,2,1,1,2,3,4,1,3,1,10,0.0,neutral or dissatisfied +32076,60488,Female,Loyal Customer,22,Business travel,Business,3685,2,2,3,2,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +32077,94461,Male,disloyal Customer,22,Business travel,Eco,239,5,0,5,4,4,5,4,4,4,3,4,4,4,4,0,0.0,satisfied +32078,121747,Male,Loyal Customer,39,Business travel,Business,1475,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +32079,39520,Female,Loyal Customer,46,Personal Travel,Eco,852,4,1,4,2,5,2,2,4,4,4,4,3,4,1,0,0.0,satisfied +32080,101937,Male,Loyal Customer,12,Business travel,Business,2807,3,3,3,3,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +32081,123411,Female,Loyal Customer,50,Business travel,Business,1337,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +32082,31086,Female,Loyal Customer,45,Business travel,Business,1014,2,2,2,2,5,2,2,5,5,5,5,1,5,1,16,25.0,satisfied +32083,9360,Female,Loyal Customer,44,Business travel,Eco,441,3,1,1,1,5,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +32084,59627,Male,Loyal Customer,23,Business travel,Business,1564,2,3,3,3,2,2,2,2,4,4,4,4,3,2,19,7.0,neutral or dissatisfied +32085,106669,Male,Loyal Customer,37,Personal Travel,Eco Plus,1590,2,1,2,2,1,2,1,1,2,4,3,4,3,1,12,20.0,neutral or dissatisfied +32086,65197,Female,Loyal Customer,58,Personal Travel,Eco,190,2,5,2,3,5,5,5,3,3,2,3,4,3,5,13,9.0,neutral or dissatisfied +32087,77378,Female,disloyal Customer,45,Business travel,Business,626,3,3,3,1,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +32088,10629,Female,Loyal Customer,32,Business travel,Business,1994,3,3,3,3,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +32089,74900,Female,Loyal Customer,51,Business travel,Business,2475,4,4,4,4,5,3,5,4,4,5,4,4,4,5,14,0.0,satisfied +32090,117568,Female,Loyal Customer,19,Business travel,Business,3945,4,1,1,1,4,4,4,4,2,4,4,3,4,4,7,5.0,neutral or dissatisfied +32091,36453,Female,disloyal Customer,35,Business travel,Business,867,2,1,1,1,3,1,3,3,3,2,1,3,2,3,6,17.0,neutral or dissatisfied +32092,18857,Male,Loyal Customer,25,Business travel,Business,551,3,3,2,3,4,4,4,4,5,1,4,2,4,4,0,0.0,satisfied +32093,115599,Male,Loyal Customer,22,Business travel,Business,404,5,5,5,5,3,4,3,3,3,5,4,4,5,3,1,0.0,satisfied +32094,101624,Female,Loyal Customer,19,Personal Travel,Eco,1371,3,5,3,3,2,3,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +32095,107976,Male,Loyal Customer,64,Personal Travel,Eco,825,3,4,3,1,4,3,5,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +32096,106318,Male,disloyal Customer,36,Business travel,Eco Plus,598,3,3,3,3,3,3,3,3,3,5,4,3,3,3,2,0.0,neutral or dissatisfied +32097,58179,Female,Loyal Customer,50,Business travel,Business,3493,3,3,3,3,4,5,5,3,3,3,3,5,3,5,70,101.0,satisfied +32098,103436,Male,Loyal Customer,59,Business travel,Business,2000,4,4,4,4,4,5,4,5,5,5,5,5,5,5,24,7.0,satisfied +32099,8349,Male,disloyal Customer,25,Business travel,Eco,383,1,2,1,3,3,1,3,3,3,4,3,4,4,3,6,1.0,neutral or dissatisfied +32100,120621,Male,Loyal Customer,47,Business travel,Business,280,5,5,5,5,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +32101,86673,Female,Loyal Customer,20,Personal Travel,Eco Plus,746,1,4,1,4,5,1,5,5,4,5,3,3,3,5,14,7.0,neutral or dissatisfied +32102,104254,Male,Loyal Customer,50,Personal Travel,Eco,1276,4,4,3,3,5,3,5,5,3,4,3,3,4,5,3,0.0,neutral or dissatisfied +32103,82742,Female,Loyal Customer,42,Business travel,Eco,409,3,4,4,4,4,2,2,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +32104,115937,Male,disloyal Customer,23,Business travel,Eco,296,0,2,0,3,3,0,3,3,5,2,1,4,3,3,0,0.0,satisfied +32105,74781,Male,Loyal Customer,35,Business travel,Business,1242,4,4,1,4,5,5,5,5,5,5,5,3,5,3,0,1.0,satisfied +32106,108420,Male,Loyal Customer,36,Business travel,Business,1444,4,4,4,4,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +32107,67456,Female,Loyal Customer,56,Personal Travel,Eco,641,3,2,3,2,4,2,3,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +32108,67576,Male,disloyal Customer,39,Business travel,Business,1235,2,2,2,1,1,2,3,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +32109,64702,Male,Loyal Customer,41,Business travel,Business,1560,5,5,5,5,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +32110,36690,Female,Loyal Customer,8,Personal Travel,Eco,1249,2,5,2,2,2,2,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +32111,126318,Female,Loyal Customer,45,Personal Travel,Eco,328,3,0,3,3,3,5,5,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +32112,93832,Male,Loyal Customer,40,Business travel,Business,391,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +32113,15654,Male,Loyal Customer,38,Business travel,Business,2163,3,2,4,2,3,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +32114,109702,Female,Loyal Customer,46,Business travel,Business,680,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +32115,28138,Female,disloyal Customer,26,Business travel,Eco,834,1,0,0,3,1,0,1,1,4,5,2,1,2,1,0,0.0,neutral or dissatisfied +32116,27191,Female,Loyal Customer,54,Business travel,Eco Plus,2677,1,3,5,5,1,1,1,4,4,2,3,1,1,1,0,15.0,neutral or dissatisfied +32117,13784,Female,Loyal Customer,63,Business travel,Eco,478,2,5,5,5,2,4,3,1,1,2,1,4,1,1,0,9.0,neutral or dissatisfied +32118,4936,Male,Loyal Customer,42,Business travel,Business,3445,3,3,3,3,3,2,2,3,3,3,3,3,3,2,3,8.0,neutral or dissatisfied +32119,27386,Male,Loyal Customer,26,Business travel,Business,2631,3,3,3,3,4,4,4,4,1,2,3,3,4,4,2,0.0,satisfied +32120,1730,Male,Loyal Customer,43,Business travel,Eco,489,2,2,2,2,2,2,2,2,3,5,3,5,3,2,36,32.0,satisfied +32121,54321,Female,Loyal Customer,25,Business travel,Business,1597,4,3,3,3,4,3,4,4,1,5,3,2,4,4,23,23.0,neutral or dissatisfied +32122,14603,Male,Loyal Customer,48,Personal Travel,Eco,986,2,4,2,1,5,2,5,5,4,3,5,4,4,5,42,42.0,neutral or dissatisfied +32123,63622,Female,disloyal Customer,39,Business travel,Business,1440,5,5,5,2,1,5,3,1,5,2,4,4,5,1,0,0.0,satisfied +32124,53410,Female,Loyal Customer,49,Business travel,Eco,2253,4,2,2,2,4,4,4,4,3,3,2,4,3,4,220,202.0,satisfied +32125,66882,Male,disloyal Customer,25,Business travel,Business,929,1,4,1,3,2,1,2,2,4,5,4,1,4,2,5,0.0,neutral or dissatisfied +32126,73850,Male,Loyal Customer,44,Business travel,Business,1810,5,5,5,5,5,3,4,2,2,2,2,4,2,3,0,0.0,satisfied +32127,6202,Female,Loyal Customer,54,Personal Travel,Eco Plus,409,1,5,1,1,4,5,5,1,1,1,3,3,1,3,75,73.0,neutral or dissatisfied +32128,51969,Male,Loyal Customer,37,Business travel,Business,347,5,5,5,5,2,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +32129,33207,Male,Loyal Customer,44,Business travel,Eco Plus,101,5,1,1,1,5,5,5,5,2,2,2,3,2,5,0,0.0,satisfied +32130,35137,Female,disloyal Customer,25,Business travel,Eco,1069,2,2,2,1,2,2,1,2,3,3,3,4,4,2,92,57.0,neutral or dissatisfied +32131,3256,Female,Loyal Customer,41,Business travel,Business,483,4,5,5,5,1,4,4,4,4,4,4,3,4,3,0,22.0,neutral or dissatisfied +32132,55834,Male,Loyal Customer,53,Business travel,Business,1416,4,5,5,5,1,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +32133,42205,Female,Loyal Customer,56,Business travel,Business,3391,5,5,5,5,4,3,3,4,4,4,4,5,4,1,31,15.0,satisfied +32134,79228,Male,Loyal Customer,57,Business travel,Business,1521,4,4,3,4,4,5,4,2,2,3,2,3,2,5,0,0.0,satisfied +32135,107873,Female,Loyal Customer,31,Personal Travel,Eco,228,4,5,4,3,2,4,1,2,4,2,5,5,5,2,49,55.0,neutral or dissatisfied +32136,124377,Female,Loyal Customer,56,Business travel,Eco,408,3,3,3,3,5,5,1,3,3,3,3,4,3,1,0,0.0,satisfied +32137,87325,Male,Loyal Customer,33,Business travel,Eco,1027,5,1,1,1,5,4,5,5,4,4,3,3,4,5,0,8.0,neutral or dissatisfied +32138,106113,Male,Loyal Customer,56,Business travel,Business,302,2,2,2,2,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +32139,5133,Female,Loyal Customer,16,Personal Travel,Eco Plus,235,3,4,3,2,4,3,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +32140,85069,Male,disloyal Customer,25,Business travel,Business,696,4,5,4,2,1,4,1,1,5,2,5,4,5,1,15,10.0,neutral or dissatisfied +32141,96655,Female,Loyal Customer,70,Personal Travel,Eco,972,2,4,2,1,5,5,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +32142,125313,Female,Loyal Customer,52,Business travel,Business,3252,2,2,2,2,3,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +32143,82803,Male,Loyal Customer,50,Business travel,Business,235,4,2,2,2,5,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +32144,61205,Male,Loyal Customer,49,Business travel,Business,862,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +32145,19615,Female,Loyal Customer,38,Personal Travel,Eco,416,2,2,2,3,3,2,3,3,1,2,3,2,3,3,26,15.0,neutral or dissatisfied +32146,96227,Female,Loyal Customer,69,Business travel,Business,1727,1,1,1,1,5,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +32147,1313,Male,Loyal Customer,45,Business travel,Business,354,4,4,2,4,2,4,5,5,5,5,5,5,5,4,0,9.0,satisfied +32148,25305,Male,Loyal Customer,60,Business travel,Business,2919,5,5,5,5,4,2,2,4,4,4,4,5,4,5,0,1.0,satisfied +32149,97060,Male,disloyal Customer,27,Business travel,Business,1390,4,4,4,3,5,4,5,5,5,2,4,5,5,5,12,0.0,satisfied +32150,31170,Male,Loyal Customer,53,Personal Travel,Eco,627,1,4,2,2,5,2,5,5,4,5,4,4,5,5,33,32.0,neutral or dissatisfied +32151,36301,Female,Loyal Customer,33,Business travel,Business,187,3,1,1,1,3,4,4,1,1,1,3,4,1,4,25,13.0,neutral or dissatisfied +32152,69028,Female,disloyal Customer,37,Business travel,Business,1389,3,3,3,4,5,3,5,5,5,5,5,5,4,5,21,26.0,neutral or dissatisfied +32153,85545,Male,disloyal Customer,40,Business travel,Business,259,2,2,2,4,2,2,2,2,4,5,5,4,4,2,1,0.0,neutral or dissatisfied +32154,113368,Female,disloyal Customer,24,Business travel,Business,407,4,0,5,2,2,5,2,2,5,3,4,3,5,2,29,22.0,satisfied +32155,95196,Female,Loyal Customer,33,Personal Travel,Eco,239,3,4,3,1,2,3,2,2,3,2,4,4,5,2,1,0.0,neutral or dissatisfied +32156,94001,Male,disloyal Customer,38,Business travel,Business,148,3,2,2,3,2,2,2,2,3,4,5,3,5,2,20,13.0,neutral or dissatisfied +32157,114336,Male,Loyal Customer,56,Personal Travel,Eco,853,4,4,4,3,5,4,5,5,4,4,4,3,5,5,1,0.0,satisfied +32158,83430,Female,Loyal Customer,65,Personal Travel,Eco,632,1,3,1,3,5,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +32159,72489,Male,Loyal Customer,39,Business travel,Business,1704,3,4,4,4,1,3,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +32160,38819,Female,Loyal Customer,11,Personal Travel,Eco,353,2,5,2,2,4,2,2,4,5,4,3,4,2,4,20,88.0,neutral or dissatisfied +32161,99831,Male,Loyal Customer,35,Business travel,Eco,468,3,1,1,1,3,2,3,3,2,4,3,3,4,3,12,8.0,neutral or dissatisfied +32162,43377,Female,Loyal Customer,21,Personal Travel,Eco,531,2,1,2,2,5,2,5,5,4,2,3,4,3,5,0,0.0,neutral or dissatisfied +32163,54645,Female,disloyal Customer,36,Business travel,Eco,787,1,1,1,4,2,1,2,2,1,2,4,4,2,2,60,51.0,neutral or dissatisfied +32164,113830,Male,Loyal Customer,8,Personal Travel,Eco Plus,197,1,5,1,5,5,1,5,5,5,1,2,1,1,5,0,0.0,neutral or dissatisfied +32165,91964,Female,Loyal Customer,9,Personal Travel,Eco,2586,1,3,1,2,1,1,1,1,1,3,2,3,3,1,0,0.0,neutral or dissatisfied +32166,107557,Male,Loyal Customer,23,Business travel,Business,1521,3,2,2,2,3,3,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +32167,118469,Female,disloyal Customer,22,Business travel,Business,370,5,5,5,3,4,5,3,4,4,2,4,3,4,4,0,0.0,satisfied +32168,32149,Male,Loyal Customer,48,Business travel,Eco,101,5,4,4,4,3,5,3,3,3,1,2,2,1,3,0,0.0,satisfied +32169,17946,Female,Loyal Customer,49,Personal Travel,Eco,95,2,3,2,1,3,1,2,1,1,2,1,1,1,2,0,6.0,neutral or dissatisfied +32170,56723,Female,Loyal Customer,68,Personal Travel,Eco,937,2,2,2,3,3,3,3,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +32171,91639,Male,Loyal Customer,55,Personal Travel,Eco,1340,0,4,1,4,4,1,4,4,1,2,4,2,4,4,0,0.0,satisfied +32172,109673,Male,Loyal Customer,39,Personal Travel,Eco,829,4,5,4,3,5,4,5,5,5,5,4,4,5,5,6,0.0,neutral or dissatisfied +32173,121495,Male,Loyal Customer,39,Business travel,Eco Plus,290,3,1,2,2,3,3,3,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +32174,115847,Male,disloyal Customer,19,Business travel,Eco,480,3,1,3,4,5,3,5,5,2,5,4,3,3,5,0,4.0,neutral or dissatisfied +32175,123569,Male,disloyal Customer,25,Business travel,Eco,1112,2,3,3,4,3,3,3,3,5,5,5,3,5,3,0,1.0,neutral or dissatisfied +32176,46715,Male,Loyal Customer,41,Personal Travel,Eco,73,3,5,3,4,2,3,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +32177,20026,Male,disloyal Customer,34,Business travel,Business,473,4,4,4,1,3,4,3,3,5,4,3,1,5,3,0,0.0,neutral or dissatisfied +32178,5300,Female,Loyal Customer,62,Personal Travel,Eco,293,3,1,3,4,1,3,3,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +32179,125112,Male,disloyal Customer,41,Business travel,Business,361,3,3,3,5,3,2,3,1,2,4,4,3,2,3,178,167.0,neutral or dissatisfied +32180,1484,Male,Loyal Customer,50,Business travel,Business,737,3,3,3,3,4,4,4,5,5,4,5,3,5,4,4,13.0,satisfied +32181,104314,Female,Loyal Customer,60,Business travel,Business,409,1,5,5,5,1,3,4,1,1,1,1,1,1,1,6,0.0,neutral or dissatisfied +32182,88419,Male,disloyal Customer,10,Business travel,Eco,594,1,2,1,3,5,1,5,5,2,5,4,2,3,5,21,12.0,neutral or dissatisfied +32183,52476,Male,Loyal Customer,46,Personal Travel,Eco Plus,370,2,2,2,4,2,2,2,2,3,1,4,1,4,2,60,47.0,neutral or dissatisfied +32184,82946,Male,Loyal Customer,50,Business travel,Business,2577,1,1,1,1,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +32185,32532,Female,Loyal Customer,37,Business travel,Eco,102,4,3,3,3,4,5,4,4,1,5,3,2,5,4,6,5.0,satisfied +32186,124017,Male,Loyal Customer,41,Business travel,Business,184,3,4,3,3,3,4,3,5,5,5,4,2,5,4,0,0.0,satisfied +32187,5837,Male,Loyal Customer,60,Business travel,Eco Plus,157,2,3,3,3,2,2,2,2,3,3,2,2,4,2,0,0.0,satisfied +32188,34778,Female,Loyal Customer,18,Personal Travel,Eco,264,4,2,4,3,2,4,2,2,1,5,3,4,3,2,1,3.0,neutral or dissatisfied +32189,81947,Male,disloyal Customer,36,Business travel,Business,1535,4,4,4,1,5,4,2,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +32190,36156,Male,disloyal Customer,40,Business travel,Business,174,4,4,4,4,2,4,2,2,3,5,4,2,3,2,6,0.0,neutral or dissatisfied +32191,83310,Male,disloyal Customer,20,Business travel,Eco,1367,4,4,4,4,4,4,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +32192,86823,Female,disloyal Customer,17,Business travel,Eco,692,2,3,3,2,5,3,5,5,3,5,4,3,5,5,1,0.0,neutral or dissatisfied +32193,56189,Female,Loyal Customer,65,Personal Travel,Eco,1504,1,5,1,4,2,5,2,2,2,1,2,3,2,4,14,3.0,neutral or dissatisfied +32194,52306,Male,Loyal Customer,32,Business travel,Business,2625,3,4,4,4,3,3,3,3,3,4,2,1,2,3,0,0.0,neutral or dissatisfied +32195,58532,Female,disloyal Customer,48,Business travel,Business,719,3,3,3,4,1,3,1,1,5,4,5,3,4,1,19,18.0,neutral or dissatisfied +32196,71114,Male,Loyal Customer,16,Personal Travel,Eco,2072,2,4,2,4,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +32197,61021,Female,Loyal Customer,21,Personal Travel,Eco,3365,0,2,0,4,5,0,5,5,4,1,4,2,3,5,20,,satisfied +32198,7699,Female,Loyal Customer,52,Personal Travel,Eco,767,1,4,1,1,4,4,4,4,4,1,4,3,4,4,13,23.0,neutral or dissatisfied +32199,123502,Female,disloyal Customer,37,Business travel,Eco,796,4,4,4,3,5,4,5,5,1,4,4,4,5,5,0,0.0,satisfied +32200,54821,Female,Loyal Customer,60,Business travel,Eco,794,3,4,4,4,2,5,2,3,3,3,3,3,3,3,0,11.0,satisfied +32201,45507,Male,Loyal Customer,54,Personal Travel,Eco Plus,522,2,5,2,3,2,2,2,2,4,4,4,3,5,2,38,52.0,neutral or dissatisfied +32202,118701,Male,Loyal Customer,34,Personal Travel,Eco,325,5,3,5,5,1,5,1,1,1,5,5,5,2,1,0,0.0,satisfied +32203,59593,Female,Loyal Customer,23,Business travel,Business,3376,4,5,5,5,4,3,4,4,3,4,3,2,3,4,6,0.0,neutral or dissatisfied +32204,118931,Female,Loyal Customer,55,Business travel,Business,1618,5,5,5,5,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +32205,70745,Male,Loyal Customer,56,Personal Travel,Eco,675,2,4,2,3,2,2,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +32206,91877,Male,Loyal Customer,56,Business travel,Business,1086,3,5,5,5,4,3,3,3,3,3,3,2,3,4,0,104.0,neutral or dissatisfied +32207,116218,Male,Loyal Customer,49,Personal Travel,Eco,333,2,5,2,3,3,2,3,3,3,4,4,5,5,3,29,13.0,neutral or dissatisfied +32208,28288,Female,Loyal Customer,44,Business travel,Business,2683,4,4,5,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +32209,128085,Male,Loyal Customer,9,Business travel,Business,2845,1,4,4,4,2,1,1,3,3,2,4,1,2,1,11,23.0,neutral or dissatisfied +32210,92440,Male,Loyal Customer,55,Business travel,Business,1947,5,5,5,5,4,3,4,4,4,4,4,4,4,5,34,20.0,satisfied +32211,48808,Female,Loyal Customer,40,Personal Travel,Business,109,3,4,3,3,1,4,3,4,4,3,5,2,4,4,0,0.0,neutral or dissatisfied +32212,83286,Female,Loyal Customer,8,Personal Travel,Eco,1979,3,2,3,4,5,3,5,5,2,4,3,2,4,5,80,64.0,neutral or dissatisfied +32213,20909,Female,Loyal Customer,25,Business travel,Eco,689,4,3,3,3,4,5,5,4,3,4,2,4,4,4,0,0.0,satisfied +32214,108239,Female,Loyal Customer,64,Business travel,Business,895,1,1,1,1,5,5,5,5,5,5,5,5,5,5,5,2.0,satisfied +32215,19574,Male,disloyal Customer,29,Business travel,Eco,173,2,3,2,3,5,2,1,5,4,3,3,3,3,5,0,0.0,neutral or dissatisfied +32216,41944,Male,disloyal Customer,30,Business travel,Business,575,4,4,4,3,2,4,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +32217,36126,Female,Loyal Customer,41,Business travel,Business,1562,4,4,4,4,4,4,4,3,5,2,4,4,4,4,286,262.0,satisfied +32218,25767,Male,Loyal Customer,50,Personal Travel,Eco Plus,356,3,4,3,1,1,3,1,1,1,2,4,5,2,1,0,0.0,neutral or dissatisfied +32219,129066,Male,Loyal Customer,42,Business travel,Business,1744,4,4,4,4,4,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +32220,80779,Male,disloyal Customer,20,Business travel,Eco,692,2,2,2,3,5,2,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +32221,15253,Female,Loyal Customer,34,Personal Travel,Eco,529,1,5,1,1,1,1,1,1,4,2,4,5,2,1,0,0.0,neutral or dissatisfied +32222,10989,Male,disloyal Customer,55,Business travel,Business,270,2,2,2,4,2,2,2,4,2,3,4,2,4,2,328,330.0,neutral or dissatisfied +32223,3500,Male,Loyal Customer,30,Personal Travel,Eco,990,3,5,3,5,4,3,4,4,4,5,5,4,4,4,2,4.0,neutral or dissatisfied +32224,18708,Female,Loyal Customer,68,Business travel,Eco Plus,201,4,1,1,1,1,1,3,4,4,4,4,4,4,5,15,14.0,satisfied +32225,10440,Female,Loyal Customer,73,Business travel,Business,3096,4,4,4,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +32226,15739,Male,Loyal Customer,48,Personal Travel,Eco,419,2,5,2,1,3,2,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +32227,58560,Male,Loyal Customer,40,Business travel,Eco Plus,1514,5,1,1,1,5,4,5,5,4,2,4,2,4,5,5,0.0,neutral or dissatisfied +32228,124926,Male,Loyal Customer,48,Business travel,Eco,328,3,1,1,1,3,3,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +32229,125291,Male,Loyal Customer,32,Business travel,Business,678,1,1,1,1,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +32230,43822,Male,disloyal Customer,39,Business travel,Eco,153,4,3,4,4,2,4,2,2,4,2,2,3,3,2,0,0.0,neutral or dissatisfied +32231,56322,Male,Loyal Customer,39,Business travel,Business,3752,4,4,4,4,5,4,4,4,4,5,5,5,4,3,0,0.0,satisfied +32232,100743,Male,Loyal Customer,52,Personal Travel,Eco,328,1,0,1,4,4,1,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +32233,610,Male,Loyal Customer,23,Business travel,Business,2557,3,3,3,3,5,5,4,5,5,3,4,4,4,5,1,5.0,satisfied +32234,36655,Male,Loyal Customer,55,Personal Travel,Eco,1121,2,5,2,2,4,2,4,4,3,4,4,5,4,4,13,0.0,neutral or dissatisfied +32235,118855,Female,Loyal Customer,7,Personal Travel,Eco Plus,647,2,4,2,2,2,2,2,2,2,1,5,2,4,2,6,0.0,neutral or dissatisfied +32236,59424,Female,Loyal Customer,45,Business travel,Business,2486,1,1,1,1,4,4,4,2,2,2,2,5,2,5,17,9.0,satisfied +32237,71079,Female,Loyal Customer,33,Personal Travel,Eco,802,2,2,2,4,2,2,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +32238,101358,Male,Loyal Customer,22,Business travel,Business,1986,2,2,2,2,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +32239,48668,Male,disloyal Customer,32,Business travel,Business,326,3,4,4,3,2,4,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +32240,122672,Male,disloyal Customer,37,Business travel,Business,361,5,5,5,1,3,5,3,3,3,3,5,3,5,3,0,0.0,satisfied +32241,9695,Male,Loyal Customer,66,Personal Travel,Eco,277,0,3,0,5,5,0,5,5,2,4,4,2,4,5,0,3.0,satisfied +32242,41346,Male,disloyal Customer,27,Business travel,Eco,956,4,4,4,3,3,4,3,3,4,3,3,1,5,3,0,0.0,neutral or dissatisfied +32243,79356,Male,Loyal Customer,70,Personal Travel,Eco,1020,1,0,1,1,4,1,4,4,4,2,5,5,4,4,38,32.0,neutral or dissatisfied +32244,99247,Male,Loyal Customer,70,Personal Travel,Eco,541,3,4,3,2,2,3,2,2,5,2,4,5,4,2,13,11.0,neutral or dissatisfied +32245,60619,Female,Loyal Customer,52,Business travel,Business,1201,1,1,4,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +32246,4589,Female,Loyal Customer,41,Business travel,Eco,416,1,3,3,3,1,1,1,1,3,4,2,4,2,1,0,0.0,neutral or dissatisfied +32247,98562,Male,Loyal Customer,9,Personal Travel,Business,834,5,5,5,4,3,5,3,3,5,5,4,5,5,3,6,3.0,satisfied +32248,111886,Male,Loyal Customer,25,Business travel,Business,228,1,2,4,4,1,1,1,1,4,3,1,3,2,1,0,0.0,neutral or dissatisfied +32249,51510,Female,Loyal Customer,36,Business travel,Eco,370,4,3,5,5,4,4,4,4,3,3,3,3,3,4,8,6.0,satisfied +32250,76483,Male,Loyal Customer,23,Business travel,Business,3285,1,1,1,1,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +32251,104883,Female,Loyal Customer,10,Personal Travel,Eco,327,2,0,2,3,4,2,4,4,3,4,4,3,4,4,14,6.0,neutral or dissatisfied +32252,44977,Female,Loyal Customer,49,Business travel,Business,2057,0,4,0,3,3,5,3,5,5,5,5,2,5,5,25,20.0,satisfied +32253,34884,Male,Loyal Customer,33,Personal Travel,Eco Plus,2248,1,4,1,5,2,1,2,2,4,4,4,5,4,2,23,21.0,neutral or dissatisfied +32254,111425,Female,Loyal Customer,41,Business travel,Eco,896,2,2,2,2,2,2,2,2,1,2,4,4,4,2,44,45.0,neutral or dissatisfied +32255,23929,Female,Loyal Customer,38,Personal Travel,Eco,589,2,2,2,3,4,2,4,4,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +32256,105162,Male,disloyal Customer,30,Business travel,Business,220,1,1,1,3,3,1,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +32257,112469,Male,Loyal Customer,76,Business travel,Eco,557,2,3,3,3,2,2,2,2,2,5,3,4,4,2,18,26.0,neutral or dissatisfied +32258,107153,Female,Loyal Customer,57,Business travel,Business,402,5,5,5,5,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +32259,101452,Female,Loyal Customer,55,Business travel,Business,345,3,3,3,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +32260,127991,Female,Loyal Customer,45,Business travel,Business,1488,5,5,5,5,4,5,5,5,5,5,5,4,5,5,10,3.0,satisfied +32261,124321,Male,Loyal Customer,26,Personal Travel,Eco,255,2,5,0,4,4,0,4,4,3,5,3,3,2,4,54,54.0,neutral or dissatisfied +32262,14902,Female,Loyal Customer,62,Personal Travel,Eco,343,3,4,3,5,5,4,5,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +32263,41996,Male,Loyal Customer,31,Business travel,Business,2478,3,3,3,3,5,5,4,5,5,4,1,3,3,5,0,0.0,satisfied +32264,13955,Female,Loyal Customer,41,Personal Travel,Eco,153,3,4,3,1,4,3,4,4,3,5,5,4,5,4,0,5.0,neutral or dissatisfied +32265,109054,Male,disloyal Customer,12,Business travel,Eco,957,3,3,3,3,4,3,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +32266,31733,Female,Loyal Customer,35,Personal Travel,Eco,862,4,3,4,3,5,4,5,5,3,3,4,4,3,5,12,2.0,neutral or dissatisfied +32267,33647,Male,Loyal Customer,56,Personal Travel,Eco,399,1,4,5,3,2,5,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +32268,94093,Female,Loyal Customer,42,Personal Travel,Business,293,1,5,1,1,4,5,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +32269,76727,Female,Loyal Customer,50,Business travel,Eco Plus,134,5,1,2,1,1,3,1,5,5,5,5,4,5,1,0,0.0,satisfied +32270,40187,Male,Loyal Customer,37,Business travel,Business,531,5,5,5,5,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +32271,31312,Female,Loyal Customer,28,Business travel,Business,1909,2,2,2,2,4,4,4,4,3,5,5,2,3,4,0,0.0,satisfied +32272,88959,Male,Loyal Customer,60,Business travel,Eco,1199,3,2,2,2,4,3,4,4,2,3,3,3,4,4,128,111.0,neutral or dissatisfied +32273,37770,Female,disloyal Customer,22,Business travel,Eco Plus,944,3,2,3,4,3,3,1,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +32274,57005,Male,Loyal Customer,18,Personal Travel,Eco,2454,3,4,3,4,3,4,4,5,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +32275,122584,Male,Loyal Customer,46,Business travel,Business,728,3,1,3,3,4,4,4,4,4,4,4,3,4,4,5,3.0,satisfied +32276,22693,Female,Loyal Customer,29,Business travel,Business,589,3,3,5,3,4,4,4,4,3,4,2,2,3,4,0,0.0,satisfied +32277,47446,Female,Loyal Customer,69,Business travel,Eco,132,3,4,4,4,5,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +32278,92144,Male,Loyal Customer,30,Business travel,Business,1589,2,2,2,2,4,5,4,4,4,4,4,5,4,4,56,32.0,satisfied +32279,92433,Female,Loyal Customer,51,Business travel,Business,1947,1,2,2,2,1,1,1,1,5,2,1,1,2,1,168,141.0,neutral or dissatisfied +32280,12689,Female,Loyal Customer,22,Business travel,Business,803,5,5,5,5,5,5,5,5,1,5,1,2,5,5,0,0.0,satisfied +32281,125339,Female,disloyal Customer,22,Business travel,Eco,599,4,0,4,3,4,4,4,4,4,4,5,4,4,4,4,42.0,satisfied +32282,129443,Female,Loyal Customer,48,Personal Travel,Eco,414,2,5,2,3,5,3,1,5,5,2,3,3,5,5,0,0.0,neutral or dissatisfied +32283,67747,Female,Loyal Customer,53,Business travel,Business,1464,1,1,1,1,4,4,4,3,2,4,4,4,5,4,172,168.0,satisfied +32284,124586,Male,Loyal Customer,55,Business travel,Business,500,1,5,5,5,1,2,3,1,1,1,1,4,1,4,0,27.0,neutral or dissatisfied +32285,73519,Female,Loyal Customer,46,Business travel,Business,594,3,1,5,5,2,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +32286,44350,Female,Loyal Customer,56,Personal Travel,Eco Plus,308,4,1,4,3,4,2,2,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +32287,90299,Male,Loyal Customer,14,Personal Travel,Eco,757,3,5,3,3,3,5,3,5,4,5,4,3,4,3,134,139.0,neutral or dissatisfied +32288,28150,Male,Loyal Customer,28,Business travel,Eco,834,2,5,2,5,2,2,2,2,4,1,2,3,3,2,0,0.0,neutral or dissatisfied +32289,73357,Male,Loyal Customer,68,Business travel,Business,1197,2,2,2,2,2,4,4,5,5,5,5,5,5,4,4,1.0,satisfied +32290,122150,Female,Loyal Customer,22,Business travel,Business,3408,1,1,1,1,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +32291,100776,Male,Loyal Customer,55,Personal Travel,Eco,1411,4,2,4,3,2,4,2,2,1,3,2,4,4,2,0,0.0,satisfied +32292,77526,Female,disloyal Customer,13,Business travel,Eco,1097,1,1,1,1,5,1,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +32293,41372,Female,Loyal Customer,47,Business travel,Eco,809,4,2,2,2,4,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +32294,129723,Female,Loyal Customer,58,Business travel,Eco,337,1,4,4,4,4,2,2,1,1,1,1,3,1,1,0,18.0,neutral or dissatisfied +32295,112188,Female,Loyal Customer,45,Personal Travel,Eco,895,1,3,1,1,5,1,1,4,4,1,4,5,4,1,52,71.0,neutral or dissatisfied +32296,98792,Male,disloyal Customer,23,Business travel,Eco,230,4,3,4,1,4,4,4,4,4,4,1,3,1,4,0,0.0,neutral or dissatisfied +32297,37680,Female,Loyal Customer,18,Personal Travel,Eco,1069,2,5,1,3,3,1,3,3,5,5,5,5,5,3,0,52.0,neutral or dissatisfied +32298,60990,Female,Loyal Customer,68,Personal Travel,Eco Plus,888,1,5,1,3,4,4,5,1,1,1,1,4,1,5,4,0.0,neutral or dissatisfied +32299,114433,Male,Loyal Customer,46,Business travel,Business,2912,3,3,3,3,4,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +32300,89790,Male,Loyal Customer,59,Personal Travel,Eco,1089,2,5,2,4,1,2,1,1,2,2,2,5,2,1,59,30.0,neutral or dissatisfied +32301,44575,Male,disloyal Customer,18,Business travel,Eco,157,1,2,1,3,4,1,4,4,2,5,4,2,4,4,43,78.0,neutral or dissatisfied +32302,54450,Male,disloyal Customer,27,Business travel,Eco,844,1,1,1,5,2,1,4,2,4,3,2,4,3,2,3,0.0,neutral or dissatisfied +32303,113949,Female,disloyal Customer,35,Business travel,Business,1855,3,3,3,1,2,3,2,2,3,4,4,3,4,2,11,8.0,neutral or dissatisfied +32304,21572,Female,Loyal Customer,61,Business travel,Eco Plus,331,2,2,3,2,5,4,4,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +32305,111727,Male,Loyal Customer,10,Business travel,Business,495,3,3,3,3,5,4,5,5,3,5,5,5,4,5,16,0.0,satisfied +32306,23528,Female,Loyal Customer,16,Personal Travel,Eco Plus,303,1,4,1,2,4,1,5,4,3,3,4,3,4,4,45,46.0,neutral or dissatisfied +32307,129450,Female,Loyal Customer,20,Personal Travel,Eco,414,2,4,2,4,1,2,1,1,4,4,3,1,4,1,112,103.0,neutral or dissatisfied +32308,83914,Male,Loyal Customer,28,Personal Travel,Eco,752,4,4,4,2,5,4,2,5,5,4,5,5,4,5,29,15.0,neutral or dissatisfied +32309,18858,Female,Loyal Customer,57,Business travel,Eco,551,5,1,1,1,1,3,5,5,5,5,5,1,5,5,0,0.0,satisfied +32310,97391,Female,disloyal Customer,22,Business travel,Business,347,2,3,2,4,5,2,5,5,4,3,4,1,3,5,29,22.0,neutral or dissatisfied +32311,5071,Male,Loyal Customer,60,Business travel,Eco,303,3,3,3,3,3,3,3,3,4,1,4,1,3,3,0,25.0,neutral or dissatisfied +32312,128552,Male,Loyal Customer,40,Business travel,Business,370,4,4,1,4,4,5,4,5,5,5,5,5,5,5,6,1.0,satisfied +32313,86154,Male,disloyal Customer,28,Business travel,Business,306,4,5,5,4,4,5,4,4,5,2,5,3,5,4,1,1.0,satisfied +32314,22481,Male,disloyal Customer,36,Personal Travel,Eco,143,1,5,1,2,1,1,1,1,4,1,5,4,5,1,0,0.0,neutral or dissatisfied +32315,32187,Female,Loyal Customer,44,Business travel,Business,101,4,4,4,4,5,3,2,5,5,5,5,3,5,3,0,0.0,satisfied +32316,30875,Male,Loyal Customer,46,Personal Travel,Eco,1546,1,5,1,4,5,1,4,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +32317,115018,Female,Loyal Customer,35,Business travel,Business,2416,0,0,0,5,2,5,5,3,3,4,4,3,3,4,0,0.0,satisfied +32318,88843,Male,Loyal Customer,13,Personal Travel,Eco Plus,270,0,0,0,1,1,0,1,1,3,5,5,5,5,1,7,5.0,satisfied +32319,111290,Female,Loyal Customer,43,Business travel,Business,3306,5,5,5,5,4,4,4,3,3,4,3,5,3,5,2,0.0,satisfied +32320,128903,Female,Loyal Customer,18,Personal Travel,Eco,2454,2,4,2,3,2,2,2,3,5,5,4,2,5,2,163,134.0,neutral or dissatisfied +32321,394,Female,Loyal Customer,35,Business travel,Business,140,1,1,1,1,2,4,4,3,3,4,4,4,3,5,3,5.0,satisfied +32322,83096,Female,Loyal Customer,44,Personal Travel,Eco,983,4,1,4,4,1,4,4,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +32323,83407,Female,Loyal Customer,43,Business travel,Business,2328,5,5,5,5,3,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +32324,107623,Female,Loyal Customer,36,Business travel,Business,1860,1,1,1,1,4,4,1,4,4,4,4,5,4,1,35,75.0,satisfied +32325,21153,Female,Loyal Customer,59,Business travel,Eco,954,1,3,4,3,2,2,3,1,1,1,1,2,1,4,62,42.0,neutral or dissatisfied +32326,66890,Male,disloyal Customer,35,Business travel,Business,929,3,4,4,5,1,4,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +32327,83000,Female,disloyal Customer,25,Business travel,Business,1127,0,0,0,4,4,0,5,4,3,3,4,4,4,4,13,1.0,satisfied +32328,98289,Female,Loyal Customer,28,Personal Travel,Eco,1072,1,2,1,3,5,1,5,5,2,3,2,3,2,5,13,0.0,neutral or dissatisfied +32329,9891,Male,Loyal Customer,39,Business travel,Business,2796,5,4,5,5,3,5,5,3,3,3,3,5,3,4,101,104.0,satisfied +32330,61193,Female,Loyal Customer,53,Business travel,Business,967,1,1,4,1,3,4,5,5,5,5,5,4,5,5,1,1.0,satisfied +32331,60575,Male,Loyal Customer,12,Business travel,Eco,1558,2,4,5,4,2,2,3,2,4,3,4,1,4,2,11,7.0,neutral or dissatisfied +32332,56925,Male,Loyal Customer,20,Business travel,Business,2565,1,1,1,1,5,5,5,4,3,3,5,5,3,5,30,32.0,satisfied +32333,61116,Male,Loyal Customer,40,Business travel,Business,1639,5,5,5,5,5,5,4,4,4,4,4,3,4,4,5,14.0,satisfied +32334,105310,Female,Loyal Customer,22,Personal Travel,Eco,738,5,4,5,3,3,4,3,3,4,4,5,5,5,3,0,3.0,satisfied +32335,81905,Female,Loyal Customer,19,Personal Travel,Eco,680,2,4,2,1,2,2,3,2,5,4,5,4,5,2,0,2.0,neutral or dissatisfied +32336,62160,Female,Loyal Customer,23,Business travel,Business,2454,3,3,3,3,5,5,5,5,3,2,3,5,4,5,9,0.0,satisfied +32337,68408,Female,disloyal Customer,29,Business travel,Eco,1045,3,4,4,3,2,4,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +32338,31314,Male,Loyal Customer,36,Business travel,Business,1950,2,2,2,2,3,4,4,4,4,4,4,1,4,1,0,0.0,satisfied +32339,44526,Female,Loyal Customer,49,Business travel,Business,1937,3,3,3,3,1,4,5,5,5,5,5,3,5,3,0,2.0,satisfied +32340,74965,Female,Loyal Customer,45,Personal Travel,Eco,2586,2,2,2,3,3,3,4,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +32341,77506,Female,Loyal Customer,27,Business travel,Eco Plus,1087,3,2,2,2,3,3,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +32342,52278,Male,disloyal Customer,40,Business travel,Eco,370,1,1,1,4,2,1,2,2,3,3,3,3,3,2,47,44.0,neutral or dissatisfied +32343,19100,Female,Loyal Customer,60,Business travel,Eco,265,4,1,4,1,5,2,1,3,3,4,3,1,3,2,0,0.0,satisfied +32344,104497,Female,disloyal Customer,43,Business travel,Business,1609,3,3,3,3,5,3,5,5,4,5,3,4,4,5,0,0.0,neutral or dissatisfied +32345,37196,Male,Loyal Customer,72,Business travel,Eco Plus,1129,1,1,1,1,1,1,1,1,4,2,4,2,4,1,0,15.0,neutral or dissatisfied +32346,64242,Male,Loyal Customer,36,Business travel,Business,1660,3,1,1,1,2,3,3,3,3,3,3,3,3,1,29,40.0,neutral or dissatisfied +32347,121499,Male,Loyal Customer,20,Business travel,Eco Plus,290,0,3,0,2,3,0,3,3,5,2,3,4,1,3,0,3.0,satisfied +32348,66318,Female,Loyal Customer,50,Personal Travel,Eco,852,1,5,1,3,1,5,5,3,4,4,4,5,4,5,162,149.0,neutral or dissatisfied +32349,3645,Female,Loyal Customer,51,Business travel,Business,431,1,1,1,1,2,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +32350,93579,Female,Loyal Customer,40,Business travel,Business,159,1,3,3,3,3,3,4,3,3,3,1,4,3,4,11,8.0,neutral or dissatisfied +32351,6767,Female,Loyal Customer,37,Business travel,Business,223,5,5,5,5,2,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +32352,56170,Female,Loyal Customer,77,Business travel,Business,3516,4,4,4,4,3,1,5,4,4,4,4,3,4,4,0,0.0,satisfied +32353,31166,Male,disloyal Customer,44,Business travel,Eco,627,1,0,1,3,2,1,2,2,3,1,3,4,4,2,6,0.0,neutral or dissatisfied +32354,43185,Female,Loyal Customer,34,Personal Travel,Eco,282,3,3,3,4,5,3,5,5,1,5,2,5,3,5,4,0.0,neutral or dissatisfied +32355,57706,Male,Loyal Customer,46,Personal Travel,Eco,867,3,4,3,2,1,3,1,1,4,4,5,5,4,1,42,30.0,neutral or dissatisfied +32356,91636,Male,Loyal Customer,17,Personal Travel,Eco,1184,2,4,2,1,3,2,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +32357,125526,Female,Loyal Customer,55,Business travel,Business,226,2,2,2,2,2,4,5,5,5,5,5,3,5,5,1,15.0,satisfied +32358,92524,Female,Loyal Customer,67,Personal Travel,Eco,1919,1,5,0,2,4,5,5,1,1,0,1,5,1,3,0,0.0,neutral or dissatisfied +32359,92287,Male,Loyal Customer,51,Personal Travel,Business,1814,2,3,2,4,2,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +32360,58709,Female,Loyal Customer,58,Personal Travel,Eco Plus,4243,3,2,3,4,3,1,5,3,1,3,3,5,2,5,60,54.0,neutral or dissatisfied +32361,70188,Female,Loyal Customer,41,Business travel,Business,2797,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +32362,71233,Female,disloyal Customer,21,Business travel,Business,733,1,1,2,4,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +32363,101013,Female,Loyal Customer,60,Business travel,Business,564,1,1,4,1,3,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +32364,17262,Female,Loyal Customer,63,Personal Travel,Eco,872,3,2,3,4,1,4,4,3,3,3,3,3,3,4,7,0.0,neutral or dissatisfied +32365,38562,Female,Loyal Customer,39,Personal Travel,Eco,2475,3,1,3,2,3,1,1,1,2,2,3,1,4,1,376,382.0,neutral or dissatisfied +32366,4238,Male,Loyal Customer,64,Business travel,Business,3888,3,4,4,4,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +32367,77846,Male,Loyal Customer,51,Business travel,Business,3948,3,3,3,3,5,4,4,5,5,5,5,5,5,5,12,1.0,satisfied +32368,87215,Female,Loyal Customer,11,Personal Travel,Eco,946,1,3,1,2,1,1,1,1,3,4,4,5,3,1,0,0.0,neutral or dissatisfied +32369,46001,Female,Loyal Customer,16,Personal Travel,Eco,300,2,1,2,3,4,2,1,4,4,3,4,3,3,4,34,40.0,neutral or dissatisfied +32370,24638,Male,Loyal Customer,9,Personal Travel,Eco,666,2,2,2,2,4,2,4,4,4,4,2,3,2,4,39,27.0,neutral or dissatisfied +32371,63011,Male,Loyal Customer,47,Business travel,Business,853,1,3,3,3,2,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +32372,7201,Female,Loyal Customer,34,Business travel,Eco,135,3,3,5,3,3,3,3,3,3,3,2,4,2,3,20,16.0,neutral or dissatisfied +32373,51996,Male,Loyal Customer,59,Business travel,Eco,1119,4,3,3,3,4,4,4,4,5,3,1,2,1,4,0,9.0,satisfied +32374,452,Female,Loyal Customer,39,Business travel,Business,3409,0,4,0,4,4,5,5,1,1,1,1,4,1,3,0,0.0,satisfied +32375,45944,Male,Loyal Customer,33,Personal Travel,Eco,913,3,3,3,4,5,3,5,5,2,4,4,3,3,5,0,0.0,neutral or dissatisfied +32376,26342,Male,Loyal Customer,47,Business travel,Business,473,2,2,2,2,3,5,3,4,4,4,4,5,4,1,0,0.0,satisfied +32377,17756,Male,Loyal Customer,27,Personal Travel,Eco,501,5,2,5,1,1,5,1,1,2,4,1,1,1,1,0,0.0,satisfied +32378,87448,Male,Loyal Customer,41,Business travel,Business,3832,1,1,1,1,5,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +32379,97581,Female,Loyal Customer,52,Personal Travel,Eco,448,2,5,2,2,2,1,1,3,5,5,5,1,3,1,176,180.0,neutral or dissatisfied +32380,112208,Male,Loyal Customer,58,Personal Travel,Business,1199,4,2,4,4,1,4,3,4,4,4,3,1,4,1,3,0.0,satisfied +32381,11482,Male,Loyal Customer,13,Personal Travel,Eco Plus,224,2,4,2,5,2,2,3,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +32382,39986,Female,Loyal Customer,37,Personal Travel,Business,508,4,5,4,3,4,5,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +32383,123138,Male,Loyal Customer,42,Business travel,Business,1814,2,1,1,1,1,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +32384,57337,Female,Loyal Customer,75,Business travel,Business,2706,1,4,4,4,5,3,2,1,1,1,1,4,1,2,76,81.0,neutral or dissatisfied +32385,100518,Male,Loyal Customer,24,Personal Travel,Eco,580,4,3,4,4,2,4,2,2,4,3,3,5,2,2,11,7.0,satisfied +32386,81823,Male,Loyal Customer,64,Business travel,Business,1701,2,1,1,1,2,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +32387,89818,Female,Loyal Customer,28,Business travel,Eco Plus,1096,4,5,5,5,4,4,4,4,1,2,4,2,3,4,36,3.0,neutral or dissatisfied +32388,91234,Male,Loyal Customer,9,Personal Travel,Eco,545,2,4,2,3,2,1,1,1,1,3,3,1,3,1,113,153.0,neutral or dissatisfied +32389,85188,Male,Loyal Customer,46,Business travel,Business,813,2,2,2,2,3,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +32390,25209,Female,Loyal Customer,45,Business travel,Eco,919,4,4,4,4,4,2,3,3,3,4,3,4,3,4,10,0.0,satisfied +32391,5782,Male,Loyal Customer,39,Business travel,Business,3570,0,0,0,4,4,4,4,2,2,2,5,5,2,5,0,19.0,satisfied +32392,118918,Male,Loyal Customer,33,Personal Travel,Eco,570,1,1,1,3,3,1,3,3,3,3,3,3,4,3,6,0.0,neutral or dissatisfied +32393,17641,Female,Loyal Customer,40,Business travel,Eco,1008,3,2,2,2,3,3,3,3,3,1,4,1,2,3,0,0.0,satisfied +32394,106293,Male,Loyal Customer,28,Personal Travel,Eco Plus,604,3,4,3,3,1,3,1,1,2,5,4,2,4,1,0,0.0,neutral or dissatisfied +32395,82934,Female,Loyal Customer,56,Business travel,Business,3662,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +32396,52902,Female,disloyal Customer,34,Business travel,Eco Plus,1024,2,2,2,3,4,2,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +32397,11414,Male,Loyal Customer,57,Business travel,Business,1810,4,4,4,4,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +32398,63323,Male,Loyal Customer,43,Business travel,Business,3817,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +32399,78368,Female,Loyal Customer,55,Business travel,Business,980,4,4,4,4,4,5,4,3,3,4,3,3,3,3,0,4.0,satisfied +32400,87705,Male,Loyal Customer,25,Personal Travel,Eco,591,1,5,1,3,2,1,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +32401,9335,Male,Loyal Customer,45,Personal Travel,Eco Plus,542,4,5,4,1,1,4,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +32402,43047,Female,Loyal Customer,44,Business travel,Eco,391,4,1,1,1,4,5,2,4,4,4,4,4,4,2,0,0.0,satisfied +32403,100318,Male,Loyal Customer,41,Business travel,Business,1073,4,4,4,4,5,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +32404,119757,Female,Loyal Customer,52,Business travel,Business,1325,2,2,2,2,2,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +32405,91870,Male,Loyal Customer,67,Personal Travel,Eco,2239,2,3,3,3,3,3,5,3,4,4,2,1,4,3,0,13.0,neutral or dissatisfied +32406,7704,Female,Loyal Customer,21,Personal Travel,Eco,604,4,1,4,4,2,4,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +32407,11054,Female,Loyal Customer,55,Personal Travel,Eco,309,2,1,2,3,4,4,3,3,3,2,3,1,3,3,2,0.0,neutral or dissatisfied +32408,7289,Female,Loyal Customer,42,Personal Travel,Eco,139,1,0,1,1,5,4,5,3,3,1,3,4,3,4,3,0.0,neutral or dissatisfied +32409,11674,Female,Loyal Customer,46,Business travel,Business,2372,4,4,4,4,2,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +32410,3291,Male,Loyal Customer,57,Personal Travel,Eco,483,5,2,3,3,3,3,2,3,4,2,2,1,4,3,0,0.0,satisfied +32411,2462,Female,Loyal Customer,29,Business travel,Business,773,2,2,2,2,2,2,2,2,3,2,4,3,3,2,0,12.0,neutral or dissatisfied +32412,100818,Female,Loyal Customer,42,Business travel,Business,1607,3,3,2,3,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +32413,21533,Male,Loyal Customer,38,Personal Travel,Eco,164,2,4,2,4,5,2,5,5,4,3,4,4,4,5,10,5.0,neutral or dissatisfied +32414,120812,Male,disloyal Customer,23,Business travel,Business,266,3,2,3,3,4,3,2,4,4,4,3,2,3,4,0,0.0,neutral or dissatisfied +32415,62763,Female,disloyal Customer,25,Business travel,Eco,2504,1,1,1,4,4,1,1,4,3,2,2,3,4,4,72,61.0,neutral or dissatisfied +32416,81643,Female,Loyal Customer,33,Personal Travel,Business,907,2,4,2,2,5,4,5,1,1,2,1,4,1,4,0,2.0,neutral or dissatisfied +32417,78413,Female,Loyal Customer,52,Business travel,Business,201,3,2,5,2,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +32418,10818,Male,Loyal Customer,59,Business travel,Business,3390,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +32419,41864,Female,Loyal Customer,13,Personal Travel,Eco,483,3,3,3,4,1,3,1,1,3,5,4,5,3,1,0,0.0,neutral or dissatisfied +32420,103195,Male,Loyal Customer,28,Business travel,Business,2717,4,4,4,4,5,5,5,5,4,1,3,5,3,5,0,0.0,satisfied +32421,79650,Male,Loyal Customer,38,Business travel,Eco,362,4,5,5,5,4,3,4,4,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +32422,32156,Male,Loyal Customer,39,Business travel,Eco,102,5,3,3,3,5,5,5,5,2,2,1,4,1,5,0,2.0,satisfied +32423,27762,Male,Loyal Customer,49,Business travel,Eco,1533,5,2,2,2,5,5,5,5,3,4,5,5,3,5,0,0.0,satisfied +32424,90962,Male,Loyal Customer,36,Business travel,Business,115,4,2,2,2,5,4,3,3,3,3,4,3,3,4,93,87.0,neutral or dissatisfied +32425,82538,Female,Loyal Customer,19,Business travel,Business,3870,5,5,5,5,4,4,4,4,3,4,4,4,3,4,161,142.0,satisfied +32426,24273,Male,Loyal Customer,39,Personal Travel,Eco,147,1,1,1,3,1,1,2,1,4,5,3,3,4,1,0,6.0,neutral or dissatisfied +32427,83920,Female,Loyal Customer,35,Business travel,Business,321,2,2,2,2,2,4,5,5,5,5,5,5,5,3,42,46.0,satisfied +32428,109386,Female,Loyal Customer,9,Personal Travel,Eco,1046,4,4,4,3,2,4,2,2,3,4,5,3,4,2,1,0.0,neutral or dissatisfied +32429,115910,Male,Loyal Customer,75,Business travel,Eco,371,3,2,2,2,3,3,3,3,4,3,4,4,3,3,8,3.0,neutral or dissatisfied +32430,24549,Female,disloyal Customer,38,Business travel,Eco,696,1,1,1,4,2,1,2,2,3,1,4,3,3,2,15,25.0,neutral or dissatisfied +32431,18592,Female,Loyal Customer,39,Business travel,Business,2018,1,3,3,3,5,2,2,2,2,2,1,3,2,1,27,17.0,neutral or dissatisfied +32432,367,Male,disloyal Customer,26,Business travel,Business,102,0,0,0,1,4,0,4,4,3,3,5,5,4,4,0,0.0,satisfied +32433,48076,Male,disloyal Customer,22,Business travel,Eco,236,1,1,1,3,4,1,4,4,2,5,2,4,3,4,18,4.0,neutral or dissatisfied +32434,97626,Male,Loyal Customer,25,Personal Travel,Eco,764,3,4,3,4,4,3,4,4,4,2,5,4,5,4,17,23.0,neutral or dissatisfied +32435,12542,Female,Loyal Customer,8,Business travel,Business,788,3,3,3,3,4,4,4,4,3,3,5,5,1,4,0,2.0,satisfied +32436,117125,Male,Loyal Customer,41,Business travel,Eco,304,4,2,2,2,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +32437,106024,Female,Loyal Customer,46,Business travel,Business,1523,2,2,2,2,3,5,4,5,5,5,5,3,5,3,4,19.0,satisfied +32438,42292,Female,Loyal Customer,41,Business travel,Business,438,2,4,2,2,2,2,2,4,4,4,4,3,4,1,38,52.0,satisfied +32439,88295,Male,disloyal Customer,10,Business travel,Eco,594,3,0,3,3,1,3,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +32440,65160,Female,Loyal Customer,14,Personal Travel,Eco,247,2,4,2,4,1,2,1,1,3,3,5,5,4,1,58,57.0,neutral or dissatisfied +32441,9964,Male,disloyal Customer,20,Business travel,Eco,134,5,1,5,3,1,5,1,1,4,3,2,2,1,1,4,0.0,satisfied +32442,81430,Male,Loyal Customer,51,Personal Travel,Eco,393,3,3,1,2,3,1,3,3,3,1,2,4,2,3,0,0.0,neutral or dissatisfied +32443,128405,Male,Loyal Customer,58,Business travel,Eco,621,3,3,3,3,3,3,3,3,3,1,4,3,3,3,26,37.0,neutral or dissatisfied +32444,8633,Female,disloyal Customer,26,Business travel,Business,227,3,4,3,2,3,3,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +32445,84743,Female,Loyal Customer,46,Business travel,Business,2641,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +32446,113210,Male,Loyal Customer,58,Business travel,Business,3622,3,3,3,3,5,4,4,4,4,4,4,4,4,5,17,11.0,satisfied +32447,32888,Male,Loyal Customer,65,Personal Travel,Eco,216,3,3,3,3,3,3,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +32448,12768,Male,Loyal Customer,42,Business travel,Eco Plus,689,5,5,5,5,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +32449,13319,Female,Loyal Customer,49,Business travel,Eco,764,4,3,1,1,1,3,4,4,4,4,4,1,4,2,45,32.0,satisfied +32450,69242,Male,Loyal Customer,39,Business travel,Business,2063,2,5,2,2,2,5,5,5,5,5,5,4,5,4,0,3.0,satisfied +32451,5871,Female,Loyal Customer,60,Business travel,Business,3971,5,5,5,5,5,5,4,5,5,5,4,5,5,4,11,8.0,satisfied +32452,119169,Female,Loyal Customer,38,Business travel,Business,2067,4,5,4,5,3,3,3,4,4,4,4,1,4,4,0,21.0,neutral or dissatisfied +32453,17636,Female,Loyal Customer,39,Business travel,Eco,783,5,4,4,4,5,5,5,5,3,3,3,3,5,5,0,0.0,satisfied +32454,19170,Male,Loyal Customer,23,Personal Travel,Eco Plus,304,2,4,2,2,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +32455,15018,Male,Loyal Customer,29,Personal Travel,Eco,557,1,1,1,4,1,1,1,1,4,4,3,4,3,1,0,2.0,neutral or dissatisfied +32456,37254,Female,Loyal Customer,54,Business travel,Business,2308,2,2,2,2,2,3,4,4,4,4,4,1,4,4,0,0.0,satisfied +32457,23103,Male,Loyal Customer,50,Personal Travel,Business,223,3,1,3,3,5,4,4,1,1,3,1,4,1,2,89,77.0,neutral or dissatisfied +32458,19073,Female,disloyal Customer,9,Business travel,Eco,569,1,0,1,4,3,1,1,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +32459,32173,Female,disloyal Customer,29,Business travel,Eco,163,2,0,3,3,4,3,4,4,5,1,4,2,1,4,0,0.0,neutral or dissatisfied +32460,124306,Female,Loyal Customer,44,Business travel,Business,2559,0,0,0,2,3,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +32461,53425,Female,Loyal Customer,55,Business travel,Business,2419,5,5,5,5,1,5,5,3,3,4,3,1,3,4,4,1.0,satisfied +32462,111540,Male,Loyal Customer,60,Business travel,Business,3983,2,2,2,2,5,4,5,3,3,3,3,5,3,4,34,20.0,satisfied +32463,23869,Male,Loyal Customer,26,Personal Travel,Eco,552,4,0,4,4,1,4,1,1,4,4,5,4,4,1,3,4.0,satisfied +32464,95577,Male,Loyal Customer,54,Business travel,Business,2038,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,5.0,satisfied +32465,80344,Female,Loyal Customer,51,Business travel,Business,3697,2,2,2,2,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +32466,63231,Male,Loyal Customer,40,Business travel,Business,337,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +32467,120945,Male,Loyal Customer,47,Business travel,Business,993,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +32468,57925,Male,Loyal Customer,25,Personal Travel,Eco,305,1,5,4,2,1,4,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +32469,86762,Female,Loyal Customer,39,Personal Travel,Eco,821,3,4,3,1,1,3,1,1,3,1,1,5,5,1,10,27.0,neutral or dissatisfied +32470,41435,Female,Loyal Customer,32,Personal Travel,Eco,913,2,4,2,5,1,2,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +32471,1917,Female,Loyal Customer,40,Business travel,Business,285,5,5,5,5,3,5,4,4,4,4,4,3,4,5,5,0.0,satisfied +32472,123915,Male,Loyal Customer,33,Personal Travel,Eco,544,3,3,3,2,3,3,1,3,2,4,3,2,1,3,0,0.0,neutral or dissatisfied +32473,96902,Female,Loyal Customer,51,Personal Travel,Eco,781,4,5,5,4,4,5,4,2,2,5,2,3,2,4,2,0.0,neutral or dissatisfied +32474,101970,Male,Loyal Customer,47,Business travel,Eco,228,1,1,1,1,1,1,1,1,2,4,4,3,4,1,101,97.0,neutral or dissatisfied +32475,55169,Female,Loyal Customer,20,Personal Travel,Eco,1635,2,5,2,3,2,2,2,2,4,3,3,4,4,2,9,15.0,neutral or dissatisfied +32476,123166,Female,Loyal Customer,16,Business travel,Business,600,2,2,2,2,2,2,2,2,3,2,3,1,3,2,34,38.0,neutral or dissatisfied +32477,103432,Female,Loyal Customer,63,Personal Travel,Eco,237,3,3,3,2,5,3,2,5,5,3,5,1,5,3,10,0.0,neutral or dissatisfied +32478,45945,Male,Loyal Customer,34,Personal Travel,Eco,563,3,5,3,3,2,3,4,2,5,3,5,4,5,2,23,8.0,neutral or dissatisfied +32479,119210,Female,Loyal Customer,59,Business travel,Business,2047,3,3,3,3,3,4,2,4,4,4,4,5,4,3,8,44.0,satisfied +32480,110270,Female,Loyal Customer,55,Business travel,Business,883,2,4,4,4,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +32481,54157,Male,Loyal Customer,55,Business travel,Eco,1400,1,2,2,2,1,1,1,1,3,5,3,1,3,1,16,35.0,neutral or dissatisfied +32482,7347,Female,Loyal Customer,39,Personal Travel,Eco,606,3,1,3,2,2,3,2,2,3,2,2,2,2,2,16,21.0,neutral or dissatisfied +32483,39680,Male,Loyal Customer,60,Personal Travel,Eco,612,2,3,3,2,2,3,2,2,5,5,1,4,4,2,5,35.0,neutral or dissatisfied +32484,22479,Female,Loyal Customer,68,Personal Travel,Eco,143,1,5,1,2,5,4,4,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +32485,66907,Male,Loyal Customer,33,Personal Travel,Business,985,2,3,2,4,3,2,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +32486,85505,Female,Loyal Customer,36,Personal Travel,Eco,106,2,5,2,2,5,2,5,5,3,2,4,3,5,5,0,5.0,neutral or dissatisfied +32487,102832,Female,disloyal Customer,25,Business travel,Business,423,5,0,4,2,3,4,3,3,3,4,4,5,4,3,35,24.0,satisfied +32488,43867,Female,disloyal Customer,24,Business travel,Eco,174,3,1,3,4,1,3,1,1,2,4,3,2,4,1,8,3.0,neutral or dissatisfied +32489,120470,Male,Loyal Customer,57,Personal Travel,Eco,366,3,4,3,1,4,3,4,4,1,4,2,5,5,4,4,0.0,neutral or dissatisfied +32490,82900,Male,Loyal Customer,21,Personal Travel,Eco,594,5,4,5,2,5,2,2,2,5,1,3,2,3,2,153,179.0,satisfied +32491,119511,Male,Loyal Customer,72,Business travel,Business,2122,3,4,4,4,5,3,4,3,3,3,3,3,3,1,3,5.0,neutral or dissatisfied +32492,36860,Female,Loyal Customer,78,Business travel,Eco,273,2,3,3,3,2,2,2,1,4,2,2,2,2,2,233,233.0,neutral or dissatisfied +32493,56701,Female,Loyal Customer,42,Personal Travel,Eco,1023,2,4,2,4,3,3,4,2,2,2,2,2,2,4,7,11.0,neutral or dissatisfied +32494,87801,Female,disloyal Customer,26,Business travel,Business,214,4,0,4,3,5,4,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +32495,65920,Male,Loyal Customer,38,Business travel,Eco,169,5,2,2,2,5,5,5,5,4,2,4,1,1,5,0,0.0,satisfied +32496,47380,Female,Loyal Customer,35,Business travel,Business,558,2,2,2,2,3,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +32497,27317,Male,Loyal Customer,22,Business travel,Business,3203,3,3,3,3,5,5,5,5,1,4,2,1,4,5,0,0.0,satisfied +32498,44913,Female,Loyal Customer,57,Business travel,Business,466,3,3,3,3,3,3,2,3,3,3,3,3,3,5,0,4.0,satisfied +32499,105464,Male,disloyal Customer,25,Business travel,Business,495,2,0,2,1,5,2,3,5,4,2,4,5,4,5,2,1.0,neutral or dissatisfied +32500,87258,Female,disloyal Customer,24,Business travel,Eco,577,2,4,3,5,2,3,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +32501,30253,Female,Loyal Customer,15,Personal Travel,Business,836,2,4,2,2,2,2,2,2,4,3,5,3,5,2,11,32.0,neutral or dissatisfied +32502,19175,Female,Loyal Customer,47,Business travel,Business,1024,2,2,2,2,5,4,1,4,4,4,4,1,4,1,0,0.0,satisfied +32503,84139,Male,Loyal Customer,11,Personal Travel,Eco,782,1,5,1,3,3,1,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +32504,91146,Male,Loyal Customer,37,Personal Travel,Eco,515,2,4,2,1,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +32505,50784,Male,Loyal Customer,19,Personal Travel,Eco,109,4,5,4,3,2,4,2,2,5,2,2,5,1,2,5,10.0,neutral or dissatisfied +32506,21825,Female,Loyal Customer,47,Business travel,Business,240,2,2,2,2,2,5,4,4,4,5,4,5,4,4,65,53.0,satisfied +32507,17858,Male,Loyal Customer,48,Personal Travel,Business,425,3,5,3,5,5,5,5,3,3,3,3,4,3,5,0,38.0,neutral or dissatisfied +32508,49884,Male,disloyal Customer,19,Business travel,Eco,78,3,4,3,3,1,3,1,1,2,2,3,4,4,1,28,25.0,neutral or dissatisfied +32509,106667,Male,Loyal Customer,28,Personal Travel,Eco,1590,4,4,4,4,1,4,1,1,2,2,4,4,5,1,16,23.0,neutral or dissatisfied +32510,82547,Female,Loyal Customer,53,Personal Travel,Eco,440,1,1,1,2,2,2,1,4,4,1,5,1,4,2,67,66.0,neutral or dissatisfied +32511,73532,Male,Loyal Customer,49,Business travel,Business,594,4,3,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +32512,60229,Female,disloyal Customer,28,Business travel,Business,1546,3,3,3,1,4,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +32513,103634,Male,Loyal Customer,45,Business travel,Business,1587,1,1,1,1,3,4,5,4,4,4,4,5,4,3,12,8.0,satisfied +32514,111680,Male,Loyal Customer,40,Business travel,Business,2060,2,2,2,2,2,5,5,4,4,4,4,4,4,5,24,5.0,satisfied +32515,56330,Female,disloyal Customer,20,Business travel,Business,200,5,2,5,3,3,5,3,3,4,2,4,3,5,3,0,0.0,satisfied +32516,96258,Male,Loyal Customer,69,Personal Travel,Eco,786,1,4,1,1,2,1,2,2,3,3,5,4,5,2,3,0.0,neutral or dissatisfied +32517,102251,Female,Loyal Customer,58,Business travel,Business,223,2,2,2,2,4,4,4,4,4,4,4,5,4,3,49,37.0,satisfied +32518,91385,Male,Loyal Customer,42,Business travel,Business,2218,3,4,4,4,4,2,3,3,3,3,3,3,3,1,0,5.0,neutral or dissatisfied +32519,8151,Male,Loyal Customer,41,Business travel,Business,1827,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +32520,119680,Male,Loyal Customer,54,Business travel,Business,903,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +32521,37200,Female,Loyal Customer,22,Personal Travel,Eco Plus,1179,1,5,1,3,2,1,2,2,5,2,3,3,5,2,0,0.0,neutral or dissatisfied +32522,46672,Female,Loyal Customer,14,Personal Travel,Eco,125,4,2,4,2,1,4,1,1,1,2,2,3,1,1,50,55.0,neutral or dissatisfied +32523,124621,Female,disloyal Customer,22,Business travel,Eco,1457,1,1,1,4,3,1,3,3,4,2,5,5,4,3,4,1.0,neutral or dissatisfied +32524,7650,Male,Loyal Customer,40,Business travel,Business,3234,4,4,4,4,4,4,4,5,5,4,5,5,5,4,2,0.0,satisfied +32525,122625,Female,Loyal Customer,46,Personal Travel,Eco,728,1,5,1,3,1,1,1,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +32526,114465,Female,Loyal Customer,28,Business travel,Business,480,3,4,4,4,3,3,3,3,3,5,3,4,3,3,3,0.0,neutral or dissatisfied +32527,55330,Female,Loyal Customer,38,Personal Travel,Eco,1325,3,4,2,3,4,2,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +32528,78963,Male,Loyal Customer,38,Business travel,Business,3364,1,1,1,1,2,4,4,3,3,3,3,4,3,4,7,21.0,satisfied +32529,95921,Female,Loyal Customer,47,Business travel,Business,1504,4,4,4,4,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +32530,34558,Female,Loyal Customer,24,Business travel,Eco,1598,5,2,1,1,5,5,5,5,3,4,4,4,5,5,0,6.0,satisfied +32531,17133,Male,disloyal Customer,66,Personal Travel,Eco,423,3,0,3,2,4,3,5,4,3,5,5,5,4,4,13,9.0,neutral or dissatisfied +32532,74655,Male,Loyal Customer,18,Personal Travel,Eco,1464,1,1,1,3,5,1,4,5,3,3,4,4,4,5,122,105.0,neutral or dissatisfied +32533,38523,Male,disloyal Customer,46,Business travel,Eco,1164,1,1,1,3,3,1,3,3,1,1,2,2,3,3,0,0.0,neutral or dissatisfied +32534,33002,Male,Loyal Customer,43,Personal Travel,Eco,163,4,5,0,5,1,0,3,1,4,3,3,2,1,1,0,4.0,neutral or dissatisfied +32535,46482,Female,Loyal Customer,12,Personal Travel,Business,141,1,4,1,4,4,1,3,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +32536,99370,Female,Loyal Customer,47,Business travel,Business,409,1,1,1,1,4,4,5,5,5,5,5,5,5,3,40,50.0,satisfied +32537,88012,Female,Loyal Customer,39,Business travel,Business,3512,2,2,2,2,4,4,4,5,5,5,5,5,5,3,9,0.0,satisfied +32538,49580,Female,disloyal Customer,50,Business travel,Eco,77,1,4,1,5,4,1,4,4,4,2,4,3,2,4,0,0.0,neutral or dissatisfied +32539,1238,Male,Loyal Customer,52,Personal Travel,Eco,309,3,2,3,2,3,2,2,4,3,1,1,2,1,2,123,134.0,neutral or dissatisfied +32540,24619,Female,disloyal Customer,22,Business travel,Eco,126,1,4,1,2,5,1,5,5,4,2,3,1,5,5,44,38.0,neutral or dissatisfied +32541,100468,Female,Loyal Customer,39,Business travel,Business,580,5,5,5,5,3,3,3,4,3,4,5,3,5,3,144,123.0,satisfied +32542,70788,Female,disloyal Customer,44,Business travel,Eco,328,1,2,1,4,4,1,3,4,4,3,3,3,3,4,0,6.0,neutral or dissatisfied +32543,85397,Female,disloyal Customer,27,Business travel,Business,332,5,5,5,3,5,5,5,5,5,4,4,3,5,5,0,0.0,satisfied +32544,23164,Male,Loyal Customer,36,Personal Travel,Eco,300,2,3,2,3,3,2,3,3,1,3,4,3,3,3,55,59.0,neutral or dissatisfied +32545,89031,Male,Loyal Customer,11,Business travel,Business,1947,5,5,5,5,5,5,5,5,4,3,5,4,4,5,4,16.0,satisfied +32546,100096,Male,Loyal Customer,66,Business travel,Business,468,4,4,4,4,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +32547,100869,Male,Loyal Customer,18,Business travel,Business,1605,3,3,3,3,5,5,5,5,3,2,4,1,5,5,8,0.0,satisfied +32548,50078,Female,Loyal Customer,35,Business travel,Eco,373,2,1,1,1,2,2,2,2,1,5,5,3,5,2,0,0.0,satisfied +32549,8086,Male,disloyal Customer,38,Business travel,Business,335,2,2,2,2,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +32550,58973,Male,disloyal Customer,26,Business travel,Business,1218,4,4,4,1,1,4,1,1,5,3,3,4,5,1,3,10.0,satisfied +32551,74488,Male,Loyal Customer,35,Business travel,Business,1205,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +32552,32048,Female,Loyal Customer,55,Business travel,Business,102,4,4,4,4,5,3,3,5,5,5,4,3,5,3,7,7.0,satisfied +32553,105779,Male,Loyal Customer,32,Personal Travel,Eco,842,2,5,2,3,1,2,1,1,4,4,5,4,5,1,2,0.0,neutral or dissatisfied +32554,125926,Male,Loyal Customer,15,Personal Travel,Eco,993,1,4,1,3,4,1,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +32555,129053,Male,Loyal Customer,25,Business travel,Business,1846,2,2,2,2,3,3,3,3,3,4,3,3,5,3,0,0.0,satisfied +32556,105210,Female,disloyal Customer,27,Business travel,Business,377,4,4,4,5,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +32557,45362,Male,Loyal Customer,39,Personal Travel,Eco,188,2,3,2,3,3,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +32558,109911,Female,Loyal Customer,63,Business travel,Business,3104,3,2,3,3,5,4,5,4,4,4,4,4,4,3,0,,satisfied +32559,17058,Male,Loyal Customer,61,Personal Travel,Eco,1134,3,2,3,4,1,3,1,1,1,4,2,3,3,1,0,0.0,neutral or dissatisfied +32560,2264,Male,Loyal Customer,48,Business travel,Business,691,4,4,4,4,5,4,4,4,4,4,4,3,4,3,78,76.0,satisfied +32561,24793,Male,Loyal Customer,9,Personal Travel,Eco,447,3,4,3,1,5,3,5,5,3,5,5,4,5,5,27,33.0,neutral or dissatisfied +32562,26502,Female,disloyal Customer,24,Business travel,Eco,829,2,2,2,3,4,2,5,4,2,2,3,2,2,4,12,12.0,neutral or dissatisfied +32563,126734,Female,Loyal Customer,36,Business travel,Business,2402,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +32564,25179,Female,disloyal Customer,21,Business travel,Business,577,2,1,2,4,5,2,5,5,4,5,4,4,3,5,94,106.0,neutral or dissatisfied +32565,91993,Female,disloyal Customer,40,Business travel,Business,236,4,4,4,4,3,4,3,3,5,2,1,4,3,3,0,0.0,satisfied +32566,5926,Male,Loyal Customer,20,Personal Travel,Eco,173,3,4,0,1,5,0,5,5,2,4,2,2,1,5,0,0.0,neutral or dissatisfied +32567,9412,Female,Loyal Customer,19,Personal Travel,Eco,1027,4,5,4,3,1,4,1,1,2,1,1,2,5,1,69,61.0,neutral or dissatisfied +32568,79470,Male,Loyal Customer,13,Personal Travel,Eco,1183,3,4,3,1,3,3,1,3,5,5,5,4,4,3,0,4.0,neutral or dissatisfied +32569,79386,Male,disloyal Customer,25,Business travel,Business,502,4,5,4,1,4,4,4,4,4,3,5,4,4,4,7,9.0,neutral or dissatisfied +32570,125887,Female,Loyal Customer,17,Personal Travel,Eco,951,2,3,2,3,4,2,4,4,2,3,3,4,3,4,29,15.0,neutral or dissatisfied +32571,82569,Female,Loyal Customer,32,Business travel,Business,2339,1,1,5,1,4,5,4,4,5,5,4,5,4,4,12,1.0,satisfied +32572,118895,Male,disloyal Customer,45,Business travel,Business,570,3,3,3,1,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +32573,42864,Male,Loyal Customer,40,Business travel,Business,2687,5,5,4,5,5,5,5,3,3,4,5,5,3,5,145,141.0,satisfied +32574,29687,Female,Loyal Customer,11,Personal Travel,Eco Plus,1448,3,2,3,4,3,3,2,3,3,5,4,4,4,3,13,14.0,neutral or dissatisfied +32575,118134,Male,Loyal Customer,31,Business travel,Business,1488,2,2,2,2,5,5,5,5,5,3,4,3,4,5,7,0.0,satisfied +32576,42298,Female,Loyal Customer,63,Personal Travel,Eco,834,3,4,3,3,3,4,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +32577,66521,Female,disloyal Customer,39,Business travel,Business,447,3,3,3,3,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +32578,105969,Male,disloyal Customer,30,Business travel,Business,2295,4,5,5,1,5,5,5,5,2,4,4,5,3,5,7,0.0,neutral or dissatisfied +32579,121861,Male,Loyal Customer,65,Business travel,Business,337,3,1,1,1,4,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +32580,117697,Male,Loyal Customer,59,Personal Travel,Eco,1814,2,4,2,3,3,2,3,3,5,2,4,4,3,3,31,31.0,neutral or dissatisfied +32581,108849,Female,Loyal Customer,34,Business travel,Business,1947,1,1,1,1,5,4,4,4,4,4,4,4,4,5,40,47.0,satisfied +32582,103024,Female,disloyal Customer,33,Business travel,Eco,546,2,1,2,1,3,2,3,3,2,1,1,4,2,3,14,0.0,neutral or dissatisfied +32583,19220,Male,Loyal Customer,23,Business travel,Business,1848,3,3,3,3,4,4,4,4,5,5,4,1,3,4,0,3.0,satisfied +32584,42903,Male,Loyal Customer,17,Business travel,Business,2088,4,1,1,1,3,3,4,3,4,3,4,4,3,3,0,0.0,neutral or dissatisfied +32585,61967,Female,Loyal Customer,27,Business travel,Business,2400,2,2,2,2,2,2,2,2,4,5,3,3,3,2,64,48.0,neutral or dissatisfied +32586,12826,Male,Loyal Customer,48,Business travel,Business,3325,2,2,2,2,1,4,4,2,2,2,2,1,2,2,0,16.0,neutral or dissatisfied +32587,71961,Male,disloyal Customer,28,Business travel,Business,1437,5,5,5,2,4,5,4,4,3,3,5,3,4,4,0,0.0,satisfied +32588,86054,Female,Loyal Customer,9,Personal Travel,Eco,528,3,3,3,4,3,1,1,4,4,4,3,1,4,1,196,191.0,neutral or dissatisfied +32589,16183,Male,Loyal Customer,42,Business travel,Business,3755,1,4,3,4,4,2,2,1,1,1,1,4,1,1,32,23.0,neutral or dissatisfied +32590,34309,Male,Loyal Customer,48,Personal Travel,Eco,496,2,4,2,2,3,2,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +32591,107269,Male,Loyal Customer,50,Business travel,Business,283,1,1,3,1,4,5,5,5,5,5,5,3,5,4,0,2.0,satisfied +32592,12817,Male,Loyal Customer,46,Business travel,Eco,528,1,4,4,4,1,1,1,1,4,2,3,1,4,1,8,68.0,neutral or dissatisfied +32593,57606,Male,Loyal Customer,15,Personal Travel,Eco,563,3,4,3,1,4,3,4,4,4,3,5,5,4,4,49,36.0,neutral or dissatisfied +32594,57768,Female,Loyal Customer,51,Business travel,Business,2704,4,4,4,4,4,4,4,2,3,3,2,4,1,4,0,17.0,neutral or dissatisfied +32595,97108,Male,Loyal Customer,59,Business travel,Business,715,3,3,4,3,2,4,4,4,4,4,4,4,4,4,20,0.0,satisfied +32596,70910,Female,disloyal Customer,26,Business travel,Eco Plus,1721,3,2,3,3,5,3,5,5,2,2,3,2,3,5,13,9.0,neutral or dissatisfied +32597,120855,Male,disloyal Customer,11,Business travel,Eco,992,2,3,3,3,2,3,3,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +32598,39087,Female,Loyal Customer,12,Business travel,Business,3882,2,1,1,1,2,3,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +32599,114577,Male,Loyal Customer,56,Business travel,Business,2519,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +32600,117040,Female,Loyal Customer,45,Business travel,Business,325,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +32601,4950,Female,Loyal Customer,43,Business travel,Business,2225,1,1,1,1,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +32602,115131,Female,disloyal Customer,25,Business travel,Business,447,3,4,3,1,3,1,1,4,5,4,5,1,4,1,209,203.0,neutral or dissatisfied +32603,52815,Male,Loyal Customer,31,Business travel,Business,2402,1,1,1,1,1,1,1,1,2,2,3,4,4,1,0,14.0,neutral or dissatisfied +32604,35690,Female,Loyal Customer,25,Business travel,Business,1892,5,5,5,5,5,5,5,5,4,3,2,5,2,5,8,13.0,satisfied +32605,55591,Male,disloyal Customer,42,Business travel,Business,419,2,2,2,5,4,2,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +32606,11877,Female,Loyal Customer,15,Personal Travel,Eco,1042,3,4,3,4,1,3,1,1,5,2,5,5,5,1,85,73.0,neutral or dissatisfied +32607,6547,Female,Loyal Customer,27,Business travel,Business,3396,3,2,4,4,3,3,3,3,3,1,3,1,4,3,23,20.0,neutral or dissatisfied +32608,65178,Female,Loyal Customer,27,Personal Travel,Eco,551,2,2,2,3,4,2,4,4,1,3,4,4,3,4,1,4.0,neutral or dissatisfied +32609,71364,Male,Loyal Customer,54,Business travel,Business,3790,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +32610,61976,Male,disloyal Customer,30,Business travel,Business,2475,3,3,3,3,4,3,4,4,4,1,3,1,3,4,0,16.0,neutral or dissatisfied +32611,49391,Female,Loyal Customer,54,Business travel,Business,2714,1,1,1,1,1,5,2,5,5,5,5,1,5,1,0,0.0,satisfied +32612,64325,Male,Loyal Customer,46,Business travel,Business,2261,4,4,4,4,4,4,5,5,5,5,5,4,5,4,14,0.0,satisfied +32613,3557,Female,disloyal Customer,22,Business travel,Eco,227,3,2,3,3,5,3,5,5,3,1,3,1,4,5,13,9.0,neutral or dissatisfied +32614,102327,Male,Loyal Customer,59,Business travel,Business,1642,1,1,1,1,3,3,4,1,1,1,1,3,1,4,8,0.0,neutral or dissatisfied +32615,114077,Male,Loyal Customer,35,Business travel,Business,1892,1,1,1,1,4,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +32616,49060,Female,Loyal Customer,47,Business travel,Eco,86,4,1,1,1,4,5,3,4,4,4,4,5,4,5,93,119.0,satisfied +32617,41459,Male,Loyal Customer,21,Personal Travel,Business,1464,3,4,3,1,1,3,1,1,5,3,3,4,5,1,18,20.0,neutral or dissatisfied +32618,92650,Male,Loyal Customer,15,Personal Travel,Eco,453,2,4,2,3,3,2,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +32619,93709,Female,Loyal Customer,70,Personal Travel,Eco,689,2,2,2,4,2,3,4,1,1,2,1,2,1,2,20,15.0,neutral or dissatisfied +32620,59,Female,Loyal Customer,41,Business travel,Business,3997,1,1,1,1,4,4,5,4,4,4,5,5,4,4,1,0.0,satisfied +32621,35557,Male,Loyal Customer,28,Personal Travel,Eco,1005,2,5,2,2,4,2,4,4,3,5,1,5,3,4,8,16.0,neutral or dissatisfied +32622,54640,Male,Loyal Customer,58,Business travel,Eco,964,5,1,2,2,5,5,5,5,3,3,1,2,3,5,0,0.0,satisfied +32623,105578,Female,Loyal Customer,28,Business travel,Business,577,2,4,4,4,2,2,2,2,1,4,3,3,3,2,6,14.0,neutral or dissatisfied +32624,30260,Male,Loyal Customer,37,Business travel,Eco,1024,3,2,2,2,3,3,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +32625,83396,Female,Loyal Customer,47,Business travel,Business,3666,5,3,5,5,5,4,4,5,5,4,5,3,5,5,8,4.0,satisfied +32626,11531,Male,Loyal Customer,33,Business travel,Business,3145,5,5,5,5,4,4,4,4,3,3,5,4,4,4,16,0.0,satisfied +32627,34020,Male,Loyal Customer,53,Personal Travel,Eco,1598,2,4,3,1,1,3,1,1,5,4,5,3,5,1,1,0.0,neutral or dissatisfied +32628,113958,Female,Loyal Customer,41,Business travel,Business,1750,3,3,2,3,4,4,4,3,4,3,5,4,4,4,145,124.0,satisfied +32629,71326,Female,Loyal Customer,39,Business travel,Business,1514,1,1,4,1,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +32630,7689,Male,Loyal Customer,47,Personal Travel,Eco,604,1,4,1,5,1,1,1,1,3,5,5,5,5,1,98,99.0,neutral or dissatisfied +32631,18221,Female,Loyal Customer,43,Business travel,Eco,179,2,4,4,4,2,1,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +32632,54083,Male,disloyal Customer,59,Business travel,Eco,1016,2,2,2,3,4,2,2,4,4,5,3,3,4,4,0,0.0,neutral or dissatisfied +32633,55289,Male,disloyal Customer,33,Business travel,Eco,1585,2,2,2,3,1,2,5,1,4,4,3,3,3,1,26,30.0,neutral or dissatisfied +32634,124090,Male,Loyal Customer,50,Business travel,Business,2080,4,4,4,4,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +32635,11232,Female,Loyal Customer,63,Personal Travel,Eco,201,3,2,3,4,4,4,4,5,5,3,5,2,5,2,0,3.0,neutral or dissatisfied +32636,82733,Female,disloyal Customer,34,Business travel,Business,409,2,2,2,2,2,2,1,2,4,2,5,5,5,2,0,4.0,neutral or dissatisfied +32637,36916,Male,Loyal Customer,39,Business travel,Business,740,4,4,4,4,3,3,3,4,4,4,4,4,4,2,7,46.0,neutral or dissatisfied +32638,64310,Female,disloyal Customer,31,Business travel,Eco,1158,1,2,2,4,4,2,4,4,1,2,4,4,3,4,20,9.0,neutral or dissatisfied +32639,62086,Male,Loyal Customer,41,Personal Travel,Eco Plus,2586,3,3,3,4,4,3,4,4,3,4,4,1,4,4,0,0.0,neutral or dissatisfied +32640,44562,Male,Loyal Customer,43,Business travel,Business,2357,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,4.0,satisfied +32641,72443,Male,Loyal Customer,32,Business travel,Business,2246,3,3,3,3,4,4,4,4,3,3,5,3,5,4,6,7.0,satisfied +32642,94824,Female,disloyal Customer,48,Business travel,Business,189,3,3,3,4,4,3,4,4,3,3,5,3,4,4,2,0.0,neutral or dissatisfied +32643,64997,Male,Loyal Customer,17,Business travel,Business,1566,2,2,2,2,5,5,5,5,5,5,4,3,2,5,15,7.0,satisfied +32644,3453,Female,Loyal Customer,70,Business travel,Business,1630,4,4,4,4,5,4,5,5,5,5,4,4,5,5,8,0.0,satisfied +32645,67630,Male,Loyal Customer,42,Business travel,Business,1431,3,3,3,3,3,4,4,2,2,2,2,3,2,4,2,0.0,satisfied +32646,24882,Male,Loyal Customer,21,Business travel,Eco Plus,534,0,4,1,1,2,1,2,2,2,1,2,3,1,2,9,2.0,satisfied +32647,1037,Male,Loyal Customer,37,Business travel,Business,1901,5,3,3,3,2,2,2,1,1,1,5,1,1,1,0,0.0,neutral or dissatisfied +32648,59835,Male,Loyal Customer,46,Business travel,Business,2335,3,3,3,3,2,5,4,5,5,5,5,4,5,4,121,83.0,satisfied +32649,108992,Male,Loyal Customer,43,Business travel,Business,1105,3,2,3,3,5,5,4,5,5,5,5,3,5,3,25,2.0,satisfied +32650,111925,Female,Loyal Customer,42,Personal Travel,Eco,472,2,4,2,2,2,3,4,2,2,2,2,3,2,4,32,16.0,neutral or dissatisfied +32651,7418,Male,Loyal Customer,36,Business travel,Business,1989,1,1,1,1,5,5,4,4,4,4,4,3,4,4,110,103.0,satisfied +32652,9134,Male,Loyal Customer,60,Business travel,Business,1529,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +32653,126995,Female,Loyal Customer,52,Business travel,Business,3356,4,4,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +32654,71456,Male,disloyal Customer,34,Business travel,Eco,867,2,2,2,1,5,2,3,5,2,1,5,5,1,5,4,0.0,neutral or dissatisfied +32655,29574,Male,disloyal Customer,24,Business travel,Eco,680,4,4,4,5,2,4,2,2,1,2,4,2,4,2,85,91.0,neutral or dissatisfied +32656,36873,Male,disloyal Customer,26,Business travel,Business,1182,3,3,3,1,3,4,4,3,3,5,5,4,5,4,205,193.0,neutral or dissatisfied +32657,22379,Male,Loyal Customer,33,Business travel,Business,2415,2,1,1,1,1,1,2,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +32658,114635,Female,disloyal Customer,36,Business travel,Business,296,3,3,3,3,3,3,3,3,4,5,5,3,4,3,33,25.0,neutral or dissatisfied +32659,99271,Male,Loyal Customer,49,Business travel,Business,2445,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +32660,61850,Male,Loyal Customer,23,Business travel,Eco Plus,1303,5,1,1,1,5,4,4,5,3,2,2,1,1,5,0,0.0,satisfied +32661,87001,Male,Loyal Customer,53,Personal Travel,Eco,907,2,4,2,1,1,2,1,1,3,3,4,5,5,1,24,20.0,neutral or dissatisfied +32662,27818,Male,Loyal Customer,17,Business travel,Business,1448,4,2,4,4,5,5,5,5,5,4,4,3,4,5,0,23.0,satisfied +32663,105640,Male,Loyal Customer,34,Business travel,Business,3402,1,1,1,1,5,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +32664,109971,Male,Loyal Customer,49,Personal Travel,Eco,971,3,4,4,3,1,4,1,1,3,5,4,3,4,1,31,16.0,neutral or dissatisfied +32665,104797,Male,Loyal Customer,39,Business travel,Business,3209,3,4,5,4,3,4,4,3,3,3,3,1,3,3,13,33.0,neutral or dissatisfied +32666,15321,Female,Loyal Customer,13,Business travel,Eco,599,1,3,3,3,1,1,4,1,3,3,3,4,3,1,1,0.0,neutral or dissatisfied +32667,108709,Male,Loyal Customer,49,Business travel,Business,3249,3,5,5,5,5,4,3,3,3,3,3,4,3,3,31,24.0,neutral or dissatisfied +32668,38993,Female,Loyal Customer,21,Business travel,Business,2736,2,4,4,4,2,2,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +32669,105711,Male,Loyal Customer,53,Business travel,Business,3826,1,1,5,1,3,5,4,5,5,5,5,3,5,3,18,0.0,satisfied +32670,60756,Male,Loyal Customer,47,Business travel,Business,628,2,5,5,5,1,3,2,2,2,3,2,3,2,2,34,57.0,neutral or dissatisfied +32671,92094,Female,Loyal Customer,25,Business travel,Business,1454,2,1,1,1,2,2,2,2,1,1,4,1,3,2,15,0.0,neutral or dissatisfied +32672,99154,Male,Loyal Customer,54,Business travel,Business,1602,5,5,3,5,2,5,4,5,5,5,5,4,5,4,15,10.0,satisfied +32673,123949,Male,Loyal Customer,17,Business travel,Eco Plus,541,3,5,5,5,3,3,3,3,2,1,3,4,4,3,0,19.0,neutral or dissatisfied +32674,15735,Male,Loyal Customer,30,Personal Travel,Eco,419,4,3,4,3,1,4,2,1,2,2,4,2,4,1,0,0.0,neutral or dissatisfied +32675,51608,Female,Loyal Customer,48,Business travel,Business,2627,5,4,4,4,2,3,3,5,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +32676,117172,Female,Loyal Customer,34,Personal Travel,Eco,304,2,4,2,2,3,2,3,3,3,5,4,3,5,3,3,0.0,neutral or dissatisfied +32677,78761,Female,Loyal Customer,50,Business travel,Business,1605,3,3,3,3,5,4,4,5,5,4,5,3,5,5,0,26.0,satisfied +32678,38577,Female,Loyal Customer,9,Personal Travel,Eco,2446,4,4,4,4,3,4,3,3,1,5,2,2,4,3,0,0.0,neutral or dissatisfied +32679,100188,Female,Loyal Customer,14,Personal Travel,Eco,725,4,4,4,2,4,4,1,4,4,1,3,4,1,4,21,15.0,neutral or dissatisfied +32680,61997,Female,Loyal Customer,37,Business travel,Business,2586,3,3,1,3,2,4,4,5,5,5,5,5,5,3,14,3.0,satisfied +32681,46548,Male,Loyal Customer,46,Business travel,Business,2499,3,3,3,3,4,2,1,4,4,4,5,5,4,4,8,4.0,satisfied +32682,103100,Female,Loyal Customer,46,Personal Travel,Eco,786,2,5,2,5,3,5,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +32683,51030,Male,Loyal Customer,56,Personal Travel,Eco,134,2,2,2,4,3,2,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +32684,118291,Male,Loyal Customer,44,Business travel,Business,602,3,3,3,3,3,5,4,4,4,4,4,4,4,4,38,15.0,satisfied +32685,57702,Female,Loyal Customer,65,Personal Travel,Eco,867,3,4,3,1,3,4,4,4,4,3,2,3,4,4,9,1.0,neutral or dissatisfied +32686,25487,Male,Loyal Customer,60,Business travel,Eco,547,5,1,1,1,5,5,5,5,1,3,5,5,1,5,0,0.0,satisfied +32687,45630,Male,Loyal Customer,34,Business travel,Eco,230,4,4,4,4,4,4,4,4,2,3,4,5,3,4,0,0.0,satisfied +32688,1904,Male,Loyal Customer,37,Business travel,Business,285,4,4,2,4,3,5,4,5,5,5,5,4,5,3,44,44.0,satisfied +32689,117987,Male,Loyal Customer,42,Personal Travel,Eco,255,2,0,2,4,2,2,2,2,5,4,4,4,5,2,19,20.0,neutral or dissatisfied +32690,105833,Male,Loyal Customer,57,Personal Travel,Eco,883,3,2,3,4,3,3,3,3,2,2,4,2,4,3,2,10.0,neutral or dissatisfied +32691,68424,Female,Loyal Customer,34,Personal Travel,Eco,1045,3,4,3,4,5,3,5,5,4,2,5,4,4,5,101,86.0,neutral or dissatisfied +32692,3661,Male,Loyal Customer,49,Business travel,Business,427,5,5,5,5,4,4,5,4,4,4,4,5,4,3,15,7.0,satisfied +32693,15499,Female,Loyal Customer,51,Personal Travel,Eco,377,3,2,3,3,2,3,3,5,5,3,1,1,5,1,0,8.0,neutral or dissatisfied +32694,79890,Male,Loyal Customer,40,Business travel,Eco,1089,3,3,3,3,3,3,3,3,3,2,3,2,2,3,0,10.0,neutral or dissatisfied +32695,112691,Female,Loyal Customer,35,Business travel,Business,697,2,2,2,2,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +32696,6482,Female,Loyal Customer,54,Business travel,Business,2763,1,1,4,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +32697,107095,Male,Loyal Customer,35,Business travel,Business,2904,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +32698,28634,Male,Loyal Customer,28,Business travel,Business,2404,2,2,2,2,2,2,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +32699,10019,Male,Loyal Customer,20,Personal Travel,Eco Plus,534,2,5,2,3,4,2,3,4,5,3,4,3,4,4,21,18.0,neutral or dissatisfied +32700,58165,Female,disloyal Customer,17,Business travel,Eco,802,5,5,5,5,5,5,5,5,4,5,5,4,4,5,0,0.0,satisfied +32701,103754,Male,Loyal Customer,32,Business travel,Eco Plus,251,5,5,5,5,5,5,5,5,4,3,3,4,4,5,7,11.0,satisfied +32702,39502,Female,Loyal Customer,27,Business travel,Business,2963,3,3,3,3,5,5,5,5,5,4,1,5,2,5,38,29.0,satisfied +32703,18948,Female,Loyal Customer,69,Personal Travel,Eco,448,1,4,1,1,5,4,4,5,5,1,5,5,5,3,6,0.0,neutral or dissatisfied +32704,125871,Female,Loyal Customer,43,Business travel,Business,593,1,1,1,1,1,1,1,5,5,5,5,4,5,5,0,0.0,satisfied +32705,91387,Male,Loyal Customer,47,Business travel,Business,2158,5,5,5,5,3,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +32706,8806,Female,disloyal Customer,22,Business travel,Business,522,0,1,0,5,1,1,1,1,3,3,5,4,4,1,0,0.0,satisfied +32707,33475,Male,Loyal Customer,65,Personal Travel,Eco Plus,2917,4,5,4,4,4,3,3,4,4,3,3,3,5,3,0,0.0,neutral or dissatisfied +32708,27503,Female,disloyal Customer,22,Business travel,Eco,537,2,4,2,4,3,2,3,3,2,1,4,3,4,3,33,24.0,neutral or dissatisfied +32709,109890,Female,Loyal Customer,49,Business travel,Business,1052,1,4,4,4,1,3,4,1,1,1,1,2,1,1,19,0.0,neutral or dissatisfied +32710,63783,Female,disloyal Customer,20,Business travel,Eco,1721,3,3,3,4,3,3,2,3,3,1,2,3,4,3,41,35.0,neutral or dissatisfied +32711,64154,Male,Loyal Customer,62,Business travel,Business,2384,2,2,2,2,2,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +32712,17665,Female,disloyal Customer,18,Business travel,Eco,1008,4,4,4,3,1,4,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +32713,86603,Female,disloyal Customer,38,Business travel,Business,746,2,1,1,4,5,1,5,5,4,2,4,3,4,5,25,17.0,neutral or dissatisfied +32714,29337,Female,Loyal Customer,10,Personal Travel,Eco,569,4,5,4,3,1,4,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +32715,80649,Female,Loyal Customer,30,Business travel,Business,3704,4,4,5,4,4,5,4,4,4,2,5,5,4,4,0,0.0,satisfied +32716,21432,Male,disloyal Customer,29,Business travel,Eco,331,3,4,3,4,3,3,3,3,1,1,5,4,5,3,0,0.0,neutral or dissatisfied +32717,42865,Male,Loyal Customer,57,Business travel,Business,467,5,5,3,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +32718,1474,Male,Loyal Customer,13,Personal Travel,Eco,695,2,1,2,3,1,2,1,1,3,5,3,2,3,1,4,0.0,neutral or dissatisfied +32719,87581,Male,Loyal Customer,51,Personal Travel,Eco,432,2,1,2,4,5,2,5,5,3,2,3,3,4,5,0,0.0,neutral or dissatisfied +32720,17358,Male,Loyal Customer,62,Personal Travel,Eco,563,1,5,1,3,4,1,4,4,5,2,4,3,4,4,2,0.0,neutral or dissatisfied +32721,18521,Male,Loyal Customer,58,Business travel,Business,3217,1,5,5,5,1,4,4,3,3,2,1,3,3,4,1,0.0,neutral or dissatisfied +32722,326,Female,Loyal Customer,31,Business travel,Business,3845,1,1,1,1,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +32723,60630,Male,disloyal Customer,19,Business travel,Business,1620,5,0,5,1,2,5,2,2,3,3,5,3,5,2,0,0.0,satisfied +32724,125383,Female,Loyal Customer,31,Business travel,Business,1440,1,1,1,1,4,4,4,4,3,4,5,3,4,4,21,0.0,satisfied +32725,97482,Female,Loyal Customer,53,Business travel,Business,670,5,5,3,5,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +32726,85015,Female,Loyal Customer,34,Business travel,Business,1590,2,5,5,5,2,3,4,2,2,1,2,2,2,1,19,20.0,neutral or dissatisfied +32727,93271,Male,Loyal Customer,25,Business travel,Business,806,5,5,5,5,4,4,4,4,5,2,4,3,4,4,27,23.0,satisfied +32728,25843,Male,Loyal Customer,24,Business travel,Eco,484,1,5,5,5,1,1,2,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +32729,128110,Female,Loyal Customer,33,Business travel,Business,1587,2,2,2,2,5,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +32730,5176,Female,Loyal Customer,43,Personal Travel,Business,383,1,4,1,1,2,4,1,3,3,1,4,5,3,5,1,9.0,neutral or dissatisfied +32731,118363,Male,Loyal Customer,13,Business travel,Eco Plus,602,2,1,1,1,2,2,3,2,1,1,4,1,3,2,10,10.0,neutral or dissatisfied +32732,14742,Male,disloyal Customer,30,Business travel,Eco,463,4,0,3,4,3,3,3,3,4,2,3,4,2,3,6,17.0,neutral or dissatisfied +32733,97369,Female,Loyal Customer,60,Personal Travel,Eco,1020,2,4,2,1,1,5,3,4,4,2,4,2,4,5,5,0.0,neutral or dissatisfied +32734,84290,Female,Loyal Customer,44,Business travel,Eco Plus,349,2,1,1,1,4,3,4,1,1,2,1,2,1,3,18,9.0,neutral or dissatisfied +32735,10932,Male,Loyal Customer,30,Business travel,Eco,247,3,2,3,2,3,3,3,3,1,3,4,3,4,3,0,0.0,neutral or dissatisfied +32736,88869,Female,Loyal Customer,57,Business travel,Business,2427,4,4,4,4,5,4,4,4,4,4,4,3,4,4,39,36.0,satisfied +32737,34270,Female,Loyal Customer,35,Business travel,Eco,280,3,3,3,3,3,3,3,3,2,3,5,2,4,3,0,0.0,satisfied +32738,84089,Female,Loyal Customer,11,Personal Travel,Eco,773,5,4,5,3,2,5,2,2,4,2,1,1,2,2,0,0.0,satisfied +32739,102253,Female,Loyal Customer,39,Business travel,Business,1940,5,5,5,5,5,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +32740,92031,Female,disloyal Customer,54,Business travel,Business,1535,4,4,4,1,1,4,1,1,3,4,4,4,4,1,6,0.0,satisfied +32741,50906,Male,Loyal Customer,23,Personal Travel,Eco,373,4,5,4,4,5,4,5,5,2,3,2,2,1,5,0,13.0,neutral or dissatisfied +32742,67342,Male,Loyal Customer,39,Personal Travel,Eco,1471,2,1,2,1,4,2,2,4,2,5,2,1,1,4,18,8.0,neutral or dissatisfied +32743,19453,Female,Loyal Customer,54,Personal Travel,Eco,363,1,1,0,4,5,4,3,1,1,0,1,2,1,4,5,5.0,neutral or dissatisfied +32744,110411,Female,Loyal Customer,42,Business travel,Eco,787,3,2,3,2,1,3,2,3,3,3,3,1,3,2,123,99.0,neutral or dissatisfied +32745,30697,Male,Loyal Customer,28,Personal Travel,Eco,680,4,5,4,4,4,4,5,4,5,5,5,2,3,4,0,0.0,neutral or dissatisfied +32746,114688,Male,Loyal Customer,39,Business travel,Business,3742,5,5,5,5,2,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +32747,114353,Male,Loyal Customer,39,Personal Travel,Eco,819,2,2,2,4,5,2,5,5,4,5,3,2,3,5,2,0.0,neutral or dissatisfied +32748,115535,Male,Loyal Customer,23,Business travel,Business,1819,3,2,2,2,3,3,3,3,1,4,4,4,4,3,19,19.0,neutral or dissatisfied +32749,121046,Male,Loyal Customer,20,Personal Travel,Eco,1013,4,5,4,4,1,4,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +32750,23473,Female,Loyal Customer,14,Personal Travel,Eco,488,3,2,3,4,4,3,4,4,4,3,3,1,4,4,99,102.0,neutral or dissatisfied +32751,5711,Female,Loyal Customer,59,Personal Travel,Eco,196,1,3,1,3,2,3,3,4,4,1,4,3,4,4,37,34.0,neutral or dissatisfied +32752,97242,Male,Loyal Customer,36,Business travel,Business,2939,0,0,0,4,3,4,5,5,5,5,5,5,5,4,0,3.0,satisfied +32753,40254,Female,Loyal Customer,38,Business travel,Business,3338,2,3,3,3,4,4,3,1,1,1,2,1,1,1,0,0.0,neutral or dissatisfied +32754,50374,Female,Loyal Customer,17,Business travel,Business,266,1,4,4,4,1,1,1,2,5,3,4,1,3,1,140,143.0,neutral or dissatisfied +32755,26414,Male,disloyal Customer,36,Business travel,Eco Plus,849,2,2,2,3,2,2,1,2,2,5,5,5,3,2,0,0.0,neutral or dissatisfied +32756,91676,Female,Loyal Customer,18,Personal Travel,Eco,954,4,2,4,3,4,4,4,4,2,4,1,3,3,4,0,3.0,satisfied +32757,122166,Male,Loyal Customer,43,Business travel,Business,544,4,4,4,4,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +32758,58298,Female,disloyal Customer,43,Business travel,Business,678,5,5,5,4,5,5,5,5,4,3,4,3,4,5,3,0.0,satisfied +32759,9578,Male,disloyal Customer,57,Business travel,Business,229,1,1,1,1,3,1,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +32760,22328,Female,disloyal Customer,39,Business travel,Eco,143,1,0,1,4,4,1,4,4,1,3,3,2,3,4,0,0.0,neutral or dissatisfied +32761,17175,Male,Loyal Customer,34,Business travel,Business,643,3,4,4,4,2,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +32762,51154,Male,Loyal Customer,48,Personal Travel,Eco,109,1,5,1,1,3,1,3,3,4,2,1,5,5,3,40,45.0,neutral or dissatisfied +32763,13349,Female,disloyal Customer,24,Business travel,Eco,748,2,2,2,4,5,2,5,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +32764,122180,Male,disloyal Customer,25,Business travel,Business,544,1,0,1,4,3,1,1,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +32765,45885,Male,Loyal Customer,42,Business travel,Eco,563,3,4,2,4,3,3,3,3,3,3,4,5,3,3,0,0.0,satisfied +32766,28549,Male,Loyal Customer,49,Personal Travel,Eco,2715,1,4,1,4,5,1,5,5,5,3,4,3,4,5,15,0.0,neutral or dissatisfied +32767,127197,Female,Loyal Customer,51,Business travel,Eco Plus,370,2,3,3,3,2,1,1,3,5,2,3,1,2,1,159,150.0,neutral or dissatisfied +32768,29918,Male,Loyal Customer,38,Business travel,Business,1691,2,2,2,2,3,1,3,5,5,5,5,3,5,5,0,0.0,satisfied +32769,125819,Female,Loyal Customer,40,Business travel,Business,861,1,1,1,1,5,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +32770,107158,Female,Loyal Customer,45,Business travel,Business,402,1,1,1,1,4,4,4,4,4,4,4,5,4,5,62,58.0,satisfied +32771,60542,Male,Loyal Customer,20,Personal Travel,Eco,862,4,3,4,3,2,4,5,2,2,3,2,2,5,2,0,0.0,neutral or dissatisfied +32772,8430,Male,Loyal Customer,32,Personal Travel,Eco,862,2,5,2,3,4,2,4,4,4,4,4,5,5,4,72,89.0,neutral or dissatisfied +32773,47942,Female,Loyal Customer,54,Personal Travel,Eco,329,1,3,3,1,2,1,3,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +32774,97711,Female,Loyal Customer,35,Business travel,Business,942,5,5,5,5,5,5,4,5,5,5,5,4,5,4,25,16.0,satisfied +32775,69483,Female,Loyal Customer,45,Business travel,Business,3866,1,2,1,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +32776,25864,Male,Loyal Customer,31,Personal Travel,Eco,484,2,3,2,5,2,2,2,2,5,1,5,4,1,2,24,13.0,neutral or dissatisfied +32777,51899,Female,disloyal Customer,30,Business travel,Eco,601,1,2,1,4,1,1,1,1,1,5,3,1,3,1,7,5.0,neutral or dissatisfied +32778,75433,Female,Loyal Customer,39,Business travel,Business,2585,2,2,2,2,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +32779,107236,Male,Loyal Customer,19,Personal Travel,Eco,583,2,3,2,3,1,2,1,1,4,1,3,3,4,1,89,79.0,neutral or dissatisfied +32780,98933,Female,Loyal Customer,39,Business travel,Business,3179,4,4,2,4,5,5,4,2,2,2,2,4,2,5,25,15.0,satisfied +32781,69099,Female,Loyal Customer,46,Business travel,Business,1391,3,3,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +32782,81188,Female,disloyal Customer,40,Business travel,Eco,580,3,2,3,1,5,3,5,5,2,3,1,4,2,5,52,39.0,neutral or dissatisfied +32783,70485,Female,Loyal Customer,24,Business travel,Business,2626,3,2,2,2,3,3,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +32784,107811,Female,disloyal Customer,34,Business travel,Eco,349,3,2,3,4,4,3,5,4,3,1,4,1,3,4,37,27.0,neutral or dissatisfied +32785,97394,Male,Loyal Customer,46,Business travel,Eco Plus,472,2,2,2,2,2,2,2,2,2,3,3,2,3,2,4,7.0,neutral or dissatisfied +32786,32765,Male,disloyal Customer,41,Business travel,Eco,101,2,3,2,4,2,2,2,2,4,4,4,4,4,2,0,2.0,neutral or dissatisfied +32787,111357,Male,Loyal Customer,59,Business travel,Business,1873,3,3,3,3,5,5,5,5,5,5,5,5,5,3,87,87.0,satisfied +32788,105273,Male,Loyal Customer,48,Personal Travel,Eco,2106,3,5,3,1,2,3,2,2,4,5,5,2,5,2,21,0.0,neutral or dissatisfied +32789,45996,Female,Loyal Customer,24,Personal Travel,Eco,483,2,4,3,1,5,3,5,5,1,1,5,2,4,5,0,0.0,neutral or dissatisfied +32790,93388,Male,disloyal Customer,24,Business travel,Eco,605,4,5,4,4,3,4,1,3,5,3,4,3,4,3,0,2.0,satisfied +32791,120844,Female,disloyal Customer,23,Business travel,Business,861,4,0,4,2,5,4,1,5,4,2,4,5,5,5,5,39.0,satisfied +32792,62893,Male,Loyal Customer,46,Business travel,Business,3003,1,3,3,3,5,1,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +32793,129291,Female,disloyal Customer,26,Business travel,Eco,550,0,1,0,4,5,0,4,5,2,4,1,1,1,5,0,0.0,satisfied +32794,92799,Male,Loyal Customer,55,Business travel,Business,1587,1,1,4,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +32795,68071,Female,Loyal Customer,56,Business travel,Business,868,1,3,3,3,1,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +32796,83694,Male,Loyal Customer,58,Personal Travel,Eco,577,3,2,3,4,1,3,1,1,3,3,4,2,4,1,57,79.0,neutral or dissatisfied +32797,25051,Female,disloyal Customer,33,Business travel,Eco,594,2,2,2,3,2,3,3,2,4,3,3,3,4,3,139,127.0,neutral or dissatisfied +32798,78746,Female,Loyal Customer,55,Business travel,Business,2440,3,3,3,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +32799,17893,Female,Loyal Customer,37,Business travel,Eco Plus,425,4,1,1,1,4,4,4,4,4,5,4,1,5,4,0,0.0,satisfied +32800,105092,Female,Loyal Customer,49,Business travel,Business,2790,5,5,5,5,4,4,4,4,4,4,4,5,4,5,21,15.0,satisfied +32801,20460,Female,Loyal Customer,46,Business travel,Business,177,3,4,4,4,1,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +32802,81737,Female,Loyal Customer,47,Business travel,Business,1487,2,2,4,2,5,5,4,5,5,5,5,5,5,3,0,6.0,satisfied +32803,42868,Female,Loyal Customer,56,Business travel,Business,2389,4,4,4,4,3,2,4,4,4,4,4,1,4,5,0,19.0,satisfied +32804,17423,Female,Loyal Customer,40,Business travel,Eco,351,4,5,5,5,4,4,4,4,2,2,5,2,5,4,0,0.0,satisfied +32805,118837,Male,Loyal Customer,47,Business travel,Eco Plus,325,2,3,3,3,2,2,2,2,4,1,2,3,2,2,19,2.0,neutral or dissatisfied +32806,122733,Male,Loyal Customer,35,Business travel,Business,651,1,1,3,1,5,5,4,5,5,5,5,5,5,3,1,2.0,satisfied +32807,60498,Female,Loyal Customer,50,Business travel,Eco,462,4,2,2,2,1,3,5,4,4,4,4,3,4,5,12,0.0,satisfied +32808,6092,Male,disloyal Customer,24,Business travel,Eco,630,4,0,4,4,5,4,5,5,4,1,3,4,5,5,0,0.0,satisfied +32809,103586,Female,Loyal Customer,41,Business travel,Business,451,4,4,4,4,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +32810,3554,Male,Loyal Customer,40,Business travel,Business,2422,0,0,0,4,2,5,4,5,5,5,5,4,5,3,0,3.0,satisfied +32811,33121,Female,Loyal Customer,30,Personal Travel,Eco,101,3,4,3,4,3,3,4,3,4,3,4,3,4,3,1,2.0,neutral or dissatisfied +32812,108688,Male,Loyal Customer,58,Business travel,Business,3120,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +32813,80232,Male,Loyal Customer,34,Business travel,Business,1518,4,1,1,1,1,2,2,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +32814,31470,Male,Loyal Customer,36,Business travel,Business,2984,3,3,3,3,4,2,3,5,5,5,5,3,5,4,5,41.0,satisfied +32815,54373,Male,Loyal Customer,44,Personal Travel,Business,305,1,5,1,2,3,4,5,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +32816,24419,Female,disloyal Customer,25,Business travel,Eco,634,4,2,4,4,4,4,1,4,4,3,4,1,3,4,0,0.0,neutral or dissatisfied +32817,40690,Male,Loyal Customer,40,Business travel,Business,3559,4,4,3,4,4,2,5,4,4,4,4,3,4,2,0,0.0,satisfied +32818,124674,Female,disloyal Customer,21,Business travel,Eco,399,3,5,3,2,4,3,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +32819,19742,Male,disloyal Customer,11,Business travel,Eco,491,1,4,1,4,4,1,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +32820,109157,Male,disloyal Customer,23,Business travel,Business,616,5,0,5,1,2,5,2,2,3,5,5,3,5,2,0,0.0,satisfied +32821,50290,Female,Loyal Customer,32,Business travel,Eco,109,3,5,4,5,3,3,3,3,2,4,3,1,4,3,0,15.0,neutral or dissatisfied +32822,74677,Male,Loyal Customer,46,Personal Travel,Eco,1242,2,4,1,5,5,1,1,5,4,3,3,4,5,5,0,0.0,neutral or dissatisfied +32823,74882,Male,Loyal Customer,44,Business travel,Business,2475,4,4,4,4,2,3,4,4,4,4,4,5,4,5,1,41.0,satisfied +32824,87316,Male,disloyal Customer,23,Business travel,Eco,577,3,3,3,4,5,3,5,5,1,4,4,3,4,5,1,0.0,neutral or dissatisfied +32825,78282,Male,Loyal Customer,42,Business travel,Business,1598,4,4,4,4,3,5,4,5,5,5,5,3,5,5,19,0.0,satisfied +32826,128947,Male,Loyal Customer,39,Business travel,Business,3045,2,2,2,2,4,4,5,5,5,5,5,5,5,4,15,12.0,satisfied +32827,53760,Female,Loyal Customer,37,Business travel,Business,3169,5,5,5,5,1,5,1,2,2,2,2,3,2,1,13,4.0,satisfied +32828,116880,Female,Loyal Customer,38,Business travel,Business,338,0,0,0,4,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +32829,62397,Male,Loyal Customer,58,Personal Travel,Eco,2704,2,1,2,3,4,2,4,4,2,4,3,2,2,4,10,0.0,neutral or dissatisfied +32830,6640,Female,Loyal Customer,61,Business travel,Business,3201,1,5,5,5,3,4,3,1,1,1,1,3,1,1,43,41.0,neutral or dissatisfied +32831,4193,Male,Loyal Customer,14,Business travel,Business,3946,3,3,3,3,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +32832,19893,Female,disloyal Customer,37,Business travel,Eco,296,2,0,2,3,1,2,1,1,3,2,1,1,5,1,49,41.0,neutral or dissatisfied +32833,24329,Male,Loyal Customer,51,Business travel,Business,2696,3,4,4,4,1,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +32834,63696,Female,Loyal Customer,65,Business travel,Business,453,1,5,5,5,3,4,3,1,1,1,1,3,1,4,19,13.0,neutral or dissatisfied +32835,76823,Male,Loyal Customer,52,Business travel,Business,1851,2,2,2,2,2,5,5,3,3,3,3,3,3,5,20,3.0,satisfied +32836,117045,Male,Loyal Customer,59,Business travel,Business,451,5,5,5,5,5,5,5,2,2,2,2,5,2,3,1,0.0,satisfied +32837,62347,Male,disloyal Customer,22,Business travel,Eco,950,2,2,2,5,1,2,1,1,4,3,5,3,4,1,14,0.0,neutral or dissatisfied +32838,80278,Female,Loyal Customer,44,Business travel,Business,2402,5,5,5,5,5,5,5,4,4,4,5,5,3,5,215,221.0,satisfied +32839,46659,Male,disloyal Customer,36,Business travel,Eco,141,2,0,2,3,3,2,3,3,2,2,4,5,3,3,0,0.0,neutral or dissatisfied +32840,45379,Male,disloyal Customer,38,Business travel,Eco Plus,290,1,1,1,4,5,1,3,5,2,3,2,3,3,5,0,0.0,neutral or dissatisfied +32841,110722,Female,disloyal Customer,21,Business travel,Eco,1166,2,2,2,3,2,2,2,2,5,5,5,5,4,2,0,2.0,satisfied +32842,62238,Female,Loyal Customer,38,Personal Travel,Eco,2454,2,4,2,3,2,2,2,2,3,5,3,2,4,2,7,0.0,neutral or dissatisfied +32843,71555,Male,Loyal Customer,43,Business travel,Business,3700,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +32844,34645,Female,Loyal Customer,50,Personal Travel,Eco,541,3,4,3,3,4,5,3,3,3,3,3,5,3,3,0,12.0,neutral or dissatisfied +32845,123552,Male,Loyal Customer,43,Business travel,Business,1773,2,2,4,2,4,3,4,3,3,3,3,4,3,5,0,0.0,satisfied +32846,109754,Female,disloyal Customer,28,Business travel,Eco Plus,680,1,1,1,3,5,1,5,5,4,3,2,3,3,5,0,0.0,neutral or dissatisfied +32847,125011,Female,Loyal Customer,17,Personal Travel,Eco,184,2,4,0,4,2,0,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +32848,89346,Female,Loyal Customer,29,Business travel,Eco,1587,2,3,3,3,2,2,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +32849,67951,Male,Loyal Customer,10,Personal Travel,Eco,1235,4,5,4,1,1,4,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +32850,8274,Male,Loyal Customer,25,Personal Travel,Eco,335,2,4,2,5,4,2,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +32851,8630,Male,Loyal Customer,25,Personal Travel,Business,181,3,3,3,3,5,3,5,5,4,3,5,3,1,5,57,75.0,neutral or dissatisfied +32852,35179,Male,disloyal Customer,47,Business travel,Eco,989,4,4,4,4,3,4,3,3,1,1,2,5,4,3,0,0.0,neutral or dissatisfied +32853,58804,Male,Loyal Customer,65,Personal Travel,Eco,1005,1,5,1,2,2,1,2,2,4,2,4,5,5,2,0,6.0,neutral or dissatisfied +32854,22450,Male,Loyal Customer,64,Personal Travel,Eco,208,2,5,2,5,2,2,2,2,3,4,4,4,3,2,74,91.0,neutral or dissatisfied +32855,223,Female,Loyal Customer,16,Personal Travel,Eco,213,1,5,1,1,1,5,5,4,5,4,4,5,3,5,192,293.0,neutral or dissatisfied +32856,11700,Female,Loyal Customer,46,Business travel,Business,395,3,3,3,3,5,4,4,5,5,5,5,3,5,3,4,8.0,satisfied +32857,107640,Male,disloyal Customer,65,Business travel,Business,466,3,3,3,2,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +32858,81794,Male,disloyal Customer,7,Business travel,Eco,1306,1,1,1,3,5,1,5,5,2,4,3,3,3,5,9,45.0,neutral or dissatisfied +32859,7741,Female,disloyal Customer,30,Business travel,Eco,489,2,1,2,2,4,2,1,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +32860,124478,Female,disloyal Customer,9,Business travel,Eco Plus,980,4,0,4,3,1,4,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +32861,110218,Female,Loyal Customer,48,Business travel,Business,1024,1,1,1,1,2,5,5,5,5,4,5,4,5,5,20,15.0,satisfied +32862,111429,Male,Loyal Customer,51,Personal Travel,Eco,896,3,1,3,2,4,3,4,4,2,1,2,1,3,4,0,0.0,neutral or dissatisfied +32863,76948,Female,Loyal Customer,16,Business travel,Business,1990,3,3,3,3,2,2,2,2,5,2,5,4,5,2,0,0.0,satisfied +32864,66650,Female,disloyal Customer,25,Business travel,Eco,802,4,4,4,3,2,4,2,2,4,3,4,3,4,2,0,,neutral or dissatisfied +32865,97377,Male,Loyal Customer,64,Personal Travel,Eco,872,4,4,4,3,3,4,3,3,2,5,2,1,3,3,3,0.0,neutral or dissatisfied +32866,80809,Female,disloyal Customer,39,Business travel,Business,484,4,4,4,3,5,4,5,5,3,2,4,4,4,5,0,0.0,satisfied +32867,61975,Male,Loyal Customer,20,Business travel,Business,2586,2,2,2,2,4,4,4,5,4,4,5,4,5,4,0,18.0,satisfied +32868,113378,Male,disloyal Customer,27,Business travel,Eco,414,3,3,3,3,5,3,5,5,1,1,3,3,3,5,68,78.0,neutral or dissatisfied +32869,6393,Male,Loyal Customer,67,Business travel,Eco,240,4,1,1,1,4,4,4,4,1,2,4,2,3,4,0,2.0,neutral or dissatisfied +32870,121818,Female,Loyal Customer,47,Business travel,Business,449,1,1,1,1,2,4,4,4,4,4,4,4,4,4,32,21.0,satisfied +32871,73167,Female,Loyal Customer,51,Business travel,Business,1145,3,3,3,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +32872,26197,Male,disloyal Customer,39,Business travel,Eco,404,2,5,2,1,5,2,5,5,3,4,2,2,2,5,4,5.0,neutral or dissatisfied +32873,122563,Female,Loyal Customer,38,Business travel,Eco Plus,500,2,5,5,5,2,2,2,2,2,3,3,2,4,2,56,63.0,neutral or dissatisfied +32874,72510,Male,Loyal Customer,58,Business travel,Business,1743,5,5,5,5,5,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +32875,99011,Female,Loyal Customer,26,Business travel,Eco Plus,479,3,3,3,3,3,3,2,3,4,4,1,2,1,3,10,18.0,neutral or dissatisfied +32876,27773,Female,Loyal Customer,41,Business travel,Business,1533,2,5,2,2,5,4,3,5,5,5,5,1,5,4,0,7.0,satisfied +32877,38758,Female,disloyal Customer,41,Business travel,Business,353,4,4,4,4,1,4,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +32878,18178,Female,disloyal Customer,16,Business travel,Eco,235,3,4,3,4,1,3,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +32879,101430,Male,disloyal Customer,37,Business travel,Business,345,5,5,5,2,5,5,5,5,4,2,4,3,4,5,45,40.0,satisfied +32880,91551,Male,Loyal Customer,37,Personal Travel,Eco,680,2,4,2,3,5,2,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +32881,30444,Male,Loyal Customer,37,Personal Travel,Business,991,1,5,0,3,5,4,4,3,3,0,3,4,3,4,0,0.0,neutral or dissatisfied +32882,112296,Male,Loyal Customer,42,Business travel,Eco Plus,1506,3,1,3,1,3,3,3,3,4,2,4,3,3,3,2,0.0,neutral or dissatisfied +32883,20761,Male,Loyal Customer,45,Business travel,Business,3198,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,13.0,satisfied +32884,82356,Female,Loyal Customer,54,Business travel,Eco,453,3,1,1,1,2,2,2,3,3,3,3,3,3,1,0,6.0,neutral or dissatisfied +32885,10631,Female,Loyal Customer,47,Business travel,Business,2422,3,3,3,3,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +32886,55581,Female,Loyal Customer,10,Personal Travel,Eco,1091,2,5,2,1,2,2,5,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +32887,15363,Female,Loyal Customer,62,Business travel,Eco,399,5,1,1,1,2,2,4,5,5,5,5,3,5,5,0,9.0,satisfied +32888,84039,Female,disloyal Customer,21,Business travel,Eco,757,2,2,2,3,2,1,1,4,3,4,5,1,5,1,116,132.0,neutral or dissatisfied +32889,3658,Female,Loyal Customer,45,Business travel,Business,3132,2,2,2,2,3,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +32890,76333,Female,Loyal Customer,45,Personal Travel,Eco Plus,2182,3,2,3,3,4,4,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +32891,58696,Male,Loyal Customer,43,Business travel,Business,4243,5,5,5,5,4,4,4,5,2,4,5,4,4,4,8,6.0,satisfied +32892,12372,Male,disloyal Customer,30,Business travel,Eco,201,3,4,2,4,1,2,1,1,1,1,3,1,4,1,0,0.0,neutral or dissatisfied +32893,20574,Female,Loyal Customer,36,Business travel,Business,233,3,2,2,2,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +32894,82955,Male,Loyal Customer,59,Business travel,Business,684,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,2.0,satisfied +32895,21188,Male,Loyal Customer,42,Business travel,Eco,192,4,3,3,3,4,4,4,4,4,2,1,5,5,4,9,8.0,satisfied +32896,10686,Male,Loyal Customer,10,Business travel,Business,1944,4,5,5,5,4,3,4,4,4,2,3,2,4,4,113,103.0,neutral or dissatisfied +32897,58773,Male,disloyal Customer,16,Business travel,Business,1182,5,5,5,3,5,5,5,5,4,2,5,5,5,5,2,0.0,satisfied +32898,89912,Female,disloyal Customer,29,Business travel,Business,1416,2,2,2,4,2,2,1,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +32899,58273,Male,Loyal Customer,50,Business travel,Business,594,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +32900,39078,Female,Loyal Customer,21,Business travel,Business,984,3,3,3,3,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +32901,101175,Male,disloyal Customer,25,Business travel,Eco,1235,1,1,1,4,4,1,4,4,2,5,3,3,4,4,0,1.0,neutral or dissatisfied +32902,86921,Male,Loyal Customer,7,Personal Travel,Eco,341,3,5,3,3,4,3,4,4,3,4,4,5,4,4,4,0.0,neutral or dissatisfied +32903,81035,Female,Loyal Customer,38,Business travel,Business,1399,1,4,4,4,2,2,2,1,1,1,1,3,1,1,15,44.0,neutral or dissatisfied +32904,71411,Male,Loyal Customer,47,Personal Travel,Eco,334,3,4,3,2,5,3,1,5,4,5,4,3,4,5,20,31.0,neutral or dissatisfied +32905,49626,Male,Loyal Customer,27,Business travel,Eco,421,3,1,5,1,3,3,3,3,2,2,3,1,3,3,7,3.0,neutral or dissatisfied +32906,36623,Female,Loyal Customer,40,Business travel,Business,3044,1,1,4,1,3,3,2,4,4,4,4,5,4,1,1,17.0,satisfied +32907,8164,Male,Loyal Customer,43,Business travel,Business,2019,4,4,4,4,2,4,4,3,3,4,5,5,3,5,0,1.0,satisfied +32908,50117,Male,Loyal Customer,56,Business travel,Business,373,3,3,3,3,5,3,3,3,3,3,3,3,3,1,18,14.0,neutral or dissatisfied +32909,56237,Female,Loyal Customer,49,Business travel,Eco Plus,1608,1,3,3,3,3,2,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +32910,51315,Female,Loyal Customer,38,Business travel,Eco Plus,89,3,1,1,1,3,3,3,3,2,1,1,1,2,3,99,100.0,neutral or dissatisfied +32911,102770,Female,Loyal Customer,52,Business travel,Business,1618,5,5,5,5,2,5,5,2,2,2,2,5,2,4,12,8.0,satisfied +32912,48312,Female,Loyal Customer,65,Personal Travel,Eco,1499,3,4,3,2,3,3,4,2,2,3,1,4,2,5,93,87.0,neutral or dissatisfied +32913,119082,Male,Loyal Customer,46,Business travel,Business,1107,5,5,4,5,4,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +32914,120969,Male,Loyal Customer,58,Business travel,Business,2767,1,2,2,2,2,4,4,1,1,1,1,3,1,1,36,60.0,neutral or dissatisfied +32915,73010,Female,Loyal Customer,48,Personal Travel,Eco,1089,1,3,1,4,2,4,1,5,5,1,4,4,5,4,13,0.0,neutral or dissatisfied +32916,88902,Male,Loyal Customer,17,Business travel,Eco,859,5,3,3,3,5,5,5,5,2,1,5,2,1,5,28,,satisfied +32917,40274,Female,Loyal Customer,12,Personal Travel,Eco,347,2,1,2,3,3,2,3,3,3,3,4,2,3,3,34,17.0,neutral or dissatisfied +32918,94562,Female,disloyal Customer,24,Business travel,Eco,189,0,5,0,2,5,0,5,5,4,3,5,4,4,5,0,0.0,satisfied +32919,106673,Female,Loyal Customer,39,Business travel,Business,2307,3,3,3,3,3,4,4,4,4,4,4,3,4,4,41,41.0,satisfied +32920,127416,Female,Loyal Customer,51,Personal Travel,Eco,868,4,3,4,3,5,4,3,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +32921,59827,Male,Loyal Customer,32,Business travel,Business,3321,2,4,2,2,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +32922,122120,Female,Loyal Customer,76,Business travel,Eco Plus,130,2,4,4,4,4,4,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +32923,107571,Female,Loyal Customer,19,Personal Travel,Eco,1521,3,5,3,4,2,3,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +32924,45321,Female,Loyal Customer,39,Business travel,Eco,461,3,5,5,5,3,3,3,3,2,5,4,1,4,3,11,24.0,neutral or dissatisfied +32925,84849,Female,disloyal Customer,14,Business travel,Eco,547,1,1,1,3,3,1,3,3,4,5,4,2,3,3,0,5.0,neutral or dissatisfied +32926,75349,Male,Loyal Customer,68,Personal Travel,Eco,2615,2,4,2,2,2,3,3,4,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +32927,2835,Male,disloyal Customer,69,Business travel,Business,491,4,4,4,1,2,4,2,2,3,3,4,3,4,2,0,0.0,satisfied +32928,8246,Male,Loyal Customer,52,Personal Travel,Eco,335,3,5,3,1,3,3,3,3,3,2,4,4,4,3,8,9.0,neutral or dissatisfied +32929,64761,Female,Loyal Customer,28,Business travel,Business,3812,3,5,3,3,4,4,4,4,5,2,5,5,4,4,0,0.0,satisfied +32930,105417,Female,Loyal Customer,58,Business travel,Business,3160,2,2,2,2,3,5,4,4,4,4,4,5,4,3,14,4.0,satisfied +32931,72927,Male,disloyal Customer,37,Business travel,Business,1096,2,2,2,2,5,2,2,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +32932,97390,Female,disloyal Customer,21,Business travel,Business,347,3,3,3,3,4,3,4,4,1,2,2,2,2,4,10,8.0,neutral or dissatisfied +32933,26527,Male,disloyal Customer,48,Business travel,Eco,990,3,2,2,3,4,2,4,4,2,1,5,4,5,4,3,0.0,neutral or dissatisfied +32934,55560,Female,disloyal Customer,23,Business travel,Eco,550,4,4,4,1,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +32935,127231,Male,Loyal Customer,51,Personal Travel,Eco,1460,3,4,3,1,3,3,3,3,5,2,4,4,4,3,0,2.0,neutral or dissatisfied +32936,10713,Male,disloyal Customer,23,Business travel,Business,163,4,0,4,2,4,4,5,4,5,3,5,4,5,4,0,0.0,satisfied +32937,31618,Male,disloyal Customer,24,Business travel,Business,862,1,3,1,2,5,1,5,5,3,2,2,4,2,5,0,16.0,neutral or dissatisfied +32938,55339,Male,Loyal Customer,17,Personal Travel,Eco,1117,2,2,3,4,3,3,3,3,4,4,4,3,3,3,26,0.0,neutral or dissatisfied +32939,45232,Male,Loyal Customer,46,Business travel,Business,511,2,2,2,2,4,4,2,5,5,5,5,4,5,5,0,0.0,satisfied +32940,38862,Female,Loyal Customer,67,Business travel,Eco,2300,2,3,3,3,2,3,4,2,2,2,2,1,2,1,16,0.0,neutral or dissatisfied +32941,13796,Male,disloyal Customer,78,Business travel,Eco,450,2,4,2,3,3,2,4,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +32942,124869,Male,Loyal Customer,31,Personal Travel,Eco Plus,280,2,4,2,3,3,2,4,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +32943,72872,Female,Loyal Customer,8,Personal Travel,Eco Plus,700,2,4,2,3,5,2,2,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +32944,107454,Female,disloyal Customer,79,Business travel,Eco Plus,325,4,4,4,2,5,3,5,4,4,4,4,1,4,1,4,0.0,neutral or dissatisfied +32945,83135,Male,Loyal Customer,24,Personal Travel,Eco,983,4,1,4,3,3,4,3,3,4,1,3,4,2,3,0,5.0,satisfied +32946,79307,Male,Loyal Customer,62,Business travel,Eco,748,5,3,4,4,5,5,5,5,2,3,4,3,4,5,0,0.0,satisfied +32947,84434,Male,Loyal Customer,48,Business travel,Eco Plus,591,2,4,4,4,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +32948,89059,Male,Loyal Customer,29,Business travel,Business,2139,2,2,2,2,4,4,4,4,4,3,3,4,5,4,9,20.0,satisfied +32949,73469,Male,Loyal Customer,45,Personal Travel,Eco,1005,4,5,5,3,5,5,5,5,1,5,1,1,2,5,0,0.0,neutral or dissatisfied +32950,15947,Female,Loyal Customer,69,Personal Travel,Eco,528,3,5,3,1,4,5,4,5,5,3,5,4,5,4,12,20.0,neutral or dissatisfied +32951,18515,Male,Loyal Customer,63,Business travel,Business,2952,1,1,1,1,5,3,1,5,5,5,5,2,5,4,0,3.0,satisfied +32952,63359,Male,Loyal Customer,44,Personal Travel,Eco,337,2,4,2,4,4,2,4,4,3,3,5,4,4,4,4,0.0,neutral or dissatisfied +32953,60194,Male,Loyal Customer,25,Business travel,Business,1709,2,2,2,2,4,4,4,4,5,5,3,5,4,4,42,22.0,satisfied +32954,11175,Female,Loyal Customer,62,Personal Travel,Eco,295,1,5,1,3,4,5,4,3,3,1,3,5,3,4,8,0.0,neutral or dissatisfied +32955,71920,Male,Loyal Customer,57,Business travel,Business,1846,5,5,5,5,3,5,4,4,4,4,4,4,4,5,75,77.0,satisfied +32956,85247,Male,Loyal Customer,39,Personal Travel,Eco,689,1,4,2,1,1,2,1,1,5,5,4,3,4,1,10,2.0,neutral or dissatisfied +32957,26033,Male,Loyal Customer,19,Personal Travel,Eco,321,2,2,2,3,3,2,1,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +32958,13393,Female,Loyal Customer,39,Business travel,Business,2909,3,2,2,2,2,3,3,1,1,1,3,3,1,1,0,0.0,neutral or dissatisfied +32959,76182,Female,Loyal Customer,57,Business travel,Business,2422,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +32960,25760,Female,Loyal Customer,13,Personal Travel,Eco,356,1,5,1,1,2,1,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +32961,11249,Female,Loyal Customer,52,Personal Travel,Eco,224,1,4,1,4,2,4,5,3,3,1,4,3,3,5,0,0.0,neutral or dissatisfied +32962,18862,Male,Loyal Customer,18,Business travel,Business,2023,2,1,1,1,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +32963,13343,Male,disloyal Customer,24,Business travel,Eco,748,2,2,2,3,1,2,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +32964,16944,Female,Loyal Customer,32,Personal Travel,Eco,820,2,5,2,1,4,2,4,4,4,2,4,2,2,4,0,0.0,neutral or dissatisfied +32965,29569,Male,Loyal Customer,26,Business travel,Eco,1448,4,4,4,4,4,4,3,4,2,1,5,5,5,4,0,0.0,satisfied +32966,108153,Female,Loyal Customer,36,Personal Travel,Eco,1105,3,5,3,1,2,3,2,2,5,3,2,4,2,2,20,23.0,neutral or dissatisfied +32967,57435,Female,disloyal Customer,25,Business travel,Business,1735,1,3,1,4,1,1,1,3,1,3,4,1,2,1,288,277.0,neutral or dissatisfied +32968,6568,Male,Loyal Customer,30,Business travel,Business,473,5,5,5,5,2,2,2,2,3,2,5,3,4,2,0,0.0,satisfied +32969,19738,Male,Loyal Customer,53,Personal Travel,Eco,475,3,5,3,5,3,4,4,1,1,2,2,4,2,4,152,169.0,neutral or dissatisfied +32970,69632,Male,Loyal Customer,40,Business travel,Business,2859,4,4,4,4,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +32971,62901,Male,Loyal Customer,33,Business travel,Business,853,1,4,4,4,1,1,1,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +32972,90981,Male,disloyal Customer,15,Business travel,Eco,270,2,2,1,4,3,1,3,3,1,3,3,1,4,3,1,0.0,neutral or dissatisfied +32973,129878,Male,Loyal Customer,42,Personal Travel,Eco Plus,337,2,5,2,1,3,2,3,3,3,4,5,4,4,3,6,14.0,neutral or dissatisfied +32974,123837,Female,Loyal Customer,54,Business travel,Eco,541,4,3,3,3,2,2,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +32975,107391,Male,Loyal Customer,51,Business travel,Business,1679,4,4,4,4,5,5,5,5,5,5,5,3,5,4,28,15.0,satisfied +32976,33888,Male,Loyal Customer,36,Business travel,Eco Plus,994,5,4,4,4,5,5,5,5,1,4,2,5,3,5,148,140.0,satisfied +32977,67048,Female,Loyal Customer,41,Business travel,Business,1973,2,2,2,2,5,5,5,2,2,3,2,3,2,3,15,0.0,satisfied +32978,75958,Male,Loyal Customer,39,Business travel,Business,228,2,2,3,2,5,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +32979,114921,Male,disloyal Customer,21,Business travel,Eco,325,3,0,3,1,1,3,1,1,4,5,5,5,4,1,0,6.0,neutral or dissatisfied +32980,120435,Female,disloyal Customer,44,Business travel,Eco,449,3,3,3,4,2,3,2,2,4,4,3,4,4,2,0,24.0,neutral or dissatisfied +32981,58134,Female,Loyal Customer,24,Personal Travel,Eco Plus,589,4,5,4,1,3,4,2,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +32982,8207,Female,disloyal Customer,38,Business travel,Eco,335,3,3,3,1,2,3,2,2,4,3,5,1,2,2,0,0.0,neutral or dissatisfied +32983,41018,Male,Loyal Customer,16,Business travel,Business,1715,5,5,5,5,5,5,5,5,5,2,4,2,4,5,0,0.0,satisfied +32984,111453,Male,disloyal Customer,23,Business travel,Eco,624,3,1,3,4,2,3,1,2,3,1,4,3,3,2,0,19.0,neutral or dissatisfied +32985,19579,Female,Loyal Customer,37,Personal Travel,Eco,160,1,5,0,1,5,0,5,5,4,5,5,3,5,5,40,46.0,neutral or dissatisfied +32986,85201,Male,Loyal Customer,31,Business travel,Business,2327,4,4,4,4,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +32987,110514,Male,Loyal Customer,45,Personal Travel,Eco Plus,663,1,3,2,3,1,2,1,1,2,4,3,1,4,1,6,7.0,neutral or dissatisfied +32988,103060,Male,Loyal Customer,50,Business travel,Business,2172,3,3,4,3,2,1,3,4,4,4,4,5,4,4,32,31.0,satisfied +32989,102027,Male,disloyal Customer,28,Business travel,Business,488,4,4,4,2,3,4,3,3,4,2,5,5,4,3,15,9.0,neutral or dissatisfied +32990,23175,Male,Loyal Customer,67,Personal Travel,Eco,223,1,5,1,1,1,1,1,1,3,2,5,5,4,1,60,44.0,neutral or dissatisfied +32991,32306,Male,Loyal Customer,35,Business travel,Business,2143,2,2,2,2,2,3,1,4,4,4,4,3,4,5,0,0.0,satisfied +32992,65452,Female,Loyal Customer,59,Business travel,Business,2216,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +32993,113607,Female,Loyal Customer,40,Personal Travel,Eco,236,0,4,0,3,4,0,4,4,2,3,3,3,4,4,0,0.0,satisfied +32994,115609,Female,Loyal Customer,45,Business travel,Business,2129,2,2,5,2,4,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +32995,44393,Female,disloyal Customer,40,Business travel,Business,342,1,1,1,3,4,1,4,4,1,3,3,1,4,4,0,0.0,neutral or dissatisfied +32996,30923,Female,Loyal Customer,23,Personal Travel,Eco,896,5,2,5,3,3,5,3,3,4,1,3,4,3,3,1,2.0,satisfied +32997,11381,Female,Loyal Customer,58,Business travel,Business,667,3,3,3,3,2,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +32998,67204,Male,Loyal Customer,70,Personal Travel,Eco,1121,3,5,3,1,1,3,2,1,5,4,4,5,5,1,12,24.0,neutral or dissatisfied +32999,30178,Male,Loyal Customer,30,Business travel,Eco Plus,725,5,4,4,4,5,5,5,5,1,2,1,4,5,5,33,32.0,satisfied +33000,111906,Female,disloyal Customer,9,Business travel,Eco,804,2,2,2,5,3,2,3,3,3,4,5,3,4,3,5,0.0,neutral or dissatisfied +33001,45499,Male,Loyal Customer,57,Personal Travel,Eco,522,2,5,2,2,3,2,2,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +33002,63158,Male,Loyal Customer,45,Business travel,Business,1893,1,1,1,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +33003,99738,Male,Loyal Customer,37,Business travel,Business,361,2,2,5,2,2,4,5,2,2,2,2,3,2,3,52,42.0,satisfied +33004,101213,Male,Loyal Customer,49,Personal Travel,Eco,1069,3,4,3,1,3,3,3,3,4,5,5,3,4,3,12,7.0,neutral or dissatisfied +33005,8636,Male,disloyal Customer,23,Business travel,Eco,304,3,0,3,1,4,3,3,4,4,3,4,5,4,4,3,0.0,neutral or dissatisfied +33006,30778,Male,disloyal Customer,39,Business travel,Eco,895,3,3,3,4,1,3,1,1,2,1,1,2,4,1,57,67.0,neutral or dissatisfied +33007,123953,Male,Loyal Customer,62,Personal Travel,Eco Plus,573,1,4,1,3,1,1,1,1,3,3,4,3,4,1,5,1.0,neutral or dissatisfied +33008,117364,Male,Loyal Customer,46,Personal Travel,Eco,296,5,5,5,5,3,5,3,3,5,2,4,3,4,3,0,0.0,satisfied +33009,82723,Female,Loyal Customer,43,Business travel,Business,2716,3,3,3,3,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +33010,125283,Female,Loyal Customer,48,Business travel,Business,678,1,1,1,1,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +33011,40318,Female,Loyal Customer,62,Business travel,Eco Plus,436,4,1,1,1,4,3,2,5,5,4,5,1,5,4,0,0.0,satisfied +33012,103829,Male,Loyal Customer,31,Business travel,Business,869,3,3,3,3,3,3,3,3,2,4,4,1,3,3,22,34.0,neutral or dissatisfied +33013,16882,Female,Loyal Customer,48,Business travel,Business,2392,2,3,2,3,1,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +33014,28712,Male,Loyal Customer,34,Business travel,Eco,2717,4,4,4,4,4,4,4,3,2,4,4,4,4,4,0,0.0,satisfied +33015,106100,Male,Loyal Customer,55,Business travel,Business,3998,0,0,0,2,3,5,5,1,1,1,1,5,1,3,0,6.0,satisfied +33016,86141,Male,Loyal Customer,38,Business travel,Business,3256,1,2,1,1,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +33017,107531,Male,Loyal Customer,44,Business travel,Business,1521,4,4,4,4,2,5,4,1,1,2,1,4,1,3,0,7.0,satisfied +33018,74583,Female,disloyal Customer,27,Business travel,Business,1126,3,3,3,3,3,3,3,3,3,3,5,3,5,3,0,2.0,neutral or dissatisfied +33019,42341,Male,Loyal Customer,60,Personal Travel,Eco,834,1,5,1,5,3,1,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +33020,42244,Male,disloyal Customer,26,Business travel,Eco,817,5,5,5,3,1,5,4,1,3,3,1,2,3,1,0,0.0,satisfied +33021,25443,Male,Loyal Customer,46,Business travel,Business,2214,2,3,3,3,4,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +33022,46716,Female,Loyal Customer,66,Personal Travel,Eco,152,3,5,3,1,5,5,4,3,3,3,3,4,3,4,28,22.0,neutral or dissatisfied +33023,102953,Male,Loyal Customer,47,Personal Travel,Eco,719,1,5,2,1,2,2,2,2,3,3,4,4,5,2,23,12.0,neutral or dissatisfied +33024,34552,Female,Loyal Customer,54,Business travel,Business,1598,4,4,4,4,4,4,3,5,5,5,5,5,5,4,0,0.0,satisfied +33025,125809,Male,Loyal Customer,39,Business travel,Business,3913,5,5,5,5,5,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +33026,121452,Male,Loyal Customer,41,Business travel,Eco,290,4,3,3,3,4,4,4,4,3,2,1,1,4,4,0,0.0,satisfied +33027,40278,Female,Loyal Customer,33,Personal Travel,Eco,347,2,1,0,3,3,0,3,3,4,2,2,2,2,3,0,0.0,neutral or dissatisfied +33028,57693,Male,Loyal Customer,34,Business travel,Eco,867,1,0,0,3,5,0,5,5,3,3,3,1,4,5,1,0.0,neutral or dissatisfied +33029,13992,Male,Loyal Customer,37,Business travel,Eco,160,5,3,3,3,5,5,5,5,2,1,1,4,4,5,0,0.0,satisfied +33030,67741,Male,disloyal Customer,27,Business travel,Business,1464,2,2,2,4,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +33031,117641,Female,Loyal Customer,15,Personal Travel,Eco,347,3,5,3,4,2,3,5,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +33032,62469,Female,disloyal Customer,28,Business travel,Business,1846,2,2,2,5,1,2,1,1,4,5,4,5,4,1,6,0.0,neutral or dissatisfied +33033,11731,Female,disloyal Customer,23,Business travel,Business,429,4,0,4,1,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +33034,41509,Male,Loyal Customer,29,Business travel,Business,1504,1,1,1,1,4,4,4,4,3,1,1,4,1,4,0,5.0,satisfied +33035,63830,Male,Loyal Customer,39,Business travel,Business,3333,2,2,2,2,3,5,4,4,4,4,4,5,4,3,66,71.0,satisfied +33036,78140,Female,Loyal Customer,48,Business travel,Business,2560,3,3,4,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +33037,76282,Male,Loyal Customer,40,Personal Travel,Eco,1927,1,3,1,2,5,1,3,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +33038,34812,Male,Loyal Customer,15,Personal Travel,Eco,301,2,4,2,3,1,2,1,1,4,3,5,4,5,1,5,6.0,neutral or dissatisfied +33039,39165,Male,Loyal Customer,39,Business travel,Eco,287,5,3,3,3,5,5,5,5,1,3,1,4,3,5,0,19.0,satisfied +33040,83905,Female,Loyal Customer,38,Business travel,Business,752,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +33041,37191,Male,Loyal Customer,31,Business travel,Eco Plus,1189,0,0,0,1,4,0,4,4,3,5,1,2,3,4,8,2.0,satisfied +33042,118892,Male,Loyal Customer,43,Business travel,Business,587,3,3,3,3,4,4,5,5,5,5,5,5,5,5,10,1.0,satisfied +33043,20292,Female,Loyal Customer,67,Personal Travel,Eco,179,3,5,3,3,5,4,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +33044,66139,Male,Loyal Customer,48,Personal Travel,Eco,583,4,4,4,2,3,4,3,3,5,1,5,3,4,3,49,51.0,neutral or dissatisfied +33045,7947,Female,Loyal Customer,55,Business travel,Business,594,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +33046,40018,Male,Loyal Customer,11,Business travel,Business,525,1,1,1,1,4,4,4,4,1,1,2,5,4,4,0,0.0,satisfied +33047,114636,Male,Loyal Customer,45,Business travel,Business,2684,1,1,1,1,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +33048,111300,Male,disloyal Customer,21,Business travel,Business,283,2,2,2,4,5,2,5,5,1,2,3,4,4,5,0,0.0,neutral or dissatisfied +33049,94229,Male,Loyal Customer,35,Business travel,Business,1639,1,1,4,1,3,5,5,4,4,5,5,4,4,5,8,8.0,satisfied +33050,20813,Male,Loyal Customer,25,Business travel,Eco,357,4,1,1,1,4,3,2,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +33051,50982,Female,Loyal Customer,33,Personal Travel,Eco,77,3,4,3,3,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +33052,82163,Male,Loyal Customer,49,Business travel,Business,1715,4,4,4,4,3,2,4,5,5,5,5,3,5,2,0,0.0,satisfied +33053,72999,Female,Loyal Customer,9,Personal Travel,Eco,1089,5,4,5,5,2,5,2,2,3,5,4,2,2,2,0,0.0,satisfied +33054,35074,Male,Loyal Customer,49,Personal Travel,Business,1069,1,4,1,4,2,5,5,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +33055,22365,Male,disloyal Customer,19,Business travel,Eco,145,5,0,5,4,5,5,5,5,4,5,1,1,2,5,0,0.0,satisfied +33056,17219,Male,Loyal Customer,54,Business travel,Business,2355,4,4,4,4,3,2,3,4,4,4,4,2,4,4,0,,neutral or dissatisfied +33057,69735,Male,Loyal Customer,39,Business travel,Business,1372,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +33058,30045,Male,disloyal Customer,26,Business travel,Eco,548,2,0,2,3,4,2,4,4,4,4,3,4,5,4,0,0.0,neutral or dissatisfied +33059,41378,Male,Loyal Customer,9,Business travel,Business,2681,2,3,4,4,2,3,2,2,3,5,3,3,4,2,0,,neutral or dissatisfied +33060,26478,Male,Loyal Customer,45,Business travel,Eco Plus,787,4,1,1,1,4,4,4,4,4,3,2,5,5,4,0,0.0,satisfied +33061,119970,Female,Loyal Customer,51,Personal Travel,Eco,868,3,4,3,3,5,1,1,3,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +33062,104802,Female,Loyal Customer,64,Personal Travel,Eco,587,0,5,0,3,4,5,4,2,2,0,2,3,2,5,0,0.0,satisfied +33063,105233,Female,Loyal Customer,40,Business travel,Eco,377,2,3,3,3,2,2,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +33064,96440,Male,Loyal Customer,39,Business travel,Business,1764,5,5,5,5,2,5,4,3,3,3,3,3,3,5,71,70.0,satisfied +33065,51436,Female,Loyal Customer,41,Personal Travel,Eco Plus,326,3,5,3,3,4,3,1,2,2,3,2,1,2,2,19,5.0,neutral or dissatisfied +33066,58813,Male,Loyal Customer,13,Personal Travel,Eco,1005,2,5,2,4,2,2,3,2,4,4,5,3,4,2,1,0.0,neutral or dissatisfied +33067,2652,Female,Loyal Customer,52,Business travel,Business,2817,4,4,4,4,3,4,5,4,4,4,4,5,4,3,28,27.0,satisfied +33068,81546,Male,Loyal Customer,8,Personal Travel,Eco,1124,0,4,0,2,4,0,3,4,3,2,4,5,5,4,0,0.0,satisfied +33069,83402,Male,Loyal Customer,43,Business travel,Business,632,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +33070,75722,Male,Loyal Customer,57,Business travel,Business,1728,3,3,1,3,2,5,5,4,4,4,4,3,4,3,7,8.0,satisfied +33071,11894,Female,Loyal Customer,49,Business travel,Business,1933,4,4,4,4,5,5,5,4,4,4,4,3,4,4,26,30.0,satisfied +33072,105318,Female,Loyal Customer,32,Personal Travel,Business,452,4,5,4,2,3,4,3,3,2,2,4,1,2,3,0,0.0,neutral or dissatisfied +33073,60872,Female,Loyal Customer,70,Personal Travel,Eco Plus,1491,4,4,4,3,3,4,4,5,5,4,5,5,5,3,0,6.0,satisfied +33074,19473,Male,disloyal Customer,37,Business travel,Eco,177,4,1,4,4,2,4,2,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +33075,111626,Male,Loyal Customer,13,Personal Travel,Eco,1014,2,2,3,3,3,3,2,3,4,5,4,1,3,3,27,2.0,neutral or dissatisfied +33076,117856,Male,disloyal Customer,23,Business travel,Eco,255,4,0,4,3,2,4,2,2,5,4,4,4,4,2,0,0.0,satisfied +33077,119043,Female,Loyal Customer,60,Business travel,Business,2279,1,1,1,1,2,5,4,4,4,4,4,4,4,5,26,0.0,satisfied +33078,7038,Female,Loyal Customer,53,Business travel,Eco Plus,196,2,3,3,3,5,3,3,2,2,2,2,4,2,3,21,15.0,neutral or dissatisfied +33079,84124,Female,Loyal Customer,57,Personal Travel,Eco,1900,3,5,3,1,2,5,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +33080,113938,Female,Loyal Customer,51,Business travel,Business,1844,1,1,1,1,3,5,5,5,5,5,5,4,5,3,9,0.0,satisfied +33081,114922,Male,Loyal Customer,52,Business travel,Business,337,4,4,4,4,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +33082,35157,Male,disloyal Customer,43,Business travel,Eco,1005,5,5,5,3,1,5,1,1,5,5,4,3,4,1,0,0.0,satisfied +33083,103966,Male,Loyal Customer,41,Personal Travel,Eco,533,3,4,3,3,2,3,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +33084,21811,Male,Loyal Customer,34,Personal Travel,Eco,341,2,4,2,1,4,2,4,4,5,4,5,4,5,4,18,9.0,neutral or dissatisfied +33085,30093,Female,Loyal Customer,59,Personal Travel,Eco,234,4,4,4,1,3,5,4,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +33086,48644,Female,Loyal Customer,58,Business travel,Business,2092,5,5,5,5,2,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +33087,115271,Female,Loyal Customer,54,Business travel,Business,2945,3,3,3,3,4,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +33088,121009,Female,Loyal Customer,68,Personal Travel,Eco,861,1,5,1,2,3,4,4,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +33089,120569,Male,Loyal Customer,54,Personal Travel,Eco,2176,2,3,2,4,2,4,4,4,2,3,3,4,2,4,133,123.0,neutral or dissatisfied +33090,78018,Female,Loyal Customer,18,Business travel,Eco,214,2,1,4,1,2,2,4,2,2,4,4,1,3,2,0,0.0,neutral or dissatisfied +33091,104216,Female,Loyal Customer,52,Business travel,Business,2412,3,3,2,3,5,4,5,5,5,5,5,5,5,4,7,0.0,satisfied +33092,9684,Male,disloyal Customer,37,Business travel,Business,277,1,1,1,4,4,1,4,4,3,1,4,1,4,4,0,0.0,neutral or dissatisfied +33093,121228,Male,Loyal Customer,52,Business travel,Business,1814,2,5,2,2,4,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +33094,31878,Female,Loyal Customer,29,Personal Travel,Eco,4983,2,4,2,5,2,4,4,2,2,4,4,4,3,4,6,0.0,neutral or dissatisfied +33095,72114,Male,Loyal Customer,54,Business travel,Business,2843,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +33096,41333,Male,Loyal Customer,54,Business travel,Business,2316,2,2,2,2,5,3,1,5,5,5,5,5,5,4,0,0.0,satisfied +33097,58214,Male,Loyal Customer,60,Personal Travel,Eco,925,4,5,4,1,3,4,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +33098,125738,Female,Loyal Customer,48,Business travel,Business,1013,3,3,3,3,5,4,5,5,5,5,5,3,5,3,0,9.0,satisfied +33099,88424,Female,Loyal Customer,65,Business travel,Eco,366,4,1,1,1,5,3,3,4,4,4,4,3,4,4,29,34.0,neutral or dissatisfied +33100,97312,Female,Loyal Customer,57,Business travel,Business,3579,0,0,0,2,5,4,4,2,2,2,1,4,2,5,0,0.0,satisfied +33101,95365,Female,Loyal Customer,36,Personal Travel,Eco,562,3,4,3,3,1,3,1,1,4,2,5,3,4,1,0,2.0,neutral or dissatisfied +33102,25473,Male,Loyal Customer,44,Business travel,Business,481,2,2,2,2,5,2,3,5,5,5,5,1,5,2,17,1.0,satisfied +33103,42691,Female,Loyal Customer,45,Business travel,Business,3563,2,2,2,2,4,4,2,5,5,5,3,2,5,4,0,0.0,satisfied +33104,63452,Male,disloyal Customer,27,Business travel,Business,337,3,4,4,4,4,4,2,4,4,5,5,4,5,4,0,2.0,neutral or dissatisfied +33105,57031,Male,disloyal Customer,27,Business travel,Eco Plus,2454,2,2,2,4,2,2,2,2,4,1,2,2,4,2,5,0.0,neutral or dissatisfied +33106,90326,Female,Loyal Customer,58,Business travel,Business,581,5,5,5,5,5,5,5,5,5,5,5,4,5,3,3,0.0,satisfied +33107,47575,Female,Loyal Customer,50,Business travel,Business,1235,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,2.0,satisfied +33108,119958,Female,disloyal Customer,46,Business travel,Eco,872,2,2,2,3,1,2,1,1,1,5,3,2,4,1,19,7.0,neutral or dissatisfied +33109,14072,Male,disloyal Customer,39,Business travel,Eco,425,3,3,3,5,5,3,1,5,4,2,4,2,2,5,0,0.0,neutral or dissatisfied +33110,8930,Female,Loyal Customer,44,Personal Travel,Eco,984,1,5,1,4,5,4,5,5,5,1,5,4,5,3,0,1.0,neutral or dissatisfied +33111,3439,Male,Loyal Customer,52,Personal Travel,Eco,296,3,5,3,1,2,3,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +33112,86052,Male,Loyal Customer,9,Personal Travel,Eco,432,3,1,3,4,1,3,1,1,2,4,3,4,3,1,0,5.0,neutral or dissatisfied +33113,20790,Male,Loyal Customer,39,Business travel,Eco,457,4,2,2,2,4,4,4,4,5,5,2,5,3,4,1,0.0,satisfied +33114,68755,Male,Loyal Customer,51,Business travel,Business,861,3,3,3,3,3,4,3,3,3,3,3,4,3,3,3,8.0,neutral or dissatisfied +33115,21554,Male,Loyal Customer,59,Business travel,Eco Plus,377,5,1,1,1,5,5,5,5,4,2,1,2,2,5,97,82.0,satisfied +33116,73970,Male,Loyal Customer,63,Personal Travel,Eco,2342,2,2,2,4,1,2,1,1,1,4,4,3,3,1,4,0.0,neutral or dissatisfied +33117,15036,Male,Loyal Customer,35,Business travel,Business,3454,1,1,1,1,5,4,3,5,5,5,5,5,5,3,0,0.0,satisfied +33118,85155,Female,Loyal Customer,25,Business travel,Eco,731,2,3,5,5,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +33119,81874,Male,Loyal Customer,11,Personal Travel,Eco,1050,4,4,4,4,3,4,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +33120,18292,Male,disloyal Customer,26,Business travel,Eco,640,1,2,1,4,4,1,4,4,1,5,3,4,3,4,66,105.0,neutral or dissatisfied +33121,70659,Male,Loyal Customer,41,Business travel,Business,3972,4,4,4,4,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +33122,103300,Male,Loyal Customer,51,Business travel,Business,1712,1,1,1,1,2,5,5,3,3,4,3,4,3,3,0,10.0,satisfied +33123,42166,Female,Loyal Customer,61,Business travel,Business,3919,1,1,1,1,2,1,3,5,5,5,5,2,5,2,0,0.0,satisfied +33124,55357,Female,Loyal Customer,41,Business travel,Business,3396,1,1,1,1,5,5,5,5,5,5,5,5,5,5,9,0.0,satisfied +33125,97024,Female,Loyal Customer,45,Business travel,Business,775,3,5,3,3,4,5,4,2,2,2,2,3,2,5,0,9.0,satisfied +33126,41539,Female,Loyal Customer,23,Business travel,Business,1504,4,4,4,4,3,3,3,3,1,5,3,1,3,3,41,65.0,satisfied +33127,36741,Female,Loyal Customer,31,Personal Travel,Eco,1754,3,4,3,4,5,3,5,5,1,1,2,1,4,5,90,90.0,neutral or dissatisfied +33128,54706,Male,Loyal Customer,59,Business travel,Eco,565,4,1,1,1,4,4,4,4,2,4,4,1,3,4,1,15.0,neutral or dissatisfied +33129,20372,Male,Loyal Customer,18,Personal Travel,Eco,265,3,5,0,3,5,0,5,5,3,3,3,1,4,5,0,0.0,neutral or dissatisfied +33130,63789,Male,disloyal Customer,37,Business travel,Business,221,4,5,5,3,1,5,1,1,1,2,1,5,4,1,0,0.0,satisfied +33131,13768,Female,Loyal Customer,52,Business travel,Business,525,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +33132,45556,Female,Loyal Customer,40,Business travel,Eco,1304,4,2,4,2,4,5,4,4,1,5,1,4,5,4,11,0.0,satisfied +33133,128600,Male,Loyal Customer,22,Business travel,Business,2798,1,1,1,1,5,5,5,5,5,4,5,3,5,5,27,56.0,satisfied +33134,21787,Female,Loyal Customer,46,Business travel,Business,2395,5,5,5,5,2,5,1,5,5,5,5,4,5,5,0,0.0,satisfied +33135,78659,Female,Loyal Customer,11,Business travel,Business,2172,5,5,3,5,2,2,2,2,4,2,5,4,5,2,0,0.0,satisfied +33136,45855,Male,disloyal Customer,24,Business travel,Eco,391,2,2,2,4,2,2,2,2,4,1,3,3,4,2,0,13.0,neutral or dissatisfied +33137,76270,Male,disloyal Customer,10,Business travel,Business,1927,5,0,5,5,2,0,2,2,4,2,4,4,5,2,0,0.0,satisfied +33138,33045,Female,Loyal Customer,12,Personal Travel,Eco,163,3,5,3,3,4,3,2,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +33139,32422,Male,disloyal Customer,22,Business travel,Eco,101,1,0,1,2,3,1,2,3,1,2,4,5,5,3,0,0.0,neutral or dissatisfied +33140,44748,Female,Loyal Customer,33,Business travel,Business,717,2,1,1,1,5,2,3,2,2,1,2,1,2,1,16,12.0,neutral or dissatisfied +33141,10386,Male,disloyal Customer,44,Business travel,Business,316,1,2,2,4,2,1,2,2,3,2,5,3,5,2,22,16.0,neutral or dissatisfied +33142,54969,Male,Loyal Customer,20,Business travel,Business,1608,4,4,4,4,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +33143,124045,Female,Loyal Customer,36,Business travel,Business,184,0,4,0,1,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +33144,126164,Female,Loyal Customer,31,Business travel,Business,600,3,3,4,3,5,5,5,5,4,3,4,5,5,5,16,4.0,satisfied +33145,16989,Female,Loyal Customer,33,Personal Travel,Eco,610,3,1,2,3,2,2,2,2,1,2,3,3,4,2,31,5.0,neutral or dissatisfied +33146,103679,Female,Loyal Customer,48,Business travel,Business,405,4,4,4,4,2,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +33147,86627,Male,Loyal Customer,52,Business travel,Business,2767,1,1,3,1,2,3,3,1,1,2,1,4,1,2,14,6.0,neutral or dissatisfied +33148,29154,Female,Loyal Customer,23,Business travel,Eco Plus,978,5,1,1,1,5,5,4,5,1,3,1,3,4,5,0,0.0,satisfied +33149,112280,Male,Loyal Customer,25,Personal Travel,Eco,1447,2,4,1,3,3,1,3,3,2,2,4,2,2,3,9,0.0,neutral or dissatisfied +33150,52667,Male,Loyal Customer,58,Personal Travel,Eco,119,1,4,0,3,3,0,5,3,3,3,4,4,4,3,10,17.0,neutral or dissatisfied +33151,7818,Male,Loyal Customer,58,Business travel,Business,3949,5,5,5,5,4,2,4,5,5,4,5,2,5,4,0,0.0,satisfied +33152,52939,Female,disloyal Customer,23,Business travel,Eco,679,4,4,4,3,1,4,1,1,5,1,5,5,5,1,0,0.0,neutral or dissatisfied +33153,1636,Male,Loyal Customer,12,Personal Travel,Eco,999,4,5,4,2,4,4,4,4,5,5,3,2,1,4,0,0.0,neutral or dissatisfied +33154,88797,Female,Loyal Customer,37,Business travel,Business,2681,5,5,2,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +33155,10614,Male,Loyal Customer,45,Business travel,Business,2356,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +33156,102946,Female,Loyal Customer,35,Business travel,Business,719,4,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +33157,78253,Female,Loyal Customer,50,Business travel,Business,1560,5,5,5,5,4,4,4,5,5,5,5,4,5,3,0,17.0,satisfied +33158,111278,Male,Loyal Customer,67,Personal Travel,Eco,459,1,3,1,3,3,1,3,3,2,4,2,1,2,3,48,46.0,neutral or dissatisfied +33159,57799,Male,Loyal Customer,25,Business travel,Business,3808,5,5,5,5,2,2,2,2,4,3,4,5,4,2,0,0.0,satisfied +33160,51678,Female,disloyal Customer,19,Business travel,Eco,261,2,3,2,3,4,2,4,4,4,4,4,3,3,4,0,9.0,neutral or dissatisfied +33161,13919,Female,Loyal Customer,38,Business travel,Business,1985,4,4,5,4,4,5,3,4,4,5,4,5,4,5,23,8.0,satisfied +33162,58258,Female,disloyal Customer,55,Business travel,Eco,1497,3,3,3,2,1,3,1,1,2,3,1,3,2,1,0,0.0,neutral or dissatisfied +33163,50859,Female,Loyal Customer,11,Personal Travel,Eco,86,3,4,3,1,3,3,3,3,3,5,4,1,1,3,0,0.0,neutral or dissatisfied +33164,102087,Female,Loyal Customer,42,Business travel,Business,1804,5,5,5,5,3,5,4,5,5,5,5,5,5,5,21,2.0,satisfied +33165,84488,Female,Loyal Customer,40,Business travel,Business,1494,4,4,4,4,4,4,4,2,4,3,1,4,3,4,0,0.0,satisfied +33166,125536,Female,Loyal Customer,51,Business travel,Business,226,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +33167,38271,Female,Loyal Customer,57,Personal Travel,Eco,1173,4,5,4,4,5,5,5,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +33168,80310,Female,Loyal Customer,22,Business travel,Business,746,3,4,4,4,3,3,3,2,5,4,3,3,4,3,303,302.0,neutral or dissatisfied +33169,64071,Male,Loyal Customer,46,Business travel,Business,2719,2,3,4,3,4,3,3,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +33170,90779,Male,Loyal Customer,37,Business travel,Business,3307,3,3,3,3,4,5,4,3,3,4,3,3,3,5,8,1.0,satisfied +33171,51367,Male,Loyal Customer,47,Personal Travel,Eco Plus,238,3,3,3,3,1,3,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +33172,49073,Male,disloyal Customer,37,Business travel,Eco,421,2,0,3,5,3,3,3,3,4,5,4,5,2,3,44,46.0,neutral or dissatisfied +33173,77831,Female,Loyal Customer,54,Personal Travel,Eco,813,2,1,2,4,5,3,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +33174,68655,Female,disloyal Customer,38,Business travel,Business,175,1,1,1,2,3,1,3,3,3,4,5,5,5,3,24,15.0,neutral or dissatisfied +33175,12198,Male,disloyal Customer,44,Business travel,Business,190,5,5,5,1,4,5,4,4,3,3,5,4,4,4,9,2.0,satisfied +33176,50154,Male,Loyal Customer,58,Business travel,Business,2774,4,4,4,4,4,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +33177,129607,Female,Loyal Customer,56,Business travel,Business,447,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +33178,46166,Male,Loyal Customer,56,Personal Travel,Eco,627,1,5,1,5,4,1,1,4,5,3,4,5,4,4,55,70.0,neutral or dissatisfied +33179,84189,Male,Loyal Customer,49,Business travel,Business,432,1,1,1,1,4,5,5,5,5,5,5,4,5,4,58,81.0,satisfied +33180,124929,Male,Loyal Customer,56,Personal Travel,Eco,728,4,3,4,3,4,4,4,4,5,2,2,2,1,4,2,7.0,neutral or dissatisfied +33181,36797,Female,Loyal Customer,67,Personal Travel,Eco,2611,3,5,2,3,2,3,3,4,3,5,4,3,4,3,49,43.0,neutral or dissatisfied +33182,49758,Female,Loyal Customer,36,Business travel,Business,89,3,3,3,3,1,5,4,5,5,5,3,2,5,3,0,0.0,satisfied +33183,56545,Female,Loyal Customer,58,Business travel,Business,1984,3,3,3,3,5,5,4,4,4,4,4,3,4,5,7,0.0,satisfied +33184,33380,Female,Loyal Customer,21,Personal Travel,Eco,2614,3,4,3,5,4,3,4,4,3,5,5,4,4,4,2,0.0,neutral or dissatisfied +33185,68206,Female,Loyal Customer,34,Business travel,Business,2975,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,17.0,satisfied +33186,27877,Female,disloyal Customer,38,Business travel,Eco Plus,1133,3,3,3,4,4,3,4,4,3,3,4,3,4,4,2,0.0,neutral or dissatisfied +33187,84710,Male,Loyal Customer,41,Business travel,Business,534,4,5,2,2,3,3,3,4,4,4,4,1,4,2,21,8.0,neutral or dissatisfied +33188,76538,Male,Loyal Customer,55,Business travel,Business,516,3,3,3,3,5,5,5,3,5,4,4,5,3,5,211,231.0,satisfied +33189,65763,Male,Loyal Customer,35,Personal Travel,Eco,936,3,4,3,2,3,3,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +33190,123296,Female,Loyal Customer,59,Business travel,Business,3414,1,1,1,1,5,5,5,5,5,4,5,3,5,4,63,58.0,satisfied +33191,116228,Male,Loyal Customer,51,Personal Travel,Eco,333,2,5,4,5,2,4,2,2,3,3,5,3,4,2,20,19.0,neutral or dissatisfied +33192,124274,Male,Loyal Customer,35,Business travel,Business,3604,2,2,2,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +33193,108523,Female,Loyal Customer,56,Business travel,Business,3677,1,1,1,1,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +33194,73557,Female,Loyal Customer,60,Business travel,Business,204,0,5,0,2,2,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +33195,21416,Male,Loyal Customer,48,Business travel,Eco,377,4,4,4,4,4,4,4,4,3,2,3,2,2,4,83,71.0,satisfied +33196,3440,Male,Loyal Customer,38,Personal Travel,Eco,296,0,2,0,2,2,0,2,2,4,5,3,3,2,2,0,6.0,satisfied +33197,90292,Male,Loyal Customer,79,Business travel,Eco,479,4,1,5,1,4,4,4,4,1,5,3,2,4,4,0,0.0,satisfied +33198,124763,Female,Loyal Customer,48,Business travel,Business,280,4,4,3,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +33199,19298,Male,Loyal Customer,34,Business travel,Business,2688,2,5,5,5,5,4,4,2,2,2,2,2,2,3,0,11.0,neutral or dissatisfied +33200,65076,Female,Loyal Customer,64,Personal Travel,Eco,469,2,4,2,3,3,5,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +33201,53362,Female,Loyal Customer,50,Business travel,Eco,1452,2,4,4,4,5,3,3,2,2,2,2,4,2,4,26,19.0,satisfied +33202,103429,Female,Loyal Customer,64,Personal Travel,Eco,237,2,4,2,4,3,5,4,3,3,2,3,4,3,4,12,3.0,neutral or dissatisfied +33203,93118,Female,Loyal Customer,62,Personal Travel,Business,1183,2,1,1,3,5,2,3,2,2,1,2,1,2,3,86,75.0,neutral or dissatisfied +33204,66061,Male,Loyal Customer,54,Personal Travel,Eco,1055,3,4,3,5,5,3,5,5,3,3,5,4,5,5,14,25.0,neutral or dissatisfied +33205,91271,Female,Loyal Customer,9,Personal Travel,Eco,515,1,4,5,3,1,5,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +33206,92698,Female,Loyal Customer,37,Personal Travel,Eco,507,2,3,2,1,1,2,5,1,1,2,4,3,2,1,0,0.0,neutral or dissatisfied +33207,83084,Male,Loyal Customer,55,Business travel,Eco,684,4,5,3,3,4,4,4,4,1,4,1,5,1,4,0,0.0,satisfied +33208,109442,Male,Loyal Customer,41,Business travel,Business,2168,5,5,5,5,3,4,5,4,4,4,4,4,4,4,50,43.0,satisfied +33209,97549,Male,Loyal Customer,46,Personal Travel,Eco,675,3,5,3,3,5,3,5,5,1,5,3,2,2,5,32,27.0,neutral or dissatisfied +33210,89328,Female,Loyal Customer,37,Business travel,Business,1587,2,2,2,2,4,4,4,4,4,4,4,5,4,5,1,1.0,satisfied +33211,39084,Male,disloyal Customer,36,Business travel,Eco,984,3,3,3,2,1,3,1,1,2,2,1,3,2,1,2,0.0,neutral or dissatisfied +33212,10259,Female,Loyal Customer,43,Personal Travel,Business,312,2,4,2,1,4,5,4,1,1,2,4,3,1,4,86,79.0,neutral or dissatisfied +33213,4175,Male,Loyal Customer,56,Personal Travel,Eco,544,2,5,2,4,3,2,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +33214,82745,Male,Loyal Customer,43,Business travel,Business,2215,4,4,4,4,5,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +33215,72143,Female,Loyal Customer,44,Personal Travel,Eco,731,3,4,3,1,3,3,3,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +33216,40562,Female,Loyal Customer,49,Business travel,Business,1945,5,5,5,5,2,4,4,4,4,4,4,2,4,4,23,16.0,satisfied +33217,112721,Female,Loyal Customer,16,Personal Travel,Eco,723,2,5,2,4,2,2,2,2,3,4,5,2,4,2,41,38.0,neutral or dissatisfied +33218,7839,Female,Loyal Customer,7,Personal Travel,Eco Plus,650,2,4,2,5,2,2,2,2,4,2,1,4,4,2,30,19.0,neutral or dissatisfied +33219,54939,Female,Loyal Customer,47,Business travel,Business,1379,2,1,5,1,3,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +33220,38799,Female,Loyal Customer,60,Personal Travel,Eco,387,1,4,1,5,5,4,5,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +33221,92512,Male,Loyal Customer,50,Personal Travel,Eco,1947,2,4,2,3,4,2,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +33222,31087,Male,Loyal Customer,31,Business travel,Business,1014,5,5,5,5,4,4,4,4,2,4,4,3,4,4,0,0.0,satisfied +33223,108245,Male,Loyal Customer,28,Business travel,Business,895,4,2,4,4,3,3,3,3,5,2,4,5,4,3,0,0.0,satisfied +33224,127438,Female,Loyal Customer,20,Personal Travel,Eco,1009,3,3,2,3,2,2,2,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +33225,55671,Female,disloyal Customer,27,Business travel,Business,895,3,3,3,4,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +33226,106675,Male,Loyal Customer,47,Business travel,Business,1880,4,4,4,4,5,4,5,5,5,5,5,5,5,4,8,3.0,satisfied +33227,102370,Female,Loyal Customer,65,Business travel,Business,2026,3,4,4,4,3,1,2,3,3,3,3,3,3,2,8,8.0,neutral or dissatisfied +33228,42148,Male,Loyal Customer,39,Business travel,Business,329,5,5,5,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +33229,9145,Female,disloyal Customer,24,Business travel,Eco,227,2,0,2,5,2,2,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +33230,87492,Female,Loyal Customer,39,Business travel,Business,1718,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +33231,87967,Male,Loyal Customer,48,Business travel,Business,594,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +33232,128672,Male,Loyal Customer,42,Business travel,Business,2288,5,5,5,5,3,5,4,5,5,5,5,4,5,4,7,0.0,satisfied +33233,56060,Female,Loyal Customer,44,Personal Travel,Eco,2475,3,4,4,3,4,5,5,4,5,3,5,5,3,5,0,0.0,neutral or dissatisfied +33234,1397,Female,Loyal Customer,63,Personal Travel,Eco Plus,312,3,4,3,3,3,5,4,5,4,5,5,4,3,4,176,179.0,neutral or dissatisfied +33235,108912,Male,Loyal Customer,28,Business travel,Business,1183,2,2,2,2,2,2,2,2,2,5,2,2,2,2,16,19.0,neutral or dissatisfied +33236,89472,Male,disloyal Customer,27,Business travel,Eco Plus,151,3,4,4,4,5,4,5,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +33237,118087,Female,Loyal Customer,22,Business travel,Eco,1276,4,4,4,4,4,4,2,4,1,2,3,3,4,4,29,5.0,neutral or dissatisfied +33238,41574,Male,Loyal Customer,67,Personal Travel,Eco,715,1,1,1,3,2,1,2,2,1,4,4,2,3,2,7,21.0,neutral or dissatisfied +33239,74527,Female,Loyal Customer,51,Business travel,Eco,1464,2,3,3,3,1,2,3,2,2,2,2,2,2,3,5,0.0,neutral or dissatisfied +33240,115207,Male,Loyal Customer,35,Business travel,Business,1529,2,2,2,2,4,5,5,4,4,4,4,3,4,3,17,16.0,satisfied +33241,56995,Female,Loyal Customer,34,Personal Travel,Eco,2565,2,1,2,4,2,2,2,3,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +33242,114626,Female,Loyal Customer,53,Business travel,Business,2410,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +33243,102518,Male,Loyal Customer,35,Personal Travel,Eco,397,2,5,2,2,2,2,2,2,5,5,5,4,5,2,0,4.0,neutral or dissatisfied +33244,118819,Female,Loyal Customer,57,Business travel,Business,2272,2,2,2,2,2,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +33245,14828,Female,Loyal Customer,23,Personal Travel,Eco,314,3,5,3,2,5,3,5,5,4,2,4,5,4,5,120,111.0,neutral or dissatisfied +33246,52280,Male,Loyal Customer,55,Business travel,Eco,425,4,5,5,5,4,4,4,4,5,1,4,2,4,4,0,0.0,satisfied +33247,123858,Male,disloyal Customer,22,Business travel,Eco,541,5,0,5,1,3,5,3,3,3,2,4,3,5,3,45,23.0,satisfied +33248,4130,Female,disloyal Customer,24,Business travel,Business,431,5,2,5,1,3,5,3,3,3,5,4,4,5,3,0,0.0,satisfied +33249,61334,Female,disloyal Customer,33,Business travel,Business,602,2,2,2,1,2,2,5,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +33250,37601,Female,Loyal Customer,63,Personal Travel,Eco,950,5,3,5,3,1,4,4,2,2,5,2,4,2,2,31,38.0,satisfied +33251,56463,Male,Loyal Customer,42,Business travel,Business,3031,4,4,5,4,4,4,4,4,4,4,4,4,4,4,6,32.0,satisfied +33252,72754,Female,Loyal Customer,32,Personal Travel,Eco,806,3,3,2,3,3,2,3,3,1,5,3,2,3,3,9,10.0,neutral or dissatisfied +33253,15737,Female,Loyal Customer,52,Personal Travel,Eco,419,1,5,1,2,5,1,5,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +33254,32939,Female,Loyal Customer,64,Personal Travel,Eco,101,4,4,4,4,3,1,2,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +33255,90673,Female,Loyal Customer,41,Business travel,Business,406,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,4.0,satisfied +33256,116704,Female,Loyal Customer,28,Business travel,Eco Plus,446,1,1,1,1,1,1,1,1,3,4,3,3,3,1,0,18.0,neutral or dissatisfied +33257,91252,Female,Loyal Customer,13,Personal Travel,Eco,594,4,2,4,3,2,4,2,2,2,4,3,3,4,2,0,0.0,satisfied +33258,45288,Female,Loyal Customer,27,Business travel,Business,3430,2,2,2,2,5,5,5,5,3,2,5,5,5,5,9,11.0,satisfied +33259,1849,Female,Loyal Customer,57,Business travel,Business,3529,1,1,1,1,5,5,5,4,4,4,4,3,4,3,38,41.0,satisfied +33260,86717,Female,Loyal Customer,60,Business travel,Eco,247,2,5,5,5,1,5,1,2,2,2,2,5,2,5,7,3.0,satisfied +33261,93911,Male,Loyal Customer,49,Personal Travel,Business,507,1,5,3,3,3,4,5,3,3,3,3,5,3,4,12,0.0,neutral or dissatisfied +33262,61186,Female,Loyal Customer,27,Business travel,Business,967,1,3,3,3,1,2,1,1,4,3,3,4,4,1,2,0.0,neutral or dissatisfied +33263,35842,Female,Loyal Customer,31,Business travel,Business,937,2,2,2,2,5,5,5,5,1,2,3,4,5,5,0,0.0,satisfied +33264,81248,Female,Loyal Customer,32,Personal Travel,Eco Plus,980,1,2,1,2,1,1,1,1,3,5,2,2,2,1,0,0.0,neutral or dissatisfied +33265,115242,Male,Loyal Customer,57,Business travel,Business,2471,1,1,1,1,3,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +33266,117278,Male,Loyal Customer,49,Business travel,Business,1716,5,5,5,5,2,5,5,4,4,4,4,5,4,4,33,17.0,satisfied +33267,121113,Female,disloyal Customer,25,Business travel,Business,1444,5,4,5,3,1,5,1,1,4,3,3,4,4,1,25,6.0,satisfied +33268,18639,Male,Loyal Customer,62,Personal Travel,Eco,201,3,2,3,3,4,3,4,4,4,5,2,3,3,4,0,0.0,neutral or dissatisfied +33269,98197,Male,disloyal Customer,21,Business travel,Eco,327,4,0,4,4,4,4,4,4,5,2,3,5,4,4,0,0.0,neutral or dissatisfied +33270,117349,Female,Loyal Customer,39,Business travel,Business,2839,0,0,0,1,3,4,4,2,2,2,2,3,2,4,0,7.0,satisfied +33271,6694,Male,Loyal Customer,16,Business travel,Business,3184,3,1,1,1,3,2,3,3,1,1,3,2,4,3,0,,neutral or dissatisfied +33272,30974,Female,Loyal Customer,53,Business travel,Eco,1476,5,5,5,5,1,2,3,5,5,5,5,3,5,4,0,10.0,satisfied +33273,67692,Female,Loyal Customer,52,Business travel,Business,1464,2,3,2,2,4,5,5,4,4,4,4,4,4,4,13,2.0,satisfied +33274,4108,Female,Loyal Customer,25,Business travel,Business,1630,3,3,3,3,3,3,3,3,1,3,2,2,2,3,123,102.0,neutral or dissatisfied +33275,26005,Female,Loyal Customer,39,Business travel,Business,3366,1,1,2,1,3,4,5,5,5,5,5,3,5,1,10,2.0,satisfied +33276,59746,Male,Loyal Customer,40,Business travel,Business,1025,3,2,3,3,3,4,4,5,5,5,5,3,5,3,0,9.0,satisfied +33277,113475,Male,Loyal Customer,26,Business travel,Business,223,1,1,4,1,5,5,5,5,4,4,5,5,4,5,0,2.0,satisfied +33278,5769,Female,Loyal Customer,31,Business travel,Business,665,2,2,2,2,2,2,2,2,4,2,3,1,4,2,4,0.0,neutral or dissatisfied +33279,6075,Female,Loyal Customer,57,Personal Travel,Eco,691,2,5,2,4,3,5,4,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +33280,38341,Female,disloyal Customer,23,Business travel,Eco,1180,4,4,4,1,2,4,1,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +33281,93421,Female,Loyal Customer,49,Business travel,Eco,605,2,3,3,3,4,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +33282,34829,Male,disloyal Customer,23,Business travel,Eco,209,2,5,2,2,2,2,3,5,1,1,2,3,2,3,210,257.0,neutral or dissatisfied +33283,12906,Male,disloyal Customer,25,Business travel,Eco,809,1,1,1,4,1,1,1,1,2,1,3,2,4,1,10,0.0,neutral or dissatisfied +33284,89965,Female,Loyal Customer,52,Personal Travel,Eco,1306,3,5,3,4,3,5,5,4,3,5,4,5,4,5,271,275.0,neutral or dissatisfied +33285,58107,Male,Loyal Customer,64,Personal Travel,Eco,589,3,4,4,4,4,4,4,4,4,4,4,3,4,4,9,10.0,neutral or dissatisfied +33286,46083,Male,disloyal Customer,24,Business travel,Eco,495,1,3,1,4,2,1,2,2,3,2,4,2,4,2,0,56.0,neutral or dissatisfied +33287,48222,Female,Loyal Customer,22,Personal Travel,Eco,192,2,4,2,5,2,2,4,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +33288,79914,Male,disloyal Customer,26,Business travel,Eco,950,2,2,2,1,4,2,4,4,3,5,2,4,1,4,0,0.0,neutral or dissatisfied +33289,98505,Female,Loyal Customer,60,Business travel,Business,2034,2,2,2,2,5,5,4,3,3,4,3,3,3,4,8,0.0,satisfied +33290,6386,Male,disloyal Customer,38,Business travel,Eco,296,1,4,1,3,3,1,2,3,2,3,4,4,4,3,0,10.0,neutral or dissatisfied +33291,109832,Female,Loyal Customer,45,Business travel,Business,1011,3,3,3,3,3,5,5,4,4,3,4,4,4,4,15,0.0,satisfied +33292,92868,Male,Loyal Customer,61,Personal Travel,Eco,2519,2,3,2,3,4,2,4,4,4,2,2,2,2,4,13,1.0,neutral or dissatisfied +33293,73988,Female,Loyal Customer,43,Personal Travel,Eco Plus,2330,2,4,2,4,2,3,3,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +33294,34993,Male,Loyal Customer,30,Business travel,Business,1182,3,3,5,3,5,4,5,5,5,4,5,5,5,5,84,100.0,satisfied +33295,110006,Male,Loyal Customer,49,Business travel,Business,2435,1,1,1,1,5,3,2,1,1,1,1,3,1,3,3,1.0,neutral or dissatisfied +33296,42801,Female,Loyal Customer,25,Business travel,Eco,677,5,1,1,1,5,5,5,5,5,5,3,3,5,5,56,48.0,satisfied +33297,127812,Male,Loyal Customer,40,Business travel,Business,2502,2,3,3,3,3,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +33298,80834,Female,Loyal Customer,44,Business travel,Eco,484,3,1,2,1,1,1,1,3,3,3,3,3,3,3,59,66.0,neutral or dissatisfied +33299,35092,Female,disloyal Customer,29,Business travel,Eco,1069,2,3,3,1,4,3,4,4,1,2,5,3,3,4,4,17.0,neutral or dissatisfied +33300,103799,Male,Loyal Customer,51,Business travel,Business,3993,3,3,3,3,3,4,5,4,4,4,4,3,4,5,24,11.0,satisfied +33301,98006,Female,Loyal Customer,48,Personal Travel,Eco Plus,483,3,3,3,3,2,2,3,3,3,3,3,2,3,2,14,1.0,neutral or dissatisfied +33302,23899,Male,Loyal Customer,42,Business travel,Business,3536,1,4,4,4,4,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +33303,78099,Male,Loyal Customer,60,Business travel,Eco,684,3,4,4,4,3,3,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +33304,28214,Female,disloyal Customer,22,Business travel,Eco,834,2,2,2,4,3,2,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +33305,86418,Female,Loyal Customer,59,Business travel,Business,2918,3,3,4,3,4,5,4,4,4,4,4,3,4,5,33,26.0,satisfied +33306,108127,Female,Loyal Customer,17,Business travel,Business,3550,2,3,3,3,2,2,2,2,4,4,3,4,4,2,1,1.0,neutral or dissatisfied +33307,40013,Female,Loyal Customer,51,Business travel,Eco,525,2,5,5,5,2,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +33308,74531,Female,disloyal Customer,46,Business travel,Eco,1235,3,3,3,4,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +33309,15454,Female,Loyal Customer,37,Business travel,Business,2545,4,4,4,4,1,2,1,5,5,5,5,5,5,4,20,13.0,satisfied +33310,95772,Female,Loyal Customer,18,Personal Travel,Eco,237,2,5,2,2,3,2,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +33311,35388,Male,Loyal Customer,57,Business travel,Eco,610,2,4,4,4,2,2,2,2,2,4,5,5,4,2,9,20.0,satisfied +33312,99547,Male,Loyal Customer,32,Business travel,Business,2142,5,5,5,5,4,5,4,4,5,2,4,4,4,4,0,0.0,satisfied +33313,121572,Female,Loyal Customer,41,Business travel,Business,936,4,4,4,4,3,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +33314,26786,Male,Loyal Customer,43,Business travel,Eco Plus,1199,1,0,0,4,4,1,4,4,4,2,3,1,3,4,0,0.0,neutral or dissatisfied +33315,7797,Female,Loyal Customer,21,Business travel,Business,650,1,1,1,1,4,5,4,4,3,4,5,3,5,4,0,0.0,satisfied +33316,72463,Female,Loyal Customer,43,Business travel,Business,3930,5,5,5,5,5,5,4,4,4,4,4,3,4,3,3,4.0,satisfied +33317,73099,Male,Loyal Customer,23,Business travel,Business,2174,4,4,4,4,4,4,4,4,5,5,5,3,5,4,27,17.0,satisfied +33318,21346,Male,disloyal Customer,35,Business travel,Eco,674,3,3,3,3,3,3,1,3,3,5,4,1,3,3,52,48.0,neutral or dissatisfied +33319,110696,Male,Loyal Customer,9,Personal Travel,Eco,1005,2,5,2,3,5,2,5,5,4,4,2,3,5,5,1,0.0,neutral or dissatisfied +33320,112631,Female,Loyal Customer,53,Business travel,Business,602,3,3,3,3,5,4,5,4,4,4,4,4,4,4,1,6.0,satisfied +33321,78608,Male,Loyal Customer,43,Business travel,Business,1426,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +33322,85832,Female,Loyal Customer,33,Personal Travel,Eco,526,1,4,1,4,3,1,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +33323,120963,Male,Loyal Customer,17,Business travel,Business,3582,2,5,5,5,2,2,2,2,3,4,4,4,3,2,8,107.0,neutral or dissatisfied +33324,50431,Male,Loyal Customer,17,Business travel,Business,2846,1,1,1,1,4,4,4,4,4,5,3,5,5,4,0,0.0,satisfied +33325,119728,Female,Loyal Customer,37,Business travel,Eco,903,2,5,5,5,2,2,2,2,2,5,4,3,3,2,14,1.0,neutral or dissatisfied +33326,64624,Female,Loyal Customer,39,Business travel,Business,551,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +33327,113686,Male,Loyal Customer,56,Personal Travel,Eco,397,3,4,3,5,1,3,1,1,4,3,5,3,4,1,15,7.0,neutral or dissatisfied +33328,42109,Male,disloyal Customer,36,Business travel,Eco,898,2,2,2,2,2,2,2,2,3,2,1,5,3,2,0,0.0,neutral or dissatisfied +33329,128070,Female,disloyal Customer,24,Business travel,Eco,1205,4,4,4,2,4,1,1,5,5,5,4,1,5,1,9,0.0,neutral or dissatisfied +33330,26307,Male,Loyal Customer,36,Business travel,Eco,2139,4,1,1,1,4,4,4,4,3,1,4,5,1,4,44,38.0,satisfied +33331,48274,Female,Loyal Customer,59,Business travel,Eco Plus,236,2,3,3,3,1,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +33332,116486,Male,Loyal Customer,47,Personal Travel,Eco,325,2,4,3,3,1,3,1,1,3,2,4,3,3,1,89,81.0,neutral or dissatisfied +33333,12472,Male,Loyal Customer,26,Personal Travel,Eco,192,3,3,3,3,2,3,2,2,3,1,2,4,1,2,17,15.0,neutral or dissatisfied +33334,109451,Female,disloyal Customer,22,Business travel,Eco,861,2,2,2,1,5,2,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +33335,42479,Female,Loyal Customer,52,Business travel,Eco Plus,429,2,2,2,2,4,2,5,2,2,2,2,1,2,3,0,2.0,satisfied +33336,115037,Male,Loyal Customer,33,Business travel,Business,480,4,1,5,1,4,4,4,4,4,5,2,3,3,4,0,0.0,neutral or dissatisfied +33337,3383,Female,Loyal Customer,56,Business travel,Business,1733,4,2,4,4,5,4,5,5,5,5,5,5,5,3,3,0.0,satisfied +33338,33202,Female,Loyal Customer,51,Business travel,Eco Plus,102,4,3,5,5,5,4,1,4,4,4,4,4,4,3,0,0.0,satisfied +33339,53436,Female,Loyal Customer,25,Business travel,Eco,2419,5,5,5,5,5,5,4,5,3,3,5,3,4,5,3,2.0,satisfied +33340,86296,Female,Loyal Customer,12,Personal Travel,Eco,356,2,5,2,1,4,2,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +33341,102250,Female,Loyal Customer,60,Business travel,Business,414,3,3,3,3,5,4,5,4,4,4,4,3,4,5,46,47.0,satisfied +33342,125913,Male,Loyal Customer,63,Personal Travel,Eco,992,3,5,4,1,3,4,3,3,5,4,4,3,5,3,28,18.0,neutral or dissatisfied +33343,27295,Female,Loyal Customer,26,Business travel,Business,1738,5,5,5,5,2,2,2,2,4,5,4,5,2,2,1,0.0,satisfied +33344,15917,Male,Loyal Customer,43,Business travel,Business,1627,4,4,3,4,3,4,5,4,4,4,4,5,4,3,109,128.0,satisfied +33345,33768,Female,Loyal Customer,27,Business travel,Eco,1990,3,1,1,1,3,3,3,3,3,3,1,4,1,3,19,61.0,neutral or dissatisfied +33346,100023,Female,Loyal Customer,42,Business travel,Eco,289,3,2,4,2,4,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +33347,103627,Female,disloyal Customer,46,Business travel,Business,405,3,4,4,3,5,3,5,5,5,2,4,4,4,5,1,0.0,neutral or dissatisfied +33348,2795,Male,Loyal Customer,39,Business travel,Eco,365,4,4,4,4,4,4,4,4,1,5,3,4,4,4,0,0.0,neutral or dissatisfied +33349,28685,Female,Loyal Customer,23,Personal Travel,Eco,2777,1,1,1,4,1,5,5,2,3,4,4,5,4,5,96,87.0,neutral or dissatisfied +33350,71128,Female,Loyal Customer,57,Business travel,Business,1739,2,2,2,2,4,4,4,3,3,4,3,5,3,3,31,21.0,satisfied +33351,119883,Male,Loyal Customer,50,Personal Travel,Eco,936,4,5,3,2,5,3,1,5,5,3,4,2,3,5,22,29.0,neutral or dissatisfied +33352,36915,Male,Loyal Customer,39,Business travel,Eco,740,4,2,2,2,4,4,4,4,1,1,4,2,2,4,3,0.0,satisfied +33353,105851,Male,disloyal Customer,18,Business travel,Eco Plus,883,3,2,3,3,5,3,5,5,1,5,3,1,4,5,9,0.0,neutral or dissatisfied +33354,2430,Female,Loyal Customer,32,Personal Travel,Eco,767,4,4,4,4,1,4,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +33355,14732,Male,Loyal Customer,38,Business travel,Business,3499,2,2,2,2,4,4,4,5,5,5,5,5,5,3,20,10.0,satisfied +33356,108043,Male,Loyal Customer,18,Personal Travel,Business,591,1,5,1,5,3,1,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +33357,95436,Female,Loyal Customer,55,Business travel,Business,248,3,3,3,3,3,5,5,5,5,5,5,4,5,3,0,3.0,satisfied +33358,46758,Female,Loyal Customer,52,Business travel,Eco Plus,125,4,2,2,2,4,5,3,4,4,4,4,5,4,2,0,3.0,satisfied +33359,15077,Female,Loyal Customer,30,Business travel,Business,2481,0,0,0,1,1,1,1,1,5,2,4,1,5,1,0,0.0,satisfied +33360,58692,Female,Loyal Customer,9,Personal Travel,Eco,299,3,3,3,3,3,3,3,3,4,4,1,1,1,3,0,0.0,neutral or dissatisfied +33361,63352,Female,Loyal Customer,26,Personal Travel,Eco,447,1,4,1,2,4,1,4,4,4,3,5,5,4,4,10,0.0,neutral or dissatisfied +33362,4713,Male,Loyal Customer,50,Personal Travel,Eco Plus,489,1,3,1,5,2,1,2,2,2,4,1,2,3,2,42,30.0,neutral or dissatisfied +33363,60738,Male,Loyal Customer,51,Personal Travel,Eco Plus,1605,3,4,2,3,5,2,5,5,5,2,5,5,4,5,48,69.0,neutral or dissatisfied +33364,52193,Female,Loyal Customer,23,Business travel,Eco,370,4,4,4,4,4,4,5,4,3,2,5,4,1,4,84,86.0,satisfied +33365,99295,Male,Loyal Customer,63,Personal Travel,Eco Plus,935,2,1,2,4,1,2,1,1,2,4,4,1,3,1,0,19.0,neutral or dissatisfied +33366,17768,Male,Loyal Customer,63,Business travel,Business,1843,5,5,4,5,2,5,5,3,3,5,3,4,3,2,21,35.0,satisfied +33367,23266,Female,Loyal Customer,57,Business travel,Eco,426,4,5,5,5,1,5,3,4,4,4,4,3,4,2,15,14.0,satisfied +33368,40446,Male,Loyal Customer,32,Business travel,Business,150,0,4,0,3,4,1,1,4,4,2,3,1,1,4,0,0.0,satisfied +33369,103193,Female,disloyal Customer,52,Business travel,Eco,814,3,3,3,4,1,3,1,1,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +33370,66437,Male,Loyal Customer,40,Business travel,Business,2096,2,2,2,2,3,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +33371,78742,Male,Loyal Customer,39,Business travel,Business,447,4,1,1,1,1,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +33372,80821,Female,Loyal Customer,52,Business travel,Business,2769,1,3,3,3,3,4,3,1,1,1,1,2,1,2,17,13.0,neutral or dissatisfied +33373,35803,Male,Loyal Customer,55,Business travel,Business,2526,5,4,5,5,4,4,4,5,5,5,5,4,5,4,14,9.0,satisfied +33374,64755,Female,Loyal Customer,62,Business travel,Business,2651,2,5,4,4,3,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +33375,51249,Male,disloyal Customer,20,Business travel,Eco,337,3,1,3,3,4,3,4,4,2,4,2,4,3,4,4,1.0,neutral or dissatisfied +33376,39394,Female,Loyal Customer,29,Business travel,Business,521,4,4,4,4,2,3,2,2,4,1,4,4,3,2,0,0.0,satisfied +33377,33487,Female,disloyal Customer,20,Business travel,Eco,881,1,1,1,3,3,1,1,3,2,1,2,3,4,3,44,41.0,neutral or dissatisfied +33378,61112,Female,disloyal Customer,38,Business travel,Eco Plus,209,4,4,4,3,4,4,4,4,5,4,2,5,3,4,0,0.0,neutral or dissatisfied +33379,93691,Male,Loyal Customer,56,Business travel,Eco,1452,2,5,5,5,2,2,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +33380,63095,Female,Loyal Customer,60,Business travel,Business,3609,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +33381,20527,Female,disloyal Customer,52,Business travel,Eco,773,5,5,5,4,3,5,5,3,5,2,3,5,1,3,0,0.0,satisfied +33382,34390,Male,disloyal Customer,52,Business travel,Eco,612,3,5,3,3,2,3,2,2,2,5,4,4,1,2,111,108.0,neutral or dissatisfied +33383,2326,Female,Loyal Customer,36,Personal Travel,Eco,691,4,2,4,4,5,4,5,5,3,3,4,2,3,5,0,1.0,satisfied +33384,53836,Male,Loyal Customer,37,Business travel,Eco,140,4,1,2,1,4,5,4,4,4,3,4,2,1,4,0,0.0,satisfied +33385,21711,Male,Loyal Customer,43,Business travel,Eco Plus,746,5,2,2,2,5,5,5,5,3,4,4,4,3,5,0,0.0,satisfied +33386,65550,Female,disloyal Customer,38,Business travel,Business,175,4,4,4,1,1,4,1,1,5,2,5,3,5,1,18,10.0,satisfied +33387,116714,Female,disloyal Customer,23,Business travel,Eco Plus,325,3,3,3,2,4,3,4,4,1,4,1,4,5,4,9,6.0,neutral or dissatisfied +33388,70919,Female,disloyal Customer,23,Business travel,Eco,612,2,0,2,3,5,2,1,5,5,5,4,3,5,5,25,10.0,neutral or dissatisfied +33389,84529,Male,disloyal Customer,36,Business travel,Business,2399,2,2,2,3,2,2,2,2,4,4,3,4,5,2,0,0.0,neutral or dissatisfied +33390,301,Male,Loyal Customer,40,Business travel,Business,821,2,2,2,2,5,5,4,3,3,2,3,5,3,4,18,19.0,satisfied +33391,110292,Female,Loyal Customer,42,Business travel,Business,842,1,1,1,1,4,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +33392,105102,Female,Loyal Customer,34,Business travel,Business,3885,0,0,0,3,2,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +33393,90914,Female,Loyal Customer,24,Business travel,Eco,406,5,1,1,1,5,5,4,5,1,4,2,3,5,5,0,0.0,satisfied +33394,37846,Female,Loyal Customer,39,Business travel,Eco,1065,4,1,1,1,4,4,4,4,2,1,4,3,3,4,0,0.0,satisfied +33395,89327,Female,Loyal Customer,35,Business travel,Business,1587,3,3,3,3,4,5,4,5,5,5,5,3,5,5,12,6.0,satisfied +33396,9718,Female,Loyal Customer,16,Personal Travel,Eco,277,3,3,3,3,2,3,2,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +33397,68405,Male,disloyal Customer,24,Business travel,Eco,1045,2,2,2,4,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +33398,2268,Female,Loyal Customer,52,Business travel,Business,1677,3,3,3,3,2,5,5,4,4,4,4,4,4,4,16,12.0,satisfied +33399,121377,Female,Loyal Customer,50,Business travel,Business,2279,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +33400,52418,Male,Loyal Customer,50,Personal Travel,Eco,451,2,4,2,3,5,2,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +33401,94568,Female,disloyal Customer,26,Business travel,Business,293,0,5,0,2,5,0,5,5,3,3,4,5,5,5,50,51.0,satisfied +33402,96170,Male,Loyal Customer,33,Business travel,Business,786,2,2,2,2,5,5,5,5,3,3,4,3,4,5,4,1.0,satisfied +33403,16702,Male,Loyal Customer,56,Business travel,Business,1685,3,5,3,3,1,2,5,4,4,4,4,5,4,5,15,18.0,satisfied +33404,52450,Male,Loyal Customer,24,Business travel,Eco Plus,370,4,4,4,4,4,4,5,4,4,3,4,5,2,4,0,4.0,satisfied +33405,36066,Male,Loyal Customer,53,Business travel,Eco,399,3,4,4,4,3,3,3,3,1,1,3,4,3,3,3,6.0,neutral or dissatisfied +33406,23057,Male,Loyal Customer,38,Business travel,Business,3266,1,1,1,1,1,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +33407,80941,Male,Loyal Customer,69,Personal Travel,Eco,341,2,5,2,5,5,2,5,5,5,3,5,4,5,5,7,12.0,neutral or dissatisfied +33408,91056,Female,Loyal Customer,37,Personal Travel,Eco,581,2,4,2,3,4,2,5,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +33409,81033,Male,disloyal Customer,9,Business travel,Eco,1399,3,2,2,3,5,3,5,5,2,4,4,3,4,5,101,90.0,neutral or dissatisfied +33410,15579,Male,disloyal Customer,27,Business travel,Business,229,2,1,1,3,5,1,5,5,4,2,5,2,4,5,84,78.0,neutral or dissatisfied +33411,120463,Male,Loyal Customer,57,Personal Travel,Eco,337,2,4,2,5,2,2,3,2,3,4,2,3,5,2,0,0.0,neutral or dissatisfied +33412,44574,Male,Loyal Customer,38,Business travel,Business,3465,0,4,0,3,4,5,1,2,2,2,2,4,2,4,0,0.0,satisfied +33413,24410,Male,Loyal Customer,50,Business travel,Eco,634,4,2,2,2,4,4,4,4,4,2,4,5,1,4,12,16.0,satisfied +33414,67679,Female,disloyal Customer,35,Business travel,Business,1431,3,3,3,3,2,3,2,2,5,5,4,3,5,2,17,24.0,neutral or dissatisfied +33415,5868,Female,Loyal Customer,42,Personal Travel,Eco Plus,1020,1,0,1,4,3,5,5,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +33416,97386,Male,Loyal Customer,58,Personal Travel,Eco,347,1,5,5,3,5,5,5,5,4,5,5,3,4,5,2,2.0,neutral or dissatisfied +33417,30673,Male,disloyal Customer,50,Business travel,Business,280,2,2,2,4,4,2,4,4,1,3,3,3,3,4,59,73.0,neutral or dissatisfied +33418,64530,Male,Loyal Customer,39,Business travel,Business,2072,3,3,3,3,2,4,5,5,5,5,5,3,5,4,0,5.0,satisfied +33419,106719,Female,Loyal Customer,21,Business travel,Business,2364,5,5,5,5,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +33420,76047,Female,Loyal Customer,44,Business travel,Business,669,1,1,1,1,3,4,5,3,3,3,3,4,3,5,0,8.0,satisfied +33421,17468,Male,Loyal Customer,17,Business travel,Business,2595,5,5,5,5,4,4,4,4,3,2,4,3,5,4,0,0.0,satisfied +33422,85020,Female,Loyal Customer,25,Personal Travel,Eco,1590,4,5,4,3,3,4,3,3,3,5,5,4,5,3,16,20.0,satisfied +33423,115321,Male,Loyal Customer,50,Business travel,Business,3205,0,0,0,1,2,4,5,3,3,3,3,5,3,3,29,23.0,satisfied +33424,77184,Female,disloyal Customer,37,Business travel,Business,290,3,3,3,3,2,3,2,2,5,5,5,3,4,2,16,7.0,neutral or dissatisfied +33425,28043,Female,Loyal Customer,26,Business travel,Eco Plus,2537,4,5,4,5,4,4,5,4,2,1,4,1,2,4,0,0.0,satisfied +33426,112059,Female,disloyal Customer,23,Business travel,Business,1046,0,4,0,4,1,0,1,1,5,4,4,4,5,1,0,0.0,satisfied +33427,20963,Male,Loyal Customer,51,Business travel,Business,3269,1,1,4,1,4,4,5,4,4,5,4,2,4,2,0,0.0,satisfied +33428,112148,Female,Loyal Customer,52,Business travel,Eco,895,4,4,4,4,5,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +33429,122462,Female,Loyal Customer,32,Business travel,Business,3054,5,5,3,5,3,4,3,3,3,3,4,3,4,3,1,1.0,satisfied +33430,36502,Female,Loyal Customer,48,Business travel,Business,2251,1,1,1,1,3,4,3,2,2,2,2,5,2,2,0,0.0,satisfied +33431,93684,Female,Loyal Customer,34,Personal Travel,Business,1452,2,1,2,3,2,3,4,1,1,2,1,1,1,3,1,0.0,neutral or dissatisfied +33432,91955,Male,Loyal Customer,69,Personal Travel,Eco,2586,1,4,1,3,3,1,3,3,5,4,3,3,4,3,0,0.0,neutral or dissatisfied +33433,45702,Male,Loyal Customer,43,Business travel,Business,2298,4,4,3,4,3,1,5,4,4,5,4,5,4,5,7,33.0,satisfied +33434,1113,Male,Loyal Customer,64,Personal Travel,Eco,354,3,4,3,3,5,3,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +33435,93078,Female,Loyal Customer,44,Business travel,Business,1995,4,4,5,4,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +33436,25446,Female,Loyal Customer,26,Personal Travel,Eco,669,2,3,2,2,5,2,5,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +33437,12203,Female,disloyal Customer,20,Business travel,Eco,201,2,5,2,4,2,2,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +33438,34715,Male,Loyal Customer,64,Business travel,Business,264,3,3,2,3,2,2,1,4,4,4,4,1,4,3,0,0.0,satisfied +33439,1836,Female,Loyal Customer,55,Personal Travel,Eco,500,2,3,2,3,5,3,3,1,1,2,1,2,1,3,20,10.0,neutral or dissatisfied +33440,94545,Male,Loyal Customer,56,Business travel,Business,189,0,5,1,1,4,5,5,5,5,5,5,5,5,5,12,2.0,satisfied +33441,88716,Male,Loyal Customer,58,Personal Travel,Eco,404,1,5,1,2,3,1,5,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +33442,11654,Male,Loyal Customer,79,Business travel,Business,525,1,1,4,1,1,5,1,4,4,4,4,3,4,3,0,0.0,satisfied +33443,75306,Female,Loyal Customer,44,Business travel,Business,2556,3,3,3,3,5,5,5,4,4,3,5,5,4,5,138,162.0,satisfied +33444,22602,Male,Loyal Customer,37,Business travel,Business,300,5,5,5,5,4,1,3,5,5,4,5,4,5,3,6,0.0,satisfied +33445,3905,Female,Loyal Customer,63,Personal Travel,Eco,213,3,0,3,3,2,5,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +33446,72095,Female,Loyal Customer,64,Personal Travel,Eco,2556,0,3,0,3,4,3,4,2,2,0,2,2,2,3,0,0.0,satisfied +33447,111825,Female,disloyal Customer,29,Business travel,Business,1605,2,2,2,3,4,2,5,4,4,3,3,3,4,4,8,4.0,neutral or dissatisfied +33448,82565,Female,Loyal Customer,50,Business travel,Business,3962,4,4,1,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +33449,68643,Female,disloyal Customer,56,Business travel,Business,175,3,3,3,4,4,3,5,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +33450,59685,Male,Loyal Customer,16,Personal Travel,Eco,964,2,3,2,3,3,2,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +33451,57571,Male,disloyal Customer,42,Business travel,Eco,1597,2,2,2,2,2,3,3,2,4,1,2,3,1,3,154,205.0,neutral or dissatisfied +33452,33280,Female,Loyal Customer,42,Personal Travel,Eco Plus,163,1,3,1,4,3,4,4,2,2,1,2,4,2,4,0,2.0,neutral or dissatisfied +33453,121683,Female,Loyal Customer,29,Personal Travel,Eco,328,5,3,5,2,1,5,1,1,2,1,3,2,2,1,9,8.0,satisfied +33454,9107,Male,disloyal Customer,14,Business travel,Business,707,5,4,5,5,1,5,1,1,4,4,4,3,4,1,0,0.0,satisfied +33455,18202,Female,disloyal Customer,40,Business travel,Business,179,2,2,2,4,1,2,1,1,1,3,3,1,2,1,11,2.0,neutral or dissatisfied +33456,21125,Male,Loyal Customer,69,Personal Travel,Eco,106,1,4,1,3,2,1,2,2,5,3,5,4,5,2,27,25.0,neutral or dissatisfied +33457,76049,Male,Loyal Customer,60,Business travel,Business,3259,1,1,2,1,3,5,5,5,5,5,5,3,5,4,7,0.0,satisfied +33458,92869,Female,Loyal Customer,51,Personal Travel,Eco,2519,3,2,3,3,5,3,2,1,1,3,1,1,1,3,5,2.0,neutral or dissatisfied +33459,124561,Female,Loyal Customer,49,Business travel,Business,453,2,2,2,2,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +33460,20124,Male,Loyal Customer,14,Personal Travel,Eco,416,3,4,3,4,3,1,1,4,3,4,3,1,3,1,177,159.0,neutral or dissatisfied +33461,31176,Male,disloyal Customer,38,Business travel,Eco,971,3,3,3,4,5,3,5,5,2,5,5,5,5,5,0,0.0,neutral or dissatisfied +33462,84168,Female,disloyal Customer,32,Business travel,Business,231,4,4,4,3,4,4,2,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +33463,75688,Male,Loyal Customer,48,Business travel,Business,868,3,2,3,3,4,4,5,5,5,5,5,5,5,3,0,7.0,satisfied +33464,45244,Male,Loyal Customer,53,Personal Travel,Eco,1013,5,3,5,2,4,5,4,4,1,2,3,1,2,4,0,0.0,satisfied +33465,30522,Female,Loyal Customer,47,Business travel,Business,2898,2,5,3,3,4,3,3,2,2,2,2,2,2,2,0,28.0,neutral or dissatisfied +33466,91707,Female,disloyal Customer,23,Business travel,Eco,588,5,5,5,2,3,5,3,3,4,3,4,4,5,3,0,2.0,satisfied +33467,106735,Female,Loyal Customer,29,Business travel,Business,2811,2,3,3,3,2,2,2,2,2,1,3,2,4,2,0,7.0,neutral or dissatisfied +33468,57378,Male,Loyal Customer,27,Personal Travel,Eco Plus,236,3,3,3,2,2,3,2,2,2,1,3,2,3,2,0,18.0,neutral or dissatisfied +33469,48672,Male,Loyal Customer,39,Business travel,Business,3729,0,4,1,1,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +33470,86926,Male,Loyal Customer,68,Personal Travel,Eco,352,2,4,5,2,3,5,3,3,5,3,4,5,4,3,42,,neutral or dissatisfied +33471,19793,Female,Loyal Customer,67,Personal Travel,Eco,578,3,4,3,3,2,5,5,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +33472,77165,Female,Loyal Customer,54,Personal Travel,Eco,1450,3,3,3,4,4,3,4,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +33473,112081,Female,disloyal Customer,54,Business travel,Eco,1091,1,1,1,3,4,1,4,4,4,2,4,3,4,4,99,112.0,neutral or dissatisfied +33474,97988,Male,Loyal Customer,25,Personal Travel,Eco,793,3,4,2,4,5,2,5,5,4,2,5,3,4,5,7,23.0,neutral or dissatisfied +33475,103579,Female,Loyal Customer,22,Personal Travel,Eco,604,1,5,1,1,4,1,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +33476,39401,Female,disloyal Customer,27,Business travel,Eco,146,3,4,3,4,3,3,3,3,4,5,5,2,4,3,0,2.0,neutral or dissatisfied +33477,98477,Female,disloyal Customer,34,Business travel,Business,668,2,2,2,3,2,5,5,4,2,5,4,5,4,5,150,160.0,neutral or dissatisfied +33478,20830,Female,Loyal Customer,43,Business travel,Business,1798,5,5,5,5,3,4,3,4,4,4,4,5,4,2,5,0.0,satisfied +33479,126449,Male,Loyal Customer,57,Business travel,Business,1849,4,2,2,2,1,2,3,4,4,4,4,3,4,4,0,6.0,neutral or dissatisfied +33480,84224,Male,Loyal Customer,70,Personal Travel,Eco,432,3,3,3,4,5,3,5,5,2,1,4,3,4,5,44,33.0,neutral or dissatisfied +33481,456,Female,Loyal Customer,34,Business travel,Business,3310,5,5,5,5,2,5,5,5,5,5,5,4,5,3,1,1.0,satisfied +33482,8003,Male,Loyal Customer,21,Personal Travel,Business,335,3,5,2,3,3,2,3,3,5,2,5,3,5,3,0,7.0,neutral or dissatisfied +33483,26152,Male,disloyal Customer,20,Business travel,Eco,270,4,1,4,2,1,4,1,1,1,1,2,3,2,1,4,0.0,neutral or dissatisfied +33484,90640,Male,disloyal Customer,23,Business travel,Business,250,0,5,0,1,4,0,4,4,4,5,4,5,5,4,0,9.0,satisfied +33485,4778,Female,Loyal Customer,45,Business travel,Business,403,2,2,2,2,2,5,5,4,4,4,4,5,4,5,7,0.0,satisfied +33486,93130,Male,Loyal Customer,36,Business travel,Eco,1075,2,5,5,5,2,2,2,2,4,5,3,3,2,2,9,6.0,neutral or dissatisfied +33487,11345,Female,Loyal Customer,67,Personal Travel,Eco,667,2,4,2,3,4,5,5,1,1,2,1,4,1,5,3,1.0,neutral or dissatisfied +33488,84650,Female,Loyal Customer,40,Business travel,Business,363,4,4,4,4,5,4,5,5,5,4,5,5,5,4,0,1.0,satisfied +33489,25186,Female,disloyal Customer,27,Business travel,Eco,577,2,2,2,3,3,2,3,3,3,5,2,3,2,3,0,0.0,neutral or dissatisfied +33490,48470,Female,Loyal Customer,20,Business travel,Business,848,5,5,5,5,4,4,4,4,1,5,2,3,1,4,0,0.0,satisfied +33491,63934,Female,Loyal Customer,61,Personal Travel,Eco,1158,4,4,4,5,2,3,5,5,5,4,5,4,5,4,3,11.0,neutral or dissatisfied +33492,125115,Female,disloyal Customer,23,Business travel,Eco,361,2,5,2,4,1,2,1,1,4,1,3,2,3,1,4,18.0,neutral or dissatisfied +33493,53332,Male,Loyal Customer,80,Business travel,Eco Plus,411,2,3,4,3,3,2,3,3,2,1,3,4,4,3,71,58.0,neutral or dissatisfied +33494,101431,Male,disloyal Customer,21,Business travel,Business,345,4,3,4,3,4,4,4,4,2,1,3,4,3,4,24,21.0,neutral or dissatisfied +33495,92281,Female,Loyal Customer,28,Personal Travel,Eco,2036,3,5,3,2,1,3,1,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +33496,127634,Female,disloyal Customer,23,Business travel,Eco,273,2,5,2,3,3,2,4,3,2,2,3,3,5,3,4,0.0,neutral or dissatisfied +33497,30374,Female,Loyal Customer,12,Business travel,Business,3974,2,1,1,1,2,2,2,2,2,2,3,3,3,2,0,7.0,neutral or dissatisfied +33498,18461,Female,Loyal Customer,31,Business travel,Eco,127,4,1,1,1,4,4,4,4,5,4,2,3,4,4,0,0.0,satisfied +33499,53459,Male,Loyal Customer,39,Business travel,Business,2253,3,1,1,1,2,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +33500,76036,Male,Loyal Customer,44,Business travel,Eco Plus,237,1,2,2,2,1,1,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +33501,64313,Male,Loyal Customer,28,Business travel,Business,1811,1,1,1,1,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +33502,60832,Male,Loyal Customer,37,Personal Travel,Eco Plus,680,3,4,3,4,5,3,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +33503,109425,Male,Loyal Customer,47,Business travel,Business,3612,3,2,2,2,3,4,4,3,3,3,3,1,3,1,1,0.0,neutral or dissatisfied +33504,64773,Male,Loyal Customer,51,Business travel,Business,224,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +33505,129289,Male,Loyal Customer,51,Business travel,Business,550,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +33506,76681,Female,Loyal Customer,68,Personal Travel,Eco,516,3,5,3,2,3,4,4,4,4,3,4,5,4,3,0,10.0,neutral or dissatisfied +33507,63404,Male,Loyal Customer,31,Personal Travel,Eco,447,4,5,4,1,1,4,1,1,2,5,5,4,1,1,6,0.0,neutral or dissatisfied +33508,106460,Female,disloyal Customer,15,Business travel,Eco Plus,1670,2,2,2,4,2,2,1,2,4,2,4,2,3,2,15,8.0,neutral or dissatisfied +33509,1329,Female,Loyal Customer,34,Business travel,Business,2386,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +33510,30895,Male,Loyal Customer,15,Personal Travel,Eco,841,2,3,2,3,3,2,3,3,4,3,3,1,2,3,0,0.0,neutral or dissatisfied +33511,102133,Female,Loyal Customer,52,Business travel,Business,3089,2,2,2,2,4,5,5,4,4,4,4,3,4,4,20,22.0,satisfied +33512,99490,Female,Loyal Customer,50,Personal Travel,Eco,307,2,4,2,4,2,4,4,3,3,2,1,5,3,4,1,0.0,neutral or dissatisfied +33513,6115,Female,Loyal Customer,30,Business travel,Business,409,5,5,5,5,2,2,2,2,3,5,5,3,4,2,0,14.0,satisfied +33514,41780,Male,Loyal Customer,31,Business travel,Business,1539,2,2,2,2,2,2,2,2,4,2,2,4,2,2,26,22.0,neutral or dissatisfied +33515,42671,Female,Loyal Customer,34,Business travel,Business,2418,4,4,4,4,5,5,3,4,4,4,4,3,4,4,0,0.0,satisfied +33516,31435,Female,Loyal Customer,29,Personal Travel,Eco,1607,3,1,3,3,5,3,5,5,3,5,3,4,3,5,0,0.0,neutral or dissatisfied +33517,90174,Female,Loyal Customer,23,Personal Travel,Eco,1084,1,4,1,2,3,1,3,3,5,5,4,5,4,3,32,15.0,neutral or dissatisfied +33518,16907,Female,Loyal Customer,18,Personal Travel,Eco,746,4,4,4,1,4,4,1,4,2,1,3,3,3,4,0,7.0,neutral or dissatisfied +33519,82437,Female,disloyal Customer,24,Business travel,Eco,502,5,0,5,4,3,0,3,3,5,5,5,4,4,3,0,0.0,satisfied +33520,81839,Female,Loyal Customer,51,Personal Travel,Eco,1310,1,4,1,2,4,3,5,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +33521,79956,Male,disloyal Customer,41,Business travel,Eco,676,2,2,2,2,1,2,1,1,2,4,3,4,4,1,0,4.0,neutral or dissatisfied +33522,103698,Male,Loyal Customer,67,Business travel,Business,1559,2,2,2,2,5,3,4,5,5,5,5,4,5,2,0,0.0,satisfied +33523,7857,Female,Loyal Customer,50,Personal Travel,Eco,1005,1,5,1,3,2,4,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +33524,105502,Female,Loyal Customer,60,Business travel,Business,2954,5,5,5,5,5,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +33525,61986,Female,Loyal Customer,61,Personal Travel,Business,2475,4,0,4,3,4,4,1,5,3,5,4,1,5,1,156,152.0,neutral or dissatisfied +33526,32168,Female,Loyal Customer,68,Business travel,Business,101,2,2,2,2,2,3,1,4,4,5,5,3,4,4,0,3.0,satisfied +33527,50071,Male,Loyal Customer,39,Business travel,Eco,373,5,5,5,5,5,5,5,5,3,4,1,4,2,5,2,4.0,satisfied +33528,59646,Male,disloyal Customer,38,Business travel,Eco,565,1,0,1,2,2,1,2,2,3,1,4,1,2,2,0,0.0,neutral or dissatisfied +33529,99725,Male,disloyal Customer,24,Business travel,Eco,255,0,4,0,4,2,0,2,2,5,5,5,5,4,2,6,8.0,satisfied +33530,16413,Female,Loyal Customer,24,Business travel,Business,2281,2,2,2,2,5,5,5,4,4,5,5,5,5,5,160,157.0,satisfied +33531,94654,Female,Loyal Customer,49,Business travel,Business,3954,1,4,1,1,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +33532,1021,Female,Loyal Customer,65,Business travel,Business,158,3,3,3,3,2,2,4,5,5,5,4,4,5,4,0,0.0,satisfied +33533,81126,Male,Loyal Customer,27,Personal Travel,Eco,991,2,3,2,3,5,2,5,5,2,4,3,4,2,5,0,0.0,neutral or dissatisfied +33534,116765,Male,Loyal Customer,15,Personal Travel,Eco Plus,404,2,5,2,1,1,2,1,1,4,3,5,5,4,1,12,6.0,neutral or dissatisfied +33535,7916,Female,Loyal Customer,41,Business travel,Eco,620,1,2,2,2,1,1,1,1,3,5,2,2,2,1,0,25.0,neutral or dissatisfied +33536,35686,Male,Loyal Customer,44,Business travel,Business,2465,5,5,5,5,4,3,3,5,5,5,5,4,5,5,0,0.0,satisfied +33537,28103,Male,Loyal Customer,11,Business travel,Business,3130,4,4,4,4,4,4,4,4,3,5,4,4,3,4,0,0.0,neutral or dissatisfied +33538,108981,Female,Loyal Customer,52,Personal Travel,Business,488,5,4,5,3,3,2,3,1,1,5,1,3,1,2,0,0.0,satisfied +33539,71731,Female,disloyal Customer,44,Business travel,Business,819,4,4,4,4,4,4,3,4,4,3,4,5,5,4,15,5.0,satisfied +33540,9975,Female,Loyal Customer,62,Personal Travel,Eco,534,2,5,2,3,2,4,5,3,3,2,2,4,3,5,0,11.0,neutral or dissatisfied +33541,54485,Female,Loyal Customer,25,Business travel,Business,925,4,4,4,4,4,5,4,4,3,2,3,3,5,4,3,0.0,satisfied +33542,67378,Male,Loyal Customer,49,Business travel,Business,721,4,2,4,4,3,5,4,5,5,4,5,5,5,5,9,0.0,satisfied +33543,7813,Female,Loyal Customer,26,Business travel,Business,650,5,5,5,5,5,5,5,5,3,4,4,4,4,5,0,2.0,satisfied +33544,78515,Female,Loyal Customer,67,Personal Travel,Eco,666,1,4,1,5,2,4,2,5,5,1,5,5,5,2,9,94.0,neutral or dissatisfied +33545,119267,Male,Loyal Customer,25,Business travel,Business,214,1,1,1,1,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +33546,14496,Female,disloyal Customer,35,Business travel,Eco,328,4,3,4,2,2,4,2,2,5,4,5,1,4,2,0,0.0,neutral or dissatisfied +33547,74136,Male,Loyal Customer,30,Business travel,Business,2403,4,4,4,4,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +33548,20232,Female,Loyal Customer,37,Business travel,Business,228,1,1,1,1,2,1,1,1,4,4,4,1,4,1,394,362.0,neutral or dissatisfied +33549,65246,Female,Loyal Customer,55,Business travel,Eco Plus,190,3,3,3,3,5,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +33550,82349,Male,Loyal Customer,55,Business travel,Business,2587,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +33551,99502,Female,Loyal Customer,42,Personal Travel,Eco,283,1,4,1,3,2,5,5,5,5,1,5,4,5,4,7,0.0,neutral or dissatisfied +33552,119094,Female,disloyal Customer,50,Business travel,Eco,1107,3,3,3,4,3,3,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +33553,65775,Female,Loyal Customer,15,Business travel,Business,1389,2,2,2,2,3,3,3,3,3,2,4,3,5,3,0,0.0,satisfied +33554,91920,Male,Loyal Customer,60,Business travel,Business,2586,3,1,3,3,4,4,4,5,5,5,5,3,5,3,0,2.0,satisfied +33555,24689,Male,Loyal Customer,32,Personal Travel,Eco,761,3,5,4,5,4,4,4,4,2,5,5,1,3,4,0,12.0,neutral or dissatisfied +33556,61455,Female,Loyal Customer,53,Business travel,Eco,2419,3,4,4,4,1,2,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +33557,104423,Male,Loyal Customer,33,Business travel,Business,1628,2,3,3,3,2,2,2,2,1,2,4,3,4,2,3,19.0,neutral or dissatisfied +33558,6622,Female,Loyal Customer,54,Business travel,Business,719,3,3,3,3,2,5,5,5,5,5,5,4,5,5,60,71.0,satisfied +33559,118407,Female,disloyal Customer,36,Business travel,Business,370,1,1,1,4,4,1,4,4,5,5,4,5,4,4,12,16.0,neutral or dissatisfied +33560,99164,Female,Loyal Customer,22,Business travel,Eco,1076,3,4,4,4,3,2,1,3,4,3,3,4,3,3,15,13.0,neutral or dissatisfied +33561,31191,Female,Loyal Customer,50,Business travel,Business,628,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +33562,46074,Female,disloyal Customer,23,Business travel,Eco,495,4,0,4,4,5,4,5,5,5,1,4,2,4,5,3,5.0,satisfied +33563,89776,Female,Loyal Customer,59,Personal Travel,Eco,944,4,2,3,3,4,4,3,2,2,3,4,2,2,1,29,2.0,satisfied +33564,24869,Female,Loyal Customer,37,Business travel,Business,356,2,3,2,2,1,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +33565,61631,Male,Loyal Customer,39,Business travel,Business,1635,4,4,4,4,3,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +33566,106047,Female,disloyal Customer,44,Business travel,Eco,452,2,5,2,4,1,2,1,1,5,1,1,5,3,1,0,0.0,neutral or dissatisfied +33567,22506,Female,disloyal Customer,25,Business travel,Eco Plus,238,2,0,2,3,4,2,4,4,1,4,3,4,3,4,0,15.0,neutral or dissatisfied +33568,6068,Male,Loyal Customer,50,Personal Travel,Eco,1041,3,4,3,1,4,3,3,4,4,5,5,3,4,4,30,25.0,neutral or dissatisfied +33569,81269,Male,Loyal Customer,30,Business travel,Business,3646,2,4,5,4,2,2,2,2,3,1,3,1,4,2,19,64.0,neutral or dissatisfied +33570,65170,Male,Loyal Customer,15,Personal Travel,Eco,354,2,5,2,3,5,2,5,5,3,4,4,5,5,5,12,7.0,neutral or dissatisfied +33571,23035,Female,Loyal Customer,32,Personal Travel,Eco,1020,2,3,2,4,4,2,4,4,3,2,4,1,4,4,27,4.0,neutral or dissatisfied +33572,51455,Male,Loyal Customer,14,Personal Travel,Eco Plus,86,2,2,2,4,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +33573,27883,Female,Loyal Customer,70,Personal Travel,Eco Plus,1448,4,3,4,2,1,5,4,4,4,4,4,5,4,4,0,5.0,neutral or dissatisfied +33574,30515,Female,Loyal Customer,43,Business travel,Business,373,3,3,5,3,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +33575,121725,Male,disloyal Customer,28,Business travel,Business,1475,3,3,3,4,5,3,3,5,5,3,4,3,4,5,0,11.0,neutral or dissatisfied +33576,60545,Female,Loyal Customer,43,Personal Travel,Eco,794,1,5,0,4,2,4,5,1,1,0,1,4,1,3,1,0.0,neutral or dissatisfied +33577,35312,Male,disloyal Customer,22,Business travel,Eco,944,4,4,4,1,5,4,5,5,3,4,5,5,3,5,0,16.0,neutral or dissatisfied +33578,78978,Female,disloyal Customer,34,Business travel,Business,306,2,2,2,2,4,2,3,4,5,2,5,4,5,4,0,4.0,neutral or dissatisfied +33579,63702,Female,Loyal Customer,47,Personal Travel,Eco,853,2,1,2,3,4,2,2,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +33580,6950,Male,disloyal Customer,19,Business travel,Eco,501,4,3,4,4,5,4,5,5,4,3,3,1,4,5,30,43.0,neutral or dissatisfied +33581,93929,Female,disloyal Customer,29,Business travel,Eco,507,1,2,1,3,1,1,1,1,4,4,4,1,4,1,66,60.0,neutral or dissatisfied +33582,1015,Male,Loyal Customer,46,Business travel,Business,113,5,5,5,5,5,1,5,4,4,4,5,1,4,1,25,21.0,satisfied +33583,21255,Male,Loyal Customer,42,Personal Travel,Eco Plus,192,2,4,0,4,5,0,3,5,3,3,4,5,4,5,54,67.0,neutral or dissatisfied +33584,120687,Female,Loyal Customer,67,Personal Travel,Eco,280,1,4,1,3,3,5,5,3,3,1,3,4,3,4,10,7.0,neutral or dissatisfied +33585,45795,Male,Loyal Customer,57,Business travel,Eco,391,4,1,1,1,5,4,5,5,4,4,2,1,1,5,0,0.0,satisfied +33586,53652,Female,Loyal Customer,22,Business travel,Eco Plus,1874,5,3,3,3,5,5,5,5,2,2,4,2,2,5,0,0.0,satisfied +33587,69475,Male,Loyal Customer,20,Personal Travel,Eco,944,3,1,3,4,1,3,3,1,2,1,3,2,3,1,13,31.0,neutral or dissatisfied +33588,40936,Male,Loyal Customer,41,Business travel,Eco Plus,599,5,1,4,1,5,5,5,5,3,2,1,5,2,5,34,35.0,satisfied +33589,79901,Male,Loyal Customer,42,Business travel,Business,1096,5,5,5,5,4,4,4,5,5,5,5,4,5,4,170,157.0,satisfied +33590,99629,Male,Loyal Customer,62,Business travel,Business,1525,2,4,4,4,2,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +33591,32269,Female,Loyal Customer,40,Business travel,Eco,163,4,4,4,4,4,4,4,4,2,2,5,4,1,4,0,6.0,satisfied +33592,113542,Female,Loyal Customer,49,Business travel,Eco,407,1,3,3,3,2,2,2,1,1,1,1,4,1,2,61,57.0,neutral or dissatisfied +33593,64590,Female,Loyal Customer,40,Business travel,Business,190,2,2,2,2,3,5,4,5,5,5,4,5,5,3,0,0.0,satisfied +33594,18930,Female,Loyal Customer,27,Personal Travel,Eco,503,2,5,3,5,4,3,4,4,5,3,4,3,5,4,0,18.0,neutral or dissatisfied +33595,92139,Male,Loyal Customer,37,Personal Travel,Eco,1589,1,3,1,3,3,1,3,3,3,2,2,3,3,3,0,0.0,neutral or dissatisfied +33596,120129,Female,Loyal Customer,60,Business travel,Eco Plus,1576,1,1,4,1,1,2,3,1,1,1,1,4,1,4,0,17.0,neutral or dissatisfied +33597,22054,Male,disloyal Customer,32,Business travel,Eco,304,3,0,3,2,1,3,1,1,3,1,1,1,3,1,0,0.0,neutral or dissatisfied +33598,59172,Female,Loyal Customer,65,Personal Travel,Eco Plus,1846,2,3,1,4,1,4,4,3,2,4,4,4,3,4,179,149.0,neutral or dissatisfied +33599,12705,Female,Loyal Customer,48,Business travel,Eco,803,5,5,5,5,4,1,5,5,5,5,5,2,5,2,0,0.0,satisfied +33600,39414,Male,Loyal Customer,37,Business travel,Eco Plus,521,4,5,5,5,4,4,4,4,5,3,1,5,1,4,0,0.0,satisfied +33601,4235,Male,Loyal Customer,25,Business travel,Business,1020,2,2,2,2,2,2,2,2,4,5,2,2,3,2,26,26.0,neutral or dissatisfied +33602,50613,Male,Loyal Customer,53,Personal Travel,Eco,89,0,5,0,3,5,0,5,5,5,2,3,5,4,5,0,6.0,satisfied +33603,30885,Female,Loyal Customer,13,Personal Travel,Eco Plus,1506,3,2,3,4,1,3,1,1,4,1,4,3,3,1,0,5.0,neutral or dissatisfied +33604,2289,Male,disloyal Customer,36,Business travel,Eco,672,3,3,3,4,3,3,2,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +33605,115716,Female,Loyal Customer,41,Business travel,Business,447,2,1,1,1,5,3,4,2,2,2,2,2,2,2,22,10.0,neutral or dissatisfied +33606,63309,Male,Loyal Customer,33,Business travel,Business,2594,0,0,0,5,5,5,5,5,4,3,5,4,4,5,18,1.0,satisfied +33607,74969,Male,Loyal Customer,51,Personal Travel,Eco,2475,3,0,3,3,2,3,2,2,4,1,5,1,1,2,0,0.0,neutral or dissatisfied +33608,53162,Male,Loyal Customer,32,Personal Travel,Business,612,1,5,1,2,5,1,2,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +33609,4855,Male,Loyal Customer,42,Business travel,Business,1537,3,3,3,3,1,2,3,5,5,5,5,3,5,3,1,5.0,satisfied +33610,12978,Female,Loyal Customer,64,Personal Travel,Business,374,3,0,3,3,5,5,4,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +33611,36443,Female,Loyal Customer,69,Personal Travel,Eco,369,3,4,3,3,1,3,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +33612,121712,Male,Loyal Customer,54,Personal Travel,Eco,683,3,5,3,3,2,3,4,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +33613,42559,Male,Loyal Customer,43,Business travel,Eco,626,4,4,4,4,5,4,5,5,2,5,1,3,3,5,13,9.0,satisfied +33614,59356,Male,Loyal Customer,56,Business travel,Business,2556,1,1,1,1,5,4,5,5,5,5,5,3,5,3,3,3.0,satisfied +33615,66898,Male,Loyal Customer,49,Business travel,Business,2795,4,4,4,4,5,5,5,5,5,5,5,5,5,3,58,95.0,satisfied +33616,62619,Male,Loyal Customer,27,Personal Travel,Eco,1846,2,5,1,4,2,1,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +33617,55262,Female,disloyal Customer,47,Business travel,Eco,1171,2,2,2,3,3,2,3,3,1,4,3,1,4,3,25,8.0,neutral or dissatisfied +33618,98778,Male,Loyal Customer,59,Business travel,Business,2442,4,4,4,4,3,5,4,3,3,3,3,3,3,5,42,52.0,satisfied +33619,109007,Female,Loyal Customer,53,Business travel,Business,2122,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +33620,52248,Male,Loyal Customer,60,Business travel,Business,3747,4,4,4,4,2,1,2,4,4,3,4,5,4,3,0,0.0,satisfied +33621,9883,Male,disloyal Customer,37,Business travel,Business,508,2,2,2,5,4,2,4,4,3,3,5,3,4,4,0,0.0,satisfied +33622,29890,Female,Loyal Customer,29,Business travel,Business,539,3,3,3,3,3,4,3,3,2,4,4,4,5,3,0,0.0,satisfied +33623,125231,Female,Loyal Customer,58,Business travel,Business,1149,2,2,2,2,3,4,5,4,4,4,4,5,4,5,6,29.0,satisfied +33624,73740,Female,Loyal Customer,10,Personal Travel,Eco,204,2,4,2,4,1,2,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +33625,86751,Female,disloyal Customer,28,Business travel,Business,821,4,3,3,3,1,3,1,1,3,2,5,4,5,1,32,21.0,neutral or dissatisfied +33626,65205,Female,disloyal Customer,27,Business travel,Business,247,3,4,4,5,3,4,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +33627,26002,Male,Loyal Customer,60,Business travel,Business,1578,3,2,2,2,5,3,3,3,3,3,3,4,3,2,29,22.0,neutral or dissatisfied +33628,114681,Female,Loyal Customer,42,Business travel,Business,325,2,2,2,2,3,4,4,5,5,5,5,3,5,4,25,27.0,satisfied +33629,28754,Female,Loyal Customer,28,Business travel,Eco,1024,5,3,3,3,5,5,5,5,2,4,2,3,4,5,0,0.0,satisfied +33630,12884,Male,Loyal Customer,36,Business travel,Eco,674,5,4,4,4,5,5,5,5,1,5,4,1,3,5,64,57.0,satisfied +33631,87915,Female,Loyal Customer,17,Business travel,Business,581,3,3,3,3,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +33632,8403,Female,Loyal Customer,22,Business travel,Business,862,2,2,2,2,5,4,5,5,5,4,5,4,4,5,91,89.0,satisfied +33633,128425,Male,Loyal Customer,36,Business travel,Business,370,2,5,5,5,4,2,2,2,2,2,2,3,2,3,6,12.0,neutral or dissatisfied +33634,15775,Female,disloyal Customer,26,Business travel,Eco,198,3,3,3,3,4,3,4,4,4,3,3,3,4,4,0,0.0,neutral or dissatisfied +33635,111998,Female,Loyal Customer,46,Business travel,Business,533,2,5,2,2,5,5,4,4,4,4,4,5,4,4,63,57.0,satisfied +33636,99102,Male,Loyal Customer,45,Business travel,Eco,419,2,1,1,1,2,2,2,2,4,2,4,4,3,2,46,37.0,neutral or dissatisfied +33637,36073,Female,disloyal Customer,25,Business travel,Eco,399,2,0,1,5,4,1,4,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +33638,54011,Male,Loyal Customer,11,Personal Travel,Business,1091,5,3,5,3,4,5,4,4,2,5,2,2,4,4,0,0.0,satisfied +33639,16322,Male,Loyal Customer,31,Business travel,Business,2935,3,5,5,5,3,2,3,3,4,4,3,2,3,3,18,37.0,neutral or dissatisfied +33640,86604,Male,Loyal Customer,29,Business travel,Business,746,2,2,5,2,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +33641,19311,Male,Loyal Customer,49,Personal Travel,Business,694,1,4,1,1,5,5,5,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +33642,45734,Female,Loyal Customer,51,Personal Travel,Eco,1463,3,5,4,3,4,3,4,3,3,4,3,5,3,4,10,0.0,neutral or dissatisfied +33643,25377,Female,Loyal Customer,40,Business travel,Business,591,1,1,1,1,3,3,4,1,1,2,1,1,1,4,25,23.0,neutral or dissatisfied +33644,44359,Female,Loyal Customer,18,Business travel,Eco,596,5,4,2,2,5,5,3,5,1,4,4,5,5,5,0,0.0,satisfied +33645,2720,Male,Loyal Customer,38,Personal Travel,Eco Plus,562,4,5,4,5,4,4,4,4,5,2,4,5,5,4,27,29.0,neutral or dissatisfied +33646,41973,Male,Loyal Customer,28,Personal Travel,Eco,575,1,4,1,4,4,1,1,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +33647,46885,Female,Loyal Customer,30,Business travel,Business,850,3,2,2,2,3,3,3,3,1,5,3,2,4,3,36,74.0,neutral or dissatisfied +33648,124024,Male,Loyal Customer,16,Personal Travel,Eco,184,3,4,3,4,2,3,2,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +33649,14723,Male,Loyal Customer,8,Personal Travel,Eco,419,3,2,3,4,5,3,5,5,3,3,4,1,3,5,0,0.0,neutral or dissatisfied +33650,52977,Male,Loyal Customer,33,Business travel,Business,2317,4,5,4,4,3,3,3,3,4,5,4,3,5,3,0,0.0,satisfied +33651,3300,Male,Loyal Customer,41,Personal Travel,Eco,483,2,0,2,1,3,2,3,3,4,5,5,5,4,3,16,13.0,neutral or dissatisfied +33652,107372,Male,Loyal Customer,13,Personal Travel,Eco Plus,584,3,5,3,3,4,3,5,4,3,2,4,3,5,4,11,3.0,neutral or dissatisfied +33653,35049,Male,Loyal Customer,31,Business travel,Business,1097,2,2,2,2,4,4,4,4,5,5,5,4,4,4,4,15.0,satisfied +33654,120434,Male,Loyal Customer,60,Business travel,Eco,366,3,5,4,5,3,3,3,3,3,5,2,1,3,3,0,0.0,satisfied +33655,49217,Female,disloyal Customer,21,Business travel,Eco,89,3,0,3,3,3,3,3,3,1,2,4,2,2,3,0,0.0,neutral or dissatisfied +33656,68852,Male,disloyal Customer,22,Business travel,Business,936,5,0,5,2,1,5,1,1,3,2,4,5,4,1,0,0.0,satisfied +33657,121403,Male,Loyal Customer,51,Business travel,Business,2338,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +33658,83910,Female,disloyal Customer,49,Business travel,Business,752,5,5,5,1,4,5,4,4,3,2,4,4,4,4,4,0.0,satisfied +33659,4824,Male,disloyal Customer,38,Business travel,Business,408,4,4,4,3,1,4,2,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +33660,103179,Female,Loyal Customer,68,Personal Travel,Eco,272,2,2,2,3,2,4,3,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +33661,81560,Male,disloyal Customer,30,Business travel,Eco,936,2,2,2,3,3,2,3,3,1,4,4,4,3,3,7,13.0,neutral or dissatisfied +33662,70543,Female,disloyal Customer,48,Business travel,Business,1258,5,5,5,4,5,5,5,5,4,5,4,5,5,5,24,26.0,satisfied +33663,101250,Male,Loyal Customer,29,Personal Travel,Eco Plus,1587,2,4,3,2,4,3,4,4,4,3,4,5,4,4,25,12.0,neutral or dissatisfied +33664,123334,Male,Loyal Customer,66,Personal Travel,Eco Plus,600,1,4,1,4,1,1,1,3,5,3,4,1,4,1,147,140.0,neutral or dissatisfied +33665,100639,Female,disloyal Customer,25,Business travel,Eco,349,4,0,4,3,4,4,4,4,4,5,3,3,4,4,0,0.0,neutral or dissatisfied +33666,106596,Male,Loyal Customer,42,Business travel,Business,986,2,2,2,2,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +33667,69709,Male,disloyal Customer,25,Business travel,Eco,1372,4,4,4,3,4,4,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +33668,43604,Female,Loyal Customer,57,Business travel,Eco,228,4,4,4,4,1,5,3,4,4,4,4,2,4,5,2,0.0,satisfied +33669,17204,Male,Loyal Customer,23,Business travel,Business,694,2,2,2,2,5,5,5,5,5,3,2,4,2,5,0,0.0,satisfied +33670,51220,Female,Loyal Customer,61,Business travel,Eco Plus,153,5,2,2,2,1,5,4,5,5,5,5,5,5,1,0,0.0,satisfied +33671,127155,Male,Loyal Customer,65,Personal Travel,Eco,651,2,2,2,3,3,2,5,3,3,4,2,3,2,3,0,0.0,neutral or dissatisfied +33672,86637,Male,Loyal Customer,24,Business travel,Business,3010,2,4,4,4,2,2,2,2,1,3,2,2,2,2,29,10.0,neutral or dissatisfied +33673,40553,Female,Loyal Customer,36,Business travel,Business,517,2,2,5,2,4,3,1,5,5,5,5,3,5,4,11,2.0,satisfied +33674,55112,Male,Loyal Customer,42,Personal Travel,Eco,1635,3,5,4,1,2,4,2,2,4,2,3,5,4,2,0,0.0,neutral or dissatisfied +33675,124661,Male,disloyal Customer,39,Business travel,Business,399,1,1,1,2,1,1,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +33676,98394,Female,disloyal Customer,35,Business travel,Business,675,2,2,2,2,2,2,2,2,4,3,4,4,5,2,0,1.0,neutral or dissatisfied +33677,72776,Female,disloyal Customer,27,Business travel,Business,1045,5,5,5,1,3,5,3,3,4,3,5,4,4,3,0,0.0,satisfied +33678,126007,Female,Loyal Customer,60,Business travel,Business,507,5,5,5,5,4,5,4,4,4,4,4,3,4,4,3,2.0,satisfied +33679,4132,Male,disloyal Customer,36,Business travel,Eco,431,3,2,3,3,3,3,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +33680,76319,Female,Loyal Customer,7,Personal Travel,Eco,2182,4,5,4,1,1,4,1,1,3,1,3,2,5,1,14,36.0,satisfied +33681,103266,Male,Loyal Customer,60,Business travel,Business,3255,5,5,5,5,5,4,4,5,5,5,5,4,5,4,58,41.0,satisfied +33682,83197,Male,Loyal Customer,46,Business travel,Eco,1123,1,4,4,4,1,1,1,1,1,3,4,2,4,1,30,14.0,neutral or dissatisfied +33683,79010,Male,Loyal Customer,47,Business travel,Business,2750,3,3,3,3,5,4,4,5,5,5,5,5,5,5,19,26.0,satisfied +33684,18064,Female,disloyal Customer,23,Business travel,Eco,605,1,1,1,3,2,1,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +33685,97473,Female,Loyal Customer,51,Business travel,Business,670,4,4,4,4,5,5,4,4,4,5,4,4,4,4,2,7.0,satisfied +33686,117438,Female,Loyal Customer,44,Business travel,Business,2995,4,4,4,4,2,4,4,5,5,5,5,5,5,4,35,44.0,satisfied +33687,105852,Female,Loyal Customer,41,Business travel,Business,2757,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,3.0,satisfied +33688,7364,Female,disloyal Customer,19,Business travel,Business,783,4,4,4,2,3,4,3,3,3,4,5,3,4,3,14,0.0,satisfied +33689,43362,Female,Loyal Customer,47,Personal Travel,Eco,358,1,4,1,3,4,5,4,5,5,1,2,3,5,3,0,0.0,neutral or dissatisfied +33690,88129,Male,Loyal Customer,43,Business travel,Business,270,3,3,3,3,2,4,5,4,4,4,4,3,4,4,35,43.0,satisfied +33691,36060,Male,disloyal Customer,32,Business travel,Eco,399,3,0,3,2,1,3,1,1,1,4,1,5,1,1,0,2.0,neutral or dissatisfied +33692,127226,Male,disloyal Customer,29,Business travel,Business,1460,3,3,3,3,1,3,1,1,4,4,5,4,5,1,7,25.0,neutral or dissatisfied +33693,114362,Female,Loyal Customer,12,Business travel,Business,3078,4,4,2,4,4,4,4,4,5,3,4,5,5,4,0,0.0,satisfied +33694,57009,Male,Loyal Customer,31,Personal Travel,Eco,2454,1,4,1,2,1,2,3,4,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +33695,33945,Male,Loyal Customer,20,Business travel,Business,3081,2,2,2,2,5,5,5,5,2,4,5,2,2,5,0,0.0,satisfied +33696,65270,Female,Loyal Customer,47,Personal Travel,Eco Plus,190,0,5,0,3,3,4,4,5,5,0,5,5,5,5,0,0.0,satisfied +33697,74457,Female,disloyal Customer,22,Business travel,Business,1205,4,4,4,4,5,4,5,5,3,2,4,3,5,5,0,0.0,satisfied +33698,77056,Female,Loyal Customer,45,Business travel,Business,2633,1,1,1,1,5,5,5,4,5,4,4,5,5,5,142,124.0,satisfied +33699,934,Female,disloyal Customer,42,Business travel,Business,282,2,2,2,4,3,2,3,3,3,3,5,4,4,3,12,0.0,neutral or dissatisfied +33700,129288,Female,disloyal Customer,21,Business travel,Eco,550,4,4,4,4,3,4,3,3,1,3,3,1,3,3,0,6.0,neutral or dissatisfied +33701,11663,Male,disloyal Customer,54,Personal Travel,Eco Plus,925,3,4,3,3,3,3,3,3,5,5,5,5,5,3,54,51.0,neutral or dissatisfied +33702,37219,Male,Loyal Customer,12,Business travel,Business,1047,2,2,2,2,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +33703,46684,Female,Loyal Customer,26,Personal Travel,Eco,125,3,2,0,4,2,0,2,2,4,1,3,4,3,2,55,50.0,neutral or dissatisfied +33704,118475,Male,Loyal Customer,41,Business travel,Business,370,2,2,2,2,5,4,5,4,4,4,4,3,4,5,61,49.0,satisfied +33705,4067,Female,Loyal Customer,50,Personal Travel,Eco,419,4,5,4,2,4,4,1,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +33706,114866,Male,disloyal Customer,39,Business travel,Business,417,2,2,2,3,1,2,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +33707,19577,Male,Loyal Customer,80,Business travel,Business,3631,4,5,5,5,3,3,3,3,3,3,4,4,3,1,25,11.0,neutral or dissatisfied +33708,91777,Female,Loyal Customer,64,Personal Travel,Eco,590,2,3,3,3,4,2,3,4,4,3,4,1,4,4,10,7.0,neutral or dissatisfied +33709,11016,Female,Loyal Customer,59,Business travel,Business,2549,1,1,1,1,2,3,1,4,4,5,5,4,4,1,0,0.0,satisfied +33710,10360,Male,Loyal Customer,60,Business travel,Business,3287,0,0,0,3,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +33711,11816,Male,Loyal Customer,37,Business travel,Business,3719,4,4,4,4,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +33712,49034,Male,Loyal Customer,63,Business travel,Eco,86,5,2,2,2,5,5,5,5,4,5,4,5,2,5,0,0.0,satisfied +33713,16280,Male,Loyal Customer,35,Personal Travel,Eco,748,3,4,3,3,1,3,1,1,5,4,5,5,4,1,99,93.0,neutral or dissatisfied +33714,74411,Male,disloyal Customer,25,Business travel,Eco,1171,4,4,4,4,4,4,4,4,3,5,5,5,4,4,0,9.0,satisfied +33715,45541,Female,Loyal Customer,42,Business travel,Eco,508,2,2,2,2,1,2,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +33716,93968,Male,disloyal Customer,27,Business travel,Eco,1218,3,3,3,4,1,3,1,1,1,3,4,4,4,1,56,34.0,neutral or dissatisfied +33717,32754,Male,disloyal Customer,50,Business travel,Eco,102,1,5,1,5,5,1,5,5,4,4,2,5,1,5,4,3.0,neutral or dissatisfied +33718,65089,Male,Loyal Customer,18,Personal Travel,Eco,247,4,4,0,5,1,0,1,1,4,3,5,3,5,1,69,62.0,neutral or dissatisfied +33719,27362,Female,disloyal Customer,42,Business travel,Eco,954,5,5,5,2,2,5,2,2,2,3,2,3,1,2,4,0.0,satisfied +33720,118699,Male,Loyal Customer,61,Personal Travel,Eco,646,2,5,3,4,3,3,3,3,1,4,1,3,3,3,0,0.0,neutral or dissatisfied +33721,67754,Female,Loyal Customer,46,Business travel,Business,1438,1,4,4,4,1,3,3,1,1,1,1,3,1,3,42,38.0,neutral or dissatisfied +33722,66255,Male,Loyal Customer,36,Personal Travel,Eco,460,3,3,3,3,3,3,2,3,1,2,3,1,3,3,0,13.0,neutral or dissatisfied +33723,10744,Female,disloyal Customer,58,Business travel,Eco,312,1,3,1,4,1,1,1,1,4,5,3,1,3,1,0,0.0,neutral or dissatisfied +33724,47960,Female,Loyal Customer,37,Personal Travel,Eco,834,3,3,4,1,2,4,2,2,2,1,4,1,5,2,0,0.0,neutral or dissatisfied +33725,65964,Male,Loyal Customer,30,Business travel,Business,1372,2,1,1,1,2,2,2,2,2,3,4,4,3,2,22,0.0,neutral or dissatisfied +33726,118187,Female,Loyal Customer,54,Business travel,Business,1440,2,5,5,5,4,2,3,2,2,2,2,1,2,3,1,8.0,neutral or dissatisfied +33727,64383,Male,Loyal Customer,47,Personal Travel,Eco,1192,1,2,1,3,4,1,4,4,4,1,2,4,4,4,0,0.0,neutral or dissatisfied +33728,129657,Male,Loyal Customer,48,Business travel,Eco,337,4,2,4,2,3,4,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +33729,23707,Female,Loyal Customer,20,Personal Travel,Eco,251,2,3,0,2,2,0,2,2,1,4,1,3,3,2,0,0.0,neutral or dissatisfied +33730,38765,Male,Loyal Customer,37,Business travel,Business,2924,1,1,1,1,4,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +33731,45324,Female,disloyal Customer,43,Business travel,Eco,188,2,1,2,3,2,5,5,2,1,4,4,5,1,5,196,187.0,neutral or dissatisfied +33732,33614,Male,disloyal Customer,36,Business travel,Eco,399,2,2,2,2,2,2,2,2,4,2,3,2,2,2,0,10.0,neutral or dissatisfied +33733,126350,Female,Loyal Customer,29,Personal Travel,Eco,600,2,5,2,4,2,2,2,2,4,5,3,1,1,2,12,15.0,neutral or dissatisfied +33734,91020,Female,Loyal Customer,18,Personal Travel,Eco,404,4,4,4,3,4,4,5,4,5,1,5,1,1,4,0,0.0,satisfied +33735,127495,Male,Loyal Customer,59,Personal Travel,Eco,2075,3,1,3,3,2,3,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +33736,79236,Female,Loyal Customer,24,Personal Travel,Eco,1521,3,3,3,1,5,3,4,5,5,3,5,3,2,5,0,0.0,neutral or dissatisfied +33737,37140,Female,Loyal Customer,37,Business travel,Business,3576,2,1,3,3,2,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +33738,110744,Male,Loyal Customer,44,Business travel,Business,1166,2,2,2,2,3,4,4,5,5,5,5,5,5,5,19,4.0,satisfied +33739,51779,Male,Loyal Customer,13,Personal Travel,Eco,261,3,2,3,3,4,3,5,4,1,4,3,3,4,4,0,0.0,neutral or dissatisfied +33740,24950,Female,Loyal Customer,23,Business travel,Business,1747,1,0,0,3,2,0,3,2,2,2,2,2,3,2,59,26.0,neutral or dissatisfied +33741,66219,Male,Loyal Customer,54,Business travel,Business,2740,3,3,3,3,3,1,2,3,3,3,3,3,3,4,4,15.0,neutral or dissatisfied +33742,41730,Female,Loyal Customer,49,Business travel,Eco,695,4,4,4,4,4,4,2,4,4,4,4,4,4,5,0,9.0,satisfied +33743,83812,Female,Loyal Customer,45,Business travel,Business,3449,4,2,4,4,5,4,5,5,5,5,5,3,5,4,9,9.0,satisfied +33744,112773,Female,disloyal Customer,40,Personal Travel,Eco,590,2,3,2,3,4,2,4,4,3,1,3,2,3,4,37,35.0,neutral or dissatisfied +33745,51888,Male,Loyal Customer,27,Business travel,Business,2281,1,1,1,1,4,4,4,4,3,2,3,1,4,4,0,0.0,satisfied +33746,33809,Female,Loyal Customer,25,Business travel,Eco,1521,3,2,2,2,3,3,1,3,4,5,4,4,4,3,13,0.0,neutral or dissatisfied +33747,31079,Male,Loyal Customer,52,Business travel,Eco Plus,862,5,3,3,3,5,5,5,5,2,1,4,2,1,5,29,25.0,satisfied +33748,111611,Female,disloyal Customer,36,Business travel,Business,1014,3,3,3,4,3,3,3,3,3,3,5,5,5,3,2,2.0,neutral or dissatisfied +33749,3178,Male,Loyal Customer,25,Business travel,Business,693,2,2,2,2,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +33750,29142,Female,Loyal Customer,35,Personal Travel,Eco,956,1,1,1,3,3,1,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +33751,104403,Female,Loyal Customer,54,Business travel,Business,1011,4,1,1,1,2,4,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +33752,125474,Male,Loyal Customer,36,Personal Travel,Eco,2860,3,4,3,4,5,3,5,5,4,5,3,1,4,5,0,0.0,neutral or dissatisfied +33753,46861,Female,Loyal Customer,34,Business travel,Business,1944,2,2,2,2,5,3,4,5,5,5,5,2,5,5,19,21.0,satisfied +33754,52774,Female,Loyal Customer,44,Business travel,Eco,1874,5,5,2,2,4,4,3,5,5,5,5,2,5,2,116,112.0,satisfied +33755,49615,Female,Loyal Customer,21,Business travel,Business,3043,1,1,1,1,5,3,4,4,1,4,5,4,2,4,450,470.0,satisfied +33756,99089,Male,disloyal Customer,23,Business travel,Eco,237,2,1,2,3,5,2,5,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +33757,82037,Male,Loyal Customer,66,Personal Travel,Eco,1535,4,5,4,4,4,4,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +33758,78290,Female,disloyal Customer,41,Business travel,Business,1598,2,2,2,2,4,2,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +33759,9967,Male,Loyal Customer,42,Personal Travel,Eco,508,3,4,3,3,3,3,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +33760,38067,Female,Loyal Customer,55,Business travel,Business,1121,2,4,3,3,3,3,3,2,2,2,2,3,2,4,0,2.0,neutral or dissatisfied +33761,73868,Male,disloyal Customer,25,Business travel,Eco,867,0,0,0,1,2,0,2,2,5,5,4,4,4,2,27,10.0,satisfied +33762,123762,Female,Loyal Customer,40,Business travel,Business,2158,5,5,5,5,2,4,4,5,5,5,5,3,5,3,70,79.0,satisfied +33763,32263,Female,Loyal Customer,41,Business travel,Business,102,5,5,5,5,3,1,1,5,5,5,4,5,5,5,0,0.0,satisfied +33764,37462,Female,Loyal Customer,35,Business travel,Eco,1028,4,1,1,1,4,4,4,4,4,2,5,4,4,4,19,30.0,satisfied +33765,38561,Male,Loyal Customer,32,Personal Travel,Eco,2465,1,4,1,1,4,1,4,4,4,3,4,2,3,4,0,10.0,neutral or dissatisfied +33766,21855,Female,Loyal Customer,40,Business travel,Business,3850,1,1,1,1,2,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +33767,107872,Female,Loyal Customer,62,Personal Travel,Eco,228,3,4,3,1,2,5,4,4,4,3,3,5,4,5,0,15.0,neutral or dissatisfied +33768,114601,Female,Loyal Customer,60,Business travel,Business,2422,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +33769,45225,Male,Loyal Customer,49,Business travel,Eco,911,2,3,3,3,2,2,2,2,4,3,3,2,4,2,33,25.0,neutral or dissatisfied +33770,82853,Male,Loyal Customer,53,Business travel,Business,594,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +33771,88979,Female,Loyal Customer,60,Personal Travel,Eco,1199,2,4,2,3,2,4,3,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +33772,98935,Female,Loyal Customer,36,Business travel,Business,2675,2,2,2,2,2,2,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +33773,65515,Female,Loyal Customer,45,Business travel,Business,1616,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +33774,122916,Female,Loyal Customer,59,Personal Travel,Business,650,4,3,4,4,1,3,3,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +33775,66484,Male,Loyal Customer,52,Business travel,Business,2382,2,2,2,2,2,4,4,5,5,5,5,4,5,5,16,7.0,satisfied +33776,4356,Female,Loyal Customer,55,Business travel,Eco,607,3,3,3,3,2,4,4,3,3,3,3,2,3,2,0,9.0,neutral or dissatisfied +33777,66727,Male,Loyal Customer,59,Personal Travel,Eco,802,3,2,3,4,5,3,5,5,3,1,3,3,4,5,4,0.0,neutral or dissatisfied +33778,53673,Male,disloyal Customer,23,Business travel,Eco,1208,3,3,3,2,1,3,1,1,5,5,1,4,2,1,0,4.0,neutral or dissatisfied +33779,50752,Male,Loyal Customer,41,Personal Travel,Eco,447,3,5,3,1,5,3,3,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +33780,75370,Male,Loyal Customer,39,Business travel,Business,2585,5,5,5,5,5,4,4,4,4,3,4,3,4,3,0,0.0,satisfied +33781,8853,Female,Loyal Customer,26,Business travel,Business,1732,3,4,3,3,4,4,4,4,5,5,5,4,5,4,0,2.0,satisfied +33782,74276,Male,Loyal Customer,49,Business travel,Business,2311,1,1,1,1,2,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +33783,112292,Male,Loyal Customer,45,Business travel,Business,1546,2,4,2,2,5,5,4,4,4,4,4,3,4,4,116,114.0,satisfied +33784,70252,Female,Loyal Customer,38,Business travel,Business,3633,3,3,4,3,2,4,1,3,3,3,3,3,3,1,0,0.0,satisfied +33785,47794,Female,Loyal Customer,47,Business travel,Eco,329,2,2,2,2,2,5,1,2,2,2,2,5,2,1,0,0.0,satisfied +33786,24532,Female,Loyal Customer,21,Business travel,Business,666,4,2,4,4,4,4,4,4,4,4,4,5,4,4,38,31.0,satisfied +33787,50205,Female,Loyal Customer,39,Business travel,Business,2720,4,4,4,4,2,4,3,2,2,2,4,1,2,4,10,4.0,neutral or dissatisfied +33788,45051,Male,Loyal Customer,42,Business travel,Business,3624,2,2,2,2,3,2,1,5,5,5,5,3,5,4,0,0.0,satisfied +33789,19370,Female,Loyal Customer,16,Business travel,Business,476,4,2,2,2,4,4,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +33790,36538,Male,Loyal Customer,38,Business travel,Eco,1197,2,1,1,1,2,2,2,2,3,1,2,4,4,2,1,0.0,satisfied +33791,10241,Female,Loyal Customer,35,Personal Travel,Business,458,3,5,3,2,2,4,4,1,1,3,1,4,1,3,84,69.0,neutral or dissatisfied +33792,122035,Male,disloyal Customer,22,Business travel,Eco,130,1,2,1,1,2,1,2,2,1,2,1,3,2,2,66,56.0,neutral or dissatisfied +33793,70764,Female,Loyal Customer,14,Personal Travel,Business,328,2,0,2,4,5,2,5,5,3,2,5,3,5,5,5,7.0,neutral or dissatisfied +33794,101136,Male,Loyal Customer,39,Business travel,Business,1090,1,1,1,1,5,4,4,4,4,4,4,5,4,5,23,14.0,satisfied +33795,78375,Female,Loyal Customer,30,Business travel,Business,2553,2,2,2,2,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +33796,94767,Female,Loyal Customer,39,Business travel,Business,323,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +33797,117738,Female,Loyal Customer,43,Business travel,Business,3417,3,3,3,3,1,4,4,3,3,3,3,2,3,1,11,6.0,neutral or dissatisfied +33798,37115,Female,disloyal Customer,42,Business travel,Eco,1046,3,3,3,2,3,3,3,3,3,3,1,3,5,3,33,28.0,satisfied +33799,10689,Female,Loyal Customer,43,Business travel,Eco,74,4,5,5,5,4,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +33800,85737,Male,Loyal Customer,59,Business travel,Business,526,1,1,1,1,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +33801,49136,Female,Loyal Customer,58,Business travel,Business,266,4,3,4,4,1,3,2,5,5,4,5,1,5,1,31,34.0,satisfied +33802,91201,Male,Loyal Customer,22,Personal Travel,Eco,404,1,5,3,3,5,3,5,5,3,5,5,5,5,5,16,4.0,neutral or dissatisfied +33803,75572,Male,disloyal Customer,26,Business travel,Business,337,4,0,4,1,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +33804,31925,Female,Loyal Customer,48,Business travel,Business,3058,3,3,3,3,4,5,5,4,4,5,4,5,4,3,3,3.0,satisfied +33805,114649,Female,Loyal Customer,31,Business travel,Business,390,5,5,5,5,4,4,4,4,5,2,4,5,5,4,4,4.0,satisfied +33806,59402,Female,Loyal Customer,14,Personal Travel,Eco,2367,1,2,1,2,5,1,5,5,4,4,1,2,1,5,0,0.0,neutral or dissatisfied +33807,54349,Female,Loyal Customer,54,Business travel,Business,3733,4,4,4,4,4,1,1,3,3,3,3,3,3,4,9,9.0,satisfied +33808,6971,Female,disloyal Customer,23,Business travel,Eco,196,5,0,5,3,2,5,2,2,4,4,4,3,5,2,28,34.0,satisfied +33809,79293,Male,Loyal Customer,25,Business travel,Business,2248,4,4,4,4,5,5,5,5,3,4,4,4,5,5,28,41.0,satisfied +33810,17986,Female,Loyal Customer,55,Business travel,Business,2911,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +33811,116859,Female,Loyal Customer,44,Business travel,Business,3631,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +33812,120051,Male,Loyal Customer,55,Personal Travel,Eco,356,4,3,4,3,5,4,5,5,2,2,4,4,4,5,0,0.0,neutral or dissatisfied +33813,2245,Male,Loyal Customer,56,Business travel,Business,3732,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +33814,66843,Male,Loyal Customer,22,Business travel,Eco,731,5,2,2,2,5,5,3,5,5,4,1,4,4,5,10,0.0,satisfied +33815,78942,Female,Loyal Customer,15,Personal Travel,Eco,500,3,5,2,2,4,2,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +33816,57461,Male,Loyal Customer,62,Personal Travel,Eco,334,2,4,2,4,2,2,2,2,5,5,5,4,5,2,11,0.0,neutral or dissatisfied +33817,76296,Male,Loyal Customer,54,Business travel,Business,2182,1,1,1,1,2,5,4,4,4,4,4,4,4,4,8,0.0,satisfied +33818,114622,Male,Loyal Customer,50,Business travel,Business,3217,5,5,5,5,2,5,4,5,5,5,5,4,5,4,2,0.0,satisfied +33819,27892,Female,Loyal Customer,29,Personal Travel,Eco,2329,4,4,4,4,3,4,3,3,5,2,5,3,5,3,1,0.0,neutral or dissatisfied +33820,41750,Female,Loyal Customer,36,Business travel,Business,456,5,5,5,5,5,4,3,4,4,4,4,3,4,4,0,0.0,satisfied +33821,86699,Male,Loyal Customer,56,Business travel,Business,1747,4,4,4,4,5,5,5,3,3,3,5,5,5,5,148,128.0,satisfied +33822,17053,Female,Loyal Customer,61,Business travel,Eco,1134,3,3,5,5,4,2,2,3,3,3,3,4,3,2,50,70.0,neutral or dissatisfied +33823,65552,Male,Loyal Customer,60,Business travel,Business,3173,3,3,3,3,5,4,4,4,4,4,5,3,4,4,0,3.0,satisfied +33824,49779,Male,Loyal Customer,36,Business travel,Eco,308,1,1,5,1,1,1,1,1,4,2,2,4,2,1,0,1.0,neutral or dissatisfied +33825,84127,Female,Loyal Customer,53,Business travel,Business,1569,5,5,2,5,3,4,4,4,4,4,4,3,4,5,11,0.0,satisfied +33826,57933,Male,disloyal Customer,28,Business travel,Business,1167,4,4,4,3,5,4,5,5,4,2,5,4,4,5,7,0.0,satisfied +33827,95858,Female,Loyal Customer,33,Business travel,Business,2956,1,1,1,1,5,4,5,4,4,4,4,3,4,5,11,4.0,satisfied +33828,115482,Male,Loyal Customer,44,Business travel,Business,2137,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +33829,5538,Male,Loyal Customer,7,Personal Travel,Eco,431,2,4,2,2,5,2,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +33830,15934,Female,Loyal Customer,15,Business travel,Business,723,5,5,5,5,3,3,3,3,3,1,3,5,2,3,0,0.0,satisfied +33831,108198,Male,Loyal Customer,22,Business travel,Eco Plus,705,4,3,3,3,4,4,4,4,3,3,2,2,1,4,4,0.0,satisfied +33832,65851,Male,Loyal Customer,65,Personal Travel,Eco,1389,5,1,5,4,4,5,4,4,1,5,3,1,4,4,2,0.0,satisfied +33833,6122,Female,Loyal Customer,35,Business travel,Business,1622,3,3,4,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +33834,43547,Female,Loyal Customer,24,Business travel,Business,3920,0,0,0,4,2,2,4,2,3,2,4,4,3,2,52,43.0,satisfied +33835,80964,Female,Loyal Customer,43,Business travel,Business,3989,0,0,0,4,5,5,4,4,4,5,5,5,4,5,0,0.0,satisfied +33836,22329,Male,disloyal Customer,62,Business travel,Eco,208,1,1,1,2,1,1,1,1,3,4,2,1,2,1,0,6.0,neutral or dissatisfied +33837,9783,Male,Loyal Customer,13,Personal Travel,Eco,383,1,4,1,2,4,1,4,4,3,4,5,3,4,4,0,9.0,neutral or dissatisfied +33838,40209,Female,Loyal Customer,51,Business travel,Business,3483,4,4,4,4,4,5,1,3,3,4,3,5,3,4,0,0.0,satisfied +33839,62977,Female,disloyal Customer,54,Business travel,Business,862,3,3,3,3,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +33840,19658,Female,Loyal Customer,59,Business travel,Eco,1236,4,3,3,3,2,1,4,4,4,4,4,3,4,1,41,93.0,satisfied +33841,52125,Male,Loyal Customer,51,Personal Travel,Eco Plus,438,3,5,3,2,2,3,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +33842,78458,Male,disloyal Customer,26,Business travel,Business,526,4,4,4,4,5,4,5,5,3,3,4,3,5,5,51,65.0,satisfied +33843,58818,Male,Loyal Customer,32,Personal Travel,Eco,1005,2,4,2,2,5,2,4,5,3,5,5,4,4,5,0,10.0,neutral or dissatisfied +33844,2905,Female,Loyal Customer,59,Personal Travel,Eco,409,4,5,4,3,2,5,4,1,1,4,1,3,1,4,0,0.0,neutral or dissatisfied +33845,92809,Female,Loyal Customer,70,Business travel,Business,1587,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +33846,75268,Male,Loyal Customer,46,Personal Travel,Eco,1726,1,5,1,2,2,1,2,2,3,5,4,5,4,2,21,14.0,neutral or dissatisfied +33847,123613,Male,Loyal Customer,60,Business travel,Eco Plus,273,4,5,5,5,4,4,4,4,3,2,4,4,1,4,0,0.0,satisfied +33848,37506,Female,disloyal Customer,17,Business travel,Eco,1011,2,2,2,4,3,2,3,3,2,3,4,3,4,3,0,0.0,neutral or dissatisfied +33849,17031,Male,Loyal Customer,41,Personal Travel,Eco,781,1,5,1,3,3,1,3,3,2,4,4,2,2,3,0,3.0,neutral or dissatisfied +33850,8979,Male,disloyal Customer,22,Business travel,Eco,325,5,5,5,4,3,5,3,3,2,4,4,4,1,3,0,0.0,satisfied +33851,40331,Female,Loyal Customer,23,Business travel,Eco Plus,463,5,1,1,1,5,5,3,5,1,3,2,1,1,5,0,0.0,satisfied +33852,103126,Male,disloyal Customer,24,Personal Travel,Eco,460,4,5,4,4,2,4,2,2,4,4,5,3,4,2,39,39.0,neutral or dissatisfied +33853,122259,Female,Loyal Customer,30,Personal Travel,Eco,544,3,1,1,1,4,1,4,4,4,5,2,3,2,4,24,62.0,neutral or dissatisfied +33854,6500,Male,Loyal Customer,60,Business travel,Business,2084,5,5,5,5,2,5,5,5,5,5,5,5,5,3,12,0.0,satisfied +33855,113462,Male,Loyal Customer,36,Business travel,Business,223,1,1,1,1,3,5,4,5,5,5,4,4,5,4,42,33.0,satisfied +33856,92894,Female,Loyal Customer,43,Business travel,Business,151,0,4,1,3,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +33857,58224,Female,Loyal Customer,43,Personal Travel,Eco,925,2,5,2,4,2,4,5,4,4,2,1,4,4,5,48,59.0,neutral or dissatisfied +33858,41641,Male,Loyal Customer,25,Personal Travel,Business,347,3,4,5,1,3,5,3,3,5,2,5,3,4,3,0,3.0,neutral or dissatisfied +33859,10168,Male,Loyal Customer,57,Business travel,Business,301,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +33860,74715,Male,Loyal Customer,51,Personal Travel,Eco,1235,5,2,5,4,5,5,5,5,4,2,4,2,4,5,0,0.0,satisfied +33861,34739,Female,disloyal Customer,24,Business travel,Eco,301,4,0,4,1,3,4,3,3,1,3,4,1,5,3,0,0.0,neutral or dissatisfied +33862,111045,Female,disloyal Customer,20,Business travel,Eco,319,2,4,2,3,3,2,5,3,2,1,4,3,4,3,19,10.0,neutral or dissatisfied +33863,36267,Male,Loyal Customer,37,Business travel,Business,2448,1,4,4,4,4,1,2,3,3,3,1,2,3,2,75,63.0,neutral or dissatisfied +33864,116,Female,disloyal Customer,26,Business travel,Business,562,2,2,2,3,3,2,4,3,1,1,3,1,3,3,0,8.0,neutral or dissatisfied +33865,92253,Female,Loyal Customer,12,Personal Travel,Eco,1670,2,0,2,1,1,2,1,1,4,4,5,4,5,1,41,18.0,neutral or dissatisfied +33866,101573,Female,Loyal Customer,42,Business travel,Business,2292,4,4,4,4,5,5,4,4,4,4,4,3,4,4,1,0.0,satisfied +33867,21376,Male,disloyal Customer,22,Business travel,Eco,528,4,3,3,3,2,3,2,2,3,3,5,3,2,2,7,0.0,satisfied +33868,86362,Male,disloyal Customer,49,Business travel,Business,762,5,5,5,1,3,5,3,3,5,5,4,4,4,3,0,0.0,satisfied +33869,78949,Male,Loyal Customer,51,Business travel,Business,2461,3,3,3,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +33870,102910,Male,Loyal Customer,9,Personal Travel,Business,436,1,4,1,2,2,1,2,2,5,3,5,5,5,2,0,,neutral or dissatisfied +33871,13428,Male,disloyal Customer,36,Business travel,Eco,475,2,5,2,3,2,1,1,1,1,3,1,1,2,1,171,185.0,neutral or dissatisfied +33872,36158,Female,Loyal Customer,35,Business travel,Eco,1674,5,2,1,2,5,5,5,5,4,5,4,1,5,5,0,4.0,satisfied +33873,116667,Female,Loyal Customer,34,Business travel,Eco Plus,404,3,1,1,1,3,3,3,3,1,3,3,1,2,3,0,0.0,neutral or dissatisfied +33874,127154,Male,Loyal Customer,58,Personal Travel,Eco,338,2,1,1,4,1,1,1,1,1,2,3,1,3,1,0,0.0,neutral or dissatisfied +33875,80579,Male,Loyal Customer,70,Personal Travel,Eco,1747,1,1,1,3,2,1,2,2,1,4,3,3,4,2,0,0.0,neutral or dissatisfied +33876,24486,Female,Loyal Customer,8,Business travel,Business,3149,3,3,3,3,4,4,4,4,5,5,5,1,5,4,0,0.0,satisfied +33877,21775,Male,Loyal Customer,43,Business travel,Business,3065,0,0,0,4,3,5,1,2,2,3,3,5,2,2,0,0.0,satisfied +33878,91429,Male,Loyal Customer,56,Personal Travel,Eco,549,4,1,4,3,3,4,3,3,4,1,3,3,2,3,2,0.0,neutral or dissatisfied +33879,70254,Male,disloyal Customer,59,Business travel,Eco,992,2,2,2,4,3,2,2,3,4,2,3,1,4,3,13,25.0,neutral or dissatisfied +33880,123503,Male,Loyal Customer,45,Business travel,Business,2217,1,1,1,1,1,1,1,4,5,4,3,1,2,1,0,6.0,neutral or dissatisfied +33881,59867,Female,Loyal Customer,46,Business travel,Business,1068,3,3,3,3,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +33882,104062,Male,Loyal Customer,52,Personal Travel,Eco,1044,2,2,2,3,5,2,5,5,2,2,2,4,3,5,0,0.0,neutral or dissatisfied +33883,21920,Female,Loyal Customer,66,Business travel,Business,448,3,4,4,4,1,4,3,3,3,3,3,4,3,1,4,4.0,neutral or dissatisfied +33884,2282,Female,disloyal Customer,25,Business travel,Eco,672,2,2,2,4,1,2,1,1,1,3,4,1,3,1,44,40.0,neutral or dissatisfied +33885,108756,Male,Loyal Customer,51,Business travel,Business,581,3,3,3,3,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +33886,7550,Female,Loyal Customer,44,Business travel,Business,2017,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +33887,55618,Female,Loyal Customer,51,Personal Travel,Eco Plus,404,2,5,2,3,3,4,4,1,1,2,5,5,1,4,2,0.0,neutral or dissatisfied +33888,91502,Female,disloyal Customer,33,Business travel,Business,1626,3,3,3,3,3,3,1,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +33889,13356,Female,disloyal Customer,56,Business travel,Eco,348,3,5,3,3,3,2,2,5,1,2,4,2,1,2,221,215.0,neutral or dissatisfied +33890,38476,Male,Loyal Customer,16,Personal Travel,Eco,846,3,4,3,5,5,3,5,5,5,3,5,5,4,5,0,5.0,neutral or dissatisfied +33891,19001,Male,Loyal Customer,31,Business travel,Business,2812,3,3,3,3,4,4,4,2,5,3,5,4,5,4,250,281.0,satisfied +33892,69407,Female,disloyal Customer,15,Business travel,Business,1096,5,2,5,1,5,2,5,5,3,2,4,5,5,5,0,0.0,satisfied +33893,107307,Female,Loyal Customer,69,Personal Travel,Eco,307,4,4,4,2,1,5,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +33894,22105,Male,Loyal Customer,27,Business travel,Business,694,1,1,1,1,4,4,4,4,4,5,2,5,5,4,3,3.0,satisfied +33895,55510,Male,disloyal Customer,39,Business travel,Business,991,4,5,5,1,1,5,1,1,4,2,5,4,4,1,79,63.0,satisfied +33896,22427,Female,Loyal Customer,15,Personal Travel,Eco,145,5,4,5,1,4,5,4,4,3,3,5,5,4,4,0,0.0,satisfied +33897,24732,Female,Loyal Customer,45,Business travel,Business,1805,1,1,1,1,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +33898,129838,Female,Loyal Customer,59,Personal Travel,Eco,308,3,5,3,4,2,5,5,3,3,3,3,4,3,4,32,24.0,neutral or dissatisfied +33899,2281,Male,Loyal Customer,50,Business travel,Business,690,2,1,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +33900,53259,Male,Loyal Customer,10,Personal Travel,Eco,4817,2,4,2,2,2,4,4,5,3,4,4,4,4,4,4,26.0,neutral or dissatisfied +33901,17316,Male,Loyal Customer,62,Personal Travel,Eco,403,4,5,2,1,4,2,4,4,4,5,4,3,5,4,0,0.0,satisfied +33902,96630,Female,disloyal Customer,22,Business travel,Eco,972,3,3,3,1,3,3,3,3,1,2,2,3,1,3,0,4.0,neutral or dissatisfied +33903,23903,Female,disloyal Customer,43,Business travel,Eco,589,2,5,3,3,2,3,3,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +33904,54831,Male,disloyal Customer,23,Business travel,Eco,641,5,1,5,1,4,5,1,4,3,2,4,3,4,4,0,5.0,satisfied +33905,31499,Male,Loyal Customer,28,Business travel,Business,3212,2,2,2,2,5,5,5,5,5,4,2,2,2,5,2,0.0,satisfied +33906,124670,Female,Loyal Customer,65,Business travel,Business,399,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,3.0,satisfied +33907,42734,Male,disloyal Customer,24,Business travel,Eco,136,1,4,1,3,4,1,4,4,1,4,3,3,4,4,0,7.0,neutral or dissatisfied +33908,75530,Female,Loyal Customer,44,Business travel,Business,2921,0,0,0,1,3,5,4,4,4,3,3,4,4,5,0,0.0,satisfied +33909,34538,Male,Loyal Customer,69,Personal Travel,Eco,636,1,5,1,4,1,1,1,1,5,2,5,3,5,1,5,22.0,neutral or dissatisfied +33910,105354,Male,Loyal Customer,45,Personal Travel,Eco,528,1,1,1,1,2,1,2,2,1,5,1,1,2,2,6,3.0,neutral or dissatisfied +33911,8579,Male,Loyal Customer,46,Business travel,Eco,308,1,0,0,4,1,4,4,3,4,4,3,4,3,4,179,166.0,neutral or dissatisfied +33912,14236,Female,Loyal Customer,48,Business travel,Business,1290,3,2,4,2,4,3,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +33913,60177,Female,Loyal Customer,40,Personal Travel,Eco,1120,2,5,2,4,2,2,2,2,3,3,4,4,4,2,0,34.0,neutral or dissatisfied +33914,68216,Female,Loyal Customer,56,Business travel,Business,1735,4,4,4,4,4,5,5,4,4,4,4,5,4,4,11,10.0,satisfied +33915,111113,Male,Loyal Customer,49,Business travel,Business,2041,3,3,3,3,3,4,5,5,5,5,4,4,5,4,0,38.0,satisfied +33916,21607,Female,Loyal Customer,53,Business travel,Eco,722,4,1,1,1,5,3,4,4,4,4,4,2,4,4,20,0.0,satisfied +33917,82438,Female,disloyal Customer,34,Business travel,Business,502,4,4,4,4,5,4,4,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +33918,81848,Female,Loyal Customer,61,Personal Travel,Eco,1416,1,3,1,3,3,4,2,5,5,1,1,1,5,1,0,0.0,neutral or dissatisfied +33919,74134,Male,Loyal Customer,54,Business travel,Business,1824,3,1,1,1,1,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +33920,79438,Female,Loyal Customer,53,Business travel,Business,187,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +33921,28976,Female,disloyal Customer,17,Business travel,Eco,1050,3,3,3,2,4,3,4,4,1,1,2,5,2,4,0,0.0,neutral or dissatisfied +33922,52564,Female,disloyal Customer,17,Business travel,Eco,160,2,4,2,5,4,2,4,4,4,3,3,4,1,4,0,0.0,neutral or dissatisfied +33923,17758,Male,Loyal Customer,41,Personal Travel,Eco,456,3,4,3,5,1,3,1,1,1,5,4,2,1,1,0,0.0,neutral or dissatisfied +33924,83865,Female,Loyal Customer,8,Personal Travel,Eco,425,2,2,2,4,5,2,5,5,3,1,4,1,3,5,0,4.0,neutral or dissatisfied +33925,112715,Female,Loyal Customer,8,Personal Travel,Eco,671,5,4,5,3,4,5,4,4,4,5,5,4,4,4,4,2.0,satisfied +33926,102469,Female,Loyal Customer,22,Personal Travel,Eco,414,1,0,1,5,2,1,2,2,4,2,3,4,4,2,5,0.0,neutral or dissatisfied +33927,93784,Female,Loyal Customer,45,Business travel,Business,859,1,1,1,1,2,4,5,2,2,2,2,3,2,5,15,0.0,satisfied +33928,52744,Male,Loyal Customer,59,Business travel,Business,3630,2,2,2,2,4,3,3,3,3,3,3,4,3,1,2,0.0,satisfied +33929,46943,Male,Loyal Customer,25,Personal Travel,Eco,848,4,4,4,3,2,4,2,2,4,1,3,3,3,2,1,0.0,neutral or dissatisfied +33930,111512,Male,Loyal Customer,12,Personal Travel,Eco,391,3,4,3,3,1,3,1,1,2,1,3,3,3,1,40,39.0,neutral or dissatisfied +33931,60957,Female,disloyal Customer,25,Business travel,Business,888,4,3,4,1,5,4,3,5,4,2,4,3,4,5,0,0.0,satisfied +33932,24589,Female,disloyal Customer,45,Business travel,Eco,526,2,0,2,2,2,2,3,2,1,5,4,3,2,2,0,0.0,neutral or dissatisfied +33933,123982,Male,disloyal Customer,36,Business travel,Business,184,1,1,1,4,4,1,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +33934,80493,Female,Loyal Customer,52,Business travel,Business,1749,2,2,2,2,3,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +33935,10374,Male,disloyal Customer,41,Business travel,Business,316,3,3,3,5,1,3,1,1,3,2,4,4,5,1,0,20.0,neutral or dissatisfied +33936,2360,Female,Loyal Customer,29,Business travel,Business,2652,1,1,1,1,1,1,1,1,4,3,3,3,4,1,0,12.0,neutral or dissatisfied +33937,43046,Female,disloyal Customer,33,Business travel,Eco,391,1,0,1,2,3,1,3,3,1,5,2,5,4,3,0,,neutral or dissatisfied +33938,18240,Female,Loyal Customer,51,Business travel,Eco,346,2,1,1,1,1,3,4,2,2,2,2,4,2,4,4,27.0,neutral or dissatisfied +33939,46421,Female,Loyal Customer,35,Business travel,Business,3026,1,1,4,1,5,4,5,3,3,3,3,3,3,4,5,26.0,satisfied +33940,43621,Female,Loyal Customer,26,Personal Travel,Eco,297,4,5,4,1,4,4,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +33941,49764,Female,Loyal Customer,45,Business travel,Eco,308,4,1,1,1,5,5,4,3,3,4,3,5,3,1,0,0.0,satisfied +33942,87973,Female,Loyal Customer,45,Business travel,Business,646,2,2,5,2,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +33943,51331,Female,Loyal Customer,27,Business travel,Eco Plus,110,4,2,2,2,4,4,4,4,3,4,4,1,4,4,47,38.0,neutral or dissatisfied +33944,93997,Male,Loyal Customer,47,Business travel,Business,3824,2,2,2,2,4,4,5,4,4,4,4,5,4,3,19,10.0,satisfied +33945,8394,Male,Loyal Customer,17,Business travel,Eco,888,3,3,2,3,3,3,2,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +33946,77308,Female,disloyal Customer,40,Business travel,Business,599,4,4,4,1,5,4,5,5,4,3,5,3,5,5,0,0.0,satisfied +33947,110464,Male,Loyal Customer,20,Personal Travel,Eco,925,4,4,4,2,2,4,2,2,5,4,3,5,4,2,18,5.0,neutral or dissatisfied +33948,33398,Male,Loyal Customer,46,Business travel,Business,2556,2,2,2,2,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +33949,70832,Female,Loyal Customer,29,Personal Travel,Business,761,2,1,2,4,2,2,2,2,2,4,4,3,3,2,61,44.0,neutral or dissatisfied +33950,48917,Male,Loyal Customer,32,Business travel,Eco,109,4,1,4,1,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +33951,104550,Female,disloyal Customer,19,Business travel,Eco Plus,1047,3,2,3,3,4,3,4,4,3,4,3,3,4,4,22,14.0,neutral or dissatisfied +33952,95571,Male,Loyal Customer,30,Personal Travel,Eco Plus,239,2,5,2,4,1,2,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +33953,70776,Male,disloyal Customer,32,Business travel,Business,328,2,2,2,2,2,2,2,2,4,4,4,4,5,2,21,12.0,neutral or dissatisfied +33954,114697,Male,Loyal Customer,36,Business travel,Business,308,0,0,0,3,5,4,5,5,5,5,5,5,5,3,52,49.0,satisfied +33955,93494,Female,disloyal Customer,25,Business travel,Eco,1107,1,1,1,4,5,1,5,5,3,3,3,3,3,5,29,9.0,neutral or dissatisfied +33956,39026,Female,Loyal Customer,11,Personal Travel,Eco,113,3,4,3,3,4,3,4,4,4,1,4,3,3,4,0,43.0,neutral or dissatisfied +33957,14143,Male,Loyal Customer,44,Personal Travel,Eco,654,1,0,1,3,2,1,1,2,3,1,3,3,2,2,0,0.0,neutral or dissatisfied +33958,106841,Female,disloyal Customer,22,Business travel,Eco,233,0,0,0,1,2,0,2,2,5,1,4,5,5,2,19,18.0,satisfied +33959,38616,Male,Loyal Customer,63,Personal Travel,Eco,231,3,5,3,1,1,3,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +33960,83082,Male,Loyal Customer,40,Business travel,Business,3082,3,1,1,1,1,2,1,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +33961,123010,Female,Loyal Customer,53,Business travel,Business,590,4,4,4,4,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +33962,121895,Female,Loyal Customer,39,Personal Travel,Eco,337,1,2,1,3,2,1,1,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +33963,116604,Female,Loyal Customer,56,Business travel,Business,362,5,5,3,5,4,5,5,5,5,5,5,5,5,5,25,26.0,satisfied +33964,40445,Female,Loyal Customer,52,Business travel,Eco,461,4,1,1,1,5,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +33965,124284,Female,Loyal Customer,43,Business travel,Business,255,0,0,0,4,3,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +33966,63326,Male,Loyal Customer,59,Business travel,Eco,337,3,5,5,5,3,3,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +33967,13419,Female,disloyal Customer,40,Business travel,Business,409,5,4,4,4,4,4,4,4,5,4,3,2,3,4,0,0.0,satisfied +33968,32910,Male,Loyal Customer,58,Personal Travel,Eco,163,3,1,3,4,2,3,1,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +33969,46292,Male,disloyal Customer,26,Business travel,Eco,533,3,3,3,1,3,3,3,3,5,3,1,3,2,3,5,4.0,neutral or dissatisfied +33970,117047,Male,disloyal Customer,24,Business travel,Eco,651,3,4,4,1,2,4,3,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +33971,78073,Male,disloyal Customer,26,Business travel,Eco Plus,332,4,2,4,4,4,4,4,4,1,1,3,1,4,4,0,3.0,neutral or dissatisfied +33972,77279,Female,Loyal Customer,43,Business travel,Eco,1931,2,2,2,2,2,2,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +33973,2498,Female,Loyal Customer,50,Personal Travel,Eco Plus,1379,2,4,2,1,1,1,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +33974,7743,Male,Loyal Customer,39,Business travel,Eco Plus,489,4,3,3,3,4,4,4,4,4,3,3,3,4,4,28,34.0,neutral or dissatisfied +33975,38292,Female,Loyal Customer,18,Business travel,Eco Plus,1111,3,3,3,3,3,3,2,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +33976,45299,Female,Loyal Customer,32,Business travel,Eco,175,4,2,4,2,4,4,4,4,5,3,2,4,3,4,0,2.0,satisfied +33977,56730,Female,Loyal Customer,51,Personal Travel,Eco,1023,4,1,4,4,2,4,3,1,1,4,1,3,1,3,2,9.0,neutral or dissatisfied +33978,65947,Female,Loyal Customer,52,Personal Travel,Business,1372,4,5,4,3,2,4,5,2,2,4,2,4,2,3,7,0.0,satisfied +33979,86997,Male,Loyal Customer,22,Personal Travel,Eco,907,3,5,3,3,3,3,2,3,5,3,4,4,4,3,67,58.0,neutral or dissatisfied +33980,74911,Female,Loyal Customer,42,Business travel,Business,2475,1,1,1,1,2,5,4,4,4,4,4,5,4,3,7,0.0,satisfied +33981,94308,Male,Loyal Customer,37,Business travel,Business,2924,5,5,3,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +33982,57764,Male,Loyal Customer,51,Business travel,Business,2704,4,2,4,4,3,3,3,5,3,4,5,3,5,3,287,272.0,satisfied +33983,34067,Male,Loyal Customer,61,Personal Travel,Eco,1674,3,5,3,2,5,3,5,5,1,4,4,5,5,5,16,0.0,neutral or dissatisfied +33984,70107,Male,Loyal Customer,54,Business travel,Business,2221,5,4,5,5,3,4,4,5,5,5,5,4,5,3,50,47.0,satisfied +33985,51706,Female,Loyal Customer,24,Business travel,Business,3986,4,5,5,5,4,4,4,4,3,1,3,3,4,4,33,26.0,neutral or dissatisfied +33986,70941,Female,disloyal Customer,22,Business travel,Eco,212,2,2,2,3,4,2,4,4,3,2,3,4,3,4,64,67.0,neutral or dissatisfied +33987,594,Male,Loyal Customer,42,Business travel,Business,1633,1,1,1,1,5,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +33988,89909,Female,disloyal Customer,27,Business travel,Business,1310,0,0,0,1,1,0,1,1,5,4,4,5,4,1,2,0.0,satisfied +33989,35961,Male,Loyal Customer,55,Business travel,Business,231,2,3,3,3,3,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +33990,90616,Female,Loyal Customer,72,Business travel,Business,240,1,1,1,1,2,3,3,1,1,1,1,2,1,1,0,16.0,neutral or dissatisfied +33991,126802,Female,disloyal Customer,42,Business travel,Business,947,5,0,0,2,1,5,1,1,4,4,5,3,5,1,0,1.0,satisfied +33992,80857,Male,Loyal Customer,49,Personal Travel,Eco,484,2,4,2,2,5,2,5,5,3,4,5,3,5,5,14,12.0,neutral or dissatisfied +33993,120266,Female,Loyal Customer,23,Business travel,Business,1576,5,5,5,5,5,5,5,5,3,2,5,3,4,5,21,42.0,satisfied +33994,87404,Male,Loyal Customer,63,Personal Travel,Eco,425,3,5,3,2,3,3,3,3,4,3,4,3,1,3,1,0.0,neutral or dissatisfied +33995,59235,Female,Loyal Customer,41,Personal Travel,Eco,649,3,1,3,3,1,3,1,1,1,4,3,1,3,1,32,28.0,neutral or dissatisfied +33996,83177,Male,disloyal Customer,38,Business travel,Business,549,2,1,1,4,3,1,1,3,3,4,4,4,5,3,13,2.0,neutral or dissatisfied +33997,121209,Male,Loyal Customer,44,Business travel,Business,2075,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +33998,75825,Female,Loyal Customer,42,Business travel,Business,1437,2,2,2,2,5,4,5,2,2,2,2,3,2,3,50,38.0,satisfied +33999,108893,Male,Loyal Customer,44,Business travel,Business,3597,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,11.0,satisfied +34000,99402,Male,Loyal Customer,35,Business travel,Business,314,4,4,4,4,4,5,5,5,5,5,5,4,5,4,10,26.0,satisfied +34001,85806,Female,Loyal Customer,27,Personal Travel,Eco,666,4,1,4,3,2,4,2,2,3,5,2,3,2,2,0,0.0,neutral or dissatisfied +34002,73582,Female,Loyal Customer,43,Business travel,Business,3926,3,3,3,3,3,5,4,5,5,5,4,4,5,3,19,16.0,satisfied +34003,118465,Male,Loyal Customer,39,Business travel,Business,621,2,2,2,2,4,5,4,5,5,5,5,5,5,5,74,77.0,satisfied +34004,109345,Female,Loyal Customer,78,Business travel,Eco Plus,672,4,2,2,2,1,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +34005,76429,Female,Loyal Customer,61,Business travel,Business,2337,2,4,4,4,3,3,3,2,2,2,2,4,2,3,76,71.0,neutral or dissatisfied +34006,115113,Male,Loyal Customer,45,Business travel,Business,1519,5,5,5,5,4,5,4,5,5,5,5,4,5,4,1,2.0,satisfied +34007,104141,Female,Loyal Customer,11,Personal Travel,Eco,393,2,4,2,3,3,2,3,3,1,3,3,2,2,3,5,0.0,neutral or dissatisfied +34008,129223,Male,disloyal Customer,21,Business travel,Business,1235,5,0,5,1,4,5,4,4,4,5,4,4,4,4,1,0.0,satisfied +34009,34032,Male,Loyal Customer,45,Business travel,Eco Plus,1617,4,1,1,1,4,4,4,4,3,2,3,3,1,4,6,0.0,satisfied +34010,14166,Female,disloyal Customer,22,Business travel,Eco,526,3,5,4,4,5,4,5,5,1,3,5,2,5,5,44,48.0,neutral or dissatisfied +34011,50118,Female,Loyal Customer,51,Business travel,Business,2591,1,1,1,1,1,1,2,2,2,2,1,1,2,2,103,101.0,neutral or dissatisfied +34012,105353,Female,Loyal Customer,18,Personal Travel,Eco,528,3,1,3,2,1,3,5,1,2,2,3,2,3,1,0,0.0,neutral or dissatisfied +34013,24597,Female,Loyal Customer,55,Business travel,Eco,526,4,5,5,5,3,1,3,4,4,4,4,1,4,2,0,0.0,satisfied +34014,6146,Female,Loyal Customer,24,Business travel,Business,501,1,1,1,1,4,4,4,4,5,4,5,3,5,4,59,70.0,satisfied +34015,87549,Female,Loyal Customer,28,Business travel,Business,743,3,3,3,3,5,5,5,5,5,5,4,4,4,5,0,0.0,satisfied +34016,37440,Male,Loyal Customer,47,Business travel,Business,1076,3,3,3,3,5,5,4,4,4,4,4,3,4,4,0,10.0,satisfied +34017,45666,Female,Loyal Customer,59,Personal Travel,Eco Plus,113,2,5,2,3,1,1,1,2,2,2,3,5,2,5,4,0.0,neutral or dissatisfied +34018,42075,Female,disloyal Customer,50,Business travel,Eco Plus,116,3,4,4,4,1,3,1,1,1,3,5,2,5,1,0,0.0,neutral or dissatisfied +34019,80298,Female,Loyal Customer,46,Business travel,Business,3831,2,1,1,1,5,3,3,2,2,2,2,2,2,1,21,0.0,neutral or dissatisfied +34020,98833,Male,Loyal Customer,12,Personal Travel,Eco,763,2,2,2,3,1,2,2,1,1,2,3,2,4,1,57,35.0,neutral or dissatisfied +34021,53010,Male,Loyal Customer,18,Business travel,Business,3485,4,5,5,5,4,4,4,4,1,4,3,1,4,4,1,0.0,neutral or dissatisfied +34022,96762,Female,Loyal Customer,13,Personal Travel,Business,849,0,5,0,3,2,0,2,2,3,2,4,4,4,2,6,5.0,satisfied +34023,18188,Male,disloyal Customer,40,Business travel,Business,235,3,3,3,3,3,3,4,3,2,2,2,3,1,3,5,0.0,satisfied +34024,16718,Female,Loyal Customer,15,Personal Travel,Eco Plus,284,3,5,2,4,5,2,5,5,4,3,4,4,4,5,11,0.0,neutral or dissatisfied +34025,105586,Male,Loyal Customer,17,Personal Travel,Eco,577,4,4,4,2,1,4,1,1,4,4,4,5,4,1,7,2.0,neutral or dissatisfied +34026,10278,Female,disloyal Customer,24,Business travel,Business,201,5,4,5,1,1,5,1,1,4,5,5,3,4,1,84,90.0,satisfied +34027,31355,Male,Loyal Customer,59,Business travel,Eco,692,4,3,3,3,4,4,4,4,2,2,4,4,2,4,0,39.0,satisfied +34028,54313,Female,Loyal Customer,43,Business travel,Business,1597,2,2,3,2,2,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +34029,95877,Female,Loyal Customer,26,Business travel,Eco,580,3,2,2,2,3,2,3,1,2,4,4,3,1,3,167,184.0,neutral or dissatisfied +34030,68303,Male,disloyal Customer,22,Business travel,Eco,1029,2,2,2,4,1,2,1,1,4,4,4,1,3,1,0,0.0,neutral or dissatisfied +34031,67851,Male,Loyal Customer,8,Personal Travel,Eco,1235,2,3,2,4,3,2,3,3,1,4,4,2,4,3,21,23.0,neutral or dissatisfied +34032,116894,Female,Loyal Customer,48,Business travel,Business,370,5,5,5,5,5,4,5,5,5,4,5,4,5,5,26,18.0,satisfied +34033,4611,Male,disloyal Customer,21,Business travel,Business,719,5,0,4,1,5,4,2,5,3,2,5,4,4,5,9,16.0,satisfied +34034,91021,Male,Loyal Customer,47,Personal Travel,Eco,404,3,4,3,2,2,3,1,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +34035,7683,Male,Loyal Customer,54,Business travel,Eco,367,4,4,4,4,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +34036,54062,Male,Loyal Customer,36,Business travel,Business,1416,1,1,5,1,3,2,3,5,5,5,5,1,5,3,1,0.0,satisfied +34037,60159,Male,Loyal Customer,33,Personal Travel,Eco,1182,4,4,4,4,2,4,2,2,4,5,4,4,4,2,0,0.0,satisfied +34038,111583,Female,Loyal Customer,10,Personal Travel,Eco,794,3,4,3,4,5,3,5,5,5,5,5,4,4,5,15,24.0,neutral or dissatisfied +34039,108840,Female,Loyal Customer,50,Personal Travel,Business,2139,5,4,5,4,5,5,4,4,4,5,4,5,4,4,60,78.0,satisfied +34040,125267,Male,disloyal Customer,24,Business travel,Eco,1497,1,1,1,3,5,1,5,5,2,2,2,1,2,5,0,19.0,neutral or dissatisfied +34041,75086,Male,Loyal Customer,28,Business travel,Business,1814,3,3,3,3,5,5,5,5,5,5,4,4,4,5,44,31.0,satisfied +34042,100368,Male,Loyal Customer,21,Personal Travel,Eco,1034,3,1,4,4,5,4,1,5,4,3,4,4,3,5,0,10.0,neutral or dissatisfied +34043,17807,Male,Loyal Customer,7,Business travel,Business,2893,4,4,4,4,4,4,4,4,1,4,4,3,3,4,23,32.0,neutral or dissatisfied +34044,6641,Male,disloyal Customer,47,Business travel,Business,416,5,5,5,4,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +34045,16116,Female,Loyal Customer,34,Business travel,Business,1706,3,3,3,3,2,4,3,3,3,3,3,3,3,3,20,16.0,neutral or dissatisfied +34046,39966,Female,Loyal Customer,48,Personal Travel,Business,1404,2,4,2,2,1,2,4,1,1,2,1,1,1,5,0,0.0,neutral or dissatisfied +34047,13394,Male,disloyal Customer,27,Business travel,Eco,456,2,0,2,3,5,2,5,5,4,3,1,5,3,5,0,0.0,neutral or dissatisfied +34048,104783,Male,Loyal Customer,48,Business travel,Business,587,4,4,2,4,2,4,5,4,4,4,4,4,4,4,10,23.0,satisfied +34049,13346,Male,Loyal Customer,50,Business travel,Eco,631,4,3,3,3,4,4,4,4,4,5,1,4,5,4,0,0.0,satisfied +34050,119452,Female,disloyal Customer,25,Business travel,Business,759,4,2,4,4,2,4,2,2,1,1,4,3,4,2,0,22.0,neutral or dissatisfied +34051,2582,Female,Loyal Customer,22,Business travel,Business,3006,2,2,2,2,2,2,2,2,1,3,4,3,3,2,13,36.0,neutral or dissatisfied +34052,75279,Female,Loyal Customer,7,Personal Travel,Eco,1723,2,5,2,4,1,2,1,1,5,5,5,4,5,1,67,44.0,neutral or dissatisfied +34053,18078,Female,Loyal Customer,67,Personal Travel,Eco,488,1,2,1,3,1,2,3,3,3,1,3,3,3,2,32,21.0,neutral or dissatisfied +34054,104089,Female,Loyal Customer,45,Business travel,Business,666,5,5,5,5,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +34055,69611,Male,Loyal Customer,23,Personal Travel,Eco,2475,2,4,2,1,5,2,5,5,5,3,4,5,3,5,0,28.0,neutral or dissatisfied +34056,94691,Female,Loyal Customer,54,Business travel,Business,192,2,3,3,3,1,3,2,3,3,3,2,4,3,1,15,7.0,neutral or dissatisfied +34057,37353,Female,Loyal Customer,39,Business travel,Business,3597,2,2,2,2,3,1,3,5,5,5,5,5,5,4,57,66.0,satisfied +34058,16179,Female,disloyal Customer,18,Business travel,Eco,212,5,0,5,2,1,5,1,1,2,3,4,5,2,1,0,0.0,satisfied +34059,77170,Male,Loyal Customer,52,Personal Travel,Business,1355,3,4,3,1,5,5,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +34060,65782,Male,Loyal Customer,33,Business travel,Business,1389,3,3,3,3,5,5,5,5,4,2,4,3,4,5,6,0.0,satisfied +34061,59654,Male,Loyal Customer,34,Personal Travel,Eco,965,3,5,3,2,1,3,1,1,4,3,5,3,4,1,1,0.0,neutral or dissatisfied +34062,28161,Female,disloyal Customer,27,Business travel,Eco,834,1,1,1,3,2,1,2,2,4,3,5,3,3,2,0,0.0,neutral or dissatisfied +34063,116273,Male,Loyal Customer,65,Personal Travel,Eco,337,1,4,1,3,2,1,2,2,5,5,5,3,4,2,28,24.0,neutral or dissatisfied +34064,85636,Female,Loyal Customer,56,Personal Travel,Eco,317,2,4,5,3,4,3,3,4,4,5,4,2,4,4,7,5.0,neutral or dissatisfied +34065,73266,Male,disloyal Customer,23,Business travel,Business,1005,0,4,0,1,5,0,5,5,3,3,4,4,5,5,31,27.0,satisfied +34066,18500,Female,Loyal Customer,42,Business travel,Business,201,3,3,3,3,4,4,3,4,4,4,5,5,4,5,0,0.0,satisfied +34067,122812,Male,Loyal Customer,26,Personal Travel,Eco,599,1,2,1,2,1,1,1,1,2,1,3,1,2,1,0,0.0,neutral or dissatisfied +34068,125251,Male,Loyal Customer,56,Personal Travel,Eco,427,2,4,4,1,2,4,2,2,3,5,5,3,1,2,0,0.0,neutral or dissatisfied +34069,88046,Male,disloyal Customer,24,Business travel,Eco,270,2,0,2,5,2,2,2,2,3,2,4,3,5,2,8,1.0,neutral or dissatisfied +34070,66719,Male,Loyal Customer,27,Personal Travel,Eco,802,3,5,4,3,4,4,3,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +34071,94619,Female,Loyal Customer,51,Business travel,Business,2176,4,4,4,4,5,4,4,3,3,3,3,4,3,3,1,10.0,satisfied +34072,68357,Male,Loyal Customer,39,Business travel,Business,1598,5,5,5,5,2,4,4,4,4,4,4,4,4,4,75,86.0,satisfied +34073,104046,Male,Loyal Customer,31,Business travel,Eco,1262,2,2,2,2,2,2,2,2,4,5,4,3,4,2,5,0.0,neutral or dissatisfied +34074,40097,Female,Loyal Customer,40,Business travel,Business,3193,3,3,3,3,1,3,1,5,5,5,5,4,5,1,3,0.0,satisfied +34075,45642,Male,Loyal Customer,20,Personal Travel,Eco,260,4,3,4,2,5,4,3,5,4,3,2,3,3,5,0,0.0,neutral or dissatisfied +34076,25565,Male,Loyal Customer,24,Business travel,Business,2013,2,2,2,2,4,4,4,4,5,3,2,5,4,4,9,16.0,satisfied +34077,84452,Male,Loyal Customer,37,Business travel,Business,290,0,0,0,3,5,5,4,2,2,2,2,4,2,5,3,0.0,satisfied +34078,101951,Male,disloyal Customer,37,Business travel,Eco,628,3,4,3,3,3,3,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +34079,31857,Male,Loyal Customer,15,Personal Travel,Eco,2640,2,4,2,2,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +34080,19443,Female,Loyal Customer,21,Business travel,Eco,503,5,3,3,3,5,5,5,5,5,2,4,5,1,5,7,0.0,satisfied +34081,126535,Male,Loyal Customer,26,Business travel,Business,644,1,1,1,1,2,2,2,2,3,4,4,5,4,2,0,4.0,satisfied +34082,118673,Female,Loyal Customer,39,Business travel,Business,2431,4,1,1,1,5,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +34083,50883,Male,Loyal Customer,67,Personal Travel,Eco,266,2,0,2,3,1,2,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +34084,5547,Male,Loyal Customer,69,Personal Travel,Eco,431,2,5,2,2,1,2,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +34085,35760,Female,Loyal Customer,54,Personal Travel,Eco Plus,1608,4,5,5,3,3,3,5,3,3,5,3,5,3,3,0,0.0,neutral or dissatisfied +34086,73634,Male,Loyal Customer,39,Business travel,Business,1884,1,1,1,1,2,4,4,5,5,5,5,3,5,3,6,13.0,satisfied +34087,112649,Male,Loyal Customer,65,Personal Travel,Eco,1845,4,5,4,3,1,4,1,1,4,5,4,3,5,1,0,11.0,neutral or dissatisfied +34088,98639,Male,Loyal Customer,33,Business travel,Business,861,3,3,3,3,3,3,3,3,1,3,3,1,4,3,15,4.0,neutral or dissatisfied +34089,17403,Female,disloyal Customer,32,Business travel,Eco,351,3,5,3,1,1,3,1,1,2,1,2,5,2,1,0,0.0,neutral or dissatisfied +34090,18119,Male,Loyal Customer,29,Business travel,Business,1691,3,3,3,3,4,5,4,4,4,2,2,3,2,4,0,0.0,satisfied +34091,126748,Female,Loyal Customer,42,Personal Travel,Eco,2521,1,1,1,1,3,2,2,1,1,1,1,1,1,2,18,0.0,neutral or dissatisfied +34092,64562,Female,disloyal Customer,24,Business travel,Business,247,4,1,4,2,1,4,1,1,4,2,5,4,5,1,0,0.0,satisfied +34093,99671,Male,Loyal Customer,56,Personal Travel,Eco,1050,2,4,2,4,3,2,3,3,4,4,5,4,5,3,2,0.0,neutral or dissatisfied +34094,118743,Female,Loyal Customer,31,Personal Travel,Eco,304,4,4,4,1,1,4,5,1,5,3,5,4,5,1,21,12.0,neutral or dissatisfied +34095,129106,Male,Loyal Customer,20,Personal Travel,Eco,2342,1,2,1,2,3,1,3,3,2,2,2,1,1,3,15,6.0,neutral or dissatisfied +34096,34577,Female,Loyal Customer,39,Business travel,Eco,1598,1,5,5,5,1,1,1,1,2,5,2,3,4,1,0,0.0,neutral or dissatisfied +34097,72546,Male,disloyal Customer,26,Business travel,Business,1119,3,3,3,1,1,3,1,1,1,4,2,4,1,1,64,57.0,neutral or dissatisfied +34098,32237,Female,Loyal Customer,52,Business travel,Eco,163,2,5,5,5,1,4,4,2,2,2,2,3,2,2,0,0.0,satisfied +34099,13785,Female,Loyal Customer,32,Personal Travel,Eco,925,5,1,5,4,5,5,5,5,3,1,3,4,4,5,12,0.0,satisfied +34100,80571,Male,Loyal Customer,56,Business travel,Business,1747,2,2,3,2,3,3,5,5,5,5,5,5,5,4,1,0.0,satisfied +34101,75955,Female,disloyal Customer,37,Business travel,Business,228,5,5,5,3,2,5,2,2,3,3,5,4,4,2,41,31.0,satisfied +34102,30477,Male,Loyal Customer,31,Business travel,Business,2917,2,2,2,2,3,2,3,3,5,4,3,3,2,3,37,31.0,satisfied +34103,94508,Male,Loyal Customer,55,Business travel,Business,239,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,10.0,satisfied +34104,36262,Male,Loyal Customer,55,Business travel,Eco,612,3,1,1,1,3,3,3,3,2,5,3,4,4,3,0,0.0,neutral or dissatisfied +34105,88121,Female,Loyal Customer,45,Business travel,Business,270,2,2,2,2,2,5,5,4,4,4,4,3,4,3,2,0.0,satisfied +34106,51861,Female,disloyal Customer,24,Business travel,Eco,522,5,0,5,4,4,5,4,4,2,2,3,2,5,4,0,0.0,satisfied +34107,72938,Female,Loyal Customer,46,Business travel,Business,3579,5,5,5,5,5,4,5,4,4,4,4,3,4,3,3,0.0,satisfied +34108,72163,Female,Loyal Customer,45,Business travel,Business,3518,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +34109,60941,Male,disloyal Customer,23,Business travel,Eco,888,3,3,3,1,4,3,4,4,5,4,4,5,5,4,0,8.0,neutral or dissatisfied +34110,59135,Female,Loyal Customer,27,Personal Travel,Eco,1744,2,5,2,2,5,2,5,5,3,3,4,4,4,5,4,0.0,neutral or dissatisfied +34111,39897,Female,disloyal Customer,30,Business travel,Eco Plus,132,2,2,2,4,1,2,2,1,1,1,3,2,3,1,23,29.0,neutral or dissatisfied +34112,109198,Female,Loyal Customer,72,Business travel,Eco,391,1,4,5,4,1,4,4,1,1,1,1,2,1,4,69,59.0,neutral or dissatisfied +34113,83214,Male,Loyal Customer,41,Business travel,Business,1979,2,2,2,2,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +34114,43295,Female,Loyal Customer,43,Business travel,Business,3604,3,3,3,3,1,5,5,4,4,4,4,3,4,2,0,0.0,satisfied +34115,55193,Female,Loyal Customer,46,Personal Travel,Eco Plus,1303,4,5,4,4,4,4,4,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +34116,97093,Male,Loyal Customer,39,Business travel,Business,3850,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +34117,117353,Female,disloyal Customer,22,Business travel,Eco,296,3,0,3,2,4,3,4,4,4,2,5,3,5,4,0,5.0,neutral or dissatisfied +34118,116287,Female,Loyal Customer,34,Personal Travel,Eco,308,1,4,2,5,3,2,3,3,5,3,5,3,3,3,11,14.0,neutral or dissatisfied +34119,33887,Female,disloyal Customer,24,Business travel,Eco Plus,994,4,0,4,4,3,4,1,3,2,1,5,3,5,3,8,6.0,satisfied +34120,9379,Female,Loyal Customer,57,Personal Travel,Eco,441,3,5,3,5,4,5,4,3,3,3,3,4,3,5,1,0.0,neutral or dissatisfied +34121,117533,Female,disloyal Customer,26,Business travel,Business,1020,5,5,5,4,5,5,5,5,5,3,5,5,4,5,24,18.0,satisfied +34122,72841,Female,Loyal Customer,63,Personal Travel,Eco,1013,2,3,2,1,5,5,5,2,2,2,4,2,2,5,39,31.0,neutral or dissatisfied +34123,96255,Male,Loyal Customer,34,Personal Travel,Eco,460,2,2,2,3,2,2,2,2,1,4,2,4,2,2,30,21.0,neutral or dissatisfied +34124,46834,Female,disloyal Customer,42,Business travel,Eco,776,3,3,3,3,2,3,2,2,4,2,4,1,2,2,0,0.0,neutral or dissatisfied +34125,94781,Male,disloyal Customer,32,Business travel,Eco,458,3,1,3,3,5,3,5,5,2,5,2,4,2,5,24,17.0,neutral or dissatisfied +34126,120767,Female,disloyal Customer,44,Business travel,Eco,678,2,2,2,4,1,2,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +34127,95276,Female,Loyal Customer,38,Personal Travel,Eco,562,4,4,4,3,5,4,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +34128,66905,Female,Loyal Customer,59,Personal Travel,Business,929,2,4,2,4,5,5,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +34129,32442,Male,Loyal Customer,33,Business travel,Business,1896,3,3,3,3,4,4,3,4,4,4,2,3,2,4,2,7.0,satisfied +34130,72858,Female,disloyal Customer,40,Business travel,Business,700,4,4,4,2,1,4,4,1,5,5,5,4,4,1,0,0.0,satisfied +34131,80544,Female,Loyal Customer,58,Business travel,Business,1747,1,1,1,1,4,3,4,4,4,4,4,5,4,3,7,0.0,satisfied +34132,43954,Male,Loyal Customer,51,Personal Travel,Eco,408,0,5,0,1,4,0,1,4,2,1,1,1,4,4,10,38.0,satisfied +34133,65268,Female,Loyal Customer,35,Business travel,Eco Plus,224,3,2,2,2,3,3,3,3,2,5,3,2,4,3,2,0.0,neutral or dissatisfied +34134,63464,Female,Loyal Customer,60,Business travel,Business,2816,1,1,1,1,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +34135,97081,Male,Loyal Customer,20,Business travel,Business,1642,5,5,5,5,5,5,5,5,4,5,3,3,5,5,17,27.0,satisfied +34136,16406,Male,Loyal Customer,59,Personal Travel,Eco,463,4,4,4,4,3,4,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +34137,98791,Female,disloyal Customer,21,Business travel,Business,230,5,3,5,4,2,5,2,2,4,1,1,5,3,2,0,0.0,satisfied +34138,29290,Male,Loyal Customer,41,Business travel,Eco,834,5,5,3,3,5,5,5,5,1,2,3,4,4,5,0,1.0,satisfied +34139,83536,Female,disloyal Customer,20,Business travel,Eco,1121,4,4,4,4,5,4,5,5,2,2,4,3,3,5,0,6.0,neutral or dissatisfied +34140,40316,Male,Loyal Customer,31,Personal Travel,Eco,358,3,5,3,3,4,3,4,4,4,2,5,4,5,4,0,,neutral or dissatisfied +34141,38654,Male,Loyal Customer,60,Business travel,Business,2704,1,1,1,1,2,4,3,3,3,4,3,2,3,1,0,0.0,satisfied +34142,25080,Female,Loyal Customer,32,Business travel,Business,957,3,4,4,4,3,3,3,3,2,3,3,1,4,3,24,42.0,neutral or dissatisfied +34143,64735,Female,Loyal Customer,56,Business travel,Business,2378,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +34144,72165,Male,Loyal Customer,22,Business travel,Eco Plus,731,4,2,2,2,4,4,4,4,5,4,2,4,1,4,0,3.0,satisfied +34145,84338,Female,Loyal Customer,41,Business travel,Business,2281,1,1,1,1,4,4,5,5,5,5,5,5,5,4,53,54.0,satisfied +34146,57167,Female,Loyal Customer,41,Business travel,Business,2227,1,1,1,1,2,5,5,2,2,2,2,4,2,4,21,0.0,satisfied +34147,12678,Male,disloyal Customer,25,Business travel,Eco,851,2,1,1,5,1,1,1,1,4,4,3,4,2,1,6,0.0,neutral or dissatisfied +34148,35746,Female,Loyal Customer,39,Business travel,Business,1826,1,5,5,5,4,3,2,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +34149,49424,Female,disloyal Customer,21,Business travel,Eco,89,1,2,1,3,1,1,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +34150,102865,Male,Loyal Customer,55,Business travel,Business,2152,5,5,5,5,2,4,5,4,4,4,4,5,4,5,19,26.0,satisfied +34151,43748,Female,Loyal Customer,38,Business travel,Business,3982,5,5,5,5,2,2,3,4,4,4,4,5,4,1,0,0.0,satisfied +34152,41369,Male,Loyal Customer,29,Business travel,Business,1782,1,1,1,1,5,5,5,5,4,3,1,1,1,5,0,0.0,satisfied +34153,65825,Male,Loyal Customer,56,Business travel,Business,1389,5,5,5,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +34154,27841,Male,Loyal Customer,50,Personal Travel,Eco,1448,3,1,3,4,4,3,5,4,1,1,3,4,4,4,0,0.0,neutral or dissatisfied +34155,30103,Male,Loyal Customer,46,Personal Travel,Eco,261,3,2,3,3,2,3,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +34156,46604,Female,Loyal Customer,71,Business travel,Business,3032,2,2,2,2,5,4,4,5,5,5,4,2,5,4,0,0.0,satisfied +34157,26945,Male,Loyal Customer,18,Business travel,Eco,2402,5,2,2,2,5,5,5,5,3,1,3,2,5,5,15,0.0,satisfied +34158,32931,Male,Loyal Customer,35,Personal Travel,Eco,101,2,4,2,3,5,2,5,5,5,3,5,3,4,5,0,17.0,neutral or dissatisfied +34159,70066,Male,Loyal Customer,41,Business travel,Business,460,3,3,3,3,4,2,3,3,3,3,3,1,3,1,32,27.0,neutral or dissatisfied +34160,66986,Female,Loyal Customer,29,Business travel,Business,2740,5,5,5,5,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +34161,102457,Male,Loyal Customer,50,Personal Travel,Eco,223,2,5,2,4,5,2,1,5,4,2,5,3,5,5,0,2.0,neutral or dissatisfied +34162,124872,Female,Loyal Customer,57,Business travel,Business,3194,1,1,1,1,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +34163,109850,Male,disloyal Customer,39,Business travel,Business,1052,2,2,2,4,2,2,2,2,4,2,4,5,5,2,52,32.0,neutral or dissatisfied +34164,52096,Female,Loyal Customer,65,Personal Travel,Eco,351,2,5,4,5,5,5,4,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +34165,725,Male,disloyal Customer,21,Business travel,Eco,309,1,5,0,2,3,0,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +34166,27332,Female,Loyal Customer,57,Business travel,Eco,987,4,4,4,4,2,2,5,4,4,4,4,4,4,5,0,0.0,satisfied +34167,122897,Male,Loyal Customer,48,Business travel,Business,590,2,2,2,2,5,4,5,5,5,5,5,4,5,3,61,53.0,satisfied +34168,113979,Female,Loyal Customer,36,Business travel,Eco,1838,3,1,1,1,3,3,3,3,3,5,3,2,4,3,9,33.0,neutral or dissatisfied +34169,61642,Male,Loyal Customer,44,Business travel,Business,1635,1,1,1,1,4,5,5,4,4,4,4,5,4,5,9,0.0,satisfied +34170,16129,Male,Loyal Customer,12,Personal Travel,Eco,725,1,1,0,4,4,0,2,4,1,5,3,3,4,4,5,11.0,neutral or dissatisfied +34171,76495,Male,disloyal Customer,32,Business travel,Business,481,2,2,2,1,2,2,2,2,4,2,4,5,4,2,23,23.0,neutral or dissatisfied +34172,44247,Female,Loyal Customer,51,Business travel,Business,3601,4,4,4,4,2,2,4,5,5,5,4,4,5,3,0,3.0,satisfied +34173,22884,Female,Loyal Customer,65,Personal Travel,Eco,302,3,5,3,2,2,5,4,1,1,3,1,3,1,4,0,4.0,neutral or dissatisfied +34174,96946,Male,Loyal Customer,40,Business travel,Business,359,1,1,1,1,4,4,4,5,5,5,5,5,5,3,33,26.0,satisfied +34175,22390,Female,disloyal Customer,23,Business travel,Eco,143,2,2,2,3,5,2,5,5,3,5,3,3,3,5,0,5.0,neutral or dissatisfied +34176,4347,Male,Loyal Customer,48,Business travel,Business,473,5,5,5,5,3,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +34177,84371,Male,disloyal Customer,9,Business travel,Eco,606,2,3,2,3,2,2,2,4,3,3,4,2,3,2,132,108.0,neutral or dissatisfied +34178,78336,Male,Loyal Customer,50,Business travel,Business,1547,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +34179,126981,Male,Loyal Customer,46,Business travel,Business,338,2,5,2,2,3,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +34180,67611,Male,disloyal Customer,55,Business travel,Business,1126,5,5,5,4,1,5,1,1,5,3,4,5,5,1,0,0.0,satisfied +34181,64727,Male,Loyal Customer,52,Business travel,Business,190,0,4,0,4,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +34182,98138,Female,Loyal Customer,44,Business travel,Business,472,3,3,3,3,2,4,5,5,5,5,5,5,5,3,10,0.0,satisfied +34183,7299,Female,disloyal Customer,54,Business travel,Business,139,4,5,5,1,3,4,3,3,3,4,5,4,5,3,0,0.0,satisfied +34184,68058,Male,disloyal Customer,28,Business travel,Business,868,2,2,2,2,1,2,1,1,4,5,5,3,4,1,23,21.0,neutral or dissatisfied +34185,108480,Male,Loyal Customer,40,Business travel,Business,570,3,3,3,3,2,5,4,4,4,4,4,4,4,5,33,21.0,satisfied +34186,127949,Female,Loyal Customer,68,Personal Travel,Business,1999,3,3,3,3,4,3,3,5,5,3,5,3,5,2,55,54.0,neutral or dissatisfied +34187,49426,Male,Loyal Customer,35,Business travel,Eco,86,4,1,1,1,4,5,4,4,2,2,4,5,4,4,0,0.0,satisfied +34188,34886,Male,Loyal Customer,42,Business travel,Business,2477,1,1,1,1,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +34189,69527,Male,disloyal Customer,25,Business travel,Eco,2475,2,2,2,4,2,2,2,4,1,4,4,2,4,2,0,0.0,neutral or dissatisfied +34190,120996,Male,Loyal Customer,46,Business travel,Business,592,4,4,4,4,4,4,5,3,3,4,3,3,3,2,0,0.0,satisfied +34191,99025,Male,disloyal Customer,29,Business travel,Business,1009,4,4,4,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +34192,11704,Male,Loyal Customer,32,Business travel,Business,2118,2,2,2,2,2,2,2,2,3,5,3,3,3,2,42,34.0,neutral or dissatisfied +34193,89570,Male,Loyal Customer,50,Business travel,Business,2664,1,1,1,1,3,5,5,5,5,5,5,3,5,4,72,49.0,satisfied +34194,120875,Male,Loyal Customer,52,Business travel,Business,861,3,3,3,3,3,5,5,4,4,4,4,3,4,5,86,65.0,satisfied +34195,119331,Male,Loyal Customer,56,Personal Travel,Eco,214,3,3,0,4,1,0,1,1,1,5,3,1,4,1,0,0.0,neutral or dissatisfied +34196,23535,Female,disloyal Customer,45,Business travel,Eco,423,3,3,3,3,4,3,5,4,3,2,3,3,3,4,0,8.0,neutral or dissatisfied +34197,36934,Male,Loyal Customer,70,Personal Travel,Eco,867,5,4,5,2,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +34198,97180,Male,Loyal Customer,40,Personal Travel,Eco,1390,1,2,1,4,3,1,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +34199,25175,Female,Loyal Customer,17,Business travel,Business,3554,4,4,4,4,4,4,4,4,4,3,4,4,4,4,2,7.0,satisfied +34200,34704,Female,Loyal Customer,60,Business travel,Business,264,0,0,0,2,4,1,5,3,3,3,3,2,3,2,0,0.0,satisfied +34201,29333,Female,Loyal Customer,49,Personal Travel,Eco,834,4,5,4,4,4,5,5,4,4,4,4,4,4,4,42,37.0,neutral or dissatisfied +34202,116866,Female,Loyal Customer,31,Business travel,Business,368,5,5,5,5,4,4,4,4,3,4,5,5,5,4,19,13.0,satisfied +34203,25069,Female,Loyal Customer,69,Personal Travel,Eco,594,1,5,1,2,4,4,2,2,2,1,4,2,2,2,10,6.0,neutral or dissatisfied +34204,115227,Female,Loyal Customer,54,Business travel,Business,325,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +34205,5655,Male,disloyal Customer,20,Business travel,Business,436,4,0,5,3,2,5,2,2,3,3,5,5,5,2,0,0.0,satisfied +34206,62966,Male,Loyal Customer,39,Business travel,Business,862,5,5,5,5,4,5,5,5,5,5,5,5,5,5,14,15.0,satisfied +34207,7615,Female,Loyal Customer,58,Personal Travel,Eco,802,2,5,2,3,4,5,2,5,5,2,2,4,5,1,0,0.0,neutral or dissatisfied +34208,125399,Female,Loyal Customer,69,Personal Travel,Eco,1440,3,1,3,3,1,4,4,2,2,3,5,1,2,1,107,96.0,neutral or dissatisfied +34209,32511,Female,Loyal Customer,37,Business travel,Business,1689,0,3,0,2,1,3,4,1,1,1,1,1,1,5,0,0.0,satisfied +34210,39328,Male,Loyal Customer,75,Business travel,Eco Plus,67,3,3,3,3,3,3,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +34211,67963,Male,Loyal Customer,42,Business travel,Business,1438,1,1,5,1,4,4,4,4,4,4,4,5,4,5,8,26.0,satisfied +34212,79348,Female,Loyal Customer,11,Personal Travel,Eco,1029,4,4,4,3,3,4,3,3,4,2,3,4,4,3,0,0.0,satisfied +34213,68893,Male,Loyal Customer,47,Business travel,Eco,536,3,4,4,4,3,3,3,3,2,3,3,1,4,3,8,0.0,neutral or dissatisfied +34214,71780,Male,Loyal Customer,48,Business travel,Business,1744,3,3,3,3,3,3,4,4,4,4,4,5,4,5,23,18.0,satisfied +34215,54442,Female,Loyal Customer,13,Personal Travel,Eco Plus,305,3,4,3,1,5,3,5,5,3,3,5,5,5,5,14,7.0,neutral or dissatisfied +34216,41775,Male,Loyal Customer,33,Personal Travel,Eco,872,3,4,3,2,3,3,3,3,2,3,4,1,3,3,50,56.0,neutral or dissatisfied +34217,37534,Male,disloyal Customer,47,Business travel,Eco,944,2,2,2,3,5,2,5,5,1,1,3,4,3,5,0,0.0,neutral or dissatisfied +34218,93606,Male,Loyal Customer,58,Business travel,Business,2364,2,2,2,2,4,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +34219,24960,Female,Loyal Customer,39,Business travel,Eco,226,4,2,2,2,4,4,4,4,4,1,5,4,1,4,0,0.0,satisfied +34220,122817,Female,Loyal Customer,52,Personal Travel,Eco,599,1,2,1,3,4,4,3,1,1,1,1,2,1,3,4,0.0,neutral or dissatisfied +34221,97124,Female,Loyal Customer,30,Business travel,Business,1129,2,5,5,5,2,2,2,2,3,1,3,1,3,2,13,13.0,neutral or dissatisfied +34222,5058,Male,Loyal Customer,57,Business travel,Business,3929,3,5,1,5,1,4,4,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +34223,66402,Male,Loyal Customer,42,Business travel,Business,1562,2,2,3,2,4,5,4,5,5,5,5,4,5,4,7,49.0,satisfied +34224,108759,Female,Loyal Customer,44,Business travel,Business,1582,1,1,1,1,2,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +34225,92187,Male,Loyal Customer,63,Business travel,Eco,1979,3,4,4,4,4,3,4,4,4,2,2,1,3,4,55,28.0,neutral or dissatisfied +34226,42206,Male,Loyal Customer,54,Business travel,Eco,784,3,3,3,3,3,3,3,3,3,2,5,1,1,3,0,0.0,satisfied +34227,38705,Female,Loyal Customer,31,Business travel,Business,2342,3,5,5,5,3,3,3,3,4,3,2,3,3,3,23,9.0,neutral or dissatisfied +34228,69221,Female,Loyal Customer,54,Business travel,Business,2775,1,1,1,1,4,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +34229,71824,Female,Loyal Customer,25,Business travel,Business,1744,3,4,4,4,3,3,3,3,2,4,3,2,2,3,1,15.0,neutral or dissatisfied +34230,12166,Female,Loyal Customer,14,Business travel,Business,3588,1,2,2,2,1,1,1,1,4,1,3,3,3,1,32,9.0,neutral or dissatisfied +34231,75577,Male,Loyal Customer,60,Business travel,Business,1966,1,4,4,4,4,3,3,1,1,1,1,1,1,2,20,10.0,neutral or dissatisfied +34232,43813,Female,Loyal Customer,60,Business travel,Business,2773,4,4,4,4,3,5,4,5,5,5,4,5,5,4,0,4.0,satisfied +34233,72631,Male,Loyal Customer,20,Personal Travel,Eco,929,4,3,4,4,2,4,2,2,2,1,4,1,3,2,0,2.0,neutral or dissatisfied +34234,18534,Male,Loyal Customer,47,Business travel,Business,1807,1,2,2,2,1,4,3,1,1,1,1,3,1,4,65,66.0,neutral or dissatisfied +34235,47528,Female,Loyal Customer,11,Personal Travel,Eco,558,2,5,2,3,2,2,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +34236,128515,Male,Loyal Customer,60,Personal Travel,Eco,647,1,3,0,2,4,0,4,4,2,4,1,1,1,4,0,0.0,neutral or dissatisfied +34237,86948,Male,disloyal Customer,38,Business travel,Business,907,4,4,4,1,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +34238,14555,Male,Loyal Customer,45,Personal Travel,Eco,288,1,5,1,1,5,1,1,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +34239,125469,Female,Loyal Customer,67,Personal Travel,Eco,2845,1,0,1,3,5,2,1,1,1,1,4,1,1,5,0,0.0,neutral or dissatisfied +34240,33225,Male,Loyal Customer,49,Business travel,Eco Plus,101,3,2,2,2,3,3,3,3,3,4,3,2,4,3,0,16.0,neutral or dissatisfied +34241,66643,Female,Loyal Customer,53,Business travel,Business,2467,5,5,4,5,4,5,5,3,3,4,3,5,3,4,4,4.0,satisfied +34242,2467,Female,Loyal Customer,40,Personal Travel,Eco,674,2,2,2,3,2,2,2,2,1,4,3,2,3,2,0,21.0,neutral or dissatisfied +34243,31466,Male,disloyal Customer,48,Business travel,Eco,862,3,2,2,4,2,2,2,2,5,2,3,3,5,2,0,13.0,neutral or dissatisfied +34244,108876,Male,Loyal Customer,48,Business travel,Eco,1587,2,2,2,2,2,2,2,2,4,2,2,1,4,2,12,23.0,neutral or dissatisfied +34245,49051,Male,Loyal Customer,25,Business travel,Eco,109,3,3,3,3,3,4,5,3,1,1,1,1,2,3,0,11.0,satisfied +34246,35401,Female,Loyal Customer,53,Business travel,Business,428,4,4,4,4,2,1,4,4,4,4,4,5,4,1,10,20.0,satisfied +34247,7438,Female,Loyal Customer,55,Personal Travel,Eco,522,1,4,3,1,5,4,5,4,4,3,4,5,4,4,26,70.0,neutral or dissatisfied +34248,89828,Female,Loyal Customer,61,Personal Travel,Eco Plus,950,3,0,3,2,4,5,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +34249,6084,Female,disloyal Customer,40,Business travel,Business,672,4,4,4,5,5,4,1,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +34250,126392,Male,Loyal Customer,61,Personal Travel,Eco,468,1,4,1,3,2,1,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +34251,52864,Male,Loyal Customer,36,Business travel,Business,3206,3,3,3,3,1,4,5,5,5,5,5,1,5,2,1,5.0,satisfied +34252,91131,Female,Loyal Customer,33,Personal Travel,Eco,444,4,2,4,3,4,4,4,4,1,3,3,1,3,4,2,15.0,neutral or dissatisfied +34253,62500,Male,Loyal Customer,52,Business travel,Eco,1744,3,4,5,5,3,3,3,3,3,2,2,2,4,3,8,9.0,neutral or dissatisfied +34254,63139,Male,Loyal Customer,46,Personal Travel,Business,372,5,4,5,5,4,5,5,1,1,5,1,4,1,4,0,0.0,satisfied +34255,52842,Male,disloyal Customer,16,Business travel,Eco,737,2,2,2,1,4,2,4,4,4,4,3,4,4,4,11,0.0,neutral or dissatisfied +34256,6014,Female,disloyal Customer,50,Business travel,Eco,672,1,1,1,3,1,1,1,1,1,4,3,1,3,1,0,17.0,neutral or dissatisfied +34257,92558,Male,Loyal Customer,20,Personal Travel,Eco,1947,3,4,3,4,5,3,4,5,5,2,3,3,4,5,4,0.0,neutral or dissatisfied +34258,19968,Male,Loyal Customer,43,Business travel,Business,2135,1,4,4,4,4,4,4,1,1,1,1,4,1,4,1,0.0,neutral or dissatisfied +34259,122440,Female,Loyal Customer,64,Personal Travel,Eco Plus,1916,4,4,4,2,5,5,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +34260,16548,Male,disloyal Customer,46,Business travel,Business,1092,3,3,3,3,5,3,5,5,4,5,5,5,5,5,24,17.0,neutral or dissatisfied +34261,55935,Male,Loyal Customer,39,Business travel,Business,1906,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +34262,67247,Female,Loyal Customer,26,Personal Travel,Eco,918,3,4,4,1,5,4,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +34263,39710,Male,disloyal Customer,54,Business travel,Eco,205,2,0,2,1,3,2,3,3,2,4,4,1,1,3,1,11.0,neutral or dissatisfied +34264,28222,Female,Loyal Customer,35,Personal Travel,Eco Plus,834,1,4,1,2,4,1,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +34265,66868,Female,Loyal Customer,52,Business travel,Business,1915,5,3,5,5,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +34266,102816,Female,disloyal Customer,30,Business travel,Eco,342,3,0,3,5,3,3,3,3,2,5,2,4,2,3,0,5.0,neutral or dissatisfied +34267,71580,Female,Loyal Customer,30,Business travel,Business,3942,4,4,4,4,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +34268,52150,Female,Loyal Customer,51,Business travel,Business,3513,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +34269,22622,Female,Loyal Customer,55,Personal Travel,Eco,223,1,5,0,3,4,4,5,4,4,0,4,5,4,4,0,0.0,neutral or dissatisfied +34270,67766,Male,Loyal Customer,53,Business travel,Business,3119,2,2,4,2,2,5,5,1,1,2,1,5,1,4,0,0.0,satisfied +34271,110383,Female,Loyal Customer,52,Business travel,Business,3164,5,5,5,5,2,5,5,2,2,2,2,4,2,3,12,4.0,satisfied +34272,103619,Female,Loyal Customer,43,Business travel,Business,3241,5,5,5,5,5,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +34273,69043,Male,Loyal Customer,39,Business travel,Business,1389,4,4,4,4,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +34274,37014,Female,Loyal Customer,44,Personal Travel,Eco,805,4,2,4,4,1,4,3,1,1,4,1,3,1,1,15,16.0,neutral or dissatisfied +34275,108632,Female,Loyal Customer,44,Business travel,Business,3665,3,5,3,3,1,2,3,3,3,2,3,4,3,4,0,0.0,satisfied +34276,105205,Female,Loyal Customer,35,Business travel,Business,1670,4,4,4,4,5,4,4,4,4,4,4,5,4,5,7,7.0,satisfied +34277,50445,Male,disloyal Customer,22,Business travel,Eco,337,0,0,0,1,3,0,3,3,5,4,1,1,1,3,18,33.0,satisfied +34278,120246,Male,Loyal Customer,33,Personal Travel,Eco,1303,4,5,4,1,5,4,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +34279,63017,Female,Loyal Customer,38,Business travel,Business,2349,3,4,4,4,3,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +34280,6587,Male,Loyal Customer,65,Personal Travel,Eco,473,5,5,5,3,1,5,1,1,4,4,5,3,2,1,0,0.0,satisfied +34281,29183,Male,Loyal Customer,54,Business travel,Eco Plus,271,5,1,4,1,5,5,5,5,3,3,2,5,3,5,0,0.0,satisfied +34282,85705,Male,Loyal Customer,39,Personal Travel,Eco,1547,2,4,2,4,4,2,4,4,4,4,5,5,5,4,2,6.0,neutral or dissatisfied +34283,60649,Male,Loyal Customer,22,Business travel,Business,1620,4,3,4,3,4,4,4,4,2,4,2,1,4,4,43,31.0,neutral or dissatisfied +34284,84498,Male,Loyal Customer,15,Personal Travel,Eco,4502,4,2,4,2,4,5,5,4,2,1,1,5,1,5,0,0.0,satisfied +34285,102711,Male,Loyal Customer,53,Business travel,Business,365,2,2,2,2,4,2,1,4,4,5,4,2,4,2,44,29.0,satisfied +34286,82376,Female,disloyal Customer,42,Business travel,Eco,814,2,2,2,4,1,2,1,1,3,1,2,4,3,1,5,12.0,neutral or dissatisfied +34287,78739,Male,Loyal Customer,59,Business travel,Business,3485,4,4,4,4,3,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +34288,73093,Female,Loyal Customer,47,Business travel,Business,1928,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +34289,104599,Male,Loyal Customer,20,Personal Travel,Eco,369,3,5,3,4,3,3,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +34290,93437,Female,Loyal Customer,52,Business travel,Eco,205,5,2,2,2,3,3,2,5,5,5,5,4,5,5,86,92.0,satisfied +34291,668,Female,Loyal Customer,46,Business travel,Business,89,0,5,0,4,5,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +34292,52381,Female,Loyal Customer,46,Personal Travel,Eco,455,2,4,2,1,2,4,5,3,3,2,3,5,3,4,5,2.0,neutral or dissatisfied +34293,84893,Male,Loyal Customer,39,Personal Travel,Eco,534,4,5,4,3,3,4,3,3,5,4,5,4,4,3,23,20.0,satisfied +34294,33214,Female,Loyal Customer,55,Business travel,Eco Plus,102,2,2,5,2,5,4,2,2,2,2,2,2,2,3,0,0.0,satisfied +34295,63463,Female,disloyal Customer,33,Business travel,Business,337,2,2,2,3,1,2,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +34296,46656,Male,disloyal Customer,29,Business travel,Eco,73,3,4,3,4,3,3,3,3,2,3,4,1,3,3,0,2.0,neutral or dissatisfied +34297,76437,Female,Loyal Customer,68,Personal Travel,Eco,405,4,2,4,3,5,2,2,1,1,4,1,1,1,4,0,0.0,neutral or dissatisfied +34298,70396,Female,Loyal Customer,48,Business travel,Business,2410,2,1,1,1,2,4,4,2,2,2,2,2,2,2,4,11.0,neutral or dissatisfied +34299,44622,Male,Loyal Customer,50,Business travel,Business,3758,1,1,1,1,4,4,4,5,5,5,4,5,5,3,23,14.0,satisfied +34300,79850,Male,Loyal Customer,60,Business travel,Business,1047,5,5,5,5,5,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +34301,29302,Female,disloyal Customer,25,Business travel,Eco,569,4,2,5,4,3,5,3,3,2,4,4,4,3,3,1,0.0,neutral or dissatisfied +34302,847,Male,Loyal Customer,48,Business travel,Business,134,3,3,2,3,2,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +34303,28530,Male,disloyal Customer,24,Business travel,Eco,719,1,1,1,4,2,1,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +34304,3540,Female,disloyal Customer,36,Business travel,Business,227,3,2,2,5,1,2,1,1,5,3,4,5,4,1,34,40.0,neutral or dissatisfied +34305,107033,Male,Loyal Customer,55,Business travel,Business,2530,5,5,5,5,3,5,4,4,4,4,4,4,4,4,29,45.0,satisfied +34306,127081,Male,Loyal Customer,22,Business travel,Business,338,4,4,4,4,4,3,4,4,3,2,3,3,4,4,3,3.0,neutral or dissatisfied +34307,114165,Male,disloyal Customer,24,Business travel,Business,948,4,4,4,2,2,4,2,2,5,3,4,4,5,2,23,13.0,satisfied +34308,40603,Female,Loyal Customer,12,Personal Travel,Eco,216,1,0,1,5,1,1,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +34309,113515,Male,disloyal Customer,26,Business travel,Eco,397,1,1,1,3,5,1,3,5,2,3,2,2,2,5,30,23.0,neutral or dissatisfied +34310,31567,Male,disloyal Customer,36,Business travel,Eco Plus,453,1,1,1,3,2,1,2,2,1,1,3,4,4,2,13,11.0,neutral or dissatisfied +34311,64452,Female,Loyal Customer,21,Personal Travel,Eco,989,1,5,1,1,1,5,5,4,2,5,5,5,4,5,255,258.0,neutral or dissatisfied +34312,32353,Male,disloyal Customer,20,Business travel,Eco,102,2,0,2,1,4,2,1,4,4,2,1,4,5,4,3,5.0,neutral or dissatisfied +34313,78750,Female,Loyal Customer,60,Business travel,Business,3231,3,5,5,5,4,4,4,3,3,3,3,3,3,1,29,23.0,neutral or dissatisfied +34314,11776,Male,Loyal Customer,10,Personal Travel,Eco,395,3,5,3,5,5,3,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +34315,77967,Male,Loyal Customer,47,Business travel,Business,2952,3,2,3,3,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +34316,45888,Female,Loyal Customer,31,Business travel,Business,913,4,1,1,1,4,4,4,4,2,2,3,2,4,4,128,114.0,neutral or dissatisfied +34317,121891,Male,Loyal Customer,7,Personal Travel,Eco,366,3,3,3,4,2,3,2,2,2,3,3,4,4,2,98,81.0,neutral or dissatisfied +34318,51146,Male,Loyal Customer,56,Personal Travel,Eco,110,3,1,3,3,5,3,5,5,3,3,4,2,4,5,0,0.0,neutral or dissatisfied +34319,19297,Male,Loyal Customer,46,Business travel,Eco,299,1,5,5,5,1,1,1,1,2,2,2,4,3,1,0,0.0,neutral or dissatisfied +34320,108462,Female,Loyal Customer,68,Personal Travel,Eco,1440,2,5,2,4,4,4,4,4,4,2,2,5,4,3,0,0.0,neutral or dissatisfied +34321,87750,Male,disloyal Customer,50,Business travel,Business,214,4,4,4,4,3,4,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +34322,103956,Male,Loyal Customer,21,Personal Travel,Eco,533,2,5,2,4,5,2,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +34323,103304,Female,Loyal Customer,18,Business travel,Business,1371,4,4,4,4,4,4,4,4,5,4,4,4,4,4,8,12.0,satisfied +34324,84459,Female,Loyal Customer,17,Personal Travel,Eco,290,2,5,2,4,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +34325,38507,Female,Loyal Customer,23,Business travel,Business,2576,2,5,2,2,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +34326,108431,Male,Loyal Customer,50,Business travel,Business,1444,3,3,3,3,2,4,5,4,4,4,4,5,4,4,25,8.0,satisfied +34327,3747,Male,Loyal Customer,42,Business travel,Eco Plus,431,3,3,5,5,3,3,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +34328,112173,Female,Loyal Customer,33,Personal Travel,Eco,895,3,5,3,3,1,3,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +34329,86065,Male,Loyal Customer,80,Business travel,Eco Plus,432,2,4,4,4,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +34330,53172,Male,Loyal Customer,39,Business travel,Business,612,5,5,5,5,4,1,3,5,5,5,5,3,5,4,0,3.0,satisfied +34331,38725,Female,Loyal Customer,49,Business travel,Business,3391,4,2,2,2,4,1,2,4,4,4,4,2,4,1,24,23.0,neutral or dissatisfied +34332,113581,Female,Loyal Customer,40,Business travel,Business,1941,3,2,2,2,2,3,4,3,3,3,3,4,3,1,21,3.0,neutral or dissatisfied +34333,3166,Male,disloyal Customer,24,Business travel,Business,585,5,5,5,4,5,5,5,5,4,4,5,3,5,5,61,64.0,satisfied +34334,83293,Male,Loyal Customer,41,Personal Travel,Eco,1979,3,1,3,4,5,3,5,5,3,5,3,1,4,5,0,4.0,neutral or dissatisfied +34335,111979,Female,Loyal Customer,50,Personal Travel,Eco,770,3,4,3,4,5,5,5,5,5,3,5,5,5,3,50,38.0,neutral or dissatisfied +34336,109774,Male,Loyal Customer,55,Business travel,Business,1011,3,2,2,2,5,3,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +34337,54800,Male,Loyal Customer,52,Business travel,Business,3256,5,5,5,5,4,1,4,4,4,4,4,2,4,3,0,0.0,satisfied +34338,24292,Female,Loyal Customer,35,Personal Travel,Eco,302,1,4,5,3,4,5,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +34339,94056,Male,Loyal Customer,27,Business travel,Business,239,0,0,0,1,5,5,5,5,3,2,4,4,4,5,29,23.0,satisfied +34340,66166,Male,Loyal Customer,54,Business travel,Business,2243,5,5,5,5,4,5,5,3,3,4,3,4,3,5,7,0.0,satisfied +34341,87644,Male,Loyal Customer,43,Business travel,Business,2815,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,7.0,satisfied +34342,106216,Male,Loyal Customer,40,Business travel,Business,471,5,5,5,5,3,4,4,5,5,5,5,4,5,4,16,6.0,satisfied +34343,29067,Female,Loyal Customer,66,Personal Travel,Eco,679,3,2,3,3,3,5,5,2,2,3,3,5,2,5,171,172.0,neutral or dissatisfied +34344,71849,Female,Loyal Customer,24,Business travel,Business,1829,3,1,5,5,3,3,3,3,3,5,2,3,4,3,56,56.0,neutral or dissatisfied +34345,72714,Female,Loyal Customer,29,Business travel,Business,2408,5,5,5,5,5,5,5,5,4,5,4,5,4,5,4,9.0,satisfied +34346,32662,Female,disloyal Customer,23,Business travel,Eco,216,1,0,1,3,1,1,1,1,1,2,2,4,3,1,0,2.0,neutral or dissatisfied +34347,128765,Female,disloyal Customer,39,Business travel,Business,550,3,3,3,3,2,3,2,2,5,4,4,3,4,2,6,1.0,neutral or dissatisfied +34348,123599,Female,Loyal Customer,44,Personal Travel,Eco,1773,4,3,4,4,1,3,3,4,4,4,4,4,4,1,14,0.0,neutral or dissatisfied +34349,84979,Male,disloyal Customer,34,Business travel,Business,1590,1,1,1,3,1,1,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +34350,95409,Female,Loyal Customer,62,Personal Travel,Eco,187,3,5,3,2,4,5,4,3,3,3,2,5,3,3,0,0.0,neutral or dissatisfied +34351,3510,Male,Loyal Customer,56,Personal Travel,Eco,968,3,4,3,1,5,3,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +34352,114422,Male,Loyal Customer,43,Business travel,Business,3837,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +34353,21233,Male,Loyal Customer,15,Personal Travel,Eco,192,2,4,2,2,3,2,3,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +34354,2348,Male,Loyal Customer,28,Personal Travel,Eco Plus,690,4,5,4,2,4,4,3,4,3,2,4,5,4,4,13,14.0,neutral or dissatisfied +34355,21795,Female,disloyal Customer,48,Business travel,Eco,241,1,4,1,3,2,1,4,2,1,2,3,1,4,2,0,8.0,neutral or dissatisfied +34356,28425,Male,Loyal Customer,12,Personal Travel,Eco,1399,1,4,1,4,1,1,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +34357,105246,Female,Loyal Customer,33,Personal Travel,Eco Plus,377,1,5,1,3,3,1,3,3,5,4,5,4,4,3,32,17.0,neutral or dissatisfied +34358,14766,Male,Loyal Customer,29,Personal Travel,Eco,463,2,4,2,5,2,2,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +34359,86213,Female,Loyal Customer,65,Business travel,Eco,356,3,3,3,3,1,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +34360,111150,Male,Loyal Customer,27,Personal Travel,Eco,1050,3,4,3,2,3,3,1,3,3,2,4,3,5,3,122,93.0,neutral or dissatisfied +34361,41873,Female,Loyal Customer,16,Personal Travel,Eco Plus,483,3,3,2,4,4,2,4,4,3,3,3,4,4,4,0,0.0,neutral or dissatisfied +34362,117100,Male,Loyal Customer,65,Business travel,Business,1578,2,2,2,2,4,4,4,2,2,2,2,1,2,4,41,43.0,neutral or dissatisfied +34363,91712,Male,Loyal Customer,57,Business travel,Business,590,3,3,5,3,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +34364,45979,Female,Loyal Customer,32,Business travel,Business,1724,1,1,1,1,5,5,5,5,3,2,1,1,2,5,47,51.0,satisfied +34365,106413,Male,Loyal Customer,59,Personal Travel,Eco,674,3,4,3,3,5,3,5,5,5,5,5,3,4,5,25,26.0,neutral or dissatisfied +34366,22841,Male,Loyal Customer,61,Personal Travel,Eco,302,0,4,0,1,5,0,4,5,4,3,3,5,5,5,7,0.0,satisfied +34367,62053,Male,Loyal Customer,8,Personal Travel,Eco,2475,2,1,3,3,1,3,1,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +34368,54805,Female,disloyal Customer,25,Business travel,Eco,775,2,2,2,3,2,2,2,2,1,1,3,3,2,2,0,0.0,neutral or dissatisfied +34369,124361,Male,disloyal Customer,45,Business travel,Business,808,4,4,4,4,1,4,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +34370,128141,Female,disloyal Customer,19,Business travel,Business,1788,1,1,1,3,3,1,3,3,4,3,4,1,4,3,2,0.0,neutral or dissatisfied +34371,27265,Female,Loyal Customer,38,Business travel,Business,1637,2,2,2,2,5,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +34372,94234,Male,disloyal Customer,37,Business travel,Business,293,2,2,2,5,3,2,3,3,3,3,5,4,4,3,63,57.0,neutral or dissatisfied +34373,1510,Female,disloyal Customer,22,Business travel,Business,922,5,4,5,2,1,5,1,1,5,3,5,3,4,1,0,0.0,satisfied +34374,123351,Male,Loyal Customer,47,Business travel,Business,2854,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +34375,8047,Female,disloyal Customer,22,Business travel,Business,530,4,5,4,1,2,4,3,2,3,5,5,5,5,2,23,17.0,satisfied +34376,60989,Male,Loyal Customer,36,Personal Travel,Eco Plus,888,3,1,3,4,1,3,1,1,2,5,3,4,4,1,0,5.0,neutral or dissatisfied +34377,90832,Female,Loyal Customer,51,Business travel,Business,250,2,2,2,2,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +34378,31070,Female,Loyal Customer,24,Personal Travel,Eco,641,3,5,2,1,4,2,1,4,4,1,3,2,3,4,0,0.0,neutral or dissatisfied +34379,18440,Male,Loyal Customer,54,Business travel,Business,3648,3,3,3,3,5,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +34380,1163,Male,Loyal Customer,68,Personal Travel,Eco,89,4,5,0,3,2,0,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +34381,41332,Female,disloyal Customer,28,Business travel,Eco,689,1,1,1,3,1,2,2,2,1,3,3,2,3,2,139,140.0,neutral or dissatisfied +34382,25132,Female,Loyal Customer,44,Business travel,Eco,1249,5,1,1,1,5,5,1,5,5,5,5,1,5,2,0,0.0,satisfied +34383,9303,Male,Loyal Customer,60,Business travel,Business,3592,2,3,3,3,5,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +34384,47486,Female,Loyal Customer,13,Personal Travel,Eco,590,4,4,4,1,3,4,3,3,5,5,5,5,5,3,38,22.0,neutral or dissatisfied +34385,115741,Male,Loyal Customer,42,Business travel,Business,3529,1,4,4,4,2,3,4,1,1,1,1,3,1,3,19,8.0,neutral or dissatisfied +34386,84322,Male,Loyal Customer,18,Personal Travel,Business,606,3,4,3,1,4,3,4,4,5,3,4,5,4,4,15,5.0,neutral or dissatisfied +34387,67999,Female,Loyal Customer,60,Business travel,Business,1675,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +34388,17600,Male,Loyal Customer,30,Business travel,Eco Plus,695,4,3,3,3,4,4,4,4,3,1,1,2,2,4,80,65.0,satisfied +34389,10811,Male,Loyal Customer,39,Business travel,Business,3184,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +34390,31795,Male,disloyal Customer,22,Business travel,Eco,1353,3,3,3,4,3,1,1,4,2,4,3,1,3,1,114,86.0,neutral or dissatisfied +34391,71748,Female,Loyal Customer,39,Business travel,Business,1846,1,1,1,1,3,5,4,5,5,4,5,5,5,4,3,20.0,satisfied +34392,26830,Female,Loyal Customer,48,Business travel,Eco,224,5,1,1,1,4,1,1,5,5,5,5,2,5,4,94,92.0,satisfied +34393,62882,Female,disloyal Customer,25,Business travel,Business,2583,5,0,5,3,5,5,2,5,5,3,5,5,4,5,5,0.0,satisfied +34394,127139,Female,Loyal Customer,49,Personal Travel,Eco,651,3,4,3,3,2,5,5,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +34395,19137,Male,Loyal Customer,38,Business travel,Eco Plus,287,3,3,2,2,3,3,3,3,4,5,4,2,4,3,10,18.0,neutral or dissatisfied +34396,32677,Male,Loyal Customer,37,Business travel,Eco,84,5,3,3,3,5,5,5,5,5,1,2,4,2,5,0,0.0,satisfied +34397,127006,Female,Loyal Customer,41,Business travel,Business,2100,5,5,5,5,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +34398,110845,Male,Loyal Customer,45,Business travel,Business,2654,2,2,4,2,2,4,5,5,5,5,5,5,5,4,16,14.0,satisfied +34399,5949,Male,Loyal Customer,57,Personal Travel,Eco,642,3,4,3,3,5,3,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +34400,60792,Female,disloyal Customer,50,Business travel,Business,472,3,3,3,4,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +34401,67942,Female,Loyal Customer,13,Personal Travel,Eco,1171,3,5,3,4,3,3,3,3,4,3,4,3,4,3,18,15.0,neutral or dissatisfied +34402,79805,Female,Loyal Customer,39,Business travel,Business,1035,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +34403,66504,Female,Loyal Customer,41,Business travel,Business,3623,5,5,5,5,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +34404,17015,Male,disloyal Customer,39,Business travel,Eco,781,4,4,4,4,3,4,3,3,4,4,3,3,4,3,0,4.0,neutral or dissatisfied +34405,34422,Male,Loyal Customer,37,Business travel,Eco Plus,212,5,4,4,4,5,5,5,5,1,1,4,5,4,5,0,0.0,satisfied +34406,24466,Female,Loyal Customer,38,Business travel,Business,516,2,2,2,2,2,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +34407,129065,Female,Loyal Customer,40,Personal Travel,Eco,1846,2,3,2,4,4,2,1,4,4,4,4,4,4,4,2,36.0,neutral or dissatisfied +34408,101666,Female,Loyal Customer,16,Business travel,Business,2106,2,3,5,3,2,2,2,2,1,3,3,3,3,2,0,14.0,neutral or dissatisfied +34409,55524,Female,Loyal Customer,46,Business travel,Business,2593,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +34410,65903,Female,Loyal Customer,42,Business travel,Business,3654,5,5,4,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +34411,93481,Male,Loyal Customer,55,Business travel,Business,1107,2,2,2,2,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +34412,35180,Female,disloyal Customer,23,Business travel,Eco,1056,1,1,1,5,5,1,5,5,3,4,4,1,3,5,0,0.0,neutral or dissatisfied +34413,98093,Female,Loyal Customer,66,Personal Travel,Eco,845,3,2,3,4,4,4,4,5,5,3,5,3,5,4,34,42.0,neutral or dissatisfied +34414,113303,Female,Loyal Customer,52,Business travel,Business,1547,4,4,4,4,5,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +34415,46324,Female,Loyal Customer,47,Business travel,Business,420,2,1,3,3,2,2,2,2,2,2,2,4,2,2,3,40.0,neutral or dissatisfied +34416,86877,Male,disloyal Customer,28,Business travel,Eco Plus,692,4,5,5,3,1,5,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +34417,32475,Female,Loyal Customer,54,Business travel,Business,3341,0,4,1,4,1,1,3,5,5,5,5,1,5,3,7,11.0,satisfied +34418,14300,Male,disloyal Customer,20,Business travel,Eco,395,2,4,2,3,3,2,3,3,1,4,4,4,3,3,0,0.0,neutral or dissatisfied +34419,129350,Female,Loyal Customer,36,Personal Travel,Eco,2475,2,4,2,3,5,2,5,5,3,1,4,1,3,5,0,9.0,neutral or dissatisfied +34420,94260,Male,Loyal Customer,59,Business travel,Business,192,4,4,3,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +34421,8939,Male,Loyal Customer,41,Business travel,Business,2587,5,5,4,5,5,5,5,5,5,5,5,5,5,3,0,2.0,satisfied +34422,60100,Male,Loyal Customer,24,Business travel,Business,2053,2,5,5,5,2,2,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +34423,11441,Male,Loyal Customer,58,Business travel,Business,1569,3,4,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +34424,30817,Male,Loyal Customer,10,Business travel,Business,3375,5,5,5,5,4,4,4,4,2,3,4,3,3,4,0,0.0,satisfied +34425,54991,Male,Loyal Customer,58,Business travel,Business,2886,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,15.0,satisfied +34426,10707,Female,Loyal Customer,43,Business travel,Eco,309,1,2,2,2,2,4,4,1,1,1,1,2,1,3,0,3.0,neutral or dissatisfied +34427,48311,Male,Loyal Customer,23,Personal Travel,Eco,1499,0,4,0,2,2,0,2,2,4,5,5,3,5,2,6,0.0,satisfied +34428,27595,Female,Loyal Customer,31,Personal Travel,Eco,679,1,5,1,4,3,1,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +34429,115533,Female,Loyal Customer,42,Business travel,Business,1768,3,1,1,1,1,3,3,3,3,3,3,4,3,2,8,7.0,neutral or dissatisfied +34430,1583,Female,disloyal Customer,25,Business travel,Business,140,4,4,4,3,4,4,3,4,5,3,5,5,4,4,0,0.0,satisfied +34431,47576,Male,disloyal Customer,48,Business travel,Business,1482,5,5,5,2,2,5,2,2,3,3,5,3,4,2,121,125.0,satisfied +34432,1334,Male,Loyal Customer,45,Business travel,Business,270,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +34433,47041,Female,Loyal Customer,23,Business travel,Eco,639,3,5,5,5,3,3,1,3,2,1,3,4,2,3,0,0.0,neutral or dissatisfied +34434,32073,Female,Loyal Customer,56,Business travel,Eco,101,4,3,3,3,1,1,1,4,4,4,4,4,4,3,0,0.0,satisfied +34435,3907,Female,Loyal Customer,26,Personal Travel,Eco,213,4,4,4,3,3,4,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +34436,123432,Male,Loyal Customer,51,Business travel,Business,796,3,2,2,2,5,1,1,3,3,3,3,4,3,3,0,6.0,neutral or dissatisfied +34437,70057,Female,Loyal Customer,55,Personal Travel,Eco Plus,583,2,5,2,3,3,4,5,5,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +34438,129738,Male,Loyal Customer,42,Business travel,Business,2090,0,0,0,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +34439,74751,Female,Loyal Customer,14,Personal Travel,Eco,1171,3,4,4,3,4,4,4,5,4,5,5,4,4,4,230,229.0,neutral or dissatisfied +34440,16016,Male,Loyal Customer,7,Personal Travel,Eco,853,2,5,2,5,1,2,1,1,4,4,5,4,5,1,0,41.0,neutral or dissatisfied +34441,16274,Male,Loyal Customer,37,Personal Travel,Eco,748,3,4,3,3,4,3,4,4,1,1,4,4,3,4,100,90.0,neutral or dissatisfied +34442,3181,Male,disloyal Customer,24,Business travel,Eco,585,2,4,2,3,3,2,5,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +34443,91197,Female,Loyal Customer,16,Personal Travel,Eco,646,3,5,3,3,5,3,4,5,4,1,1,3,5,5,0,0.0,neutral or dissatisfied +34444,22354,Female,Loyal Customer,31,Business travel,Business,3876,2,2,2,2,4,4,5,4,1,2,5,2,4,4,0,0.0,satisfied +34445,49148,Female,Loyal Customer,46,Business travel,Eco,89,5,1,1,1,2,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +34446,2812,Male,Loyal Customer,28,Business travel,Business,3178,2,1,1,1,2,2,2,2,4,2,3,2,3,2,0,11.0,neutral or dissatisfied +34447,24621,Female,Loyal Customer,68,Business travel,Eco,126,4,3,3,3,3,5,5,3,3,4,3,3,3,1,0,0.0,satisfied +34448,112023,Female,Loyal Customer,60,Business travel,Business,680,2,2,2,2,2,5,4,4,4,4,4,5,4,5,30,2.0,satisfied +34449,78983,Female,Loyal Customer,39,Business travel,Business,226,3,3,3,3,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +34450,77194,Male,Loyal Customer,35,Personal Travel,Eco,290,1,4,1,3,4,1,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +34451,66590,Male,Loyal Customer,42,Business travel,Business,761,3,3,3,3,5,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +34452,124635,Female,Loyal Customer,65,Personal Travel,Eco,1671,1,1,2,2,3,2,2,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +34453,30139,Male,Loyal Customer,26,Personal Travel,Eco,399,1,2,1,3,5,1,3,5,1,1,4,2,4,5,4,9.0,neutral or dissatisfied +34454,96164,Female,Loyal Customer,36,Business travel,Business,3042,1,1,1,1,2,5,4,5,5,5,5,4,5,3,9,3.0,satisfied +34455,13304,Female,Loyal Customer,25,Personal Travel,Eco Plus,468,1,2,1,3,1,1,1,1,4,2,3,3,4,1,21,30.0,neutral or dissatisfied +34456,88637,Male,Loyal Customer,68,Personal Travel,Eco,250,3,3,3,4,3,3,5,3,2,4,4,3,3,3,2,0.0,neutral or dissatisfied +34457,69308,Female,disloyal Customer,28,Business travel,Business,1096,2,2,2,3,2,2,2,2,5,2,5,5,5,2,15,0.0,neutral or dissatisfied +34458,63803,Male,Loyal Customer,28,Business travel,Business,2724,4,4,4,4,3,4,3,3,4,4,4,5,4,3,117,99.0,satisfied +34459,113991,Female,Loyal Customer,51,Business travel,Eco,1728,3,4,4,4,2,3,2,3,3,3,3,4,3,1,4,22.0,satisfied +34460,120316,Male,Loyal Customer,51,Business travel,Business,2025,3,5,5,5,3,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +34461,56286,Male,Loyal Customer,57,Business travel,Business,2227,2,2,2,2,4,3,4,5,5,5,5,4,5,5,2,0.0,satisfied +34462,14614,Male,Loyal Customer,53,Personal Travel,Eco,448,3,4,3,3,2,3,2,2,4,3,3,1,4,2,16,1.0,neutral or dissatisfied +34463,119388,Male,Loyal Customer,57,Business travel,Business,2610,3,3,3,3,4,4,5,4,4,5,4,5,4,5,8,4.0,satisfied +34464,128036,Female,Loyal Customer,59,Business travel,Business,1440,2,1,1,1,1,3,3,2,2,2,2,3,2,1,0,,neutral or dissatisfied +34465,111308,Female,disloyal Customer,27,Business travel,Business,283,0,0,0,3,3,0,2,3,4,4,5,3,5,3,0,5.0,satisfied +34466,118948,Female,disloyal Customer,19,Business travel,Eco,682,1,0,0,4,4,0,4,4,4,2,3,2,3,4,26,24.0,neutral or dissatisfied +34467,102115,Male,disloyal Customer,27,Business travel,Business,407,3,3,3,4,5,3,3,5,4,3,4,3,4,5,4,3.0,neutral or dissatisfied +34468,101003,Female,Loyal Customer,42,Business travel,Business,2545,3,3,3,3,5,4,5,3,3,2,3,3,3,3,0,5.0,satisfied +34469,73132,Female,Loyal Customer,23,Business travel,Business,1830,2,4,4,4,2,2,2,2,4,4,3,2,3,2,0,27.0,neutral or dissatisfied +34470,116053,Female,Loyal Customer,40,Personal Travel,Eco,480,1,5,1,2,3,1,3,3,3,5,5,4,1,3,17,12.0,neutral or dissatisfied +34471,37569,Male,disloyal Customer,37,Business travel,Eco,676,4,4,4,2,4,4,4,4,1,3,5,1,1,4,0,0.0,satisfied +34472,24844,Male,Loyal Customer,10,Personal Travel,Eco,894,4,1,4,4,2,4,2,2,1,2,3,3,3,2,0,13.0,neutral or dissatisfied +34473,120957,Male,disloyal Customer,25,Business travel,Eco,861,4,4,4,2,2,4,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +34474,20089,Male,Loyal Customer,42,Business travel,Business,3633,4,4,4,4,3,5,5,5,5,5,5,5,5,4,19,16.0,satisfied +34475,4488,Female,Loyal Customer,50,Business travel,Business,2411,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +34476,37652,Male,Loyal Customer,25,Personal Travel,Eco,944,3,5,3,3,4,3,4,4,3,5,2,3,5,4,4,0.0,neutral or dissatisfied +34477,117153,Female,Loyal Customer,9,Personal Travel,Eco,370,1,4,1,4,4,1,4,4,1,3,4,2,4,4,49,45.0,neutral or dissatisfied +34478,83448,Male,disloyal Customer,25,Business travel,Business,946,4,2,4,2,3,4,3,3,5,4,5,3,5,3,0,0.0,satisfied +34479,101552,Female,Loyal Customer,65,Personal Travel,Eco,345,2,2,2,3,2,3,3,5,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +34480,83626,Female,Loyal Customer,19,Personal Travel,Eco,409,2,5,2,3,4,2,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +34481,46911,Female,Loyal Customer,43,Business travel,Eco,819,5,4,4,4,4,3,5,5,5,5,5,4,5,2,0,0.0,satisfied +34482,39844,Female,disloyal Customer,20,Business travel,Eco,221,4,1,4,4,4,4,4,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +34483,30992,Male,disloyal Customer,27,Business travel,Eco,391,4,5,4,5,2,4,5,2,4,3,2,4,3,2,6,9.0,neutral or dissatisfied +34484,82821,Female,Loyal Customer,51,Personal Travel,Business,645,4,3,5,4,5,3,4,4,4,5,2,1,4,1,0,0.0,neutral or dissatisfied +34485,16799,Male,disloyal Customer,23,Business travel,Eco,1017,5,5,5,4,1,5,1,1,1,3,4,4,3,1,0,2.0,satisfied +34486,81182,Male,disloyal Customer,15,Business travel,Eco,980,5,5,5,5,4,5,4,4,4,2,4,3,4,4,0,0.0,satisfied +34487,124942,Female,Loyal Customer,61,Personal Travel,Eco,728,1,3,1,4,2,3,3,3,3,1,3,3,3,3,0,33.0,neutral or dissatisfied +34488,17543,Female,disloyal Customer,27,Business travel,Eco,908,2,2,2,3,2,2,2,2,4,2,2,3,2,2,49,31.0,neutral or dissatisfied +34489,27517,Male,Loyal Customer,68,Personal Travel,Eco,954,3,5,3,1,3,3,3,3,5,2,4,3,4,3,0,3.0,neutral or dissatisfied +34490,73241,Male,Loyal Customer,44,Personal Travel,Eco Plus,946,1,2,1,4,3,1,4,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +34491,32402,Male,disloyal Customer,23,Business travel,Business,216,5,0,5,5,2,0,2,2,1,1,1,4,2,2,0,0.0,satisfied +34492,79192,Female,disloyal Customer,27,Business travel,Business,1040,5,5,5,2,3,5,3,3,5,3,3,3,4,3,16,0.0,satisfied +34493,98916,Male,Loyal Customer,29,Business travel,Business,569,3,3,3,3,5,5,5,5,5,5,5,4,4,5,25,15.0,satisfied +34494,113362,Male,disloyal Customer,39,Business travel,Business,197,2,2,2,3,1,2,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +34495,89534,Male,Loyal Customer,40,Business travel,Business,2465,5,5,5,5,4,5,4,4,4,4,4,3,4,3,3,1.0,satisfied +34496,68394,Male,Loyal Customer,51,Business travel,Business,1045,4,4,4,4,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +34497,102372,Female,Loyal Customer,50,Business travel,Eco,236,5,2,2,2,1,3,2,5,5,5,5,3,5,1,9,16.0,satisfied +34498,79839,Male,Loyal Customer,41,Business travel,Business,1534,5,5,5,5,4,3,3,4,3,5,4,3,3,3,157,127.0,satisfied +34499,128811,Female,Loyal Customer,54,Business travel,Business,2586,1,1,2,1,4,4,4,5,4,3,5,4,5,4,4,4.0,satisfied +34500,99919,Female,Loyal Customer,50,Personal Travel,Business,764,2,5,2,1,2,2,2,5,2,5,5,2,5,2,150,134.0,neutral or dissatisfied +34501,69060,Female,Loyal Customer,57,Business travel,Eco,1389,3,3,2,3,1,4,3,3,3,3,3,2,3,1,0,4.0,neutral or dissatisfied +34502,32862,Male,Loyal Customer,13,Personal Travel,Eco,101,4,4,4,3,2,4,2,2,4,3,5,5,4,2,6,1.0,neutral or dissatisfied +34503,102979,Male,Loyal Customer,57,Business travel,Business,666,4,4,4,4,2,5,4,4,4,4,4,4,4,5,25,0.0,satisfied +34504,4598,Female,Loyal Customer,23,Personal Travel,Eco,416,2,4,2,1,1,2,1,1,3,1,5,5,5,1,0,8.0,neutral or dissatisfied +34505,97442,Male,Loyal Customer,8,Personal Travel,Eco,585,1,4,1,2,5,1,1,5,5,3,5,5,5,5,21,12.0,neutral or dissatisfied +34506,77280,Female,Loyal Customer,25,Business travel,Business,1931,1,1,1,1,1,1,1,1,4,5,4,1,3,1,2,0.0,neutral or dissatisfied +34507,93468,Female,disloyal Customer,23,Business travel,Eco,605,0,3,0,4,1,0,1,1,3,4,4,5,5,1,0,0.0,satisfied +34508,42698,Female,Loyal Customer,69,Personal Travel,Eco,604,2,4,2,3,2,4,4,5,5,2,5,3,5,5,23,64.0,neutral or dissatisfied +34509,63892,Male,Loyal Customer,43,Business travel,Eco,1172,2,4,4,4,2,2,2,2,4,4,1,3,2,2,0,6.0,neutral or dissatisfied +34510,105675,Male,Loyal Customer,51,Business travel,Business,925,3,3,3,3,4,4,4,4,4,5,4,4,5,4,157,182.0,satisfied +34511,104231,Female,Loyal Customer,11,Personal Travel,Eco,680,2,4,2,5,5,2,5,5,5,3,4,5,5,5,27,15.0,neutral or dissatisfied +34512,87330,Female,Loyal Customer,42,Business travel,Business,425,2,2,5,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +34513,19154,Male,Loyal Customer,38,Business travel,Eco,304,2,2,2,2,2,2,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +34514,57269,Male,disloyal Customer,25,Business travel,Eco,804,3,4,4,3,3,4,3,3,5,5,3,5,3,3,2,0.0,neutral or dissatisfied +34515,107069,Male,Loyal Customer,23,Personal Travel,Eco,480,4,5,4,4,3,4,3,3,1,1,1,4,4,3,43,17.0,neutral or dissatisfied +34516,70965,Male,Loyal Customer,49,Personal Travel,Business,802,3,2,3,4,3,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +34517,21849,Female,Loyal Customer,47,Personal Travel,Business,448,3,5,3,1,3,3,2,5,5,3,5,1,5,2,0,0.0,neutral or dissatisfied +34518,124549,Male,Loyal Customer,58,Personal Travel,Eco,1276,2,5,2,1,5,2,2,5,4,2,3,4,4,5,0,0.0,neutral or dissatisfied +34519,68798,Female,Loyal Customer,22,Personal Travel,Eco,861,1,3,1,4,2,1,4,2,4,2,3,3,4,2,0,4.0,neutral or dissatisfied +34520,109795,Male,Loyal Customer,60,Business travel,Business,3503,1,1,1,1,4,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +34521,114969,Male,Loyal Customer,49,Business travel,Business,3858,0,0,0,3,2,5,5,1,1,1,1,5,1,4,36,30.0,satisfied +34522,120517,Male,Loyal Customer,39,Business travel,Business,3869,4,4,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +34523,68863,Male,disloyal Customer,26,Business travel,Eco,936,2,2,2,4,4,2,4,4,2,1,4,2,3,4,88,82.0,neutral or dissatisfied +34524,84859,Male,disloyal Customer,16,Business travel,Eco,516,3,4,3,3,2,3,2,2,3,1,3,2,4,2,2,0.0,neutral or dissatisfied +34525,120212,Female,Loyal Customer,67,Business travel,Business,1303,3,2,4,2,3,3,3,3,3,3,3,4,3,1,77,60.0,neutral or dissatisfied +34526,121443,Female,Loyal Customer,29,Business travel,Business,1619,5,5,1,5,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +34527,67169,Male,Loyal Customer,10,Personal Travel,Eco,964,1,4,1,3,1,1,1,1,4,4,5,3,5,1,22,21.0,neutral or dissatisfied +34528,98829,Male,Loyal Customer,7,Personal Travel,Eco,763,2,4,2,3,4,2,4,4,2,2,5,3,1,4,0,0.0,neutral or dissatisfied +34529,81378,Female,Loyal Customer,57,Business travel,Business,874,4,4,5,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +34530,88560,Male,Loyal Customer,34,Personal Travel,Eco,404,2,5,2,4,1,2,1,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +34531,48547,Male,Loyal Customer,43,Personal Travel,Eco,819,2,2,3,2,5,3,5,5,1,5,2,3,2,5,0,0.0,neutral or dissatisfied +34532,65465,Female,Loyal Customer,50,Business travel,Eco,1303,1,2,3,3,4,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +34533,73820,Female,Loyal Customer,54,Business travel,Business,2600,4,4,2,4,5,5,5,2,2,2,2,3,2,4,0,5.0,satisfied +34534,74401,Female,Loyal Customer,27,Business travel,Business,1517,2,2,2,2,5,5,5,5,4,5,5,3,4,5,12,24.0,satisfied +34535,80465,Female,Loyal Customer,52,Business travel,Business,1299,2,2,5,2,4,4,5,5,5,5,5,5,5,5,10,1.0,satisfied +34536,89376,Female,Loyal Customer,42,Business travel,Business,151,3,3,5,3,5,4,4,4,4,4,5,3,4,5,43,48.0,satisfied +34537,62454,Female,Loyal Customer,47,Business travel,Business,1846,1,1,2,1,2,3,5,4,4,4,4,3,4,4,0,7.0,satisfied +34538,21623,Female,disloyal Customer,29,Business travel,Eco,780,3,3,3,3,1,3,1,1,3,4,4,2,3,1,78,77.0,neutral or dissatisfied +34539,126664,Male,disloyal Customer,30,Business travel,Eco Plus,602,2,2,2,3,5,2,5,5,4,4,2,1,3,5,81,84.0,neutral or dissatisfied +34540,123059,Female,Loyal Customer,24,Business travel,Eco,631,2,3,3,3,2,2,1,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +34541,30595,Female,Loyal Customer,40,Business travel,Eco,472,4,5,5,5,4,4,4,4,5,1,1,5,4,4,4,0.0,satisfied +34542,66914,Female,Loyal Customer,43,Business travel,Business,3137,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +34543,91541,Female,Loyal Customer,27,Business travel,Business,1961,4,4,4,4,5,5,5,5,3,3,5,3,5,5,52,39.0,satisfied +34544,43778,Male,Loyal Customer,12,Personal Travel,Eco,546,1,1,1,2,2,1,2,2,4,3,3,1,2,2,0,18.0,neutral or dissatisfied +34545,61797,Male,Loyal Customer,12,Personal Travel,Eco,1379,3,4,3,1,5,3,4,5,3,3,1,1,4,5,22,24.0,neutral or dissatisfied +34546,71881,Male,Loyal Customer,41,Personal Travel,Eco,1723,2,4,2,1,2,2,2,2,3,3,4,5,5,2,6,2.0,neutral or dissatisfied +34547,15338,Female,Loyal Customer,7,Personal Travel,Eco Plus,589,2,5,2,3,5,2,5,5,4,3,4,3,5,5,15,3.0,neutral or dissatisfied +34548,76782,Male,Loyal Customer,54,Business travel,Business,546,5,5,3,5,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +34549,60035,Male,Loyal Customer,50,Personal Travel,Eco,1065,1,5,1,5,5,1,2,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +34550,52526,Male,disloyal Customer,23,Business travel,Eco,119,2,4,2,4,3,2,3,3,5,5,1,1,3,3,0,0.0,neutral or dissatisfied +34551,43304,Female,disloyal Customer,32,Business travel,Eco,358,2,4,2,3,2,2,2,2,3,1,3,2,4,2,7,3.0,neutral or dissatisfied +34552,16221,Male,Loyal Customer,37,Business travel,Eco Plus,277,4,5,5,5,4,5,4,4,4,2,3,1,5,4,0,0.0,satisfied +34553,88108,Female,disloyal Customer,36,Business travel,Business,404,2,2,2,1,4,2,4,4,4,2,5,4,5,4,19,28.0,neutral or dissatisfied +34554,118715,Male,Loyal Customer,25,Personal Travel,Eco,647,1,5,1,4,3,1,3,3,1,4,3,3,2,3,31,25.0,neutral or dissatisfied +34555,18207,Male,Loyal Customer,55,Business travel,Eco,235,5,3,3,3,4,5,4,4,2,1,3,2,2,4,127,128.0,satisfied +34556,53490,Male,Loyal Customer,42,Personal Travel,Eco,2419,3,4,3,4,3,2,2,5,2,5,5,2,3,2,31,17.0,neutral or dissatisfied +34557,75531,Male,Loyal Customer,59,Business travel,Business,337,3,2,2,2,2,2,3,3,3,3,3,1,3,4,20,14.0,neutral or dissatisfied +34558,107943,Female,Loyal Customer,7,Personal Travel,Eco,611,1,4,1,1,2,1,2,2,1,1,1,5,2,2,18,9.0,neutral or dissatisfied +34559,123087,Female,Loyal Customer,58,Business travel,Business,2376,3,3,3,3,5,4,4,5,5,5,5,3,5,4,75,80.0,satisfied +34560,98561,Female,Loyal Customer,50,Personal Travel,Business,861,3,5,4,2,1,4,4,1,1,4,1,2,1,1,0,0.0,neutral or dissatisfied +34561,12157,Male,Loyal Customer,55,Business travel,Business,3724,3,3,3,3,5,2,4,5,5,5,5,4,5,4,0,0.0,satisfied +34562,60463,Male,Loyal Customer,31,Business travel,Eco,934,1,2,2,2,1,1,1,1,3,3,3,4,4,1,29,17.0,neutral or dissatisfied +34563,65540,Male,Loyal Customer,65,Business travel,Business,237,2,1,4,4,5,4,4,2,2,2,2,2,2,3,31,28.0,neutral or dissatisfied +34564,61103,Female,Loyal Customer,45,Personal Travel,Eco,1546,3,5,3,1,4,4,4,1,1,3,1,3,1,4,12,43.0,neutral or dissatisfied +34565,50980,Male,Loyal Customer,28,Personal Travel,Eco,109,2,5,2,4,3,2,5,3,5,1,3,3,4,3,0,0.0,neutral or dissatisfied +34566,73709,Male,disloyal Customer,39,Business travel,Business,204,2,2,2,4,4,2,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +34567,117522,Female,Loyal Customer,44,Business travel,Business,347,5,5,5,5,5,5,4,4,4,4,4,3,4,4,82,85.0,satisfied +34568,11985,Female,Loyal Customer,23,Personal Travel,Eco,643,2,5,2,5,5,2,5,5,3,4,5,5,5,5,0,22.0,neutral or dissatisfied +34569,67235,Female,Loyal Customer,7,Personal Travel,Eco,1119,2,1,2,4,1,2,1,1,2,3,4,4,4,1,0,19.0,neutral or dissatisfied +34570,100034,Female,Loyal Customer,57,Business travel,Business,2358,3,5,4,5,5,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +34571,54391,Female,Loyal Customer,78,Business travel,Business,2383,1,3,3,3,1,2,2,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +34572,67615,Male,Loyal Customer,59,Business travel,Business,1826,2,2,2,2,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +34573,63127,Male,Loyal Customer,54,Business travel,Business,2421,3,3,3,3,4,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +34574,45688,Female,Loyal Customer,26,Business travel,Business,2132,2,2,2,2,2,2,2,2,1,5,4,3,3,2,12,28.0,neutral or dissatisfied +34575,46047,Female,Loyal Customer,61,Business travel,Business,1657,2,2,2,2,1,5,5,5,5,5,5,4,5,1,5,45.0,satisfied +34576,25711,Male,Loyal Customer,38,Business travel,Eco,528,3,1,1,1,3,3,3,3,2,1,5,4,3,3,8,0.0,satisfied +34577,114079,Female,disloyal Customer,54,Business travel,Business,1947,3,4,4,4,3,3,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +34578,103201,Female,Loyal Customer,41,Business travel,Business,1482,1,1,5,1,4,5,5,5,5,5,5,4,5,5,44,29.0,satisfied +34579,12904,Male,disloyal Customer,38,Business travel,Eco,456,3,3,3,4,4,3,4,4,1,4,3,1,4,4,0,0.0,neutral or dissatisfied +34580,36492,Female,Loyal Customer,26,Business travel,Business,1121,1,1,1,1,5,5,5,5,1,3,2,5,4,5,19,1.0,satisfied +34581,77834,Female,Loyal Customer,28,Personal Travel,Eco,874,3,4,3,3,1,3,1,1,1,3,2,3,4,1,25,36.0,neutral or dissatisfied +34582,100366,Female,Loyal Customer,43,Personal Travel,Eco,971,3,4,3,4,3,5,4,3,3,3,4,5,3,3,0,0.0,neutral or dissatisfied +34583,105957,Female,Loyal Customer,44,Business travel,Business,2295,2,2,2,2,3,3,3,5,3,5,5,3,5,3,1,16.0,satisfied +34584,121316,Female,Loyal Customer,24,Personal Travel,Eco,1009,1,5,1,4,1,1,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +34585,9306,Male,Loyal Customer,51,Business travel,Business,419,4,4,4,4,4,4,4,3,2,4,4,4,3,4,203,268.0,satisfied +34586,30181,Female,Loyal Customer,35,Business travel,Eco Plus,253,3,3,3,3,3,2,3,3,5,1,2,1,1,3,19,17.0,satisfied +34587,87139,Male,Loyal Customer,52,Business travel,Eco Plus,594,1,5,5,5,1,1,1,1,1,1,3,3,4,1,35,23.0,neutral or dissatisfied +34588,19505,Male,Loyal Customer,40,Business travel,Eco,566,2,5,5,5,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +34589,105139,Male,Loyal Customer,58,Business travel,Eco,289,2,3,3,3,2,2,2,2,3,1,3,2,4,2,39,24.0,neutral or dissatisfied +34590,82985,Female,Loyal Customer,24,Business travel,Business,2206,2,2,2,2,4,4,4,4,4,4,5,4,4,4,1,0.0,satisfied +34591,19224,Male,Loyal Customer,10,Personal Travel,Eco,588,2,4,2,3,2,4,4,4,2,4,4,4,5,4,118,181.0,neutral or dissatisfied +34592,32886,Male,Loyal Customer,35,Personal Travel,Eco,101,4,5,0,3,5,0,5,5,4,3,3,4,2,5,0,0.0,neutral or dissatisfied +34593,60707,Female,Loyal Customer,18,Business travel,Business,1605,4,4,4,4,4,4,4,4,5,3,4,5,5,4,1,4.0,satisfied +34594,43782,Male,Loyal Customer,47,Personal Travel,Eco,481,4,1,2,4,2,2,2,2,2,3,3,3,4,2,0,0.0,satisfied +34595,112781,Female,Loyal Customer,41,Personal Travel,Eco,590,3,5,3,5,4,3,4,4,3,2,4,5,2,4,0,6.0,neutral or dissatisfied +34596,18239,Male,Loyal Customer,38,Business travel,Business,179,3,3,1,3,2,5,4,5,5,5,3,4,5,3,15,2.0,satisfied +34597,86449,Male,Loyal Customer,58,Business travel,Eco,749,3,3,3,3,3,3,3,3,2,1,4,3,4,3,7,0.0,neutral or dissatisfied +34598,116972,Male,Loyal Customer,41,Business travel,Business,2276,2,2,2,2,4,5,5,5,5,5,5,5,5,5,54,43.0,satisfied +34599,87726,Female,Loyal Customer,68,Personal Travel,Eco Plus,591,4,3,4,4,4,4,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +34600,86128,Male,disloyal Customer,25,Business travel,Business,356,4,5,4,3,2,4,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +34601,5172,Male,Loyal Customer,28,Business travel,Business,351,1,1,1,1,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +34602,71735,Male,Loyal Customer,42,Business travel,Business,1744,3,3,3,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +34603,67806,Male,Loyal Customer,68,Business travel,Eco,805,2,4,4,4,2,2,2,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +34604,7305,Female,Loyal Customer,51,Business travel,Business,2312,4,4,4,4,2,4,5,4,4,5,5,5,4,5,4,0.0,satisfied +34605,100087,Female,disloyal Customer,24,Business travel,Eco,289,4,4,4,1,3,4,3,3,5,2,4,4,4,3,4,5.0,satisfied +34606,94918,Male,Loyal Customer,41,Business travel,Business,2933,4,4,4,4,2,1,5,4,4,5,4,1,4,5,4,3.0,satisfied +34607,76579,Female,Loyal Customer,34,Business travel,Business,1849,1,4,4,4,1,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +34608,78428,Female,Loyal Customer,45,Business travel,Business,666,1,1,1,1,2,5,5,4,4,5,4,4,4,5,114,128.0,satisfied +34609,73359,Male,Loyal Customer,53,Business travel,Business,3545,2,2,4,2,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +34610,39117,Male,disloyal Customer,22,Business travel,Eco,252,3,2,3,2,2,3,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +34611,80766,Male,Loyal Customer,55,Personal Travel,Eco,440,2,3,2,3,1,2,1,1,4,3,1,1,1,1,0,0.0,neutral or dissatisfied +34612,74722,Male,Loyal Customer,62,Personal Travel,Eco,1464,2,5,2,3,3,2,3,3,5,4,3,3,4,3,0,0.0,neutral or dissatisfied +34613,72155,Female,Loyal Customer,50,Personal Travel,Eco,731,3,4,3,3,2,2,4,2,2,3,1,4,2,5,0,0.0,neutral or dissatisfied +34614,84814,Male,Loyal Customer,47,Business travel,Eco,547,4,5,1,1,4,4,4,4,4,5,2,3,3,4,0,0.0,neutral or dissatisfied +34615,74994,Female,Loyal Customer,41,Personal Travel,Eco Plus,2475,3,4,3,2,3,4,5,3,3,3,3,4,3,3,0,16.0,neutral or dissatisfied +34616,90533,Female,disloyal Customer,44,Business travel,Business,404,4,4,4,1,4,4,4,4,3,4,4,3,4,4,0,5.0,satisfied +34617,46913,Female,disloyal Customer,20,Business travel,Eco,844,1,1,1,3,2,1,2,2,2,4,2,4,2,2,0,0.0,neutral or dissatisfied +34618,29410,Female,Loyal Customer,65,Personal Travel,Eco,2378,2,5,2,1,3,3,5,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +34619,2815,Female,Loyal Customer,48,Business travel,Business,475,1,1,1,1,4,4,4,5,5,5,5,5,5,4,71,63.0,satisfied +34620,103597,Female,Loyal Customer,60,Personal Travel,Eco Plus,451,2,4,2,3,4,5,4,3,3,2,5,3,3,4,8,9.0,neutral or dissatisfied +34621,118876,Male,Loyal Customer,42,Business travel,Eco,1136,3,4,4,4,3,3,3,3,3,2,3,3,4,3,5,0.0,neutral or dissatisfied +34622,18956,Male,Loyal Customer,39,Business travel,Eco Plus,448,4,5,5,5,4,4,4,4,2,3,1,2,3,4,8,8.0,satisfied +34623,87602,Male,Loyal Customer,55,Business travel,Eco Plus,432,1,3,3,3,1,1,1,1,4,2,4,2,3,1,0,2.0,neutral or dissatisfied +34624,24497,Female,Loyal Customer,39,Personal Travel,Eco,516,2,4,2,1,2,2,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +34625,7011,Male,Loyal Customer,8,Personal Travel,Eco,234,3,4,3,5,5,3,5,5,3,5,5,4,5,5,0,26.0,neutral or dissatisfied +34626,30803,Male,Loyal Customer,56,Business travel,Business,3609,5,5,5,5,5,3,5,5,5,5,5,5,5,1,10,7.0,satisfied +34627,118086,Male,Loyal Customer,56,Business travel,Business,1520,1,1,1,1,3,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +34628,98359,Female,Loyal Customer,45,Business travel,Eco,1046,3,2,2,2,4,3,2,3,3,3,3,3,3,4,4,0.0,neutral or dissatisfied +34629,112365,Male,Loyal Customer,63,Business travel,Business,846,4,4,4,4,2,5,4,4,4,4,4,5,4,5,36,12.0,satisfied +34630,103283,Female,Loyal Customer,48,Personal Travel,Eco,718,1,4,1,5,3,4,4,2,2,1,2,4,2,3,10,5.0,neutral or dissatisfied +34631,107167,Female,Loyal Customer,40,Business travel,Business,2177,3,1,3,3,5,5,5,5,5,5,5,5,5,3,24,20.0,satisfied +34632,101334,Male,Loyal Customer,34,Business travel,Business,1771,3,5,5,5,3,3,4,3,3,3,3,4,3,2,27,13.0,neutral or dissatisfied +34633,63222,Female,Loyal Customer,37,Business travel,Eco,447,5,3,3,3,5,4,5,5,4,4,3,1,3,5,0,0.0,neutral or dissatisfied +34634,68905,Male,Loyal Customer,46,Personal Travel,Eco,1061,3,4,3,4,4,3,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +34635,2421,Female,Loyal Customer,24,Personal Travel,Eco,604,3,4,2,4,2,2,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +34636,87347,Male,Loyal Customer,45,Business travel,Business,425,3,3,3,3,4,5,4,4,4,4,4,5,4,4,2,0.0,satisfied +34637,51583,Male,Loyal Customer,48,Business travel,Business,2215,4,4,4,4,2,5,5,5,5,5,5,4,5,5,4,2.0,satisfied +34638,41659,Male,Loyal Customer,36,Business travel,Business,1836,3,3,3,3,2,2,3,3,3,3,3,1,3,2,0,11.0,neutral or dissatisfied +34639,36652,Male,Loyal Customer,68,Personal Travel,Eco,1237,2,5,1,4,4,1,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +34640,26133,Female,Loyal Customer,34,Business travel,Business,3865,4,4,4,4,2,2,2,5,5,5,5,2,5,2,0,0.0,satisfied +34641,38270,Male,Loyal Customer,58,Business travel,Business,1173,2,2,2,2,1,5,4,5,5,5,5,1,5,5,0,0.0,satisfied +34642,120964,Female,Loyal Customer,32,Business travel,Business,992,4,1,1,1,4,4,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +34643,113403,Male,Loyal Customer,60,Business travel,Business,226,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,4.0,satisfied +34644,56997,Male,Loyal Customer,34,Personal Travel,Eco,2434,1,4,0,4,0,1,3,5,4,4,5,3,5,3,31,9.0,neutral or dissatisfied +34645,9482,Male,Loyal Customer,47,Business travel,Business,2479,0,0,0,3,5,5,5,1,1,1,1,3,1,4,30,34.0,satisfied +34646,95941,Female,Loyal Customer,34,Business travel,Business,1069,2,2,2,2,4,5,4,5,5,5,5,3,5,4,0,3.0,satisfied +34647,52926,Male,disloyal Customer,41,Business travel,Business,279,1,1,1,2,3,1,3,3,3,2,3,5,2,3,14,1.0,neutral or dissatisfied +34648,119862,Male,Loyal Customer,17,Personal Travel,Eco,936,2,4,2,1,1,2,5,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +34649,77045,Male,Loyal Customer,52,Business travel,Business,2214,5,5,5,5,4,4,5,4,4,4,4,3,4,5,6,0.0,satisfied +34650,23634,Female,Loyal Customer,55,Business travel,Eco,793,4,2,2,2,1,5,2,4,4,4,4,3,4,1,0,0.0,satisfied +34651,16757,Male,disloyal Customer,25,Business travel,Eco,569,4,5,4,1,3,4,5,3,4,2,3,3,5,3,62,68.0,satisfied +34652,124256,Male,disloyal Customer,50,Business travel,Eco Plus,1916,3,2,2,3,1,3,2,1,4,5,1,1,2,1,0,0.0,neutral or dissatisfied +34653,75258,Female,Loyal Customer,14,Personal Travel,Eco,1744,4,4,4,5,1,4,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +34654,22587,Male,Loyal Customer,46,Business travel,Business,3719,2,2,2,2,5,3,2,5,5,5,5,2,5,4,94,94.0,satisfied +34655,108101,Male,Loyal Customer,44,Business travel,Business,3168,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +34656,15711,Male,Loyal Customer,25,Business travel,Business,1839,4,4,4,4,4,4,4,4,2,3,5,5,5,4,110,99.0,satisfied +34657,114290,Female,Loyal Customer,38,Personal Travel,Eco,909,5,4,5,3,2,5,2,2,1,1,4,4,3,2,0,0.0,satisfied +34658,66977,Female,Loyal Customer,45,Business travel,Business,3326,2,2,2,2,3,4,5,5,5,4,5,5,5,4,15,8.0,satisfied +34659,91123,Female,Loyal Customer,50,Personal Travel,Eco,594,2,4,3,3,3,1,1,4,1,3,1,1,2,1,136,152.0,neutral or dissatisfied +34660,19461,Male,disloyal Customer,62,Business travel,Eco,177,3,5,3,3,3,3,5,3,4,4,4,3,3,3,18,29.0,neutral or dissatisfied +34661,109635,Male,Loyal Customer,41,Business travel,Business,802,2,2,1,2,3,4,5,5,5,5,5,5,5,5,58,58.0,satisfied +34662,72687,Female,Loyal Customer,26,Personal Travel,Eco,985,4,4,4,2,3,4,3,3,5,4,4,5,5,3,58,55.0,neutral or dissatisfied +34663,10612,Female,Loyal Customer,51,Business travel,Business,3941,4,4,4,4,3,4,4,4,4,4,4,4,4,5,46,30.0,satisfied +34664,75155,Female,disloyal Customer,38,Business travel,Business,1744,1,1,1,4,3,1,3,3,4,3,4,5,4,3,0,2.0,neutral or dissatisfied +34665,20267,Female,Loyal Customer,61,Business travel,Business,2947,2,2,2,2,3,4,4,2,2,2,2,4,2,2,29,15.0,neutral or dissatisfied +34666,6187,Male,Loyal Customer,16,Personal Travel,Eco,501,4,5,5,1,1,5,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +34667,81464,Male,disloyal Customer,23,Business travel,Business,408,5,0,5,5,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +34668,24350,Female,Loyal Customer,17,Personal Travel,Eco,634,2,4,2,1,2,2,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +34669,3965,Male,Loyal Customer,32,Personal Travel,Eco,764,2,5,2,1,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +34670,60778,Female,Loyal Customer,18,Personal Travel,Eco,628,3,5,3,2,5,3,5,5,5,4,4,4,4,5,7,9.0,neutral or dissatisfied +34671,54679,Female,Loyal Customer,48,Business travel,Eco,965,4,2,2,2,2,3,5,4,4,4,4,5,4,5,0,5.0,satisfied +34672,108884,Female,disloyal Customer,26,Business travel,Business,843,0,0,0,2,3,0,3,3,4,5,5,3,5,3,0,0.0,satisfied +34673,125813,Female,Loyal Customer,28,Business travel,Business,861,2,5,5,5,2,2,2,2,3,2,4,1,4,2,0,8.0,neutral or dissatisfied +34674,109520,Male,Loyal Customer,31,Business travel,Business,994,2,4,4,4,2,1,2,2,2,5,3,2,4,2,31,44.0,neutral or dissatisfied +34675,40163,Female,Loyal Customer,35,Business travel,Business,3719,1,1,1,1,1,4,2,2,2,2,2,4,2,2,0,0.0,satisfied +34676,95152,Male,Loyal Customer,67,Personal Travel,Eco,319,2,5,2,4,1,2,1,1,5,4,1,3,1,1,0,0.0,neutral or dissatisfied +34677,71265,Female,Loyal Customer,27,Personal Travel,Eco,733,1,5,1,2,1,1,1,4,2,1,3,1,2,1,217,,neutral or dissatisfied +34678,120634,Male,Loyal Customer,55,Business travel,Business,280,4,4,5,4,4,4,5,5,5,5,5,5,5,5,30,21.0,satisfied +34679,48757,Male,disloyal Customer,44,Business travel,Business,337,3,3,3,2,2,3,2,2,1,2,3,1,3,2,0,0.0,neutral or dissatisfied +34680,110982,Female,Loyal Customer,42,Business travel,Business,319,0,0,0,5,2,2,5,5,5,4,4,5,4,5,209,181.0,satisfied +34681,8888,Male,Loyal Customer,64,Personal Travel,Eco,622,3,4,3,1,1,3,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +34682,38175,Female,Loyal Customer,68,Personal Travel,Eco,1121,2,4,2,4,3,5,4,2,2,2,2,4,2,4,18,13.0,neutral or dissatisfied +34683,33117,Female,Loyal Customer,17,Personal Travel,Eco,216,5,4,0,4,2,0,2,2,4,2,2,3,5,2,0,2.0,satisfied +34684,48397,Female,Loyal Customer,57,Personal Travel,Eco,522,2,4,2,4,2,4,5,5,5,2,5,4,5,4,34,30.0,neutral or dissatisfied +34685,17247,Male,Loyal Customer,32,Business travel,Business,2511,4,4,1,4,3,3,3,3,5,2,4,1,2,3,0,0.0,satisfied +34686,84611,Male,Loyal Customer,46,Business travel,Business,669,4,3,3,3,2,3,4,4,4,4,4,4,4,3,60,44.0,neutral or dissatisfied +34687,90207,Female,Loyal Customer,22,Personal Travel,Eco,957,1,4,1,4,2,1,2,2,1,5,3,3,4,2,1,3.0,neutral or dissatisfied +34688,68854,Male,Loyal Customer,41,Business travel,Business,2695,3,3,3,3,3,4,4,5,5,5,5,5,5,5,15,12.0,satisfied +34689,26406,Male,Loyal Customer,47,Personal Travel,Eco,1084,4,4,4,4,3,4,2,3,4,2,5,4,4,3,0,2.0,neutral or dissatisfied +34690,87961,Female,Loyal Customer,43,Business travel,Business,3547,3,3,3,3,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +34691,52555,Female,Loyal Customer,34,Business travel,Business,3746,1,1,3,1,3,1,4,5,5,5,5,4,5,4,0,0.0,satisfied +34692,19547,Male,Loyal Customer,38,Business travel,Eco,212,4,1,1,1,4,4,4,4,3,4,1,3,1,4,23,13.0,satisfied +34693,28023,Male,Loyal Customer,26,Business travel,Business,1835,5,4,5,5,5,5,5,5,1,5,2,3,5,5,0,10.0,satisfied +34694,55902,Male,disloyal Customer,24,Business travel,Eco,733,2,2,2,1,2,2,5,2,1,5,2,3,1,2,0,13.0,neutral or dissatisfied +34695,31602,Female,Loyal Customer,48,Personal Travel,Eco,602,4,5,4,3,2,5,4,4,4,4,2,3,4,3,0,0.0,neutral or dissatisfied +34696,103351,Male,Loyal Customer,23,Personal Travel,Business,342,3,4,4,4,1,4,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +34697,57149,Male,Loyal Customer,20,Business travel,Business,1824,3,3,3,3,3,3,3,3,4,3,5,3,5,3,8,0.0,satisfied +34698,38983,Male,Loyal Customer,51,Business travel,Business,3846,3,3,3,3,2,3,3,4,4,4,4,2,4,5,34,71.0,satisfied +34699,45701,Female,disloyal Customer,23,Business travel,Eco,852,5,5,5,4,3,5,5,3,3,3,4,5,4,3,0,0.0,satisfied +34700,78263,Male,Loyal Customer,27,Business travel,Business,2783,2,5,5,5,2,2,2,2,2,3,3,2,3,2,0,7.0,neutral or dissatisfied +34701,54003,Male,Loyal Customer,26,Business travel,Business,395,1,1,1,1,4,5,4,4,4,4,1,4,1,4,6,0.0,satisfied +34702,30848,Male,Loyal Customer,31,Business travel,Business,973,5,5,5,5,3,3,3,3,2,4,3,3,4,3,36,26.0,satisfied +34703,44739,Male,Loyal Customer,39,Personal Travel,Eco Plus,67,2,1,2,3,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +34704,13243,Female,Loyal Customer,56,Business travel,Eco,657,2,3,3,3,5,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +34705,110833,Male,Loyal Customer,31,Business travel,Eco Plus,1166,4,4,4,4,4,4,4,4,2,3,4,4,4,4,3,0.0,neutral or dissatisfied +34706,57648,Male,Loyal Customer,62,Business travel,Business,1574,3,3,3,3,4,5,1,5,5,5,3,1,5,3,22,10.0,satisfied +34707,111815,Female,Loyal Customer,22,Personal Travel,Eco,349,4,4,4,1,2,4,2,2,3,3,3,5,3,2,34,34.0,neutral or dissatisfied +34708,122569,Female,Loyal Customer,45,Business travel,Business,728,5,5,5,5,4,4,4,2,2,3,2,3,2,5,0,0.0,satisfied +34709,95035,Female,Loyal Customer,58,Personal Travel,Eco,189,2,4,2,4,1,4,4,5,5,2,5,4,5,2,30,25.0,neutral or dissatisfied +34710,16277,Female,Loyal Customer,61,Personal Travel,Eco,631,1,3,1,3,1,4,5,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +34711,100131,Male,disloyal Customer,28,Business travel,Business,717,4,4,4,1,5,4,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +34712,6437,Male,Loyal Customer,16,Personal Travel,Eco,296,1,5,3,1,2,3,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +34713,74784,Female,Loyal Customer,42,Business travel,Business,1464,2,4,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +34714,101685,Male,Loyal Customer,40,Business travel,Business,1500,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +34715,54812,Male,disloyal Customer,34,Business travel,Eco,862,2,2,2,3,3,2,3,3,3,3,5,4,2,3,0,0.0,neutral or dissatisfied +34716,107326,Female,Loyal Customer,48,Business travel,Business,2047,2,4,2,2,2,4,4,3,3,4,3,5,3,4,36,18.0,satisfied +34717,53988,Male,Loyal Customer,26,Business travel,Business,1825,3,3,3,3,4,4,4,4,4,3,4,4,5,4,0,12.0,satisfied +34718,9664,Female,disloyal Customer,45,Business travel,Business,284,3,3,3,5,5,3,3,5,4,3,5,4,4,5,6,19.0,neutral or dissatisfied +34719,38759,Male,disloyal Customer,24,Business travel,Eco,353,4,5,4,1,5,4,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +34720,112367,Male,Loyal Customer,40,Business travel,Business,853,2,2,2,2,4,5,4,4,4,5,4,4,4,3,7,3.0,satisfied +34721,90817,Female,Loyal Customer,35,Business travel,Eco,406,3,5,5,5,3,3,3,3,2,4,3,4,4,3,16,13.0,neutral or dissatisfied +34722,124604,Female,Loyal Customer,33,Personal Travel,Eco Plus,500,3,5,3,5,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +34723,2534,Male,disloyal Customer,37,Business travel,Business,280,3,3,3,3,5,3,5,5,3,2,4,5,5,5,0,1.0,neutral or dissatisfied +34724,88045,Female,Loyal Customer,58,Business travel,Business,240,5,5,5,5,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +34725,126940,Male,Loyal Customer,46,Business travel,Business,2597,5,5,5,5,5,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +34726,122315,Male,Loyal Customer,29,Business travel,Business,2806,1,1,1,1,4,4,4,4,5,5,4,5,4,4,2,0.0,satisfied +34727,115310,Male,Loyal Customer,47,Business travel,Business,337,0,0,0,2,3,4,5,3,3,3,3,3,3,4,0,,satisfied +34728,38826,Female,Loyal Customer,44,Personal Travel,Eco,354,3,4,3,1,2,5,5,4,4,3,4,3,4,5,32,25.0,neutral or dissatisfied +34729,61999,Female,disloyal Customer,26,Business travel,Business,2475,4,4,4,3,2,4,2,2,5,2,5,3,5,2,1,0.0,neutral or dissatisfied +34730,125824,Male,Loyal Customer,43,Business travel,Business,1883,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +34731,27408,Male,Loyal Customer,34,Business travel,Business,1050,5,5,5,5,3,5,3,5,5,5,5,4,5,2,7,0.0,satisfied +34732,48315,Female,Loyal Customer,40,Business travel,Eco Plus,1499,5,5,4,5,5,5,5,5,3,2,1,1,2,5,47,48.0,satisfied +34733,26293,Female,Loyal Customer,22,Business travel,Business,2041,3,3,3,3,2,2,2,2,3,2,1,1,3,2,13,5.0,satisfied +34734,57096,Female,Loyal Customer,51,Business travel,Business,2931,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +34735,113009,Male,Loyal Customer,10,Personal Travel,Eco,1797,3,4,3,1,5,3,5,5,2,3,4,3,4,5,3,5.0,neutral or dissatisfied +34736,24555,Female,Loyal Customer,10,Business travel,Business,874,3,3,3,3,5,5,5,5,1,2,4,5,4,5,4,0.0,satisfied +34737,118924,Female,Loyal Customer,49,Personal Travel,Eco,587,1,4,1,4,5,4,4,3,3,1,2,3,3,2,0,0.0,neutral or dissatisfied +34738,44642,Male,disloyal Customer,40,Business travel,Eco,67,0,0,0,2,5,0,5,5,3,4,1,3,1,5,0,0.0,satisfied +34739,23684,Male,Loyal Customer,55,Business travel,Eco,196,2,5,5,5,2,2,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +34740,37288,Male,Loyal Customer,40,Business travel,Business,1028,2,5,2,2,1,5,4,4,4,4,4,5,4,2,123,117.0,satisfied +34741,26479,Female,Loyal Customer,49,Business travel,Eco Plus,787,5,4,4,4,5,5,5,3,2,4,4,5,5,5,279,276.0,satisfied +34742,95134,Female,Loyal Customer,54,Personal Travel,Eco,319,4,3,4,1,3,2,2,2,2,4,2,3,2,4,3,0.0,neutral or dissatisfied +34743,77100,Female,Loyal Customer,39,Business travel,Business,1481,2,2,2,2,4,5,4,3,3,3,3,4,3,4,7,7.0,satisfied +34744,95703,Female,Loyal Customer,51,Business travel,Business,419,2,2,2,2,3,5,5,5,5,5,5,3,5,4,50,41.0,satisfied +34745,107113,Female,Loyal Customer,29,Business travel,Business,2184,4,4,4,4,3,4,3,3,3,4,4,4,4,3,6,5.0,satisfied +34746,44809,Male,Loyal Customer,23,Business travel,Eco,1041,2,3,3,3,2,2,1,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +34747,102794,Female,Loyal Customer,65,Business travel,Eco Plus,1099,3,1,1,1,4,4,3,2,2,3,2,1,2,2,0,2.0,neutral or dissatisfied +34748,85929,Female,disloyal Customer,22,Business travel,Eco,447,1,0,1,4,1,1,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +34749,79355,Male,Loyal Customer,24,Personal Travel,Eco,1020,3,3,3,4,3,3,3,3,2,1,4,1,3,3,14,9.0,neutral or dissatisfied +34750,2521,Female,disloyal Customer,22,Business travel,Eco,227,0,4,0,1,3,0,3,3,3,4,4,5,5,3,0,0.0,satisfied +34751,77383,Female,Loyal Customer,17,Business travel,Business,1737,3,3,3,3,3,3,3,3,3,4,3,4,4,3,26,21.0,neutral or dissatisfied +34752,119281,Male,Loyal Customer,37,Business travel,Eco,214,4,1,1,1,4,3,4,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +34753,126630,Male,Loyal Customer,41,Business travel,Business,2179,5,5,4,5,3,4,4,5,5,5,5,5,5,3,50,39.0,satisfied +34754,129538,Male,Loyal Customer,31,Business travel,Business,2583,1,1,1,1,3,3,3,3,4,2,5,5,4,3,3,0.0,satisfied +34755,81566,Male,disloyal Customer,17,Business travel,Eco,936,3,3,3,3,5,3,5,5,4,2,3,4,3,5,0,15.0,neutral or dissatisfied +34756,101162,Male,Loyal Customer,58,Business travel,Business,2567,4,5,5,5,1,4,4,4,4,4,4,2,4,2,85,74.0,neutral or dissatisfied +34757,23258,Female,Loyal Customer,43,Business travel,Business,2367,4,4,4,4,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +34758,110068,Male,Loyal Customer,42,Business travel,Business,1754,1,1,1,1,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +34759,32103,Male,Loyal Customer,45,Business travel,Eco,216,5,5,5,5,5,5,5,5,3,3,1,3,3,5,0,4.0,satisfied +34760,105275,Female,Loyal Customer,52,Business travel,Business,3583,1,1,5,1,5,5,4,4,4,4,4,4,4,4,68,61.0,satisfied +34761,35709,Female,Loyal Customer,35,Personal Travel,Eco,2465,1,5,2,4,2,4,4,4,3,3,5,4,4,4,0,9.0,neutral or dissatisfied +34762,69847,Female,Loyal Customer,48,Personal Travel,Eco,1055,1,5,1,4,1,4,4,1,1,1,1,4,1,4,87,87.0,neutral or dissatisfied +34763,47434,Female,Loyal Customer,65,Business travel,Business,3407,3,3,3,3,5,1,1,4,4,4,3,5,4,2,0,4.0,satisfied +34764,63335,Female,Loyal Customer,45,Business travel,Eco,337,5,3,3,3,1,5,4,5,5,5,5,2,5,5,1,1.0,satisfied +34765,32201,Female,Loyal Customer,43,Business travel,Eco,201,4,1,1,1,5,5,2,4,4,4,4,5,4,3,8,13.0,satisfied +34766,111641,Female,Loyal Customer,45,Business travel,Business,3741,4,4,4,4,1,2,3,4,4,4,4,1,4,3,9,1.0,satisfied +34767,61404,Male,Loyal Customer,37,Personal Travel,Eco,679,4,1,5,3,2,5,2,2,4,5,3,3,3,2,11,0.0,satisfied +34768,99496,Male,Loyal Customer,47,Personal Travel,Eco,283,4,4,4,4,3,4,3,3,2,3,3,1,4,3,0,13.0,neutral or dissatisfied +34769,49684,Female,disloyal Customer,47,Business travel,Eco,56,3,3,3,3,1,3,1,1,3,4,3,1,3,1,36,26.0,neutral or dissatisfied +34770,85452,Male,Loyal Customer,49,Business travel,Business,214,3,3,4,3,5,5,4,4,4,4,5,4,4,4,28,25.0,satisfied +34771,127343,Male,Loyal Customer,34,Business travel,Business,3223,3,5,5,5,4,3,3,3,3,3,3,1,3,4,1,4.0,neutral or dissatisfied +34772,105495,Male,Loyal Customer,48,Business travel,Eco,116,2,4,4,4,2,2,2,2,1,2,3,3,3,2,0,0.0,neutral or dissatisfied +34773,93165,Male,Loyal Customer,53,Personal Travel,Eco,1066,3,4,3,2,3,3,3,3,4,4,4,3,4,3,51,81.0,neutral or dissatisfied +34774,21050,Male,Loyal Customer,39,Business travel,Business,3457,1,1,4,1,3,3,4,5,5,5,3,3,5,4,0,0.0,satisfied +34775,75869,Female,Loyal Customer,51,Business travel,Business,1972,1,1,1,1,4,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +34776,31763,Female,Loyal Customer,42,Business travel,Business,1593,2,2,2,2,1,1,2,5,5,5,5,4,5,4,0,0.0,satisfied +34777,61819,Female,Loyal Customer,56,Personal Travel,Eco,1504,2,4,2,3,4,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +34778,50335,Female,Loyal Customer,54,Business travel,Eco,134,2,5,5,5,4,4,5,2,2,2,2,4,2,5,7,0.0,satisfied +34779,39642,Female,Loyal Customer,43,Business travel,Eco,1172,4,5,5,5,1,3,3,4,4,4,4,2,4,4,11,23.0,neutral or dissatisfied +34780,85735,Female,disloyal Customer,26,Business travel,Business,666,5,5,5,3,4,5,4,4,4,3,4,3,5,4,8,17.0,satisfied +34781,8262,Male,Loyal Customer,60,Personal Travel,Eco,335,2,5,2,4,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +34782,89280,Male,disloyal Customer,27,Business travel,Business,453,3,3,3,4,2,3,2,2,4,2,4,5,4,2,25,44.0,neutral or dissatisfied +34783,14890,Female,disloyal Customer,37,Business travel,Eco,343,1,0,1,4,1,1,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +34784,23295,Male,Loyal Customer,35,Business travel,Eco,927,4,5,5,5,4,4,4,4,1,2,5,2,3,4,22,19.0,satisfied +34785,35562,Female,Loyal Customer,20,Business travel,Eco Plus,950,0,5,0,1,1,0,1,1,2,1,1,3,2,1,0,63.0,satisfied +34786,40842,Male,Loyal Customer,59,Business travel,Eco,174,1,4,4,4,1,1,1,2,3,3,3,1,4,1,139,135.0,neutral or dissatisfied +34787,108291,Male,disloyal Customer,19,Business travel,Eco,1075,4,4,4,3,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +34788,75399,Male,disloyal Customer,26,Business travel,Business,2267,5,5,5,2,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +34789,125533,Male,Loyal Customer,52,Business travel,Business,3023,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +34790,45147,Female,Loyal Customer,50,Business travel,Business,3053,2,2,2,2,5,1,1,5,5,5,5,1,5,5,27,27.0,satisfied +34791,102398,Male,Loyal Customer,70,Business travel,Eco,397,2,3,3,3,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +34792,33999,Male,Loyal Customer,53,Business travel,Business,1598,2,5,5,5,1,3,2,2,2,2,2,4,2,1,37,26.0,neutral or dissatisfied +34793,84860,Male,Loyal Customer,77,Business travel,Business,3587,4,4,4,4,4,4,3,3,3,3,4,4,3,4,15,17.0,neutral or dissatisfied +34794,52396,Female,Loyal Customer,25,Personal Travel,Eco,425,2,0,5,3,3,5,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +34795,80477,Female,Loyal Customer,41,Personal Travel,Eco,1299,2,4,2,5,3,2,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +34796,56910,Female,disloyal Customer,41,Business travel,Business,2454,3,3,3,2,3,5,5,4,4,5,5,5,4,5,7,10.0,neutral or dissatisfied +34797,105163,Male,disloyal Customer,24,Business travel,Eco,220,1,0,1,1,5,1,5,5,3,2,5,4,1,5,20,19.0,neutral or dissatisfied +34798,86815,Female,Loyal Customer,57,Business travel,Business,692,3,1,1,1,5,4,4,3,3,3,3,4,3,3,1,0.0,neutral or dissatisfied +34799,56657,Male,Loyal Customer,25,Business travel,Business,3433,3,3,3,3,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +34800,77013,Female,Loyal Customer,48,Business travel,Business,3291,1,1,2,1,4,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +34801,35007,Female,Loyal Customer,50,Personal Travel,Eco,1182,1,4,1,3,5,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +34802,34942,Male,Loyal Customer,46,Personal Travel,Eco,395,4,4,4,5,5,4,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +34803,59956,Male,Loyal Customer,63,Business travel,Eco,1085,3,5,5,5,3,3,3,3,4,1,2,1,3,3,1,0.0,neutral or dissatisfied +34804,116986,Female,disloyal Customer,23,Business travel,Business,370,4,1,4,3,5,4,5,5,2,3,4,1,3,5,63,52.0,neutral or dissatisfied +34805,96954,Male,Loyal Customer,26,Business travel,Business,3786,3,3,3,3,5,5,5,5,4,3,5,3,5,5,0,4.0,satisfied +34806,100218,Female,Loyal Customer,14,Personal Travel,Eco,762,2,2,2,4,3,2,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +34807,57912,Female,Loyal Customer,52,Personal Travel,Eco,305,0,1,0,4,4,3,4,5,5,0,5,3,5,4,0,0.0,satisfied +34808,67061,Female,Loyal Customer,11,Business travel,Business,1765,2,1,2,1,2,2,2,2,3,4,2,3,3,2,0,0.0,neutral or dissatisfied +34809,51697,Male,disloyal Customer,47,Business travel,Eco,425,3,0,3,2,1,3,2,1,4,5,2,1,3,1,0,0.0,neutral or dissatisfied +34810,101464,Male,Loyal Customer,43,Business travel,Business,2973,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +34811,53823,Male,Loyal Customer,36,Business travel,Business,224,2,2,2,2,1,5,3,3,3,4,3,3,3,1,0,2.0,satisfied +34812,61607,Male,Loyal Customer,60,Business travel,Business,1346,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +34813,59346,Male,Loyal Customer,37,Business travel,Business,2556,3,3,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +34814,35674,Female,Loyal Customer,44,Business travel,Eco,2446,4,5,5,5,4,4,4,3,5,4,1,4,1,4,0,0.0,satisfied +34815,90165,Male,Loyal Customer,57,Personal Travel,Eco,1127,2,4,2,1,3,2,3,3,3,2,5,3,4,3,1,0.0,neutral or dissatisfied +34816,5929,Male,Loyal Customer,13,Personal Travel,Eco,173,5,3,5,1,3,5,3,3,2,2,3,3,5,3,0,0.0,satisfied +34817,87440,Female,Loyal Customer,38,Business travel,Business,373,2,3,2,2,2,4,5,4,4,4,4,5,4,3,12,0.0,satisfied +34818,72540,Female,disloyal Customer,29,Business travel,Business,1119,5,5,5,1,5,5,5,5,3,2,5,4,5,5,2,4.0,satisfied +34819,35196,Male,Loyal Customer,21,Business travel,Business,2804,2,3,2,2,4,4,4,4,2,4,5,5,2,4,19,0.0,satisfied +34820,55463,Female,Loyal Customer,42,Business travel,Business,1825,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +34821,68636,Female,Loyal Customer,44,Business travel,Business,2055,2,2,2,2,4,4,5,4,4,4,5,4,4,3,13,8.0,satisfied +34822,92104,Male,Loyal Customer,39,Personal Travel,Eco,1589,1,4,1,2,5,1,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +34823,16767,Male,Loyal Customer,55,Business travel,Eco,569,1,1,1,1,1,1,1,1,2,2,3,4,4,1,37,27.0,neutral or dissatisfied +34824,68110,Male,Loyal Customer,46,Personal Travel,Eco,868,3,4,3,3,4,3,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +34825,25180,Female,Loyal Customer,23,Business travel,Business,577,3,2,2,2,3,3,3,3,1,4,3,4,3,3,72,80.0,neutral or dissatisfied +34826,54120,Female,Loyal Customer,23,Business travel,Eco,1400,0,4,0,2,4,0,4,4,2,5,5,4,4,4,0,0.0,satisfied +34827,5467,Male,Loyal Customer,55,Personal Travel,Eco,265,1,4,1,3,5,1,5,5,3,1,4,5,3,5,0,0.0,neutral or dissatisfied +34828,43680,Male,Loyal Customer,43,Business travel,Business,489,4,4,4,4,2,4,2,4,4,4,4,2,4,5,37,47.0,satisfied +34829,94339,Male,Loyal Customer,43,Business travel,Business,189,1,1,1,1,4,5,4,4,4,4,5,4,4,3,68,66.0,satisfied +34830,9776,Female,Loyal Customer,30,Business travel,Business,2660,3,3,3,3,4,4,4,4,3,3,4,5,1,4,0,0.0,satisfied +34831,99836,Female,Loyal Customer,58,Business travel,Business,2525,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +34832,98549,Male,Loyal Customer,27,Personal Travel,Eco Plus,402,2,4,2,4,2,2,5,2,4,5,4,4,5,2,9,0.0,neutral or dissatisfied +34833,90959,Female,Loyal Customer,31,Business travel,Business,271,0,0,0,3,1,1,1,1,3,5,4,2,4,1,0,0.0,satisfied +34834,32394,Male,Loyal Customer,53,Business travel,Eco,101,5,4,4,4,4,5,4,4,3,2,2,2,5,4,0,0.0,satisfied +34835,62794,Female,Loyal Customer,54,Personal Travel,Eco,2486,1,1,1,4,3,4,4,4,4,1,2,2,4,2,5,2.0,neutral or dissatisfied +34836,30449,Female,Loyal Customer,41,Business travel,Business,991,5,5,5,5,3,2,4,4,4,4,4,3,4,5,0,0.0,satisfied +34837,62266,Male,Loyal Customer,11,Personal Travel,Eco Plus,2565,2,5,2,2,5,2,5,5,5,2,3,5,5,5,27,,neutral or dissatisfied +34838,35064,Female,Loyal Customer,8,Business travel,Business,972,5,5,5,5,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +34839,69959,Male,Loyal Customer,54,Personal Travel,Eco,2174,1,4,1,3,5,1,5,5,3,4,3,2,3,5,22,5.0,neutral or dissatisfied +34840,88220,Male,disloyal Customer,77,Business travel,Business,404,1,1,1,1,4,4,4,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +34841,120918,Female,Loyal Customer,30,Business travel,Business,3719,5,5,5,5,5,5,5,5,5,5,4,4,5,5,29,,satisfied +34842,79504,Female,Loyal Customer,41,Business travel,Business,3625,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +34843,124899,Male,disloyal Customer,44,Business travel,Business,728,5,5,5,1,5,2,2,5,3,5,4,2,4,2,194,183.0,satisfied +34844,24338,Male,Loyal Customer,42,Business travel,Business,3736,3,2,2,2,3,3,3,3,3,3,3,1,3,1,16,13.0,neutral or dissatisfied +34845,75703,Female,Loyal Customer,59,Business travel,Business,1663,1,1,1,1,2,5,4,5,5,5,5,4,5,5,47,78.0,satisfied +34846,64942,Female,disloyal Customer,37,Business travel,Eco,469,2,1,2,4,3,2,3,3,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +34847,9794,Male,Loyal Customer,34,Business travel,Eco Plus,456,2,3,3,3,2,2,2,2,1,2,4,3,4,2,1,0.0,neutral or dissatisfied +34848,93686,Male,Loyal Customer,32,Business travel,Business,1452,2,2,2,2,4,4,4,4,4,2,5,5,5,4,29,6.0,satisfied +34849,66349,Female,disloyal Customer,15,Business travel,Business,986,4,2,4,2,4,4,4,4,4,5,5,3,5,4,1,8.0,satisfied +34850,40099,Male,Loyal Customer,50,Business travel,Business,3362,2,2,2,2,5,4,1,4,4,4,3,4,4,1,0,0.0,satisfied +34851,118246,Male,Loyal Customer,25,Business travel,Business,1972,5,5,5,5,4,5,4,4,4,4,3,3,5,4,17,1.0,satisfied +34852,116433,Female,Loyal Customer,20,Personal Travel,Eco,296,4,4,4,5,4,4,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +34853,125732,Male,Loyal Customer,67,Business travel,Eco Plus,499,2,1,1,1,2,2,2,2,4,5,4,3,3,2,26,17.0,neutral or dissatisfied +34854,91721,Female,Loyal Customer,42,Business travel,Business,3354,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +34855,742,Female,Loyal Customer,46,Business travel,Business,158,2,5,5,5,1,3,2,1,1,2,2,1,1,3,0,0.0,neutral or dissatisfied +34856,65459,Male,Loyal Customer,48,Business travel,Business,1685,2,2,2,2,4,4,4,4,5,4,4,4,5,4,147,200.0,satisfied +34857,83992,Female,disloyal Customer,21,Business travel,Eco,321,2,3,2,2,5,2,5,5,3,2,4,2,4,5,1,0.0,neutral or dissatisfied +34858,64532,Female,Loyal Customer,48,Business travel,Business,2935,1,1,1,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +34859,41119,Male,disloyal Customer,27,Business travel,Eco,191,3,2,3,3,4,3,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +34860,127825,Female,Loyal Customer,46,Personal Travel,Eco,1262,4,5,4,3,5,3,5,2,2,4,2,3,2,3,0,15.0,neutral or dissatisfied +34861,10783,Male,Loyal Customer,60,Business travel,Business,1713,1,1,1,1,3,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +34862,8914,Male,Loyal Customer,18,Business travel,Eco Plus,510,0,4,0,1,2,0,2,2,1,2,4,5,2,2,0,15.0,satisfied +34863,86091,Female,Loyal Customer,54,Business travel,Business,1972,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +34864,127598,Female,disloyal Customer,36,Business travel,Eco,1773,3,3,3,3,2,3,2,2,1,1,4,4,4,2,0,0.0,neutral or dissatisfied +34865,50764,Female,Loyal Customer,70,Personal Travel,Eco,109,1,4,0,3,3,3,4,1,1,0,1,5,1,2,0,2.0,neutral or dissatisfied +34866,3133,Female,disloyal Customer,39,Business travel,Business,140,1,1,1,2,4,1,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +34867,40623,Female,Loyal Customer,47,Personal Travel,Eco,391,3,5,3,3,2,5,5,4,4,3,3,3,4,5,9,46.0,neutral or dissatisfied +34868,99449,Male,Loyal Customer,60,Business travel,Business,2205,2,4,4,4,3,4,4,2,2,2,2,4,2,3,1,10.0,neutral or dissatisfied +34869,9066,Female,Loyal Customer,39,Business travel,Business,2607,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +34870,27514,Male,Loyal Customer,70,Personal Travel,Eco,954,4,3,4,3,4,4,4,4,2,4,2,2,4,4,13,0.0,satisfied +34871,30159,Female,Loyal Customer,27,Personal Travel,Eco,548,3,0,3,4,2,3,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +34872,2410,Female,Loyal Customer,42,Business travel,Business,767,4,4,4,4,3,2,2,4,4,4,4,4,4,2,12,15.0,neutral or dissatisfied +34873,12525,Male,disloyal Customer,28,Business travel,Eco,828,2,2,2,4,3,2,3,3,3,4,4,2,3,3,4,0.0,neutral or dissatisfied +34874,14278,Male,Loyal Customer,36,Business travel,Business,429,3,3,3,3,5,4,5,4,4,4,4,5,4,1,23,19.0,satisfied +34875,69980,Male,Loyal Customer,56,Business travel,Business,2465,4,4,1,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +34876,34563,Female,disloyal Customer,37,Business travel,Eco,1598,2,2,2,1,2,2,2,2,4,2,5,2,4,2,0,0.0,neutral or dissatisfied +34877,52612,Male,disloyal Customer,33,Business travel,Eco,119,2,2,2,3,5,2,5,5,1,4,3,1,3,5,0,0.0,neutral or dissatisfied +34878,23318,Female,Loyal Customer,40,Business travel,Eco,674,3,4,4,4,3,3,3,3,4,4,2,1,3,3,0,0.0,neutral or dissatisfied +34879,5145,Female,Loyal Customer,51,Business travel,Business,622,2,2,1,2,5,5,5,4,4,4,4,3,4,4,51,81.0,satisfied +34880,23713,Female,Loyal Customer,66,Personal Travel,Eco,73,3,5,3,3,2,4,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +34881,125531,Female,Loyal Customer,37,Business travel,Business,2432,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +34882,129140,Male,Loyal Customer,50,Business travel,Business,954,1,1,1,1,2,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +34883,123495,Male,Loyal Customer,34,Business travel,Business,2125,3,2,2,2,2,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +34884,4152,Female,Loyal Customer,39,Business travel,Eco,427,2,2,2,2,2,2,2,2,4,3,3,2,2,2,0,0.0,neutral or dissatisfied +34885,114235,Male,Loyal Customer,53,Business travel,Business,862,2,1,5,1,5,3,3,2,2,2,2,4,2,3,31,26.0,neutral or dissatisfied +34886,3071,Male,Loyal Customer,40,Business travel,Business,413,1,1,1,1,2,4,5,5,5,5,5,5,5,5,60,71.0,satisfied +34887,30006,Female,Loyal Customer,43,Business travel,Eco,503,2,2,2,2,1,3,3,2,2,2,2,2,2,2,21,23.0,neutral or dissatisfied +34888,60111,Male,disloyal Customer,26,Business travel,Business,1012,5,5,5,3,4,5,4,4,3,3,5,3,5,4,8,0.0,satisfied +34889,113188,Male,Loyal Customer,41,Business travel,Business,2607,2,2,2,2,4,5,5,4,4,4,4,3,4,4,6,0.0,satisfied +34890,17286,Female,Loyal Customer,35,Business travel,Eco Plus,440,1,2,2,2,1,1,1,1,4,4,4,1,2,1,134,131.0,neutral or dissatisfied +34891,30822,Female,Loyal Customer,50,Business travel,Eco,896,3,4,4,4,3,1,3,3,3,3,3,1,3,1,35,31.0,satisfied +34892,41545,Female,disloyal Customer,46,Business travel,Eco,1334,3,2,2,3,1,3,1,1,4,4,3,4,3,1,0,8.0,neutral or dissatisfied +34893,94478,Female,disloyal Customer,26,Business travel,Eco,239,2,3,3,3,5,3,5,5,2,3,4,4,3,5,0,0.0,neutral or dissatisfied +34894,67148,Male,Loyal Customer,49,Business travel,Business,2422,4,1,1,1,1,4,4,4,4,4,4,4,4,2,1,0.0,neutral or dissatisfied +34895,95924,Female,disloyal Customer,27,Business travel,Eco,1411,3,4,4,4,3,3,3,3,2,3,4,2,4,3,6,8.0,neutral or dissatisfied +34896,24287,Female,Loyal Customer,51,Personal Travel,Eco,147,3,5,3,5,5,4,4,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +34897,72746,Female,Loyal Customer,69,Personal Travel,Business,806,2,1,2,2,4,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +34898,6509,Female,Loyal Customer,51,Business travel,Business,2425,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +34899,74521,Female,Loyal Customer,41,Business travel,Business,1464,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,54.0,satisfied +34900,92899,Male,Loyal Customer,33,Business travel,Business,151,4,4,5,4,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +34901,60740,Female,Loyal Customer,31,Business travel,Business,2958,4,4,4,4,4,4,4,4,5,2,5,5,4,4,51,36.0,satisfied +34902,128786,Female,Loyal Customer,54,Business travel,Business,2586,5,5,5,5,4,4,4,4,2,3,4,4,5,4,1,0.0,satisfied +34903,82342,Male,disloyal Customer,24,Business travel,Business,453,5,1,5,4,4,5,5,4,4,3,4,3,5,4,67,74.0,satisfied +34904,53203,Male,Loyal Customer,57,Business travel,Eco,589,3,2,2,2,3,3,3,3,1,4,3,1,3,3,0,1.0,neutral or dissatisfied +34905,96841,Female,disloyal Customer,26,Business travel,Eco,571,1,4,1,3,1,1,1,1,2,4,3,2,3,1,41,35.0,neutral or dissatisfied +34906,128162,Male,disloyal Customer,36,Business travel,Eco,1788,2,2,2,4,2,2,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +34907,118891,Female,Loyal Customer,57,Business travel,Business,3829,3,3,5,3,3,5,5,5,5,5,5,4,5,5,70,73.0,satisfied +34908,114924,Female,Loyal Customer,47,Business travel,Business,342,2,2,2,2,5,4,4,5,5,5,5,3,5,5,51,50.0,satisfied +34909,90625,Male,Loyal Customer,43,Business travel,Business,2567,5,5,5,5,2,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +34910,21517,Male,Loyal Customer,20,Personal Travel,Eco,377,1,2,1,3,3,1,3,3,2,3,3,3,3,3,85,75.0,neutral or dissatisfied +34911,10486,Female,disloyal Customer,49,Business travel,Business,295,2,2,2,3,2,2,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +34912,52696,Male,Loyal Customer,15,Personal Travel,Eco Plus,119,4,4,4,2,3,4,1,3,5,3,1,2,5,3,0,0.0,neutral or dissatisfied +34913,114094,Female,Loyal Customer,18,Personal Travel,Eco,1892,5,1,5,2,2,5,5,2,3,3,1,1,3,2,0,0.0,satisfied +34914,16321,Male,Loyal Customer,42,Business travel,Eco,594,2,2,2,2,2,2,2,2,4,5,3,2,3,2,38,39.0,neutral or dissatisfied +34915,125729,Male,Loyal Customer,51,Business travel,Business,2982,2,2,2,2,5,5,5,5,5,5,5,5,5,4,54,61.0,satisfied +34916,15031,Female,Loyal Customer,45,Business travel,Business,1943,4,4,2,4,4,5,2,5,5,5,5,3,5,3,0,6.0,satisfied +34917,71067,Female,Loyal Customer,62,Personal Travel,Eco,802,5,1,5,4,1,3,4,4,4,5,2,4,4,3,0,0.0,satisfied +34918,127629,Female,Loyal Customer,47,Business travel,Business,1773,3,1,1,1,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +34919,35962,Female,Loyal Customer,27,Business travel,Business,3225,2,4,4,4,2,2,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +34920,2945,Female,Loyal Customer,48,Business travel,Business,835,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +34921,111403,Female,Loyal Customer,12,Personal Travel,Eco,1180,3,4,3,3,3,3,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +34922,121445,Male,Loyal Customer,53,Business travel,Eco,331,4,3,2,3,4,4,4,4,2,3,4,2,3,4,4,1.0,neutral or dissatisfied +34923,68622,Male,Loyal Customer,48,Business travel,Business,175,0,5,0,4,2,4,4,3,3,3,3,5,3,5,5,2.0,satisfied +34924,107360,Female,Loyal Customer,14,Personal Travel,Eco,584,4,5,4,3,5,4,5,5,2,1,1,4,5,5,0,0.0,neutral or dissatisfied +34925,2339,Male,Loyal Customer,65,Personal Travel,Eco,691,3,4,3,4,2,3,5,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +34926,56069,Male,Loyal Customer,16,Personal Travel,Eco,2586,3,2,3,3,3,3,5,2,4,2,4,5,3,5,1,0.0,neutral or dissatisfied +34927,62961,Male,disloyal Customer,30,Business travel,Business,846,4,4,4,4,4,4,4,4,3,4,5,3,4,4,1,7.0,satisfied +34928,54403,Male,Loyal Customer,39,Business travel,Eco,305,5,2,2,2,5,5,5,5,4,3,4,2,4,5,0,0.0,satisfied +34929,3028,Male,Loyal Customer,52,Personal Travel,Eco,922,3,5,3,2,4,3,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +34930,108305,Female,Loyal Customer,42,Business travel,Business,1844,3,3,3,3,2,3,5,5,5,5,5,3,5,4,12,40.0,satisfied +34931,23003,Male,Loyal Customer,34,Personal Travel,Eco,489,2,0,2,4,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +34932,80376,Male,Loyal Customer,40,Business travel,Business,1685,3,1,1,1,1,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +34933,7401,Male,Loyal Customer,41,Business travel,Business,552,2,2,2,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +34934,72148,Female,Loyal Customer,22,Personal Travel,Eco,731,1,5,1,1,4,1,4,4,1,5,5,2,5,4,0,3.0,neutral or dissatisfied +34935,109870,Female,disloyal Customer,27,Business travel,Business,1165,5,5,5,3,2,5,3,2,4,2,5,3,5,2,22,3.0,satisfied +34936,96416,Female,Loyal Customer,42,Personal Travel,Eco,1246,4,5,5,3,2,4,5,3,3,5,3,4,3,4,24,12.0,neutral or dissatisfied +34937,19999,Male,Loyal Customer,53,Business travel,Business,2517,1,1,1,1,5,1,1,4,4,4,4,3,4,5,1,0.0,satisfied +34938,118528,Female,Loyal Customer,44,Business travel,Eco,338,1,0,0,4,5,4,4,2,2,1,2,3,2,1,57,54.0,neutral or dissatisfied +34939,94896,Male,disloyal Customer,36,Business travel,Eco,293,2,0,2,4,1,2,5,1,5,1,1,3,4,1,0,0.0,neutral or dissatisfied +34940,45886,Female,disloyal Customer,31,Business travel,Eco,913,1,1,1,1,4,1,4,4,4,3,2,5,2,4,0,0.0,neutral or dissatisfied +34941,41888,Female,Loyal Customer,25,Personal Travel,Business,129,2,4,2,3,5,2,2,5,2,5,4,1,4,5,116,118.0,neutral or dissatisfied +34942,79741,Male,Loyal Customer,49,Business travel,Business,3104,4,4,4,4,3,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +34943,96082,Female,Loyal Customer,11,Personal Travel,Eco,795,1,5,1,4,3,1,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +34944,111242,Male,Loyal Customer,54,Business travel,Business,1972,3,1,3,3,4,5,5,4,4,4,4,5,4,4,9,0.0,satisfied +34945,112468,Male,Loyal Customer,45,Business travel,Eco,909,5,5,5,5,5,5,5,5,2,3,4,2,1,5,38,28.0,satisfied +34946,87696,Male,Loyal Customer,36,Personal Travel,Eco,591,3,4,3,3,2,3,2,2,3,4,4,3,4,2,18,5.0,neutral or dissatisfied +34947,19836,Male,Loyal Customer,70,Personal Travel,Eco,528,3,5,3,2,3,3,3,3,5,2,5,4,4,3,46,71.0,neutral or dissatisfied +34948,72760,Male,Loyal Customer,57,Business travel,Business,1827,5,5,2,5,4,4,5,5,5,5,5,3,5,3,4,0.0,satisfied +34949,74219,Male,Loyal Customer,50,Business travel,Business,1746,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +34950,43929,Female,Loyal Customer,17,Personal Travel,Eco,114,3,5,0,3,5,0,5,5,1,3,4,4,4,5,0,0.0,neutral or dissatisfied +34951,23810,Male,Loyal Customer,55,Personal Travel,Eco,374,4,4,4,1,3,4,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +34952,54190,Male,Loyal Customer,58,Personal Travel,Eco,1400,3,4,3,4,4,3,4,4,4,1,4,2,3,4,0,0.0,neutral or dissatisfied +34953,75038,Male,Loyal Customer,56,Personal Travel,Eco,236,2,4,2,3,5,2,5,5,5,3,5,3,5,5,47,40.0,neutral or dissatisfied +34954,102054,Male,Loyal Customer,32,Personal Travel,Business,397,3,4,3,1,4,3,4,4,4,2,5,4,5,4,11,9.0,neutral or dissatisfied +34955,8374,Male,disloyal Customer,29,Business travel,Eco,701,3,3,3,4,5,3,4,5,1,1,4,1,3,5,25,35.0,neutral or dissatisfied +34956,123234,Female,Loyal Customer,45,Personal Travel,Eco,507,2,5,2,4,3,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +34957,38772,Female,Loyal Customer,51,Business travel,Eco,354,4,1,1,1,2,1,5,4,4,4,4,2,4,4,9,7.0,satisfied +34958,109014,Female,Loyal Customer,54,Business travel,Business,957,1,1,1,1,4,5,4,4,4,4,4,3,4,5,1,0.0,satisfied +34959,76896,Female,Loyal Customer,22,Business travel,Business,3205,2,5,1,5,2,2,2,2,4,3,3,1,3,2,47,41.0,neutral or dissatisfied +34960,14250,Female,Loyal Customer,16,Business travel,Eco Plus,1027,5,3,3,3,5,4,1,5,4,2,3,2,2,5,34,46.0,neutral or dissatisfied +34961,84866,Male,Loyal Customer,37,Personal Travel,Eco,547,1,4,1,4,3,1,3,3,4,3,3,1,4,3,12,5.0,neutral or dissatisfied +34962,77724,Male,Loyal Customer,62,Business travel,Business,2185,2,5,5,5,4,4,4,2,2,2,2,1,2,3,99,85.0,neutral or dissatisfied +34963,122844,Male,Loyal Customer,40,Business travel,Business,226,4,4,4,4,5,5,4,5,5,5,5,4,5,3,66,35.0,satisfied +34964,19270,Male,Loyal Customer,47,Business travel,Business,430,5,5,5,5,5,5,5,4,4,4,4,3,4,3,14,24.0,satisfied +34965,106337,Male,disloyal Customer,58,Business travel,Business,425,2,2,2,2,1,2,1,1,3,5,5,4,5,1,7,4.0,neutral or dissatisfied +34966,107556,Female,Loyal Customer,27,Business travel,Business,1521,1,4,4,4,1,1,1,1,3,5,3,2,4,1,11,0.0,neutral or dissatisfied +34967,105200,Female,Loyal Customer,67,Personal Travel,Eco Plus,220,2,4,0,1,1,1,2,5,5,0,5,5,5,5,5,0.0,neutral or dissatisfied +34968,114180,Female,Loyal Customer,45,Business travel,Business,846,5,5,5,5,5,4,4,5,5,5,5,4,5,5,37,18.0,satisfied +34969,93659,Female,Loyal Customer,45,Business travel,Business,1885,2,2,2,2,2,4,4,4,4,4,4,5,4,3,9,17.0,satisfied +34970,93474,Female,Loyal Customer,33,Business travel,Eco Plus,605,2,4,4,4,2,2,2,2,2,4,4,2,3,2,55,48.0,neutral or dissatisfied +34971,92341,Female,Loyal Customer,25,Business travel,Business,2486,5,5,5,5,5,5,5,5,3,5,4,5,3,5,0,8.0,satisfied +34972,27473,Male,Loyal Customer,63,Business travel,Eco,679,2,1,1,1,2,2,2,2,1,3,2,4,2,2,0,0.0,neutral or dissatisfied +34973,17359,Male,Loyal Customer,22,Personal Travel,Eco,563,3,4,3,4,2,3,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +34974,124777,Male,Loyal Customer,45,Business travel,Business,2056,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,74.0,satisfied +34975,53224,Male,Loyal Customer,47,Personal Travel,Eco,589,4,4,4,1,1,4,1,1,5,2,5,4,5,1,0,0.0,satisfied +34976,84331,Male,disloyal Customer,37,Business travel,Business,606,1,1,1,2,2,1,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +34977,42719,Male,disloyal Customer,28,Business travel,Eco,912,2,2,2,3,2,2,2,2,1,1,3,1,3,2,1,22.0,neutral or dissatisfied +34978,5959,Male,Loyal Customer,36,Business travel,Business,850,1,4,4,4,4,3,4,1,1,1,1,4,1,1,7,6.0,neutral or dissatisfied +34979,11887,Male,Loyal Customer,39,Business travel,Business,2626,4,4,4,4,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +34980,39728,Female,Loyal Customer,51,Business travel,Business,162,1,1,1,1,2,2,1,2,2,1,1,1,2,4,0,0.0,neutral or dissatisfied +34981,69856,Male,Loyal Customer,10,Personal Travel,Eco,1055,2,4,2,1,1,2,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +34982,20453,Male,disloyal Customer,18,Business travel,Eco,177,3,4,4,4,5,4,5,5,3,5,3,3,4,5,34,32.0,neutral or dissatisfied +34983,75666,Female,Loyal Customer,49,Business travel,Business,3726,4,4,4,4,3,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +34984,72113,Female,Loyal Customer,58,Business travel,Business,731,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +34985,88093,Female,Loyal Customer,36,Business travel,Business,223,4,4,4,4,5,5,4,5,5,5,5,3,5,5,3,4.0,satisfied +34986,7448,Male,Loyal Customer,23,Personal Travel,Eco,522,3,5,3,2,5,3,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +34987,82332,Female,disloyal Customer,45,Business travel,Business,456,2,2,2,2,5,2,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +34988,105825,Female,Loyal Customer,47,Personal Travel,Eco,925,3,4,4,1,3,5,4,5,5,4,3,3,5,3,2,1.0,neutral or dissatisfied +34989,118576,Male,Loyal Customer,55,Business travel,Business,370,1,1,1,1,2,4,4,4,4,4,4,5,4,4,12,14.0,satisfied +34990,9458,Female,Loyal Customer,25,Personal Travel,Eco,299,2,4,2,2,3,2,4,3,5,5,4,5,5,3,2,0.0,neutral or dissatisfied +34991,59689,Male,Loyal Customer,48,Personal Travel,Eco,787,1,4,1,2,3,1,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +34992,42829,Male,Loyal Customer,41,Business travel,Eco,328,4,3,3,3,4,4,4,4,5,5,5,2,5,4,0,0.0,satisfied +34993,113384,Female,Loyal Customer,43,Business travel,Business,223,0,4,0,3,2,4,4,5,5,5,5,3,5,4,0,22.0,satisfied +34994,118650,Female,disloyal Customer,34,Business travel,Business,369,3,3,3,4,3,3,2,3,4,2,5,5,4,3,4,0.0,neutral or dissatisfied +34995,98022,Female,disloyal Customer,8,Business travel,Eco,1014,3,3,3,4,5,3,5,5,3,2,4,3,3,5,57,43.0,neutral or dissatisfied +34996,115691,Female,disloyal Customer,37,Business travel,Eco,446,2,1,2,4,1,2,1,1,1,3,3,3,4,1,48,33.0,neutral or dissatisfied +34997,123212,Female,Loyal Customer,26,Personal Travel,Eco,631,2,3,2,2,3,2,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +34998,38006,Female,Loyal Customer,41,Business travel,Eco,1197,5,5,5,5,5,5,5,5,4,1,4,2,4,5,0,0.0,satisfied +34999,55399,Female,Loyal Customer,32,Personal Travel,Eco Plus,594,2,3,2,2,1,2,1,1,2,5,2,1,2,1,0,0.0,neutral or dissatisfied +35000,54215,Female,Loyal Customer,40,Business travel,Business,1222,4,4,4,4,4,4,4,4,4,4,4,4,4,3,34,15.0,satisfied +35001,95174,Female,Loyal Customer,13,Personal Travel,Eco,323,3,5,3,4,3,3,3,3,3,1,5,2,2,3,14,19.0,neutral or dissatisfied +35002,126404,Male,Loyal Customer,55,Business travel,Business,328,3,3,3,3,3,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +35003,112018,Male,Loyal Customer,43,Business travel,Business,2186,5,5,2,5,4,4,4,4,4,4,4,4,4,4,39,39.0,satisfied +35004,65084,Male,Loyal Customer,68,Personal Travel,Eco,224,4,3,4,2,1,4,1,1,2,2,3,4,5,1,0,0.0,satisfied +35005,30542,Male,disloyal Customer,32,Business travel,Eco,896,1,1,1,4,2,1,3,2,3,3,1,4,2,2,15,85.0,neutral or dissatisfied +35006,91973,Female,Loyal Customer,41,Business travel,Business,2586,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +35007,45601,Male,Loyal Customer,50,Business travel,Business,2543,2,2,2,2,4,3,2,4,4,4,4,2,4,3,0,0.0,satisfied +35008,11736,Female,disloyal Customer,25,Business travel,Business,429,0,0,0,5,1,0,1,1,4,3,5,5,4,1,0,0.0,satisfied +35009,59811,Female,Loyal Customer,68,Business travel,Business,2812,1,5,5,5,2,4,3,1,1,1,1,3,1,1,9,0.0,neutral or dissatisfied +35010,73966,Female,Loyal Customer,60,Personal Travel,Eco,2330,3,5,3,1,3,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +35011,21686,Male,Loyal Customer,31,Business travel,Business,3374,4,1,4,4,2,2,2,2,3,2,5,3,4,2,0,0.0,satisfied +35012,87528,Female,disloyal Customer,65,Business travel,Eco Plus,373,1,1,1,4,1,1,1,1,2,1,4,2,3,1,54,39.0,neutral or dissatisfied +35013,81808,Male,Loyal Customer,31,Business travel,Business,1416,3,3,4,3,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +35014,58261,Female,disloyal Customer,40,Business travel,Business,572,3,3,3,3,1,3,1,1,1,1,3,4,3,1,0,0.0,neutral or dissatisfied +35015,121422,Male,disloyal Customer,22,Business travel,Eco,331,4,1,4,2,3,4,3,3,5,3,4,5,5,3,14,34.0,satisfied +35016,94088,Female,Loyal Customer,49,Personal Travel,Business,496,4,4,4,2,3,4,4,2,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +35017,58128,Female,Loyal Customer,50,Business travel,Business,612,3,3,3,3,3,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +35018,63068,Female,Loyal Customer,30,Personal Travel,Eco,967,2,5,2,4,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +35019,75836,Male,Loyal Customer,41,Business travel,Business,1440,2,2,2,2,5,5,4,5,5,5,5,3,5,3,3,0.0,satisfied +35020,103847,Male,Loyal Customer,25,Business travel,Business,2323,3,5,5,5,3,3,3,3,2,1,3,4,3,3,1,34.0,neutral or dissatisfied +35021,118729,Male,Loyal Customer,14,Personal Travel,Eco,338,3,4,3,5,4,3,4,4,5,4,4,5,4,4,14,23.0,neutral or dissatisfied +35022,51000,Female,Loyal Customer,34,Personal Travel,Eco,363,3,5,2,2,5,2,5,5,5,4,4,5,4,5,18,9.0,neutral or dissatisfied +35023,24476,Male,disloyal Customer,25,Business travel,Eco,481,4,5,3,4,3,3,3,3,5,5,5,1,5,3,0,0.0,satisfied +35024,55074,Female,disloyal Customer,64,Business travel,Business,1379,4,3,3,3,1,4,1,1,3,5,4,5,5,1,3,0.0,satisfied +35025,23090,Female,Loyal Customer,24,Personal Travel,Eco,794,3,4,3,4,1,3,1,1,5,5,5,5,5,1,107,99.0,neutral or dissatisfied +35026,50485,Female,disloyal Customer,26,Business travel,Business,262,2,2,2,3,2,2,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +35027,100790,Male,Loyal Customer,28,Business travel,Business,748,3,3,3,3,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +35028,66322,Male,Loyal Customer,19,Personal Travel,Eco,852,4,4,4,4,5,4,1,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +35029,6100,Female,Loyal Customer,52,Business travel,Business,409,2,2,5,2,3,5,4,4,4,4,4,5,4,4,36,103.0,satisfied +35030,18686,Male,Loyal Customer,63,Personal Travel,Eco,127,1,2,1,4,1,1,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +35031,79258,Female,Loyal Customer,9,Personal Travel,Eco,1598,1,5,1,3,2,1,3,2,4,2,5,4,5,2,27,7.0,neutral or dissatisfied +35032,90755,Female,Loyal Customer,54,Business travel,Business,406,5,5,5,5,3,4,4,4,4,4,4,5,4,5,3,5.0,satisfied +35033,9399,Female,Loyal Customer,47,Business travel,Business,1822,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +35034,99561,Female,Loyal Customer,51,Business travel,Eco,808,2,5,5,5,2,3,3,2,2,2,2,4,2,4,5,0.0,neutral or dissatisfied +35035,87780,Male,Loyal Customer,45,Business travel,Business,2101,4,4,4,4,3,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +35036,45210,Female,disloyal Customer,35,Business travel,Eco,1013,1,1,1,4,3,1,3,3,2,4,3,4,4,3,99,83.0,neutral or dissatisfied +35037,32386,Male,disloyal Customer,27,Business travel,Eco,101,2,0,2,4,1,2,1,1,3,4,2,3,3,1,0,0.0,neutral or dissatisfied +35038,98603,Male,Loyal Customer,44,Business travel,Business,2779,2,2,1,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +35039,79787,Female,disloyal Customer,22,Business travel,Eco,1089,4,4,4,3,2,4,2,2,4,4,4,4,4,2,0,4.0,satisfied +35040,112065,Male,disloyal Customer,10,Business travel,Eco,1240,1,1,1,1,3,1,3,3,4,3,3,3,4,3,0,0.0,neutral or dissatisfied +35041,75090,Male,Loyal Customer,37,Personal Travel,Eco,1814,1,5,1,3,3,1,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +35042,90671,Female,Loyal Customer,73,Business travel,Business,2135,3,1,2,1,4,3,2,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +35043,59797,Female,Loyal Customer,52,Business travel,Business,1023,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +35044,36874,Female,Loyal Customer,40,Business travel,Business,2141,2,1,1,1,3,4,4,2,2,2,2,4,2,1,14,25.0,neutral or dissatisfied +35045,54774,Male,Loyal Customer,34,Business travel,Eco Plus,861,5,2,2,2,5,5,5,5,2,5,3,3,5,5,89,73.0,satisfied +35046,44250,Male,Loyal Customer,30,Business travel,Eco,235,0,0,0,2,5,0,5,5,5,3,2,4,3,5,0,0.0,satisfied +35047,42630,Female,Loyal Customer,42,Business travel,Business,2629,1,1,1,1,5,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +35048,64803,Female,disloyal Customer,22,Business travel,Business,190,0,4,1,1,4,1,2,4,3,2,4,4,4,4,0,0.0,satisfied +35049,79772,Female,Loyal Customer,51,Business travel,Business,1076,2,1,2,2,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +35050,52516,Female,Loyal Customer,43,Business travel,Business,3164,2,2,2,2,4,4,5,4,4,4,5,1,4,3,0,0.0,satisfied +35051,82007,Male,Loyal Customer,49,Business travel,Business,3337,3,2,2,2,4,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +35052,1960,Female,Loyal Customer,51,Business travel,Eco,383,4,4,4,4,2,2,4,4,4,4,4,1,4,1,0,0.0,satisfied +35053,69951,Female,Loyal Customer,67,Personal Travel,Eco,2174,3,1,3,3,2,3,3,5,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +35054,71648,Female,Loyal Customer,32,Personal Travel,Eco,1197,2,4,2,5,2,2,2,2,3,5,3,3,5,2,8,0.0,neutral or dissatisfied +35055,26273,Male,disloyal Customer,21,Business travel,Eco,859,3,2,2,2,5,2,5,5,5,5,2,3,1,5,5,0.0,neutral or dissatisfied +35056,28715,Female,Loyal Customer,47,Business travel,Business,2554,3,5,5,5,3,3,3,3,1,4,4,3,1,3,8,19.0,neutral or dissatisfied +35057,91586,Male,Loyal Customer,29,Business travel,Business,1069,3,2,2,2,3,3,3,3,2,2,4,2,3,3,0,10.0,neutral or dissatisfied +35058,78690,Male,Loyal Customer,35,Personal Travel,Eco,674,4,4,4,2,3,4,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +35059,21738,Male,Loyal Customer,35,Business travel,Business,2786,4,4,5,4,5,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +35060,60353,Male,Loyal Customer,41,Business travel,Business,1024,2,4,2,2,3,5,5,4,4,4,4,4,4,4,2,0.0,satisfied +35061,11076,Female,Loyal Customer,12,Personal Travel,Eco,201,2,2,2,3,4,2,1,4,3,3,3,2,2,4,0,0.0,neutral or dissatisfied +35062,14851,Male,Loyal Customer,49,Business travel,Business,3166,0,0,0,3,3,3,5,2,2,2,4,5,2,3,17,33.0,satisfied +35063,41518,Male,disloyal Customer,25,Business travel,Eco,715,3,3,3,5,3,3,3,3,3,3,4,1,1,3,120,119.0,neutral or dissatisfied +35064,38969,Male,Loyal Customer,52,Business travel,Eco,113,5,3,3,3,4,5,4,4,2,3,2,3,5,4,71,96.0,satisfied +35065,122604,Female,Loyal Customer,13,Business travel,Business,728,1,4,4,4,1,1,1,1,4,1,3,2,4,1,0,0.0,neutral or dissatisfied +35066,41443,Male,Loyal Customer,10,Personal Travel,Eco Plus,563,2,5,2,2,1,2,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +35067,53737,Female,Loyal Customer,59,Personal Travel,Eco,1190,2,4,2,3,2,4,4,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +35068,94051,Male,Loyal Customer,34,Business travel,Business,248,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,5.0,satisfied +35069,117927,Female,Loyal Customer,52,Business travel,Business,255,0,0,0,3,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +35070,77349,Female,disloyal Customer,24,Business travel,Eco,626,5,0,5,3,3,0,3,3,3,3,5,4,5,3,3,0.0,satisfied +35071,30346,Male,Loyal Customer,27,Business travel,Eco Plus,391,5,4,4,4,5,5,5,5,4,4,5,4,4,5,0,1.0,satisfied +35072,35367,Female,Loyal Customer,29,Business travel,Eco,1069,1,3,3,3,1,1,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +35073,85093,Female,Loyal Customer,46,Business travel,Business,696,2,2,2,2,5,5,4,5,5,4,5,4,5,3,5,0.0,satisfied +35074,116030,Male,Loyal Customer,70,Personal Travel,Eco,417,1,3,1,4,2,1,2,2,1,5,4,1,3,2,6,1.0,neutral or dissatisfied +35075,80086,Female,disloyal Customer,44,Business travel,Eco Plus,550,1,1,1,3,3,1,3,3,1,1,3,1,3,3,0,0.0,neutral or dissatisfied +35076,4979,Male,disloyal Customer,23,Business travel,Eco,502,3,4,4,4,4,4,4,4,4,5,4,5,5,4,20,32.0,neutral or dissatisfied +35077,124685,Female,Loyal Customer,60,Business travel,Business,399,3,3,3,3,4,4,4,4,4,4,4,5,4,4,22,27.0,satisfied +35078,106208,Female,Loyal Customer,12,Personal Travel,Eco Plus,436,3,1,3,2,5,3,5,5,3,3,2,1,2,5,0,0.0,neutral or dissatisfied +35079,70674,Male,Loyal Customer,58,Business travel,Business,447,5,5,5,5,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +35080,47803,Female,Loyal Customer,39,Business travel,Eco,838,2,2,2,2,2,2,2,2,5,2,3,4,5,2,0,0.0,satisfied +35081,82122,Male,Loyal Customer,47,Business travel,Eco Plus,1276,2,5,5,5,1,2,1,1,1,4,3,4,3,1,1,0.0,neutral or dissatisfied +35082,120537,Female,Loyal Customer,10,Personal Travel,Business,2176,0,3,0,5,3,0,3,3,3,3,1,4,1,3,1,0.0,satisfied +35083,73594,Male,disloyal Customer,24,Business travel,Business,204,4,4,4,4,5,4,5,5,3,4,4,3,5,5,10,6.0,satisfied +35084,59429,Female,Loyal Customer,33,Business travel,Eco Plus,2338,2,4,5,4,2,3,2,2,1,4,3,4,3,2,33,32.0,neutral or dissatisfied +35085,53816,Male,disloyal Customer,25,Business travel,Eco,140,3,3,3,4,3,3,3,3,3,5,1,2,3,3,79,71.0,neutral or dissatisfied +35086,113030,Male,disloyal Customer,20,Business travel,Eco,479,4,0,3,4,2,3,2,2,4,5,5,4,4,2,18,9.0,satisfied +35087,69848,Female,Loyal Customer,51,Personal Travel,Eco,1345,1,3,1,3,3,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +35088,70709,Female,Loyal Customer,43,Business travel,Business,3269,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +35089,53516,Male,Loyal Customer,13,Personal Travel,Eco,2419,4,4,4,3,4,1,1,5,3,5,5,1,3,1,18,0.0,neutral or dissatisfied +35090,20107,Female,Loyal Customer,42,Business travel,Business,2217,4,4,4,4,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +35091,15663,Male,disloyal Customer,37,Business travel,Eco,764,3,2,2,5,5,2,5,5,4,2,4,3,2,5,20,3.0,neutral or dissatisfied +35092,37647,Male,Loyal Customer,18,Personal Travel,Eco,1005,2,4,2,1,5,2,1,5,5,5,4,3,5,5,0,14.0,neutral or dissatisfied +35093,16690,Female,Loyal Customer,35,Business travel,Eco,200,4,2,2,2,4,4,4,4,2,5,5,4,3,4,0,0.0,satisfied +35094,71139,Female,Loyal Customer,55,Business travel,Business,2914,1,1,1,1,2,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +35095,31587,Male,Loyal Customer,51,Business travel,Eco,602,4,4,4,4,4,4,4,4,3,4,1,3,3,4,0,0.0,satisfied +35096,42914,Female,Loyal Customer,26,Personal Travel,Eco,200,4,4,4,2,3,4,3,3,5,5,2,5,4,3,0,0.0,neutral or dissatisfied +35097,24034,Female,Loyal Customer,26,Personal Travel,Eco,595,3,1,3,4,2,3,2,2,1,4,4,3,3,2,0,0.0,neutral or dissatisfied +35098,20306,Male,Loyal Customer,60,Business travel,Eco Plus,235,4,1,1,1,4,4,4,4,4,2,3,1,1,4,32,23.0,satisfied +35099,128693,Female,Loyal Customer,53,Personal Travel,Eco Plus,2288,1,2,1,4,4,3,3,5,5,1,5,3,5,3,3,0.0,neutral or dissatisfied +35100,100884,Female,Loyal Customer,23,Personal Travel,Eco Plus,2133,3,4,3,4,5,3,5,5,2,5,4,1,4,5,0,0.0,neutral or dissatisfied +35101,127136,Male,Loyal Customer,10,Personal Travel,Eco,651,4,1,4,3,3,4,3,3,4,1,2,3,3,3,0,1.0,satisfied +35102,51440,Female,Loyal Customer,35,Personal Travel,Eco Plus,373,1,3,1,3,1,1,3,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +35103,108314,Female,Loyal Customer,29,Business travel,Business,1750,5,5,5,5,5,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +35104,105844,Female,disloyal Customer,22,Business travel,Business,919,5,0,5,3,2,5,2,2,3,3,4,5,5,2,4,8.0,satisfied +35105,57823,Male,Loyal Customer,57,Business travel,Business,2869,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +35106,87246,Male,disloyal Customer,26,Business travel,Business,577,1,1,1,2,3,1,3,3,3,2,4,5,5,3,0,2.0,neutral or dissatisfied +35107,123413,Female,Loyal Customer,41,Business travel,Business,1337,3,3,3,3,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +35108,3183,Male,Loyal Customer,29,Business travel,Business,585,1,1,1,1,4,4,4,4,4,2,4,5,5,4,25,26.0,satisfied +35109,71969,Male,Loyal Customer,46,Business travel,Business,1440,3,3,2,3,3,4,5,4,4,4,4,3,4,3,37,38.0,satisfied +35110,4468,Male,Loyal Customer,49,Personal Travel,Eco,1005,5,4,5,5,3,5,3,3,3,3,4,5,5,3,0,3.0,satisfied +35111,49210,Male,Loyal Customer,43,Business travel,Eco,266,4,3,3,3,4,4,4,4,3,5,1,5,4,4,0,0.0,satisfied +35112,101344,Male,Loyal Customer,51,Business travel,Business,2026,5,5,5,5,3,5,4,4,4,4,4,4,4,3,8,5.0,satisfied +35113,89395,Male,Loyal Customer,68,Business travel,Business,3919,1,1,1,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +35114,41397,Female,Loyal Customer,42,Business travel,Business,2246,1,1,5,1,2,5,4,5,5,5,5,5,5,2,0,0.0,satisfied +35115,55548,Male,Loyal Customer,55,Personal Travel,Eco,550,3,0,3,4,4,3,4,4,4,2,1,5,1,4,0,0.0,neutral or dissatisfied +35116,80387,Female,disloyal Customer,34,Business travel,Eco,368,2,1,3,3,1,3,1,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +35117,38380,Male,Loyal Customer,20,Personal Travel,Eco,1173,2,5,2,1,2,2,2,2,5,5,4,3,5,2,12,7.0,neutral or dissatisfied +35118,96925,Male,Loyal Customer,54,Business travel,Business,488,3,3,3,3,4,4,4,4,4,4,4,4,4,4,40,24.0,satisfied +35119,33013,Female,Loyal Customer,10,Personal Travel,Eco,163,3,1,3,2,2,3,2,2,4,4,3,4,2,2,32,35.0,neutral or dissatisfied +35120,71774,Male,Loyal Customer,58,Business travel,Business,1744,3,3,3,3,5,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +35121,45056,Male,Loyal Customer,33,Business travel,Eco,265,5,5,5,5,5,5,5,5,1,1,4,3,5,5,0,0.0,satisfied +35122,19743,Male,Loyal Customer,49,Personal Travel,Eco Plus,491,3,1,4,3,1,4,1,1,2,5,2,1,3,1,0,0.0,neutral or dissatisfied +35123,35372,Female,Loyal Customer,65,Business travel,Business,1069,3,2,2,2,3,3,2,3,3,3,3,3,3,4,10,36.0,neutral or dissatisfied +35124,126362,Male,Loyal Customer,58,Personal Travel,Eco,650,4,3,4,4,2,4,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +35125,105602,Male,Loyal Customer,60,Business travel,Business,919,3,3,3,3,3,5,5,5,5,5,5,4,5,4,12,6.0,satisfied +35126,120473,Male,Loyal Customer,42,Personal Travel,Eco,449,1,4,1,2,3,1,3,3,5,5,4,4,5,3,6,0.0,neutral or dissatisfied +35127,117067,Female,Loyal Customer,39,Business travel,Eco,325,3,4,4,4,3,3,3,3,2,5,3,3,3,3,0,8.0,neutral or dissatisfied +35128,2914,Female,Loyal Customer,61,Business travel,Eco Plus,409,2,2,2,2,2,2,1,2,2,2,2,3,2,4,35,39.0,neutral or dissatisfied +35129,25349,Male,Loyal Customer,36,Personal Travel,Eco,691,2,4,2,2,1,2,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +35130,31886,Male,Loyal Customer,40,Business travel,Business,2762,5,5,5,5,3,3,1,2,2,2,2,4,2,2,0,0.0,satisfied +35131,112613,Female,Loyal Customer,58,Personal Travel,Eco,602,1,2,1,3,4,3,4,3,3,1,1,2,3,1,0,0.0,neutral or dissatisfied +35132,58806,Male,Loyal Customer,32,Personal Travel,Eco,1012,3,4,3,4,1,3,1,1,2,1,4,5,4,1,21,0.0,neutral or dissatisfied +35133,78030,Female,Loyal Customer,41,Personal Travel,Eco,214,5,0,5,1,4,5,4,4,3,2,4,5,5,4,0,9.0,satisfied +35134,123687,Female,Loyal Customer,52,Business travel,Business,2381,3,3,3,3,4,2,1,5,5,5,3,1,5,1,0,0.0,satisfied +35135,110891,Female,disloyal Customer,21,Business travel,Eco,406,2,2,1,3,2,1,2,2,4,1,3,1,4,2,41,35.0,neutral or dissatisfied +35136,26222,Male,Loyal Customer,39,Personal Travel,Eco,581,3,5,3,4,3,3,3,3,5,5,4,5,5,3,8,13.0,neutral or dissatisfied +35137,57944,Male,Loyal Customer,42,Business travel,Business,1629,5,5,5,5,4,4,4,4,4,4,4,4,4,5,4,8.0,satisfied +35138,106095,Female,disloyal Customer,47,Business travel,Business,444,3,3,3,5,2,3,2,2,4,4,5,5,5,2,79,77.0,neutral or dissatisfied +35139,81474,Female,Loyal Customer,48,Business travel,Eco,528,4,1,1,1,4,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +35140,81422,Male,Loyal Customer,34,Business travel,Business,1767,4,4,4,4,5,3,3,4,4,4,4,4,4,3,1,0.0,neutral or dissatisfied +35141,19676,Male,Loyal Customer,38,Business travel,Business,3541,4,4,4,4,2,5,2,4,4,4,4,3,4,5,5,0.0,satisfied +35142,12540,Male,Loyal Customer,25,Business travel,Business,1536,3,1,1,1,3,3,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +35143,45894,Male,Loyal Customer,53,Business travel,Business,3472,2,2,2,2,5,4,4,4,4,4,4,4,4,2,1,0.0,satisfied +35144,77722,Female,Loyal Customer,42,Business travel,Business,3912,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +35145,26201,Female,disloyal Customer,21,Business travel,Eco,404,2,4,2,4,1,2,4,1,4,5,3,1,4,1,24,22.0,neutral or dissatisfied +35146,93009,Male,disloyal Customer,29,Business travel,Eco,1524,3,3,3,3,5,3,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +35147,82917,Female,Loyal Customer,63,Personal Travel,Eco,594,3,5,3,2,2,3,4,5,5,3,5,4,5,4,26,27.0,neutral or dissatisfied +35148,61407,Female,Loyal Customer,67,Personal Travel,Eco,679,1,4,1,4,3,4,4,5,5,1,5,3,5,4,6,0.0,neutral or dissatisfied +35149,121198,Male,Loyal Customer,50,Personal Travel,Eco,2402,3,5,3,1,3,1,3,3,4,5,5,3,3,3,13,56.0,neutral or dissatisfied +35150,98556,Female,Loyal Customer,23,Business travel,Business,992,3,3,3,3,3,3,3,3,5,2,4,3,5,3,60,40.0,satisfied +35151,124414,Female,disloyal Customer,46,Business travel,Business,1044,3,3,3,1,5,3,5,5,3,3,5,5,4,5,53,41.0,neutral or dissatisfied +35152,24098,Male,Loyal Customer,19,Personal Travel,Eco Plus,625,2,5,3,3,3,3,3,3,5,4,4,5,5,3,47,49.0,neutral or dissatisfied +35153,19454,Female,Loyal Customer,30,Personal Travel,Eco,363,4,4,5,3,5,5,5,5,3,4,5,4,4,5,0,1.0,satisfied +35154,66686,Male,disloyal Customer,25,Business travel,Business,802,5,0,5,2,2,5,2,2,4,2,5,5,4,2,7,0.0,satisfied +35155,62713,Female,Loyal Customer,25,Business travel,Business,2556,3,3,3,3,4,4,4,4,2,4,5,4,4,4,18,4.0,satisfied +35156,122673,Male,Loyal Customer,35,Business travel,Eco,361,2,5,5,5,2,2,2,2,1,1,4,3,4,2,11,11.0,neutral or dissatisfied +35157,23908,Female,Loyal Customer,26,Business travel,Business,589,4,1,1,1,4,4,4,4,3,3,4,2,4,4,30,17.0,neutral or dissatisfied +35158,16441,Male,disloyal Customer,27,Business travel,Eco,445,3,4,3,3,2,3,2,2,1,4,3,3,4,2,0,1.0,neutral or dissatisfied +35159,101302,Male,Loyal Customer,33,Personal Travel,Eco,763,1,3,1,2,5,1,5,5,2,5,3,2,2,5,16,13.0,neutral or dissatisfied +35160,23189,Female,Loyal Customer,9,Personal Travel,Eco,223,2,4,0,1,3,0,3,3,5,3,5,5,5,3,0,8.0,neutral or dissatisfied +35161,113326,Female,Loyal Customer,37,Business travel,Eco,397,1,2,2,2,1,1,1,1,2,3,3,2,3,1,19,14.0,neutral or dissatisfied +35162,64464,Male,Loyal Customer,49,Business travel,Eco Plus,589,5,2,5,5,5,5,5,5,1,5,2,4,4,5,17,7.0,satisfied +35163,127540,Female,disloyal Customer,21,Business travel,Business,1009,3,2,3,3,1,3,4,1,1,4,3,2,4,1,0,4.0,neutral or dissatisfied +35164,53051,Female,Loyal Customer,7,Personal Travel,Eco,1208,2,2,2,4,4,2,4,4,4,2,4,1,4,4,3,4.0,neutral or dissatisfied +35165,105555,Female,disloyal Customer,26,Business travel,Eco Plus,611,3,2,3,3,5,3,5,5,1,2,3,3,4,5,0,0.0,neutral or dissatisfied +35166,65098,Female,Loyal Customer,51,Personal Travel,Eco,224,3,4,3,4,5,4,4,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +35167,89919,Female,disloyal Customer,44,Business travel,Eco,1487,4,4,4,4,4,4,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +35168,14104,Male,Loyal Customer,60,Personal Travel,Eco,201,3,4,3,4,4,3,4,4,1,3,4,4,5,4,42,26.0,neutral or dissatisfied +35169,102119,Female,Loyal Customer,42,Business travel,Business,197,5,5,5,5,5,5,4,5,5,5,4,4,5,3,19,15.0,satisfied +35170,16544,Female,Loyal Customer,12,Personal Travel,Eco,1134,3,4,3,3,5,3,5,5,3,4,4,5,5,5,9,11.0,neutral or dissatisfied +35171,105155,Male,Loyal Customer,35,Business travel,Business,2327,0,5,1,4,4,1,5,4,4,4,4,2,4,2,4,0.0,satisfied +35172,113227,Female,Loyal Customer,40,Business travel,Business,236,5,5,5,5,2,4,4,4,4,4,4,4,4,5,20,29.0,satisfied +35173,83696,Female,Loyal Customer,36,Personal Travel,Eco,577,2,4,2,4,1,2,1,1,5,3,5,3,5,1,64,74.0,neutral or dissatisfied +35174,23234,Female,Loyal Customer,11,Personal Travel,Eco,116,5,4,5,3,5,5,2,5,3,3,3,2,4,5,0,0.0,satisfied +35175,57242,Female,Loyal Customer,41,Business travel,Business,804,4,2,2,2,5,4,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +35176,72351,Female,Loyal Customer,66,Personal Travel,Business,1121,2,1,2,3,1,2,2,4,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +35177,14870,Male,Loyal Customer,36,Business travel,Eco,315,3,2,5,2,3,3,3,3,3,5,3,2,4,3,0,0.0,neutral or dissatisfied +35178,68431,Female,Loyal Customer,28,Business travel,Business,1687,5,5,5,5,4,5,4,4,4,3,4,4,5,4,0,0.0,satisfied +35179,44197,Female,Loyal Customer,18,Personal Travel,Eco,157,3,5,0,2,2,0,2,2,5,4,5,3,4,2,0,2.0,neutral or dissatisfied +35180,105297,Female,Loyal Customer,41,Business travel,Business,738,3,5,5,5,3,3,3,3,3,3,3,1,3,4,7,0.0,neutral or dissatisfied +35181,29883,Male,disloyal Customer,17,Business travel,Eco,261,2,1,2,4,1,2,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +35182,66599,Male,Loyal Customer,43,Business travel,Business,761,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +35183,70759,Female,Loyal Customer,51,Business travel,Business,328,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +35184,128652,Female,Loyal Customer,56,Business travel,Business,2288,2,3,3,3,2,2,2,4,2,2,2,2,2,2,3,8.0,neutral or dissatisfied +35185,62766,Male,Loyal Customer,53,Business travel,Business,2504,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +35186,108857,Female,Loyal Customer,51,Business travel,Eco,639,5,3,3,3,2,1,5,5,5,5,5,2,5,3,75,88.0,satisfied +35187,71101,Male,Loyal Customer,51,Personal Travel,Eco Plus,802,4,1,4,4,1,4,1,1,1,4,3,4,3,1,1,0.0,satisfied +35188,5694,Female,Loyal Customer,36,Business travel,Eco,234,4,3,1,3,4,4,4,4,2,5,4,1,4,4,56,100.0,neutral or dissatisfied +35189,124060,Female,Loyal Customer,50,Business travel,Business,2153,4,4,4,4,4,1,2,4,4,4,4,4,4,2,7,16.0,neutral or dissatisfied +35190,56030,Female,disloyal Customer,26,Business travel,Business,2586,2,0,2,3,2,2,2,4,5,4,4,2,3,2,0,0.0,neutral or dissatisfied +35191,66565,Female,Loyal Customer,37,Business travel,Eco Plus,328,2,4,4,4,2,2,2,2,4,4,4,3,4,2,11,12.0,neutral or dissatisfied +35192,108352,Female,Loyal Customer,22,Business travel,Business,1838,1,3,3,3,1,1,1,1,4,2,2,3,4,1,4,0.0,neutral or dissatisfied +35193,17806,Male,disloyal Customer,38,Business travel,Eco,986,3,3,3,4,4,3,3,4,1,2,5,4,3,4,0,0.0,neutral or dissatisfied +35194,39814,Female,Loyal Customer,33,Business travel,Eco,272,0,0,0,3,1,0,1,1,4,4,3,1,2,1,0,0.0,satisfied +35195,35491,Male,Loyal Customer,59,Personal Travel,Eco,828,3,4,3,3,4,3,3,4,5,3,5,3,4,4,23,18.0,neutral or dissatisfied +35196,127602,Female,disloyal Customer,37,Business travel,Business,1773,3,3,3,4,4,3,4,4,5,2,4,3,4,4,0,0.0,neutral or dissatisfied +35197,103367,Female,Loyal Customer,24,Business travel,Business,1844,4,4,4,4,4,4,4,4,4,5,1,3,1,4,0,0.0,satisfied +35198,96431,Male,Loyal Customer,38,Personal Travel,Business,436,4,4,4,2,4,5,4,4,4,4,4,4,4,5,46,47.0,neutral or dissatisfied +35199,129195,Female,Loyal Customer,57,Business travel,Business,2288,3,3,3,3,4,5,5,5,5,3,5,5,3,5,156,133.0,satisfied +35200,82863,Female,disloyal Customer,25,Business travel,Eco,594,3,1,3,3,3,3,3,3,2,1,4,4,3,3,8,16.0,neutral or dissatisfied +35201,94730,Male,Loyal Customer,57,Business travel,Business,1659,2,3,3,3,1,3,3,2,2,2,2,3,2,3,12,12.0,neutral or dissatisfied +35202,103744,Female,Loyal Customer,29,Business travel,Eco Plus,251,1,5,5,5,1,2,1,1,2,5,4,1,4,1,0,0.0,neutral or dissatisfied +35203,106476,Female,Loyal Customer,45,Business travel,Business,1624,3,3,3,3,3,4,5,4,4,4,4,3,4,4,25,13.0,satisfied +35204,18249,Female,Loyal Customer,9,Personal Travel,Eco,346,3,4,3,4,5,3,5,5,3,3,4,3,5,5,0,1.0,neutral or dissatisfied +35205,49266,Female,disloyal Customer,55,Business travel,Eco,109,1,0,1,2,5,1,5,5,3,3,1,2,1,5,0,0.0,neutral or dissatisfied +35206,64583,Female,Loyal Customer,41,Business travel,Business,2574,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +35207,97096,Female,Loyal Customer,32,Business travel,Business,1242,3,2,5,2,3,3,3,3,2,3,4,4,4,3,4,0.0,neutral or dissatisfied +35208,92720,Female,Loyal Customer,39,Business travel,Business,2165,2,2,2,2,4,4,5,3,3,3,3,4,3,3,3,0.0,satisfied +35209,15331,Male,Loyal Customer,54,Personal Travel,Eco,589,3,5,2,2,5,2,1,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +35210,43169,Male,Loyal Customer,53,Business travel,Eco Plus,840,4,1,3,1,4,4,4,4,4,3,1,5,1,4,0,0.0,satisfied +35211,66534,Male,disloyal Customer,22,Business travel,Eco,333,3,2,3,4,3,3,3,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +35212,41392,Male,Loyal Customer,34,Business travel,Business,2686,1,1,1,1,2,1,3,5,5,5,5,4,5,4,0,0.0,satisfied +35213,102021,Female,Loyal Customer,55,Business travel,Business,2409,2,2,2,2,3,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +35214,40955,Female,Loyal Customer,43,Business travel,Business,1853,2,2,2,2,3,1,2,5,5,5,5,5,5,5,5,14.0,satisfied +35215,111202,Male,Loyal Customer,32,Business travel,Eco,1546,4,5,5,5,4,4,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +35216,74505,Male,Loyal Customer,43,Business travel,Business,1438,2,5,5,5,2,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +35217,68847,Female,Loyal Customer,55,Business travel,Business,1061,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,1.0,satisfied +35218,126627,Male,Loyal Customer,21,Business travel,Business,602,2,2,4,2,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +35219,10694,Male,Loyal Customer,48,Business travel,Eco,224,2,2,2,2,2,2,2,2,4,4,4,4,4,2,0,15.0,neutral or dissatisfied +35220,32609,Male,Loyal Customer,45,Business travel,Business,163,3,4,4,4,2,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +35221,15217,Male,Loyal Customer,27,Business travel,Business,445,2,3,4,4,2,2,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +35222,86022,Male,Loyal Customer,51,Business travel,Eco,447,5,2,2,2,5,5,5,5,2,4,5,4,3,5,2,0.0,satisfied +35223,72831,Male,Loyal Customer,45,Business travel,Business,2822,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +35224,71290,Male,Loyal Customer,64,Business travel,Eco Plus,333,2,2,2,2,2,2,2,2,3,2,4,1,3,2,0,29.0,neutral or dissatisfied +35225,27361,Female,Loyal Customer,26,Business travel,Eco,1050,0,4,0,4,5,4,5,5,3,4,5,5,2,5,0,0.0,satisfied +35226,45573,Male,Loyal Customer,56,Business travel,Business,2533,0,0,0,3,2,4,4,2,2,2,2,3,2,3,9,7.0,satisfied +35227,93632,Male,Loyal Customer,35,Personal Travel,Eco,577,3,5,3,3,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +35228,78593,Female,disloyal Customer,41,Business travel,Business,2454,1,1,1,2,5,1,5,5,4,5,3,5,5,5,0,0.0,neutral or dissatisfied +35229,25300,Male,Loyal Customer,47,Business travel,Eco,432,4,5,2,5,4,4,4,4,3,4,2,5,1,4,0,0.0,satisfied +35230,30996,Female,Loyal Customer,36,Business travel,Eco,391,5,4,4,4,5,5,5,5,4,2,2,2,3,5,14,11.0,satisfied +35231,89844,Male,Loyal Customer,46,Business travel,Business,2141,2,4,4,4,3,3,4,2,2,3,2,4,2,2,11,51.0,neutral or dissatisfied +35232,66295,Female,disloyal Customer,28,Business travel,Business,852,4,4,4,4,4,4,4,4,3,2,4,3,4,4,0,5.0,satisfied +35233,860,Female,Loyal Customer,56,Business travel,Business,247,3,5,5,5,4,4,4,3,3,4,3,3,3,2,9,5.0,neutral or dissatisfied +35234,33874,Male,Loyal Customer,29,Business travel,Business,3191,3,3,3,3,4,4,4,4,2,5,5,4,5,4,0,0.0,satisfied +35235,74043,Female,Loyal Customer,39,Business travel,Business,1194,1,1,1,1,3,5,4,5,5,5,5,5,5,4,1,0.0,satisfied +35236,120245,Male,Loyal Customer,29,Personal Travel,Eco,1325,1,4,1,1,1,1,2,1,5,4,4,4,4,1,29,35.0,neutral or dissatisfied +35237,38046,Male,Loyal Customer,23,Business travel,Eco,1249,0,5,0,3,1,0,1,1,5,3,5,4,2,1,36,27.0,satisfied +35238,48328,Male,Loyal Customer,47,Business travel,Business,522,1,4,4,4,3,4,4,1,1,1,1,3,1,4,46,36.0,neutral or dissatisfied +35239,75032,Female,Loyal Customer,33,Personal Travel,Eco,236,2,1,2,3,1,2,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +35240,26804,Female,disloyal Customer,16,Business travel,Eco,1077,1,1,1,4,1,1,2,1,1,5,4,4,4,1,6,0.0,neutral or dissatisfied +35241,17437,Female,Loyal Customer,44,Personal Travel,Eco,351,1,4,1,2,3,4,5,5,5,1,5,4,5,5,91,82.0,neutral or dissatisfied +35242,113450,Female,Loyal Customer,24,Business travel,Business,3644,3,5,5,5,3,2,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +35243,127870,Female,Loyal Customer,40,Business travel,Business,1276,4,4,4,4,4,4,5,5,5,5,5,5,5,4,0,24.0,satisfied +35244,13137,Male,Loyal Customer,20,Personal Travel,Eco,562,1,4,1,4,2,1,5,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +35245,99239,Female,Loyal Customer,19,Personal Travel,Eco,495,1,4,1,1,3,1,3,3,3,5,4,3,4,3,7,17.0,neutral or dissatisfied +35246,80816,Male,Loyal Customer,57,Business travel,Business,1635,1,1,2,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +35247,13000,Male,Loyal Customer,58,Business travel,Eco,438,4,4,4,4,4,4,4,4,2,1,5,4,2,4,0,0.0,satisfied +35248,121137,Female,Loyal Customer,20,Business travel,Business,2370,2,2,2,2,3,3,3,3,5,4,5,3,5,3,60,,satisfied +35249,23399,Male,Loyal Customer,20,Personal Travel,Eco,300,4,4,4,3,1,4,1,1,3,4,4,5,5,1,0,0.0,satisfied +35250,35181,Male,disloyal Customer,17,Business travel,Eco,950,4,4,4,1,4,4,5,4,1,1,1,4,4,4,0,0.0,satisfied +35251,54618,Female,Loyal Customer,31,Business travel,Business,3347,4,4,4,4,5,5,5,5,4,4,3,5,4,5,21,5.0,satisfied +35252,16766,Male,Loyal Customer,48,Business travel,Business,3724,2,5,5,5,1,4,4,2,2,2,2,1,2,2,69,76.0,neutral or dissatisfied +35253,25507,Female,Loyal Customer,31,Business travel,Eco,481,3,1,5,5,3,3,3,3,4,4,2,1,3,3,75,64.0,neutral or dissatisfied +35254,94295,Male,Loyal Customer,44,Business travel,Business,248,1,1,1,1,2,4,5,3,3,4,3,5,3,4,1,0.0,satisfied +35255,30798,Male,Loyal Customer,62,Personal Travel,Eco,701,3,5,3,3,1,3,1,1,2,5,2,5,1,1,23,23.0,neutral or dissatisfied +35256,59785,Female,Loyal Customer,57,Personal Travel,Eco,1062,2,4,2,2,3,5,4,5,5,2,5,4,5,3,30,30.0,neutral or dissatisfied +35257,34,Female,Loyal Customer,48,Business travel,Business,173,0,5,0,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +35258,80961,Male,Loyal Customer,55,Business travel,Business,228,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +35259,17180,Male,Loyal Customer,36,Business travel,Eco,243,4,2,2,2,4,4,4,4,3,1,2,3,5,4,0,0.0,satisfied +35260,124681,Male,disloyal Customer,32,Business travel,Business,399,1,1,1,4,5,1,5,5,5,4,5,4,4,5,3,0.0,neutral or dissatisfied +35261,79461,Female,Loyal Customer,31,Business travel,Business,2522,1,0,0,4,0,2,2,1,4,3,3,2,2,2,219,189.0,neutral or dissatisfied +35262,6590,Female,Loyal Customer,38,Personal Travel,Eco,618,4,5,4,3,1,4,5,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +35263,109581,Female,Loyal Customer,48,Personal Travel,Eco,993,5,5,5,2,5,5,4,1,1,5,1,3,1,5,0,0.0,satisfied +35264,126472,Female,Loyal Customer,58,Business travel,Business,1849,3,3,4,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +35265,56806,Male,disloyal Customer,28,Business travel,Eco,1605,3,3,3,4,5,3,5,5,2,1,2,4,3,5,38,25.0,neutral or dissatisfied +35266,11131,Male,Loyal Customer,49,Personal Travel,Eco,301,3,4,3,4,5,3,4,5,5,4,5,3,5,5,1,1.0,neutral or dissatisfied +35267,42442,Male,Loyal Customer,39,Business travel,Business,3267,1,1,1,1,5,5,4,5,5,5,5,5,5,4,0,,satisfied +35268,65719,Female,Loyal Customer,55,Business travel,Business,3389,3,3,3,3,4,5,4,5,5,5,5,5,5,5,7,0.0,satisfied +35269,3700,Male,Loyal Customer,68,Business travel,Eco,431,1,2,2,2,1,1,1,1,4,5,3,4,3,1,2,0.0,neutral or dissatisfied +35270,98850,Male,Loyal Customer,64,Personal Travel,Business,1751,1,3,2,3,1,3,4,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +35271,107744,Male,Loyal Customer,55,Personal Travel,Eco,466,1,4,1,2,1,4,4,3,3,4,4,4,3,4,136,,neutral or dissatisfied +35272,114187,Male,Loyal Customer,46,Business travel,Business,862,1,5,1,1,5,5,5,5,5,5,5,4,5,3,53,50.0,satisfied +35273,112498,Female,Loyal Customer,62,Personal Travel,Eco,850,5,3,5,4,2,5,2,5,5,3,5,4,5,3,0,0.0,satisfied +35274,1577,Female,disloyal Customer,22,Business travel,Business,140,5,0,5,1,5,5,4,5,4,2,5,4,4,5,0,5.0,satisfied +35275,126528,Male,Loyal Customer,40,Business travel,Business,644,5,5,5,5,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +35276,107062,Female,Loyal Customer,56,Personal Travel,Eco,480,2,3,2,3,5,3,4,3,3,2,4,1,3,2,10,0.0,neutral or dissatisfied +35277,111847,Male,Loyal Customer,31,Business travel,Business,628,1,1,5,1,5,5,5,5,4,5,5,4,5,5,1,0.0,satisfied +35278,40753,Male,Loyal Customer,27,Business travel,Business,1563,3,3,3,3,4,4,4,4,1,1,1,5,5,4,0,0.0,satisfied +35279,85024,Male,Loyal Customer,56,Personal Travel,Eco,1590,3,5,3,2,1,3,1,1,3,3,4,5,5,1,6,0.0,neutral or dissatisfied +35280,26267,Male,Loyal Customer,40,Business travel,Eco,859,5,1,1,1,5,5,5,5,2,3,5,1,1,5,0,0.0,satisfied +35281,72038,Male,Loyal Customer,43,Business travel,Business,3784,2,2,4,2,4,4,4,3,4,3,4,4,5,4,0,0.0,satisfied +35282,100796,Female,Loyal Customer,46,Business travel,Business,748,1,1,1,1,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +35283,39665,Male,Loyal Customer,54,Business travel,Eco,476,4,1,1,1,3,4,3,3,1,4,3,2,2,3,117,118.0,satisfied +35284,87607,Female,Loyal Customer,56,Business travel,Business,3078,3,2,3,3,5,4,5,5,5,5,5,4,5,4,13,0.0,satisfied +35285,56458,Male,Loyal Customer,14,Personal Travel,Eco,719,4,4,4,3,4,4,4,4,4,3,5,3,5,4,21,23.0,neutral or dissatisfied +35286,127843,Female,Loyal Customer,43,Personal Travel,Eco Plus,1262,2,4,2,2,2,4,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +35287,90314,Male,Loyal Customer,14,Personal Travel,Eco Plus,757,4,4,4,3,4,4,3,4,4,5,4,4,4,4,3,0.0,neutral or dissatisfied +35288,14588,Female,Loyal Customer,51,Business travel,Eco,586,2,4,4,4,1,4,4,2,2,2,2,2,2,2,7,43.0,neutral or dissatisfied +35289,38309,Male,Loyal Customer,55,Personal Travel,Eco,2342,3,2,3,3,2,3,2,2,2,4,2,3,2,2,0,110.0,neutral or dissatisfied +35290,90554,Male,disloyal Customer,34,Business travel,Eco,406,2,1,2,2,3,2,3,3,3,5,3,2,2,3,3,8.0,neutral or dissatisfied +35291,84215,Female,Loyal Customer,47,Business travel,Business,2758,4,5,5,5,5,3,2,4,4,4,4,4,4,3,0,7.0,neutral or dissatisfied +35292,109927,Female,Loyal Customer,59,Personal Travel,Eco,1073,4,4,4,3,4,4,4,3,3,4,3,3,3,4,21,8.0,neutral or dissatisfied +35293,35588,Female,Loyal Customer,22,Business travel,Eco Plus,950,3,4,4,4,3,4,4,3,3,2,5,1,2,3,42,45.0,satisfied +35294,128829,Female,disloyal Customer,30,Business travel,Eco,2586,2,2,2,3,2,1,1,2,2,4,3,1,3,1,0,6.0,neutral or dissatisfied +35295,30915,Female,Loyal Customer,22,Business travel,Eco,896,4,4,4,4,4,4,3,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +35296,126062,Female,Loyal Customer,57,Business travel,Business,631,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,6.0,satisfied +35297,9227,Male,Loyal Customer,53,Business travel,Eco,100,2,4,3,4,2,2,2,2,1,2,3,2,4,2,89,88.0,neutral or dissatisfied +35298,106955,Male,Loyal Customer,47,Business travel,Business,972,2,2,2,2,3,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +35299,8612,Female,Loyal Customer,45,Business travel,Business,1371,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +35300,56918,Female,Loyal Customer,29,Business travel,Business,2425,2,2,2,2,2,2,2,3,4,4,5,2,5,2,25,25.0,satisfied +35301,62950,Female,Loyal Customer,46,Business travel,Business,967,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +35302,43665,Female,Loyal Customer,28,Business travel,Eco,700,4,1,5,5,4,4,4,4,4,4,5,1,2,4,0,0.0,satisfied +35303,55252,Male,Loyal Customer,53,Personal Travel,Eco,1009,2,3,2,1,1,2,1,1,4,2,3,2,1,1,29,13.0,neutral or dissatisfied +35304,40482,Female,Loyal Customer,13,Personal Travel,Eco,188,3,4,3,4,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +35305,101066,Male,Loyal Customer,43,Personal Travel,Eco,368,3,5,3,3,5,3,5,5,5,5,4,2,4,5,0,0.0,neutral or dissatisfied +35306,8462,Female,Loyal Customer,61,Personal Travel,Eco,1379,4,4,4,2,5,4,4,3,3,4,3,4,3,3,71,58.0,neutral or dissatisfied +35307,57617,Male,Loyal Customer,42,Business travel,Business,2965,1,1,1,1,3,5,5,5,5,5,5,4,5,5,2,0.0,satisfied +35308,45012,Female,Loyal Customer,29,Personal Travel,Eco,222,1,2,1,3,1,1,1,1,2,3,3,3,2,1,0,0.0,neutral or dissatisfied +35309,247,Male,Loyal Customer,11,Business travel,Business,719,4,1,1,1,4,4,4,4,4,3,4,4,3,4,38,,neutral or dissatisfied +35310,128443,Female,Loyal Customer,63,Business travel,Business,370,5,5,5,5,1,4,2,5,5,5,5,3,5,3,2,0.0,satisfied +35311,111596,Female,disloyal Customer,27,Business travel,Business,359,3,3,3,1,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +35312,60271,Female,Loyal Customer,53,Business travel,Business,2583,3,3,3,3,2,2,2,4,4,4,5,2,5,2,91,108.0,satisfied +35313,8625,Female,Loyal Customer,56,Business travel,Business,2778,4,4,4,4,2,5,4,4,4,4,4,5,4,3,25,30.0,satisfied +35314,116749,Female,Loyal Customer,19,Personal Travel,Eco Plus,342,4,3,4,3,2,4,2,2,3,1,3,2,2,2,0,0.0,satisfied +35315,28845,Male,disloyal Customer,35,Business travel,Eco,697,2,2,2,3,3,2,3,3,3,3,1,5,1,3,76,82.0,neutral or dissatisfied +35316,117768,Female,Loyal Customer,59,Personal Travel,Eco,1670,2,4,2,3,4,3,4,3,3,2,4,2,3,3,4,0.0,neutral or dissatisfied +35317,76353,Male,Loyal Customer,59,Business travel,Eco,1851,1,5,5,5,1,1,1,1,1,3,1,3,3,1,0,5.0,neutral or dissatisfied +35318,77626,Male,Loyal Customer,30,Business travel,Business,731,3,3,3,3,5,5,5,5,3,4,5,3,5,5,0,0.0,satisfied +35319,34444,Male,disloyal Customer,24,Business travel,Eco,228,2,2,2,3,2,2,2,2,3,4,3,4,2,2,116,118.0,neutral or dissatisfied +35320,66929,Male,Loyal Customer,41,Business travel,Business,1119,3,3,3,3,3,4,5,4,4,5,4,3,4,4,34,26.0,satisfied +35321,24385,Male,Loyal Customer,59,Business travel,Eco,669,4,1,1,1,3,4,3,3,2,2,4,1,3,3,0,16.0,neutral or dissatisfied +35322,120596,Female,Loyal Customer,54,Personal Travel,Eco,980,2,4,2,1,2,4,5,3,3,2,1,4,3,4,0,0.0,neutral or dissatisfied +35323,52924,Female,Loyal Customer,46,Business travel,Eco,279,4,1,1,1,3,4,3,4,4,4,4,1,4,1,27,10.0,neutral or dissatisfied +35324,22473,Female,Loyal Customer,61,Personal Travel,Eco,145,3,5,3,4,3,2,3,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +35325,33374,Female,Loyal Customer,51,Personal Travel,Eco,2355,1,4,1,4,5,4,4,4,4,1,4,1,4,2,13,0.0,neutral or dissatisfied +35326,64386,Female,Loyal Customer,66,Personal Travel,Eco,1158,2,5,2,3,2,3,5,3,3,2,3,4,3,5,23,11.0,neutral or dissatisfied +35327,16880,Male,disloyal Customer,23,Business travel,Eco,708,2,2,2,3,5,2,5,5,1,3,3,4,3,5,67,60.0,neutral or dissatisfied +35328,35653,Male,Loyal Customer,29,Business travel,Eco,2586,4,2,5,2,4,4,4,4,4,5,2,4,3,4,0,0.0,satisfied +35329,106221,Male,Loyal Customer,33,Business travel,Business,471,1,3,1,1,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +35330,1059,Male,Loyal Customer,25,Personal Travel,Eco,229,2,2,0,3,4,0,4,4,2,3,3,3,3,4,0,0.0,neutral or dissatisfied +35331,124390,Male,Loyal Customer,53,Personal Travel,Eco,575,4,5,4,3,3,4,3,3,5,4,4,3,4,3,0,3.0,neutral or dissatisfied +35332,4596,Female,Loyal Customer,26,Personal Travel,Eco,416,3,5,1,3,1,1,5,1,3,1,3,2,5,1,0,6.0,neutral or dissatisfied +35333,97406,Female,Loyal Customer,58,Business travel,Business,1987,1,1,1,1,4,4,5,5,5,4,5,4,5,3,1,0.0,satisfied +35334,84341,Female,Loyal Customer,48,Business travel,Business,3893,4,4,1,4,4,4,4,4,4,4,5,4,4,4,122,139.0,satisfied +35335,38146,Male,Loyal Customer,47,Personal Travel,Eco,1121,1,5,1,1,1,4,5,4,3,4,5,5,4,5,141,123.0,neutral or dissatisfied +35336,28968,Male,Loyal Customer,28,Business travel,Eco,956,4,4,4,4,4,4,4,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +35337,93578,Female,disloyal Customer,29,Business travel,Eco,159,4,2,4,4,5,4,5,5,1,5,3,3,3,5,67,83.0,neutral or dissatisfied +35338,63811,Female,Loyal Customer,64,Business travel,Business,2724,3,3,4,3,4,5,4,5,5,5,5,5,5,4,20,17.0,satisfied +35339,96916,Male,Loyal Customer,46,Personal Travel,Eco,957,3,5,3,3,4,3,4,4,5,2,5,5,5,4,2,8.0,neutral or dissatisfied +35340,69754,Female,Loyal Customer,47,Personal Travel,Eco,1085,1,4,1,3,2,5,4,3,3,1,4,3,3,4,0,,neutral or dissatisfied +35341,12849,Male,Loyal Customer,41,Personal Travel,Eco,817,1,1,1,1,5,1,5,5,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +35342,57950,Male,Loyal Customer,28,Business travel,Business,1062,3,5,5,5,3,3,3,3,1,3,3,3,2,3,23,7.0,neutral or dissatisfied +35343,85296,Female,Loyal Customer,61,Personal Travel,Eco,689,1,4,0,2,2,5,4,4,4,0,4,1,4,3,32,41.0,neutral or dissatisfied +35344,64376,Male,Loyal Customer,60,Personal Travel,Eco,1172,3,5,3,4,3,3,3,3,5,3,4,3,4,3,12,6.0,neutral or dissatisfied +35345,2208,Female,Loyal Customer,45,Business travel,Business,624,5,5,5,5,4,4,5,3,3,3,3,5,3,3,75,75.0,satisfied +35346,115092,Male,Loyal Customer,39,Business travel,Business,342,5,5,4,5,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +35347,120012,Male,Loyal Customer,65,Personal Travel,Eco,328,2,5,4,3,3,4,1,3,3,4,3,5,4,3,0,9.0,neutral or dissatisfied +35348,10890,Female,Loyal Customer,40,Business travel,Business,3718,4,3,3,3,5,4,3,4,4,4,4,4,4,4,4,10.0,neutral or dissatisfied +35349,17816,Female,Loyal Customer,29,Personal Travel,Eco,1075,3,3,3,4,1,3,1,1,5,4,3,5,1,1,6,0.0,neutral or dissatisfied +35350,57791,Female,Loyal Customer,40,Business travel,Business,2704,3,3,2,3,5,5,5,3,2,5,4,5,5,5,7,0.0,satisfied +35351,112132,Female,Loyal Customer,13,Personal Travel,Business,895,2,2,2,4,1,2,1,1,3,1,3,2,4,1,0,0.0,neutral or dissatisfied +35352,95303,Female,Loyal Customer,43,Personal Travel,Eco,293,1,3,1,3,2,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +35353,32772,Male,Loyal Customer,76,Business travel,Eco,84,4,5,5,5,4,4,4,4,2,5,4,1,4,4,0,0.0,satisfied +35354,22485,Female,Loyal Customer,38,Personal Travel,Eco,145,3,4,3,4,4,3,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +35355,71855,Male,Loyal Customer,60,Business travel,Business,346,0,0,0,4,2,1,5,2,2,2,1,1,2,1,0,0.0,satisfied +35356,75418,Male,Loyal Customer,58,Business travel,Business,2585,5,5,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +35357,76985,Male,disloyal Customer,39,Business travel,Business,368,2,2,2,1,3,2,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +35358,104715,Female,Loyal Customer,48,Personal Travel,Business,1246,1,5,1,1,4,3,5,1,1,1,1,5,1,4,15,19.0,neutral or dissatisfied +35359,124628,Female,Loyal Customer,16,Personal Travel,Eco,1671,2,2,1,3,4,1,4,4,3,3,4,2,3,4,0,0.0,neutral or dissatisfied +35360,83537,Male,Loyal Customer,47,Business travel,Business,1771,1,1,1,1,5,4,5,4,4,5,4,4,4,5,0,17.0,satisfied +35361,21632,Female,Loyal Customer,14,Personal Travel,Eco,794,3,5,3,3,3,3,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +35362,39189,Female,Loyal Customer,37,Business travel,Eco Plus,237,4,4,4,4,4,4,4,4,1,5,1,4,5,4,4,0.0,satisfied +35363,113098,Female,Loyal Customer,42,Personal Travel,Eco,569,3,4,3,4,4,4,3,3,3,3,2,4,3,1,9,0.0,neutral or dissatisfied +35364,52031,Female,Loyal Customer,33,Personal Travel,Eco,328,2,2,5,4,3,5,3,3,1,1,4,4,4,3,0,10.0,neutral or dissatisfied +35365,121781,Female,disloyal Customer,38,Business travel,Business,449,4,4,4,4,3,4,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +35366,40492,Male,Loyal Customer,18,Personal Travel,Eco,175,3,4,0,3,5,0,2,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +35367,124539,Female,Loyal Customer,47,Business travel,Business,1276,1,4,3,4,1,4,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +35368,35420,Female,Loyal Customer,51,Personal Travel,Eco,944,0,3,0,4,1,3,2,3,3,0,3,2,3,2,0,0.0,satisfied +35369,23618,Female,Loyal Customer,25,Business travel,Business,2857,5,5,4,5,5,5,5,5,1,4,4,5,5,5,36,61.0,satisfied +35370,111317,Male,disloyal Customer,32,Business travel,Business,283,2,2,2,3,2,2,1,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +35371,5310,Male,Loyal Customer,33,Business travel,Business,285,1,1,1,1,5,5,5,5,4,2,4,5,5,5,1,0.0,satisfied +35372,5613,Male,Loyal Customer,39,Business travel,Business,2565,2,1,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +35373,122530,Female,Loyal Customer,50,Business travel,Business,500,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +35374,71288,Female,Loyal Customer,41,Business travel,Business,3580,1,1,1,1,5,5,5,5,5,5,5,3,5,4,6,0.0,satisfied +35375,120187,Male,Loyal Customer,27,Business travel,Business,1430,2,2,4,2,4,4,4,4,4,2,4,5,4,4,0,4.0,satisfied +35376,35210,Female,disloyal Customer,22,Business travel,Eco,1102,4,4,4,4,3,4,3,3,4,2,1,2,5,3,0,0.0,satisfied +35377,91051,Female,Loyal Customer,69,Personal Travel,Eco,406,4,5,4,4,2,4,5,2,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +35378,117601,Female,Loyal Customer,45,Business travel,Eco,872,2,5,5,5,5,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +35379,41023,Female,Loyal Customer,44,Business travel,Eco,989,4,2,2,2,1,4,5,3,3,4,3,5,3,1,0,0.0,satisfied +35380,121595,Male,Loyal Customer,70,Personal Travel,Eco,912,2,5,2,5,5,2,4,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +35381,83353,Female,disloyal Customer,46,Business travel,Business,1124,3,3,3,4,4,3,4,4,5,5,5,5,4,4,0,54.0,neutral or dissatisfied +35382,3655,Male,Loyal Customer,57,Business travel,Business,427,5,5,5,5,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +35383,53527,Male,Loyal Customer,35,Personal Travel,Eco,2288,1,1,0,4,2,0,2,2,2,3,3,4,4,2,0,0.0,neutral or dissatisfied +35384,18653,Female,Loyal Customer,39,Personal Travel,Eco,253,2,3,2,1,1,2,1,1,2,4,4,1,1,1,0,34.0,neutral or dissatisfied +35385,9234,Female,Loyal Customer,57,Business travel,Business,157,2,2,2,2,2,4,4,1,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +35386,10463,Male,Loyal Customer,37,Business travel,Business,140,3,4,4,4,3,3,4,1,1,1,3,3,1,4,95,89.0,neutral or dissatisfied +35387,112725,Male,Loyal Customer,9,Personal Travel,Eco,671,1,5,1,1,3,1,3,3,2,2,3,1,5,3,19,17.0,neutral or dissatisfied +35388,36177,Female,Loyal Customer,53,Personal Travel,Eco,1674,4,1,4,1,5,2,1,1,1,4,1,1,1,3,9,8.0,neutral or dissatisfied +35389,81232,Female,Loyal Customer,46,Personal Travel,Eco,449,5,5,5,2,2,4,5,2,2,5,2,5,2,3,0,0.0,satisfied +35390,92676,Female,Loyal Customer,60,Business travel,Business,2096,5,5,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +35391,57556,Female,Loyal Customer,43,Business travel,Business,1597,4,4,4,4,2,3,5,4,4,4,4,3,4,4,29,9.0,satisfied +35392,79832,Female,disloyal Customer,23,Business travel,Business,1005,4,5,4,3,3,4,3,3,5,2,5,5,4,3,0,0.0,satisfied +35393,73914,Female,disloyal Customer,46,Business travel,Business,1011,5,5,5,3,4,5,4,4,4,5,5,4,4,4,14,19.0,satisfied +35394,13501,Male,Loyal Customer,44,Business travel,Eco,227,5,3,3,3,5,5,5,5,3,1,1,5,2,5,0,0.0,satisfied +35395,126117,Female,disloyal Customer,39,Business travel,Business,328,2,2,2,3,2,2,2,2,3,3,4,3,4,2,16,21.0,neutral or dissatisfied +35396,25765,Female,Loyal Customer,43,Business travel,Eco Plus,356,2,2,2,2,2,4,4,2,2,2,2,3,2,2,6,0.0,neutral or dissatisfied +35397,41760,Female,disloyal Customer,25,Business travel,Eco,491,2,0,1,4,4,1,4,4,5,1,3,5,5,4,4,17.0,neutral or dissatisfied +35398,122691,Male,Loyal Customer,15,Business travel,Business,361,1,1,1,1,1,1,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +35399,63775,Male,Loyal Customer,43,Business travel,Business,1721,2,2,5,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +35400,26959,Female,Loyal Customer,61,Personal Travel,Business,867,4,3,4,3,2,4,4,4,4,4,5,3,4,3,0,5.0,satisfied +35401,74433,Male,Loyal Customer,50,Business travel,Business,2000,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +35402,78166,Female,Loyal Customer,50,Business travel,Business,1856,5,2,5,5,4,5,4,4,4,4,5,4,4,4,0,17.0,satisfied +35403,1969,Male,Loyal Customer,60,Personal Travel,Eco,295,2,3,2,2,3,2,3,3,4,1,2,3,3,3,11,15.0,neutral or dissatisfied +35404,106581,Female,Loyal Customer,39,Business travel,Business,333,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,9.0,satisfied +35405,10824,Male,Loyal Customer,16,Business travel,Business,3939,3,4,4,4,5,4,3,5,4,1,3,3,4,5,0,0.0,neutral or dissatisfied +35406,128830,Male,Loyal Customer,60,Business travel,Business,2586,2,1,1,1,2,2,2,1,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +35407,91126,Male,Loyal Customer,65,Personal Travel,Eco,545,1,3,1,2,4,1,4,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +35408,9957,Male,Loyal Customer,24,Business travel,Eco,534,3,4,4,4,3,3,1,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +35409,53902,Male,Loyal Customer,24,Personal Travel,Eco,191,4,4,4,1,2,4,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +35410,24787,Female,Loyal Customer,22,Personal Travel,Eco,447,3,5,3,3,3,3,3,3,5,4,4,3,2,3,0,0.0,neutral or dissatisfied +35411,72727,Male,Loyal Customer,49,Business travel,Eco Plus,585,4,4,4,4,4,4,4,4,2,5,2,4,4,4,0,0.0,satisfied +35412,35993,Female,Loyal Customer,16,Personal Travel,Eco,2496,4,5,4,2,4,5,5,3,4,5,5,5,4,5,1,1.0,neutral or dissatisfied +35413,9690,Female,Loyal Customer,40,Business travel,Eco,212,2,4,4,4,2,2,2,2,3,5,5,1,2,2,0,6.0,satisfied +35414,54952,Female,Loyal Customer,53,Business travel,Business,1530,1,1,1,1,4,5,5,4,4,4,4,4,4,5,16,0.0,satisfied +35415,129472,Male,Loyal Customer,48,Business travel,Business,2704,5,5,5,5,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +35416,48420,Female,Loyal Customer,35,Business travel,Business,3809,4,4,2,4,3,5,3,5,5,5,5,2,5,1,13,5.0,satisfied +35417,94701,Female,disloyal Customer,37,Business travel,Eco,248,4,3,4,3,2,4,2,2,4,1,3,2,4,2,17,18.0,neutral or dissatisfied +35418,73996,Female,disloyal Customer,40,Business travel,Business,1972,1,1,1,4,3,1,3,3,1,5,3,2,3,3,2,9.0,neutral or dissatisfied +35419,52525,Male,Loyal Customer,42,Business travel,Business,110,1,1,1,1,2,3,2,5,5,5,4,1,5,2,0,0.0,satisfied +35420,8477,Male,Loyal Customer,24,Business travel,Business,1187,3,1,1,1,3,3,3,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +35421,24147,Male,Loyal Customer,45,Business travel,Business,134,0,3,0,1,1,2,2,4,4,2,2,1,4,3,0,0.0,satisfied +35422,121188,Male,Loyal Customer,68,Personal Travel,Eco,2521,2,2,2,2,2,2,2,2,5,3,2,2,1,2,0,0.0,neutral or dissatisfied +35423,64632,Male,disloyal Customer,49,Business travel,Business,190,5,5,5,4,1,5,1,1,5,3,5,5,4,1,0,0.0,satisfied +35424,98243,Female,Loyal Customer,49,Business travel,Business,2816,1,1,1,1,3,4,4,5,5,5,5,4,5,4,7,0.0,satisfied +35425,42925,Male,Loyal Customer,25,Business travel,Eco Plus,628,5,2,2,2,5,5,4,5,2,2,1,4,3,5,0,2.0,satisfied +35426,35610,Male,Loyal Customer,67,Personal Travel,Eco Plus,1097,1,4,1,4,5,1,3,5,4,5,5,5,5,5,0,1.0,neutral or dissatisfied +35427,18110,Female,disloyal Customer,22,Business travel,Eco,629,5,0,5,5,2,5,2,2,3,1,5,4,1,2,0,0.0,satisfied +35428,54079,Male,Loyal Customer,36,Business travel,Eco,1016,2,5,5,5,2,1,2,2,4,4,4,3,4,2,10,0.0,neutral or dissatisfied +35429,63481,Male,Loyal Customer,40,Personal Travel,Eco Plus,337,3,5,3,3,1,3,2,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +35430,6995,Male,Loyal Customer,59,Business travel,Business,3762,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +35431,43075,Male,Loyal Customer,19,Personal Travel,Eco,236,3,5,0,3,4,0,4,4,3,3,4,2,5,4,6,9.0,neutral or dissatisfied +35432,77806,Male,Loyal Customer,52,Personal Travel,Eco,874,3,1,2,2,2,5,5,4,5,3,2,5,2,5,264,288.0,neutral or dissatisfied +35433,4646,Female,Loyal Customer,25,Business travel,Business,3787,1,1,1,1,4,4,4,4,4,5,5,5,5,4,0,1.0,satisfied +35434,52845,Female,Loyal Customer,52,Personal Travel,Eco,1721,2,5,2,4,2,4,4,3,3,4,4,4,5,4,302,314.0,neutral or dissatisfied +35435,26466,Male,Loyal Customer,52,Personal Travel,Eco,842,2,5,3,3,4,3,4,4,5,5,4,4,1,4,7,0.0,neutral or dissatisfied +35436,118131,Male,disloyal Customer,46,Business travel,Business,1488,2,2,2,5,1,2,3,1,5,3,4,5,5,1,2,0.0,satisfied +35437,49654,Female,Loyal Customer,36,Business travel,Business,266,0,0,0,3,3,3,3,5,5,5,5,2,5,4,0,0.0,satisfied +35438,47348,Female,Loyal Customer,44,Business travel,Eco,558,2,4,4,4,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +35439,127827,Female,Loyal Customer,37,Personal Travel,Eco,1262,3,5,3,2,1,3,1,1,3,2,3,5,5,1,0,23.0,neutral or dissatisfied +35440,128360,Female,Loyal Customer,33,Business travel,Business,338,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +35441,70866,Female,Loyal Customer,12,Personal Travel,Eco,761,2,4,2,4,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +35442,29169,Female,disloyal Customer,26,Business travel,Eco Plus,697,3,3,3,4,3,3,3,3,5,1,3,5,5,3,48,45.0,neutral or dissatisfied +35443,22424,Male,Loyal Customer,15,Personal Travel,Eco,208,5,3,5,2,1,5,1,1,3,3,2,4,4,1,0,0.0,satisfied +35444,102278,Male,Loyal Customer,52,Business travel,Business,197,2,2,2,2,1,4,3,2,2,2,2,1,2,2,23,14.0,neutral or dissatisfied +35445,36237,Female,Loyal Customer,58,Business travel,Eco Plus,496,4,2,4,2,2,2,2,4,4,4,4,3,4,1,0,43.0,satisfied +35446,115519,Female,Loyal Customer,41,Business travel,Business,3950,3,3,3,3,3,4,5,4,4,4,4,4,4,4,4,2.0,satisfied +35447,114291,Female,Loyal Customer,19,Personal Travel,Eco,862,3,5,4,3,5,4,5,5,4,2,5,4,5,5,15,0.0,neutral or dissatisfied +35448,125449,Female,disloyal Customer,30,Business travel,Business,2845,3,3,3,1,3,3,3,3,3,2,4,3,4,3,22,1.0,neutral or dissatisfied +35449,25788,Male,Loyal Customer,36,Business travel,Business,3616,3,3,3,3,4,4,4,5,5,5,5,4,5,1,1,0.0,satisfied +35450,5222,Male,Loyal Customer,39,Business travel,Business,2608,3,3,3,3,3,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +35451,20749,Female,Loyal Customer,23,Personal Travel,Eco,363,2,5,2,4,5,2,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +35452,78358,Female,disloyal Customer,29,Business travel,Eco,1290,3,3,3,3,1,3,1,1,1,5,4,2,3,1,12,14.0,neutral or dissatisfied +35453,74362,Male,Loyal Customer,24,Business travel,Eco,1126,3,1,1,1,3,3,1,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +35454,93010,Female,Loyal Customer,37,Business travel,Business,1524,5,5,5,5,4,5,5,5,5,5,5,4,5,5,11,21.0,satisfied +35455,2194,Male,Loyal Customer,47,Personal Travel,Eco,624,1,5,2,3,4,2,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +35456,56520,Male,Loyal Customer,51,Business travel,Business,1945,3,3,3,3,2,4,5,4,4,4,4,3,4,3,0,15.0,satisfied +35457,5905,Female,Loyal Customer,59,Business travel,Business,215,1,5,5,5,4,3,3,3,3,3,1,3,3,1,18,13.0,neutral or dissatisfied +35458,111904,Female,Loyal Customer,33,Personal Travel,Eco,804,4,4,4,4,3,4,3,3,2,2,3,2,5,3,10,0.0,neutral or dissatisfied +35459,90357,Female,disloyal Customer,61,Business travel,Business,271,3,3,3,4,2,3,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +35460,65685,Male,Loyal Customer,42,Personal Travel,Eco,926,2,2,2,4,1,2,1,1,4,5,3,4,4,1,50,54.0,neutral or dissatisfied +35461,20973,Male,Loyal Customer,70,Personal Travel,Eco,721,1,3,1,3,1,1,1,1,3,3,1,4,5,1,0,0.0,neutral or dissatisfied +35462,107714,Male,disloyal Customer,26,Business travel,Eco,251,1,1,1,3,1,1,1,1,1,3,3,2,3,1,3,13.0,neutral or dissatisfied +35463,116310,Male,Loyal Customer,33,Personal Travel,Eco,296,2,5,2,3,5,2,5,5,4,4,4,5,5,5,6,0.0,neutral or dissatisfied +35464,19721,Female,Loyal Customer,53,Personal Travel,Eco,409,3,4,3,2,2,4,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +35465,42581,Male,Loyal Customer,29,Personal Travel,Eco,315,1,5,1,1,3,1,3,3,4,5,4,5,4,3,39,40.0,neutral or dissatisfied +35466,17480,Male,Loyal Customer,28,Business travel,Business,2425,3,3,3,3,5,4,5,5,4,3,5,5,1,5,0,0.0,satisfied +35467,25303,Male,disloyal Customer,24,Business travel,Eco,432,4,0,3,4,4,3,3,4,4,1,4,3,1,4,4,0.0,neutral or dissatisfied +35468,88426,Female,Loyal Customer,66,Business travel,Eco,594,3,1,5,5,4,3,3,3,3,3,3,3,3,1,61,50.0,neutral or dissatisfied +35469,38118,Female,Loyal Customer,38,Business travel,Business,1249,3,4,5,5,4,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +35470,96826,Male,disloyal Customer,27,Business travel,Eco,928,1,1,1,4,4,1,4,4,3,3,4,4,4,4,127,116.0,neutral or dissatisfied +35471,122335,Female,Loyal Customer,62,Personal Travel,Eco Plus,541,2,5,2,1,3,4,4,4,4,2,2,5,4,4,0,6.0,neutral or dissatisfied +35472,85903,Female,disloyal Customer,22,Business travel,Eco,761,1,1,1,4,2,1,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +35473,46053,Male,Loyal Customer,58,Personal Travel,Eco,964,2,4,2,3,4,2,3,4,3,2,4,5,4,4,113,112.0,neutral or dissatisfied +35474,108634,Female,Loyal Customer,49,Personal Travel,Eco,1547,2,5,2,5,4,3,4,5,5,2,5,3,5,4,0,23.0,neutral or dissatisfied +35475,15568,Male,Loyal Customer,31,Business travel,Eco,283,5,2,2,2,5,5,5,5,3,3,4,3,1,5,34,38.0,satisfied +35476,18346,Male,Loyal Customer,50,Personal Travel,Eco,563,2,4,2,4,2,2,1,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +35477,88845,Male,Loyal Customer,59,Personal Travel,Eco Plus,646,2,3,2,3,4,2,4,4,5,4,2,3,2,4,0,0.0,neutral or dissatisfied +35478,20473,Female,disloyal Customer,39,Business travel,Business,177,3,3,3,3,3,3,1,3,5,3,2,4,2,3,0,0.0,neutral or dissatisfied +35479,54357,Female,disloyal Customer,24,Business travel,Eco,1235,4,4,4,4,4,3,3,1,4,3,4,3,4,3,167,139.0,neutral or dissatisfied +35480,92510,Female,Loyal Customer,30,Personal Travel,Eco,2116,1,1,1,4,2,1,3,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +35481,61075,Female,Loyal Customer,45,Business travel,Eco,1607,3,5,3,5,4,4,4,3,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +35482,121751,Male,disloyal Customer,23,Business travel,Eco,449,3,0,3,1,1,3,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +35483,42749,Male,Loyal Customer,45,Business travel,Business,3576,4,4,4,4,5,5,4,4,4,4,5,5,4,4,0,0.0,satisfied +35484,124221,Female,Loyal Customer,53,Business travel,Business,1916,5,5,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +35485,122433,Male,disloyal Customer,22,Business travel,Eco,416,5,0,4,2,1,4,1,1,1,2,2,2,4,1,0,0.0,satisfied +35486,76941,Male,disloyal Customer,25,Business travel,Business,1990,5,0,5,4,4,5,5,4,3,4,5,3,5,4,13,20.0,satisfied +35487,40675,Female,Loyal Customer,57,Personal Travel,Business,584,3,4,4,4,4,5,4,4,4,4,4,3,4,4,38,17.0,neutral or dissatisfied +35488,82507,Male,disloyal Customer,30,Business travel,Business,1117,4,4,4,3,1,4,1,1,5,2,4,3,4,1,0,0.0,satisfied +35489,45933,Male,Loyal Customer,45,Personal Travel,Eco,809,1,5,1,3,1,1,1,1,2,5,4,3,1,1,0,0.0,neutral or dissatisfied +35490,53635,Male,Loyal Customer,8,Personal Travel,Eco,1874,3,2,3,3,3,3,3,3,3,4,3,2,3,3,22,28.0,neutral or dissatisfied +35491,128267,Female,disloyal Customer,44,Business travel,Business,370,5,5,5,5,5,5,5,5,4,5,5,3,4,5,14,8.0,satisfied +35492,90866,Female,Loyal Customer,35,Business travel,Eco,581,3,4,4,4,3,3,3,3,4,5,4,3,4,3,11,8.0,neutral or dissatisfied +35493,111959,Male,Loyal Customer,52,Business travel,Business,770,4,4,4,4,5,4,4,5,5,5,5,3,5,4,17,19.0,satisfied +35494,117135,Male,disloyal Customer,56,Personal Travel,Eco,369,0,2,0,4,3,0,3,3,1,5,3,3,4,3,0,0.0,satisfied +35495,32032,Female,Loyal Customer,30,Business travel,Business,2813,5,5,5,5,4,4,5,4,3,5,1,2,3,4,0,3.0,satisfied +35496,78827,Female,Loyal Customer,22,Personal Travel,Eco,528,2,4,2,2,3,2,3,3,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +35497,4404,Male,Loyal Customer,65,Personal Travel,Eco Plus,618,4,4,4,3,5,4,5,5,4,2,5,5,4,5,0,0.0,satisfied +35498,89058,Male,Loyal Customer,31,Business travel,Business,1947,4,4,3,4,5,5,5,5,4,2,4,3,4,5,0,17.0,satisfied +35499,16717,Female,Loyal Customer,30,Business travel,Eco Plus,284,3,4,4,4,3,3,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +35500,68332,Male,Loyal Customer,67,Personal Travel,Eco,2165,3,4,4,3,1,4,1,1,4,1,3,1,3,1,0,0.0,neutral or dissatisfied +35501,21316,Male,Loyal Customer,46,Business travel,Eco Plus,714,4,4,4,4,4,4,4,4,5,1,2,4,5,4,8,,satisfied +35502,19915,Female,Loyal Customer,58,Business travel,Business,3749,0,0,0,3,4,4,4,3,3,1,2,4,3,4,212,217.0,satisfied +35503,31539,Male,Loyal Customer,19,Personal Travel,Eco,862,1,4,1,3,4,1,4,4,3,2,5,5,5,4,26,9.0,neutral or dissatisfied +35504,32740,Female,Loyal Customer,52,Business travel,Eco,163,1,0,0,4,1,3,4,1,1,1,1,2,1,3,1,6.0,neutral or dissatisfied +35505,36757,Female,disloyal Customer,27,Business travel,Eco,1341,1,1,1,4,1,2,2,5,1,4,5,2,4,2,0,3.0,neutral or dissatisfied +35506,22779,Female,Loyal Customer,46,Business travel,Business,302,3,3,3,3,4,4,5,5,5,5,5,2,5,2,0,4.0,satisfied +35507,11030,Male,Loyal Customer,30,Business travel,Business,2360,3,3,3,3,3,5,3,3,3,3,2,4,5,3,0,0.0,satisfied +35508,110306,Female,Loyal Customer,39,Business travel,Business,2162,2,4,4,4,2,3,4,2,2,2,2,1,2,3,78,61.0,neutral or dissatisfied +35509,107112,Male,disloyal Customer,22,Business travel,Eco,842,2,2,2,3,1,2,1,1,5,2,5,3,5,1,24,13.0,neutral or dissatisfied +35510,81584,Male,Loyal Customer,54,Personal Travel,Eco,503,2,4,2,1,5,2,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +35511,64574,Female,Loyal Customer,46,Business travel,Business,2713,5,5,5,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +35512,32568,Female,Loyal Customer,51,Business travel,Eco,102,5,3,3,3,5,1,2,4,4,5,4,1,4,3,0,0.0,satisfied +35513,25488,Female,disloyal Customer,33,Business travel,Eco,547,1,4,1,3,2,1,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +35514,12641,Male,disloyal Customer,24,Business travel,Eco,444,2,5,3,3,5,3,5,5,2,2,3,2,5,5,9,0.0,neutral or dissatisfied +35515,59323,Female,Loyal Customer,53,Business travel,Business,2486,3,3,3,3,5,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +35516,19142,Female,Loyal Customer,15,Personal Travel,Eco Plus,323,4,3,4,4,4,4,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +35517,64606,Female,Loyal Customer,54,Business travel,Business,190,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +35518,21827,Male,disloyal Customer,24,Business travel,Eco,640,2,5,2,1,1,2,1,1,3,3,3,4,1,1,8,0.0,neutral or dissatisfied +35519,66472,Female,disloyal Customer,26,Business travel,Business,447,2,2,2,4,2,2,1,2,2,1,3,1,4,2,0,0.0,neutral or dissatisfied +35520,46496,Male,Loyal Customer,50,Business travel,Business,1794,1,1,1,1,4,5,2,5,5,5,3,5,5,2,12,11.0,satisfied +35521,13162,Female,disloyal Customer,38,Business travel,Eco Plus,595,3,3,3,3,4,3,2,4,3,4,4,2,3,4,14,6.0,neutral or dissatisfied +35522,62047,Male,disloyal Customer,18,Business travel,Eco,1431,3,3,3,4,4,3,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +35523,67949,Male,Loyal Customer,70,Personal Travel,Eco,1235,4,3,4,3,1,4,5,1,2,5,3,1,4,1,17,0.0,neutral or dissatisfied +35524,62539,Female,Loyal Customer,56,Business travel,Business,1744,2,4,4,4,3,2,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +35525,78871,Female,Loyal Customer,40,Personal Travel,Eco,1995,2,1,2,3,2,2,2,2,3,3,3,3,4,2,13,0.0,neutral or dissatisfied +35526,32645,Male,disloyal Customer,43,Business travel,Eco,101,4,0,4,2,3,4,3,3,1,3,3,2,1,3,0,0.0,neutral or dissatisfied +35527,61617,Male,Loyal Customer,43,Business travel,Business,1379,2,2,2,2,4,5,5,5,5,5,5,3,5,5,31,17.0,satisfied +35528,69704,Female,Loyal Customer,36,Business travel,Business,1372,1,1,1,1,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +35529,6498,Female,Loyal Customer,37,Business travel,Business,2855,5,5,5,5,3,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +35530,84171,Male,Loyal Customer,48,Business travel,Business,2809,1,1,1,1,2,4,3,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +35531,6931,Female,Loyal Customer,62,Personal Travel,Business,588,4,5,4,3,4,4,4,5,5,4,4,5,5,3,23,46.0,neutral or dissatisfied +35532,93433,Male,Loyal Customer,36,Business travel,Business,2798,4,4,4,4,2,3,3,4,4,4,4,4,4,3,2,0.0,neutral or dissatisfied +35533,20974,Male,Loyal Customer,26,Personal Travel,Eco,851,4,4,4,5,5,4,5,5,4,4,4,5,5,5,0,3.0,neutral or dissatisfied +35534,10764,Female,Loyal Customer,41,Business travel,Business,429,1,3,3,3,1,3,3,1,1,1,1,1,1,2,42,39.0,neutral or dissatisfied +35535,115096,Male,disloyal Customer,23,Business travel,Eco,362,4,0,4,3,1,4,1,1,5,4,4,4,4,1,14,10.0,neutral or dissatisfied +35536,87732,Male,Loyal Customer,61,Business travel,Eco,4502,2,3,3,3,2,2,2,1,1,3,2,2,3,2,0,0.0,neutral or dissatisfied +35537,28620,Male,disloyal Customer,9,Business travel,Eco,1449,2,2,2,3,2,2,2,2,1,2,1,3,3,2,0,0.0,neutral or dissatisfied +35538,114220,Male,disloyal Customer,45,Business travel,Eco,967,4,4,4,4,5,4,5,5,2,2,4,1,4,5,0,0.0,neutral or dissatisfied +35539,44598,Male,Loyal Customer,55,Business travel,Business,166,1,1,1,1,3,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +35540,99381,Female,disloyal Customer,23,Business travel,Eco,337,1,0,1,4,3,1,4,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +35541,7635,Female,Loyal Customer,45,Business travel,Business,641,4,4,5,4,2,4,4,5,5,5,5,4,5,4,9,24.0,satisfied +35542,21467,Female,disloyal Customer,20,Business travel,Eco,164,2,4,2,4,4,2,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +35543,29451,Male,Loyal Customer,46,Business travel,Eco,421,3,5,5,5,3,3,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +35544,82673,Male,Loyal Customer,22,Business travel,Business,3629,5,5,5,5,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +35545,5674,Male,Loyal Customer,46,Business travel,Business,436,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +35546,83321,Male,Loyal Customer,58,Personal Travel,Eco,1671,3,3,3,1,5,3,5,5,5,2,5,1,1,5,0,0.0,neutral or dissatisfied +35547,32516,Male,Loyal Customer,69,Business travel,Business,102,1,1,4,1,1,1,3,5,5,5,4,5,5,1,7,2.0,satisfied +35548,73098,Male,Loyal Customer,42,Business travel,Business,2174,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,11.0,satisfied +35549,16142,Female,Loyal Customer,43,Business travel,Business,199,1,4,1,1,5,5,4,4,4,4,5,5,4,3,0,0.0,satisfied +35550,20759,Female,Loyal Customer,26,Business travel,Business,515,4,4,4,4,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +35551,37361,Female,Loyal Customer,56,Business travel,Business,3859,2,2,2,2,1,3,5,3,3,5,3,5,3,2,0,0.0,satisfied +35552,103189,Female,Loyal Customer,49,Business travel,Business,3766,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,4.0,satisfied +35553,49593,Male,Loyal Customer,57,Business travel,Eco,421,4,5,5,5,4,4,4,4,1,3,5,2,3,4,51,42.0,satisfied +35554,20129,Male,Loyal Customer,8,Personal Travel,Eco,416,1,2,1,4,1,1,1,1,3,1,4,1,3,1,8,23.0,neutral or dissatisfied +35555,61768,Male,Loyal Customer,35,Personal Travel,Eco,1635,3,4,3,4,5,3,5,5,1,4,2,3,4,5,40,17.0,neutral or dissatisfied +35556,84713,Female,Loyal Customer,19,Personal Travel,Business,547,3,2,3,3,5,3,5,5,3,2,3,1,3,5,59,53.0,neutral or dissatisfied +35557,37083,Male,Loyal Customer,48,Business travel,Business,1129,3,2,3,2,2,2,2,3,3,3,3,4,3,3,0,7.0,neutral or dissatisfied +35558,105524,Male,disloyal Customer,21,Business travel,Business,611,4,0,4,3,5,4,5,5,4,3,5,4,4,5,32,39.0,satisfied +35559,51731,Male,Loyal Customer,32,Personal Travel,Eco,237,2,5,2,3,2,2,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +35560,32206,Male,Loyal Customer,36,Business travel,Eco,163,5,5,5,5,5,5,5,5,4,1,5,2,4,5,0,0.0,satisfied +35561,90502,Female,Loyal Customer,46,Business travel,Business,581,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +35562,62080,Male,Loyal Customer,41,Business travel,Business,2586,4,4,4,4,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +35563,99342,Female,disloyal Customer,42,Business travel,Business,1771,4,4,4,3,5,4,5,5,5,4,3,3,5,5,19,24.0,neutral or dissatisfied +35564,71758,Male,Loyal Customer,39,Business travel,Business,1652,1,1,3,1,2,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +35565,84993,Male,Loyal Customer,52,Business travel,Business,1590,4,4,4,4,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +35566,106559,Female,Loyal Customer,60,Business travel,Business,1024,3,3,3,3,3,4,4,5,5,5,5,5,5,5,0,16.0,satisfied +35567,81950,Female,Loyal Customer,42,Business travel,Business,1532,5,4,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +35568,36698,Female,Loyal Customer,57,Personal Travel,Eco,1091,3,3,3,3,4,5,1,4,4,3,4,4,4,1,0,15.0,neutral or dissatisfied +35569,98220,Male,Loyal Customer,8,Personal Travel,Eco,842,2,4,2,3,1,2,1,1,3,3,3,4,2,1,0,0.0,neutral or dissatisfied +35570,53111,Female,disloyal Customer,39,Business travel,Business,2065,4,4,4,4,2,4,2,2,4,4,4,2,3,2,15,10.0,neutral or dissatisfied +35571,28360,Male,Loyal Customer,47,Business travel,Eco Plus,467,4,4,4,4,4,4,4,4,5,3,4,4,4,4,20,8.0,satisfied +35572,84401,Female,Loyal Customer,43,Business travel,Business,2082,2,2,2,2,3,4,3,2,2,2,2,1,2,3,16,10.0,neutral or dissatisfied +35573,16701,Female,Loyal Customer,13,Personal Travel,Eco,169,3,4,3,3,4,3,4,4,4,4,4,4,4,4,71,60.0,neutral or dissatisfied +35574,17551,Female,Loyal Customer,38,Business travel,Business,3844,2,2,2,2,4,3,3,2,2,2,2,1,2,1,108,93.0,neutral or dissatisfied +35575,120395,Female,Loyal Customer,44,Business travel,Business,366,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +35576,45315,Male,disloyal Customer,32,Business travel,Eco,188,3,3,2,2,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +35577,20301,Male,Loyal Customer,47,Personal Travel,Eco,228,2,5,0,3,5,0,5,5,5,2,4,4,4,5,66,42.0,neutral or dissatisfied +35578,76794,Male,disloyal Customer,27,Business travel,Eco,689,2,2,2,4,3,2,3,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +35579,9806,Female,Loyal Customer,53,Business travel,Business,1686,1,1,1,1,4,4,5,5,5,5,5,3,5,3,6,0.0,satisfied +35580,82563,Female,Loyal Customer,46,Business travel,Business,528,2,2,2,2,4,4,4,3,3,5,5,4,5,4,181,176.0,satisfied +35581,27102,Male,Loyal Customer,35,Business travel,Business,1721,2,5,5,5,2,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +35582,29133,Male,Loyal Customer,32,Personal Travel,Eco,679,3,4,3,3,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +35583,1353,Male,Loyal Customer,41,Business travel,Business,2899,3,3,4,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +35584,113697,Female,Loyal Customer,11,Personal Travel,Eco,386,2,5,5,3,5,5,5,5,4,5,4,3,4,5,58,55.0,neutral or dissatisfied +35585,118591,Male,disloyal Customer,22,Business travel,Eco,368,2,2,1,3,4,1,4,4,3,4,4,2,3,4,5,1.0,neutral or dissatisfied +35586,71383,Male,Loyal Customer,67,Personal Travel,Eco,258,2,4,2,5,3,2,3,3,1,3,3,5,1,3,0,0.0,neutral or dissatisfied +35587,115231,Female,Loyal Customer,47,Business travel,Eco,371,2,1,1,1,5,4,4,2,2,2,2,1,2,2,13,6.0,neutral or dissatisfied +35588,56301,Male,Loyal Customer,58,Personal Travel,Eco,2227,2,5,2,1,3,2,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +35589,64129,Male,Loyal Customer,38,Business travel,Eco Plus,788,5,1,1,1,4,5,5,5,1,3,3,5,5,5,0,10.0,satisfied +35590,107308,Male,Loyal Customer,19,Personal Travel,Eco,307,4,4,4,4,3,4,3,3,5,2,5,5,5,3,1,0.0,neutral or dissatisfied +35591,78982,Male,disloyal Customer,43,Business travel,Business,356,3,3,3,1,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +35592,25906,Female,disloyal Customer,23,Business travel,Eco,507,2,5,2,2,2,2,2,2,4,1,2,5,4,2,4,0.0,neutral or dissatisfied +35593,11392,Female,disloyal Customer,28,Business travel,Business,247,2,2,2,4,4,2,1,4,5,4,4,3,4,4,5,0.0,neutral or dissatisfied +35594,83822,Female,Loyal Customer,40,Business travel,Business,425,3,3,3,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +35595,66220,Female,disloyal Customer,39,Business travel,Business,460,4,4,4,2,2,4,2,2,2,1,1,1,2,2,0,0.0,neutral or dissatisfied +35596,102765,Female,disloyal Customer,17,Business travel,Business,1383,4,2,4,5,2,4,2,2,4,4,3,4,4,2,5,0.0,satisfied +35597,104768,Male,Loyal Customer,23,Business travel,Eco Plus,1246,1,3,3,3,1,1,1,1,4,3,2,2,1,1,9,5.0,neutral or dissatisfied +35598,80156,Male,disloyal Customer,33,Business travel,Business,2586,4,4,4,5,4,3,3,5,4,5,5,3,3,3,0,0.0,neutral or dissatisfied +35599,5391,Male,Loyal Customer,61,Personal Travel,Eco,812,2,1,2,4,5,2,5,5,2,5,3,2,4,5,0,0.0,neutral or dissatisfied +35600,62107,Male,disloyal Customer,22,Business travel,Eco,1149,3,4,4,1,1,4,2,1,5,2,4,3,5,1,0,0.0,satisfied +35601,128479,Female,Loyal Customer,17,Personal Travel,Eco,370,1,3,1,3,5,1,1,5,4,2,5,2,4,5,0,22.0,neutral or dissatisfied +35602,74650,Male,Loyal Customer,48,Personal Travel,Eco,1188,3,5,3,3,3,3,3,3,3,2,5,5,4,3,0,3.0,neutral or dissatisfied +35603,110665,Male,Loyal Customer,47,Business travel,Business,837,4,1,4,4,4,5,5,4,4,4,4,4,4,4,0,2.0,satisfied +35604,45957,Female,Loyal Customer,48,Business travel,Eco Plus,641,2,5,5,5,4,3,4,2,2,2,2,1,2,1,10,6.0,neutral or dissatisfied +35605,61294,Male,Loyal Customer,52,Personal Travel,Eco,853,2,4,2,1,5,2,5,5,5,5,4,4,4,5,13,7.0,neutral or dissatisfied +35606,126130,Male,disloyal Customer,23,Business travel,Eco,507,4,5,4,4,1,4,1,1,5,2,5,5,5,1,5,0.0,satisfied +35607,33564,Female,Loyal Customer,30,Business travel,Business,2402,4,4,4,4,5,5,5,5,2,4,5,2,2,5,8,0.0,satisfied +35608,52330,Female,Loyal Customer,36,Business travel,Business,1587,2,2,2,2,3,5,1,5,5,5,5,3,5,3,1,0.0,satisfied +35609,20614,Male,Loyal Customer,22,Business travel,Eco,864,5,1,1,1,5,4,4,5,4,2,1,1,1,5,0,0.0,satisfied +35610,83586,Male,Loyal Customer,42,Personal Travel,Eco,936,3,1,4,2,4,4,3,4,2,2,2,1,2,4,0,2.0,neutral or dissatisfied +35611,24942,Male,disloyal Customer,42,Business travel,Eco,1747,1,1,1,2,5,1,5,5,4,2,3,3,4,5,6,0.0,neutral or dissatisfied +35612,52356,Female,Loyal Customer,8,Personal Travel,Eco,370,3,2,3,3,2,3,2,2,1,3,3,4,4,2,9,7.0,neutral or dissatisfied +35613,33807,Male,Loyal Customer,31,Business travel,Business,1521,1,1,1,1,4,4,4,4,3,2,3,4,1,4,2,0.0,satisfied +35614,70652,Female,Loyal Customer,16,Business travel,Business,946,1,1,1,1,5,5,5,5,5,5,5,5,4,5,20,0.0,satisfied +35615,117576,Male,disloyal Customer,52,Business travel,Eco,872,2,2,2,2,3,2,3,3,2,5,1,2,1,3,41,25.0,neutral or dissatisfied +35616,93682,Male,Loyal Customer,54,Business travel,Business,3292,3,3,1,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +35617,119663,Female,Loyal Customer,65,Personal Travel,Eco,507,4,3,4,3,1,4,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +35618,54377,Male,Loyal Customer,35,Business travel,Eco,305,3,4,4,4,3,3,3,3,1,3,3,2,4,3,5,0.0,satisfied +35619,29147,Female,Loyal Customer,7,Personal Travel,Eco,697,3,4,3,4,4,3,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +35620,97339,Male,Loyal Customer,51,Business travel,Business,2866,1,1,1,1,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +35621,25490,Female,disloyal Customer,24,Business travel,Eco,516,4,5,5,3,4,5,4,4,1,4,1,2,2,4,0,0.0,satisfied +35622,76162,Female,Loyal Customer,59,Personal Travel,Eco,689,2,5,2,1,3,4,4,2,2,2,4,3,2,3,9,9.0,neutral or dissatisfied +35623,89877,Male,Loyal Customer,35,Business travel,Business,1501,3,3,2,3,2,4,4,5,5,5,5,3,5,4,3,0.0,satisfied +35624,4161,Male,Loyal Customer,28,Personal Travel,Eco,431,0,4,0,2,2,0,3,2,3,2,4,3,4,2,0,0.0,satisfied +35625,21172,Female,Loyal Customer,53,Business travel,Business,1602,1,5,5,5,1,4,3,2,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +35626,113389,Male,Loyal Customer,59,Business travel,Business,386,4,4,4,4,3,5,5,4,4,4,4,5,4,4,82,88.0,satisfied +35627,31462,Female,disloyal Customer,52,Business travel,Eco,967,3,3,3,2,2,3,1,2,5,2,3,3,4,2,108,103.0,neutral or dissatisfied +35628,108413,Male,Loyal Customer,56,Business travel,Business,1444,2,2,3,2,3,5,5,4,4,4,4,5,4,5,6,4.0,satisfied +35629,54408,Female,disloyal Customer,22,Business travel,Eco,305,2,3,2,3,5,2,5,5,1,1,3,2,2,5,0,0.0,neutral or dissatisfied +35630,91924,Male,Loyal Customer,27,Business travel,Eco,2475,4,3,3,3,4,4,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +35631,77955,Male,Loyal Customer,49,Business travel,Business,214,5,5,5,5,2,5,5,5,5,5,4,4,5,4,0,0.0,satisfied +35632,41701,Male,disloyal Customer,24,Business travel,Eco,936,4,4,4,4,3,4,3,3,2,5,4,3,3,3,4,4.0,neutral or dissatisfied +35633,62708,Female,Loyal Customer,30,Business travel,Business,2399,4,4,4,4,4,4,4,4,4,5,4,3,5,4,7,10.0,satisfied +35634,83951,Female,Loyal Customer,47,Business travel,Business,373,5,5,5,5,4,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +35635,20171,Male,Loyal Customer,62,Personal Travel,Eco,438,2,4,2,1,5,2,5,5,5,2,4,5,5,5,0,14.0,neutral or dissatisfied +35636,18528,Male,disloyal Customer,36,Business travel,Eco,192,2,0,2,5,3,2,3,3,1,4,5,3,3,3,109,108.0,neutral or dissatisfied +35637,12417,Male,Loyal Customer,17,Personal Travel,Eco,190,5,5,5,1,3,5,3,3,3,3,4,5,4,3,0,2.0,satisfied +35638,115740,Male,disloyal Customer,20,Business travel,Eco,337,2,0,2,5,3,2,3,3,4,4,4,3,4,3,12,0.0,neutral or dissatisfied +35639,20931,Male,Loyal Customer,50,Business travel,Eco,721,5,1,1,1,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +35640,116217,Male,Loyal Customer,52,Personal Travel,Eco,447,4,4,4,4,1,4,1,1,4,1,3,3,4,1,27,17.0,neutral or dissatisfied +35641,122471,Male,Loyal Customer,31,Business travel,Business,3130,3,5,5,5,3,3,3,3,1,1,3,3,3,3,0,5.0,neutral or dissatisfied +35642,23533,Male,Loyal Customer,56,Business travel,Business,472,3,5,2,5,2,3,3,3,3,3,3,4,3,4,33,25.0,neutral or dissatisfied +35643,13624,Male,Loyal Customer,26,Business travel,Business,872,1,1,1,1,4,4,4,4,2,1,5,5,5,4,101,110.0,satisfied +35644,106762,Male,Loyal Customer,54,Personal Travel,Eco,1005,4,4,4,3,1,4,1,1,4,5,5,5,5,1,0,0.0,satisfied +35645,50294,Female,Loyal Customer,44,Business travel,Business,1813,1,5,5,5,1,2,3,1,1,1,1,2,1,3,3,16.0,neutral or dissatisfied +35646,124148,Male,Loyal Customer,61,Personal Travel,Business,2133,3,3,3,3,4,4,4,1,1,3,1,2,1,1,24,13.0,neutral or dissatisfied +35647,36640,Female,Loyal Customer,15,Personal Travel,Eco,1185,3,3,3,3,2,3,2,2,4,1,2,3,2,2,0,0.0,neutral or dissatisfied +35648,125053,Female,disloyal Customer,27,Business travel,Business,2300,4,5,5,3,5,2,2,4,5,5,4,2,4,2,0,17.0,neutral or dissatisfied +35649,98003,Male,Loyal Customer,9,Personal Travel,Eco Plus,612,2,3,2,2,1,2,1,1,3,1,4,4,2,1,0,0.0,neutral or dissatisfied +35650,97494,Male,Loyal Customer,45,Personal Travel,Eco,756,5,5,5,4,4,5,4,4,4,2,5,5,5,4,2,5.0,satisfied +35651,46828,Female,Loyal Customer,46,Business travel,Eco,846,5,1,1,1,4,5,3,5,5,5,5,2,5,4,18,15.0,satisfied +35652,83436,Male,Loyal Customer,26,Business travel,Business,2253,5,2,5,5,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +35653,126342,Male,Loyal Customer,29,Personal Travel,Eco,600,1,4,0,2,3,0,3,3,2,4,5,5,2,3,7,32.0,neutral or dissatisfied +35654,52210,Female,Loyal Customer,25,Business travel,Business,646,5,5,5,5,5,5,5,5,5,4,4,5,1,5,0,0.0,satisfied +35655,82259,Female,disloyal Customer,23,Business travel,Eco,1365,1,0,0,3,5,1,5,5,4,2,3,4,4,5,75,64.0,neutral or dissatisfied +35656,13678,Female,Loyal Customer,58,Business travel,Eco Plus,462,4,4,1,4,2,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +35657,111282,Male,Loyal Customer,59,Personal Travel,Eco,459,1,4,1,3,4,1,4,4,3,3,5,4,5,4,2,1.0,neutral or dissatisfied +35658,10172,Female,Loyal Customer,27,Business travel,Business,1884,4,4,4,4,5,5,5,5,3,3,5,5,5,5,18,6.0,satisfied +35659,27200,Male,disloyal Customer,27,Business travel,Eco,2554,3,3,3,3,2,3,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +35660,19732,Female,Loyal Customer,57,Personal Travel,Eco,475,3,2,3,3,5,3,3,2,2,3,2,3,2,2,97,93.0,neutral or dissatisfied +35661,111081,Male,Loyal Customer,58,Personal Travel,Eco,319,3,3,3,3,1,3,5,1,2,3,5,1,4,1,0,0.0,neutral or dissatisfied +35662,45055,Female,Loyal Customer,57,Business travel,Business,3474,0,1,1,2,2,2,5,5,5,5,5,1,5,4,0,0.0,satisfied +35663,8169,Male,disloyal Customer,17,Business travel,Eco,402,2,0,2,3,4,2,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +35664,18368,Female,disloyal Customer,25,Business travel,Eco,169,1,5,1,4,1,1,5,1,5,1,2,5,4,1,59,54.0,neutral or dissatisfied +35665,88085,Male,Loyal Customer,51,Business travel,Business,581,2,2,2,2,5,5,5,4,4,4,4,5,4,3,14,92.0,satisfied +35666,70168,Female,Loyal Customer,50,Business travel,Business,460,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +35667,114135,Female,disloyal Customer,39,Business travel,Business,853,5,5,5,4,2,5,2,2,4,5,4,3,5,2,9,0.0,satisfied +35668,72347,Male,Loyal Customer,44,Business travel,Business,985,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +35669,73152,Male,disloyal Customer,28,Business travel,Business,1501,1,0,0,3,3,0,3,3,4,2,5,4,5,3,0,4.0,neutral or dissatisfied +35670,95981,Female,disloyal Customer,42,Business travel,Business,1069,5,5,5,3,2,5,2,2,5,4,4,3,5,2,9,0.0,satisfied +35671,101444,Male,Loyal Customer,50,Business travel,Business,1767,4,4,4,4,4,4,4,4,4,4,4,4,4,3,24,48.0,satisfied +35672,24197,Male,Loyal Customer,44,Business travel,Business,1515,0,0,0,2,2,3,1,1,1,1,3,5,1,5,0,0.0,satisfied +35673,81308,Female,Loyal Customer,60,Business travel,Business,1520,2,2,3,3,3,4,4,2,2,2,2,1,2,3,46,29.0,neutral or dissatisfied +35674,46311,Male,Loyal Customer,42,Personal Travel,Eco,1069,4,4,4,2,4,4,4,4,4,5,5,5,4,4,1,0.0,neutral or dissatisfied +35675,13342,Male,Loyal Customer,27,Business travel,Business,2923,3,4,3,3,2,2,2,2,1,1,2,1,3,2,0,0.0,satisfied +35676,67947,Male,Loyal Customer,26,Personal Travel,Eco,1235,2,5,2,2,1,2,1,1,5,4,5,4,4,1,28,17.0,neutral or dissatisfied +35677,28335,Female,Loyal Customer,37,Business travel,Business,3277,3,5,3,3,3,4,4,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +35678,83981,Male,disloyal Customer,61,Business travel,Business,321,1,1,1,5,5,1,1,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +35679,14249,Male,Loyal Customer,60,Personal Travel,Eco,1136,3,4,3,3,1,3,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +35680,123014,Female,Loyal Customer,56,Business travel,Business,3171,4,4,4,4,3,5,4,4,4,5,4,5,4,4,1,7.0,satisfied +35681,77632,Female,Loyal Customer,41,Business travel,Business,689,4,4,4,4,2,4,5,5,5,5,5,4,5,4,4,13.0,satisfied +35682,65314,Female,Loyal Customer,55,Personal Travel,Business,432,1,4,1,1,1,4,5,1,1,1,5,3,1,5,0,0.0,neutral or dissatisfied +35683,61627,Male,disloyal Customer,22,Business travel,Business,1358,0,0,0,5,2,0,2,2,5,4,5,4,5,2,11,7.0,satisfied +35684,82709,Male,Loyal Customer,9,Personal Travel,Eco,632,3,5,3,4,3,3,2,3,4,2,5,3,5,3,80,88.0,neutral or dissatisfied +35685,71126,Female,Loyal Customer,31,Business travel,Business,1739,2,2,2,2,5,5,5,5,5,4,5,4,4,5,0,6.0,satisfied +35686,115843,Female,Loyal Customer,47,Business travel,Eco,342,4,2,2,2,5,1,4,4,4,4,4,4,4,3,0,0.0,satisfied +35687,59537,Male,disloyal Customer,27,Business travel,Business,854,2,2,2,3,5,2,5,5,4,3,5,4,5,5,5,0.0,neutral or dissatisfied +35688,95856,Male,Loyal Customer,58,Business travel,Business,2985,4,4,5,4,5,5,4,5,5,5,5,5,5,4,5,4.0,satisfied +35689,52417,Male,Loyal Customer,70,Personal Travel,Eco,493,3,2,3,4,3,3,3,3,2,2,4,1,4,3,0,0.0,neutral or dissatisfied +35690,39833,Female,disloyal Customer,44,Business travel,Eco,272,1,1,1,3,3,1,3,3,1,2,3,3,2,3,0,0.0,neutral or dissatisfied +35691,85954,Male,Loyal Customer,51,Business travel,Business,447,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +35692,3632,Female,Loyal Customer,46,Business travel,Business,2311,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +35693,102532,Male,Loyal Customer,19,Personal Travel,Eco,236,3,5,0,2,4,0,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +35694,18987,Male,Loyal Customer,37,Business travel,Business,451,2,5,5,5,3,4,3,2,2,2,2,2,2,1,64,63.0,neutral or dissatisfied +35695,10965,Female,Loyal Customer,42,Business travel,Eco,166,2,5,5,5,1,2,1,2,2,2,2,5,2,1,0,0.0,satisfied +35696,69580,Female,Loyal Customer,10,Personal Travel,Eco,2586,3,4,3,3,3,4,4,5,5,1,3,4,3,4,6,15.0,neutral or dissatisfied +35697,78039,Female,Loyal Customer,23,Personal Travel,Eco,214,3,3,3,2,3,3,3,3,3,3,4,4,5,3,10,0.0,neutral or dissatisfied +35698,10083,Female,Loyal Customer,43,Business travel,Business,2702,0,0,0,1,3,4,4,4,4,4,4,5,4,5,49,37.0,satisfied +35699,71804,Male,Loyal Customer,22,Business travel,Business,1744,2,2,5,2,4,5,4,4,5,5,4,4,4,4,3,0.0,satisfied +35700,91155,Female,Loyal Customer,51,Personal Travel,Eco,270,3,0,3,2,2,3,4,1,1,3,1,4,1,4,13,12.0,neutral or dissatisfied +35701,29655,Female,Loyal Customer,17,Personal Travel,Eco,680,3,4,3,4,4,3,4,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +35702,98801,Female,Loyal Customer,52,Personal Travel,Eco,1111,4,4,4,2,5,4,4,1,1,4,5,4,1,4,0,0.0,satisfied +35703,34372,Male,Loyal Customer,60,Business travel,Eco Plus,427,4,1,1,1,4,4,4,4,3,1,2,4,5,4,6,14.0,satisfied +35704,95835,Male,Loyal Customer,42,Business travel,Business,580,3,4,4,4,2,4,3,3,3,3,3,3,3,1,18,9.0,neutral or dissatisfied +35705,103662,Male,disloyal Customer,34,Business travel,Business,251,4,5,5,1,3,5,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +35706,16509,Female,Loyal Customer,15,Personal Travel,Eco,246,3,4,3,4,1,3,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +35707,27645,Female,Loyal Customer,11,Personal Travel,Eco Plus,1050,3,4,3,2,3,3,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +35708,14153,Female,Loyal Customer,24,Business travel,Eco Plus,654,3,5,5,5,3,3,1,3,1,1,4,2,3,3,20,16.0,neutral or dissatisfied +35709,105018,Female,disloyal Customer,23,Business travel,Eco,255,4,5,4,1,1,4,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +35710,36463,Female,Loyal Customer,67,Personal Travel,Eco,867,2,5,2,3,4,4,5,2,2,2,4,3,2,4,0,0.0,neutral or dissatisfied +35711,110205,Female,Loyal Customer,49,Business travel,Business,2793,4,4,4,4,3,5,5,4,4,4,4,5,4,5,13,23.0,satisfied +35712,102165,Female,Loyal Customer,40,Business travel,Business,226,0,0,0,3,5,5,5,5,5,5,5,5,5,4,4,0.0,satisfied +35713,37739,Female,Loyal Customer,17,Personal Travel,Eco,944,4,5,4,4,1,4,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +35714,17168,Male,Loyal Customer,26,Business travel,Eco,643,0,5,0,5,3,0,3,3,5,3,5,2,1,3,0,0.0,satisfied +35715,21054,Male,disloyal Customer,24,Business travel,Business,227,2,3,2,3,1,2,1,1,4,3,4,3,4,1,3,0.0,neutral or dissatisfied +35716,65008,Male,disloyal Customer,36,Business travel,Eco,247,3,2,3,3,4,3,4,4,2,1,4,3,3,4,7,0.0,neutral or dissatisfied +35717,61841,Female,Loyal Customer,40,Business travel,Business,3340,5,5,5,5,3,4,5,1,1,2,1,4,1,4,0,0.0,satisfied +35718,97973,Female,Loyal Customer,41,Personal Travel,Eco,401,3,4,3,4,2,3,2,2,2,2,4,5,5,2,31,10.0,neutral or dissatisfied +35719,427,Female,disloyal Customer,35,Business travel,Business,113,1,1,1,4,3,1,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +35720,60552,Male,Loyal Customer,44,Business travel,Business,1951,3,3,3,3,5,4,5,3,3,2,3,4,3,5,0,0.0,satisfied +35721,12984,Male,disloyal Customer,37,Business travel,Eco,374,3,5,3,1,2,3,2,2,5,4,4,1,3,2,13,26.0,neutral or dissatisfied +35722,123360,Male,Loyal Customer,43,Business travel,Business,644,2,2,5,5,1,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +35723,62924,Male,Loyal Customer,53,Business travel,Business,2518,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +35724,96234,Female,Loyal Customer,55,Business travel,Eco,146,5,3,5,3,1,1,3,4,4,5,4,1,4,5,45,41.0,satisfied +35725,74442,Male,Loyal Customer,53,Business travel,Business,1464,3,3,3,3,4,5,5,3,3,4,3,5,3,5,0,3.0,satisfied +35726,100070,Female,Loyal Customer,21,Personal Travel,Eco,220,3,0,3,1,3,3,5,3,3,4,3,4,5,3,0,0.0,neutral or dissatisfied +35727,106708,Female,Loyal Customer,34,Personal Travel,Eco,516,4,4,4,3,3,4,3,3,5,3,2,4,4,3,14,10.0,neutral or dissatisfied +35728,117724,Male,Loyal Customer,22,Business travel,Business,3320,4,4,4,4,5,5,5,5,5,5,4,5,4,5,5,0.0,satisfied +35729,53263,Female,Loyal Customer,53,Business travel,Business,811,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,16.0,satisfied +35730,94016,Female,Loyal Customer,72,Business travel,Business,2198,0,1,1,4,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +35731,128795,Male,Loyal Customer,53,Business travel,Business,2475,2,2,2,2,5,5,5,4,3,4,4,5,3,5,5,0.0,satisfied +35732,95645,Female,Loyal Customer,23,Personal Travel,Eco Plus,484,2,5,2,4,4,2,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +35733,96999,Female,Loyal Customer,68,Personal Travel,Eco,883,3,4,3,3,4,3,4,2,2,3,2,1,2,4,35,13.0,neutral or dissatisfied +35734,129191,Male,Loyal Customer,48,Business travel,Business,2419,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +35735,2382,Male,Loyal Customer,60,Business travel,Business,3710,3,3,3,3,5,5,4,5,5,5,5,4,5,5,81,97.0,satisfied +35736,113358,Male,Loyal Customer,41,Business travel,Business,1759,3,3,2,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +35737,67311,Female,disloyal Customer,35,Business travel,Business,985,3,2,2,5,3,2,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +35738,102679,Female,disloyal Customer,44,Business travel,Eco,255,3,1,3,4,4,3,4,4,2,2,3,1,4,4,5,11.0,neutral or dissatisfied +35739,35813,Female,Loyal Customer,54,Business travel,Business,1065,1,1,1,1,3,3,4,5,5,5,5,3,5,2,4,28.0,satisfied +35740,31931,Female,Loyal Customer,32,Business travel,Business,3326,2,2,5,2,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +35741,100523,Male,Loyal Customer,28,Personal Travel,Eco,580,3,4,3,3,2,3,2,2,4,4,3,3,3,2,0,2.0,neutral or dissatisfied +35742,43266,Male,Loyal Customer,37,Business travel,Eco,436,4,1,1,1,4,4,4,4,5,1,4,1,5,4,0,12.0,satisfied +35743,10445,Female,Loyal Customer,49,Business travel,Business,2497,5,5,5,5,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +35744,96536,Female,Loyal Customer,63,Personal Travel,Eco,302,3,5,2,1,5,4,5,4,4,2,5,3,4,5,41,32.0,neutral or dissatisfied +35745,117406,Male,Loyal Customer,55,Business travel,Business,1609,3,3,3,3,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +35746,121871,Male,Loyal Customer,70,Business travel,Business,3152,5,4,5,5,3,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +35747,3962,Female,Loyal Customer,42,Personal Travel,Eco,764,1,3,1,2,2,1,1,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +35748,42280,Female,disloyal Customer,26,Business travel,Eco,451,1,5,1,1,1,1,1,1,4,4,1,5,3,1,0,0.0,neutral or dissatisfied +35749,93846,Male,Loyal Customer,44,Personal Travel,Eco,391,2,3,2,3,1,2,1,1,4,2,3,1,3,1,18,12.0,neutral or dissatisfied +35750,46586,Female,Loyal Customer,57,Business travel,Eco,73,5,1,4,1,3,3,4,5,5,5,5,3,5,3,0,0.0,satisfied +35751,62064,Male,Loyal Customer,19,Personal Travel,Eco,2475,4,5,4,3,3,4,3,3,4,5,5,4,4,3,4,0.0,satisfied +35752,27209,Male,Loyal Customer,48,Personal Travel,Eco,2554,2,5,2,3,2,2,2,2,2,3,5,1,2,2,0,4.0,neutral or dissatisfied +35753,79475,Male,Loyal Customer,39,Business travel,Business,2090,2,3,3,3,3,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +35754,110632,Female,Loyal Customer,55,Personal Travel,Eco,719,2,4,2,2,3,5,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +35755,84302,Female,disloyal Customer,29,Business travel,Eco,235,3,3,3,4,2,3,2,2,3,3,4,3,4,2,7,30.0,neutral or dissatisfied +35756,43480,Female,Loyal Customer,23,Business travel,Business,1716,2,3,3,3,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +35757,117070,Male,disloyal Customer,20,Business travel,Eco,325,2,4,2,1,2,2,2,2,4,3,4,5,5,2,5,0.0,neutral or dissatisfied +35758,38504,Female,Loyal Customer,47,Business travel,Business,2475,4,4,3,4,5,5,4,5,5,5,5,2,5,4,8,0.0,satisfied +35759,76284,Female,Loyal Customer,19,Personal Travel,Eco,1927,3,4,3,5,2,3,2,2,3,3,4,4,5,2,8,0.0,neutral or dissatisfied +35760,99008,Female,disloyal Customer,27,Business travel,Eco Plus,479,2,2,2,4,3,2,3,3,3,5,3,4,3,3,11,6.0,neutral or dissatisfied +35761,111952,Male,Loyal Customer,72,Business travel,Eco,533,2,2,2,2,2,2,2,2,3,3,4,1,4,2,17,0.0,neutral or dissatisfied +35762,8515,Female,disloyal Customer,37,Business travel,Eco,462,3,0,3,3,4,3,4,4,4,5,5,2,2,4,4,10.0,neutral or dissatisfied +35763,93945,Male,Loyal Customer,41,Personal Travel,Eco,507,2,5,2,2,2,2,2,2,5,4,5,3,5,2,34,29.0,neutral or dissatisfied +35764,94322,Male,Loyal Customer,58,Business travel,Business,3433,4,4,4,4,2,4,4,3,3,4,3,5,3,4,59,60.0,satisfied +35765,28595,Female,Loyal Customer,49,Personal Travel,Eco Plus,2607,3,4,3,4,3,3,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +35766,733,Female,Loyal Customer,57,Business travel,Business,354,0,0,0,3,3,5,5,4,4,3,3,3,4,3,0,0.0,satisfied +35767,48596,Female,Loyal Customer,49,Personal Travel,Eco,737,3,2,3,3,4,3,4,2,2,3,2,4,2,2,0,2.0,neutral or dissatisfied +35768,96801,Female,Loyal Customer,51,Business travel,Business,781,3,3,2,3,5,4,5,5,5,5,5,4,5,3,17,8.0,satisfied +35769,28208,Female,Loyal Customer,68,Personal Travel,Eco,933,2,5,2,2,2,4,4,5,5,2,5,5,5,5,2,1.0,neutral or dissatisfied +35770,102058,Female,Loyal Customer,14,Personal Travel,Business,226,1,4,1,3,3,1,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +35771,91907,Male,Loyal Customer,50,Business travel,Business,2475,1,1,1,1,2,4,4,3,3,4,3,5,3,5,0,6.0,satisfied +35772,97981,Female,Loyal Customer,21,Personal Travel,Eco,483,3,0,3,3,3,3,1,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +35773,13614,Male,disloyal Customer,23,Business travel,Eco,152,1,3,1,3,5,1,5,5,2,2,4,4,3,5,84,84.0,neutral or dissatisfied +35774,112726,Male,Loyal Customer,40,Personal Travel,Eco,605,3,4,3,3,3,3,3,3,4,2,4,4,5,3,0,15.0,neutral or dissatisfied +35775,121100,Male,Loyal Customer,51,Personal Travel,Eco Plus,1558,3,5,3,2,3,4,4,5,5,5,5,4,3,4,67,143.0,neutral or dissatisfied +35776,52945,Female,Loyal Customer,15,Business travel,Business,1448,2,2,2,2,5,5,5,5,2,1,3,2,4,5,0,0.0,satisfied +35777,643,Female,Loyal Customer,60,Business travel,Business,3931,2,4,2,2,3,4,5,5,5,5,5,3,5,3,11,20.0,satisfied +35778,83095,Male,Loyal Customer,53,Personal Travel,Eco,1084,2,4,2,4,2,2,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +35779,91981,Male,Loyal Customer,62,Personal Travel,Eco Plus,2475,4,4,4,5,2,4,2,2,5,3,5,1,1,2,39,37.0,neutral or dissatisfied +35780,57356,Male,Loyal Customer,38,Business travel,Eco,414,4,3,3,3,4,4,4,4,2,3,5,1,3,4,0,0.0,satisfied +35781,77735,Female,Loyal Customer,51,Business travel,Business,874,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +35782,14934,Male,Loyal Customer,23,Business travel,Business,3035,1,1,1,1,5,5,5,5,2,1,3,3,5,5,0,0.0,satisfied +35783,114804,Male,Loyal Customer,35,Business travel,Business,3642,3,3,3,3,3,5,4,4,4,4,4,3,4,5,73,71.0,satisfied +35784,86911,Male,Loyal Customer,50,Business travel,Eco,341,4,1,1,1,4,4,4,4,4,1,4,2,4,4,31,27.0,neutral or dissatisfied +35785,62510,Male,Loyal Customer,47,Business travel,Business,1846,3,3,3,3,5,5,5,5,5,5,5,4,5,3,64,70.0,satisfied +35786,106214,Male,Loyal Customer,53,Business travel,Business,471,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +35787,23608,Male,Loyal Customer,35,Personal Travel,Eco,692,3,5,3,1,1,3,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +35788,45691,Male,Loyal Customer,77,Business travel,Business,426,3,3,3,3,1,2,1,3,3,3,3,1,3,4,34,55.0,neutral or dissatisfied +35789,1951,Female,Loyal Customer,35,Business travel,Eco,293,2,4,4,4,2,2,2,2,1,5,4,2,4,2,109,115.0,neutral or dissatisfied +35790,59493,Male,Loyal Customer,23,Personal Travel,Eco,901,3,5,3,2,2,3,2,2,5,4,2,4,4,2,29,7.0,neutral or dissatisfied +35791,113995,Female,Loyal Customer,16,Business travel,Business,1728,5,5,5,5,5,5,5,5,2,2,3,1,4,5,0,0.0,satisfied +35792,64524,Female,disloyal Customer,23,Business travel,Business,247,5,5,5,1,2,5,2,2,3,2,4,4,4,2,0,0.0,satisfied +35793,85202,Female,disloyal Customer,30,Business travel,Business,874,4,4,4,3,3,4,3,3,5,3,4,4,4,3,0,0.0,satisfied +35794,95961,Female,Loyal Customer,45,Business travel,Business,2327,2,2,2,2,2,4,5,4,4,4,4,5,4,5,8,9.0,satisfied +35795,48813,Female,Loyal Customer,26,Personal Travel,Business,109,1,2,1,3,5,1,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +35796,76832,Female,disloyal Customer,28,Business travel,Eco,1289,2,2,2,3,2,2,2,2,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +35797,14368,Female,Loyal Customer,24,Business travel,Business,2305,5,5,5,5,5,5,5,5,1,3,5,5,3,5,1,3.0,satisfied +35798,11544,Male,Loyal Customer,9,Business travel,Business,3740,4,3,5,3,4,4,4,4,1,1,4,4,3,4,112,97.0,neutral or dissatisfied +35799,110919,Male,Loyal Customer,9,Personal Travel,Eco,581,1,5,1,4,3,1,3,3,4,2,5,4,4,3,26,27.0,neutral or dissatisfied +35800,101359,Male,disloyal Customer,46,Business travel,Business,1321,2,2,2,3,3,2,3,3,5,2,5,4,4,3,23,8.0,satisfied +35801,13963,Female,Loyal Customer,40,Personal Travel,Eco,192,3,5,3,1,3,3,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +35802,66999,Female,disloyal Customer,39,Business travel,Business,964,2,2,2,1,3,2,3,3,3,3,4,3,4,3,21,0.0,satisfied +35803,75347,Female,Loyal Customer,41,Personal Travel,Eco,2504,3,1,3,4,4,3,4,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +35804,25596,Female,Loyal Customer,31,Personal Travel,Eco,874,1,0,1,3,4,1,4,4,5,5,3,4,4,4,5,0.0,neutral or dissatisfied +35805,1098,Male,Loyal Customer,11,Personal Travel,Eco,229,3,5,3,1,4,3,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +35806,34211,Male,Loyal Customer,31,Personal Travel,Eco,1288,4,4,4,4,1,4,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +35807,25077,Male,Loyal Customer,58,Business travel,Eco,957,3,2,2,2,3,3,3,3,1,1,4,4,3,3,0,39.0,neutral or dissatisfied +35808,47677,Male,Loyal Customer,30,Personal Travel,Eco,1464,1,5,1,1,1,1,1,1,5,2,4,4,5,1,6,0.0,neutral or dissatisfied +35809,78020,Female,Loyal Customer,38,Business travel,Business,332,3,3,3,3,2,5,1,4,4,4,4,4,4,2,4,22.0,satisfied +35810,86873,Female,Loyal Customer,45,Business travel,Business,2720,3,3,5,3,4,4,5,4,4,4,4,3,4,4,14,0.0,satisfied +35811,27793,Male,Loyal Customer,38,Business travel,Business,3828,5,5,5,5,4,1,5,4,4,4,4,3,4,4,20,35.0,satisfied +35812,51024,Male,Loyal Customer,27,Personal Travel,Eco,326,3,5,3,4,2,3,2,2,5,1,3,3,5,2,1,0.0,neutral or dissatisfied +35813,84799,Male,Loyal Customer,41,Business travel,Business,3723,3,2,2,2,5,2,1,3,3,3,3,1,3,1,13,11.0,neutral or dissatisfied +35814,31699,Male,Loyal Customer,44,Business travel,Eco,567,5,4,4,4,5,5,5,5,3,1,2,1,5,5,0,0.0,satisfied +35815,69107,Female,Loyal Customer,37,Business travel,Eco Plus,989,5,3,4,3,5,5,5,5,5,2,3,4,4,5,0,0.0,satisfied +35816,86220,Male,disloyal Customer,20,Business travel,Eco,226,1,3,1,3,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +35817,50310,Female,Loyal Customer,54,Business travel,Eco,86,3,4,4,4,5,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +35818,19672,Female,Loyal Customer,44,Personal Travel,Business,475,3,2,3,3,1,4,4,1,1,3,1,2,1,3,0,0.0,neutral or dissatisfied +35819,110399,Male,disloyal Customer,11,Business travel,Eco,787,3,4,4,3,4,4,5,4,1,3,2,1,2,4,9,0.0,neutral or dissatisfied +35820,89604,Male,Loyal Customer,34,Business travel,Business,1080,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +35821,90941,Female,Loyal Customer,31,Business travel,Eco,581,3,5,5,5,3,3,3,3,4,5,3,3,3,3,4,0.0,neutral or dissatisfied +35822,20018,Male,Loyal Customer,51,Business travel,Business,1798,1,1,1,1,5,5,4,5,5,5,5,3,5,4,9,2.0,satisfied +35823,52659,Female,Loyal Customer,61,Personal Travel,Eco,160,3,5,3,3,2,4,5,5,5,3,4,5,5,5,0,5.0,neutral or dissatisfied +35824,36297,Female,disloyal Customer,23,Business travel,Eco,187,5,0,5,5,1,5,1,1,4,1,4,4,4,1,9,0.0,satisfied +35825,118606,Male,Loyal Customer,52,Business travel,Business,451,1,4,4,4,2,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +35826,42987,Female,Loyal Customer,39,Business travel,Eco,391,4,5,5,5,4,4,4,4,5,1,2,4,4,4,0,0.0,satisfied +35827,112820,Female,Loyal Customer,38,Business travel,Business,1357,5,5,5,5,2,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +35828,29633,Female,Loyal Customer,39,Business travel,Business,1634,3,1,1,1,2,3,4,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +35829,95936,Female,Loyal Customer,48,Personal Travel,Eco,1411,2,3,2,3,4,4,1,5,5,2,5,1,5,1,15,0.0,neutral or dissatisfied +35830,48684,Male,Loyal Customer,46,Business travel,Business,1738,1,1,1,1,4,5,4,5,5,5,5,3,5,5,18,15.0,satisfied +35831,21770,Male,Loyal Customer,54,Business travel,Business,352,2,2,2,2,1,3,1,5,5,5,5,4,5,2,0,0.0,satisfied +35832,113032,Male,Loyal Customer,72,Business travel,Business,569,5,5,5,5,3,4,5,5,5,5,5,4,5,4,41,34.0,satisfied +35833,46752,Male,Loyal Customer,42,Business travel,Eco Plus,125,4,5,5,5,5,4,5,5,5,1,3,3,4,5,16,22.0,satisfied +35834,94591,Female,Loyal Customer,53,Business travel,Business,187,3,3,3,3,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +35835,100284,Female,Loyal Customer,27,Business travel,Business,3904,1,1,1,1,5,5,5,5,5,5,4,3,5,5,59,44.0,satisfied +35836,70940,Male,Loyal Customer,31,Business travel,Business,612,1,1,1,1,3,4,3,3,5,2,4,2,4,3,15,6.0,satisfied +35837,9917,Female,Loyal Customer,17,Business travel,Business,357,2,1,2,1,2,2,2,2,2,3,3,1,2,2,91,86.0,neutral or dissatisfied +35838,116379,Male,Loyal Customer,14,Personal Travel,Eco,308,4,5,4,4,2,4,1,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +35839,31119,Female,Loyal Customer,38,Business travel,Business,991,1,1,2,1,3,1,2,5,5,5,5,5,5,1,0,0.0,satisfied +35840,49010,Male,Loyal Customer,31,Business travel,Business,2513,1,1,3,1,4,5,5,4,5,4,1,5,3,4,0,0.0,satisfied +35841,62873,Male,Loyal Customer,52,Personal Travel,Eco,2446,2,4,2,1,4,2,4,4,3,3,5,4,4,4,7,0.0,neutral or dissatisfied +35842,80901,Male,Loyal Customer,29,Personal Travel,Business,341,1,1,4,3,1,4,1,1,3,1,4,2,4,1,0,0.0,neutral or dissatisfied +35843,75947,Female,Loyal Customer,56,Business travel,Business,297,1,1,1,1,3,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +35844,41257,Male,Loyal Customer,49,Business travel,Business,2985,2,2,2,2,1,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +35845,91199,Female,Loyal Customer,61,Personal Travel,Eco,240,1,1,1,4,3,3,4,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +35846,91974,Female,Loyal Customer,31,Business travel,Eco Plus,2446,4,2,2,2,4,3,4,4,2,1,2,1,3,4,4,0.0,neutral or dissatisfied +35847,13251,Female,Loyal Customer,52,Business travel,Eco,772,3,4,4,4,3,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +35848,63314,Female,Loyal Customer,55,Business travel,Eco,337,3,1,4,1,3,4,3,3,3,3,3,4,3,2,4,14.0,neutral or dissatisfied +35849,116003,Male,Loyal Customer,47,Personal Travel,Eco,358,3,5,3,2,2,3,2,2,3,5,5,3,5,2,4,1.0,neutral or dissatisfied +35850,17258,Female,disloyal Customer,35,Business travel,Eco,872,3,2,2,1,2,2,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +35851,72026,Male,Loyal Customer,49,Business travel,Business,3784,4,4,4,4,4,4,4,4,5,3,4,4,3,4,19,0.0,satisfied +35852,86038,Female,Loyal Customer,26,Personal Travel,Eco,447,3,5,3,1,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +35853,73860,Female,Loyal Customer,53,Personal Travel,Eco,1810,1,3,1,3,3,3,4,1,1,1,1,4,1,2,1,16.0,neutral or dissatisfied +35854,43549,Female,disloyal Customer,25,Business travel,Eco,308,2,4,2,3,2,2,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +35855,2701,Male,disloyal Customer,37,Business travel,Eco,562,1,1,1,4,2,1,2,2,2,4,4,4,4,2,42,65.0,neutral or dissatisfied +35856,40071,Male,disloyal Customer,24,Business travel,Eco,493,0,0,0,2,3,0,3,3,2,4,2,2,4,3,0,0.0,satisfied +35857,14737,Male,Loyal Customer,44,Business travel,Eco,404,5,1,1,1,5,5,5,5,5,5,1,5,1,5,19,63.0,satisfied +35858,45798,Female,disloyal Customer,47,Business travel,Eco,391,4,1,3,4,5,3,1,5,4,4,4,3,4,5,0,1.0,neutral or dissatisfied +35859,62136,Male,Loyal Customer,54,Business travel,Business,2565,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +35860,91406,Male,Loyal Customer,27,Personal Travel,Eco,2342,5,5,5,3,5,2,2,3,1,2,3,2,1,2,0,0.0,satisfied +35861,66195,Male,Loyal Customer,47,Business travel,Business,1644,5,5,5,5,4,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +35862,122623,Female,Loyal Customer,10,Personal Travel,Eco,728,2,3,3,3,4,3,2,4,2,4,3,1,3,4,6,14.0,neutral or dissatisfied +35863,8917,Male,Loyal Customer,51,Business travel,Business,3912,5,5,5,5,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +35864,30013,Female,disloyal Customer,23,Business travel,Eco,183,3,4,3,3,4,3,4,4,1,3,2,4,4,4,0,0.0,neutral or dissatisfied +35865,90995,Female,disloyal Customer,16,Business travel,Eco,240,5,0,5,2,2,5,2,2,2,1,4,5,5,2,0,0.0,satisfied +35866,122617,Female,Loyal Customer,50,Personal Travel,Eco,728,1,4,2,2,4,4,5,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +35867,92678,Female,Loyal Customer,57,Business travel,Business,507,5,5,5,5,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +35868,126046,Female,Loyal Customer,32,Business travel,Business,468,1,1,1,1,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +35869,32893,Male,Loyal Customer,46,Personal Travel,Eco,216,3,1,3,3,2,3,5,2,2,4,2,1,2,2,0,2.0,neutral or dissatisfied +35870,129156,Male,Loyal Customer,13,Business travel,Business,954,3,3,3,3,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +35871,104074,Male,Loyal Customer,56,Business travel,Business,3805,2,2,2,2,3,4,3,2,2,2,2,1,2,4,12,12.0,neutral or dissatisfied +35872,85432,Female,disloyal Customer,44,Business travel,Business,152,1,0,0,4,3,1,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +35873,72713,Female,Loyal Customer,48,Business travel,Business,3129,3,3,3,3,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +35874,54156,Female,Loyal Customer,36,Business travel,Eco,1400,5,5,5,5,5,5,5,5,3,4,1,4,2,5,2,0.0,satisfied +35875,115272,Female,Loyal Customer,49,Business travel,Business,372,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +35876,74962,Male,Loyal Customer,19,Personal Travel,Eco,2475,2,5,3,3,2,3,2,2,3,3,5,3,5,2,41,87.0,neutral or dissatisfied +35877,39170,Female,disloyal Customer,26,Business travel,Eco,287,2,4,2,2,4,2,4,4,4,3,1,4,5,4,0,0.0,neutral or dissatisfied +35878,44136,Female,disloyal Customer,19,Business travel,Eco,198,1,1,0,4,4,0,4,4,3,1,3,2,3,4,40,40.0,neutral or dissatisfied +35879,70735,Male,Loyal Customer,58,Personal Travel,Eco,675,4,5,4,1,4,4,4,4,3,2,4,4,4,4,19,7.0,satisfied +35880,60274,Male,disloyal Customer,21,Business travel,Eco,2218,3,3,3,3,3,3,3,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +35881,24828,Male,Loyal Customer,58,Business travel,Eco,991,5,1,1,1,4,5,4,4,2,2,2,1,4,4,0,1.0,satisfied +35882,116046,Female,Loyal Customer,28,Personal Travel,Eco,325,0,2,0,3,4,0,4,4,2,5,4,3,3,4,1,0.0,satisfied +35883,69823,Male,Loyal Customer,50,Business travel,Business,3562,4,4,4,4,2,4,5,5,5,5,5,5,5,3,45,26.0,satisfied +35884,79493,Female,Loyal Customer,20,Personal Travel,Business,712,4,5,4,2,2,4,2,2,1,5,3,3,2,2,0,17.0,neutral or dissatisfied +35885,71035,Female,Loyal Customer,35,Business travel,Business,3714,1,1,5,1,5,5,4,2,2,3,2,5,2,5,0,0.0,satisfied +35886,110712,Male,disloyal Customer,22,Business travel,Business,997,4,4,4,2,3,4,3,3,3,4,5,5,4,3,0,0.0,satisfied +35887,67452,Male,Loyal Customer,32,Personal Travel,Eco,721,2,5,2,3,5,2,5,5,4,5,4,3,5,5,25,14.0,neutral or dissatisfied +35888,119,Female,Loyal Customer,37,Business travel,Eco,162,2,1,1,1,2,2,2,2,3,4,3,3,3,2,0,21.0,neutral or dissatisfied +35889,86181,Female,Loyal Customer,46,Business travel,Eco,306,2,4,4,4,5,4,3,2,2,2,2,2,2,2,9,6.0,neutral or dissatisfied +35890,2986,Male,Loyal Customer,72,Business travel,Business,922,3,3,4,3,2,4,4,5,5,4,5,3,5,4,4,0.0,satisfied +35891,64619,Female,Loyal Customer,46,Business travel,Business,2340,1,1,1,1,2,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +35892,48435,Female,Loyal Customer,26,Business travel,Business,2351,1,1,5,1,4,4,4,4,1,1,4,3,4,4,30,,satisfied +35893,72386,Male,disloyal Customer,28,Business travel,Business,1121,5,5,5,5,3,5,4,3,3,2,4,5,4,3,6,31.0,satisfied +35894,39912,Female,Loyal Customer,60,Personal Travel,Eco Plus,272,3,0,3,1,3,5,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +35895,72626,Female,Loyal Customer,42,Personal Travel,Eco,985,3,4,4,5,4,4,4,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +35896,119356,Male,Loyal Customer,19,Personal Travel,Eco Plus,214,2,0,2,3,3,2,3,3,5,5,4,4,5,3,0,2.0,neutral or dissatisfied +35897,14110,Female,Loyal Customer,43,Personal Travel,Eco,425,3,0,3,3,3,4,5,3,3,3,3,4,3,4,14,0.0,neutral or dissatisfied +35898,20482,Female,Loyal Customer,46,Business travel,Eco,130,4,2,2,2,5,3,3,4,4,4,4,1,4,4,10,7.0,satisfied +35899,75609,Female,Loyal Customer,21,Personal Travel,Eco,337,2,1,2,3,5,2,5,5,3,1,2,1,3,5,0,0.0,neutral or dissatisfied +35900,38461,Female,Loyal Customer,45,Personal Travel,Eco,1504,2,5,3,3,5,4,5,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +35901,127089,Male,disloyal Customer,18,Business travel,Eco,651,4,0,4,5,4,4,4,4,3,5,4,4,3,4,1,0.0,neutral or dissatisfied +35902,52471,Female,Loyal Customer,40,Personal Travel,Eco Plus,261,2,4,0,3,4,0,4,4,5,3,3,4,5,4,0,0.0,neutral or dissatisfied +35903,14397,Male,Loyal Customer,44,Personal Travel,Eco,789,1,5,1,3,1,1,1,1,4,5,5,3,5,1,43,19.0,neutral or dissatisfied +35904,36755,Male,Loyal Customer,39,Business travel,Business,2588,2,2,4,2,4,4,4,5,5,5,4,4,1,4,0,0.0,satisfied +35905,93417,Female,Loyal Customer,40,Business travel,Business,671,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +35906,21793,Female,Loyal Customer,38,Business travel,Eco,352,1,4,1,4,1,1,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +35907,21753,Female,Loyal Customer,59,Personal Travel,Eco,563,2,1,1,3,4,3,3,5,5,1,1,1,5,1,0,0.0,neutral or dissatisfied +35908,51492,Female,disloyal Customer,24,Business travel,Business,598,3,3,3,4,3,3,3,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +35909,68374,Female,Loyal Customer,36,Business travel,Business,2149,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,2.0,satisfied +35910,10589,Male,Loyal Customer,41,Business travel,Business,1889,0,0,0,4,5,4,4,1,1,1,1,4,1,4,6,5.0,satisfied +35911,9707,Male,Loyal Customer,24,Personal Travel,Eco,212,2,4,2,3,5,2,5,5,4,5,3,1,4,5,0,7.0,neutral or dissatisfied +35912,45264,Female,disloyal Customer,30,Business travel,Business,188,2,2,2,3,2,2,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +35913,83332,Female,Loyal Customer,46,Business travel,Business,2368,4,4,4,4,1,1,3,5,5,5,5,1,5,3,0,0.0,satisfied +35914,108103,Male,Loyal Customer,28,Business travel,Business,2464,1,1,1,1,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +35915,59485,Female,Loyal Customer,28,Business travel,Business,2253,5,5,5,5,5,5,5,5,3,5,4,4,4,5,4,0.0,satisfied +35916,125933,Male,Loyal Customer,42,Personal Travel,Eco,861,1,2,0,4,3,0,3,3,3,2,4,2,3,3,40,33.0,neutral or dissatisfied +35917,65195,Male,Loyal Customer,56,Personal Travel,Eco,224,1,3,1,3,5,1,5,5,2,4,4,1,4,5,48,44.0,neutral or dissatisfied +35918,96030,Male,Loyal Customer,38,Business travel,Business,1090,2,4,4,4,5,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +35919,125071,Female,Loyal Customer,85,Business travel,Business,3156,3,5,5,5,4,3,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +35920,3977,Female,Loyal Customer,47,Business travel,Business,2975,5,5,5,5,3,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +35921,41841,Female,Loyal Customer,61,Personal Travel,Eco,462,2,3,2,3,3,4,4,2,2,2,4,4,2,2,0,0.0,neutral or dissatisfied +35922,9649,Female,disloyal Customer,59,Business travel,Business,212,5,5,5,4,5,5,5,5,5,3,5,3,4,5,8,7.0,satisfied +35923,108133,Female,Loyal Customer,37,Business travel,Business,3577,2,2,2,2,2,4,3,2,2,2,2,4,2,4,23,26.0,neutral or dissatisfied +35924,105591,Female,disloyal Customer,25,Business travel,Business,577,4,0,4,2,2,4,2,2,5,2,5,4,5,2,0,0.0,satisfied +35925,38337,Male,Loyal Customer,42,Business travel,Business,3293,1,1,1,1,3,4,3,5,5,5,5,4,5,4,0,2.0,satisfied +35926,111989,Female,Loyal Customer,32,Personal Travel,Eco,533,4,4,4,4,1,4,1,1,3,3,4,5,4,1,10,11.0,neutral or dissatisfied +35927,83166,Female,Loyal Customer,32,Personal Travel,Eco Plus,1127,3,5,3,4,5,3,4,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +35928,44445,Male,Loyal Customer,62,Business travel,Eco Plus,420,4,1,1,1,4,4,4,4,1,5,2,2,3,4,5,0.0,satisfied +35929,95655,Female,disloyal Customer,40,Business travel,Business,445,1,1,1,3,4,1,4,4,1,4,4,4,4,4,61,49.0,neutral or dissatisfied +35930,92182,Female,Loyal Customer,39,Business travel,Business,1979,2,2,2,2,2,4,5,4,4,4,4,4,4,3,40,35.0,satisfied +35931,109706,Male,Loyal Customer,43,Business travel,Business,587,5,5,5,5,3,5,5,2,2,2,2,4,2,3,8,4.0,satisfied +35932,114733,Female,Loyal Customer,38,Business travel,Business,3731,1,1,4,1,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +35933,43121,Male,Loyal Customer,61,Personal Travel,Eco,391,2,5,2,2,2,3,3,5,4,5,5,3,1,3,133,118.0,neutral or dissatisfied +35934,50082,Female,Loyal Customer,24,Business travel,Business,1742,2,3,3,3,1,1,2,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +35935,38428,Male,Loyal Customer,21,Personal Travel,Eco,965,4,5,4,1,1,4,1,1,5,4,4,4,4,1,0,0.0,satisfied +35936,49121,Male,Loyal Customer,38,Business travel,Eco,156,5,2,2,2,5,5,5,5,5,4,4,5,5,5,0,0.0,satisfied +35937,128281,Female,Loyal Customer,50,Business travel,Business,1581,5,5,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +35938,7058,Female,disloyal Customer,43,Business travel,Business,157,3,3,3,4,5,3,5,5,3,2,4,4,5,5,1,0.0,neutral or dissatisfied +35939,40570,Female,disloyal Customer,24,Business travel,Business,391,3,3,3,3,3,3,4,3,2,5,4,3,4,3,71,59.0,neutral or dissatisfied +35940,51631,Female,Loyal Customer,63,Business travel,Business,651,3,3,3,3,3,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +35941,125671,Male,Loyal Customer,58,Business travel,Eco,814,3,3,3,3,2,3,2,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +35942,18657,Male,Loyal Customer,49,Personal Travel,Eco,201,3,5,3,4,2,3,2,2,4,3,1,1,2,2,0,0.0,neutral or dissatisfied +35943,100549,Female,Loyal Customer,55,Business travel,Eco Plus,180,3,5,5,5,5,4,1,3,3,3,3,2,3,3,10,1.0,satisfied +35944,78666,Female,Loyal Customer,42,Business travel,Business,3711,5,5,5,5,3,5,4,5,5,5,5,3,5,4,18,20.0,satisfied +35945,48971,Female,Loyal Customer,30,Business travel,Business,2662,1,1,1,1,5,5,5,5,4,4,5,1,1,5,71,72.0,satisfied +35946,79782,Female,Loyal Customer,60,Personal Travel,Business,1010,1,4,1,1,4,5,3,2,2,1,2,2,2,5,0,0.0,neutral or dissatisfied +35947,90887,Male,Loyal Customer,60,Business travel,Business,515,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +35948,104535,Male,disloyal Customer,23,Business travel,Eco,1256,4,4,4,4,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +35949,53141,Female,Loyal Customer,26,Business travel,Eco,413,1,3,3,3,1,1,3,1,3,2,3,4,3,1,44,38.0,neutral or dissatisfied +35950,76851,Male,Loyal Customer,30,Business travel,Eco,1195,4,3,3,3,4,4,4,4,4,1,3,2,4,4,19,21.0,neutral or dissatisfied +35951,11701,Male,Loyal Customer,36,Business travel,Business,2864,3,3,3,3,2,4,4,4,4,4,4,4,4,5,3,0.0,satisfied +35952,85689,Female,disloyal Customer,25,Business travel,Business,1547,3,5,4,4,5,4,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +35953,60771,Male,disloyal Customer,28,Business travel,Eco,804,3,3,3,4,5,3,1,5,3,2,4,4,3,5,41,22.0,neutral or dissatisfied +35954,57064,Female,Loyal Customer,44,Personal Travel,Business,2065,3,5,3,1,3,3,4,4,4,3,4,3,4,4,1,0.0,neutral or dissatisfied +35955,28900,Male,Loyal Customer,23,Business travel,Business,1689,4,4,4,4,4,4,4,4,5,2,5,4,1,4,0,0.0,satisfied +35956,86472,Female,Loyal Customer,17,Business travel,Business,794,2,5,5,5,2,2,2,2,1,5,4,1,3,2,11,0.0,neutral or dissatisfied +35957,122061,Female,Loyal Customer,53,Business travel,Business,3696,1,3,3,3,4,3,4,2,2,2,1,2,2,2,90,87.0,neutral or dissatisfied +35958,129647,Male,Loyal Customer,64,Business travel,Eco,337,2,2,2,2,2,2,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +35959,93794,Male,Loyal Customer,47,Business travel,Business,3722,4,4,4,4,5,5,4,5,5,5,5,3,5,4,123,,satisfied +35960,86261,Male,Loyal Customer,25,Personal Travel,Eco,226,1,5,1,5,5,1,5,5,4,4,4,3,4,5,73,68.0,neutral or dissatisfied +35961,58859,Male,disloyal Customer,26,Business travel,Business,888,4,5,5,1,5,5,5,5,5,3,5,4,5,5,70,72.0,satisfied +35962,84255,Male,disloyal Customer,30,Business travel,Eco,1814,2,2,2,3,2,2,1,2,3,1,4,3,4,2,0,8.0,neutral or dissatisfied +35963,24706,Female,Loyal Customer,59,Business travel,Eco,397,4,4,3,3,5,4,3,4,4,4,4,4,4,3,21,27.0,neutral or dissatisfied +35964,108519,Male,Loyal Customer,50,Personal Travel,Eco,519,2,5,2,5,4,2,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +35965,94943,Male,Loyal Customer,31,Business travel,Business,2755,2,3,3,3,2,2,2,2,3,5,4,4,4,2,7,4.0,neutral or dissatisfied +35966,89873,Male,disloyal Customer,24,Business travel,Eco,1310,4,5,5,1,4,4,2,4,3,3,5,3,5,4,0,0.0,satisfied +35967,31139,Male,Loyal Customer,48,Personal Travel,Eco,991,3,5,3,5,4,3,4,4,3,2,5,4,5,4,19,29.0,neutral or dissatisfied +35968,104071,Male,disloyal Customer,27,Business travel,Business,359,5,5,5,4,1,5,1,1,5,5,5,3,4,1,0,0.0,satisfied +35969,60794,Female,Loyal Customer,53,Business travel,Business,3997,2,2,4,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +35970,29617,Male,Loyal Customer,60,Business travel,Eco,680,4,2,1,2,4,4,4,4,2,4,2,4,4,4,0,0.0,satisfied +35971,77430,Female,Loyal Customer,39,Personal Travel,Eco,590,2,4,2,3,3,2,2,3,3,3,5,4,5,3,7,0.0,neutral or dissatisfied +35972,44382,Female,disloyal Customer,38,Business travel,Eco Plus,229,4,3,3,2,5,3,5,5,2,3,4,4,4,5,0,5.0,satisfied +35973,52232,Female,Loyal Customer,27,Business travel,Business,3159,1,1,1,1,4,4,4,4,1,1,5,4,2,4,22,6.0,satisfied +35974,125656,Female,Loyal Customer,55,Business travel,Business,759,4,4,4,4,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +35975,12445,Female,Loyal Customer,27,Personal Travel,Eco,305,3,5,3,1,3,3,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +35976,9919,Male,Loyal Customer,38,Business travel,Business,534,3,4,4,4,4,4,4,3,3,3,3,3,3,2,26,11.0,neutral or dissatisfied +35977,61678,Male,disloyal Customer,49,Business travel,Business,1379,4,4,4,3,2,4,4,2,3,3,5,5,4,2,7,7.0,satisfied +35978,79360,Female,Loyal Customer,51,Business travel,Business,2585,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +35979,100768,Male,disloyal Customer,26,Business travel,Business,1411,2,2,2,1,1,2,1,1,5,2,5,4,5,1,19,6.0,neutral or dissatisfied +35980,108389,Male,Loyal Customer,9,Personal Travel,Eco,1750,3,4,3,3,3,1,1,1,3,4,4,1,2,1,448,445.0,neutral or dissatisfied +35981,74736,Male,Loyal Customer,51,Personal Travel,Eco,1464,3,5,3,5,3,3,4,3,5,3,4,5,5,3,63,60.0,neutral or dissatisfied +35982,7881,Male,disloyal Customer,24,Business travel,Eco,948,3,3,3,4,2,3,2,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +35983,129528,Female,Loyal Customer,57,Business travel,Business,2583,5,1,5,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +35984,32129,Male,Loyal Customer,48,Business travel,Business,3081,1,1,1,1,3,1,2,4,4,4,4,4,4,1,0,0.0,satisfied +35985,64679,Male,Loyal Customer,42,Business travel,Business,1976,5,5,2,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +35986,8556,Female,Loyal Customer,34,Business travel,Business,109,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,3.0,satisfied +35987,50387,Female,disloyal Customer,25,Business travel,Eco,110,2,1,2,3,1,2,1,1,1,5,3,4,4,1,0,0.0,neutral or dissatisfied +35988,76327,Female,Loyal Customer,41,Personal Travel,Eco,2182,3,2,3,3,1,3,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +35989,36587,Male,Loyal Customer,33,Business travel,Business,1630,2,2,2,2,2,2,2,2,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +35990,107579,Female,Loyal Customer,39,Personal Travel,Eco,1521,3,4,3,3,5,3,5,5,1,2,4,4,3,5,3,8.0,neutral or dissatisfied +35991,33511,Female,Loyal Customer,51,Business travel,Eco Plus,965,3,2,2,2,5,5,3,3,3,3,3,4,3,3,0,0.0,satisfied +35992,59099,Female,Loyal Customer,27,Personal Travel,Eco,1781,4,5,4,3,1,4,3,1,4,5,4,5,4,1,12,37.0,neutral or dissatisfied +35993,11502,Male,Loyal Customer,19,Personal Travel,Eco Plus,308,4,2,1,4,5,1,1,5,2,3,4,4,3,5,0,0.0,satisfied +35994,51102,Female,Loyal Customer,48,Personal Travel,Eco,156,1,2,1,3,4,4,4,3,3,1,3,1,3,3,0,3.0,neutral or dissatisfied +35995,77363,Male,disloyal Customer,25,Business travel,Business,588,1,4,1,3,4,1,2,4,4,4,4,5,5,4,17,0.0,neutral or dissatisfied +35996,8301,Male,Loyal Customer,51,Business travel,Business,2462,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +35997,97366,Male,Loyal Customer,39,Personal Travel,Eco,872,2,4,2,4,5,2,5,5,3,1,4,3,4,5,43,21.0,neutral or dissatisfied +35998,81277,Male,Loyal Customer,53,Business travel,Eco,1020,4,2,2,2,5,4,5,5,3,1,4,4,3,5,108,89.0,neutral or dissatisfied +35999,102346,Female,disloyal Customer,36,Business travel,Eco,236,1,1,2,3,2,2,2,2,4,4,3,4,3,2,18,15.0,neutral or dissatisfied +36000,33879,Male,disloyal Customer,31,Business travel,Eco,994,4,4,4,3,5,4,5,5,1,5,3,1,4,5,36,41.0,neutral or dissatisfied +36001,110313,Female,Loyal Customer,42,Business travel,Business,1560,4,4,4,4,3,5,4,5,5,5,5,3,5,4,9,0.0,satisfied +36002,16807,Female,Loyal Customer,41,Business travel,Eco,645,2,3,3,3,2,2,2,2,5,2,4,2,1,2,0,0.0,satisfied +36003,10826,Male,disloyal Customer,18,Business travel,Eco,295,4,2,4,3,1,4,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +36004,52578,Male,disloyal Customer,26,Business travel,Eco,119,5,0,5,3,2,5,2,2,5,2,5,5,4,2,0,0.0,satisfied +36005,109600,Female,Loyal Customer,20,Personal Travel,Eco Plus,994,3,5,3,3,5,3,5,5,3,5,5,5,4,5,19,17.0,neutral or dissatisfied +36006,18955,Male,Loyal Customer,22,Business travel,Eco Plus,500,0,5,0,4,3,0,3,3,5,3,2,4,4,3,1,0.0,satisfied +36007,33299,Female,Loyal Customer,20,Personal Travel,Eco Plus,101,3,2,3,3,1,3,1,1,4,5,3,4,2,1,6,18.0,neutral or dissatisfied +36008,93921,Male,Loyal Customer,44,Business travel,Business,3577,3,3,1,3,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +36009,77324,Female,Loyal Customer,59,Business travel,Business,588,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +36010,31496,Male,Loyal Customer,43,Business travel,Eco,862,4,4,4,4,4,4,4,4,3,5,1,4,2,4,0,0.0,satisfied +36011,14271,Female,Loyal Customer,44,Business travel,Business,429,5,5,5,5,1,5,3,5,5,5,5,5,5,5,0,0.0,satisfied +36012,42233,Female,Loyal Customer,44,Business travel,Business,2568,1,1,5,1,4,3,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +36013,81594,Female,Loyal Customer,46,Business travel,Business,1655,0,0,0,2,5,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +36014,36112,Female,Loyal Customer,47,Business travel,Business,1609,1,1,1,1,3,3,3,1,1,1,1,1,1,3,47,49.0,neutral or dissatisfied +36015,37581,Male,Loyal Customer,46,Business travel,Eco,669,2,4,4,4,2,2,2,2,4,3,4,4,4,2,0,6.0,neutral or dissatisfied +36016,102586,Female,disloyal Customer,22,Business travel,Eco,488,2,2,1,4,1,1,1,1,1,1,3,4,3,1,21,18.0,neutral or dissatisfied +36017,23674,Male,Loyal Customer,29,Business travel,Eco,196,0,0,0,1,2,0,2,2,3,5,1,3,2,2,32,22.0,satisfied +36018,102153,Female,Loyal Customer,59,Business travel,Business,258,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +36019,122464,Female,disloyal Customer,38,Business travel,Business,808,4,4,4,4,2,4,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +36020,98707,Female,Loyal Customer,46,Business travel,Business,992,4,4,4,4,2,4,4,3,3,2,3,4,3,3,0,0.0,satisfied +36021,111558,Male,Loyal Customer,44,Business travel,Business,1703,3,2,2,2,2,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +36022,64642,Female,Loyal Customer,63,Business travel,Business,190,1,1,1,1,3,5,4,4,4,4,5,5,4,4,8,6.0,satisfied +36023,67883,Female,Loyal Customer,34,Personal Travel,Eco,1242,4,5,4,5,2,4,2,2,5,3,3,4,4,2,93,89.0,neutral or dissatisfied +36024,54768,Female,Loyal Customer,47,Business travel,Eco Plus,854,5,3,3,3,5,5,5,5,5,5,5,2,5,2,17,28.0,satisfied +36025,110595,Male,Loyal Customer,46,Personal Travel,Eco,674,4,5,4,1,3,4,3,3,4,4,5,3,5,3,70,59.0,neutral or dissatisfied +36026,82289,Female,Loyal Customer,43,Business travel,Business,1481,5,5,2,5,4,5,4,5,5,5,5,4,5,3,3,9.0,satisfied +36027,71191,Male,Loyal Customer,47,Business travel,Business,2015,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +36028,68871,Female,Loyal Customer,39,Business travel,Business,1061,5,5,5,5,5,5,5,1,1,2,1,3,1,4,0,0.0,satisfied +36029,54106,Male,Loyal Customer,57,Business travel,Business,1400,4,4,4,4,4,4,4,3,3,3,3,3,3,3,51,28.0,satisfied +36030,71229,Male,Loyal Customer,24,Business travel,Business,733,5,5,5,5,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +36031,75278,Male,Loyal Customer,17,Personal Travel,Eco,1744,3,0,3,1,5,3,5,5,3,2,5,4,5,5,3,0.0,neutral or dissatisfied +36032,33472,Female,disloyal Customer,18,Business travel,Eco,896,3,4,4,3,4,1,1,1,5,5,3,1,4,1,0,21.0,neutral or dissatisfied +36033,78961,Female,Loyal Customer,56,Business travel,Business,356,4,4,4,4,2,4,5,3,3,4,3,5,3,3,9,20.0,satisfied +36034,78217,Male,Loyal Customer,32,Personal Travel,Eco,259,1,5,1,4,1,3,3,2,4,1,4,3,4,3,148,144.0,neutral or dissatisfied +36035,35618,Male,Loyal Customer,46,Personal Travel,Eco Plus,1097,2,3,3,4,5,3,5,5,3,1,4,3,3,5,2,29.0,neutral or dissatisfied +36036,8376,Female,disloyal Customer,30,Business travel,Eco,701,3,3,3,4,4,3,4,4,4,4,4,3,4,4,23,47.0,neutral or dissatisfied +36037,115075,Male,Loyal Customer,42,Business travel,Eco,480,3,4,4,4,4,3,4,4,3,3,3,1,4,4,0,2.0,neutral or dissatisfied +36038,73822,Female,Loyal Customer,34,Business travel,Eco,1194,2,1,1,1,2,2,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +36039,6865,Female,Loyal Customer,28,Business travel,Business,2070,3,3,2,3,3,3,3,3,3,4,5,3,5,3,0,0.0,satisfied +36040,30291,Male,Loyal Customer,41,Business travel,Business,1476,3,3,3,3,3,2,4,4,4,4,4,2,4,2,0,0.0,satisfied +36041,35436,Male,Loyal Customer,35,Personal Travel,Eco,1069,2,5,2,1,4,2,4,4,2,1,1,5,3,4,58,41.0,neutral or dissatisfied +36042,86101,Male,Loyal Customer,44,Personal Travel,Business,226,1,1,1,3,3,2,2,5,5,1,1,2,5,4,0,0.0,neutral or dissatisfied +36043,41809,Male,disloyal Customer,22,Business travel,Eco,257,2,3,2,2,5,2,2,5,1,2,2,4,3,5,55,38.0,neutral or dissatisfied +36044,54673,Female,Loyal Customer,31,Business travel,Business,787,5,5,5,5,3,3,3,3,1,1,4,5,2,3,1,0.0,satisfied +36045,99735,Female,Loyal Customer,55,Business travel,Business,2996,3,1,1,1,4,3,3,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +36046,95721,Female,disloyal Customer,38,Business travel,Business,419,1,1,1,4,5,1,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +36047,54765,Male,Loyal Customer,30,Business travel,Eco Plus,965,5,1,1,1,5,5,5,5,4,1,4,1,1,5,87,117.0,satisfied +36048,25770,Male,disloyal Customer,20,Business travel,Business,762,2,3,2,3,3,2,3,3,4,4,4,2,3,3,18,9.0,neutral or dissatisfied +36049,8834,Female,Loyal Customer,30,Business travel,Business,552,4,4,4,4,4,4,4,4,4,3,4,4,4,4,16,14.0,satisfied +36050,93482,Female,disloyal Customer,49,Business travel,Business,1107,5,5,5,3,2,5,2,2,3,2,5,4,4,2,1,0.0,satisfied +36051,76846,Male,Loyal Customer,49,Business travel,Business,1777,4,4,4,4,5,5,5,4,4,4,4,4,4,4,1,1.0,satisfied +36052,45699,Female,Loyal Customer,50,Business travel,Eco Plus,826,4,1,1,1,2,2,2,5,5,4,5,2,5,3,0,0.0,satisfied +36053,85983,Female,disloyal Customer,50,Business travel,Business,554,3,3,3,1,3,3,3,3,3,5,5,4,4,3,21,0.0,neutral or dissatisfied +36054,57330,Female,Loyal Customer,45,Business travel,Business,1635,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +36055,4101,Male,Loyal Customer,44,Business travel,Business,2647,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,8.0,satisfied +36056,44874,Male,Loyal Customer,31,Business travel,Eco,240,3,5,5,5,3,3,3,3,1,4,4,1,4,3,0,9.0,neutral or dissatisfied +36057,11938,Male,Loyal Customer,47,Business travel,Eco,781,2,5,5,5,1,2,1,1,4,1,3,4,3,1,38,27.0,neutral or dissatisfied +36058,50652,Female,Loyal Customer,40,Personal Travel,Eco,156,4,3,4,4,2,4,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +36059,81318,Male,Loyal Customer,53,Business travel,Business,2091,5,5,4,5,4,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +36060,45236,Female,Loyal Customer,36,Personal Travel,Eco,1013,4,1,4,4,5,4,4,5,4,4,4,4,3,5,2,27.0,neutral or dissatisfied +36061,22911,Male,disloyal Customer,35,Business travel,Business,630,2,2,2,3,5,2,5,5,3,3,3,3,3,5,2,1.0,neutral or dissatisfied +36062,123594,Female,Loyal Customer,22,Personal Travel,Eco,1773,2,1,2,2,3,2,3,3,1,3,2,3,2,3,0,0.0,neutral or dissatisfied +36063,43100,Female,Loyal Customer,29,Personal Travel,Eco,192,1,5,1,5,5,1,5,5,4,5,4,5,5,5,1,22.0,neutral or dissatisfied +36064,120093,Female,Loyal Customer,56,Business travel,Business,1576,4,4,4,4,4,4,4,5,5,5,5,5,5,3,115,,satisfied +36065,41083,Male,Loyal Customer,45,Business travel,Business,224,4,4,4,4,5,5,4,5,5,5,5,3,5,2,37,26.0,satisfied +36066,47036,Female,disloyal Customer,43,Business travel,Eco,639,5,0,5,1,1,5,1,1,3,2,2,5,5,1,0,2.0,satisfied +36067,110543,Female,disloyal Customer,26,Business travel,Business,674,4,4,4,2,3,4,3,3,3,4,4,3,5,3,0,0.0,satisfied +36068,43412,Male,Loyal Customer,55,Business travel,Eco Plus,402,5,4,4,4,4,5,4,4,2,4,5,3,3,4,0,6.0,satisfied +36069,68910,Male,Loyal Customer,42,Personal Travel,Eco,1061,2,4,2,5,4,2,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +36070,14229,Female,Loyal Customer,31,Business travel,Eco Plus,692,4,5,5,5,4,4,4,4,5,1,2,4,1,4,111,103.0,satisfied +36071,65093,Male,Loyal Customer,21,Personal Travel,Eco,247,4,4,4,1,2,4,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +36072,117614,Male,Loyal Customer,39,Business travel,Business,2015,1,3,3,3,4,4,3,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +36073,125225,Male,Loyal Customer,55,Business travel,Business,3808,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,12.0,satisfied +36074,52212,Male,Loyal Customer,57,Business travel,Eco,261,5,1,1,1,4,5,4,4,5,5,4,4,3,4,0,0.0,satisfied +36075,66032,Female,disloyal Customer,22,Business travel,Eco,1055,4,4,4,2,5,4,4,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +36076,115060,Female,Loyal Customer,44,Business travel,Business,417,1,1,4,1,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +36077,95826,Male,Loyal Customer,46,Personal Travel,Eco,1428,3,4,3,3,5,3,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +36078,61863,Male,Loyal Customer,43,Personal Travel,Eco Plus,1635,2,4,2,2,2,2,2,2,4,2,5,4,5,2,17,0.0,neutral or dissatisfied +36079,75557,Female,Loyal Customer,51,Business travel,Business,2892,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +36080,103607,Female,Loyal Customer,34,Personal Travel,Business,405,1,4,1,5,4,5,4,2,2,1,2,5,2,4,4,0.0,neutral or dissatisfied +36081,30963,Female,Loyal Customer,19,Personal Travel,Eco,1024,3,3,3,3,4,3,4,4,2,5,4,2,3,4,6,13.0,neutral or dissatisfied +36082,84359,Female,Loyal Customer,51,Business travel,Business,591,4,3,3,3,4,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +36083,95418,Male,Loyal Customer,57,Business travel,Business,1922,5,5,4,5,5,4,4,4,4,4,4,4,4,4,9,9.0,satisfied +36084,80682,Female,Loyal Customer,18,Business travel,Business,874,3,2,2,2,3,3,3,3,1,4,4,2,3,3,13,0.0,neutral or dissatisfied +36085,99767,Male,Loyal Customer,51,Business travel,Business,255,4,4,4,4,4,4,5,4,4,4,4,3,4,4,99,110.0,satisfied +36086,57430,Male,Loyal Customer,35,Business travel,Eco,533,1,4,5,4,1,1,1,1,1,1,2,2,3,1,0,0.0,neutral or dissatisfied +36087,94080,Female,disloyal Customer,24,Business travel,Eco,562,2,1,2,3,2,2,4,2,4,5,3,2,2,2,0,0.0,neutral or dissatisfied +36088,82627,Female,Loyal Customer,52,Personal Travel,Eco,528,4,5,4,2,4,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +36089,1302,Female,Loyal Customer,68,Personal Travel,Eco,164,2,4,2,4,3,4,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +36090,97799,Female,Loyal Customer,50,Personal Travel,Eco,471,2,5,3,2,1,1,1,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +36091,42051,Female,disloyal Customer,37,Business travel,Eco,106,1,1,1,1,1,1,4,1,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +36092,60360,Male,Loyal Customer,68,Personal Travel,Business,1452,2,4,2,5,4,3,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +36093,33440,Female,disloyal Customer,38,Business travel,Eco,855,2,1,1,4,1,5,4,2,5,3,3,4,3,4,0,47.0,neutral or dissatisfied +36094,51840,Female,Loyal Customer,67,Personal Travel,Eco Plus,493,2,4,2,2,5,4,5,5,5,2,2,4,5,4,0,0.0,neutral or dissatisfied +36095,22126,Male,Loyal Customer,67,Personal Travel,Eco,743,3,4,3,3,1,3,1,1,4,4,5,5,4,1,0,1.0,neutral or dissatisfied +36096,95629,Female,Loyal Customer,40,Personal Travel,Eco,670,3,4,4,3,3,4,3,3,5,4,4,4,4,3,11,4.0,neutral or dissatisfied +36097,27799,Female,disloyal Customer,23,Business travel,Eco,680,3,3,3,4,1,3,1,1,1,3,4,3,4,1,10,8.0,neutral or dissatisfied +36098,120026,Male,Loyal Customer,58,Personal Travel,Eco,511,2,4,2,1,3,2,3,3,3,5,4,5,5,3,28,35.0,neutral or dissatisfied +36099,52052,Male,Loyal Customer,41,Business travel,Business,438,5,5,5,5,3,4,4,3,3,4,3,2,3,2,0,0.0,satisfied +36100,115757,Male,disloyal Customer,47,Business travel,Business,447,4,4,4,3,2,4,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +36101,125468,Male,Loyal Customer,51,Business travel,Business,1360,3,3,3,3,1,5,3,5,5,5,5,3,5,2,0,0.0,satisfied +36102,110815,Female,Loyal Customer,39,Personal Travel,Eco,997,4,4,4,2,2,4,2,2,2,3,5,1,4,2,21,16.0,satisfied +36103,22348,Female,Loyal Customer,37,Business travel,Business,3316,2,2,4,2,4,5,5,5,5,5,5,3,5,5,27,22.0,satisfied +36104,102703,Male,Loyal Customer,56,Business travel,Eco,365,3,5,4,5,3,3,3,3,2,5,3,3,3,3,13,14.0,neutral or dissatisfied +36105,90940,Male,Loyal Customer,16,Business travel,Business,1948,1,1,5,1,3,3,3,3,2,2,3,5,2,3,0,0.0,satisfied +36106,19986,Female,disloyal Customer,45,Business travel,Eco,589,3,0,3,3,4,3,2,4,3,5,3,2,5,4,19,9.0,neutral or dissatisfied +36107,72580,Male,disloyal Customer,30,Business travel,Eco,929,3,3,3,3,5,3,5,5,1,1,3,2,3,5,0,7.0,neutral or dissatisfied +36108,31129,Male,Loyal Customer,43,Business travel,Eco,991,4,3,5,3,4,4,4,4,2,4,3,1,2,4,0,14.0,neutral or dissatisfied +36109,24674,Female,Loyal Customer,28,Business travel,Eco,691,5,4,4,4,5,5,5,5,5,3,5,5,3,5,0,0.0,satisfied +36110,11941,Female,Loyal Customer,50,Business travel,Business,2472,3,1,1,1,2,2,1,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +36111,52008,Male,Loyal Customer,36,Business travel,Eco,328,4,5,5,5,4,4,4,4,3,5,3,4,5,4,0,0.0,satisfied +36112,74270,Male,disloyal Customer,29,Business travel,Business,2311,1,1,1,2,5,1,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +36113,101054,Female,Loyal Customer,59,Business travel,Business,368,3,3,3,3,4,5,5,2,2,2,2,3,2,4,1,0.0,satisfied +36114,538,Female,Loyal Customer,39,Business travel,Business,3983,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +36115,110415,Female,disloyal Customer,27,Business travel,Eco,663,4,2,5,3,4,5,4,4,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +36116,31397,Male,disloyal Customer,25,Business travel,Eco,1199,4,4,4,4,4,4,4,4,3,5,2,4,4,4,1,3.0,satisfied +36117,4811,Female,disloyal Customer,23,Business travel,Eco Plus,403,2,3,2,3,4,2,5,4,4,5,2,2,2,4,96,129.0,neutral or dissatisfied +36118,30533,Female,Loyal Customer,48,Personal Travel,Eco,683,3,5,3,3,2,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +36119,99601,Female,Loyal Customer,13,Personal Travel,Eco,802,1,5,1,1,2,1,5,2,3,5,3,2,3,2,19,13.0,neutral or dissatisfied +36120,61887,Male,Loyal Customer,36,Business travel,Business,1970,1,1,2,1,1,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +36121,10114,Male,disloyal Customer,38,Business travel,Eco,984,4,4,4,1,1,4,1,1,3,2,2,2,2,1,92,75.0,neutral or dissatisfied +36122,40879,Male,Loyal Customer,60,Personal Travel,Eco,541,1,5,1,2,4,1,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +36123,91696,Male,disloyal Customer,22,Business travel,Eco,588,2,5,3,2,3,3,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +36124,57181,Female,Loyal Customer,12,Personal Travel,Eco,2227,4,3,4,3,4,4,2,4,3,4,4,2,4,4,17,2.0,neutral or dissatisfied +36125,23142,Male,Loyal Customer,49,Business travel,Business,2607,2,4,4,4,5,2,2,3,3,2,2,3,3,3,0,7.0,neutral or dissatisfied +36126,88207,Male,Loyal Customer,49,Business travel,Business,2268,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,1.0,satisfied +36127,5131,Male,Loyal Customer,49,Personal Travel,Eco Plus,137,2,0,2,1,2,2,2,2,3,3,2,5,1,2,82,85.0,neutral or dissatisfied +36128,20241,Female,disloyal Customer,37,Business travel,Eco,228,3,2,3,4,3,4,3,1,5,3,4,3,2,3,153,147.0,neutral or dissatisfied +36129,110646,Male,Loyal Customer,58,Business travel,Business,1635,1,1,1,1,5,5,5,4,4,4,4,4,4,4,25,13.0,satisfied +36130,116591,Female,Loyal Customer,50,Business travel,Business,1662,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +36131,113144,Male,disloyal Customer,30,Business travel,Business,677,1,1,1,5,4,1,3,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +36132,14623,Female,Loyal Customer,52,Business travel,Eco Plus,450,3,1,1,1,5,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +36133,96354,Female,Loyal Customer,64,Personal Travel,Eco,1609,3,1,3,3,2,4,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +36134,86545,Female,disloyal Customer,40,Business travel,Business,762,3,3,3,4,2,3,2,2,4,4,5,4,5,2,1,0.0,neutral or dissatisfied +36135,10217,Male,disloyal Customer,44,Business travel,Business,166,5,4,4,4,5,5,5,5,4,2,5,5,5,5,0,0.0,satisfied +36136,72249,Male,Loyal Customer,41,Business travel,Business,1551,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +36137,79305,Male,disloyal Customer,41,Business travel,Eco,903,2,2,2,3,1,2,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +36138,35207,Male,Loyal Customer,23,Business travel,Eco,1074,5,3,3,3,5,5,4,5,4,2,4,5,4,5,0,0.0,satisfied +36139,26850,Male,Loyal Customer,33,Personal Travel,Eco,224,4,5,4,3,4,4,4,4,3,3,4,5,5,4,0,0.0,satisfied +36140,53961,Male,Loyal Customer,58,Business travel,Eco,717,3,4,4,4,3,3,3,3,2,3,4,2,4,3,44,25.0,neutral or dissatisfied +36141,115822,Female,Loyal Customer,54,Business travel,Eco,371,2,2,2,2,3,3,3,2,2,2,2,1,2,4,95,82.0,neutral or dissatisfied +36142,83689,Male,disloyal Customer,37,Business travel,Eco,177,1,4,1,4,1,1,1,1,1,1,4,4,4,1,0,0.0,neutral or dissatisfied +36143,110258,Female,Loyal Customer,47,Business travel,Business,663,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +36144,8388,Female,Loyal Customer,68,Personal Travel,Eco Plus,701,3,4,3,1,2,2,1,5,5,3,1,2,5,5,14,26.0,neutral or dissatisfied +36145,11533,Female,disloyal Customer,33,Business travel,Business,201,1,1,1,1,1,1,1,1,3,2,5,3,5,1,0,1.0,neutral or dissatisfied +36146,83733,Male,Loyal Customer,20,Personal Travel,Eco,1027,2,4,2,4,4,2,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +36147,110571,Male,Loyal Customer,51,Business travel,Eco,643,3,4,4,4,4,3,4,4,3,2,4,2,3,4,31,28.0,neutral or dissatisfied +36148,5143,Male,Loyal Customer,45,Business travel,Business,622,2,2,2,2,5,5,5,2,2,2,2,4,2,4,40,53.0,satisfied +36149,27943,Male,disloyal Customer,30,Business travel,Eco,1270,1,1,1,3,5,1,5,5,5,1,3,2,5,5,0,0.0,neutral or dissatisfied +36150,95279,Female,Loyal Customer,50,Personal Travel,Eco,677,2,5,2,4,2,5,5,5,5,2,5,4,5,5,42,34.0,neutral or dissatisfied +36151,124308,Female,disloyal Customer,38,Business travel,Eco,255,2,3,2,3,5,2,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +36152,81780,Male,Loyal Customer,45,Business travel,Business,1310,4,4,4,4,3,5,5,5,5,5,5,3,5,4,69,48.0,satisfied +36153,91250,Female,Loyal Customer,63,Personal Travel,Eco,270,4,0,4,3,1,4,3,2,2,4,4,1,2,1,33,30.0,neutral or dissatisfied +36154,22501,Male,Loyal Customer,14,Personal Travel,Eco,238,3,2,3,3,3,3,3,3,3,5,4,1,4,3,107,104.0,neutral or dissatisfied +36155,43859,Female,Loyal Customer,56,Business travel,Eco,199,4,5,5,5,4,2,2,4,4,4,4,5,4,1,0,0.0,satisfied +36156,43021,Female,Loyal Customer,76,Business travel,Business,192,5,5,5,5,2,5,3,4,4,4,5,4,4,5,0,0.0,satisfied +36157,20272,Male,Loyal Customer,52,Personal Travel,Eco,235,4,4,4,2,5,4,5,5,4,2,5,3,5,5,25,19.0,neutral or dissatisfied +36158,58898,Male,Loyal Customer,42,Business travel,Business,888,4,4,4,4,4,4,4,4,4,4,4,3,4,4,9,1.0,satisfied +36159,104443,Female,Loyal Customer,58,Business travel,Business,2204,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,1.0,satisfied +36160,65409,Male,Loyal Customer,67,Personal Travel,Eco,631,2,1,2,1,2,2,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +36161,10729,Male,disloyal Customer,23,Business travel,Eco,517,2,0,2,4,5,2,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +36162,99026,Male,disloyal Customer,20,Business travel,Eco,1009,4,4,4,4,3,4,3,3,5,5,4,5,4,3,2,0.0,satisfied +36163,101960,Female,disloyal Customer,28,Business travel,Eco,628,1,4,1,4,2,1,3,2,3,5,4,2,4,2,7,2.0,neutral or dissatisfied +36164,97176,Female,Loyal Customer,35,Personal Travel,Eco,1211,1,0,1,1,1,1,1,1,5,4,5,5,4,1,0,9.0,neutral or dissatisfied +36165,37232,Male,Loyal Customer,59,Business travel,Business,2483,2,2,2,2,1,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +36166,127333,Female,disloyal Customer,23,Business travel,Business,507,0,2,0,5,2,0,2,2,3,5,4,3,5,2,4,0.0,satisfied +36167,791,Female,disloyal Customer,17,Business travel,Eco,354,3,4,3,4,4,3,4,4,1,4,3,4,4,4,10,12.0,neutral or dissatisfied +36168,97975,Male,Loyal Customer,20,Personal Travel,Eco,612,3,2,3,4,3,3,3,3,2,2,3,2,3,3,1,0.0,neutral or dissatisfied +36169,12271,Male,disloyal Customer,48,Business travel,Business,285,1,1,1,3,5,1,5,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +36170,110389,Female,Loyal Customer,41,Business travel,Business,3732,3,1,1,1,4,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +36171,4808,Male,Loyal Customer,41,Business travel,Business,2710,4,4,4,4,5,4,5,3,3,4,3,4,3,5,12,0.0,satisfied +36172,54275,Male,Loyal Customer,56,Personal Travel,Eco,1222,4,3,4,2,4,4,4,4,1,4,3,1,2,4,61,90.0,neutral or dissatisfied +36173,10819,Male,Loyal Customer,37,Business travel,Business,3648,3,5,5,5,1,3,3,3,3,2,3,2,3,2,1,0.0,neutral or dissatisfied +36174,129604,Male,Loyal Customer,39,Business travel,Business,2419,2,3,3,3,4,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +36175,100506,Female,disloyal Customer,25,Business travel,Business,759,2,5,2,4,1,2,4,1,5,2,4,5,5,1,0,0.0,neutral or dissatisfied +36176,68490,Male,disloyal Customer,35,Business travel,Business,1067,2,2,2,3,3,2,3,3,5,1,2,4,4,3,7,0.0,neutral or dissatisfied +36177,94749,Female,Loyal Customer,60,Business travel,Business,319,3,3,3,3,1,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +36178,19622,Male,Loyal Customer,38,Personal Travel,Eco Plus,416,3,5,3,1,2,3,2,2,3,1,5,4,1,2,10,4.0,neutral or dissatisfied +36179,115779,Female,Loyal Customer,47,Business travel,Eco,446,4,3,3,3,5,3,2,4,4,4,4,3,4,4,44,31.0,neutral or dissatisfied +36180,99697,Female,Loyal Customer,31,Personal Travel,Eco,442,4,1,5,4,5,5,5,5,2,3,3,4,3,5,6,9.0,neutral or dissatisfied +36181,104486,Male,disloyal Customer,10,Business travel,Eco,860,3,3,3,2,3,3,3,3,5,2,4,5,5,3,6,0.0,neutral or dissatisfied +36182,90004,Male,Loyal Customer,39,Business travel,Business,557,2,4,4,4,3,3,4,2,2,2,2,4,2,1,58,40.0,neutral or dissatisfied +36183,109404,Female,Loyal Customer,45,Personal Travel,Eco Plus,1237,1,4,1,2,5,4,4,5,5,1,1,3,5,4,0,0.0,neutral or dissatisfied +36184,113208,Male,Loyal Customer,52,Business travel,Business,2143,3,2,2,2,1,2,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +36185,56506,Male,disloyal Customer,21,Business travel,Business,1065,4,0,4,2,5,4,5,5,3,5,4,5,5,5,0,0.0,satisfied +36186,84240,Male,Loyal Customer,46,Business travel,Eco Plus,432,2,2,2,2,2,2,2,2,3,5,4,1,4,2,19,47.0,neutral or dissatisfied +36187,56617,Female,Loyal Customer,31,Business travel,Business,1920,5,1,3,1,5,4,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +36188,51809,Female,Loyal Customer,31,Personal Travel,Eco,370,2,4,2,4,3,2,3,3,4,5,4,4,3,3,8,16.0,neutral or dissatisfied +36189,55105,Male,Loyal Customer,68,Personal Travel,Eco,1379,5,4,5,5,2,5,2,2,5,3,4,5,4,2,1,0.0,satisfied +36190,24417,Female,Loyal Customer,46,Business travel,Eco,634,2,1,1,1,2,2,2,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +36191,126728,Male,disloyal Customer,22,Business travel,Eco,1383,3,3,3,4,2,3,2,2,3,5,4,4,3,2,32,8.0,neutral or dissatisfied +36192,49988,Female,Loyal Customer,40,Business travel,Eco,266,5,5,5,5,5,5,5,5,3,3,1,2,1,5,0,1.0,satisfied +36193,63911,Male,Loyal Customer,58,Business travel,Business,792,1,1,1,1,4,4,4,1,1,1,1,2,1,1,15,31.0,neutral or dissatisfied +36194,50093,Male,Loyal Customer,44,Business travel,Eco,156,2,2,3,2,2,2,2,2,1,4,3,2,2,2,0,1.0,neutral or dissatisfied +36195,27029,Female,disloyal Customer,25,Business travel,Eco Plus,954,3,0,4,3,4,4,2,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +36196,1461,Female,disloyal Customer,35,Business travel,Business,772,1,1,1,4,1,1,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +36197,52462,Male,disloyal Customer,38,Business travel,Eco Plus,370,3,3,3,4,2,3,2,2,3,5,2,4,1,2,0,2.0,neutral or dissatisfied +36198,21999,Female,Loyal Customer,40,Personal Travel,Eco,500,1,5,1,5,4,1,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +36199,66850,Male,Loyal Customer,56,Personal Travel,Eco,731,1,3,1,4,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +36200,57200,Female,Loyal Customer,38,Business travel,Business,1514,5,5,5,5,2,4,5,5,5,5,5,4,5,3,3,0.0,satisfied +36201,126434,Male,Loyal Customer,29,Personal Travel,Eco Plus,631,1,2,0,3,4,0,4,4,3,4,4,2,3,4,97,83.0,neutral or dissatisfied +36202,68477,Female,Loyal Customer,49,Business travel,Business,2526,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +36203,64266,Male,Loyal Customer,39,Business travel,Business,3523,4,4,4,4,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +36204,61107,Male,Loyal Customer,21,Personal Travel,Eco,1607,2,4,2,1,3,2,3,3,4,5,3,3,5,3,0,0.0,neutral or dissatisfied +36205,124224,Female,Loyal Customer,46,Business travel,Business,1916,5,5,5,5,3,3,4,4,4,4,4,5,4,3,2,0.0,satisfied +36206,90876,Male,disloyal Customer,23,Business travel,Eco,240,4,2,4,4,4,3,3,3,3,3,3,3,4,3,312,304.0,neutral or dissatisfied +36207,95039,Male,Loyal Customer,26,Personal Travel,Eco,189,1,5,1,2,3,1,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +36208,14758,Female,disloyal Customer,17,Business travel,Eco,533,2,2,2,3,2,2,2,2,3,4,3,4,4,2,83,78.0,neutral or dissatisfied +36209,128891,Female,Loyal Customer,30,Business travel,Eco,2454,3,2,2,2,3,2,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +36210,13546,Male,Loyal Customer,39,Business travel,Business,3597,2,3,3,3,5,4,4,2,2,2,2,2,2,4,0,10.0,neutral or dissatisfied +36211,64884,Male,Loyal Customer,48,Business travel,Business,190,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,3.0,satisfied +36212,121027,Male,Loyal Customer,27,Personal Travel,Eco,993,1,4,1,3,2,1,2,2,2,4,3,3,4,2,0,24.0,neutral or dissatisfied +36213,52575,Female,Loyal Customer,39,Business travel,Business,3955,0,3,0,1,2,4,3,5,5,5,5,4,5,2,0,0.0,satisfied +36214,66922,Female,Loyal Customer,26,Business travel,Business,2037,5,5,5,5,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +36215,120488,Female,Loyal Customer,11,Personal Travel,Eco,449,1,4,1,2,1,1,1,1,4,1,5,5,3,1,19,78.0,neutral or dissatisfied +36216,7840,Male,Loyal Customer,51,Personal Travel,Eco Plus,710,3,5,3,3,2,3,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +36217,128403,Female,Loyal Customer,21,Business travel,Eco,621,3,3,4,3,3,3,2,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +36218,100820,Male,Loyal Customer,53,Business travel,Business,2413,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +36219,3594,Female,Loyal Customer,31,Business travel,Business,2798,2,3,3,3,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +36220,25841,Female,disloyal Customer,27,Business travel,Eco,484,3,0,3,4,1,3,1,1,4,5,3,4,2,1,0,0.0,neutral or dissatisfied +36221,5094,Male,Loyal Customer,15,Personal Travel,Eco,122,1,4,1,3,5,1,5,5,1,4,5,1,1,5,8,21.0,neutral or dissatisfied +36222,88040,Male,Loyal Customer,45,Business travel,Business,2628,3,3,3,3,5,5,4,4,4,4,4,5,4,3,109,116.0,satisfied +36223,73673,Male,Loyal Customer,31,Business travel,Business,192,3,3,3,3,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +36224,31779,Male,Loyal Customer,9,Personal Travel,Eco,602,3,5,3,3,1,3,1,1,4,5,5,5,5,1,23,29.0,neutral or dissatisfied +36225,100066,Female,Loyal Customer,29,Personal Travel,Eco,277,1,5,5,3,4,5,5,4,2,5,4,2,3,4,31,43.0,neutral or dissatisfied +36226,79361,Female,Loyal Customer,53,Business travel,Business,3429,4,4,4,4,2,5,5,5,5,5,5,4,5,4,8,0.0,satisfied +36227,83868,Female,Loyal Customer,36,Business travel,Eco Plus,425,3,4,4,4,3,3,3,3,1,2,4,2,4,3,38,66.0,neutral or dissatisfied +36228,123718,Male,Loyal Customer,52,Personal Travel,Eco,214,3,0,3,4,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +36229,1964,Female,Loyal Customer,24,Business travel,Business,3173,5,5,5,5,4,4,4,4,2,5,2,3,3,4,14,22.0,satisfied +36230,127763,Female,Loyal Customer,63,Personal Travel,Eco,255,3,4,0,3,3,1,5,3,3,0,3,1,3,2,49,45.0,neutral or dissatisfied +36231,18079,Male,Loyal Customer,68,Personal Travel,Eco,488,3,0,3,3,5,3,5,5,3,3,4,3,5,5,81,75.0,neutral or dissatisfied +36232,1499,Female,Loyal Customer,27,Personal Travel,Eco,737,4,4,5,2,3,5,3,3,3,2,4,5,4,3,5,16.0,satisfied +36233,107809,Female,disloyal Customer,38,Business travel,Eco,349,2,0,2,4,3,2,2,3,4,1,4,4,4,3,8,67.0,neutral or dissatisfied +36234,82454,Female,Loyal Customer,67,Business travel,Business,3656,2,4,4,4,2,3,3,2,2,2,2,4,2,3,37,38.0,neutral or dissatisfied +36235,103855,Female,Loyal Customer,23,Business travel,Eco,482,4,1,1,1,4,4,3,4,1,2,1,1,4,4,7,0.0,satisfied +36236,69128,Female,Loyal Customer,26,Personal Travel,Eco,1598,0,1,0,3,4,0,4,4,1,4,4,2,3,4,0,0.0,satisfied +36237,76944,Female,Loyal Customer,30,Business travel,Business,1990,3,3,1,3,2,2,2,2,4,3,5,4,4,2,25,15.0,satisfied +36238,89754,Female,Loyal Customer,7,Personal Travel,Eco,944,5,1,4,4,1,4,1,1,3,3,3,3,3,1,0,0.0,satisfied +36239,48422,Female,Loyal Customer,50,Business travel,Business,3360,1,1,1,1,4,5,5,4,4,4,4,5,4,5,45,36.0,satisfied +36240,59876,Female,Loyal Customer,58,Business travel,Business,3676,2,2,1,2,4,5,4,5,5,5,5,3,5,4,75,65.0,satisfied +36241,53117,Male,Loyal Customer,60,Business travel,Business,2065,1,3,3,3,3,2,1,1,1,1,1,3,1,4,47,28.0,neutral or dissatisfied +36242,32311,Female,disloyal Customer,22,Business travel,Eco,163,5,0,5,2,4,5,4,4,3,3,4,3,2,4,0,0.0,satisfied +36243,72627,Female,Loyal Customer,47,Personal Travel,Eco,964,1,4,1,3,2,4,4,5,5,1,1,4,5,3,0,0.0,neutral or dissatisfied +36244,34256,Male,Loyal Customer,41,Business travel,Business,280,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +36245,42760,Female,Loyal Customer,39,Business travel,Business,493,3,3,3,3,2,3,1,4,4,4,4,3,4,1,0,0.0,satisfied +36246,8170,Female,Loyal Customer,55,Business travel,Business,2383,2,2,5,2,3,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +36247,70982,Female,disloyal Customer,26,Business travel,Business,802,4,3,3,3,4,3,4,4,3,4,4,5,5,4,0,0.0,satisfied +36248,1060,Male,Loyal Customer,24,Personal Travel,Eco,113,5,1,0,2,1,0,1,1,4,5,2,1,2,1,0,0.0,satisfied +36249,66930,Female,Loyal Customer,50,Business travel,Business,964,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +36250,84253,Female,Loyal Customer,45,Business travel,Business,1814,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +36251,86337,Female,Loyal Customer,55,Personal Travel,Business,760,4,5,4,4,5,4,4,4,4,4,4,3,4,5,3,0.0,neutral or dissatisfied +36252,125525,Female,disloyal Customer,27,Business travel,Business,226,1,1,1,5,2,1,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +36253,115984,Male,Loyal Customer,33,Personal Travel,Eco,372,3,2,3,2,3,3,3,3,1,4,1,2,2,3,0,0.0,neutral or dissatisfied +36254,9085,Female,Loyal Customer,52,Personal Travel,Eco,160,2,4,2,1,2,5,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +36255,44053,Male,Loyal Customer,34,Personal Travel,Eco,296,2,5,2,2,3,2,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +36256,86059,Male,disloyal Customer,37,Business travel,Business,447,2,2,2,3,1,2,1,1,4,3,4,3,5,1,11,11.0,satisfied +36257,116711,Female,disloyal Customer,23,Business travel,Eco,337,4,3,4,2,4,4,4,4,5,3,1,1,3,4,27,21.0,satisfied +36258,115170,Female,disloyal Customer,36,Business travel,Business,325,4,5,5,4,1,5,1,1,4,3,4,4,5,1,1,2.0,neutral or dissatisfied +36259,59667,Male,Loyal Customer,64,Personal Travel,Eco,964,4,4,4,3,5,4,5,5,3,3,5,5,4,5,0,0.0,satisfied +36260,127296,Male,disloyal Customer,16,Business travel,Eco Plus,1020,4,0,4,3,2,4,2,2,3,2,4,1,1,2,0,0.0,neutral or dissatisfied +36261,37180,Female,Loyal Customer,12,Personal Travel,Eco,1237,3,4,3,2,1,3,1,1,5,4,5,3,4,1,42,45.0,neutral or dissatisfied +36262,32440,Female,disloyal Customer,40,Business travel,Business,102,3,3,3,2,5,3,4,5,2,3,2,2,1,5,26,33.0,neutral or dissatisfied +36263,36258,Male,disloyal Customer,27,Business travel,Eco,612,1,4,1,3,5,1,1,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +36264,29354,Female,Loyal Customer,44,Business travel,Eco,2355,5,3,5,5,3,4,4,4,4,5,4,2,4,4,15,3.0,satisfied +36265,58395,Male,Loyal Customer,43,Business travel,Business,2095,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +36266,14041,Male,Loyal Customer,44,Business travel,Business,2528,4,4,4,4,4,5,4,5,5,5,4,5,5,3,5,0.0,satisfied +36267,112241,Male,Loyal Customer,34,Business travel,Business,1703,2,2,2,2,5,5,5,5,2,5,5,5,3,5,151,177.0,satisfied +36268,36855,Male,Loyal Customer,36,Business travel,Eco,273,2,4,4,4,2,2,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +36269,65262,Male,Loyal Customer,19,Business travel,Eco Plus,247,2,2,1,1,2,2,2,2,1,4,4,2,4,2,31,21.0,neutral or dissatisfied +36270,38968,Male,Loyal Customer,30,Business travel,Business,230,0,0,0,4,4,4,2,4,1,1,5,1,5,4,0,39.0,satisfied +36271,60249,Male,Loyal Customer,15,Personal Travel,Eco,1506,1,4,1,5,1,1,1,1,4,4,4,4,4,1,36,44.0,neutral or dissatisfied +36272,43922,Female,Loyal Customer,69,Personal Travel,Eco,255,1,3,1,3,2,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +36273,121936,Female,Loyal Customer,42,Personal Travel,Eco Plus,449,3,1,1,4,5,4,3,3,3,1,3,2,3,3,64,49.0,neutral or dissatisfied +36274,35240,Female,Loyal Customer,40,Business travel,Eco,950,4,3,3,3,4,4,4,4,2,1,1,4,4,4,0,0.0,satisfied +36275,112227,Female,Loyal Customer,25,Personal Travel,Eco,1199,2,4,2,4,2,2,2,2,1,3,4,5,2,2,1,1.0,neutral or dissatisfied +36276,70805,Female,Loyal Customer,41,Business travel,Business,1904,3,3,5,3,5,5,5,5,5,5,5,5,5,3,1,0.0,satisfied +36277,36577,Female,disloyal Customer,25,Business travel,Eco,1249,5,5,5,1,1,5,1,1,5,1,4,3,3,1,0,0.0,satisfied +36278,51753,Female,Loyal Customer,43,Personal Travel,Eco,451,4,5,4,1,5,5,5,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +36279,19204,Male,Loyal Customer,25,Business travel,Eco Plus,542,5,2,1,1,5,5,5,5,4,4,2,3,2,5,6,4.0,satisfied +36280,122558,Male,Loyal Customer,42,Personal Travel,Eco,500,2,4,2,4,2,2,2,2,3,3,2,2,4,2,0,0.0,neutral or dissatisfied +36281,81040,Male,Loyal Customer,47,Business travel,Business,1175,2,4,4,4,3,4,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +36282,32110,Female,disloyal Customer,27,Business travel,Eco,163,1,0,1,1,3,1,2,3,1,1,5,3,3,3,0,0.0,neutral or dissatisfied +36283,83680,Male,Loyal Customer,42,Business travel,Business,577,4,3,4,4,4,4,4,3,3,3,3,4,3,3,18,35.0,satisfied +36284,70013,Male,Loyal Customer,15,Personal Travel,Eco Plus,236,2,4,2,5,4,2,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +36285,56555,Male,Loyal Customer,44,Business travel,Business,937,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +36286,44907,Male,Loyal Customer,27,Business travel,Business,3049,3,4,4,4,3,3,3,3,4,1,3,1,2,3,0,0.0,neutral or dissatisfied +36287,75108,Male,Loyal Customer,66,Personal Travel,Business,1723,1,4,1,3,3,2,4,4,4,1,4,3,4,3,0,14.0,neutral or dissatisfied +36288,77619,Female,disloyal Customer,30,Business travel,Business,731,1,1,1,3,4,1,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +36289,76767,Female,Loyal Customer,40,Business travel,Business,1742,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +36290,54695,Female,Loyal Customer,44,Business travel,Business,3621,1,2,2,2,1,3,4,1,1,2,1,4,1,1,32,15.0,neutral or dissatisfied +36291,37780,Female,Loyal Customer,43,Business travel,Eco Plus,1005,4,4,4,4,4,4,5,4,4,4,4,1,4,1,64,73.0,satisfied +36292,50067,Female,Loyal Customer,45,Business travel,Business,2465,2,5,5,5,1,2,1,4,4,4,2,1,4,1,5,6.0,neutral or dissatisfied +36293,94027,Female,Loyal Customer,47,Business travel,Business,2063,4,4,1,4,2,5,5,4,4,4,4,5,4,4,17,6.0,satisfied +36294,39334,Male,Loyal Customer,48,Personal Travel,Eco Plus,67,3,5,3,3,3,3,3,3,5,2,4,5,4,3,17,43.0,neutral or dissatisfied +36295,85716,Female,Loyal Customer,47,Business travel,Business,2407,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +36296,78543,Male,Loyal Customer,47,Personal Travel,Eco,526,4,5,5,3,1,5,1,1,3,2,5,3,4,1,6,2.0,neutral or dissatisfied +36297,52079,Female,Loyal Customer,29,Business travel,Business,2146,5,5,3,5,4,4,4,4,1,2,5,2,3,4,13,11.0,satisfied +36298,55532,Female,Loyal Customer,46,Business travel,Eco,550,2,3,3,3,2,3,4,2,2,2,2,2,2,3,1,0.0,neutral or dissatisfied +36299,70988,Male,Loyal Customer,49,Business travel,Business,3977,5,3,5,5,5,4,5,4,4,4,4,3,4,5,62,57.0,satisfied +36300,107334,Female,disloyal Customer,26,Business travel,Business,584,0,0,0,4,4,0,4,4,4,2,5,5,5,4,24,11.0,satisfied +36301,4554,Female,Loyal Customer,30,Business travel,Business,561,1,5,5,5,1,1,1,1,1,3,2,1,2,1,0,0.0,neutral or dissatisfied +36302,70060,Female,Loyal Customer,59,Business travel,Business,1961,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +36303,26051,Female,disloyal Customer,27,Business travel,Eco,432,3,2,3,4,5,3,5,5,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +36304,68959,Male,disloyal Customer,42,Business travel,Business,700,4,4,4,2,2,4,3,2,4,3,4,3,4,2,0,0.0,satisfied +36305,7071,Male,Loyal Customer,46,Business travel,Business,3396,2,2,2,2,2,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +36306,7379,Male,Loyal Customer,19,Personal Travel,Eco,888,1,1,1,3,4,1,4,4,4,4,2,4,3,4,0,0.0,neutral or dissatisfied +36307,50661,Male,Loyal Customer,28,Personal Travel,Eco,89,2,5,2,3,3,2,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +36308,116855,Male,Loyal Customer,51,Business travel,Business,2796,3,3,3,3,5,4,4,5,5,5,5,4,5,4,50,43.0,satisfied +36309,51623,Female,disloyal Customer,39,Business travel,Business,370,4,4,4,5,2,4,2,2,5,1,3,1,1,2,0,0.0,satisfied +36310,34408,Male,Loyal Customer,18,Personal Travel,Eco,612,3,3,3,4,3,3,3,3,1,2,5,2,2,3,0,0.0,neutral or dissatisfied +36311,17574,Male,disloyal Customer,23,Business travel,Eco,1034,3,3,3,3,1,3,1,1,3,3,3,1,4,1,70,35.0,neutral or dissatisfied +36312,93144,Male,Loyal Customer,52,Business travel,Eco,1075,3,1,1,1,3,3,3,3,1,5,4,1,3,3,29,12.0,neutral or dissatisfied +36313,57694,Female,disloyal Customer,27,Business travel,Business,867,2,2,2,3,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +36314,44358,Female,Loyal Customer,51,Business travel,Eco,596,2,5,5,5,4,3,2,2,2,2,2,5,2,5,0,0.0,satisfied +36315,7036,Female,Loyal Customer,64,Business travel,Eco Plus,234,4,5,5,5,4,3,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +36316,31802,Female,Loyal Customer,53,Business travel,Business,2640,2,2,2,2,2,2,2,1,2,5,1,2,3,2,0,0.0,satisfied +36317,65297,Female,Loyal Customer,52,Personal Travel,Eco Plus,247,3,4,0,3,4,4,5,5,5,0,5,3,5,3,8,2.0,neutral or dissatisfied +36318,4992,Male,Loyal Customer,54,Business travel,Business,2329,4,4,4,4,5,4,5,3,3,4,3,3,3,3,0,5.0,satisfied +36319,89345,Male,Loyal Customer,26,Business travel,Business,1541,2,4,4,4,2,2,2,2,3,4,4,3,3,2,1,,neutral or dissatisfied +36320,122923,Female,Loyal Customer,29,Personal Travel,Business,328,3,0,3,4,4,3,4,4,4,2,3,5,4,4,0,6.0,neutral or dissatisfied +36321,125259,Male,Loyal Customer,37,Personal Travel,Eco Plus,427,3,3,3,1,1,3,1,1,5,3,4,2,5,1,0,0.0,neutral or dissatisfied +36322,7314,Female,Loyal Customer,43,Personal Travel,Eco Plus,116,4,3,4,3,3,4,4,5,5,4,3,4,5,4,0,0.0,neutral or dissatisfied +36323,29371,Male,Loyal Customer,38,Business travel,Business,2541,4,1,3,1,4,4,4,3,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +36324,12837,Male,Loyal Customer,36,Business travel,Business,241,2,4,4,4,1,4,4,2,2,2,2,2,2,1,14,11.0,neutral or dissatisfied +36325,8586,Male,Loyal Customer,31,Personal Travel,Eco,308,5,3,5,4,5,5,2,5,3,4,3,2,3,5,0,0.0,satisfied +36326,107588,Female,Loyal Customer,54,Business travel,Business,423,2,2,2,2,5,5,5,5,5,5,5,4,5,4,9,0.0,satisfied +36327,72435,Male,Loyal Customer,57,Business travel,Business,2782,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +36328,122791,Female,Loyal Customer,49,Business travel,Business,3292,4,4,3,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +36329,67659,Female,Loyal Customer,34,Business travel,Business,1242,5,5,5,5,5,5,4,4,4,4,4,5,4,3,57,46.0,satisfied +36330,48320,Male,disloyal Customer,22,Business travel,Eco,1203,5,5,5,2,5,5,5,5,1,2,5,1,2,5,0,0.0,satisfied +36331,43900,Female,Loyal Customer,12,Personal Travel,Eco,144,1,5,0,2,1,0,1,1,3,2,5,4,4,1,0,1.0,neutral or dissatisfied +36332,9203,Male,Loyal Customer,10,Personal Travel,Eco,227,2,4,0,3,5,0,2,5,4,2,4,3,4,5,6,12.0,neutral or dissatisfied +36333,95837,Male,Loyal Customer,47,Business travel,Business,3490,5,5,5,5,2,4,5,4,4,4,4,4,4,5,4,3.0,satisfied +36334,45313,Male,disloyal Customer,33,Business travel,Eco,175,2,1,2,4,3,2,3,3,4,2,3,1,3,3,0,1.0,neutral or dissatisfied +36335,106988,Female,Loyal Customer,52,Personal Travel,Eco,937,2,4,2,4,2,4,5,5,5,2,5,3,5,3,2,3.0,neutral or dissatisfied +36336,67056,Female,Loyal Customer,51,Business travel,Business,985,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +36337,61418,Female,disloyal Customer,12,Business travel,Eco,679,2,3,3,4,3,3,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +36338,28144,Male,Loyal Customer,13,Business travel,Eco,569,2,3,3,3,2,1,2,2,2,1,3,2,3,2,0,0.0,neutral or dissatisfied +36339,59780,Male,Loyal Customer,13,Personal Travel,Eco,1025,1,4,1,1,5,1,5,5,5,5,5,5,5,5,3,11.0,neutral or dissatisfied +36340,119377,Male,Loyal Customer,51,Business travel,Business,2229,2,2,2,2,5,4,5,5,5,5,5,4,5,5,79,88.0,satisfied +36341,19423,Male,Loyal Customer,24,Business travel,Business,2092,2,5,5,5,2,2,2,2,2,2,4,4,4,2,129,107.0,neutral or dissatisfied +36342,117758,Male,Loyal Customer,23,Business travel,Eco,1670,4,5,5,5,4,4,3,4,1,3,3,3,4,4,14,36.0,neutral or dissatisfied +36343,35208,Male,Loyal Customer,40,Business travel,Business,2642,4,4,4,4,1,5,2,2,2,2,2,1,2,1,0,0.0,satisfied +36344,51159,Male,Loyal Customer,56,Personal Travel,Eco,209,3,3,3,3,1,3,3,1,2,4,2,2,3,1,0,0.0,neutral or dissatisfied +36345,24131,Male,Loyal Customer,17,Personal Travel,Eco,779,2,5,2,3,4,2,5,4,5,3,4,3,5,4,7,18.0,neutral or dissatisfied +36346,14302,Male,Loyal Customer,46,Business travel,Eco,395,5,4,4,4,4,5,4,4,4,2,5,5,1,4,12,10.0,satisfied +36347,54737,Male,Loyal Customer,61,Personal Travel,Eco,861,2,4,2,2,5,2,4,5,3,5,4,3,4,5,5,0.0,neutral or dissatisfied +36348,6663,Male,disloyal Customer,20,Business travel,Eco,438,2,0,2,2,1,2,1,1,5,5,4,3,5,1,15,20.0,neutral or dissatisfied +36349,52697,Male,Loyal Customer,14,Personal Travel,Eco Plus,160,3,4,3,2,2,3,2,2,3,5,5,4,5,2,0,4.0,neutral or dissatisfied +36350,50436,Female,Loyal Customer,43,Business travel,Eco,262,2,2,2,2,4,4,4,3,3,2,3,1,3,2,34,25.0,neutral or dissatisfied +36351,9138,Male,disloyal Customer,44,Business travel,Eco,426,2,5,3,2,1,3,1,1,2,2,3,5,4,1,1,28.0,neutral or dissatisfied +36352,37789,Male,Loyal Customer,43,Business travel,Eco Plus,1076,4,5,5,5,5,4,5,5,4,1,2,1,2,5,17,0.0,neutral or dissatisfied +36353,35640,Male,disloyal Customer,9,Business travel,Eco,2569,2,2,2,4,2,3,3,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +36354,33497,Male,Loyal Customer,46,Business travel,Eco Plus,2496,4,5,5,5,5,4,5,5,1,2,5,1,5,5,6,13.0,satisfied +36355,88179,Female,disloyal Customer,23,Business travel,Eco,250,0,4,0,3,3,0,3,3,4,3,5,4,5,3,18,12.0,satisfied +36356,56135,Male,Loyal Customer,53,Business travel,Business,1400,5,5,5,5,5,5,5,3,5,4,5,5,4,5,146,175.0,satisfied +36357,22639,Male,Loyal Customer,24,Personal Travel,Eco,223,4,1,4,2,2,4,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +36358,12770,Female,disloyal Customer,29,Business travel,Eco Plus,721,2,2,2,4,1,2,1,1,1,4,3,1,3,1,76,63.0,neutral or dissatisfied +36359,58445,Male,Loyal Customer,61,Personal Travel,Eco,733,3,3,3,3,5,3,5,5,4,2,4,2,4,5,122,106.0,neutral or dissatisfied +36360,65893,Female,Loyal Customer,21,Business travel,Business,569,4,4,4,4,2,2,2,2,5,3,4,4,5,2,0,2.0,satisfied +36361,49442,Male,Loyal Customer,53,Business travel,Eco,78,2,3,3,3,2,2,2,2,1,3,4,3,4,2,0,1.0,neutral or dissatisfied +36362,23835,Female,Loyal Customer,44,Business travel,Eco,715,4,2,2,2,5,1,2,4,4,4,4,1,4,5,0,0.0,satisfied +36363,118128,Male,Loyal Customer,59,Business travel,Business,1488,3,3,3,3,2,5,4,5,5,5,5,5,5,5,27,21.0,satisfied +36364,30782,Female,Loyal Customer,35,Business travel,Business,3537,1,1,1,1,4,5,2,4,4,4,4,2,4,5,0,0.0,satisfied +36365,116597,Female,Loyal Customer,40,Business travel,Business,446,2,2,2,2,2,4,4,4,4,4,4,4,4,3,45,31.0,satisfied +36366,76885,Female,disloyal Customer,22,Business travel,Eco,630,3,5,3,5,5,3,5,5,5,3,5,3,4,5,0,5.0,neutral or dissatisfied +36367,31384,Female,disloyal Customer,24,Business travel,Eco,895,4,4,4,2,4,4,4,4,5,3,5,3,2,4,25,13.0,satisfied +36368,12105,Male,Loyal Customer,47,Business travel,Business,1097,3,3,5,3,2,5,1,5,5,5,5,2,5,4,0,0.0,satisfied +36369,19527,Male,Loyal Customer,39,Business travel,Business,173,3,2,2,2,2,3,3,3,3,2,3,3,3,2,5,4.0,neutral or dissatisfied +36370,43659,Male,Loyal Customer,40,Business travel,Eco,700,2,4,4,4,2,2,2,2,1,1,4,4,4,2,15,26.0,neutral or dissatisfied +36371,50939,Female,Loyal Customer,40,Personal Travel,Eco,209,1,3,1,4,3,1,5,3,2,1,3,4,3,3,0,13.0,neutral or dissatisfied +36372,40389,Female,Loyal Customer,51,Business travel,Business,3733,5,1,5,5,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +36373,71083,Female,Loyal Customer,22,Personal Travel,Eco,802,3,3,4,1,4,4,4,4,4,3,4,3,4,4,2,1.0,neutral or dissatisfied +36374,127570,Male,Loyal Customer,19,Personal Travel,Eco,1670,4,5,4,3,1,4,1,1,3,4,4,4,4,1,0,12.0,neutral or dissatisfied +36375,34135,Male,Loyal Customer,77,Business travel,Eco,1046,4,4,4,4,4,4,4,4,3,4,1,4,2,4,0,0.0,neutral or dissatisfied +36376,98985,Male,Loyal Customer,24,Personal Travel,Eco,479,1,5,5,1,1,5,1,1,5,2,4,4,3,1,35,30.0,neutral or dissatisfied +36377,52086,Male,Loyal Customer,43,Business travel,Eco,639,1,4,4,4,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +36378,43677,Male,Loyal Customer,29,Personal Travel,Eco,695,2,4,2,2,2,2,2,2,5,3,5,5,5,2,52,56.0,neutral or dissatisfied +36379,96909,Male,Loyal Customer,59,Personal Travel,Eco,816,3,5,3,3,1,3,1,1,5,4,5,3,5,1,1,0.0,neutral or dissatisfied +36380,16866,Female,disloyal Customer,48,Business travel,Eco,708,2,2,2,5,2,2,2,2,2,3,4,2,5,2,31,20.0,neutral or dissatisfied +36381,47175,Female,disloyal Customer,25,Business travel,Eco,679,3,3,3,4,4,3,4,4,1,5,4,1,3,4,49,37.0,neutral or dissatisfied +36382,102094,Male,Loyal Customer,52,Business travel,Business,2262,0,0,0,2,4,4,5,1,1,1,1,4,1,5,0,8.0,satisfied +36383,82529,Male,Loyal Customer,13,Personal Travel,Eco,1749,2,3,2,1,3,2,3,3,5,4,2,3,3,3,9,0.0,neutral or dissatisfied +36384,116881,Female,disloyal Customer,27,Business travel,Business,370,4,4,4,5,1,4,1,1,3,3,5,4,4,1,0,0.0,satisfied +36385,85282,Female,Loyal Customer,8,Personal Travel,Eco,731,2,2,2,4,4,2,1,4,3,5,3,1,3,4,16,13.0,neutral or dissatisfied +36386,45908,Male,Loyal Customer,40,Business travel,Business,3251,4,4,4,4,2,4,3,4,4,5,4,1,4,1,0,0.0,satisfied +36387,121324,Male,Loyal Customer,36,Personal Travel,Eco,1009,1,4,1,1,5,1,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +36388,82933,Female,disloyal Customer,41,Business travel,Business,594,3,3,3,2,4,3,4,4,5,5,4,4,4,4,0,0.0,satisfied +36389,74363,Male,Loyal Customer,42,Business travel,Business,2073,1,1,1,1,3,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +36390,41040,Female,Loyal Customer,7,Business travel,Business,3110,3,2,5,5,3,3,3,3,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +36391,122543,Female,Loyal Customer,52,Business travel,Eco,500,3,5,5,5,4,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +36392,48323,Female,Loyal Customer,48,Business travel,Eco Plus,1203,4,3,5,5,2,1,2,4,4,4,4,4,4,5,0,0.0,satisfied +36393,95505,Male,Loyal Customer,32,Business travel,Eco Plus,148,2,5,5,5,2,2,2,2,3,2,4,4,3,2,0,0.0,neutral or dissatisfied +36394,60243,Female,Loyal Customer,33,Personal Travel,Eco,1546,3,4,3,4,4,3,4,4,2,3,3,3,3,4,0,0.0,neutral or dissatisfied +36395,24631,Male,Loyal Customer,11,Personal Travel,Eco,526,3,4,3,2,4,3,4,4,5,2,5,3,5,4,0,10.0,neutral or dissatisfied +36396,106757,Male,Loyal Customer,43,Personal Travel,Eco,829,2,4,2,3,4,2,4,4,5,2,5,5,4,4,1,0.0,neutral or dissatisfied +36397,22781,Female,Loyal Customer,45,Business travel,Business,134,0,5,0,2,2,1,4,1,1,1,1,2,1,3,16,13.0,satisfied +36398,41684,Male,Loyal Customer,7,Personal Travel,Eco,347,2,4,2,3,2,2,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +36399,19970,Female,disloyal Customer,26,Business travel,Eco,157,0,2,0,4,2,0,2,2,5,3,3,5,1,2,0,4.0,satisfied +36400,112666,Male,disloyal Customer,36,Business travel,Eco,605,2,2,1,3,5,1,5,5,4,5,3,2,4,5,8,5.0,neutral or dissatisfied +36401,43003,Male,Loyal Customer,59,Business travel,Business,2595,4,4,4,4,1,1,5,5,5,5,5,5,5,3,0,0.0,satisfied +36402,115383,Female,disloyal Customer,28,Business travel,Business,308,3,3,3,5,5,3,5,5,4,2,5,3,4,5,27,19.0,neutral or dissatisfied +36403,80070,Female,disloyal Customer,23,Business travel,Eco,1096,3,3,3,3,5,3,5,5,4,2,4,3,4,5,0,13.0,neutral or dissatisfied +36404,2040,Female,Loyal Customer,44,Business travel,Business,785,1,1,1,1,5,4,4,5,5,5,5,5,5,5,0,14.0,satisfied +36405,32298,Male,Loyal Customer,53,Business travel,Eco,216,3,2,2,2,3,3,3,3,1,4,2,4,2,3,0,0.0,satisfied +36406,28750,Female,Loyal Customer,23,Business travel,Eco,1024,5,2,2,2,5,5,3,5,5,5,4,2,5,5,0,0.0,satisfied +36407,41472,Male,disloyal Customer,34,Business travel,Eco,1464,2,3,3,3,5,2,5,5,3,1,3,3,2,5,78,78.0,neutral or dissatisfied +36408,123408,Male,Loyal Customer,28,Business travel,Business,1337,3,3,3,3,4,4,4,4,4,4,5,4,4,4,15,0.0,satisfied +36409,84049,Female,Loyal Customer,60,Business travel,Business,773,5,5,5,5,4,4,4,4,4,5,4,4,4,3,0,14.0,satisfied +36410,73238,Male,Loyal Customer,59,Personal Travel,Eco Plus,946,5,3,5,5,5,5,5,5,1,1,2,4,4,5,0,0.0,satisfied +36411,48972,Female,Loyal Customer,43,Business travel,Business,337,1,1,1,1,1,2,4,5,5,5,5,4,5,5,0,0.0,satisfied +36412,31337,Male,Loyal Customer,24,Personal Travel,Eco,1062,4,4,4,1,2,4,2,2,4,3,4,5,5,2,0,3.0,neutral or dissatisfied +36413,93942,Female,Loyal Customer,59,Personal Travel,Eco,507,3,5,4,4,3,4,4,3,3,4,2,2,3,3,0,0.0,neutral or dissatisfied +36414,95030,Female,Loyal Customer,41,Personal Travel,Eco,239,4,3,4,4,3,4,3,3,4,1,3,3,4,3,6,1.0,neutral or dissatisfied +36415,83829,Male,disloyal Customer,33,Business travel,Business,425,1,1,1,3,1,1,5,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +36416,115993,Male,Loyal Customer,36,Personal Travel,Eco,480,1,2,1,4,1,1,1,1,2,1,4,2,4,1,1,0.0,neutral or dissatisfied +36417,8310,Female,disloyal Customer,36,Business travel,Eco Plus,402,3,3,3,3,1,3,1,1,4,1,2,4,3,1,15,10.0,neutral or dissatisfied +36418,98233,Male,Loyal Customer,53,Business travel,Business,2204,5,5,5,5,5,5,5,4,4,4,4,5,4,3,0,3.0,satisfied +36419,75963,Male,disloyal Customer,24,Business travel,Business,228,4,3,4,2,2,4,2,2,5,5,4,5,5,2,0,0.0,satisfied +36420,86439,Male,Loyal Customer,42,Business travel,Business,1825,1,5,5,5,1,3,4,1,1,1,1,1,1,3,55,27.0,neutral or dissatisfied +36421,113336,Female,disloyal Customer,24,Business travel,Business,407,2,1,2,3,1,2,1,1,2,4,4,3,3,1,0,0.0,neutral or dissatisfied +36422,63534,Male,Loyal Customer,40,Business travel,Business,2922,3,1,1,1,2,3,4,3,3,3,3,2,3,3,2,0.0,neutral or dissatisfied +36423,6446,Female,Loyal Customer,23,Personal Travel,Eco,240,3,5,3,1,4,3,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +36424,117745,Male,Loyal Customer,38,Personal Travel,Eco,833,4,3,4,4,5,4,5,5,3,3,3,3,4,5,2,4.0,satisfied +36425,54166,Male,Loyal Customer,10,Business travel,Business,1400,5,5,5,5,4,5,4,4,1,2,5,2,5,4,0,0.0,satisfied +36426,68169,Female,Loyal Customer,42,Business travel,Eco,603,1,1,1,1,4,3,3,1,1,1,1,2,1,1,22,23.0,neutral or dissatisfied +36427,9680,Female,Loyal Customer,55,Business travel,Business,199,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +36428,85959,Female,disloyal Customer,26,Business travel,Business,528,4,4,4,1,2,4,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +36429,69966,Female,Loyal Customer,48,Business travel,Business,1988,3,4,3,3,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +36430,95743,Male,disloyal Customer,27,Business travel,Business,237,1,1,1,3,1,1,1,1,1,2,3,3,4,1,12,9.0,neutral or dissatisfied +36431,11495,Female,Loyal Customer,37,Personal Travel,Eco Plus,191,2,4,0,2,3,0,3,3,4,4,4,3,5,3,9,0.0,neutral or dissatisfied +36432,57351,Female,disloyal Customer,20,Business travel,Eco,236,2,2,2,4,5,2,5,5,2,2,4,2,4,5,22,15.0,neutral or dissatisfied +36433,11628,Female,disloyal Customer,25,Business travel,Business,657,3,4,3,2,2,3,5,2,3,4,5,4,4,2,6,0.0,neutral or dissatisfied +36434,8196,Male,Loyal Customer,39,Business travel,Business,402,2,2,2,2,2,4,2,4,4,4,4,2,4,4,4,0.0,satisfied +36435,122548,Male,Loyal Customer,35,Business travel,Eco,500,3,4,4,4,3,3,3,3,3,4,4,4,3,3,0,2.0,neutral or dissatisfied +36436,57916,Male,Loyal Customer,8,Personal Travel,Eco,305,3,4,3,2,3,3,3,3,5,4,5,3,4,3,2,0.0,neutral or dissatisfied +36437,27563,Female,Loyal Customer,20,Personal Travel,Eco,679,2,5,2,1,3,2,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +36438,119531,Female,Loyal Customer,58,Personal Travel,Eco,759,4,5,4,3,3,5,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +36439,48776,Male,Loyal Customer,69,Business travel,Business,3034,1,1,3,1,5,1,2,1,1,1,1,3,1,1,0,4.0,neutral or dissatisfied +36440,103525,Female,Loyal Customer,60,Personal Travel,Business,967,4,4,4,1,3,5,5,4,4,4,4,5,4,3,3,0.0,neutral or dissatisfied +36441,44831,Female,Loyal Customer,54,Personal Travel,Eco,462,2,5,2,1,4,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +36442,125718,Female,Loyal Customer,55,Personal Travel,Eco,899,3,4,3,3,1,2,2,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +36443,32199,Female,Loyal Customer,26,Business travel,Business,163,5,5,5,5,5,5,4,5,4,2,5,4,3,5,0,0.0,satisfied +36444,44918,Male,disloyal Customer,34,Business travel,Eco,416,2,0,2,4,4,2,4,4,5,5,1,2,3,4,31,29.0,neutral or dissatisfied +36445,95333,Male,Loyal Customer,29,Personal Travel,Eco,187,2,4,2,4,4,2,4,4,4,4,4,3,5,4,24,10.0,neutral or dissatisfied +36446,21163,Male,Loyal Customer,50,Business travel,Eco Plus,954,5,3,3,3,5,5,5,5,4,2,4,4,3,5,0,0.0,satisfied +36447,101507,Male,Loyal Customer,39,Business travel,Eco,345,3,4,1,4,3,3,3,3,3,3,4,2,3,3,29,26.0,neutral or dissatisfied +36448,56764,Female,disloyal Customer,64,Business travel,Eco Plus,937,1,1,1,3,4,1,4,4,3,5,4,3,3,4,0,3.0,neutral or dissatisfied +36449,92986,Male,disloyal Customer,29,Business travel,Eco,738,3,4,4,3,4,4,1,4,2,4,2,1,2,4,45,38.0,neutral or dissatisfied +36450,73431,Male,Loyal Customer,19,Personal Travel,Eco,1182,2,4,2,2,4,2,4,4,3,3,4,4,5,4,0,6.0,neutral or dissatisfied +36451,93439,Female,Loyal Customer,36,Business travel,Business,1906,1,1,1,1,2,3,5,5,5,5,3,1,5,5,0,0.0,satisfied +36452,18560,Female,Loyal Customer,48,Business travel,Business,2204,3,3,3,3,3,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +36453,49311,Female,Loyal Customer,42,Business travel,Eco,134,4,4,2,2,1,4,2,4,4,4,4,4,4,4,15,16.0,satisfied +36454,59354,Female,Loyal Customer,42,Business travel,Business,2615,5,5,5,5,5,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +36455,48603,Male,Loyal Customer,45,Personal Travel,Eco,737,3,4,4,2,1,4,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +36456,84935,Female,Loyal Customer,59,Personal Travel,Eco,534,2,4,2,4,5,3,3,2,2,2,2,4,2,3,2,19.0,neutral or dissatisfied +36457,125742,Female,disloyal Customer,20,Business travel,Eco,861,5,5,5,5,3,5,4,3,4,5,4,5,4,3,21,24.0,satisfied +36458,74405,Female,Loyal Customer,36,Business travel,Business,1623,2,4,4,4,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +36459,126313,Female,Loyal Customer,36,Personal Travel,Eco,590,4,5,4,4,5,4,5,5,4,3,4,4,4,5,0,0.0,satisfied +36460,38853,Female,Loyal Customer,28,Business travel,Business,2153,2,2,2,2,5,5,5,5,2,2,4,3,4,5,62,70.0,satisfied +36461,2168,Female,Loyal Customer,55,Business travel,Business,3103,3,3,3,3,5,4,5,4,4,4,4,3,4,4,23,18.0,satisfied +36462,51625,Male,Loyal Customer,53,Business travel,Eco,493,4,4,4,4,3,4,3,3,4,1,3,5,1,3,0,0.0,satisfied +36463,116827,Male,Loyal Customer,62,Business travel,Business,2423,5,5,5,5,3,4,5,5,5,5,5,5,5,4,43,29.0,satisfied +36464,106453,Male,Loyal Customer,39,Business travel,Business,1670,1,1,1,1,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +36465,23074,Male,Loyal Customer,21,Personal Travel,Eco Plus,1211,3,0,3,4,4,3,4,4,4,2,3,2,4,4,10,5.0,neutral or dissatisfied +36466,77111,Female,Loyal Customer,44,Business travel,Business,1481,4,5,5,5,4,4,4,4,2,4,4,4,4,4,164,153.0,neutral or dissatisfied +36467,126976,Female,disloyal Customer,18,Business travel,Eco,621,5,0,5,5,2,5,2,2,3,4,5,3,5,2,0,0.0,satisfied +36468,59899,Male,disloyal Customer,46,Business travel,Business,1023,3,3,3,4,4,3,4,4,3,2,4,4,5,4,3,0.0,neutral or dissatisfied +36469,120847,Female,Loyal Customer,8,Business travel,Business,3817,3,5,5,5,3,3,3,3,1,1,3,4,3,3,0,0.0,neutral or dissatisfied +36470,96300,Female,Loyal Customer,60,Personal Travel,Eco,687,3,5,3,5,5,5,5,4,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +36471,27744,Female,Loyal Customer,14,Business travel,Eco,680,5,4,4,4,5,5,3,5,5,3,4,4,2,5,0,1.0,satisfied +36472,83102,Male,Loyal Customer,46,Personal Travel,Eco,983,3,5,3,5,3,3,3,3,5,5,4,3,4,3,20,19.0,neutral or dissatisfied +36473,84829,Female,Loyal Customer,32,Business travel,Business,2946,2,1,3,1,2,2,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +36474,127241,Male,Loyal Customer,57,Business travel,Business,1020,2,2,2,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +36475,34579,Male,Loyal Customer,38,Business travel,Business,1598,2,2,2,2,5,5,1,5,5,5,5,2,5,5,0,0.0,satisfied +36476,92585,Female,Loyal Customer,56,Business travel,Business,2218,3,3,2,3,5,5,4,4,4,4,4,3,4,5,3,0.0,satisfied +36477,28442,Male,Loyal Customer,68,Personal Travel,Eco,2496,2,5,2,3,2,3,3,5,3,3,4,3,4,3,36,1.0,neutral or dissatisfied +36478,87561,Female,disloyal Customer,26,Business travel,Eco,432,2,4,2,3,5,2,5,5,2,1,3,2,3,5,10,12.0,neutral or dissatisfied +36479,120474,Female,Loyal Customer,65,Personal Travel,Eco,449,2,4,5,3,1,4,4,2,2,5,4,4,2,2,0,12.0,neutral or dissatisfied +36480,47081,Female,Loyal Customer,39,Personal Travel,Eco,639,3,5,2,1,2,2,2,2,5,4,4,4,5,2,59,41.0,neutral or dissatisfied +36481,18385,Male,Loyal Customer,28,Business travel,Business,2536,4,4,4,4,4,4,4,4,4,5,4,1,3,4,0,0.0,neutral or dissatisfied +36482,118181,Male,Loyal Customer,39,Business travel,Business,1440,1,4,4,4,3,1,1,1,1,1,1,1,1,2,117,107.0,neutral or dissatisfied +36483,64515,Male,Loyal Customer,45,Personal Travel,Business,354,1,5,1,1,4,4,4,2,2,1,2,3,2,3,3,17.0,neutral or dissatisfied +36484,14362,Female,Loyal Customer,25,Personal Travel,Eco Plus,395,2,4,2,2,2,2,2,2,2,5,5,2,3,2,6,9.0,neutral or dissatisfied +36485,113761,Female,Loyal Customer,17,Personal Travel,Eco,226,2,4,2,3,5,2,5,5,5,3,4,3,4,5,7,0.0,neutral or dissatisfied +36486,23253,Male,Loyal Customer,25,Business travel,Business,3486,1,1,1,1,1,1,1,1,3,5,4,1,3,1,41,46.0,neutral or dissatisfied +36487,120275,Female,disloyal Customer,29,Business travel,Business,1576,2,2,2,3,4,2,4,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +36488,66605,Male,Loyal Customer,12,Personal Travel,Eco,761,3,5,4,1,3,4,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +36489,68258,Male,Loyal Customer,41,Personal Travel,Eco,631,2,5,2,4,3,2,5,3,3,2,5,5,5,3,8,0.0,neutral or dissatisfied +36490,10179,Female,Loyal Customer,56,Business travel,Business,2480,2,2,4,2,5,5,5,4,4,4,5,3,4,4,46,34.0,satisfied +36491,124680,Male,Loyal Customer,33,Business travel,Business,399,5,5,5,5,4,5,4,4,3,3,5,4,5,4,0,0.0,satisfied +36492,67492,Female,Loyal Customer,41,Business travel,Business,2343,4,4,4,4,3,5,5,4,4,4,4,5,4,3,16,15.0,satisfied +36493,127809,Male,Loyal Customer,49,Business travel,Business,1044,1,1,1,1,3,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +36494,13596,Male,Loyal Customer,10,Personal Travel,Eco,106,2,4,2,4,3,2,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +36495,47635,Male,Loyal Customer,21,Business travel,Business,3792,2,2,2,2,4,4,4,4,1,4,3,4,5,4,43,20.0,satisfied +36496,41979,Male,Loyal Customer,22,Personal Travel,Eco,575,4,1,4,4,5,4,5,5,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +36497,108856,Female,Loyal Customer,55,Business travel,Eco,1947,1,2,2,2,2,2,3,1,1,1,1,4,1,1,12,18.0,neutral or dissatisfied +36498,14791,Male,Loyal Customer,52,Business travel,Business,622,1,3,3,3,1,3,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +36499,94490,Male,Loyal Customer,16,Business travel,Business,1803,2,2,2,2,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +36500,46621,Female,Loyal Customer,67,Business travel,Business,2483,1,2,2,2,4,3,3,3,3,3,1,3,3,1,47,42.0,neutral or dissatisfied +36501,38131,Male,Loyal Customer,22,Business travel,Business,1121,2,2,2,2,5,5,5,5,5,3,5,2,5,5,0,0.0,satisfied +36502,62536,Female,Loyal Customer,44,Business travel,Business,1744,1,3,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +36503,74125,Male,Loyal Customer,24,Business travel,Eco,641,1,3,3,3,1,1,2,1,2,2,3,3,4,1,0,21.0,neutral or dissatisfied +36504,111319,Female,disloyal Customer,17,Business travel,Eco,283,4,2,4,4,4,4,4,4,4,3,3,3,3,4,20,10.0,neutral or dissatisfied +36505,47925,Male,Loyal Customer,52,Personal Travel,Eco,726,2,4,2,1,3,2,3,3,5,4,1,5,2,3,0,0.0,neutral or dissatisfied +36506,70335,Female,Loyal Customer,57,Business travel,Business,2397,1,1,1,1,2,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +36507,62688,Male,Loyal Customer,33,Business travel,Business,2486,1,3,3,3,1,1,1,4,4,4,4,1,2,1,2,38.0,neutral or dissatisfied +36508,65912,Female,Loyal Customer,57,Business travel,Business,569,2,3,3,3,4,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +36509,85869,Male,Loyal Customer,51,Business travel,Business,2172,1,1,1,1,2,3,4,3,3,3,3,3,3,3,66,52.0,satisfied +36510,77765,Female,Loyal Customer,35,Personal Travel,Eco,813,3,1,3,2,3,3,3,3,3,5,1,3,2,3,0,0.0,neutral or dissatisfied +36511,21934,Male,Loyal Customer,48,Business travel,Eco,503,2,2,3,2,2,2,2,2,2,5,3,4,3,2,12,8.0,neutral or dissatisfied +36512,35827,Male,disloyal Customer,24,Business travel,Business,1068,5,0,5,5,3,0,3,3,1,1,3,3,5,3,17,0.0,satisfied +36513,86391,Female,Loyal Customer,41,Business travel,Business,3093,2,2,2,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +36514,88776,Female,Loyal Customer,23,Business travel,Business,2899,3,3,3,3,5,4,5,5,4,5,4,4,4,5,0,0.0,satisfied +36515,52571,Female,Loyal Customer,44,Business travel,Eco,119,4,3,3,3,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +36516,34126,Female,Loyal Customer,36,Business travel,Business,1189,1,1,1,1,4,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +36517,471,Female,Loyal Customer,56,Business travel,Business,89,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +36518,3685,Male,Loyal Customer,50,Business travel,Business,3755,3,1,4,4,4,3,2,3,3,3,3,2,3,2,9,8.0,neutral or dissatisfied +36519,20878,Male,disloyal Customer,25,Business travel,Eco Plus,534,5,0,5,3,5,5,5,5,2,3,3,4,1,5,0,0.0,satisfied +36520,40961,Female,Loyal Customer,22,Business travel,Business,2030,4,4,3,4,5,5,5,5,1,2,3,5,4,5,0,3.0,satisfied +36521,101060,Female,Loyal Customer,45,Business travel,Business,2887,2,2,5,2,4,4,3,2,2,2,2,2,2,1,16,12.0,neutral or dissatisfied +36522,32380,Female,Loyal Customer,42,Business travel,Business,1671,3,5,5,5,5,4,4,2,2,3,3,1,2,1,0,0.0,neutral or dissatisfied +36523,84606,Female,Loyal Customer,34,Business travel,Business,669,1,1,3,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +36524,24978,Female,disloyal Customer,25,Business travel,Eco,692,2,2,2,4,5,2,5,5,4,1,5,1,4,5,0,0.0,neutral or dissatisfied +36525,36586,Female,disloyal Customer,23,Business travel,Eco,1237,2,2,2,4,4,2,4,4,3,3,3,3,3,4,24,62.0,neutral or dissatisfied +36526,82320,Female,disloyal Customer,34,Business travel,Business,456,1,1,1,4,2,1,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +36527,36454,Female,Loyal Customer,58,Business travel,Business,2186,5,5,5,5,1,1,5,4,4,4,4,1,4,1,14,22.0,satisfied +36528,109121,Female,Loyal Customer,39,Personal Travel,Eco Plus,849,1,5,1,3,2,1,2,2,5,4,5,3,4,2,62,52.0,neutral or dissatisfied +36529,58563,Male,Loyal Customer,57,Business travel,Business,1514,2,2,2,2,4,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +36530,31097,Female,Loyal Customer,50,Personal Travel,Eco,1014,3,4,3,4,2,4,3,2,2,3,3,1,2,3,12,4.0,neutral or dissatisfied +36531,6697,Male,Loyal Customer,37,Business travel,Eco,403,2,2,2,2,2,2,2,2,4,2,2,4,3,2,0,0.0,neutral or dissatisfied +36532,99628,Female,disloyal Customer,26,Business travel,Eco,1224,1,1,1,3,3,1,3,3,3,3,4,3,3,3,0,24.0,neutral or dissatisfied +36533,85559,Female,disloyal Customer,56,Business travel,Business,192,4,4,4,4,1,4,1,1,4,2,5,3,4,1,1,0.0,neutral or dissatisfied +36534,93685,Female,Loyal Customer,30,Business travel,Business,1452,5,3,5,5,5,5,5,5,3,5,4,3,4,5,4,8.0,satisfied +36535,96957,Male,Loyal Customer,43,Business travel,Eco,794,1,4,4,4,1,1,1,1,1,1,3,2,4,1,26,,neutral or dissatisfied +36536,109825,Male,Loyal Customer,44,Business travel,Business,1523,3,3,3,3,3,4,4,4,4,4,4,3,4,5,2,5.0,satisfied +36537,6158,Male,Loyal Customer,42,Business travel,Eco,409,3,4,3,4,3,3,3,3,2,1,2,4,2,3,0,14.0,neutral or dissatisfied +36538,76235,Male,disloyal Customer,35,Business travel,Business,1399,3,3,3,5,1,3,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +36539,73235,Female,disloyal Customer,28,Business travel,Eco Plus,946,1,1,1,3,5,1,2,5,2,5,3,4,3,5,0,8.0,neutral or dissatisfied +36540,21995,Male,Loyal Customer,22,Personal Travel,Eco,551,3,3,3,2,1,3,1,1,1,3,2,3,3,1,20,28.0,neutral or dissatisfied +36541,64262,Female,disloyal Customer,25,Business travel,Business,1660,4,5,4,4,4,4,4,4,5,3,3,4,4,4,10,20.0,neutral or dissatisfied +36542,73437,Male,Loyal Customer,70,Personal Travel,Eco,1197,4,5,4,2,3,4,3,3,3,5,4,3,4,3,0,1.0,neutral or dissatisfied +36543,41404,Male,Loyal Customer,31,Business travel,Eco,913,3,2,2,2,3,3,3,3,3,3,4,3,3,3,0,45.0,neutral or dissatisfied +36544,87611,Female,Loyal Customer,64,Personal Travel,Business,606,3,2,3,3,3,3,3,2,2,3,2,1,2,4,11,12.0,neutral or dissatisfied +36545,55485,Male,Loyal Customer,44,Business travel,Eco,2434,4,3,3,3,4,4,4,4,4,4,3,1,4,4,17,11.0,neutral or dissatisfied +36546,114461,Male,Loyal Customer,40,Business travel,Business,3106,4,2,2,2,3,4,3,4,4,4,4,3,4,1,29,25.0,neutral or dissatisfied +36547,46756,Female,Loyal Customer,34,Business travel,Eco Plus,125,4,4,4,4,4,4,4,4,1,1,1,3,3,4,81,98.0,satisfied +36548,60889,Female,Loyal Customer,57,Personal Travel,Eco,1062,2,5,3,5,4,4,4,5,5,3,5,4,5,4,1,0.0,neutral or dissatisfied +36549,33966,Male,Loyal Customer,35,Business travel,Eco,1598,5,5,5,5,5,5,5,5,1,4,4,3,3,5,81,43.0,satisfied +36550,46705,Female,Loyal Customer,36,Personal Travel,Eco,73,3,1,3,4,4,3,1,4,3,4,4,1,4,4,18,15.0,neutral or dissatisfied +36551,90112,Male,Loyal Customer,31,Business travel,Business,2437,5,5,3,5,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +36552,90100,Female,Loyal Customer,44,Business travel,Business,3536,4,4,4,4,5,5,5,5,5,5,5,5,5,5,6,0.0,satisfied +36553,89894,Female,Loyal Customer,54,Business travel,Business,1416,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +36554,25013,Female,Loyal Customer,53,Business travel,Business,2405,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +36555,7890,Male,Loyal Customer,9,Personal Travel,Eco,910,3,2,3,3,4,3,4,4,2,1,2,2,3,4,0,0.0,neutral or dissatisfied +36556,82750,Female,Loyal Customer,41,Business travel,Eco,409,2,1,1,1,2,2,2,2,2,1,4,3,4,2,10,0.0,neutral or dissatisfied +36557,19360,Female,Loyal Customer,47,Business travel,Eco,589,4,3,3,3,5,4,2,4,4,4,4,2,4,1,82,78.0,satisfied +36558,60965,Female,Loyal Customer,35,Business travel,Business,3848,2,3,2,3,2,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +36559,34473,Male,disloyal Customer,25,Business travel,Business,266,5,3,5,3,5,4,4,1,1,2,1,4,2,4,398,392.0,satisfied +36560,6664,Male,disloyal Customer,25,Business travel,Business,438,4,0,4,3,2,4,2,2,4,3,4,3,5,2,8,1.0,satisfied +36561,22784,Male,Loyal Customer,16,Business travel,Business,3857,3,5,5,5,2,2,3,2,2,3,4,1,3,2,1,0.0,neutral or dissatisfied +36562,117096,Male,disloyal Customer,34,Business travel,Eco,304,4,4,4,4,3,4,3,3,2,2,3,1,3,3,40,27.0,neutral or dissatisfied +36563,43407,Female,Loyal Customer,42,Business travel,Eco Plus,347,2,1,1,1,5,2,5,2,2,2,2,4,2,3,0,3.0,satisfied +36564,106778,Female,disloyal Customer,7,Business travel,Eco,829,3,3,3,4,2,3,5,2,2,4,3,1,3,2,4,42.0,neutral or dissatisfied +36565,82173,Female,Loyal Customer,53,Business travel,Business,1848,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +36566,113984,Female,disloyal Customer,40,Business travel,Business,1728,2,2,2,3,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +36567,49882,Male,Loyal Customer,66,Business travel,Business,190,0,4,0,4,3,1,2,3,3,3,3,1,3,1,0,0.0,satisfied +36568,123856,Female,Loyal Customer,24,Business travel,Business,541,1,2,4,2,1,1,1,1,1,3,4,4,4,1,0,7.0,neutral or dissatisfied +36569,87981,Male,Loyal Customer,41,Business travel,Business,444,5,5,5,5,2,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +36570,80720,Female,Loyal Customer,70,Personal Travel,Eco,920,2,5,2,4,3,4,5,4,4,2,4,5,4,3,0,1.0,neutral or dissatisfied +36571,54112,Male,Loyal Customer,51,Business travel,Business,3474,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +36572,122767,Male,Loyal Customer,37,Business travel,Business,3035,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +36573,48262,Male,Loyal Customer,57,Personal Travel,Eco,192,2,4,2,4,2,2,2,2,5,4,4,3,5,2,26,24.0,neutral or dissatisfied +36574,8676,Male,Loyal Customer,44,Business travel,Business,1611,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +36575,18320,Male,Loyal Customer,48,Business travel,Eco,705,5,3,3,3,5,5,5,5,5,2,4,2,5,5,14,3.0,satisfied +36576,106117,Female,Loyal Customer,53,Business travel,Business,436,3,3,3,3,4,4,4,4,4,4,4,5,4,3,12,6.0,satisfied +36577,112696,Male,Loyal Customer,44,Business travel,Business,3606,2,5,5,5,2,4,4,2,2,2,2,4,2,3,44,27.0,neutral or dissatisfied +36578,29238,Male,Loyal Customer,45,Business travel,Business,873,3,3,3,3,5,4,1,4,4,4,4,3,4,3,0,0.0,satisfied +36579,11535,Male,Loyal Customer,16,Business travel,Eco Plus,301,5,1,1,1,5,5,4,5,5,2,4,5,3,5,13,3.0,satisfied +36580,28795,Male,Loyal Customer,54,Personal Travel,Business,956,3,5,3,2,5,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +36581,69946,Female,disloyal Customer,36,Business travel,Business,2174,3,3,3,4,1,3,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +36582,12925,Male,Loyal Customer,24,Business travel,Business,456,5,5,5,5,5,5,5,5,3,3,2,2,3,5,0,0.0,satisfied +36583,37954,Female,disloyal Customer,13,Business travel,Eco,937,5,5,5,3,1,5,1,1,2,3,5,4,3,1,0,0.0,satisfied +36584,119187,Female,Loyal Customer,48,Business travel,Business,2798,1,1,1,1,3,4,5,4,4,4,4,5,4,4,0,17.0,satisfied +36585,66557,Female,Loyal Customer,17,Personal Travel,Eco,328,3,2,1,4,4,1,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +36586,40747,Female,Loyal Customer,47,Business travel,Eco,588,5,5,1,5,5,1,4,5,5,5,5,5,5,1,0,0.0,satisfied +36587,82162,Male,Loyal Customer,33,Business travel,Business,3598,2,5,5,5,2,2,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +36588,20195,Male,disloyal Customer,33,Business travel,Eco,334,1,4,1,4,1,1,1,1,2,3,5,4,1,1,5,0.0,neutral or dissatisfied +36589,75667,Female,Loyal Customer,49,Business travel,Business,868,3,3,4,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +36590,67675,Female,Loyal Customer,44,Business travel,Business,3297,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +36591,109972,Male,Loyal Customer,22,Personal Travel,Eco,1011,2,4,2,3,2,2,5,2,1,5,3,3,4,2,12,17.0,neutral or dissatisfied +36592,120694,Male,Loyal Customer,47,Personal Travel,Eco,280,2,5,2,5,3,2,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +36593,30579,Female,disloyal Customer,34,Business travel,Eco,628,3,5,3,2,1,3,1,1,4,2,2,1,5,1,0,0.0,neutral or dissatisfied +36594,6287,Female,Loyal Customer,62,Personal Travel,Eco,585,2,4,2,3,2,4,5,3,3,2,3,5,3,5,10,16.0,neutral or dissatisfied +36595,17845,Male,Loyal Customer,25,Business travel,Business,3472,5,5,5,5,5,5,5,5,3,5,5,1,1,5,3,10.0,satisfied +36596,99184,Female,Loyal Customer,70,Personal Travel,Eco,351,0,4,0,4,2,4,5,3,3,0,3,5,3,5,0,0.0,satisfied +36597,39268,Female,disloyal Customer,55,Business travel,Eco,67,3,1,3,4,1,3,1,1,2,2,3,2,3,1,3,12.0,neutral or dissatisfied +36598,92350,Male,Loyal Customer,29,Personal Travel,Eco,2556,1,5,1,1,4,1,4,4,2,1,3,3,3,4,4,0.0,neutral or dissatisfied +36599,58316,Female,Loyal Customer,55,Business travel,Business,1739,3,4,4,4,4,2,3,3,3,3,3,2,3,1,48,38.0,neutral or dissatisfied +36600,27642,Female,Loyal Customer,9,Personal Travel,Eco Plus,954,2,4,2,2,5,2,5,5,4,4,4,5,5,5,2,5.0,neutral or dissatisfied +36601,75073,Female,Loyal Customer,16,Personal Travel,Eco,2611,3,2,2,3,4,2,4,4,3,3,3,4,4,4,12,0.0,neutral or dissatisfied +36602,87490,Female,Loyal Customer,17,Business travel,Business,3335,3,5,5,5,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +36603,124512,Male,Loyal Customer,67,Personal Travel,Eco Plus,930,4,2,5,4,4,5,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +36604,16737,Male,Loyal Customer,17,Personal Travel,Eco,1167,3,4,3,5,4,3,4,4,5,2,4,5,5,4,7,30.0,neutral or dissatisfied +36605,42194,Female,Loyal Customer,33,Business travel,Business,3329,1,1,1,1,5,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +36606,112856,Female,Loyal Customer,21,Business travel,Business,1390,3,3,3,3,5,5,5,5,5,2,4,5,5,5,9,0.0,satisfied +36607,53466,Female,Loyal Customer,57,Business travel,Business,2419,5,5,5,5,4,4,4,3,2,4,5,4,5,4,0,0.0,satisfied +36608,91084,Male,Loyal Customer,17,Personal Travel,Eco,250,1,5,0,1,3,0,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +36609,14401,Male,Loyal Customer,63,Personal Travel,Eco,900,2,3,2,3,1,2,1,1,1,2,2,4,3,1,0,0.0,neutral or dissatisfied +36610,8474,Male,Loyal Customer,48,Business travel,Business,2864,2,2,2,2,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +36611,41418,Male,Loyal Customer,30,Personal Travel,Eco,809,3,4,3,3,5,3,5,5,2,1,3,4,4,5,0,0.0,neutral or dissatisfied +36612,55793,Female,disloyal Customer,35,Business travel,Eco,2400,4,4,4,2,4,5,5,4,5,2,2,5,4,5,0,26.0,neutral or dissatisfied +36613,20946,Female,Loyal Customer,65,Business travel,Business,689,3,4,4,4,1,3,4,3,3,3,3,3,3,4,11,0.0,neutral or dissatisfied +36614,56561,Female,Loyal Customer,40,Business travel,Business,2266,5,5,5,5,2,4,5,4,4,4,4,4,4,3,11,13.0,satisfied +36615,60308,Female,Loyal Customer,68,Business travel,Business,406,2,4,4,4,5,3,3,2,2,2,2,4,2,4,2,13.0,neutral or dissatisfied +36616,28671,Male,Loyal Customer,44,Personal Travel,Eco Plus,2541,2,5,2,2,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +36617,85322,Male,Loyal Customer,37,Personal Travel,Eco,696,2,4,2,2,5,2,5,5,3,5,4,5,4,5,38,27.0,neutral or dissatisfied +36618,114415,Male,Loyal Customer,60,Business travel,Business,358,2,2,2,2,5,5,5,4,4,5,4,3,4,5,12,5.0,satisfied +36619,54314,Female,disloyal Customer,27,Business travel,Eco,1597,2,1,1,3,3,2,3,3,4,4,1,3,2,3,0,0.0,neutral or dissatisfied +36620,7145,Male,disloyal Customer,21,Business travel,Business,130,5,0,5,2,3,5,4,3,5,4,5,4,5,3,6,5.0,satisfied +36621,115768,Female,disloyal Customer,50,Business travel,Business,480,5,5,5,4,1,5,1,1,4,4,5,4,4,1,20,2.0,satisfied +36622,14345,Female,Loyal Customer,31,Personal Travel,Eco,429,3,5,3,3,2,3,4,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +36623,92479,Male,Loyal Customer,52,Business travel,Eco,1892,1,2,2,2,1,1,1,1,3,3,4,3,4,1,14,0.0,neutral or dissatisfied +36624,82540,Male,disloyal Customer,24,Business travel,Eco,629,1,5,1,1,1,1,1,1,5,2,4,5,4,1,45,60.0,neutral or dissatisfied +36625,73116,Female,Loyal Customer,59,Personal Travel,Eco,2174,5,3,5,3,2,2,3,2,2,5,2,3,2,2,0,0.0,satisfied +36626,16676,Female,Loyal Customer,43,Personal Travel,Eco,488,3,5,3,4,2,3,2,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +36627,127269,Female,disloyal Customer,38,Business travel,Eco,707,1,1,1,2,3,1,3,3,5,1,1,3,1,3,0,0.0,neutral or dissatisfied +36628,55349,Male,disloyal Customer,25,Business travel,Business,594,2,0,2,3,4,2,4,4,3,4,4,5,5,4,6,22.0,neutral or dissatisfied +36629,81240,Female,Loyal Customer,30,Business travel,Business,930,5,5,2,5,5,5,5,5,4,5,4,4,5,5,17,22.0,satisfied +36630,102505,Female,Loyal Customer,24,Personal Travel,Eco,258,2,4,2,3,3,2,3,3,4,1,4,2,1,3,40,29.0,neutral or dissatisfied +36631,91755,Female,Loyal Customer,41,Business travel,Business,2158,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +36632,7464,Female,Loyal Customer,58,Business travel,Business,3386,5,5,5,5,5,4,4,4,4,4,4,5,4,4,4,0.0,satisfied +36633,28895,Male,Loyal Customer,41,Business travel,Eco,679,4,5,5,5,4,4,4,4,1,4,2,1,2,4,0,0.0,satisfied +36634,749,Male,Loyal Customer,58,Business travel,Business,354,3,3,3,3,3,4,4,4,4,4,4,5,4,3,10,8.0,satisfied +36635,27001,Male,Loyal Customer,28,Business travel,Business,954,4,4,5,4,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +36636,73125,Female,Loyal Customer,9,Personal Travel,Eco,2174,1,3,1,4,3,1,3,3,3,2,3,1,3,3,28,26.0,neutral or dissatisfied +36637,63818,Male,Loyal Customer,44,Business travel,Business,1192,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,12.0,satisfied +36638,30207,Male,Loyal Customer,62,Personal Travel,Eco Plus,548,4,1,4,4,1,4,1,1,1,4,3,1,4,1,0,0.0,neutral or dissatisfied +36639,116283,Male,Loyal Customer,25,Personal Travel,Eco,358,1,4,1,5,3,1,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +36640,27825,Male,Loyal Customer,32,Business travel,Business,2380,3,1,2,1,3,3,3,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +36641,85870,Male,disloyal Customer,27,Business travel,Business,938,5,5,5,2,4,5,1,4,3,2,4,4,4,4,0,0.0,satisfied +36642,26425,Male,Loyal Customer,52,Business travel,Eco,787,4,5,5,5,4,4,4,4,2,2,2,1,3,4,11,1.0,satisfied +36643,81583,Female,Loyal Customer,46,Personal Travel,Eco,503,1,4,1,2,4,4,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +36644,117585,Male,Loyal Customer,23,Business travel,Business,2452,2,4,3,3,2,2,2,2,3,3,3,4,3,2,25,18.0,neutral or dissatisfied +36645,2255,Female,Loyal Customer,51,Business travel,Business,3637,5,5,5,5,5,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +36646,2685,Female,Loyal Customer,64,Personal Travel,Eco Plus,597,3,4,3,4,5,3,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +36647,3952,Female,Loyal Customer,35,Business travel,Business,764,2,2,4,4,4,4,4,2,2,2,2,1,2,3,33,52.0,neutral or dissatisfied +36648,114166,Female,Loyal Customer,32,Business travel,Business,957,1,1,4,1,4,4,4,4,4,3,5,3,5,4,1,2.0,satisfied +36649,46817,Male,Loyal Customer,55,Business travel,Eco,844,5,5,5,5,5,5,5,5,4,1,5,5,3,5,70,70.0,satisfied +36650,12339,Female,Loyal Customer,39,Business travel,Business,253,4,2,2,2,5,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +36651,111096,Female,disloyal Customer,54,Business travel,Business,240,2,2,2,1,4,2,4,4,3,5,4,3,4,4,23,18.0,neutral or dissatisfied +36652,38207,Male,Loyal Customer,37,Business travel,Eco Plus,1249,5,4,4,4,5,5,5,5,2,1,3,3,5,5,0,0.0,satisfied +36653,14825,Male,Loyal Customer,62,Business travel,Eco,314,5,4,4,4,5,5,5,5,1,1,3,4,3,5,1,5.0,satisfied +36654,109382,Female,disloyal Customer,26,Business travel,Eco,789,1,0,0,5,2,0,2,2,5,5,1,5,2,2,0,0.0,neutral or dissatisfied +36655,174,Female,Loyal Customer,39,Business travel,Business,3822,3,4,3,4,1,3,4,3,3,3,3,4,3,2,6,9.0,neutral or dissatisfied +36656,1837,Male,Loyal Customer,11,Personal Travel,Eco,408,3,2,4,4,1,4,1,1,2,2,4,4,3,1,29,18.0,neutral or dissatisfied +36657,66725,Male,Loyal Customer,31,Personal Travel,Eco,802,3,2,3,3,4,3,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +36658,68249,Male,Loyal Customer,47,Business travel,Business,231,2,4,2,4,4,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +36659,86383,Male,disloyal Customer,34,Business travel,Eco,762,3,3,3,4,2,3,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +36660,23000,Female,Loyal Customer,54,Personal Travel,Eco,641,3,5,2,3,5,4,5,3,3,2,3,4,3,5,100,96.0,neutral or dissatisfied +36661,111663,Female,disloyal Customer,28,Business travel,Business,991,5,5,5,2,5,5,5,5,3,5,4,3,4,5,1,0.0,satisfied +36662,19642,Male,Loyal Customer,9,Personal Travel,Eco,642,3,2,3,3,4,3,4,4,3,1,3,1,4,4,10,0.0,neutral or dissatisfied +36663,85970,Female,disloyal Customer,51,Business travel,Business,528,1,1,1,4,3,1,3,3,3,5,5,5,4,3,0,6.0,neutral or dissatisfied +36664,98598,Female,Loyal Customer,34,Business travel,Business,1564,3,3,3,3,2,4,5,4,4,4,4,5,4,4,9,0.0,satisfied +36665,56684,Female,Loyal Customer,17,Personal Travel,Eco,937,2,5,2,3,4,2,4,4,4,2,5,3,5,4,1,0.0,neutral or dissatisfied +36666,60633,Male,disloyal Customer,25,Business travel,Business,763,5,0,5,2,5,5,5,5,3,3,3,3,5,5,1,0.0,satisfied +36667,40136,Female,Loyal Customer,14,Personal Travel,Eco Plus,368,3,3,3,4,5,3,5,5,3,1,4,4,1,5,0,0.0,neutral or dissatisfied +36668,40920,Female,Loyal Customer,42,Personal Travel,Eco,588,2,4,2,3,3,3,5,4,4,2,1,2,4,5,0,0.0,neutral or dissatisfied +36669,85460,Female,Loyal Customer,52,Business travel,Business,3881,5,5,5,5,2,5,5,5,5,5,5,4,5,4,67,57.0,satisfied +36670,82826,Female,Loyal Customer,53,Business travel,Business,1790,3,3,3,3,3,4,4,4,4,4,4,4,4,3,9,10.0,satisfied +36671,21701,Female,Loyal Customer,56,Personal Travel,Eco,746,2,4,2,3,5,4,2,5,5,2,5,4,5,5,52,64.0,neutral or dissatisfied +36672,61228,Male,disloyal Customer,27,Business travel,Eco,862,1,1,1,3,3,1,5,3,3,1,4,4,4,3,0,0.0,neutral or dissatisfied +36673,90912,Male,Loyal Customer,28,Business travel,Business,3902,2,2,2,2,2,2,2,2,3,3,4,3,4,2,2,6.0,neutral or dissatisfied +36674,54524,Male,Loyal Customer,11,Personal Travel,Eco,925,4,4,4,1,5,4,5,5,4,2,4,4,5,5,0,0.0,satisfied +36675,21461,Female,Loyal Customer,56,Business travel,Eco,331,4,5,5,5,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +36676,109326,Female,Loyal Customer,42,Personal Travel,Eco,1072,2,5,2,4,2,5,4,2,2,2,2,5,2,4,18,3.0,neutral or dissatisfied +36677,7047,Male,Loyal Customer,24,Personal Travel,Eco Plus,299,4,5,4,5,3,4,4,3,5,5,4,5,5,3,10,11.0,neutral or dissatisfied +36678,19316,Male,Loyal Customer,44,Business travel,Eco,743,5,4,4,4,5,5,5,5,1,4,4,5,2,5,0,12.0,satisfied +36679,7459,Female,Loyal Customer,9,Personal Travel,Eco Plus,522,5,4,5,2,2,5,2,2,3,4,4,4,4,2,0,0.0,satisfied +36680,38731,Male,Loyal Customer,57,Business travel,Eco,353,4,5,5,5,4,4,4,4,2,2,2,2,3,4,0,0.0,satisfied +36681,7863,Female,Loyal Customer,46,Business travel,Business,948,4,4,4,4,5,4,5,3,3,4,3,3,3,4,14,17.0,satisfied +36682,104996,Female,Loyal Customer,30,Personal Travel,Eco,406,4,4,4,1,2,4,2,2,5,5,5,3,5,2,6,0.0,neutral or dissatisfied +36683,38741,Male,Loyal Customer,29,Business travel,Business,3187,1,1,5,1,5,5,5,5,2,1,5,2,3,5,0,0.0,satisfied +36684,49192,Male,Loyal Customer,61,Business travel,Eco,209,5,2,2,2,5,5,5,5,5,3,4,5,4,5,0,0.0,satisfied +36685,110213,Female,disloyal Customer,29,Business travel,Eco,1310,2,3,3,4,1,2,1,1,2,3,3,2,3,1,0,8.0,neutral or dissatisfied +36686,21838,Female,disloyal Customer,21,Business travel,Business,448,5,0,5,5,2,5,3,2,3,4,4,4,5,2,0,0.0,satisfied +36687,47472,Male,Loyal Customer,70,Personal Travel,Eco,574,3,2,3,2,1,3,1,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +36688,56169,Female,disloyal Customer,26,Business travel,Eco,1000,2,3,3,4,3,3,3,3,5,3,2,1,3,3,0,0.0,neutral or dissatisfied +36689,43176,Female,disloyal Customer,25,Business travel,Eco Plus,781,3,0,3,2,2,3,2,2,3,1,4,5,3,2,2,0.0,neutral or dissatisfied +36690,128227,Female,Loyal Customer,40,Business travel,Business,602,4,3,3,3,2,3,3,4,4,3,4,2,4,2,18,28.0,neutral or dissatisfied +36691,121420,Female,Loyal Customer,41,Business travel,Business,2699,1,1,1,1,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +36692,105518,Female,Loyal Customer,51,Business travel,Business,611,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +36693,14637,Male,Loyal Customer,25,Business travel,Business,948,3,3,3,3,4,4,4,4,3,1,3,2,4,4,11,0.0,satisfied +36694,41626,Female,Loyal Customer,59,Personal Travel,Eco Plus,1211,3,0,3,2,2,3,4,5,5,3,5,5,5,4,0,1.0,neutral or dissatisfied +36695,43864,Male,Loyal Customer,54,Business travel,Business,255,1,1,1,1,2,1,5,4,4,4,4,1,4,2,6,0.0,satisfied +36696,118468,Male,Loyal Customer,34,Business travel,Business,3916,5,5,5,5,2,5,5,4,4,4,4,3,4,5,1,0.0,satisfied +36697,122196,Male,disloyal Customer,43,Business travel,Business,541,2,2,2,5,3,2,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +36698,12397,Female,disloyal Customer,22,Business travel,Eco,127,5,0,5,3,5,5,5,5,3,3,3,2,2,5,0,0.0,satisfied +36699,58182,Male,Loyal Customer,50,Business travel,Eco,925,3,4,4,4,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +36700,17920,Female,Loyal Customer,21,Personal Travel,Eco,900,3,4,4,2,3,4,1,3,3,5,2,3,5,3,0,0.0,neutral or dissatisfied +36701,58145,Male,Loyal Customer,51,Personal Travel,Business,925,3,5,3,2,5,4,2,3,3,3,3,5,3,4,54,28.0,neutral or dissatisfied +36702,132,Male,disloyal Customer,59,Business travel,Business,227,2,2,2,3,2,2,2,2,4,3,4,4,5,2,11,5.0,neutral or dissatisfied +36703,99318,Male,Loyal Customer,47,Business travel,Eco,448,2,5,5,5,3,2,3,3,1,4,2,1,2,3,0,0.0,neutral or dissatisfied +36704,31200,Female,Loyal Customer,58,Business travel,Business,3465,1,1,1,1,5,1,2,5,5,5,5,5,5,3,11,12.0,satisfied +36705,10326,Male,disloyal Customer,29,Business travel,Business,229,5,5,5,2,2,5,2,2,3,4,4,4,4,2,48,36.0,satisfied +36706,76932,Male,Loyal Customer,54,Business travel,Business,3976,1,4,4,4,5,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +36707,86123,Female,Loyal Customer,42,Business travel,Business,226,0,0,0,2,4,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +36708,66176,Female,disloyal Customer,24,Business travel,Eco,550,1,4,1,4,1,1,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +36709,59047,Female,Loyal Customer,50,Business travel,Business,1723,5,5,5,5,2,3,5,3,3,3,3,4,3,5,1,0.0,satisfied +36710,93414,Male,Loyal Customer,57,Business travel,Business,605,3,2,2,2,3,3,3,3,3,3,3,4,3,4,43,33.0,neutral or dissatisfied +36711,97389,Female,Loyal Customer,38,Business travel,Eco Plus,347,4,3,4,3,4,4,4,4,4,1,4,1,3,4,22,13.0,neutral or dissatisfied +36712,88701,Female,Loyal Customer,61,Personal Travel,Eco,366,2,1,2,4,5,4,3,5,5,2,5,1,5,2,70,60.0,neutral or dissatisfied +36713,80750,Female,Loyal Customer,52,Personal Travel,Eco,393,4,4,4,4,4,4,5,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +36714,31635,Male,Loyal Customer,40,Business travel,Business,3084,2,2,2,2,3,4,4,5,5,5,5,2,5,3,11,7.0,satisfied +36715,916,Female,disloyal Customer,61,Business travel,Business,247,5,5,5,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +36716,88920,Male,Loyal Customer,9,Personal Travel,Eco,859,3,5,4,2,4,4,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +36717,25829,Male,Loyal Customer,30,Business travel,Business,3439,1,1,1,1,5,5,5,5,5,5,1,5,1,5,25,18.0,satisfied +36718,26166,Female,disloyal Customer,22,Business travel,Eco,404,1,3,1,2,5,1,5,5,5,4,2,3,4,5,0,0.0,neutral or dissatisfied +36719,49491,Male,disloyal Customer,23,Business travel,Eco,156,3,5,3,4,4,3,4,4,2,1,2,3,5,4,0,0.0,neutral or dissatisfied +36720,7717,Female,disloyal Customer,24,Business travel,Business,859,5,5,4,1,5,4,5,5,5,5,5,4,4,5,0,0.0,satisfied +36721,4293,Male,Loyal Customer,17,Personal Travel,Eco,502,3,5,3,3,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +36722,28037,Male,Loyal Customer,30,Business travel,Eco,2537,4,1,4,1,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +36723,68600,Female,Loyal Customer,46,Business travel,Business,1739,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +36724,90800,Female,Loyal Customer,16,Business travel,Business,646,3,1,2,1,3,3,3,3,3,4,3,2,4,3,10,20.0,neutral or dissatisfied +36725,78273,Female,Loyal Customer,67,Personal Travel,Business,1598,2,5,2,4,2,3,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +36726,6497,Male,Loyal Customer,58,Business travel,Business,3296,3,3,3,3,2,5,5,5,5,5,5,3,5,3,63,61.0,satisfied +36727,36899,Male,disloyal Customer,29,Business travel,Business,2072,4,4,4,4,1,4,1,1,3,5,5,4,5,1,26,4.0,satisfied +36728,124350,Female,Loyal Customer,48,Business travel,Business,2494,1,1,1,1,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +36729,115440,Male,Loyal Customer,62,Business travel,Business,308,2,2,2,2,3,5,4,5,5,5,5,5,5,3,11,3.0,satisfied +36730,19168,Male,disloyal Customer,25,Business travel,Eco Plus,304,2,2,2,3,1,2,1,1,1,3,2,4,3,1,0,24.0,neutral or dissatisfied +36731,7654,Female,Loyal Customer,58,Business travel,Business,2675,4,4,3,4,2,4,4,4,4,4,4,4,4,4,3,26.0,satisfied +36732,30390,Female,Loyal Customer,70,Personal Travel,Eco,775,2,4,2,4,2,3,5,3,3,2,2,5,3,5,0,14.0,neutral or dissatisfied +36733,33048,Male,Loyal Customer,58,Personal Travel,Eco,102,1,4,1,3,5,1,5,5,1,4,2,1,1,5,15,14.0,neutral or dissatisfied +36734,48174,Male,disloyal Customer,25,Business travel,Eco,259,2,4,2,4,4,2,2,4,2,1,2,4,3,4,0,0.0,neutral or dissatisfied +36735,60328,Male,Loyal Customer,57,Business travel,Business,2296,5,5,5,5,2,4,4,4,4,4,4,5,4,3,13,18.0,satisfied +36736,108147,Female,Loyal Customer,48,Business travel,Business,2040,1,1,1,1,4,2,5,5,5,5,5,5,5,2,4,0.0,satisfied +36737,48814,Female,Loyal Customer,15,Personal Travel,Business,421,3,2,3,4,2,3,2,2,1,3,4,4,3,2,0,0.0,neutral or dissatisfied +36738,119470,Male,Loyal Customer,46,Business travel,Business,814,4,4,4,4,3,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +36739,124471,Female,Loyal Customer,58,Personal Travel,Eco,980,3,4,3,4,3,5,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +36740,120300,Male,Loyal Customer,51,Business travel,Business,2048,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +36741,15686,Female,Loyal Customer,58,Business travel,Eco,335,2,3,3,3,1,4,4,2,2,2,2,4,2,3,14,0.0,neutral or dissatisfied +36742,20948,Male,Loyal Customer,34,Business travel,Business,1576,3,2,2,2,4,2,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +36743,41031,Female,Loyal Customer,51,Business travel,Business,1609,1,1,1,1,3,3,3,4,4,4,4,4,4,5,0,0.0,satisfied +36744,37350,Male,Loyal Customer,44,Business travel,Business,3328,5,5,5,5,2,2,1,4,4,4,4,2,4,2,35,52.0,satisfied +36745,122510,Female,Loyal Customer,34,Business travel,Business,2042,5,5,5,5,4,4,5,5,5,5,5,3,5,3,29,28.0,satisfied +36746,80700,Female,Loyal Customer,19,Personal Travel,Eco,1013,4,5,4,2,3,4,3,3,2,3,3,2,2,3,0,0.0,neutral or dissatisfied +36747,35053,Female,Loyal Customer,42,Business travel,Business,828,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,15.0,satisfied +36748,62126,Female,Loyal Customer,39,Business travel,Business,2454,5,5,5,5,4,4,4,5,5,5,5,4,5,4,2,0.0,satisfied +36749,88418,Male,disloyal Customer,26,Business travel,Business,366,4,4,4,1,4,4,2,4,3,4,4,3,5,4,4,0.0,neutral or dissatisfied +36750,74859,Male,Loyal Customer,57,Business travel,Business,1995,3,3,3,3,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +36751,30569,Female,Loyal Customer,48,Business travel,Eco,628,4,5,5,5,4,2,2,4,4,4,4,3,4,1,38,30.0,satisfied +36752,91599,Male,Loyal Customer,47,Business travel,Business,1340,4,4,4,4,3,4,5,3,3,3,3,5,3,3,65,63.0,satisfied +36753,113206,Male,Loyal Customer,42,Business travel,Business,2105,3,3,3,3,2,5,5,3,3,4,3,5,3,5,7,0.0,satisfied +36754,58335,Female,Loyal Customer,46,Business travel,Business,315,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +36755,83600,Female,disloyal Customer,27,Business travel,Business,409,5,5,5,4,2,5,2,2,4,2,4,5,4,2,14,8.0,satisfied +36756,7272,Female,Loyal Customer,38,Personal Travel,Eco,116,3,2,3,3,5,3,5,5,2,3,4,2,4,5,0,0.0,neutral or dissatisfied +36757,11670,Male,Loyal Customer,20,Personal Travel,Eco,1117,3,3,2,3,2,2,2,2,1,4,4,2,4,2,0,0.0,neutral or dissatisfied +36758,5668,Male,disloyal Customer,47,Business travel,Eco,436,3,3,3,3,4,3,4,4,3,4,3,1,4,4,16,22.0,neutral or dissatisfied +36759,92036,Male,Loyal Customer,58,Business travel,Business,1576,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +36760,129085,Female,disloyal Customer,38,Business travel,Business,2342,1,1,1,3,1,5,5,5,5,4,4,5,3,5,30,46.0,neutral or dissatisfied +36761,54467,Female,Loyal Customer,40,Business travel,Eco,925,5,3,3,3,5,5,5,5,4,4,4,4,3,5,0,0.0,satisfied +36762,80183,Male,Loyal Customer,36,Personal Travel,Eco,2475,3,2,3,3,3,3,3,1,1,4,3,3,4,3,122,184.0,neutral or dissatisfied +36763,84974,Female,Loyal Customer,46,Business travel,Business,1590,5,5,5,5,4,4,5,3,3,4,3,3,3,3,9,5.0,satisfied +36764,69438,Male,Loyal Customer,34,Personal Travel,Eco,1096,3,1,3,4,5,3,5,5,4,1,4,4,3,5,0,0.0,neutral or dissatisfied +36765,34978,Female,Loyal Customer,22,Business travel,Business,273,3,3,3,3,4,4,4,4,2,4,2,4,4,4,8,2.0,satisfied +36766,14330,Female,Loyal Customer,64,Personal Travel,Eco,395,4,4,4,3,2,5,5,4,4,4,4,5,4,3,21,18.0,neutral or dissatisfied +36767,129486,Male,Loyal Customer,73,Business travel,Eco,1204,4,5,5,5,4,4,4,4,3,3,3,4,3,4,2,1.0,neutral or dissatisfied +36768,112683,Male,Loyal Customer,48,Business travel,Business,2922,1,1,2,1,3,5,5,4,4,4,4,3,4,5,3,0.0,satisfied +36769,3597,Female,Loyal Customer,62,Business travel,Business,3675,3,1,3,3,4,4,4,3,3,3,3,4,3,4,70,84.0,neutral or dissatisfied +36770,119368,Male,Loyal Customer,33,Business travel,Business,2950,3,3,3,3,4,4,4,4,3,4,4,5,5,4,0,12.0,satisfied +36771,18053,Female,disloyal Customer,27,Business travel,Eco,605,5,0,5,3,3,5,3,3,1,5,1,4,1,3,0,0.0,satisfied +36772,86184,Female,disloyal Customer,58,Business travel,Eco,306,3,1,3,4,2,3,2,2,4,3,3,2,3,2,124,114.0,neutral or dissatisfied +36773,45508,Male,Loyal Customer,48,Personal Travel,Eco Plus,587,2,2,2,4,4,2,4,4,2,5,3,2,3,4,0,0.0,neutral or dissatisfied +36774,64434,Female,Loyal Customer,39,Business travel,Business,2656,1,1,2,1,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +36775,85743,Female,Loyal Customer,20,Business travel,Business,666,1,1,1,1,5,5,5,5,3,3,5,3,4,5,22,30.0,satisfied +36776,117546,Female,Loyal Customer,49,Business travel,Business,1568,2,2,2,2,3,5,5,4,4,4,4,5,4,3,8,0.0,satisfied +36777,67327,Male,Loyal Customer,24,Personal Travel,Eco Plus,985,3,4,2,4,5,2,3,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +36778,126373,Female,Loyal Customer,18,Personal Travel,Eco,600,3,5,3,5,4,3,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +36779,25171,Female,Loyal Customer,47,Business travel,Business,369,4,4,4,4,2,1,1,4,4,4,4,3,4,3,0,0.0,satisfied +36780,112404,Female,Loyal Customer,41,Business travel,Business,2632,4,4,4,4,3,5,5,4,4,5,4,4,4,4,26,11.0,satisfied +36781,37565,Male,disloyal Customer,18,Business travel,Eco,944,3,3,3,4,4,3,3,4,2,4,3,3,3,4,101,84.0,neutral or dissatisfied +36782,110754,Female,Loyal Customer,57,Business travel,Business,3740,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,2.0,satisfied +36783,76651,Male,Loyal Customer,21,Personal Travel,Eco,516,2,4,2,3,5,2,5,5,5,4,4,4,4,5,0,16.0,neutral or dissatisfied +36784,24153,Female,Loyal Customer,33,Business travel,Business,1608,3,1,3,3,2,3,4,5,5,5,3,5,5,4,0,0.0,satisfied +36785,108049,Female,Loyal Customer,26,Personal Travel,Eco,591,3,0,3,4,5,3,5,5,4,2,4,5,4,5,27,16.0,neutral or dissatisfied +36786,25082,Female,Loyal Customer,54,Personal Travel,Eco,957,2,5,2,1,4,5,4,5,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +36787,4156,Male,disloyal Customer,18,Business travel,Eco,431,2,3,2,3,5,2,5,5,4,1,4,1,4,5,28,74.0,neutral or dissatisfied +36788,60882,Female,Loyal Customer,61,Business travel,Business,3710,2,1,1,1,2,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +36789,86968,Female,disloyal Customer,28,Business travel,Eco,907,2,2,2,3,2,3,3,1,5,4,3,3,1,3,211,203.0,neutral or dissatisfied +36790,119928,Female,Loyal Customer,42,Business travel,Business,1984,3,3,1,3,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +36791,98097,Female,Loyal Customer,52,Business travel,Business,3345,5,5,5,5,2,4,4,4,4,4,4,4,4,3,5,5.0,satisfied +36792,64236,Male,Loyal Customer,43,Business travel,Business,1660,2,2,2,2,2,4,4,2,2,2,2,3,2,3,1,0.0,satisfied +36793,114439,Male,Loyal Customer,25,Business travel,Business,362,1,1,3,1,4,4,4,4,4,4,5,4,4,4,7,5.0,satisfied +36794,115734,Female,disloyal Customer,26,Business travel,Eco,373,2,4,2,3,5,2,5,5,2,1,4,1,4,5,78,62.0,neutral or dissatisfied +36795,21273,Male,Loyal Customer,29,Business travel,Business,2194,4,4,4,4,5,5,5,5,1,5,2,5,5,5,0,0.0,satisfied +36796,41223,Male,disloyal Customer,19,Business travel,Eco,1042,4,4,4,3,2,4,2,2,1,5,3,4,3,2,53,35.0,neutral or dissatisfied +36797,95479,Male,disloyal Customer,37,Business travel,Business,148,3,3,3,1,4,3,2,4,4,4,4,4,4,4,0,0.0,satisfied +36798,1931,Male,Loyal Customer,33,Business travel,Business,3155,3,3,3,3,3,3,3,3,3,4,3,1,4,3,81,82.0,neutral or dissatisfied +36799,56676,Male,Loyal Customer,32,Personal Travel,Eco,1065,3,4,2,4,3,2,3,3,4,4,3,2,4,3,0,11.0,neutral or dissatisfied +36800,67350,Male,Loyal Customer,8,Personal Travel,Eco,1471,2,4,2,1,3,2,3,3,4,4,3,5,4,3,0,0.0,neutral or dissatisfied +36801,94870,Female,Loyal Customer,43,Business travel,Business,189,0,5,0,4,3,4,5,4,4,3,3,4,4,3,0,0.0,satisfied +36802,96130,Male,disloyal Customer,59,Business travel,Business,460,5,5,5,1,4,5,4,4,5,2,4,4,5,4,0,0.0,satisfied +36803,121431,Male,Loyal Customer,47,Business travel,Eco,331,4,3,3,3,4,4,4,4,4,1,2,3,2,4,14,9.0,neutral or dissatisfied +36804,24972,Male,Loyal Customer,37,Business travel,Business,484,5,5,5,5,3,1,3,3,3,4,3,3,3,3,2,0.0,satisfied +36805,61542,Female,Loyal Customer,26,Personal Travel,Eco,2419,3,4,3,1,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +36806,74100,Male,Loyal Customer,43,Business travel,Business,641,5,5,5,5,4,5,5,5,5,5,5,3,5,5,2,0.0,satisfied +36807,15329,Female,disloyal Customer,24,Business travel,Eco,589,4,0,5,1,4,5,4,4,1,1,5,2,4,4,0,0.0,neutral or dissatisfied +36808,4024,Male,Loyal Customer,51,Business travel,Business,2385,1,3,3,3,2,3,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +36809,61792,Male,Loyal Customer,58,Personal Travel,Eco,1346,0,2,0,3,2,0,2,2,1,3,2,3,3,2,10,0.0,satisfied +36810,1267,Male,Loyal Customer,19,Personal Travel,Eco,89,1,5,1,2,4,1,4,4,3,2,4,4,4,4,40,57.0,neutral or dissatisfied +36811,21100,Female,disloyal Customer,20,Business travel,Eco,227,2,0,2,3,3,2,3,3,5,3,3,2,1,3,0,0.0,neutral or dissatisfied +36812,55248,Male,Loyal Customer,17,Personal Travel,Eco,1009,2,5,2,3,4,2,4,4,4,4,4,4,5,4,4,0.0,neutral or dissatisfied +36813,51353,Female,Loyal Customer,32,Business travel,Eco Plus,89,4,1,1,1,4,4,4,4,5,4,1,2,3,4,0,11.0,satisfied +36814,90792,Female,disloyal Customer,22,Business travel,Eco,594,3,2,3,3,4,3,4,4,2,5,4,4,3,4,8,13.0,neutral or dissatisfied +36815,126076,Male,Loyal Customer,38,Business travel,Business,2709,2,2,2,2,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +36816,103862,Male,Loyal Customer,51,Personal Travel,Eco,869,3,1,3,3,3,3,3,3,1,1,4,2,4,3,12,11.0,neutral or dissatisfied +36817,3872,Male,Loyal Customer,58,Business travel,Business,1784,1,1,2,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +36818,128304,Female,Loyal Customer,47,Business travel,Business,1525,4,4,3,4,4,5,4,5,5,5,5,5,5,3,2,12.0,satisfied +36819,92483,Male,Loyal Customer,25,Business travel,Business,1947,1,1,1,1,5,5,5,5,5,3,3,4,5,5,6,0.0,satisfied +36820,25369,Female,Loyal Customer,44,Business travel,Business,591,3,3,3,3,5,4,1,5,5,5,5,2,5,2,0,0.0,satisfied +36821,83495,Male,Loyal Customer,57,Business travel,Business,946,1,2,2,2,3,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +36822,105566,Female,Loyal Customer,48,Business travel,Business,3157,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +36823,113322,Female,Loyal Customer,42,Business travel,Business,3828,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +36824,75878,Male,Loyal Customer,22,Personal Travel,Eco,1972,3,0,3,2,4,3,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +36825,69184,Male,Loyal Customer,19,Personal Travel,Eco,187,3,3,3,3,1,3,1,1,4,3,2,3,3,1,41,32.0,neutral or dissatisfied +36826,123855,Female,Loyal Customer,52,Business travel,Business,3068,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +36827,22648,Female,disloyal Customer,39,Business travel,Business,300,2,2,2,3,5,2,5,5,4,1,5,5,3,5,38,30.0,neutral or dissatisfied +36828,53029,Male,Loyal Customer,32,Business travel,Business,1190,1,1,1,1,1,1,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +36829,119273,Female,Loyal Customer,36,Business travel,Business,214,3,3,3,3,1,4,4,1,1,1,3,2,1,1,0,0.0,neutral or dissatisfied +36830,129178,Male,Loyal Customer,20,Business travel,Business,954,1,1,1,1,4,4,4,4,4,2,5,4,5,4,19,13.0,satisfied +36831,76763,Female,Loyal Customer,48,Business travel,Business,3198,2,5,2,2,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +36832,126720,Female,disloyal Customer,40,Business travel,Business,2402,2,2,2,3,4,2,5,4,1,4,3,1,4,4,0,12.0,neutral or dissatisfied +36833,30252,Male,disloyal Customer,43,Business travel,Business,624,3,3,3,3,4,3,4,4,3,3,4,3,4,4,24,22.0,neutral or dissatisfied +36834,79298,Female,Loyal Customer,51,Business travel,Business,2248,4,1,4,4,5,5,5,3,4,5,5,5,4,5,0,0.0,satisfied +36835,58185,Female,Loyal Customer,58,Business travel,Eco,925,3,2,2,2,5,3,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +36836,84929,Female,Loyal Customer,36,Personal Travel,Eco,547,2,3,2,3,2,2,5,2,4,5,5,3,4,2,11,4.0,neutral or dissatisfied +36837,73999,Female,Loyal Customer,51,Business travel,Business,1931,2,5,5,5,3,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +36838,82054,Female,Loyal Customer,39,Business travel,Eco Plus,1532,3,4,4,4,3,3,3,3,3,2,4,4,4,3,40,27.0,neutral or dissatisfied +36839,61714,Female,Loyal Customer,39,Business travel,Business,3361,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +36840,39479,Male,disloyal Customer,26,Business travel,Eco,867,4,4,4,3,3,4,3,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +36841,37642,Female,Loyal Customer,31,Personal Travel,Eco,1028,1,5,1,1,2,1,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +36842,67691,Male,Loyal Customer,47,Business travel,Business,1607,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +36843,46318,Female,Loyal Customer,63,Business travel,Business,420,2,2,2,2,1,5,3,3,3,3,3,3,3,2,0,0.0,satisfied +36844,9199,Female,Loyal Customer,50,Business travel,Business,2480,1,1,1,1,2,4,4,4,4,4,4,4,4,3,6,0.0,satisfied +36845,22380,Female,disloyal Customer,36,Business travel,Eco,145,3,5,3,2,2,3,2,2,5,4,2,4,2,2,0,2.0,neutral or dissatisfied +36846,4213,Female,Loyal Customer,67,Personal Travel,Eco,888,3,3,3,1,3,3,1,5,5,3,3,2,5,2,0,0.0,neutral or dissatisfied +36847,10510,Male,Loyal Customer,33,Business travel,Business,2337,5,5,3,5,4,4,4,4,4,5,5,3,5,4,68,61.0,satisfied +36848,56291,Female,disloyal Customer,28,Business travel,Business,2227,1,1,1,2,2,1,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +36849,91824,Female,Loyal Customer,58,Business travel,Business,588,5,5,5,5,4,5,5,4,4,5,4,5,4,4,23,14.0,satisfied +36850,105393,Female,Loyal Customer,18,Personal Travel,Eco,369,4,1,5,1,5,5,5,5,1,3,1,4,1,5,23,23.0,neutral or dissatisfied +36851,10557,Female,disloyal Customer,22,Business travel,Eco,216,2,0,1,2,2,1,2,2,4,5,5,4,4,2,3,1.0,neutral or dissatisfied +36852,122475,Male,disloyal Customer,37,Business travel,Eco,575,3,3,2,4,5,2,5,5,4,3,3,4,4,5,0,0.0,neutral or dissatisfied +36853,78629,Female,Loyal Customer,59,Personal Travel,Eco,1426,3,5,3,3,5,4,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +36854,98689,Female,Loyal Customer,35,Personal Travel,Eco,992,2,5,2,5,1,2,1,1,4,4,4,4,4,1,14,11.0,neutral or dissatisfied +36855,40627,Female,Loyal Customer,51,Personal Travel,Eco,216,3,0,3,2,1,1,4,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +36856,122760,Female,Loyal Customer,39,Personal Travel,Eco,651,2,0,2,4,2,2,2,2,5,3,4,4,4,2,0,2.0,neutral or dissatisfied +36857,37276,Male,Loyal Customer,41,Business travel,Business,2178,3,3,3,3,2,2,3,5,5,5,5,1,5,3,0,0.0,satisfied +36858,48805,Male,Loyal Customer,29,Personal Travel,Business,190,3,4,3,1,3,3,3,3,5,4,5,3,5,3,89,111.0,neutral or dissatisfied +36859,43717,Male,Loyal Customer,22,Personal Travel,Eco,257,2,5,2,2,4,2,4,4,1,2,3,5,3,4,0,0.0,neutral or dissatisfied +36860,27248,Male,Loyal Customer,38,Business travel,Eco Plus,1024,4,4,4,4,4,4,4,4,5,4,2,1,3,4,0,0.0,satisfied +36861,97678,Male,Loyal Customer,29,Personal Travel,Eco,491,3,4,3,2,3,3,3,3,4,4,1,4,2,3,8,7.0,neutral or dissatisfied +36862,118491,Female,disloyal Customer,23,Business travel,Eco,369,2,2,2,4,5,2,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +36863,78852,Female,Loyal Customer,73,Business travel,Eco Plus,447,1,4,4,4,2,3,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +36864,109778,Male,Loyal Customer,42,Business travel,Business,3697,5,5,5,5,3,5,5,5,5,5,5,4,5,4,7,0.0,satisfied +36865,89373,Female,Loyal Customer,30,Personal Travel,Business,134,3,0,0,3,1,0,1,1,4,1,5,4,3,1,0,0.0,neutral or dissatisfied +36866,103280,Male,Loyal Customer,59,Business travel,Business,1528,5,5,2,5,2,5,4,4,4,4,4,3,4,3,22,23.0,satisfied +36867,106384,Male,disloyal Customer,25,Business travel,Eco,551,3,1,3,2,3,3,3,3,3,3,2,2,2,3,4,13.0,neutral or dissatisfied +36868,85658,Female,Loyal Customer,55,Personal Travel,Business,903,3,5,3,4,2,5,5,1,1,3,1,3,1,3,34,4.0,neutral or dissatisfied +36869,65203,Female,Loyal Customer,58,Business travel,Business,3338,0,1,1,4,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +36870,68920,Female,Loyal Customer,46,Personal Travel,Eco,936,1,4,1,1,1,3,3,4,5,4,4,3,5,3,142,135.0,neutral or dissatisfied +36871,121892,Female,Loyal Customer,19,Personal Travel,Eco,366,1,3,1,3,1,1,1,1,1,5,2,1,2,1,0,0.0,neutral or dissatisfied +36872,7896,Female,disloyal Customer,22,Business travel,Eco,1020,3,3,3,4,4,3,3,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +36873,11913,Male,Loyal Customer,69,Personal Travel,Eco,744,1,1,1,4,5,1,5,5,1,2,3,1,4,5,0,0.0,neutral or dissatisfied +36874,115584,Female,Loyal Customer,41,Business travel,Business,3459,1,4,2,4,2,4,3,1,1,1,1,4,1,3,2,0.0,neutral or dissatisfied +36875,6196,Male,Loyal Customer,73,Business travel,Eco Plus,409,3,1,4,1,3,3,3,3,4,1,3,2,2,3,12,17.0,neutral or dissatisfied +36876,68049,Female,Loyal Customer,55,Business travel,Business,813,2,2,2,2,5,4,5,5,5,5,5,3,5,3,1,0.0,satisfied +36877,94476,Male,Loyal Customer,55,Business travel,Business,3090,1,1,1,1,2,5,5,5,5,5,5,4,5,4,46,41.0,satisfied +36878,1131,Male,Loyal Customer,48,Personal Travel,Eco,164,1,4,1,4,5,1,1,5,3,2,5,5,4,5,26,28.0,neutral or dissatisfied +36879,94718,Male,Loyal Customer,31,Business travel,Eco,239,1,3,3,3,1,1,1,1,2,1,4,4,4,1,21,26.0,neutral or dissatisfied +36880,11121,Male,Loyal Customer,11,Personal Travel,Eco,140,1,1,1,2,3,1,3,3,4,3,2,4,3,3,4,8.0,neutral or dissatisfied +36881,3145,Male,disloyal Customer,59,Business travel,Business,237,1,1,1,2,3,1,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +36882,115851,Male,Loyal Customer,56,Business travel,Eco,342,3,1,1,1,3,3,3,3,2,2,4,1,4,3,57,53.0,neutral or dissatisfied +36883,11334,Female,Loyal Customer,69,Personal Travel,Eco,308,3,5,3,2,2,5,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +36884,18485,Male,Loyal Customer,54,Business travel,Business,2497,5,5,5,5,4,5,5,5,5,5,5,5,5,5,0,6.0,satisfied +36885,102405,Female,Loyal Customer,34,Personal Travel,Eco,258,3,5,3,5,3,3,3,3,5,5,2,1,2,3,0,0.0,neutral or dissatisfied +36886,87991,Female,Loyal Customer,46,Business travel,Business,581,3,3,3,3,5,5,5,5,5,5,5,4,5,5,19,29.0,satisfied +36887,102103,Male,Loyal Customer,66,Business travel,Business,414,2,2,2,2,5,5,4,4,4,4,4,3,4,5,31,9.0,satisfied +36888,51099,Female,Loyal Customer,34,Personal Travel,Eco,373,2,5,2,3,1,2,1,1,3,4,1,3,2,1,4,24.0,neutral or dissatisfied +36889,105525,Male,Loyal Customer,31,Business travel,Business,611,2,2,2,2,4,4,4,4,3,4,5,5,4,4,8,14.0,satisfied +36890,43435,Male,Loyal Customer,33,Business travel,Business,3616,4,4,4,4,2,2,2,2,3,2,4,4,5,2,8,40.0,satisfied +36891,5629,Female,Loyal Customer,27,Business travel,Business,2042,1,1,1,1,4,4,4,4,4,5,4,3,4,4,31,18.0,satisfied +36892,129161,Male,Loyal Customer,32,Business travel,Eco,954,4,5,5,5,4,4,4,4,2,3,1,5,3,4,0,0.0,satisfied +36893,35766,Male,Loyal Customer,55,Business travel,Business,2495,0,3,0,5,2,3,1,4,4,4,1,3,4,4,0,0.0,satisfied +36894,32372,Male,Loyal Customer,59,Business travel,Eco,163,5,2,2,2,4,5,4,4,5,1,1,2,1,4,1,2.0,satisfied +36895,121728,Male,Loyal Customer,20,Business travel,Business,1475,3,3,3,3,4,4,4,4,4,2,5,3,4,4,0,13.0,satisfied +36896,67000,Female,disloyal Customer,49,Business travel,Business,964,5,5,5,5,5,5,5,5,5,4,5,5,4,5,0,0.0,satisfied +36897,43436,Female,disloyal Customer,40,Business travel,Business,752,4,4,4,2,1,4,5,1,4,2,4,3,5,1,19,29.0,neutral or dissatisfied +36898,96177,Male,Loyal Customer,54,Business travel,Business,3410,4,4,4,4,3,5,5,5,5,5,5,3,5,5,57,48.0,satisfied +36899,95725,Female,disloyal Customer,24,Business travel,Business,181,2,1,3,4,3,3,3,3,3,4,4,2,4,3,16,13.0,neutral or dissatisfied +36900,47965,Male,Loyal Customer,37,Personal Travel,Eco,451,3,5,1,3,4,1,4,4,1,3,4,1,2,4,31,27.0,neutral or dissatisfied +36901,17501,Female,disloyal Customer,26,Business travel,Eco,352,2,0,2,2,2,2,2,2,4,2,5,4,3,2,0,0.0,neutral or dissatisfied +36902,83719,Female,Loyal Customer,29,Personal Travel,Eco Plus,577,1,5,0,1,3,0,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +36903,115862,Male,Loyal Customer,37,Business travel,Business,308,3,3,3,3,3,4,1,4,4,4,4,1,4,2,0,0.0,satisfied +36904,74298,Female,Loyal Customer,41,Business travel,Business,2288,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +36905,56697,Male,Loyal Customer,30,Personal Travel,Eco,937,3,5,3,5,3,2,1,2,3,2,1,1,2,1,123,164.0,neutral or dissatisfied +36906,56876,Female,disloyal Customer,23,Business travel,Eco,2454,2,2,2,3,2,4,4,1,5,2,3,4,4,4,0,33.0,neutral or dissatisfied +36907,79168,Female,Loyal Customer,31,Personal Travel,Business,2422,2,5,2,3,2,5,5,3,2,5,4,5,4,5,3,0.0,neutral or dissatisfied +36908,128632,Female,Loyal Customer,44,Personal Travel,Eco,954,2,2,2,3,4,3,3,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +36909,102659,Male,Loyal Customer,50,Business travel,Business,3589,3,4,3,4,5,4,3,3,3,3,3,3,3,2,58,53.0,neutral or dissatisfied +36910,113198,Male,disloyal Customer,24,Business travel,Eco,197,3,5,4,4,3,4,5,3,5,4,5,3,5,3,4,4.0,neutral or dissatisfied +36911,57848,Male,Loyal Customer,22,Business travel,Business,2329,2,2,5,2,4,4,4,4,5,3,3,5,4,4,0,0.0,satisfied +36912,20053,Male,disloyal Customer,23,Business travel,Eco,528,4,2,4,1,4,4,4,4,3,5,2,3,2,4,31,38.0,satisfied +36913,33644,Male,Loyal Customer,61,Personal Travel,Eco,399,2,5,2,3,4,2,4,4,5,4,5,5,5,4,0,20.0,neutral or dissatisfied +36914,15822,Male,Loyal Customer,23,Business travel,Eco Plus,246,2,4,4,4,2,2,4,2,4,5,3,4,4,2,10,8.0,neutral or dissatisfied +36915,57610,Female,Loyal Customer,15,Personal Travel,Business,200,4,3,4,1,1,4,1,1,3,1,1,3,3,1,3,0.0,satisfied +36916,28651,Female,Loyal Customer,41,Personal Travel,Eco,2404,0,4,0,4,2,0,2,2,1,2,3,4,4,2,0,0.0,satisfied +36917,67636,Female,Loyal Customer,45,Business travel,Business,2103,5,5,4,5,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +36918,86229,Female,disloyal Customer,23,Business travel,Eco,356,4,0,4,1,4,4,2,4,4,2,5,4,3,4,0,0.0,satisfied +36919,21077,Male,Loyal Customer,25,Business travel,Business,3449,4,4,2,4,4,4,4,4,4,4,4,3,3,4,0,0.0,satisfied +36920,91288,Male,Loyal Customer,56,Business travel,Business,406,4,4,4,4,2,4,4,4,4,5,4,5,4,3,19,4.0,satisfied +36921,60745,Female,disloyal Customer,48,Business travel,Business,628,2,2,2,3,4,2,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +36922,75010,Male,Loyal Customer,36,Business travel,Business,3745,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +36923,119755,Female,Loyal Customer,62,Personal Travel,Eco,1430,3,2,4,4,3,4,4,2,2,4,2,1,2,3,0,0.0,neutral or dissatisfied +36924,58643,Female,Loyal Customer,50,Business travel,Eco,867,3,4,4,4,5,4,3,3,3,3,3,1,3,3,3,3.0,neutral or dissatisfied +36925,53561,Female,Loyal Customer,39,Business travel,Business,3145,3,3,3,3,5,2,1,4,4,4,4,2,4,2,1,0.0,satisfied +36926,113993,Female,Loyal Customer,57,Business travel,Business,3355,4,4,4,4,3,2,5,4,4,4,4,2,4,3,1,0.0,satisfied +36927,15899,Male,Loyal Customer,7,Personal Travel,Eco,378,4,1,1,4,4,1,4,4,1,5,3,4,4,4,6,0.0,satisfied +36928,77381,Male,disloyal Customer,36,Business travel,Business,588,1,1,1,4,1,1,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +36929,84046,Female,Loyal Customer,33,Business travel,Business,757,5,5,5,5,2,4,5,4,4,4,4,3,4,3,4,2.0,satisfied +36930,77524,Female,Loyal Customer,58,Business travel,Business,2025,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +36931,78123,Female,disloyal Customer,34,Business travel,Business,1797,1,1,1,3,5,1,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +36932,70148,Female,Loyal Customer,58,Personal Travel,Eco,550,2,0,2,2,2,5,4,1,1,2,1,5,1,5,4,0.0,neutral or dissatisfied +36933,101531,Male,Loyal Customer,36,Personal Travel,Eco,345,3,4,3,4,4,3,4,4,5,2,5,3,5,4,54,57.0,neutral or dissatisfied +36934,92223,Female,Loyal Customer,24,Personal Travel,Eco,2079,1,3,1,3,5,1,5,5,4,4,2,1,4,5,5,0.0,neutral or dissatisfied +36935,121754,Male,Loyal Customer,49,Business travel,Business,366,1,1,1,1,4,4,4,3,3,3,3,3,3,4,89,72.0,satisfied +36936,121076,Female,Loyal Customer,15,Business travel,Eco Plus,920,4,5,5,5,4,1,4,3,1,3,3,4,3,4,169,173.0,neutral or dissatisfied +36937,54671,Female,Loyal Customer,47,Business travel,Eco,964,4,5,3,5,1,3,3,4,4,4,4,4,4,1,1,0.0,neutral or dissatisfied +36938,63887,Female,disloyal Customer,39,Business travel,Business,1172,3,3,3,4,2,3,2,2,2,2,4,2,4,2,30,31.0,neutral or dissatisfied +36939,43710,Male,Loyal Customer,36,Personal Travel,Eco,489,5,3,5,4,3,5,3,3,3,1,4,1,4,3,0,3.0,satisfied +36940,30531,Male,Loyal Customer,59,Business travel,Business,683,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,5.0,satisfied +36941,113203,Male,Loyal Customer,47,Business travel,Business,236,0,0,0,2,2,4,4,3,3,3,3,4,3,3,6,3.0,satisfied +36942,49372,Male,Loyal Customer,40,Business travel,Business,2079,0,5,0,3,4,2,4,2,2,2,2,5,2,5,0,0.0,satisfied +36943,32220,Male,Loyal Customer,25,Business travel,Business,3619,0,3,0,1,3,3,3,3,2,4,1,1,2,3,0,0.0,satisfied +36944,41073,Female,disloyal Customer,77,Business travel,Eco,224,5,0,5,3,2,5,3,2,1,1,4,1,3,2,0,13.0,satisfied +36945,107551,Male,disloyal Customer,23,Business travel,Eco,1521,2,2,2,4,1,2,1,1,4,4,4,1,4,1,22,53.0,neutral or dissatisfied +36946,124787,Female,Loyal Customer,37,Business travel,Business,280,5,5,5,5,2,4,5,5,5,5,5,5,5,3,0,30.0,satisfied +36947,95349,Female,Loyal Customer,8,Personal Travel,Eco,562,2,5,3,2,4,3,4,4,3,4,4,1,5,4,0,0.0,neutral or dissatisfied +36948,106575,Female,Loyal Customer,41,Business travel,Business,1506,5,5,5,5,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +36949,14012,Female,Loyal Customer,35,Business travel,Eco,182,4,3,3,3,4,4,4,4,3,2,4,3,2,4,0,0.0,satisfied +36950,16249,Male,disloyal Customer,25,Business travel,Eco,748,2,2,2,1,3,2,3,3,1,3,5,2,5,3,100,88.0,neutral or dissatisfied +36951,50944,Female,Loyal Customer,34,Personal Travel,Eco,86,2,5,0,3,2,0,3,2,1,3,3,5,1,2,0,0.0,neutral or dissatisfied +36952,36977,Male,Loyal Customer,59,Business travel,Eco,814,4,1,1,1,4,4,4,4,4,4,3,4,2,4,27,18.0,neutral or dissatisfied +36953,89241,Female,Loyal Customer,49,Business travel,Eco Plus,447,1,2,2,2,5,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +36954,38644,Female,Loyal Customer,40,Business travel,Business,2611,1,1,4,1,1,1,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +36955,82943,Female,Loyal Customer,28,Business travel,Business,1127,2,2,2,2,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +36956,17572,Female,disloyal Customer,43,Business travel,Eco,1034,2,2,2,2,1,2,1,1,4,1,3,4,2,1,7,0.0,neutral or dissatisfied +36957,52814,Female,disloyal Customer,34,Business travel,Eco,1126,1,1,1,4,4,1,4,4,2,1,2,1,4,4,0,18.0,neutral or dissatisfied +36958,46815,Female,Loyal Customer,27,Business travel,Business,1671,1,1,1,1,4,4,4,4,3,1,4,5,2,4,45,45.0,satisfied +36959,122080,Male,Loyal Customer,26,Personal Travel,Eco,130,1,3,1,4,4,1,4,4,3,4,2,3,4,4,34,99.0,neutral or dissatisfied +36960,128675,Male,Loyal Customer,41,Business travel,Business,2419,4,4,4,4,5,5,5,3,5,3,5,5,3,5,0,0.0,satisfied +36961,51207,Male,Loyal Customer,36,Business travel,Eco Plus,209,4,1,4,1,4,4,4,4,2,5,3,2,2,4,0,0.0,satisfied +36962,33339,Female,disloyal Customer,26,Business travel,Eco,2349,1,2,2,1,4,1,4,4,4,2,4,2,2,4,0,0.0,neutral or dissatisfied +36963,60810,Female,disloyal Customer,27,Business travel,Business,455,3,3,3,2,3,3,3,5,4,5,4,3,5,3,161,200.0,neutral or dissatisfied +36964,5785,Male,Loyal Customer,48,Business travel,Business,2768,0,5,0,4,4,4,4,2,2,2,2,4,2,4,29,35.0,satisfied +36965,76050,Male,Loyal Customer,53,Business travel,Business,669,2,2,2,2,5,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +36966,51762,Male,Loyal Customer,31,Personal Travel,Eco,493,1,4,1,1,2,1,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +36967,75144,Male,Loyal Customer,56,Business travel,Business,1744,1,1,2,1,4,3,3,3,5,3,4,3,4,3,197,174.0,satisfied +36968,38480,Female,Loyal Customer,39,Personal Travel,Eco,846,1,5,1,1,1,1,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +36969,19961,Female,Loyal Customer,70,Personal Travel,Eco Plus,315,3,5,3,3,4,5,4,2,2,3,2,3,2,3,96,89.0,neutral or dissatisfied +36970,101313,Female,disloyal Customer,20,Business travel,Eco,986,2,2,2,4,3,2,3,3,3,4,4,3,5,3,77,67.0,neutral or dissatisfied +36971,17935,Male,Loyal Customer,51,Business travel,Business,95,5,5,5,5,1,2,5,5,5,5,5,1,5,5,0,0.0,satisfied +36972,13634,Male,Loyal Customer,18,Personal Travel,Eco,1162,4,4,3,4,4,3,4,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +36973,114489,Male,disloyal Customer,39,Business travel,Business,446,1,1,1,4,3,1,3,3,1,4,4,4,3,3,2,0.0,neutral or dissatisfied +36974,55298,Female,disloyal Customer,28,Business travel,Eco Plus,1585,1,1,1,3,2,1,5,2,1,5,4,1,3,2,5,3.0,neutral or dissatisfied +36975,33315,Male,Loyal Customer,21,Personal Travel,Business,2614,4,3,4,2,1,4,1,1,3,4,3,3,2,1,0,0.0,satisfied +36976,382,Female,Loyal Customer,46,Business travel,Business,1987,3,3,3,3,3,4,4,4,4,4,4,5,4,3,70,66.0,satisfied +36977,87744,Female,Loyal Customer,56,Business travel,Business,214,2,2,2,2,5,5,5,5,5,5,4,4,5,3,43,32.0,satisfied +36978,12619,Female,Loyal Customer,18,Personal Travel,Eco,802,2,5,2,5,2,2,2,2,2,1,2,5,5,2,15,5.0,neutral or dissatisfied +36979,35697,Female,Loyal Customer,12,Personal Travel,Eco,2475,2,1,2,3,2,3,3,2,4,1,2,3,1,3,0,0.0,neutral or dissatisfied +36980,1816,Female,disloyal Customer,18,Business travel,Business,500,0,0,0,4,4,0,4,4,3,3,5,3,4,4,0,0.0,satisfied +36981,29543,Female,Loyal Customer,24,Business travel,Business,1533,4,4,4,4,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +36982,94070,Female,disloyal Customer,41,Business travel,Business,323,2,2,2,3,2,2,4,2,2,2,3,3,4,2,18,7.0,neutral or dissatisfied +36983,110563,Female,Loyal Customer,58,Business travel,Business,1634,2,2,2,2,2,4,4,4,4,4,4,3,4,5,2,3.0,satisfied +36984,46100,Male,disloyal Customer,38,Business travel,Business,1201,3,3,3,4,4,3,4,4,4,3,4,3,5,4,10,0.0,neutral or dissatisfied +36985,52677,Female,Loyal Customer,68,Personal Travel,Eco,160,1,4,1,5,5,5,5,3,3,1,1,3,3,5,0,0.0,neutral or dissatisfied +36986,48826,Male,Loyal Customer,65,Personal Travel,Business,86,1,5,1,3,1,4,3,2,2,1,2,2,2,4,114,120.0,neutral or dissatisfied +36987,94253,Male,disloyal Customer,24,Business travel,Business,441,0,0,0,5,5,0,5,5,5,3,4,4,4,5,5,0.0,satisfied +36988,71225,Female,Loyal Customer,27,Business travel,Business,3320,2,1,1,1,2,2,2,2,2,4,2,2,2,2,0,0.0,neutral or dissatisfied +36989,52963,Female,Loyal Customer,41,Business travel,Business,2306,3,1,1,1,1,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +36990,29411,Female,Loyal Customer,60,Personal Travel,Eco,2614,4,2,4,4,4,2,2,1,4,4,3,2,1,2,0,11.0,neutral or dissatisfied +36991,86444,Female,Loyal Customer,26,Business travel,Eco,762,2,2,2,2,2,2,1,2,3,5,4,3,3,2,0,0.0,neutral or dissatisfied +36992,89491,Female,Loyal Customer,56,Personal Travel,Eco,1931,3,3,3,3,5,2,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +36993,111436,Male,Loyal Customer,49,Business travel,Business,836,1,1,1,1,3,5,4,4,4,4,4,5,4,5,15,8.0,satisfied +36994,74452,Male,Loyal Customer,32,Business travel,Business,1235,3,3,4,3,5,5,5,5,4,3,5,5,5,5,42,17.0,satisfied +36995,7375,Male,Loyal Customer,48,Business travel,Business,888,3,3,3,3,4,3,4,3,3,3,3,3,3,3,33,25.0,neutral or dissatisfied +36996,43669,Female,Loyal Customer,55,Business travel,Eco,700,1,4,4,4,4,3,4,1,1,1,1,3,1,3,0,3.0,neutral or dissatisfied +36997,38287,Female,disloyal Customer,22,Business travel,Eco Plus,1180,3,4,3,4,1,3,1,1,2,2,3,1,4,1,0,0.0,neutral or dissatisfied +36998,70441,Female,disloyal Customer,26,Business travel,Business,187,2,2,2,4,3,2,3,3,5,2,5,3,4,3,0,2.0,neutral or dissatisfied +36999,33660,Male,Loyal Customer,30,Business travel,Eco Plus,399,5,5,5,5,5,5,5,5,2,3,5,2,3,5,0,0.0,satisfied +37000,118454,Male,disloyal Customer,25,Business travel,Business,325,2,0,2,3,3,2,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +37001,19271,Female,disloyal Customer,23,Business travel,Eco,430,3,5,3,5,4,3,4,4,3,5,1,2,3,4,0,0.0,neutral or dissatisfied +37002,1168,Male,Loyal Customer,31,Personal Travel,Eco,134,3,3,3,2,2,3,3,2,4,1,3,4,3,2,0,1.0,neutral or dissatisfied +37003,115807,Female,Loyal Customer,28,Business travel,Business,2654,2,5,5,5,2,2,2,2,1,3,3,4,4,2,13,14.0,neutral or dissatisfied +37004,78556,Female,Loyal Customer,31,Business travel,Eco Plus,666,3,2,2,2,3,3,3,4,1,4,4,3,2,3,91,155.0,neutral or dissatisfied +37005,1255,Female,Loyal Customer,61,Personal Travel,Eco,282,1,4,1,5,2,3,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +37006,44534,Female,Loyal Customer,56,Business travel,Business,157,4,1,1,1,3,4,3,4,4,4,4,2,4,2,0,8.0,neutral or dissatisfied +37007,72844,Female,Loyal Customer,39,Business travel,Business,3740,1,1,2,1,5,4,4,5,5,5,5,5,5,3,25,7.0,satisfied +37008,36882,Female,Loyal Customer,43,Business travel,Business,1529,4,4,4,4,4,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +37009,78025,Male,Loyal Customer,48,Business travel,Business,214,0,5,0,4,2,1,3,3,3,3,3,3,3,1,0,0.0,satisfied +37010,8175,Female,disloyal Customer,22,Business travel,Business,294,5,0,5,3,2,5,2,2,5,4,5,3,5,2,0,0.0,satisfied +37011,78559,Male,Loyal Customer,51,Personal Travel,Eco Plus,666,2,3,2,4,1,2,1,1,4,1,4,2,3,1,20,28.0,neutral or dissatisfied +37012,95381,Female,Loyal Customer,15,Personal Travel,Eco,192,4,5,0,4,5,0,1,5,5,5,4,4,5,5,0,11.0,neutral or dissatisfied +37013,59057,Male,disloyal Customer,22,Business travel,Eco,1846,2,2,2,4,1,2,1,1,3,4,4,3,4,1,8,0.0,neutral or dissatisfied +37014,57112,Male,Loyal Customer,41,Business travel,Eco,1222,2,5,1,1,2,2,2,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +37015,41297,Female,Loyal Customer,69,Personal Travel,Eco,844,3,4,3,3,3,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +37016,96723,Female,Loyal Customer,45,Personal Travel,Eco,696,2,5,2,1,3,4,5,3,3,2,3,4,3,5,53,42.0,neutral or dissatisfied +37017,64415,Female,Loyal Customer,40,Personal Travel,Eco Plus,1212,3,5,4,4,4,4,4,4,4,3,4,1,5,4,10,4.0,neutral or dissatisfied +37018,20796,Female,Loyal Customer,37,Business travel,Business,3719,2,2,2,2,4,2,3,4,4,5,4,4,4,2,0,0.0,satisfied +37019,125057,Female,Loyal Customer,69,Personal Travel,Business,90,3,3,3,3,3,1,2,3,3,3,3,1,3,2,0,25.0,neutral or dissatisfied +37020,93734,Female,Loyal Customer,53,Business travel,Business,2711,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +37021,64799,Male,Loyal Customer,43,Business travel,Business,3577,2,2,2,2,3,4,5,4,4,4,4,5,4,4,5,0.0,satisfied +37022,119282,Female,Loyal Customer,59,Business travel,Business,3427,1,1,1,1,4,5,4,5,5,5,5,5,5,3,66,55.0,satisfied +37023,85410,Male,disloyal Customer,44,Business travel,Business,152,4,3,3,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +37024,30239,Female,disloyal Customer,37,Business travel,Eco,496,4,2,4,4,2,4,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +37025,64025,Female,Loyal Customer,45,Business travel,Business,919,2,2,2,2,3,4,5,5,5,5,5,3,5,3,0,7.0,satisfied +37026,78884,Female,Loyal Customer,38,Personal Travel,Eco Plus,449,3,5,3,1,2,3,2,2,4,3,4,5,4,2,67,45.0,neutral or dissatisfied +37027,36040,Female,disloyal Customer,38,Business travel,Eco,399,3,0,3,3,2,3,2,2,1,2,1,2,3,2,0,0.0,neutral or dissatisfied +37028,97927,Male,Loyal Customer,44,Business travel,Business,655,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +37029,47221,Female,Loyal Customer,23,Personal Travel,Eco,748,3,4,3,4,4,3,4,4,3,2,4,2,3,4,10,0.0,neutral or dissatisfied +37030,123672,Female,Loyal Customer,49,Business travel,Business,214,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +37031,55011,Male,Loyal Customer,40,Business travel,Business,1379,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,29.0,satisfied +37032,120777,Female,Loyal Customer,57,Personal Travel,Eco,678,1,4,1,3,5,4,4,2,2,1,3,3,2,4,18,13.0,neutral or dissatisfied +37033,121638,Male,Loyal Customer,11,Business travel,Eco Plus,936,3,1,1,1,3,3,2,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +37034,4289,Male,Loyal Customer,44,Personal Travel,Eco,502,4,4,4,1,5,4,4,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +37035,14606,Female,Loyal Customer,49,Business travel,Business,3260,1,1,1,1,5,3,2,3,3,4,3,1,3,4,0,18.0,satisfied +37036,120568,Male,Loyal Customer,59,Personal Travel,Eco,2176,3,1,3,3,2,3,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +37037,125242,Male,Loyal Customer,38,Personal Travel,Eco,1149,1,4,1,1,5,1,5,5,3,4,4,5,5,5,0,17.0,neutral or dissatisfied +37038,116503,Male,Loyal Customer,27,Personal Travel,Eco,358,2,4,2,1,1,2,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +37039,44979,Male,Loyal Customer,44,Business travel,Business,2892,3,3,3,3,3,1,2,5,5,5,4,2,5,4,0,0.0,satisfied +37040,68282,Male,Loyal Customer,28,Personal Travel,Eco Plus,432,3,1,5,1,5,5,5,5,4,3,1,1,1,5,0,0.0,neutral or dissatisfied +37041,12265,Male,Loyal Customer,49,Business travel,Eco,201,4,5,5,5,4,4,4,4,2,2,3,4,5,4,0,0.0,satisfied +37042,103898,Female,Loyal Customer,52,Business travel,Eco Plus,882,3,4,4,4,3,2,3,4,4,3,4,2,4,2,0,8.0,neutral or dissatisfied +37043,100481,Male,disloyal Customer,20,Business travel,Eco,759,3,3,3,3,2,3,2,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +37044,39567,Female,disloyal Customer,20,Business travel,Eco,954,4,4,4,4,5,4,5,5,3,4,3,5,1,5,37,21.0,neutral or dissatisfied +37045,5801,Female,Loyal Customer,31,Business travel,Eco,177,1,2,2,2,1,1,1,1,4,2,2,3,2,1,0,8.0,neutral or dissatisfied +37046,64009,Male,Loyal Customer,24,Business travel,Business,2079,2,2,2,2,3,4,3,3,4,5,5,3,4,3,0,0.0,satisfied +37047,36672,Male,Loyal Customer,48,Personal Travel,Eco,1091,1,1,1,3,3,1,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +37048,57882,Male,disloyal Customer,34,Business travel,Business,305,3,3,3,3,1,3,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +37049,107679,Male,Loyal Customer,46,Business travel,Business,3291,5,5,5,5,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +37050,65181,Female,Loyal Customer,15,Personal Travel,Eco,354,3,4,3,1,2,3,2,2,5,2,5,5,5,2,47,43.0,neutral or dissatisfied +37051,92618,Female,Loyal Customer,44,Business travel,Business,1781,5,5,5,5,2,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +37052,113751,Female,Loyal Customer,23,Personal Travel,Eco,397,1,5,1,3,4,1,4,4,5,3,5,4,4,4,56,42.0,neutral or dissatisfied +37053,69086,Male,Loyal Customer,16,Personal Travel,Eco,1389,3,4,3,3,1,3,4,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +37054,116613,Female,disloyal Customer,38,Business travel,Business,358,4,4,4,1,5,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +37055,58138,Female,Loyal Customer,54,Business travel,Business,925,4,4,4,4,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +37056,78081,Female,Loyal Customer,53,Business travel,Eco Plus,332,2,3,3,3,1,4,3,1,1,2,1,2,1,1,85,92.0,neutral or dissatisfied +37057,124950,Female,Loyal Customer,30,Business travel,Eco Plus,728,3,2,2,2,3,3,3,3,3,4,3,1,4,3,3,15.0,neutral or dissatisfied +37058,101689,Female,Loyal Customer,31,Business travel,Business,1500,5,5,5,5,5,4,5,5,5,2,5,4,4,5,0,0.0,satisfied +37059,105082,Male,Loyal Customer,42,Business travel,Business,3944,3,3,3,3,5,4,4,4,4,4,4,5,4,3,5,0.0,satisfied +37060,109705,Female,Loyal Customer,51,Business travel,Business,587,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +37061,89706,Male,Loyal Customer,20,Personal Travel,Eco,1076,2,5,2,4,5,2,3,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +37062,39461,Female,Loyal Customer,19,Personal Travel,Eco,129,4,5,4,3,3,4,5,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +37063,60924,Male,Loyal Customer,52,Business travel,Business,3728,4,4,2,4,2,5,4,4,4,4,4,3,4,5,0,20.0,satisfied +37064,45609,Female,Loyal Customer,53,Business travel,Eco,313,4,1,1,1,2,5,1,4,4,4,4,2,4,2,0,16.0,satisfied +37065,112560,Female,Loyal Customer,46,Personal Travel,Eco Plus,957,3,4,3,3,1,4,4,4,4,3,4,4,4,3,22,7.0,neutral or dissatisfied +37066,41781,Female,Loyal Customer,20,Personal Travel,Eco,508,1,4,1,2,4,1,3,4,5,3,5,3,5,4,8,7.0,neutral or dissatisfied +37067,28691,Male,Loyal Customer,30,Business travel,Business,2182,5,5,2,5,5,5,5,5,5,5,4,1,2,5,47,88.0,satisfied +37068,53503,Male,Loyal Customer,59,Personal Travel,Eco,2288,3,3,3,4,2,3,5,2,2,1,4,1,3,2,0,0.0,neutral or dissatisfied +37069,116286,Male,Loyal Customer,30,Personal Travel,Eco,337,1,5,1,3,2,1,2,2,5,4,2,1,3,2,3,0.0,neutral or dissatisfied +37070,103503,Female,Loyal Customer,49,Business travel,Business,1779,5,5,5,5,5,5,4,5,5,5,5,4,5,3,5,0.0,satisfied +37071,98578,Male,Loyal Customer,49,Business travel,Business,834,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +37072,95623,Female,Loyal Customer,21,Personal Travel,Eco,756,3,4,3,4,2,3,2,2,5,5,4,4,5,2,11,6.0,neutral or dissatisfied +37073,10850,Male,disloyal Customer,37,Business travel,Business,224,3,3,3,3,5,3,5,5,1,5,3,3,3,5,40,48.0,neutral or dissatisfied +37074,62121,Male,Loyal Customer,51,Business travel,Business,2454,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +37075,122727,Male,Loyal Customer,46,Business travel,Business,651,2,2,2,2,2,5,4,5,5,5,5,5,5,4,1,8.0,satisfied +37076,95834,Male,Loyal Customer,47,Business travel,Business,580,5,5,5,5,2,4,4,4,4,4,4,5,4,5,3,0.0,satisfied +37077,34027,Male,Loyal Customer,41,Personal Travel,Eco,1598,2,3,2,3,4,2,4,4,3,5,2,3,4,4,32,9.0,neutral or dissatisfied +37078,52727,Male,Loyal Customer,11,Personal Travel,Eco,406,2,4,2,5,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +37079,32822,Female,Loyal Customer,61,Business travel,Business,2535,1,1,1,1,5,3,5,4,4,4,5,3,4,1,0,2.0,satisfied +37080,5345,Male,Loyal Customer,60,Business travel,Business,2916,4,3,3,3,2,3,3,4,4,4,4,2,4,3,0,7.0,neutral or dissatisfied +37081,72330,Female,Loyal Customer,26,Business travel,Business,2454,5,5,5,5,4,4,4,4,3,2,5,5,4,4,0,2.0,satisfied +37082,102492,Female,Loyal Customer,41,Personal Travel,Eco,386,4,4,4,3,1,4,4,1,5,5,4,3,4,1,13,3.0,neutral or dissatisfied +37083,13435,Male,Loyal Customer,39,Business travel,Business,3854,1,4,4,4,3,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +37084,85991,Male,disloyal Customer,24,Business travel,Eco,554,2,5,2,1,3,2,3,3,3,2,5,3,4,3,25,32.0,neutral or dissatisfied +37085,93024,Female,Loyal Customer,7,Personal Travel,Eco,1524,2,3,3,4,2,3,2,2,4,3,4,4,4,2,48,46.0,neutral or dissatisfied +37086,119025,Male,disloyal Customer,22,Business travel,Eco,1060,5,5,5,3,2,5,2,2,2,4,5,1,2,2,0,0.0,satisfied +37087,62368,Female,Loyal Customer,54,Business travel,Business,2704,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +37088,59536,Male,Loyal Customer,44,Business travel,Business,964,4,4,4,4,5,5,4,4,4,4,4,5,4,5,4,12.0,satisfied +37089,114125,Female,disloyal Customer,27,Business travel,Business,967,5,4,4,4,4,4,4,4,3,5,4,4,5,4,35,25.0,satisfied +37090,99580,Female,Loyal Customer,33,Business travel,Business,2831,4,5,5,5,2,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +37091,109790,Female,Loyal Customer,56,Business travel,Business,2259,3,3,3,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +37092,86394,Female,disloyal Customer,49,Business travel,Business,762,3,4,4,3,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +37093,99648,Male,Loyal Customer,33,Business travel,Business,1670,5,5,5,5,4,4,4,4,1,3,4,4,1,4,0,0.0,satisfied +37094,13516,Female,Loyal Customer,52,Business travel,Business,3227,2,2,2,2,2,4,1,5,5,5,5,2,5,1,0,0.0,satisfied +37095,40477,Female,Loyal Customer,21,Business travel,Business,222,2,5,5,5,1,1,2,1,1,1,2,4,1,1,0,,neutral or dissatisfied +37096,78292,Male,Loyal Customer,23,Business travel,Eco,998,5,2,2,2,5,5,5,1,1,2,4,5,1,5,750,729.0,satisfied +37097,25232,Male,Loyal Customer,29,Personal Travel,Eco,925,5,5,5,2,2,5,2,2,3,2,5,3,4,2,0,0.0,satisfied +37098,17601,Male,Loyal Customer,62,Personal Travel,Eco Plus,695,4,4,4,3,1,4,1,1,4,1,3,3,5,1,0,0.0,neutral or dissatisfied +37099,86358,Male,Loyal Customer,40,Business travel,Business,3454,3,3,3,3,2,4,4,4,4,4,4,3,4,3,20,0.0,satisfied +37100,79395,Male,Loyal Customer,15,Business travel,Business,1783,2,2,2,2,5,5,5,5,3,2,4,4,4,5,0,0.0,satisfied +37101,60731,Female,Loyal Customer,54,Personal Travel,Eco,1605,5,2,5,3,4,2,3,4,4,5,3,3,4,2,2,0.0,satisfied +37102,39620,Male,Loyal Customer,24,Personal Travel,Eco,679,1,4,1,3,1,1,1,1,3,4,4,4,5,1,14,12.0,neutral or dissatisfied +37103,77016,Female,disloyal Customer,44,Business travel,Business,422,2,3,3,1,1,2,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +37104,107784,Female,disloyal Customer,24,Business travel,Eco,666,1,3,1,4,2,1,2,2,1,2,4,4,4,2,3,0.0,neutral or dissatisfied +37105,18986,Female,disloyal Customer,44,Business travel,Eco,388,3,1,3,4,3,3,2,3,4,3,4,1,3,3,84,77.0,neutral or dissatisfied +37106,96498,Female,Loyal Customer,68,Business travel,Eco,302,2,1,1,1,5,4,3,2,2,2,2,2,2,3,26,26.0,neutral or dissatisfied +37107,124069,Male,Loyal Customer,24,Personal Travel,Eco,2153,2,5,2,2,2,2,3,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +37108,84887,Male,Loyal Customer,67,Personal Travel,Eco,547,2,4,2,5,2,4,5,4,4,4,5,5,3,5,133,120.0,neutral or dissatisfied +37109,40106,Female,Loyal Customer,42,Business travel,Business,422,2,2,2,2,5,5,3,5,5,4,5,3,5,3,0,0.0,satisfied +37110,50753,Female,Loyal Customer,61,Personal Travel,Eco,78,2,4,2,4,2,4,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +37111,20611,Male,Loyal Customer,42,Business travel,Eco,794,3,4,4,4,3,3,3,3,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +37112,115513,Male,Loyal Customer,53,Business travel,Business,447,1,1,1,1,3,5,4,5,5,5,5,5,5,3,29,36.0,satisfied +37113,123830,Female,Loyal Customer,59,Business travel,Business,546,4,4,4,4,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +37114,87927,Male,Loyal Customer,41,Business travel,Business,1768,2,2,2,2,2,4,4,4,4,4,4,5,4,3,5,0.0,satisfied +37115,25580,Male,disloyal Customer,29,Business travel,Eco,696,3,3,3,4,4,3,2,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +37116,100699,Female,Loyal Customer,20,Personal Travel,Eco,677,1,3,1,3,2,1,2,2,3,1,4,4,4,2,20,17.0,neutral or dissatisfied +37117,110637,Male,Loyal Customer,45,Business travel,Business,829,4,4,4,4,2,5,5,5,5,5,5,4,5,5,15,11.0,satisfied +37118,85921,Female,Loyal Customer,24,Personal Travel,Eco,761,1,4,0,2,2,0,5,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +37119,56305,Female,Loyal Customer,34,Personal Travel,Eco Plus,2227,3,1,3,4,1,3,1,1,1,5,4,3,4,1,3,0.0,neutral or dissatisfied +37120,44743,Female,disloyal Customer,37,Business travel,Eco,589,3,5,3,2,3,3,1,3,2,2,4,4,4,3,7,1.0,neutral or dissatisfied +37121,76661,Male,Loyal Customer,14,Personal Travel,Eco,534,4,5,4,4,2,4,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +37122,58228,Female,Loyal Customer,32,Personal Travel,Eco,925,2,5,2,3,5,2,5,5,5,5,5,4,5,5,13,0.0,neutral or dissatisfied +37123,7713,Male,Loyal Customer,38,Personal Travel,Business,806,1,5,1,1,5,4,5,5,5,1,2,1,5,2,25,18.0,neutral or dissatisfied +37124,126394,Male,Loyal Customer,20,Personal Travel,Eco,631,4,4,4,3,1,4,3,1,4,5,3,2,3,1,0,0.0,neutral or dissatisfied +37125,5307,Female,Loyal Customer,66,Personal Travel,Eco,383,2,5,2,3,4,5,5,3,3,2,1,4,3,4,0,0.0,neutral or dissatisfied +37126,11870,Male,Loyal Customer,47,Personal Travel,Eco,912,1,4,2,3,2,2,2,2,3,3,4,3,5,2,62,36.0,neutral or dissatisfied +37127,36393,Female,Loyal Customer,14,Business travel,Business,2381,1,1,2,2,2,1,1,2,3,3,4,1,4,1,44,68.0,neutral or dissatisfied +37128,128989,Male,Loyal Customer,51,Personal Travel,Eco,236,4,5,4,1,5,4,5,5,2,1,1,3,1,5,0,0.0,neutral or dissatisfied +37129,13621,Male,Loyal Customer,34,Business travel,Business,1641,3,3,3,3,2,5,4,3,3,4,3,1,3,5,0,14.0,satisfied +37130,57196,Male,Loyal Customer,15,Personal Travel,Business,1514,1,3,0,3,2,0,2,2,1,3,3,3,2,2,0,0.0,neutral or dissatisfied +37131,49385,Male,Loyal Customer,44,Business travel,Business,2874,2,2,2,2,1,4,3,4,4,4,4,5,4,2,0,0.0,satisfied +37132,30982,Female,Loyal Customer,23,Business travel,Business,1476,4,4,4,4,2,2,2,2,5,1,5,2,5,2,0,0.0,satisfied +37133,111109,Male,Loyal Customer,17,Personal Travel,Eco Plus,240,4,3,4,3,1,4,1,1,4,4,1,1,1,1,66,93.0,neutral or dissatisfied +37134,113596,Male,disloyal Customer,20,Business travel,Eco,226,3,5,3,4,5,3,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +37135,121776,Female,Loyal Customer,32,Business travel,Business,366,1,1,1,1,1,1,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +37136,31279,Male,disloyal Customer,29,Business travel,Eco,533,4,2,4,3,5,4,4,5,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +37137,30789,Female,Loyal Customer,12,Personal Travel,Eco,895,3,4,3,4,1,3,1,1,4,3,5,3,4,1,102,99.0,neutral or dissatisfied +37138,109731,Female,Loyal Customer,85,Business travel,Business,187,2,3,3,3,4,2,4,3,5,4,4,4,1,4,17,11.0,neutral or dissatisfied +37139,101194,Male,Loyal Customer,47,Personal Travel,Eco,1235,2,4,2,4,1,2,5,1,5,4,3,5,4,1,71,67.0,neutral or dissatisfied +37140,73091,Female,Loyal Customer,35,Personal Travel,Eco,1085,2,4,2,5,5,2,5,5,3,1,2,4,4,5,0,0.0,neutral or dissatisfied +37141,21431,Male,Loyal Customer,44,Business travel,Eco,399,5,4,4,4,5,5,5,5,4,3,2,1,4,5,0,0.0,satisfied +37142,14872,Female,disloyal Customer,40,Business travel,Business,240,3,3,3,2,5,3,5,5,4,1,3,3,3,5,0,10.0,neutral or dissatisfied +37143,64615,Male,disloyal Customer,42,Business travel,Business,247,4,4,4,2,2,4,2,2,5,4,5,5,4,2,0,0.0,satisfied +37144,111137,Female,Loyal Customer,27,Business travel,Business,1050,5,2,5,5,5,5,5,5,3,3,4,5,4,5,33,20.0,satisfied +37145,26911,Female,Loyal Customer,25,Business travel,Business,1660,2,2,1,2,2,2,2,2,4,2,3,3,4,2,45,30.0,neutral or dissatisfied +37146,28740,Female,disloyal Customer,28,Business travel,Eco,1024,1,0,0,1,1,0,1,1,3,5,2,2,4,1,0,0.0,neutral or dissatisfied +37147,128605,Male,Loyal Customer,30,Business travel,Business,679,3,3,4,3,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +37148,77134,Female,Loyal Customer,44,Business travel,Business,2105,2,2,2,2,3,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +37149,65156,Female,Loyal Customer,12,Personal Travel,Eco,247,3,2,3,3,4,3,2,4,3,5,3,2,4,4,0,0.0,neutral or dissatisfied +37150,15206,Female,Loyal Customer,41,Business travel,Business,2221,1,1,4,1,3,5,4,5,5,5,5,5,5,3,25,29.0,satisfied +37151,53780,Male,disloyal Customer,23,Business travel,Eco,191,2,0,2,4,5,2,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +37152,21110,Male,Loyal Customer,40,Personal Travel,Eco,227,2,5,2,5,1,2,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +37153,126018,Female,Loyal Customer,40,Business travel,Business,3180,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +37154,114799,Male,Loyal Customer,62,Business travel,Business,1970,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +37155,77085,Male,Loyal Customer,23,Personal Travel,Eco,991,3,5,3,4,4,3,2,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +37156,83018,Male,Loyal Customer,37,Business travel,Business,1084,3,3,1,3,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +37157,115127,Female,Loyal Customer,48,Business travel,Business,1934,2,2,2,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +37158,19146,Male,disloyal Customer,35,Business travel,Business,304,1,1,1,3,3,1,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +37159,102368,Male,Loyal Customer,30,Business travel,Business,236,4,4,4,4,4,4,4,4,1,5,4,3,3,4,58,49.0,neutral or dissatisfied +37160,32484,Female,Loyal Customer,58,Business travel,Eco,102,5,3,4,4,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +37161,43789,Female,Loyal Customer,55,Business travel,Eco Plus,223,1,2,5,5,1,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +37162,97329,Male,Loyal Customer,30,Business travel,Eco,843,2,5,5,5,2,2,2,2,4,3,3,1,3,2,45,27.0,neutral or dissatisfied +37163,118137,Male,Loyal Customer,18,Personal Travel,Eco,1488,3,4,3,4,4,3,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +37164,56630,Female,Loyal Customer,42,Business travel,Business,2695,3,3,3,3,5,5,5,5,5,5,5,3,5,4,0,4.0,satisfied +37165,106031,Male,Loyal Customer,31,Personal Travel,Eco,682,4,3,4,3,1,4,1,1,1,4,3,5,4,1,64,90.0,neutral or dissatisfied +37166,33468,Female,Loyal Customer,66,Personal Travel,Eco Plus,2556,5,3,5,1,1,5,5,4,4,5,4,3,4,1,0,0.0,satisfied +37167,51823,Male,Loyal Customer,55,Business travel,Eco Plus,237,5,4,4,4,4,5,4,4,2,5,5,1,4,4,0,0.0,satisfied +37168,51586,Female,Loyal Customer,44,Business travel,Eco,370,4,1,1,1,3,2,4,4,4,4,4,4,4,2,0,0.0,satisfied +37169,115677,Male,disloyal Customer,24,Business travel,Business,333,4,0,4,3,3,4,3,3,4,4,5,4,5,3,0,4.0,satisfied +37170,84346,Female,disloyal Customer,33,Business travel,Business,606,2,2,2,2,3,2,3,3,4,2,4,4,4,3,7,0.0,neutral or dissatisfied +37171,19927,Female,Loyal Customer,47,Personal Travel,Eco,343,1,5,1,2,4,1,2,4,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +37172,57905,Female,Loyal Customer,51,Business travel,Eco,305,4,4,4,4,1,2,3,3,3,4,3,3,3,2,7,0.0,satisfied +37173,10238,Male,disloyal Customer,20,Business travel,Eco,312,3,4,3,3,1,3,1,1,2,4,4,2,4,1,16,16.0,neutral or dissatisfied +37174,129795,Male,Loyal Customer,25,Personal Travel,Eco,447,3,3,3,2,4,3,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +37175,124099,Female,disloyal Customer,14,Business travel,Eco,529,4,0,4,1,4,4,4,4,4,3,5,3,5,4,31,14.0,satisfied +37176,33506,Male,Loyal Customer,31,Personal Travel,Eco,965,3,4,3,5,3,3,3,5,3,4,4,3,3,3,365,357.0,neutral or dissatisfied +37177,81971,Female,Loyal Customer,62,Business travel,Eco,1576,2,5,2,5,1,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +37178,88393,Male,Loyal Customer,41,Business travel,Business,2284,3,4,4,4,3,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +37179,3092,Male,Loyal Customer,50,Business travel,Business,1949,5,5,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +37180,78208,Male,Loyal Customer,70,Personal Travel,Eco,259,3,5,0,2,4,0,4,4,1,2,3,1,1,4,71,75.0,neutral or dissatisfied +37181,64647,Male,Loyal Customer,39,Business travel,Business,3272,5,2,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +37182,120048,Female,Loyal Customer,63,Personal Travel,Business,356,5,5,4,3,3,5,4,2,2,4,2,5,2,4,0,0.0,satisfied +37183,105298,Male,Loyal Customer,64,Business travel,Business,1875,2,3,3,3,2,4,3,2,2,2,2,1,2,4,4,9.0,neutral or dissatisfied +37184,117849,Male,Loyal Customer,38,Business travel,Eco,2133,4,2,2,2,4,4,4,4,4,1,3,3,4,4,8,6.0,neutral or dissatisfied +37185,19517,Male,Loyal Customer,49,Business travel,Eco Plus,508,3,4,4,4,3,3,3,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +37186,70352,Female,Loyal Customer,44,Business travel,Business,986,5,3,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +37187,9498,Female,disloyal Customer,25,Business travel,Business,239,2,5,3,2,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +37188,126273,Male,Loyal Customer,50,Personal Travel,Eco,590,2,4,1,2,3,1,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +37189,46229,Female,Loyal Customer,36,Business travel,Eco,679,4,4,4,4,4,4,4,4,5,4,1,1,5,4,0,0.0,satisfied +37190,69996,Female,Loyal Customer,14,Personal Travel,Eco,236,2,5,2,3,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +37191,125856,Male,disloyal Customer,30,Business travel,Business,861,2,3,3,3,2,3,2,2,5,2,4,3,4,2,4,0.0,neutral or dissatisfied +37192,19310,Male,Loyal Customer,40,Business travel,Business,694,5,5,5,5,2,5,4,4,4,4,4,5,4,5,13,8.0,satisfied +37193,40924,Female,disloyal Customer,27,Business travel,Eco Plus,501,4,4,4,2,3,4,4,3,1,5,3,4,5,3,0,0.0,neutral or dissatisfied +37194,52765,Male,Loyal Customer,31,Business travel,Eco,1874,5,1,1,1,5,5,5,5,4,4,5,1,2,5,16,11.0,satisfied +37195,36526,Male,disloyal Customer,24,Business travel,Eco,1220,4,4,4,3,2,4,2,2,2,3,5,2,1,2,0,2.0,satisfied +37196,60130,Male,disloyal Customer,25,Business travel,Eco,1144,3,3,3,1,3,3,3,3,5,2,4,5,5,3,3,0.0,neutral or dissatisfied +37197,89700,Male,Loyal Customer,48,Business travel,Eco,669,4,2,2,2,4,4,4,4,4,2,3,1,5,4,0,0.0,satisfied +37198,20470,Female,Loyal Customer,12,Personal Travel,Eco,84,5,1,5,1,3,5,3,3,3,2,2,4,2,3,0,0.0,satisfied +37199,89979,Female,Loyal Customer,41,Business travel,Eco Plus,1310,1,1,1,1,4,4,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +37200,107796,Female,Loyal Customer,34,Business travel,Business,3579,5,5,5,5,2,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +37201,91143,Male,Loyal Customer,29,Personal Travel,Eco,366,1,4,1,5,2,1,2,2,5,5,5,3,5,2,7,5.0,neutral or dissatisfied +37202,5862,Male,Loyal Customer,11,Personal Travel,Eco,1020,3,2,3,4,5,3,1,5,1,2,3,2,4,5,0,7.0,neutral or dissatisfied +37203,46732,Female,Loyal Customer,33,Personal Travel,Eco,125,4,3,4,3,4,4,4,4,4,5,5,3,1,4,0,0.0,neutral or dissatisfied +37204,126088,Female,Loyal Customer,50,Business travel,Business,507,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +37205,14612,Male,Loyal Customer,53,Business travel,Business,1609,3,3,3,3,4,5,5,4,4,5,4,1,4,5,0,0.0,satisfied +37206,85105,Female,Loyal Customer,24,Business travel,Business,731,2,2,2,2,5,5,5,5,4,5,5,3,4,5,0,0.0,satisfied +37207,64233,Female,disloyal Customer,27,Business travel,Business,1660,0,1,1,3,3,1,3,3,3,4,4,4,4,3,0,0.0,satisfied +37208,108183,Male,Loyal Customer,21,Personal Travel,Eco,990,1,1,1,4,5,1,5,5,3,5,3,1,4,5,12,22.0,neutral or dissatisfied +37209,30388,Female,Loyal Customer,30,Business travel,Business,3838,3,1,1,1,3,3,3,3,4,2,3,3,3,3,42,48.0,neutral or dissatisfied +37210,119730,Male,Loyal Customer,51,Business travel,Eco,903,5,2,2,2,5,5,5,5,4,2,1,4,4,5,0,0.0,satisfied +37211,85498,Female,Loyal Customer,26,Personal Travel,Eco,152,2,5,2,1,3,2,3,3,3,4,4,3,4,3,9,10.0,neutral or dissatisfied +37212,15113,Male,Loyal Customer,40,Business travel,Business,3850,1,1,1,1,4,1,2,4,4,4,4,3,4,2,5,5.0,satisfied +37213,119266,Male,Loyal Customer,44,Business travel,Business,3601,2,2,4,2,4,5,5,4,4,4,4,4,4,4,62,65.0,satisfied +37214,82676,Female,Loyal Customer,58,Personal Travel,Business,632,1,5,1,4,2,5,4,4,4,1,2,4,4,4,0,9.0,neutral or dissatisfied +37215,124529,Female,Loyal Customer,32,Business travel,Business,1276,4,4,4,4,5,5,5,5,4,2,4,3,5,5,0,0.0,satisfied +37216,81491,Female,Loyal Customer,48,Personal Travel,Eco,528,3,5,3,1,4,4,5,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +37217,37150,Male,disloyal Customer,25,Business travel,Business,1129,2,3,3,3,2,3,2,2,1,3,4,1,4,2,0,17.0,neutral or dissatisfied +37218,74620,Female,Loyal Customer,15,Business travel,Business,1438,5,5,1,5,4,4,4,4,3,5,2,4,1,4,6,0.0,satisfied +37219,68041,Female,Loyal Customer,23,Business travel,Business,2153,2,2,2,2,4,4,4,4,3,4,5,4,4,4,49,39.0,satisfied +37220,60322,Female,Loyal Customer,43,Business travel,Business,3000,3,3,3,3,3,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +37221,24768,Female,Loyal Customer,36,Business travel,Eco,447,5,3,3,3,5,5,5,5,4,2,2,4,1,5,0,3.0,satisfied +37222,50229,Female,Loyal Customer,57,Business travel,Business,3488,3,3,3,3,3,3,3,2,2,2,3,3,2,2,15,6.0,neutral or dissatisfied +37223,88642,Female,Loyal Customer,50,Personal Travel,Eco,270,1,4,1,2,2,5,5,5,5,1,5,4,5,4,1,0.0,neutral or dissatisfied +37224,61489,Female,disloyal Customer,26,Business travel,Business,954,5,5,5,4,3,5,2,3,5,5,3,3,4,3,0,0.0,satisfied +37225,44922,Male,Loyal Customer,40,Business travel,Eco Plus,416,5,5,5,5,5,5,5,5,4,4,2,3,1,5,0,0.0,satisfied +37226,14861,Male,Loyal Customer,33,Business travel,Eco,315,5,4,4,4,5,5,5,5,2,1,2,5,1,5,32,32.0,satisfied +37227,51834,Male,Loyal Customer,56,Business travel,Eco Plus,370,4,3,3,3,4,4,4,4,4,2,3,3,2,4,0,0.0,neutral or dissatisfied +37228,119284,Male,Loyal Customer,57,Business travel,Business,3167,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +37229,38232,Female,Loyal Customer,20,Personal Travel,Business,1133,4,4,5,3,4,5,4,4,4,4,3,3,5,4,1,0.0,neutral or dissatisfied +37230,64152,Female,Loyal Customer,46,Business travel,Business,989,3,3,3,3,3,5,4,5,5,5,5,3,5,5,72,58.0,satisfied +37231,87268,Male,disloyal Customer,52,Business travel,Eco,577,3,4,2,4,2,2,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +37232,92515,Male,Loyal Customer,55,Personal Travel,Eco,1919,3,5,3,4,3,3,4,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +37233,55107,Male,Loyal Customer,58,Personal Travel,Eco,1346,3,4,3,4,5,3,5,5,1,4,4,1,4,5,16,17.0,neutral or dissatisfied +37234,38915,Male,Loyal Customer,52,Business travel,Business,410,1,3,3,3,1,4,4,1,1,1,1,2,1,1,0,25.0,neutral or dissatisfied +37235,114975,Male,Loyal Customer,29,Business travel,Business,3604,1,1,2,1,2,2,2,2,5,5,5,5,4,2,0,0.0,satisfied +37236,7007,Male,Loyal Customer,76,Business travel,Business,3381,4,2,4,4,4,4,1,4,4,4,4,4,4,3,0,0.0,satisfied +37237,96752,Male,disloyal Customer,23,Business travel,Eco,849,5,5,5,1,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +37238,72698,Female,Loyal Customer,45,Personal Travel,Eco,964,1,5,1,3,2,5,5,4,4,1,1,5,4,5,0,0.0,neutral or dissatisfied +37239,47419,Female,Loyal Customer,42,Business travel,Business,1979,3,5,5,5,3,3,2,3,3,3,3,1,3,3,9,13.0,neutral or dissatisfied +37240,96381,Male,disloyal Customer,22,Business travel,Eco,1407,4,5,5,1,5,4,2,5,4,3,5,5,4,5,0,0.0,satisfied +37241,85532,Female,Loyal Customer,46,Business travel,Business,259,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +37242,52403,Female,Loyal Customer,61,Personal Travel,Eco,237,2,3,2,1,2,5,5,1,1,2,1,2,1,5,6,22.0,neutral or dissatisfied +37243,42566,Male,Loyal Customer,10,Personal Travel,Eco,563,1,3,1,2,5,1,5,5,4,4,2,5,4,5,0,0.0,neutral or dissatisfied +37244,9632,Female,disloyal Customer,20,Business travel,Business,277,0,2,0,3,2,0,3,2,4,2,4,3,5,2,0,10.0,satisfied +37245,53838,Male,Loyal Customer,50,Business travel,Eco,191,5,5,5,5,5,5,5,5,2,4,5,5,3,5,0,0.0,satisfied +37246,53614,Female,disloyal Customer,39,Business travel,Business,1874,3,3,3,1,1,3,1,1,3,3,3,1,5,1,46,39.0,neutral or dissatisfied +37247,44348,Male,Loyal Customer,20,Personal Travel,Eco,308,2,5,2,3,2,2,1,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +37248,28167,Female,Loyal Customer,51,Business travel,Business,3591,4,4,4,4,3,1,4,4,4,4,4,1,4,4,0,0.0,satisfied +37249,89610,Male,Loyal Customer,58,Business travel,Business,2515,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,2.0,satisfied +37250,47384,Male,Loyal Customer,40,Business travel,Eco,626,2,1,1,1,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +37251,31107,Female,Loyal Customer,35,Business travel,Eco,483,5,1,1,1,5,5,5,5,3,3,4,4,3,5,0,0.0,satisfied +37252,109553,Male,Loyal Customer,7,Personal Travel,Eco,920,3,4,3,1,1,3,1,1,4,4,5,4,5,1,0,5.0,neutral or dissatisfied +37253,63435,Female,Loyal Customer,57,Personal Travel,Eco,447,2,5,2,4,2,4,4,4,3,4,5,4,5,4,128,142.0,neutral or dissatisfied +37254,93371,Male,Loyal Customer,63,Personal Travel,Eco,1024,4,4,4,4,3,4,3,3,4,2,5,3,4,3,0,0.0,satisfied +37255,71484,Male,Loyal Customer,41,Business travel,Business,3017,3,3,3,3,3,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +37256,99976,Female,Loyal Customer,40,Business travel,Business,3696,0,0,0,3,4,5,4,4,4,4,4,5,4,4,33,27.0,satisfied +37257,40185,Male,Loyal Customer,43,Business travel,Eco,402,4,5,5,5,4,4,4,4,5,4,2,1,3,4,5,15.0,satisfied +37258,101206,Female,Loyal Customer,60,Personal Travel,Eco,1090,1,4,1,3,5,4,3,1,1,1,4,3,1,3,4,0.0,neutral or dissatisfied +37259,65761,Female,Loyal Customer,22,Personal Travel,Eco,936,3,5,3,2,4,3,4,4,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +37260,109661,Male,Loyal Customer,39,Business travel,Eco,930,3,4,4,4,3,2,3,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +37261,128159,Male,disloyal Customer,24,Business travel,Business,795,5,0,5,3,1,5,1,1,3,2,4,5,5,1,0,0.0,satisfied +37262,20390,Female,disloyal Customer,18,Business travel,Eco,588,2,4,3,4,4,3,4,4,3,1,4,2,4,4,16,10.0,neutral or dissatisfied +37263,17209,Male,Loyal Customer,63,Personal Travel,Eco,694,4,4,4,2,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +37264,63125,Male,Loyal Customer,45,Business travel,Business,2215,3,3,2,3,4,4,4,5,5,5,5,4,5,3,62,47.0,satisfied +37265,44315,Male,Loyal Customer,34,Business travel,Business,837,3,3,3,3,2,4,3,5,5,5,5,3,5,4,0,2.0,satisfied +37266,75717,Female,Loyal Customer,45,Business travel,Business,1918,4,4,4,4,4,4,4,5,5,5,5,3,5,5,5,23.0,satisfied +37267,128455,Male,Loyal Customer,53,Personal Travel,Eco,646,3,5,3,3,4,3,1,4,2,2,1,4,5,4,42,22.0,neutral or dissatisfied +37268,112440,Female,Loyal Customer,43,Business travel,Business,3568,3,3,2,3,2,4,4,5,5,5,5,5,5,5,11,11.0,satisfied +37269,1545,Female,Loyal Customer,40,Business travel,Business,522,1,5,5,5,5,4,4,1,1,1,1,1,1,4,21,13.0,neutral or dissatisfied +37270,87439,Female,Loyal Customer,45,Business travel,Business,373,5,3,5,5,3,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +37271,10644,Male,Loyal Customer,54,Business travel,Business,2479,5,5,5,5,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +37272,108722,Male,Loyal Customer,53,Business travel,Business,1693,2,2,2,2,4,5,5,5,5,5,5,5,5,5,0,4.0,satisfied +37273,125561,Female,Loyal Customer,24,Business travel,Business,226,2,2,2,2,4,4,4,4,5,5,3,5,1,4,0,0.0,satisfied +37274,76450,Female,Loyal Customer,40,Business travel,Business,1809,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +37275,31702,Male,Loyal Customer,50,Personal Travel,Eco,853,3,1,3,3,1,3,5,1,3,1,4,1,4,1,38,17.0,neutral or dissatisfied +37276,74105,Male,Loyal Customer,35,Business travel,Business,641,5,5,5,5,3,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +37277,121634,Female,Loyal Customer,49,Business travel,Business,912,1,1,4,1,5,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +37278,76528,Male,Loyal Customer,55,Business travel,Business,1611,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +37279,68850,Male,Loyal Customer,52,Business travel,Business,936,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +37280,24097,Male,Loyal Customer,39,Business travel,Eco Plus,554,4,2,5,2,4,4,4,4,5,2,1,5,2,4,0,0.0,satisfied +37281,6265,Male,Loyal Customer,35,Business travel,Business,585,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +37282,61688,Male,Loyal Customer,29,Business travel,Business,1379,2,1,1,1,2,2,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +37283,92837,Male,Loyal Customer,33,Personal Travel,Eco,1541,2,2,2,4,3,2,3,3,2,1,3,2,3,3,0,7.0,neutral or dissatisfied +37284,24308,Male,Loyal Customer,55,Personal Travel,Eco Plus,147,1,4,1,3,2,1,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +37285,101984,Male,Loyal Customer,42,Personal Travel,Eco,628,2,5,3,3,2,3,2,2,5,3,5,3,4,2,1,0.0,neutral or dissatisfied +37286,28082,Male,disloyal Customer,29,Business travel,Eco,1134,3,3,3,3,3,3,2,3,5,5,3,2,3,3,0,0.0,neutral or dissatisfied +37287,29840,Female,Loyal Customer,33,Business travel,Business,261,3,1,2,1,5,4,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +37288,96671,Male,Loyal Customer,57,Personal Travel,Eco,937,5,3,5,3,4,3,1,4,4,4,3,2,3,4,0,0.0,satisfied +37289,65366,Male,Loyal Customer,43,Business travel,Business,3384,3,1,1,1,3,3,4,3,3,3,3,4,3,4,34,37.0,neutral or dissatisfied +37290,124812,Male,disloyal Customer,39,Business travel,Business,280,4,4,4,3,1,4,1,1,2,4,3,2,4,1,0,8.0,neutral or dissatisfied +37291,48359,Female,disloyal Customer,27,Business travel,Eco,522,2,3,2,2,2,2,2,2,4,1,2,2,5,2,0,0.0,neutral or dissatisfied +37292,18163,Female,Loyal Customer,63,Personal Travel,Eco,430,3,4,3,4,5,1,3,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +37293,125213,Female,Loyal Customer,43,Personal Travel,Eco,651,1,1,0,4,5,4,3,4,4,0,5,3,4,4,0,1.0,neutral or dissatisfied +37294,60827,Female,Loyal Customer,42,Personal Travel,Eco Plus,455,1,4,1,2,3,1,5,5,5,1,5,5,5,5,13,7.0,neutral or dissatisfied +37295,68788,Male,Loyal Customer,30,Business travel,Business,926,3,5,5,5,3,3,3,1,3,4,3,3,4,3,131,115.0,neutral or dissatisfied +37296,125678,Female,disloyal Customer,35,Business travel,Business,899,2,3,3,5,5,3,5,5,4,4,5,5,5,5,2,8.0,neutral or dissatisfied +37297,90183,Male,Loyal Customer,10,Personal Travel,Eco,983,3,1,3,3,5,3,5,5,3,5,3,2,4,5,2,7.0,neutral or dissatisfied +37298,60441,Female,Loyal Customer,27,Business travel,Business,2115,3,3,3,3,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +37299,20648,Female,Loyal Customer,44,Business travel,Eco,552,4,4,4,4,5,3,1,4,4,4,4,4,4,2,42,36.0,satisfied +37300,82731,Female,Loyal Customer,27,Personal Travel,Business,409,3,3,3,3,5,3,5,5,5,3,5,1,4,5,0,0.0,neutral or dissatisfied +37301,75946,Female,Loyal Customer,50,Business travel,Business,297,5,5,5,5,5,5,5,3,3,4,3,4,3,3,81,94.0,satisfied +37302,76725,Female,Loyal Customer,14,Business travel,Eco Plus,481,1,4,4,4,1,1,2,1,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +37303,253,Male,Loyal Customer,39,Personal Travel,Eco Plus,719,2,5,2,2,2,2,2,2,4,5,4,3,5,2,51,79.0,neutral or dissatisfied +37304,111975,Female,Loyal Customer,53,Business travel,Business,370,1,1,1,1,4,1,1,5,5,5,5,5,5,4,11,20.0,satisfied +37305,121031,Male,Loyal Customer,24,Personal Travel,Eco,920,3,4,3,4,3,3,3,3,5,4,5,3,4,3,0,4.0,neutral or dissatisfied +37306,31133,Male,disloyal Customer,19,Business travel,Eco,991,2,2,2,3,2,2,2,2,4,3,3,4,3,2,0,25.0,neutral or dissatisfied +37307,118733,Male,Loyal Customer,55,Personal Travel,Eco,338,3,4,3,3,2,3,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +37308,55686,Female,Loyal Customer,43,Business travel,Business,895,4,4,4,4,4,5,4,5,5,5,5,4,5,5,16,13.0,satisfied +37309,26240,Female,Loyal Customer,44,Personal Travel,Eco,404,1,4,1,3,3,4,4,2,2,1,2,4,2,3,17,12.0,neutral or dissatisfied +37310,19932,Female,Loyal Customer,47,Personal Travel,Eco,315,3,5,3,4,2,5,4,1,1,3,1,2,1,1,16,8.0,neutral or dissatisfied +37311,3192,Female,disloyal Customer,54,Business travel,Eco,293,3,4,3,1,5,3,5,5,1,1,4,5,1,5,0,0.0,neutral or dissatisfied +37312,29159,Female,Loyal Customer,20,Business travel,Eco Plus,937,0,3,1,3,4,1,5,4,1,1,1,4,1,4,34,20.0,satisfied +37313,52757,Female,disloyal Customer,17,Business travel,Business,1059,5,0,5,2,3,5,3,3,3,2,5,4,5,3,0,0.0,satisfied +37314,47617,Female,Loyal Customer,32,Business travel,Business,1235,1,1,1,1,5,5,5,5,4,1,1,1,5,5,28,22.0,satisfied +37315,90364,Female,Loyal Customer,38,Business travel,Business,3762,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +37316,18714,Male,Loyal Customer,37,Personal Travel,Eco Plus,262,2,3,2,5,5,2,5,5,2,5,5,3,5,5,0,0.0,neutral or dissatisfied +37317,124531,Female,Loyal Customer,39,Business travel,Business,3558,2,3,3,3,2,2,2,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +37318,29432,Male,Loyal Customer,43,Business travel,Business,2149,4,4,4,4,1,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +37319,43682,Male,disloyal Customer,38,Business travel,Eco,489,3,0,3,5,3,3,3,3,2,2,4,2,2,3,0,0.0,neutral or dissatisfied +37320,96002,Male,Loyal Customer,40,Business travel,Business,1235,3,4,3,3,4,4,4,5,3,4,5,4,4,4,149,146.0,satisfied +37321,113829,Female,Loyal Customer,22,Personal Travel,Eco Plus,197,3,4,0,3,1,0,1,1,3,3,4,4,4,1,4,35.0,neutral or dissatisfied +37322,103685,Female,disloyal Customer,34,Business travel,Eco,405,3,2,3,4,1,3,1,1,2,5,3,3,4,1,10,2.0,neutral or dissatisfied +37323,97656,Female,Loyal Customer,50,Business travel,Business,2249,3,3,5,3,3,4,4,5,5,5,5,5,5,3,21,15.0,satisfied +37324,14932,Female,disloyal Customer,25,Business travel,Eco,554,4,0,4,3,2,4,4,2,2,4,1,4,5,2,8,7.0,satisfied +37325,67318,Male,Loyal Customer,16,Personal Travel,Eco Plus,985,2,5,2,5,1,2,4,1,5,5,5,5,4,1,2,0.0,neutral or dissatisfied +37326,112571,Female,disloyal Customer,45,Business travel,Business,602,4,3,3,4,1,4,1,1,4,4,4,4,5,1,11,0.0,satisfied +37327,24324,Male,Loyal Customer,45,Business travel,Business,1083,4,5,4,4,5,4,4,4,4,3,4,1,4,2,25,8.0,neutral or dissatisfied +37328,83931,Male,Loyal Customer,58,Business travel,Business,3739,5,5,5,5,2,5,4,5,5,5,5,3,5,5,17,38.0,satisfied +37329,29458,Male,Loyal Customer,33,Personal Travel,Eco,421,3,4,3,2,1,3,1,1,4,5,3,4,2,1,0,0.0,neutral or dissatisfied +37330,37018,Male,Loyal Customer,45,Personal Travel,Eco,759,4,5,4,4,3,4,3,3,5,1,2,3,3,3,0,0.0,neutral or dissatisfied +37331,126227,Male,Loyal Customer,38,Business travel,Business,3668,0,0,0,3,4,5,2,4,4,4,4,4,4,1,0,0.0,satisfied +37332,77287,Female,Loyal Customer,62,Personal Travel,Eco,1931,4,5,4,3,5,5,5,1,1,4,1,5,1,5,0,0.0,neutral or dissatisfied +37333,110449,Male,Loyal Customer,61,Personal Travel,Eco,925,3,4,3,4,5,3,4,5,5,3,4,5,4,5,0,11.0,neutral or dissatisfied +37334,115713,Female,Loyal Customer,48,Business travel,Business,3812,0,0,0,2,2,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +37335,73765,Male,Loyal Customer,16,Personal Travel,Eco,204,5,4,5,1,2,5,2,2,3,2,5,1,5,2,0,0.0,satisfied +37336,120903,Male,Loyal Customer,31,Business travel,Business,3932,5,5,5,5,4,4,4,4,5,4,5,3,5,4,0,19.0,satisfied +37337,60703,Female,Loyal Customer,32,Business travel,Business,1725,5,5,5,5,2,2,2,2,5,4,4,5,4,2,65,51.0,satisfied +37338,32273,Female,Loyal Customer,48,Business travel,Eco,101,4,2,2,2,2,3,4,4,4,4,4,3,4,4,5,7.0,satisfied +37339,52182,Male,Loyal Customer,59,Business travel,Eco,237,5,1,1,1,5,5,5,5,4,3,5,2,2,5,0,0.0,satisfied +37340,979,Female,Loyal Customer,59,Business travel,Business,2260,2,2,2,2,3,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +37341,49977,Male,disloyal Customer,38,Business travel,Eco,78,2,5,2,4,2,2,4,2,4,5,1,5,5,2,0,0.0,neutral or dissatisfied +37342,5190,Male,Loyal Customer,49,Business travel,Business,295,0,0,0,4,3,4,4,1,1,1,1,4,1,4,0,0.0,satisfied +37343,105535,Female,disloyal Customer,37,Business travel,Eco,611,1,3,1,3,2,1,2,2,3,1,3,2,3,2,10,30.0,neutral or dissatisfied +37344,40929,Female,Loyal Customer,23,Business travel,Eco Plus,574,5,3,3,3,5,5,4,5,1,2,2,3,5,5,0,0.0,satisfied +37345,62889,Female,Loyal Customer,44,Business travel,Business,948,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +37346,78626,Male,Loyal Customer,27,Business travel,Business,1426,2,2,3,2,5,4,5,5,5,3,4,5,4,5,0,0.0,satisfied +37347,62819,Male,Loyal Customer,55,Personal Travel,Eco,2338,3,3,3,3,5,3,5,5,2,5,4,1,4,5,0,0.0,neutral or dissatisfied +37348,74659,Female,Loyal Customer,70,Personal Travel,Eco,1438,0,4,0,3,3,5,4,1,1,0,1,4,1,5,11,0.0,satisfied +37349,68576,Female,disloyal Customer,27,Business travel,Eco,714,3,3,3,3,3,3,3,3,4,4,3,2,4,3,10,0.0,neutral or dissatisfied +37350,44929,Female,Loyal Customer,28,Business travel,Eco Plus,438,0,0,0,1,2,0,2,2,5,2,1,3,4,2,5,17.0,satisfied +37351,40940,Female,Loyal Customer,47,Personal Travel,Eco Plus,590,4,2,4,4,3,4,4,3,3,4,3,3,3,2,0,12.0,satisfied +37352,111986,Female,Loyal Customer,68,Personal Travel,Eco,533,1,5,1,3,2,4,5,2,2,1,2,3,2,3,13,10.0,neutral or dissatisfied +37353,63203,Female,Loyal Customer,41,Business travel,Business,2137,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +37354,83142,Male,Loyal Customer,10,Personal Travel,Eco,1084,2,5,1,3,5,1,2,5,4,4,5,4,5,5,3,0.0,neutral or dissatisfied +37355,61582,Female,Loyal Customer,49,Business travel,Business,1619,3,4,4,4,2,2,1,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +37356,33263,Male,Loyal Customer,44,Personal Travel,Eco Plus,163,2,5,0,4,4,0,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +37357,83764,Male,Loyal Customer,45,Business travel,Business,3111,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +37358,2843,Female,Loyal Customer,48,Business travel,Business,1608,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +37359,27094,Male,disloyal Customer,22,Business travel,Eco,1497,5,5,5,2,1,5,1,1,5,3,4,1,3,1,0,0.0,satisfied +37360,54589,Male,Loyal Customer,55,Business travel,Business,964,3,3,3,3,2,5,5,4,4,4,4,3,4,4,0,6.0,satisfied +37361,116206,Female,Loyal Customer,53,Personal Travel,Eco,337,3,5,3,1,2,3,1,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +37362,4533,Male,Loyal Customer,13,Personal Travel,Eco,677,3,5,3,1,5,3,5,5,1,1,3,5,1,5,0,0.0,neutral or dissatisfied +37363,4759,Female,Loyal Customer,51,Business travel,Business,2642,4,4,5,4,3,4,4,4,4,5,4,4,4,5,70,63.0,satisfied +37364,14738,Male,disloyal Customer,20,Business travel,Eco,533,3,2,3,3,3,3,4,3,1,3,2,2,2,3,0,0.0,neutral or dissatisfied +37365,54005,Female,Loyal Customer,24,Business travel,Business,2876,1,1,1,1,4,4,4,4,5,1,4,3,3,4,0,0.0,satisfied +37366,9764,Male,disloyal Customer,39,Business travel,Eco,456,1,3,1,3,2,1,2,2,4,4,3,3,4,2,12,0.0,neutral or dissatisfied +37367,21274,Male,Loyal Customer,22,Business travel,Eco,620,5,1,4,4,5,5,4,5,4,3,1,5,3,5,8,0.0,satisfied +37368,56994,Female,Loyal Customer,49,Personal Travel,Eco,2454,1,5,0,5,0,4,4,2,3,2,1,4,5,4,0,0.0,neutral or dissatisfied +37369,51781,Female,Loyal Customer,51,Personal Travel,Eco,451,2,1,2,3,4,3,2,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +37370,60427,Male,Loyal Customer,57,Personal Travel,Business,862,2,4,2,3,3,4,4,4,4,2,3,5,4,4,0,0.0,neutral or dissatisfied +37371,50156,Female,Loyal Customer,27,Business travel,Business,2272,3,3,3,3,5,5,4,5,3,4,4,5,3,5,0,0.0,satisfied +37372,87033,Female,Loyal Customer,57,Business travel,Business,3681,3,3,2,3,5,5,4,4,4,4,4,3,4,5,7,0.0,satisfied +37373,75045,Male,Loyal Customer,41,Business travel,Business,1592,2,2,2,2,4,4,4,2,2,2,2,5,2,5,11,3.0,satisfied +37374,99094,Male,disloyal Customer,38,Business travel,Eco,419,4,2,4,4,3,4,4,3,2,1,4,1,4,3,56,56.0,neutral or dissatisfied +37375,11851,Female,Loyal Customer,42,Business travel,Business,3184,3,3,3,3,4,5,5,4,4,4,4,5,4,4,17,12.0,satisfied +37376,94902,Male,Loyal Customer,58,Business travel,Eco,239,5,5,5,5,5,5,5,5,2,3,1,2,4,5,15,24.0,satisfied +37377,71979,Female,disloyal Customer,49,Business travel,Eco,1440,2,2,2,2,3,2,3,3,3,4,3,4,3,3,57,81.0,neutral or dissatisfied +37378,81032,Female,Loyal Customer,57,Business travel,Business,1399,4,4,4,4,2,4,5,5,5,4,5,5,5,5,27,49.0,satisfied +37379,1516,Male,Loyal Customer,36,Business travel,Business,2041,5,5,4,5,3,5,5,5,5,4,5,3,5,3,0,5.0,satisfied +37380,94546,Male,Loyal Customer,48,Business travel,Business,341,0,0,0,1,5,4,5,1,1,1,1,3,1,5,0,0.0,satisfied +37381,55519,Female,Loyal Customer,39,Personal Travel,Eco,991,3,4,3,4,4,3,3,4,1,4,3,2,4,4,0,3.0,neutral or dissatisfied +37382,121023,Female,Loyal Customer,65,Personal Travel,Eco,993,2,5,2,4,5,5,4,5,5,2,4,4,5,5,0,55.0,neutral or dissatisfied +37383,45065,Male,Loyal Customer,67,Business travel,Eco,265,3,2,2,2,3,3,3,3,1,3,1,1,2,3,0,0.0,neutral or dissatisfied +37384,65362,Male,Loyal Customer,79,Business travel,Business,432,4,3,3,3,2,4,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +37385,95005,Female,Loyal Customer,64,Personal Travel,Eco,562,2,5,2,1,4,4,4,1,1,2,1,3,1,4,1,3.0,neutral or dissatisfied +37386,20731,Female,Loyal Customer,37,Personal Travel,Eco,707,1,4,1,2,5,1,5,5,3,4,4,3,5,5,32,24.0,neutral or dissatisfied +37387,102062,Male,Loyal Customer,64,Personal Travel,Business,236,3,3,3,3,1,3,4,4,4,3,2,3,4,1,25,16.0,neutral or dissatisfied +37388,109257,Male,Loyal Customer,57,Business travel,Business,655,1,1,1,1,5,4,5,4,4,4,4,4,4,4,74,80.0,satisfied +37389,99507,Male,Loyal Customer,25,Personal Travel,Eco,307,2,2,2,2,5,2,5,5,2,5,2,2,2,5,0,0.0,neutral or dissatisfied +37390,84947,Female,Loyal Customer,57,Business travel,Business,481,4,4,1,4,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +37391,84070,Female,Loyal Customer,43,Business travel,Business,757,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,11.0,satisfied +37392,116059,Female,Loyal Customer,22,Personal Travel,Eco,337,3,5,3,4,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +37393,13158,Male,Loyal Customer,25,Personal Travel,Eco,427,3,5,3,4,3,3,3,3,4,3,4,4,5,3,28,13.0,neutral or dissatisfied +37394,61854,Female,Loyal Customer,25,Personal Travel,Eco Plus,1635,2,4,2,3,5,2,5,5,3,5,5,3,4,5,10,8.0,neutral or dissatisfied +37395,67556,Female,disloyal Customer,20,Business travel,Eco,1235,2,1,1,3,4,1,4,4,4,2,4,4,5,4,9,2.0,neutral or dissatisfied +37396,27080,Male,Loyal Customer,44,Business travel,Business,2496,2,2,2,2,5,5,2,5,5,5,5,3,5,3,0,20.0,satisfied +37397,125676,Female,Loyal Customer,49,Business travel,Business,2882,4,4,4,4,2,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +37398,10215,Male,Loyal Customer,32,Business travel,Business,308,1,1,3,1,4,4,4,4,3,3,5,3,4,4,5,5.0,satisfied +37399,45067,Male,Loyal Customer,49,Personal Travel,Eco,342,3,4,3,3,4,3,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +37400,3761,Male,Loyal Customer,31,Business travel,Business,2040,1,1,1,1,3,3,3,3,3,2,5,3,4,3,1,0.0,satisfied +37401,113007,Female,Loyal Customer,16,Personal Travel,Eco,1797,2,3,2,3,3,2,3,3,2,2,4,3,1,3,2,0.0,neutral or dissatisfied +37402,72031,Female,Loyal Customer,31,Business travel,Eco,3711,2,5,5,5,2,2,2,2,4,4,4,2,4,2,174,165.0,neutral or dissatisfied +37403,114006,Female,Loyal Customer,17,Personal Travel,Eco,1728,4,5,4,5,2,4,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +37404,23681,Female,Loyal Customer,38,Business travel,Eco,251,3,4,4,4,3,3,3,3,5,3,5,4,1,3,0,5.0,satisfied +37405,40646,Female,Loyal Customer,28,Personal Travel,Eco Plus,391,1,4,1,2,2,1,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +37406,70952,Male,Loyal Customer,7,Personal Travel,Eco,612,2,4,3,3,4,3,4,4,1,3,4,3,4,4,19,7.0,neutral or dissatisfied +37407,62253,Male,Loyal Customer,60,Business travel,Business,2565,5,5,5,5,4,4,4,5,5,5,5,3,5,5,95,93.0,satisfied +37408,77793,Female,Loyal Customer,13,Personal Travel,Eco,731,3,3,3,4,4,3,1,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +37409,88009,Male,Loyal Customer,55,Business travel,Business,3293,2,4,2,2,3,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +37410,68060,Male,Loyal Customer,54,Business travel,Eco,868,3,2,2,2,3,3,3,3,3,4,3,4,3,3,1,50.0,neutral or dissatisfied +37411,93300,Male,disloyal Customer,15,Business travel,Business,1733,5,5,5,3,4,5,4,4,3,2,5,3,4,4,1,3.0,satisfied +37412,87519,Female,Loyal Customer,44,Personal Travel,Eco,373,3,3,1,4,5,3,3,5,5,1,4,3,5,4,1,0.0,neutral or dissatisfied +37413,50809,Male,Loyal Customer,10,Personal Travel,Eco,77,2,4,2,1,5,2,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +37414,124247,Female,Loyal Customer,28,Personal Travel,Eco,1916,3,5,3,2,4,3,5,4,4,4,3,3,5,4,0,0.0,neutral or dissatisfied +37415,112497,Female,Loyal Customer,41,Personal Travel,Eco,909,2,4,2,2,4,2,4,4,3,4,4,4,4,4,1,12.0,neutral or dissatisfied +37416,47530,Female,Loyal Customer,54,Personal Travel,Eco,590,1,5,1,3,1,4,4,5,5,5,4,4,3,4,156,178.0,neutral or dissatisfied +37417,81347,Male,Loyal Customer,30,Business travel,Business,1299,2,1,1,1,2,2,2,2,4,4,4,1,4,2,14,24.0,neutral or dissatisfied +37418,5413,Male,Loyal Customer,29,Business travel,Eco Plus,812,2,5,5,5,2,2,2,2,3,1,2,3,2,2,0,22.0,neutral or dissatisfied +37419,15408,Female,Loyal Customer,32,Business travel,Eco,306,2,5,5,5,2,2,2,2,2,3,3,2,2,2,12,11.0,neutral or dissatisfied +37420,91054,Female,Loyal Customer,10,Personal Travel,Eco,270,2,1,2,3,1,2,1,1,4,4,3,4,2,1,20,12.0,neutral or dissatisfied +37421,70304,Female,disloyal Customer,29,Business travel,Business,334,5,5,5,5,5,5,5,5,5,2,4,5,5,5,11,0.0,satisfied +37422,103308,Female,Loyal Customer,59,Business travel,Business,2202,1,1,4,1,4,5,4,4,4,4,4,4,4,3,4,6.0,satisfied +37423,79336,Female,Loyal Customer,26,Business travel,Business,3438,4,1,1,1,4,4,4,3,5,3,4,4,3,4,117,197.0,neutral or dissatisfied +37424,102985,Female,disloyal Customer,25,Business travel,Business,546,3,0,3,2,4,3,5,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +37425,117432,Male,Loyal Customer,56,Business travel,Business,1553,2,2,2,2,2,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +37426,106456,Male,Loyal Customer,42,Business travel,Eco,1670,2,1,1,1,2,2,2,2,4,4,3,4,2,2,0,40.0,neutral or dissatisfied +37427,96062,Female,Loyal Customer,59,Business travel,Business,2180,2,5,3,5,2,4,4,2,2,2,2,1,2,2,15,17.0,neutral or dissatisfied +37428,92569,Female,Loyal Customer,41,Business travel,Business,2139,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +37429,69201,Female,Loyal Customer,56,Business travel,Business,733,2,5,5,5,3,4,3,2,2,2,2,1,2,1,0,62.0,neutral or dissatisfied +37430,75145,Female,Loyal Customer,31,Business travel,Business,1652,4,4,4,4,1,2,1,1,5,2,3,4,4,1,0,0.0,satisfied +37431,7610,Male,Loyal Customer,14,Personal Travel,Eco,802,0,5,0,4,1,0,1,1,4,2,5,4,5,1,0,0.0,satisfied +37432,122255,Male,Loyal Customer,39,Personal Travel,Eco,646,4,1,4,4,5,4,5,5,1,1,3,2,3,5,0,0.0,satisfied +37433,80095,Female,Loyal Customer,46,Business travel,Business,1620,4,4,4,4,2,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +37434,60418,Male,Loyal Customer,51,Personal Travel,Eco,391,5,4,1,4,4,1,4,4,5,4,2,1,1,4,0,0.0,satisfied +37435,3705,Female,Loyal Customer,37,Personal Travel,Eco,431,0,4,0,5,4,0,4,4,4,3,4,5,5,4,9,23.0,satisfied +37436,75997,Female,Loyal Customer,15,Personal Travel,Eco Plus,297,3,3,3,4,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +37437,80424,Male,disloyal Customer,12,Business travel,Eco,1371,2,2,2,2,2,2,5,2,2,5,3,4,2,2,0,27.0,neutral or dissatisfied +37438,4312,Female,Loyal Customer,31,Business travel,Business,184,0,4,0,3,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +37439,100900,Male,Loyal Customer,45,Business travel,Business,377,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +37440,58067,Female,Loyal Customer,42,Business travel,Business,1867,4,4,4,4,4,4,5,4,4,4,4,3,4,5,5,0.0,satisfied +37441,55529,Male,Loyal Customer,40,Business travel,Business,3170,4,4,4,4,3,4,4,4,4,4,4,5,4,3,75,58.0,satisfied +37442,75948,Male,Loyal Customer,50,Business travel,Business,228,3,3,3,3,2,4,4,4,4,4,4,5,4,3,3,0.0,satisfied +37443,32312,Male,Loyal Customer,41,Business travel,Eco,102,3,2,2,2,3,3,3,3,4,3,5,4,5,3,0,0.0,satisfied +37444,759,Female,disloyal Customer,24,Business travel,Business,158,0,0,0,1,2,0,2,2,3,3,4,4,5,2,0,46.0,satisfied +37445,76688,Male,Loyal Customer,30,Personal Travel,Eco,516,2,3,2,3,3,2,3,3,3,5,1,1,3,3,2,11.0,neutral or dissatisfied +37446,69105,Male,disloyal Customer,27,Business travel,Business,1389,4,4,4,1,2,4,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +37447,69056,Male,Loyal Customer,45,Business travel,Business,1389,1,5,1,1,4,5,5,5,5,4,5,5,5,4,4,0.0,satisfied +37448,39436,Female,Loyal Customer,34,Business travel,Eco,129,3,2,2,2,3,4,3,3,2,2,2,5,4,3,7,20.0,satisfied +37449,128911,Female,Loyal Customer,56,Business travel,Eco,2248,3,2,2,2,5,3,3,3,3,3,3,4,3,1,8,0.0,neutral or dissatisfied +37450,122038,Female,Loyal Customer,65,Business travel,Eco,130,2,5,5,5,1,3,3,2,2,2,2,1,2,1,10,12.0,neutral or dissatisfied +37451,47018,Male,Loyal Customer,59,Business travel,Business,2046,1,1,5,1,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +37452,35163,Female,Loyal Customer,40,Business travel,Business,2052,2,2,4,2,5,3,1,2,2,2,2,2,2,5,1,0.0,satisfied +37453,98262,Male,disloyal Customer,25,Business travel,Eco,1072,3,3,3,3,4,3,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +37454,87239,Male,Loyal Customer,40,Personal Travel,Business,577,4,1,4,2,4,1,2,4,4,4,4,1,4,2,2,1.0,satisfied +37455,6757,Male,Loyal Customer,60,Business travel,Business,2423,3,3,3,3,2,5,5,5,5,5,5,5,5,4,32,26.0,satisfied +37456,39785,Male,Loyal Customer,60,Business travel,Business,2118,5,1,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +37457,24602,Male,disloyal Customer,12,Business travel,Eco,526,3,3,3,4,1,3,1,1,3,1,3,1,4,1,48,43.0,neutral or dissatisfied +37458,27864,Male,Loyal Customer,49,Business travel,Eco Plus,680,1,3,3,3,1,1,1,1,4,1,3,4,3,1,9,11.0,neutral or dissatisfied +37459,122347,Male,Loyal Customer,47,Business travel,Business,529,2,2,2,2,3,4,5,4,4,4,4,4,4,4,7,0.0,satisfied +37460,59875,Male,Loyal Customer,51,Business travel,Business,1065,3,3,1,3,2,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +37461,34705,Female,Loyal Customer,32,Business travel,Business,3536,5,5,4,5,5,5,5,5,5,4,5,2,1,5,0,0.0,satisfied +37462,65938,Female,Loyal Customer,25,Business travel,Business,3569,1,1,1,1,2,2,2,2,4,4,5,4,5,2,3,10.0,satisfied +37463,83012,Female,Loyal Customer,60,Business travel,Business,3418,5,5,5,5,2,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +37464,114448,Male,Loyal Customer,56,Business travel,Business,3012,0,0,0,4,2,4,4,4,4,4,4,4,4,5,6,0.0,satisfied +37465,82758,Male,disloyal Customer,29,Business travel,Eco,409,2,0,2,1,3,2,3,3,1,4,2,2,4,3,0,0.0,neutral or dissatisfied +37466,13085,Female,Loyal Customer,69,Personal Travel,Business,427,4,3,4,2,1,3,2,3,3,4,4,4,3,4,0,0.0,neutral or dissatisfied +37467,15531,Female,Loyal Customer,40,Business travel,Business,534,4,4,3,4,3,3,2,4,4,4,4,1,4,1,0,0.0,satisfied +37468,61494,Female,Loyal Customer,43,Business travel,Business,2288,3,3,3,3,5,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +37469,112118,Male,Loyal Customer,33,Business travel,Business,977,2,2,2,2,4,4,4,4,5,4,4,4,5,4,2,0.0,satisfied +37470,112896,Female,Loyal Customer,56,Business travel,Business,2052,2,2,2,2,3,4,5,3,3,2,3,5,3,4,15,10.0,satisfied +37471,50197,Male,disloyal Customer,47,Business travel,Eco,77,4,1,4,3,1,4,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +37472,42053,Male,Loyal Customer,62,Personal Travel,Eco,116,3,3,3,2,5,3,5,5,2,2,2,2,3,5,0,0.0,neutral or dissatisfied +37473,50996,Female,Loyal Customer,13,Personal Travel,Eco,199,3,3,3,3,4,3,5,4,4,2,4,3,3,4,2,0.0,neutral or dissatisfied +37474,28,Male,Loyal Customer,58,Business travel,Business,2867,0,5,0,4,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +37475,45143,Female,disloyal Customer,36,Business travel,Eco,174,2,3,2,2,4,2,5,4,4,4,5,5,1,4,0,15.0,neutral or dissatisfied +37476,61497,Female,Loyal Customer,22,Business travel,Business,2288,2,3,3,3,2,2,2,2,3,5,2,4,3,2,0,7.0,neutral or dissatisfied +37477,87823,Male,disloyal Customer,39,Business travel,Business,214,5,5,5,5,1,5,1,1,5,1,5,1,3,1,5,0.0,satisfied +37478,61956,Male,Loyal Customer,63,Business travel,Eco,552,5,4,4,4,5,5,5,5,3,2,1,4,3,5,0,0.0,satisfied +37479,21136,Male,Loyal Customer,63,Personal Travel,Eco,152,1,4,1,1,4,1,5,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +37480,59809,Female,disloyal Customer,47,Business travel,Business,997,1,1,1,2,3,1,3,3,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +37481,80646,Male,Loyal Customer,42,Business travel,Business,3042,3,3,3,3,3,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +37482,42027,Male,Loyal Customer,60,Business travel,Business,3935,3,3,3,3,4,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +37483,48206,Female,disloyal Customer,23,Business travel,Eco,259,1,2,1,3,1,1,1,1,4,4,3,1,3,1,39,27.0,neutral or dissatisfied +37484,33743,Male,Loyal Customer,38,Business travel,Business,2277,5,2,2,2,1,2,3,5,5,4,5,4,5,2,4,0.0,neutral or dissatisfied +37485,116407,Male,Loyal Customer,64,Personal Travel,Eco,390,2,4,2,2,3,2,3,3,4,4,4,3,4,3,43,40.0,neutral or dissatisfied +37486,89250,Male,Loyal Customer,26,Personal Travel,Eco Plus,1947,5,5,5,1,3,5,3,3,5,3,4,5,5,3,6,3.0,satisfied +37487,118621,Male,Loyal Customer,29,Business travel,Eco,338,2,3,3,3,2,2,2,2,4,3,2,1,3,2,20,16.0,neutral or dissatisfied +37488,75713,Male,Loyal Customer,53,Business travel,Business,868,4,5,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +37489,68281,Female,Loyal Customer,58,Personal Travel,Eco Plus,432,3,5,3,2,5,4,4,2,2,3,5,3,2,5,0,0.0,neutral or dissatisfied +37490,114133,Female,Loyal Customer,44,Business travel,Business,846,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +37491,65294,Male,Loyal Customer,8,Personal Travel,Eco Plus,247,1,3,1,4,5,1,3,5,4,4,3,4,4,5,1,0.0,neutral or dissatisfied +37492,59182,Female,Loyal Customer,29,Business travel,Business,1440,3,3,1,3,4,4,4,4,5,3,4,3,5,4,1,0.0,satisfied +37493,24997,Female,Loyal Customer,65,Personal Travel,Eco,692,3,5,3,5,3,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +37494,96003,Male,Loyal Customer,46,Business travel,Business,1235,3,3,3,3,3,5,4,4,4,5,4,4,4,4,1,0.0,satisfied +37495,92906,Female,Loyal Customer,54,Business travel,Business,1959,4,3,4,4,2,5,4,5,5,5,4,3,5,4,0,3.0,satisfied +37496,90415,Female,Loyal Customer,28,Business travel,Business,3494,5,5,5,5,3,4,3,3,4,4,4,3,5,3,0,0.0,satisfied +37497,51863,Female,Loyal Customer,27,Business travel,Eco,522,5,3,1,1,5,5,5,5,1,1,5,1,5,5,0,0.0,satisfied +37498,12694,Male,Loyal Customer,31,Business travel,Business,2537,4,2,2,2,4,4,4,4,1,2,4,1,3,4,3,0.0,neutral or dissatisfied +37499,105164,Male,Loyal Customer,36,Personal Travel,Eco,289,1,5,5,1,2,5,4,2,4,4,5,3,5,2,24,6.0,neutral or dissatisfied +37500,12752,Male,Loyal Customer,66,Personal Travel,Eco,721,1,5,1,4,1,1,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +37501,92502,Female,Loyal Customer,60,Business travel,Business,3537,1,1,1,1,2,3,5,5,5,5,5,4,5,5,10,0.0,satisfied +37502,93394,Male,Loyal Customer,30,Business travel,Business,2354,4,4,4,4,4,4,4,4,3,2,5,5,5,4,6,2.0,satisfied +37503,67464,Female,Loyal Customer,55,Personal Travel,Eco,641,4,4,4,1,4,5,5,1,1,4,1,5,1,5,0,0.0,satisfied +37504,18092,Female,Loyal Customer,28,Business travel,Eco Plus,488,4,5,5,5,4,4,4,4,2,4,5,5,1,4,49,40.0,satisfied +37505,111675,Female,Loyal Customer,57,Personal Travel,Eco,991,1,5,1,1,4,5,4,3,3,1,2,4,3,5,8,28.0,neutral or dissatisfied +37506,24210,Female,Loyal Customer,33,Business travel,Eco,170,4,3,3,3,4,4,4,4,5,3,1,3,5,4,0,0.0,satisfied +37507,54921,Female,Loyal Customer,52,Personal Travel,Eco Plus,794,3,4,3,5,2,4,5,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +37508,24587,Male,Loyal Customer,32,Business travel,Business,666,1,1,1,1,2,2,2,2,2,2,2,2,4,2,0,2.0,satisfied +37509,6432,Male,Loyal Customer,32,Personal Travel,Eco,296,3,4,3,2,5,3,5,5,3,3,1,2,3,5,8,5.0,neutral or dissatisfied +37510,70247,Male,Loyal Customer,60,Business travel,Business,1592,2,3,3,3,1,3,4,2,2,2,2,1,2,2,56,43.0,neutral or dissatisfied +37511,1337,Female,Loyal Customer,57,Business travel,Business,354,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +37512,2740,Male,Loyal Customer,58,Business travel,Business,772,3,3,3,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +37513,77893,Female,Loyal Customer,56,Business travel,Business,3286,1,1,4,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +37514,24368,Female,Loyal Customer,26,Business travel,Eco,669,3,3,3,3,3,4,4,3,3,5,1,3,4,3,0,8.0,satisfied +37515,66088,Male,Loyal Customer,58,Business travel,Business,1345,5,4,5,5,2,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +37516,87913,Male,Loyal Customer,36,Business travel,Business,250,0,1,1,1,2,5,5,3,3,3,3,3,3,5,3,0.0,satisfied +37517,6344,Female,Loyal Customer,45,Business travel,Business,296,2,2,2,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +37518,104935,Male,Loyal Customer,44,Business travel,Business,3690,1,3,1,1,4,5,5,2,2,2,2,3,2,5,18,0.0,satisfied +37519,102823,Male,Loyal Customer,16,Personal Travel,Eco,342,3,5,3,3,3,3,3,3,2,2,3,4,4,3,4,0.0,neutral or dissatisfied +37520,118886,Female,Loyal Customer,46,Personal Travel,Business,587,1,5,1,1,2,5,4,1,1,1,1,4,1,3,21,15.0,neutral or dissatisfied +37521,33494,Female,Loyal Customer,56,Personal Travel,Eco,2496,3,5,2,2,2,4,1,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +37522,115816,Male,disloyal Customer,20,Business travel,Eco,296,0,0,0,2,4,0,4,4,2,2,5,3,5,4,0,0.0,satisfied +37523,65695,Male,Loyal Customer,33,Business travel,Business,1770,3,4,5,4,3,3,3,3,2,2,3,1,3,3,0,3.0,neutral or dissatisfied +37524,59714,Female,disloyal Customer,19,Business travel,Eco,965,2,2,2,4,2,2,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +37525,95894,Female,Loyal Customer,13,Personal Travel,Eco,580,2,4,2,4,1,2,1,1,4,2,5,5,4,1,1,0.0,neutral or dissatisfied +37526,76789,Female,Loyal Customer,46,Business travel,Business,3396,4,4,4,4,2,5,4,5,5,4,5,3,5,5,0,5.0,satisfied +37527,115949,Male,Loyal Customer,45,Personal Travel,Eco,342,2,4,2,5,3,2,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +37528,25726,Female,Loyal Customer,23,Personal Travel,Eco,432,1,4,1,3,5,1,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +37529,30713,Female,disloyal Customer,22,Business travel,Eco,464,3,2,3,4,3,3,3,3,1,4,4,1,3,3,20,8.0,neutral or dissatisfied +37530,83732,Female,Loyal Customer,30,Personal Travel,Eco,1027,2,4,2,4,4,2,3,4,5,4,3,1,1,4,0,0.0,neutral or dissatisfied +37531,32987,Female,Loyal Customer,48,Personal Travel,Eco,101,0,4,0,1,5,5,4,4,4,0,5,3,4,4,0,1.0,satisfied +37532,77179,Female,Loyal Customer,38,Business travel,Business,290,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +37533,4776,Male,Loyal Customer,46,Business travel,Business,403,1,1,1,1,3,4,5,4,4,4,4,3,4,3,16,2.0,satisfied +37534,17107,Female,Loyal Customer,65,Personal Travel,Eco,416,3,1,5,1,5,1,2,5,5,5,5,2,5,4,0,0.0,neutral or dissatisfied +37535,22332,Male,Loyal Customer,39,Business travel,Business,214,1,1,4,1,4,1,2,4,4,4,5,4,4,3,0,0.0,satisfied +37536,33089,Female,Loyal Customer,56,Personal Travel,Eco,163,4,5,4,1,5,1,4,5,5,4,5,1,5,4,0,0.0,neutral or dissatisfied +37537,5014,Female,Loyal Customer,69,Personal Travel,Eco,502,1,5,1,4,3,4,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +37538,531,Male,Loyal Customer,52,Business travel,Business,2055,0,0,0,3,2,5,4,2,2,2,2,3,2,5,7,9.0,satisfied +37539,8016,Female,disloyal Customer,33,Business travel,Business,335,1,1,1,3,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +37540,15951,Male,Loyal Customer,64,Personal Travel,Eco,607,4,4,4,3,3,4,3,3,5,2,5,3,5,3,56,33.0,neutral or dissatisfied +37541,76368,Female,Loyal Customer,43,Business travel,Business,2915,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +37542,28611,Female,Loyal Customer,27,Business travel,Business,2355,4,4,4,4,4,5,4,4,3,2,4,2,1,4,0,0.0,satisfied +37543,57074,Female,Loyal Customer,69,Personal Travel,Eco,2065,2,5,2,1,5,4,4,1,1,2,1,4,1,4,50,42.0,neutral or dissatisfied +37544,126830,Female,disloyal Customer,29,Business travel,Business,2296,1,1,1,4,4,1,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +37545,41807,Male,Loyal Customer,51,Business travel,Business,3103,4,4,4,4,3,1,4,4,4,4,4,4,4,4,0,0.0,satisfied +37546,33948,Female,Loyal Customer,41,Personal Travel,Eco,1188,3,4,2,5,4,2,5,4,4,3,4,4,2,4,0,0.0,neutral or dissatisfied +37547,38528,Male,disloyal Customer,26,Business travel,Eco,1146,3,3,3,2,2,3,2,2,3,2,3,5,1,2,0,19.0,neutral or dissatisfied +37548,4292,Female,Loyal Customer,38,Personal Travel,Eco,502,2,5,3,2,2,3,2,2,3,4,4,5,5,2,17,29.0,neutral or dissatisfied +37549,103969,Female,disloyal Customer,45,Business travel,Eco Plus,770,1,1,1,4,5,1,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +37550,106553,Male,Loyal Customer,58,Personal Travel,Eco,727,5,3,5,3,4,5,5,4,1,3,3,4,3,4,0,0.0,satisfied +37551,42156,Female,Loyal Customer,23,Personal Travel,Business,784,2,1,2,4,3,2,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +37552,106472,Male,Loyal Customer,13,Personal Travel,Eco,1300,3,3,3,2,3,3,3,3,1,4,2,4,2,3,12,10.0,neutral or dissatisfied +37553,15567,Female,disloyal Customer,32,Business travel,Eco,283,4,0,4,5,5,4,5,5,3,3,1,3,1,5,0,8.0,neutral or dissatisfied +37554,4442,Female,Loyal Customer,26,Personal Travel,Eco,762,1,5,1,2,5,1,5,5,1,4,2,2,4,5,0,0.0,neutral or dissatisfied +37555,95671,Female,Loyal Customer,7,Personal Travel,Eco,1131,1,5,1,3,1,1,1,1,5,5,4,3,4,1,60,35.0,neutral or dissatisfied +37556,31188,Female,Loyal Customer,34,Business travel,Business,1511,2,2,2,2,1,5,3,4,4,4,4,3,4,3,1,64.0,satisfied +37557,37008,Female,Loyal Customer,58,Personal Travel,Eco,759,2,2,1,2,1,2,2,5,5,1,5,2,5,4,20,11.0,neutral or dissatisfied +37558,51698,Female,disloyal Customer,20,Business travel,Eco,425,2,3,2,3,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +37559,23173,Female,Loyal Customer,44,Personal Travel,Eco,223,4,4,4,4,5,4,3,2,2,4,1,3,2,3,19,9.0,neutral or dissatisfied +37560,88342,Male,Loyal Customer,41,Business travel,Business,1744,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +37561,109171,Female,Loyal Customer,51,Business travel,Business,1738,3,5,5,5,3,3,3,3,1,2,2,3,4,3,182,178.0,neutral or dissatisfied +37562,10332,Female,Loyal Customer,40,Business travel,Business,2315,1,1,4,1,2,5,4,5,5,5,5,3,5,3,14,25.0,satisfied +37563,101285,Female,Loyal Customer,60,Business travel,Eco,763,1,3,3,3,4,3,4,2,2,1,2,4,2,4,67,63.0,neutral or dissatisfied +37564,15835,Female,Loyal Customer,19,Personal Travel,Eco,1148,2,3,2,4,4,2,4,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +37565,115985,Female,Loyal Customer,18,Personal Travel,Eco,358,4,2,4,3,1,4,1,1,4,2,4,3,4,1,20,1.0,neutral or dissatisfied +37566,65865,Female,Loyal Customer,45,Personal Travel,Eco,1389,1,4,1,2,2,3,4,5,5,1,5,2,5,2,0,0.0,neutral or dissatisfied +37567,16203,Female,Loyal Customer,46,Personal Travel,Eco,277,1,3,2,5,1,2,5,1,1,2,1,1,1,2,16,24.0,neutral or dissatisfied +37568,30792,Male,Loyal Customer,67,Personal Travel,Eco,895,1,5,1,2,1,1,1,5,4,5,4,1,3,1,156,153.0,neutral or dissatisfied +37569,17700,Female,Loyal Customer,7,Personal Travel,Eco Plus,854,4,5,4,2,2,4,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +37570,23600,Male,Loyal Customer,40,Business travel,Business,1923,2,2,2,2,3,5,2,5,5,5,5,5,5,2,55,66.0,satisfied +37571,106634,Male,Loyal Customer,36,Business travel,Business,306,4,2,2,2,5,3,4,4,4,4,4,1,4,3,27,24.0,neutral or dissatisfied +37572,87253,Female,Loyal Customer,40,Business travel,Business,2430,4,4,4,4,5,5,5,3,5,5,4,5,3,5,330,321.0,satisfied +37573,121051,Female,Loyal Customer,51,Personal Travel,Eco,920,2,5,2,3,5,5,4,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +37574,109315,Male,Loyal Customer,46,Business travel,Business,3667,2,2,2,2,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +37575,70984,Male,Loyal Customer,49,Business travel,Business,2006,4,4,4,4,2,4,5,2,2,2,2,5,2,5,57,,satisfied +37576,63663,Male,disloyal Customer,21,Business travel,Eco,1236,1,1,1,2,5,1,5,5,5,2,3,4,4,5,11,0.0,neutral or dissatisfied +37577,30921,Male,Loyal Customer,36,Business travel,Eco,426,1,3,3,3,1,1,1,1,1,5,4,3,4,1,31,51.0,neutral or dissatisfied +37578,90757,Female,Loyal Customer,45,Business travel,Eco,545,1,0,0,2,3,3,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +37579,6487,Male,disloyal Customer,22,Business travel,Eco,557,2,4,2,1,1,2,1,1,4,4,5,3,4,1,0,5.0,neutral or dissatisfied +37580,49966,Male,Loyal Customer,37,Business travel,Eco,209,1,5,5,5,1,1,1,1,2,5,3,1,4,1,0,0.0,neutral or dissatisfied +37581,21585,Male,Loyal Customer,36,Business travel,Eco Plus,399,4,2,2,2,4,4,4,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +37582,58665,Female,Loyal Customer,63,Business travel,Eco Plus,867,1,1,1,1,3,4,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +37583,98173,Female,Loyal Customer,42,Business travel,Business,327,2,2,2,2,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +37584,32693,Male,disloyal Customer,37,Business travel,Business,216,2,2,2,3,1,2,1,1,1,2,1,3,3,1,1,0.0,neutral or dissatisfied +37585,37495,Female,disloyal Customer,23,Business travel,Eco,1165,3,3,3,4,5,3,5,5,4,4,4,3,3,5,35,28.0,neutral or dissatisfied +37586,109679,Male,Loyal Customer,30,Personal Travel,Eco,802,4,4,5,1,2,5,2,2,3,3,1,5,1,2,0,0.0,satisfied +37587,65496,Female,Loyal Customer,34,Personal Travel,Eco,1303,2,4,2,3,3,2,1,3,3,5,3,3,5,3,25,10.0,neutral or dissatisfied +37588,20477,Male,disloyal Customer,24,Business travel,Business,139,3,3,3,3,4,3,4,4,2,2,4,2,3,4,105,113.0,neutral or dissatisfied +37589,32635,Male,Loyal Customer,53,Business travel,Business,2340,3,3,3,3,4,3,2,4,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +37590,45263,Female,Loyal Customer,46,Business travel,Business,175,5,5,5,5,3,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +37591,55911,Female,Loyal Customer,59,Personal Travel,Eco,733,3,2,3,3,3,3,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +37592,83933,Female,disloyal Customer,22,Business travel,Business,373,4,0,4,5,5,4,5,5,4,5,5,4,4,5,11,0.0,satisfied +37593,92641,Female,disloyal Customer,38,Business travel,Eco,453,3,0,3,4,4,3,4,4,1,1,4,2,4,4,0,3.0,neutral or dissatisfied +37594,13779,Male,disloyal Customer,9,Business travel,Eco,837,3,4,4,4,2,4,5,2,2,4,3,3,3,2,12,18.0,neutral or dissatisfied +37595,5117,Male,Loyal Customer,65,Personal Travel,Eco,235,1,5,1,3,4,1,1,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +37596,30195,Female,Loyal Customer,37,Business travel,Eco Plus,571,2,1,1,1,2,3,2,2,1,3,2,2,3,2,0,0.0,neutral or dissatisfied +37597,94492,Female,Loyal Customer,27,Business travel,Business,441,2,3,3,3,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +37598,1399,Female,Loyal Customer,20,Personal Travel,Eco Plus,309,3,5,4,3,4,4,4,4,1,2,2,5,1,4,11,0.0,neutral or dissatisfied +37599,9245,Male,Loyal Customer,15,Personal Travel,Eco,177,2,2,0,3,4,0,4,4,3,3,3,2,4,4,28,20.0,neutral or dissatisfied +37600,112332,Male,Loyal Customer,28,Personal Travel,Business,862,2,3,2,3,4,2,4,4,4,5,3,1,2,4,51,39.0,neutral or dissatisfied +37601,103416,Female,Loyal Customer,23,Business travel,Business,237,2,3,3,3,2,2,2,2,1,3,4,3,3,2,11,10.0,neutral or dissatisfied +37602,34281,Male,Loyal Customer,48,Business travel,Business,3724,3,3,3,3,1,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +37603,45932,Male,Loyal Customer,39,Personal Travel,Eco,913,3,5,3,5,2,3,2,2,5,3,3,3,4,2,21,1.0,neutral or dissatisfied +37604,14134,Male,Loyal Customer,58,Business travel,Business,528,3,2,2,2,1,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +37605,83917,Male,Loyal Customer,36,Business travel,Business,304,0,0,0,2,2,4,4,2,2,2,2,4,2,5,0,11.0,satisfied +37606,127915,Female,Loyal Customer,21,Business travel,Business,1671,2,2,2,2,4,4,4,4,5,2,3,3,4,4,0,2.0,satisfied +37607,88765,Male,Loyal Customer,40,Business travel,Eco Plus,581,3,5,5,5,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +37608,112704,Female,Loyal Customer,16,Business travel,Business,2843,3,3,2,3,3,3,3,3,3,5,3,4,4,3,17,26.0,neutral or dissatisfied +37609,104788,Female,Loyal Customer,57,Business travel,Business,3832,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +37610,7608,Female,Loyal Customer,38,Business travel,Eco,425,4,5,5,5,4,4,4,4,3,1,2,1,4,4,0,0.0,satisfied +37611,80321,Female,Loyal Customer,60,Personal Travel,Eco,746,2,4,2,4,5,4,3,4,4,2,4,3,4,2,18,21.0,neutral or dissatisfied +37612,19557,Female,Loyal Customer,59,Business travel,Business,212,1,1,1,1,4,3,4,1,2,5,5,4,5,4,142,137.0,satisfied +37613,106856,Female,Loyal Customer,59,Business travel,Business,2727,1,4,4,4,3,1,1,1,1,1,1,2,1,1,15,8.0,neutral or dissatisfied +37614,78391,Female,Loyal Customer,21,Personal Travel,Eco,980,3,4,3,5,5,3,5,5,3,2,5,3,4,5,0,2.0,neutral or dissatisfied +37615,61907,Male,disloyal Customer,52,Business travel,Business,550,3,3,3,1,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +37616,62914,Male,Loyal Customer,59,Business travel,Business,3341,3,3,2,3,4,5,5,3,3,4,3,5,3,4,83,76.0,satisfied +37617,52203,Male,Loyal Customer,44,Business travel,Eco,451,3,4,4,4,3,3,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +37618,50115,Male,Loyal Customer,46,Business travel,Eco,373,1,0,0,3,2,1,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +37619,57979,Female,Loyal Customer,56,Business travel,Business,3860,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +37620,19470,Male,disloyal Customer,39,Business travel,Eco,177,2,2,2,3,2,2,2,2,4,5,3,4,4,2,9,22.0,neutral or dissatisfied +37621,70981,Female,Loyal Customer,59,Business travel,Business,802,2,2,2,2,2,5,5,5,5,5,5,5,5,3,5,0.0,satisfied +37622,24386,Male,Loyal Customer,69,Personal Travel,Eco,669,2,3,2,3,5,2,5,5,1,1,3,4,3,5,3,0.0,neutral or dissatisfied +37623,84941,Male,Loyal Customer,43,Personal Travel,Eco,547,1,3,1,4,3,1,3,3,2,3,2,2,4,3,20,17.0,neutral or dissatisfied +37624,33357,Female,Loyal Customer,45,Business travel,Eco,2409,2,4,1,1,3,2,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +37625,7283,Male,Loyal Customer,15,Personal Travel,Eco,135,2,0,2,1,2,2,2,2,1,2,5,1,3,2,5,11.0,neutral or dissatisfied +37626,63679,Female,Loyal Customer,36,Business travel,Business,2159,1,1,1,1,1,3,3,5,5,5,5,1,5,3,0,1.0,satisfied +37627,51533,Male,Loyal Customer,44,Business travel,Business,3221,4,4,4,4,3,4,1,2,2,2,2,3,2,5,0,0.0,satisfied +37628,117411,Female,Loyal Customer,25,Personal Travel,Eco,1136,2,4,2,4,3,2,3,3,1,1,3,2,4,3,0,0.0,neutral or dissatisfied +37629,72001,Female,Loyal Customer,14,Personal Travel,Eco,1440,1,4,1,3,1,1,1,1,5,4,3,5,4,1,33,36.0,neutral or dissatisfied +37630,64637,Female,Loyal Customer,51,Business travel,Business,224,2,2,2,2,2,5,5,4,4,4,4,5,4,5,12,0.0,satisfied +37631,25467,Female,Loyal Customer,9,Business travel,Business,1547,2,2,2,2,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +37632,80704,Male,Loyal Customer,27,Personal Travel,Eco,874,3,5,3,3,1,3,1,1,4,2,4,2,2,1,0,0.0,neutral or dissatisfied +37633,9982,Male,Loyal Customer,38,Personal Travel,Eco,508,1,4,1,3,3,1,3,3,4,5,4,5,5,3,29,35.0,neutral or dissatisfied +37634,49999,Female,disloyal Customer,33,Business travel,Eco,199,4,4,4,4,3,4,3,3,2,2,3,2,3,3,6,0.0,neutral or dissatisfied +37635,119791,Female,Loyal Customer,64,Business travel,Business,3289,5,5,5,5,5,4,4,5,5,5,5,5,5,4,13,0.0,satisfied +37636,21712,Male,Loyal Customer,54,Personal Travel,Eco Plus,746,4,5,4,4,4,5,5,5,3,4,3,5,3,5,104,154.0,neutral or dissatisfied +37637,127714,Female,Loyal Customer,44,Business travel,Business,601,5,5,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +37638,39584,Male,Loyal Customer,38,Business travel,Business,945,4,3,3,3,2,3,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +37639,105482,Male,Loyal Customer,46,Personal Travel,Eco Plus,495,3,5,2,4,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +37640,71390,Female,Loyal Customer,39,Business travel,Business,2388,0,0,0,4,3,4,4,2,2,2,2,3,2,3,41,32.0,satisfied +37641,118479,Male,Loyal Customer,52,Business travel,Business,370,5,5,5,5,5,5,5,5,5,5,5,3,5,4,20,18.0,satisfied +37642,79830,Male,Loyal Customer,46,Business travel,Business,1035,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +37643,58002,Female,Loyal Customer,27,Personal Travel,Eco Plus,1943,2,4,2,2,3,2,1,3,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +37644,75048,Female,Loyal Customer,51,Business travel,Business,1592,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +37645,126637,Male,Loyal Customer,52,Business travel,Business,2470,3,3,3,3,5,4,5,4,4,4,4,4,4,4,17,0.0,satisfied +37646,105274,Male,Loyal Customer,34,Business travel,Business,3012,1,1,1,1,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +37647,29852,Female,Loyal Customer,38,Business travel,Business,2876,2,2,2,2,3,5,5,5,5,5,5,3,5,3,0,1.0,satisfied +37648,25898,Male,Loyal Customer,58,Personal Travel,Eco,907,4,4,4,5,2,4,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +37649,11321,Female,Loyal Customer,36,Personal Travel,Eco,166,3,5,0,2,5,0,2,5,5,3,5,5,4,5,3,0.0,neutral or dissatisfied +37650,52901,Female,Loyal Customer,22,Business travel,Eco Plus,1024,3,2,2,2,3,3,2,3,2,5,3,2,4,3,35,18.0,neutral or dissatisfied +37651,120405,Female,Loyal Customer,48,Business travel,Business,2827,2,4,4,4,2,3,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +37652,94149,Male,Loyal Customer,59,Business travel,Business,3814,0,4,0,4,3,4,4,5,5,5,5,3,5,4,7,0.0,satisfied +37653,171,Female,Loyal Customer,49,Business travel,Business,1798,4,4,4,4,5,4,5,5,5,5,5,3,5,3,15,12.0,satisfied +37654,70041,Male,Loyal Customer,57,Business travel,Business,2444,3,3,3,3,5,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +37655,61151,Female,Loyal Customer,41,Business travel,Business,846,4,4,2,4,3,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +37656,20496,Male,Loyal Customer,47,Business travel,Business,3388,4,4,4,4,4,3,3,5,5,5,3,3,5,1,21,21.0,satisfied +37657,58270,Female,Loyal Customer,40,Business travel,Eco,678,4,4,4,4,4,4,4,4,2,5,3,2,4,4,29,16.0,neutral or dissatisfied +37658,78566,Female,disloyal Customer,20,Business travel,Eco,630,4,0,4,2,4,4,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +37659,112883,Female,Loyal Customer,48,Business travel,Business,1476,3,3,3,3,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +37660,91995,Male,Loyal Customer,27,Personal Travel,Eco,236,4,4,4,3,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +37661,98340,Female,disloyal Customer,24,Business travel,Business,1237,5,0,5,1,4,5,4,4,3,4,4,3,5,4,0,3.0,satisfied +37662,12758,Female,Loyal Customer,49,Personal Travel,Eco,721,3,4,3,4,1,4,2,2,2,3,5,3,2,5,0,0.0,neutral or dissatisfied +37663,39615,Male,Loyal Customer,36,Personal Travel,Eco,908,2,2,2,3,2,2,3,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +37664,96586,Female,disloyal Customer,27,Business travel,Business,861,2,2,2,4,4,2,4,4,4,4,5,3,5,4,0,9.0,neutral or dissatisfied +37665,45469,Male,Loyal Customer,47,Business travel,Business,522,5,5,5,5,5,2,1,3,3,4,3,1,3,4,26,40.0,satisfied +37666,43840,Female,disloyal Customer,55,Business travel,Eco,199,3,2,4,3,4,4,4,4,3,4,4,1,4,4,0,0.0,neutral or dissatisfied +37667,94859,Male,Loyal Customer,56,Business travel,Business,277,3,3,3,3,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +37668,34383,Female,Loyal Customer,58,Business travel,Eco,612,2,4,4,4,3,4,3,2,2,2,2,2,2,4,29,20.0,neutral or dissatisfied +37669,87631,Female,Loyal Customer,42,Business travel,Business,2709,1,1,1,1,4,5,4,1,1,2,1,4,1,3,0,0.0,satisfied +37670,74812,Female,Loyal Customer,68,Business travel,Eco Plus,771,4,5,5,5,2,3,1,4,4,4,4,3,4,2,0,0.0,satisfied +37671,63221,Male,Loyal Customer,58,Business travel,Business,337,3,3,2,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +37672,128175,Female,Loyal Customer,35,Business travel,Eco,1972,3,1,1,1,3,3,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +37673,28254,Female,Loyal Customer,29,Business travel,Eco,1542,0,0,0,3,2,0,2,2,4,4,4,4,5,2,7,0.0,satisfied +37674,16643,Female,Loyal Customer,46,Business travel,Eco,488,4,2,5,2,4,1,4,4,4,4,4,2,4,5,0,0.0,satisfied +37675,54693,Female,disloyal Customer,13,Business travel,Eco,861,3,4,4,4,4,4,3,4,2,4,4,3,3,4,28,17.0,neutral or dissatisfied +37676,25721,Male,Loyal Customer,66,Business travel,Business,432,2,1,2,2,1,1,4,4,4,5,4,1,4,2,13,2.0,satisfied +37677,2586,Male,Loyal Customer,33,Personal Travel,Eco,227,1,5,1,2,2,1,2,2,1,1,1,4,3,2,0,0.0,neutral or dissatisfied +37678,8793,Male,Loyal Customer,34,Business travel,Business,552,2,1,1,1,5,3,4,2,2,2,2,1,2,4,12,12.0,neutral or dissatisfied +37679,75677,Male,Loyal Customer,47,Business travel,Business,3696,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +37680,109721,Male,disloyal Customer,30,Business travel,Eco,534,4,1,4,3,3,4,3,3,2,4,3,1,2,3,30,16.0,neutral or dissatisfied +37681,25385,Female,Loyal Customer,48,Personal Travel,Eco,591,4,1,4,1,3,1,1,2,2,4,2,1,2,1,1,0.0,neutral or dissatisfied +37682,46879,Female,Loyal Customer,33,Business travel,Business,2413,1,5,5,5,4,3,3,1,1,1,1,2,1,2,0,9.0,neutral or dissatisfied +37683,71515,Male,Loyal Customer,59,Business travel,Business,2658,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +37684,22496,Male,Loyal Customer,12,Personal Travel,Eco,208,4,4,4,4,1,4,5,1,2,1,4,3,4,1,0,1.0,neutral or dissatisfied +37685,55188,Female,disloyal Customer,60,Business travel,Business,1346,3,3,3,1,1,3,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +37686,97670,Male,Loyal Customer,15,Business travel,Business,3770,3,4,4,4,3,3,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +37687,45800,Female,Loyal Customer,42,Business travel,Business,391,3,1,1,1,5,3,4,3,3,3,3,2,3,1,0,23.0,neutral or dissatisfied +37688,91492,Female,Loyal Customer,55,Personal Travel,Eco Plus,1050,4,3,3,1,4,2,4,1,1,3,1,5,1,4,29,24.0,neutral or dissatisfied +37689,94335,Male,Loyal Customer,54,Business travel,Business,2374,5,5,5,5,5,4,5,5,5,4,5,4,5,4,85,85.0,satisfied +37690,13750,Female,Loyal Customer,26,Personal Travel,Eco,384,2,4,4,3,4,2,2,3,5,5,4,2,4,2,209,200.0,neutral or dissatisfied +37691,107464,Male,Loyal Customer,49,Business travel,Business,1709,5,5,5,5,2,5,4,5,5,5,5,4,5,4,4,0.0,satisfied +37692,75289,Female,Loyal Customer,46,Business travel,Business,1744,5,5,5,5,2,3,4,5,5,5,5,3,5,3,0,6.0,satisfied +37693,70351,Male,Loyal Customer,59,Personal Travel,Eco,986,2,4,2,5,3,2,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +37694,116193,Female,Loyal Customer,31,Personal Travel,Eco,371,3,4,1,4,2,1,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +37695,53417,Male,Loyal Customer,43,Business travel,Business,2419,1,1,1,1,5,5,5,4,5,4,5,5,3,5,146,124.0,satisfied +37696,42736,Male,Loyal Customer,11,Personal Travel,Eco,536,5,4,5,2,3,5,3,3,3,5,4,5,4,3,0,0.0,satisfied +37697,27097,Female,disloyal Customer,27,Business travel,Eco,1721,3,3,3,1,2,3,5,2,1,1,5,2,4,2,1,0.0,neutral or dissatisfied +37698,41091,Male,Loyal Customer,53,Business travel,Business,191,4,4,4,4,1,4,3,5,5,5,3,4,5,3,25,14.0,satisfied +37699,81969,Male,disloyal Customer,25,Business travel,Eco,1121,3,3,3,4,2,3,2,2,4,2,3,4,4,2,53,64.0,satisfied +37700,74989,Female,Loyal Customer,44,Business travel,Eco Plus,975,3,5,5,5,3,3,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +37701,113980,Male,Loyal Customer,45,Business travel,Business,1855,4,4,4,4,2,3,5,5,5,5,5,5,5,3,0,14.0,satisfied +37702,30833,Male,Loyal Customer,36,Personal Travel,Eco,1026,1,4,1,2,1,1,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +37703,41708,Female,Loyal Customer,31,Business travel,Eco,1404,3,4,4,4,3,3,3,3,1,4,4,2,3,3,0,3.0,neutral or dissatisfied +37704,5378,Male,Loyal Customer,35,Business travel,Eco,785,2,4,4,4,2,2,2,2,4,5,3,4,3,2,14,0.0,neutral or dissatisfied +37705,86631,Female,Loyal Customer,43,Business travel,Eco,746,1,4,4,4,5,4,4,1,1,1,1,1,1,1,27,16.0,neutral or dissatisfied +37706,856,Female,Loyal Customer,58,Business travel,Business,354,2,2,2,2,1,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +37707,101379,Female,Loyal Customer,44,Business travel,Business,2694,5,5,5,5,4,5,4,5,5,5,5,3,5,3,28,25.0,satisfied +37708,30142,Female,Loyal Customer,17,Personal Travel,Eco,571,2,4,2,4,3,2,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +37709,23468,Male,disloyal Customer,19,Business travel,Eco,576,2,4,2,3,4,2,4,4,1,1,4,3,4,4,0,11.0,neutral or dissatisfied +37710,39286,Female,Loyal Customer,40,Business travel,Business,1675,4,4,4,4,4,2,5,5,5,5,3,3,5,2,0,0.0,satisfied +37711,45127,Male,Loyal Customer,53,Business travel,Eco Plus,84,5,2,2,2,5,5,5,5,1,5,2,4,3,5,15,9.0,satisfied +37712,62569,Male,disloyal Customer,9,Business travel,Eco,1052,2,3,3,3,3,2,1,3,3,3,2,2,3,3,77,73.0,neutral or dissatisfied +37713,23849,Female,disloyal Customer,18,Business travel,Eco,522,4,0,4,2,4,4,1,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +37714,45184,Female,disloyal Customer,22,Business travel,Eco Plus,174,3,0,3,5,3,5,5,2,1,2,1,5,1,5,316,326.0,neutral or dissatisfied +37715,43252,Male,Loyal Customer,38,Business travel,Eco,436,5,2,2,2,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +37716,90033,Female,Loyal Customer,54,Business travel,Business,1802,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +37717,58173,Male,Loyal Customer,42,Business travel,Business,1697,1,1,4,1,4,5,4,5,5,5,5,5,5,5,11,6.0,satisfied +37718,82626,Male,Loyal Customer,22,Personal Travel,Eco,528,2,5,2,1,3,2,3,3,4,5,4,4,4,3,0,1.0,neutral or dissatisfied +37719,116722,Male,Loyal Customer,56,Business travel,Eco Plus,325,2,5,5,5,2,2,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +37720,59370,Male,Loyal Customer,31,Business travel,Business,2556,3,3,3,3,5,5,5,5,5,2,5,3,5,5,0,0.0,satisfied +37721,105887,Female,Loyal Customer,39,Business travel,Business,1598,2,2,2,2,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +37722,60624,Male,Loyal Customer,37,Business travel,Eco Plus,801,4,4,2,4,4,4,4,4,2,1,1,1,1,4,4,0.0,satisfied +37723,71519,Female,Loyal Customer,47,Business travel,Business,1197,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +37724,60992,Male,Loyal Customer,48,Business travel,Business,1734,3,4,4,4,1,4,3,3,3,3,3,1,3,3,1,0.0,neutral or dissatisfied +37725,91202,Female,Loyal Customer,45,Personal Travel,Eco,581,2,5,2,1,5,4,5,2,2,2,4,3,2,4,92,102.0,neutral or dissatisfied +37726,125461,Female,Loyal Customer,20,Business travel,Business,2860,5,3,5,5,2,2,2,2,4,3,4,3,5,2,0,0.0,satisfied +37727,55415,Male,Loyal Customer,31,Personal Travel,Business,2254,2,4,3,4,3,4,4,5,2,5,4,4,3,4,31,39.0,neutral or dissatisfied +37728,31822,Female,Loyal Customer,52,Business travel,Business,2762,1,1,1,1,5,5,5,2,2,4,4,5,5,5,0,0.0,satisfied +37729,28565,Male,Loyal Customer,59,Personal Travel,Eco Plus,2701,3,5,3,2,1,3,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +37730,19929,Female,Loyal Customer,63,Personal Travel,Eco,315,2,2,2,2,5,1,2,4,4,2,4,3,4,1,85,89.0,neutral or dissatisfied +37731,5892,Female,disloyal Customer,54,Business travel,Business,108,2,2,2,5,1,2,1,1,3,5,4,3,4,1,0,2.0,neutral or dissatisfied +37732,119447,Male,Loyal Customer,46,Business travel,Business,1837,5,5,5,5,2,4,5,4,4,4,4,3,4,4,1,14.0,satisfied +37733,102275,Male,Loyal Customer,39,Business travel,Business,2249,1,1,1,1,1,2,2,1,1,1,1,2,1,2,26,30.0,neutral or dissatisfied +37734,56068,Male,Loyal Customer,18,Personal Travel,Eco,2475,3,3,3,2,3,3,3,4,4,3,2,3,3,3,6,0.0,neutral or dissatisfied +37735,11641,Female,Loyal Customer,57,Business travel,Business,2170,1,1,1,1,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +37736,1472,Male,Loyal Customer,64,Personal Travel,Eco,772,3,5,3,2,3,3,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +37737,117963,Female,Loyal Customer,47,Personal Travel,Eco,255,5,4,5,3,3,4,4,5,5,5,5,3,5,3,10,2.0,satisfied +37738,29434,Female,Loyal Customer,35,Personal Travel,Eco Plus,2149,1,4,1,3,4,1,4,4,5,2,3,5,4,4,1,0.0,neutral or dissatisfied +37739,104524,Male,Loyal Customer,40,Business travel,Business,1256,4,4,4,4,2,5,5,4,4,4,4,3,4,5,6,17.0,satisfied +37740,74308,Female,Loyal Customer,41,Business travel,Business,2277,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +37741,83878,Male,Loyal Customer,43,Business travel,Business,1670,2,2,2,2,5,5,4,4,4,4,4,5,4,3,0,7.0,satisfied +37742,82487,Male,Loyal Customer,28,Personal Travel,Eco Plus,502,2,5,2,3,5,2,2,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +37743,61504,Male,disloyal Customer,33,Business travel,Eco,1392,3,3,3,3,3,5,5,3,3,3,4,5,1,5,184,179.0,neutral or dissatisfied +37744,151,Male,Loyal Customer,36,Business travel,Business,1534,5,1,5,5,2,5,5,5,5,5,5,4,5,5,11,19.0,satisfied +37745,56051,Male,Loyal Customer,48,Business travel,Business,975,2,2,2,2,1,4,3,2,2,2,2,2,2,3,0,0.0,satisfied +37746,39682,Female,disloyal Customer,21,Business travel,Eco,612,2,2,2,3,1,2,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +37747,105840,Female,Loyal Customer,36,Personal Travel,Eco,842,4,5,4,1,1,4,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +37748,118339,Female,disloyal Customer,22,Business travel,Eco,202,2,0,2,3,1,2,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +37749,42993,Male,Loyal Customer,48,Business travel,Business,236,2,3,2,2,2,2,5,5,5,5,5,3,5,2,0,11.0,satisfied +37750,98719,Male,Loyal Customer,37,Business travel,Eco Plus,551,5,4,4,4,5,5,5,5,1,2,3,4,3,5,0,0.0,satisfied +37751,118497,Male,disloyal Customer,65,Business travel,Business,369,4,4,4,4,1,4,1,1,3,2,5,4,5,1,0,0.0,satisfied +37752,21634,Male,Loyal Customer,25,Personal Travel,Eco,722,5,3,5,4,4,5,4,4,2,2,5,1,3,4,0,0.0,satisfied +37753,33022,Male,Loyal Customer,8,Personal Travel,Eco,102,3,4,0,1,2,0,2,2,4,3,4,3,2,2,16,18.0,neutral or dissatisfied +37754,98065,Male,Loyal Customer,47,Business travel,Business,1449,4,5,5,5,3,3,3,4,4,4,4,3,4,4,30,16.0,neutral or dissatisfied +37755,58494,Male,disloyal Customer,27,Business travel,Eco,719,2,2,2,2,4,2,4,4,1,3,3,2,3,4,100,,neutral or dissatisfied +37756,70363,Female,Loyal Customer,32,Business travel,Eco,1145,2,2,2,2,2,2,2,2,2,5,4,2,3,2,0,0.0,neutral or dissatisfied +37757,30066,Female,Loyal Customer,39,Business travel,Eco,234,2,2,2,2,2,2,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +37758,58080,Male,disloyal Customer,22,Business travel,Business,589,0,0,0,3,4,0,4,4,3,5,4,5,4,4,0,0.0,satisfied +37759,50475,Male,disloyal Customer,24,Business travel,Eco,373,3,0,3,2,1,3,5,1,3,5,3,5,4,1,0,0.0,neutral or dissatisfied +37760,96088,Male,Loyal Customer,14,Personal Travel,Eco,583,2,2,2,4,4,2,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +37761,85734,Male,Loyal Customer,59,Business travel,Business,2531,3,3,3,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +37762,90713,Female,Loyal Customer,45,Business travel,Business,3503,5,5,3,5,3,5,5,3,3,3,3,3,3,4,22,17.0,satisfied +37763,14223,Male,Loyal Customer,29,Personal Travel,Eco,620,1,4,1,4,3,1,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +37764,57569,Male,Loyal Customer,23,Business travel,Business,1597,1,5,5,5,1,1,1,1,4,5,3,2,4,1,0,0.0,neutral or dissatisfied +37765,76380,Male,Loyal Customer,53,Business travel,Business,931,1,1,1,1,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +37766,30397,Male,Loyal Customer,48,Personal Travel,Eco,641,4,5,4,4,5,4,4,5,4,2,4,5,5,5,0,0.0,satisfied +37767,63974,Female,Loyal Customer,52,Business travel,Eco Plus,792,1,5,5,5,1,3,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +37768,127098,Female,Loyal Customer,34,Business travel,Business,2836,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +37769,68349,Male,Loyal Customer,46,Business travel,Business,1598,1,3,3,3,1,2,4,1,1,1,1,2,1,2,45,47.0,neutral or dissatisfied +37770,85495,Female,Loyal Customer,22,Personal Travel,Eco,332,1,3,1,3,2,1,2,2,1,5,4,4,4,2,10,3.0,neutral or dissatisfied +37771,74671,Female,Loyal Customer,32,Personal Travel,Eco,1235,3,5,3,3,1,3,1,1,1,2,4,2,2,1,0,0.0,neutral or dissatisfied +37772,109306,Female,disloyal Customer,36,Business travel,Business,1072,4,4,4,5,2,4,2,2,4,4,4,4,4,2,62,39.0,neutral or dissatisfied +37773,105650,Male,Loyal Customer,59,Business travel,Eco,883,3,3,4,3,3,3,3,3,2,5,3,3,3,3,19,10.0,neutral or dissatisfied +37774,82075,Male,Loyal Customer,34,Business travel,Business,1789,5,5,5,5,4,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +37775,80628,Male,Loyal Customer,42,Business travel,Business,3609,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +37776,96829,Male,Loyal Customer,21,Business travel,Eco,571,1,5,5,5,1,1,2,1,4,4,4,2,4,1,23,15.0,neutral or dissatisfied +37777,39579,Female,Loyal Customer,45,Business travel,Business,3590,1,3,2,2,1,3,4,1,1,1,1,1,1,2,0,7.0,neutral or dissatisfied +37778,16499,Male,Loyal Customer,51,Business travel,Eco,143,4,3,3,3,4,4,4,4,5,3,3,3,5,4,0,0.0,satisfied +37779,67211,Male,Loyal Customer,57,Personal Travel,Eco,1119,2,4,2,4,4,2,3,4,3,3,4,4,3,4,68,51.0,neutral or dissatisfied +37780,121993,Female,Loyal Customer,47,Business travel,Business,1860,2,2,2,2,5,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +37781,21740,Female,Loyal Customer,49,Business travel,Eco,563,2,5,5,5,4,1,4,2,2,2,2,1,2,4,0,0.0,satisfied +37782,9726,Male,Loyal Customer,46,Business travel,Eco Plus,199,3,5,5,5,3,3,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +37783,16534,Female,Loyal Customer,17,Personal Travel,Eco,209,4,1,0,2,2,0,2,2,2,2,2,2,3,2,0,0.0,satisfied +37784,64577,Female,disloyal Customer,22,Business travel,Eco,551,1,0,1,2,5,1,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +37785,71337,Male,Loyal Customer,20,Personal Travel,Eco,1514,5,5,5,2,3,5,3,3,5,3,3,5,4,3,0,0.0,satisfied +37786,43550,Female,Loyal Customer,35,Business travel,Business,438,1,1,1,1,2,1,5,5,5,5,5,4,5,3,0,0.0,satisfied +37787,126960,Female,Loyal Customer,56,Business travel,Business,325,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +37788,123716,Male,Loyal Customer,25,Personal Travel,Eco,214,3,0,0,5,2,0,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +37789,10748,Female,disloyal Customer,23,Business travel,Eco,201,2,3,3,3,2,3,2,2,3,1,3,1,4,2,28,26.0,neutral or dissatisfied +37790,81345,Female,disloyal Customer,85,Business travel,Business,899,2,2,2,4,2,3,3,2,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +37791,47015,Female,Loyal Customer,48,Business travel,Business,639,4,4,4,4,4,4,4,4,2,5,5,4,4,4,137,158.0,satisfied +37792,75576,Female,disloyal Customer,23,Business travel,Eco,337,2,0,2,2,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +37793,31456,Female,disloyal Customer,24,Business travel,Eco,862,5,5,5,1,5,3,3,3,1,4,5,3,2,3,181,180.0,satisfied +37794,95730,Male,Loyal Customer,58,Business travel,Business,419,3,3,5,3,3,4,5,4,4,4,4,5,4,4,75,70.0,satisfied +37795,41772,Female,Loyal Customer,39,Personal Travel,Eco,872,3,0,3,1,1,3,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +37796,103215,Male,disloyal Customer,24,Business travel,Eco,462,5,0,5,1,2,5,2,2,3,4,5,4,5,2,4,1.0,satisfied +37797,118721,Male,Loyal Customer,46,Personal Travel,Eco,647,3,3,3,2,2,3,2,2,3,2,5,2,2,2,32,12.0,neutral or dissatisfied +37798,31125,Male,Loyal Customer,50,Business travel,Eco,991,3,4,4,4,3,3,3,3,3,1,3,4,3,3,116,114.0,neutral or dissatisfied +37799,13918,Male,Loyal Customer,60,Business travel,Business,192,3,3,4,3,4,1,2,5,5,5,5,5,5,4,61,40.0,satisfied +37800,16375,Male,Loyal Customer,55,Business travel,Business,3249,3,4,4,4,4,2,2,3,3,3,3,1,3,1,74,116.0,neutral or dissatisfied +37801,98930,Female,Loyal Customer,52,Business travel,Business,3598,5,5,5,5,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +37802,40390,Male,Loyal Customer,41,Business travel,Business,290,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,14.0,satisfied +37803,62788,Female,disloyal Customer,40,Personal Travel,Eco,2486,1,4,1,4,1,3,4,1,3,3,3,4,2,4,0,5.0,neutral or dissatisfied +37804,73959,Male,Loyal Customer,57,Personal Travel,Eco,2342,3,2,3,2,3,3,4,3,2,1,2,2,2,3,4,0.0,neutral or dissatisfied +37805,103435,Female,disloyal Customer,22,Business travel,Business,237,4,0,4,1,2,4,2,2,4,4,4,5,5,2,0,0.0,satisfied +37806,44205,Female,Loyal Customer,43,Personal Travel,Eco,157,2,5,2,3,2,1,1,3,3,4,4,1,3,1,160,175.0,neutral or dissatisfied +37807,66089,Female,Loyal Customer,37,Business travel,Business,1055,1,1,1,1,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +37808,7222,Female,Loyal Customer,30,Business travel,Business,135,4,4,4,4,4,4,5,4,5,4,4,5,4,4,0,0.0,satisfied +37809,38478,Female,Loyal Customer,19,Personal Travel,Eco,846,0,5,0,2,3,0,3,3,5,4,5,4,5,3,15,17.0,satisfied +37810,54247,Female,Loyal Customer,32,Business travel,Business,1587,2,2,2,2,5,5,5,5,4,2,2,3,3,5,0,0.0,satisfied +37811,58476,Male,disloyal Customer,48,Business travel,Business,719,3,3,3,4,5,3,5,5,3,5,4,3,5,5,9,0.0,satisfied +37812,113705,Male,Loyal Customer,68,Personal Travel,Eco,258,4,3,0,3,2,0,2,2,2,5,3,2,3,2,21,11.0,neutral or dissatisfied +37813,74197,Female,Loyal Customer,23,Personal Travel,Eco,721,2,1,2,4,2,3,3,4,1,3,4,3,4,3,254,239.0,neutral or dissatisfied +37814,121040,Female,Loyal Customer,58,Personal Travel,Eco,951,2,2,2,3,3,2,3,1,1,2,5,2,1,3,0,0.0,neutral or dissatisfied +37815,84939,Male,Loyal Customer,24,Personal Travel,Eco,481,4,3,4,4,3,4,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +37816,46013,Male,Loyal Customer,44,Business travel,Business,2444,4,4,4,4,5,4,3,4,4,4,4,4,4,1,0,4.0,neutral or dissatisfied +37817,17660,Male,Loyal Customer,61,Business travel,Business,2717,1,2,2,2,5,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +37818,90262,Male,Loyal Customer,41,Business travel,Business,3239,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +37819,38070,Female,Loyal Customer,35,Business travel,Business,3235,4,4,4,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +37820,70347,Female,Loyal Customer,60,Personal Travel,Eco,986,4,4,4,3,3,5,4,3,3,4,3,4,3,4,10,4.0,satisfied +37821,71137,Female,disloyal Customer,45,Business travel,Business,585,3,3,3,4,1,3,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +37822,78213,Male,Loyal Customer,50,Personal Travel,Eco,153,4,4,4,3,5,4,5,5,3,4,1,2,2,5,0,0.0,neutral or dissatisfied +37823,27262,Male,disloyal Customer,23,Business travel,Business,605,5,0,5,4,2,5,2,2,3,2,5,4,4,2,0,1.0,satisfied +37824,72229,Female,Loyal Customer,51,Business travel,Business,2646,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +37825,122850,Female,disloyal Customer,37,Business travel,Business,226,2,2,2,3,5,2,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +37826,6275,Female,Loyal Customer,72,Business travel,Business,2303,1,1,2,2,3,3,2,1,1,1,1,2,1,1,9,3.0,neutral or dissatisfied +37827,129630,Male,disloyal Customer,59,Business travel,Business,308,2,3,3,3,1,2,1,1,5,4,5,4,4,1,9,12.0,neutral or dissatisfied +37828,104782,Male,Loyal Customer,60,Business travel,Business,587,4,4,4,4,2,5,4,3,3,3,3,3,3,3,9,8.0,satisfied +37829,124322,Male,Loyal Customer,16,Personal Travel,Eco,255,3,3,0,3,5,0,5,5,1,5,2,1,3,5,0,0.0,neutral or dissatisfied +37830,128237,Male,Loyal Customer,36,Personal Travel,Eco,602,3,4,3,2,1,3,1,1,4,5,4,4,5,1,2,2.0,neutral or dissatisfied +37831,123591,Female,Loyal Customer,25,Personal Travel,Eco,1773,3,5,2,5,5,2,5,5,4,5,3,5,5,5,3,0.0,neutral or dissatisfied +37832,30519,Male,Loyal Customer,10,Personal Travel,Eco,484,1,5,1,2,3,1,1,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +37833,41547,Male,Loyal Customer,62,Business travel,Business,1482,3,4,4,4,4,3,3,3,3,3,3,1,3,4,2,0.0,neutral or dissatisfied +37834,70059,Female,Loyal Customer,59,Business travel,Business,2499,1,1,3,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +37835,116244,Male,Loyal Customer,47,Personal Travel,Eco,446,3,5,4,3,2,4,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +37836,79506,Male,Loyal Customer,32,Business travel,Business,3456,5,5,5,5,4,4,4,4,5,2,5,4,5,4,5,0.0,satisfied +37837,124924,Female,Loyal Customer,47,Business travel,Eco,728,1,1,1,1,4,4,4,1,1,1,1,1,1,2,2,41.0,neutral or dissatisfied +37838,18491,Female,disloyal Customer,21,Business travel,Eco,201,2,0,2,5,3,2,3,3,1,4,5,1,2,3,0,0.0,neutral or dissatisfied +37839,73915,Female,disloyal Customer,28,Business travel,Business,1462,4,4,4,4,2,4,2,2,4,3,4,5,4,2,0,0.0,satisfied +37840,46250,Male,Loyal Customer,41,Business travel,Eco,679,1,3,3,3,1,1,1,4,2,3,4,1,4,1,115,185.0,neutral or dissatisfied +37841,115798,Male,disloyal Customer,23,Business travel,Eco,337,2,4,2,2,3,2,3,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +37842,37483,Female,Loyal Customer,61,Business travel,Business,1056,3,3,3,3,2,5,3,5,5,5,5,3,5,3,0,0.0,satisfied +37843,108489,Female,Loyal Customer,35,Business travel,Eco,570,2,2,2,2,2,2,2,2,1,3,4,3,4,2,2,0.0,neutral or dissatisfied +37844,43876,Female,Loyal Customer,56,Business travel,Business,2871,2,3,3,3,1,4,3,3,3,3,2,4,3,3,1,0.0,neutral or dissatisfied +37845,65265,Male,Loyal Customer,74,Business travel,Eco Plus,190,1,3,3,3,1,1,1,1,2,1,4,3,3,1,0,0.0,neutral or dissatisfied +37846,52449,Male,Loyal Customer,32,Personal Travel,Eco,598,2,3,2,4,2,2,2,2,1,4,2,1,3,2,0,2.0,neutral or dissatisfied +37847,2094,Female,Loyal Customer,26,Personal Travel,Eco,785,1,5,1,5,1,1,5,1,5,3,4,4,5,1,32,39.0,neutral or dissatisfied +37848,122323,Male,Loyal Customer,40,Business travel,Eco Plus,573,2,4,4,4,2,3,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +37849,105104,Female,Loyal Customer,49,Business travel,Business,3942,0,0,0,3,2,5,5,2,2,2,2,5,2,5,4,0.0,satisfied +37850,95742,Male,Loyal Customer,45,Business travel,Business,3806,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +37851,69322,Female,Loyal Customer,56,Business travel,Business,1089,5,3,5,5,3,4,5,4,4,4,4,3,4,4,2,0.0,satisfied +37852,93639,Male,Loyal Customer,54,Personal Travel,Eco,577,2,5,1,4,3,1,3,3,4,2,5,4,5,3,12,0.0,neutral or dissatisfied +37853,118288,Female,Loyal Customer,38,Business travel,Business,2787,4,4,1,4,4,5,4,4,4,4,4,5,4,4,2,3.0,satisfied +37854,72153,Male,Loyal Customer,67,Personal Travel,Eco,731,2,4,1,3,5,1,5,5,1,1,3,3,4,5,0,3.0,neutral or dissatisfied +37855,61781,Male,Loyal Customer,61,Personal Travel,Eco,1609,3,4,3,3,1,3,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +37856,91483,Male,Loyal Customer,44,Personal Travel,Eco,859,2,5,2,2,4,2,4,4,3,4,5,5,5,4,3,0.0,neutral or dissatisfied +37857,91335,Female,Loyal Customer,9,Personal Travel,Eco Plus,271,4,3,4,4,2,4,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +37858,72302,Female,Loyal Customer,65,Personal Travel,Eco,919,5,5,4,1,5,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +37859,80819,Female,Loyal Customer,52,Business travel,Business,484,1,4,4,4,5,3,2,1,1,1,1,3,1,3,65,64.0,neutral or dissatisfied +37860,19756,Male,disloyal Customer,22,Business travel,Eco,462,3,1,4,2,1,4,1,1,1,1,3,3,2,1,35,30.0,neutral or dissatisfied +37861,7476,Male,Loyal Customer,68,Business travel,Business,3215,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +37862,106374,Female,disloyal Customer,28,Business travel,Business,551,5,5,5,5,4,5,4,4,3,5,4,4,4,4,45,38.0,satisfied +37863,3012,Male,Loyal Customer,42,Business travel,Business,2346,2,2,2,2,2,4,5,4,4,4,4,3,4,5,0,28.0,satisfied +37864,96043,Male,Loyal Customer,43,Business travel,Eco,583,2,4,4,4,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +37865,93673,Female,Loyal Customer,24,Personal Travel,Eco,667,2,5,2,3,5,2,5,5,4,2,4,4,5,5,10,12.0,neutral or dissatisfied +37866,3522,Female,Loyal Customer,49,Business travel,Business,3240,1,5,5,5,3,3,3,1,1,1,1,1,1,2,0,15.0,neutral or dissatisfied +37867,38536,Female,Loyal Customer,34,Business travel,Business,2586,1,5,5,5,2,3,4,1,1,1,1,2,1,1,4,13.0,neutral or dissatisfied +37868,22592,Female,disloyal Customer,42,Business travel,Eco,250,1,2,1,2,5,1,5,5,1,3,2,1,2,5,39,22.0,neutral or dissatisfied +37869,95061,Male,Loyal Customer,49,Personal Travel,Eco,562,3,4,3,1,2,3,2,2,5,1,3,3,4,2,0,0.0,neutral or dissatisfied +37870,128106,Female,disloyal Customer,26,Business travel,Business,1587,0,0,0,3,2,4,2,2,4,4,3,5,5,2,0,0.0,satisfied +37871,77911,Female,Loyal Customer,16,Personal Travel,Eco,610,3,5,3,4,3,3,3,3,4,2,4,3,4,3,5,0.0,neutral or dissatisfied +37872,36355,Female,Loyal Customer,15,Business travel,Business,200,2,3,3,3,1,2,2,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +37873,38096,Male,Loyal Customer,46,Business travel,Eco,1185,3,1,1,1,3,4,4,1,1,3,3,4,1,4,236,229.0,neutral or dissatisfied +37874,9169,Female,disloyal Customer,32,Business travel,Business,416,4,4,4,2,3,4,3,3,4,3,4,3,5,3,0,7.0,neutral or dissatisfied +37875,84496,Female,Loyal Customer,42,Business travel,Business,4502,4,4,4,4,5,5,5,3,3,3,5,5,3,5,0,0.0,satisfied +37876,129320,Female,Loyal Customer,40,Business travel,Business,2475,5,5,5,5,4,5,4,5,5,5,5,3,5,5,41,63.0,satisfied +37877,33810,Female,Loyal Customer,35,Business travel,Eco,1428,2,5,3,3,2,3,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +37878,17580,Female,Loyal Customer,55,Personal Travel,Eco,1034,2,4,2,2,5,5,5,3,3,2,1,5,3,5,0,9.0,neutral or dissatisfied +37879,123562,Female,Loyal Customer,54,Business travel,Business,1773,5,5,2,5,4,3,4,4,4,5,4,4,4,5,1,0.0,satisfied +37880,113941,Male,Loyal Customer,47,Business travel,Business,1855,1,1,5,1,3,3,5,4,4,5,4,5,4,3,0,0.0,satisfied +37881,107240,Female,Loyal Customer,46,Business travel,Business,307,2,2,2,2,3,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +37882,112983,Female,Loyal Customer,40,Personal Travel,Eco Plus,1129,3,5,3,4,2,3,2,2,3,2,3,3,4,2,0,1.0,neutral or dissatisfied +37883,75390,Female,Loyal Customer,58,Business travel,Business,2342,3,3,4,3,2,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +37884,100921,Male,Loyal Customer,54,Business travel,Business,2889,2,5,5,5,1,4,4,2,2,2,2,1,2,4,12,6.0,neutral or dissatisfied +37885,123136,Male,Loyal Customer,70,Business travel,Business,328,1,4,4,4,1,4,4,1,1,1,1,1,1,4,92,87.0,neutral or dissatisfied +37886,128959,Male,Loyal Customer,36,Business travel,Eco,236,5,5,3,5,5,5,5,5,5,2,1,5,5,5,0,0.0,satisfied +37887,52339,Female,Loyal Customer,39,Business travel,Eco,261,4,1,1,1,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +37888,95893,Female,Loyal Customer,26,Personal Travel,Eco,580,2,4,2,4,5,2,5,5,3,3,3,3,4,5,11,0.0,neutral or dissatisfied +37889,41340,Female,Loyal Customer,13,Personal Travel,Eco,689,1,5,1,1,4,1,2,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +37890,17848,Male,disloyal Customer,38,Business travel,Eco,615,1,4,1,1,1,4,4,3,1,5,2,4,3,4,139,109.0,neutral or dissatisfied +37891,112304,Male,Loyal Customer,29,Personal Travel,Eco Plus,1671,3,3,2,4,1,2,1,1,4,1,4,2,4,1,99,,neutral or dissatisfied +37892,1675,Female,Loyal Customer,29,Business travel,Business,561,3,3,1,3,4,4,4,4,4,4,5,3,4,4,79,93.0,satisfied +37893,47542,Male,Loyal Customer,35,Personal Travel,Eco,599,2,0,2,4,2,2,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +37894,66735,Female,Loyal Customer,64,Personal Travel,Eco,978,4,4,4,2,3,4,4,4,4,4,4,4,4,3,26,17.0,neutral or dissatisfied +37895,76290,Female,Loyal Customer,22,Business travel,Business,2677,1,5,5,5,1,1,1,1,4,3,2,4,2,1,21,0.0,neutral or dissatisfied +37896,4141,Female,Loyal Customer,24,Business travel,Business,2502,2,5,5,5,2,2,2,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +37897,99196,Female,Loyal Customer,60,Business travel,Business,1180,4,4,4,4,4,4,4,3,3,3,3,4,3,5,15,11.0,satisfied +37898,98500,Female,disloyal Customer,40,Business travel,Business,402,3,3,3,3,1,3,1,1,3,2,5,5,4,1,28,35.0,neutral or dissatisfied +37899,26335,Male,Loyal Customer,42,Business travel,Eco,873,5,3,3,3,5,5,5,5,4,1,5,2,1,5,0,0.0,satisfied +37900,24150,Male,disloyal Customer,32,Business travel,Eco,170,2,0,2,2,2,2,2,2,1,2,2,1,5,2,30,15.0,neutral or dissatisfied +37901,54055,Male,Loyal Customer,22,Business travel,Business,1416,5,5,5,5,5,5,5,5,4,4,2,3,5,5,64,51.0,satisfied +37902,65436,Female,Loyal Customer,46,Business travel,Business,2165,2,2,4,2,2,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +37903,16664,Female,Loyal Customer,22,Business travel,Business,1999,3,4,4,4,3,2,3,3,3,3,4,3,4,3,15,17.0,neutral or dissatisfied +37904,64250,Female,Loyal Customer,52,Personal Travel,Eco,1660,4,4,4,2,2,4,5,5,5,4,5,3,5,5,0,15.0,neutral or dissatisfied +37905,55829,Male,Loyal Customer,44,Business travel,Business,1416,3,3,3,3,3,5,5,4,4,4,4,5,4,3,5,12.0,satisfied +37906,18777,Male,Loyal Customer,51,Business travel,Business,3627,2,2,2,2,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +37907,112722,Male,Loyal Customer,63,Personal Travel,Eco,671,2,5,2,3,3,2,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +37908,123909,Female,Loyal Customer,45,Personal Travel,Eco,544,4,4,4,4,5,1,5,1,1,4,1,4,1,3,0,20.0,neutral or dissatisfied +37909,109102,Female,Loyal Customer,51,Personal Travel,Eco,928,1,4,1,3,2,4,2,3,3,1,4,1,3,1,42,33.0,neutral or dissatisfied +37910,50101,Female,Loyal Customer,48,Business travel,Business,250,3,3,3,3,1,2,3,3,3,3,3,3,3,4,46,52.0,neutral or dissatisfied +37911,6162,Male,disloyal Customer,34,Business travel,Eco,409,4,1,4,3,3,4,1,3,3,3,3,4,3,3,0,50.0,neutral or dissatisfied +37912,114428,Female,Loyal Customer,35,Business travel,Business,3579,2,2,2,2,2,4,4,5,5,5,5,4,5,5,70,57.0,satisfied +37913,63343,Female,Loyal Customer,45,Business travel,Eco,447,2,3,3,3,5,3,4,2,2,2,2,2,2,1,3,0.0,neutral or dissatisfied +37914,97632,Female,Loyal Customer,44,Business travel,Business,3708,3,3,3,3,4,4,4,3,4,5,4,4,4,4,192,193.0,satisfied +37915,77094,Female,Loyal Customer,29,Business travel,Business,1481,4,1,4,4,3,3,3,3,4,4,4,4,4,3,13,10.0,satisfied +37916,3512,Male,Loyal Customer,45,Business travel,Business,1722,3,3,5,3,2,5,5,4,4,4,4,3,4,4,74,60.0,satisfied +37917,64340,Female,Loyal Customer,51,Business travel,Business,1172,4,4,3,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +37918,92975,Female,Loyal Customer,31,Business travel,Business,1614,4,4,4,4,4,4,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +37919,68913,Male,Loyal Customer,16,Personal Travel,Eco,936,2,1,2,4,4,2,3,4,1,5,4,2,3,4,0,0.0,neutral or dissatisfied +37920,112058,Female,Loyal Customer,60,Business travel,Business,1754,2,2,2,2,3,2,2,5,5,4,4,2,5,2,137,157.0,satisfied +37921,109751,Female,disloyal Customer,37,Business travel,Business,587,5,5,5,2,4,5,4,4,3,5,4,5,5,4,90,88.0,satisfied +37922,33589,Female,Loyal Customer,25,Business travel,Business,1762,1,1,1,1,1,1,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +37923,99149,Female,Loyal Customer,36,Business travel,Eco Plus,237,5,5,5,5,5,5,5,5,3,1,5,4,2,5,25,9.0,satisfied +37924,66831,Male,Loyal Customer,41,Business travel,Business,731,4,4,4,4,3,5,5,5,5,5,5,3,5,3,7,0.0,satisfied +37925,69501,Female,Loyal Customer,7,Personal Travel,Eco Plus,1089,2,3,2,2,5,2,5,5,1,3,2,1,3,5,0,0.0,neutral or dissatisfied +37926,100142,Female,Loyal Customer,41,Business travel,Business,725,1,1,1,1,4,4,4,4,4,4,4,5,4,5,12,0.0,satisfied +37927,9943,Female,disloyal Customer,20,Business travel,Eco,457,1,2,1,4,5,1,5,5,1,5,4,4,4,5,0,9.0,neutral or dissatisfied +37928,74760,Female,Loyal Customer,62,Personal Travel,Eco,1313,2,4,2,1,2,4,5,5,5,2,5,4,5,4,0,9.0,neutral or dissatisfied +37929,110513,Male,Loyal Customer,58,Personal Travel,Eco Plus,663,2,5,2,2,4,2,4,4,5,3,5,4,5,4,41,28.0,neutral or dissatisfied +37930,99865,Female,Loyal Customer,41,Business travel,Business,2897,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +37931,73134,Female,disloyal Customer,37,Business travel,Eco,668,1,3,1,4,2,1,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +37932,95722,Male,Loyal Customer,54,Business travel,Business,2423,3,3,3,3,4,4,5,4,4,4,4,3,4,3,106,104.0,satisfied +37933,15194,Male,Loyal Customer,52,Business travel,Eco,461,2,2,3,3,2,2,2,2,2,4,3,4,3,2,60,58.0,neutral or dissatisfied +37934,12877,Male,disloyal Customer,41,Business travel,Eco,641,2,0,2,4,2,2,5,2,2,1,5,4,5,2,0,0.0,neutral or dissatisfied +37935,8054,Male,disloyal Customer,42,Business travel,Business,335,4,4,4,1,5,4,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +37936,54657,Male,Loyal Customer,39,Business travel,Business,2486,2,2,2,2,1,1,5,3,3,4,3,1,3,3,2,0.0,satisfied +37937,45169,Female,Loyal Customer,44,Personal Travel,Eco,174,3,5,3,5,5,3,5,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +37938,105995,Female,disloyal Customer,22,Business travel,Eco,1370,4,3,3,3,3,4,3,3,4,5,4,5,4,3,13,0.0,neutral or dissatisfied +37939,63642,Male,Loyal Customer,45,Personal Travel,Eco,602,1,3,1,2,2,1,2,2,3,2,2,1,2,2,0,1.0,neutral or dissatisfied +37940,34713,Male,disloyal Customer,39,Business travel,Eco,301,4,4,4,1,1,4,1,1,5,1,3,4,5,1,18,18.0,satisfied +37941,66333,Female,Loyal Customer,17,Personal Travel,Eco Plus,852,2,2,1,4,3,1,3,3,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +37942,127260,Female,disloyal Customer,49,Business travel,Business,1107,4,3,3,2,5,4,5,5,3,5,5,5,5,5,0,0.0,satisfied +37943,97474,Male,Loyal Customer,39,Business travel,Business,822,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +37944,82046,Female,Loyal Customer,10,Personal Travel,Eco,1454,2,2,2,2,5,2,5,5,4,3,2,2,3,5,0,0.0,neutral or dissatisfied +37945,61194,Male,Loyal Customer,43,Business travel,Business,3473,3,3,3,3,3,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +37946,89196,Male,Loyal Customer,41,Personal Travel,Eco,1947,3,2,3,3,2,3,5,2,3,5,2,1,4,2,9,0.0,neutral or dissatisfied +37947,63580,Male,Loyal Customer,49,Business travel,Business,2133,1,1,1,1,5,3,5,5,5,5,5,3,5,5,0,1.0,satisfied +37948,40294,Male,Loyal Customer,47,Personal Travel,Eco,436,4,4,4,5,3,4,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +37949,78383,Female,Loyal Customer,59,Business travel,Eco,980,1,4,4,4,2,4,4,1,1,1,1,4,1,2,0,2.0,neutral or dissatisfied +37950,97260,Male,Loyal Customer,51,Personal Travel,Eco,296,1,4,4,3,5,4,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +37951,119969,Male,Loyal Customer,27,Personal Travel,Eco,868,2,1,2,3,2,2,3,2,2,2,2,4,3,2,0,0.0,neutral or dissatisfied +37952,12023,Male,disloyal Customer,45,Business travel,Business,351,4,4,4,3,1,4,1,1,3,2,3,4,3,1,19,12.0,satisfied +37953,93530,Female,disloyal Customer,54,Business travel,Eco,915,3,3,3,4,2,3,4,2,1,1,1,2,4,2,0,0.0,neutral or dissatisfied +37954,44750,Female,Loyal Customer,54,Business travel,Eco,189,1,4,4,4,1,1,1,1,1,1,1,4,1,2,65,53.0,neutral or dissatisfied +37955,43205,Female,Loyal Customer,23,Personal Travel,Eco,466,4,4,5,1,1,5,1,1,3,2,5,5,4,1,0,0.0,satisfied +37956,94652,Male,Loyal Customer,34,Business travel,Eco,239,2,2,2,2,2,2,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +37957,32961,Female,Loyal Customer,26,Personal Travel,Eco,102,3,2,3,4,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +37958,115206,Male,disloyal Customer,37,Business travel,Business,480,1,1,1,2,5,1,5,5,4,3,4,5,4,5,55,51.0,neutral or dissatisfied +37959,45690,Female,Loyal Customer,30,Business travel,Business,826,5,5,5,5,3,3,3,3,3,5,3,3,5,3,0,0.0,satisfied +37960,48683,Male,Loyal Customer,31,Business travel,Business,3845,2,2,4,2,3,4,5,3,5,5,5,5,5,3,0,0.0,satisfied +37961,91311,Male,Loyal Customer,43,Business travel,Business,404,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +37962,234,Male,Loyal Customer,47,Business travel,Eco Plus,213,3,4,4,4,3,3,3,3,1,4,5,4,3,3,0,0.0,satisfied +37963,83269,Female,Loyal Customer,38,Business travel,Eco,2079,3,1,1,1,3,3,3,3,4,5,1,3,2,3,0,18.0,neutral or dissatisfied +37964,51435,Female,Loyal Customer,45,Personal Travel,Eco Plus,109,1,3,1,4,1,3,3,1,1,1,1,1,1,5,6,3.0,neutral or dissatisfied +37965,122989,Male,Loyal Customer,41,Business travel,Business,3759,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +37966,70038,Female,Loyal Customer,70,Business travel,Business,1956,1,1,5,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +37967,24321,Male,Loyal Customer,31,Business travel,Business,1048,1,5,1,1,4,4,4,4,4,4,1,2,5,4,16,68.0,satisfied +37968,75107,Male,Loyal Customer,30,Personal Travel,Business,1723,1,4,1,4,2,1,2,2,4,2,4,3,5,2,0,28.0,neutral or dissatisfied +37969,25731,Female,Loyal Customer,37,Personal Travel,Eco,528,2,5,1,3,2,1,2,2,4,4,3,1,3,2,22,4.0,neutral or dissatisfied +37970,74222,Female,Loyal Customer,16,Personal Travel,Eco,1746,1,3,1,3,3,1,5,3,3,4,1,1,3,3,45,30.0,neutral or dissatisfied +37971,127721,Female,Loyal Customer,49,Business travel,Business,255,4,4,4,4,4,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +37972,62810,Female,Loyal Customer,51,Personal Travel,Eco,2338,3,2,2,3,2,4,4,1,3,3,4,4,1,4,20,36.0,neutral or dissatisfied +37973,117671,Female,Loyal Customer,59,Personal Travel,Eco,1449,3,4,3,2,2,4,2,3,3,3,3,2,3,3,14,0.0,neutral or dissatisfied +37974,34809,Male,Loyal Customer,55,Personal Travel,Eco,301,4,4,4,1,4,4,3,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +37975,107639,Male,disloyal Customer,37,Business travel,Business,405,2,1,1,1,4,1,4,4,3,2,5,5,5,4,10,5.0,neutral or dissatisfied +37976,112835,Female,Loyal Customer,28,Business travel,Business,1390,1,1,1,1,5,5,5,5,4,3,5,4,4,5,17,6.0,satisfied +37977,63465,Female,Loyal Customer,45,Business travel,Eco Plus,447,3,2,2,2,4,4,3,3,3,3,3,2,3,2,71,103.0,neutral or dissatisfied +37978,4035,Female,disloyal Customer,56,Business travel,Eco,425,4,0,4,3,2,4,1,2,5,2,4,2,5,2,0,0.0,neutral or dissatisfied +37979,128516,Male,Loyal Customer,8,Personal Travel,Eco,304,3,4,5,4,4,5,4,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +37980,95460,Female,Loyal Customer,39,Business travel,Business,3612,4,4,4,4,4,5,4,4,4,4,4,4,4,4,2,2.0,satisfied +37981,74266,Male,Loyal Customer,51,Business travel,Business,748,1,1,1,1,4,5,5,5,5,5,5,3,5,4,12,18.0,satisfied +37982,114584,Female,Loyal Customer,56,Business travel,Business,3561,1,1,1,1,2,5,4,5,5,5,5,3,5,5,43,40.0,satisfied +37983,63946,Female,Loyal Customer,53,Personal Travel,Eco,1172,3,4,3,1,3,5,4,5,5,3,5,4,5,3,0,9.0,neutral or dissatisfied +37984,116385,Female,Loyal Customer,68,Personal Travel,Eco,342,4,5,4,2,4,2,4,3,3,4,3,1,3,1,0,0.0,satisfied +37985,119805,Male,disloyal Customer,39,Business travel,Business,936,2,2,2,3,2,2,2,2,4,3,5,3,4,2,17,7.0,satisfied +37986,12995,Female,Loyal Customer,43,Business travel,Eco,374,4,2,2,2,4,3,1,4,4,4,4,2,4,3,0,0.0,satisfied +37987,24645,Female,Loyal Customer,55,Personal Travel,Eco Plus,666,3,4,3,3,3,3,4,4,4,3,4,3,4,2,35,34.0,neutral or dissatisfied +37988,187,Male,disloyal Customer,36,Business travel,Business,213,3,3,3,3,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +37989,13989,Female,Loyal Customer,56,Business travel,Business,1930,3,5,5,5,1,4,4,4,4,4,3,2,4,1,4,21.0,neutral or dissatisfied +37990,40467,Female,disloyal Customer,22,Business travel,Eco,222,3,0,3,1,5,3,5,5,1,5,3,1,2,5,0,0.0,neutral or dissatisfied +37991,23157,Male,Loyal Customer,62,Personal Travel,Eco,250,1,4,1,2,3,1,5,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +37992,118225,Female,Loyal Customer,49,Business travel,Business,1587,1,1,1,1,3,5,4,5,5,5,5,4,5,3,128,114.0,satisfied +37993,71,Female,disloyal Customer,47,Business travel,Eco,173,1,4,1,1,3,1,3,3,5,5,1,4,4,3,0,14.0,neutral or dissatisfied +37994,82881,Female,Loyal Customer,48,Business travel,Business,245,1,5,5,5,4,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +37995,26034,Male,Loyal Customer,62,Personal Travel,Eco,321,3,4,3,1,4,3,4,4,2,3,1,4,2,4,15,12.0,neutral or dissatisfied +37996,63822,Female,disloyal Customer,24,Business travel,Business,1192,3,3,4,3,4,4,4,4,4,3,3,3,3,4,0,0.0,neutral or dissatisfied +37997,68430,Male,Loyal Customer,12,Personal Travel,Eco,1045,1,2,1,2,1,1,1,1,1,4,2,2,3,1,18,11.0,neutral or dissatisfied +37998,102854,Female,Loyal Customer,52,Personal Travel,Eco,423,3,0,3,2,5,5,4,4,4,3,4,4,4,4,1,0.0,neutral or dissatisfied +37999,47564,Male,Loyal Customer,29,Personal Travel,Eco Plus,501,2,5,2,3,4,2,1,4,5,4,4,5,4,4,5,6.0,neutral or dissatisfied +38000,19808,Female,Loyal Customer,30,Business travel,Business,594,5,5,5,5,4,5,4,4,2,4,1,4,1,4,32,30.0,satisfied +38001,6109,Female,Loyal Customer,53,Personal Travel,Business,409,1,4,1,2,3,5,5,4,4,1,4,5,4,3,8,34.0,neutral or dissatisfied +38002,104755,Female,Loyal Customer,9,Personal Travel,Eco,1246,0,4,0,1,5,0,5,5,4,3,4,4,4,5,23,0.0,satisfied +38003,10575,Female,Loyal Customer,54,Business travel,Business,2953,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +38004,94404,Male,Loyal Customer,39,Business travel,Business,3724,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +38005,46204,Male,Loyal Customer,41,Business travel,Business,3942,2,2,2,2,4,4,4,2,2,2,2,3,2,4,0,1.0,satisfied +38006,105728,Female,Loyal Customer,47,Business travel,Business,2450,1,1,1,1,4,4,5,4,4,4,4,4,4,3,9,5.0,satisfied +38007,104521,Male,disloyal Customer,57,Business travel,Business,1256,2,2,2,4,2,2,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +38008,24181,Male,disloyal Customer,30,Business travel,Eco,302,2,5,2,5,4,2,4,4,5,2,1,3,2,4,0,0.0,neutral or dissatisfied +38009,103578,Female,Loyal Customer,60,Personal Travel,Eco,689,0,5,1,4,5,5,4,3,3,1,3,3,3,5,0,0.0,satisfied +38010,74553,Male,Loyal Customer,48,Business travel,Business,1431,3,3,3,3,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +38011,100429,Female,disloyal Customer,29,Business travel,Eco,120,3,0,4,3,5,4,5,5,3,4,2,2,3,5,0,9.0,neutral or dissatisfied +38012,43079,Male,Loyal Customer,47,Personal Travel,Eco,259,4,4,4,4,5,4,3,5,2,5,3,1,4,5,0,0.0,satisfied +38013,43615,Male,Loyal Customer,31,Business travel,Eco,190,0,0,0,3,4,5,2,4,1,3,2,2,4,4,0,3.0,satisfied +38014,67652,Female,Loyal Customer,44,Business travel,Business,2710,4,4,4,4,4,4,4,4,4,5,4,5,4,4,1,0.0,satisfied +38015,23934,Male,Loyal Customer,47,Business travel,Eco,616,4,3,3,3,4,4,4,4,2,1,3,2,4,4,0,0.0,satisfied +38016,77485,Female,Loyal Customer,53,Business travel,Business,989,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,5.0,satisfied +38017,118389,Female,disloyal Customer,22,Business travel,Eco,651,2,3,3,3,1,3,1,1,1,4,3,2,4,1,40,44.0,neutral or dissatisfied +38018,38332,Male,Loyal Customer,26,Business travel,Business,2427,5,5,5,5,5,5,5,5,3,3,4,5,3,5,0,0.0,satisfied +38019,31423,Male,Loyal Customer,36,Business travel,Business,1506,1,5,5,5,3,2,2,1,1,1,1,2,1,3,43,40.0,neutral or dissatisfied +38020,107050,Male,Loyal Customer,37,Business travel,Business,2273,4,4,4,4,3,3,4,4,4,4,4,3,4,4,7,8.0,neutral or dissatisfied +38021,90270,Female,Loyal Customer,27,Business travel,Business,2470,5,5,1,5,4,4,4,4,5,2,4,4,5,4,28,17.0,satisfied +38022,25197,Female,Loyal Customer,17,Business travel,Eco Plus,577,1,3,3,3,1,2,3,1,1,4,3,2,4,1,1,0.0,neutral or dissatisfied +38023,123041,Male,Loyal Customer,52,Business travel,Business,2628,1,1,1,1,3,5,5,4,4,4,4,5,4,3,19,21.0,satisfied +38024,125100,Male,Loyal Customer,43,Business travel,Eco,361,4,3,3,3,4,4,4,4,1,2,2,3,3,4,0,0.0,neutral or dissatisfied +38025,10511,Female,Loyal Customer,57,Business travel,Business,166,5,5,5,5,4,5,5,3,3,4,4,3,3,5,0,0.0,satisfied +38026,94273,Female,Loyal Customer,54,Business travel,Business,192,0,5,0,3,5,5,4,2,2,2,2,5,2,4,52,50.0,satisfied +38027,2964,Male,Loyal Customer,54,Personal Travel,Eco,737,1,5,1,1,4,1,4,4,5,4,5,4,4,4,0,5.0,neutral or dissatisfied +38028,84192,Female,Loyal Customer,54,Business travel,Business,432,3,3,4,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +38029,21499,Female,Loyal Customer,19,Personal Travel,Eco,399,1,4,1,1,4,1,4,4,3,1,1,1,3,4,0,0.0,neutral or dissatisfied +38030,110568,Female,Loyal Customer,62,Business travel,Business,2697,2,2,2,2,3,3,3,2,2,2,2,4,2,1,57,52.0,neutral or dissatisfied +38031,46023,Male,Loyal Customer,28,Business travel,Business,2745,2,2,2,2,5,5,5,5,2,1,4,2,2,5,5,3.0,satisfied +38032,12201,Female,Loyal Customer,46,Business travel,Business,253,3,3,5,3,2,5,5,4,4,4,4,3,4,4,49,49.0,satisfied +38033,108270,Female,Loyal Customer,57,Personal Travel,Eco,895,1,4,1,4,2,3,4,2,2,1,3,3,2,4,20,13.0,neutral or dissatisfied +38034,23878,Male,Loyal Customer,67,Business travel,Business,3446,2,1,1,1,1,2,3,2,2,2,2,4,2,3,8,24.0,neutral or dissatisfied +38035,116490,Male,Loyal Customer,62,Personal Travel,Eco,404,4,4,4,3,4,4,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +38036,33640,Female,Loyal Customer,38,Personal Travel,Eco,413,2,4,2,3,4,2,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +38037,88054,Female,Loyal Customer,47,Business travel,Business,2900,3,3,3,3,4,4,5,3,3,4,3,4,3,3,0,3.0,satisfied +38038,43909,Female,Loyal Customer,18,Personal Travel,Eco,255,3,5,0,3,1,0,1,1,2,3,3,2,2,1,0,0.0,neutral or dissatisfied +38039,129254,Female,Loyal Customer,62,Personal Travel,Eco,1235,2,4,2,3,4,4,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +38040,40793,Male,disloyal Customer,30,Business travel,Eco,599,3,3,3,3,1,3,1,1,2,4,2,5,1,1,0,2.0,neutral or dissatisfied +38041,128377,Female,disloyal Customer,36,Business travel,Business,647,3,3,3,3,2,3,4,2,5,5,4,5,5,2,5,4.0,neutral or dissatisfied +38042,101632,Female,Loyal Customer,31,Personal Travel,Eco,1139,3,4,3,3,2,3,2,2,4,3,5,5,5,2,14,0.0,neutral or dissatisfied +38043,93192,Female,Loyal Customer,37,Business travel,Business,896,5,5,5,5,2,5,5,2,2,2,2,4,2,3,34,17.0,satisfied +38044,95696,Male,Loyal Customer,41,Business travel,Business,1741,1,1,1,1,2,5,5,5,5,5,5,3,5,3,23,25.0,satisfied +38045,23754,Female,Loyal Customer,39,Business travel,Business,1554,2,4,3,4,3,2,3,2,2,2,2,3,2,3,78,93.0,neutral or dissatisfied +38046,61433,Female,Loyal Customer,41,Business travel,Business,2419,2,2,2,2,2,3,4,4,4,4,4,5,4,3,0,4.0,satisfied +38047,87882,Male,Loyal Customer,43,Personal Travel,Eco Plus,214,2,3,2,2,5,2,5,5,3,5,5,2,4,5,0,4.0,neutral or dissatisfied +38048,80425,Male,Loyal Customer,7,Business travel,Business,2248,3,2,2,2,3,3,3,3,2,3,3,4,3,3,43,29.0,neutral or dissatisfied +38049,80859,Male,Loyal Customer,49,Personal Travel,Eco,692,3,4,3,5,4,3,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +38050,100324,Male,disloyal Customer,12,Business travel,Business,1092,3,2,3,4,4,3,4,4,1,4,3,1,4,4,30,16.0,neutral or dissatisfied +38051,70434,Female,Loyal Customer,48,Business travel,Business,3494,5,5,2,5,5,5,5,5,3,4,4,5,5,5,148,200.0,satisfied +38052,87774,Female,Loyal Customer,54,Business travel,Business,2838,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +38053,27149,Male,disloyal Customer,20,Business travel,Eco,2640,2,2,2,3,2,3,3,1,3,3,3,3,1,3,0,0.0,neutral or dissatisfied +38054,124484,Female,Loyal Customer,59,Business travel,Business,930,2,2,5,2,3,5,5,4,4,4,4,5,4,5,114,78.0,satisfied +38055,12303,Female,Loyal Customer,48,Business travel,Business,3544,1,1,1,1,4,3,5,4,4,4,4,3,4,3,14,0.0,satisfied +38056,88717,Male,Loyal Customer,64,Personal Travel,Eco,581,3,5,3,4,5,3,5,5,3,2,5,3,5,5,0,12.0,neutral or dissatisfied +38057,43039,Male,Loyal Customer,57,Business travel,Business,2940,3,1,1,1,3,4,3,3,3,3,3,4,3,4,16,13.0,neutral or dissatisfied +38058,33496,Male,Loyal Customer,35,Personal Travel,Eco,2496,3,1,3,3,1,3,1,1,2,5,2,2,2,1,0,0.0,neutral or dissatisfied +38059,44267,Male,Loyal Customer,55,Personal Travel,Eco,118,2,3,2,3,3,2,5,3,1,4,5,2,3,3,0,0.0,neutral or dissatisfied +38060,20425,Female,Loyal Customer,26,Personal Travel,Eco,299,5,5,5,3,5,5,5,5,2,4,4,3,5,5,0,0.0,satisfied +38061,26116,Male,Loyal Customer,56,Business travel,Business,581,1,1,1,1,5,4,4,5,5,5,5,3,5,5,37,37.0,satisfied +38062,105392,Female,Loyal Customer,7,Personal Travel,Eco,369,2,1,2,4,4,2,4,4,1,2,4,3,4,4,0,0.0,neutral or dissatisfied +38063,89466,Male,disloyal Customer,39,Business travel,Business,134,1,1,1,2,4,1,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +38064,108611,Male,Loyal Customer,62,Personal Travel,Eco,696,4,5,4,4,5,4,5,5,4,5,5,3,5,5,28,19.0,neutral or dissatisfied +38065,29497,Female,Loyal Customer,42,Business travel,Eco,816,3,1,1,1,1,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +38066,1562,Male,disloyal Customer,22,Business travel,Business,140,0,0,0,4,1,0,1,1,4,2,5,4,5,1,0,0.0,satisfied +38067,27063,Female,Loyal Customer,31,Business travel,Business,1399,1,1,1,1,1,1,1,1,1,2,4,1,4,1,1,0.0,neutral or dissatisfied +38068,84764,Male,disloyal Customer,22,Business travel,Eco,481,0,5,0,1,1,0,1,1,3,2,4,4,5,1,0,0.0,satisfied +38069,18043,Male,Loyal Customer,29,Business travel,Business,488,4,2,2,2,4,4,4,4,4,4,1,2,1,4,118,94.0,neutral or dissatisfied +38070,77716,Female,disloyal Customer,35,Business travel,Business,874,2,2,2,4,4,2,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +38071,73041,Female,Loyal Customer,12,Personal Travel,Eco,1096,1,1,1,4,4,1,2,4,2,2,3,2,3,4,0,17.0,neutral or dissatisfied +38072,48756,Female,Loyal Customer,53,Business travel,Business,2917,2,2,4,2,5,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +38073,98635,Female,Loyal Customer,27,Business travel,Eco,920,3,1,1,1,3,3,3,3,2,4,4,4,3,3,70,58.0,neutral or dissatisfied +38074,129600,Male,disloyal Customer,39,Business travel,Eco,447,2,2,2,3,3,2,3,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +38075,37755,Female,disloyal Customer,20,Business travel,Eco Plus,1076,3,0,3,3,5,3,5,5,3,4,4,4,1,5,16,0.0,neutral or dissatisfied +38076,23393,Male,Loyal Customer,65,Business travel,Business,2733,1,3,3,3,3,4,3,1,1,1,1,3,1,3,6,3.0,neutral or dissatisfied +38077,120656,Male,Loyal Customer,70,Business travel,Eco,280,2,4,4,4,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +38078,59043,Male,Loyal Customer,34,Business travel,Business,1846,2,3,3,3,4,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +38079,124824,Female,Loyal Customer,61,Business travel,Eco,280,1,2,2,2,4,1,2,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +38080,20952,Male,Loyal Customer,41,Business travel,Eco,851,2,5,5,5,2,2,2,2,2,1,3,4,3,2,0,21.0,neutral or dissatisfied +38081,69533,Female,Loyal Customer,58,Business travel,Business,2475,5,5,5,5,5,5,5,5,4,3,5,5,3,5,0,11.0,satisfied +38082,78198,Female,disloyal Customer,24,Business travel,Eco,259,4,0,4,1,3,4,3,3,5,5,5,3,4,3,0,0.0,satisfied +38083,25218,Male,Loyal Customer,37,Business travel,Business,1921,2,2,2,2,5,3,2,5,5,5,5,4,5,4,65,61.0,satisfied +38084,97078,Male,disloyal Customer,45,Business travel,Business,1164,3,4,4,1,3,3,3,3,5,5,5,4,4,3,53,35.0,neutral or dissatisfied +38085,116131,Male,Loyal Customer,37,Personal Travel,Eco,337,2,5,2,4,1,2,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +38086,58748,Male,Loyal Customer,23,Business travel,Business,1182,1,1,1,1,2,2,2,2,5,3,5,5,5,2,5,0.0,satisfied +38087,70179,Male,Loyal Customer,52,Business travel,Business,258,1,1,1,1,5,4,4,4,4,4,4,5,4,3,0,5.0,satisfied +38088,17255,Male,Loyal Customer,44,Business travel,Business,472,3,2,2,2,3,3,3,3,5,4,3,3,4,3,351,336.0,neutral or dissatisfied +38089,99880,Female,disloyal Customer,29,Business travel,Eco Plus,1436,2,2,2,3,1,2,1,1,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +38090,18291,Male,Loyal Customer,41,Business travel,Eco,640,1,4,4,4,1,1,1,1,1,3,4,2,4,1,55,56.0,neutral or dissatisfied +38091,53690,Male,Loyal Customer,26,Business travel,Business,1984,4,4,4,4,4,4,4,4,4,5,3,1,5,4,0,0.0,satisfied +38092,32795,Female,disloyal Customer,27,Business travel,Eco,163,3,5,3,5,1,3,1,1,3,4,2,4,1,1,0,2.0,neutral or dissatisfied +38093,98763,Female,Loyal Customer,17,Business travel,Business,1814,2,5,5,5,2,2,2,2,3,4,4,3,3,2,23,11.0,neutral or dissatisfied +38094,16431,Female,Loyal Customer,29,Business travel,Eco,529,5,4,4,4,5,5,5,5,2,3,4,2,4,5,0,0.0,satisfied +38095,57824,Male,Loyal Customer,59,Personal Travel,Eco,622,2,5,2,3,2,2,2,2,4,2,5,4,5,2,0,13.0,neutral or dissatisfied +38096,123611,Male,Loyal Customer,34,Business travel,Eco Plus,1773,3,5,5,5,3,3,3,3,2,5,3,3,4,3,19,33.0,neutral or dissatisfied +38097,113573,Male,Loyal Customer,66,Business travel,Business,2951,4,2,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +38098,54105,Male,Loyal Customer,50,Business travel,Eco Plus,1416,4,1,1,1,4,4,4,4,1,1,2,4,1,4,0,0.0,satisfied +38099,99369,Female,Loyal Customer,33,Personal Travel,Eco,409,1,4,2,4,5,2,5,5,3,2,2,2,1,5,1,0.0,neutral or dissatisfied +38100,17446,Female,Loyal Customer,60,Personal Travel,Eco,376,1,4,1,3,2,5,4,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +38101,25283,Female,disloyal Customer,38,Business travel,Eco,321,1,0,0,4,1,0,1,1,1,2,2,1,4,1,8,33.0,neutral or dissatisfied +38102,111548,Female,Loyal Customer,58,Business travel,Business,883,5,5,5,5,5,4,5,4,4,4,4,4,4,4,8,1.0,satisfied +38103,117483,Male,Loyal Customer,33,Business travel,Eco,507,4,1,1,1,4,4,4,4,4,5,2,2,3,4,0,0.0,neutral or dissatisfied +38104,128311,Male,Loyal Customer,34,Business travel,Business,3872,1,1,1,1,2,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +38105,77230,Female,disloyal Customer,30,Business travel,Eco,1590,3,4,4,4,1,3,1,1,3,2,2,4,3,1,5,29.0,neutral or dissatisfied +38106,49455,Female,Loyal Customer,50,Business travel,Business,2399,3,3,3,3,3,2,2,5,5,5,5,5,5,2,0,0.0,satisfied +38107,114266,Female,Loyal Customer,53,Business travel,Eco,453,4,4,4,4,1,5,4,5,5,4,5,3,5,4,23,6.0,satisfied +38108,45723,Male,Loyal Customer,37,Personal Travel,Eco,852,3,5,3,5,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +38109,105774,Female,disloyal Customer,80,Business travel,Business,525,2,2,2,4,4,4,3,3,3,2,3,3,3,2,11,19.0,neutral or dissatisfied +38110,33157,Male,Loyal Customer,66,Personal Travel,Eco,163,1,4,1,4,1,1,1,1,5,5,4,5,3,1,13,13.0,neutral or dissatisfied +38111,88521,Male,Loyal Customer,59,Personal Travel,Eco,646,3,4,3,3,3,3,3,3,5,5,5,2,2,3,0,3.0,neutral or dissatisfied +38112,65962,Female,Loyal Customer,39,Business travel,Business,1372,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +38113,101731,Male,Loyal Customer,47,Personal Travel,Eco,1216,2,3,2,3,5,2,5,5,3,3,4,3,4,5,10,0.0,neutral or dissatisfied +38114,109168,Male,Loyal Customer,49,Business travel,Business,1729,5,5,5,5,2,4,4,5,5,5,5,4,5,4,5,5.0,satisfied +38115,86402,Female,Loyal Customer,47,Business travel,Business,749,2,3,2,2,4,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +38116,66678,Female,Loyal Customer,56,Business travel,Business,802,2,3,3,3,1,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +38117,21902,Female,Loyal Customer,40,Business travel,Eco,500,2,3,1,3,2,2,2,2,2,2,3,2,2,2,0,0.0,satisfied +38118,120013,Male,Loyal Customer,41,Personal Travel,Eco,328,4,4,4,2,3,4,3,3,5,4,5,3,5,3,0,0.0,satisfied +38119,44930,Female,Loyal Customer,56,Business travel,Business,397,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +38120,62849,Female,Loyal Customer,54,Business travel,Business,2583,4,4,4,4,3,3,5,5,5,5,5,3,5,3,0,0.0,satisfied +38121,12952,Female,Loyal Customer,15,Personal Travel,Eco,641,1,4,2,3,3,2,3,3,5,4,5,4,5,3,8,12.0,neutral or dissatisfied +38122,35222,Male,Loyal Customer,48,Business travel,Business,1069,2,2,4,2,3,3,3,4,4,4,4,3,4,1,17,22.0,satisfied +38123,106666,Female,Loyal Customer,60,Personal Travel,Eco,1590,1,5,1,3,4,3,5,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +38124,77850,Female,disloyal Customer,17,Business travel,Eco,731,5,5,5,4,4,5,5,4,2,4,3,3,3,4,9,0.0,satisfied +38125,80159,Female,Loyal Customer,56,Business travel,Business,2586,3,1,4,4,3,3,3,3,2,3,2,3,3,3,35,34.0,neutral or dissatisfied +38126,121477,Male,Loyal Customer,18,Personal Travel,Eco,331,3,4,3,4,5,3,3,5,2,2,4,2,4,5,0,0.0,neutral or dissatisfied +38127,54934,Male,Loyal Customer,57,Business travel,Business,2576,5,5,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +38128,100410,Female,Loyal Customer,17,Business travel,Business,3545,4,4,4,4,5,5,5,5,4,4,5,5,4,5,181,163.0,satisfied +38129,215,Male,Loyal Customer,34,Personal Travel,Eco,213,3,4,3,3,4,3,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +38130,89896,Female,disloyal Customer,36,Business travel,Eco,1416,4,4,4,3,4,4,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +38131,118054,Female,disloyal Customer,27,Business travel,Eco,1262,2,2,2,4,2,2,2,2,1,4,4,2,3,2,3,0.0,neutral or dissatisfied +38132,7706,Female,Loyal Customer,60,Personal Travel,Eco,767,3,5,3,3,5,4,5,4,4,3,4,5,4,5,0,1.0,neutral or dissatisfied +38133,70475,Female,Loyal Customer,60,Business travel,Business,867,1,1,1,1,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +38134,59297,Male,Loyal Customer,56,Personal Travel,Business,2556,2,2,2,4,2,3,4,5,5,2,5,3,5,2,2,0.0,neutral or dissatisfied +38135,109213,Male,Loyal Customer,41,Business travel,Business,483,2,2,2,2,4,1,5,4,4,4,4,1,4,1,0,0.0,satisfied +38136,109166,Female,disloyal Customer,44,Business travel,Business,722,2,2,2,4,4,2,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +38137,100864,Female,Loyal Customer,55,Business travel,Business,1605,2,1,2,2,5,5,5,3,4,5,5,5,5,5,271,250.0,satisfied +38138,91681,Female,Loyal Customer,41,Business travel,Business,2421,4,4,4,4,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +38139,13479,Female,Loyal Customer,40,Business travel,Business,227,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +38140,38386,Male,Loyal Customer,67,Personal Travel,Eco Plus,1133,4,4,4,3,3,4,3,3,5,3,4,5,4,3,0,3.0,neutral or dissatisfied +38141,120042,Female,Loyal Customer,57,Business travel,Business,168,4,1,4,4,3,5,5,5,5,4,4,5,5,4,1,30.0,satisfied +38142,84711,Female,Loyal Customer,50,Business travel,Business,547,2,2,2,2,3,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +38143,108501,Female,disloyal Customer,21,Business travel,Eco,287,3,2,3,4,3,3,2,3,3,3,3,3,4,3,0,29.0,neutral or dissatisfied +38144,93199,Male,Loyal Customer,51,Business travel,Business,2280,1,1,1,1,5,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +38145,51664,Female,Loyal Customer,57,Business travel,Business,2508,4,4,4,4,1,3,5,4,4,4,4,3,4,1,0,0.0,satisfied +38146,88278,Female,Loyal Customer,41,Business travel,Business,3860,2,2,2,2,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +38147,42872,Male,Loyal Customer,26,Business travel,Business,867,1,1,1,1,1,1,1,1,1,1,4,4,4,1,0,0.0,neutral or dissatisfied +38148,72219,Male,disloyal Customer,29,Business travel,Business,919,2,2,2,3,5,2,5,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +38149,73878,Male,Loyal Customer,28,Business travel,Business,2342,3,3,3,3,5,4,5,5,4,4,4,4,4,5,0,0.0,satisfied +38150,124783,Male,Loyal Customer,52,Business travel,Business,3539,4,4,4,4,4,4,5,4,4,4,4,5,4,4,25,18.0,satisfied +38151,57759,Male,disloyal Customer,33,Business travel,Business,2704,4,4,4,3,4,3,1,4,2,5,5,1,5,1,10,0.0,neutral or dissatisfied +38152,121299,Male,Loyal Customer,43,Business travel,Business,2495,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +38153,10271,Female,Loyal Customer,24,Personal Travel,Business,312,2,5,2,4,1,2,1,1,5,4,4,4,5,1,27,22.0,neutral or dissatisfied +38154,44939,Female,Loyal Customer,30,Business travel,Business,397,5,5,5,5,4,4,4,4,5,4,3,2,5,4,9,14.0,satisfied +38155,16846,Female,Loyal Customer,47,Business travel,Eco Plus,245,5,3,2,3,2,5,3,5,5,5,5,4,5,2,0,0.0,satisfied +38156,16792,Male,Loyal Customer,60,Personal Travel,Business,1017,3,4,3,4,5,4,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +38157,106784,Male,Loyal Customer,57,Personal Travel,Eco Plus,837,4,5,4,2,1,4,1,1,4,4,4,5,1,1,0,10.0,neutral or dissatisfied +38158,1082,Female,Loyal Customer,15,Personal Travel,Eco,158,3,2,3,2,4,3,4,4,1,2,2,1,2,4,0,1.0,neutral or dissatisfied +38159,3886,Female,Loyal Customer,46,Business travel,Business,213,2,2,2,2,5,5,5,4,4,5,4,3,4,5,0,27.0,satisfied +38160,60168,Female,Loyal Customer,15,Personal Travel,Eco,1120,4,4,4,1,2,4,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +38161,117136,Female,Loyal Customer,50,Personal Travel,Eco,304,0,5,0,2,5,4,5,5,5,0,5,4,5,3,94,84.0,satisfied +38162,80736,Female,disloyal Customer,42,Business travel,Business,393,5,5,5,1,3,5,3,3,5,2,4,5,5,3,0,0.0,satisfied +38163,104889,Female,disloyal Customer,21,Business travel,Eco,327,1,4,1,3,5,1,1,5,1,4,4,1,3,5,3,0.0,neutral or dissatisfied +38164,53191,Male,Loyal Customer,51,Business travel,Eco,612,4,3,3,3,4,4,4,4,3,2,5,1,1,4,0,0.0,satisfied +38165,99467,Female,Loyal Customer,67,Business travel,Business,3764,3,5,5,5,2,3,2,3,3,3,3,3,3,1,36,33.0,neutral or dissatisfied +38166,103250,Female,Loyal Customer,44,Business travel,Eco,267,3,1,1,1,5,1,2,2,2,3,2,4,2,5,0,0.0,satisfied +38167,51627,Female,Loyal Customer,15,Business travel,Business,370,4,1,1,1,4,4,4,4,4,5,3,2,3,4,13,12.0,neutral or dissatisfied +38168,11103,Female,Loyal Customer,66,Personal Travel,Eco,429,5,4,5,4,3,2,1,3,3,5,5,3,3,3,0,5.0,satisfied +38169,80659,Male,Loyal Customer,59,Business travel,Business,821,4,4,3,4,3,5,4,4,4,4,4,3,4,3,6,1.0,satisfied +38170,65014,Female,Loyal Customer,42,Business travel,Business,224,2,4,4,4,1,3,4,2,2,1,2,3,2,2,64,52.0,neutral or dissatisfied +38171,104723,Male,Loyal Customer,45,Business travel,Business,1407,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,9.0,satisfied +38172,114338,Female,Loyal Customer,29,Personal Travel,Eco,967,2,1,2,3,3,2,3,3,2,2,4,4,3,3,0,30.0,neutral or dissatisfied +38173,87782,Female,Loyal Customer,48,Business travel,Eco,214,1,0,0,3,5,4,3,1,1,1,1,3,1,2,46,49.0,neutral or dissatisfied +38174,101872,Male,disloyal Customer,35,Business travel,Eco,1747,2,2,2,3,5,2,1,5,3,4,3,3,1,5,11,0.0,neutral or dissatisfied +38175,82294,Female,Loyal Customer,66,Personal Travel,Eco Plus,1481,4,4,4,5,1,1,1,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +38176,4645,Male,disloyal Customer,33,Business travel,Business,364,3,3,3,2,2,3,2,2,3,4,5,5,4,2,0,6.0,neutral or dissatisfied +38177,4360,Female,Loyal Customer,40,Business travel,Business,2532,2,2,2,2,4,5,5,5,3,4,4,5,3,5,109,164.0,satisfied +38178,61216,Male,Loyal Customer,54,Business travel,Eco,862,2,2,2,2,2,2,2,2,4,1,3,1,3,2,5,10.0,neutral or dissatisfied +38179,80757,Male,Loyal Customer,53,Business travel,Business,3891,1,4,4,4,3,3,4,1,1,1,1,4,1,2,0,7.0,neutral or dissatisfied +38180,19017,Female,Loyal Customer,57,Business travel,Business,2988,1,3,2,3,5,3,3,1,1,2,1,1,1,1,21,8.0,neutral or dissatisfied +38181,122995,Female,Loyal Customer,42,Business travel,Business,2516,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,19.0,satisfied +38182,125925,Male,Loyal Customer,55,Personal Travel,Eco,861,1,4,1,2,1,1,1,1,4,4,5,5,5,1,1,13.0,neutral or dissatisfied +38183,22305,Female,Loyal Customer,51,Business travel,Eco,238,4,2,2,2,2,3,1,4,4,4,4,5,4,2,34,29.0,satisfied +38184,124106,Male,Loyal Customer,23,Business travel,Eco,529,3,5,2,5,3,3,2,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +38185,104912,Female,Loyal Customer,40,Business travel,Business,3265,5,5,5,5,5,5,5,5,5,5,5,4,5,5,87,88.0,satisfied +38186,10889,Male,Loyal Customer,21,Business travel,Eco,517,4,4,5,5,4,3,4,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +38187,59994,Female,Loyal Customer,20,Personal Travel,Eco,1023,4,3,4,3,3,4,3,3,4,1,3,1,3,3,71,100.0,neutral or dissatisfied +38188,5116,Male,Loyal Customer,17,Personal Travel,Eco,122,2,3,2,3,2,2,2,2,1,4,2,1,3,2,0,0.0,neutral or dissatisfied +38189,13447,Male,Loyal Customer,41,Personal Travel,Eco,475,1,5,1,1,3,1,3,3,5,1,2,3,5,3,0,0.0,neutral or dissatisfied +38190,50799,Female,Loyal Customer,59,Personal Travel,Eco,266,2,5,2,2,1,4,5,5,5,2,5,3,5,3,0,17.0,neutral or dissatisfied +38191,102873,Female,Loyal Customer,55,Business travel,Business,2322,2,5,5,5,3,4,4,2,2,2,2,3,2,3,27,27.0,neutral or dissatisfied +38192,41706,Male,disloyal Customer,29,Business travel,Eco,1404,4,4,4,4,3,4,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +38193,112047,Female,Loyal Customer,59,Personal Travel,Eco,1015,4,0,4,5,4,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +38194,6673,Male,Loyal Customer,45,Business travel,Business,258,3,3,3,3,5,5,5,4,4,4,4,5,4,4,30,41.0,satisfied +38195,58533,Male,Loyal Customer,43,Business travel,Eco Plus,719,3,4,4,4,3,3,3,3,3,5,3,4,3,3,1,0.0,neutral or dissatisfied +38196,76481,Female,Loyal Customer,47,Business travel,Business,547,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +38197,32371,Male,disloyal Customer,25,Business travel,Eco,101,0,0,0,5,3,0,3,3,4,1,4,3,4,3,0,0.0,satisfied +38198,80,Female,Loyal Customer,46,Personal Travel,Eco,173,1,1,1,3,1,3,4,5,5,1,5,1,5,3,45,29.0,neutral or dissatisfied +38199,46175,Male,Loyal Customer,22,Personal Travel,Eco,604,1,4,1,3,2,1,2,2,3,4,5,3,5,2,30,16.0,neutral or dissatisfied +38200,59275,Female,Loyal Customer,48,Business travel,Business,1802,2,2,2,2,5,5,5,4,5,5,4,5,4,5,0,0.0,satisfied +38201,58373,Male,Loyal Customer,51,Business travel,Business,528,4,2,2,2,2,4,4,4,4,4,4,1,4,3,4,4.0,neutral or dissatisfied +38202,53414,Male,Loyal Customer,33,Business travel,Business,2419,2,2,2,2,4,4,4,2,3,4,1,4,5,4,0,14.0,satisfied +38203,115675,Female,Loyal Customer,40,Business travel,Business,480,2,2,5,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +38204,29160,Male,Loyal Customer,33,Business travel,Eco Plus,1050,2,1,1,1,2,2,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +38205,29212,Female,Loyal Customer,68,Personal Travel,Eco,2311,3,5,3,5,1,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +38206,34599,Male,Loyal Customer,10,Personal Travel,Eco,1617,3,2,3,4,4,3,4,4,1,3,4,4,3,4,33,31.0,neutral or dissatisfied +38207,10750,Female,disloyal Customer,33,Business travel,Eco,201,2,2,2,3,5,2,5,5,2,5,3,2,3,5,43,37.0,neutral or dissatisfied +38208,87678,Male,Loyal Customer,29,Business travel,Business,1898,4,2,2,2,4,4,4,4,1,3,4,2,4,4,8,12.0,neutral or dissatisfied +38209,122840,Female,disloyal Customer,23,Business travel,Business,226,0,0,0,2,5,0,5,5,5,4,5,4,4,5,7,9.0,satisfied +38210,32239,Male,Loyal Customer,57,Business travel,Business,3284,1,1,1,1,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +38211,57842,Male,Loyal Customer,63,Personal Travel,Eco,1491,1,5,1,5,1,1,1,1,4,5,5,3,4,1,0,53.0,neutral or dissatisfied +38212,51073,Female,Loyal Customer,41,Personal Travel,Eco,262,1,3,1,3,2,1,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +38213,53396,Male,Loyal Customer,55,Business travel,Business,2419,5,5,5,5,5,5,5,5,2,3,5,5,5,5,0,0.0,satisfied +38214,29605,Female,Loyal Customer,18,Business travel,Business,1448,1,1,1,1,4,4,4,4,5,3,3,1,2,4,0,15.0,satisfied +38215,119048,Female,Loyal Customer,55,Business travel,Business,2279,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +38216,80026,Female,Loyal Customer,40,Personal Travel,Eco,1076,3,1,4,3,2,4,1,2,3,5,3,1,4,2,20,13.0,neutral or dissatisfied +38217,102798,Male,disloyal Customer,62,Business travel,Business,342,2,2,2,4,1,2,1,1,3,5,4,4,4,1,0,17.0,satisfied +38218,18471,Female,Loyal Customer,34,Business travel,Eco,127,5,4,4,4,5,5,5,5,4,5,3,4,2,5,0,0.0,satisfied +38219,21445,Male,Loyal Customer,37,Business travel,Business,331,3,2,2,2,1,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +38220,58406,Female,Loyal Customer,38,Business travel,Business,733,5,5,5,5,3,3,3,3,5,5,5,3,4,3,132,115.0,satisfied +38221,83851,Male,Loyal Customer,28,Personal Travel,Eco,425,5,5,5,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +38222,12606,Male,Loyal Customer,68,Personal Travel,Eco,542,3,5,3,3,3,3,3,3,1,1,4,3,5,3,0,0.0,neutral or dissatisfied +38223,51622,Female,Loyal Customer,49,Business travel,Eco,451,3,5,5,5,2,3,2,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +38224,685,Male,Loyal Customer,54,Business travel,Business,309,2,4,4,4,5,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +38225,110675,Female,Loyal Customer,52,Business travel,Business,2850,2,3,3,3,2,3,3,2,2,2,2,3,2,4,33,33.0,neutral or dissatisfied +38226,121312,Female,Loyal Customer,59,Business travel,Eco,1009,3,1,1,1,5,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +38227,13920,Female,disloyal Customer,54,Business travel,Eco,153,2,3,2,3,1,2,1,1,1,5,3,4,5,1,53,44.0,neutral or dissatisfied +38228,65407,Female,Loyal Customer,18,Personal Travel,Eco,631,2,5,1,1,3,1,3,3,4,3,1,5,3,3,1,0.0,neutral or dissatisfied +38229,91479,Female,Loyal Customer,33,Personal Travel,Eco,859,3,3,3,4,1,3,1,1,4,4,4,3,3,1,0,63.0,neutral or dissatisfied +38230,6986,Male,disloyal Customer,57,Business travel,Business,234,2,2,2,3,5,2,5,5,1,3,3,2,4,5,33,27.0,neutral or dissatisfied +38231,57038,Male,Loyal Customer,34,Personal Travel,Eco Plus,2565,2,1,2,1,2,1,1,4,1,2,2,1,1,1,0,2.0,neutral or dissatisfied +38232,48119,Male,Loyal Customer,46,Business travel,Eco,391,4,1,5,1,3,4,3,3,4,4,3,5,3,3,0,0.0,satisfied +38233,12963,Female,Loyal Customer,39,Business travel,Eco Plus,359,1,4,5,4,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +38234,17375,Male,Loyal Customer,8,Business travel,Business,533,1,1,5,1,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +38235,36195,Male,disloyal Customer,24,Business travel,Eco,496,4,3,4,1,2,4,2,2,5,3,5,4,2,2,0,0.0,satisfied +38236,22405,Male,Loyal Customer,51,Business travel,Business,143,1,1,1,1,4,3,5,5,5,5,4,3,5,5,16,16.0,satisfied +38237,17111,Female,Loyal Customer,49,Personal Travel,Eco,416,2,5,2,4,4,3,1,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +38238,22517,Female,disloyal Customer,38,Business travel,Eco Plus,238,4,4,4,1,4,4,4,4,4,2,1,2,4,4,0,0.0,neutral or dissatisfied +38239,102456,Female,Loyal Customer,52,Personal Travel,Eco,414,4,4,4,5,1,4,4,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +38240,126456,Female,disloyal Customer,42,Business travel,Business,1788,1,0,0,2,3,1,4,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +38241,107600,Male,Loyal Customer,50,Business travel,Business,423,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +38242,120968,Female,Loyal Customer,42,Business travel,Business,1013,1,1,1,1,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +38243,67264,Female,Loyal Customer,35,Personal Travel,Eco,985,4,4,4,3,1,4,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +38244,120076,Male,Loyal Customer,41,Business travel,Business,1508,2,5,5,5,1,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +38245,42892,Male,disloyal Customer,34,Business travel,Eco,368,3,0,3,1,4,3,4,4,3,4,3,1,5,4,0,0.0,neutral or dissatisfied +38246,104306,Female,disloyal Customer,24,Business travel,Eco,452,2,0,2,4,3,2,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +38247,79689,Male,Loyal Customer,20,Personal Travel,Eco,762,3,4,3,3,1,3,1,1,5,4,5,4,4,1,87,70.0,neutral or dissatisfied +38248,116381,Male,Loyal Customer,52,Personal Travel,Eco,372,4,4,4,4,2,4,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +38249,59889,Female,disloyal Customer,24,Business travel,Eco,937,3,3,3,3,2,3,2,2,4,3,5,5,4,2,5,0.0,neutral or dissatisfied +38250,4872,Male,Loyal Customer,37,Personal Travel,Eco,500,2,4,2,1,2,3,3,5,2,4,4,3,3,3,215,203.0,neutral or dissatisfied +38251,85557,Female,Loyal Customer,49,Business travel,Business,153,0,4,0,3,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +38252,96239,Male,Loyal Customer,25,Business travel,Business,687,1,2,2,2,1,1,1,1,2,3,3,2,3,1,25,20.0,neutral or dissatisfied +38253,12814,Female,disloyal Customer,59,Business travel,Eco,489,3,1,3,4,3,3,3,3,4,1,3,1,3,3,4,0.0,neutral or dissatisfied +38254,113566,Female,Loyal Customer,60,Business travel,Business,2024,1,5,4,5,5,4,4,1,1,1,1,2,1,1,4,7.0,neutral or dissatisfied +38255,119924,Female,Loyal Customer,34,Business travel,Business,868,3,3,5,3,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +38256,73722,Female,Loyal Customer,50,Business travel,Eco,204,5,4,4,4,3,1,5,5,5,5,5,4,5,2,26,17.0,satisfied +38257,63384,Female,Loyal Customer,35,Personal Travel,Eco,337,5,4,5,4,1,5,1,1,4,4,5,5,4,1,0,5.0,satisfied +38258,123748,Male,Loyal Customer,17,Personal Travel,Eco,96,2,5,2,3,5,2,4,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +38259,78688,Male,Loyal Customer,23,Personal Travel,Eco,761,3,4,3,3,2,3,2,2,5,3,5,4,5,2,0,8.0,neutral or dissatisfied +38260,95222,Male,Loyal Customer,32,Personal Travel,Eco,192,0,5,0,3,2,0,5,2,4,2,5,3,4,2,0,0.0,satisfied +38261,48864,Male,Loyal Customer,34,Business travel,Business,109,5,3,5,5,4,2,3,4,4,4,5,4,4,5,22,25.0,satisfied +38262,31329,Male,Loyal Customer,41,Personal Travel,Eco Plus,1123,3,1,3,3,2,3,2,2,3,3,3,2,4,2,4,33.0,neutral or dissatisfied +38263,32049,Male,Loyal Customer,30,Business travel,Business,1524,1,1,5,1,5,5,3,5,2,3,2,2,3,5,0,0.0,satisfied +38264,1446,Female,Loyal Customer,30,Business travel,Business,772,1,1,4,1,5,4,5,5,4,4,5,3,5,5,6,0.0,satisfied +38265,31233,Male,Loyal Customer,27,Business travel,Business,1960,5,5,5,5,4,4,4,4,4,2,1,2,3,4,0,0.0,satisfied +38266,6352,Female,Loyal Customer,53,Business travel,Business,3451,0,0,0,3,3,5,4,3,3,3,5,3,3,3,0,0.0,satisfied +38267,18942,Female,Loyal Customer,46,Personal Travel,Eco,448,1,4,2,1,3,4,4,1,1,2,1,3,1,3,18,13.0,neutral or dissatisfied +38268,31636,Male,Loyal Customer,44,Business travel,Eco,967,3,4,4,4,3,3,3,3,1,1,3,2,3,3,1,0.0,satisfied +38269,12291,Male,Loyal Customer,39,Business travel,Eco,192,5,4,4,4,5,5,5,5,2,2,1,2,5,5,0,0.0,satisfied +38270,57,Female,Loyal Customer,56,Business travel,Business,67,1,1,1,1,2,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +38271,103835,Male,Loyal Customer,70,Business travel,Business,2849,2,4,4,4,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +38272,84122,Female,Loyal Customer,19,Personal Travel,Eco,1900,2,4,2,1,5,2,5,5,5,2,3,3,5,5,80,75.0,neutral or dissatisfied +38273,9504,Male,Loyal Customer,56,Personal Travel,Eco,239,2,4,2,2,4,2,4,4,4,3,4,3,5,4,11,11.0,neutral or dissatisfied +38274,54143,Male,Loyal Customer,47,Business travel,Business,1400,3,3,3,3,4,4,1,4,4,4,4,3,4,2,65,79.0,satisfied +38275,40658,Male,Loyal Customer,56,Business travel,Business,558,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +38276,11611,Female,Loyal Customer,51,Personal Travel,Eco,771,3,4,3,3,5,4,4,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +38277,87114,Female,Loyal Customer,33,Personal Travel,Eco,594,4,1,4,4,4,4,4,4,3,2,3,3,4,4,0,0.0,satisfied +38278,129047,Male,Loyal Customer,56,Business travel,Business,1846,2,5,5,5,1,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +38279,14905,Male,Loyal Customer,23,Personal Travel,Eco,315,3,2,3,2,2,3,2,2,1,3,2,1,3,2,0,0.0,neutral or dissatisfied +38280,7380,Female,Loyal Customer,49,Business travel,Business,2932,5,5,5,5,2,5,4,5,5,5,5,3,5,4,35,34.0,satisfied +38281,10874,Male,Loyal Customer,42,Business travel,Business,2963,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +38282,19294,Male,Loyal Customer,38,Business travel,Business,299,3,3,3,3,1,4,3,3,3,3,3,4,3,1,0,14.0,neutral or dissatisfied +38283,13519,Male,Loyal Customer,26,Business travel,Business,227,5,5,5,5,4,4,4,4,4,5,4,3,4,4,2,0.0,satisfied +38284,108076,Female,Loyal Customer,48,Business travel,Business,3771,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +38285,104620,Male,Loyal Customer,36,Business travel,Business,2220,3,3,3,3,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +38286,26895,Female,Loyal Customer,23,Business travel,Eco Plus,689,3,5,5,5,3,3,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +38287,116353,Female,Loyal Customer,12,Personal Travel,Eco,372,1,2,1,3,3,1,3,3,2,5,3,1,3,3,2,23.0,neutral or dissatisfied +38288,39449,Male,Loyal Customer,32,Personal Travel,Eco,129,1,2,1,3,3,1,4,3,4,4,3,1,4,3,0,9.0,neutral or dissatisfied +38289,89391,Female,disloyal Customer,27,Business travel,Business,134,2,2,2,1,5,2,1,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +38290,30571,Female,Loyal Customer,30,Business travel,Business,1570,1,2,1,1,2,2,2,2,4,3,2,5,2,2,0,0.0,satisfied +38291,123275,Female,Loyal Customer,11,Personal Travel,Eco,468,1,4,1,3,2,1,2,2,5,5,5,4,4,2,9,2.0,neutral or dissatisfied +38292,105865,Female,Loyal Customer,35,Personal Travel,Eco Plus,919,1,5,1,5,1,2,2,3,2,4,4,2,5,2,327,313.0,neutral or dissatisfied +38293,66021,Male,Loyal Customer,51,Business travel,Business,2130,3,3,3,3,4,4,4,4,4,4,4,4,4,4,14,15.0,satisfied +38294,52831,Male,Loyal Customer,44,Business travel,Business,1721,3,3,3,3,2,3,2,4,4,4,4,1,4,4,0,0.0,satisfied +38295,110259,Female,Loyal Customer,53,Business travel,Business,1789,5,5,5,5,4,4,5,2,2,2,2,3,2,4,59,56.0,satisfied +38296,113321,Male,Loyal Customer,53,Business travel,Business,226,4,4,4,4,3,4,5,5,5,5,5,5,5,5,11,0.0,satisfied +38297,44617,Female,Loyal Customer,68,Personal Travel,Eco,566,1,5,1,2,3,4,5,5,5,1,2,3,5,5,5,10.0,neutral or dissatisfied +38298,81091,Female,Loyal Customer,20,Personal Travel,Eco,931,4,4,4,4,5,4,4,5,1,3,3,4,3,5,0,0.0,neutral or dissatisfied +38299,19694,Female,disloyal Customer,36,Business travel,Eco,409,1,0,1,5,5,1,5,5,5,4,4,2,4,5,0,0.0,neutral or dissatisfied +38300,104742,Male,Loyal Customer,59,Business travel,Eco,1246,2,5,5,5,2,2,2,2,3,2,2,1,2,2,10,6.0,neutral or dissatisfied +38301,6443,Female,Loyal Customer,47,Personal Travel,Eco,296,4,4,4,5,3,4,5,3,3,4,3,4,3,3,0,4.0,neutral or dissatisfied +38302,101402,Female,Loyal Customer,36,Personal Travel,Eco,486,1,4,1,3,1,1,1,1,3,4,4,5,4,1,27,14.0,neutral or dissatisfied +38303,63418,Female,Loyal Customer,17,Personal Travel,Eco,372,4,0,4,4,1,4,1,1,5,4,4,5,4,1,0,0.0,satisfied +38304,126210,Female,Loyal Customer,25,Business travel,Eco,631,4,2,4,2,4,4,4,4,2,2,4,2,4,4,3,17.0,neutral or dissatisfied +38305,65275,Male,Loyal Customer,36,Personal Travel,Eco Plus,190,3,5,3,3,1,3,5,1,2,4,1,4,1,1,0,2.0,neutral or dissatisfied +38306,42381,Female,Loyal Customer,43,Personal Travel,Eco,329,3,4,3,4,3,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +38307,8514,Female,Loyal Customer,44,Business travel,Eco,462,5,5,5,5,3,5,3,4,4,5,4,1,4,1,0,2.0,satisfied +38308,127574,Male,Loyal Customer,69,Personal Travel,Eco,1670,3,3,3,4,5,3,4,5,3,5,4,3,3,5,22,0.0,neutral or dissatisfied +38309,38566,Female,Loyal Customer,55,Personal Travel,Eco,2586,1,5,1,4,1,5,4,1,1,4,5,4,4,4,176,160.0,neutral or dissatisfied +38310,34694,Female,Loyal Customer,58,Business travel,Business,301,3,1,4,1,3,3,3,3,3,3,3,3,3,4,23,12.0,neutral or dissatisfied +38311,129179,Female,Loyal Customer,43,Business travel,Eco Plus,954,3,4,4,4,3,2,2,4,4,3,4,4,4,2,12,1.0,neutral or dissatisfied +38312,2937,Male,Loyal Customer,31,Business travel,Business,2939,2,2,2,2,2,3,2,2,4,5,4,4,4,2,14,11.0,satisfied +38313,69999,Female,Loyal Customer,45,Personal Travel,Eco,236,1,4,1,2,2,4,5,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +38314,36139,Female,Loyal Customer,26,Personal Travel,Eco,1609,1,2,2,3,5,2,4,5,1,5,4,1,3,5,0,1.0,neutral or dissatisfied +38315,33754,Male,Loyal Customer,47,Business travel,Business,3037,4,4,4,4,2,2,1,3,3,4,3,2,3,3,4,10.0,satisfied +38316,33572,Male,Loyal Customer,52,Business travel,Business,2491,4,4,4,4,3,2,1,4,4,4,4,1,4,2,0,0.0,satisfied +38317,83061,Female,Loyal Customer,42,Business travel,Eco,983,4,2,2,2,3,2,2,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +38318,54482,Male,Loyal Customer,50,Business travel,Eco,925,3,4,4,4,3,3,3,3,2,3,1,2,2,3,0,0.0,neutral or dissatisfied +38319,23893,Female,Loyal Customer,39,Business travel,Business,1939,1,4,4,4,1,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +38320,37172,Female,Loyal Customer,9,Personal Travel,Eco,1046,3,4,2,5,2,2,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +38321,52445,Male,Loyal Customer,58,Personal Travel,Eco,369,1,1,1,2,2,1,2,2,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +38322,23809,Female,Loyal Customer,47,Personal Travel,Eco,374,2,4,2,3,4,3,3,3,3,2,5,1,3,3,0,0.0,neutral or dissatisfied +38323,127133,Female,Loyal Customer,65,Personal Travel,Eco,338,3,2,2,3,2,3,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +38324,44003,Male,Loyal Customer,39,Business travel,Eco,397,2,3,3,3,2,2,2,2,3,4,1,4,2,2,31,27.0,neutral or dissatisfied +38325,19711,Male,Loyal Customer,46,Business travel,Business,1866,4,1,1,1,1,3,3,4,4,4,4,2,4,4,11,8.0,neutral or dissatisfied +38326,101523,Female,Loyal Customer,37,Personal Travel,Eco,345,3,4,3,4,4,3,4,4,1,2,3,1,3,4,6,0.0,neutral or dissatisfied +38327,95538,Female,Loyal Customer,18,Personal Travel,Eco Plus,239,2,4,2,3,4,2,4,4,3,4,3,3,4,4,31,31.0,neutral or dissatisfied +38328,109873,Male,Loyal Customer,45,Business travel,Business,2757,1,1,1,1,3,5,5,4,4,4,4,5,4,4,7,0.0,satisfied +38329,41994,Male,Loyal Customer,43,Business travel,Business,3710,2,2,2,2,5,2,4,4,4,4,3,3,4,5,0,7.0,satisfied +38330,8764,Female,Loyal Customer,60,Business travel,Business,3373,3,4,3,4,2,3,4,3,3,3,3,3,3,2,0,29.0,neutral or dissatisfied +38331,18269,Female,Loyal Customer,39,Personal Travel,Eco,235,2,4,2,1,1,2,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +38332,125593,Male,Loyal Customer,32,Business travel,Business,1587,1,1,1,1,5,5,5,5,4,4,3,4,4,5,0,0.0,satisfied +38333,86620,Female,Loyal Customer,42,Business travel,Business,1893,1,4,1,1,3,5,5,4,4,4,4,4,4,5,4,0.0,satisfied +38334,60531,Male,Loyal Customer,57,Personal Travel,Eco,862,4,4,4,1,3,4,3,3,5,2,4,5,5,3,17,5.0,neutral or dissatisfied +38335,123931,Female,Loyal Customer,46,Personal Travel,Eco,541,3,4,3,2,3,5,4,1,1,3,1,5,1,4,0,1.0,neutral or dissatisfied +38336,18353,Female,Loyal Customer,70,Personal Travel,Business,314,2,2,2,2,3,3,2,4,4,2,2,4,4,1,81,93.0,neutral or dissatisfied +38337,33087,Female,Loyal Customer,40,Personal Travel,Eco,102,0,4,0,4,1,0,1,1,4,4,4,5,5,1,0,0.0,satisfied +38338,70417,Male,Loyal Customer,53,Personal Travel,Eco Plus,1562,5,5,5,1,2,5,2,2,4,3,4,3,4,2,26,21.0,satisfied +38339,119342,Male,Loyal Customer,66,Personal Travel,Eco,214,3,2,3,3,2,3,2,2,2,4,2,1,3,2,0,0.0,neutral or dissatisfied +38340,4956,Male,disloyal Customer,22,Business travel,Business,931,5,4,5,1,4,5,4,4,4,3,5,3,5,4,0,0.0,satisfied +38341,115453,Male,Loyal Customer,59,Business travel,Business,2927,0,0,0,3,3,5,5,5,5,5,5,3,5,4,3,0.0,satisfied +38342,79939,Male,Loyal Customer,46,Business travel,Business,1069,2,3,4,3,2,2,2,4,4,3,3,2,1,2,218,199.0,neutral or dissatisfied +38343,89705,Male,Loyal Customer,64,Personal Travel,Eco,1035,4,1,4,3,4,5,5,1,2,3,3,5,2,5,250,253.0,neutral or dissatisfied +38344,112085,Male,Loyal Customer,50,Personal Travel,Eco,1491,2,3,2,3,2,2,2,2,2,2,2,1,4,2,10,12.0,neutral or dissatisfied +38345,100591,Female,Loyal Customer,26,Personal Travel,Eco,486,3,0,3,2,3,3,3,3,3,4,4,3,4,3,45,38.0,neutral or dissatisfied +38346,110286,Female,Loyal Customer,43,Business travel,Business,925,5,5,5,5,4,5,5,4,4,4,4,4,4,5,48,30.0,satisfied +38347,71335,Female,Loyal Customer,62,Personal Travel,Eco,1514,3,4,3,3,5,3,3,1,1,3,1,4,1,4,80,66.0,neutral or dissatisfied +38348,83255,Female,Loyal Customer,9,Business travel,Business,1979,2,2,2,2,5,5,5,5,3,2,5,4,5,5,0,5.0,satisfied +38349,94638,Female,Loyal Customer,43,Business travel,Business,3941,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +38350,52477,Male,Loyal Customer,7,Personal Travel,Eco Plus,451,3,4,2,3,3,2,3,3,4,4,4,3,4,3,25,21.0,neutral or dissatisfied +38351,1459,Male,Loyal Customer,56,Business travel,Business,2697,2,1,1,1,3,4,3,2,2,2,2,3,2,4,0,32.0,neutral or dissatisfied +38352,106646,Male,Loyal Customer,25,Business travel,Business,2558,4,4,4,4,4,4,4,4,5,4,5,5,5,4,10,5.0,satisfied +38353,22489,Male,Loyal Customer,63,Personal Travel,Eco,208,2,4,2,3,5,2,5,5,1,5,3,3,4,5,0,0.0,neutral or dissatisfied +38354,76416,Male,Loyal Customer,65,Business travel,Business,1849,3,3,3,3,3,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +38355,62997,Male,Loyal Customer,15,Business travel,Business,3508,3,3,3,3,4,5,4,4,3,5,4,3,5,4,0,0.0,satisfied +38356,116261,Female,Loyal Customer,49,Personal Travel,Eco,390,3,5,3,2,2,5,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +38357,11607,Male,Loyal Customer,61,Personal Travel,Eco,657,2,5,2,3,2,3,3,5,5,5,5,3,5,3,132,120.0,neutral or dissatisfied +38358,34512,Male,disloyal Customer,39,Business travel,Business,1121,1,0,0,2,3,0,3,3,5,3,2,4,3,3,0,4.0,neutral or dissatisfied +38359,54413,Female,Loyal Customer,43,Business travel,Business,3873,4,4,4,4,3,2,3,4,4,3,4,1,4,4,13,8.0,neutral or dissatisfied +38360,62911,Male,disloyal Customer,22,Business travel,Eco,862,2,2,2,1,2,2,2,2,3,3,5,5,4,2,90,77.0,neutral or dissatisfied +38361,83412,Female,disloyal Customer,49,Business travel,Business,632,4,4,4,3,2,4,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +38362,86377,Female,Loyal Customer,60,Business travel,Business,749,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +38363,14850,Female,Loyal Customer,48,Business travel,Eco,343,4,1,1,1,5,2,4,4,4,4,4,4,4,3,16,50.0,satisfied +38364,32275,Male,disloyal Customer,39,Business travel,Business,216,4,4,4,1,3,4,3,3,2,5,3,5,3,3,0,7.0,satisfied +38365,127192,Female,Loyal Customer,34,Business travel,Eco Plus,370,1,1,1,1,1,1,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +38366,127525,Female,Loyal Customer,16,Business travel,Business,2374,3,5,3,3,4,4,4,4,4,3,4,5,4,4,6,28.0,satisfied +38367,63162,Male,Loyal Customer,60,Business travel,Business,3537,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +38368,86940,Female,Loyal Customer,8,Personal Travel,Business,907,4,4,4,1,4,4,4,4,4,4,4,4,4,4,4,1.0,neutral or dissatisfied +38369,95662,Female,Loyal Customer,52,Business travel,Business,928,4,4,4,4,2,4,5,4,4,4,4,4,4,3,0,1.0,satisfied +38370,105788,Male,Loyal Customer,26,Personal Travel,Eco,925,3,5,3,2,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +38371,80666,Male,Loyal Customer,20,Business travel,Eco,821,2,4,4,4,2,2,1,2,3,2,4,4,3,2,0,0.0,neutral or dissatisfied +38372,14807,Female,Loyal Customer,17,Business travel,Business,95,2,2,4,2,4,4,3,4,2,3,3,1,4,4,0,0.0,satisfied +38373,11594,Female,Loyal Customer,7,Business travel,Business,1998,2,3,3,3,2,2,2,2,3,2,4,1,3,2,15,14.0,neutral or dissatisfied +38374,40173,Female,Loyal Customer,52,Business travel,Business,3042,2,4,2,2,1,5,5,4,4,4,4,4,4,2,0,0.0,satisfied +38375,109562,Male,Loyal Customer,26,Personal Travel,Eco,861,2,4,2,4,4,2,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +38376,91850,Female,Loyal Customer,48,Personal Travel,Eco,1619,0,4,0,4,4,3,4,2,2,0,2,4,2,3,0,0.0,satisfied +38377,120841,Female,Loyal Customer,47,Business travel,Business,2014,3,1,1,1,5,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +38378,23819,Female,Loyal Customer,33,Personal Travel,Eco,374,3,3,3,3,4,3,4,4,3,2,5,5,5,4,5,35.0,neutral or dissatisfied +38379,7566,Male,Loyal Customer,45,Business travel,Business,3772,5,5,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +38380,983,Female,Loyal Customer,48,Business travel,Business,3783,4,4,4,4,2,1,2,5,5,5,5,4,5,3,0,1.0,satisfied +38381,45911,Female,disloyal Customer,25,Business travel,Eco,775,3,3,3,4,5,3,5,5,3,1,4,1,4,5,0,11.0,neutral or dissatisfied +38382,106759,Female,Loyal Customer,68,Personal Travel,Eco,945,4,3,4,2,2,2,3,2,2,4,4,5,2,2,26,27.0,satisfied +38383,123442,Male,Loyal Customer,47,Business travel,Business,2125,4,4,4,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +38384,89070,Male,Loyal Customer,40,Business travel,Business,1947,5,5,5,5,2,3,5,4,4,4,4,4,4,5,9,0.0,satisfied +38385,73447,Male,Loyal Customer,14,Personal Travel,Eco,1197,4,4,4,4,4,4,3,4,5,4,4,4,5,4,17,0.0,satisfied +38386,75788,Female,Loyal Customer,47,Personal Travel,Eco,813,2,1,1,3,5,2,3,1,1,1,1,2,1,3,7,0.0,neutral or dissatisfied +38387,68295,Female,Loyal Customer,20,Business travel,Business,1797,5,5,5,5,5,5,5,5,4,3,3,5,4,5,0,3.0,satisfied +38388,67009,Female,Loyal Customer,54,Business travel,Business,3850,2,2,2,2,2,5,5,3,3,3,3,3,3,4,11,16.0,satisfied +38389,85739,Male,Loyal Customer,46,Business travel,Business,666,1,1,1,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +38390,123524,Male,Loyal Customer,30,Personal Travel,Eco,2296,3,3,3,3,5,3,5,5,4,3,4,1,3,5,1,0.0,neutral or dissatisfied +38391,112729,Male,Loyal Customer,54,Personal Travel,Eco,605,1,5,1,2,5,1,5,5,4,2,4,4,5,5,25,23.0,neutral or dissatisfied +38392,7538,Male,Loyal Customer,30,Personal Travel,Eco,762,3,5,3,4,4,3,2,4,3,2,4,4,4,4,0,3.0,neutral or dissatisfied +38393,10281,Female,Loyal Customer,59,Business travel,Business,247,2,2,2,2,2,5,4,4,4,4,4,4,4,3,29,23.0,satisfied +38394,49194,Female,disloyal Customer,33,Business travel,Eco,89,1,4,2,3,5,2,4,5,5,4,3,4,5,5,0,0.0,neutral or dissatisfied +38395,50096,Male,Loyal Customer,42,Business travel,Business,86,2,4,4,4,3,2,3,3,3,3,2,2,3,4,34,63.0,neutral or dissatisfied +38396,58695,Female,Loyal Customer,25,Business travel,Business,4243,4,4,4,4,4,4,4,5,2,5,5,4,5,4,5,0.0,satisfied +38397,73242,Female,Loyal Customer,47,Business travel,Business,3840,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +38398,99414,Male,Loyal Customer,36,Business travel,Business,314,4,4,2,4,2,1,3,4,4,4,4,3,4,4,2,28.0,satisfied +38399,5349,Female,disloyal Customer,29,Business travel,Business,812,1,1,1,2,4,1,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +38400,59130,Female,Loyal Customer,7,Personal Travel,Eco,1744,1,2,1,3,4,1,4,4,2,4,4,4,4,4,15,0.0,neutral or dissatisfied +38401,124297,Female,disloyal Customer,27,Business travel,Business,601,1,1,1,1,2,1,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +38402,51962,Female,disloyal Customer,38,Business travel,Eco,347,2,2,2,4,4,2,4,4,4,2,3,4,3,4,0,0.0,neutral or dissatisfied +38403,46918,Female,Loyal Customer,39,Business travel,Business,819,2,5,5,5,3,4,4,2,2,2,2,1,2,1,0,50.0,neutral or dissatisfied +38404,32515,Male,disloyal Customer,48,Business travel,Business,216,3,3,3,3,4,3,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +38405,68069,Male,disloyal Customer,57,Business travel,Business,813,3,3,3,4,5,3,5,5,3,2,4,3,5,5,9,5.0,neutral or dissatisfied +38406,88361,Female,disloyal Customer,27,Business travel,Business,581,5,5,5,4,2,5,1,2,3,4,5,4,4,2,0,0.0,satisfied +38407,53969,Female,disloyal Customer,11,Personal Travel,Eco,1325,5,5,5,2,2,5,2,2,3,5,3,5,4,2,5,0.0,satisfied +38408,35106,Male,Loyal Customer,21,Business travel,Eco,1076,4,3,3,3,4,4,4,4,4,3,5,4,3,4,0,9.0,satisfied +38409,97525,Female,Loyal Customer,33,Business travel,Business,2210,2,2,2,2,1,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +38410,48026,Female,disloyal Customer,44,Business travel,Eco,1384,3,3,3,4,2,3,2,2,3,3,1,2,3,2,0,0.0,neutral or dissatisfied +38411,41143,Female,Loyal Customer,58,Personal Travel,Eco,140,3,4,3,4,4,3,4,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +38412,21944,Male,disloyal Customer,26,Business travel,Eco,448,1,4,1,1,3,1,3,3,1,1,2,2,4,3,27,25.0,neutral or dissatisfied +38413,30746,Female,Loyal Customer,12,Business travel,Business,3720,2,3,3,3,2,3,2,2,4,3,3,3,3,2,28,82.0,neutral or dissatisfied +38414,109223,Male,Loyal Customer,49,Business travel,Business,3108,1,1,1,1,1,3,3,1,1,1,1,4,1,3,0,9.0,neutral or dissatisfied +38415,47242,Male,Loyal Customer,46,Business travel,Business,590,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,2.0,satisfied +38416,61853,Female,Loyal Customer,50,Personal Travel,Eco Plus,1635,1,4,1,4,3,4,4,3,3,1,5,4,3,5,1,0.0,neutral or dissatisfied +38417,89702,Male,Loyal Customer,57,Personal Travel,Eco,950,5,4,5,5,2,5,2,2,4,3,3,4,4,2,2,0.0,satisfied +38418,17347,Female,Loyal Customer,59,Business travel,Business,3301,1,2,3,2,4,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +38419,93816,Female,Loyal Customer,68,Business travel,Business,391,4,4,4,4,2,5,4,4,4,4,4,3,4,4,12,11.0,satisfied +38420,75831,Male,Loyal Customer,47,Business travel,Business,1437,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +38421,50463,Female,Loyal Customer,39,Business travel,Business,2203,3,4,4,4,4,3,4,3,3,4,3,2,3,3,0,4.0,neutral or dissatisfied +38422,45745,Female,Loyal Customer,39,Business travel,Business,3112,1,1,1,1,3,4,4,5,5,4,5,5,5,4,2,2.0,satisfied +38423,112558,Female,Loyal Customer,38,Business travel,Eco Plus,450,2,1,1,1,2,2,2,2,1,2,4,1,3,2,27,21.0,neutral or dissatisfied +38424,51240,Male,Loyal Customer,48,Business travel,Eco Plus,86,5,3,1,1,5,5,5,5,4,1,3,5,3,5,0,0.0,satisfied +38425,99856,Male,Loyal Customer,49,Personal Travel,Eco,534,3,5,3,1,1,3,2,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +38426,33302,Female,Loyal Customer,55,Personal Travel,Eco Plus,101,1,2,0,4,5,3,4,3,3,0,5,2,3,1,0,0.0,neutral or dissatisfied +38427,50059,Female,Loyal Customer,46,Business travel,Eco,109,3,4,4,4,5,4,3,3,3,3,3,1,3,3,0,0.0,satisfied +38428,63794,Male,Loyal Customer,40,Personal Travel,Eco,1721,1,4,1,3,5,1,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +38429,110779,Female,Loyal Customer,51,Business travel,Business,3804,5,5,4,5,5,4,5,5,5,5,5,3,5,4,0,5.0,satisfied +38430,8495,Female,Loyal Customer,57,Business travel,Business,862,2,2,2,2,3,3,3,2,2,2,2,1,2,1,52,35.0,neutral or dissatisfied +38431,21102,Male,Loyal Customer,80,Business travel,Business,106,4,4,4,4,5,1,2,4,4,4,5,3,4,5,0,0.0,satisfied +38432,117752,Male,Loyal Customer,53,Business travel,Business,1670,5,5,2,5,4,3,5,2,2,2,2,5,2,5,18,15.0,satisfied +38433,82642,Female,Loyal Customer,20,Personal Travel,Eco Plus,528,1,3,2,3,1,2,1,1,3,5,3,5,4,1,0,0.0,neutral or dissatisfied +38434,90339,Male,Loyal Customer,39,Business travel,Business,545,2,2,5,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +38435,40032,Female,Loyal Customer,45,Personal Travel,Eco,525,4,5,4,3,2,4,5,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +38436,59935,Female,Loyal Customer,51,Business travel,Business,937,4,2,2,2,1,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +38437,119503,Female,Loyal Customer,29,Business travel,Business,2389,5,4,5,5,5,5,5,5,3,3,4,5,5,5,9,0.0,satisfied +38438,20380,Male,Loyal Customer,41,Business travel,Eco Plus,265,4,5,5,5,4,4,4,4,4,1,5,2,4,4,0,0.0,satisfied +38439,63951,Female,Loyal Customer,70,Personal Travel,Eco,1172,4,5,5,4,2,3,5,1,1,5,1,3,1,4,17,21.0,neutral or dissatisfied +38440,42337,Male,Loyal Customer,52,Personal Travel,Eco,817,1,2,1,2,5,1,5,5,4,4,3,2,2,5,0,0.0,neutral or dissatisfied +38441,49848,Female,Loyal Customer,33,Business travel,Business,2836,4,4,4,4,3,1,3,5,5,5,5,2,5,3,0,0.0,satisfied +38442,128366,Male,Loyal Customer,39,Business travel,Business,370,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +38443,12364,Female,Loyal Customer,38,Business travel,Business,2303,4,2,2,2,4,3,3,1,1,1,4,3,1,4,62,56.0,neutral or dissatisfied +38444,8820,Female,Loyal Customer,20,Personal Travel,Eco,522,2,4,2,3,2,3,3,4,3,5,4,3,3,3,454,458.0,neutral or dissatisfied +38445,65302,Female,Loyal Customer,68,Personal Travel,Eco Plus,247,2,4,0,3,4,5,4,2,2,0,2,4,2,5,1,2.0,neutral or dissatisfied +38446,33034,Female,Loyal Customer,41,Personal Travel,Eco,101,3,2,3,2,5,3,5,5,3,1,2,2,3,5,0,1.0,neutral or dissatisfied +38447,555,Male,Loyal Customer,31,Business travel,Business,3057,2,2,2,2,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +38448,56815,Female,Loyal Customer,25,Business travel,Business,1605,2,3,3,3,2,2,2,2,2,1,2,2,3,2,8,11.0,neutral or dissatisfied +38449,23838,Male,disloyal Customer,27,Business travel,Eco,715,2,2,2,3,4,2,1,4,3,1,2,2,3,4,0,0.0,neutral or dissatisfied +38450,80042,Female,Loyal Customer,60,Personal Travel,Eco,950,2,3,2,3,3,2,3,4,4,2,2,4,4,2,29,0.0,neutral or dissatisfied +38451,125704,Female,Loyal Customer,41,Personal Travel,Eco,899,1,4,1,5,1,1,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +38452,117022,Female,disloyal Customer,39,Business travel,Business,338,5,4,4,1,4,4,5,4,5,3,5,3,4,4,7,1.0,satisfied +38453,20071,Female,Loyal Customer,59,Personal Travel,Eco,738,2,5,2,2,4,5,5,3,3,2,5,3,3,4,6,22.0,neutral or dissatisfied +38454,66398,Male,Loyal Customer,40,Business travel,Business,1562,2,2,2,2,2,4,5,5,5,5,5,3,5,3,10,0.0,satisfied +38455,127219,Male,Loyal Customer,48,Personal Travel,Eco Plus,304,1,4,3,3,3,3,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +38456,102800,Male,Loyal Customer,39,Business travel,Business,342,1,1,1,1,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +38457,73276,Male,Loyal Customer,58,Business travel,Business,1120,1,2,2,2,4,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +38458,87101,Male,Loyal Customer,12,Personal Travel,Eco,594,1,5,1,2,1,1,3,1,5,2,2,4,2,1,29,22.0,neutral or dissatisfied +38459,100891,Male,Loyal Customer,47,Business travel,Eco,377,3,1,1,1,3,3,3,3,4,4,3,3,2,3,0,0.0,neutral or dissatisfied +38460,42913,Male,Loyal Customer,49,Personal Travel,Eco,422,3,0,3,1,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +38461,24648,Male,Loyal Customer,54,Business travel,Eco,834,4,3,3,3,4,4,4,4,1,5,3,4,2,4,0,0.0,satisfied +38462,18839,Female,disloyal Customer,37,Business travel,Eco,500,2,3,2,2,3,2,3,3,2,2,5,3,3,3,0,0.0,neutral or dissatisfied +38463,60790,Male,Loyal Customer,38,Business travel,Business,2426,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +38464,63427,Female,Loyal Customer,13,Personal Travel,Eco,337,2,5,2,4,3,2,1,3,4,4,5,5,4,3,1,10.0,neutral or dissatisfied +38465,45827,Female,Loyal Customer,50,Personal Travel,Eco,391,2,3,2,3,1,1,4,5,5,2,5,4,5,5,15,3.0,neutral or dissatisfied +38466,97319,Female,Loyal Customer,59,Business travel,Business,3679,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +38467,104872,Male,disloyal Customer,44,Business travel,Eco,327,4,2,3,2,5,3,5,5,2,5,3,4,3,5,32,11.0,neutral or dissatisfied +38468,378,Male,disloyal Customer,41,Business travel,Business,309,5,1,1,4,5,5,5,5,5,3,5,4,4,5,0,0.0,satisfied +38469,117472,Male,Loyal Customer,49,Business travel,Business,507,5,5,2,5,2,4,5,4,4,4,4,3,4,3,6,9.0,satisfied +38470,119161,Male,Loyal Customer,38,Business travel,Business,2193,2,2,2,2,2,4,5,4,4,5,4,3,4,3,23,8.0,satisfied +38471,80833,Male,Loyal Customer,45,Business travel,Business,692,3,5,5,5,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +38472,105419,Male,disloyal Customer,38,Business travel,Business,452,3,4,4,1,4,4,4,4,5,3,4,5,4,4,3,11.0,neutral or dissatisfied +38473,100461,Male,Loyal Customer,40,Business travel,Business,2790,2,5,2,2,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +38474,109799,Female,Loyal Customer,50,Business travel,Business,1033,4,4,5,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +38475,67704,Male,disloyal Customer,26,Business travel,Eco,1476,2,2,2,2,5,2,5,5,4,2,3,2,3,5,44,62.0,neutral or dissatisfied +38476,15575,Male,Loyal Customer,39,Business travel,Eco,292,2,1,1,1,2,2,2,2,4,3,2,3,4,2,0,0.0,satisfied +38477,96163,Female,Loyal Customer,26,Business travel,Business,546,2,2,2,2,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +38478,122382,Male,Loyal Customer,7,Personal Travel,Eco,529,0,3,0,1,1,0,1,1,1,2,2,1,3,1,1,5.0,satisfied +38479,6369,Female,disloyal Customer,27,Business travel,Eco,213,2,4,2,3,3,2,3,3,3,2,3,3,4,3,38,54.0,neutral or dissatisfied +38480,38878,Female,Loyal Customer,49,Business travel,Eco,261,4,1,1,1,4,3,1,4,4,4,4,2,4,2,0,0.0,satisfied +38481,71084,Male,Loyal Customer,18,Personal Travel,Eco,802,4,4,4,4,2,4,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +38482,58830,Male,Loyal Customer,24,Business travel,Business,2949,3,3,1,3,5,5,5,5,5,5,4,4,5,5,34,36.0,satisfied +38483,114513,Female,Loyal Customer,49,Business travel,Business,3087,0,0,0,2,2,4,5,3,3,3,1,5,3,3,22,26.0,satisfied +38484,107177,Male,Loyal Customer,31,Business travel,Business,668,4,4,4,4,4,4,4,4,5,5,4,4,4,4,5,0.0,satisfied +38485,88427,Male,Loyal Customer,43,Business travel,Business,1937,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +38486,86015,Male,disloyal Customer,22,Business travel,Eco,528,2,3,2,3,4,2,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +38487,92427,Female,disloyal Customer,42,Business travel,Business,1947,3,3,3,3,2,3,2,2,3,4,5,5,5,2,5,0.0,neutral or dissatisfied +38488,108605,Male,Loyal Customer,60,Business travel,Eco,696,2,2,2,2,2,2,2,2,3,5,4,4,4,2,36,37.0,neutral or dissatisfied +38489,54212,Male,Loyal Customer,42,Personal Travel,Eco Plus,1400,2,5,2,5,5,2,5,5,3,2,3,5,5,5,0,0.0,neutral or dissatisfied +38490,125429,Male,Loyal Customer,66,Personal Travel,Eco,735,5,5,5,1,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +38491,98461,Female,Loyal Customer,44,Business travel,Business,3586,0,4,0,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +38492,59059,Female,Loyal Customer,44,Business travel,Business,1846,2,4,4,4,2,3,3,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +38493,17386,Male,Loyal Customer,21,Personal Travel,Eco,770,2,5,2,5,4,2,4,4,3,5,5,4,5,4,17,34.0,neutral or dissatisfied +38494,810,Male,disloyal Customer,26,Business travel,Business,354,3,1,3,3,3,3,3,3,2,5,3,3,3,3,0,7.0,neutral or dissatisfied +38495,96831,Female,Loyal Customer,67,Business travel,Eco,781,2,1,1,1,3,3,2,2,2,2,2,1,2,4,23,28.0,neutral or dissatisfied +38496,100565,Female,Loyal Customer,61,Personal Travel,Business,486,1,2,1,4,2,2,4,3,3,1,3,2,3,1,0,0.0,neutral or dissatisfied +38497,114645,Female,Loyal Customer,52,Business travel,Business,373,4,4,4,4,3,4,4,4,4,4,4,4,4,3,7,0.0,satisfied +38498,87108,Male,Loyal Customer,35,Personal Travel,Eco,594,3,1,3,4,1,3,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +38499,126405,Male,Loyal Customer,19,Business travel,Business,650,2,2,2,2,5,5,5,5,5,4,5,4,5,5,2,0.0,satisfied +38500,24912,Male,Loyal Customer,68,Business travel,Eco,762,3,2,2,2,3,3,3,3,1,2,3,4,3,3,4,0.0,neutral or dissatisfied +38501,76111,Female,disloyal Customer,21,Business travel,Eco,363,2,0,2,5,4,2,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +38502,74802,Female,Loyal Customer,29,Business travel,Eco Plus,1431,3,3,3,3,3,3,3,3,3,1,3,4,4,3,0,2.0,neutral or dissatisfied +38503,32335,Male,Loyal Customer,80,Business travel,Eco,101,2,5,5,5,2,2,2,2,4,5,3,1,4,2,0,0.0,neutral or dissatisfied +38504,113011,Female,Loyal Customer,25,Personal Travel,Eco,1751,2,5,2,2,4,2,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +38505,50495,Male,Loyal Customer,40,Personal Travel,Eco,78,5,4,0,4,1,0,1,1,3,1,3,3,4,1,0,0.0,satisfied +38506,22260,Male,Loyal Customer,35,Business travel,Eco,145,5,4,4,4,5,4,5,5,1,3,5,3,1,5,62,51.0,satisfied +38507,54298,Male,Loyal Customer,36,Personal Travel,Eco,1075,3,5,3,3,5,3,2,5,5,3,5,5,5,5,4,0.0,neutral or dissatisfied +38508,16253,Male,Loyal Customer,8,Business travel,Business,748,4,4,4,4,4,4,4,4,5,4,2,1,1,4,6,6.0,satisfied +38509,111117,Female,Loyal Customer,54,Business travel,Business,1050,3,3,1,3,2,5,5,5,5,5,5,3,5,3,26,9.0,satisfied +38510,74359,Male,Loyal Customer,32,Business travel,Business,3814,1,1,2,1,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +38511,119691,Female,Loyal Customer,40,Business travel,Business,1325,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,20.0,satisfied +38512,61915,Male,disloyal Customer,26,Business travel,Eco,550,1,2,0,1,1,0,1,1,4,1,1,4,2,1,46,37.0,neutral or dissatisfied +38513,81718,Female,Loyal Customer,34,Business travel,Business,1416,3,3,3,3,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +38514,58592,Female,Loyal Customer,48,Business travel,Eco,334,4,3,3,3,4,2,2,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +38515,95761,Male,Loyal Customer,14,Personal Travel,Eco,237,2,5,2,1,2,2,2,2,4,5,4,4,5,2,34,20.0,neutral or dissatisfied +38516,12081,Male,disloyal Customer,38,Business travel,Business,351,3,4,4,3,5,4,2,5,1,4,5,5,4,5,0,0.0,neutral or dissatisfied +38517,94071,Female,Loyal Customer,18,Business travel,Business,2089,4,4,4,4,4,3,4,4,4,2,4,2,3,4,40,42.0,neutral or dissatisfied +38518,34404,Female,disloyal Customer,23,Business travel,Eco,612,3,2,3,4,1,3,1,1,3,5,4,1,4,1,0,0.0,neutral or dissatisfied +38519,40900,Male,Loyal Customer,26,Personal Travel,Eco,588,3,4,3,4,4,3,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +38520,58291,Female,Loyal Customer,16,Personal Travel,Eco,413,4,5,5,5,3,5,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +38521,47138,Female,disloyal Customer,39,Business travel,Business,954,3,3,3,3,5,3,5,5,1,2,1,2,2,5,0,0.0,neutral or dissatisfied +38522,3582,Female,Loyal Customer,8,Personal Travel,Eco Plus,227,2,2,2,3,4,2,4,4,3,3,3,1,3,4,27,24.0,neutral or dissatisfied +38523,80018,Female,Loyal Customer,46,Personal Travel,Eco,1089,2,5,2,4,2,4,2,4,4,2,4,5,4,2,6,0.0,neutral or dissatisfied +38524,14142,Male,Loyal Customer,61,Personal Travel,Eco,528,4,3,4,2,1,4,1,1,2,4,3,5,2,1,0,0.0,satisfied +38525,93395,Female,Loyal Customer,40,Business travel,Business,2797,5,5,5,5,2,4,4,5,5,5,5,4,5,4,0,7.0,satisfied +38526,91018,Female,Loyal Customer,43,Personal Travel,Eco,270,0,4,0,3,5,4,4,2,2,0,2,3,2,1,1,7.0,satisfied +38527,64205,Male,Loyal Customer,62,Personal Travel,Eco,853,2,5,1,3,3,1,5,3,4,3,5,5,4,3,29,24.0,neutral or dissatisfied +38528,119628,Female,disloyal Customer,22,Business travel,Eco,1016,5,5,5,1,4,5,4,4,3,3,3,5,4,4,0,5.0,satisfied +38529,75981,Male,Loyal Customer,26,Personal Travel,Eco,297,2,3,2,3,1,2,1,1,1,1,5,4,2,1,0,7.0,neutral or dissatisfied +38530,35075,Female,Loyal Customer,14,Personal Travel,Business,1102,1,4,1,3,1,1,1,1,2,1,3,2,4,1,17,18.0,neutral or dissatisfied +38531,94838,Female,Loyal Customer,39,Business travel,Business,1880,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +38532,115399,Female,disloyal Customer,25,Business travel,Business,371,2,0,2,3,5,2,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +38533,86811,Female,disloyal Customer,23,Business travel,Eco,692,1,1,1,3,4,1,4,4,3,4,4,5,4,4,1,2.0,neutral or dissatisfied +38534,95094,Female,Loyal Customer,16,Personal Travel,Eco,239,3,5,3,2,4,3,4,4,4,5,4,3,4,4,3,0.0,neutral or dissatisfied +38535,85457,Male,Loyal Customer,47,Business travel,Business,2728,4,4,4,4,5,5,4,4,4,4,5,3,4,3,0,1.0,satisfied +38536,41724,Male,disloyal Customer,29,Business travel,Eco,695,5,5,5,3,2,5,2,2,1,4,3,2,1,2,0,34.0,satisfied +38537,115405,Female,Loyal Customer,52,Business travel,Business,3112,4,4,3,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +38538,37512,Female,disloyal Customer,28,Business travel,Eco,1074,4,4,4,4,3,4,3,3,4,1,3,3,3,3,126,118.0,neutral or dissatisfied +38539,125840,Female,disloyal Customer,28,Business travel,Business,920,1,1,1,1,4,1,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +38540,33447,Male,Loyal Customer,8,Personal Travel,Eco,2614,4,5,4,1,4,5,5,3,3,4,5,5,3,5,0,41.0,neutral or dissatisfied +38541,79414,Male,Loyal Customer,44,Personal Travel,Eco,502,4,5,4,4,1,4,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +38542,58259,Male,Loyal Customer,49,Business travel,Business,2072,5,5,5,5,2,3,5,4,4,4,4,5,4,5,4,0.0,satisfied +38543,6653,Female,Loyal Customer,68,Personal Travel,Eco Plus,416,3,4,3,4,5,3,4,4,4,3,4,1,4,4,28,22.0,neutral or dissatisfied +38544,69061,Male,disloyal Customer,29,Business travel,Business,1389,2,2,2,3,3,2,2,3,3,4,4,5,5,3,5,4.0,neutral or dissatisfied +38545,56444,Female,Loyal Customer,49,Personal Travel,Eco,719,3,1,3,3,5,3,2,1,1,3,2,1,1,1,3,9.0,neutral or dissatisfied +38546,88292,Male,Loyal Customer,54,Business travel,Business,2607,5,5,4,5,3,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +38547,95309,Female,Loyal Customer,65,Personal Travel,Eco,528,1,4,1,2,5,5,4,2,2,1,2,4,2,4,43,34.0,neutral or dissatisfied +38548,90931,Female,disloyal Customer,27,Business travel,Eco,406,2,2,2,3,2,2,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +38549,44175,Male,disloyal Customer,36,Business travel,Eco,157,1,3,1,5,2,1,2,2,5,5,1,4,1,2,0,0.0,neutral or dissatisfied +38550,99489,Female,Loyal Customer,54,Personal Travel,Eco,283,4,5,4,3,5,4,5,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +38551,90909,Female,disloyal Customer,29,Business travel,Eco,581,2,2,3,3,4,3,4,4,2,3,4,4,4,4,1,0.0,neutral or dissatisfied +38552,57771,Female,disloyal Customer,28,Business travel,Eco,723,3,3,3,3,3,4,4,1,2,3,3,4,4,4,37,35.0,neutral or dissatisfied +38553,109671,Female,disloyal Customer,23,Business travel,Eco,829,1,1,1,2,1,1,1,1,3,3,1,2,2,1,4,0.0,neutral or dissatisfied +38554,28532,Male,Loyal Customer,35,Business travel,Business,2701,4,2,2,2,2,2,4,4,4,3,4,2,4,4,16,0.0,neutral or dissatisfied +38555,9844,Female,Loyal Customer,45,Business travel,Business,1929,2,2,2,2,3,5,5,4,4,5,4,4,4,3,13,0.0,satisfied +38556,122730,Female,Loyal Customer,37,Business travel,Business,651,2,2,2,2,2,4,4,3,3,3,3,5,3,3,1,0.0,satisfied +38557,17442,Male,Loyal Customer,30,Personal Travel,Eco,376,2,2,2,3,2,2,2,2,3,2,3,4,3,2,0,4.0,neutral or dissatisfied +38558,118008,Female,Loyal Customer,56,Business travel,Business,1037,1,2,1,1,3,5,5,5,5,5,5,3,5,4,8,0.0,satisfied +38559,14316,Female,disloyal Customer,29,Business travel,Eco,395,2,4,2,4,5,2,5,5,3,1,4,3,4,5,0,0.0,neutral or dissatisfied +38560,59407,Female,Loyal Customer,65,Personal Travel,Eco,2367,1,4,1,2,2,4,4,2,2,1,2,5,2,3,17,0.0,neutral or dissatisfied +38561,59184,Male,Loyal Customer,33,Business travel,Business,1440,2,2,2,2,2,2,2,2,2,2,2,2,4,2,171,167.0,neutral or dissatisfied +38562,73592,Male,Loyal Customer,56,Business travel,Business,192,5,5,5,5,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +38563,100880,Female,disloyal Customer,27,Business travel,Business,2133,3,3,3,3,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +38564,18625,Female,Loyal Customer,59,Personal Travel,Eco,285,3,5,3,1,3,4,4,1,1,3,3,4,1,5,0,0.0,neutral or dissatisfied +38565,70539,Female,Loyal Customer,45,Business travel,Business,1258,3,3,3,3,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +38566,82958,Female,Loyal Customer,43,Business travel,Business,3658,2,2,2,2,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +38567,100883,Female,Loyal Customer,9,Personal Travel,Eco,2133,2,1,2,3,3,2,3,3,2,5,3,2,3,3,11,0.0,neutral or dissatisfied +38568,122208,Female,Loyal Customer,38,Business travel,Business,3997,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +38569,91633,Male,disloyal Customer,40,Business travel,Eco,799,1,1,1,3,5,1,5,5,1,2,3,3,4,5,64,63.0,neutral or dissatisfied +38570,86396,Female,Loyal Customer,58,Business travel,Business,3553,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +38571,111004,Male,Loyal Customer,54,Business travel,Business,3700,1,1,1,1,5,4,5,4,4,4,4,4,4,3,20,29.0,satisfied +38572,109692,Male,Loyal Customer,45,Business travel,Business,829,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +38573,3970,Male,Loyal Customer,45,Business travel,Business,3985,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +38574,67409,Male,Loyal Customer,48,Business travel,Business,3090,3,4,2,4,1,3,4,3,3,3,3,2,3,1,31,21.0,neutral or dissatisfied +38575,534,Male,disloyal Customer,32,Business travel,Business,309,3,3,3,2,4,3,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +38576,27246,Male,Loyal Customer,37,Business travel,Eco Plus,1024,4,5,5,5,4,4,4,4,2,1,2,5,1,4,0,0.0,satisfied +38577,52915,Male,Loyal Customer,34,Business travel,Eco,679,3,3,2,3,3,4,3,3,5,5,2,3,3,3,44,46.0,satisfied +38578,103849,Female,Loyal Customer,48,Business travel,Eco,882,2,3,3,3,1,4,3,2,2,2,2,1,2,2,0,4.0,neutral or dissatisfied +38579,83404,Female,Loyal Customer,30,Business travel,Business,632,3,3,3,3,2,2,2,2,5,4,5,5,4,2,0,6.0,satisfied +38580,56483,Female,Loyal Customer,57,Personal Travel,Eco,4963,3,4,3,5,3,3,3,3,1,5,1,3,3,3,12,17.0,neutral or dissatisfied +38581,113077,Female,disloyal Customer,20,Business travel,Eco,569,3,1,3,3,1,3,1,1,4,5,3,2,2,1,31,28.0,neutral or dissatisfied +38582,60375,Male,Loyal Customer,60,Business travel,Business,1452,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +38583,21949,Male,Loyal Customer,35,Business travel,Business,2923,2,3,3,3,5,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +38584,14505,Female,disloyal Customer,23,Business travel,Eco,402,4,0,4,5,3,4,3,3,2,5,2,1,1,3,4,0.0,satisfied +38585,89530,Male,Loyal Customer,51,Business travel,Business,2735,3,4,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +38586,97851,Female,Loyal Customer,48,Business travel,Business,1548,5,5,5,5,5,4,5,4,4,4,4,5,4,5,57,58.0,satisfied +38587,91446,Male,Loyal Customer,53,Business travel,Business,859,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +38588,15427,Female,Loyal Customer,54,Business travel,Business,2422,2,1,1,1,4,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +38589,105238,Male,Loyal Customer,49,Personal Travel,Eco,377,1,3,1,3,5,1,2,5,1,1,4,1,3,5,35,17.0,neutral or dissatisfied +38590,5940,Male,Loyal Customer,34,Business travel,Business,3472,2,2,2,2,2,5,4,5,5,4,5,4,5,4,3,5.0,satisfied +38591,93778,Male,Loyal Customer,56,Business travel,Business,1865,5,5,5,5,3,5,4,5,5,5,5,5,5,3,16,10.0,satisfied +38592,50336,Female,Loyal Customer,36,Business travel,Business,3642,1,1,1,1,1,2,2,4,4,4,4,2,4,1,29,27.0,satisfied +38593,111226,Male,Loyal Customer,24,Personal Travel,Eco,1447,2,3,2,3,3,2,3,3,4,4,3,4,4,3,0,8.0,neutral or dissatisfied +38594,99508,Male,Loyal Customer,53,Personal Travel,Eco,283,4,4,4,3,5,4,2,5,4,2,5,4,5,5,6,11.0,neutral or dissatisfied +38595,109000,Female,disloyal Customer,22,Business travel,Eco,781,4,4,4,2,4,4,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +38596,78189,Female,disloyal Customer,37,Business travel,Eco,259,3,4,3,4,4,3,4,4,1,3,3,1,4,4,1,3.0,neutral or dissatisfied +38597,32526,Male,Loyal Customer,78,Business travel,Business,3771,2,2,5,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +38598,76559,Male,Loyal Customer,36,Business travel,Eco,547,3,5,5,5,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +38599,27992,Male,Loyal Customer,39,Business travel,Eco,1016,1,0,0,3,1,0,1,1,2,1,3,2,3,1,3,0.0,neutral or dissatisfied +38600,91039,Male,Loyal Customer,45,Personal Travel,Eco,270,1,1,1,3,3,1,3,3,3,5,2,1,2,3,1,0.0,neutral or dissatisfied +38601,53792,Female,Loyal Customer,51,Business travel,Eco,191,4,4,4,4,1,3,2,4,4,4,4,3,4,1,10,9.0,satisfied +38602,42963,Female,Loyal Customer,39,Business travel,Eco,391,4,3,3,3,4,4,4,4,5,5,3,3,4,4,0,0.0,satisfied +38603,39845,Female,Loyal Customer,37,Business travel,Eco,221,5,5,5,5,5,5,5,5,1,2,3,5,5,5,0,0.0,satisfied +38604,89769,Male,Loyal Customer,54,Personal Travel,Eco,944,1,4,1,3,3,1,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +38605,77656,Male,Loyal Customer,45,Business travel,Business,696,3,3,3,3,3,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +38606,99134,Male,Loyal Customer,31,Personal Travel,Eco,419,2,4,4,2,5,4,5,5,2,1,5,2,2,5,97,82.0,neutral or dissatisfied +38607,114779,Male,Loyal Customer,55,Business travel,Business,3253,5,5,4,5,4,4,5,4,4,4,4,5,4,4,43,34.0,satisfied +38608,101367,Male,Loyal Customer,51,Personal Travel,Eco,1986,3,4,3,2,3,3,3,3,3,4,2,5,4,3,7,2.0,neutral or dissatisfied +38609,11896,Male,Loyal Customer,58,Business travel,Business,3441,2,2,2,2,4,5,4,4,4,4,4,3,4,5,130,120.0,satisfied +38610,50179,Female,Loyal Customer,39,Business travel,Eco,89,5,4,4,4,5,5,5,5,4,4,5,3,4,5,0,,satisfied +38611,121815,Male,Loyal Customer,43,Business travel,Business,3696,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +38612,75750,Male,Loyal Customer,45,Business travel,Eco,468,4,5,5,5,4,4,4,1,2,4,4,4,3,4,154,143.0,satisfied +38613,35151,Female,Loyal Customer,31,Business travel,Business,1074,4,4,4,4,4,4,4,4,4,1,2,2,3,4,4,1.0,satisfied +38614,11266,Male,Loyal Customer,22,Personal Travel,Eco,517,1,4,1,2,4,1,5,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +38615,35327,Female,disloyal Customer,23,Business travel,Eco,1069,2,2,2,4,2,1,1,2,5,3,3,1,1,1,180,194.0,neutral or dissatisfied +38616,48975,Female,Loyal Customer,59,Business travel,Business,2297,1,1,1,1,5,5,3,5,5,5,3,1,5,2,0,0.0,satisfied +38617,85972,Female,Loyal Customer,73,Business travel,Business,432,1,5,5,5,2,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +38618,84138,Male,Loyal Customer,64,Personal Travel,Eco,782,3,2,3,1,4,3,2,4,3,3,2,4,2,4,14,2.0,neutral or dissatisfied +38619,117051,Female,Loyal Customer,22,Business travel,Business,2898,2,5,1,5,2,3,2,2,3,3,4,3,4,2,5,0.0,neutral or dissatisfied +38620,47230,Male,Loyal Customer,29,Business travel,Eco Plus,954,2,5,4,5,2,2,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +38621,101565,Female,Loyal Customer,68,Personal Travel,Eco Plus,345,1,5,1,4,3,4,4,4,4,1,4,3,4,5,0,8.0,neutral or dissatisfied +38622,102736,Female,Loyal Customer,62,Personal Travel,Eco,365,3,3,3,4,2,4,3,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +38623,65888,Female,Loyal Customer,41,Business travel,Business,1655,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +38624,50401,Female,disloyal Customer,24,Business travel,Business,304,4,0,4,4,1,4,1,1,5,1,3,2,5,1,0,0.0,satisfied +38625,59975,Male,disloyal Customer,38,Business travel,Eco,537,4,2,3,4,5,3,5,5,4,5,3,1,4,5,0,7.0,neutral or dissatisfied +38626,36116,Female,Loyal Customer,46,Business travel,Eco,1562,4,5,5,5,1,4,5,4,4,4,4,3,4,1,0,0.0,satisfied +38627,92925,Female,Loyal Customer,37,Business travel,Business,134,4,1,1,1,4,4,3,3,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +38628,97479,Male,Loyal Customer,30,Business travel,Business,2835,3,3,4,3,3,3,3,3,2,4,4,3,4,3,0,0.0,neutral or dissatisfied +38629,111099,Male,disloyal Customer,27,Business travel,Business,197,2,3,3,5,4,3,4,4,4,5,4,3,4,4,13,9.0,neutral or dissatisfied +38630,89623,Female,Loyal Customer,45,Business travel,Business,1010,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,10.0,satisfied +38631,3592,Female,Loyal Customer,45,Business travel,Eco,999,1,4,4,4,4,4,3,1,1,1,1,4,1,4,19,94.0,neutral or dissatisfied +38632,71165,Female,Loyal Customer,68,Personal Travel,Eco,646,2,1,2,2,3,3,3,3,3,2,5,1,3,4,8,0.0,neutral or dissatisfied +38633,51693,Female,Loyal Customer,45,Business travel,Business,261,4,4,4,4,5,4,3,5,5,5,5,4,5,3,0,3.0,satisfied +38634,76696,Male,Loyal Customer,64,Personal Travel,Eco,547,3,0,3,4,1,3,1,1,1,1,4,3,3,1,0,0.0,neutral or dissatisfied +38635,100301,Male,Loyal Customer,51,Business travel,Eco,1092,3,2,2,2,4,3,4,4,4,3,3,3,3,4,9,18.0,neutral or dissatisfied +38636,32207,Male,Loyal Customer,45,Business travel,Business,3580,3,2,2,2,5,3,4,2,2,2,3,3,2,1,0,0.0,neutral or dissatisfied +38637,114516,Female,Loyal Customer,57,Business travel,Business,2759,1,1,1,1,3,4,4,4,4,4,4,5,4,3,16,4.0,satisfied +38638,19218,Female,Loyal Customer,33,Business travel,Business,2083,2,4,4,4,1,3,4,2,2,2,2,4,2,3,0,8.0,neutral or dissatisfied +38639,69774,Female,Loyal Customer,48,Business travel,Business,2454,2,1,1,1,2,2,2,3,4,4,4,2,4,2,0,39.0,neutral or dissatisfied +38640,47167,Female,Loyal Customer,41,Business travel,Eco,748,4,3,3,3,4,4,4,4,5,5,5,1,1,4,0,20.0,satisfied +38641,104075,Female,Loyal Customer,41,Business travel,Eco,359,2,3,5,5,2,2,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +38642,16863,Female,Loyal Customer,59,Business travel,Business,3975,1,1,1,1,4,5,3,5,5,5,5,1,5,3,45,17.0,satisfied +38643,108679,Female,disloyal Customer,25,Business travel,Business,577,0,5,0,3,2,0,4,2,5,2,4,4,4,2,15,1.0,satisfied +38644,98036,Male,Loyal Customer,43,Business travel,Business,1797,4,4,4,4,4,4,4,4,4,4,4,5,4,5,86,73.0,satisfied +38645,83521,Female,Loyal Customer,66,Personal Travel,Eco,946,3,5,3,1,3,1,2,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +38646,116187,Male,Loyal Customer,33,Personal Travel,Eco,447,1,4,1,3,3,1,3,3,5,1,2,3,1,3,9,0.0,neutral or dissatisfied +38647,79310,Male,Loyal Customer,39,Personal Travel,Eco,2248,1,4,1,3,5,1,5,5,5,2,3,5,5,5,7,0.0,neutral or dissatisfied +38648,121183,Female,Loyal Customer,21,Personal Travel,Eco,2370,2,4,2,5,2,3,2,5,4,4,5,2,4,2,0,41.0,neutral or dissatisfied +38649,109514,Male,disloyal Customer,35,Business travel,Business,966,4,4,4,1,4,4,2,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +38650,127107,Male,Loyal Customer,19,Personal Travel,Eco,621,2,4,2,3,5,2,3,5,1,3,4,4,3,5,0,3.0,neutral or dissatisfied +38651,79352,Female,Loyal Customer,17,Personal Travel,Eco,1020,1,4,1,4,4,1,4,4,4,2,3,4,4,4,56,50.0,neutral or dissatisfied +38652,26094,Male,Loyal Customer,46,Personal Travel,Eco,591,4,4,4,5,1,4,1,1,1,4,5,5,3,1,5,0.0,neutral or dissatisfied +38653,14909,Female,Loyal Customer,47,Personal Travel,Eco,315,1,5,5,2,4,4,4,3,3,5,3,3,3,4,0,0.0,neutral or dissatisfied +38654,31852,Female,Loyal Customer,73,Business travel,Eco,1140,5,4,4,4,4,2,3,5,5,5,5,5,5,2,0,0.0,satisfied +38655,7069,Male,Loyal Customer,58,Business travel,Business,177,0,5,0,1,2,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +38656,125408,Male,Loyal Customer,23,Business travel,Eco Plus,1440,2,5,5,5,2,3,1,2,1,4,3,4,3,2,0,10.0,neutral or dissatisfied +38657,99758,Female,Loyal Customer,41,Personal Travel,Eco,255,2,3,2,4,3,2,3,3,4,2,3,1,4,3,2,0.0,neutral or dissatisfied +38658,18733,Male,disloyal Customer,38,Business travel,Business,1167,2,2,2,2,3,2,3,3,4,1,2,3,2,3,0,0.0,neutral or dissatisfied +38659,114370,Female,disloyal Customer,20,Business travel,Eco,967,3,3,3,3,1,3,1,1,2,2,3,4,4,1,23,11.0,neutral or dissatisfied +38660,123480,Female,disloyal Customer,40,Business travel,Business,1249,5,4,4,3,2,4,2,2,3,3,3,5,4,2,0,5.0,satisfied +38661,57368,Female,Loyal Customer,63,Personal Travel,Eco,414,3,2,2,3,4,4,3,1,1,2,1,2,1,3,3,13.0,neutral or dissatisfied +38662,86103,Male,Loyal Customer,18,Personal Travel,Business,306,3,5,3,4,3,3,3,3,5,5,5,3,5,3,15,18.0,neutral or dissatisfied +38663,128948,Male,Loyal Customer,55,Business travel,Business,414,2,5,5,5,5,2,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +38664,40403,Female,Loyal Customer,70,Personal Travel,Business,222,2,0,2,3,4,4,1,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +38665,111451,Female,Loyal Customer,53,Business travel,Eco,1024,1,1,5,1,4,2,2,1,1,1,1,3,1,4,29,46.0,neutral or dissatisfied +38666,31551,Male,Loyal Customer,49,Personal Travel,Eco,862,3,4,3,4,3,3,3,3,5,4,5,3,5,3,86,86.0,neutral or dissatisfied +38667,85900,Male,Loyal Customer,50,Business travel,Business,1539,5,4,5,5,3,5,5,3,3,4,3,3,3,3,30,13.0,satisfied +38668,59794,Female,disloyal Customer,34,Business travel,Eco Plus,927,3,3,3,3,3,3,3,3,3,3,2,2,5,3,0,0.0,neutral or dissatisfied +38669,98582,Female,Loyal Customer,40,Business travel,Business,920,5,5,5,5,3,5,4,3,3,4,3,4,3,5,0,7.0,satisfied +38670,53201,Male,Loyal Customer,33,Business travel,Business,589,4,4,4,4,3,3,3,3,5,3,4,3,1,3,0,13.0,satisfied +38671,117373,Female,Loyal Customer,33,Personal Travel,Eco Plus,296,4,5,5,1,5,5,5,5,4,2,1,1,4,5,0,0.0,neutral or dissatisfied +38672,39805,Male,Loyal Customer,35,Business travel,Eco,132,4,4,4,4,4,4,4,4,4,1,1,3,4,4,0,0.0,satisfied +38673,83420,Male,Loyal Customer,17,Personal Travel,Eco,632,5,4,5,2,4,5,4,4,3,4,5,4,4,4,16,10.0,satisfied +38674,75802,Female,Loyal Customer,51,Personal Travel,Eco,868,5,1,5,4,5,3,3,3,3,5,1,2,3,4,0,2.0,satisfied +38675,57836,Male,Loyal Customer,46,Business travel,Business,1491,4,4,2,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +38676,43233,Male,Loyal Customer,10,Personal Travel,Eco,1037,4,4,4,3,3,4,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +38677,18140,Female,Loyal Customer,53,Business travel,Business,3777,3,3,3,3,1,5,5,5,5,5,5,1,5,2,33,,satisfied +38678,7110,Male,Loyal Customer,30,Personal Travel,Eco,273,2,5,1,4,4,1,1,4,3,2,3,1,5,4,0,0.0,neutral or dissatisfied +38679,26680,Male,Loyal Customer,36,Personal Travel,Eco,270,2,4,2,3,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +38680,50530,Male,Loyal Customer,57,Personal Travel,Eco,372,3,0,3,2,3,3,3,3,2,4,4,3,1,3,8,7.0,neutral or dissatisfied +38681,94042,Male,Loyal Customer,49,Business travel,Business,2985,3,3,3,3,5,4,5,4,4,4,5,3,4,4,0,9.0,satisfied +38682,95635,Female,Loyal Customer,22,Personal Travel,Eco,756,3,2,3,3,2,3,1,2,1,1,4,2,3,2,68,63.0,neutral or dissatisfied +38683,107166,Female,Loyal Customer,56,Business travel,Business,2565,3,3,3,3,5,5,5,4,2,4,4,5,5,5,173,234.0,satisfied +38684,51103,Male,Loyal Customer,53,Personal Travel,Eco,86,2,4,2,3,3,2,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +38685,91583,Male,Loyal Customer,59,Personal Travel,Eco,1123,3,5,3,4,4,3,1,4,5,5,4,4,5,4,15,13.0,neutral or dissatisfied +38686,46340,Male,disloyal Customer,8,Business travel,Eco,692,3,3,3,4,3,3,3,3,3,1,4,1,4,3,0,0.0,neutral or dissatisfied +38687,52911,Female,Loyal Customer,31,Business travel,Eco,679,4,2,3,2,4,4,4,4,2,2,1,5,3,4,0,0.0,satisfied +38688,107426,Male,Loyal Customer,32,Personal Travel,Eco,725,3,4,3,3,1,3,5,1,2,3,4,5,3,1,24,18.0,neutral or dissatisfied +38689,29627,Male,Loyal Customer,41,Business travel,Business,1133,4,4,5,4,5,5,3,2,2,2,2,2,2,4,0,0.0,satisfied +38690,76133,Female,disloyal Customer,36,Business travel,Business,689,4,4,4,2,2,4,2,2,4,5,4,3,5,2,1,6.0,neutral or dissatisfied +38691,79281,Male,Loyal Customer,65,Personal Travel,Business,2248,1,4,1,2,5,5,4,3,3,1,3,3,3,5,19,7.0,neutral or dissatisfied +38692,99206,Female,Loyal Customer,23,Personal Travel,Eco,583,5,4,5,4,4,5,3,4,4,5,4,3,5,4,8,0.0,satisfied +38693,54670,Male,Loyal Customer,31,Business travel,Eco,787,4,4,2,2,4,4,4,4,5,5,3,5,1,4,0,0.0,satisfied +38694,62488,Male,disloyal Customer,30,Business travel,Business,1846,2,2,2,3,2,2,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +38695,77259,Female,Loyal Customer,8,Personal Travel,Eco,1590,2,4,2,3,2,2,2,2,5,5,4,5,4,2,2,45.0,neutral or dissatisfied +38696,119595,Male,Loyal Customer,38,Business travel,Business,1979,3,3,3,3,3,4,4,3,3,3,3,5,3,4,3,0.0,satisfied +38697,33328,Male,Loyal Customer,26,Business travel,Eco,2355,0,3,0,1,2,0,3,2,5,2,5,3,3,2,0,0.0,satisfied +38698,26964,Male,Loyal Customer,30,Business travel,Business,2783,3,3,3,3,5,5,5,5,4,3,3,1,2,5,0,0.0,satisfied +38699,92455,Female,Loyal Customer,66,Business travel,Business,1892,1,0,0,2,5,3,2,1,1,0,1,1,1,3,0,0.0,neutral or dissatisfied +38700,118797,Male,Loyal Customer,47,Personal Travel,Eco,370,3,4,3,4,3,3,3,3,1,5,2,4,4,3,40,43.0,neutral or dissatisfied +38701,57892,Male,Loyal Customer,34,Business travel,Business,305,3,3,4,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +38702,44763,Male,Loyal Customer,36,Business travel,Eco,1250,5,3,3,3,5,4,5,5,3,2,3,5,3,5,7,30.0,satisfied +38703,107644,Male,Loyal Customer,54,Business travel,Business,2804,2,1,1,1,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +38704,117134,Female,Loyal Customer,16,Personal Travel,Eco,369,3,4,3,4,1,3,1,1,2,4,5,2,4,1,0,0.0,neutral or dissatisfied +38705,11396,Female,Loyal Customer,58,Business travel,Business,216,2,2,2,2,5,4,4,5,5,5,4,5,5,5,0,0.0,satisfied +38706,39718,Male,Loyal Customer,30,Business travel,Business,320,2,2,2,2,3,4,3,3,2,4,1,1,3,3,0,0.0,satisfied +38707,100475,Male,Loyal Customer,52,Business travel,Business,580,4,4,4,4,3,4,5,4,4,4,4,5,4,3,5,2.0,satisfied +38708,54362,Male,Loyal Customer,33,Personal Travel,Eco,1235,3,5,3,4,4,3,4,4,5,5,3,4,4,4,0,0.0,neutral or dissatisfied +38709,69186,Female,Loyal Customer,67,Personal Travel,Eco,187,4,4,4,3,3,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +38710,108974,Male,Loyal Customer,56,Business travel,Business,3320,5,5,5,5,3,4,4,5,5,5,5,4,5,4,45,54.0,satisfied +38711,66050,Male,Loyal Customer,43,Business travel,Eco,1055,3,3,3,3,3,3,3,3,3,3,2,4,2,3,4,0.0,neutral or dissatisfied +38712,33775,Male,Loyal Customer,29,Business travel,Business,1617,2,1,1,1,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +38713,69212,Male,Loyal Customer,50,Business travel,Business,3033,3,3,5,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +38714,250,Female,Loyal Customer,70,Personal Travel,Eco,719,3,4,3,4,5,5,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +38715,105137,Female,Loyal Customer,56,Business travel,Business,220,1,1,1,1,4,5,4,3,3,4,4,5,3,4,56,58.0,satisfied +38716,6038,Male,disloyal Customer,29,Business travel,Business,691,2,2,2,2,4,2,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +38717,99307,Male,Loyal Customer,56,Business travel,Eco,337,1,5,2,5,1,1,1,1,3,5,4,1,3,1,32,21.0,neutral or dissatisfied +38718,17492,Female,disloyal Customer,40,Business travel,Business,341,2,2,2,3,2,2,2,2,5,1,3,1,3,2,0,0.0,neutral or dissatisfied +38719,14955,Male,Loyal Customer,45,Personal Travel,Eco,554,4,3,4,3,4,4,4,4,4,1,4,5,5,4,0,0.0,neutral or dissatisfied +38720,12539,Female,disloyal Customer,38,Business travel,Eco,871,1,1,1,4,3,1,3,3,2,3,4,4,4,3,0,12.0,neutral or dissatisfied +38721,100460,Male,disloyal Customer,24,Business travel,Eco,580,2,4,2,1,2,2,2,2,3,2,4,5,5,2,8,2.0,neutral or dissatisfied +38722,6329,Female,disloyal Customer,20,Business travel,Eco,315,1,0,1,3,5,1,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +38723,18529,Male,Loyal Customer,56,Business travel,Business,253,4,4,4,4,1,2,1,3,3,4,3,1,3,2,0,0.0,satisfied +38724,124644,Male,Loyal Customer,46,Business travel,Business,399,5,5,5,5,2,5,4,5,5,5,5,4,5,3,0,2.0,satisfied +38725,101202,Female,Loyal Customer,69,Personal Travel,Eco,1235,3,5,3,1,5,3,3,5,5,3,5,3,5,5,69,72.0,neutral or dissatisfied +38726,38601,Female,Loyal Customer,35,Business travel,Eco,231,4,2,2,2,4,4,4,4,2,4,4,2,4,4,1,0.0,satisfied +38727,98044,Male,Loyal Customer,30,Business travel,Business,1751,4,4,4,4,4,4,4,4,5,5,5,3,5,4,17,2.0,satisfied +38728,88247,Female,Loyal Customer,44,Business travel,Business,2570,1,1,1,1,2,5,5,5,5,4,5,3,5,5,16,8.0,satisfied +38729,88915,Male,Loyal Customer,50,Personal Travel,Eco,859,3,4,3,3,2,3,2,2,2,5,3,5,4,2,0,0.0,neutral or dissatisfied +38730,98941,Female,Loyal Customer,65,Business travel,Eco,569,1,5,5,5,2,3,4,2,2,1,2,3,2,4,40,37.0,neutral or dissatisfied +38731,107217,Female,Loyal Customer,69,Personal Travel,Eco Plus,668,2,4,2,3,3,5,4,5,5,2,5,5,5,5,11,0.0,neutral or dissatisfied +38732,70650,Male,Loyal Customer,24,Business travel,Business,1974,3,3,3,3,4,4,4,4,3,4,5,4,4,4,113,116.0,satisfied +38733,1347,Female,Loyal Customer,60,Business travel,Business,354,3,3,3,3,5,5,5,5,5,5,5,3,5,4,9,1.0,satisfied +38734,21832,Female,Loyal Customer,40,Personal Travel,Eco,640,3,4,3,1,3,3,3,3,4,5,4,4,4,3,42,31.0,neutral or dissatisfied +38735,80043,Male,Loyal Customer,16,Personal Travel,Eco,944,2,4,2,3,3,2,3,3,4,2,4,2,3,3,0,9.0,neutral or dissatisfied +38736,58848,Male,Loyal Customer,57,Personal Travel,Eco,783,4,5,4,2,5,4,5,5,5,5,4,5,4,5,115,101.0,neutral or dissatisfied +38737,98474,Male,disloyal Customer,20,Business travel,Eco Plus,210,2,3,2,3,4,2,4,4,1,4,3,1,3,4,43,59.0,neutral or dissatisfied +38738,12547,Male,disloyal Customer,24,Business travel,Eco,471,3,4,2,4,5,2,5,5,3,5,4,3,4,5,43,40.0,neutral or dissatisfied +38739,116511,Male,Loyal Customer,47,Personal Travel,Eco,480,1,4,1,2,5,1,3,5,5,2,4,2,5,5,0,0.0,neutral or dissatisfied +38740,107975,Female,Loyal Customer,40,Business travel,Business,2300,5,5,5,5,1,1,4,4,4,4,4,4,4,4,89,88.0,satisfied +38741,61569,Male,disloyal Customer,20,Business travel,Business,1635,4,5,4,4,4,4,4,4,4,5,4,4,4,4,18,1.0,satisfied +38742,120024,Male,Loyal Customer,42,Personal Travel,Eco,511,3,4,3,2,5,3,1,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +38743,74875,Male,Loyal Customer,69,Personal Travel,Eco,2239,1,4,1,3,5,1,5,5,3,2,3,3,5,5,3,0.0,neutral or dissatisfied +38744,9414,Male,Loyal Customer,7,Personal Travel,Eco Plus,1027,3,4,3,4,5,3,5,5,4,3,5,3,4,5,0,15.0,neutral or dissatisfied +38745,15628,Female,Loyal Customer,35,Personal Travel,Eco,288,4,4,4,4,3,4,3,3,5,3,4,4,5,3,0,0.0,satisfied +38746,32276,Male,Loyal Customer,32,Business travel,Business,3338,4,4,4,4,5,4,4,5,1,3,2,2,3,5,0,1.0,satisfied +38747,93406,Female,disloyal Customer,42,Business travel,Eco,697,1,2,2,3,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +38748,13380,Female,Loyal Customer,28,Business travel,Eco Plus,946,2,5,5,5,2,2,2,2,4,4,3,2,4,2,46,65.0,neutral or dissatisfied +38749,21057,Female,Loyal Customer,45,Business travel,Business,3340,5,5,5,5,4,2,3,4,4,4,4,1,4,5,0,0.0,satisfied +38750,111272,Male,Loyal Customer,40,Business travel,Business,2408,1,1,1,1,2,5,5,4,4,4,4,5,4,3,8,3.0,satisfied +38751,74519,Female,Loyal Customer,30,Business travel,Business,3038,3,3,3,3,3,3,3,3,5,3,5,4,5,3,1,0.0,satisfied +38752,59128,Male,Loyal Customer,13,Personal Travel,Eco,1744,4,5,5,3,4,5,4,4,5,3,4,4,5,4,35,37.0,neutral or dissatisfied +38753,103192,Male,disloyal Customer,21,Business travel,Eco,814,2,2,2,5,4,2,4,4,4,5,5,4,4,4,3,0.0,neutral or dissatisfied +38754,30234,Female,Loyal Customer,31,Business travel,Business,2943,4,5,5,5,4,4,4,4,2,1,4,1,3,4,0,4.0,neutral or dissatisfied +38755,51914,Male,Loyal Customer,33,Personal Travel,Eco,507,1,5,1,4,5,1,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +38756,100057,Female,Loyal Customer,26,Personal Travel,Eco,220,1,5,1,2,2,1,2,2,2,4,3,5,2,2,29,29.0,neutral or dissatisfied +38757,81854,Male,Loyal Customer,52,Business travel,Business,1416,4,4,4,4,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +38758,90956,Male,Loyal Customer,80,Business travel,Business,444,4,4,4,4,4,4,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +38759,122345,Female,Loyal Customer,51,Business travel,Business,529,2,2,4,2,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +38760,128402,Female,Loyal Customer,49,Business travel,Business,3784,4,3,4,3,3,4,3,4,4,3,4,2,4,1,10,14.0,neutral or dissatisfied +38761,101527,Male,Loyal Customer,28,Personal Travel,Eco,345,3,4,3,4,2,3,2,2,4,4,2,4,2,2,0,0.0,neutral or dissatisfied +38762,76874,Female,Loyal Customer,49,Business travel,Business,2377,3,3,3,3,2,4,4,4,4,4,4,4,4,4,6,5.0,satisfied +38763,55441,Female,Loyal Customer,55,Personal Travel,Eco,2521,0,1,0,2,0,1,1,2,1,1,2,1,3,1,0,0.0,satisfied +38764,100058,Female,Loyal Customer,26,Personal Travel,Eco,289,5,4,5,1,4,5,4,4,3,5,4,4,4,4,0,0.0,satisfied +38765,89101,Female,Loyal Customer,55,Business travel,Business,1919,1,1,3,1,2,3,5,5,5,5,5,3,5,5,56,37.0,satisfied +38766,127151,Male,Loyal Customer,62,Personal Travel,Eco,621,2,4,2,4,5,2,1,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +38767,124286,Male,disloyal Customer,64,Business travel,Business,255,4,4,4,3,2,4,4,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +38768,94025,Male,disloyal Customer,25,Business travel,Business,239,2,5,2,2,2,2,2,2,4,5,4,3,4,2,4,6.0,neutral or dissatisfied +38769,1798,Female,disloyal Customer,44,Business travel,Business,408,5,5,5,4,2,5,2,2,5,4,4,4,5,2,0,0.0,satisfied +38770,2885,Female,Loyal Customer,14,Personal Travel,Eco,491,1,4,1,4,5,1,5,5,3,2,4,4,5,5,11,0.0,neutral or dissatisfied +38771,40817,Female,Loyal Customer,23,Business travel,Business,2254,3,3,3,3,3,3,3,3,3,2,4,4,4,3,4,0.0,neutral or dissatisfied +38772,108174,Female,Loyal Customer,45,Personal Travel,Eco,990,4,5,4,4,4,4,5,2,2,4,2,3,2,3,0,6.0,neutral or dissatisfied +38773,28799,Male,disloyal Customer,48,Business travel,Eco,1050,2,1,1,4,1,1,1,1,2,4,1,3,2,1,0,6.0,neutral or dissatisfied +38774,25387,Male,Loyal Customer,44,Business travel,Eco Plus,591,4,1,1,1,5,4,5,5,4,1,2,1,5,5,3,1.0,satisfied +38775,35344,Female,disloyal Customer,29,Business travel,Eco,1028,1,1,1,3,1,2,2,1,5,3,3,2,3,2,101,210.0,neutral or dissatisfied +38776,109271,Female,Loyal Customer,20,Personal Travel,Eco Plus,612,4,5,4,2,4,4,4,4,5,4,4,5,5,4,12,3.0,neutral or dissatisfied +38777,54323,Male,disloyal Customer,29,Business travel,Eco,1009,3,3,3,3,3,3,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +38778,93334,Male,Loyal Customer,56,Business travel,Business,3971,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +38779,51683,Male,disloyal Customer,21,Business travel,Eco,451,4,4,4,4,3,4,3,3,2,2,2,3,4,3,0,1.0,satisfied +38780,30087,Female,Loyal Customer,55,Personal Travel,Eco,399,2,5,2,2,2,1,1,4,4,5,4,1,4,1,204,199.0,neutral or dissatisfied +38781,15625,Female,Loyal Customer,54,Personal Travel,Eco,296,3,5,3,3,3,4,5,2,2,3,2,5,2,5,10,26.0,neutral or dissatisfied +38782,41180,Female,Loyal Customer,24,Business travel,Eco Plus,1117,5,3,5,5,5,5,4,5,5,5,5,2,1,5,0,0.0,satisfied +38783,34133,Female,Loyal Customer,56,Business travel,Eco,1189,5,4,4,4,1,3,2,5,5,5,5,1,5,3,0,0.0,satisfied +38784,31672,Female,Loyal Customer,52,Business travel,Eco,853,4,3,5,5,3,3,3,5,5,4,5,3,5,5,0,0.0,satisfied +38785,42476,Male,Loyal Customer,48,Personal Travel,Eco,395,2,3,2,2,3,2,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +38786,64616,Female,Loyal Customer,60,Business travel,Business,1632,4,4,4,4,4,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +38787,45540,Male,Loyal Customer,46,Business travel,Eco,566,4,2,2,2,3,4,3,3,1,4,3,4,4,3,50,46.0,satisfied +38788,74640,Female,Loyal Customer,38,Business travel,Business,1578,2,2,2,2,2,4,3,5,5,5,5,5,5,1,0,0.0,satisfied +38789,114724,Female,Loyal Customer,49,Business travel,Business,2849,5,5,5,5,4,5,4,5,5,5,5,3,5,3,23,14.0,satisfied +38790,7399,Male,Loyal Customer,57,Business travel,Business,522,4,4,4,4,5,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +38791,57568,Female,Loyal Customer,45,Business travel,Eco,1597,4,3,3,3,2,4,4,4,4,4,4,2,4,4,4,21.0,neutral or dissatisfied +38792,9763,Female,Loyal Customer,56,Business travel,Business,383,3,3,3,3,5,4,4,4,4,4,4,4,4,4,28,24.0,satisfied +38793,60242,Male,Loyal Customer,62,Personal Travel,Eco,1506,3,2,3,4,2,3,2,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +38794,16143,Female,Loyal Customer,52,Personal Travel,Business,277,2,3,2,3,4,3,4,1,1,2,1,3,1,3,11,8.0,neutral or dissatisfied +38795,104981,Male,disloyal Customer,32,Business travel,Business,337,2,2,2,3,2,2,2,2,3,5,4,3,5,2,8,5.0,neutral or dissatisfied +38796,42726,Male,Loyal Customer,25,Personal Travel,Eco Plus,912,2,5,1,2,5,1,4,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +38797,9835,Female,Loyal Customer,47,Personal Travel,Business,642,2,5,2,3,3,5,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +38798,14472,Male,Loyal Customer,41,Personal Travel,Eco,674,3,5,3,4,3,3,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +38799,77044,Male,Loyal Customer,59,Business travel,Business,3474,1,1,1,1,4,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +38800,83850,Male,Loyal Customer,43,Personal Travel,Eco,425,2,0,4,2,2,4,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +38801,98963,Female,disloyal Customer,22,Business travel,Eco,543,3,1,3,3,2,3,2,2,3,2,3,4,4,2,41,34.0,neutral or dissatisfied +38802,109700,Female,Loyal Customer,70,Personal Travel,Eco Plus,973,3,4,3,2,5,5,4,2,2,3,2,5,2,3,42,24.0,neutral or dissatisfied +38803,106597,Male,Loyal Customer,46,Business travel,Eco,986,4,4,4,4,4,4,4,3,1,4,4,4,3,4,155,142.0,neutral or dissatisfied +38804,46833,Male,disloyal Customer,22,Business travel,Eco,845,5,5,5,1,5,5,5,5,4,3,4,1,3,5,15,9.0,satisfied +38805,121613,Male,Loyal Customer,32,Personal Travel,Eco,912,3,4,3,1,5,3,5,5,3,3,4,5,4,5,7,0.0,neutral or dissatisfied +38806,74591,Female,Loyal Customer,71,Business travel,Eco,1438,4,2,2,2,1,4,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +38807,21666,Female,Loyal Customer,48,Business travel,Eco,746,3,3,3,3,5,2,1,3,3,3,3,3,3,3,0,0.0,satisfied +38808,27472,Male,disloyal Customer,21,Business travel,Eco,978,2,2,2,4,2,2,2,2,2,4,3,2,4,2,19,14.0,neutral or dissatisfied +38809,111646,Female,Loyal Customer,57,Personal Travel,Eco,1558,5,5,5,4,3,3,5,1,1,5,1,5,1,5,19,26.0,satisfied +38810,2974,Female,Loyal Customer,56,Business travel,Business,462,2,2,2,2,5,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +38811,20512,Male,Loyal Customer,12,Personal Travel,Eco Plus,139,3,0,3,4,1,3,1,1,3,5,5,3,4,1,0,22.0,neutral or dissatisfied +38812,67773,Female,disloyal Customer,23,Business travel,Eco,1431,2,2,2,3,1,2,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +38813,9132,Female,Loyal Customer,40,Business travel,Business,826,3,3,2,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +38814,122952,Male,Loyal Customer,54,Business travel,Business,507,3,2,2,2,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +38815,30835,Male,Loyal Customer,66,Personal Travel,Eco,955,2,4,2,1,2,2,2,2,5,5,5,4,5,2,31,39.0,neutral or dissatisfied +38816,120933,Male,disloyal Customer,25,Business travel,Eco,1013,4,4,4,4,2,4,4,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +38817,118827,Female,Loyal Customer,66,Business travel,Eco Plus,338,4,3,3,3,4,2,2,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +38818,119865,Male,Loyal Customer,42,Personal Travel,Eco,912,3,4,3,4,3,3,3,3,3,5,4,5,4,3,3,19.0,neutral or dissatisfied +38819,63092,Female,disloyal Customer,28,Business travel,Business,909,3,3,3,4,4,3,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +38820,114171,Female,Loyal Customer,54,Business travel,Business,3630,2,1,2,2,5,4,5,4,4,4,4,5,4,5,5,0.0,satisfied +38821,21918,Male,Loyal Customer,46,Business travel,Business,3399,2,2,2,2,2,4,2,5,5,4,5,1,5,1,0,0.0,satisfied +38822,49746,Female,Loyal Customer,47,Business travel,Business,363,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +38823,56675,Male,Loyal Customer,15,Personal Travel,Eco,997,1,2,1,3,3,1,3,3,1,4,4,4,3,3,42,64.0,neutral or dissatisfied +38824,48466,Male,Loyal Customer,48,Business travel,Eco,776,4,3,3,3,4,4,4,4,3,2,5,3,4,4,7,10.0,satisfied +38825,81669,Female,Loyal Customer,54,Business travel,Business,907,3,3,3,3,4,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +38826,5283,Male,Loyal Customer,69,Personal Travel,Eco,351,2,5,2,5,4,2,4,4,5,5,4,5,4,4,0,13.0,neutral or dissatisfied +38827,54538,Female,Loyal Customer,19,Personal Travel,Eco,925,3,5,2,3,4,2,2,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +38828,5795,Female,Loyal Customer,54,Business travel,Business,157,1,1,1,1,4,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +38829,47859,Female,Loyal Customer,27,Business travel,Business,3864,1,4,4,4,1,1,1,1,1,5,4,3,3,1,11,9.0,neutral or dissatisfied +38830,23928,Female,Loyal Customer,65,Personal Travel,Eco,579,3,4,2,2,3,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +38831,98731,Female,Loyal Customer,41,Business travel,Business,1558,3,3,4,3,5,5,4,4,4,4,4,5,4,5,23,42.0,satisfied +38832,23409,Male,Loyal Customer,35,Business travel,Business,1673,3,2,2,2,5,4,3,3,3,3,3,1,3,2,1,0.0,neutral or dissatisfied +38833,64016,Male,Loyal Customer,38,Business travel,Business,2218,5,5,3,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +38834,116457,Female,Loyal Customer,67,Personal Travel,Eco,362,2,4,3,3,5,5,5,5,5,3,5,4,5,3,5,0.0,neutral or dissatisfied +38835,19036,Female,Loyal Customer,40,Business travel,Eco Plus,788,3,4,4,4,3,4,3,3,1,1,3,5,5,3,0,35.0,satisfied +38836,114005,Male,Loyal Customer,66,Personal Travel,Eco,1855,3,3,2,3,5,2,5,5,2,4,3,1,4,5,0,0.0,neutral or dissatisfied +38837,121898,Male,Loyal Customer,62,Personal Travel,Eco,366,3,4,4,5,4,4,1,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +38838,79771,Male,Loyal Customer,44,Business travel,Business,3531,1,1,1,1,4,5,5,4,4,5,4,4,4,4,14,0.0,satisfied +38839,64115,Male,Loyal Customer,43,Business travel,Business,2288,5,1,5,5,3,3,3,5,4,4,5,3,5,3,0,0.0,satisfied +38840,115720,Female,Loyal Customer,37,Business travel,Business,372,4,2,5,2,5,4,3,4,4,4,4,1,4,1,4,11.0,neutral or dissatisfied +38841,60465,Female,disloyal Customer,20,Business travel,Eco,862,2,2,2,3,5,2,5,5,1,4,4,4,4,5,35,32.0,neutral or dissatisfied +38842,43287,Female,Loyal Customer,38,Business travel,Business,387,1,1,1,1,2,3,5,3,3,4,3,3,3,2,0,0.0,satisfied +38843,75487,Male,Loyal Customer,41,Business travel,Business,2342,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +38844,89914,Female,Loyal Customer,29,Business travel,Business,1981,2,2,4,2,2,2,2,2,3,4,4,1,3,2,69,52.0,neutral or dissatisfied +38845,75628,Female,Loyal Customer,43,Business travel,Business,337,2,2,4,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +38846,58959,Male,Loyal Customer,50,Business travel,Business,1846,2,2,2,2,2,4,5,5,5,5,5,5,5,3,64,50.0,satisfied +38847,69038,Female,Loyal Customer,31,Business travel,Business,1521,2,2,2,2,5,5,5,5,4,2,4,3,4,5,0,0.0,satisfied +38848,87126,Female,Loyal Customer,41,Personal Travel,Eco,594,2,2,2,3,2,2,4,2,3,4,2,2,2,2,9,5.0,neutral or dissatisfied +38849,103424,Female,Loyal Customer,65,Personal Travel,Eco,237,2,1,2,4,3,4,4,4,4,2,4,4,4,3,19,12.0,neutral or dissatisfied +38850,65535,Male,Loyal Customer,56,Personal Travel,Eco Plus,1616,2,5,2,2,5,2,5,5,5,4,4,3,5,5,5,17.0,neutral or dissatisfied +38851,98010,Female,Loyal Customer,28,Business travel,Business,3263,3,3,3,3,5,5,5,5,5,3,4,5,4,5,1,0.0,satisfied +38852,106984,Female,Loyal Customer,39,Personal Travel,Eco,937,1,1,1,3,2,1,2,2,1,2,3,1,3,2,45,55.0,neutral or dissatisfied +38853,118684,Male,Loyal Customer,25,Personal Travel,Eco,368,3,5,3,1,3,3,3,3,2,5,2,5,4,3,4,0.0,neutral or dissatisfied +38854,108020,Male,Loyal Customer,60,Business travel,Eco,589,3,3,5,5,3,3,3,3,4,1,4,1,3,3,20,0.0,neutral or dissatisfied +38855,35731,Male,Loyal Customer,18,Personal Travel,Eco Plus,2576,1,1,1,4,1,3,3,1,1,3,3,3,2,3,173,174.0,neutral or dissatisfied +38856,59933,Female,Loyal Customer,35,Business travel,Eco,1085,2,5,5,5,2,2,2,2,3,2,3,1,4,2,20,12.0,neutral or dissatisfied +38857,100829,Male,Loyal Customer,52,Business travel,Business,2872,5,4,5,5,5,5,5,4,4,5,4,5,4,3,1,1.0,satisfied +38858,71501,Male,Loyal Customer,66,Personal Travel,Business,1197,3,4,3,2,3,4,5,1,1,3,1,2,1,5,0,0.0,neutral or dissatisfied +38859,117994,Female,Loyal Customer,39,Business travel,Eco Plus,255,2,2,2,2,2,2,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +38860,89284,Male,disloyal Customer,27,Business travel,Business,453,2,1,1,1,2,1,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +38861,121759,Male,Loyal Customer,55,Business travel,Business,449,3,4,4,4,1,4,4,3,3,3,3,2,3,4,44,41.0,neutral or dissatisfied +38862,4847,Male,Loyal Customer,42,Business travel,Eco,408,3,1,1,1,3,3,3,3,1,1,4,3,3,3,0,4.0,neutral or dissatisfied +38863,101070,Female,Loyal Customer,53,Business travel,Business,2051,1,1,1,1,3,4,4,4,4,4,4,4,4,4,14,4.0,satisfied +38864,39874,Male,Loyal Customer,23,Personal Travel,Eco,272,1,4,1,3,5,1,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +38865,95546,Female,Loyal Customer,42,Personal Travel,Eco Plus,496,2,4,2,4,5,5,5,4,4,2,4,5,4,5,40,34.0,neutral or dissatisfied +38866,63136,Male,Loyal Customer,57,Business travel,Business,337,4,2,2,2,5,2,3,4,4,4,4,4,4,3,42,44.0,neutral or dissatisfied +38867,63919,Male,Loyal Customer,74,Business travel,Business,3310,4,4,4,4,2,4,4,5,5,5,5,4,5,1,0,0.0,satisfied +38868,91424,Female,Loyal Customer,45,Business travel,Eco,549,3,4,5,5,1,4,4,3,3,3,3,1,3,4,24,34.0,neutral or dissatisfied +38869,97305,Female,disloyal Customer,21,Business travel,Eco,872,0,0,0,4,4,0,4,4,3,3,4,3,4,4,16,5.0,satisfied +38870,91806,Male,Loyal Customer,41,Personal Travel,Eco,626,3,5,3,1,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +38871,51424,Male,Loyal Customer,64,Personal Travel,Eco Plus,373,1,4,1,3,2,1,3,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +38872,86142,Male,Loyal Customer,54,Business travel,Business,3667,4,1,1,1,5,3,4,4,4,4,4,3,4,2,0,9.0,neutral or dissatisfied +38873,35475,Male,Loyal Customer,61,Personal Travel,Eco,1069,3,4,3,2,3,3,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +38874,65240,Male,Loyal Customer,52,Business travel,Business,3919,5,5,5,5,3,4,4,4,4,4,4,3,4,5,10,1.0,satisfied +38875,6751,Male,Loyal Customer,45,Business travel,Business,1720,1,1,1,1,4,5,4,4,4,4,4,3,4,3,11,32.0,satisfied +38876,25367,Male,Loyal Customer,48,Business travel,Eco,591,3,3,3,3,3,3,3,3,1,1,1,4,4,3,35,86.0,satisfied +38877,59316,Female,Loyal Customer,42,Business travel,Business,2486,3,3,3,3,4,4,4,4,4,4,4,4,4,4,8,0.0,satisfied +38878,23750,Male,Loyal Customer,42,Business travel,Business,2266,3,3,3,3,5,3,3,5,5,5,5,5,5,4,0,0.0,satisfied +38879,3994,Female,Loyal Customer,44,Business travel,Business,3208,3,3,3,3,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +38880,1852,Male,Loyal Customer,44,Personal Travel,Eco Plus,500,4,5,4,2,1,4,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +38881,38474,Male,Loyal Customer,16,Business travel,Business,846,5,5,5,5,4,4,4,4,3,1,2,2,1,4,0,0.0,satisfied +38882,926,Female,Loyal Customer,25,Business travel,Business,89,4,5,5,5,0,1,4,0,2,4,4,3,4,0,27,29.0,neutral or dissatisfied +38883,101814,Female,disloyal Customer,30,Business travel,Business,1521,2,2,2,1,4,2,4,4,3,2,4,3,5,4,2,4.0,neutral or dissatisfied +38884,121968,Male,disloyal Customer,27,Business travel,Business,130,0,0,0,4,4,0,4,4,3,3,4,3,5,4,14,17.0,satisfied +38885,36793,Male,Loyal Customer,20,Personal Travel,Eco,2611,3,5,3,3,3,5,5,3,1,3,2,5,4,5,0,0.0,neutral or dissatisfied +38886,39909,Female,Loyal Customer,36,Personal Travel,Eco Plus,272,4,4,4,3,4,4,4,4,5,3,4,4,5,4,122,122.0,neutral or dissatisfied +38887,34749,Male,Loyal Customer,45,Business travel,Business,209,1,1,1,1,1,3,2,4,4,4,4,1,4,4,2,0.0,satisfied +38888,12506,Male,Loyal Customer,46,Personal Travel,Eco Plus,127,2,1,2,3,2,2,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +38889,92011,Male,disloyal Customer,35,Personal Travel,Business,1532,4,5,4,2,3,4,3,3,4,2,3,5,4,3,0,0.0,neutral or dissatisfied +38890,63832,Male,disloyal Customer,22,Business travel,Business,1172,4,5,4,5,1,4,1,1,5,3,5,3,5,1,0,16.0,satisfied +38891,45705,Female,disloyal Customer,31,Business travel,Eco,1024,2,2,2,4,3,2,3,3,1,1,1,3,1,3,24,31.0,neutral or dissatisfied +38892,91999,Female,Loyal Customer,63,Personal Travel,Eco,236,1,5,1,3,4,5,4,3,3,1,5,3,3,4,0,11.0,neutral or dissatisfied +38893,83274,Female,Loyal Customer,38,Personal Travel,Eco,1979,0,4,0,5,3,0,3,3,2,5,4,4,2,3,14,28.0,satisfied +38894,58674,Male,Loyal Customer,38,Business travel,Business,622,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +38895,110371,Male,Loyal Customer,54,Business travel,Eco,787,2,4,4,4,2,2,2,2,2,5,3,2,4,2,2,7.0,neutral or dissatisfied +38896,67819,Female,Loyal Customer,16,Business travel,Business,2661,4,4,4,4,4,4,4,4,4,5,3,3,4,4,2,0.0,neutral or dissatisfied +38897,47884,Male,Loyal Customer,38,Business travel,Business,2606,5,5,5,5,4,1,3,4,4,4,4,1,4,5,4,0.0,satisfied +38898,33932,Female,Loyal Customer,20,Business travel,Business,3738,4,4,4,4,5,5,5,5,2,1,3,3,2,5,1,13.0,satisfied +38899,84785,Female,Loyal Customer,55,Business travel,Business,3273,2,2,1,2,5,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +38900,18002,Female,Loyal Customer,51,Business travel,Eco,332,4,5,5,5,3,1,2,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +38901,30812,Male,Loyal Customer,50,Business travel,Eco Plus,1199,5,4,4,4,5,5,5,5,4,2,4,5,1,5,0,0.0,satisfied +38902,101218,Male,Loyal Customer,47,Personal Travel,Eco,583,4,5,4,1,3,4,3,3,5,2,4,3,4,3,70,58.0,neutral or dissatisfied +38903,35233,Female,Loyal Customer,27,Business travel,Business,2486,2,2,2,2,4,4,4,4,4,5,3,1,1,4,0,0.0,satisfied +38904,22863,Female,Loyal Customer,35,Personal Travel,Eco,147,4,4,4,2,3,4,1,3,5,4,4,3,5,3,38,30.0,neutral or dissatisfied +38905,84103,Male,Loyal Customer,57,Business travel,Business,879,5,5,5,5,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +38906,672,Male,Loyal Customer,44,Business travel,Business,2525,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,16.0,satisfied +38907,50468,Female,Loyal Customer,22,Business travel,Business,2499,2,3,3,3,2,2,2,2,4,5,4,4,4,2,2,0.0,neutral or dissatisfied +38908,42624,Female,Loyal Customer,49,Business travel,Business,3108,3,3,3,3,5,3,3,4,4,4,4,5,4,3,0,0.0,satisfied +38909,30796,Male,Loyal Customer,63,Business travel,Business,2575,1,5,5,5,1,4,3,1,1,1,1,1,1,4,16,10.0,neutral or dissatisfied +38910,126198,Male,Loyal Customer,43,Business travel,Business,2321,2,2,2,2,5,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +38911,41019,Male,Loyal Customer,29,Business travel,Business,2870,4,4,4,4,5,5,5,5,4,2,1,4,3,5,0,0.0,satisfied +38912,101383,Male,Loyal Customer,44,Business travel,Business,3411,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +38913,61062,Male,Loyal Customer,54,Business travel,Eco,1703,3,5,5,5,4,3,4,4,4,4,3,3,4,4,49,74.0,neutral or dissatisfied +38914,123944,Female,disloyal Customer,51,Business travel,Eco Plus,541,3,2,2,1,4,3,4,4,3,5,2,4,2,4,1,0.0,neutral or dissatisfied +38915,86891,Female,Loyal Customer,46,Business travel,Business,341,1,1,1,1,3,4,3,1,1,1,1,4,1,2,9,1.0,neutral or dissatisfied +38916,107667,Female,disloyal Customer,21,Business travel,Eco,405,1,5,1,5,3,1,3,3,3,5,5,4,5,3,0,14.0,neutral or dissatisfied +38917,120658,Male,Loyal Customer,43,Business travel,Eco,280,2,4,4,4,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +38918,11451,Male,Loyal Customer,33,Business travel,Eco Plus,224,3,3,3,3,3,3,3,3,3,1,4,3,3,3,62,58.0,neutral or dissatisfied +38919,63007,Female,disloyal Customer,21,Business travel,Business,862,2,3,1,4,1,1,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +38920,59635,Female,disloyal Customer,10,Business travel,Eco,964,0,0,0,2,1,0,1,1,3,2,4,5,4,1,10,0.0,satisfied +38921,50715,Female,Loyal Customer,15,Personal Travel,Eco,153,3,4,3,2,3,3,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +38922,80765,Female,Loyal Customer,12,Personal Travel,Eco,440,4,4,4,1,1,4,1,1,4,5,5,4,5,1,0,0.0,satisfied +38923,60953,Female,Loyal Customer,46,Business travel,Eco,888,2,5,5,5,4,3,4,2,2,2,2,2,2,2,0,9.0,neutral or dissatisfied +38924,44623,Male,disloyal Customer,23,Business travel,Eco,67,0,0,0,2,2,0,2,2,3,2,5,3,4,2,70,72.0,satisfied +38925,40673,Female,Loyal Customer,35,Personal Travel,Business,590,1,4,1,3,4,4,4,4,4,1,2,3,4,5,0,0.0,neutral or dissatisfied +38926,79673,Male,Loyal Customer,34,Personal Travel,Eco,760,1,2,1,4,2,1,4,2,1,3,4,1,4,2,6,31.0,neutral or dissatisfied +38927,21020,Female,disloyal Customer,61,Business travel,Eco,227,0,5,0,4,4,0,4,4,2,3,2,1,1,4,0,0.0,satisfied +38928,35539,Female,Loyal Customer,45,Personal Travel,Eco,1097,2,5,2,4,5,5,5,5,5,2,5,4,5,5,0,48.0,neutral or dissatisfied +38929,24690,Female,Loyal Customer,9,Personal Travel,Eco,761,1,5,1,3,1,1,1,3,4,4,4,1,5,1,286,290.0,neutral or dissatisfied +38930,52407,Male,Loyal Customer,49,Personal Travel,Eco,261,3,5,3,4,2,3,2,2,4,1,3,4,2,2,2,0.0,neutral or dissatisfied +38931,79406,Male,Loyal Customer,27,Business travel,Business,502,2,3,4,3,2,1,2,2,1,3,3,1,2,2,76,57.0,neutral or dissatisfied +38932,53910,Female,Loyal Customer,7,Personal Travel,Eco,191,2,3,2,3,2,2,5,2,1,1,4,5,3,2,10,4.0,neutral or dissatisfied +38933,434,Female,Loyal Customer,27,Personal Travel,Business,158,3,5,3,5,3,3,3,3,3,3,5,4,5,3,24,23.0,neutral or dissatisfied +38934,89513,Male,Loyal Customer,46,Business travel,Business,2475,3,3,5,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +38935,26971,Male,Loyal Customer,27,Business travel,Eco,954,4,2,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +38936,123948,Female,disloyal Customer,25,Business travel,Eco Plus,544,4,4,5,3,5,5,5,5,3,2,4,2,3,5,24,84.0,neutral or dissatisfied +38937,122836,Male,Loyal Customer,35,Personal Travel,Business,226,0,5,0,2,4,4,4,1,1,0,1,5,1,4,0,0.0,satisfied +38938,107507,Male,Loyal Customer,32,Personal Travel,Eco,711,1,3,1,3,1,1,1,1,5,3,3,5,2,1,17,73.0,neutral or dissatisfied +38939,30408,Male,Loyal Customer,52,Personal Travel,Eco,641,2,2,2,3,3,2,2,3,3,4,4,4,3,3,0,0.0,neutral or dissatisfied +38940,43727,Female,Loyal Customer,28,Business travel,Eco Plus,489,5,2,2,2,5,5,5,5,4,5,3,5,2,5,0,0.0,satisfied +38941,25769,Female,Loyal Customer,44,Business travel,Business,2060,2,1,1,1,3,3,4,2,2,2,2,1,2,4,27,49.0,neutral or dissatisfied +38942,90683,Male,Loyal Customer,41,Business travel,Business,2132,1,1,1,1,2,4,5,5,5,5,5,4,5,5,3,4.0,satisfied +38943,58036,Female,Loyal Customer,17,Business travel,Business,589,1,4,4,4,1,1,1,2,3,3,4,1,3,1,194,211.0,neutral or dissatisfied +38944,70162,Female,Loyal Customer,38,Personal Travel,Eco,550,1,5,2,3,4,2,4,4,4,5,5,1,5,4,5,0.0,neutral or dissatisfied +38945,39925,Female,Loyal Customer,23,Business travel,Eco,1087,4,4,4,4,4,4,4,4,3,4,4,3,3,4,31,23.0,satisfied +38946,125570,Female,Loyal Customer,37,Personal Travel,Eco,226,2,5,2,5,3,2,3,3,3,3,5,4,5,3,3,0.0,neutral or dissatisfied +38947,82028,Male,Loyal Customer,64,Personal Travel,Eco,1522,2,1,2,3,1,2,1,1,4,2,4,4,3,1,0,7.0,neutral or dissatisfied +38948,56423,Male,Loyal Customer,50,Business travel,Business,1578,3,3,3,3,2,4,5,4,4,4,4,5,4,5,38,29.0,satisfied +38949,71769,Female,Loyal Customer,46,Business travel,Business,1723,1,1,1,1,5,5,4,4,4,5,4,4,4,5,9,0.0,satisfied +38950,47452,Male,Loyal Customer,44,Personal Travel,Eco,574,2,5,2,3,2,2,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +38951,85610,Female,Loyal Customer,10,Personal Travel,Eco,259,3,2,0,3,5,0,5,5,4,4,4,4,3,5,0,0.0,neutral or dissatisfied +38952,87275,Female,Loyal Customer,29,Business travel,Business,577,3,3,3,3,3,3,3,3,2,4,3,2,4,3,0,0.0,neutral or dissatisfied +38953,32412,Female,Loyal Customer,17,Business travel,Business,101,2,5,5,5,2,2,2,2,2,3,4,1,4,2,0,0.0,neutral or dissatisfied +38954,109025,Female,disloyal Customer,22,Business travel,Business,849,5,5,5,1,5,5,5,5,4,5,4,4,4,5,1,1.0,satisfied +38955,38831,Male,Loyal Customer,31,Personal Travel,Eco,354,3,1,3,3,4,3,4,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +38956,116472,Male,Loyal Customer,32,Personal Travel,Eco,371,3,3,3,2,5,3,5,5,1,5,2,5,4,5,26,22.0,neutral or dissatisfied +38957,51391,Female,Loyal Customer,15,Personal Travel,Eco Plus,89,1,4,0,2,5,0,5,5,4,2,4,5,5,5,8,21.0,neutral or dissatisfied +38958,104806,Male,Loyal Customer,26,Personal Travel,Eco,587,2,5,2,2,2,2,2,2,5,3,5,4,4,2,0,5.0,neutral or dissatisfied +38959,13108,Male,disloyal Customer,24,Business travel,Eco,427,2,0,2,2,2,2,2,2,1,5,1,4,3,2,0,0.0,neutral or dissatisfied +38960,92534,Male,Loyal Customer,30,Personal Travel,Eco,1947,4,4,4,1,4,1,5,3,2,4,5,5,3,5,138,167.0,neutral or dissatisfied +38961,108376,Female,Loyal Customer,33,Personal Travel,Eco,1728,2,5,2,3,4,2,4,4,3,4,3,3,1,4,79,61.0,neutral or dissatisfied +38962,80749,Female,Loyal Customer,30,Personal Travel,Eco,393,1,4,1,1,1,1,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +38963,69167,Female,Loyal Customer,32,Business travel,Business,2866,4,4,4,4,4,4,5,4,3,2,5,4,5,4,16,14.0,satisfied +38964,46626,Male,Loyal Customer,34,Business travel,Eco,251,1,3,3,3,1,1,1,1,1,1,1,2,4,1,0,0.0,neutral or dissatisfied +38965,1761,Male,Loyal Customer,59,Personal Travel,Eco Plus,364,3,5,3,3,1,3,1,1,3,5,4,5,5,1,4,0.0,neutral or dissatisfied +38966,112192,Male,Loyal Customer,25,Business travel,Business,2769,2,2,2,2,4,4,4,4,3,2,5,3,5,4,19,13.0,satisfied +38967,85143,Male,Loyal Customer,51,Business travel,Business,3747,4,3,3,3,1,3,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +38968,18013,Male,Loyal Customer,46,Personal Travel,Eco,332,3,5,1,3,2,1,2,2,3,1,1,2,3,2,0,24.0,neutral or dissatisfied +38969,31440,Female,Loyal Customer,24,Business travel,Eco,1541,2,3,3,3,2,2,2,2,2,1,2,1,2,2,2,0.0,neutral or dissatisfied +38970,38174,Female,Loyal Customer,35,Personal Travel,Eco,1121,2,4,1,2,1,1,5,1,5,5,5,4,5,1,10,0.0,neutral or dissatisfied +38971,64380,Female,Loyal Customer,7,Personal Travel,Eco,1192,2,4,1,5,2,1,1,2,4,2,3,3,4,2,37,32.0,neutral or dissatisfied +38972,90503,Female,Loyal Customer,44,Business travel,Business,1827,3,3,3,3,2,5,5,2,2,2,2,5,2,4,23,17.0,satisfied +38973,59486,Male,disloyal Customer,31,Business travel,Eco,921,3,2,2,4,3,2,3,3,1,5,3,2,4,3,125,113.0,neutral or dissatisfied +38974,42495,Female,Loyal Customer,63,Business travel,Eco Plus,185,2,3,3,3,2,1,2,2,2,2,2,1,2,3,4,2.0,neutral or dissatisfied +38975,41551,Female,Loyal Customer,22,Business travel,Business,1464,3,5,5,5,3,3,3,3,4,4,3,2,3,3,26,24.0,neutral or dissatisfied +38976,91298,Female,Loyal Customer,28,Business travel,Business,3859,1,1,1,1,5,5,5,5,5,4,5,3,4,5,10,6.0,satisfied +38977,25578,Female,disloyal Customer,29,Business travel,Eco,874,4,4,4,4,4,4,4,4,1,4,4,2,3,4,54,47.0,neutral or dissatisfied +38978,4104,Female,Loyal Customer,32,Business travel,Business,2938,1,1,1,1,5,5,5,5,5,4,5,3,5,5,11,1.0,satisfied +38979,104070,Female,Loyal Customer,40,Business travel,Business,359,2,2,3,2,3,5,5,4,4,4,4,5,4,3,6,0.0,satisfied +38980,94194,Male,disloyal Customer,22,Business travel,Eco,496,1,0,1,1,2,1,2,2,3,3,4,4,5,2,7,0.0,neutral or dissatisfied +38981,70808,Male,Loyal Customer,52,Business travel,Business,1542,1,5,5,5,3,3,3,1,1,1,1,3,1,2,2,0.0,neutral or dissatisfied +38982,83406,Female,disloyal Customer,27,Business travel,Eco,632,3,4,3,3,1,3,1,1,1,1,3,2,3,1,57,45.0,neutral or dissatisfied +38983,31401,Female,Loyal Customer,10,Personal Travel,Eco,1199,3,3,3,4,1,3,1,1,2,3,3,3,4,1,12,20.0,neutral or dissatisfied +38984,114383,Female,Loyal Customer,29,Personal Travel,Eco Plus,957,3,5,3,4,4,3,4,4,4,5,4,3,5,4,0,3.0,neutral or dissatisfied +38985,119955,Male,disloyal Customer,21,Business travel,Business,1009,0,5,0,2,5,0,5,5,3,4,5,4,4,5,0,0.0,satisfied +38986,62832,Male,Loyal Customer,45,Business travel,Business,2367,4,4,4,4,5,3,5,5,5,5,5,3,5,3,8,4.0,satisfied +38987,28452,Male,disloyal Customer,21,Business travel,Eco,1037,3,3,3,2,3,5,3,2,1,4,3,3,5,3,13,0.0,neutral or dissatisfied +38988,52454,Male,Loyal Customer,41,Business travel,Eco Plus,455,4,4,4,4,4,4,4,4,1,1,2,1,1,4,0,2.0,satisfied +38989,112854,Female,disloyal Customer,29,Business travel,Business,1390,0,0,0,5,5,0,5,5,5,3,5,5,4,5,29,3.0,satisfied +38990,71595,Male,Loyal Customer,55,Business travel,Business,1012,2,2,2,2,5,1,2,2,2,2,2,1,2,4,8,11.0,neutral or dissatisfied +38991,63049,Female,Loyal Customer,17,Personal Travel,Eco,862,3,5,3,2,5,3,5,5,4,5,5,4,5,5,3,3.0,neutral or dissatisfied +38992,89199,Male,Loyal Customer,53,Personal Travel,Eco,1947,2,3,2,2,3,2,3,3,3,3,2,1,3,3,30,20.0,neutral or dissatisfied +38993,99676,Male,Loyal Customer,54,Business travel,Business,3624,5,5,5,5,2,5,5,4,4,4,4,3,4,5,18,7.0,satisfied +38994,80883,Female,disloyal Customer,34,Business travel,Business,692,4,4,4,3,1,4,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +38995,62249,Female,Loyal Customer,64,Personal Travel,Eco,2565,3,3,3,3,4,3,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +38996,60797,Male,Loyal Customer,47,Business travel,Business,472,3,3,3,3,4,4,5,3,3,4,3,4,3,5,32,43.0,satisfied +38997,26262,Female,disloyal Customer,19,Business travel,Business,859,4,0,4,1,2,4,3,2,4,4,4,3,5,2,1,0.0,satisfied +38998,35352,Female,disloyal Customer,48,Business travel,Eco,944,4,3,3,4,5,3,1,5,3,2,3,4,4,5,0,24.0,neutral or dissatisfied +38999,37572,Female,disloyal Customer,23,Business travel,Eco,676,4,4,4,4,5,4,5,5,3,5,3,4,4,5,81,91.0,neutral or dissatisfied +39000,98166,Female,Loyal Customer,32,Personal Travel,Eco,745,3,5,3,5,1,3,1,1,3,2,5,3,5,1,0,8.0,neutral or dissatisfied +39001,81411,Female,disloyal Customer,25,Business travel,Business,448,3,0,4,4,1,4,1,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +39002,108805,Male,Loyal Customer,27,Personal Travel,Eco,404,2,4,2,3,3,2,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +39003,121942,Female,disloyal Customer,36,Business travel,Business,430,3,3,3,4,5,3,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +39004,112335,Male,disloyal Customer,22,Business travel,Eco,819,2,2,2,5,4,2,4,4,5,2,5,5,5,4,117,113.0,neutral or dissatisfied +39005,95748,Female,Loyal Customer,51,Business travel,Business,237,2,2,2,2,2,3,4,5,5,5,5,5,5,4,10,0.0,satisfied +39006,113081,Male,Loyal Customer,32,Business travel,Business,2353,3,3,3,3,4,4,4,4,5,4,5,4,4,4,18,5.0,satisfied +39007,119162,Female,Loyal Customer,41,Business travel,Business,331,3,3,3,3,5,5,5,5,5,5,5,3,5,3,53,50.0,satisfied +39008,129151,Male,disloyal Customer,42,Business travel,Business,954,2,3,3,5,5,2,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +39009,17526,Female,Loyal Customer,46,Personal Travel,Eco,341,2,3,2,4,4,4,3,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +39010,6001,Male,Loyal Customer,57,Business travel,Business,1769,3,3,3,3,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +39011,76649,Female,Loyal Customer,65,Personal Travel,Eco,481,4,2,4,4,4,3,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +39012,112204,Male,Loyal Customer,28,Business travel,Business,3090,2,1,1,1,2,2,2,2,4,2,4,4,3,2,9,26.0,neutral or dissatisfied +39013,35034,Female,disloyal Customer,44,Business travel,Eco,718,3,3,3,3,5,3,5,5,2,4,4,4,4,5,0,18.0,neutral or dissatisfied +39014,54270,Male,Loyal Customer,24,Personal Travel,Eco,1222,2,5,2,2,4,2,4,4,5,3,1,3,2,4,4,0.0,neutral or dissatisfied +39015,120278,Male,Loyal Customer,32,Business travel,Business,1576,2,1,1,1,2,2,2,2,3,5,2,2,2,2,69,64.0,neutral or dissatisfied +39016,124,Female,Loyal Customer,7,Personal Travel,Eco,562,1,5,1,2,2,1,5,2,5,2,5,4,5,2,0,2.0,neutral or dissatisfied +39017,40527,Female,disloyal Customer,24,Business travel,Eco,517,0,5,1,3,1,1,1,1,3,5,5,5,5,1,0,0.0,satisfied +39018,66641,Male,Loyal Customer,53,Business travel,Business,3269,3,4,4,4,1,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +39019,38338,Female,Loyal Customer,59,Business travel,Business,1050,5,2,5,5,3,1,2,5,5,5,5,4,5,1,0,0.0,satisfied +39020,126909,Male,Loyal Customer,45,Business travel,Business,3599,4,4,4,4,4,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +39021,52666,Female,Loyal Customer,48,Personal Travel,Eco,110,3,3,3,4,1,4,4,5,5,3,5,4,5,4,2,0.0,neutral or dissatisfied +39022,78054,Female,Loyal Customer,17,Personal Travel,Eco,332,4,5,4,1,1,4,3,1,4,3,4,1,5,1,12,10.0,neutral or dissatisfied +39023,25214,Male,Loyal Customer,46,Business travel,Eco,925,4,1,1,1,4,4,4,4,5,2,1,5,5,4,48,49.0,satisfied +39024,100638,Male,Loyal Customer,66,Business travel,Business,3790,3,3,3,3,5,3,4,3,3,3,3,4,3,3,0,6.0,neutral or dissatisfied +39025,63660,Male,Loyal Customer,52,Business travel,Business,2405,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +39026,69432,Female,Loyal Customer,53,Personal Travel,Eco,1089,4,3,4,4,3,4,4,1,1,4,1,3,1,2,0,0.0,satisfied +39027,68283,Female,Loyal Customer,59,Business travel,Business,2447,1,1,3,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +39028,34392,Female,Loyal Customer,24,Business travel,Eco,728,1,3,3,3,1,1,3,1,1,5,3,1,3,1,0,0.0,neutral or dissatisfied +39029,27492,Male,Loyal Customer,34,Business travel,Business,3809,4,4,4,4,3,4,3,3,3,4,3,4,3,5,9,10.0,satisfied +39030,45426,Female,Loyal Customer,60,Business travel,Business,2435,2,3,3,3,5,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +39031,81016,Female,Loyal Customer,19,Business travel,Business,1399,3,3,4,3,4,5,4,4,5,4,4,3,4,4,0,0.0,satisfied +39032,73036,Male,Loyal Customer,15,Personal Travel,Eco,1096,2,1,2,3,5,2,1,5,2,3,2,2,4,5,0,0.0,neutral or dissatisfied +39033,13114,Male,Loyal Customer,42,Business travel,Business,562,4,4,4,4,1,4,3,5,5,5,5,1,5,5,45,32.0,satisfied +39034,55626,Female,Loyal Customer,58,Business travel,Business,1824,1,3,3,3,2,3,4,1,1,1,1,4,1,4,0,9.0,neutral or dissatisfied +39035,65482,Female,Loyal Customer,17,Business travel,Business,3165,2,2,2,2,4,4,4,4,5,3,1,5,5,4,0,0.0,satisfied +39036,25393,Female,Loyal Customer,34,Business travel,Business,3789,3,3,3,3,5,5,5,5,3,1,2,5,2,5,341,334.0,satisfied +39037,100174,Male,Loyal Customer,34,Personal Travel,Eco,468,2,5,2,3,2,2,2,2,4,2,5,5,4,2,26,34.0,neutral or dissatisfied +39038,120487,Male,Loyal Customer,68,Personal Travel,Eco,449,2,2,2,2,2,2,2,2,2,3,2,4,2,2,13,13.0,neutral or dissatisfied +39039,13944,Female,disloyal Customer,27,Business travel,Eco,192,2,3,2,4,2,2,2,2,3,1,4,1,4,2,0,6.0,neutral or dissatisfied +39040,75699,Male,disloyal Customer,30,Business travel,Business,813,1,1,1,3,3,1,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +39041,102673,Male,Loyal Customer,38,Business travel,Business,2293,1,3,3,3,1,3,4,1,1,1,1,4,1,1,0,10.0,neutral or dissatisfied +39042,32008,Male,Loyal Customer,24,Personal Travel,Business,102,3,3,3,2,1,3,1,1,5,1,3,1,5,1,0,0.0,neutral or dissatisfied +39043,116057,Female,Loyal Customer,70,Personal Travel,Eco,337,5,3,5,2,5,2,3,2,2,5,2,1,2,2,11,7.0,satisfied +39044,6238,Male,Loyal Customer,39,Business travel,Eco,594,3,4,4,4,3,3,3,3,4,4,2,3,3,3,53,50.0,neutral or dissatisfied +39045,58731,Male,Loyal Customer,50,Business travel,Business,3256,4,4,4,4,5,4,5,5,5,5,5,3,5,4,0,1.0,satisfied +39046,102787,Female,Loyal Customer,17,Personal Travel,Eco,1099,3,3,3,4,5,3,4,5,1,5,2,3,3,5,9,20.0,neutral or dissatisfied +39047,78920,Male,Loyal Customer,46,Business travel,Business,3966,3,3,3,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +39048,46650,Male,Loyal Customer,41,Business travel,Business,73,3,3,3,3,2,5,5,4,4,4,5,1,4,5,0,0.0,satisfied +39049,51335,Female,Loyal Customer,66,Business travel,Eco Plus,86,2,5,5,5,3,4,4,2,2,2,2,2,2,2,23,7.0,neutral or dissatisfied +39050,62537,Female,Loyal Customer,47,Business travel,Business,1846,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,18.0,satisfied +39051,33685,Male,Loyal Customer,41,Business travel,Eco,759,4,2,2,2,4,4,4,4,2,5,4,1,4,4,0,2.0,satisfied +39052,92564,Male,Loyal Customer,23,Business travel,Business,1919,2,2,2,2,2,2,2,2,3,4,3,5,4,2,0,0.0,satisfied +39053,57140,Female,Loyal Customer,49,Business travel,Business,3239,3,1,3,3,3,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +39054,71327,Male,disloyal Customer,37,Business travel,Eco,1285,2,2,2,3,4,2,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +39055,120265,Female,Loyal Customer,60,Personal Travel,Business,1576,3,5,4,4,4,3,4,4,4,4,2,4,4,5,28,36.0,neutral or dissatisfied +39056,18307,Female,Loyal Customer,57,Business travel,Business,549,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +39057,34001,Female,Loyal Customer,48,Business travel,Eco,1576,3,2,2,2,3,3,2,2,2,3,2,1,2,1,71,91.0,neutral or dissatisfied +39058,52311,Female,disloyal Customer,43,Business travel,Eco,370,2,3,2,4,3,2,3,3,2,5,3,3,4,3,0,10.0,neutral or dissatisfied +39059,42953,Female,disloyal Customer,24,Business travel,Eco,236,4,4,4,5,4,4,4,4,4,1,3,4,2,4,0,0.0,neutral or dissatisfied +39060,8708,Female,Loyal Customer,61,Personal Travel,Eco,280,0,2,0,3,1,3,4,2,2,0,2,1,2,1,0,2.0,satisfied +39061,27179,Female,Loyal Customer,34,Personal Travel,Eco,2688,3,5,3,4,3,5,5,4,3,3,5,5,5,5,1,0.0,neutral or dissatisfied +39062,58833,Female,Loyal Customer,53,Business travel,Eco Plus,1050,2,1,1,1,5,4,3,2,2,2,2,2,2,2,9,0.0,neutral or dissatisfied +39063,126670,Female,Loyal Customer,54,Business travel,Business,2276,5,5,5,5,3,4,4,5,5,5,5,4,5,5,114,88.0,satisfied +39064,20354,Female,disloyal Customer,23,Business travel,Business,323,1,3,1,3,5,1,5,5,1,5,4,3,4,5,70,59.0,neutral or dissatisfied +39065,35806,Male,Loyal Customer,62,Personal Travel,Business,1023,3,4,4,3,3,4,3,1,1,4,1,5,1,2,0,0.0,neutral or dissatisfied +39066,9172,Male,Loyal Customer,58,Business travel,Business,2525,4,4,4,4,3,5,4,3,3,3,3,3,3,4,5,4.0,satisfied +39067,7737,Female,Loyal Customer,18,Business travel,Business,489,4,4,4,4,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +39068,50400,Male,disloyal Customer,27,Business travel,Eco,262,2,5,3,3,1,3,1,1,4,1,2,5,5,1,0,0.0,neutral or dissatisfied +39069,74083,Female,disloyal Customer,25,Business travel,Business,592,5,0,4,1,5,4,5,5,3,2,5,5,4,5,0,0.0,satisfied +39070,128058,Female,Loyal Customer,56,Personal Travel,Eco Plus,735,2,5,2,3,2,4,1,2,2,2,2,1,2,2,6,13.0,neutral or dissatisfied +39071,61167,Female,Loyal Customer,29,Business travel,Business,1917,4,4,4,4,5,5,5,5,3,5,4,3,4,5,51,45.0,satisfied +39072,97649,Male,Loyal Customer,32,Personal Travel,Eco,1587,3,5,3,2,5,3,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +39073,90144,Female,Loyal Customer,33,Business travel,Business,3348,4,4,4,4,5,5,1,5,5,5,5,3,5,1,0,0.0,satisfied +39074,83775,Male,Loyal Customer,62,Personal Travel,Eco Plus,926,2,5,2,2,4,2,4,4,4,5,4,4,4,4,13,4.0,neutral or dissatisfied +39075,32985,Female,Loyal Customer,56,Personal Travel,Eco,102,1,1,1,4,5,3,4,3,3,1,3,3,3,2,0,2.0,neutral or dissatisfied +39076,41160,Female,Loyal Customer,9,Personal Travel,Eco,295,1,5,4,3,1,4,1,1,4,5,5,5,2,1,16,,neutral or dissatisfied +39077,129107,Male,Loyal Customer,35,Personal Travel,Eco,2218,2,3,2,2,1,2,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +39078,117855,Male,Loyal Customer,39,Business travel,Business,255,4,4,4,4,4,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +39079,120610,Female,disloyal Customer,38,Business travel,Eco,453,3,4,3,3,1,3,2,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +39080,59695,Male,Loyal Customer,28,Personal Travel,Eco,787,4,4,4,3,2,4,2,2,4,4,5,4,5,2,22,32.0,neutral or dissatisfied +39081,100773,Male,Loyal Customer,50,Business travel,Business,1411,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +39082,6532,Male,Loyal Customer,13,Personal Travel,Eco,599,3,0,3,1,3,3,3,3,3,5,4,5,5,3,8,14.0,neutral or dissatisfied +39083,20551,Male,Loyal Customer,52,Business travel,Business,565,1,2,2,2,1,1,1,4,3,3,3,1,1,1,137,139.0,neutral or dissatisfied +39084,97245,Male,Loyal Customer,45,Business travel,Business,2161,2,2,2,2,2,4,5,4,4,4,4,5,4,3,36,34.0,satisfied +39085,29732,Male,Loyal Customer,25,Business travel,Business,2552,2,2,2,2,4,4,4,4,2,3,3,3,2,4,0,0.0,satisfied +39086,53820,Female,Loyal Customer,59,Business travel,Eco,191,5,4,4,4,3,1,1,5,5,5,5,4,5,5,0,0.0,satisfied +39087,49176,Female,Loyal Customer,24,Business travel,Eco,190,4,2,2,2,5,5,4,5,5,4,1,1,5,5,0,0.0,satisfied +39088,73944,Male,disloyal Customer,44,Business travel,Eco,842,3,3,3,1,2,3,2,2,2,2,1,1,2,2,0,0.0,neutral or dissatisfied +39089,43881,Female,disloyal Customer,80,Business travel,Business,174,2,2,2,4,1,3,4,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +39090,72099,Male,Loyal Customer,70,Personal Travel,Eco,2486,2,2,2,3,4,2,4,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +39091,118909,Male,Loyal Customer,65,Personal Travel,Eco,587,4,4,4,4,1,4,1,1,4,3,5,5,4,1,0,3.0,neutral or dissatisfied +39092,118272,Male,Loyal Customer,41,Business travel,Business,602,1,0,0,4,1,4,3,4,4,0,4,4,4,4,27,8.0,neutral or dissatisfied +39093,24911,Female,Loyal Customer,66,Business travel,Eco,762,5,3,2,2,3,3,2,5,5,5,5,2,5,2,3,0.0,satisfied +39094,79854,Female,Loyal Customer,49,Business travel,Business,3378,2,2,2,2,2,5,5,4,4,4,4,4,4,4,36,42.0,satisfied +39095,65271,Male,Loyal Customer,17,Personal Travel,Eco Plus,224,1,4,1,3,5,1,5,5,4,3,5,4,5,5,12,5.0,neutral or dissatisfied +39096,42134,Female,Loyal Customer,50,Personal Travel,Eco Plus,898,4,4,5,1,5,5,5,2,2,5,2,3,2,5,0,0.0,neutral or dissatisfied +39097,52624,Female,disloyal Customer,27,Business travel,Eco,119,3,4,3,4,3,3,3,3,1,4,1,4,2,3,0,0.0,neutral or dissatisfied +39098,80951,Male,Loyal Customer,62,Personal Travel,Eco Plus,341,4,4,4,3,1,4,1,1,3,5,5,3,5,1,2,0.0,neutral or dissatisfied +39099,63492,Male,Loyal Customer,14,Personal Travel,Eco,651,1,0,1,4,4,1,4,4,5,4,4,4,5,4,39,37.0,neutral or dissatisfied +39100,79289,Female,Loyal Customer,41,Business travel,Business,2248,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +39101,7822,Female,Loyal Customer,43,Personal Travel,Eco,650,5,4,5,4,2,3,3,2,2,5,2,4,2,1,16,3.0,satisfied +39102,64931,Female,disloyal Customer,54,Business travel,Business,190,4,4,4,4,2,4,2,2,3,4,5,3,4,2,3,4.0,satisfied +39103,32045,Male,Loyal Customer,33,Business travel,Business,2027,0,4,0,4,1,1,1,1,3,1,5,1,1,1,0,0.0,satisfied +39104,121058,Female,Loyal Customer,59,Personal Travel,Eco,920,3,2,3,3,2,3,4,3,3,3,3,3,3,2,10,9.0,neutral or dissatisfied +39105,14203,Female,disloyal Customer,7,Business travel,Eco,714,2,3,3,3,4,3,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +39106,18715,Female,Loyal Customer,32,Personal Travel,Eco Plus,383,0,4,0,3,4,0,4,4,5,5,5,5,4,4,0,0.0,satisfied +39107,123329,Male,Loyal Customer,17,Business travel,Eco Plus,468,4,1,1,1,4,4,4,4,5,2,2,2,2,4,0,0.0,satisfied +39108,1257,Female,Loyal Customer,9,Personal Travel,Eco,164,3,2,3,4,1,3,1,1,2,1,4,4,4,1,3,18.0,neutral or dissatisfied +39109,32555,Female,Loyal Customer,27,Business travel,Eco,101,4,4,4,4,5,5,5,5,5,3,4,5,1,5,0,0.0,satisfied +39110,70022,Female,Loyal Customer,48,Business travel,Eco,583,1,5,5,5,2,3,3,1,1,1,1,3,1,2,80,56.0,neutral or dissatisfied +39111,87334,Female,disloyal Customer,23,Business travel,Eco,425,1,4,0,3,5,0,5,5,4,3,3,3,3,5,34,34.0,neutral or dissatisfied +39112,117617,Female,Loyal Customer,43,Business travel,Eco,872,4,3,3,3,3,5,3,4,4,4,4,3,4,3,0,0.0,satisfied +39113,17244,Female,disloyal Customer,30,Business travel,Eco,872,4,4,4,2,5,4,5,5,2,4,3,1,3,5,15,5.0,neutral or dissatisfied +39114,115928,Male,Loyal Customer,49,Business travel,Business,308,2,2,2,2,2,1,5,5,5,5,5,1,5,4,6,2.0,satisfied +39115,127775,Male,disloyal Customer,26,Business travel,Business,1037,2,2,2,3,3,2,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +39116,100437,Male,Loyal Customer,51,Business travel,Business,1912,3,3,3,3,4,5,4,4,4,4,4,3,4,5,3,0.0,satisfied +39117,102749,Female,Loyal Customer,58,Business travel,Business,3473,5,5,5,5,3,5,5,4,4,4,4,4,4,3,2,1.0,satisfied +39118,39338,Male,Loyal Customer,33,Business travel,Business,3942,3,3,3,3,4,4,4,4,4,5,5,3,5,4,0,0.0,satisfied +39119,79427,Male,Loyal Customer,49,Personal Travel,Eco,502,3,5,3,3,2,3,4,2,5,4,5,5,5,2,59,41.0,neutral or dissatisfied +39120,127621,Female,Loyal Customer,54,Business travel,Business,1773,1,1,1,1,5,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +39121,83679,Female,Loyal Customer,45,Business travel,Eco,577,1,4,4,4,5,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +39122,68095,Female,disloyal Customer,10,Business travel,Eco,868,5,5,5,3,4,5,4,4,4,4,4,5,5,4,0,0.0,satisfied +39123,98528,Male,Loyal Customer,9,Personal Travel,Eco,668,3,5,4,3,3,4,3,3,3,2,4,4,5,3,1,0.0,neutral or dissatisfied +39124,671,Female,disloyal Customer,21,Business travel,Eco,134,1,0,1,1,4,1,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +39125,126741,Male,Loyal Customer,35,Business travel,Business,2402,5,5,5,5,4,4,1,2,2,2,2,4,2,2,0,0.0,satisfied +39126,103942,Female,disloyal Customer,26,Business travel,Business,533,2,0,2,2,4,2,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +39127,117440,Female,Loyal Customer,36,Business travel,Business,1107,2,2,2,2,5,5,5,4,4,4,4,4,4,5,9,16.0,satisfied +39128,74383,Male,Loyal Customer,37,Business travel,Business,3784,3,3,3,3,1,3,4,3,3,3,3,1,3,4,2,0.0,neutral or dissatisfied +39129,94822,Female,disloyal Customer,26,Business travel,Eco,248,2,2,2,3,5,2,5,5,3,2,4,2,3,5,43,36.0,neutral or dissatisfied +39130,12334,Male,Loyal Customer,50,Business travel,Eco,262,5,1,1,1,5,5,5,5,2,1,3,1,5,5,0,0.0,satisfied +39131,80125,Female,Loyal Customer,45,Personal Travel,Business,2586,2,5,2,5,2,4,4,3,5,4,5,4,3,4,0,0.0,neutral or dissatisfied +39132,21427,Male,disloyal Customer,27,Business travel,Eco,164,3,3,3,1,2,3,2,2,2,3,1,1,1,2,0,0.0,neutral or dissatisfied +39133,99745,Male,Loyal Customer,65,Business travel,Business,2601,3,2,4,4,5,2,3,3,3,4,3,4,3,1,66,54.0,neutral or dissatisfied +39134,18380,Female,Loyal Customer,8,Personal Travel,Eco,409,4,3,4,1,4,4,4,4,3,2,5,5,2,4,49,27.0,satisfied +39135,43142,Female,Loyal Customer,15,Personal Travel,Eco Plus,259,2,1,2,2,4,2,4,4,3,5,2,1,2,4,1,0.0,neutral or dissatisfied +39136,4271,Male,disloyal Customer,25,Business travel,Business,502,3,4,3,1,5,3,5,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +39137,44015,Female,Loyal Customer,31,Personal Travel,Eco,397,3,5,3,2,4,3,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +39138,110170,Female,Loyal Customer,69,Personal Travel,Eco,882,1,2,1,4,3,4,4,5,5,1,5,4,5,2,8,11.0,neutral or dissatisfied +39139,28117,Male,Loyal Customer,31,Business travel,Business,1823,4,4,2,4,4,4,4,4,3,4,3,2,5,4,0,0.0,satisfied +39140,1578,Female,Loyal Customer,56,Business travel,Business,2772,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +39141,82361,Female,Loyal Customer,59,Personal Travel,Eco,453,3,5,5,4,5,4,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +39142,2813,Male,Loyal Customer,67,Business travel,Business,3906,2,2,2,2,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +39143,109150,Male,Loyal Customer,31,Business travel,Business,2235,5,5,5,5,4,4,4,4,4,4,5,4,4,4,11,13.0,satisfied +39144,80698,Female,disloyal Customer,26,Business travel,Eco,874,1,1,1,3,5,1,1,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +39145,108825,Male,Loyal Customer,58,Business travel,Business,3403,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +39146,42862,Male,disloyal Customer,46,Business travel,Business,867,5,5,5,3,3,5,3,3,3,5,4,3,5,3,0,9.0,satisfied +39147,8942,Male,Loyal Customer,60,Business travel,Business,3369,3,3,3,3,2,4,4,2,2,2,2,3,2,5,0,1.0,satisfied +39148,34906,Male,Loyal Customer,45,Business travel,Eco,395,4,3,4,3,4,4,4,4,4,2,5,1,2,4,0,0.0,satisfied +39149,38087,Female,Loyal Customer,39,Business travel,Business,3091,4,4,4,4,3,3,3,3,3,4,3,5,3,4,0,0.0,satisfied +39150,18217,Female,Loyal Customer,52,Business travel,Business,2833,2,2,2,2,5,2,1,5,5,5,5,3,5,2,0,1.0,satisfied +39151,114160,Female,Loyal Customer,51,Business travel,Business,2591,1,1,4,1,3,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +39152,7368,Male,Loyal Customer,41,Business travel,Eco,783,3,5,2,5,3,3,3,3,3,5,4,3,3,3,97,103.0,neutral or dissatisfied +39153,105882,Female,Loyal Customer,60,Business travel,Business,2801,0,0,0,4,3,3,3,3,2,5,5,3,4,3,185,183.0,satisfied +39154,113229,Female,Loyal Customer,47,Business travel,Business,226,3,3,3,3,2,4,5,5,5,5,5,4,5,3,13,4.0,satisfied +39155,37358,Female,disloyal Customer,22,Business travel,Eco,1118,5,5,5,1,3,5,3,3,2,2,5,3,4,3,17,26.0,satisfied +39156,85176,Female,Loyal Customer,36,Business travel,Business,3338,3,3,3,3,1,3,4,3,3,3,3,4,3,2,12,0.0,neutral or dissatisfied +39157,75962,Female,Loyal Customer,48,Business travel,Business,3806,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,3.0,satisfied +39158,83053,Male,Loyal Customer,28,Business travel,Business,1889,2,3,3,3,2,2,2,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +39159,42052,Female,Loyal Customer,10,Personal Travel,Eco,241,2,5,2,4,1,2,1,1,5,5,1,3,2,1,0,0.0,neutral or dissatisfied +39160,36993,Male,Loyal Customer,38,Business travel,Business,899,1,4,4,4,5,3,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +39161,15099,Male,Loyal Customer,57,Personal Travel,Eco,224,2,4,2,3,4,2,4,4,4,2,4,3,4,4,13,12.0,neutral or dissatisfied +39162,19260,Male,Loyal Customer,34,Business travel,Business,1982,4,4,4,4,3,1,4,4,4,4,4,1,4,4,0,0.0,satisfied +39163,118806,Male,Loyal Customer,68,Personal Travel,Eco,304,2,4,2,3,5,2,5,5,3,2,4,4,4,5,2,0.0,neutral or dissatisfied +39164,25637,Male,disloyal Customer,43,Business travel,Eco,126,3,0,3,3,3,3,3,3,1,4,1,1,1,3,8,0.0,neutral or dissatisfied +39165,113787,Female,Loyal Customer,44,Business travel,Business,1512,0,0,0,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +39166,112556,Female,disloyal Customer,39,Business travel,Eco Plus,557,2,2,2,4,1,2,1,1,2,2,3,1,4,1,40,58.0,neutral or dissatisfied +39167,88099,Female,Loyal Customer,43,Business travel,Business,1617,5,5,2,5,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +39168,13870,Male,Loyal Customer,29,Business travel,Business,667,3,3,5,3,5,3,3,4,1,4,5,3,4,3,133,140.0,satisfied +39169,102535,Female,Loyal Customer,50,Personal Travel,Eco,197,3,4,3,1,4,1,1,1,1,3,2,3,1,5,7,9.0,neutral or dissatisfied +39170,104503,Female,disloyal Customer,29,Business travel,Business,1609,4,4,4,4,4,4,4,4,3,5,5,4,5,4,0,5.0,satisfied +39171,60612,Female,Loyal Customer,70,Personal Travel,Eco,991,4,4,4,1,3,5,5,1,1,4,1,3,1,4,7,0.0,neutral or dissatisfied +39172,44263,Female,Loyal Customer,35,Personal Travel,Eco,222,1,5,0,4,2,0,5,2,3,2,4,5,1,2,0,0.0,neutral or dissatisfied +39173,21560,Male,disloyal Customer,21,Business travel,Eco,377,5,0,5,1,4,5,4,4,1,1,5,5,2,4,0,4.0,satisfied +39174,121462,Male,disloyal Customer,17,Personal Travel,Eco,331,4,4,4,4,4,4,4,4,2,2,3,2,3,4,0,0.0,satisfied +39175,34803,Female,Loyal Customer,35,Personal Travel,Eco,301,1,1,1,4,2,1,3,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +39176,18861,Male,Loyal Customer,40,Business travel,Eco,503,3,5,5,5,3,3,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +39177,70216,Male,Loyal Customer,46,Business travel,Business,403,2,2,2,2,4,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +39178,34483,Male,Loyal Customer,52,Personal Travel,Eco,266,3,5,3,2,4,3,4,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +39179,60086,Female,Loyal Customer,39,Business travel,Business,1012,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +39180,86272,Female,Loyal Customer,39,Personal Travel,Eco,356,0,1,0,3,2,0,2,2,3,4,3,2,3,2,0,0.0,satisfied +39181,119145,Female,disloyal Customer,22,Business travel,Eco,119,0,4,0,5,4,0,4,4,5,5,5,4,4,4,7,0.0,satisfied +39182,42832,Female,Loyal Customer,44,Business travel,Eco,328,5,1,4,1,4,3,4,5,5,5,5,1,5,3,0,23.0,satisfied +39183,126355,Female,Loyal Customer,11,Personal Travel,Eco,600,1,3,1,3,4,1,4,4,4,2,2,1,4,4,0,7.0,neutral or dissatisfied +39184,27579,Female,Loyal Customer,42,Personal Travel,Eco,672,3,3,4,3,5,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +39185,43114,Male,Loyal Customer,42,Personal Travel,Eco,236,3,1,3,3,5,3,5,5,4,1,2,3,2,5,78,69.0,neutral or dissatisfied +39186,33289,Female,Loyal Customer,39,Personal Travel,Eco Plus,101,5,4,5,1,2,5,2,2,5,3,5,3,5,2,0,4.0,satisfied +39187,73411,Female,Loyal Customer,44,Business travel,Eco,797,4,1,1,1,4,4,3,4,4,4,4,2,4,2,12,3.0,satisfied +39188,84099,Female,Loyal Customer,59,Business travel,Business,2684,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +39189,127392,Female,Loyal Customer,64,Business travel,Eco,868,2,5,5,5,1,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +39190,1664,Male,Loyal Customer,20,Personal Travel,Eco,551,3,1,3,2,3,1,1,3,1,2,2,1,2,1,164,283.0,neutral or dissatisfied +39191,33005,Female,Loyal Customer,17,Personal Travel,Eco,102,1,5,1,3,5,1,5,5,3,1,1,4,3,5,0,0.0,neutral or dissatisfied +39192,6970,Female,Loyal Customer,55,Business travel,Business,1501,2,2,4,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +39193,126478,Female,Loyal Customer,39,Business travel,Business,1972,4,4,5,4,2,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +39194,2020,Male,Loyal Customer,60,Business travel,Business,3144,3,5,5,5,3,3,2,3,3,3,3,4,3,3,14,11.0,neutral or dissatisfied +39195,94836,Male,Loyal Customer,59,Business travel,Business,2307,3,2,2,2,2,3,3,3,3,3,3,2,3,2,51,40.0,neutral or dissatisfied +39196,29179,Female,disloyal Customer,44,Business travel,Eco Plus,697,2,2,2,4,4,2,4,4,2,3,4,1,4,4,0,3.0,neutral or dissatisfied +39197,12086,Female,Loyal Customer,55,Business travel,Business,2205,5,5,5,5,5,5,5,3,3,4,3,5,3,5,18,0.0,satisfied +39198,50098,Female,Loyal Customer,50,Business travel,Eco,266,1,1,1,1,5,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +39199,83956,Female,Loyal Customer,46,Business travel,Eco,373,3,4,4,4,3,2,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +39200,115708,Female,Loyal Customer,47,Business travel,Eco,358,2,3,3,3,1,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +39201,103667,Male,Loyal Customer,35,Business travel,Business,405,1,1,1,1,4,3,3,1,1,1,1,4,1,1,33,26.0,neutral or dissatisfied +39202,110012,Female,Loyal Customer,36,Business travel,Business,1204,3,4,4,4,5,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +39203,101122,Female,Loyal Customer,40,Business travel,Business,1069,2,2,4,2,5,5,4,5,5,5,5,5,5,3,4,0.0,satisfied +39204,103587,Male,Loyal Customer,60,Business travel,Business,2815,4,4,4,4,5,4,4,5,5,5,5,3,5,5,37,25.0,satisfied +39205,78412,Female,disloyal Customer,39,Business travel,Business,453,5,5,5,2,2,5,2,2,5,3,5,3,4,2,0,5.0,satisfied +39206,73373,Male,Loyal Customer,39,Business travel,Business,3473,4,4,1,4,2,4,4,4,4,4,4,3,4,3,0,7.0,satisfied +39207,115560,Male,Loyal Customer,44,Business travel,Business,362,2,2,2,2,3,4,4,4,4,4,4,4,4,3,6,0.0,satisfied +39208,85483,Female,Loyal Customer,53,Personal Travel,Eco,227,3,4,3,1,2,4,5,1,1,3,1,3,1,3,55,48.0,neutral or dissatisfied +39209,16779,Female,Loyal Customer,9,Personal Travel,Eco,569,4,3,4,1,1,4,1,1,3,1,4,5,2,1,0,0.0,neutral or dissatisfied +39210,60620,Female,disloyal Customer,39,Business travel,Business,1201,3,3,3,2,2,3,2,2,3,1,3,1,2,2,0,19.0,neutral or dissatisfied +39211,124786,Female,disloyal Customer,37,Business travel,Eco,280,1,1,1,3,1,1,1,1,2,5,3,2,2,1,0,0.0,neutral or dissatisfied +39212,118728,Female,Loyal Customer,29,Personal Travel,Eco,621,3,5,3,1,1,3,1,1,3,4,5,5,4,1,10,13.0,neutral or dissatisfied +39213,33418,Female,Loyal Customer,46,Business travel,Business,2409,3,3,3,3,2,5,1,3,3,3,3,4,3,4,0,0.0,satisfied +39214,7912,Female,Loyal Customer,37,Business travel,Business,2943,1,1,1,1,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +39215,87109,Male,Loyal Customer,27,Personal Travel,Eco,645,3,5,3,1,4,3,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +39216,49023,Male,Loyal Customer,46,Business travel,Business,3494,2,2,2,2,4,5,2,4,4,4,4,4,4,2,0,0.0,satisfied +39217,97105,Male,Loyal Customer,51,Business travel,Business,1390,2,2,2,2,3,5,5,4,4,4,4,5,4,4,11,14.0,satisfied +39218,42436,Male,Loyal Customer,20,Personal Travel,Eco,1119,4,4,4,3,1,4,1,1,5,4,5,4,5,1,0,2.0,satisfied +39219,90582,Female,Loyal Customer,26,Business travel,Business,594,4,4,3,4,3,3,3,3,4,4,4,5,5,3,0,0.0,satisfied +39220,46054,Female,Loyal Customer,63,Personal Travel,Eco,996,1,5,1,4,3,5,4,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +39221,24379,Male,Loyal Customer,38,Business travel,Business,669,1,1,1,1,1,5,4,5,5,5,5,5,5,4,0,6.0,satisfied +39222,39206,Female,Loyal Customer,56,Business travel,Business,3504,4,4,4,4,2,5,5,4,4,4,5,5,4,5,0,3.0,satisfied +39223,39938,Male,disloyal Customer,23,Business travel,Eco,1195,2,2,2,5,5,2,5,5,2,5,3,5,3,5,24,3.0,neutral or dissatisfied +39224,89281,Male,Loyal Customer,48,Business travel,Business,453,2,2,2,2,3,5,4,4,4,4,4,3,4,4,6,1.0,satisfied +39225,70166,Female,Loyal Customer,45,Business travel,Business,3813,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +39226,71833,Male,Loyal Customer,45,Business travel,Eco,1744,3,4,3,4,4,3,4,4,1,5,4,2,3,4,43,52.0,neutral or dissatisfied +39227,108873,Male,Loyal Customer,44,Business travel,Business,1587,3,3,3,3,3,3,4,4,4,4,4,5,4,5,87,79.0,satisfied +39228,12529,Female,Loyal Customer,48,Business travel,Business,788,5,5,5,5,3,4,2,3,3,4,3,2,3,4,12,21.0,satisfied +39229,32430,Female,disloyal Customer,26,Business travel,Eco,216,1,4,1,4,4,1,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +39230,110800,Female,Loyal Customer,19,Personal Travel,Eco,1166,2,4,2,2,3,2,3,3,4,5,5,3,5,3,62,69.0,neutral or dissatisfied +39231,52797,Male,Loyal Customer,56,Personal Travel,Eco,1874,2,2,2,3,5,2,5,5,1,4,4,3,3,5,0,0.0,neutral or dissatisfied +39232,7773,Female,Loyal Customer,44,Business travel,Business,3958,3,3,3,3,4,5,3,4,4,4,4,4,4,4,0,0.0,satisfied +39233,28309,Male,Loyal Customer,28,Business travel,Business,3380,3,3,3,3,4,4,4,4,2,4,3,4,5,4,0,5.0,satisfied +39234,75257,Female,Loyal Customer,68,Personal Travel,Eco,1726,3,4,3,4,3,5,4,3,3,3,2,3,3,5,51,21.0,neutral or dissatisfied +39235,38734,Female,Loyal Customer,25,Business travel,Business,387,3,5,3,3,5,5,5,5,5,4,5,1,4,5,0,0.0,satisfied +39236,58550,Male,Loyal Customer,43,Business travel,Eco,1114,4,3,3,3,4,4,4,4,2,4,2,2,3,4,8,12.0,satisfied +39237,1893,Female,Loyal Customer,66,Personal Travel,Business,285,2,2,2,3,4,3,4,1,1,2,1,4,1,2,10,7.0,neutral or dissatisfied +39238,88188,Female,disloyal Customer,27,Business travel,Business,270,3,3,3,3,4,3,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +39239,37004,Female,Loyal Customer,45,Personal Travel,Eco,759,4,5,4,2,3,4,4,1,1,4,1,4,1,5,16,0.0,neutral or dissatisfied +39240,85081,Female,Loyal Customer,52,Business travel,Business,731,5,5,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +39241,3367,Male,Loyal Customer,39,Business travel,Business,1763,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,1.0,satisfied +39242,43802,Male,Loyal Customer,40,Personal Travel,Eco Plus,913,2,4,2,3,3,2,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +39243,4523,Male,Loyal Customer,23,Business travel,Business,2793,2,2,2,2,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +39244,18135,Female,Loyal Customer,54,Business travel,Business,632,3,3,3,3,2,3,3,3,2,4,5,3,4,3,125,138.0,satisfied +39245,109332,Female,Loyal Customer,55,Personal Travel,Eco,1200,1,5,1,2,4,3,4,2,2,1,5,1,2,3,15,0.0,neutral or dissatisfied +39246,5368,Female,Loyal Customer,26,Business travel,Eco,812,3,3,3,3,3,3,1,3,4,3,4,4,3,3,54,37.0,neutral or dissatisfied +39247,105648,Male,Loyal Customer,45,Business travel,Business,2487,5,5,3,5,4,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +39248,100493,Male,Loyal Customer,44,Business travel,Eco,580,2,3,3,3,2,2,2,2,4,3,2,3,3,2,14,5.0,neutral or dissatisfied +39249,70614,Female,Loyal Customer,41,Business travel,Business,1926,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +39250,113666,Male,Loyal Customer,70,Personal Travel,Eco,258,2,2,2,3,4,2,5,4,1,3,4,1,4,4,20,18.0,neutral or dissatisfied +39251,43483,Female,disloyal Customer,37,Business travel,Eco,455,3,4,3,3,4,3,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +39252,114485,Male,Loyal Customer,31,Business travel,Business,2177,3,3,3,3,5,5,5,5,3,4,5,4,4,5,1,0.0,satisfied +39253,82063,Female,Loyal Customer,35,Personal Travel,Business,1298,1,5,1,1,3,4,4,3,3,1,2,5,3,3,0,0.0,neutral or dissatisfied +39254,81244,Male,Loyal Customer,51,Business travel,Business,930,3,1,1,1,3,3,3,4,2,2,2,3,4,3,130,141.0,neutral or dissatisfied +39255,20728,Male,Loyal Customer,8,Personal Travel,Eco,765,3,5,3,1,3,3,5,3,4,2,5,5,5,3,41,25.0,neutral or dissatisfied +39256,129566,Male,Loyal Customer,24,Personal Travel,Eco,2583,3,5,3,3,4,3,4,4,1,5,5,3,5,4,0,0.0,neutral or dissatisfied +39257,95658,Male,Loyal Customer,59,Personal Travel,Eco,845,2,4,2,3,1,2,1,1,4,5,5,5,5,1,15,9.0,neutral or dissatisfied +39258,8182,Male,Loyal Customer,19,Business travel,Eco,335,4,4,4,4,4,4,1,4,4,4,3,1,3,4,0,6.0,neutral or dissatisfied +39259,64400,Male,Loyal Customer,58,Business travel,Business,1746,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +39260,3564,Female,Loyal Customer,47,Business travel,Business,3939,2,2,2,2,3,1,1,2,2,3,2,3,2,2,35,34.0,neutral or dissatisfied +39261,84990,Male,Loyal Customer,40,Business travel,Business,1590,5,5,5,5,3,3,4,4,4,4,4,5,4,5,25,5.0,satisfied +39262,77344,Male,Loyal Customer,37,Business travel,Business,2965,3,3,3,3,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +39263,6621,Male,Loyal Customer,32,Business travel,Business,3803,3,2,2,2,3,2,3,3,1,5,2,4,2,3,25,20.0,neutral or dissatisfied +39264,42088,Male,Loyal Customer,36,Business travel,Business,898,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +39265,1161,Female,Loyal Customer,35,Personal Travel,Eco,158,2,4,0,2,4,0,4,4,4,2,4,5,4,4,0,13.0,neutral or dissatisfied +39266,15928,Male,Loyal Customer,65,Business travel,Business,3743,1,3,3,3,3,3,3,1,1,1,1,1,1,3,19,7.0,neutral or dissatisfied +39267,128456,Male,Loyal Customer,62,Personal Travel,Eco,621,3,4,3,3,5,3,5,5,4,4,5,4,4,5,1,7.0,neutral or dissatisfied +39268,8145,Female,Loyal Customer,57,Business travel,Business,2607,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +39269,27,Male,Loyal Customer,50,Business travel,Business,2168,3,3,3,3,2,4,5,5,5,5,5,4,5,4,6,24.0,satisfied +39270,115267,Female,Loyal Customer,32,Business travel,Business,3999,4,4,4,4,5,5,5,5,5,2,4,3,4,5,2,0.0,satisfied +39271,24029,Female,Loyal Customer,20,Business travel,Business,427,1,5,3,5,1,1,1,1,2,1,4,3,4,1,0,1.0,neutral or dissatisfied +39272,33080,Female,Loyal Customer,38,Personal Travel,Eco,101,2,4,2,3,3,2,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +39273,129553,Female,Loyal Customer,50,Personal Travel,Eco,2342,3,5,3,2,3,4,4,5,5,3,1,3,5,5,0,0.0,neutral or dissatisfied +39274,20166,Female,disloyal Customer,32,Business travel,Eco,403,4,3,4,3,4,4,5,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +39275,10095,Male,disloyal Customer,23,Business travel,Business,961,5,0,4,2,5,4,5,5,4,5,4,5,5,5,6,0.0,satisfied +39276,128530,Female,Loyal Customer,9,Personal Travel,Eco,370,1,2,1,4,3,1,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +39277,78152,Male,Loyal Customer,55,Business travel,Business,1973,2,2,2,2,5,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +39278,19295,Female,disloyal Customer,37,Business travel,Eco,299,3,1,3,3,3,2,3,1,1,3,3,3,3,3,265,291.0,neutral or dissatisfied +39279,13384,Female,Loyal Customer,42,Business travel,Business,3262,4,4,4,4,5,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +39280,66820,Female,Loyal Customer,35,Business travel,Business,2479,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,1.0,satisfied +39281,13629,Male,Loyal Customer,55,Business travel,Eco,1014,4,2,2,2,5,4,5,5,1,3,2,2,3,5,0,0.0,satisfied +39282,22391,Female,Loyal Customer,30,Business travel,Eco,238,4,4,4,4,4,4,4,4,4,4,1,4,3,4,0,4.0,satisfied +39283,107466,Female,disloyal Customer,38,Business travel,Eco,1121,2,2,2,4,5,2,4,5,1,5,4,3,4,5,25,35.0,neutral or dissatisfied +39284,98001,Female,disloyal Customer,16,Business travel,Eco,612,3,3,3,5,1,3,1,1,3,2,4,5,2,1,13,5.0,neutral or dissatisfied +39285,73163,Male,Loyal Customer,42,Business travel,Eco,1145,4,4,1,1,3,4,3,3,3,5,5,4,4,3,0,0.0,satisfied +39286,98160,Female,Loyal Customer,60,Personal Travel,Eco,745,5,3,5,2,3,5,5,4,4,5,5,4,4,3,2,6.0,satisfied +39287,125886,Male,Loyal Customer,43,Personal Travel,Eco,1013,3,3,3,3,4,3,3,4,2,5,1,4,4,4,0,0.0,neutral or dissatisfied +39288,21957,Female,Loyal Customer,25,Business travel,Eco,448,3,4,4,4,3,3,4,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +39289,55687,Male,Loyal Customer,57,Business travel,Business,2720,4,4,4,4,2,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +39290,47945,Male,Loyal Customer,26,Personal Travel,Eco,834,4,3,4,3,5,4,5,5,2,3,3,3,1,5,0,0.0,neutral or dissatisfied +39291,103322,Female,disloyal Customer,39,Business travel,Eco,739,3,2,2,2,2,3,3,2,1,1,2,3,1,3,151,,neutral or dissatisfied +39292,129753,Female,Loyal Customer,36,Business travel,Business,447,5,5,5,5,1,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +39293,52202,Female,Loyal Customer,50,Business travel,Eco,751,4,1,1,1,5,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +39294,30442,Male,disloyal Customer,19,Business travel,Business,991,4,2,4,4,5,4,3,5,4,3,5,4,4,5,91,105.0,satisfied +39295,127328,Female,Loyal Customer,46,Business travel,Business,3886,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +39296,81293,Female,Loyal Customer,12,Personal Travel,Eco,1020,4,4,4,3,3,4,3,3,3,3,2,4,1,3,0,0.0,satisfied +39297,58776,Male,Loyal Customer,45,Business travel,Business,3556,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +39298,12246,Male,Loyal Customer,38,Business travel,Eco,253,5,3,3,3,5,5,5,5,4,2,3,5,1,5,73,70.0,satisfied +39299,59872,Male,Loyal Customer,39,Business travel,Business,3171,2,3,3,3,2,3,3,2,2,2,2,3,2,1,25,13.0,neutral or dissatisfied +39300,3162,Male,Loyal Customer,56,Business travel,Business,2589,3,3,3,3,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +39301,20448,Female,Loyal Customer,37,Business travel,Eco,177,5,4,4,4,5,5,5,5,4,4,5,1,3,5,55,79.0,satisfied +39302,12534,Male,Loyal Customer,44,Business travel,Business,871,3,3,3,3,5,5,1,2,2,2,2,5,2,5,0,0.0,satisfied +39303,15640,Male,Loyal Customer,17,Business travel,Eco Plus,292,4,3,3,3,4,4,3,4,4,2,3,2,1,4,0,0.0,satisfied +39304,48368,Female,disloyal Customer,36,Business travel,Eco,274,3,5,3,5,2,3,2,2,1,1,4,1,2,2,0,0.0,neutral or dissatisfied +39305,104682,Male,Loyal Customer,59,Business travel,Eco Plus,641,1,1,1,1,1,1,1,1,4,1,3,2,3,1,0,0.0,neutral or dissatisfied +39306,61798,Female,Loyal Customer,28,Personal Travel,Eco,1379,3,5,2,5,5,2,2,5,3,5,4,4,5,5,24,19.0,neutral or dissatisfied +39307,112634,Female,disloyal Customer,64,Business travel,Eco Plus,602,3,3,3,3,2,3,3,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +39308,73037,Male,Loyal Customer,8,Personal Travel,Eco,1035,2,1,2,3,5,2,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +39309,125250,Male,Loyal Customer,17,Business travel,Business,427,3,1,1,1,3,3,3,3,4,3,3,1,3,3,41,62.0,neutral or dissatisfied +39310,74700,Female,Loyal Customer,54,Personal Travel,Eco,1126,1,4,1,3,3,4,4,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +39311,13178,Male,Loyal Customer,59,Business travel,Eco,419,5,4,4,4,5,5,5,5,1,3,2,5,5,5,137,134.0,satisfied +39312,6763,Female,disloyal Customer,30,Business travel,Business,235,4,4,4,4,1,4,1,1,4,5,5,3,4,1,92,80.0,satisfied +39313,97220,Female,Loyal Customer,41,Personal Travel,Eco Plus,1164,4,5,5,5,2,4,4,1,1,5,1,5,1,4,0,0.0,neutral or dissatisfied +39314,6953,Male,Loyal Customer,9,Personal Travel,Eco,501,3,5,3,4,4,3,4,4,4,5,5,3,5,4,83,76.0,neutral or dissatisfied +39315,45628,Male,Loyal Customer,31,Business travel,Business,2808,3,3,2,3,5,5,5,5,5,1,2,1,1,5,0,0.0,satisfied +39316,66960,Female,Loyal Customer,40,Business travel,Business,2139,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +39317,75838,Female,Loyal Customer,59,Business travel,Business,1440,4,4,4,4,5,4,4,4,4,4,4,5,4,3,7,0.0,satisfied +39318,10941,Female,Loyal Customer,57,Business travel,Business,3612,1,1,1,1,3,3,2,1,1,1,1,1,1,2,5,3.0,neutral or dissatisfied +39319,68171,Female,Loyal Customer,67,Business travel,Eco,603,4,5,4,5,2,3,2,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +39320,54540,Male,Loyal Customer,28,Personal Travel,Eco,925,4,5,4,4,5,4,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +39321,14571,Female,Loyal Customer,48,Business travel,Business,2634,5,2,5,5,1,1,2,4,4,4,4,5,4,3,17,0.0,satisfied +39322,68718,Male,Loyal Customer,58,Personal Travel,Eco,175,1,4,1,4,5,1,5,5,5,4,4,4,5,5,0,6.0,neutral or dissatisfied +39323,29382,Male,Loyal Customer,57,Business travel,Business,2466,3,3,3,3,4,4,4,2,3,3,4,4,1,4,0,10.0,satisfied +39324,105264,Male,Loyal Customer,10,Personal Travel,Eco,2106,4,2,4,4,4,4,4,4,3,3,3,4,1,4,0,13.0,satisfied +39325,110096,Male,Loyal Customer,40,Business travel,Business,2334,1,1,1,1,5,5,5,5,5,5,5,3,5,3,12,18.0,satisfied +39326,22764,Male,disloyal Customer,26,Business travel,Eco,147,1,5,1,3,4,1,4,4,4,5,1,5,3,4,30,14.0,neutral or dissatisfied +39327,20702,Male,Loyal Customer,49,Personal Travel,Eco,584,5,5,5,1,5,3,3,5,3,4,5,3,4,3,132,118.0,satisfied +39328,18724,Male,Loyal Customer,59,Personal Travel,Eco Plus,127,3,5,3,3,1,3,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +39329,70002,Female,Loyal Customer,17,Personal Travel,Eco,236,1,5,1,4,3,1,3,3,4,5,2,3,3,3,25,22.0,neutral or dissatisfied +39330,89666,Male,Loyal Customer,48,Business travel,Eco,950,3,4,4,4,4,3,4,4,4,1,3,4,2,4,0,0.0,neutral or dissatisfied +39331,56257,Male,Loyal Customer,50,Business travel,Business,3883,2,3,3,3,5,2,3,2,2,2,2,3,2,4,0,39.0,neutral or dissatisfied +39332,56028,Female,Loyal Customer,54,Business travel,Business,2586,2,2,2,2,4,4,4,5,5,3,5,4,4,4,0,0.0,satisfied +39333,33665,Female,Loyal Customer,29,Business travel,Eco Plus,413,4,4,4,4,4,4,4,4,4,2,2,2,5,4,0,0.0,satisfied +39334,109985,Male,Loyal Customer,56,Business travel,Business,2772,2,2,2,2,3,4,4,3,3,4,3,4,3,3,8,0.0,satisfied +39335,79262,Male,Loyal Customer,18,Personal Travel,Eco,1598,1,5,1,1,1,1,1,1,5,4,5,4,4,1,41,49.0,neutral or dissatisfied +39336,119748,Female,Loyal Customer,28,Personal Travel,Eco,1303,2,3,2,3,2,2,2,2,3,2,2,3,3,2,0,0.0,neutral or dissatisfied +39337,127723,Female,disloyal Customer,25,Business travel,Business,601,4,0,4,4,2,4,3,2,5,3,4,5,4,2,0,0.0,satisfied +39338,95634,Male,Loyal Customer,45,Personal Travel,Eco,670,2,5,2,2,3,2,3,3,4,2,4,4,5,3,11,1.0,neutral or dissatisfied +39339,103806,Female,Loyal Customer,43,Business travel,Business,2435,5,5,5,5,3,5,4,5,5,5,5,4,5,5,16,7.0,satisfied +39340,40615,Female,Loyal Customer,27,Personal Travel,Eco,411,4,4,4,4,2,4,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +39341,8273,Male,Loyal Customer,41,Personal Travel,Eco,335,2,5,2,5,5,2,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +39342,91005,Male,Loyal Customer,30,Personal Travel,Eco,404,4,3,1,3,2,1,2,2,3,5,2,2,5,2,0,0.0,satisfied +39343,47379,Female,disloyal Customer,11,Business travel,Eco,599,5,0,5,1,2,0,2,2,2,2,5,2,4,2,0,0.0,satisfied +39344,79977,Male,Loyal Customer,47,Business travel,Eco,676,5,1,1,1,5,5,5,5,2,5,4,1,1,5,6,0.0,satisfied +39345,119523,Male,Loyal Customer,37,Business travel,Eco,499,5,4,4,4,5,5,5,5,2,4,1,4,4,5,0,2.0,satisfied +39346,37334,Female,Loyal Customer,26,Business travel,Eco,1035,4,5,5,5,4,4,4,2,1,1,5,4,5,4,145,193.0,satisfied +39347,44916,Male,disloyal Customer,23,Business travel,Eco,466,2,1,2,3,5,2,5,5,3,2,3,4,3,5,34,30.0,neutral or dissatisfied +39348,95142,Male,Loyal Customer,15,Personal Travel,Eco,248,3,5,3,2,5,3,5,5,4,3,5,3,5,5,94,93.0,neutral or dissatisfied +39349,108930,Female,Loyal Customer,60,Personal Travel,Eco,1075,0,4,0,1,3,4,4,2,2,0,2,5,2,3,0,1.0,satisfied +39350,69776,Female,Loyal Customer,52,Business travel,Business,2454,5,5,5,5,5,5,5,4,3,3,5,5,4,5,0,3.0,satisfied +39351,123348,Female,Loyal Customer,24,Business travel,Business,644,4,4,5,4,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +39352,18118,Male,Loyal Customer,28,Business travel,Business,528,5,5,4,5,5,5,5,5,5,3,4,3,5,5,22,3.0,satisfied +39353,29452,Female,Loyal Customer,30,Personal Travel,Eco,421,3,4,1,2,4,1,4,4,5,5,5,5,3,4,0,0.0,neutral or dissatisfied +39354,28578,Female,Loyal Customer,10,Business travel,Business,2631,5,5,5,5,5,5,5,5,1,3,3,2,1,5,7,0.0,satisfied +39355,112517,Female,Loyal Customer,56,Personal Travel,Eco,853,2,5,2,3,4,5,4,2,2,2,2,5,2,5,2,0.0,neutral or dissatisfied +39356,81551,Male,disloyal Customer,39,Business travel,Business,936,3,3,3,3,3,3,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +39357,111049,Male,Loyal Customer,61,Business travel,Business,319,3,5,5,5,1,3,3,3,3,3,3,2,3,1,88,83.0,neutral or dissatisfied +39358,100239,Male,Loyal Customer,49,Personal Travel,Business,1011,2,1,2,4,4,3,4,4,4,2,2,1,4,1,9,4.0,neutral or dissatisfied +39359,111237,Male,Loyal Customer,39,Business travel,Business,1546,3,3,3,3,2,5,4,5,5,5,5,4,5,5,15,5.0,satisfied +39360,24436,Female,disloyal Customer,25,Business travel,Eco Plus,634,1,3,1,4,5,1,5,5,2,1,2,5,3,5,0,0.0,neutral or dissatisfied +39361,32429,Male,disloyal Customer,40,Business travel,Eco,163,4,0,4,1,1,4,1,1,3,1,2,5,2,1,0,0.0,satisfied +39362,92790,Male,disloyal Customer,23,Business travel,Eco,723,1,1,1,2,1,1,1,1,2,1,3,2,2,1,0,35.0,neutral or dissatisfied +39363,3274,Female,Loyal Customer,61,Business travel,Eco,479,5,5,1,1,1,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +39364,78701,Male,Loyal Customer,50,Business travel,Business,1958,3,3,3,3,2,4,5,4,4,4,4,3,4,5,19,16.0,satisfied +39365,125577,Female,disloyal Customer,23,Business travel,Eco,226,4,0,4,2,3,4,3,3,4,3,5,4,4,3,2,0.0,satisfied +39366,10344,Female,disloyal Customer,39,Business travel,Business,247,2,2,2,1,2,2,2,2,3,5,4,4,5,2,94,95.0,neutral or dissatisfied +39367,50536,Male,Loyal Customer,55,Personal Travel,Eco,109,3,3,3,1,4,3,5,4,2,3,1,2,5,4,2,3.0,neutral or dissatisfied +39368,114234,Female,disloyal Customer,20,Business travel,Business,909,4,0,4,4,5,4,5,5,5,3,4,4,4,5,31,1.0,satisfied +39369,7277,Male,Loyal Customer,58,Personal Travel,Eco,139,2,5,2,4,5,2,5,5,4,2,5,5,4,5,21,13.0,neutral or dissatisfied +39370,84925,Male,Loyal Customer,67,Personal Travel,Eco,481,2,5,4,5,3,4,3,3,3,3,1,1,4,3,0,0.0,neutral or dissatisfied +39371,8385,Male,Loyal Customer,44,Personal Travel,Eco,701,3,4,3,3,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +39372,43766,Male,Loyal Customer,47,Business travel,Business,481,4,4,4,4,5,4,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +39373,30601,Male,Loyal Customer,49,Business travel,Business,3491,4,4,4,4,1,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +39374,22128,Male,disloyal Customer,23,Business travel,Eco,566,2,2,2,2,5,2,5,5,3,2,2,4,1,5,10,15.0,neutral or dissatisfied +39375,99529,Female,Loyal Customer,47,Business travel,Business,802,3,3,3,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +39376,118664,Male,Loyal Customer,27,Business travel,Business,2748,2,3,4,3,2,2,2,2,2,4,2,2,1,2,17,12.0,neutral or dissatisfied +39377,16832,Female,Loyal Customer,11,Personal Travel,Eco,645,2,5,2,3,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +39378,51018,Male,Loyal Customer,39,Personal Travel,Eco,266,1,2,1,4,4,1,4,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +39379,65600,Male,Loyal Customer,63,Business travel,Eco,175,4,3,3,3,4,4,4,4,4,4,2,3,3,4,46,37.0,neutral or dissatisfied +39380,9045,Female,Loyal Customer,66,Business travel,Eco,212,4,1,1,1,4,3,3,4,4,4,4,1,4,4,70,62.0,neutral or dissatisfied +39381,124655,Female,Loyal Customer,42,Business travel,Business,399,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,7.0,satisfied +39382,25388,Male,disloyal Customer,41,Business travel,Eco Plus,591,1,1,1,3,1,5,5,3,2,3,3,5,1,5,306,295.0,neutral or dissatisfied +39383,115013,Female,Loyal Customer,59,Business travel,Business,333,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +39384,124032,Male,Loyal Customer,49,Personal Travel,Eco,184,2,5,2,3,2,2,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +39385,12027,Female,Loyal Customer,44,Business travel,Eco,351,5,1,1,1,3,3,4,5,5,5,5,1,5,5,0,0.0,satisfied +39386,74016,Female,Loyal Customer,34,Business travel,Business,1471,5,5,5,5,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +39387,109476,Female,Loyal Customer,41,Business travel,Business,834,2,2,4,2,5,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +39388,13308,Female,Loyal Customer,39,Business travel,Eco,448,4,5,5,5,4,4,4,4,4,5,1,2,2,4,0,0.0,satisfied +39389,53722,Female,Loyal Customer,59,Personal Travel,Eco,1190,3,4,3,1,5,5,5,2,2,3,2,4,2,5,6,0.0,neutral or dissatisfied +39390,119300,Female,Loyal Customer,59,Business travel,Eco,214,3,1,1,1,5,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +39391,61380,Female,disloyal Customer,26,Business travel,Business,679,4,4,4,4,1,4,1,1,3,4,4,5,5,1,0,0.0,satisfied +39392,22800,Female,Loyal Customer,32,Business travel,Business,2000,2,2,2,2,4,4,4,4,5,1,3,1,3,4,0,17.0,satisfied +39393,21317,Female,disloyal Customer,30,Business travel,Eco Plus,620,0,0,0,3,4,0,3,4,2,5,1,4,3,4,14,12.0,satisfied +39394,19234,Female,Loyal Customer,49,Business travel,Eco,782,4,1,1,1,2,4,4,4,4,4,4,1,4,2,31,30.0,satisfied +39395,53609,Male,Loyal Customer,24,Business travel,Business,1874,2,2,2,2,4,4,4,4,5,4,3,1,3,4,6,19.0,satisfied +39396,109358,Male,Loyal Customer,60,Business travel,Business,1789,5,5,5,5,2,5,5,2,2,2,2,5,2,4,8,0.0,satisfied +39397,10126,Female,Loyal Customer,47,Business travel,Business,1911,3,3,4,3,4,5,5,3,3,3,3,5,3,4,1,4.0,satisfied +39398,69070,Female,disloyal Customer,25,Business travel,Business,1389,1,0,1,5,2,1,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +39399,57659,Male,Loyal Customer,59,Personal Travel,Eco,200,2,1,2,4,2,2,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +39400,37899,Male,disloyal Customer,41,Business travel,Eco,537,4,0,4,1,4,4,5,5,5,1,4,5,2,5,151,136.0,neutral or dissatisfied +39401,90201,Male,Loyal Customer,19,Personal Travel,Eco,1084,2,1,2,4,1,2,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +39402,20647,Male,disloyal Customer,34,Business travel,Business,522,2,2,2,2,2,3,3,1,4,3,3,3,3,3,141,125.0,neutral or dissatisfied +39403,56822,Male,disloyal Customer,15,Business travel,Eco,1170,3,4,4,4,2,3,2,2,4,4,3,1,3,2,65,48.0,neutral or dissatisfied +39404,16715,Female,Loyal Customer,51,Business travel,Eco Plus,284,4,3,2,2,4,1,3,4,4,4,4,1,4,3,26,19.0,satisfied +39405,125322,Female,Loyal Customer,28,Business travel,Business,3016,1,1,1,1,4,4,4,4,3,3,5,3,5,4,36,41.0,satisfied +39406,22712,Male,Loyal Customer,52,Business travel,Eco Plus,589,2,4,4,4,2,2,2,3,3,4,3,2,1,2,265,250.0,neutral or dissatisfied +39407,64895,Female,disloyal Customer,54,Business travel,Business,190,3,3,3,1,3,3,4,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +39408,110199,Female,Loyal Customer,46,Business travel,Eco Plus,979,3,5,5,5,2,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +39409,53976,Female,Loyal Customer,37,Personal Travel,Eco,1325,1,5,1,2,2,1,2,2,3,3,2,1,5,2,6,0.0,neutral or dissatisfied +39410,14324,Female,Loyal Customer,59,Personal Travel,Eco,429,0,1,0,4,4,3,3,3,3,0,3,1,3,1,0,0.0,satisfied +39411,68017,Male,Loyal Customer,67,Business travel,Eco,280,5,2,1,2,5,5,5,5,1,3,3,5,2,5,0,0.0,satisfied +39412,120068,Female,Loyal Customer,34,Business travel,Business,1871,4,4,4,4,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +39413,31482,Female,disloyal Customer,37,Business travel,Eco,967,4,4,4,1,1,4,1,1,4,1,2,4,4,1,43,49.0,neutral or dissatisfied +39414,45921,Male,disloyal Customer,21,Business travel,Eco,809,2,1,1,4,1,1,1,1,1,5,4,3,3,1,15,15.0,neutral or dissatisfied +39415,117037,Female,Loyal Customer,42,Business travel,Business,369,3,1,1,1,1,3,3,3,3,2,3,2,3,4,1,0.0,neutral or dissatisfied +39416,82764,Male,Loyal Customer,61,Personal Travel,Eco,409,2,1,2,2,3,2,3,3,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +39417,59854,Female,Loyal Customer,52,Business travel,Business,2382,3,3,3,3,3,4,5,5,5,5,5,4,5,5,35,38.0,satisfied +39418,117404,Male,disloyal Customer,30,Business travel,Business,1136,0,1,1,1,5,1,5,5,3,4,4,5,4,5,0,0.0,satisfied +39419,268,Male,disloyal Customer,20,Business travel,Eco,802,3,3,3,4,3,3,3,3,2,1,3,2,4,3,35,18.0,neutral or dissatisfied +39420,70428,Female,Loyal Customer,55,Business travel,Business,3675,5,1,5,5,5,4,5,5,5,5,4,4,5,4,0,5.0,satisfied +39421,96373,Female,disloyal Customer,20,Business travel,Business,1246,5,0,5,3,5,5,5,5,3,3,5,3,5,5,9,24.0,satisfied +39422,98439,Male,disloyal Customer,25,Business travel,Business,814,4,0,4,3,4,4,4,4,3,2,5,3,5,4,108,116.0,satisfied +39423,41999,Male,Loyal Customer,34,Business travel,Eco,116,4,2,4,2,4,4,4,4,4,2,1,5,1,4,0,0.0,satisfied +39424,29680,Male,Loyal Customer,30,Business travel,Eco Plus,680,4,3,3,3,4,4,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +39425,126006,Male,Loyal Customer,52,Business travel,Business,631,4,4,4,4,2,4,5,4,4,3,4,4,4,4,0,0.0,satisfied +39426,32364,Male,Loyal Customer,43,Business travel,Business,101,4,4,4,4,3,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +39427,102011,Female,Loyal Customer,35,Business travel,Business,3066,3,3,3,3,4,4,4,3,3,4,3,5,3,3,42,39.0,satisfied +39428,26254,Male,Loyal Customer,44,Business travel,Eco Plus,515,1,5,5,5,1,1,1,1,2,4,2,4,1,1,0,8.0,neutral or dissatisfied +39429,56866,Male,Loyal Customer,51,Business travel,Business,2454,4,4,4,4,4,4,4,4,4,4,4,4,4,4,9,1.0,satisfied +39430,65549,Male,Loyal Customer,51,Business travel,Business,3959,5,5,5,5,5,5,4,3,3,4,3,3,3,3,3,3.0,satisfied +39431,15682,Male,Loyal Customer,58,Personal Travel,Eco,617,3,0,3,3,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +39432,93827,Female,disloyal Customer,25,Business travel,Business,391,4,5,4,3,1,4,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +39433,10613,Male,Loyal Customer,52,Business travel,Business,2580,3,2,2,2,3,3,2,3,3,3,3,2,3,1,98,103.0,neutral or dissatisfied +39434,50589,Female,Loyal Customer,70,Personal Travel,Eco,373,2,0,4,3,1,2,2,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +39435,43260,Male,disloyal Customer,41,Business travel,Eco,402,2,0,2,5,1,2,1,1,4,1,1,2,1,1,0,13.0,neutral or dissatisfied +39436,116413,Male,Loyal Customer,34,Personal Travel,Eco,373,0,1,0,3,2,0,2,2,3,4,4,4,4,2,10,0.0,satisfied +39437,36749,Female,Loyal Customer,47,Business travel,Eco,2611,4,4,4,4,4,4,4,2,2,3,3,4,3,4,0,0.0,satisfied +39438,11713,Male,Loyal Customer,50,Business travel,Business,395,4,4,4,4,2,5,4,2,2,2,2,4,2,3,9,0.0,satisfied +39439,15596,Female,Loyal Customer,77,Business travel,Eco,229,3,5,5,5,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +39440,121837,Female,Loyal Customer,49,Business travel,Eco,449,2,1,1,1,3,2,3,2,2,2,2,3,2,4,83,86.0,neutral or dissatisfied +39441,10495,Female,Loyal Customer,48,Business travel,Business,2534,5,5,5,5,4,4,5,3,3,3,3,4,3,5,52,53.0,satisfied +39442,111872,Female,Loyal Customer,55,Business travel,Business,628,1,1,1,1,3,4,5,4,4,4,4,5,4,5,1,1.0,satisfied +39443,97004,Male,Loyal Customer,51,Personal Travel,Eco,794,4,4,4,2,4,4,4,4,5,2,4,5,5,4,13,22.0,neutral or dissatisfied +39444,122729,Male,Loyal Customer,39,Business travel,Business,1903,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +39445,93819,Female,Loyal Customer,50,Business travel,Business,3031,1,1,1,1,2,5,4,4,4,4,4,4,4,3,1,16.0,satisfied +39446,63993,Female,Loyal Customer,37,Business travel,Eco,612,2,5,5,5,2,2,2,2,1,2,3,3,3,2,5,5.0,neutral or dissatisfied +39447,113771,Female,Loyal Customer,52,Personal Travel,Eco,414,2,4,2,2,4,3,2,5,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +39448,121611,Female,Loyal Customer,62,Personal Travel,Eco,912,3,3,3,3,4,3,4,1,1,3,1,1,1,2,0,0.0,neutral or dissatisfied +39449,59183,Male,disloyal Customer,27,Business travel,Business,1440,4,4,4,4,3,4,2,3,5,5,5,3,5,3,103,87.0,satisfied +39450,92934,Male,Loyal Customer,65,Personal Travel,Eco,134,3,0,3,1,1,3,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +39451,33205,Male,Loyal Customer,33,Business travel,Eco Plus,102,4,4,4,4,4,4,4,4,2,4,3,2,3,4,0,0.0,satisfied +39452,48986,Female,disloyal Customer,23,Business travel,Eco,109,3,0,3,4,4,3,5,4,5,1,3,1,5,4,0,0.0,neutral or dissatisfied +39453,22274,Male,Loyal Customer,45,Business travel,Eco,145,4,4,4,4,4,4,4,4,1,4,2,2,5,4,0,0.0,satisfied +39454,57812,Male,Loyal Customer,48,Personal Travel,Eco Plus,1235,3,3,3,2,4,3,1,4,5,5,2,5,3,4,2,0.0,neutral or dissatisfied +39455,40273,Female,Loyal Customer,14,Personal Travel,Eco,387,4,5,4,5,4,4,4,4,4,4,4,4,5,4,0,12.0,neutral or dissatisfied +39456,71603,Male,Loyal Customer,24,Business travel,Business,1197,5,4,4,4,5,4,5,5,1,2,4,2,4,5,1,0.0,neutral or dissatisfied +39457,52958,Female,disloyal Customer,44,Business travel,Eco,2306,3,3,3,3,3,2,2,2,3,4,1,2,5,2,0,0.0,neutral or dissatisfied +39458,30196,Female,disloyal Customer,22,Business travel,Eco,253,5,0,5,3,3,5,2,3,3,2,4,3,1,3,0,0.0,satisfied +39459,26283,Male,Loyal Customer,32,Personal Travel,Eco,859,3,1,3,4,5,3,5,5,3,1,3,4,3,5,28,8.0,neutral or dissatisfied +39460,50539,Male,Loyal Customer,40,Personal Travel,Eco,209,2,5,2,4,3,2,3,3,1,5,3,5,4,3,0,0.0,neutral or dissatisfied +39461,99251,Male,Loyal Customer,45,Personal Travel,Eco,541,4,4,4,3,2,4,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +39462,57429,Female,disloyal Customer,22,Business travel,Business,533,0,4,0,5,3,0,3,3,3,4,4,5,4,3,0,0.0,satisfied +39463,110895,Female,disloyal Customer,46,Business travel,Eco,406,3,0,4,3,5,4,5,5,1,5,4,2,4,5,0,17.0,neutral or dissatisfied +39464,113047,Male,Loyal Customer,24,Business travel,Eco,479,4,3,3,3,4,4,2,4,2,2,1,4,1,4,0,0.0,neutral or dissatisfied +39465,105951,Male,Loyal Customer,31,Business travel,Business,2295,2,2,2,2,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +39466,128254,Male,Loyal Customer,45,Business travel,Business,1737,0,0,0,4,3,5,5,1,1,1,1,3,1,3,1,0.0,satisfied +39467,30831,Male,Loyal Customer,63,Business travel,Business,2009,2,3,3,3,3,3,2,2,2,2,2,3,2,2,0,30.0,neutral or dissatisfied +39468,13495,Male,Loyal Customer,46,Business travel,Business,3462,5,5,5,5,2,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +39469,38256,Female,disloyal Customer,24,Business travel,Eco,1180,4,4,4,2,4,4,4,4,2,3,1,4,1,4,69,58.0,satisfied +39470,101899,Male,Loyal Customer,38,Business travel,Business,1984,1,4,5,4,4,2,3,1,1,2,1,1,1,4,2,0.0,neutral or dissatisfied +39471,61544,Female,Loyal Customer,35,Personal Travel,Eco,2288,1,3,2,3,3,2,3,3,2,1,4,2,4,3,0,0.0,neutral or dissatisfied +39472,85836,Male,Loyal Customer,47,Personal Travel,Eco,526,2,5,2,3,3,2,5,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +39473,125896,Female,Loyal Customer,32,Personal Travel,Eco,951,3,4,3,3,2,3,2,2,1,1,4,2,4,2,18,17.0,neutral or dissatisfied +39474,119487,Male,Loyal Customer,48,Business travel,Business,3237,3,4,4,4,3,3,3,3,3,3,3,4,3,2,5,17.0,neutral or dissatisfied +39475,123240,Male,Loyal Customer,70,Personal Travel,Eco,600,2,4,2,3,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +39476,115971,Male,Loyal Customer,67,Personal Travel,Eco,447,4,4,4,1,2,4,3,2,3,4,4,5,4,2,7,0.0,neutral or dissatisfied +39477,20224,Female,disloyal Customer,38,Business travel,Eco,235,3,0,3,5,5,3,5,5,1,4,3,3,4,5,1,0.0,neutral or dissatisfied +39478,99092,Male,Loyal Customer,49,Business travel,Business,2472,3,1,1,1,4,3,3,3,3,3,3,1,3,4,88,89.0,neutral or dissatisfied +39479,25280,Female,Loyal Customer,27,Business travel,Eco Plus,425,0,0,0,4,3,0,3,3,3,5,1,4,2,3,0,0.0,satisfied +39480,101272,Female,disloyal Customer,19,Business travel,Eco,1206,4,4,4,1,5,4,5,5,5,2,4,5,4,5,0,0.0,satisfied +39481,47453,Female,Loyal Customer,29,Personal Travel,Eco,599,5,4,5,4,2,5,2,2,3,2,5,4,5,2,0,0.0,satisfied +39482,40065,Female,Loyal Customer,30,Business travel,Business,3294,4,4,4,4,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +39483,54224,Female,Loyal Customer,60,Business travel,Eco,1222,4,3,3,3,5,1,1,4,4,4,4,5,4,1,0,0.0,satisfied +39484,20305,Male,Loyal Customer,33,Personal Travel,Eco Plus,346,1,5,1,1,5,1,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +39485,106126,Male,Loyal Customer,43,Business travel,Eco,302,3,5,5,5,3,3,3,3,1,4,4,4,4,3,52,48.0,neutral or dissatisfied +39486,124161,Male,Loyal Customer,43,Business travel,Eco,2133,3,4,5,4,3,3,3,3,2,1,2,3,4,3,0,4.0,neutral or dissatisfied +39487,43127,Female,Loyal Customer,57,Business travel,Eco Plus,259,3,4,4,4,5,2,4,3,3,3,3,2,3,2,46,39.0,satisfied +39488,121641,Male,disloyal Customer,22,Business travel,Eco,936,2,3,3,3,1,3,2,1,2,5,4,4,3,1,0,0.0,neutral or dissatisfied +39489,95428,Male,Loyal Customer,58,Business travel,Business,2502,3,3,3,3,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +39490,100972,Male,Loyal Customer,49,Business travel,Business,1524,5,5,5,5,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +39491,24250,Female,Loyal Customer,59,Personal Travel,Eco,170,0,4,0,2,2,4,4,5,5,0,5,3,5,3,0,0.0,satisfied +39492,105285,Male,Loyal Customer,58,Business travel,Business,967,2,2,2,2,5,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +39493,52013,Male,disloyal Customer,39,Business travel,Eco,328,1,0,1,4,1,1,1,1,3,3,1,3,2,1,0,0.0,neutral or dissatisfied +39494,76030,Female,Loyal Customer,28,Personal Travel,Eco,311,3,4,3,1,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +39495,113277,Female,disloyal Customer,23,Business travel,Eco,197,0,4,0,2,5,0,5,5,5,5,5,5,5,5,4,1.0,satisfied +39496,22281,Female,Loyal Customer,31,Business travel,Business,238,4,4,4,4,4,4,4,4,3,1,3,3,4,4,0,0.0,satisfied +39497,82471,Male,Loyal Customer,14,Personal Travel,Eco,509,4,4,4,4,3,4,1,3,3,2,5,3,4,3,0,0.0,satisfied +39498,107671,Male,Loyal Customer,43,Business travel,Business,1664,2,3,2,2,2,5,4,4,4,4,4,3,4,4,7,0.0,satisfied +39499,128689,Male,Loyal Customer,36,Personal Travel,Eco,2442,2,5,2,1,2,1,3,4,5,5,5,3,3,3,13,8.0,neutral or dissatisfied +39500,17471,Male,Loyal Customer,35,Business travel,Eco,341,4,5,5,5,4,3,4,4,2,2,2,1,2,4,0,19.0,satisfied +39501,60112,Female,Loyal Customer,55,Business travel,Business,1120,5,5,5,5,2,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +39502,44298,Male,Loyal Customer,13,Personal Travel,Eco Plus,563,2,5,2,1,2,2,2,2,3,4,5,3,5,2,10,28.0,neutral or dissatisfied +39503,112167,Female,disloyal Customer,47,Business travel,Eco,495,3,0,2,1,5,2,5,5,4,5,2,5,5,5,0,0.0,neutral or dissatisfied +39504,41884,Female,disloyal Customer,39,Business travel,Business,1117,5,4,4,3,5,4,5,5,5,4,5,1,2,5,0,0.0,satisfied +39505,116664,Female,Loyal Customer,52,Business travel,Eco Plus,342,2,1,5,1,1,4,3,2,2,2,2,4,2,1,25,13.0,neutral or dissatisfied +39506,30765,Male,Loyal Customer,56,Personal Travel,Eco,683,2,5,2,5,3,2,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +39507,73748,Male,Loyal Customer,40,Personal Travel,Eco,192,2,3,2,5,5,2,1,5,4,2,4,5,5,5,0,6.0,neutral or dissatisfied +39508,78751,Male,Loyal Customer,48,Business travel,Business,447,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +39509,51462,Male,Loyal Customer,61,Personal Travel,Eco Plus,86,1,5,1,1,5,1,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +39510,16270,Female,disloyal Customer,43,Business travel,Eco,546,1,2,1,3,3,1,3,3,2,4,3,2,4,3,117,118.0,neutral or dissatisfied +39511,79732,Male,Loyal Customer,42,Business travel,Business,762,5,5,5,5,5,5,5,5,5,5,5,3,5,4,5,2.0,satisfied +39512,107790,Male,Loyal Customer,49,Business travel,Business,349,1,3,5,5,1,1,1,4,4,4,3,1,4,1,138,113.0,neutral or dissatisfied +39513,124892,Female,Loyal Customer,40,Business travel,Business,728,3,3,3,3,5,4,5,4,4,4,4,4,4,4,13,2.0,satisfied +39514,94424,Female,Loyal Customer,45,Business travel,Business,2385,2,2,2,2,2,4,4,4,4,4,4,4,4,3,21,21.0,satisfied +39515,84806,Female,Loyal Customer,45,Business travel,Business,3395,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +39516,39182,Male,Loyal Customer,13,Personal Travel,Eco,237,3,4,3,3,5,3,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +39517,101612,Male,Loyal Customer,25,Business travel,Business,1371,2,1,1,1,2,2,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +39518,28077,Male,Loyal Customer,55,Business travel,Eco Plus,2562,4,1,1,1,4,4,4,4,5,5,4,4,2,4,0,0.0,satisfied +39519,48449,Male,disloyal Customer,27,Business travel,Eco,853,4,4,4,4,5,4,3,5,2,1,1,4,5,5,0,7.0,satisfied +39520,24672,Male,Loyal Customer,43,Business travel,Business,691,2,4,4,4,4,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +39521,41940,Female,Loyal Customer,60,Business travel,Eco Plus,129,2,1,4,1,2,4,3,2,2,2,2,4,2,2,57,63.0,neutral or dissatisfied +39522,112397,Male,Loyal Customer,48,Business travel,Business,3311,5,5,5,5,4,5,5,5,5,5,5,5,5,3,1,1.0,satisfied +39523,101775,Female,Loyal Customer,11,Personal Travel,Business,1521,4,1,4,4,4,4,4,4,2,1,3,3,4,4,0,11.0,satisfied +39524,101010,Male,Loyal Customer,59,Business travel,Business,564,4,2,4,4,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +39525,89644,Female,Loyal Customer,36,Business travel,Business,944,5,5,4,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +39526,35203,Male,Loyal Customer,28,Business travel,Business,1010,5,5,5,5,5,5,5,5,3,5,2,4,3,5,0,0.0,satisfied +39527,102501,Female,Loyal Customer,40,Personal Travel,Eco,414,2,2,2,3,2,2,2,2,1,1,3,4,3,2,16,15.0,neutral or dissatisfied +39528,47805,Female,Loyal Customer,24,Business travel,Business,726,5,5,5,5,5,5,5,5,2,5,4,4,5,5,0,0.0,satisfied +39529,72310,Female,disloyal Customer,38,Business travel,Business,921,4,4,4,1,2,4,2,2,5,3,5,4,5,2,0,3.0,satisfied +39530,36844,Female,Loyal Customer,19,Personal Travel,Eco,369,2,4,5,3,2,5,1,2,1,3,3,3,4,2,0,0.0,neutral or dissatisfied +39531,74114,Female,Loyal Customer,49,Business travel,Business,721,4,4,4,4,2,5,5,2,2,2,2,3,2,5,92,82.0,satisfied +39532,15211,Male,disloyal Customer,32,Business travel,Eco,529,4,0,5,4,5,5,5,5,4,5,3,5,1,5,0,0.0,neutral or dissatisfied +39533,118048,Female,Loyal Customer,24,Business travel,Business,3619,1,2,4,2,1,1,1,1,2,2,3,3,4,1,8,24.0,neutral or dissatisfied +39534,126808,Male,Loyal Customer,27,Business travel,Business,2125,3,3,4,3,3,3,3,3,5,4,5,4,5,3,0,0.0,satisfied +39535,120937,Female,Loyal Customer,30,Business travel,Business,2525,3,3,3,3,2,2,2,2,5,3,4,3,4,2,0,0.0,satisfied +39536,40930,Male,disloyal Customer,8,Business travel,Eco,574,1,2,2,3,4,2,4,4,4,1,3,1,4,4,0,0.0,neutral or dissatisfied +39537,38535,Female,Loyal Customer,29,Business travel,Eco,2475,3,2,2,2,3,3,3,3,1,4,2,4,4,3,0,10.0,neutral or dissatisfied +39538,68457,Female,Loyal Customer,41,Business travel,Business,1067,4,4,2,4,3,4,4,2,2,2,2,3,2,4,12,19.0,satisfied +39539,100858,Female,Loyal Customer,38,Business travel,Eco Plus,311,2,3,3,3,2,2,2,2,1,3,4,1,3,2,0,25.0,neutral or dissatisfied +39540,75080,Male,Loyal Customer,32,Personal Travel,Eco Plus,2611,3,4,3,2,5,3,5,5,5,2,4,1,5,5,2,0.0,neutral or dissatisfied +39541,39310,Female,Loyal Customer,57,Personal Travel,Eco,67,1,5,1,3,3,4,4,5,5,1,5,4,5,5,8,7.0,neutral or dissatisfied +39542,32236,Male,Loyal Customer,61,Business travel,Business,2446,0,5,0,1,5,4,4,4,4,1,1,3,4,3,0,0.0,satisfied +39543,69529,Female,Loyal Customer,55,Business travel,Business,2586,4,4,2,4,5,5,5,5,3,3,5,5,3,5,0,0.0,satisfied +39544,37536,Female,Loyal Customer,22,Business travel,Business,1955,2,3,3,3,2,2,2,2,2,5,3,4,3,2,7,0.0,neutral or dissatisfied +39545,123400,Male,Loyal Customer,39,Business travel,Business,1337,2,2,2,2,2,4,5,5,5,5,5,4,5,5,67,59.0,satisfied +39546,75760,Male,Loyal Customer,27,Personal Travel,Eco,813,4,3,4,3,5,4,5,5,4,3,3,4,4,5,15,12.0,satisfied +39547,74198,Male,Loyal Customer,44,Business travel,Business,1592,4,4,4,4,4,5,5,4,5,4,4,5,3,5,333,380.0,satisfied +39548,1296,Female,Loyal Customer,28,Personal Travel,Eco,134,2,3,2,3,3,2,3,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +39549,34614,Male,Loyal Customer,64,Personal Travel,Eco,1598,3,4,4,1,2,4,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +39550,114959,Male,disloyal Customer,40,Business travel,Business,373,3,3,3,2,1,3,1,1,5,3,4,4,5,1,10,6.0,neutral or dissatisfied +39551,111796,Female,Loyal Customer,49,Business travel,Business,349,0,0,0,4,2,5,5,5,5,5,5,5,5,3,35,42.0,satisfied +39552,36872,Male,Loyal Customer,42,Personal Travel,Eco Plus,273,2,3,2,3,5,2,5,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +39553,31046,Female,disloyal Customer,16,Business travel,Eco,641,4,2,4,3,4,4,4,4,1,2,3,3,4,4,0,0.0,neutral or dissatisfied +39554,107395,Female,disloyal Customer,22,Business travel,Eco,717,2,2,2,4,4,2,4,4,4,3,5,3,5,4,19,14.0,neutral or dissatisfied +39555,129595,Male,Loyal Customer,35,Personal Travel,Business,447,1,4,1,3,5,4,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +39556,48568,Male,Loyal Customer,40,Personal Travel,Eco,848,2,5,2,4,1,2,2,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +39557,59457,Male,Loyal Customer,53,Business travel,Eco,758,2,5,4,5,2,2,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +39558,117960,Female,disloyal Customer,38,Business travel,Eco,255,2,1,2,3,5,2,5,5,4,4,4,1,4,5,0,0.0,neutral or dissatisfied +39559,63936,Male,Loyal Customer,24,Personal Travel,Eco,1192,1,5,1,5,1,1,1,1,4,3,4,5,5,1,0,2.0,neutral or dissatisfied +39560,101413,Male,Loyal Customer,14,Personal Travel,Eco,486,4,1,4,3,3,4,3,3,4,5,1,1,3,3,0,0.0,neutral or dissatisfied +39561,90627,Male,Loyal Customer,50,Business travel,Business,2926,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +39562,45452,Female,Loyal Customer,53,Business travel,Business,122,3,5,5,5,5,4,3,2,2,2,3,2,2,1,74,65.0,neutral or dissatisfied +39563,5742,Female,Loyal Customer,48,Business travel,Business,2393,4,5,4,4,4,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +39564,53958,Male,disloyal Customer,31,Business travel,Business,1117,2,2,2,3,2,2,1,2,4,1,3,3,2,2,34,24.0,neutral or dissatisfied +39565,85584,Female,Loyal Customer,50,Business travel,Business,2973,4,2,2,2,2,4,3,2,2,3,4,4,2,1,0,0.0,neutral or dissatisfied +39566,71651,Male,Loyal Customer,63,Personal Travel,Eco,1197,1,5,0,3,2,0,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +39567,78581,Female,Loyal Customer,38,Personal Travel,Eco,630,4,5,4,5,2,4,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +39568,129327,Female,Loyal Customer,41,Business travel,Business,2586,2,1,1,1,5,3,3,2,2,2,2,1,2,1,13,14.0,neutral or dissatisfied +39569,7344,Male,Loyal Customer,61,Personal Travel,Eco,606,2,4,2,3,3,2,1,3,3,3,5,4,5,3,0,33.0,neutral or dissatisfied +39570,118971,Male,Loyal Customer,8,Personal Travel,Eco,570,3,5,3,2,3,3,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +39571,27749,Female,Loyal Customer,30,Business travel,Business,1448,4,4,4,4,4,4,4,4,4,1,1,2,5,4,0,0.0,satisfied +39572,75138,Female,disloyal Customer,22,Business travel,Business,755,4,0,4,4,3,4,3,3,5,5,4,4,5,3,2,0.0,satisfied +39573,87816,Female,Loyal Customer,54,Business travel,Business,214,4,4,4,4,5,5,5,5,5,5,4,5,5,4,0,0.0,satisfied +39574,112017,Male,Loyal Customer,46,Business travel,Business,680,4,4,4,4,2,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +39575,23160,Female,Loyal Customer,45,Personal Travel,Eco,646,4,4,4,4,5,4,4,2,2,4,1,4,2,2,0,0.0,neutral or dissatisfied +39576,89410,Male,Loyal Customer,35,Business travel,Eco,151,2,2,5,5,2,2,2,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +39577,71153,Male,Loyal Customer,54,Business travel,Eco,646,3,5,5,5,3,3,3,3,2,2,3,4,3,3,0,0.0,neutral or dissatisfied +39578,9140,Female,Loyal Customer,56,Business travel,Business,227,2,2,2,2,2,4,5,4,4,4,4,5,4,3,4,6.0,satisfied +39579,21490,Female,Loyal Customer,68,Personal Travel,Eco,164,0,5,0,1,2,5,4,2,2,0,1,5,2,4,11,3.0,satisfied +39580,95601,Female,Loyal Customer,45,Business travel,Business,756,4,4,4,4,3,5,5,5,5,5,5,5,5,3,12,5.0,satisfied +39581,121828,Male,Loyal Customer,51,Business travel,Business,413,1,1,1,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +39582,80123,Female,Loyal Customer,52,Business travel,Business,2475,1,2,2,2,1,1,1,3,5,3,4,1,2,1,7,0.0,neutral or dissatisfied +39583,18315,Female,disloyal Customer,40,Business travel,Business,705,4,4,4,5,5,4,5,5,5,5,3,5,2,5,0,9.0,neutral or dissatisfied +39584,5076,Female,disloyal Customer,26,Business travel,Eco,223,3,3,3,3,1,3,1,1,4,4,3,3,3,1,14,30.0,neutral or dissatisfied +39585,116543,Female,Loyal Customer,57,Personal Travel,Eco,373,3,2,3,3,5,3,3,5,5,3,5,1,5,4,6,6.0,neutral or dissatisfied +39586,66984,Female,Loyal Customer,49,Business travel,Business,964,4,4,4,4,5,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +39587,37750,Female,Loyal Customer,17,Business travel,Eco Plus,1076,5,1,1,1,5,5,3,5,2,1,3,1,5,5,12,9.0,satisfied +39588,107232,Male,Loyal Customer,20,Business travel,Business,1983,2,2,2,2,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +39589,70557,Male,disloyal Customer,24,Business travel,Eco,1258,3,3,3,1,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +39590,81677,Female,Loyal Customer,45,Business travel,Business,907,4,4,4,4,5,4,5,5,5,5,5,3,5,5,15,4.0,satisfied +39591,46425,Female,Loyal Customer,39,Business travel,Business,2449,4,4,4,4,5,1,5,5,5,5,5,2,5,1,0,0.0,satisfied +39592,90433,Male,disloyal Customer,61,Business travel,Business,404,3,3,3,1,2,3,2,2,5,4,5,3,4,2,21,17.0,neutral or dissatisfied +39593,14944,Male,Loyal Customer,36,Business travel,Business,2075,4,4,4,4,3,5,3,4,4,5,4,3,4,4,0,0.0,satisfied +39594,123396,Male,Loyal Customer,58,Business travel,Business,1337,4,4,4,4,4,4,5,4,4,4,4,5,4,4,7,0.0,satisfied +39595,49854,Female,disloyal Customer,39,Business travel,Business,209,3,2,2,4,2,2,2,2,2,2,5,5,5,2,0,0.0,neutral or dissatisfied +39596,26544,Female,Loyal Customer,54,Personal Travel,Eco,990,2,5,2,4,3,5,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +39597,92732,Male,Loyal Customer,43,Business travel,Business,2369,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,5.0,satisfied +39598,20237,Male,Loyal Customer,40,Business travel,Business,2697,5,5,5,5,4,1,1,5,5,5,5,3,5,5,0,0.0,satisfied +39599,28004,Female,disloyal Customer,24,Business travel,Business,763,5,2,5,1,1,5,1,1,1,3,3,3,4,1,0,0.0,satisfied +39600,14356,Male,disloyal Customer,26,Business travel,Eco Plus,395,2,4,2,3,4,2,4,4,2,5,3,4,4,4,12,7.0,neutral or dissatisfied +39601,31753,Male,Loyal Customer,40,Business travel,Business,602,5,5,5,5,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +39602,83105,Male,Loyal Customer,36,Personal Travel,Eco,1084,3,5,3,5,4,3,4,4,5,2,4,4,5,4,17,10.0,neutral or dissatisfied +39603,35495,Female,Loyal Customer,68,Personal Travel,Eco,1028,1,3,1,3,5,4,4,4,4,1,5,3,4,2,0,0.0,neutral or dissatisfied +39604,59206,Female,disloyal Customer,28,Business travel,Eco,1413,4,4,4,4,2,4,2,2,3,1,3,4,4,2,108,83.0,neutral or dissatisfied +39605,68136,Male,Loyal Customer,44,Business travel,Business,1853,1,1,1,1,5,5,4,4,4,4,4,5,4,4,7,0.0,satisfied +39606,117380,Female,Loyal Customer,27,Personal Travel,Eco,1294,3,5,3,3,2,3,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +39607,55642,Female,Loyal Customer,45,Business travel,Business,315,5,5,5,5,2,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +39608,46955,Male,Loyal Customer,24,Personal Travel,Eco,737,4,4,4,3,3,4,4,3,5,4,4,5,4,3,0,0.0,satisfied +39609,119561,Female,Loyal Customer,46,Personal Travel,Eco,814,3,0,3,2,5,5,4,4,4,3,4,3,4,3,0,51.0,neutral or dissatisfied +39610,28787,Female,Loyal Customer,51,Business travel,Business,1050,3,3,2,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +39611,115228,Male,Loyal Customer,57,Business travel,Business,1844,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +39612,96208,Male,Loyal Customer,57,Business travel,Business,328,0,0,0,1,3,5,5,3,3,4,4,4,3,4,70,61.0,satisfied +39613,109981,Female,Loyal Customer,50,Personal Travel,Eco,1033,4,1,4,3,1,3,2,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +39614,104799,Female,Loyal Customer,61,Business travel,Business,2932,3,1,1,1,3,4,3,3,3,3,3,3,3,3,50,41.0,neutral or dissatisfied +39615,53277,Male,disloyal Customer,14,Business travel,Eco,758,3,3,3,4,3,3,3,3,1,1,4,2,3,3,15,63.0,neutral or dissatisfied +39616,22093,Male,disloyal Customer,19,Business travel,Eco,782,2,3,3,4,2,3,4,2,3,2,3,1,3,2,126,128.0,neutral or dissatisfied +39617,68188,Female,Loyal Customer,36,Personal Travel,Eco,597,2,0,2,1,3,2,3,3,5,2,4,3,4,3,38,37.0,neutral or dissatisfied +39618,120297,Female,Loyal Customer,62,Business travel,Business,1779,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +39619,13976,Male,Loyal Customer,34,Business travel,Eco Plus,259,5,5,5,5,5,5,5,5,4,4,1,5,3,5,39,37.0,satisfied +39620,47157,Male,Loyal Customer,24,Business travel,Eco,965,2,1,1,1,2,2,1,2,3,4,2,1,2,2,0,0.0,neutral or dissatisfied +39621,80924,Female,Loyal Customer,59,Business travel,Business,1736,0,0,0,4,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +39622,52333,Female,Loyal Customer,62,Business travel,Business,2356,3,3,3,3,3,4,4,4,4,4,4,2,4,2,0,0.0,satisfied +39623,55957,Female,disloyal Customer,13,Business travel,Business,1315,4,5,4,2,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +39624,2114,Male,Loyal Customer,66,Business travel,Business,404,2,2,2,2,2,4,4,5,5,5,5,4,5,3,36,38.0,satisfied +39625,12012,Female,Loyal Customer,31,Personal Travel,Business,376,2,4,2,2,5,2,5,5,5,5,5,3,4,5,27,18.0,neutral or dissatisfied +39626,122878,Female,Loyal Customer,20,Personal Travel,Eco,226,3,4,3,5,1,3,1,1,5,5,5,3,5,1,70,102.0,neutral or dissatisfied +39627,108079,Male,disloyal Customer,25,Business travel,Business,997,2,4,2,4,2,2,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +39628,85422,Male,Loyal Customer,50,Business travel,Business,227,0,0,0,3,4,4,5,5,5,5,5,5,5,5,11,14.0,satisfied +39629,78997,Male,Loyal Customer,58,Business travel,Business,3950,4,4,3,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +39630,18222,Female,Loyal Customer,58,Business travel,Eco,224,3,4,4,4,2,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +39631,39046,Male,Loyal Customer,35,Business travel,Eco Plus,406,5,4,3,4,5,5,5,5,5,4,4,3,3,5,0,0.0,satisfied +39632,129617,Female,Loyal Customer,32,Business travel,Business,2420,4,4,4,4,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +39633,74218,Female,disloyal Customer,30,Business travel,Business,1746,2,2,2,2,3,2,1,3,4,5,3,4,5,3,0,21.0,neutral or dissatisfied +39634,122809,Male,Loyal Customer,35,Personal Travel,Eco,599,3,3,3,2,1,3,1,1,1,1,5,5,1,1,4,6.0,neutral or dissatisfied +39635,98733,Male,disloyal Customer,35,Business travel,Eco,1558,3,3,3,4,4,3,4,4,3,3,4,3,4,4,15,30.0,neutral or dissatisfied +39636,121371,Male,Loyal Customer,59,Business travel,Eco Plus,1670,2,4,5,4,1,2,1,1,2,4,2,4,4,1,0,8.0,neutral or dissatisfied +39637,26798,Male,Loyal Customer,51,Business travel,Eco,2139,2,2,4,4,2,2,2,2,3,2,5,5,5,2,0,0.0,satisfied +39638,106152,Male,Loyal Customer,44,Business travel,Eco,436,3,1,1,1,3,3,3,3,4,1,4,1,3,3,21,14.0,neutral or dissatisfied +39639,39145,Male,Loyal Customer,47,Personal Travel,Eco,252,3,5,3,4,4,3,4,4,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +39640,94178,Male,Loyal Customer,55,Business travel,Business,1795,5,5,5,5,5,5,5,4,4,4,5,3,4,3,17,12.0,satisfied +39641,51612,Male,Loyal Customer,22,Business travel,Business,651,3,3,3,3,4,5,4,4,3,4,4,5,4,4,2,0.0,satisfied +39642,37378,Female,Loyal Customer,49,Business travel,Eco,1028,4,3,3,3,1,3,4,4,4,4,4,4,4,2,38,17.0,satisfied +39643,74701,Male,Loyal Customer,35,Personal Travel,Eco,1464,3,5,3,1,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +39644,62030,Male,Loyal Customer,49,Business travel,Business,2586,1,2,2,2,2,3,2,1,1,1,1,4,1,1,18,0.0,neutral or dissatisfied +39645,61026,Male,Loyal Customer,27,Business travel,Business,3414,5,5,5,5,5,5,5,4,3,4,4,5,4,5,8,11.0,satisfied +39646,57993,Male,Loyal Customer,37,Business travel,Eco Plus,844,1,1,1,1,1,1,1,1,1,4,4,3,3,1,0,0.0,neutral or dissatisfied +39647,70930,Female,disloyal Customer,25,Business travel,Eco,612,1,4,1,3,1,3,3,1,5,3,4,3,2,3,97,161.0,neutral or dissatisfied +39648,97051,Male,Loyal Customer,49,Business travel,Business,2357,2,2,2,2,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +39649,50930,Male,Loyal Customer,60,Personal Travel,Eco,110,4,4,4,3,5,4,5,5,1,2,4,1,4,5,54,53.0,neutral or dissatisfied +39650,33613,Male,Loyal Customer,24,Business travel,Business,474,1,1,1,1,5,5,5,5,3,4,1,3,5,5,0,0.0,satisfied +39651,60340,Male,Loyal Customer,41,Business travel,Eco,1024,1,3,3,3,1,1,1,1,3,2,3,3,3,1,1,18.0,neutral or dissatisfied +39652,81543,Female,Loyal Customer,10,Personal Travel,Eco,1124,2,2,3,2,5,3,5,5,3,4,1,4,3,5,0,0.0,neutral or dissatisfied +39653,37687,Female,Loyal Customer,60,Personal Travel,Eco,1005,2,4,2,1,2,2,1,3,3,2,3,4,3,5,19,35.0,neutral or dissatisfied +39654,108503,Female,Loyal Customer,52,Business travel,Business,1774,3,3,3,3,2,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +39655,23143,Male,Loyal Customer,58,Business travel,Business,3236,1,1,1,1,5,2,4,4,4,4,4,2,4,3,30,20.0,satisfied +39656,31479,Female,disloyal Customer,42,Business travel,Eco,967,3,3,3,4,2,3,2,2,2,2,1,1,1,2,101,106.0,neutral or dissatisfied +39657,61996,Female,Loyal Customer,50,Business travel,Business,2475,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +39658,85566,Male,Loyal Customer,52,Business travel,Business,3286,3,4,4,4,3,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +39659,92994,Male,Loyal Customer,47,Personal Travel,Eco,738,2,3,2,3,3,2,3,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +39660,97384,Male,Loyal Customer,32,Personal Travel,Eco,347,1,5,1,1,1,1,1,1,3,4,4,4,5,1,0,2.0,neutral or dissatisfied +39661,13285,Male,Loyal Customer,39,Personal Travel,Eco,772,2,3,2,5,3,2,3,3,5,1,4,4,2,3,0,2.0,neutral or dissatisfied +39662,51786,Male,Loyal Customer,18,Personal Travel,Eco,355,3,4,3,5,4,3,4,4,4,2,4,4,4,4,0,2.0,neutral or dissatisfied +39663,59202,Female,Loyal Customer,53,Business travel,Business,1440,2,2,2,2,5,4,5,5,5,5,5,3,5,3,6,0.0,satisfied +39664,112925,Female,Loyal Customer,42,Personal Travel,Eco,1357,1,1,1,4,1,3,4,5,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +39665,105757,Female,disloyal Customer,39,Business travel,Eco,483,2,1,2,3,3,2,3,3,4,2,3,3,3,3,29,44.0,neutral or dissatisfied +39666,24373,Female,Loyal Customer,24,Business travel,Eco,669,2,1,1,1,2,2,4,2,3,3,3,1,3,2,0,8.0,neutral or dissatisfied +39667,39673,Female,Loyal Customer,42,Personal Travel,Eco Plus,476,1,2,2,2,4,2,2,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +39668,94808,Male,Loyal Customer,33,Business travel,Business,2076,1,0,0,3,4,0,4,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +39669,22373,Female,Loyal Customer,33,Business travel,Business,2143,3,2,4,2,1,3,1,2,3,4,4,1,3,1,138,129.0,neutral or dissatisfied +39670,62414,Male,disloyal Customer,34,Business travel,Business,2329,1,1,1,3,3,1,3,3,3,2,4,4,5,3,18,0.0,neutral or dissatisfied +39671,49161,Male,Loyal Customer,41,Business travel,Business,308,4,4,4,4,2,2,5,4,4,4,4,1,4,3,0,0.0,satisfied +39672,40512,Female,Loyal Customer,39,Business travel,Eco Plus,175,4,5,5,5,4,4,4,4,1,3,3,1,4,4,0,0.0,satisfied +39673,32657,Male,Loyal Customer,57,Business travel,Business,1940,3,4,4,4,3,4,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +39674,125400,Male,Loyal Customer,18,Personal Travel,Eco,1440,1,1,1,2,2,1,1,2,2,5,1,3,3,2,10,7.0,neutral or dissatisfied +39675,30401,Male,Loyal Customer,29,Personal Travel,Eco,641,1,4,1,2,5,1,5,5,4,5,5,3,5,5,0,5.0,neutral or dissatisfied +39676,90664,Male,disloyal Customer,38,Business travel,Business,646,2,2,2,3,3,2,1,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +39677,50585,Male,Loyal Customer,16,Personal Travel,Eco,134,2,5,0,4,3,0,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +39678,48812,Male,Loyal Customer,26,Personal Travel,Business,134,4,2,4,3,3,4,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +39679,57795,Male,Loyal Customer,49,Personal Travel,Eco Plus,2704,2,5,2,5,2,2,2,5,2,4,5,2,1,2,6,37.0,neutral or dissatisfied +39680,30451,Male,Loyal Customer,35,Business travel,Business,2528,2,2,2,2,4,5,1,5,5,5,5,1,5,4,23,15.0,satisfied +39681,66209,Female,Loyal Customer,34,Business travel,Business,3113,4,4,4,4,5,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +39682,86570,Male,Loyal Customer,52,Business travel,Business,3001,5,5,5,5,3,5,5,4,4,4,4,4,4,4,7,0.0,satisfied +39683,65078,Male,Loyal Customer,48,Personal Travel,Eco,247,2,5,0,3,2,0,4,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +39684,103500,Female,disloyal Customer,37,Business travel,Business,1047,4,4,4,1,2,4,2,2,5,3,5,5,4,2,0,0.0,satisfied +39685,56268,Male,Loyal Customer,8,Personal Travel,Eco,404,3,5,3,3,2,3,2,2,5,2,3,1,5,2,0,3.0,neutral or dissatisfied +39686,124547,Male,Loyal Customer,13,Personal Travel,Eco,1276,3,5,3,3,5,3,5,5,3,2,3,4,5,5,0,0.0,neutral or dissatisfied +39687,80430,Male,disloyal Customer,54,Business travel,Eco,748,2,2,2,3,1,2,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +39688,105856,Female,Loyal Customer,49,Business travel,Eco Plus,925,3,3,3,3,5,4,4,3,3,3,3,1,3,3,101,77.0,neutral or dissatisfied +39689,126715,Male,Loyal Customer,48,Business travel,Business,2521,3,3,3,3,2,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +39690,3231,Female,Loyal Customer,55,Business travel,Business,2562,5,5,5,5,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +39691,44246,Female,Loyal Customer,24,Business travel,Business,359,1,3,3,3,1,2,1,1,1,5,4,4,3,1,0,9.0,neutral or dissatisfied +39692,118864,Female,Loyal Customer,37,Personal Travel,Eco Plus,304,4,4,4,3,3,4,3,3,4,2,5,5,4,3,7,4.0,satisfied +39693,54425,Female,Loyal Customer,65,Personal Travel,Eco,305,1,5,1,3,1,5,1,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +39694,61394,Female,Loyal Customer,23,Business travel,Business,679,4,4,1,4,5,5,5,5,1,5,4,5,4,5,0,0.0,satisfied +39695,2820,Female,disloyal Customer,45,Business travel,Business,491,3,3,3,3,2,3,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +39696,85562,Male,Loyal Customer,45,Business travel,Business,2353,3,3,3,3,5,5,5,4,4,4,4,4,4,3,6,16.0,satisfied +39697,32464,Male,Loyal Customer,49,Business travel,Eco,163,4,3,3,3,4,4,4,4,2,4,5,3,5,4,0,0.0,satisfied +39698,3975,Female,Loyal Customer,10,Personal Travel,Eco Plus,764,3,5,3,3,2,3,2,2,5,4,5,1,1,2,0,0.0,neutral or dissatisfied +39699,27286,Male,Loyal Customer,28,Business travel,Eco,978,5,4,3,3,5,5,5,5,3,2,4,1,2,5,0,0.0,satisfied +39700,79363,Female,disloyal Customer,25,Business travel,Business,1020,3,5,3,3,2,3,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +39701,63964,Male,Loyal Customer,60,Personal Travel,Eco,1192,2,4,2,4,3,2,4,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +39702,114456,Male,Loyal Customer,58,Business travel,Business,417,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +39703,3242,Male,Loyal Customer,48,Business travel,Business,483,5,5,5,5,2,5,4,5,5,5,5,4,5,4,8,7.0,satisfied +39704,31837,Female,Loyal Customer,53,Personal Travel,Eco,2762,4,4,4,3,4,4,4,3,3,4,4,4,4,4,0,31.0,neutral or dissatisfied +39705,17688,Female,Loyal Customer,60,Business travel,Eco,334,3,1,1,1,2,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +39706,67077,Female,Loyal Customer,46,Business travel,Business,3673,4,4,1,4,3,4,5,2,2,2,2,5,2,5,3,0.0,satisfied +39707,104019,Female,Loyal Customer,40,Business travel,Business,3711,3,1,1,1,2,3,3,3,3,3,3,1,3,1,28,16.0,neutral or dissatisfied +39708,21550,Female,Loyal Customer,19,Personal Travel,Eco,331,2,2,2,3,3,2,3,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +39709,69619,Female,disloyal Customer,27,Business travel,Eco Plus,2475,2,2,2,3,2,1,1,3,4,2,1,1,5,1,3,0.0,neutral or dissatisfied +39710,20471,Female,Loyal Customer,52,Personal Travel,Eco,177,2,4,2,3,4,5,4,5,5,2,5,5,5,5,9,3.0,neutral or dissatisfied +39711,20757,Male,Loyal Customer,47,Personal Travel,Eco Plus,363,2,4,2,5,2,2,2,2,5,4,4,3,4,2,0,1.0,neutral or dissatisfied +39712,23712,Male,Loyal Customer,69,Personal Travel,Eco,251,4,3,0,3,1,0,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +39713,98679,Male,Loyal Customer,7,Personal Travel,Eco,966,1,5,1,4,2,1,2,2,4,2,4,3,4,2,21,25.0,neutral or dissatisfied +39714,116447,Female,Loyal Customer,39,Personal Travel,Eco,480,2,3,2,2,5,2,1,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +39715,98365,Female,Loyal Customer,41,Personal Travel,Eco,1189,4,4,4,1,4,4,4,4,3,4,3,4,4,4,0,0.0,satisfied +39716,83111,Female,Loyal Customer,20,Personal Travel,Eco,1084,2,5,2,2,5,2,5,5,4,5,4,3,4,5,7,8.0,neutral or dissatisfied +39717,109675,Female,Loyal Customer,42,Personal Travel,Eco,930,4,4,4,2,3,4,4,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +39718,23915,Female,Loyal Customer,42,Business travel,Eco,189,3,5,5,5,3,1,5,3,3,3,3,2,3,2,1,0.0,satisfied +39719,110889,Female,disloyal Customer,15,Business travel,Eco,545,2,2,2,4,3,2,3,3,4,5,4,1,3,3,40,35.0,neutral or dissatisfied +39720,123801,Female,Loyal Customer,50,Business travel,Business,3139,1,1,1,1,4,5,5,2,2,2,2,5,2,3,2,0.0,satisfied +39721,79846,Female,Loyal Customer,46,Business travel,Business,1765,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,5.0,satisfied +39722,7431,Female,disloyal Customer,20,Business travel,Eco,122,1,2,1,3,3,1,3,3,1,2,3,4,3,3,83,71.0,neutral or dissatisfied +39723,18612,Male,Loyal Customer,46,Personal Travel,Eco,285,5,4,5,4,2,5,2,2,4,4,5,5,4,2,9,0.0,satisfied +39724,5007,Male,disloyal Customer,27,Business travel,Eco,502,3,4,3,4,5,3,5,5,2,5,4,3,4,5,0,2.0,neutral or dissatisfied +39725,29707,Male,Loyal Customer,8,Personal Travel,Eco,1542,3,3,3,3,5,3,5,5,4,2,3,3,2,5,0,0.0,neutral or dissatisfied +39726,18965,Male,Loyal Customer,35,Business travel,Eco Plus,448,3,2,2,2,3,3,3,3,2,3,3,2,3,3,20,12.0,neutral or dissatisfied +39727,37909,Male,Loyal Customer,31,Personal Travel,Eco,1023,2,5,2,1,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +39728,27423,Male,Loyal Customer,49,Business travel,Business,3847,3,3,3,3,3,1,5,4,4,4,4,5,4,2,0,0.0,satisfied +39729,35883,Female,Loyal Customer,41,Personal Travel,Eco,1065,3,4,3,3,5,3,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +39730,121063,Male,Loyal Customer,50,Business travel,Business,2045,5,5,4,5,4,4,4,4,4,4,4,4,4,4,0,24.0,satisfied +39731,11018,Female,Loyal Customer,56,Business travel,Business,166,2,4,4,4,1,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +39732,9228,Female,Loyal Customer,39,Business travel,Business,2537,1,1,1,1,1,4,3,2,2,2,1,2,2,1,0,0.0,neutral or dissatisfied +39733,43535,Female,disloyal Customer,26,Business travel,Eco,643,3,1,3,4,4,3,4,4,4,3,3,1,3,4,120,121.0,neutral or dissatisfied +39734,39255,Female,disloyal Customer,59,Business travel,Eco,67,3,1,3,4,2,3,2,2,1,3,4,1,3,2,57,55.0,neutral or dissatisfied +39735,107460,Female,Loyal Customer,16,Personal Travel,Eco Plus,725,3,2,3,4,5,3,5,5,3,4,4,3,3,5,0,0.0,neutral or dissatisfied +39736,60719,Female,disloyal Customer,22,Business travel,Eco,225,5,2,5,3,5,5,5,5,1,5,2,2,3,5,12,0.0,satisfied +39737,64098,Female,Loyal Customer,68,Personal Travel,Eco,919,2,5,1,4,3,5,4,4,4,1,1,4,4,4,0,0.0,neutral or dissatisfied +39738,53341,Male,Loyal Customer,23,Business travel,Business,1476,5,5,5,5,5,5,5,5,2,1,3,3,2,5,14,11.0,satisfied +39739,58391,Male,Loyal Customer,31,Business travel,Business,733,4,4,1,4,5,5,5,3,5,4,5,5,5,5,353,359.0,satisfied +39740,33433,Female,Loyal Customer,51,Business travel,Eco,2556,1,2,2,2,1,1,1,1,5,4,4,1,3,1,0,7.0,neutral or dissatisfied +39741,89446,Female,Loyal Customer,55,Personal Travel,Eco,151,3,5,3,4,3,5,4,2,2,3,5,3,2,5,0,4.0,neutral or dissatisfied +39742,36674,Male,Loyal Customer,13,Personal Travel,Eco,1237,3,3,3,4,1,3,1,1,1,4,2,2,4,1,0,16.0,neutral or dissatisfied +39743,21468,Male,disloyal Customer,39,Business travel,Eco,164,2,0,2,3,1,2,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +39744,48659,Male,Loyal Customer,45,Business travel,Business,3036,5,5,5,5,5,5,4,4,4,4,5,5,4,3,0,1.0,satisfied +39745,115356,Female,Loyal Customer,40,Business travel,Business,2123,0,0,0,2,3,4,4,4,4,4,4,5,4,3,60,45.0,satisfied +39746,11746,Female,disloyal Customer,26,Business travel,Eco,429,3,3,3,3,5,3,5,5,3,4,3,3,4,5,0,0.0,neutral or dissatisfied +39747,82791,Male,Loyal Customer,62,Personal Travel,Eco,231,2,4,2,1,5,2,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +39748,8714,Female,Loyal Customer,31,Personal Travel,Eco,304,1,5,3,3,3,3,3,3,3,3,5,5,5,3,0,6.0,neutral or dissatisfied +39749,104106,Male,Loyal Customer,62,Business travel,Eco,297,4,1,1,1,4,4,4,4,3,3,3,3,2,4,0,0.0,satisfied +39750,94556,Female,Loyal Customer,46,Business travel,Business,562,4,4,4,4,2,4,4,2,2,2,2,3,2,4,1,0.0,satisfied +39751,34969,Male,disloyal Customer,22,Business travel,Eco,273,4,3,3,4,4,3,4,4,3,3,3,1,3,4,61,52.0,neutral or dissatisfied +39752,115157,Female,Loyal Customer,53,Business travel,Business,2871,2,1,4,1,3,4,3,2,2,2,2,4,2,3,5,22.0,neutral or dissatisfied +39753,58246,Male,disloyal Customer,55,Business travel,Eco Plus,525,1,1,1,4,3,1,3,3,3,4,4,3,4,3,4,0.0,neutral or dissatisfied +39754,19903,Male,Loyal Customer,43,Business travel,Eco,315,4,3,3,3,4,4,4,4,3,2,3,2,3,4,0,0.0,satisfied +39755,91972,Female,Loyal Customer,58,Business travel,Business,2475,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +39756,99945,Female,Loyal Customer,54,Business travel,Business,1986,4,4,4,4,4,5,5,5,5,5,5,3,5,3,8,0.0,satisfied +39757,119616,Female,Loyal Customer,11,Business travel,Eco Plus,1979,2,3,3,3,2,2,3,2,1,4,3,1,3,2,1,11.0,neutral or dissatisfied +39758,88318,Female,disloyal Customer,40,Business travel,Business,406,2,2,2,4,1,2,1,1,1,4,3,2,3,1,0,0.0,neutral or dissatisfied +39759,58009,Male,Loyal Customer,52,Business travel,Business,1578,1,2,2,2,3,4,3,1,1,1,1,2,1,2,24,12.0,neutral or dissatisfied +39760,85274,Female,Loyal Customer,59,Personal Travel,Eco,731,2,3,3,4,1,4,4,4,4,3,1,3,4,3,4,0.0,neutral or dissatisfied +39761,108564,Male,Loyal Customer,11,Personal Travel,Eco Plus,735,1,5,1,4,5,1,5,5,4,2,4,5,3,5,0,0.0,neutral or dissatisfied +39762,47698,Female,Loyal Customer,70,Personal Travel,Eco,715,3,2,3,3,5,3,3,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +39763,123566,Female,Loyal Customer,53,Business travel,Business,1773,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +39764,1834,Male,Loyal Customer,18,Personal Travel,Eco,500,5,3,5,4,1,5,1,1,2,1,4,2,3,1,0,0.0,satisfied +39765,80007,Female,Loyal Customer,7,Personal Travel,Eco,950,3,1,3,3,2,3,2,2,4,5,4,3,3,2,0,2.0,neutral or dissatisfied +39766,22264,Female,Loyal Customer,66,Business travel,Business,2237,0,5,0,5,3,2,2,4,4,4,4,5,4,4,0,0.0,satisfied +39767,54862,Female,Loyal Customer,34,Business travel,Business,3827,1,1,1,1,2,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +39768,97837,Male,Loyal Customer,45,Personal Travel,Eco,395,1,5,1,4,5,1,5,5,3,5,4,4,4,5,20,23.0,neutral or dissatisfied +39769,119811,Male,disloyal Customer,38,Business travel,Business,936,5,5,5,1,5,5,5,5,3,5,4,5,4,5,6,7.0,satisfied +39770,23080,Female,disloyal Customer,26,Business travel,Eco,794,1,1,1,4,4,1,4,4,5,5,2,1,2,4,4,1.0,neutral or dissatisfied +39771,88656,Female,Loyal Customer,68,Personal Travel,Eco,240,3,5,3,4,2,4,5,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +39772,21594,Male,Loyal Customer,26,Business travel,Business,780,3,3,3,3,2,2,2,2,2,1,1,4,4,2,33,24.0,satisfied +39773,45790,Female,Loyal Customer,47,Business travel,Business,2614,1,3,3,3,4,3,4,1,1,1,1,2,1,2,9,11.0,neutral or dissatisfied +39774,106940,Female,Loyal Customer,40,Business travel,Business,1036,2,2,2,2,4,5,4,4,4,5,4,5,4,3,16,36.0,satisfied +39775,89571,Female,Loyal Customer,55,Business travel,Business,1096,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +39776,8991,Male,Loyal Customer,38,Personal Travel,Eco Plus,799,4,4,3,4,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +39777,35701,Female,Loyal Customer,15,Personal Travel,Eco,2586,2,4,2,1,2,2,2,2,2,2,1,2,5,2,0,12.0,neutral or dissatisfied +39778,79676,Female,Loyal Customer,16,Personal Travel,Eco,712,5,3,5,4,3,5,4,3,4,3,5,3,1,3,1,0.0,satisfied +39779,8184,Female,disloyal Customer,20,Business travel,Eco,335,2,2,3,3,5,3,5,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +39780,121505,Male,Loyal Customer,35,Personal Travel,Eco Plus,257,2,2,2,3,1,2,1,1,1,2,3,1,3,1,0,0.0,neutral or dissatisfied +39781,7183,Female,Loyal Customer,42,Business travel,Business,2657,1,1,1,1,4,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +39782,74120,Male,Loyal Customer,19,Business travel,Business,3218,3,3,3,3,3,3,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +39783,106554,Female,Loyal Customer,47,Business travel,Business,719,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,3.0,satisfied +39784,112749,Male,Loyal Customer,40,Business travel,Business,3491,3,3,5,3,4,5,4,5,5,5,5,4,5,4,6,0.0,satisfied +39785,43157,Female,Loyal Customer,35,Business travel,Eco,1368,2,1,1,1,2,2,2,2,1,1,3,4,3,2,0,9.0,neutral or dissatisfied +39786,60862,Female,Loyal Customer,46,Business travel,Business,1491,5,5,5,5,4,5,5,4,4,4,4,3,4,4,8,0.0,satisfied +39787,40672,Male,Loyal Customer,51,Personal Travel,Business,599,2,1,2,3,1,3,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +39788,52976,Male,Loyal Customer,45,Business travel,Eco Plus,806,5,2,2,2,5,5,5,5,2,4,1,3,3,5,42,9.0,satisfied +39789,93248,Male,Loyal Customer,17,Personal Travel,Eco,689,3,5,3,2,4,3,4,4,5,4,5,5,4,4,17,13.0,neutral or dissatisfied +39790,76413,Male,disloyal Customer,30,Business travel,Eco,405,2,2,2,4,1,2,1,1,2,3,4,3,3,1,0,0.0,neutral or dissatisfied +39791,18737,Male,disloyal Customer,25,Business travel,Eco,1167,1,1,1,4,2,1,2,2,2,1,3,1,2,2,0,0.0,neutral or dissatisfied +39792,53850,Female,Loyal Customer,45,Business travel,Business,191,2,2,4,4,5,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +39793,89779,Male,Loyal Customer,10,Personal Travel,Eco,944,1,4,1,4,3,1,2,3,2,4,2,1,3,3,13,2.0,neutral or dissatisfied +39794,14492,Female,Loyal Customer,50,Business travel,Eco Plus,541,3,1,1,1,3,3,4,3,3,3,3,3,3,4,35,39.0,neutral or dissatisfied +39795,60277,Male,Loyal Customer,44,Business travel,Eco,2446,3,5,5,5,2,3,2,2,4,4,3,4,3,2,80,52.0,neutral or dissatisfied +39796,77553,Female,Loyal Customer,21,Personal Travel,Eco,986,2,5,2,3,3,2,2,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +39797,121159,Male,Loyal Customer,46,Business travel,Business,2521,4,4,4,4,4,4,4,4,2,4,5,4,3,4,0,0.0,satisfied +39798,45209,Male,Loyal Customer,35,Business travel,Eco,1013,3,1,2,1,3,3,3,3,1,3,4,3,4,3,51,57.0,neutral or dissatisfied +39799,127600,Male,Loyal Customer,49,Business travel,Business,1773,5,5,5,5,3,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +39800,79003,Male,Loyal Customer,51,Business travel,Business,3917,0,0,0,3,3,5,4,2,2,2,2,4,2,3,9,6.0,satisfied +39801,103049,Female,disloyal Customer,40,Business travel,Business,328,2,1,1,2,1,1,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +39802,49175,Male,Loyal Customer,50,Business travel,Business,2075,3,3,3,3,2,3,3,5,5,5,4,5,5,2,0,0.0,satisfied +39803,105012,Male,Loyal Customer,43,Business travel,Business,255,1,1,1,1,3,5,5,4,4,4,4,3,4,3,5,0.0,satisfied +39804,66023,Female,disloyal Customer,27,Business travel,Business,1345,3,4,4,3,2,4,1,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +39805,116062,Female,Loyal Customer,70,Personal Travel,Eco,404,3,5,4,5,4,3,2,5,5,4,1,5,5,1,9,2.0,neutral or dissatisfied +39806,36068,Male,Loyal Customer,28,Business travel,Eco,399,1,0,0,1,5,0,5,5,3,3,2,1,1,5,0,0.0,neutral or dissatisfied +39807,44193,Female,disloyal Customer,38,Business travel,Eco,157,2,2,2,3,2,2,2,2,4,4,3,2,4,2,5,0.0,neutral or dissatisfied +39808,29522,Female,Loyal Customer,45,Business travel,Eco,1009,2,2,2,2,5,2,3,2,2,2,2,2,2,2,0,8.0,neutral or dissatisfied +39809,61126,Male,disloyal Customer,23,Business travel,Eco,967,4,4,4,1,2,4,2,2,5,4,5,3,4,2,69,64.0,satisfied +39810,19655,Female,Loyal Customer,43,Personal Travel,Eco,763,2,5,2,4,2,5,5,5,4,4,5,5,3,5,358,346.0,neutral or dissatisfied +39811,97330,Female,Loyal Customer,43,Business travel,Business,872,1,1,1,1,4,4,5,5,5,5,5,4,5,5,19,9.0,satisfied +39812,70480,Female,disloyal Customer,36,Business travel,Eco,867,2,2,2,4,4,2,3,4,1,2,3,2,4,4,64,51.0,neutral or dissatisfied +39813,113255,Female,Loyal Customer,37,Business travel,Business,1548,0,0,0,2,5,4,4,5,5,5,5,3,5,4,3,17.0,satisfied +39814,114700,Male,Loyal Customer,54,Business travel,Business,2007,5,5,3,5,5,4,5,5,5,5,5,4,5,5,1,3.0,satisfied +39815,52183,Male,disloyal Customer,37,Business travel,Eco,751,2,1,1,3,5,1,5,5,4,5,5,4,2,5,1,0.0,neutral or dissatisfied +39816,70687,Female,Loyal Customer,16,Personal Travel,Eco,447,3,3,2,4,4,2,2,4,4,1,3,2,4,4,0,13.0,neutral or dissatisfied +39817,18133,Female,Loyal Customer,55,Personal Travel,Eco,120,1,5,1,3,1,5,5,3,4,4,5,5,4,5,191,258.0,neutral or dissatisfied +39818,85434,Female,Loyal Customer,33,Business travel,Business,1949,3,1,1,1,2,3,3,3,3,3,3,1,3,4,10,10.0,neutral or dissatisfied +39819,10672,Male,disloyal Customer,25,Business travel,Business,667,3,0,3,3,1,3,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +39820,107027,Male,Loyal Customer,57,Business travel,Business,395,2,5,2,2,3,5,5,5,5,5,5,4,5,4,0,15.0,satisfied +39821,90768,Male,Loyal Customer,47,Business travel,Business,515,1,1,1,1,2,5,5,2,2,2,2,5,2,4,3,0.0,satisfied +39822,105822,Male,Loyal Customer,64,Personal Travel,Eco,919,1,4,1,4,5,1,5,5,5,5,3,1,5,5,110,113.0,neutral or dissatisfied +39823,94511,Male,Loyal Customer,42,Business travel,Business,562,4,4,4,4,3,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +39824,31550,Male,Loyal Customer,15,Personal Travel,Eco,844,3,3,2,3,2,2,1,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +39825,4669,Male,Loyal Customer,50,Business travel,Business,3703,5,1,5,5,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +39826,2935,Female,Loyal Customer,26,Personal Travel,Eco,806,2,5,2,5,1,2,1,1,1,1,1,2,5,1,0,0.0,neutral or dissatisfied +39827,108021,Female,Loyal Customer,53,Personal Travel,Eco,589,3,4,3,3,3,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +39828,62024,Male,Loyal Customer,39,Business travel,Business,2475,2,2,2,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +39829,37793,Male,disloyal Customer,24,Business travel,Business,1074,0,0,0,1,1,0,1,1,4,2,5,1,4,1,36,29.0,satisfied +39830,47986,Male,Loyal Customer,16,Personal Travel,Eco,329,3,3,3,4,1,3,1,1,2,5,4,3,3,1,0,0.0,neutral or dissatisfied +39831,54672,Female,Loyal Customer,54,Business travel,Eco,787,4,4,4,4,4,3,5,4,4,4,4,2,4,2,7,0.0,satisfied +39832,258,Male,Loyal Customer,48,Business travel,Business,1708,4,4,4,4,4,4,5,4,4,4,4,3,4,5,4,0.0,satisfied +39833,99175,Male,disloyal Customer,39,Business travel,Business,351,1,1,1,5,3,1,3,3,4,5,4,4,5,3,6,3.0,neutral or dissatisfied +39834,43806,Male,Loyal Customer,9,Personal Travel,Eco,448,3,5,2,1,1,2,1,1,3,4,4,1,4,1,15,,neutral or dissatisfied +39835,26989,Male,Loyal Customer,23,Business travel,Eco,867,1,2,2,2,1,1,3,1,2,3,4,3,3,1,0,0.0,neutral or dissatisfied +39836,76201,Female,disloyal Customer,43,Business travel,Eco,922,3,3,3,4,3,3,3,3,4,1,1,5,1,3,0,0.0,neutral or dissatisfied +39837,46733,Female,Loyal Customer,53,Personal Travel,Eco,73,1,4,1,3,4,5,5,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +39838,111341,Female,Loyal Customer,58,Business travel,Business,1701,4,4,4,4,4,4,4,5,5,5,5,3,5,3,8,5.0,satisfied +39839,855,Male,Loyal Customer,45,Business travel,Business,2930,0,1,1,2,4,5,5,1,1,1,1,4,1,4,0,0.0,satisfied +39840,74582,Female,Loyal Customer,30,Business travel,Business,2210,1,3,3,3,1,1,1,1,2,5,4,1,4,1,39,25.0,neutral or dissatisfied +39841,78389,Female,Loyal Customer,42,Business travel,Eco,580,1,3,3,3,2,3,3,1,1,1,1,3,1,2,16,6.0,neutral or dissatisfied +39842,38434,Female,disloyal Customer,25,Business travel,Eco,2277,3,3,3,3,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +39843,53983,Female,Loyal Customer,55,Business travel,Business,1825,3,3,3,3,4,5,5,4,4,4,4,4,4,5,14,1.0,satisfied +39844,80504,Male,disloyal Customer,22,Business travel,Eco,1117,2,2,2,4,5,2,5,5,5,3,4,4,5,5,0,0.0,satisfied +39845,114612,Female,Loyal Customer,53,Business travel,Business,417,5,5,5,5,3,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +39846,20347,Female,Loyal Customer,53,Business travel,Business,2143,1,4,4,4,2,3,3,1,1,2,1,4,1,1,51,44.0,neutral or dissatisfied +39847,59054,Male,Loyal Customer,49,Business travel,Business,1726,3,3,3,3,3,5,4,3,3,3,3,4,3,4,17,0.0,satisfied +39848,111338,Female,Loyal Customer,12,Personal Travel,Eco,283,3,5,3,2,2,3,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +39849,117639,Male,Loyal Customer,41,Personal Travel,Eco,347,1,5,1,1,1,1,1,1,3,4,5,4,4,1,25,21.0,neutral or dissatisfied +39850,111334,Male,Loyal Customer,12,Personal Travel,Eco,283,3,4,4,2,1,4,1,1,3,5,4,4,4,1,23,42.0,neutral or dissatisfied +39851,12944,Female,Loyal Customer,22,Personal Travel,Eco,563,3,5,3,1,5,3,3,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +39852,94458,Female,disloyal Customer,29,Business travel,Business,189,2,2,2,2,2,2,2,2,5,4,4,4,5,2,34,25.0,neutral or dissatisfied +39853,127571,Female,Loyal Customer,11,Personal Travel,Eco,1670,2,0,2,3,1,2,1,1,3,1,4,4,2,1,0,0.0,neutral or dissatisfied +39854,71631,Male,Loyal Customer,36,Business travel,Business,720,3,3,3,3,5,2,3,4,4,4,4,1,4,1,0,0.0,satisfied +39855,37044,Male,Loyal Customer,69,Personal Travel,Eco,994,2,2,2,3,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +39856,97432,Male,Loyal Customer,55,Business travel,Business,1541,4,4,4,4,4,5,5,3,3,3,3,5,3,3,0,4.0,satisfied +39857,125480,Male,Loyal Customer,70,Personal Travel,Eco,2845,2,4,2,1,2,2,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +39858,75914,Female,Loyal Customer,33,Personal Travel,Eco,597,3,4,3,2,4,3,3,4,1,2,4,2,2,4,0,0.0,neutral or dissatisfied +39859,28824,Female,Loyal Customer,24,Business travel,Business,954,2,2,5,2,5,5,5,5,4,2,5,2,5,5,0,0.0,satisfied +39860,50694,Male,Loyal Customer,41,Personal Travel,Eco,308,4,5,4,3,3,4,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +39861,60431,Female,Loyal Customer,49,Business travel,Business,3893,3,3,3,3,2,5,5,3,3,4,3,3,3,4,3,0.0,satisfied +39862,117243,Female,Loyal Customer,27,Personal Travel,Eco,325,3,4,3,1,1,3,1,1,3,4,2,5,5,1,70,92.0,neutral or dissatisfied +39863,12833,Female,Loyal Customer,66,Business travel,Eco,417,5,1,1,1,4,1,2,5,5,5,5,4,5,5,0,0.0,satisfied +39864,29058,Female,Loyal Customer,16,Personal Travel,Eco,679,5,5,5,4,2,5,2,2,3,5,4,3,5,2,0,0.0,satisfied +39865,115078,Male,Loyal Customer,46,Business travel,Business,3765,3,2,3,3,5,4,5,3,3,4,3,3,3,3,97,107.0,satisfied +39866,35606,Male,Loyal Customer,50,Personal Travel,Eco Plus,1074,5,5,5,2,2,5,2,2,5,2,5,5,4,2,3,0.0,satisfied +39867,67672,Female,Loyal Customer,46,Business travel,Business,1464,2,2,2,2,4,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +39868,44968,Female,Loyal Customer,74,Business travel,Business,222,1,1,3,1,1,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +39869,30682,Female,Loyal Customer,40,Business travel,Eco,680,5,5,5,5,5,5,5,5,2,1,4,4,4,5,19,12.0,satisfied +39870,67233,Female,Loyal Customer,20,Personal Travel,Eco,929,3,4,3,4,4,3,2,4,5,4,5,4,4,4,0,7.0,neutral or dissatisfied +39871,18709,Female,Loyal Customer,55,Business travel,Eco Plus,383,1,1,1,1,5,4,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +39872,113448,Male,Loyal Customer,58,Business travel,Business,3050,4,4,4,4,4,5,5,2,2,2,2,4,2,3,64,62.0,satisfied +39873,86528,Female,Loyal Customer,18,Personal Travel,Eco,760,2,5,2,1,5,2,5,5,5,3,5,3,4,5,27,11.0,neutral or dissatisfied +39874,48793,Male,Loyal Customer,59,Business travel,Business,109,0,5,0,2,3,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +39875,50844,Female,Loyal Customer,51,Personal Travel,Eco,86,2,1,2,4,2,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +39876,42580,Male,Loyal Customer,7,Personal Travel,Eco,315,4,5,4,3,5,4,5,5,3,1,4,3,5,5,0,15.0,neutral or dissatisfied +39877,93204,Female,disloyal Customer,25,Business travel,Eco,1080,3,3,3,4,3,3,3,3,3,2,4,1,3,3,12,17.0,neutral or dissatisfied +39878,62550,Male,Loyal Customer,33,Business travel,Business,1846,3,3,3,3,5,5,5,5,4,2,3,3,4,5,0,0.0,satisfied +39879,18629,Female,Loyal Customer,64,Personal Travel,Eco,201,1,3,0,3,1,4,4,2,2,0,2,4,2,3,2,13.0,neutral or dissatisfied +39880,84825,Female,Loyal Customer,56,Business travel,Eco,481,3,2,2,2,1,3,4,3,3,3,3,1,3,4,9,6.0,neutral or dissatisfied +39881,93095,Female,Loyal Customer,49,Business travel,Business,3636,1,1,1,1,5,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +39882,91195,Female,Loyal Customer,20,Personal Travel,Eco,442,5,4,5,1,5,5,3,5,5,5,5,3,4,5,0,0.0,satisfied +39883,125142,Female,disloyal Customer,23,Business travel,Eco,1291,3,3,3,3,4,3,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +39884,43503,Female,Loyal Customer,32,Personal Travel,Eco,679,3,5,3,1,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +39885,64542,Male,disloyal Customer,23,Business travel,Business,247,5,0,5,3,4,5,2,4,5,4,4,3,4,4,0,0.0,satisfied +39886,38361,Male,Loyal Customer,44,Business travel,Eco,780,3,2,2,2,3,3,3,3,4,4,2,2,2,3,0,0.0,neutral or dissatisfied +39887,116575,Male,Loyal Customer,48,Business travel,Business,337,2,2,2,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +39888,103821,Male,Loyal Customer,47,Business travel,Business,3785,2,2,4,2,2,5,5,4,4,4,4,3,4,3,6,3.0,satisfied +39889,106898,Male,Loyal Customer,63,Personal Travel,Eco,577,2,1,2,2,4,2,4,4,2,5,2,4,2,4,19,2.0,neutral or dissatisfied +39890,7531,Male,disloyal Customer,28,Business travel,Eco,762,3,2,2,3,1,2,1,1,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +39891,121947,Male,disloyal Customer,38,Business travel,Business,430,2,3,3,2,1,3,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +39892,58108,Male,Loyal Customer,46,Personal Travel,Eco,612,1,4,1,4,3,1,3,3,3,3,3,2,4,3,89,84.0,neutral or dissatisfied +39893,63088,Female,Loyal Customer,44,Business travel,Business,2178,5,5,5,5,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +39894,8841,Male,Loyal Customer,66,Personal Travel,Eco Plus,522,1,5,1,3,3,1,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +39895,19769,Male,disloyal Customer,21,Business travel,Eco,578,3,0,2,5,1,2,1,1,4,4,4,5,5,1,0,11.0,neutral or dissatisfied +39896,33669,Female,Loyal Customer,45,Personal Travel,Eco Plus,399,3,4,3,1,5,4,5,5,5,3,2,5,5,3,30,42.0,neutral or dissatisfied +39897,12288,Female,Loyal Customer,59,Business travel,Business,1877,3,3,3,3,3,5,1,5,5,5,3,5,5,1,0,0.0,satisfied +39898,47086,Female,Loyal Customer,21,Personal Travel,Eco,602,3,4,3,3,4,3,4,4,5,5,4,4,4,4,14,7.0,neutral or dissatisfied +39899,26318,Male,Loyal Customer,46,Business travel,Business,1673,4,4,4,4,4,5,4,5,5,5,5,2,5,5,40,89.0,satisfied +39900,41777,Female,Loyal Customer,51,Business travel,Business,2159,4,4,4,4,5,1,5,5,5,5,5,4,5,3,0,0.0,satisfied +39901,75083,Female,Loyal Customer,41,Personal Travel,Business,1814,3,5,3,4,5,5,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +39902,18120,Male,Loyal Customer,55,Business travel,Eco Plus,408,5,4,4,4,5,5,5,5,2,4,5,4,3,5,0,0.0,satisfied +39903,3791,Female,Loyal Customer,57,Personal Travel,Eco,599,2,1,2,4,2,4,3,5,5,2,3,2,5,1,38,23.0,neutral or dissatisfied +39904,5671,Male,Loyal Customer,52,Business travel,Business,3247,1,1,1,1,5,4,4,5,5,5,4,3,5,5,0,0.0,satisfied +39905,49294,Male,disloyal Customer,55,Business travel,Eco,193,3,4,3,1,4,3,1,4,1,2,5,4,2,4,27,24.0,neutral or dissatisfied +39906,49501,Female,disloyal Customer,24,Business travel,Eco,262,3,0,3,4,1,3,1,1,4,2,3,5,1,1,2,0.0,neutral or dissatisfied +39907,65760,Male,Loyal Customer,62,Personal Travel,Eco,936,2,5,2,4,4,2,4,4,5,4,5,4,5,4,3,0.0,neutral or dissatisfied +39908,98820,Male,Loyal Customer,27,Business travel,Eco,763,1,0,0,4,3,0,3,3,2,1,3,4,3,3,21,24.0,neutral or dissatisfied +39909,109405,Female,Loyal Customer,29,Personal Travel,Eco Plus,1046,5,3,5,3,2,5,2,2,4,5,3,2,3,2,0,0.0,satisfied +39910,60892,Female,Loyal Customer,22,Business travel,Business,420,5,2,2,2,5,4,5,5,2,3,3,1,4,5,96,108.0,neutral or dissatisfied +39911,15709,Female,Loyal Customer,52,Business travel,Eco,479,2,4,4,4,1,2,4,1,1,2,1,1,1,4,33,14.0,satisfied +39912,49744,Male,disloyal Customer,37,Business travel,Eco,109,4,0,4,2,5,4,5,5,4,1,4,2,5,5,0,1.0,satisfied +39913,124715,Male,Loyal Customer,22,Personal Travel,Eco,399,2,5,2,4,3,2,3,3,4,4,5,4,4,3,2,0.0,neutral or dissatisfied +39914,4165,Male,Loyal Customer,40,Personal Travel,Eco,431,2,1,2,4,1,2,1,1,1,4,4,2,3,1,9,29.0,neutral or dissatisfied +39915,53864,Female,Loyal Customer,52,Business travel,Eco,140,2,2,2,2,5,3,3,2,2,2,2,1,2,4,25,22.0,neutral or dissatisfied +39916,11003,Male,Loyal Customer,35,Business travel,Business,1843,1,3,3,3,4,3,4,1,1,1,1,2,1,2,26,27.0,neutral or dissatisfied +39917,34106,Female,Loyal Customer,49,Business travel,Eco,1129,5,3,3,3,3,2,4,5,5,5,5,5,5,2,0,0.0,satisfied +39918,56407,Male,Loyal Customer,60,Business travel,Business,2578,3,3,3,3,3,4,4,4,4,4,4,5,4,5,0,16.0,satisfied +39919,86023,Female,Loyal Customer,36,Business travel,Eco,447,3,2,2,2,3,4,3,3,3,4,4,5,4,3,0,0.0,satisfied +39920,6333,Male,Loyal Customer,51,Business travel,Business,1679,0,0,0,4,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +39921,72743,Male,Loyal Customer,27,Business travel,Eco Plus,985,1,0,0,4,5,0,5,5,1,5,3,4,3,5,0,0.0,neutral or dissatisfied +39922,13401,Male,Loyal Customer,8,Business travel,Eco Plus,505,0,4,0,3,4,4,4,4,3,2,2,2,2,4,0,0.0,satisfied +39923,68325,Male,disloyal Customer,25,Business travel,Eco,1387,1,0,0,3,2,1,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +39924,39779,Male,Loyal Customer,56,Personal Travel,Eco,521,1,3,1,4,1,1,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +39925,50845,Male,Loyal Customer,9,Personal Travel,Eco,421,2,3,2,1,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +39926,12001,Male,Loyal Customer,25,Business travel,Eco Plus,643,0,3,0,3,2,0,2,2,2,2,1,4,5,2,0,0.0,satisfied +39927,128838,Female,Loyal Customer,40,Business travel,Business,2391,3,3,3,3,4,4,4,5,3,3,2,4,5,4,4,5.0,satisfied +39928,62346,Female,Loyal Customer,12,Personal Travel,Eco Plus,236,2,1,2,2,3,2,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +39929,91153,Female,Loyal Customer,43,Personal Travel,Eco,545,3,5,5,1,5,4,4,2,2,2,1,4,2,4,182,177.0,neutral or dissatisfied +39930,54085,Female,Loyal Customer,64,Personal Travel,Eco,1416,4,5,4,3,4,5,4,3,3,4,3,3,3,3,8,0.0,neutral or dissatisfied +39931,978,Male,disloyal Customer,37,Business travel,Business,312,5,4,4,4,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +39932,122683,Female,disloyal Customer,41,Business travel,Business,361,1,1,1,1,5,1,5,5,3,5,5,5,4,5,14,0.0,neutral or dissatisfied +39933,115565,Female,disloyal Customer,25,Business travel,Business,390,2,0,2,5,5,2,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +39934,109093,Male,Loyal Customer,19,Personal Travel,Eco,957,1,5,2,2,4,2,1,4,4,2,4,4,5,4,13,10.0,neutral or dissatisfied +39935,42483,Male,Loyal Customer,43,Business travel,Eco,585,4,2,1,2,4,4,4,4,2,3,3,1,4,4,0,0.0,satisfied +39936,129672,Male,Loyal Customer,31,Business travel,Business,3800,1,1,1,1,5,5,5,5,5,4,4,3,5,5,1,0.0,satisfied +39937,108285,Male,disloyal Customer,29,Business travel,Business,1153,0,1,1,2,4,1,4,4,3,2,4,5,4,4,36,27.0,satisfied +39938,1717,Male,Loyal Customer,35,Business travel,Business,364,3,4,4,4,5,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +39939,43912,Male,Loyal Customer,67,Personal Travel,Eco,199,5,4,5,3,3,5,3,3,1,3,3,2,4,3,0,0.0,satisfied +39940,32952,Female,Loyal Customer,53,Personal Travel,Eco,216,4,0,0,5,2,5,4,2,2,0,5,5,2,5,4,0.0,neutral or dissatisfied +39941,68996,Male,Loyal Customer,9,Personal Travel,Eco,2422,2,4,2,3,2,4,4,5,2,3,4,4,3,4,193,189.0,neutral or dissatisfied +39942,117247,Female,Loyal Customer,42,Personal Travel,Eco,338,4,5,4,3,5,5,2,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +39943,13524,Female,Loyal Customer,43,Business travel,Business,227,4,4,1,4,4,4,4,3,2,3,2,4,5,4,116,137.0,satisfied +39944,41823,Female,Loyal Customer,29,Personal Travel,Eco,196,4,4,4,2,1,4,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +39945,9116,Female,disloyal Customer,22,Business travel,Eco,765,3,3,3,4,2,3,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +39946,124988,Male,disloyal Customer,25,Business travel,Eco,184,3,1,3,2,4,3,1,4,1,1,2,4,3,4,0,0.0,neutral or dissatisfied +39947,58484,Male,Loyal Customer,43,Business travel,Business,719,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +39948,65171,Male,Loyal Customer,65,Personal Travel,Eco,247,2,4,2,5,4,2,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +39949,47944,Female,Loyal Customer,64,Personal Travel,Eco,838,2,5,2,3,3,4,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +39950,71448,Female,Loyal Customer,30,Business travel,Business,3298,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,1.0,satisfied +39951,1742,Male,Loyal Customer,18,Personal Travel,Eco,327,2,0,2,2,4,2,4,4,3,5,4,3,5,4,0,2.0,neutral or dissatisfied +39952,57669,Female,disloyal Customer,44,Business travel,Business,200,5,5,5,2,1,5,1,1,4,5,5,5,5,1,0,0.0,satisfied +39953,74854,Female,Loyal Customer,47,Business travel,Business,1995,5,5,5,5,5,3,4,5,5,5,5,3,5,4,39,26.0,satisfied +39954,109247,Male,Loyal Customer,7,Personal Travel,Eco,616,2,5,2,3,3,2,1,3,3,5,2,4,1,3,32,36.0,neutral or dissatisfied +39955,47077,Male,Loyal Customer,48,Personal Travel,Eco,602,3,4,3,4,3,3,3,3,3,1,4,4,3,3,42,37.0,neutral or dissatisfied +39956,5098,Female,Loyal Customer,21,Personal Travel,Eco,235,3,5,3,1,5,3,3,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +39957,3600,Female,disloyal Customer,26,Business travel,Eco,599,3,4,3,3,5,3,2,5,5,2,2,1,2,5,0,0.0,neutral or dissatisfied +39958,7,Male,Loyal Customer,43,Business travel,Business,1963,3,3,3,3,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +39959,106600,Female,disloyal Customer,27,Business travel,Business,589,4,4,4,5,3,4,1,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +39960,56610,Female,disloyal Customer,28,Business travel,Eco,997,3,3,3,3,2,3,5,2,3,3,3,4,2,2,0,1.0,neutral or dissatisfied +39961,17889,Male,Loyal Customer,45,Personal Travel,Eco,399,1,2,1,3,1,1,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +39962,16967,Female,Loyal Customer,47,Personal Travel,Eco,195,2,4,2,1,4,1,5,2,2,2,2,4,2,1,47,37.0,neutral or dissatisfied +39963,109139,Female,Loyal Customer,34,Business travel,Business,1898,4,4,4,4,2,4,5,4,4,4,4,4,4,4,2,1.0,satisfied +39964,71701,Male,Loyal Customer,64,Business travel,Eco Plus,1144,3,1,1,1,4,3,4,4,4,2,3,1,2,4,0,0.0,neutral or dissatisfied +39965,51468,Male,Loyal Customer,34,Business travel,Eco Plus,78,4,2,2,2,4,4,4,4,4,5,4,4,4,4,16,19.0,neutral or dissatisfied +39966,26565,Male,Loyal Customer,45,Business travel,Business,2552,3,3,3,3,4,4,4,5,5,5,5,3,5,3,4,14.0,satisfied +39967,11032,Female,Loyal Customer,39,Business travel,Eco,309,5,2,1,2,5,5,5,5,5,3,2,2,1,5,7,5.0,satisfied +39968,112534,Male,Loyal Customer,36,Personal Travel,Eco,862,2,5,2,5,2,1,1,4,3,4,4,1,5,1,240,242.0,neutral or dissatisfied +39969,81535,Female,Loyal Customer,36,Business travel,Business,3499,2,2,2,2,4,3,3,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +39970,69362,Female,Loyal Customer,49,Business travel,Business,1096,3,3,3,3,2,4,4,4,4,4,4,5,4,4,40,43.0,satisfied +39971,52208,Female,Loyal Customer,61,Business travel,Eco,370,4,5,1,5,4,2,1,4,4,4,4,5,4,3,0,0.0,satisfied +39972,33434,Female,disloyal Customer,23,Business travel,Eco,2399,4,4,4,2,2,4,2,2,2,1,4,1,4,2,0,3.0,neutral or dissatisfied +39973,119872,Female,Loyal Customer,30,Personal Travel,Eco,936,1,5,1,4,4,1,1,4,4,4,5,2,2,4,0,0.0,neutral or dissatisfied +39974,100527,Male,Loyal Customer,39,Personal Travel,Eco,580,2,5,2,3,2,2,2,2,5,4,4,5,5,2,46,42.0,neutral or dissatisfied +39975,7565,Male,Loyal Customer,52,Business travel,Business,594,1,1,1,1,5,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +39976,13945,Female,Loyal Customer,42,Business travel,Business,3674,1,1,1,1,3,4,1,5,5,5,4,1,5,4,7,3.0,satisfied +39977,100044,Male,Loyal Customer,44,Personal Travel,Eco,289,3,4,3,4,2,3,2,2,5,5,4,4,5,2,26,14.0,neutral or dissatisfied +39978,111216,Female,disloyal Customer,34,Business travel,Eco,1546,1,1,1,3,3,1,5,3,4,5,4,4,3,3,0,6.0,neutral or dissatisfied +39979,12411,Female,Loyal Customer,39,Business travel,Business,127,2,3,3,3,3,4,3,1,1,1,2,3,1,2,19,7.0,neutral or dissatisfied +39980,121601,Male,Loyal Customer,18,Personal Travel,Eco,912,2,1,2,4,4,2,4,4,1,3,4,4,3,4,0,27.0,neutral or dissatisfied +39981,111576,Male,Loyal Customer,61,Business travel,Business,375,3,3,3,3,1,2,5,4,4,4,4,2,4,1,1,0.0,satisfied +39982,14427,Male,Loyal Customer,35,Business travel,Eco Plus,585,5,1,1,1,5,5,5,5,4,3,3,1,4,5,95,112.0,satisfied +39983,39392,Female,Loyal Customer,36,Business travel,Business,521,3,3,3,3,5,5,5,3,3,5,3,1,3,1,0,0.0,satisfied +39984,84810,Female,Loyal Customer,30,Business travel,Business,547,3,4,4,4,3,3,3,3,1,2,2,1,3,3,0,0.0,neutral or dissatisfied +39985,16287,Female,Loyal Customer,46,Personal Travel,Eco,748,3,4,2,2,5,5,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +39986,36424,Female,Loyal Customer,45,Business travel,Business,369,5,5,5,5,1,4,3,5,5,5,5,1,5,4,0,0.0,satisfied +39987,28291,Female,Loyal Customer,20,Personal Travel,Business,867,2,3,2,3,2,2,4,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +39988,78620,Male,Loyal Customer,51,Business travel,Business,1426,4,4,4,4,4,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +39989,14473,Female,disloyal Customer,26,Business travel,Eco Plus,674,3,5,4,2,4,4,4,4,3,3,1,3,1,4,0,0.0,neutral or dissatisfied +39990,65096,Female,Loyal Customer,33,Personal Travel,Eco,190,2,4,0,4,5,0,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +39991,91065,Female,Loyal Customer,65,Personal Travel,Eco,581,3,5,3,3,3,5,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +39992,83796,Male,Loyal Customer,60,Business travel,Business,425,3,3,3,3,2,5,5,5,5,5,5,3,5,4,49,39.0,satisfied +39993,67485,Female,Loyal Customer,51,Business travel,Business,3022,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +39994,27348,Female,Loyal Customer,15,Business travel,Business,2656,3,3,3,3,5,5,5,5,4,1,3,1,4,5,0,0.0,satisfied +39995,88252,Female,Loyal Customer,40,Business travel,Business,2480,3,3,3,3,2,5,4,5,5,5,5,5,5,5,2,2.0,satisfied +39996,21540,Female,Loyal Customer,16,Personal Travel,Eco,331,2,5,5,5,1,5,1,1,5,1,4,5,3,1,65,99.0,neutral or dissatisfied +39997,34382,Female,disloyal Customer,52,Business travel,Eco,612,3,5,3,5,1,3,1,1,1,4,5,3,2,1,46,34.0,neutral or dissatisfied +39998,20993,Female,Loyal Customer,31,Business travel,Eco Plus,851,0,0,0,1,0,3,3,4,5,1,1,3,1,3,134,136.0,satisfied +39999,106966,Female,Loyal Customer,40,Business travel,Eco,1036,2,3,3,3,2,2,2,2,1,1,2,1,2,2,26,32.0,neutral or dissatisfied +40000,54152,Female,Loyal Customer,34,Business travel,Business,1569,2,2,2,2,3,1,3,3,3,4,3,3,3,3,0,0.0,satisfied +40001,26463,Female,Loyal Customer,54,Personal Travel,Eco,925,3,4,4,4,3,3,4,4,4,4,4,3,4,2,0,1.0,neutral or dissatisfied +40002,46257,Female,Loyal Customer,69,Personal Travel,Eco,624,3,1,3,4,4,3,3,4,4,3,4,1,4,3,36,33.0,neutral or dissatisfied +40003,33133,Male,Loyal Customer,48,Personal Travel,Eco,102,4,4,4,3,1,4,1,1,4,3,5,5,5,1,1,4.0,satisfied +40004,74876,Female,Loyal Customer,52,Personal Travel,Eco,2239,0,5,1,3,5,5,4,3,3,1,3,5,3,3,0,0.0,satisfied +40005,113702,Female,Loyal Customer,26,Personal Travel,Eco,414,1,4,1,4,1,1,2,1,3,2,3,4,4,1,0,1.0,neutral or dissatisfied +40006,41096,Female,Loyal Customer,35,Business travel,Eco,191,4,1,1,1,4,4,4,4,2,4,1,5,3,4,0,0.0,satisfied +40007,56695,Male,Loyal Customer,48,Personal Travel,Eco,997,4,4,3,3,3,3,3,3,4,4,4,5,5,3,0,6.0,neutral or dissatisfied +40008,50895,Male,Loyal Customer,30,Personal Travel,Eco,199,1,5,0,3,5,0,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +40009,49983,Male,Loyal Customer,41,Business travel,Eco,308,1,5,5,5,1,1,1,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +40010,67231,Male,Loyal Customer,28,Personal Travel,Eco,1121,1,3,1,3,5,1,5,5,3,1,4,3,3,5,8,0.0,neutral or dissatisfied +40011,61852,Male,Loyal Customer,27,Personal Travel,Eco Plus,1635,0,4,0,2,5,0,5,5,1,2,3,3,5,5,14,8.0,satisfied +40012,50265,Male,Loyal Customer,34,Business travel,Business,2501,3,1,1,1,4,4,3,4,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +40013,128622,Male,disloyal Customer,46,Business travel,Business,954,5,5,5,1,1,5,5,1,3,4,4,5,5,1,0,0.0,satisfied +40014,45431,Male,Loyal Customer,28,Business travel,Business,649,3,3,3,3,2,2,2,2,1,2,5,4,5,2,0,0.0,satisfied +40015,53334,Female,Loyal Customer,63,Personal Travel,Eco Plus,758,4,5,4,3,4,4,4,4,3,4,5,4,4,4,146,124.0,neutral or dissatisfied +40016,110659,Female,disloyal Customer,27,Business travel,Business,829,1,1,1,4,1,1,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +40017,91069,Male,Loyal Customer,57,Personal Travel,Eco,406,2,1,2,4,3,2,3,3,2,5,3,4,3,3,0,12.0,neutral or dissatisfied +40018,49490,Male,Loyal Customer,35,Business travel,Business,2783,2,5,5,5,4,3,4,2,2,2,2,4,2,3,0,1.0,neutral or dissatisfied +40019,118151,Male,Loyal Customer,31,Business travel,Business,1444,4,4,4,4,5,5,5,5,2,4,5,5,5,5,194,231.0,satisfied +40020,72718,Female,Loyal Customer,59,Business travel,Business,2658,4,4,4,4,2,5,5,4,4,4,4,4,4,4,89,71.0,satisfied +40021,106072,Male,Loyal Customer,32,Business travel,Business,302,1,1,1,1,4,4,4,4,5,4,4,5,4,4,21,6.0,satisfied +40022,44266,Male,Loyal Customer,16,Personal Travel,Eco,222,3,1,3,3,1,3,5,1,1,4,3,3,3,1,0,0.0,neutral or dissatisfied +40023,10303,Female,Loyal Customer,53,Business travel,Business,2553,1,1,1,1,5,5,4,4,4,4,4,3,4,5,9,8.0,satisfied +40024,71407,Male,Loyal Customer,52,Business travel,Eco,334,3,4,4,4,3,3,3,3,4,1,3,2,4,3,98,91.0,neutral or dissatisfied +40025,9327,Female,Loyal Customer,58,Personal Travel,Eco,542,1,4,1,5,3,5,3,1,1,1,3,1,1,1,5,0.0,neutral or dissatisfied +40026,14107,Female,Loyal Customer,65,Personal Travel,Eco,453,3,2,3,3,3,4,4,4,3,3,3,4,4,4,514,624.0,neutral or dissatisfied +40027,116555,Male,Loyal Customer,68,Personal Travel,Eco,358,1,5,1,5,3,1,3,3,5,2,4,5,5,3,11,8.0,neutral or dissatisfied +40028,128279,Male,Loyal Customer,42,Personal Travel,Business,646,1,3,1,3,2,3,4,1,1,1,1,4,1,4,0,15.0,neutral or dissatisfied +40029,98088,Female,Loyal Customer,28,Business travel,Eco,845,2,5,5,5,2,2,2,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +40030,33281,Female,Loyal Customer,42,Personal Travel,Eco Plus,216,4,2,4,3,1,2,3,2,2,4,4,3,2,4,0,0.0,satisfied +40031,53291,Female,Loyal Customer,45,Business travel,Eco,758,5,3,3,3,4,5,3,5,5,5,5,5,5,3,1,0.0,satisfied +40032,114640,Male,Loyal Customer,51,Business travel,Business,308,2,2,2,2,5,4,5,4,4,4,4,4,4,3,19,15.0,satisfied +40033,54847,Male,Loyal Customer,25,Business travel,Business,862,5,5,5,5,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +40034,127058,Female,Loyal Customer,57,Business travel,Business,3516,1,1,2,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +40035,74327,Female,Loyal Customer,49,Business travel,Business,3386,4,1,1,1,2,4,3,4,4,4,4,4,4,3,7,3.0,neutral or dissatisfied +40036,101661,Female,Loyal Customer,44,Business travel,Business,2106,2,2,2,2,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +40037,21674,Female,Loyal Customer,31,Business travel,Business,2353,1,1,1,1,4,4,4,4,5,1,3,2,2,4,0,0.0,satisfied +40038,104092,Male,disloyal Customer,30,Business travel,Eco,588,4,2,4,3,4,4,3,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +40039,94846,Male,Loyal Customer,16,Business travel,Business,1912,2,4,4,4,2,2,2,2,2,2,3,3,4,2,3,0.0,neutral or dissatisfied +40040,40291,Female,Loyal Customer,30,Personal Travel,Eco,347,2,5,2,3,2,2,2,2,3,2,5,3,1,2,65,49.0,neutral or dissatisfied +40041,105288,Female,Loyal Customer,58,Business travel,Business,2089,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +40042,114395,Male,Loyal Customer,44,Business travel,Business,373,5,5,5,5,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +40043,111902,Female,Loyal Customer,7,Personal Travel,Eco,804,3,4,3,4,4,3,4,4,2,4,4,2,3,4,15,15.0,neutral or dissatisfied +40044,5347,Female,Loyal Customer,57,Business travel,Business,3409,1,1,1,1,5,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +40045,121038,Male,Loyal Customer,68,Personal Travel,Eco,861,0,4,0,3,5,0,5,5,4,2,4,3,5,5,0,0.0,satisfied +40046,4057,Male,Loyal Customer,29,Personal Travel,Eco,479,2,4,2,1,1,2,1,1,1,2,5,5,1,1,67,39.0,neutral or dissatisfied +40047,100325,Male,Loyal Customer,29,Business travel,Eco,1034,2,3,3,3,2,2,2,2,4,4,2,3,3,2,10,20.0,neutral or dissatisfied +40048,101987,Female,Loyal Customer,49,Personal Travel,Eco,628,3,4,3,2,4,5,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +40049,38266,Male,disloyal Customer,27,Business travel,Business,1133,4,4,4,3,4,4,5,4,4,3,3,2,3,4,0,8.0,neutral or dissatisfied +40050,102085,Male,Loyal Customer,45,Business travel,Business,391,4,4,4,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +40051,66616,Female,Loyal Customer,54,Business travel,Business,802,5,5,5,5,3,4,4,5,5,4,5,5,5,4,71,70.0,satisfied +40052,80062,Female,Loyal Customer,12,Personal Travel,Eco,1076,2,2,2,4,5,2,5,5,3,5,3,3,3,5,1,0.0,neutral or dissatisfied +40053,9909,Male,Loyal Customer,35,Business travel,Business,357,3,3,3,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +40054,19650,Female,Loyal Customer,28,Business travel,Business,1563,5,5,5,5,4,4,4,4,1,2,5,3,4,4,0,0.0,satisfied +40055,100963,Male,Loyal Customer,70,Personal Travel,Eco,1142,1,5,1,4,2,1,4,2,3,5,5,3,5,2,14,34.0,neutral or dissatisfied +40056,80614,Female,Loyal Customer,32,Business travel,Business,236,2,5,5,5,2,2,2,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +40057,49624,Male,Loyal Customer,38,Business travel,Eco,373,2,5,5,5,2,2,2,2,5,4,1,3,2,2,0,0.0,satisfied +40058,118333,Female,Loyal Customer,42,Business travel,Eco,602,1,2,2,2,3,3,4,1,1,1,1,3,1,3,28,6.0,neutral or dissatisfied +40059,8830,Male,Loyal Customer,57,Personal Travel,Eco,552,3,5,3,3,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +40060,26642,Female,disloyal Customer,40,Business travel,Business,581,3,3,3,3,2,3,2,2,1,5,4,2,1,2,0,0.0,neutral or dissatisfied +40061,86990,Female,Loyal Customer,43,Personal Travel,Eco,907,1,4,1,1,2,5,4,2,2,1,2,3,2,3,52,47.0,neutral or dissatisfied +40062,34450,Female,Loyal Customer,58,Business travel,Business,2930,4,4,4,4,4,2,1,4,4,4,4,5,4,4,0,0.0,satisfied +40063,27615,Female,Loyal Customer,45,Personal Travel,Eco,697,3,4,3,3,5,3,4,5,5,3,5,4,5,2,1,7.0,neutral or dissatisfied +40064,14617,Male,Loyal Customer,40,Business travel,Business,450,3,5,4,4,4,4,3,3,3,4,3,3,3,1,38,29.0,neutral or dissatisfied +40065,88492,Male,Loyal Customer,38,Business travel,Business,2533,1,2,2,2,1,1,4,1,1,1,1,2,1,2,4,0.0,neutral or dissatisfied +40066,56905,Female,Loyal Customer,54,Business travel,Business,2565,2,2,2,2,5,5,5,5,2,5,5,5,3,5,23,26.0,satisfied +40067,29843,Male,Loyal Customer,34,Business travel,Business,2482,4,4,4,4,1,1,4,5,5,5,3,1,5,1,0,0.0,satisfied +40068,23931,Male,Loyal Customer,15,Business travel,Eco Plus,589,5,3,4,3,5,5,4,5,2,2,4,3,1,5,0,2.0,satisfied +40069,115246,Male,disloyal Customer,37,Business travel,Business,337,4,4,4,1,5,4,5,5,5,2,4,3,4,5,0,0.0,satisfied +40070,59554,Female,Loyal Customer,55,Business travel,Business,2237,5,5,4,5,2,4,5,4,4,4,4,4,4,4,39,26.0,satisfied +40071,31238,Female,Loyal Customer,41,Business travel,Eco,472,4,4,4,4,4,4,4,4,4,5,1,5,4,4,11,8.0,satisfied +40072,47514,Female,Loyal Customer,39,Personal Travel,Eco,599,4,5,4,2,5,4,5,5,5,5,2,5,4,5,6,0.0,neutral or dissatisfied +40073,10558,Female,Loyal Customer,48,Business travel,Business,201,4,4,4,4,2,4,5,4,4,5,5,3,4,3,0,9.0,satisfied +40074,5991,Female,Loyal Customer,54,Business travel,Business,691,3,3,3,3,3,5,4,2,2,2,2,5,2,3,0,36.0,satisfied +40075,73023,Female,Loyal Customer,46,Personal Travel,Eco,1096,3,3,3,3,3,4,3,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +40076,76066,Female,Loyal Customer,25,Business travel,Business,2973,4,4,4,4,3,3,3,3,5,2,5,4,4,3,0,0.0,satisfied +40077,35214,Female,Loyal Customer,48,Business travel,Eco,1028,5,3,3,3,3,3,1,5,5,5,5,3,5,1,0,7.0,satisfied +40078,6373,Female,Loyal Customer,60,Business travel,Eco,296,3,3,2,2,3,3,4,3,3,3,3,4,3,4,0,15.0,neutral or dissatisfied +40079,42508,Female,Loyal Customer,43,Business travel,Eco Plus,541,1,2,2,2,5,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +40080,7956,Male,disloyal Customer,25,Business travel,Business,594,2,5,2,3,2,2,2,2,5,2,5,3,5,2,2,0.0,neutral or dissatisfied +40081,3155,Female,Loyal Customer,23,Personal Travel,Eco,140,3,5,3,4,4,3,4,4,3,1,2,1,2,4,0,0.0,neutral or dissatisfied +40082,105385,Male,Loyal Customer,31,Business travel,Eco,369,4,3,3,3,4,4,4,4,1,4,4,1,4,4,26,13.0,neutral or dissatisfied +40083,28228,Female,Loyal Customer,55,Personal Travel,Business,1009,4,2,4,4,1,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +40084,86085,Female,Loyal Customer,41,Business travel,Business,3852,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +40085,101789,Female,disloyal Customer,14,Business travel,Eco,1521,3,3,3,4,2,3,2,2,1,2,4,3,4,2,35,40.0,neutral or dissatisfied +40086,106569,Female,Loyal Customer,24,Business travel,Business,1506,3,3,1,3,4,4,4,4,5,3,4,4,5,4,87,78.0,satisfied +40087,112496,Male,Loyal Customer,59,Personal Travel,Eco,850,2,5,2,3,3,2,3,3,4,2,4,5,4,3,13,5.0,neutral or dissatisfied +40088,25239,Male,Loyal Customer,64,Personal Travel,Eco,925,3,3,3,2,2,3,2,2,2,5,3,4,2,2,0,10.0,neutral or dissatisfied +40089,78240,Male,Loyal Customer,64,Business travel,Eco Plus,259,1,1,1,1,1,1,1,1,2,5,3,3,3,1,12,10.0,neutral or dissatisfied +40090,89315,Male,Loyal Customer,9,Personal Travel,Business,1587,4,5,4,2,5,4,5,5,3,3,4,4,5,5,44,41.0,neutral or dissatisfied +40091,81144,Female,Loyal Customer,26,Personal Travel,Business,1310,2,4,2,4,2,2,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +40092,56961,Male,Loyal Customer,61,Business travel,Business,925,3,3,3,3,3,3,3,3,5,4,4,3,4,3,0,2.0,neutral or dissatisfied +40093,3273,Male,Loyal Customer,51,Business travel,Eco,479,4,2,2,2,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +40094,85436,Female,Loyal Customer,60,Business travel,Eco,332,3,1,1,1,5,3,2,2,2,3,2,2,2,1,0,1.0,neutral or dissatisfied +40095,92320,Female,Loyal Customer,49,Business travel,Business,2486,2,2,3,2,5,5,5,5,3,4,4,5,5,5,0,9.0,satisfied +40096,108418,Male,disloyal Customer,27,Business travel,Business,1444,4,4,4,4,5,4,5,5,4,5,4,3,4,5,7,1.0,neutral or dissatisfied +40097,80260,Male,Loyal Customer,57,Personal Travel,Eco,1969,2,3,2,3,1,2,1,1,1,5,3,2,4,1,11,3.0,neutral or dissatisfied +40098,70510,Male,Loyal Customer,32,Personal Travel,Eco,867,3,4,3,2,4,3,2,4,4,2,5,1,5,4,0,0.0,neutral or dissatisfied +40099,118201,Female,Loyal Customer,31,Personal Travel,Eco,1444,1,4,1,3,4,1,4,4,4,3,4,4,3,4,1,,neutral or dissatisfied +40100,124385,Male,Loyal Customer,39,Personal Travel,Eco,808,2,4,2,4,3,2,3,3,4,1,3,2,3,3,15,3.0,neutral or dissatisfied +40101,85756,Male,disloyal Customer,20,Business travel,Business,666,0,4,0,3,4,0,4,4,4,3,5,4,5,4,28,25.0,satisfied +40102,54376,Male,disloyal Customer,28,Business travel,Eco,305,3,5,3,3,2,3,2,2,2,1,3,1,4,2,6,0.0,neutral or dissatisfied +40103,128887,Female,Loyal Customer,43,Business travel,Eco,2454,4,2,2,2,4,4,4,4,4,2,3,4,3,4,30,27.0,neutral or dissatisfied +40104,66627,Female,Loyal Customer,70,Personal Travel,Business,802,1,2,1,3,1,3,3,4,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +40105,35058,Female,disloyal Customer,20,Business travel,Business,828,2,2,2,2,5,2,5,5,1,2,3,4,3,5,0,21.0,neutral or dissatisfied +40106,91321,Male,disloyal Customer,22,Business travel,Eco,240,1,1,1,4,4,1,5,4,4,4,3,4,4,4,0,23.0,neutral or dissatisfied +40107,19061,Female,Loyal Customer,42,Business travel,Business,642,4,4,4,4,5,1,4,4,4,4,4,4,4,2,12,6.0,satisfied +40108,32191,Male,disloyal Customer,36,Business travel,Eco,102,4,3,4,4,5,4,3,5,5,4,4,1,4,5,0,0.0,neutral or dissatisfied +40109,41232,Male,Loyal Customer,36,Business travel,Business,2260,3,4,4,4,2,3,4,3,3,3,3,3,3,4,17,8.0,neutral or dissatisfied +40110,95442,Male,Loyal Customer,32,Business travel,Business,248,0,1,1,3,4,4,4,4,3,2,4,5,4,4,77,81.0,satisfied +40111,15541,Female,Loyal Customer,67,Personal Travel,Eco,812,2,3,2,4,2,3,3,2,2,2,2,1,2,3,61,70.0,neutral or dissatisfied +40112,4719,Male,disloyal Customer,23,Business travel,Eco,888,3,3,3,3,1,3,1,1,4,5,4,3,4,1,56,46.0,neutral or dissatisfied +40113,86475,Female,Loyal Customer,49,Business travel,Eco,762,5,3,3,3,2,1,5,5,5,5,5,2,5,5,16,3.0,satisfied +40114,64930,Female,disloyal Customer,18,Business travel,Eco,190,3,2,3,4,2,3,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +40115,10321,Female,Loyal Customer,52,Business travel,Business,3524,0,4,0,5,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +40116,20815,Female,Loyal Customer,58,Business travel,Eco,534,2,5,5,5,5,3,4,2,2,2,2,4,2,3,15,23.0,neutral or dissatisfied +40117,32804,Female,disloyal Customer,73,Business travel,Eco,102,3,0,2,2,5,2,5,5,2,4,5,2,3,5,0,0.0,neutral or dissatisfied +40118,101460,Male,Loyal Customer,51,Business travel,Business,2562,5,5,5,5,4,4,4,5,5,5,5,5,5,3,48,41.0,satisfied +40119,30200,Female,disloyal Customer,25,Business travel,Eco Plus,95,3,1,3,4,4,3,5,4,1,2,4,4,4,4,0,0.0,neutral or dissatisfied +40120,74438,Female,disloyal Customer,36,Business travel,Business,1431,3,3,3,1,2,3,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +40121,26593,Female,Loyal Customer,27,Business travel,Eco,545,5,3,3,3,5,5,5,5,4,2,2,3,2,5,0,0.0,satisfied +40122,94901,Female,disloyal Customer,24,Business travel,Eco,341,2,0,2,3,2,2,2,2,5,5,5,3,3,2,0,0.0,neutral or dissatisfied +40123,41183,Male,Loyal Customer,51,Business travel,Business,395,5,5,5,5,4,2,4,4,4,4,4,4,4,1,41,21.0,satisfied +40124,47691,Male,Loyal Customer,15,Personal Travel,Eco,1504,1,4,1,2,3,1,3,3,4,3,4,4,5,3,4,2.0,neutral or dissatisfied +40125,66858,Female,Loyal Customer,55,Personal Travel,Eco,731,3,2,3,2,2,2,2,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +40126,37614,Female,Loyal Customer,65,Personal Travel,Eco,1005,3,4,2,1,3,5,4,3,3,2,3,5,3,4,70,62.0,neutral or dissatisfied +40127,76263,Male,Loyal Customer,34,Business travel,Business,1927,1,1,1,1,4,4,5,2,2,2,2,4,2,3,28,34.0,satisfied +40128,3494,Female,Loyal Customer,40,Personal Travel,Eco,1080,4,3,4,4,3,4,3,3,3,5,5,5,3,3,0,0.0,neutral or dissatisfied +40129,30608,Male,Loyal Customer,58,Personal Travel,Eco,472,2,5,2,3,3,2,3,3,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +40130,27714,Female,Loyal Customer,43,Business travel,Business,1448,1,1,5,1,5,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +40131,2440,Male,Loyal Customer,11,Personal Travel,Eco,641,3,4,3,3,4,3,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +40132,89286,Female,Loyal Customer,16,Business travel,Business,453,1,5,5,5,1,1,1,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +40133,40596,Male,Loyal Customer,40,Business travel,Eco,391,4,5,5,5,4,4,4,4,1,4,3,3,3,4,4,0.0,neutral or dissatisfied +40134,113174,Female,Loyal Customer,27,Personal Travel,Eco,628,2,4,2,1,2,2,2,2,4,5,4,5,5,2,11,1.0,neutral or dissatisfied +40135,15065,Male,Loyal Customer,22,Personal Travel,Eco,488,1,4,1,3,5,1,1,5,3,3,5,5,5,5,12,16.0,neutral or dissatisfied +40136,60781,Male,Loyal Customer,42,Personal Travel,Eco,804,2,5,2,2,2,2,2,2,1,2,5,2,2,2,0,11.0,neutral or dissatisfied +40137,82021,Male,Loyal Customer,28,Personal Travel,Eco,1589,4,5,4,3,4,4,4,4,5,2,4,5,5,4,9,41.0,neutral or dissatisfied +40138,73598,Female,Loyal Customer,50,Business travel,Business,192,4,3,4,4,3,5,5,5,5,5,5,4,5,3,9,6.0,satisfied +40139,50054,Female,Loyal Customer,40,Business travel,Business,262,2,3,3,3,5,3,4,2,2,2,2,4,2,4,106,106.0,neutral or dissatisfied +40140,58863,Female,Loyal Customer,37,Business travel,Business,888,4,4,4,4,2,5,5,4,4,4,4,3,4,3,14,0.0,satisfied +40141,53564,Female,Loyal Customer,27,Business travel,Business,1195,5,2,5,5,5,5,5,5,5,4,4,1,2,5,0,0.0,satisfied +40142,43835,Female,Loyal Customer,52,Business travel,Business,114,4,1,4,4,5,3,5,5,5,5,5,2,5,2,0,0.0,satisfied +40143,52921,Female,Loyal Customer,19,Business travel,Business,679,2,5,2,5,2,2,2,2,1,3,4,3,4,2,9,21.0,neutral or dissatisfied +40144,53791,Male,Loyal Customer,29,Business travel,Eco,191,5,3,5,3,5,5,5,5,1,2,2,2,2,5,15,2.0,satisfied +40145,117946,Male,Loyal Customer,45,Business travel,Business,3212,2,2,2,2,2,5,4,5,5,5,5,3,5,5,0,1.0,satisfied +40146,35615,Female,Loyal Customer,37,Personal Travel,Eco Plus,1010,3,3,3,3,4,3,4,4,4,2,4,1,3,4,0,20.0,neutral or dissatisfied +40147,6322,Male,Loyal Customer,63,Business travel,Business,296,5,5,5,5,5,4,5,4,4,4,4,4,4,5,24,13.0,satisfied +40148,60250,Female,Loyal Customer,39,Personal Travel,Eco,1546,4,4,4,3,2,4,2,2,3,3,3,2,4,2,11,10.0,neutral or dissatisfied +40149,75829,Female,Loyal Customer,27,Business travel,Business,1440,1,1,2,1,4,4,4,4,5,3,4,3,5,4,56,129.0,satisfied +40150,38238,Female,Loyal Customer,65,Business travel,Eco,1173,4,1,1,1,2,3,1,4,4,4,4,5,4,3,70,80.0,satisfied +40151,27442,Female,Loyal Customer,33,Business travel,Business,3811,5,5,5,5,1,5,4,5,5,5,5,4,5,3,0,2.0,satisfied +40152,23782,Female,Loyal Customer,31,Business travel,Business,2827,5,5,5,5,5,5,5,5,5,3,2,5,4,5,0,19.0,satisfied +40153,34568,Female,disloyal Customer,34,Business travel,Eco,1576,2,2,2,3,5,2,5,5,2,4,3,2,2,5,7,14.0,neutral or dissatisfied +40154,25568,Female,Loyal Customer,31,Business travel,Business,3040,2,2,2,2,2,2,2,2,4,1,2,4,3,2,27,42.0,satisfied +40155,106235,Male,Loyal Customer,56,Personal Travel,Eco,471,3,3,3,5,5,3,5,5,5,1,1,5,3,5,0,0.0,neutral or dissatisfied +40156,29891,Female,disloyal Customer,26,Business travel,Eco,95,0,4,0,4,4,0,4,4,5,2,2,3,1,4,17,29.0,satisfied +40157,19741,Female,Loyal Customer,29,Business travel,Eco Plus,475,4,4,4,4,4,4,4,4,2,1,4,3,5,4,3,0.0,satisfied +40158,63927,Female,Loyal Customer,21,Personal Travel,Eco,1192,4,4,4,4,3,4,3,3,1,4,2,1,4,3,0,26.0,satisfied +40159,101766,Female,Loyal Customer,13,Personal Travel,Eco,1590,2,4,2,4,3,2,1,3,5,2,5,4,5,3,35,30.0,neutral or dissatisfied +40160,69145,Male,Loyal Customer,26,Business travel,Business,2248,2,2,2,2,5,5,5,5,3,4,5,4,5,5,10,0.0,satisfied +40161,53787,Male,Loyal Customer,57,Personal Travel,Business,191,4,4,4,1,3,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +40162,77461,Male,Loyal Customer,54,Business travel,Business,3255,5,5,5,5,2,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +40163,117747,Male,Loyal Customer,55,Personal Travel,Eco,833,4,5,4,3,2,4,2,2,5,3,5,5,4,2,75,58.0,neutral or dissatisfied +40164,38952,Male,Loyal Customer,50,Personal Travel,Eco Plus,162,1,4,1,4,5,1,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +40165,36695,Female,Loyal Customer,55,Personal Travel,Eco,1010,3,3,3,1,3,3,4,2,5,2,5,4,2,4,157,152.0,neutral or dissatisfied +40166,60217,Female,Loyal Customer,46,Business travel,Business,1607,5,5,5,5,2,3,5,5,5,5,5,4,5,4,95,92.0,satisfied +40167,43491,Female,Loyal Customer,31,Personal Travel,Eco,679,2,5,2,2,2,2,3,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +40168,90890,Male,disloyal Customer,43,Business travel,Eco,406,3,4,4,3,5,4,3,5,2,2,3,4,3,5,0,2.0,neutral or dissatisfied +40169,47491,Male,Loyal Customer,31,Personal Travel,Eco,558,2,5,2,1,4,2,4,4,4,4,3,3,2,4,0,4.0,neutral or dissatisfied +40170,77081,Male,Loyal Customer,23,Personal Travel,Eco,991,3,5,3,2,4,3,4,4,5,2,5,3,5,4,11,0.0,neutral or dissatisfied +40171,40499,Female,Loyal Customer,11,Personal Travel,Eco,461,1,5,1,2,1,1,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +40172,47915,Female,Loyal Customer,12,Personal Travel,Eco,329,0,3,0,4,0,2,2,4,2,1,2,2,4,2,140,137.0,satisfied +40173,59348,Male,Loyal Customer,57,Business travel,Eco,2399,3,4,2,4,3,3,3,4,3,4,3,3,2,3,334,326.0,neutral or dissatisfied +40174,66276,Female,Loyal Customer,46,Business travel,Business,550,4,4,4,4,3,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +40175,61593,Male,disloyal Customer,34,Business travel,Eco,1000,4,4,4,3,1,4,1,1,3,4,2,2,4,1,0,0.0,neutral or dissatisfied +40176,7477,Male,Loyal Customer,32,Personal Travel,Eco Plus,510,2,5,2,3,2,2,2,2,5,2,4,4,5,2,0,60.0,neutral or dissatisfied +40177,79714,Female,Loyal Customer,20,Personal Travel,Eco,762,2,4,2,3,4,2,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +40178,20603,Male,Loyal Customer,42,Business travel,Eco Plus,133,1,5,5,5,1,1,1,1,1,3,4,2,4,1,42,44.0,neutral or dissatisfied +40179,26234,Female,Loyal Customer,11,Personal Travel,Eco,406,3,2,3,2,5,3,5,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +40180,122737,Male,Loyal Customer,23,Business travel,Business,1888,4,5,5,5,4,3,4,4,1,3,4,4,4,4,0,0.0,neutral or dissatisfied +40181,96699,Male,Loyal Customer,52,Business travel,Business,2253,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +40182,16782,Female,Loyal Customer,39,Personal Travel,Eco,569,3,2,4,4,1,4,1,1,2,2,3,2,4,1,0,26.0,neutral or dissatisfied +40183,95312,Female,Loyal Customer,65,Personal Travel,Eco,277,2,4,2,4,4,3,4,2,2,2,2,1,2,3,0,6.0,neutral or dissatisfied +40184,39510,Male,Loyal Customer,44,Business travel,Eco,1068,4,2,2,2,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +40185,23791,Female,Loyal Customer,24,Business travel,Eco,374,2,4,4,4,2,2,1,2,4,5,3,1,4,2,0,2.0,neutral or dissatisfied +40186,45703,Female,disloyal Customer,38,Business travel,Eco,836,3,3,3,3,5,3,5,5,1,4,5,5,1,5,23,19.0,neutral or dissatisfied +40187,2763,Male,Loyal Customer,36,Business travel,Business,1631,3,3,5,3,4,5,4,5,5,5,5,3,5,4,43,27.0,satisfied +40188,15085,Male,Loyal Customer,35,Business travel,Eco,322,3,4,4,4,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +40189,54742,Female,Loyal Customer,67,Personal Travel,Eco,787,4,4,4,2,2,5,5,2,2,4,2,4,2,4,23,12.0,neutral or dissatisfied +40190,43231,Female,Loyal Customer,35,Business travel,Business,2825,3,2,2,2,5,3,2,3,3,3,3,1,3,1,0,5.0,neutral or dissatisfied +40191,3734,Female,Loyal Customer,12,Personal Travel,Eco,544,2,2,2,2,5,2,5,5,3,3,3,3,3,5,1,0.0,neutral or dissatisfied +40192,28488,Female,Loyal Customer,27,Business travel,Eco,1739,2,2,5,2,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +40193,25799,Male,Loyal Customer,44,Personal Travel,Eco,762,3,3,3,3,1,3,1,1,3,4,2,1,3,1,116,105.0,neutral or dissatisfied +40194,52177,Male,disloyal Customer,24,Business travel,Eco,651,5,0,5,1,3,5,3,3,3,3,1,1,1,3,89,81.0,satisfied +40195,50703,Male,Loyal Customer,25,Personal Travel,Eco,207,2,2,2,3,5,2,2,5,2,2,3,2,3,5,0,0.0,neutral or dissatisfied +40196,35191,Male,Loyal Customer,25,Business travel,Business,2443,1,1,5,1,4,4,4,4,3,2,4,3,5,4,0,2.0,satisfied +40197,52577,Male,disloyal Customer,33,Business travel,Eco,160,4,1,4,3,3,4,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +40198,23135,Female,Loyal Customer,45,Business travel,Business,223,5,5,5,5,4,4,2,5,5,5,4,4,5,3,0,4.0,satisfied +40199,120017,Male,Loyal Customer,37,Personal Travel,Eco,328,3,4,3,5,3,3,3,3,2,4,5,1,2,3,0,30.0,neutral or dissatisfied +40200,126919,Female,Loyal Customer,50,Business travel,Business,621,5,5,5,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +40201,108505,Female,Loyal Customer,14,Personal Travel,Eco,287,0,5,0,5,1,0,3,1,3,5,5,5,5,1,0,0.0,satisfied +40202,104525,Male,disloyal Customer,29,Business travel,Business,1256,0,0,0,4,1,0,1,1,5,5,4,5,5,1,6,0.0,satisfied +40203,27896,Male,Loyal Customer,40,Personal Travel,Eco Plus,2329,3,4,3,1,3,1,1,3,3,3,1,1,2,1,0,0.0,neutral or dissatisfied +40204,63363,Male,Loyal Customer,10,Personal Travel,Eco,337,5,5,5,4,1,5,1,1,4,4,5,4,5,1,1,0.0,satisfied +40205,23402,Female,Loyal Customer,51,Personal Travel,Eco,300,2,5,2,3,2,4,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +40206,55117,Male,Loyal Customer,69,Personal Travel,Eco,1635,3,4,2,3,3,2,3,3,5,2,3,4,5,3,95,107.0,neutral or dissatisfied +40207,23551,Male,Loyal Customer,25,Business travel,Business,3501,3,3,3,3,5,5,5,5,3,3,5,1,3,5,0,0.0,satisfied +40208,1077,Female,Loyal Customer,55,Personal Travel,Eco,89,5,5,5,3,3,1,1,1,1,5,1,2,1,2,0,0.0,satisfied +40209,104473,Female,disloyal Customer,25,Business travel,Business,1671,4,5,3,3,5,3,5,5,4,5,5,4,4,5,4,10.0,neutral or dissatisfied +40210,26016,Male,Loyal Customer,42,Business travel,Eco,425,4,3,3,3,4,4,4,4,3,5,4,5,4,4,0,0.0,satisfied +40211,42685,Female,Loyal Customer,11,Business travel,Business,627,3,3,2,3,4,4,4,4,3,2,3,4,1,4,0,0.0,satisfied +40212,88600,Male,Loyal Customer,45,Personal Travel,Eco,515,1,5,1,2,2,1,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +40213,70264,Female,Loyal Customer,15,Personal Travel,Business,852,3,5,3,4,5,3,5,5,4,2,5,5,5,5,1,0.0,neutral or dissatisfied +40214,77200,Female,Loyal Customer,57,Business travel,Business,2994,1,1,1,1,4,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +40215,48721,Male,disloyal Customer,22,Business travel,Business,308,4,0,4,2,5,4,5,5,3,3,5,3,5,5,110,126.0,satisfied +40216,120863,Female,Loyal Customer,33,Business travel,Business,920,3,3,3,3,4,5,5,5,5,5,5,4,5,4,1,20.0,satisfied +40217,96507,Female,Loyal Customer,72,Business travel,Business,436,2,3,5,5,1,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +40218,70554,Male,Loyal Customer,23,Business travel,Eco,1258,2,3,3,3,2,2,2,2,2,2,3,3,3,2,0,5.0,neutral or dissatisfied +40219,79404,Male,disloyal Customer,30,Business travel,Eco,502,1,1,1,2,5,1,5,5,3,1,2,4,2,5,0,0.0,neutral or dissatisfied +40220,3774,Female,Loyal Customer,59,Business travel,Business,599,3,3,3,3,5,4,4,4,4,4,4,5,4,5,105,115.0,satisfied +40221,110985,Male,Loyal Customer,47,Business travel,Business,3830,4,5,4,4,4,4,4,4,4,4,4,5,4,4,11,1.0,satisfied +40222,126182,Male,Loyal Customer,45,Business travel,Business,468,1,1,3,3,5,3,2,1,1,1,1,1,1,1,12,17.0,neutral or dissatisfied +40223,93971,Male,Loyal Customer,50,Business travel,Business,1218,3,3,3,3,4,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +40224,61760,Female,Loyal Customer,9,Personal Travel,Eco,1303,2,5,2,5,1,2,1,1,5,2,4,3,4,1,2,0.0,neutral or dissatisfied +40225,29378,Female,Loyal Customer,44,Business travel,Business,2614,2,5,4,4,2,2,2,3,2,4,4,2,2,2,0,35.0,neutral or dissatisfied +40226,104597,Female,Loyal Customer,22,Personal Travel,Eco,369,5,1,5,4,4,5,4,4,4,2,3,1,4,4,4,11.0,satisfied +40227,91826,Female,Loyal Customer,35,Business travel,Business,588,2,5,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +40228,31195,Male,Loyal Customer,27,Business travel,Business,1685,3,3,3,3,5,5,5,5,4,5,5,4,2,5,0,0.0,satisfied +40229,79046,Female,Loyal Customer,41,Business travel,Business,1873,4,1,1,1,1,3,4,4,4,4,4,4,4,2,14,21.0,neutral or dissatisfied +40230,65226,Male,Loyal Customer,58,Business travel,Business,190,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +40231,36929,Male,Loyal Customer,47,Business travel,Eco,867,4,5,5,5,4,4,4,4,1,4,3,2,1,4,0,28.0,satisfied +40232,89474,Female,Loyal Customer,63,Personal Travel,Eco Plus,134,3,0,3,2,4,3,4,4,4,3,4,5,4,5,1,0.0,neutral or dissatisfied +40233,4529,Female,disloyal Customer,23,Business travel,Business,677,5,5,5,1,1,5,1,1,3,4,5,3,4,1,0,0.0,satisfied +40234,1615,Female,Loyal Customer,30,Business travel,Business,3733,3,2,2,2,3,3,3,3,4,2,4,1,3,3,11,16.0,neutral or dissatisfied +40235,113875,Male,Loyal Customer,57,Personal Travel,Eco,1592,2,4,2,3,2,2,2,2,5,2,4,5,4,2,3,0.0,neutral or dissatisfied +40236,56459,Male,Loyal Customer,27,Personal Travel,Eco,719,3,1,3,3,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +40237,108366,Male,Loyal Customer,16,Personal Travel,Eco,1750,4,4,4,2,5,4,5,5,4,1,2,4,1,5,0,0.0,neutral or dissatisfied +40238,59304,Female,Loyal Customer,39,Business travel,Business,2399,2,2,2,2,5,3,4,2,2,2,2,5,2,5,38,18.0,satisfied +40239,66041,Male,Loyal Customer,46,Business travel,Business,3631,2,1,2,2,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +40240,100186,Male,Loyal Customer,38,Personal Travel,Eco,725,1,1,1,4,4,1,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +40241,11135,Female,Loyal Customer,20,Personal Travel,Eco,301,2,5,2,2,2,2,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +40242,15137,Male,Loyal Customer,48,Business travel,Business,1609,2,5,5,5,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +40243,129378,Male,disloyal Customer,46,Business travel,Business,2454,4,4,4,5,4,4,4,4,5,3,3,3,5,4,1,0.0,satisfied +40244,14476,Male,Loyal Customer,8,Business travel,Eco Plus,674,3,3,3,3,3,3,2,3,1,5,4,1,4,3,105,94.0,neutral or dissatisfied +40245,110862,Male,disloyal Customer,35,Business travel,Business,406,2,2,2,3,4,2,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +40246,91733,Male,Loyal Customer,43,Business travel,Business,588,3,3,3,3,2,4,5,3,3,3,3,5,3,3,2,0.0,satisfied +40247,37312,Female,Loyal Customer,29,Business travel,Eco,1069,5,5,5,5,5,5,5,5,3,5,2,5,1,5,134,132.0,satisfied +40248,99110,Female,Loyal Customer,27,Business travel,Eco,237,5,3,3,3,5,4,5,5,4,4,2,5,3,5,0,0.0,satisfied +40249,67855,Female,Loyal Customer,65,Personal Travel,Eco,1235,2,1,2,4,3,2,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +40250,64879,Female,Loyal Customer,54,Business travel,Business,3502,1,1,1,1,5,4,4,4,4,4,4,4,4,3,8,2.0,satisfied +40251,84155,Male,Loyal Customer,45,Business travel,Business,1355,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +40252,120913,Female,Loyal Customer,60,Business travel,Business,993,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +40253,9307,Male,Loyal Customer,44,Business travel,Business,2478,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +40254,99404,Male,Loyal Customer,51,Business travel,Business,1991,3,5,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +40255,121899,Male,Loyal Customer,37,Personal Travel,Eco,337,3,4,3,2,2,3,1,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +40256,61488,Female,Loyal Customer,26,Business travel,Business,2288,3,1,3,3,3,3,3,3,3,1,2,1,3,3,0,2.0,neutral or dissatisfied +40257,38976,Male,Loyal Customer,24,Business travel,Eco,313,5,2,2,2,5,5,3,5,4,5,1,4,3,5,0,0.0,satisfied +40258,29967,Male,disloyal Customer,22,Business travel,Eco,373,3,2,3,3,3,3,3,3,1,4,4,4,3,3,1,13.0,neutral or dissatisfied +40259,40954,Female,Loyal Customer,23,Business travel,Business,3879,2,2,2,2,4,4,4,4,1,4,1,3,2,4,0,0.0,satisfied +40260,36077,Female,Loyal Customer,38,Personal Travel,Eco,413,5,5,5,3,2,5,2,2,5,2,4,4,4,2,0,0.0,satisfied +40261,55335,Female,Loyal Customer,48,Personal Travel,Eco,1117,2,5,3,4,5,5,4,4,4,3,3,3,4,3,29,0.0,neutral or dissatisfied +40262,73257,Male,disloyal Customer,20,Business travel,Eco,675,4,4,4,4,3,4,3,3,4,5,3,1,4,3,0,1.0,neutral or dissatisfied +40263,68792,Male,disloyal Customer,37,Business travel,Eco,526,2,2,2,3,5,2,2,5,4,5,3,3,4,5,0,0.0,neutral or dissatisfied +40264,8386,Female,Loyal Customer,42,Business travel,Business,3982,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,1.0,satisfied +40265,57668,Male,Loyal Customer,59,Business travel,Business,200,2,2,2,2,4,5,4,4,4,4,4,5,4,4,8,0.0,satisfied +40266,78771,Male,Loyal Customer,51,Business travel,Business,2748,2,2,3,2,2,5,4,5,5,5,5,5,5,4,105,110.0,satisfied +40267,127094,Female,disloyal Customer,21,Business travel,Eco,370,0,0,1,5,1,1,1,1,2,4,5,2,3,1,0,0.0,satisfied +40268,61830,Female,Loyal Customer,55,Business travel,Business,1464,4,4,4,4,3,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +40269,23832,Female,Loyal Customer,43,Personal Travel,Eco,1131,3,4,3,4,2,4,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +40270,46414,Male,Loyal Customer,24,Business travel,Business,1883,1,1,1,1,4,4,4,4,4,5,5,5,2,4,0,0.0,satisfied +40271,59571,Male,Loyal Customer,23,Business travel,Business,854,5,5,5,5,5,5,5,5,4,3,4,4,4,5,37,30.0,satisfied +40272,68686,Male,Loyal Customer,24,Business travel,Eco,175,5,4,4,4,5,5,5,5,3,5,4,5,2,5,0,0.0,satisfied +40273,82725,Female,Loyal Customer,50,Business travel,Business,2493,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,1.0,satisfied +40274,112544,Male,disloyal Customer,38,Business travel,Business,862,2,2,2,2,3,2,3,3,5,4,4,3,4,3,11,0.0,neutral or dissatisfied +40275,52833,Female,Loyal Customer,52,Business travel,Eco,1721,4,2,5,5,2,3,2,4,4,4,4,2,4,5,10,0.0,satisfied +40276,67967,Female,Loyal Customer,39,Business travel,Business,1438,4,1,4,4,3,5,4,5,5,5,5,4,5,5,19,24.0,satisfied +40277,6967,Male,Loyal Customer,34,Business travel,Business,3604,2,2,4,2,5,5,5,4,4,4,4,5,4,5,86,85.0,satisfied +40278,63724,Male,Loyal Customer,18,Business travel,Business,1660,3,4,4,4,3,3,3,3,1,2,3,3,3,3,277,268.0,neutral or dissatisfied +40279,22561,Female,Loyal Customer,10,Personal Travel,Business,300,2,2,2,3,4,2,4,4,3,5,3,4,3,4,44,59.0,neutral or dissatisfied +40280,57931,Female,Loyal Customer,17,Personal Travel,Eco Plus,305,2,2,2,3,4,2,4,4,3,4,3,3,2,4,0,0.0,neutral or dissatisfied +40281,17117,Female,disloyal Customer,34,Business travel,Eco,821,3,3,3,3,4,3,4,4,4,2,3,1,2,4,0,0.0,neutral or dissatisfied +40282,73374,Male,disloyal Customer,28,Business travel,Eco,1197,4,4,4,4,4,4,4,4,2,5,3,4,3,4,3,0.0,neutral or dissatisfied +40283,94272,Female,Loyal Customer,57,Business travel,Business,2344,0,4,0,4,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +40284,42652,Male,Loyal Customer,78,Business travel,Eco Plus,386,5,3,5,3,5,5,5,5,2,3,3,1,1,5,0,0.0,satisfied +40285,49117,Female,Loyal Customer,38,Business travel,Business,89,5,1,5,5,5,4,3,4,4,4,5,1,4,5,0,0.0,satisfied +40286,86646,Male,Loyal Customer,61,Business travel,Eco,346,4,4,4,4,4,4,4,4,2,3,4,4,4,4,0,0.0,satisfied +40287,49069,Female,Loyal Customer,23,Business travel,Eco,373,4,2,2,2,4,4,3,4,5,1,4,5,3,4,33,28.0,satisfied +40288,63349,Male,disloyal Customer,44,Business travel,Eco,447,2,2,2,3,3,2,3,3,1,3,3,4,4,3,31,24.0,neutral or dissatisfied +40289,20681,Male,Loyal Customer,65,Personal Travel,Eco,522,3,4,3,3,5,3,5,5,4,4,1,3,1,5,20,27.0,neutral or dissatisfied +40290,816,Female,Loyal Customer,48,Business travel,Business,2658,0,0,0,1,3,4,5,2,2,5,5,5,2,5,0,0.0,satisfied +40291,112141,Female,Loyal Customer,50,Business travel,Business,1795,1,1,1,1,3,4,4,3,3,3,3,4,3,3,45,41.0,satisfied +40292,101992,Male,Loyal Customer,57,Personal Travel,Eco,628,2,5,2,3,5,2,5,5,3,5,4,5,4,5,6,6.0,neutral or dissatisfied +40293,60169,Female,Loyal Customer,48,Personal Travel,Eco,1182,1,4,1,1,4,4,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +40294,111633,Male,disloyal Customer,27,Business travel,Business,1290,5,5,5,3,3,5,2,3,5,4,5,5,5,3,3,0.0,satisfied +40295,100755,Male,Loyal Customer,19,Personal Travel,Eco,328,3,0,3,4,1,3,1,1,1,4,4,3,4,1,12,1.0,neutral or dissatisfied +40296,76577,Female,Loyal Customer,43,Business travel,Eco,516,3,4,4,4,4,3,4,3,3,3,3,4,3,2,0,6.0,neutral or dissatisfied +40297,50317,Female,Loyal Customer,61,Business travel,Business,207,1,1,1,1,3,2,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +40298,17225,Female,Loyal Customer,60,Business travel,Eco,872,5,2,2,2,1,2,4,5,5,5,5,2,5,5,0,0.0,satisfied +40299,35201,Female,Loyal Customer,63,Business travel,Business,2015,1,1,2,1,3,3,1,5,5,5,5,1,5,2,0,2.0,satisfied +40300,24655,Male,disloyal Customer,29,Business travel,Eco,834,3,3,3,1,3,3,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +40301,36427,Female,Loyal Customer,15,Business travel,Eco,369,0,4,0,3,2,0,2,2,2,3,5,2,5,2,0,0.0,satisfied +40302,101893,Female,Loyal Customer,29,Business travel,Business,2039,1,1,1,1,5,5,5,5,4,5,5,4,5,5,5,0.0,satisfied +40303,77105,Male,Loyal Customer,55,Business travel,Business,1481,3,3,3,3,1,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +40304,30604,Female,Loyal Customer,33,Business travel,Business,472,4,3,3,3,5,3,3,4,4,4,4,4,4,4,29,29.0,neutral or dissatisfied +40305,96303,Male,Loyal Customer,41,Business travel,Business,3101,5,5,5,5,5,4,4,4,4,4,4,5,4,4,0,1.0,satisfied +40306,17644,Female,Loyal Customer,48,Business travel,Eco,1008,5,5,5,5,4,5,3,5,5,5,5,2,5,1,0,0.0,satisfied +40307,4880,Female,Loyal Customer,8,Personal Travel,Eco,408,4,3,4,4,4,4,4,4,3,4,3,2,4,4,0,8.0,neutral or dissatisfied +40308,95404,Male,Loyal Customer,9,Personal Travel,Eco,239,4,2,4,4,2,4,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +40309,30488,Male,Loyal Customer,24,Business travel,Eco,516,2,1,3,1,2,2,4,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +40310,104167,Female,Loyal Customer,32,Business travel,Business,1615,4,2,2,2,4,3,4,4,4,5,4,2,3,4,0,0.0,neutral or dissatisfied +40311,25715,Female,Loyal Customer,60,Business travel,Eco,447,5,5,5,5,5,4,1,5,5,5,5,1,5,2,1,0.0,satisfied +40312,69487,Male,Loyal Customer,22,Business travel,Eco Plus,944,1,4,4,4,1,1,2,1,2,2,4,3,4,1,11,10.0,neutral or dissatisfied +40313,27119,Female,disloyal Customer,26,Business travel,Eco,936,2,2,2,3,2,5,5,1,2,5,5,5,1,5,0,23.0,neutral or dissatisfied +40314,126618,Female,Loyal Customer,26,Business travel,Business,3033,4,4,4,4,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +40315,97352,Male,Loyal Customer,50,Business travel,Eco,472,2,3,5,5,3,2,3,3,4,1,4,4,3,3,14,10.0,neutral or dissatisfied +40316,87400,Female,Loyal Customer,49,Personal Travel,Eco,425,5,3,5,3,3,3,3,5,5,5,5,1,5,3,8,1.0,satisfied +40317,53646,Female,Loyal Customer,20,Personal Travel,Eco,1874,4,4,3,4,3,3,3,3,1,3,3,4,4,3,93,95.0,neutral or dissatisfied +40318,12229,Male,Loyal Customer,64,Personal Travel,Business,192,2,4,2,3,3,4,5,3,3,2,3,5,3,3,0,2.0,neutral or dissatisfied +40319,84508,Female,Loyal Customer,46,Business travel,Business,2556,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +40320,6932,Male,Loyal Customer,54,Business travel,Business,501,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,1.0,satisfied +40321,56211,Male,disloyal Customer,15,Business travel,Eco,1127,3,3,3,5,3,3,4,3,4,5,4,5,5,3,16,21.0,neutral or dissatisfied +40322,128415,Male,Loyal Customer,49,Business travel,Business,3587,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +40323,11335,Female,Loyal Customer,14,Personal Travel,Eco,295,2,4,2,3,2,2,1,2,5,3,4,3,5,2,0,1.0,neutral or dissatisfied +40324,76982,Female,disloyal Customer,27,Business travel,Business,422,1,1,1,3,3,1,3,3,3,3,5,3,5,3,0,7.0,neutral or dissatisfied +40325,17238,Female,disloyal Customer,23,Business travel,Eco,872,2,2,2,4,3,2,3,3,2,2,3,1,3,3,89,105.0,neutral or dissatisfied +40326,47675,Male,Loyal Customer,32,Personal Travel,Eco,1242,1,4,1,3,4,1,4,4,3,4,4,3,5,4,19,0.0,neutral or dissatisfied +40327,59961,Male,Loyal Customer,58,Business travel,Business,997,2,2,2,2,2,5,4,5,5,5,5,3,5,5,7,5.0,satisfied +40328,58990,Male,Loyal Customer,53,Business travel,Business,1744,4,4,4,4,3,3,4,5,5,5,5,4,5,4,7,0.0,satisfied +40329,11333,Female,Loyal Customer,31,Personal Travel,Eco,74,3,4,3,4,3,3,3,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +40330,11676,Female,Loyal Customer,53,Business travel,Business,395,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +40331,58602,Male,Loyal Customer,33,Personal Travel,Eco,334,3,4,3,1,3,3,3,3,3,5,4,4,5,3,5,0.0,neutral or dissatisfied +40332,1454,Male,Loyal Customer,53,Business travel,Business,3868,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +40333,2913,Male,Loyal Customer,53,Business travel,Eco Plus,409,2,5,5,5,2,2,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +40334,61821,Male,Loyal Customer,26,Personal Travel,Eco,1635,3,4,3,3,5,3,3,5,4,4,4,4,4,5,9,12.0,neutral or dissatisfied +40335,100590,Female,Loyal Customer,55,Personal Travel,Eco,486,2,4,2,3,5,5,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +40336,122310,Male,Loyal Customer,25,Business travel,Eco Plus,541,2,2,2,2,2,1,3,2,4,4,2,2,3,2,0,0.0,neutral or dissatisfied +40337,69229,Male,Loyal Customer,58,Business travel,Business,3952,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +40338,65335,Female,disloyal Customer,37,Business travel,Business,432,4,4,4,4,1,4,1,1,4,5,4,3,4,1,19,22.0,satisfied +40339,58469,Male,Loyal Customer,36,Business travel,Business,2862,2,2,2,2,2,5,5,5,5,5,5,3,5,4,2,0.0,satisfied +40340,101017,Male,Loyal Customer,43,Business travel,Business,467,1,1,1,1,5,5,4,5,5,5,5,5,5,3,10,0.0,satisfied +40341,11388,Female,disloyal Customer,24,Business travel,Business,429,5,3,5,5,2,5,2,2,5,5,5,3,4,2,0,0.0,satisfied +40342,107221,Male,Loyal Customer,40,Business travel,Business,1751,2,2,2,2,2,3,5,5,5,5,5,4,5,4,12,17.0,satisfied +40343,109437,Female,disloyal Customer,42,Business travel,Business,861,5,4,4,5,5,5,5,5,5,5,5,5,3,5,158,,satisfied +40344,2735,Female,Loyal Customer,41,Business travel,Business,772,1,1,1,1,5,5,4,5,5,5,5,3,5,4,36,13.0,satisfied +40345,76234,Male,Loyal Customer,39,Business travel,Eco,1175,3,2,2,2,3,3,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +40346,8819,Male,Loyal Customer,16,Personal Travel,Eco,552,4,5,5,3,2,5,2,2,5,4,4,4,3,2,0,0.0,neutral or dissatisfied +40347,120025,Male,Loyal Customer,68,Personal Travel,Eco,328,3,4,3,4,1,3,1,1,1,2,4,2,4,1,0,0.0,neutral or dissatisfied +40348,105387,Male,Loyal Customer,45,Business travel,Business,369,1,0,0,3,3,3,3,3,3,0,3,4,3,3,0,0.0,neutral or dissatisfied +40349,19209,Female,disloyal Customer,42,Business travel,Eco,459,3,0,3,2,4,3,4,4,3,5,2,4,4,4,0,5.0,neutral or dissatisfied +40350,63262,Male,Loyal Customer,59,Business travel,Business,2521,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +40351,37607,Female,Loyal Customer,53,Personal Travel,Eco,1074,1,4,2,5,4,4,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +40352,93619,Female,Loyal Customer,47,Business travel,Eco,577,2,3,3,3,5,2,3,2,2,2,2,1,2,2,9,11.0,neutral or dissatisfied +40353,101617,Male,disloyal Customer,47,Business travel,Eco,739,5,5,5,3,2,5,2,2,3,2,3,5,4,2,0,0.0,satisfied +40354,68555,Female,Loyal Customer,51,Personal Travel,Business,2136,2,4,2,1,3,5,5,5,5,2,5,4,5,3,81,45.0,neutral or dissatisfied +40355,45907,Male,disloyal Customer,27,Business travel,Eco,913,2,2,2,3,4,2,4,4,4,2,3,1,4,4,33,15.0,neutral or dissatisfied +40356,60096,Male,Loyal Customer,59,Business travel,Business,3231,3,3,3,3,3,5,4,4,4,4,4,5,4,5,0,5.0,satisfied +40357,79091,Male,Loyal Customer,56,Personal Travel,Eco,356,2,5,2,2,1,2,1,1,5,3,4,5,4,1,0,9.0,neutral or dissatisfied +40358,46411,Male,Loyal Customer,23,Business travel,Business,649,5,5,5,5,3,2,3,3,4,4,5,2,4,3,5,19.0,satisfied +40359,67431,Female,disloyal Customer,22,Business travel,Business,641,4,0,4,3,2,4,4,2,5,3,4,5,5,2,0,0.0,satisfied +40360,50612,Male,Loyal Customer,40,Personal Travel,Eco,266,1,4,1,4,2,1,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +40361,53195,Male,Loyal Customer,35,Business travel,Eco,589,3,2,2,2,2,3,3,1,4,1,1,3,4,3,202,203.0,neutral or dissatisfied +40362,30909,Male,Loyal Customer,29,Business travel,Eco,896,5,1,1,1,5,4,5,5,1,3,2,3,4,5,4,0.0,satisfied +40363,123003,Male,Loyal Customer,28,Business travel,Business,2379,5,5,5,5,4,4,4,4,3,2,5,5,4,4,0,11.0,satisfied +40364,111107,Male,Loyal Customer,7,Personal Travel,Eco Plus,197,4,4,4,4,4,4,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +40365,72097,Female,Loyal Customer,70,Personal Travel,Eco,2486,4,1,4,2,1,2,2,5,5,4,5,2,5,2,3,2.0,satisfied +40366,17406,Female,Loyal Customer,55,Business travel,Business,376,5,5,5,5,2,2,5,5,5,5,5,5,5,4,0,0.0,satisfied +40367,98591,Male,disloyal Customer,17,Business travel,Business,834,0,0,0,3,5,0,5,5,4,3,5,4,5,5,0,21.0,satisfied +40368,4212,Male,Loyal Customer,62,Personal Travel,Eco,888,5,5,5,1,5,5,5,5,2,5,1,3,4,5,38,54.0,satisfied +40369,73369,Male,disloyal Customer,57,Business travel,Business,1144,4,4,4,4,1,4,1,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +40370,5580,Female,Loyal Customer,50,Business travel,Business,2716,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +40371,115177,Male,disloyal Customer,39,Business travel,Business,417,3,3,3,1,4,3,4,4,5,5,5,5,5,4,8,4.0,neutral or dissatisfied +40372,40971,Female,Loyal Customer,55,Personal Travel,Eco,601,5,5,5,1,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +40373,48643,Female,Loyal Customer,45,Business travel,Business,1696,0,0,0,5,2,5,4,5,5,5,5,5,5,3,28,26.0,satisfied +40374,8693,Male,Loyal Customer,47,Business travel,Business,181,3,1,1,1,3,4,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +40375,65831,Male,disloyal Customer,36,Business travel,Eco,1391,3,3,3,4,1,3,1,1,4,3,4,4,3,1,4,0.0,neutral or dissatisfied +40376,30180,Male,Loyal Customer,39,Business travel,Eco Plus,82,5,5,5,5,5,5,5,5,3,1,3,2,3,5,0,0.0,satisfied +40377,57017,Male,Loyal Customer,40,Personal Travel,Eco,2454,2,2,2,3,2,1,5,3,4,3,3,5,3,5,23,59.0,neutral or dissatisfied +40378,59653,Male,Loyal Customer,68,Personal Travel,Eco,854,0,5,0,1,3,0,3,3,3,2,5,5,5,3,4,0.0,satisfied +40379,112703,Male,disloyal Customer,26,Business travel,Business,723,3,3,3,2,5,3,5,5,3,5,4,5,5,5,8,0.0,neutral or dissatisfied +40380,28950,Male,Loyal Customer,44,Business travel,Business,672,4,4,4,4,1,3,4,4,4,4,4,2,4,2,14,16.0,neutral or dissatisfied +40381,71462,Female,Loyal Customer,19,Personal Travel,Eco,867,3,4,3,3,2,3,2,2,4,3,5,1,5,2,0,0.0,neutral or dissatisfied +40382,116640,Female,Loyal Customer,51,Business travel,Business,2157,4,4,4,4,2,4,4,4,4,4,4,5,4,3,28,18.0,satisfied +40383,40913,Female,Loyal Customer,21,Personal Travel,Eco,558,3,5,3,5,2,3,2,2,5,2,5,5,5,2,0,7.0,neutral or dissatisfied +40384,49271,Male,Loyal Customer,39,Business travel,Business,1970,1,1,1,1,3,3,5,5,5,5,5,3,5,5,82,82.0,satisfied +40385,70858,Male,disloyal Customer,30,Business travel,Eco,761,3,4,4,3,1,4,1,1,2,5,4,4,3,1,0,0.0,neutral or dissatisfied +40386,39314,Female,Loyal Customer,17,Personal Travel,Eco,67,1,5,1,4,2,1,2,2,4,4,4,4,4,2,3,11.0,neutral or dissatisfied +40387,40366,Male,Loyal Customer,24,Business travel,Eco,1250,1,4,1,4,1,1,5,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +40388,64810,Male,Loyal Customer,56,Business travel,Business,469,5,5,5,5,3,4,5,4,4,4,4,4,4,4,2,0.0,satisfied +40389,26982,Male,disloyal Customer,48,Business travel,Eco,867,1,1,1,3,3,1,1,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +40390,60602,Male,disloyal Customer,24,Business travel,Business,991,4,5,4,4,2,4,2,2,4,5,4,5,5,2,49,41.0,satisfied +40391,114883,Male,Loyal Customer,24,Business travel,Business,1904,1,1,1,1,5,5,5,5,3,5,4,5,5,5,0,1.0,satisfied +40392,41753,Female,Loyal Customer,70,Personal Travel,Eco,456,3,4,3,1,2,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +40393,92671,Male,Loyal Customer,37,Business travel,Business,3147,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +40394,61537,Female,Loyal Customer,29,Personal Travel,Eco,2253,3,4,3,3,2,3,5,2,3,4,4,3,5,2,12,0.0,neutral or dissatisfied +40395,13522,Male,Loyal Customer,48,Business travel,Business,3592,4,1,4,4,1,5,4,5,5,5,5,5,5,2,70,76.0,satisfied +40396,89369,Female,Loyal Customer,37,Business travel,Business,3588,0,4,0,4,5,4,4,3,3,3,3,5,3,3,8,3.0,satisfied +40397,42672,Female,Loyal Customer,58,Business travel,Eco,627,5,3,3,3,5,2,1,5,5,5,5,3,5,2,0,0.0,satisfied +40398,8617,Female,Loyal Customer,57,Personal Travel,Eco Plus,1371,4,3,4,4,4,4,4,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +40399,29550,Female,Loyal Customer,33,Business travel,Business,1448,2,2,2,2,5,1,3,4,4,4,4,2,4,1,1,0.0,satisfied +40400,53102,Female,disloyal Customer,25,Business travel,Eco,1129,2,2,2,3,1,2,1,1,1,3,3,1,3,1,29,30.0,neutral or dissatisfied +40401,14976,Female,Loyal Customer,31,Business travel,Business,1020,3,3,3,3,5,5,5,5,2,5,2,4,4,5,10,15.0,satisfied +40402,60909,Male,Loyal Customer,15,Personal Travel,Eco,589,2,4,2,4,3,2,3,3,4,5,5,4,5,3,0,4.0,neutral or dissatisfied +40403,39546,Male,Loyal Customer,43,Business travel,Business,2063,4,4,4,4,1,3,1,4,4,4,4,4,4,1,0,0.0,satisfied +40404,107689,Female,disloyal Customer,23,Business travel,Eco,251,4,0,4,1,1,4,1,1,3,5,5,3,4,1,33,29.0,satisfied +40405,46244,Male,Loyal Customer,59,Business travel,Eco,594,2,5,2,5,2,2,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +40406,107946,Female,Loyal Customer,67,Personal Travel,Eco,611,3,3,2,3,2,3,2,4,4,2,5,5,4,1,21,34.0,neutral or dissatisfied +40407,31803,Female,disloyal Customer,23,Business travel,Eco,891,1,1,1,3,1,5,5,1,5,2,3,5,3,5,0,0.0,neutral or dissatisfied +40408,116224,Female,Loyal Customer,43,Personal Travel,Eco,358,3,5,3,5,5,4,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +40409,7674,Female,Loyal Customer,35,Business travel,Eco,604,3,1,2,2,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +40410,90653,Male,Loyal Customer,51,Business travel,Business,404,5,5,5,5,2,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +40411,129032,Female,Loyal Customer,58,Business travel,Business,1846,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +40412,44310,Male,disloyal Customer,20,Business travel,Eco,305,4,0,4,1,4,4,4,4,2,2,4,3,2,4,0,0.0,neutral or dissatisfied +40413,122449,Female,Loyal Customer,55,Business travel,Business,2374,1,1,1,1,5,4,5,3,3,4,3,5,3,4,24,27.0,satisfied +40414,16491,Male,disloyal Customer,22,Business travel,Eco,246,2,3,2,3,3,2,1,3,3,4,3,4,3,3,49,92.0,neutral or dissatisfied +40415,22514,Female,Loyal Customer,24,Business travel,Eco Plus,143,0,5,0,4,1,0,1,1,5,2,5,4,3,1,0,0.0,satisfied +40416,94301,Female,disloyal Customer,28,Business travel,Business,293,2,2,2,3,5,2,5,5,4,2,4,3,5,5,4,0.0,neutral or dissatisfied +40417,103887,Female,Loyal Customer,68,Personal Travel,Eco,1072,4,5,4,3,4,5,5,4,4,4,4,3,4,4,18,0.0,neutral or dissatisfied +40418,105659,Male,Loyal Customer,51,Business travel,Business,1565,3,1,3,3,2,4,4,2,2,2,2,3,2,3,22,39.0,satisfied +40419,112549,Female,Loyal Customer,33,Business travel,Eco Plus,846,1,5,5,5,1,2,1,1,4,5,3,4,4,1,12,8.0,neutral or dissatisfied +40420,116377,Female,Loyal Customer,55,Personal Travel,Eco,342,3,4,3,1,2,4,5,3,3,3,3,5,3,3,11,4.0,neutral or dissatisfied +40421,55605,Female,Loyal Customer,55,Business travel,Business,2104,3,2,2,2,5,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +40422,44493,Female,disloyal Customer,49,Business travel,Eco,261,3,5,3,2,5,3,5,5,2,1,5,2,1,5,0,,neutral or dissatisfied +40423,1870,Male,Loyal Customer,30,Business travel,Business,3779,1,5,5,5,1,1,1,1,1,4,3,2,4,1,4,18.0,neutral or dissatisfied +40424,89917,Female,Loyal Customer,30,Business travel,Business,1501,1,5,5,5,1,1,1,1,1,1,1,1,2,1,0,0.0,neutral or dissatisfied +40425,42346,Male,Loyal Customer,32,Personal Travel,Eco,329,5,5,5,3,3,5,3,3,2,4,1,3,4,3,0,0.0,satisfied +40426,37679,Female,Loyal Customer,7,Personal Travel,Eco,1028,1,4,1,2,2,1,3,2,3,2,4,5,4,2,5,1.0,neutral or dissatisfied +40427,72444,Female,disloyal Customer,28,Business travel,Business,1121,0,0,0,3,4,0,4,4,3,2,5,3,4,4,0,0.0,satisfied +40428,49547,Female,Loyal Customer,44,Business travel,Eco,250,5,1,1,1,1,1,5,5,5,5,5,1,5,2,48,38.0,satisfied +40429,6660,Male,Loyal Customer,61,Personal Travel,Business,438,1,5,1,5,3,5,5,1,1,1,1,5,1,3,6,79.0,neutral or dissatisfied +40430,95240,Female,Loyal Customer,18,Personal Travel,Eco,239,1,3,1,2,1,1,1,1,4,2,1,3,1,1,0,0.0,neutral or dissatisfied +40431,12300,Male,Loyal Customer,44,Business travel,Eco,192,4,3,3,3,4,4,4,4,1,1,3,1,2,4,13,6.0,satisfied +40432,69473,Female,Loyal Customer,69,Personal Travel,Eco,1096,1,4,1,4,2,2,3,3,3,1,1,1,3,2,88,93.0,neutral or dissatisfied +40433,54531,Male,Loyal Customer,26,Personal Travel,Eco,925,3,3,3,3,5,3,5,5,1,5,3,2,3,5,15,0.0,neutral or dissatisfied +40434,65429,Female,Loyal Customer,41,Personal Travel,Eco,2165,1,4,1,4,1,1,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +40435,97817,Male,Loyal Customer,55,Business travel,Business,2747,5,5,5,5,3,5,5,5,5,5,5,4,5,3,95,97.0,satisfied +40436,100256,Female,disloyal Customer,22,Business travel,Business,1165,5,0,5,1,2,5,2,2,3,5,4,3,5,2,53,37.0,satisfied +40437,84733,Female,Loyal Customer,25,Business travel,Business,3924,4,5,4,4,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +40438,90809,Female,Loyal Customer,50,Business travel,Eco,646,2,3,3,3,5,4,3,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +40439,88573,Male,Loyal Customer,57,Personal Travel,Eco,250,2,5,2,5,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +40440,60347,Female,Loyal Customer,59,Personal Travel,Eco,1024,4,5,4,3,1,5,5,3,3,4,5,2,3,2,0,0.0,satisfied +40441,83083,Female,Loyal Customer,60,Business travel,Business,1557,1,4,4,4,4,3,4,1,1,1,1,2,1,3,0,8.0,neutral or dissatisfied +40442,98510,Female,Loyal Customer,36,Business travel,Business,402,2,3,4,4,2,2,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +40443,126757,Female,Loyal Customer,49,Personal Travel,Eco,2402,3,5,2,3,4,3,2,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +40444,14195,Female,disloyal Customer,45,Business travel,Eco,620,4,2,4,4,2,4,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +40445,113234,Female,Loyal Customer,38,Business travel,Business,3896,2,4,4,4,3,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +40446,6861,Male,disloyal Customer,23,Business travel,Eco,622,5,0,5,3,5,5,5,5,3,2,4,3,5,5,1,0.0,satisfied +40447,33620,Male,Loyal Customer,30,Business travel,Business,399,2,2,2,2,2,2,2,2,2,1,4,1,4,2,37,37.0,neutral or dissatisfied +40448,101120,Female,disloyal Customer,21,Business travel,Eco,1069,3,3,3,4,4,3,4,4,3,3,4,4,5,4,30,20.0,neutral or dissatisfied +40449,94326,Female,Loyal Customer,49,Business travel,Business,2135,1,1,4,1,4,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +40450,10128,Male,Loyal Customer,22,Business travel,Business,946,2,1,1,1,2,2,2,2,2,2,3,1,3,2,0,3.0,neutral or dissatisfied +40451,129466,Female,disloyal Customer,25,Business travel,Business,2611,2,5,2,3,3,2,3,3,4,2,5,5,4,3,3,0.0,neutral or dissatisfied +40452,1674,Female,Loyal Customer,51,Business travel,Business,561,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,10.0,satisfied +40453,124269,Male,Loyal Customer,40,Business travel,Business,1639,4,4,4,4,2,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +40454,69898,Male,Loyal Customer,59,Business travel,Business,1514,3,3,3,3,5,4,4,5,5,5,5,3,5,5,104,91.0,satisfied +40455,53972,Male,Loyal Customer,63,Personal Travel,Eco,1117,1,4,1,4,3,1,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +40456,119425,Female,Loyal Customer,51,Personal Travel,Eco,399,3,5,3,3,4,5,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +40457,58876,Female,disloyal Customer,42,Business travel,Business,888,2,2,2,1,5,2,5,5,3,4,5,4,5,5,62,52.0,neutral or dissatisfied +40458,75393,Female,Loyal Customer,59,Business travel,Business,2218,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +40459,16128,Female,Loyal Customer,21,Personal Travel,Eco,725,3,4,3,4,3,3,3,3,3,5,3,1,4,3,39,48.0,neutral or dissatisfied +40460,65546,Male,Loyal Customer,62,Personal Travel,Business,175,2,5,2,2,4,5,4,3,3,2,3,3,3,4,2,14.0,neutral or dissatisfied +40461,103960,Female,Loyal Customer,37,Personal Travel,Eco,533,1,5,1,2,1,1,1,1,5,5,5,3,5,1,21,5.0,neutral or dissatisfied +40462,77367,Female,Loyal Customer,67,Business travel,Eco,588,2,5,5,5,2,2,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +40463,114710,Female,Loyal Customer,39,Business travel,Business,2191,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,3.0,satisfied +40464,75772,Female,Loyal Customer,12,Personal Travel,Eco,813,1,1,1,3,4,1,2,4,4,5,2,2,4,4,0,0.0,neutral or dissatisfied +40465,80934,Male,Loyal Customer,25,Personal Travel,Eco,341,2,4,2,1,4,2,3,4,3,5,5,5,4,4,27,27.0,neutral or dissatisfied +40466,123223,Male,Loyal Customer,45,Personal Travel,Eco,590,3,5,3,1,5,3,5,5,5,5,4,4,4,5,25,12.0,neutral or dissatisfied +40467,127229,Female,Loyal Customer,35,Business travel,Business,1460,3,2,2,2,5,3,3,3,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +40468,101397,Male,Loyal Customer,53,Business travel,Eco,486,1,4,4,4,1,1,1,1,2,3,3,2,3,1,0,0.0,neutral or dissatisfied +40469,48413,Female,Loyal Customer,55,Personal Travel,Business,909,4,4,4,1,1,4,2,3,3,4,4,2,3,4,35,37.0,neutral or dissatisfied +40470,81266,Male,disloyal Customer,27,Business travel,Business,1020,2,1,1,5,3,1,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +40471,101835,Female,Loyal Customer,63,Personal Travel,Eco,1521,3,4,3,3,3,4,5,4,4,3,3,5,4,3,73,51.0,neutral or dissatisfied +40472,59850,Female,Loyal Customer,53,Business travel,Business,3423,4,4,4,4,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +40473,57841,Male,disloyal Customer,36,Business travel,Business,1091,3,2,2,3,2,2,2,2,2,3,3,4,3,2,0,0.0,neutral or dissatisfied +40474,102031,Female,disloyal Customer,36,Business travel,Business,236,4,4,4,2,4,4,4,4,5,4,4,4,5,4,7,0.0,neutral or dissatisfied +40475,111424,Female,Loyal Customer,33,Business travel,Business,896,2,2,2,2,5,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +40476,42200,Male,disloyal Customer,37,Business travel,Eco,329,3,5,3,3,5,3,2,5,2,3,2,5,4,5,5,0.0,neutral or dissatisfied +40477,65467,Female,Loyal Customer,42,Business travel,Business,3764,1,1,1,1,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +40478,83292,Male,Loyal Customer,50,Personal Travel,Eco,1979,3,4,3,4,2,3,5,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +40479,126537,Female,Loyal Customer,45,Business travel,Business,1971,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +40480,129110,Male,Loyal Customer,41,Personal Travel,Eco,2342,5,3,5,5,5,1,1,3,2,3,3,1,4,1,1,3.0,satisfied +40481,8215,Female,Loyal Customer,42,Business travel,Business,335,3,3,3,3,3,1,1,4,4,4,4,5,4,3,0,0.0,satisfied +40482,68364,Male,Loyal Customer,48,Personal Travel,Eco,2072,3,4,3,5,3,3,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +40483,6089,Male,disloyal Customer,20,Business travel,Eco,272,4,4,4,2,5,4,5,5,1,3,5,3,4,5,16,31.0,satisfied +40484,115346,Male,Loyal Customer,43,Business travel,Business,2891,1,1,1,1,5,5,5,5,5,5,5,5,5,5,45,38.0,satisfied +40485,80077,Female,disloyal Customer,25,Business travel,Business,1069,2,4,2,5,5,2,5,5,3,2,4,4,5,5,16,0.0,neutral or dissatisfied +40486,57541,Female,Loyal Customer,53,Personal Travel,Eco,413,3,5,3,4,5,5,5,5,5,3,5,3,5,5,9,11.0,neutral or dissatisfied +40487,85768,Female,Loyal Customer,20,Business travel,Business,526,3,3,3,3,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +40488,84017,Female,Loyal Customer,57,Personal Travel,Eco,321,4,5,5,4,4,2,4,2,2,5,2,3,2,5,0,0.0,neutral or dissatisfied +40489,65235,Male,Loyal Customer,56,Business travel,Business,3100,4,4,4,4,5,5,4,5,5,4,4,5,5,3,0,0.0,satisfied +40490,128286,Female,Loyal Customer,48,Business travel,Business,1630,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +40491,58843,Male,Loyal Customer,22,Business travel,Business,783,3,3,3,3,5,4,5,5,4,3,5,3,5,5,2,0.0,satisfied +40492,126199,Male,Loyal Customer,45,Business travel,Eco,631,2,4,4,4,2,2,2,2,1,5,3,2,2,2,68,47.0,neutral or dissatisfied +40493,87720,Female,Loyal Customer,36,Business travel,Eco Plus,606,2,3,3,3,2,2,2,2,2,1,2,2,3,2,0,4.0,neutral or dissatisfied +40494,27918,Male,disloyal Customer,35,Business travel,Eco,689,2,2,2,3,2,2,2,2,5,2,2,4,1,2,0,4.0,neutral or dissatisfied +40495,126990,Female,Loyal Customer,50,Business travel,Business,646,5,5,5,5,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +40496,13508,Female,Loyal Customer,46,Business travel,Eco,227,3,3,3,3,5,5,2,3,3,3,3,5,3,2,0,14.0,satisfied +40497,10340,Male,disloyal Customer,37,Business travel,Business,201,4,4,4,1,4,4,1,4,4,4,4,4,5,4,9,1.0,satisfied +40498,76489,Male,Loyal Customer,48,Business travel,Business,547,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +40499,64462,Female,disloyal Customer,37,Business travel,Eco Plus,989,2,2,2,3,5,2,2,5,4,5,3,2,3,5,0,0.0,neutral or dissatisfied +40500,103451,Female,Loyal Customer,62,Business travel,Business,3408,2,1,1,1,4,2,3,2,2,2,2,4,2,2,35,30.0,neutral or dissatisfied +40501,128792,Male,Loyal Customer,46,Personal Travel,Business,2475,1,5,1,3,1,3,3,4,2,4,5,3,5,3,0,4.0,neutral or dissatisfied +40502,5233,Male,Loyal Customer,41,Business travel,Eco,295,3,5,5,5,3,3,3,3,4,3,1,4,2,3,7,13.0,neutral or dissatisfied +40503,51046,Female,Loyal Customer,15,Personal Travel,Eco,78,3,1,3,3,4,3,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +40504,50658,Male,Loyal Customer,20,Personal Travel,Eco,250,3,5,0,2,4,0,4,4,4,2,4,1,4,4,40,39.0,neutral or dissatisfied +40505,4786,Male,Loyal Customer,65,Business travel,Business,258,1,4,4,4,5,4,3,1,1,1,1,3,1,3,64,60.0,neutral or dissatisfied +40506,15874,Male,Loyal Customer,37,Business travel,Eco,332,2,3,4,3,2,2,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +40507,121408,Male,Loyal Customer,42,Business travel,Business,331,0,0,0,1,3,5,4,2,2,3,3,3,2,5,0,0.0,satisfied +40508,4871,Female,Loyal Customer,24,Personal Travel,Eco,408,1,4,1,2,3,1,3,3,2,3,5,5,2,3,0,0.0,neutral or dissatisfied +40509,96485,Male,Loyal Customer,37,Business travel,Business,436,4,2,2,2,2,3,4,4,4,4,4,4,4,2,48,44.0,neutral or dissatisfied +40510,65592,Female,disloyal Customer,39,Business travel,Business,175,2,2,2,4,5,2,1,5,4,5,4,2,4,5,14,10.0,neutral or dissatisfied +40511,72481,Female,Loyal Customer,36,Business travel,Business,3657,2,3,5,3,1,4,4,2,2,2,2,3,2,2,32,28.0,neutral or dissatisfied +40512,84577,Male,disloyal Customer,38,Business travel,Eco,1257,4,4,4,3,1,4,2,1,1,5,3,4,4,1,1,5.0,neutral or dissatisfied +40513,5536,Male,Loyal Customer,33,Personal Travel,Eco,404,4,5,4,4,5,4,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +40514,117127,Male,Loyal Customer,55,Personal Travel,Eco,370,4,5,4,3,4,4,2,4,5,4,2,2,4,4,7,0.0,satisfied +40515,339,Female,Loyal Customer,22,Personal Travel,Eco,853,2,2,3,2,2,3,2,2,2,4,2,4,3,2,0,0.0,neutral or dissatisfied +40516,64065,Female,Loyal Customer,41,Business travel,Eco,919,3,5,5,5,3,3,3,3,2,3,4,2,4,3,0,17.0,neutral or dissatisfied +40517,123203,Female,Loyal Customer,23,Personal Travel,Eco,631,2,3,2,2,3,2,3,3,5,4,5,2,2,3,0,0.0,neutral or dissatisfied +40518,32780,Female,Loyal Customer,64,Business travel,Business,3707,1,1,1,1,4,5,4,4,4,4,3,2,4,1,0,0.0,satisfied +40519,12889,Female,Loyal Customer,22,Business travel,Business,563,3,3,3,3,4,4,4,4,3,5,1,2,2,4,38,30.0,satisfied +40520,49055,Male,Loyal Customer,46,Business travel,Business,308,1,1,1,1,3,1,2,5,5,5,5,2,5,3,0,0.0,satisfied +40521,9011,Female,Loyal Customer,53,Business travel,Business,108,0,5,0,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +40522,91644,Male,Loyal Customer,41,Personal Travel,Eco,1199,1,1,1,3,5,1,5,5,3,3,3,2,3,5,3,3.0,neutral or dissatisfied +40523,7664,Female,Loyal Customer,41,Business travel,Business,641,1,1,1,1,3,4,5,4,4,5,4,5,4,5,2,0.0,satisfied +40524,80149,Male,Loyal Customer,59,Business travel,Business,2586,4,4,4,4,4,4,4,5,3,4,4,4,4,4,0,0.0,satisfied +40525,98836,Female,Loyal Customer,26,Personal Travel,Eco,763,3,5,3,3,2,3,2,2,5,5,5,3,4,2,34,34.0,neutral or dissatisfied +40526,65193,Male,Loyal Customer,40,Personal Travel,Eco,190,4,4,4,3,2,4,2,2,5,4,5,5,5,2,1,9.0,neutral or dissatisfied +40527,88674,Female,Loyal Customer,42,Personal Travel,Eco,581,4,5,4,3,3,4,4,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +40528,62689,Male,Loyal Customer,56,Business travel,Business,2556,2,2,2,2,5,4,4,3,2,4,5,4,3,4,28,64.0,satisfied +40529,61928,Male,Loyal Customer,57,Personal Travel,Eco,550,4,2,4,4,3,4,3,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +40530,11901,Male,disloyal Customer,26,Business travel,Business,501,3,4,4,1,2,4,2,2,5,3,4,5,4,2,0,3.0,neutral or dissatisfied +40531,112325,Male,Loyal Customer,53,Business travel,Business,2976,2,2,2,2,4,5,4,5,5,5,5,5,5,5,10,1.0,satisfied +40532,4909,Female,Loyal Customer,55,Business travel,Eco,1020,3,4,4,4,4,3,3,3,3,3,3,1,3,3,0,8.0,neutral or dissatisfied +40533,68932,Male,disloyal Customer,17,Business travel,Eco,646,3,4,3,4,4,3,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +40534,43493,Male,Loyal Customer,67,Personal Travel,Eco,752,3,4,3,5,1,3,1,1,4,5,5,4,4,1,0,5.0,neutral or dissatisfied +40535,81414,Female,Loyal Customer,34,Business travel,Business,393,1,1,1,1,1,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +40536,79197,Female,Loyal Customer,57,Business travel,Business,1990,3,3,3,3,5,4,4,5,5,5,5,3,5,5,10,6.0,satisfied +40537,7991,Male,Loyal Customer,42,Business travel,Business,3315,4,4,4,4,3,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +40538,44779,Male,disloyal Customer,26,Business travel,Eco,1250,1,1,1,4,3,1,3,3,4,5,3,2,4,3,16,14.0,neutral or dissatisfied +40539,20781,Male,disloyal Customer,30,Business travel,Eco,508,2,5,2,2,4,2,4,4,5,2,3,5,2,4,0,0.0,neutral or dissatisfied +40540,115743,Female,disloyal Customer,36,Business travel,Business,447,2,2,2,4,1,2,1,1,4,3,5,5,5,1,7,0.0,neutral or dissatisfied +40541,489,Male,disloyal Customer,20,Business travel,Eco,164,2,0,2,3,2,2,2,2,3,4,4,4,5,2,0,1.0,neutral or dissatisfied +40542,93374,Male,disloyal Customer,37,Business travel,Eco Plus,1024,2,2,2,3,5,2,5,5,3,4,4,3,4,5,9,0.0,neutral or dissatisfied +40543,31249,Male,disloyal Customer,45,Business travel,Eco,524,1,4,1,5,4,1,4,4,1,5,2,4,2,4,4,7.0,neutral or dissatisfied +40544,48285,Female,Loyal Customer,9,Personal Travel,Eco Plus,192,2,4,2,1,4,2,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +40545,116822,Male,Loyal Customer,26,Business travel,Business,2147,5,5,5,5,3,3,3,3,4,4,4,4,4,3,0,0.0,satisfied +40546,30643,Female,disloyal Customer,10,Business travel,Eco,770,2,2,2,4,2,2,2,2,1,2,4,1,3,2,74,68.0,neutral or dissatisfied +40547,7719,Male,Loyal Customer,42,Business travel,Business,1525,4,4,3,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +40548,108378,Female,Loyal Customer,52,Personal Travel,Eco,1838,3,4,2,1,2,4,5,1,1,2,1,3,1,5,1,5.0,neutral or dissatisfied +40549,6807,Male,Loyal Customer,12,Personal Travel,Eco,235,2,5,2,3,5,2,5,5,5,4,4,3,5,5,19,19.0,neutral or dissatisfied +40550,67996,Male,Loyal Customer,69,Personal Travel,Eco Plus,1235,3,5,3,3,3,3,3,3,5,3,1,2,1,3,0,12.0,neutral or dissatisfied +40551,92275,Male,disloyal Customer,22,Business travel,Eco,1415,3,3,3,4,1,3,2,1,1,1,5,5,2,1,0,0.0,satisfied +40552,35371,Male,Loyal Customer,55,Business travel,Eco,1028,4,3,3,3,4,4,4,4,4,1,3,4,4,4,0,0.0,satisfied +40553,70505,Female,Loyal Customer,25,Personal Travel,Eco,867,1,4,1,1,3,1,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +40554,62641,Male,Loyal Customer,37,Personal Travel,Eco,1846,0,4,0,3,3,0,2,3,4,4,5,2,3,3,8,0.0,satisfied +40555,80433,Female,Loyal Customer,62,Personal Travel,Eco,2248,2,4,2,1,3,4,4,3,3,2,2,5,3,5,0,0.0,neutral or dissatisfied +40556,19971,Female,disloyal Customer,22,Business travel,Business,557,4,2,4,4,3,4,3,3,4,1,4,3,3,3,50,46.0,neutral or dissatisfied +40557,9831,Female,Loyal Customer,27,Personal Travel,Eco,476,1,3,1,3,5,1,5,5,3,3,3,1,3,5,104,126.0,neutral or dissatisfied +40558,65136,Female,Loyal Customer,7,Personal Travel,Eco,469,3,3,3,4,4,3,4,4,4,2,2,3,1,4,14,11.0,neutral or dissatisfied +40559,44356,Male,Loyal Customer,22,Business travel,Business,596,3,3,3,3,5,4,5,5,1,5,2,5,2,5,0,16.0,satisfied +40560,20068,Male,Loyal Customer,55,Personal Travel,Eco,607,2,4,2,1,3,2,3,3,3,3,4,5,4,3,29,25.0,neutral or dissatisfied +40561,42393,Female,disloyal Customer,32,Business travel,Eco Plus,748,3,3,3,3,2,3,2,2,2,5,2,5,3,2,9,8.0,neutral or dissatisfied +40562,22806,Male,disloyal Customer,24,Business travel,Eco,302,0,3,0,1,2,0,2,2,5,2,3,1,3,2,0,0.0,satisfied +40563,95965,Male,Loyal Customer,54,Business travel,Business,2942,1,1,3,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +40564,122973,Male,Loyal Customer,50,Business travel,Business,2466,4,5,5,5,5,4,4,4,4,4,4,2,4,4,4,0.0,neutral or dissatisfied +40565,39151,Female,disloyal Customer,24,Business travel,Eco,119,4,3,4,3,4,4,4,2,3,3,3,4,2,4,172,189.0,neutral or dissatisfied +40566,88250,Male,Loyal Customer,40,Business travel,Business,3791,4,4,4,4,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +40567,115095,Female,disloyal Customer,37,Business travel,Business,342,1,1,1,3,3,1,1,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +40568,126908,Female,disloyal Customer,17,Business travel,Eco,651,0,4,1,3,1,1,1,1,3,5,4,3,4,1,0,0.0,satisfied +40569,109932,Female,Loyal Customer,56,Personal Travel,Eco,1052,4,4,4,2,3,4,5,3,3,4,3,3,3,4,16,15.0,neutral or dissatisfied +40570,110430,Female,Loyal Customer,37,Business travel,Business,525,1,0,0,4,3,3,4,4,4,0,4,4,4,1,17,6.0,neutral or dissatisfied +40571,35996,Female,Loyal Customer,39,Personal Travel,Eco Plus,2496,3,5,3,1,4,3,4,4,3,5,5,2,2,4,0,0.0,neutral or dissatisfied +40572,125324,Female,Loyal Customer,54,Business travel,Business,599,2,1,2,1,5,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +40573,116558,Male,Loyal Customer,57,Personal Travel,Eco,325,5,4,5,3,1,5,1,1,2,4,1,5,3,1,0,0.0,satisfied +40574,101684,Female,Loyal Customer,29,Business travel,Business,1500,4,4,4,4,4,4,4,4,4,2,5,3,4,4,9,0.0,satisfied +40575,81416,Female,disloyal Customer,25,Business travel,Business,448,1,0,1,3,3,1,3,3,4,3,4,5,4,3,0,9.0,neutral or dissatisfied +40576,120613,Female,Loyal Customer,29,Business travel,Business,3081,1,1,1,1,3,3,3,3,3,3,4,3,5,3,8,26.0,satisfied +40577,22733,Female,Loyal Customer,28,Business travel,Eco,147,5,1,1,1,5,5,5,5,2,2,1,4,1,5,4,2.0,satisfied +40578,41379,Male,Loyal Customer,42,Business travel,Eco,563,2,2,2,2,2,2,2,2,2,2,4,1,4,2,0,1.0,neutral or dissatisfied +40579,51818,Female,Loyal Customer,29,Business travel,Eco Plus,261,4,5,5,5,4,4,4,4,2,4,3,5,2,4,0,0.0,satisfied +40580,10868,Female,disloyal Customer,21,Business travel,Eco,134,2,4,1,4,1,1,1,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +40581,34025,Female,Loyal Customer,7,Personal Travel,Eco,1576,3,4,3,2,3,3,3,3,4,3,3,4,5,3,0,0.0,neutral or dissatisfied +40582,64385,Female,Loyal Customer,64,Personal Travel,Eco,1192,3,4,3,3,4,5,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +40583,96612,Male,Loyal Customer,53,Business travel,Business,3597,2,2,2,2,5,4,5,4,4,5,4,5,4,5,0,2.0,satisfied +40584,37057,Male,Loyal Customer,39,Business travel,Eco,1188,5,1,1,1,5,5,5,5,2,3,3,3,5,5,0,0.0,satisfied +40585,31225,Female,disloyal Customer,25,Business travel,Eco Plus,628,2,2,2,3,1,2,1,1,1,4,4,1,3,1,3,0.0,neutral or dissatisfied +40586,51633,Male,Loyal Customer,48,Business travel,Business,370,3,3,3,3,3,5,1,5,5,5,5,4,5,4,18,8.0,satisfied +40587,123535,Male,Loyal Customer,70,Personal Travel,Eco Plus,2077,2,3,2,4,5,2,1,5,4,4,2,2,4,5,14,7.0,neutral or dissatisfied +40588,9860,Female,Loyal Customer,68,Personal Travel,Eco,642,3,4,3,1,2,4,5,2,2,3,2,3,2,4,21,13.0,neutral or dissatisfied +40589,5390,Male,Loyal Customer,31,Personal Travel,Eco,733,0,5,0,2,1,0,1,1,4,4,4,1,4,1,0,0.0,satisfied +40590,119829,Female,Loyal Customer,53,Business travel,Business,3113,5,5,5,5,4,5,5,5,5,5,5,5,5,4,4,4.0,satisfied +40591,35460,Female,Loyal Customer,17,Personal Travel,Eco,1069,2,5,2,2,4,2,4,4,5,5,5,3,4,4,0,4.0,neutral or dissatisfied +40592,84897,Male,Loyal Customer,48,Personal Travel,Eco,534,1,5,3,3,1,3,1,1,3,2,4,3,5,1,36,27.0,neutral or dissatisfied +40593,6935,Male,Loyal Customer,33,Business travel,Business,3797,2,2,2,2,4,4,4,4,5,5,4,5,5,4,12,35.0,satisfied +40594,17561,Male,Loyal Customer,39,Business travel,Business,1034,4,4,4,4,5,3,4,4,4,5,4,1,4,5,0,0.0,satisfied +40595,10872,Female,disloyal Customer,25,Business travel,Business,517,4,0,4,2,3,4,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +40596,91120,Male,Loyal Customer,25,Personal Travel,Eco,404,3,4,3,2,1,3,1,1,3,5,4,5,4,1,10,5.0,neutral or dissatisfied +40597,34726,Male,Loyal Customer,44,Business travel,Business,3093,0,4,0,3,3,2,1,4,4,4,4,3,4,1,60,72.0,satisfied +40598,99907,Female,Loyal Customer,49,Business travel,Business,2338,4,4,5,4,3,5,5,4,4,4,4,5,4,5,51,33.0,satisfied +40599,44244,Female,disloyal Customer,23,Business travel,Eco,222,1,1,1,4,4,1,2,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +40600,39304,Female,Loyal Customer,27,Personal Travel,Eco,67,5,4,5,4,4,5,4,4,4,3,5,5,5,4,0,0.0,satisfied +40601,39319,Female,Loyal Customer,49,Personal Travel,Eco,67,2,5,2,1,5,4,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +40602,63194,Female,Loyal Customer,56,Business travel,Business,2390,3,3,3,3,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +40603,110507,Female,Loyal Customer,60,Business travel,Eco Plus,263,4,2,2,2,5,4,3,3,3,4,3,2,3,4,0,0.0,satisfied +40604,121111,Male,disloyal Customer,23,Business travel,Business,971,4,5,4,1,2,4,2,2,4,4,5,4,4,2,15,0.0,satisfied +40605,67018,Female,Loyal Customer,39,Business travel,Business,929,3,3,3,3,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +40606,82079,Female,Loyal Customer,55,Business travel,Business,2553,1,1,1,1,5,4,4,4,4,4,4,4,4,3,13,12.0,satisfied +40607,72659,Female,Loyal Customer,17,Personal Travel,Eco,985,2,5,2,5,5,2,5,5,4,4,5,4,5,5,7,8.0,neutral or dissatisfied +40608,64760,Female,Loyal Customer,45,Business travel,Business,282,4,1,4,4,4,4,4,4,4,5,5,4,4,4,152,139.0,satisfied +40609,94835,Female,disloyal Customer,59,Business travel,Business,277,2,2,2,3,2,2,2,2,4,4,4,3,4,2,2,1.0,neutral or dissatisfied +40610,2021,Female,Loyal Customer,11,Business travel,Business,3655,2,5,5,5,2,2,2,2,1,4,4,2,2,2,131,127.0,neutral or dissatisfied +40611,51486,Female,Loyal Customer,53,Business travel,Business,751,5,5,5,5,4,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +40612,9688,Male,disloyal Customer,23,Business travel,Eco,212,3,3,3,4,3,1,1,4,2,4,3,1,1,1,202,190.0,neutral or dissatisfied +40613,38997,Female,disloyal Customer,20,Business travel,Eco,260,5,4,5,4,3,5,3,3,3,3,1,4,5,3,0,0.0,satisfied +40614,24458,Female,disloyal Customer,25,Business travel,Eco,547,2,3,2,3,1,2,1,1,4,1,3,4,2,1,0,0.0,neutral or dissatisfied +40615,67300,Female,Loyal Customer,58,Business travel,Business,1523,1,1,1,1,4,5,5,5,5,5,5,5,5,3,4,0.0,satisfied +40616,25120,Male,Loyal Customer,36,Personal Travel,Eco,946,4,4,4,3,5,4,5,5,3,3,3,3,4,5,0,13.0,neutral or dissatisfied +40617,59147,Female,disloyal Customer,24,Personal Travel,Eco,1846,2,5,2,3,1,2,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +40618,51195,Male,Loyal Customer,58,Business travel,Eco Plus,207,5,3,3,3,5,5,5,5,3,3,4,4,2,5,0,0.0,satisfied +40619,29390,Female,disloyal Customer,13,Business travel,Eco,1290,3,3,3,3,4,3,4,4,4,2,2,1,3,4,0,0.0,neutral or dissatisfied +40620,36746,Male,Loyal Customer,41,Personal Travel,Business,2588,3,3,3,1,3,3,4,3,4,5,4,4,4,4,45,27.0,neutral or dissatisfied +40621,105194,Male,Loyal Customer,53,Business travel,Business,2045,3,1,3,3,3,5,5,5,5,5,5,4,5,4,10,1.0,satisfied +40622,16401,Female,Loyal Customer,35,Personal Travel,Eco,404,3,5,3,2,3,3,3,3,5,3,3,2,1,3,0,1.0,neutral or dissatisfied +40623,62063,Male,Loyal Customer,11,Personal Travel,Eco,2586,1,4,1,3,1,1,1,1,3,2,4,4,3,1,40,39.0,neutral or dissatisfied +40624,108124,Female,disloyal Customer,14,Business travel,Eco,1105,5,5,5,3,3,5,3,3,3,2,5,5,5,3,0,0.0,satisfied +40625,87753,Female,Loyal Customer,54,Business travel,Business,3867,3,3,3,3,2,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +40626,63254,Female,Loyal Customer,50,Business travel,Business,3158,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +40627,59030,Female,disloyal Customer,21,Business travel,Eco,1846,2,2,2,4,5,2,2,5,4,2,3,3,4,5,0,,neutral or dissatisfied +40628,48294,Female,Loyal Customer,51,Business travel,Business,1499,4,4,4,4,2,2,3,4,4,4,4,5,4,4,0,21.0,satisfied +40629,34684,Female,Loyal Customer,33,Business travel,Business,3125,1,1,1,1,4,2,1,5,5,5,5,1,5,2,0,0.0,satisfied +40630,30560,Male,Loyal Customer,31,Business travel,Business,628,1,1,3,1,5,5,5,5,4,2,1,1,5,5,0,0.0,satisfied +40631,43925,Male,Loyal Customer,64,Personal Travel,Eco,114,4,1,4,4,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +40632,45526,Male,disloyal Customer,10,Business travel,Eco,689,4,4,4,1,5,4,5,5,4,1,5,4,3,5,2,0.0,satisfied +40633,34250,Female,disloyal Customer,49,Business travel,Eco,1666,3,3,3,3,2,3,4,2,2,1,3,2,4,2,48,94.0,neutral or dissatisfied +40634,101618,Female,Loyal Customer,38,Business travel,Eco,739,4,5,4,4,4,5,4,4,1,1,2,5,1,4,18,14.0,satisfied +40635,42826,Female,Loyal Customer,36,Business travel,Business,3731,4,2,2,2,2,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +40636,21225,Female,Loyal Customer,19,Personal Travel,Eco,317,0,4,0,4,2,0,2,2,2,2,4,2,4,2,0,0.0,satisfied +40637,85139,Male,disloyal Customer,21,Business travel,Business,689,4,3,4,2,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +40638,8528,Female,Loyal Customer,19,Personal Travel,Eco,862,3,4,3,2,3,3,3,3,3,2,4,4,5,3,1,0.0,neutral or dissatisfied +40639,124598,Female,Loyal Customer,61,Personal Travel,Eco,500,2,1,2,2,1,1,1,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +40640,35922,Female,Loyal Customer,29,Business travel,Eco Plus,2248,3,1,1,1,3,3,3,3,1,4,2,3,3,3,6,0.0,neutral or dissatisfied +40641,67607,Female,disloyal Customer,35,Business travel,Business,1188,3,3,3,5,3,3,3,3,3,2,4,3,5,3,0,2.0,neutral or dissatisfied +40642,72303,Female,Loyal Customer,16,Personal Travel,Eco,919,2,4,2,4,4,2,4,4,4,5,4,3,4,4,23,26.0,neutral or dissatisfied +40643,5099,Male,Loyal Customer,28,Personal Travel,Eco,235,5,4,5,5,1,5,1,1,3,3,4,5,4,1,0,0.0,satisfied +40644,29801,Male,Loyal Customer,38,Business travel,Business,2323,3,3,3,3,1,1,4,4,4,4,4,1,4,4,0,0.0,satisfied +40645,115129,Female,disloyal Customer,35,Business travel,Business,342,2,2,2,4,1,2,1,1,3,5,5,3,5,1,4,1.0,neutral or dissatisfied +40646,56109,Female,Loyal Customer,38,Personal Travel,Eco,2402,3,2,3,3,3,3,5,1,4,4,3,5,4,5,1,17.0,neutral or dissatisfied +40647,39070,Male,Loyal Customer,45,Business travel,Business,737,3,4,4,4,3,3,3,4,3,3,4,3,1,3,163,172.0,neutral or dissatisfied +40648,103767,Male,disloyal Customer,36,Business travel,Business,882,3,3,3,3,2,3,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +40649,87391,Male,Loyal Customer,66,Business travel,Eco,425,3,2,2,2,3,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +40650,51526,Female,Loyal Customer,25,Business travel,Business,370,3,3,3,3,4,4,4,4,1,3,5,4,3,4,13,5.0,satisfied +40651,96353,Female,Loyal Customer,24,Personal Travel,Eco,1609,2,5,2,4,1,2,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +40652,18808,Female,Loyal Customer,51,Business travel,Business,2444,3,3,3,3,5,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +40653,40003,Female,Loyal Customer,50,Business travel,Eco,525,5,5,5,5,3,5,4,5,5,5,5,2,5,4,0,0.0,satisfied +40654,64026,Female,Loyal Customer,67,Business travel,Business,2415,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +40655,82109,Female,Loyal Customer,16,Personal Travel,Eco,1276,2,2,2,4,2,2,3,2,2,5,2,2,3,2,9,8.0,neutral or dissatisfied +40656,7759,Female,Loyal Customer,45,Business travel,Business,2812,4,4,2,4,5,4,4,5,5,5,5,4,5,4,0,9.0,satisfied +40657,89137,Male,Loyal Customer,66,Business travel,Eco,1919,2,3,3,3,2,2,2,2,3,2,4,4,4,2,17,7.0,neutral or dissatisfied +40658,85235,Male,disloyal Customer,24,Business travel,Eco,413,0,0,0,3,3,0,3,3,3,4,4,5,3,3,0,0.0,satisfied +40659,93343,Male,Loyal Customer,45,Business travel,Business,3826,4,4,4,4,2,4,4,2,2,2,2,5,2,4,6,1.0,satisfied +40660,84931,Male,Loyal Customer,48,Personal Travel,Eco,547,2,4,2,2,3,2,4,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +40661,18337,Male,Loyal Customer,22,Personal Travel,Eco Plus,554,4,4,4,1,2,4,4,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +40662,123103,Female,disloyal Customer,20,Business travel,Eco,590,3,3,3,4,1,3,2,1,2,3,4,4,3,1,76,55.0,neutral or dissatisfied +40663,64539,Male,Loyal Customer,57,Business travel,Business,2545,0,0,0,1,2,5,5,4,4,4,5,3,4,4,5,4.0,satisfied +40664,117992,Male,Loyal Customer,52,Business travel,Business,255,3,3,3,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +40665,78124,Female,disloyal Customer,21,Business travel,Business,1619,3,0,3,4,1,3,1,1,4,4,3,2,3,1,17,6.0,neutral or dissatisfied +40666,90635,Male,Loyal Customer,57,Business travel,Business,406,4,4,4,4,2,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +40667,36034,Female,Loyal Customer,50,Business travel,Business,474,3,2,3,3,5,3,2,3,3,3,3,3,3,2,0,0.0,satisfied +40668,95874,Female,Loyal Customer,33,Business travel,Business,759,1,1,1,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +40669,78864,Male,Loyal Customer,24,Business travel,Business,1995,5,5,5,5,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +40670,126902,Male,Loyal Customer,29,Personal Travel,Eco Plus,2077,3,3,3,2,3,3,3,3,1,2,2,1,3,3,36,15.0,neutral or dissatisfied +40671,98141,Female,Loyal Customer,42,Personal Travel,Eco Plus,472,2,3,2,3,3,2,2,2,2,2,2,4,2,3,29,20.0,neutral or dissatisfied +40672,93902,Male,Loyal Customer,67,Personal Travel,Eco,590,4,1,5,3,2,5,2,2,1,3,3,3,3,2,0,0.0,satisfied +40673,62183,Female,disloyal Customer,22,Business travel,Business,2565,4,2,3,1,2,3,2,2,5,4,3,3,5,2,10,0.0,satisfied +40674,83551,Male,Loyal Customer,33,Business travel,Business,1865,4,4,4,4,5,5,5,5,5,4,3,4,4,5,81,42.0,satisfied +40675,47569,Female,Loyal Customer,48,Personal Travel,Eco Plus,501,3,1,3,4,4,4,3,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +40676,30379,Female,Loyal Customer,28,Business travel,Business,862,1,4,4,4,1,1,1,1,1,2,4,1,4,1,3,28.0,neutral or dissatisfied +40677,7447,Male,Loyal Customer,31,Personal Travel,Eco,552,3,0,3,1,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +40678,120176,Female,Loyal Customer,31,Business travel,Business,1927,5,5,5,5,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +40679,21019,Female,Loyal Customer,55,Business travel,Business,2483,0,4,0,2,4,4,4,1,2,3,3,4,3,4,277,278.0,satisfied +40680,48032,Female,Loyal Customer,25,Personal Travel,Eco,1187,3,4,2,1,5,2,5,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +40681,33625,Female,Loyal Customer,48,Personal Travel,Eco,413,5,5,5,2,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +40682,22588,Male,disloyal Customer,34,Business travel,Eco,300,2,3,2,2,1,2,4,1,4,3,5,5,1,1,0,0.0,neutral or dissatisfied +40683,120185,Female,Loyal Customer,31,Business travel,Business,1303,3,3,3,3,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +40684,106718,Male,Loyal Customer,42,Business travel,Business,3981,2,2,2,2,3,5,5,4,4,4,4,3,4,3,41,49.0,satisfied +40685,47808,Male,disloyal Customer,49,Business travel,Eco,838,3,3,3,1,2,3,2,2,4,5,2,4,3,2,0,0.0,neutral or dissatisfied +40686,68545,Male,Loyal Customer,39,Personal Travel,Eco,1013,3,4,3,3,5,3,5,5,4,4,1,3,5,5,17,57.0,neutral or dissatisfied +40687,24564,Male,Loyal Customer,11,Personal Travel,Eco,874,3,4,4,3,2,4,2,2,1,4,2,4,3,2,63,57.0,neutral or dissatisfied +40688,93014,Female,disloyal Customer,29,Business travel,Eco,1524,2,2,2,4,2,5,5,2,1,4,3,5,1,5,173,195.0,neutral or dissatisfied +40689,97590,Female,Loyal Customer,64,Personal Travel,Eco Plus,448,4,5,3,3,3,2,1,3,3,3,4,2,3,4,6,0.0,neutral or dissatisfied +40690,67811,Male,Loyal Customer,43,Business travel,Eco,835,2,3,4,3,2,2,2,2,1,2,4,1,3,2,1,12.0,neutral or dissatisfied +40691,51269,Female,Loyal Customer,39,Business travel,Eco Plus,262,5,4,4,4,5,5,5,5,2,4,1,4,5,5,0,0.0,satisfied +40692,49860,Female,disloyal Customer,38,Business travel,Eco,209,2,0,2,4,3,2,3,3,5,3,1,1,4,3,0,5.0,neutral or dissatisfied +40693,51937,Male,Loyal Customer,46,Business travel,Eco,347,2,1,1,1,2,2,2,2,5,4,3,1,4,2,0,0.0,satisfied +40694,80269,Female,Loyal Customer,57,Business travel,Business,746,1,4,1,1,5,5,5,4,4,4,4,3,4,5,2,0.0,satisfied +40695,18627,Female,Loyal Customer,48,Personal Travel,Eco,285,2,5,2,3,3,4,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +40696,72420,Male,Loyal Customer,54,Business travel,Business,2775,2,2,5,2,3,4,4,2,2,2,2,3,2,4,0,1.0,satisfied +40697,61581,Male,disloyal Customer,23,Business travel,Eco,1356,4,4,4,3,5,4,5,5,4,5,5,3,4,5,0,0.0,satisfied +40698,118346,Male,Loyal Customer,13,Personal Travel,Eco,602,3,5,3,4,2,3,2,2,3,2,4,4,4,2,20,11.0,neutral or dissatisfied +40699,51490,Female,Loyal Customer,34,Business travel,Business,3633,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +40700,47969,Male,Loyal Customer,45,Personal Travel,Eco,329,1,1,1,3,3,1,3,3,4,1,3,1,3,3,6,34.0,neutral or dissatisfied +40701,71232,Male,Loyal Customer,52,Business travel,Business,1602,1,1,1,1,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +40702,124320,Male,Loyal Customer,42,Personal Travel,Eco,255,1,5,1,4,5,1,5,5,2,5,3,4,3,5,0,5.0,neutral or dissatisfied +40703,35396,Female,disloyal Customer,17,Business travel,Eco,1074,3,3,3,4,2,3,2,2,1,2,3,4,3,2,21,11.0,neutral or dissatisfied +40704,97364,Female,Loyal Customer,69,Personal Travel,Eco,347,4,5,5,3,2,5,5,3,3,5,3,4,3,5,0,0.0,neutral or dissatisfied +40705,62734,Female,disloyal Customer,28,Business travel,Eco,2615,2,2,2,4,2,1,1,2,4,2,4,1,4,1,1,15.0,neutral or dissatisfied +40706,35751,Male,Loyal Customer,46,Business travel,Business,1608,1,1,1,1,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +40707,42983,Male,Loyal Customer,36,Business travel,Eco,391,2,3,3,3,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +40708,112618,Female,Loyal Customer,37,Personal Travel,Eco,602,5,3,4,4,3,4,3,3,5,3,5,5,5,3,0,0.0,satisfied +40709,120718,Female,Loyal Customer,41,Business travel,Business,90,4,1,4,4,5,4,5,3,4,5,5,5,4,5,64,210.0,satisfied +40710,122876,Male,Loyal Customer,31,Personal Travel,Eco,226,5,4,0,4,4,0,5,4,4,5,4,4,5,4,0,0.0,satisfied +40711,53321,Female,Loyal Customer,9,Personal Travel,Eco,758,3,4,2,3,5,2,4,5,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +40712,26332,Female,Loyal Customer,65,Business travel,Business,2257,2,1,1,1,2,3,4,2,2,2,2,4,2,2,4,0.0,neutral or dissatisfied +40713,45160,Male,Loyal Customer,16,Business travel,Business,2846,1,2,2,2,4,4,1,4,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +40714,54380,Male,Loyal Customer,38,Business travel,Business,305,2,3,2,2,2,1,2,5,5,4,5,5,5,4,0,0.0,satisfied +40715,3647,Male,Loyal Customer,43,Business travel,Business,2219,2,5,5,5,5,3,3,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +40716,108100,Male,disloyal Customer,38,Business travel,Business,997,2,2,2,3,4,2,4,4,3,2,4,4,5,4,10,0.0,neutral or dissatisfied +40717,94306,Female,Loyal Customer,54,Business travel,Business,496,2,2,2,2,2,5,5,4,4,4,4,4,4,3,0,5.0,satisfied +40718,5212,Male,disloyal Customer,44,Business travel,Business,351,3,3,3,4,1,3,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +40719,62755,Female,Loyal Customer,41,Business travel,Business,2486,1,2,1,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +40720,92604,Female,disloyal Customer,44,Business travel,Eco,842,3,3,3,3,4,3,4,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +40721,106862,Female,Loyal Customer,60,Business travel,Business,3772,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +40722,114449,Male,Loyal Customer,53,Business travel,Business,337,1,1,1,1,4,5,4,5,5,5,5,3,5,3,19,9.0,satisfied +40723,64288,Male,Loyal Customer,29,Business travel,Business,2716,3,3,3,3,5,5,5,5,5,4,5,3,5,5,4,0.0,satisfied +40724,126874,Male,Loyal Customer,17,Personal Travel,Eco,2125,2,4,2,2,1,2,1,1,1,4,2,3,4,1,0,0.0,neutral or dissatisfied +40725,64948,Male,Loyal Customer,30,Business travel,Business,1975,4,2,2,2,1,1,4,1,2,2,3,3,4,1,9,0.0,neutral or dissatisfied +40726,25144,Female,Loyal Customer,38,Personal Travel,Business,406,1,4,2,3,1,4,5,2,2,2,2,5,2,1,21,13.0,neutral or dissatisfied +40727,31866,Male,Loyal Customer,43,Business travel,Eco,2603,3,1,1,1,3,3,3,3,3,4,5,1,4,3,6,0.0,satisfied +40728,108254,Female,Loyal Customer,22,Business travel,Business,895,3,3,3,3,2,2,2,2,5,4,5,5,5,2,0,0.0,satisfied +40729,71877,Male,Loyal Customer,66,Personal Travel,Eco,1723,2,5,2,5,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +40730,110946,Female,Loyal Customer,46,Business travel,Business,3091,4,4,4,4,5,5,4,3,3,3,3,4,3,4,16,7.0,satisfied +40731,45504,Male,Loyal Customer,25,Business travel,Eco Plus,522,3,5,5,5,3,3,2,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +40732,105186,Male,Loyal Customer,21,Personal Travel,Eco,220,1,4,1,3,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +40733,128528,Female,Loyal Customer,49,Personal Travel,Eco,304,3,4,3,3,3,5,5,1,1,3,1,5,1,3,0,1.0,neutral or dissatisfied +40734,82591,Female,Loyal Customer,37,Business travel,Business,528,2,2,2,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +40735,100338,Male,Loyal Customer,43,Business travel,Business,652,3,3,3,3,5,3,1,5,5,5,5,4,5,3,3,0.0,satisfied +40736,66485,Male,Loyal Customer,56,Business travel,Business,2644,1,1,1,1,4,5,5,5,5,4,5,4,5,3,0,3.0,satisfied +40737,26514,Female,disloyal Customer,24,Business travel,Eco,990,2,2,2,3,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +40738,115468,Male,disloyal Customer,17,Business travel,Eco,417,3,1,3,3,3,3,1,3,3,4,3,1,4,3,16,22.0,neutral or dissatisfied +40739,35086,Male,Loyal Customer,40,Business travel,Eco,1097,5,5,5,5,5,5,5,5,5,5,1,2,2,5,11,22.0,satisfied +40740,36115,Female,disloyal Customer,48,Business travel,Eco,708,2,2,2,5,2,2,2,2,3,5,1,5,3,2,57,91.0,neutral or dissatisfied +40741,96838,Male,Loyal Customer,60,Business travel,Business,994,2,2,2,2,5,4,5,4,4,4,4,4,4,4,32,17.0,satisfied +40742,108171,Female,Loyal Customer,55,Personal Travel,Eco,990,3,4,4,3,4,4,5,1,1,4,1,5,1,5,0,1.0,neutral or dissatisfied +40743,50163,Female,Loyal Customer,26,Business travel,Business,110,2,2,2,2,4,4,3,4,1,5,5,5,1,4,0,0.0,satisfied +40744,66396,Male,Loyal Customer,54,Business travel,Business,1562,4,4,3,4,5,5,5,4,3,5,5,5,4,5,275,262.0,satisfied +40745,127974,Male,Loyal Customer,39,Business travel,Business,1149,1,1,1,1,3,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +40746,62649,Male,Loyal Customer,24,Personal Travel,Eco,1846,3,4,3,3,5,3,5,5,4,4,3,5,4,5,0,0.0,neutral or dissatisfied +40747,9820,Female,Loyal Customer,40,Business travel,Business,2590,1,1,1,1,3,4,4,5,5,5,5,3,5,5,11,0.0,satisfied +40748,94354,Male,Loyal Customer,56,Business travel,Business,187,2,2,2,2,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +40749,123792,Female,Loyal Customer,42,Business travel,Business,2728,3,3,3,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +40750,12605,Female,Loyal Customer,16,Personal Travel,Eco,542,3,5,3,1,5,3,5,5,5,3,4,4,4,5,6,4.0,neutral or dissatisfied +40751,83892,Female,Loyal Customer,58,Business travel,Business,1450,2,3,2,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +40752,122264,Female,Loyal Customer,29,Personal Travel,Eco,544,1,5,1,4,5,1,5,5,4,1,5,4,2,5,0,0.0,neutral or dissatisfied +40753,107909,Female,disloyal Customer,26,Business travel,Eco,861,2,2,2,4,4,2,3,4,2,4,4,3,3,4,96,103.0,neutral or dissatisfied +40754,91346,Female,Loyal Customer,12,Personal Travel,Eco Plus,406,1,5,1,2,3,1,3,3,4,5,5,3,5,3,0,14.0,neutral or dissatisfied +40755,3506,Female,Loyal Customer,46,Business travel,Business,1597,5,5,5,5,4,4,5,4,4,4,4,5,4,5,40,21.0,satisfied +40756,59156,Female,Loyal Customer,32,Business travel,Business,1723,3,3,3,3,5,5,5,5,3,4,5,5,5,5,13,16.0,satisfied +40757,12958,Male,Loyal Customer,34,Business travel,Eco Plus,359,4,4,4,4,4,4,4,4,2,3,3,5,2,4,0,0.0,satisfied +40758,120455,Female,Loyal Customer,69,Personal Travel,Eco,366,2,1,5,3,5,3,4,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +40759,33062,Male,Loyal Customer,12,Personal Travel,Eco,201,2,2,2,4,2,2,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +40760,45619,Male,Loyal Customer,36,Business travel,Eco,230,4,2,2,2,4,4,4,4,2,4,3,1,3,4,0,0.0,neutral or dissatisfied +40761,70050,Female,Loyal Customer,12,Personal Travel,Eco,583,5,5,5,3,3,5,3,3,3,4,5,3,4,3,0,0.0,satisfied +40762,122826,Female,Loyal Customer,59,Business travel,Business,3316,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +40763,121866,Male,Loyal Customer,35,Business travel,Business,337,2,3,3,3,2,4,3,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +40764,128183,Male,Loyal Customer,19,Personal Travel,Eco,1849,3,1,3,4,4,3,4,4,4,4,4,4,3,4,0,0.0,neutral or dissatisfied +40765,105344,Male,disloyal Customer,36,Business travel,Eco,528,4,1,4,4,2,4,2,2,2,3,4,4,4,2,0,0.0,neutral or dissatisfied +40766,40201,Female,Loyal Customer,40,Business travel,Business,2134,2,2,2,2,1,4,4,4,4,4,4,5,4,2,0,0.0,satisfied +40767,59886,Female,Loyal Customer,23,Business travel,Business,1085,4,2,2,2,4,4,4,4,2,2,3,4,3,4,3,0.0,neutral or dissatisfied +40768,52916,Male,Loyal Customer,45,Business travel,Business,2799,4,4,4,4,4,5,3,2,2,2,2,3,2,2,7,0.0,satisfied +40769,127399,Female,disloyal Customer,24,Business travel,Business,1009,1,2,1,3,3,1,4,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +40770,24257,Female,Loyal Customer,33,Personal Travel,Eco,302,1,3,1,3,5,1,5,5,3,5,3,1,3,5,57,58.0,neutral or dissatisfied +40771,105203,Female,Loyal Customer,13,Personal Travel,Eco Plus,289,0,3,0,5,2,0,2,2,2,5,3,4,2,2,1,3.0,satisfied +40772,115825,Female,disloyal Customer,25,Business travel,Eco,404,5,0,5,4,2,5,2,2,5,2,3,5,3,2,3,0.0,satisfied +40773,34864,Female,disloyal Customer,42,Business travel,Eco,774,2,2,2,2,5,2,5,5,3,3,4,2,2,5,18,34.0,neutral or dissatisfied +40774,29312,Female,Loyal Customer,70,Personal Travel,Eco,859,3,5,3,1,3,5,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +40775,33410,Male,Loyal Customer,23,Business travel,Eco,2399,4,4,4,4,4,4,5,4,3,2,3,4,3,4,0,5.0,satisfied +40776,121819,Female,Loyal Customer,33,Business travel,Business,366,3,3,3,3,5,4,5,2,2,2,2,3,2,3,23,18.0,satisfied +40777,57451,Male,Loyal Customer,53,Business travel,Business,334,3,5,3,3,4,5,5,5,5,5,5,4,5,5,5,0.0,satisfied +40778,9267,Male,disloyal Customer,22,Business travel,Business,441,5,3,5,3,5,5,5,5,5,5,5,5,4,5,1,0.0,satisfied +40779,77791,Male,Loyal Customer,64,Personal Travel,Eco,696,2,5,2,3,5,2,5,5,4,5,5,3,4,5,76,69.0,neutral or dissatisfied +40780,3111,Female,Loyal Customer,10,Personal Travel,Eco Plus,413,2,4,2,3,2,2,2,2,2,1,4,2,3,2,15,41.0,neutral or dissatisfied +40781,5024,Male,disloyal Customer,24,Business travel,Eco,235,3,4,3,3,5,3,5,5,3,5,5,5,5,5,12,9.0,neutral or dissatisfied +40782,90495,Male,Loyal Customer,46,Business travel,Business,270,4,4,4,4,3,4,5,5,5,5,5,3,5,4,75,61.0,satisfied +40783,115365,Female,disloyal Customer,40,Business travel,Business,404,4,4,4,3,4,4,4,4,4,5,5,3,5,4,0,0.0,satisfied +40784,96973,Male,Loyal Customer,59,Business travel,Business,794,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +40785,28681,Female,Loyal Customer,44,Business travel,Business,2777,2,2,2,2,5,5,5,3,3,5,3,4,3,1,3,0.0,satisfied +40786,91270,Female,Loyal Customer,45,Personal Travel,Eco,270,3,5,3,3,2,3,2,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +40787,119946,Female,disloyal Customer,29,Business travel,Eco,868,2,2,2,3,3,2,5,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +40788,32852,Female,Loyal Customer,45,Personal Travel,Eco,201,2,4,2,3,1,4,3,2,2,2,5,4,2,3,0,0.0,neutral or dissatisfied +40789,124990,Male,Loyal Customer,48,Business travel,Eco,184,2,3,3,3,2,2,2,2,1,2,3,4,3,2,0,0.0,neutral or dissatisfied +40790,5844,Male,Loyal Customer,23,Business travel,Business,3780,3,3,3,3,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +40791,104967,Female,Loyal Customer,32,Business travel,Business,337,3,3,3,3,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +40792,34103,Male,disloyal Customer,24,Business travel,Eco,1046,5,5,5,4,5,2,2,1,4,2,5,2,2,2,139,142.0,satisfied +40793,47988,Male,Loyal Customer,21,Personal Travel,Eco,451,4,5,4,4,4,4,4,4,4,5,5,1,5,4,0,4.0,neutral or dissatisfied +40794,37329,Male,Loyal Customer,38,Business travel,Business,2623,1,1,1,1,4,4,4,4,4,4,4,5,4,1,0,0.0,satisfied +40795,76138,Female,Loyal Customer,59,Business travel,Business,2193,3,3,3,3,5,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +40796,117563,Male,Loyal Customer,42,Business travel,Business,347,1,1,1,1,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +40797,65848,Female,Loyal Customer,50,Business travel,Business,2933,1,1,1,1,4,2,1,5,5,5,5,3,5,3,0,0.0,satisfied +40798,15511,Female,Loyal Customer,13,Personal Travel,Eco,433,2,4,2,2,2,2,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +40799,14441,Male,Loyal Customer,27,Business travel,Business,1773,1,1,4,1,4,4,4,4,2,3,1,1,5,4,68,78.0,satisfied +40800,72499,Female,Loyal Customer,28,Business travel,Business,3946,2,4,4,4,2,3,2,2,3,2,3,2,3,2,0,6.0,neutral or dissatisfied +40801,117565,Female,disloyal Customer,25,Business travel,Business,347,4,0,4,4,5,4,5,5,4,3,4,3,5,5,59,58.0,satisfied +40802,122127,Male,Loyal Customer,7,Personal Travel,Eco Plus,130,3,4,0,2,3,0,3,3,5,4,3,3,5,3,11,11.0,neutral or dissatisfied +40803,25885,Female,Loyal Customer,54,Business travel,Eco,907,4,2,2,2,2,2,5,5,5,4,5,2,5,4,0,19.0,satisfied +40804,79851,Male,Loyal Customer,48,Business travel,Business,2244,5,5,1,5,2,5,4,5,5,5,5,3,5,5,51,38.0,satisfied +40805,16550,Female,Loyal Customer,61,Personal Travel,Business,872,3,3,3,3,4,3,2,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +40806,94389,Female,Loyal Customer,60,Business travel,Business,1582,0,0,0,2,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +40807,28518,Female,Loyal Customer,26,Business travel,Business,2640,4,5,5,5,4,4,4,4,1,3,4,1,4,4,0,0.0,neutral or dissatisfied +40808,104164,Male,disloyal Customer,23,Business travel,Eco,349,4,0,4,3,5,4,5,5,4,5,4,4,5,5,17,7.0,satisfied +40809,77621,Male,Loyal Customer,52,Business travel,Business,2716,2,2,2,2,4,5,5,4,4,4,4,3,4,5,9,0.0,satisfied +40810,94246,Male,disloyal Customer,44,Business travel,Business,192,5,5,5,3,2,5,2,2,5,2,4,5,5,2,0,0.0,satisfied +40811,122168,Female,disloyal Customer,25,Business travel,Business,546,2,0,2,4,4,2,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +40812,3757,Female,Loyal Customer,57,Personal Travel,Eco Plus,431,4,5,4,4,3,5,4,1,1,4,1,3,1,5,0,0.0,neutral or dissatisfied +40813,95148,Female,Loyal Customer,68,Personal Travel,Eco,319,3,2,3,4,5,3,4,3,3,3,2,1,3,1,0,0.0,neutral or dissatisfied +40814,33051,Female,Loyal Customer,39,Personal Travel,Eco,101,3,5,3,1,1,3,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +40815,50727,Female,Loyal Customer,66,Personal Travel,Eco,326,4,5,4,1,2,3,1,1,1,4,1,3,1,3,0,5.0,neutral or dissatisfied +40816,102404,Female,Loyal Customer,34,Personal Travel,Eco,223,4,1,4,3,3,4,3,3,1,4,3,2,2,3,0,0.0,satisfied +40817,48651,Male,disloyal Customer,38,Business travel,Business,373,5,4,4,2,2,4,2,2,5,4,5,4,4,2,0,0.0,satisfied +40818,78851,Male,Loyal Customer,50,Business travel,Eco Plus,528,4,1,1,1,4,4,4,4,4,4,3,4,3,4,138,141.0,neutral or dissatisfied +40819,127904,Female,Loyal Customer,22,Personal Travel,Eco,1671,0,3,0,3,3,0,3,3,2,3,1,3,1,3,12,5.0,satisfied +40820,98537,Female,Loyal Customer,50,Personal Travel,Eco,402,1,4,1,2,2,5,4,4,4,1,2,3,4,5,2,0.0,neutral or dissatisfied +40821,18244,Male,disloyal Customer,36,Business travel,Business,228,2,2,2,2,2,2,2,2,1,5,1,4,2,2,86,66.0,neutral or dissatisfied +40822,30727,Female,Loyal Customer,43,Personal Travel,Eco,1062,4,3,4,4,1,4,3,4,4,4,4,5,4,1,0,0.0,satisfied +40823,39463,Female,Loyal Customer,17,Personal Travel,Eco,129,3,1,0,3,5,0,5,5,1,4,3,2,4,5,0,0.0,neutral or dissatisfied +40824,113162,Female,Loyal Customer,55,Business travel,Business,1987,1,1,1,1,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +40825,26167,Female,disloyal Customer,35,Business travel,Eco,406,4,0,4,4,3,4,3,3,3,2,5,4,3,3,18,10.0,neutral or dissatisfied +40826,117224,Female,Loyal Customer,14,Personal Travel,Eco,325,3,4,4,3,1,4,1,1,2,4,5,2,4,1,0,0.0,neutral or dissatisfied +40827,101880,Female,Loyal Customer,21,Personal Travel,Eco,1747,0,1,0,3,2,0,2,2,2,2,2,2,3,2,4,0.0,satisfied +40828,103853,Male,disloyal Customer,40,Business travel,Eco,482,3,1,4,1,5,4,5,5,2,4,1,3,2,5,29,16.0,neutral or dissatisfied +40829,105679,Male,Loyal Customer,48,Business travel,Business,1836,1,1,1,1,3,4,4,4,4,4,4,4,4,4,12,0.0,satisfied +40830,107611,Male,Loyal Customer,58,Business travel,Eco,423,1,2,2,2,1,1,1,1,2,5,4,3,4,1,12,4.0,neutral or dissatisfied +40831,13481,Male,Loyal Customer,30,Business travel,Business,3142,3,3,3,3,4,4,5,4,5,2,5,3,5,4,0,0.0,satisfied +40832,60459,Female,Loyal Customer,59,Business travel,Business,2825,4,2,4,4,3,4,5,5,5,5,5,5,5,3,0,3.0,satisfied +40833,122151,Male,Loyal Customer,52,Business travel,Business,3343,4,4,5,4,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +40834,41117,Male,Loyal Customer,40,Business travel,Business,3641,2,3,3,3,1,4,3,4,4,4,2,1,4,1,29,23.0,neutral or dissatisfied +40835,102288,Male,Loyal Customer,48,Business travel,Business,2875,1,5,5,5,1,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +40836,77870,Male,Loyal Customer,47,Business travel,Business,1262,1,4,3,3,4,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +40837,20694,Female,disloyal Customer,23,Business travel,Eco,584,2,0,3,3,4,3,4,4,1,1,4,3,5,4,0,0.0,neutral or dissatisfied +40838,93917,Female,Loyal Customer,23,Business travel,Business,507,2,2,2,2,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +40839,41672,Female,disloyal Customer,25,Business travel,Eco,347,4,3,4,2,4,4,4,4,5,2,4,4,3,4,0,0.0,neutral or dissatisfied +40840,121199,Female,Loyal Customer,39,Personal Travel,Eco,2402,3,4,3,2,5,3,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +40841,115501,Female,disloyal Customer,36,Business travel,Eco,447,2,1,2,2,3,2,3,3,3,4,3,2,2,3,0,0.0,neutral or dissatisfied +40842,16511,Male,Loyal Customer,54,Personal Travel,Eco,143,2,1,0,3,5,0,5,5,1,4,4,4,4,5,47,41.0,neutral or dissatisfied +40843,92336,Male,disloyal Customer,21,Business travel,Eco,872,2,2,2,3,2,1,1,4,2,4,3,1,4,1,0,13.0,neutral or dissatisfied +40844,121224,Male,Loyal Customer,37,Business travel,Business,1814,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +40845,79011,Female,Loyal Customer,37,Business travel,Eco,331,3,2,2,2,3,3,3,3,4,3,3,2,3,3,13,0.0,neutral or dissatisfied +40846,126800,Male,Loyal Customer,60,Business travel,Business,2125,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +40847,112523,Female,Loyal Customer,37,Personal Travel,Eco,850,4,5,4,4,2,4,2,2,4,5,5,4,5,2,0,0.0,satisfied +40848,31450,Male,Loyal Customer,19,Business travel,Business,853,3,3,3,3,4,4,4,4,4,2,5,5,5,4,25,50.0,satisfied +40849,62971,Female,Loyal Customer,46,Business travel,Business,967,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +40850,3345,Male,disloyal Customer,38,Business travel,Business,296,3,3,3,4,3,3,2,3,5,4,4,4,4,3,0,0.0,neutral or dissatisfied +40851,106051,Female,Loyal Customer,22,Personal Travel,Eco,452,4,5,4,3,1,4,1,1,5,4,4,4,4,1,0,14.0,satisfied +40852,55643,Male,Loyal Customer,64,Business travel,Business,315,5,5,5,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +40853,106452,Female,Loyal Customer,57,Business travel,Business,1670,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,11.0,satisfied +40854,112433,Male,Loyal Customer,42,Business travel,Business,1975,3,3,3,3,2,4,5,2,2,3,2,3,2,3,23,0.0,satisfied +40855,2544,Female,Loyal Customer,56,Business travel,Business,304,0,0,0,3,2,4,4,5,5,5,5,3,5,4,75,69.0,satisfied +40856,47219,Female,Loyal Customer,60,Personal Travel,Eco,954,3,4,3,2,3,4,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +40857,109924,Female,Loyal Customer,39,Personal Travel,Eco,1053,2,4,2,1,3,2,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +40858,82427,Female,Loyal Customer,40,Business travel,Business,3415,3,3,3,3,3,5,5,5,5,5,5,3,5,4,5,0.0,satisfied +40859,4700,Female,Loyal Customer,52,Personal Travel,Eco,327,2,4,2,1,5,5,5,2,2,2,1,4,2,3,0,18.0,neutral or dissatisfied +40860,24698,Male,Loyal Customer,37,Business travel,Eco,397,5,3,3,3,5,5,5,5,3,2,4,4,2,5,0,2.0,satisfied +40861,59743,Male,Loyal Customer,44,Business travel,Business,895,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +40862,93952,Female,Loyal Customer,56,Personal Travel,Eco,507,4,4,2,2,2,4,5,4,4,2,4,5,4,4,17,9.0,neutral or dissatisfied +40863,107604,Female,Loyal Customer,44,Business travel,Business,423,3,1,1,1,4,3,4,3,3,3,3,1,3,1,53,48.0,neutral or dissatisfied +40864,7232,Male,Loyal Customer,35,Business travel,Business,1751,3,3,3,3,3,3,5,4,4,4,4,5,4,2,0,0.0,satisfied +40865,32483,Female,disloyal Customer,39,Business travel,Eco,102,4,4,4,4,5,4,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +40866,99589,Male,Loyal Customer,25,Personal Travel,Eco,930,2,4,2,3,2,2,1,2,5,2,4,5,4,2,3,22.0,neutral or dissatisfied +40867,113289,Female,Loyal Customer,66,Business travel,Business,2593,0,4,0,2,5,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +40868,55636,Male,disloyal Customer,20,Business travel,Business,563,4,2,4,1,3,4,3,3,4,4,4,5,4,3,0,0.0,satisfied +40869,105185,Female,Loyal Customer,69,Personal Travel,Eco,281,3,4,3,2,4,5,4,3,3,3,3,5,3,5,111,99.0,neutral or dissatisfied +40870,31396,Female,Loyal Customer,47,Business travel,Eco,1199,5,4,4,4,3,3,4,5,5,5,5,3,5,2,6,14.0,satisfied +40871,28440,Male,disloyal Customer,59,Business travel,Eco,996,4,4,4,4,4,1,4,1,4,4,4,4,3,4,3,7.0,neutral or dissatisfied +40872,53941,Female,Loyal Customer,32,Personal Travel,Eco,2007,3,5,3,1,4,3,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +40873,18219,Female,disloyal Customer,20,Business travel,Eco,346,1,3,2,1,4,2,4,4,1,2,5,2,5,4,1,0.0,neutral or dissatisfied +40874,78475,Male,Loyal Customer,37,Business travel,Business,666,5,5,5,5,5,4,5,5,5,5,5,5,5,4,4,15.0,satisfied +40875,11347,Male,Loyal Customer,48,Personal Travel,Eco,247,3,5,3,3,2,3,2,2,5,3,5,4,5,2,32,27.0,neutral or dissatisfied +40876,112533,Male,Loyal Customer,16,Personal Travel,Eco,853,2,4,2,2,3,2,3,3,5,5,4,3,4,3,33,57.0,neutral or dissatisfied +40877,24582,Male,Loyal Customer,30,Business travel,Business,526,1,1,1,1,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +40878,36701,Male,Loyal Customer,38,Personal Travel,Eco,1185,2,2,2,4,2,2,2,2,1,1,3,3,4,2,0,23.0,neutral or dissatisfied +40879,69232,Male,Loyal Customer,51,Business travel,Business,1908,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +40880,25992,Male,Loyal Customer,21,Business travel,Business,2589,2,2,2,2,5,5,5,5,5,1,4,4,1,5,0,0.0,satisfied +40881,32542,Male,Loyal Customer,79,Business travel,Eco,163,2,3,3,3,3,2,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +40882,699,Female,Loyal Customer,46,Business travel,Business,113,4,4,4,4,4,4,4,4,4,4,4,5,4,3,8,8.0,satisfied +40883,73780,Male,Loyal Customer,17,Personal Travel,Eco,192,4,1,4,3,3,4,1,3,4,3,3,1,4,3,14,3.0,neutral or dissatisfied +40884,65785,Male,Loyal Customer,44,Business travel,Business,1389,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,6.0,satisfied +40885,9221,Female,disloyal Customer,36,Business travel,Business,100,4,4,4,5,2,4,2,2,4,3,4,5,4,2,122,119.0,neutral or dissatisfied +40886,4485,Male,Loyal Customer,52,Business travel,Business,1147,5,5,5,5,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +40887,103203,Male,Loyal Customer,53,Business travel,Business,1482,2,2,5,2,5,4,4,2,2,2,2,4,2,3,13,5.0,satisfied +40888,52184,Male,Loyal Customer,51,Business travel,Eco,451,4,3,3,3,4,4,4,4,4,2,4,4,3,4,0,5.0,satisfied +40889,96103,Male,Loyal Customer,26,Personal Travel,Eco,758,3,5,3,1,4,3,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +40890,33114,Female,Loyal Customer,26,Personal Travel,Eco,102,3,5,3,2,5,3,5,5,4,4,5,3,2,5,0,0.0,neutral or dissatisfied +40891,89100,Female,Loyal Customer,57,Business travel,Business,1947,5,5,5,5,4,5,4,5,5,5,5,3,5,5,59,53.0,satisfied +40892,57404,Male,disloyal Customer,21,Business travel,Eco,524,5,0,5,4,0,4,4,4,5,5,5,4,4,4,398,377.0,satisfied +40893,90500,Female,disloyal Customer,33,Business travel,Business,406,3,3,3,2,1,3,3,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +40894,33057,Female,Loyal Customer,13,Personal Travel,Eco,101,1,5,1,5,2,1,2,2,5,5,4,3,5,2,0,13.0,neutral or dissatisfied +40895,99788,Female,Loyal Customer,46,Business travel,Business,632,2,5,2,2,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +40896,85264,Male,Loyal Customer,54,Personal Travel,Eco,689,2,2,2,3,1,2,1,1,3,3,3,3,3,1,100,102.0,neutral or dissatisfied +40897,128803,Female,Loyal Customer,58,Business travel,Business,2475,2,2,3,2,4,4,4,5,2,4,4,4,4,4,0,0.0,satisfied +40898,123988,Female,Loyal Customer,33,Business travel,Business,184,4,2,2,2,4,3,4,3,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +40899,10728,Female,disloyal Customer,39,Business travel,Business,201,3,3,3,5,2,3,2,2,5,5,4,4,5,2,54,52.0,neutral or dissatisfied +40900,79434,Female,disloyal Customer,25,Business travel,Eco Plus,502,3,3,3,4,5,3,5,5,2,5,3,1,4,5,0,31.0,neutral or dissatisfied +40901,113472,Male,disloyal Customer,34,Business travel,Business,397,3,3,3,5,4,3,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +40902,70056,Female,Loyal Customer,69,Personal Travel,Eco Plus,583,5,4,5,1,4,4,5,1,1,5,1,5,1,4,0,0.0,satisfied +40903,119430,Male,Loyal Customer,48,Personal Travel,Eco,399,2,5,2,1,2,2,2,2,3,3,5,5,5,2,27,12.0,neutral or dissatisfied +40904,105923,Male,Loyal Customer,40,Business travel,Business,3874,0,0,0,4,3,5,5,4,4,4,3,3,4,5,0,0.0,satisfied +40905,33460,Male,Loyal Customer,21,Business travel,Eco Plus,2355,0,5,0,2,3,0,3,3,2,3,5,5,1,3,0,1.0,satisfied +40906,32373,Female,Loyal Customer,58,Business travel,Eco,101,4,5,5,5,4,4,2,4,4,4,4,1,4,5,0,5.0,satisfied +40907,77394,Male,Loyal Customer,38,Personal Travel,Eco,590,1,5,1,3,5,1,5,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +40908,30215,Male,Loyal Customer,9,Personal Travel,Eco Plus,253,3,4,3,3,2,3,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +40909,5454,Male,disloyal Customer,26,Business travel,Eco,265,1,4,1,3,1,1,1,1,3,4,4,1,4,1,0,6.0,neutral or dissatisfied +40910,3914,Female,Loyal Customer,8,Personal Travel,Eco,213,3,3,3,1,4,3,4,4,4,3,4,3,5,4,2,0.0,neutral or dissatisfied +40911,2327,Female,Loyal Customer,39,Personal Travel,Eco,925,2,4,2,3,2,2,2,4,3,5,4,2,5,2,267,239.0,neutral or dissatisfied +40912,16333,Male,Loyal Customer,15,Personal Travel,Eco,594,2,1,2,1,5,2,3,5,3,1,1,1,1,5,0,0.0,neutral or dissatisfied +40913,69247,Female,Loyal Customer,46,Business travel,Business,733,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +40914,74724,Female,Loyal Customer,55,Personal Travel,Eco,1171,1,5,1,1,3,3,4,1,1,1,5,3,1,5,0,0.0,neutral or dissatisfied +40915,92551,Female,Loyal Customer,37,Personal Travel,Eco,1947,4,4,4,2,3,4,3,3,3,3,4,3,5,3,0,0.0,satisfied +40916,33602,Female,Loyal Customer,61,Business travel,Eco,399,2,2,2,2,5,2,2,2,2,2,2,2,2,3,76,67.0,neutral or dissatisfied +40917,82368,Male,Loyal Customer,53,Personal Travel,Eco,453,1,4,1,5,2,1,2,2,5,4,4,3,4,2,26,9.0,neutral or dissatisfied +40918,102565,Female,Loyal Customer,52,Business travel,Business,236,1,1,1,1,5,5,4,5,5,5,5,3,5,5,30,29.0,satisfied +40919,110772,Female,Loyal Customer,25,Business travel,Business,1166,4,2,4,4,5,5,5,5,4,4,5,4,4,5,60,121.0,satisfied +40920,69019,Male,disloyal Customer,25,Business travel,Business,1389,4,1,4,2,2,4,1,2,4,4,5,5,4,2,0,0.0,satisfied +40921,122711,Male,Loyal Customer,41,Personal Travel,Eco,813,2,1,2,2,2,2,1,2,3,5,1,4,2,2,7,2.0,neutral or dissatisfied +40922,117594,Male,disloyal Customer,61,Business travel,Business,347,3,3,3,3,4,3,5,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +40923,32868,Female,Loyal Customer,32,Personal Travel,Eco,163,3,5,3,2,4,3,4,4,4,4,4,5,4,4,2,10.0,neutral or dissatisfied +40924,23307,Female,Loyal Customer,33,Business travel,Eco,809,5,1,1,1,5,5,5,5,1,3,4,1,5,5,3,13.0,satisfied +40925,53785,Female,Loyal Customer,75,Business travel,Business,191,2,4,5,5,4,2,2,1,1,1,2,1,1,1,0,0.0,neutral or dissatisfied +40926,129121,Female,Loyal Customer,58,Business travel,Business,3557,3,3,3,3,1,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +40927,8848,Male,Loyal Customer,17,Personal Travel,Eco,1371,4,5,4,3,3,4,2,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +40928,37424,Male,disloyal Customer,49,Business travel,Eco,1035,2,2,2,2,1,2,1,1,4,3,3,2,2,1,52,44.0,neutral or dissatisfied +40929,63685,Female,Loyal Customer,43,Business travel,Business,853,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +40930,25527,Female,Loyal Customer,39,Personal Travel,Eco,481,3,2,3,4,5,3,5,5,1,3,4,1,3,5,7,0.0,neutral or dissatisfied +40931,48472,Female,Loyal Customer,31,Business travel,Business,845,3,3,3,3,2,2,2,2,5,3,3,3,5,2,0,0.0,satisfied +40932,6337,Male,Loyal Customer,52,Business travel,Business,2488,0,5,0,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +40933,90679,Male,disloyal Customer,22,Business travel,Eco,515,0,4,0,2,3,0,5,3,3,3,4,5,4,3,0,0.0,satisfied +40934,125553,Female,Loyal Customer,48,Business travel,Business,226,2,4,4,4,4,2,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +40935,38755,Female,Loyal Customer,44,Business travel,Business,353,4,4,4,4,5,4,5,4,4,4,4,2,4,1,0,0.0,satisfied +40936,116435,Male,Loyal Customer,25,Personal Travel,Eco,342,3,5,3,1,4,3,4,4,3,5,5,5,5,4,11,2.0,neutral or dissatisfied +40937,91879,Female,Loyal Customer,42,Personal Travel,Business,2475,5,1,5,1,2,1,1,2,2,5,2,3,2,1,11,0.0,satisfied +40938,40916,Female,Loyal Customer,59,Personal Travel,Eco,599,3,5,3,4,2,5,5,4,4,3,5,3,4,3,37,33.0,neutral or dissatisfied +40939,29308,Male,Loyal Customer,45,Personal Travel,Eco,834,3,4,4,3,5,4,5,5,3,4,4,3,4,5,0,4.0,neutral or dissatisfied +40940,98402,Female,Loyal Customer,20,Business travel,Business,1518,1,5,5,5,1,1,1,1,3,2,2,2,2,1,0,11.0,neutral or dissatisfied +40941,16744,Male,Loyal Customer,20,Personal Travel,Eco Plus,1167,2,4,2,4,4,2,4,4,3,4,4,3,4,4,0,25.0,neutral or dissatisfied +40942,22959,Male,Loyal Customer,26,Business travel,Business,2629,3,3,2,3,3,4,3,3,1,4,4,1,3,3,0,16.0,neutral or dissatisfied +40943,46787,Male,Loyal Customer,53,Business travel,Business,3598,1,1,1,1,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +40944,33776,Male,Loyal Customer,69,Personal Travel,Business,588,3,5,3,2,5,4,4,5,5,3,4,4,5,5,16,14.0,neutral or dissatisfied +40945,106316,Female,Loyal Customer,41,Business travel,Business,1857,1,1,1,1,4,5,5,4,4,4,4,4,4,5,38,22.0,satisfied +40946,110623,Female,Loyal Customer,58,Business travel,Business,3203,4,4,4,4,4,5,5,4,4,4,4,3,4,4,1,0.0,satisfied +40947,97424,Female,Loyal Customer,51,Personal Travel,Eco,587,1,4,0,3,3,4,2,5,5,0,3,1,5,3,0,0.0,neutral or dissatisfied +40948,3098,Female,Loyal Customer,33,Personal Travel,Eco,413,2,1,2,3,5,2,1,5,2,2,4,3,4,5,0,0.0,neutral or dissatisfied +40949,41978,Female,Loyal Customer,48,Personal Travel,Eco,618,1,5,1,1,5,5,5,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +40950,42269,Female,Loyal Customer,48,Business travel,Eco,817,3,5,5,5,1,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +40951,23238,Female,disloyal Customer,43,Business travel,Eco,549,5,0,5,5,1,5,1,1,3,5,3,1,5,1,0,0.0,satisfied +40952,95489,Male,disloyal Customer,38,Business travel,Business,496,1,1,1,4,3,1,3,3,4,3,5,3,5,3,9,6.0,neutral or dissatisfied +40953,92533,Male,Loyal Customer,66,Personal Travel,Eco,1892,3,3,2,3,3,2,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +40954,26284,Male,Loyal Customer,23,Personal Travel,Eco,859,2,4,2,5,2,2,3,2,5,4,5,3,4,2,7,0.0,neutral or dissatisfied +40955,118318,Male,Loyal Customer,23,Business travel,Business,1778,2,3,3,3,2,2,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +40956,107958,Male,Loyal Customer,46,Business travel,Business,2019,5,5,3,5,2,5,5,5,5,5,5,3,5,4,40,26.0,satisfied +40957,78122,Female,Loyal Customer,45,Personal Travel,Eco,1619,2,5,2,3,4,4,4,4,4,2,1,4,4,5,0,0.0,neutral or dissatisfied +40958,19582,Female,Loyal Customer,44,Personal Travel,Eco,173,4,5,0,1,3,4,4,4,4,0,2,5,4,5,57,80.0,neutral or dissatisfied +40959,50518,Male,Loyal Customer,54,Personal Travel,Eco,308,4,3,4,3,3,4,3,3,4,2,2,4,3,3,2,0.0,satisfied +40960,62226,Female,Loyal Customer,36,Personal Travel,Eco,2565,2,2,2,4,2,2,2,2,3,5,3,1,4,2,5,0.0,neutral or dissatisfied +40961,42871,Male,disloyal Customer,25,Business travel,Eco,867,1,1,1,3,1,1,2,1,3,3,3,4,4,1,0,35.0,neutral or dissatisfied +40962,12420,Male,Loyal Customer,59,Personal Travel,Eco,201,5,1,5,4,2,5,1,2,1,4,3,2,3,2,31,29.0,satisfied +40963,99289,Female,Loyal Customer,8,Personal Travel,Eco,833,3,4,3,2,4,3,4,4,3,4,5,3,4,4,0,12.0,neutral or dissatisfied +40964,22652,Female,Loyal Customer,49,Business travel,Eco Plus,300,5,2,2,2,5,5,3,5,5,5,5,1,5,4,0,0.0,satisfied +40965,4944,Male,Loyal Customer,42,Personal Travel,Eco,268,1,3,1,4,2,1,2,2,1,1,3,2,4,2,46,67.0,neutral or dissatisfied +40966,38152,Male,Loyal Customer,13,Personal Travel,Eco,1249,2,5,2,1,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +40967,120224,Female,Loyal Customer,52,Business travel,Business,1325,3,1,1,1,3,3,4,3,3,3,3,1,3,4,0,5.0,neutral or dissatisfied +40968,45174,Male,Loyal Customer,51,Personal Travel,Eco,174,5,5,5,1,5,5,5,5,1,4,1,1,3,5,0,4.0,satisfied +40969,64396,Male,Loyal Customer,53,Personal Travel,Eco,1172,1,5,1,5,3,1,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +40970,77306,Female,Loyal Customer,65,Personal Travel,Business,590,1,4,1,4,4,5,4,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +40971,8226,Female,Loyal Customer,48,Personal Travel,Eco,402,3,5,3,3,2,5,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +40972,104910,Female,Loyal Customer,69,Personal Travel,Eco,1565,1,4,1,2,1,5,5,5,2,5,5,5,3,5,259,265.0,neutral or dissatisfied +40973,46256,Female,Loyal Customer,24,Personal Travel,Eco,624,3,4,4,1,4,4,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +40974,3999,Female,Loyal Customer,43,Business travel,Business,1724,5,5,5,5,2,5,4,5,5,5,5,3,5,3,0,6.0,satisfied +40975,87070,Female,Loyal Customer,60,Business travel,Eco,594,3,1,1,1,4,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +40976,102607,Female,Loyal Customer,34,Personal Travel,Eco Plus,391,2,4,2,3,1,2,1,1,4,2,5,4,5,1,56,46.0,neutral or dissatisfied +40977,31153,Female,disloyal Customer,27,Business travel,Eco,495,1,1,1,4,4,1,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +40978,77825,Male,Loyal Customer,59,Personal Travel,Eco,731,2,1,2,3,2,4,2,2,1,4,3,2,1,2,288,279.0,neutral or dissatisfied +40979,54650,Male,disloyal Customer,23,Business travel,Eco,964,2,2,2,3,5,2,5,5,1,3,4,5,2,5,20,1.0,neutral or dissatisfied +40980,68751,Male,Loyal Customer,25,Business travel,Business,926,2,2,2,2,5,5,5,5,5,2,5,3,5,5,16,10.0,satisfied +40981,44219,Female,Loyal Customer,61,Business travel,Business,235,4,4,4,4,5,5,5,3,5,4,3,5,1,5,242,228.0,satisfied +40982,78960,Male,Loyal Customer,24,Personal Travel,Business,226,3,4,3,5,3,3,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +40983,101623,Male,Loyal Customer,23,Personal Travel,Eco,1371,2,5,2,4,1,2,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +40984,104544,Female,Loyal Customer,61,Personal Travel,Eco,1256,3,5,3,3,3,3,5,3,3,3,4,4,3,5,0,6.0,neutral or dissatisfied +40985,87553,Female,disloyal Customer,59,Business travel,Business,432,4,4,4,3,1,4,1,1,4,4,5,3,4,1,5,0.0,satisfied +40986,57588,Female,Loyal Customer,50,Personal Travel,Eco,1597,3,3,3,3,4,2,4,1,1,3,1,4,1,2,0,11.0,neutral or dissatisfied +40987,121811,Female,Loyal Customer,57,Business travel,Business,2444,2,2,2,2,5,5,5,5,3,5,4,5,4,5,182,169.0,satisfied +40988,24427,Female,Loyal Customer,25,Personal Travel,Eco,634,3,4,4,4,5,4,5,5,4,2,4,4,4,5,27,25.0,neutral or dissatisfied +40989,119184,Female,disloyal Customer,22,Business travel,Business,257,5,5,5,4,2,5,2,2,5,3,5,3,5,2,0,0.0,satisfied +40990,103687,Female,Loyal Customer,52,Business travel,Business,3928,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +40991,118744,Male,Loyal Customer,49,Personal Travel,Eco,304,3,5,3,3,5,3,5,5,5,2,4,5,4,5,23,18.0,neutral or dissatisfied +40992,11371,Female,Loyal Customer,11,Personal Travel,Eco,667,2,5,2,1,2,2,3,2,5,3,4,3,4,2,4,0.0,neutral or dissatisfied +40993,8502,Male,disloyal Customer,23,Business travel,Business,737,5,4,5,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +40994,129453,Female,Loyal Customer,49,Personal Travel,Eco,236,2,5,2,4,3,4,4,2,2,2,2,4,2,5,9,1.0,neutral or dissatisfied +40995,24573,Male,Loyal Customer,50,Personal Travel,Eco,874,3,2,3,3,2,3,2,2,4,2,1,1,3,2,0,0.0,neutral or dissatisfied +40996,44340,Female,Loyal Customer,67,Personal Travel,Eco,230,3,5,0,3,3,5,5,5,5,0,5,3,5,4,0,0.0,neutral or dissatisfied +40997,30361,Male,Loyal Customer,48,Business travel,Business,3597,1,1,1,1,5,2,1,4,4,4,4,2,4,4,0,12.0,satisfied +40998,88219,Male,Loyal Customer,43,Business travel,Eco,442,3,2,3,2,3,3,3,3,3,2,3,2,3,3,7,7.0,neutral or dissatisfied +40999,115445,Male,Loyal Customer,45,Business travel,Business,2972,2,5,2,5,5,3,2,2,2,2,2,3,2,2,37,49.0,neutral or dissatisfied +41000,73045,Male,Loyal Customer,57,Personal Travel,Eco,1096,3,4,3,2,3,3,3,3,2,2,3,4,3,3,0,0.0,neutral or dissatisfied +41001,23957,Female,Loyal Customer,11,Personal Travel,Eco,936,3,5,3,3,4,3,4,4,5,3,3,4,4,4,4,4.0,neutral or dissatisfied +41002,54057,Female,Loyal Customer,43,Business travel,Eco,1416,3,4,4,4,1,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +41003,51737,Male,Loyal Customer,48,Personal Travel,Eco,261,2,3,2,1,3,2,3,3,2,3,4,4,5,3,9,6.0,neutral or dissatisfied +41004,28239,Female,Loyal Customer,26,Personal Travel,Eco,1009,3,2,3,3,5,3,2,5,2,4,4,3,3,5,0,0.0,neutral or dissatisfied +41005,30298,Female,Loyal Customer,56,Business travel,Eco,1533,3,5,5,5,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +41006,43024,Male,Loyal Customer,52,Business travel,Business,192,4,4,4,4,5,3,1,4,4,4,4,3,4,1,0,0.0,satisfied +41007,45709,Male,Loyal Customer,41,Business travel,Business,3982,4,4,4,4,2,2,1,4,4,4,4,4,4,3,14,31.0,satisfied +41008,45972,Male,Loyal Customer,35,Personal Travel,Eco,872,3,2,3,3,2,3,2,2,3,3,4,1,4,2,7,6.0,neutral or dissatisfied +41009,10166,Male,Loyal Customer,54,Business travel,Business,3123,0,0,0,3,4,4,4,4,4,5,5,3,4,3,65,67.0,satisfied +41010,65365,Female,disloyal Customer,52,Business travel,Business,631,4,4,4,5,5,4,5,5,5,5,5,3,4,5,0,0.0,satisfied +41011,108399,Male,Loyal Customer,51,Personal Travel,Eco Plus,1844,2,1,2,3,1,2,2,1,4,2,3,4,3,1,16,24.0,neutral or dissatisfied +41012,45706,Male,Loyal Customer,22,Business travel,Business,3930,2,3,2,2,3,4,3,3,5,5,5,2,2,3,0,0.0,satisfied +41013,128140,Female,disloyal Customer,56,Business travel,Business,472,3,3,3,3,4,3,4,4,4,5,3,4,3,4,15,8.0,neutral or dissatisfied +41014,7505,Male,disloyal Customer,21,Business travel,Business,762,5,4,5,5,4,5,4,4,5,4,4,3,4,4,0,0.0,satisfied +41015,104344,Male,Loyal Customer,34,Personal Travel,Eco,528,2,5,2,3,1,2,1,1,4,4,4,5,5,1,10,4.0,neutral or dissatisfied +41016,23190,Female,Loyal Customer,65,Personal Travel,Eco,223,1,2,1,4,5,4,3,3,3,1,3,3,3,3,37,33.0,neutral or dissatisfied +41017,99782,Female,Loyal Customer,48,Business travel,Business,584,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +41018,45865,Male,disloyal Customer,25,Business travel,Business,409,4,0,3,5,2,3,2,2,4,3,4,4,4,2,0,0.0,satisfied +41019,78975,Female,disloyal Customer,32,Business travel,Eco,306,2,1,2,4,5,2,5,5,1,3,3,4,4,5,0,0.0,neutral or dissatisfied +41020,64392,Male,Loyal Customer,58,Personal Travel,Eco,1192,1,4,1,4,3,1,4,3,4,4,4,5,4,3,2,0.0,neutral or dissatisfied +41021,4243,Male,Loyal Customer,41,Business travel,Eco,620,5,5,5,5,5,5,5,5,3,4,1,1,3,5,0,0.0,satisfied +41022,88870,Male,Loyal Customer,56,Business travel,Business,859,1,1,1,1,2,5,4,4,4,4,4,5,4,5,0,2.0,satisfied +41023,91906,Female,disloyal Customer,27,Business travel,Business,1277,0,0,0,2,5,0,5,5,3,3,5,3,5,5,0,0.0,satisfied +41024,34560,Female,Loyal Customer,32,Business travel,Eco,1598,0,0,0,3,3,0,2,3,4,5,3,3,4,3,4,0.0,satisfied +41025,782,Male,disloyal Customer,39,Business travel,Business,89,5,0,0,3,1,0,1,1,5,5,4,4,5,1,23,38.0,satisfied +41026,31011,Female,Loyal Customer,18,Business travel,Business,391,1,5,5,5,1,1,1,1,4,3,3,1,4,1,17,17.0,neutral or dissatisfied +41027,109285,Female,Loyal Customer,30,Personal Travel,Business,1072,2,5,2,3,4,2,4,4,4,4,4,4,5,4,34,19.0,neutral or dissatisfied +41028,68314,Male,Loyal Customer,40,Business travel,Business,2165,4,4,4,4,5,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +41029,129747,Male,Loyal Customer,33,Business travel,Business,3935,1,4,4,4,1,1,1,1,2,1,3,1,3,1,0,6.0,neutral or dissatisfied +41030,103083,Female,Loyal Customer,41,Personal Travel,Eco,546,3,3,3,4,4,3,4,4,4,5,2,5,4,4,0,0.0,neutral or dissatisfied +41031,101873,Male,Loyal Customer,68,Personal Travel,Eco,1747,3,3,3,3,4,3,4,4,2,2,2,2,4,4,0,0.0,neutral or dissatisfied +41032,90874,Female,Loyal Customer,36,Business travel,Eco,404,1,3,5,3,1,1,1,1,4,1,4,3,3,1,0,10.0,neutral or dissatisfied +41033,15864,Female,Loyal Customer,51,Business travel,Eco,618,2,2,2,2,4,1,5,1,1,2,1,1,1,5,26,23.0,satisfied +41034,128963,Male,disloyal Customer,21,Business travel,Eco,414,5,4,5,3,5,5,1,5,3,3,2,3,1,5,0,0.0,satisfied +41035,72239,Female,Loyal Customer,42,Business travel,Business,2042,3,1,4,1,2,3,3,3,3,3,3,2,3,4,39,42.0,neutral or dissatisfied +41036,82542,Male,Loyal Customer,59,Business travel,Business,3380,2,1,1,1,5,3,3,2,2,1,2,1,2,1,0,10.0,neutral or dissatisfied +41037,110061,Male,Loyal Customer,46,Business travel,Business,1984,4,4,4,4,4,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +41038,71090,Female,Loyal Customer,43,Business travel,Business,802,3,3,3,3,4,5,5,5,5,5,5,3,5,4,29,34.0,satisfied +41039,84011,Female,Loyal Customer,40,Personal Travel,Eco,373,4,3,4,3,2,4,2,2,2,2,3,3,4,2,1,0.0,neutral or dissatisfied +41040,90395,Female,Loyal Customer,35,Personal Travel,Business,366,3,1,3,3,5,2,2,2,2,3,2,2,2,1,28,27.0,neutral or dissatisfied +41041,29214,Female,Loyal Customer,43,Business travel,Business,3325,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +41042,102834,Female,Loyal Customer,46,Business travel,Business,3093,4,4,4,4,3,5,4,4,4,4,4,3,4,4,2,2.0,satisfied +41043,28273,Female,Loyal Customer,32,Business travel,Business,2402,5,5,5,5,4,4,4,3,5,4,4,4,4,4,0,13.0,satisfied +41044,33139,Female,Loyal Customer,47,Personal Travel,Eco,101,2,4,2,5,4,4,4,3,3,2,3,5,3,5,0,3.0,neutral or dissatisfied +41045,67109,Male,Loyal Customer,39,Business travel,Eco,1017,4,3,3,3,4,4,4,4,3,4,4,3,3,4,0,0.0,neutral or dissatisfied +41046,65225,Male,Loyal Customer,40,Business travel,Business,247,4,4,5,4,3,5,4,5,5,5,5,4,5,4,0,4.0,satisfied +41047,67415,Female,Loyal Customer,44,Business travel,Business,1737,4,4,4,4,5,5,4,4,4,4,4,3,4,3,32,16.0,satisfied +41048,16552,Male,Loyal Customer,32,Business travel,Business,3025,5,5,5,5,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +41049,26524,Female,Loyal Customer,23,Business travel,Business,990,5,5,5,5,3,4,3,3,2,3,1,1,2,3,0,0.0,satisfied +41050,16952,Male,Loyal Customer,61,Business travel,Eco,116,4,5,5,5,4,4,4,4,5,1,1,3,5,4,0,2.0,satisfied +41051,120131,Female,Loyal Customer,60,Business travel,Eco Plus,1176,4,5,5,5,2,3,3,4,4,4,4,2,4,4,53,54.0,neutral or dissatisfied +41052,124889,Female,Loyal Customer,43,Business travel,Business,728,3,3,3,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +41053,41402,Female,Loyal Customer,59,Business travel,Eco,563,3,3,3,3,4,3,4,2,2,3,2,2,2,4,97,91.0,neutral or dissatisfied +41054,11553,Male,Loyal Customer,52,Business travel,Business,2741,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +41055,78385,Female,Loyal Customer,58,Business travel,Eco,980,1,0,0,4,2,4,3,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +41056,122611,Female,Loyal Customer,41,Business travel,Eco,728,5,3,3,3,5,5,5,5,4,4,5,1,3,5,2,0.0,satisfied +41057,59018,Male,disloyal Customer,22,Business travel,Business,759,0,0,0,1,3,0,3,3,3,5,4,3,5,3,13,8.0,satisfied +41058,38132,Female,disloyal Customer,27,Business travel,Eco,837,3,3,3,4,4,3,4,4,1,3,3,3,4,4,82,88.0,neutral or dissatisfied +41059,108048,Male,disloyal Customer,54,Personal Travel,Eco,591,2,5,2,1,5,2,5,5,4,2,4,4,5,5,29,21.0,neutral or dissatisfied +41060,12179,Male,Loyal Customer,49,Business travel,Eco,642,5,4,4,4,5,5,5,5,3,1,3,3,5,5,2,0.0,satisfied +41061,121214,Male,Loyal Customer,47,Personal Travel,Business,2075,3,2,3,2,5,1,2,5,5,3,5,1,5,3,0,8.0,neutral or dissatisfied +41062,106620,Male,Loyal Customer,11,Personal Travel,Eco,1216,3,1,4,3,5,4,5,5,1,3,2,3,3,5,0,0.0,neutral or dissatisfied +41063,6034,Male,Loyal Customer,36,Business travel,Business,2391,2,4,3,4,2,2,2,4,3,3,4,2,2,2,294,283.0,neutral or dissatisfied +41064,92608,Female,Loyal Customer,66,Personal Travel,Eco,2342,2,3,2,3,1,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +41065,39110,Male,Loyal Customer,64,Business travel,Eco,228,4,2,1,2,4,4,4,4,2,3,2,3,3,4,0,0.0,satisfied +41066,38074,Female,disloyal Customer,45,Business travel,Eco,1197,3,3,3,3,2,3,2,2,2,2,1,4,3,2,0,0.0,neutral or dissatisfied +41067,29057,Female,Loyal Customer,57,Personal Travel,Eco,954,1,2,1,4,2,4,4,5,5,1,1,2,5,1,0,0.0,neutral or dissatisfied +41068,24691,Male,Loyal Customer,21,Personal Travel,Eco,761,3,5,3,4,3,3,3,3,2,1,4,3,1,3,0,0.0,neutral or dissatisfied +41069,2551,Male,disloyal Customer,25,Business travel,Eco,304,2,0,2,4,2,2,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +41070,90065,Male,disloyal Customer,25,Business travel,Eco,1084,3,3,3,4,1,3,2,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +41071,59804,Male,disloyal Customer,38,Business travel,Business,937,1,1,1,3,3,1,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +41072,108979,Female,Loyal Customer,59,Business travel,Business,2198,1,5,4,5,2,4,3,1,1,1,1,2,1,3,33,41.0,neutral or dissatisfied +41073,71171,Female,Loyal Customer,41,Business travel,Business,3926,3,3,2,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +41074,129383,Female,Loyal Customer,15,Personal Travel,Eco,2454,4,5,4,4,5,4,5,5,4,4,3,4,4,5,0,0.0,neutral or dissatisfied +41075,99389,Female,disloyal Customer,35,Business travel,Eco,314,2,4,3,3,2,3,2,2,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +41076,93418,Male,Loyal Customer,47,Business travel,Business,697,2,3,3,3,2,2,2,1,3,3,4,2,3,2,200,188.0,neutral or dissatisfied +41077,84062,Male,disloyal Customer,24,Business travel,Business,932,0,0,0,3,3,0,2,3,5,3,5,5,5,3,0,0.0,satisfied +41078,102573,Female,Loyal Customer,68,Business travel,Eco Plus,386,2,2,2,2,4,2,2,2,2,2,2,2,2,3,25,13.0,neutral or dissatisfied +41079,129001,Male,disloyal Customer,46,Business travel,Business,2704,3,3,3,4,4,3,4,4,4,2,3,5,4,4,7,,neutral or dissatisfied +41080,101466,Male,Loyal Customer,49,Business travel,Business,2017,0,0,0,3,2,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +41081,2715,Male,Loyal Customer,42,Personal Travel,Eco,562,3,5,3,3,3,3,3,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +41082,22839,Male,Loyal Customer,58,Business travel,Eco,302,4,4,4,4,4,4,4,4,3,2,5,5,1,4,54,53.0,satisfied +41083,58466,Male,Loyal Customer,48,Business travel,Business,1517,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +41084,50549,Male,Loyal Customer,14,Personal Travel,Eco,326,2,1,4,4,5,4,5,5,3,2,2,1,4,5,0,0.0,neutral or dissatisfied +41085,66341,Female,disloyal Customer,29,Business travel,Business,986,0,0,0,1,1,0,1,1,4,2,4,4,4,1,0,0.0,satisfied +41086,122508,Female,Loyal Customer,54,Business travel,Business,930,3,3,3,3,4,4,5,4,4,4,4,4,4,3,120,121.0,satisfied +41087,127180,Male,Loyal Customer,58,Business travel,Business,647,1,1,1,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +41088,113575,Male,Loyal Customer,56,Business travel,Business,397,5,5,5,5,4,1,3,2,2,2,2,2,2,2,0,0.0,satisfied +41089,37080,Male,Loyal Customer,51,Business travel,Business,2797,3,5,5,5,3,3,2,3,3,3,3,4,3,4,111,114.0,neutral or dissatisfied +41090,101566,Male,Loyal Customer,34,Personal Travel,Eco Plus,345,3,5,3,4,2,3,2,2,4,2,5,3,4,2,0,1.0,neutral or dissatisfied +41091,9377,Female,Loyal Customer,13,Personal Travel,Eco,401,2,5,2,1,5,2,5,5,4,4,4,5,5,5,0,11.0,neutral or dissatisfied +41092,98875,Male,Loyal Customer,48,Business travel,Eco,991,3,3,3,3,3,3,3,3,1,5,2,4,3,3,16,16.0,neutral or dissatisfied +41093,3180,Female,Loyal Customer,26,Business travel,Business,2603,4,4,4,4,4,4,4,4,5,3,5,5,4,4,0,6.0,satisfied +41094,76400,Male,Loyal Customer,34,Business travel,Business,931,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +41095,71807,Male,Loyal Customer,29,Business travel,Eco,1846,2,3,3,3,2,2,2,2,3,5,3,4,3,2,0,12.0,neutral or dissatisfied +41096,107478,Female,Loyal Customer,27,Business travel,Business,711,2,2,2,2,5,5,5,5,4,5,4,4,4,5,10,12.0,satisfied +41097,21310,Male,Loyal Customer,70,Personal Travel,Eco,620,2,4,2,3,2,2,2,2,3,4,5,5,5,2,14,10.0,neutral or dissatisfied +41098,66070,Female,Loyal Customer,24,Personal Travel,Eco,1055,2,4,2,3,1,2,1,1,3,3,5,4,5,1,37,30.0,neutral or dissatisfied +41099,106926,Female,Loyal Customer,18,Personal Travel,Eco,1259,3,3,3,3,3,3,3,3,4,3,4,2,4,3,28,23.0,neutral or dissatisfied +41100,38319,Female,Loyal Customer,41,Business travel,Eco Plus,1666,1,5,5,5,4,1,2,1,1,1,1,2,1,1,0,6.0,neutral or dissatisfied +41101,117537,Female,Loyal Customer,47,Business travel,Business,2708,5,3,5,5,5,5,4,5,5,5,5,5,5,5,4,0.0,satisfied +41102,111038,Male,Loyal Customer,39,Business travel,Business,3889,4,4,4,4,3,5,4,5,5,5,5,4,5,4,6,9.0,satisfied +41103,30210,Female,Loyal Customer,67,Personal Travel,Eco Plus,253,1,4,0,5,2,5,5,1,1,0,1,1,1,5,0,0.0,neutral or dissatisfied +41104,124729,Female,Loyal Customer,15,Personal Travel,Eco,399,2,1,4,4,5,4,5,5,2,5,3,4,4,5,41,47.0,neutral or dissatisfied +41105,79808,Female,disloyal Customer,36,Business travel,Business,1089,3,3,3,1,3,3,3,3,3,2,4,4,5,3,37,14.0,neutral or dissatisfied +41106,15991,Male,disloyal Customer,29,Business travel,Eco,780,3,3,3,3,5,3,5,5,1,5,3,5,2,5,0,0.0,neutral or dissatisfied +41107,103768,Female,Loyal Customer,39,Business travel,Business,882,2,5,5,5,5,4,3,2,2,2,2,1,2,2,30,13.0,neutral or dissatisfied +41108,74783,Female,Loyal Customer,58,Business travel,Business,1235,4,4,4,4,4,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +41109,84720,Female,Loyal Customer,30,Business travel,Business,3871,3,3,3,3,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +41110,75101,Male,disloyal Customer,46,Business travel,Business,1652,3,4,4,4,4,3,4,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +41111,61513,Female,Loyal Customer,23,Personal Travel,Eco,2288,3,2,4,4,2,4,2,2,3,3,4,3,4,2,1,0.0,neutral or dissatisfied +41112,27915,Female,Loyal Customer,61,Business travel,Eco,689,1,4,4,4,2,3,3,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +41113,62453,Female,disloyal Customer,43,Business travel,Business,1744,2,3,3,3,1,2,2,1,3,2,3,4,5,1,11,0.0,neutral or dissatisfied +41114,16575,Male,disloyal Customer,29,Business travel,Eco,692,3,3,3,3,4,3,4,4,4,4,3,3,3,4,22,29.0,neutral or dissatisfied +41115,74619,Female,Loyal Customer,51,Business travel,Eco,771,4,5,5,5,1,1,1,4,4,4,4,1,4,4,65,59.0,satisfied +41116,126411,Male,disloyal Customer,26,Business travel,Business,507,4,4,4,1,3,4,3,3,4,4,4,3,5,3,0,0.0,satisfied +41117,11717,Female,Loyal Customer,48,Business travel,Business,429,1,1,3,1,4,4,4,5,5,5,5,3,5,5,1,9.0,satisfied +41118,61523,Male,Loyal Customer,44,Personal Travel,Eco,2288,1,2,1,3,2,1,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +41119,77867,Female,disloyal Customer,35,Business travel,Business,1262,3,3,3,3,1,3,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +41120,71230,Male,Loyal Customer,49,Business travel,Business,733,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,2.0,satisfied +41121,64131,Female,Loyal Customer,48,Personal Travel,Eco Plus,2311,2,5,2,3,2,4,5,3,3,2,3,4,3,4,38,22.0,neutral or dissatisfied +41122,36274,Male,Loyal Customer,22,Personal Travel,Eco,728,3,1,3,4,4,3,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +41123,16097,Female,Loyal Customer,38,Business travel,Eco,303,2,3,3,3,2,2,2,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +41124,15844,Male,Loyal Customer,21,Personal Travel,Eco,1107,5,5,5,4,4,5,4,4,1,3,3,4,2,4,32,36.0,satisfied +41125,17608,Female,Loyal Customer,60,Personal Travel,Eco,196,1,5,1,3,1,1,1,2,1,2,5,1,4,1,176,160.0,neutral or dissatisfied +41126,94778,Female,Loyal Customer,53,Business travel,Business,3727,0,4,0,3,3,5,4,5,5,3,3,3,5,4,2,0.0,satisfied +41127,9821,Male,Loyal Customer,49,Business travel,Business,3627,1,1,1,1,3,5,4,5,5,5,5,5,5,5,31,18.0,satisfied +41128,86970,Male,Loyal Customer,57,Business travel,Business,907,2,2,2,2,2,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +41129,52010,Female,Loyal Customer,67,Business travel,Business,328,0,0,0,2,2,3,4,2,2,2,2,4,2,3,0,0.0,satisfied +41130,55670,Female,Loyal Customer,45,Business travel,Business,3959,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,3.0,satisfied +41131,114198,Female,Loyal Customer,29,Business travel,Business,1897,1,5,5,5,1,1,1,1,3,3,4,1,4,1,11,7.0,neutral or dissatisfied +41132,11493,Male,Loyal Customer,13,Personal Travel,Eco Plus,216,4,2,4,3,3,4,3,3,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +41133,95685,Male,Loyal Customer,48,Personal Travel,Business,181,2,4,2,1,5,2,1,1,1,2,4,2,1,3,0,0.0,neutral or dissatisfied +41134,24808,Female,disloyal Customer,23,Business travel,Eco,991,4,4,4,3,3,4,3,3,3,2,3,1,4,3,0,6.0,neutral or dissatisfied +41135,20076,Male,Loyal Customer,37,Personal Travel,Eco,607,3,5,3,3,4,3,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +41136,103111,Male,Loyal Customer,30,Personal Travel,Eco,666,4,3,5,4,4,5,4,4,1,4,1,4,5,4,0,0.0,neutral or dissatisfied +41137,82995,Female,Loyal Customer,35,Business travel,Business,1086,3,3,3,3,3,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +41138,39330,Female,Loyal Customer,65,Personal Travel,Eco Plus,67,1,3,1,3,3,2,3,3,3,1,3,4,3,3,0,17.0,neutral or dissatisfied +41139,42390,Female,Loyal Customer,56,Business travel,Eco Plus,451,5,4,4,4,3,3,4,5,5,5,5,4,5,1,0,0.0,satisfied +41140,32474,Female,Loyal Customer,49,Business travel,Business,1599,0,3,0,5,1,1,2,4,4,4,1,4,4,4,3,3.0,satisfied +41141,49510,Male,Loyal Customer,41,Business travel,Eco,86,5,2,2,2,5,5,5,5,3,2,5,4,5,5,16,31.0,satisfied +41142,83009,Female,disloyal Customer,22,Business travel,Business,1127,4,0,4,3,1,4,1,1,5,5,4,5,4,1,0,3.0,satisfied +41143,122498,Male,Loyal Customer,57,Business travel,Business,930,1,1,1,1,3,4,5,4,4,4,4,4,4,4,8,0.0,satisfied +41144,86100,Female,Loyal Customer,70,Personal Travel,Business,226,1,4,1,1,4,4,4,2,2,1,2,3,2,4,35,40.0,neutral or dissatisfied +41145,14135,Male,Loyal Customer,43,Business travel,Business,528,2,2,2,2,4,4,4,2,2,2,2,1,2,3,0,27.0,neutral or dissatisfied +41146,14544,Male,disloyal Customer,17,Business travel,Eco,362,4,0,4,3,5,4,5,5,1,1,4,2,2,5,0,0.0,satisfied +41147,55010,Male,disloyal Customer,35,Business travel,Business,1635,4,4,4,5,3,4,3,3,3,3,5,3,4,3,26,25.0,neutral or dissatisfied +41148,50800,Male,Loyal Customer,23,Personal Travel,Eco,86,2,4,2,2,2,2,5,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +41149,42958,Female,Loyal Customer,40,Business travel,Business,2882,5,5,5,5,1,3,3,5,5,5,4,4,5,2,0,8.0,satisfied +41150,21062,Female,disloyal Customer,26,Business travel,Eco,227,2,5,2,3,3,2,3,3,1,1,1,4,3,3,0,0.0,neutral or dissatisfied +41151,51852,Female,Loyal Customer,15,Personal Travel,Business,374,2,4,2,1,1,2,1,1,5,2,5,3,4,1,61,57.0,neutral or dissatisfied +41152,58505,Male,disloyal Customer,47,Business travel,Eco,319,1,1,2,3,2,4,4,1,2,4,3,4,3,4,171,164.0,neutral or dissatisfied +41153,69125,Male,Loyal Customer,50,Personal Travel,Eco,1598,1,5,1,4,1,1,1,1,4,4,3,5,5,1,3,0.0,neutral or dissatisfied +41154,10425,Female,Loyal Customer,50,Business travel,Business,3435,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +41155,107374,Male,Loyal Customer,40,Business travel,Business,1881,2,2,2,2,5,4,5,4,4,4,4,3,4,5,13,8.0,satisfied +41156,6904,Male,Loyal Customer,40,Personal Travel,Eco,265,4,5,4,3,5,4,5,5,5,1,3,3,2,5,18,22.0,neutral or dissatisfied +41157,34030,Male,Loyal Customer,14,Personal Travel,Eco,1598,4,5,4,2,1,4,1,1,5,2,3,3,5,1,0,0.0,neutral or dissatisfied +41158,108586,Male,Loyal Customer,47,Business travel,Business,696,3,3,3,3,5,5,4,2,2,2,2,3,2,5,25,14.0,satisfied +41159,42537,Female,Loyal Customer,23,Business travel,Eco,1091,4,1,1,1,4,4,4,4,4,3,5,5,1,4,0,28.0,satisfied +41160,112919,Male,disloyal Customer,23,Business travel,Eco,764,0,0,0,1,5,0,5,5,1,5,2,1,4,5,1,0.0,satisfied +41161,54109,Female,disloyal Customer,29,Business travel,Business,1400,1,1,1,3,3,1,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +41162,100551,Male,Loyal Customer,46,Personal Travel,Eco Plus,759,3,5,2,1,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +41163,123803,Male,disloyal Customer,34,Business travel,Business,541,3,3,3,2,2,3,5,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +41164,19438,Male,Loyal Customer,30,Personal Travel,Eco,645,3,5,3,4,4,3,4,4,3,4,4,4,5,4,11,13.0,neutral or dissatisfied +41165,129476,Male,disloyal Customer,24,Business travel,Business,2611,5,4,5,3,3,5,3,3,4,5,4,5,5,3,0,9.0,satisfied +41166,46871,Male,disloyal Customer,22,Business travel,Eco,909,5,5,5,1,1,5,2,1,3,4,1,3,1,1,4,44.0,satisfied +41167,4096,Female,Loyal Customer,59,Business travel,Business,1512,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +41168,97480,Female,disloyal Customer,27,Business travel,Eco,670,3,3,3,4,5,3,5,5,3,3,3,3,3,5,23,16.0,neutral or dissatisfied +41169,94130,Female,Loyal Customer,54,Business travel,Business,3183,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,4.0,satisfied +41170,12639,Male,Loyal Customer,28,Business travel,Business,844,5,5,3,5,4,4,4,4,2,1,3,1,4,4,11,3.0,satisfied +41171,81980,Female,disloyal Customer,29,Business travel,Business,1522,0,0,0,1,3,0,3,3,3,2,4,3,4,3,0,0.0,satisfied +41172,67616,Female,Loyal Customer,40,Business travel,Business,1917,3,3,3,3,5,4,4,3,3,4,3,5,3,5,4,3.0,satisfied +41173,42004,Male,Loyal Customer,47,Business travel,Eco,106,4,5,5,5,4,4,4,4,5,2,4,5,3,4,0,0.0,satisfied +41174,15455,Female,Loyal Customer,57,Business travel,Business,306,5,5,5,5,4,1,4,5,5,5,5,5,5,3,0,1.0,satisfied +41175,34346,Female,Loyal Customer,35,Business travel,Business,427,4,4,4,4,2,4,4,5,5,5,5,4,5,1,28,23.0,satisfied +41176,48352,Female,Loyal Customer,28,Business travel,Eco,522,4,4,4,4,4,4,4,4,5,2,1,1,2,4,0,0.0,satisfied +41177,31588,Female,disloyal Customer,21,Business travel,Eco,602,3,3,3,5,1,3,1,1,5,5,3,2,3,1,0,0.0,neutral or dissatisfied +41178,43648,Female,Loyal Customer,43,Business travel,Business,2737,4,4,4,4,2,1,1,4,4,4,4,3,4,4,0,0.0,satisfied +41179,30095,Male,Loyal Customer,34,Personal Travel,Eco,261,4,4,0,2,3,0,4,3,5,2,1,5,2,3,10,9.0,neutral or dissatisfied +41180,60762,Male,Loyal Customer,47,Business travel,Business,628,2,2,2,2,2,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +41181,103494,Female,Loyal Customer,47,Business travel,Business,1796,3,3,5,3,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +41182,108945,Male,Loyal Customer,46,Business travel,Business,3161,4,4,4,4,4,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +41183,44243,Male,Loyal Customer,65,Business travel,Eco,222,2,3,3,3,2,2,2,2,4,4,3,3,3,2,0,0.0,neutral or dissatisfied +41184,13757,Female,Loyal Customer,20,Personal Travel,Eco,401,3,5,3,2,1,3,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +41185,36169,Female,Loyal Customer,32,Business travel,Eco,1674,5,5,5,5,5,5,5,5,1,1,3,1,1,5,0,0.0,satisfied +41186,53266,Male,Loyal Customer,58,Business travel,Eco,758,4,4,4,4,4,4,4,4,2,1,3,5,4,4,0,0.0,satisfied +41187,73154,Female,disloyal Customer,35,Business travel,Eco,1501,2,1,1,2,2,2,2,2,4,5,5,1,4,2,0,3.0,neutral or dissatisfied +41188,17179,Female,Loyal Customer,39,Business travel,Business,243,2,3,3,3,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +41189,85485,Female,Loyal Customer,68,Personal Travel,Eco,152,3,5,3,4,3,5,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +41190,38874,Male,Loyal Customer,51,Business travel,Eco,261,5,2,2,2,5,5,5,5,3,2,1,2,1,5,0,0.0,satisfied +41191,101564,Female,Loyal Customer,36,Business travel,Eco Plus,345,4,2,3,3,4,4,4,4,2,1,2,2,1,4,0,0.0,satisfied +41192,43458,Female,Loyal Customer,55,Business travel,Eco,594,2,1,2,1,3,4,3,2,2,2,2,5,2,2,0,0.0,satisfied +41193,74372,Male,Loyal Customer,48,Business travel,Business,1464,4,4,4,4,3,3,3,3,2,4,5,3,4,3,134,118.0,satisfied +41194,114174,Male,Loyal Customer,60,Business travel,Business,1540,5,5,5,5,4,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +41195,26913,Male,Loyal Customer,54,Business travel,Business,1770,3,4,4,4,5,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +41196,65593,Male,Loyal Customer,65,Business travel,Business,175,4,2,4,2,2,4,4,3,3,3,4,4,3,4,5,0.0,neutral or dissatisfied +41197,96745,Female,Loyal Customer,50,Personal Travel,Eco Plus,813,2,4,2,3,5,3,3,3,3,2,3,3,3,3,4,0.0,neutral or dissatisfied +41198,50325,Female,Loyal Customer,35,Business travel,Business,3697,4,4,4,4,2,2,5,4,4,4,4,3,4,2,0,0.0,satisfied +41199,64353,Female,Loyal Customer,25,Business travel,Business,3046,4,4,4,4,4,4,4,4,5,1,4,5,1,4,4,0.0,satisfied +41200,123561,Male,disloyal Customer,12,Business travel,Eco,1290,1,1,1,4,3,1,3,3,1,3,4,1,3,3,1,0.0,neutral or dissatisfied +41201,99429,Female,Loyal Customer,50,Personal Travel,Eco,314,3,5,3,2,2,4,4,2,2,3,2,5,2,4,11,6.0,neutral or dissatisfied +41202,49894,Male,Loyal Customer,47,Business travel,Business,262,2,5,5,5,1,2,2,3,5,3,3,2,2,2,253,257.0,neutral or dissatisfied +41203,48904,Male,disloyal Customer,25,Business travel,Eco,250,2,5,1,4,2,1,2,2,5,2,4,4,5,2,0,4.0,neutral or dissatisfied +41204,46116,Female,Loyal Customer,51,Business travel,Business,3160,2,2,2,2,4,4,5,4,4,4,4,4,4,3,11,0.0,satisfied +41205,24913,Male,Loyal Customer,55,Business travel,Eco,762,4,2,2,2,4,4,4,4,2,4,4,2,1,4,24,11.0,satisfied +41206,44676,Female,disloyal Customer,20,Business travel,Eco,67,4,3,4,3,5,4,5,5,4,4,4,4,4,5,9,4.0,neutral or dissatisfied +41207,79304,Female,disloyal Customer,28,Business travel,Eco,909,1,1,1,2,5,1,1,5,1,1,1,2,3,5,0,0.0,neutral or dissatisfied +41208,924,Female,Loyal Customer,41,Business travel,Business,102,1,5,5,5,2,3,4,2,2,2,1,2,2,4,0,0.0,neutral or dissatisfied +41209,111705,Male,Loyal Customer,59,Business travel,Eco,541,1,5,4,5,1,1,1,1,4,2,3,3,3,1,126,119.0,neutral or dissatisfied +41210,110915,Female,Loyal Customer,16,Business travel,Eco,545,5,5,5,5,5,5,4,5,1,5,4,4,1,5,0,3.0,satisfied +41211,32703,Female,disloyal Customer,22,Business travel,Eco,102,3,2,3,3,1,3,1,1,4,3,3,3,3,1,20,21.0,neutral or dissatisfied +41212,15767,Female,Loyal Customer,45,Business travel,Business,2243,1,1,1,1,3,3,1,5,5,5,5,3,5,4,0,0.0,satisfied +41213,60476,Male,disloyal Customer,26,Business travel,Business,985,2,2,2,4,1,2,1,1,4,3,4,5,4,1,1,0.0,neutral or dissatisfied +41214,93675,Male,Loyal Customer,64,Personal Travel,Eco,655,3,1,4,4,4,4,4,4,3,1,4,1,3,4,2,15.0,neutral or dissatisfied +41215,34136,Male,Loyal Customer,35,Business travel,Business,1813,2,2,2,2,2,5,5,4,4,4,4,1,4,3,9,21.0,satisfied +41216,13217,Male,disloyal Customer,25,Business travel,Eco,771,4,4,4,4,3,4,3,3,3,5,4,3,1,3,20,1.0,neutral or dissatisfied +41217,35306,Female,disloyal Customer,28,Business travel,Eco,1041,3,3,3,3,5,3,5,5,2,4,3,3,4,5,12,14.0,neutral or dissatisfied +41218,110052,Female,Loyal Customer,42,Personal Travel,Eco,2173,4,5,4,3,4,4,5,1,1,4,1,5,1,5,1,0.0,satisfied +41219,86748,Female,disloyal Customer,49,Business travel,Business,821,3,3,3,3,2,3,5,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +41220,15666,Male,Loyal Customer,36,Business travel,Business,764,3,3,2,3,2,2,1,5,5,5,5,1,5,1,0,0.0,satisfied +41221,52788,Female,Loyal Customer,54,Business travel,Eco,1874,2,3,3,3,1,4,4,2,2,2,2,3,2,1,69,46.0,neutral or dissatisfied +41222,35482,Female,Loyal Customer,67,Personal Travel,Eco,1041,2,2,2,3,5,2,3,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +41223,123579,Male,Loyal Customer,70,Business travel,Business,3449,3,5,5,5,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +41224,113874,Female,Loyal Customer,35,Personal Travel,Eco,1334,4,4,4,4,5,4,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +41225,76751,Male,Loyal Customer,26,Personal Travel,Eco,205,1,3,1,4,5,1,5,5,2,1,4,2,4,5,0,0.0,neutral or dissatisfied +41226,13280,Male,Loyal Customer,41,Personal Travel,Eco,657,3,4,3,4,4,3,4,4,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +41227,34275,Male,Loyal Customer,41,Business travel,Business,496,2,2,2,2,2,1,1,4,4,4,4,3,4,1,0,0.0,satisfied +41228,87261,Male,Loyal Customer,48,Business travel,Business,577,5,5,5,5,4,4,5,2,2,2,2,3,2,4,30,21.0,satisfied +41229,35427,Female,Loyal Customer,55,Personal Travel,Eco,944,0,2,0,4,2,4,3,3,3,0,3,1,3,3,68,80.0,satisfied +41230,7511,Male,Loyal Customer,49,Business travel,Business,3247,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +41231,28069,Male,Loyal Customer,80,Business travel,Business,2447,1,1,1,1,3,1,3,3,3,3,3,1,3,4,12,0.0,satisfied +41232,31102,Male,disloyal Customer,69,Personal Travel,Eco,1014,2,4,2,4,3,2,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +41233,116043,Female,Loyal Customer,30,Personal Travel,Eco,417,3,5,3,2,4,3,4,4,3,1,2,1,3,4,37,24.0,neutral or dissatisfied +41234,89227,Male,Loyal Customer,67,Personal Travel,Eco,1947,2,2,2,3,3,2,3,3,4,2,2,2,3,3,25,26.0,neutral or dissatisfied +41235,129063,Male,Loyal Customer,57,Personal Travel,Eco,1846,1,4,1,4,1,2,2,2,2,3,3,2,1,2,184,179.0,neutral or dissatisfied +41236,90508,Male,disloyal Customer,23,Business travel,Eco,515,5,2,5,2,2,2,2,2,5,2,4,4,5,2,0,0.0,satisfied +41237,64643,Male,Loyal Customer,57,Business travel,Business,1785,4,4,4,4,5,5,4,4,4,4,4,5,4,4,0,3.0,satisfied +41238,69544,Male,Loyal Customer,30,Business travel,Business,2586,5,5,5,5,5,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +41239,101606,Male,disloyal Customer,55,Business travel,Business,1139,5,5,5,4,5,5,5,5,3,3,5,5,4,5,17,0.0,satisfied +41240,73441,Male,Loyal Customer,11,Personal Travel,Eco,1197,3,4,3,3,4,3,4,4,5,5,3,4,4,4,1,0.0,neutral or dissatisfied +41241,70196,Male,Loyal Customer,44,Business travel,Business,258,1,1,5,1,3,2,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +41242,61341,Female,Loyal Customer,58,Business travel,Business,2804,2,3,2,2,5,5,5,5,5,4,5,4,5,5,5,0.0,satisfied +41243,116014,Female,Loyal Customer,30,Personal Travel,Eco,342,3,5,3,1,5,3,4,5,3,2,4,3,5,5,14,16.0,neutral or dissatisfied +41244,43181,Male,Loyal Customer,31,Business travel,Business,3637,4,4,4,4,4,4,4,4,3,1,5,4,5,4,1,0.0,satisfied +41245,70980,Female,disloyal Customer,18,Business travel,Business,802,0,5,0,2,4,0,4,4,3,2,4,3,4,4,28,25.0,satisfied +41246,39896,Female,Loyal Customer,20,Personal Travel,Eco,272,1,4,1,4,2,1,2,2,3,5,5,4,5,2,0,11.0,neutral or dissatisfied +41247,109809,Female,Loyal Customer,40,Business travel,Business,1204,2,2,2,2,5,4,4,5,5,5,5,5,5,3,44,9.0,satisfied +41248,102815,Male,Loyal Customer,56,Business travel,Business,342,1,0,0,2,3,3,2,4,4,0,5,4,4,3,63,87.0,neutral or dissatisfied +41249,56249,Male,Loyal Customer,35,Business travel,Business,404,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +41250,94886,Male,Loyal Customer,58,Business travel,Business,3591,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +41251,4255,Female,disloyal Customer,25,Business travel,Business,502,3,5,3,4,1,3,1,1,4,4,5,3,4,1,22,58.0,neutral or dissatisfied +41252,93001,Male,Loyal Customer,47,Business travel,Business,1524,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +41253,5054,Female,Loyal Customer,37,Business travel,Eco,235,3,4,4,4,3,3,3,1,2,3,4,3,3,3,154,140.0,neutral or dissatisfied +41254,54806,Female,Loyal Customer,31,Business travel,Business,2652,3,1,1,1,3,3,3,3,1,1,1,1,4,3,8,0.0,neutral or dissatisfied +41255,93810,Female,disloyal Customer,46,Business travel,Business,391,4,4,4,2,5,4,5,5,5,3,4,5,4,5,3,0.0,satisfied +41256,90088,Female,disloyal Customer,36,Business travel,Business,1145,1,1,1,3,3,1,1,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +41257,2585,Male,Loyal Customer,69,Personal Travel,Eco,227,3,4,3,3,2,3,1,2,3,4,3,3,3,2,1,0.0,neutral or dissatisfied +41258,71930,Female,disloyal Customer,24,Business travel,Business,1846,5,0,5,1,3,5,3,3,4,3,5,3,4,3,3,12.0,satisfied +41259,90184,Male,Loyal Customer,32,Personal Travel,Eco,957,3,1,3,3,2,3,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +41260,112655,Male,disloyal Customer,24,Business travel,Eco,723,3,3,3,3,2,3,3,2,5,2,5,5,4,2,32,18.0,neutral or dissatisfied +41261,7437,Female,Loyal Customer,46,Personal Travel,Eco,522,4,4,4,4,3,5,4,2,2,4,2,5,2,3,92,97.0,neutral or dissatisfied +41262,43986,Male,Loyal Customer,36,Business travel,Eco,397,4,3,3,3,4,4,4,4,2,1,4,5,3,4,0,4.0,satisfied +41263,37963,Male,Loyal Customer,56,Business travel,Business,1538,3,3,3,3,5,4,5,3,3,3,3,4,3,3,7,0.0,satisfied +41264,127683,Male,Loyal Customer,56,Personal Travel,Business,2133,3,4,3,3,5,3,4,1,1,3,4,4,1,1,4,0.0,neutral or dissatisfied +41265,5417,Male,Loyal Customer,46,Business travel,Business,589,3,3,3,3,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +41266,75391,Male,disloyal Customer,30,Business travel,Business,2342,3,3,3,2,4,3,4,4,4,2,4,5,4,4,3,0.0,neutral or dissatisfied +41267,129610,Female,Loyal Customer,58,Business travel,Business,2302,1,1,1,1,3,5,4,4,4,4,4,3,4,5,95,127.0,satisfied +41268,83449,Female,Loyal Customer,22,Personal Travel,Business,946,1,5,1,2,3,1,5,3,1,4,1,5,1,3,0,0.0,neutral or dissatisfied +41269,50787,Male,Loyal Customer,28,Personal Travel,Eco,86,3,4,3,5,5,3,5,5,2,1,2,1,1,5,0,0.0,neutral or dissatisfied +41270,50618,Male,Loyal Customer,24,Personal Travel,Eco,110,1,1,1,3,4,1,4,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +41271,113252,Male,disloyal Customer,47,Business travel,Business,397,4,4,4,3,5,4,5,5,5,5,5,4,4,5,0,0.0,satisfied +41272,97363,Male,Loyal Customer,31,Personal Travel,Eco,347,2,1,2,3,4,2,4,4,1,1,3,1,4,4,1,0.0,neutral or dissatisfied +41273,107481,Male,Loyal Customer,54,Business travel,Eco,711,1,5,2,2,1,1,1,1,1,1,3,1,3,1,0,8.0,neutral or dissatisfied +41274,33455,Female,Loyal Customer,9,Personal Travel,Eco,2417,3,4,3,2,3,1,1,1,2,5,4,1,3,1,42,84.0,neutral or dissatisfied +41275,86818,Female,Loyal Customer,20,Business travel,Business,2247,4,4,4,4,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +41276,21219,Female,Loyal Customer,34,Personal Travel,Eco,153,3,3,3,3,3,3,3,3,2,5,2,2,4,3,0,0.0,neutral or dissatisfied +41277,73501,Female,Loyal Customer,40,Business travel,Business,1005,3,3,3,3,3,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +41278,82472,Female,Loyal Customer,23,Personal Travel,Eco,241,4,5,4,2,1,4,1,1,5,3,4,5,5,1,0,0.0,satisfied +41279,53689,Male,Loyal Customer,35,Business travel,Business,2653,2,2,2,2,5,3,3,4,4,4,4,2,4,3,5,3.0,satisfied +41280,57736,Male,Loyal Customer,56,Personal Travel,Eco,1754,5,3,5,3,4,5,4,4,1,2,3,1,3,4,5,0.0,satisfied +41281,24240,Female,Loyal Customer,29,Business travel,Business,1602,2,2,2,2,5,5,3,5,3,3,5,2,3,5,0,0.0,satisfied +41282,14820,Female,disloyal Customer,24,Business travel,Eco,563,3,0,3,5,3,3,3,3,3,4,3,5,2,3,9,0.0,neutral or dissatisfied +41283,45271,Male,Loyal Customer,53,Personal Travel,Business,175,3,5,3,4,4,4,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +41284,7560,Male,Loyal Customer,66,Personal Travel,Eco,606,4,5,4,4,3,4,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +41285,41203,Male,Loyal Customer,56,Business travel,Business,3810,3,3,3,3,5,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +41286,21987,Male,Loyal Customer,10,Personal Travel,Eco,448,3,5,3,5,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +41287,4123,Female,disloyal Customer,37,Business travel,Business,431,2,2,2,3,2,2,2,2,5,5,5,4,5,2,0,7.0,neutral or dissatisfied +41288,38412,Male,Loyal Customer,19,Business travel,Business,1747,4,4,4,4,5,5,5,5,5,2,5,1,2,5,59,55.0,satisfied +41289,63647,Male,disloyal Customer,35,Business travel,Business,651,2,2,2,3,2,2,1,2,5,4,5,3,5,2,16,0.0,neutral or dissatisfied +41290,51047,Male,Loyal Customer,29,Personal Travel,Eco,363,3,1,3,4,1,3,5,1,1,5,4,1,3,1,2,14.0,neutral or dissatisfied +41291,95836,Male,Loyal Customer,52,Business travel,Business,3325,1,1,1,1,2,5,5,4,4,4,4,4,4,3,7,15.0,satisfied +41292,90980,Female,Loyal Customer,49,Business travel,Eco,246,5,1,1,1,1,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +41293,29880,Male,Loyal Customer,46,Business travel,Business,571,1,1,1,1,5,4,4,2,2,2,1,4,4,4,142,,satisfied +41294,20001,Male,Loyal Customer,52,Business travel,Business,646,4,1,1,1,2,4,3,4,4,4,4,2,4,2,65,65.0,neutral or dissatisfied +41295,34425,Female,Loyal Customer,7,Personal Travel,Eco Plus,612,4,5,4,2,1,4,1,1,2,5,1,4,3,1,26,18.0,neutral or dissatisfied +41296,36556,Female,disloyal Customer,22,Business travel,Eco,1121,4,4,4,4,1,4,1,1,4,4,1,3,1,1,28,31.0,neutral or dissatisfied +41297,81689,Female,Loyal Customer,73,Business travel,Eco,507,2,5,5,5,5,3,4,2,2,2,2,2,2,2,39,30.0,neutral or dissatisfied +41298,113035,Male,disloyal Customer,26,Business travel,Business,479,0,0,0,4,4,0,2,4,5,3,4,5,4,4,1,3.0,satisfied +41299,17029,Male,Loyal Customer,64,Personal Travel,Eco,781,1,4,1,4,4,1,4,4,3,2,5,5,5,4,25,21.0,neutral or dissatisfied +41300,89437,Female,Loyal Customer,16,Personal Travel,Eco,134,0,2,0,4,5,0,5,5,2,1,3,1,3,5,0,0.0,satisfied +41301,104518,Male,Loyal Customer,9,Personal Travel,Business,1047,3,5,3,3,3,4,5,5,3,4,4,5,5,5,221,199.0,neutral or dissatisfied +41302,100650,Female,Loyal Customer,9,Personal Travel,Eco Plus,349,2,3,2,4,2,2,2,2,1,1,3,2,4,2,11,5.0,neutral or dissatisfied +41303,106017,Male,Loyal Customer,80,Business travel,Eco Plus,499,4,2,2,2,4,4,4,4,1,5,3,2,4,4,32,41.0,neutral or dissatisfied +41304,98430,Female,Loyal Customer,41,Personal Travel,Eco,1910,3,5,3,1,3,3,3,3,5,5,3,3,4,3,0,0.0,neutral or dissatisfied +41305,53753,Male,Loyal Customer,41,Business travel,Business,1195,2,2,2,2,4,1,4,4,4,4,4,4,4,3,0,0.0,satisfied +41306,12746,Female,Loyal Customer,21,Personal Travel,Eco,803,2,3,2,4,1,2,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +41307,39951,Male,Loyal Customer,52,Personal Travel,Eco,1086,1,5,1,1,3,1,3,3,4,3,4,5,4,3,24,0.0,neutral or dissatisfied +41308,57558,Female,Loyal Customer,28,Business travel,Business,1597,3,3,3,3,5,5,5,5,3,5,5,4,5,5,1,0.0,satisfied +41309,63153,Female,Loyal Customer,47,Business travel,Business,337,0,0,0,3,5,5,4,2,2,2,2,3,2,5,7,6.0,satisfied +41310,58064,Male,Loyal Customer,53,Business travel,Business,1712,1,1,1,1,2,4,5,4,4,4,4,3,4,3,3,7.0,satisfied +41311,102123,Male,Loyal Customer,47,Business travel,Business,1701,1,1,2,1,5,5,5,3,3,4,3,5,3,5,27,28.0,satisfied +41312,60047,Male,Loyal Customer,41,Business travel,Eco Plus,1065,4,1,1,1,4,4,4,4,1,4,2,1,2,4,0,0.0,neutral or dissatisfied +41313,74075,Male,disloyal Customer,25,Business travel,Business,721,0,5,0,2,1,0,1,1,3,5,4,3,5,1,0,0.0,satisfied +41314,19627,Male,Loyal Customer,29,Business travel,Business,1672,4,4,4,4,3,3,3,3,1,5,4,3,3,3,0,0.0,satisfied +41315,126617,Female,Loyal Customer,47,Personal Travel,Eco Plus,1337,1,5,1,5,5,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +41316,6591,Female,Loyal Customer,53,Personal Travel,Eco,618,2,5,2,2,4,5,4,2,2,2,2,4,2,4,0,1.0,neutral or dissatisfied +41317,34302,Male,Loyal Customer,53,Personal Travel,Eco,280,3,2,3,2,4,3,2,4,3,4,2,1,1,4,0,0.0,neutral or dissatisfied +41318,80484,Female,disloyal Customer,45,Business travel,Business,1299,3,3,3,3,1,3,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +41319,2987,Male,Loyal Customer,52,Business travel,Business,3140,5,5,5,5,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +41320,88721,Female,Loyal Customer,37,Personal Travel,Eco,271,3,2,3,3,3,3,3,3,3,2,3,1,2,3,0,0.0,neutral or dissatisfied +41321,94566,Male,Loyal Customer,58,Business travel,Business,3824,1,1,1,1,2,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +41322,53757,Male,Loyal Customer,33,Business travel,Business,3836,5,5,5,5,5,4,5,5,1,2,4,3,4,5,0,0.0,satisfied +41323,1220,Female,Loyal Customer,26,Personal Travel,Eco,247,3,2,3,4,5,3,5,5,1,4,3,1,3,5,2,0.0,neutral or dissatisfied +41324,40709,Female,Loyal Customer,17,Business travel,Business,558,4,4,4,4,4,5,4,4,2,2,2,3,2,4,40,21.0,satisfied +41325,103317,Male,Loyal Customer,55,Business travel,Eco,1139,1,1,1,1,1,1,1,1,2,2,3,3,3,1,1,0.0,neutral or dissatisfied +41326,110689,Male,Loyal Customer,51,Personal Travel,Eco,837,2,1,2,3,1,2,1,1,4,4,4,2,3,1,29,17.0,neutral or dissatisfied +41327,64484,Female,disloyal Customer,21,Business travel,Eco,354,4,0,4,5,4,4,5,4,4,3,4,5,4,4,0,0.0,satisfied +41328,34955,Male,Loyal Customer,43,Personal Travel,Eco,187,1,5,1,3,2,1,1,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +41329,105337,Female,Loyal Customer,49,Business travel,Business,2265,3,3,3,3,3,4,4,5,5,5,5,5,5,5,1,3.0,satisfied +41330,80336,Male,Loyal Customer,55,Personal Travel,Eco Plus,746,2,4,2,4,4,2,4,4,2,4,4,1,2,4,0,0.0,neutral or dissatisfied +41331,33709,Male,Loyal Customer,36,Business travel,Eco,499,3,3,3,3,3,3,3,3,4,4,3,1,4,3,19,46.0,neutral or dissatisfied +41332,48594,Female,Loyal Customer,31,Personal Travel,Eco,844,4,2,4,2,4,4,4,4,3,5,2,4,2,4,40,17.0,neutral or dissatisfied +41333,80483,Male,Loyal Customer,46,Business travel,Business,3638,5,5,5,5,4,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +41334,129360,Male,Loyal Customer,58,Business travel,Business,2454,4,4,4,4,4,3,4,2,2,2,2,3,2,4,1,0.0,satisfied +41335,110770,Female,disloyal Customer,50,Business travel,Business,997,4,4,4,3,1,4,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +41336,129504,Female,Loyal Customer,24,Business travel,Eco,1846,2,4,2,4,2,2,2,2,1,5,2,1,3,2,0,21.0,neutral or dissatisfied +41337,24780,Female,Loyal Customer,36,Business travel,Eco,128,4,4,5,4,4,4,4,4,3,4,3,4,1,4,4,3.0,satisfied +41338,5986,Male,Loyal Customer,34,Business travel,Business,2079,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,21.0,satisfied +41339,57510,Female,Loyal Customer,52,Business travel,Business,3399,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,4.0,satisfied +41340,103401,Female,disloyal Customer,37,Business travel,Eco,237,1,1,1,1,2,1,2,2,3,4,2,2,2,2,20,17.0,neutral or dissatisfied +41341,122327,Male,disloyal Customer,17,Business travel,Eco,541,1,2,0,3,2,0,2,2,2,3,3,1,3,2,8,0.0,neutral or dissatisfied +41342,60276,Male,Loyal Customer,25,Business travel,Business,2583,3,1,1,1,3,3,3,1,2,2,2,3,2,3,17,19.0,neutral or dissatisfied +41343,83358,Female,Loyal Customer,35,Business travel,Business,2530,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +41344,101252,Male,Loyal Customer,27,Personal Travel,Eco Plus,1587,5,5,5,3,1,5,1,1,4,5,4,5,5,1,0,0.0,satisfied +41345,61690,Male,disloyal Customer,45,Business travel,Eco,1379,2,2,2,3,1,2,1,1,1,5,3,3,2,1,70,53.0,neutral or dissatisfied +41346,75951,Female,Loyal Customer,35,Business travel,Business,1990,0,0,0,3,5,5,5,1,1,1,1,4,1,4,0,0.0,satisfied +41347,89335,Male,Loyal Customer,23,Business travel,Business,1541,5,1,5,5,5,5,5,5,5,2,5,3,5,5,3,0.0,satisfied +41348,124707,Female,Loyal Customer,34,Personal Travel,Eco,399,4,5,4,2,2,4,5,2,5,5,2,2,3,2,0,0.0,satisfied +41349,10521,Male,Loyal Customer,59,Business travel,Business,295,3,3,3,3,5,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +41350,5181,Female,Loyal Customer,44,Business travel,Business,3250,5,3,5,5,2,5,5,5,5,5,5,4,5,3,10,16.0,satisfied +41351,71715,Female,Loyal Customer,56,Business travel,Business,1007,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +41352,41330,Female,disloyal Customer,22,Business travel,Eco,689,4,4,4,4,3,4,3,3,4,1,3,5,3,3,7,0.0,satisfied +41353,100100,Female,Loyal Customer,42,Business travel,Business,725,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +41354,31064,Female,Loyal Customer,61,Business travel,Business,462,4,3,3,3,1,3,4,4,4,4,4,1,4,2,0,4.0,neutral or dissatisfied +41355,105465,Female,Loyal Customer,64,Personal Travel,Business,495,3,4,3,5,5,4,5,4,4,3,2,5,4,3,8,11.0,neutral or dissatisfied +41356,113687,Female,Loyal Customer,13,Personal Travel,Eco,397,4,4,3,1,4,3,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +41357,93730,Male,Loyal Customer,60,Personal Travel,Eco,630,3,5,3,2,1,3,1,1,5,4,2,3,2,1,17,10.0,neutral or dissatisfied +41358,89147,Female,disloyal Customer,37,Business travel,Eco,447,3,2,3,3,4,3,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +41359,76866,Male,Loyal Customer,39,Business travel,Eco,1927,1,1,1,1,1,1,1,1,3,4,2,3,3,1,0,0.0,neutral or dissatisfied +41360,37941,Male,Loyal Customer,44,Business travel,Eco Plus,1065,4,1,5,1,4,4,4,4,5,2,3,5,3,4,28,0.0,satisfied +41361,9433,Male,Loyal Customer,44,Business travel,Eco,299,2,4,4,4,2,2,2,2,3,1,4,3,3,2,0,0.0,neutral or dissatisfied +41362,105496,Female,Loyal Customer,55,Personal Travel,Eco,516,2,4,2,3,1,5,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +41363,67158,Male,disloyal Customer,18,Business travel,Eco,1017,1,1,1,3,1,1,1,1,3,5,2,3,3,1,22,17.0,neutral or dissatisfied +41364,88706,Male,Loyal Customer,14,Personal Travel,Eco,545,3,4,1,5,4,1,4,4,2,2,2,5,4,4,28,29.0,neutral or dissatisfied +41365,58271,Female,Loyal Customer,60,Business travel,Business,3507,5,5,5,5,2,5,4,3,3,3,3,3,3,5,2,0.0,satisfied +41366,96907,Female,Loyal Customer,36,Personal Travel,Eco,928,3,3,3,4,5,3,5,5,1,2,4,2,4,5,4,7.0,neutral or dissatisfied +41367,128985,Male,Loyal Customer,39,Personal Travel,Eco,414,2,4,2,1,1,2,1,1,4,2,3,4,4,1,0,0.0,neutral or dissatisfied +41368,28708,Male,Loyal Customer,32,Business travel,Eco,2717,5,5,5,5,5,5,5,1,5,5,1,5,4,5,0,10.0,satisfied +41369,47429,Female,Loyal Customer,60,Business travel,Eco,101,5,1,2,1,2,3,5,5,5,5,5,4,5,1,0,0.0,satisfied +41370,9,Male,Loyal Customer,50,Business travel,Business,2607,4,1,1,1,3,2,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +41371,11286,Female,Loyal Customer,53,Personal Travel,Eco,201,4,2,4,4,2,4,4,5,5,4,3,4,5,4,0,6.0,neutral or dissatisfied +41372,113351,Female,Loyal Customer,49,Business travel,Business,226,0,0,0,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +41373,73206,Female,Loyal Customer,70,Personal Travel,Eco,1258,3,2,3,1,5,1,1,4,4,3,2,1,4,2,27,21.0,neutral or dissatisfied +41374,43357,Male,Loyal Customer,32,Business travel,Business,1856,1,1,1,1,5,5,5,5,3,2,2,2,3,5,15,4.0,satisfied +41375,92711,Male,Loyal Customer,43,Personal Travel,Eco,2153,1,2,1,4,1,1,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +41376,54436,Female,Loyal Customer,36,Business travel,Eco Plus,305,4,4,4,4,4,4,4,4,4,1,2,3,3,4,26,21.0,satisfied +41377,90729,Male,disloyal Customer,54,Business travel,Business,240,3,2,2,4,4,3,2,4,5,3,4,3,5,4,0,15.0,neutral or dissatisfied +41378,94605,Male,disloyal Customer,38,Business travel,Eco,239,4,2,4,3,4,4,5,4,3,4,4,1,4,4,31,24.0,neutral or dissatisfied +41379,10503,Female,Loyal Customer,36,Business travel,Business,517,1,1,1,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +41380,111700,Male,Loyal Customer,52,Business travel,Business,3073,4,4,3,4,2,4,5,3,3,3,3,4,3,5,30,17.0,satisfied +41381,74258,Female,Loyal Customer,39,Business travel,Business,1810,1,1,1,1,2,4,5,4,4,4,4,4,4,5,11,0.0,satisfied +41382,79972,Male,disloyal Customer,26,Business travel,Eco,635,3,2,3,3,4,3,4,4,4,2,3,1,3,4,19,11.0,neutral or dissatisfied +41383,70470,Female,Loyal Customer,52,Business travel,Business,3178,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +41384,92302,Female,Loyal Customer,30,Business travel,Business,2615,1,5,5,5,1,1,1,2,2,3,4,1,3,1,47,41.0,neutral or dissatisfied +41385,13879,Female,Loyal Customer,30,Business travel,Business,578,2,4,4,4,2,2,2,2,4,3,1,2,1,2,0,5.0,neutral or dissatisfied +41386,93152,Female,Loyal Customer,13,Business travel,Eco,1075,3,1,1,1,3,3,2,3,2,4,3,2,4,3,0,2.0,neutral or dissatisfied +41387,21638,Female,Loyal Customer,41,Personal Travel,Eco,780,3,1,3,3,1,3,1,1,2,2,3,1,3,1,121,111.0,neutral or dissatisfied +41388,127003,Female,Loyal Customer,49,Business travel,Business,3767,5,5,5,5,4,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +41389,74756,Female,Loyal Customer,32,Personal Travel,Eco,1205,2,2,2,2,3,2,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +41390,34612,Male,Loyal Customer,66,Personal Travel,Eco,1598,1,4,1,3,2,1,2,2,4,2,4,5,5,2,120,97.0,neutral or dissatisfied +41391,84767,Male,Loyal Customer,60,Business travel,Business,547,3,3,3,3,2,4,4,4,4,4,4,4,4,4,5,0.0,satisfied +41392,84755,Male,Loyal Customer,29,Business travel,Business,2615,5,5,5,5,4,4,4,4,5,4,4,4,5,4,12,7.0,satisfied +41393,28526,Female,disloyal Customer,23,Business travel,Eco,1316,1,1,1,3,5,1,5,5,5,4,3,1,4,5,5,0.0,neutral or dissatisfied +41394,98000,Male,Loyal Customer,29,Business travel,Eco Plus,612,3,5,5,5,3,3,3,3,2,2,3,3,3,3,31,36.0,neutral or dissatisfied +41395,59803,Female,Loyal Customer,41,Business travel,Business,1065,5,5,5,5,4,5,5,5,5,5,5,3,5,3,50,17.0,satisfied +41396,111445,Female,Loyal Customer,31,Business travel,Business,836,4,5,5,5,4,4,4,4,4,5,3,3,3,4,0,0.0,neutral or dissatisfied +41397,58109,Female,Loyal Customer,13,Personal Travel,Eco,612,2,3,3,3,1,3,1,1,2,4,3,1,3,1,73,61.0,neutral or dissatisfied +41398,109073,Male,Loyal Customer,17,Personal Travel,Eco,849,4,4,4,4,4,4,4,4,5,4,5,4,5,4,12,11.0,satisfied +41399,78052,Male,Loyal Customer,29,Personal Travel,Eco,214,2,3,2,1,4,2,4,4,4,5,3,2,1,4,0,0.0,neutral or dissatisfied +41400,10245,Female,Loyal Customer,65,Personal Travel,Business,482,3,2,3,3,4,4,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +41401,29258,Female,Loyal Customer,27,Business travel,Business,3160,3,2,3,3,5,5,5,5,2,3,3,1,2,5,0,8.0,satisfied +41402,98421,Female,disloyal Customer,22,Business travel,Business,2176,0,2,0,1,0,3,5,4,3,4,5,5,5,5,1,0.0,satisfied +41403,91110,Female,Loyal Customer,57,Personal Travel,Eco,404,3,5,3,2,4,4,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +41404,81951,Male,Loyal Customer,45,Business travel,Business,1532,3,3,3,3,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +41405,73596,Female,Loyal Customer,46,Business travel,Business,192,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +41406,16065,Female,disloyal Customer,14,Business travel,Eco,501,4,2,4,3,4,4,5,4,3,2,3,2,4,4,0,8.0,neutral or dissatisfied +41407,93268,Female,disloyal Customer,20,Business travel,Eco,806,2,2,2,2,4,2,4,4,4,4,5,5,4,4,7,5.0,neutral or dissatisfied +41408,73846,Male,Loyal Customer,55,Business travel,Business,1709,3,3,5,3,3,4,4,4,4,4,4,4,4,4,28,34.0,satisfied +41409,38209,Male,Loyal Customer,33,Business travel,Eco Plus,1237,4,3,3,3,4,4,4,4,2,3,1,1,5,4,0,5.0,satisfied +41410,80754,Male,Loyal Customer,18,Business travel,Eco Plus,448,2,2,5,2,2,3,3,2,1,5,4,4,3,2,0,2.0,neutral or dissatisfied +41411,126450,Male,Loyal Customer,47,Business travel,Business,3847,0,0,0,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +41412,65532,Female,Loyal Customer,49,Personal Travel,Eco,1616,1,5,2,4,2,4,5,1,1,2,1,5,1,3,0,24.0,neutral or dissatisfied +41413,115838,Male,disloyal Customer,59,Business travel,Eco,337,4,0,4,4,1,4,1,1,5,2,3,3,2,1,2,5.0,neutral or dissatisfied +41414,88285,Female,Loyal Customer,28,Business travel,Business,2033,2,4,4,4,2,2,2,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +41415,77365,Male,Loyal Customer,22,Business travel,Eco,590,2,5,3,5,2,4,2,4,2,4,3,2,3,2,163,170.0,neutral or dissatisfied +41416,34519,Male,Loyal Customer,21,Personal Travel,Eco,1521,1,3,1,2,5,1,5,5,3,2,1,3,5,5,0,8.0,neutral or dissatisfied +41417,92181,Female,disloyal Customer,39,Business travel,Business,1979,2,2,2,1,2,2,2,2,4,3,4,3,5,2,0,2.0,neutral or dissatisfied +41418,65116,Female,Loyal Customer,34,Personal Travel,Eco,190,3,4,3,3,2,3,2,2,1,2,3,4,4,2,124,128.0,neutral or dissatisfied +41419,120867,Male,disloyal Customer,37,Business travel,Business,861,5,5,5,3,1,5,1,1,4,4,5,4,4,1,65,53.0,satisfied +41420,2560,Male,Loyal Customer,64,Business travel,Eco,227,2,3,5,3,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +41421,118945,Female,Loyal Customer,52,Business travel,Business,682,2,5,5,5,4,2,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +41422,26237,Male,Loyal Customer,67,Personal Travel,Eco,515,3,4,3,3,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +41423,35884,Female,Loyal Customer,60,Personal Travel,Eco,1065,2,5,3,2,3,5,5,2,2,3,2,4,2,4,4,5.0,neutral or dissatisfied +41424,100024,Male,Loyal Customer,52,Business travel,Eco,281,2,2,2,2,1,2,1,1,2,4,3,1,3,1,32,24.0,neutral or dissatisfied +41425,105821,Male,Loyal Customer,45,Personal Travel,Eco,925,2,1,2,2,4,2,4,4,1,4,2,1,2,4,0,11.0,neutral or dissatisfied +41426,101508,Male,Loyal Customer,45,Business travel,Business,1984,2,2,2,2,1,3,4,2,2,2,2,4,2,2,40,36.0,neutral or dissatisfied +41427,9793,Male,Loyal Customer,39,Business travel,Business,2967,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +41428,56061,Female,Loyal Customer,64,Personal Travel,Eco,2475,3,5,3,1,3,1,1,5,4,5,1,1,1,1,0,0.0,neutral or dissatisfied +41429,23648,Female,Loyal Customer,49,Business travel,Business,251,2,3,4,3,2,2,2,2,2,4,3,2,3,2,141,143.0,neutral or dissatisfied +41430,82000,Male,Loyal Customer,39,Business travel,Business,1589,2,2,2,2,3,3,5,4,4,5,4,3,4,5,2,0.0,satisfied +41431,11361,Female,Loyal Customer,24,Personal Travel,Eco,301,3,5,3,4,2,3,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +41432,81105,Female,Loyal Customer,33,Business travel,Business,991,3,4,3,3,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +41433,75007,Female,Loyal Customer,60,Business travel,Business,236,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +41434,86374,Male,Loyal Customer,57,Business travel,Business,762,2,3,2,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +41435,23752,Female,disloyal Customer,43,Business travel,Eco,1048,2,2,2,4,5,2,1,5,1,3,3,2,2,5,0,0.0,neutral or dissatisfied +41436,117288,Female,disloyal Customer,27,Business travel,Business,304,0,0,0,1,3,0,5,3,5,5,5,3,4,3,9,0.0,satisfied +41437,87250,Female,Loyal Customer,46,Business travel,Business,2624,1,2,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +41438,19202,Male,Loyal Customer,70,Personal Travel,Eco,542,2,3,2,4,3,2,3,3,1,3,5,4,4,3,0,0.0,neutral or dissatisfied +41439,73921,Female,Loyal Customer,25,Business travel,Business,2342,2,2,4,2,4,4,4,3,2,4,4,4,5,4,0,9.0,satisfied +41440,12561,Female,Loyal Customer,70,Personal Travel,Eco,871,5,4,5,3,1,4,2,4,4,5,2,1,4,2,0,0.0,satisfied +41441,19785,Male,Loyal Customer,25,Business travel,Business,667,2,3,3,3,2,2,2,2,4,2,2,3,2,2,73,55.0,neutral or dissatisfied +41442,56166,Male,Loyal Customer,37,Business travel,Eco,1400,4,2,4,2,4,3,4,4,4,2,3,3,3,4,1,0.0,neutral or dissatisfied +41443,95597,Male,Loyal Customer,26,Business travel,Business,670,3,3,3,3,3,3,3,3,1,5,3,2,2,3,0,0.0,neutral or dissatisfied +41444,26595,Female,Loyal Customer,49,Business travel,Business,515,1,1,1,1,1,1,4,4,4,4,4,2,4,4,0,0.0,satisfied +41445,43381,Female,Loyal Customer,46,Personal Travel,Eco,436,3,5,3,3,4,5,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +41446,126737,Female,Loyal Customer,32,Business travel,Eco,2402,0,0,0,4,3,0,3,3,5,2,2,3,4,3,25,36.0,satisfied +41447,38147,Female,Loyal Customer,66,Personal Travel,Eco,1185,2,5,2,2,2,4,4,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +41448,122618,Male,Loyal Customer,12,Personal Travel,Eco,728,2,3,2,3,4,2,4,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +41449,115169,Male,disloyal Customer,20,Business travel,Eco,417,1,3,1,3,2,1,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +41450,80187,Male,Loyal Customer,35,Personal Travel,Eco,2586,2,5,1,4,1,3,3,3,2,5,4,3,5,3,0,0.0,neutral or dissatisfied +41451,21854,Female,Loyal Customer,48,Business travel,Eco,448,4,4,4,4,4,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +41452,22355,Female,Loyal Customer,36,Business travel,Business,2196,2,2,1,2,2,3,4,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +41453,83510,Female,Loyal Customer,61,Personal Travel,Eco,946,2,4,2,3,1,4,4,5,5,2,5,4,5,1,3,36.0,neutral or dissatisfied +41454,33549,Male,Loyal Customer,43,Business travel,Business,3792,3,3,3,3,1,1,3,3,3,3,3,3,3,4,0,0.0,satisfied +41455,66758,Male,Loyal Customer,36,Personal Travel,Eco,978,5,4,5,3,4,5,4,4,3,2,4,3,4,4,0,0.0,satisfied +41456,94460,Male,Loyal Customer,36,Business travel,Business,1689,3,1,1,1,2,2,3,4,4,4,3,2,4,3,0,4.0,neutral or dissatisfied +41457,11051,Female,Loyal Customer,34,Personal Travel,Eco,216,3,0,3,1,3,3,3,3,5,4,5,4,1,3,0,8.0,neutral or dissatisfied +41458,127025,Female,disloyal Customer,27,Business travel,Business,647,2,2,2,5,5,2,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +41459,111829,Female,Loyal Customer,56,Business travel,Business,1605,1,1,3,1,5,5,5,5,5,4,4,5,5,5,190,206.0,satisfied +41460,44140,Female,disloyal Customer,35,Business travel,Eco,98,3,5,3,4,4,3,4,4,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +41461,8535,Female,Loyal Customer,51,Business travel,Business,109,5,5,5,5,3,4,4,4,4,4,5,4,4,5,122,121.0,satisfied +41462,5526,Female,Loyal Customer,67,Business travel,Eco,404,2,2,2,2,3,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +41463,839,Female,Loyal Customer,45,Business travel,Business,2708,2,5,5,5,5,3,3,2,2,3,2,2,2,1,4,0.0,neutral or dissatisfied +41464,52716,Male,Loyal Customer,55,Business travel,Eco Plus,1162,5,3,3,3,5,5,5,5,4,5,1,3,2,5,0,0.0,satisfied +41465,30047,Male,Loyal Customer,32,Business travel,Business,82,2,2,2,2,5,5,3,5,1,5,5,5,1,5,0,0.0,satisfied +41466,114023,Female,Loyal Customer,25,Business travel,Business,1855,3,3,3,3,5,4,5,5,3,4,3,3,4,5,21,0.0,satisfied +41467,91939,Female,Loyal Customer,19,Business travel,Business,2475,4,4,4,4,4,4,4,4,5,4,1,3,4,4,0,0.0,satisfied +41468,129394,Male,Loyal Customer,60,Business travel,Business,236,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +41469,43333,Male,Loyal Customer,56,Business travel,Business,1679,2,5,5,5,2,3,4,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +41470,20609,Female,Loyal Customer,43,Business travel,Eco,864,5,2,2,2,3,3,5,5,5,5,5,5,5,1,106,109.0,satisfied +41471,116329,Female,Loyal Customer,41,Personal Travel,Eco,358,4,4,4,4,5,4,1,5,1,2,4,5,5,5,9,0.0,satisfied +41472,74526,Female,disloyal Customer,28,Business travel,Business,1438,3,3,3,2,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +41473,84754,Male,disloyal Customer,52,Business travel,Business,547,3,3,3,4,4,3,4,4,4,5,5,4,5,4,0,0.0,satisfied +41474,126790,Female,disloyal Customer,31,Business travel,Business,2077,3,3,3,3,4,3,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +41475,108718,Male,disloyal Customer,10,Business travel,Business,591,1,4,1,4,1,1,1,1,2,5,4,4,4,1,44,57.0,neutral or dissatisfied +41476,62137,Female,Loyal Customer,47,Business travel,Business,2454,1,1,4,1,5,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +41477,67571,Female,Loyal Customer,24,Business travel,Business,1464,5,5,5,5,4,5,4,4,4,3,5,4,5,4,38,35.0,satisfied +41478,29834,Male,disloyal Customer,24,Business travel,Eco,261,2,3,2,3,3,2,1,3,3,5,2,4,3,3,0,0.0,neutral or dissatisfied +41479,121275,Male,Loyal Customer,53,Business travel,Business,2075,1,1,1,1,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +41480,89426,Female,Loyal Customer,23,Business travel,Eco,134,4,5,5,5,4,4,3,4,3,3,5,1,1,4,0,0.0,satisfied +41481,128464,Male,Loyal Customer,8,Personal Travel,Eco,325,4,4,4,5,2,4,2,2,1,1,1,5,2,2,3,11.0,satisfied +41482,30269,Female,Loyal Customer,50,Business travel,Business,1024,3,3,3,3,5,4,3,4,4,4,4,1,4,1,9,0.0,satisfied +41483,116065,Male,Loyal Customer,52,Personal Travel,Eco,417,2,3,2,1,2,2,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +41484,91400,Male,Loyal Customer,16,Personal Travel,Eco,2342,3,3,2,3,3,2,3,3,3,4,2,2,3,3,40,34.0,neutral or dissatisfied +41485,40496,Male,Loyal Customer,27,Personal Travel,Eco,290,2,5,2,5,5,2,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +41486,46039,Female,Loyal Customer,48,Business travel,Business,3889,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,11.0,satisfied +41487,9255,Male,Loyal Customer,28,Personal Travel,Eco,177,2,4,2,1,2,2,5,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +41488,261,Female,Loyal Customer,61,Personal Travel,Eco,612,2,4,3,4,1,1,2,2,2,3,2,3,2,4,6,6.0,neutral or dissatisfied +41489,107910,Male,disloyal Customer,26,Business travel,Eco,861,3,4,4,4,4,1,1,1,2,3,3,1,3,1,201,195.0,neutral or dissatisfied +41490,33109,Male,Loyal Customer,38,Personal Travel,Eco,101,2,5,0,5,1,0,1,1,3,4,5,3,4,1,0,0.0,neutral or dissatisfied +41491,22246,Male,Loyal Customer,25,Business travel,Business,208,3,3,3,3,5,5,4,5,3,5,3,1,1,5,0,0.0,satisfied +41492,110906,Male,Loyal Customer,46,Business travel,Eco,406,2,3,3,3,2,2,2,2,2,3,3,1,2,2,0,0.0,neutral or dissatisfied +41493,92421,Female,Loyal Customer,55,Business travel,Business,1892,4,4,4,4,4,4,4,4,4,4,4,5,4,5,1,2.0,satisfied +41494,63577,Female,Loyal Customer,47,Business travel,Business,2133,2,4,4,4,3,3,3,2,2,3,2,4,2,1,26,0.0,neutral or dissatisfied +41495,4768,Male,Loyal Customer,47,Business travel,Business,3602,1,1,1,1,5,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +41496,80606,Male,Loyal Customer,38,Business travel,Business,2403,2,2,2,2,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +41497,116861,Female,Loyal Customer,40,Business travel,Business,3644,1,1,1,1,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +41498,11648,Female,Loyal Customer,49,Business travel,Business,3470,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +41499,125796,Male,Loyal Customer,58,Business travel,Business,2316,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +41500,76423,Female,disloyal Customer,40,Business travel,Business,405,2,2,2,4,3,2,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +41501,80922,Male,disloyal Customer,34,Business travel,Business,341,1,1,1,3,5,1,4,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +41502,32684,Female,disloyal Customer,57,Business travel,Eco,101,2,0,2,5,5,2,5,5,4,4,3,4,3,5,0,0.0,neutral or dissatisfied +41503,116551,Female,Loyal Customer,51,Personal Travel,Eco,362,3,5,4,5,2,4,4,1,1,4,1,3,1,5,15,11.0,neutral or dissatisfied +41504,104321,Female,Loyal Customer,53,Business travel,Business,3536,1,1,1,1,4,4,4,4,2,4,5,4,5,4,352,335.0,satisfied +41505,85950,Male,Loyal Customer,54,Business travel,Business,554,3,3,3,3,2,5,4,3,3,3,3,4,3,5,3,0.0,satisfied +41506,66520,Female,disloyal Customer,20,Business travel,Business,447,5,4,5,2,5,5,5,5,5,2,5,5,4,5,4,11.0,satisfied +41507,71654,Male,Loyal Customer,33,Personal Travel,Eco,1005,1,5,1,5,1,1,1,1,5,3,5,5,5,1,6,0.0,neutral or dissatisfied +41508,91132,Male,Loyal Customer,22,Personal Travel,Eco,270,2,0,2,3,1,2,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +41509,20078,Male,Loyal Customer,27,Business travel,Eco Plus,738,4,1,1,1,4,4,4,4,4,3,2,4,4,4,96,90.0,satisfied +41510,69900,Male,Loyal Customer,34,Business travel,Business,1671,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +41511,36092,Male,Loyal Customer,65,Personal Travel,Eco,474,2,4,2,3,4,2,4,4,4,2,5,5,1,4,0,0.0,neutral or dissatisfied +41512,19404,Male,Loyal Customer,15,Personal Travel,Eco Plus,261,3,5,3,2,4,3,4,4,3,1,4,4,5,4,0,0.0,neutral or dissatisfied +41513,19138,Female,Loyal Customer,36,Business travel,Eco Plus,323,5,1,1,1,5,5,5,5,2,1,5,5,4,5,0,0.0,satisfied +41514,7187,Female,disloyal Customer,36,Business travel,Eco,139,4,3,4,3,3,4,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +41515,61383,Male,Loyal Customer,55,Business travel,Business,679,3,3,5,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +41516,124008,Male,Loyal Customer,32,Business travel,Business,184,4,1,1,1,3,3,4,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +41517,82728,Female,Loyal Customer,43,Business travel,Business,1759,2,2,2,2,5,4,5,5,5,5,5,3,5,5,106,110.0,satisfied +41518,4088,Male,Loyal Customer,66,Personal Travel,Business,431,4,5,4,1,2,4,4,3,3,4,1,5,3,5,0,0.0,satisfied +41519,45115,Male,disloyal Customer,30,Business travel,Eco,157,3,3,3,4,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +41520,92659,Female,Loyal Customer,19,Personal Travel,Eco,453,3,3,3,3,1,3,1,1,3,2,4,2,4,1,0,0.0,neutral or dissatisfied +41521,52282,Female,disloyal Customer,26,Business travel,Eco,451,2,5,2,3,2,2,4,2,3,5,3,2,2,2,5,3.0,neutral or dissatisfied +41522,44367,Male,Loyal Customer,57,Personal Travel,Eco,596,2,5,2,3,2,2,2,2,4,4,5,5,3,2,0,0.0,neutral or dissatisfied +41523,47223,Male,Loyal Customer,8,Personal Travel,Eco,748,4,1,4,1,3,4,3,3,3,5,1,3,1,3,23,19.0,neutral or dissatisfied +41524,124833,Female,Loyal Customer,11,Personal Travel,Eco,280,1,3,2,4,2,2,2,2,2,3,1,2,5,2,0,27.0,neutral or dissatisfied +41525,67858,Female,Loyal Customer,37,Personal Travel,Eco,1171,2,5,2,2,4,2,4,4,5,5,3,3,5,4,0,0.0,neutral or dissatisfied +41526,9921,Male,disloyal Customer,21,Business travel,Eco,515,3,4,3,3,3,3,3,3,1,4,4,2,4,3,16,12.0,neutral or dissatisfied +41527,26326,Female,Loyal Customer,16,Personal Travel,Eco,892,1,5,1,3,3,1,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +41528,117886,Female,disloyal Customer,38,Business travel,Business,255,1,1,1,2,4,1,4,4,3,5,5,3,5,4,0,8.0,neutral or dissatisfied +41529,95582,Male,disloyal Customer,20,Business travel,Eco,670,4,4,4,3,4,4,3,4,3,2,4,5,5,4,0,0.0,satisfied +41530,80944,Male,Loyal Customer,11,Personal Travel,Eco,341,1,5,1,2,4,1,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +41531,5057,Male,Loyal Customer,66,Business travel,Business,3559,2,2,2,2,2,4,3,3,3,3,2,4,3,2,0,14.0,neutral or dissatisfied +41532,47124,Female,Loyal Customer,21,Business travel,Business,3668,5,5,4,5,5,5,5,5,3,2,4,5,4,5,2,0.0,satisfied +41533,8934,Female,Loyal Customer,70,Business travel,Business,2478,3,3,3,3,5,4,5,5,5,4,5,3,5,5,0,7.0,satisfied +41534,114155,Female,Loyal Customer,53,Business travel,Business,3690,4,4,4,4,4,5,4,4,4,4,4,5,4,5,68,59.0,satisfied +41535,99350,Female,Loyal Customer,16,Business travel,Business,1771,1,1,5,1,1,1,1,1,3,4,4,4,4,1,0,15.0,neutral or dissatisfied +41536,17623,Female,Loyal Customer,30,Personal Travel,Eco,622,1,4,1,3,5,1,4,5,3,2,5,5,1,5,0,0.0,neutral or dissatisfied +41537,52560,Female,Loyal Customer,38,Business travel,Eco,160,4,5,3,5,4,4,4,4,2,3,4,5,3,4,0,2.0,satisfied +41538,119725,Male,Loyal Customer,42,Business travel,Eco,1303,1,1,1,1,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +41539,5135,Male,Loyal Customer,56,Business travel,Business,184,0,4,0,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +41540,62067,Female,Loyal Customer,45,Personal Travel,Eco,2475,3,4,3,5,4,4,5,4,4,3,4,5,4,5,0,4.0,neutral or dissatisfied +41541,81511,Male,Loyal Customer,20,Personal Travel,Eco Plus,528,3,3,3,1,3,3,2,3,3,2,5,3,3,3,0,0.0,neutral or dissatisfied +41542,17508,Male,Loyal Customer,49,Business travel,Eco,352,4,2,2,2,4,4,4,4,1,3,3,3,4,4,0,0.0,satisfied +41543,81189,Female,Loyal Customer,63,Personal Travel,Eco,726,4,5,4,3,4,3,3,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +41544,99532,Male,Loyal Customer,43,Personal Travel,Business,829,3,4,3,1,3,4,4,4,4,3,4,5,4,4,1,8.0,neutral or dissatisfied +41545,124048,Female,Loyal Customer,26,Personal Travel,Eco Plus,184,1,4,1,2,5,1,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +41546,120418,Male,Loyal Customer,33,Business travel,Business,366,4,4,2,4,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +41547,28158,Female,disloyal Customer,37,Business travel,Eco,434,3,0,4,2,4,4,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +41548,44202,Female,Loyal Customer,64,Personal Travel,Eco,157,2,2,2,3,5,4,4,2,2,2,2,3,2,4,0,1.0,neutral or dissatisfied +41549,40650,Male,Loyal Customer,48,Business travel,Business,532,1,1,1,1,2,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +41550,14888,Male,disloyal Customer,23,Business travel,Eco,296,5,4,5,3,2,5,1,2,4,3,3,2,1,2,0,0.0,satisfied +41551,78928,Female,Loyal Customer,53,Business travel,Business,500,4,4,4,4,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +41552,83909,Female,Loyal Customer,41,Business travel,Business,2328,3,3,4,3,5,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +41553,24111,Male,disloyal Customer,13,Business travel,Eco,584,2,2,2,2,5,2,5,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +41554,110178,Female,Loyal Customer,40,Personal Travel,Eco,882,2,2,1,4,2,1,2,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +41555,50464,Male,disloyal Customer,80,Business travel,Eco,337,3,0,4,4,3,4,3,3,2,5,4,4,2,3,0,0.0,neutral or dissatisfied +41556,24214,Female,Loyal Customer,27,Business travel,Business,3374,0,4,0,5,5,5,5,5,3,3,1,4,2,5,0,0.0,satisfied +41557,98732,Female,Loyal Customer,35,Business travel,Business,2746,1,1,1,1,2,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +41558,18927,Female,Loyal Customer,41,Personal Travel,Eco,551,3,5,3,3,2,3,2,2,4,2,4,5,1,2,0,0.0,neutral or dissatisfied +41559,106356,Female,Loyal Customer,60,Business travel,Business,488,4,4,4,4,2,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +41560,108504,Male,Loyal Customer,43,Personal Travel,Eco,287,2,1,3,2,4,3,5,4,3,5,2,3,2,4,9,8.0,neutral or dissatisfied +41561,26713,Male,Loyal Customer,47,Personal Travel,Eco,404,2,5,2,2,5,2,2,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +41562,71491,Female,disloyal Customer,27,Business travel,Business,1182,2,2,2,4,5,2,5,5,3,3,5,3,4,5,15,1.0,neutral or dissatisfied +41563,125664,Male,Loyal Customer,25,Business travel,Business,1846,4,4,4,4,5,5,5,5,4,4,4,5,4,5,4,0.0,satisfied +41564,74142,Female,Loyal Customer,56,Business travel,Eco,641,2,3,4,4,2,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +41565,116917,Male,Loyal Customer,54,Business travel,Business,370,2,2,2,2,4,5,5,4,4,4,4,4,4,5,22,16.0,satisfied +41566,11222,Male,Loyal Customer,64,Personal Travel,Eco,301,1,4,1,2,5,1,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +41567,86529,Female,Loyal Customer,39,Personal Travel,Eco,762,3,3,3,4,2,3,2,2,3,2,4,3,3,2,10,4.0,neutral or dissatisfied +41568,59820,Female,Loyal Customer,14,Personal Travel,Business,1065,2,5,2,4,2,2,2,2,5,3,4,3,5,2,66,36.0,neutral or dissatisfied +41569,5193,Female,disloyal Customer,36,Business travel,Business,190,3,2,2,4,2,2,2,2,3,2,5,4,4,2,3,0.0,neutral or dissatisfied +41570,118099,Female,Loyal Customer,34,Business travel,Business,1999,4,4,4,4,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +41571,38675,Female,Loyal Customer,36,Personal Travel,Eco,2611,2,2,2,3,2,2,3,2,2,3,2,4,2,2,11,9.0,neutral or dissatisfied +41572,123663,Male,Loyal Customer,47,Business travel,Business,214,2,2,2,2,5,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +41573,14678,Male,Loyal Customer,55,Personal Travel,Eco,430,5,4,3,4,4,3,4,4,4,4,5,4,5,4,0,0.0,satisfied +41574,38537,Female,disloyal Customer,25,Business travel,Eco,1446,3,3,3,3,2,3,2,2,4,3,2,4,4,2,35,6.0,neutral or dissatisfied +41575,19216,Female,Loyal Customer,25,Business travel,Business,459,3,1,1,1,3,4,3,3,4,2,2,3,2,3,0,32.0,neutral or dissatisfied +41576,128030,Female,Loyal Customer,51,Business travel,Business,1440,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +41577,673,Female,Loyal Customer,39,Business travel,Business,2929,4,4,2,4,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +41578,41110,Female,disloyal Customer,21,Business travel,Eco,667,2,3,2,4,1,2,1,1,1,2,3,2,3,1,19,22.0,neutral or dissatisfied +41579,60581,Male,Loyal Customer,50,Business travel,Business,2256,4,1,1,1,4,2,2,4,4,4,4,1,4,3,4,0.0,neutral or dissatisfied +41580,79564,Female,Loyal Customer,50,Business travel,Business,762,3,3,3,3,5,5,5,3,3,5,5,5,5,5,138,120.0,satisfied +41581,86654,Male,Loyal Customer,53,Personal Travel,Eco,746,2,3,2,5,4,2,4,4,3,1,5,2,4,4,0,0.0,neutral or dissatisfied +41582,91339,Male,Loyal Customer,7,Personal Travel,Eco Plus,581,5,5,5,3,4,5,4,4,3,3,5,5,4,4,0,0.0,satisfied +41583,16038,Female,Loyal Customer,35,Business travel,Eco Plus,853,4,4,4,4,4,5,4,4,3,4,4,2,5,4,0,10.0,satisfied +41584,1716,Male,Loyal Customer,49,Business travel,Business,3101,3,2,2,2,3,4,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +41585,122793,Female,Loyal Customer,52,Business travel,Business,599,4,4,4,4,2,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +41586,82859,Female,Loyal Customer,41,Business travel,Business,1951,2,2,2,2,5,4,4,4,4,5,4,5,4,5,2,3.0,satisfied +41587,22483,Male,Loyal Customer,51,Personal Travel,Eco,83,5,5,0,4,3,0,3,3,3,5,3,3,5,3,0,0.0,satisfied +41588,36571,Male,Loyal Customer,43,Business travel,Eco,1121,4,2,5,2,4,4,4,4,3,3,4,1,4,4,55,104.0,satisfied +41589,7046,Female,Loyal Customer,31,Personal Travel,Eco Plus,196,2,3,2,2,1,2,1,1,3,1,1,3,3,1,0,0.0,neutral or dissatisfied +41590,8257,Female,Loyal Customer,48,Personal Travel,Eco,125,3,5,0,3,5,4,4,5,5,0,5,5,5,4,0,0.0,neutral or dissatisfied +41591,35108,Male,disloyal Customer,27,Business travel,Eco,944,2,2,2,3,3,2,3,3,1,4,5,2,4,3,0,0.0,neutral or dissatisfied +41592,110346,Female,Loyal Customer,42,Business travel,Business,2232,2,2,2,2,2,5,4,5,5,5,5,5,5,5,10,7.0,satisfied +41593,57290,Male,Loyal Customer,46,Business travel,Eco Plus,228,2,2,2,2,2,2,2,2,2,3,3,3,3,2,13,17.0,neutral or dissatisfied +41594,29706,Female,Loyal Customer,69,Personal Travel,Eco,1542,4,5,4,2,3,4,5,5,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +41595,86932,Male,disloyal Customer,25,Business travel,Business,352,0,2,0,2,4,0,4,4,5,5,4,3,4,4,0,0.0,satisfied +41596,77604,Male,Loyal Customer,24,Business travel,Business,2980,2,2,2,2,4,4,4,4,3,2,5,3,4,4,0,0.0,satisfied +41597,110720,Male,Loyal Customer,52,Business travel,Business,2628,2,2,2,2,3,4,4,4,4,4,4,3,4,3,36,40.0,satisfied +41598,55754,Female,Loyal Customer,9,Personal Travel,Eco,1737,0,5,1,3,5,1,5,5,3,2,4,4,1,5,7,0.0,satisfied +41599,122424,Male,Loyal Customer,45,Business travel,Business,1916,2,2,2,2,2,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +41600,13193,Female,disloyal Customer,33,Business travel,Eco,419,2,1,2,3,1,2,1,1,1,4,4,1,3,1,0,0.0,neutral or dissatisfied +41601,123587,Female,Loyal Customer,13,Personal Travel,Eco,1773,3,3,4,2,5,4,1,5,1,5,5,2,2,5,11,0.0,neutral or dissatisfied +41602,85651,Male,Loyal Customer,61,Personal Travel,Eco Plus,192,3,4,3,1,3,3,3,3,3,5,5,5,4,3,34,21.0,neutral or dissatisfied +41603,87199,Female,Loyal Customer,51,Business travel,Business,946,1,1,1,1,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +41604,69046,Female,Loyal Customer,60,Business travel,Business,1389,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,8.0,satisfied +41605,100958,Male,disloyal Customer,17,Business travel,Eco,1204,2,2,2,4,3,2,3,3,3,1,3,1,3,3,22,27.0,neutral or dissatisfied +41606,6044,Female,Loyal Customer,34,Business travel,Business,693,1,1,1,1,3,1,2,5,5,5,5,2,5,4,0,0.0,satisfied +41607,113463,Female,disloyal Customer,17,Business travel,Eco,197,0,4,0,3,5,0,4,5,4,4,4,3,4,5,0,0.0,satisfied +41608,26727,Female,Loyal Customer,40,Business travel,Eco Plus,515,5,3,3,3,5,5,5,3,5,4,4,5,2,5,160,154.0,satisfied +41609,33046,Female,Loyal Customer,26,Personal Travel,Eco,101,2,5,2,3,3,2,3,3,3,3,4,5,5,3,0,1.0,neutral or dissatisfied +41610,32260,Female,Loyal Customer,29,Business travel,Business,163,0,4,0,2,5,4,4,5,3,4,4,3,5,5,0,0.0,satisfied +41611,6989,Male,Loyal Customer,40,Business travel,Business,1742,3,1,1,1,3,3,4,2,2,2,3,2,2,1,0,0.0,neutral or dissatisfied +41612,71116,Male,Loyal Customer,43,Personal Travel,Eco,2072,3,4,3,1,3,3,3,4,2,3,4,3,3,3,188,178.0,neutral or dissatisfied +41613,20976,Male,Loyal Customer,20,Personal Travel,Eco,851,1,5,1,5,2,1,1,2,3,3,4,5,4,2,66,60.0,neutral or dissatisfied +41614,114541,Male,Loyal Customer,68,Personal Travel,Business,417,2,5,2,2,4,5,2,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +41615,78006,Male,Loyal Customer,77,Business travel,Business,2363,2,5,5,5,1,4,3,1,1,2,2,2,1,3,0,1.0,neutral or dissatisfied +41616,106495,Male,Loyal Customer,39,Business travel,Business,495,5,5,5,5,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +41617,93131,Female,Loyal Customer,50,Business travel,Business,2574,2,5,5,5,4,3,4,2,2,2,2,4,2,4,4,12.0,neutral or dissatisfied +41618,89090,Male,disloyal Customer,39,Business travel,Business,1103,5,5,5,2,5,5,5,5,4,5,4,3,5,5,21,25.0,satisfied +41619,111293,Female,Loyal Customer,27,Personal Travel,Eco Plus,479,3,2,3,4,5,3,2,5,3,2,3,4,3,5,23,12.0,neutral or dissatisfied +41620,103387,Female,Loyal Customer,38,Business travel,Business,2541,1,1,1,1,4,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +41621,91919,Male,Loyal Customer,35,Business travel,Business,2475,4,4,4,4,3,5,5,4,4,4,4,4,4,5,90,83.0,satisfied +41622,84314,Female,Loyal Customer,51,Business travel,Business,591,2,2,2,2,2,4,5,5,5,5,5,5,5,3,42,28.0,satisfied +41623,20434,Female,disloyal Customer,39,Business travel,Business,299,2,2,2,3,2,2,2,2,4,2,4,2,3,2,0,0.0,neutral or dissatisfied +41624,79590,Female,Loyal Customer,48,Business travel,Business,1525,5,5,5,5,2,5,5,5,5,5,5,3,5,3,2,9.0,satisfied +41625,27965,Female,Loyal Customer,29,Personal Travel,Eco,1774,1,4,1,3,2,1,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +41626,90575,Male,Loyal Customer,48,Business travel,Business,2263,3,3,3,3,4,4,5,5,5,5,5,5,5,4,32,21.0,satisfied +41627,72221,Female,Loyal Customer,52,Personal Travel,Business,919,1,5,2,2,3,4,4,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +41628,119961,Male,Loyal Customer,47,Business travel,Eco,868,2,3,3,3,3,2,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +41629,63575,Female,Loyal Customer,51,Business travel,Business,2133,1,1,1,1,5,3,5,5,5,5,5,3,5,3,31,38.0,satisfied +41630,19042,Female,Loyal Customer,58,Business travel,Business,304,5,5,3,5,2,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +41631,49199,Male,disloyal Customer,33,Business travel,Eco,110,1,1,1,4,5,1,5,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +41632,64625,Male,Loyal Customer,60,Business travel,Business,3821,0,0,0,3,5,4,4,5,5,3,3,3,5,5,5,0.0,satisfied +41633,24156,Female,Loyal Customer,15,Business travel,Business,2633,2,5,4,4,3,4,2,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +41634,45905,Female,Loyal Customer,57,Business travel,Business,3634,1,3,2,3,5,2,2,1,1,2,1,1,1,2,3,0.0,neutral or dissatisfied +41635,11765,Female,Loyal Customer,17,Personal Travel,Eco,395,4,1,4,2,3,4,3,3,4,1,2,4,2,3,0,0.0,satisfied +41636,44020,Female,Loyal Customer,22,Personal Travel,Eco Plus,397,4,2,4,3,1,4,4,1,4,1,4,2,3,1,0,0.0,satisfied +41637,15230,Male,Loyal Customer,39,Business travel,Business,3489,4,4,4,4,3,4,2,4,4,4,4,1,4,2,0,0.0,satisfied +41638,110310,Female,Loyal Customer,32,Business travel,Business,919,5,5,5,5,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +41639,106929,Male,Loyal Customer,31,Business travel,Business,2511,4,4,4,4,4,4,4,4,4,4,4,4,5,4,6,2.0,satisfied +41640,49743,Female,Loyal Customer,36,Business travel,Eco,373,5,3,3,3,5,5,5,5,5,5,5,1,3,5,0,7.0,satisfied +41641,128785,Female,Loyal Customer,20,Personal Travel,Eco,2248,3,4,3,1,3,4,4,3,5,4,4,4,5,4,1,40.0,neutral or dissatisfied +41642,69168,Female,Loyal Customer,59,Business travel,Business,1538,1,1,1,1,3,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +41643,98750,Female,Loyal Customer,62,Personal Travel,Eco,1290,2,5,2,3,5,3,5,2,2,2,2,3,2,3,20,21.0,neutral or dissatisfied +41644,24284,Male,Loyal Customer,24,Personal Travel,Eco,147,2,1,0,2,5,0,5,5,4,4,3,1,2,5,1,0.0,neutral or dissatisfied +41645,39883,Male,Loyal Customer,70,Personal Travel,Eco,272,4,5,4,3,2,4,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +41646,45847,Female,Loyal Customer,10,Personal Travel,Eco,391,2,4,2,3,5,2,5,5,4,2,3,2,3,5,3,0.0,neutral or dissatisfied +41647,21561,Female,Loyal Customer,36,Business travel,Eco Plus,331,3,5,5,5,3,3,3,3,3,3,3,5,1,3,0,0.0,satisfied +41648,60319,Female,Loyal Customer,41,Business travel,Business,836,4,4,4,4,5,4,5,4,4,5,4,5,4,5,11,1.0,satisfied +41649,83264,Male,Loyal Customer,25,Business travel,Business,1956,5,5,5,5,3,3,3,3,5,2,3,4,5,3,0,0.0,satisfied +41650,51316,Female,Loyal Customer,36,Business travel,Eco Plus,86,5,3,3,3,5,5,5,5,4,5,4,3,1,5,1,0.0,satisfied +41651,70600,Male,disloyal Customer,33,Business travel,Business,2611,4,4,4,2,4,4,4,1,1,2,3,4,2,4,0,0.0,neutral or dissatisfied +41652,97077,Male,Loyal Customer,51,Business travel,Business,3038,5,5,4,5,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +41653,79666,Female,Loyal Customer,29,Personal Travel,Eco,760,3,3,3,3,5,3,5,5,1,3,3,3,2,5,7,37.0,neutral or dissatisfied +41654,20243,Female,Loyal Customer,47,Business travel,Business,2863,2,2,2,2,4,1,5,5,5,5,5,1,5,5,0,0.0,satisfied +41655,71186,Male,disloyal Customer,23,Business travel,Eco,733,3,3,3,4,2,3,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +41656,48941,Male,Loyal Customer,27,Business travel,Business,3270,4,4,4,4,5,5,5,5,5,5,3,1,3,5,24,25.0,satisfied +41657,42054,Male,Loyal Customer,40,Personal Travel,Eco,116,1,4,1,4,5,1,5,5,4,4,4,5,2,5,0,10.0,neutral or dissatisfied +41658,90273,Female,Loyal Customer,62,Business travel,Business,3272,4,4,4,4,2,5,5,3,3,4,3,4,3,4,24,22.0,satisfied +41659,3581,Male,Loyal Customer,60,Personal Travel,Eco Plus,227,4,5,4,1,1,4,3,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +41660,107823,Female,Loyal Customer,33,Personal Travel,Eco,349,2,1,5,3,4,5,4,4,1,5,2,4,2,4,0,0.0,neutral or dissatisfied +41661,30500,Male,Loyal Customer,45,Business travel,Business,373,3,3,3,3,2,3,1,4,4,4,4,2,4,5,25,30.0,satisfied +41662,62256,Female,Loyal Customer,60,Business travel,Business,2434,1,1,2,1,2,4,5,4,4,4,4,5,4,4,12,0.0,satisfied +41663,19840,Male,Loyal Customer,34,Personal Travel,Eco Plus,528,1,5,1,2,2,1,2,2,5,5,4,3,5,2,127,124.0,neutral or dissatisfied +41664,47845,Male,Loyal Customer,35,Business travel,Eco,329,5,2,2,2,5,5,5,5,3,3,5,5,5,5,10,0.0,satisfied +41665,107385,Male,Loyal Customer,32,Business travel,Business,3247,3,3,3,3,5,5,5,5,5,5,4,4,4,5,8,0.0,satisfied +41666,125073,Male,disloyal Customer,37,Business travel,Business,361,1,1,1,5,4,1,1,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +41667,72526,Female,Loyal Customer,71,Business travel,Business,918,4,5,5,5,4,4,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +41668,107858,Female,Loyal Customer,75,Business travel,Eco,228,2,4,4,4,4,1,1,2,2,2,2,4,2,3,22,14.0,neutral or dissatisfied +41669,75165,Female,Loyal Customer,50,Business travel,Business,1744,3,3,5,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +41670,54799,Male,Loyal Customer,48,Business travel,Eco,641,4,5,5,5,4,4,4,4,2,4,3,4,4,4,100,91.0,satisfied +41671,108814,Male,Loyal Customer,45,Business travel,Eco Plus,406,1,5,5,5,1,1,1,1,1,3,4,1,3,1,2,1.0,neutral or dissatisfied +41672,66028,Male,Loyal Customer,30,Business travel,Business,1500,1,4,1,1,5,5,5,5,5,3,4,5,4,5,7,14.0,satisfied +41673,9343,Male,Loyal Customer,29,Business travel,Business,441,1,1,1,1,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +41674,68029,Female,Loyal Customer,23,Business travel,Business,868,5,5,5,5,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +41675,78657,Female,disloyal Customer,20,Business travel,Business,897,5,0,5,3,1,5,2,1,3,4,3,5,4,1,0,9.0,satisfied +41676,42255,Female,Loyal Customer,38,Business travel,Eco,834,2,3,3,3,2,2,2,2,1,3,3,1,3,2,0,8.0,neutral or dissatisfied +41677,113879,Female,Loyal Customer,63,Personal Travel,Eco Plus,1334,2,5,2,1,4,5,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +41678,80169,Female,Loyal Customer,8,Business travel,Business,2475,2,3,3,3,2,2,2,2,2,2,4,2,2,2,0,0.0,neutral or dissatisfied +41679,110043,Male,disloyal Customer,50,Business travel,Eco,2039,2,2,2,3,3,2,3,3,1,2,2,1,2,3,0,10.0,neutral or dissatisfied +41680,26245,Male,Loyal Customer,53,Personal Travel,Eco,581,3,2,3,3,3,3,3,3,3,3,3,3,4,3,9,1.0,neutral or dissatisfied +41681,931,Female,Loyal Customer,57,Business travel,Business,164,2,2,2,2,5,3,2,2,2,2,2,2,2,1,29,39.0,neutral or dissatisfied +41682,120821,Female,Loyal Customer,16,Personal Travel,Eco,666,3,1,3,3,2,3,5,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +41683,63008,Female,Loyal Customer,66,Business travel,Business,862,2,5,5,5,1,4,3,2,2,2,2,4,2,3,0,1.0,neutral or dissatisfied +41684,51471,Female,disloyal Customer,43,Business travel,Eco Plus,89,3,3,3,2,4,3,5,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +41685,13743,Male,Loyal Customer,52,Business travel,Eco,401,2,1,1,1,2,2,2,2,2,1,3,4,3,2,26,12.0,neutral or dissatisfied +41686,128166,Female,disloyal Customer,48,Business travel,Eco,849,3,3,3,3,3,3,3,3,4,3,3,1,3,3,2,0.0,neutral or dissatisfied +41687,71764,Male,disloyal Customer,26,Business travel,Business,1744,5,5,5,1,3,0,3,3,3,2,4,4,5,3,0,0.0,satisfied +41688,36317,Male,Loyal Customer,46,Business travel,Business,2608,2,5,3,3,2,4,3,4,4,4,2,3,4,1,0,4.0,neutral or dissatisfied +41689,121633,Male,Loyal Customer,28,Business travel,Business,936,5,5,5,5,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +41690,42239,Male,Loyal Customer,32,Business travel,Business,1668,5,5,5,5,5,5,5,5,5,4,4,1,3,5,2,0.0,satisfied +41691,4097,Female,Loyal Customer,42,Business travel,Business,2036,5,5,5,5,4,5,4,4,4,4,4,4,4,5,15,19.0,satisfied +41692,104906,Female,Loyal Customer,7,Personal Travel,Eco,1565,1,5,1,4,3,1,3,3,3,2,5,4,5,3,6,6.0,neutral or dissatisfied +41693,59619,Female,Loyal Customer,28,Business travel,Business,861,3,5,5,5,3,3,3,3,3,4,2,1,2,3,0,0.0,neutral or dissatisfied +41694,62460,Female,Loyal Customer,59,Personal Travel,Business,1723,1,5,1,3,4,3,5,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +41695,45383,Female,disloyal Customer,37,Business travel,Eco Plus,175,5,5,5,1,4,5,3,4,1,2,1,2,4,4,0,0.0,satisfied +41696,46199,Female,Loyal Customer,39,Business travel,Eco Plus,472,4,1,1,1,4,4,4,4,1,5,5,1,3,4,50,53.0,satisfied +41697,113754,Female,Loyal Customer,34,Personal Travel,Eco,197,1,4,1,4,2,1,2,2,3,5,4,4,5,2,1,0.0,neutral or dissatisfied +41698,68024,Female,Loyal Customer,47,Personal Travel,Eco,304,4,5,4,3,5,4,5,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +41699,112030,Male,Loyal Customer,38,Personal Travel,Eco,680,2,5,2,3,3,2,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +41700,73952,Female,Loyal Customer,41,Business travel,Eco,718,3,1,1,1,3,3,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +41701,9714,Male,Loyal Customer,23,Personal Travel,Eco,199,2,5,0,5,5,0,5,5,1,5,2,4,2,5,20,29.0,neutral or dissatisfied +41702,76349,Female,Loyal Customer,38,Business travel,Business,1851,5,5,5,5,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +41703,16817,Female,Loyal Customer,47,Business travel,Business,1871,5,5,5,5,3,2,2,4,4,4,4,3,4,1,80,125.0,satisfied +41704,40009,Female,Loyal Customer,25,Business travel,Eco,618,5,5,5,5,5,5,5,5,1,1,2,3,5,5,0,0.0,satisfied +41705,43184,Male,Loyal Customer,60,Personal Travel,Eco,282,3,4,3,3,5,3,5,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +41706,49138,Male,disloyal Customer,33,Business travel,Eco,372,4,0,4,2,1,4,1,1,2,1,5,4,5,1,8,0.0,neutral or dissatisfied +41707,72605,Female,Loyal Customer,15,Personal Travel,Eco,964,5,5,5,3,5,5,3,5,4,4,4,3,5,5,5,0.0,satisfied +41708,107739,Female,Loyal Customer,65,Personal Travel,Eco,251,2,4,2,1,2,5,4,3,3,2,3,5,3,3,0,4.0,neutral or dissatisfied +41709,96633,Female,Loyal Customer,47,Business travel,Business,1605,4,4,4,4,4,4,5,5,5,5,5,3,5,3,12,13.0,satisfied +41710,47905,Female,Loyal Customer,46,Business travel,Eco,748,3,3,3,3,5,3,3,3,3,3,3,1,3,1,0,2.0,neutral or dissatisfied +41711,105953,Male,Loyal Customer,55,Business travel,Business,2329,1,1,1,1,3,3,5,4,4,4,4,4,4,4,5,0.0,satisfied +41712,2814,Male,Loyal Customer,36,Personal Travel,Business,409,1,4,1,2,1,4,4,2,2,1,3,4,2,4,168,171.0,neutral or dissatisfied +41713,81727,Female,Loyal Customer,45,Personal Travel,Business,1416,3,5,3,5,5,5,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +41714,50659,Female,Loyal Customer,33,Personal Travel,Eco,109,2,5,2,4,4,2,4,4,3,4,1,1,2,4,0,3.0,neutral or dissatisfied +41715,31483,Male,Loyal Customer,50,Business travel,Eco,862,4,4,4,4,4,4,4,4,4,3,2,3,5,4,0,31.0,satisfied +41716,71850,Male,Loyal Customer,17,Business travel,Business,1846,1,4,4,4,1,2,1,1,4,5,2,3,4,1,3,19.0,neutral or dissatisfied +41717,85696,Male,disloyal Customer,26,Business travel,Business,1547,0,0,0,2,4,0,4,4,3,5,4,3,4,4,0,0.0,satisfied +41718,27548,Male,Loyal Customer,47,Personal Travel,Eco,1050,4,4,4,3,5,4,5,5,3,2,2,1,4,5,0,0.0,neutral or dissatisfied +41719,22854,Male,Loyal Customer,65,Personal Travel,Eco,147,1,3,0,3,4,0,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +41720,124168,Female,Loyal Customer,24,Personal Travel,Eco,2133,2,4,2,4,5,2,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +41721,122942,Female,Loyal Customer,53,Business travel,Eco,590,3,3,3,3,4,3,3,3,3,3,3,4,3,2,36,35.0,neutral or dissatisfied +41722,58872,Female,Loyal Customer,45,Business travel,Business,2542,2,2,2,2,3,4,5,5,5,5,5,4,5,4,10,0.0,satisfied +41723,34844,Female,Loyal Customer,61,Personal Travel,Eco Plus,301,2,5,2,5,2,2,2,4,3,4,4,2,3,2,156,209.0,neutral or dissatisfied +41724,33500,Male,Loyal Customer,13,Personal Travel,Business,965,5,3,5,3,1,5,1,1,3,2,4,3,4,1,0,0.0,satisfied +41725,122067,Male,Loyal Customer,67,Business travel,Business,1907,5,5,5,5,5,3,1,5,5,5,3,1,5,2,0,0.0,satisfied +41726,127608,Male,disloyal Customer,29,Business travel,Business,1773,4,4,4,3,3,4,3,3,3,5,3,4,5,3,0,0.0,neutral or dissatisfied +41727,49661,Female,Loyal Customer,43,Business travel,Eco,109,1,4,4,4,3,3,4,1,1,1,1,4,1,1,9,20.0,neutral or dissatisfied +41728,75841,Male,Loyal Customer,43,Business travel,Business,1440,5,5,5,5,3,5,4,2,2,3,2,3,2,4,0,0.0,satisfied +41729,15688,Female,Loyal Customer,18,Business travel,Business,2489,2,2,2,2,4,4,4,4,3,2,2,3,3,4,0,0.0,satisfied +41730,108096,Male,Loyal Customer,52,Business travel,Business,3701,2,2,2,2,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +41731,124300,Female,disloyal Customer,36,Business travel,Business,255,4,4,4,5,5,4,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +41732,66835,Female,disloyal Customer,32,Business travel,Business,731,4,4,4,3,5,4,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +41733,68856,Female,Loyal Customer,44,Business travel,Business,1744,3,3,3,3,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +41734,21698,Male,Loyal Customer,11,Personal Travel,Eco,746,1,5,1,3,5,1,5,5,4,4,1,2,5,5,38,68.0,neutral or dissatisfied +41735,28210,Female,Loyal Customer,46,Personal Travel,Eco,569,1,1,1,3,2,3,2,2,2,1,2,1,2,4,106,107.0,neutral or dissatisfied +41736,103708,Male,Loyal Customer,36,Personal Travel,Eco,405,4,5,4,4,3,4,3,3,4,5,5,4,5,3,61,53.0,neutral or dissatisfied +41737,120868,Female,Loyal Customer,29,Business travel,Business,2103,2,2,2,2,4,4,4,4,4,2,5,3,4,4,91,65.0,satisfied +41738,16048,Female,Loyal Customer,56,Business travel,Business,3653,5,2,5,5,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +41739,114984,Female,Loyal Customer,47,Business travel,Business,3415,2,2,2,2,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +41740,83653,Male,Loyal Customer,50,Business travel,Business,1784,1,1,1,1,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +41741,104393,Male,Loyal Customer,19,Business travel,Business,1646,4,4,5,4,5,5,5,5,4,5,4,4,4,5,26,12.0,satisfied +41742,114421,Male,Loyal Customer,56,Business travel,Business,2708,1,1,1,1,3,4,4,4,4,4,4,3,4,5,33,25.0,satisfied +41743,57463,Female,Loyal Customer,7,Personal Travel,Eco,334,1,5,1,4,1,1,1,1,4,2,5,3,4,1,84,72.0,neutral or dissatisfied +41744,77808,Female,Loyal Customer,24,Personal Travel,Eco,874,3,1,3,4,4,3,1,4,4,1,3,3,4,4,3,2.0,neutral or dissatisfied +41745,43171,Female,Loyal Customer,49,Business travel,Eco,781,4,1,1,1,4,4,4,1,2,3,3,4,5,4,126,141.0,satisfied +41746,3392,Male,Loyal Customer,57,Business travel,Business,296,1,5,5,5,2,1,1,1,1,1,1,1,1,3,30,29.0,neutral or dissatisfied +41747,45317,Female,Loyal Customer,39,Business travel,Eco,150,3,1,1,1,2,3,3,1,3,3,4,3,1,3,200,193.0,neutral or dissatisfied +41748,119577,Female,Loyal Customer,50,Business travel,Business,3649,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,1.0,satisfied +41749,5574,Female,Loyal Customer,23,Personal Travel,Eco,588,3,4,2,3,2,2,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +41750,55735,Female,disloyal Customer,21,Business travel,Eco,1366,3,3,3,5,5,3,1,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +41751,127738,Female,Loyal Customer,52,Business travel,Business,2496,4,4,4,4,5,4,4,4,4,4,4,3,4,3,1,0.0,satisfied +41752,101177,Male,disloyal Customer,24,Business travel,Eco,395,5,0,5,4,1,5,1,1,5,4,3,4,4,1,0,0.0,satisfied +41753,85416,Male,Loyal Customer,43,Business travel,Business,1702,4,4,4,4,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +41754,88109,Male,Loyal Customer,20,Business travel,Business,594,5,5,5,5,2,2,2,2,4,5,4,3,5,2,0,0.0,satisfied +41755,83477,Male,Loyal Customer,28,Business travel,Business,946,2,4,4,4,2,3,2,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +41756,94655,Female,disloyal Customer,21,Business travel,Eco,192,3,3,3,4,1,3,1,1,3,1,3,2,4,1,22,23.0,neutral or dissatisfied +41757,94565,Male,Loyal Customer,66,Business travel,Business,233,1,4,4,4,2,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +41758,59581,Male,Loyal Customer,16,Business travel,Eco,956,4,1,1,1,4,4,2,4,3,5,4,3,3,4,7,6.0,neutral or dissatisfied +41759,45641,Female,Loyal Customer,64,Personal Travel,Eco,313,2,4,2,3,5,4,5,5,5,2,5,3,5,4,31,19.0,neutral or dissatisfied +41760,148,Female,Loyal Customer,54,Business travel,Business,227,2,3,3,3,2,3,3,2,2,2,2,3,2,3,58,62.0,neutral or dissatisfied +41761,88499,Male,Loyal Customer,34,Business travel,Business,3772,4,4,4,4,2,2,1,5,5,5,5,3,5,3,85,70.0,satisfied +41762,106396,Male,Loyal Customer,49,Business travel,Business,2182,2,4,4,4,4,3,4,2,2,2,2,1,2,4,7,0.0,neutral or dissatisfied +41763,48803,Female,Loyal Customer,20,Personal Travel,Business,372,4,1,4,3,1,4,1,1,4,1,3,1,4,1,16,14.0,satisfied +41764,80597,Female,Loyal Customer,43,Business travel,Business,1747,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +41765,109003,Male,Loyal Customer,53,Business travel,Business,2238,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +41766,46709,Male,Loyal Customer,10,Personal Travel,Eco,73,2,4,2,1,3,2,3,3,4,4,1,3,3,3,110,115.0,neutral or dissatisfied +41767,120381,Female,Loyal Customer,61,Business travel,Business,3565,1,1,1,1,2,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +41768,72500,Male,Loyal Customer,47,Business travel,Business,964,2,2,2,2,2,3,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +41769,92991,Female,Loyal Customer,57,Personal Travel,Eco,738,2,2,2,4,4,4,4,2,2,2,2,3,2,1,9,7.0,neutral or dissatisfied +41770,125456,Female,Loyal Customer,29,Business travel,Business,2860,3,3,5,3,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +41771,20770,Male,Loyal Customer,32,Business travel,Business,534,3,3,3,3,5,5,5,5,1,4,4,4,1,5,49,55.0,satisfied +41772,59898,Male,Loyal Customer,29,Business travel,Business,1023,1,1,1,1,5,5,5,5,3,4,5,5,4,5,3,0.0,satisfied +41773,124717,Male,Loyal Customer,9,Personal Travel,Eco,399,1,2,1,2,4,1,4,4,3,2,3,2,3,4,4,0.0,neutral or dissatisfied +41774,38513,Male,Loyal Customer,39,Business travel,Business,2446,4,4,4,4,3,5,5,3,3,3,3,4,3,5,19,5.0,satisfied +41775,8060,Female,Loyal Customer,57,Business travel,Business,294,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +41776,116844,Female,Loyal Customer,29,Personal Travel,Business,369,2,4,2,3,4,2,4,4,1,1,4,2,4,4,1,8.0,neutral or dissatisfied +41777,111190,Female,disloyal Customer,24,Business travel,Business,1506,0,0,0,4,4,0,4,4,4,2,5,3,4,4,0,0.0,satisfied +41778,89172,Female,Loyal Customer,62,Personal Travel,Eco,1947,4,5,4,1,4,4,5,2,2,4,2,4,2,5,29,0.0,neutral or dissatisfied +41779,20170,Female,Loyal Customer,46,Personal Travel,Eco,403,1,4,1,4,5,4,5,3,3,1,4,4,3,5,0,19.0,neutral or dissatisfied +41780,25827,Male,Loyal Customer,61,Business travel,Eco,484,4,2,2,2,4,4,4,4,1,5,5,1,3,4,25,22.0,satisfied +41781,78007,Male,Loyal Customer,39,Business travel,Eco,214,3,3,3,3,3,3,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +41782,24311,Male,Loyal Customer,19,Personal Travel,Eco Plus,302,3,5,3,2,4,3,5,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +41783,98352,Female,disloyal Customer,25,Business travel,Eco,1189,2,2,2,2,1,2,1,1,3,4,2,2,2,1,0,0.0,neutral or dissatisfied +41784,104698,Male,Loyal Customer,35,Business travel,Eco,159,2,4,4,4,2,2,2,2,3,4,3,4,2,2,57,57.0,neutral or dissatisfied +41785,105051,Female,Loyal Customer,38,Personal Travel,Eco,255,3,5,3,2,2,3,5,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +41786,112788,Male,Loyal Customer,27,Business travel,Business,715,3,3,3,3,5,5,5,5,3,4,5,4,4,5,78,78.0,satisfied +41787,67706,Male,Loyal Customer,45,Business travel,Business,1843,5,5,5,5,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +41788,106090,Female,Loyal Customer,59,Business travel,Business,1780,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +41789,110586,Male,Loyal Customer,49,Personal Travel,Eco,488,1,3,1,4,3,1,3,3,2,5,4,1,3,3,0,0.0,neutral or dissatisfied +41790,125586,Male,Loyal Customer,40,Business travel,Business,1587,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,10.0,satisfied +41791,32925,Female,Loyal Customer,41,Personal Travel,Eco,216,5,2,5,3,3,5,3,3,4,4,3,1,3,3,0,0.0,satisfied +41792,96056,Female,Loyal Customer,42,Business travel,Business,835,3,3,3,3,3,4,1,5,5,5,5,5,5,5,14,16.0,satisfied +41793,7835,Male,Loyal Customer,59,Business travel,Business,3386,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +41794,30273,Male,Loyal Customer,51,Business travel,Business,2534,1,1,1,1,2,1,1,5,5,5,5,4,5,3,0,0.0,satisfied +41795,57919,Female,Loyal Customer,30,Personal Travel,Eco,305,3,2,3,4,1,3,3,1,3,5,4,2,3,1,0,0.0,neutral or dissatisfied +41796,43583,Female,Loyal Customer,21,Business travel,Eco Plus,1499,3,1,1,1,3,3,3,4,3,4,4,3,2,3,154,196.0,neutral or dissatisfied +41797,118382,Female,Loyal Customer,36,Business travel,Business,338,5,2,5,5,3,5,4,4,4,4,4,4,4,3,39,47.0,satisfied +41798,43739,Male,Loyal Customer,17,Business travel,Eco,622,4,1,1,1,4,4,4,4,1,4,2,1,1,4,9,0.0,satisfied +41799,129463,Male,Loyal Customer,36,Business travel,Business,2704,3,5,3,3,4,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +41800,87767,Male,Loyal Customer,50,Business travel,Business,3524,3,3,3,3,2,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +41801,62236,Female,Loyal Customer,67,Personal Travel,Eco,2454,4,4,4,3,4,4,4,4,4,4,4,3,4,4,3,0.0,neutral or dissatisfied +41802,113291,Female,Loyal Customer,48,Business travel,Business,488,5,5,5,5,2,4,5,5,5,5,5,5,5,4,9,0.0,satisfied +41803,77817,Male,Loyal Customer,11,Personal Travel,Eco,696,3,5,2,1,2,2,4,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +41804,19546,Female,disloyal Customer,38,Business travel,Eco,212,2,0,2,4,3,2,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +41805,26561,Male,Loyal Customer,44,Business travel,Business,1575,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,19.0,satisfied +41806,59548,Male,disloyal Customer,17,Business travel,Eco,787,4,3,3,1,3,3,4,3,4,3,4,4,5,3,0,0.0,satisfied +41807,87184,Male,Loyal Customer,55,Business travel,Business,946,3,3,3,3,5,4,4,4,4,5,4,4,4,3,10,0.0,satisfied +41808,83886,Male,Loyal Customer,14,Personal Travel,Eco,1670,2,4,2,5,4,2,4,4,2,5,2,2,5,4,0,0.0,neutral or dissatisfied +41809,97731,Female,Loyal Customer,44,Business travel,Business,2257,2,2,2,2,5,5,5,5,5,5,5,5,5,5,6,3.0,satisfied +41810,81155,Female,Loyal Customer,51,Business travel,Business,1607,2,2,2,2,5,5,5,5,5,5,5,4,5,5,3,0.0,satisfied +41811,102672,Female,Loyal Customer,55,Business travel,Business,2565,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +41812,56814,Male,disloyal Customer,25,Business travel,Eco,982,4,4,4,1,3,4,3,3,3,2,5,4,4,3,0,0.0,satisfied +41813,6015,Male,Loyal Customer,57,Business travel,Eco,672,4,2,2,2,4,4,4,4,4,4,3,3,4,4,1,0.0,neutral or dissatisfied +41814,63868,Female,Loyal Customer,44,Business travel,Business,1158,1,1,1,1,2,4,4,4,4,5,4,5,4,3,7,0.0,satisfied +41815,80978,Male,disloyal Customer,40,Business travel,Business,297,2,3,3,3,2,3,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +41816,16053,Female,Loyal Customer,38,Personal Travel,Business,501,4,5,4,4,3,5,5,1,1,4,1,5,1,5,0,0.0,neutral or dissatisfied +41817,123885,Female,disloyal Customer,43,Business travel,Eco,203,2,4,2,4,4,2,2,4,3,5,4,3,3,4,0,6.0,neutral or dissatisfied +41818,117111,Female,Loyal Customer,39,Business travel,Business,338,3,4,4,4,1,4,3,3,3,3,3,4,3,4,11,15.0,neutral or dissatisfied +41819,43844,Female,Loyal Customer,45,Business travel,Business,3972,3,4,4,4,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +41820,116467,Male,Loyal Customer,44,Personal Travel,Eco,480,3,3,3,3,5,3,5,5,3,4,2,1,2,5,13,0.0,neutral or dissatisfied +41821,47114,Female,Loyal Customer,55,Business travel,Business,784,1,3,3,3,2,4,3,1,1,1,1,4,1,1,10,12.0,neutral or dissatisfied +41822,44233,Female,Loyal Customer,38,Business travel,Business,359,3,3,3,3,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +41823,1701,Male,disloyal Customer,33,Business travel,Business,364,4,4,4,5,1,4,1,1,5,5,4,4,5,1,35,30.0,neutral or dissatisfied +41824,14270,Female,Loyal Customer,28,Business travel,Business,429,2,2,2,2,3,4,3,3,1,1,4,5,3,3,0,0.0,satisfied +41825,29108,Male,Loyal Customer,32,Personal Travel,Eco,987,3,5,3,3,5,3,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +41826,25431,Male,Loyal Customer,21,Business travel,Business,3107,5,5,5,5,3,5,3,3,5,2,5,2,4,3,13,0.0,satisfied +41827,24563,Female,Loyal Customer,28,Business travel,Eco,696,3,4,4,4,3,4,3,3,3,5,2,4,2,3,1,0.0,neutral or dissatisfied +41828,122988,Female,Loyal Customer,55,Business travel,Business,507,3,3,3,3,3,4,4,5,5,4,5,3,5,3,1,2.0,satisfied +41829,66323,Female,Loyal Customer,61,Personal Travel,Eco,852,3,4,3,3,1,4,4,4,4,3,4,4,4,4,69,70.0,neutral or dissatisfied +41830,97888,Male,Loyal Customer,52,Business travel,Business,684,4,4,4,4,5,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +41831,48044,Male,Loyal Customer,56,Business travel,Eco,896,1,4,4,4,1,1,1,1,3,4,3,3,3,1,27,7.0,neutral or dissatisfied +41832,101315,Male,Loyal Customer,43,Business travel,Business,2468,2,2,2,2,5,4,5,5,5,5,5,4,5,4,57,46.0,satisfied +41833,104158,Female,disloyal Customer,24,Business travel,Eco,349,2,5,2,2,4,2,4,4,3,3,5,5,5,4,12,13.0,neutral or dissatisfied +41834,105466,Male,Loyal Customer,60,Business travel,Business,495,3,3,3,3,5,5,4,3,3,3,3,4,3,4,44,39.0,satisfied +41835,118435,Female,Loyal Customer,44,Business travel,Business,2408,1,1,1,1,2,4,5,4,4,4,4,4,4,3,34,20.0,satisfied +41836,111264,Female,Loyal Customer,59,Business travel,Business,3670,4,4,4,4,4,4,5,4,4,4,4,4,4,4,0,6.0,satisfied +41837,72334,Male,disloyal Customer,22,Business travel,Eco,1017,2,2,2,2,4,2,4,4,3,2,4,5,4,4,12,10.0,neutral or dissatisfied +41838,56805,Female,Loyal Customer,50,Business travel,Business,1725,4,4,4,4,2,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +41839,50992,Female,Loyal Customer,62,Personal Travel,Eco,156,3,4,0,1,2,5,4,3,3,0,3,3,3,3,0,0.0,neutral or dissatisfied +41840,48962,Male,Loyal Customer,44,Business travel,Eco,86,4,4,4,4,4,4,4,4,2,2,4,5,4,4,15,18.0,satisfied +41841,46392,Male,Loyal Customer,50,Personal Travel,Eco,1081,4,5,4,5,2,4,2,2,2,3,2,1,4,2,16,3.0,neutral or dissatisfied +41842,1169,Female,Loyal Customer,41,Personal Travel,Eco,158,3,4,3,4,4,3,5,4,4,2,5,3,4,4,17,21.0,neutral or dissatisfied +41843,42604,Male,disloyal Customer,22,Business travel,Eco,546,2,4,2,3,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +41844,17140,Male,Loyal Customer,47,Business travel,Eco,455,4,4,4,4,4,4,4,4,4,2,3,1,4,4,0,11.0,neutral or dissatisfied +41845,72326,Male,Loyal Customer,24,Business travel,Business,1935,5,5,5,5,3,3,3,3,5,2,5,3,5,3,0,0.0,satisfied +41846,52557,Female,Loyal Customer,51,Business travel,Business,119,5,5,5,5,2,4,5,5,5,5,4,5,5,5,0,4.0,satisfied +41847,51428,Female,Loyal Customer,35,Personal Travel,Eco Plus,337,3,4,3,4,5,3,5,5,3,5,5,3,4,5,18,19.0,neutral or dissatisfied +41848,28880,Male,disloyal Customer,36,Business travel,Eco,954,2,1,1,4,2,1,2,2,5,3,2,5,2,2,0,0.0,neutral or dissatisfied +41849,65866,Female,Loyal Customer,60,Personal Travel,Eco,1389,3,3,3,4,2,4,2,4,4,3,4,5,4,5,0,3.0,neutral or dissatisfied +41850,87446,Female,Loyal Customer,46,Business travel,Business,3088,4,4,4,4,5,5,5,5,5,5,5,5,5,3,4,9.0,satisfied +41851,9380,Female,Loyal Customer,44,Personal Travel,Eco,384,3,4,3,2,3,5,4,2,2,3,2,3,2,3,6,7.0,neutral or dissatisfied +41852,116626,Male,Loyal Customer,46,Business travel,Business,373,5,5,5,5,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +41853,42263,Female,disloyal Customer,37,Business travel,Eco,451,2,4,3,3,4,3,4,4,2,1,5,5,3,4,0,0.0,neutral or dissatisfied +41854,105454,Female,Loyal Customer,52,Personal Travel,Eco,998,2,5,2,1,3,5,4,5,5,2,5,4,5,3,17,0.0,neutral or dissatisfied +41855,26921,Male,Loyal Customer,60,Personal Travel,Eco,1660,3,3,4,3,2,4,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +41856,119927,Male,Loyal Customer,60,Business travel,Business,2726,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,3.0,satisfied +41857,109988,Male,disloyal Customer,45,Business travel,Business,1092,3,3,3,1,2,3,2,2,5,5,4,4,4,2,15,3.0,neutral or dissatisfied +41858,7205,Male,Loyal Customer,52,Business travel,Business,135,1,4,4,4,3,2,2,2,2,2,1,1,2,2,39,80.0,neutral or dissatisfied +41859,88231,Female,Loyal Customer,38,Business travel,Eco,404,2,2,2,2,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +41860,70608,Female,Loyal Customer,41,Business travel,Business,2611,1,1,1,1,4,4,4,3,4,5,4,4,5,4,0,0.0,satisfied +41861,90059,Female,Loyal Customer,40,Business travel,Business,2662,1,1,1,1,2,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +41862,83609,Male,Loyal Customer,65,Business travel,Business,409,3,4,4,4,5,2,2,3,3,3,3,3,3,2,16,23.0,neutral or dissatisfied +41863,117589,Female,Loyal Customer,45,Business travel,Business,347,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +41864,65291,Female,Loyal Customer,32,Personal Travel,Eco Plus,247,3,4,3,5,1,3,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +41865,78819,Female,Loyal Customer,70,Personal Travel,Eco,432,4,5,5,3,1,5,2,5,5,5,5,1,5,2,5,0.0,satisfied +41866,88446,Male,Loyal Customer,25,Business travel,Business,3037,3,5,5,5,3,3,3,3,3,2,2,1,3,3,15,0.0,neutral or dissatisfied +41867,21842,Female,Loyal Customer,50,Business travel,Business,503,1,1,1,1,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +41868,95278,Female,Loyal Customer,22,Personal Travel,Eco,189,1,4,1,2,2,1,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +41869,80317,Female,Loyal Customer,22,Personal Travel,Eco,746,2,3,2,3,2,2,2,2,4,1,3,3,4,2,81,88.0,neutral or dissatisfied +41870,100937,Female,Loyal Customer,54,Business travel,Business,3703,2,2,2,2,4,3,3,2,2,2,2,4,2,4,1,0.0,neutral or dissatisfied +41871,74492,Male,Loyal Customer,52,Business travel,Eco,1126,3,5,5,5,3,3,3,3,3,1,3,3,2,3,11,14.0,neutral or dissatisfied +41872,10721,Male,Loyal Customer,42,Business travel,Business,3368,1,1,1,1,5,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +41873,85749,Male,Loyal Customer,56,Business travel,Business,666,4,4,3,4,4,4,4,4,4,4,4,3,4,4,3,0.0,satisfied +41874,7909,Male,disloyal Customer,29,Business travel,Eco,1020,3,3,3,3,3,3,3,3,2,2,2,1,3,3,0,11.0,neutral or dissatisfied +41875,78767,Male,Loyal Customer,42,Business travel,Business,554,3,3,3,3,4,5,4,4,4,4,4,5,4,3,25,16.0,satisfied +41876,56659,Female,Loyal Customer,41,Business travel,Business,2380,1,1,1,1,3,2,3,4,4,4,4,5,4,5,0,0.0,satisfied +41877,3075,Male,Loyal Customer,32,Business travel,Business,3005,5,5,5,5,5,4,5,5,3,2,5,4,4,5,55,81.0,satisfied +41878,92546,Female,Loyal Customer,53,Personal Travel,Eco,2139,2,4,2,2,4,5,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +41879,38273,Female,Loyal Customer,28,Personal Travel,Eco,1133,2,4,1,4,3,1,3,3,5,1,3,2,5,3,84,76.0,neutral or dissatisfied +41880,119580,Female,Loyal Customer,70,Personal Travel,Eco,313,3,5,3,1,2,4,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +41881,97737,Male,Loyal Customer,19,Business travel,Business,1828,4,4,4,4,4,4,4,4,1,1,4,1,4,4,9,0.0,neutral or dissatisfied +41882,125952,Male,Loyal Customer,31,Business travel,Eco Plus,920,1,4,4,4,1,1,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +41883,44428,Female,disloyal Customer,22,Business travel,Eco,542,2,2,2,4,4,2,4,4,4,2,3,1,4,4,0,0.0,neutral or dissatisfied +41884,74871,Male,Loyal Customer,43,Business travel,Business,2239,5,5,5,5,3,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +41885,89505,Female,Loyal Customer,28,Business travel,Eco Plus,684,2,4,4,4,2,2,2,2,2,3,3,1,4,2,0,0.0,neutral or dissatisfied +41886,84094,Female,Loyal Customer,50,Personal Travel,Eco,879,2,1,2,3,2,4,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +41887,74914,Male,Loyal Customer,48,Business travel,Business,2586,2,2,2,2,2,3,5,3,3,3,3,3,3,5,68,65.0,satisfied +41888,10274,Male,Loyal Customer,37,Personal Travel,Business,191,2,4,2,4,2,4,4,4,2,5,5,4,3,4,149,140.0,neutral or dissatisfied +41889,55154,Male,Loyal Customer,70,Personal Travel,Eco,1346,3,5,3,4,2,3,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +41890,20060,Female,Loyal Customer,51,Personal Travel,Eco,607,4,4,4,4,3,3,3,3,3,4,3,4,3,3,9,0.0,neutral or dissatisfied +41891,17554,Female,Loyal Customer,40,Personal Travel,Eco,970,1,5,1,4,2,1,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +41892,85506,Female,Loyal Customer,37,Personal Travel,Eco,332,2,4,2,1,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +41893,23036,Male,Loyal Customer,22,Personal Travel,Eco,927,3,5,3,4,4,3,4,4,4,5,4,5,5,4,83,65.0,neutral or dissatisfied +41894,112124,Female,Loyal Customer,45,Business travel,Business,3638,3,2,3,3,3,5,4,4,4,4,4,5,4,3,57,48.0,satisfied +41895,25786,Male,disloyal Customer,35,Business travel,Eco,762,2,2,2,4,4,2,4,4,4,2,5,5,5,4,1,0.0,neutral or dissatisfied +41896,50456,Male,Loyal Customer,38,Business travel,Eco,337,2,5,2,5,2,2,2,2,2,5,3,1,4,2,87,89.0,neutral or dissatisfied +41897,53537,Female,Loyal Customer,59,Business travel,Eco Plus,919,4,1,1,1,5,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +41898,100769,Female,Loyal Customer,47,Business travel,Business,1504,3,3,3,3,5,4,4,4,4,4,4,5,4,5,50,25.0,satisfied +41899,64437,Female,disloyal Customer,42,Business travel,Business,989,1,1,1,3,1,1,1,1,4,5,4,4,4,1,32,38.0,neutral or dissatisfied +41900,101885,Male,Loyal Customer,53,Business travel,Business,2039,3,3,5,3,2,4,5,5,5,5,5,4,5,3,15,0.0,satisfied +41901,121448,Female,Loyal Customer,50,Business travel,Business,257,1,1,3,1,5,5,5,5,5,5,5,3,5,3,0,1.0,satisfied +41902,85649,Male,Loyal Customer,54,Personal Travel,Eco Plus,192,2,2,0,4,5,0,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +41903,13452,Male,Loyal Customer,15,Personal Travel,Eco,475,1,3,1,4,3,1,3,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +41904,8823,Female,Loyal Customer,44,Personal Travel,Eco,522,1,5,1,4,3,4,5,5,5,1,5,3,5,3,0,13.0,neutral or dissatisfied +41905,106680,Male,Loyal Customer,57,Business travel,Eco,451,1,2,2,2,1,1,1,1,4,5,4,3,4,1,0,8.0,neutral or dissatisfied +41906,45450,Female,disloyal Customer,28,Business travel,Business,522,5,5,5,3,1,5,1,1,4,2,4,4,5,1,16,13.0,satisfied +41907,4633,Female,Loyal Customer,29,Business travel,Eco,489,2,2,2,2,2,2,2,2,2,2,3,1,3,2,0,5.0,neutral or dissatisfied +41908,102396,Female,disloyal Customer,37,Business travel,Eco,386,2,0,2,2,4,2,2,4,5,1,5,1,3,4,0,0.0,neutral or dissatisfied +41909,59999,Female,Loyal Customer,18,Personal Travel,Eco,937,2,5,2,2,1,2,1,1,5,2,2,1,1,1,0,0.0,neutral or dissatisfied +41910,39090,Male,Loyal Customer,52,Business travel,Eco,584,2,3,3,3,2,2,2,2,3,5,3,2,4,2,11,34.0,neutral or dissatisfied +41911,10000,Male,Loyal Customer,30,Personal Travel,Eco,534,4,5,4,2,3,4,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +41912,114729,Male,Loyal Customer,48,Business travel,Business,2773,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,12.0,satisfied +41913,70445,Male,Loyal Customer,37,Personal Travel,Eco,187,2,4,2,4,5,2,2,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +41914,81682,Female,disloyal Customer,26,Business travel,Eco,907,4,4,4,4,5,4,5,5,1,3,4,4,4,5,0,0.0,neutral or dissatisfied +41915,64063,Male,disloyal Customer,26,Business travel,Business,921,2,2,2,2,1,2,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +41916,60085,Male,Loyal Customer,25,Business travel,Business,2266,1,1,1,1,3,3,3,3,5,4,5,5,5,3,0,2.0,satisfied +41917,39486,Female,Loyal Customer,34,Personal Travel,Eco,867,5,4,5,3,3,5,1,3,3,3,2,3,3,3,0,0.0,satisfied +41918,42123,Male,Loyal Customer,48,Personal Travel,Eco,991,4,5,5,3,5,5,4,5,3,3,5,5,4,5,7,0.0,neutral or dissatisfied +41919,74709,Female,Loyal Customer,44,Personal Travel,Eco,1464,4,5,3,3,5,4,4,3,3,3,1,5,3,3,0,0.0,neutral or dissatisfied +41920,71997,Female,Loyal Customer,51,Personal Travel,Eco,1440,2,5,2,4,3,5,5,4,4,2,4,3,4,5,12,40.0,neutral or dissatisfied +41921,42025,Female,Loyal Customer,30,Business travel,Business,116,0,5,0,1,2,2,2,2,4,5,4,3,4,2,0,0.0,satisfied +41922,115390,Female,Loyal Customer,49,Business travel,Business,371,3,4,4,4,2,3,3,3,3,3,3,1,3,1,19,6.0,neutral or dissatisfied +41923,107018,Female,Loyal Customer,22,Business travel,Business,395,4,4,4,4,5,4,5,5,5,4,4,4,4,5,19,7.0,satisfied +41924,26123,Female,Loyal Customer,47,Personal Travel,Business,406,3,5,3,3,3,4,5,5,5,3,5,3,5,5,49,40.0,neutral or dissatisfied +41925,126172,Female,Loyal Customer,45,Business travel,Business,631,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +41926,79546,Female,Loyal Customer,59,Business travel,Business,762,1,1,1,1,2,5,4,2,2,2,2,4,2,3,13,23.0,satisfied +41927,5951,Male,Loyal Customer,64,Personal Travel,Eco,612,3,3,3,3,4,3,4,4,4,1,4,2,2,4,0,0.0,neutral or dissatisfied +41928,43879,Female,disloyal Customer,18,Business travel,Eco,174,2,2,2,4,4,2,1,4,4,5,4,3,4,4,0,59.0,neutral or dissatisfied +41929,103016,Male,Loyal Customer,53,Business travel,Business,460,4,4,2,4,2,4,4,4,4,4,4,5,4,4,50,42.0,satisfied +41930,43236,Male,Loyal Customer,51,Business travel,Business,358,5,5,5,5,2,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +41931,55887,Male,Loyal Customer,23,Business travel,Business,3951,1,1,5,1,1,1,1,4,5,3,3,1,4,1,151,126.0,neutral or dissatisfied +41932,56091,Female,Loyal Customer,52,Personal Travel,Eco Plus,2475,2,1,2,3,2,2,2,1,3,4,4,2,4,2,74,67.0,neutral or dissatisfied +41933,117279,Female,Loyal Customer,34,Business travel,Business,370,5,5,3,5,3,4,4,5,5,5,5,3,5,5,0,6.0,satisfied +41934,56129,Male,disloyal Customer,36,Business travel,Business,1400,2,2,2,2,3,2,3,3,3,3,4,5,4,3,112,97.0,neutral or dissatisfied +41935,23183,Female,Loyal Customer,10,Personal Travel,Eco,300,2,5,2,1,4,2,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +41936,26286,Female,Loyal Customer,52,Business travel,Eco Plus,859,5,4,2,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +41937,99067,Female,Loyal Customer,59,Business travel,Business,237,2,2,2,2,5,5,5,5,4,5,4,5,4,5,138,125.0,satisfied +41938,76288,Female,disloyal Customer,24,Business travel,Eco,1261,1,1,1,2,1,5,5,3,3,3,5,5,3,5,0,0.0,neutral or dissatisfied +41939,98855,Female,Loyal Customer,55,Business travel,Business,1751,2,2,2,2,4,2,4,2,2,2,2,1,2,4,7,13.0,neutral or dissatisfied +41940,7677,Female,disloyal Customer,22,Business travel,Eco,641,3,2,3,4,5,3,5,5,3,1,3,3,4,5,0,0.0,neutral or dissatisfied +41941,122397,Male,Loyal Customer,27,Personal Travel,Eco,529,3,4,5,1,5,5,5,5,4,3,5,2,2,5,0,0.0,neutral or dissatisfied +41942,71266,Male,Loyal Customer,55,Personal Travel,Eco,733,2,1,2,4,4,2,4,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +41943,92472,Female,Loyal Customer,54,Business travel,Business,1947,3,4,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +41944,64513,Male,Loyal Customer,70,Personal Travel,Business,354,2,4,2,3,3,4,4,4,4,2,5,5,4,5,16,22.0,neutral or dissatisfied +41945,89612,Female,Loyal Customer,41,Business travel,Business,1010,5,5,5,5,3,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +41946,115831,Female,disloyal Customer,36,Business travel,Eco,446,2,3,3,2,3,3,3,3,1,4,3,3,1,3,0,4.0,neutral or dissatisfied +41947,17020,Female,disloyal Customer,20,Business travel,Eco,781,1,2,2,4,5,2,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +41948,19976,Male,Loyal Customer,51,Personal Travel,Eco,557,3,3,3,3,5,3,5,5,2,4,1,2,5,5,0,0.0,neutral or dissatisfied +41949,112102,Male,Loyal Customer,74,Business travel,Eco,662,4,4,4,4,4,4,4,4,1,5,4,3,5,4,25,0.0,satisfied +41950,17860,Female,Loyal Customer,35,Business travel,Eco,453,5,4,4,4,5,5,5,5,4,3,3,5,5,5,0,0.0,satisfied +41951,5416,Female,Loyal Customer,57,Business travel,Business,589,1,1,1,1,2,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +41952,37107,Male,Loyal Customer,50,Business travel,Business,2757,5,5,5,5,3,3,3,4,3,5,3,3,2,3,233,250.0,satisfied +41953,26239,Male,Loyal Customer,11,Personal Travel,Eco,581,3,4,3,2,5,3,5,5,3,5,5,4,4,5,16,23.0,neutral or dissatisfied +41954,66226,Male,Loyal Customer,56,Business travel,Business,550,4,4,4,4,5,4,4,4,4,4,4,1,4,3,5,12.0,neutral or dissatisfied +41955,93905,Female,Loyal Customer,21,Business travel,Business,1686,4,4,4,4,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +41956,89497,Male,Loyal Customer,47,Personal Travel,Business,684,4,5,4,4,5,4,5,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +41957,62980,Male,Loyal Customer,55,Business travel,Business,3431,2,2,2,2,4,4,4,2,2,2,2,4,2,4,27,24.0,satisfied +41958,31264,Female,Loyal Customer,49,Business travel,Eco,533,4,5,5,5,3,1,2,4,4,4,4,5,4,1,45,40.0,satisfied +41959,82836,Male,Loyal Customer,14,Business travel,Business,2366,5,5,2,5,4,4,4,4,4,2,5,5,4,4,0,21.0,satisfied +41960,113271,Female,Loyal Customer,56,Business travel,Business,2760,1,1,3,3,5,1,2,5,5,4,1,1,5,3,28,26.0,neutral or dissatisfied +41961,4505,Female,Loyal Customer,65,Personal Travel,Eco,435,0,5,0,2,4,4,4,3,3,0,3,3,3,5,0,0.0,satisfied +41962,3270,Male,Loyal Customer,45,Business travel,Eco,479,3,1,1,1,4,3,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +41963,95123,Male,Loyal Customer,20,Personal Travel,Eco,189,2,3,2,3,2,2,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +41964,64108,Male,disloyal Customer,22,Business travel,Eco,1297,1,1,1,1,2,1,2,2,3,2,4,3,4,2,5,19.0,neutral or dissatisfied +41965,52521,Male,Loyal Customer,57,Business travel,Eco,119,4,4,4,4,4,4,4,4,4,2,4,4,1,4,0,0.0,satisfied +41966,97818,Male,disloyal Customer,32,Business travel,Eco,480,3,2,3,2,1,3,1,1,3,3,3,3,2,1,0,0.0,neutral or dissatisfied +41967,95182,Female,Loyal Customer,7,Personal Travel,Eco,319,1,4,2,4,1,2,1,1,4,1,5,4,4,1,0,0.0,neutral or dissatisfied +41968,20997,Male,disloyal Customer,22,Business travel,Eco,721,5,5,5,2,5,5,4,5,1,2,3,2,3,5,0,0.0,satisfied +41969,39907,Female,Loyal Customer,64,Personal Travel,Eco Plus,272,4,0,4,1,3,4,3,1,1,4,2,5,1,3,4,0.0,neutral or dissatisfied +41970,7322,Male,Loyal Customer,20,Personal Travel,Eco Plus,116,3,4,0,2,5,0,5,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +41971,23115,Female,disloyal Customer,44,Business travel,Eco,646,3,4,3,4,4,3,4,4,4,5,4,2,3,4,0,0.0,neutral or dissatisfied +41972,14771,Male,disloyal Customer,28,Business travel,Eco,545,1,5,1,4,5,1,5,5,4,4,4,3,1,5,0,0.0,neutral or dissatisfied +41973,101305,Female,Loyal Customer,49,Business travel,Business,444,4,4,4,4,5,5,4,5,5,5,5,5,5,3,30,26.0,satisfied +41974,120640,Male,disloyal Customer,22,Business travel,Business,280,4,3,4,2,3,4,3,3,3,2,4,5,5,3,39,32.0,satisfied +41975,32022,Female,Loyal Customer,55,Business travel,Eco,216,5,5,5,5,5,5,2,5,5,5,5,2,5,2,0,0.0,satisfied +41976,74955,Male,Loyal Customer,54,Business travel,Business,946,3,3,1,3,5,1,3,4,4,4,4,5,4,5,0,0.0,satisfied +41977,118261,Female,Loyal Customer,50,Personal Travel,Eco,1972,3,3,2,2,2,2,3,3,3,2,5,3,3,2,0,8.0,neutral or dissatisfied +41978,23999,Female,Loyal Customer,32,Business travel,Business,427,3,5,5,5,3,3,3,3,3,3,2,2,2,3,0,0.0,neutral or dissatisfied +41979,41,Female,Loyal Customer,54,Business travel,Business,1554,2,2,2,2,2,4,4,4,4,4,4,3,4,5,59,70.0,satisfied +41980,48724,Male,Loyal Customer,32,Business travel,Business,1667,4,5,4,5,4,4,4,4,3,4,5,5,5,4,77,,satisfied +41981,111348,Male,Loyal Customer,30,Business travel,Business,3845,4,4,4,4,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +41982,81342,Male,Loyal Customer,31,Business travel,Business,2316,1,0,0,3,4,0,4,4,4,2,3,1,3,4,0,0.0,neutral or dissatisfied +41983,90701,Male,disloyal Customer,38,Business travel,Business,594,2,2,2,3,4,2,4,4,3,2,4,5,5,4,12,8.0,satisfied +41984,62252,Female,disloyal Customer,25,Business travel,Business,1294,4,0,4,3,4,4,2,4,3,5,5,4,4,4,14,1.0,satisfied +41985,106401,Male,Loyal Customer,33,Business travel,Business,551,2,4,5,4,2,2,2,2,1,4,3,3,3,2,19,21.0,neutral or dissatisfied +41986,105046,Female,Loyal Customer,34,Personal Travel,Eco,361,3,4,3,1,5,3,2,5,3,5,5,3,5,5,5,0.0,neutral or dissatisfied +41987,96836,Male,disloyal Customer,39,Business travel,Business,849,5,5,5,3,3,5,1,3,3,4,4,5,5,3,26,4.0,satisfied +41988,38921,Female,disloyal Customer,65,Business travel,Eco,320,2,2,2,3,1,2,1,1,4,5,3,3,3,1,5,11.0,neutral or dissatisfied +41989,53359,Female,Loyal Customer,39,Business travel,Eco,1452,4,1,3,1,4,4,4,4,1,2,2,4,1,4,5,0.0,satisfied +41990,95751,Male,disloyal Customer,37,Business travel,Eco,181,2,2,2,4,5,2,2,5,4,2,4,2,4,5,7,0.0,neutral or dissatisfied +41991,85638,Male,Loyal Customer,22,Personal Travel,Eco,317,4,4,4,3,4,4,4,4,5,3,5,4,3,4,0,0.0,neutral or dissatisfied +41992,3168,Female,Loyal Customer,39,Business travel,Business,1777,3,3,3,3,3,5,5,4,4,4,4,5,4,4,0,29.0,satisfied +41993,54773,Female,Loyal Customer,49,Business travel,Eco Plus,387,2,5,5,5,3,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +41994,53026,Female,disloyal Customer,18,Business travel,Eco,1190,2,2,2,3,4,2,4,4,4,2,3,3,4,4,0,0.0,neutral or dissatisfied +41995,60269,Male,disloyal Customer,29,Business travel,Business,2446,0,0,0,2,0,2,2,3,2,3,4,2,3,2,0,11.0,satisfied +41996,17583,Female,Loyal Customer,68,Personal Travel,Eco,1034,3,5,4,1,3,5,5,5,5,4,1,3,5,4,0,0.0,neutral or dissatisfied +41997,100162,Male,disloyal Customer,20,Business travel,Eco,123,4,2,4,2,4,4,4,4,4,5,2,2,1,4,11,25.0,neutral or dissatisfied +41998,18160,Male,Loyal Customer,48,Personal Travel,Eco,430,1,2,1,3,5,1,5,5,1,5,4,1,3,5,0,0.0,neutral or dissatisfied +41999,6929,Female,Loyal Customer,57,Business travel,Business,3325,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,2.0,satisfied +42000,108155,Male,Loyal Customer,15,Personal Travel,Eco,997,3,3,3,3,3,3,5,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +42001,58099,Female,Loyal Customer,58,Personal Travel,Eco,589,3,4,3,2,3,4,4,3,3,3,1,4,3,4,1,0.0,neutral or dissatisfied +42002,46291,Female,Loyal Customer,21,Personal Travel,Business,770,1,4,1,2,3,1,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +42003,54427,Female,Loyal Customer,60,Personal Travel,Eco,305,2,4,2,2,5,5,5,4,4,2,2,5,4,4,0,0.0,neutral or dissatisfied +42004,53065,Female,Loyal Customer,58,Personal Travel,Eco,1190,3,5,3,2,3,4,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +42005,35018,Male,Loyal Customer,15,Business travel,Business,2907,5,5,5,5,5,5,5,5,4,5,4,5,1,5,0,0.0,satisfied +42006,5089,Female,Loyal Customer,35,Business travel,Business,3910,3,3,3,3,3,2,4,4,4,4,4,3,4,4,0,1.0,satisfied +42007,70673,Female,Loyal Customer,36,Business travel,Business,3731,2,2,2,2,3,5,4,4,4,5,4,5,4,5,17,28.0,satisfied +42008,89326,Male,Loyal Customer,60,Business travel,Business,1587,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +42009,83360,Female,Loyal Customer,23,Business travel,Business,3306,4,3,2,3,4,4,4,4,4,2,4,4,3,4,1,21.0,neutral or dissatisfied +42010,5119,Male,Loyal Customer,46,Business travel,Business,2766,5,5,4,5,2,4,5,4,4,4,4,5,4,5,0,11.0,satisfied +42011,40293,Male,Loyal Customer,67,Personal Travel,Eco,347,3,5,3,3,4,3,5,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +42012,6601,Male,Loyal Customer,57,Personal Travel,Eco,473,2,4,2,4,4,2,5,4,3,1,3,2,3,4,2,0.0,neutral or dissatisfied +42013,6142,Male,Loyal Customer,43,Business travel,Business,3403,4,4,4,4,5,5,4,5,5,5,5,4,5,4,42,41.0,satisfied +42014,52490,Female,Loyal Customer,64,Personal Travel,Eco Plus,751,2,4,2,2,3,5,5,5,5,2,5,5,5,3,129,120.0,neutral or dissatisfied +42015,104929,Female,Loyal Customer,28,Personal Travel,Eco,210,2,4,2,4,1,2,1,1,3,2,3,4,3,1,37,42.0,neutral or dissatisfied +42016,80862,Female,Loyal Customer,66,Personal Travel,Eco,692,3,4,3,4,3,4,5,2,2,3,2,5,2,5,0,8.0,neutral or dissatisfied +42017,56436,Male,disloyal Customer,30,Business travel,Eco,719,2,2,2,3,5,2,5,5,3,2,3,4,3,5,0,11.0,neutral or dissatisfied +42018,79062,Male,Loyal Customer,57,Business travel,Business,3765,3,3,3,3,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +42019,124029,Female,Loyal Customer,28,Personal Travel,Eco,184,3,1,3,4,4,3,4,4,4,1,4,1,3,4,14,5.0,neutral or dissatisfied +42020,101758,Male,Loyal Customer,64,Personal Travel,Eco,1590,3,5,3,4,1,3,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +42021,13808,Female,Loyal Customer,33,Business travel,Business,641,3,3,3,3,4,2,4,4,4,4,4,4,4,3,0,0.0,satisfied +42022,112485,Female,Loyal Customer,24,Personal Travel,Eco,846,3,4,3,2,4,3,4,4,3,2,4,5,4,4,9,1.0,neutral or dissatisfied +42023,82940,Female,Loyal Customer,28,Personal Travel,Eco Plus,594,3,4,3,3,5,3,5,5,4,4,3,1,3,5,0,0.0,neutral or dissatisfied +42024,86994,Female,Loyal Customer,65,Personal Travel,Eco,907,3,4,3,1,5,5,5,1,1,3,1,5,1,4,8,6.0,neutral or dissatisfied +42025,26957,Female,Loyal Customer,40,Business travel,Business,1717,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +42026,110980,Male,Loyal Customer,40,Business travel,Business,197,3,3,3,3,5,4,4,4,4,4,5,4,4,4,11,1.0,satisfied +42027,27637,Female,Loyal Customer,48,Business travel,Eco Plus,554,5,1,1,1,1,3,3,5,5,5,5,5,5,2,0,0.0,satisfied +42028,31320,Male,Loyal Customer,17,Personal Travel,Eco,680,4,4,5,3,4,5,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +42029,30060,Female,Loyal Customer,37,Business travel,Eco,183,4,2,2,2,4,4,4,4,3,5,1,4,3,4,71,57.0,satisfied +42030,34987,Female,Loyal Customer,55,Personal Travel,Eco Plus,273,4,3,4,1,4,5,3,3,3,4,3,5,3,3,0,4.0,neutral or dissatisfied +42031,107866,Male,disloyal Customer,22,Business travel,Business,228,5,3,4,1,3,4,3,3,4,2,5,3,4,3,26,32.0,satisfied +42032,115500,Male,Loyal Customer,40,Business travel,Business,3080,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +42033,78870,Male,Loyal Customer,39,Personal Travel,Eco,1995,2,4,2,5,5,2,5,5,3,5,4,4,5,5,2,11.0,neutral or dissatisfied +42034,1246,Male,Loyal Customer,24,Personal Travel,Eco,164,3,4,3,4,4,3,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +42035,11927,Male,Loyal Customer,29,Personal Travel,Eco,744,3,5,3,3,2,3,2,2,5,4,5,4,4,2,0,2.0,neutral or dissatisfied +42036,410,Male,Loyal Customer,57,Business travel,Business,3687,2,1,1,1,1,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +42037,58873,Female,disloyal Customer,29,Business travel,Business,888,4,4,4,4,1,4,1,1,4,5,5,4,5,1,14,22.0,satisfied +42038,73652,Male,Loyal Customer,57,Business travel,Business,2818,1,1,5,1,5,5,4,4,4,5,4,4,4,5,6,0.0,satisfied +42039,91504,Male,Loyal Customer,39,Business travel,Business,1620,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +42040,39260,Female,Loyal Customer,56,Business travel,Business,2881,1,1,1,1,5,3,3,3,3,3,1,1,3,3,0,18.0,neutral or dissatisfied +42041,9133,Female,Loyal Customer,30,Business travel,Business,3267,3,3,3,3,4,4,4,4,3,4,4,4,3,4,327,326.0,satisfied +42042,20753,Male,Loyal Customer,59,Personal Travel,Eco,363,2,2,3,2,3,3,2,3,4,4,1,3,2,3,4,13.0,neutral or dissatisfied +42043,59305,Male,Loyal Customer,33,Business travel,Business,2367,2,2,2,2,5,5,5,5,4,3,4,4,5,5,7,1.0,satisfied +42044,29666,Male,Loyal Customer,59,Personal Travel,Eco,680,4,5,4,4,3,4,3,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +42045,104053,Female,Loyal Customer,38,Personal Travel,Eco,1044,3,4,3,5,5,3,4,5,5,1,2,1,1,5,12,12.0,neutral or dissatisfied +42046,17505,Male,Loyal Customer,29,Business travel,Business,2668,2,2,2,2,3,4,3,3,1,5,4,1,2,3,16,0.0,satisfied +42047,97050,Male,disloyal Customer,29,Business travel,Business,1242,4,4,4,4,4,5,5,3,3,5,5,5,4,5,301,289.0,neutral or dissatisfied +42048,35052,Male,Loyal Customer,40,Business travel,Business,3415,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +42049,41942,Male,Loyal Customer,49,Business travel,Business,3284,5,5,5,5,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +42050,54306,Male,Loyal Customer,34,Business travel,Business,1597,1,1,1,1,4,4,4,5,5,5,5,4,5,4,4,0.0,satisfied +42051,53431,Female,Loyal Customer,25,Business travel,Business,2288,3,3,3,3,5,4,5,5,3,4,4,2,4,5,0,0.0,satisfied +42052,80049,Male,Loyal Customer,28,Personal Travel,Eco,1069,2,1,2,2,4,2,4,4,3,2,1,4,2,4,0,0.0,neutral or dissatisfied +42053,121304,Male,Loyal Customer,55,Business travel,Business,3959,5,5,5,5,3,5,5,5,5,5,5,3,5,3,7,0.0,satisfied +42054,107508,Male,Loyal Customer,12,Personal Travel,Eco,711,2,4,1,3,5,1,5,5,3,3,4,2,4,5,49,47.0,neutral or dissatisfied +42055,32485,Male,Loyal Customer,67,Business travel,Business,163,1,1,1,1,2,1,5,4,4,4,4,1,4,5,0,0.0,satisfied +42056,73230,Male,Loyal Customer,55,Personal Travel,Eco,946,2,5,3,1,3,3,3,3,5,1,1,3,3,3,0,0.0,neutral or dissatisfied +42057,25922,Male,Loyal Customer,56,Business travel,Eco,594,4,4,1,4,4,4,4,4,1,1,4,4,2,4,7,0.0,satisfied +42058,29898,Male,Loyal Customer,56,Business travel,Eco,261,5,1,1,1,5,5,5,5,3,1,2,4,2,5,0,0.0,satisfied +42059,88867,Male,disloyal Customer,35,Business travel,Business,859,2,2,2,2,4,2,5,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +42060,119150,Female,disloyal Customer,41,Business travel,Business,331,2,2,2,4,4,2,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +42061,29740,Female,disloyal Customer,37,Business travel,Business,548,3,2,2,4,4,2,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +42062,110357,Female,disloyal Customer,25,Business travel,Eco,663,1,2,1,3,2,1,2,2,1,5,3,4,3,2,28,12.0,neutral or dissatisfied +42063,45534,Male,disloyal Customer,28,Business travel,Eco,566,3,1,3,4,2,3,2,2,4,3,3,4,4,2,100,88.0,neutral or dissatisfied +42064,81517,Male,Loyal Customer,50,Business travel,Business,1124,1,1,4,1,2,4,4,3,3,3,3,4,3,4,13,3.0,satisfied +42065,20095,Female,Loyal Customer,34,Business travel,Eco,416,2,5,5,5,2,2,2,2,1,5,3,3,4,2,22,38.0,neutral or dissatisfied +42066,84744,Male,Loyal Customer,32,Business travel,Business,516,4,4,5,4,4,5,4,4,4,3,5,5,4,4,0,0.0,satisfied +42067,11527,Female,Loyal Customer,69,Personal Travel,Eco Plus,429,3,3,2,3,5,3,4,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +42068,6412,Female,Loyal Customer,35,Personal Travel,Eco,315,2,4,2,3,2,2,3,2,4,4,3,2,4,2,0,20.0,neutral or dissatisfied +42069,52071,Female,disloyal Customer,33,Business travel,Eco,639,3,5,3,5,3,3,3,3,1,1,1,5,3,3,47,50.0,neutral or dissatisfied +42070,45267,Male,Loyal Customer,44,Business travel,Business,3357,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +42071,32028,Female,disloyal Customer,55,Business travel,Eco,163,3,3,3,5,5,3,5,5,2,2,3,2,5,5,0,0.0,neutral or dissatisfied +42072,44644,Female,Loyal Customer,38,Business travel,Eco,67,4,1,1,1,4,4,4,4,3,2,4,4,4,4,11,1.0,satisfied +42073,76063,Male,Loyal Customer,39,Business travel,Business,669,1,1,1,1,3,4,5,5,5,5,5,4,5,3,20,68.0,satisfied +42074,47038,Female,Loyal Customer,35,Business travel,Eco,438,4,2,1,2,4,4,4,4,2,3,4,5,3,4,0,0.0,satisfied +42075,99574,Male,disloyal Customer,28,Business travel,Eco,829,2,2,2,3,1,2,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +42076,4683,Male,Loyal Customer,23,Personal Travel,Eco,364,2,5,2,1,2,2,2,2,4,2,5,3,5,2,0,40.0,neutral or dissatisfied +42077,93549,Female,disloyal Customer,21,Business travel,Eco,719,1,1,1,1,4,1,1,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +42078,65382,Female,Loyal Customer,50,Personal Travel,Eco,432,3,3,2,3,1,3,5,2,2,2,4,2,2,5,0,21.0,neutral or dissatisfied +42079,88598,Male,Loyal Customer,12,Personal Travel,Eco,444,4,4,4,5,1,4,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +42080,70642,Female,Loyal Customer,44,Business travel,Business,2214,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +42081,50191,Female,Loyal Customer,26,Business travel,Business,3879,3,2,2,2,3,3,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +42082,32115,Female,Loyal Customer,42,Business travel,Business,216,3,3,3,3,2,4,3,4,4,4,3,1,4,4,1,4.0,neutral or dissatisfied +42083,43016,Female,Loyal Customer,37,Business travel,Business,1554,3,3,2,3,4,4,4,3,3,3,3,2,3,1,47,33.0,neutral or dissatisfied +42084,24179,Female,Loyal Customer,17,Business travel,Eco,134,4,5,3,3,4,4,3,4,2,5,3,4,4,4,10,15.0,neutral or dissatisfied +42085,50343,Male,disloyal Customer,30,Business travel,Eco,134,1,1,0,4,3,0,5,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +42086,119353,Male,Loyal Customer,40,Personal Travel,Eco Plus,214,5,5,5,4,1,5,1,1,3,2,4,5,5,1,0,0.0,satisfied +42087,90103,Female,disloyal Customer,27,Business travel,Eco,957,1,1,1,3,2,1,2,2,4,4,3,1,4,2,1,0.0,neutral or dissatisfied +42088,66628,Female,Loyal Customer,17,Personal Travel,Business,802,3,1,3,2,2,3,3,2,3,1,2,4,2,2,25,29.0,neutral or dissatisfied +42089,72419,Female,Loyal Customer,25,Business travel,Business,918,5,5,5,5,4,4,4,4,3,5,4,5,4,4,0,0.0,satisfied +42090,125991,Female,Loyal Customer,54,Personal Travel,Business,507,1,4,1,3,5,1,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +42091,112105,Male,Loyal Customer,25,Personal Travel,Eco,1062,2,4,2,2,5,2,1,5,4,4,5,5,5,5,58,34.0,neutral or dissatisfied +42092,16741,Male,Loyal Customer,56,Personal Travel,Eco,1167,4,5,4,3,4,4,4,4,4,4,5,4,5,4,0,8.0,neutral or dissatisfied +42093,16729,Male,Loyal Customer,36,Business travel,Eco,1167,1,5,5,5,1,1,1,1,4,2,3,2,3,1,0,21.0,neutral or dissatisfied +42094,1502,Female,Loyal Customer,15,Personal Travel,Eco,737,3,4,2,3,2,2,2,2,4,3,5,3,4,2,0,4.0,neutral or dissatisfied +42095,13416,Female,Loyal Customer,47,Business travel,Business,409,4,4,4,4,3,4,2,4,4,4,4,4,4,5,0,0.0,satisfied +42096,44631,Male,Loyal Customer,57,Business travel,Business,2587,5,5,5,5,1,1,4,4,4,4,4,3,4,4,0,71.0,satisfied +42097,112145,Male,Loyal Customer,51,Business travel,Business,895,4,4,4,4,5,5,5,3,3,3,3,5,3,5,4,0.0,satisfied +42098,45566,Female,Loyal Customer,23,Personal Travel,Eco,1304,3,5,3,3,5,3,5,5,5,4,4,4,4,5,55,44.0,neutral or dissatisfied +42099,97655,Male,Loyal Customer,38,Business travel,Business,2922,2,2,2,2,3,5,4,4,4,4,4,5,4,3,17,13.0,satisfied +42100,35826,Male,Loyal Customer,37,Business travel,Eco,997,4,4,4,4,4,4,4,4,2,1,5,4,1,4,371,372.0,satisfied +42101,32361,Male,Loyal Customer,39,Business travel,Business,2396,0,3,0,4,1,3,4,5,5,5,5,2,5,3,0,0.0,satisfied +42102,28070,Male,Loyal Customer,68,Personal Travel,Eco,2603,5,5,5,2,5,5,5,1,5,5,3,5,5,5,20,52.0,satisfied +42103,31315,Female,Loyal Customer,51,Personal Travel,Eco,680,2,5,2,5,4,5,5,5,5,2,5,5,5,3,8,8.0,neutral or dissatisfied +42104,93535,Male,Loyal Customer,56,Personal Travel,Eco,1315,1,5,2,3,1,2,2,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +42105,34878,Male,Loyal Customer,64,Personal Travel,Eco,2248,1,4,1,3,1,2,2,5,4,3,4,2,4,2,16,40.0,neutral or dissatisfied +42106,65691,Female,Loyal Customer,45,Business travel,Business,936,4,4,5,4,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +42107,65213,Male,Loyal Customer,36,Business travel,Business,2387,2,2,2,2,5,4,5,4,4,4,5,5,4,5,0,0.0,satisfied +42108,11023,Male,Loyal Customer,43,Business travel,Business,3079,3,3,3,3,4,5,5,5,5,5,3,3,5,4,0,0.0,satisfied +42109,86473,Female,Loyal Customer,57,Business travel,Eco,312,5,4,1,4,5,2,5,5,5,5,5,1,5,5,0,0.0,satisfied +42110,43622,Male,Loyal Customer,37,Personal Travel,Eco,297,4,4,4,4,1,4,1,1,5,2,5,5,5,1,0,6.0,satisfied +42111,122741,Male,Loyal Customer,29,Business travel,Business,3688,4,4,4,4,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +42112,66,Male,Loyal Customer,36,Business travel,Business,173,1,5,5,5,4,3,3,3,3,3,1,2,3,3,12,8.0,neutral or dissatisfied +42113,107164,Female,Loyal Customer,54,Business travel,Business,3918,3,3,1,3,5,5,5,5,4,4,5,5,5,5,124,143.0,satisfied +42114,48091,Female,Loyal Customer,55,Business travel,Eco,236,5,3,3,3,1,3,3,5,5,5,5,2,5,3,29,24.0,satisfied +42115,13256,Male,Loyal Customer,53,Business travel,Eco,772,2,2,2,2,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +42116,21509,Female,Loyal Customer,42,Personal Travel,Eco,164,1,2,1,4,1,4,4,3,3,1,3,1,3,4,10,2.0,neutral or dissatisfied +42117,102663,Male,Loyal Customer,43,Business travel,Business,255,3,3,3,3,2,4,4,5,5,5,5,3,5,3,4,0.0,satisfied +42118,125335,Female,Loyal Customer,57,Business travel,Business,599,3,3,3,3,4,5,5,4,4,5,4,5,4,4,4,1.0,satisfied +42119,36094,Male,Loyal Customer,25,Personal Travel,Eco,399,2,4,2,3,3,2,3,3,5,5,5,4,4,3,65,55.0,neutral or dissatisfied +42120,103530,Female,Loyal Customer,58,Business travel,Business,1719,1,1,1,1,2,4,4,5,5,5,5,4,5,3,12,2.0,satisfied +42121,22310,Male,disloyal Customer,16,Business travel,Eco,83,1,3,1,3,4,1,4,4,2,5,4,1,4,4,39,31.0,neutral or dissatisfied +42122,55697,Male,disloyal Customer,25,Business travel,Eco,1062,3,3,3,4,3,3,2,3,1,3,4,4,3,3,0,2.0,neutral or dissatisfied +42123,94712,Female,disloyal Customer,26,Business travel,Eco,323,2,2,2,4,4,2,4,4,4,2,3,2,4,4,11,13.0,neutral or dissatisfied +42124,71826,Female,Loyal Customer,18,Business travel,Business,1726,2,2,2,2,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +42125,120852,Male,Loyal Customer,18,Personal Travel,Business,861,3,4,4,1,5,4,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +42126,45833,Female,Loyal Customer,62,Personal Travel,Eco,391,3,5,3,1,3,4,4,4,4,5,5,4,4,4,147,137.0,neutral or dissatisfied +42127,120420,Male,Loyal Customer,39,Business travel,Eco,366,2,2,2,2,2,2,2,2,3,3,2,2,2,2,3,0.0,neutral or dissatisfied +42128,103314,Female,Loyal Customer,47,Business travel,Business,1139,3,1,1,1,1,4,4,3,3,4,3,1,3,4,68,84.0,neutral or dissatisfied +42129,123008,Male,Loyal Customer,25,Business travel,Business,3975,3,2,3,3,4,4,4,4,3,4,4,3,5,4,45,37.0,satisfied +42130,8225,Female,Loyal Customer,20,Personal Travel,Eco,335,3,4,5,5,3,5,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +42131,73016,Male,Loyal Customer,11,Personal Travel,Eco,1096,1,3,0,4,3,0,3,3,3,2,3,4,4,3,10,13.0,neutral or dissatisfied +42132,85948,Female,Loyal Customer,48,Business travel,Business,554,1,1,1,1,2,5,5,4,4,5,4,4,4,4,1,0.0,satisfied +42133,123253,Male,Loyal Customer,59,Personal Travel,Eco,468,4,5,4,3,3,4,3,3,5,5,4,3,5,3,9,14.0,neutral or dissatisfied +42134,129656,Male,Loyal Customer,35,Business travel,Business,337,4,4,5,4,3,4,4,4,4,4,4,3,4,3,67,63.0,satisfied +42135,59053,Male,disloyal Customer,38,Business travel,Eco,1726,2,2,2,3,2,2,2,2,3,4,4,3,3,2,19,0.0,neutral or dissatisfied +42136,98473,Male,Loyal Customer,28,Personal Travel,Eco,210,1,4,1,4,4,1,4,4,3,1,3,1,4,4,6,1.0,neutral or dissatisfied +42137,80630,Male,Loyal Customer,43,Business travel,Business,2351,3,3,3,3,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +42138,70695,Male,Loyal Customer,39,Business travel,Eco Plus,447,3,5,3,5,3,3,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +42139,57194,Female,disloyal Customer,28,Business travel,Business,1514,4,3,3,1,4,3,4,4,4,2,4,5,5,4,0,0.0,satisfied +42140,19452,Male,Loyal Customer,35,Business travel,Business,3206,4,4,4,4,1,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +42141,125432,Male,Loyal Customer,69,Personal Travel,Eco,735,4,5,4,3,5,4,5,5,1,3,4,1,4,5,0,0.0,satisfied +42142,83698,Female,Loyal Customer,18,Personal Travel,Eco,577,2,2,2,3,5,2,5,5,1,2,3,3,3,5,66,100.0,neutral or dissatisfied +42143,127420,Female,Loyal Customer,55,Personal Travel,Eco,1009,3,2,3,4,3,3,4,1,1,3,1,2,1,3,4,0.0,neutral or dissatisfied +42144,92352,Male,Loyal Customer,65,Personal Travel,Eco,2399,2,5,1,3,1,1,1,5,4,3,4,1,4,1,0,7.0,neutral or dissatisfied +42145,41962,Female,Loyal Customer,17,Business travel,Business,2062,1,0,0,3,2,0,5,2,2,2,2,1,3,2,0,0.0,neutral or dissatisfied +42146,118969,Male,Loyal Customer,22,Personal Travel,Eco,570,2,3,2,3,5,2,5,5,1,5,3,4,4,5,0,0.0,neutral or dissatisfied +42147,45102,Male,Loyal Customer,39,Business travel,Business,3143,3,3,3,3,2,1,1,4,4,4,5,4,4,4,43,37.0,satisfied +42148,76728,Male,Loyal Customer,72,Business travel,Eco Plus,147,5,2,2,2,5,5,5,5,2,2,1,4,3,5,0,0.0,satisfied +42149,96638,Female,Loyal Customer,50,Business travel,Business,937,5,5,5,5,4,4,5,4,4,4,4,3,4,5,2,0.0,satisfied +42150,79299,Male,Loyal Customer,48,Business travel,Business,2248,2,2,2,2,5,3,5,4,4,4,4,3,4,3,97,81.0,satisfied +42151,43034,Female,Loyal Customer,36,Business travel,Business,3624,5,5,5,5,1,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +42152,100358,Male,Loyal Customer,50,Personal Travel,Eco,1052,2,4,2,4,5,2,5,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +42153,28786,Female,Loyal Customer,31,Business travel,Business,605,2,2,2,2,2,2,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +42154,12893,Male,Loyal Customer,44,Business travel,Business,2247,4,1,4,4,4,1,3,4,4,5,4,3,4,5,0,0.0,satisfied +42155,110351,Female,Loyal Customer,22,Business travel,Business,925,2,2,1,2,4,4,4,4,5,2,5,4,4,4,34,12.0,satisfied +42156,79391,Male,disloyal Customer,32,Business travel,Business,502,1,1,1,3,2,1,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +42157,85060,Female,Loyal Customer,30,Business travel,Business,3874,3,3,3,3,4,4,4,4,5,3,4,3,4,4,0,9.0,satisfied +42158,61962,Male,Loyal Customer,29,Personal Travel,Eco,2161,4,1,4,4,5,4,5,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +42159,66167,Male,Loyal Customer,34,Business travel,Business,460,5,5,5,5,4,4,5,3,3,2,3,5,3,3,1,0.0,satisfied +42160,129460,Male,Loyal Customer,55,Business travel,Business,2590,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +42161,114944,Female,Loyal Customer,46,Business travel,Business,373,1,1,5,1,3,5,5,4,4,4,4,5,4,4,79,66.0,satisfied +42162,51531,Female,Loyal Customer,52,Business travel,Business,370,1,1,4,1,4,2,5,4,4,4,4,3,4,3,0,0.0,satisfied +42163,32536,Female,Loyal Customer,41,Business travel,Eco,163,4,3,3,3,4,4,4,4,2,4,3,3,2,4,3,0.0,satisfied +42164,51370,Male,Loyal Customer,28,Personal Travel,Eco Plus,109,2,0,2,1,3,2,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +42165,69293,Female,Loyal Customer,40,Business travel,Business,2024,3,3,3,3,5,4,5,4,4,4,4,5,4,3,7,14.0,satisfied +42166,126113,Female,Loyal Customer,52,Business travel,Business,507,1,3,5,3,5,4,4,1,1,1,1,2,1,1,4,9.0,neutral or dissatisfied +42167,105938,Female,Loyal Customer,44,Personal Travel,Eco,1491,1,5,1,3,4,5,1,1,1,1,1,3,1,3,0,8.0,neutral or dissatisfied +42168,24431,Female,Loyal Customer,63,Personal Travel,Eco,634,2,5,2,2,3,4,5,1,1,2,1,3,1,5,0,1.0,neutral or dissatisfied +42169,120698,Male,Loyal Customer,63,Personal Travel,Eco,280,1,5,1,1,1,1,1,1,5,2,4,4,5,1,82,86.0,neutral or dissatisfied +42170,36271,Female,Loyal Customer,57,Personal Travel,Eco,728,2,4,1,4,4,3,5,2,2,1,2,2,2,3,19,7.0,neutral or dissatisfied +42171,40379,Female,Loyal Customer,26,Personal Travel,Eco,1250,4,5,3,2,1,3,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +42172,122291,Female,Loyal Customer,38,Personal Travel,Eco,603,3,4,3,3,3,3,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +42173,31239,Male,Loyal Customer,41,Business travel,Business,472,1,1,3,1,3,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +42174,111618,Female,Loyal Customer,53,Business travel,Business,3245,3,4,4,4,3,3,3,4,1,4,3,3,2,3,147,167.0,neutral or dissatisfied +42175,24209,Female,Loyal Customer,41,Business travel,Business,147,1,1,1,1,1,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +42176,72507,Male,Loyal Customer,27,Business travel,Business,3247,5,5,5,5,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +42177,32814,Male,disloyal Customer,35,Business travel,Eco,101,4,4,4,4,2,4,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +42178,111285,Female,Loyal Customer,54,Personal Travel,Eco,459,2,4,2,2,4,5,5,3,3,2,3,5,3,5,0,10.0,neutral or dissatisfied +42179,97471,Male,Loyal Customer,41,Business travel,Business,2297,2,2,5,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +42180,97552,Male,Loyal Customer,46,Business travel,Eco Plus,675,2,5,2,2,2,2,2,2,4,3,3,3,4,2,24,9.0,neutral or dissatisfied +42181,51121,Male,Loyal Customer,56,Personal Travel,Eco,109,2,4,2,2,1,2,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +42182,37453,Male,Loyal Customer,25,Business travel,Business,2438,3,1,1,1,3,3,3,3,4,5,4,2,4,3,0,15.0,neutral or dissatisfied +42183,64674,Female,Loyal Customer,57,Business travel,Business,2968,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +42184,192,Male,Loyal Customer,52,Business travel,Business,2129,2,2,3,2,5,4,4,2,2,2,2,2,2,3,95,85.0,neutral or dissatisfied +42185,115903,Male,Loyal Customer,57,Business travel,Eco,296,2,2,2,2,2,2,2,2,4,5,3,2,4,2,0,0.0,neutral or dissatisfied +42186,111060,Female,Loyal Customer,60,Personal Travel,Eco,319,3,5,2,4,2,2,3,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +42187,65092,Female,Loyal Customer,70,Personal Travel,Eco,190,3,3,3,4,2,4,3,2,2,3,2,1,2,3,1,3.0,neutral or dissatisfied +42188,128782,Male,Loyal Customer,59,Business travel,Business,2248,2,2,2,2,2,4,4,4,4,4,4,4,4,5,3,0.0,satisfied +42189,57970,Female,Loyal Customer,25,Personal Travel,Eco Plus,1670,3,3,3,1,3,3,3,3,5,2,4,5,4,3,2,6.0,neutral or dissatisfied +42190,124740,Male,Loyal Customer,24,Personal Travel,Eco Plus,399,4,4,4,2,4,4,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +42191,51129,Female,Loyal Customer,21,Personal Travel,Eco,109,1,4,1,2,5,1,5,5,4,3,3,3,1,5,0,0.0,neutral or dissatisfied +42192,78405,Female,Loyal Customer,59,Business travel,Business,201,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +42193,22423,Male,Loyal Customer,34,Personal Travel,Eco,238,5,5,0,4,4,0,4,4,5,2,4,5,4,4,0,28.0,satisfied +42194,113530,Female,Loyal Customer,56,Business travel,Business,2489,4,4,4,4,2,5,4,5,5,5,5,3,5,4,29,12.0,satisfied +42195,53049,Female,Loyal Customer,8,Personal Travel,Eco,1208,4,2,4,4,2,4,2,2,4,1,3,2,4,2,10,0.0,neutral or dissatisfied +42196,102754,Male,Loyal Customer,31,Personal Travel,Eco Plus,365,4,1,1,3,3,1,3,3,2,2,2,4,2,3,0,0.0,satisfied +42197,20012,Male,Loyal Customer,29,Personal Travel,Eco,589,3,4,3,3,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +42198,100683,Female,Loyal Customer,51,Business travel,Business,1785,3,4,4,4,1,3,4,3,3,3,3,3,3,2,4,36.0,neutral or dissatisfied +42199,122279,Female,Loyal Customer,56,Personal Travel,Eco,544,5,3,2,4,4,4,4,4,4,2,4,4,4,2,0,0.0,satisfied +42200,12013,Male,Loyal Customer,37,Personal Travel,Business,376,2,5,2,4,2,4,5,5,5,2,5,5,5,3,0,12.0,neutral or dissatisfied +42201,94101,Male,Loyal Customer,10,Personal Travel,Business,562,3,1,3,3,2,3,2,2,1,1,4,3,3,2,37,29.0,neutral or dissatisfied +42202,109824,Female,Loyal Customer,39,Business travel,Business,1011,4,4,4,4,2,5,5,5,5,5,5,3,5,5,7,6.0,satisfied +42203,85678,Female,Loyal Customer,37,Business travel,Eco Plus,503,4,1,1,1,4,4,4,4,1,2,3,4,1,4,0,0.0,satisfied +42204,2959,Male,Loyal Customer,39,Business travel,Eco,737,3,1,1,1,3,3,3,3,2,2,3,3,4,3,0,9.0,neutral or dissatisfied +42205,10456,Female,Loyal Customer,48,Business travel,Business,2238,5,5,5,5,4,4,4,5,5,5,5,4,5,3,3,19.0,satisfied +42206,85615,Male,Loyal Customer,18,Personal Travel,Eco,259,3,5,3,4,4,3,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +42207,55511,Female,disloyal Customer,23,Business travel,Eco,991,3,2,2,3,2,2,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +42208,55458,Female,Loyal Customer,62,Personal Travel,Eco,2327,3,5,3,3,4,4,5,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +42209,24643,Female,Loyal Customer,32,Personal Travel,Eco Plus,666,2,4,2,4,2,2,5,2,1,3,5,1,4,2,1,0.0,neutral or dissatisfied +42210,114973,Female,disloyal Customer,30,Business travel,Business,337,1,1,1,4,2,1,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +42211,14210,Female,Loyal Customer,25,Business travel,Business,3785,5,5,5,5,5,5,5,5,4,4,4,2,3,5,0,0.0,satisfied +42212,11686,Female,Loyal Customer,52,Business travel,Business,175,5,3,5,5,2,4,5,4,4,4,5,5,4,4,106,105.0,satisfied +42213,48009,Male,Loyal Customer,9,Personal Travel,Eco Plus,550,2,0,2,3,2,2,4,2,2,5,2,4,4,2,0,0.0,neutral or dissatisfied +42214,63504,Female,Loyal Customer,25,Personal Travel,Eco,1956,3,5,3,3,2,3,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +42215,48170,Female,Loyal Customer,24,Business travel,Business,3408,2,4,4,4,2,2,2,2,4,2,2,3,2,2,0,12.0,neutral or dissatisfied +42216,74945,Male,Loyal Customer,53,Business travel,Business,2475,3,3,3,3,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +42217,30685,Male,disloyal Customer,48,Business travel,Eco,680,1,1,1,4,3,1,3,3,1,5,3,1,4,3,0,8.0,neutral or dissatisfied +42218,100483,Male,Loyal Customer,53,Business travel,Business,3264,1,1,1,1,3,4,5,5,5,5,5,3,5,5,2,0.0,satisfied +42219,60054,Male,Loyal Customer,22,Personal Travel,Eco Plus,997,3,4,2,2,2,4,4,3,5,4,4,4,5,4,437,429.0,neutral or dissatisfied +42220,56993,Female,Loyal Customer,19,Personal Travel,Eco,2454,1,3,1,2,1,3,3,2,5,3,3,3,4,3,0,10.0,neutral or dissatisfied +42221,1932,Male,Loyal Customer,39,Business travel,Business,3777,3,3,3,3,2,5,5,5,5,5,5,5,5,5,9,0.0,satisfied +42222,125669,Male,Loyal Customer,42,Business travel,Business,759,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +42223,26480,Male,Loyal Customer,36,Business travel,Eco Plus,842,4,1,1,1,4,4,4,4,5,2,4,2,2,4,0,0.0,satisfied +42224,48393,Male,Loyal Customer,32,Personal Travel,Eco,522,2,5,2,4,3,2,3,3,3,2,5,3,5,3,59,43.0,neutral or dissatisfied +42225,94394,Female,Loyal Customer,60,Business travel,Business,3182,1,1,1,1,5,4,4,5,5,4,4,4,5,5,13,11.0,satisfied +42226,20589,Male,disloyal Customer,26,Business travel,Eco Plus,533,2,2,2,1,5,2,5,5,5,4,3,5,2,5,0,0.0,neutral or dissatisfied +42227,87084,Male,Loyal Customer,47,Business travel,Business,1737,4,2,5,2,2,3,4,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +42228,80254,Male,Loyal Customer,70,Business travel,Eco Plus,869,5,4,1,4,5,5,5,5,1,4,4,5,2,5,0,0.0,satisfied +42229,9411,Female,Loyal Customer,27,Personal Travel,Eco,1027,3,4,3,3,3,3,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +42230,28964,Male,disloyal Customer,25,Business travel,Eco,978,3,3,3,3,1,3,1,1,1,4,3,4,5,1,0,0.0,neutral or dissatisfied +42231,27198,Male,Loyal Customer,17,Personal Travel,Eco,2182,3,3,2,4,1,2,1,1,4,4,1,5,2,1,0,0.0,neutral or dissatisfied +42232,93492,Male,Loyal Customer,46,Business travel,Eco,1107,2,2,2,2,2,2,2,2,4,4,3,1,3,2,12,3.0,neutral or dissatisfied +42233,74143,Male,disloyal Customer,23,Business travel,Eco,721,3,3,3,3,3,3,3,3,2,3,4,4,4,3,0,0.0,neutral or dissatisfied +42234,67962,Female,Loyal Customer,44,Business travel,Business,1464,3,3,5,3,3,5,4,4,4,4,4,5,4,5,17,17.0,satisfied +42235,50575,Female,Loyal Customer,54,Personal Travel,Eco,337,3,5,3,5,3,5,5,2,2,3,5,5,2,3,0,0.0,neutral or dissatisfied +42236,94477,Female,Loyal Customer,53,Business travel,Business,2936,2,2,2,2,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +42237,39837,Male,Loyal Customer,31,Business travel,Eco,272,5,5,5,5,5,5,5,5,5,3,4,3,2,5,0,0.0,satisfied +42238,25272,Female,Loyal Customer,30,Business travel,Business,2840,2,2,2,2,2,2,2,2,2,3,4,3,4,2,0,0.0,neutral or dissatisfied +42239,63476,Female,Loyal Customer,14,Personal Travel,Eco Plus,372,2,1,2,3,3,2,3,3,4,4,1,3,2,3,14,18.0,neutral or dissatisfied +42240,18314,Female,disloyal Customer,23,Business travel,Eco,705,4,4,4,4,5,4,5,5,4,1,4,1,5,5,0,0.0,satisfied +42241,110024,Female,Loyal Customer,37,Personal Travel,Eco,1142,2,5,2,2,2,3,3,3,5,3,4,3,4,3,164,156.0,neutral or dissatisfied +42242,124182,Male,Loyal Customer,44,Personal Travel,Eco,2089,5,0,5,1,5,5,5,5,3,5,5,3,4,5,0,0.0,satisfied +42243,112293,Female,Loyal Customer,34,Business travel,Eco Plus,1703,2,5,5,5,2,2,2,2,1,2,1,4,2,2,0,8.0,neutral or dissatisfied +42244,113842,Male,Loyal Customer,44,Business travel,Business,1334,2,2,5,2,4,4,5,2,2,2,2,4,2,3,18,20.0,satisfied +42245,46450,Male,Loyal Customer,55,Business travel,Business,152,0,5,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +42246,95517,Female,Loyal Customer,39,Business travel,Eco Plus,189,4,5,5,5,4,4,4,4,2,2,2,4,3,4,58,60.0,satisfied +42247,123445,Male,Loyal Customer,45,Business travel,Business,2077,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,16.0,satisfied +42248,3350,Female,Loyal Customer,56,Business travel,Business,3216,2,1,1,1,2,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +42249,31639,Female,disloyal Customer,37,Business travel,Eco,967,4,4,4,3,2,4,2,2,4,2,2,3,3,2,0,0.0,satisfied +42250,127286,Male,Loyal Customer,60,Personal Travel,Eco,1107,4,1,4,3,1,4,1,1,4,3,3,3,2,1,13,0.0,neutral or dissatisfied +42251,126595,Female,Loyal Customer,38,Business travel,Business,1337,3,3,3,3,3,5,5,3,3,3,3,4,3,3,6,0.0,satisfied +42252,91856,Female,Loyal Customer,63,Personal Travel,Eco,1797,2,5,2,3,5,5,4,1,1,2,1,5,1,5,11,10.0,neutral or dissatisfied +42253,105126,Female,Loyal Customer,33,Business travel,Business,3636,4,3,3,3,4,3,3,4,4,4,4,2,4,3,0,4.0,neutral or dissatisfied +42254,67841,Male,Loyal Customer,10,Personal Travel,Eco,1235,4,5,3,1,3,3,3,3,3,2,1,1,4,3,0,0.0,satisfied +42255,121791,Male,disloyal Customer,40,Business travel,Business,449,4,4,4,1,2,4,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +42256,128445,Female,Loyal Customer,36,Business travel,Business,1811,5,5,3,5,5,1,4,2,2,2,2,4,2,2,0,3.0,satisfied +42257,48747,Female,Loyal Customer,44,Business travel,Business,1860,2,5,5,5,4,3,4,2,2,2,2,1,2,4,16,16.0,neutral or dissatisfied +42258,54572,Female,Loyal Customer,62,Business travel,Eco Plus,525,5,1,1,1,2,1,4,5,5,5,5,5,5,1,0,0.0,satisfied +42259,104292,Female,Loyal Customer,41,Business travel,Business,440,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +42260,30119,Female,Loyal Customer,27,Personal Travel,Eco,571,1,5,1,2,4,1,5,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +42261,92496,Male,Loyal Customer,18,Business travel,Business,1947,3,3,3,3,4,4,4,4,5,4,3,4,3,4,0,0.0,satisfied +42262,42579,Female,Loyal Customer,30,Personal Travel,Eco,315,3,3,3,3,4,3,4,4,1,1,5,3,2,4,41,76.0,neutral or dissatisfied +42263,69587,Female,Loyal Customer,31,Personal Travel,Eco,2475,2,4,2,3,2,2,2,5,3,5,5,2,4,2,0,6.0,neutral or dissatisfied +42264,34925,Male,disloyal Customer,59,Business travel,Eco,187,1,2,0,4,1,0,1,1,2,1,4,4,4,1,0,0.0,neutral or dissatisfied +42265,66291,Male,disloyal Customer,20,Business travel,Eco,852,4,4,4,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +42266,55247,Female,Loyal Customer,41,Personal Travel,Eco,1009,2,5,2,4,3,2,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +42267,31981,Female,disloyal Customer,26,Business travel,Business,101,2,5,2,1,4,2,4,4,4,5,4,3,4,4,0,2.0,neutral or dissatisfied +42268,116598,Male,Loyal Customer,45,Business travel,Business,2433,5,5,5,5,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +42269,127056,Male,Loyal Customer,23,Business travel,Business,3756,1,1,1,1,3,3,3,3,3,4,5,5,4,3,2,0.0,satisfied +42270,25724,Female,Loyal Customer,36,Personal Travel,Eco,447,2,4,2,3,5,2,5,5,3,5,4,3,4,5,16,15.0,neutral or dissatisfied +42271,25312,Male,disloyal Customer,63,Business travel,Eco,432,1,3,1,4,1,1,1,1,2,1,3,2,4,1,0,3.0,neutral or dissatisfied +42272,122712,Male,Loyal Customer,41,Business travel,Business,3034,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +42273,108581,Female,disloyal Customer,24,Business travel,Eco,696,4,4,4,4,1,4,1,1,3,4,4,5,5,1,0,0.0,satisfied +42274,5527,Male,disloyal Customer,39,Business travel,Business,404,4,3,3,3,4,3,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +42275,47341,Female,Loyal Customer,36,Business travel,Business,2577,3,3,3,3,5,3,5,4,4,4,4,2,4,4,0,0.0,satisfied +42276,96817,Female,Loyal Customer,44,Business travel,Business,849,4,4,4,4,4,4,4,5,5,4,5,3,5,5,9,2.0,satisfied +42277,39885,Female,Loyal Customer,10,Personal Travel,Eco,221,1,3,0,3,4,0,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +42278,129695,Male,disloyal Customer,26,Business travel,Eco,447,3,3,4,3,4,4,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +42279,67477,Female,Loyal Customer,25,Personal Travel,Eco,641,1,4,1,4,1,1,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +42280,114641,Male,Loyal Customer,40,Business travel,Business,2270,3,1,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +42281,68969,Female,disloyal Customer,26,Business travel,Business,700,2,0,1,1,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +42282,113053,Female,Loyal Customer,16,Business travel,Business,2071,3,3,3,3,4,4,4,4,4,5,4,5,4,4,24,14.0,satisfied +42283,4492,Female,Loyal Customer,47,Business travel,Business,551,3,1,3,3,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +42284,56664,Female,Loyal Customer,50,Personal Travel,Eco,997,5,5,5,3,3,4,4,4,4,5,1,3,4,5,64,57.0,satisfied +42285,88502,Female,Loyal Customer,36,Business travel,Business,115,2,3,3,3,2,4,4,4,4,4,2,2,4,1,0,7.0,neutral or dissatisfied +42286,96443,Male,Loyal Customer,56,Business travel,Business,2655,1,1,3,1,4,4,4,3,5,4,5,4,3,4,121,137.0,satisfied +42287,34674,Male,Loyal Customer,37,Business travel,Eco,264,3,5,5,5,3,4,3,3,2,1,3,5,5,3,2,0.0,satisfied +42288,12788,Female,Loyal Customer,35,Business travel,Eco,528,5,5,5,5,5,5,5,5,1,1,2,4,2,5,26,16.0,satisfied +42289,127784,Male,Loyal Customer,53,Personal Travel,Eco,1037,4,2,4,3,5,4,4,5,1,3,2,3,3,5,0,0.0,satisfied +42290,58282,Female,Loyal Customer,18,Personal Travel,Eco,678,1,4,1,2,4,1,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +42291,1829,Male,Loyal Customer,22,Personal Travel,Eco,408,3,4,3,1,2,3,3,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +42292,110539,Female,disloyal Customer,30,Business travel,Business,674,1,1,1,1,2,1,5,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +42293,101903,Female,Loyal Customer,43,Business travel,Eco,1984,1,1,5,5,1,4,3,1,1,1,1,1,1,4,11,0.0,neutral or dissatisfied +42294,111851,Female,disloyal Customer,40,Business travel,Business,628,1,1,1,2,2,1,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +42295,82394,Female,Loyal Customer,36,Business travel,Business,3159,3,4,4,4,2,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +42296,53091,Female,Loyal Customer,25,Business travel,Eco Plus,2327,5,5,5,5,5,4,5,2,5,4,5,5,4,5,12,17.0,satisfied +42297,13045,Male,Loyal Customer,56,Personal Travel,Eco,374,1,5,1,2,2,1,2,2,2,1,3,3,2,2,79,71.0,neutral or dissatisfied +42298,74791,Male,disloyal Customer,24,Business travel,Eco,1235,3,3,3,2,5,3,5,5,5,2,4,5,4,5,0,0.0,neutral or dissatisfied +42299,52119,Male,Loyal Customer,33,Business travel,Eco Plus,639,5,1,3,1,5,5,5,5,3,1,1,4,4,5,0,0.0,satisfied +42300,12704,Female,disloyal Customer,26,Business travel,Eco,689,3,3,3,2,5,3,5,5,3,4,1,3,1,5,0,,neutral or dissatisfied +42301,109335,Male,Loyal Customer,40,Personal Travel,Eco,1188,2,5,2,3,4,2,4,4,5,3,4,3,4,4,5,17.0,neutral or dissatisfied +42302,112184,Male,Loyal Customer,49,Personal Travel,Eco,895,1,2,1,2,1,1,1,1,3,5,2,3,3,1,1,0.0,neutral or dissatisfied +42303,113440,Female,Loyal Customer,56,Business travel,Eco,386,3,3,3,3,4,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +42304,100420,Female,Loyal Customer,34,Personal Travel,Eco Plus,971,4,5,4,3,5,4,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +42305,55631,Male,disloyal Customer,18,Business travel,Eco,841,2,2,2,2,5,2,5,5,4,2,3,5,5,5,0,0.0,neutral or dissatisfied +42306,76530,Male,Loyal Customer,55,Business travel,Business,2242,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +42307,30393,Male,Loyal Customer,35,Personal Travel,Eco,862,4,5,5,4,2,5,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +42308,105028,Male,Loyal Customer,41,Business travel,Business,3360,4,1,1,1,1,3,3,4,4,4,4,3,4,2,14,19.0,neutral or dissatisfied +42309,55305,Male,Loyal Customer,50,Business travel,Business,2072,1,1,1,1,3,4,5,3,3,3,3,3,3,4,0,26.0,satisfied +42310,111476,Female,Loyal Customer,37,Personal Travel,Business,1452,3,5,3,2,3,5,4,5,5,3,5,2,5,3,36,44.0,neutral or dissatisfied +42311,102958,Female,Loyal Customer,39,Personal Travel,Eco,719,2,4,2,1,1,2,1,1,5,5,4,4,4,1,45,45.0,neutral or dissatisfied +42312,95095,Male,Loyal Customer,31,Personal Travel,Eco,562,2,4,1,2,1,1,1,1,4,5,4,4,4,1,4,1.0,neutral or dissatisfied +42313,102665,Female,Loyal Customer,59,Business travel,Business,255,5,5,5,5,4,4,5,5,5,5,5,5,5,3,75,72.0,satisfied +42314,81046,Female,Loyal Customer,40,Business travel,Business,1399,3,2,2,2,2,4,4,3,3,2,3,3,3,4,6,3.0,neutral or dissatisfied +42315,21305,Male,Loyal Customer,65,Personal Travel,Eco,714,5,4,5,2,3,4,3,3,4,2,5,4,4,3,0,0.0,satisfied +42316,24191,Male,Loyal Customer,36,Business travel,Business,302,3,3,3,3,1,3,5,4,4,4,4,1,4,2,0,0.0,satisfied +42317,48558,Female,Loyal Customer,67,Personal Travel,Eco,948,1,1,2,2,4,1,3,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +42318,49662,Female,Loyal Customer,22,Business travel,Business,308,2,2,2,2,4,4,4,4,1,2,2,2,4,4,16,3.0,satisfied +42319,14651,Male,Loyal Customer,35,Business travel,Eco,112,4,2,4,4,4,4,4,4,2,2,4,2,3,4,0,2.0,satisfied +42320,66210,Female,Loyal Customer,24,Business travel,Business,550,4,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0.0,satisfied +42321,68725,Female,disloyal Customer,29,Business travel,Eco Plus,237,3,3,3,4,5,3,5,5,1,2,3,1,4,5,0,0.0,neutral or dissatisfied +42322,91796,Female,Loyal Customer,11,Personal Travel,Eco,588,4,4,4,3,4,4,4,4,5,2,4,4,5,4,0,0.0,satisfied +42323,97412,Female,Loyal Customer,41,Business travel,Business,3651,3,3,3,3,5,4,5,4,4,4,4,3,4,3,6,1.0,satisfied +42324,82804,Female,Loyal Customer,51,Business travel,Business,235,1,1,1,1,2,4,4,1,1,2,1,1,1,4,12,1.0,neutral or dissatisfied +42325,35951,Female,disloyal Customer,23,Business travel,Eco,231,0,0,0,3,3,0,3,3,5,4,4,1,2,3,0,0.0,satisfied +42326,37362,Female,Loyal Customer,63,Business travel,Business,972,4,4,4,4,2,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +42327,5459,Male,Loyal Customer,40,Business travel,Eco,265,3,3,3,3,3,3,3,3,2,3,4,3,3,3,17,16.0,neutral or dissatisfied +42328,102130,Male,disloyal Customer,39,Business travel,Business,236,1,1,1,4,4,1,4,4,5,3,5,5,5,4,63,60.0,neutral or dissatisfied +42329,121783,Female,Loyal Customer,60,Business travel,Business,449,5,5,3,5,3,4,5,2,2,2,2,4,2,3,21,24.0,satisfied +42330,9999,Female,Loyal Customer,58,Personal Travel,Eco,534,2,5,2,3,3,5,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +42331,50058,Female,Loyal Customer,48,Business travel,Eco,337,5,2,2,2,1,3,3,5,5,5,5,1,5,4,0,0.0,satisfied +42332,106861,Male,Loyal Customer,47,Business travel,Business,2145,4,4,4,4,4,4,5,5,5,5,5,4,5,4,21,10.0,satisfied +42333,114805,Male,disloyal Customer,20,Business travel,Business,371,5,0,4,2,2,4,2,2,4,5,5,4,4,2,19,13.0,satisfied +42334,110338,Female,Loyal Customer,51,Business travel,Business,3790,1,1,1,1,5,4,5,5,5,5,5,5,5,5,24,10.0,satisfied +42335,101254,Male,Loyal Customer,28,Business travel,Business,1910,3,3,3,3,4,4,4,4,4,4,4,4,4,4,24,18.0,satisfied +42336,18555,Male,Loyal Customer,54,Business travel,Eco,305,4,1,1,1,4,4,4,4,5,4,2,2,4,4,0,0.0,satisfied +42337,39807,Female,Loyal Customer,33,Business travel,Business,2929,3,3,3,3,5,4,5,5,5,5,5,4,5,2,0,4.0,satisfied +42338,122305,Male,Loyal Customer,23,Personal Travel,Eco,546,5,4,5,1,4,5,4,4,2,4,2,2,4,4,0,0.0,satisfied +42339,58374,Male,disloyal Customer,27,Business travel,Business,733,3,3,3,3,5,3,5,5,3,4,3,4,2,5,29,22.0,neutral or dissatisfied +42340,52752,Male,Loyal Customer,57,Business travel,Business,1874,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +42341,106523,Female,Loyal Customer,69,Personal Travel,Eco,271,2,4,2,4,5,3,3,4,4,2,1,3,4,3,9,0.0,neutral or dissatisfied +42342,590,Female,Loyal Customer,56,Business travel,Business,2694,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,2.0,satisfied +42343,109839,Female,Loyal Customer,36,Business travel,Business,2672,2,2,2,2,5,4,3,2,2,2,2,4,2,2,5,0.0,neutral or dissatisfied +42344,62962,Male,disloyal Customer,23,Business travel,Business,967,4,0,5,1,2,5,2,2,4,4,5,4,4,2,5,2.0,satisfied +42345,88215,Female,Loyal Customer,59,Business travel,Business,2930,0,5,0,4,3,4,4,2,2,2,2,4,2,3,35,36.0,satisfied +42346,87452,Male,Loyal Customer,37,Business travel,Business,373,1,1,2,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +42347,51646,Male,Loyal Customer,61,Business travel,Business,370,2,2,5,2,5,4,4,4,4,4,4,2,4,1,0,0.0,satisfied +42348,12674,Male,disloyal Customer,48,Business travel,Eco,721,4,4,4,3,4,4,4,4,2,4,5,5,4,4,3,0.0,neutral or dissatisfied +42349,64510,Female,Loyal Customer,23,Personal Travel,Business,224,3,4,3,3,4,3,2,4,2,1,4,5,3,4,24,9.0,neutral or dissatisfied +42350,59615,Female,Loyal Customer,42,Business travel,Business,854,1,2,2,2,3,4,3,1,1,1,1,4,1,4,94,94.0,neutral or dissatisfied +42351,75854,Female,Loyal Customer,68,Personal Travel,Eco,1440,2,3,1,4,1,2,3,4,4,1,4,2,4,4,50,55.0,neutral or dissatisfied +42352,98217,Female,disloyal Customer,26,Business travel,Business,442,0,0,0,3,2,0,2,2,5,5,2,4,2,2,0,1.0,satisfied +42353,117942,Female,Loyal Customer,35,Business travel,Business,255,4,1,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +42354,68128,Male,Loyal Customer,38,Personal Travel,Eco,868,2,2,2,3,3,2,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +42355,56643,Male,Loyal Customer,59,Business travel,Business,3880,2,2,2,2,5,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +42356,96787,Male,disloyal Customer,36,Business travel,Business,957,2,2,2,3,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +42357,89948,Male,Loyal Customer,61,Personal Travel,Eco,1306,4,5,3,3,2,3,2,2,5,2,3,4,5,2,88,115.0,satisfied +42358,18430,Male,Loyal Customer,61,Business travel,Business,1959,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +42359,63249,Female,Loyal Customer,45,Business travel,Business,337,1,1,1,1,2,5,4,4,4,4,4,4,4,3,11,0.0,satisfied +42360,55387,Female,Loyal Customer,40,Personal Travel,Eco,678,3,4,3,2,1,3,1,1,4,5,5,3,4,1,32,27.0,neutral or dissatisfied +42361,34153,Male,Loyal Customer,26,Business travel,Business,1189,2,2,4,2,5,5,5,5,2,2,2,3,3,5,0,0.0,satisfied +42362,1038,Female,Loyal Customer,34,Business travel,Business,3301,1,1,1,1,3,5,2,4,4,4,4,2,4,4,0,0.0,satisfied +42363,120837,Female,Loyal Customer,40,Business travel,Business,2631,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +42364,69415,Male,Loyal Customer,66,Business travel,Business,3915,1,1,1,1,1,3,5,5,5,4,5,1,5,4,62,70.0,satisfied +42365,71682,Female,Loyal Customer,36,Personal Travel,Eco,1197,1,4,1,4,3,1,3,3,3,3,5,5,4,3,53,48.0,neutral or dissatisfied +42366,27344,Male,disloyal Customer,33,Business travel,Eco,697,2,2,2,4,1,2,1,1,4,2,5,1,5,1,0,0.0,neutral or dissatisfied +42367,54549,Female,Loyal Customer,49,Personal Travel,Eco,925,3,4,3,1,3,5,1,2,2,3,2,2,2,5,0,2.0,neutral or dissatisfied +42368,124979,Male,Loyal Customer,46,Business travel,Business,2729,0,4,0,5,4,5,4,2,2,2,2,5,2,5,38,36.0,satisfied +42369,112326,Female,disloyal Customer,13,Business travel,Business,957,4,3,4,4,2,4,2,2,4,3,4,1,4,2,16,7.0,neutral or dissatisfied +42370,35927,Male,disloyal Customer,10,Business travel,Eco,2381,3,3,3,3,5,3,5,5,5,2,4,1,3,5,18,8.0,neutral or dissatisfied +42371,90089,Female,Loyal Customer,48,Business travel,Eco,1127,3,5,5,5,5,3,4,3,3,3,3,3,3,2,54,36.0,neutral or dissatisfied +42372,55783,Female,Loyal Customer,41,Business travel,Business,599,3,3,3,3,3,4,5,5,5,5,5,5,5,4,12,0.0,satisfied +42373,126651,Female,Loyal Customer,51,Personal Travel,Eco,602,2,3,2,3,4,3,1,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +42374,105981,Male,Loyal Customer,26,Personal Travel,Eco,2295,2,1,3,4,3,5,4,1,5,4,3,4,3,4,44,60.0,neutral or dissatisfied +42375,54938,Female,disloyal Customer,22,Business travel,Eco,1303,4,4,4,4,5,4,5,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +42376,88483,Male,Loyal Customer,51,Business travel,Eco,270,4,3,2,3,4,4,4,4,1,1,2,1,2,4,25,18.0,satisfied +42377,107610,Male,Loyal Customer,75,Business travel,Business,3004,3,4,4,4,3,4,3,3,3,3,3,3,3,4,102,96.0,neutral or dissatisfied +42378,95986,Male,Loyal Customer,33,Business travel,Business,1069,4,4,4,4,5,5,5,5,3,2,4,3,5,5,3,0.0,satisfied +42379,100265,Female,Loyal Customer,40,Business travel,Business,2837,2,2,2,2,3,5,5,2,2,2,2,3,2,3,17,49.0,satisfied +42380,41764,Male,Loyal Customer,27,Business travel,Eco,872,5,5,5,5,5,5,5,5,2,3,2,5,4,5,0,0.0,satisfied +42381,53226,Male,Loyal Customer,59,Personal Travel,Eco,589,4,2,4,4,4,4,3,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +42382,50460,Female,Loyal Customer,35,Business travel,Business,1815,1,1,1,1,4,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +42383,105135,Female,Loyal Customer,19,Business travel,Business,3257,3,1,1,1,3,3,3,3,3,1,3,3,3,3,1,0.0,neutral or dissatisfied +42384,15668,Male,Loyal Customer,29,Personal Travel,Eco,764,2,3,2,2,2,2,2,2,5,3,4,3,4,2,0,24.0,neutral or dissatisfied +42385,35322,Female,Loyal Customer,39,Business travel,Eco,950,4,3,3,3,4,4,4,4,4,2,1,5,5,4,0,0.0,satisfied +42386,61086,Female,Loyal Customer,63,Personal Travel,Eco,1546,5,5,5,4,5,3,4,3,3,5,3,3,3,5,0,0.0,satisfied +42387,127853,Female,Loyal Customer,60,Business travel,Business,1582,2,2,2,2,4,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +42388,26365,Female,disloyal Customer,36,Business travel,Eco,894,3,3,3,4,3,3,3,3,2,5,2,4,4,3,0,0.0,neutral or dissatisfied +42389,13588,Female,Loyal Customer,31,Personal Travel,Eco,227,2,5,2,4,4,2,4,4,3,3,5,4,5,4,0,35.0,neutral or dissatisfied +42390,36401,Female,disloyal Customer,16,Business travel,Eco,632,4,4,4,4,5,4,4,5,2,5,4,2,3,5,0,0.0,neutral or dissatisfied +42391,114145,Female,Loyal Customer,34,Business travel,Business,3644,5,5,5,5,2,5,5,4,4,4,4,5,4,4,7,0.0,satisfied +42392,63050,Male,Loyal Customer,7,Personal Travel,Eco,967,3,4,3,2,3,3,3,3,5,3,5,3,5,3,2,0.0,neutral or dissatisfied +42393,125605,Male,Loyal Customer,13,Personal Travel,Eco,1587,2,4,2,3,2,1,1,4,3,4,4,1,3,1,131,186.0,neutral or dissatisfied +42394,12564,Male,Loyal Customer,13,Personal Travel,Eco,788,4,5,3,3,1,3,1,1,5,4,5,5,4,1,0,0.0,satisfied +42395,25480,Male,Loyal Customer,26,Business travel,Business,3871,5,5,5,5,5,5,5,5,1,5,3,1,2,5,0,0.0,satisfied +42396,50696,Female,Loyal Customer,41,Personal Travel,Eco,86,2,3,2,2,2,2,2,2,3,5,1,5,5,2,0,0.0,neutral or dissatisfied +42397,93046,Male,Loyal Customer,44,Personal Travel,Eco,317,2,1,2,3,4,2,4,4,4,3,2,1,3,4,0,0.0,neutral or dissatisfied +42398,106545,Male,Loyal Customer,27,Business travel,Business,3318,2,1,5,1,2,3,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +42399,99320,Male,disloyal Customer,23,Business travel,Eco,448,2,4,2,4,4,2,4,4,1,2,3,1,4,4,15,13.0,neutral or dissatisfied +42400,6105,Male,disloyal Customer,24,Business travel,Eco,409,5,0,5,4,3,5,3,3,3,2,5,5,5,3,0,0.0,satisfied +42401,39681,Male,Loyal Customer,21,Personal Travel,Eco,717,2,5,2,3,1,2,1,1,4,3,3,2,1,1,25,7.0,neutral or dissatisfied +42402,21761,Male,Loyal Customer,38,Business travel,Business,3182,5,5,5,5,5,4,4,4,4,4,4,5,4,5,2,0.0,satisfied +42403,43350,Male,disloyal Customer,20,Business travel,Eco,402,1,4,1,2,1,1,1,1,1,3,2,5,5,1,0,0.0,neutral or dissatisfied +42404,122997,Female,Loyal Customer,50,Business travel,Business,1902,5,5,4,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +42405,37575,Male,disloyal Customer,39,Business travel,Eco,428,1,0,1,4,3,1,3,3,1,3,4,5,3,3,0,0.0,neutral or dissatisfied +42406,3435,Female,Loyal Customer,36,Personal Travel,Eco,240,3,4,0,3,3,0,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +42407,87135,Female,Loyal Customer,55,Business travel,Business,3140,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +42408,63643,Female,Loyal Customer,42,Personal Travel,Eco,602,4,2,3,4,2,3,3,2,2,3,1,2,2,1,0,5.0,neutral or dissatisfied +42409,10252,Male,Loyal Customer,31,Personal Travel,Business,216,1,0,1,5,4,1,4,4,5,5,1,1,3,4,0,0.0,neutral or dissatisfied +42410,35966,Female,Loyal Customer,41,Personal Travel,Eco,231,3,5,0,5,5,0,4,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +42411,86974,Female,Loyal Customer,53,Business travel,Business,2694,1,1,1,1,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +42412,41303,Female,Loyal Customer,41,Business travel,Business,802,2,2,2,2,1,5,3,5,5,5,5,3,5,4,0,0.0,satisfied +42413,11659,Female,Loyal Customer,37,Personal Travel,Eco,837,3,5,3,1,5,3,5,5,3,4,5,3,4,5,110,114.0,neutral or dissatisfied +42414,75516,Male,disloyal Customer,11,Business travel,Eco,748,1,1,1,4,4,1,4,4,4,2,4,3,3,4,14,19.0,neutral or dissatisfied +42415,17389,Male,Loyal Customer,53,Business travel,Business,376,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +42416,113976,Female,disloyal Customer,38,Business travel,Business,1844,2,2,2,3,3,2,3,3,5,4,4,4,5,3,0,0.0,satisfied +42417,113201,Male,Loyal Customer,53,Business travel,Business,236,3,5,5,5,4,2,2,3,3,3,3,1,3,2,26,29.0,neutral or dissatisfied +42418,21075,Male,Loyal Customer,37,Business travel,Business,106,2,4,4,4,3,3,3,3,3,3,2,2,3,4,3,0.0,neutral or dissatisfied +42419,37147,Female,disloyal Customer,25,Business travel,Eco,1189,2,2,2,3,2,2,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +42420,28769,Female,Loyal Customer,39,Business travel,Business,3380,3,2,3,3,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +42421,59847,Female,Loyal Customer,47,Business travel,Business,2343,4,4,4,4,2,5,4,4,4,5,4,5,4,4,0,63.0,satisfied +42422,117654,Female,Loyal Customer,52,Business travel,Business,3660,3,1,1,1,1,3,3,3,3,3,3,1,3,1,111,96.0,neutral or dissatisfied +42423,109441,Female,Loyal Customer,34,Business travel,Business,834,1,1,1,1,4,4,5,5,5,5,5,5,5,3,15,0.0,satisfied +42424,115518,Male,Loyal Customer,34,Business travel,Business,2983,1,1,1,1,5,3,3,1,1,1,1,1,1,2,20,18.0,neutral or dissatisfied +42425,26093,Male,Loyal Customer,47,Business travel,Business,191,2,5,5,5,5,1,1,2,2,2,2,4,2,3,18,15.0,neutral or dissatisfied +42426,86208,Male,Loyal Customer,59,Business travel,Business,356,3,5,5,5,3,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +42427,712,Female,Loyal Customer,52,Business travel,Business,3854,4,4,4,4,2,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +42428,100750,Female,Loyal Customer,29,Personal Travel,Eco,328,3,4,3,3,3,3,2,3,3,2,5,5,4,3,14,8.0,neutral or dissatisfied +42429,69703,Male,Loyal Customer,48,Business travel,Business,1372,3,3,3,3,4,3,3,3,3,3,3,2,3,1,0,1.0,neutral or dissatisfied +42430,54930,Female,disloyal Customer,27,Business travel,Business,1635,5,5,5,4,2,5,2,2,3,2,4,3,4,2,0,5.0,satisfied +42431,47611,Male,Loyal Customer,50,Business travel,Eco,1464,4,4,4,4,4,4,4,4,3,1,2,3,2,4,21,7.0,satisfied +42432,128924,Male,Loyal Customer,49,Business travel,Business,3691,3,3,3,3,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +42433,111863,Male,Loyal Customer,53,Business travel,Business,628,2,2,2,2,2,5,5,5,5,5,5,4,5,3,42,35.0,satisfied +42434,59232,Female,Loyal Customer,56,Business travel,Eco,649,3,3,2,2,4,3,4,3,3,3,3,3,3,2,11,9.0,neutral or dissatisfied +42435,9534,Female,Loyal Customer,38,Business travel,Business,305,2,1,1,1,5,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +42436,62046,Female,disloyal Customer,26,Business travel,Eco,1186,2,2,2,3,3,2,4,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +42437,54041,Male,Loyal Customer,51,Business travel,Eco,1416,4,5,5,5,4,4,4,4,4,2,1,3,4,4,0,1.0,satisfied +42438,92980,Male,Loyal Customer,46,Business travel,Business,738,4,4,4,4,4,4,5,5,5,5,5,3,5,4,21,,satisfied +42439,11128,Female,Loyal Customer,60,Personal Travel,Eco,667,4,5,4,3,5,4,5,4,4,4,4,5,4,3,64,51.0,neutral or dissatisfied +42440,65012,Female,disloyal Customer,20,Business travel,Eco,469,4,3,3,4,1,3,1,1,4,1,3,3,4,1,56,61.0,neutral or dissatisfied +42441,118353,Male,Loyal Customer,54,Personal Travel,Eco,602,2,5,2,2,3,2,3,3,3,3,4,4,4,3,85,73.0,neutral or dissatisfied +42442,107626,Male,Loyal Customer,7,Personal Travel,Eco,423,4,5,4,3,3,4,3,3,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +42443,126407,Male,Loyal Customer,32,Business travel,Business,3703,4,4,4,4,5,5,5,5,4,5,5,3,5,5,0,0.0,satisfied +42444,74277,Female,Loyal Customer,25,Business travel,Business,2288,5,5,5,5,2,2,2,2,3,3,5,4,5,2,0,0.0,satisfied +42445,8837,Female,Loyal Customer,72,Business travel,Eco Plus,522,4,5,5,5,4,3,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +42446,70820,Male,Loyal Customer,15,Personal Travel,Eco,624,5,1,5,4,2,5,2,2,3,3,4,4,3,2,0,0.0,satisfied +42447,968,Male,Loyal Customer,57,Business travel,Business,309,3,3,3,3,1,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +42448,6349,Male,Loyal Customer,38,Business travel,Business,3126,0,0,0,4,3,4,4,1,1,1,1,5,1,5,0,0.0,satisfied +42449,74121,Female,Loyal Customer,39,Business travel,Business,1760,3,3,3,3,5,4,5,5,5,5,5,5,5,4,0,26.0,satisfied +42450,64620,Male,Loyal Customer,60,Business travel,Business,224,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,1.0,satisfied +42451,102984,Female,Loyal Customer,44,Business travel,Business,460,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +42452,120966,Male,Loyal Customer,60,Business travel,Business,920,2,2,2,2,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +42453,78485,Female,Loyal Customer,38,Business travel,Eco,666,3,1,1,1,3,4,3,3,2,4,3,3,3,3,17,28.0,neutral or dissatisfied +42454,34920,Male,disloyal Customer,21,Business travel,Eco,187,2,1,1,3,3,1,3,3,3,2,3,3,2,3,24,30.0,neutral or dissatisfied +42455,24493,Male,Loyal Customer,27,Personal Travel,Eco,481,3,4,3,3,5,3,5,5,1,5,4,3,4,5,0,0.0,neutral or dissatisfied +42456,1395,Female,Loyal Customer,24,Personal Travel,Eco Plus,158,3,5,3,2,1,3,1,1,3,4,4,5,4,1,0,10.0,neutral or dissatisfied +42457,99204,Male,Loyal Customer,19,Personal Travel,Eco,583,2,3,1,3,3,1,3,3,1,5,3,4,2,3,0,0.0,neutral or dissatisfied +42458,21242,Male,Loyal Customer,43,Personal Travel,Eco,153,1,4,1,3,4,1,4,4,4,4,4,4,4,4,2,0.0,neutral or dissatisfied +42459,98408,Female,Loyal Customer,8,Personal Travel,Eco,675,3,3,3,3,3,3,3,3,2,3,3,2,3,3,8,14.0,neutral or dissatisfied +42460,55784,Male,Loyal Customer,31,Personal Travel,Eco Plus,646,2,1,2,3,4,2,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +42461,55037,Female,Loyal Customer,25,Business travel,Business,1379,3,3,3,3,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +42462,50553,Male,Loyal Customer,21,Personal Travel,Eco,109,1,5,1,4,2,1,2,2,2,1,2,5,3,2,0,9.0,neutral or dissatisfied +42463,84994,Female,Loyal Customer,51,Business travel,Business,1590,5,5,5,5,4,4,4,4,4,4,4,5,4,4,20,7.0,satisfied +42464,42729,Female,Loyal Customer,42,Business travel,Eco,646,4,4,1,1,3,4,1,4,4,4,4,1,4,2,11,8.0,satisfied +42465,42371,Male,Loyal Customer,23,Personal Travel,Eco,329,3,2,3,2,4,3,4,4,1,1,2,3,2,4,0,0.0,neutral or dissatisfied +42466,104436,Male,Loyal Customer,35,Personal Travel,Eco,1138,1,4,1,2,5,1,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +42467,27105,Female,Loyal Customer,57,Personal Travel,Eco,1721,3,5,3,5,4,3,5,4,4,3,4,4,4,4,0,4.0,neutral or dissatisfied +42468,85030,Female,Loyal Customer,16,Personal Travel,Eco,1590,3,5,3,1,5,3,1,5,3,2,5,4,4,5,6,0.0,neutral or dissatisfied +42469,75758,Male,Loyal Customer,28,Business travel,Business,868,4,4,4,4,4,3,4,4,5,4,4,4,5,4,0,0.0,satisfied +42470,16658,Female,Loyal Customer,28,Business travel,Eco,605,3,4,4,4,3,3,3,3,2,4,4,3,3,3,19,13.0,neutral or dissatisfied +42471,23084,Female,Loyal Customer,24,Business travel,Eco,864,2,2,2,2,2,2,4,2,4,2,3,3,3,2,6,2.0,neutral or dissatisfied +42472,94033,Male,Loyal Customer,45,Business travel,Business,1702,3,3,3,3,5,4,4,5,5,5,5,4,5,3,14,10.0,satisfied +42473,86517,Male,Loyal Customer,8,Personal Travel,Eco,712,2,4,3,5,4,3,4,4,2,2,1,4,3,4,0,1.0,neutral or dissatisfied +42474,70451,Male,Loyal Customer,59,Business travel,Business,2962,0,4,0,4,2,4,5,1,1,1,1,5,1,4,54,46.0,satisfied +42475,12918,Male,Loyal Customer,42,Business travel,Business,2142,3,2,4,2,1,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +42476,55503,Male,Loyal Customer,42,Business travel,Business,1739,3,3,3,3,4,4,4,3,3,3,3,5,3,5,3,0.0,satisfied +42477,125065,Female,Loyal Customer,32,Personal Travel,Eco,90,2,3,2,3,3,2,2,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +42478,7225,Female,Loyal Customer,53,Business travel,Eco,130,3,2,2,2,2,4,3,3,3,3,3,1,3,4,14,9.0,neutral or dissatisfied +42479,26377,Male,Loyal Customer,45,Personal Travel,Eco,894,2,5,2,2,2,2,2,2,3,2,4,5,5,2,92,84.0,neutral or dissatisfied +42480,74350,Female,disloyal Customer,38,Business travel,Business,1235,2,2,2,1,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +42481,41578,Male,Loyal Customer,51,Personal Travel,Eco,1482,4,4,4,3,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +42482,68946,Male,Loyal Customer,68,Personal Travel,Eco,646,3,4,3,4,3,3,3,3,3,2,3,3,4,3,8,11.0,neutral or dissatisfied +42483,22567,Female,Loyal Customer,31,Business travel,Business,223,4,4,2,4,5,5,3,5,3,3,1,2,4,5,12,9.0,satisfied +42484,9059,Male,disloyal Customer,29,Business travel,Business,160,4,4,4,4,4,4,4,4,3,3,5,4,4,4,5,3.0,satisfied +42485,103395,Female,Loyal Customer,42,Business travel,Business,3176,2,2,4,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +42486,7781,Female,Loyal Customer,60,Personal Travel,Eco,1080,2,5,2,5,4,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +42487,107786,Male,Loyal Customer,23,Business travel,Business,666,1,5,5,5,1,1,1,1,2,4,3,3,4,1,6,0.0,neutral or dissatisfied +42488,104165,Female,Loyal Customer,39,Business travel,Business,2113,3,3,1,3,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +42489,37826,Female,Loyal Customer,12,Personal Travel,Business,937,3,5,3,3,1,3,1,1,5,5,5,4,5,1,12,0.0,neutral or dissatisfied +42490,109861,Female,Loyal Customer,23,Business travel,Business,2359,2,2,2,2,2,3,2,2,2,1,3,1,3,2,98,76.0,neutral or dissatisfied +42491,109112,Female,Loyal Customer,55,Business travel,Eco Plus,816,3,4,4,4,2,3,3,3,3,3,3,3,3,1,4,0.0,neutral or dissatisfied +42492,35750,Female,Loyal Customer,58,Personal Travel,Eco Plus,1826,4,4,4,1,3,4,4,3,3,4,3,4,3,5,11,8.0,neutral or dissatisfied +42493,5337,Female,Loyal Customer,39,Business travel,Business,733,4,4,5,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +42494,6610,Female,Loyal Customer,16,Personal Travel,Eco,607,4,5,3,3,4,3,4,4,5,2,5,5,5,4,29,27.0,neutral or dissatisfied +42495,45382,Female,Loyal Customer,60,Business travel,Eco Plus,150,5,5,1,5,3,5,5,5,5,5,5,5,5,4,0,2.0,satisfied +42496,669,Male,Loyal Customer,40,Business travel,Business,3893,3,3,3,3,3,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +42497,38377,Female,Loyal Customer,15,Personal Travel,Eco,1133,2,4,2,1,2,2,2,2,3,5,3,3,4,2,65,72.0,neutral or dissatisfied +42498,66359,Male,Loyal Customer,50,Business travel,Eco,986,1,2,2,2,1,1,1,1,1,1,4,1,4,1,0,0.0,neutral or dissatisfied +42499,5806,Male,Loyal Customer,35,Business travel,Eco,157,2,3,3,3,2,2,2,2,2,5,2,3,4,2,0,0.0,satisfied +42500,57001,Male,Loyal Customer,37,Personal Travel,Eco,2565,2,5,2,3,2,5,4,5,2,3,2,4,2,4,7,0.0,neutral or dissatisfied +42501,45971,Female,disloyal Customer,54,Business travel,Eco,872,3,3,3,2,4,3,4,4,4,2,3,4,3,4,4,32.0,neutral or dissatisfied +42502,121506,Male,Loyal Customer,42,Business travel,Business,1727,3,3,3,3,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +42503,80048,Male,Loyal Customer,37,Personal Travel,Eco,1089,4,5,4,3,4,4,4,4,5,3,3,2,5,4,0,0.0,satisfied +42504,24269,Male,Loyal Customer,66,Personal Travel,Eco,147,3,5,3,4,2,3,2,2,5,1,4,4,1,2,34,26.0,neutral or dissatisfied +42505,97558,Male,Loyal Customer,60,Business travel,Business,2948,3,3,3,3,3,5,4,4,4,4,4,4,4,5,16,14.0,satisfied +42506,42955,Female,disloyal Customer,25,Business travel,Eco,192,1,5,1,4,5,1,1,5,5,1,3,3,2,5,0,0.0,neutral or dissatisfied +42507,115958,Male,Loyal Customer,23,Personal Travel,Eco,325,3,3,1,4,2,1,2,2,1,3,4,2,3,2,69,65.0,neutral or dissatisfied +42508,21157,Male,Loyal Customer,44,Business travel,Business,1807,4,4,1,4,4,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +42509,93262,Male,Loyal Customer,50,Business travel,Business,564,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +42510,129717,Female,disloyal Customer,22,Business travel,Business,337,4,4,4,4,4,4,4,3,3,5,4,4,3,4,201,200.0,satisfied +42511,90993,Female,disloyal Customer,43,Business travel,Eco,145,2,3,3,1,3,3,3,3,3,5,5,3,2,3,22,12.0,neutral or dissatisfied +42512,4399,Male,Loyal Customer,45,Personal Travel,Eco,473,1,4,1,2,1,1,1,1,3,2,5,2,3,1,0,0.0,neutral or dissatisfied +42513,36543,Male,Loyal Customer,36,Business travel,Business,1197,2,2,2,2,3,4,1,5,5,5,5,4,5,3,31,15.0,satisfied +42514,69874,Female,disloyal Customer,48,Business travel,Business,1055,2,2,2,1,3,2,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +42515,77525,Female,Loyal Customer,54,Business travel,Business,2509,4,4,4,4,3,5,4,3,3,4,3,3,3,3,6,0.0,satisfied +42516,102326,Female,disloyal Customer,27,Business travel,Eco,223,2,3,2,3,2,2,2,2,1,2,4,1,4,2,38,32.0,neutral or dissatisfied +42517,25561,Male,Loyal Customer,31,Business travel,Business,3533,1,1,1,1,4,4,4,4,3,5,3,5,4,4,4,0.0,satisfied +42518,80191,Male,Loyal Customer,9,Personal Travel,Eco,2586,1,5,1,5,1,5,5,5,2,3,5,5,4,5,55,34.0,neutral or dissatisfied +42519,86252,Male,Loyal Customer,35,Personal Travel,Eco,226,2,4,2,5,5,2,5,5,3,3,4,4,4,5,0,4.0,neutral or dissatisfied +42520,48012,Female,Loyal Customer,27,Personal Travel,Eco Plus,550,3,4,3,4,4,3,4,4,4,4,3,4,5,4,6,0.0,neutral or dissatisfied +42521,46130,Male,disloyal Customer,25,Business travel,Eco,604,3,4,2,2,1,2,1,1,4,1,1,5,4,1,97,92.0,neutral or dissatisfied +42522,114939,Female,Loyal Customer,44,Business travel,Business,2156,4,4,4,4,5,5,5,4,4,4,4,4,4,4,16,20.0,satisfied +42523,60686,Female,Loyal Customer,7,Personal Travel,Business,1605,2,5,2,2,3,2,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +42524,32656,Female,Loyal Customer,33,Business travel,Business,2517,5,5,5,5,3,4,4,4,4,4,4,1,4,2,0,0.0,satisfied +42525,6177,Male,Loyal Customer,15,Personal Travel,Eco,491,2,3,2,3,2,2,2,2,2,5,4,1,4,2,59,64.0,neutral or dissatisfied +42526,2894,Male,Loyal Customer,21,Personal Travel,Eco,475,2,3,2,1,3,2,3,3,1,3,1,5,3,3,55,42.0,neutral or dissatisfied +42527,128467,Male,Loyal Customer,35,Personal Travel,Eco,304,3,1,3,3,1,3,1,1,1,2,2,4,2,1,5,0.0,neutral or dissatisfied +42528,107237,Male,Loyal Customer,10,Personal Travel,Eco,583,3,4,3,5,3,3,3,3,5,4,5,4,4,3,39,38.0,neutral or dissatisfied +42529,25463,Male,Loyal Customer,40,Business travel,Business,2224,3,3,3,3,5,4,4,2,2,3,2,4,2,4,0,47.0,satisfied +42530,62836,Male,Loyal Customer,59,Business travel,Business,2399,5,5,2,5,4,3,5,5,5,5,5,5,5,3,8,8.0,satisfied +42531,97252,Male,Loyal Customer,39,Business travel,Eco,296,3,2,2,2,3,3,3,3,3,2,3,3,3,3,2,0.0,neutral or dissatisfied +42532,15999,Male,Loyal Customer,59,Business travel,Eco,794,3,3,2,3,3,3,3,3,2,2,3,5,5,3,14,2.0,satisfied +42533,109066,Female,Loyal Customer,44,Business travel,Eco,557,5,4,4,4,5,5,1,5,5,5,5,3,5,2,1,1.0,satisfied +42534,26944,Male,Loyal Customer,53,Business travel,Eco,2402,4,2,5,2,4,4,4,4,3,2,5,3,1,4,0,0.0,satisfied +42535,19057,Male,Loyal Customer,48,Personal Travel,Business,569,4,2,4,2,5,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +42536,5556,Male,Loyal Customer,59,Business travel,Business,501,4,4,4,4,3,5,5,2,2,2,2,3,2,4,18,33.0,satisfied +42537,126864,Male,Loyal Customer,27,Personal Travel,Eco,2077,2,2,2,2,2,2,2,2,1,1,2,4,1,2,0,0.0,neutral or dissatisfied +42538,22983,Male,Loyal Customer,48,Business travel,Business,2965,2,2,2,2,2,3,4,4,4,4,4,4,4,2,12,21.0,satisfied +42539,58864,Male,Loyal Customer,38,Business travel,Business,3699,4,4,4,4,4,4,5,3,3,3,3,5,3,4,5,0.0,satisfied +42540,39571,Male,disloyal Customer,25,Business travel,Eco,679,4,4,4,5,2,4,2,2,1,4,3,4,4,2,81,78.0,satisfied +42541,102162,Female,disloyal Customer,22,Business travel,Business,407,5,0,5,2,5,5,5,5,4,4,4,3,4,5,22,14.0,satisfied +42542,69916,Female,Loyal Customer,23,Personal Travel,Eco,1514,4,2,4,3,1,4,2,1,2,2,4,2,3,1,0,0.0,neutral or dissatisfied +42543,48891,Male,Loyal Customer,39,Business travel,Business,266,0,0,0,4,3,3,1,1,1,1,1,5,1,2,0,0.0,satisfied +42544,127981,Male,Loyal Customer,57,Business travel,Business,1149,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,1.0,satisfied +42545,14566,Male,Loyal Customer,50,Business travel,Eco,986,4,3,3,3,4,4,4,4,3,3,1,2,2,4,0,0.0,satisfied +42546,3585,Female,disloyal Customer,30,Business travel,Business,999,3,3,3,2,5,3,1,5,3,5,5,5,5,5,3,0.0,neutral or dissatisfied +42547,105073,Female,Loyal Customer,40,Business travel,Business,220,5,5,5,5,3,5,5,5,5,4,4,3,5,4,9,0.0,satisfied +42548,91363,Female,Loyal Customer,48,Personal Travel,Eco Plus,271,3,1,3,3,3,3,2,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +42549,22009,Male,Loyal Customer,22,Personal Travel,Eco,500,2,4,2,4,4,2,4,4,3,3,3,3,3,4,0,11.0,neutral or dissatisfied +42550,102921,Female,disloyal Customer,21,Business travel,Eco,317,1,2,1,4,3,1,3,3,1,2,4,2,3,3,45,48.0,neutral or dissatisfied +42551,67067,Female,Loyal Customer,49,Business travel,Business,3133,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +42552,38368,Female,Loyal Customer,61,Personal Travel,Eco,1111,1,5,1,3,3,4,4,2,2,1,2,4,2,5,0,1.0,neutral or dissatisfied +42553,117812,Male,Loyal Customer,41,Business travel,Business,328,2,2,2,2,2,5,5,4,4,4,4,2,4,1,6,2.0,satisfied +42554,103405,Male,Loyal Customer,33,Business travel,Business,3710,4,4,4,4,4,4,4,4,2,2,3,4,4,4,7,0.0,neutral or dissatisfied +42555,4091,Female,Loyal Customer,60,Business travel,Business,2869,1,1,1,1,4,4,4,3,3,3,3,3,3,5,0,2.0,satisfied +42556,71548,Female,disloyal Customer,36,Business travel,Business,1182,1,1,1,3,4,1,4,4,4,3,5,5,5,4,0,5.0,neutral or dissatisfied +42557,25476,Female,Loyal Customer,48,Business travel,Eco,481,5,1,1,1,2,5,1,5,5,5,5,1,5,5,0,0.0,satisfied +42558,126925,Male,Loyal Customer,42,Personal Travel,Business,647,3,2,3,1,5,1,1,2,2,3,4,2,2,4,0,0.0,neutral or dissatisfied +42559,19434,Female,Loyal Customer,39,Personal Travel,Eco,645,1,3,1,3,1,1,1,1,2,3,3,1,3,1,45,37.0,neutral or dissatisfied +42560,68710,Female,Loyal Customer,34,Personal Travel,Eco,175,5,5,5,4,2,5,5,2,4,3,4,4,4,2,3,5.0,satisfied +42561,60435,Male,Loyal Customer,46,Business travel,Business,3026,1,1,1,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +42562,122959,Female,Loyal Customer,38,Business travel,Business,600,2,2,2,2,4,4,4,2,2,2,2,5,2,4,0,5.0,satisfied +42563,107704,Female,Loyal Customer,30,Business travel,Business,3024,4,2,2,2,4,4,4,4,4,2,4,4,3,4,69,60.0,neutral or dissatisfied +42564,117292,Female,Loyal Customer,48,Business travel,Business,3329,2,2,2,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +42565,80729,Male,Loyal Customer,43,Business travel,Business,3221,1,1,1,1,4,5,5,4,4,4,4,3,4,5,11,0.0,satisfied +42566,52632,Female,Loyal Customer,35,Business travel,Eco,160,2,1,3,1,2,2,2,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +42567,70299,Female,Loyal Customer,43,Personal Travel,Eco Plus,852,3,4,3,3,3,5,4,3,3,3,3,3,3,4,48,35.0,neutral or dissatisfied +42568,101166,Male,Loyal Customer,34,Business travel,Business,1940,2,3,3,3,4,3,3,2,2,2,2,3,2,3,90,90.0,neutral or dissatisfied +42569,128043,Female,disloyal Customer,17,Business travel,Eco,878,1,2,2,3,4,1,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +42570,33232,Female,disloyal Customer,44,Business travel,Eco Plus,101,2,2,2,4,1,2,1,1,3,1,2,5,4,1,0,0.0,neutral or dissatisfied +42571,113560,Male,Loyal Customer,51,Business travel,Eco,226,2,3,3,3,2,2,2,2,4,5,3,1,2,2,41,34.0,neutral or dissatisfied +42572,9755,Female,Loyal Customer,42,Business travel,Business,2122,2,5,5,5,5,3,3,2,2,2,2,3,2,2,0,6.0,neutral or dissatisfied +42573,128228,Male,Loyal Customer,44,Business travel,Eco,202,1,5,4,5,1,1,1,1,1,4,3,1,4,1,33,37.0,neutral or dissatisfied +42574,106412,Female,Loyal Customer,9,Personal Travel,Eco,488,1,0,1,1,4,1,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +42575,81787,Female,disloyal Customer,22,Business travel,Eco,1416,2,1,1,1,2,2,2,2,4,2,5,4,5,2,16,16.0,neutral or dissatisfied +42576,14254,Female,disloyal Customer,34,Business travel,Business,429,1,0,0,2,3,0,3,3,5,2,4,3,4,3,14,9.0,neutral or dissatisfied +42577,96185,Male,Loyal Customer,47,Business travel,Business,2081,3,3,3,3,4,4,4,5,5,5,5,3,5,5,8,3.0,satisfied +42578,65081,Female,Loyal Customer,69,Personal Travel,Eco,224,3,4,0,4,3,5,5,2,2,0,5,3,2,5,0,11.0,neutral or dissatisfied +42579,66623,Male,Loyal Customer,45,Business travel,Business,802,3,3,3,3,4,3,4,3,3,3,3,3,3,3,26,24.0,neutral or dissatisfied +42580,116641,Female,disloyal Customer,27,Business travel,Eco Plus,447,2,1,1,4,4,1,4,4,2,1,3,2,3,4,14,0.0,neutral or dissatisfied +42581,59826,Female,Loyal Customer,40,Business travel,Business,2887,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +42582,47413,Male,Loyal Customer,30,Business travel,Business,501,2,2,2,2,2,2,2,2,1,2,2,5,4,2,0,0.0,satisfied +42583,1272,Female,Loyal Customer,51,Personal Travel,Eco,134,1,5,1,2,3,5,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +42584,31826,Female,disloyal Customer,24,Business travel,Eco,1233,4,4,4,1,4,5,5,4,5,4,4,5,1,5,0,0.0,satisfied +42585,89671,Male,Loyal Customer,31,Business travel,Business,3591,3,4,4,4,3,3,3,3,2,2,2,4,3,3,0,0.0,neutral or dissatisfied +42586,122890,Female,Loyal Customer,37,Business travel,Eco Plus,226,2,3,3,3,2,2,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +42587,115086,Male,Loyal Customer,32,Business travel,Business,447,5,5,5,5,5,4,5,5,3,5,4,3,5,5,123,128.0,satisfied +42588,9095,Male,Loyal Customer,37,Business travel,Eco Plus,173,2,3,3,3,2,3,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +42589,18148,Male,disloyal Customer,27,Business travel,Business,229,2,2,2,1,4,2,4,4,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +42590,73405,Male,Loyal Customer,48,Business travel,Business,1971,3,3,3,3,3,3,3,4,3,3,2,3,1,3,140,208.0,neutral or dissatisfied +42591,127631,Female,disloyal Customer,26,Business travel,Eco,1773,2,2,2,4,1,2,1,1,3,1,3,4,3,1,54,44.0,neutral or dissatisfied +42592,51111,Male,Loyal Customer,31,Personal Travel,Eco,190,2,5,2,5,5,2,3,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +42593,13368,Male,Loyal Customer,56,Personal Travel,Eco,748,2,5,1,4,3,1,3,3,5,5,5,3,5,3,10,31.0,neutral or dissatisfied +42594,7327,Female,disloyal Customer,27,Business travel,Business,606,1,1,1,4,1,1,1,1,3,5,4,4,4,1,39,46.0,neutral or dissatisfied +42595,38306,Female,Loyal Customer,9,Personal Travel,Eco,2583,2,2,2,3,2,5,5,2,4,3,4,5,4,5,46,33.0,neutral or dissatisfied +42596,110255,Female,Loyal Customer,20,Personal Travel,Eco Plus,1024,2,1,2,3,3,2,3,3,3,3,2,3,2,3,4,18.0,neutral or dissatisfied +42597,64984,Female,disloyal Customer,37,Business travel,Eco,190,3,1,3,3,2,3,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +42598,107202,Female,Loyal Customer,15,Personal Travel,Eco,402,3,1,3,3,3,3,3,3,2,5,2,1,2,3,7,2.0,neutral or dissatisfied +42599,71104,Male,Loyal Customer,11,Personal Travel,Eco Plus,802,3,1,3,2,3,3,3,3,1,3,2,2,3,3,0,0.0,neutral or dissatisfied +42600,19749,Male,Loyal Customer,35,Business travel,Business,3595,4,4,4,4,1,3,4,5,5,4,5,4,5,4,4,2.0,satisfied +42601,4736,Male,Loyal Customer,28,Business travel,Business,1730,1,1,1,1,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +42602,96295,Female,Loyal Customer,23,Personal Travel,Eco,666,3,0,3,5,3,3,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +42603,91471,Male,Loyal Customer,44,Personal Travel,Eco,859,1,5,1,3,2,1,2,2,5,4,4,4,5,2,50,34.0,neutral or dissatisfied +42604,9110,Male,Loyal Customer,43,Business travel,Business,765,1,2,2,2,4,3,2,1,1,1,1,1,1,4,2,0.0,neutral or dissatisfied +42605,44276,Female,Loyal Customer,40,Business travel,Eco Plus,359,5,4,1,4,5,5,5,5,4,4,1,2,2,5,0,0.0,satisfied +42606,59687,Female,Loyal Customer,39,Personal Travel,Eco,964,4,4,4,3,2,4,2,2,5,3,4,5,4,2,17,0.0,satisfied +42607,17993,Female,Loyal Customer,29,Business travel,Business,332,1,1,1,1,5,5,5,5,5,1,4,3,3,5,0,0.0,satisfied +42608,42571,Female,Loyal Customer,68,Business travel,Business,3695,4,4,4,4,1,3,4,5,5,4,5,1,5,5,0,0.0,satisfied +42609,19387,Female,Loyal Customer,30,Personal Travel,Eco,844,3,4,3,4,1,3,1,1,1,3,3,2,4,1,2,0.0,neutral or dissatisfied +42610,101107,Male,Loyal Customer,41,Business travel,Business,1235,3,3,3,3,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +42611,75354,Female,Loyal Customer,58,Business travel,Business,2504,4,4,4,4,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +42612,113878,Male,Loyal Customer,58,Business travel,Eco Plus,1363,3,4,4,4,3,3,3,3,4,4,4,2,4,3,5,6.0,neutral or dissatisfied +42613,40083,Male,Loyal Customer,19,Personal Travel,Eco,493,5,5,5,1,3,5,3,3,4,5,4,3,4,3,0,0.0,satisfied +42614,52566,Female,disloyal Customer,20,Business travel,Eco,110,1,4,1,3,4,1,5,4,4,1,4,1,4,4,0,7.0,neutral or dissatisfied +42615,80345,Female,Loyal Customer,37,Business travel,Business,3165,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +42616,79409,Male,Loyal Customer,63,Business travel,Business,3579,2,1,1,1,5,3,4,1,1,1,2,4,1,2,11,0.0,neutral or dissatisfied +42617,45565,Female,Loyal Customer,42,Personal Travel,Eco,1304,2,2,2,3,3,3,3,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +42618,104289,Male,Loyal Customer,48,Business travel,Business,3326,1,1,5,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +42619,18016,Male,Loyal Customer,39,Personal Travel,Eco,332,3,5,4,4,2,4,2,2,1,4,2,1,5,2,43,29.0,neutral or dissatisfied +42620,95299,Male,Loyal Customer,58,Personal Travel,Eco,239,4,5,4,3,5,4,5,5,4,2,4,4,5,5,2,0.0,neutral or dissatisfied +42621,117925,Female,Loyal Customer,46,Business travel,Business,255,4,5,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +42622,14599,Male,Loyal Customer,45,Personal Travel,Eco,986,1,5,1,4,1,1,1,1,4,5,4,5,4,1,28,0.0,neutral or dissatisfied +42623,25357,Male,disloyal Customer,36,Business travel,Eco,591,4,5,5,1,5,5,5,5,4,4,1,1,3,5,1,0.0,neutral or dissatisfied +42624,35688,Male,Loyal Customer,47,Business travel,Eco,2475,2,5,5,5,2,2,2,2,2,2,4,2,3,2,0,3.0,neutral or dissatisfied +42625,77339,Female,Loyal Customer,47,Business travel,Business,1545,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +42626,69486,Female,disloyal Customer,27,Business travel,Business,1089,3,3,3,3,1,3,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +42627,43244,Male,Loyal Customer,60,Personal Travel,Business,358,1,5,1,2,4,4,5,5,5,1,5,4,5,3,1,15.0,neutral or dissatisfied +42628,21988,Female,Loyal Customer,60,Personal Travel,Eco,503,3,3,3,4,4,3,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +42629,110734,Male,Loyal Customer,49,Business travel,Business,2847,5,5,5,5,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +42630,17305,Female,disloyal Customer,26,Business travel,Eco,403,4,4,4,3,4,4,4,4,4,3,4,4,3,4,0,0.0,satisfied +42631,73800,Male,Loyal Customer,65,Business travel,Eco Plus,204,3,4,4,4,3,3,3,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +42632,75006,Male,disloyal Customer,23,Business travel,Eco,236,3,0,3,2,3,3,3,3,5,3,4,4,4,3,4,3.0,neutral or dissatisfied +42633,96931,Male,Loyal Customer,37,Personal Travel,Eco Plus,849,3,1,3,3,5,3,5,5,3,1,3,3,3,5,42,27.0,neutral or dissatisfied +42634,84001,Male,Loyal Customer,69,Personal Travel,Eco,373,2,0,2,5,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +42635,4708,Female,Loyal Customer,23,Business travel,Eco Plus,489,4,2,2,2,4,4,4,3,3,4,3,4,3,4,205,225.0,neutral or dissatisfied +42636,92234,Male,Loyal Customer,58,Business travel,Eco Plus,579,1,5,5,5,1,1,1,1,4,3,3,2,4,1,84,76.0,neutral or dissatisfied +42637,42149,Female,Loyal Customer,53,Personal Travel,Business,329,2,3,1,1,2,4,1,2,2,1,4,1,2,5,0,0.0,neutral or dissatisfied +42638,92752,Male,Loyal Customer,22,Personal Travel,Eco,1276,4,4,3,1,4,3,4,4,4,4,5,5,5,4,0,0.0,satisfied +42639,94898,Male,Loyal Customer,61,Business travel,Eco,319,5,2,2,2,5,5,5,5,5,4,2,4,3,5,5,0.0,satisfied +42640,124646,Male,Loyal Customer,45,Business travel,Business,3618,4,4,4,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +42641,1970,Male,Loyal Customer,28,Personal Travel,Eco,351,3,5,3,1,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +42642,118383,Male,Loyal Customer,47,Business travel,Business,1759,4,4,3,4,4,4,4,5,5,5,5,4,5,3,12,6.0,satisfied +42643,41209,Female,disloyal Customer,11,Business travel,Eco,986,2,2,2,1,3,2,5,3,4,4,2,2,4,3,0,0.0,neutral or dissatisfied +42644,17849,Female,disloyal Customer,23,Business travel,Eco,615,3,0,3,5,1,3,1,1,4,5,1,4,2,1,68,44.0,neutral or dissatisfied +42645,122582,Female,Loyal Customer,54,Business travel,Business,2031,5,5,2,5,4,4,5,5,5,5,5,5,5,4,33,20.0,satisfied +42646,71467,Female,Loyal Customer,50,Business travel,Eco Plus,867,2,3,3,3,3,3,3,2,2,2,2,3,2,1,34,32.0,neutral or dissatisfied +42647,40625,Female,Loyal Customer,47,Personal Travel,Eco,391,1,4,1,2,5,5,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +42648,40896,Female,Loyal Customer,29,Personal Travel,Eco,584,3,3,3,4,3,3,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +42649,117937,Male,Loyal Customer,36,Business travel,Business,3284,3,4,5,5,4,3,3,3,3,2,3,3,3,4,46,36.0,neutral or dissatisfied +42650,58022,Male,Loyal Customer,44,Personal Travel,Eco,1721,3,5,2,2,5,2,5,5,5,3,4,3,4,5,13,0.0,neutral or dissatisfied +42651,13410,Female,disloyal Customer,35,Business travel,Eco,409,1,0,1,2,5,1,4,5,1,3,4,3,4,5,109,108.0,neutral or dissatisfied +42652,4615,Female,Loyal Customer,47,Personal Travel,Eco,719,3,4,3,5,5,5,5,2,2,3,2,5,2,3,0,4.0,neutral or dissatisfied +42653,7432,Male,Loyal Customer,11,Personal Travel,Eco,522,4,4,4,2,1,4,1,1,5,2,4,3,4,1,35,29.0,satisfied +42654,110892,Male,Loyal Customer,48,Business travel,Business,2318,5,2,5,5,5,4,5,4,4,4,4,3,4,4,11,1.0,satisfied +42655,8592,Female,Loyal Customer,20,Personal Travel,Eco,109,2,3,2,1,5,2,1,5,5,2,1,4,5,5,3,8.0,neutral or dissatisfied +42656,43662,Male,Loyal Customer,60,Business travel,Business,2427,4,1,1,1,4,2,2,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +42657,54387,Male,Loyal Customer,38,Business travel,Eco,305,5,4,4,4,5,5,5,5,4,2,3,5,1,5,0,0.0,satisfied +42658,86093,Female,Loyal Customer,20,Business travel,Business,2342,2,3,3,3,2,2,2,2,3,1,4,4,3,2,5,7.0,neutral or dissatisfied +42659,78541,Female,Loyal Customer,25,Personal Travel,Eco,666,2,3,2,3,2,2,2,2,4,4,1,3,3,2,0,0.0,neutral or dissatisfied +42660,97910,Female,disloyal Customer,32,Business travel,Business,483,1,1,1,1,1,1,1,1,3,3,5,5,5,1,7,0.0,neutral or dissatisfied +42661,114274,Male,disloyal Customer,22,Business travel,Eco,453,4,0,3,1,1,3,1,1,5,4,1,3,3,1,8,0.0,neutral or dissatisfied +42662,12941,Male,Loyal Customer,57,Personal Travel,Eco,641,3,1,3,2,3,3,3,3,2,5,2,4,3,3,128,115.0,neutral or dissatisfied +42663,63937,Female,Loyal Customer,36,Personal Travel,Eco,1172,2,3,2,4,2,2,2,2,2,2,2,3,4,2,0,0.0,neutral or dissatisfied +42664,61702,Male,disloyal Customer,20,Business travel,Business,1379,0,0,0,4,4,0,1,4,5,4,5,4,4,4,0,0.0,satisfied +42665,68491,Female,Loyal Customer,57,Business travel,Business,1618,3,3,3,3,3,1,2,5,5,5,5,3,5,1,32,45.0,satisfied +42666,109346,Male,Loyal Customer,7,Personal Travel,Eco Plus,1072,3,2,3,3,3,3,3,2,5,4,3,3,2,3,158,144.0,neutral or dissatisfied +42667,45418,Female,Loyal Customer,44,Business travel,Eco,649,4,5,5,5,2,1,2,4,4,4,4,3,4,1,0,1.0,satisfied +42668,90525,Male,Loyal Customer,51,Business travel,Business,404,5,5,5,5,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +42669,55150,Male,Loyal Customer,12,Personal Travel,Eco,1303,2,5,2,3,3,2,4,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +42670,83830,Female,disloyal Customer,19,Business travel,Eco,425,4,0,5,2,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +42671,85889,Female,Loyal Customer,17,Personal Travel,Eco,2172,3,3,3,3,5,3,5,5,4,4,3,2,2,5,5,0.0,neutral or dissatisfied +42672,94281,Male,disloyal Customer,26,Business travel,Business,189,0,4,0,2,5,0,5,5,5,2,5,4,5,5,0,0.0,satisfied +42673,18449,Female,Loyal Customer,46,Personal Travel,Business,201,2,4,2,4,2,3,4,4,4,2,4,3,4,1,6,0.0,neutral or dissatisfied +42674,109664,Female,disloyal Customer,38,Business travel,Business,808,2,3,3,5,4,3,4,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +42675,92017,Female,Loyal Customer,27,Business travel,Business,1589,4,4,4,4,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +42676,19225,Male,Loyal Customer,50,Personal Travel,Eco,459,2,5,2,3,1,2,1,1,4,5,4,3,5,1,21,30.0,neutral or dissatisfied +42677,122338,Female,Loyal Customer,42,Business travel,Business,2030,4,4,4,4,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +42678,91912,Male,Loyal Customer,29,Business travel,Business,2475,1,1,1,1,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +42679,34424,Female,Loyal Customer,24,Personal Travel,Eco Plus,612,1,5,1,1,4,1,4,4,5,5,4,4,5,4,0,1.0,neutral or dissatisfied +42680,38854,Female,Loyal Customer,39,Business travel,Business,2153,4,3,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +42681,80995,Female,Loyal Customer,40,Business travel,Eco,228,5,5,5,5,5,5,5,5,5,2,1,1,5,5,0,0.0,satisfied +42682,70781,Male,Loyal Customer,43,Business travel,Business,3728,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +42683,75891,Male,Loyal Customer,39,Business travel,Business,603,3,3,3,3,5,5,4,5,5,5,5,3,5,4,18,6.0,satisfied +42684,41077,Male,Loyal Customer,52,Business travel,Eco,667,4,4,5,4,4,4,4,4,1,4,1,4,5,4,0,0.0,satisfied +42685,120917,Male,Loyal Customer,26,Business travel,Business,2026,3,3,3,3,4,4,4,4,4,2,5,4,5,4,19,100.0,satisfied +42686,14635,Male,Loyal Customer,45,Business travel,Business,1650,4,4,4,4,1,5,2,4,4,4,5,5,4,3,0,0.0,satisfied +42687,17680,Male,Loyal Customer,33,Personal Travel,Eco Plus,408,3,5,5,2,2,5,2,2,5,2,5,3,5,2,2,0.0,neutral or dissatisfied +42688,90827,Male,Loyal Customer,45,Business travel,Business,406,3,3,3,3,3,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +42689,111359,Male,Loyal Customer,19,Personal Travel,Business,1180,3,5,3,2,4,3,1,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +42690,102760,Male,Loyal Customer,48,Business travel,Business,1618,4,4,4,4,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +42691,21042,Female,Loyal Customer,30,Business travel,Business,3015,5,5,5,5,4,4,4,4,1,5,1,4,1,4,0,0.0,satisfied +42692,16610,Female,Loyal Customer,34,Business travel,Business,1008,1,1,1,1,5,4,2,2,2,2,2,3,2,2,0,0.0,satisfied +42693,21744,Female,Loyal Customer,22,Business travel,Eco,563,4,2,2,2,4,4,4,4,3,5,1,2,5,4,2,0.0,satisfied +42694,52349,Female,Loyal Customer,58,Business travel,Business,455,3,1,1,1,1,4,4,3,3,3,3,1,3,3,6,19.0,neutral or dissatisfied +42695,22,Female,Loyal Customer,70,Personal Travel,Eco,853,1,4,1,2,2,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +42696,110934,Male,Loyal Customer,65,Personal Travel,Eco,545,3,3,3,4,5,3,5,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +42697,50972,Male,Loyal Customer,35,Personal Travel,Eco,262,2,2,2,3,2,2,1,2,2,3,3,1,3,2,50,53.0,neutral or dissatisfied +42698,105180,Female,Loyal Customer,27,Personal Travel,Eco,220,0,3,0,3,5,0,5,5,2,2,2,1,2,5,0,0.0,satisfied +42699,67900,Male,Loyal Customer,57,Personal Travel,Eco,1438,2,1,2,2,1,2,1,1,1,5,3,3,2,1,29,31.0,neutral or dissatisfied +42700,68749,Female,Loyal Customer,57,Business travel,Business,1021,3,3,3,3,5,5,4,4,4,4,4,3,4,5,86,82.0,satisfied +42701,9953,Female,disloyal Customer,38,Business travel,Eco,357,2,1,2,4,2,2,2,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +42702,75303,Female,Loyal Customer,49,Personal Travel,Business,2556,4,2,3,4,3,1,1,2,3,4,4,1,3,1,0,2.0,neutral or dissatisfied +42703,17892,Male,Loyal Customer,51,Business travel,Eco Plus,371,4,1,4,1,4,4,4,4,3,5,1,4,3,4,174,160.0,satisfied +42704,109338,Female,Loyal Customer,67,Personal Travel,Eco,1072,3,1,3,3,1,3,3,1,1,3,1,4,1,1,6,12.0,neutral or dissatisfied +42705,115054,Male,Loyal Customer,33,Business travel,Business,1788,5,5,5,5,4,4,4,4,5,4,4,3,4,4,40,35.0,satisfied +42706,48543,Female,Loyal Customer,62,Business travel,Business,1538,2,2,2,2,2,3,3,5,5,5,5,5,5,5,0,0.0,satisfied +42707,81173,Male,Loyal Customer,47,Business travel,Business,2122,2,2,2,2,2,5,5,5,5,5,5,4,5,5,59,64.0,satisfied +42708,26535,Female,Loyal Customer,25,Business travel,Business,1599,2,1,1,1,2,2,2,2,2,3,4,2,4,2,0,0.0,neutral or dissatisfied +42709,78705,Female,disloyal Customer,25,Business travel,Business,554,3,2,3,4,4,3,4,4,1,5,3,4,4,4,9,0.0,neutral or dissatisfied +42710,84625,Male,Loyal Customer,44,Personal Travel,Eco,707,3,4,3,3,1,3,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +42711,37216,Female,Loyal Customer,25,Business travel,Business,2309,3,3,3,3,4,4,4,4,5,3,5,3,5,4,35,23.0,satisfied +42712,104134,Male,Loyal Customer,58,Business travel,Business,1526,4,3,4,3,4,4,4,4,4,4,4,1,4,1,11,5.0,neutral or dissatisfied +42713,71665,Male,Loyal Customer,62,Personal Travel,Eco,1012,2,1,2,4,1,2,1,1,4,3,4,1,4,1,0,6.0,neutral or dissatisfied +42714,108011,Female,Loyal Customer,45,Personal Travel,Eco Plus,271,4,5,4,5,2,4,5,4,4,4,4,5,4,5,6,2.0,satisfied +42715,73704,Male,Loyal Customer,68,Business travel,Eco,192,4,3,5,3,4,4,4,4,2,2,2,1,1,4,0,0.0,neutral or dissatisfied +42716,92488,Female,Loyal Customer,57,Business travel,Eco,1919,2,5,5,5,2,2,2,1,2,4,3,2,4,2,179,157.0,neutral or dissatisfied +42717,12306,Male,Loyal Customer,56,Business travel,Eco,285,4,4,4,4,4,4,4,4,1,3,4,1,3,4,0,0.0,neutral or dissatisfied +42718,119819,Male,Loyal Customer,48,Business travel,Business,912,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +42719,33226,Male,Loyal Customer,30,Business travel,Eco Plus,101,2,3,3,3,2,2,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +42720,114925,Female,disloyal Customer,22,Business travel,Business,372,4,0,4,3,5,4,1,5,5,5,5,4,5,5,1,0.0,satisfied +42721,66083,Female,Loyal Customer,12,Personal Travel,Eco,1055,2,5,2,3,4,2,1,4,3,3,5,3,4,4,0,3.0,neutral or dissatisfied +42722,34954,Male,Loyal Customer,17,Personal Travel,Eco,187,2,5,2,1,2,2,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +42723,88063,Female,Loyal Customer,55,Business travel,Business,2366,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +42724,106111,Female,Loyal Customer,43,Business travel,Business,3474,5,5,5,5,3,4,5,4,4,4,4,4,4,5,5,9.0,satisfied +42725,51554,Female,disloyal Customer,27,Business travel,Eco,355,1,1,1,3,1,1,1,1,4,1,3,2,2,1,0,0.0,neutral or dissatisfied +42726,106350,Male,Loyal Customer,60,Business travel,Business,674,2,2,2,2,2,4,5,5,5,5,5,3,5,4,25,7.0,satisfied +42727,125711,Female,Loyal Customer,16,Personal Travel,Eco,892,2,5,2,2,2,2,2,2,4,2,5,3,5,2,0,15.0,neutral or dissatisfied +42728,104542,Female,Loyal Customer,34,Personal Travel,Eco,1047,2,5,2,4,5,2,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +42729,6755,Male,Loyal Customer,25,Business travel,Business,2922,1,1,1,1,5,5,5,5,3,3,4,5,5,5,16,14.0,satisfied +42730,30820,Male,Loyal Customer,61,Personal Travel,Business,896,2,3,2,3,2,3,2,5,5,2,5,3,5,5,35,23.0,neutral or dissatisfied +42731,22038,Male,Loyal Customer,45,Personal Travel,Eco Plus,448,3,3,3,4,2,3,1,2,3,3,3,3,3,2,48,35.0,neutral or dissatisfied +42732,50487,Female,Loyal Customer,71,Business travel,Eco,209,3,5,5,5,2,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +42733,55033,Female,Loyal Customer,50,Business travel,Business,1609,2,3,3,3,3,2,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +42734,82364,Female,Loyal Customer,52,Personal Travel,Eco,453,1,5,1,1,3,4,4,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +42735,21121,Male,Loyal Customer,14,Personal Travel,Eco,227,2,4,0,3,2,0,4,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +42736,35029,Male,Loyal Customer,47,Business travel,Business,2707,2,2,2,2,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +42737,45491,Male,Loyal Customer,59,Personal Travel,Eco,587,5,3,5,3,2,5,5,2,3,1,3,4,2,2,11,5.0,satisfied +42738,72946,Female,Loyal Customer,62,Business travel,Eco,1089,1,4,2,4,1,3,3,1,1,1,1,4,1,1,10,2.0,neutral or dissatisfied +42739,47109,Female,Loyal Customer,28,Business travel,Business,2018,2,5,2,2,4,4,4,4,5,3,5,1,4,4,65,86.0,satisfied +42740,3799,Female,Loyal Customer,46,Business travel,Business,2934,4,4,1,4,4,3,3,5,3,4,5,3,3,3,229,257.0,satisfied +42741,109750,Female,disloyal Customer,24,Business travel,Business,587,4,0,4,5,2,4,2,2,3,2,4,5,5,2,0,0.0,satisfied +42742,67486,Female,disloyal Customer,40,Business travel,Business,641,3,3,3,3,2,3,4,2,5,4,5,3,4,2,46,46.0,neutral or dissatisfied +42743,54875,Male,disloyal Customer,43,Business travel,Eco,462,2,0,2,2,1,2,1,1,4,5,3,1,4,1,14,4.0,neutral or dissatisfied +42744,36656,Male,Loyal Customer,26,Personal Travel,Eco,1211,3,0,3,3,5,3,5,5,4,2,5,4,4,5,5,0.0,neutral or dissatisfied +42745,126435,Female,Loyal Customer,46,Personal Travel,Eco Plus,328,3,1,3,4,4,4,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +42746,107713,Female,Loyal Customer,55,Business travel,Business,2690,1,1,1,1,4,5,5,5,5,5,5,3,5,3,8,2.0,satisfied +42747,35465,Male,Loyal Customer,13,Personal Travel,Eco,972,3,2,2,4,2,2,2,2,3,5,3,2,4,2,88,99.0,neutral or dissatisfied +42748,21372,Male,Loyal Customer,36,Business travel,Business,528,5,5,5,5,3,1,4,4,4,4,4,2,4,5,46,40.0,satisfied +42749,6491,Male,Loyal Customer,49,Personal Travel,Eco,557,1,4,1,4,1,1,4,1,3,4,5,4,4,4,181,246.0,neutral or dissatisfied +42750,115340,Male,Loyal Customer,38,Business travel,Business,372,4,4,4,4,5,3,3,4,4,4,4,4,4,2,32,27.0,neutral or dissatisfied +42751,111782,Female,Loyal Customer,58,Business travel,Business,1620,1,3,3,3,3,3,2,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +42752,88327,Male,Loyal Customer,23,Business travel,Eco,444,3,4,4,4,3,3,1,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +42753,26616,Male,disloyal Customer,27,Business travel,Eco,404,4,0,4,3,3,4,3,3,4,4,3,3,4,3,0,13.0,neutral or dissatisfied +42754,103636,Male,Loyal Customer,44,Business travel,Business,251,1,1,1,1,2,4,5,4,4,4,4,5,4,4,22,20.0,satisfied +42755,49471,Male,Loyal Customer,36,Business travel,Business,3369,4,4,4,4,1,2,5,4,4,4,4,3,4,1,0,0.0,satisfied +42756,91099,Female,Loyal Customer,21,Personal Travel,Eco,404,2,4,2,3,2,2,2,2,1,4,4,3,4,2,4,4.0,neutral or dissatisfied +42757,16943,Male,Loyal Customer,60,Personal Travel,Eco,820,3,4,3,4,4,3,4,4,1,1,4,2,3,4,1,0.0,neutral or dissatisfied +42758,52719,Male,Loyal Customer,39,Business travel,Eco,406,4,2,2,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +42759,124201,Male,Loyal Customer,53,Business travel,Business,2176,5,5,2,5,4,3,5,4,4,5,4,3,4,4,0,0.0,satisfied +42760,73358,Male,Loyal Customer,46,Business travel,Business,1182,1,1,1,1,5,5,4,4,4,4,4,3,4,5,3,0.0,satisfied +42761,4674,Male,Loyal Customer,22,Business travel,Eco,327,4,3,3,3,4,4,4,4,1,4,1,5,5,4,2,6.0,satisfied +42762,72777,Female,Loyal Customer,40,Business travel,Business,2956,5,5,1,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +42763,120724,Female,Loyal Customer,42,Business travel,Business,90,3,2,2,2,5,4,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +42764,59983,Male,Loyal Customer,59,Personal Travel,Eco,997,3,4,3,3,4,3,4,4,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +42765,12230,Female,Loyal Customer,11,Personal Travel,Business,127,4,2,0,4,3,0,3,3,3,1,3,1,4,3,0,0.0,satisfied +42766,42936,Male,Loyal Customer,24,Business travel,Business,2323,2,2,2,2,4,5,4,4,3,5,4,5,4,4,0,0.0,satisfied +42767,69968,Male,Loyal Customer,57,Personal Travel,Business,236,4,5,0,4,2,1,1,2,2,0,2,1,2,4,0,0.0,neutral or dissatisfied +42768,17859,Male,Loyal Customer,66,Personal Travel,Business,371,3,3,3,3,1,4,4,1,1,3,5,3,1,2,0,0.0,neutral or dissatisfied +42769,57775,Female,Loyal Customer,40,Business travel,Business,2704,4,4,5,4,5,5,5,4,3,4,4,5,4,5,7,22.0,satisfied +42770,54299,Female,Loyal Customer,18,Personal Travel,Eco,1075,3,5,3,3,5,3,5,5,4,5,5,3,4,5,15,8.0,neutral or dissatisfied +42771,111410,Female,Loyal Customer,10,Personal Travel,Eco Plus,1050,3,4,3,4,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +42772,126911,Female,disloyal Customer,22,Business travel,Eco,370,3,4,3,5,2,3,4,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +42773,69183,Female,Loyal Customer,34,Personal Travel,Eco,187,3,4,0,1,2,0,2,2,4,2,4,4,4,2,38,37.0,neutral or dissatisfied +42774,40376,Female,Loyal Customer,61,Business travel,Business,2162,2,2,2,2,4,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +42775,103212,Female,Loyal Customer,32,Business travel,Business,3693,2,2,2,2,2,2,2,2,3,5,4,3,5,2,0,1.0,satisfied +42776,26236,Female,Loyal Customer,18,Personal Travel,Eco,270,2,0,2,1,5,2,5,5,3,4,5,3,5,5,19,14.0,neutral or dissatisfied +42777,5068,Female,Loyal Customer,46,Business travel,Business,122,3,3,3,3,4,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +42778,112994,Male,Loyal Customer,43,Business travel,Business,1797,1,1,1,1,3,5,5,4,4,4,4,4,4,3,2,0.0,satisfied +42779,127320,Female,Loyal Customer,55,Personal Travel,Eco Plus,1979,1,3,1,3,3,4,3,2,2,1,2,4,2,2,18,0.0,neutral or dissatisfied +42780,51423,Female,Loyal Customer,31,Personal Travel,Eco Plus,250,4,5,4,3,4,4,3,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +42781,43402,Male,Loyal Customer,9,Personal Travel,Eco,436,2,5,2,4,3,2,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +42782,34813,Female,Loyal Customer,54,Personal Travel,Eco,301,1,3,1,1,1,2,5,4,4,1,4,2,4,5,0,11.0,neutral or dissatisfied +42783,78016,Female,disloyal Customer,30,Business travel,Eco,332,2,3,2,3,1,2,1,1,1,1,3,2,4,1,76,85.0,neutral or dissatisfied +42784,68034,Male,disloyal Customer,21,Business travel,Eco,468,4,0,4,3,2,4,2,2,4,5,4,3,4,2,14,10.0,neutral or dissatisfied +42785,12121,Male,Loyal Customer,20,Personal Travel,Eco,1034,4,5,4,4,4,4,4,4,4,4,4,5,4,4,0,25.0,neutral or dissatisfied +42786,9826,Female,Loyal Customer,48,Business travel,Business,2389,4,4,4,4,5,5,5,4,4,4,4,5,5,5,87,146.0,satisfied +42787,82972,Male,Loyal Customer,39,Business travel,Business,1633,5,5,1,5,3,5,5,4,4,4,4,5,4,5,112,90.0,satisfied +42788,39201,Male,Loyal Customer,60,Business travel,Business,67,4,4,4,4,3,4,5,5,5,5,4,5,5,5,35,49.0,satisfied +42789,61214,Male,Loyal Customer,49,Business travel,Business,2679,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +42790,18000,Female,Loyal Customer,75,Business travel,Eco,332,4,1,4,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +42791,16184,Female,Loyal Customer,53,Business travel,Eco,277,4,1,1,1,5,2,4,4,4,4,4,5,4,1,0,0.0,satisfied +42792,35518,Female,Loyal Customer,20,Personal Travel,Eco,1076,2,1,2,3,2,1,1,2,1,2,3,1,3,1,135,124.0,neutral or dissatisfied +42793,106886,Female,disloyal Customer,25,Business travel,Eco,577,2,1,2,2,3,2,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +42794,78101,Male,Loyal Customer,49,Business travel,Business,3913,1,1,1,1,3,3,3,4,4,4,4,1,4,1,3,5.0,satisfied +42795,60136,Female,Loyal Customer,20,Business travel,Eco,1182,2,2,2,2,2,2,1,2,2,4,3,3,4,2,12,0.0,neutral or dissatisfied +42796,85243,Female,Loyal Customer,55,Business travel,Eco,289,3,3,3,3,4,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +42797,20447,Female,disloyal Customer,36,Business travel,Eco,177,3,0,2,4,5,2,4,5,3,5,1,3,1,5,40,21.0,neutral or dissatisfied +42798,56087,Male,Loyal Customer,8,Business travel,Eco Plus,2586,2,5,5,5,2,2,2,1,1,2,4,2,3,2,39,5.0,neutral or dissatisfied +42799,116959,Male,Loyal Customer,54,Business travel,Eco,338,1,5,4,5,2,1,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +42800,98751,Male,Loyal Customer,42,Personal Travel,Eco Plus,1558,1,4,1,2,5,1,5,5,5,5,3,5,4,5,7,0.0,neutral or dissatisfied +42801,73305,Female,Loyal Customer,32,Business travel,Business,3574,1,1,1,1,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +42802,77803,Male,Loyal Customer,50,Personal Travel,Eco,874,3,4,3,2,2,3,4,2,2,4,4,2,2,2,0,0.0,neutral or dissatisfied +42803,51049,Male,Loyal Customer,18,Personal Travel,Eco,109,1,4,1,4,5,1,5,5,4,4,4,4,3,5,1,2.0,neutral or dissatisfied +42804,46588,Male,Loyal Customer,51,Business travel,Business,125,3,2,2,2,5,2,2,1,1,1,3,1,1,3,16,36.0,neutral or dissatisfied +42805,113657,Female,Loyal Customer,25,Personal Travel,Eco,391,5,4,5,3,4,5,4,4,2,4,4,1,3,4,5,1.0,satisfied +42806,11470,Male,Loyal Customer,46,Business travel,Business,1724,5,5,5,5,4,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +42807,65774,Female,Loyal Customer,36,Business travel,Business,1389,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,19.0,satisfied +42808,120366,Female,Loyal Customer,39,Business travel,Business,2363,5,5,5,5,2,4,4,5,5,4,5,5,5,5,15,11.0,satisfied +42809,42996,Male,disloyal Customer,37,Business travel,Eco,192,2,5,2,3,3,2,3,3,1,5,1,5,1,3,65,62.0,neutral or dissatisfied +42810,128869,Male,Loyal Customer,37,Business travel,Business,2565,1,1,1,1,4,4,4,4,5,5,4,4,3,4,0,0.0,satisfied +42811,127854,Female,disloyal Customer,18,Business travel,Business,1276,4,0,4,3,2,4,2,2,3,5,4,4,5,2,0,0.0,satisfied +42812,56834,Female,Loyal Customer,50,Personal Travel,Eco,1605,2,3,2,3,4,2,3,4,4,2,3,1,4,3,6,19.0,neutral or dissatisfied +42813,86689,Female,Loyal Customer,56,Business travel,Business,1747,5,5,5,5,5,5,5,5,4,4,4,5,3,5,153,145.0,satisfied +42814,48980,Female,Loyal Customer,76,Business travel,Business,250,4,5,4,4,4,5,3,4,4,4,4,3,4,4,0,9.0,satisfied +42815,4545,Male,Loyal Customer,46,Business travel,Business,719,1,1,1,1,4,4,5,4,4,4,4,4,4,4,8,0.0,satisfied +42816,17443,Male,Loyal Customer,62,Personal Travel,Eco,376,1,5,1,2,3,1,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +42817,20498,Female,disloyal Customer,20,Business travel,Eco,139,3,5,4,2,2,4,2,2,4,5,3,1,2,2,0,0.0,neutral or dissatisfied +42818,127280,Female,Loyal Customer,15,Personal Travel,Eco,1107,3,4,3,5,5,3,5,5,5,5,4,3,5,5,57,56.0,neutral or dissatisfied +42819,52279,Female,Loyal Customer,52,Business travel,Business,3367,1,1,1,1,1,4,1,4,4,4,4,4,4,4,0,0.0,satisfied +42820,119341,Male,Loyal Customer,46,Personal Travel,Eco,214,3,2,0,4,4,0,3,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +42821,33783,Female,Loyal Customer,27,Business travel,Business,1661,3,3,3,3,5,5,5,5,1,2,1,5,5,5,0,0.0,satisfied +42822,25482,Male,Loyal Customer,59,Business travel,Eco,481,5,1,1,1,5,5,5,5,3,5,2,1,1,5,23,4.0,satisfied +42823,47356,Male,disloyal Customer,20,Business travel,Eco,599,1,2,1,4,4,1,4,4,1,1,3,2,4,4,0,0.0,neutral or dissatisfied +42824,64031,Female,Loyal Customer,15,Business travel,Business,3587,3,3,3,3,2,2,2,2,4,2,4,5,5,2,0,0.0,satisfied +42825,50537,Female,Loyal Customer,42,Personal Travel,Eco,421,0,1,0,2,3,2,2,3,3,0,3,1,3,4,2,23.0,satisfied +42826,52969,Male,Loyal Customer,19,Personal Travel,Eco,2306,4,4,4,4,5,4,5,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +42827,110677,Male,Loyal Customer,56,Business travel,Business,3126,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +42828,81201,Female,Loyal Customer,43,Business travel,Business,1426,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +42829,58071,Male,Loyal Customer,44,Business travel,Business,612,4,1,4,4,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +42830,12713,Male,disloyal Customer,28,Business travel,Eco,803,1,1,1,4,3,1,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +42831,6241,Female,Loyal Customer,31,Business travel,Eco,413,4,4,2,4,4,4,4,4,3,4,3,1,3,4,7,14.0,neutral or dissatisfied +42832,118218,Male,Loyal Customer,33,Business travel,Business,2029,4,4,4,4,4,4,4,4,2,4,3,4,4,4,0,0.0,neutral or dissatisfied +42833,100618,Male,Loyal Customer,31,Business travel,Business,3094,4,4,4,4,4,4,4,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +42834,122051,Female,disloyal Customer,38,Business travel,Eco,130,1,2,1,4,2,1,2,2,4,5,4,1,4,2,43,51.0,neutral or dissatisfied +42835,116779,Female,Loyal Customer,49,Personal Travel,Eco Plus,480,2,5,2,1,1,2,4,5,5,2,1,1,5,2,1,0.0,neutral or dissatisfied +42836,100151,Female,Loyal Customer,51,Business travel,Business,725,3,2,2,2,4,2,3,3,3,3,3,4,3,2,59,52.0,neutral or dissatisfied +42837,57232,Female,disloyal Customer,27,Business travel,Business,1514,5,5,5,1,3,5,3,3,4,5,5,4,5,3,13,0.0,satisfied +42838,12658,Female,Loyal Customer,31,Business travel,Business,1236,2,2,2,2,2,2,2,2,3,5,4,1,4,2,19,1.0,satisfied +42839,105828,Female,Loyal Customer,57,Personal Travel,Eco,842,3,4,3,3,1,3,3,4,4,3,4,1,4,2,6,25.0,neutral or dissatisfied +42840,16088,Male,Loyal Customer,32,Business travel,Eco,303,5,3,3,3,5,5,5,5,1,1,2,2,3,5,76,68.0,satisfied +42841,49745,Female,disloyal Customer,61,Business travel,Eco,373,3,2,3,3,2,3,2,2,1,1,3,4,4,2,21,33.0,neutral or dissatisfied +42842,51819,Male,Loyal Customer,32,Business travel,Eco Plus,370,4,5,5,5,4,4,4,4,4,1,3,1,4,4,0,0.0,satisfied +42843,79965,Male,disloyal Customer,34,Business travel,Business,1069,1,1,1,3,5,1,5,5,4,5,3,2,5,5,0,0.0,neutral or dissatisfied +42844,8899,Male,Loyal Customer,52,Business travel,Eco Plus,139,3,3,3,3,3,3,3,3,4,2,2,2,1,3,14,34.0,neutral or dissatisfied +42845,66042,Male,disloyal Customer,13,Business travel,Eco,1055,2,2,2,4,1,2,1,1,1,3,3,2,3,1,51,48.0,neutral or dissatisfied +42846,76174,Male,Loyal Customer,14,Personal Travel,Eco,546,3,3,5,1,2,5,2,2,3,5,3,1,3,2,0,2.0,neutral or dissatisfied +42847,79620,Male,Loyal Customer,27,Business travel,Business,3406,4,4,4,4,4,4,4,4,4,3,5,5,5,4,0,0.0,satisfied +42848,56422,Female,Loyal Customer,51,Business travel,Business,719,3,3,3,3,5,5,4,4,4,4,4,3,4,4,1,0.0,satisfied +42849,11904,Female,Loyal Customer,49,Business travel,Business,3128,2,2,2,2,5,5,5,4,4,4,4,3,4,3,2,2.0,satisfied +42850,46966,Male,Loyal Customer,56,Personal Travel,Eco,848,3,4,3,2,2,3,2,2,5,3,2,5,2,2,0,0.0,neutral or dissatisfied +42851,104685,Male,disloyal Customer,50,Business travel,Business,159,3,3,3,2,4,3,4,4,3,4,4,4,5,4,0,0.0,satisfied +42852,62050,Female,Loyal Customer,14,Personal Travel,Eco,2475,5,5,5,3,1,5,1,1,1,4,5,1,2,1,8,7.0,satisfied +42853,36811,Male,Loyal Customer,22,Business travel,Business,2300,1,1,1,1,2,2,2,2,5,3,4,5,3,2,25,12.0,satisfied +42854,10361,Female,Loyal Customer,52,Business travel,Business,158,1,1,1,1,4,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +42855,89483,Female,Loyal Customer,37,Business travel,Business,1931,4,5,4,4,3,4,5,4,4,4,4,3,4,5,10,0.0,satisfied +42856,58501,Male,Loyal Customer,44,Business travel,Business,2533,1,1,4,1,4,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +42857,31123,Male,Loyal Customer,51,Business travel,Business,991,3,3,3,3,3,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +42858,69863,Female,Loyal Customer,39,Personal Travel,Eco,1055,2,4,2,3,2,2,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +42859,45967,Female,Loyal Customer,39,Business travel,Eco,872,4,5,5,5,4,4,4,4,1,2,3,4,5,4,1,0.0,satisfied +42860,15913,Male,disloyal Customer,19,Business travel,Eco,528,5,4,5,5,3,5,3,3,1,5,4,5,1,3,11,0.0,satisfied +42861,115335,Male,disloyal Customer,28,Business travel,Eco,337,2,1,2,4,4,2,4,4,4,1,3,1,3,4,15,8.0,neutral or dissatisfied +42862,55717,Female,Loyal Customer,57,Business travel,Business,2343,1,1,2,1,3,4,5,4,4,4,4,3,4,5,0,6.0,satisfied +42863,35440,Female,Loyal Customer,17,Personal Travel,Eco,1056,3,5,3,2,4,3,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +42864,108960,Male,Loyal Customer,35,Business travel,Business,1871,5,5,5,5,4,5,4,4,4,4,4,5,4,4,27,34.0,satisfied +42865,98542,Female,Loyal Customer,33,Personal Travel,Eco,402,3,4,3,4,2,3,2,2,4,2,4,5,5,2,6,4.0,neutral or dissatisfied +42866,11410,Female,Loyal Customer,52,Business travel,Business,2423,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,4.0,satisfied +42867,76836,Male,Loyal Customer,30,Business travel,Business,989,1,1,5,1,4,4,4,4,5,2,5,3,4,4,26,42.0,satisfied +42868,73823,Male,Loyal Customer,36,Business travel,Business,3160,2,5,5,5,4,2,3,2,2,2,2,4,2,2,18,27.0,neutral or dissatisfied +42869,72262,Female,Loyal Customer,27,Business travel,Business,919,4,1,1,1,4,4,4,4,2,1,4,1,3,4,0,0.0,neutral or dissatisfied +42870,76642,Female,Loyal Customer,24,Personal Travel,Eco,534,3,5,2,2,4,2,1,4,5,2,5,3,4,4,0,9.0,neutral or dissatisfied +42871,109547,Male,Loyal Customer,31,Personal Travel,Eco,834,5,1,5,3,3,1,3,3,4,3,3,1,2,3,0,0.0,satisfied +42872,73071,Male,Loyal Customer,34,Business travel,Business,1085,2,1,2,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +42873,112236,Female,Loyal Customer,49,Business travel,Business,1506,1,1,1,1,4,4,5,5,5,5,5,4,5,3,8,13.0,satisfied +42874,119936,Male,Loyal Customer,30,Business travel,Business,868,4,4,4,4,5,5,5,5,3,4,4,4,4,5,0,7.0,satisfied +42875,9894,Male,Loyal Customer,39,Business travel,Business,508,1,1,1,1,2,4,5,4,4,4,4,5,4,5,13,13.0,satisfied +42876,26026,Male,Loyal Customer,44,Business travel,Eco,321,3,3,2,3,3,3,3,3,3,1,5,2,4,3,0,0.0,satisfied +42877,39140,Male,Loyal Customer,33,Personal Travel,Eco,252,2,4,2,1,4,2,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +42878,8242,Male,Loyal Customer,17,Personal Travel,Eco,294,2,5,2,4,1,2,1,1,3,4,4,4,4,1,10,9.0,neutral or dissatisfied +42879,95156,Male,Loyal Customer,51,Personal Travel,Eco,192,4,5,4,2,1,4,1,1,3,2,5,3,5,1,16,4.0,neutral or dissatisfied +42880,91771,Female,disloyal Customer,24,Business travel,Eco,226,3,2,3,3,5,3,5,5,2,5,3,3,4,5,0,2.0,neutral or dissatisfied +42881,76897,Female,Loyal Customer,51,Business travel,Eco,630,3,4,4,4,5,4,4,3,3,3,3,4,3,1,0,5.0,neutral or dissatisfied +42882,5656,Male,Loyal Customer,45,Business travel,Business,147,5,4,5,5,3,5,5,4,4,4,5,4,4,3,126,119.0,satisfied +42883,20139,Male,Loyal Customer,21,Personal Travel,Eco Plus,416,4,4,4,3,1,4,4,1,3,5,5,5,2,1,5,2.0,neutral or dissatisfied +42884,61195,Male,Loyal Customer,48,Business travel,Eco,948,4,4,4,4,4,4,4,4,3,1,4,4,4,4,42,36.0,neutral or dissatisfied +42885,24727,Male,Loyal Customer,16,Personal Travel,Eco,406,2,4,2,4,2,2,3,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +42886,125661,Female,Loyal Customer,46,Business travel,Eco,759,3,2,2,2,3,3,3,3,3,3,3,1,3,1,4,0.0,neutral or dissatisfied +42887,83362,Male,disloyal Customer,20,Business travel,Eco,1124,2,2,2,1,3,2,5,3,3,4,5,5,4,3,5,0.0,neutral or dissatisfied +42888,1690,Female,Loyal Customer,53,Personal Travel,Business,489,3,3,4,4,4,4,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +42889,89383,Male,Loyal Customer,30,Business travel,Business,2667,5,5,5,5,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +42890,4048,Female,Loyal Customer,24,Personal Travel,Eco,479,3,5,3,5,2,3,2,2,5,5,3,1,4,2,0,0.0,neutral or dissatisfied +42891,8091,Female,disloyal Customer,27,Business travel,Business,125,5,5,5,3,1,5,1,1,3,3,5,4,4,1,0,0.0,satisfied +42892,104824,Male,Loyal Customer,30,Business travel,Business,472,5,5,5,5,4,4,4,4,3,2,5,4,4,4,27,20.0,satisfied +42893,43966,Male,Loyal Customer,9,Business travel,Eco,596,2,3,3,3,2,2,1,2,3,3,4,1,4,2,66,67.0,neutral or dissatisfied +42894,4011,Male,disloyal Customer,33,Business travel,Business,419,1,1,1,1,3,1,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +42895,110088,Female,disloyal Customer,47,Business travel,Business,882,4,4,4,1,5,4,2,5,5,3,5,4,4,5,5,0.0,satisfied +42896,127453,Female,Loyal Customer,37,Personal Travel,Business,2075,4,2,4,4,1,2,3,4,4,4,4,4,4,2,2,0.0,neutral or dissatisfied +42897,87303,Male,Loyal Customer,46,Personal Travel,Eco,577,1,4,1,1,2,1,2,2,4,2,5,4,5,2,1,0.0,neutral or dissatisfied +42898,3550,Female,Loyal Customer,45,Business travel,Business,227,5,5,5,5,3,4,4,5,5,5,5,4,5,4,38,36.0,satisfied +42899,78010,Female,Loyal Customer,59,Business travel,Eco,214,4,4,4,4,2,2,2,5,5,4,5,1,5,4,0,11.0,neutral or dissatisfied +42900,113852,Female,Loyal Customer,42,Business travel,Business,1363,2,2,2,2,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +42901,8683,Female,Loyal Customer,44,Business travel,Business,2078,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +42902,111085,Male,Loyal Customer,67,Personal Travel,Eco,240,3,4,3,5,5,3,5,5,4,5,5,3,4,5,5,6.0,neutral or dissatisfied +42903,59440,Male,Loyal Customer,50,Business travel,Eco,606,1,0,0,2,2,1,2,2,4,2,2,4,2,2,0,5.0,neutral or dissatisfied +42904,38013,Female,Loyal Customer,46,Business travel,Business,3510,4,4,3,4,1,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +42905,104196,Female,Loyal Customer,60,Business travel,Business,1416,2,2,2,2,4,4,3,2,2,2,2,2,2,3,0,11.0,neutral or dissatisfied +42906,98158,Male,Loyal Customer,42,Business travel,Business,3990,4,2,2,2,2,2,2,4,4,4,4,3,4,3,14,3.0,neutral or dissatisfied +42907,119604,Male,Loyal Customer,66,Business travel,Business,3218,2,1,1,1,3,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +42908,48063,Female,disloyal Customer,25,Business travel,Business,414,2,0,2,2,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +42909,71130,Male,disloyal Customer,37,Business travel,Business,1739,3,3,3,3,3,3,3,3,5,2,4,4,4,3,4,5.0,neutral or dissatisfied +42910,53702,Male,Loyal Customer,20,Business travel,Business,2255,4,4,4,4,4,3,4,4,4,3,5,5,4,4,0,0.0,satisfied +42911,20943,Female,Loyal Customer,40,Business travel,Eco,689,1,3,3,3,1,1,1,4,4,3,2,1,1,1,172,191.0,neutral or dissatisfied +42912,96451,Male,disloyal Customer,25,Business travel,Business,436,2,4,3,3,5,3,5,5,5,2,5,5,4,5,6,19.0,neutral or dissatisfied +42913,70693,Male,disloyal Customer,40,Business travel,Business,447,4,3,3,3,2,3,2,2,4,2,4,5,4,2,11,0.0,satisfied +42914,37220,Female,Loyal Customer,32,Business travel,Business,3902,4,2,4,4,4,4,4,4,4,3,4,4,4,4,0,3.0,satisfied +42915,67765,Female,disloyal Customer,62,Business travel,Business,1464,4,4,4,4,5,4,5,5,4,4,5,4,5,5,0,2.0,neutral or dissatisfied +42916,83750,Male,disloyal Customer,29,Business travel,Business,1183,4,4,4,3,5,4,5,5,5,4,5,1,2,5,0,2.0,satisfied +42917,77385,Female,Loyal Customer,55,Business travel,Eco,188,4,1,1,1,1,3,5,5,5,4,5,2,5,5,0,0.0,satisfied +42918,122119,Female,Loyal Customer,35,Business travel,Eco Plus,130,3,1,1,1,3,3,3,3,1,3,4,2,4,3,0,17.0,neutral or dissatisfied +42919,85637,Male,Loyal Customer,11,Personal Travel,Eco,153,3,3,3,1,5,3,5,5,5,4,5,1,3,5,0,0.0,neutral or dissatisfied +42920,37749,Male,disloyal Customer,37,Business travel,Eco Plus,1028,1,1,1,2,5,1,5,5,5,5,3,4,3,5,9,3.0,neutral or dissatisfied +42921,11329,Male,Loyal Customer,24,Personal Travel,Eco,270,2,1,2,3,5,2,5,5,3,5,2,1,3,5,0,0.0,neutral or dissatisfied +42922,18455,Male,Loyal Customer,39,Business travel,Eco,201,3,1,4,1,3,3,3,3,5,5,4,3,4,3,6,5.0,satisfied +42923,49862,Male,Loyal Customer,41,Business travel,Eco,56,5,2,2,2,5,5,5,5,3,1,4,2,3,5,0,0.0,satisfied +42924,87443,Male,Loyal Customer,58,Business travel,Business,1756,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,1.0,satisfied +42925,95809,Male,Loyal Customer,31,Personal Travel,Eco,1050,3,4,3,3,5,3,4,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +42926,45436,Male,Loyal Customer,26,Personal Travel,Eco,649,1,4,1,3,5,1,5,5,3,4,3,3,4,5,0,4.0,neutral or dissatisfied +42927,106457,Male,Loyal Customer,68,Personal Travel,Eco,1670,2,1,2,3,5,2,4,5,2,4,4,4,3,5,3,0.0,neutral or dissatisfied +42928,20864,Male,Loyal Customer,43,Personal Travel,Eco,508,2,5,2,3,2,2,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +42929,13083,Female,Loyal Customer,17,Business travel,Business,3982,3,3,5,3,3,3,3,3,1,5,3,3,4,3,8,9.0,neutral or dissatisfied +42930,18265,Female,Loyal Customer,56,Personal Travel,Eco,235,2,3,2,4,1,4,3,3,3,2,2,3,3,4,74,94.0,neutral or dissatisfied +42931,26488,Male,Loyal Customer,48,Personal Travel,Business,829,2,4,2,1,3,5,4,3,3,2,3,3,3,5,0,9.0,neutral or dissatisfied +42932,38879,Male,Loyal Customer,30,Business travel,Eco,261,5,4,3,3,5,5,5,5,5,1,3,4,2,5,0,0.0,satisfied +42933,60791,Female,Loyal Customer,56,Business travel,Business,472,1,1,1,1,4,5,4,4,4,4,4,4,4,5,42,61.0,satisfied +42934,84383,Female,Loyal Customer,38,Business travel,Eco,591,4,5,5,5,4,4,4,4,3,2,4,1,4,4,0,7.0,neutral or dissatisfied +42935,35489,Male,Loyal Customer,50,Personal Travel,Eco,1005,1,3,1,3,3,1,3,3,5,5,5,2,3,3,0,37.0,neutral or dissatisfied +42936,92458,Female,disloyal Customer,44,Business travel,Business,2139,3,3,3,3,2,3,2,2,3,5,3,3,5,2,0,0.0,neutral or dissatisfied +42937,45655,Male,Loyal Customer,30,Personal Travel,Eco,230,2,4,0,4,2,0,2,2,1,2,4,4,4,2,0,0.0,neutral or dissatisfied +42938,45681,Male,disloyal Customer,25,Business travel,Eco,826,2,2,2,5,3,2,3,3,5,4,3,2,4,3,0,0.0,neutral or dissatisfied +42939,94692,Female,Loyal Customer,43,Business travel,Business,323,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +42940,112868,Male,Loyal Customer,22,Business travel,Business,2734,3,3,5,3,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +42941,27181,Male,Loyal Customer,43,Personal Travel,Eco,2677,4,5,4,4,4,4,4,5,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +42942,69299,Female,disloyal Customer,26,Business travel,Business,1096,0,0,0,3,4,0,4,4,5,4,5,4,4,4,0,4.0,satisfied +42943,1679,Male,Loyal Customer,55,Personal Travel,Eco,561,1,4,1,2,3,1,3,3,4,5,5,3,5,3,0,12.0,neutral or dissatisfied +42944,26255,Female,Loyal Customer,35,Business travel,Eco Plus,406,3,3,3,3,3,4,3,3,4,3,3,2,4,3,20,14.0,neutral or dissatisfied +42945,102001,Male,Loyal Customer,25,Business travel,Eco Plus,628,2,5,5,5,2,2,4,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +42946,49838,Female,disloyal Customer,38,Business travel,Eco,109,2,0,2,3,4,2,4,4,5,5,5,1,3,4,0,0.0,neutral or dissatisfied +42947,10124,Female,Loyal Customer,48,Business travel,Business,3288,3,1,1,1,3,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +42948,3569,Male,Loyal Customer,45,Personal Travel,Eco,227,3,4,3,2,3,3,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +42949,58623,Female,disloyal Customer,41,Business travel,Business,235,3,3,3,3,3,3,3,3,3,5,3,4,4,3,9,7.0,neutral or dissatisfied +42950,8208,Male,Loyal Customer,58,Business travel,Business,294,4,4,4,4,1,4,5,4,4,4,4,1,4,5,0,2.0,satisfied +42951,65327,Male,disloyal Customer,48,Business travel,Business,631,5,5,5,4,3,5,3,3,5,5,5,4,5,3,0,0.0,satisfied +42952,4023,Male,Loyal Customer,43,Business travel,Business,483,4,4,4,4,5,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +42953,3292,Male,Loyal Customer,22,Personal Travel,Eco,479,4,2,4,4,4,4,1,4,1,5,4,2,4,4,0,43.0,neutral or dissatisfied +42954,121355,Female,Loyal Customer,19,Business travel,Eco Plus,347,5,4,4,4,5,5,5,5,4,5,3,4,1,5,6,0.0,satisfied +42955,98232,Male,Loyal Customer,40,Business travel,Business,1697,2,2,2,2,5,5,5,3,3,3,3,4,3,5,10,0.0,satisfied +42956,41748,Female,disloyal Customer,24,Business travel,Eco,695,1,1,1,2,3,1,3,3,4,4,2,1,3,3,0,0.0,neutral or dissatisfied +42957,114307,Male,Loyal Customer,60,Personal Travel,Eco,819,3,1,3,4,1,3,1,1,1,4,4,1,4,1,15,13.0,neutral or dissatisfied +42958,78534,Male,Loyal Customer,21,Personal Travel,Eco,526,2,4,2,1,3,2,4,3,3,4,4,5,4,3,4,0.0,neutral or dissatisfied +42959,59721,Female,Loyal Customer,33,Business travel,Business,2829,3,3,3,3,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +42960,27575,Male,Loyal Customer,52,Personal Travel,Eco,697,2,4,2,3,5,2,2,5,1,1,3,4,3,5,0,0.0,neutral or dissatisfied +42961,109677,Male,Loyal Customer,50,Personal Travel,Eco,802,3,1,3,4,1,3,1,1,1,3,4,3,3,1,0,0.0,neutral or dissatisfied +42962,49285,Male,Loyal Customer,30,Business travel,Business,308,5,5,5,5,5,5,5,5,4,1,2,3,3,5,2,0.0,satisfied +42963,104833,Female,Loyal Customer,52,Business travel,Business,3734,2,3,3,3,3,2,2,2,2,2,2,3,2,1,11,27.0,neutral or dissatisfied +42964,104809,Female,Loyal Customer,50,Personal Travel,Eco,587,2,5,3,1,5,5,4,5,5,3,5,5,5,4,27,33.0,neutral or dissatisfied +42965,63367,Female,Loyal Customer,66,Personal Travel,Eco,337,3,5,3,4,3,1,1,2,2,3,2,4,2,4,0,18.0,neutral or dissatisfied +42966,51609,Female,Loyal Customer,53,Business travel,Eco,425,3,2,2,2,2,5,2,2,2,3,2,1,2,2,0,0.0,satisfied +42967,51131,Female,Loyal Customer,26,Personal Travel,Eco,78,3,5,3,4,2,3,2,2,1,2,4,1,2,2,0,0.0,neutral or dissatisfied +42968,119219,Male,disloyal Customer,52,Personal Travel,Eco,257,3,1,3,3,4,3,4,4,2,4,4,2,4,4,0,0.0,neutral or dissatisfied +42969,75488,Male,Loyal Customer,43,Business travel,Business,2267,4,4,4,4,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +42970,81463,Male,disloyal Customer,45,Business travel,Business,528,4,4,4,5,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +42971,54036,Male,Loyal Customer,44,Business travel,Business,1416,5,5,5,5,2,1,2,3,3,3,3,4,3,4,0,0.0,satisfied +42972,10225,Male,Loyal Customer,47,Business travel,Business,308,4,4,4,4,5,4,4,5,5,5,5,4,5,3,10,20.0,satisfied +42973,56357,Female,Loyal Customer,23,Personal Travel,Eco,200,3,5,3,2,2,3,2,2,5,5,5,5,4,2,7,0.0,neutral or dissatisfied +42974,52399,Male,Loyal Customer,46,Personal Travel,Eco,355,1,4,1,4,4,1,4,4,3,2,5,4,4,4,10,20.0,neutral or dissatisfied +42975,96383,Male,Loyal Customer,39,Business travel,Business,3121,1,1,1,1,2,4,5,5,5,5,5,4,5,3,1,0.0,satisfied +42976,81445,Male,disloyal Customer,36,Business travel,Business,408,2,2,2,5,1,2,2,1,3,5,5,4,5,1,64,95.0,neutral or dissatisfied +42977,120119,Female,Loyal Customer,62,Personal Travel,Eco,1576,0,4,0,3,2,3,4,3,3,0,2,1,3,4,0,0.0,satisfied +42978,123942,Male,Loyal Customer,29,Personal Travel,Eco,544,1,2,1,3,3,1,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +42979,24524,Female,disloyal Customer,26,Business travel,Eco,892,3,3,3,3,1,3,1,1,2,2,3,3,4,1,0,23.0,neutral or dissatisfied +42980,24968,Female,Loyal Customer,30,Business travel,Eco Plus,949,4,4,4,4,4,4,4,4,1,5,4,1,3,4,0,0.0,satisfied +42981,31807,Male,disloyal Customer,20,Business travel,Eco,1153,4,4,4,3,1,4,1,1,1,1,3,4,3,1,0,0.0,satisfied +42982,66148,Female,Loyal Customer,17,Business travel,Eco Plus,583,4,3,2,3,4,4,3,4,2,4,4,1,4,4,125,119.0,neutral or dissatisfied +42983,123898,Female,Loyal Customer,47,Personal Travel,Eco,546,3,4,3,4,2,5,4,5,5,3,4,3,5,3,5,20.0,neutral or dissatisfied +42984,76643,Female,Loyal Customer,44,Personal Travel,Eco,516,1,4,4,2,5,5,5,5,5,4,5,5,5,4,3,0.0,neutral or dissatisfied +42985,1653,Female,Loyal Customer,48,Business travel,Business,3949,3,2,2,2,1,1,1,3,3,3,3,2,3,1,13,22.0,neutral or dissatisfied +42986,70372,Female,Loyal Customer,15,Personal Travel,Eco,1145,2,1,2,3,1,2,1,1,2,1,3,2,3,1,57,69.0,neutral or dissatisfied +42987,80841,Female,Loyal Customer,44,Business travel,Eco,692,4,5,2,5,2,2,2,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +42988,9642,Male,Loyal Customer,48,Business travel,Business,199,5,5,5,5,2,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +42989,88103,Male,Loyal Customer,39,Business travel,Business,3808,3,3,3,3,4,4,5,5,5,5,5,4,5,3,41,25.0,satisfied +42990,107907,Female,Loyal Customer,59,Business travel,Eco,861,3,2,5,2,3,3,2,2,2,3,2,1,2,3,0,12.0,neutral or dissatisfied +42991,107549,Male,Loyal Customer,34,Business travel,Eco,1521,2,3,3,3,2,3,2,2,4,3,4,2,3,2,14,5.0,neutral or dissatisfied +42992,89457,Male,Loyal Customer,61,Personal Travel,Eco,151,1,3,1,1,5,1,5,5,5,5,5,3,1,5,0,0.0,neutral or dissatisfied +42993,115134,Male,Loyal Customer,43,Business travel,Business,3007,1,1,1,1,2,4,4,5,5,4,5,5,5,5,1,4.0,satisfied +42994,102740,Male,Loyal Customer,13,Personal Travel,Eco,365,2,4,5,3,3,5,4,3,2,2,4,4,3,3,8,3.0,neutral or dissatisfied +42995,71972,Male,Loyal Customer,33,Business travel,Business,1440,4,4,4,4,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +42996,54311,Male,Loyal Customer,50,Business travel,Business,1597,4,4,4,4,4,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +42997,38641,Male,Loyal Customer,35,Business travel,Business,2704,5,5,4,5,1,4,5,5,5,5,5,4,5,1,0,0.0,satisfied +42998,88211,Male,Loyal Customer,46,Business travel,Business,3034,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +42999,35650,Female,Loyal Customer,20,Business travel,Business,2465,4,4,1,4,5,5,5,3,1,4,1,5,5,5,0,20.0,satisfied +43000,108511,Male,disloyal Customer,23,Business travel,Eco,519,5,1,5,3,4,5,5,4,5,3,5,3,4,4,2,0.0,satisfied +43001,96852,Female,Loyal Customer,43,Business travel,Business,2426,3,3,3,3,2,5,4,4,4,4,4,3,4,4,8,3.0,satisfied +43002,64197,Male,disloyal Customer,23,Business travel,Eco,853,4,4,4,4,1,4,1,1,4,5,4,4,5,1,38,59.0,neutral or dissatisfied +43003,27821,Male,Loyal Customer,24,Business travel,Eco,680,2,2,2,2,2,2,4,2,4,3,4,3,3,2,0,0.0,neutral or dissatisfied +43004,14475,Male,disloyal Customer,13,Business travel,Eco Plus,674,4,3,4,4,1,4,1,1,1,3,4,2,1,1,0,0.0,satisfied +43005,26906,Female,Loyal Customer,52,Business travel,Business,1770,5,5,5,5,1,4,5,5,5,5,5,1,5,1,0,0.0,satisfied +43006,58400,Female,Loyal Customer,27,Business travel,Business,3104,4,3,3,3,4,3,4,4,3,3,3,4,2,4,19,6.0,neutral or dissatisfied +43007,76018,Female,Loyal Customer,47,Business travel,Business,311,3,3,3,3,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +43008,60645,Male,Loyal Customer,8,Business travel,Business,1620,3,3,3,3,2,2,2,2,5,5,3,3,4,2,2,0.0,satisfied +43009,116015,Male,Loyal Customer,60,Personal Travel,Eco,342,4,5,5,4,2,5,2,2,3,2,4,5,5,2,0,0.0,satisfied +43010,128446,Female,disloyal Customer,23,Business travel,Eco,247,1,1,1,3,5,1,5,5,3,4,3,4,4,5,31,34.0,neutral or dissatisfied +43011,79163,Female,Loyal Customer,11,Personal Travel,Eco Plus,2239,2,4,2,5,2,3,3,3,5,3,5,3,5,3,0,9.0,neutral or dissatisfied +43012,45839,Female,Loyal Customer,49,Personal Travel,Eco,517,3,5,3,5,3,4,4,3,3,3,4,5,3,5,6,5.0,neutral or dissatisfied +43013,41456,Male,Loyal Customer,31,Personal Travel,Business,1269,1,4,2,3,2,2,2,2,1,2,3,3,3,2,0,0.0,neutral or dissatisfied +43014,115496,Male,disloyal Customer,42,Business travel,Eco,337,4,2,4,4,3,4,3,3,3,2,4,3,3,3,17,10.0,neutral or dissatisfied +43015,98188,Female,Loyal Customer,47,Business travel,Business,327,0,0,0,2,5,4,5,4,4,4,3,3,4,3,60,56.0,satisfied +43016,2476,Male,Loyal Customer,44,Personal Travel,Eco Plus,773,4,3,4,3,1,4,1,1,3,3,4,4,4,1,0,12.0,neutral or dissatisfied +43017,113915,Male,Loyal Customer,19,Business travel,Eco Plus,2295,1,2,1,2,1,1,2,1,4,2,3,1,3,1,0,8.0,neutral or dissatisfied +43018,109969,Male,Loyal Customer,17,Personal Travel,Eco,1165,2,5,2,4,4,2,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +43019,39860,Male,Loyal Customer,33,Business travel,Business,272,1,1,1,1,5,5,5,5,3,2,3,1,4,5,0,0.0,satisfied +43020,70391,Female,disloyal Customer,36,Business travel,Business,1562,4,4,4,2,5,4,5,5,5,3,4,3,5,5,1,0.0,neutral or dissatisfied +43021,10183,Female,Loyal Customer,42,Business travel,Business,301,0,0,0,3,3,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +43022,64014,Male,Loyal Customer,58,Business travel,Business,919,2,5,5,5,1,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +43023,74897,Female,Loyal Customer,42,Business travel,Business,2475,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +43024,126959,Male,Loyal Customer,52,Business travel,Business,3119,1,1,1,1,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +43025,95530,Male,Loyal Customer,67,Personal Travel,Eco Plus,239,4,4,0,1,1,0,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +43026,99412,Female,disloyal Customer,30,Business travel,Eco,337,3,1,3,4,4,3,3,4,1,5,3,4,4,4,0,0.0,neutral or dissatisfied +43027,70785,Male,disloyal Customer,48,Business travel,Eco,328,3,4,3,3,2,3,2,2,4,4,3,3,3,2,28,24.0,neutral or dissatisfied +43028,50701,Male,Loyal Customer,27,Personal Travel,Eco,250,5,4,0,5,5,0,5,5,5,4,5,3,4,5,9,0.0,satisfied +43029,82694,Female,Loyal Customer,42,Business travel,Business,632,2,2,2,2,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +43030,7609,Male,Loyal Customer,70,Business travel,Business,402,3,3,3,3,3,3,4,4,4,4,4,5,4,3,18,0.0,satisfied +43031,33040,Male,Loyal Customer,65,Personal Travel,Eco,216,3,0,0,3,1,0,1,1,4,4,5,4,4,1,5,1.0,neutral or dissatisfied +43032,43487,Female,Loyal Customer,33,Business travel,Business,1720,5,5,5,5,2,4,3,5,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +43033,6239,Male,Loyal Customer,72,Business travel,Eco,594,3,4,4,4,3,3,3,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +43034,82196,Female,Loyal Customer,66,Personal Travel,Eco,1927,1,4,1,2,5,3,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +43035,22711,Female,disloyal Customer,27,Business travel,Eco Plus,589,3,3,3,4,3,3,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +43036,108436,Male,Loyal Customer,44,Business travel,Eco,1444,3,3,3,3,3,3,3,3,2,5,1,3,1,3,43,23.0,neutral or dissatisfied +43037,3299,Male,Loyal Customer,30,Personal Travel,Eco,479,2,4,2,5,2,2,2,2,5,3,1,2,2,2,0,0.0,neutral or dissatisfied +43038,73895,Female,Loyal Customer,35,Business travel,Business,2585,2,2,2,2,4,4,4,4,2,4,5,4,5,4,32,55.0,satisfied +43039,53132,Female,Loyal Customer,47,Personal Travel,Eco Plus,2065,4,5,4,4,2,4,4,4,4,4,4,5,4,5,5,23.0,neutral or dissatisfied +43040,25291,Male,disloyal Customer,26,Business travel,Eco,321,3,0,3,2,5,3,5,5,3,2,1,5,5,5,0,0.0,neutral or dissatisfied +43041,63941,Female,Loyal Customer,48,Personal Travel,Eco,1192,2,4,2,2,2,5,5,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +43042,108054,Male,Loyal Customer,23,Personal Travel,Eco,591,2,4,2,5,5,2,5,5,5,5,5,4,5,5,50,45.0,neutral or dissatisfied +43043,44094,Male,Loyal Customer,40,Business travel,Business,3531,4,4,4,4,3,2,5,5,5,5,5,5,5,4,0,0.0,satisfied +43044,119047,Male,Loyal Customer,31,Business travel,Business,2279,3,3,3,3,4,5,4,4,5,3,4,3,4,4,0,0.0,satisfied +43045,76652,Female,Loyal Customer,53,Personal Travel,Eco,547,3,3,3,2,5,4,2,3,3,3,3,3,3,4,0,4.0,neutral or dissatisfied +43046,42612,Female,Loyal Customer,21,Business travel,Business,481,2,2,2,2,4,4,4,4,4,2,5,2,3,4,0,0.0,satisfied +43047,110786,Female,Loyal Customer,72,Business travel,Eco,990,2,4,4,4,2,3,3,3,3,2,3,3,3,4,40,32.0,neutral or dissatisfied +43048,88435,Female,disloyal Customer,25,Business travel,Eco,545,3,2,3,3,4,3,4,4,1,1,3,4,3,4,0,8.0,neutral or dissatisfied +43049,12188,Female,Loyal Customer,20,Personal Travel,Eco,1075,3,4,2,3,5,2,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +43050,29288,Female,disloyal Customer,38,Business travel,Eco,834,2,2,2,5,3,2,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +43051,60658,Male,Loyal Customer,63,Personal Travel,Eco,1620,5,5,5,4,1,5,1,1,5,4,3,4,4,1,20,,satisfied +43052,94589,Male,Loyal Customer,31,Business travel,Business,239,1,1,1,1,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +43053,6058,Female,Loyal Customer,25,Personal Travel,Eco,690,1,4,1,3,1,1,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +43054,29205,Male,disloyal Customer,22,Business travel,Eco,1064,2,2,2,2,4,2,4,4,1,2,3,2,2,4,0,0.0,neutral or dissatisfied +43055,105429,Male,Loyal Customer,15,Personal Travel,Eco,452,3,4,3,3,2,3,2,2,4,5,4,3,5,2,4,6.0,neutral or dissatisfied +43056,52722,Female,Loyal Customer,46,Business travel,Eco,406,4,5,3,5,4,3,3,4,4,4,4,2,4,3,0,3.0,neutral or dissatisfied +43057,67610,Male,disloyal Customer,25,Business travel,Eco,1171,5,5,5,2,2,5,2,2,4,5,5,3,5,2,24,0.0,satisfied +43058,110493,Female,Loyal Customer,53,Personal Travel,Eco,883,2,5,2,3,3,5,5,1,1,2,1,4,1,1,1,0.0,neutral or dissatisfied +43059,18991,Male,Loyal Customer,31,Business travel,Business,388,3,1,1,1,3,3,3,4,3,4,4,3,2,3,178,202.0,neutral or dissatisfied +43060,95796,Female,Loyal Customer,61,Business travel,Eco Plus,181,3,4,4,4,5,4,3,3,3,3,3,3,3,3,11,7.0,neutral or dissatisfied +43061,83759,Male,Loyal Customer,49,Business travel,Business,2746,5,5,5,5,2,5,4,5,5,5,5,3,5,5,2,6.0,satisfied +43062,52852,Male,Loyal Customer,46,Personal Travel,Eco,1721,1,2,1,2,3,1,3,3,4,4,2,2,2,3,38,39.0,neutral or dissatisfied +43063,44279,Female,Loyal Customer,10,Personal Travel,Eco Plus,118,2,5,2,4,5,2,3,5,1,1,5,1,5,5,0,0.0,neutral or dissatisfied +43064,102015,Male,Loyal Customer,51,Business travel,Business,2054,4,4,4,4,3,4,5,5,5,5,5,5,5,4,0,8.0,satisfied +43065,117004,Female,disloyal Customer,24,Business travel,Eco,621,4,0,4,1,4,4,4,4,4,5,4,4,3,4,166,167.0,satisfied +43066,69817,Female,disloyal Customer,23,Business travel,Eco,1055,1,1,1,2,4,1,3,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +43067,55672,Female,disloyal Customer,36,Business travel,Business,1025,2,2,2,3,5,2,4,5,4,5,4,4,4,5,37,40.0,neutral or dissatisfied +43068,32953,Female,Loyal Customer,58,Personal Travel,Eco,101,3,3,3,1,1,1,3,4,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +43069,81696,Male,Loyal Customer,8,Personal Travel,Eco,907,3,5,3,4,2,3,2,2,5,5,4,4,5,2,7,0.0,neutral or dissatisfied +43070,113058,Female,disloyal Customer,28,Business travel,Eco,569,2,1,2,2,5,2,5,5,2,5,3,2,2,5,0,0.0,neutral or dissatisfied +43071,111994,Female,Loyal Customer,70,Personal Travel,Eco,533,3,5,3,2,3,4,5,3,3,3,3,4,3,5,8,5.0,neutral or dissatisfied +43072,75674,Male,Loyal Customer,41,Business travel,Business,2562,2,2,2,2,5,5,4,4,4,4,4,4,4,3,6,0.0,satisfied +43073,76150,Female,Loyal Customer,55,Business travel,Business,689,5,5,5,5,2,4,5,5,5,5,5,4,5,3,0,3.0,satisfied +43074,71943,Male,disloyal Customer,28,Business travel,Business,1440,5,4,4,5,3,4,3,3,4,5,5,4,4,3,0,5.0,satisfied +43075,54840,Female,Loyal Customer,63,Business travel,Business,862,3,3,2,2,3,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +43076,3725,Male,Loyal Customer,53,Personal Travel,Eco,431,3,4,3,5,3,3,3,3,5,4,5,3,5,3,106,89.0,neutral or dissatisfied +43077,102105,Female,Loyal Customer,39,Business travel,Business,2255,2,2,2,2,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +43078,124496,Male,Loyal Customer,30,Business travel,Eco,930,3,4,4,4,3,3,3,3,1,1,2,1,3,3,0,0.0,neutral or dissatisfied +43079,113889,Male,Loyal Customer,28,Business travel,Business,2329,4,4,4,4,4,4,4,4,4,4,5,3,5,4,7,11.0,satisfied +43080,99705,Male,Loyal Customer,20,Business travel,Eco,2026,2,3,3,3,2,1,1,2,4,1,1,3,2,2,40,45.0,neutral or dissatisfied +43081,124759,Female,Loyal Customer,42,Business travel,Business,1535,1,5,1,1,3,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +43082,86544,Male,Loyal Customer,28,Personal Travel,Eco,762,3,5,3,3,5,3,5,5,5,4,5,4,4,5,1,9.0,neutral or dissatisfied +43083,96107,Female,Loyal Customer,15,Personal Travel,Eco,775,1,4,1,3,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +43084,111208,Male,disloyal Customer,9,Business travel,Eco,821,4,3,3,3,5,3,3,5,5,2,3,5,4,5,0,0.0,satisfied +43085,73968,Male,Loyal Customer,28,Personal Travel,Eco,2218,3,5,3,3,2,3,2,2,2,2,1,2,1,2,4,0.0,neutral or dissatisfied +43086,80822,Female,Loyal Customer,42,Business travel,Business,1571,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +43087,52602,Male,Loyal Customer,37,Business travel,Eco,160,4,3,3,3,4,4,4,4,4,3,5,4,1,4,3,0.0,satisfied +43088,64034,Female,Loyal Customer,25,Business travel,Business,1596,2,2,2,2,4,4,4,4,3,4,5,5,4,4,4,0.0,satisfied +43089,46334,Male,Loyal Customer,27,Business travel,Business,692,2,2,2,2,4,4,4,4,1,5,5,5,5,4,5,29.0,satisfied +43090,99042,Female,Loyal Customer,52,Business travel,Business,2131,0,4,0,3,4,4,4,2,2,2,2,3,2,4,11,13.0,satisfied +43091,14975,Male,Loyal Customer,41,Business travel,Eco,527,4,2,2,2,4,4,4,4,4,1,3,5,1,4,0,0.0,satisfied +43092,49025,Female,Loyal Customer,33,Business travel,Business,86,4,4,4,4,5,3,5,4,4,4,4,1,4,4,23,27.0,satisfied +43093,53586,Male,Loyal Customer,44,Personal Travel,Eco,391,0,4,0,3,4,0,4,4,4,5,4,5,5,4,0,0.0,satisfied +43094,67140,Male,disloyal Customer,23,Business travel,Eco,1121,3,3,3,4,4,3,4,4,1,1,3,4,4,4,0,0.0,neutral or dissatisfied +43095,43655,Male,Loyal Customer,26,Business travel,Eco,695,4,5,5,5,4,4,5,4,1,5,2,4,4,4,0,14.0,satisfied +43096,96035,Male,disloyal Customer,39,Business travel,Business,795,4,4,4,1,3,4,3,3,3,4,4,3,5,3,0,0.0,satisfied +43097,342,Male,Loyal Customer,27,Personal Travel,Eco,821,2,4,2,2,3,2,3,3,3,5,5,5,4,3,0,12.0,neutral or dissatisfied +43098,49381,Female,Loyal Customer,41,Business travel,Eco,156,3,5,5,5,3,3,3,3,1,3,3,4,4,3,8,6.0,neutral or dissatisfied +43099,108350,Female,Loyal Customer,38,Business travel,Eco,1855,3,1,1,1,3,3,3,3,1,1,3,4,3,3,20,6.0,neutral or dissatisfied +43100,82296,Female,disloyal Customer,23,Business travel,Eco,986,3,3,3,4,5,3,4,5,4,4,3,4,3,5,5,0.0,neutral or dissatisfied +43101,96423,Male,Loyal Customer,49,Business travel,Eco Plus,942,2,5,5,5,2,2,2,2,3,4,4,2,3,2,39,26.0,neutral or dissatisfied +43102,111660,Female,disloyal Customer,30,Business travel,Business,991,1,1,1,4,3,1,3,3,2,5,4,4,4,3,14,16.0,neutral or dissatisfied +43103,124546,Female,disloyal Customer,13,Personal Travel,Eco,1276,4,3,4,3,5,4,5,5,5,2,3,1,5,5,39,26.0,neutral or dissatisfied +43104,84584,Male,Loyal Customer,48,Business travel,Business,707,2,4,2,2,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +43105,125494,Male,Loyal Customer,41,Business travel,Business,3472,5,5,5,5,5,5,5,4,4,4,4,5,4,3,0,16.0,satisfied +43106,119117,Male,Loyal Customer,55,Personal Travel,Eco,1107,3,3,3,1,1,3,1,1,2,2,2,1,4,1,0,0.0,neutral or dissatisfied +43107,62989,Female,Loyal Customer,57,Business travel,Business,2234,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +43108,1448,Male,Loyal Customer,51,Business travel,Business,695,4,4,4,4,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +43109,122860,Female,disloyal Customer,16,Business travel,Eco,226,1,3,1,3,2,1,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +43110,5250,Male,Loyal Customer,61,Business travel,Eco,351,2,1,1,1,2,2,2,2,4,5,3,2,3,2,5,10.0,neutral or dissatisfied +43111,45037,Female,Loyal Customer,54,Personal Travel,Eco,837,4,4,4,2,1,5,1,3,3,4,3,4,3,1,7,1.0,neutral or dissatisfied +43112,94895,Male,Loyal Customer,51,Business travel,Eco,192,4,4,3,3,4,4,4,4,1,2,3,3,4,4,0,0.0,satisfied +43113,105834,Female,Loyal Customer,26,Personal Travel,Eco,663,2,1,3,2,2,3,2,2,1,3,2,4,3,2,0,0.0,neutral or dissatisfied +43114,2876,Male,Loyal Customer,12,Personal Travel,Eco,409,2,5,2,4,2,2,2,2,4,2,5,5,4,2,35,43.0,neutral or dissatisfied +43115,80146,Male,Loyal Customer,58,Business travel,Business,2475,4,4,4,4,5,5,5,5,5,4,4,5,4,5,1,0.0,satisfied +43116,78164,Male,disloyal Customer,20,Business travel,Eco,259,4,0,4,3,3,4,3,3,5,4,4,3,5,3,14,7.0,satisfied +43117,115754,Male,Loyal Customer,43,Business travel,Eco,325,2,3,3,3,2,2,2,2,2,5,3,4,3,2,86,70.0,neutral or dissatisfied +43118,113060,Male,Loyal Customer,31,Business travel,Business,2978,2,2,2,2,5,5,5,5,4,3,5,5,4,5,5,0.0,satisfied +43119,87741,Male,Loyal Customer,42,Business travel,Business,214,0,5,0,1,3,3,3,3,5,5,5,3,3,3,221,217.0,satisfied +43120,29771,Male,Loyal Customer,60,Business travel,Business,3437,5,5,3,5,2,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +43121,62765,Male,disloyal Customer,22,Business travel,Eco,2556,4,4,4,3,4,4,4,3,4,4,4,4,4,4,0,10.0,neutral or dissatisfied +43122,46066,Male,Loyal Customer,54,Business travel,Business,3434,1,5,4,5,3,3,4,1,1,2,1,4,1,1,6,4.0,neutral or dissatisfied +43123,82587,Female,Loyal Customer,43,Business travel,Eco,528,3,2,2,2,5,4,3,3,3,3,3,4,3,1,87,88.0,neutral or dissatisfied +43124,53067,Male,Loyal Customer,14,Personal Travel,Eco,1208,5,1,4,2,3,4,3,3,1,2,3,3,2,3,0,0.0,satisfied +43125,27831,Female,Loyal Customer,66,Personal Travel,Eco,1533,3,4,3,3,4,4,4,1,1,3,1,4,1,5,5,0.0,neutral or dissatisfied +43126,121108,Female,Loyal Customer,68,Personal Travel,Business,2402,1,4,1,4,3,5,4,3,3,1,2,4,3,4,25,0.0,neutral or dissatisfied +43127,75919,Female,Loyal Customer,50,Personal Travel,Eco Plus,603,5,5,5,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +43128,114726,Male,Loyal Customer,51,Business travel,Business,3002,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +43129,101195,Male,Loyal Customer,28,Personal Travel,Eco,1069,3,4,3,4,1,3,1,1,3,5,3,2,1,1,0,0.0,neutral or dissatisfied +43130,79947,Male,disloyal Customer,18,Business travel,Eco,1010,1,1,1,4,3,1,3,3,2,4,3,1,4,3,60,99.0,neutral or dissatisfied +43131,54649,Male,disloyal Customer,44,Business travel,Eco,787,2,1,1,4,4,1,4,4,3,1,1,5,2,4,2,0.0,neutral or dissatisfied +43132,127499,Male,Loyal Customer,24,Personal Travel,Eco,2075,3,3,3,1,4,3,4,4,5,4,1,3,4,4,0,2.0,neutral or dissatisfied +43133,78083,Female,Loyal Customer,23,Business travel,Eco Plus,214,4,1,1,1,4,4,4,4,1,5,2,5,1,4,0,0.0,satisfied +43134,124919,Male,Loyal Customer,38,Business travel,Business,3369,4,4,4,4,3,1,5,4,4,4,4,5,4,4,0,0.0,satisfied +43135,106277,Female,Loyal Customer,35,Business travel,Business,3451,3,4,4,4,4,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +43136,32004,Female,Loyal Customer,19,Personal Travel,Business,216,1,0,1,3,3,1,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +43137,42353,Female,Loyal Customer,25,Personal Travel,Eco,550,2,4,2,2,5,2,5,5,5,3,3,4,5,5,0,0.0,neutral or dissatisfied +43138,10156,Female,disloyal Customer,31,Business travel,Eco,1195,1,1,1,3,1,3,3,1,5,3,3,3,4,3,145,155.0,neutral or dissatisfied +43139,43086,Female,Loyal Customer,28,Personal Travel,Eco,192,4,4,4,1,2,4,2,2,4,2,5,4,5,2,0,0.0,satisfied +43140,73617,Male,Loyal Customer,53,Business travel,Business,192,0,5,1,5,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +43141,36488,Female,Loyal Customer,36,Personal Travel,Business,1237,1,5,1,4,2,3,5,4,4,1,4,4,4,5,42,51.0,neutral or dissatisfied +43142,77698,Female,disloyal Customer,23,Business travel,Eco,731,2,2,2,2,5,2,4,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +43143,115189,Male,Loyal Customer,58,Business travel,Business,3484,0,0,0,3,5,4,5,4,4,4,4,3,4,5,0,3.0,satisfied +43144,74431,Female,disloyal Customer,60,Business travel,Business,1438,5,5,5,2,3,5,3,3,4,4,5,3,5,3,44,27.0,satisfied +43145,80979,Female,Loyal Customer,30,Business travel,Business,2882,4,4,4,4,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +43146,76973,Male,Loyal Customer,45,Business travel,Business,1969,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +43147,32130,Female,Loyal Customer,27,Business travel,Business,3533,4,4,4,4,5,5,4,5,1,4,1,4,3,5,0,0.0,satisfied +43148,26173,Male,Loyal Customer,54,Business travel,Business,2270,5,5,5,5,2,4,2,5,5,5,5,4,5,4,6,0.0,satisfied +43149,85956,Female,Loyal Customer,58,Business travel,Business,447,1,1,1,1,3,5,5,4,4,4,4,3,4,4,50,39.0,satisfied +43150,85174,Female,disloyal Customer,28,Business travel,Eco,696,3,3,3,4,1,3,1,1,2,5,4,4,3,1,5,0.0,neutral or dissatisfied +43151,44504,Female,Loyal Customer,30,Personal Travel,Eco,503,4,4,4,3,2,4,2,2,3,2,5,4,5,2,0,0.0,satisfied +43152,69108,Female,Loyal Customer,48,Personal Travel,Eco Plus,1389,2,3,2,3,5,4,1,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +43153,52328,Female,Loyal Customer,56,Business travel,Eco,370,3,1,3,1,3,3,2,3,3,3,3,3,3,3,0,3.0,neutral or dissatisfied +43154,75895,Female,Loyal Customer,15,Business travel,Business,2924,4,3,4,4,4,5,4,4,5,4,5,3,4,4,15,1.0,satisfied +43155,42922,Female,Loyal Customer,13,Personal Travel,Eco,628,4,4,4,4,3,4,3,3,5,5,4,4,5,3,0,7.0,satisfied +43156,69628,Female,Loyal Customer,56,Business travel,Business,1762,4,4,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +43157,69467,Female,Loyal Customer,48,Personal Travel,Eco,1089,3,5,3,4,4,5,1,3,3,3,5,3,3,5,0,0.0,neutral or dissatisfied +43158,94608,Female,Loyal Customer,57,Business travel,Business,2321,1,1,1,1,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +43159,47156,Male,Loyal Customer,25,Business travel,Business,908,4,4,5,4,5,5,5,5,3,4,4,1,5,5,0,0.0,satisfied +43160,81417,Female,Loyal Customer,41,Business travel,Business,2348,2,2,2,2,3,5,4,4,4,3,4,4,4,5,1,1.0,satisfied +43161,33915,Male,Loyal Customer,46,Business travel,Business,636,3,1,4,1,3,3,3,4,3,3,3,3,3,3,164,171.0,neutral or dissatisfied +43162,41661,Male,Loyal Customer,39,Business travel,Business,2537,2,2,2,2,1,1,3,4,4,4,4,1,4,4,0,0.0,satisfied +43163,112492,Male,Loyal Customer,53,Personal Travel,Eco,967,3,2,3,3,3,3,3,3,4,1,4,3,4,3,105,87.0,neutral or dissatisfied +43164,73685,Female,Loyal Customer,37,Business travel,Business,2005,4,1,1,1,2,3,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +43165,49386,Female,Loyal Customer,55,Business travel,Eco,373,5,1,1,1,5,3,1,4,4,5,4,4,4,1,5,6.0,satisfied +43166,48581,Female,Loyal Customer,62,Personal Travel,Eco,819,2,4,2,2,4,3,1,3,3,2,1,5,3,4,0,0.0,neutral or dissatisfied +43167,11067,Male,Loyal Customer,52,Personal Travel,Eco,312,2,5,2,5,2,2,2,2,4,3,4,3,5,2,0,22.0,neutral or dissatisfied +43168,118796,Female,Loyal Customer,51,Personal Travel,Eco,338,2,4,4,5,3,5,5,1,1,4,1,5,1,3,12,11.0,neutral or dissatisfied +43169,86885,Female,Loyal Customer,54,Personal Travel,Eco Plus,484,1,1,1,3,2,3,2,5,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +43170,75280,Male,Loyal Customer,27,Personal Travel,Eco,1744,0,5,0,2,4,0,4,4,3,3,5,4,4,4,0,0.0,satisfied +43171,69032,Male,disloyal Customer,39,Business travel,Business,1389,4,3,3,2,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +43172,104971,Male,disloyal Customer,44,Business travel,Business,406,5,5,5,1,3,5,5,3,5,3,4,5,4,3,0,0.0,satisfied +43173,4308,Male,Loyal Customer,58,Business travel,Business,1997,2,2,2,2,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +43174,126319,Male,Loyal Customer,12,Personal Travel,Eco,507,1,4,1,3,2,1,2,2,5,5,5,4,5,2,2,7.0,neutral or dissatisfied +43175,115962,Male,Loyal Customer,46,Personal Travel,Eco,362,2,4,2,4,5,2,5,5,3,2,5,4,4,5,112,109.0,neutral or dissatisfied +43176,2055,Female,Loyal Customer,50,Business travel,Business,2274,1,1,3,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +43177,43311,Male,Loyal Customer,38,Business travel,Eco,387,2,4,4,4,2,2,2,2,1,2,4,3,4,2,0,0.0,neutral or dissatisfied +43178,97337,Male,Loyal Customer,49,Business travel,Business,2245,2,2,3,2,3,5,5,5,5,5,5,5,5,5,34,39.0,satisfied +43179,99590,Male,Loyal Customer,58,Personal Travel,Eco,895,1,4,2,5,5,2,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +43180,16409,Male,disloyal Customer,23,Business travel,Eco,533,0,1,0,5,2,0,2,2,3,2,5,2,4,2,0,0.0,satisfied +43181,17261,Female,Loyal Customer,68,Personal Travel,Eco,872,2,4,2,3,4,3,3,5,5,2,3,4,5,1,0,0.0,neutral or dissatisfied +43182,76628,Female,Loyal Customer,56,Business travel,Eco,147,4,2,2,2,5,1,3,4,4,4,4,3,4,3,0,0.0,satisfied +43183,129502,Female,Loyal Customer,42,Business travel,Business,1744,3,3,3,3,2,4,5,4,4,4,4,4,4,3,5,0.0,satisfied +43184,93514,Male,Loyal Customer,33,Business travel,Eco Plus,1107,3,5,5,5,3,3,3,3,2,1,3,1,4,3,3,0.0,neutral or dissatisfied +43185,54098,Male,Loyal Customer,26,Business travel,Eco Plus,1416,0,4,0,5,5,4,5,5,3,2,3,1,2,5,0,0.0,satisfied +43186,111499,Male,Loyal Customer,25,Business travel,Business,3383,3,3,3,3,3,3,3,3,5,3,4,5,5,3,4,0.0,satisfied +43187,2673,Male,Loyal Customer,37,Personal Travel,Eco,597,2,0,2,3,4,2,5,4,4,3,5,4,5,4,55,43.0,neutral or dissatisfied +43188,84976,Female,Loyal Customer,32,Business travel,Business,1590,1,0,0,3,0,3,3,3,5,4,4,3,2,3,275,277.0,neutral or dissatisfied +43189,56650,Female,Loyal Customer,48,Business travel,Business,3231,2,2,2,2,3,3,5,4,4,4,4,3,4,4,0,3.0,satisfied +43190,126672,Male,Loyal Customer,46,Business travel,Business,2276,5,5,5,5,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +43191,92409,Female,Loyal Customer,40,Business travel,Business,2139,4,1,1,1,5,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +43192,48705,Female,Loyal Customer,55,Business travel,Business,2332,0,5,1,1,3,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +43193,75580,Female,disloyal Customer,22,Business travel,Eco,337,2,1,2,3,2,2,2,2,4,3,3,1,2,2,60,52.0,neutral or dissatisfied +43194,50426,Female,Loyal Customer,51,Business travel,Eco,89,5,3,1,3,5,4,1,5,5,5,5,4,5,3,0,0.0,satisfied +43195,10915,Male,Loyal Customer,26,Business travel,Business,201,1,2,5,5,1,1,1,1,4,2,3,2,3,1,44,52.0,neutral or dissatisfied +43196,31923,Female,disloyal Customer,21,Business travel,Eco,101,4,0,5,4,5,5,2,5,3,4,4,4,5,5,0,0.0,satisfied +43197,36776,Female,Loyal Customer,57,Business travel,Eco,2602,2,4,4,4,2,2,2,2,2,1,3,2,2,2,17,7.0,neutral or dissatisfied +43198,8211,Male,Loyal Customer,35,Business travel,Eco,530,2,1,2,1,2,2,2,2,4,1,3,4,3,2,0,10.0,neutral or dissatisfied +43199,113821,Female,Loyal Customer,52,Personal Travel,Eco Plus,197,5,5,5,3,5,4,5,3,3,5,3,3,3,5,6,1.0,satisfied +43200,61913,Female,disloyal Customer,34,Business travel,Business,550,2,2,2,3,3,2,3,3,3,4,4,5,5,3,2,0.0,neutral or dissatisfied +43201,119654,Female,Loyal Customer,51,Business travel,Business,2574,2,2,2,2,3,4,4,2,2,3,2,4,2,4,0,0.0,satisfied +43202,4925,Male,Loyal Customer,51,Personal Travel,Eco,1020,2,3,2,5,5,2,3,5,5,3,5,2,2,5,0,0.0,neutral or dissatisfied +43203,86177,Male,disloyal Customer,39,Business travel,Business,356,3,2,2,2,2,2,1,2,3,4,3,1,2,2,0,0.0,neutral or dissatisfied +43204,29350,Female,Loyal Customer,52,Personal Travel,Eco,2588,1,3,1,3,5,4,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +43205,44645,Male,Loyal Customer,48,Business travel,Business,2590,1,1,4,1,2,5,1,3,3,4,5,1,3,4,0,0.0,satisfied +43206,13185,Male,Loyal Customer,32,Business travel,Business,1906,3,3,3,3,3,4,3,3,2,3,4,4,5,3,5,0.0,satisfied +43207,115244,Female,Loyal Customer,40,Business travel,Business,342,2,2,2,2,4,5,4,4,4,4,4,5,4,3,48,50.0,satisfied +43208,35504,Female,Loyal Customer,21,Personal Travel,Eco,1118,1,4,1,1,1,5,5,4,3,4,4,5,4,5,238,241.0,neutral or dissatisfied +43209,75886,Male,disloyal Customer,22,Business travel,Eco,603,3,5,3,3,5,3,5,5,4,5,4,4,5,5,6,12.0,neutral or dissatisfied +43210,58739,Male,Loyal Customer,57,Business travel,Business,2943,1,1,1,1,3,4,5,4,4,4,4,5,4,4,6,0.0,satisfied +43211,108788,Female,Loyal Customer,49,Business travel,Business,1731,1,1,1,1,5,5,5,5,5,5,5,5,5,4,21,18.0,satisfied +43212,23593,Female,Loyal Customer,66,Personal Travel,Eco,1024,2,5,2,1,4,5,5,5,5,2,5,3,5,3,8,0.0,neutral or dissatisfied +43213,8074,Female,Loyal Customer,59,Business travel,Business,3861,0,5,0,1,2,5,4,1,1,1,1,5,1,3,0,0.0,satisfied +43214,88850,Male,Loyal Customer,45,Personal Travel,Eco Plus,581,4,5,4,4,3,4,3,3,4,2,5,3,4,3,24,26.0,neutral or dissatisfied +43215,107922,Male,Loyal Customer,50,Business travel,Business,2920,3,3,3,3,2,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +43216,49532,Male,Loyal Customer,22,Business travel,Eco,199,4,4,4,4,4,4,5,4,4,3,3,3,5,4,0,0.0,satisfied +43217,11866,Female,Loyal Customer,48,Business travel,Business,1042,2,2,2,2,5,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +43218,10977,Female,disloyal Customer,42,Business travel,Eco,224,4,5,3,3,3,3,3,3,4,2,4,4,2,3,10,0.0,neutral or dissatisfied +43219,52185,Male,disloyal Customer,23,Business travel,Eco,261,5,4,5,2,2,5,2,2,2,5,1,1,5,2,0,0.0,satisfied +43220,85564,Female,Loyal Customer,55,Business travel,Eco,153,3,5,5,5,5,2,2,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +43221,27741,Female,Loyal Customer,43,Business travel,Eco,1448,4,3,5,3,4,2,2,4,4,4,4,5,4,5,0,0.0,satisfied +43222,74059,Male,disloyal Customer,54,Business travel,Eco,1027,1,1,1,4,1,2,2,3,2,4,3,2,1,2,0,6.0,neutral or dissatisfied +43223,100991,Male,disloyal Customer,23,Business travel,Business,564,5,0,5,4,4,5,4,4,5,2,5,4,5,4,3,0.0,satisfied +43224,23153,Male,disloyal Customer,20,Business travel,Business,223,5,3,5,3,5,5,5,5,4,1,5,5,2,5,6,0.0,satisfied +43225,87503,Female,disloyal Customer,41,Business travel,Business,321,1,1,1,1,5,3,5,5,3,5,1,5,5,5,0,0.0,neutral or dissatisfied +43226,24958,Female,Loyal Customer,51,Business travel,Business,2013,4,4,4,4,2,3,3,5,5,4,5,2,5,4,60,59.0,satisfied +43227,92220,Male,Loyal Customer,28,Personal Travel,Eco,1956,3,1,3,2,3,3,2,3,3,2,3,3,2,3,0,0.0,neutral or dissatisfied +43228,107708,Male,Loyal Customer,38,Business travel,Business,405,2,1,1,1,4,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +43229,95701,Female,Loyal Customer,61,Business travel,Business,3925,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,1.0,satisfied +43230,50709,Male,Loyal Customer,15,Personal Travel,Eco,262,2,2,2,3,1,2,1,1,1,1,3,3,3,1,7,15.0,neutral or dissatisfied +43231,59628,Male,Loyal Customer,56,Business travel,Eco,854,2,4,4,4,2,2,2,2,2,1,3,1,3,2,2,5.0,neutral or dissatisfied +43232,124805,Female,disloyal Customer,48,Business travel,Eco,280,4,4,4,4,3,4,2,3,3,2,3,1,4,3,0,16.0,neutral or dissatisfied +43233,99786,Female,Loyal Customer,52,Business travel,Business,2685,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,2.0,satisfied +43234,13591,Male,Loyal Customer,47,Personal Travel,Eco,227,3,1,3,2,5,3,5,5,2,2,2,3,3,5,0,4.0,neutral or dissatisfied +43235,19681,Female,Loyal Customer,57,Business travel,Eco,409,5,3,2,3,5,5,5,5,3,5,4,5,2,5,179,168.0,satisfied +43236,81364,Female,Loyal Customer,35,Business travel,Eco Plus,1299,5,4,4,4,5,5,5,5,1,5,4,1,5,5,0,9.0,satisfied +43237,46625,Male,Loyal Customer,60,Business travel,Business,141,2,1,4,1,4,2,2,3,3,3,2,2,3,3,0,6.0,neutral or dissatisfied +43238,35441,Male,Loyal Customer,21,Personal Travel,Eco,828,2,4,1,4,4,1,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +43239,72717,Male,Loyal Customer,22,Business travel,Business,1102,2,2,2,2,4,4,4,5,5,5,4,4,4,4,279,253.0,satisfied +43240,126763,Male,Loyal Customer,32,Personal Travel,Eco,2402,3,4,3,1,2,3,2,2,2,2,2,1,1,2,0,6.0,neutral or dissatisfied +43241,34642,Male,Loyal Customer,7,Personal Travel,Eco,427,5,0,4,1,2,4,5,2,3,4,4,4,4,2,0,0.0,satisfied +43242,113646,Male,Loyal Customer,64,Personal Travel,Eco,226,2,1,2,3,2,2,2,2,4,4,3,2,4,2,57,57.0,neutral or dissatisfied +43243,37951,Male,Loyal Customer,29,Personal Travel,Eco Plus,997,1,5,1,2,3,1,3,3,3,3,4,3,4,3,15,3.0,neutral or dissatisfied +43244,115459,Female,Loyal Customer,80,Business travel,Business,2612,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,3.0,satisfied +43245,48534,Male,Loyal Customer,35,Business travel,Eco,819,4,5,5,5,4,4,4,4,5,3,4,4,3,4,0,0.0,satisfied +43246,96526,Male,Loyal Customer,63,Personal Travel,Eco,436,3,5,3,3,1,3,1,1,5,2,5,3,4,1,64,,neutral or dissatisfied +43247,43355,Male,disloyal Customer,24,Business travel,Eco,463,2,2,2,3,4,2,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +43248,62351,Male,Loyal Customer,57,Business travel,Business,1735,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +43249,4483,Male,Loyal Customer,62,Personal Travel,Eco,1147,1,4,1,4,4,1,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +43250,28975,Male,Loyal Customer,24,Business travel,Business,954,1,4,4,4,1,2,1,1,4,1,2,4,2,1,0,8.0,neutral or dissatisfied +43251,18894,Male,disloyal Customer,39,Business travel,Eco,448,3,0,4,4,5,4,5,5,5,2,5,1,4,5,0,4.0,neutral or dissatisfied +43252,112821,Male,disloyal Customer,25,Business travel,Eco,1313,4,4,4,4,2,4,2,2,3,2,5,5,5,2,30,23.0,satisfied +43253,117643,Male,Loyal Customer,36,Personal Travel,Eco,872,1,3,0,3,5,0,5,5,2,1,4,3,3,5,3,0.0,neutral or dissatisfied +43254,67971,Male,Loyal Customer,33,Business travel,Eco Plus,1431,2,2,2,2,2,2,2,2,4,3,2,1,2,2,28,19.0,neutral or dissatisfied +43255,120768,Female,disloyal Customer,30,Business travel,Eco,678,2,2,2,3,4,2,4,4,1,2,4,1,4,4,0,2.0,neutral or dissatisfied +43256,120540,Female,Loyal Customer,39,Business travel,Business,2176,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,15.0,satisfied +43257,36530,Male,disloyal Customer,29,Business travel,Eco,1249,3,3,3,3,2,3,2,2,1,1,3,3,4,2,0,9.0,neutral or dissatisfied +43258,6798,Male,Loyal Customer,67,Business travel,Business,3462,4,3,3,3,2,3,3,4,4,3,4,2,4,2,7,6.0,neutral or dissatisfied +43259,5628,Male,Loyal Customer,59,Business travel,Business,1919,3,3,3,3,2,5,5,2,2,2,2,5,2,5,34,33.0,satisfied +43260,34165,Female,Loyal Customer,58,Business travel,Eco,1046,3,2,2,2,1,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +43261,81394,Male,Loyal Customer,65,Personal Travel,Eco,748,0,4,0,1,3,0,3,3,3,2,5,4,5,3,5,0.0,satisfied +43262,20632,Male,Loyal Customer,30,Business travel,Business,1549,3,3,3,3,5,5,5,5,5,2,2,5,3,5,600,589.0,satisfied +43263,68296,Male,Loyal Customer,34,Business travel,Business,1797,4,4,3,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +43264,115614,Male,Loyal Customer,36,Business travel,Business,2896,4,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +43265,22547,Female,disloyal Customer,39,Business travel,Business,300,4,4,4,3,1,4,1,1,3,3,4,4,5,1,0,8.0,satisfied +43266,89662,Female,Loyal Customer,25,Business travel,Business,944,2,4,2,2,4,4,4,4,4,2,5,5,4,4,18,3.0,satisfied +43267,111148,Male,Loyal Customer,23,Business travel,Eco,780,4,5,5,5,4,4,5,4,3,1,1,3,1,4,0,0.0,satisfied +43268,36306,Male,Loyal Customer,40,Business travel,Eco,187,4,1,4,1,4,4,4,4,2,1,4,3,5,4,1,37.0,satisfied +43269,1766,Male,Loyal Customer,26,Business travel,Business,2328,3,1,5,1,3,3,3,3,2,3,4,4,3,3,0,15.0,neutral or dissatisfied +43270,29314,Female,Loyal Customer,45,Personal Travel,Eco,873,1,1,1,3,3,3,3,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +43271,82580,Male,disloyal Customer,23,Business travel,Eco,528,4,2,4,3,3,4,4,3,3,4,5,4,4,3,0,0.0,satisfied +43272,83253,Female,disloyal Customer,20,Business travel,Business,1444,4,0,4,1,5,4,5,5,3,3,4,5,5,5,5,0.0,satisfied +43273,115036,Female,Loyal Customer,54,Business travel,Business,373,3,2,3,3,2,2,2,4,2,5,4,2,3,2,132,131.0,satisfied +43274,92326,Male,Loyal Customer,41,Business travel,Business,2486,3,3,2,3,4,3,3,4,4,3,4,3,5,3,0,9.0,satisfied +43275,51157,Male,Loyal Customer,70,Personal Travel,Eco,86,1,1,1,3,1,1,1,1,2,2,3,4,2,1,0,0.0,neutral or dissatisfied +43276,108609,Male,Loyal Customer,51,Business travel,Eco,296,4,3,3,3,4,4,4,4,5,5,5,2,2,4,20,0.0,satisfied +43277,113106,Male,Loyal Customer,32,Personal Travel,Eco,569,2,4,2,3,5,2,2,5,2,5,4,2,2,5,46,34.0,neutral or dissatisfied +43278,108307,Female,Loyal Customer,59,Business travel,Business,1838,4,4,4,4,5,4,5,4,4,4,4,4,4,4,33,44.0,satisfied +43279,74890,Female,disloyal Customer,53,Personal Travel,Business,2475,4,5,4,1,1,4,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +43280,117188,Male,Loyal Customer,32,Personal Travel,Eco,370,3,4,3,4,4,3,4,4,2,1,2,3,3,4,0,0.0,neutral or dissatisfied +43281,66177,Female,disloyal Customer,27,Business travel,Business,460,0,0,0,2,5,0,5,5,4,4,5,3,4,5,0,0.0,satisfied +43282,28303,Female,Loyal Customer,38,Business travel,Business,954,2,2,2,2,2,3,1,4,4,4,4,2,4,4,3,0.0,satisfied +43283,117862,Male,Loyal Customer,45,Business travel,Business,365,5,5,5,5,5,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +43284,77219,Male,Loyal Customer,39,Business travel,Business,1590,2,2,2,2,3,4,4,1,1,2,1,4,1,4,0,0.0,satisfied +43285,78828,Female,Loyal Customer,25,Personal Travel,Eco,432,4,5,4,3,4,4,4,4,4,2,4,4,5,4,0,11.0,neutral or dissatisfied +43286,103893,Female,Loyal Customer,43,Business travel,Business,3466,1,1,1,1,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +43287,46806,Female,disloyal Customer,24,Business travel,Eco,853,4,4,4,5,2,4,2,2,1,4,2,3,3,2,2,4.0,neutral or dissatisfied +43288,56584,Female,Loyal Customer,46,Business travel,Business,2827,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +43289,127475,Female,disloyal Customer,24,Business travel,Eco,867,1,1,1,2,4,1,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +43290,82282,Male,Loyal Customer,19,Personal Travel,Eco,1481,5,2,5,3,5,5,5,5,4,1,4,1,3,5,6,0.0,satisfied +43291,30266,Female,Loyal Customer,58,Business travel,Business,2356,3,3,3,3,3,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +43292,9608,Male,Loyal Customer,22,Personal Travel,Eco,229,2,4,2,4,3,2,5,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +43293,91427,Male,Loyal Customer,40,Personal Travel,Eco,549,2,2,2,3,1,2,1,1,2,4,1,4,3,1,0,0.0,neutral or dissatisfied +43294,31586,Male,Loyal Customer,37,Business travel,Business,3771,1,1,1,1,3,3,1,2,2,2,2,5,2,5,1,31.0,satisfied +43295,35415,Female,disloyal Customer,25,Business travel,Eco,1097,2,2,2,4,2,2,3,2,3,3,4,2,3,2,0,9.0,neutral or dissatisfied +43296,4684,Male,Loyal Customer,9,Personal Travel,Eco,489,2,3,3,4,5,3,5,5,5,5,3,3,3,5,0,0.0,neutral or dissatisfied +43297,14202,Male,Loyal Customer,30,Business travel,Eco,692,2,1,1,1,2,2,2,2,4,5,3,4,4,2,2,23.0,neutral or dissatisfied +43298,89692,Male,Loyal Customer,64,Business travel,Business,3767,1,1,1,1,3,5,5,5,5,5,5,1,5,2,21,0.0,satisfied +43299,16841,Male,Loyal Customer,12,Personal Travel,Eco,645,4,5,4,5,2,4,2,2,5,3,5,3,4,2,2,23.0,neutral or dissatisfied +43300,70637,Female,Loyal Customer,34,Business travel,Eco,946,4,3,3,3,4,4,4,4,4,5,3,2,4,4,12,0.0,neutral or dissatisfied +43301,65439,Female,Loyal Customer,55,Business travel,Business,1792,1,1,1,1,3,5,4,5,5,5,5,5,5,4,0,11.0,satisfied +43302,116975,Male,Loyal Customer,51,Business travel,Business,325,0,0,0,4,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +43303,42623,Male,Loyal Customer,40,Business travel,Business,1813,4,4,1,4,1,4,5,3,3,2,3,3,3,3,25,63.0,satisfied +43304,10634,Male,Loyal Customer,27,Business travel,Eco,74,3,3,4,4,3,2,3,3,3,4,4,2,4,3,60,56.0,neutral or dissatisfied +43305,33952,Male,Loyal Customer,34,Business travel,Eco Plus,1188,2,5,5,5,2,2,2,2,1,4,4,1,4,2,34,29.0,neutral or dissatisfied +43306,129561,Female,Loyal Customer,31,Personal Travel,Eco,2583,3,2,3,3,4,3,4,4,2,3,1,4,2,4,0,0.0,neutral or dissatisfied +43307,60081,Female,Loyal Customer,45,Business travel,Business,1005,1,1,1,1,5,5,4,5,5,5,5,4,5,3,14,14.0,satisfied +43308,108982,Male,Loyal Customer,47,Personal Travel,Business,781,3,2,3,3,1,3,3,4,4,3,4,3,4,1,24,21.0,neutral or dissatisfied +43309,110140,Female,disloyal Customer,47,Business travel,Business,890,5,5,5,5,5,5,5,4,3,5,5,5,3,5,132,124.0,satisfied +43310,101246,Female,Loyal Customer,44,Personal Travel,Eco,1587,1,4,0,2,5,5,5,1,1,0,1,4,1,5,21,4.0,neutral or dissatisfied +43311,11841,Male,Loyal Customer,57,Business travel,Business,3470,5,5,5,5,3,5,5,4,4,4,4,4,4,4,8,2.0,satisfied +43312,62026,Male,Loyal Customer,29,Business travel,Business,2475,3,3,3,3,3,4,3,3,3,2,3,3,4,3,0,0.0,satisfied +43313,74597,Female,Loyal Customer,44,Business travel,Business,3847,2,2,5,2,3,4,4,2,2,2,2,4,2,5,8,0.0,satisfied +43314,82363,Male,Loyal Customer,54,Personal Travel,Eco,453,5,4,5,5,1,5,1,1,3,3,4,5,4,1,2,0.0,satisfied +43315,104881,Male,Loyal Customer,37,Personal Travel,Eco,327,2,0,2,4,5,2,5,5,3,5,5,5,4,5,10,0.0,neutral or dissatisfied +43316,70723,Male,Loyal Customer,50,Business travel,Business,1613,2,4,4,4,3,4,3,2,2,2,2,3,2,4,43,65.0,neutral or dissatisfied +43317,118666,Male,Loyal Customer,45,Business travel,Business,3335,4,2,4,4,3,4,3,4,4,4,4,1,4,4,6,0.0,satisfied +43318,85135,Female,Loyal Customer,43,Business travel,Business,696,2,2,2,2,3,5,4,2,2,2,2,4,2,5,0,9.0,satisfied +43319,124897,Female,Loyal Customer,27,Business travel,Business,1842,4,4,4,4,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +43320,1181,Male,Loyal Customer,48,Personal Travel,Eco,113,2,5,2,4,1,2,1,1,2,5,2,3,5,1,0,0.0,neutral or dissatisfied +43321,55593,Female,Loyal Customer,44,Business travel,Business,3466,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +43322,72010,Male,Loyal Customer,39,Personal Travel,Eco Plus,1440,2,5,2,3,2,3,2,3,5,4,4,2,5,2,296,301.0,neutral or dissatisfied +43323,2509,Female,Loyal Customer,51,Business travel,Business,3228,2,1,1,1,3,4,4,2,2,2,2,2,2,2,8,3.0,neutral or dissatisfied +43324,129770,Female,Loyal Customer,20,Personal Travel,Eco,308,4,5,4,2,2,4,2,2,4,2,1,1,3,2,0,0.0,neutral or dissatisfied +43325,115163,Female,Loyal Customer,47,Business travel,Business,447,5,5,5,5,4,5,5,4,4,3,4,3,4,4,31,12.0,satisfied +43326,28808,Female,disloyal Customer,25,Business travel,Eco,978,5,5,5,1,4,5,4,4,4,5,3,1,2,4,45,52.0,satisfied +43327,7456,Male,Loyal Customer,56,Business travel,Business,3063,2,5,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +43328,56829,Male,Loyal Customer,13,Personal Travel,Eco,1605,1,5,0,1,4,0,4,4,4,3,3,4,4,4,0,7.0,neutral or dissatisfied +43329,62139,Female,disloyal Customer,28,Business travel,Eco,1492,3,3,3,3,1,3,1,1,2,1,1,1,3,1,6,0.0,neutral or dissatisfied +43330,125122,Male,Loyal Customer,7,Personal Travel,Eco,361,4,4,4,2,2,4,2,2,3,5,5,5,4,2,24,46.0,neutral or dissatisfied +43331,64196,Female,Loyal Customer,59,Business travel,Business,853,1,1,2,1,2,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +43332,126092,Female,disloyal Customer,17,Business travel,Eco,507,0,0,0,3,2,0,2,2,4,3,5,4,4,2,1,0.0,satisfied +43333,54204,Female,Loyal Customer,34,Personal Travel,Eco,1400,3,4,3,1,2,3,2,2,2,2,3,2,2,2,0,0.0,neutral or dissatisfied +43334,99224,Male,Loyal Customer,38,Business travel,Business,495,1,1,1,1,3,4,4,5,5,5,5,5,5,3,11,10.0,satisfied +43335,9135,Female,disloyal Customer,30,Business travel,Eco,826,3,3,3,4,2,3,1,2,2,4,4,3,4,2,1,0.0,neutral or dissatisfied +43336,121013,Male,Loyal Customer,30,Personal Travel,Eco,861,1,4,1,2,4,1,1,4,5,3,4,4,5,4,0,14.0,neutral or dissatisfied +43337,75846,Male,Loyal Customer,51,Business travel,Business,1440,1,4,1,1,5,5,4,5,5,5,5,4,5,5,15,5.0,satisfied +43338,108651,Female,Loyal Customer,47,Business travel,Business,1747,4,4,4,4,4,5,5,5,5,5,5,4,5,5,29,34.0,satisfied +43339,18788,Male,Loyal Customer,42,Business travel,Eco,448,5,3,3,3,4,5,4,4,3,1,5,5,5,4,0,0.0,satisfied +43340,121364,Male,Loyal Customer,21,Personal Travel,Eco,1670,1,0,1,5,5,1,5,5,3,3,4,5,5,5,0,29.0,neutral or dissatisfied +43341,59663,Male,Loyal Customer,7,Personal Travel,Eco,965,2,5,2,3,3,2,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +43342,6403,Male,Loyal Customer,55,Personal Travel,Eco,315,3,3,3,2,5,3,5,5,4,4,3,3,2,5,0,25.0,neutral or dissatisfied +43343,28840,Male,Loyal Customer,40,Business travel,Eco,978,3,4,3,4,3,4,3,3,2,4,2,1,2,3,11,11.0,satisfied +43344,54029,Male,Loyal Customer,12,Personal Travel,Eco Plus,1091,3,2,3,4,4,3,4,4,2,3,3,3,4,4,80,83.0,neutral or dissatisfied +43345,56023,Female,Loyal Customer,48,Business travel,Business,2475,3,3,3,3,5,5,5,5,5,5,5,5,4,5,2,0.0,satisfied +43346,106254,Female,Loyal Customer,29,Personal Travel,Business,1500,2,4,2,3,2,2,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +43347,17120,Female,Loyal Customer,14,Personal Travel,Eco,821,1,4,1,3,3,1,3,3,4,4,4,5,4,3,10,0.0,neutral or dissatisfied +43348,101425,Female,Loyal Customer,51,Business travel,Business,3783,4,4,4,4,2,4,5,4,4,4,4,5,4,5,25,22.0,satisfied +43349,39291,Female,Loyal Customer,46,Personal Travel,Eco,268,3,1,3,4,5,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +43350,38594,Male,Loyal Customer,31,Business travel,Business,231,1,1,1,1,5,5,5,5,2,1,3,2,3,5,0,0.0,satisfied +43351,63055,Male,Loyal Customer,35,Personal Travel,Eco,776,2,5,2,3,2,2,4,2,5,4,5,3,4,2,12,0.0,neutral or dissatisfied +43352,93470,Male,Loyal Customer,32,Business travel,Business,605,2,2,3,2,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +43353,89495,Male,Loyal Customer,40,Business travel,Business,2890,3,3,3,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +43354,32771,Male,disloyal Customer,16,Business travel,Eco,216,5,0,5,2,4,5,4,4,4,2,4,4,1,4,0,0.0,satisfied +43355,105934,Female,Loyal Customer,48,Business travel,Business,1491,5,5,5,5,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +43356,89271,Male,Loyal Customer,49,Business travel,Business,3635,5,5,3,5,4,3,3,5,4,4,4,3,5,3,166,159.0,satisfied +43357,66967,Female,Loyal Customer,48,Business travel,Business,2102,4,4,4,4,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +43358,86609,Male,disloyal Customer,25,Business travel,Business,746,4,3,4,2,1,4,1,1,3,5,4,5,5,1,2,0.0,satisfied +43359,66474,Male,Loyal Customer,58,Personal Travel,Business,447,3,2,3,4,2,3,4,3,3,3,5,3,3,3,38,37.0,neutral or dissatisfied +43360,88879,Female,Loyal Customer,56,Business travel,Business,2738,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,1.0,satisfied +43361,111160,Female,Loyal Customer,41,Personal Travel,Eco,1180,4,4,4,4,5,4,5,5,3,2,3,5,5,5,0,0.0,neutral or dissatisfied +43362,69842,Female,Loyal Customer,37,Personal Travel,Eco,1055,1,5,1,3,3,1,3,3,5,3,4,5,5,3,8,0.0,neutral or dissatisfied +43363,117666,Male,disloyal Customer,16,Business travel,Eco,1449,2,2,2,4,4,2,4,4,1,5,3,4,3,4,21,28.0,neutral or dissatisfied +43364,71726,Female,Loyal Customer,10,Personal Travel,Eco,1007,3,5,3,4,2,3,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +43365,58449,Male,Loyal Customer,16,Personal Travel,Eco,733,2,3,2,3,5,2,5,5,2,4,4,1,3,5,8,0.0,neutral or dissatisfied +43366,64569,Male,disloyal Customer,37,Business travel,Business,282,3,3,3,3,4,3,3,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +43367,74878,Female,Loyal Customer,40,Business travel,Business,2475,4,4,4,4,2,4,5,5,5,5,5,5,5,3,27,0.0,satisfied +43368,54974,Male,disloyal Customer,49,Business travel,Business,1379,5,4,4,4,5,5,5,5,4,4,4,5,5,5,19,13.0,satisfied +43369,20483,Female,Loyal Customer,58,Business travel,Business,139,4,4,4,4,1,1,4,4,4,4,4,4,4,3,24,23.0,satisfied +43370,61595,Male,Loyal Customer,45,Business travel,Business,3055,2,2,2,2,5,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +43371,112507,Male,Loyal Customer,57,Personal Travel,Eco,948,2,0,2,3,4,2,4,4,5,4,5,4,4,4,3,4.0,neutral or dissatisfied +43372,95883,Female,disloyal Customer,39,Business travel,Eco,180,2,3,2,3,3,2,3,3,4,5,4,1,3,3,4,0.0,neutral or dissatisfied +43373,64836,Female,Loyal Customer,67,Business travel,Business,469,3,4,2,2,3,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +43374,107852,Male,Loyal Customer,39,Business travel,Business,2274,2,2,2,2,5,5,5,4,4,4,4,4,4,3,8,17.0,satisfied +43375,32213,Male,Loyal Customer,46,Business travel,Business,4000,3,3,3,3,4,2,1,4,4,4,4,3,4,4,9,20.0,satisfied +43376,35905,Male,Loyal Customer,41,Business travel,Business,2248,1,1,1,1,4,4,4,4,4,4,4,5,4,4,12,0.0,satisfied +43377,120513,Female,Loyal Customer,63,Personal Travel,Eco Plus,449,1,2,1,4,1,3,4,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +43378,31908,Male,disloyal Customer,27,Business travel,Business,163,4,4,4,4,5,4,4,5,5,3,5,5,5,5,4,5.0,satisfied +43379,120609,Female,Loyal Customer,52,Business travel,Business,453,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,60.0,satisfied +43380,36030,Male,Loyal Customer,34,Business travel,Business,2881,4,4,4,4,4,3,3,2,1,4,4,3,3,3,454,502.0,satisfied +43381,107546,Male,disloyal Customer,44,Business travel,Business,1521,3,3,3,2,3,3,3,3,4,5,5,3,5,3,54,50.0,neutral or dissatisfied +43382,54804,Female,disloyal Customer,23,Business travel,Eco,775,2,2,2,1,5,2,5,5,3,3,2,5,1,5,0,0.0,neutral or dissatisfied +43383,101996,Male,Loyal Customer,35,Personal Travel,Eco,628,4,5,4,2,5,4,3,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +43384,36211,Male,Loyal Customer,38,Business travel,Business,2916,3,3,3,3,2,1,4,5,5,5,5,4,5,3,0,0.0,satisfied +43385,57388,Female,disloyal Customer,23,Business travel,Business,472,1,3,1,4,5,1,5,5,3,1,3,1,4,5,3,0.0,neutral or dissatisfied +43386,35684,Female,Loyal Customer,58,Business travel,Business,2586,2,2,2,2,5,5,5,1,3,5,1,5,5,5,2,0.0,satisfied +43387,97217,Female,disloyal Customer,21,Business travel,Eco,1390,3,3,3,4,4,3,4,4,1,3,3,4,4,4,14,0.0,neutral or dissatisfied +43388,23121,Female,disloyal Customer,42,Business travel,Eco,223,4,0,4,4,4,4,3,4,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +43389,93704,Male,Loyal Customer,28,Business travel,Business,2015,1,4,1,1,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +43390,11647,Male,disloyal Customer,29,Business travel,Business,878,3,4,4,5,2,4,3,2,3,2,4,3,5,2,36,30.0,neutral or dissatisfied +43391,30866,Female,Loyal Customer,52,Business travel,Eco,1506,5,1,2,1,2,3,4,5,5,5,5,4,5,1,0,0.0,satisfied +43392,77885,Female,Loyal Customer,40,Personal Travel,Eco,700,2,5,1,3,2,1,2,2,3,4,4,3,5,2,88,99.0,neutral or dissatisfied +43393,98211,Male,Loyal Customer,67,Personal Travel,Business,842,1,3,1,4,3,4,3,1,1,1,3,2,1,4,24,8.0,neutral or dissatisfied +43394,109945,Female,Loyal Customer,47,Personal Travel,Eco,1204,1,1,1,3,1,4,3,2,2,1,1,2,2,3,0,0.0,neutral or dissatisfied +43395,46763,Male,Loyal Customer,48,Business travel,Eco Plus,125,2,4,4,4,2,2,2,2,1,1,4,4,4,2,0,16.0,neutral or dissatisfied +43396,105571,Female,Loyal Customer,45,Business travel,Business,1572,1,1,1,1,4,4,4,5,5,4,5,4,5,5,6,0.0,satisfied +43397,45208,Male,Loyal Customer,72,Business travel,Eco,1013,4,5,5,5,4,4,4,4,5,3,1,4,2,4,0,4.0,satisfied +43398,80734,Male,Loyal Customer,22,Business travel,Business,393,3,5,5,5,3,3,3,3,1,1,3,2,3,3,0,16.0,neutral or dissatisfied +43399,104370,Male,Loyal Customer,60,Business travel,Business,228,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +43400,35785,Male,Loyal Customer,46,Personal Travel,Eco,200,2,1,2,2,2,1,1,1,3,2,2,1,3,1,142,152.0,neutral or dissatisfied +43401,3635,Female,Loyal Customer,55,Business travel,Business,427,2,2,2,2,3,4,4,4,4,4,4,5,4,3,48,46.0,satisfied +43402,2690,Female,Loyal Customer,51,Business travel,Business,3555,4,4,4,4,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +43403,14429,Male,Loyal Customer,48,Personal Travel,Eco Plus,585,3,4,3,4,1,3,1,1,3,1,4,1,4,1,21,24.0,neutral or dissatisfied +43404,9118,Female,Loyal Customer,53,Business travel,Eco,707,2,1,1,1,2,2,2,3,4,4,4,2,3,2,157,183.0,neutral or dissatisfied +43405,102929,Female,Loyal Customer,33,Personal Travel,Eco,317,3,4,3,2,4,3,4,4,5,3,1,1,1,4,0,0.0,neutral or dissatisfied +43406,91260,Male,Loyal Customer,30,Personal Travel,Eco,581,4,4,4,5,3,4,3,3,4,4,5,5,4,3,2,0.0,neutral or dissatisfied +43407,10638,Female,Loyal Customer,59,Business travel,Business,312,3,3,3,3,3,4,5,3,3,4,3,3,3,4,8,9.0,satisfied +43408,12056,Female,Loyal Customer,27,Personal Travel,Eco,351,2,4,2,4,4,2,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +43409,71255,Male,disloyal Customer,20,Business travel,Eco,733,2,2,2,3,2,2,2,2,2,1,4,2,4,2,23,31.0,neutral or dissatisfied +43410,91246,Female,Loyal Customer,46,Personal Travel,Eco,581,2,5,2,2,5,5,4,2,2,2,2,3,2,5,2,1.0,neutral or dissatisfied +43411,95471,Male,Loyal Customer,46,Business travel,Business,1727,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +43412,33617,Male,Loyal Customer,57,Business travel,Eco,399,4,3,2,3,5,4,5,5,5,4,5,1,3,5,0,0.0,satisfied +43413,34477,Male,Loyal Customer,53,Business travel,Business,266,3,3,4,3,1,4,3,3,3,3,3,2,3,4,0,8.0,neutral or dissatisfied +43414,27893,Male,Loyal Customer,60,Personal Travel,Eco,2329,2,5,2,1,2,1,1,5,2,4,5,1,3,1,0,0.0,neutral or dissatisfied +43415,17796,Male,disloyal Customer,23,Business travel,Business,1075,2,2,2,3,3,2,3,3,1,5,3,3,3,3,5,0.0,neutral or dissatisfied +43416,94683,Female,Loyal Customer,36,Business travel,Business,3237,3,3,3,3,4,5,4,5,5,5,5,3,5,4,12,1.0,satisfied +43417,49525,Male,Loyal Customer,47,Business travel,Business,2827,0,5,1,1,2,3,4,4,4,5,5,5,4,5,0,3.0,satisfied +43418,14355,Male,Loyal Customer,68,Business travel,Eco Plus,395,2,2,2,2,2,2,2,2,1,1,3,3,3,2,34,24.0,neutral or dissatisfied +43419,96454,Female,Loyal Customer,52,Business travel,Business,2381,5,5,5,5,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +43420,28436,Male,Loyal Customer,44,Business travel,Eco,2496,3,5,5,5,3,3,3,2,4,1,3,3,1,3,0,17.0,neutral or dissatisfied +43421,95770,Female,Loyal Customer,54,Personal Travel,Eco,453,2,4,2,3,2,5,4,5,5,2,2,4,5,5,6,0.0,neutral or dissatisfied +43422,64067,Male,Loyal Customer,47,Business travel,Business,919,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +43423,112841,Female,Loyal Customer,43,Business travel,Business,1476,5,5,5,5,3,5,4,5,5,5,5,3,5,4,14,0.0,satisfied +43424,64020,Male,Loyal Customer,41,Business travel,Business,1819,3,3,3,3,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +43425,85088,Male,Loyal Customer,53,Business travel,Business,689,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +43426,39164,Male,Loyal Customer,43,Business travel,Business,67,2,2,4,2,5,4,3,4,4,4,5,3,4,1,5,4.0,satisfied +43427,45401,Female,Loyal Customer,44,Personal Travel,Business,649,4,5,4,1,5,5,4,3,3,4,1,5,3,5,16,18.0,neutral or dissatisfied +43428,51944,Male,Loyal Customer,37,Business travel,Business,3513,2,2,2,2,5,3,2,4,4,4,4,1,4,5,0,0.0,satisfied +43429,112628,Female,Loyal Customer,59,Business travel,Business,639,4,4,4,4,5,4,5,4,4,4,4,3,4,4,9,0.0,satisfied +43430,124268,Male,Loyal Customer,27,Personal Travel,Business,255,4,4,4,3,5,4,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +43431,51725,Male,Loyal Customer,47,Personal Travel,Eco,355,4,5,4,1,3,4,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +43432,80899,Female,Loyal Customer,39,Business travel,Business,3743,0,0,0,2,2,5,5,5,5,5,2,4,5,3,0,0.0,satisfied +43433,1308,Female,disloyal Customer,33,Business travel,Business,89,1,1,1,4,2,1,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +43434,3246,Male,disloyal Customer,39,Business travel,Business,425,2,2,2,5,5,2,5,5,4,5,5,5,5,5,4,0.0,neutral or dissatisfied +43435,105574,Female,Loyal Customer,50,Business travel,Business,577,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +43436,94137,Male,Loyal Customer,49,Business travel,Business,187,0,4,0,4,5,5,4,1,1,1,1,5,1,3,33,27.0,satisfied +43437,104430,Male,Loyal Customer,39,Business travel,Business,611,1,2,2,2,4,4,4,1,1,1,1,2,1,2,46,42.0,neutral or dissatisfied +43438,87279,Female,disloyal Customer,22,Business travel,Eco,577,4,1,4,3,5,4,5,5,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +43439,21351,Male,Loyal Customer,68,Personal Travel,Eco,674,4,4,4,1,2,4,2,2,4,5,4,5,4,2,6,0.0,neutral or dissatisfied +43440,35714,Male,Loyal Customer,61,Personal Travel,Eco,2475,3,5,3,5,3,2,5,3,4,4,4,5,5,5,12,0.0,neutral or dissatisfied +43441,42005,Female,Loyal Customer,51,Business travel,Eco,116,4,1,1,1,4,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +43442,127238,Male,Loyal Customer,57,Business travel,Business,1460,4,4,4,4,3,4,5,5,5,5,5,3,5,4,21,22.0,satisfied +43443,124608,Male,Loyal Customer,23,Business travel,Business,1671,1,1,1,1,5,5,5,5,5,4,5,3,4,5,0,5.0,satisfied +43444,86973,Male,Loyal Customer,48,Business travel,Business,907,4,4,4,4,2,4,5,5,5,5,5,4,5,5,2,0.0,satisfied +43445,54851,Female,Loyal Customer,54,Business travel,Business,2400,5,5,5,5,5,4,5,4,4,4,4,3,4,5,43,25.0,satisfied +43446,17091,Male,Loyal Customer,36,Business travel,Business,1998,5,5,5,5,2,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +43447,95451,Male,Loyal Customer,44,Business travel,Business,239,3,3,4,3,5,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +43448,124290,Female,Loyal Customer,46,Business travel,Business,2096,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +43449,27908,Female,disloyal Customer,21,Business travel,Eco,1339,5,5,5,1,5,5,5,5,5,4,4,1,1,5,0,0.0,satisfied +43450,85530,Female,Loyal Customer,22,Personal Travel,Business,259,1,1,0,3,5,0,5,5,2,5,2,2,3,5,0,0.0,neutral or dissatisfied +43451,2329,Female,Loyal Customer,43,Personal Travel,Eco,691,3,4,4,1,4,5,5,2,2,4,2,3,2,4,0,6.0,neutral or dissatisfied +43452,44162,Male,Loyal Customer,54,Business travel,Eco,229,5,3,3,3,5,5,5,5,5,4,2,2,5,5,5,0.0,satisfied +43453,78483,Male,disloyal Customer,25,Business travel,Business,526,4,0,4,2,3,4,3,3,3,5,4,5,4,3,0,0.0,satisfied +43454,37428,Female,Loyal Customer,35,Business travel,Business,950,5,5,5,5,5,3,1,5,5,5,5,5,5,5,0,0.0,satisfied +43455,32378,Male,Loyal Customer,57,Business travel,Business,201,5,5,5,5,5,2,3,4,4,4,5,5,4,4,0,0.0,satisfied +43456,33222,Female,Loyal Customer,74,Business travel,Eco Plus,101,5,5,5,5,2,5,2,5,5,5,5,2,5,2,0,0.0,satisfied +43457,96226,Female,disloyal Customer,20,Business travel,Eco,460,1,3,1,3,5,1,2,5,2,4,3,3,3,5,47,37.0,neutral or dissatisfied +43458,80218,Female,Loyal Customer,24,Business travel,Business,2153,4,4,4,4,4,4,4,4,5,5,5,3,4,4,28,0.0,satisfied +43459,16396,Male,disloyal Customer,25,Business travel,Eco,463,2,3,2,4,4,2,4,4,2,5,4,1,4,4,43,41.0,neutral or dissatisfied +43460,80913,Male,Loyal Customer,43,Business travel,Business,341,5,5,5,5,3,4,5,5,5,5,5,4,5,4,0,1.0,satisfied +43461,75622,Female,disloyal Customer,37,Business travel,Business,337,3,4,4,1,3,4,1,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +43462,86809,Female,Loyal Customer,46,Business travel,Business,3653,5,5,3,5,3,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +43463,124316,Female,Loyal Customer,22,Personal Travel,Eco,255,4,4,4,5,5,4,5,5,4,2,5,5,5,5,8,6.0,satisfied +43464,122332,Female,Loyal Customer,43,Personal Travel,Eco Plus,544,1,5,1,1,5,2,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +43465,88100,Female,Loyal Customer,56,Business travel,Business,3451,1,1,1,1,4,4,5,3,3,3,3,4,3,4,2,6.0,satisfied +43466,94599,Male,Loyal Customer,54,Business travel,Business,3888,0,0,0,4,5,5,5,5,5,5,5,4,5,3,24,19.0,satisfied +43467,128836,Female,Loyal Customer,37,Business travel,Business,2615,3,1,1,1,3,3,3,4,3,4,3,3,3,3,0,1.0,neutral or dissatisfied +43468,89051,Female,Loyal Customer,57,Business travel,Business,1947,2,2,2,2,3,5,5,4,4,4,4,5,4,3,10,18.0,satisfied +43469,118487,Female,disloyal Customer,23,Business travel,Eco,338,1,0,1,2,3,1,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +43470,121349,Male,Loyal Customer,26,Personal Travel,Eco,430,2,5,2,4,5,2,2,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +43471,68244,Female,Loyal Customer,42,Business travel,Eco,631,5,5,5,5,5,4,2,5,5,5,5,1,5,2,0,0.0,satisfied +43472,72332,Female,Loyal Customer,28,Business travel,Business,985,2,2,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +43473,99846,Female,Loyal Customer,69,Personal Travel,Eco,587,3,4,3,4,4,5,4,3,3,3,3,3,3,4,6,0.0,neutral or dissatisfied +43474,77480,Male,disloyal Customer,23,Business travel,Eco,1087,4,3,3,1,2,3,2,2,3,5,4,4,5,2,14,3.0,satisfied +43475,85687,Female,Loyal Customer,51,Business travel,Business,1547,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +43476,52556,Male,disloyal Customer,26,Business travel,Eco,110,3,4,3,3,4,3,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +43477,91308,Female,Loyal Customer,51,Business travel,Eco Plus,515,3,1,1,1,3,2,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +43478,9850,Female,Loyal Customer,51,Business travel,Business,1713,3,3,4,3,4,4,4,5,5,4,5,4,5,3,112,129.0,satisfied +43479,106547,Female,Loyal Customer,45,Business travel,Business,1674,3,3,4,3,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +43480,129287,Female,Loyal Customer,54,Business travel,Business,550,5,5,5,5,5,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +43481,97191,Male,Loyal Customer,65,Personal Travel,Eco,1390,2,2,3,2,5,3,5,5,1,3,1,4,3,5,15,7.0,neutral or dissatisfied +43482,40413,Male,disloyal Customer,27,Business travel,Eco,188,2,0,2,3,4,2,4,4,4,2,4,2,2,4,0,0.0,neutral or dissatisfied +43483,50066,Female,Loyal Customer,42,Business travel,Eco,421,2,4,4,4,3,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +43484,58775,Female,disloyal Customer,62,Business travel,Eco,1005,3,3,3,3,3,3,3,3,4,3,3,3,3,3,21,6.0,neutral or dissatisfied +43485,8698,Male,Loyal Customer,37,Business travel,Eco,280,2,4,1,1,2,2,2,2,5,5,1,1,4,2,0,0.0,satisfied +43486,79059,Female,Loyal Customer,33,Business travel,Business,356,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +43487,83638,Female,Loyal Customer,40,Business travel,Business,3061,1,1,1,1,3,5,5,2,2,3,2,4,2,3,0,22.0,satisfied +43488,30736,Female,Loyal Customer,11,Personal Travel,Eco,1069,4,4,4,1,3,4,3,3,5,5,4,5,4,3,4,0.0,neutral or dissatisfied +43489,11206,Male,Loyal Customer,39,Personal Travel,Eco,667,1,5,1,3,4,1,1,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +43490,113381,Male,Loyal Customer,41,Business travel,Business,1563,3,3,4,3,3,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +43491,59505,Female,disloyal Customer,57,Business travel,Business,964,4,4,4,2,3,4,3,3,5,3,5,3,4,3,22,7.0,satisfied +43492,45101,Male,Loyal Customer,50,Business travel,Eco,157,5,2,4,2,5,5,5,5,2,3,4,2,2,5,0,0.0,satisfied +43493,62991,Female,Loyal Customer,42,Business travel,Business,909,4,3,5,3,1,4,3,4,4,4,4,3,4,1,8,1.0,neutral or dissatisfied +43494,97313,Male,Loyal Customer,39,Business travel,Business,2972,3,3,3,3,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +43495,61197,Male,Loyal Customer,54,Business travel,Business,862,4,4,4,4,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +43496,76843,Male,disloyal Customer,38,Business travel,Business,989,2,2,2,2,1,2,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +43497,75881,Male,Loyal Customer,36,Personal Travel,Eco,1972,3,1,3,3,3,3,3,3,4,4,2,2,3,3,10,0.0,neutral or dissatisfied +43498,29130,Female,Loyal Customer,62,Personal Travel,Eco,956,2,4,2,1,4,5,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +43499,85926,Female,disloyal Customer,22,Business travel,Eco,528,4,5,4,3,5,4,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +43500,3455,Male,Loyal Customer,61,Business travel,Business,296,0,0,0,2,2,5,5,3,3,3,3,4,3,3,69,88.0,satisfied +43501,50011,Female,Loyal Customer,34,Business travel,Business,3062,3,1,1,1,3,3,4,3,3,3,3,2,3,4,0,14.0,neutral or dissatisfied +43502,19431,Male,Loyal Customer,46,Personal Travel,Eco,645,4,2,4,4,3,4,3,3,4,2,3,2,4,3,33,36.0,satisfied +43503,41813,Female,disloyal Customer,25,Business travel,Eco,489,2,3,3,1,1,3,1,1,1,3,3,5,2,1,0,0.0,neutral or dissatisfied +43504,108042,Female,Loyal Customer,57,Business travel,Business,1979,1,5,5,5,2,3,4,1,1,1,1,1,1,2,30,15.0,neutral or dissatisfied +43505,127483,Male,disloyal Customer,20,Business travel,Eco,1190,4,4,4,2,5,4,5,5,3,1,4,1,3,5,6,4.0,satisfied +43506,129537,Female,Loyal Customer,46,Business travel,Business,2583,2,3,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +43507,114147,Female,Loyal Customer,47,Business travel,Business,3586,1,1,1,1,3,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +43508,71536,Female,Loyal Customer,49,Business travel,Business,2080,1,1,1,1,2,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +43509,56566,Female,Loyal Customer,54,Business travel,Business,1871,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,5.0,satisfied +43510,51812,Female,Loyal Customer,26,Personal Travel,Eco,370,3,5,3,1,5,3,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +43511,118058,Male,disloyal Customer,17,Business travel,Eco,1262,3,3,3,1,3,3,3,3,3,3,4,4,4,3,0,4.0,neutral or dissatisfied +43512,67078,Male,Loyal Customer,52,Business travel,Business,3598,4,4,3,4,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +43513,100833,Male,Loyal Customer,12,Business travel,Business,711,2,2,2,2,2,2,2,2,1,2,3,4,4,2,9,0.0,neutral or dissatisfied +43514,128768,Male,Loyal Customer,29,Personal Travel,Eco,550,3,2,3,4,2,3,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +43515,97090,Male,disloyal Customer,24,Business travel,Business,715,4,5,4,3,4,4,4,4,3,5,5,4,4,4,18,7.0,satisfied +43516,104512,Male,disloyal Customer,18,Business travel,Eco,942,5,5,5,1,4,5,4,4,4,4,4,3,4,4,0,21.0,satisfied +43517,57983,Male,Loyal Customer,50,Business travel,Business,3681,2,2,2,2,5,3,2,4,4,4,4,3,4,2,12,7.0,satisfied +43518,8671,Male,Loyal Customer,21,Business travel,Business,280,2,2,2,2,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +43519,99805,Female,Loyal Customer,32,Personal Travel,Eco,584,3,5,3,5,3,3,3,3,5,2,4,3,5,3,75,67.0,neutral or dissatisfied +43520,49824,Female,Loyal Customer,46,Business travel,Eco,421,4,5,5,5,1,4,2,4,4,4,4,4,4,1,42,41.0,satisfied +43521,128387,Male,Loyal Customer,45,Business travel,Business,2345,4,4,4,4,5,4,4,4,4,4,4,5,4,4,3,4.0,satisfied +43522,128732,Female,Loyal Customer,11,Personal Travel,Eco,1464,1,4,1,2,1,1,1,1,4,3,5,5,5,1,22,37.0,neutral or dissatisfied +43523,77305,Male,Loyal Customer,43,Business travel,Business,2646,3,3,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +43524,119141,Male,Loyal Customer,19,Personal Travel,Eco,119,2,4,0,2,4,0,4,4,4,1,2,5,2,4,0,0.0,neutral or dissatisfied +43525,37799,Male,Loyal Customer,58,Personal Travel,Eco Plus,989,0,5,0,3,4,0,4,4,4,5,4,3,4,4,0,0.0,satisfied +43526,60509,Female,Loyal Customer,36,Personal Travel,Eco,862,2,4,2,5,4,2,4,4,4,4,4,4,5,4,0,2.0,neutral or dissatisfied +43527,36300,Female,disloyal Customer,38,Business travel,Eco,395,2,0,2,5,3,2,3,3,1,2,5,4,4,3,0,0.0,neutral or dissatisfied +43528,19305,Male,Loyal Customer,60,Personal Travel,Eco,299,3,4,3,1,1,3,1,1,4,3,4,3,5,1,0,12.0,neutral or dissatisfied +43529,101824,Female,Loyal Customer,10,Personal Travel,Eco,1521,1,5,1,1,5,1,5,5,3,2,3,5,4,5,42,20.0,neutral or dissatisfied +43530,21641,Female,Loyal Customer,52,Personal Travel,Eco,780,4,5,3,5,5,5,1,3,3,3,3,5,3,2,0,0.0,neutral or dissatisfied +43531,90979,Male,Loyal Customer,52,Business travel,Eco,145,4,4,4,4,4,4,4,4,2,3,5,5,3,4,0,1.0,satisfied +43532,39385,Male,disloyal Customer,22,Business travel,Eco,546,5,5,5,4,5,5,5,5,4,3,1,3,5,5,0,0.0,satisfied +43533,93032,Male,Loyal Customer,33,Business travel,Business,2532,5,5,3,5,5,5,5,5,4,2,4,5,4,5,21,8.0,satisfied +43534,98843,Female,Loyal Customer,47,Personal Travel,Eco Plus,763,1,5,0,5,4,5,4,2,2,0,2,3,2,4,0,0.0,neutral or dissatisfied +43535,114342,Male,Loyal Customer,43,Personal Travel,Eco,948,3,3,3,4,3,3,4,3,1,2,4,2,4,3,11,5.0,neutral or dissatisfied +43536,30550,Male,Loyal Customer,53,Personal Travel,Eco,1026,2,4,2,2,5,2,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +43537,86301,Female,Loyal Customer,28,Personal Travel,Eco,226,4,4,0,4,4,0,4,4,3,3,5,4,4,4,0,1.0,neutral or dissatisfied +43538,74465,Male,Loyal Customer,43,Business travel,Business,1464,5,5,4,5,2,4,5,2,2,2,2,4,2,3,1,0.0,satisfied +43539,48118,Male,Loyal Customer,39,Business travel,Eco,414,5,5,5,5,5,5,5,5,1,2,2,5,4,5,89,89.0,satisfied +43540,18999,Female,Loyal Customer,47,Personal Travel,Business,788,2,4,2,3,2,5,5,4,4,2,4,3,4,3,5,17.0,neutral or dissatisfied +43541,5387,Male,Loyal Customer,25,Personal Travel,Eco,812,2,3,2,3,5,2,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +43542,95792,Male,disloyal Customer,20,Business travel,Business,419,4,4,4,1,5,4,5,5,4,2,5,3,4,5,0,0.0,satisfied +43543,92705,Male,Loyal Customer,32,Business travel,Business,2153,2,2,2,2,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +43544,102243,Female,Loyal Customer,75,Business travel,Eco,386,3,2,1,2,1,2,3,3,3,3,3,3,3,1,16,14.0,neutral or dissatisfied +43545,46959,Male,Loyal Customer,60,Personal Travel,Eco,776,4,4,4,2,2,4,2,2,4,4,4,3,4,2,0,0.0,satisfied +43546,87011,Male,Loyal Customer,19,Personal Travel,Eco,907,0,5,0,3,2,0,2,2,3,3,4,4,5,2,0,0.0,satisfied +43547,29835,Female,Loyal Customer,73,Business travel,Business,261,2,2,2,2,3,2,5,3,3,4,3,1,3,4,3,1.0,satisfied +43548,127338,Male,Loyal Customer,45,Business travel,Business,507,5,5,5,5,4,4,5,4,4,4,4,5,4,4,57,57.0,satisfied +43549,36198,Female,Loyal Customer,56,Business travel,Eco,280,5,1,2,2,4,4,1,5,5,5,5,2,5,2,0,9.0,satisfied +43550,23425,Male,disloyal Customer,27,Business travel,Eco,1201,1,1,1,3,2,1,2,2,4,3,5,5,5,2,82,56.0,neutral or dissatisfied +43551,120647,Female,Loyal Customer,53,Business travel,Business,3463,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +43552,85337,Female,Loyal Customer,58,Business travel,Business,813,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +43553,62184,Female,Loyal Customer,13,Business travel,Business,2454,2,2,2,2,5,4,5,5,3,4,4,5,4,5,3,0.0,satisfied +43554,6899,Female,disloyal Customer,20,Business travel,Eco,265,3,3,3,4,3,3,2,3,3,4,4,2,3,3,1,0.0,neutral or dissatisfied +43555,97865,Female,Loyal Customer,64,Business travel,Business,2673,4,4,4,4,5,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +43556,41622,Female,Loyal Customer,8,Personal Travel,Eco Plus,1269,3,5,3,1,4,3,2,4,3,3,5,4,5,4,0,8.0,neutral or dissatisfied +43557,54629,Female,Loyal Customer,42,Business travel,Eco,787,4,2,3,2,2,5,1,4,4,4,4,2,4,4,0,0.0,satisfied +43558,104489,Female,Loyal Customer,23,Business travel,Eco,860,3,1,1,1,3,3,3,1,3,3,3,3,1,3,143,123.0,neutral or dissatisfied +43559,4116,Male,disloyal Customer,24,Business travel,Eco,544,2,0,2,4,5,2,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +43560,114643,Female,Loyal Customer,50,Business travel,Business,2210,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +43561,1574,Female,Loyal Customer,32,Business travel,Business,3043,2,2,2,2,4,4,4,4,5,4,4,5,5,4,16,25.0,satisfied +43562,126793,Female,Loyal Customer,46,Business travel,Business,2125,2,2,2,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +43563,14567,Male,Loyal Customer,36,Business travel,Business,986,2,2,2,2,3,2,4,4,4,4,4,5,4,2,18,0.0,satisfied +43564,15958,Male,Loyal Customer,62,Personal Travel,Eco,528,3,4,3,3,3,3,3,3,1,1,5,1,5,3,0,0.0,neutral or dissatisfied +43565,118888,Female,disloyal Customer,38,Business travel,Business,587,2,3,3,3,2,3,2,2,5,3,4,4,5,2,7,6.0,neutral or dissatisfied +43566,109540,Male,Loyal Customer,11,Personal Travel,Eco,834,2,4,2,3,5,2,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +43567,58216,Female,Loyal Customer,69,Personal Travel,Eco,925,2,5,2,3,2,5,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +43568,78313,Female,Loyal Customer,11,Personal Travel,Eco Plus,1598,3,5,3,5,5,3,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +43569,63096,Female,disloyal Customer,48,Business travel,Business,967,4,4,4,3,3,4,3,3,3,4,4,4,5,3,0,0.0,satisfied +43570,63375,Male,Loyal Customer,70,Personal Travel,Eco,372,4,2,4,2,2,4,2,2,3,4,1,3,2,2,7,0.0,neutral or dissatisfied +43571,117378,Male,Loyal Customer,60,Business travel,Business,3459,5,5,4,5,4,4,4,1,1,2,1,3,1,3,2,0.0,satisfied +43572,39244,Female,Loyal Customer,54,Business travel,Business,2236,2,2,3,2,5,2,5,5,5,5,3,2,5,1,0,3.0,satisfied +43573,112576,Male,Loyal Customer,57,Business travel,Business,2397,2,3,2,2,3,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +43574,40404,Male,Loyal Customer,33,Personal Travel,Business,290,3,4,3,2,2,3,2,2,3,3,4,4,5,2,4,2.0,neutral or dissatisfied +43575,108628,Male,disloyal Customer,20,Business travel,Eco,1547,1,1,1,4,5,1,5,5,3,1,3,2,3,5,5,6.0,neutral or dissatisfied +43576,31306,Female,Loyal Customer,31,Business travel,Eco,680,4,3,3,3,4,4,4,4,1,5,4,2,3,4,0,0.0,satisfied +43577,2312,Male,Loyal Customer,79,Business travel,Business,525,2,2,2,2,5,1,3,4,4,4,4,5,4,3,0,0.0,satisfied +43578,77018,Female,Loyal Customer,52,Business travel,Business,2960,5,5,5,5,3,4,5,2,2,2,2,5,2,4,52,48.0,satisfied +43579,32303,Male,Loyal Customer,42,Business travel,Business,2346,4,4,1,4,4,2,3,4,4,5,3,3,4,1,0,0.0,satisfied +43580,18075,Female,Loyal Customer,69,Personal Travel,Eco,488,2,0,2,3,5,5,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +43581,75353,Female,Loyal Customer,54,Business travel,Business,2615,1,1,1,1,5,5,5,3,2,3,5,5,5,5,0,41.0,satisfied +43582,128716,Female,Loyal Customer,49,Business travel,Business,1235,1,5,1,1,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +43583,98358,Female,Loyal Customer,51,Business travel,Business,1707,3,5,5,5,1,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +43584,7501,Female,Loyal Customer,23,Personal Travel,Eco Plus,925,4,4,4,3,4,4,5,4,5,5,5,5,4,4,0,9.0,neutral or dissatisfied +43585,51089,Female,Loyal Customer,10,Personal Travel,Eco,262,4,2,4,3,1,4,1,1,4,3,3,1,4,1,0,3.0,neutral or dissatisfied +43586,71262,Female,Loyal Customer,44,Personal Travel,Eco,733,3,3,3,2,2,3,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +43587,54074,Female,Loyal Customer,46,Business travel,Business,1416,1,4,4,4,3,2,2,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +43588,55692,Female,Loyal Customer,27,Business travel,Eco,927,2,1,4,1,2,2,2,2,2,4,3,1,3,2,27,26.0,neutral or dissatisfied +43589,91535,Female,Loyal Customer,38,Business travel,Business,3469,2,2,3,2,3,5,5,4,4,4,4,3,4,5,0,2.0,satisfied +43590,83409,Female,Loyal Customer,77,Business travel,Business,632,1,5,5,5,4,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +43591,52587,Female,Loyal Customer,60,Business travel,Eco,160,5,3,3,3,4,1,3,5,5,5,5,1,5,3,0,5.0,satisfied +43592,96611,Male,Loyal Customer,49,Business travel,Business,2432,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +43593,83187,Male,Loyal Customer,51,Business travel,Business,1123,4,4,1,4,5,4,4,5,5,5,5,4,5,3,0,22.0,satisfied +43594,24758,Male,Loyal Customer,51,Business travel,Business,2647,3,3,3,3,5,1,2,5,5,5,5,4,5,5,0,0.0,satisfied +43595,28543,Male,Loyal Customer,42,Personal Travel,Eco,2640,1,5,1,3,1,1,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +43596,89988,Male,Loyal Customer,47,Business travel,Business,2927,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +43597,76563,Male,Loyal Customer,55,Business travel,Business,3774,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,13.0,satisfied +43598,332,Male,Loyal Customer,44,Business travel,Eco,453,4,1,5,1,4,4,4,4,2,3,3,5,2,4,0,0.0,satisfied +43599,103112,Female,Loyal Customer,44,Personal Travel,Eco,328,1,5,1,3,2,2,5,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +43600,64754,Female,disloyal Customer,29,Business travel,Business,190,5,4,4,3,1,4,1,1,4,5,4,3,4,1,5,0.0,satisfied +43601,101332,Female,disloyal Customer,24,Business travel,Business,1771,0,0,0,5,3,0,3,3,3,4,4,4,5,3,0,0.0,satisfied +43602,5821,Female,Loyal Customer,67,Personal Travel,Eco,157,1,2,1,4,3,4,4,4,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +43603,125458,Female,Loyal Customer,54,Business travel,Business,2917,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +43604,100230,Female,disloyal Customer,39,Business travel,Business,1165,2,3,3,3,5,3,5,5,4,3,4,4,4,5,12,9.0,neutral or dissatisfied +43605,86053,Male,Loyal Customer,39,Personal Travel,Eco,432,2,4,2,4,2,4,4,5,5,5,4,4,3,4,174,178.0,neutral or dissatisfied +43606,13484,Male,Loyal Customer,32,Personal Travel,Business,227,1,4,1,3,5,1,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +43607,111637,Female,Loyal Customer,52,Business travel,Business,1558,4,4,2,4,3,5,5,5,5,5,5,5,5,5,3,0.0,satisfied +43608,126786,Female,Loyal Customer,43,Business travel,Business,2125,2,2,3,2,5,4,4,4,4,4,4,4,4,4,0,22.0,satisfied +43609,117094,Male,Loyal Customer,48,Business travel,Eco,251,5,4,4,4,5,5,5,5,1,3,5,4,4,5,4,0.0,satisfied +43610,34836,Female,Loyal Customer,36,Business travel,Eco Plus,209,4,2,2,2,4,3,4,4,2,3,4,1,4,4,30,30.0,neutral or dissatisfied +43611,106224,Male,Loyal Customer,60,Business travel,Business,2588,5,5,5,5,3,4,4,4,4,4,4,3,4,4,7,0.0,satisfied +43612,50818,Male,Loyal Customer,63,Personal Travel,Eco,134,4,3,4,2,5,4,4,5,5,2,3,4,5,5,0,0.0,satisfied +43613,76152,Male,Loyal Customer,42,Business travel,Business,3868,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +43614,49037,Female,Loyal Customer,42,Business travel,Business,1544,2,2,2,2,4,3,3,5,5,5,5,3,5,3,0,0.0,satisfied +43615,90376,Female,Loyal Customer,43,Business travel,Business,3099,2,2,2,2,2,5,4,3,3,4,3,4,3,5,0,13.0,satisfied +43616,1944,Male,disloyal Customer,42,Business travel,Eco,383,3,2,3,3,5,3,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +43617,14379,Male,Loyal Customer,58,Business travel,Eco,900,4,4,4,4,5,4,5,5,1,3,3,4,2,5,0,0.0,satisfied +43618,22583,Female,disloyal Customer,24,Business travel,Eco,223,3,1,3,4,5,3,5,5,3,4,4,3,4,5,1,7.0,neutral or dissatisfied +43619,96727,Male,Loyal Customer,35,Personal Travel,Eco,696,4,1,3,2,1,3,1,1,4,1,2,4,3,1,18,2.0,neutral or dissatisfied +43620,63024,Female,Loyal Customer,60,Business travel,Business,1952,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +43621,49811,Male,Loyal Customer,42,Business travel,Eco,78,2,1,1,1,2,2,2,2,2,3,4,3,3,2,38,33.0,neutral or dissatisfied +43622,90605,Male,disloyal Customer,21,Business travel,Business,404,4,0,4,2,1,4,1,1,3,3,5,5,4,1,0,0.0,satisfied +43623,79803,Male,disloyal Customer,22,Business travel,Business,950,5,0,5,1,1,5,1,1,3,2,5,4,5,1,6,40.0,satisfied +43624,55488,Male,Loyal Customer,29,Business travel,Business,1739,1,1,4,1,5,5,5,5,4,3,5,5,5,5,6,0.0,satisfied +43625,63149,Male,Loyal Customer,51,Business travel,Business,337,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +43626,46213,Female,Loyal Customer,40,Business travel,Eco,594,5,4,4,4,5,5,5,5,1,4,1,5,5,5,0,0.0,satisfied +43627,42323,Male,Loyal Customer,67,Personal Travel,Eco,550,1,1,1,2,4,1,4,4,3,4,1,2,3,4,0,0.0,neutral or dissatisfied +43628,7525,Male,Loyal Customer,42,Business travel,Business,2455,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +43629,6680,Male,disloyal Customer,19,Business travel,Eco,258,0,5,1,1,4,1,1,4,4,5,5,3,4,4,0,0.0,satisfied +43630,85496,Male,Loyal Customer,39,Personal Travel,Eco,332,4,3,4,3,2,4,2,2,3,1,3,3,4,2,30,19.0,neutral or dissatisfied +43631,29850,Male,Loyal Customer,33,Business travel,Business,3417,3,3,3,3,5,5,5,5,4,3,3,4,2,5,0,0.0,satisfied +43632,104342,Male,Loyal Customer,34,Personal Travel,Eco,409,3,5,3,2,1,3,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +43633,506,Male,Loyal Customer,50,Business travel,Business,3003,0,0,0,2,5,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +43634,80184,Male,Loyal Customer,43,Personal Travel,Eco,2475,3,5,3,3,3,1,1,5,4,3,5,1,5,1,62,125.0,neutral or dissatisfied +43635,18790,Male,Loyal Customer,40,Business travel,Eco,551,5,4,3,3,5,5,5,5,4,2,3,5,2,5,0,0.0,satisfied +43636,54048,Male,Loyal Customer,24,Business travel,Business,1416,3,3,3,3,4,4,4,4,5,4,2,5,3,4,0,0.0,satisfied +43637,28670,Male,Loyal Customer,31,Business travel,Eco Plus,2355,3,3,3,3,3,3,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +43638,6306,Male,Loyal Customer,69,Personal Travel,Business,296,4,5,4,2,4,5,5,5,5,4,5,4,5,4,6,0.0,neutral or dissatisfied +43639,38659,Male,Loyal Customer,56,Business travel,Business,2611,4,4,4,4,5,1,1,4,4,4,4,1,4,4,0,6.0,neutral or dissatisfied +43640,67168,Female,Loyal Customer,21,Personal Travel,Eco,1102,1,2,1,3,3,1,4,3,4,1,3,1,4,3,2,0.0,neutral or dissatisfied +43641,33204,Female,Loyal Customer,31,Business travel,Eco Plus,101,4,2,5,2,4,4,4,4,3,3,1,2,1,4,0,0.0,satisfied +43642,15826,Male,Loyal Customer,41,Business travel,Business,2030,1,1,1,1,3,4,3,4,4,4,1,3,4,2,0,0.0,neutral or dissatisfied +43643,42165,Female,Loyal Customer,25,Business travel,Business,834,5,5,5,5,4,5,4,4,2,2,5,4,2,4,0,0.0,satisfied +43644,58780,Male,Loyal Customer,37,Business travel,Eco,1005,4,3,3,3,4,4,4,4,4,4,4,3,3,4,17,10.0,neutral or dissatisfied +43645,63992,Female,Loyal Customer,58,Business travel,Business,612,4,4,4,4,3,5,5,4,4,4,4,5,4,4,5,14.0,satisfied +43646,50588,Male,Loyal Customer,63,Personal Travel,Eco,337,3,5,3,2,2,3,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +43647,34472,Male,Loyal Customer,38,Business travel,Business,1713,4,4,4,4,2,3,1,4,4,4,4,1,4,5,43,44.0,satisfied +43648,16945,Male,Loyal Customer,14,Personal Travel,Eco,820,2,1,2,4,4,2,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +43649,71797,Female,Loyal Customer,49,Business travel,Business,1744,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +43650,44796,Male,Loyal Customer,46,Personal Travel,Eco Plus,1250,4,5,4,3,4,4,4,4,3,3,4,4,4,4,0,12.0,neutral or dissatisfied +43651,119001,Female,Loyal Customer,51,Business travel,Business,3475,3,5,3,3,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +43652,38777,Male,disloyal Customer,22,Business travel,Business,354,4,2,4,3,4,4,4,4,1,4,4,3,4,4,0,26.0,neutral or dissatisfied +43653,40799,Female,Loyal Customer,39,Business travel,Business,1926,3,2,2,2,2,3,3,3,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +43654,95857,Male,Loyal Customer,29,Business travel,Business,2087,4,3,3,3,4,4,4,4,1,5,4,1,4,4,5,0.0,neutral or dissatisfied +43655,126759,Male,Loyal Customer,24,Personal Travel,Eco,2521,3,5,3,4,5,3,5,5,5,1,5,2,1,5,8,6.0,neutral or dissatisfied +43656,89934,Female,Loyal Customer,60,Personal Travel,Eco,1306,4,5,4,4,4,5,4,1,1,4,1,5,1,4,0,0.0,satisfied +43657,61570,Male,disloyal Customer,24,Business travel,Eco,1117,2,2,2,5,2,2,2,2,4,3,5,5,5,2,2,0.0,neutral or dissatisfied +43658,62383,Male,Loyal Customer,60,Business travel,Business,2704,3,3,3,3,3,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +43659,111360,Female,Loyal Customer,47,Business travel,Business,1111,4,4,2,4,3,5,5,4,4,4,4,3,4,4,21,15.0,satisfied +43660,122748,Male,Loyal Customer,37,Business travel,Business,251,1,1,2,1,4,1,3,5,5,5,5,3,5,3,0,0.0,satisfied +43661,20968,Female,Loyal Customer,43,Business travel,Business,2882,0,0,0,2,2,1,3,5,5,3,3,3,5,4,6,0.0,satisfied +43662,117427,Male,Loyal Customer,11,Personal Travel,Eco,1460,4,2,5,3,4,5,1,4,1,2,1,4,3,4,1,0.0,neutral or dissatisfied +43663,98058,Female,disloyal Customer,42,Business travel,Business,1310,5,0,0,4,4,5,3,4,5,3,5,3,4,4,101,82.0,satisfied +43664,90516,Male,Loyal Customer,18,Business travel,Business,545,4,4,4,4,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +43665,121966,Male,Loyal Customer,46,Business travel,Business,130,2,2,3,2,3,4,4,2,2,2,2,3,2,2,35,37.0,neutral or dissatisfied +43666,122413,Male,disloyal Customer,21,Business travel,Business,1916,1,3,1,4,2,1,1,2,3,3,4,4,3,2,0,9.0,neutral or dissatisfied +43667,43609,Female,Loyal Customer,53,Business travel,Business,2381,1,4,4,4,5,3,2,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +43668,73489,Male,Loyal Customer,50,Personal Travel,Eco,1120,0,5,0,1,2,0,2,2,3,3,1,3,3,2,1,0.0,satisfied +43669,75611,Male,Loyal Customer,61,Personal Travel,Eco,337,2,5,2,3,5,2,1,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +43670,88742,Female,Loyal Customer,40,Personal Travel,Eco,594,1,4,1,1,2,1,2,2,5,3,3,1,4,2,0,14.0,neutral or dissatisfied +43671,122024,Female,Loyal Customer,59,Business travel,Business,3635,3,3,5,3,3,4,4,5,5,5,4,4,5,4,4,0.0,satisfied +43672,29051,Female,Loyal Customer,64,Personal Travel,Eco,954,2,1,2,4,4,4,3,2,2,2,1,3,2,1,0,0.0,neutral or dissatisfied +43673,60,Male,Loyal Customer,57,Business travel,Business,3392,1,1,1,1,5,5,5,4,4,4,5,3,4,5,19,34.0,satisfied +43674,119065,Female,Loyal Customer,52,Business travel,Business,1719,4,4,4,4,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +43675,50391,Male,disloyal Customer,29,Business travel,Eco,373,1,5,1,4,5,1,5,5,3,5,2,4,2,5,0,0.0,neutral or dissatisfied +43676,7517,Male,Loyal Customer,48,Business travel,Business,762,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +43677,72395,Female,Loyal Customer,23,Business travel,Business,3612,1,1,1,1,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +43678,73552,Male,Loyal Customer,71,Business travel,Eco Plus,594,2,5,5,5,2,2,2,2,3,5,4,2,4,2,41,35.0,neutral or dissatisfied +43679,23472,Female,Loyal Customer,12,Personal Travel,Eco,516,5,4,5,3,2,5,2,2,3,2,4,2,5,2,9,24.0,satisfied +43680,122070,Female,Loyal Customer,31,Business travel,Eco,130,5,1,1,1,5,5,5,5,2,5,1,3,2,5,1,0.0,satisfied +43681,92825,Female,Loyal Customer,57,Business travel,Business,1541,4,4,4,4,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +43682,72030,Female,disloyal Customer,22,Business travel,Eco,3784,2,1,1,3,2,4,4,3,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +43683,75606,Male,Loyal Customer,57,Personal Travel,Eco,337,3,2,3,2,2,3,2,2,3,4,2,2,3,2,13,5.0,neutral or dissatisfied +43684,96377,Female,Loyal Customer,33,Business travel,Business,2851,4,4,4,4,5,5,5,3,3,3,3,4,3,3,33,36.0,satisfied +43685,89680,Male,Loyal Customer,38,Business travel,Eco,550,4,4,4,4,4,5,4,4,3,5,1,3,4,4,0,15.0,satisfied +43686,52466,Female,Loyal Customer,25,Business travel,Eco Plus,237,5,2,2,2,5,5,3,5,2,2,1,4,1,5,1,0.0,satisfied +43687,98011,Female,disloyal Customer,26,Business travel,Business,1014,4,4,4,4,1,4,1,1,3,5,5,3,4,1,9,19.0,satisfied +43688,23526,Female,Loyal Customer,54,Business travel,Eco Plus,349,3,4,4,4,3,3,3,1,1,2,3,3,4,3,144,151.0,neutral or dissatisfied +43689,83926,Male,Loyal Customer,54,Business travel,Business,1735,1,1,1,1,5,4,4,4,4,4,4,5,4,3,13,1.0,satisfied +43690,25295,Male,Loyal Customer,46,Business travel,Eco Plus,321,5,5,5,5,5,5,5,5,2,4,2,2,5,5,0,0.0,satisfied +43691,15319,Female,disloyal Customer,24,Business travel,Eco,589,1,3,1,1,4,1,4,4,4,1,4,5,4,4,5,18.0,neutral or dissatisfied +43692,36361,Male,disloyal Customer,29,Business travel,Eco,200,4,5,4,2,1,4,1,1,3,1,5,4,5,1,0,0.0,neutral or dissatisfied +43693,76386,Female,Loyal Customer,45,Business travel,Business,2240,3,4,4,4,1,2,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +43694,1007,Male,Loyal Customer,36,Business travel,Business,3881,3,5,3,3,1,2,2,5,5,5,5,4,5,4,0,0.0,satisfied +43695,43937,Male,Loyal Customer,17,Business travel,Eco Plus,255,3,3,3,3,3,3,2,3,4,2,3,3,3,3,96,82.0,neutral or dissatisfied +43696,68187,Male,Loyal Customer,22,Personal Travel,Eco,597,2,0,2,1,2,1,1,3,4,5,4,1,5,1,151,190.0,neutral or dissatisfied +43697,102197,Male,disloyal Customer,21,Business travel,Business,226,5,3,5,3,2,5,2,2,3,5,5,5,5,2,0,0.0,satisfied +43698,21000,Female,disloyal Customer,7,Business travel,Eco,721,2,2,2,4,4,2,4,4,1,1,4,3,4,4,3,7.0,neutral or dissatisfied +43699,110109,Female,Loyal Customer,48,Business travel,Business,2098,5,5,3,5,3,5,4,4,4,4,4,4,4,4,14,17.0,satisfied +43700,13740,Female,disloyal Customer,37,Business travel,Eco,401,2,1,2,4,5,2,3,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +43701,51002,Female,Loyal Customer,7,Personal Travel,Eco,153,3,3,3,4,3,3,3,3,2,4,3,1,3,3,1,0.0,neutral or dissatisfied +43702,66399,Male,Loyal Customer,52,Business travel,Business,1562,2,2,4,2,4,4,5,5,5,5,5,3,5,5,66,66.0,satisfied +43703,17396,Male,Loyal Customer,49,Business travel,Business,3702,2,2,4,2,5,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +43704,89966,Male,Loyal Customer,58,Personal Travel,Eco,1501,3,3,3,4,5,3,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +43705,26504,Female,Loyal Customer,45,Business travel,Business,2741,2,2,2,2,5,5,1,4,4,4,4,5,4,1,0,0.0,satisfied +43706,124402,Female,Loyal Customer,63,Business travel,Business,1671,4,4,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +43707,59546,Male,Loyal Customer,40,Business travel,Business,3531,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +43708,117530,Female,Loyal Customer,15,Personal Travel,Business,872,4,2,4,3,4,4,4,4,3,5,4,1,4,4,21,17.0,neutral or dissatisfied +43709,101971,Female,Loyal Customer,23,Business travel,Business,228,3,2,2,2,3,3,3,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +43710,45754,Male,Loyal Customer,41,Business travel,Eco,391,4,5,5,5,4,4,4,4,1,1,3,1,5,4,9,0.0,satisfied +43711,90082,Female,Loyal Customer,32,Business travel,Business,3792,4,4,4,4,3,4,3,3,4,5,4,5,5,3,0,0.0,satisfied +43712,42660,Female,disloyal Customer,22,Business travel,Eco,557,2,0,2,1,4,2,4,4,1,3,3,3,5,4,0,0.0,neutral or dissatisfied +43713,64283,Male,Loyal Customer,55,Business travel,Business,2597,2,2,5,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +43714,120022,Male,Loyal Customer,46,Personal Travel,Eco,511,3,4,3,5,1,3,1,1,5,4,5,4,5,1,0,10.0,neutral or dissatisfied +43715,74206,Male,Loyal Customer,38,Business travel,Eco Plus,721,4,2,2,2,4,4,4,4,4,2,2,1,1,4,0,0.0,neutral or dissatisfied +43716,16770,Female,Loyal Customer,46,Business travel,Business,2579,5,2,2,2,1,2,3,5,5,4,5,2,5,4,0,3.0,neutral or dissatisfied +43717,34963,Female,Loyal Customer,48,Business travel,Eco Plus,395,5,1,1,1,2,4,2,5,5,5,5,5,5,5,0,8.0,satisfied +43718,64143,Male,Loyal Customer,57,Business travel,Business,3550,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +43719,83445,Female,Loyal Customer,59,Business travel,Business,2026,2,4,2,2,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +43720,51408,Female,Loyal Customer,10,Personal Travel,Eco Plus,363,4,5,3,5,3,3,3,3,3,3,4,3,4,3,69,79.0,neutral or dissatisfied +43721,18683,Male,Loyal Customer,60,Personal Travel,Eco,305,4,3,4,4,1,4,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +43722,67066,Female,Loyal Customer,52,Business travel,Business,1942,3,3,5,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +43723,59160,Female,Loyal Customer,36,Business travel,Eco Plus,1726,2,5,5,5,2,2,2,2,4,2,4,1,4,2,18,1.0,neutral or dissatisfied +43724,117223,Male,Loyal Customer,69,Personal Travel,Eco,304,2,4,2,1,5,2,1,5,5,4,5,3,4,5,0,5.0,neutral or dissatisfied +43725,116718,Male,disloyal Customer,27,Business travel,Eco Plus,337,2,2,2,3,3,2,3,3,3,5,4,3,4,3,28,21.0,neutral or dissatisfied +43726,35788,Male,Loyal Customer,23,Personal Travel,Eco,200,4,3,4,2,5,4,4,5,1,2,3,1,1,5,0,0.0,neutral or dissatisfied +43727,126166,Male,disloyal Customer,52,Business travel,Eco,631,3,2,3,3,2,3,5,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +43728,95127,Male,Loyal Customer,13,Personal Travel,Eco,677,2,4,2,3,3,2,3,3,1,4,4,2,1,3,0,0.0,neutral or dissatisfied +43729,98263,Male,Loyal Customer,40,Business travel,Eco,1136,3,4,4,4,3,3,3,3,4,5,3,2,4,3,0,1.0,neutral or dissatisfied +43730,101703,Male,Loyal Customer,54,Business travel,Business,1624,3,3,3,3,5,3,4,3,3,3,3,5,3,5,0,0.0,satisfied +43731,9065,Male,disloyal Customer,22,Business travel,Eco,173,4,1,3,4,2,3,2,2,3,3,3,3,3,2,4,0.0,neutral or dissatisfied +43732,26131,Female,Loyal Customer,53,Business travel,Business,404,4,4,4,4,5,5,2,4,4,4,4,2,4,4,0,0.0,satisfied +43733,53106,Female,Loyal Customer,49,Business travel,Business,212,2,2,2,2,5,4,4,5,5,5,3,2,5,4,0,0.0,satisfied +43734,55676,Female,Loyal Customer,53,Business travel,Business,2833,4,4,4,4,3,4,4,4,4,4,4,4,4,5,13,1.0,satisfied +43735,116935,Female,Loyal Customer,57,Business travel,Business,3727,5,5,5,5,2,5,5,5,5,5,5,5,5,3,10,6.0,satisfied +43736,3777,Male,Loyal Customer,53,Business travel,Business,1727,1,1,1,1,2,4,4,5,5,5,5,5,5,4,0,1.0,satisfied +43737,1233,Female,Loyal Customer,56,Personal Travel,Eco,354,2,4,4,2,3,4,5,1,1,4,1,5,1,4,35,35.0,neutral or dissatisfied +43738,58467,Female,Loyal Customer,42,Business travel,Business,2796,3,3,3,3,5,5,5,4,4,4,4,4,4,3,3,37.0,satisfied +43739,19312,Female,Loyal Customer,42,Personal Travel,Business,743,3,5,3,4,5,4,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +43740,123955,Male,Loyal Customer,37,Personal Travel,Eco Plus,541,2,5,2,2,3,2,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +43741,97012,Female,Loyal Customer,16,Personal Travel,Eco,359,2,5,2,5,2,2,3,2,5,4,4,5,4,2,70,67.0,neutral or dissatisfied +43742,125482,Female,Loyal Customer,26,Personal Travel,Eco,2860,4,4,4,3,1,4,1,1,3,5,4,5,5,1,16,0.0,satisfied +43743,10699,Male,disloyal Customer,38,Business travel,Business,216,1,1,1,1,4,1,4,4,4,4,5,3,4,4,0,6.0,neutral or dissatisfied +43744,51043,Female,Loyal Customer,32,Personal Travel,Eco,373,1,1,4,3,5,4,5,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +43745,96541,Female,Loyal Customer,9,Personal Travel,Eco,436,3,2,3,3,1,3,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +43746,27876,Female,disloyal Customer,23,Business travel,Eco,1498,3,3,3,3,3,3,3,3,5,2,1,5,3,3,0,0.0,neutral or dissatisfied +43747,24073,Female,Loyal Customer,37,Business travel,Business,2075,4,4,2,4,4,5,4,3,3,3,3,1,3,4,0,0.0,satisfied +43748,8731,Male,Loyal Customer,20,Personal Travel,Eco,227,2,5,2,3,2,2,3,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +43749,50781,Female,Loyal Customer,32,Personal Travel,Eco,199,1,5,1,4,4,1,4,4,3,1,4,3,3,4,0,0.0,neutral or dissatisfied +43750,118027,Male,Loyal Customer,52,Business travel,Business,3135,2,3,2,2,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +43751,66315,Male,Loyal Customer,49,Business travel,Eco,852,2,3,3,3,3,2,3,3,2,3,1,2,1,3,0,0.0,satisfied +43752,79223,Male,disloyal Customer,22,Business travel,Eco,724,3,3,3,3,3,3,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +43753,64992,Male,disloyal Customer,26,Business travel,Eco,247,4,0,4,1,3,4,3,3,4,1,2,3,5,3,0,0.0,neutral or dissatisfied +43754,121622,Female,Loyal Customer,31,Personal Travel,Eco,912,1,4,1,1,1,1,3,1,3,5,5,5,5,1,0,13.0,neutral or dissatisfied +43755,129683,Male,Loyal Customer,43,Business travel,Business,308,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +43756,66676,Male,Loyal Customer,50,Business travel,Business,1518,3,3,4,3,4,5,4,4,4,4,4,5,4,5,24,19.0,satisfied +43757,80031,Female,Loyal Customer,23,Personal Travel,Eco,950,2,3,2,3,5,2,5,5,4,3,3,3,5,5,0,0.0,neutral or dissatisfied +43758,9226,Male,Loyal Customer,27,Business travel,Business,2467,1,4,4,4,3,3,1,3,3,2,2,4,2,3,32,25.0,neutral or dissatisfied +43759,103938,Male,Loyal Customer,60,Business travel,Business,533,5,5,5,5,5,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +43760,58049,Male,Loyal Customer,39,Business travel,Business,589,2,2,2,2,5,5,5,2,2,3,2,3,2,5,3,1.0,satisfied +43761,50702,Male,Loyal Customer,22,Personal Travel,Eco,209,4,3,0,2,2,0,2,2,3,2,2,2,2,2,0,0.0,neutral or dissatisfied +43762,58146,Female,Loyal Customer,48,Personal Travel,Business,925,1,3,1,3,1,2,2,3,5,2,2,2,4,2,306,299.0,neutral or dissatisfied +43763,40539,Male,disloyal Customer,39,Business travel,Eco,517,2,3,2,1,1,2,1,1,3,2,4,4,3,1,66,69.0,neutral or dissatisfied +43764,88710,Female,Loyal Customer,14,Personal Travel,Eco,581,1,4,1,4,1,1,1,1,5,5,4,5,5,1,0,20.0,neutral or dissatisfied +43765,60442,Female,Loyal Customer,45,Business travel,Business,985,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +43766,99535,Female,disloyal Customer,24,Business travel,Eco,808,5,5,5,4,2,5,5,2,4,4,5,3,4,2,13,18.0,satisfied +43767,42427,Female,Loyal Customer,54,Personal Travel,Eco Plus,451,3,4,2,4,3,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +43768,46643,Female,Loyal Customer,65,Business travel,Eco,125,2,1,1,1,1,3,3,2,2,2,2,4,2,4,16,6.0,neutral or dissatisfied +43769,36252,Male,disloyal Customer,40,Business travel,Eco,612,2,4,2,1,5,2,5,5,1,3,5,2,3,5,1,6.0,neutral or dissatisfied +43770,47003,Male,Loyal Customer,38,Personal Travel,Eco Plus,776,2,4,2,2,1,2,3,1,3,3,5,3,5,1,12,34.0,neutral or dissatisfied +43771,81246,Male,disloyal Customer,43,Business travel,Eco,530,2,3,2,2,1,2,1,1,1,3,5,5,4,1,0,0.0,neutral or dissatisfied +43772,53012,Female,Loyal Customer,30,Business travel,Business,2020,1,1,1,1,5,5,5,5,3,5,2,3,5,5,0,24.0,satisfied +43773,72193,Female,Loyal Customer,20,Personal Travel,Eco,594,0,2,0,3,1,2,1,1,2,3,4,1,4,1,0,3.0,satisfied +43774,84453,Female,Loyal Customer,52,Business travel,Business,290,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +43775,113506,Male,Loyal Customer,29,Business travel,Business,3887,3,5,5,5,3,3,3,3,3,4,3,1,4,3,38,32.0,neutral or dissatisfied +43776,119541,Male,Loyal Customer,27,Personal Travel,Eco,759,4,5,4,4,5,4,5,5,4,5,5,3,4,5,40,47.0,neutral or dissatisfied +43777,57745,Female,Loyal Customer,13,Personal Travel,Business,2704,4,3,4,4,2,4,2,2,5,1,5,1,1,2,0,0.0,neutral or dissatisfied +43778,62229,Male,Loyal Customer,59,Personal Travel,Eco,2565,1,4,2,3,2,2,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +43779,54179,Female,Loyal Customer,41,Business travel,Eco,1000,5,5,5,5,5,5,5,5,1,4,4,4,2,5,12,27.0,satisfied +43780,42460,Male,Loyal Customer,34,Personal Travel,Eco,926,1,4,1,5,2,1,2,2,5,2,5,5,4,2,25,0.0,neutral or dissatisfied +43781,125805,Male,Loyal Customer,40,Business travel,Business,920,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +43782,48536,Male,Loyal Customer,57,Business travel,Business,433,5,5,5,5,3,4,3,5,5,5,5,1,5,5,7,23.0,satisfied +43783,49765,Male,Loyal Customer,49,Business travel,Eco,109,2,1,1,1,2,2,2,2,4,3,3,1,4,2,0,0.0,satisfied +43784,86993,Male,Loyal Customer,63,Personal Travel,Eco,907,1,3,1,2,3,1,3,3,2,5,2,4,3,3,8,2.0,neutral or dissatisfied +43785,25353,Female,Loyal Customer,26,Business travel,Business,591,1,1,1,1,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +43786,84943,Female,Loyal Customer,29,Business travel,Business,547,5,5,5,5,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +43787,69983,Male,disloyal Customer,26,Business travel,Business,236,3,2,3,3,5,3,5,5,1,4,3,4,4,5,0,0.0,neutral or dissatisfied +43788,71348,Female,Loyal Customer,28,Personal Travel,Eco,1514,1,4,1,2,1,1,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +43789,95237,Female,Loyal Customer,59,Personal Travel,Eco,239,3,5,3,2,4,4,5,3,3,3,3,3,3,3,26,21.0,neutral or dissatisfied +43790,79082,Male,Loyal Customer,59,Personal Travel,Eco,226,4,1,4,3,3,4,3,3,3,4,3,2,4,3,46,38.0,satisfied +43791,24203,Female,Loyal Customer,48,Business travel,Business,147,1,1,1,1,3,3,3,2,2,2,1,4,2,1,2,7.0,neutral or dissatisfied +43792,76469,Female,disloyal Customer,26,Business travel,Business,534,2,4,1,5,4,1,4,4,3,2,4,3,4,4,0,1.0,neutral or dissatisfied +43793,85721,Female,Loyal Customer,36,Business travel,Business,666,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +43794,18635,Male,Loyal Customer,49,Personal Travel,Eco,190,2,1,2,3,2,2,5,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +43795,67358,Male,Loyal Customer,26,Business travel,Business,3766,5,5,5,5,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +43796,44089,Male,Loyal Customer,51,Business travel,Business,3834,3,3,3,3,3,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +43797,78179,Male,disloyal Customer,44,Business travel,Business,192,1,1,1,1,5,1,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +43798,31386,Male,Loyal Customer,46,Business travel,Business,1981,3,3,3,3,2,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +43799,65479,Female,disloyal Customer,54,Business travel,Business,1303,5,5,5,1,2,5,5,2,3,4,5,4,5,2,0,0.0,satisfied +43800,70018,Male,Loyal Customer,49,Business travel,Business,2732,4,4,2,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +43801,99789,Female,Loyal Customer,46,Business travel,Business,3783,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,4.0,satisfied +43802,55351,Female,Loyal Customer,59,Business travel,Business,413,5,5,4,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +43803,11111,Female,Loyal Customer,8,Personal Travel,Eco,201,4,4,0,2,5,0,5,5,1,4,2,3,3,5,0,0.0,neutral or dissatisfied +43804,30942,Female,disloyal Customer,20,Business travel,Eco,1024,4,4,4,1,4,4,4,4,1,2,5,4,3,4,25,33.0,satisfied +43805,56928,Female,disloyal Customer,25,Business travel,Eco,824,3,3,3,4,3,4,4,3,1,4,3,4,3,4,0,24.0,neutral or dissatisfied +43806,83658,Male,Loyal Customer,43,Business travel,Business,3198,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +43807,2120,Male,disloyal Customer,45,Business travel,Business,404,1,2,2,4,2,1,2,2,5,2,4,4,5,2,17,7.0,neutral or dissatisfied +43808,112673,Male,Loyal Customer,51,Business travel,Business,3535,5,5,5,5,4,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +43809,78974,Female,disloyal Customer,37,Business travel,Business,306,3,3,3,3,1,3,1,1,5,2,5,3,5,1,0,7.0,neutral or dissatisfied +43810,122428,Male,Loyal Customer,41,Business travel,Eco,416,4,4,4,4,4,4,4,4,4,1,5,5,2,4,0,0.0,satisfied +43811,113939,Female,Loyal Customer,46,Business travel,Business,1728,3,3,1,3,4,4,4,2,2,2,2,5,2,5,8,9.0,satisfied +43812,125572,Male,Loyal Customer,13,Personal Travel,Eco,226,5,5,5,3,3,5,3,3,5,2,4,5,3,3,0,0.0,satisfied +43813,66877,Female,Loyal Customer,52,Business travel,Business,2130,4,4,4,4,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +43814,29690,Male,Loyal Customer,40,Business travel,Eco,1542,5,5,5,5,5,5,5,5,4,1,4,1,2,5,0,0.0,satisfied +43815,73013,Female,Loyal Customer,11,Personal Travel,Eco,1035,5,5,5,1,3,5,5,3,5,5,4,3,4,3,0,,satisfied +43816,92746,Female,Loyal Customer,46,Personal Travel,Eco,1276,3,3,2,5,1,3,4,5,5,2,3,5,5,3,0,0.0,neutral or dissatisfied +43817,67558,Male,Loyal Customer,28,Business travel,Business,1205,3,3,3,3,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +43818,53834,Male,Loyal Customer,55,Business travel,Business,140,3,4,4,4,4,3,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +43819,47921,Female,Loyal Customer,47,Personal Travel,Eco,451,2,5,2,3,5,5,5,4,4,2,3,4,4,3,4,9.0,neutral or dissatisfied +43820,45311,Male,Loyal Customer,57,Business travel,Eco,150,1,1,5,5,1,1,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +43821,55698,Male,Loyal Customer,38,Business travel,Business,895,4,1,3,1,4,4,4,4,4,4,4,4,4,3,0,7.0,neutral or dissatisfied +43822,128970,Male,Loyal Customer,59,Personal Travel,Eco,236,3,5,3,5,5,3,2,5,3,5,4,2,4,5,0,0.0,neutral or dissatisfied +43823,48020,Female,Loyal Customer,77,Business travel,Eco Plus,150,2,2,2,2,3,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +43824,1751,Male,Loyal Customer,51,Personal Travel,Eco,364,4,1,4,4,4,4,4,4,4,1,4,4,4,4,0,0.0,satisfied +43825,89904,Male,Loyal Customer,35,Business travel,Business,1416,4,1,1,1,2,2,3,4,4,4,4,4,4,2,0,10.0,neutral or dissatisfied +43826,98187,Male,Loyal Customer,42,Business travel,Business,327,2,5,5,5,1,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +43827,41356,Female,disloyal Customer,14,Personal Travel,Business,913,3,5,3,4,1,3,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +43828,5189,Female,Loyal Customer,55,Business travel,Business,2065,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +43829,106527,Male,Loyal Customer,50,Personal Travel,Eco,271,2,1,2,3,2,2,5,2,2,3,3,3,3,2,27,,neutral or dissatisfied +43830,100902,Female,disloyal Customer,23,Business travel,Business,377,3,2,3,3,5,3,4,5,2,2,3,2,4,5,0,0.0,neutral or dissatisfied +43831,76383,Female,Loyal Customer,72,Business travel,Business,1853,1,2,2,2,1,3,3,1,1,1,1,3,1,1,10,24.0,neutral or dissatisfied +43832,115642,Female,Loyal Customer,38,Business travel,Business,2410,4,4,4,4,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +43833,116865,Female,Loyal Customer,36,Business travel,Business,3470,4,4,4,4,2,4,5,2,2,2,2,4,2,4,36,24.0,satisfied +43834,13655,Female,Loyal Customer,39,Business travel,Business,1711,0,4,0,3,1,3,3,5,5,5,5,5,5,3,0,0.0,satisfied +43835,85182,Male,Loyal Customer,49,Business travel,Eco,874,4,5,5,5,4,4,4,4,1,1,4,3,4,4,27,26.0,neutral or dissatisfied +43836,34417,Male,Loyal Customer,27,Personal Travel,Eco,612,4,4,4,2,3,4,3,3,5,5,4,3,2,3,30,20.0,neutral or dissatisfied +43837,122524,Female,Loyal Customer,68,Personal Travel,Business,500,2,1,2,4,2,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +43838,20249,Female,disloyal Customer,33,Business travel,Eco,179,2,3,2,4,2,2,2,2,2,3,2,3,3,2,0,0.0,neutral or dissatisfied +43839,47957,Female,Loyal Customer,12,Personal Travel,Eco,329,1,2,1,4,5,1,5,5,3,3,4,4,4,5,57,46.0,neutral or dissatisfied +43840,10125,Male,disloyal Customer,24,Business travel,Business,946,5,5,5,5,1,5,1,1,3,4,5,3,5,1,0,0.0,satisfied +43841,51924,Male,Loyal Customer,46,Business travel,Eco Plus,601,2,5,5,5,2,2,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +43842,64519,Male,Loyal Customer,48,Personal Travel,Business,224,3,3,3,4,2,3,3,4,4,3,4,1,4,2,0,4.0,neutral or dissatisfied +43843,117873,Female,Loyal Customer,42,Business travel,Business,2040,2,2,2,2,5,4,5,5,5,5,5,5,5,4,19,41.0,satisfied +43844,60932,Female,Loyal Customer,48,Business travel,Business,3936,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +43845,115479,Female,Loyal Customer,41,Business travel,Business,2520,3,4,4,4,3,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +43846,108443,Female,Loyal Customer,47,Business travel,Business,1444,2,2,2,2,2,5,4,4,4,4,4,5,4,3,27,23.0,satisfied +43847,111958,Female,disloyal Customer,27,Business travel,Business,533,2,1,1,4,5,1,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +43848,35997,Female,disloyal Customer,39,Business travel,Business,474,4,4,4,2,5,4,5,5,5,2,5,5,5,5,0,4.0,neutral or dissatisfied +43849,13310,Female,disloyal Customer,66,Business travel,Eco,448,1,0,0,3,2,0,2,2,3,2,3,1,4,2,4,0.0,neutral or dissatisfied +43850,47120,Female,Loyal Customer,38,Personal Travel,Eco,737,2,5,2,4,4,2,5,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +43851,4417,Male,disloyal Customer,42,Business travel,Business,762,3,3,3,1,2,3,2,2,3,2,5,4,4,2,2,21.0,satisfied +43852,126409,Female,Loyal Customer,25,Business travel,Business,600,5,5,5,5,5,5,5,3,2,4,5,5,5,5,174,179.0,satisfied +43853,44182,Male,Loyal Customer,57,Business travel,Eco,157,4,2,2,2,5,4,5,5,3,2,3,3,2,5,0,0.0,satisfied +43854,25161,Female,disloyal Customer,23,Business travel,Eco,1421,2,2,2,4,3,2,3,3,4,3,3,1,4,3,17,28.0,neutral or dissatisfied +43855,102389,Female,disloyal Customer,22,Business travel,Eco,397,5,0,5,1,3,5,5,3,4,4,5,3,3,3,70,75.0,satisfied +43856,80461,Male,Loyal Customer,57,Business travel,Business,1299,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +43857,10917,Female,Loyal Customer,57,Business travel,Business,2457,1,3,3,3,4,3,4,4,4,4,1,1,4,3,0,0.0,neutral or dissatisfied +43858,115604,Female,Loyal Customer,44,Business travel,Business,337,3,2,2,2,2,3,3,3,3,3,3,4,3,2,25,22.0,neutral or dissatisfied +43859,63101,Female,disloyal Customer,9,Business travel,Eco,967,1,1,1,2,4,1,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +43860,127808,Male,Loyal Customer,41,Business travel,Business,1997,3,3,3,3,1,2,3,3,3,3,3,2,3,3,57,49.0,neutral or dissatisfied +43861,35671,Female,Loyal Customer,41,Business travel,Eco,2586,4,1,1,1,4,4,4,1,5,4,1,4,5,4,0,0.0,satisfied +43862,103257,Male,Loyal Customer,52,Business travel,Business,3623,4,4,4,4,3,4,4,5,5,5,5,5,5,4,42,44.0,satisfied +43863,62002,Female,Loyal Customer,57,Business travel,Business,2586,1,1,1,1,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +43864,3930,Male,Loyal Customer,25,Personal Travel,Eco Plus,213,3,5,3,1,5,3,5,5,4,2,3,4,5,5,0,0.0,neutral or dissatisfied +43865,111371,Male,disloyal Customer,35,Business travel,Business,1050,2,2,2,3,4,2,4,4,3,4,5,3,4,4,19,20.0,neutral or dissatisfied +43866,119672,Female,disloyal Customer,28,Business travel,Eco Plus,507,2,2,2,3,5,2,5,5,4,4,2,2,3,5,0,0.0,neutral or dissatisfied +43867,46465,Female,disloyal Customer,26,Business travel,Business,73,1,2,1,3,4,1,4,4,1,1,3,1,4,4,0,0.0,neutral or dissatisfied +43868,30092,Female,Loyal Customer,61,Personal Travel,Eco,82,3,5,3,3,2,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +43869,5909,Female,Loyal Customer,41,Business travel,Eco,108,5,2,2,2,5,5,5,5,3,4,4,3,1,5,0,0.0,satisfied +43870,100337,Male,Loyal Customer,65,Business travel,Eco,611,2,3,5,5,2,2,2,2,3,1,5,4,4,2,11,6.0,satisfied +43871,85679,Male,Loyal Customer,56,Business travel,Business,1547,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +43872,30840,Female,Loyal Customer,31,Business travel,Business,1514,5,5,5,5,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +43873,24595,Female,Loyal Customer,32,Business travel,Business,666,3,3,4,3,3,3,3,3,5,1,1,5,2,3,0,2.0,satisfied +43874,11006,Male,Loyal Customer,30,Business travel,Business,1889,5,5,5,5,5,5,5,5,2,3,3,4,2,5,0,0.0,satisfied +43875,69180,Male,Loyal Customer,32,Personal Travel,Eco,187,3,5,3,3,4,3,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +43876,18448,Male,Loyal Customer,38,Personal Travel,Business,190,2,5,2,3,3,4,5,1,1,2,1,3,1,4,1,0.0,neutral or dissatisfied +43877,43850,Male,Loyal Customer,30,Business travel,Business,3491,3,3,3,3,4,4,4,4,4,1,2,2,3,4,0,0.0,satisfied +43878,30445,Male,Loyal Customer,70,Personal Travel,Business,991,2,4,2,1,2,4,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +43879,88666,Female,Loyal Customer,69,Personal Travel,Eco,270,5,1,4,3,3,2,3,1,1,4,1,3,1,3,5,0.0,satisfied +43880,53105,Female,Loyal Customer,34,Business travel,Eco Plus,1628,5,3,5,3,5,5,5,5,4,1,4,5,4,5,0,7.0,satisfied +43881,119462,Male,Loyal Customer,54,Business travel,Business,2480,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +43882,63224,Female,Loyal Customer,42,Business travel,Business,447,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +43883,83792,Male,disloyal Customer,47,Business travel,Business,425,5,5,5,1,5,5,2,5,5,5,4,5,5,5,0,0.0,satisfied +43884,2591,Female,Loyal Customer,66,Personal Travel,Eco,227,4,4,4,2,3,5,4,4,4,4,4,4,4,3,15,27.0,neutral or dissatisfied +43885,4302,Male,disloyal Customer,45,Business travel,Business,502,1,1,1,5,1,1,1,1,5,2,4,3,4,1,5,0.0,neutral or dissatisfied +43886,36175,Male,Loyal Customer,20,Personal Travel,Eco,1674,3,3,3,3,4,3,4,4,2,2,4,1,4,4,5,0.0,neutral or dissatisfied +43887,57886,Male,Loyal Customer,47,Business travel,Business,305,0,0,0,4,5,5,5,1,1,1,1,5,1,5,0,0.0,satisfied +43888,60898,Female,Loyal Customer,44,Personal Travel,Eco,420,1,5,1,3,3,3,5,4,4,1,3,4,4,3,5,0.0,neutral or dissatisfied +43889,40362,Female,disloyal Customer,37,Business travel,Eco,1250,3,3,3,3,3,5,5,4,4,4,4,5,1,5,179,165.0,neutral or dissatisfied +43890,34339,Female,disloyal Customer,26,Business travel,Eco,846,3,4,4,3,2,4,2,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +43891,4670,Male,disloyal Customer,41,Business travel,Business,364,4,4,4,2,4,4,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +43892,5985,Female,Loyal Customer,42,Business travel,Business,672,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +43893,95535,Female,Loyal Customer,16,Personal Travel,Eco Plus,233,2,5,0,2,2,0,2,2,5,1,4,5,5,2,0,1.0,neutral or dissatisfied +43894,50193,Female,disloyal Customer,40,Business travel,Business,86,1,1,1,4,1,1,2,1,5,5,2,3,2,1,0,0.0,neutral or dissatisfied +43895,98957,Female,Loyal Customer,37,Business travel,Eco,569,3,5,3,3,3,3,3,3,2,4,2,3,3,3,72,66.0,neutral or dissatisfied +43896,47277,Female,Loyal Customer,40,Business travel,Business,2940,5,5,5,5,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +43897,47401,Male,Loyal Customer,51,Business travel,Eco,558,5,1,2,1,5,5,5,5,1,1,3,1,2,5,0,0.0,satisfied +43898,37880,Male,disloyal Customer,26,Business travel,Eco,937,2,2,2,3,5,2,5,5,4,1,2,2,2,5,0,0.0,neutral or dissatisfied +43899,27495,Male,Loyal Customer,50,Business travel,Eco,587,5,4,5,4,5,5,5,5,4,5,4,2,2,5,0,6.0,satisfied +43900,93028,Female,disloyal Customer,25,Business travel,Business,436,2,4,2,3,2,2,2,2,2,1,4,2,3,2,11,1.0,neutral or dissatisfied +43901,98455,Female,Loyal Customer,48,Business travel,Business,210,5,5,5,5,2,4,5,4,4,4,4,4,4,3,5,15.0,satisfied +43902,67744,Male,Loyal Customer,22,Business travel,Business,1235,5,5,5,5,3,3,3,3,3,3,4,5,4,3,0,0.0,satisfied +43903,127867,Female,disloyal Customer,27,Business travel,Business,1276,5,5,5,2,5,5,2,5,5,3,4,3,4,5,0,0.0,satisfied +43904,84182,Male,Loyal Customer,53,Business travel,Business,432,1,1,5,1,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +43905,17591,Female,disloyal Customer,9,Business travel,Eco,852,4,4,4,3,3,4,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +43906,110368,Female,Loyal Customer,52,Business travel,Business,919,3,3,3,3,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +43907,82474,Male,Loyal Customer,30,Personal Travel,Eco,502,0,1,0,2,4,0,4,4,2,1,3,3,2,4,0,0.0,satisfied +43908,38178,Female,Loyal Customer,11,Personal Travel,Eco,1249,4,5,4,2,1,4,1,1,5,2,4,5,4,1,0,0.0,satisfied +43909,109579,Male,Loyal Customer,52,Personal Travel,Eco,834,5,5,5,4,3,5,3,3,4,5,5,3,4,3,0,0.0,satisfied +43910,117630,Male,Loyal Customer,52,Personal Travel,Eco,347,4,4,3,3,3,3,3,3,4,3,4,4,5,3,30,25.0,neutral or dissatisfied +43911,102363,Female,disloyal Customer,40,Business travel,Business,397,1,1,1,3,3,1,2,3,2,5,3,3,4,3,34,43.0,neutral or dissatisfied +43912,32479,Male,Loyal Customer,33,Business travel,Eco,101,3,4,5,4,3,3,3,3,3,3,4,4,3,3,2,9.0,neutral or dissatisfied +43913,46719,Female,Loyal Customer,11,Personal Travel,Eco,125,3,2,3,4,2,3,2,2,2,1,4,2,4,2,27,30.0,neutral or dissatisfied +43914,102428,Female,Loyal Customer,24,Personal Travel,Eco,407,4,2,4,4,3,4,5,3,1,1,3,4,3,3,0,0.0,satisfied +43915,48139,Female,Loyal Customer,39,Business travel,Eco,236,5,1,5,5,5,5,5,5,3,3,5,5,1,5,0,0.0,satisfied +43916,87008,Male,Loyal Customer,36,Personal Travel,Eco,907,2,4,1,4,3,1,3,3,3,3,4,5,5,3,1,0.0,neutral or dissatisfied +43917,116693,Female,Loyal Customer,44,Business travel,Eco Plus,446,3,3,3,3,5,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +43918,48112,Female,Loyal Customer,37,Business travel,Business,2622,5,5,5,5,3,2,3,4,4,5,4,2,4,2,0,0.0,satisfied +43919,127061,Male,Loyal Customer,30,Business travel,Business,646,1,3,3,3,1,1,1,1,1,3,2,4,2,1,2,0.0,neutral or dissatisfied +43920,69791,Male,disloyal Customer,28,Business travel,Business,1055,2,2,2,3,5,2,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +43921,128646,Male,Loyal Customer,51,Business travel,Business,1923,2,2,2,2,4,5,5,4,4,3,4,3,4,3,0,0.0,satisfied +43922,62000,Female,disloyal Customer,55,Business travel,Eco,712,3,3,3,2,2,3,2,2,3,5,3,4,2,2,0,0.0,neutral or dissatisfied +43923,88694,Female,Loyal Customer,22,Personal Travel,Eco,406,3,5,3,2,2,3,2,2,1,2,2,5,5,2,2,0.0,neutral or dissatisfied +43924,32947,Female,Loyal Customer,8,Personal Travel,Eco,216,3,0,3,2,1,3,1,1,3,3,4,5,4,1,4,8.0,neutral or dissatisfied +43925,80092,Male,Loyal Customer,20,Personal Travel,Eco Plus,950,2,3,2,2,1,2,1,1,3,4,5,2,4,1,0,0.0,neutral or dissatisfied +43926,1330,Female,Loyal Customer,41,Business travel,Business,134,3,4,3,3,3,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +43927,92194,Male,Loyal Customer,55,Business travel,Business,2079,1,1,1,1,5,2,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +43928,40162,Male,Loyal Customer,51,Personal Travel,Business,387,1,5,1,1,4,4,1,3,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +43929,114416,Female,Loyal Customer,51,Business travel,Business,404,4,4,4,4,5,4,4,4,4,5,4,5,4,4,72,76.0,satisfied +43930,114341,Female,Loyal Customer,29,Personal Travel,Eco,862,4,4,4,2,3,4,3,3,5,4,4,3,4,3,17,4.0,neutral or dissatisfied +43931,80523,Female,Loyal Customer,25,Business travel,Eco Plus,1749,1,5,5,5,1,1,2,1,2,3,2,1,3,1,44,31.0,neutral or dissatisfied +43932,27391,Male,disloyal Customer,25,Business travel,Eco,671,2,2,2,4,2,2,2,2,4,5,4,3,3,2,21,3.0,neutral or dissatisfied +43933,21588,Male,disloyal Customer,20,Business travel,Eco,780,4,3,3,3,3,3,3,3,3,1,2,3,1,3,0,0.0,satisfied +43934,88362,Male,Loyal Customer,57,Business travel,Business,3403,1,1,1,1,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +43935,111777,Male,Loyal Customer,45,Business travel,Eco,1620,2,2,2,2,1,2,1,1,3,3,3,4,4,1,47,55.0,neutral or dissatisfied +43936,37262,Female,Loyal Customer,25,Business travel,Eco,1010,0,5,0,3,3,0,5,3,1,4,5,2,1,3,0,0.0,satisfied +43937,93189,Male,Loyal Customer,42,Business travel,Business,2899,2,2,3,2,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +43938,114026,Female,disloyal Customer,25,Business travel,Eco Plus,1750,2,3,2,3,2,2,2,2,1,3,2,3,4,2,6,3.0,neutral or dissatisfied +43939,17798,Male,disloyal Customer,28,Business travel,Eco,1214,2,2,2,2,4,2,4,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +43940,39724,Male,Loyal Customer,25,Business travel,Business,2079,1,1,1,1,4,4,3,4,4,3,2,2,3,4,0,0.0,satisfied +43941,14056,Male,Loyal Customer,42,Business travel,Business,141,2,2,2,2,3,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +43942,47058,Female,Loyal Customer,22,Business travel,Business,2643,5,5,5,5,4,4,4,4,3,3,2,4,5,4,0,0.0,satisfied +43943,18470,Male,Loyal Customer,37,Business travel,Eco,192,5,4,5,4,5,5,5,5,5,4,5,5,5,5,0,3.0,satisfied +43944,128813,Female,disloyal Customer,29,Business travel,Business,1267,4,5,5,4,5,2,2,4,5,5,4,2,3,2,152,146.0,satisfied +43945,60821,Female,Loyal Customer,46,Personal Travel,Eco,455,3,2,3,4,3,3,4,4,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +43946,17098,Female,Loyal Customer,36,Personal Travel,Eco,466,1,1,2,2,1,2,1,1,1,5,3,3,2,1,61,75.0,neutral or dissatisfied +43947,110176,Male,Loyal Customer,56,Personal Travel,Eco,869,1,2,1,2,5,1,5,5,3,1,2,2,3,5,0,10.0,neutral or dissatisfied +43948,116230,Male,Loyal Customer,20,Personal Travel,Eco,404,2,4,2,3,3,2,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +43949,106369,Female,Loyal Customer,24,Business travel,Business,1624,3,1,1,1,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +43950,104775,Male,disloyal Customer,50,Business travel,Business,587,2,3,3,3,1,2,1,1,5,4,5,5,4,1,53,47.0,neutral or dissatisfied +43951,35119,Male,disloyal Customer,23,Business travel,Eco,944,5,5,5,1,1,5,1,1,3,4,4,2,5,1,0,0.0,satisfied +43952,74176,Female,Loyal Customer,37,Personal Travel,Eco,641,2,4,2,1,3,2,3,3,3,3,5,5,4,3,43,47.0,neutral or dissatisfied +43953,43118,Male,Loyal Customer,51,Personal Travel,Eco,173,2,1,2,4,2,2,2,2,1,4,4,1,3,2,56,51.0,neutral or dissatisfied +43954,80770,Female,Loyal Customer,55,Personal Travel,Eco,440,2,5,5,1,2,4,5,5,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +43955,42737,Female,Loyal Customer,16,Personal Travel,Eco,536,2,4,2,4,2,2,2,2,5,5,4,4,4,2,1,11.0,neutral or dissatisfied +43956,71578,Male,disloyal Customer,20,Business travel,Business,1182,5,0,5,4,1,5,1,1,4,2,4,3,5,1,0,0.0,satisfied +43957,37854,Female,Loyal Customer,30,Business travel,Eco,937,4,3,4,3,4,4,4,4,4,2,4,3,1,4,0,0.0,satisfied +43958,123352,Male,Loyal Customer,26,Business travel,Business,644,1,1,1,1,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +43959,125617,Female,disloyal Customer,20,Business travel,Eco,759,2,2,2,3,1,2,1,1,2,4,4,2,4,1,0,0.0,neutral or dissatisfied +43960,27192,Female,Loyal Customer,30,Business travel,Eco Plus,2640,1,2,2,2,1,1,1,3,5,4,4,1,3,1,0,6.0,neutral or dissatisfied +43961,26776,Male,Loyal Customer,17,Business travel,Business,1199,2,2,5,2,4,4,4,4,3,5,2,4,5,4,2,0.0,satisfied +43962,61014,Male,Loyal Customer,59,Business travel,Business,3365,1,1,1,1,2,2,2,4,5,4,5,2,3,2,16,8.0,satisfied +43963,71864,Male,Loyal Customer,36,Business travel,Business,1731,2,2,2,2,2,4,3,5,5,5,5,1,5,1,0,0.0,satisfied +43964,3768,Male,Loyal Customer,53,Business travel,Business,599,3,3,3,3,2,4,5,5,5,5,5,4,5,4,28,55.0,satisfied +43965,127337,Male,disloyal Customer,34,Business travel,Business,507,4,4,4,1,5,4,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +43966,121416,Female,Loyal Customer,36,Business travel,Business,257,3,3,3,3,5,5,4,5,5,5,5,4,5,4,4,6.0,satisfied +43967,129464,Male,disloyal Customer,15,Business travel,Eco,2704,3,3,3,4,1,3,2,1,2,1,4,3,3,1,18,0.0,neutral or dissatisfied +43968,89874,Male,Loyal Customer,39,Business travel,Business,1306,5,5,5,5,3,4,4,4,4,4,4,3,4,4,62,38.0,satisfied +43969,47443,Female,Loyal Customer,38,Business travel,Business,3829,1,1,0,4,5,4,4,4,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +43970,119506,Male,disloyal Customer,42,Business travel,Business,814,3,3,3,1,5,3,1,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +43971,62272,Male,Loyal Customer,50,Business travel,Business,414,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,6.0,satisfied +43972,82096,Male,Loyal Customer,58,Business travel,Business,876,1,1,1,1,3,1,4,5,5,5,5,5,5,2,1,3.0,satisfied +43973,89579,Male,disloyal Customer,22,Business travel,Business,1010,4,1,4,1,2,4,2,2,3,5,5,4,4,2,8,0.0,satisfied +43974,64410,Male,Loyal Customer,55,Business travel,Business,1172,1,1,1,1,2,4,4,5,5,5,5,4,5,5,11,0.0,satisfied +43975,15062,Female,Loyal Customer,64,Personal Travel,Eco,627,4,2,4,4,4,1,5,4,2,3,3,5,3,5,142,146.0,neutral or dissatisfied +43976,4090,Female,Loyal Customer,38,Personal Travel,Business,427,2,4,3,4,4,3,4,4,4,3,4,1,4,4,17,16.0,neutral or dissatisfied +43977,1218,Male,Loyal Customer,10,Personal Travel,Eco,247,3,5,3,2,1,3,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +43978,125521,Female,Loyal Customer,50,Business travel,Business,226,0,1,1,1,3,5,4,3,3,3,5,4,3,3,0,0.0,satisfied +43979,61951,Male,Loyal Customer,30,Business travel,Business,2052,3,3,4,3,3,3,3,3,3,3,2,2,4,3,31,16.0,neutral or dissatisfied +43980,128541,Male,disloyal Customer,61,Business travel,Business,338,4,4,4,5,5,4,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +43981,28455,Female,Loyal Customer,30,Business travel,Business,2588,1,1,1,1,5,3,3,2,2,4,2,3,5,3,0,0.0,satisfied +43982,63962,Female,Loyal Customer,16,Personal Travel,Eco,1212,3,3,3,3,2,3,2,2,1,1,2,4,3,2,0,0.0,neutral or dissatisfied +43983,28974,Female,Loyal Customer,24,Business travel,Business,605,5,5,5,5,4,4,4,4,1,2,5,3,4,4,0,0.0,satisfied +43984,129137,Female,Loyal Customer,40,Business travel,Business,679,2,2,2,2,3,5,5,5,5,5,5,5,5,5,6,12.0,satisfied +43985,79974,Female,Loyal Customer,22,Business travel,Business,3439,2,4,5,5,2,3,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +43986,58053,Female,Loyal Customer,58,Business travel,Business,3610,5,5,5,5,4,4,4,4,4,4,4,5,4,3,114,106.0,satisfied +43987,31864,Female,Loyal Customer,23,Business travel,Business,2603,1,1,1,1,4,4,4,4,2,3,5,1,5,4,0,0.0,satisfied +43988,69947,Male,disloyal Customer,29,Business travel,Eco,1205,2,2,2,4,2,2,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +43989,12461,Male,Loyal Customer,32,Personal Travel,Eco,285,3,5,3,2,2,3,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +43990,99505,Female,Loyal Customer,52,Personal Travel,Eco,283,1,4,5,3,5,5,5,4,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +43991,109900,Female,Loyal Customer,35,Business travel,Eco,1092,5,5,5,5,5,5,5,5,3,2,3,4,2,5,1,0.0,satisfied +43992,109857,Female,Loyal Customer,51,Business travel,Business,2506,4,4,4,4,4,5,4,4,4,4,4,4,4,3,55,56.0,satisfied +43993,74048,Female,Loyal Customer,49,Personal Travel,Eco,1194,4,5,4,2,3,3,5,4,4,4,4,3,4,3,2,7.0,neutral or dissatisfied +43994,81844,Female,Loyal Customer,48,Personal Travel,Eco,1306,1,4,1,1,4,4,4,1,1,1,3,5,1,5,15,9.0,neutral or dissatisfied +43995,57593,Male,Loyal Customer,58,Business travel,Business,1597,1,1,5,1,5,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +43996,109482,Female,disloyal Customer,18,Business travel,Eco,920,1,1,1,2,3,1,3,3,3,4,5,3,5,3,18,0.0,neutral or dissatisfied +43997,23181,Male,Loyal Customer,12,Personal Travel,Eco,300,2,5,2,5,3,2,3,3,4,5,4,3,5,3,0,7.0,neutral or dissatisfied +43998,60529,Male,Loyal Customer,19,Personal Travel,Eco,862,2,5,2,4,4,2,2,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +43999,126896,Male,Loyal Customer,39,Business travel,Business,2296,2,2,4,2,4,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +44000,81501,Female,Loyal Customer,55,Personal Travel,Eco,528,3,5,3,4,3,1,5,1,1,3,1,5,1,5,0,83.0,neutral or dissatisfied +44001,128410,Male,Loyal Customer,28,Business travel,Eco,651,1,3,3,3,1,1,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +44002,27583,Female,Loyal Customer,20,Personal Travel,Eco,1050,2,4,2,3,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +44003,56222,Female,disloyal Customer,10,Business travel,Eco,883,3,4,4,3,1,3,1,1,2,4,4,1,3,1,0,0.0,neutral or dissatisfied +44004,65640,Male,Loyal Customer,64,Business travel,Business,3423,4,4,4,4,3,4,5,5,5,5,5,5,5,3,11,7.0,satisfied +44005,87652,Male,Loyal Customer,41,Business travel,Business,606,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +44006,56691,Male,Loyal Customer,13,Personal Travel,Eco,1023,5,5,5,2,3,5,3,3,5,5,3,3,2,3,3,0.0,satisfied +44007,26282,Male,Loyal Customer,51,Personal Travel,Eco,859,4,5,4,3,2,4,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +44008,37733,Female,Loyal Customer,33,Personal Travel,Eco,1010,3,3,3,2,5,3,5,5,4,1,2,4,4,5,0,0.0,neutral or dissatisfied +44009,48991,Female,disloyal Customer,38,Business travel,Eco,109,4,0,4,1,5,4,5,5,2,2,2,2,1,5,0,0.0,neutral or dissatisfied +44010,4211,Female,Loyal Customer,48,Business travel,Business,2963,2,3,3,3,1,3,3,2,2,2,2,3,2,2,13,53.0,neutral or dissatisfied +44011,81670,Female,Loyal Customer,63,Business travel,Business,907,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,32.0,satisfied +44012,6945,Male,Loyal Customer,42,Business travel,Eco,588,3,4,4,4,3,3,3,3,3,4,3,2,4,3,14,15.0,neutral or dissatisfied +44013,13224,Female,Loyal Customer,51,Business travel,Business,2084,1,1,1,1,3,1,1,4,4,4,4,2,4,1,0,0.0,satisfied +44014,126692,Female,Loyal Customer,43,Business travel,Business,2402,1,1,1,1,2,4,5,5,5,5,5,3,5,5,5,0.0,satisfied +44015,42332,Male,Loyal Customer,44,Personal Travel,Eco,834,3,5,3,1,4,3,4,4,4,2,4,4,4,4,5,6.0,neutral or dissatisfied +44016,97505,Male,Loyal Customer,36,Personal Travel,Eco,756,2,4,3,1,1,3,1,1,5,2,5,5,4,1,92,91.0,neutral or dissatisfied +44017,42406,Female,disloyal Customer,46,Business travel,Eco Plus,834,2,2,2,5,5,2,5,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +44018,60507,Female,Loyal Customer,30,Personal Travel,Eco,862,3,4,3,3,2,3,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +44019,551,Female,Loyal Customer,44,Business travel,Business,3447,0,5,0,1,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +44020,81895,Female,Loyal Customer,39,Business travel,Business,2191,4,4,4,4,5,5,4,5,5,5,5,3,5,3,15,0.0,satisfied +44021,61735,Male,Loyal Customer,55,Business travel,Eco,1064,1,5,5,5,1,1,1,1,1,5,4,1,3,1,30,36.0,neutral or dissatisfied +44022,103251,Male,Loyal Customer,52,Personal Travel,Eco,667,1,4,1,3,4,1,5,4,3,2,4,3,5,4,19,10.0,neutral or dissatisfied +44023,17544,Male,Loyal Customer,24,Business travel,Eco,970,0,5,0,1,5,0,1,5,5,5,3,1,3,5,0,0.0,satisfied +44024,37359,Male,disloyal Customer,13,Business travel,Eco,944,4,4,4,4,2,4,2,2,1,5,5,2,4,2,0,0.0,satisfied +44025,126935,Female,Loyal Customer,26,Business travel,Business,651,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +44026,83171,Female,Loyal Customer,39,Business travel,Eco Plus,1127,3,3,3,3,3,3,3,3,3,5,3,3,3,3,0,0.0,neutral or dissatisfied +44027,20362,Male,Loyal Customer,35,Business travel,Business,2763,4,2,2,2,4,3,3,4,4,4,4,3,4,3,14,8.0,neutral or dissatisfied +44028,47309,Female,Loyal Customer,53,Business travel,Business,2772,1,1,2,1,4,2,4,4,4,4,4,4,4,1,0,0.0,satisfied +44029,16583,Male,Loyal Customer,49,Personal Travel,Eco,872,2,2,2,3,3,2,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +44030,108201,Male,Loyal Customer,28,Personal Travel,Eco Plus,1166,0,3,0,3,1,0,4,1,2,1,3,3,3,1,7,0.0,satisfied +44031,107860,Female,disloyal Customer,72,Business travel,Business,228,1,1,1,1,1,1,1,1,5,4,4,5,4,1,12,15.0,neutral or dissatisfied +44032,124927,Male,Loyal Customer,69,Personal Travel,Eco,728,1,3,1,3,5,1,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +44033,14048,Female,Loyal Customer,61,Personal Travel,Eco Plus,106,2,4,0,4,4,5,5,1,1,0,1,4,1,5,0,0.0,neutral or dissatisfied +44034,29945,Female,Loyal Customer,51,Business travel,Eco,234,1,1,1,1,2,3,4,1,1,1,1,4,1,4,113,112.0,neutral or dissatisfied +44035,124839,Male,Loyal Customer,59,Personal Travel,Eco,280,3,4,3,2,4,3,1,4,3,3,5,4,5,4,0,101.0,neutral or dissatisfied +44036,14624,Female,Loyal Customer,37,Business travel,Eco Plus,450,1,5,5,5,1,1,1,1,4,4,3,3,4,1,0,0.0,neutral or dissatisfied +44037,113843,Female,Loyal Customer,48,Business travel,Business,1334,2,2,5,2,5,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +44038,59273,Male,Loyal Customer,13,Personal Travel,Eco,4243,4,0,5,3,5,2,5,2,4,3,1,5,2,5,0,0.0,neutral or dissatisfied +44039,72587,Female,Loyal Customer,39,Business travel,Business,529,3,1,1,1,2,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +44040,33279,Female,Loyal Customer,16,Personal Travel,Eco Plus,163,4,3,4,3,1,4,1,1,2,5,4,2,4,1,0,1.0,neutral or dissatisfied +44041,24502,Female,Loyal Customer,13,Personal Travel,Eco,481,4,4,4,5,2,4,2,2,4,1,5,2,5,2,1,0.0,neutral or dissatisfied +44042,103899,Female,disloyal Customer,14,Business travel,Business,1072,0,0,0,2,4,0,4,4,3,3,5,5,4,4,12,3.0,satisfied +44043,103318,Female,Loyal Customer,53,Business travel,Eco,1139,3,4,4,4,4,2,2,3,3,3,3,2,3,4,49,54.0,neutral or dissatisfied +44044,125571,Male,Loyal Customer,38,Personal Travel,Eco,226,3,5,3,3,3,3,2,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +44045,79838,Female,Loyal Customer,41,Business travel,Business,2576,3,3,3,3,2,2,2,5,5,5,5,2,4,2,126,143.0,satisfied +44046,34193,Female,Loyal Customer,53,Personal Travel,Eco,1189,2,4,2,2,2,3,4,2,2,2,2,5,2,3,11,6.0,neutral or dissatisfied +44047,58596,Male,disloyal Customer,43,Business travel,Eco,334,2,0,2,1,2,2,2,2,2,1,5,5,1,2,0,0.0,neutral or dissatisfied +44048,31680,Male,disloyal Customer,30,Business travel,Eco,846,4,4,4,4,3,4,3,3,1,4,3,3,4,3,0,0.0,neutral or dissatisfied +44049,38542,Female,Loyal Customer,72,Business travel,Business,2586,2,3,3,3,5,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +44050,114567,Female,Loyal Customer,35,Personal Travel,Business,390,2,5,2,3,5,2,2,4,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +44051,125015,Female,Loyal Customer,63,Personal Travel,Eco,184,3,3,3,3,3,3,3,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +44052,87082,Female,Loyal Customer,54,Business travel,Eco,645,1,2,2,2,1,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +44053,85901,Female,Loyal Customer,49,Business travel,Business,2577,4,4,4,4,2,5,5,3,3,3,3,5,3,4,26,29.0,satisfied +44054,101784,Female,disloyal Customer,30,Business travel,Business,1521,1,1,1,3,2,1,2,2,3,4,4,3,4,2,45,18.0,neutral or dissatisfied +44055,124038,Male,Loyal Customer,33,Personal Travel,Eco,184,2,4,2,2,5,2,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +44056,36759,Male,Loyal Customer,21,Business travel,Business,2588,5,5,5,5,3,3,3,5,3,4,3,3,5,3,54,49.0,satisfied +44057,128817,Female,disloyal Customer,46,Business travel,Business,846,5,5,5,1,2,5,2,2,4,2,5,5,5,2,0,,satisfied +44058,41757,Female,Loyal Customer,65,Business travel,Business,230,3,2,2,2,1,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +44059,10878,Female,Loyal Customer,51,Business travel,Eco,308,2,2,4,2,2,3,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +44060,124418,Female,Loyal Customer,32,Business travel,Eco,1262,2,5,5,5,2,2,2,2,2,5,2,4,3,2,0,0.0,neutral or dissatisfied +44061,56158,Female,Loyal Customer,34,Business travel,Business,1400,3,2,5,5,5,2,1,3,3,3,3,3,3,1,57,60.0,neutral or dissatisfied +44062,54704,Female,disloyal Customer,26,Business travel,Eco,565,1,3,1,4,2,1,2,2,4,5,4,4,3,2,18,17.0,neutral or dissatisfied +44063,38748,Female,Loyal Customer,45,Business travel,Business,2665,5,3,5,5,5,5,1,5,5,5,5,5,5,2,0,0.0,satisfied +44064,106297,Female,disloyal Customer,22,Business travel,Eco,998,1,1,1,1,2,1,2,2,3,4,5,5,5,2,14,1.0,neutral or dissatisfied +44065,17754,Female,Loyal Customer,25,Personal Travel,Eco,383,4,3,4,4,4,4,4,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +44066,69542,Female,Loyal Customer,46,Business travel,Business,2475,1,1,1,1,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +44067,97720,Female,Loyal Customer,43,Business travel,Business,1682,5,1,2,2,1,3,4,5,5,4,5,2,5,2,44,38.0,neutral or dissatisfied +44068,103830,Female,disloyal Customer,28,Business travel,Eco,869,2,2,2,3,5,2,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +44069,48432,Male,Loyal Customer,44,Business travel,Eco,844,4,1,1,1,4,4,4,4,2,3,3,5,2,4,0,0.0,satisfied +44070,90399,Female,Loyal Customer,40,Personal Travel,Business,406,3,4,3,1,3,4,4,4,4,3,4,3,4,3,64,60.0,neutral or dissatisfied +44071,20513,Male,Loyal Customer,35,Personal Travel,Eco Plus,139,3,4,3,5,1,3,1,1,4,4,4,4,5,1,53,62.0,neutral or dissatisfied +44072,51611,Male,Loyal Customer,30,Business travel,Business,370,4,4,4,4,5,4,5,5,2,3,5,5,5,5,0,0.0,satisfied +44073,37629,Female,Loyal Customer,22,Personal Travel,Eco,1144,3,4,3,5,4,3,4,4,4,5,5,5,4,4,14,15.0,neutral or dissatisfied +44074,8611,Male,disloyal Customer,25,Business travel,Eco,1371,4,4,4,3,3,4,3,3,2,3,3,1,3,3,0,4.0,neutral or dissatisfied +44075,105301,Male,disloyal Customer,41,Business travel,Eco,567,4,0,4,3,2,4,2,2,4,4,4,5,4,2,26,35.0,neutral or dissatisfied +44076,6108,Female,Loyal Customer,30,Personal Travel,Business,409,3,5,3,3,5,3,4,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +44077,11861,Female,disloyal Customer,28,Business travel,Eco,1042,2,2,2,4,3,2,3,3,4,5,4,1,4,3,12,2.0,neutral or dissatisfied +44078,127439,Female,Loyal Customer,27,Personal Travel,Eco,868,4,4,4,5,2,4,2,2,4,5,2,5,1,2,13,13.0,neutral or dissatisfied +44079,129080,Male,Loyal Customer,45,Business travel,Business,2218,3,2,3,3,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +44080,5266,Female,Loyal Customer,55,Personal Travel,Eco,293,1,4,1,1,3,5,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +44081,95821,Male,Loyal Customer,40,Business travel,Business,1428,4,2,4,4,4,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +44082,112282,Male,Loyal Customer,20,Personal Travel,Eco,1447,3,2,4,3,3,4,3,3,4,1,4,1,3,3,33,12.0,neutral or dissatisfied +44083,94792,Male,Loyal Customer,63,Business travel,Business,248,0,0,0,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +44084,34072,Male,Loyal Customer,36,Personal Travel,Eco,1674,4,2,4,3,3,4,3,3,3,1,4,2,4,3,2,0.0,neutral or dissatisfied +44085,88545,Female,Loyal Customer,21,Personal Travel,Eco,545,3,1,3,4,4,3,2,4,2,1,4,2,4,4,17,20.0,neutral or dissatisfied +44086,54333,Female,Loyal Customer,48,Personal Travel,Eco,1597,1,5,1,1,4,5,4,3,3,1,4,3,3,4,87,64.0,neutral or dissatisfied +44087,2832,Female,Loyal Customer,54,Business travel,Business,1661,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0,9.0,satisfied +44088,48141,Female,disloyal Customer,59,Business travel,Eco,192,1,0,0,4,1,0,1,1,5,4,3,3,1,1,41,40.0,neutral or dissatisfied +44089,64537,Male,disloyal Customer,27,Business travel,Business,551,4,4,4,2,3,4,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +44090,800,Male,disloyal Customer,25,Business travel,Business,309,3,3,3,2,3,3,2,3,1,2,3,4,2,3,0,0.0,neutral or dissatisfied +44091,87165,Male,disloyal Customer,27,Business travel,Business,946,4,4,4,2,5,4,5,5,5,2,5,5,5,5,0,0.0,satisfied +44092,13151,Male,Loyal Customer,20,Personal Travel,Eco,595,3,1,3,3,2,3,2,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +44093,90152,Male,disloyal Customer,30,Business travel,Eco,957,2,2,2,4,1,2,1,1,4,3,1,5,5,1,0,0.0,neutral or dissatisfied +44094,74770,Male,Loyal Customer,49,Personal Travel,Eco,1235,4,4,4,1,3,4,3,3,3,2,4,3,4,3,0,,satisfied +44095,115990,Female,Loyal Customer,28,Personal Travel,Eco,333,3,5,3,4,3,3,3,3,5,5,4,4,5,3,31,24.0,neutral or dissatisfied +44096,36632,Female,Loyal Customer,36,Business travel,Business,3617,2,3,3,3,3,1,2,2,2,2,2,4,2,3,19,30.0,neutral or dissatisfied +44097,24430,Female,Loyal Customer,53,Personal Travel,Eco,634,1,1,1,3,2,3,3,5,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +44098,125178,Female,Loyal Customer,59,Business travel,Business,3121,1,2,2,2,3,4,3,1,1,1,1,1,1,3,72,53.0,neutral or dissatisfied +44099,113599,Female,disloyal Customer,38,Business travel,Eco,386,1,1,1,4,4,1,4,4,2,2,4,4,4,4,19,12.0,neutral or dissatisfied +44100,53005,Male,Loyal Customer,59,Business travel,Eco,1208,5,1,1,1,5,5,5,5,2,4,5,5,5,5,0,0.0,satisfied +44101,111076,Male,Loyal Customer,70,Personal Travel,Eco,197,1,2,1,4,1,1,1,1,2,1,4,4,3,1,0,0.0,neutral or dissatisfied +44102,110326,Male,Loyal Customer,45,Business travel,Business,1953,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +44103,69902,Male,disloyal Customer,42,Business travel,Business,1514,4,5,5,2,4,4,4,4,3,2,4,5,5,4,0,15.0,neutral or dissatisfied +44104,21327,Female,Loyal Customer,40,Personal Travel,Business,674,4,5,4,3,2,5,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +44105,103951,Female,disloyal Customer,26,Business travel,Eco,370,4,2,4,4,1,4,1,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +44106,47013,Female,Loyal Customer,45,Personal Travel,Eco,771,2,5,2,3,5,5,5,5,5,2,3,3,5,3,0,0.0,neutral or dissatisfied +44107,19421,Female,Loyal Customer,38,Business travel,Business,645,1,1,1,1,5,5,5,4,3,2,4,5,5,5,147,183.0,satisfied +44108,94282,Male,Loyal Customer,41,Business travel,Business,189,0,4,0,3,4,5,5,3,3,3,3,3,3,3,11,0.0,satisfied +44109,57956,Male,Loyal Customer,15,Personal Travel,Eco,1062,3,4,3,3,3,3,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +44110,70491,Male,disloyal Customer,22,Business travel,Business,867,5,4,5,4,2,4,5,2,3,3,4,5,5,2,0,0.0,satisfied +44111,7824,Female,Loyal Customer,57,Personal Travel,Eco,650,0,3,0,3,4,1,3,4,4,0,4,3,4,3,0,0.0,satisfied +44112,3834,Male,Loyal Customer,33,Personal Travel,Eco,650,1,4,1,2,1,1,1,1,1,4,2,5,3,1,0,0.0,neutral or dissatisfied +44113,92908,Male,Loyal Customer,31,Business travel,Eco,151,1,5,4,5,1,1,1,2,2,4,4,1,1,1,129,152.0,neutral or dissatisfied +44114,5972,Female,Loyal Customer,42,Personal Travel,Business,691,5,5,5,4,4,4,4,2,2,5,2,4,2,3,14,34.0,satisfied +44115,120815,Male,Loyal Customer,33,Business travel,Business,2989,4,5,5,5,4,4,4,4,1,4,3,3,4,4,0,19.0,neutral or dissatisfied +44116,34950,Female,Loyal Customer,60,Personal Travel,Eco,395,2,4,4,5,4,5,5,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +44117,128949,Male,Loyal Customer,49,Business travel,Business,2879,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +44118,81600,Female,Loyal Customer,68,Business travel,Business,3002,3,1,1,1,5,3,3,3,3,3,3,3,3,2,11,6.0,neutral or dissatisfied +44119,33610,Female,disloyal Customer,18,Business travel,Eco,399,2,1,2,4,5,2,5,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +44120,104336,Female,Loyal Customer,66,Business travel,Business,3789,2,4,4,4,2,2,2,2,2,2,2,2,2,1,12,12.0,neutral or dissatisfied +44121,11683,Female,Loyal Customer,63,Personal Travel,Business,429,1,4,1,1,2,5,4,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +44122,71300,Female,Loyal Customer,26,Business travel,Business,1514,3,3,3,3,3,3,3,3,3,2,4,4,3,3,2,0.0,neutral or dissatisfied +44123,80966,Male,disloyal Customer,23,Business travel,Eco,297,1,4,1,1,1,1,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +44124,71333,Female,Loyal Customer,47,Business travel,Eco,1514,4,5,5,5,3,4,1,4,4,4,4,4,4,1,103,96.0,satisfied +44125,109088,Male,Loyal Customer,43,Personal Travel,Eco,994,1,5,1,2,1,1,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +44126,87159,Female,disloyal Customer,15,Business travel,Business,946,4,5,4,3,5,4,1,5,3,3,4,5,5,5,27,34.0,satisfied +44127,102074,Male,Loyal Customer,50,Business travel,Business,2246,5,5,5,5,3,4,5,4,4,4,4,5,4,4,23,16.0,satisfied +44128,2130,Male,Loyal Customer,69,Business travel,Business,3335,3,4,4,4,4,2,3,3,3,3,3,3,3,1,61,64.0,neutral or dissatisfied +44129,41446,Female,disloyal Customer,28,Business travel,Business,715,2,3,3,4,2,3,2,2,3,5,4,3,4,2,4,6.0,neutral or dissatisfied +44130,15494,Female,Loyal Customer,50,Personal Travel,Eco,433,5,5,5,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +44131,55306,Male,disloyal Customer,33,Business travel,Eco,1285,3,3,3,3,3,3,3,3,1,5,4,3,3,3,71,52.0,neutral or dissatisfied +44132,7213,Male,Loyal Customer,47,Business travel,Eco,135,4,2,4,4,4,4,4,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +44133,8312,Female,Loyal Customer,39,Business travel,Eco Plus,335,3,2,2,2,3,3,3,3,1,3,2,3,2,3,0,0.0,neutral or dissatisfied +44134,16877,Female,Loyal Customer,47,Business travel,Eco,746,3,1,1,1,3,3,3,3,3,3,3,1,3,1,101,108.0,neutral or dissatisfied +44135,128302,Female,Loyal Customer,49,Business travel,Business,3785,1,1,1,1,3,5,4,5,5,5,5,4,5,5,4,9.0,satisfied +44136,52451,Male,Loyal Customer,28,Business travel,Eco Plus,509,5,1,4,1,5,5,5,5,2,5,4,1,3,5,0,0.0,satisfied +44137,27407,Female,disloyal Customer,26,Business travel,Eco,679,2,2,2,2,4,2,4,4,4,1,1,1,1,4,0,0.0,neutral or dissatisfied +44138,9471,Male,disloyal Customer,37,Business travel,Business,362,2,1,1,3,4,1,4,4,3,1,4,1,3,4,0,6.0,neutral or dissatisfied +44139,64389,Female,Loyal Customer,10,Personal Travel,Eco,1192,2,1,2,3,3,2,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +44140,72012,Male,Loyal Customer,25,Business travel,Business,3784,1,1,1,1,5,5,5,5,3,3,4,5,5,5,54,27.0,satisfied +44141,32972,Male,Loyal Customer,30,Personal Travel,Eco,201,5,4,5,3,3,5,3,3,3,5,1,5,4,3,0,2.0,satisfied +44142,9020,Male,disloyal Customer,33,Business travel,Business,173,2,2,2,4,2,2,2,2,5,5,5,4,4,2,19,13.0,neutral or dissatisfied +44143,118144,Female,disloyal Customer,45,Business travel,Business,1444,2,2,2,3,5,2,5,5,2,2,4,1,3,5,32,30.0,neutral or dissatisfied +44144,56717,Female,Loyal Customer,14,Personal Travel,Eco,1023,1,4,1,2,4,1,4,4,3,1,4,5,5,4,0,21.0,neutral or dissatisfied +44145,2227,Male,Loyal Customer,14,Business travel,Business,642,1,1,1,1,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +44146,17192,Male,Loyal Customer,11,Personal Travel,Eco,643,1,4,1,1,5,1,5,5,4,5,5,3,4,5,0,13.0,neutral or dissatisfied +44147,37743,Female,Loyal Customer,43,Personal Travel,Eco,989,2,3,2,3,1,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +44148,35549,Female,Loyal Customer,21,Personal Travel,Eco,1097,2,1,2,3,1,2,1,1,3,4,2,4,2,1,0,0.0,neutral or dissatisfied +44149,26007,Male,disloyal Customer,18,Business travel,Eco,425,3,1,3,2,1,3,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +44150,123567,Female,disloyal Customer,27,Business travel,Business,1773,2,1,1,1,1,1,4,1,4,5,3,5,4,1,3,0.0,neutral or dissatisfied +44151,17495,Female,Loyal Customer,24,Business travel,Business,341,4,1,1,1,4,4,4,4,3,5,3,1,3,4,0,0.0,neutral or dissatisfied +44152,9215,Female,disloyal Customer,22,Business travel,Business,157,4,0,4,4,5,4,3,5,3,3,4,4,4,5,104,84.0,satisfied +44153,4921,Female,Loyal Customer,57,Personal Travel,Eco,1020,4,1,4,3,3,3,4,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +44154,100253,Male,disloyal Customer,23,Business travel,Business,1033,5,2,5,1,4,5,4,4,5,4,4,4,4,4,0,0.0,satisfied +44155,30804,Male,disloyal Customer,23,Business travel,Eco,1199,2,2,2,2,1,2,1,1,1,2,4,5,2,1,0,1.0,neutral or dissatisfied +44156,105911,Male,Loyal Customer,33,Personal Travel,Eco,283,0,4,0,4,1,0,1,1,5,4,5,3,5,1,0,0.0,satisfied +44157,111301,Female,Loyal Customer,52,Business travel,Business,283,0,0,0,1,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +44158,69397,Female,Loyal Customer,43,Business travel,Business,3941,3,3,3,3,4,4,4,5,5,5,5,4,5,3,98,98.0,satisfied +44159,3357,Male,Loyal Customer,38,Business travel,Business,240,3,3,3,3,2,5,5,5,5,5,5,5,5,5,40,32.0,satisfied +44160,78126,Male,disloyal Customer,29,Business travel,Business,489,2,2,2,4,3,2,5,3,1,4,3,3,4,3,0,9.0,neutral or dissatisfied +44161,104541,Male,Loyal Customer,64,Personal Travel,Eco,1256,3,5,3,5,2,3,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +44162,56939,Female,Loyal Customer,30,Business travel,Business,2454,5,5,5,5,3,3,3,4,5,4,5,3,3,3,12,34.0,satisfied +44163,97293,Male,Loyal Customer,44,Business travel,Business,3007,3,3,4,3,2,5,4,4,4,4,4,5,4,3,44,43.0,satisfied +44164,2248,Female,Loyal Customer,49,Business travel,Business,2464,4,4,4,4,3,5,5,5,5,4,5,4,5,3,20,14.0,satisfied +44165,81741,Male,Loyal Customer,57,Business travel,Business,1310,5,5,5,5,5,4,4,5,5,5,5,5,5,5,2,0.0,satisfied +44166,66124,Female,disloyal Customer,39,Business travel,Eco,183,3,0,3,4,1,3,1,1,5,3,1,5,3,1,0,0.0,neutral or dissatisfied +44167,23514,Female,disloyal Customer,27,Business travel,Eco,303,2,1,2,3,3,2,3,3,2,1,3,3,3,3,112,95.0,neutral or dissatisfied +44168,39841,Female,Loyal Customer,61,Business travel,Business,221,4,5,5,5,5,3,4,4,4,4,4,4,4,2,0,5.0,neutral or dissatisfied +44169,37986,Female,Loyal Customer,50,Business travel,Business,1185,2,2,2,2,4,3,2,4,4,3,4,1,4,3,0,0.0,satisfied +44170,73129,Male,Loyal Customer,39,Business travel,Business,3664,5,5,5,5,3,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +44171,4075,Male,Loyal Customer,56,Business travel,Business,544,3,1,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +44172,2023,Female,Loyal Customer,18,Personal Travel,Business,785,3,4,4,1,5,4,5,5,5,4,4,4,5,5,16,31.0,neutral or dissatisfied +44173,55270,Male,Loyal Customer,19,Personal Travel,Eco,2007,4,4,4,1,5,4,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +44174,94109,Male,Loyal Customer,69,Personal Travel,Business,677,2,5,3,5,4,4,5,4,4,3,1,3,4,3,3,11.0,neutral or dissatisfied +44175,97015,Male,Loyal Customer,31,Personal Travel,Eco,775,3,5,4,3,4,4,4,4,3,1,4,3,5,4,30,16.0,neutral or dissatisfied +44176,119716,Female,disloyal Customer,18,Business travel,Eco,1303,1,1,1,3,5,1,5,5,4,5,4,2,3,5,0,0.0,neutral or dissatisfied +44177,72371,Male,Loyal Customer,47,Business travel,Business,985,1,1,1,1,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +44178,96524,Female,Loyal Customer,68,Personal Travel,Eco,302,3,4,3,3,1,3,4,4,4,3,4,3,4,2,51,43.0,neutral or dissatisfied +44179,69991,Male,Loyal Customer,64,Personal Travel,Eco,236,3,4,0,4,2,0,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +44180,35661,Female,Loyal Customer,17,Business travel,Business,2475,2,2,2,2,5,5,5,5,2,3,3,5,4,5,0,0.0,satisfied +44181,24377,Female,Loyal Customer,36,Business travel,Business,669,4,4,4,4,3,4,4,5,5,5,5,1,5,5,0,0.0,satisfied +44182,29784,Male,Loyal Customer,29,Business travel,Business,2528,5,5,5,5,3,4,3,3,2,2,1,1,5,3,0,5.0,satisfied +44183,83054,Female,Loyal Customer,40,Business travel,Business,2845,2,5,5,5,1,3,3,2,2,2,2,3,2,4,0,39.0,neutral or dissatisfied +44184,80235,Female,Loyal Customer,34,Business travel,Eco,1269,1,4,4,4,1,1,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +44185,85285,Male,Loyal Customer,47,Personal Travel,Eco,813,2,1,1,3,4,1,1,4,2,1,3,4,3,4,44,51.0,neutral or dissatisfied +44186,37901,Male,disloyal Customer,25,Business travel,Eco,537,4,1,4,3,5,4,5,5,1,4,4,4,4,5,0,0.0,neutral or dissatisfied +44187,129377,Male,Loyal Customer,56,Business travel,Business,2454,1,1,1,1,4,3,4,4,4,4,4,4,4,5,8,0.0,satisfied +44188,38618,Female,Loyal Customer,8,Personal Travel,Eco Plus,231,3,5,3,2,2,3,2,2,5,2,5,5,1,2,0,0.0,neutral or dissatisfied +44189,129576,Female,Loyal Customer,39,Personal Travel,Eco Plus,2342,4,4,4,4,2,4,2,2,2,4,4,5,4,2,19,0.0,satisfied +44190,107618,Female,disloyal Customer,21,Business travel,Eco,423,2,4,2,4,5,2,5,5,2,5,4,3,4,5,39,33.0,neutral or dissatisfied +44191,47192,Female,Loyal Customer,45,Business travel,Eco,565,4,3,3,3,3,3,1,4,4,4,4,4,4,4,18,17.0,satisfied +44192,21076,Male,Loyal Customer,37,Business travel,Eco,106,2,2,2,2,2,2,2,2,4,1,3,4,3,2,47,50.0,neutral or dissatisfied +44193,614,Male,disloyal Customer,40,Business travel,Business,309,3,3,3,3,2,3,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +44194,114016,Female,Loyal Customer,55,Personal Travel,Eco,1750,2,3,2,2,2,3,4,2,2,2,5,5,2,4,1,0.0,neutral or dissatisfied +44195,98349,Male,Loyal Customer,54,Business travel,Business,2846,5,5,3,5,5,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +44196,75467,Male,Loyal Customer,52,Personal Travel,Eco,2342,4,4,4,3,1,4,1,1,2,5,4,3,3,1,0,0.0,neutral or dissatisfied +44197,108160,Female,Loyal Customer,46,Personal Travel,Eco,1105,0,4,0,3,2,4,4,1,1,0,1,1,1,4,0,3.0,satisfied +44198,114572,Female,Loyal Customer,35,Business travel,Business,342,5,5,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +44199,95255,Male,Loyal Customer,51,Personal Travel,Eco,239,2,1,2,3,5,2,5,5,4,4,3,2,3,5,6,0.0,neutral or dissatisfied +44200,8084,Female,Loyal Customer,39,Business travel,Business,2407,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +44201,6458,Female,disloyal Customer,62,Business travel,Eco Plus,315,3,3,3,3,1,3,1,1,1,2,4,4,4,1,2,0.0,neutral or dissatisfied +44202,29698,Male,Loyal Customer,23,Business travel,Eco,1542,4,3,3,3,4,4,5,4,4,4,3,2,2,4,0,0.0,satisfied +44203,99932,Male,Loyal Customer,46,Personal Travel,Eco,764,1,5,1,4,4,1,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +44204,96313,Female,Loyal Customer,26,Personal Travel,Eco Plus,460,3,3,3,4,5,3,5,5,2,1,4,2,3,5,12,12.0,neutral or dissatisfied +44205,89668,Female,Loyal Customer,25,Business travel,Business,1096,4,1,1,1,4,4,4,1,1,3,4,4,1,4,167,165.0,neutral or dissatisfied +44206,43828,Female,disloyal Customer,35,Business travel,Eco,114,2,3,2,4,1,2,1,1,3,2,3,4,4,1,0,28.0,neutral or dissatisfied +44207,61653,Female,Loyal Customer,39,Business travel,Eco,1635,2,2,2,2,2,2,2,2,3,2,3,3,4,2,1,9.0,neutral or dissatisfied +44208,92407,Male,disloyal Customer,23,Business travel,Eco,833,5,5,5,3,3,5,3,3,4,3,3,4,5,3,0,0.0,satisfied +44209,21562,Male,Loyal Customer,41,Business travel,Eco Plus,399,4,1,1,1,4,4,4,4,4,1,4,4,2,4,0,4.0,satisfied +44210,11955,Female,Loyal Customer,45,Personal Travel,Eco,781,3,5,3,4,2,3,2,2,2,3,1,1,2,4,77,64.0,neutral or dissatisfied +44211,9661,Female,Loyal Customer,54,Business travel,Business,277,3,3,3,3,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +44212,59837,Female,disloyal Customer,23,Business travel,Business,1023,4,5,4,1,1,4,1,1,3,4,5,5,4,1,9,0.0,satisfied +44213,20192,Male,Loyal Customer,39,Business travel,Eco Plus,277,5,5,5,5,5,5,5,5,4,2,4,4,4,5,1,16.0,satisfied +44214,25961,Female,Loyal Customer,62,Business travel,Business,2793,4,4,4,4,1,4,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +44215,67862,Male,Loyal Customer,47,Personal Travel,Eco,1171,1,4,1,2,3,1,3,3,4,2,4,3,5,3,37,39.0,neutral or dissatisfied +44216,6540,Female,Loyal Customer,33,Business travel,Business,528,2,2,2,2,1,2,2,2,2,2,2,2,2,1,30,14.0,neutral or dissatisfied +44217,13291,Female,Loyal Customer,25,Business travel,Eco Plus,771,1,5,5,5,1,1,3,1,3,2,3,3,4,1,0,0.0,neutral or dissatisfied +44218,29748,Male,Loyal Customer,46,Business travel,Business,95,1,1,4,1,3,4,5,5,5,5,4,3,5,3,1,0.0,satisfied +44219,111040,Male,Loyal Customer,70,Business travel,Business,1545,2,4,4,4,2,3,4,3,3,3,2,4,3,1,27,11.0,neutral or dissatisfied +44220,91010,Female,Loyal Customer,63,Personal Travel,Eco,581,2,5,2,5,4,5,5,1,1,2,1,4,1,3,59,46.0,neutral or dissatisfied +44221,7721,Male,Loyal Customer,54,Business travel,Business,2431,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,3.0,satisfied +44222,104761,Female,Loyal Customer,54,Personal Travel,Eco,1246,2,4,2,5,4,5,4,3,3,2,3,4,3,5,82,59.0,neutral or dissatisfied +44223,49562,Male,Loyal Customer,66,Business travel,Business,1878,1,3,3,3,4,3,4,3,3,3,1,4,3,2,9,1.0,neutral or dissatisfied +44224,70920,Male,disloyal Customer,30,Business travel,Eco,612,3,4,2,3,2,1,1,1,2,4,3,1,4,1,290,290.0,neutral or dissatisfied +44225,44363,Male,disloyal Customer,38,Business travel,Eco,196,2,3,1,3,2,1,2,2,3,4,4,2,1,2,2,1.0,neutral or dissatisfied +44226,105311,Male,Loyal Customer,58,Business travel,Business,2372,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +44227,82601,Male,disloyal Customer,38,Business travel,Eco,408,1,1,2,4,2,2,5,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +44228,22152,Female,Loyal Customer,29,Business travel,Business,533,1,1,1,1,4,4,4,4,2,4,5,3,2,4,1,0.0,satisfied +44229,32695,Female,Loyal Customer,58,Business travel,Business,3600,1,2,5,2,1,3,4,4,4,3,1,2,4,3,0,0.0,neutral or dissatisfied +44230,62899,Male,Loyal Customer,39,Business travel,Business,862,4,4,4,4,3,5,4,4,4,4,4,3,4,5,54,,satisfied +44231,42245,Male,Loyal Customer,25,Business travel,Eco,846,5,5,5,5,5,5,5,5,4,1,1,4,5,5,0,0.0,satisfied +44232,121805,Female,Loyal Customer,48,Business travel,Business,1569,4,4,3,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +44233,77289,Female,Loyal Customer,57,Personal Travel,Eco Plus,1931,3,5,3,5,4,4,4,2,2,3,2,5,2,3,0,1.0,neutral or dissatisfied +44234,25160,Male,Loyal Customer,24,Business travel,Business,2106,3,4,4,4,3,3,3,3,2,4,3,1,3,3,8,24.0,neutral or dissatisfied +44235,33175,Male,Loyal Customer,27,Personal Travel,Eco,216,3,0,3,2,4,3,4,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +44236,41532,Female,Loyal Customer,31,Business travel,Business,1504,5,5,5,5,5,5,5,5,3,5,2,2,5,5,61,57.0,satisfied +44237,42430,Female,Loyal Customer,30,Business travel,Eco Plus,451,4,5,5,5,4,4,4,4,1,2,3,2,3,4,10,23.0,satisfied +44238,352,Female,Loyal Customer,7,Personal Travel,Eco Plus,853,2,5,1,2,5,1,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +44239,34667,Female,Loyal Customer,39,Business travel,Business,2056,1,5,5,5,1,1,1,1,3,3,4,1,1,1,460,457.0,neutral or dissatisfied +44240,126005,Female,disloyal Customer,39,Business travel,Business,590,4,3,3,3,3,3,3,3,4,4,4,3,5,3,0,0.0,satisfied +44241,47394,Female,disloyal Customer,52,Business travel,Eco,588,1,3,0,3,4,0,4,4,3,2,2,3,2,4,0,0.0,neutral or dissatisfied +44242,6066,Female,Loyal Customer,16,Personal Travel,Eco,925,2,5,1,1,4,1,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +44243,9429,Male,disloyal Customer,25,Business travel,Eco,288,3,2,3,2,3,4,4,3,4,2,3,4,1,4,152,142.0,neutral or dissatisfied +44244,85408,Male,Loyal Customer,58,Business travel,Business,3995,0,4,0,4,3,5,4,5,5,5,5,5,5,3,31,28.0,satisfied +44245,123928,Female,Loyal Customer,27,Personal Travel,Eco,544,4,5,4,3,2,4,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +44246,126468,Female,Loyal Customer,58,Business travel,Business,1788,1,1,3,1,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +44247,57494,Male,Loyal Customer,40,Business travel,Business,1075,4,1,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +44248,12454,Female,Loyal Customer,13,Personal Travel,Eco,201,3,3,3,3,5,3,5,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +44249,128582,Male,Loyal Customer,57,Business travel,Business,2552,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +44250,116887,Female,Loyal Customer,45,Business travel,Business,1594,1,1,3,1,3,4,5,4,4,4,4,5,4,4,4,4.0,satisfied +44251,11411,Female,Loyal Customer,44,Business travel,Business,2859,5,5,5,5,4,5,4,4,4,4,5,3,4,4,0,1.0,satisfied +44252,58267,Male,Loyal Customer,45,Business travel,Business,678,5,5,5,5,3,4,5,3,3,4,3,5,3,3,6,0.0,satisfied +44253,118849,Female,Loyal Customer,17,Personal Travel,Eco Plus,647,3,4,3,5,5,3,5,5,1,4,5,3,2,5,59,59.0,neutral or dissatisfied +44254,91572,Male,Loyal Customer,31,Business travel,Business,1123,2,4,4,4,2,2,2,2,4,5,3,3,2,2,23,14.0,neutral or dissatisfied +44255,115571,Male,Loyal Customer,26,Business travel,Business,390,1,1,1,1,3,4,3,3,3,2,4,5,4,3,1,0.0,satisfied +44256,56013,Female,Loyal Customer,44,Business travel,Business,2475,2,2,2,2,5,5,5,4,5,4,4,5,4,5,0,0.0,satisfied +44257,43452,Female,Loyal Customer,44,Business travel,Eco,679,4,4,3,3,2,2,4,4,4,4,4,3,4,2,0,0.0,satisfied +44258,125564,Male,Loyal Customer,41,Personal Travel,Eco,226,1,5,0,5,3,0,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +44259,41483,Male,Loyal Customer,36,Business travel,Eco,1242,3,4,4,4,3,5,3,3,4,5,2,5,1,3,0,20.0,satisfied +44260,118092,Male,disloyal Customer,22,Business travel,Eco,1276,1,1,1,3,4,1,4,4,3,2,4,5,5,4,18,14.0,neutral or dissatisfied +44261,25206,Female,Loyal Customer,43,Business travel,Business,925,5,3,5,5,2,3,1,4,4,4,4,2,4,2,15,1.0,satisfied +44262,121130,Male,Loyal Customer,49,Business travel,Business,2370,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +44263,17914,Female,Loyal Customer,46,Business travel,Eco,789,4,4,4,4,2,4,1,4,4,4,4,1,4,5,0,0.0,satisfied +44264,76205,Male,Loyal Customer,37,Personal Travel,Eco,2422,1,4,1,4,2,1,2,2,4,2,3,4,5,2,0,0.0,neutral or dissatisfied +44265,57988,Male,Loyal Customer,52,Business travel,Business,3087,1,1,1,1,3,5,5,4,4,4,4,5,4,3,25,20.0,satisfied +44266,105360,Male,Loyal Customer,49,Business travel,Business,1942,4,2,4,4,5,5,5,4,4,4,4,3,4,4,41,25.0,satisfied +44267,34701,Male,Loyal Customer,46,Business travel,Business,3259,1,1,1,1,5,5,5,3,3,3,3,5,5,5,183,174.0,satisfied +44268,44484,Female,Loyal Customer,31,Personal Travel,Eco,692,1,5,1,3,2,1,2,2,3,4,4,3,5,2,47,51.0,neutral or dissatisfied +44269,59808,Male,Loyal Customer,35,Business travel,Business,937,3,4,3,4,4,2,3,3,3,3,3,1,3,4,25,16.0,neutral or dissatisfied +44270,107143,Female,Loyal Customer,54,Business travel,Business,3159,3,3,5,3,5,5,5,4,4,4,4,5,4,4,2,2.0,satisfied +44271,14835,Male,disloyal Customer,21,Business travel,Eco,261,3,0,3,2,3,3,3,3,4,5,1,1,2,3,128,129.0,neutral or dissatisfied +44272,60984,Female,Loyal Customer,60,Business travel,Business,888,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,9.0,satisfied +44273,71403,Male,disloyal Customer,17,Business travel,Eco,334,2,5,2,1,3,2,1,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +44274,30774,Male,Loyal Customer,69,Personal Travel,Business,895,3,3,3,3,2,3,3,5,5,3,5,4,5,4,23,12.0,neutral or dissatisfied +44275,49787,Female,Loyal Customer,59,Business travel,Business,110,3,3,3,3,2,3,2,1,2,4,3,2,3,2,163,157.0,neutral or dissatisfied +44276,55095,Female,disloyal Customer,27,Business travel,Eco,979,2,2,2,3,1,2,3,1,4,1,4,2,3,1,21,10.0,neutral or dissatisfied +44277,84179,Female,Loyal Customer,39,Personal Travel,Eco Plus,231,3,2,0,3,3,0,3,3,2,1,2,3,3,3,0,0.0,neutral or dissatisfied +44278,63633,Female,Loyal Customer,23,Business travel,Business,2764,1,3,1,1,1,1,1,1,4,1,2,2,2,1,27,9.0,neutral or dissatisfied +44279,84386,Female,disloyal Customer,43,Business travel,Business,606,5,5,5,4,5,1,4,5,4,5,5,4,3,4,164,163.0,satisfied +44280,113295,Female,Loyal Customer,58,Business travel,Business,1519,2,2,4,2,5,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +44281,64402,Female,disloyal Customer,44,Business travel,Eco Plus,1192,2,2,2,3,4,2,4,4,3,1,2,4,3,4,26,27.0,neutral or dissatisfied +44282,4941,Female,Loyal Customer,25,Personal Travel,Eco,268,2,0,2,3,4,2,4,4,3,3,1,5,3,4,0,0.0,neutral or dissatisfied +44283,36202,Female,Loyal Customer,40,Business travel,Eco,496,5,1,1,1,5,5,5,5,3,1,3,2,5,5,0,10.0,satisfied +44284,98984,Female,Loyal Customer,26,Personal Travel,Eco,543,3,4,3,2,4,3,1,4,5,5,4,5,5,4,37,30.0,neutral or dissatisfied +44285,43672,Male,Loyal Customer,31,Personal Travel,Eco,695,1,1,2,2,4,2,2,4,4,1,2,2,3,4,0,0.0,neutral or dissatisfied +44286,66329,Female,Loyal Customer,17,Business travel,Business,3983,4,4,4,4,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +44287,73881,Female,Loyal Customer,39,Business travel,Business,2330,4,4,4,4,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +44288,46985,Female,Loyal Customer,70,Personal Travel,Eco,776,3,4,3,3,5,5,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +44289,72045,Female,Loyal Customer,49,Business travel,Business,2556,3,2,2,2,4,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +44290,63157,Male,Loyal Customer,51,Business travel,Business,1604,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +44291,15766,Male,disloyal Customer,15,Business travel,Eco,198,3,1,3,3,2,3,2,2,1,4,4,4,4,2,124,95.0,neutral or dissatisfied +44292,123654,Female,Loyal Customer,42,Business travel,Business,2042,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +44293,66554,Female,Loyal Customer,69,Personal Travel,Eco,328,3,0,3,3,2,4,4,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +44294,50672,Female,Loyal Customer,68,Personal Travel,Eco,373,2,3,2,4,3,4,4,2,2,2,2,3,2,4,2,7.0,neutral or dissatisfied +44295,49933,Female,Loyal Customer,48,Business travel,Business,3260,3,3,4,3,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +44296,112891,Female,disloyal Customer,25,Business travel,Eco,1390,2,2,2,3,1,2,1,1,4,2,4,3,3,1,25,14.0,neutral or dissatisfied +44297,105161,Male,Loyal Customer,56,Business travel,Eco,281,4,3,3,3,4,4,4,4,1,1,4,2,3,4,0,0.0,satisfied +44298,24870,Male,disloyal Customer,38,Business travel,Business,356,3,3,3,4,2,3,1,2,4,2,3,4,3,2,0,2.0,neutral or dissatisfied +44299,84294,Male,Loyal Customer,52,Business travel,Business,2202,3,3,3,3,2,5,4,5,5,5,5,3,5,5,52,26.0,satisfied +44300,22396,Female,Loyal Customer,33,Business travel,Business,1763,5,5,5,5,5,2,2,5,5,5,3,4,5,1,0,0.0,satisfied +44301,44109,Female,Loyal Customer,63,Personal Travel,Eco,473,4,4,4,2,5,1,1,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +44302,20626,Female,Loyal Customer,59,Business travel,Business,3351,2,2,2,2,4,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +44303,87903,Female,disloyal Customer,46,Business travel,Business,406,4,4,4,3,1,4,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +44304,36485,Male,Loyal Customer,57,Business travel,Business,3140,3,5,5,5,4,3,3,3,3,3,3,3,3,4,12,0.0,neutral or dissatisfied +44305,68421,Male,Loyal Customer,21,Personal Travel,Eco,1045,3,4,3,1,2,3,4,2,5,1,5,3,4,2,0,0.0,neutral or dissatisfied +44306,88161,Male,disloyal Customer,27,Business travel,Business,271,2,2,2,4,3,2,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +44307,7365,Female,Loyal Customer,42,Business travel,Business,3647,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +44308,72064,Female,Loyal Customer,39,Business travel,Business,2556,3,3,3,3,5,3,5,4,4,4,4,5,4,5,36,0.0,satisfied +44309,784,Male,disloyal Customer,24,Business travel,Eco,134,3,0,3,1,5,3,5,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +44310,37322,Male,disloyal Customer,36,Business travel,Eco,1028,2,2,2,3,2,2,2,2,5,3,2,2,2,2,0,0.0,neutral or dissatisfied +44311,63814,Female,disloyal Customer,37,Business travel,Business,1192,3,3,3,2,4,3,4,4,3,3,5,5,4,4,10,3.0,neutral or dissatisfied +44312,111607,Male,Loyal Customer,54,Business travel,Business,1014,2,2,2,2,5,4,4,4,4,4,4,5,4,3,6,12.0,satisfied +44313,105549,Male,Loyal Customer,25,Personal Travel,Eco,611,4,5,4,3,4,2,2,5,3,2,3,2,5,2,175,192.0,neutral or dissatisfied +44314,63063,Female,Loyal Customer,25,Personal Travel,Eco,862,3,3,3,3,1,3,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +44315,30839,Male,Loyal Customer,29,Business travel,Eco Plus,955,4,2,2,2,4,4,4,4,3,2,3,2,1,4,0,1.0,satisfied +44316,92484,Male,disloyal Customer,25,Business travel,Business,2139,5,0,5,4,3,5,3,3,5,2,3,4,4,3,0,0.0,satisfied +44317,45018,Male,Loyal Customer,39,Personal Travel,Eco,359,4,5,4,3,3,4,3,3,4,2,5,3,2,3,0,0.0,neutral or dissatisfied +44318,73231,Female,Loyal Customer,50,Personal Travel,Eco,946,3,1,3,2,3,2,2,1,1,3,1,4,1,2,50,52.0,neutral or dissatisfied +44319,102279,Male,Loyal Customer,37,Business travel,Business,3592,3,4,4,4,2,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +44320,63817,Male,Loyal Customer,42,Business travel,Business,1623,5,5,5,5,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +44321,14989,Male,Loyal Customer,26,Personal Travel,Eco Plus,1080,2,4,3,4,3,3,3,3,5,4,5,4,5,3,6,0.0,neutral or dissatisfied +44322,8206,Male,Loyal Customer,42,Business travel,Business,2244,3,5,5,5,5,4,4,3,3,3,3,1,3,2,7,12.0,neutral or dissatisfied +44323,48339,Male,Loyal Customer,29,Business travel,Business,1988,4,4,2,4,5,4,5,5,1,1,2,5,5,5,0,0.0,satisfied +44324,23984,Female,Loyal Customer,52,Business travel,Eco,427,4,4,4,4,3,5,5,4,4,4,4,5,4,4,3,10.0,satisfied +44325,79411,Male,disloyal Customer,26,Business travel,Eco,102,2,2,2,3,3,2,3,3,1,4,4,1,4,3,81,77.0,neutral or dissatisfied +44326,51283,Female,Loyal Customer,35,Business travel,Eco Plus,250,1,4,4,4,1,1,1,1,4,2,2,1,2,1,55,,neutral or dissatisfied +44327,107587,Male,Loyal Customer,53,Business travel,Business,3537,3,3,3,3,5,5,5,5,5,5,5,3,5,5,7,0.0,satisfied +44328,60848,Female,Loyal Customer,7,Personal Travel,Eco,1754,1,1,1,3,1,1,1,1,3,4,3,1,3,1,2,0.0,neutral or dissatisfied +44329,34046,Male,Loyal Customer,34,Business travel,Business,1674,4,4,4,4,4,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +44330,62350,Male,Loyal Customer,40,Business travel,Eco,1735,2,4,4,4,2,2,2,2,4,2,2,1,3,2,29,27.0,neutral or dissatisfied +44331,113811,Female,disloyal Customer,32,Business travel,Eco Plus,407,2,2,2,3,3,2,3,3,3,1,3,2,3,3,31,34.0,neutral or dissatisfied +44332,54654,Female,Loyal Customer,30,Business travel,Business,854,5,5,5,5,5,5,5,5,3,1,4,5,1,5,0,0.0,satisfied +44333,51202,Male,Loyal Customer,40,Business travel,Eco Plus,373,5,5,1,5,5,5,5,5,4,3,2,5,4,5,0,7.0,satisfied +44334,102764,Male,Loyal Customer,34,Business travel,Business,1618,4,4,4,4,5,3,5,5,5,5,5,4,5,4,37,11.0,satisfied +44335,58,Female,Loyal Customer,43,Business travel,Business,2199,0,5,0,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +44336,84727,Female,Loyal Customer,40,Business travel,Business,3521,3,3,2,3,2,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +44337,30317,Female,disloyal Customer,25,Business travel,Eco,391,1,0,1,3,5,1,5,5,1,4,2,4,5,5,3,0.0,neutral or dissatisfied +44338,33706,Male,disloyal Customer,20,Business travel,Eco,759,3,3,3,3,1,3,1,1,4,1,4,1,4,1,8,11.0,neutral or dissatisfied +44339,54865,Male,Loyal Customer,57,Business travel,Business,862,3,3,3,3,4,4,5,4,4,4,4,4,4,4,8,0.0,satisfied +44340,6191,Male,Loyal Customer,52,Personal Travel,Eco,491,2,1,4,3,3,4,3,3,2,1,4,4,3,3,16,17.0,neutral or dissatisfied +44341,99701,Male,Loyal Customer,48,Business travel,Business,1767,5,5,5,5,4,5,5,5,5,5,5,3,5,3,20,21.0,satisfied +44342,9112,Female,Loyal Customer,46,Business travel,Business,2473,3,3,3,3,3,4,4,5,5,5,5,4,5,4,5,26.0,satisfied +44343,66360,Female,disloyal Customer,85,Business travel,Business,586,2,2,2,3,2,2,5,2,4,3,1,5,2,5,0,0.0,neutral or dissatisfied +44344,5042,Female,Loyal Customer,59,Business travel,Business,235,3,3,3,3,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +44345,120436,Female,Loyal Customer,62,Business travel,Business,2845,2,2,2,2,1,4,3,4,4,4,4,4,4,5,0,0.0,satisfied +44346,82426,Male,Loyal Customer,47,Business travel,Business,241,0,0,0,3,4,5,5,5,5,5,5,4,5,3,5,0.0,satisfied +44347,41339,Male,Loyal Customer,21,Personal Travel,Eco,689,3,1,3,3,2,3,3,2,4,1,3,1,3,2,0,22.0,neutral or dissatisfied +44348,84129,Female,Loyal Customer,49,Personal Travel,Eco,1569,4,4,3,3,2,4,5,4,4,3,4,4,4,5,0,0.0,satisfied +44349,116245,Female,Loyal Customer,14,Personal Travel,Eco,325,5,1,5,3,2,5,2,2,1,1,4,2,3,2,4,0.0,satisfied +44350,90169,Female,Loyal Customer,46,Personal Travel,Eco,1084,3,5,3,4,3,5,3,3,2,4,5,3,5,3,247,238.0,neutral or dissatisfied +44351,60751,Female,Loyal Customer,25,Business travel,Business,628,2,2,2,2,4,5,4,4,3,2,4,4,5,4,17,14.0,satisfied +44352,83934,Male,Loyal Customer,46,Business travel,Business,3724,5,5,2,5,4,5,4,4,4,4,4,3,4,4,0,18.0,satisfied +44353,16542,Male,Loyal Customer,25,Business travel,Business,2365,1,1,5,1,4,5,4,4,3,5,2,4,2,4,0,0.0,satisfied +44354,37022,Female,Loyal Customer,61,Personal Travel,Eco Plus,899,3,5,3,3,3,5,4,4,4,3,4,4,4,5,28,38.0,neutral or dissatisfied +44355,89270,Male,Loyal Customer,54,Business travel,Business,2392,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +44356,76816,Male,Loyal Customer,31,Business travel,Business,3095,5,5,5,5,5,5,5,5,5,3,5,4,5,5,7,5.0,satisfied +44357,37269,Female,Loyal Customer,54,Business travel,Eco,1056,5,5,5,5,2,1,4,5,5,5,5,4,5,4,0,0.0,satisfied +44358,115226,Female,Loyal Customer,58,Business travel,Business,337,2,4,4,4,3,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +44359,30289,Male,Loyal Customer,41,Business travel,Business,1476,3,3,3,3,3,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +44360,53518,Male,Loyal Customer,68,Personal Travel,Eco,2419,1,4,1,3,1,5,5,3,3,5,5,5,3,5,4,4.0,neutral or dissatisfied +44361,113572,Male,Loyal Customer,50,Business travel,Eco,414,3,1,2,2,3,3,3,3,1,1,3,3,2,3,0,0.0,neutral or dissatisfied +44362,108938,Male,Loyal Customer,62,Personal Travel,Eco,1075,4,5,4,4,1,4,1,1,5,3,5,5,4,1,54,37.0,neutral or dissatisfied +44363,13008,Female,Loyal Customer,47,Business travel,Business,1686,3,3,3,3,1,5,3,4,4,4,4,5,4,4,0,0.0,satisfied +44364,105791,Male,Loyal Customer,34,Personal Travel,Eco,925,3,4,3,1,3,3,3,3,4,5,4,4,5,3,1,0.0,neutral or dissatisfied +44365,58509,Male,Loyal Customer,67,Personal Travel,Eco,719,4,4,4,3,4,4,4,4,3,2,5,4,5,4,37,29.0,neutral or dissatisfied +44366,126972,Male,Loyal Customer,42,Business travel,Business,325,3,3,3,3,2,4,5,5,5,5,5,3,5,4,1,0.0,satisfied +44367,112916,Female,Loyal Customer,58,Business travel,Business,1076,1,3,3,3,2,3,4,1,1,1,1,2,1,2,25,9.0,neutral or dissatisfied +44368,50858,Male,Loyal Customer,67,Personal Travel,Eco,363,3,5,3,3,5,3,5,5,4,4,4,5,4,5,5,2.0,neutral or dissatisfied +44369,16235,Female,Loyal Customer,11,Business travel,Business,2869,1,4,4,4,1,1,1,1,4,5,4,1,3,1,2,17.0,neutral or dissatisfied +44370,6789,Female,disloyal Customer,26,Business travel,Business,303,2,0,2,2,4,2,4,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +44371,82056,Female,disloyal Customer,35,Business travel,Eco Plus,1522,2,2,2,2,2,2,2,2,2,2,1,4,2,2,1,0.0,neutral or dissatisfied +44372,19432,Male,Loyal Customer,38,Personal Travel,Eco,645,2,4,2,1,4,2,3,4,1,5,1,3,2,4,37,63.0,neutral or dissatisfied +44373,37451,Male,disloyal Customer,21,Business travel,Eco,1028,2,2,2,4,1,2,1,1,5,1,3,4,4,1,2,0.0,neutral or dissatisfied +44374,104839,Female,Loyal Customer,46,Personal Travel,Eco,472,2,2,5,3,4,3,3,2,2,5,2,4,2,2,44,30.0,neutral or dissatisfied +44375,11605,Male,Loyal Customer,40,Personal Travel,Eco,657,4,4,4,4,5,4,5,5,5,5,4,4,4,5,0,0.0,satisfied +44376,92523,Female,Loyal Customer,28,Personal Travel,Eco,1947,2,4,2,4,5,2,5,5,3,2,5,3,5,5,14,0.0,neutral or dissatisfied +44377,59779,Female,Loyal Customer,35,Personal Travel,Eco,927,4,4,4,2,1,4,1,1,4,3,4,3,4,1,0,0.0,satisfied +44378,15539,Female,Loyal Customer,32,Business travel,Business,3611,4,4,4,4,4,4,4,4,5,4,1,4,4,4,26,4.0,satisfied +44379,18071,Male,Loyal Customer,64,Personal Travel,Eco,488,5,0,5,4,4,5,4,4,3,2,4,3,3,4,0,0.0,satisfied +44380,127037,Female,disloyal Customer,22,Business travel,Eco,651,3,1,3,2,5,3,5,5,4,2,3,3,3,5,1,10.0,neutral or dissatisfied +44381,31116,Male,Loyal Customer,24,Business travel,Business,3920,1,1,1,1,4,4,4,4,3,4,3,4,5,4,0,0.0,satisfied +44382,109781,Female,Loyal Customer,42,Personal Travel,Business,1052,4,4,5,3,5,3,3,4,2,5,4,3,4,3,338,304.0,neutral or dissatisfied +44383,62588,Male,Loyal Customer,31,Business travel,Business,1726,5,5,5,5,5,5,5,5,1,4,2,5,2,5,0,0.0,satisfied +44384,63623,Male,Loyal Customer,34,Business travel,Business,1440,3,3,3,3,4,4,4,5,5,4,4,4,5,4,147,157.0,satisfied +44385,74533,Female,Loyal Customer,18,Business travel,Business,1126,2,2,2,2,4,3,4,4,5,4,5,5,4,4,0,0.0,satisfied +44386,23564,Female,Loyal Customer,41,Business travel,Eco Plus,770,1,2,2,2,3,3,4,1,1,1,1,2,1,1,15,15.0,neutral or dissatisfied +44387,67595,Female,disloyal Customer,35,Business travel,Business,1242,4,4,4,5,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +44388,81924,Female,Loyal Customer,42,Business travel,Business,3535,5,5,5,5,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +44389,6132,Male,disloyal Customer,21,Business travel,Eco,475,1,0,1,1,2,1,2,2,5,5,5,3,5,2,8,7.0,neutral or dissatisfied +44390,10442,Male,disloyal Customer,33,Business travel,Business,201,3,2,2,1,4,2,4,4,4,2,5,3,4,4,65,100.0,neutral or dissatisfied +44391,93680,Male,Loyal Customer,60,Business travel,Business,3254,5,5,1,5,2,4,5,4,4,4,4,3,4,5,24,66.0,satisfied +44392,72023,Female,Loyal Customer,53,Business travel,Business,3784,3,3,3,3,4,4,4,5,3,4,5,4,5,4,0,0.0,satisfied +44393,57470,Male,Loyal Customer,46,Business travel,Business,1875,1,1,1,1,4,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +44394,35149,Male,disloyal Customer,39,Business travel,Business,1118,2,3,3,3,1,3,4,1,3,5,3,1,3,1,0,20.0,neutral or dissatisfied +44395,125823,Male,disloyal Customer,23,Business travel,Eco,1013,3,3,3,3,5,3,3,5,3,5,4,5,5,5,4,0.0,neutral or dissatisfied +44396,116925,Male,Loyal Customer,49,Business travel,Business,2778,3,3,3,3,2,5,4,5,5,5,5,3,5,4,22,6.0,satisfied +44397,103326,Female,Loyal Customer,35,Personal Travel,Eco,1139,2,4,2,1,5,2,5,5,5,4,3,3,5,5,0,4.0,neutral or dissatisfied +44398,104969,Female,Loyal Customer,59,Business travel,Business,314,2,2,2,2,4,5,4,5,5,5,5,3,5,3,80,69.0,satisfied +44399,54556,Female,Loyal Customer,64,Personal Travel,Eco,925,3,1,3,3,2,3,2,4,4,3,4,2,4,1,0,3.0,neutral or dissatisfied +44400,114469,Male,Loyal Customer,75,Business travel,Business,371,1,1,1,1,4,2,2,1,1,1,1,1,1,1,14,11.0,neutral or dissatisfied +44401,61306,Male,Loyal Customer,9,Personal Travel,Eco,862,2,1,2,2,4,2,4,4,3,3,1,3,2,4,2,1.0,neutral or dissatisfied +44402,18117,Female,Loyal Customer,44,Business travel,Eco Plus,629,3,1,1,1,5,3,4,3,3,3,3,1,3,2,11,8.0,neutral or dissatisfied +44403,65932,Female,Loyal Customer,13,Personal Travel,Eco,569,2,3,2,3,1,2,1,1,5,2,2,1,4,1,59,62.0,neutral or dissatisfied +44404,57316,Male,Loyal Customer,53,Business travel,Business,414,1,1,1,1,4,4,5,5,5,4,5,5,5,3,0,1.0,satisfied +44405,55434,Female,Loyal Customer,44,Business travel,Eco,2136,2,2,4,4,2,2,2,2,5,2,2,2,2,2,0,51.0,neutral or dissatisfied +44406,105469,Female,disloyal Customer,28,Business travel,Business,495,2,2,2,1,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +44407,15297,Female,disloyal Customer,23,Business travel,Eco,612,3,5,3,1,2,3,2,2,3,1,5,2,3,2,0,0.0,neutral or dissatisfied +44408,127101,Female,Loyal Customer,32,Personal Travel,Eco,647,5,5,5,2,1,5,1,1,3,5,1,5,4,1,0,0.0,satisfied +44409,112872,Female,Loyal Customer,39,Business travel,Business,1357,3,3,1,3,4,5,5,2,2,2,2,4,2,5,1,0.0,satisfied +44410,97574,Female,Loyal Customer,53,Business travel,Business,3497,5,5,5,5,5,5,4,3,3,3,3,5,3,3,43,43.0,satisfied +44411,100010,Female,Loyal Customer,44,Business travel,Business,277,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +44412,115618,Male,Loyal Customer,51,Business travel,Business,1898,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +44413,25728,Male,Loyal Customer,40,Personal Travel,Eco,528,5,4,5,2,4,5,4,4,4,3,5,3,4,4,12,0.0,satisfied +44414,111717,Female,Loyal Customer,25,Personal Travel,Eco,541,3,4,3,2,1,3,1,1,4,5,5,5,4,1,33,37.0,neutral or dissatisfied +44415,13734,Male,Loyal Customer,53,Business travel,Eco,401,4,3,3,3,4,4,4,2,2,3,5,4,2,4,242,242.0,satisfied +44416,2415,Male,Loyal Customer,8,Personal Travel,Eco,604,2,5,2,3,5,2,5,5,4,5,4,3,1,5,0,0.0,neutral or dissatisfied +44417,89624,Male,Loyal Customer,24,Business travel,Eco,1035,4,4,4,4,4,4,4,4,2,1,3,3,3,4,26,4.0,neutral or dissatisfied +44418,36007,Female,disloyal Customer,33,Business travel,Eco,399,2,0,2,2,4,2,5,4,2,3,5,4,3,4,0,0.0,neutral or dissatisfied +44419,67683,Female,Loyal Customer,57,Business travel,Business,3161,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +44420,10437,Female,disloyal Customer,22,Business travel,Business,224,0,4,0,1,3,0,3,3,4,5,4,4,4,3,0,0.0,satisfied +44421,110284,Female,disloyal Customer,19,Business travel,Business,883,5,0,5,2,5,5,5,5,3,5,4,4,5,5,8,22.0,satisfied +44422,122491,Male,Loyal Customer,57,Business travel,Eco Plus,808,1,2,2,2,1,1,1,1,1,4,2,3,2,1,0,0.0,neutral or dissatisfied +44423,103301,Male,disloyal Customer,24,Business travel,Eco,1139,4,3,3,3,1,3,1,1,3,2,5,5,5,1,0,0.0,satisfied +44424,36157,Male,Loyal Customer,14,Personal Travel,Business,1674,1,3,1,3,3,1,4,3,4,4,3,2,3,3,42,91.0,neutral or dissatisfied +44425,3,Male,Loyal Customer,41,Business travel,Business,853,4,4,4,4,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +44426,3854,Male,Loyal Customer,53,Personal Travel,Eco,650,3,1,3,2,2,3,2,2,4,1,2,1,3,2,0,0.0,neutral or dissatisfied +44427,106560,Male,Loyal Customer,48,Business travel,Business,2123,1,1,1,1,2,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +44428,113683,Female,Loyal Customer,26,Personal Travel,Eco,197,1,3,0,3,3,0,3,3,4,3,3,3,3,3,16,18.0,neutral or dissatisfied +44429,48500,Female,Loyal Customer,24,Business travel,Business,3795,3,3,3,3,5,4,5,5,3,5,1,4,3,5,0,0.0,satisfied +44430,119193,Female,Loyal Customer,45,Business travel,Eco,331,1,3,3,3,4,4,3,1,1,1,1,1,1,3,26,30.0,neutral or dissatisfied +44431,48424,Male,Loyal Customer,47,Business travel,Eco,819,4,2,2,2,5,4,5,5,1,5,4,5,1,5,0,0.0,satisfied +44432,6253,Female,Loyal Customer,8,Personal Travel,Eco,413,2,5,2,2,5,2,5,5,2,3,4,4,2,5,0,0.0,neutral or dissatisfied +44433,100655,Female,Loyal Customer,58,Business travel,Business,1858,3,3,3,3,2,5,5,4,4,4,4,5,4,4,2,8.0,satisfied +44434,58151,Female,Loyal Customer,42,Business travel,Business,3239,5,5,5,5,2,5,5,4,4,5,4,5,4,4,0,34.0,satisfied +44435,95245,Male,Loyal Customer,49,Personal Travel,Eco,189,3,1,3,4,1,3,1,1,1,3,3,4,4,1,0,0.0,neutral or dissatisfied +44436,111155,Female,Loyal Customer,68,Personal Travel,Eco,1173,3,4,3,1,4,5,4,4,4,3,2,3,4,4,0,0.0,neutral or dissatisfied +44437,49354,Male,Loyal Customer,47,Business travel,Eco,156,4,5,5,5,5,4,5,5,2,1,4,4,2,5,1,1.0,satisfied +44438,79934,Female,Loyal Customer,31,Business travel,Business,3025,3,4,3,3,5,5,5,5,5,2,5,4,4,5,10,0.0,satisfied +44439,32884,Male,Loyal Customer,15,Personal Travel,Eco,216,4,5,0,3,2,0,2,2,5,2,4,5,5,2,0,1.0,neutral or dissatisfied +44440,86004,Male,Loyal Customer,51,Business travel,Business,554,1,1,1,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +44441,123646,Female,disloyal Customer,26,Business travel,Business,214,5,5,5,1,1,5,1,1,3,3,5,3,5,1,0,0.0,satisfied +44442,4521,Male,Loyal Customer,41,Business travel,Business,2836,2,2,3,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +44443,114074,Male,Loyal Customer,9,Business travel,Business,2139,1,1,1,1,1,1,1,4,3,4,4,1,3,1,130,134.0,neutral or dissatisfied +44444,67680,Female,Loyal Customer,47,Business travel,Business,3835,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,9.0,satisfied +44445,6793,Female,Loyal Customer,54,Business travel,Business,224,2,3,3,3,2,2,2,3,4,2,3,2,2,2,65,154.0,neutral or dissatisfied +44446,78719,Female,Loyal Customer,57,Business travel,Business,2306,5,5,5,5,2,4,4,4,4,5,4,4,4,3,59,60.0,satisfied +44447,55200,Male,Loyal Customer,50,Personal Travel,Eco Plus,1609,5,1,5,3,4,5,4,4,3,1,4,1,4,4,0,0.0,satisfied +44448,2614,Female,Loyal Customer,68,Personal Travel,Eco,280,1,1,1,4,2,3,3,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +44449,128532,Male,Loyal Customer,35,Personal Travel,Eco,370,2,4,2,4,3,2,3,3,2,3,4,4,3,3,33,34.0,neutral or dissatisfied +44450,98514,Male,disloyal Customer,37,Business travel,Business,402,1,2,2,2,3,2,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +44451,6570,Female,Loyal Customer,33,Business travel,Business,473,4,1,1,1,2,3,3,4,4,4,4,1,4,3,45,40.0,neutral or dissatisfied +44452,31220,Female,Loyal Customer,60,Personal Travel,Eco,628,4,1,4,2,4,2,2,5,5,4,5,3,5,3,0,5.0,neutral or dissatisfied +44453,126643,Male,Loyal Customer,28,Business travel,Business,2045,4,3,3,3,4,4,4,4,1,4,4,1,4,4,0,0.0,neutral or dissatisfied +44454,28469,Female,disloyal Customer,30,Business travel,Eco,1721,4,4,4,3,3,4,3,3,5,4,3,2,5,3,2,10.0,satisfied +44455,74061,Male,disloyal Customer,40,Business travel,Business,722,4,4,4,3,4,4,5,4,4,4,4,3,4,4,4,0.0,neutral or dissatisfied +44456,42363,Male,Loyal Customer,10,Personal Travel,Eco,550,2,4,2,4,4,2,1,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +44457,127368,Male,Loyal Customer,49,Business travel,Business,1009,5,4,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +44458,17040,Male,Loyal Customer,52,Business travel,Eco,1134,5,4,4,4,5,5,5,2,4,5,4,5,3,5,293,284.0,satisfied +44459,43143,Male,Loyal Customer,39,Personal Travel,Eco Plus,192,3,5,3,3,4,3,4,4,3,2,4,5,5,4,36,40.0,neutral or dissatisfied +44460,93693,Female,Loyal Customer,51,Business travel,Business,1452,3,3,3,3,3,4,5,1,1,2,1,4,1,3,0,0.0,satisfied +44461,83260,Female,Loyal Customer,54,Business travel,Business,1979,5,5,5,5,4,3,4,5,5,5,5,4,5,4,4,11.0,satisfied +44462,68099,Female,disloyal Customer,11,Business travel,Eco,868,4,4,4,3,3,4,3,3,1,5,4,1,3,3,0,3.0,neutral or dissatisfied +44463,126894,Female,Loyal Customer,57,Business travel,Business,2125,1,1,1,1,4,5,5,4,4,4,4,3,4,3,14,0.0,satisfied +44464,107834,Male,Loyal Customer,32,Personal Travel,Eco,349,5,4,5,5,4,5,4,4,3,4,5,3,4,4,3,0.0,satisfied +44465,122811,Male,Loyal Customer,66,Personal Travel,Eco,599,3,2,3,4,3,3,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +44466,22691,Female,Loyal Customer,30,Business travel,Business,1992,3,3,3,3,3,3,3,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +44467,116747,Female,Loyal Customer,29,Personal Travel,Eco Plus,358,1,5,2,3,5,2,5,5,4,2,4,5,4,5,13,4.0,neutral or dissatisfied +44468,49469,Female,Loyal Customer,31,Business travel,Eco,109,5,5,4,5,5,4,5,5,5,2,4,2,2,5,0,2.0,satisfied +44469,17652,Male,Loyal Customer,45,Business travel,Business,1008,5,5,5,5,1,4,2,4,4,4,4,2,4,3,1,1.0,satisfied +44470,88132,Male,disloyal Customer,23,Business travel,Eco,366,2,5,1,1,2,1,2,2,4,3,4,3,5,2,36,31.0,neutral or dissatisfied +44471,118928,Female,disloyal Customer,33,Business travel,Eco Plus,587,3,3,3,4,1,3,1,1,3,3,4,1,3,1,6,0.0,neutral or dissatisfied +44472,44567,Female,Loyal Customer,64,Business travel,Eco,84,3,2,2,2,2,5,4,4,4,3,4,1,4,1,10,16.0,satisfied +44473,79067,Male,Loyal Customer,36,Business travel,Business,226,4,4,4,4,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +44474,86156,Female,Loyal Customer,59,Business travel,Business,1626,1,1,1,1,5,5,4,5,5,5,5,3,5,4,3,7.0,satisfied +44475,80090,Female,Loyal Customer,9,Personal Travel,Eco Plus,950,3,1,2,3,2,2,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +44476,120055,Male,disloyal Customer,23,Business travel,Business,237,4,4,4,1,5,4,5,5,5,5,5,3,4,5,0,0.0,satisfied +44477,106878,Female,disloyal Customer,11,Business travel,Eco,577,4,2,4,3,2,4,2,2,2,4,4,1,3,2,70,63.0,neutral or dissatisfied +44478,58199,Female,Loyal Customer,11,Business travel,Business,1887,3,5,5,5,3,2,3,3,4,3,4,2,4,3,0,9.0,neutral or dissatisfied +44479,47928,Female,Loyal Customer,24,Personal Travel,Eco,817,3,1,3,3,2,3,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +44480,51411,Male,Loyal Customer,63,Personal Travel,Eco Plus,209,5,3,5,3,4,5,2,4,4,5,4,1,4,4,0,0.0,satisfied +44481,121583,Female,Loyal Customer,53,Business travel,Business,936,1,4,4,4,3,3,3,1,1,2,1,1,1,4,8,28.0,neutral or dissatisfied +44482,25499,Female,Loyal Customer,33,Business travel,Business,3889,5,5,5,5,2,1,2,2,2,2,2,4,2,3,0,0.0,satisfied +44483,85581,Female,disloyal Customer,25,Business travel,Business,259,2,0,2,5,3,2,3,3,3,5,5,3,4,3,0,2.0,neutral or dissatisfied +44484,96154,Female,Loyal Customer,28,Business travel,Business,546,3,3,3,3,5,5,5,5,4,5,5,4,4,5,0,0.0,satisfied +44485,8847,Male,disloyal Customer,25,Business travel,Eco,1371,3,3,3,3,4,3,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +44486,43592,Female,Loyal Customer,42,Business travel,Business,297,0,0,0,3,1,3,1,5,5,5,5,5,5,2,0,0.0,satisfied +44487,53369,Female,disloyal Customer,25,Business travel,Eco,968,2,2,2,4,2,2,2,2,2,1,4,1,3,2,34,26.0,neutral or dissatisfied +44488,32355,Female,Loyal Customer,38,Business travel,Business,101,5,5,5,5,3,2,3,4,4,4,5,3,4,2,5,9.0,satisfied +44489,17791,Male,Loyal Customer,42,Business travel,Eco,1214,2,3,3,3,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +44490,31829,Female,disloyal Customer,21,Business travel,Eco,1155,2,3,3,4,3,3,3,4,4,4,1,3,2,3,0,0.0,neutral or dissatisfied +44491,47963,Male,Loyal Customer,56,Personal Travel,Eco,784,1,4,1,3,1,1,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +44492,96432,Male,disloyal Customer,60,Personal Travel,Business,302,2,4,2,1,1,2,2,1,5,5,5,4,4,1,6,4.0,neutral or dissatisfied +44493,90480,Female,disloyal Customer,25,Business travel,Business,404,5,1,5,2,2,5,2,2,5,5,4,5,4,2,0,0.0,satisfied +44494,69036,Female,disloyal Customer,20,Business travel,Business,1389,4,0,4,4,4,4,4,4,5,2,4,5,4,4,0,0.0,satisfied +44495,93469,Male,Loyal Customer,40,Business travel,Business,671,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +44496,75672,Female,disloyal Customer,22,Business travel,Eco,813,4,4,4,5,1,4,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +44497,21967,Female,Loyal Customer,39,Business travel,Business,448,3,1,1,1,3,4,4,3,3,3,3,3,3,2,5,0.0,neutral or dissatisfied +44498,21251,Male,Loyal Customer,71,Business travel,Eco Plus,153,3,3,3,3,3,3,3,3,3,2,4,1,3,3,75,73.0,neutral or dissatisfied +44499,15884,Female,Loyal Customer,9,Personal Travel,Eco,618,1,5,1,3,4,1,1,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +44500,4777,Female,Loyal Customer,60,Business travel,Eco,438,1,1,1,1,2,3,4,1,1,1,1,2,1,4,75,82.0,neutral or dissatisfied +44501,36480,Female,Loyal Customer,41,Business travel,Business,2084,1,1,1,1,5,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +44502,111751,Male,Loyal Customer,32,Personal Travel,Eco,1154,3,4,4,1,2,4,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +44503,105188,Male,Loyal Customer,63,Personal Travel,Eco,220,1,4,1,4,4,1,4,4,1,3,4,3,3,4,25,44.0,neutral or dissatisfied +44504,37001,Female,Loyal Customer,12,Personal Travel,Eco,759,3,4,3,5,4,3,4,4,3,5,5,5,5,4,23,27.0,neutral or dissatisfied +44505,64757,Male,disloyal Customer,22,Business travel,Eco,247,2,5,2,1,4,2,3,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +44506,104446,Female,Loyal Customer,33,Business travel,Eco Plus,1024,2,1,1,1,2,2,2,2,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +44507,69064,Female,Loyal Customer,51,Business travel,Business,1389,2,3,3,3,2,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +44508,92346,Male,Loyal Customer,48,Business travel,Business,2213,4,3,3,3,3,4,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +44509,60894,Male,disloyal Customer,22,Business travel,Eco,420,3,2,3,3,1,3,1,1,1,4,4,4,3,1,0,0.0,neutral or dissatisfied +44510,55629,Male,Loyal Customer,65,Personal Travel,Eco,1824,1,5,1,3,1,1,2,1,3,5,5,3,5,1,2,0.0,neutral or dissatisfied +44511,40189,Male,Loyal Customer,59,Business travel,Business,2040,1,1,1,1,4,3,5,2,2,2,2,1,2,3,0,7.0,satisfied +44512,66774,Male,Loyal Customer,40,Business travel,Business,802,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,3.0,satisfied +44513,66113,Female,disloyal Customer,27,Business travel,Business,583,1,1,1,3,3,1,4,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +44514,34747,Female,Loyal Customer,61,Business travel,Eco,301,2,2,2,2,4,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +44515,49446,Female,Loyal Customer,49,Business travel,Business,421,5,5,5,5,4,4,2,5,5,5,5,2,5,4,7,4.0,satisfied +44516,67246,Female,Loyal Customer,7,Personal Travel,Eco,1119,1,5,1,5,4,1,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +44517,50462,Female,Loyal Customer,57,Business travel,Business,109,1,3,3,3,3,1,2,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +44518,127443,Female,Loyal Customer,40,Business travel,Eco Plus,1009,3,5,5,5,3,3,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +44519,52431,Male,Loyal Customer,45,Personal Travel,Eco,425,3,4,3,3,3,3,3,3,1,4,2,1,4,3,0,0.0,neutral or dissatisfied +44520,49035,Male,Loyal Customer,56,Business travel,Business,363,3,3,3,3,3,2,2,5,5,5,5,2,5,5,0,0.0,satisfied +44521,9711,Female,Loyal Customer,33,Personal Travel,Eco,212,1,0,1,3,1,1,1,3,1,5,3,1,3,1,165,179.0,neutral or dissatisfied +44522,105925,Female,Loyal Customer,33,Business travel,Business,1491,5,5,5,5,2,5,4,4,4,5,4,3,4,3,13,8.0,satisfied +44523,77534,Male,Loyal Customer,30,Business travel,Eco Plus,1310,5,2,2,2,5,5,5,5,2,1,4,5,2,5,24,12.0,satisfied +44524,36144,Female,Loyal Customer,22,Business travel,Eco Plus,1562,3,3,3,3,3,3,4,3,2,5,4,2,3,3,0,20.0,neutral or dissatisfied +44525,44064,Male,Loyal Customer,37,Personal Travel,Eco,610,3,3,3,3,5,3,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +44526,121579,Male,disloyal Customer,37,Business travel,Eco,912,2,2,2,4,4,2,4,4,4,3,4,3,3,4,71,86.0,neutral or dissatisfied +44527,97606,Male,Loyal Customer,59,Business travel,Eco,442,4,5,5,5,4,4,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +44528,89405,Female,Loyal Customer,43,Business travel,Business,1511,3,3,3,3,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +44529,43263,Female,disloyal Customer,39,Business travel,Business,347,3,3,3,1,5,3,5,5,4,5,5,2,3,5,0,0.0,neutral or dissatisfied +44530,115262,Male,disloyal Customer,45,Business travel,Business,342,4,3,3,1,1,4,1,1,3,5,5,5,5,1,0,0.0,satisfied +44531,75939,Female,Loyal Customer,15,Personal Travel,Eco,1572,2,4,2,3,4,2,4,4,4,5,3,4,5,4,0,0.0,neutral or dissatisfied +44532,88737,Male,Loyal Customer,26,Personal Travel,Eco,545,5,1,5,3,1,5,1,1,1,1,4,4,3,1,2,5.0,satisfied +44533,84618,Female,Loyal Customer,59,Business travel,Business,269,0,0,0,1,3,3,5,1,1,1,1,3,1,1,0,0.0,satisfied +44534,114538,Male,Loyal Customer,66,Personal Travel,Business,337,3,4,4,4,4,4,4,3,3,4,3,5,3,3,42,32.0,neutral or dissatisfied +44535,87922,Female,disloyal Customer,22,Business travel,Eco,270,1,2,1,3,1,1,1,1,4,3,4,1,3,1,43,37.0,neutral or dissatisfied +44536,55540,Female,disloyal Customer,37,Business travel,Business,550,4,4,4,1,2,4,2,2,3,4,4,3,5,2,0,0.0,satisfied +44537,28739,Male,Loyal Customer,25,Business travel,Business,1024,3,5,5,5,3,3,3,3,4,5,3,2,4,3,0,30.0,neutral or dissatisfied +44538,122645,Female,disloyal Customer,34,Business travel,Business,361,2,3,3,4,3,2,2,2,4,4,4,2,4,2,138,140.0,neutral or dissatisfied +44539,118763,Male,Loyal Customer,60,Personal Travel,Eco,304,2,4,2,5,1,2,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +44540,55526,Female,Loyal Customer,40,Business travel,Business,550,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +44541,91988,Male,Loyal Customer,40,Business travel,Business,236,4,4,3,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +44542,48751,Female,disloyal Customer,33,Business travel,Business,373,2,2,2,3,4,2,5,4,2,1,3,2,3,4,1,0.0,neutral or dissatisfied +44543,11434,Male,Loyal Customer,27,Business travel,Eco Plus,667,2,3,3,3,2,2,2,2,3,4,3,3,2,2,69,64.0,neutral or dissatisfied +44544,87324,Male,Loyal Customer,40,Business travel,Business,1027,4,4,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +44545,117663,Female,Loyal Customer,40,Business travel,Business,1449,4,4,4,4,3,5,4,4,4,4,4,4,4,4,4,27.0,satisfied +44546,71078,Female,Loyal Customer,25,Personal Travel,Eco,802,1,4,1,1,5,1,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +44547,89444,Female,Loyal Customer,20,Personal Travel,Eco,302,4,5,4,1,5,4,5,5,5,2,5,3,4,5,0,1.0,neutral or dissatisfied +44548,4007,Female,Loyal Customer,55,Business travel,Business,483,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +44549,100019,Male,Loyal Customer,49,Business travel,Business,1955,3,1,5,1,2,2,2,3,3,3,3,3,3,1,52,46.0,neutral or dissatisfied +44550,116893,Male,Loyal Customer,59,Business travel,Business,2306,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +44551,79317,Male,Loyal Customer,25,Personal Travel,Eco,2248,2,4,2,2,4,2,4,4,5,2,4,4,4,4,10,0.0,neutral or dissatisfied +44552,3531,Female,Loyal Customer,46,Business travel,Business,157,3,3,3,3,2,3,5,4,4,4,4,4,4,1,0,3.0,satisfied +44553,127079,Female,Loyal Customer,48,Business travel,Eco,370,2,5,5,5,5,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +44554,109919,Male,Loyal Customer,37,Personal Travel,Eco,1144,1,5,1,2,2,1,4,2,3,5,4,4,4,2,5,13.0,neutral or dissatisfied +44555,68673,Female,disloyal Customer,21,Business travel,Eco,237,2,3,2,3,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +44556,91107,Male,Loyal Customer,31,Personal Travel,Eco,270,1,3,1,3,4,1,1,4,3,3,3,3,3,4,13,9.0,neutral or dissatisfied +44557,86779,Female,Loyal Customer,25,Business travel,Business,2943,3,3,3,3,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +44558,82131,Female,Loyal Customer,46,Business travel,Business,2519,4,4,4,4,5,5,5,4,5,5,5,5,3,5,23,21.0,satisfied +44559,66514,Female,Loyal Customer,53,Personal Travel,Eco,447,2,5,2,1,1,3,4,3,3,2,3,5,3,2,46,48.0,neutral or dissatisfied +44560,67587,Male,disloyal Customer,37,Business travel,Business,1235,1,1,1,2,1,1,1,1,3,4,5,3,5,1,0,1.0,neutral or dissatisfied +44561,8957,Female,Loyal Customer,49,Business travel,Business,738,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +44562,70315,Male,Loyal Customer,26,Business travel,Business,1501,3,3,3,3,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +44563,100662,Female,Loyal Customer,46,Business travel,Business,2954,2,2,2,2,5,5,4,4,4,4,4,5,4,3,10,33.0,satisfied +44564,65062,Male,Loyal Customer,13,Personal Travel,Eco,224,5,4,0,4,4,0,3,4,3,4,4,5,4,4,1,5.0,satisfied +44565,124102,Male,Loyal Customer,28,Business travel,Business,529,3,3,2,3,4,4,4,4,4,5,5,4,5,4,20,28.0,satisfied +44566,103540,Male,disloyal Customer,36,Business travel,Eco,738,2,2,2,3,1,2,1,1,1,1,4,4,3,1,21,10.0,neutral or dissatisfied +44567,16373,Male,Loyal Customer,9,Business travel,Business,1325,4,1,1,1,4,4,4,4,4,3,3,1,4,4,51,60.0,neutral or dissatisfied +44568,26638,Female,Loyal Customer,37,Business travel,Business,1527,1,1,1,1,1,3,5,2,2,2,2,1,2,3,0,0.0,satisfied +44569,107462,Male,Loyal Customer,33,Business travel,Business,3684,2,2,2,2,5,5,5,5,3,3,4,4,4,5,26,20.0,satisfied +44570,40873,Female,Loyal Customer,67,Personal Travel,Eco,558,3,4,3,3,2,4,5,5,5,3,5,3,5,4,2,5.0,neutral or dissatisfied +44571,107452,Female,disloyal Customer,34,Business travel,Eco Plus,725,1,1,1,4,1,3,3,1,2,3,3,3,4,3,194,204.0,neutral or dissatisfied +44572,29198,Female,Loyal Customer,46,Personal Travel,Eco Plus,954,2,5,2,3,2,5,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +44573,14426,Male,Loyal Customer,59,Business travel,Eco Plus,585,5,3,3,3,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +44574,4576,Male,Loyal Customer,70,Personal Travel,Business,416,1,5,1,3,5,5,1,2,2,1,2,2,2,5,74,76.0,neutral or dissatisfied +44575,74459,Female,Loyal Customer,44,Business travel,Business,1171,3,3,3,3,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +44576,121265,Male,Loyal Customer,63,Personal Travel,Eco,2075,2,3,2,3,3,2,3,3,2,2,2,2,4,3,0,7.0,neutral or dissatisfied +44577,82475,Female,Loyal Customer,60,Personal Travel,Eco,241,1,4,1,5,5,4,4,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +44578,14113,Male,Loyal Customer,41,Business travel,Eco Plus,453,2,1,1,1,2,2,2,2,5,4,2,5,1,2,51,42.0,satisfied +44579,2270,Male,disloyal Customer,24,Business travel,Business,691,4,5,3,4,2,3,2,2,3,3,5,4,5,2,9,3.0,satisfied +44580,121311,Female,disloyal Customer,17,Business travel,Business,1009,5,0,5,1,1,5,1,1,5,2,4,4,5,1,0,0.0,satisfied +44581,119315,Male,Loyal Customer,30,Personal Travel,Eco,214,3,0,3,1,5,3,3,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +44582,75988,Female,Loyal Customer,32,Personal Travel,Eco,228,4,4,0,4,2,0,2,2,2,4,3,1,4,2,7,0.0,satisfied +44583,113484,Male,Loyal Customer,47,Business travel,Eco,226,3,4,4,4,3,3,3,3,1,3,4,1,4,3,24,10.0,neutral or dissatisfied +44584,52775,Female,Loyal Customer,11,Business travel,Business,1874,2,3,3,3,2,2,2,2,2,3,4,1,3,2,8,11.0,neutral or dissatisfied +44585,69800,Male,Loyal Customer,46,Business travel,Business,3331,4,4,4,4,5,5,4,4,4,4,4,5,4,4,14,10.0,satisfied +44586,18474,Female,Loyal Customer,39,Business travel,Eco,201,5,5,5,5,5,5,5,5,2,1,2,4,1,5,0,0.0,satisfied +44587,121525,Female,disloyal Customer,39,Business travel,Business,912,4,4,4,4,4,4,1,4,4,3,5,4,5,4,3,19.0,neutral or dissatisfied +44588,19589,Male,Loyal Customer,14,Personal Travel,Eco,212,2,4,2,3,1,2,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +44589,65392,Male,Loyal Customer,11,Personal Travel,Eco,631,2,3,2,1,5,2,5,5,4,2,4,4,2,5,0,0.0,neutral or dissatisfied +44590,79635,Female,Loyal Customer,24,Business travel,Eco,762,4,2,3,3,4,4,3,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +44591,41273,Male,Loyal Customer,30,Personal Travel,Business,788,2,4,2,4,3,2,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +44592,33311,Female,Loyal Customer,46,Business travel,Business,2409,4,4,4,4,2,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +44593,64460,Male,Loyal Customer,54,Business travel,Eco Plus,989,4,3,3,3,4,4,4,4,4,5,4,3,4,4,25,17.0,neutral or dissatisfied +44594,78233,Male,Loyal Customer,42,Personal Travel,Eco,259,3,4,3,3,4,3,4,4,4,1,1,5,3,4,10,1.0,neutral or dissatisfied +44595,112932,Male,Loyal Customer,48,Personal Travel,Eco,1390,2,5,2,4,3,2,3,3,1,5,2,5,1,3,33,14.0,neutral or dissatisfied +44596,107635,Male,Loyal Customer,39,Business travel,Business,251,0,0,0,4,2,2,2,3,4,4,4,2,3,2,162,158.0,satisfied +44597,102572,Male,Loyal Customer,52,Business travel,Business,3825,2,2,2,2,3,5,5,4,4,4,4,5,4,4,2,0.0,satisfied +44598,8351,Female,Loyal Customer,26,Personal Travel,Eco,783,0,5,0,3,1,0,2,1,3,5,5,5,4,1,0,0.0,satisfied +44599,51027,Female,Loyal Customer,26,Personal Travel,Eco,207,4,4,4,5,4,4,4,4,5,2,3,4,3,4,0,2.0,neutral or dissatisfied +44600,34378,Female,Loyal Customer,22,Business travel,Eco,728,0,5,0,3,4,0,4,4,2,4,5,4,4,4,0,0.0,satisfied +44601,107032,Female,disloyal Customer,43,Business travel,Eco,395,3,4,3,4,4,3,4,4,1,3,4,1,3,4,2,2.0,neutral or dissatisfied +44602,120117,Male,Loyal Customer,36,Business travel,Eco,1176,3,3,3,3,3,3,3,3,3,3,4,2,4,3,30,65.0,neutral or dissatisfied +44603,31823,Male,Loyal Customer,40,Business travel,Business,2762,2,2,2,2,5,5,5,2,5,3,2,5,1,5,0,12.0,satisfied +44604,106991,Male,Loyal Customer,55,Personal Travel,Eco,937,1,3,1,2,1,1,1,1,2,3,2,4,3,1,30,20.0,neutral or dissatisfied +44605,89165,Female,Loyal Customer,33,Personal Travel,Eco,1947,2,5,2,3,4,2,4,4,3,4,4,3,4,4,2,14.0,neutral or dissatisfied +44606,88454,Female,Loyal Customer,48,Business travel,Business,3358,4,4,4,4,5,2,4,5,5,5,5,3,5,3,112,130.0,satisfied +44607,106700,Female,Loyal Customer,49,Business travel,Eco,516,3,3,3,3,2,2,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +44608,126430,Female,Loyal Customer,58,Business travel,Eco Plus,231,5,1,1,1,5,5,1,5,5,5,5,5,5,2,74,92.0,satisfied +44609,54711,Female,Loyal Customer,74,Business travel,Eco,564,5,1,1,1,2,4,5,5,5,5,5,2,5,2,0,5.0,satisfied +44610,127722,Male,Loyal Customer,41,Business travel,Business,2231,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +44611,128316,Female,disloyal Customer,22,Business travel,Eco,647,1,5,1,4,5,1,5,5,3,4,4,5,5,5,3,0.0,neutral or dissatisfied +44612,115416,Male,disloyal Customer,20,Business travel,Eco,296,2,0,2,1,3,2,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +44613,119476,Female,disloyal Customer,20,Business travel,Eco,814,2,2,2,4,4,2,4,4,3,2,4,4,5,4,0,11.0,neutral or dissatisfied +44614,24224,Female,Loyal Customer,33,Business travel,Eco,134,1,3,3,3,1,1,1,1,1,5,3,3,4,1,5,34.0,neutral or dissatisfied +44615,100556,Male,Loyal Customer,55,Personal Travel,Eco,1111,3,5,3,2,1,3,1,1,4,4,4,4,5,1,8,4.0,neutral or dissatisfied +44616,25812,Male,Loyal Customer,27,Business travel,Business,1747,3,3,3,3,4,4,4,4,5,1,3,3,4,4,19,26.0,satisfied +44617,54687,Female,Loyal Customer,69,Business travel,Eco,861,4,1,1,1,5,4,4,4,4,4,4,3,4,3,53,93.0,neutral or dissatisfied +44618,70697,Male,Loyal Customer,39,Personal Travel,Eco Plus,447,3,4,3,3,4,3,4,4,3,5,4,3,4,4,3,0.0,neutral or dissatisfied +44619,111888,Male,Loyal Customer,37,Business travel,Eco,404,3,5,3,5,3,4,3,3,1,2,5,3,2,3,14,0.0,satisfied +44620,53718,Male,Loyal Customer,66,Personal Travel,Eco,1190,1,4,1,3,5,1,5,5,1,4,3,2,3,5,1,0.0,neutral or dissatisfied +44621,104491,Male,Loyal Customer,59,Personal Travel,Eco,860,4,4,4,4,1,4,1,1,1,1,4,4,4,1,0,0.0,satisfied +44622,118140,Male,Loyal Customer,53,Business travel,Business,1444,1,1,1,1,3,5,5,4,4,5,4,3,4,5,2,0.0,satisfied +44623,42026,Female,Loyal Customer,41,Business travel,Eco,116,5,5,5,5,5,5,5,5,5,5,4,4,2,5,0,1.0,satisfied +44624,45199,Female,Loyal Customer,50,Business travel,Eco,1120,2,1,1,1,5,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +44625,39249,Male,disloyal Customer,48,Business travel,Eco,173,4,0,3,1,4,3,5,4,4,5,5,2,4,4,0,0.0,satisfied +44626,113591,Female,disloyal Customer,23,Business travel,Eco,414,3,0,3,2,1,3,1,1,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +44627,122348,Female,Loyal Customer,53,Business travel,Business,529,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +44628,16345,Female,Loyal Customer,51,Business travel,Eco,160,5,4,4,4,5,2,1,5,5,5,5,5,5,2,27,11.0,satisfied +44629,114555,Female,Loyal Customer,26,Personal Travel,Business,342,2,4,2,1,1,2,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +44630,59921,Male,Loyal Customer,35,Business travel,Business,3754,3,1,1,1,3,4,4,3,3,3,3,3,3,3,3,0.0,neutral or dissatisfied +44631,35267,Female,Loyal Customer,37,Business travel,Eco,1076,1,4,4,4,1,1,1,2,1,4,4,1,4,1,237,244.0,neutral or dissatisfied +44632,30986,Female,Loyal Customer,42,Personal Travel,Eco,1476,4,1,3,3,3,2,4,1,1,3,1,2,1,2,64,74.0,neutral or dissatisfied +44633,49976,Female,Loyal Customer,69,Business travel,Business,3055,1,2,2,2,4,3,3,1,1,1,1,1,1,4,8,0.0,neutral or dissatisfied +44634,27175,Male,Loyal Customer,43,Personal Travel,Eco,2701,3,5,3,5,3,1,1,3,2,5,4,1,4,1,0,0.0,neutral or dissatisfied +44635,122845,Female,Loyal Customer,40,Business travel,Business,226,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +44636,119593,Female,disloyal Customer,38,Business travel,Business,1979,4,4,4,4,4,4,2,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +44637,13058,Female,Loyal Customer,35,Business travel,Eco,936,4,5,5,5,4,4,4,4,2,1,3,3,5,4,0,0.0,satisfied +44638,16234,Male,Loyal Customer,48,Business travel,Business,631,1,1,1,1,5,5,5,5,5,5,5,5,5,5,16,14.0,satisfied +44639,119575,Male,Loyal Customer,30,Personal Travel,Eco Plus,814,1,0,1,4,1,1,1,1,4,3,4,4,3,1,0,0.0,neutral or dissatisfied +44640,14522,Male,Loyal Customer,52,Business travel,Eco,288,4,1,4,1,4,4,4,4,1,5,1,4,3,4,0,0.0,satisfied +44641,129516,Male,Loyal Customer,45,Business travel,Business,1744,2,2,2,2,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +44642,45376,Male,Loyal Customer,61,Business travel,Eco Plus,150,4,1,1,1,4,4,4,4,3,5,3,1,3,4,0,0.0,satisfied +44643,3866,Male,Loyal Customer,15,Personal Travel,Business,290,3,5,3,4,5,3,3,5,5,2,4,3,5,5,9,0.0,neutral or dissatisfied +44644,7844,Male,Loyal Customer,26,Business travel,Business,1760,3,3,2,3,4,4,4,4,2,4,5,4,3,4,94,160.0,satisfied +44645,98288,Female,Loyal Customer,23,Personal Travel,Eco,1136,5,4,5,2,4,5,5,4,5,3,5,5,4,4,1,0.0,satisfied +44646,20407,Male,Loyal Customer,32,Business travel,Eco,196,4,1,1,1,4,4,4,4,2,5,1,3,4,4,96,89.0,satisfied +44647,9933,Male,Loyal Customer,47,Business travel,Eco,457,1,5,5,5,1,1,1,1,2,1,2,3,2,1,7,4.0,neutral or dissatisfied +44648,90084,Female,Loyal Customer,26,Business travel,Eco,1086,4,2,1,2,4,3,1,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +44649,87867,Female,Loyal Customer,40,Business travel,Business,2269,3,5,3,3,3,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +44650,1447,Female,disloyal Customer,26,Business travel,Business,772,4,4,4,1,1,4,1,1,5,2,5,3,5,1,0,0.0,satisfied +44651,95699,Male,Loyal Customer,33,Business travel,Business,3233,3,3,4,3,4,4,4,4,3,4,5,4,5,4,37,43.0,satisfied +44652,31231,Female,disloyal Customer,26,Business travel,Business,472,1,2,1,3,2,1,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +44653,57421,Male,Loyal Customer,56,Personal Travel,Eco,258,2,4,0,5,3,0,3,3,2,3,5,5,1,3,0,0.0,neutral or dissatisfied +44654,491,Female,Loyal Customer,57,Business travel,Business,229,3,3,3,3,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +44655,105551,Female,Loyal Customer,60,Personal Travel,Eco,611,2,5,2,2,3,1,3,1,1,2,1,5,1,3,10,0.0,neutral or dissatisfied +44656,84092,Male,Loyal Customer,40,Personal Travel,Eco,757,1,5,1,4,4,1,4,4,4,4,5,3,4,4,6,52.0,neutral or dissatisfied +44657,41496,Male,Loyal Customer,27,Business travel,Business,1504,5,5,4,5,4,5,4,4,3,2,5,1,4,4,0,0.0,satisfied +44658,61119,Male,Loyal Customer,60,Business travel,Business,3967,5,5,5,5,2,5,5,4,4,5,4,5,4,4,2,9.0,satisfied +44659,90825,Female,Loyal Customer,46,Business travel,Business,270,4,4,4,4,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +44660,71645,Female,Loyal Customer,69,Personal Travel,Eco,1012,4,4,4,3,5,1,4,2,2,4,2,1,2,2,0,0.0,satisfied +44661,74800,Female,Loyal Customer,15,Business travel,Eco Plus,1205,3,4,4,4,3,3,2,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +44662,89987,Female,Loyal Customer,57,Personal Travel,Eco Plus,1310,2,4,2,3,4,3,5,2,2,2,2,3,2,5,3,1.0,neutral or dissatisfied +44663,63337,Male,Loyal Customer,56,Business travel,Eco,447,4,5,5,5,4,4,4,4,2,3,3,1,4,4,1,3.0,satisfied +44664,29652,Female,Loyal Customer,53,Personal Travel,Eco,1448,3,3,3,2,4,1,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +44665,36651,Male,Loyal Customer,11,Personal Travel,Eco,1197,3,1,4,3,4,4,4,4,1,5,2,3,2,4,0,0.0,neutral or dissatisfied +44666,3644,Male,Loyal Customer,43,Business travel,Business,431,3,3,3,3,4,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +44667,129780,Female,Loyal Customer,17,Personal Travel,Eco,337,4,3,4,5,3,4,3,3,4,5,3,3,2,3,57,51.0,neutral or dissatisfied +44668,46266,Female,Loyal Customer,66,Personal Travel,Eco,679,1,5,2,1,3,5,5,2,2,2,4,4,2,3,11,23.0,neutral or dissatisfied +44669,56105,Female,Loyal Customer,79,Business travel,Eco,902,5,4,4,4,5,5,5,4,4,1,5,5,5,5,0,5.0,satisfied +44670,104517,Female,Loyal Customer,52,Personal Travel,Eco,942,4,4,4,5,1,4,3,4,4,4,4,1,4,4,0,20.0,neutral or dissatisfied +44671,94755,Male,Loyal Customer,33,Business travel,Eco,239,3,5,5,5,3,3,3,3,2,2,3,1,2,3,3,1.0,neutral or dissatisfied +44672,25166,Female,Loyal Customer,48,Business travel,Business,369,5,5,5,5,3,5,1,4,4,4,4,1,4,4,0,0.0,satisfied +44673,60115,Female,Loyal Customer,11,Business travel,Business,1182,3,3,3,3,5,5,5,5,4,5,5,3,5,5,0,0.0,satisfied +44674,80845,Female,Loyal Customer,55,Business travel,Eco,692,4,5,5,5,3,4,4,4,4,4,4,4,4,2,3,11.0,neutral or dissatisfied +44675,102024,Female,Loyal Customer,43,Business travel,Business,3194,2,2,1,2,4,4,5,3,3,3,3,5,3,4,0,1.0,satisfied +44676,42811,Female,disloyal Customer,39,Business travel,Business,896,2,2,2,4,5,2,5,5,1,3,4,2,3,5,7,17.0,neutral or dissatisfied +44677,61467,Female,Loyal Customer,24,Business travel,Business,2442,1,1,1,1,5,5,5,5,5,3,5,4,5,5,7,0.0,satisfied +44678,57654,Female,Loyal Customer,33,Personal Travel,Eco,200,4,5,4,3,2,4,2,2,3,3,5,1,3,2,1,0.0,neutral or dissatisfied +44679,50917,Female,Loyal Customer,65,Personal Travel,Eco,109,3,4,3,2,5,4,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +44680,80991,Male,Loyal Customer,49,Business travel,Business,2508,3,3,3,3,4,3,5,5,5,5,5,4,5,1,0,0.0,satisfied +44681,36182,Male,Loyal Customer,46,Business travel,Eco Plus,1674,1,1,4,1,1,1,1,1,2,2,3,4,4,1,9,88.0,neutral or dissatisfied +44682,108746,Female,Loyal Customer,37,Business travel,Business,2435,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,1.0,satisfied +44683,10329,Female,Loyal Customer,49,Business travel,Business,1727,1,1,4,1,5,5,4,4,4,4,4,4,4,3,23,13.0,satisfied +44684,106613,Female,Loyal Customer,57,Business travel,Business,3131,4,5,4,4,2,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +44685,68446,Female,Loyal Customer,51,Business travel,Business,1303,1,1,1,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +44686,34123,Male,Loyal Customer,9,Business travel,Eco,1046,2,1,5,5,2,2,1,2,4,1,4,3,4,2,0,2.0,neutral or dissatisfied +44687,127021,Female,disloyal Customer,22,Business travel,Eco,647,1,3,1,3,3,1,3,3,2,2,3,3,3,3,3,0.0,neutral or dissatisfied +44688,68679,Female,disloyal Customer,25,Business travel,Eco,237,2,0,2,2,3,2,3,3,3,5,3,1,4,3,2,0.0,neutral or dissatisfied +44689,23071,Male,Loyal Customer,23,Business travel,Eco Plus,820,3,3,3,3,3,3,4,3,1,1,4,2,4,3,31,31.0,neutral or dissatisfied +44690,83963,Female,Loyal Customer,24,Business travel,Eco,321,4,1,1,1,4,4,2,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +44691,64909,Male,Loyal Customer,25,Business travel,Eco,551,4,1,1,1,4,4,2,4,1,5,3,2,4,4,0,0.0,neutral or dissatisfied +44692,45298,Male,Loyal Customer,56,Business travel,Business,188,4,3,5,3,1,4,1,2,2,3,3,1,3,1,184,175.0,neutral or dissatisfied +44693,114492,Male,Loyal Customer,56,Business travel,Business,2206,1,1,1,1,3,3,3,1,1,2,1,4,1,3,51,40.0,neutral or dissatisfied +44694,104225,Male,Loyal Customer,11,Personal Travel,Eco,680,2,4,2,3,1,2,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +44695,49852,Female,Loyal Customer,47,Business travel,Business,3506,4,4,4,4,1,3,1,4,4,4,4,3,4,2,9,22.0,satisfied +44696,2957,Female,Loyal Customer,50,Business travel,Business,835,2,2,2,2,2,3,3,2,2,2,2,4,2,1,25,3.0,neutral or dissatisfied +44697,17424,Female,Loyal Customer,37,Business travel,Eco,351,5,1,1,1,5,5,5,5,4,5,4,1,1,5,2,0.0,satisfied +44698,128451,Male,Loyal Customer,40,Personal Travel,Eco,304,4,5,3,4,3,3,3,3,5,5,4,3,4,3,0,2.0,satisfied +44699,115994,Male,Loyal Customer,33,Personal Travel,Eco,342,2,4,2,3,3,2,2,3,3,4,5,5,4,3,7,5.0,neutral or dissatisfied +44700,116284,Female,Loyal Customer,19,Personal Travel,Eco,446,3,4,3,3,1,3,1,1,4,2,5,4,4,1,30,18.0,neutral or dissatisfied +44701,35713,Female,Loyal Customer,15,Personal Travel,Eco,2586,2,5,2,1,2,1,1,4,5,4,5,1,3,1,0,22.0,neutral or dissatisfied +44702,4373,Female,Loyal Customer,22,Business travel,Business,3487,3,4,5,4,3,3,3,1,4,3,4,3,2,3,112,139.0,neutral or dissatisfied +44703,84692,Female,Loyal Customer,52,Personal Travel,Eco,2182,1,4,1,4,3,2,1,4,4,1,2,1,4,3,0,0.0,neutral or dissatisfied +44704,8897,Female,Loyal Customer,27,Business travel,Eco Plus,622,2,2,2,2,2,2,2,2,1,3,3,3,4,2,11,2.0,neutral or dissatisfied +44705,82957,Male,Loyal Customer,31,Personal Travel,Business,1145,2,5,2,3,3,2,3,3,3,2,5,3,4,3,0,7.0,neutral or dissatisfied +44706,117416,Male,Loyal Customer,39,Business travel,Business,1460,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,21.0,satisfied +44707,98774,Male,Loyal Customer,18,Personal Travel,Eco,2075,3,2,3,2,3,3,3,3,2,5,1,2,2,3,106,117.0,neutral or dissatisfied +44708,38404,Male,Loyal Customer,36,Personal Travel,Eco,1754,3,3,3,3,1,3,1,1,5,2,1,1,4,1,0,29.0,neutral or dissatisfied +44709,98205,Female,Loyal Customer,7,Personal Travel,Eco,327,3,0,3,2,4,3,3,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +44710,3560,Male,disloyal Customer,44,Business travel,Business,227,2,2,2,4,1,2,1,1,1,5,3,1,4,1,0,0.0,neutral or dissatisfied +44711,89788,Male,Loyal Customer,20,Personal Travel,Eco,1096,3,5,3,4,5,3,5,5,3,5,4,5,1,5,0,0.0,neutral or dissatisfied +44712,55036,Female,Loyal Customer,58,Business travel,Eco,1303,3,1,1,1,3,3,3,3,4,3,3,3,2,3,161,158.0,neutral or dissatisfied +44713,104658,Male,disloyal Customer,48,Business travel,Business,641,5,5,5,1,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +44714,73992,Female,Loyal Customer,52,Business travel,Business,1972,4,4,4,4,3,4,5,5,5,5,5,4,5,4,2,0.0,satisfied +44715,32809,Male,Loyal Customer,69,Business travel,Business,216,3,3,3,3,2,2,4,5,5,5,5,3,5,2,0,0.0,satisfied +44716,50986,Male,Loyal Customer,25,Personal Travel,Eco,153,3,5,3,1,1,3,1,1,4,5,4,3,5,1,3,0.0,neutral or dissatisfied +44717,45464,Female,disloyal Customer,20,Business travel,Eco,522,1,0,0,1,5,0,3,5,4,1,5,1,1,5,7,18.0,neutral or dissatisfied +44718,1914,Male,disloyal Customer,38,Business travel,Business,295,3,3,3,3,4,3,2,4,5,4,5,3,5,4,24,17.0,satisfied +44719,54562,Male,Loyal Customer,30,Business travel,Eco Plus,925,5,3,5,3,5,5,5,5,5,3,5,5,1,5,5,6.0,satisfied +44720,58767,Female,Loyal Customer,36,Business travel,Business,1005,1,4,4,4,4,4,4,1,1,1,1,2,1,4,3,0.0,neutral or dissatisfied +44721,125024,Male,Loyal Customer,48,Business travel,Eco Plus,184,3,5,5,5,3,3,3,3,3,2,4,2,3,3,0,9.0,neutral or dissatisfied +44722,61782,Female,Loyal Customer,53,Personal Travel,Eco,1609,1,5,1,4,3,4,5,2,2,1,2,3,2,4,0,2.0,neutral or dissatisfied +44723,10550,Female,disloyal Customer,37,Business travel,Business,247,1,0,0,3,3,0,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +44724,117748,Female,Loyal Customer,16,Personal Travel,Eco,935,3,5,3,1,2,3,2,2,3,3,4,4,4,2,24,11.0,neutral or dissatisfied +44725,73239,Female,Loyal Customer,40,Personal Travel,Eco Plus,946,3,4,3,5,1,3,1,1,1,5,5,2,3,1,0,0.0,neutral or dissatisfied +44726,11768,Male,Loyal Customer,47,Personal Travel,Eco,395,2,2,4,4,3,4,3,3,1,5,3,2,3,3,50,45.0,neutral or dissatisfied +44727,21805,Male,Loyal Customer,42,Business travel,Eco,341,4,4,4,4,4,4,4,4,3,4,2,3,1,4,80,67.0,satisfied +44728,26312,Female,Loyal Customer,15,Business travel,Business,1947,3,1,1,1,3,3,3,3,3,1,3,2,3,3,6,9.0,neutral or dissatisfied +44729,46351,Female,Loyal Customer,38,Business travel,Business,1646,3,3,3,3,5,5,5,2,4,5,2,5,5,5,187,185.0,satisfied +44730,4423,Male,Loyal Customer,56,Business travel,Business,762,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +44731,24662,Female,Loyal Customer,19,Personal Travel,Eco,861,2,1,2,3,5,2,5,5,4,4,3,1,2,5,34,30.0,neutral or dissatisfied +44732,102401,Female,Loyal Customer,44,Personal Travel,Eco,236,3,5,3,3,5,5,5,1,1,3,1,4,1,5,0,5.0,neutral or dissatisfied +44733,105777,Male,Loyal Customer,72,Business travel,Business,2975,2,2,2,2,3,4,3,4,4,4,4,4,4,2,0,0.0,satisfied +44734,90695,Male,Loyal Customer,49,Business travel,Business,545,4,4,4,4,3,5,5,5,5,5,5,3,5,4,5,0.0,satisfied +44735,55865,Female,Loyal Customer,35,Business travel,Business,2438,3,3,3,3,3,5,4,3,3,3,3,5,3,4,4,0.0,satisfied +44736,103018,Female,Loyal Customer,46,Business travel,Business,460,3,2,2,2,2,1,2,3,3,3,3,3,3,2,5,0.0,neutral or dissatisfied +44737,27688,Male,Loyal Customer,44,Business travel,Business,1107,4,4,3,4,4,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +44738,19778,Male,disloyal Customer,26,Business travel,Eco,578,3,3,2,3,2,1,1,1,4,2,1,1,5,1,131,121.0,neutral or dissatisfied +44739,90819,Female,Loyal Customer,39,Business travel,Business,3499,3,1,1,1,3,4,4,3,3,3,3,1,3,4,2,0.0,neutral or dissatisfied +44740,104330,Female,Loyal Customer,33,Business travel,Business,3877,2,4,4,4,3,2,3,2,2,2,2,1,2,3,15,10.0,neutral or dissatisfied +44741,110136,Female,disloyal Customer,22,Business travel,Eco,1056,3,3,3,3,3,3,3,3,4,3,3,1,3,3,30,47.0,neutral or dissatisfied +44742,960,Male,Loyal Customer,48,Business travel,Business,102,0,4,0,2,5,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +44743,47531,Female,Loyal Customer,56,Personal Travel,Eco,541,2,5,2,3,4,4,2,1,1,2,5,4,1,1,46,33.0,neutral or dissatisfied +44744,102284,Female,disloyal Customer,20,Business travel,Eco,197,2,3,2,3,2,2,2,2,1,1,3,3,3,2,47,54.0,neutral or dissatisfied +44745,12485,Female,Loyal Customer,53,Business travel,Eco Plus,253,4,3,3,3,4,5,3,4,4,4,4,2,4,4,5,0.0,satisfied +44746,25438,Male,disloyal Customer,25,Business travel,Eco,669,2,2,2,4,1,2,1,1,4,4,4,5,1,1,0,0.0,neutral or dissatisfied +44747,86056,Female,Loyal Customer,7,Personal Travel,Eco,447,3,4,3,2,4,3,4,4,3,5,4,3,5,4,77,88.0,neutral or dissatisfied +44748,82111,Male,Loyal Customer,15,Personal Travel,Eco,1276,1,3,1,2,2,1,2,2,4,4,3,3,4,2,0,0.0,neutral or dissatisfied +44749,97770,Female,Loyal Customer,55,Business travel,Business,471,1,4,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +44750,48739,Female,Loyal Customer,40,Business travel,Business,2768,0,5,0,4,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +44751,15521,Female,Loyal Customer,48,Business travel,Eco Plus,164,2,1,1,1,1,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +44752,82153,Female,Loyal Customer,46,Business travel,Business,311,4,4,5,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +44753,84098,Female,Loyal Customer,48,Business travel,Business,879,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +44754,35062,Female,Loyal Customer,9,Business travel,Business,1780,1,5,5,5,1,1,1,1,4,1,3,3,4,1,24,29.0,neutral or dissatisfied +44755,111615,Male,Loyal Customer,28,Business travel,Business,2057,4,4,4,4,5,5,5,5,5,5,4,4,5,5,22,10.0,satisfied +44756,55662,Female,disloyal Customer,24,Business travel,Eco,1062,5,5,5,5,5,5,5,5,3,5,5,5,5,5,0,7.0,satisfied +44757,111470,Male,Loyal Customer,66,Personal Travel,Eco,1024,2,5,2,4,3,2,3,3,5,3,4,3,5,3,1,0.0,neutral or dissatisfied +44758,53108,Male,Loyal Customer,53,Business travel,Business,2065,2,3,3,3,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +44759,64374,Female,Loyal Customer,8,Personal Travel,Eco,1158,1,4,1,1,1,1,1,1,3,4,5,5,5,1,22,15.0,neutral or dissatisfied +44760,42101,Female,Loyal Customer,26,Business travel,Business,2745,3,1,3,1,3,3,3,3,1,3,2,3,1,3,2,13.0,neutral or dissatisfied +44761,118874,Male,Loyal Customer,29,Business travel,Eco,1136,2,2,2,2,2,2,2,2,3,3,4,1,3,2,20,22.0,neutral or dissatisfied +44762,57990,Female,Loyal Customer,29,Business travel,Business,2191,1,1,3,1,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +44763,46836,Female,Loyal Customer,28,Business travel,Business,2465,1,1,1,1,4,4,4,4,4,4,5,2,1,4,0,0.0,satisfied +44764,51364,Male,Loyal Customer,32,Personal Travel,Eco Plus,363,2,5,2,2,2,2,2,2,4,4,5,4,4,2,5,17.0,neutral or dissatisfied +44765,15263,Female,Loyal Customer,52,Business travel,Business,1640,2,5,5,5,5,3,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +44766,53575,Female,Loyal Customer,60,Business travel,Eco,1195,5,2,2,2,2,3,4,5,5,5,5,1,5,3,14,0.0,satisfied +44767,7572,Female,Loyal Customer,59,Business travel,Business,3718,2,2,2,2,3,4,5,5,5,5,5,4,5,3,55,49.0,satisfied +44768,72521,Female,disloyal Customer,20,Business travel,Eco,1121,1,1,1,3,5,1,5,5,3,1,3,2,3,5,0,18.0,neutral or dissatisfied +44769,51647,Female,Loyal Customer,45,Business travel,Eco,651,2,1,1,1,3,3,4,2,2,2,2,3,2,3,24,15.0,neutral or dissatisfied +44770,54733,Male,Loyal Customer,33,Personal Travel,Eco,854,4,4,4,5,3,4,3,3,3,2,4,4,4,3,6,0.0,neutral or dissatisfied +44771,82880,Male,Loyal Customer,25,Business travel,Business,3214,2,2,2,2,2,2,2,2,1,2,3,3,2,2,0,0.0,neutral or dissatisfied +44772,42473,Male,Loyal Customer,59,Business travel,Business,3644,5,5,5,5,1,3,4,4,4,4,4,3,4,1,24,12.0,satisfied +44773,77570,Male,Loyal Customer,41,Business travel,Business,1893,5,5,2,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +44774,26679,Male,Loyal Customer,8,Personal Travel,Eco,270,1,4,1,5,1,1,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +44775,62048,Female,Loyal Customer,40,Business travel,Business,1573,1,2,2,2,4,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +44776,38325,Female,Loyal Customer,35,Personal Travel,Business,1050,4,5,5,1,4,4,4,2,2,5,2,5,2,5,0,0.0,neutral or dissatisfied +44777,114979,Female,disloyal Customer,22,Business travel,Eco,325,2,5,1,4,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +44778,114423,Female,Loyal Customer,43,Business travel,Business,2203,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +44779,41837,Female,Loyal Customer,37,Business travel,Eco,462,4,3,5,3,4,3,4,4,1,5,4,1,4,4,0,0.0,neutral or dissatisfied +44780,126785,Female,Loyal Customer,32,Business travel,Eco,2125,3,5,5,5,3,3,3,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +44781,119816,Female,Loyal Customer,43,Business travel,Business,912,4,5,4,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +44782,91766,Female,Loyal Customer,24,Business travel,Eco,588,1,4,4,4,1,1,4,1,2,3,4,1,4,1,0,0.0,neutral or dissatisfied +44783,41055,Female,Loyal Customer,28,Business travel,Eco Plus,1086,5,4,2,4,5,5,5,5,2,2,2,4,2,5,17,7.0,satisfied +44784,14469,Female,Loyal Customer,69,Personal Travel,Eco,761,3,3,3,3,3,3,4,2,2,3,2,1,2,2,20,6.0,neutral or dissatisfied +44785,97565,Female,Loyal Customer,52,Business travel,Business,448,2,2,2,2,3,5,4,5,5,5,5,5,5,5,16,7.0,satisfied +44786,10392,Male,disloyal Customer,27,Business travel,Business,429,4,4,4,1,5,4,1,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +44787,16854,Female,Loyal Customer,52,Business travel,Business,2116,1,1,1,1,2,2,4,4,4,4,4,1,4,3,28,27.0,satisfied +44788,23334,Male,Loyal Customer,48,Personal Travel,Eco,456,3,4,3,3,5,3,5,5,3,4,5,4,2,5,1,4.0,neutral or dissatisfied +44789,108775,Female,Loyal Customer,46,Business travel,Business,2951,2,2,2,2,5,5,5,4,4,4,4,3,4,3,17,12.0,satisfied +44790,2455,Male,Loyal Customer,60,Business travel,Business,1623,4,4,4,4,4,5,4,5,5,5,5,3,5,5,0,3.0,satisfied +44791,125393,Female,Loyal Customer,53,Business travel,Business,1440,2,4,4,4,1,2,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +44792,47524,Male,Loyal Customer,41,Personal Travel,Eco,599,3,1,3,1,4,3,4,4,3,5,2,4,2,4,0,0.0,neutral or dissatisfied +44793,6561,Male,disloyal Customer,38,Business travel,Business,473,4,4,4,1,1,4,1,1,5,3,4,5,5,1,43,37.0,satisfied +44794,109847,Male,Loyal Customer,51,Business travel,Business,2748,4,4,4,4,5,4,4,5,5,5,5,5,5,3,17,0.0,satisfied +44795,94398,Male,Loyal Customer,48,Business travel,Business,239,4,4,4,4,4,4,4,5,5,5,5,5,5,4,3,3.0,satisfied +44796,47578,Female,Loyal Customer,41,Business travel,Business,1211,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +44797,13763,Female,disloyal Customer,30,Business travel,Eco Plus,401,3,3,3,4,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +44798,44732,Female,Loyal Customer,51,Business travel,Eco Plus,173,5,5,5,5,2,4,4,5,5,5,5,2,5,3,0,0.0,satisfied +44799,62762,Female,disloyal Customer,72,Business travel,Eco,2486,2,2,2,1,2,3,3,4,2,2,2,3,3,3,4,17.0,neutral or dissatisfied +44800,96090,Female,Loyal Customer,10,Personal Travel,Eco,1235,3,5,3,5,5,3,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +44801,64883,Female,Loyal Customer,39,Business travel,Business,3649,3,2,2,2,1,4,4,3,3,3,3,4,3,4,0,5.0,neutral or dissatisfied +44802,15680,Male,Loyal Customer,37,Personal Travel,Eco,617,2,1,2,3,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +44803,311,Male,disloyal Customer,26,Business travel,Business,821,2,2,2,3,4,2,4,4,4,5,4,5,4,4,10,5.0,neutral or dissatisfied +44804,103601,Male,Loyal Customer,58,Business travel,Business,2384,2,2,3,2,2,5,5,4,4,4,4,3,4,4,4,0.0,satisfied +44805,77038,Female,disloyal Customer,22,Business travel,Eco,368,2,5,2,1,4,2,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +44806,99755,Male,Loyal Customer,57,Personal Travel,Eco,255,4,1,0,4,4,0,4,4,2,2,4,1,4,4,46,37.0,neutral or dissatisfied +44807,100642,Male,Loyal Customer,44,Personal Travel,Eco,349,2,4,2,3,5,2,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +44808,66494,Male,Loyal Customer,48,Business travel,Business,3165,2,4,2,2,2,4,4,5,5,5,5,4,5,3,50,47.0,satisfied +44809,4462,Female,Loyal Customer,56,Business travel,Business,3532,1,1,2,1,4,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +44810,68860,Female,disloyal Customer,47,Business travel,Eco,936,2,3,3,3,1,3,1,1,1,4,4,3,4,1,0,3.0,neutral or dissatisfied +44811,26053,Female,Loyal Customer,21,Personal Travel,Eco,432,1,5,1,1,1,1,1,1,4,5,4,3,4,1,3,2.0,neutral or dissatisfied +44812,69971,Male,Loyal Customer,54,Business travel,Business,236,5,5,3,5,4,5,4,4,4,4,4,3,4,4,18,15.0,satisfied +44813,43,Female,Loyal Customer,54,Business travel,Business,1584,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,8.0,satisfied +44814,129437,Female,disloyal Customer,26,Business travel,Eco,236,2,4,2,3,1,2,1,1,3,1,4,3,3,1,6,8.0,neutral or dissatisfied +44815,66885,Female,Loyal Customer,22,Business travel,Business,2384,1,1,1,1,5,5,5,3,4,4,4,5,4,5,142,133.0,satisfied +44816,67707,Female,Loyal Customer,42,Business travel,Business,1464,1,1,1,1,3,5,5,5,5,5,5,3,5,3,11,13.0,satisfied +44817,48412,Female,Loyal Customer,7,Personal Travel,Business,853,3,3,3,4,3,3,3,3,3,4,4,4,3,3,5,0.0,neutral or dissatisfied +44818,74040,Female,Loyal Customer,50,Business travel,Business,1194,5,5,5,5,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +44819,122048,Female,Loyal Customer,50,Business travel,Business,1775,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +44820,14168,Female,Loyal Customer,57,Business travel,Eco,526,4,1,4,1,4,4,4,5,5,3,4,4,3,4,185,175.0,satisfied +44821,21523,Male,Loyal Customer,57,Personal Travel,Eco,399,2,4,2,1,2,2,2,2,4,5,4,3,5,2,1,0.0,neutral or dissatisfied +44822,19879,Female,Loyal Customer,54,Business travel,Business,3774,4,4,4,4,3,1,5,4,4,4,4,1,4,1,31,15.0,satisfied +44823,112115,Male,Loyal Customer,29,Personal Travel,Eco,1024,2,5,2,3,1,2,1,1,5,4,5,4,4,1,84,89.0,neutral or dissatisfied +44824,90212,Female,Loyal Customer,28,Personal Travel,Eco,1084,1,5,1,2,3,1,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +44825,7604,Female,disloyal Customer,28,Business travel,Business,802,3,3,3,3,1,3,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +44826,20064,Male,Loyal Customer,21,Personal Travel,Eco,473,3,4,3,3,5,3,4,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +44827,40329,Male,Loyal Customer,54,Business travel,Eco Plus,463,4,4,4,4,4,4,4,4,1,1,3,1,4,4,38,24.0,neutral or dissatisfied +44828,98222,Female,Loyal Customer,37,Business travel,Eco Plus,442,4,2,2,2,4,4,4,4,5,3,1,3,2,4,3,0.0,satisfied +44829,126110,Male,Loyal Customer,59,Business travel,Eco,650,2,1,4,4,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +44830,24809,Female,Loyal Customer,27,Business travel,Eco,991,4,2,2,2,4,4,4,4,5,3,1,3,2,4,0,0.0,satisfied +44831,53591,Female,disloyal Customer,30,Business travel,Eco,599,2,0,2,2,2,2,2,2,2,4,3,4,4,2,9,0.0,neutral or dissatisfied +44832,3614,Female,Loyal Customer,56,Business travel,Business,427,4,4,4,4,4,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +44833,30916,Male,Loyal Customer,29,Business travel,Business,1891,3,3,3,3,4,4,4,4,1,1,4,3,5,4,0,0.0,satisfied +44834,10838,Male,Loyal Customer,48,Business travel,Eco,517,4,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +44835,9124,Male,Loyal Customer,27,Personal Travel,Eco,765,3,4,3,5,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +44836,645,Male,Loyal Customer,58,Business travel,Business,164,4,4,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +44837,70334,Male,disloyal Customer,37,Business travel,Business,986,2,2,2,4,1,2,1,1,3,2,5,4,4,1,50,10.0,neutral or dissatisfied +44838,120732,Male,Loyal Customer,50,Business travel,Business,3477,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +44839,86918,Male,Loyal Customer,18,Personal Travel,Eco,341,1,4,5,3,2,5,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +44840,30123,Female,Loyal Customer,12,Personal Travel,Eco,548,1,0,1,2,4,1,4,4,5,1,4,5,1,4,0,0.0,neutral or dissatisfied +44841,110212,Male,disloyal Customer,22,Business travel,Eco,1310,3,3,3,2,3,3,3,3,4,4,1,4,1,3,0,0.0,neutral or dissatisfied +44842,64568,Male,disloyal Customer,21,Business travel,Eco,247,0,0,0,4,2,0,2,2,3,2,4,4,4,2,3,4.0,satisfied +44843,1234,Male,Loyal Customer,33,Personal Travel,Eco,134,2,5,2,4,4,2,4,4,3,3,5,4,4,4,12,21.0,neutral or dissatisfied +44844,69722,Female,Loyal Customer,30,Personal Travel,Eco,1372,3,5,3,2,4,3,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +44845,37596,Female,Loyal Customer,18,Business travel,Business,1901,4,3,3,3,4,4,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +44846,1114,Female,Loyal Customer,46,Personal Travel,Eco,134,1,0,1,3,4,5,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +44847,61856,Male,Loyal Customer,34,Personal Travel,Eco Plus,1346,4,5,4,1,3,4,3,3,3,2,3,4,5,3,0,0.0,neutral or dissatisfied +44848,47946,Female,Loyal Customer,7,Personal Travel,Eco,550,3,5,3,1,2,3,2,2,3,2,5,4,4,2,17,8.0,neutral or dissatisfied +44849,74476,Male,Loyal Customer,53,Business travel,Business,1464,4,4,4,4,5,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +44850,17236,Female,disloyal Customer,28,Business travel,Eco,1092,2,2,2,1,1,2,4,1,3,1,2,2,5,1,0,0.0,neutral or dissatisfied +44851,121363,Male,Loyal Customer,47,Business travel,Business,170,0,3,0,3,3,4,2,4,4,4,4,1,4,4,0,0.0,satisfied +44852,63922,Female,Loyal Customer,69,Personal Travel,Eco,1192,3,5,4,3,3,5,4,1,1,4,1,5,1,5,0,35.0,neutral or dissatisfied +44853,89599,Female,Loyal Customer,71,Business travel,Business,1998,5,2,2,2,2,2,2,5,5,4,5,3,5,1,7,48.0,neutral or dissatisfied +44854,36584,Female,disloyal Customer,28,Business travel,Eco,1197,1,1,1,3,3,1,1,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +44855,66876,Female,Loyal Customer,31,Business travel,Business,1119,3,3,3,3,5,5,5,5,3,2,4,5,4,5,19,16.0,satisfied +44856,55416,Male,Loyal Customer,53,Business travel,Business,2521,2,2,2,2,5,5,5,3,5,5,4,5,3,5,0,0.0,satisfied +44857,71606,Male,Loyal Customer,30,Business travel,Business,3857,5,5,5,5,5,5,5,5,4,2,5,4,4,5,0,0.0,satisfied +44858,87640,Male,Loyal Customer,51,Business travel,Business,1550,4,4,4,4,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +44859,60875,Male,Loyal Customer,24,Business travel,Business,1062,5,5,5,5,3,3,3,3,4,5,5,4,5,3,0,0.0,satisfied +44860,119894,Female,disloyal Customer,22,Business travel,Eco,912,3,3,3,3,3,3,3,3,3,3,2,2,3,3,0,0.0,neutral or dissatisfied +44861,97546,Female,Loyal Customer,30,Personal Travel,Eco,462,3,4,3,2,2,3,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +44862,82894,Male,Loyal Customer,14,Personal Travel,Eco,645,3,5,3,2,4,3,4,4,3,1,1,5,3,4,0,0.0,neutral or dissatisfied +44863,24272,Male,Loyal Customer,58,Personal Travel,Eco,147,2,4,2,3,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +44864,89340,Female,disloyal Customer,20,Business travel,Eco,1587,3,3,3,3,4,3,4,4,4,2,4,2,3,4,19,3.0,neutral or dissatisfied +44865,3780,Male,Loyal Customer,41,Business travel,Business,2475,1,3,3,3,4,2,3,1,1,1,1,3,1,1,0,43.0,neutral or dissatisfied +44866,104586,Female,Loyal Customer,17,Business travel,Business,369,3,2,2,2,3,3,3,3,3,1,4,2,4,3,63,68.0,neutral or dissatisfied +44867,65114,Female,Loyal Customer,16,Personal Travel,Eco,551,5,2,5,3,2,5,2,2,1,3,3,4,4,2,0,5.0,satisfied +44868,18900,Male,Loyal Customer,28,Personal Travel,Eco,448,5,4,5,3,1,5,1,1,2,5,4,1,3,1,0,0.0,satisfied +44869,43389,Female,Loyal Customer,68,Personal Travel,Eco,347,2,3,2,4,4,2,2,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +44870,81167,Female,Loyal Customer,37,Business travel,Business,196,5,5,5,5,5,5,3,4,4,5,4,1,4,2,0,0.0,satisfied +44871,9899,Male,Loyal Customer,46,Business travel,Business,1975,2,2,2,2,2,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +44872,17013,Male,Loyal Customer,24,Business travel,Business,781,3,3,2,3,4,4,4,4,2,2,5,2,3,4,0,0.0,satisfied +44873,88533,Female,Loyal Customer,41,Personal Travel,Eco,406,2,4,2,2,3,2,3,3,3,3,5,4,5,3,22,18.0,neutral or dissatisfied +44874,56454,Male,Loyal Customer,50,Personal Travel,Eco,719,4,4,4,1,1,4,1,1,4,5,4,4,4,1,104,110.0,neutral or dissatisfied +44875,7586,Female,Loyal Customer,52,Personal Travel,Eco,594,3,4,3,3,4,5,3,5,5,3,5,2,5,5,0,0.0,neutral or dissatisfied +44876,114686,Female,disloyal Customer,26,Business travel,Business,480,0,1,1,4,3,1,2,3,4,4,5,4,5,3,0,0.0,satisfied +44877,14816,Female,disloyal Customer,24,Business travel,Eco,95,2,3,2,4,5,2,5,5,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +44878,61693,Female,Loyal Customer,41,Business travel,Business,1608,3,3,2,3,5,2,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +44879,62809,Female,Loyal Customer,68,Personal Travel,Eco,2449,1,3,1,3,1,1,1,1,4,3,2,1,1,1,0,18.0,neutral or dissatisfied +44880,45626,Male,Loyal Customer,25,Business travel,Business,2680,2,2,2,2,5,5,5,5,4,1,1,4,3,5,0,0.0,satisfied +44881,31098,Female,Loyal Customer,50,Personal Travel,Eco,1014,4,2,4,3,5,4,3,5,5,4,5,2,5,2,28,19.0,neutral or dissatisfied +44882,4591,Female,Loyal Customer,65,Business travel,Eco,416,5,1,3,1,4,2,4,5,5,5,5,1,5,3,66,63.0,satisfied +44883,33081,Female,Loyal Customer,47,Personal Travel,Eco,101,4,3,4,3,1,4,3,4,4,4,4,1,4,5,0,0.0,neutral or dissatisfied +44884,64494,Male,Loyal Customer,47,Business travel,Business,1715,2,4,4,4,4,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +44885,116782,Male,Loyal Customer,13,Personal Travel,Eco Plus,296,2,4,2,2,5,2,5,5,4,4,3,5,4,5,13,5.0,neutral or dissatisfied +44886,106488,Female,Loyal Customer,44,Personal Travel,Business,495,2,4,2,4,2,5,4,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +44887,29527,Male,Loyal Customer,70,Personal Travel,Eco,1009,4,1,4,3,4,4,4,4,2,1,3,1,4,4,1,6.0,neutral or dissatisfied +44888,31712,Male,Loyal Customer,49,Personal Travel,Eco,853,2,4,2,3,2,2,1,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +44889,77304,Male,disloyal Customer,21,Business travel,Eco,626,4,1,4,3,2,4,2,2,2,3,4,3,3,2,0,6.0,neutral or dissatisfied +44890,49097,Female,Loyal Customer,62,Business travel,Eco,158,1,3,3,3,1,1,1,2,5,2,3,1,1,1,153,158.0,neutral or dissatisfied +44891,122294,Female,Loyal Customer,59,Personal Travel,Eco,541,3,5,3,1,2,5,4,2,2,3,3,4,2,3,0,0.0,neutral or dissatisfied +44892,64958,Female,disloyal Customer,39,Business travel,Business,190,3,3,3,3,3,3,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +44893,26006,Female,Loyal Customer,28,Business travel,Business,425,2,2,2,2,4,4,4,4,2,5,4,4,1,4,14,0.0,satisfied +44894,108126,Male,Loyal Customer,27,Business travel,Business,990,3,1,1,1,3,3,3,3,2,3,3,1,3,3,63,53.0,neutral or dissatisfied +44895,80141,Male,disloyal Customer,22,Business travel,Eco,1089,4,4,4,1,4,2,2,5,2,3,5,2,3,2,0,0.0,satisfied +44896,110749,Male,disloyal Customer,28,Business travel,Business,997,2,3,3,3,5,3,5,5,5,3,4,4,5,5,11,5.0,neutral or dissatisfied +44897,10939,Female,disloyal Customer,22,Business travel,Business,74,0,5,0,5,5,0,5,5,5,3,5,4,4,5,0,0.0,satisfied +44898,80400,Female,Loyal Customer,40,Business travel,Business,368,1,1,1,1,2,5,4,5,5,5,5,5,5,3,6,0.0,satisfied +44899,24241,Male,disloyal Customer,37,Business travel,Eco,170,3,1,3,3,1,3,3,1,1,5,4,2,3,1,0,0.0,neutral or dissatisfied +44900,116259,Male,Loyal Customer,61,Personal Travel,Eco,417,2,5,2,4,2,2,2,2,2,1,1,2,5,2,0,0.0,neutral or dissatisfied +44901,96277,Male,Loyal Customer,14,Personal Travel,Eco,460,4,5,4,3,3,4,3,3,3,2,5,3,4,3,24,21.0,neutral or dissatisfied +44902,81559,Male,Loyal Customer,25,Business travel,Business,936,3,2,2,2,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +44903,17988,Female,Loyal Customer,32,Business travel,Business,332,3,3,3,3,5,5,5,5,1,5,3,2,3,5,0,0.0,satisfied +44904,3741,Male,Loyal Customer,48,Personal Travel,Eco,544,3,4,3,4,5,3,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +44905,39653,Female,disloyal Customer,21,Business travel,Business,736,0,0,0,1,3,0,1,3,4,4,2,4,2,3,11,45.0,satisfied +44906,60587,Male,Loyal Customer,55,Business travel,Business,1158,1,1,1,1,5,1,1,5,5,5,5,1,5,2,0,0.0,satisfied +44907,38818,Male,Loyal Customer,12,Personal Travel,Eco,354,3,4,4,4,1,4,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +44908,62235,Female,Loyal Customer,12,Personal Travel,Eco,2565,1,3,1,4,1,1,1,1,1,3,3,5,5,1,0,2.0,neutral or dissatisfied +44909,37767,Male,Loyal Customer,22,Business travel,Eco Plus,944,4,3,3,3,4,5,4,4,4,5,1,3,4,4,0,0.0,satisfied +44910,27158,Female,disloyal Customer,23,Business travel,Eco,1325,3,3,3,1,3,3,3,5,1,3,5,3,3,3,0,1.0,neutral or dissatisfied +44911,1588,Male,disloyal Customer,16,Business travel,Eco,237,3,0,3,1,4,3,4,4,1,1,3,2,5,4,0,0.0,neutral or dissatisfied +44912,82391,Male,disloyal Customer,28,Business travel,Business,500,1,1,1,1,4,1,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +44913,20982,Male,Loyal Customer,64,Personal Travel,Eco,803,2,1,2,4,4,2,4,4,1,3,4,2,3,4,0,0.0,neutral or dissatisfied +44914,92933,Male,Loyal Customer,24,Personal Travel,Eco,134,4,0,4,4,5,4,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +44915,3347,Female,Loyal Customer,47,Business travel,Business,315,1,1,1,1,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +44916,91031,Male,Loyal Customer,34,Personal Travel,Eco,250,1,4,1,5,5,1,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +44917,76800,Male,Loyal Customer,60,Personal Travel,Eco,546,3,3,2,3,3,2,3,3,1,3,4,2,2,3,1,0.0,neutral or dissatisfied +44918,49946,Female,Loyal Customer,34,Business travel,Business,2308,3,3,3,3,5,5,1,4,4,4,4,2,4,2,0,0.0,satisfied +44919,21850,Female,Loyal Customer,13,Personal Travel,Business,503,4,4,4,3,5,4,5,5,3,5,4,4,4,5,0,0.0,satisfied +44920,88968,Female,Loyal Customer,58,Business travel,Business,3543,1,2,2,2,5,3,4,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +44921,65679,Male,Loyal Customer,56,Personal Travel,Eco,1021,3,5,4,3,3,4,3,3,2,2,4,1,5,3,38,41.0,neutral or dissatisfied +44922,27694,Male,Loyal Customer,25,Personal Travel,Eco,1107,0,5,0,1,2,0,2,2,5,4,5,3,4,2,0,0.0,satisfied +44923,92480,Female,Loyal Customer,43,Business travel,Business,1919,2,3,3,3,2,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +44924,29326,Male,Loyal Customer,24,Personal Travel,Eco,933,4,4,4,1,4,4,4,4,5,5,4,5,5,4,11,11.0,neutral or dissatisfied +44925,92717,Male,Loyal Customer,43,Business travel,Business,1987,1,1,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +44926,114337,Male,Loyal Customer,8,Personal Travel,Eco,862,4,5,4,5,2,4,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +44927,34609,Female,Loyal Customer,62,Personal Travel,Eco,1598,3,5,3,5,5,4,5,1,1,3,1,3,1,3,15,35.0,neutral or dissatisfied +44928,62422,Male,Loyal Customer,40,Business travel,Business,2329,2,2,2,2,5,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +44929,14654,Male,disloyal Customer,36,Business travel,Eco,162,1,5,1,4,3,1,3,3,5,4,4,1,3,3,9,11.0,neutral or dissatisfied +44930,116682,Male,Loyal Customer,47,Business travel,Eco Plus,447,4,4,2,2,4,4,4,4,3,4,3,4,3,4,84,78.0,neutral or dissatisfied +44931,76271,Female,Loyal Customer,34,Business travel,Business,1927,2,5,5,5,3,2,3,2,2,2,2,4,2,2,5,0.0,neutral or dissatisfied +44932,25857,Female,Loyal Customer,47,Personal Travel,Eco,692,3,4,3,1,4,4,4,4,4,3,5,4,4,3,6,6.0,neutral or dissatisfied +44933,24601,Male,Loyal Customer,29,Business travel,Business,3788,1,1,1,1,4,4,4,4,4,2,5,1,4,4,0,0.0,satisfied +44934,60547,Female,Loyal Customer,46,Personal Travel,Eco,862,2,4,2,1,4,3,5,1,1,2,5,1,1,2,1,0.0,neutral or dissatisfied +44935,67810,Male,Loyal Customer,38,Business travel,Eco,835,5,2,2,2,5,5,5,5,2,3,1,5,2,5,2,0.0,satisfied +44936,90198,Female,Loyal Customer,37,Personal Travel,Eco,957,1,2,0,3,5,0,5,5,2,4,4,1,3,5,29,15.0,neutral or dissatisfied +44937,81516,Male,Loyal Customer,39,Business travel,Business,2895,4,4,4,4,3,5,4,5,5,5,5,3,5,3,4,0.0,satisfied +44938,226,Male,Loyal Customer,66,Personal Travel,Eco,290,3,5,3,4,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +44939,91987,Male,Loyal Customer,52,Business travel,Business,1958,0,0,0,3,4,5,5,5,5,2,2,3,5,5,0,0.0,satisfied +44940,88881,Male,disloyal Customer,39,Business travel,Business,859,2,2,2,4,2,2,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +44941,46980,Female,Loyal Customer,34,Personal Travel,Eco,845,4,5,4,3,2,4,2,2,4,2,5,5,5,2,0,2.0,neutral or dissatisfied +44942,113763,Female,Loyal Customer,15,Personal Travel,Eco,386,5,5,5,3,4,5,4,4,4,3,4,4,5,4,0,0.0,satisfied +44943,12973,Female,disloyal Customer,24,Business travel,Business,304,5,0,5,3,5,5,5,5,3,2,4,4,5,5,46,50.0,satisfied +44944,78314,Male,Loyal Customer,33,Business travel,Business,2404,4,4,4,4,5,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +44945,55919,Female,Loyal Customer,66,Personal Travel,Eco,733,2,4,2,1,4,5,4,3,3,2,1,1,3,2,0,19.0,neutral or dissatisfied +44946,110556,Male,Loyal Customer,41,Business travel,Business,488,2,2,1,2,4,4,4,5,5,5,5,3,5,4,53,46.0,satisfied +44947,121442,Male,Loyal Customer,62,Business travel,Eco,257,3,1,1,1,3,3,3,3,4,5,3,2,4,3,6,0.0,neutral or dissatisfied +44948,124922,Female,Loyal Customer,23,Business travel,Eco,328,2,3,4,3,2,1,3,2,4,4,3,3,3,2,0,14.0,neutral or dissatisfied +44949,126893,Female,Loyal Customer,50,Business travel,Business,2125,1,1,2,1,2,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +44950,28256,Female,Loyal Customer,22,Business travel,Eco,1542,2,4,4,4,2,3,4,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +44951,77879,Female,disloyal Customer,43,Business travel,Eco,700,2,2,2,2,4,2,1,4,4,1,2,2,3,4,0,0.0,neutral or dissatisfied +44952,27370,Female,Loyal Customer,53,Business travel,Eco,954,4,2,2,2,5,2,3,3,3,4,3,2,3,5,0,0.0,satisfied +44953,60103,Female,Loyal Customer,67,Business travel,Business,1005,1,1,1,1,2,1,1,2,4,4,3,1,4,1,161,138.0,neutral or dissatisfied +44954,81835,Male,Loyal Customer,40,Personal Travel,Eco,1487,3,5,3,4,1,3,1,1,5,4,3,4,4,1,0,0.0,neutral or dissatisfied +44955,4359,Male,Loyal Customer,46,Business travel,Business,473,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +44956,45860,Female,Loyal Customer,63,Personal Travel,Eco Plus,391,1,4,1,1,3,5,5,4,4,1,4,4,4,5,40,63.0,neutral or dissatisfied +44957,43664,Female,disloyal Customer,26,Business travel,Eco,695,3,3,3,4,2,3,2,2,1,2,4,3,4,2,0,9.0,neutral or dissatisfied +44958,12578,Male,disloyal Customer,22,Business travel,Eco,542,3,0,3,1,2,3,2,2,4,2,4,1,2,2,22,16.0,neutral or dissatisfied +44959,68849,Male,Loyal Customer,58,Business travel,Business,1581,1,1,1,1,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +44960,109940,Male,Loyal Customer,63,Personal Travel,Eco,971,3,4,3,2,3,2,2,4,5,5,5,2,4,2,142,136.0,neutral or dissatisfied +44961,39481,Male,disloyal Customer,22,Business travel,Eco,867,4,4,4,2,4,4,4,4,3,2,5,1,5,4,0,7.0,satisfied +44962,78954,Female,Loyal Customer,37,Business travel,Business,1612,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,7.0,satisfied +44963,60844,Female,disloyal Customer,15,Business travel,Business,1265,4,0,3,3,3,3,3,3,5,2,4,5,4,3,1,0.0,satisfied +44964,121661,Male,Loyal Customer,56,Business travel,Business,3991,0,0,0,1,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +44965,6197,Female,disloyal Customer,27,Business travel,Eco Plus,491,3,2,2,2,2,5,5,4,2,1,1,5,2,5,98,166.0,neutral or dissatisfied +44966,65678,Female,Loyal Customer,63,Personal Travel,Eco,861,1,2,1,4,4,4,4,5,5,1,5,2,5,1,0,0.0,neutral or dissatisfied +44967,106469,Female,disloyal Customer,62,Business travel,Eco,900,3,3,3,4,5,3,5,5,3,3,4,3,3,5,11,0.0,neutral or dissatisfied +44968,11909,Female,Loyal Customer,49,Business travel,Eco,501,4,5,2,5,3,3,3,4,4,4,4,3,4,2,0,15.0,neutral or dissatisfied +44969,115502,Female,disloyal Customer,23,Business travel,Eco,372,1,0,1,4,5,1,5,5,4,1,3,2,4,5,44,40.0,neutral or dissatisfied +44970,91189,Male,Loyal Customer,42,Personal Travel,Eco,594,2,2,2,4,2,2,2,2,3,2,4,3,4,2,20,15.0,neutral or dissatisfied +44971,44873,Male,disloyal Customer,20,Business travel,Eco,240,2,2,2,4,5,2,5,5,2,1,4,3,4,5,61,57.0,neutral or dissatisfied +44972,84162,Male,Loyal Customer,16,Personal Travel,Eco,503,3,5,3,5,2,3,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +44973,6076,Female,Loyal Customer,52,Personal Travel,Eco,690,3,4,3,2,4,4,4,3,3,3,4,5,3,4,56,49.0,neutral or dissatisfied +44974,95999,Female,Loyal Customer,54,Business travel,Business,795,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +44975,111228,Male,Loyal Customer,47,Personal Travel,Eco,1506,4,3,4,2,4,4,3,3,1,1,5,3,5,3,163,158.0,neutral or dissatisfied +44976,34412,Female,Loyal Customer,55,Personal Travel,Eco,612,2,5,2,2,5,1,5,1,1,2,5,1,1,2,0,0.0,neutral or dissatisfied +44977,53887,Male,Loyal Customer,41,Personal Travel,Eco,140,2,4,2,3,4,2,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +44978,97813,Male,Loyal Customer,42,Business travel,Business,480,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +44979,109472,Female,disloyal Customer,38,Business travel,Business,920,4,4,4,3,2,4,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +44980,33996,Male,Loyal Customer,59,Business travel,Eco,1598,2,2,5,5,2,2,2,2,1,1,3,1,5,2,58,39.0,satisfied +44981,10410,Male,Loyal Customer,40,Business travel,Business,201,2,2,2,2,3,4,5,4,4,4,5,4,4,3,0,0.0,satisfied +44982,101369,Female,Loyal Customer,29,Personal Travel,Eco,1986,2,3,2,4,2,2,2,4,2,3,3,2,3,2,176,170.0,neutral or dissatisfied +44983,73483,Female,Loyal Customer,25,Personal Travel,Eco,1120,1,4,1,3,1,1,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +44984,65641,Female,Loyal Customer,62,Business travel,Eco Plus,175,2,3,3,3,1,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +44985,64086,Male,Loyal Customer,69,Personal Travel,Eco,919,3,4,3,4,3,3,3,3,5,2,5,4,4,3,0,8.0,neutral or dissatisfied +44986,49502,Male,Loyal Customer,27,Business travel,Business,3989,5,5,5,5,5,5,5,5,5,2,4,2,5,5,0,0.0,satisfied +44987,29219,Female,disloyal Customer,38,Business travel,Business,834,2,2,2,1,2,2,5,2,5,4,5,3,4,2,0,0.0,satisfied +44988,4734,Female,Loyal Customer,36,Business travel,Business,888,1,1,1,1,5,5,4,5,5,5,5,4,5,5,7,27.0,satisfied +44989,66408,Male,Loyal Customer,42,Business travel,Business,1733,1,1,3,1,4,4,1,5,5,5,5,5,5,2,0,0.0,satisfied +44990,100836,Male,disloyal Customer,7,Business travel,Eco,711,4,4,4,3,2,4,3,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +44991,128298,Male,Loyal Customer,49,Business travel,Business,2850,5,5,1,5,2,5,4,4,4,4,4,4,4,4,4,7.0,satisfied +44992,57574,Female,Loyal Customer,40,Business travel,Business,1597,2,2,3,2,2,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +44993,51886,Male,Loyal Customer,37,Business travel,Business,2945,2,2,2,2,5,4,3,5,5,5,5,5,5,2,0,13.0,satisfied +44994,19482,Male,Loyal Customer,11,Personal Travel,Eco,177,2,1,2,1,5,2,5,5,2,1,1,1,1,5,0,0.0,neutral or dissatisfied +44995,40154,Female,disloyal Customer,25,Business travel,Business,387,3,5,3,2,5,3,1,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +44996,6909,Male,Loyal Customer,67,Personal Travel,Eco,287,3,5,3,1,5,3,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +44997,38122,Male,Loyal Customer,44,Business travel,Business,2487,1,1,1,1,3,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +44998,13388,Female,Loyal Customer,60,Business travel,Eco,456,2,5,3,5,2,1,3,2,2,2,2,4,2,1,26,8.0,satisfied +44999,95545,Male,Loyal Customer,42,Personal Travel,Eco Plus,277,3,1,3,2,4,3,4,4,1,5,3,2,2,4,2,14.0,neutral or dissatisfied +45000,59101,Male,Loyal Customer,18,Personal Travel,Eco,1726,4,4,4,4,3,4,3,3,3,4,5,5,5,3,1,0.0,neutral or dissatisfied +45001,22597,Male,Loyal Customer,41,Business travel,Business,2768,5,5,5,5,4,3,4,5,5,5,5,5,5,2,0,0.0,satisfied +45002,120649,Female,Loyal Customer,56,Business travel,Business,2875,0,0,0,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +45003,52709,Male,disloyal Customer,18,Business travel,Eco,1162,2,2,2,4,3,2,3,3,1,3,4,4,5,3,0,5.0,neutral or dissatisfied +45004,119814,Female,Loyal Customer,49,Business travel,Business,3842,2,2,3,2,4,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +45005,70681,Male,Loyal Customer,58,Personal Travel,Eco,447,1,4,1,4,2,1,1,2,4,5,1,4,2,2,4,0.0,neutral or dissatisfied +45006,67032,Female,disloyal Customer,27,Business travel,Eco,964,2,2,2,4,4,2,5,4,2,3,4,2,3,4,3,0.0,neutral or dissatisfied +45007,72335,Female,disloyal Customer,44,Business travel,Business,1121,5,5,5,4,5,5,5,5,4,2,5,4,4,5,21,5.0,satisfied +45008,64593,Female,Loyal Customer,55,Business travel,Business,2453,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +45009,13116,Male,Loyal Customer,24,Business travel,Business,595,2,2,2,2,2,2,2,2,1,2,4,3,4,2,14,6.0,neutral or dissatisfied +45010,62039,Male,disloyal Customer,25,Business travel,Eco,2586,3,3,3,4,4,3,4,4,2,1,3,3,4,4,0,0.0,neutral or dissatisfied +45011,14497,Male,Loyal Customer,55,Business travel,Business,2464,3,3,3,3,1,2,2,4,4,4,4,4,4,1,19,13.0,satisfied +45012,2584,Male,Loyal Customer,57,Personal Travel,Eco,181,1,4,1,1,5,1,5,5,5,1,1,5,5,5,5,17.0,neutral or dissatisfied +45013,50466,Male,disloyal Customer,54,Business travel,Eco,373,1,1,1,3,3,1,5,3,4,4,4,2,3,3,0,0.0,neutral or dissatisfied +45014,28052,Female,disloyal Customer,22,Business travel,Eco Plus,1739,2,0,2,1,5,2,1,5,4,1,4,4,4,5,6,0.0,neutral or dissatisfied +45015,68541,Male,Loyal Customer,69,Business travel,Business,3929,2,2,2,2,3,5,1,3,3,2,3,1,3,1,8,14.0,satisfied +45016,84670,Male,disloyal Customer,15,Business travel,Eco,864,3,3,3,2,4,3,4,4,4,3,5,5,5,4,15,7.0,neutral or dissatisfied +45017,2358,Male,Loyal Customer,42,Business travel,Business,925,3,3,3,3,5,5,5,3,3,4,5,5,5,5,174,180.0,satisfied +45018,10385,Male,Loyal Customer,45,Business travel,Business,3523,2,2,2,2,2,5,4,5,5,5,5,4,5,4,6,4.0,satisfied +45019,69646,Male,disloyal Customer,27,Business travel,Business,569,3,3,3,4,3,3,5,3,4,4,5,5,4,3,0,14.0,neutral or dissatisfied +45020,84575,Female,Loyal Customer,38,Personal Travel,Eco Plus,2556,3,1,3,4,3,3,3,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +45021,22751,Male,Loyal Customer,33,Business travel,Eco,302,5,1,1,1,5,5,5,5,1,4,5,5,2,5,0,0.0,satisfied +45022,96921,Female,Loyal Customer,52,Personal Travel,Eco,816,3,3,3,2,2,3,2,2,2,3,1,1,2,1,18,2.0,neutral or dissatisfied +45023,114078,Male,disloyal Customer,16,Business travel,Business,1892,5,0,5,1,1,5,5,1,4,2,3,4,4,1,6,0.0,satisfied +45024,85884,Male,Loyal Customer,39,Personal Travel,Eco,2172,4,4,4,4,1,4,5,1,5,2,5,4,4,1,0,0.0,satisfied +45025,52143,Male,Loyal Customer,47,Business travel,Business,2725,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +45026,22630,Male,Loyal Customer,51,Personal Travel,Eco,223,3,5,3,1,3,3,3,3,5,3,4,5,4,3,1,0.0,neutral or dissatisfied +45027,20654,Male,Loyal Customer,40,Business travel,Eco,522,4,4,4,4,4,4,4,4,1,5,4,4,1,4,0,0.0,satisfied +45028,94003,Male,Loyal Customer,57,Business travel,Business,2383,0,4,0,4,2,4,4,1,1,1,1,3,1,3,37,38.0,satisfied +45029,126522,Female,disloyal Customer,27,Business travel,Eco,196,1,0,1,2,4,1,5,4,4,3,1,3,3,4,0,0.0,neutral or dissatisfied +45030,46779,Male,Loyal Customer,60,Business travel,Business,848,1,1,1,1,4,4,4,4,4,4,5,4,3,4,207,223.0,satisfied +45031,127408,Male,disloyal Customer,18,Business travel,Eco,868,1,2,2,4,2,2,2,2,2,1,4,2,3,2,14,8.0,neutral or dissatisfied +45032,110300,Female,Loyal Customer,35,Business travel,Business,3566,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +45033,70466,Male,Loyal Customer,20,Business travel,Eco,867,2,1,2,1,2,2,4,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +45034,71085,Female,Loyal Customer,69,Personal Travel,Eco,802,3,4,3,4,5,2,2,5,5,3,5,1,5,3,21,17.0,neutral or dissatisfied +45035,97272,Male,Loyal Customer,38,Personal Travel,Eco Plus,296,3,4,3,2,2,3,2,2,3,3,4,4,4,2,16,11.0,neutral or dissatisfied +45036,116406,Male,Loyal Customer,34,Personal Travel,Eco,337,3,5,3,1,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +45037,14263,Male,Loyal Customer,72,Business travel,Eco,395,4,4,4,4,3,4,3,3,3,5,2,3,3,3,2,2.0,neutral or dissatisfied +45038,95537,Male,Loyal Customer,44,Personal Travel,Eco Plus,192,3,5,3,1,1,3,1,1,5,5,5,5,4,1,8,3.0,neutral or dissatisfied +45039,64234,Female,Loyal Customer,27,Business travel,Business,1660,3,1,4,1,3,3,3,3,1,3,3,3,3,3,0,4.0,neutral or dissatisfied +45040,78042,Female,Loyal Customer,12,Personal Travel,Eco,332,3,4,3,4,2,3,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +45041,97811,Male,disloyal Customer,32,Business travel,Eco,480,3,4,3,3,3,3,3,3,2,3,4,4,3,3,0,0.0,neutral or dissatisfied +45042,115915,Female,disloyal Customer,37,Business travel,Eco,447,2,0,2,3,1,2,1,1,2,1,2,1,5,1,1,0.0,neutral or dissatisfied +45043,24572,Male,Loyal Customer,56,Personal Travel,Eco,874,4,0,4,4,3,4,4,3,4,4,4,3,4,3,0,21.0,neutral or dissatisfied +45044,102091,Female,Loyal Customer,41,Business travel,Business,3933,3,3,3,3,3,3,3,5,2,5,5,3,3,3,190,182.0,satisfied +45045,126518,Female,Loyal Customer,49,Business travel,Eco Plus,313,2,5,5,5,5,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +45046,43076,Male,Loyal Customer,69,Personal Travel,Eco,192,4,5,4,2,3,4,3,3,5,2,5,4,5,3,33,25.0,neutral or dissatisfied +45047,95631,Female,Loyal Customer,18,Personal Travel,Eco,822,4,4,4,3,5,4,5,5,3,3,5,5,5,5,4,3.0,satisfied +45048,108692,Male,Loyal Customer,46,Personal Travel,Eco,577,3,5,3,3,4,3,4,4,4,5,5,4,5,4,2,0.0,neutral or dissatisfied +45049,114060,Female,Loyal Customer,25,Business travel,Business,2139,4,4,4,4,2,2,2,2,3,2,5,5,4,2,4,2.0,satisfied +45050,14443,Male,disloyal Customer,25,Business travel,Eco,761,2,2,2,4,4,2,4,4,2,3,4,1,4,4,13,4.0,neutral or dissatisfied +45051,59208,Male,Loyal Customer,31,Business travel,Business,1440,4,4,4,4,4,4,4,4,2,5,2,5,3,4,0,0.0,satisfied +45052,125916,Male,Loyal Customer,47,Personal Travel,Eco,920,4,2,4,3,4,4,2,4,4,4,3,4,3,4,0,0.0,neutral or dissatisfied +45053,75692,Female,Loyal Customer,42,Business travel,Business,868,4,4,4,4,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +45054,121037,Female,Loyal Customer,27,Personal Travel,Eco,992,3,5,3,2,4,3,4,4,4,4,5,3,4,4,28,43.0,neutral or dissatisfied +45055,66231,Female,Loyal Customer,41,Business travel,Business,1836,4,4,4,4,4,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +45056,38888,Male,disloyal Customer,39,Business travel,Eco,621,4,0,4,2,2,4,2,2,3,3,5,1,2,2,0,18.0,neutral or dissatisfied +45057,21848,Female,Loyal Customer,64,Personal Travel,Business,500,2,5,2,3,2,4,5,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +45058,116209,Male,Loyal Customer,64,Personal Travel,Eco,480,0,2,0,2,4,0,2,4,2,2,3,2,2,4,6,1.0,satisfied +45059,97161,Female,Loyal Customer,12,Personal Travel,Eco,1390,4,4,4,4,4,4,4,4,4,5,3,4,3,4,0,0.0,satisfied +45060,66693,Female,Loyal Customer,30,Business travel,Business,1538,2,4,4,4,2,2,2,2,1,2,2,3,3,2,90,78.0,neutral or dissatisfied +45061,11990,Female,Loyal Customer,65,Personal Travel,Eco,643,2,4,2,3,1,3,3,3,3,2,3,1,3,1,0,1.0,neutral or dissatisfied +45062,73547,Female,Loyal Customer,14,Personal Travel,Eco,594,4,3,4,4,5,4,5,5,1,2,4,2,4,5,1,5.0,neutral or dissatisfied +45063,45959,Female,Loyal Customer,13,Personal Travel,Eco Plus,809,2,3,2,4,5,2,5,5,1,5,4,3,4,5,24,22.0,neutral or dissatisfied +45064,121167,Female,Loyal Customer,37,Business travel,Business,3974,4,4,4,4,2,4,4,4,4,4,4,1,4,4,0,,neutral or dissatisfied +45065,15712,Female,disloyal Customer,20,Business travel,Eco,479,4,5,4,4,2,4,2,2,4,5,3,5,2,2,0,0.0,satisfied +45066,116446,Male,Loyal Customer,14,Personal Travel,Eco,446,2,4,2,2,1,2,1,1,3,3,4,5,5,1,9,8.0,neutral or dissatisfied +45067,63957,Male,Loyal Customer,36,Personal Travel,Eco,1192,2,4,2,1,1,2,1,1,5,2,4,3,5,1,0,5.0,neutral or dissatisfied +45068,54870,Female,disloyal Customer,26,Business travel,Eco,585,5,3,5,4,3,5,5,3,5,2,4,5,3,3,31,0.0,satisfied +45069,39862,Male,Loyal Customer,56,Business travel,Business,1830,3,4,4,4,2,4,4,1,1,1,3,2,1,2,0,0.0,neutral or dissatisfied +45070,75585,Female,Loyal Customer,51,Business travel,Eco,337,1,1,5,1,1,3,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +45071,111034,Male,Loyal Customer,47,Business travel,Business,197,0,4,0,3,4,4,4,5,5,5,2,3,5,3,5,0.0,satisfied +45072,17009,Male,Loyal Customer,45,Business travel,Business,781,3,4,4,4,5,4,4,3,3,3,3,4,3,3,13,14.0,neutral or dissatisfied +45073,13451,Female,Loyal Customer,25,Personal Travel,Eco,409,1,5,1,3,1,1,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +45074,40701,Male,Loyal Customer,42,Business travel,Business,558,3,3,3,3,3,4,2,2,2,2,2,1,2,3,0,0.0,satisfied +45075,81691,Male,Loyal Customer,53,Personal Travel,Eco,907,1,5,1,3,3,1,3,3,5,4,5,5,4,3,2,0.0,neutral or dissatisfied +45076,118308,Female,disloyal Customer,38,Business travel,Business,602,3,3,3,3,5,3,5,5,3,2,4,4,4,5,13,0.0,neutral or dissatisfied +45077,19334,Male,Loyal Customer,22,Personal Travel,Eco,694,2,5,2,3,4,2,4,4,4,3,4,5,4,4,11,0.0,neutral or dissatisfied +45078,93781,Male,Loyal Customer,62,Personal Travel,Eco,1865,3,5,3,4,5,3,5,5,2,4,5,4,2,5,0,0.0,neutral or dissatisfied +45079,118376,Male,disloyal Customer,20,Business travel,Eco,304,0,0,0,3,1,0,1,1,3,3,4,3,5,1,0,0.0,satisfied +45080,103846,Male,Loyal Customer,35,Business travel,Eco,1056,1,3,3,3,1,1,1,1,3,4,3,4,4,1,21,24.0,neutral or dissatisfied +45081,69493,Male,Loyal Customer,23,Personal Travel,Eco Plus,1096,3,5,3,3,3,3,5,3,5,5,4,4,5,3,0,,neutral or dissatisfied +45082,115164,Male,disloyal Customer,32,Business travel,Business,373,3,3,3,2,4,3,4,4,5,2,5,3,5,4,53,43.0,neutral or dissatisfied +45083,97489,Male,Loyal Customer,59,Business travel,Eco,756,3,3,3,3,4,3,4,4,2,4,2,2,1,4,0,0.0,neutral or dissatisfied +45084,113278,Female,disloyal Customer,23,Business travel,Eco,236,1,4,1,2,3,1,3,3,5,2,5,4,5,3,17,18.0,neutral or dissatisfied +45085,80266,Female,Loyal Customer,29,Personal Travel,Eco,488,2,1,2,3,5,2,3,5,2,5,4,2,3,5,0,0.0,neutral or dissatisfied +45086,126513,Male,Loyal Customer,46,Business travel,Business,3245,4,5,5,5,4,3,3,4,4,4,4,4,4,2,3,0.0,neutral or dissatisfied +45087,105952,Male,disloyal Customer,19,Business travel,Business,1188,4,3,5,1,5,5,5,3,5,5,5,5,4,5,0,35.0,satisfied +45088,36028,Female,disloyal Customer,21,Business travel,Eco,474,3,0,4,3,4,4,4,4,3,1,5,2,3,4,0,0.0,neutral or dissatisfied +45089,2597,Male,Loyal Customer,27,Personal Travel,Eco,280,1,2,1,3,3,1,1,3,4,5,2,4,2,3,11,5.0,neutral or dissatisfied +45090,80710,Female,Loyal Customer,34,Personal Travel,Eco,1640,1,5,1,3,2,1,4,2,4,2,4,4,5,2,57,49.0,neutral or dissatisfied +45091,13826,Male,Loyal Customer,42,Business travel,Business,628,1,1,1,1,4,1,4,4,4,4,4,1,4,2,94,101.0,satisfied +45092,34584,Male,Loyal Customer,27,Business travel,Business,1617,4,4,4,4,5,5,5,5,4,1,4,5,1,5,0,0.0,satisfied +45093,80411,Female,Loyal Customer,34,Business travel,Business,2248,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,1.0,satisfied +45094,33530,Male,Loyal Customer,41,Personal Travel,Eco,228,2,5,2,4,3,2,3,3,4,2,5,5,5,3,0,19.0,neutral or dissatisfied +45095,64743,Male,disloyal Customer,22,Business travel,Business,190,0,4,0,2,4,0,4,4,5,5,4,5,5,4,0,0.0,satisfied +45096,96213,Male,disloyal Customer,59,Business travel,Eco,460,3,3,3,4,2,3,2,2,3,1,4,4,4,2,54,52.0,neutral or dissatisfied +45097,7579,Male,Loyal Customer,57,Business travel,Business,3697,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +45098,63285,Male,Loyal Customer,44,Business travel,Business,3377,4,4,4,4,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +45099,85597,Male,Loyal Customer,38,Business travel,Business,153,2,1,1,1,2,4,3,1,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +45100,102613,Female,Loyal Customer,51,Business travel,Business,1858,3,3,4,3,2,5,5,4,4,4,4,4,4,5,35,11.0,satisfied +45101,82354,Female,Loyal Customer,54,Business travel,Business,453,3,5,5,5,3,4,4,3,3,3,3,4,3,1,91,80.0,neutral or dissatisfied +45102,21465,Female,disloyal Customer,26,Business travel,Eco,377,4,2,4,3,1,4,1,1,1,1,2,4,3,1,0,0.0,neutral or dissatisfied +45103,122075,Male,Loyal Customer,53,Personal Travel,Eco,130,3,2,3,3,5,3,1,5,4,4,4,1,4,5,2,0.0,neutral or dissatisfied +45104,114263,Male,Loyal Customer,37,Business travel,Business,3971,2,2,2,2,1,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +45105,65558,Female,Loyal Customer,54,Business travel,Business,3519,4,4,4,4,4,5,5,5,5,5,5,4,5,5,10,8.0,satisfied +45106,27678,Female,disloyal Customer,13,Business travel,Eco,1107,2,2,2,3,1,2,1,1,1,1,4,1,3,1,13,7.0,neutral or dissatisfied +45107,35156,Female,Loyal Customer,38,Business travel,Eco,1056,5,5,2,5,5,5,5,5,4,5,1,3,2,5,0,0.0,satisfied +45108,49230,Female,Loyal Customer,58,Business travel,Eco,109,5,2,2,2,5,5,5,4,4,5,4,4,4,2,0,0.0,satisfied +45109,87923,Male,Loyal Customer,37,Business travel,Business,270,5,5,5,5,5,4,4,5,5,5,5,4,5,4,95,93.0,satisfied +45110,40015,Male,Loyal Customer,41,Business travel,Business,575,2,2,2,2,5,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +45111,119182,Male,Loyal Customer,42,Business travel,Business,3941,3,3,3,3,5,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +45112,12115,Female,disloyal Customer,25,Business travel,Eco,1034,4,4,4,5,4,4,4,4,1,5,5,5,1,4,0,0.0,satisfied +45113,60376,Male,Loyal Customer,26,Business travel,Business,1452,5,5,5,5,4,4,4,4,3,3,4,5,4,4,22,5.0,satisfied +45114,86879,Female,Loyal Customer,36,Personal Travel,Eco Plus,692,1,5,1,3,1,3,3,4,4,4,5,3,4,3,163,142.0,neutral or dissatisfied +45115,63501,Male,disloyal Customer,44,Business travel,Eco,1956,2,1,1,2,1,2,1,1,2,2,1,2,3,1,106,93.0,neutral or dissatisfied +45116,81766,Male,disloyal Customer,25,Business travel,Eco,1310,3,3,3,4,5,3,5,5,4,4,5,5,4,5,17,19.0,neutral or dissatisfied +45117,99361,Male,Loyal Customer,39,Business travel,Business,409,2,2,3,2,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +45118,13723,Male,disloyal Customer,26,Business travel,Eco,401,0,0,0,4,0,2,2,1,1,3,3,2,4,2,177,163.0,satisfied +45119,43793,Male,Loyal Customer,51,Business travel,Eco,282,4,2,3,2,4,4,4,4,4,3,2,5,2,4,0,0.0,satisfied +45120,60389,Male,disloyal Customer,24,Business travel,Eco,862,4,4,4,3,5,4,5,5,1,4,4,2,4,5,6,13.0,neutral or dissatisfied +45121,117737,Male,Loyal Customer,31,Business travel,Business,2332,3,1,1,1,3,3,3,3,4,3,4,3,3,3,9,9.0,neutral or dissatisfied +45122,82160,Female,Loyal Customer,56,Business travel,Business,3304,2,1,3,3,2,3,3,2,2,2,2,4,2,4,13,11.0,neutral or dissatisfied +45123,124064,Male,Loyal Customer,51,Business travel,Business,653,3,3,3,3,2,2,3,5,5,5,5,1,5,4,0,0.0,satisfied +45124,69269,Male,Loyal Customer,33,Personal Travel,Eco,733,4,1,3,4,3,3,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +45125,71160,Female,Loyal Customer,62,Business travel,Business,1769,2,2,2,2,5,3,3,2,2,2,2,3,2,1,20,16.0,neutral or dissatisfied +45126,2121,Male,Loyal Customer,43,Business travel,Business,2844,4,4,4,4,4,5,4,2,2,2,2,5,2,5,21,28.0,satisfied +45127,57150,Male,Loyal Customer,48,Business travel,Business,1824,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +45128,101562,Female,Loyal Customer,40,Business travel,Business,345,0,0,0,2,2,4,4,2,2,2,1,3,2,4,0,0.0,satisfied +45129,46473,Male,Loyal Customer,44,Business travel,Business,3419,0,4,0,3,4,4,4,1,1,1,1,4,1,3,0,0.0,satisfied +45130,58039,Female,Loyal Customer,21,Personal Travel,Business,612,2,5,2,2,1,2,1,1,4,5,4,4,5,1,14,4.0,neutral or dissatisfied +45131,7362,Male,disloyal Customer,23,Business travel,Eco,783,1,1,1,3,3,1,3,3,5,2,4,4,4,3,30,25.0,neutral or dissatisfied +45132,96019,Male,Loyal Customer,23,Business travel,Business,1090,5,5,5,5,2,2,2,2,3,2,4,3,5,2,5,5.0,satisfied +45133,71667,Female,Loyal Customer,38,Personal Travel,Eco,1197,3,4,3,4,3,3,3,3,1,2,3,4,2,3,0,0.0,neutral or dissatisfied +45134,70853,Male,Loyal Customer,39,Business travel,Business,1599,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +45135,25096,Male,Loyal Customer,36,Business travel,Business,369,3,3,3,3,5,1,2,4,4,4,4,5,4,2,0,0.0,satisfied +45136,406,Male,disloyal Customer,36,Business travel,Business,134,2,1,1,1,4,1,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +45137,111009,Male,disloyal Customer,24,Business travel,Eco,319,4,4,4,4,4,4,4,4,2,5,3,3,4,4,52,62.0,neutral or dissatisfied +45138,46908,Male,Loyal Customer,62,Business travel,Eco,833,3,1,4,1,3,3,3,3,4,4,3,2,3,3,0,2.0,neutral or dissatisfied +45139,99201,Male,Loyal Customer,30,Business travel,Eco,583,2,3,3,3,2,1,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +45140,79875,Male,Loyal Customer,51,Business travel,Business,1701,2,2,2,2,5,5,4,5,5,5,5,3,5,5,2,0.0,satisfied +45141,23376,Male,Loyal Customer,14,Personal Travel,Eco,1162,2,5,2,2,4,2,4,4,5,4,5,3,5,4,19,16.0,neutral or dissatisfied +45142,104828,Male,Loyal Customer,26,Business travel,Business,472,1,5,3,5,1,1,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +45143,55228,Male,Loyal Customer,25,Business travel,Business,1009,3,3,3,3,3,4,3,3,4,5,3,3,3,3,1,1.0,neutral or dissatisfied +45144,35816,Male,Loyal Customer,26,Business travel,Eco,937,5,1,1,1,5,5,4,5,3,3,2,1,5,5,0,0.0,satisfied +45145,123879,Male,Loyal Customer,64,Business travel,Eco,144,5,3,3,3,5,5,5,5,2,2,2,3,2,5,0,1.0,satisfied +45146,12400,Female,Loyal Customer,60,Business travel,Business,3261,2,2,2,2,2,3,4,2,2,2,2,2,2,3,89,87.0,neutral or dissatisfied +45147,42161,Female,disloyal Customer,26,Business travel,Eco,834,5,5,5,4,1,5,5,1,2,1,2,3,2,1,0,0.0,satisfied +45148,123857,Male,Loyal Customer,25,Business travel,Eco,603,3,3,3,3,3,3,3,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +45149,128447,Female,disloyal Customer,55,Business travel,Eco,370,3,4,3,2,5,3,5,5,3,4,2,1,3,5,4,3.0,neutral or dissatisfied +45150,115382,Male,Loyal Customer,41,Business travel,Eco,337,4,3,3,3,4,4,4,4,3,5,3,3,4,4,2,0.0,neutral or dissatisfied +45151,108590,Male,Loyal Customer,70,Business travel,Business,696,4,3,3,3,2,4,3,4,4,4,4,2,4,4,33,33.0,neutral or dissatisfied +45152,53882,Male,Loyal Customer,40,Personal Travel,Eco,140,4,5,0,1,3,0,3,3,4,1,2,2,1,3,82,107.0,neutral or dissatisfied +45153,75868,Female,Loyal Customer,40,Business travel,Business,1972,4,4,3,4,4,4,4,5,5,5,5,5,5,3,4,3.0,satisfied +45154,119608,Female,Loyal Customer,20,Personal Travel,Eco,1979,2,4,2,3,3,2,3,3,3,2,4,3,1,3,4,0.0,neutral or dissatisfied +45155,24510,Male,Loyal Customer,20,Personal Travel,Eco,481,1,1,1,4,1,1,1,1,2,3,4,4,4,1,0,0.0,neutral or dissatisfied +45156,62538,Male,Loyal Customer,58,Business travel,Business,1846,1,1,1,1,2,3,4,2,2,2,2,3,2,3,7,0.0,satisfied +45157,106003,Female,Loyal Customer,25,Business travel,Business,1999,2,3,2,3,2,2,2,2,4,3,2,1,3,2,0,0.0,neutral or dissatisfied +45158,29887,Male,Loyal Customer,50,Business travel,Eco,261,4,3,3,3,4,4,4,4,5,5,1,3,2,4,0,0.0,satisfied +45159,82085,Female,Loyal Customer,54,Business travel,Business,1276,3,5,5,5,3,3,3,3,3,3,3,4,3,1,16,31.0,neutral or dissatisfied +45160,82419,Male,disloyal Customer,25,Business travel,Business,502,1,5,1,4,5,1,5,5,3,5,4,3,5,5,18,2.0,neutral or dissatisfied +45161,77882,Female,Loyal Customer,44,Business travel,Eco,700,2,3,3,3,2,2,2,4,1,4,3,2,3,2,307,293.0,neutral or dissatisfied +45162,7921,Female,Loyal Customer,10,Personal Travel,Eco,1020,3,0,3,2,2,3,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +45163,93924,Female,disloyal Customer,36,Business travel,Business,507,3,3,3,4,1,3,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +45164,90226,Female,Loyal Customer,55,Business travel,Business,2639,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +45165,88127,Male,Loyal Customer,40,Business travel,Business,2058,0,0,0,1,3,5,5,3,3,3,3,3,3,4,0,12.0,satisfied +45166,70770,Female,disloyal Customer,27,Business travel,Business,328,3,3,3,3,5,3,5,5,5,3,4,3,4,5,31,19.0,neutral or dissatisfied +45167,39088,Female,Loyal Customer,25,Business travel,Business,2297,2,4,4,4,2,2,2,2,2,1,3,3,4,2,0,0.0,neutral or dissatisfied +45168,22922,Female,Loyal Customer,47,Business travel,Business,1724,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +45169,61189,Male,Loyal Customer,61,Business travel,Business,3347,1,1,1,1,3,5,5,5,5,5,5,4,5,5,12,15.0,satisfied +45170,48546,Male,Loyal Customer,28,Personal Travel,Eco,909,4,3,4,3,2,4,2,2,4,4,3,1,3,2,66,62.0,satisfied +45171,120544,Female,Loyal Customer,47,Business travel,Business,2176,1,1,1,1,3,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +45172,72520,Female,Loyal Customer,45,Business travel,Business,2461,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +45173,5371,Male,Loyal Customer,62,Business travel,Business,812,3,3,3,3,4,3,3,3,3,4,3,1,3,2,0,14.0,neutral or dissatisfied +45174,74402,Female,Loyal Customer,56,Business travel,Business,1438,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +45175,41063,Female,disloyal Customer,38,Business travel,Business,224,1,1,1,4,4,1,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +45176,6857,Male,Loyal Customer,36,Business travel,Business,622,2,3,3,3,1,3,2,2,2,2,2,3,2,2,51,122.0,neutral or dissatisfied +45177,87411,Male,Loyal Customer,33,Personal Travel,Eco,425,4,0,4,1,5,4,5,5,3,5,5,3,4,5,10,3.0,neutral or dissatisfied +45178,57237,Male,Loyal Customer,38,Business travel,Business,628,3,3,3,3,2,4,4,4,4,5,4,5,4,3,0,16.0,satisfied +45179,75959,Male,Loyal Customer,40,Business travel,Eco,228,4,3,5,3,4,4,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +45180,46840,Male,Loyal Customer,24,Business travel,Eco,948,4,5,5,5,4,4,5,4,5,5,4,5,3,4,0,0.0,satisfied +45181,11205,Female,Loyal Customer,34,Personal Travel,Eco,134,1,0,1,2,1,1,1,1,4,2,5,4,5,1,21,25.0,neutral or dissatisfied +45182,77800,Male,Loyal Customer,30,Personal Travel,Eco,731,2,2,2,4,1,2,1,1,2,2,4,1,3,1,5,0.0,neutral or dissatisfied +45183,973,Female,Loyal Customer,42,Business travel,Business,2747,2,2,2,2,4,4,3,2,2,2,2,4,2,2,43,55.0,neutral or dissatisfied +45184,24904,Male,Loyal Customer,41,Business travel,Eco,762,5,4,1,4,5,5,5,5,2,2,4,2,4,5,0,6.0,satisfied +45185,4968,Female,Loyal Customer,59,Business travel,Business,931,2,2,5,2,2,5,5,3,3,3,3,5,3,4,0,17.0,satisfied +45186,95556,Female,Loyal Customer,19,Personal Travel,Eco Plus,441,1,1,1,3,5,1,5,5,3,5,3,3,3,5,70,60.0,neutral or dissatisfied +45187,89481,Female,Loyal Customer,49,Business travel,Business,1931,3,3,3,3,4,4,5,2,2,2,2,5,2,4,19,12.0,satisfied +45188,75078,Male,Loyal Customer,48,Business travel,Business,2611,4,4,1,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +45189,52069,Male,Loyal Customer,45,Business travel,Business,351,2,3,2,2,5,4,5,4,4,4,4,3,4,1,0,3.0,satisfied +45190,106068,Female,disloyal Customer,36,Business travel,Business,436,3,3,3,3,2,3,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +45191,67817,Female,disloyal Customer,36,Business travel,Eco,1031,2,2,2,3,3,2,3,3,2,2,4,3,4,3,7,4.0,neutral or dissatisfied +45192,51168,Male,Loyal Customer,18,Personal Travel,Eco,109,4,4,0,2,3,0,3,3,4,1,1,3,2,3,34,24.0,neutral or dissatisfied +45193,83195,Female,Loyal Customer,40,Business travel,Eco,1123,3,3,3,3,3,3,3,3,4,1,3,1,2,3,0,0.0,neutral or dissatisfied +45194,81522,Female,disloyal Customer,25,Business travel,Business,1124,5,5,5,1,2,5,3,2,3,2,4,4,4,2,1,0.0,satisfied +45195,16488,Male,Loyal Customer,36,Business travel,Eco,246,4,4,4,4,4,4,4,4,4,2,1,2,3,4,0,0.0,satisfied +45196,67250,Female,Loyal Customer,62,Personal Travel,Eco,929,4,5,4,3,3,5,5,5,5,4,1,5,5,4,0,0.0,neutral or dissatisfied +45197,42688,Male,Loyal Customer,40,Business travel,Business,3325,3,2,2,2,4,4,4,3,3,4,3,2,3,2,50,50.0,neutral or dissatisfied +45198,74477,Male,disloyal Customer,19,Business travel,Business,1464,5,0,5,5,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +45199,26754,Female,Loyal Customer,44,Business travel,Business,859,2,4,4,4,1,2,3,2,2,2,2,1,2,1,15,23.0,neutral or dissatisfied +45200,36308,Male,Loyal Customer,35,Business travel,Business,3246,5,5,4,5,5,1,4,4,4,4,4,4,4,4,7,12.0,satisfied +45201,87829,Female,disloyal Customer,27,Business travel,Eco,214,3,5,3,3,4,3,4,4,1,1,5,1,5,4,0,0.0,neutral or dissatisfied +45202,98143,Male,Loyal Customer,58,Business travel,Business,562,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +45203,84658,Male,Loyal Customer,48,Business travel,Business,2182,2,2,2,2,3,5,4,5,5,5,5,3,5,3,10,0.0,satisfied +45204,84602,Female,disloyal Customer,22,Business travel,Business,707,5,0,5,3,1,5,1,1,3,4,5,5,4,1,0,0.0,satisfied +45205,125670,Male,Loyal Customer,44,Business travel,Business,3898,4,5,5,5,1,3,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +45206,93992,Male,Loyal Customer,10,Personal Travel,Eco,1315,4,4,5,3,1,5,1,1,5,2,5,4,4,1,0,0.0,satisfied +45207,14170,Male,disloyal Customer,15,Business travel,Eco,526,4,5,4,3,2,4,2,2,3,3,3,5,1,2,19,25.0,satisfied +45208,83155,Male,Loyal Customer,48,Business travel,Business,3354,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +45209,94947,Female,Loyal Customer,49,Business travel,Business,3313,1,5,5,5,1,4,4,1,1,1,1,3,1,2,21,18.0,neutral or dissatisfied +45210,118245,Male,Loyal Customer,18,Personal Travel,Business,1972,1,0,1,2,3,1,2,3,4,5,5,5,5,3,13,15.0,neutral or dissatisfied +45211,56145,Male,Loyal Customer,30,Business travel,Business,1400,4,1,1,1,4,4,4,4,2,3,4,1,3,4,6,9.0,neutral or dissatisfied +45212,76381,Male,disloyal Customer,35,Business travel,Eco,931,2,2,2,4,5,2,5,5,2,5,4,4,3,5,0,0.0,neutral or dissatisfied +45213,122485,Female,Loyal Customer,38,Personal Travel,Eco,808,3,3,3,4,3,3,3,3,3,1,4,4,4,3,0,0.0,neutral or dissatisfied +45214,110706,Female,Loyal Customer,27,Personal Travel,Eco Plus,829,2,5,2,5,3,2,3,3,5,3,5,3,4,3,1,0.0,neutral or dissatisfied +45215,47117,Male,Loyal Customer,65,Personal Travel,Eco,784,3,4,2,4,5,2,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +45216,124419,Female,Loyal Customer,44,Business travel,Business,1992,5,5,5,5,3,4,4,4,4,4,4,5,4,4,2,3.0,satisfied +45217,11401,Female,Loyal Customer,58,Business travel,Business,667,5,5,5,5,3,5,5,3,3,2,3,3,3,3,3,0.0,satisfied +45218,61611,Male,Loyal Customer,43,Business travel,Business,1608,5,5,5,5,3,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +45219,48457,Male,Loyal Customer,31,Business travel,Business,916,4,4,4,4,4,4,4,4,4,5,5,1,5,4,0,3.0,satisfied +45220,2424,Male,Loyal Customer,70,Personal Travel,Eco,767,2,4,2,4,5,2,5,5,5,5,5,3,4,5,68,98.0,neutral or dissatisfied +45221,57234,Female,disloyal Customer,54,Business travel,Eco Plus,1514,1,1,1,3,4,1,3,4,3,1,2,2,2,4,0,0.0,neutral or dissatisfied +45222,126045,Male,Loyal Customer,61,Business travel,Business,2738,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +45223,79526,Male,Loyal Customer,41,Business travel,Business,762,1,5,5,5,2,3,3,1,1,1,1,4,1,2,33,45.0,neutral or dissatisfied +45224,9886,Female,Loyal Customer,51,Business travel,Business,1521,3,3,3,3,4,5,4,2,2,2,2,4,2,5,0,3.0,satisfied +45225,72731,Female,Loyal Customer,55,Personal Travel,Eco Plus,964,4,4,4,3,3,5,5,2,2,4,2,5,2,5,4,0.0,satisfied +45226,91306,Male,Loyal Customer,71,Business travel,Eco Plus,366,4,4,4,4,4,4,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +45227,44075,Female,Loyal Customer,24,Business travel,Business,3326,2,5,2,2,5,5,5,5,3,3,1,2,3,5,0,2.0,satisfied +45228,103894,Female,Loyal Customer,30,Business travel,Eco Plus,1056,2,3,3,3,2,2,2,2,2,3,4,1,4,2,0,21.0,neutral or dissatisfied +45229,95217,Male,Loyal Customer,45,Personal Travel,Eco,148,0,5,0,2,3,0,3,3,1,5,2,4,1,3,0,0.0,satisfied +45230,32341,Female,disloyal Customer,27,Business travel,Eco,216,1,0,1,4,4,1,4,4,1,5,2,2,4,4,0,0.0,neutral or dissatisfied +45231,82743,Female,Loyal Customer,50,Business travel,Eco,409,1,2,1,1,4,3,4,1,1,1,1,2,1,3,22,7.0,neutral or dissatisfied +45232,62837,Male,disloyal Customer,12,Business travel,Eco,2486,1,1,1,4,1,1,1,1,2,3,3,1,3,1,1,4.0,neutral or dissatisfied +45233,107037,Male,Loyal Customer,55,Business travel,Business,2300,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,3.0,satisfied +45234,87735,Female,disloyal Customer,7,Business travel,Eco,999,4,4,4,4,4,4,4,3,5,3,3,4,2,4,15,46.0,neutral or dissatisfied +45235,49728,Male,Loyal Customer,34,Business travel,Business,3036,3,3,3,3,2,5,4,5,5,5,3,4,5,3,0,0.0,satisfied +45236,56558,Male,Loyal Customer,48,Business travel,Business,1023,1,1,1,1,4,4,4,5,5,5,5,5,5,5,61,49.0,satisfied +45237,26350,Female,Loyal Customer,54,Business travel,Business,1696,2,2,2,2,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +45238,85011,Female,disloyal Customer,11,Business travel,Eco,885,2,2,2,3,4,2,4,4,5,2,4,3,4,4,0,0.0,neutral or dissatisfied +45239,118401,Female,Loyal Customer,21,Personal Travel,Business,325,2,3,2,3,3,2,3,3,4,1,1,3,5,3,14,17.0,neutral or dissatisfied +45240,94950,Female,Loyal Customer,75,Business travel,Eco,248,2,1,1,1,2,1,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +45241,95760,Female,Loyal Customer,40,Personal Travel,Eco,419,3,3,3,4,3,3,3,3,4,3,4,2,1,3,0,0.0,neutral or dissatisfied +45242,71545,Male,disloyal Customer,50,Business travel,Business,1012,2,2,2,3,3,2,4,3,4,5,4,5,5,3,40,27.0,neutral or dissatisfied +45243,24596,Male,Loyal Customer,31,Business travel,Eco,526,4,3,4,3,4,4,4,4,2,1,1,5,4,4,8,24.0,satisfied +45244,9612,Female,Loyal Customer,41,Personal Travel,Eco,229,3,5,3,4,5,3,5,5,4,4,5,3,5,5,25,20.0,neutral or dissatisfied +45245,128851,Male,Loyal Customer,14,Personal Travel,Eco,2475,3,2,2,4,1,2,1,1,4,4,4,3,3,1,29,,neutral or dissatisfied +45246,92848,Male,Loyal Customer,47,Business travel,Eco Plus,1587,2,2,2,2,2,2,2,2,3,2,2,4,4,2,0,0.0,neutral or dissatisfied +45247,82986,Female,disloyal Customer,19,Business travel,Eco,1084,1,1,1,3,5,1,5,5,4,2,4,4,4,5,71,55.0,neutral or dissatisfied +45248,65034,Male,Loyal Customer,56,Personal Travel,Eco,224,3,4,3,3,3,3,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +45249,108287,Male,disloyal Customer,12,Business travel,Eco,1288,3,3,3,5,2,3,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +45250,23248,Male,Loyal Customer,27,Business travel,Business,2894,3,4,3,3,2,2,2,4,2,1,3,2,2,2,134,117.0,satisfied +45251,6478,Female,disloyal Customer,24,Business travel,Eco,557,2,0,2,1,3,2,3,3,3,2,5,3,5,3,19,20.0,neutral or dissatisfied +45252,4335,Male,Loyal Customer,53,Business travel,Business,473,3,3,3,3,4,5,5,4,4,4,4,5,4,5,0,7.0,satisfied +45253,95438,Male,Loyal Customer,56,Business travel,Eco Plus,248,1,1,5,1,1,1,1,1,2,2,2,1,3,1,13,11.0,neutral or dissatisfied +45254,49141,Female,Loyal Customer,77,Business travel,Business,3639,1,1,4,1,1,3,1,4,4,4,5,2,4,2,0,2.0,satisfied +45255,59750,Male,disloyal Customer,21,Business travel,Business,927,4,4,4,2,3,4,3,3,5,3,4,3,5,3,0,0.0,satisfied +45256,129183,Female,Loyal Customer,28,Business travel,Business,2288,4,4,4,4,4,4,4,4,5,5,3,3,5,4,0,0.0,satisfied +45257,83291,Male,Loyal Customer,62,Personal Travel,Eco,1979,3,1,3,3,2,3,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +45258,19194,Female,disloyal Customer,28,Business travel,Eco,542,3,0,3,1,3,3,3,3,5,1,2,3,3,3,5,4.0,neutral or dissatisfied +45259,62845,Male,Loyal Customer,12,Personal Travel,Eco Plus,2399,3,4,2,3,2,2,2,2,1,3,4,3,3,2,0,9.0,neutral or dissatisfied +45260,59565,Female,Loyal Customer,27,Business travel,Business,787,3,3,3,3,5,5,5,5,3,5,5,4,5,5,0,4.0,satisfied +45261,71647,Female,Loyal Customer,67,Personal Travel,Eco,1005,3,5,3,3,2,5,5,4,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +45262,78318,Male,disloyal Customer,30,Business travel,Business,1547,2,2,2,4,1,2,2,1,2,3,3,1,3,1,0,0.0,neutral or dissatisfied +45263,53486,Female,Loyal Customer,57,Business travel,Eco,788,4,3,5,3,2,2,3,4,4,4,4,5,4,1,0,0.0,satisfied +45264,8048,Female,Loyal Customer,32,Business travel,Business,3212,5,5,5,5,4,4,4,4,4,2,4,4,4,4,0,5.0,satisfied +45265,128119,Male,disloyal Customer,27,Business travel,Eco,1488,4,4,4,3,2,4,1,2,3,5,2,3,4,2,0,0.0,neutral or dissatisfied +45266,44161,Male,disloyal Customer,26,Business travel,Business,229,4,0,4,5,1,4,1,1,1,3,4,4,3,1,0,0.0,satisfied +45267,96074,Female,Loyal Customer,21,Personal Travel,Eco,1069,2,5,2,1,1,2,1,1,5,1,2,2,5,1,0,0.0,neutral or dissatisfied +45268,65048,Female,Loyal Customer,10,Personal Travel,Eco,247,4,1,4,3,2,4,2,2,4,4,2,2,2,2,5,0.0,neutral or dissatisfied +45269,99178,Female,Loyal Customer,52,Business travel,Business,1620,1,1,1,1,5,4,4,2,2,2,2,4,2,4,18,5.0,satisfied +45270,1012,Male,Loyal Customer,54,Business travel,Business,3098,3,3,3,3,1,1,1,5,5,5,5,5,5,2,0,0.0,satisfied +45271,12116,Female,Loyal Customer,20,Business travel,Eco,1034,0,5,0,2,5,0,5,5,5,2,1,3,2,5,0,0.0,satisfied +45272,18083,Male,Loyal Customer,70,Personal Travel,Eco,488,3,2,3,3,4,3,3,4,2,3,3,4,4,4,0,0.0,neutral or dissatisfied +45273,88313,Female,Loyal Customer,39,Business travel,Eco,444,1,2,2,2,1,1,1,1,4,5,3,1,3,1,29,23.0,neutral or dissatisfied +45274,8810,Female,Loyal Customer,40,Business travel,Business,3492,2,2,2,2,5,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +45275,127630,Female,Loyal Customer,36,Business travel,Eco,1773,2,3,3,3,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +45276,29764,Male,Loyal Customer,41,Business travel,Business,198,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +45277,40601,Male,Loyal Customer,67,Personal Travel,Eco,391,5,4,5,3,3,5,3,3,3,5,4,3,4,3,0,0.0,satisfied +45278,33287,Female,Loyal Customer,16,Personal Travel,Eco Plus,102,2,1,2,2,3,2,3,3,4,4,2,3,3,3,0,0.0,neutral or dissatisfied +45279,35652,Male,Loyal Customer,52,Business travel,Eco,2475,4,2,2,2,4,4,4,5,2,5,4,4,4,4,0,25.0,satisfied +45280,47004,Male,Loyal Customer,45,Personal Travel,Eco Plus,916,4,4,4,4,2,4,2,2,4,2,5,3,5,2,6,5.0,neutral or dissatisfied +45281,23165,Female,Loyal Customer,36,Personal Travel,Eco,300,5,2,5,2,2,5,2,2,4,5,2,2,2,2,0,0.0,satisfied +45282,102728,Female,Loyal Customer,31,Personal Travel,Eco,255,3,5,3,1,3,1,1,5,3,3,1,1,4,1,164,156.0,neutral or dissatisfied +45283,9042,Female,disloyal Customer,37,Business travel,Business,108,5,5,5,3,2,5,2,2,5,3,5,3,4,2,0,0.0,satisfied +45284,48180,Male,Loyal Customer,37,Business travel,Business,2541,4,4,4,4,3,4,2,4,4,4,4,4,4,3,0,0.0,satisfied +45285,14803,Male,Loyal Customer,54,Business travel,Business,95,4,4,4,4,2,2,4,4,4,4,5,4,4,4,2,0.0,satisfied +45286,60730,Male,Loyal Customer,65,Personal Travel,Eco,1605,3,4,3,2,2,3,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +45287,24704,Female,Loyal Customer,45,Business travel,Eco,397,4,4,4,4,3,3,2,4,4,4,4,2,4,1,1,6.0,satisfied +45288,81635,Male,Loyal Customer,8,Business travel,Business,907,4,5,5,5,4,4,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +45289,122489,Male,Loyal Customer,31,Personal Travel,Eco,808,2,5,1,3,2,1,2,2,4,5,2,3,5,2,4,1.0,neutral or dissatisfied +45290,113625,Female,Loyal Customer,49,Personal Travel,Eco,258,1,3,1,5,3,5,1,1,1,1,1,1,1,2,39,37.0,neutral or dissatisfied +45291,89713,Female,Loyal Customer,12,Personal Travel,Eco,1076,2,4,2,3,3,2,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +45292,105068,Female,disloyal Customer,23,Business travel,Eco,289,2,4,2,1,4,2,1,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +45293,48392,Male,Loyal Customer,48,Personal Travel,Eco,522,3,5,3,5,2,3,2,2,5,3,5,3,4,2,36,31.0,neutral or dissatisfied +45294,91066,Male,Loyal Customer,49,Personal Travel,Eco,581,1,5,0,1,1,0,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +45295,19947,Female,Loyal Customer,65,Personal Travel,Eco,315,3,4,3,4,3,4,4,5,3,4,3,4,4,4,234,253.0,neutral or dissatisfied +45296,71256,Female,disloyal Customer,21,Business travel,Eco,733,3,3,3,3,1,3,1,1,3,1,3,1,4,1,0,0.0,neutral or dissatisfied +45297,16289,Female,Loyal Customer,50,Personal Travel,Eco,748,4,5,3,1,5,4,5,3,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +45298,17242,Female,Loyal Customer,34,Business travel,Business,2514,1,1,1,1,5,3,4,1,1,1,1,1,1,4,114,91.0,neutral or dissatisfied +45299,69508,Male,Loyal Customer,13,Personal Travel,Eco,1746,3,3,3,4,3,3,3,3,4,5,4,3,3,3,1,0.0,neutral or dissatisfied +45300,87068,Female,Loyal Customer,42,Business travel,Business,594,4,4,4,4,4,5,4,5,5,5,5,5,5,5,33,25.0,satisfied +45301,75310,Male,Loyal Customer,49,Business travel,Business,2486,2,2,2,2,5,4,4,5,4,3,4,4,4,4,0,38.0,satisfied +45302,125566,Female,Loyal Customer,9,Personal Travel,Eco,226,2,5,0,3,3,0,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +45303,89974,Male,Loyal Customer,28,Business travel,Business,3147,4,4,4,4,5,5,5,5,4,4,4,3,5,5,0,8.0,satisfied +45304,124578,Male,Loyal Customer,55,Business travel,Business,1888,5,5,2,5,5,5,4,5,5,5,5,3,5,4,8,4.0,satisfied +45305,124455,Female,disloyal Customer,35,Business travel,Business,980,1,1,1,3,3,1,4,3,3,5,4,5,5,3,0,6.0,neutral or dissatisfied +45306,11466,Female,disloyal Customer,20,Business travel,Eco,316,2,5,2,3,1,2,1,1,3,3,5,3,5,1,0,2.0,neutral or dissatisfied +45307,74356,Female,Loyal Customer,47,Business travel,Business,1171,2,2,2,2,3,5,5,2,2,2,2,4,2,5,0,,satisfied +45308,29798,Female,Loyal Customer,35,Business travel,Eco,204,3,1,1,1,3,3,3,3,1,2,3,4,2,3,3,2.0,satisfied +45309,335,Female,Loyal Customer,56,Business travel,Business,421,1,0,0,3,5,3,3,1,1,0,1,4,1,1,10,0.0,neutral or dissatisfied +45310,106543,Female,Loyal Customer,30,Business travel,Business,719,1,5,1,1,5,5,5,5,3,4,5,4,4,5,0,10.0,satisfied +45311,41727,Female,disloyal Customer,25,Business travel,Business,695,1,5,1,2,3,1,3,3,1,1,2,1,2,3,2,5.0,neutral or dissatisfied +45312,9810,Male,Loyal Customer,61,Personal Travel,Eco,493,2,4,2,4,4,2,4,4,4,3,4,3,5,4,33,25.0,neutral or dissatisfied +45313,105749,Female,disloyal Customer,31,Business travel,Eco,919,1,1,1,3,5,1,4,5,3,1,4,1,3,5,0,0.0,neutral or dissatisfied +45314,101288,Male,Loyal Customer,63,Business travel,Eco,763,3,2,2,2,3,3,3,3,2,5,3,4,4,3,14,0.0,neutral or dissatisfied +45315,18018,Female,Loyal Customer,43,Business travel,Eco Plus,332,3,1,4,1,3,3,3,1,4,3,3,3,4,3,142,157.0,satisfied +45316,127456,Male,Loyal Customer,45,Business travel,Business,2075,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +45317,127449,Female,Loyal Customer,31,Business travel,Business,2075,2,2,2,2,4,4,4,4,4,4,5,4,5,4,32,18.0,satisfied +45318,45744,Female,disloyal Customer,23,Business travel,Eco,391,1,2,1,3,2,1,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +45319,33481,Female,disloyal Customer,38,Business travel,Eco,922,2,2,2,4,2,2,2,2,2,3,4,4,4,2,0,0.0,neutral or dissatisfied +45320,102826,Male,disloyal Customer,22,Business travel,Eco,342,0,3,0,2,2,3,2,2,5,3,4,3,4,2,9,0.0,satisfied +45321,126203,Female,disloyal Customer,35,Business travel,Eco,507,4,2,4,3,3,4,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +45322,113001,Male,Loyal Customer,52,Business travel,Eco,1797,4,3,3,3,4,4,4,4,3,5,4,4,4,4,7,7.0,neutral or dissatisfied +45323,14877,Male,Loyal Customer,64,Business travel,Business,240,1,4,5,4,5,3,3,1,1,1,1,4,1,3,0,3.0,neutral or dissatisfied +45324,112779,Female,Loyal Customer,34,Personal Travel,Eco,590,2,4,2,3,3,2,3,3,4,3,5,3,5,3,29,9.0,neutral or dissatisfied +45325,49922,Male,disloyal Customer,16,Business travel,Eco,190,1,2,1,3,5,1,4,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +45326,78694,Male,Loyal Customer,44,Business travel,Business,1879,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,13.0,satisfied +45327,65167,Male,Loyal Customer,13,Personal Travel,Eco,551,3,2,3,4,2,3,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +45328,16361,Male,Loyal Customer,44,Business travel,Eco,319,4,5,4,4,4,4,4,4,1,5,3,1,4,4,6,0.0,neutral or dissatisfied +45329,86776,Female,Loyal Customer,41,Business travel,Business,3249,3,3,3,3,4,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +45330,15962,Female,Loyal Customer,37,Personal Travel,Eco,566,2,3,2,3,4,2,5,4,4,3,3,4,4,4,0,6.0,neutral or dissatisfied +45331,2141,Female,Loyal Customer,55,Personal Travel,Eco,404,4,2,4,2,3,2,2,3,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +45332,76401,Male,Loyal Customer,12,Business travel,Eco Plus,931,4,2,2,2,4,4,2,4,1,2,4,4,3,4,0,24.0,neutral or dissatisfied +45333,25759,Female,Loyal Customer,65,Personal Travel,Eco,356,3,4,3,4,2,4,4,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +45334,22984,Male,Loyal Customer,21,Personal Travel,Eco,956,3,5,3,1,4,3,4,4,3,5,5,4,4,4,20,15.0,neutral or dissatisfied +45335,15354,Male,Loyal Customer,51,Personal Travel,Business,399,3,4,4,2,2,2,3,5,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +45336,121402,Male,Loyal Customer,36,Business travel,Business,2594,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,6.0,satisfied +45337,73680,Female,disloyal Customer,50,Business travel,Eco,192,3,3,3,4,4,3,4,4,2,1,4,1,4,4,1,11.0,neutral or dissatisfied +45338,16073,Female,Loyal Customer,7,Personal Travel,Eco,501,2,3,2,4,1,2,1,1,2,2,4,1,4,1,8,5.0,neutral or dissatisfied +45339,7875,Female,Loyal Customer,24,Business travel,Business,910,4,4,4,4,5,5,5,5,5,2,4,3,4,5,25,25.0,satisfied +45340,50891,Male,Loyal Customer,60,Personal Travel,Eco,250,5,5,5,4,4,5,4,4,5,2,5,3,5,4,19,3.0,satisfied +45341,118587,Female,disloyal Customer,24,Business travel,Business,304,4,4,4,2,3,4,3,3,3,3,5,4,5,3,0,0.0,satisfied +45342,91114,Male,Loyal Customer,58,Personal Travel,Eco,250,3,4,3,4,1,3,1,1,3,4,5,3,5,1,31,33.0,neutral or dissatisfied +45343,124538,Male,Loyal Customer,43,Business travel,Business,1663,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +45344,126098,Female,Loyal Customer,66,Business travel,Business,468,3,1,1,1,3,3,2,3,3,2,3,4,3,4,46,40.0,neutral or dissatisfied +45345,51254,Female,disloyal Customer,24,Business travel,Eco Plus,158,2,0,2,2,2,2,2,2,3,3,4,4,5,2,0,35.0,neutral or dissatisfied +45346,86897,Male,Loyal Customer,59,Business travel,Business,341,2,2,5,2,5,4,5,4,4,4,4,5,4,4,8,15.0,satisfied +45347,63940,Male,Loyal Customer,14,Personal Travel,Eco,1172,2,5,2,4,1,2,1,1,5,2,3,3,5,1,0,1.0,neutral or dissatisfied +45348,75835,Female,Loyal Customer,42,Business travel,Business,1437,3,3,3,3,5,5,4,5,5,5,5,5,5,4,0,1.0,satisfied +45349,98844,Male,Loyal Customer,40,Business travel,Business,1482,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +45350,886,Male,Loyal Customer,47,Business travel,Business,2708,2,1,1,1,3,2,1,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +45351,120952,Female,Loyal Customer,31,Business travel,Business,993,1,1,1,1,4,5,4,4,3,2,4,5,4,4,0,0.0,satisfied +45352,113134,Female,Loyal Customer,62,Personal Travel,Eco Plus,479,3,5,3,1,3,5,2,4,4,3,4,5,4,4,21,23.0,neutral or dissatisfied +45353,72027,Female,Loyal Customer,49,Business travel,Business,3711,5,4,5,5,4,4,4,5,3,4,5,4,4,4,0,0.0,satisfied +45354,106157,Female,Loyal Customer,67,Personal Travel,Eco,436,0,1,0,4,2,3,4,4,4,0,2,1,4,3,35,69.0,satisfied +45355,54133,Male,Loyal Customer,28,Business travel,Business,1400,1,1,5,1,4,4,4,4,5,2,1,4,5,4,6,0.0,satisfied +45356,16215,Female,Loyal Customer,67,Business travel,Eco Plus,199,4,2,5,5,3,4,4,4,4,4,4,3,4,3,0,35.0,neutral or dissatisfied +45357,24135,Female,disloyal Customer,32,Business travel,Business,302,3,3,3,2,3,3,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +45358,76585,Male,Loyal Customer,50,Business travel,Eco,534,4,5,5,5,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +45359,48650,Female,Loyal Customer,51,Business travel,Business,3882,3,3,3,3,3,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +45360,16684,Female,Loyal Customer,56,Business travel,Eco Plus,605,2,5,5,5,1,3,4,2,2,2,2,1,2,4,11,35.0,neutral or dissatisfied +45361,82273,Male,Loyal Customer,25,Business travel,Business,1481,4,4,4,4,5,5,5,5,5,3,4,4,4,5,7,0.0,satisfied +45362,73977,Female,Loyal Customer,56,Personal Travel,Eco,2218,2,4,2,3,2,5,5,3,5,4,1,5,3,5,0,3.0,neutral or dissatisfied +45363,125354,Male,disloyal Customer,22,Business travel,Eco,599,1,2,1,4,2,1,2,2,2,4,3,4,4,2,0,5.0,neutral or dissatisfied +45364,123242,Male,Loyal Customer,42,Personal Travel,Eco,600,4,3,4,3,3,4,3,3,1,3,3,4,2,3,0,0.0,neutral or dissatisfied +45365,55650,Female,Loyal Customer,27,Business travel,Business,315,2,2,2,2,4,4,4,4,5,2,5,4,5,4,116,130.0,satisfied +45366,58008,Female,disloyal Customer,20,Business travel,Eco,1162,2,2,2,2,3,2,2,3,3,3,1,1,2,3,15,8.0,neutral or dissatisfied +45367,2909,Female,Loyal Customer,19,Personal Travel,Eco,409,3,4,3,2,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +45368,867,Female,Loyal Customer,45,Business travel,Business,3665,1,5,5,5,5,3,3,3,3,3,1,2,3,1,0,0.0,neutral or dissatisfied +45369,11035,Male,Loyal Customer,37,Business travel,Business,2477,3,2,2,2,5,4,3,3,3,3,3,2,3,3,7,31.0,neutral or dissatisfied +45370,125087,Female,Loyal Customer,60,Business travel,Business,361,2,2,2,2,5,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +45371,25110,Male,Loyal Customer,37,Business travel,Business,1962,4,1,3,1,1,3,2,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +45372,25451,Male,Loyal Customer,55,Personal Travel,Eco,669,2,5,2,1,3,2,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +45373,31205,Female,Loyal Customer,50,Business travel,Business,628,1,1,1,1,4,1,1,3,3,4,3,4,3,1,0,8.0,satisfied +45374,40933,Male,Loyal Customer,43,Business travel,Eco Plus,590,5,3,3,3,5,5,5,5,4,4,1,3,2,5,0,0.0,satisfied +45375,71488,Female,Loyal Customer,48,Business travel,Business,3558,1,3,3,3,1,1,1,2,4,3,3,1,3,1,134,125.0,neutral or dissatisfied +45376,52390,Male,Loyal Customer,57,Personal Travel,Eco,370,3,4,4,3,3,4,3,3,4,5,5,5,2,3,0,0.0,neutral or dissatisfied +45377,106868,Female,Loyal Customer,35,Business travel,Business,2506,3,3,3,3,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +45378,6924,Male,Loyal Customer,51,Personal Travel,Eco,265,3,4,3,2,1,3,1,1,1,5,3,1,5,1,12,10.0,neutral or dissatisfied +45379,96986,Female,Loyal Customer,42,Business travel,Business,3929,4,4,4,4,4,5,4,3,3,4,3,3,3,5,3,0.0,satisfied +45380,70633,Female,Loyal Customer,51,Business travel,Business,3879,3,3,5,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +45381,107007,Male,Loyal Customer,47,Business travel,Business,2482,5,5,2,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +45382,34522,Female,Loyal Customer,51,Personal Travel,Eco,1521,3,2,3,4,4,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +45383,96747,Male,Loyal Customer,63,Personal Travel,Eco Plus,813,4,1,4,4,4,4,4,4,3,2,3,3,4,4,0,0.0,satisfied +45384,107765,Male,Loyal Customer,67,Personal Travel,Eco,251,3,4,0,3,4,0,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +45385,68887,Female,Loyal Customer,47,Business travel,Eco,1061,4,5,5,5,2,3,3,4,4,4,4,3,4,3,4,11.0,neutral or dissatisfied +45386,53781,Female,Loyal Customer,50,Business travel,Business,191,2,2,2,2,1,4,4,3,3,3,2,1,3,1,0,0.0,neutral or dissatisfied +45387,59888,Female,Loyal Customer,45,Business travel,Business,3356,2,2,2,2,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +45388,128330,Male,Loyal Customer,41,Business travel,Business,3575,1,1,1,1,2,5,5,5,5,5,5,4,5,3,68,66.0,satisfied +45389,73082,Female,Loyal Customer,34,Business travel,Business,1636,1,1,1,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +45390,43089,Female,Loyal Customer,15,Personal Travel,Eco,236,2,5,0,2,5,0,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +45391,80045,Male,Loyal Customer,68,Personal Travel,Eco,1005,4,5,3,3,4,3,4,4,5,3,4,5,5,4,0,3.0,neutral or dissatisfied +45392,9753,Female,disloyal Customer,9,Business travel,Eco,970,5,5,5,3,1,5,1,1,5,4,4,5,5,1,0,0.0,satisfied +45393,73029,Male,Loyal Customer,56,Personal Travel,Eco,1096,1,0,1,4,2,1,4,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +45394,17250,Male,Loyal Customer,28,Business travel,Business,1092,2,5,5,5,2,2,2,2,2,3,3,3,4,2,0,0.0,neutral or dissatisfied +45395,112082,Female,Loyal Customer,66,Business travel,Eco,1091,4,2,2,2,2,5,4,4,4,4,4,5,4,1,0,0.0,satisfied +45396,59317,Female,disloyal Customer,30,Business travel,Business,2449,3,3,3,4,1,3,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +45397,82537,Male,disloyal Customer,21,Business travel,Business,440,5,1,5,4,5,5,5,5,5,4,5,4,4,5,3,0.0,satisfied +45398,39581,Female,disloyal Customer,37,Business travel,Eco,954,3,3,3,4,1,3,5,1,3,4,3,3,4,1,0,0.0,neutral or dissatisfied +45399,86287,Female,Loyal Customer,25,Personal Travel,Eco,356,3,4,2,2,2,2,5,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +45400,4767,Male,disloyal Customer,42,Business travel,Business,438,4,4,4,4,3,4,3,3,3,4,5,5,4,3,0,0.0,satisfied +45401,102763,Male,Loyal Customer,59,Business travel,Business,1618,4,4,4,4,4,3,5,5,5,5,5,5,5,3,10,4.0,satisfied +45402,103580,Female,Loyal Customer,57,Business travel,Business,3590,5,5,5,5,4,5,5,4,4,4,4,4,4,3,68,67.0,satisfied +45403,20578,Female,Loyal Customer,46,Personal Travel,Eco,565,2,4,2,1,4,4,5,5,5,2,5,5,5,4,25,52.0,neutral or dissatisfied +45404,40351,Female,Loyal Customer,47,Business travel,Eco,1428,5,4,4,4,3,4,3,5,5,5,5,5,5,2,27,11.0,satisfied +45405,123843,Male,disloyal Customer,25,Business travel,Eco,541,1,1,1,3,2,1,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +45406,31458,Female,Loyal Customer,32,Business travel,Business,846,5,5,5,5,3,3,3,3,3,2,1,3,3,3,0,10.0,satisfied +45407,28569,Female,Loyal Customer,42,Business travel,Eco,2603,4,4,4,4,5,5,3,4,4,4,4,4,4,4,0,0.0,satisfied +45408,44859,Male,Loyal Customer,24,Business travel,Business,585,3,3,3,3,5,5,5,5,3,4,5,1,3,5,0,0.0,satisfied +45409,82980,Female,Loyal Customer,46,Business travel,Business,2419,5,5,5,5,3,4,5,4,4,4,4,5,4,5,2,48.0,satisfied +45410,115777,Female,Loyal Customer,49,Business travel,Business,325,3,5,5,5,1,4,4,3,3,3,3,1,3,3,1,0.0,neutral or dissatisfied +45411,29457,Female,Loyal Customer,41,Personal Travel,Eco,421,3,4,3,3,3,3,3,3,3,3,2,2,1,3,0,0.0,neutral or dissatisfied +45412,20581,Male,Loyal Customer,28,Personal Travel,Eco,533,4,2,3,3,2,3,2,2,3,1,3,2,4,2,0,0.0,satisfied +45413,124216,Female,Loyal Customer,19,Personal Travel,Eco,2176,4,1,4,2,4,4,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +45414,126768,Male,Loyal Customer,31,Business travel,Business,2370,1,1,3,1,5,4,5,5,5,4,3,3,4,5,0,15.0,satisfied +45415,118705,Male,Loyal Customer,39,Personal Travel,Eco,325,3,1,3,2,3,3,3,3,3,2,2,3,2,3,8,6.0,neutral or dissatisfied +45416,56192,Female,Loyal Customer,48,Personal Travel,Eco,1372,2,5,1,2,5,4,5,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +45417,95227,Male,Loyal Customer,30,Personal Travel,Eco,189,2,5,2,1,5,2,5,5,2,5,2,2,4,5,46,43.0,neutral or dissatisfied +45418,50185,Male,Loyal Customer,53,Business travel,Business,86,4,5,5,5,2,3,3,1,1,1,4,1,1,2,0,0.0,neutral or dissatisfied +45419,11707,Female,Loyal Customer,52,Business travel,Business,3338,3,3,5,3,5,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +45420,97393,Female,Loyal Customer,23,Business travel,Eco Plus,843,3,4,4,4,3,3,3,3,2,3,3,4,4,3,3,5.0,neutral or dissatisfied +45421,310,Female,Loyal Customer,60,Business travel,Business,2180,1,1,1,1,5,4,4,3,3,3,3,5,3,4,0,12.0,satisfied +45422,10441,Female,Loyal Customer,42,Business travel,Business,140,0,4,0,5,3,4,4,5,5,5,5,5,5,3,18,2.0,satisfied +45423,39638,Male,Loyal Customer,67,Personal Travel,Eco Plus,620,1,4,1,1,1,1,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +45424,11716,Male,Loyal Customer,43,Business travel,Business,429,3,3,3,3,4,4,4,5,5,5,5,5,5,3,29,22.0,satisfied +45425,102387,Male,Loyal Customer,35,Business travel,Business,3097,3,2,2,2,3,4,4,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +45426,90590,Female,Loyal Customer,38,Business travel,Business,1778,2,2,2,2,2,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +45427,40109,Female,Loyal Customer,70,Business travel,Business,3922,3,1,1,1,2,3,3,3,3,3,3,1,3,1,19,21.0,neutral or dissatisfied +45428,93590,Male,Loyal Customer,46,Personal Travel,Eco,159,1,4,0,2,2,0,2,2,3,4,4,3,5,2,25,22.0,neutral or dissatisfied +45429,120985,Male,Loyal Customer,48,Business travel,Business,920,3,3,3,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +45430,97172,Female,Loyal Customer,24,Personal Travel,Eco,1313,3,3,4,4,5,4,5,5,4,2,4,1,3,5,3,0.0,neutral or dissatisfied +45431,46449,Male,Loyal Customer,41,Business travel,Business,3132,4,4,4,4,5,4,5,5,5,4,4,5,5,4,0,0.0,satisfied +45432,88970,Female,disloyal Customer,28,Business travel,Eco,1312,2,2,2,4,3,2,5,3,2,2,4,4,4,3,1,0.0,neutral or dissatisfied +45433,107230,Male,Loyal Customer,51,Business travel,Business,2065,5,5,5,5,2,5,5,5,5,5,5,5,5,5,23,0.0,satisfied +45434,7114,Male,Loyal Customer,34,Personal Travel,Eco,177,3,3,3,3,2,3,2,2,1,2,2,3,2,2,0,0.0,neutral or dissatisfied +45435,85855,Male,Loyal Customer,60,Personal Travel,Eco Plus,666,2,5,2,3,2,2,2,2,4,2,2,4,2,2,11,0.0,neutral or dissatisfied +45436,118239,Male,Loyal Customer,66,Business travel,Eco,1187,1,1,1,1,1,1,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +45437,43950,Male,Loyal Customer,60,Business travel,Eco,257,3,2,2,2,3,3,3,3,3,3,1,3,2,3,0,0.0,satisfied +45438,25281,Male,disloyal Customer,22,Business travel,Eco,321,2,4,2,3,3,2,3,3,5,4,1,2,3,3,18,8.0,neutral or dissatisfied +45439,88675,Female,Loyal Customer,9,Personal Travel,Eco,594,2,1,2,2,2,2,2,2,1,5,3,3,2,2,0,6.0,neutral or dissatisfied +45440,62614,Male,Loyal Customer,23,Personal Travel,Eco,1846,3,0,3,2,4,3,4,4,4,4,3,4,4,4,0,17.0,neutral or dissatisfied +45441,86173,Male,disloyal Customer,64,Business travel,Business,377,5,5,5,3,2,5,2,2,4,5,4,5,4,2,0,0.0,satisfied +45442,33632,Female,Loyal Customer,15,Personal Travel,Eco,413,2,5,2,2,3,2,5,3,3,4,5,4,5,3,0,25.0,neutral or dissatisfied +45443,107859,Female,Loyal Customer,39,Business travel,Business,2681,3,4,4,4,2,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +45444,41120,Male,disloyal Customer,26,Business travel,Business,224,1,2,1,3,5,1,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +45445,117851,Female,Loyal Customer,31,Personal Travel,Eco,2133,4,1,4,2,2,4,2,2,2,5,1,4,1,2,76,84.0,neutral or dissatisfied +45446,53380,Male,Loyal Customer,8,Personal Travel,Eco,1476,3,4,3,4,2,3,2,2,3,1,3,3,3,2,7,22.0,neutral or dissatisfied +45447,13402,Female,Loyal Customer,22,Business travel,Eco Plus,456,0,4,4,4,0,1,2,0,4,1,3,2,3,0,0,0.0,neutral or dissatisfied +45448,72200,Male,Loyal Customer,21,Personal Travel,Eco,594,2,4,2,2,2,2,5,2,5,2,3,1,2,2,0,0.0,neutral or dissatisfied +45449,99804,Male,Loyal Customer,40,Personal Travel,Eco,632,4,5,4,4,3,4,3,3,5,5,5,5,4,3,0,0.0,satisfied +45450,51761,Female,Loyal Customer,68,Personal Travel,Eco,261,2,5,2,3,2,2,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +45451,111808,Male,Loyal Customer,60,Personal Travel,Eco,349,1,4,4,2,1,4,1,1,5,3,2,5,4,1,32,30.0,neutral or dissatisfied +45452,95387,Male,Loyal Customer,47,Personal Travel,Eco,239,3,4,3,2,5,3,5,5,3,2,4,5,5,5,12,7.0,neutral or dissatisfied +45453,34683,Male,disloyal Customer,44,Business travel,Eco,209,2,4,2,2,5,2,5,5,1,5,3,3,2,5,8,30.0,neutral or dissatisfied +45454,30692,Female,Loyal Customer,49,Business travel,Eco,680,1,3,3,3,3,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +45455,27639,Female,disloyal Customer,38,Business travel,Eco Plus,650,3,3,3,2,3,3,3,3,1,4,1,3,5,3,0,0.0,neutral or dissatisfied +45456,51439,Male,Loyal Customer,46,Personal Travel,Eco Plus,308,1,2,1,4,2,1,2,2,1,4,3,1,3,2,0,12.0,neutral or dissatisfied +45457,81211,Male,Loyal Customer,44,Business travel,Business,1426,3,3,3,3,5,5,5,4,4,4,4,4,4,4,15,12.0,satisfied +45458,113891,Female,Loyal Customer,30,Business travel,Business,2329,4,4,4,4,3,3,3,3,5,3,4,3,5,3,6,29.0,satisfied +45459,80536,Female,Loyal Customer,8,Personal Travel,Eco Plus,1678,3,5,3,4,2,3,2,2,1,1,2,1,2,2,0,0.0,neutral or dissatisfied +45460,12108,Female,disloyal Customer,27,Business travel,Eco,1034,4,5,5,4,3,5,3,3,5,4,5,3,1,3,0,0.0,satisfied +45461,88682,Female,Loyal Customer,58,Personal Travel,Eco,581,4,4,4,4,4,5,5,3,3,4,3,5,3,5,0,0.0,neutral or dissatisfied +45462,109713,Female,Loyal Customer,28,Business travel,Business,587,5,5,5,5,4,4,4,4,3,3,4,3,4,4,127,123.0,satisfied +45463,124698,Male,Loyal Customer,45,Business travel,Business,1971,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +45464,46903,Female,Loyal Customer,49,Business travel,Eco,844,2,2,2,2,2,2,2,2,2,2,2,1,2,1,20,25.0,neutral or dissatisfied +45465,62418,Male,Loyal Customer,49,Business travel,Business,2457,2,2,2,2,4,3,5,5,5,5,5,3,5,4,2,0.0,satisfied +45466,99500,Female,Loyal Customer,49,Personal Travel,Eco,283,3,5,3,4,4,4,5,4,4,3,1,3,4,4,0,0.0,neutral or dissatisfied +45467,71267,Female,Loyal Customer,39,Personal Travel,Eco,733,5,2,5,3,2,5,2,2,1,2,3,2,4,2,0,0.0,satisfied +45468,81686,Male,disloyal Customer,27,Business travel,Eco,907,2,2,2,3,1,2,1,1,1,1,4,4,4,1,49,42.0,neutral or dissatisfied +45469,120313,Male,Loyal Customer,43,Business travel,Business,268,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,2.0,satisfied +45470,86802,Male,disloyal Customer,20,Business travel,Eco,692,4,4,4,2,4,4,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +45471,34318,Female,Loyal Customer,48,Personal Travel,Eco Plus,280,2,2,2,4,4,3,4,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +45472,107057,Female,Loyal Customer,67,Business travel,Business,480,5,5,5,5,4,3,3,2,2,2,2,1,2,5,0,0.0,satisfied +45473,30069,Female,Loyal Customer,67,Personal Travel,Eco,204,5,4,5,4,5,3,3,3,3,5,3,4,3,1,0,3.0,satisfied +45474,48178,Male,disloyal Customer,28,Business travel,Eco,259,3,5,3,1,5,3,5,5,2,2,5,5,3,5,0,0.0,neutral or dissatisfied +45475,123209,Male,Loyal Customer,22,Personal Travel,Eco,600,4,2,4,3,2,4,2,2,2,3,3,3,4,2,0,0.0,neutral or dissatisfied +45476,88025,Male,disloyal Customer,44,Business travel,Business,404,3,3,3,3,2,3,1,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +45477,48082,Male,Loyal Customer,43,Business travel,Business,3530,2,2,2,2,1,3,3,3,3,4,3,4,3,4,0,0.0,satisfied +45478,107845,Female,disloyal Customer,18,Business travel,Business,349,0,4,0,3,2,0,3,2,3,2,5,3,5,2,16,2.0,satisfied +45479,22533,Female,Loyal Customer,46,Personal Travel,Eco Plus,143,3,4,3,2,4,2,2,4,4,3,4,3,4,2,16,11.0,neutral or dissatisfied +45480,60213,Male,Loyal Customer,26,Business travel,Eco,1546,1,2,2,2,1,1,4,1,2,1,3,4,4,1,10,8.0,neutral or dissatisfied +45481,95805,Female,Loyal Customer,43,Business travel,Business,3094,1,5,5,5,1,3,3,1,1,1,1,2,1,1,7,0.0,neutral or dissatisfied +45482,16207,Female,Loyal Customer,29,Personal Travel,Eco,199,2,5,2,2,5,2,5,5,5,4,5,5,4,5,19,12.0,neutral or dissatisfied +45483,99156,Male,Loyal Customer,38,Business travel,Business,986,2,2,2,2,2,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +45484,124263,Male,Loyal Customer,35,Personal Travel,Eco Plus,1916,2,1,2,2,1,2,1,1,2,2,2,2,3,1,4,3.0,neutral or dissatisfied +45485,94833,Female,disloyal Customer,37,Business travel,Business,677,2,2,2,3,4,2,4,4,5,3,5,5,4,4,5,1.0,neutral or dissatisfied +45486,77225,Male,disloyal Customer,23,Business travel,Business,1590,5,0,5,2,3,5,5,3,4,3,3,5,5,3,26,16.0,satisfied +45487,61673,Male,disloyal Customer,26,Business travel,Business,1609,1,1,1,4,4,1,3,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +45488,111023,Female,disloyal Customer,54,Business travel,Eco,240,3,1,3,4,2,3,2,2,3,1,4,1,4,2,8,9.0,neutral or dissatisfied +45489,114432,Female,disloyal Customer,34,Business travel,Business,390,1,2,2,5,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +45490,93293,Female,Loyal Customer,26,Personal Travel,Eco,806,0,5,0,2,3,0,5,3,5,3,4,5,3,3,4,2.0,satisfied +45491,67426,Female,Loyal Customer,51,Business travel,Eco,641,3,2,2,2,3,4,3,3,3,3,3,1,3,1,0,11.0,neutral or dissatisfied +45492,106739,Male,Loyal Customer,21,Business travel,Eco,829,1,3,5,3,1,1,2,1,1,5,3,1,3,1,49,60.0,neutral or dissatisfied +45493,88380,Male,Loyal Customer,30,Business travel,Business,3239,3,4,4,4,3,4,3,3,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +45494,6604,Male,Loyal Customer,51,Personal Travel,Eco,473,2,4,2,1,3,2,3,3,3,4,1,1,5,3,3,4.0,neutral or dissatisfied +45495,114358,Female,disloyal Customer,32,Business travel,Business,957,1,1,1,4,1,1,1,1,4,3,5,5,5,1,8,0.0,neutral or dissatisfied +45496,105152,Female,Loyal Customer,42,Business travel,Eco,220,2,3,5,5,2,2,2,1,1,2,3,2,2,2,289,288.0,neutral or dissatisfied +45497,117584,Male,disloyal Customer,9,Business travel,Eco,843,4,4,4,4,2,4,2,2,1,1,4,3,3,2,0,0.0,neutral or dissatisfied +45498,58032,Female,Loyal Customer,59,Personal Travel,Eco Plus,1721,4,4,4,3,2,2,3,4,4,4,2,2,4,1,1,0.0,satisfied +45499,27281,Female,Loyal Customer,49,Personal Travel,Business,1050,2,2,2,4,4,4,3,4,4,2,4,3,4,2,0,5.0,neutral or dissatisfied +45500,66186,Male,Loyal Customer,65,Business travel,Eco,550,3,5,3,5,3,3,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +45501,66202,Female,Loyal Customer,35,Business travel,Business,3210,3,1,1,1,3,3,3,3,3,3,3,2,3,1,4,0.0,neutral or dissatisfied +45502,12701,Male,Loyal Customer,36,Business travel,Business,2113,5,5,5,5,3,1,1,5,5,5,5,1,5,5,0,0.0,satisfied +45503,6483,Female,Loyal Customer,26,Business travel,Eco,557,2,2,3,2,2,2,4,2,3,3,4,1,3,2,12,14.0,neutral or dissatisfied +45504,97611,Female,Loyal Customer,39,Personal Travel,Eco,442,2,5,4,3,5,4,5,5,3,2,5,3,4,5,41,45.0,neutral or dissatisfied +45505,82377,Male,Loyal Customer,42,Business travel,Eco,1953,2,3,3,3,2,2,2,2,4,4,1,2,3,2,71,79.0,neutral or dissatisfied +45506,118173,Male,disloyal Customer,29,Business travel,Business,1444,4,4,4,3,4,4,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +45507,102868,Male,disloyal Customer,22,Business travel,Business,472,4,0,4,5,3,4,3,3,5,3,5,3,4,3,8,0.0,satisfied +45508,108698,Female,Loyal Customer,8,Personal Travel,Eco,577,3,2,3,3,2,3,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +45509,59924,Female,disloyal Customer,50,Business travel,Eco,997,3,3,3,4,4,3,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +45510,120752,Male,Loyal Customer,40,Business travel,Business,678,5,5,5,5,2,4,5,5,5,5,5,3,5,3,8,0.0,satisfied +45511,8520,Female,Loyal Customer,70,Personal Travel,Eco,862,1,4,1,4,2,4,4,2,2,1,2,4,2,2,0,0.0,neutral or dissatisfied +45512,118278,Female,Loyal Customer,36,Business travel,Business,3166,2,2,2,2,2,4,4,3,3,4,3,3,3,4,41,33.0,satisfied +45513,1261,Male,Loyal Customer,63,Personal Travel,Eco,113,2,1,2,4,1,2,4,1,1,5,4,4,4,1,0,0.0,neutral or dissatisfied +45514,93176,Female,Loyal Customer,12,Personal Travel,Eco,1075,2,4,2,5,1,2,1,1,5,5,5,4,5,1,16,5.0,neutral or dissatisfied +45515,28207,Female,Loyal Customer,38,Personal Travel,Eco,550,3,3,3,4,5,3,5,5,1,1,4,2,4,5,0,0.0,neutral or dissatisfied +45516,80678,Female,Loyal Customer,58,Business travel,Business,2230,2,2,2,2,5,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +45517,23679,Male,disloyal Customer,49,Business travel,Eco,251,4,2,3,5,4,3,4,4,5,2,5,1,5,4,22,18.0,satisfied +45518,112387,Male,Loyal Customer,41,Business travel,Business,3932,3,3,3,3,4,4,5,5,5,5,5,5,5,3,19,8.0,satisfied +45519,22037,Male,Loyal Customer,50,Personal Travel,Eco Plus,551,1,3,1,3,1,1,1,1,2,1,2,4,4,1,60,48.0,neutral or dissatisfied +45520,110482,Male,Loyal Customer,63,Personal Travel,Eco,787,4,4,5,5,3,5,3,3,4,3,5,5,4,3,19,12.0,neutral or dissatisfied +45521,88949,Female,disloyal Customer,24,Business travel,Eco,1199,3,3,3,2,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +45522,70010,Female,disloyal Customer,17,Business travel,Eco,236,2,1,2,3,5,2,5,5,4,3,3,2,3,5,0,0.0,neutral or dissatisfied +45523,127205,Male,Loyal Customer,60,Business travel,Eco Plus,370,3,5,5,5,3,3,3,3,1,1,2,1,1,3,0,0.0,neutral or dissatisfied +45524,87319,Female,disloyal Customer,23,Business travel,Eco,577,1,4,1,4,2,1,5,2,3,2,4,1,3,2,17,18.0,neutral or dissatisfied +45525,17100,Female,Loyal Customer,62,Personal Travel,Eco,416,4,3,4,3,4,4,4,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +45526,55726,Male,Loyal Customer,52,Business travel,Business,3509,3,3,3,3,5,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +45527,36147,Male,Loyal Customer,22,Personal Travel,Eco Plus,1562,4,4,4,3,1,4,5,1,3,2,3,4,5,1,0,0.0,neutral or dissatisfied +45528,26689,Male,Loyal Customer,66,Personal Travel,Eco,545,2,5,2,2,3,2,3,3,5,4,5,1,3,3,46,56.0,neutral or dissatisfied +45529,34127,Male,disloyal Customer,25,Business travel,Eco,1046,5,5,5,3,2,5,2,2,4,4,2,2,3,2,56,51.0,satisfied +45530,116974,Female,Loyal Customer,36,Business travel,Business,3850,1,2,2,2,3,2,2,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +45531,64693,Male,Loyal Customer,29,Business travel,Business,551,2,2,3,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +45532,76994,Female,Loyal Customer,41,Business travel,Business,368,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +45533,26228,Female,Loyal Customer,15,Personal Travel,Eco,404,3,4,3,2,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +45534,46303,Male,Loyal Customer,48,Business travel,Eco,802,2,3,3,3,2,2,2,2,3,5,3,1,1,2,6,0.0,satisfied +45535,71163,Male,Loyal Customer,63,Personal Travel,Eco,646,1,3,2,2,5,2,5,5,3,1,3,5,1,5,6,0.0,neutral or dissatisfied +45536,37811,Male,Loyal Customer,38,Personal Travel,Eco Plus,950,1,4,2,3,2,2,2,2,4,3,4,2,3,2,67,51.0,neutral or dissatisfied +45537,61608,Male,Loyal Customer,22,Business travel,Business,1346,3,3,3,3,4,4,4,4,4,2,4,4,5,4,2,0.0,satisfied +45538,3629,Female,disloyal Customer,21,Business travel,Eco,431,4,5,4,5,3,4,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +45539,110337,Female,disloyal Customer,45,Business travel,Business,842,5,5,5,4,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +45540,88323,Male,disloyal Customer,21,Business travel,Eco,594,3,3,3,3,5,3,5,5,4,5,2,3,2,5,0,0.0,neutral or dissatisfied +45541,70839,Male,Loyal Customer,43,Business travel,Business,1670,3,3,3,3,4,5,5,4,4,4,4,5,4,4,12,0.0,satisfied +45542,129666,Male,Loyal Customer,47,Business travel,Business,1568,3,3,3,3,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +45543,94119,Male,Loyal Customer,11,Personal Travel,Business,239,1,5,1,4,1,1,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +45544,83567,Female,disloyal Customer,23,Business travel,Eco,936,5,5,5,1,5,0,5,5,4,4,4,4,5,5,0,0.0,satisfied +45545,107797,Male,disloyal Customer,21,Business travel,Business,349,5,2,5,2,3,5,3,3,4,2,4,5,4,3,36,33.0,satisfied +45546,90806,Male,disloyal Customer,21,Business travel,Eco,594,1,1,1,3,2,1,2,2,3,2,3,2,3,2,1,1.0,neutral or dissatisfied +45547,104226,Female,Loyal Customer,29,Personal Travel,Eco,680,2,5,2,4,5,2,5,5,5,4,5,5,4,5,1,0.0,neutral or dissatisfied +45548,14929,Female,Loyal Customer,45,Business travel,Business,2217,2,2,2,2,4,4,4,5,5,5,5,3,5,5,1,2.0,satisfied +45549,9941,Female,Loyal Customer,38,Business travel,Business,357,1,3,3,3,2,2,3,1,1,1,1,2,1,4,6,35.0,neutral or dissatisfied +45550,50369,Male,Loyal Customer,33,Business travel,Business,109,3,3,3,3,4,5,3,4,1,4,3,1,4,4,0,0.0,satisfied +45551,19966,Female,Loyal Customer,21,Business travel,Business,2311,5,5,5,5,2,2,2,2,3,1,4,4,4,2,0,0.0,satisfied +45552,39657,Male,disloyal Customer,38,Business travel,Eco,288,3,3,3,3,2,3,2,2,4,2,3,2,3,2,11,6.0,neutral or dissatisfied +45553,51853,Female,disloyal Customer,28,Business travel,Eco,438,1,0,2,4,1,2,5,1,3,3,2,2,3,1,4,5.0,neutral or dissatisfied +45554,41051,Female,Loyal Customer,51,Personal Travel,Eco,1086,2,4,1,3,3,4,5,5,5,1,5,5,5,3,0,2.0,neutral or dissatisfied +45555,56354,Female,Loyal Customer,34,Personal Travel,Eco,200,2,1,2,4,3,2,3,3,1,4,3,1,4,3,2,0.0,neutral or dissatisfied +45556,54307,Female,Loyal Customer,53,Business travel,Eco,1597,5,1,1,1,5,4,5,5,5,5,5,5,5,5,3,0.0,satisfied +45557,68462,Female,disloyal Customer,14,Business travel,Eco,1303,4,4,4,5,1,4,1,1,5,3,4,3,4,1,32,0.0,neutral or dissatisfied +45558,48057,Male,Loyal Customer,29,Personal Travel,Eco,677,4,5,4,3,2,4,3,2,3,2,4,4,5,2,3,5.0,neutral or dissatisfied +45559,112458,Female,Loyal Customer,45,Business travel,Business,450,1,1,1,1,5,1,1,5,5,5,5,1,5,5,29,32.0,satisfied +45560,97746,Female,Loyal Customer,38,Business travel,Business,787,2,2,2,2,4,4,3,2,2,2,2,2,2,4,51,53.0,neutral or dissatisfied +45561,62144,Male,Loyal Customer,34,Business travel,Business,2565,3,3,1,3,3,3,5,3,3,3,3,4,3,4,0,0.0,satisfied +45562,121943,Female,Loyal Customer,44,Personal Travel,Business,430,4,5,4,4,4,5,5,2,2,4,2,4,2,1,8,0.0,neutral or dissatisfied +45563,18214,Male,Loyal Customer,49,Business travel,Business,3622,4,4,4,4,5,4,5,4,4,4,4,5,4,1,0,12.0,satisfied +45564,15989,Female,Loyal Customer,32,Business travel,Business,3541,3,3,3,3,5,5,5,5,5,4,2,2,1,5,0,2.0,satisfied +45565,77248,Female,Loyal Customer,48,Business travel,Business,1590,3,3,3,3,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +45566,53928,Female,disloyal Customer,35,Business travel,Eco Plus,224,1,2,2,4,1,2,1,1,1,5,3,3,4,1,6,14.0,neutral or dissatisfied +45567,91422,Female,Loyal Customer,53,Business travel,Business,3016,5,5,5,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +45568,43359,Female,Loyal Customer,40,Personal Travel,Eco,387,3,4,3,4,2,3,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +45569,129703,Male,disloyal Customer,41,Business travel,Eco,337,1,1,0,2,4,0,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +45570,10526,Female,Loyal Customer,43,Business travel,Business,309,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +45571,57477,Male,Loyal Customer,64,Business travel,Business,280,1,3,3,3,5,1,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +45572,102862,Male,Loyal Customer,60,Business travel,Business,2908,1,1,1,1,5,4,5,3,3,3,3,3,3,4,0,1.0,satisfied +45573,41353,Male,Loyal Customer,27,Business travel,Business,3535,4,4,4,4,4,4,4,4,3,3,4,5,4,4,52,61.0,satisfied +45574,22728,Male,disloyal Customer,37,Business travel,Eco,302,4,4,4,5,3,4,1,3,5,5,1,3,2,3,9,6.0,neutral or dissatisfied +45575,15585,Female,Loyal Customer,55,Business travel,Business,3301,1,3,3,3,5,2,2,1,1,1,1,2,1,2,68,52.0,neutral or dissatisfied +45576,34511,Female,Loyal Customer,22,Business travel,Eco,1521,2,5,3,5,2,1,2,2,2,4,4,3,3,2,0,14.0,neutral or dissatisfied +45577,106585,Male,Loyal Customer,17,Personal Travel,Eco,333,1,4,1,3,4,1,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +45578,1726,Female,Loyal Customer,63,Business travel,Eco,364,1,5,5,5,3,3,3,1,1,1,1,4,1,3,101,108.0,neutral or dissatisfied +45579,62148,Female,Loyal Customer,54,Business travel,Eco,2454,1,3,3,3,3,3,4,1,1,1,1,1,1,2,61,36.0,neutral or dissatisfied +45580,91524,Female,disloyal Customer,29,Business travel,Business,680,1,1,1,3,3,1,5,3,5,2,4,3,5,3,55,50.0,neutral or dissatisfied +45581,79331,Male,Loyal Customer,50,Business travel,Business,2838,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +45582,84301,Female,Loyal Customer,50,Business travel,Business,235,0,0,0,2,3,4,5,1,1,1,1,3,1,4,1,9.0,satisfied +45583,79754,Female,Loyal Customer,52,Business travel,Business,2633,2,2,2,2,4,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +45584,89721,Female,Loyal Customer,47,Personal Travel,Eco,1096,4,3,4,3,1,4,1,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +45585,72742,Male,Loyal Customer,28,Personal Travel,Eco Plus,918,4,5,4,4,4,4,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +45586,89486,Male,Loyal Customer,57,Business travel,Eco,1931,3,4,4,4,3,3,3,3,4,2,4,3,4,3,0,10.0,neutral or dissatisfied +45587,36233,Male,Loyal Customer,47,Personal Travel,Eco,280,1,4,1,1,1,1,1,1,5,4,1,3,1,1,0,0.0,neutral or dissatisfied +45588,64858,Male,Loyal Customer,57,Business travel,Business,354,2,1,1,1,4,3,3,2,2,2,2,2,2,2,11,6.0,neutral or dissatisfied +45589,64427,Male,Loyal Customer,35,Business travel,Business,1754,3,3,3,3,5,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +45590,97844,Male,Loyal Customer,49,Personal Travel,Eco,395,2,5,2,4,4,2,4,4,4,2,5,4,5,4,11,18.0,neutral or dissatisfied +45591,40028,Female,disloyal Customer,21,Business travel,Eco,125,4,0,4,1,5,4,5,5,5,5,4,3,1,5,0,0.0,satisfied +45592,99827,Male,Loyal Customer,46,Business travel,Business,3872,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +45593,1633,Male,Loyal Customer,68,Personal Travel,Eco,999,2,5,2,3,1,2,1,1,4,4,5,3,4,1,6,0.0,neutral or dissatisfied +45594,71136,Male,Loyal Customer,58,Business travel,Business,2328,4,4,4,4,3,5,5,4,4,4,4,4,4,5,9,1.0,satisfied +45595,38625,Male,Loyal Customer,38,Personal Travel,Business,2611,3,1,3,3,4,4,3,2,2,3,5,3,2,3,7,0.0,neutral or dissatisfied +45596,17039,Female,Loyal Customer,25,Personal Travel,Business,1134,3,4,2,3,2,2,2,2,5,2,4,5,5,2,77,57.0,neutral or dissatisfied +45597,102638,Male,disloyal Customer,23,Business travel,Eco,255,2,0,2,2,1,2,1,1,3,2,4,4,5,1,12,7.0,neutral or dissatisfied +45598,87752,Male,Loyal Customer,45,Business travel,Business,3180,5,5,5,5,2,4,4,4,4,4,5,5,4,5,22,11.0,satisfied +45599,73265,Male,Loyal Customer,28,Personal Travel,Eco Plus,675,4,5,4,4,4,4,4,4,5,2,4,5,4,4,5,1.0,neutral or dissatisfied +45600,71100,Male,Loyal Customer,63,Personal Travel,Eco Plus,802,2,2,2,3,4,2,4,4,2,3,2,4,3,4,12,0.0,neutral or dissatisfied +45601,75797,Male,Loyal Customer,16,Personal Travel,Eco,813,1,3,1,4,3,1,3,3,4,3,2,4,4,3,0,0.0,neutral or dissatisfied +45602,69179,Female,Loyal Customer,30,Personal Travel,Eco,187,1,2,1,4,2,1,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +45603,127019,Female,disloyal Customer,58,Business travel,Eco,304,1,2,1,2,1,1,1,1,4,3,2,1,3,1,0,0.0,neutral or dissatisfied +45604,39058,Female,Loyal Customer,60,Business travel,Business,3854,5,5,1,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +45605,106630,Male,Loyal Customer,61,Business travel,Business,1676,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +45606,80353,Male,Loyal Customer,40,Business travel,Business,3748,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +45607,32349,Female,Loyal Customer,35,Business travel,Eco,121,4,1,1,1,4,4,4,4,5,1,3,3,5,4,0,0.0,satisfied +45608,53449,Male,Loyal Customer,49,Business travel,Business,2419,4,4,5,4,5,5,5,4,5,5,5,5,4,5,0,0.0,satisfied +45609,118592,Male,Loyal Customer,47,Business travel,Business,2678,2,2,1,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +45610,128983,Male,Loyal Customer,34,Personal Travel,Eco,414,1,1,1,3,4,1,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +45611,52175,Female,disloyal Customer,25,Business travel,Eco,598,1,4,1,5,2,1,2,2,5,3,3,2,2,2,0,0.0,neutral or dissatisfied +45612,82069,Male,disloyal Customer,29,Business travel,Business,1276,0,1,1,3,3,1,3,3,5,2,5,3,5,3,3,4.0,satisfied +45613,114,Female,Loyal Customer,51,Business travel,Business,562,2,3,3,3,1,4,4,2,2,3,2,4,2,3,0,15.0,neutral or dissatisfied +45614,14523,Male,Loyal Customer,34,Business travel,Business,362,2,2,3,2,5,3,4,4,4,4,4,3,4,1,19,19.0,satisfied +45615,89302,Male,Loyal Customer,66,Personal Travel,Eco,453,4,1,4,4,3,4,3,3,3,3,3,3,3,3,0,2.0,neutral or dissatisfied +45616,110360,Female,disloyal Customer,22,Business travel,Eco,925,2,2,2,4,2,2,2,2,2,3,3,3,3,2,0,12.0,neutral or dissatisfied +45617,106057,Female,Loyal Customer,51,Business travel,Business,503,4,4,5,4,2,5,5,3,3,3,3,5,3,3,73,65.0,satisfied +45618,122078,Female,Loyal Customer,14,Personal Travel,Eco,130,2,0,2,3,2,2,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +45619,103492,Female,Loyal Customer,50,Personal Travel,Eco,382,3,4,3,1,3,5,4,1,1,3,1,4,1,3,34,14.0,neutral or dissatisfied +45620,109082,Male,Loyal Customer,42,Personal Travel,Eco,1041,2,5,2,3,4,2,2,4,5,2,4,5,4,4,14,4.0,neutral or dissatisfied +45621,8344,Male,Loyal Customer,36,Personal Travel,Eco Plus,661,3,2,3,3,5,3,4,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +45622,77346,Female,Loyal Customer,48,Business travel,Business,3794,2,2,2,2,4,5,5,4,4,4,4,5,4,3,1,11.0,satisfied +45623,106677,Male,Loyal Customer,47,Business travel,Business,2030,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,10.0,satisfied +45624,46559,Male,disloyal Customer,38,Business travel,Eco,141,2,0,2,2,5,2,4,5,4,3,2,5,2,5,0,0.0,neutral or dissatisfied +45625,59436,Male,Loyal Customer,61,Personal Travel,Eco Plus,746,4,4,3,4,3,4,4,4,3,5,5,4,3,4,140,135.0,neutral or dissatisfied +45626,99857,Female,Loyal Customer,7,Personal Travel,Eco,534,3,5,3,4,2,3,2,2,3,3,4,4,4,2,19,12.0,neutral or dissatisfied +45627,81052,Female,Loyal Customer,42,Personal Travel,Eco,1399,3,5,3,1,2,3,5,3,3,3,5,3,3,4,0,23.0,neutral or dissatisfied +45628,36829,Male,Loyal Customer,57,Business travel,Eco,369,4,4,3,4,4,4,4,4,3,2,2,3,3,4,0,0.0,satisfied +45629,123626,Male,Loyal Customer,33,Business travel,Business,214,4,4,4,4,5,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +45630,122500,Female,disloyal Customer,30,Business travel,Business,930,1,1,1,4,1,1,1,1,3,4,4,5,5,1,22,20.0,neutral or dissatisfied +45631,81054,Female,Loyal Customer,14,Personal Travel,Eco,1399,1,3,1,4,4,1,4,4,3,1,3,1,5,4,8,12.0,neutral or dissatisfied +45632,37144,Female,disloyal Customer,64,Business travel,Eco,1046,4,4,4,4,4,2,2,1,2,4,4,2,1,2,132,131.0,neutral or dissatisfied +45633,100297,Male,disloyal Customer,29,Business travel,Eco,971,3,3,3,3,1,3,1,1,4,2,3,4,4,1,4,0.0,neutral or dissatisfied +45634,47895,Female,Loyal Customer,41,Business travel,Business,329,0,0,0,3,3,2,5,5,5,4,4,2,5,5,0,0.0,satisfied +45635,13279,Female,Loyal Customer,50,Personal Travel,Eco,468,3,5,3,3,4,5,4,2,2,3,2,4,2,5,0,18.0,neutral or dissatisfied +45636,112792,Female,Loyal Customer,49,Business travel,Business,3248,4,4,5,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +45637,88751,Male,Loyal Customer,10,Personal Travel,Eco,271,1,2,1,2,4,1,5,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +45638,122690,Male,disloyal Customer,43,Business travel,Business,361,3,3,3,3,3,3,1,3,2,3,3,5,3,3,0,0.0,neutral or dissatisfied +45639,125403,Male,Loyal Customer,34,Personal Travel,Eco,1440,3,5,3,3,4,3,4,4,5,5,3,5,4,4,10,22.0,neutral or dissatisfied +45640,48565,Male,Loyal Customer,59,Personal Travel,Eco,776,1,5,0,3,3,0,3,3,5,2,5,5,4,3,1,25.0,neutral or dissatisfied +45641,110604,Female,disloyal Customer,22,Business travel,Business,551,5,2,5,3,4,5,4,4,4,2,5,5,5,4,0,0.0,satisfied +45642,41099,Female,disloyal Customer,38,Business travel,Eco,667,4,5,4,4,5,4,5,5,5,5,2,1,4,5,2,3.0,neutral or dissatisfied +45643,22928,Female,disloyal Customer,26,Business travel,Eco,528,1,3,1,3,3,1,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +45644,19159,Female,disloyal Customer,44,Business travel,Eco,304,3,2,3,4,1,3,1,1,2,2,4,2,3,1,0,5.0,neutral or dissatisfied +45645,66953,Male,Loyal Customer,39,Business travel,Business,1121,5,5,5,5,4,4,4,3,3,3,3,3,3,4,2,6.0,satisfied +45646,8772,Male,Loyal Customer,45,Business travel,Business,552,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +45647,20290,Female,Loyal Customer,12,Personal Travel,Eco,235,3,5,3,2,2,3,2,2,4,4,4,5,5,2,1,0.0,neutral or dissatisfied +45648,97157,Female,Loyal Customer,56,Business travel,Business,729,1,1,1,1,1,4,2,4,4,4,4,5,4,1,1,0.0,satisfied +45649,8053,Male,disloyal Customer,25,Business travel,Business,125,1,4,1,4,3,1,3,3,4,4,5,3,5,3,6,8.0,neutral or dissatisfied +45650,74622,Male,Loyal Customer,62,Business travel,Business,835,3,3,3,3,5,4,2,5,5,5,5,3,5,4,0,0.0,satisfied +45651,13253,Male,Loyal Customer,40,Business travel,Business,2164,2,3,3,3,2,2,2,4,3,4,3,2,3,2,328,337.0,neutral or dissatisfied +45652,79893,Female,Loyal Customer,9,Business travel,Business,2240,2,2,2,2,5,5,5,5,4,5,5,3,4,5,0,0.0,satisfied +45653,68975,Male,Loyal Customer,53,Personal Travel,Eco,700,4,5,4,1,4,4,2,4,4,4,4,1,5,4,0,0.0,neutral or dissatisfied +45654,62315,Female,disloyal Customer,20,Business travel,Eco,414,2,1,2,4,2,2,5,2,3,4,3,2,4,2,1,1.0,neutral or dissatisfied +45655,4782,Male,disloyal Customer,34,Business travel,Eco,438,2,2,2,3,2,2,2,2,3,2,3,1,4,2,0,36.0,neutral or dissatisfied +45656,122716,Female,Loyal Customer,37,Business travel,Business,651,2,2,2,2,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +45657,25174,Male,disloyal Customer,24,Business travel,Business,577,4,0,3,4,4,3,4,4,3,5,4,3,5,4,11,0.0,satisfied +45658,23166,Female,Loyal Customer,49,Personal Travel,Eco,300,2,5,5,3,1,3,1,5,5,5,5,4,5,4,8,0.0,neutral or dissatisfied +45659,71952,Male,Loyal Customer,24,Business travel,Business,1440,4,4,4,4,5,5,5,5,3,4,5,3,5,5,17,23.0,satisfied +45660,52983,Male,Loyal Customer,11,Personal Travel,Business,1208,2,1,2,2,4,2,4,4,2,4,1,4,2,4,17,22.0,neutral or dissatisfied +45661,47214,Female,Loyal Customer,24,Personal Travel,Eco,954,3,4,3,1,5,3,2,5,5,3,4,5,4,5,0,19.0,neutral or dissatisfied +45662,129474,Male,Loyal Customer,43,Business travel,Business,2704,1,1,1,1,3,4,5,4,4,4,4,3,4,4,10,0.0,satisfied +45663,115747,Female,Loyal Customer,38,Business travel,Business,1638,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,1.0,satisfied +45664,126179,Male,Loyal Customer,70,Business travel,Business,3080,1,3,3,3,3,4,3,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +45665,67581,Female,Loyal Customer,49,Business travel,Business,1431,4,1,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +45666,30805,Male,Loyal Customer,37,Business travel,Business,1199,3,3,2,3,2,4,5,3,3,2,3,4,3,1,0,14.0,satisfied +45667,67760,Female,Loyal Customer,53,Business travel,Business,1438,3,5,5,5,5,3,3,3,3,3,3,3,3,1,0,30.0,neutral or dissatisfied +45668,115554,Male,Loyal Customer,74,Business travel,Business,308,0,0,0,2,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +45669,98177,Female,Loyal Customer,53,Business travel,Business,1518,2,2,2,2,2,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +45670,104999,Female,Loyal Customer,42,Personal Travel,Eco,314,4,4,4,4,5,4,5,3,3,4,3,4,3,4,66,45.0,neutral or dissatisfied +45671,98139,Male,disloyal Customer,39,Business travel,Business,472,5,5,5,2,2,5,2,2,4,4,4,3,5,2,1,0.0,satisfied +45672,128320,Female,Loyal Customer,45,Business travel,Business,3743,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +45673,69555,Male,Loyal Customer,39,Business travel,Business,2446,2,2,2,2,4,4,4,5,3,5,4,4,3,4,0,3.0,satisfied +45674,12095,Female,disloyal Customer,50,Business travel,Eco,1034,3,3,3,1,5,3,5,5,1,3,5,2,4,5,0,0.0,neutral or dissatisfied +45675,93407,Male,Loyal Customer,50,Business travel,Business,671,1,4,5,5,2,4,3,1,1,2,1,4,1,4,60,73.0,neutral or dissatisfied +45676,114499,Male,Loyal Customer,36,Business travel,Business,1600,3,4,4,4,2,4,4,3,3,3,3,2,3,4,18,11.0,neutral or dissatisfied +45677,91194,Female,Loyal Customer,11,Personal Travel,Eco,406,3,4,3,4,2,3,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +45678,116606,Female,Loyal Customer,54,Business travel,Business,1518,3,3,3,3,3,4,4,5,5,5,5,3,5,3,6,3.0,satisfied +45679,57807,Male,disloyal Customer,39,Business travel,Eco,835,4,4,4,3,1,4,2,1,1,1,3,3,3,1,0,4.0,satisfied +45680,21576,Female,Loyal Customer,53,Personal Travel,Eco Plus,331,3,5,3,1,5,5,5,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +45681,10483,Female,Loyal Customer,54,Business travel,Business,3513,3,3,3,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +45682,23184,Female,Loyal Customer,64,Personal Travel,Eco,300,1,4,1,1,1,2,3,3,3,1,3,2,3,2,0,21.0,neutral or dissatisfied +45683,111428,Male,Loyal Customer,50,Personal Travel,Eco,896,3,2,3,4,1,3,1,1,3,4,3,2,4,1,13,3.0,neutral or dissatisfied +45684,93478,Female,Loyal Customer,46,Personal Travel,Eco Plus,671,3,3,2,4,5,4,4,3,3,2,3,4,3,3,18,11.0,neutral or dissatisfied +45685,11097,Male,Loyal Customer,11,Personal Travel,Eco,429,2,5,2,1,2,2,2,2,1,1,3,4,3,2,7,7.0,neutral or dissatisfied +45686,104387,Female,Loyal Customer,55,Business travel,Eco Plus,228,3,3,2,3,5,3,4,4,4,3,4,3,4,2,61,72.0,neutral or dissatisfied +45687,1677,Female,Loyal Customer,53,Business travel,Business,2875,1,1,1,1,2,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +45688,57608,Male,disloyal Customer,32,Business travel,Business,200,4,4,4,3,3,4,3,3,4,2,5,4,4,3,6,0.0,neutral or dissatisfied +45689,87845,Male,Loyal Customer,51,Personal Travel,Eco,214,3,2,3,4,4,3,4,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +45690,68738,Female,Loyal Customer,51,Business travel,Business,3855,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +45691,9840,Female,Loyal Customer,39,Business travel,Business,717,5,5,5,5,5,5,5,4,4,4,4,4,4,5,64,47.0,satisfied +45692,114615,Female,Loyal Customer,43,Business travel,Business,2959,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +45693,10273,Female,Loyal Customer,50,Personal Travel,Business,201,4,4,4,4,2,4,3,1,1,4,1,4,1,4,0,0.0,satisfied +45694,2950,Female,disloyal Customer,35,Business travel,Eco,737,3,4,4,3,5,4,5,5,3,3,3,1,4,5,0,0.0,neutral or dissatisfied +45695,35035,Female,Loyal Customer,37,Personal Travel,Eco,718,3,1,3,4,5,3,5,5,1,1,4,2,4,5,0,0.0,neutral or dissatisfied +45696,113571,Male,Loyal Customer,29,Business travel,Business,258,2,1,1,1,2,2,2,2,4,3,3,2,4,2,115,130.0,neutral or dissatisfied +45697,83320,Male,Loyal Customer,20,Personal Travel,Eco,1671,1,2,1,3,4,1,2,4,4,1,4,3,3,4,0,0.0,neutral or dissatisfied +45698,61857,Male,Loyal Customer,54,Personal Travel,Eco Plus,1635,2,4,1,4,2,1,2,2,4,4,5,3,4,2,20,4.0,neutral or dissatisfied +45699,104274,Male,disloyal Customer,22,Business travel,Eco,718,3,3,3,2,3,3,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +45700,44291,Female,Loyal Customer,64,Personal Travel,Eco,1015,2,2,2,3,2,5,5,2,3,3,4,5,1,5,210,216.0,neutral or dissatisfied +45701,73203,Male,Loyal Customer,53,Personal Travel,Eco,1258,4,5,4,3,5,4,4,5,4,3,4,3,5,5,33,54.0,satisfied +45702,113187,Male,Loyal Customer,42,Business travel,Business,3385,1,1,3,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +45703,7377,Female,Loyal Customer,54,Business travel,Business,888,4,1,1,1,2,3,4,4,4,4,4,4,4,3,35,24.0,neutral or dissatisfied +45704,85126,Female,Loyal Customer,48,Business travel,Business,813,5,5,5,5,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +45705,23496,Female,Loyal Customer,37,Personal Travel,Business,303,3,4,3,4,3,4,4,2,2,3,2,3,2,4,43,119.0,neutral or dissatisfied +45706,119225,Female,Loyal Customer,28,Personal Travel,Eco,331,1,3,1,2,5,1,1,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +45707,63051,Male,Loyal Customer,42,Personal Travel,Eco,862,3,1,3,4,3,3,3,3,3,4,3,3,4,3,85,73.0,neutral or dissatisfied +45708,107362,Female,Loyal Customer,11,Personal Travel,Eco,632,2,5,2,3,1,2,2,1,4,2,5,5,5,1,16,1.0,neutral or dissatisfied +45709,96514,Male,Loyal Customer,47,Personal Travel,Eco,436,2,4,2,1,4,2,4,4,5,2,5,4,4,4,8,4.0,neutral or dissatisfied +45710,40229,Male,disloyal Customer,36,Business travel,Eco,402,4,0,4,2,1,4,1,1,4,5,2,4,5,1,0,0.0,neutral or dissatisfied +45711,73077,Male,Loyal Customer,37,Business travel,Eco,1085,3,2,2,2,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +45712,106676,Female,disloyal Customer,23,Business travel,Eco,451,4,0,4,2,4,4,1,4,3,4,5,3,5,4,5,5.0,neutral or dissatisfied +45713,100783,Female,Loyal Customer,37,Personal Travel,Eco,1411,1,5,1,3,1,1,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +45714,970,Male,Loyal Customer,57,Business travel,Business,89,2,2,2,2,2,4,4,5,5,5,4,3,5,4,5,4.0,satisfied +45715,3123,Female,Loyal Customer,69,Personal Travel,Eco,1013,3,3,3,1,2,5,2,5,5,3,5,1,5,5,0,14.0,neutral or dissatisfied +45716,102802,Male,Loyal Customer,44,Business travel,Business,342,3,3,3,3,3,5,5,5,5,5,5,3,5,4,11,0.0,satisfied +45717,27736,Male,disloyal Customer,24,Business travel,Eco,909,5,5,5,3,1,5,1,1,1,5,1,3,5,1,0,0.0,satisfied +45718,98189,Male,Loyal Customer,45,Business travel,Business,1924,2,2,2,2,3,4,4,5,5,5,5,3,5,5,6,0.0,satisfied +45719,98425,Male,disloyal Customer,57,Business travel,Eco,676,4,4,4,2,4,4,4,4,3,1,2,1,2,4,33,21.0,neutral or dissatisfied +45720,51394,Male,Loyal Customer,66,Personal Travel,Eco Plus,56,2,1,0,4,5,0,5,5,4,5,3,3,4,5,0,13.0,neutral or dissatisfied +45721,43132,Female,Loyal Customer,48,Business travel,Eco Plus,236,5,2,2,2,4,2,1,5,5,5,5,5,5,1,120,109.0,satisfied +45722,42044,Female,Loyal Customer,59,Business travel,Business,2250,4,4,4,4,4,5,3,5,5,5,3,2,5,4,0,0.0,satisfied +45723,76621,Male,Loyal Customer,42,Business travel,Business,2173,5,5,5,5,2,4,1,4,4,4,4,4,4,3,0,0.0,satisfied +45724,52669,Male,Loyal Customer,24,Personal Travel,Eco,160,2,4,2,2,1,2,2,1,3,2,5,5,5,1,13,10.0,neutral or dissatisfied +45725,102212,Male,Loyal Customer,47,Business travel,Business,236,2,2,2,2,3,4,4,5,5,5,5,4,5,3,3,0.0,satisfied +45726,68916,Female,Loyal Customer,64,Personal Travel,Eco,936,4,2,4,3,1,3,3,5,5,4,5,2,5,4,3,8.0,neutral or dissatisfied +45727,54248,Female,disloyal Customer,38,Business travel,Eco,1222,2,2,2,1,5,2,5,5,1,3,3,1,3,5,0,0.0,neutral or dissatisfied +45728,38586,Male,Loyal Customer,33,Personal Travel,Eco Plus,2576,3,5,3,3,3,3,3,3,5,1,4,4,4,3,0,0.0,neutral or dissatisfied +45729,57871,Female,Loyal Customer,60,Business travel,Business,305,5,5,5,5,5,4,4,5,5,5,5,3,5,5,22,23.0,satisfied +45730,23850,Female,Loyal Customer,42,Business travel,Business,2024,5,5,5,5,1,2,3,5,5,5,5,5,5,5,0,0.0,satisfied +45731,52637,Female,Loyal Customer,56,Personal Travel,Eco,160,1,4,1,3,2,4,4,3,3,1,2,4,3,3,11,3.0,neutral or dissatisfied +45732,111518,Female,Loyal Customer,20,Personal Travel,Eco,391,3,5,3,4,1,3,1,1,5,4,5,5,5,1,13,15.0,neutral or dissatisfied +45733,20317,Female,Loyal Customer,48,Business travel,Eco,837,2,2,2,2,1,3,3,2,2,2,2,4,2,3,0,8.0,neutral or dissatisfied +45734,71482,Male,Loyal Customer,44,Business travel,Business,1182,5,5,5,5,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +45735,56376,Female,Loyal Customer,39,Business travel,Business,3753,3,3,4,3,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +45736,45158,Female,Loyal Customer,55,Business travel,Eco,174,5,2,2,2,1,4,3,5,5,5,5,2,5,2,12,20.0,satisfied +45737,50514,Female,Loyal Customer,12,Personal Travel,Eco,158,0,5,0,3,2,0,2,2,3,3,4,3,5,2,0,0.0,satisfied +45738,41377,Female,Loyal Customer,28,Business travel,Business,1942,2,2,2,2,5,5,5,5,3,5,1,5,4,5,148,163.0,satisfied +45739,40062,Male,disloyal Customer,22,Business travel,Eco,866,3,3,3,3,5,3,5,5,4,3,3,2,3,5,5,22.0,neutral or dissatisfied +45740,122687,Female,Loyal Customer,39,Business travel,Business,2598,3,1,3,1,2,3,4,3,3,3,3,3,3,1,0,6.0,neutral or dissatisfied +45741,10041,Female,Loyal Customer,52,Personal Travel,Business,326,5,5,5,4,3,4,4,4,4,5,4,1,4,1,0,0.0,satisfied +45742,92702,Male,Loyal Customer,48,Business travel,Eco Plus,507,2,2,2,2,2,2,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +45743,34012,Female,Loyal Customer,20,Personal Travel,Eco,1617,0,1,0,3,2,0,2,2,2,3,3,4,3,2,0,0.0,satisfied +45744,58031,Male,Loyal Customer,36,Personal Travel,Eco Plus,1721,1,4,1,2,5,1,5,5,3,4,5,4,4,5,1,1.0,neutral or dissatisfied +45745,114790,Male,disloyal Customer,44,Business travel,Business,417,3,3,3,4,1,3,1,1,4,4,5,3,5,1,35,48.0,neutral or dissatisfied +45746,83693,Male,disloyal Customer,55,Personal Travel,Eco,577,0,5,0,3,3,5,3,3,3,4,5,3,4,3,0,0.0,satisfied +45747,50643,Female,Loyal Customer,54,Personal Travel,Eco,363,3,1,3,4,5,3,3,5,5,3,1,4,5,4,0,0.0,neutral or dissatisfied +45748,20499,Male,Loyal Customer,18,Personal Travel,Eco,130,2,1,2,2,2,2,2,1,5,3,2,2,3,2,84,183.0,neutral or dissatisfied +45749,105234,Female,Loyal Customer,55,Business travel,Business,2571,3,1,1,1,5,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +45750,78630,Female,Loyal Customer,60,Personal Travel,Eco,1426,3,2,3,3,3,4,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +45751,12464,Female,Loyal Customer,35,Personal Travel,Eco,201,2,2,2,3,1,2,1,1,2,5,3,1,4,1,14,6.0,neutral or dissatisfied +45752,52166,Female,Loyal Customer,32,Business travel,Business,3465,2,2,2,2,4,4,4,4,2,2,4,5,5,4,0,2.0,satisfied +45753,9523,Female,Loyal Customer,38,Business travel,Business,3995,3,3,3,3,3,3,4,3,3,3,3,4,3,2,31,19.0,neutral or dissatisfied +45754,124954,Female,Loyal Customer,12,Personal Travel,Business,184,0,4,0,4,4,0,4,4,1,1,3,1,1,4,0,0.0,satisfied +45755,29281,Female,Loyal Customer,48,Business travel,Eco,550,2,3,3,3,4,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +45756,4050,Female,Loyal Customer,20,Personal Travel,Eco,419,2,1,2,3,5,2,5,5,2,3,3,3,2,5,0,0.0,neutral or dissatisfied +45757,41014,Male,Loyal Customer,29,Personal Travel,Business,1195,0,4,1,2,2,1,1,2,4,2,3,3,5,2,15,3.0,satisfied +45758,96844,Male,Loyal Customer,9,Business travel,Eco,816,3,5,4,5,3,3,4,3,4,1,4,2,4,3,54,52.0,neutral or dissatisfied +45759,36895,Male,Loyal Customer,20,Business travel,Business,1368,3,2,2,2,3,3,3,3,2,1,3,2,3,3,95,74.0,neutral or dissatisfied +45760,80929,Male,Loyal Customer,37,Business travel,Eco,341,4,2,2,2,4,4,4,4,3,3,5,3,1,4,0,0.0,satisfied +45761,25408,Male,Loyal Customer,30,Business travel,Business,1504,1,3,3,3,1,1,1,1,2,5,3,2,4,1,1,0.0,neutral or dissatisfied +45762,98317,Female,Loyal Customer,47,Business travel,Business,1547,1,1,1,1,4,4,5,4,4,4,4,4,4,4,21,20.0,satisfied +45763,99657,Male,Loyal Customer,48,Business travel,Business,3567,5,5,5,5,2,1,4,4,4,4,4,4,4,1,23,3.0,satisfied +45764,61620,Male,Loyal Customer,43,Business travel,Business,1504,3,3,5,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +45765,66254,Female,Loyal Customer,52,Personal Travel,Eco,460,4,4,4,3,1,3,3,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +45766,50402,Female,Loyal Customer,42,Business travel,Business,447,1,2,2,2,2,3,3,1,1,1,1,3,1,3,18,8.0,neutral or dissatisfied +45767,54597,Male,Loyal Customer,36,Business travel,Business,956,2,5,5,5,4,3,4,2,2,2,2,1,2,1,103,89.0,neutral or dissatisfied +45768,97722,Female,Loyal Customer,25,Personal Travel,Business,587,3,5,3,1,4,3,4,4,4,5,4,3,5,4,46,35.0,neutral or dissatisfied +45769,25328,Male,Loyal Customer,23,Business travel,Business,2597,4,4,4,4,5,4,5,5,5,4,5,2,5,5,0,0.0,satisfied +45770,61733,Male,Loyal Customer,58,Business travel,Eco,135,2,1,1,1,3,2,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +45771,62668,Male,Loyal Customer,45,Business travel,Business,1846,5,5,5,5,3,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +45772,71108,Female,Loyal Customer,44,Business travel,Business,2072,1,1,1,1,4,3,4,4,4,4,4,5,4,3,3,0.0,satisfied +45773,84506,Male,Loyal Customer,49,Business travel,Business,2556,3,3,1,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +45774,109048,Female,Loyal Customer,41,Business travel,Business,2713,3,5,5,5,1,3,3,3,3,3,3,1,3,2,56,44.0,neutral or dissatisfied +45775,106251,Male,Loyal Customer,35,Business travel,Business,3899,2,2,2,2,5,5,4,3,3,4,3,4,3,3,55,44.0,satisfied +45776,14575,Male,Loyal Customer,48,Business travel,Business,986,3,2,2,2,2,4,4,3,3,3,3,2,3,1,3,18.0,neutral or dissatisfied +45777,53546,Male,Loyal Customer,45,Business travel,Eco Plus,2419,5,3,5,5,5,5,5,3,3,4,5,5,2,5,23,16.0,satisfied +45778,61247,Female,disloyal Customer,27,Business travel,Eco,453,3,0,3,1,4,3,4,4,3,4,3,4,5,4,7,4.0,neutral or dissatisfied +45779,30485,Male,Loyal Customer,50,Personal Travel,Business,627,1,3,1,4,4,4,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +45780,81733,Female,Loyal Customer,41,Business travel,Business,1416,5,5,5,5,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +45781,55231,Male,Loyal Customer,46,Business travel,Eco,1009,3,5,5,5,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +45782,94044,Male,disloyal Customer,27,Business travel,Business,189,5,5,5,5,2,5,2,2,4,2,5,3,5,2,27,28.0,satisfied +45783,4094,Female,Loyal Customer,30,Business travel,Business,1531,2,2,2,2,5,5,5,5,4,3,5,3,5,5,33,25.0,satisfied +45784,41677,Female,Loyal Customer,40,Personal Travel,Eco,936,2,4,2,2,2,2,2,2,5,5,4,3,4,2,39,42.0,neutral or dissatisfied +45785,78539,Male,Loyal Customer,31,Personal Travel,Eco,666,1,0,2,3,5,2,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +45786,75640,Male,Loyal Customer,47,Personal Travel,Business,304,3,5,3,1,2,5,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +45787,56958,Male,disloyal Customer,16,Business travel,Eco,709,3,3,3,3,3,3,3,2,5,3,3,3,3,3,10,6.0,neutral or dissatisfied +45788,11521,Male,Loyal Customer,35,Personal Travel,Eco Plus,312,3,4,3,3,1,3,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +45789,88947,Female,Loyal Customer,33,Business travel,Business,1199,1,1,5,1,5,4,5,4,4,4,4,5,4,4,2,25.0,satisfied +45790,55230,Female,Loyal Customer,47,Business travel,Business,3799,5,5,5,5,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +45791,38210,Female,disloyal Customer,20,Business travel,Eco,1237,4,4,4,1,2,4,2,2,2,4,2,2,4,2,45,33.0,satisfied +45792,115423,Female,Loyal Customer,23,Business travel,Business,3571,4,3,5,3,4,4,4,4,3,4,3,4,4,4,0,0.0,neutral or dissatisfied +45793,80539,Male,Loyal Customer,53,Business travel,Business,1747,3,3,3,3,4,4,4,3,3,2,3,5,3,4,0,0.0,satisfied +45794,127751,Female,Loyal Customer,62,Personal Travel,Eco,601,2,5,2,4,2,4,2,4,4,2,4,1,4,1,17,6.0,neutral or dissatisfied +45795,94928,Female,disloyal Customer,36,Business travel,Eco,248,3,0,3,2,1,3,5,1,5,3,5,2,4,1,6,0.0,neutral or dissatisfied +45796,91182,Female,Loyal Customer,15,Personal Travel,Eco,271,3,0,3,4,5,3,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +45797,103734,Female,Loyal Customer,70,Personal Travel,Eco,466,2,5,2,4,3,5,5,5,5,2,3,3,5,3,23,9.0,neutral or dissatisfied +45798,115259,Male,disloyal Customer,20,Business travel,Eco,337,3,0,3,3,2,3,2,2,5,5,5,5,5,2,25,18.0,neutral or dissatisfied +45799,37202,Male,Loyal Customer,22,Personal Travel,Eco Plus,1189,3,4,4,4,1,4,1,1,5,2,5,5,5,1,39,41.0,neutral or dissatisfied +45800,3690,Male,Loyal Customer,22,Business travel,Business,3010,1,1,1,1,4,4,4,4,5,3,5,4,5,4,0,3.0,satisfied +45801,76660,Female,Loyal Customer,7,Personal Travel,Eco,547,3,2,3,4,4,3,4,4,3,5,3,2,4,4,28,28.0,neutral or dissatisfied +45802,37840,Male,Loyal Customer,40,Business travel,Business,3025,4,4,4,4,2,2,1,4,4,4,4,3,4,2,0,0.0,satisfied +45803,70329,Female,Loyal Customer,32,Business travel,Business,986,3,3,3,3,2,2,2,2,3,3,5,5,4,2,0,0.0,satisfied +45804,16915,Male,Loyal Customer,40,Business travel,Eco Plus,746,1,0,0,4,3,0,3,3,3,5,3,4,3,3,13,12.0,neutral or dissatisfied +45805,15545,Female,Loyal Customer,58,Business travel,Business,1973,1,1,5,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +45806,82662,Female,Loyal Customer,64,Personal Travel,Eco,120,3,5,3,2,1,1,4,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +45807,70861,Female,Loyal Customer,48,Business travel,Business,761,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +45808,23414,Male,Loyal Customer,25,Business travel,Business,541,2,5,5,5,2,2,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +45809,112510,Female,Loyal Customer,9,Personal Travel,Eco,948,1,1,2,3,1,2,1,1,2,1,4,3,3,1,1,0.0,neutral or dissatisfied +45810,12154,Female,Loyal Customer,36,Business travel,Business,1214,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +45811,86738,Female,Loyal Customer,32,Personal Travel,Business,821,4,4,4,4,5,4,5,5,2,5,4,2,3,5,0,0.0,satisfied +45812,5777,Female,Loyal Customer,48,Business travel,Business,273,1,1,1,1,5,4,5,5,5,5,5,5,5,4,0,52.0,satisfied +45813,64818,Male,Loyal Customer,30,Business travel,Eco,247,1,3,3,3,1,1,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +45814,73095,Male,Loyal Customer,9,Personal Travel,Eco Plus,1085,4,4,4,5,5,4,1,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +45815,99437,Male,Loyal Customer,47,Business travel,Business,1844,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +45816,107646,Female,Loyal Customer,44,Business travel,Business,405,1,3,3,3,1,2,1,1,1,1,1,2,1,4,3,1.0,neutral or dissatisfied +45817,20200,Female,Loyal Customer,9,Personal Travel,Eco Plus,349,4,5,3,5,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +45818,118629,Male,Loyal Customer,56,Business travel,Business,2946,4,1,1,1,2,1,2,4,4,4,4,1,4,1,76,66.0,neutral or dissatisfied +45819,3409,Female,Loyal Customer,23,Personal Travel,Eco,315,2,4,2,3,5,2,5,5,1,5,3,4,1,5,26,26.0,neutral or dissatisfied +45820,109642,Male,Loyal Customer,40,Business travel,Business,829,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +45821,13431,Female,Loyal Customer,40,Business travel,Business,491,3,3,3,3,1,3,4,3,3,3,3,3,3,2,67,67.0,neutral or dissatisfied +45822,51143,Male,Loyal Customer,37,Personal Travel,Eco,86,4,4,4,3,3,4,3,3,4,5,5,4,5,3,9,2.0,neutral or dissatisfied +45823,15167,Female,Loyal Customer,24,Business travel,Eco,430,4,5,5,5,4,4,4,4,5,4,1,1,3,4,42,32.0,satisfied +45824,44387,Male,Loyal Customer,54,Business travel,Eco,342,3,3,3,3,4,3,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +45825,72778,Female,disloyal Customer,25,Business travel,Business,1045,3,0,3,1,1,3,1,1,4,3,4,3,5,1,34,40.0,neutral or dissatisfied +45826,61176,Male,Loyal Customer,47,Business travel,Business,3607,3,3,3,3,4,5,5,5,5,5,5,3,5,5,5,0.0,satisfied +45827,67729,Female,disloyal Customer,28,Business travel,Business,1235,5,5,5,2,2,0,2,2,3,4,4,3,5,2,0,0.0,satisfied +45828,90160,Male,Loyal Customer,24,Personal Travel,Eco,957,2,5,2,3,2,2,2,2,4,3,5,3,4,2,0,1.0,neutral or dissatisfied +45829,80064,Female,Loyal Customer,50,Personal Travel,Eco,950,1,4,1,4,2,4,4,1,1,1,1,1,1,2,70,52.0,neutral or dissatisfied +45830,15796,Female,disloyal Customer,36,Business travel,Eco,143,3,4,3,1,4,3,4,4,3,3,5,1,3,4,40,30.0,neutral or dissatisfied +45831,120965,Female,Loyal Customer,49,Business travel,Business,1537,5,5,5,5,2,4,4,4,4,4,4,5,4,4,7,23.0,satisfied +45832,77050,Male,Loyal Customer,19,Business travel,Eco,1156,3,4,4,4,3,3,2,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +45833,74944,Female,Loyal Customer,39,Business travel,Business,2475,5,5,5,5,5,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +45834,40543,Male,Loyal Customer,55,Business travel,Eco,216,5,2,2,2,4,5,4,4,3,1,1,2,1,4,0,0.0,satisfied +45835,110876,Male,disloyal Customer,42,Business travel,Business,406,5,5,5,4,4,5,4,4,3,2,4,3,5,4,0,0.0,satisfied +45836,32037,Male,disloyal Customer,40,Business travel,Eco,101,3,0,3,2,1,3,1,1,5,2,1,3,5,1,0,0.0,neutral or dissatisfied +45837,97958,Female,Loyal Customer,23,Business travel,Eco,616,0,5,0,2,4,0,3,4,4,2,2,3,3,4,0,0.0,satisfied +45838,100406,Male,Loyal Customer,44,Business travel,Business,2991,1,1,1,1,4,4,4,4,4,5,4,4,4,4,109,138.0,satisfied +45839,96425,Female,Loyal Customer,41,Business travel,Business,1831,3,3,2,3,4,4,4,3,3,3,3,3,3,3,8,5.0,neutral or dissatisfied +45840,22790,Male,Loyal Customer,50,Business travel,Business,3449,1,1,1,1,2,4,2,4,4,4,4,1,4,5,0,0.0,satisfied +45841,105971,Male,Loyal Customer,36,Business travel,Eco,829,2,5,4,5,2,2,2,5,4,5,3,2,3,2,9,22.0,satisfied +45842,53397,Male,Loyal Customer,46,Business travel,Business,2419,1,1,1,1,4,4,4,5,4,4,5,4,5,4,7,32.0,satisfied +45843,120712,Male,Loyal Customer,55,Personal Travel,Eco Plus,280,1,4,1,1,3,1,3,3,2,3,3,2,3,3,1,34.0,neutral or dissatisfied +45844,24991,Female,disloyal Customer,30,Business travel,Eco,692,3,3,3,3,1,3,1,1,2,3,3,4,2,1,0,0.0,neutral or dissatisfied +45845,25046,Female,Loyal Customer,47,Business travel,Business,3439,1,1,1,1,2,1,4,3,3,3,3,1,3,3,33,102.0,satisfied +45846,111500,Male,Loyal Customer,42,Business travel,Business,2895,4,4,4,4,4,4,4,4,4,5,4,4,4,5,32,25.0,satisfied +45847,119052,Male,Loyal Customer,38,Business travel,Business,779,1,1,1,1,4,2,4,5,5,4,5,4,5,3,0,0.0,satisfied +45848,31295,Male,Loyal Customer,57,Personal Travel,Eco Plus,533,3,5,3,4,1,3,1,1,5,4,5,4,4,1,0,5.0,neutral or dissatisfied +45849,5507,Female,Loyal Customer,46,Business travel,Business,948,1,1,1,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +45850,53640,Female,Loyal Customer,58,Personal Travel,Eco,1874,2,1,1,4,1,4,3,5,5,1,5,2,5,2,0,12.0,neutral or dissatisfied +45851,88440,Female,Loyal Customer,49,Business travel,Eco,404,3,4,4,4,3,3,3,3,3,3,3,1,3,4,19,18.0,neutral or dissatisfied +45852,121001,Male,Loyal Customer,22,Personal Travel,Eco,861,4,4,4,4,3,4,3,3,4,3,5,5,4,3,27,37.0,satisfied +45853,97945,Female,Loyal Customer,53,Business travel,Business,1886,2,4,4,4,5,3,4,2,2,2,2,4,2,1,54,43.0,neutral or dissatisfied +45854,89210,Male,Loyal Customer,10,Personal Travel,Eco,1892,3,1,3,3,1,3,5,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +45855,86097,Female,Loyal Customer,44,Business travel,Business,2791,4,4,5,4,3,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +45856,14689,Male,Loyal Customer,34,Business travel,Business,3848,1,1,1,1,1,5,4,5,5,5,5,2,5,4,0,92.0,satisfied +45857,1331,Female,Loyal Customer,37,Business travel,Business,1638,1,1,1,1,3,4,4,5,5,5,5,5,5,3,124,111.0,satisfied +45858,43694,Male,Loyal Customer,27,Business travel,Business,3229,0,0,0,2,2,2,2,2,3,2,3,3,3,2,0,0.0,satisfied +45859,84230,Female,Loyal Customer,55,Personal Travel,Eco,432,3,2,4,4,2,3,3,5,5,4,5,1,5,3,1,2.0,neutral or dissatisfied +45860,93488,Male,Loyal Customer,45,Business travel,Business,2616,3,3,3,3,5,5,5,4,4,4,4,4,4,3,6,6.0,satisfied +45861,104009,Female,Loyal Customer,33,Personal Travel,Eco,1334,5,5,5,2,5,5,3,5,3,3,5,5,4,5,5,4.0,satisfied +45862,27081,Female,Loyal Customer,34,Business travel,Business,2496,5,5,5,5,5,4,4,1,1,2,1,3,1,1,0,0.0,satisfied +45863,97290,Male,Loyal Customer,42,Business travel,Business,3011,4,4,4,4,4,4,5,5,5,4,5,4,5,4,24,16.0,satisfied +45864,101898,Female,Loyal Customer,50,Business travel,Business,2173,2,2,2,2,5,1,3,2,2,2,2,2,2,2,17,12.0,neutral or dissatisfied +45865,3563,Female,disloyal Customer,24,Business travel,Eco,227,4,4,4,1,1,4,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +45866,44208,Female,Loyal Customer,54,Personal Travel,Eco,157,2,3,2,2,5,1,3,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +45867,40332,Female,Loyal Customer,80,Business travel,Eco Plus,436,2,1,1,1,4,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +45868,26264,Male,Loyal Customer,43,Business travel,Business,3302,2,2,2,2,4,2,4,3,3,4,3,2,3,3,4,5.0,satisfied +45869,28628,Male,Loyal Customer,50,Business travel,Eco,2676,3,2,2,2,3,3,3,3,4,1,1,1,3,3,1,0.0,neutral or dissatisfied +45870,50960,Female,Loyal Customer,42,Personal Travel,Eco,110,2,5,2,3,5,3,5,3,3,2,3,5,3,2,0,,neutral or dissatisfied +45871,1494,Female,Loyal Customer,49,Business travel,Business,1766,4,1,2,2,1,4,4,4,4,3,4,4,4,3,51,61.0,neutral or dissatisfied +45872,119749,Male,Loyal Customer,12,Personal Travel,Eco,1303,3,5,3,1,3,3,3,3,5,4,3,3,5,3,0,0.0,neutral or dissatisfied +45873,55041,Male,disloyal Customer,21,Business travel,Eco,772,2,2,2,2,2,2,2,2,3,3,4,3,5,2,11,7.0,neutral or dissatisfied +45874,92819,Female,Loyal Customer,60,Business travel,Business,1587,2,5,5,5,1,3,4,2,2,2,2,3,2,3,7,0.0,neutral or dissatisfied +45875,62433,Male,Loyal Customer,38,Personal Travel,Eco,1911,3,5,3,3,3,3,2,3,3,2,4,3,5,3,24,21.0,neutral or dissatisfied +45876,24664,Male,Loyal Customer,14,Personal Travel,Eco,873,1,0,1,4,4,1,4,4,1,3,3,1,1,4,0,0.0,neutral or dissatisfied +45877,28447,Male,disloyal Customer,25,Business travel,Eco,1264,3,3,3,1,3,4,4,2,4,4,5,4,1,4,0,4.0,neutral or dissatisfied +45878,23410,Female,Loyal Customer,24,Business travel,Business,541,3,3,3,3,5,5,5,5,3,4,4,5,2,5,0,0.0,satisfied +45879,45393,Male,Loyal Customer,26,Personal Travel,Eco,344,4,3,4,2,3,4,3,3,2,5,2,1,1,3,0,0.0,satisfied +45880,115160,Female,disloyal Customer,25,Business travel,Business,447,2,0,2,2,1,2,1,1,5,2,4,3,4,1,27,16.0,neutral or dissatisfied +45881,58162,Male,Loyal Customer,30,Business travel,Business,802,2,2,2,2,3,4,3,3,5,4,4,5,4,3,0,1.0,satisfied +45882,44059,Female,Loyal Customer,59,Business travel,Business,501,1,1,4,1,3,2,4,5,5,5,5,4,5,1,91,107.0,satisfied +45883,128794,Female,Loyal Customer,52,Personal Travel,Business,2475,1,0,1,4,1,1,1,2,4,2,4,1,4,1,0,6.0,neutral or dissatisfied +45884,58100,Female,Loyal Customer,42,Personal Travel,Eco,589,4,5,3,4,3,4,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +45885,19122,Male,Loyal Customer,55,Business travel,Eco,323,2,1,1,1,1,2,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +45886,70741,Male,Loyal Customer,61,Personal Travel,Eco,675,2,5,2,1,1,2,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +45887,51153,Male,Loyal Customer,30,Personal Travel,Eco,308,3,4,3,1,5,3,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +45888,12375,Female,disloyal Customer,20,Business travel,Eco,190,1,0,2,3,4,2,2,4,4,4,3,3,3,4,0,8.0,neutral or dissatisfied +45889,39564,Female,Loyal Customer,26,Business travel,Eco,965,0,5,0,1,4,0,4,4,4,4,1,3,2,4,1,0.0,satisfied +45890,71593,Male,Loyal Customer,33,Business travel,Eco,1182,1,5,5,5,1,1,1,1,2,2,4,3,4,1,23,19.0,neutral or dissatisfied +45891,40348,Male,Loyal Customer,50,Business travel,Business,1428,3,5,3,3,1,5,5,5,5,5,5,2,5,2,0,0.0,satisfied +45892,15358,Male,disloyal Customer,33,Business travel,Eco,399,3,0,3,3,2,3,5,2,4,4,1,3,4,2,0,0.0,neutral or dissatisfied +45893,60280,Female,Loyal Customer,57,Personal Travel,Eco,2446,4,5,3,2,5,5,4,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +45894,103284,Male,Loyal Customer,27,Personal Travel,Eco,718,3,2,3,3,2,3,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +45895,86224,Female,Loyal Customer,25,Business travel,Business,3431,2,5,5,5,2,2,2,2,3,2,3,3,3,2,0,12.0,neutral or dissatisfied +45896,58993,Female,Loyal Customer,42,Business travel,Business,1744,3,3,3,3,3,3,5,5,5,5,5,3,5,3,0,0.0,satisfied +45897,33594,Female,Loyal Customer,25,Business travel,Eco,399,0,5,0,5,2,0,2,2,5,2,2,2,1,2,0,0.0,satisfied +45898,25475,Female,Loyal Customer,28,Business travel,Business,3129,3,3,3,3,3,3,3,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +45899,118950,Male,disloyal Customer,33,Business travel,Eco,682,1,1,1,3,1,3,4,3,3,3,3,4,4,4,206,243.0,neutral or dissatisfied +45900,106341,Female,Loyal Customer,48,Business travel,Business,1729,2,3,2,2,5,4,5,5,5,5,5,5,5,4,4,34.0,satisfied +45901,16082,Male,Loyal Customer,11,Business travel,Eco Plus,744,0,4,0,3,2,0,2,2,1,3,5,2,4,2,0,0.0,satisfied +45902,34418,Male,Loyal Customer,29,Personal Travel,Eco,612,4,4,4,3,1,4,1,1,1,3,4,1,2,1,0,0.0,neutral or dissatisfied +45903,4765,Female,Loyal Customer,38,Business travel,Business,3394,0,0,0,2,2,4,5,5,5,5,5,4,5,3,13,28.0,satisfied +45904,13228,Male,Loyal Customer,34,Business travel,Business,1562,1,3,1,1,5,4,2,5,5,5,5,3,5,3,0,0.0,satisfied +45905,82618,Female,Loyal Customer,13,Personal Travel,Eco,528,1,4,1,1,5,1,5,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +45906,74931,Female,Loyal Customer,49,Business travel,Business,2475,3,3,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +45907,107001,Female,Loyal Customer,14,Personal Travel,Eco,937,2,4,2,5,4,2,5,4,5,4,4,3,5,4,2,2.0,neutral or dissatisfied +45908,77655,Male,disloyal Customer,8,Business travel,Business,731,3,4,3,4,4,3,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +45909,19805,Male,Loyal Customer,44,Business travel,Business,528,3,3,3,3,4,2,1,4,4,4,4,3,4,1,0,0.0,satisfied +45910,21890,Male,disloyal Customer,22,Business travel,Eco,503,1,4,1,3,5,1,2,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +45911,4296,Male,Loyal Customer,11,Personal Travel,Eco,502,3,5,3,1,1,3,1,1,3,2,5,3,4,1,0,3.0,neutral or dissatisfied +45912,104410,Male,Loyal Customer,30,Business travel,Business,1024,3,3,3,3,5,5,5,5,3,2,4,3,4,5,2,3.0,satisfied +45913,110466,Female,Loyal Customer,63,Personal Travel,Eco,663,2,2,2,4,5,3,4,2,2,2,2,2,2,3,31,28.0,neutral or dissatisfied +45914,54717,Male,Loyal Customer,8,Personal Travel,Eco,787,4,3,4,4,2,4,2,2,4,4,1,3,1,2,0,0.0,satisfied +45915,32789,Male,Loyal Customer,40,Business travel,Eco,201,4,4,4,4,4,4,4,4,3,3,2,1,2,4,0,0.0,satisfied +45916,22870,Male,Loyal Customer,14,Personal Travel,Eco,147,1,5,1,4,4,1,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +45917,57120,Female,Loyal Customer,19,Business travel,Eco,1222,4,4,4,4,4,4,3,4,3,4,3,1,1,4,5,0.0,satisfied +45918,36535,Female,disloyal Customer,19,Business travel,Eco,1121,1,1,1,1,5,1,5,5,1,3,4,2,1,5,0,0.0,neutral or dissatisfied +45919,11228,Female,Loyal Customer,8,Personal Travel,Eco,216,5,0,5,4,5,5,5,5,3,2,4,2,4,5,0,0.0,satisfied +45920,56746,Female,disloyal Customer,25,Business travel,Business,997,3,0,3,4,3,3,3,3,3,3,5,4,5,3,6,2.0,neutral or dissatisfied +45921,55710,Male,Loyal Customer,58,Personal Travel,Eco,895,2,5,2,1,2,2,2,2,5,2,4,1,4,2,25,31.0,neutral or dissatisfied +45922,37582,Male,disloyal Customer,30,Business travel,Eco,944,1,1,1,4,3,1,5,3,1,5,1,5,5,3,6,0.0,neutral or dissatisfied +45923,71973,Female,disloyal Customer,25,Business travel,Business,1437,4,0,4,2,2,4,2,2,5,2,5,3,4,2,14,0.0,satisfied +45924,9962,Male,Loyal Customer,35,Business travel,Business,2310,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +45925,26029,Female,Loyal Customer,24,Personal Travel,Eco,321,1,4,1,3,4,1,4,4,4,4,4,1,4,4,1,0.0,neutral or dissatisfied +45926,109769,Female,disloyal Customer,42,Business travel,Business,1053,4,5,5,3,4,4,4,4,4,5,5,5,5,4,0,15.0,neutral or dissatisfied +45927,8775,Male,Loyal Customer,54,Business travel,Business,1943,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +45928,100167,Female,Loyal Customer,34,Personal Travel,Eco,725,4,4,4,2,5,4,2,5,2,4,1,4,1,5,0,9.0,satisfied +45929,92548,Female,Loyal Customer,65,Personal Travel,Eco,1919,3,5,3,4,1,5,3,5,5,3,5,4,5,1,1,30.0,neutral or dissatisfied +45930,119522,Male,Loyal Customer,50,Business travel,Business,414,3,2,3,3,4,2,1,5,5,5,5,3,5,2,0,0.0,satisfied +45931,68646,Female,disloyal Customer,26,Business travel,Business,175,1,0,0,4,4,0,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +45932,74886,Male,disloyal Customer,35,Business travel,Business,2475,1,1,1,3,4,1,4,4,2,5,2,3,4,4,78,66.0,neutral or dissatisfied +45933,54455,Male,Loyal Customer,40,Business travel,Business,1815,4,4,4,4,5,5,5,4,4,4,4,5,4,5,101,90.0,satisfied +45934,21524,Male,Loyal Customer,38,Personal Travel,Eco,164,3,4,0,5,3,0,3,3,5,4,4,5,5,3,41,35.0,neutral or dissatisfied +45935,22086,Female,disloyal Customer,34,Business travel,Eco,782,4,5,5,3,4,5,4,4,4,3,2,2,1,4,25,13.0,neutral or dissatisfied +45936,29187,Female,Loyal Customer,32,Personal Travel,Eco Plus,1050,2,4,2,3,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +45937,4761,Male,disloyal Customer,27,Business travel,Business,403,5,4,4,3,5,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +45938,21213,Female,Loyal Customer,41,Business travel,Eco,192,4,1,2,1,4,4,4,4,2,2,3,3,3,4,0,0.0,neutral or dissatisfied +45939,65223,Female,Loyal Customer,57,Business travel,Eco Plus,224,3,4,4,4,5,4,3,3,3,3,3,3,3,3,81,85.0,neutral or dissatisfied +45940,20109,Male,Loyal Customer,41,Business travel,Business,1721,1,1,1,1,3,3,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +45941,114350,Female,disloyal Customer,11,Personal Travel,Eco,853,2,4,2,4,5,2,5,5,5,4,4,1,4,5,0,0.0,neutral or dissatisfied +45942,48982,Female,Loyal Customer,51,Business travel,Eco,156,4,5,5,5,1,3,1,4,4,4,4,3,4,5,11,13.0,satisfied +45943,43917,Male,Loyal Customer,33,Personal Travel,Eco,174,5,5,5,2,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +45944,65832,Male,Loyal Customer,39,Business travel,Business,1389,4,4,4,4,2,5,5,4,4,4,4,5,4,3,65,44.0,satisfied +45945,113898,Female,disloyal Customer,13,Business travel,Eco,2329,1,1,1,4,1,1,1,1,3,3,2,1,4,1,25,8.0,neutral or dissatisfied +45946,36020,Male,disloyal Customer,39,Business travel,Eco,399,2,0,2,1,2,3,3,2,2,5,2,3,1,3,383,401.0,neutral or dissatisfied +45947,73909,Female,Loyal Customer,49,Business travel,Business,2585,1,1,1,1,4,4,4,3,2,5,5,4,3,4,36,48.0,satisfied +45948,127030,Male,Loyal Customer,40,Business travel,Business,338,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +45949,23524,Female,Loyal Customer,47,Business travel,Eco Plus,349,4,5,5,5,4,5,5,1,2,4,5,5,2,5,140,123.0,satisfied +45950,68658,Male,Loyal Customer,56,Business travel,Eco,237,4,2,2,2,4,4,4,4,3,2,3,1,3,4,0,26.0,neutral or dissatisfied +45951,19488,Female,Loyal Customer,41,Business travel,Eco Plus,177,4,5,5,5,1,1,5,4,4,4,4,4,4,4,0,8.0,satisfied +45952,51204,Female,Loyal Customer,58,Business travel,Eco Plus,193,3,2,2,2,5,3,3,3,3,3,3,5,3,5,0,0.0,satisfied +45953,104291,Male,disloyal Customer,21,Business travel,Eco,440,2,4,2,4,5,2,4,5,4,3,4,4,3,5,67,58.0,neutral or dissatisfied +45954,3783,Male,Loyal Customer,53,Business travel,Business,599,2,2,2,2,4,4,3,2,2,2,2,3,2,1,43,26.0,neutral or dissatisfied +45955,61028,Female,Loyal Customer,13,Business travel,Eco Plus,3365,4,2,2,2,4,2,4,1,1,3,3,4,2,4,69,102.0,neutral or dissatisfied +45956,65588,Female,disloyal Customer,21,Business travel,Eco,175,1,3,0,4,5,0,5,5,3,2,4,1,3,5,0,0.0,neutral or dissatisfied +45957,81868,Female,Loyal Customer,42,Business travel,Business,1050,2,2,2,2,3,4,5,3,3,4,3,5,3,3,18,15.0,satisfied +45958,20017,Female,Loyal Customer,49,Business travel,Eco Plus,589,5,2,5,2,5,3,1,4,4,5,4,3,4,3,0,0.0,satisfied +45959,116155,Female,Loyal Customer,9,Personal Travel,Eco,342,4,1,4,4,3,4,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +45960,52631,Female,Loyal Customer,38,Business travel,Eco,110,3,4,4,4,3,3,3,3,3,2,2,1,2,3,67,60.0,neutral or dissatisfied +45961,42201,Male,disloyal Customer,23,Business travel,Eco,817,3,3,3,5,1,3,1,1,4,3,2,2,1,1,0,0.0,neutral or dissatisfied +45962,90742,Female,Loyal Customer,36,Business travel,Business,1552,3,1,1,1,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +45963,84358,Male,Loyal Customer,49,Business travel,Business,606,1,2,2,2,3,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +45964,8043,Female,disloyal Customer,35,Business travel,Business,530,4,4,4,4,1,4,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +45965,12740,Male,Loyal Customer,19,Personal Travel,Eco,689,1,4,2,3,5,2,5,5,3,2,5,3,4,5,27,15.0,neutral or dissatisfied +45966,83935,Male,Loyal Customer,60,Business travel,Business,321,2,2,4,2,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +45967,9828,Male,Loyal Customer,54,Business travel,Business,1523,2,2,2,2,5,4,5,5,5,5,5,3,5,3,20,21.0,satisfied +45968,117653,Female,Loyal Customer,28,Personal Travel,Eco Plus,347,3,4,3,3,1,3,3,1,3,3,2,1,5,1,0,0.0,neutral or dissatisfied +45969,7800,Female,disloyal Customer,26,Business travel,Business,710,4,0,4,3,5,4,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +45970,43505,Female,Loyal Customer,14,Personal Travel,Eco,679,4,3,4,3,5,4,5,5,1,2,2,1,5,5,3,9.0,neutral or dissatisfied +45971,5606,Male,Loyal Customer,42,Business travel,Business,3682,5,5,5,5,5,5,5,4,4,4,4,5,4,4,116,128.0,satisfied +45972,13927,Male,Loyal Customer,66,Business travel,Eco,317,4,2,2,2,4,4,4,4,1,3,2,3,1,4,0,0.0,satisfied +45973,67085,Male,Loyal Customer,39,Business travel,Business,1102,3,3,3,3,4,4,5,4,4,4,4,3,4,3,4,7.0,satisfied +45974,53991,Male,Loyal Customer,46,Business travel,Business,1825,2,4,4,4,5,2,4,2,2,2,2,2,2,3,7,0.0,neutral or dissatisfied +45975,82393,Male,Loyal Customer,51,Business travel,Business,2212,1,1,1,1,2,4,4,5,5,5,5,5,5,3,12,60.0,satisfied +45976,49207,Male,disloyal Customer,22,Business travel,Eco,109,1,0,1,3,1,1,1,1,5,1,2,2,4,1,0,0.0,neutral or dissatisfied +45977,98924,Female,Loyal Customer,44,Business travel,Business,2565,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +45978,3262,Female,Loyal Customer,47,Business travel,Business,419,2,2,2,2,5,4,4,5,5,5,5,5,5,5,9,0.0,satisfied +45979,100839,Female,disloyal Customer,29,Business travel,Eco,711,2,2,2,4,4,2,4,4,4,5,3,3,3,4,19,10.0,neutral or dissatisfied +45980,78309,Female,Loyal Customer,52,Business travel,Business,1598,2,2,2,2,4,3,5,4,4,5,4,3,4,3,0,0.0,satisfied +45981,4304,Male,Loyal Customer,34,Business travel,Eco Plus,502,2,1,1,1,2,2,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +45982,38192,Female,Loyal Customer,40,Personal Travel,Eco,1211,5,4,5,3,3,5,3,3,2,5,3,2,3,3,0,0.0,satisfied +45983,12806,Female,Loyal Customer,25,Business travel,Eco,817,4,3,3,3,4,4,4,4,1,2,4,1,4,4,0,0.0,satisfied +45984,58422,Male,Loyal Customer,54,Business travel,Business,3402,2,3,3,3,4,3,2,2,2,2,2,4,2,4,9,24.0,neutral or dissatisfied +45985,8059,Male,Loyal Customer,41,Business travel,Business,1911,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +45986,117553,Male,Loyal Customer,49,Business travel,Business,3154,3,3,2,3,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +45987,113337,Female,Loyal Customer,39,Business travel,Business,226,0,0,0,3,5,5,5,2,2,2,5,5,2,5,26,18.0,satisfied +45988,90102,Female,Loyal Customer,22,Business travel,Eco,1145,4,1,1,1,4,4,3,4,3,2,3,4,4,4,75,69.0,neutral or dissatisfied +45989,50423,Male,disloyal Customer,22,Business travel,Eco,190,4,0,4,5,4,4,3,4,2,1,1,4,5,4,0,0.0,neutral or dissatisfied +45990,40400,Male,Loyal Customer,54,Business travel,Business,175,4,4,4,4,1,3,3,3,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +45991,22113,Female,disloyal Customer,25,Business travel,Eco,694,3,4,4,3,3,4,3,3,4,1,5,4,3,3,21,13.0,neutral or dissatisfied +45992,55316,Female,Loyal Customer,53,Business travel,Eco,1325,1,3,3,3,5,2,2,1,1,1,1,4,1,2,11,5.0,neutral or dissatisfied +45993,67262,Female,Loyal Customer,9,Personal Travel,Eco,1119,0,3,0,2,4,0,4,4,2,1,3,1,3,4,0,0.0,satisfied +45994,5241,Female,disloyal Customer,38,Business travel,Eco,293,3,2,3,4,3,3,3,3,1,1,4,4,3,3,0,6.0,neutral or dissatisfied +45995,86288,Female,Loyal Customer,34,Personal Travel,Eco,356,1,4,1,3,3,1,3,3,2,1,4,3,1,3,9,0.0,neutral or dissatisfied +45996,101923,Male,Loyal Customer,35,Business travel,Business,2297,1,1,1,1,2,3,4,4,4,4,4,3,4,4,8,0.0,satisfied +45997,36192,Male,Loyal Customer,47,Personal Travel,Business,496,4,5,2,1,2,5,5,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +45998,20547,Male,Loyal Customer,30,Business travel,Business,773,3,3,3,3,4,4,4,4,4,4,1,4,3,4,0,0.0,satisfied +45999,109216,Male,Loyal Customer,34,Business travel,Business,391,2,2,2,2,4,5,5,4,4,4,4,3,4,4,78,75.0,satisfied +46000,69231,Male,Loyal Customer,48,Business travel,Business,3584,2,5,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +46001,49095,Male,Loyal Customer,47,Business travel,Eco,421,4,2,2,2,4,4,4,4,1,3,2,5,4,4,0,0.0,satisfied +46002,61367,Male,Loyal Customer,56,Personal Travel,Business,679,0,1,0,3,2,4,4,4,4,0,4,4,4,3,0,0.0,satisfied +46003,106379,Female,Loyal Customer,50,Business travel,Business,3568,2,2,2,2,4,5,5,4,4,4,4,5,4,3,4,0.0,satisfied +46004,1063,Male,Loyal Customer,67,Personal Travel,Eco,140,0,2,0,3,5,0,5,5,4,1,3,3,4,5,9,0.0,satisfied +46005,97771,Male,Loyal Customer,35,Business travel,Business,3214,1,1,1,1,5,5,5,5,5,5,5,5,5,4,9,0.0,satisfied +46006,19028,Male,Loyal Customer,34,Personal Travel,Eco,871,1,4,1,4,1,1,1,1,1,1,3,2,4,1,118,131.0,neutral or dissatisfied +46007,118808,Male,Loyal Customer,8,Personal Travel,Eco,338,4,5,4,3,2,4,2,2,4,3,5,5,4,2,6,14.0,neutral or dissatisfied +46008,22376,Female,Loyal Customer,50,Business travel,Business,83,3,4,4,4,5,3,4,2,2,2,3,4,2,2,11,7.0,neutral or dissatisfied +46009,2514,Female,Loyal Customer,50,Business travel,Business,2180,4,4,3,4,4,5,4,4,4,4,4,3,4,5,8,10.0,satisfied +46010,88824,Female,disloyal Customer,37,Business travel,Eco Plus,270,4,4,4,2,5,4,5,5,4,5,1,3,2,5,0,0.0,neutral or dissatisfied +46011,18761,Female,Loyal Customer,31,Personal Travel,Eco,926,2,5,2,1,1,2,1,1,4,2,4,5,5,1,26,0.0,neutral or dissatisfied +46012,85255,Female,Loyal Customer,60,Personal Travel,Eco,689,5,2,5,3,4,4,4,1,1,2,1,4,1,2,0,0.0,satisfied +46013,62357,Female,Loyal Customer,65,Business travel,Eco Plus,235,1,1,1,1,2,4,3,1,1,1,1,4,1,1,51,43.0,neutral or dissatisfied +46014,20028,Female,Loyal Customer,50,Business travel,Business,1835,4,4,4,4,2,2,5,4,4,4,4,3,4,3,35,35.0,satisfied +46015,54394,Male,disloyal Customer,36,Business travel,Eco,305,3,1,3,3,3,3,3,3,3,2,4,3,4,3,1,0.0,neutral or dissatisfied +46016,36881,Male,Loyal Customer,57,Business travel,Eco,1182,3,4,4,4,3,3,3,1,5,3,4,3,2,3,452,440.0,neutral or dissatisfied +46017,90676,Male,Loyal Customer,38,Business travel,Eco,406,3,2,2,2,3,3,3,3,2,2,4,1,4,3,0,9.0,neutral or dissatisfied +46018,59091,Male,Loyal Customer,9,Personal Travel,Eco,1846,2,4,2,5,3,2,5,3,3,3,4,4,4,3,12,16.0,neutral or dissatisfied +46019,15429,Male,disloyal Customer,59,Business travel,Eco,164,4,0,3,5,4,3,4,4,5,2,1,2,5,4,0,0.0,neutral or dissatisfied +46020,99706,Male,Loyal Customer,31,Personal Travel,Eco,2026,2,4,2,3,1,2,1,1,5,3,4,3,4,1,10,0.0,neutral or dissatisfied +46021,84772,Male,Loyal Customer,44,Business travel,Business,3028,2,2,2,2,4,4,5,4,4,4,4,3,4,5,6,5.0,satisfied +46022,49312,Male,disloyal Customer,21,Business travel,Business,363,4,0,5,3,5,5,5,5,4,2,3,5,1,5,0,4.0,satisfied +46023,81986,Female,Loyal Customer,41,Business travel,Business,1535,3,3,3,3,2,4,4,3,3,3,3,1,3,3,62,38.0,neutral or dissatisfied +46024,80665,Female,disloyal Customer,25,Business travel,Eco,821,3,3,3,2,2,3,2,2,2,5,3,4,3,2,0,5.0,neutral or dissatisfied +46025,112651,Male,Loyal Customer,20,Business travel,Eco Plus,1845,1,4,4,4,1,1,1,1,2,4,3,3,2,1,0,0.0,neutral or dissatisfied +46026,77125,Male,Loyal Customer,37,Business travel,Business,1481,3,3,3,3,3,4,4,3,3,3,3,3,3,3,7,0.0,satisfied +46027,5968,Male,Loyal Customer,43,Business travel,Business,2913,2,3,3,3,5,3,4,2,2,2,2,2,2,2,0,27.0,neutral or dissatisfied +46028,33074,Female,Loyal Customer,29,Personal Travel,Eco,163,4,3,4,3,4,4,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +46029,36186,Male,Loyal Customer,55,Business travel,Business,3374,2,4,4,4,1,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +46030,67203,Female,Loyal Customer,31,Personal Travel,Eco,929,3,1,3,3,3,3,4,3,2,1,3,4,3,3,10,5.0,neutral or dissatisfied +46031,107921,Female,Loyal Customer,34,Business travel,Business,611,4,4,4,4,2,4,5,4,4,4,4,4,4,3,14,9.0,satisfied +46032,11635,Male,Loyal Customer,22,Business travel,Business,3056,3,3,3,3,4,4,4,4,3,3,4,4,4,4,19,7.0,satisfied +46033,52691,Female,Loyal Customer,55,Business travel,Eco Plus,160,2,3,3,3,4,3,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +46034,103967,Female,Loyal Customer,47,Personal Travel,Eco,770,2,5,1,3,2,4,4,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +46035,48948,Female,Loyal Customer,41,Business travel,Eco,308,5,5,5,5,5,5,5,5,1,1,5,1,1,5,13,23.0,satisfied +46036,86842,Male,Loyal Customer,14,Personal Travel,Eco,692,3,4,3,2,5,3,5,5,3,5,4,3,5,5,21,3.0,neutral or dissatisfied +46037,126879,Female,Loyal Customer,17,Personal Travel,Eco,2296,3,5,3,3,3,3,3,3,1,2,4,5,5,3,0,0.0,neutral or dissatisfied +46038,3225,Female,Loyal Customer,58,Personal Travel,Eco,1187,1,3,0,4,1,2,3,1,1,0,1,3,1,1,24,39.0,neutral or dissatisfied +46039,19143,Female,Loyal Customer,36,Personal Travel,Eco Plus,287,3,4,2,3,5,2,5,5,4,3,4,3,5,5,2,0.0,neutral or dissatisfied +46040,88386,Male,Loyal Customer,73,Business travel,Business,2736,1,5,5,5,2,3,2,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +46041,58191,Female,Loyal Customer,30,Business travel,Business,2710,1,1,1,1,1,2,1,1,3,3,2,3,2,1,0,3.0,neutral or dissatisfied +46042,124701,Male,Loyal Customer,56,Business travel,Business,3817,1,1,1,1,4,2,2,5,5,5,5,3,5,1,0,41.0,satisfied +46043,52406,Female,Loyal Customer,32,Personal Travel,Eco,493,1,1,3,2,2,3,2,2,4,3,2,4,2,2,0,0.0,neutral or dissatisfied +46044,38298,Male,Loyal Customer,56,Business travel,Business,2583,1,4,4,4,1,1,1,2,2,3,3,1,2,1,56,56.0,neutral or dissatisfied +46045,89975,Female,Loyal Customer,52,Business travel,Business,3076,5,5,5,5,3,4,5,4,4,4,4,4,4,5,38,32.0,satisfied +46046,48764,Female,Loyal Customer,48,Business travel,Business,2981,1,3,3,3,1,2,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +46047,31351,Male,Loyal Customer,50,Business travel,Business,3129,4,4,4,4,4,5,4,4,4,4,4,3,4,5,80,83.0,satisfied +46048,16923,Male,Loyal Customer,38,Business travel,Eco,820,4,5,5,5,4,4,4,4,5,1,4,2,3,4,27,23.0,satisfied +46049,117201,Female,Loyal Customer,59,Personal Travel,Eco,369,1,3,1,3,3,4,3,3,3,1,3,4,3,1,19,11.0,neutral or dissatisfied +46050,58578,Male,Loyal Customer,66,Personal Travel,Eco,403,4,5,4,3,4,4,4,4,4,3,5,4,5,4,1,0.0,satisfied +46051,15842,Female,Loyal Customer,9,Business travel,Business,2104,5,5,5,5,5,5,5,5,5,4,5,1,2,5,5,0.0,satisfied +46052,106584,Female,disloyal Customer,26,Business travel,Business,333,4,2,3,4,5,3,5,5,3,3,4,4,4,5,0,0.0,satisfied +46053,9700,Male,Loyal Customer,58,Personal Travel,Eco,277,2,1,2,4,3,2,5,3,2,4,3,3,4,3,0,0.0,neutral or dissatisfied +46054,102692,Female,Loyal Customer,77,Business travel,Eco,255,2,2,1,2,2,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +46055,114452,Male,Loyal Customer,34,Business travel,Business,2675,4,4,4,4,3,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +46056,39094,Female,Loyal Customer,43,Personal Travel,Eco,984,5,4,5,3,5,1,1,5,3,4,5,1,3,1,118,135.0,satisfied +46057,85846,Male,Loyal Customer,43,Personal Travel,Eco,666,2,5,2,1,2,2,2,2,4,5,3,2,2,2,0,0.0,neutral or dissatisfied +46058,14857,Male,disloyal Customer,38,Business travel,Eco,315,5,0,5,1,3,5,3,3,5,1,3,2,3,3,3,16.0,satisfied +46059,45284,Male,disloyal Customer,45,Business travel,Eco,290,1,5,1,3,4,1,4,4,4,2,3,5,3,4,0,0.0,neutral or dissatisfied +46060,86292,Male,Loyal Customer,49,Personal Travel,Eco,226,2,4,2,3,3,2,3,3,4,5,4,4,5,3,6,16.0,neutral or dissatisfied +46061,51767,Female,Loyal Customer,69,Personal Travel,Eco,425,2,0,5,4,5,4,2,1,1,5,1,1,1,1,0,0.0,neutral or dissatisfied +46062,38495,Male,disloyal Customer,20,Business travel,Eco,1103,3,3,3,4,5,3,5,5,1,5,4,2,1,5,2,0.0,neutral or dissatisfied +46063,126356,Female,Loyal Customer,8,Personal Travel,Eco,600,1,5,1,1,5,1,5,5,4,5,5,4,4,5,2,0.0,neutral or dissatisfied +46064,41275,Female,Loyal Customer,52,Business travel,Eco,812,5,1,1,1,3,2,2,4,4,5,4,4,4,4,0,5.0,satisfied +46065,24056,Female,Loyal Customer,50,Personal Travel,Eco,562,4,5,4,3,5,4,5,3,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +46066,122856,Female,disloyal Customer,25,Business travel,Eco,226,3,1,3,3,1,3,1,1,3,5,2,3,2,1,0,0.0,neutral or dissatisfied +46067,86674,Female,Loyal Customer,42,Personal Travel,Eco Plus,746,4,4,4,4,2,3,4,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +46068,115717,Male,Loyal Customer,18,Business travel,Business,446,2,5,5,5,2,2,2,2,4,2,3,3,4,2,23,27.0,neutral or dissatisfied +46069,77188,Female,Loyal Customer,66,Personal Travel,Eco,290,2,4,2,5,5,4,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +46070,22179,Female,Loyal Customer,26,Business travel,Business,1613,3,3,3,3,4,4,4,4,5,3,4,4,1,4,0,0.0,satisfied +46071,62338,Female,disloyal Customer,20,Business travel,Business,414,0,5,0,1,5,0,5,5,5,3,5,5,4,5,0,0.0,satisfied +46072,57221,Female,Loyal Customer,41,Personal Travel,Eco,1514,4,3,4,4,1,4,1,1,1,2,4,4,3,1,0,36.0,neutral or dissatisfied +46073,15787,Female,disloyal Customer,55,Business travel,Eco Plus,198,1,1,1,5,2,1,2,2,5,1,1,2,4,2,35,33.0,neutral or dissatisfied +46074,124569,Male,disloyal Customer,34,Business travel,Business,453,3,3,3,1,3,3,5,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +46075,5719,Female,Loyal Customer,58,Personal Travel,Eco,299,1,4,1,3,4,5,4,3,3,1,3,3,3,5,32,40.0,neutral or dissatisfied +46076,87737,Male,Loyal Customer,35,Personal Travel,Eco,4502,1,1,1,3,1,3,3,1,2,2,2,3,2,3,0,32.0,neutral or dissatisfied +46077,4068,Male,Loyal Customer,18,Personal Travel,Eco,419,2,5,5,4,5,5,5,5,5,1,4,1,5,5,0,0.0,neutral or dissatisfied +46078,29070,Male,Loyal Customer,55,Personal Travel,Eco,978,1,4,1,4,5,1,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +46079,107749,Female,Loyal Customer,21,Personal Travel,Eco,251,2,5,2,3,3,2,3,3,1,2,5,2,1,3,1,0.0,neutral or dissatisfied +46080,105517,Male,Loyal Customer,33,Business travel,Business,611,5,5,5,5,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +46081,50457,Female,Loyal Customer,38,Business travel,Business,2376,3,3,3,3,5,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +46082,12346,Male,Loyal Customer,18,Business travel,Business,201,1,1,1,1,1,1,1,1,3,1,3,2,4,1,50,53.0,neutral or dissatisfied +46083,30352,Female,Loyal Customer,22,Business travel,Eco,862,4,3,3,3,4,4,3,4,5,5,5,2,4,4,4,37.0,satisfied +46084,10594,Female,Loyal Customer,39,Business travel,Business,166,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +46085,35859,Female,Loyal Customer,61,Personal Travel,Eco,937,1,4,0,4,2,3,4,4,4,0,4,2,4,2,0,0.0,neutral or dissatisfied +46086,106233,Female,Loyal Customer,24,Personal Travel,Eco,471,3,2,3,4,2,3,5,2,3,1,3,3,4,2,6,0.0,neutral or dissatisfied +46087,5978,Male,Loyal Customer,51,Business travel,Business,691,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,,satisfied +46088,53626,Male,disloyal Customer,55,Business travel,Eco,374,4,4,4,2,2,4,2,2,5,1,3,2,5,2,0,10.0,neutral or dissatisfied +46089,81923,Male,disloyal Customer,54,Business travel,Business,1535,4,4,4,4,3,4,3,3,3,5,3,4,4,3,1,0.0,neutral or dissatisfied +46090,106659,Female,Loyal Customer,53,Business travel,Business,1590,3,5,5,5,5,2,4,3,3,3,3,2,3,3,5,0.0,neutral or dissatisfied +46091,95407,Female,Loyal Customer,44,Personal Travel,Eco,323,0,1,0,4,3,4,3,5,5,0,5,4,5,3,0,0.0,satisfied +46092,14647,Female,disloyal Customer,22,Business travel,Business,112,5,0,5,2,1,5,1,1,3,4,5,4,5,1,1,0.0,satisfied +46093,64439,Female,Loyal Customer,46,Business travel,Business,2372,5,5,5,5,5,5,4,4,4,4,4,3,4,3,3,14.0,satisfied +46094,65221,Male,Loyal Customer,52,Business travel,Business,2150,5,5,5,5,5,5,5,5,5,5,5,5,5,3,46,42.0,satisfied +46095,1722,Female,Loyal Customer,73,Business travel,Business,364,2,2,2,2,4,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +46096,35293,Male,Loyal Customer,21,Business travel,Business,3530,3,5,5,5,3,3,3,1,2,2,3,3,3,3,163,196.0,neutral or dissatisfied +46097,6338,Male,Loyal Customer,59,Business travel,Business,315,4,4,4,4,4,4,4,4,4,4,4,4,4,4,62,68.0,satisfied +46098,99036,Male,Loyal Customer,26,Personal Travel,Eco,1009,3,5,3,5,5,3,5,5,4,4,2,2,3,5,0,0.0,neutral or dissatisfied +46099,76461,Male,Loyal Customer,42,Personal Travel,Business,516,3,3,3,4,3,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +46100,114648,Male,Loyal Customer,45,Business travel,Business,3588,3,3,4,3,4,4,4,4,3,4,4,4,5,4,152,136.0,satisfied +46101,117286,Male,Loyal Customer,54,Business travel,Business,3054,0,0,0,3,2,5,4,5,5,5,5,3,5,4,62,46.0,satisfied +46102,39112,Male,disloyal Customer,32,Business travel,Eco,252,3,3,3,3,4,3,4,4,1,4,3,1,4,4,0,0.0,neutral or dissatisfied +46103,125962,Female,Loyal Customer,59,Personal Travel,Eco Plus,920,3,4,3,3,2,4,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +46104,109807,Male,Loyal Customer,59,Business travel,Business,3652,3,3,3,3,4,5,4,3,3,3,3,5,3,3,15,0.0,satisfied +46105,123546,Male,disloyal Customer,27,Business travel,Business,756,4,4,4,1,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +46106,121105,Female,Loyal Customer,46,Business travel,Business,2402,2,3,3,3,2,2,2,2,2,4,4,2,1,2,21,53.0,neutral or dissatisfied +46107,29985,Male,disloyal Customer,24,Business travel,Eco,261,1,4,1,3,4,1,4,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +46108,120521,Male,disloyal Customer,25,Business travel,Business,96,5,0,5,4,5,5,4,5,3,4,5,5,4,5,0,0.0,satisfied +46109,65747,Female,Loyal Customer,25,Personal Travel,Eco,1061,3,4,3,3,5,3,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +46110,66208,Female,disloyal Customer,24,Business travel,Business,550,1,3,1,3,1,1,1,1,4,5,4,1,3,1,20,33.0,neutral or dissatisfied +46111,92788,Male,Loyal Customer,7,Personal Travel,Eco Plus,1671,2,5,2,2,4,2,4,4,2,3,5,2,1,4,0,0.0,neutral or dissatisfied +46112,103275,Female,Loyal Customer,12,Business travel,Eco Plus,888,0,5,5,5,0,1,4,0,3,4,3,4,4,0,11,2.0,neutral or dissatisfied +46113,100791,Male,Loyal Customer,30,Business travel,Business,3236,5,5,5,5,4,4,4,4,3,2,4,5,4,4,4,0.0,satisfied +46114,124002,Male,disloyal Customer,27,Business travel,Eco,184,2,3,2,2,1,2,1,1,3,5,3,2,2,1,0,0.0,neutral or dissatisfied +46115,110884,Female,disloyal Customer,33,Business travel,Eco,581,4,1,4,3,1,4,4,1,1,3,4,4,4,1,25,29.0,neutral or dissatisfied +46116,94223,Male,disloyal Customer,21,Business travel,Eco,496,3,4,3,4,2,3,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +46117,125147,Male,Loyal Customer,12,Business travel,Business,1999,2,5,5,5,2,2,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +46118,69447,Female,Loyal Customer,60,Personal Travel,Eco,1035,3,4,3,3,5,4,5,5,5,3,5,3,5,3,0,11.0,neutral or dissatisfied +46119,91682,Female,Loyal Customer,44,Business travel,Business,1678,1,3,3,3,2,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +46120,30243,Female,Loyal Customer,17,Personal Travel,Eco,896,2,2,2,4,2,2,2,2,1,3,3,4,3,2,21,20.0,neutral or dissatisfied +46121,115006,Male,Loyal Customer,55,Business travel,Business,3737,2,2,2,2,3,5,4,4,4,4,4,4,4,4,13,3.0,satisfied +46122,54636,Female,Loyal Customer,24,Business travel,Business,964,4,4,4,4,5,5,5,5,5,4,2,5,5,5,0,0.0,satisfied +46123,126093,Male,Loyal Customer,29,Business travel,Business,507,4,4,4,4,2,2,2,2,4,2,5,3,4,2,39,50.0,satisfied +46124,55881,Female,Loyal Customer,28,Business travel,Business,733,1,1,1,1,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +46125,71581,Male,Loyal Customer,58,Business travel,Business,2212,3,2,2,2,2,1,2,3,3,3,3,3,3,4,14,33.0,neutral or dissatisfied +46126,29894,Female,Loyal Customer,31,Business travel,Business,2670,2,2,2,2,5,5,5,5,2,4,5,1,3,5,32,27.0,satisfied +46127,38780,Female,Loyal Customer,37,Business travel,Eco,353,4,4,3,3,4,4,4,4,2,1,4,4,5,4,0,0.0,satisfied +46128,36605,Male,disloyal Customer,24,Business travel,Eco,1197,2,2,2,4,4,2,4,4,2,2,3,4,3,4,5,0.0,neutral or dissatisfied +46129,21498,Female,Loyal Customer,13,Personal Travel,Eco,306,2,5,2,1,5,2,5,5,5,2,5,4,5,5,0,6.0,neutral or dissatisfied +46130,101274,Female,Loyal Customer,24,Business travel,Business,3198,3,3,2,3,5,5,5,5,4,5,4,5,5,5,13,0.0,satisfied +46131,37320,Female,Loyal Customer,27,Business travel,Business,3869,1,1,1,1,4,4,4,2,5,2,1,4,1,4,122,177.0,satisfied +46132,9450,Male,Loyal Customer,51,Personal Travel,Eco,368,1,4,1,3,4,1,1,4,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +46133,19871,Female,Loyal Customer,39,Business travel,Business,2090,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +46134,11090,Female,Loyal Customer,40,Personal Travel,Eco,74,2,5,2,2,5,2,5,5,5,4,4,3,5,5,46,52.0,neutral or dissatisfied +46135,2111,Female,Loyal Customer,11,Personal Travel,Eco Plus,785,2,4,2,1,3,2,3,3,4,2,4,5,5,3,0,14.0,neutral or dissatisfied +46136,94518,Female,Loyal Customer,39,Business travel,Business,2336,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +46137,15117,Male,disloyal Customer,37,Business travel,Eco,1042,1,1,1,5,5,1,5,5,5,4,1,4,2,5,0,0.0,neutral or dissatisfied +46138,96778,Female,Loyal Customer,30,Business travel,Business,816,1,1,1,1,4,5,4,4,3,4,4,5,5,4,0,0.0,satisfied +46139,110826,Female,Loyal Customer,70,Personal Travel,Eco,849,2,4,2,2,4,5,4,4,4,2,1,4,4,3,0,0.0,neutral or dissatisfied +46140,57482,Female,Loyal Customer,23,Business travel,Business,1589,2,2,1,2,5,5,5,5,5,4,4,5,5,5,10,32.0,satisfied +46141,76762,Male,Loyal Customer,47,Business travel,Business,546,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +46142,113090,Female,Loyal Customer,20,Business travel,Business,479,3,4,4,4,3,3,3,3,3,4,3,2,3,3,49,42.0,neutral or dissatisfied +46143,57464,Male,Loyal Customer,38,Personal Travel,Eco,334,4,4,4,1,4,4,4,4,5,5,4,5,4,4,7,6.0,neutral or dissatisfied +46144,106977,Female,disloyal Customer,36,Business travel,Eco,537,2,3,2,3,5,2,5,5,2,1,3,2,4,5,21,21.0,neutral or dissatisfied +46145,126100,Male,Loyal Customer,58,Business travel,Business,328,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +46146,22951,Male,Loyal Customer,32,Business travel,Business,817,5,5,5,5,5,5,5,5,4,4,1,4,4,5,0,0.0,satisfied +46147,65589,Female,Loyal Customer,49,Business travel,Eco,175,2,5,5,5,1,4,4,2,2,2,2,2,2,1,0,2.0,neutral or dissatisfied +46148,52717,Female,Loyal Customer,46,Personal Travel,Eco Plus,1162,3,3,3,3,5,4,4,1,1,3,1,3,1,1,24,17.0,neutral or dissatisfied +46149,7658,Female,disloyal Customer,26,Business travel,Business,604,0,0,0,3,5,0,1,5,3,5,4,5,4,5,0,0.0,satisfied +46150,100779,Female,Loyal Customer,51,Personal Travel,Eco,1411,4,3,4,3,2,3,3,4,4,4,5,4,4,3,0,0.0,satisfied +46151,83872,Female,Loyal Customer,55,Business travel,Business,1670,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +46152,117645,Female,Loyal Customer,54,Business travel,Business,872,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +46153,10604,Female,Loyal Customer,41,Business travel,Eco,158,1,5,5,5,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +46154,46276,Female,Loyal Customer,63,Personal Travel,Eco,594,2,5,2,3,1,4,1,3,3,2,3,5,3,2,0,3.0,neutral or dissatisfied +46155,46663,Male,Loyal Customer,33,Business travel,Business,3320,1,1,1,1,5,5,3,5,3,5,2,3,2,5,0,0.0,satisfied +46156,24955,Male,Loyal Customer,67,Personal Travel,Eco,1747,2,5,2,4,4,2,3,4,4,3,4,5,4,4,54,34.0,neutral or dissatisfied +46157,48163,Female,disloyal Customer,26,Business travel,Eco,391,4,0,4,5,5,4,5,5,3,1,4,3,3,5,0,0.0,satisfied +46158,44362,Male,Loyal Customer,54,Business travel,Business,2581,0,5,0,4,4,4,3,1,1,2,2,2,1,2,0,0.0,satisfied +46159,62987,Female,Loyal Customer,36,Business travel,Business,967,2,2,1,2,4,4,4,5,5,5,5,3,5,4,7,0.0,satisfied +46160,125307,Female,Loyal Customer,52,Personal Travel,Eco,678,1,5,1,3,2,5,1,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +46161,96677,Male,Loyal Customer,59,Business travel,Eco Plus,972,1,2,2,2,1,1,1,1,1,5,4,1,3,1,2,0.0,neutral or dissatisfied +46162,101144,Male,Loyal Customer,55,Business travel,Eco,1235,2,4,4,4,2,2,2,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +46163,55388,Male,Loyal Customer,42,Personal Travel,Eco,413,2,4,2,4,2,2,2,2,3,5,4,5,5,2,0,40.0,neutral or dissatisfied +46164,23654,Male,Loyal Customer,42,Business travel,Business,73,1,1,1,1,1,2,4,4,4,4,5,3,4,3,50,43.0,satisfied +46165,96652,Male,Loyal Customer,32,Personal Travel,Eco,937,3,5,3,4,2,3,2,2,4,3,5,5,5,2,10,1.0,neutral or dissatisfied +46166,103306,Female,disloyal Customer,20,Business travel,Eco,1139,4,4,4,1,3,4,3,3,5,3,5,4,5,3,0,0.0,satisfied +46167,60261,Female,disloyal Customer,28,Business travel,Business,1546,2,2,2,3,2,2,2,2,5,4,4,3,4,2,0,1.0,neutral or dissatisfied +46168,42762,Male,Loyal Customer,24,Business travel,Eco,493,2,1,5,1,2,2,1,2,3,3,3,2,4,2,19,15.0,neutral or dissatisfied +46169,69773,Female,disloyal Customer,35,Business travel,Business,2454,1,1,1,1,1,1,2,4,4,3,4,2,3,2,14,0.0,neutral or dissatisfied +46170,100893,Male,disloyal Customer,28,Business travel,Business,377,1,1,1,5,4,1,4,4,4,3,5,3,4,4,1,11.0,neutral or dissatisfied +46171,39305,Male,Loyal Customer,42,Personal Travel,Eco,67,1,5,1,4,2,1,1,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +46172,71817,Male,Loyal Customer,46,Business travel,Business,1846,4,4,4,4,5,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +46173,40178,Female,Loyal Customer,48,Business travel,Business,1724,4,4,4,4,4,3,1,4,4,4,4,4,4,4,0,0.0,satisfied +46174,124883,Female,Loyal Customer,19,Business travel,Business,3979,4,5,4,4,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +46175,54001,Female,Loyal Customer,44,Business travel,Eco Plus,325,4,4,4,4,5,1,2,4,4,4,4,4,4,3,22,0.0,satisfied +46176,91663,Male,Loyal Customer,30,Business travel,Eco Plus,1312,3,4,4,4,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +46177,103820,Female,Loyal Customer,42,Business travel,Business,1242,1,1,1,1,5,5,5,4,4,4,4,5,4,4,37,42.0,satisfied +46178,43932,Female,Loyal Customer,36,Business travel,Eco Plus,255,4,2,2,2,4,4,4,4,2,4,1,2,2,4,0,0.0,satisfied +46179,116882,Female,Loyal Customer,53,Business travel,Business,647,4,4,4,4,4,5,5,3,3,3,3,3,3,4,21,8.0,satisfied +46180,37328,Male,Loyal Customer,31,Business travel,Business,3920,5,5,5,5,5,5,5,5,3,3,4,1,3,5,2,0.0,satisfied +46181,98164,Female,Loyal Customer,12,Personal Travel,Eco,562,3,4,3,1,2,3,2,2,2,4,1,1,2,2,0,0.0,neutral or dissatisfied +46182,36884,Female,Loyal Customer,63,Personal Travel,Eco,1182,5,4,5,4,5,4,4,2,2,5,2,3,2,5,0,0.0,satisfied +46183,13293,Female,Loyal Customer,38,Business travel,Eco Plus,657,2,1,1,1,2,2,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +46184,79014,Female,disloyal Customer,20,Business travel,Eco,226,3,5,3,4,3,3,3,3,4,2,4,3,4,3,2,0.0,neutral or dissatisfied +46185,23109,Male,Loyal Customer,47,Business travel,Eco,223,3,2,4,2,2,3,2,2,2,5,3,5,3,2,0,0.0,satisfied +46186,107014,Male,Loyal Customer,40,Personal Travel,Eco Plus,937,1,5,1,3,2,1,2,2,2,5,4,3,2,2,12,5.0,neutral or dissatisfied +46187,103410,Female,disloyal Customer,56,Business travel,Eco,237,2,0,2,1,3,2,3,3,1,5,5,3,3,3,2,5.0,neutral or dissatisfied +46188,74557,Male,Loyal Customer,35,Business travel,Eco,1171,4,3,3,3,4,4,4,4,4,4,2,3,2,4,0,0.0,neutral or dissatisfied +46189,72660,Male,Loyal Customer,57,Personal Travel,Eco,1119,2,1,2,4,2,2,2,2,3,3,3,2,3,2,17,5.0,neutral or dissatisfied +46190,18883,Female,Loyal Customer,36,Business travel,Business,2411,1,4,2,4,5,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +46191,55694,Female,Loyal Customer,57,Business travel,Business,2924,1,1,1,1,3,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +46192,87543,Female,disloyal Customer,27,Business travel,Eco,782,3,3,3,3,5,3,4,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +46193,4082,Male,disloyal Customer,38,Business travel,Business,544,5,5,5,1,2,5,2,2,5,3,4,5,5,2,0,0.0,satisfied +46194,74207,Male,Loyal Customer,41,Business travel,Eco Plus,641,2,3,3,3,2,2,2,2,4,4,4,1,3,2,32,22.0,neutral or dissatisfied +46195,34192,Male,Loyal Customer,62,Personal Travel,Eco,1189,2,4,2,3,2,2,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +46196,35456,Female,Loyal Customer,14,Personal Travel,Eco,1097,1,2,1,4,4,1,2,4,4,1,3,3,4,4,47,62.0,neutral or dissatisfied +46197,52634,Female,Loyal Customer,35,Business travel,Eco,160,5,2,2,2,5,5,5,5,2,1,5,4,4,5,0,0.0,satisfied +46198,84920,Male,Loyal Customer,57,Personal Travel,Eco,481,2,5,3,3,4,3,4,4,1,1,5,4,1,4,0,0.0,neutral or dissatisfied +46199,129086,Male,Loyal Customer,30,Business travel,Business,2342,2,1,1,1,2,2,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +46200,31411,Male,disloyal Customer,22,Business travel,Eco,1387,1,1,1,2,1,1,1,1,4,2,3,4,4,1,18,0.0,neutral or dissatisfied +46201,82422,Female,Loyal Customer,28,Business travel,Business,502,4,4,4,4,4,4,4,4,5,5,5,5,5,4,0,1.0,satisfied +46202,81402,Male,Loyal Customer,35,Business travel,Business,3401,4,4,1,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +46203,37523,Female,Loyal Customer,35,Business travel,Eco,1076,2,5,5,5,2,2,2,2,3,3,2,1,3,2,0,0.0,neutral or dissatisfied +46204,7756,Female,Loyal Customer,16,Personal Travel,Eco,1013,0,2,0,3,3,0,3,3,1,3,3,4,2,3,0,0.0,satisfied +46205,116746,Male,Loyal Customer,13,Personal Travel,Eco Plus,373,2,2,2,4,3,2,5,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +46206,93318,Female,Loyal Customer,41,Business travel,Business,287,3,3,3,3,2,5,4,4,4,4,4,5,4,3,21,13.0,satisfied +46207,26670,Female,Loyal Customer,66,Personal Travel,Eco,581,5,4,5,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +46208,58308,Male,Loyal Customer,26,Business travel,Business,1739,3,3,3,3,4,4,4,4,4,4,5,3,4,4,8,15.0,satisfied +46209,57765,Male,disloyal Customer,39,Business travel,Business,2704,2,2,2,4,2,5,5,4,5,4,5,5,3,5,0,0.0,neutral or dissatisfied +46210,90565,Female,disloyal Customer,22,Business travel,Business,404,5,0,5,5,2,5,3,2,4,3,4,4,4,2,0,6.0,satisfied +46211,108372,Male,Loyal Customer,14,Personal Travel,Eco,1855,4,5,3,4,3,3,3,3,1,2,1,3,2,3,80,64.0,neutral or dissatisfied +46212,91554,Female,Loyal Customer,55,Personal Travel,Eco,680,2,4,2,2,5,2,1,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +46213,39309,Male,Loyal Customer,28,Personal Travel,Eco,268,2,0,2,4,4,2,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +46214,26738,Female,Loyal Customer,21,Personal Travel,Eco Plus,404,2,4,2,1,5,2,3,5,5,3,5,3,4,5,24,16.0,neutral or dissatisfied +46215,89954,Male,Loyal Customer,38,Personal Travel,Eco,1416,3,5,3,1,3,3,3,3,4,5,5,3,4,3,0,3.0,neutral or dissatisfied +46216,106292,Female,Loyal Customer,27,Personal Travel,Eco Plus,689,4,5,4,3,5,4,4,5,1,4,2,4,5,5,0,5.0,neutral or dissatisfied +46217,30908,Male,Loyal Customer,34,Business travel,Business,826,3,3,3,3,5,3,4,2,2,2,2,1,2,5,65,74.0,satisfied +46218,121315,Male,Loyal Customer,28,Personal Travel,Eco,1009,3,4,3,2,2,3,2,2,3,1,2,5,1,2,0,0.0,neutral or dissatisfied +46219,71684,Male,Loyal Customer,51,Personal Travel,Eco,1120,1,5,1,3,3,1,3,3,5,5,4,5,5,3,1,0.0,neutral or dissatisfied +46220,4885,Female,Loyal Customer,11,Personal Travel,Eco,500,0,5,0,2,5,0,5,5,5,2,4,3,5,5,0,0.0,satisfied +46221,118237,Female,disloyal Customer,48,Business travel,Eco,1319,2,2,2,3,5,2,5,5,1,2,4,4,4,5,80,57.0,neutral or dissatisfied +46222,119167,Male,Loyal Customer,44,Business travel,Business,257,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +46223,92198,Male,Loyal Customer,36,Business travel,Eco,1979,3,1,1,1,3,3,3,3,1,1,3,3,4,3,22,0.0,neutral or dissatisfied +46224,110520,Male,Loyal Customer,22,Business travel,Business,551,2,2,2,2,5,5,5,5,4,2,4,4,5,5,6,0.0,satisfied +46225,125706,Male,Loyal Customer,36,Personal Travel,Eco,857,3,5,3,1,4,3,4,4,3,4,4,5,5,4,23,11.0,neutral or dissatisfied +46226,120814,Male,Loyal Customer,44,Business travel,Eco,266,2,4,4,4,2,2,2,2,1,1,1,1,5,2,0,0.0,satisfied +46227,53593,Male,Loyal Customer,10,Personal Travel,Eco,599,4,3,4,3,5,4,1,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +46228,88110,Female,Loyal Customer,49,Business travel,Business,271,0,0,0,4,5,5,4,1,1,1,1,5,1,5,44,42.0,satisfied +46229,5406,Male,Loyal Customer,53,Personal Travel,Eco,812,2,5,2,3,2,2,3,2,4,4,2,5,2,2,10,0.0,neutral or dissatisfied +46230,79188,Female,Loyal Customer,40,Business travel,Business,1990,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +46231,61828,Female,Loyal Customer,17,Personal Travel,Eco,1379,1,1,1,3,1,1,1,1,3,2,3,4,3,1,11,0.0,neutral or dissatisfied +46232,125714,Male,Loyal Customer,55,Personal Travel,Eco,759,5,5,5,5,2,5,2,2,5,2,4,4,5,2,0,0.0,satisfied +46233,85192,Male,disloyal Customer,21,Business travel,Eco,696,1,1,1,4,4,1,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +46234,60423,Male,Loyal Customer,40,Business travel,Business,794,3,3,3,3,2,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +46235,37873,Female,Loyal Customer,50,Business travel,Eco,1065,2,4,4,4,4,2,2,3,3,2,3,3,3,2,3,0.0,neutral or dissatisfied +46236,79777,Female,disloyal Customer,25,Business travel,Business,550,4,5,4,4,3,4,3,3,5,3,4,5,5,3,18,0.0,satisfied +46237,19076,Male,Loyal Customer,40,Personal Travel,Eco,569,1,5,1,3,4,1,1,4,3,2,1,5,2,4,0,0.0,neutral or dissatisfied +46238,25410,Female,Loyal Customer,41,Personal Travel,Eco,990,2,5,2,4,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +46239,52763,Male,Loyal Customer,46,Business travel,Eco,1874,5,4,4,4,5,5,5,5,5,2,4,1,4,5,0,0.0,satisfied +46240,52689,Male,disloyal Customer,21,Business travel,Eco,119,5,0,5,1,4,5,4,4,5,3,2,4,4,4,0,0.0,satisfied +46241,128806,Male,Loyal Customer,42,Business travel,Business,2586,4,4,4,4,2,2,2,5,4,3,5,2,4,2,0,0.0,satisfied +46242,68063,Female,Loyal Customer,25,Business travel,Business,813,4,4,3,4,4,4,4,4,4,3,4,5,4,4,4,0.0,satisfied +46243,23708,Male,Loyal Customer,11,Personal Travel,Eco,251,1,4,0,3,3,0,3,3,3,4,5,3,5,3,24,17.0,neutral or dissatisfied +46244,30085,Male,Loyal Customer,34,Personal Travel,Eco,1192,2,5,2,4,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +46245,84668,Female,Loyal Customer,49,Business travel,Business,2182,3,5,3,3,4,4,5,4,4,4,4,5,4,4,7,0.0,satisfied +46246,77510,Female,Loyal Customer,55,Business travel,Business,1587,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +46247,109603,Male,Loyal Customer,34,Business travel,Business,861,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +46248,33286,Female,Loyal Customer,62,Personal Travel,Eco Plus,102,2,5,2,3,1,3,4,3,3,2,5,5,3,5,0,0.0,neutral or dissatisfied +46249,24832,Male,Loyal Customer,58,Business travel,Business,2212,1,1,1,1,3,2,2,4,4,4,4,5,4,2,0,0.0,satisfied +46250,93174,Male,Loyal Customer,63,Personal Travel,Eco,1066,3,4,3,1,4,3,4,4,5,3,4,4,4,4,20,30.0,neutral or dissatisfied +46251,21667,Male,Loyal Customer,49,Business travel,Business,746,3,3,3,3,2,3,2,4,4,4,4,3,4,1,76,72.0,satisfied +46252,26253,Male,Loyal Customer,50,Business travel,Eco Plus,404,4,4,4,4,4,4,4,4,4,1,4,4,3,4,0,0.0,satisfied +46253,68003,Female,Loyal Customer,42,Business travel,Business,304,1,1,1,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +46254,95991,Female,Loyal Customer,40,Business travel,Business,795,2,2,5,2,5,4,5,2,2,2,2,3,2,5,63,83.0,satisfied +46255,15121,Male,Loyal Customer,40,Business travel,Business,1042,4,2,2,2,4,4,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +46256,44148,Female,Loyal Customer,33,Personal Travel,Eco,198,1,1,1,3,2,1,2,2,1,3,4,3,4,2,0,1.0,neutral or dissatisfied +46257,89285,Male,Loyal Customer,21,Business travel,Business,3586,5,5,5,5,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +46258,29800,Female,disloyal Customer,25,Business travel,Eco,627,1,0,1,3,4,1,4,4,2,2,4,4,4,4,0,5.0,neutral or dissatisfied +46259,8087,Male,Loyal Customer,50,Business travel,Business,3638,5,5,5,5,3,5,4,4,4,4,4,5,4,4,39,40.0,satisfied +46260,50913,Female,Loyal Customer,64,Personal Travel,Eco,262,2,1,0,3,1,4,3,2,2,0,4,3,2,1,0,0.0,neutral or dissatisfied +46261,97755,Male,Loyal Customer,60,Personal Travel,Eco,787,2,4,2,3,2,2,2,4,2,4,4,2,3,2,116,145.0,neutral or dissatisfied +46262,56062,Male,Loyal Customer,24,Personal Travel,Eco,2475,2,2,2,3,2,2,2,1,2,4,4,2,2,2,9,0.0,neutral or dissatisfied +46263,101486,Male,Loyal Customer,40,Business travel,Business,1899,0,0,0,4,5,4,4,5,5,5,5,4,5,5,2,0.0,satisfied +46264,64794,Male,disloyal Customer,24,Business travel,Eco,190,2,4,2,2,5,2,5,5,5,4,5,5,4,5,40,34.0,neutral or dissatisfied +46265,73998,Female,Loyal Customer,57,Business travel,Business,1972,1,5,5,5,1,4,3,1,1,1,1,2,1,4,10,0.0,neutral or dissatisfied +46266,74323,Male,Loyal Customer,29,Business travel,Business,3692,2,2,2,2,5,5,5,4,4,5,4,5,5,5,235,228.0,satisfied +46267,48083,Male,Loyal Customer,53,Business travel,Eco,236,5,3,3,3,5,5,5,5,1,5,2,3,2,5,8,11.0,satisfied +46268,93094,Male,disloyal Customer,37,Business travel,Business,641,2,2,2,3,4,2,4,4,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +46269,128577,Female,Loyal Customer,54,Business travel,Business,2552,2,2,2,2,5,4,4,3,2,5,5,4,3,4,0,0.0,satisfied +46270,6863,Female,disloyal Customer,45,Business travel,Business,622,4,4,4,3,3,4,3,3,4,5,4,5,4,3,2,0.0,satisfied +46271,104155,Male,Loyal Customer,59,Business travel,Business,2909,1,1,1,1,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +46272,43838,Male,Loyal Customer,50,Business travel,Business,114,3,3,3,3,4,2,2,5,5,5,3,4,5,4,0,4.0,satisfied +46273,59373,Female,Loyal Customer,30,Business travel,Business,2399,4,4,4,4,4,4,4,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +46274,60913,Female,Loyal Customer,44,Business travel,Business,888,3,3,2,3,2,5,4,2,2,2,2,3,2,5,18,14.0,satisfied +46275,31776,Male,Loyal Customer,11,Personal Travel,Eco,602,1,5,1,1,5,1,5,5,3,5,4,3,5,5,0,3.0,neutral or dissatisfied +46276,66854,Male,Loyal Customer,62,Personal Travel,Eco,731,3,2,3,3,3,3,3,3,1,1,3,1,3,3,14,10.0,neutral or dissatisfied +46277,47263,Female,Loyal Customer,37,Personal Travel,Business,588,2,5,2,5,2,3,3,4,3,5,5,3,5,3,154,140.0,neutral or dissatisfied +46278,23024,Male,disloyal Customer,23,Business travel,Eco,1025,5,5,5,2,1,5,1,1,2,5,1,2,1,1,0,0.0,satisfied +46279,7590,Male,Loyal Customer,53,Personal Travel,Eco,594,3,3,3,3,3,3,1,3,1,5,3,1,5,3,0,0.0,neutral or dissatisfied +46280,122521,Male,Loyal Customer,41,Business travel,Business,3520,5,5,4,5,3,5,4,3,3,3,3,4,3,5,86,84.0,satisfied +46281,108935,Female,Loyal Customer,25,Personal Travel,Eco,1066,2,4,2,1,5,2,5,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +46282,43744,Male,disloyal Customer,26,Business travel,Business,546,4,4,4,5,2,4,2,2,4,3,4,3,5,2,2,50.0,satisfied +46283,42225,Male,Loyal Customer,48,Business travel,Business,817,4,4,4,4,4,4,4,5,3,4,2,4,4,4,136,139.0,satisfied +46284,537,Male,disloyal Customer,23,Business travel,Eco,134,4,4,4,4,4,4,4,4,5,3,4,5,4,4,0,0.0,satisfied +46285,108875,Female,Loyal Customer,41,Business travel,Eco,1587,1,3,3,3,1,1,1,1,3,2,2,1,4,1,0,0.0,neutral or dissatisfied +46286,59219,Male,Loyal Customer,63,Personal Travel,Eco,1440,3,4,3,1,2,3,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +46287,120594,Male,Loyal Customer,41,Personal Travel,Eco,980,3,2,4,4,5,4,5,5,1,2,4,4,4,5,0,0.0,neutral or dissatisfied +46288,34502,Male,Loyal Customer,49,Business travel,Business,1521,3,4,3,4,3,3,3,3,3,3,3,1,3,4,33,12.0,neutral or dissatisfied +46289,54787,Male,Loyal Customer,59,Business travel,Business,1570,2,1,5,1,4,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +46290,31997,Male,Loyal Customer,22,Personal Travel,Business,216,3,4,0,1,3,0,5,3,3,2,1,1,2,3,0,4.0,neutral or dissatisfied +46291,28342,Male,Loyal Customer,65,Business travel,Eco,467,2,4,4,4,2,2,2,2,1,3,4,1,4,2,1,0.0,neutral or dissatisfied +46292,98294,Female,Loyal Customer,7,Personal Travel,Eco,1072,3,5,3,2,5,3,5,5,3,5,5,3,4,5,5,28.0,neutral or dissatisfied +46293,93401,Male,Loyal Customer,49,Business travel,Business,723,3,3,3,3,5,4,5,5,5,5,5,3,5,5,17,22.0,satisfied +46294,84108,Female,Loyal Customer,61,Business travel,Business,1900,2,2,2,2,2,5,4,4,4,4,4,3,4,4,74,55.0,satisfied +46295,47757,Female,Loyal Customer,36,Business travel,Eco,329,2,3,3,3,2,2,2,2,2,1,5,4,1,2,0,,satisfied +46296,99070,Female,Loyal Customer,60,Business travel,Business,181,2,2,2,2,4,4,5,5,5,5,4,4,5,4,70,77.0,satisfied +46297,31108,Male,Loyal Customer,35,Business travel,Eco,483,1,4,2,4,1,1,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +46298,77723,Male,Loyal Customer,39,Business travel,Business,813,2,2,2,2,3,3,3,2,2,2,2,1,2,2,4,0.0,neutral or dissatisfied +46299,57415,Female,Loyal Customer,59,Business travel,Business,3887,4,4,4,4,3,1,1,4,4,4,4,5,4,5,0,0.0,satisfied +46300,62101,Male,Loyal Customer,23,Personal Travel,Business,2454,3,4,3,3,4,3,4,4,5,5,2,4,1,4,0,0.0,neutral or dissatisfied +46301,55234,Female,disloyal Customer,28,Business travel,Eco,1009,2,2,2,3,4,2,4,4,2,1,3,2,4,4,15,2.0,neutral or dissatisfied +46302,74179,Male,Loyal Customer,8,Personal Travel,Eco,641,2,5,3,4,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +46303,38988,Female,Loyal Customer,42,Business travel,Business,313,5,5,5,5,3,4,5,4,4,4,4,5,4,1,34,36.0,satisfied +46304,1585,Male,disloyal Customer,36,Business travel,Business,140,1,1,1,3,5,1,5,5,4,3,3,2,4,5,4,11.0,neutral or dissatisfied +46305,37856,Male,disloyal Customer,32,Business travel,Eco,937,3,3,3,5,5,3,5,5,4,3,4,4,2,5,0,0.0,neutral or dissatisfied +46306,90195,Male,Loyal Customer,20,Personal Travel,Eco,983,2,4,2,2,5,2,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +46307,60697,Female,Loyal Customer,55,Business travel,Business,1725,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +46308,100976,Male,Loyal Customer,40,Business travel,Business,1524,1,1,5,1,4,5,5,4,4,4,4,5,4,4,13,26.0,satisfied +46309,26772,Male,Loyal Customer,37,Business travel,Business,1199,1,1,1,1,3,4,2,5,5,4,5,5,5,3,0,0.0,satisfied +46310,74795,Female,Loyal Customer,60,Business travel,Business,1464,1,2,1,1,5,5,5,4,4,4,4,3,4,4,0,7.0,satisfied +46311,97395,Female,disloyal Customer,21,Business travel,Business,347,5,5,5,5,2,5,2,2,1,4,3,2,5,2,0,0.0,satisfied +46312,97274,Female,Loyal Customer,38,Personal Travel,Eco Plus,296,2,2,2,3,5,2,5,5,2,2,2,2,2,5,24,15.0,neutral or dissatisfied +46313,36544,Female,disloyal Customer,25,Business travel,Eco,1249,3,4,4,3,1,4,1,1,1,2,5,4,1,1,39,31.0,neutral or dissatisfied +46314,17371,Female,Loyal Customer,22,Business travel,Business,1817,2,2,2,2,5,5,5,5,1,5,5,1,4,5,0,0.0,satisfied +46315,39482,Female,Loyal Customer,39,Business travel,Eco,867,3,3,3,3,3,3,3,3,2,5,3,3,3,3,40,32.0,neutral or dissatisfied +46316,88149,Male,Loyal Customer,56,Business travel,Business,3207,3,3,3,3,4,5,4,5,5,5,5,3,5,3,14,15.0,satisfied +46317,65742,Female,disloyal Customer,16,Business travel,Eco,1061,1,1,1,3,2,1,1,2,4,1,4,1,3,2,27,19.0,neutral or dissatisfied +46318,124542,Male,Loyal Customer,7,Personal Travel,Eco,1276,1,5,1,1,1,1,1,1,5,3,4,5,5,1,0,2.0,neutral or dissatisfied +46319,47672,Female,Loyal Customer,30,Personal Travel,Eco,1334,2,5,2,4,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +46320,111481,Female,Loyal Customer,45,Business travel,Business,1452,5,5,5,5,2,4,5,2,2,2,2,5,2,4,90,92.0,satisfied +46321,101691,Male,Loyal Customer,30,Business travel,Business,1500,5,5,5,5,4,4,4,4,5,2,4,5,5,4,10,0.0,satisfied +46322,99010,Female,Loyal Customer,54,Business travel,Eco Plus,479,2,5,5,5,3,3,3,2,2,2,2,4,2,3,1,0.0,satisfied +46323,19964,Female,Loyal Customer,17,Personal Travel,Business,557,2,4,2,3,3,2,3,3,2,2,4,2,4,3,36,23.0,neutral or dissatisfied +46324,117939,Male,disloyal Customer,36,Business travel,Eco,255,2,1,3,4,4,3,4,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +46325,109031,Female,Loyal Customer,22,Business travel,Business,3934,2,2,2,2,5,5,5,5,5,2,5,4,4,5,8,4.0,satisfied +46326,112315,Male,Loyal Customer,33,Business travel,Business,3305,3,3,3,3,2,2,2,2,5,2,5,5,4,2,91,86.0,satisfied +46327,73452,Female,Loyal Customer,9,Personal Travel,Eco,1197,3,4,3,3,5,3,2,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +46328,107711,Female,Loyal Customer,43,Business travel,Eco,466,3,5,5,5,3,3,3,2,4,4,4,3,2,3,164,166.0,neutral or dissatisfied +46329,82525,Female,Loyal Customer,7,Personal Travel,Eco,1749,2,2,2,4,2,2,2,2,3,4,4,1,3,2,60,35.0,neutral or dissatisfied +46330,46819,Male,Loyal Customer,38,Business travel,Eco,959,4,2,4,2,4,4,4,4,1,3,2,1,5,4,0,0.0,satisfied +46331,1339,Male,Loyal Customer,59,Business travel,Business,1959,0,4,0,1,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +46332,126505,Male,Loyal Customer,60,Personal Travel,Eco,1788,2,4,2,2,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +46333,79954,Female,Loyal Customer,23,Business travel,Business,1089,1,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +46334,31799,Female,Loyal Customer,39,Personal Travel,Eco,2677,3,1,3,3,3,2,1,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +46335,6877,Female,disloyal Customer,23,Business travel,Eco,622,1,4,1,3,5,1,1,5,5,4,4,4,4,5,20,72.0,neutral or dissatisfied +46336,7385,Female,Loyal Customer,35,Business travel,Business,3485,3,3,5,3,5,5,5,4,4,4,4,4,4,3,11,14.0,satisfied +46337,2162,Female,Loyal Customer,59,Business travel,Business,3647,5,5,1,5,5,4,4,4,4,4,4,5,4,4,22,15.0,satisfied +46338,53668,Female,Loyal Customer,22,Business travel,Business,3459,3,3,3,3,4,4,4,4,4,3,4,4,1,4,13,10.0,satisfied +46339,24900,Male,disloyal Customer,36,Business travel,Business,762,3,3,3,1,5,3,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +46340,76934,Female,Loyal Customer,26,Personal Travel,Eco,1823,2,4,2,1,5,2,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +46341,71848,Male,Loyal Customer,30,Business travel,Business,1652,3,1,1,1,3,2,3,3,1,3,2,2,3,3,1,0.0,neutral or dissatisfied +46342,93935,Male,Loyal Customer,25,Business travel,Eco,507,3,3,3,3,3,3,1,3,4,1,3,3,2,3,96,83.0,neutral or dissatisfied +46343,27351,Male,Loyal Customer,47,Business travel,Eco,954,4,3,4,3,4,4,4,4,4,3,3,3,5,4,8,2.0,satisfied +46344,31686,Female,Loyal Customer,40,Business travel,Business,2862,1,4,4,4,3,2,1,1,1,1,1,4,1,3,0,12.0,neutral or dissatisfied +46345,56076,Male,Loyal Customer,48,Personal Travel,Eco,2586,3,3,3,3,3,5,5,2,3,3,4,5,2,5,12,0.0,neutral or dissatisfied +46346,12753,Male,Loyal Customer,44,Personal Travel,Eco,803,3,4,3,5,2,3,2,2,2,3,2,2,4,2,0,0.0,neutral or dissatisfied +46347,87110,Female,Loyal Customer,50,Personal Travel,Eco,594,3,2,3,3,5,3,3,2,2,3,1,1,2,3,67,50.0,neutral or dissatisfied +46348,43095,Female,Loyal Customer,11,Personal Travel,Eco,259,3,4,3,3,4,3,4,4,4,2,3,4,4,4,0,4.0,neutral or dissatisfied +46349,17539,Female,Loyal Customer,57,Personal Travel,Eco,297,2,4,2,2,4,4,4,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +46350,105933,Female,Loyal Customer,30,Business travel,Business,1491,1,3,3,3,1,1,1,1,1,2,3,1,4,1,63,58.0,neutral or dissatisfied +46351,127210,Female,disloyal Customer,37,Business travel,Eco Plus,246,4,4,4,3,2,4,2,2,3,1,3,4,3,2,23,18.0,neutral or dissatisfied +46352,56809,Male,Loyal Customer,53,Business travel,Business,1605,5,5,5,5,2,4,4,4,4,4,4,5,4,4,53,58.0,satisfied +46353,33678,Male,Loyal Customer,34,Business travel,Business,759,5,5,5,5,5,1,4,5,5,5,5,2,5,1,5,20.0,satisfied +46354,92456,Female,disloyal Customer,34,Business travel,Business,2139,3,3,3,1,3,3,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +46355,63213,Male,disloyal Customer,32,Business travel,Business,337,3,2,2,2,5,2,5,5,4,4,4,3,5,5,12,2.0,neutral or dissatisfied +46356,34857,Male,Loyal Customer,70,Personal Travel,Eco,1826,3,4,3,1,4,3,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +46357,121094,Female,Loyal Customer,46,Business travel,Business,1158,4,4,4,4,1,4,3,4,4,4,4,4,4,3,0,0.0,satisfied +46358,33762,Female,Loyal Customer,16,Personal Travel,Eco,266,3,3,3,2,2,3,2,2,4,5,5,1,4,2,0,0.0,neutral or dissatisfied +46359,62543,Female,Loyal Customer,40,Business travel,Business,1723,5,5,5,5,5,4,5,2,2,2,2,3,2,4,18,0.0,satisfied +46360,81699,Male,Loyal Customer,28,Personal Travel,Eco,907,3,4,3,5,5,3,5,5,4,4,4,4,4,5,3,0.0,neutral or dissatisfied +46361,52920,Female,Loyal Customer,49,Business travel,Business,1861,2,4,4,4,5,3,3,2,2,3,2,2,2,2,36,19.0,neutral or dissatisfied +46362,106478,Male,Loyal Customer,42,Business travel,Business,1624,2,2,2,2,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +46363,51372,Male,Loyal Customer,48,Personal Travel,Eco Plus,266,2,0,2,4,2,2,1,2,1,2,3,4,3,2,0,0.0,neutral or dissatisfied +46364,45803,Male,Loyal Customer,33,Business travel,Business,2670,1,3,3,3,1,1,1,1,4,2,3,2,3,1,26,18.0,neutral or dissatisfied +46365,73896,Male,disloyal Customer,23,Business travel,Eco,809,2,2,2,4,4,2,1,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +46366,80503,Female,Loyal Customer,55,Business travel,Business,1749,2,5,5,5,5,3,4,2,2,2,2,3,2,1,2,0.0,neutral or dissatisfied +46367,68497,Female,Loyal Customer,67,Personal Travel,Eco,1067,1,4,1,2,3,4,5,1,1,1,1,3,1,4,26,13.0,neutral or dissatisfied +46368,41981,Female,Loyal Customer,38,Business travel,Eco Plus,618,5,5,5,5,5,5,5,5,5,2,4,4,2,5,0,0.0,satisfied +46369,36753,Male,Loyal Customer,57,Business travel,Business,2611,1,1,1,1,5,5,5,5,3,5,1,5,5,5,1,0.0,satisfied +46370,73960,Female,Loyal Customer,54,Personal Travel,Eco,2342,2,4,2,3,5,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +46371,126033,Male,Loyal Customer,39,Business travel,Business,2751,1,4,1,1,3,5,5,4,4,4,4,5,4,4,0,5.0,satisfied +46372,51454,Female,Loyal Customer,65,Personal Travel,Eco Plus,158,1,2,1,3,2,3,3,1,1,1,1,4,1,4,3,27.0,neutral or dissatisfied +46373,87937,Male,disloyal Customer,39,Business travel,Business,270,2,2,2,4,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +46374,83235,Female,Loyal Customer,51,Business travel,Business,1979,4,4,3,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +46375,58169,Female,disloyal Customer,27,Business travel,Business,925,4,4,4,2,5,4,5,5,5,5,5,3,4,5,19,32.0,satisfied +46376,110002,Male,disloyal Customer,18,Business travel,Eco,1204,5,4,4,4,4,2,2,4,3,5,5,2,3,2,133,99.0,satisfied +46377,360,Male,disloyal Customer,27,Business travel,Business,113,4,4,4,5,5,4,2,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +46378,90132,Male,disloyal Customer,25,Business travel,Eco,1127,5,5,5,2,3,5,3,3,4,3,5,5,4,3,0,0.0,satisfied +46379,42006,Male,Loyal Customer,57,Business travel,Eco,116,3,4,3,4,3,3,3,3,2,4,3,3,4,3,52,50.0,neutral or dissatisfied +46380,48246,Female,Loyal Customer,12,Personal Travel,Eco,391,1,5,1,1,4,1,4,4,5,5,5,3,5,4,24,21.0,neutral or dissatisfied +46381,45458,Female,Loyal Customer,39,Business travel,Eco,587,4,2,2,2,4,4,4,4,3,3,4,3,3,4,0,0.0,satisfied +46382,105778,Male,Loyal Customer,47,Personal Travel,Eco,842,3,5,3,4,1,3,1,1,5,2,5,4,4,1,0,12.0,neutral or dissatisfied +46383,60076,Female,Loyal Customer,46,Business travel,Business,3532,2,2,2,2,2,5,5,3,3,3,3,4,3,4,72,78.0,satisfied +46384,9291,Female,Loyal Customer,31,Personal Travel,Eco,1157,3,4,3,3,5,3,5,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +46385,2663,Female,Loyal Customer,53,Business travel,Business,539,5,5,5,5,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +46386,15320,Male,Loyal Customer,50,Business travel,Eco,599,1,3,3,3,1,1,1,1,3,3,4,4,4,1,4,16.0,neutral or dissatisfied +46387,90060,Female,Loyal Customer,47,Business travel,Business,957,3,3,3,3,2,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +46388,53025,Male,Loyal Customer,53,Business travel,Business,1603,4,5,5,5,3,3,3,4,4,4,4,1,4,1,4,23.0,neutral or dissatisfied +46389,79703,Female,Loyal Customer,66,Personal Travel,Eco,760,3,4,3,3,5,4,5,1,1,3,1,3,1,5,1,0.0,neutral or dissatisfied +46390,116871,Male,disloyal Customer,20,Business travel,Business,370,5,4,5,3,1,5,1,1,3,5,4,4,4,1,23,7.0,satisfied +46391,95867,Female,Loyal Customer,52,Business travel,Business,759,1,1,1,1,3,5,4,5,5,5,5,4,5,3,16,16.0,satisfied +46392,124633,Male,Loyal Customer,7,Personal Travel,Eco,1671,2,1,2,3,2,2,1,2,4,4,3,4,4,2,0,7.0,neutral or dissatisfied +46393,45200,Male,Loyal Customer,19,Personal Travel,Eco,1120,1,4,1,5,2,1,3,2,4,4,5,4,5,2,9,9.0,neutral or dissatisfied +46394,25521,Female,Loyal Customer,60,Personal Travel,Eco,547,2,4,2,4,1,3,4,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +46395,59947,Female,Loyal Customer,52,Business travel,Eco,1068,2,5,5,5,3,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +46396,114140,Female,Loyal Customer,42,Business travel,Business,3275,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +46397,109109,Female,Loyal Customer,41,Business travel,Business,972,2,2,2,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +46398,62364,Male,disloyal Customer,25,Business travel,Business,2704,3,2,3,4,3,4,4,3,4,3,3,4,1,4,0,37.0,neutral or dissatisfied +46399,106819,Male,Loyal Customer,48,Business travel,Business,1488,2,2,2,2,3,5,5,4,4,4,4,4,4,4,12,0.0,satisfied +46400,60553,Male,Loyal Customer,43,Business travel,Business,1863,4,4,4,4,3,5,4,2,2,2,2,3,2,4,0,12.0,satisfied +46401,67569,Male,Loyal Customer,56,Business travel,Business,2557,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +46402,56620,Female,disloyal Customer,25,Business travel,Business,937,3,4,3,4,5,3,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +46403,71681,Male,Loyal Customer,20,Personal Travel,Eco,1197,3,5,3,3,2,3,2,2,1,3,1,1,3,2,0,0.0,neutral or dissatisfied +46404,122423,Female,disloyal Customer,24,Business travel,Eco,1916,4,4,4,3,4,4,3,4,3,5,3,2,3,4,16,18.0,neutral or dissatisfied +46405,63624,Male,Loyal Customer,52,Business travel,Business,3279,1,5,5,5,5,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +46406,103390,Female,Loyal Customer,50,Business travel,Business,237,2,2,3,2,4,4,4,5,5,5,5,3,5,4,5,0.0,satisfied +46407,102063,Male,Loyal Customer,34,Personal Travel,Business,223,3,5,3,4,3,4,4,2,2,3,2,4,2,4,14,9.0,neutral or dissatisfied +46408,1739,Male,Loyal Customer,50,Personal Travel,Eco,364,1,4,1,4,1,1,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +46409,23323,Female,Loyal Customer,24,Business travel,Business,456,2,3,3,3,2,2,2,2,4,4,3,4,3,2,119,116.0,neutral or dissatisfied +46410,25602,Female,Loyal Customer,26,Business travel,Eco Plus,874,4,5,5,5,4,4,4,4,5,3,3,2,5,4,0,0.0,satisfied +46411,49252,Female,disloyal Customer,47,Business travel,Eco,78,4,5,4,2,4,4,4,4,4,5,4,2,3,4,4,0.0,neutral or dissatisfied +46412,91526,Male,Loyal Customer,52,Business travel,Business,3382,4,4,4,4,4,4,5,5,5,5,5,3,5,5,18,36.0,satisfied +46413,72949,Female,Loyal Customer,50,Business travel,Eco,1096,4,4,4,4,1,4,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +46414,91367,Male,Loyal Customer,61,Personal Travel,Eco Plus,404,3,2,3,3,4,3,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +46415,128982,Male,Loyal Customer,67,Personal Travel,Eco,236,4,4,4,3,2,4,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +46416,128960,Female,disloyal Customer,41,Business travel,Business,414,3,3,3,1,5,5,5,5,2,5,2,5,3,5,0,0.0,neutral or dissatisfied +46417,22272,Male,Loyal Customer,51,Business travel,Eco,145,4,5,2,5,4,4,4,4,1,4,1,3,4,4,122,116.0,satisfied +46418,23875,Female,Loyal Customer,57,Business travel,Business,589,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +46419,65488,Male,Loyal Customer,33,Personal Travel,Eco,1303,1,5,1,4,2,1,2,2,4,4,4,4,4,2,26,6.0,neutral or dissatisfied +46420,84494,Male,Loyal Customer,47,Business travel,Business,2994,2,2,2,2,2,2,2,5,5,4,4,2,4,2,0,0.0,satisfied +46421,30508,Female,Loyal Customer,33,Business travel,Business,1620,4,5,5,5,3,4,4,1,5,4,4,4,4,4,134,145.0,neutral or dissatisfied +46422,11316,Male,Loyal Customer,8,Personal Travel,Eco,216,0,5,0,3,1,0,1,1,5,2,4,5,4,1,0,0.0,satisfied +46423,15486,Male,Loyal Customer,38,Personal Travel,Eco,399,4,4,3,1,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +46424,23820,Female,Loyal Customer,36,Personal Travel,Eco,374,2,4,2,3,5,2,5,5,3,2,5,3,3,5,0,16.0,neutral or dissatisfied +46425,48417,Male,Loyal Customer,55,Business travel,Business,819,3,3,3,3,1,4,5,4,4,4,4,1,4,1,0,0.0,satisfied +46426,30158,Male,Loyal Customer,22,Personal Travel,Eco,234,2,5,0,1,4,0,4,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +46427,50591,Male,Loyal Customer,21,Personal Travel,Eco,156,3,2,3,4,3,3,3,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +46428,24339,Male,Loyal Customer,24,Business travel,Business,634,5,5,5,5,4,4,4,4,3,1,3,4,1,4,0,3.0,satisfied +46429,48959,Female,disloyal Customer,29,Business travel,Eco,190,3,4,3,2,4,3,3,4,4,3,2,4,4,4,0,0.0,neutral or dissatisfied +46430,76,Male,disloyal Customer,55,Business travel,Eco,108,5,0,4,5,4,4,5,4,5,2,5,4,2,4,0,0.0,satisfied +46431,106373,Female,disloyal Customer,28,Business travel,Business,674,4,4,4,3,1,4,1,1,5,5,5,3,5,1,6,15.0,satisfied +46432,38426,Male,Loyal Customer,39,Personal Travel,Eco,965,1,4,1,4,3,1,3,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +46433,5542,Female,Loyal Customer,44,Personal Travel,Eco,431,3,2,3,3,5,3,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +46434,34007,Male,Loyal Customer,62,Business travel,Business,998,5,5,5,5,5,3,2,5,5,5,5,1,5,2,10,0.0,satisfied +46435,112829,Female,Loyal Customer,26,Business travel,Business,1164,2,2,1,2,5,5,5,5,4,3,4,5,5,5,0,0.0,satisfied +46436,44189,Male,Loyal Customer,48,Business travel,Eco,157,5,5,4,5,5,5,5,5,4,1,4,1,5,5,0,0.0,satisfied +46437,123184,Male,Loyal Customer,7,Personal Travel,Eco,468,5,4,5,3,4,5,4,4,4,3,4,3,4,4,0,12.0,satisfied +46438,65721,Female,Loyal Customer,50,Business travel,Business,1859,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +46439,20245,Female,Loyal Customer,47,Business travel,Eco,179,4,1,1,1,2,3,3,4,4,4,4,1,4,4,43,29.0,neutral or dissatisfied +46440,107348,Female,Loyal Customer,13,Business travel,Business,2600,4,4,4,4,5,5,5,5,5,5,5,5,5,5,0,2.0,satisfied +46441,9808,Female,Loyal Customer,22,Personal Travel,Eco,493,4,5,5,1,4,5,4,4,4,5,4,5,5,4,0,12.0,neutral or dissatisfied +46442,65606,Male,Loyal Customer,52,Business travel,Eco,237,1,3,3,3,1,1,1,1,2,3,3,1,4,1,29,40.0,neutral or dissatisfied +46443,96248,Female,Loyal Customer,67,Personal Travel,Eco,460,4,4,4,4,4,4,4,1,1,4,1,2,1,3,19,20.0,neutral or dissatisfied +46444,66825,Male,disloyal Customer,29,Business travel,Business,731,5,5,5,4,3,5,3,3,3,3,5,4,5,3,0,0.0,satisfied +46445,117854,Female,Loyal Customer,47,Business travel,Business,601,3,3,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +46446,109447,Male,disloyal Customer,26,Business travel,Business,861,2,2,2,1,3,2,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +46447,83347,Female,Loyal Customer,8,Personal Travel,Eco,187,3,1,0,2,3,0,2,3,3,5,3,4,3,3,1,0.0,neutral or dissatisfied +46448,60369,Female,Loyal Customer,41,Business travel,Business,1452,1,1,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +46449,72674,Female,Loyal Customer,39,Personal Travel,Eco,1102,1,2,2,3,4,2,4,4,4,3,3,3,3,4,0,55.0,neutral or dissatisfied +46450,646,Male,Loyal Customer,52,Business travel,Business,3811,0,0,0,4,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +46451,125705,Male,Loyal Customer,62,Personal Travel,Eco,759,2,4,2,2,1,2,1,1,4,2,5,3,4,1,75,63.0,neutral or dissatisfied +46452,7000,Female,disloyal Customer,38,Business travel,Eco,196,3,3,4,3,4,4,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +46453,23088,Female,Loyal Customer,44,Personal Travel,Eco,794,3,2,3,2,5,2,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +46454,127512,Male,Loyal Customer,15,Personal Travel,Eco,1814,2,4,2,3,2,2,5,2,1,5,4,1,3,2,0,3.0,neutral or dissatisfied +46455,126996,Male,Loyal Customer,42,Business travel,Business,2014,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +46456,125780,Male,Loyal Customer,26,Business travel,Business,1013,5,5,5,5,5,5,5,5,3,4,5,3,5,5,47,38.0,satisfied +46457,29658,Male,Loyal Customer,47,Personal Travel,Eco,909,2,4,2,2,5,2,5,5,4,1,3,3,4,5,0,0.0,neutral or dissatisfied +46458,21051,Female,Loyal Customer,52,Business travel,Business,106,1,1,1,1,2,4,3,5,5,5,3,1,5,3,0,0.0,satisfied +46459,78699,Male,disloyal Customer,25,Business travel,Business,447,3,5,3,2,2,3,3,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +46460,85951,Male,Loyal Customer,43,Business travel,Business,554,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +46461,60849,Female,Loyal Customer,55,Personal Travel,Eco,1754,2,3,1,3,1,3,2,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +46462,90302,Female,Loyal Customer,22,Personal Travel,Eco,879,3,0,3,3,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +46463,75383,Male,disloyal Customer,25,Business travel,Eco,748,0,0,0,3,1,1,1,1,3,2,4,4,5,1,20,14.0,satisfied +46464,115122,Female,disloyal Customer,25,Business travel,Business,337,1,0,1,5,1,1,1,1,3,5,5,4,4,1,39,46.0,neutral or dissatisfied +46465,72223,Female,Loyal Customer,49,Business travel,Business,919,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +46466,13136,Female,Loyal Customer,33,Personal Travel,Eco,427,3,4,3,4,3,3,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +46467,84038,Male,disloyal Customer,26,Business travel,Business,879,3,3,3,1,3,3,3,3,3,3,5,4,5,3,5,2.0,neutral or dissatisfied +46468,8765,Male,Loyal Customer,40,Business travel,Business,552,3,3,3,3,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +46469,20334,Male,Loyal Customer,60,Business travel,Business,3833,2,2,4,2,5,4,3,4,4,4,4,5,4,4,42,30.0,satisfied +46470,68740,Female,Loyal Customer,22,Business travel,Eco,585,3,3,3,3,3,3,1,3,3,5,3,3,3,3,0,6.0,neutral or dissatisfied +46471,39641,Male,Loyal Customer,48,Business travel,Eco,1190,1,5,4,4,1,1,1,1,2,5,1,1,1,1,25,60.0,neutral or dissatisfied +46472,73522,Male,disloyal Customer,22,Business travel,Business,594,5,3,5,2,3,5,3,3,4,2,5,5,4,3,9,15.0,satisfied +46473,75987,Female,Loyal Customer,60,Personal Travel,Eco,297,2,4,2,3,2,3,1,5,5,2,5,5,5,1,38,25.0,neutral or dissatisfied +46474,116008,Female,Loyal Customer,28,Personal Travel,Eco,337,4,3,4,2,3,4,3,3,2,1,3,3,5,3,38,22.0,neutral or dissatisfied +46475,79833,Female,Loyal Customer,42,Business travel,Business,1096,4,4,4,4,2,4,5,5,5,5,5,5,5,4,0,4.0,satisfied +46476,5489,Male,Loyal Customer,51,Business travel,Business,3306,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,6.0,satisfied +46477,107101,Male,Loyal Customer,19,Personal Travel,Eco,562,3,4,2,3,3,2,3,3,4,4,5,3,4,3,6,22.0,neutral or dissatisfied +46478,111584,Male,Loyal Customer,12,Personal Travel,Eco,794,1,4,1,4,1,1,1,1,4,4,5,3,5,1,7,4.0,neutral or dissatisfied +46479,22156,Male,Loyal Customer,29,Business travel,Business,3185,3,3,3,3,3,2,3,3,5,3,2,3,3,3,0,0.0,satisfied +46480,40982,Female,disloyal Customer,39,Business travel,Business,984,2,2,2,1,2,2,3,2,4,3,1,1,2,2,0,0.0,neutral or dissatisfied +46481,6317,Female,Loyal Customer,48,Business travel,Business,1848,2,2,2,2,4,5,4,5,5,5,5,4,5,4,5,8.0,satisfied +46482,11229,Male,Loyal Customer,69,Personal Travel,Eco,517,2,3,2,2,3,2,3,3,2,2,1,4,4,3,19,2.0,neutral or dissatisfied +46483,51383,Female,Loyal Customer,23,Personal Travel,Eco Plus,190,3,5,3,3,3,3,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +46484,54527,Female,Loyal Customer,9,Personal Travel,Eco,925,3,4,3,1,3,3,3,3,3,5,5,4,5,3,0,10.0,neutral or dissatisfied +46485,60336,Female,Loyal Customer,49,Business travel,Business,2999,5,5,5,5,2,4,4,5,5,5,5,4,5,4,6,0.0,satisfied +46486,129488,Female,disloyal Customer,15,Personal Travel,Eco,2704,1,0,1,4,1,1,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +46487,71380,Male,Loyal Customer,43,Business travel,Business,258,2,5,5,5,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +46488,74706,Female,Loyal Customer,18,Personal Travel,Eco,1464,2,4,2,1,3,2,3,3,4,3,5,3,4,3,19,0.0,neutral or dissatisfied +46489,78075,Female,Loyal Customer,35,Business travel,Business,2857,4,4,4,4,3,5,5,4,4,4,4,3,4,3,19,34.0,satisfied +46490,53233,Female,Loyal Customer,18,Personal Travel,Eco,589,3,4,3,1,4,3,4,4,3,4,4,4,4,4,4,0.0,neutral or dissatisfied +46491,81163,Female,disloyal Customer,32,Business travel,Business,196,3,4,4,4,3,4,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +46492,16710,Male,Loyal Customer,12,Personal Travel,Eco,284,0,5,0,3,5,0,2,5,3,3,5,3,4,5,0,0.0,satisfied +46493,68966,Female,Loyal Customer,40,Business travel,Eco,700,2,4,1,4,2,2,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +46494,5971,Female,Loyal Customer,49,Business travel,Business,2990,2,2,2,2,2,5,5,4,4,4,4,3,4,3,3,0.0,satisfied +46495,62955,Female,Loyal Customer,43,Business travel,Business,967,3,3,3,3,3,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +46496,48380,Female,Loyal Customer,54,Personal Travel,Eco,522,2,4,2,5,2,4,1,5,5,2,3,4,5,5,0,0.0,neutral or dissatisfied +46497,77849,Male,Loyal Customer,37,Business travel,Eco Plus,289,2,2,2,2,2,2,2,2,1,3,4,2,4,2,73,58.0,neutral or dissatisfied +46498,89962,Male,Loyal Customer,11,Personal Travel,Eco,1310,2,5,2,3,4,2,4,4,5,4,4,4,5,4,0,10.0,neutral or dissatisfied +46499,94590,Female,disloyal Customer,23,Business travel,Eco,189,3,2,3,3,1,3,1,1,1,5,4,2,4,1,64,62.0,neutral or dissatisfied +46500,15129,Male,Loyal Customer,48,Business travel,Business,912,1,1,4,1,2,1,2,5,5,5,5,3,5,5,75,82.0,satisfied +46501,83006,Female,Loyal Customer,47,Business travel,Eco,957,3,1,1,1,2,4,3,3,3,3,3,2,3,1,45,39.0,neutral or dissatisfied +46502,79371,Female,Loyal Customer,51,Business travel,Business,502,3,3,3,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +46503,70501,Female,Loyal Customer,33,Personal Travel,Eco,867,2,3,2,3,5,2,4,5,3,3,4,1,4,5,3,62.0,neutral or dissatisfied +46504,1607,Male,Loyal Customer,18,Personal Travel,Eco Plus,140,2,1,2,3,3,2,2,3,2,2,2,2,3,3,0,0.0,neutral or dissatisfied +46505,34065,Male,Loyal Customer,30,Personal Travel,Eco,1674,4,3,4,1,5,4,5,5,4,1,1,3,4,5,0,0.0,satisfied +46506,88282,Female,Loyal Customer,27,Business travel,Business,2758,1,5,5,5,1,1,1,1,3,5,4,4,3,1,3,0.0,neutral or dissatisfied +46507,96021,Female,Loyal Customer,15,Business travel,Business,3993,3,4,4,4,3,2,3,3,4,4,4,3,4,3,1,0.0,neutral or dissatisfied +46508,96142,Female,disloyal Customer,25,Business travel,Business,490,2,0,2,4,3,2,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +46509,57406,Female,Loyal Customer,58,Business travel,Business,455,5,5,5,5,5,4,4,3,3,4,3,5,3,3,64,62.0,satisfied +46510,18721,Male,Loyal Customer,15,Personal Travel,Eco Plus,201,4,4,4,4,2,4,4,2,2,4,2,2,3,2,0,0.0,neutral or dissatisfied +46511,80999,Female,Loyal Customer,25,Personal Travel,Eco,297,4,2,4,3,5,4,5,5,1,3,3,1,3,5,0,0.0,neutral or dissatisfied +46512,116525,Male,Loyal Customer,38,Personal Travel,Eco,373,1,3,1,4,4,1,4,4,4,4,1,3,1,4,0,0.0,neutral or dissatisfied +46513,59341,Female,Loyal Customer,41,Business travel,Business,2338,3,3,3,3,4,4,5,4,4,4,4,5,4,4,8,0.0,satisfied +46514,71500,Male,Loyal Customer,64,Personal Travel,Business,1120,3,5,3,1,4,1,1,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +46515,49366,Female,Loyal Customer,46,Business travel,Business,2365,0,5,1,4,5,3,5,5,5,5,5,2,5,2,0,0.0,satisfied +46516,25440,Female,disloyal Customer,25,Business travel,Eco,669,3,3,3,3,5,3,5,5,2,1,3,3,3,5,5,4.0,neutral or dissatisfied +46517,12562,Female,Loyal Customer,56,Personal Travel,Eco,788,2,5,2,4,5,4,4,5,5,2,4,5,5,5,0,2.0,neutral or dissatisfied +46518,98725,Male,Loyal Customer,39,Personal Travel,Eco Plus,992,4,4,4,4,2,4,2,2,4,4,4,3,3,2,0,3.0,neutral or dissatisfied +46519,20971,Female,Loyal Customer,61,Personal Travel,Eco,689,2,3,2,4,3,1,1,5,5,2,5,3,5,3,11,0.0,neutral or dissatisfied +46520,114356,Female,Loyal Customer,22,Business travel,Eco Plus,957,2,1,1,1,2,2,2,2,4,4,3,1,4,2,5,1.0,neutral or dissatisfied +46521,78283,Male,disloyal Customer,31,Business travel,Eco,805,2,2,2,3,3,2,3,3,3,4,3,2,2,3,0,18.0,neutral or dissatisfied +46522,70046,Male,Loyal Customer,43,Personal Travel,Eco,583,5,5,5,1,5,5,4,5,3,4,4,4,4,5,13,0.0,satisfied +46523,66065,Male,Loyal Customer,60,Personal Travel,Eco,1055,1,4,1,3,1,1,1,1,1,1,3,2,4,1,21,14.0,neutral or dissatisfied +46524,59882,Male,disloyal Customer,43,Business travel,Business,997,5,5,5,1,5,5,5,5,3,5,4,4,4,5,3,0.0,satisfied +46525,2337,Female,Loyal Customer,15,Personal Travel,Eco,690,4,5,3,2,4,3,3,4,2,2,4,4,3,4,0,11.0,neutral or dissatisfied +46526,4327,Female,Loyal Customer,61,Personal Travel,Eco,589,3,5,4,1,5,4,5,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +46527,81170,Female,disloyal Customer,33,Business travel,Business,196,1,1,1,4,3,1,3,3,4,4,4,3,4,3,108,119.0,neutral or dissatisfied +46528,67625,Male,Loyal Customer,45,Business travel,Business,1464,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +46529,40147,Female,Loyal Customer,69,Personal Travel,Eco,840,3,3,3,3,5,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +46530,22585,Female,Loyal Customer,60,Business travel,Eco,300,4,4,4,4,5,3,5,4,4,4,4,3,4,1,0,0.0,satisfied +46531,124226,Male,Loyal Customer,30,Business travel,Business,1916,1,1,1,1,4,5,4,4,5,4,5,3,5,4,0,0.0,satisfied +46532,10532,Female,Loyal Customer,54,Business travel,Business,3392,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +46533,71156,Female,Loyal Customer,46,Business travel,Business,646,2,4,4,4,1,4,4,2,2,2,2,2,2,3,10,0.0,neutral or dissatisfied +46534,82813,Female,Loyal Customer,61,Personal Travel,Eco,235,3,4,3,3,4,5,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +46535,41525,Female,Loyal Customer,42,Business travel,Business,1504,1,1,4,1,5,3,1,5,5,5,5,3,5,2,0,47.0,satisfied +46536,6997,Male,Loyal Customer,52,Business travel,Business,3454,3,5,5,5,3,3,3,4,3,3,3,3,3,3,88,138.0,neutral or dissatisfied +46537,91501,Female,disloyal Customer,38,Business travel,Business,391,4,4,4,5,2,4,3,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +46538,37913,Female,Loyal Customer,31,Personal Travel,Eco,937,1,4,1,3,1,5,5,3,3,5,4,5,4,5,161,168.0,neutral or dissatisfied +46539,46852,Female,Loyal Customer,47,Business travel,Business,3536,4,3,4,4,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +46540,121773,Male,Loyal Customer,42,Business travel,Business,337,2,4,2,2,5,4,5,5,5,5,5,3,5,4,47,18.0,satisfied +46541,38909,Male,Loyal Customer,31,Business travel,Eco,162,4,3,3,3,4,4,4,4,2,2,4,3,3,4,74,101.0,neutral or dissatisfied +46542,72802,Male,Loyal Customer,37,Personal Travel,Eco,1045,1,4,1,2,2,1,2,2,5,2,4,5,4,2,15,2.0,neutral or dissatisfied +46543,87663,Male,Loyal Customer,44,Business travel,Business,606,2,4,2,2,5,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +46544,5611,Male,Loyal Customer,54,Business travel,Business,3888,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +46545,83296,Male,Loyal Customer,70,Personal Travel,Eco,1979,3,3,3,5,2,3,2,2,1,4,4,4,5,2,15,12.0,neutral or dissatisfied +46546,40502,Male,Loyal Customer,28,Personal Travel,Eco,188,3,5,3,4,3,3,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +46547,60667,Male,Loyal Customer,32,Personal Travel,Eco,1620,5,5,5,1,3,5,3,3,3,3,4,4,4,3,0,0.0,satisfied +46548,67902,Female,Loyal Customer,7,Personal Travel,Eco,1188,4,4,4,5,1,4,1,1,4,2,4,5,4,1,0,0.0,satisfied +46549,92870,Female,Loyal Customer,24,Personal Travel,Eco,2519,1,4,1,2,3,1,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +46550,112223,Female,Loyal Customer,79,Business travel,Business,799,3,2,2,2,5,4,4,3,3,3,3,3,3,4,9,0.0,neutral or dissatisfied +46551,51545,Female,Loyal Customer,41,Business travel,Eco,455,5,2,2,2,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +46552,46775,Male,Loyal Customer,14,Personal Travel,Eco Plus,125,1,4,1,4,3,1,3,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +46553,28978,Male,Loyal Customer,30,Business travel,Business,1050,2,2,2,2,5,5,5,5,5,3,4,1,2,5,0,0.0,satisfied +46554,6420,Male,Loyal Customer,65,Personal Travel,Eco,296,2,5,2,5,5,2,5,5,3,4,4,4,4,5,2,36.0,neutral or dissatisfied +46555,74234,Female,Loyal Customer,44,Personal Travel,Eco,888,4,4,4,3,4,3,3,2,2,3,3,3,1,3,154,135.0,neutral or dissatisfied +46556,22963,Female,Loyal Customer,8,Business travel,Business,641,2,3,3,3,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +46557,31112,Male,disloyal Customer,28,Business travel,Business,991,4,4,4,1,2,4,2,2,3,2,5,5,4,2,6,4.0,neutral or dissatisfied +46558,34204,Male,Loyal Customer,70,Personal Travel,Eco,1063,2,4,2,2,5,2,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +46559,80003,Female,Loyal Customer,34,Personal Travel,Eco,944,5,1,5,2,1,5,1,1,2,3,3,1,2,1,0,0.0,satisfied +46560,15096,Female,Loyal Customer,38,Personal Travel,Eco,322,4,3,4,1,1,4,1,1,3,2,2,3,4,1,0,0.0,neutral or dissatisfied +46561,78544,Male,Loyal Customer,64,Personal Travel,Eco,526,3,4,4,2,4,4,4,4,5,3,5,4,4,4,1,0.0,neutral or dissatisfied +46562,114890,Male,Loyal Customer,58,Business travel,Business,2749,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +46563,80208,Male,Loyal Customer,34,Personal Travel,Eco Plus,2586,3,3,3,4,3,1,1,4,5,4,2,1,3,1,202,,neutral or dissatisfied +46564,69290,Male,Loyal Customer,47,Business travel,Business,2173,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +46565,54781,Female,Loyal Customer,19,Personal Travel,Eco Plus,956,3,5,3,2,5,3,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +46566,68666,Male,Loyal Customer,34,Business travel,Business,2143,4,2,2,2,2,3,4,4,4,4,4,3,4,4,47,41.0,neutral or dissatisfied +46567,128163,Female,Loyal Customer,59,Business travel,Eco,1849,3,4,4,4,4,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +46568,43571,Male,Loyal Customer,41,Business travel,Eco,1499,4,4,4,4,4,4,4,4,4,4,3,1,1,4,25,40.0,satisfied +46569,18538,Male,disloyal Customer,26,Business travel,Eco,253,3,0,3,4,3,3,3,3,3,5,2,4,5,3,48,34.0,neutral or dissatisfied +46570,27651,Female,disloyal Customer,29,Business travel,Eco Plus,937,2,2,2,3,3,2,3,3,3,2,4,1,3,3,0,0.0,neutral or dissatisfied +46571,109507,Male,Loyal Customer,30,Business travel,Business,2604,4,4,4,4,5,5,5,5,5,3,4,3,4,5,2,0.0,satisfied +46572,92517,Male,Loyal Customer,34,Personal Travel,Eco,1919,1,4,1,2,3,1,5,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +46573,6776,Male,disloyal Customer,38,Business travel,Business,235,4,4,4,5,3,4,4,3,3,4,4,5,5,3,48,40.0,satisfied +46574,110602,Female,Loyal Customer,11,Personal Travel,Eco,551,3,3,3,1,1,3,1,1,5,5,5,5,5,1,9,2.0,neutral or dissatisfied +46575,125576,Female,disloyal Customer,26,Business travel,Business,226,2,2,2,1,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +46576,80660,Female,disloyal Customer,24,Business travel,Business,821,0,4,0,1,5,0,5,5,3,5,5,3,5,5,12,0.0,satisfied +46577,70939,Male,Loyal Customer,43,Business travel,Eco,212,4,4,4,4,4,4,4,4,5,4,1,1,4,4,0,0.0,satisfied +46578,68779,Female,Loyal Customer,33,Business travel,Business,926,2,2,2,2,5,5,5,3,4,4,5,5,4,5,310,307.0,satisfied +46579,124757,Male,Loyal Customer,55,Business travel,Business,2096,1,1,2,1,2,5,4,4,4,4,4,4,4,5,25,22.0,satisfied +46580,35776,Female,disloyal Customer,27,Business travel,Eco,200,1,1,1,4,1,1,1,1,4,5,3,2,4,1,0,0.0,neutral or dissatisfied +46581,9252,Female,Loyal Customer,14,Personal Travel,Eco,157,3,5,3,4,2,3,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +46582,117417,Male,Loyal Customer,39,Business travel,Business,1460,1,1,1,1,5,4,5,5,5,5,5,5,5,3,30,17.0,satisfied +46583,7976,Female,disloyal Customer,20,Business travel,Eco Plus,594,3,4,3,3,3,1,1,1,2,4,3,1,1,1,141,129.0,neutral or dissatisfied +46584,43924,Male,Loyal Customer,41,Personal Travel,Eco,174,3,3,3,4,5,3,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +46585,40319,Female,Loyal Customer,48,Business travel,Eco Plus,402,5,1,1,1,2,4,3,4,4,5,4,5,4,4,0,0.0,satisfied +46586,23280,Male,disloyal Customer,27,Business travel,Eco,456,1,3,1,1,2,1,2,2,5,5,1,1,5,2,0,0.0,neutral or dissatisfied +46587,47541,Female,Loyal Customer,57,Personal Travel,Eco,599,1,5,1,4,1,1,3,3,3,1,1,1,3,2,0,0.0,neutral or dissatisfied +46588,12272,Male,disloyal Customer,27,Business travel,Eco,253,4,0,4,2,5,4,5,5,3,1,4,1,2,5,0,0.0,satisfied +46589,34918,Male,Loyal Customer,23,Business travel,Business,3711,4,4,4,4,5,5,5,5,1,3,1,1,1,5,37,26.0,satisfied +46590,28340,Female,Loyal Customer,47,Business travel,Business,3664,2,2,2,2,1,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +46591,2164,Female,Loyal Customer,45,Business travel,Business,685,4,4,4,4,4,5,5,5,5,5,5,4,5,3,30,21.0,satisfied +46592,998,Male,Loyal Customer,37,Business travel,Eco,158,3,4,4,4,3,3,3,3,4,2,2,1,1,3,0,0.0,neutral or dissatisfied +46593,70959,Male,Loyal Customer,51,Business travel,Business,802,3,2,2,2,2,3,4,3,3,3,3,1,3,3,4,0.0,neutral or dissatisfied +46594,20455,Male,Loyal Customer,27,Business travel,Business,84,5,5,5,5,5,5,4,5,5,1,1,1,3,5,0,0.0,satisfied +46595,5820,Female,Loyal Customer,43,Personal Travel,Eco,157,4,3,4,3,3,5,4,1,1,4,1,1,1,4,0,0.0,neutral or dissatisfied +46596,39124,Female,Loyal Customer,40,Business travel,Business,119,2,2,2,2,2,3,4,4,4,4,2,4,4,2,0,0.0,neutral or dissatisfied +46597,15769,Female,disloyal Customer,48,Business travel,Eco,198,5,3,5,5,5,5,5,5,4,5,5,1,4,5,0,0.0,satisfied +46598,129749,Male,Loyal Customer,47,Business travel,Eco,337,4,2,4,2,4,4,4,4,3,1,5,4,1,4,0,0.0,satisfied +46599,78457,Male,Loyal Customer,54,Business travel,Business,1871,4,3,4,4,3,5,5,4,4,4,4,5,4,5,108,130.0,satisfied +46600,90974,Male,Loyal Customer,45,Business travel,Eco,646,3,3,2,3,3,3,3,3,4,2,4,4,4,3,4,0.0,neutral or dissatisfied +46601,94597,Female,Loyal Customer,55,Business travel,Business,3679,4,4,4,4,3,4,5,4,4,4,4,3,4,4,7,3.0,satisfied +46602,95232,Female,Loyal Customer,58,Personal Travel,Eco,293,2,2,2,3,3,3,3,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +46603,61564,Female,Loyal Customer,61,Personal Travel,Eco Plus,2419,5,3,5,3,4,5,1,1,1,5,1,4,1,1,0,0.0,satisfied +46604,78822,Male,Loyal Customer,68,Personal Travel,Eco,554,3,4,3,5,4,3,4,4,5,2,4,4,5,4,7,0.0,neutral or dissatisfied +46605,90206,Female,Loyal Customer,31,Personal Travel,Eco,1127,2,4,2,5,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +46606,55009,Female,disloyal Customer,22,Business travel,Business,1379,5,0,5,1,3,5,3,3,3,4,5,3,4,3,0,5.0,satisfied +46607,102382,Male,Loyal Customer,38,Business travel,Eco,397,5,4,4,4,5,5,5,5,4,5,4,3,2,5,0,0.0,satisfied +46608,55066,Female,disloyal Customer,27,Business travel,Eco,1608,2,2,2,3,2,2,2,2,1,3,3,2,3,2,0,7.0,neutral or dissatisfied +46609,113826,Male,Loyal Customer,56,Personal Travel,Eco Plus,236,3,4,3,2,5,3,5,5,5,4,4,5,4,5,25,23.0,neutral or dissatisfied +46610,7424,Male,Loyal Customer,41,Business travel,Business,552,1,1,1,1,4,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +46611,37504,Male,disloyal Customer,20,Business travel,Eco,1056,3,3,3,3,5,3,5,5,2,4,2,4,2,5,13,7.0,neutral or dissatisfied +46612,68794,Male,Loyal Customer,61,Business travel,Business,621,2,4,4,4,2,4,4,2,2,2,2,4,2,4,0,21.0,neutral or dissatisfied +46613,55606,Female,disloyal Customer,22,Business travel,Business,404,3,3,3,3,5,3,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +46614,67185,Male,disloyal Customer,25,Personal Travel,Eco,1017,4,3,4,4,2,4,2,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +46615,13782,Female,Loyal Customer,38,Business travel,Eco,478,2,3,3,3,2,2,2,2,3,5,1,4,1,2,0,0.0,neutral or dissatisfied +46616,83790,Male,disloyal Customer,35,Business travel,Business,425,1,1,1,4,2,1,5,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +46617,4919,Female,Loyal Customer,44,Business travel,Eco,1020,1,1,1,1,5,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +46618,42471,Male,Loyal Customer,59,Business travel,Business,2021,1,1,1,1,5,3,2,5,5,5,5,2,5,2,35,34.0,satisfied +46619,19766,Male,Loyal Customer,69,Business travel,Eco Plus,462,2,2,3,2,3,2,3,3,3,1,4,4,4,3,0,0.0,neutral or dissatisfied +46620,44256,Male,disloyal Customer,19,Business travel,Eco,359,3,1,2,4,3,2,3,3,1,5,4,3,4,3,0,0.0,neutral or dissatisfied +46621,14408,Female,Loyal Customer,8,Personal Travel,Eco Plus,900,3,4,3,1,2,3,2,2,3,1,1,2,3,2,0,0.0,neutral or dissatisfied +46622,38318,Female,Loyal Customer,44,Personal Travel,Eco,1666,1,2,2,3,3,3,3,5,5,2,5,2,5,2,0,0.0,neutral or dissatisfied +46623,107064,Female,Loyal Customer,23,Personal Travel,Eco,395,3,5,3,3,2,3,2,2,3,4,5,3,4,2,13,0.0,neutral or dissatisfied +46624,101463,Female,Loyal Customer,64,Business travel,Business,1709,0,0,0,2,3,4,5,3,3,5,5,5,3,4,16,2.0,satisfied +46625,125274,Female,Loyal Customer,13,Personal Travel,Eco,1488,3,3,3,5,1,3,1,1,4,2,3,1,1,1,0,30.0,neutral or dissatisfied +46626,78148,Female,Loyal Customer,46,Business travel,Business,3444,0,5,0,3,3,5,4,4,4,2,2,4,4,3,16,16.0,satisfied +46627,56441,Male,Loyal Customer,55,Business travel,Business,319,1,1,1,1,1,3,1,5,5,5,5,5,5,2,37,13.0,satisfied +46628,115751,Female,Loyal Customer,40,Business travel,Business,480,5,5,4,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +46629,42578,Male,Loyal Customer,9,Personal Travel,Eco,240,3,5,0,5,4,0,4,4,5,4,4,4,5,4,21,26.0,neutral or dissatisfied +46630,19858,Female,Loyal Customer,42,Business travel,Business,2384,2,2,2,2,1,4,3,2,2,2,2,2,2,2,16,14.0,neutral or dissatisfied +46631,33718,Male,Loyal Customer,48,Personal Travel,Eco,899,2,5,3,2,1,3,1,1,5,3,5,5,4,1,14,19.0,neutral or dissatisfied +46632,119178,Female,Loyal Customer,54,Business travel,Eco,290,4,2,2,2,3,1,1,4,4,4,4,1,4,3,0,20.0,neutral or dissatisfied +46633,115606,Female,Loyal Customer,63,Business travel,Business,1545,1,1,1,1,5,4,5,3,3,2,3,3,3,3,46,37.0,satisfied +46634,115427,Female,Loyal Customer,55,Business travel,Eco,308,2,3,3,3,5,3,4,2,2,2,2,1,2,2,33,37.0,neutral or dissatisfied +46635,1092,Male,Loyal Customer,68,Personal Travel,Eco,396,3,5,3,4,4,3,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +46636,58028,Male,Loyal Customer,43,Personal Travel,Eco,1721,2,1,2,3,3,2,3,3,2,4,3,1,4,3,99,111.0,neutral or dissatisfied +46637,29012,Female,Loyal Customer,52,Business travel,Business,3558,2,2,2,2,3,5,4,5,5,5,3,1,5,1,0,0.0,satisfied +46638,47947,Male,Loyal Customer,43,Personal Travel,Eco,550,2,2,2,4,5,2,4,5,3,5,4,3,4,5,7,7.0,neutral or dissatisfied +46639,107675,Male,Loyal Customer,48,Business travel,Business,3274,0,0,0,2,3,5,5,3,3,3,3,3,3,4,11,11.0,satisfied +46640,110135,Male,Loyal Customer,28,Business travel,Eco,869,3,1,1,1,3,3,3,3,1,1,3,3,2,3,116,103.0,neutral or dissatisfied +46641,75044,Female,Loyal Customer,7,Personal Travel,Eco,236,1,5,1,3,5,1,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +46642,69104,Female,disloyal Customer,10,Business travel,Business,1389,4,0,4,2,2,4,2,2,3,5,5,5,5,2,0,0.0,satisfied +46643,6326,Female,Loyal Customer,29,Business travel,Business,1834,3,3,3,3,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +46644,119422,Male,Loyal Customer,54,Personal Travel,Eco,399,3,4,3,2,5,3,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +46645,57660,Female,Loyal Customer,64,Personal Travel,Eco,200,2,3,2,5,3,5,2,1,1,2,1,3,1,4,0,15.0,neutral or dissatisfied +46646,6513,Male,Loyal Customer,36,Business travel,Business,646,4,4,4,4,5,5,5,3,5,5,4,5,5,5,156,200.0,satisfied +46647,108472,Female,Loyal Customer,29,Personal Travel,Eco,1444,4,0,4,4,3,4,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +46648,36337,Male,Loyal Customer,58,Personal Travel,Eco,187,1,4,1,3,5,1,5,5,1,2,4,1,4,5,11,14.0,neutral or dissatisfied +46649,81925,Female,Loyal Customer,54,Business travel,Business,1135,4,1,5,5,4,4,3,4,4,4,4,4,4,3,6,0.0,neutral or dissatisfied +46650,27676,Female,Loyal Customer,51,Business travel,Eco,1107,3,4,3,3,2,3,4,3,3,3,3,4,3,5,2,0.0,satisfied +46651,75578,Male,Loyal Customer,61,Business travel,Eco,337,2,4,4,4,1,2,1,1,3,3,2,1,3,1,0,34.0,neutral or dissatisfied +46652,21288,Female,Loyal Customer,32,Business travel,Business,714,3,3,3,3,3,5,3,3,3,3,2,5,3,3,0,0.0,satisfied +46653,91797,Female,Loyal Customer,45,Personal Travel,Eco,590,1,2,1,3,2,4,3,4,4,1,4,3,4,4,3,4.0,neutral or dissatisfied +46654,118594,Female,disloyal Customer,34,Business travel,Eco,370,2,4,2,3,2,2,2,2,2,5,3,3,4,2,35,30.0,neutral or dissatisfied +46655,103567,Male,Loyal Customer,41,Business travel,Business,3303,4,4,4,4,3,5,4,4,4,4,4,3,4,4,12,5.0,satisfied +46656,112088,Male,Loyal Customer,50,Personal Travel,Eco,1491,3,4,4,3,1,4,1,1,4,2,3,3,4,1,0,0.0,neutral or dissatisfied +46657,121722,Male,Loyal Customer,29,Personal Travel,Eco Plus,683,4,4,4,3,1,4,4,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +46658,69681,Female,Loyal Customer,32,Personal Travel,Eco,569,4,3,4,3,5,4,5,5,1,2,3,4,4,5,0,0.0,neutral or dissatisfied +46659,43730,Female,Loyal Customer,46,Personal Travel,Eco Plus,257,2,3,2,3,1,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +46660,97622,Male,Loyal Customer,41,Business travel,Eco,764,2,5,4,5,2,2,2,2,1,4,3,2,3,2,1,0.0,neutral or dissatisfied +46661,103850,Male,Loyal Customer,25,Business travel,Eco,882,2,1,1,1,2,2,1,2,3,3,2,3,2,2,14,12.0,neutral or dissatisfied +46662,48714,Female,Loyal Customer,42,Business travel,Business,250,0,0,0,3,2,5,4,3,3,3,3,3,3,5,4,0.0,satisfied +46663,30621,Female,disloyal Customer,50,Business travel,Eco,524,1,0,1,4,1,1,1,1,2,3,4,2,3,1,0,8.0,neutral or dissatisfied +46664,103101,Male,Loyal Customer,41,Personal Travel,Eco,460,3,4,3,3,2,3,2,2,4,5,5,4,5,2,12,7.0,neutral or dissatisfied +46665,127359,Male,Loyal Customer,18,Personal Travel,Eco,507,3,5,3,4,4,3,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +46666,75971,Male,Loyal Customer,57,Business travel,Business,3651,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +46667,70676,Female,disloyal Customer,40,Business travel,Business,447,4,4,4,2,4,4,4,4,3,2,5,4,5,4,0,2.0,satisfied +46668,95272,Male,Loyal Customer,28,Personal Travel,Eco,192,3,4,0,5,3,0,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +46669,25492,Female,Loyal Customer,39,Business travel,Business,547,2,2,2,2,4,2,4,4,4,4,4,2,4,3,16,0.0,satisfied +46670,9448,Male,Loyal Customer,41,Business travel,Business,3149,2,1,1,1,5,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +46671,52508,Male,Loyal Customer,7,Personal Travel,Business,119,2,1,0,3,2,0,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +46672,83405,Female,Loyal Customer,50,Business travel,Business,3831,2,3,2,2,4,5,4,3,3,3,3,4,3,3,0,2.0,satisfied +46673,103081,Female,Loyal Customer,35,Personal Travel,Eco,460,4,5,4,5,4,4,4,4,3,5,5,5,5,4,0,18.0,neutral or dissatisfied +46674,21691,Male,disloyal Customer,37,Business travel,Business,346,2,2,2,3,4,2,5,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +46675,129449,Female,Loyal Customer,42,Personal Travel,Eco,236,4,1,4,2,2,2,2,1,1,4,1,2,1,2,3,2.0,satisfied +46676,97853,Male,Loyal Customer,41,Business travel,Business,612,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +46677,46527,Male,Loyal Customer,53,Business travel,Eco,73,4,3,3,3,4,4,4,4,4,3,5,2,2,4,0,0.0,satisfied +46678,98678,Male,Loyal Customer,46,Personal Travel,Eco,992,1,4,1,4,5,1,5,5,5,2,4,5,5,5,2,0.0,neutral or dissatisfied +46679,83517,Female,Loyal Customer,37,Personal Travel,Eco,946,3,1,3,4,1,3,1,1,2,2,4,1,4,1,0,3.0,neutral or dissatisfied +46680,91004,Female,disloyal Customer,27,Personal Travel,Eco,270,2,4,0,4,4,0,4,4,3,2,5,3,4,4,13,1.0,neutral or dissatisfied +46681,23969,Female,disloyal Customer,10,Business travel,Eco,596,3,4,3,3,3,3,3,3,1,2,4,4,3,3,29,9.0,neutral or dissatisfied +46682,20863,Male,Loyal Customer,23,Personal Travel,Eco,534,0,4,0,4,4,0,4,4,5,4,4,4,4,4,0,0.0,satisfied +46683,13580,Female,Loyal Customer,55,Personal Travel,Eco,214,2,4,2,3,4,4,4,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +46684,15977,Male,Loyal Customer,46,Business travel,Business,2064,2,1,1,1,2,4,3,2,2,2,2,3,2,1,0,11.0,neutral or dissatisfied +46685,19087,Female,Loyal Customer,46,Business travel,Eco,296,4,5,5,5,1,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +46686,67845,Female,Loyal Customer,58,Personal Travel,Eco,1464,2,5,2,4,4,5,4,2,2,2,5,4,2,3,1,0.0,neutral or dissatisfied +46687,30860,Female,Loyal Customer,53,Business travel,Eco,1546,5,4,4,4,4,2,1,5,5,5,5,5,5,4,0,0.0,satisfied +46688,28863,Female,disloyal Customer,25,Business travel,Eco,1050,4,4,4,3,3,4,3,3,3,2,2,2,2,3,0,0.0,neutral or dissatisfied +46689,29601,Male,Loyal Customer,33,Business travel,Business,680,2,1,1,1,2,2,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +46690,69324,Female,disloyal Customer,42,Business travel,Business,1035,1,1,1,2,3,1,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +46691,79393,Male,Loyal Customer,40,Business travel,Eco,241,2,4,2,2,2,2,2,2,2,4,3,2,3,2,0,4.0,neutral or dissatisfied +46692,126383,Male,Loyal Customer,65,Personal Travel,Eco,507,2,4,2,2,1,2,1,1,5,3,4,4,4,1,2,5.0,neutral or dissatisfied +46693,93457,Male,Loyal Customer,57,Personal Travel,Eco,605,3,5,3,5,2,3,2,2,3,5,5,3,5,2,16,18.0,neutral or dissatisfied +46694,60324,Female,Loyal Customer,42,Business travel,Business,2303,2,2,2,2,4,4,5,3,3,4,3,5,3,3,6,0.0,satisfied +46695,87457,Female,Loyal Customer,49,Business travel,Business,3156,3,3,3,3,5,4,5,5,5,5,5,3,5,4,38,50.0,satisfied +46696,121417,Male,Loyal Customer,40,Business travel,Business,2613,0,0,0,3,4,4,4,2,2,2,2,5,2,3,0,3.0,satisfied +46697,116101,Female,Loyal Customer,63,Personal Travel,Eco,342,2,5,2,1,4,4,5,4,4,2,4,5,4,5,6,0.0,neutral or dissatisfied +46698,73182,Male,disloyal Customer,35,Business travel,Business,1258,3,3,3,3,3,3,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +46699,91523,Male,Loyal Customer,60,Personal Travel,Eco Plus,1620,3,5,3,1,1,3,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +46700,14734,Male,Loyal Customer,54,Business travel,Business,533,1,1,1,1,2,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +46701,57894,Female,disloyal Customer,20,Business travel,Eco,305,4,5,4,5,1,4,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +46702,44572,Female,disloyal Customer,33,Business travel,Eco,177,3,1,3,4,3,4,4,1,2,4,4,4,1,4,120,137.0,neutral or dissatisfied +46703,93064,Female,Loyal Customer,67,Business travel,Eco,297,5,5,2,2,2,1,3,5,5,5,5,2,5,2,33,19.0,satisfied +46704,114036,Female,Loyal Customer,42,Business travel,Business,3956,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +46705,56075,Female,Loyal Customer,58,Personal Travel,Eco,2475,3,2,2,3,2,5,5,1,1,3,3,5,3,5,65,103.0,neutral or dissatisfied +46706,6722,Male,Loyal Customer,61,Business travel,Business,403,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +46707,70855,Male,disloyal Customer,29,Business travel,Eco,761,2,2,2,3,3,2,3,3,2,3,4,4,4,3,0,12.0,neutral or dissatisfied +46708,76674,Female,Loyal Customer,56,Personal Travel,Eco,534,2,4,2,1,3,5,4,1,1,2,1,4,1,4,59,65.0,neutral or dissatisfied +46709,8704,Male,Loyal Customer,68,Personal Travel,Eco,280,3,4,3,3,4,3,5,4,5,5,4,4,4,4,7,6.0,neutral or dissatisfied +46710,80706,Female,Loyal Customer,38,Personal Travel,Eco,1013,2,4,2,4,5,2,5,5,2,5,5,4,3,5,44,12.0,neutral or dissatisfied +46711,118986,Male,Loyal Customer,31,Business travel,Business,3354,4,4,4,4,4,5,4,4,3,4,5,4,4,4,38,47.0,satisfied +46712,44294,Male,Loyal Customer,56,Business travel,Business,2668,3,3,4,3,2,3,5,5,5,5,5,2,5,4,0,0.0,satisfied +46713,18019,Male,Loyal Customer,63,Business travel,Eco Plus,296,4,5,5,5,4,4,4,4,3,5,4,1,4,4,0,0.0,satisfied +46714,113546,Female,Loyal Customer,63,Business travel,Business,3762,1,1,1,1,4,4,4,5,5,5,5,3,5,3,15,12.0,satisfied +46715,96987,Male,Loyal Customer,58,Business travel,Business,3216,2,2,2,2,2,2,2,2,2,2,2,1,2,3,7,12.0,neutral or dissatisfied +46716,65537,Male,Loyal Customer,51,Business travel,Business,1901,3,3,3,3,3,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +46717,333,Female,disloyal Customer,37,Business travel,Eco,421,5,3,5,3,2,5,2,2,5,2,1,1,3,2,5,15.0,satisfied +46718,116949,Male,disloyal Customer,20,Business travel,Business,368,0,5,0,2,2,0,2,2,5,5,4,5,5,2,9,0.0,satisfied +46719,89182,Male,Loyal Customer,25,Personal Travel,Eco,2139,2,5,2,3,2,2,2,2,5,2,4,4,5,2,77,57.0,neutral or dissatisfied +46720,129052,Male,Loyal Customer,24,Business travel,Business,1744,4,4,4,4,4,4,4,4,3,3,4,4,4,4,0,3.0,satisfied +46721,89829,Female,Loyal Customer,45,Personal Travel,Eco Plus,1035,4,5,5,5,2,5,5,4,4,5,4,3,4,3,0,24.0,neutral or dissatisfied +46722,114766,Male,disloyal Customer,22,Business travel,Eco,417,2,0,2,3,2,2,2,2,5,4,4,3,5,2,39,37.0,neutral or dissatisfied +46723,74174,Male,Loyal Customer,33,Personal Travel,Eco,592,4,5,4,2,4,4,4,4,5,1,1,5,1,4,0,0.0,neutral or dissatisfied +46724,42990,Male,Loyal Customer,36,Business travel,Eco,236,3,4,4,4,3,3,3,3,4,5,4,4,2,3,1,0.0,satisfied +46725,50547,Female,Loyal Customer,70,Personal Travel,Eco,86,2,5,0,4,2,2,5,3,3,0,3,5,3,5,41,40.0,neutral or dissatisfied +46726,32761,Male,disloyal Customer,34,Business travel,Business,216,1,1,1,3,1,1,1,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +46727,77026,Female,Loyal Customer,30,Business travel,Business,368,3,5,3,3,4,4,4,4,5,1,4,1,2,4,2,1.0,satisfied +46728,97660,Male,Loyal Customer,34,Business travel,Business,491,2,5,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +46729,66339,Female,Loyal Customer,39,Business travel,Business,1637,3,3,3,3,5,4,5,5,5,5,5,4,5,5,35,25.0,satisfied +46730,93384,Female,Loyal Customer,54,Business travel,Business,605,1,1,1,1,2,4,4,4,4,4,4,3,4,4,3,0.0,satisfied +46731,118998,Male,Loyal Customer,35,Business travel,Business,3835,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +46732,94661,Male,disloyal Customer,25,Business travel,Business,248,4,4,4,1,2,4,2,2,4,3,5,4,5,2,4,0.0,neutral or dissatisfied +46733,120735,Female,Loyal Customer,45,Business travel,Business,1557,2,2,2,2,3,3,4,2,2,2,2,1,2,4,8,18.0,neutral or dissatisfied +46734,60489,Female,Loyal Customer,33,Business travel,Business,862,3,5,5,5,3,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +46735,70439,Male,Loyal Customer,33,Business travel,Eco,187,3,4,4,4,3,2,3,3,2,4,2,2,2,3,6,0.0,neutral or dissatisfied +46736,117931,Male,Loyal Customer,44,Business travel,Business,2059,3,3,3,3,2,4,5,5,5,5,5,4,5,4,4,20.0,satisfied +46737,16812,Female,Loyal Customer,23,Business travel,Business,645,3,3,3,3,5,5,5,5,5,4,5,2,5,5,0,0.0,satisfied +46738,63553,Male,Loyal Customer,51,Business travel,Business,1009,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +46739,100274,Female,disloyal Customer,26,Business travel,Business,1101,3,5,3,4,3,3,3,3,4,4,5,4,5,3,0,12.0,neutral or dissatisfied +46740,84015,Male,Loyal Customer,21,Personal Travel,Eco,321,3,5,3,4,3,3,3,3,2,4,2,4,5,3,22,20.0,neutral or dissatisfied +46741,40877,Male,Loyal Customer,39,Personal Travel,Eco,590,1,3,1,1,5,1,4,5,3,4,4,3,3,5,0,9.0,neutral or dissatisfied +46742,62353,Female,Loyal Customer,18,Personal Travel,Eco,1735,1,4,1,4,2,1,2,2,4,5,3,4,4,2,10,28.0,neutral or dissatisfied +46743,49146,Male,disloyal Customer,22,Business travel,Eco,156,4,0,4,3,5,4,5,5,4,5,4,3,4,5,22,27.0,neutral or dissatisfied +46744,80688,Female,Loyal Customer,39,Business travel,Business,2000,3,3,1,3,4,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +46745,75194,Male,Loyal Customer,30,Business travel,Business,1744,2,2,2,2,2,1,2,2,1,5,4,4,4,2,0,29.0,neutral or dissatisfied +46746,55802,Male,Loyal Customer,41,Business travel,Business,1416,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +46747,28343,Male,Loyal Customer,68,Personal Travel,Eco,867,2,5,2,3,5,2,5,5,3,4,4,2,5,5,0,0.0,neutral or dissatisfied +46748,58758,Female,Loyal Customer,47,Business travel,Eco,1005,1,2,2,2,3,3,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +46749,3358,Male,disloyal Customer,25,Business travel,Eco,296,2,4,2,4,2,5,5,1,3,4,4,5,4,5,207,206.0,neutral or dissatisfied +46750,66782,Female,Loyal Customer,53,Business travel,Business,3711,3,3,3,3,4,3,3,5,5,4,5,3,4,3,1,113.0,satisfied +46751,74730,Female,Loyal Customer,34,Personal Travel,Eco,1235,5,1,5,3,3,5,3,3,3,2,2,3,3,3,0,0.0,satisfied +46752,45660,Female,Loyal Customer,35,Business travel,Eco Plus,230,5,5,5,5,5,5,5,5,2,2,2,3,2,5,8,9.0,satisfied +46753,52136,Male,Loyal Customer,43,Business travel,Business,2102,3,3,3,3,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +46754,30213,Male,Loyal Customer,46,Personal Travel,Eco Plus,82,1,5,1,1,3,1,4,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +46755,44290,Male,Loyal Customer,46,Business travel,Business,1123,1,0,0,3,3,3,3,2,2,0,3,4,2,3,0,6.0,neutral or dissatisfied +46756,125734,Female,Loyal Customer,55,Personal Travel,Eco Plus,857,1,1,1,2,2,2,2,2,2,1,2,4,2,3,9,17.0,neutral or dissatisfied +46757,16459,Male,Loyal Customer,60,Personal Travel,Eco,529,3,5,5,1,5,5,5,5,2,4,1,1,2,5,6,0.0,neutral or dissatisfied +46758,45676,Female,Loyal Customer,45,Business travel,Eco,826,5,1,1,1,5,5,2,5,5,5,5,1,5,5,100,,satisfied +46759,128392,Male,disloyal Customer,33,Business travel,Eco,647,1,2,1,3,4,1,4,4,2,4,4,2,3,4,27,30.0,neutral or dissatisfied +46760,5147,Male,Loyal Customer,42,Business travel,Eco,622,3,4,4,4,3,3,3,3,3,5,4,2,3,3,0,0.0,neutral or dissatisfied +46761,39406,Male,Loyal Customer,28,Personal Travel,Eco,546,1,1,1,4,3,1,3,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +46762,79280,Male,Loyal Customer,68,Personal Travel,Business,2248,4,4,4,2,5,4,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +46763,116764,Female,Loyal Customer,56,Personal Travel,Eco Plus,447,1,5,2,1,2,3,3,5,5,4,5,3,5,3,141,129.0,neutral or dissatisfied +46764,37342,Female,Loyal Customer,51,Business travel,Business,944,3,3,3,3,1,3,5,4,4,4,4,1,4,4,21,30.0,satisfied +46765,117817,Female,Loyal Customer,8,Personal Travel,Eco,328,3,2,3,3,3,3,3,3,3,4,4,4,3,3,0,0.0,neutral or dissatisfied +46766,62122,Female,Loyal Customer,49,Business travel,Business,2425,5,5,4,5,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +46767,129142,Male,Loyal Customer,44,Business travel,Business,2963,1,1,1,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +46768,8264,Male,Loyal Customer,7,Personal Travel,Eco,125,2,3,0,2,0,1,1,1,1,3,2,1,4,1,226,222.0,neutral or dissatisfied +46769,114525,Male,Loyal Customer,31,Personal Travel,Business,296,4,5,4,3,3,4,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +46770,129880,Female,Loyal Customer,20,Personal Travel,Eco Plus,337,3,1,3,2,2,3,2,2,4,4,1,4,2,2,0,0.0,neutral or dissatisfied +46771,72078,Male,Loyal Customer,39,Business travel,Eco,1056,4,1,1,1,4,4,4,4,3,2,1,3,4,4,10,0.0,satisfied +46772,63805,Male,disloyal Customer,37,Business travel,Business,2724,3,3,3,3,2,3,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +46773,77909,Female,Loyal Customer,50,Personal Travel,Eco,456,2,1,2,3,1,4,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +46774,27946,Male,Loyal Customer,42,Business travel,Business,1774,4,4,4,4,2,4,2,4,4,4,4,5,4,3,0,0.0,satisfied +46775,79657,Male,Loyal Customer,76,Business travel,Business,362,3,4,4,4,4,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +46776,49613,Female,disloyal Customer,55,Business travel,Eco,78,2,0,2,1,1,2,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +46777,124895,Female,Loyal Customer,48,Business travel,Business,728,5,5,2,5,2,5,4,5,5,5,5,5,5,3,5,9.0,satisfied +46778,61287,Male,Loyal Customer,24,Personal Travel,Eco,853,2,5,2,3,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +46779,58562,Female,Loyal Customer,30,Personal Travel,Eco Plus,1514,4,4,3,2,5,3,4,5,3,3,4,3,5,5,8,0.0,satisfied +46780,127588,Female,Loyal Customer,50,Business travel,Business,1773,1,1,1,1,3,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +46781,17440,Female,Loyal Customer,8,Personal Travel,Eco,351,3,4,3,3,3,3,3,3,4,4,4,3,5,3,21,9.0,neutral or dissatisfied +46782,128883,Female,Loyal Customer,32,Business travel,Business,2454,1,1,1,1,4,4,4,3,5,3,4,4,5,4,1,0.0,satisfied +46783,105086,Male,Loyal Customer,41,Business travel,Business,2055,5,5,5,5,4,5,5,5,5,5,5,3,5,5,9,0.0,satisfied +46784,74264,Female,Loyal Customer,39,Business travel,Business,1649,1,2,2,2,1,3,3,1,1,1,1,1,1,2,12,16.0,neutral or dissatisfied +46785,94975,Female,Loyal Customer,38,Business travel,Business,248,5,5,5,5,1,5,2,5,5,5,5,1,5,2,0,0.0,satisfied +46786,113170,Female,Loyal Customer,48,Personal Travel,Eco,628,1,5,1,5,1,4,3,4,4,5,5,3,5,3,371,372.0,neutral or dissatisfied +46787,124938,Male,Loyal Customer,46,Personal Travel,Eco,728,1,4,1,1,3,1,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +46788,78638,Male,disloyal Customer,37,Business travel,Business,2172,2,2,2,5,2,2,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +46789,3040,Male,Loyal Customer,43,Business travel,Business,1632,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +46790,75466,Male,Loyal Customer,31,Personal Travel,Eco,2218,4,5,4,2,5,4,5,5,4,3,1,3,5,5,0,0.0,neutral or dissatisfied +46791,123814,Female,Loyal Customer,59,Business travel,Business,3818,1,1,1,1,5,4,5,5,5,5,5,4,5,3,34,18.0,satisfied +46792,11678,Male,Loyal Customer,43,Business travel,Business,3730,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +46793,128404,Female,disloyal Customer,30,Business travel,Eco,370,4,2,4,3,5,4,5,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +46794,119642,Male,Loyal Customer,40,Business travel,Business,2967,3,3,3,3,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +46795,123062,Male,disloyal Customer,8,Business travel,Eco,600,2,5,2,1,1,2,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +46796,9929,Female,Loyal Customer,33,Business travel,Business,457,3,3,3,3,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +46797,25947,Male,disloyal Customer,27,Business travel,Business,946,3,3,3,2,1,3,1,1,4,5,5,5,5,1,103,72.0,neutral or dissatisfied +46798,19788,Male,disloyal Customer,18,Business travel,Eco,667,3,1,3,4,4,3,4,4,1,5,3,1,3,4,0,0.0,neutral or dissatisfied +46799,126777,Male,disloyal Customer,41,Business travel,Business,2296,3,3,3,3,5,3,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +46800,51775,Female,Loyal Customer,48,Personal Travel,Eco,370,2,3,2,2,2,3,3,2,2,2,2,4,2,3,99,94.0,neutral or dissatisfied +46801,28145,Male,Loyal Customer,33,Business travel,Eco,569,3,5,3,5,5,5,5,5,2,3,3,4,5,5,0,0.0,satisfied +46802,47585,Male,Loyal Customer,39,Business travel,Eco,1211,3,3,3,3,4,3,3,2,4,3,2,3,2,3,318,314.0,satisfied +46803,129744,Male,Loyal Customer,33,Business travel,Eco,337,5,1,1,1,5,4,5,5,3,1,3,1,4,5,0,0.0,neutral or dissatisfied +46804,85385,Male,Loyal Customer,53,Personal Travel,Business,332,3,5,4,3,2,4,4,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +46805,42944,Female,Loyal Customer,21,Personal Travel,Business,192,1,5,1,1,2,1,2,2,4,2,5,4,4,2,38,33.0,neutral or dissatisfied +46806,55184,Male,Loyal Customer,60,Business travel,Business,1379,1,1,4,1,3,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +46807,102709,Male,Loyal Customer,41,Business travel,Eco,365,4,3,3,3,5,4,5,5,2,5,5,2,5,5,2,0.0,satisfied +46808,122237,Female,Loyal Customer,45,Business travel,Business,541,3,3,5,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +46809,18267,Male,Loyal Customer,53,Personal Travel,Eco,179,1,3,1,3,2,1,2,2,3,1,1,3,2,2,0,0.0,neutral or dissatisfied +46810,122328,Female,disloyal Customer,33,Business travel,Eco Plus,603,2,2,2,4,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +46811,55607,Male,Loyal Customer,40,Business travel,Business,2314,1,1,1,1,5,1,1,4,4,4,4,5,4,2,0,0.0,satisfied +46812,70261,Male,Loyal Customer,40,Business travel,Business,852,5,5,5,5,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +46813,69539,Female,Loyal Customer,43,Business travel,Business,2446,4,4,4,4,4,4,4,3,4,4,4,4,3,4,46,108.0,satisfied +46814,22165,Female,disloyal Customer,26,Business travel,Eco,533,1,0,2,3,2,2,2,2,5,2,3,3,4,2,0,9.0,neutral or dissatisfied +46815,59415,Female,Loyal Customer,38,Personal Travel,Eco,2367,2,4,2,1,1,2,3,1,5,3,4,5,4,1,4,0.0,neutral or dissatisfied +46816,39356,Male,disloyal Customer,22,Business travel,Eco,896,3,3,3,4,3,3,3,3,1,3,2,4,3,3,0,,neutral or dissatisfied +46817,119732,Male,Loyal Customer,27,Business travel,Business,1882,3,2,3,2,3,2,3,3,2,2,3,4,4,3,0,21.0,neutral or dissatisfied +46818,117489,Male,Loyal Customer,55,Business travel,Business,2027,1,1,4,1,2,4,5,5,5,5,5,3,5,3,9,0.0,satisfied +46819,85435,Female,Loyal Customer,47,Business travel,Business,1986,4,3,4,4,2,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +46820,13616,Female,Loyal Customer,60,Personal Travel,Eco Plus,214,3,0,3,3,4,4,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +46821,108014,Female,Loyal Customer,59,Business travel,Business,3133,2,2,2,2,5,5,4,4,4,5,4,5,4,5,3,2.0,satisfied +46822,96919,Male,Loyal Customer,46,Personal Travel,Eco,849,3,4,3,3,4,3,4,4,4,4,5,3,5,4,35,18.0,neutral or dissatisfied +46823,34737,Male,disloyal Customer,20,Business travel,Eco,209,2,1,2,3,3,2,3,3,3,3,3,2,3,3,5,4.0,neutral or dissatisfied +46824,61636,Female,disloyal Customer,41,Business travel,Business,1379,1,1,1,3,1,1,1,1,4,4,4,5,5,1,18,0.0,neutral or dissatisfied +46825,43638,Male,Loyal Customer,25,Business travel,Business,3982,2,2,2,2,4,4,4,4,3,2,4,5,2,4,0,0.0,satisfied +46826,51950,Male,Loyal Customer,56,Business travel,Business,2314,3,3,3,3,4,1,2,4,4,4,4,4,4,4,0,6.0,satisfied +46827,91170,Female,Loyal Customer,57,Personal Travel,Eco,594,1,3,1,3,2,1,2,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +46828,38066,Male,Loyal Customer,38,Business travel,Business,1197,2,2,4,2,4,1,1,4,4,4,4,2,4,1,0,0.0,satisfied +46829,106280,Male,disloyal Customer,48,Business travel,Business,604,3,3,3,3,2,3,1,2,5,3,5,5,5,2,8,7.0,neutral or dissatisfied +46830,84637,Male,disloyal Customer,21,Business travel,Eco,707,4,4,4,5,1,4,1,1,3,2,4,3,5,1,0,0.0,satisfied +46831,11515,Male,Loyal Customer,18,Personal Travel,Eco Plus,308,3,5,3,3,2,3,2,2,3,5,4,4,5,2,0,3.0,neutral or dissatisfied +46832,53571,Male,Loyal Customer,50,Business travel,Business,1195,3,5,5,5,2,2,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +46833,56663,Female,disloyal Customer,27,Business travel,Eco,537,2,1,3,4,5,3,5,5,2,5,3,1,3,5,19,16.0,neutral or dissatisfied +46834,129755,Female,disloyal Customer,37,Business travel,Eco,337,1,2,1,4,1,1,1,1,2,2,4,1,3,1,1,13.0,neutral or dissatisfied +46835,118894,Female,Loyal Customer,34,Business travel,Business,570,3,3,3,3,5,5,5,5,5,5,5,3,5,5,11,3.0,satisfied +46836,74801,Female,Loyal Customer,30,Business travel,Business,2494,2,2,4,2,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +46837,64575,Female,disloyal Customer,26,Business travel,Business,247,1,0,1,2,5,1,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +46838,38288,Female,Loyal Customer,30,Business travel,Eco Plus,1050,4,2,2,2,4,4,4,4,2,3,5,4,1,4,0,0.0,satisfied +46839,13562,Female,Loyal Customer,56,Personal Travel,Eco,106,4,4,4,2,3,5,4,5,5,4,5,3,5,5,2,77.0,neutral or dissatisfied +46840,106435,Male,Loyal Customer,19,Business travel,Business,643,2,2,2,2,3,3,3,3,5,5,4,5,4,3,0,0.0,satisfied +46841,113920,Male,disloyal Customer,19,Business travel,Eco,1366,4,5,5,4,3,4,3,3,3,4,2,3,2,3,0,0.0,satisfied +46842,99834,Female,Loyal Customer,45,Business travel,Eco,534,3,4,4,4,1,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +46843,116312,Male,Loyal Customer,40,Personal Travel,Eco,371,1,3,4,4,1,4,1,1,4,5,3,3,4,1,32,31.0,neutral or dissatisfied +46844,66481,Female,Loyal Customer,59,Business travel,Business,447,2,2,2,2,4,5,4,5,5,5,5,3,5,4,17,6.0,satisfied +46845,64316,Female,disloyal Customer,28,Business travel,Business,1192,4,4,4,2,4,4,2,4,5,2,4,5,5,4,0,0.0,satisfied +46846,94015,Male,Loyal Customer,50,Business travel,Business,2356,3,3,3,3,4,4,5,5,5,5,5,4,5,4,73,76.0,satisfied +46847,3010,Male,Loyal Customer,54,Business travel,Business,987,1,3,3,3,4,2,2,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +46848,31812,Male,Loyal Customer,42,Business travel,Business,4983,3,3,3,3,5,4,4,4,5,4,3,4,2,4,0,0.0,satisfied +46849,51763,Female,Loyal Customer,26,Personal Travel,Eco,261,1,4,1,5,4,1,4,4,4,2,3,4,1,4,0,0.0,neutral or dissatisfied +46850,35307,Male,Loyal Customer,46,Business travel,Business,3273,2,4,4,4,4,4,4,2,2,2,2,3,2,4,17,21.0,neutral or dissatisfied +46851,8716,Male,Loyal Customer,59,Personal Travel,Eco,304,2,5,4,4,2,4,4,2,5,5,4,3,5,2,17,57.0,neutral or dissatisfied +46852,128876,Male,Loyal Customer,58,Business travel,Business,2565,2,2,2,2,4,4,4,4,5,3,4,4,3,4,0,0.0,satisfied +46853,124166,Female,Loyal Customer,53,Personal Travel,Eco,2133,1,2,1,3,4,2,4,5,5,1,1,2,5,2,0,0.0,neutral or dissatisfied +46854,32458,Female,disloyal Customer,50,Business travel,Eco,101,3,4,3,4,1,3,1,1,1,1,3,3,3,1,6,3.0,neutral or dissatisfied +46855,98659,Male,Loyal Customer,61,Personal Travel,Eco,951,3,4,3,4,3,3,3,3,1,2,4,3,3,3,0,0.0,neutral or dissatisfied +46856,101393,Female,disloyal Customer,24,Business travel,Eco,486,2,1,1,4,5,1,5,5,2,2,4,1,4,5,9,0.0,neutral or dissatisfied +46857,37560,Male,Loyal Customer,33,Business travel,Business,1080,2,2,2,2,2,2,2,2,5,4,4,1,3,2,0,0.0,satisfied +46858,19813,Female,disloyal Customer,23,Business travel,Eco,413,0,4,0,1,1,0,1,1,4,5,1,5,5,1,0,0.0,satisfied +46859,5577,Male,Loyal Customer,31,Personal Travel,Eco,588,3,4,3,1,5,3,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +46860,3427,Female,Loyal Customer,61,Personal Travel,Eco,315,2,5,2,1,3,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +46861,64339,Male,Loyal Customer,28,Business travel,Business,1212,4,4,4,4,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +46862,103220,Female,Loyal Customer,56,Business travel,Eco,351,2,3,3,3,2,4,3,2,2,2,2,2,2,4,38,46.0,neutral or dissatisfied +46863,86293,Female,Loyal Customer,8,Personal Travel,Eco,306,2,4,2,5,2,1,1,3,5,4,5,1,4,1,132,128.0,neutral or dissatisfied +46864,128962,Female,Loyal Customer,39,Business travel,Business,236,2,2,2,2,1,3,1,4,4,4,4,3,4,5,0,0.0,satisfied +46865,44951,Male,Loyal Customer,37,Personal Travel,Eco,349,3,5,3,3,1,3,1,1,4,5,5,5,4,1,3,37.0,neutral or dissatisfied +46866,9336,Female,disloyal Customer,38,Business travel,Business,401,5,5,5,3,4,5,1,4,3,5,4,3,5,4,44,32.0,satisfied +46867,39370,Male,Loyal Customer,35,Business travel,Eco Plus,826,5,1,1,1,5,4,5,5,1,1,1,2,5,5,76,110.0,satisfied +46868,14558,Male,Loyal Customer,19,Business travel,Eco Plus,299,1,5,5,5,1,1,2,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +46869,44771,Female,Loyal Customer,46,Business travel,Eco,1250,2,3,3,3,4,5,2,2,2,2,2,2,2,1,0,0.0,satisfied +46870,15126,Female,Loyal Customer,35,Business travel,Eco,1042,5,4,4,4,5,5,5,5,1,2,5,2,3,5,0,0.0,satisfied +46871,22024,Male,Loyal Customer,57,Business travel,Eco Plus,500,4,2,2,2,4,4,4,4,1,4,2,4,4,4,0,1.0,satisfied +46872,106833,Male,Loyal Customer,49,Business travel,Business,1733,3,3,3,3,4,4,5,5,5,5,5,3,5,3,2,0.0,satisfied +46873,52370,Female,Loyal Customer,8,Personal Travel,Eco,370,3,3,3,3,1,3,1,1,4,2,5,3,2,1,1,12.0,neutral or dissatisfied +46874,62111,Male,Loyal Customer,64,Business travel,Business,2454,3,3,3,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +46875,72128,Male,disloyal Customer,10,Business travel,Business,731,5,4,5,3,2,5,2,2,5,5,5,5,5,2,0,0.0,satisfied +46876,4455,Male,Loyal Customer,36,Personal Travel,Eco Plus,762,2,4,2,3,5,2,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +46877,32351,Male,disloyal Customer,39,Business travel,Eco,121,2,5,1,4,4,1,4,4,1,3,4,1,3,4,0,0.0,neutral or dissatisfied +46878,28433,Male,Loyal Customer,26,Business travel,Business,2496,2,2,2,2,2,2,2,4,5,3,5,2,2,2,0,22.0,satisfied +46879,56709,Female,Loyal Customer,54,Personal Travel,Eco,1068,3,4,3,1,5,4,4,5,5,3,5,3,5,3,47,22.0,neutral or dissatisfied +46880,123580,Female,Loyal Customer,17,Personal Travel,Eco,1773,2,3,1,3,2,1,5,2,4,1,3,2,3,2,2,0.0,neutral or dissatisfied +46881,66833,Male,Loyal Customer,31,Business travel,Business,2914,4,4,4,4,4,4,4,4,4,3,5,5,4,4,42,20.0,satisfied +46882,78442,Male,disloyal Customer,32,Business travel,Eco,666,2,1,1,4,2,1,2,2,2,2,4,1,3,2,0,27.0,neutral or dissatisfied +46883,49329,Female,Loyal Customer,37,Business travel,Eco,337,4,4,4,4,4,4,4,4,4,3,3,5,1,4,0,0.0,satisfied +46884,127102,Male,Loyal Customer,57,Personal Travel,Eco,370,5,1,5,4,2,5,2,2,1,5,3,1,3,2,8,0.0,satisfied +46885,82124,Female,Loyal Customer,41,Business travel,Business,2519,5,5,5,5,2,4,4,3,3,4,3,3,3,3,3,0.0,satisfied +46886,51507,Male,disloyal Customer,36,Business travel,Eco,598,3,0,3,3,5,3,3,5,2,1,5,3,2,5,0,0.0,neutral or dissatisfied +46887,94113,Female,Loyal Customer,29,Personal Travel,Business,323,3,1,3,3,3,3,3,3,2,1,3,1,3,3,124,106.0,neutral or dissatisfied +46888,111051,Female,Loyal Customer,52,Business travel,Business,3214,1,1,1,1,4,3,3,4,4,4,4,2,4,2,4,0.0,satisfied +46889,123926,Female,Loyal Customer,22,Personal Travel,Eco,544,3,4,3,1,5,3,5,5,2,2,3,4,5,5,0,0.0,neutral or dissatisfied +46890,113386,Female,Loyal Customer,59,Business travel,Business,2682,4,4,2,4,2,5,5,5,5,5,5,3,5,3,16,11.0,satisfied +46891,100305,Male,disloyal Customer,27,Business travel,Eco,1011,1,1,1,4,2,1,2,2,3,2,4,4,4,2,6,0.0,neutral or dissatisfied +46892,38231,Female,disloyal Customer,16,Business travel,Eco,1173,4,4,4,3,5,4,5,5,3,5,3,1,3,5,84,86.0,neutral or dissatisfied +46893,112815,Male,Loyal Customer,50,Business travel,Business,3628,4,4,2,4,4,5,4,4,4,4,4,5,4,3,4,8.0,satisfied +46894,90020,Male,disloyal Customer,24,Business travel,Eco,1127,4,5,5,1,1,5,1,1,5,3,4,3,4,1,0,0.0,satisfied +46895,36254,Male,Loyal Customer,30,Business travel,Business,728,4,1,1,1,4,4,4,4,1,1,2,1,2,4,34,51.0,neutral or dissatisfied +46896,2866,Female,Loyal Customer,34,Business travel,Business,409,1,1,1,1,1,2,3,3,3,5,3,2,3,1,6,0.0,satisfied +46897,86259,Female,Loyal Customer,15,Personal Travel,Eco,226,4,1,4,4,5,4,5,5,1,5,4,1,4,5,0,1.0,satisfied +46898,115692,Female,disloyal Customer,33,Business travel,Business,417,2,2,2,1,5,2,3,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +46899,29507,Female,Loyal Customer,42,Personal Travel,Eco,1107,3,2,3,3,4,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +46900,74995,Female,Loyal Customer,65,Personal Travel,Eco Plus,2586,1,5,1,4,5,4,5,4,4,1,1,3,4,3,67,40.0,neutral or dissatisfied +46901,2450,Female,Loyal Customer,24,Personal Travel,Eco Plus,641,2,4,2,2,3,2,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +46902,25229,Male,Loyal Customer,15,Business travel,Eco,925,4,2,2,2,4,4,4,4,1,4,4,5,5,4,3,0.0,satisfied +46903,44218,Male,Loyal Customer,33,Business travel,Business,222,2,2,2,2,5,5,5,5,5,5,3,5,5,5,0,0.0,satisfied +46904,6804,Female,disloyal Customer,80,Business travel,Business,235,4,4,4,3,5,4,4,5,5,4,5,1,5,5,13,0.0,satisfied +46905,104688,Male,Loyal Customer,48,Business travel,Business,3386,0,4,0,1,2,4,5,2,2,3,3,5,2,4,102,88.0,satisfied +46906,39180,Female,Loyal Customer,13,Personal Travel,Eco,287,3,3,3,2,2,3,2,2,1,2,2,5,1,2,0,6.0,neutral or dissatisfied +46907,21086,Female,Loyal Customer,48,Business travel,Business,106,1,3,3,3,1,2,2,4,4,4,1,4,4,4,19,13.0,neutral or dissatisfied +46908,32963,Female,Loyal Customer,28,Personal Travel,Eco,101,4,5,4,3,2,4,2,2,5,5,4,4,5,2,0,3.0,satisfied +46909,88337,Female,disloyal Customer,26,Business travel,Eco,515,3,2,3,3,4,3,4,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +46910,84245,Female,Loyal Customer,41,Personal Travel,Eco Plus,432,0,4,0,3,4,5,5,4,4,0,4,4,4,4,0,0.0,satisfied +46911,103216,Male,Loyal Customer,49,Business travel,Business,462,5,5,5,5,3,5,5,4,4,4,4,5,4,3,23,2.0,satisfied +46912,123745,Male,disloyal Customer,38,Business travel,Business,96,4,4,4,4,2,4,2,2,3,5,4,3,5,2,0,0.0,satisfied +46913,89636,Male,Loyal Customer,37,Business travel,Business,1096,4,4,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +46914,25835,Male,Loyal Customer,29,Business travel,Business,692,1,1,1,1,4,4,4,4,2,3,2,3,1,4,0,0.0,satisfied +46915,32748,Female,Loyal Customer,33,Business travel,Eco,101,4,5,5,5,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +46916,113820,Female,Loyal Customer,30,Personal Travel,Eco Plus,236,3,5,3,2,1,3,1,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +46917,1311,Male,Loyal Customer,42,Business travel,Business,3521,1,1,5,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +46918,54315,Male,Loyal Customer,52,Business travel,Eco,1597,3,2,2,2,3,3,3,3,2,5,2,2,3,3,3,0.0,neutral or dissatisfied +46919,65481,Female,disloyal Customer,27,Business travel,Eco,903,3,3,3,4,4,3,4,4,5,3,4,2,1,4,0,0.0,neutral or dissatisfied +46920,74448,Female,disloyal Customer,29,Business travel,Business,1205,4,4,4,2,3,4,3,3,3,3,4,3,4,3,0,0.0,satisfied +46921,29837,Male,Loyal Customer,38,Business travel,Business,2627,3,1,1,1,3,4,4,3,3,3,3,1,3,4,30,25.0,neutral or dissatisfied +46922,109337,Female,Loyal Customer,47,Personal Travel,Eco,1200,2,2,1,3,1,4,4,2,2,1,2,4,2,4,11,7.0,neutral or dissatisfied +46923,49309,Male,Loyal Customer,26,Business travel,Business,2758,4,5,5,5,2,2,4,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +46924,5070,Male,Loyal Customer,35,Business travel,Eco,224,1,5,5,5,1,1,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +46925,87982,Female,Loyal Customer,55,Business travel,Business,271,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +46926,72344,Male,Loyal Customer,47,Business travel,Business,3633,1,1,1,1,2,4,3,1,1,1,1,1,1,4,0,4.0,neutral or dissatisfied +46927,82848,Female,Loyal Customer,40,Business travel,Business,3473,5,5,5,5,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +46928,103735,Male,Loyal Customer,60,Personal Travel,Eco,405,1,1,1,3,4,1,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +46929,4814,Male,Loyal Customer,46,Business travel,Business,2916,3,3,3,3,2,4,4,4,4,4,4,3,4,5,5,10.0,satisfied +46930,75712,Female,Loyal Customer,49,Business travel,Business,813,1,1,3,1,5,4,5,4,4,4,4,3,4,4,20,1.0,satisfied +46931,53590,Male,disloyal Customer,25,Business travel,Eco,599,4,3,4,4,3,4,3,3,5,5,3,5,2,3,14,0.0,satisfied +46932,129643,Female,Loyal Customer,44,Business travel,Business,1803,0,0,0,3,2,5,4,1,1,1,1,5,1,5,87,90.0,satisfied +46933,110932,Male,Loyal Customer,69,Personal Travel,Eco,406,3,4,3,3,3,3,3,3,4,4,1,4,3,3,0,0.0,neutral or dissatisfied +46934,20340,Female,disloyal Customer,42,Business travel,Eco,287,2,0,2,5,3,2,4,3,3,5,4,5,5,3,60,45.0,neutral or dissatisfied +46935,28348,Male,Loyal Customer,55,Personal Travel,Eco,867,3,2,3,3,2,3,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +46936,101990,Female,Loyal Customer,58,Personal Travel,Eco,628,3,4,3,1,2,4,5,4,4,3,4,5,4,4,3,0.0,neutral or dissatisfied +46937,125893,Male,Loyal Customer,42,Personal Travel,Eco,920,4,4,4,4,4,4,4,4,1,2,4,3,4,4,0,10.0,neutral or dissatisfied +46938,107929,Male,Loyal Customer,49,Business travel,Business,3982,3,1,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +46939,60092,Male,Loyal Customer,46,Business travel,Business,1005,5,5,5,5,2,4,4,3,3,3,3,3,3,4,28,3.0,satisfied +46940,53215,Female,Loyal Customer,29,Business travel,Business,3240,4,2,2,2,4,3,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +46941,39744,Female,disloyal Customer,38,Business travel,Eco Plus,410,4,4,4,3,3,4,3,3,1,3,3,2,4,3,0,15.0,neutral or dissatisfied +46942,36100,Female,Loyal Customer,9,Personal Travel,Eco,399,2,4,2,5,1,2,1,1,3,4,3,5,2,1,0,0.0,neutral or dissatisfied +46943,93047,Male,Loyal Customer,48,Personal Travel,Eco,436,3,5,3,5,1,3,1,1,4,2,5,4,5,1,0,,neutral or dissatisfied +46944,112874,Female,Loyal Customer,30,Business travel,Business,1164,2,2,2,2,5,5,5,5,3,4,5,3,5,5,0,0.0,satisfied +46945,17269,Female,Loyal Customer,54,Personal Travel,Eco,872,1,1,1,3,2,3,4,2,2,1,1,1,2,2,0,0.0,neutral or dissatisfied +46946,6517,Male,Loyal Customer,25,Business travel,Eco,599,2,3,3,3,2,2,2,2,3,1,4,1,3,2,25,14.0,neutral or dissatisfied +46947,46359,Female,Loyal Customer,52,Business travel,Business,3246,2,3,3,3,4,2,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +46948,87595,Male,Loyal Customer,26,Personal Travel,Eco,432,4,5,4,3,4,4,4,4,4,5,5,5,5,4,0,21.0,neutral or dissatisfied +46949,51974,Female,Loyal Customer,59,Business travel,Eco,347,4,1,1,1,3,4,4,4,4,4,4,4,4,1,0,0.0,satisfied +46950,2979,Female,Loyal Customer,41,Business travel,Business,462,3,2,2,2,3,3,3,1,4,3,2,3,2,3,185,174.0,neutral or dissatisfied +46951,23932,Male,Loyal Customer,38,Business travel,Eco Plus,589,4,4,5,4,4,4,4,4,1,5,3,1,4,4,49,25.0,neutral or dissatisfied +46952,113231,Male,disloyal Customer,27,Business travel,Business,226,3,3,3,4,4,3,5,4,1,2,3,4,4,4,21,15.0,neutral or dissatisfied +46953,41022,Female,Loyal Customer,35,Business travel,Business,1086,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +46954,112504,Male,Loyal Customer,14,Personal Travel,Eco,819,4,5,4,3,4,4,5,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +46955,13262,Male,Loyal Customer,37,Business travel,Business,468,2,2,2,2,5,3,3,2,2,1,2,2,2,3,0,5.0,neutral or dissatisfied +46956,119268,Female,Loyal Customer,54,Business travel,Business,3964,0,5,0,1,3,5,5,4,4,4,2,3,4,3,0,0.0,satisfied +46957,4938,Male,disloyal Customer,41,Business travel,Business,268,3,3,3,4,1,3,1,1,2,3,3,2,3,1,11,29.0,neutral or dissatisfied +46958,111590,Male,Loyal Customer,23,Personal Travel,Eco,794,3,4,3,2,3,3,3,3,3,5,4,4,5,3,24,29.0,neutral or dissatisfied +46959,30759,Female,Loyal Customer,49,Business travel,Eco,683,4,3,4,4,5,4,1,4,4,4,4,5,4,2,9,11.0,satisfied +46960,78180,Male,Loyal Customer,43,Business travel,Business,3851,3,3,3,3,4,4,5,5,5,5,4,5,5,4,0,0.0,satisfied +46961,53772,Female,Loyal Customer,12,Personal Travel,Eco,1195,1,5,1,2,2,1,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +46962,51056,Female,Loyal Customer,7,Personal Travel,Eco,209,3,3,3,4,4,3,4,4,1,4,4,2,3,4,3,0.0,neutral or dissatisfied +46963,78866,Female,disloyal Customer,23,Business travel,Eco,979,3,3,3,4,3,3,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +46964,56255,Male,Loyal Customer,71,Business travel,Business,404,3,2,2,2,5,3,2,3,3,2,3,2,3,1,11,23.0,neutral or dissatisfied +46965,59062,Male,Loyal Customer,46,Business travel,Business,1744,1,1,1,1,3,4,5,5,5,5,5,4,5,3,3,0.0,satisfied +46966,63160,Female,Loyal Customer,44,Business travel,Business,1860,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,9.0,satisfied +46967,116630,Male,Loyal Customer,48,Business travel,Eco Plus,337,4,5,5,5,4,4,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +46968,6505,Female,Loyal Customer,30,Business travel,Business,599,1,1,1,1,5,4,5,5,5,4,5,3,5,5,14,7.0,satisfied +46969,108134,Male,Loyal Customer,46,Business travel,Business,1166,3,5,5,5,4,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +46970,52849,Male,Loyal Customer,57,Personal Travel,Eco,1721,3,4,3,2,4,3,3,4,5,4,4,4,1,4,0,0.0,neutral or dissatisfied +46971,30659,Male,Loyal Customer,18,Personal Travel,Eco,533,4,3,1,4,5,1,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +46972,112782,Female,Loyal Customer,46,Personal Travel,Eco,590,4,5,4,5,2,5,5,4,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +46973,21089,Female,Loyal Customer,32,Business travel,Business,2369,2,1,3,3,1,1,2,1,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +46974,32721,Male,Loyal Customer,38,Business travel,Eco,101,4,4,4,4,4,4,4,4,4,3,3,3,2,4,0,0.0,satisfied +46975,63949,Male,Loyal Customer,12,Personal Travel,Eco,1192,3,4,3,3,3,3,3,3,3,5,2,2,3,3,0,0.0,neutral or dissatisfied +46976,71172,Female,Loyal Customer,39,Business travel,Business,2644,4,4,4,4,3,4,4,4,4,4,4,4,4,4,26,29.0,satisfied +46977,31554,Female,Loyal Customer,34,Personal Travel,Eco,846,3,3,3,5,2,3,2,2,5,3,5,2,5,2,0,2.0,neutral or dissatisfied +46978,29892,Male,disloyal Customer,20,Business travel,Eco,548,3,1,3,3,5,3,3,5,2,3,4,1,4,5,20,9.0,neutral or dissatisfied +46979,50805,Male,Loyal Customer,9,Personal Travel,Eco,89,4,4,4,4,1,4,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +46980,60668,Male,Loyal Customer,10,Personal Travel,Eco,1620,3,5,3,3,1,3,1,1,3,3,4,5,5,1,18,7.0,neutral or dissatisfied +46981,103064,Male,disloyal Customer,16,Business travel,Eco,687,3,3,3,3,3,3,3,3,1,2,3,2,4,3,45,38.0,neutral or dissatisfied +46982,117508,Female,Loyal Customer,39,Personal Travel,Eco,507,3,5,3,3,5,3,5,5,5,4,4,2,4,5,0,5.0,neutral or dissatisfied +46983,67205,Male,Loyal Customer,38,Personal Travel,Eco,918,2,4,2,5,2,2,2,2,4,2,5,4,5,2,48,42.0,neutral or dissatisfied +46984,7700,Male,Loyal Customer,22,Personal Travel,Eco,604,1,4,1,4,3,1,3,3,3,5,5,4,4,3,0,7.0,neutral or dissatisfied +46985,33818,Female,Loyal Customer,66,Personal Travel,Eco,1521,3,4,3,4,5,4,3,2,2,3,1,4,2,4,0,0.0,neutral or dissatisfied +46986,39302,Male,Loyal Customer,35,Personal Travel,Eco,268,3,2,3,3,4,3,4,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +46987,55906,Male,Loyal Customer,23,Business travel,Business,733,2,2,2,2,5,5,5,5,3,1,4,1,1,5,67,35.0,satisfied +46988,5200,Male,Loyal Customer,42,Business travel,Business,3482,2,2,2,2,4,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +46989,109943,Male,Loyal Customer,40,Personal Travel,Eco,1204,2,4,2,3,2,2,2,2,4,2,2,1,3,2,9,0.0,neutral or dissatisfied +46990,50024,Female,disloyal Customer,23,Business travel,Eco,262,4,0,4,2,1,4,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +46991,127023,Male,Loyal Customer,51,Business travel,Business,647,1,5,5,5,4,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +46992,120514,Female,Loyal Customer,27,Personal Travel,Eco Plus,337,1,5,1,3,3,1,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +46993,396,Male,Loyal Customer,35,Business travel,Business,3838,3,1,5,1,1,4,3,3,3,3,3,2,3,3,0,3.0,neutral or dissatisfied +46994,66247,Male,Loyal Customer,59,Personal Travel,Eco,460,4,5,4,4,3,4,3,3,4,4,4,3,5,3,19,14.0,neutral or dissatisfied +46995,127670,Male,Loyal Customer,36,Business travel,Eco,2153,4,1,1,1,4,4,4,4,1,1,2,4,1,4,0,2.0,neutral or dissatisfied +46996,4307,Male,Loyal Customer,34,Personal Travel,Eco Plus,502,2,5,2,1,1,2,1,1,4,2,4,3,5,1,0,0.0,neutral or dissatisfied +46997,104949,Male,Loyal Customer,60,Business travel,Business,2258,0,0,0,3,3,5,4,3,3,3,3,5,3,3,113,108.0,satisfied +46998,42343,Male,Loyal Customer,70,Personal Travel,Eco,412,3,5,3,2,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +46999,19757,Female,Loyal Customer,48,Business travel,Business,462,4,4,4,4,2,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +47000,83867,Male,Loyal Customer,46,Business travel,Business,2374,3,3,3,3,2,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +47001,60505,Female,Loyal Customer,52,Personal Travel,Eco,641,4,5,4,1,1,3,3,3,3,4,5,4,3,4,2,2.0,satisfied +47002,26459,Male,disloyal Customer,72,Business travel,Eco,387,3,0,3,5,2,3,2,2,3,4,1,5,1,2,0,0.0,neutral or dissatisfied +47003,13323,Male,Loyal Customer,59,Business travel,Business,3892,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +47004,101940,Male,Loyal Customer,42,Business travel,Business,2752,5,5,5,5,2,5,5,4,4,4,4,5,4,4,11,1.0,satisfied +47005,54752,Female,Loyal Customer,7,Personal Travel,Eco,787,3,5,3,4,2,3,4,2,4,2,5,4,4,2,62,49.0,neutral or dissatisfied +47006,94268,Male,Loyal Customer,57,Business travel,Business,189,1,1,1,1,4,5,5,4,4,4,4,5,4,3,15,11.0,satisfied +47007,20856,Male,Loyal Customer,48,Personal Travel,Eco,534,4,4,3,5,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +47008,101908,Female,Loyal Customer,50,Personal Travel,Eco,2039,4,5,4,4,2,5,4,1,1,4,1,3,1,4,31,12.0,neutral or dissatisfied +47009,44378,Female,disloyal Customer,24,Business travel,Eco,229,2,1,2,2,5,2,1,5,4,1,2,1,2,5,0,6.0,neutral or dissatisfied +47010,15700,Male,Loyal Customer,21,Personal Travel,Business,419,1,2,1,3,3,1,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +47011,25586,Female,Loyal Customer,35,Business travel,Eco,813,2,5,5,5,2,2,2,2,1,1,3,1,4,2,8,0.0,neutral or dissatisfied +47012,110518,Female,Loyal Customer,46,Business travel,Business,2670,3,3,3,3,2,5,5,3,3,4,3,4,3,5,8,0.0,satisfied +47013,58454,Male,Loyal Customer,26,Personal Travel,Eco,723,3,3,4,3,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +47014,70370,Male,Loyal Customer,53,Personal Travel,Eco,1145,1,5,1,3,4,1,4,4,3,3,5,3,4,4,2,0.0,neutral or dissatisfied +47015,89260,Male,disloyal Customer,36,Business travel,Business,453,3,3,3,4,4,3,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +47016,114322,Female,Loyal Customer,55,Personal Travel,Eco,850,2,4,2,2,2,4,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +47017,40678,Female,Loyal Customer,28,Business travel,Business,3409,3,3,5,3,3,3,3,3,3,3,1,3,1,3,0,0.0,satisfied +47018,107961,Female,disloyal Customer,26,Business travel,Business,825,2,2,2,1,2,2,2,2,5,3,4,5,4,2,0,8.0,neutral or dissatisfied +47019,13005,Male,Loyal Customer,47,Business travel,Eco,374,1,3,3,3,1,1,1,1,1,4,4,4,3,1,0,8.0,neutral or dissatisfied +47020,99153,Male,disloyal Customer,35,Business travel,Business,1076,1,1,1,3,3,1,3,3,4,4,4,2,3,3,3,11.0,neutral or dissatisfied +47021,129830,Male,Loyal Customer,39,Personal Travel,Eco,337,1,5,1,4,2,1,4,2,3,4,5,4,5,2,0,30.0,neutral or dissatisfied +47022,113910,Male,Loyal Customer,38,Personal Travel,Eco,2329,2,4,2,1,5,2,4,5,5,5,3,4,5,5,12,18.0,neutral or dissatisfied +47023,4126,Male,Loyal Customer,33,Business travel,Business,427,1,3,3,3,1,1,1,1,1,1,4,2,3,1,8,0.0,neutral or dissatisfied +47024,8629,Female,disloyal Customer,39,Business travel,Business,280,3,3,3,4,3,3,3,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +47025,102879,Male,Loyal Customer,12,Personal Travel,Eco,472,1,4,1,2,3,1,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +47026,36717,Female,Loyal Customer,23,Business travel,Eco Plus,1185,4,3,3,3,4,5,5,4,3,2,4,5,1,4,7,0.0,satisfied +47027,23799,Male,disloyal Customer,27,Business travel,Eco,374,2,2,2,3,1,2,1,1,4,3,3,4,3,1,2,0.0,neutral or dissatisfied +47028,12742,Male,Loyal Customer,18,Personal Travel,Eco,721,3,0,3,3,2,3,2,2,2,2,2,1,4,2,0,0.0,neutral or dissatisfied +47029,84280,Female,Loyal Customer,52,Personal Travel,Eco,334,2,4,2,1,3,4,5,4,4,2,3,3,4,3,20,95.0,neutral or dissatisfied +47030,72931,Female,Loyal Customer,38,Business travel,Business,2511,2,1,1,1,2,2,2,3,1,4,4,2,4,2,149,160.0,neutral or dissatisfied +47031,95946,Male,Loyal Customer,49,Business travel,Business,775,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +47032,81426,Female,disloyal Customer,30,Business travel,Eco,448,3,3,3,5,1,3,1,1,3,1,3,2,5,1,0,0.0,neutral or dissatisfied +47033,23604,Male,disloyal Customer,20,Business travel,Eco,292,3,4,3,3,2,3,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +47034,12657,Male,Loyal Customer,27,Business travel,Business,2944,4,4,4,4,4,5,4,4,5,3,3,4,4,4,0,6.0,satisfied +47035,72258,Female,Loyal Customer,45,Business travel,Eco,921,1,5,5,5,5,4,4,1,1,1,1,2,1,3,11,0.0,neutral or dissatisfied +47036,99537,Female,disloyal Customer,29,Business travel,Business,802,2,2,2,3,5,2,5,5,4,4,4,5,4,5,66,56.0,neutral or dissatisfied +47037,95063,Male,Loyal Customer,18,Personal Travel,Eco,239,1,4,0,2,4,0,4,4,2,3,3,2,2,4,3,6.0,neutral or dissatisfied +47038,3198,Male,Loyal Customer,18,Personal Travel,Eco,693,3,5,3,2,2,3,2,2,5,3,5,5,5,2,1,0.0,neutral or dissatisfied +47039,29403,Male,Loyal Customer,67,Personal Travel,Eco,2676,4,4,4,4,4,1,1,3,5,3,5,1,4,1,0,0.0,neutral or dissatisfied +47040,128022,Female,Loyal Customer,44,Business travel,Business,1440,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,30.0,satisfied +47041,5361,Female,disloyal Customer,26,Business travel,Eco,812,1,1,1,3,1,1,1,1,1,3,4,1,4,1,62,42.0,neutral or dissatisfied +47042,50846,Male,Loyal Customer,18,Personal Travel,Eco,78,3,5,3,3,5,3,5,5,3,4,4,5,4,5,12,11.0,neutral or dissatisfied +47043,81999,Female,Loyal Customer,23,Business travel,Eco,1532,4,3,3,3,4,3,2,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +47044,12722,Male,disloyal Customer,34,Business travel,Eco,721,2,2,2,3,3,2,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +47045,73186,Male,disloyal Customer,39,Business travel,Eco,1258,1,1,1,4,4,1,4,4,3,3,3,4,3,4,18,17.0,neutral or dissatisfied +47046,118717,Female,Loyal Customer,21,Personal Travel,Eco,304,1,5,4,3,1,4,1,1,5,3,4,5,5,1,0,2.0,neutral or dissatisfied +47047,8726,Female,Loyal Customer,7,Personal Travel,Eco,280,3,4,3,2,4,3,4,4,5,3,5,3,5,4,32,38.0,neutral or dissatisfied +47048,58225,Male,Loyal Customer,41,Personal Travel,Eco,925,1,5,1,1,4,1,4,4,1,3,1,3,3,4,0,4.0,neutral or dissatisfied +47049,119365,Female,Loyal Customer,65,Personal Travel,Business,399,1,5,1,4,5,5,4,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +47050,61196,Female,disloyal Customer,49,Business travel,Business,967,1,1,1,3,5,1,1,5,3,5,4,3,4,5,20,1.0,neutral or dissatisfied +47051,53720,Male,Loyal Customer,20,Personal Travel,Eco,1208,1,2,1,4,1,1,1,1,4,1,3,1,4,1,0,0.0,neutral or dissatisfied +47052,97318,Male,Loyal Customer,48,Business travel,Business,347,0,0,0,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +47053,98059,Male,Loyal Customer,48,Business travel,Eco Plus,1797,4,5,5,5,4,4,4,4,4,2,3,4,2,4,37,41.0,neutral or dissatisfied +47054,1475,Male,Loyal Customer,47,Personal Travel,Eco,772,3,5,3,2,5,3,5,5,4,2,2,3,1,5,0,0.0,neutral or dissatisfied +47055,69382,Female,Loyal Customer,33,Business travel,Eco,1089,1,3,3,3,1,1,1,1,1,2,4,3,4,1,0,0.0,neutral or dissatisfied +47056,6359,Male,Loyal Customer,23,Business travel,Business,3257,3,1,4,1,3,3,3,3,2,5,3,3,3,3,37,73.0,neutral or dissatisfied +47057,114129,Female,Loyal Customer,46,Business travel,Business,846,5,5,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +47058,46006,Female,Loyal Customer,53,Personal Travel,Eco,300,3,4,3,2,3,5,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +47059,65387,Male,Loyal Customer,59,Personal Travel,Eco,631,2,4,2,3,1,2,1,1,3,3,4,5,4,1,6,0.0,neutral or dissatisfied +47060,51011,Male,Loyal Customer,51,Personal Travel,Eco,337,1,5,1,2,2,1,2,2,5,5,4,5,5,2,31,25.0,neutral or dissatisfied +47061,39851,Male,disloyal Customer,57,Business travel,Business,221,5,5,5,3,1,5,1,1,1,1,4,3,4,1,0,,satisfied +47062,52420,Male,Loyal Customer,20,Personal Travel,Eco,261,2,4,2,2,2,2,2,2,1,3,5,5,1,2,0,0.0,neutral or dissatisfied +47063,75910,Male,Loyal Customer,17,Personal Travel,Eco,597,2,2,2,3,4,2,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +47064,103467,Female,Loyal Customer,43,Business travel,Business,2893,2,5,2,2,5,4,5,5,5,5,5,4,5,4,100,99.0,satisfied +47065,93305,Male,Loyal Customer,15,Business travel,Business,1733,2,2,2,2,5,5,5,5,5,3,4,5,5,5,0,22.0,satisfied +47066,100516,Male,Loyal Customer,28,Personal Travel,Eco,580,5,4,5,3,3,5,3,3,1,1,4,1,3,3,2,0.0,satisfied +47067,82456,Female,Loyal Customer,77,Business travel,Eco,241,2,5,5,5,1,4,3,2,2,2,2,1,2,2,34,25.0,neutral or dissatisfied +47068,20613,Male,Loyal Customer,40,Business travel,Business,2589,5,2,5,5,1,1,1,5,5,5,5,1,5,5,0,0.0,satisfied +47069,53045,Male,Loyal Customer,47,Personal Travel,Eco,1208,3,4,3,2,3,3,5,3,1,2,4,4,2,3,0,0.0,neutral or dissatisfied +47070,34486,Female,Loyal Customer,30,Personal Travel,Eco Plus,266,2,0,0,4,4,0,4,4,5,4,4,5,2,4,0,0.0,neutral or dissatisfied +47071,44778,Female,disloyal Customer,29,Business travel,Eco,1250,3,3,3,3,4,3,4,4,4,3,3,3,3,4,72,63.0,neutral or dissatisfied +47072,52762,Female,Loyal Customer,30,Business travel,Business,1874,5,5,5,5,4,4,4,4,1,4,4,1,1,4,0,0.0,satisfied +47073,75721,Male,Loyal Customer,41,Business travel,Business,2488,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +47074,97303,Female,Loyal Customer,67,Business travel,Eco,872,2,5,5,5,3,3,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +47075,15955,Male,Loyal Customer,61,Personal Travel,Eco,528,1,5,1,5,2,1,2,2,5,5,4,2,2,2,0,11.0,neutral or dissatisfied +47076,97400,Male,Loyal Customer,49,Business travel,Business,1972,1,1,1,1,4,4,4,5,5,5,4,4,5,4,46,36.0,satisfied +47077,48003,Male,Loyal Customer,42,Business travel,Eco Plus,329,3,4,4,4,3,3,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +47078,128408,Female,disloyal Customer,39,Business travel,Business,325,3,3,3,3,4,3,4,4,1,1,4,2,3,4,31,25.0,neutral or dissatisfied +47079,75589,Male,Loyal Customer,39,Business travel,Business,337,2,4,4,4,1,3,3,2,2,2,2,4,2,1,109,120.0,neutral or dissatisfied +47080,78906,Female,Loyal Customer,50,Business travel,Business,3890,3,3,3,3,5,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +47081,22198,Male,Loyal Customer,48,Personal Travel,Eco,773,4,4,5,2,3,5,3,3,4,5,5,5,4,3,0,4.0,satisfied +47082,83097,Male,Loyal Customer,56,Personal Travel,Eco,1084,2,5,2,1,3,2,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +47083,2725,Female,Loyal Customer,60,Business travel,Business,2521,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +47084,111811,Female,Loyal Customer,60,Personal Travel,Eco,349,2,5,1,3,1,2,5,3,3,1,3,1,3,3,26,30.0,neutral or dissatisfied +47085,28219,Female,disloyal Customer,20,Business travel,Eco,873,4,4,4,3,1,4,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +47086,32969,Male,Loyal Customer,15,Personal Travel,Eco,216,4,4,4,2,4,4,4,4,3,5,4,5,4,4,0,2.0,neutral or dissatisfied +47087,26983,Male,Loyal Customer,37,Business travel,Business,2503,1,1,1,1,1,3,5,3,3,2,3,2,3,2,0,0.0,satisfied +47088,77434,Male,Loyal Customer,54,Personal Travel,Eco,532,2,4,2,3,4,2,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +47089,20735,Male,Loyal Customer,52,Business travel,Business,3827,2,2,2,2,5,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +47090,105456,Female,Loyal Customer,23,Personal Travel,Eco,998,1,4,1,1,1,1,1,1,5,4,5,5,5,1,48,39.0,neutral or dissatisfied +47091,76128,Male,disloyal Customer,34,Business travel,Business,689,2,2,2,1,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +47092,48804,Female,Loyal Customer,10,Personal Travel,Business,56,4,3,4,3,5,4,5,5,3,5,4,2,4,5,5,2.0,neutral or dissatisfied +47093,5636,Male,Loyal Customer,60,Business travel,Business,2667,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +47094,66667,Female,disloyal Customer,26,Business travel,Business,802,0,0,0,4,3,0,4,3,3,3,5,4,5,3,13,0.0,satisfied +47095,73338,Female,disloyal Customer,22,Business travel,Eco,1182,3,4,4,1,5,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +47096,120411,Female,disloyal Customer,85,Business travel,Eco,366,3,2,3,3,3,3,3,3,1,2,2,3,1,3,0,0.0,neutral or dissatisfied +47097,105485,Male,disloyal Customer,28,Business travel,Business,516,4,4,4,4,3,4,3,3,3,5,5,3,4,3,35,30.0,satisfied +47098,26709,Male,Loyal Customer,49,Personal Travel,Eco,404,3,5,3,2,3,3,3,3,5,3,5,3,5,3,43,35.0,neutral or dissatisfied +47099,60302,Female,disloyal Customer,27,Business travel,Business,406,5,5,5,5,4,1,4,4,4,2,5,5,5,4,3,16.0,satisfied +47100,100800,Male,Loyal Customer,13,Personal Travel,Eco,748,3,4,3,3,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +47101,118707,Male,Loyal Customer,24,Personal Travel,Eco,647,3,3,3,3,3,3,3,3,4,2,4,4,3,3,69,62.0,neutral or dissatisfied +47102,113237,Male,Loyal Customer,34,Personal Travel,Business,236,1,4,1,3,5,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +47103,43156,Female,Loyal Customer,67,Business travel,Business,1368,3,1,2,1,2,4,4,3,3,3,3,1,3,2,39,31.0,neutral or dissatisfied +47104,15981,Female,Loyal Customer,36,Business travel,Eco,794,4,5,3,5,4,4,4,4,3,5,4,1,2,4,77,75.0,satisfied +47105,71223,Female,disloyal Customer,27,Business travel,Eco,733,1,1,1,4,5,1,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +47106,46056,Female,Loyal Customer,33,Personal Travel,Eco,898,4,2,4,3,3,4,3,3,2,2,3,1,4,3,2,0.0,satisfied +47107,55688,Female,Loyal Customer,57,Business travel,Business,2566,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,13.0,satisfied +47108,43574,Female,Loyal Customer,35,Business travel,Business,1499,5,5,5,5,5,4,1,5,5,5,5,3,5,3,2,0.0,satisfied +47109,115932,Male,Loyal Customer,37,Business travel,Business,3736,2,3,3,3,2,1,1,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +47110,54978,Female,Loyal Customer,25,Business travel,Business,1303,3,3,3,3,4,4,4,4,5,5,5,3,5,4,21,,satisfied +47111,79029,Female,Loyal Customer,37,Business travel,Business,306,4,1,1,1,3,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +47112,88799,Female,disloyal Customer,30,Business travel,Eco Plus,545,2,2,2,4,1,2,1,1,3,4,3,3,4,1,7,2.0,neutral or dissatisfied +47113,3377,Female,Loyal Customer,30,Business travel,Business,2105,2,2,2,2,5,5,5,5,2,5,4,5,5,5,194,196.0,satisfied +47114,129266,Male,disloyal Customer,30,Business travel,Business,992,0,1,1,4,4,1,2,4,5,3,3,5,4,4,0,32.0,satisfied +47115,35033,Female,Loyal Customer,50,Business travel,Business,2658,3,3,3,3,3,1,3,5,5,5,5,2,5,1,0,0.0,satisfied +47116,28737,Male,Loyal Customer,40,Business travel,Business,1024,1,1,1,1,2,4,2,3,3,3,3,4,3,4,0,0.0,satisfied +47117,52750,Male,Loyal Customer,69,Personal Travel,Eco,2306,3,1,3,4,5,3,5,5,2,2,2,1,4,5,67,70.0,neutral or dissatisfied +47118,60525,Female,Loyal Customer,68,Personal Travel,Eco,862,2,5,2,5,5,5,4,2,2,2,2,4,2,3,2,0.0,neutral or dissatisfied +47119,127590,Female,disloyal Customer,23,Business travel,Eco,1209,2,2,2,3,1,2,1,1,5,4,4,4,4,1,1,16.0,neutral or dissatisfied +47120,95261,Male,Loyal Customer,9,Personal Travel,Eco,293,1,4,5,3,4,5,4,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +47121,85980,Male,Loyal Customer,45,Business travel,Business,2736,3,4,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +47122,93298,Female,Loyal Customer,60,Business travel,Eco Plus,406,4,2,2,2,5,2,4,4,4,4,4,1,4,5,31,8.0,satisfied +47123,8496,Male,disloyal Customer,10,Business travel,Eco,862,1,1,1,4,1,1,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +47124,57401,Female,Loyal Customer,23,Business travel,Business,1855,3,3,3,3,5,5,5,5,4,4,4,5,4,5,4,0.0,satisfied +47125,48126,Male,disloyal Customer,23,Business travel,Eco,236,3,5,3,3,4,3,2,4,2,5,1,1,4,4,0,0.0,neutral or dissatisfied +47126,61704,Male,Loyal Customer,34,Business travel,Business,1504,2,4,4,4,4,4,4,2,2,1,2,3,2,3,3,17.0,neutral or dissatisfied +47127,86980,Female,Loyal Customer,17,Business travel,Business,2822,3,2,2,2,3,3,3,3,1,4,3,2,3,3,16,8.0,neutral or dissatisfied +47128,76251,Male,Loyal Customer,46,Personal Travel,Eco,1399,3,1,3,4,3,3,4,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +47129,9157,Female,Loyal Customer,53,Business travel,Business,1560,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +47130,73997,Female,Loyal Customer,51,Business travel,Business,1972,1,1,1,1,3,5,5,4,4,4,4,3,4,3,10,29.0,satisfied +47131,32853,Male,Loyal Customer,25,Personal Travel,Eco,216,2,1,2,3,5,2,5,5,1,4,2,2,3,5,0,0.0,neutral or dissatisfied +47132,42036,Female,Loyal Customer,37,Business travel,Eco,106,5,2,2,2,5,5,5,5,3,3,2,3,3,5,30,28.0,satisfied +47133,35559,Female,Loyal Customer,23,Business travel,Eco Plus,950,0,4,0,2,2,4,2,2,4,1,5,2,5,2,0,0.0,satisfied +47134,66244,Female,Loyal Customer,41,Personal Travel,Eco,460,4,2,4,4,3,4,3,3,3,5,3,4,4,3,0,0.0,satisfied +47135,52656,Male,Loyal Customer,32,Personal Travel,Eco,110,4,2,4,3,5,4,5,5,4,3,3,1,3,5,0,0.0,satisfied +47136,63064,Female,Loyal Customer,39,Personal Travel,Eco,967,2,5,2,5,1,2,1,1,5,3,4,3,5,1,0,6.0,neutral or dissatisfied +47137,10464,Male,Loyal Customer,50,Business travel,Business,2342,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +47138,106371,Female,Loyal Customer,32,Business travel,Business,3251,2,2,2,2,3,3,3,3,4,5,5,3,4,3,3,0.0,satisfied +47139,76236,Female,Loyal Customer,32,Business travel,Eco,1399,3,3,3,3,3,3,3,3,2,4,4,2,3,3,10,6.0,neutral or dissatisfied +47140,31301,Male,Loyal Customer,26,Business travel,Business,3103,4,4,4,4,4,4,4,4,3,2,4,1,5,4,17,6.0,satisfied +47141,1085,Female,Loyal Customer,31,Personal Travel,Eco,158,3,1,3,4,3,3,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +47142,94795,Female,Loyal Customer,47,Business travel,Business,1588,2,3,2,2,3,3,3,2,2,3,2,2,2,3,22,22.0,neutral or dissatisfied +47143,55525,Female,Loyal Customer,57,Business travel,Business,3516,4,4,4,4,3,4,5,4,4,4,4,4,4,5,20,53.0,satisfied +47144,102263,Female,Loyal Customer,40,Business travel,Business,1803,2,2,2,2,2,5,4,4,4,4,4,5,4,5,8,0.0,satisfied +47145,123929,Female,Loyal Customer,39,Personal Travel,Eco,544,2,3,2,2,3,2,5,3,1,1,3,4,1,3,0,30.0,neutral or dissatisfied +47146,27298,Male,Loyal Customer,33,Business travel,Business,2610,5,5,5,5,5,4,5,5,5,1,3,5,4,5,0,0.0,satisfied +47147,63381,Female,Loyal Customer,45,Personal Travel,Eco,337,3,5,3,2,5,5,4,3,3,3,3,4,3,3,0,9.0,neutral or dissatisfied +47148,81311,Female,Loyal Customer,53,Personal Travel,Business,1299,0,5,0,4,5,5,4,3,3,0,3,4,3,5,0,14.0,satisfied +47149,110069,Male,Loyal Customer,50,Business travel,Business,869,2,5,1,5,2,3,3,2,2,2,2,2,2,2,64,55.0,neutral or dissatisfied +47150,54931,Female,Loyal Customer,50,Business travel,Business,1346,2,2,2,2,4,4,5,5,5,5,5,3,5,5,26,17.0,satisfied +47151,71562,Female,Loyal Customer,45,Business travel,Business,2842,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +47152,27593,Male,Loyal Customer,26,Personal Travel,Eco,679,2,4,2,5,5,2,5,5,3,2,4,5,5,5,0,6.0,neutral or dissatisfied +47153,20772,Female,disloyal Customer,30,Business travel,Eco,515,3,2,3,3,4,3,4,4,3,1,3,1,3,4,0,6.0,neutral or dissatisfied +47154,60185,Female,Loyal Customer,51,Business travel,Business,1844,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +47155,106438,Male,Loyal Customer,31,Personal Travel,Eco Plus,674,3,4,3,3,2,3,2,2,1,3,3,1,4,2,92,95.0,neutral or dissatisfied +47156,70461,Female,Loyal Customer,55,Business travel,Business,2889,2,2,2,2,4,4,4,4,4,4,4,3,4,4,15,0.0,satisfied +47157,27559,Male,Loyal Customer,66,Personal Travel,Eco,679,2,5,2,4,3,2,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +47158,108281,Female,Loyal Customer,52,Business travel,Business,3669,3,3,3,3,5,4,4,4,4,4,4,3,4,3,12,11.0,satisfied +47159,107822,Male,disloyal Customer,20,Business travel,Eco,349,0,0,0,4,2,0,2,2,3,3,3,3,2,2,0,0.0,satisfied +47160,116997,Female,disloyal Customer,23,Business travel,Eco,338,3,4,3,4,1,3,1,1,4,5,5,4,5,1,6,0.0,neutral or dissatisfied +47161,110363,Male,disloyal Customer,27,Business travel,Eco,663,2,1,2,4,2,2,5,2,4,1,4,2,3,2,12,11.0,neutral or dissatisfied +47162,106313,Male,Loyal Customer,17,Personal Travel,Eco,998,2,1,1,3,3,1,3,3,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +47163,93359,Male,Loyal Customer,55,Business travel,Business,3070,3,3,1,3,1,4,4,3,3,2,3,4,3,3,1,0.0,neutral or dissatisfied +47164,9347,Female,Loyal Customer,59,Business travel,Business,2599,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +47165,83684,Female,Loyal Customer,57,Business travel,Eco,177,4,3,3,3,1,4,3,4,4,4,4,4,4,3,0,2.0,neutral or dissatisfied +47166,59732,Female,Loyal Customer,12,Personal Travel,Eco Plus,787,3,5,3,5,5,3,5,5,3,2,2,2,4,5,14,2.0,neutral or dissatisfied +47167,39988,Female,Loyal Customer,43,Business travel,Eco,508,4,1,1,1,2,2,4,4,4,4,4,5,4,5,8,7.0,satisfied +47168,94530,Male,Loyal Customer,43,Business travel,Business,3537,3,4,3,3,4,5,4,5,5,5,5,4,5,4,5,2.0,satisfied +47169,53112,Male,Loyal Customer,31,Business travel,Eco,2065,5,2,2,2,5,5,5,5,2,4,3,1,3,5,0,0.0,satisfied +47170,5618,Male,Loyal Customer,70,Personal Travel,Eco,685,1,4,0,1,5,0,5,5,3,3,5,3,4,5,0,26.0,neutral or dissatisfied +47171,8417,Male,disloyal Customer,7,Business travel,Eco,862,3,3,3,3,4,3,4,4,3,2,4,2,4,4,0,9.0,neutral or dissatisfied +47172,18952,Female,Loyal Customer,62,Personal Travel,Eco,551,3,2,3,3,3,3,4,1,1,3,1,3,1,4,6,14.0,neutral or dissatisfied +47173,91047,Male,Loyal Customer,45,Personal Travel,Eco,223,3,2,0,3,3,0,3,3,2,2,3,1,3,3,5,27.0,neutral or dissatisfied +47174,125715,Male,Loyal Customer,37,Personal Travel,Eco,759,3,4,3,5,5,3,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +47175,89661,Female,Loyal Customer,44,Business travel,Business,1069,3,2,2,2,2,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +47176,26962,Female,Loyal Customer,50,Personal Travel,Business,867,1,4,0,5,5,4,3,1,1,0,1,5,1,3,0,0.0,neutral or dissatisfied +47177,46195,Male,Loyal Customer,13,Personal Travel,Eco,423,3,2,3,3,5,3,5,5,4,1,4,4,4,5,11,4.0,neutral or dissatisfied +47178,128060,Female,disloyal Customer,23,Business travel,Eco,735,0,0,0,3,1,0,1,1,5,4,5,4,4,1,0,0.0,satisfied +47179,91235,Male,Loyal Customer,30,Personal Travel,Eco,270,4,4,4,5,2,4,5,2,4,5,5,5,5,2,0,0.0,satisfied +47180,86283,Female,Loyal Customer,67,Personal Travel,Eco,356,4,4,4,4,5,4,5,2,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +47181,58938,Male,Loyal Customer,10,Personal Travel,Eco,888,2,2,2,4,4,2,4,4,4,2,3,4,3,4,9,7.0,neutral or dissatisfied +47182,18037,Female,Loyal Customer,52,Business travel,Eco,488,2,1,1,1,4,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +47183,95916,Female,Loyal Customer,53,Business travel,Business,1411,2,2,2,2,2,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +47184,32701,Male,Loyal Customer,32,Business travel,Business,2362,0,3,0,1,2,2,2,2,5,3,1,4,1,2,0,0.0,satisfied +47185,25134,Male,disloyal Customer,24,Business travel,Eco,1249,5,5,5,3,4,5,4,4,2,3,3,4,1,4,0,0.0,satisfied +47186,1293,Male,Loyal Customer,61,Personal Travel,Eco,354,4,5,4,4,1,4,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +47187,19522,Male,Loyal Customer,41,Business travel,Business,108,2,2,2,2,2,5,4,5,5,5,4,4,5,5,5,0.0,satisfied +47188,65955,Female,Loyal Customer,53,Business travel,Business,1372,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +47189,57162,Female,Loyal Customer,33,Business travel,Business,2227,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +47190,6760,Female,Loyal Customer,41,Business travel,Business,2240,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +47191,3233,Male,Loyal Customer,51,Business travel,Business,3464,4,5,5,5,5,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +47192,70190,Male,Loyal Customer,45,Business travel,Business,258,0,0,0,5,3,5,4,5,5,5,5,5,5,5,36,35.0,satisfied +47193,11077,Female,Loyal Customer,7,Personal Travel,Eco,140,4,1,4,2,5,4,5,5,1,5,2,4,1,5,0,0.0,neutral or dissatisfied +47194,83055,Female,Loyal Customer,35,Business travel,Business,1084,4,4,4,4,3,5,4,4,4,4,4,3,4,5,5,11.0,satisfied +47195,24199,Male,disloyal Customer,48,Business travel,Eco,302,5,0,5,3,3,5,3,3,5,4,3,3,1,3,0,0.0,satisfied +47196,111331,Male,Loyal Customer,18,Personal Travel,Eco,283,3,2,4,3,2,4,2,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +47197,69521,Female,Loyal Customer,29,Business travel,Business,2475,3,3,3,3,5,5,5,3,3,4,5,5,3,5,1,6.0,satisfied +47198,98033,Female,Loyal Customer,52,Personal Travel,Eco Plus,1014,4,3,4,5,5,3,3,1,1,4,1,4,1,4,6,4.0,satisfied +47199,9963,Female,Loyal Customer,40,Business travel,Eco,108,4,4,4,4,4,5,4,4,2,5,4,2,3,4,0,0.0,satisfied +47200,11367,Male,Loyal Customer,8,Personal Travel,Eco,295,1,2,1,4,5,1,5,5,1,5,3,4,3,5,0,0.0,neutral or dissatisfied +47201,76712,Female,Loyal Customer,30,Business travel,Business,1736,4,4,4,4,4,4,4,4,4,4,5,5,4,4,3,0.0,satisfied +47202,26760,Female,Loyal Customer,42,Personal Travel,Eco,859,2,5,1,4,3,5,4,5,5,1,5,5,5,3,3,10.0,neutral or dissatisfied +47203,10787,Female,disloyal Customer,38,Business travel,Eco,216,4,2,4,4,4,4,4,4,3,4,3,4,2,4,187,205.0,neutral or dissatisfied +47204,103029,Female,disloyal Customer,50,Business travel,Eco,546,1,0,1,4,3,1,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +47205,94060,Female,Loyal Customer,49,Business travel,Business,323,3,1,1,1,2,2,2,3,3,2,3,4,3,3,2,0.0,neutral or dissatisfied +47206,97534,Male,Loyal Customer,44,Business travel,Business,3765,5,5,5,5,5,5,5,5,5,5,5,5,3,5,150,128.0,satisfied +47207,111350,Female,disloyal Customer,23,Business travel,Business,777,0,3,0,5,3,0,3,3,3,5,5,5,4,3,0,0.0,satisfied +47208,129766,Male,Loyal Customer,12,Personal Travel,Eco,337,1,2,1,4,1,1,3,1,1,2,3,1,3,1,17,3.0,neutral or dissatisfied +47209,123042,Male,disloyal Customer,21,Business travel,Eco,468,2,0,2,4,4,2,4,4,3,2,5,5,4,4,17,39.0,neutral or dissatisfied +47210,63148,Male,Loyal Customer,70,Business travel,Business,447,4,4,4,4,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +47211,87811,Female,Loyal Customer,52,Business travel,Business,214,3,2,2,2,4,3,3,2,2,2,3,3,2,4,4,0.0,neutral or dissatisfied +47212,26721,Female,Loyal Customer,38,Business travel,Eco Plus,404,3,4,4,4,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +47213,77297,Male,Loyal Customer,34,Personal Travel,Eco,391,3,4,3,3,4,3,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +47214,100970,Female,Loyal Customer,59,Business travel,Business,1142,5,5,5,5,2,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +47215,125932,Female,Loyal Customer,34,Personal Travel,Eco,861,2,4,2,2,3,2,5,3,3,3,5,5,4,3,2,3.0,neutral or dissatisfied +47216,121089,Male,Loyal Customer,58,Personal Travel,Eco,196,2,4,2,3,4,2,4,4,3,2,4,5,5,4,0,5.0,neutral or dissatisfied +47217,40255,Male,Loyal Customer,38,Business travel,Business,3733,1,1,1,1,2,2,2,4,4,4,4,3,4,4,0,1.0,satisfied +47218,121449,Male,Loyal Customer,45,Business travel,Business,2935,3,3,5,3,1,3,3,3,3,3,3,3,3,4,16,0.0,neutral or dissatisfied +47219,43162,Male,Loyal Customer,28,Business travel,Business,2357,2,3,3,3,2,2,2,2,1,4,3,4,4,2,0,10.0,neutral or dissatisfied +47220,72426,Female,Loyal Customer,48,Business travel,Eco,929,1,5,5,5,3,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +47221,118393,Female,Loyal Customer,29,Business travel,Business,2053,4,5,5,5,4,4,4,4,3,4,3,4,3,4,19,13.0,neutral or dissatisfied +47222,68980,Male,Loyal Customer,14,Personal Travel,Eco,700,0,4,0,4,4,0,4,4,3,4,4,4,5,4,0,0.0,satisfied +47223,119780,Female,Loyal Customer,7,Personal Travel,Business,912,2,4,2,3,4,2,4,4,4,5,4,4,5,4,0,17.0,neutral or dissatisfied +47224,59906,Male,Loyal Customer,54,Business travel,Business,2300,4,4,2,4,4,5,4,2,2,2,2,5,2,4,10,0.0,satisfied +47225,33853,Female,Loyal Customer,64,Personal Travel,Eco,1609,4,2,4,4,5,4,3,5,5,4,5,1,5,3,30,0.0,satisfied +47226,62281,Female,Loyal Customer,49,Business travel,Business,414,3,3,3,3,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +47227,105877,Female,Loyal Customer,45,Personal Travel,Business,283,3,5,3,3,2,5,5,4,4,3,4,5,4,4,15,14.0,neutral or dissatisfied +47228,62628,Male,Loyal Customer,35,Personal Travel,Eco,1744,4,1,3,3,4,3,4,4,4,2,3,4,2,4,0,0.0,neutral or dissatisfied +47229,69009,Male,Loyal Customer,46,Business travel,Business,1389,1,1,1,1,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +47230,12425,Male,Loyal Customer,58,Personal Travel,Eco,190,4,4,4,3,5,4,5,5,1,2,3,2,4,5,21,22.0,neutral or dissatisfied +47231,18649,Female,Loyal Customer,26,Personal Travel,Eco,253,1,5,1,3,2,1,2,2,3,2,5,2,1,2,0,0.0,neutral or dissatisfied +47232,56065,Female,Loyal Customer,24,Personal Travel,Eco,2586,3,4,3,4,3,5,5,4,2,3,4,5,5,5,0,9.0,neutral or dissatisfied +47233,644,Female,Loyal Customer,49,Business travel,Business,89,0,4,0,3,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +47234,48909,Male,disloyal Customer,24,Business travel,Eco,308,5,0,5,1,2,5,2,2,5,5,4,3,5,2,0,8.0,satisfied +47235,20522,Female,Loyal Customer,16,Personal Travel,Business,533,1,5,1,4,5,1,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +47236,12767,Female,Loyal Customer,61,Business travel,Eco Plus,689,2,1,1,1,2,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +47237,87185,Female,disloyal Customer,29,Business travel,Eco,946,1,1,1,3,1,1,1,1,2,1,3,3,4,1,82,68.0,neutral or dissatisfied +47238,17729,Female,Loyal Customer,18,Business travel,Business,529,3,3,4,3,4,4,4,4,4,5,1,3,2,4,0,4.0,satisfied +47239,96066,Male,Loyal Customer,26,Personal Travel,Eco,1069,3,4,2,4,1,2,1,1,3,5,4,1,3,1,16,24.0,neutral or dissatisfied +47240,26617,Female,disloyal Customer,23,Business travel,Eco,270,1,4,1,3,4,1,4,4,4,2,5,4,2,4,11,42.0,neutral or dissatisfied +47241,5981,Female,Loyal Customer,42,Business travel,Business,925,5,4,5,5,4,5,5,4,4,4,4,3,4,5,11,0.0,satisfied +47242,62801,Male,Loyal Customer,53,Personal Travel,Eco,2504,2,2,2,3,2,3,3,3,2,3,2,3,1,3,0,9.0,neutral or dissatisfied +47243,58227,Male,Loyal Customer,10,Personal Travel,Eco,925,3,5,3,1,4,3,3,4,1,5,1,2,2,4,0,6.0,neutral or dissatisfied +47244,40536,Male,Loyal Customer,60,Business travel,Eco,391,2,5,5,5,2,2,2,2,3,3,1,1,1,2,0,0.0,satisfied +47245,127965,Male,Loyal Customer,30,Personal Travel,Eco,1999,2,4,2,3,5,2,3,5,5,4,4,5,4,5,9,26.0,neutral or dissatisfied +47246,50867,Male,Loyal Customer,44,Personal Travel,Eco,134,4,1,4,4,4,4,4,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +47247,41426,Male,Loyal Customer,32,Personal Travel,Eco,563,3,4,2,1,5,2,5,5,5,2,5,4,5,5,9,14.0,neutral or dissatisfied +47248,70114,Female,disloyal Customer,37,Business travel,Business,550,2,2,2,4,3,2,3,3,4,4,4,4,4,3,3,0.0,neutral or dissatisfied +47249,57644,Female,Loyal Customer,53,Business travel,Business,200,5,5,5,5,5,4,2,4,4,4,5,2,4,2,0,0.0,satisfied +47250,27835,Female,Loyal Customer,56,Personal Travel,Eco,1448,4,3,4,3,4,2,1,1,1,4,1,3,1,3,0,0.0,satisfied +47251,106414,Female,Loyal Customer,40,Personal Travel,Eco,674,4,4,4,2,1,4,1,1,5,5,4,5,5,1,0,9.0,satisfied +47252,3576,Female,Loyal Customer,56,Personal Travel,Eco,227,3,4,3,4,2,4,1,5,5,3,5,3,5,3,82,78.0,neutral or dissatisfied +47253,93589,Female,Loyal Customer,40,Personal Travel,Eco,159,2,5,2,2,2,2,5,2,4,3,4,4,5,2,0,2.0,neutral or dissatisfied +47254,76393,Male,Loyal Customer,17,Personal Travel,Eco,931,4,5,4,4,5,4,5,5,4,5,4,5,4,5,0,0.0,satisfied +47255,40978,Male,Loyal Customer,43,Business travel,Eco Plus,601,5,1,1,1,5,5,5,5,5,1,3,1,3,5,0,0.0,satisfied +47256,29022,Male,disloyal Customer,23,Business travel,Eco,297,4,3,4,3,2,4,2,2,5,2,2,1,2,2,0,0.0,neutral or dissatisfied +47257,124591,Male,Loyal Customer,60,Business travel,Eco,500,3,5,5,5,3,3,3,3,4,1,3,3,4,3,15,8.0,neutral or dissatisfied +47258,17282,Male,disloyal Customer,39,Business travel,Eco,440,4,3,4,2,1,4,1,1,3,4,4,5,1,1,0,0.0,satisfied +47259,41468,Male,Loyal Customer,38,Business travel,Business,1482,4,4,4,4,5,5,1,4,4,4,4,3,4,4,3,0.0,satisfied +47260,120334,Male,Loyal Customer,18,Business travel,Eco Plus,268,3,5,5,5,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +47261,83069,Male,Loyal Customer,42,Business travel,Eco,957,1,0,0,3,1,1,1,1,4,1,4,3,3,1,0,0.0,neutral or dissatisfied +47262,74458,Female,disloyal Customer,50,Business travel,Business,1464,3,3,3,5,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +47263,41267,Female,disloyal Customer,27,Business travel,Eco,305,1,0,1,1,2,1,2,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +47264,98886,Male,Loyal Customer,50,Personal Travel,Eco,991,3,4,3,3,5,3,5,5,5,2,4,5,5,5,25,12.0,neutral or dissatisfied +47265,59996,Male,Loyal Customer,42,Personal Travel,Eco,1068,1,3,1,4,5,1,2,5,3,5,3,4,3,5,2,0.0,neutral or dissatisfied +47266,89357,Female,Loyal Customer,20,Personal Travel,Eco,1587,1,4,1,2,3,1,3,3,4,3,5,3,5,3,12,0.0,neutral or dissatisfied +47267,99447,Female,Loyal Customer,34,Business travel,Business,1994,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +47268,79476,Female,disloyal Customer,49,Business travel,Business,760,1,1,1,2,3,1,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +47269,94751,Female,Loyal Customer,52,Business travel,Eco,239,2,4,4,4,2,3,3,2,2,2,2,1,2,1,14,12.0,neutral or dissatisfied +47270,28855,Female,disloyal Customer,31,Business travel,Eco,978,3,3,3,1,5,3,5,5,2,5,1,4,2,5,0,0.0,neutral or dissatisfied +47271,110322,Male,Loyal Customer,50,Business travel,Business,2851,1,1,1,1,3,4,4,5,5,5,5,4,5,3,5,0.0,satisfied +47272,27144,Female,Loyal Customer,42,Business travel,Business,2701,4,5,5,5,4,4,4,2,5,3,2,4,3,4,0,24.0,neutral or dissatisfied +47273,105515,Female,Loyal Customer,54,Business travel,Business,2058,2,2,2,2,4,4,5,3,3,3,3,5,3,4,0,10.0,satisfied +47274,89300,Female,Loyal Customer,45,Personal Travel,Eco,453,1,4,2,4,5,1,5,4,4,2,4,1,4,5,10,1.0,neutral or dissatisfied +47275,17868,Male,Loyal Customer,25,Business travel,Business,3651,4,4,4,4,4,4,4,4,5,4,2,4,3,4,41,26.0,satisfied +47276,18868,Female,disloyal Customer,21,Business travel,Eco,448,2,0,1,3,2,1,2,2,1,5,4,1,2,2,0,0.0,neutral or dissatisfied +47277,1080,Male,Loyal Customer,41,Personal Travel,Eco,89,3,4,0,2,0,2,2,4,3,3,2,2,2,2,140,141.0,neutral or dissatisfied +47278,15924,Male,Loyal Customer,66,Business travel,Eco,738,3,5,5,5,3,3,3,3,5,3,4,5,4,3,0,1.0,satisfied +47279,86820,Female,disloyal Customer,43,Business travel,Eco,692,1,1,1,4,1,1,1,1,3,1,4,3,3,1,6,7.0,neutral or dissatisfied +47280,55703,Male,Loyal Customer,27,Personal Travel,Eco,1062,5,2,5,3,5,5,5,5,1,2,3,2,3,5,0,8.0,satisfied +47281,72085,Male,Loyal Customer,55,Personal Travel,Eco,2486,3,2,2,4,5,2,5,5,4,5,4,3,3,5,0,0.0,neutral or dissatisfied +47282,43651,Male,Loyal Customer,51,Business travel,Eco,695,4,2,2,2,4,4,4,4,3,3,4,1,1,4,91,99.0,satisfied +47283,77312,Male,Loyal Customer,32,Business travel,Business,626,2,2,2,2,4,5,4,4,5,5,5,5,4,4,0,5.0,satisfied +47284,72657,Female,Loyal Customer,30,Personal Travel,Eco,985,1,4,1,3,1,1,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +47285,92597,Female,Loyal Customer,9,Business travel,Eco,2218,2,5,5,5,2,2,3,2,2,4,4,4,4,2,34,29.0,neutral or dissatisfied +47286,7888,Female,Loyal Customer,66,Personal Travel,Eco,948,2,3,2,3,2,4,3,4,4,2,4,4,4,2,82,70.0,neutral or dissatisfied +47287,21164,Female,disloyal Customer,38,Business travel,Eco Plus,954,3,2,2,4,4,2,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +47288,10292,Female,disloyal Customer,26,Business travel,Business,216,4,4,4,1,5,4,5,5,3,2,5,4,4,5,15,27.0,neutral or dissatisfied +47289,100456,Female,Loyal Customer,66,Personal Travel,Business,759,2,5,2,5,2,4,4,3,3,2,3,3,3,4,12,0.0,neutral or dissatisfied +47290,59647,Male,Loyal Customer,15,Business travel,Eco,787,4,2,2,2,4,4,3,4,5,1,3,5,5,4,0,0.0,satisfied +47291,3413,Male,Loyal Customer,41,Personal Travel,Eco,240,2,5,2,5,5,2,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +47292,117302,Male,Loyal Customer,48,Business travel,Eco Plus,304,3,4,4,4,3,3,3,3,2,3,4,4,4,3,33,12.0,neutral or dissatisfied +47293,105250,Female,disloyal Customer,28,Business travel,Business,2106,5,4,4,2,2,4,2,2,3,4,3,5,4,2,0,0.0,satisfied +47294,115512,Male,Loyal Customer,49,Business travel,Business,3719,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +47295,97277,Male,Loyal Customer,34,Business travel,Business,2324,4,3,4,4,5,4,5,5,5,5,5,5,5,5,99,105.0,satisfied +47296,80592,Male,Loyal Customer,48,Business travel,Business,1747,4,4,4,4,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +47297,36018,Female,Loyal Customer,62,Business travel,Business,399,3,3,3,3,1,1,2,4,4,4,4,2,4,4,0,0.0,satisfied +47298,71040,Female,Loyal Customer,49,Business travel,Business,2322,1,0,0,3,2,3,3,3,3,0,3,1,3,4,19,13.0,neutral or dissatisfied +47299,6842,Female,disloyal Customer,25,Business travel,Business,303,5,5,5,3,5,5,5,5,4,4,5,4,5,5,0,0.0,satisfied +47300,12656,Male,Loyal Customer,41,Business travel,Business,1236,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,4.0,satisfied +47301,60349,Male,Loyal Customer,43,Personal Travel,Eco,836,3,4,3,3,3,3,3,3,3,5,3,4,1,3,0,0.0,neutral or dissatisfied +47302,75808,Female,Loyal Customer,43,Business travel,Business,2466,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +47303,64698,Male,Loyal Customer,53,Business travel,Business,469,1,1,1,1,2,4,5,3,3,4,3,5,3,4,3,0.0,satisfied +47304,105091,Female,disloyal Customer,27,Business travel,Business,220,4,4,4,3,3,4,3,3,3,2,5,5,5,3,11,7.0,satisfied +47305,19797,Male,Loyal Customer,45,Personal Travel,Eco,578,2,4,2,3,3,2,3,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +47306,15926,Female,Loyal Customer,45,Business travel,Eco,566,1,3,3,3,2,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +47307,47042,Male,Loyal Customer,40,Business travel,Business,2404,1,1,1,1,5,5,1,4,4,4,4,3,4,2,0,0.0,satisfied +47308,95568,Male,Loyal Customer,41,Personal Travel,Eco Plus,562,2,4,2,3,2,2,2,2,5,2,5,5,4,2,69,66.0,neutral or dissatisfied +47309,63707,Female,Loyal Customer,55,Business travel,Business,1660,2,2,2,2,3,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +47310,123307,Female,disloyal Customer,23,Business travel,Eco,328,2,4,2,4,3,2,3,3,2,5,4,2,3,3,0,1.0,neutral or dissatisfied +47311,5818,Male,Loyal Customer,69,Personal Travel,Eco,157,1,4,0,1,2,0,2,2,4,4,4,3,4,2,0,16.0,neutral or dissatisfied +47312,19211,Male,Loyal Customer,55,Business travel,Eco,588,4,4,5,4,4,4,4,4,2,5,1,1,2,4,26,19.0,satisfied +47313,22295,Male,Loyal Customer,53,Business travel,Eco,238,2,5,5,5,2,2,2,2,4,1,1,3,5,2,93,85.0,satisfied +47314,119802,Male,Loyal Customer,39,Business travel,Business,3868,3,3,3,3,2,5,5,1,1,2,1,3,1,5,3,3.0,satisfied +47315,93754,Female,Loyal Customer,34,Business travel,Business,368,2,4,4,4,3,4,4,2,2,2,2,4,2,1,44,40.0,neutral or dissatisfied +47316,63103,Female,disloyal Customer,8,Business travel,Eco,846,2,2,2,4,4,2,4,4,2,1,4,4,3,4,16,26.0,neutral or dissatisfied +47317,75185,Male,disloyal Customer,25,Business travel,Eco,1652,1,1,1,4,5,1,5,5,3,1,4,1,3,5,0,0.0,neutral or dissatisfied +47318,105746,Male,disloyal Customer,24,Business travel,Eco,919,4,4,4,3,2,4,2,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +47319,35411,Female,Loyal Customer,53,Business travel,Business,544,4,4,2,4,4,5,5,2,2,2,2,4,2,5,31,18.0,satisfied +47320,76436,Female,Loyal Customer,66,Personal Travel,Eco,405,3,2,3,3,2,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +47321,122891,Male,Loyal Customer,44,Business travel,Business,3343,3,3,3,3,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +47322,50675,Female,Loyal Customer,27,Personal Travel,Eco,86,3,3,0,4,4,0,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +47323,71976,Female,Loyal Customer,60,Business travel,Business,1440,3,3,3,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +47324,29339,Female,Loyal Customer,53,Personal Travel,Eco,859,3,5,3,2,5,1,2,4,4,3,4,5,4,3,23,27.0,neutral or dissatisfied +47325,34946,Male,Loyal Customer,54,Personal Travel,Eco,395,1,5,1,4,2,1,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +47326,27323,Female,Loyal Customer,43,Business travel,Business,2269,3,3,3,3,2,5,2,5,5,5,5,1,5,2,0,5.0,satisfied +47327,29537,Male,Loyal Customer,57,Business travel,Business,1533,3,4,3,3,3,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +47328,11297,Male,Loyal Customer,55,Personal Travel,Eco,166,4,5,4,3,2,4,2,2,5,5,5,5,5,2,41,32.0,neutral or dissatisfied +47329,127373,Male,Loyal Customer,55,Business travel,Business,3101,2,2,3,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +47330,20096,Male,Loyal Customer,45,Business travel,Business,1593,4,4,4,4,2,1,1,2,2,3,2,2,2,2,10,4.0,satisfied +47331,103651,Male,Loyal Customer,50,Business travel,Business,2330,2,2,2,2,2,5,5,3,3,3,3,5,3,3,95,113.0,satisfied +47332,38374,Male,Loyal Customer,26,Personal Travel,Eco,1111,2,5,1,1,4,1,4,4,5,2,5,4,4,4,0,9.0,neutral or dissatisfied +47333,36106,Male,Loyal Customer,38,Business travel,Eco Plus,413,4,4,4,4,4,4,4,4,5,3,2,2,1,4,0,0.0,satisfied +47334,52050,Female,Loyal Customer,48,Business travel,Eco,351,3,2,2,2,4,2,2,3,3,3,3,4,3,4,0,0.0,satisfied +47335,23698,Male,Loyal Customer,49,Business travel,Eco,251,1,4,4,4,2,1,2,2,3,2,2,1,2,2,0,0.0,neutral or dissatisfied +47336,123094,Male,Loyal Customer,39,Business travel,Business,468,2,2,2,2,2,5,4,4,4,4,4,5,4,3,4,0.0,satisfied +47337,52288,Female,Loyal Customer,39,Business travel,Business,451,3,3,3,3,3,3,3,4,4,4,4,2,4,3,0,3.0,satisfied +47338,105532,Male,Loyal Customer,12,Business travel,Business,611,1,1,1,1,5,4,5,5,5,3,4,3,5,5,0,0.0,satisfied +47339,46025,Male,Loyal Customer,46,Business travel,Eco,996,2,5,5,5,2,2,2,2,2,3,1,5,4,2,18,18.0,satisfied +47340,128902,Female,Loyal Customer,61,Personal Travel,Eco,2454,3,5,3,3,3,1,1,3,3,5,4,1,4,1,0,0.0,neutral or dissatisfied +47341,94607,Male,Loyal Customer,58,Business travel,Business,3138,1,1,2,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +47342,14117,Female,Loyal Customer,43,Business travel,Business,1676,5,5,5,5,5,4,4,5,5,5,5,4,5,3,3,0.0,satisfied +47343,3850,Male,Loyal Customer,35,Personal Travel,Eco,650,3,5,3,4,5,3,3,5,2,2,1,3,5,5,0,0.0,neutral or dissatisfied +47344,53874,Male,Loyal Customer,47,Business travel,Business,2693,4,5,5,5,2,4,4,1,1,1,4,4,1,4,5,1.0,neutral or dissatisfied +47345,68884,Female,disloyal Customer,64,Business travel,Eco,936,3,3,3,4,5,3,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +47346,30553,Female,Loyal Customer,42,Business travel,Eco Plus,1026,2,3,3,3,3,3,3,2,2,2,2,1,2,1,52,61.0,neutral or dissatisfied +47347,71091,Male,Loyal Customer,35,Business travel,Eco Plus,802,3,4,4,4,3,3,3,3,1,1,3,3,3,3,60,51.0,neutral or dissatisfied +47348,100680,Male,disloyal Customer,17,Business travel,Eco,628,4,0,4,3,5,4,5,5,4,4,4,4,4,5,3,0.0,neutral or dissatisfied +47349,107080,Male,Loyal Customer,63,Personal Travel,Eco,395,2,4,2,5,1,2,1,1,4,2,5,5,5,1,19,15.0,neutral or dissatisfied +47350,81062,Male,Loyal Customer,48,Personal Travel,Eco Plus,1399,2,1,2,3,1,2,5,1,3,3,4,1,3,1,38,40.0,neutral or dissatisfied +47351,11216,Male,Loyal Customer,17,Personal Travel,Eco,224,3,5,3,5,4,3,4,4,4,4,4,5,4,4,58,49.0,neutral or dissatisfied +47352,105736,Female,Loyal Customer,20,Business travel,Business,883,4,1,1,1,4,4,4,4,4,5,3,1,2,4,20,30.0,neutral or dissatisfied +47353,101889,Male,Loyal Customer,29,Business travel,Business,2173,3,3,3,3,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +47354,116211,Male,Loyal Customer,40,Personal Travel,Eco,296,4,5,4,1,5,4,5,5,4,4,4,3,4,5,42,30.0,neutral or dissatisfied +47355,22819,Female,Loyal Customer,38,Business travel,Eco,302,3,2,2,2,3,5,3,3,2,4,2,1,1,3,0,0.0,satisfied +47356,7825,Male,Loyal Customer,64,Personal Travel,Eco,650,3,2,3,1,5,3,5,5,3,5,2,1,2,5,0,5.0,neutral or dissatisfied +47357,33113,Male,Loyal Customer,10,Personal Travel,Eco,201,2,3,0,3,1,0,1,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +47358,67863,Male,Loyal Customer,70,Personal Travel,Eco,1205,2,3,2,3,2,2,2,2,4,1,3,2,4,2,13,6.0,neutral or dissatisfied +47359,25984,Female,disloyal Customer,37,Business travel,Eco,577,4,3,4,2,5,4,5,5,5,5,1,3,5,5,0,28.0,neutral or dissatisfied +47360,116574,Female,Loyal Customer,60,Business travel,Business,325,4,4,4,4,4,5,5,5,5,5,5,5,5,4,17,15.0,satisfied +47361,34724,Female,disloyal Customer,26,Business travel,Eco,301,1,5,1,2,4,1,3,4,2,1,1,1,5,4,4,0.0,neutral or dissatisfied +47362,86924,Female,Loyal Customer,38,Personal Travel,Eco,341,3,1,3,3,4,3,4,4,2,5,2,4,3,4,9,22.0,neutral or dissatisfied +47363,82841,Female,Loyal Customer,31,Business travel,Business,594,4,5,5,5,4,4,4,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +47364,90787,Female,Loyal Customer,43,Business travel,Eco,270,1,2,2,2,1,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +47365,97969,Male,Loyal Customer,18,Personal Travel,Eco,483,4,2,4,4,2,4,2,2,1,2,3,4,3,2,53,39.0,neutral or dissatisfied +47366,39574,Male,Loyal Customer,40,Business travel,Eco,954,5,2,3,2,5,5,5,5,1,3,4,1,4,5,105,98.0,satisfied +47367,54807,Female,Loyal Customer,32,Business travel,Business,2994,1,1,1,1,4,4,4,4,2,5,3,4,4,4,43,47.0,satisfied +47368,70078,Male,Loyal Customer,25,Business travel,Business,2685,2,2,2,2,5,5,5,4,4,4,4,5,5,5,175,,satisfied +47369,108732,Female,Loyal Customer,33,Personal Travel,Eco,591,3,5,3,3,3,3,3,3,4,2,5,4,4,3,24,22.0,neutral or dissatisfied +47370,37551,Male,disloyal Customer,19,Business travel,Eco,1028,1,1,1,3,4,1,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +47371,15513,Female,Loyal Customer,41,Personal Travel,Eco,433,4,5,4,3,2,4,4,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +47372,105320,Male,disloyal Customer,25,Business travel,Business,452,5,0,4,1,3,4,5,3,4,4,5,3,4,3,44,27.0,satisfied +47373,73296,Male,Loyal Customer,56,Business travel,Business,2730,1,1,1,1,5,5,4,5,5,5,5,4,5,5,12,14.0,satisfied +47374,26779,Female,Loyal Customer,39,Business travel,Business,2602,4,4,4,4,3,2,1,4,4,4,4,4,4,1,0,5.0,satisfied +47375,12573,Female,Loyal Customer,49,Business travel,Business,2854,5,5,1,5,1,3,3,5,5,4,5,2,5,3,33,35.0,neutral or dissatisfied +47376,26423,Male,Loyal Customer,42,Business travel,Eco,787,5,2,2,2,5,5,5,5,3,4,5,2,2,5,33,32.0,satisfied +47377,27940,Female,Loyal Customer,32,Business travel,Eco,1774,0,0,0,4,3,0,2,3,1,1,4,2,2,3,0,0.0,satisfied +47378,71270,Male,Loyal Customer,59,Personal Travel,Eco,733,1,3,1,3,1,1,4,1,2,3,3,3,4,1,1,3.0,neutral or dissatisfied +47379,7868,Male,Loyal Customer,28,Business travel,Business,910,2,2,3,2,5,5,5,5,3,2,4,4,4,5,0,0.0,satisfied +47380,509,Female,Loyal Customer,57,Business travel,Business,2241,1,1,1,1,4,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +47381,53092,Female,disloyal Customer,23,Business travel,Eco Plus,2327,2,2,2,3,2,2,2,4,4,2,3,2,3,2,315,346.0,neutral or dissatisfied +47382,102114,Female,disloyal Customer,44,Business travel,Business,258,3,3,3,4,3,3,3,3,5,5,5,5,5,3,7,4.0,neutral or dissatisfied +47383,84899,Female,Loyal Customer,52,Personal Travel,Eco,481,2,5,2,1,1,2,2,5,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +47384,128965,Female,disloyal Customer,36,Business travel,Eco,236,4,3,4,3,5,4,5,5,1,5,3,1,2,5,0,0.0,neutral or dissatisfied +47385,100548,Female,Loyal Customer,28,Business travel,Business,3628,3,3,3,3,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +47386,73707,Female,Loyal Customer,41,Business travel,Eco,192,3,5,5,5,3,3,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +47387,94900,Female,Loyal Customer,38,Business travel,Eco,239,2,2,3,2,2,2,2,2,3,1,2,5,4,2,1,0.0,satisfied +47388,36997,Female,Loyal Customer,11,Personal Travel,Eco,899,5,4,5,4,3,5,3,3,5,2,4,4,5,3,24,27.0,satisfied +47389,65441,Female,Loyal Customer,28,Business travel,Business,3733,3,3,3,3,5,5,5,5,4,4,4,5,5,5,3,0.0,satisfied +47390,67544,Male,Loyal Customer,32,Personal Travel,Business,1235,4,5,4,4,5,4,5,5,4,2,3,5,5,5,6,1.0,neutral or dissatisfied +47391,76967,Female,Loyal Customer,41,Personal Travel,Eco,1990,1,1,1,4,3,1,4,3,2,2,3,2,3,3,5,8.0,neutral or dissatisfied +47392,100361,Male,Loyal Customer,47,Personal Travel,Eco,1034,3,5,3,2,3,2,2,4,3,4,4,2,4,2,183,144.0,neutral or dissatisfied +47393,80953,Male,Loyal Customer,71,Business travel,Business,3269,3,3,3,3,4,5,5,5,1,1,2,5,3,5,184,174.0,satisfied +47394,103592,Female,Loyal Customer,77,Business travel,Business,1974,3,2,4,2,5,2,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +47395,37028,Female,disloyal Customer,26,Business travel,Business,994,2,5,1,4,1,1,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +47396,41362,Female,disloyal Customer,25,Business travel,Eco,913,4,4,4,1,3,4,3,3,2,3,1,4,5,3,0,0.0,neutral or dissatisfied +47397,113200,Female,Loyal Customer,39,Business travel,Business,3007,3,3,3,3,4,5,5,5,5,5,5,4,5,5,1,10.0,satisfied +47398,79421,Male,Loyal Customer,62,Personal Travel,Eco,502,2,4,2,3,5,2,5,5,5,4,4,4,4,5,73,56.0,neutral or dissatisfied +47399,41814,Female,Loyal Customer,52,Business travel,Business,489,4,4,4,4,1,5,4,5,5,5,5,2,5,5,0,0.0,satisfied +47400,77588,Female,disloyal Customer,25,Business travel,Business,731,5,2,5,1,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +47401,41412,Female,Loyal Customer,28,Personal Travel,Eco,563,3,4,4,4,1,4,1,1,4,2,4,1,3,1,0,9.0,neutral or dissatisfied +47402,8494,Female,Loyal Customer,57,Business travel,Business,3535,3,5,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +47403,108216,Male,disloyal Customer,57,Business travel,Business,777,5,5,5,2,2,5,2,2,3,2,4,5,5,2,0,0.0,satisfied +47404,65564,Female,Loyal Customer,42,Business travel,Business,3142,3,3,3,3,5,5,4,4,4,4,5,5,4,3,6,9.0,satisfied +47405,100740,Male,Loyal Customer,37,Business travel,Business,328,2,2,2,2,2,4,3,2,2,2,2,1,2,4,19,22.0,neutral or dissatisfied +47406,38347,Male,Loyal Customer,26,Business travel,Eco,1173,5,3,3,3,5,5,4,5,3,5,4,3,4,5,0,0.0,satisfied +47407,47987,Male,Loyal Customer,32,Personal Travel,Eco,838,4,5,4,2,2,4,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +47408,119181,Male,Loyal Customer,50,Business travel,Business,331,5,5,2,5,3,4,4,4,4,4,4,5,4,4,73,64.0,satisfied +47409,65313,Male,Loyal Customer,26,Personal Travel,Business,631,2,4,3,2,4,3,5,4,2,4,1,5,4,4,7,0.0,neutral or dissatisfied +47410,38351,Male,Loyal Customer,45,Business travel,Business,3038,2,2,2,2,5,3,2,4,4,4,4,5,4,2,0,0.0,satisfied +47411,81599,Male,Loyal Customer,52,Business travel,Business,334,0,0,0,4,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +47412,121991,Female,Loyal Customer,57,Business travel,Business,3038,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +47413,47385,Male,Loyal Customer,49,Business travel,Business,1809,3,4,4,4,2,3,3,3,3,3,3,2,3,3,65,43.0,neutral or dissatisfied +47414,50171,Female,Loyal Customer,49,Business travel,Business,89,2,3,4,3,2,3,4,3,3,3,2,3,3,2,37,30.0,neutral or dissatisfied +47415,43220,Female,disloyal Customer,54,Business travel,Eco,423,2,0,3,4,3,3,3,3,1,3,2,2,5,3,1,0.0,neutral or dissatisfied +47416,85066,Female,Loyal Customer,25,Business travel,Business,3248,1,1,1,1,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +47417,36817,Male,Loyal Customer,18,Business travel,Eco Plus,2300,4,3,5,3,4,4,5,4,1,5,4,4,3,4,3,0.0,satisfied +47418,37429,Male,disloyal Customer,24,Business travel,Business,1076,5,0,5,3,3,5,3,3,5,2,2,3,2,3,0,0.0,satisfied +47419,24418,Female,disloyal Customer,8,Business travel,Eco,634,0,4,0,1,5,0,5,5,2,5,1,4,2,5,0,0.0,satisfied +47420,31687,Female,Loyal Customer,27,Business travel,Business,967,2,1,5,1,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +47421,69034,Male,disloyal Customer,26,Business travel,Business,1389,4,4,4,1,4,4,4,4,5,2,5,3,4,4,13,0.0,satisfied +47422,12322,Female,Loyal Customer,38,Business travel,Business,192,3,3,3,3,4,3,1,5,5,5,4,2,5,2,0,0.0,satisfied +47423,96788,Male,Loyal Customer,51,Business travel,Business,2888,3,3,3,3,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +47424,81588,Female,Loyal Customer,63,Personal Travel,Business,349,4,4,4,2,3,5,5,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +47425,69189,Female,Loyal Customer,41,Personal Travel,Eco,187,3,4,3,2,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +47426,21624,Male,disloyal Customer,21,Business travel,Eco,780,4,4,4,3,4,4,4,4,1,2,3,4,4,4,37,16.0,neutral or dissatisfied +47427,117028,Male,Loyal Customer,65,Business travel,Business,3193,2,1,1,1,2,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +47428,18262,Female,Loyal Customer,27,Personal Travel,Eco,179,1,4,1,3,4,1,4,4,2,5,4,2,3,4,0,0.0,neutral or dissatisfied +47429,122872,Male,Loyal Customer,47,Personal Travel,Eco,226,2,4,2,3,5,2,5,5,4,4,5,3,4,5,3,0.0,neutral or dissatisfied +47430,109678,Female,Loyal Customer,30,Personal Travel,Eco,829,3,4,3,1,5,3,5,5,5,4,5,4,4,5,13,12.0,neutral or dissatisfied +47431,70332,Male,disloyal Customer,35,Business travel,Business,986,4,4,4,1,5,4,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +47432,108257,Male,Loyal Customer,22,Business travel,Business,895,3,4,4,4,3,3,3,3,4,3,4,4,3,3,0,0.0,neutral or dissatisfied +47433,87195,Female,Loyal Customer,40,Business travel,Eco,946,4,1,2,2,4,4,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +47434,73007,Female,Loyal Customer,21,Personal Travel,Eco,1089,3,3,3,4,4,3,4,4,3,5,5,2,1,4,0,0.0,neutral or dissatisfied +47435,37646,Male,Loyal Customer,15,Personal Travel,Eco,1074,1,4,1,2,3,1,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +47436,13090,Female,Loyal Customer,51,Business travel,Business,562,3,3,3,3,3,5,3,4,4,4,4,1,4,2,0,0.0,satisfied +47437,83093,Female,Loyal Customer,9,Personal Travel,Eco,983,2,4,2,2,1,2,1,1,4,4,5,5,4,1,0,65.0,neutral or dissatisfied +47438,46431,Female,Loyal Customer,47,Personal Travel,Eco,649,3,5,3,4,2,1,1,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +47439,32613,Female,Loyal Customer,40,Business travel,Eco,102,4,2,2,2,4,4,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +47440,49105,Male,disloyal Customer,25,Business travel,Eco,199,2,5,2,3,2,2,2,2,2,2,2,3,4,2,6,0.0,neutral or dissatisfied +47441,104946,Female,Loyal Customer,13,Personal Travel,Eco,1180,3,2,3,3,4,3,4,4,3,2,4,2,3,4,27,11.0,neutral or dissatisfied +47442,52181,Female,Loyal Customer,38,Business travel,Eco,237,4,3,3,3,4,4,4,4,2,4,4,2,4,4,0,0.0,satisfied +47443,46142,Female,disloyal Customer,41,Business travel,Eco,604,1,4,1,2,2,1,2,2,5,5,5,2,4,2,0,0.0,neutral or dissatisfied +47444,14003,Female,Loyal Customer,11,Personal Travel,Eco Plus,160,3,3,3,3,3,3,3,3,3,3,4,4,3,3,55,37.0,neutral or dissatisfied +47445,41561,Female,Loyal Customer,20,Business travel,Eco,1504,5,4,4,4,5,5,5,5,2,4,1,4,1,5,0,0.0,satisfied +47446,21505,Female,Loyal Customer,51,Personal Travel,Eco,399,2,2,2,4,3,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +47447,118323,Female,Loyal Customer,29,Business travel,Business,602,2,4,4,4,2,2,2,2,4,5,3,4,3,2,44,27.0,neutral or dissatisfied +47448,24163,Female,Loyal Customer,38,Business travel,Eco,147,4,2,2,2,4,4,4,4,2,5,1,1,2,4,44,26.0,satisfied +47449,97962,Female,Loyal Customer,12,Personal Travel,Eco,616,2,3,2,1,3,2,3,3,3,4,1,1,5,3,6,0.0,neutral or dissatisfied +47450,125401,Female,Loyal Customer,11,Personal Travel,Eco,1440,3,5,3,3,1,3,1,1,5,3,5,4,4,1,102,83.0,neutral or dissatisfied +47451,35654,Male,Loyal Customer,47,Business travel,Business,2475,4,1,1,1,4,4,4,1,4,3,3,4,3,4,0,0.0,neutral or dissatisfied +47452,99651,Male,Loyal Customer,45,Business travel,Business,2766,2,2,2,2,4,4,4,2,2,2,2,4,2,5,30,26.0,satisfied +47453,8251,Male,Loyal Customer,10,Personal Travel,Eco,402,3,4,3,3,4,3,1,4,3,3,4,3,3,4,21,19.0,neutral or dissatisfied +47454,20046,Male,Loyal Customer,26,Business travel,Business,3422,4,4,4,4,5,5,5,5,5,2,4,5,1,5,11,0.0,satisfied +47455,65397,Male,Loyal Customer,60,Personal Travel,Eco,631,2,5,1,2,1,1,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +47456,96820,Female,disloyal Customer,12,Business travel,Eco,849,1,1,1,4,4,1,4,4,1,2,3,3,4,4,18,3.0,neutral or dissatisfied +47457,8768,Male,Loyal Customer,72,Business travel,Business,2068,2,2,2,2,2,3,3,2,2,3,2,2,2,3,0,8.0,neutral or dissatisfied +47458,33220,Male,Loyal Customer,56,Business travel,Eco Plus,102,4,4,4,4,4,4,4,4,5,2,5,4,4,4,0,3.0,satisfied +47459,129021,Female,Loyal Customer,54,Personal Travel,Eco,2611,2,1,2,3,2,4,4,3,3,2,4,4,2,4,1,16.0,neutral or dissatisfied +47460,20956,Male,Loyal Customer,12,Business travel,Eco,721,4,4,4,4,4,5,3,4,5,5,2,2,2,4,0,0.0,satisfied +47461,2928,Female,Loyal Customer,40,Business travel,Business,3711,4,4,4,4,2,4,5,4,4,4,4,5,4,4,7,0.0,satisfied +47462,248,Male,Loyal Customer,23,Business travel,Business,719,3,4,4,4,3,3,3,3,2,2,4,2,3,3,35,42.0,neutral or dissatisfied +47463,104528,Female,disloyal Customer,26,Business travel,Business,1047,4,4,4,1,5,4,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +47464,9619,Male,Loyal Customer,30,Business travel,Business,2672,5,5,5,5,5,5,5,5,4,3,4,4,5,5,0,46.0,satisfied +47465,27936,Male,Loyal Customer,29,Business travel,Business,1774,5,5,5,5,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +47466,114642,Male,Loyal Customer,43,Business travel,Eco,362,2,4,4,4,2,2,2,2,4,5,2,3,3,2,10,5.0,neutral or dissatisfied +47467,116874,Female,Loyal Customer,57,Business travel,Business,1768,0,0,0,2,4,4,4,4,4,4,4,3,4,4,8,0.0,satisfied +47468,56623,Female,Loyal Customer,49,Business travel,Eco,1065,2,1,1,1,1,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +47469,88449,Female,disloyal Customer,38,Business travel,Business,581,4,3,3,4,5,3,5,5,5,2,5,3,4,5,3,0.0,satisfied +47470,47402,Female,Loyal Customer,72,Business travel,Eco,599,4,4,4,4,5,2,2,4,4,4,4,3,4,4,75,68.0,neutral or dissatisfied +47471,101089,Male,disloyal Customer,23,Business travel,Business,1235,4,0,4,2,3,4,3,3,3,2,4,4,5,3,7,0.0,satisfied +47472,55818,Male,disloyal Customer,25,Business travel,Business,1416,5,5,5,1,5,5,5,5,4,4,4,5,5,5,0,21.0,satisfied +47473,103848,Male,disloyal Customer,10,Business travel,Eco,979,4,4,4,4,5,4,5,5,4,4,4,1,4,5,13,17.0,neutral or dissatisfied +47474,17122,Female,Loyal Customer,32,Business travel,Business,1633,2,2,2,2,5,5,5,5,5,5,5,3,2,5,0,10.0,satisfied +47475,1217,Female,Loyal Customer,39,Personal Travel,Eco,158,3,4,3,5,4,3,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +47476,104265,Male,Loyal Customer,33,Business travel,Business,456,2,5,2,5,2,1,2,2,4,4,3,4,3,2,26,17.0,neutral or dissatisfied +47477,78675,Female,disloyal Customer,23,Business travel,Eco,674,3,3,3,4,1,3,1,1,5,3,4,3,5,1,4,27.0,neutral or dissatisfied +47478,83179,Male,disloyal Customer,23,Business travel,Business,549,4,4,4,2,3,4,3,3,3,5,4,3,4,3,67,74.0,satisfied +47479,129756,Female,Loyal Customer,43,Business travel,Business,308,4,2,2,2,4,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +47480,94936,Male,Loyal Customer,31,Business travel,Business,319,4,4,4,4,4,4,4,4,5,1,3,2,4,4,1,0.0,satisfied +47481,49669,Male,Loyal Customer,38,Business travel,Business,89,5,5,4,5,2,1,4,4,4,4,4,2,4,1,0,0.0,satisfied +47482,67314,Female,Loyal Customer,33,Business travel,Eco Plus,929,5,5,5,5,5,5,5,5,1,3,1,3,2,5,0,1.0,satisfied +47483,49130,Male,Loyal Customer,43,Business travel,Business,2989,1,1,1,1,2,3,4,4,4,4,4,2,4,2,0,0.0,satisfied +47484,67821,Female,disloyal Customer,36,Business travel,Eco,771,2,2,2,1,3,2,3,3,4,3,2,3,2,3,12,14.0,neutral or dissatisfied +47485,36537,Male,disloyal Customer,54,Business travel,Eco,1237,3,3,3,3,1,3,1,1,3,2,3,3,3,1,0,11.0,neutral or dissatisfied +47486,114556,Male,Loyal Customer,39,Personal Travel,Business,390,4,5,4,3,1,1,1,1,1,4,1,5,1,4,0,0.0,satisfied +47487,14318,Female,Loyal Customer,35,Business travel,Eco,395,2,4,4,4,2,2,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +47488,24663,Female,Loyal Customer,57,Personal Travel,Eco,873,2,1,3,3,4,4,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +47489,102330,Male,disloyal Customer,38,Business travel,Eco,258,1,2,0,2,2,0,2,2,3,1,1,4,1,2,0,0.0,neutral or dissatisfied +47490,122815,Female,Loyal Customer,62,Personal Travel,Eco,599,2,2,1,3,5,2,4,3,3,1,3,3,3,1,1,4.0,neutral or dissatisfied +47491,50296,Female,disloyal Customer,38,Business travel,Eco,207,1,3,1,5,5,1,5,5,5,2,3,5,1,5,0,0.0,neutral or dissatisfied +47492,38262,Male,Loyal Customer,34,Business travel,Business,2657,2,2,2,2,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +47493,110809,Female,Loyal Customer,44,Personal Travel,Eco,990,4,5,4,5,4,5,5,3,3,4,3,4,3,5,0,16.0,neutral or dissatisfied +47494,62151,Female,Loyal Customer,35,Business travel,Business,2454,3,2,2,2,2,2,3,3,3,3,3,1,3,1,1,0.0,neutral or dissatisfied +47495,104142,Male,Loyal Customer,58,Personal Travel,Eco,393,2,2,2,3,3,2,3,3,3,4,3,4,3,3,15,1.0,neutral or dissatisfied +47496,91092,Female,Loyal Customer,55,Personal Travel,Eco,406,1,5,1,3,3,2,2,2,2,1,2,1,2,2,100,96.0,neutral or dissatisfied +47497,45405,Male,Loyal Customer,42,Business travel,Business,3791,4,4,3,4,2,2,4,5,5,5,5,4,5,3,0,0.0,satisfied +47498,28694,Female,Loyal Customer,23,Business travel,Business,2182,5,5,5,5,5,5,5,5,1,3,4,5,3,5,0,2.0,satisfied +47499,24062,Male,Loyal Customer,66,Personal Travel,Eco,595,2,1,2,3,5,2,5,5,4,1,4,1,4,5,0,0.0,neutral or dissatisfied +47500,107433,Male,Loyal Customer,49,Personal Travel,Eco,725,3,1,3,2,1,3,1,1,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +47501,22509,Male,Loyal Customer,60,Business travel,Eco Plus,83,4,1,1,1,4,4,4,5,3,4,4,4,1,4,195,186.0,satisfied +47502,78841,Female,Loyal Customer,15,Personal Travel,Eco,528,3,2,3,4,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +47503,117187,Male,Loyal Customer,69,Personal Travel,Eco,369,1,4,1,3,4,1,4,4,4,2,3,4,4,4,5,0.0,neutral or dissatisfied +47504,59831,Female,Loyal Customer,52,Business travel,Business,1871,2,2,2,2,3,5,4,4,4,4,4,3,4,5,11,5.0,satisfied +47505,49570,Male,Loyal Customer,39,Business travel,Eco,109,3,3,3,3,3,3,3,3,1,4,2,5,1,3,0,0.0,satisfied +47506,42629,Female,Loyal Customer,9,Business travel,Eco,546,3,4,4,4,3,3,4,3,2,2,3,3,3,3,17,13.0,neutral or dissatisfied +47507,67325,Male,Loyal Customer,50,Personal Travel,Eco Plus,929,2,5,2,4,5,2,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +47508,52374,Female,Loyal Customer,49,Personal Travel,Eco,751,4,5,4,1,4,4,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +47509,64680,Male,Loyal Customer,39,Business travel,Business,2974,1,1,1,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +47510,60475,Male,Loyal Customer,42,Business travel,Business,862,3,3,3,3,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +47511,6884,Female,Loyal Customer,61,Business travel,Business,3725,2,2,2,2,4,5,4,5,5,4,5,5,5,4,2,14.0,satisfied +47512,9829,Male,disloyal Customer,22,Business travel,Eco,476,3,4,3,4,1,3,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +47513,9216,Female,disloyal Customer,39,Business travel,Business,157,4,4,4,3,1,4,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +47514,20023,Male,Loyal Customer,7,Personal Travel,Business,473,1,2,3,4,1,3,1,1,2,1,4,3,4,1,87,78.0,neutral or dissatisfied +47515,98675,Male,Loyal Customer,7,Personal Travel,Eco,951,4,4,4,2,5,4,5,5,2,4,4,5,3,5,86,126.0,neutral or dissatisfied +47516,11988,Male,Loyal Customer,17,Personal Travel,Eco,643,2,5,2,3,3,2,3,3,3,3,4,3,5,3,111,101.0,neutral or dissatisfied +47517,77337,Male,disloyal Customer,27,Business travel,Business,590,3,3,3,5,4,3,4,4,4,4,5,5,5,4,0,12.0,neutral or dissatisfied +47518,67278,Female,Loyal Customer,34,Personal Travel,Eco,1121,1,2,1,3,4,1,4,4,2,5,4,2,4,4,51,56.0,neutral or dissatisfied +47519,116834,Female,disloyal Customer,27,Business travel,Business,304,4,4,4,3,2,4,3,2,1,3,4,3,3,2,16,17.0,neutral or dissatisfied +47520,18125,Female,Loyal Customer,64,Business travel,Eco,120,2,3,3,3,5,4,2,1,1,2,1,2,1,4,49,33.0,satisfied +47521,5316,Female,Loyal Customer,56,Business travel,Eco Plus,351,3,3,3,3,4,2,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +47522,88720,Male,Loyal Customer,35,Personal Travel,Eco,404,4,4,4,2,5,4,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +47523,49526,Female,disloyal Customer,25,Business travel,Eco,110,2,3,1,3,5,1,5,5,1,4,1,4,3,5,7,0.0,neutral or dissatisfied +47524,18843,Female,disloyal Customer,52,Business travel,Eco,503,3,2,3,3,3,3,3,3,3,1,4,4,4,3,0,0.0,neutral or dissatisfied +47525,118423,Male,Loyal Customer,50,Business travel,Business,3100,1,1,1,1,4,5,4,3,3,4,3,5,3,5,94,113.0,satisfied +47526,95580,Male,Loyal Customer,17,Personal Travel,Business,822,2,5,3,2,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +47527,58218,Male,Loyal Customer,7,Personal Travel,Eco,925,2,5,2,1,3,2,3,3,5,4,2,1,4,3,0,1.0,neutral or dissatisfied +47528,107687,Female,disloyal Customer,37,Business travel,Business,405,3,3,3,4,1,3,1,1,4,3,5,3,4,1,105,129.0,neutral or dissatisfied +47529,63257,Male,Loyal Customer,58,Business travel,Business,337,0,0,0,4,2,4,5,2,2,2,2,3,2,3,48,45.0,satisfied +47530,13244,Male,disloyal Customer,32,Business travel,Eco,772,2,2,2,3,2,5,5,4,3,3,3,5,2,5,126,135.0,neutral or dissatisfied +47531,126775,Female,disloyal Customer,16,Business travel,Eco,757,4,4,4,4,1,4,1,1,2,5,5,5,5,1,0,0.0,satisfied +47532,103752,Female,Loyal Customer,21,Personal Travel,Eco Plus,405,3,4,3,3,2,3,2,2,5,3,4,3,5,2,21,19.0,neutral or dissatisfied +47533,125600,Male,Loyal Customer,39,Personal Travel,Eco,1587,3,3,3,3,1,3,1,1,1,3,3,4,4,1,7,1.0,neutral or dissatisfied +47534,44605,Female,Loyal Customer,42,Business travel,Eco,566,5,3,3,3,3,2,2,4,4,5,4,1,4,2,0,0.0,satisfied +47535,29571,Male,Loyal Customer,60,Business travel,Eco,1448,5,1,1,1,4,5,4,4,3,4,3,5,3,4,0,0.0,satisfied +47536,65492,Male,Loyal Customer,52,Personal Travel,Eco,1303,4,5,4,5,4,4,4,4,4,3,5,2,4,4,0,0.0,satisfied +47537,41988,Male,Loyal Customer,63,Personal Travel,Business,116,2,1,2,3,2,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +47538,19003,Male,Loyal Customer,44,Business travel,Eco,788,5,5,4,4,5,5,5,5,1,1,3,4,1,5,0,0.0,satisfied +47539,62196,Female,disloyal Customer,35,Business travel,Eco,2565,1,1,1,1,3,1,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +47540,112641,Male,Loyal Customer,68,Personal Travel,Eco Plus,639,4,4,4,2,3,4,3,3,5,3,5,3,5,3,4,0.0,satisfied +47541,125582,Male,Loyal Customer,7,Personal Travel,Eco Plus,226,1,4,1,3,1,1,1,1,3,3,3,3,4,1,0,0.0,neutral or dissatisfied +47542,27261,Male,disloyal Customer,23,Business travel,Eco,987,5,5,5,4,1,5,1,1,3,3,4,5,5,1,0,0.0,satisfied +47543,29303,Female,Loyal Customer,37,Personal Travel,Eco,834,4,4,5,2,2,5,2,2,4,5,5,5,4,2,1,1.0,satisfied +47544,85574,Female,disloyal Customer,21,Business travel,Eco,192,4,0,4,4,1,4,4,1,5,4,4,5,4,1,0,0.0,satisfied +47545,42240,Male,disloyal Customer,10,Business travel,Eco,834,2,2,2,3,2,2,2,2,2,4,4,4,3,2,0,12.0,neutral or dissatisfied +47546,119278,Male,Loyal Customer,51,Business travel,Eco,214,2,4,4,4,1,2,1,1,2,3,4,2,4,1,0,5.0,neutral or dissatisfied +47547,9693,Female,Loyal Customer,64,Business travel,Business,1857,2,1,1,1,3,3,4,1,1,1,2,1,1,3,38,41.0,neutral or dissatisfied +47548,121258,Male,Loyal Customer,54,Business travel,Eco,314,1,4,4,4,2,1,2,2,4,1,3,4,4,2,0,21.0,neutral or dissatisfied +47549,55205,Female,Loyal Customer,42,Personal Travel,Eco Plus,1379,3,5,3,5,2,5,1,4,4,3,4,4,4,4,19,19.0,neutral or dissatisfied +47550,126102,Female,Loyal Customer,60,Business travel,Eco,631,2,2,2,2,2,2,2,3,3,3,2,2,1,2,296,286.0,neutral or dissatisfied +47551,76574,Male,Loyal Customer,38,Business travel,Business,2205,5,4,5,5,5,5,5,5,2,5,4,5,5,5,104,147.0,satisfied +47552,75141,Female,Loyal Customer,49,Business travel,Business,1723,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +47553,57296,Male,Loyal Customer,40,Business travel,Business,414,2,2,2,2,2,4,4,5,5,5,5,3,5,5,7,7.0,satisfied +47554,51135,Male,Loyal Customer,11,Personal Travel,Eco,262,2,5,0,4,3,0,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +47555,123015,Male,Loyal Customer,45,Business travel,Business,2139,3,3,5,3,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +47556,5915,Female,Loyal Customer,53,Personal Travel,Eco,173,1,4,1,3,1,1,1,4,4,1,4,1,4,1,81,85.0,neutral or dissatisfied +47557,35703,Female,Loyal Customer,67,Personal Travel,Eco,2586,2,4,2,3,2,1,1,4,3,4,5,1,3,1,0,0.0,neutral or dissatisfied +47558,53101,Female,Loyal Customer,44,Business travel,Business,1628,2,2,2,2,1,4,1,5,5,5,5,5,5,3,16,3.0,satisfied +47559,114067,Female,Loyal Customer,50,Business travel,Eco,1892,2,1,1,1,1,2,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +47560,87038,Female,Loyal Customer,46,Business travel,Business,594,1,1,1,1,4,5,4,5,5,5,5,3,5,3,37,32.0,satisfied +47561,57438,Female,Loyal Customer,54,Business travel,Business,1735,2,4,4,4,3,4,4,2,2,2,2,4,2,1,7,9.0,neutral or dissatisfied +47562,117474,Male,Loyal Customer,46,Business travel,Business,2453,4,4,4,4,5,5,5,3,3,4,3,3,3,5,0,3.0,satisfied +47563,68757,Male,Loyal Customer,40,Business travel,Business,3693,2,2,4,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +47564,95516,Female,disloyal Customer,38,Business travel,Eco Plus,323,1,1,1,3,2,1,2,2,1,2,4,4,3,2,16,18.0,neutral or dissatisfied +47565,86382,Male,Loyal Customer,40,Business travel,Business,2687,4,2,4,4,4,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +47566,41467,Female,disloyal Customer,20,Business travel,Eco,929,4,4,4,2,4,4,4,4,1,2,2,3,3,4,0,0.0,satisfied +47567,43274,Male,disloyal Customer,38,Business travel,Eco,387,2,0,2,4,5,2,5,5,3,5,2,3,5,5,0,0.0,neutral or dissatisfied +47568,63718,Male,Loyal Customer,55,Business travel,Business,1660,1,1,1,1,2,4,5,3,3,3,3,3,3,5,15,0.0,satisfied +47569,27012,Female,Loyal Customer,9,Personal Travel,Eco,867,3,4,3,1,5,3,5,5,3,2,5,5,5,5,4,2.0,neutral or dissatisfied +47570,56012,Male,Loyal Customer,42,Business travel,Business,2475,3,3,4,3,5,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +47571,82973,Female,Loyal Customer,36,Business travel,Business,3918,3,3,1,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +47572,129081,Male,disloyal Customer,39,Business travel,Business,2583,4,5,5,4,5,5,5,5,2,4,5,5,3,5,0,0.0,neutral or dissatisfied +47573,45364,Male,Loyal Customer,24,Personal Travel,Eco,222,2,1,2,4,5,2,5,5,4,5,3,3,3,5,0,0.0,neutral or dissatisfied +47574,54868,Male,Loyal Customer,63,Business travel,Eco,462,2,5,5,5,2,2,2,2,4,1,2,4,1,2,0,0.0,satisfied +47575,95153,Male,Loyal Customer,41,Personal Travel,Eco,248,4,4,4,5,5,4,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +47576,112538,Male,Loyal Customer,66,Personal Travel,Eco,862,3,5,3,1,5,3,5,5,3,4,5,4,5,5,31,16.0,neutral or dissatisfied +47577,24095,Male,Loyal Customer,48,Personal Travel,Eco,625,3,3,3,5,3,3,3,3,2,1,3,4,5,3,68,99.0,neutral or dissatisfied +47578,35085,Male,Loyal Customer,40,Business travel,Eco,1035,5,1,1,1,5,5,5,5,5,4,4,3,4,5,74,58.0,satisfied +47579,112234,Male,disloyal Customer,25,Business travel,Business,1506,1,3,1,2,3,1,3,3,3,3,3,4,2,3,0,2.0,neutral or dissatisfied +47580,126239,Female,Loyal Customer,55,Business travel,Business,1535,0,3,0,4,4,4,4,1,1,1,1,3,1,1,20,30.0,satisfied +47581,71538,Male,Loyal Customer,46,Business travel,Eco,1005,2,3,3,3,2,2,2,2,4,3,2,1,3,2,0,0.0,neutral or dissatisfied +47582,87806,Male,Loyal Customer,42,Business travel,Business,2256,1,1,1,1,5,4,4,5,5,5,4,4,5,4,9,5.0,satisfied +47583,104526,Female,Loyal Customer,42,Business travel,Business,3163,4,4,5,4,3,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +47584,112902,Female,Loyal Customer,57,Business travel,Business,1390,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +47585,16324,Male,disloyal Customer,29,Business travel,Eco,602,4,3,4,3,5,4,5,5,4,2,4,2,4,5,15,8.0,neutral or dissatisfied +47586,53004,Female,disloyal Customer,26,Business travel,Eco,1208,3,4,4,4,5,4,5,5,4,3,1,4,4,5,0,0.0,neutral or dissatisfied +47587,30712,Male,Loyal Customer,19,Personal Travel,Eco,464,2,5,2,3,3,2,3,3,3,3,5,3,5,3,28,16.0,neutral or dissatisfied +47588,94865,Female,disloyal Customer,26,Business travel,Business,187,2,5,2,4,4,2,5,4,5,3,5,3,5,4,4,3.0,neutral or dissatisfied +47589,55156,Male,Loyal Customer,15,Personal Travel,Eco,1303,1,4,2,1,1,2,1,1,4,4,5,4,5,1,0,22.0,neutral or dissatisfied +47590,23512,Male,Loyal Customer,56,Business travel,Business,3750,4,4,4,4,4,2,4,5,5,5,5,1,5,4,0,0.0,satisfied +47591,18183,Female,disloyal Customer,37,Business travel,Eco,228,2,0,2,2,2,2,4,2,2,5,2,4,2,2,0,0.0,neutral or dissatisfied +47592,72278,Male,disloyal Customer,28,Business travel,Eco,519,3,4,2,4,5,2,5,5,5,1,5,4,2,5,0,0.0,neutral or dissatisfied +47593,13974,Female,disloyal Customer,59,Business travel,Eco Plus,192,3,4,4,4,2,3,2,2,1,5,3,3,3,2,16,18.0,neutral or dissatisfied +47594,91253,Male,Loyal Customer,43,Personal Travel,Eco,581,4,5,4,2,5,4,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +47595,90661,Female,Loyal Customer,30,Business travel,Business,545,2,5,5,5,2,2,2,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +47596,32319,Male,Loyal Customer,35,Business travel,Business,1627,0,5,0,5,3,5,5,3,3,3,3,1,3,5,0,0.0,satisfied +47597,111053,Male,Loyal Customer,36,Business travel,Business,1937,1,1,1,1,1,3,3,4,4,4,5,2,4,4,0,0.0,satisfied +47598,101183,Male,Loyal Customer,10,Personal Travel,Eco,1235,3,5,3,2,3,3,5,3,3,3,4,4,5,3,9,0.0,neutral or dissatisfied +47599,58158,Male,Loyal Customer,25,Business travel,Business,3018,1,1,1,1,5,5,5,5,4,5,4,5,5,5,4,8.0,satisfied +47600,54130,Female,Loyal Customer,22,Business travel,Business,1400,5,5,5,5,5,5,5,5,2,3,2,5,3,5,0,14.0,satisfied +47601,75293,Female,Loyal Customer,65,Personal Travel,Eco Plus,1846,0,4,0,2,3,4,1,2,2,0,2,5,2,2,0,0.0,satisfied +47602,117419,Male,Loyal Customer,51,Business travel,Business,1460,2,2,2,2,4,4,5,4,4,5,4,5,4,5,35,28.0,satisfied +47603,28106,Male,Loyal Customer,36,Business travel,Eco,569,4,5,5,5,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +47604,21334,Male,Loyal Customer,58,Business travel,Eco,761,3,5,5,5,2,3,2,2,2,5,4,3,4,2,82,85.0,satisfied +47605,11616,Male,Loyal Customer,39,Personal Travel,Eco,468,3,5,3,3,3,3,4,3,3,4,4,4,5,3,0,9.0,neutral or dissatisfied +47606,19465,Female,Loyal Customer,40,Business travel,Business,177,5,5,5,5,2,5,4,5,5,5,4,5,5,1,0,0.0,satisfied +47607,32396,Female,Loyal Customer,32,Business travel,Business,163,3,3,3,3,5,4,3,5,1,2,3,1,3,5,0,0.0,satisfied +47608,93114,Female,Loyal Customer,52,Business travel,Business,3734,4,4,4,4,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +47609,79645,Female,Loyal Customer,53,Business travel,Business,3075,1,0,0,4,1,3,3,5,5,0,5,1,5,1,0,0.0,neutral or dissatisfied +47610,77963,Male,Loyal Customer,26,Business travel,Business,214,1,1,1,1,4,4,5,4,3,4,5,3,4,4,0,0.0,satisfied +47611,18540,Male,Loyal Customer,37,Business travel,Business,190,2,2,2,2,4,4,5,4,4,4,5,4,4,1,3,46.0,satisfied +47612,87461,Male,Loyal Customer,51,Business travel,Business,3173,3,3,2,3,3,5,4,3,3,4,3,4,3,5,2,0.0,satisfied +47613,63348,Female,disloyal Customer,38,Business travel,Eco,337,4,4,3,1,2,3,2,2,2,4,4,1,2,2,0,0.0,neutral or dissatisfied +47614,108903,Female,Loyal Customer,53,Business travel,Business,3610,3,5,5,5,2,2,3,3,3,3,3,3,3,4,13,7.0,neutral or dissatisfied +47615,31727,Female,Loyal Customer,20,Personal Travel,Eco,853,1,5,2,1,2,2,2,2,3,3,5,4,4,2,5,0.0,neutral or dissatisfied +47616,63396,Male,Loyal Customer,52,Personal Travel,Eco,372,2,5,2,2,1,2,1,1,5,3,4,3,4,1,12,6.0,neutral or dissatisfied +47617,115203,Male,Loyal Customer,45,Business travel,Business,2576,5,5,5,5,3,5,5,5,5,5,5,3,5,5,7,13.0,satisfied +47618,54301,Male,Loyal Customer,23,Personal Travel,Eco,1075,2,2,2,4,4,2,4,4,4,1,3,4,4,4,4,0.0,neutral or dissatisfied +47619,21200,Male,Loyal Customer,35,Business travel,Business,192,4,4,4,4,1,1,1,4,4,4,4,2,4,3,0,0.0,satisfied +47620,57922,Female,Loyal Customer,22,Personal Travel,Eco,305,4,5,4,1,1,4,4,1,1,3,4,5,4,1,61,58.0,neutral or dissatisfied +47621,84874,Male,Loyal Customer,43,Personal Travel,Eco,516,3,2,4,3,2,4,2,2,3,5,3,3,3,2,1,0.0,neutral or dissatisfied +47622,102356,Female,Loyal Customer,37,Business travel,Business,3336,4,3,1,3,4,4,3,4,4,4,4,3,4,4,32,30.0,neutral or dissatisfied +47623,12340,Male,Loyal Customer,61,Business travel,Eco,201,5,1,1,1,5,5,5,5,3,1,2,4,1,5,0,0.0,satisfied +47624,35983,Female,Loyal Customer,37,Personal Travel,Business,2496,2,2,2,3,2,4,4,3,4,2,3,4,2,4,0,0.0,neutral or dissatisfied +47625,95452,Female,Loyal Customer,58,Business travel,Business,189,4,4,4,4,3,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +47626,46936,Female,disloyal Customer,63,Personal Travel,Eco,776,5,5,4,4,3,4,3,3,5,2,5,3,5,3,7,,satisfied +47627,118801,Female,Loyal Customer,51,Personal Travel,Eco,647,4,5,4,1,5,5,3,5,5,4,1,1,5,3,22,11.0,neutral or dissatisfied +47628,69844,Male,Loyal Customer,9,Personal Travel,Eco,1345,2,1,2,2,5,2,5,5,4,4,3,3,2,5,0,0.0,neutral or dissatisfied +47629,108218,Male,Loyal Customer,33,Personal Travel,Eco,777,1,5,1,5,1,1,1,1,3,4,5,4,4,1,6,0.0,neutral or dissatisfied +47630,102540,Female,Loyal Customer,67,Personal Travel,Eco,407,1,4,1,1,1,3,5,5,5,1,5,1,5,3,8,1.0,neutral or dissatisfied +47631,35025,Male,Loyal Customer,49,Business travel,Eco Plus,740,5,4,4,4,5,5,5,5,4,1,1,4,3,5,2,9.0,satisfied +47632,125195,Male,disloyal Customer,23,Business travel,Eco,651,0,0,1,4,3,1,3,3,4,3,5,5,5,3,2,0.0,satisfied +47633,24464,Male,Loyal Customer,45,Business travel,Eco,481,4,2,2,2,4,4,4,4,3,4,2,3,2,4,0,0.0,satisfied +47634,80073,Female,Loyal Customer,49,Business travel,Business,944,4,4,5,4,3,5,4,3,3,4,3,4,3,4,29,20.0,satisfied +47635,103545,Male,Loyal Customer,48,Business travel,Business,2236,3,4,4,4,2,3,3,3,3,3,3,4,3,1,3,0.0,neutral or dissatisfied +47636,27926,Male,Loyal Customer,34,Business travel,Eco Plus,689,5,3,3,3,5,5,5,5,4,4,1,5,4,5,0,,satisfied +47637,57471,Male,Loyal Customer,50,Business travel,Business,3353,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,2.0,satisfied +47638,129816,Female,Loyal Customer,54,Personal Travel,Eco,308,1,5,1,4,2,4,5,2,2,1,3,4,2,3,7,0.0,neutral or dissatisfied +47639,128617,Male,disloyal Customer,28,Business travel,Business,679,0,0,0,4,2,0,2,2,5,2,4,3,5,2,3,0.0,satisfied +47640,5792,Female,Loyal Customer,55,Business travel,Business,3482,4,4,4,4,4,5,4,5,2,5,5,4,4,4,135,167.0,satisfied +47641,119779,Female,Loyal Customer,61,Personal Travel,Business,936,4,5,4,2,1,4,1,3,3,4,3,1,3,2,3,0.0,neutral or dissatisfied +47642,58885,Male,Loyal Customer,54,Business travel,Eco,1081,2,1,1,1,2,2,2,2,3,1,3,4,3,2,49,58.0,neutral or dissatisfied +47643,120827,Female,Loyal Customer,17,Business travel,Business,2535,4,4,4,4,4,4,4,4,3,3,4,3,4,4,0,1.0,satisfied +47644,16500,Male,disloyal Customer,38,Business travel,Business,282,1,1,1,4,1,1,1,1,3,4,5,3,2,1,26,21.0,neutral or dissatisfied +47645,40600,Female,Loyal Customer,68,Personal Travel,Eco,391,3,4,3,3,2,4,4,1,1,3,5,3,1,5,12,0.0,neutral or dissatisfied +47646,56852,Female,Loyal Customer,49,Business travel,Business,2565,3,2,3,3,4,4,4,4,3,5,4,4,4,4,2,16.0,satisfied +47647,125728,Female,disloyal Customer,45,Business travel,Business,814,4,4,4,4,3,4,1,3,3,4,4,3,5,3,6,5.0,satisfied +47648,44062,Female,Loyal Customer,48,Business travel,Business,456,1,1,1,1,4,2,2,5,5,5,5,2,5,1,0,0.0,satisfied +47649,129444,Male,Loyal Customer,62,Personal Travel,Eco,236,4,4,4,4,1,4,1,1,3,5,5,3,4,1,0,0.0,satisfied +47650,40295,Male,Loyal Customer,63,Personal Travel,Eco,358,3,4,3,3,5,3,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +47651,59765,Female,Loyal Customer,38,Business travel,Business,3889,5,5,1,5,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +47652,108191,Male,Loyal Customer,40,Business travel,Business,1105,5,5,5,5,4,3,3,3,3,5,4,3,5,3,271,270.0,satisfied +47653,30766,Male,Loyal Customer,37,Personal Travel,Eco Plus,683,1,4,1,1,4,1,3,4,5,3,5,4,4,4,8,8.0,neutral or dissatisfied +47654,42548,Female,Loyal Customer,29,Personal Travel,Eco,1174,2,4,1,1,5,1,5,5,3,4,3,3,2,5,0,0.0,neutral or dissatisfied +47655,127254,Male,Loyal Customer,31,Business travel,Business,1107,4,4,4,4,5,5,5,5,4,2,4,4,5,5,14,1.0,satisfied +47656,53661,Male,Loyal Customer,38,Personal Travel,Business,1190,2,5,2,2,3,5,4,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +47657,54703,Female,Loyal Customer,79,Business travel,Eco,564,5,5,5,5,3,1,1,5,5,5,5,3,5,2,2,20.0,satisfied +47658,12498,Female,Loyal Customer,18,Business travel,Eco Plus,253,5,2,2,2,5,5,4,5,5,2,2,1,4,5,5,0.0,satisfied +47659,113049,Male,disloyal Customer,23,Business travel,Business,543,4,5,4,3,3,4,3,3,5,2,5,4,4,3,0,1.0,satisfied +47660,118242,Female,disloyal Customer,55,Business travel,Eco Plus,1587,2,2,2,2,2,2,2,2,4,5,3,3,3,2,0,9.0,neutral or dissatisfied +47661,65941,Female,Loyal Customer,44,Business travel,Business,569,3,3,3,3,5,4,4,4,4,4,4,5,4,4,1,2.0,satisfied +47662,61029,Female,Loyal Customer,19,Personal Travel,Eco Plus,3365,2,5,2,4,2,3,3,5,5,3,2,3,3,3,0,0.0,neutral or dissatisfied +47663,34490,Female,Loyal Customer,46,Business travel,Business,1990,5,5,5,5,2,5,3,2,2,2,2,5,2,4,0,0.0,satisfied +47664,12847,Female,Loyal Customer,30,Personal Travel,Eco,641,3,5,3,1,4,3,4,4,4,2,4,3,4,4,55,44.0,neutral or dissatisfied +47665,47956,Female,Loyal Customer,54,Personal Travel,Eco,784,1,4,1,3,2,3,3,2,2,1,2,2,2,4,0,13.0,neutral or dissatisfied +47666,20260,Female,Loyal Customer,22,Business travel,Business,3518,5,5,5,5,5,5,3,5,2,3,5,2,1,5,0,23.0,satisfied +47667,41515,Female,Loyal Customer,29,Business travel,Business,1428,2,2,2,2,3,3,3,3,3,5,3,4,1,3,0,0.0,satisfied +47668,112467,Female,Loyal Customer,40,Business travel,Eco,446,2,5,2,5,2,2,2,2,2,2,1,2,2,2,3,10.0,neutral or dissatisfied +47669,27302,Female,Loyal Customer,25,Business travel,Eco,987,4,2,2,2,4,4,4,4,4,3,3,4,2,4,0,0.0,satisfied +47670,32996,Male,Loyal Customer,64,Personal Travel,Eco,101,3,5,3,3,1,3,1,1,5,4,5,4,5,1,0,2.0,neutral or dissatisfied +47671,120000,Male,disloyal Customer,32,Business travel,Business,328,1,1,1,5,4,1,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +47672,50656,Female,Loyal Customer,54,Personal Travel,Eco,363,4,4,4,3,3,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +47673,50832,Male,Loyal Customer,49,Personal Travel,Eco,209,3,2,3,2,4,3,4,4,4,4,1,3,2,4,2,2.0,neutral or dissatisfied +47674,35257,Male,Loyal Customer,52,Business travel,Business,3581,4,4,4,4,4,4,4,2,1,3,3,4,2,4,256,274.0,satisfied +47675,62108,Male,Loyal Customer,30,Business travel,Eco,2434,2,3,3,3,2,2,2,2,4,3,3,4,4,2,4,0.0,neutral or dissatisfied +47676,57197,Female,Loyal Customer,42,Business travel,Business,1514,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +47677,65873,Female,Loyal Customer,48,Personal Travel,Eco,1389,0,4,0,4,2,2,2,3,3,0,3,4,3,1,0,0.0,satisfied +47678,105364,Male,Loyal Customer,48,Personal Travel,Business,369,0,1,0,4,2,3,3,5,5,0,1,3,5,3,14,13.0,satisfied +47679,72564,Female,Loyal Customer,63,Business travel,Business,1121,1,3,5,3,3,4,4,1,1,1,1,4,1,1,10,10.0,neutral or dissatisfied +47680,8727,Female,Loyal Customer,20,Personal Travel,Eco,227,3,4,3,4,2,3,2,2,5,2,5,5,5,2,40,64.0,neutral or dissatisfied +47681,86535,Male,Loyal Customer,33,Personal Travel,Eco,760,3,5,3,1,1,3,1,1,5,2,5,3,5,1,0,16.0,neutral or dissatisfied +47682,82001,Male,Loyal Customer,16,Business travel,Business,1532,4,4,4,4,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +47683,37676,Female,Loyal Customer,50,Personal Travel,Eco,828,3,5,3,3,5,5,4,2,2,3,2,5,2,4,81,79.0,neutral or dissatisfied +47684,73176,Female,Loyal Customer,41,Business travel,Business,3768,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +47685,31382,Male,Loyal Customer,53,Business travel,Eco,895,3,3,3,3,3,3,3,3,1,4,3,1,4,3,23,26.0,neutral or dissatisfied +47686,23657,Male,Loyal Customer,59,Business travel,Business,1756,2,2,2,2,1,3,1,4,4,4,4,4,4,1,26,15.0,satisfied +47687,118177,Female,Loyal Customer,48,Business travel,Eco,1444,1,2,2,2,4,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +47688,16527,Female,Loyal Customer,45,Business travel,Eco,209,1,2,2,2,5,4,3,1,1,1,1,1,1,4,7,4.0,neutral or dissatisfied +47689,43312,Female,disloyal Customer,24,Business travel,Business,402,4,4,4,3,1,4,1,1,3,1,2,4,3,1,0,3.0,satisfied +47690,50852,Female,Loyal Customer,41,Personal Travel,Eco,250,1,5,1,3,3,1,3,3,4,4,3,2,5,3,45,32.0,neutral or dissatisfied +47691,69993,Male,Loyal Customer,45,Personal Travel,Eco,236,0,4,0,5,2,0,2,2,3,2,4,5,5,2,2,1.0,satisfied +47692,108877,Female,Loyal Customer,44,Personal Travel,Eco,1587,4,4,4,4,5,4,4,2,2,4,2,4,2,5,18,22.0,neutral or dissatisfied +47693,21703,Female,Loyal Customer,65,Personal Travel,Eco,746,2,5,2,3,5,5,4,3,3,2,1,4,3,4,4,0.0,neutral or dissatisfied +47694,39318,Male,Loyal Customer,27,Personal Travel,Eco,67,2,5,2,3,4,2,4,4,3,3,5,3,4,4,6,15.0,neutral or dissatisfied +47695,39423,Female,Loyal Customer,60,Business travel,Eco,129,5,3,3,3,4,1,5,5,5,5,5,2,5,1,0,1.0,satisfied +47696,54035,Male,Loyal Customer,9,Personal Travel,Business,1416,2,4,1,3,1,4,4,4,4,4,4,4,3,4,147,147.0,neutral or dissatisfied +47697,67433,Male,Loyal Customer,55,Business travel,Eco,641,3,1,5,1,3,3,3,3,3,1,4,1,3,3,38,85.0,neutral or dissatisfied +47698,102175,Male,disloyal Customer,38,Business travel,Business,223,3,3,3,4,5,3,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +47699,125765,Male,Loyal Customer,44,Business travel,Business,920,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +47700,2609,Female,Loyal Customer,32,Personal Travel,Eco,227,4,4,0,2,5,0,5,5,3,2,5,4,5,5,0,8.0,neutral or dissatisfied +47701,96691,Male,Loyal Customer,39,Business travel,Business,3421,3,3,4,3,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +47702,101459,Male,Loyal Customer,39,Business travel,Business,345,5,5,2,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +47703,88808,Female,disloyal Customer,9,Business travel,Eco Plus,515,3,3,3,3,3,3,3,3,3,1,4,3,4,3,3,0.0,neutral or dissatisfied +47704,124264,Male,Loyal Customer,45,Business travel,Business,601,1,1,1,1,3,5,5,4,4,4,4,4,4,4,14,0.0,satisfied +47705,117013,Male,disloyal Customer,23,Business travel,Eco,647,4,0,4,1,5,4,5,5,3,2,4,3,4,5,6,0.0,neutral or dissatisfied +47706,81876,Male,Loyal Customer,32,Business travel,Business,2305,1,1,1,1,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +47707,52099,Male,Loyal Customer,52,Personal Travel,Eco,639,0,4,0,3,4,0,4,4,3,2,4,3,4,4,64,53.0,satisfied +47708,81773,Male,Loyal Customer,37,Business travel,Business,2711,4,4,4,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +47709,62675,Male,Loyal Customer,31,Personal Travel,Eco Plus,1744,3,4,3,3,5,3,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +47710,11764,Male,disloyal Customer,20,Business travel,Eco,395,4,0,4,3,1,4,2,1,4,4,3,1,1,1,0,0.0,neutral or dissatisfied +47711,15314,Female,disloyal Customer,40,Business travel,Business,589,2,2,2,3,4,2,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +47712,97556,Female,Loyal Customer,38,Business travel,Business,3474,2,4,4,4,4,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +47713,54779,Female,Loyal Customer,65,Personal Travel,Eco Plus,787,2,5,2,3,4,1,4,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +47714,128833,Female,disloyal Customer,21,Business travel,Eco,975,5,5,5,2,5,1,3,1,4,1,4,3,3,3,0,0.0,satisfied +47715,3160,Female,Loyal Customer,39,Business travel,Business,3576,3,2,3,3,2,4,4,3,3,4,3,4,3,3,20,115.0,satisfied +47716,9301,Male,disloyal Customer,29,Business travel,Business,542,1,2,2,3,2,2,2,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +47717,123784,Male,Loyal Customer,49,Business travel,Business,544,3,3,3,3,4,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +47718,44720,Male,Loyal Customer,51,Personal Travel,Eco,268,3,2,3,3,3,3,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +47719,82925,Male,Loyal Customer,42,Business travel,Business,594,3,3,3,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +47720,20696,Female,Loyal Customer,29,Business travel,Business,584,1,0,0,3,4,0,4,4,4,1,4,3,3,4,2,0.0,neutral or dissatisfied +47721,37217,Female,Loyal Customer,47,Business travel,Business,1144,4,4,4,4,5,4,4,4,4,5,4,3,4,3,8,1.0,satisfied +47722,38101,Female,Loyal Customer,35,Business travel,Business,2838,2,3,3,3,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +47723,2863,Female,Loyal Customer,42,Business travel,Business,1568,3,5,5,5,2,3,3,3,3,3,3,3,3,2,0,7.0,neutral or dissatisfied +47724,19139,Male,Loyal Customer,37,Personal Travel,Eco Plus,323,4,5,4,2,5,4,5,5,1,4,2,1,5,5,0,0.0,satisfied +47725,9746,Male,Loyal Customer,44,Business travel,Eco,508,3,5,5,5,2,3,2,2,2,3,3,3,4,2,77,71.0,neutral or dissatisfied +47726,70629,Female,Loyal Customer,47,Personal Travel,Eco,1217,1,0,1,3,4,4,4,4,4,1,2,3,4,4,0,0.0,neutral or dissatisfied +47727,125568,Male,Loyal Customer,19,Personal Travel,Eco,226,3,5,3,5,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +47728,103816,Male,disloyal Customer,21,Business travel,Eco,882,2,2,2,3,3,2,5,3,4,5,3,3,3,3,14,6.0,neutral or dissatisfied +47729,109577,Female,Loyal Customer,60,Personal Travel,Eco,834,3,2,3,3,3,4,3,1,1,3,3,3,1,1,48,32.0,neutral or dissatisfied +47730,122385,Male,Loyal Customer,49,Personal Travel,Eco,529,2,4,2,3,4,2,4,4,3,4,4,4,4,4,119,111.0,neutral or dissatisfied +47731,57709,Male,Loyal Customer,46,Personal Travel,Eco,867,2,3,2,3,5,2,5,5,1,5,2,3,3,5,0,0.0,neutral or dissatisfied +47732,62099,Female,Loyal Customer,33,Business travel,Business,2565,2,4,4,4,5,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +47733,119254,Male,disloyal Customer,25,Business travel,Business,214,2,5,2,4,2,2,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +47734,25735,Male,Loyal Customer,63,Personal Travel,Eco,432,2,5,2,3,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +47735,36688,Female,Loyal Customer,17,Personal Travel,Eco,1237,2,3,1,3,5,1,5,5,2,2,3,1,4,5,0,58.0,neutral or dissatisfied +47736,38517,Male,Loyal Customer,26,Business travel,Business,2586,1,3,3,3,1,1,1,1,1,4,2,3,2,1,46,20.0,neutral or dissatisfied +47737,104045,Male,Loyal Customer,17,Business travel,Eco,1044,5,2,2,2,5,5,4,5,2,2,3,4,5,5,0,0.0,satisfied +47738,55285,Male,disloyal Customer,29,Business travel,Business,1608,3,3,3,1,5,3,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +47739,103553,Female,Loyal Customer,43,Personal Travel,Eco,967,3,1,3,2,4,3,2,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +47740,98373,Female,Loyal Customer,14,Personal Travel,Eco,1046,3,4,4,5,5,4,3,5,3,5,4,3,4,5,50,48.0,neutral or dissatisfied +47741,36103,Female,Loyal Customer,56,Personal Travel,Eco,474,2,4,2,5,5,4,2,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +47742,27589,Female,Loyal Customer,29,Personal Travel,Eco,1050,2,4,2,3,2,2,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +47743,33759,Female,Loyal Customer,38,Personal Travel,Eco,266,2,0,0,3,5,0,5,5,5,2,4,4,4,5,85,105.0,neutral or dissatisfied +47744,54609,Female,Loyal Customer,30,Business travel,Business,3499,1,1,1,1,5,5,5,5,5,4,2,3,4,5,32,9.0,satisfied +47745,101653,Female,disloyal Customer,35,Business travel,Eco Plus,1733,2,2,2,4,3,2,3,3,4,1,3,2,4,3,6,0.0,neutral or dissatisfied +47746,2829,Male,Loyal Customer,58,Business travel,Business,409,2,2,2,2,2,5,4,4,4,4,4,5,4,3,11,25.0,satisfied +47747,98741,Female,Loyal Customer,38,Personal Travel,Eco,1558,3,4,3,3,2,3,2,2,5,2,5,4,5,2,16,17.0,neutral or dissatisfied +47748,38505,Female,Loyal Customer,47,Business travel,Business,2586,4,4,4,4,3,4,3,4,4,4,4,4,4,2,0,0.0,satisfied +47749,53216,Female,Loyal Customer,53,Business travel,Eco,589,3,3,3,3,3,2,3,3,3,3,3,2,3,3,22,45.0,neutral or dissatisfied +47750,25817,Male,Loyal Customer,47,Business travel,Eco,1747,5,4,4,4,5,5,5,5,2,1,4,5,4,5,22,23.0,satisfied +47751,120188,Female,Loyal Customer,53,Business travel,Business,1430,1,1,1,1,5,5,4,5,5,5,5,3,5,4,12,18.0,satisfied +47752,51984,Female,Loyal Customer,28,Personal Travel,Eco,936,4,5,4,2,3,4,3,3,3,2,4,5,4,3,41,39.0,neutral or dissatisfied +47753,36692,Female,Loyal Customer,34,Personal Travel,Eco,1237,3,4,3,2,5,3,5,5,5,3,5,3,4,5,0,7.0,neutral or dissatisfied +47754,17752,Male,Loyal Customer,70,Personal Travel,Eco,383,1,1,1,4,4,1,4,4,1,2,4,4,3,4,40,26.0,neutral or dissatisfied +47755,79927,Female,Loyal Customer,29,Business travel,Business,1089,1,4,4,4,1,1,1,1,1,2,4,4,4,1,0,0.0,neutral or dissatisfied +47756,3373,Male,Loyal Customer,39,Business travel,Business,3169,3,2,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +47757,40084,Female,disloyal Customer,22,Business travel,Eco,493,1,5,1,2,3,1,3,3,1,1,3,1,5,3,0,0.0,neutral or dissatisfied +47758,72119,Male,Loyal Customer,43,Business travel,Business,731,2,3,3,3,1,3,3,2,2,2,2,2,2,2,62,77.0,neutral or dissatisfied +47759,114942,Female,disloyal Customer,22,Business travel,Business,417,0,0,0,5,4,0,4,4,5,2,4,5,5,4,96,98.0,satisfied +47760,93749,Female,disloyal Customer,21,Business travel,Eco,368,4,1,4,3,3,4,3,3,3,1,4,2,4,3,24,15.0,neutral or dissatisfied +47761,7986,Male,disloyal Customer,26,Business travel,Business,294,2,4,3,3,5,3,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +47762,65861,Female,Loyal Customer,29,Personal Travel,Eco,1389,3,5,3,1,4,3,4,4,4,5,5,4,4,4,37,38.0,neutral or dissatisfied +47763,126329,Male,Loyal Customer,69,Personal Travel,Eco,507,2,4,2,3,4,2,4,4,3,5,4,3,4,4,30,11.0,neutral or dissatisfied +47764,101018,Male,Loyal Customer,45,Business travel,Eco,164,5,3,3,3,5,5,5,5,2,1,3,2,1,5,0,0.0,satisfied +47765,55217,Male,Loyal Customer,35,Business travel,Business,1009,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +47766,52441,Female,Loyal Customer,8,Personal Travel,Eco,493,2,5,2,1,2,2,2,2,4,5,4,3,4,2,61,73.0,neutral or dissatisfied +47767,94921,Female,Loyal Customer,52,Business travel,Eco,248,4,2,2,2,3,2,3,4,4,4,4,1,4,3,0,0.0,satisfied +47768,7371,Female,Loyal Customer,18,Personal Travel,Eco,783,2,4,2,2,3,2,4,3,5,4,4,5,4,3,32,41.0,neutral or dissatisfied +47769,94753,Female,disloyal Customer,30,Business travel,Eco,189,4,2,4,3,3,4,3,3,4,1,4,2,4,3,0,35.0,neutral or dissatisfied +47770,71984,Male,Loyal Customer,51,Business travel,Business,1440,5,5,5,5,3,3,4,4,4,4,4,3,4,3,9,3.0,satisfied +47771,82323,Female,Loyal Customer,65,Business travel,Business,2193,2,4,4,4,1,2,3,2,2,2,2,2,2,1,14,12.0,neutral or dissatisfied +47772,129345,Male,Loyal Customer,51,Personal Travel,Eco,2475,1,1,1,3,5,1,5,5,2,1,3,4,3,5,12,12.0,neutral or dissatisfied +47773,87042,Female,Loyal Customer,53,Business travel,Business,1672,2,2,2,2,3,4,5,5,5,5,5,5,5,3,3,22.0,satisfied +47774,124912,Male,Loyal Customer,47,Business travel,Business,728,4,4,2,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +47775,10362,Female,disloyal Customer,39,Business travel,Business,247,2,2,2,1,2,2,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +47776,4563,Male,Loyal Customer,38,Personal Travel,Eco,561,4,5,4,5,5,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +47777,114683,Male,Loyal Customer,43,Business travel,Business,3774,1,1,1,1,4,4,5,5,5,5,5,3,5,4,67,72.0,satisfied +47778,126912,Male,Loyal Customer,57,Business travel,Business,3285,3,1,1,1,4,4,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +47779,53488,Male,Loyal Customer,63,Business travel,Eco,788,3,2,2,2,3,3,3,3,4,2,1,2,5,3,6,0.0,satisfied +47780,63441,Female,Loyal Customer,27,Personal Travel,Eco,372,1,5,1,3,2,1,4,2,3,2,3,5,2,2,0,0.0,neutral or dissatisfied +47781,97205,Female,Loyal Customer,45,Personal Travel,Eco,1211,1,0,1,2,4,5,5,1,1,1,1,4,1,4,32,18.0,neutral or dissatisfied +47782,11729,Male,disloyal Customer,32,Business travel,Business,395,4,4,4,4,4,4,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +47783,127054,Male,disloyal Customer,25,Business travel,Eco,651,2,4,2,3,5,2,3,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +47784,3387,Female,disloyal Customer,21,Business travel,Eco,296,1,2,1,4,1,1,1,1,3,5,4,2,4,1,0,0.0,neutral or dissatisfied +47785,118648,Male,Loyal Customer,59,Business travel,Eco,325,2,4,4,4,2,2,2,2,4,2,3,3,3,2,23,17.0,neutral or dissatisfied +47786,8303,Female,disloyal Customer,21,Business travel,Eco,402,5,2,5,1,4,2,4,4,3,2,5,5,5,4,0,0.0,satisfied +47787,106415,Male,Loyal Customer,20,Personal Travel,Eco,674,5,4,5,4,5,5,3,5,5,5,4,5,4,5,15,5.0,satisfied +47788,21048,Female,Loyal Customer,34,Business travel,Eco,227,4,4,4,4,4,4,4,4,1,4,3,1,2,4,0,0.0,satisfied +47789,19679,Male,disloyal Customer,38,Business travel,Eco,475,0,5,0,4,1,0,1,1,4,3,2,5,1,1,0,0.0,satisfied +47790,71589,Female,Loyal Customer,31,Business travel,Business,1012,3,5,5,5,3,3,3,3,1,4,2,1,3,3,75,83.0,neutral or dissatisfied +47791,63536,Male,Loyal Customer,59,Business travel,Eco,1009,4,4,4,4,4,4,4,4,3,5,1,2,2,4,0,0.0,satisfied +47792,19540,Female,Loyal Customer,37,Business travel,Eco,160,5,1,1,1,5,5,5,5,1,4,3,2,3,5,87,78.0,satisfied +47793,22110,Male,disloyal Customer,39,Business travel,Eco,694,3,3,3,2,3,3,3,3,2,3,4,3,3,3,67,67.0,neutral or dissatisfied +47794,67626,Female,Loyal Customer,24,Business travel,Business,1438,5,5,5,5,5,5,5,5,5,4,5,3,5,5,32,40.0,satisfied +47795,121518,Female,Loyal Customer,65,Personal Travel,Business,912,2,5,2,2,3,4,5,5,5,2,5,3,5,3,7,11.0,neutral or dissatisfied +47796,42100,Female,Loyal Customer,9,Business travel,Eco,898,1,3,3,3,1,3,1,4,5,3,2,1,2,1,323,311.0,neutral or dissatisfied +47797,92909,Female,Loyal Customer,49,Business travel,Business,2729,3,3,3,3,5,3,2,1,1,1,3,1,1,2,0,0.0,neutral or dissatisfied +47798,77323,Male,Loyal Customer,56,Business travel,Business,588,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +47799,25908,Female,Loyal Customer,52,Business travel,Business,3309,5,5,5,5,4,4,5,5,5,5,5,5,5,3,32,28.0,satisfied +47800,36569,Female,disloyal Customer,49,Business travel,Eco,1121,4,4,4,2,4,4,4,4,1,3,5,2,1,4,0,0.0,neutral or dissatisfied +47801,26023,Male,Loyal Customer,55,Business travel,Business,321,0,0,0,4,5,5,5,5,5,5,5,4,5,4,25,25.0,satisfied +47802,21254,Female,Loyal Customer,30,Personal Travel,Eco Plus,192,2,4,0,4,4,0,2,4,2,3,1,1,2,4,21,13.0,neutral or dissatisfied +47803,28947,Male,Loyal Customer,47,Business travel,Eco,956,5,3,4,3,5,5,5,5,4,4,4,2,3,5,0,0.0,satisfied +47804,9372,Female,Loyal Customer,41,Business travel,Business,2852,1,1,1,1,1,3,4,4,4,4,4,1,4,4,8,7.0,satisfied +47805,111529,Male,disloyal Customer,38,Business travel,Business,794,2,3,3,2,2,3,2,2,3,4,5,3,5,2,20,14.0,satisfied +47806,36823,Male,Loyal Customer,36,Business travel,Business,369,5,2,5,5,3,2,2,5,5,5,5,3,5,2,0,0.0,satisfied +47807,122626,Female,Loyal Customer,24,Personal Travel,Eco,728,4,4,3,2,3,3,3,3,4,5,2,3,2,3,0,0.0,satisfied +47808,5136,Female,Loyal Customer,58,Business travel,Business,184,2,1,1,1,3,4,3,3,3,3,2,3,3,3,14,,neutral or dissatisfied +47809,10500,Male,disloyal Customer,44,Business travel,Business,396,3,3,3,4,4,3,4,4,4,4,5,4,5,4,0,3.0,satisfied +47810,66416,Male,Loyal Customer,40,Personal Travel,Eco,1562,3,1,3,4,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +47811,17243,Female,disloyal Customer,14,Business travel,Eco,872,1,1,1,4,3,1,3,3,2,5,4,2,4,3,61,33.0,neutral or dissatisfied +47812,87731,Female,Loyal Customer,47,Business travel,Business,4502,3,3,2,3,4,4,4,4,5,5,5,4,4,4,0,20.0,satisfied +47813,42355,Male,Loyal Customer,43,Personal Travel,Eco,726,4,5,4,3,3,4,3,3,4,4,4,1,2,3,0,0.0,neutral or dissatisfied +47814,70863,Female,disloyal Customer,44,Business travel,Eco,361,3,2,3,3,2,3,2,2,2,1,3,4,3,2,0,9.0,neutral or dissatisfied +47815,105764,Male,Loyal Customer,21,Business travel,Business,1753,4,4,4,4,4,4,4,4,4,3,3,1,4,4,5,0.0,neutral or dissatisfied +47816,111788,Male,Loyal Customer,70,Personal Travel,Eco,1620,4,5,4,4,2,4,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +47817,85044,Male,Loyal Customer,45,Business travel,Business,1968,2,2,5,2,2,5,5,4,4,4,4,3,4,3,10,1.0,satisfied +47818,104860,Male,Loyal Customer,34,Business travel,Business,327,4,5,5,5,2,2,3,4,4,4,4,2,4,3,30,20.0,neutral or dissatisfied +47819,77712,Male,disloyal Customer,34,Business travel,Eco,696,1,1,1,3,3,1,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +47820,120269,Male,disloyal Customer,30,Business travel,Business,1576,4,4,4,2,2,4,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +47821,106538,Male,Loyal Customer,54,Personal Travel,Eco,321,4,5,4,4,3,4,1,3,2,5,2,2,5,3,7,24.0,neutral or dissatisfied +47822,108860,Female,Loyal Customer,10,Personal Travel,Eco,1892,0,4,0,3,3,0,4,3,2,1,4,2,3,3,7,0.0,satisfied +47823,32194,Female,Loyal Customer,52,Business travel,Eco,102,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +47824,115338,Male,Loyal Customer,42,Business travel,Business,446,1,1,1,1,4,4,5,4,4,4,4,3,4,3,77,79.0,satisfied +47825,82687,Male,Loyal Customer,52,Business travel,Business,2634,2,5,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +47826,125743,Female,disloyal Customer,14,Business travel,Eco,920,2,2,2,4,4,2,4,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +47827,30580,Male,Loyal Customer,43,Business travel,Business,3917,4,2,2,2,2,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +47828,105908,Female,Loyal Customer,37,Business travel,Business,283,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +47829,3673,Female,disloyal Customer,24,Business travel,Eco,431,1,0,1,4,4,1,4,4,3,4,4,5,4,4,10,1.0,neutral or dissatisfied +47830,37800,Male,Loyal Customer,17,Personal Travel,Eco Plus,1069,2,2,2,4,5,2,4,5,4,4,3,3,4,5,31,29.0,neutral or dissatisfied +47831,94840,Male,Loyal Customer,33,Business travel,Eco,319,4,5,5,5,4,3,4,4,1,1,4,1,4,4,3,1.0,neutral or dissatisfied +47832,27285,Male,disloyal Customer,22,Business travel,Eco,937,4,4,4,1,3,4,3,3,4,4,4,4,2,3,0,0.0,satisfied +47833,58208,Male,Loyal Customer,56,Business travel,Eco,925,2,3,3,3,2,2,2,2,3,3,3,1,3,2,1,0.0,neutral or dissatisfied +47834,43405,Female,disloyal Customer,44,Business travel,Eco Plus,402,2,2,2,2,5,2,5,5,2,1,1,2,4,5,0,0.0,neutral or dissatisfied +47835,2936,Female,disloyal Customer,20,Business travel,Eco,737,1,1,1,3,5,1,2,5,4,4,5,3,4,5,2,0.0,neutral or dissatisfied +47836,123399,Male,Loyal Customer,49,Business travel,Business,1337,5,5,5,5,5,4,5,5,5,5,5,3,5,4,26,58.0,satisfied +47837,105227,Male,disloyal Customer,58,Business travel,Eco,377,1,1,1,3,3,1,2,3,3,1,3,3,2,3,65,111.0,neutral or dissatisfied +47838,44167,Male,Loyal Customer,45,Business travel,Eco Plus,229,3,1,1,1,4,3,4,4,3,5,4,3,4,4,0,3.0,satisfied +47839,10991,Female,disloyal Customer,21,Business travel,Business,308,2,2,2,4,3,2,3,3,2,3,3,2,4,3,11,10.0,neutral or dissatisfied +47840,56264,Male,Loyal Customer,20,Business travel,Business,404,1,3,3,3,1,2,1,1,1,5,4,2,3,1,60,46.0,neutral or dissatisfied +47841,86564,Female,Loyal Customer,63,Personal Travel,Eco Plus,712,1,4,1,3,5,4,5,2,2,1,2,5,2,4,30,16.0,neutral or dissatisfied +47842,126536,Male,Loyal Customer,41,Business travel,Business,1741,4,4,4,4,5,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +47843,126218,Male,disloyal Customer,20,Business travel,Eco,507,2,4,2,3,3,2,3,3,1,5,4,2,4,3,34,36.0,neutral or dissatisfied +47844,5816,Female,Loyal Customer,48,Personal Travel,Eco,157,3,3,3,4,1,4,3,4,4,3,1,2,4,4,0,0.0,neutral or dissatisfied +47845,29951,Male,disloyal Customer,27,Business travel,Eco,183,3,3,3,3,2,3,2,2,3,3,3,4,2,2,0,0.0,neutral or dissatisfied +47846,29814,Female,Loyal Customer,61,Business travel,Business,3507,1,1,4,1,4,4,5,4,4,4,5,2,4,1,0,0.0,satisfied +47847,75285,Female,disloyal Customer,24,Business travel,Business,1081,4,0,4,1,2,4,2,2,4,5,4,5,5,2,0,0.0,satisfied +47848,94271,Female,Loyal Customer,50,Business travel,Business,3728,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +47849,13729,Female,Loyal Customer,44,Business travel,Business,441,3,3,3,3,1,2,5,4,4,4,4,2,4,5,23,4.0,satisfied +47850,82797,Female,disloyal Customer,25,Business travel,Business,235,1,4,1,1,4,1,4,4,5,4,4,5,5,4,0,13.0,neutral or dissatisfied +47851,84715,Male,Loyal Customer,16,Personal Travel,Business,481,2,4,2,2,1,2,1,1,5,5,5,2,3,1,0,0.0,neutral or dissatisfied +47852,16673,Male,Loyal Customer,69,Personal Travel,Eco,488,3,1,3,4,5,3,5,5,3,1,3,4,4,5,12,14.0,neutral or dissatisfied +47853,99665,Male,Loyal Customer,55,Personal Travel,Eco,1050,1,5,1,2,4,1,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +47854,48821,Male,Loyal Customer,67,Personal Travel,Business,158,2,5,0,4,5,5,5,2,2,0,2,4,2,5,36,34.0,neutral or dissatisfied +47855,56050,Male,disloyal Customer,40,Business travel,Eco,975,1,2,2,4,2,3,3,4,1,3,1,3,3,3,18,47.0,neutral or dissatisfied +47856,33213,Male,Loyal Customer,38,Business travel,Eco Plus,102,3,2,2,2,3,3,3,3,4,3,3,2,3,3,0,10.0,neutral or dissatisfied +47857,28823,Male,Loyal Customer,19,Business travel,Business,2147,4,4,3,4,4,4,4,4,5,3,2,1,1,4,54,58.0,satisfied +47858,97250,Male,Loyal Customer,66,Business travel,Business,393,2,3,3,3,4,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +47859,911,Female,disloyal Customer,23,Business travel,Eco,282,1,4,1,4,4,1,4,4,4,1,3,2,3,4,34,30.0,neutral or dissatisfied +47860,79075,Female,Loyal Customer,53,Business travel,Eco,356,3,3,3,3,2,3,3,3,3,3,3,3,3,4,0,6.0,neutral or dissatisfied +47861,36995,Female,disloyal Customer,36,Business travel,Eco,359,3,1,3,4,3,3,3,3,3,1,4,3,4,3,42,35.0,neutral or dissatisfied +47862,97951,Female,Loyal Customer,56,Business travel,Business,3738,2,2,2,2,3,5,5,5,5,5,5,4,5,4,9,0.0,satisfied +47863,117838,Male,Loyal Customer,33,Business travel,Eco Plus,328,4,3,3,3,4,4,4,4,4,4,4,2,4,4,17,11.0,neutral or dissatisfied +47864,38346,Female,Loyal Customer,50,Business travel,Business,1050,3,1,1,1,4,3,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +47865,2,Female,Loyal Customer,35,Business travel,Business,821,2,2,2,2,3,5,4,5,5,5,5,3,5,5,26,39.0,satisfied +47866,98896,Male,Loyal Customer,42,Business travel,Business,1811,2,2,2,2,4,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +47867,17731,Female,Loyal Customer,32,Business travel,Business,501,1,1,1,1,5,5,5,5,3,2,5,5,2,5,55,41.0,satisfied +47868,108870,Male,Loyal Customer,34,Personal Travel,Eco Plus,1892,3,2,3,2,5,3,5,5,4,1,2,1,3,5,10,9.0,neutral or dissatisfied +47869,4189,Female,Loyal Customer,59,Business travel,Business,2584,4,4,2,4,3,5,4,5,5,5,5,4,5,3,96,73.0,satisfied +47870,13152,Female,Loyal Customer,30,Personal Travel,Eco,562,3,4,3,5,3,3,3,3,4,2,5,3,5,3,7,0.0,neutral or dissatisfied +47871,82989,Male,disloyal Customer,24,Business travel,Eco,1084,3,2,2,2,1,2,1,1,4,5,4,5,5,1,45,42.0,neutral or dissatisfied +47872,121552,Female,disloyal Customer,52,Business travel,Eco,912,2,2,2,3,5,2,5,5,2,1,2,2,2,5,0,0.0,neutral or dissatisfied +47873,85268,Male,Loyal Customer,46,Personal Travel,Eco,813,2,4,2,3,1,2,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +47874,13472,Female,disloyal Customer,72,Business travel,Eco Plus,475,2,2,2,3,4,2,1,4,4,2,4,3,4,4,70,58.0,neutral or dissatisfied +47875,60621,Female,Loyal Customer,46,Business travel,Business,1201,4,4,4,4,5,3,3,4,4,4,4,4,4,3,3,0.0,neutral or dissatisfied +47876,61533,Female,Loyal Customer,67,Personal Travel,Eco,2419,3,2,3,4,1,4,3,5,5,3,3,2,5,2,6,2.0,neutral or dissatisfied +47877,94885,Female,disloyal Customer,50,Business travel,Eco,458,3,0,3,4,4,3,4,4,3,4,3,4,4,4,0,0.0,neutral or dissatisfied +47878,110290,Female,Loyal Customer,38,Business travel,Business,3433,1,1,1,1,4,4,5,4,4,5,4,4,4,5,36,29.0,satisfied +47879,50811,Female,Loyal Customer,54,Personal Travel,Eco,363,4,2,4,4,3,4,4,3,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +47880,96936,Female,Loyal Customer,42,Business travel,Business,794,1,1,5,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +47881,39507,Female,Loyal Customer,21,Business travel,Business,2438,3,2,2,2,3,3,3,3,1,1,2,3,4,3,0,0.0,neutral or dissatisfied +47882,16868,Male,disloyal Customer,22,Business travel,Eco,746,1,1,1,1,1,1,1,4,4,2,5,1,5,1,213,221.0,neutral or dissatisfied +47883,88379,Male,Loyal Customer,51,Business travel,Business,2435,3,3,3,3,5,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +47884,112491,Female,Loyal Customer,19,Personal Travel,Eco,967,2,2,1,3,1,1,1,1,3,5,3,2,3,1,14,0.0,neutral or dissatisfied +47885,41470,Male,Loyal Customer,56,Business travel,Eco,715,5,5,5,5,5,5,5,5,1,1,1,2,4,5,0,0.0,satisfied +47886,41660,Female,Loyal Customer,25,Business travel,Eco,936,3,5,5,5,3,3,4,3,2,4,3,3,3,3,21,16.0,neutral or dissatisfied +47887,110549,Male,Loyal Customer,48,Business travel,Business,2491,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +47888,54460,Male,Loyal Customer,18,Business travel,Business,925,3,3,3,3,5,5,5,5,3,1,1,1,5,5,12,0.0,satisfied +47889,77997,Male,Loyal Customer,47,Business travel,Business,3836,0,4,0,4,5,4,4,5,5,5,5,5,5,3,0,7.0,satisfied +47890,91901,Male,Loyal Customer,42,Business travel,Business,2475,3,3,3,3,4,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +47891,124494,Female,Loyal Customer,51,Business travel,Business,3541,3,3,4,3,3,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +47892,3732,Female,Loyal Customer,45,Personal Travel,Eco,431,2,1,3,3,2,3,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +47893,83154,Male,Loyal Customer,38,Business travel,Business,2209,5,5,3,5,3,5,5,5,5,5,5,4,5,5,3,9.0,satisfied +47894,18967,Female,Loyal Customer,36,Personal Travel,Eco Plus,448,3,5,3,3,3,3,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +47895,109450,Female,disloyal Customer,23,Business travel,Business,861,0,0,0,3,3,0,3,3,3,4,4,3,4,3,0,10.0,satisfied +47896,57907,Female,Loyal Customer,61,Business travel,Business,305,2,2,3,2,5,1,1,3,3,4,3,2,3,4,15,8.0,satisfied +47897,120291,Female,Loyal Customer,66,Personal Travel,Eco,1576,5,4,5,2,2,3,5,3,3,5,3,4,3,3,0,0.0,satisfied +47898,33903,Female,Loyal Customer,30,Personal Travel,Eco,1226,2,1,2,3,2,2,2,2,2,2,3,4,3,2,34,31.0,neutral or dissatisfied +47899,1412,Male,Loyal Customer,20,Personal Travel,Eco Plus,247,3,4,3,1,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +47900,121368,Male,Loyal Customer,55,Personal Travel,Eco,1670,2,1,2,3,3,2,3,3,1,2,2,1,2,3,0,0.0,neutral or dissatisfied +47901,24401,Male,disloyal Customer,28,Business travel,Business,634,4,4,4,4,3,4,2,3,4,2,4,3,4,3,0,9.0,satisfied +47902,18922,Female,Loyal Customer,36,Personal Travel,Eco,448,3,3,3,4,5,3,1,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +47903,30362,Female,Loyal Customer,44,Business travel,Business,862,3,3,3,3,4,2,3,4,4,4,4,1,4,5,0,0.0,satisfied +47904,4773,Female,Loyal Customer,56,Business travel,Business,1575,1,1,1,1,3,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +47905,79881,Male,Loyal Customer,47,Business travel,Business,1076,1,1,1,1,3,4,5,2,2,2,2,3,2,4,95,60.0,satisfied +47906,30495,Male,Loyal Customer,18,Personal Travel,Eco,516,2,1,2,3,1,2,1,1,4,2,3,2,3,1,0,6.0,neutral or dissatisfied +47907,59517,Male,Loyal Customer,20,Personal Travel,Business,965,4,4,4,4,4,4,4,1,4,4,3,4,1,4,368,357.0,satisfied +47908,90802,Male,Loyal Customer,46,Business travel,Eco,406,3,3,3,3,3,3,3,3,1,1,3,3,3,3,89,74.0,neutral or dissatisfied +47909,27346,Female,Loyal Customer,42,Business travel,Eco,956,4,1,1,1,5,1,4,3,3,4,3,5,3,2,0,0.0,satisfied +47910,65752,Female,disloyal Customer,26,Personal Travel,Eco,936,2,2,3,3,2,3,3,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +47911,126631,Female,disloyal Customer,22,Business travel,Eco,602,1,4,1,4,4,1,4,4,2,1,4,3,4,4,35,27.0,neutral or dissatisfied +47912,86450,Female,Loyal Customer,48,Business travel,Business,760,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +47913,13783,Female,Loyal Customer,36,Business travel,Business,2721,1,5,5,5,4,3,4,1,1,1,1,4,1,4,0,13.0,neutral or dissatisfied +47914,51237,Female,Loyal Customer,47,Business travel,Eco Plus,109,4,1,5,5,2,2,3,4,4,4,4,5,4,4,0,0.0,satisfied +47915,10148,Female,Loyal Customer,34,Personal Travel,Eco,1190,4,5,4,1,5,4,5,5,3,4,3,5,4,5,0,0.0,satisfied +47916,72360,Male,disloyal Customer,25,Business travel,Business,1017,5,0,5,3,3,5,3,3,5,3,4,3,5,3,0,0.0,satisfied +47917,127887,Female,Loyal Customer,54,Personal Travel,Eco Plus,1276,3,4,2,3,3,5,5,3,3,2,3,3,3,5,4,16.0,neutral or dissatisfied +47918,112923,Female,Loyal Customer,49,Personal Travel,Eco,1211,2,2,2,3,2,1,3,2,2,2,2,1,2,3,1,0.0,neutral or dissatisfied +47919,88274,Female,Loyal Customer,26,Business travel,Business,2607,3,5,5,5,3,3,3,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +47920,98601,Female,Loyal Customer,45,Business travel,Business,834,2,4,4,4,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +47921,113127,Male,disloyal Customer,22,Business travel,Eco Plus,479,3,2,3,3,1,3,4,1,3,4,2,2,3,1,33,26.0,neutral or dissatisfied +47922,99568,Male,Loyal Customer,36,Business travel,Business,829,2,3,3,3,1,4,3,2,2,2,2,1,2,1,18,10.0,neutral or dissatisfied +47923,83068,Female,disloyal Customer,32,Business travel,Eco,983,3,3,3,3,4,3,5,4,3,3,3,2,3,4,0,7.0,neutral or dissatisfied +47924,25078,Female,Loyal Customer,48,Business travel,Business,557,3,3,3,3,5,2,1,5,5,5,5,2,5,2,13,31.0,satisfied +47925,24293,Female,Loyal Customer,34,Personal Travel,Eco,147,4,4,0,3,4,0,4,4,5,4,5,5,4,4,0,0.0,satisfied +47926,129352,Male,Loyal Customer,57,Personal Travel,Eco,2475,4,4,4,4,1,4,1,1,3,2,4,4,3,1,0,1.0,satisfied +47927,18359,Male,Loyal Customer,36,Personal Travel,Business,169,4,4,4,4,4,5,5,4,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +47928,19705,Male,Loyal Customer,48,Business travel,Business,475,2,2,2,2,3,4,5,5,5,5,5,4,5,2,0,0.0,satisfied +47929,88297,Male,Loyal Customer,47,Business travel,Business,2900,1,1,1,1,2,5,4,4,4,4,4,3,4,5,4,5.0,satisfied +47930,25246,Female,Loyal Customer,47,Personal Travel,Eco,787,1,5,1,5,2,4,5,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +47931,127384,Male,Loyal Customer,53,Business travel,Business,2114,3,3,3,3,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +47932,95794,Female,disloyal Customer,32,Business travel,Business,419,2,2,2,1,2,2,2,2,3,4,5,4,5,2,1,0.0,neutral or dissatisfied +47933,58946,Female,disloyal Customer,31,Business travel,Eco Plus,888,3,3,3,4,1,3,2,1,4,2,3,4,3,1,8,26.0,neutral or dissatisfied +47934,82617,Male,Loyal Customer,20,Personal Travel,Eco,528,5,4,5,2,2,5,2,2,3,5,4,3,5,2,5,28.0,satisfied +47935,9574,Female,Loyal Customer,58,Business travel,Eco,296,3,2,2,2,1,4,4,3,3,3,3,4,3,4,17,16.0,neutral or dissatisfied +47936,127413,Male,Loyal Customer,51,Personal Travel,Eco,1009,5,3,4,1,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +47937,124482,Male,Loyal Customer,56,Business travel,Business,930,4,4,4,4,5,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +47938,101630,Male,Loyal Customer,47,Personal Travel,Eco,1371,3,4,3,1,2,3,2,2,3,5,4,5,4,2,1,0.0,neutral or dissatisfied +47939,41219,Female,Loyal Customer,39,Business travel,Eco Plus,1091,4,2,2,2,4,4,4,4,3,1,4,1,3,4,0,20.0,satisfied +47940,19824,Male,disloyal Customer,25,Business travel,Eco,654,2,2,2,3,5,2,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +47941,55944,Male,Loyal Customer,59,Business travel,Business,1620,5,2,5,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +47942,37309,Male,Loyal Customer,28,Business travel,Eco,944,0,0,0,2,5,0,5,5,2,5,2,1,3,5,0,13.0,satisfied +47943,30786,Female,Loyal Customer,34,Business travel,Business,2944,3,1,1,1,2,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +47944,10539,Female,Loyal Customer,57,Business travel,Business,270,1,1,3,1,3,5,5,5,5,5,5,5,5,5,36,27.0,satisfied +47945,79463,Male,Loyal Customer,23,Business travel,Business,2389,2,2,2,2,5,5,5,5,5,5,1,3,1,5,0,0.0,satisfied +47946,104718,Female,Loyal Customer,42,Business travel,Business,1407,1,1,1,1,2,4,4,5,5,5,5,3,5,5,5,27.0,satisfied +47947,61485,Male,Loyal Customer,43,Business travel,Business,2419,5,5,5,5,2,3,5,4,4,4,4,5,4,3,47,31.0,satisfied +47948,115200,Male,Loyal Customer,45,Business travel,Eco,333,3,2,2,2,3,3,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +47949,103759,Female,Loyal Customer,49,Personal Travel,Eco,484,3,0,3,3,5,4,5,4,4,3,4,3,4,3,12,8.0,neutral or dissatisfied +47950,124526,Male,Loyal Customer,51,Business travel,Eco,1276,4,3,2,2,4,4,4,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +47951,116390,Male,Loyal Customer,66,Personal Travel,Eco,358,2,5,2,3,1,2,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +47952,79152,Male,Loyal Customer,70,Personal Travel,Eco Plus,306,2,4,2,2,1,2,1,1,5,2,5,3,4,1,0,5.0,neutral or dissatisfied +47953,122373,Female,disloyal Customer,17,Business travel,Eco,529,2,4,2,3,3,2,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +47954,125186,Female,Loyal Customer,46,Business travel,Business,1977,4,4,4,4,3,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +47955,48045,Female,Loyal Customer,41,Business travel,Eco,677,3,3,3,3,3,3,3,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +47956,7768,Male,Loyal Customer,55,Business travel,Business,3930,3,3,3,3,3,5,5,3,3,3,3,3,3,3,0,3.0,satisfied +47957,68591,Male,Loyal Customer,13,Personal Travel,Eco,1616,1,5,1,1,3,1,3,3,4,5,4,3,4,3,23,0.0,neutral or dissatisfied +47958,6013,Male,Loyal Customer,43,Business travel,Business,3042,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,3.0,satisfied +47959,40251,Male,Loyal Customer,38,Business travel,Business,347,2,2,2,2,5,4,3,2,2,2,2,2,2,4,0,4.0,neutral or dissatisfied +47960,97721,Male,Loyal Customer,46,Business travel,Business,3579,3,3,3,3,3,4,5,5,5,5,5,4,5,4,9,2.0,satisfied +47961,127994,Female,Loyal Customer,37,Business travel,Business,1488,1,4,4,4,2,3,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +47962,80673,Female,Loyal Customer,62,Personal Travel,Eco,821,2,2,2,4,3,3,4,4,4,2,5,4,4,4,4,13.0,neutral or dissatisfied +47963,16913,Female,Loyal Customer,60,Business travel,Eco Plus,746,5,2,2,2,4,2,4,5,5,5,5,2,5,5,7,0.0,satisfied +47964,7197,Female,disloyal Customer,38,Business travel,Eco,139,1,1,1,3,1,1,1,1,1,5,3,1,4,1,1,14.0,neutral or dissatisfied +47965,104764,Male,Loyal Customer,18,Personal Travel,Eco,1407,1,4,1,3,1,1,1,1,3,4,5,3,5,1,34,50.0,neutral or dissatisfied +47966,68179,Male,Loyal Customer,29,Personal Travel,Eco,603,1,4,1,4,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +47967,52956,Male,Loyal Customer,30,Business travel,Business,2306,2,2,2,2,4,4,4,4,4,3,5,4,1,4,6,8.0,satisfied +47968,51420,Male,Loyal Customer,23,Personal Travel,Eco Plus,209,1,3,0,3,3,0,1,3,1,2,3,1,3,3,0,2.0,neutral or dissatisfied +47969,115490,Male,Loyal Customer,41,Business travel,Eco,337,4,1,1,1,4,4,4,4,1,2,3,4,4,4,16,7.0,neutral or dissatisfied +47970,71712,Male,Loyal Customer,42,Business travel,Business,1631,4,4,4,4,4,5,5,5,5,4,5,5,5,5,239,238.0,satisfied +47971,80201,Male,Loyal Customer,51,Personal Travel,Eco,2586,3,5,3,1,3,5,5,1,5,4,4,5,2,5,0,0.0,neutral or dissatisfied +47972,117277,Female,disloyal Customer,44,Business travel,Business,369,4,4,4,3,5,4,5,5,3,3,4,3,4,5,1,1.0,satisfied +47973,43123,Female,Loyal Customer,35,Business travel,Eco Plus,173,5,1,1,1,5,5,5,5,4,2,1,4,3,5,0,0.0,satisfied +47974,82144,Male,Loyal Customer,47,Business travel,Business,237,3,3,3,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +47975,119639,Female,Loyal Customer,58,Business travel,Business,507,4,4,4,4,5,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +47976,27980,Female,disloyal Customer,38,Business travel,Eco,878,3,3,3,4,3,1,1,2,5,4,3,1,4,1,0,13.0,neutral or dissatisfied +47977,50188,Male,disloyal Customer,34,Business travel,Eco,337,3,0,4,1,2,4,2,2,1,2,2,3,1,2,0,1.0,neutral or dissatisfied +47978,19963,Female,Loyal Customer,31,Personal Travel,Eco Plus,296,2,5,2,2,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +47979,38462,Female,disloyal Customer,17,Business travel,Eco,1226,4,4,4,3,4,4,4,4,2,1,3,4,4,4,0,0.0,neutral or dissatisfied +47980,73845,Male,Loyal Customer,61,Business travel,Business,1810,5,5,5,5,5,3,5,2,2,3,2,3,2,3,0,0.0,satisfied +47981,26018,Male,Loyal Customer,57,Personal Travel,Eco,425,4,4,4,3,5,4,5,5,5,3,4,5,5,5,1,0.0,neutral or dissatisfied +47982,129177,Female,Loyal Customer,66,Personal Travel,Eco,679,5,3,5,4,3,3,3,4,4,5,1,2,4,2,0,0.0,satisfied +47983,5790,Male,disloyal Customer,38,Business travel,Business,273,4,4,4,3,5,4,5,5,3,5,4,5,4,5,0,0.0,satisfied +47984,990,Male,Loyal Customer,40,Business travel,Eco,396,4,4,4,4,4,4,4,4,1,1,3,1,2,4,7,30.0,satisfied +47985,94667,Male,Loyal Customer,39,Business travel,Business,2208,3,4,4,4,1,2,1,3,3,3,3,4,3,4,79,74.0,neutral or dissatisfied +47986,9136,Female,Loyal Customer,46,Business travel,Business,2356,2,1,1,1,3,3,3,2,2,2,2,3,2,3,23,9.0,neutral or dissatisfied +47987,1512,Male,Loyal Customer,50,Business travel,Business,862,4,4,4,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +47988,44407,Male,Loyal Customer,61,Personal Travel,Eco,323,3,5,3,1,4,3,3,4,4,4,5,1,5,4,21,39.0,neutral or dissatisfied +47989,125062,Female,Loyal Customer,46,Business travel,Business,1935,2,2,2,2,5,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +47990,27400,Female,Loyal Customer,31,Business travel,Business,937,5,5,5,5,2,3,2,2,1,4,4,1,2,2,3,0.0,satisfied +47991,93553,Male,disloyal Customer,27,Business travel,Business,719,2,2,2,4,3,2,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +47992,65372,Male,Loyal Customer,67,Business travel,Business,432,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,4.0,satisfied +47993,54242,Female,Loyal Customer,22,Business travel,Business,1682,1,1,1,1,4,4,4,4,5,5,3,5,3,4,2,4.0,satisfied +47994,103383,Female,Loyal Customer,57,Business travel,Business,237,5,5,5,5,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +47995,48069,Male,Loyal Customer,50,Business travel,Business,3378,2,2,4,2,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +47996,127842,Female,Loyal Customer,20,Business travel,Eco Plus,1262,0,3,0,5,1,0,1,1,1,5,5,3,4,1,0,0.0,satisfied +47997,90509,Female,Loyal Customer,31,Business travel,Business,250,1,1,1,1,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +47998,95351,Male,Loyal Customer,67,Personal Travel,Eco,239,2,4,2,5,2,2,2,2,4,4,4,4,4,2,2,0.0,neutral or dissatisfied +47999,24557,Female,disloyal Customer,30,Business travel,Eco,696,4,5,5,4,1,5,1,1,3,5,1,3,2,1,1,2.0,neutral or dissatisfied +48000,71374,Male,Loyal Customer,34,Business travel,Business,3281,4,3,2,2,2,3,3,4,4,4,4,4,4,1,5,3.0,neutral or dissatisfied +48001,80320,Male,Loyal Customer,49,Personal Travel,Eco,746,2,4,2,3,3,2,3,3,3,2,4,3,4,3,0,9.0,neutral or dissatisfied +48002,9739,Male,disloyal Customer,25,Business travel,Business,908,1,0,1,2,3,1,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +48003,34048,Male,Loyal Customer,27,Business travel,Business,1674,5,5,5,5,5,5,5,5,2,1,4,4,1,5,30,1.0,satisfied +48004,109117,Female,Loyal Customer,40,Business travel,Eco Plus,705,5,4,4,4,5,5,5,5,3,3,4,2,3,5,34,13.0,satisfied +48005,121180,Male,Loyal Customer,33,Personal Travel,Eco,2521,1,2,2,4,2,2,1,1,5,4,3,1,3,1,24,23.0,neutral or dissatisfied +48006,109349,Female,Loyal Customer,24,Business travel,Business,2174,2,2,2,2,5,5,5,5,5,4,5,4,4,5,14,16.0,satisfied +48007,18111,Female,Loyal Customer,33,Business travel,Business,2884,4,5,4,4,3,3,4,4,4,4,4,3,4,3,0,4.0,satisfied +48008,129172,Male,Loyal Customer,41,Personal Travel,Eco,679,2,4,2,3,1,2,1,1,3,2,4,4,4,1,5,12.0,neutral or dissatisfied +48009,12253,Female,disloyal Customer,42,Business travel,Eco,253,1,0,1,4,4,1,4,4,5,3,3,3,3,4,0,0.0,neutral or dissatisfied +48010,38252,Male,disloyal Customer,11,Business travel,Eco,1111,2,2,2,4,2,3,3,3,3,3,3,3,2,3,327,303.0,neutral or dissatisfied +48011,43526,Female,Loyal Customer,36,Business travel,Eco,807,4,5,5,5,4,4,4,4,2,5,4,3,4,4,28,39.0,neutral or dissatisfied +48012,91164,Female,Loyal Customer,35,Personal Travel,Eco,223,3,4,3,3,3,3,3,3,5,5,4,5,4,3,0,7.0,neutral or dissatisfied +48013,116215,Male,Loyal Customer,47,Personal Travel,Eco,325,3,3,3,2,2,3,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +48014,104559,Female,Loyal Customer,53,Business travel,Business,2360,3,3,3,3,5,5,5,3,3,3,3,3,3,4,8,6.0,satisfied +48015,55287,Male,Loyal Customer,43,Business travel,Eco,1585,2,5,5,5,2,3,3,1,4,4,3,3,4,3,112,133.0,neutral or dissatisfied +48016,32078,Male,Loyal Customer,58,Business travel,Business,3407,4,4,4,4,4,1,1,4,4,4,4,1,4,5,2,4.0,satisfied +48017,30507,Female,disloyal Customer,43,Business travel,Eco,1346,3,3,3,2,5,3,5,5,3,3,3,1,2,5,0,4.0,neutral or dissatisfied +48018,50437,Female,disloyal Customer,21,Business travel,Eco,337,2,0,2,5,1,2,1,1,5,3,1,5,4,1,1,0.0,neutral or dissatisfied +48019,16752,Female,Loyal Customer,27,Business travel,Business,2976,2,1,1,1,2,2,2,2,1,2,3,1,4,2,0,44.0,neutral or dissatisfied +48020,1258,Male,Loyal Customer,23,Personal Travel,Eco,309,2,4,2,5,1,2,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +48021,126288,Male,Loyal Customer,21,Personal Travel,Eco,631,1,5,1,3,1,1,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +48022,85794,Female,disloyal Customer,59,Business travel,Eco,526,2,2,2,2,4,2,4,4,4,4,3,1,2,4,0,0.0,neutral or dissatisfied +48023,41230,Male,Loyal Customer,38,Business travel,Business,744,2,2,2,2,1,2,4,5,5,5,5,3,5,5,18,26.0,satisfied +48024,33306,Female,Loyal Customer,64,Personal Travel,Eco Plus,163,3,5,3,4,5,4,5,4,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +48025,112767,Female,disloyal Customer,10,Business travel,Eco,588,4,5,4,4,4,4,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +48026,60180,Female,Loyal Customer,19,Personal Travel,Eco,1050,2,5,1,2,3,1,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +48027,66992,Male,Loyal Customer,52,Business travel,Business,2071,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +48028,67487,Male,Loyal Customer,40,Business travel,Business,1744,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +48029,24979,Male,Loyal Customer,35,Business travel,Eco,484,1,2,2,2,1,1,1,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +48030,117798,Female,Loyal Customer,46,Business travel,Business,328,4,4,4,4,3,5,4,3,3,4,3,3,3,5,0,3.0,satisfied +48031,126128,Female,disloyal Customer,18,Business travel,Eco,328,3,1,3,4,5,3,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +48032,67372,Male,Loyal Customer,57,Business travel,Business,769,5,5,3,5,5,4,5,4,4,4,4,5,4,5,0,3.0,satisfied +48033,73386,Male,Loyal Customer,30,Business travel,Business,2307,4,4,4,4,4,3,4,4,2,1,2,2,3,4,7,16.0,neutral or dissatisfied +48034,97560,Male,Loyal Customer,58,Business travel,Business,448,3,3,3,3,3,4,5,4,4,4,4,4,4,4,17,11.0,satisfied +48035,42286,Female,Loyal Customer,36,Business travel,Business,3569,2,1,1,1,1,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +48036,51005,Female,Loyal Customer,52,Personal Travel,Eco,190,2,5,2,1,5,4,4,2,2,2,2,4,2,3,115,102.0,neutral or dissatisfied +48037,27704,Male,Loyal Customer,42,Personal Travel,Eco Plus,1107,3,1,3,1,1,3,1,1,1,4,2,3,1,1,0,0.0,neutral or dissatisfied +48038,16389,Female,Loyal Customer,39,Business travel,Business,2790,3,3,3,3,5,2,1,3,3,3,3,4,3,3,0,5.0,neutral or dissatisfied +48039,33944,Female,disloyal Customer,31,Business travel,Eco,1072,2,2,2,3,4,2,4,4,2,2,4,3,4,4,0,0.0,neutral or dissatisfied +48040,48107,Male,Loyal Customer,45,Business travel,Eco,236,5,1,1,1,5,5,5,5,1,4,1,4,2,5,1,4.0,satisfied +48041,117245,Female,Loyal Customer,15,Personal Travel,Eco,621,1,5,2,1,3,2,3,3,4,3,5,3,5,3,25,14.0,neutral or dissatisfied +48042,112242,Male,disloyal Customer,22,Business travel,Eco,733,3,3,3,4,4,3,2,4,4,2,5,4,5,4,19,1.0,neutral or dissatisfied +48043,82510,Male,Loyal Customer,45,Business travel,Business,1749,4,4,3,4,3,4,5,4,4,5,4,5,4,3,19,6.0,satisfied +48044,8027,Male,Loyal Customer,38,Business travel,Business,125,2,5,5,5,3,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +48045,26791,Male,disloyal Customer,36,Business travel,Business,226,4,4,4,3,1,4,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +48046,62391,Female,Loyal Customer,24,Business travel,Business,2662,3,5,5,5,3,3,3,3,3,3,3,2,4,3,52,32.0,neutral or dissatisfied +48047,94210,Female,Loyal Customer,23,Business travel,Business,3671,4,4,4,4,5,5,5,5,5,5,5,4,5,5,74,84.0,satisfied +48048,76494,Female,disloyal Customer,20,Business travel,Eco,357,4,3,4,3,3,4,3,3,3,1,4,2,3,3,0,20.0,neutral or dissatisfied +48049,68683,Male,Loyal Customer,54,Business travel,Business,3974,1,1,1,1,2,2,1,4,4,4,5,3,4,2,0,0.0,satisfied +48050,41872,Male,Loyal Customer,59,Personal Travel,Eco Plus,483,1,2,1,2,2,1,2,2,1,3,3,1,2,2,82,71.0,neutral or dissatisfied +48051,4398,Female,Loyal Customer,39,Personal Travel,Eco,607,1,5,1,1,3,1,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +48052,128490,Female,Loyal Customer,56,Personal Travel,Eco,646,2,4,2,4,1,2,1,3,3,2,5,3,3,3,6,24.0,neutral or dissatisfied +48053,100497,Male,disloyal Customer,25,Business travel,Eco,580,3,3,3,4,4,3,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +48054,89478,Female,Loyal Customer,57,Business travel,Business,1931,2,4,4,4,3,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +48055,123023,Female,Loyal Customer,53,Business travel,Business,468,4,4,5,4,5,4,5,4,4,4,4,5,4,5,32,29.0,satisfied +48056,68172,Female,disloyal Customer,19,Business travel,Eco,603,3,1,3,4,1,3,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +48057,11391,Female,disloyal Customer,34,Business travel,Business,301,1,1,1,5,2,1,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +48058,79876,Female,Loyal Customer,40,Business travel,Business,1069,2,2,2,2,4,4,4,4,4,4,4,4,4,4,56,58.0,satisfied +48059,12134,Female,Loyal Customer,44,Business travel,Business,2951,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +48060,77573,Male,disloyal Customer,23,Business travel,Eco,874,5,4,4,2,2,4,4,2,5,2,4,3,5,2,0,0.0,satisfied +48061,47199,Female,disloyal Customer,18,Business travel,Eco,954,3,3,3,3,1,3,4,1,5,1,4,5,4,1,0,0.0,neutral or dissatisfied +48062,20887,Male,Loyal Customer,45,Personal Travel,Eco Plus,508,3,4,3,3,3,3,2,3,3,4,5,5,5,3,29,20.0,neutral or dissatisfied +48063,35545,Female,Loyal Customer,10,Personal Travel,Eco,1005,2,5,3,2,5,3,5,5,3,4,5,3,5,5,25,12.0,neutral or dissatisfied +48064,90880,Female,Loyal Customer,49,Business travel,Business,581,2,5,5,5,3,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +48065,4244,Male,disloyal Customer,35,Business travel,Eco,1020,2,3,3,1,2,3,2,2,1,4,1,1,5,2,0,2.0,neutral or dissatisfied +48066,107472,Female,Loyal Customer,21,Personal Travel,Eco Plus,1121,2,4,2,2,5,2,1,5,5,2,4,4,5,5,23,0.0,neutral or dissatisfied +48067,101504,Male,Loyal Customer,56,Business travel,Business,345,1,4,3,4,3,3,3,1,1,2,1,2,1,2,56,53.0,neutral or dissatisfied +48068,17038,Female,Loyal Customer,42,Business travel,Business,1134,5,5,5,5,3,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +48069,72381,Female,Loyal Customer,43,Business travel,Business,1559,3,3,3,3,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +48070,6738,Female,Loyal Customer,36,Business travel,Eco Plus,268,3,5,5,5,3,3,3,3,3,3,3,1,3,3,10,7.0,neutral or dissatisfied +48071,18033,Female,disloyal Customer,24,Business travel,Business,488,0,0,0,2,4,0,4,4,4,4,4,1,5,4,7,0.0,satisfied +48072,29092,Female,Loyal Customer,45,Personal Travel,Eco,956,3,4,3,4,5,4,5,4,4,3,1,5,4,4,0,0.0,neutral or dissatisfied +48073,111142,Male,Loyal Customer,37,Business travel,Business,3621,3,3,3,3,2,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +48074,6612,Female,Loyal Customer,39,Business travel,Business,3199,4,4,4,4,5,4,4,4,4,4,4,4,4,4,13,5.0,satisfied +48075,45656,Male,Loyal Customer,43,Personal Travel,Eco,406,3,4,3,1,3,3,3,3,3,2,5,3,5,3,0,9.0,neutral or dissatisfied +48076,126673,Male,disloyal Customer,26,Business travel,Business,2276,2,2,2,4,3,2,3,3,3,3,3,3,4,3,33,50.0,neutral or dissatisfied +48077,10740,Male,Loyal Customer,37,Business travel,Eco,308,1,3,3,3,1,1,1,1,2,3,3,4,3,1,25,33.0,neutral or dissatisfied +48078,43855,Female,Loyal Customer,63,Business travel,Business,199,4,4,4,4,5,4,4,3,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +48079,83073,Female,disloyal Customer,22,Business travel,Eco,957,2,3,3,3,5,3,5,5,2,3,3,3,4,5,0,6.0,neutral or dissatisfied +48080,96464,Female,Loyal Customer,57,Business travel,Eco,436,3,2,2,2,4,1,2,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +48081,72220,Female,disloyal Customer,22,Business travel,Eco,919,3,3,3,1,4,3,4,4,4,3,1,1,1,4,17,76.0,neutral or dissatisfied +48082,12556,Female,Loyal Customer,18,Personal Travel,Eco,871,1,3,1,2,2,1,2,2,3,4,4,4,5,2,2,0.0,neutral or dissatisfied +48083,28003,Male,Loyal Customer,32,Business travel,Business,763,5,5,5,5,5,5,5,5,1,2,1,2,4,5,0,0.0,satisfied +48084,51308,Male,Loyal Customer,41,Business travel,Eco Plus,109,3,3,3,3,3,3,3,3,3,4,3,3,3,3,0,1.0,neutral or dissatisfied +48085,92172,Female,Loyal Customer,47,Business travel,Business,1956,1,1,1,1,4,5,4,5,5,5,5,5,5,3,1,18.0,satisfied +48086,13959,Male,Loyal Customer,15,Personal Travel,Eco,192,2,1,2,3,4,2,4,4,4,3,2,4,2,4,49,50.0,neutral or dissatisfied +48087,125995,Male,Loyal Customer,54,Personal Travel,Business,507,4,1,4,4,2,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +48088,105697,Male,Loyal Customer,46,Business travel,Business,787,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,20.0,satisfied +48089,40533,Male,disloyal Customer,47,Business travel,Eco,391,2,0,2,1,3,2,3,3,5,4,3,3,4,3,0,0.0,neutral or dissatisfied +48090,29665,Female,Loyal Customer,14,Personal Travel,Eco,1448,1,5,2,4,4,2,4,4,5,1,2,5,5,4,0,0.0,neutral or dissatisfied +48091,47618,Male,Loyal Customer,44,Business travel,Business,715,2,2,2,2,2,5,1,4,4,5,4,3,4,3,39,53.0,satisfied +48092,90380,Female,Loyal Customer,49,Business travel,Business,270,2,4,3,4,2,4,4,2,2,2,2,3,2,3,8,0.0,neutral or dissatisfied +48093,72416,Male,Loyal Customer,30,Business travel,Business,1119,4,4,4,4,5,4,5,5,3,4,4,4,5,5,0,18.0,satisfied +48094,35089,Female,Loyal Customer,48,Business travel,Business,2285,4,4,4,4,2,2,2,5,5,5,5,2,5,4,0,31.0,satisfied +48095,125041,Male,Loyal Customer,39,Business travel,Eco,800,1,0,0,3,0,3,3,4,5,4,3,3,3,3,0,18.0,neutral or dissatisfied +48096,17802,Male,Loyal Customer,32,Business travel,Business,2443,4,4,4,4,5,5,5,5,3,2,2,1,3,5,0,0.0,satisfied +48097,114515,Female,disloyal Customer,47,Business travel,Business,325,5,5,5,4,1,5,1,1,5,3,5,3,5,1,9,0.0,satisfied +48098,106639,Male,Loyal Customer,19,Business travel,Eco Plus,306,3,1,4,4,3,3,4,3,4,1,3,2,3,3,11,11.0,neutral or dissatisfied +48099,3837,Female,Loyal Customer,16,Personal Travel,Eco,710,2,4,2,4,1,2,1,1,5,5,4,3,5,1,14,21.0,neutral or dissatisfied +48100,127595,Female,Loyal Customer,47,Business travel,Business,1773,5,5,5,5,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +48101,118687,Male,Loyal Customer,63,Personal Travel,Eco,370,1,3,1,4,2,1,2,2,2,2,2,1,3,2,3,3.0,neutral or dissatisfied +48102,108700,Male,Loyal Customer,57,Personal Travel,Eco Plus,577,4,4,4,3,3,4,3,3,4,2,5,5,4,3,33,28.0,neutral or dissatisfied +48103,121222,Male,Loyal Customer,44,Business travel,Business,2075,1,1,1,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +48104,59397,Male,Loyal Customer,48,Personal Travel,Eco,2556,1,4,1,4,1,1,1,3,3,2,2,1,2,1,626,604.0,neutral or dissatisfied +48105,33153,Female,Loyal Customer,14,Personal Travel,Eco,102,2,1,2,3,3,2,3,3,1,5,3,3,3,3,2,2.0,neutral or dissatisfied +48106,80639,Male,Loyal Customer,31,Personal Travel,Eco,282,1,4,3,4,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +48107,127579,Male,Loyal Customer,40,Business travel,Business,1773,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +48108,32872,Female,Loyal Customer,18,Personal Travel,Eco,216,2,2,2,4,5,2,5,5,2,5,2,1,4,5,0,0.0,neutral or dissatisfied +48109,119993,Female,Loyal Customer,35,Personal Travel,Business,328,3,0,3,2,5,4,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +48110,86917,Female,Loyal Customer,47,Personal Travel,Eco,341,2,5,2,1,3,4,4,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +48111,85837,Male,Loyal Customer,26,Personal Travel,Eco,526,1,2,1,4,2,1,2,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +48112,123633,Female,disloyal Customer,36,Business travel,Business,214,3,3,3,4,5,3,1,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +48113,59285,Male,disloyal Customer,22,Business travel,Business,3365,0,5,0,1,0,3,3,1,1,2,2,3,3,3,6,0.0,satisfied +48114,92603,Male,Loyal Customer,42,Business travel,Eco,718,4,3,3,3,4,4,4,4,4,5,2,3,5,4,1,0.0,satisfied +48115,2865,Male,disloyal Customer,44,Business travel,Eco,491,5,0,5,4,4,5,4,4,3,3,3,2,4,4,0,27.0,satisfied +48116,59175,Male,Loyal Customer,62,Personal Travel,Eco Plus,1846,2,4,2,1,1,2,1,1,3,4,5,1,5,1,12,3.0,neutral or dissatisfied +48117,35283,Male,Loyal Customer,47,Business travel,Business,3892,1,1,1,1,1,5,1,5,5,5,5,3,5,2,4,0.0,satisfied +48118,109039,Female,disloyal Customer,21,Business travel,Eco,488,4,0,4,4,1,4,1,1,5,2,5,5,5,1,34,31.0,satisfied +48119,60110,Male,disloyal Customer,26,Business travel,Business,1012,0,0,0,3,3,2,5,3,4,4,5,5,5,3,11,10.0,satisfied +48120,956,Female,disloyal Customer,21,Business travel,Eco,89,1,4,0,3,4,0,4,4,2,2,3,3,3,4,0,0.0,neutral or dissatisfied +48121,112607,Male,Loyal Customer,55,Business travel,Business,1796,5,5,5,5,3,1,2,4,4,4,4,1,4,5,0,0.0,satisfied +48122,118790,Male,Loyal Customer,35,Personal Travel,Eco,370,2,4,2,2,4,2,5,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +48123,38254,Female,Loyal Customer,56,Business travel,Eco,1133,2,5,5,5,3,4,5,2,2,2,2,4,2,1,11,0.0,satisfied +48124,89650,Female,Loyal Customer,49,Business travel,Business,2243,1,3,3,3,1,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +48125,21784,Male,Loyal Customer,53,Business travel,Business,3402,3,3,3,3,3,5,4,4,4,4,4,4,4,3,20,10.0,satisfied +48126,35258,Male,Loyal Customer,56,Business travel,Business,1634,3,3,1,3,4,2,1,4,4,4,4,5,4,5,0,0.0,satisfied +48127,77787,Female,Loyal Customer,31,Personal Travel,Eco,689,5,3,5,4,5,5,5,5,2,2,3,1,3,5,0,2.0,satisfied +48128,4722,Male,disloyal Customer,40,Business travel,Business,888,2,2,2,3,2,2,5,2,2,2,3,1,4,2,21,4.0,neutral or dissatisfied +48129,49588,Male,Loyal Customer,31,Business travel,Business,2460,4,4,4,4,5,5,3,5,4,4,5,5,1,5,12,12.0,satisfied +48130,17963,Male,Loyal Customer,51,Personal Travel,Eco,460,4,1,4,4,5,4,5,5,1,3,3,2,3,5,0,0.0,satisfied +48131,79186,Male,Loyal Customer,62,Personal Travel,Eco,2422,2,4,2,3,2,4,4,3,3,3,5,4,3,4,0,4.0,neutral or dissatisfied +48132,29953,Male,disloyal Customer,26,Business travel,Eco,253,3,1,3,3,5,3,5,5,3,3,3,1,4,5,73,72.0,neutral or dissatisfied +48133,125675,Female,disloyal Customer,21,Business travel,Eco,814,3,3,3,3,2,3,2,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +48134,41601,Female,Loyal Customer,33,Personal Travel,Eco,1464,3,5,3,1,2,3,5,2,5,5,4,4,4,2,24,19.0,neutral or dissatisfied +48135,49620,Female,disloyal Customer,33,Business travel,Eco,373,1,0,1,2,2,1,3,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +48136,97736,Male,disloyal Customer,35,Business travel,Business,787,3,3,3,4,4,3,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +48137,97052,Female,Loyal Customer,60,Business travel,Business,3752,1,1,1,1,5,5,4,4,4,4,4,4,4,5,18,24.0,satisfied +48138,119474,Male,disloyal Customer,47,Business travel,Business,857,2,2,2,5,5,2,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +48139,17499,Male,Loyal Customer,35,Business travel,Business,3477,4,1,3,1,1,3,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +48140,38674,Female,Loyal Customer,26,Personal Travel,Eco,2611,3,4,3,4,5,3,5,5,1,1,4,2,3,5,10,0.0,neutral or dissatisfied +48141,41131,Male,Loyal Customer,46,Business travel,Eco,224,5,4,4,4,4,5,4,4,3,5,5,1,5,4,0,0.0,satisfied +48142,40680,Female,disloyal Customer,22,Business travel,Eco,588,0,0,0,4,3,0,3,3,5,3,5,1,2,3,0,11.0,satisfied +48143,54194,Male,Loyal Customer,52,Personal Travel,Eco,1400,3,2,3,3,3,3,3,3,3,5,3,4,4,3,38,3.0,neutral or dissatisfied +48144,126014,Male,Loyal Customer,55,Business travel,Business,3210,5,5,4,5,4,5,4,4,4,4,4,5,4,3,6,5.0,satisfied +48145,98901,Female,Loyal Customer,70,Personal Travel,Business,543,1,5,1,4,5,4,5,4,4,1,4,5,4,5,30,20.0,neutral or dissatisfied +48146,26635,Female,disloyal Customer,58,Business travel,Eco,270,2,1,2,3,3,2,1,3,2,2,4,2,4,3,0,25.0,neutral or dissatisfied +48147,4998,Female,disloyal Customer,21,Business travel,Eco,502,3,1,2,2,2,2,2,2,3,5,3,3,3,2,43,49.0,neutral or dissatisfied +48148,110669,Male,Loyal Customer,29,Business travel,Business,2283,3,4,4,4,3,3,3,3,3,1,1,4,2,3,44,37.0,neutral or dissatisfied +48149,22367,Male,Loyal Customer,34,Business travel,Business,1507,2,4,4,4,1,3,4,3,3,2,2,4,3,2,8,11.0,neutral or dissatisfied +48150,62016,Female,Loyal Customer,36,Business travel,Business,2475,1,3,3,3,1,4,3,1,1,1,1,1,1,1,10,0.0,neutral or dissatisfied +48151,30856,Female,Loyal Customer,59,Business travel,Business,1703,1,1,2,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +48152,106678,Female,disloyal Customer,38,Business travel,Eco,451,2,0,2,4,5,2,5,5,1,3,3,3,4,5,40,39.0,neutral or dissatisfied +48153,29596,Male,Loyal Customer,56,Business travel,Eco,1448,4,1,1,1,4,4,4,4,3,3,2,2,4,4,0,4.0,satisfied +48154,125014,Female,Loyal Customer,36,Personal Travel,Eco,184,2,5,2,1,1,2,1,1,4,2,5,4,5,1,0,14.0,neutral or dissatisfied +48155,14198,Female,disloyal Customer,24,Business travel,Eco,620,4,0,4,3,4,4,4,4,3,5,3,1,2,4,0,7.0,satisfied +48156,77725,Male,disloyal Customer,62,Business travel,Eco,813,2,2,2,3,5,2,5,5,3,1,3,4,2,5,0,0.0,neutral or dissatisfied +48157,49868,Female,disloyal Customer,25,Business travel,Eco,266,2,2,2,3,4,2,4,4,2,5,4,4,3,4,0,6.0,neutral or dissatisfied +48158,90945,Female,Loyal Customer,46,Business travel,Eco,194,2,1,3,1,5,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +48159,129606,Male,Loyal Customer,43,Business travel,Business,1863,0,0,0,1,5,4,5,1,1,1,1,5,1,5,0,0.0,satisfied +48160,127395,Female,Loyal Customer,57,Business travel,Business,868,3,3,3,3,5,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +48161,71133,Male,Loyal Customer,60,Personal Travel,Eco,1739,3,4,3,3,2,3,2,2,4,2,4,3,4,2,39,20.0,neutral or dissatisfied +48162,84464,Male,Loyal Customer,45,Business travel,Business,2968,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +48163,127748,Female,Loyal Customer,36,Business travel,Eco,255,2,1,1,1,2,2,2,2,3,5,4,1,3,2,0,0.0,neutral or dissatisfied +48164,106060,Male,Loyal Customer,68,Personal Travel,Eco,903,1,4,1,5,4,1,4,4,3,1,5,1,2,4,2,0.0,neutral or dissatisfied +48165,99494,Male,Loyal Customer,41,Personal Travel,Eco,283,2,4,2,3,4,2,4,4,3,4,4,3,5,4,15,9.0,neutral or dissatisfied +48166,126119,Male,disloyal Customer,24,Business travel,Eco,590,4,0,4,2,4,4,2,4,5,5,5,3,4,4,0,1.0,satisfied +48167,27716,Female,disloyal Customer,38,Business travel,Business,1048,3,3,3,3,3,3,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +48168,87934,Female,disloyal Customer,12,Business travel,Business,581,3,1,3,4,2,3,2,2,3,1,3,1,4,2,0,12.0,neutral or dissatisfied +48169,85348,Male,disloyal Customer,22,Business travel,Eco,813,2,2,2,3,5,2,4,5,3,2,4,3,4,5,5,0.0,neutral or dissatisfied +48170,89629,Female,Loyal Customer,39,Business travel,Business,2554,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +48171,42451,Female,disloyal Customer,57,Business travel,Eco,466,3,0,3,5,4,3,4,4,5,3,3,3,2,4,0,0.0,neutral or dissatisfied +48172,88790,Female,Loyal Customer,23,Business travel,Business,2996,1,1,1,1,2,2,2,2,5,3,4,4,4,2,1,0.0,satisfied +48173,119000,Male,Loyal Customer,43,Business travel,Business,479,4,3,4,4,5,5,5,5,3,4,5,5,5,5,272,267.0,satisfied +48174,43053,Male,Loyal Customer,55,Business travel,Business,3381,1,1,1,1,2,1,5,3,3,3,3,4,3,1,8,0.0,satisfied +48175,108528,Male,disloyal Customer,45,Business travel,Eco,649,1,4,1,3,5,1,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +48176,92080,Male,Loyal Customer,49,Business travel,Business,1535,1,1,1,1,2,4,5,4,4,4,4,5,4,3,8,0.0,satisfied +48177,15122,Male,Loyal Customer,33,Business travel,Business,2939,4,4,4,4,5,5,5,5,2,4,2,1,3,5,2,0.0,satisfied +48178,22599,Female,Loyal Customer,41,Business travel,Business,300,1,2,2,2,1,3,3,1,1,1,1,1,1,1,26,15.0,neutral or dissatisfied +48179,86925,Female,Loyal Customer,58,Personal Travel,Eco,341,2,4,2,1,3,5,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +48180,56397,Male,Loyal Customer,58,Business travel,Business,3052,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,17.0,satisfied +48181,102750,Male,Loyal Customer,44,Business travel,Business,2335,5,5,5,5,2,4,4,4,4,4,4,4,4,3,6,0.0,satisfied +48182,103594,Male,Loyal Customer,44,Personal Travel,Eco,451,1,5,4,3,4,4,3,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +48183,107317,Female,Loyal Customer,47,Business travel,Business,2425,4,4,4,4,4,4,4,5,5,5,5,3,5,5,73,70.0,satisfied +48184,36143,Female,Loyal Customer,42,Business travel,Eco Plus,1562,4,3,3,3,5,2,4,4,4,4,4,2,4,5,13,15.0,satisfied +48185,84439,Male,Loyal Customer,10,Business travel,Eco Plus,606,4,5,5,5,4,4,1,4,3,1,3,1,3,4,6,5.0,neutral or dissatisfied +48186,67518,Female,disloyal Customer,37,Business travel,Business,1235,4,4,4,1,5,4,5,5,5,3,4,5,5,5,1,4.0,satisfied +48187,93151,Male,Loyal Customer,32,Business travel,Business,2768,4,1,1,1,4,3,4,4,4,4,4,3,3,4,45,30.0,neutral or dissatisfied +48188,83140,Male,Loyal Customer,65,Personal Travel,Eco,957,2,3,2,3,5,2,5,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +48189,23075,Female,Loyal Customer,38,Business travel,Eco,1174,4,4,4,4,4,4,4,4,1,1,1,2,3,4,30,14.0,satisfied +48190,122880,Male,Loyal Customer,12,Personal Travel,Eco,226,2,5,2,3,1,2,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +48191,110041,Male,Loyal Customer,60,Business travel,Business,2173,1,1,1,1,5,4,5,5,5,5,5,5,5,3,123,121.0,satisfied +48192,96322,Male,Loyal Customer,46,Business travel,Business,2562,3,2,3,3,4,4,5,4,4,4,4,3,4,4,16,8.0,satisfied +48193,23638,Male,Loyal Customer,11,Personal Travel,Eco,911,2,2,3,2,4,3,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +48194,8769,Male,Loyal Customer,51,Business travel,Business,2908,2,2,2,2,2,5,4,4,4,4,4,5,4,5,3,0.0,satisfied +48195,117274,Male,Loyal Customer,51,Business travel,Business,2228,0,0,0,4,4,4,4,1,1,1,1,3,1,5,1,0.0,satisfied +48196,14598,Female,Loyal Customer,23,Personal Travel,Eco,986,3,5,3,3,5,3,5,5,3,5,4,4,5,5,0,8.0,neutral or dissatisfied +48197,76346,Female,Loyal Customer,46,Business travel,Business,1851,4,4,4,4,2,3,5,4,4,4,4,5,4,4,22,21.0,satisfied +48198,106994,Male,Loyal Customer,51,Personal Travel,Eco,937,2,5,2,1,1,2,1,1,3,5,4,4,5,1,27,4.0,neutral or dissatisfied +48199,117650,Male,Loyal Customer,38,Personal Travel,Eco Plus,872,1,5,1,4,5,1,5,5,4,4,5,4,4,5,1,13.0,neutral or dissatisfied +48200,71419,Male,disloyal Customer,11,Business travel,Eco,867,2,2,2,1,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +48201,31514,Female,Loyal Customer,34,Business travel,Business,862,1,1,1,1,3,1,4,3,3,3,3,3,3,1,0,0.0,satisfied +48202,16036,Male,Loyal Customer,51,Business travel,Eco Plus,853,4,4,4,4,3,4,3,3,3,2,4,2,5,3,0,0.0,satisfied +48203,62127,Female,Loyal Customer,49,Business travel,Business,2565,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +48204,85127,Female,Loyal Customer,42,Business travel,Business,2038,2,5,2,2,3,4,5,4,4,4,4,3,4,3,10,0.0,satisfied +48205,95879,Female,Loyal Customer,45,Business travel,Eco,580,1,5,5,5,3,4,4,1,1,1,1,4,1,2,23,16.0,neutral or dissatisfied +48206,77079,Female,Loyal Customer,21,Personal Travel,Eco,991,3,4,3,5,5,3,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +48207,114651,Male,Loyal Customer,58,Business travel,Business,1842,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +48208,88001,Female,Loyal Customer,40,Business travel,Business,3698,1,1,1,1,3,4,4,5,5,5,5,3,5,3,121,123.0,satisfied +48209,19763,Male,Loyal Customer,46,Business travel,Eco Plus,462,4,3,3,3,4,4,4,4,5,3,1,2,3,4,29,33.0,satisfied +48210,89434,Female,Loyal Customer,69,Personal Travel,Eco,134,3,3,0,1,3,3,5,1,1,0,1,2,1,3,15,6.0,neutral or dissatisfied +48211,101077,Female,disloyal Customer,28,Business travel,Business,583,4,4,4,3,3,4,3,3,4,4,4,4,5,3,55,54.0,satisfied +48212,91926,Female,Loyal Customer,56,Business travel,Business,2475,1,1,1,1,2,4,4,5,5,5,5,3,5,5,3,0.0,satisfied +48213,119256,Male,Loyal Customer,43,Business travel,Business,214,1,1,1,1,5,4,3,4,4,4,1,3,4,2,39,14.0,neutral or dissatisfied +48214,92090,Male,disloyal Customer,27,Business travel,Eco,766,1,1,1,3,2,1,2,2,3,3,3,2,2,2,0,0.0,neutral or dissatisfied +48215,25155,Female,Loyal Customer,40,Business travel,Eco,2106,4,4,4,4,4,4,4,5,1,4,5,4,1,4,143,145.0,satisfied +48216,2006,Female,Loyal Customer,57,Personal Travel,Eco Plus,383,1,2,1,3,2,3,3,4,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +48217,86512,Female,Loyal Customer,34,Personal Travel,Eco,762,1,3,1,5,3,1,3,3,5,5,5,4,1,3,47,31.0,neutral or dissatisfied +48218,60352,Female,Loyal Customer,7,Personal Travel,Eco,836,4,5,4,2,3,4,3,3,3,2,4,5,5,3,0,0.0,satisfied +48219,58363,Female,Loyal Customer,66,Personal Travel,Eco,599,3,3,3,3,3,2,2,3,2,4,4,2,2,2,158,153.0,neutral or dissatisfied +48220,64776,Male,Loyal Customer,77,Business travel,Business,1629,3,4,3,3,3,2,2,3,3,3,3,3,3,4,0,6.0,neutral or dissatisfied +48221,123639,Female,disloyal Customer,21,Business travel,Eco,214,4,0,4,1,4,4,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +48222,10662,Male,Loyal Customer,55,Business travel,Business,2601,3,1,3,1,1,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +48223,11008,Female,Loyal Customer,67,Business travel,Business,2699,2,2,2,2,3,3,3,3,3,3,2,2,3,3,47,38.0,neutral or dissatisfied +48224,49466,Female,disloyal Customer,49,Business travel,Eco,308,4,4,4,3,2,4,2,2,4,4,3,5,2,2,0,14.0,satisfied +48225,127007,Male,Loyal Customer,59,Business travel,Business,2659,5,5,5,5,4,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +48226,76956,Male,Loyal Customer,42,Business travel,Business,1990,2,2,2,2,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +48227,65316,Male,Loyal Customer,10,Personal Travel,Business,432,0,5,0,3,3,0,4,3,4,2,5,3,5,3,0,0.0,satisfied +48228,17105,Female,Loyal Customer,68,Personal Travel,Eco,416,1,1,1,3,1,2,2,3,3,1,3,4,3,3,108,131.0,neutral or dissatisfied +48229,23424,Female,Loyal Customer,51,Business travel,Eco,1154,5,1,1,1,1,1,3,5,5,5,5,1,5,2,66,67.0,satisfied +48230,78764,Female,Loyal Customer,35,Business travel,Business,3428,4,2,2,2,4,3,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +48231,111452,Female,Loyal Customer,39,Business travel,Business,1024,4,5,5,5,2,4,4,4,4,4,4,1,4,3,37,45.0,neutral or dissatisfied +48232,75912,Male,Loyal Customer,16,Personal Travel,Eco,603,3,4,3,3,5,3,5,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +48233,41854,Male,Loyal Customer,32,Business travel,Eco,483,5,3,3,3,5,5,5,5,3,4,1,2,3,5,0,0.0,satisfied +48234,97281,Female,Loyal Customer,68,Personal Travel,Business,347,3,5,3,5,3,4,4,1,1,3,1,3,1,3,1,0.0,neutral or dissatisfied +48235,71297,Female,disloyal Customer,26,Business travel,Business,1514,1,0,1,2,5,1,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +48236,95181,Male,Loyal Customer,42,Personal Travel,Eco,239,2,5,2,3,1,2,1,1,3,4,5,5,5,1,61,61.0,neutral or dissatisfied +48237,6488,Male,Loyal Customer,29,Business travel,Business,3256,4,3,2,2,4,4,4,4,4,1,3,2,4,4,31,44.0,neutral or dissatisfied +48238,49144,Female,Loyal Customer,53,Business travel,Business,421,2,3,2,2,4,1,5,4,4,4,4,4,4,4,1,0.0,satisfied +48239,111183,Male,Loyal Customer,45,Business travel,Business,1546,1,1,1,1,4,4,5,4,4,4,4,5,4,4,17,15.0,satisfied +48240,32221,Male,Loyal Customer,51,Business travel,Eco,163,2,2,2,2,2,2,2,2,1,2,3,2,3,2,0,0.0,neutral or dissatisfied +48241,96546,Female,Loyal Customer,34,Personal Travel,Eco,302,2,5,2,2,2,2,2,2,5,2,5,5,5,2,7,3.0,neutral or dissatisfied +48242,110239,Female,Loyal Customer,52,Business travel,Eco,1011,4,4,4,4,3,2,2,5,5,4,5,2,5,4,0,0.0,neutral or dissatisfied +48243,65800,Male,Loyal Customer,31,Business travel,Business,1389,3,5,3,3,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +48244,26498,Male,Loyal Customer,32,Business travel,Eco,829,5,2,2,2,5,4,5,5,4,1,2,1,2,5,4,0.0,neutral or dissatisfied +48245,2989,Male,Loyal Customer,43,Business travel,Business,1793,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +48246,18755,Female,Loyal Customer,36,Personal Travel,Eco,1167,4,5,5,2,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +48247,38265,Female,disloyal Customer,29,Business travel,Eco,1133,3,3,3,2,4,3,4,4,2,3,2,2,3,4,74,70.0,neutral or dissatisfied +48248,16623,Male,Loyal Customer,29,Personal Travel,Eco,1008,4,5,4,3,1,4,1,1,5,5,1,3,3,1,37,38.0,neutral or dissatisfied +48249,47248,Female,Loyal Customer,20,Business travel,Business,590,4,4,4,4,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +48250,56833,Female,Loyal Customer,66,Personal Travel,Eco,1725,1,5,1,3,3,5,4,3,3,1,4,4,3,4,77,83.0,neutral or dissatisfied +48251,79750,Male,Loyal Customer,65,Personal Travel,Eco Plus,760,1,4,1,3,5,1,5,5,3,3,4,3,4,5,72,121.0,neutral or dissatisfied +48252,111000,Female,Loyal Customer,53,Business travel,Business,2022,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,4.0,satisfied +48253,77058,Male,Loyal Customer,56,Personal Travel,Business,991,2,5,3,4,3,4,5,1,1,3,1,4,1,4,0,8.0,neutral or dissatisfied +48254,41869,Male,Loyal Customer,27,Personal Travel,Eco,483,3,5,3,4,1,3,1,1,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +48255,129850,Female,Loyal Customer,12,Personal Travel,Eco,447,2,4,2,3,3,2,3,3,4,3,3,1,3,3,0,0.0,neutral or dissatisfied +48256,1731,Female,Loyal Customer,38,Business travel,Business,327,2,2,2,2,5,3,4,5,5,5,5,4,5,2,34,40.0,satisfied +48257,122248,Male,Loyal Customer,63,Business travel,Eco,144,1,2,2,2,1,1,1,1,1,4,3,4,3,1,16,20.0,neutral or dissatisfied +48258,80281,Female,Loyal Customer,49,Business travel,Business,2049,5,5,5,5,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +48259,67074,Female,disloyal Customer,20,Business travel,Eco,1119,3,3,3,4,5,3,5,5,1,3,4,4,4,5,10,51.0,neutral or dissatisfied +48260,83295,Male,Loyal Customer,26,Personal Travel,Eco,1979,3,4,3,4,3,3,3,3,2,2,2,3,2,3,43,30.0,neutral or dissatisfied +48261,42009,Female,Loyal Customer,49,Business travel,Business,116,4,4,4,4,2,1,3,4,4,4,5,2,4,4,0,2.0,satisfied +48262,17252,Male,disloyal Customer,55,Business travel,Eco,692,3,3,3,3,1,3,1,1,3,1,4,4,3,1,37,41.0,neutral or dissatisfied +48263,2779,Male,Loyal Customer,52,Business travel,Business,764,3,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0.0,satisfied +48264,36070,Female,disloyal Customer,26,Business travel,Eco,399,4,1,4,4,3,4,3,3,3,5,4,1,4,3,21,3.0,neutral or dissatisfied +48265,26784,Female,Loyal Customer,23,Personal Travel,Eco,1199,2,3,3,4,5,3,5,5,4,2,1,4,3,5,2,0.0,neutral or dissatisfied +48266,23497,Female,Loyal Customer,47,Personal Travel,Business,349,2,3,2,3,3,2,3,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +48267,41233,Female,Loyal Customer,17,Personal Travel,Eco,744,2,1,2,4,1,2,1,1,2,2,3,2,4,1,39,34.0,neutral or dissatisfied +48268,55947,Male,disloyal Customer,20,Business travel,Business,1620,5,0,5,3,4,5,4,4,3,2,4,3,4,4,1,0.0,satisfied +48269,23481,Male,Loyal Customer,10,Personal Travel,Eco,576,4,4,4,2,3,4,3,3,3,2,4,4,5,3,0,2.0,neutral or dissatisfied +48270,5841,Male,Loyal Customer,33,Business travel,Eco Plus,177,1,3,3,3,1,1,1,1,1,4,4,2,4,1,34,55.0,neutral or dissatisfied +48271,56183,Male,Loyal Customer,62,Personal Travel,Eco,1400,1,3,1,5,2,1,3,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +48272,30510,Female,Loyal Customer,70,Personal Travel,Eco,1620,3,4,3,4,5,3,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +48273,97809,Female,Loyal Customer,39,Business travel,Business,480,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +48274,48187,Female,Loyal Customer,17,Business travel,Eco,192,0,3,1,3,2,1,2,2,5,4,1,1,2,2,0,0.0,satisfied +48275,59754,Male,disloyal Customer,29,Business travel,Business,1025,2,2,2,2,5,2,5,5,5,5,5,4,5,5,8,2.0,neutral or dissatisfied +48276,107129,Female,Loyal Customer,35,Personal Travel,Eco,842,2,5,2,4,5,2,2,5,1,2,5,2,1,5,14,7.0,neutral or dissatisfied +48277,34360,Female,Loyal Customer,33,Business travel,Business,2423,2,4,1,4,1,3,3,2,2,2,2,2,2,3,9,2.0,neutral or dissatisfied +48278,49707,Male,Loyal Customer,42,Business travel,Business,199,5,5,5,5,4,2,1,4,4,4,5,5,4,3,0,0.0,satisfied +48279,20032,Male,Loyal Customer,25,Business travel,Eco,607,2,2,2,2,2,2,3,2,3,2,4,2,3,2,13,16.0,neutral or dissatisfied +48280,100365,Female,Loyal Customer,33,Personal Travel,Eco,1053,1,5,1,4,1,1,1,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +48281,33160,Male,Loyal Customer,60,Personal Travel,Eco,84,2,4,2,3,3,2,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +48282,96588,Female,Loyal Customer,53,Business travel,Business,1896,1,5,5,5,2,3,3,1,1,1,1,3,1,1,5,7.0,neutral or dissatisfied +48283,59971,Female,Loyal Customer,44,Business travel,Eco,665,5,2,2,2,3,2,4,5,5,5,5,3,5,4,0,0.0,satisfied +48284,78707,Female,Loyal Customer,41,Business travel,Business,2377,1,2,2,2,4,2,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +48285,46441,Male,Loyal Customer,38,Personal Travel,Eco,1304,3,4,3,3,3,3,3,3,3,3,5,4,5,3,1,0.0,neutral or dissatisfied +48286,25557,Female,Loyal Customer,40,Business travel,Business,696,3,3,3,3,2,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +48287,55149,Female,Loyal Customer,52,Personal Travel,Eco,1346,2,4,2,4,2,2,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +48288,111718,Male,Loyal Customer,61,Personal Travel,Eco,541,3,5,3,1,4,3,2,4,5,4,4,3,5,4,15,4.0,neutral or dissatisfied +48289,75225,Male,disloyal Customer,15,Business travel,Eco,1846,3,3,3,3,5,3,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +48290,43119,Female,Loyal Customer,38,Personal Travel,Eco,391,2,5,2,4,5,2,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +48291,63009,Female,disloyal Customer,32,Business travel,Eco,967,1,1,1,4,2,1,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +48292,14418,Male,Loyal Customer,52,Business travel,Business,2484,3,3,3,3,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +48293,121808,Male,Loyal Customer,49,Business travel,Business,366,3,3,3,3,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +48294,56285,Male,Loyal Customer,25,Business travel,Business,2227,3,5,5,5,3,3,3,3,2,5,2,4,3,3,0,0.0,neutral or dissatisfied +48295,1712,Female,Loyal Customer,53,Business travel,Business,2566,5,5,5,5,5,5,5,5,5,5,5,4,5,5,56,64.0,satisfied +48296,113235,Female,disloyal Customer,63,Business travel,Business,236,2,2,2,3,2,2,2,2,5,3,5,4,4,2,34,30.0,neutral or dissatisfied +48297,73233,Female,Loyal Customer,9,Personal Travel,Eco,946,2,3,2,3,3,2,3,3,2,4,4,1,4,3,0,0.0,neutral or dissatisfied +48298,102210,Female,Loyal Customer,38,Business travel,Business,3173,1,1,1,1,4,4,5,4,4,4,4,5,4,3,1,0.0,satisfied +48299,120221,Female,Loyal Customer,53,Business travel,Business,2824,1,3,3,3,3,3,3,1,1,2,1,2,1,2,0,3.0,neutral or dissatisfied +48300,32610,Female,disloyal Customer,22,Business travel,Eco,216,5,4,5,3,3,5,3,3,1,3,1,3,2,3,12,11.0,satisfied +48301,73677,Female,disloyal Customer,25,Business travel,Eco,192,2,2,2,2,4,2,4,4,2,1,3,1,3,4,21,23.0,neutral or dissatisfied +48302,9842,Female,Loyal Customer,52,Business travel,Business,3994,1,1,1,1,2,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +48303,80015,Male,Loyal Customer,69,Personal Travel,Eco,1005,1,4,1,4,4,1,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +48304,43144,Male,Loyal Customer,54,Personal Travel,Eco Plus,236,1,3,1,3,1,1,1,1,3,2,2,1,3,1,0,0.0,neutral or dissatisfied +48305,23703,Male,Loyal Customer,64,Business travel,Eco,212,5,5,5,5,5,5,5,5,2,3,1,5,3,5,0,0.0,satisfied +48306,13584,Female,Loyal Customer,26,Personal Travel,Eco,106,3,4,0,4,4,0,4,4,4,5,4,4,5,4,47,36.0,neutral or dissatisfied +48307,102235,Female,Loyal Customer,48,Business travel,Business,3080,4,2,2,2,1,3,2,4,4,4,4,3,4,3,23,11.0,neutral or dissatisfied +48308,51714,Female,Loyal Customer,28,Personal Travel,Eco,370,4,4,4,2,1,4,1,1,4,1,5,4,5,1,0,0.0,satisfied +48309,127116,Male,Loyal Customer,25,Personal Travel,Eco,338,1,4,1,3,4,1,4,4,1,4,4,4,3,4,0,0.0,neutral or dissatisfied +48310,70087,Female,Loyal Customer,44,Business travel,Business,550,3,3,3,3,2,5,4,5,5,5,5,3,5,5,15,0.0,satisfied +48311,45662,Male,Loyal Customer,34,Business travel,Eco Plus,391,4,2,2,2,4,4,4,4,1,4,4,2,2,4,20,24.0,satisfied +48312,86251,Female,Loyal Customer,47,Personal Travel,Eco,164,1,4,0,1,3,5,5,1,1,0,1,1,1,5,71,75.0,neutral or dissatisfied +48313,61635,Female,Loyal Customer,44,Business travel,Business,1379,5,5,5,5,3,5,4,3,3,2,3,4,3,5,4,0.0,satisfied +48314,109541,Male,Loyal Customer,61,Personal Travel,Eco,861,4,5,4,2,1,4,1,1,4,3,4,4,5,1,0,1.0,neutral or dissatisfied +48315,97858,Female,disloyal Customer,28,Business travel,Business,612,1,1,1,3,5,1,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +48316,44006,Male,Loyal Customer,36,Business travel,Eco,397,3,3,3,3,3,3,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +48317,83861,Male,Loyal Customer,10,Personal Travel,Eco,425,3,4,3,2,5,3,5,5,3,4,5,4,4,5,15,17.0,neutral or dissatisfied +48318,59600,Male,disloyal Customer,27,Business travel,Business,854,5,5,5,2,1,5,1,1,5,3,5,5,4,1,10,15.0,satisfied +48319,31099,Male,Loyal Customer,25,Personal Travel,Eco,1014,3,4,3,4,2,3,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +48320,14129,Male,Loyal Customer,39,Business travel,Eco,413,3,1,1,1,3,3,3,3,3,3,3,3,2,3,0,14.0,neutral or dissatisfied +48321,35010,Male,Loyal Customer,45,Business travel,Eco Plus,1182,5,4,4,4,5,5,5,5,1,2,2,4,3,5,0,0.0,satisfied +48322,98322,Male,disloyal Customer,25,Business travel,Eco,774,2,2,2,2,1,2,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +48323,23098,Female,Loyal Customer,32,Business travel,Business,300,0,0,0,2,4,4,4,4,3,2,5,4,4,4,0,1.0,satisfied +48324,66285,Male,Loyal Customer,61,Personal Travel,Eco Plus,550,4,3,4,4,3,4,3,3,1,3,3,4,4,3,0,11.0,satisfied +48325,66618,Female,disloyal Customer,25,Business travel,Business,802,1,4,1,4,5,1,4,5,4,5,4,5,4,5,10,0.0,neutral or dissatisfied +48326,59949,Female,Loyal Customer,56,Business travel,Eco,1068,3,5,1,1,3,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +48327,91570,Female,Loyal Customer,58,Business travel,Business,2220,4,4,4,4,4,5,5,5,5,5,5,3,5,5,79,72.0,satisfied +48328,95560,Male,Loyal Customer,59,Personal Travel,Eco Plus,187,1,1,1,4,1,1,4,1,1,4,4,2,4,1,25,44.0,neutral or dissatisfied +48329,54250,Female,Loyal Customer,60,Business travel,Business,3573,3,3,3,3,4,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +48330,72176,Male,Loyal Customer,51,Business travel,Business,594,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +48331,50380,Female,disloyal Customer,45,Business travel,Eco,109,3,2,3,3,3,3,2,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +48332,46452,Male,Loyal Customer,60,Business travel,Business,2712,4,4,4,4,5,4,4,4,4,4,5,3,4,5,0,5.0,satisfied +48333,119838,Male,Loyal Customer,51,Business travel,Eco,912,1,0,0,4,1,1,1,1,1,4,3,4,4,1,9,23.0,neutral or dissatisfied +48334,78022,Female,Loyal Customer,33,Business travel,Eco,227,5,2,2,2,5,5,5,5,5,1,5,2,3,5,0,0.0,satisfied +48335,113557,Female,Loyal Customer,27,Business travel,Business,236,2,4,4,4,2,2,2,2,2,1,3,2,3,2,9,12.0,neutral or dissatisfied +48336,65687,Female,Loyal Customer,22,Business travel,Business,1724,5,5,4,5,4,4,4,4,5,3,4,3,4,4,2,0.0,satisfied +48337,101278,Male,Loyal Customer,54,Business travel,Business,444,1,1,1,1,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +48338,63558,Male,Loyal Customer,31,Personal Travel,Eco Plus,1009,2,5,2,5,2,2,2,2,2,1,1,4,1,2,9,6.0,neutral or dissatisfied +48339,77182,Male,disloyal Customer,38,Business travel,Business,290,2,2,2,4,1,2,1,1,3,2,5,3,4,1,0,5.0,neutral or dissatisfied +48340,17093,Female,Loyal Customer,56,Business travel,Eco,416,5,1,1,1,1,4,4,5,5,5,5,2,5,5,0,0.0,satisfied +48341,17950,Female,Loyal Customer,35,Business travel,Business,460,1,1,1,1,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +48342,8849,Female,Loyal Customer,51,Personal Travel,Eco,1371,3,5,3,1,2,5,5,5,5,3,5,4,5,4,30,21.0,neutral or dissatisfied +48343,43429,Female,Loyal Customer,57,Business travel,Eco,748,3,4,4,4,4,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +48344,94221,Male,disloyal Customer,25,Business travel,Business,441,5,4,4,3,3,4,3,3,4,4,4,3,5,3,65,61.0,satisfied +48345,31693,Male,Loyal Customer,40,Business travel,Business,1992,4,2,2,2,2,4,4,4,4,4,4,1,4,1,87,84.0,neutral or dissatisfied +48346,94805,Female,Loyal Customer,71,Business travel,Eco,239,3,5,4,5,1,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +48347,22392,Female,Loyal Customer,59,Business travel,Eco,143,2,4,4,4,5,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +48348,55063,Male,Loyal Customer,42,Business travel,Business,1635,1,1,1,1,5,5,4,4,4,4,4,4,4,3,7,0.0,satisfied +48349,47862,Male,Loyal Customer,34,Business travel,Business,2527,2,3,4,3,3,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +48350,98876,Male,disloyal Customer,18,Business travel,Eco,991,2,2,2,3,1,2,1,1,1,4,3,1,3,1,21,17.0,neutral or dissatisfied +48351,18593,Female,disloyal Customer,37,Business travel,Eco,383,3,4,4,3,2,4,2,2,1,4,3,4,3,2,0,14.0,neutral or dissatisfied +48352,35929,Male,Loyal Customer,27,Business travel,Business,2381,1,4,4,4,1,1,1,1,1,2,4,1,4,1,4,0.0,neutral or dissatisfied +48353,21446,Female,Loyal Customer,47,Business travel,Eco,331,3,5,5,5,4,3,3,3,3,3,3,1,3,3,97,96.0,neutral or dissatisfied +48354,100632,Female,Loyal Customer,28,Business travel,Business,3138,3,3,3,3,4,4,4,4,4,3,5,4,5,4,7,5.0,satisfied +48355,80489,Male,Loyal Customer,44,Business travel,Business,1749,3,2,2,2,2,2,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +48356,5267,Female,Loyal Customer,68,Personal Travel,Eco,295,3,4,5,2,3,4,5,4,4,5,4,5,4,3,8,11.0,neutral or dissatisfied +48357,128157,Male,Loyal Customer,47,Business travel,Business,1788,1,1,1,1,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +48358,88919,Male,Loyal Customer,16,Personal Travel,Eco,859,5,1,5,2,3,1,3,3,1,4,2,2,2,3,0,0.0,satisfied +48359,37070,Female,disloyal Customer,23,Business travel,Eco,1072,2,2,2,4,4,2,3,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +48360,87803,Male,disloyal Customer,57,Business travel,Business,214,1,1,1,2,3,1,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +48361,47102,Female,Loyal Customer,49,Business travel,Eco Plus,438,5,1,1,1,5,1,1,5,5,5,5,1,5,1,0,0.0,satisfied +48362,51925,Female,Loyal Customer,37,Business travel,Eco Plus,507,4,3,3,3,4,4,4,4,2,2,4,1,3,4,0,0.0,neutral or dissatisfied +48363,83345,Male,Loyal Customer,11,Personal Travel,Eco,187,1,5,1,5,4,1,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +48364,55460,Female,Loyal Customer,22,Personal Travel,Business,1825,3,4,4,3,5,4,5,5,3,3,4,4,5,5,18,0.0,neutral or dissatisfied +48365,100573,Female,Loyal Customer,53,Business travel,Business,486,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +48366,20123,Male,Loyal Customer,49,Personal Travel,Eco,466,1,3,3,2,5,3,5,5,1,5,2,3,1,5,0,0.0,neutral or dissatisfied +48367,27448,Female,disloyal Customer,22,Business travel,Eco,1050,1,1,1,3,3,1,3,3,2,2,2,2,2,3,0,1.0,neutral or dissatisfied +48368,50289,Male,Loyal Customer,47,Business travel,Eco,308,4,1,1,1,4,4,4,4,3,4,1,3,2,4,0,1.0,satisfied +48369,16734,Male,Loyal Customer,71,Business travel,Business,767,1,5,5,5,2,3,4,1,1,1,1,3,1,3,5,0.0,neutral or dissatisfied +48370,48480,Female,Loyal Customer,23,Business travel,Business,776,1,1,1,1,4,4,4,4,5,2,1,3,1,4,1,2.0,satisfied +48371,89044,Male,Loyal Customer,47,Business travel,Business,2116,4,4,4,4,2,4,5,4,4,4,4,5,4,4,24,12.0,satisfied +48372,18161,Male,Loyal Customer,58,Personal Travel,Eco,430,2,5,2,3,4,2,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +48373,34145,Female,disloyal Customer,20,Business travel,Eco,1046,1,0,0,3,2,0,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +48374,65801,Female,disloyal Customer,25,Business travel,Business,1389,3,0,3,1,1,3,1,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +48375,27254,Female,disloyal Customer,23,Business travel,Eco,954,2,2,2,2,2,2,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +48376,108290,Male,disloyal Customer,14,Business travel,Eco,866,2,3,3,3,3,2,3,3,4,5,1,1,3,3,5,22.0,neutral or dissatisfied +48377,122951,Female,disloyal Customer,24,Business travel,Eco,328,3,4,3,4,1,3,1,1,3,5,5,5,4,1,27,8.0,neutral or dissatisfied +48378,121925,Male,disloyal Customer,27,Business travel,Business,449,0,0,0,5,2,0,5,2,3,3,4,4,4,2,0,2.0,satisfied +48379,7070,Male,disloyal Customer,50,Business travel,Business,157,2,2,2,3,2,2,2,2,4,4,4,4,4,2,4,15.0,neutral or dissatisfied +48380,104649,Male,Loyal Customer,64,Personal Travel,Eco,1754,2,5,2,3,1,2,1,1,1,5,2,2,3,1,0,0.0,neutral or dissatisfied +48381,43808,Female,Loyal Customer,51,Business travel,Business,76,3,3,3,3,5,5,5,4,4,4,5,5,4,5,6,6.0,satisfied +48382,12083,Female,Loyal Customer,8,Personal Travel,Eco Plus,376,1,5,1,1,5,1,5,5,5,2,4,3,4,5,1,0.0,neutral or dissatisfied +48383,75475,Female,Loyal Customer,13,Personal Travel,Eco,2342,4,1,4,3,3,4,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +48384,18349,Male,Loyal Customer,45,Business travel,Eco,200,1,3,3,3,1,1,1,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +48385,35451,Male,Loyal Customer,8,Personal Travel,Eco,1056,2,3,2,3,4,2,4,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +48386,74827,Female,Loyal Customer,55,Personal Travel,Eco Plus,1205,2,2,2,3,2,4,4,3,3,2,5,1,3,2,0,0.0,neutral or dissatisfied +48387,45166,Female,disloyal Customer,22,Business travel,Eco,174,2,2,2,3,5,2,5,5,2,4,3,2,4,5,17,60.0,neutral or dissatisfied +48388,100075,Female,Loyal Customer,34,Business travel,Eco Plus,289,2,4,3,3,2,2,2,2,4,1,4,3,3,2,0,0.0,neutral or dissatisfied +48389,53090,Male,Loyal Customer,39,Business travel,Eco Plus,2327,5,2,2,2,5,5,5,5,5,4,3,1,3,5,16,0.0,satisfied +48390,103388,Male,disloyal Customer,23,Business travel,Eco,237,2,5,2,3,2,2,2,2,4,4,4,5,5,2,1,0.0,neutral or dissatisfied +48391,56839,Male,Loyal Customer,67,Personal Travel,Eco Plus,1605,3,5,3,3,2,3,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +48392,43907,Female,Loyal Customer,36,Personal Travel,Eco,114,2,4,2,4,2,1,1,2,1,5,2,1,3,1,178,163.0,neutral or dissatisfied +48393,6462,Female,disloyal Customer,20,Business travel,Eco Plus,296,3,1,3,3,4,3,2,4,2,1,4,3,3,4,0,0.0,neutral or dissatisfied +48394,120628,Male,Loyal Customer,41,Business travel,Business,1785,2,2,2,2,4,5,5,5,5,5,5,4,5,5,12,9.0,satisfied +48395,41171,Female,disloyal Customer,39,Business travel,Business,216,4,4,4,3,4,4,1,4,1,1,4,4,4,4,89,89.0,neutral or dissatisfied +48396,22241,Female,Loyal Customer,58,Business travel,Business,208,2,5,5,5,5,3,2,3,3,3,2,3,3,2,0,0.0,neutral or dissatisfied +48397,10006,Female,Loyal Customer,57,Personal Travel,Eco,457,3,2,3,3,4,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +48398,112311,Female,Loyal Customer,37,Business travel,Business,1876,1,5,1,1,2,5,5,2,2,2,2,5,2,4,16,12.0,satisfied +48399,27884,Male,Loyal Customer,49,Business travel,Business,2329,3,1,1,1,2,4,3,3,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +48400,85041,Female,Loyal Customer,45,Business travel,Business,813,1,1,1,1,2,5,4,5,5,5,5,4,5,4,15,10.0,satisfied +48401,93785,Male,Loyal Customer,16,Personal Travel,Business,1259,2,5,2,4,5,2,5,5,4,5,3,4,5,5,0,0.0,neutral or dissatisfied +48402,127048,Female,Loyal Customer,48,Business travel,Business,370,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +48403,73319,Male,disloyal Customer,23,Business travel,Eco,1012,3,3,3,3,3,3,2,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +48404,121326,Male,Loyal Customer,10,Personal Travel,Eco,1009,0,2,0,3,4,0,4,4,1,3,4,2,3,4,0,0.0,satisfied +48405,99668,Female,Loyal Customer,69,Personal Travel,Eco,1050,2,5,3,5,3,5,4,2,2,3,4,3,2,5,0,0.0,neutral or dissatisfied +48406,92344,Female,Loyal Customer,47,Business travel,Business,2615,4,5,2,2,3,4,4,2,4,4,4,4,1,4,214,190.0,neutral or dissatisfied +48407,124583,Male,Loyal Customer,55,Business travel,Business,1629,4,4,4,4,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +48408,122585,Male,Loyal Customer,44,Business travel,Business,728,1,1,1,1,3,5,5,4,4,4,4,4,4,5,35,15.0,satisfied +48409,94069,Male,disloyal Customer,45,Business travel,Business,441,1,1,1,4,3,1,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +48410,29004,Male,Loyal Customer,52,Business travel,Business,2342,1,1,1,1,4,5,4,4,4,5,4,1,4,4,1,0.0,satisfied +48411,110374,Male,Loyal Customer,35,Business travel,Business,883,3,3,5,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +48412,40740,Female,Loyal Customer,37,Business travel,Business,2300,1,0,0,4,2,4,3,1,1,0,1,1,1,1,0,0.0,neutral or dissatisfied +48413,106266,Male,Loyal Customer,39,Business travel,Business,1869,2,2,2,2,1,4,5,5,5,5,5,2,5,1,2,0.0,satisfied +48414,8101,Female,Loyal Customer,49,Business travel,Business,125,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +48415,74929,Female,Loyal Customer,42,Business travel,Business,2475,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +48416,86712,Male,Loyal Customer,36,Business travel,Business,1747,2,4,4,4,5,3,2,2,2,3,2,2,2,1,35,19.0,neutral or dissatisfied +48417,61173,Male,Loyal Customer,48,Business travel,Business,862,3,3,4,3,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +48418,85099,Male,disloyal Customer,22,Business travel,Business,696,4,0,4,3,1,4,1,1,4,5,4,5,5,1,27,16.0,satisfied +48419,116958,Female,Loyal Customer,31,Business travel,Eco,325,2,2,3,2,2,2,2,2,2,5,3,3,3,2,2,0.0,neutral or dissatisfied +48420,43541,Female,Loyal Customer,66,Personal Travel,Eco,643,2,5,2,4,4,5,5,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +48421,100916,Female,Loyal Customer,54,Business travel,Eco Plus,377,4,2,2,2,5,4,4,4,4,4,4,1,4,2,7,16.0,neutral or dissatisfied +48422,45913,Female,Loyal Customer,42,Business travel,Eco,563,4,1,1,1,2,3,1,4,4,4,4,5,4,3,3,0.0,satisfied +48423,110085,Male,Loyal Customer,38,Business travel,Business,2868,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +48424,85852,Female,Loyal Customer,28,Business travel,Eco Plus,666,3,4,1,4,3,3,3,3,4,2,3,3,4,3,15,8.0,neutral or dissatisfied +48425,6632,Male,Loyal Customer,60,Personal Travel,Eco,719,1,4,1,2,2,1,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +48426,16347,Male,Loyal Customer,17,Business travel,Eco,160,4,5,5,5,4,4,3,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +48427,66573,Female,Loyal Customer,47,Business travel,Business,624,2,2,4,2,4,5,4,5,5,5,5,4,5,3,39,36.0,satisfied +48428,63607,Female,disloyal Customer,41,Business travel,Eco,1440,3,3,3,3,3,3,3,3,3,5,4,2,3,3,9,0.0,neutral or dissatisfied +48429,82535,Male,Loyal Customer,43,Business travel,Business,629,4,4,4,4,5,4,4,4,4,4,4,3,4,4,63,50.0,satisfied +48430,85919,Female,Loyal Customer,35,Personal Travel,Eco,674,2,4,2,3,4,2,4,4,4,3,5,4,4,4,130,119.0,neutral or dissatisfied +48431,27608,Female,Loyal Customer,54,Personal Travel,Eco,937,4,4,4,4,5,5,5,2,2,4,4,5,2,5,0,0.0,neutral or dissatisfied +48432,128556,Male,Loyal Customer,15,Business travel,Business,1800,1,1,1,1,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +48433,55166,Male,Loyal Customer,67,Personal Travel,Eco,1608,2,5,3,2,2,3,2,2,5,5,5,4,5,2,0,1.0,neutral or dissatisfied +48434,16198,Male,Loyal Customer,65,Personal Travel,Eco,199,2,4,0,2,4,0,4,4,3,3,4,3,5,4,0,12.0,neutral or dissatisfied +48435,85449,Female,Loyal Customer,26,Business travel,Business,1607,3,1,3,1,2,2,3,2,4,5,3,4,3,2,8,9.0,neutral or dissatisfied +48436,87163,Male,Loyal Customer,44,Business travel,Business,946,1,1,1,1,5,5,4,5,5,5,5,3,5,3,28,2.0,satisfied +48437,91058,Male,Loyal Customer,57,Personal Travel,Eco,270,3,5,0,3,4,0,5,4,4,3,5,5,4,4,28,18.0,neutral or dissatisfied +48438,109401,Male,Loyal Customer,24,Business travel,Eco Plus,1189,2,2,5,2,2,2,1,2,1,3,3,3,3,2,8,0.0,neutral or dissatisfied +48439,80242,Male,Loyal Customer,40,Business travel,Business,2214,4,4,4,4,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +48440,75596,Male,Loyal Customer,27,Personal Travel,Eco,337,5,5,5,5,3,5,3,3,5,2,5,3,4,3,1,0.0,satisfied +48441,128353,Female,Loyal Customer,41,Business travel,Business,325,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +48442,102592,Female,Loyal Customer,36,Business travel,Eco Plus,258,5,4,4,4,5,5,5,5,5,2,5,5,5,5,12,9.0,satisfied +48443,11385,Male,Loyal Customer,42,Business travel,Business,3866,4,4,4,4,3,5,4,5,5,5,5,5,5,5,44,41.0,satisfied +48444,103658,Male,Loyal Customer,39,Business travel,Business,2336,3,3,3,3,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +48445,38473,Female,disloyal Customer,21,Business travel,Eco,846,3,3,3,2,1,3,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +48446,104627,Male,Loyal Customer,47,Business travel,Business,861,2,2,3,2,2,3,3,2,2,2,2,4,2,3,0,7.0,neutral or dissatisfied +48447,6119,Female,Loyal Customer,46,Business travel,Business,2407,3,3,3,3,2,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +48448,103605,Male,Loyal Customer,64,Business travel,Business,3607,2,1,1,1,3,4,3,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +48449,63232,Female,Loyal Customer,49,Business travel,Business,2119,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +48450,22575,Male,Loyal Customer,51,Business travel,Business,3358,0,0,0,3,2,5,3,4,4,4,4,1,4,3,31,24.0,satisfied +48451,67655,Male,Loyal Customer,41,Business travel,Business,1205,3,4,4,4,2,4,4,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +48452,103454,Female,Loyal Customer,37,Business travel,Business,1752,3,3,3,3,1,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +48453,715,Male,Loyal Customer,35,Business travel,Business,3640,4,4,4,4,2,4,5,5,5,5,5,4,5,4,31,47.0,satisfied +48454,75833,Female,Loyal Customer,54,Business travel,Business,1440,4,4,4,4,3,4,4,4,4,4,4,3,4,4,12,0.0,satisfied +48455,114873,Male,Loyal Customer,51,Business travel,Business,373,5,5,5,5,3,4,5,5,5,5,5,3,5,3,1,9.0,satisfied +48456,5983,Male,Loyal Customer,35,Business travel,Business,2999,2,3,2,2,5,4,4,4,4,4,4,4,4,4,39,30.0,satisfied +48457,60399,Male,Loyal Customer,12,Personal Travel,Eco,1476,1,4,1,1,4,1,1,4,4,2,4,4,4,4,69,85.0,neutral or dissatisfied +48458,112061,Female,Loyal Customer,31,Business travel,Eco,1754,2,1,1,1,2,2,2,2,4,4,3,4,3,2,27,32.0,neutral or dissatisfied +48459,127993,Male,Loyal Customer,54,Business travel,Business,1488,3,3,3,3,5,5,5,5,5,5,5,4,5,3,1,6.0,satisfied +48460,5036,Male,Loyal Customer,36,Business travel,Business,3163,4,4,4,4,5,4,4,4,4,4,4,4,4,3,102,103.0,satisfied +48461,17155,Female,Loyal Customer,55,Business travel,Business,2375,3,3,3,3,5,3,4,3,3,2,3,2,3,1,0,4.0,neutral or dissatisfied +48462,122735,Male,disloyal Customer,29,Business travel,Eco,651,3,4,3,4,1,3,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +48463,103498,Female,Loyal Customer,31,Business travel,Business,1047,2,2,2,2,5,5,5,5,3,2,5,3,5,5,65,63.0,satisfied +48464,119535,Male,Loyal Customer,54,Personal Travel,Eco,814,4,2,4,3,4,4,4,4,2,2,4,2,3,4,0,16.0,neutral or dissatisfied +48465,31328,Male,Loyal Customer,42,Personal Travel,Eco,1123,1,5,2,3,5,2,3,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +48466,77052,Male,Loyal Customer,29,Personal Travel,Eco,920,2,4,2,2,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +48467,76980,Female,Loyal Customer,52,Personal Travel,Eco,1969,3,4,3,3,1,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +48468,19820,Female,Loyal Customer,62,Business travel,Eco,413,4,4,4,4,2,4,3,4,4,4,4,4,4,4,23,27.0,satisfied +48469,56888,Male,disloyal Customer,22,Business travel,Business,2565,4,0,4,3,4,1,1,4,2,3,4,1,5,1,0,11.0,satisfied +48470,79457,Male,Loyal Customer,27,Business travel,Business,2251,3,3,3,3,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +48471,36827,Male,Loyal Customer,23,Business travel,Business,2167,4,4,4,4,4,4,4,4,5,3,2,1,5,4,0,0.0,satisfied +48472,100398,Female,Loyal Customer,43,Business travel,Business,1052,2,2,2,2,2,4,5,5,5,5,5,4,5,5,77,119.0,satisfied +48473,21040,Male,Loyal Customer,38,Business travel,Business,1836,5,5,2,5,2,5,1,5,5,5,5,3,5,2,0,0.0,satisfied +48474,26041,Male,Loyal Customer,40,Business travel,Business,432,5,5,1,5,5,1,5,4,4,4,4,4,4,1,6,0.0,satisfied +48475,103428,Female,Loyal Customer,61,Personal Travel,Eco,237,3,5,3,3,4,4,4,5,5,3,1,3,5,5,16,6.0,neutral or dissatisfied +48476,108752,Male,Loyal Customer,41,Business travel,Business,581,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +48477,13433,Female,disloyal Customer,45,Business travel,Eco,409,3,5,3,2,3,3,3,3,1,4,5,3,2,3,0,0.0,neutral or dissatisfied +48478,113717,Female,Loyal Customer,49,Personal Travel,Eco,386,3,5,3,1,4,5,5,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +48479,124285,Male,Loyal Customer,54,Business travel,Business,2671,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +48480,85034,Male,Loyal Customer,66,Personal Travel,Eco,1590,1,5,1,3,2,1,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +48481,49653,Female,Loyal Customer,51,Business travel,Eco,109,5,4,4,4,1,1,3,5,5,5,5,3,5,5,0,0.0,satisfied +48482,123514,Male,Loyal Customer,27,Personal Travel,Eco,2296,3,4,2,1,2,5,5,3,3,3,4,5,3,5,132,167.0,neutral or dissatisfied +48483,79347,Female,Loyal Customer,34,Personal Travel,Eco,1020,0,4,0,3,4,0,4,4,4,3,1,2,5,4,4,0.0,satisfied +48484,43341,Male,Loyal Customer,23,Business travel,Business,3402,4,4,4,4,4,4,4,4,5,2,5,4,2,4,0,0.0,satisfied +48485,16260,Male,Loyal Customer,20,Business travel,Business,3387,2,2,2,2,5,5,5,5,1,5,5,1,4,5,13,12.0,satisfied +48486,21129,Male,Loyal Customer,61,Personal Travel,Eco,227,3,4,0,3,4,0,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +48487,112663,Male,Loyal Customer,39,Business travel,Business,2429,3,3,4,3,2,5,4,5,5,4,5,5,5,5,27,21.0,satisfied +48488,1136,Male,Loyal Customer,28,Personal Travel,Eco,89,3,4,3,3,2,3,2,2,3,2,2,1,3,2,0,0.0,neutral or dissatisfied +48489,10426,Female,Loyal Customer,52,Business travel,Business,3089,0,0,0,1,2,4,4,5,5,2,2,4,5,4,15,18.0,satisfied +48490,89565,Male,Loyal Customer,26,Business travel,Business,1076,1,1,2,1,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +48491,41928,Male,Loyal Customer,8,Personal Travel,Eco,129,1,1,1,3,4,1,4,4,4,3,5,2,4,4,4,9.0,neutral or dissatisfied +48492,117398,Male,Loyal Customer,45,Business travel,Business,3130,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,3.0,satisfied +48493,75154,Female,Loyal Customer,58,Business travel,Business,1829,3,3,3,3,5,3,4,5,5,5,5,3,5,3,0,0.0,satisfied +48494,107172,Female,disloyal Customer,27,Business travel,Business,402,1,1,1,4,2,1,2,2,3,3,5,3,4,2,14,0.0,neutral or dissatisfied +48495,57641,Female,Loyal Customer,44,Business travel,Business,1767,0,5,0,1,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +48496,106033,Female,Loyal Customer,29,Personal Travel,Eco,682,3,5,3,3,4,3,4,4,4,2,5,3,4,4,11,16.0,neutral or dissatisfied +48497,21448,Female,Loyal Customer,49,Business travel,Business,3351,2,2,2,2,3,2,1,5,5,5,5,4,5,2,0,0.0,satisfied +48498,92132,Male,Loyal Customer,33,Personal Travel,Eco,1532,1,1,1,2,5,1,5,5,1,1,2,3,2,5,0,0.0,neutral or dissatisfied +48499,2823,Female,Loyal Customer,41,Business travel,Business,409,3,3,3,3,5,5,5,5,5,5,5,3,5,3,0,28.0,satisfied +48500,70672,Male,Loyal Customer,35,Business travel,Business,2978,4,4,4,4,4,3,4,4,4,4,4,4,4,4,13,12.0,neutral or dissatisfied +48501,39946,Male,Loyal Customer,48,Personal Travel,Eco,1086,3,2,3,4,2,3,2,2,3,5,3,1,4,2,12,0.0,neutral or dissatisfied +48502,116524,Male,Loyal Customer,40,Personal Travel,Eco,358,2,5,2,4,2,3,3,4,4,4,5,3,5,3,162,151.0,neutral or dissatisfied +48503,114730,Female,Loyal Customer,39,Business travel,Business,333,4,4,4,4,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +48504,12069,Male,Loyal Customer,30,Personal Travel,Eco,376,3,5,3,2,5,3,5,5,4,4,4,5,4,5,17,17.0,neutral or dissatisfied +48505,110414,Female,Loyal Customer,15,Business travel,Business,3580,1,3,3,3,1,1,1,1,3,1,3,4,4,1,8,9.0,neutral or dissatisfied +48506,40965,Male,disloyal Customer,10,Business travel,Eco,601,4,5,4,2,2,4,2,2,5,3,3,5,1,2,0,0.0,satisfied +48507,110619,Female,Loyal Customer,43,Business travel,Business,719,3,5,5,5,4,3,3,2,1,3,2,3,1,3,130,134.0,neutral or dissatisfied +48508,64441,Male,Loyal Customer,41,Business travel,Business,989,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +48509,59001,Female,disloyal Customer,40,Business travel,Business,908,5,5,5,2,3,5,2,3,5,5,4,3,4,3,12,28.0,satisfied +48510,54291,Male,disloyal Customer,20,Business travel,Eco,1075,4,4,4,2,2,4,2,2,2,1,2,2,1,2,0,0.0,neutral or dissatisfied +48511,66383,Female,disloyal Customer,30,Business travel,Business,1562,3,3,3,3,5,3,1,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +48512,99525,Female,disloyal Customer,25,Business travel,Business,528,5,0,5,2,2,5,2,2,5,2,5,4,4,2,0,0.0,satisfied +48513,19847,Male,disloyal Customer,24,Business travel,Eco,585,3,3,3,3,3,2,4,2,4,4,3,4,4,4,147,155.0,neutral or dissatisfied +48514,70749,Male,Loyal Customer,47,Business travel,Business,675,5,5,5,5,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +48515,14100,Female,Loyal Customer,69,Personal Travel,Eco,399,3,2,3,3,2,3,2,3,3,3,3,2,3,4,8,12.0,neutral or dissatisfied +48516,8279,Female,Loyal Customer,10,Personal Travel,Eco,125,2,4,2,4,3,2,3,3,2,5,4,4,4,3,17,,neutral or dissatisfied +48517,40408,Male,Loyal Customer,41,Business travel,Eco,188,5,5,5,5,5,5,5,5,2,5,5,3,4,5,0,0.0,satisfied +48518,86193,Female,Loyal Customer,18,Business travel,Business,2872,5,5,5,5,5,5,5,5,4,2,4,4,4,5,0,0.0,satisfied +48519,104083,Male,Loyal Customer,47,Personal Travel,Eco,666,2,4,2,3,2,2,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +48520,123577,Female,Loyal Customer,58,Business travel,Business,273,5,5,5,5,1,2,5,5,5,5,5,1,5,4,0,0.0,satisfied +48521,41976,Female,Loyal Customer,9,Personal Travel,Eco,525,1,5,1,2,3,1,3,3,3,4,4,3,2,3,0,0.0,neutral or dissatisfied +48522,128483,Male,Loyal Customer,17,Personal Travel,Eco,647,3,4,3,5,5,3,5,5,5,1,5,5,4,5,0,1.0,neutral or dissatisfied +48523,75627,Male,Loyal Customer,56,Business travel,Business,337,0,0,0,2,2,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +48524,95523,Female,disloyal Customer,41,Business travel,Business,189,3,3,3,4,5,3,5,5,1,1,3,3,3,5,0,0.0,neutral or dissatisfied +48525,66185,Female,Loyal Customer,25,Business travel,Business,2585,5,5,5,5,4,4,4,4,4,3,5,4,5,4,6,0.0,satisfied +48526,101994,Male,Loyal Customer,44,Personal Travel,Eco,628,2,5,2,3,5,2,4,5,5,5,5,3,4,5,0,34.0,neutral or dissatisfied +48527,90709,Female,Loyal Customer,44,Business travel,Eco,270,3,3,3,3,1,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +48528,113240,Female,Loyal Customer,22,Personal Travel,Business,258,2,3,2,5,5,2,3,5,1,5,1,4,4,5,8,11.0,neutral or dissatisfied +48529,90860,Male,Loyal Customer,62,Business travel,Business,2932,4,4,4,4,2,4,3,4,4,4,4,2,4,4,1,6.0,neutral or dissatisfied +48530,8123,Female,disloyal Customer,23,Business travel,Eco,125,2,2,2,3,4,2,4,4,3,5,3,2,3,4,0,1.0,neutral or dissatisfied +48531,116967,Male,disloyal Customer,26,Business travel,Business,621,5,5,5,3,3,5,3,3,5,5,4,5,5,3,68,54.0,satisfied +48532,11186,Female,Loyal Customer,15,Personal Travel,Eco,458,3,4,3,3,2,3,2,2,5,5,5,4,3,2,8,1.0,neutral or dissatisfied +48533,78693,Female,Loyal Customer,46,Business travel,Business,3425,1,1,5,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +48534,80437,Male,Loyal Customer,47,Personal Travel,Eco,2248,2,5,2,3,5,2,5,5,1,3,4,5,4,5,4,0.0,neutral or dissatisfied +48535,26871,Male,Loyal Customer,26,Business travel,Eco,2329,5,5,5,5,5,4,5,5,1,5,5,2,1,5,0,0.0,satisfied +48536,51963,Male,Loyal Customer,50,Business travel,Eco,347,4,3,3,3,4,4,4,4,2,5,4,4,5,4,0,1.0,satisfied +48537,118551,Male,Loyal Customer,47,Business travel,Business,1718,2,2,2,2,3,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +48538,103772,Female,Loyal Customer,15,Personal Travel,Business,1072,2,5,2,4,5,2,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +48539,41711,Female,disloyal Customer,28,Business travel,Eco,1404,1,1,1,5,5,1,5,5,4,5,4,3,2,5,0,0.0,neutral or dissatisfied +48540,106110,Female,disloyal Customer,29,Business travel,Business,302,2,2,2,4,2,2,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +48541,97509,Female,Loyal Customer,71,Business travel,Eco Plus,670,2,2,2,2,2,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +48542,90567,Female,Loyal Customer,42,Business travel,Business,2034,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +48543,111421,Female,Loyal Customer,51,Business travel,Business,2423,3,3,1,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +48544,119746,Male,Loyal Customer,7,Personal Travel,Eco,1303,3,4,3,4,4,3,2,4,4,4,3,5,4,4,2,0.0,neutral or dissatisfied +48545,54271,Female,Loyal Customer,34,Personal Travel,Eco,1222,1,5,1,1,3,1,3,3,1,5,1,1,5,3,0,0.0,neutral or dissatisfied +48546,28223,Male,Loyal Customer,8,Personal Travel,Eco Plus,834,1,5,1,4,3,1,3,3,5,4,4,4,5,3,0,21.0,neutral or dissatisfied +48547,88336,Female,disloyal Customer,21,Business travel,Eco,581,4,0,4,2,5,4,5,5,4,4,5,5,4,5,0,2.0,neutral or dissatisfied +48548,60521,Female,Loyal Customer,44,Personal Travel,Eco,862,3,5,3,5,5,5,4,3,3,3,3,5,3,3,12,9.0,neutral or dissatisfied +48549,7226,Male,Loyal Customer,44,Business travel,Business,116,4,1,1,1,4,3,4,1,1,2,4,4,1,4,0,2.0,neutral or dissatisfied +48550,71703,Female,Loyal Customer,34,Business travel,Eco Plus,1144,5,4,4,4,5,4,5,5,1,2,1,2,4,5,0,0.0,satisfied +48551,35809,Female,Loyal Customer,33,Business travel,Business,937,5,5,5,5,5,4,5,5,5,5,5,4,5,2,0,0.0,satisfied +48552,34561,Male,Loyal Customer,50,Business travel,Eco,1617,4,2,5,5,3,4,3,3,4,4,5,5,3,3,0,0.0,satisfied +48553,58223,Female,Loyal Customer,17,Personal Travel,Eco,925,2,3,2,4,3,2,5,3,2,3,4,5,5,3,0,0.0,neutral or dissatisfied +48554,23912,Female,disloyal Customer,38,Business travel,Eco,189,3,0,3,3,1,3,1,1,1,5,4,5,5,1,0,2.0,neutral or dissatisfied +48555,9734,Male,Loyal Customer,26,Personal Travel,Eco,926,2,5,2,1,2,5,5,4,5,4,4,5,3,5,138,144.0,neutral or dissatisfied +48556,122756,Female,Loyal Customer,54,Personal Travel,Eco,651,4,4,4,2,4,1,1,1,1,4,1,3,1,1,0,0.0,neutral or dissatisfied +48557,216,Female,Loyal Customer,35,Personal Travel,Eco,213,0,3,0,4,3,0,3,3,4,3,4,3,4,3,0,2.0,satisfied +48558,17474,Male,disloyal Customer,26,Business travel,Eco,241,2,2,2,3,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +48559,99052,Female,Loyal Customer,44,Business travel,Business,181,3,3,3,3,3,4,4,5,5,5,4,3,5,4,4,3.0,satisfied +48560,112519,Female,Loyal Customer,48,Personal Travel,Eco,957,2,5,3,4,3,5,5,1,1,3,1,5,1,4,35,25.0,neutral or dissatisfied +48561,55333,Male,Loyal Customer,22,Personal Travel,Eco,1325,3,5,3,2,3,3,3,4,2,5,4,3,3,3,97,143.0,neutral or dissatisfied +48562,26432,Male,Loyal Customer,32,Business travel,Business,3771,1,1,1,1,2,2,2,2,4,2,2,5,2,2,0,0.0,satisfied +48563,51754,Female,Loyal Customer,10,Personal Travel,Eco,493,3,5,3,3,3,3,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +48564,51311,Female,Loyal Customer,52,Business travel,Eco Plus,363,2,2,2,2,5,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +48565,95172,Female,Loyal Customer,30,Personal Travel,Eco,528,1,5,2,2,2,2,2,2,5,1,5,4,4,2,0,0.0,neutral or dissatisfied +48566,37290,Male,Loyal Customer,31,Business travel,Business,1671,4,4,5,4,4,4,4,4,5,2,4,5,5,4,16,44.0,satisfied +48567,111041,Male,disloyal Customer,21,Business travel,Eco,268,2,2,2,4,5,2,5,5,2,3,3,4,4,5,13,13.0,neutral or dissatisfied +48568,38718,Female,Loyal Customer,36,Personal Travel,Eco Plus,2342,3,3,3,1,5,3,5,5,3,2,3,2,1,5,58,36.0,neutral or dissatisfied +48569,25005,Female,Loyal Customer,43,Personal Travel,Eco,692,1,3,0,4,5,3,4,1,1,0,1,3,1,3,0,0.0,neutral or dissatisfied +48570,120575,Male,Loyal Customer,69,Personal Travel,Eco Plus,2176,2,2,2,3,4,2,4,4,3,4,4,2,3,4,58,89.0,neutral or dissatisfied +48571,85298,Female,Loyal Customer,50,Personal Travel,Eco,689,3,2,3,4,3,4,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +48572,99678,Female,Loyal Customer,43,Business travel,Business,442,4,4,2,4,5,5,4,4,4,5,4,5,4,3,2,4.0,satisfied +48573,71859,Male,disloyal Customer,37,Business travel,Eco,244,3,5,3,4,3,3,3,3,5,3,3,1,4,3,3,0.0,neutral or dissatisfied +48574,52627,Female,Loyal Customer,32,Business travel,Business,2416,5,5,5,5,4,4,5,4,2,5,3,3,2,4,0,3.0,satisfied +48575,27160,Female,disloyal Customer,21,Business travel,Eco,785,4,4,4,3,4,3,3,4,2,3,2,3,3,3,0,0.0,neutral or dissatisfied +48576,50756,Female,Loyal Customer,52,Personal Travel,Eco,77,4,5,0,4,4,5,5,4,4,0,4,4,4,4,8,5.0,neutral or dissatisfied +48577,22350,Female,disloyal Customer,39,Business travel,Eco,143,4,4,4,2,1,4,1,1,2,5,2,5,1,1,2,0.0,satisfied +48578,99207,Male,Loyal Customer,51,Business travel,Eco Plus,583,2,3,1,3,2,2,2,2,2,3,4,4,3,2,3,0.0,neutral or dissatisfied +48579,2182,Female,Loyal Customer,44,Business travel,Eco,624,3,1,1,1,4,1,1,2,2,3,2,3,2,3,0,11.0,neutral or dissatisfied +48580,14840,Male,Loyal Customer,45,Business travel,Business,2587,4,4,2,4,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +48581,16778,Male,Loyal Customer,22,Personal Travel,Eco,642,2,5,2,2,1,2,1,1,4,2,5,5,5,1,0,3.0,neutral or dissatisfied +48582,120697,Female,Loyal Customer,62,Personal Travel,Eco,280,1,5,1,2,3,5,4,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +48583,112464,Female,disloyal Customer,21,Business travel,Business,548,5,0,5,2,2,5,2,2,3,3,4,2,4,2,0,0.0,satisfied +48584,108703,Male,Loyal Customer,41,Personal Travel,Business,425,2,2,3,3,3,3,3,1,1,3,1,4,1,4,26,11.0,neutral or dissatisfied +48585,70886,Female,Loyal Customer,30,Business travel,Business,1721,3,3,3,3,3,3,3,3,1,4,3,2,2,3,0,0.0,neutral or dissatisfied +48586,114507,Male,Loyal Customer,37,Business travel,Business,3869,0,0,0,3,3,5,5,2,2,5,5,5,2,3,0,0.0,satisfied +48587,92486,Female,Loyal Customer,55,Business travel,Eco,2092,1,3,4,4,1,4,4,2,2,1,2,1,2,3,36,10.0,neutral or dissatisfied +48588,19926,Female,Loyal Customer,17,Personal Travel,Eco,315,5,5,5,2,2,5,2,2,5,3,4,3,4,2,0,15.0,satisfied +48589,82304,Female,Loyal Customer,52,Business travel,Eco,986,2,1,1,1,4,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +48590,92067,Male,Loyal Customer,18,Business travel,Business,1589,3,3,1,3,2,2,2,2,3,2,3,5,5,2,2,0.0,satisfied +48591,5486,Female,Loyal Customer,8,Business travel,Business,910,4,4,4,4,4,4,4,4,2,1,4,3,4,4,0,19.0,neutral or dissatisfied +48592,15544,Female,Loyal Customer,52,Business travel,Business,296,4,4,4,4,4,5,5,4,2,5,5,5,4,5,151,225.0,satisfied +48593,53876,Female,Loyal Customer,49,Business travel,Eco,140,3,2,2,2,4,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +48594,88588,Female,Loyal Customer,41,Personal Travel,Eco,404,5,4,5,1,2,5,2,2,5,2,4,5,5,2,0,0.0,satisfied +48595,105582,Male,Loyal Customer,39,Personal Travel,Eco,577,2,4,2,1,1,2,1,1,4,3,4,5,4,1,15,40.0,neutral or dissatisfied +48596,10120,Female,Loyal Customer,27,Personal Travel,Eco,984,3,4,3,1,5,3,2,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +48597,8204,Male,Loyal Customer,48,Business travel,Eco,402,3,3,3,3,2,3,2,2,1,5,4,4,3,2,0,6.0,neutral or dissatisfied +48598,47991,Female,disloyal Customer,27,Business travel,Eco Plus,550,4,3,3,2,3,3,3,3,5,4,1,1,2,3,0,0.0,neutral or dissatisfied +48599,62544,Male,disloyal Customer,29,Business travel,Eco,1020,4,4,4,4,4,4,4,4,1,4,3,3,3,4,3,0.0,neutral or dissatisfied +48600,97359,Male,disloyal Customer,21,Business travel,Eco,620,4,1,4,4,5,4,5,5,4,3,3,2,4,5,8,23.0,neutral or dissatisfied +48601,96446,Male,Loyal Customer,48,Business travel,Business,302,0,0,0,4,3,4,4,2,2,2,2,5,2,4,0,2.0,satisfied +48602,84045,Male,Loyal Customer,31,Business travel,Business,757,2,2,2,2,2,2,2,2,4,2,5,4,4,2,3,0.0,satisfied +48603,26582,Female,disloyal Customer,41,Business travel,Eco,581,3,0,3,1,3,3,3,3,2,2,4,3,1,3,0,0.0,neutral or dissatisfied +48604,62942,Female,Loyal Customer,28,Business travel,Business,862,1,1,1,1,5,5,5,5,3,4,4,5,5,5,65,47.0,satisfied +48605,22224,Male,Loyal Customer,52,Business travel,Eco Plus,565,5,3,3,3,5,5,5,5,1,1,1,5,4,5,10,0.0,satisfied +48606,104119,Female,Loyal Customer,48,Business travel,Business,2205,3,3,3,3,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +48607,80215,Female,Loyal Customer,26,Business travel,Business,2153,1,1,5,1,5,5,5,5,3,4,3,5,5,5,22,20.0,satisfied +48608,15650,Female,disloyal Customer,23,Business travel,Eco,292,3,2,3,3,4,3,4,4,4,2,4,4,3,4,111,113.0,neutral or dissatisfied +48609,84266,Male,Loyal Customer,46,Business travel,Business,334,5,4,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +48610,79940,Female,Loyal Customer,19,Business travel,Business,1089,4,4,4,4,4,4,4,4,3,5,4,4,3,4,2,0.0,neutral or dissatisfied +48611,18495,Female,Loyal Customer,58,Business travel,Business,1917,0,0,0,2,4,3,1,3,3,3,3,2,3,2,0,16.0,satisfied +48612,14677,Male,Loyal Customer,66,Personal Travel,Eco,416,4,3,4,2,4,4,1,4,4,2,3,4,4,4,28,22.0,neutral or dissatisfied +48613,69246,Male,Loyal Customer,11,Business travel,Business,733,2,1,2,2,2,2,2,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +48614,104239,Male,Loyal Customer,28,Business travel,Business,2307,2,2,2,2,5,5,5,5,4,2,4,4,5,5,2,8.0,satisfied +48615,58882,Female,Loyal Customer,41,Business travel,Eco,888,3,3,3,3,3,3,3,3,2,1,4,2,3,3,13,0.0,neutral or dissatisfied +48616,85868,Male,Loyal Customer,46,Business travel,Business,2172,5,5,5,5,3,4,4,4,4,4,4,3,4,3,17,5.0,satisfied +48617,36745,Female,Loyal Customer,34,Personal Travel,Business,2704,4,1,4,4,4,1,5,3,5,2,4,5,4,5,0,0.0,neutral or dissatisfied +48618,74347,Female,Loyal Customer,15,Personal Travel,Business,1235,1,5,0,2,1,0,1,1,4,2,4,5,4,1,0,1.0,neutral or dissatisfied +48619,1396,Male,Loyal Customer,29,Personal Travel,Eco Plus,134,2,3,0,3,5,0,5,5,3,5,3,2,4,5,0,0.0,neutral or dissatisfied +48620,52386,Female,Loyal Customer,15,Personal Travel,Eco,261,3,1,3,1,2,3,2,2,4,4,2,2,2,2,0,0.0,neutral or dissatisfied +48621,24154,Male,disloyal Customer,33,Business travel,Eco,170,1,3,1,2,4,1,4,4,1,5,1,4,3,4,15,18.0,neutral or dissatisfied +48622,6144,Female,Loyal Customer,43,Business travel,Business,491,3,3,3,3,2,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +48623,120946,Male,disloyal Customer,25,Business travel,Business,951,4,0,4,3,3,4,3,3,3,3,4,3,4,3,1,0.0,satisfied +48624,66838,Female,Loyal Customer,36,Business travel,Eco,731,3,4,1,1,3,3,3,3,2,2,4,4,4,3,61,57.0,neutral or dissatisfied +48625,111970,Male,Loyal Customer,42,Business travel,Business,3375,2,2,2,2,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +48626,71532,Female,Loyal Customer,47,Business travel,Business,3024,4,4,4,4,3,4,5,5,5,5,5,4,5,5,18,8.0,satisfied +48627,100467,Female,Loyal Customer,35,Business travel,Business,580,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,6.0,satisfied +48628,52567,Female,Loyal Customer,39,Business travel,Business,119,4,4,4,4,5,3,2,5,5,5,3,3,5,2,0,0.0,satisfied +48629,8239,Female,Loyal Customer,44,Personal Travel,Eco,125,2,3,2,3,3,2,2,5,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +48630,91064,Female,Loyal Customer,33,Personal Travel,Eco,444,4,4,4,2,2,4,2,2,3,5,4,4,5,2,0,1.0,neutral or dissatisfied +48631,10192,Female,Loyal Customer,44,Business travel,Business,3578,2,5,2,2,4,5,4,4,4,4,4,3,4,3,14,4.0,satisfied +48632,88841,Female,Loyal Customer,63,Personal Travel,Eco Plus,270,2,5,2,2,5,5,4,4,4,2,4,5,4,4,3,0.0,neutral or dissatisfied +48633,1286,Male,Loyal Customer,11,Personal Travel,Eco,102,1,3,1,1,5,1,5,5,4,5,3,2,5,5,0,0.0,neutral or dissatisfied +48634,57190,Female,Loyal Customer,47,Personal Travel,Eco Plus,2227,5,4,5,3,2,4,5,3,3,5,3,3,3,3,0,1.0,satisfied +48635,67934,Female,Loyal Customer,37,Personal Travel,Eco,1188,2,2,2,3,2,2,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +48636,98363,Male,Loyal Customer,23,Business travel,Business,3612,3,2,2,2,3,3,3,3,2,2,4,2,4,3,39,39.0,neutral or dissatisfied +48637,60022,Male,Loyal Customer,37,Personal Travel,Eco,1023,3,4,3,5,5,3,4,5,4,2,2,5,5,5,0,0.0,neutral or dissatisfied +48638,98002,Female,Loyal Customer,18,Personal Travel,Eco Plus,616,1,4,1,1,1,2,2,3,3,5,4,2,3,2,199,196.0,neutral or dissatisfied +48639,102445,Male,Loyal Customer,32,Personal Travel,Eco,223,3,5,3,2,2,3,5,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +48640,47108,Female,Loyal Customer,34,Business travel,Business,1569,1,1,1,1,4,2,2,4,4,4,4,5,4,1,4,,satisfied +48641,103136,Female,Loyal Customer,29,Business travel,Eco Plus,546,4,3,3,3,4,4,4,4,3,4,4,4,4,4,58,60.0,neutral or dissatisfied +48642,91715,Female,Loyal Customer,30,Business travel,Business,2633,2,4,4,4,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +48643,69005,Female,disloyal Customer,49,Business travel,Business,1389,2,2,2,3,1,2,1,1,1,2,4,1,4,1,3,13.0,neutral or dissatisfied +48644,128067,Male,Loyal Customer,46,Business travel,Business,2917,1,1,1,1,5,5,5,3,5,3,5,5,4,5,4,9.0,satisfied +48645,122928,Female,Loyal Customer,40,Business travel,Business,3464,1,1,1,1,4,4,5,4,4,4,4,4,4,3,5,8.0,satisfied +48646,72189,Female,Loyal Customer,35,Business travel,Business,594,3,5,5,5,1,3,3,3,3,3,3,1,3,1,0,6.0,neutral or dissatisfied +48647,6523,Female,Loyal Customer,26,Personal Travel,Eco,599,2,0,3,1,3,3,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +48648,50362,Male,Loyal Customer,54,Business travel,Eco,77,2,1,4,4,3,2,3,3,2,5,4,4,4,3,4,6.0,neutral or dissatisfied +48649,30432,Male,Loyal Customer,22,Business travel,Business,483,2,2,3,2,4,4,4,4,4,3,2,4,3,4,0,0.0,satisfied +48650,16988,Male,Loyal Customer,44,Personal Travel,Eco,610,3,4,3,1,4,3,4,4,5,4,5,4,4,4,0,18.0,neutral or dissatisfied +48651,25613,Female,Loyal Customer,32,Business travel,Business,1574,4,4,4,4,4,4,4,4,2,2,5,2,2,4,49,41.0,satisfied +48652,18256,Male,Loyal Customer,55,Personal Travel,Eco,224,3,4,3,3,3,3,3,3,3,4,4,4,4,3,69,83.0,neutral or dissatisfied +48653,121721,Female,Loyal Customer,14,Personal Travel,Eco,683,3,4,3,1,5,3,5,5,2,4,2,4,1,5,8,9.0,neutral or dissatisfied +48654,52675,Female,Loyal Customer,42,Personal Travel,Eco,160,1,3,1,1,2,4,2,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +48655,129321,Female,Loyal Customer,57,Business travel,Business,2586,2,2,2,2,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +48656,76314,Male,Loyal Customer,29,Business travel,Business,2182,5,5,5,5,2,2,2,2,4,2,5,5,4,2,1,0.0,satisfied +48657,78714,Female,Loyal Customer,45,Business travel,Business,3575,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +48658,92772,Male,Loyal Customer,41,Business travel,Business,1671,4,4,4,4,4,3,5,2,2,2,2,5,2,5,13,1.0,satisfied +48659,86518,Male,Loyal Customer,62,Personal Travel,Eco,749,3,4,4,1,4,4,4,4,5,4,4,4,4,4,8,0.0,neutral or dissatisfied +48660,105474,Female,Loyal Customer,46,Business travel,Eco,495,3,3,3,3,1,3,3,3,3,3,3,4,3,3,41,76.0,neutral or dissatisfied +48661,102827,Male,Loyal Customer,39,Personal Travel,Eco Plus,342,3,4,3,2,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +48662,45668,Male,Loyal Customer,32,Personal Travel,Eco Plus,406,1,4,1,1,3,1,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +48663,28762,Female,Loyal Customer,31,Personal Travel,Eco,1024,3,5,3,3,4,3,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +48664,13526,Male,disloyal Customer,48,Business travel,Business,227,2,3,3,3,5,2,5,5,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +48665,5735,Female,Loyal Customer,28,Personal Travel,Eco Plus,299,4,4,4,4,2,4,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +48666,95136,Male,Loyal Customer,56,Personal Travel,Eco,458,1,5,1,3,2,1,2,2,4,2,4,5,3,2,0,2.0,neutral or dissatisfied +48667,19384,Female,disloyal Customer,25,Business travel,Eco,844,2,2,2,3,2,1,1,4,5,3,4,1,3,1,127,149.0,neutral or dissatisfied +48668,76928,Male,Loyal Customer,32,Business travel,Eco,1823,2,3,3,3,2,2,2,2,1,5,2,1,4,2,2,0.0,neutral or dissatisfied +48669,117476,Male,Loyal Customer,57,Business travel,Eco,507,1,4,5,5,1,1,1,1,3,1,3,3,2,1,62,63.0,neutral or dissatisfied +48670,122077,Male,Loyal Customer,37,Personal Travel,Eco,185,2,4,0,4,2,0,2,2,1,3,5,3,5,2,0,0.0,neutral or dissatisfied +48671,22008,Female,Loyal Customer,57,Personal Travel,Eco,500,3,4,3,1,4,4,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +48672,74821,Female,Loyal Customer,27,Personal Travel,Eco Plus,1438,2,4,1,3,5,1,2,5,4,3,3,4,5,5,0,0.0,neutral or dissatisfied +48673,65935,Male,Loyal Customer,55,Personal Travel,Eco,569,2,4,2,3,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +48674,117828,Female,Loyal Customer,59,Personal Travel,Eco,328,4,3,4,3,1,3,2,3,3,4,3,1,3,2,7,0.0,neutral or dissatisfied +48675,123707,Female,Loyal Customer,66,Personal Travel,Eco,214,1,0,1,4,5,5,5,5,5,1,3,5,5,5,0,0.0,neutral or dissatisfied +48676,103562,Female,Loyal Customer,62,Business travel,Eco Plus,738,3,3,4,3,1,2,3,3,3,3,3,3,3,2,25,17.0,neutral or dissatisfied +48677,68309,Male,Loyal Customer,54,Personal Travel,Eco,1797,1,4,1,5,5,1,5,5,5,4,4,5,5,5,11,38.0,neutral or dissatisfied +48678,90864,Female,Loyal Customer,19,Business travel,Eco,406,1,5,5,5,1,1,3,1,4,5,3,3,4,1,74,79.0,neutral or dissatisfied +48679,125207,Female,disloyal Customer,40,Business travel,Business,251,1,0,0,2,3,0,3,3,2,1,5,4,1,3,0,0.0,neutral or dissatisfied +48680,49327,Male,Loyal Customer,57,Business travel,Business,89,2,4,4,4,4,3,4,1,1,1,2,4,1,4,0,19.0,neutral or dissatisfied +48681,87657,Male,disloyal Customer,41,Business travel,Business,591,3,3,3,3,1,3,3,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +48682,80949,Male,Loyal Customer,67,Business travel,Eco Plus,341,3,1,5,1,3,3,3,3,3,4,2,4,1,3,4,40.0,neutral or dissatisfied +48683,105489,Female,Loyal Customer,59,Business travel,Business,1741,3,3,3,3,3,4,4,5,5,5,5,4,5,5,45,54.0,satisfied +48684,106222,Female,Loyal Customer,47,Business travel,Business,471,5,2,2,2,4,3,4,5,5,4,5,2,5,2,33,26.0,neutral or dissatisfied +48685,84152,Male,Loyal Customer,47,Business travel,Business,3510,3,3,3,3,1,5,2,4,4,4,4,2,4,4,12,0.0,satisfied +48686,90488,Male,Loyal Customer,53,Business travel,Business,3315,3,3,4,3,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +48687,98080,Female,Loyal Customer,56,Business travel,Business,3033,1,1,1,1,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +48688,102104,Female,disloyal Customer,36,Business travel,Business,407,2,2,2,1,5,2,4,5,3,3,4,5,4,5,8,25.0,neutral or dissatisfied +48689,113615,Female,Loyal Customer,60,Personal Travel,Eco,407,1,4,1,4,2,3,3,2,2,1,5,1,2,4,0,0.0,neutral or dissatisfied +48690,2773,Female,Loyal Customer,45,Business travel,Business,3784,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +48691,96332,Male,disloyal Customer,66,Business travel,Business,359,1,1,1,3,5,1,4,5,4,2,3,1,3,5,39,30.0,neutral or dissatisfied +48692,12247,Female,Loyal Customer,55,Business travel,Business,190,4,4,4,4,3,1,1,3,3,4,5,3,3,2,120,115.0,satisfied +48693,84389,Female,disloyal Customer,41,Business travel,Business,591,5,5,5,4,4,5,4,4,3,5,5,4,5,4,0,0.0,satisfied +48694,57949,Female,Loyal Customer,55,Business travel,Business,3824,1,1,1,1,5,5,4,4,4,4,4,4,4,3,26,13.0,satisfied +48695,24362,Female,Loyal Customer,40,Business travel,Business,3924,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +48696,84252,Male,Loyal Customer,44,Business travel,Business,1814,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +48697,101498,Male,Loyal Customer,37,Business travel,Eco,345,2,5,5,5,2,2,2,2,4,5,4,1,3,2,39,26.0,neutral or dissatisfied +48698,45914,Male,disloyal Customer,30,Business travel,Eco,563,1,1,1,3,3,1,1,3,2,4,3,1,3,3,0,2.0,neutral or dissatisfied +48699,92839,Male,Loyal Customer,39,Personal Travel,Eco,1587,4,5,4,3,4,4,3,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +48700,70270,Male,Loyal Customer,30,Business travel,Business,852,2,2,2,2,3,4,3,3,4,2,5,5,5,3,0,0.0,satisfied +48701,37587,Male,Loyal Customer,17,Business travel,Business,2150,1,1,1,1,1,1,1,1,4,5,3,1,4,1,2,0.0,neutral or dissatisfied +48702,106137,Female,Loyal Customer,37,Business travel,Eco,302,4,1,1,1,4,3,4,4,1,3,3,2,3,4,39,43.0,neutral or dissatisfied +48703,118175,Male,Loyal Customer,38,Business travel,Business,1440,4,1,4,4,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +48704,86481,Male,Loyal Customer,64,Personal Travel,Eco,762,5,5,5,3,1,5,1,1,3,5,5,3,5,1,31,3.0,satisfied +48705,25633,Female,Loyal Customer,19,Business travel,Business,2496,2,4,4,4,2,2,2,2,3,1,3,2,4,2,0,0.0,neutral or dissatisfied +48706,129235,Male,Loyal Customer,8,Business travel,Business,1464,2,2,2,2,2,3,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +48707,36135,Female,Loyal Customer,50,Business travel,Eco,1162,2,4,4,4,1,3,4,2,2,2,2,3,2,4,0,1.0,satisfied +48708,95192,Male,Loyal Customer,15,Personal Travel,Eco,323,3,2,3,4,2,3,2,2,1,4,3,2,4,2,98,93.0,neutral or dissatisfied +48709,37598,Male,Loyal Customer,66,Business travel,Eco,550,3,3,3,3,3,3,3,3,5,2,3,1,1,3,0,0.0,satisfied +48710,18076,Female,Loyal Customer,32,Personal Travel,Eco,488,2,3,2,4,1,2,1,1,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +48711,73343,Male,Loyal Customer,47,Business travel,Business,1182,2,2,2,2,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +48712,100788,Male,Loyal Customer,44,Business travel,Business,1809,4,4,4,4,4,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +48713,21422,Female,Loyal Customer,33,Business travel,Eco,331,5,5,5,5,5,5,5,5,1,3,1,4,1,5,19,23.0,satisfied +48714,53926,Male,Loyal Customer,46,Business travel,Eco Plus,191,1,2,2,2,1,1,1,1,1,1,4,2,4,1,21,3.0,neutral or dissatisfied +48715,93870,Male,Loyal Customer,39,Business travel,Business,590,2,2,3,2,5,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +48716,87054,Male,disloyal Customer,23,Business travel,Business,594,4,4,4,2,2,4,2,2,3,2,5,3,4,2,0,0.0,satisfied +48717,510,Female,Loyal Customer,52,Business travel,Business,354,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +48718,119923,Female,Loyal Customer,43,Business travel,Business,868,1,1,1,1,5,5,5,3,3,4,3,5,3,3,0,1.0,satisfied +48719,99958,Male,Loyal Customer,58,Personal Travel,Eco Plus,1986,3,4,3,1,1,3,1,1,5,1,4,3,2,1,0,0.0,neutral or dissatisfied +48720,100620,Female,Loyal Customer,66,Business travel,Eco,721,4,5,5,5,3,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +48721,91616,Female,Loyal Customer,59,Business travel,Business,1352,2,2,2,2,4,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +48722,8070,Female,Loyal Customer,37,Business travel,Business,125,1,1,1,1,2,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +48723,107986,Male,Loyal Customer,41,Business travel,Business,1758,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +48724,28315,Female,disloyal Customer,24,Business travel,Eco,867,3,3,3,1,5,3,5,5,4,1,4,1,5,5,0,0.0,neutral or dissatisfied +48725,82411,Male,disloyal Customer,20,Business travel,Eco,502,0,4,0,1,2,0,4,2,5,4,5,3,5,2,0,0.0,satisfied +48726,46668,Female,Loyal Customer,51,Business travel,Eco,125,5,3,3,3,5,1,2,5,5,5,5,3,5,1,3,0.0,satisfied +48727,40115,Male,Loyal Customer,65,Business travel,Eco,368,5,5,5,5,5,5,5,5,5,2,5,3,3,5,0,2.0,satisfied +48728,19006,Female,disloyal Customer,23,Business travel,Eco,788,1,1,1,3,1,1,1,1,2,4,1,1,5,1,0,0.0,neutral or dissatisfied +48729,27221,Male,disloyal Customer,22,Business travel,Eco,1024,2,2,2,2,5,2,2,5,5,5,5,1,1,5,0,0.0,neutral or dissatisfied +48730,83717,Male,disloyal Customer,16,Business travel,Eco,577,2,3,2,4,1,2,1,1,4,3,3,4,3,1,2,18.0,neutral or dissatisfied +48731,78756,Male,Loyal Customer,48,Business travel,Eco,432,2,1,3,1,2,2,2,1,1,3,3,2,3,2,204,195.0,neutral or dissatisfied +48732,24200,Female,Loyal Customer,23,Business travel,Business,3464,4,1,1,1,3,3,4,3,1,5,3,2,4,3,0,0.0,neutral or dissatisfied +48733,52729,Male,Loyal Customer,29,Personal Travel,Eco,406,2,4,5,1,5,5,4,5,3,2,5,5,5,5,0,2.0,neutral or dissatisfied +48734,30272,Female,Loyal Customer,24,Business travel,Business,2706,4,5,5,5,4,3,4,4,3,1,3,3,4,4,0,0.0,neutral or dissatisfied +48735,101910,Female,Loyal Customer,21,Personal Travel,Eco,2173,2,5,2,3,4,2,4,4,3,3,4,3,4,4,10,5.0,neutral or dissatisfied +48736,71970,Female,Loyal Customer,22,Business travel,Business,1437,5,5,5,5,4,4,4,4,3,4,5,3,4,4,3,0.0,satisfied +48737,92627,Male,Loyal Customer,56,Business travel,Business,1970,2,2,2,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +48738,103571,Female,Loyal Customer,47,Business travel,Business,3721,5,5,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +48739,83313,Male,Loyal Customer,42,Business travel,Business,1671,5,5,3,5,4,3,4,5,5,5,5,3,5,5,7,0.0,satisfied +48740,12118,Male,Loyal Customer,24,Business travel,Business,642,3,5,5,5,3,3,3,3,3,3,3,2,3,3,10,0.0,neutral or dissatisfied +48741,70074,Male,disloyal Customer,27,Business travel,Business,550,5,5,5,4,5,3,4,3,4,4,4,4,5,4,145,132.0,satisfied +48742,129796,Female,Loyal Customer,14,Personal Travel,Eco,447,2,4,2,4,2,2,2,2,1,1,4,2,4,2,0,1.0,neutral or dissatisfied +48743,20405,Male,Loyal Customer,40,Personal Travel,Eco Plus,588,2,5,2,2,2,2,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +48744,77872,Female,Loyal Customer,53,Personal Travel,Eco,1262,2,5,2,3,4,5,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +48745,6219,Male,Loyal Customer,54,Business travel,Business,413,4,4,1,4,3,5,4,4,4,4,4,4,4,4,39,26.0,satisfied +48746,51607,Male,Loyal Customer,61,Business travel,Business,370,4,4,4,4,5,4,1,5,5,5,5,3,5,2,70,68.0,satisfied +48747,27899,Male,disloyal Customer,23,Business travel,Eco,822,2,3,3,5,2,3,5,2,3,5,2,5,5,5,0,0.0,neutral or dissatisfied +48748,43841,Female,Loyal Customer,52,Business travel,Business,3624,4,4,4,4,1,3,4,5,5,5,5,2,5,5,30,25.0,satisfied +48749,92710,Female,Loyal Customer,48,Personal Travel,Eco,2153,3,1,4,4,5,4,4,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +48750,116264,Female,Loyal Customer,48,Personal Travel,Eco,404,2,4,2,1,4,5,5,2,2,2,4,3,2,4,0,0.0,neutral or dissatisfied +48751,92611,Female,Loyal Customer,33,Business travel,Eco Plus,2342,4,3,3,3,4,3,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +48752,44482,Female,Loyal Customer,51,Business travel,Eco,589,4,2,2,2,2,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +48753,99202,Female,Loyal Customer,16,Business travel,Business,583,2,5,3,3,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +48754,40830,Female,Loyal Customer,58,Business travel,Business,188,1,1,1,1,3,1,5,5,5,5,5,3,5,4,0,0.0,satisfied +48755,52324,Male,Loyal Customer,37,Business travel,Business,3414,1,1,1,1,4,3,5,5,5,5,5,1,5,1,0,2.0,satisfied +48756,6583,Female,Loyal Customer,40,Business travel,Business,128,1,4,4,4,2,4,4,2,2,2,1,1,2,3,18,45.0,neutral or dissatisfied +48757,77001,Male,Loyal Customer,33,Business travel,Business,2387,4,4,5,4,5,5,5,5,3,2,5,4,5,5,2,0.0,satisfied +48758,103937,Female,Loyal Customer,55,Business travel,Business,770,1,1,1,1,2,4,5,5,5,5,5,3,5,3,34,40.0,satisfied +48759,32821,Female,Loyal Customer,57,Business travel,Eco,101,5,4,4,4,4,2,3,5,5,5,5,4,5,3,0,0.0,satisfied +48760,36592,Male,Loyal Customer,23,Business travel,Business,1944,1,1,1,1,1,1,1,1,4,5,4,2,4,1,27,28.0,neutral or dissatisfied +48761,102107,Female,disloyal Customer,27,Business travel,Business,386,4,4,4,5,5,4,1,5,3,5,5,4,4,5,2,0.0,neutral or dissatisfied +48762,24848,Female,Loyal Customer,10,Personal Travel,Eco,894,3,2,3,4,1,3,1,1,3,3,4,3,3,1,29,71.0,neutral or dissatisfied +48763,89886,Male,Loyal Customer,46,Business travel,Business,1416,2,2,2,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +48764,50704,Male,Loyal Customer,19,Personal Travel,Eco,153,1,4,1,1,1,1,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +48765,47160,Male,Loyal Customer,46,Business travel,Business,945,4,4,4,4,2,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +48766,34682,Female,disloyal Customer,37,Business travel,Eco,301,3,3,3,2,3,2,2,4,5,4,5,2,1,2,220,219.0,neutral or dissatisfied +48767,25995,Male,Loyal Customer,38,Personal Travel,Eco,577,3,5,4,3,4,4,3,4,5,5,4,5,4,4,40,66.0,neutral or dissatisfied +48768,72673,Female,Loyal Customer,47,Personal Travel,Eco,985,1,4,1,1,5,4,4,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +48769,22593,Male,disloyal Customer,21,Business travel,Eco,223,5,0,5,2,1,5,1,1,4,2,4,4,3,1,0,0.0,satisfied +48770,67510,Female,disloyal Customer,24,Business travel,Eco,1171,4,4,4,2,1,4,1,1,3,2,5,5,4,1,23,0.0,satisfied +48771,39357,Female,Loyal Customer,18,Business travel,Business,3518,1,1,1,1,4,4,4,4,5,4,4,5,1,4,0,0.0,satisfied +48772,71762,Female,Loyal Customer,40,Business travel,Business,1726,4,3,4,4,5,4,4,5,5,5,5,4,5,3,11,10.0,satisfied +48773,104401,Male,Loyal Customer,60,Business travel,Business,3545,5,1,5,5,4,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +48774,44705,Female,Loyal Customer,43,Personal Travel,Eco,67,2,3,2,4,1,4,2,4,4,2,4,5,4,2,29,38.0,neutral or dissatisfied +48775,80341,Female,Loyal Customer,47,Business travel,Business,952,4,1,1,1,4,4,3,4,4,4,4,4,4,3,4,26.0,neutral or dissatisfied +48776,46262,Male,Loyal Customer,64,Personal Travel,Eco,455,3,5,3,1,1,3,1,1,5,3,5,5,4,1,5,0.0,neutral or dissatisfied +48777,27910,Male,Loyal Customer,14,Personal Travel,Eco,2311,1,4,1,4,1,3,3,4,5,4,3,3,1,3,16,18.0,neutral or dissatisfied +48778,128324,Male,Loyal Customer,36,Business travel,Business,2411,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +48779,39208,Female,Loyal Customer,69,Business travel,Business,67,2,2,2,2,1,3,3,3,3,3,2,1,3,4,7,8.0,neutral or dissatisfied +48780,83690,Male,Loyal Customer,32,Personal Travel,Eco,577,4,5,4,4,5,4,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +48781,70722,Female,Loyal Customer,22,Business travel,Business,675,2,1,2,2,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +48782,25754,Female,Loyal Customer,60,Business travel,Business,356,3,5,5,5,5,2,2,3,3,3,3,1,3,2,9,0.0,neutral or dissatisfied +48783,121651,Female,Loyal Customer,26,Personal Travel,Business,328,3,3,3,3,2,3,1,2,3,5,2,3,4,2,0,0.0,neutral or dissatisfied +48784,91775,Female,Loyal Customer,24,Personal Travel,Eco,588,4,5,4,4,4,4,4,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +48785,88394,Male,Loyal Customer,22,Business travel,Business,1983,2,5,5,5,2,2,2,2,1,4,4,3,4,2,1,11.0,neutral or dissatisfied +48786,67352,Male,Loyal Customer,39,Personal Travel,Eco,1471,4,4,4,2,2,4,2,2,5,3,5,3,5,2,22,11.0,neutral or dissatisfied +48787,67559,Male,Loyal Customer,39,Business travel,Business,1235,2,5,2,2,4,5,4,5,5,5,5,5,5,5,5,4.0,satisfied +48788,67357,Female,Loyal Customer,55,Business travel,Business,1911,2,1,2,2,3,4,4,5,5,5,5,4,5,5,38,36.0,satisfied +48789,54078,Male,Loyal Customer,33,Business travel,Business,1416,3,3,3,3,2,2,2,2,4,2,2,5,1,2,35,38.0,satisfied +48790,96594,Female,Loyal Customer,13,Personal Travel,Eco,861,3,5,3,1,2,3,2,2,5,3,4,3,5,2,3,0.0,neutral or dissatisfied +48791,94637,Male,Loyal Customer,44,Business travel,Eco,293,3,1,4,1,3,3,3,3,1,4,3,1,4,3,42,36.0,neutral or dissatisfied +48792,124328,Female,Loyal Customer,34,Personal Travel,Eco Plus,255,3,5,3,3,2,3,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +48793,67742,Female,disloyal Customer,29,Business travel,Eco,1235,3,3,3,4,3,3,3,3,3,4,3,4,4,3,27,12.0,neutral or dissatisfied +48794,89529,Male,Loyal Customer,38,Business travel,Business,3164,3,3,3,3,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +48795,16848,Female,Loyal Customer,28,Business travel,Business,3449,1,1,1,1,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +48796,24810,Male,Loyal Customer,29,Business travel,Eco,861,4,3,3,3,4,4,4,4,2,5,3,5,2,4,0,0.0,satisfied +48797,27313,Female,Loyal Customer,31,Business travel,Business,3326,5,5,5,5,5,5,5,5,1,5,1,2,5,5,0,0.0,satisfied +48798,120301,Female,disloyal Customer,25,Business travel,Eco,268,3,3,2,4,1,2,1,1,4,5,4,2,3,1,0,6.0,neutral or dissatisfied +48799,62031,Male,disloyal Customer,40,Business travel,Business,2586,2,2,2,3,5,2,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +48800,49845,Female,Loyal Customer,48,Business travel,Eco,89,2,2,2,2,4,3,3,1,1,2,1,4,1,1,0,20.0,neutral or dissatisfied +48801,113824,Male,Loyal Customer,9,Personal Travel,Eco Plus,386,3,5,3,2,5,3,4,5,4,2,5,5,5,5,6,11.0,neutral or dissatisfied +48802,48244,Male,Loyal Customer,50,Personal Travel,Eco,259,2,4,2,2,1,2,1,1,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +48803,103912,Male,Loyal Customer,51,Business travel,Business,533,3,3,3,3,5,4,4,4,4,4,4,5,4,5,4,6.0,satisfied +48804,93544,Female,disloyal Customer,25,Business travel,Business,585,5,0,5,5,5,5,5,5,4,4,4,3,4,5,7,20.0,satisfied +48805,71627,Female,Loyal Customer,42,Business travel,Eco,797,2,2,2,2,5,3,5,2,2,2,2,5,2,4,18,9.0,satisfied +48806,100505,Female,disloyal Customer,30,Business travel,Eco,759,2,2,2,4,3,2,3,3,3,5,4,4,3,3,15,10.0,neutral or dissatisfied +48807,11127,Male,Loyal Customer,19,Personal Travel,Eco,312,1,5,3,4,5,3,1,5,4,2,5,5,4,5,12,5.0,neutral or dissatisfied +48808,18978,Male,disloyal Customer,10,Business travel,Eco,792,1,1,1,3,4,1,4,4,1,4,3,2,4,4,14,29.0,neutral or dissatisfied +48809,31614,Male,Loyal Customer,42,Business travel,Business,2895,5,5,4,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +48810,22677,Female,Loyal Customer,35,Business travel,Business,2420,4,4,4,4,1,2,3,4,4,4,4,3,4,1,0,16.0,satisfied +48811,32812,Female,Loyal Customer,22,Business travel,Eco,102,3,2,2,2,3,3,1,3,2,5,4,1,3,3,10,11.0,neutral or dissatisfied +48812,11987,Female,Loyal Customer,61,Personal Travel,Eco,643,2,4,2,2,4,5,4,5,5,2,5,4,5,5,100,112.0,neutral or dissatisfied +48813,81702,Female,Loyal Customer,57,Personal Travel,Eco,907,1,4,1,2,3,5,5,2,2,1,5,3,2,3,0,0.0,neutral or dissatisfied +48814,120217,Female,Loyal Customer,40,Business travel,Business,1325,2,2,2,2,2,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +48815,33517,Male,disloyal Customer,15,Business travel,Eco,1141,4,4,4,5,4,4,4,4,2,4,4,5,1,4,0,5.0,neutral or dissatisfied +48816,87318,Female,Loyal Customer,55,Business travel,Eco Plus,177,4,5,3,5,3,5,4,4,4,4,4,1,4,4,0,0.0,satisfied +48817,55841,Male,disloyal Customer,23,Business travel,Eco,1016,5,5,5,3,5,5,5,5,5,3,3,5,2,5,28,32.0,satisfied +48818,6764,Female,disloyal Customer,37,Business travel,Business,223,5,5,5,3,1,5,1,1,5,4,5,5,5,1,0,0.0,satisfied +48819,103155,Female,Loyal Customer,57,Business travel,Business,272,0,0,0,4,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +48820,21199,Male,Loyal Customer,28,Business travel,Business,2207,0,5,0,2,2,2,2,2,4,3,2,1,5,2,0,0.0,satisfied +48821,115974,Female,Loyal Customer,68,Personal Travel,Eco,342,3,4,3,4,3,3,4,3,3,3,3,4,3,4,11,0.0,neutral or dissatisfied +48822,96124,Female,Loyal Customer,41,Personal Travel,Eco Plus,795,1,5,1,1,4,5,5,3,3,1,3,5,3,4,12,2.0,neutral or dissatisfied +48823,124600,Female,Loyal Customer,67,Personal Travel,Eco,500,2,3,2,3,2,4,3,2,2,2,2,4,2,3,128,116.0,neutral or dissatisfied +48824,46317,Female,Loyal Customer,51,Business travel,Business,420,3,3,3,3,5,3,2,5,5,5,5,2,5,5,0,0.0,satisfied +48825,25976,Male,Loyal Customer,26,Business travel,Eco Plus,946,4,2,2,2,4,3,2,4,1,1,2,1,2,4,33,26.0,neutral or dissatisfied +48826,115613,Female,disloyal Customer,51,Business travel,Business,480,4,4,4,4,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +48827,81152,Female,Loyal Customer,30,Business travel,Business,3560,5,5,5,5,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +48828,108460,Male,Loyal Customer,17,Personal Travel,Eco,1440,2,4,2,4,2,2,2,2,3,2,5,5,4,2,11,0.0,neutral or dissatisfied +48829,129384,Female,Loyal Customer,33,Personal Travel,Eco,2454,1,5,0,3,3,0,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +48830,81421,Male,Loyal Customer,54,Business travel,Business,448,2,2,2,2,3,4,5,4,4,4,4,5,4,5,11,11.0,satisfied +48831,101763,Male,Loyal Customer,8,Personal Travel,Eco,1590,3,5,3,4,3,3,3,3,2,3,5,3,1,3,8,0.0,neutral or dissatisfied +48832,112873,Female,Loyal Customer,33,Business travel,Business,1476,3,4,3,3,2,5,5,4,4,4,4,5,4,5,1,0.0,satisfied +48833,112797,Male,disloyal Customer,20,Business travel,Business,1313,4,0,5,5,1,5,1,1,5,5,4,3,5,1,0,0.0,satisfied +48834,26438,Male,Loyal Customer,30,Business travel,Business,1912,2,4,4,4,2,2,2,2,1,5,4,2,4,2,0,0.0,neutral or dissatisfied +48835,807,Female,disloyal Customer,58,Business travel,Business,396,4,4,4,4,5,4,5,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +48836,129862,Female,Loyal Customer,39,Business travel,Business,2667,0,0,0,1,5,5,5,3,3,3,3,5,3,3,1,0.0,satisfied +48837,42173,Female,Loyal Customer,38,Business travel,Eco,412,4,2,2,2,4,4,4,4,1,1,3,3,3,4,12,0.0,satisfied +48838,6357,Male,Loyal Customer,43,Business travel,Business,315,2,2,2,2,3,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +48839,49925,Female,Loyal Customer,42,Business travel,Business,156,5,5,5,5,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +48840,101270,Female,Loyal Customer,59,Personal Travel,Eco,1910,5,4,5,4,5,5,5,4,4,5,4,4,4,4,4,0.0,satisfied +48841,28426,Female,Loyal Customer,62,Personal Travel,Eco,1399,3,1,3,3,3,3,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +48842,25575,Female,Loyal Customer,53,Business travel,Business,3522,3,3,3,3,2,5,3,4,4,4,4,5,4,2,0,0.0,satisfied +48843,96022,Male,Loyal Customer,31,Business travel,Eco,1235,1,2,3,3,1,1,1,1,1,1,4,1,3,1,15,45.0,neutral or dissatisfied +48844,99778,Male,disloyal Customer,28,Business travel,Business,584,2,2,2,1,3,2,3,3,4,3,4,3,5,3,22,14.0,neutral or dissatisfied +48845,93126,Female,disloyal Customer,25,Business travel,Business,1066,5,5,5,1,2,5,4,2,3,4,4,5,5,2,27,14.0,satisfied +48846,46517,Female,disloyal Customer,55,Business travel,Eco,125,3,4,3,4,5,3,5,5,2,5,3,1,2,5,60,56.0,neutral or dissatisfied +48847,85148,Female,Loyal Customer,56,Business travel,Business,2028,5,5,5,5,2,4,4,3,3,4,3,5,3,3,37,16.0,satisfied +48848,28821,Male,Loyal Customer,38,Business travel,Business,1050,3,3,5,3,5,1,2,5,5,5,5,2,5,2,0,0.0,satisfied +48849,65139,Male,Loyal Customer,35,Personal Travel,Eco,282,3,3,3,3,2,3,2,2,5,1,1,3,5,2,62,74.0,neutral or dissatisfied +48850,72492,Male,Loyal Customer,23,Business travel,Business,1949,1,1,1,1,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +48851,102044,Female,disloyal Customer,17,Business travel,Business,414,5,0,5,4,3,5,4,3,4,3,4,3,4,3,1,0.0,satisfied +48852,115333,Male,Loyal Customer,51,Business travel,Business,1857,5,5,5,5,4,5,4,4,4,4,4,5,4,5,17,18.0,satisfied +48853,34547,Female,Loyal Customer,24,Business travel,Business,1617,1,1,1,1,5,5,5,5,3,1,4,1,1,5,0,5.0,satisfied +48854,22066,Female,Loyal Customer,38,Personal Travel,Eco,304,1,2,1,4,4,1,4,4,2,3,3,4,4,4,24,28.0,neutral or dissatisfied +48855,74793,Female,disloyal Customer,39,Business travel,Business,1235,2,3,3,4,4,3,4,4,3,1,4,4,3,4,14,14.0,neutral or dissatisfied +48856,26288,Male,Loyal Customer,28,Business travel,Business,3018,1,1,3,1,3,3,3,3,5,5,4,4,4,3,5,10.0,satisfied +48857,112422,Male,disloyal Customer,8,Business travel,Eco,862,3,3,3,4,5,3,5,5,2,3,3,1,4,5,29,20.0,neutral or dissatisfied +48858,69809,Male,Loyal Customer,42,Business travel,Business,2454,4,3,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +48859,47455,Male,Loyal Customer,57,Personal Travel,Eco,588,2,2,2,3,3,2,3,3,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +48860,24916,Female,Loyal Customer,22,Business travel,Business,3119,1,1,1,1,4,4,4,4,2,2,4,3,3,4,1,0.0,satisfied +48861,42496,Female,Loyal Customer,42,Business travel,Eco,495,4,4,4,4,5,4,3,4,4,4,4,2,4,5,2,22.0,satisfied +48862,99729,Male,disloyal Customer,32,Business travel,Business,255,3,3,3,3,5,3,5,5,3,3,5,5,4,5,69,66.0,neutral or dissatisfied +48863,15118,Male,Loyal Customer,45,Business travel,Eco,912,4,3,3,3,4,4,4,4,3,5,3,2,4,4,0,2.0,neutral or dissatisfied +48864,123821,Female,Loyal Customer,65,Business travel,Eco,646,1,2,2,2,3,4,4,1,1,1,1,1,1,2,0,12.0,neutral or dissatisfied +48865,66614,Female,Loyal Customer,62,Personal Travel,Eco Plus,761,3,5,3,2,5,5,5,2,2,3,2,4,2,4,0,9.0,neutral or dissatisfied +48866,94302,Female,Loyal Customer,41,Business travel,Business,323,0,0,0,1,4,4,5,5,5,5,5,3,5,4,40,30.0,satisfied +48867,33694,Male,disloyal Customer,13,Business travel,Eco,759,5,5,5,4,2,5,2,2,1,4,1,5,2,2,0,0.0,satisfied +48868,63207,Female,Loyal Customer,38,Business travel,Eco,337,4,4,1,1,4,4,4,4,4,2,3,1,3,4,2,3.0,neutral or dissatisfied +48869,116274,Male,Loyal Customer,34,Personal Travel,Eco,362,3,5,4,3,5,4,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +48870,40338,Male,Loyal Customer,61,Personal Travel,Eco Plus,402,4,5,5,5,3,5,4,3,3,3,4,3,4,3,0,0.0,satisfied +48871,70388,Male,Loyal Customer,37,Business travel,Business,1562,4,4,4,4,5,5,5,3,3,3,3,4,3,4,0,23.0,satisfied +48872,108661,Female,Loyal Customer,52,Personal Travel,Eco,1747,4,1,4,4,3,4,3,2,2,4,2,4,2,3,24,17.0,neutral or dissatisfied +48873,73982,Female,Loyal Customer,46,Business travel,Business,2330,2,2,2,2,3,3,4,5,5,4,5,5,5,5,0,28.0,satisfied +48874,117267,Male,Loyal Customer,29,Personal Travel,Eco,621,3,4,3,1,4,3,4,4,1,1,3,2,3,4,0,0.0,neutral or dissatisfied +48875,18573,Female,Loyal Customer,60,Business travel,Business,3796,1,4,3,4,5,2,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +48876,7248,Female,Loyal Customer,14,Personal Travel,Eco,116,3,4,3,2,4,3,4,4,3,5,2,4,1,4,0,0.0,neutral or dissatisfied +48877,32000,Male,Loyal Customer,48,Personal Travel,Business,216,1,2,1,3,2,3,3,4,4,1,4,4,4,3,2,5.0,neutral or dissatisfied +48878,59291,Female,Loyal Customer,29,Business travel,Business,2338,1,1,1,1,2,2,2,2,3,4,4,5,4,2,21,1.0,satisfied +48879,25933,Male,Loyal Customer,70,Personal Travel,Eco,594,1,4,1,4,2,1,2,2,2,2,4,3,3,2,12,2.0,neutral or dissatisfied +48880,107802,Male,Loyal Customer,48,Business travel,Business,2449,0,0,0,2,4,4,5,5,5,5,5,3,5,3,2,5.0,satisfied +48881,128432,Female,disloyal Customer,37,Business travel,Business,370,1,1,1,3,1,1,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +48882,70731,Male,Loyal Customer,37,Business travel,Business,2935,5,5,5,5,4,5,3,5,5,5,5,5,5,1,0,0.0,satisfied +48883,94832,Female,Loyal Customer,33,Business travel,Eco,248,2,5,3,5,2,2,2,2,1,3,2,3,2,2,24,16.0,neutral or dissatisfied +48884,100043,Male,Loyal Customer,64,Business travel,Eco,281,5,1,1,1,4,5,4,4,4,2,1,2,1,4,0,0.0,satisfied +48885,122146,Male,Loyal Customer,31,Business travel,Business,546,1,1,1,1,3,3,3,3,3,4,4,3,4,3,20,22.0,satisfied +48886,92314,Female,Loyal Customer,55,Business travel,Business,2615,4,4,4,4,2,3,5,5,5,5,5,4,5,3,4,0.0,satisfied +48887,49796,Male,disloyal Customer,36,Business travel,Eco,193,4,0,4,3,1,4,1,1,4,1,4,2,4,1,38,30.0,neutral or dissatisfied +48888,16077,Male,Loyal Customer,51,Personal Travel,Eco,744,2,4,2,3,2,2,2,2,1,2,5,3,5,2,0,0.0,neutral or dissatisfied +48889,2817,Male,disloyal Customer,17,Business travel,Eco,491,1,4,1,4,1,1,1,1,4,4,3,4,3,1,0,1.0,neutral or dissatisfied +48890,78987,Male,Loyal Customer,58,Business travel,Business,2213,2,2,5,2,5,4,5,5,5,5,5,3,5,5,27,42.0,satisfied +48891,69459,Female,Loyal Customer,37,Personal Travel,Eco,1096,1,2,1,3,1,1,1,1,3,4,3,3,3,1,0,0.0,neutral or dissatisfied +48892,81383,Female,Loyal Customer,54,Business travel,Business,1942,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +48893,83612,Male,disloyal Customer,38,Business travel,Eco,409,3,4,3,3,2,3,3,2,1,1,3,4,3,2,3,0.0,neutral or dissatisfied +48894,44095,Female,Loyal Customer,45,Business travel,Business,2156,5,5,5,5,3,1,5,4,4,4,4,4,4,3,0,3.0,satisfied +48895,21269,Female,Loyal Customer,56,Personal Travel,Business,692,2,4,2,3,4,5,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +48896,35586,Male,Loyal Customer,41,Business travel,Eco Plus,1041,1,2,4,2,1,1,1,1,4,4,4,2,3,1,74,62.0,neutral or dissatisfied +48897,105978,Male,Loyal Customer,25,Personal Travel,Eco,2295,2,3,2,4,4,2,4,4,2,4,4,4,4,4,31,0.0,neutral or dissatisfied +48898,75129,Male,Loyal Customer,52,Business travel,Business,1744,4,4,4,4,5,3,5,5,5,5,5,3,5,4,11,0.0,satisfied +48899,113815,Male,Loyal Customer,23,Business travel,Eco Plus,414,5,5,5,5,5,5,3,5,5,4,2,3,4,5,0,0.0,satisfied +48900,20242,Female,Loyal Customer,33,Business travel,Business,228,5,5,4,5,1,5,3,4,4,4,4,4,4,5,64,43.0,satisfied +48901,31048,Female,Loyal Customer,32,Business travel,Business,862,2,2,2,2,5,5,5,5,1,5,4,4,3,5,0,0.0,satisfied +48902,47373,Male,Loyal Customer,63,Business travel,Business,2361,4,2,4,4,1,2,3,2,2,2,2,1,2,4,0,18.0,satisfied +48903,127979,Female,Loyal Customer,29,Business travel,Business,1885,2,2,5,2,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +48904,32875,Male,Loyal Customer,58,Personal Travel,Eco,163,1,4,0,4,2,0,2,2,3,3,4,2,4,2,2,7.0,neutral or dissatisfied +48905,67160,Female,disloyal Customer,38,Business travel,Eco,721,2,3,3,4,5,3,5,5,4,2,4,4,1,5,0,0.0,neutral or dissatisfied +48906,34098,Male,Loyal Customer,67,Personal Travel,Business,1129,4,5,4,2,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +48907,90484,Female,Loyal Customer,46,Business travel,Business,2283,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +48908,3892,Female,disloyal Customer,27,Business travel,Business,290,2,2,2,3,4,2,5,4,2,5,2,4,3,4,0,0.0,neutral or dissatisfied +48909,24599,Female,Loyal Customer,47,Business travel,Eco,526,5,3,3,3,3,4,1,5,5,5,5,5,5,4,1,14.0,satisfied +48910,104415,Male,disloyal Customer,31,Business travel,Eco,1011,3,3,3,3,4,3,4,4,2,2,4,4,3,4,0,3.0,neutral or dissatisfied +48911,76140,Female,disloyal Customer,25,Business travel,Eco,689,3,3,3,4,5,3,2,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +48912,39135,Male,Loyal Customer,28,Personal Travel,Eco,228,1,4,1,5,2,1,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +48913,104438,Male,Loyal Customer,33,Personal Travel,Eco,1138,3,5,3,3,2,3,2,2,3,3,4,4,5,2,12,29.0,neutral or dissatisfied +48914,116799,Female,Loyal Customer,15,Personal Travel,Eco Plus,296,2,4,2,4,1,2,1,1,5,3,5,4,5,1,16,11.0,neutral or dissatisfied +48915,124217,Female,Loyal Customer,32,Personal Travel,Eco,2176,1,3,1,3,2,1,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +48916,58381,Male,Loyal Customer,39,Business travel,Business,473,4,1,4,4,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +48917,23020,Female,disloyal Customer,48,Business travel,Business,927,2,2,2,1,3,2,4,3,4,4,4,5,4,3,2,0.0,neutral or dissatisfied +48918,9834,Male,Loyal Customer,30,Personal Travel,Eco,476,0,1,0,3,5,0,5,5,4,4,3,3,3,5,0,0.0,satisfied +48919,42588,Female,Loyal Customer,46,Business travel,Business,3100,4,4,4,4,4,5,1,4,4,4,4,5,4,5,1,2.0,satisfied +48920,117342,Female,disloyal Customer,20,Business travel,Eco,296,2,4,2,2,5,2,5,5,5,4,4,3,4,5,66,66.0,neutral or dissatisfied +48921,37515,Female,Loyal Customer,56,Business travel,Eco,1005,2,4,4,4,1,3,3,2,2,2,2,3,2,4,103,102.0,neutral or dissatisfied +48922,24050,Male,Loyal Customer,37,Personal Travel,Eco,595,3,3,3,5,5,3,5,5,5,3,4,3,3,5,0,0.0,neutral or dissatisfied +48923,49091,Male,Loyal Customer,39,Business travel,Business,421,5,5,4,5,4,1,1,4,4,4,4,1,4,4,26,23.0,satisfied +48924,70360,Female,disloyal Customer,20,Business travel,Business,1145,4,4,4,2,2,4,5,2,3,3,5,3,5,2,0,0.0,satisfied +48925,29083,Female,Loyal Customer,54,Personal Travel,Eco,697,1,5,1,2,4,1,2,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +48926,99663,Female,Loyal Customer,66,Personal Travel,Eco,920,4,5,4,1,5,5,5,2,2,4,2,5,2,4,0,0.0,neutral or dissatisfied +48927,11319,Female,Loyal Customer,25,Personal Travel,Eco,74,3,4,0,1,5,0,5,5,4,5,4,5,4,5,49,34.0,neutral or dissatisfied +48928,113054,Male,Loyal Customer,44,Business travel,Business,2084,4,4,4,4,4,4,5,5,5,5,5,4,5,5,2,0.0,satisfied +48929,54428,Male,Loyal Customer,28,Personal Travel,Eco,305,1,5,1,4,5,1,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +48930,46858,Female,Loyal Customer,41,Business travel,Business,737,2,2,2,2,1,2,2,5,5,5,5,2,5,2,0,0.0,satisfied +48931,19969,Male,Loyal Customer,36,Business travel,Business,3024,3,2,2,2,1,4,4,3,3,2,3,4,3,3,48,38.0,neutral or dissatisfied +48932,30494,Female,Loyal Customer,22,Personal Travel,Eco,627,1,1,1,2,3,1,1,3,1,4,3,3,3,3,10,40.0,neutral or dissatisfied +48933,78624,Male,Loyal Customer,29,Business travel,Business,1426,3,1,1,1,3,4,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +48934,62996,Female,Loyal Customer,42,Business travel,Eco,862,2,3,3,3,5,4,4,2,2,2,2,3,2,4,66,59.0,neutral or dissatisfied +48935,125305,Male,Loyal Customer,33,Personal Travel,Eco,678,4,1,4,4,1,4,1,1,4,2,3,1,4,1,0,0.0,neutral or dissatisfied +48936,87930,Female,Loyal Customer,39,Business travel,Business,2784,3,4,4,4,4,3,4,3,3,3,3,2,3,1,6,18.0,neutral or dissatisfied +48937,19883,Male,Loyal Customer,43,Business travel,Eco,315,2,4,4,4,2,2,2,2,3,3,1,3,1,2,6,4.0,satisfied +48938,32767,Male,disloyal Customer,41,Business travel,Business,216,2,2,2,3,3,2,3,3,1,3,4,1,4,3,4,26.0,neutral or dissatisfied +48939,106893,Male,Loyal Customer,41,Personal Travel,Eco,704,2,5,2,1,4,2,4,4,4,3,4,3,4,4,2,0.0,neutral or dissatisfied +48940,36450,Male,Loyal Customer,25,Business travel,Eco Plus,1368,3,5,5,5,3,3,2,3,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +48941,46376,Female,disloyal Customer,42,Business travel,Eco,1013,1,1,1,3,3,1,3,3,1,1,4,4,3,3,8,0.0,neutral or dissatisfied +48942,60528,Male,Loyal Customer,39,Personal Travel,Eco,985,4,5,4,2,5,4,2,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +48943,47125,Male,Loyal Customer,36,Business travel,Business,3088,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +48944,116412,Male,Loyal Customer,13,Personal Travel,Eco,342,2,1,2,3,2,2,2,2,2,3,4,4,4,2,48,42.0,neutral or dissatisfied +48945,35506,Female,Loyal Customer,65,Personal Travel,Eco,1076,4,5,4,5,2,5,5,2,2,4,4,5,2,3,0,0.0,neutral or dissatisfied +48946,55740,Female,Loyal Customer,60,Personal Travel,Eco,2161,2,2,2,3,2,3,4,2,2,2,2,4,2,2,0,7.0,neutral or dissatisfied +48947,48183,Female,Loyal Customer,48,Business travel,Business,2269,1,3,3,3,4,3,3,1,1,1,1,4,1,4,50,46.0,neutral or dissatisfied +48948,24049,Female,Loyal Customer,46,Personal Travel,Eco,595,2,5,2,3,2,5,5,4,4,2,4,1,4,2,4,0.0,neutral or dissatisfied +48949,74638,Male,disloyal Customer,36,Business travel,Eco,835,1,1,1,4,5,1,5,5,4,1,5,1,5,5,0,0.0,neutral or dissatisfied +48950,35290,Male,Loyal Customer,23,Business travel,Business,1032,4,4,4,4,5,4,5,5,2,2,4,4,5,5,0,0.0,satisfied +48951,106215,Female,disloyal Customer,24,Business travel,Business,471,5,0,5,2,1,5,1,1,4,4,4,5,5,1,0,0.0,satisfied +48952,121829,Male,Loyal Customer,57,Business travel,Business,2002,4,4,4,4,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +48953,104903,Male,Loyal Customer,23,Business travel,Business,1565,1,3,3,3,1,1,1,1,3,3,4,4,3,1,21,28.0,neutral or dissatisfied +48954,111339,Female,Loyal Customer,50,Personal Travel,Eco,283,1,3,1,2,2,1,2,4,4,1,4,2,4,3,19,28.0,neutral or dissatisfied +48955,126558,Female,disloyal Customer,24,Business travel,Eco Plus,644,5,1,5,2,2,1,2,2,3,5,3,3,1,2,3,6.0,satisfied +48956,98610,Female,disloyal Customer,32,Business travel,Business,873,1,1,1,1,2,1,2,2,3,2,5,3,4,2,13,0.0,neutral or dissatisfied +48957,126365,Male,Loyal Customer,63,Personal Travel,Eco,631,1,3,0,3,4,0,4,4,3,5,5,3,4,4,16,23.0,neutral or dissatisfied +48958,94572,Male,Loyal Customer,45,Business travel,Business,3234,2,2,2,2,2,4,5,2,2,2,2,3,2,4,0,4.0,satisfied +48959,24045,Male,Loyal Customer,22,Personal Travel,Eco,562,4,1,4,2,3,4,3,3,3,1,2,1,3,3,0,0.0,satisfied +48960,99064,Male,Loyal Customer,64,Business travel,Business,3407,2,4,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +48961,28986,Male,Loyal Customer,43,Business travel,Eco,954,5,2,2,2,5,5,5,5,5,1,4,1,4,5,0,0.0,satisfied +48962,10769,Female,Loyal Customer,35,Business travel,Business,396,2,5,5,5,5,4,4,2,2,3,2,2,2,1,5,5.0,neutral or dissatisfied +48963,79894,Female,disloyal Customer,20,Business travel,Eco,1096,2,3,3,2,4,3,5,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +48964,35271,Female,Loyal Customer,44,Business travel,Business,1069,5,5,5,5,5,4,3,4,4,4,4,2,4,2,32,33.0,satisfied +48965,49820,Female,Loyal Customer,61,Business travel,Eco,153,4,1,1,1,1,3,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +48966,119534,Male,Loyal Customer,39,Personal Travel,Eco,814,1,0,1,3,1,1,2,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +48967,14290,Female,Loyal Customer,48,Business travel,Eco,429,4,2,2,2,5,5,3,4,4,4,4,1,4,5,42,42.0,satisfied +48968,50091,Male,disloyal Customer,36,Business travel,Eco,156,3,0,3,4,1,3,1,1,1,3,3,4,5,1,0,0.0,neutral or dissatisfied +48969,80604,Male,Loyal Customer,45,Business travel,Business,3492,0,0,0,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +48970,2481,Female,disloyal Customer,25,Business travel,Business,1379,3,0,3,2,2,3,2,2,3,2,5,3,4,2,13,16.0,neutral or dissatisfied +48971,70598,Male,Loyal Customer,58,Business travel,Business,2611,3,3,3,3,3,3,3,4,4,3,3,3,2,3,0,22.0,neutral or dissatisfied +48972,74898,Male,Loyal Customer,58,Business travel,Business,2475,2,5,2,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +48973,38091,Female,Loyal Customer,51,Business travel,Eco,1237,2,3,3,3,4,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +48974,55226,Male,Loyal Customer,39,Business travel,Business,1009,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +48975,102385,Female,Loyal Customer,58,Business travel,Business,1695,2,5,5,5,2,4,3,4,4,4,2,1,4,4,27,31.0,neutral or dissatisfied +48976,101301,Male,Loyal Customer,25,Personal Travel,Eco,763,3,5,3,5,3,3,3,3,3,3,2,4,2,3,14,16.0,neutral or dissatisfied +48977,46322,Female,disloyal Customer,24,Business travel,Eco,420,3,4,3,2,5,3,5,5,3,3,3,1,5,5,3,0.0,neutral or dissatisfied +48978,128742,Female,disloyal Customer,25,Business travel,Business,998,5,1,5,3,5,2,3,3,2,4,4,3,3,3,0,6.0,satisfied +48979,64162,Male,Loyal Customer,66,Personal Travel,Eco,989,3,4,3,2,1,3,1,1,5,3,4,3,4,1,48,29.0,neutral or dissatisfied +48980,32999,Female,Loyal Customer,7,Personal Travel,Eco,216,3,3,0,4,2,0,1,2,1,2,3,1,3,2,0,0.0,neutral or dissatisfied +48981,109270,Male,Loyal Customer,64,Personal Travel,Eco Plus,793,1,5,1,1,4,1,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +48982,7157,Female,disloyal Customer,21,Business travel,Business,139,5,0,5,1,5,5,5,5,5,2,5,5,4,5,5,22.0,satisfied +48983,50002,Female,Loyal Customer,33,Business travel,Business,2926,3,5,3,3,1,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +48984,83027,Female,Loyal Customer,59,Business travel,Business,1973,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +48985,62553,Female,Loyal Customer,49,Business travel,Business,1744,2,2,2,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +48986,50898,Male,Loyal Customer,20,Personal Travel,Eco,363,2,5,3,1,2,3,4,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +48987,67240,Female,Loyal Customer,34,Personal Travel,Eco,929,3,4,3,1,2,3,2,2,3,5,5,5,4,2,0,18.0,neutral or dissatisfied +48988,78036,Female,Loyal Customer,37,Personal Travel,Eco,152,3,5,3,1,2,3,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +48989,28160,Female,Loyal Customer,59,Business travel,Eco,434,4,1,4,4,1,2,4,4,4,4,4,1,4,5,0,1.0,satisfied +48990,90335,Male,Loyal Customer,49,Business travel,Business,404,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +48991,29358,Male,Loyal Customer,59,Business travel,Business,2404,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,2.0,satisfied +48992,88795,Male,Loyal Customer,47,Business travel,Business,1797,1,1,1,1,4,4,4,2,2,2,2,3,2,4,0,4.0,satisfied +48993,82286,Male,Loyal Customer,21,Personal Travel,Eco,1481,4,2,4,4,5,4,5,5,4,1,4,3,4,5,15,66.0,neutral or dissatisfied +48994,4649,Female,disloyal Customer,64,Business travel,Business,364,5,5,5,3,2,5,2,2,3,5,5,4,4,2,0,0.0,satisfied +48995,19802,Female,disloyal Customer,28,Business travel,Business,528,2,2,2,3,3,2,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +48996,43393,Female,Loyal Customer,12,Personal Travel,Eco,463,3,4,3,4,2,3,2,2,4,5,5,5,5,2,0,3.0,neutral or dissatisfied +48997,89993,Male,Loyal Customer,45,Business travel,Business,983,1,1,3,1,2,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +48998,81479,Male,Loyal Customer,41,Business travel,Business,528,3,1,3,3,4,3,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +48999,12159,Male,Loyal Customer,45,Business travel,Eco,1042,5,1,1,1,5,5,5,5,2,4,5,2,4,5,2,0.0,satisfied +49000,28259,Male,Loyal Customer,43,Business travel,Business,3334,1,3,3,3,4,4,3,1,1,1,1,4,1,1,37,30.0,neutral or dissatisfied +49001,31901,Male,Loyal Customer,41,Business travel,Business,3400,4,4,4,4,5,5,5,4,4,4,4,3,4,3,0,2.0,satisfied +49002,60873,Male,Loyal Customer,19,Personal Travel,Eco Plus,1491,1,2,1,3,2,1,1,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +49003,88457,Male,Loyal Customer,28,Business travel,Business,3680,5,5,5,5,5,5,5,5,4,5,1,4,3,5,0,17.0,satisfied +49004,17067,Male,Loyal Customer,56,Business travel,Eco,282,4,1,1,1,4,4,4,4,1,4,2,4,4,4,0,0.0,satisfied +49005,65328,Female,Loyal Customer,35,Business travel,Business,631,4,4,4,4,3,5,4,5,5,5,5,5,5,4,82,77.0,satisfied +49006,2176,Male,Loyal Customer,46,Business travel,Eco,685,3,1,1,1,3,3,3,3,2,5,1,3,2,3,4,17.0,neutral or dissatisfied +49007,35998,Male,Loyal Customer,51,Business travel,Business,1529,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +49008,114597,Male,disloyal Customer,26,Business travel,Business,362,4,0,4,2,2,4,2,2,4,2,5,3,4,2,2,0.0,satisfied +49009,122359,Male,Loyal Customer,27,Business travel,Business,529,2,2,2,2,2,1,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +49010,70303,Male,Loyal Customer,58,Business travel,Business,334,4,4,4,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +49011,93886,Female,Loyal Customer,58,Business travel,Eco,590,2,3,2,3,5,3,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +49012,56108,Female,Loyal Customer,12,Personal Travel,Eco,2402,3,0,2,3,1,2,1,1,4,5,4,4,5,1,6,0.0,neutral or dissatisfied +49013,119498,Female,Loyal Customer,56,Business travel,Business,759,4,4,4,4,3,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +49014,109413,Female,disloyal Customer,35,Business travel,Business,861,4,4,4,3,5,4,5,5,5,4,4,3,5,5,128,118.0,neutral or dissatisfied +49015,41735,Female,Loyal Customer,55,Business travel,Eco,695,3,4,4,4,2,4,3,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +49016,60148,Female,disloyal Customer,37,Business travel,Eco,720,3,3,3,1,1,3,1,1,4,4,1,5,2,1,0,0.0,neutral or dissatisfied +49017,38697,Male,disloyal Customer,23,Business travel,Eco,1488,2,2,2,4,5,2,5,5,1,5,5,4,2,5,6,0.0,neutral or dissatisfied +49018,105912,Male,Loyal Customer,29,Personal Travel,Eco,283,1,1,1,3,2,1,2,2,3,3,4,2,3,2,2,11.0,neutral or dissatisfied +49019,67775,Male,disloyal Customer,28,Business travel,Eco,1205,4,4,4,3,4,4,4,4,2,3,2,2,2,4,30,45.0,neutral or dissatisfied +49020,35561,Female,disloyal Customer,37,Business travel,Eco Plus,972,3,3,3,1,3,3,3,3,3,5,2,1,3,3,62,42.0,neutral or dissatisfied +49021,123205,Female,Loyal Customer,18,Personal Travel,Eco,507,1,1,2,3,3,2,3,3,2,1,3,4,4,3,27,32.0,neutral or dissatisfied +49022,120711,Male,Loyal Customer,55,Personal Travel,Eco Plus,280,1,4,1,2,2,1,2,2,5,2,5,5,4,2,73,81.0,neutral or dissatisfied +49023,32663,Female,Loyal Customer,43,Business travel,Eco,101,5,4,4,4,2,3,1,5,5,5,5,1,5,1,0,0.0,satisfied +49024,122399,Male,Loyal Customer,40,Business travel,Business,3162,1,1,1,1,2,4,4,4,4,4,4,3,4,4,62,54.0,satisfied +49025,67421,Male,disloyal Customer,21,Business travel,Eco,641,3,3,3,3,1,3,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +49026,90418,Female,Loyal Customer,53,Business travel,Business,545,4,4,4,4,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +49027,27696,Female,Loyal Customer,55,Personal Travel,Eco,1107,4,1,4,3,3,2,3,1,1,4,1,3,1,2,0,0.0,neutral or dissatisfied +49028,27930,Female,disloyal Customer,25,Business travel,Business,1770,3,5,3,2,1,3,1,1,4,2,3,5,4,1,0,0.0,neutral or dissatisfied +49029,37076,Male,Loyal Customer,10,Personal Travel,Eco,1072,3,4,3,2,1,3,1,1,5,4,5,3,5,1,18,0.0,neutral or dissatisfied +49030,68909,Female,Loyal Customer,47,Personal Travel,Eco,1061,2,4,2,2,5,5,5,5,5,2,1,5,5,4,0,12.0,neutral or dissatisfied +49031,115155,Male,disloyal Customer,38,Business travel,Eco,296,3,3,3,3,1,3,1,1,4,3,3,4,3,1,0,0.0,neutral or dissatisfied +49032,45510,Female,Loyal Customer,38,Business travel,Business,3709,1,3,3,3,5,3,3,1,1,1,1,2,1,4,0,3.0,neutral or dissatisfied +49033,11440,Female,disloyal Customer,22,Business travel,Business,140,5,2,5,5,2,5,2,2,4,3,5,5,4,2,2,0.0,satisfied +49034,110369,Male,Loyal Customer,38,Business travel,Business,1730,4,4,1,4,2,5,5,4,4,4,4,5,4,3,12,11.0,satisfied +49035,5209,Male,Loyal Customer,39,Business travel,Business,3625,5,5,5,5,5,5,4,5,5,5,5,4,5,4,2,1.0,satisfied +49036,66081,Female,Loyal Customer,59,Personal Travel,Eco,1055,2,4,2,3,4,4,4,2,2,2,2,3,2,5,9,0.0,neutral or dissatisfied +49037,49213,Male,disloyal Customer,32,Business travel,Eco,158,1,5,2,3,4,2,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +49038,57264,Male,Loyal Customer,22,Business travel,Business,3011,3,3,3,3,3,3,3,3,2,3,2,2,3,3,1,0.0,neutral or dissatisfied +49039,74057,Female,Loyal Customer,52,Business travel,Business,2527,4,4,4,4,4,4,4,5,4,5,4,4,5,4,0,0.0,satisfied +49040,32654,Male,disloyal Customer,68,Business travel,Eco,163,2,2,2,3,4,2,4,4,1,1,2,1,3,4,0,9.0,neutral or dissatisfied +49041,43214,Female,Loyal Customer,36,Business travel,Eco,472,4,3,3,3,4,4,4,4,5,4,2,3,2,4,0,0.0,satisfied +49042,119414,Male,Loyal Customer,16,Business travel,Business,399,2,5,5,5,2,2,2,2,1,4,3,1,2,2,0,0.0,neutral or dissatisfied +49043,112203,Male,disloyal Customer,22,Business travel,Eco,649,3,1,3,3,2,3,5,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +49044,26806,Male,Loyal Customer,68,Personal Travel,Eco,2139,2,5,2,4,1,2,1,1,3,5,4,5,5,1,37,23.0,neutral or dissatisfied +49045,73408,Female,disloyal Customer,34,Business travel,Eco,1012,2,2,2,5,3,2,3,3,1,2,1,2,4,3,1,0.0,neutral or dissatisfied +49046,74237,Male,Loyal Customer,45,Business travel,Business,1007,4,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +49047,99731,Female,disloyal Customer,25,Business travel,Business,255,1,0,1,3,1,3,3,5,5,5,4,3,4,3,198,185.0,neutral or dissatisfied +49048,101993,Female,Loyal Customer,21,Personal Travel,Eco,628,1,4,0,4,4,0,4,4,2,5,1,5,1,4,13,0.0,neutral or dissatisfied +49049,82688,Female,disloyal Customer,8,Business travel,Eco,632,1,1,2,3,2,2,1,2,4,2,4,4,3,2,5,0.0,neutral or dissatisfied +49050,109392,Male,Loyal Customer,10,Personal Travel,Eco,1189,0,5,0,2,1,0,5,1,3,4,5,3,5,1,7,0.0,satisfied +49051,71296,Male,Loyal Customer,14,Personal Travel,Eco Plus,733,4,1,4,1,4,4,4,4,1,2,1,1,2,4,23,26.0,neutral or dissatisfied +49052,63786,Male,Loyal Customer,27,Business travel,Business,1721,3,3,3,3,4,4,4,4,5,2,4,1,1,4,0,0.0,satisfied +49053,63407,Female,Loyal Customer,52,Personal Travel,Eco,337,4,5,4,1,5,5,5,2,2,4,5,3,2,4,6,0.0,neutral or dissatisfied +49054,44602,Female,Loyal Customer,40,Business travel,Business,508,3,3,3,3,3,4,4,5,5,5,5,2,5,1,0,26.0,satisfied +49055,108783,Male,Loyal Customer,33,Business travel,Business,406,4,3,3,3,4,4,4,4,1,4,4,4,4,4,13,12.0,neutral or dissatisfied +49056,10778,Female,Loyal Customer,56,Business travel,Business,2531,4,4,4,4,2,4,4,4,4,4,5,5,4,5,1,0.0,satisfied +49057,126019,Male,disloyal Customer,23,Business travel,Business,600,4,0,4,2,1,4,1,1,5,5,4,4,4,1,12,9.0,satisfied +49058,86027,Male,Loyal Customer,72,Business travel,Eco,447,5,1,1,1,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +49059,7838,Male,Loyal Customer,9,Personal Travel,Eco Plus,710,4,5,5,2,5,5,5,5,4,3,5,4,4,5,17,11.0,neutral or dissatisfied +49060,95870,Female,disloyal Customer,23,Business travel,Business,759,5,0,5,4,4,5,4,4,5,3,5,5,4,4,0,0.0,satisfied +49061,114630,Male,Loyal Customer,58,Business travel,Business,362,5,2,5,5,5,5,5,4,4,4,4,3,4,3,6,7.0,satisfied +49062,60232,Male,Loyal Customer,16,Business travel,Eco,1546,3,3,3,3,3,3,2,3,2,1,3,3,4,3,17,7.0,neutral or dissatisfied +49063,17460,Male,Loyal Customer,53,Business travel,Eco,677,5,1,1,1,5,5,5,5,5,5,1,5,3,5,6,17.0,satisfied +49064,64185,Female,Loyal Customer,33,Business travel,Business,3271,2,5,5,5,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +49065,53617,Male,Loyal Customer,41,Business travel,Business,1874,2,1,1,1,1,2,3,2,2,2,2,1,2,3,84,69.0,neutral or dissatisfied +49066,17239,Male,disloyal Customer,36,Business travel,Business,1092,2,2,2,1,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +49067,55758,Female,Loyal Customer,46,Business travel,Business,1737,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +49068,28039,Female,Loyal Customer,44,Business travel,Business,1037,2,2,2,2,4,1,5,4,4,5,4,5,4,3,0,0.0,satisfied +49069,63729,Female,disloyal Customer,43,Business travel,Eco,160,2,4,2,3,1,2,1,1,1,1,4,3,3,1,0,4.0,neutral or dissatisfied +49070,95596,Female,disloyal Customer,21,Business travel,Eco,822,3,3,3,3,4,3,2,4,2,2,4,2,3,4,0,0.0,neutral or dissatisfied +49071,92520,Female,Loyal Customer,18,Personal Travel,Eco,2139,4,5,4,1,1,4,5,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +49072,43077,Male,Loyal Customer,54,Personal Travel,Eco,192,1,5,1,1,5,1,5,5,2,4,1,3,1,5,115,109.0,neutral or dissatisfied +49073,21036,Male,Loyal Customer,48,Business travel,Business,2393,1,1,1,1,2,1,5,4,4,4,4,2,4,5,0,0.0,satisfied +49074,63179,Male,Loyal Customer,59,Business travel,Business,447,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,5.0,satisfied +49075,101263,Male,Loyal Customer,43,Business travel,Business,1910,1,1,1,1,5,4,5,2,2,2,2,5,2,3,8,0.0,satisfied +49076,57655,Female,Loyal Customer,20,Personal Travel,Eco,200,1,3,1,2,3,1,3,3,2,2,5,3,1,3,51,48.0,neutral or dissatisfied +49077,75901,Male,Loyal Customer,56,Business travel,Eco,597,3,1,2,1,3,3,3,3,3,4,4,1,3,3,113,111.0,neutral or dissatisfied +49078,113022,Male,disloyal Customer,23,Business travel,Business,169,1,2,1,3,2,1,2,2,1,2,4,1,4,2,1,0.0,neutral or dissatisfied +49079,38704,Female,disloyal Customer,23,Business travel,Eco,954,5,5,5,1,5,5,5,5,5,4,5,3,4,5,77,102.0,satisfied +49080,125829,Female,Loyal Customer,35,Business travel,Business,3155,1,4,1,4,1,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +49081,18084,Male,Loyal Customer,24,Personal Travel,Eco,488,3,1,3,4,3,3,3,3,1,4,2,3,4,3,3,0.0,neutral or dissatisfied +49082,63885,Male,Loyal Customer,49,Business travel,Business,1820,3,3,3,3,3,4,5,3,3,4,3,3,3,5,0,2.0,satisfied +49083,52419,Male,Loyal Customer,9,Personal Travel,Eco,355,3,5,3,4,2,3,2,2,5,3,5,3,4,2,0,3.0,neutral or dissatisfied +49084,124826,Female,disloyal Customer,23,Business travel,Eco,280,4,0,4,5,2,4,2,2,4,4,4,3,1,2,0,0.0,neutral or dissatisfied +49085,89460,Female,Loyal Customer,12,Personal Travel,Eco,134,3,2,0,3,1,0,4,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +49086,85297,Female,Loyal Customer,25,Personal Travel,Eco,731,1,4,1,3,2,1,2,2,4,3,4,1,4,2,20,10.0,neutral or dissatisfied +49087,47152,Male,Loyal Customer,39,Business travel,Business,1534,1,1,1,1,5,2,4,5,5,5,5,2,5,5,0,0.0,satisfied +49088,55748,Male,Loyal Customer,39,Business travel,Business,1737,2,2,2,2,4,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +49089,49971,Male,Loyal Customer,40,Business travel,Business,110,2,2,2,2,1,2,5,4,4,4,5,2,4,3,0,0.0,satisfied +49090,77851,Female,Loyal Customer,16,Personal Travel,Eco Plus,731,0,1,0,2,2,0,2,2,3,3,2,4,3,2,0,0.0,satisfied +49091,52628,Female,disloyal Customer,16,Business travel,Eco,160,2,0,2,4,4,2,4,4,4,1,5,2,1,4,0,0.0,neutral or dissatisfied +49092,16669,Female,Loyal Customer,53,Personal Travel,Eco,488,3,4,3,3,2,4,4,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +49093,23219,Male,Loyal Customer,37,Personal Travel,Eco,326,1,3,1,4,5,1,5,5,4,4,3,4,4,5,30,26.0,neutral or dissatisfied +49094,9488,Female,disloyal Customer,39,Business travel,Business,239,5,5,5,4,5,5,5,5,5,2,5,4,4,5,0,45.0,satisfied +49095,71577,Female,disloyal Customer,39,Business travel,Business,1120,2,2,2,3,1,2,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +49096,127447,Female,Loyal Customer,56,Personal Travel,Eco Plus,1009,4,1,4,3,4,4,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +49097,5684,Male,disloyal Customer,39,Business travel,Eco,196,3,2,3,3,2,3,2,2,3,5,3,3,3,2,42,31.0,neutral or dissatisfied +49098,107934,Female,Loyal Customer,48,Business travel,Eco,611,2,1,1,1,3,3,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +49099,124902,Male,Loyal Customer,60,Business travel,Business,728,3,3,3,3,2,4,4,4,4,4,4,4,4,4,11,7.0,satisfied +49100,100602,Male,Loyal Customer,30,Business travel,Business,2402,3,2,5,2,3,2,3,3,1,1,3,4,4,3,0,6.0,neutral or dissatisfied +49101,23332,Male,Loyal Customer,25,Personal Travel,Eco,809,3,3,3,3,3,3,3,3,1,2,3,1,3,3,63,70.0,neutral or dissatisfied +49102,41210,Male,Loyal Customer,52,Business travel,Eco,1091,5,5,5,5,5,5,5,5,5,3,2,3,1,5,0,0.0,satisfied +49103,107728,Female,Loyal Customer,41,Personal Travel,Eco,251,1,1,1,3,5,1,5,5,1,4,3,1,2,5,1,0.0,neutral or dissatisfied +49104,23591,Male,disloyal Customer,50,Business travel,Eco,1024,3,3,3,1,1,3,1,1,1,2,4,1,4,1,1,21.0,neutral or dissatisfied +49105,102351,Male,disloyal Customer,62,Business travel,Eco,386,3,2,3,3,2,3,2,2,4,2,4,2,3,2,1,0.0,neutral or dissatisfied +49106,633,Female,Loyal Customer,53,Business travel,Business,3785,5,5,5,5,4,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +49107,118350,Female,Loyal Customer,58,Personal Travel,Eco,602,2,3,1,5,5,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +49108,469,Male,Loyal Customer,48,Business travel,Business,3617,0,5,0,4,2,5,5,3,3,3,3,5,3,4,0,15.0,satisfied +49109,6862,Male,Loyal Customer,46,Business travel,Business,622,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +49110,43276,Male,disloyal Customer,24,Business travel,Eco,463,4,5,4,1,4,4,4,4,5,1,5,5,3,4,5,0.0,neutral or dissatisfied +49111,90761,Male,Loyal Customer,58,Business travel,Business,594,1,1,1,1,5,4,5,4,4,4,4,5,4,4,42,35.0,satisfied +49112,9815,Female,Loyal Customer,23,Personal Travel,Eco,955,2,3,2,3,2,2,2,2,1,3,3,4,4,2,4,0.0,neutral or dissatisfied +49113,118846,Male,disloyal Customer,20,Business travel,Eco Plus,646,2,2,2,3,3,2,3,3,2,2,4,4,3,3,34,32.0,neutral or dissatisfied +49114,30730,Female,Loyal Customer,28,Business travel,Eco,1069,0,0,0,5,2,0,2,2,5,5,1,3,3,2,2,4.0,satisfied +49115,107501,Male,Loyal Customer,16,Personal Travel,Eco,711,1,5,1,1,2,1,2,2,5,4,1,3,2,2,91,79.0,neutral or dissatisfied +49116,68529,Female,disloyal Customer,26,Business travel,Business,1013,5,5,5,5,1,5,1,1,5,3,4,3,5,1,0,0.0,satisfied +49117,95361,Female,Loyal Customer,58,Personal Travel,Eco,677,2,3,2,4,4,4,3,1,1,2,1,2,1,1,17,0.0,neutral or dissatisfied +49118,73000,Female,Loyal Customer,59,Personal Travel,Eco,1096,3,3,3,3,4,3,3,5,5,3,5,3,5,1,3,0.0,neutral or dissatisfied +49119,79090,Male,Loyal Customer,58,Personal Travel,Eco,356,3,4,3,2,5,3,1,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +49120,76410,Male,Loyal Customer,21,Personal Travel,Business,405,3,5,3,4,3,3,1,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +49121,88615,Female,Loyal Customer,70,Personal Travel,Eco,581,2,5,2,3,4,5,5,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +49122,33090,Female,Loyal Customer,69,Personal Travel,Eco,101,1,5,1,2,3,5,5,2,2,1,2,3,2,3,12,17.0,neutral or dissatisfied +49123,10369,Male,disloyal Customer,38,Business travel,Business,667,5,4,4,3,4,1,3,4,3,5,4,3,4,3,173,178.0,satisfied +49124,743,Female,Loyal Customer,52,Business travel,Business,1975,0,0,0,4,5,5,4,1,1,1,1,4,1,3,0,0.0,satisfied +49125,51571,Male,disloyal Customer,25,Business travel,Eco,425,2,0,2,2,5,2,5,5,1,2,4,1,2,5,0,0.0,neutral or dissatisfied +49126,73849,Male,Loyal Customer,56,Business travel,Eco,1810,1,3,3,3,1,1,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +49127,31760,Female,Loyal Customer,12,Business travel,Business,2036,3,3,3,3,4,4,4,4,5,4,2,3,2,4,0,1.0,satisfied +49128,28264,Female,Loyal Customer,35,Personal Travel,Eco,1542,1,4,1,5,5,1,1,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +49129,51968,Male,Loyal Customer,41,Business travel,Eco,936,1,1,1,1,1,1,1,1,1,3,1,1,2,1,0,0.0,neutral or dissatisfied +49130,104900,Female,Loyal Customer,22,Business travel,Business,1565,3,3,3,3,5,5,5,5,5,4,5,3,4,5,1,0.0,satisfied +49131,56097,Male,Loyal Customer,29,Business travel,Business,2402,5,5,5,5,4,4,4,5,2,5,5,4,4,4,154,204.0,satisfied +49132,70904,Male,disloyal Customer,39,Business travel,Business,221,4,4,4,3,4,4,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +49133,111068,Male,Loyal Customer,50,Personal Travel,Eco,319,3,3,3,1,1,3,1,1,3,2,3,4,5,1,16,22.0,neutral or dissatisfied +49134,73791,Female,Loyal Customer,51,Business travel,Business,204,4,4,4,4,2,5,5,5,5,5,5,5,5,5,1,8.0,satisfied +49135,4054,Female,Loyal Customer,10,Personal Travel,Eco,483,1,0,1,2,3,1,5,3,4,5,5,5,4,3,24,2.0,neutral or dissatisfied +49136,84722,Female,Loyal Customer,30,Business travel,Business,534,5,5,5,5,4,4,4,4,5,3,4,4,4,4,1,0.0,satisfied +49137,9756,Male,Loyal Customer,15,Business travel,Business,1621,2,2,2,2,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +49138,51862,Male,disloyal Customer,37,Business travel,Eco,522,5,0,5,4,2,5,4,2,5,3,3,2,1,2,0,18.0,satisfied +49139,70490,Male,Loyal Customer,42,Business travel,Eco,867,2,1,1,1,2,2,2,2,4,5,2,2,1,2,1,35.0,neutral or dissatisfied +49140,7356,Female,Loyal Customer,32,Personal Travel,Eco,864,3,4,3,3,5,3,5,5,5,3,3,1,2,5,22,20.0,neutral or dissatisfied +49141,126933,Male,disloyal Customer,23,Business travel,Business,304,4,0,4,4,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +49142,17314,Male,Loyal Customer,33,Business travel,Eco,403,3,3,3,3,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +49143,48135,Female,disloyal Customer,40,Business travel,Business,259,5,5,5,1,4,5,5,4,3,3,5,4,2,4,16,9.0,satisfied +49144,74915,Male,disloyal Customer,27,Business travel,Business,1106,5,5,5,1,5,2,2,3,5,4,5,2,5,2,272,262.0,satisfied +49145,28794,Female,Loyal Customer,63,Personal Travel,Business,978,3,4,3,1,3,5,4,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +49146,90365,Female,Loyal Customer,58,Business travel,Business,515,5,5,5,5,4,4,5,4,4,4,4,4,4,5,53,43.0,satisfied +49147,87585,Male,Loyal Customer,49,Personal Travel,Eco,432,1,4,1,1,5,1,5,5,3,2,4,5,4,5,6,0.0,neutral or dissatisfied +49148,18433,Male,Loyal Customer,59,Business travel,Business,127,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +49149,22337,Male,Loyal Customer,39,Business travel,Eco,238,4,3,3,3,4,4,4,4,3,2,3,5,2,4,0,0.0,satisfied +49150,128867,Female,Loyal Customer,47,Business travel,Business,2454,2,2,2,2,4,4,4,5,5,5,4,4,4,4,0,0.0,satisfied +49151,72263,Female,Loyal Customer,40,Business travel,Eco,919,2,1,1,1,2,3,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +49152,42223,Male,disloyal Customer,62,Business travel,Eco,329,2,0,2,5,4,2,3,4,4,1,4,5,3,4,39,36.0,neutral or dissatisfied +49153,99177,Male,Loyal Customer,47,Business travel,Business,351,4,3,4,4,5,4,4,4,4,4,4,3,4,3,14,14.0,satisfied +49154,120595,Female,Loyal Customer,28,Personal Travel,Eco,980,3,4,3,3,4,3,1,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +49155,23639,Male,Loyal Customer,41,Personal Travel,Eco,911,3,5,3,4,1,3,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +49156,53695,Male,disloyal Customer,23,Business travel,Eco,1190,3,3,3,2,1,3,1,1,2,3,2,2,2,1,2,8.0,neutral or dissatisfied +49157,48569,Male,Loyal Customer,23,Personal Travel,Eco,737,3,4,3,3,3,3,3,3,4,5,2,4,4,3,1,0.0,neutral or dissatisfied +49158,80714,Male,Loyal Customer,37,Business travel,Business,2483,2,2,2,2,2,3,4,2,2,1,2,3,2,2,0,1.0,neutral or dissatisfied +49159,76445,Male,Loyal Customer,43,Business travel,Business,2560,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +49160,2576,Male,Loyal Customer,65,Business travel,Business,3018,2,2,2,2,1,2,3,4,4,4,4,4,4,1,40,41.0,satisfied +49161,107421,Female,disloyal Customer,25,Business travel,Eco,123,2,0,2,5,1,2,1,1,1,1,2,2,4,1,2,1.0,neutral or dissatisfied +49162,370,Male,Loyal Customer,49,Business travel,Business,3770,1,1,1,1,4,5,4,5,5,5,4,5,5,4,0,0.0,satisfied +49163,35819,Female,Loyal Customer,23,Business travel,Eco,1068,4,2,3,3,4,4,4,4,5,4,5,2,5,4,0,0.0,satisfied +49164,87062,Male,Loyal Customer,43,Business travel,Business,3849,5,5,5,5,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +49165,64160,Female,Loyal Customer,59,Business travel,Eco,589,3,4,4,4,4,2,1,3,3,3,3,4,3,2,44,26.0,neutral or dissatisfied +49166,7194,Female,Loyal Customer,46,Business travel,Business,2620,4,4,4,4,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +49167,88307,Male,Loyal Customer,41,Business travel,Business,406,2,2,5,2,4,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +49168,126071,Female,Loyal Customer,45,Business travel,Business,1946,3,3,4,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +49169,54363,Female,Loyal Customer,32,Personal Travel,Eco,1235,1,3,1,1,5,1,1,5,5,5,3,5,3,5,3,0.0,neutral or dissatisfied +49170,22160,Female,Loyal Customer,30,Business travel,Business,2835,5,5,5,5,4,4,4,4,3,3,4,5,1,4,0,0.0,satisfied +49171,113383,Male,Loyal Customer,54,Business travel,Business,2720,4,4,2,4,5,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +49172,101948,Male,Loyal Customer,17,Business travel,Business,1639,3,3,3,3,4,4,4,4,2,5,5,4,3,4,258,252.0,satisfied +49173,124342,Male,Loyal Customer,51,Business travel,Business,637,4,4,2,4,2,3,1,3,3,4,3,3,3,4,0,0.0,satisfied +49174,4544,Female,disloyal Customer,38,Business travel,Eco,719,2,2,2,3,4,2,4,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +49175,28856,Male,Loyal Customer,42,Business travel,Business,1544,5,5,5,5,4,1,3,5,5,5,5,5,5,3,0,0.0,satisfied +49176,89922,Male,disloyal Customer,14,Business travel,Eco,1310,1,1,1,3,4,1,1,4,1,1,3,2,3,4,11,9.0,neutral or dissatisfied +49177,73497,Male,Loyal Customer,23,Personal Travel,Eco,1197,3,2,3,4,3,3,3,3,1,4,2,2,4,3,0,2.0,neutral or dissatisfied +49178,840,Female,Loyal Customer,51,Business travel,Business,229,2,1,1,1,5,3,3,2,2,2,2,3,2,4,12,4.0,neutral or dissatisfied +49179,41849,Male,Loyal Customer,31,Business travel,Eco,483,5,4,4,4,5,5,5,2,2,1,4,5,3,5,126,139.0,satisfied +49180,95298,Male,Loyal Customer,10,Personal Travel,Eco,248,2,5,0,1,2,0,5,2,3,3,5,3,5,2,69,71.0,neutral or dissatisfied +49181,77249,Male,Loyal Customer,59,Business travel,Business,1590,1,1,4,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +49182,90879,Male,Loyal Customer,52,Business travel,Business,270,2,3,3,3,1,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +49183,54910,Male,Loyal Customer,56,Business travel,Business,2689,2,5,2,2,2,4,4,4,4,4,4,4,4,3,0,6.0,satisfied +49184,23895,Female,Loyal Customer,61,Business travel,Business,579,3,3,1,1,3,3,3,3,3,3,3,4,3,4,0,11.0,neutral or dissatisfied +49185,4481,Female,Loyal Customer,57,Business travel,Eco,747,4,2,2,2,5,3,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +49186,3682,Male,Loyal Customer,16,Business travel,Business,431,3,2,2,2,3,3,3,3,4,2,3,4,3,3,2,0.0,neutral or dissatisfied +49187,31243,Male,Loyal Customer,48,Business travel,Eco,472,5,3,3,3,5,5,5,5,1,4,4,5,3,5,0,0.0,satisfied +49188,43014,Male,Loyal Customer,52,Business travel,Business,2229,1,2,2,2,3,3,2,2,2,2,1,2,2,3,0,0.0,neutral or dissatisfied +49189,60671,Female,Loyal Customer,38,Business travel,Business,1620,1,1,1,1,2,3,5,5,5,5,5,3,5,4,7,3.0,satisfied +49190,37866,Female,Loyal Customer,36,Business travel,Business,1902,3,1,3,1,5,4,3,3,3,3,3,3,3,2,34,46.0,neutral or dissatisfied +49191,36545,Male,disloyal Customer,29,Business travel,Eco,1249,1,1,1,5,5,1,5,5,1,5,5,2,2,5,0,0.0,neutral or dissatisfied +49192,126063,Male,Loyal Customer,42,Business travel,Business,507,5,5,5,5,5,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +49193,120625,Female,Loyal Customer,52,Business travel,Business,2142,0,0,0,4,5,5,4,2,2,2,2,5,2,3,15,8.0,satisfied +49194,50729,Female,Loyal Customer,21,Personal Travel,Eco,190,1,4,1,3,2,1,2,2,5,4,4,3,4,2,93,105.0,neutral or dissatisfied +49195,124012,Male,Loyal Customer,17,Business travel,Business,184,1,5,5,5,3,3,1,3,2,2,3,3,4,3,15,0.0,neutral or dissatisfied +49196,8877,Male,disloyal Customer,10,Business travel,Eco,622,3,3,3,3,3,3,3,3,1,2,4,1,4,3,0,11.0,neutral or dissatisfied +49197,125343,Male,disloyal Customer,28,Business travel,Business,599,5,5,5,5,4,5,4,4,5,3,5,5,4,4,1,4.0,satisfied +49198,46433,Male,Loyal Customer,30,Business travel,Eco Plus,649,1,5,4,5,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +49199,62367,Male,Loyal Customer,49,Business travel,Business,2704,1,1,4,1,5,4,5,4,4,4,4,3,4,3,69,48.0,satisfied +49200,64377,Female,Loyal Customer,52,Personal Travel,Eco,1192,5,5,5,2,2,4,4,5,5,5,5,1,5,5,9,0.0,satisfied +49201,14904,Female,Loyal Customer,9,Personal Travel,Eco,296,3,5,3,2,3,5,5,3,2,4,4,5,5,5,142,147.0,neutral or dissatisfied +49202,85165,Female,Loyal Customer,29,Business travel,Business,1717,4,4,3,4,4,3,4,4,1,3,3,4,4,4,7,8.0,neutral or dissatisfied +49203,38486,Female,Loyal Customer,41,Business travel,Business,2446,4,5,4,4,4,3,4,4,4,4,4,3,4,5,18,0.0,satisfied +49204,95638,Male,Loyal Customer,61,Personal Travel,Eco,670,2,4,2,2,2,2,2,2,4,4,4,5,5,2,5,0.0,neutral or dissatisfied +49205,118580,Female,Loyal Customer,42,Business travel,Business,370,3,3,3,3,4,5,4,4,4,4,4,4,4,5,24,22.0,satisfied +49206,42219,Male,Loyal Customer,51,Business travel,Business,550,4,4,4,4,3,2,2,4,4,4,4,1,4,5,29,20.0,satisfied +49207,80955,Male,Loyal Customer,62,Personal Travel,Eco,872,2,3,2,2,4,2,4,4,4,5,2,1,3,4,0,0.0,neutral or dissatisfied +49208,72029,Male,Loyal Customer,42,Business travel,Business,3784,4,4,4,4,4,4,4,4,2,4,5,4,3,4,0,0.0,satisfied +49209,75897,Male,Loyal Customer,56,Business travel,Business,603,5,5,5,5,4,4,5,5,5,5,5,5,5,3,89,86.0,satisfied +49210,113798,Male,disloyal Customer,27,Business travel,Business,223,3,3,3,4,5,3,5,5,4,5,3,3,4,5,12,9.0,neutral or dissatisfied +49211,85241,Female,Loyal Customer,47,Business travel,Eco,296,2,5,5,5,1,3,4,1,1,2,1,1,1,2,1,6.0,neutral or dissatisfied +49212,11213,Female,Loyal Customer,22,Personal Travel,Eco,312,3,2,4,3,1,4,1,1,1,4,3,3,3,1,0,6.0,neutral or dissatisfied +49213,123992,Male,disloyal Customer,20,Business travel,Business,184,0,0,0,4,3,0,3,3,3,3,4,5,5,3,0,0.0,satisfied +49214,120865,Male,disloyal Customer,30,Business travel,Business,951,3,3,3,2,5,3,3,5,3,2,5,3,5,5,2,8.0,neutral or dissatisfied +49215,106671,Female,Loyal Customer,9,Personal Travel,Business,451,3,4,3,3,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +49216,13301,Male,Loyal Customer,55,Personal Travel,Eco Plus,657,3,3,3,4,1,3,1,1,4,3,4,3,4,1,0,2.0,neutral or dissatisfied +49217,5616,Male,disloyal Customer,36,Business travel,Business,285,3,3,3,5,1,3,1,1,5,5,4,2,1,1,9,0.0,neutral or dissatisfied +49218,117703,Male,disloyal Customer,12,Business travel,Eco,792,2,2,2,4,5,2,4,5,4,3,4,5,4,5,12,4.0,neutral or dissatisfied +49219,72400,Female,Loyal Customer,46,Business travel,Business,2401,1,1,1,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +49220,28097,Male,disloyal Customer,36,Business travel,Eco,859,2,2,2,2,1,2,5,1,2,2,5,5,3,1,0,0.0,neutral or dissatisfied +49221,96661,Male,Loyal Customer,37,Personal Travel,Eco,972,1,1,1,3,5,1,5,5,4,1,4,4,4,5,20,11.0,neutral or dissatisfied +49222,60600,Female,Loyal Customer,30,Personal Travel,Eco Plus,1290,3,4,3,4,4,3,4,4,4,4,3,4,5,4,13,4.0,neutral or dissatisfied +49223,75533,Male,Loyal Customer,57,Business travel,Business,337,3,2,4,4,3,3,4,3,3,3,3,4,3,2,4,4.0,neutral or dissatisfied +49224,59173,Male,Loyal Customer,19,Personal Travel,Eco Plus,1846,3,2,2,3,1,2,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +49225,15605,Male,Loyal Customer,53,Business travel,Business,292,1,3,3,3,1,4,3,1,1,1,1,4,1,4,59,57.0,neutral or dissatisfied +49226,71806,Male,Loyal Customer,39,Business travel,Business,1652,1,1,1,1,2,3,4,3,3,3,3,3,3,5,3,0.0,satisfied +49227,41315,Female,disloyal Customer,25,Business travel,Eco,802,1,2,2,1,4,2,3,4,1,2,2,5,2,4,0,0.0,neutral or dissatisfied +49228,26839,Female,Loyal Customer,39,Business travel,Business,1946,2,4,4,4,3,4,3,2,2,3,2,3,2,4,0,4.0,neutral or dissatisfied +49229,107621,Male,Loyal Customer,44,Business travel,Business,423,2,3,3,3,1,3,4,2,2,2,2,1,2,2,31,18.0,neutral or dissatisfied +49230,93042,Female,Loyal Customer,43,Business travel,Eco,436,1,4,4,4,2,4,3,1,1,1,1,4,1,4,0,6.0,neutral or dissatisfied +49231,81500,Male,Loyal Customer,27,Personal Travel,Eco,528,4,5,2,1,2,1,1,3,3,4,4,1,4,1,214,204.0,neutral or dissatisfied +49232,71187,Male,disloyal Customer,19,Business travel,Eco,733,3,3,3,3,5,3,5,5,5,3,4,4,5,5,79,65.0,neutral or dissatisfied +49233,42132,Female,Loyal Customer,9,Personal Travel,Eco Plus,996,2,5,2,3,1,2,1,1,3,2,4,5,4,1,13,9.0,neutral or dissatisfied +49234,73064,Male,Loyal Customer,20,Personal Travel,Eco Plus,1089,2,5,2,4,3,2,3,3,2,5,5,2,3,3,29,24.0,neutral or dissatisfied +49235,108672,Male,Loyal Customer,31,Business travel,Business,1846,2,2,2,2,2,2,2,2,4,5,3,4,3,2,13,6.0,neutral or dissatisfied +49236,45771,Male,Loyal Customer,40,Business travel,Business,3695,1,1,1,1,4,3,1,5,5,5,5,2,5,5,0,0.0,satisfied +49237,96572,Female,Loyal Customer,57,Business travel,Eco,333,4,4,4,4,1,4,5,4,4,4,4,3,4,2,6,1.0,satisfied +49238,53428,Female,Loyal Customer,26,Business travel,Business,2288,3,3,3,3,2,2,2,4,3,5,2,2,3,2,1,23.0,satisfied +49239,109254,Male,disloyal Customer,34,Business travel,Business,684,1,1,1,2,5,1,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +49240,86253,Male,Loyal Customer,43,Personal Travel,Eco,356,3,1,3,4,5,3,5,5,4,1,3,1,4,5,11,1.0,neutral or dissatisfied +49241,19581,Female,Loyal Customer,58,Personal Travel,Eco,173,1,4,1,3,3,3,4,1,1,1,5,1,1,2,5,6.0,neutral or dissatisfied +49242,49891,Female,disloyal Customer,40,Business travel,Business,308,3,3,3,1,4,3,4,4,2,3,3,4,2,4,0,0.0,satisfied +49243,74578,Female,Loyal Customer,42,Business travel,Eco,1242,1,1,1,1,2,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +49244,121826,Female,disloyal Customer,23,Business travel,Eco,366,1,0,1,3,4,1,4,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +49245,44661,Male,Loyal Customer,56,Business travel,Business,2090,1,3,3,3,2,4,4,3,3,3,1,3,3,3,0,0.0,neutral or dissatisfied +49246,46328,Male,Loyal Customer,55,Personal Travel,Eco,420,2,2,2,3,2,2,2,2,2,1,4,2,4,2,2,19.0,neutral or dissatisfied +49247,38487,Male,Loyal Customer,53,Business travel,Business,2475,5,5,5,5,3,4,5,5,5,5,5,5,5,4,3,0.0,satisfied +49248,80085,Female,Loyal Customer,40,Business travel,Eco Plus,647,4,1,1,1,4,4,4,4,5,1,2,3,1,4,0,0.0,satisfied +49249,56960,Female,disloyal Customer,22,Business travel,Eco,1018,4,4,4,4,5,4,3,5,5,4,1,5,2,5,21,4.0,neutral or dissatisfied +49250,122898,Female,Loyal Customer,25,Business travel,Business,650,2,2,4,2,5,5,5,5,3,3,4,4,4,5,0,1.0,satisfied +49251,39508,Female,Loyal Customer,25,Business travel,Business,3075,4,4,4,4,4,4,4,4,1,5,3,4,4,4,24,4.0,satisfied +49252,86346,Male,Loyal Customer,53,Business travel,Business,2210,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +49253,16927,Female,Loyal Customer,22,Business travel,Business,820,1,1,1,1,5,5,5,5,4,3,1,4,3,5,0,0.0,satisfied +49254,52834,Female,disloyal Customer,35,Business travel,Eco,1721,2,2,2,5,2,2,3,2,2,3,3,5,1,2,0,0.0,neutral or dissatisfied +49255,116493,Male,Loyal Customer,41,Personal Travel,Eco,337,2,5,2,1,2,2,5,2,5,5,4,4,4,2,4,0.0,neutral or dissatisfied +49256,74924,Male,disloyal Customer,49,Business travel,Eco,2475,2,2,2,4,2,2,2,2,1,3,2,2,4,2,13,0.0,neutral or dissatisfied +49257,100895,Male,disloyal Customer,19,Business travel,Business,377,4,4,4,3,3,4,5,3,3,5,5,4,5,3,37,42.0,satisfied +49258,37183,Male,Loyal Customer,8,Personal Travel,Eco,1189,2,2,2,2,1,2,1,1,1,2,1,4,2,1,0,0.0,neutral or dissatisfied +49259,61816,Male,Loyal Customer,60,Personal Travel,Eco,1379,2,4,2,1,4,2,4,4,5,2,4,2,1,4,0,0.0,neutral or dissatisfied +49260,116404,Female,Loyal Customer,62,Personal Travel,Eco,358,2,4,3,3,2,5,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +49261,88097,Female,disloyal Customer,29,Business travel,Eco,515,3,2,3,4,5,3,5,5,4,3,3,1,3,5,13,14.0,neutral or dissatisfied +49262,111406,Male,Loyal Customer,11,Personal Travel,Eco,1050,3,5,3,1,3,3,3,3,5,5,5,4,4,3,17,16.0,neutral or dissatisfied +49263,82720,Male,Loyal Customer,50,Personal Travel,Eco,632,4,5,4,3,3,4,1,3,5,2,5,3,5,3,3,0.0,neutral or dissatisfied +49264,53340,Male,disloyal Customer,46,Business travel,Eco,1145,2,2,2,2,5,2,3,5,2,2,2,4,1,5,35,52.0,neutral or dissatisfied +49265,83478,Male,disloyal Customer,29,Business travel,Business,946,3,3,3,2,4,3,4,4,5,5,5,4,5,4,29,12.0,neutral or dissatisfied +49266,6795,Male,Loyal Customer,62,Business travel,Business,3724,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +49267,55946,Male,Loyal Customer,53,Personal Travel,Business,1620,3,4,2,3,4,4,4,3,3,2,3,5,3,4,15,7.0,neutral or dissatisfied +49268,14834,Male,Loyal Customer,41,Business travel,Eco,261,5,4,4,4,5,5,5,5,1,1,5,5,4,5,0,0.0,satisfied +49269,47414,Female,Loyal Customer,27,Business travel,Business,588,4,4,4,4,4,4,4,4,2,2,3,1,2,4,0,0.0,neutral or dissatisfied +49270,116202,Female,Loyal Customer,32,Personal Travel,Eco,337,4,4,4,3,5,4,3,5,1,4,3,4,2,5,87,73.0,neutral or dissatisfied +49271,28053,Male,Loyal Customer,44,Business travel,Business,2603,5,5,5,5,5,5,5,3,4,5,5,5,4,5,0,9.0,satisfied +49272,16654,Male,Loyal Customer,42,Business travel,Eco,488,2,4,4,4,2,2,2,2,4,3,4,1,3,2,124,122.0,neutral or dissatisfied +49273,24428,Male,Loyal Customer,37,Personal Travel,Eco,634,1,5,1,1,1,1,1,1,3,2,5,5,5,1,4,9.0,neutral or dissatisfied +49274,69100,Male,Loyal Customer,42,Business travel,Business,1389,5,5,5,5,5,4,5,2,2,2,2,5,2,4,4,0.0,satisfied +49275,4489,Female,Loyal Customer,50,Personal Travel,Business,551,3,4,3,3,3,2,4,5,5,3,3,3,5,4,0,0.0,neutral or dissatisfied +49276,1940,Female,Loyal Customer,47,Business travel,Business,2157,0,1,1,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +49277,75646,Female,Loyal Customer,57,Business travel,Business,3644,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +49278,114816,Female,Loyal Customer,39,Business travel,Business,308,0,0,0,4,4,5,5,1,1,1,1,5,1,3,1,0.0,satisfied +49279,124876,Male,Loyal Customer,41,Business travel,Business,2835,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +49280,2303,Male,Loyal Customer,45,Business travel,Business,3362,4,4,3,4,5,5,5,3,3,2,3,5,3,5,264,272.0,satisfied +49281,75796,Male,Loyal Customer,50,Personal Travel,Eco,813,3,5,3,3,5,3,3,5,2,4,4,5,3,5,28,23.0,neutral or dissatisfied +49282,63397,Male,Loyal Customer,24,Personal Travel,Eco,372,1,0,1,5,1,1,1,1,1,4,4,5,1,1,9,10.0,neutral or dissatisfied +49283,64748,Male,disloyal Customer,42,Business travel,Business,247,2,2,2,3,1,2,1,1,5,3,4,4,4,1,0,4.0,neutral or dissatisfied +49284,33930,Male,Loyal Customer,44,Personal Travel,Business,1072,4,4,4,3,3,4,4,3,3,4,4,3,3,4,0,0.0,neutral or dissatisfied +49285,2661,Male,Loyal Customer,34,Business travel,Business,539,5,5,2,5,2,5,5,2,2,2,2,5,2,3,23,26.0,satisfied +49286,19339,Female,Loyal Customer,12,Personal Travel,Eco,694,2,5,2,5,2,2,2,2,4,2,5,4,4,2,12,8.0,neutral or dissatisfied +49287,1094,Female,Loyal Customer,52,Personal Travel,Eco,89,4,4,4,3,4,5,5,5,5,4,4,3,5,5,0,0.0,satisfied +49288,100192,Female,Loyal Customer,55,Personal Travel,Eco,725,3,4,3,4,4,3,4,2,2,3,2,4,2,3,15,0.0,neutral or dissatisfied +49289,69846,Female,Loyal Customer,69,Personal Travel,Eco,1055,3,4,3,3,4,5,4,4,4,3,4,4,4,3,5,0.0,neutral or dissatisfied +49290,76086,Female,disloyal Customer,22,Business travel,Eco,669,2,0,2,3,5,2,5,5,2,3,4,4,2,5,0,0.0,neutral or dissatisfied +49291,97708,Female,disloyal Customer,25,Business travel,Business,456,4,0,4,4,5,4,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +49292,24984,Male,disloyal Customer,42,Business travel,Eco,692,4,4,4,5,4,4,4,4,1,4,3,2,1,4,0,0.0,satisfied +49293,30590,Female,Loyal Customer,33,Personal Travel,Eco,628,3,4,3,3,2,3,2,2,5,1,1,4,3,2,114,107.0,neutral or dissatisfied +49294,16362,Female,Loyal Customer,58,Business travel,Eco,319,3,4,4,4,3,3,4,3,3,3,3,4,3,2,6,0.0,neutral or dissatisfied +49295,4939,Female,Loyal Customer,58,Personal Travel,Eco,268,3,2,3,3,5,3,4,2,2,3,2,3,2,3,13,34.0,neutral or dissatisfied +49296,92579,Male,Loyal Customer,70,Personal Travel,Eco Plus,2139,3,4,3,3,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +49297,72861,Female,disloyal Customer,8,Business travel,Eco,700,3,4,4,4,5,4,5,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +49298,22049,Female,Loyal Customer,50,Business travel,Eco,304,4,5,5,5,1,4,1,4,4,4,4,2,4,1,0,0.0,satisfied +49299,111960,Male,Loyal Customer,48,Business travel,Business,2405,4,4,4,4,3,4,4,5,5,5,5,3,5,3,10,12.0,satisfied +49300,26336,Female,Loyal Customer,50,Business travel,Business,1573,4,4,4,4,5,1,5,4,4,5,4,1,4,5,3,2.0,satisfied +49301,30752,Female,Loyal Customer,66,Personal Travel,Eco,977,2,4,2,3,2,4,5,1,1,2,4,5,1,3,0,6.0,neutral or dissatisfied +49302,67265,Female,Loyal Customer,14,Personal Travel,Eco,985,2,5,2,4,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +49303,31670,Female,Loyal Customer,69,Business travel,Eco,862,1,0,0,3,3,3,4,4,4,1,4,3,4,1,0,4.0,neutral or dissatisfied +49304,83339,Male,Loyal Customer,30,Personal Travel,Eco Plus,2105,3,0,3,3,4,3,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +49305,35969,Male,Loyal Customer,21,Personal Travel,Eco,231,2,4,2,3,2,2,2,2,4,5,3,3,4,2,1,0.0,neutral or dissatisfied +49306,95813,Male,Loyal Customer,24,Business travel,Eco Plus,1050,1,1,1,1,1,1,2,1,2,5,2,3,1,1,18,11.0,neutral or dissatisfied +49307,121695,Male,disloyal Customer,21,Business travel,Eco,168,4,1,4,3,5,4,5,5,4,3,3,3,2,5,35,36.0,neutral or dissatisfied +49308,97658,Male,Loyal Customer,25,Business travel,Business,3132,1,1,1,1,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +49309,27290,Male,disloyal Customer,30,Business travel,Eco,987,3,3,3,1,2,3,2,2,1,5,3,1,5,2,5,13.0,neutral or dissatisfied +49310,49353,Female,disloyal Customer,21,Business travel,Eco,209,1,4,1,4,4,1,3,4,1,5,4,2,3,4,0,0.0,neutral or dissatisfied +49311,95825,Female,disloyal Customer,36,Business travel,Eco,1028,2,2,2,4,2,2,5,2,3,3,4,1,4,2,0,9.0,neutral or dissatisfied +49312,33320,Male,Loyal Customer,56,Business travel,Business,2556,4,4,5,4,3,4,3,2,2,2,2,4,2,5,0,0.0,satisfied +49313,21659,Female,Loyal Customer,48,Business travel,Eco,746,4,4,4,4,3,4,2,4,4,4,4,2,4,4,0,0.0,satisfied +49314,106890,Female,Loyal Customer,20,Personal Travel,Eco,577,2,4,1,4,3,1,3,3,4,4,3,3,4,3,5,0.0,neutral or dissatisfied +49315,25965,Female,disloyal Customer,80,Business travel,Business,546,2,2,2,3,3,5,3,2,2,2,2,3,2,5,0,0.0,satisfied +49316,8856,Female,Loyal Customer,59,Business travel,Business,2222,5,2,5,5,5,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +49317,91994,Female,Loyal Customer,37,Business travel,Eco,236,4,3,3,3,4,4,4,4,3,4,3,5,2,4,0,0.0,satisfied +49318,93897,Male,Loyal Customer,32,Personal Travel,Eco,590,2,5,2,3,3,2,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +49319,30265,Male,Loyal Customer,40,Business travel,Eco,1024,2,2,2,2,2,2,2,2,1,3,3,1,4,2,0,11.0,neutral or dissatisfied +49320,21221,Male,Loyal Customer,25,Personal Travel,Eco,259,5,1,5,3,1,5,1,1,4,1,3,3,4,1,0,0.0,satisfied +49321,3538,Male,Loyal Customer,22,Personal Travel,Eco Plus,557,2,4,2,4,5,2,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +49322,53868,Female,Loyal Customer,58,Business travel,Business,2905,0,5,0,3,2,5,1,2,2,2,2,3,2,5,0,0.0,satisfied +49323,61149,Female,Loyal Customer,44,Business travel,Business,2466,1,1,1,1,4,4,5,1,1,2,1,5,1,5,60,51.0,satisfied +49324,67252,Male,Loyal Customer,8,Personal Travel,Eco,964,1,2,1,4,2,1,2,2,3,4,3,3,3,2,21,27.0,neutral or dissatisfied +49325,61525,Female,Loyal Customer,19,Personal Travel,Eco,2442,2,5,2,3,3,2,3,3,5,3,5,3,5,3,14,15.0,neutral or dissatisfied +49326,43449,Male,Loyal Customer,47,Business travel,Business,3729,3,1,1,1,2,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +49327,125160,Male,Loyal Customer,64,Personal Travel,Eco,969,3,4,3,1,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +49328,31988,Female,Loyal Customer,70,Personal Travel,Business,101,5,5,0,1,1,3,4,2,2,0,2,3,2,4,0,0.0,satisfied +49329,18324,Female,Loyal Customer,59,Personal Travel,Eco,715,1,4,1,4,4,3,3,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +49330,64713,Female,Loyal Customer,39,Business travel,Business,3919,2,2,2,2,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +49331,25559,Female,Loyal Customer,39,Business travel,Eco,874,5,2,4,2,5,5,5,5,4,3,5,3,5,5,8,0.0,satisfied +49332,37103,Male,disloyal Customer,27,Business travel,Business,1179,2,2,2,1,3,2,3,3,5,4,2,2,2,3,0,11.0,neutral or dissatisfied +49333,13997,Male,Loyal Customer,30,Business travel,Business,1566,4,5,5,5,1,1,4,1,4,3,3,3,3,1,79,115.0,neutral or dissatisfied +49334,12655,Female,disloyal Customer,13,Business travel,Eco,844,2,2,2,2,5,2,5,5,3,3,3,3,4,5,2,0.0,neutral or dissatisfied +49335,5455,Female,Loyal Customer,42,Business travel,Business,3257,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +49336,64248,Male,Loyal Customer,61,Personal Travel,Eco,1660,3,4,4,5,1,4,1,1,5,3,4,3,5,1,0,20.0,neutral or dissatisfied +49337,29207,Female,disloyal Customer,44,Business travel,Eco,891,4,4,4,4,3,4,3,3,1,2,5,1,3,3,44,83.0,satisfied +49338,64777,Male,Loyal Customer,36,Business travel,Business,1935,3,3,3,3,5,5,4,5,5,5,5,4,5,4,4,0.0,satisfied +49339,23924,Male,Loyal Customer,57,Personal Travel,Eco,579,1,5,0,3,1,0,1,1,2,3,5,5,2,1,0,0.0,neutral or dissatisfied +49340,82357,Female,Loyal Customer,59,Business travel,Business,2715,2,2,2,2,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +49341,77896,Female,Loyal Customer,47,Business travel,Business,456,1,1,3,1,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +49342,77581,Female,Loyal Customer,36,Personal Travel,Business,689,2,5,2,4,4,5,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +49343,38090,Male,Loyal Customer,45,Business travel,Business,1237,1,3,4,4,2,2,2,1,1,1,1,2,1,1,6,15.0,neutral or dissatisfied +49344,6750,Male,Loyal Customer,40,Business travel,Business,2145,4,4,4,4,3,4,5,3,3,4,5,4,3,5,0,0.0,satisfied +49345,101550,Male,Loyal Customer,49,Personal Travel,Eco,345,2,2,2,3,1,2,1,1,3,1,4,4,4,1,0,4.0,neutral or dissatisfied +49346,123557,Female,Loyal Customer,60,Business travel,Business,1773,5,5,5,5,3,4,5,4,4,4,4,5,4,4,12,0.0,satisfied +49347,3903,Female,Loyal Customer,64,Personal Travel,Eco,213,2,5,2,1,5,5,5,4,4,2,4,4,4,5,58,28.0,neutral or dissatisfied +49348,21415,Female,Loyal Customer,55,Business travel,Eco,399,5,1,1,1,4,3,1,4,4,5,4,4,4,3,3,8.0,satisfied +49349,111149,Female,Loyal Customer,13,Personal Travel,Eco,1111,3,2,3,4,4,3,4,4,1,3,4,3,3,4,3,0.0,neutral or dissatisfied +49350,1945,Male,Loyal Customer,36,Business travel,Business,1926,1,2,2,2,3,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +49351,115253,Male,Loyal Customer,59,Business travel,Business,2593,3,3,3,3,1,4,3,3,3,3,3,2,3,1,5,0.0,neutral or dissatisfied +49352,27046,Female,Loyal Customer,44,Business travel,Eco,1709,4,5,5,5,3,3,4,3,3,4,3,3,3,1,0,0.0,satisfied +49353,72825,Female,disloyal Customer,23,Business travel,Eco,1013,3,3,3,1,2,3,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +49354,83505,Male,Loyal Customer,46,Personal Travel,Eco,946,1,1,1,1,3,1,5,3,1,4,1,2,2,3,3,15.0,neutral or dissatisfied +49355,14535,Female,Loyal Customer,36,Business travel,Eco,310,1,2,4,4,1,1,1,1,2,3,4,2,4,1,26,28.0,neutral or dissatisfied +49356,99391,Male,Loyal Customer,58,Business travel,Eco,314,3,5,5,5,3,3,3,3,3,1,4,2,3,3,6,0.0,neutral or dissatisfied +49357,13719,Male,Loyal Customer,55,Business travel,Business,384,5,5,5,5,3,5,3,5,5,5,5,5,5,5,21,19.0,satisfied +49358,4044,Female,disloyal Customer,23,Business travel,Eco,479,2,0,2,4,5,2,5,5,3,1,2,1,3,5,0,0.0,neutral or dissatisfied +49359,38224,Female,Loyal Customer,50,Personal Travel,Eco Plus,1185,3,5,3,5,5,4,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +49360,10296,Male,disloyal Customer,41,Business travel,Business,301,5,5,5,3,2,5,2,2,4,3,5,5,4,2,0,0.0,satisfied +49361,27907,Male,Loyal Customer,35,Business travel,Business,2311,4,4,4,4,5,5,5,3,4,3,1,5,3,5,0,0.0,satisfied +49362,45659,Male,Loyal Customer,56,Business travel,Eco Plus,260,5,5,5,5,5,5,5,5,4,2,4,3,5,5,0,5.0,satisfied +49363,68659,Male,disloyal Customer,21,Business travel,Eco,175,2,3,1,3,2,1,2,2,4,3,2,4,2,2,0,0.0,neutral or dissatisfied +49364,30745,Male,disloyal Customer,27,Business travel,Eco,977,2,2,2,4,5,2,5,5,1,5,5,5,2,5,34,96.0,neutral or dissatisfied +49365,5005,Female,Loyal Customer,46,Business travel,Business,2062,2,2,2,2,3,2,1,4,4,4,4,2,4,5,0,0.0,satisfied +49366,20277,Female,Loyal Customer,59,Personal Travel,Eco,224,4,5,0,1,4,5,4,5,5,0,5,5,5,4,25,10.0,neutral or dissatisfied +49367,69511,Male,Loyal Customer,36,Business travel,Business,1746,2,2,2,2,5,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +49368,369,Female,Loyal Customer,53,Business travel,Business,2366,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +49369,96198,Female,disloyal Customer,26,Business travel,Eco,666,3,4,4,3,3,4,3,3,4,5,3,1,3,3,43,81.0,neutral or dissatisfied +49370,63324,Female,Loyal Customer,51,Business travel,Business,2049,4,3,3,3,3,3,4,4,4,4,4,1,4,3,1,0.0,neutral or dissatisfied +49371,66241,Female,disloyal Customer,24,Business travel,Eco,550,1,3,1,3,5,1,5,5,2,3,4,4,4,5,0,0.0,neutral or dissatisfied +49372,14124,Female,Loyal Customer,41,Business travel,Eco,528,5,3,4,3,5,5,5,5,3,5,5,4,2,5,75,73.0,satisfied +49373,80256,Male,Loyal Customer,51,Business travel,Business,1969,2,2,2,2,3,3,5,5,5,5,5,3,5,5,0,1.0,satisfied +49374,10277,Male,Loyal Customer,50,Business travel,Business,2883,3,3,5,3,3,5,5,4,4,4,4,4,4,4,88,79.0,satisfied +49375,34627,Male,Loyal Customer,61,Personal Travel,Business,541,2,4,2,1,4,1,5,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +49376,21013,Male,Loyal Customer,47,Business travel,Business,3651,4,2,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +49377,13336,Male,Loyal Customer,49,Business travel,Business,946,5,5,5,5,5,4,1,5,5,5,5,4,5,3,0,21.0,satisfied +49378,127047,Male,disloyal Customer,21,Business travel,Eco,370,5,0,5,1,3,5,3,3,3,4,4,3,5,3,0,0.0,satisfied +49379,92010,Female,Loyal Customer,19,Personal Travel,Business,1576,2,4,2,4,4,2,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +49380,118722,Female,Loyal Customer,35,Personal Travel,Eco,368,3,2,3,4,4,3,4,4,1,3,4,4,3,4,0,0.0,neutral or dissatisfied +49381,44214,Male,Loyal Customer,22,Business travel,Business,359,5,5,5,5,5,5,5,5,2,5,3,3,5,5,0,0.0,satisfied +49382,28231,Female,disloyal Customer,24,Business travel,Eco,1009,4,4,4,4,2,4,3,2,5,4,2,4,4,2,0,4.0,satisfied +49383,93769,Female,Loyal Customer,51,Business travel,Eco Plus,368,1,0,0,3,4,4,3,3,3,1,3,1,3,4,27,18.0,neutral or dissatisfied +49384,83828,Female,Loyal Customer,45,Business travel,Business,2529,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +49385,75253,Female,Loyal Customer,24,Personal Travel,Eco,1723,1,5,1,3,2,1,2,2,3,4,3,5,5,2,4,0.0,neutral or dissatisfied +49386,99471,Male,Loyal Customer,41,Business travel,Business,1573,0,0,0,2,3,5,4,3,3,3,3,4,3,4,15,20.0,satisfied +49387,63991,Male,Loyal Customer,52,Business travel,Business,1578,5,5,4,5,4,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +49388,129097,Male,disloyal Customer,27,Business travel,Business,1331,5,5,5,4,5,4,4,5,2,4,4,4,3,4,0,0.0,satisfied +49389,67614,Female,disloyal Customer,25,Business travel,Business,1205,0,3,0,4,2,0,2,2,5,3,5,3,4,2,0,9.0,satisfied +49390,21252,Male,Loyal Customer,10,Personal Travel,Eco Plus,317,2,3,2,3,1,2,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +49391,63932,Female,Loyal Customer,55,Personal Travel,Eco,1158,3,3,4,4,2,5,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +49392,83036,Male,Loyal Customer,42,Business travel,Business,2784,3,3,3,3,2,3,2,3,3,3,3,2,3,3,0,5.0,neutral or dissatisfied +49393,113756,Female,Loyal Customer,21,Personal Travel,Eco,223,4,5,4,2,1,4,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +49394,25245,Male,Loyal Customer,70,Personal Travel,Eco,925,2,5,2,2,1,2,1,1,4,3,2,4,2,1,0,0.0,neutral or dissatisfied +49395,83543,Male,Loyal Customer,43,Business travel,Business,1121,4,4,4,4,4,4,4,5,5,5,5,4,5,3,0,10.0,satisfied +49396,17707,Female,disloyal Customer,38,Business travel,Eco,311,3,1,3,3,1,3,1,1,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +49397,107278,Male,Loyal Customer,62,Business travel,Business,307,2,4,5,4,2,3,4,2,2,2,2,3,2,4,31,22.0,neutral or dissatisfied +49398,126161,Female,disloyal Customer,27,Business travel,Business,507,2,2,2,4,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +49399,25664,Male,Loyal Customer,57,Business travel,Business,3482,3,2,2,2,3,3,3,3,3,3,3,2,3,2,13,18.0,neutral or dissatisfied +49400,27966,Female,Loyal Customer,40,Personal Travel,Eco,1660,3,0,3,3,5,3,5,5,5,4,4,3,4,5,2,0.0,neutral or dissatisfied +49401,112977,Female,Loyal Customer,64,Personal Travel,Eco Plus,1497,2,2,2,3,5,4,4,2,2,2,2,4,2,1,12,12.0,neutral or dissatisfied +49402,32446,Male,Loyal Customer,40,Business travel,Business,216,1,1,1,1,5,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +49403,46948,Male,Loyal Customer,27,Personal Travel,Eco,819,4,2,4,2,3,4,3,3,1,4,3,2,2,3,34,48.0,neutral or dissatisfied +49404,14536,Male,Loyal Customer,69,Business travel,Business,362,1,5,5,5,1,1,1,3,4,4,3,1,4,1,215,216.0,neutral or dissatisfied +49405,71275,Male,Loyal Customer,68,Personal Travel,Eco,733,1,4,1,4,2,1,2,2,1,3,4,1,3,2,1,0.0,neutral or dissatisfied +49406,15505,Male,Loyal Customer,8,Personal Travel,Eco,331,4,3,4,3,2,4,2,2,1,1,3,5,1,2,1,0.0,neutral or dissatisfied +49407,128935,Male,Loyal Customer,53,Business travel,Business,3448,4,4,4,4,3,5,4,4,4,4,4,3,4,4,69,78.0,satisfied +49408,46781,Female,Loyal Customer,46,Business travel,Business,3159,4,4,4,4,2,4,4,5,5,5,5,4,5,5,58,56.0,satisfied +49409,35706,Female,Loyal Customer,50,Personal Travel,Eco,2465,1,5,1,3,1,4,4,3,5,4,4,4,3,4,0,24.0,neutral or dissatisfied +49410,66851,Female,Loyal Customer,46,Personal Travel,Eco,731,2,4,3,3,4,1,2,4,4,3,4,2,4,1,0,1.0,neutral or dissatisfied +49411,61446,Male,Loyal Customer,39,Business travel,Business,2358,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +49412,12475,Female,Loyal Customer,70,Personal Travel,Eco,127,4,4,4,3,3,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +49413,111524,Male,Loyal Customer,49,Business travel,Business,775,2,2,2,2,2,4,4,5,5,5,5,4,5,5,24,19.0,satisfied +49414,83508,Male,Loyal Customer,25,Personal Travel,Eco,946,2,3,2,3,3,2,5,3,1,3,3,1,3,3,0,3.0,neutral or dissatisfied +49415,74348,Female,Loyal Customer,35,Business travel,Business,1235,1,1,1,1,4,5,5,4,4,4,4,3,4,3,2,16.0,satisfied +49416,9277,Male,disloyal Customer,35,Business travel,Business,1190,4,4,4,1,4,4,2,4,3,2,5,4,4,4,4,0.0,neutral or dissatisfied +49417,75932,Male,Loyal Customer,48,Business travel,Business,1894,3,5,3,3,5,5,5,5,5,5,5,5,5,5,307,299.0,satisfied +49418,67104,Female,Loyal Customer,47,Business travel,Business,985,1,1,1,1,2,4,4,3,3,3,3,4,3,4,0,7.0,satisfied +49419,66280,Male,disloyal Customer,26,Business travel,Business,550,4,4,4,3,3,4,3,3,3,4,5,4,5,3,2,0.0,satisfied +49420,20763,Female,Loyal Customer,48,Business travel,Business,3930,4,4,4,4,2,5,5,5,5,5,5,4,5,4,120,109.0,satisfied +49421,21644,Female,Loyal Customer,30,Personal Travel,Eco,853,5,4,5,4,1,4,1,1,5,4,5,3,5,1,0,0.0,satisfied +49422,17528,Female,Loyal Customer,34,Business travel,Eco Plus,341,5,2,2,2,5,5,5,5,2,4,3,2,2,5,32,22.0,satisfied +49423,59926,Female,Loyal Customer,58,Business travel,Eco,937,3,5,5,5,5,4,3,3,3,3,3,2,3,3,85,91.0,neutral or dissatisfied +49424,5886,Male,Loyal Customer,45,Business travel,Business,2628,4,4,4,4,2,4,5,5,5,5,5,3,5,4,15,17.0,satisfied +49425,88646,Male,Loyal Customer,9,Personal Travel,Eco,444,3,4,3,3,3,3,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +49426,53671,Female,Loyal Customer,40,Business travel,Business,3778,3,3,3,3,5,4,2,5,5,5,5,4,5,2,29,17.0,satisfied +49427,75720,Male,Loyal Customer,67,Business travel,Business,1729,2,2,2,2,2,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +49428,42951,Male,Loyal Customer,62,Business travel,Business,3934,2,2,4,2,4,3,1,5,5,4,5,5,5,4,58,47.0,satisfied +49429,45072,Male,Loyal Customer,45,Personal Travel,Eco,342,3,3,3,3,4,3,4,4,5,3,2,1,1,4,39,19.0,neutral or dissatisfied +49430,103374,Female,Loyal Customer,46,Business travel,Business,342,4,4,4,4,5,5,4,4,4,4,4,4,4,4,5,0.0,satisfied +49431,125550,Male,Loyal Customer,47,Business travel,Business,226,4,4,4,4,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +49432,29307,Female,Loyal Customer,37,Personal Travel,Eco,933,3,4,4,5,5,4,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +49433,97470,Male,Loyal Customer,48,Business travel,Business,3439,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +49434,62522,Male,Loyal Customer,53,Business travel,Business,1744,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +49435,78609,Female,Loyal Customer,57,Business travel,Business,1426,4,4,2,4,2,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +49436,57885,Female,Loyal Customer,47,Business travel,Business,2660,3,3,3,3,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +49437,35224,Female,Loyal Customer,46,Business travel,Business,1005,3,5,3,5,1,4,3,3,3,3,3,1,3,1,112,110.0,neutral or dissatisfied +49438,46938,Female,Loyal Customer,44,Personal Travel,Eco,845,5,4,5,2,2,5,4,1,1,5,1,4,1,4,29,8.0,satisfied +49439,70555,Male,Loyal Customer,51,Business travel,Business,3780,4,4,4,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +49440,69114,Female,disloyal Customer,43,Business travel,Business,998,3,3,3,4,1,3,1,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +49441,60483,Female,disloyal Customer,40,Business travel,Business,794,1,1,1,2,3,1,3,3,5,5,5,3,4,3,6,0.0,neutral or dissatisfied +49442,13476,Male,Loyal Customer,22,Personal Travel,Eco Plus,475,1,3,1,2,3,1,3,3,4,1,5,5,3,3,0,0.0,neutral or dissatisfied +49443,45343,Male,Loyal Customer,34,Personal Travel,Eco,188,1,3,1,3,5,1,5,5,1,4,3,4,3,5,0,8.0,neutral or dissatisfied +49444,102842,Male,Loyal Customer,36,Business travel,Business,2236,1,3,3,3,4,3,4,1,1,1,1,3,1,1,0,18.0,neutral or dissatisfied +49445,111131,Female,Loyal Customer,26,Business travel,Business,2402,2,2,2,2,3,3,3,3,4,5,5,4,5,3,10,0.0,satisfied +49446,72399,Male,Loyal Customer,58,Business travel,Business,3944,5,5,2,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +49447,103485,Male,Loyal Customer,45,Business travel,Eco,440,4,3,1,3,4,4,4,4,1,5,3,2,3,4,2,8.0,neutral or dissatisfied +49448,84118,Female,Loyal Customer,46,Business travel,Business,1900,1,5,2,2,3,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +49449,12370,Male,Loyal Customer,31,Business travel,Business,3438,2,2,2,2,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +49450,122602,Female,Loyal Customer,47,Business travel,Eco,728,2,4,4,4,5,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +49451,127688,Female,Loyal Customer,38,Business travel,Business,2133,4,4,4,4,4,4,4,5,5,5,5,3,5,3,10,1.0,satisfied +49452,129108,Male,Loyal Customer,26,Personal Travel,Eco,2342,3,1,3,4,4,3,4,4,1,5,3,1,3,4,0,0.0,neutral or dissatisfied +49453,85943,Female,Loyal Customer,47,Business travel,Business,432,5,5,5,5,3,5,5,5,5,5,5,4,5,3,8,0.0,satisfied +49454,9698,Female,Loyal Customer,40,Personal Travel,Eco,199,5,4,5,3,2,5,1,2,5,5,5,3,5,2,0,0.0,satisfied +49455,51829,Female,Loyal Customer,45,Business travel,Eco Plus,509,4,4,3,4,1,5,3,4,4,4,4,1,4,1,0,0.0,satisfied +49456,60237,Female,disloyal Customer,25,Business travel,Eco,1607,2,2,2,4,4,2,1,4,2,4,1,3,2,4,0,0.0,neutral or dissatisfied +49457,42866,Female,disloyal Customer,29,Business travel,Eco,867,3,3,3,1,4,3,4,4,3,1,3,4,2,4,0,0.0,neutral or dissatisfied +49458,121344,Female,disloyal Customer,16,Business travel,Eco,430,1,4,1,3,4,1,2,4,1,2,3,1,3,4,18,32.0,neutral or dissatisfied +49459,19870,Female,Loyal Customer,49,Business travel,Business,1961,1,1,1,1,4,4,5,5,5,5,5,4,5,5,4,0.0,satisfied +49460,96197,Male,Loyal Customer,51,Business travel,Business,2959,5,5,4,5,4,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +49461,101267,Male,Loyal Customer,11,Personal Travel,Eco,2176,3,4,3,3,3,3,3,3,2,4,5,5,5,3,37,32.0,neutral or dissatisfied +49462,75307,Female,Loyal Customer,59,Business travel,Business,2556,4,4,4,4,5,4,4,4,4,3,5,4,4,4,34,28.0,satisfied +49463,13957,Male,Loyal Customer,33,Personal Travel,Eco,153,3,4,0,1,5,0,4,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +49464,52783,Female,Loyal Customer,29,Business travel,Business,1874,1,2,1,1,1,1,1,1,1,3,2,4,4,1,0,0.0,neutral or dissatisfied +49465,108561,Male,Loyal Customer,51,Personal Travel,Eco,735,3,5,3,1,5,3,5,5,4,5,4,4,4,5,3,0.0,neutral or dissatisfied +49466,45095,Female,Loyal Customer,28,Personal Travel,Business,177,1,3,1,3,2,1,2,2,4,1,3,1,2,2,0,0.0,neutral or dissatisfied +49467,120294,Male,disloyal Customer,22,Business travel,Eco,268,5,0,5,3,5,5,5,5,5,2,4,4,5,5,0,12.0,satisfied +49468,100973,Female,Loyal Customer,60,Business travel,Business,1524,1,1,1,1,2,5,4,5,5,5,5,3,5,3,6,0.0,satisfied +49469,70713,Female,Loyal Customer,50,Business travel,Business,675,1,4,4,4,1,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +49470,86185,Female,disloyal Customer,28,Business travel,Eco,356,4,2,4,4,5,4,5,5,2,5,4,1,4,5,1,0.0,neutral or dissatisfied +49471,11322,Male,Loyal Customer,70,Personal Travel,Eco,166,3,5,3,2,1,3,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +49472,96478,Male,Loyal Customer,54,Business travel,Eco,302,1,3,3,3,1,1,1,1,1,4,4,3,4,1,31,28.0,neutral or dissatisfied +49473,2871,Male,Loyal Customer,24,Business travel,Eco,409,5,1,1,1,5,5,5,5,5,3,5,1,1,5,0,0.0,satisfied +49474,98573,Female,Loyal Customer,47,Business travel,Business,3221,2,2,2,2,5,5,5,5,5,5,5,3,5,4,34,26.0,satisfied +49475,37354,Female,Loyal Customer,30,Business travel,Business,1674,4,4,4,4,5,5,5,5,1,3,2,4,4,5,116,100.0,satisfied +49476,44459,Female,disloyal Customer,21,Business travel,Eco,196,5,0,5,1,4,5,4,4,5,1,5,1,1,4,0,0.0,satisfied +49477,90681,Female,Loyal Customer,26,Business travel,Business,3892,2,2,2,2,3,4,3,3,4,5,5,5,4,3,14,7.0,satisfied +49478,2611,Female,Loyal Customer,67,Personal Travel,Eco,304,1,1,1,2,2,3,2,3,3,1,3,4,3,3,16,12.0,neutral or dissatisfied +49479,10036,Female,disloyal Customer,45,Business travel,Eco,230,4,2,4,2,1,4,1,1,5,1,1,4,2,1,0,0.0,satisfied +49480,91701,Female,Loyal Customer,42,Business travel,Business,3309,1,1,1,1,3,5,5,4,4,4,4,3,4,4,26,7.0,satisfied +49481,128346,Female,Loyal Customer,45,Business travel,Business,370,5,5,5,5,3,5,5,1,1,2,1,3,1,5,0,0.0,satisfied +49482,1485,Male,Loyal Customer,33,Business travel,Business,2151,4,4,4,4,4,4,4,4,3,2,5,5,5,4,0,5.0,satisfied +49483,40751,Female,Loyal Customer,27,Business travel,Business,599,1,1,1,1,2,2,2,1,5,1,5,2,3,2,120,151.0,satisfied +49484,115284,Male,disloyal Customer,36,Business travel,Eco,446,4,2,4,4,5,4,4,5,2,2,4,4,3,5,104,100.0,neutral or dissatisfied +49485,97430,Female,Loyal Customer,52,Business travel,Business,2814,5,5,1,5,4,4,5,5,5,5,5,5,5,4,15,7.0,satisfied +49486,39737,Male,Loyal Customer,13,Personal Travel,Eco,320,3,4,3,5,3,5,5,2,5,3,4,5,5,5,171,179.0,neutral or dissatisfied +49487,66749,Male,Loyal Customer,38,Personal Travel,Eco,802,3,3,2,4,5,2,5,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +49488,82230,Female,Loyal Customer,21,Business travel,Eco,405,0,3,0,3,5,0,5,5,2,4,4,5,5,5,0,0.0,satisfied +49489,30387,Male,Loyal Customer,16,Business travel,Business,775,2,1,1,1,2,2,2,2,2,5,3,4,3,2,42,38.0,neutral or dissatisfied +49490,98327,Female,Loyal Customer,48,Personal Travel,Business,1046,1,4,2,2,3,4,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +49491,92249,Female,Loyal Customer,53,Business travel,Business,1670,1,1,1,1,4,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +49492,103505,Male,Loyal Customer,49,Business travel,Business,3455,1,1,1,1,5,5,4,4,4,4,4,4,4,5,10,2.0,satisfied +49493,31627,Male,disloyal Customer,40,Business travel,Eco,846,2,2,2,3,1,2,1,1,3,1,1,2,3,1,0,12.0,neutral or dissatisfied +49494,48075,Male,Loyal Customer,51,Business travel,Business,3247,2,2,2,2,5,4,3,2,2,2,2,2,2,4,98,87.0,neutral or dissatisfied +49495,126641,Female,disloyal Customer,27,Business travel,Business,602,2,2,2,3,4,2,4,4,3,2,4,4,5,4,116,93.0,neutral or dissatisfied +49496,25284,Male,disloyal Customer,38,Business travel,Eco,321,4,0,4,1,3,4,3,3,2,4,1,1,1,3,0,0.0,neutral or dissatisfied +49497,109445,Female,Loyal Customer,26,Business travel,Business,951,4,4,4,4,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +49498,48221,Male,Loyal Customer,16,Personal Travel,Eco,192,4,4,4,3,4,4,4,4,5,4,5,5,4,4,42,31.0,neutral or dissatisfied +49499,37555,Male,Loyal Customer,40,Business travel,Business,3059,2,2,2,2,1,5,1,4,4,4,4,3,4,3,65,42.0,satisfied +49500,128796,Female,disloyal Customer,23,Business travel,Eco,1194,2,2,2,2,2,3,4,4,3,5,5,4,5,4,0,6.0,neutral or dissatisfied +49501,5927,Male,Loyal Customer,28,Personal Travel,Eco,173,2,4,0,2,5,0,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +49502,17056,Male,disloyal Customer,27,Business travel,Business,1134,2,2,2,4,1,2,1,1,2,2,3,3,4,1,11,21.0,neutral or dissatisfied +49503,32781,Female,Loyal Customer,41,Business travel,Business,3544,4,4,4,4,1,4,3,1,1,1,4,3,1,4,0,0.0,neutral or dissatisfied +49504,126035,Female,Loyal Customer,51,Business travel,Business,547,5,5,5,5,2,5,5,5,5,5,5,5,5,3,71,64.0,satisfied +49505,109138,Female,Loyal Customer,50,Business travel,Business,401,3,1,4,4,1,4,3,3,3,3,3,1,3,1,43,26.0,neutral or dissatisfied +49506,60099,Female,Loyal Customer,45,Business travel,Business,3961,1,1,1,1,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +49507,55617,Female,Loyal Customer,22,Business travel,Eco Plus,404,0,1,1,1,0,1,2,0,4,5,3,2,4,0,0,0.0,neutral or dissatisfied +49508,46895,Male,disloyal Customer,24,Business travel,Eco,819,5,5,5,2,2,5,2,2,5,3,5,5,2,2,8,7.0,satisfied +49509,121381,Female,Loyal Customer,20,Personal Travel,Eco,2279,3,5,3,3,4,3,4,4,5,5,5,4,4,4,3,0.0,neutral or dissatisfied +49510,76909,Female,Loyal Customer,43,Personal Travel,Eco,630,2,2,2,2,3,3,3,2,2,2,2,4,2,3,1,13.0,neutral or dissatisfied +49511,116692,Male,Loyal Customer,41,Business travel,Business,417,3,3,3,3,2,4,4,2,2,2,2,5,2,5,4,2.0,satisfied +49512,123007,Male,Loyal Customer,42,Business travel,Business,3426,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +49513,121526,Female,Loyal Customer,46,Business travel,Business,912,4,4,4,4,2,5,5,4,4,4,4,3,4,4,2,0.0,satisfied +49514,93518,Male,Loyal Customer,20,Business travel,Business,1569,5,5,5,5,4,4,4,4,3,2,4,3,5,4,1,14.0,satisfied +49515,126884,Female,Loyal Customer,38,Personal Travel,Eco,2125,2,4,2,4,5,2,5,5,3,5,2,1,1,5,0,6.0,neutral or dissatisfied +49516,48043,Male,Loyal Customer,59,Business travel,Eco,677,2,4,4,4,2,2,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +49517,60171,Female,Loyal Customer,61,Personal Travel,Eco,1120,2,5,2,2,5,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +49518,115616,Male,Loyal Customer,30,Business travel,Business,296,2,2,2,2,2,2,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +49519,87986,Male,disloyal Customer,46,Business travel,Business,406,3,3,3,4,1,3,1,1,3,5,4,4,4,1,25,18.0,neutral or dissatisfied +49520,68105,Male,Loyal Customer,18,Personal Travel,Eco,868,5,1,4,4,5,4,2,5,1,2,4,2,3,5,99,116.0,satisfied +49521,121931,Female,Loyal Customer,38,Business travel,Eco Plus,366,3,2,2,2,3,3,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +49522,101356,Male,Loyal Customer,48,Personal Travel,Business,1986,4,4,4,4,5,1,2,2,2,4,2,4,2,2,40,31.0,neutral or dissatisfied +49523,35911,Male,Loyal Customer,31,Business travel,Eco,2248,0,0,0,3,4,0,4,4,2,3,4,3,1,4,0,0.0,satisfied +49524,15918,Male,disloyal Customer,25,Business travel,Eco,738,2,2,2,5,3,2,3,3,2,3,4,5,2,3,6,4.0,neutral or dissatisfied +49525,67474,Male,Loyal Customer,48,Personal Travel,Eco,641,2,4,2,4,4,2,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +49526,25650,Female,Loyal Customer,30,Personal Travel,Eco,666,2,2,2,4,2,2,2,2,2,5,4,1,3,2,0,0.0,neutral or dissatisfied +49527,30588,Male,Loyal Customer,38,Personal Travel,Eco,628,1,4,1,2,3,1,2,3,5,4,4,5,4,3,4,0.0,neutral or dissatisfied +49528,100350,Female,Loyal Customer,43,Personal Travel,Eco,1165,4,4,4,2,3,4,5,1,1,4,1,4,1,4,2,0.0,satisfied +49529,103931,Male,Loyal Customer,25,Business travel,Business,770,1,1,1,1,4,4,4,4,5,4,4,3,5,4,26,27.0,satisfied +49530,52798,Female,Loyal Customer,31,Personal Travel,Eco,1874,3,3,3,3,5,3,5,5,4,1,2,4,1,5,13,0.0,neutral or dissatisfied +49531,28266,Male,Loyal Customer,11,Personal Travel,Eco,1542,4,5,4,1,2,4,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +49532,23485,Female,Loyal Customer,48,Personal Travel,Eco,576,1,5,1,1,4,4,5,3,3,1,3,3,3,4,0,15.0,neutral or dissatisfied +49533,63615,Female,Loyal Customer,43,Business travel,Business,1440,2,5,5,5,2,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +49534,37795,Male,Loyal Customer,37,Business travel,Eco Plus,611,2,1,2,2,2,2,2,2,2,3,3,3,4,2,37,35.0,neutral or dissatisfied +49535,96771,Male,Loyal Customer,34,Business travel,Business,488,4,4,4,4,5,5,5,4,4,4,4,5,4,4,12,1.0,satisfied +49536,106805,Female,Loyal Customer,16,Personal Travel,Eco,977,2,4,3,2,2,3,2,2,3,4,5,3,5,2,21,13.0,neutral or dissatisfied +49537,80711,Female,Loyal Customer,30,Personal Travel,Eco,1640,5,5,5,3,1,5,1,1,4,2,5,5,4,1,0,0.0,satisfied +49538,808,Female,Loyal Customer,50,Business travel,Business,134,4,4,1,4,3,5,5,4,4,4,5,3,4,3,4,8.0,satisfied +49539,98775,Male,Loyal Customer,59,Personal Travel,Eco,2075,3,4,4,3,5,4,5,5,4,3,3,2,4,5,0,0.0,neutral or dissatisfied +49540,39968,Male,Loyal Customer,46,Business travel,Business,1404,5,5,5,5,5,1,2,2,2,2,2,1,2,1,0,0.0,satisfied +49541,36021,Female,Loyal Customer,56,Business travel,Eco,399,5,4,4,4,4,3,4,5,5,5,5,2,5,5,16,38.0,satisfied +49542,120515,Male,Loyal Customer,50,Personal Travel,Eco Plus,337,3,4,4,3,4,4,4,4,3,3,5,4,4,4,106,99.0,neutral or dissatisfied +49543,128961,Female,Loyal Customer,50,Business travel,Business,3207,1,5,5,5,1,3,3,1,1,1,1,3,1,4,9,0.0,neutral or dissatisfied +49544,3871,Male,Loyal Customer,39,Business travel,Business,3092,2,2,2,2,3,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +49545,89256,Male,Loyal Customer,36,Business travel,Business,453,1,5,1,5,3,3,3,1,1,1,1,1,1,2,20,23.0,neutral or dissatisfied +49546,79943,Female,Loyal Customer,25,Business travel,Business,3845,2,5,5,5,2,2,2,2,4,1,2,3,2,2,3,15.0,neutral or dissatisfied +49547,13365,Male,Loyal Customer,37,Personal Travel,Eco,748,2,5,2,4,2,5,3,3,5,4,5,3,4,3,208,248.0,neutral or dissatisfied +49548,58880,Male,Loyal Customer,48,Business travel,Business,888,4,4,4,4,4,4,4,4,4,4,4,5,4,4,28,21.0,satisfied +49549,3001,Female,disloyal Customer,24,Business travel,Eco,922,4,4,4,4,5,4,5,5,5,3,4,4,4,5,0,12.0,satisfied +49550,75782,Female,Loyal Customer,70,Personal Travel,Eco,868,1,2,1,2,2,1,1,5,5,1,5,2,5,1,34,20.0,neutral or dissatisfied +49551,46079,Female,disloyal Customer,32,Business travel,Eco,541,2,4,3,3,5,3,5,5,5,4,4,3,5,5,7,19.0,neutral or dissatisfied +49552,105619,Female,Loyal Customer,57,Business travel,Business,3945,1,1,5,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +49553,94134,Male,Loyal Customer,29,Business travel,Business,323,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,2.0,satisfied +49554,8815,Male,Loyal Customer,37,Personal Travel,Eco,522,3,4,3,1,2,3,2,2,3,3,4,3,4,2,0,1.0,neutral or dissatisfied +49555,107968,Female,disloyal Customer,30,Business travel,Eco,825,2,2,2,4,3,2,3,3,1,5,4,2,4,3,24,19.0,neutral or dissatisfied +49556,115229,Female,Loyal Customer,32,Business travel,Business,480,1,1,1,1,5,5,5,5,5,4,4,3,5,5,3,2.0,satisfied +49557,12629,Female,Loyal Customer,34,Business travel,Business,2228,5,5,4,5,1,1,3,5,5,5,5,4,5,3,4,0.0,satisfied +49558,23195,Female,Loyal Customer,36,Business travel,Eco Plus,223,4,4,4,4,4,4,4,4,2,1,3,1,4,4,0,3.0,neutral or dissatisfied +49559,54635,Female,Loyal Customer,29,Business travel,Business,2026,1,3,1,1,5,5,5,5,4,1,3,2,4,5,13,12.0,satisfied +49560,72368,Female,Loyal Customer,33,Business travel,Business,1119,1,1,1,1,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +49561,113095,Female,Loyal Customer,18,Personal Travel,Eco,569,0,1,1,3,2,1,2,2,3,2,2,1,2,2,15,10.0,satisfied +49562,51876,Male,Loyal Customer,41,Personal Travel,Eco,771,4,4,4,3,5,4,5,5,5,4,5,5,5,5,0,7.0,neutral or dissatisfied +49563,89151,Male,disloyal Customer,16,Business travel,Eco,2092,3,3,3,3,4,3,4,4,2,1,4,4,4,4,45,53.0,neutral or dissatisfied +49564,123384,Female,Loyal Customer,54,Business travel,Business,1337,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +49565,38732,Male,disloyal Customer,34,Business travel,Business,354,1,1,1,4,5,1,5,5,3,1,1,4,1,5,0,0.0,neutral or dissatisfied +49566,111221,Female,disloyal Customer,27,Business travel,Eco,1455,2,2,2,3,3,2,3,3,2,3,3,2,3,3,0,10.0,neutral or dissatisfied +49567,44106,Female,Loyal Customer,36,Personal Travel,Eco,473,1,2,1,3,5,1,5,5,3,2,4,2,3,5,0,0.0,neutral or dissatisfied +49568,65671,Male,disloyal Customer,13,Business travel,Business,1021,4,3,4,4,4,4,4,4,5,2,4,5,4,4,3,0.0,satisfied +49569,123290,Female,Loyal Customer,19,Personal Travel,Eco,468,4,4,4,3,2,4,2,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +49570,117299,Male,Loyal Customer,25,Business travel,Eco Plus,338,4,4,4,4,4,4,2,4,2,3,3,1,3,4,3,0.0,neutral or dissatisfied +49571,57687,Female,Loyal Customer,56,Business travel,Business,3262,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,7.0,satisfied +49572,73100,Female,disloyal Customer,10,Personal Travel,Business,2174,2,2,2,2,4,2,4,4,1,1,2,2,3,4,0,0.0,neutral or dissatisfied +49573,50144,Male,Loyal Customer,41,Business travel,Business,109,2,3,4,3,5,3,3,1,1,1,2,2,1,2,0,0.0,neutral or dissatisfied +49574,80366,Female,disloyal Customer,42,Business travel,Business,368,5,5,5,3,1,5,1,1,4,5,4,5,4,1,10,1.0,satisfied +49575,108117,Female,Loyal Customer,36,Business travel,Business,3340,4,5,4,4,5,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +49576,115700,Male,disloyal Customer,24,Business travel,Eco,373,2,2,3,3,2,3,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +49577,125522,Male,disloyal Customer,48,Business travel,Business,226,4,4,4,4,1,4,1,1,5,3,4,3,5,1,51,39.0,neutral or dissatisfied +49578,72060,Female,Loyal Customer,45,Business travel,Business,2486,4,4,4,4,5,3,5,2,2,2,2,4,2,5,0,0.0,satisfied +49579,84221,Female,Loyal Customer,28,Business travel,Business,432,2,2,2,2,4,4,4,4,3,3,3,3,1,4,0,9.0,satisfied +49580,90190,Male,Loyal Customer,41,Personal Travel,Eco,1127,2,4,3,2,4,3,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +49581,17631,Female,disloyal Customer,29,Business travel,Eco,930,3,3,3,4,1,3,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +49582,126726,Female,Loyal Customer,64,Business travel,Eco,2402,1,1,1,1,2,3,4,1,1,1,1,4,1,3,2,0.0,neutral or dissatisfied +49583,123571,Female,Loyal Customer,41,Business travel,Business,1773,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +49584,15693,Female,Loyal Customer,32,Business travel,Business,2068,4,4,4,4,2,2,2,2,5,4,5,4,4,2,0,0.0,satisfied +49585,6927,Female,Loyal Customer,38,Business travel,Eco Plus,265,5,1,1,1,5,5,5,5,1,1,5,1,2,5,41,82.0,satisfied +49586,11460,Female,Loyal Customer,19,Business travel,Eco Plus,458,3,5,5,5,3,3,3,3,1,5,4,2,3,3,1,0.0,neutral or dissatisfied +49587,56452,Male,Loyal Customer,58,Personal Travel,Eco,719,2,5,2,2,2,2,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +49588,84582,Female,Loyal Customer,56,Business travel,Business,1572,5,5,4,5,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +49589,48849,Female,Loyal Customer,15,Personal Travel,Business,109,3,5,3,3,4,3,4,4,4,4,4,3,2,4,111,110.0,neutral or dissatisfied +49590,129041,Male,Loyal Customer,48,Business travel,Business,1846,3,3,3,3,4,3,5,5,5,5,5,3,5,4,6,11.0,satisfied +49591,30155,Female,Loyal Customer,27,Personal Travel,Eco,234,2,3,2,4,3,2,3,3,4,3,3,4,3,3,2,9.0,neutral or dissatisfied +49592,54784,Female,Loyal Customer,52,Business travel,Business,2742,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +49593,48955,Male,Loyal Customer,64,Business travel,Eco,86,4,1,1,1,4,4,4,4,5,1,1,1,4,4,0,29.0,satisfied +49594,106872,Female,Loyal Customer,49,Business travel,Business,704,1,1,1,1,2,5,5,5,5,5,5,4,5,3,16,0.0,satisfied +49595,35730,Female,Loyal Customer,11,Personal Travel,Eco Plus,2446,2,5,1,1,1,4,4,5,5,4,5,4,4,4,16,60.0,neutral or dissatisfied +49596,73280,Male,Loyal Customer,60,Business travel,Business,3177,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,4.0,satisfied +49597,104705,Male,Loyal Customer,41,Personal Travel,Eco,159,1,5,1,3,5,1,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +49598,65350,Female,Loyal Customer,57,Business travel,Business,432,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +49599,96297,Male,Loyal Customer,63,Personal Travel,Eco,546,2,3,2,3,3,2,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +49600,20922,Male,Loyal Customer,44,Business travel,Eco,689,4,5,5,5,4,4,4,4,5,1,1,5,2,4,0,0.0,satisfied +49601,14098,Female,Loyal Customer,45,Personal Travel,Eco,201,3,5,0,3,2,2,3,1,1,0,4,5,1,5,0,0.0,neutral or dissatisfied +49602,113354,Male,disloyal Customer,25,Business travel,Business,414,3,0,3,4,4,3,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +49603,28573,Male,disloyal Customer,46,Business travel,Business,1355,5,5,5,2,1,5,1,1,1,1,3,4,5,1,87,59.0,satisfied +49604,49641,Female,Loyal Customer,35,Business travel,Eco,190,5,4,4,4,5,5,5,5,4,4,5,2,2,5,63,55.0,satisfied +49605,35301,Female,Loyal Customer,33,Business travel,Eco,1076,2,1,1,1,2,2,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +49606,125703,Female,Loyal Customer,36,Personal Travel,Eco,899,0,4,0,4,5,0,5,5,4,5,1,1,3,5,0,0.0,satisfied +49607,84581,Male,Loyal Customer,57,Business travel,Business,1572,2,2,2,2,3,4,5,5,5,5,5,4,5,5,1,37.0,satisfied +49608,75041,Male,Loyal Customer,43,Personal Travel,Eco,236,4,2,0,2,2,0,2,2,1,1,1,1,2,2,0,0.0,neutral or dissatisfied +49609,116674,Male,disloyal Customer,38,Business travel,Eco Plus,447,1,1,1,2,2,1,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +49610,5603,Female,Loyal Customer,57,Business travel,Business,685,2,2,2,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +49611,127458,Male,Loyal Customer,48,Business travel,Business,1814,3,3,3,3,3,5,4,5,5,5,5,3,5,5,5,10.0,satisfied +49612,84601,Male,disloyal Customer,32,Business travel,Business,669,3,3,3,4,1,3,1,1,3,5,4,3,5,1,19,20.0,neutral or dissatisfied +49613,40926,Male,Loyal Customer,43,Business travel,Eco Plus,501,2,5,5,5,2,2,2,2,2,5,1,3,2,2,0,0.0,satisfied +49614,49263,Female,Loyal Customer,30,Business travel,Eco,89,5,5,5,5,5,4,5,5,4,1,3,3,5,5,0,0.0,satisfied +49615,34138,Female,disloyal Customer,24,Business travel,Eco,1189,2,2,2,4,2,2,2,2,4,5,1,5,3,2,0,7.0,neutral or dissatisfied +49616,87155,Female,Loyal Customer,40,Business travel,Business,3631,3,3,3,3,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +49617,92679,Female,disloyal Customer,10,Business travel,Eco,507,2,3,2,3,4,2,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +49618,111656,Female,Loyal Customer,30,Personal Travel,Eco Plus,1290,2,5,3,2,2,3,2,2,5,2,4,4,5,2,19,14.0,neutral or dissatisfied +49619,127972,Male,disloyal Customer,36,Business travel,Business,1149,2,2,2,5,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +49620,67385,Male,Loyal Customer,46,Business travel,Business,3926,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +49621,35682,Male,Loyal Customer,43,Business travel,Business,2475,2,2,2,2,3,2,2,2,5,1,3,2,4,2,2,16.0,neutral or dissatisfied +49622,80020,Male,Loyal Customer,34,Personal Travel,Eco,1076,3,4,3,2,5,3,5,5,4,1,1,5,1,5,0,8.0,neutral or dissatisfied +49623,35644,Female,Loyal Customer,47,Personal Travel,Business,2465,1,2,1,2,1,4,4,2,5,2,2,4,3,4,0,20.0,neutral or dissatisfied +49624,59965,Male,disloyal Customer,41,Business travel,Eco,668,3,2,3,3,3,3,3,3,1,3,3,3,2,3,293,264.0,neutral or dissatisfied +49625,86389,Male,Loyal Customer,41,Business travel,Business,760,4,4,4,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +49626,17285,Female,Loyal Customer,48,Business travel,Business,629,2,2,2,2,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +49627,49012,Male,Loyal Customer,40,Business travel,Eco,156,4,5,5,5,4,4,4,4,1,3,5,4,5,4,0,0.0,satisfied +49628,4991,Female,disloyal Customer,28,Business travel,Business,502,0,0,0,1,5,0,5,5,3,2,5,4,5,5,0,0.0,satisfied +49629,73505,Female,disloyal Customer,54,Business travel,Business,1197,4,4,4,4,5,4,5,5,5,3,4,3,5,5,88,67.0,neutral or dissatisfied +49630,120749,Female,Loyal Customer,57,Business travel,Business,678,3,3,3,3,5,5,4,5,5,5,5,4,5,3,24,23.0,satisfied +49631,46293,Female,Loyal Customer,49,Business travel,Eco,637,5,4,4,4,1,3,3,5,5,5,5,2,5,4,21,27.0,satisfied +49632,93634,Female,Loyal Customer,23,Personal Travel,Eco,704,2,5,2,3,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +49633,60979,Female,Loyal Customer,50,Personal Travel,Eco,888,1,1,1,1,2,2,2,1,1,1,4,3,1,4,0,3.0,neutral or dissatisfied +49634,31569,Female,Loyal Customer,30,Personal Travel,Eco Plus,853,3,2,2,4,4,2,4,4,4,5,3,3,3,4,0,32.0,neutral or dissatisfied +49635,29686,Female,Loyal Customer,8,Personal Travel,Eco Plus,680,2,4,2,3,5,2,5,5,4,4,5,5,3,5,12,21.0,neutral or dissatisfied +49636,69328,Male,Loyal Customer,59,Business travel,Business,1096,3,3,3,3,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +49637,92856,Female,Loyal Customer,34,Personal Travel,Eco Plus,2125,2,1,1,4,4,1,4,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +49638,53699,Female,Loyal Customer,51,Business travel,Business,3802,5,5,5,5,3,5,4,5,5,5,5,2,5,4,0,5.0,satisfied +49639,40945,Male,Loyal Customer,30,Personal Travel,Eco Plus,590,3,5,3,4,1,3,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +49640,112010,Female,disloyal Customer,28,Business travel,Business,680,5,5,5,1,1,5,1,1,3,4,5,5,4,1,0,0.0,satisfied +49641,71319,Male,Loyal Customer,57,Business travel,Business,1671,2,2,2,2,2,4,5,4,4,4,4,3,4,3,88,81.0,satisfied +49642,6455,Female,disloyal Customer,24,Business travel,Business,296,4,5,4,1,2,4,2,2,5,4,5,4,4,2,0,0.0,satisfied +49643,127785,Female,Loyal Customer,45,Personal Travel,Eco,1037,2,2,2,3,5,3,3,3,3,2,5,4,3,2,0,16.0,neutral or dissatisfied +49644,16492,Male,Loyal Customer,42,Business travel,Eco,143,2,4,4,4,2,2,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +49645,41643,Female,Loyal Customer,57,Personal Travel,Business,347,3,4,3,4,5,5,5,5,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +49646,58978,Male,disloyal Customer,23,Business travel,Eco,1369,1,1,1,1,4,1,4,4,5,5,5,3,4,4,4,0.0,neutral or dissatisfied +49647,113372,Male,Loyal Customer,49,Business travel,Business,2456,0,0,0,2,2,5,5,5,5,5,5,3,5,5,0,3.0,satisfied +49648,43440,Male,Loyal Customer,45,Business travel,Business,2439,2,2,2,2,1,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +49649,100317,Male,Loyal Customer,30,Business travel,Business,1053,1,5,5,5,1,1,1,1,1,2,1,1,2,1,17,7.0,neutral or dissatisfied +49650,51755,Male,Loyal Customer,41,Personal Travel,Eco,370,5,4,5,2,3,5,3,3,4,1,1,3,4,3,0,0.0,satisfied +49651,14993,Female,Loyal Customer,65,Personal Travel,Eco Plus,476,2,3,2,3,4,4,4,5,5,2,5,1,5,1,55,48.0,neutral or dissatisfied +49652,100682,Female,Loyal Customer,45,Business travel,Eco,677,4,1,2,2,4,3,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +49653,116857,Female,Loyal Customer,46,Business travel,Business,1960,0,0,0,1,4,5,5,1,1,1,1,4,1,5,25,18.0,satisfied +49654,75591,Female,Loyal Customer,71,Business travel,Eco,337,5,4,4,4,4,3,1,5,5,5,5,4,5,4,0,0.0,satisfied +49655,115664,Male,Loyal Customer,50,Business travel,Business,362,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +49656,36949,Female,Loyal Customer,31,Business travel,Eco Plus,718,3,3,3,3,3,2,3,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +49657,125379,Male,disloyal Customer,21,Business travel,Business,1440,0,0,0,3,5,0,5,5,3,4,5,5,5,5,0,0.0,satisfied +49658,64500,Male,disloyal Customer,32,Business travel,Business,469,1,0,0,3,5,0,5,5,1,2,2,3,2,5,83,94.0,neutral or dissatisfied +49659,91136,Female,Loyal Customer,12,Personal Travel,Eco,271,3,5,3,4,1,3,1,1,3,4,5,5,5,1,5,0.0,neutral or dissatisfied +49660,124509,Male,Loyal Customer,35,Personal Travel,Eco,930,4,4,4,3,3,4,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +49661,33639,Female,Loyal Customer,41,Personal Travel,Eco,399,4,5,4,4,3,4,3,3,4,5,4,3,5,3,26,34.0,neutral or dissatisfied +49662,28476,Male,Loyal Customer,69,Business travel,Eco,221,4,5,3,3,4,4,4,4,3,2,1,1,2,4,0,0.0,satisfied +49663,9620,Female,Loyal Customer,58,Business travel,Business,2183,0,0,0,4,4,4,4,3,3,3,3,4,3,4,42,36.0,satisfied +49664,109607,Male,Loyal Customer,44,Business travel,Business,3214,2,5,5,5,1,3,2,2,2,2,2,3,2,4,29,37.0,neutral or dissatisfied +49665,86963,Male,Loyal Customer,48,Business travel,Business,3457,4,3,4,4,2,5,4,5,5,5,5,5,5,4,0,2.0,satisfied +49666,107585,Female,Loyal Customer,40,Business travel,Business,1859,3,3,3,3,3,5,4,5,5,5,5,3,5,3,1,15.0,satisfied +49667,84504,Female,Loyal Customer,50,Personal Travel,Business,2486,2,3,2,3,3,3,3,1,1,2,1,3,1,1,21,5.0,neutral or dissatisfied +49668,52239,Female,Loyal Customer,31,Business travel,Business,2306,5,5,5,5,5,5,5,5,1,4,5,3,5,5,0,2.0,satisfied +49669,72784,Male,Loyal Customer,29,Business travel,Business,3053,1,1,1,1,1,1,1,1,1,5,1,1,2,1,0,8.0,neutral or dissatisfied +49670,83863,Female,Loyal Customer,48,Personal Travel,Eco,425,1,2,1,2,4,1,3,4,4,1,4,2,4,2,0,4.0,neutral or dissatisfied +49671,54775,Female,Loyal Customer,53,Personal Travel,Eco Plus,787,2,1,2,4,4,4,3,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +49672,74548,Male,Loyal Customer,59,Business travel,Eco,1205,4,3,3,3,4,4,4,4,4,3,2,1,2,4,4,0.0,neutral or dissatisfied +49673,12735,Female,Loyal Customer,67,Personal Travel,Eco,689,3,2,3,4,4,3,4,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +49674,91222,Male,Loyal Customer,7,Personal Travel,Eco,271,2,0,2,5,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +49675,62187,Female,Loyal Customer,68,Business travel,Business,925,2,3,3,3,2,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +49676,102302,Female,Loyal Customer,39,Business travel,Business,223,3,3,3,3,5,4,4,4,4,4,4,5,4,5,29,24.0,satisfied +49677,28001,Female,Loyal Customer,44,Business travel,Business,2253,5,5,4,5,1,5,1,4,4,4,4,5,4,1,0,0.0,satisfied +49678,100524,Male,Loyal Customer,38,Personal Travel,Eco,759,0,4,0,3,2,0,2,2,3,4,4,4,4,2,0,0.0,satisfied +49679,14570,Male,Loyal Customer,40,Business travel,Business,986,3,3,3,3,2,5,4,5,5,5,5,3,5,1,0,0.0,satisfied +49680,561,Male,disloyal Customer,23,Business travel,Business,247,4,5,4,5,5,4,5,5,4,2,4,3,4,5,80,76.0,satisfied +49681,61464,Male,Loyal Customer,20,Business travel,Business,2442,1,1,1,1,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +49682,65462,Male,Loyal Customer,47,Business travel,Business,1067,5,5,5,5,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +49683,88631,Female,Loyal Customer,38,Personal Travel,Eco,404,4,5,4,1,3,4,5,3,4,5,5,3,5,3,0,0.0,satisfied +49684,104791,Female,disloyal Customer,22,Business travel,Eco,587,2,0,1,2,2,1,3,2,4,3,4,4,5,2,8,0.0,neutral or dissatisfied +49685,44647,Male,Loyal Customer,54,Business travel,Business,67,4,4,4,4,3,3,1,5,5,5,4,1,5,1,3,0.0,satisfied +49686,25668,Female,disloyal Customer,20,Business travel,Eco,361,2,0,2,2,1,2,1,1,4,4,3,2,2,1,0,0.0,neutral or dissatisfied +49687,80405,Male,Loyal Customer,45,Business travel,Business,1416,2,2,4,2,3,4,4,5,5,5,5,4,5,5,29,9.0,satisfied +49688,67958,Female,disloyal Customer,22,Business travel,Eco,1235,4,4,4,3,5,4,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +49689,42560,Female,disloyal Customer,22,Business travel,Business,626,5,0,5,2,2,5,2,2,3,3,3,3,5,2,0,16.0,satisfied +49690,80255,Male,Loyal Customer,16,Business travel,Business,1969,2,1,1,1,2,2,2,2,2,4,3,3,4,2,0,4.0,neutral or dissatisfied +49691,64949,Female,disloyal Customer,68,Business travel,Eco,190,3,1,3,2,3,3,3,3,2,4,3,3,2,3,0,0.0,neutral or dissatisfied +49692,24936,Female,Loyal Customer,69,Personal Travel,Eco,2106,3,1,3,3,5,3,4,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +49693,68247,Male,Loyal Customer,45,Business travel,Business,2900,4,4,4,4,3,4,3,5,5,5,5,4,5,5,25,39.0,satisfied +49694,96720,Male,disloyal Customer,23,Business travel,Eco,696,2,2,2,2,2,2,2,2,3,4,5,2,2,2,0,0.0,neutral or dissatisfied +49695,106366,Female,disloyal Customer,29,Business travel,Business,674,2,2,2,2,2,2,2,2,5,3,4,5,4,2,116,115.0,neutral or dissatisfied +49696,26330,Male,Loyal Customer,25,Business travel,Business,3371,1,1,1,1,5,5,5,5,1,5,4,5,5,5,30,30.0,satisfied +49697,71634,Male,disloyal Customer,20,Business travel,Eco,1012,1,1,1,4,1,1,1,1,3,1,4,1,4,1,0,0.0,neutral or dissatisfied +49698,94408,Female,Loyal Customer,57,Business travel,Business,1985,1,1,1,1,5,5,4,4,4,4,4,5,4,4,59,61.0,satisfied +49699,105504,Male,disloyal Customer,39,Business travel,Business,611,2,2,2,2,4,2,1,4,1,1,2,1,2,4,0,0.0,neutral or dissatisfied +49700,44275,Female,disloyal Customer,25,Business travel,Eco Plus,118,4,0,4,1,4,4,4,4,4,5,1,1,5,4,0,6.0,neutral or dissatisfied +49701,67465,Female,Loyal Customer,8,Personal Travel,Eco,592,3,3,3,3,2,3,2,2,3,1,4,5,4,2,3,0.0,neutral or dissatisfied +49702,21514,Female,Loyal Customer,55,Personal Travel,Eco,377,3,2,3,3,4,3,4,4,4,3,4,2,4,4,0,1.0,neutral or dissatisfied +49703,119244,Female,Loyal Customer,45,Business travel,Business,2272,5,5,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +49704,116973,Male,Loyal Customer,45,Business travel,Business,3438,5,5,5,5,4,5,4,5,5,5,5,5,5,4,16,6.0,satisfied +49705,41494,Male,Loyal Customer,45,Business travel,Business,715,2,2,2,2,4,2,5,4,4,4,4,4,4,2,0,17.0,satisfied +49706,61182,Male,Loyal Customer,52,Business travel,Business,2300,3,3,3,3,5,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +49707,39264,Female,Loyal Customer,17,Business travel,Business,268,2,1,1,1,2,2,2,2,3,3,4,4,3,2,53,57.0,neutral or dissatisfied +49708,58423,Female,Loyal Customer,33,Business travel,Business,733,3,5,5,5,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +49709,75380,Male,Loyal Customer,50,Business travel,Business,2585,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +49710,67666,Female,Loyal Customer,41,Business travel,Business,1431,1,1,1,1,2,5,4,4,4,4,4,3,4,5,20,12.0,satisfied +49711,53981,Male,Loyal Customer,35,Business travel,Eco Plus,1117,4,4,4,4,4,4,4,4,3,2,5,3,2,4,6,0.0,satisfied +49712,125499,Male,Loyal Customer,46,Business travel,Business,666,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +49713,96015,Male,Loyal Customer,47,Business travel,Business,1069,5,2,5,5,4,4,5,5,5,5,5,3,5,5,34,24.0,satisfied +49714,54802,Male,Loyal Customer,58,Business travel,Eco,934,3,3,5,3,3,3,3,3,1,3,4,2,1,3,0,0.0,satisfied +49715,419,Male,Loyal Customer,58,Business travel,Business,309,5,5,3,5,4,4,4,4,4,4,4,3,4,4,0,1.0,satisfied +49716,54504,Female,Loyal Customer,51,Business travel,Eco,925,2,1,1,1,5,3,2,2,2,2,2,3,2,3,47,29.0,neutral or dissatisfied +49717,125510,Female,Loyal Customer,19,Personal Travel,Eco,666,2,1,2,3,4,2,4,4,2,3,3,4,3,4,5,17.0,neutral or dissatisfied +49718,10815,Male,Loyal Customer,57,Business travel,Business,312,1,1,1,1,1,3,3,1,1,1,1,1,1,3,79,75.0,neutral or dissatisfied +49719,75188,Male,Loyal Customer,24,Business travel,Business,1829,2,1,1,1,2,2,2,2,1,3,3,1,3,2,25,23.0,neutral or dissatisfied +49720,55152,Female,Loyal Customer,44,Personal Travel,Eco,1635,2,4,2,4,2,4,1,4,4,3,4,1,4,1,132,134.0,neutral or dissatisfied +49721,86754,Female,Loyal Customer,56,Personal Travel,Eco,821,1,3,1,3,1,3,3,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +49722,42743,Female,disloyal Customer,52,Business travel,Eco Plus,536,3,3,3,5,1,3,1,1,2,1,3,5,5,1,0,0.0,neutral or dissatisfied +49723,27483,Male,Loyal Customer,69,Business travel,Eco,679,5,1,1,1,5,5,5,5,3,2,5,1,4,5,0,0.0,satisfied +49724,8912,Female,Loyal Customer,26,Business travel,Eco Plus,510,2,5,5,5,2,2,3,2,3,5,4,2,3,2,0,28.0,neutral or dissatisfied +49725,40843,Female,Loyal Customer,39,Business travel,Eco,158,4,3,2,2,4,4,4,4,4,4,4,4,3,4,0,0.0,neutral or dissatisfied +49726,30780,Male,Loyal Customer,21,Business travel,Eco,895,4,1,1,1,4,4,5,4,2,3,3,1,3,4,20,26.0,satisfied +49727,112275,Male,Loyal Customer,38,Business travel,Business,2133,4,4,4,4,4,5,4,5,5,5,5,2,5,1,30,25.0,satisfied +49728,54684,Male,Loyal Customer,22,Business travel,Business,965,5,5,5,5,5,5,5,5,2,2,4,4,4,5,0,0.0,satisfied +49729,57782,Male,Loyal Customer,67,Personal Travel,Eco,2704,1,4,1,4,1,3,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +49730,112623,Female,Loyal Customer,37,Personal Travel,Eco,602,2,4,2,5,2,2,2,2,3,5,5,5,5,2,24,12.0,neutral or dissatisfied +49731,113173,Male,Loyal Customer,14,Personal Travel,Eco,628,1,3,2,2,3,2,3,3,5,3,5,4,5,3,1,0.0,neutral or dissatisfied +49732,129778,Male,Loyal Customer,62,Personal Travel,Eco,447,3,5,3,2,1,3,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +49733,115198,Female,Loyal Customer,30,Business travel,Business,2794,2,3,3,3,2,2,2,2,3,3,4,4,4,2,38,38.0,neutral or dissatisfied +49734,62719,Female,Loyal Customer,52,Business travel,Business,2367,2,2,2,2,5,5,5,5,5,5,5,5,5,3,101,93.0,satisfied +49735,44226,Male,Loyal Customer,44,Business travel,Eco,222,3,4,4,4,3,3,3,3,1,2,3,5,3,3,0,9.0,satisfied +49736,74091,Male,disloyal Customer,20,Business travel,Eco,641,2,3,2,4,5,2,3,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +49737,54674,Female,disloyal Customer,27,Business travel,Eco,787,2,2,2,4,1,2,5,1,1,4,3,1,4,1,36,22.0,neutral or dissatisfied +49738,27411,Male,Loyal Customer,42,Business travel,Eco,672,2,5,5,5,2,2,2,2,5,4,3,1,5,2,0,3.0,satisfied +49739,65296,Male,Loyal Customer,50,Personal Travel,Eco Plus,551,1,3,1,4,5,1,5,5,1,3,3,3,4,5,0,0.0,neutral or dissatisfied +49740,54606,Female,Loyal Customer,26,Business travel,Eco,965,5,1,1,1,5,5,4,5,2,4,4,1,5,5,34,35.0,satisfied +49741,93200,Male,Loyal Customer,25,Business travel,Business,496,5,5,5,5,5,4,5,5,4,2,4,3,3,5,0,9.0,neutral or dissatisfied +49742,89757,Male,Loyal Customer,15,Personal Travel,Eco,1089,4,3,4,3,3,4,3,3,4,1,4,3,3,3,30,13.0,neutral or dissatisfied +49743,4297,Male,Loyal Customer,65,Personal Travel,Eco,502,3,4,3,3,1,3,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +49744,62400,Male,Loyal Customer,38,Personal Travel,Eco,2704,3,3,2,5,1,2,1,1,4,3,4,3,5,1,32,0.0,neutral or dissatisfied +49745,106906,Male,Loyal Customer,48,Business travel,Business,577,5,5,5,5,5,4,4,4,4,4,4,3,4,4,7,0.0,satisfied +49746,71150,Female,Loyal Customer,44,Business travel,Business,3857,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +49747,76981,Male,Loyal Customer,7,Personal Travel,Eco,1969,2,5,2,3,3,2,3,3,4,4,4,4,4,3,41,42.0,neutral or dissatisfied +49748,9525,Female,Loyal Customer,43,Personal Travel,Business,292,3,5,2,3,5,5,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +49749,71412,Male,Loyal Customer,23,Personal Travel,Eco,334,3,5,5,4,3,5,3,3,4,5,5,3,5,3,23,32.0,neutral or dissatisfied +49750,20599,Female,Loyal Customer,40,Personal Travel,Eco Plus,565,4,5,4,3,5,4,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +49751,114450,Female,disloyal Customer,44,Business travel,Business,362,3,3,3,1,1,3,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +49752,67633,Female,disloyal Customer,37,Business travel,Business,1431,2,2,2,2,4,2,4,4,3,5,4,5,5,4,25,53.0,neutral or dissatisfied +49753,76520,Male,Loyal Customer,45,Business travel,Business,547,1,1,5,1,4,4,4,3,3,3,3,3,3,5,0,31.0,satisfied +49754,104169,Male,Loyal Customer,27,Business travel,Business,3424,1,1,1,1,4,3,3,4,4,5,4,3,4,3,181,,satisfied +49755,51540,Female,Loyal Customer,29,Business travel,Business,2700,2,2,2,2,5,4,5,5,2,3,2,3,4,5,0,0.0,satisfied +49756,54744,Male,Loyal Customer,47,Personal Travel,Eco,965,2,4,2,4,1,2,5,1,3,2,4,5,5,1,18,16.0,neutral or dissatisfied +49757,12151,Female,Loyal Customer,35,Business travel,Eco,1214,4,2,2,2,4,4,4,4,2,3,1,3,5,4,0,0.0,satisfied +49758,18351,Male,Loyal Customer,51,Business travel,Eco,632,2,3,3,3,2,2,2,2,2,5,4,3,3,2,0,32.0,neutral or dissatisfied +49759,28875,Female,Loyal Customer,26,Business travel,Business,605,1,1,1,1,2,2,2,2,3,4,1,5,1,2,0,0.0,satisfied +49760,86178,Female,Loyal Customer,23,Business travel,Business,1789,3,4,4,4,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +49761,94238,Male,Loyal Customer,31,Business travel,Business,2125,1,1,1,1,4,4,4,4,4,3,4,4,5,4,126,122.0,satisfied +49762,52802,Female,Loyal Customer,38,Business travel,Eco Plus,1874,4,1,1,1,4,4,4,4,4,2,3,5,1,4,0,0.0,satisfied +49763,4134,Male,Loyal Customer,66,Business travel,Business,544,2,4,4,4,4,3,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +49764,71612,Female,Loyal Customer,46,Business travel,Eco,1120,3,3,3,3,4,3,4,3,3,3,3,1,3,1,2,0.0,neutral or dissatisfied +49765,60050,Female,disloyal Customer,14,Business travel,Eco Plus,1023,3,1,3,4,2,3,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +49766,50830,Male,Loyal Customer,24,Personal Travel,Eco,109,3,5,0,3,5,0,5,5,4,3,5,3,4,5,47,55.0,neutral or dissatisfied +49767,93853,Male,disloyal Customer,27,Business travel,Eco Plus,391,2,2,2,4,1,2,2,1,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +49768,24286,Male,Loyal Customer,20,Personal Travel,Eco,170,1,2,1,4,3,1,3,3,3,5,4,4,3,3,19,16.0,neutral or dissatisfied +49769,108983,Female,Loyal Customer,54,Business travel,Business,1676,5,5,5,5,5,4,4,5,5,5,5,4,5,3,1,1.0,satisfied +49770,61284,Male,Loyal Customer,36,Personal Travel,Eco,967,1,2,1,3,1,1,1,1,2,2,3,2,3,1,23,41.0,neutral or dissatisfied +49771,10979,Female,Loyal Customer,56,Business travel,Eco,458,4,1,1,1,1,5,3,4,4,4,4,5,4,1,0,0.0,satisfied +49772,91925,Male,disloyal Customer,35,Business travel,Eco,2586,3,3,3,3,4,3,4,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +49773,54023,Female,Loyal Customer,38,Personal Travel,Eco,1091,4,1,4,4,5,4,5,5,3,2,3,3,3,5,60,41.0,neutral or dissatisfied +49774,116323,Male,Loyal Customer,45,Personal Travel,Eco,296,4,4,4,4,3,4,3,3,2,3,4,1,4,3,7,4.0,neutral or dissatisfied +49775,39989,Female,Loyal Customer,43,Business travel,Eco,508,4,3,3,3,5,3,5,4,4,4,4,1,4,5,6,0.0,satisfied +49776,87677,Female,Loyal Customer,29,Business travel,Eco,591,2,1,1,1,2,2,2,2,1,2,4,2,4,2,18,4.0,neutral or dissatisfied +49777,126495,Female,Loyal Customer,33,Personal Travel,Eco,1849,1,1,1,2,2,1,2,2,3,3,2,4,2,2,0,2.0,neutral or dissatisfied +49778,90842,Male,Loyal Customer,42,Business travel,Business,3434,4,4,4,4,4,4,4,5,5,5,5,4,5,5,4,0.0,satisfied +49779,96449,Female,disloyal Customer,21,Business travel,Eco,302,3,5,4,3,5,4,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +49780,125125,Male,Loyal Customer,39,Personal Travel,Eco,361,2,5,2,4,5,2,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +49781,36042,Female,Loyal Customer,47,Business travel,Business,399,5,5,5,5,4,5,5,4,3,1,1,5,4,5,175,191.0,satisfied +49782,127913,Male,disloyal Customer,49,Business travel,Business,1671,1,1,1,2,4,1,1,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +49783,17253,Female,disloyal Customer,19,Business travel,Eco,872,5,5,5,4,1,0,4,1,1,1,4,2,3,1,3,1.0,satisfied +49784,103032,Female,disloyal Customer,37,Business travel,Business,460,2,2,2,3,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +49785,86042,Male,Loyal Customer,18,Personal Travel,Eco,447,2,3,4,3,4,4,4,4,3,1,2,2,1,4,0,0.0,neutral or dissatisfied +49786,90293,Female,disloyal Customer,15,Business travel,Eco,757,1,1,1,4,2,1,4,2,1,2,3,4,3,2,54,39.0,neutral or dissatisfied +49787,98979,Female,Loyal Customer,43,Personal Travel,Eco,543,4,5,4,3,3,3,4,3,3,4,3,4,3,2,16,20.0,neutral or dissatisfied +49788,95388,Male,Loyal Customer,26,Personal Travel,Eco,239,2,4,0,3,3,0,3,3,5,2,5,5,5,3,2,5.0,neutral or dissatisfied +49789,18369,Male,Loyal Customer,12,Personal Travel,Eco,169,3,5,3,4,3,3,3,3,5,4,4,5,4,3,0,5.0,neutral or dissatisfied +49790,32923,Male,Loyal Customer,60,Personal Travel,Eco,121,0,1,0,1,1,0,1,1,3,4,1,4,2,1,0,0.0,satisfied +49791,58881,Male,Loyal Customer,48,Business travel,Business,2866,2,2,2,2,2,5,4,4,4,4,4,5,4,3,12,27.0,satisfied +49792,114162,Male,Loyal Customer,56,Business travel,Business,3068,1,1,1,1,5,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +49793,91961,Male,Loyal Customer,66,Personal Travel,Eco,2586,2,4,2,3,2,2,2,2,5,3,4,2,3,2,0,0.0,neutral or dissatisfied +49794,128506,Female,Loyal Customer,27,Personal Travel,Eco,651,2,5,2,4,1,2,2,1,4,1,5,1,3,1,0,0.0,neutral or dissatisfied +49795,13494,Female,Loyal Customer,37,Business travel,Business,106,2,2,2,2,4,4,2,5,5,5,4,3,5,2,0,0.0,satisfied +49796,39215,Female,Loyal Customer,54,Business travel,Eco,67,5,5,5,5,3,2,3,5,5,5,5,4,5,3,84,92.0,satisfied +49797,71176,Male,Loyal Customer,29,Business travel,Business,2232,3,3,5,3,5,5,5,5,5,2,5,4,5,5,33,31.0,satisfied +49798,77523,Female,Loyal Customer,52,Business travel,Business,3755,2,2,2,2,3,4,5,4,4,4,4,4,4,5,61,55.0,satisfied +49799,23339,Male,Loyal Customer,29,Personal Travel,Eco,456,3,5,3,3,5,3,4,5,2,4,3,4,4,5,51,46.0,neutral or dissatisfied +49800,4219,Female,Loyal Customer,31,Personal Travel,Eco,888,4,4,4,3,3,4,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +49801,104622,Male,disloyal Customer,12,Business travel,Eco,861,2,2,2,4,2,2,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +49802,34277,Male,disloyal Customer,24,Business travel,Eco,496,3,3,3,2,5,3,5,5,2,1,2,1,3,5,0,0.0,neutral or dissatisfied +49803,83617,Female,disloyal Customer,20,Business travel,Eco,409,4,0,4,5,2,4,2,2,4,3,4,4,5,2,0,0.0,satisfied +49804,19279,Female,Loyal Customer,67,Personal Travel,Eco,430,1,4,3,3,5,4,4,3,3,3,4,3,3,3,0,3.0,neutral or dissatisfied +49805,129510,Female,Loyal Customer,59,Personal Travel,Eco,1744,2,1,2,2,5,2,2,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +49806,89756,Male,Loyal Customer,29,Personal Travel,Eco,1076,1,4,1,1,4,1,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +49807,44711,Male,Loyal Customer,31,Personal Travel,Eco,67,2,5,2,5,4,2,4,4,3,5,5,4,4,4,0,17.0,neutral or dissatisfied +49808,32071,Male,Loyal Customer,38,Business travel,Eco,163,4,3,3,3,4,4,4,4,5,3,3,5,4,4,0,0.0,satisfied +49809,83208,Male,Loyal Customer,68,Personal Travel,Eco,1123,1,5,1,1,5,1,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +49810,79973,Male,Loyal Customer,38,Business travel,Eco,676,2,4,4,4,2,2,2,2,4,3,4,1,3,2,4,10.0,neutral or dissatisfied +49811,93272,Female,disloyal Customer,28,Business travel,Eco,867,2,1,1,4,1,1,1,1,4,4,4,2,4,1,30,22.0,neutral or dissatisfied +49812,98587,Female,disloyal Customer,23,Business travel,Eco,834,4,4,4,2,2,4,2,2,5,5,4,3,4,2,0,0.0,satisfied +49813,21070,Female,Loyal Customer,37,Business travel,Business,3455,2,2,2,2,2,3,1,5,5,5,5,3,5,3,0,0.0,satisfied +49814,94759,Male,disloyal Customer,37,Business travel,Business,239,5,5,5,5,1,5,1,1,5,2,5,4,5,1,2,0.0,satisfied +49815,31572,Male,Loyal Customer,47,Business travel,Eco,771,5,4,1,4,5,5,5,5,4,1,4,4,5,5,11,0.0,satisfied +49816,68139,Female,disloyal Customer,39,Business travel,Business,868,3,4,4,5,2,4,2,2,5,4,4,3,4,2,0,2.0,neutral or dissatisfied +49817,56748,Female,Loyal Customer,39,Business travel,Business,1852,2,2,2,2,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +49818,89536,Male,Loyal Customer,44,Business travel,Business,2169,3,3,1,3,5,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +49819,25982,Male,Loyal Customer,35,Business travel,Eco,577,3,3,3,3,3,3,3,3,1,2,5,1,2,3,2,0.0,satisfied +49820,110911,Male,Loyal Customer,43,Business travel,Business,581,2,4,4,4,1,3,3,2,2,2,2,2,2,2,32,39.0,neutral or dissatisfied +49821,31082,Male,Loyal Customer,58,Personal Travel,Eco Plus,641,2,4,2,4,3,2,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +49822,34260,Female,Loyal Customer,17,Personal Travel,Business,496,5,5,5,3,4,5,4,4,4,2,5,3,4,4,0,0.0,satisfied +49823,21818,Male,Loyal Customer,52,Business travel,Eco Plus,352,4,2,2,2,4,4,4,4,1,4,3,1,4,4,0,0.0,satisfied +49824,92505,Male,Loyal Customer,53,Business travel,Business,419,1,2,2,2,3,4,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +49825,82334,Male,Loyal Customer,49,Business travel,Business,2020,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,4.0,satisfied +49826,79664,Male,Loyal Customer,31,Personal Travel,Eco,762,4,4,4,5,1,4,5,1,4,2,4,4,5,1,1,13.0,neutral or dissatisfied +49827,99872,Male,Loyal Customer,53,Business travel,Business,1436,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +49828,19909,Male,Loyal Customer,43,Business travel,Eco,343,5,2,2,2,5,5,5,5,1,1,5,3,5,5,0,0.0,satisfied +49829,107820,Female,disloyal Customer,38,Business travel,Eco,349,3,3,3,3,5,3,5,5,2,4,3,2,3,5,23,33.0,neutral or dissatisfied +49830,2001,Female,Loyal Customer,51,Business travel,Business,295,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +49831,116541,Male,Loyal Customer,18,Personal Travel,Eco,337,4,4,4,4,5,4,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +49832,22894,Male,Loyal Customer,56,Business travel,Eco Plus,302,5,2,2,2,5,5,5,5,5,4,1,3,4,5,9,0.0,satisfied +49833,86584,Male,Loyal Customer,50,Business travel,Eco,1269,2,3,3,3,2,2,2,2,2,3,4,2,4,2,31,25.0,neutral or dissatisfied +49834,16726,Female,disloyal Customer,39,Business travel,Business,1167,5,5,5,1,4,5,4,4,1,1,4,4,1,4,0,0.0,satisfied +49835,16572,Female,Loyal Customer,40,Business travel,Business,3866,1,3,3,3,2,2,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +49836,69394,Female,disloyal Customer,43,Business travel,Eco,1035,2,2,2,3,4,2,4,4,3,2,2,3,3,4,0,25.0,neutral or dissatisfied +49837,71486,Female,Loyal Customer,50,Business travel,Business,3105,2,2,2,2,1,4,4,2,2,2,2,1,2,3,13,26.0,neutral or dissatisfied +49838,59749,Male,disloyal Customer,25,Business travel,Business,895,4,0,4,3,3,4,3,3,5,2,5,4,4,3,14,12.0,satisfied +49839,97679,Female,Loyal Customer,29,Personal Travel,Eco,272,1,2,1,4,3,1,3,3,4,2,4,2,3,3,22,13.0,neutral or dissatisfied +49840,128200,Female,Loyal Customer,26,Business travel,Business,3846,1,1,1,1,4,4,4,4,3,2,5,4,4,4,16,7.0,satisfied +49841,26710,Female,Loyal Customer,61,Personal Travel,Eco,406,3,4,3,3,4,5,5,5,5,3,5,4,5,5,35,47.0,neutral or dissatisfied +49842,100544,Female,Loyal Customer,29,Business travel,Business,2117,3,3,3,3,4,4,4,4,3,3,4,5,4,4,26,25.0,satisfied +49843,75373,Male,Loyal Customer,52,Business travel,Business,2218,2,5,5,5,5,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +49844,115755,Female,Loyal Customer,40,Business travel,Business,2614,3,5,5,5,1,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +49845,89095,Male,Loyal Customer,55,Business travel,Business,2092,3,3,3,3,2,4,4,3,3,4,3,5,3,5,1,0.0,satisfied +49846,32907,Male,Loyal Customer,48,Personal Travel,Eco,101,2,4,2,4,4,2,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +49847,95731,Male,Loyal Customer,40,Business travel,Business,1642,0,4,0,4,2,4,4,4,4,1,1,3,4,3,4,0.0,satisfied +49848,83309,Female,Loyal Customer,45,Business travel,Business,1671,4,2,4,4,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +49849,72367,Female,Loyal Customer,19,Business travel,Business,3832,4,4,4,4,5,5,5,5,4,3,4,5,4,5,2,0.0,satisfied +49850,35828,Female,Loyal Customer,23,Business travel,Business,2310,3,3,3,3,5,5,5,5,2,4,1,3,5,5,0,9.0,satisfied +49851,116063,Male,Loyal Customer,50,Personal Travel,Eco,337,3,3,3,5,1,3,1,1,2,5,5,5,4,1,0,2.0,neutral or dissatisfied +49852,12993,Female,disloyal Customer,43,Business travel,Eco,374,3,5,3,4,2,3,2,2,2,1,5,1,1,2,0,0.0,neutral or dissatisfied +49853,50590,Female,Loyal Customer,20,Personal Travel,Eco,109,4,4,4,3,5,4,5,5,3,5,5,5,5,5,26,32.0,satisfied +49854,57174,Female,Loyal Customer,55,Business travel,Business,2227,4,3,3,3,3,4,3,4,4,4,4,3,4,1,111,77.0,neutral or dissatisfied +49855,128764,Male,Loyal Customer,42,Business travel,Business,2761,1,5,5,5,5,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +49856,22546,Female,Loyal Customer,45,Business travel,Business,1756,3,3,3,3,3,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +49857,85463,Female,disloyal Customer,40,Business travel,Business,214,1,1,1,3,2,1,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +49858,101671,Male,Loyal Customer,45,Personal Travel,Eco,2106,2,5,2,4,2,2,2,2,1,5,5,3,3,2,9,0.0,neutral or dissatisfied +49859,50843,Female,Loyal Customer,46,Personal Travel,Eco,109,3,0,3,3,3,4,5,4,4,3,4,4,4,4,17,21.0,neutral or dissatisfied +49860,84966,Female,Loyal Customer,19,Personal Travel,Eco Plus,534,2,2,2,3,3,2,3,3,3,4,3,3,4,3,13,0.0,neutral or dissatisfied +49861,77497,Female,disloyal Customer,25,Business travel,Eco,589,3,1,3,3,1,3,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +49862,37127,Female,Loyal Customer,45,Business travel,Eco,1046,3,3,3,3,4,3,3,3,3,3,3,1,3,2,12,2.0,neutral or dissatisfied +49863,22937,Male,Loyal Customer,41,Business travel,Eco,489,3,3,1,1,3,3,3,3,3,1,4,1,1,3,0,0.0,satisfied +49864,97402,Female,Loyal Customer,37,Business travel,Business,3560,5,5,5,5,5,5,5,5,5,5,5,4,5,5,48,38.0,satisfied +49865,59369,Female,Loyal Customer,44,Business travel,Eco,2504,2,2,5,2,2,3,2,2,2,2,2,1,2,4,12,2.0,neutral or dissatisfied +49866,106653,Female,Loyal Customer,31,Business travel,Business,1590,1,1,1,1,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +49867,115866,Male,disloyal Customer,27,Business travel,Business,358,2,2,2,3,1,2,1,1,2,2,3,3,1,1,0,0.0,neutral or dissatisfied +49868,57060,Female,Loyal Customer,31,Personal Travel,Eco,2133,1,1,2,4,5,2,5,5,3,2,3,3,4,5,12,11.0,neutral or dissatisfied +49869,97808,Female,Loyal Customer,59,Business travel,Business,2960,4,4,4,4,3,4,5,2,2,2,2,5,2,4,54,37.0,satisfied +49870,54393,Male,Loyal Customer,19,Business travel,Business,305,2,3,3,3,2,2,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +49871,117182,Female,Loyal Customer,39,Personal Travel,Eco,646,1,3,1,2,4,1,4,4,4,3,2,2,3,4,0,0.0,neutral or dissatisfied +49872,11542,Female,disloyal Customer,25,Business travel,Business,657,3,0,3,2,5,3,5,5,5,5,5,3,5,5,2,0.0,neutral or dissatisfied +49873,110805,Female,Loyal Customer,55,Personal Travel,Eco,1128,1,5,1,3,3,3,4,2,2,1,2,4,2,4,0,24.0,neutral or dissatisfied +49874,117169,Female,Loyal Customer,64,Personal Travel,Eco,325,2,3,2,4,3,3,3,1,1,2,1,2,1,1,25,19.0,neutral or dissatisfied +49875,97322,Male,disloyal Customer,37,Business travel,Business,1020,3,3,3,1,5,3,5,5,4,4,4,5,4,5,4,3.0,neutral or dissatisfied +49876,79816,Female,disloyal Customer,37,Business travel,Business,1080,3,3,3,5,3,4,5,3,3,4,4,5,5,5,125,206.0,neutral or dissatisfied +49877,117881,Male,disloyal Customer,38,Business travel,Business,365,3,4,4,1,2,4,1,2,3,2,5,5,4,2,7,1.0,neutral or dissatisfied +49878,109453,Male,Loyal Customer,52,Business travel,Business,1990,3,3,3,3,3,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +49879,122982,Female,Loyal Customer,58,Business travel,Business,328,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +49880,107381,Female,disloyal Customer,37,Business travel,Business,725,3,3,3,3,5,3,5,5,5,5,5,3,5,5,60,60.0,neutral or dissatisfied +49881,67459,Male,Loyal Customer,62,Personal Travel,Eco,592,3,2,3,3,3,3,3,3,1,2,4,4,3,3,0,4.0,neutral or dissatisfied +49882,58483,Female,Loyal Customer,26,Business travel,Business,3718,1,1,1,1,4,4,4,4,4,4,4,3,4,4,24,11.0,satisfied +49883,116191,Male,Loyal Customer,19,Personal Travel,Eco,362,1,1,1,3,2,1,1,2,2,3,4,1,3,2,0,0.0,neutral or dissatisfied +49884,69441,Female,Loyal Customer,45,Personal Travel,Eco,1096,1,2,1,4,5,4,3,3,3,1,3,1,3,1,0,1.0,neutral or dissatisfied +49885,107743,Female,Loyal Customer,62,Personal Travel,Eco,405,2,1,2,3,2,3,3,2,1,3,4,3,2,3,249,288.0,neutral or dissatisfied +49886,67196,Female,Loyal Customer,24,Personal Travel,Eco,1121,2,4,2,2,2,2,2,2,3,3,4,3,4,2,8,0.0,neutral or dissatisfied +49887,112967,Female,disloyal Customer,26,Business travel,Business,1164,3,3,3,2,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +49888,15311,Female,Loyal Customer,57,Business travel,Eco,599,5,4,2,4,3,5,3,5,5,5,5,5,5,5,0,8.0,satisfied +49889,7899,Male,Loyal Customer,43,Business travel,Business,3892,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,1.0,satisfied +49890,111745,Female,Loyal Customer,59,Business travel,Eco,1154,3,4,4,4,4,2,2,3,3,3,3,4,3,4,6,0.0,neutral or dissatisfied +49891,26516,Female,Loyal Customer,33,Business travel,Business,2232,4,4,4,4,2,5,4,5,5,5,5,1,5,2,7,6.0,satisfied +49892,9447,Female,Loyal Customer,49,Business travel,Business,368,2,2,2,2,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +49893,83459,Female,Loyal Customer,35,Business travel,Business,2755,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,17.0,satisfied +49894,116595,Female,Loyal Customer,24,Business travel,Business,1765,4,4,4,4,4,4,4,4,5,4,4,4,4,4,27,18.0,satisfied +49895,46085,Male,Loyal Customer,41,Business travel,Business,3800,5,5,5,5,4,3,3,4,4,4,4,5,4,5,0,0.0,satisfied +49896,64474,Male,disloyal Customer,21,Business travel,Eco,282,0,5,0,3,2,0,2,2,4,2,5,4,5,2,2,8.0,satisfied +49897,24757,Male,Loyal Customer,45,Business travel,Business,432,3,3,3,3,1,2,1,5,5,5,5,3,5,4,3,0.0,satisfied +49898,41625,Male,Loyal Customer,68,Personal Travel,Eco Plus,1269,1,2,1,4,1,1,3,1,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +49899,19878,Female,Loyal Customer,39,Business travel,Business,2433,5,5,5,5,2,4,1,5,5,5,5,1,5,4,15,17.0,satisfied +49900,53320,Male,Loyal Customer,29,Personal Travel,Eco,901,2,1,2,4,1,2,1,1,2,3,4,3,4,1,0,0.0,neutral or dissatisfied +49901,111735,Female,Loyal Customer,59,Business travel,Business,2171,4,4,4,4,2,5,5,5,5,5,5,4,5,4,10,5.0,satisfied +49902,47688,Female,disloyal Customer,70,Personal Travel,Eco,1464,4,5,4,2,5,4,2,5,3,3,3,3,4,5,15,11.0,neutral or dissatisfied +49903,38397,Male,disloyal Customer,22,Business travel,Eco,898,1,1,1,3,2,1,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +49904,125117,Male,disloyal Customer,26,Business travel,Business,361,3,2,3,4,5,3,5,5,4,3,4,2,4,5,0,0.0,neutral or dissatisfied +49905,101852,Male,Loyal Customer,50,Business travel,Business,519,5,5,5,5,4,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +49906,40184,Female,disloyal Customer,37,Business travel,Eco,358,2,0,1,2,4,1,4,4,1,1,3,1,2,4,0,0.0,neutral or dissatisfied +49907,87836,Male,Loyal Customer,51,Personal Travel,Eco,214,2,0,2,2,5,2,3,5,3,4,5,3,4,5,38,66.0,neutral or dissatisfied +49908,9062,Female,disloyal Customer,54,Business travel,Eco,160,3,2,3,4,2,3,2,2,4,5,4,4,3,2,0,11.0,neutral or dissatisfied +49909,91809,Female,Loyal Customer,15,Personal Travel,Eco,590,4,4,4,2,5,4,3,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +49910,79646,Male,Loyal Customer,45,Business travel,Eco,362,4,1,1,1,4,4,4,4,5,1,4,2,5,4,0,0.0,satisfied +49911,125349,Male,disloyal Customer,11,Business travel,Eco,599,2,4,3,1,1,3,1,1,3,3,5,3,5,1,0,5.0,neutral or dissatisfied +49912,81575,Male,Loyal Customer,57,Business travel,Business,2370,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +49913,68696,Male,Loyal Customer,7,Personal Travel,Eco,175,4,4,4,2,4,4,4,4,3,2,5,5,5,4,6,0.0,satisfied +49914,80414,Female,Loyal Customer,43,Business travel,Business,2248,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +49915,2371,Male,Loyal Customer,69,Business travel,Eco Plus,925,3,4,4,4,3,3,3,3,3,1,3,3,4,3,0,4.0,neutral or dissatisfied +49916,49554,Male,Loyal Customer,52,Business travel,Business,2047,4,4,4,4,3,2,5,5,5,5,5,4,5,2,11,27.0,satisfied +49917,25516,Male,disloyal Customer,47,Business travel,Eco,116,3,0,3,1,5,3,5,5,5,3,4,1,5,5,19,4.0,neutral or dissatisfied +49918,129513,Female,Loyal Customer,16,Personal Travel,Eco,1744,4,3,4,3,4,4,4,4,1,2,3,1,3,4,1,0.0,neutral or dissatisfied +49919,122780,Male,disloyal Customer,40,Business travel,Business,599,4,3,3,3,5,3,5,5,5,5,5,3,4,5,0,0.0,satisfied +49920,125276,Female,Loyal Customer,56,Personal Travel,Business,678,4,5,4,2,5,5,5,3,3,4,3,4,3,5,0,3.0,satisfied +49921,93703,Female,Loyal Customer,59,Business travel,Business,689,5,5,5,5,3,4,4,5,5,5,5,4,5,3,55,46.0,satisfied +49922,50482,Male,Loyal Customer,36,Business travel,Eco,262,3,3,3,3,3,4,3,3,3,2,2,4,2,3,0,0.0,satisfied +49923,127091,Male,Loyal Customer,74,Business travel,Business,251,3,5,5,5,2,3,3,3,3,3,3,1,3,4,6,12.0,neutral or dissatisfied +49924,59052,Female,Loyal Customer,36,Business travel,Business,1723,2,2,1,2,4,4,5,4,4,5,4,3,4,3,113,88.0,satisfied +49925,92777,Female,Loyal Customer,33,Business travel,Business,1671,5,5,5,5,5,4,5,2,2,2,2,4,2,5,2,4.0,satisfied +49926,40891,Female,Loyal Customer,59,Personal Travel,Eco,588,2,4,2,4,5,5,4,2,2,2,2,5,2,3,7,0.0,neutral or dissatisfied +49927,53165,Male,disloyal Customer,26,Business travel,Eco,612,1,4,1,1,4,1,2,4,3,5,4,3,1,4,0,0.0,neutral or dissatisfied +49928,119044,Male,Loyal Customer,41,Business travel,Business,2279,4,1,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +49929,127614,Female,Loyal Customer,43,Business travel,Business,1773,5,4,5,5,5,3,5,4,4,4,4,5,4,3,0,15.0,satisfied +49930,87078,Female,Loyal Customer,31,Business travel,Business,3028,3,3,3,3,3,3,3,3,2,3,2,3,1,3,0,0.0,neutral or dissatisfied +49931,96934,Female,Loyal Customer,32,Business travel,Business,3252,1,1,1,1,2,2,2,2,3,5,5,3,4,2,0,0.0,satisfied +49932,85548,Male,Loyal Customer,58,Business travel,Business,2314,0,1,1,2,2,5,4,1,1,1,1,3,1,5,0,0.0,satisfied +49933,102291,Female,Loyal Customer,35,Business travel,Business,258,1,2,2,2,4,4,3,1,1,1,1,3,1,2,10,10.0,neutral or dissatisfied +49934,22930,Male,Loyal Customer,42,Business travel,Eco,817,4,2,2,2,4,4,4,4,3,4,3,1,5,4,0,1.0,satisfied +49935,69664,Female,Loyal Customer,9,Personal Travel,Eco,569,1,4,0,1,1,0,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +49936,111683,Male,disloyal Customer,22,Business travel,Business,541,1,2,0,4,1,0,1,1,4,5,4,2,4,1,44,44.0,neutral or dissatisfied +49937,23174,Male,Loyal Customer,30,Personal Travel,Eco,223,2,0,2,1,2,2,2,2,4,5,4,3,4,2,49,47.0,neutral or dissatisfied +49938,85727,Female,Loyal Customer,16,Personal Travel,Business,666,1,5,1,4,1,1,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +49939,113207,Male,Loyal Customer,27,Business travel,Business,197,4,4,4,4,4,4,4,4,4,4,4,4,5,4,1,0.0,satisfied +49940,74054,Female,Loyal Customer,47,Personal Travel,Eco Plus,1194,2,5,2,5,4,5,4,3,3,2,5,4,3,4,0,0.0,neutral or dissatisfied +49941,104973,Female,Loyal Customer,49,Business travel,Eco,314,2,5,2,5,5,4,4,2,2,2,2,3,2,4,11,27.0,neutral or dissatisfied +49942,124067,Female,Loyal Customer,30,Personal Travel,Eco,2153,0,4,0,1,4,0,4,4,3,5,5,4,4,4,5,0.0,satisfied +49943,122188,Male,Loyal Customer,53,Business travel,Business,2561,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +49944,77476,Female,disloyal Customer,40,Business travel,Business,2125,1,1,1,3,5,1,5,5,5,2,4,3,5,5,3,0.0,neutral or dissatisfied +49945,85107,Female,disloyal Customer,21,Business travel,Eco,731,4,4,4,2,5,4,5,5,3,4,5,3,5,5,1,0.0,satisfied +49946,58474,Male,disloyal Customer,45,Business travel,Business,719,5,5,5,2,3,5,3,3,5,2,4,5,4,3,0,0.0,satisfied +49947,3901,Male,Loyal Customer,25,Personal Travel,Eco,213,2,2,2,4,1,2,1,1,4,1,4,1,3,1,0,0.0,neutral or dissatisfied +49948,100094,Female,Loyal Customer,22,Business travel,Business,3858,5,5,5,5,2,2,2,2,4,3,4,3,4,2,0,0.0,satisfied +49949,10762,Female,Loyal Customer,60,Business travel,Business,308,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +49950,29097,Male,Loyal Customer,57,Personal Travel,Eco,954,1,4,1,4,2,1,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +49951,76825,Male,disloyal Customer,24,Business travel,Eco,1851,4,4,4,4,3,4,3,3,3,5,3,5,5,3,6,0.0,satisfied +49952,91390,Male,Loyal Customer,55,Business travel,Eco,2218,1,2,2,2,1,1,1,1,2,5,3,2,3,1,20,7.0,neutral or dissatisfied +49953,119703,Female,Loyal Customer,60,Business travel,Business,1430,5,5,5,5,4,5,4,5,5,5,5,5,5,3,50,42.0,satisfied +49954,52545,Female,Loyal Customer,38,Business travel,Eco,160,5,3,5,3,5,5,5,5,1,3,1,2,2,5,0,0.0,satisfied +49955,70654,Male,Loyal Customer,60,Business travel,Business,946,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +49956,55218,Female,Loyal Customer,52,Business travel,Business,1009,2,2,2,2,2,4,5,4,4,4,4,3,4,5,16,5.0,satisfied +49957,8484,Male,Loyal Customer,60,Business travel,Business,677,1,1,1,1,4,4,4,4,3,4,4,4,4,4,174,172.0,satisfied +49958,66778,Male,Loyal Customer,47,Personal Travel,Eco Plus,802,4,1,4,4,4,4,4,4,1,1,4,2,3,4,16,17.0,neutral or dissatisfied +49959,118643,Male,Loyal Customer,51,Business travel,Business,1516,5,5,2,5,5,4,5,4,4,4,4,4,4,3,4,4.0,satisfied +49960,117964,Female,Loyal Customer,62,Personal Travel,Eco,365,2,4,2,3,2,4,4,3,3,2,4,3,3,3,12,10.0,neutral or dissatisfied +49961,80670,Female,Loyal Customer,62,Personal Travel,Eco,821,0,2,1,2,1,2,3,2,2,1,2,4,2,3,0,0.0,satisfied +49962,82524,Male,Loyal Customer,38,Business travel,Eco,249,5,2,2,2,5,5,5,5,3,2,5,3,2,5,75,65.0,satisfied +49963,100734,Male,disloyal Customer,34,Business travel,Business,328,3,3,3,1,2,3,5,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +49964,106522,Male,Loyal Customer,39,Personal Travel,Eco,271,3,3,1,4,3,1,3,3,4,2,3,4,4,3,24,22.0,neutral or dissatisfied +49965,100608,Male,Loyal Customer,44,Business travel,Business,1670,3,3,3,3,5,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +49966,98995,Male,Loyal Customer,12,Personal Travel,Eco,543,1,5,1,2,3,1,3,3,3,5,5,4,5,3,1,0.0,neutral or dissatisfied +49967,76840,Female,disloyal Customer,47,Business travel,Business,989,3,3,3,1,5,3,5,5,4,2,4,3,5,5,13,15.0,neutral or dissatisfied +49968,88733,Male,Loyal Customer,15,Personal Travel,Eco,545,2,5,2,1,1,2,1,1,1,4,5,4,2,1,20,18.0,neutral or dissatisfied +49969,52769,Female,Loyal Customer,23,Business travel,Eco,1874,3,3,2,3,3,3,4,3,1,3,4,4,4,3,0,0.0,neutral or dissatisfied +49970,66988,Male,Loyal Customer,51,Business travel,Business,3968,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +49971,72111,Female,Loyal Customer,39,Business travel,Business,2581,3,4,4,4,5,3,4,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +49972,126264,Female,Loyal Customer,52,Business travel,Business,468,3,2,2,2,1,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +49973,118038,Male,disloyal Customer,43,Business travel,Business,1044,4,4,4,5,4,4,4,4,3,4,4,3,5,4,19,3.0,satisfied +49974,11920,Male,Loyal Customer,67,Personal Travel,Eco,744,3,5,4,4,2,4,2,2,4,3,5,4,5,2,35,32.0,neutral or dissatisfied +49975,41953,Female,disloyal Customer,22,Business travel,Eco,618,4,5,4,5,2,4,5,2,4,1,4,2,5,2,0,0.0,neutral or dissatisfied +49976,87861,Male,Loyal Customer,23,Personal Travel,Eco,214,3,2,3,3,5,3,5,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +49977,122431,Female,disloyal Customer,23,Business travel,Eco,416,3,0,3,3,2,3,2,2,1,5,1,2,4,2,0,0.0,neutral or dissatisfied +49978,100295,Male,disloyal Customer,27,Business travel,Business,1033,3,3,3,3,5,3,3,5,3,4,5,5,5,5,23,23.0,neutral or dissatisfied +49979,18072,Female,Loyal Customer,28,Personal Travel,Eco,488,5,4,5,2,1,5,1,1,1,2,4,2,4,1,10,0.0,satisfied +49980,68264,Female,Loyal Customer,68,Personal Travel,Eco,631,3,4,3,5,4,4,5,2,2,3,2,5,2,4,0,5.0,neutral or dissatisfied +49981,91097,Male,Loyal Customer,49,Personal Travel,Eco,581,1,1,1,3,3,1,3,3,2,1,4,2,4,3,0,0.0,neutral or dissatisfied +49982,91128,Male,Loyal Customer,38,Personal Travel,Eco,270,1,4,1,2,4,1,4,4,5,3,4,5,4,4,3,9.0,neutral or dissatisfied +49983,58011,Male,Loyal Customer,43,Personal Travel,Eco,1162,1,5,0,3,5,0,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +49984,75807,Male,Loyal Customer,56,Business travel,Business,1679,5,5,5,5,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +49985,79466,Male,Loyal Customer,10,Personal Travel,Eco,1183,3,5,4,5,1,4,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +49986,57601,Female,Loyal Customer,52,Business travel,Business,3302,1,1,2,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +49987,60938,Female,Loyal Customer,52,Business travel,Business,3297,5,5,5,5,3,5,5,3,3,3,3,5,3,3,5,0.0,satisfied +49988,36385,Male,Loyal Customer,60,Personal Travel,Eco,200,3,4,3,1,5,3,5,5,2,1,5,1,1,5,0,0.0,neutral or dissatisfied +49989,73168,Male,Loyal Customer,52,Business travel,Business,3218,2,2,2,2,1,2,2,4,3,3,4,2,1,2,255,244.0,neutral or dissatisfied +49990,118234,Male,Loyal Customer,44,Business travel,Business,1587,1,1,1,1,2,1,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +49991,17936,Male,Loyal Customer,53,Business travel,Business,214,4,4,4,4,2,4,2,4,4,4,5,1,4,5,0,0.0,satisfied +49992,15376,Male,Loyal Customer,56,Business travel,Business,1858,3,3,5,3,1,2,1,5,5,5,5,5,5,1,0,0.0,satisfied +49993,77402,Male,Loyal Customer,12,Personal Travel,Eco,532,3,4,3,1,5,3,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +49994,129069,Male,Loyal Customer,41,Business travel,Business,2342,2,2,2,2,4,4,4,3,3,5,4,4,5,4,3,0.0,satisfied +49995,99918,Female,Loyal Customer,48,Business travel,Business,3175,2,5,5,5,2,2,2,2,4,4,4,2,1,2,334,330.0,neutral or dissatisfied +49996,54925,Male,Loyal Customer,42,Business travel,Business,862,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +49997,50408,Female,Loyal Customer,25,Business travel,Business,1877,2,2,2,2,4,4,4,4,1,5,1,1,4,4,0,0.0,satisfied +49998,9898,Female,disloyal Customer,19,Business travel,Eco,534,5,0,5,4,1,5,1,1,4,4,5,3,5,1,12,11.0,satisfied +49999,42984,Male,disloyal Customer,33,Business travel,Eco,173,1,0,1,4,5,1,2,5,2,3,1,1,4,5,0,0.0,neutral or dissatisfied +50000,27182,Male,Loyal Customer,10,Personal Travel,Eco,2640,2,4,2,3,2,1,1,4,3,4,5,1,5,1,0,0.0,neutral or dissatisfied +50001,117266,Male,Loyal Customer,17,Personal Travel,Eco,368,1,4,2,4,4,2,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +50002,36591,Female,Loyal Customer,17,Business travel,Business,1249,2,4,4,4,2,2,2,2,4,5,4,4,4,2,0,39.0,neutral or dissatisfied +50003,64722,Male,Loyal Customer,47,Business travel,Business,1622,4,4,4,4,4,5,4,3,3,3,3,4,3,4,22,14.0,satisfied +50004,75479,Male,Loyal Customer,59,Personal Travel,Eco,2342,1,3,1,3,1,1,1,1,3,3,3,5,3,1,9,6.0,neutral or dissatisfied +50005,54287,Male,disloyal Customer,26,Business travel,Business,1075,1,1,1,3,5,1,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +50006,91248,Male,Loyal Customer,19,Personal Travel,Eco,545,2,4,2,4,5,2,5,5,4,4,4,1,4,5,0,0.0,neutral or dissatisfied +50007,49809,Female,Loyal Customer,42,Business travel,Eco,373,4,2,2,2,2,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +50008,65120,Female,Loyal Customer,31,Personal Travel,Eco,224,2,4,2,4,4,2,3,4,5,4,4,5,4,4,11,8.0,neutral or dissatisfied +50009,103769,Male,Loyal Customer,54,Business travel,Business,3789,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +50010,124222,Female,disloyal Customer,49,Business travel,Business,1916,2,2,2,5,2,2,2,2,3,3,5,4,4,2,6,0.0,neutral or dissatisfied +50011,73424,Female,Loyal Customer,68,Personal Travel,Eco,1182,3,4,3,4,2,3,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +50012,98817,Female,Loyal Customer,46,Business travel,Business,444,5,5,5,5,3,5,5,4,4,4,4,4,4,5,12,6.0,satisfied +50013,67565,Male,disloyal Customer,36,Business travel,Business,1205,3,3,3,3,5,3,3,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +50014,102820,Male,Loyal Customer,48,Personal Travel,Eco,342,4,4,4,3,3,4,3,3,4,3,4,5,5,3,0,2.0,neutral or dissatisfied +50015,32958,Female,Loyal Customer,51,Personal Travel,Eco,101,3,3,3,5,4,2,2,2,2,3,1,4,2,1,0,0.0,neutral or dissatisfied +50016,81975,Male,Loyal Customer,38,Business travel,Business,1522,2,2,5,2,2,4,4,2,2,2,2,2,2,1,64,39.0,neutral or dissatisfied +50017,113840,Male,Loyal Customer,26,Business travel,Business,1334,1,1,1,1,4,4,4,4,4,2,4,5,5,4,10,9.0,satisfied +50018,104205,Male,Loyal Customer,23,Business travel,Business,2704,4,4,4,4,5,5,5,5,5,2,4,4,4,5,12,15.0,satisfied +50019,52353,Male,Loyal Customer,15,Personal Travel,Eco,455,1,4,1,4,1,1,1,1,5,3,4,3,5,1,0,6.0,neutral or dissatisfied +50020,104346,Female,Loyal Customer,63,Personal Travel,Eco,452,2,5,2,2,3,4,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +50021,43799,Female,disloyal Customer,24,Business travel,Eco,348,2,0,2,3,3,2,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +50022,10789,Female,Loyal Customer,55,Business travel,Business,3953,4,5,5,5,3,3,3,4,4,4,4,4,4,4,0,11.0,neutral or dissatisfied +50023,63610,Male,Loyal Customer,43,Business travel,Business,1440,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,6.0,satisfied +50024,45988,Female,Loyal Customer,40,Business travel,Business,3560,5,5,5,5,5,3,5,5,5,5,5,4,5,4,42,33.0,satisfied +50025,3471,Female,Loyal Customer,18,Personal Travel,Eco Plus,315,2,4,2,3,5,2,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +50026,8431,Female,Loyal Customer,47,Personal Travel,Eco,862,1,5,1,5,3,5,5,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +50027,46713,Female,Loyal Customer,14,Personal Travel,Eco,141,5,4,5,2,1,5,1,1,4,3,4,3,5,1,0,0.0,satisfied +50028,1672,Female,Loyal Customer,46,Business travel,Business,3843,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +50029,107102,Male,Loyal Customer,61,Personal Travel,Eco,562,4,4,4,3,3,4,3,3,5,2,5,4,4,3,29,10.0,neutral or dissatisfied +50030,111546,Female,Loyal Customer,44,Business travel,Business,2297,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +50031,65131,Male,Loyal Customer,14,Personal Travel,Eco,247,2,5,2,3,3,2,3,3,3,5,4,5,4,3,34,31.0,neutral or dissatisfied +50032,10193,Female,disloyal Customer,24,Business travel,Eco,312,0,0,0,4,4,0,4,4,3,4,4,5,4,4,16,8.0,satisfied +50033,123620,Female,disloyal Customer,68,Business travel,Business,214,1,1,1,5,1,1,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +50034,21395,Female,Loyal Customer,56,Business travel,Business,377,3,3,3,3,5,2,2,4,4,5,4,1,4,4,34,32.0,satisfied +50035,118607,Female,disloyal Customer,37,Business travel,Eco,325,2,1,2,4,3,2,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +50036,8758,Male,Loyal Customer,19,Personal Travel,Eco,1147,1,4,1,2,1,1,1,1,3,2,4,3,4,1,97,84.0,neutral or dissatisfied +50037,58662,Female,Loyal Customer,16,Personal Travel,Eco,867,4,4,4,1,2,4,1,2,4,5,5,5,5,2,17,0.0,satisfied +50038,25547,Male,Loyal Customer,34,Business travel,Eco Plus,516,5,5,5,5,5,4,5,5,2,5,5,4,3,5,11,21.0,satisfied +50039,67361,Female,disloyal Customer,37,Business travel,Business,241,2,2,2,3,3,2,4,3,1,2,4,3,3,3,25,20.0,neutral or dissatisfied +50040,114462,Male,disloyal Customer,21,Business travel,Business,390,5,4,5,5,2,5,2,2,3,5,4,3,5,2,0,0.0,satisfied +50041,13474,Female,Loyal Customer,24,Business travel,Eco Plus,409,3,1,1,1,3,4,5,3,2,4,1,2,4,3,0,0.0,satisfied +50042,36959,Male,disloyal Customer,24,Business travel,Eco,667,2,5,2,4,2,2,1,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +50043,46671,Male,Loyal Customer,35,Personal Travel,Eco,73,5,4,0,3,2,0,2,2,1,1,3,3,3,2,0,0.0,satisfied +50044,28087,Male,Loyal Customer,44,Business travel,Business,873,5,5,5,5,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +50045,47073,Male,Loyal Customer,69,Personal Travel,Eco,639,1,3,1,3,5,1,3,5,4,4,2,2,2,5,15,0.0,neutral or dissatisfied +50046,40219,Male,Loyal Customer,37,Business travel,Eco,387,5,2,2,2,5,5,5,5,3,5,3,3,5,5,0,11.0,satisfied +50047,92307,Female,Loyal Customer,38,Business travel,Business,2486,2,5,5,5,4,2,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +50048,45262,Male,Loyal Customer,57,Business travel,Business,2076,5,5,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +50049,69616,Female,Loyal Customer,49,Business travel,Business,2475,3,3,3,3,4,5,5,3,2,5,5,5,3,5,5,29.0,satisfied +50050,104249,Female,Loyal Customer,50,Business travel,Eco,876,5,2,2,2,1,2,1,5,5,5,5,5,5,2,83,69.0,satisfied +50051,107886,Male,Loyal Customer,61,Business travel,Eco Plus,228,2,4,4,4,2,2,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +50052,63327,Female,disloyal Customer,20,Business travel,Eco,337,3,1,3,3,2,3,5,2,4,5,3,3,2,2,0,0.0,neutral or dissatisfied +50053,53053,Male,Loyal Customer,65,Personal Travel,Eco,1190,3,4,3,3,4,3,4,4,4,5,5,5,4,4,19,10.0,neutral or dissatisfied +50054,73021,Female,Loyal Customer,52,Personal Travel,Eco,1096,1,0,1,2,1,4,4,2,2,1,2,2,2,1,0,2.0,neutral or dissatisfied +50055,48923,Female,Loyal Customer,33,Business travel,Eco,153,5,5,5,5,5,4,5,5,2,2,4,5,5,5,3,0.0,satisfied +50056,29500,Female,Loyal Customer,12,Personal Travel,Eco,1107,2,5,2,4,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +50057,94444,Female,Loyal Customer,52,Business travel,Business,496,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,1.0,satisfied +50058,110768,Male,disloyal Customer,24,Business travel,Eco,849,0,0,0,1,2,0,2,2,4,3,4,5,4,2,0,0.0,satisfied +50059,61681,Female,Loyal Customer,27,Business travel,Business,1504,4,4,2,4,4,4,4,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +50060,41685,Male,Loyal Customer,52,Personal Travel,Eco,347,3,2,3,4,3,3,3,3,1,3,3,2,3,3,0,0.0,neutral or dissatisfied +50061,34794,Female,Loyal Customer,39,Personal Travel,Eco,264,2,2,2,4,2,2,2,2,3,3,4,2,4,2,0,5.0,neutral or dissatisfied +50062,4622,Male,Loyal Customer,45,Business travel,Business,327,0,0,0,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +50063,3313,Female,Loyal Customer,49,Business travel,Business,1613,2,1,1,1,2,3,4,2,2,2,2,1,2,2,46,66.0,neutral or dissatisfied +50064,10350,Male,Loyal Customer,27,Business travel,Business,301,5,5,3,5,4,4,4,4,3,4,5,5,5,4,22,24.0,satisfied +50065,59248,Female,disloyal Customer,18,Business travel,Business,1261,5,0,5,1,5,2,2,3,2,3,4,2,5,2,18,39.0,satisfied +50066,50889,Female,Loyal Customer,32,Personal Travel,Eco,337,3,3,3,3,1,3,1,1,2,3,3,3,3,1,3,1.0,neutral or dissatisfied +50067,17716,Male,Loyal Customer,45,Business travel,Business,1666,3,3,3,3,2,3,5,4,4,4,4,4,4,1,10,0.0,satisfied +50068,52707,Female,Loyal Customer,56,Personal Travel,Eco Plus,584,4,4,4,2,2,4,4,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +50069,92347,Male,Loyal Customer,58,Business travel,Eco,2556,2,3,3,3,2,2,2,3,5,2,2,2,1,2,0,21.0,neutral or dissatisfied +50070,97698,Male,Loyal Customer,60,Business travel,Business,3647,2,2,2,2,4,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +50071,109653,Female,Loyal Customer,30,Business travel,Business,1660,1,3,3,3,1,1,1,1,3,3,4,3,4,1,34,14.0,neutral or dissatisfied +50072,100445,Female,Loyal Customer,63,Business travel,Business,3471,3,5,5,5,3,4,3,3,3,3,3,4,3,2,47,49.0,neutral or dissatisfied +50073,119258,Male,Loyal Customer,39,Business travel,Business,3090,4,5,5,5,1,3,4,3,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +50074,99510,Male,Loyal Customer,33,Personal Travel,Eco,283,4,5,2,3,1,2,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +50075,126004,Male,Loyal Customer,35,Business travel,Business,3928,2,2,2,2,4,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +50076,92647,Female,Loyal Customer,70,Personal Travel,Eco,453,2,3,5,3,4,1,4,2,2,5,3,4,2,2,0,0.0,neutral or dissatisfied +50077,106777,Male,Loyal Customer,43,Business travel,Business,2927,2,2,2,2,5,4,4,4,4,5,4,5,4,4,0,3.0,satisfied +50078,108205,Female,Loyal Customer,43,Business travel,Business,3067,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +50079,71946,Female,disloyal Customer,55,Business travel,Business,1440,2,2,2,3,4,2,4,4,1,4,3,2,3,4,0,0.0,neutral or dissatisfied +50080,32668,Male,Loyal Customer,33,Business travel,Business,163,2,4,4,4,1,1,2,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +50081,35171,Female,Loyal Customer,25,Business travel,Business,1069,3,3,3,3,4,5,4,4,5,5,5,4,1,4,0,0.0,satisfied +50082,58839,Female,Loyal Customer,70,Personal Travel,Eco Plus,1012,1,5,1,2,1,5,3,5,5,1,2,2,5,3,35,37.0,neutral or dissatisfied +50083,79193,Male,Loyal Customer,45,Business travel,Business,1990,2,1,2,2,3,3,5,5,5,5,5,4,5,5,2,0.0,satisfied +50084,31747,Male,Loyal Customer,14,Personal Travel,Eco Plus,967,0,5,1,1,3,1,3,3,3,5,5,3,5,3,4,0.0,satisfied +50085,105049,Male,Loyal Customer,35,Personal Travel,Eco,255,2,5,0,1,1,0,1,1,5,5,4,3,5,1,27,14.0,neutral or dissatisfied +50086,54327,Male,Loyal Customer,30,Personal Travel,Eco,1597,0,2,0,4,1,0,1,1,4,1,2,2,3,1,0,0.0,satisfied +50087,64352,Female,Loyal Customer,66,Business travel,Eco,758,3,5,5,5,5,4,1,3,3,3,3,3,3,3,0,0.0,satisfied +50088,97385,Male,Loyal Customer,40,Personal Travel,Eco,347,3,4,3,3,5,3,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +50089,14183,Female,Loyal Customer,45,Business travel,Eco,620,5,1,1,1,2,2,2,5,5,5,5,3,5,1,9,0.0,satisfied +50090,2606,Female,Loyal Customer,65,Personal Travel,Eco,280,3,4,4,1,5,5,5,4,4,4,4,4,4,3,0,6.0,neutral or dissatisfied +50091,43427,Male,disloyal Customer,28,Business travel,Eco,748,4,5,5,2,1,5,1,1,5,2,4,5,3,1,75,112.0,satisfied +50092,3203,Female,Loyal Customer,55,Personal Travel,Eco,585,4,5,5,4,4,4,5,3,3,5,5,4,3,5,0,0.0,neutral or dissatisfied +50093,43993,Male,Loyal Customer,30,Business travel,Business,3091,1,1,1,1,2,2,2,2,4,4,4,2,2,2,0,0.0,satisfied +50094,46200,Male,Loyal Customer,39,Business travel,Eco Plus,472,1,1,1,1,1,1,1,1,4,4,3,4,3,1,50,39.0,neutral or dissatisfied +50095,80805,Male,Loyal Customer,49,Business travel,Business,3016,4,4,4,4,4,4,4,4,4,4,4,3,4,3,1,4.0,satisfied +50096,6111,Male,Loyal Customer,55,Personal Travel,Business,475,3,3,3,3,3,1,1,3,3,4,4,1,4,1,197,185.0,neutral or dissatisfied +50097,75034,Male,Loyal Customer,28,Personal Travel,Eco,236,4,4,4,1,5,4,2,5,4,3,4,3,5,5,6,0.0,neutral or dissatisfied +50098,112686,Female,Loyal Customer,32,Business travel,Business,2454,1,1,1,1,2,2,2,2,4,2,4,5,4,2,0,0.0,satisfied +50099,170,Female,Loyal Customer,36,Personal Travel,Eco,227,3,5,3,2,2,3,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +50100,62600,Female,disloyal Customer,33,Business travel,Eco,1106,1,1,1,2,3,1,3,3,4,1,1,5,5,3,0,0.0,neutral or dissatisfied +50101,74288,Male,disloyal Customer,17,Business travel,Eco,2288,3,3,3,4,4,3,5,4,2,3,3,1,3,4,0,4.0,neutral or dissatisfied +50102,22284,Female,Loyal Customer,30,Business travel,Business,83,5,5,4,5,5,5,4,5,4,1,3,3,3,5,0,0.0,satisfied +50103,69706,Male,disloyal Customer,28,Business travel,Eco,1372,1,1,1,4,5,1,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +50104,25437,Male,Loyal Customer,48,Business travel,Business,1855,3,3,3,3,1,2,3,5,5,4,5,2,5,2,1,5.0,satisfied +50105,36527,Male,disloyal Customer,28,Business travel,Eco,1237,3,3,3,4,3,3,5,3,4,4,1,1,3,3,2,0.0,neutral or dissatisfied +50106,4103,Female,Loyal Customer,44,Business travel,Business,3890,3,3,1,3,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +50107,39155,Female,Loyal Customer,8,Personal Travel,Eco Plus,190,4,5,4,3,1,4,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +50108,65824,Female,disloyal Customer,71,Business travel,Eco,1389,3,3,3,3,4,3,4,4,1,2,2,3,2,4,68,43.0,neutral or dissatisfied +50109,112943,Male,Loyal Customer,36,Personal Travel,Eco,1642,3,4,4,3,3,4,3,3,2,1,5,4,5,3,36,13.0,neutral or dissatisfied +50110,50526,Female,Loyal Customer,52,Personal Travel,Eco,363,4,5,4,1,4,5,4,2,2,4,2,4,2,5,1,0.0,neutral or dissatisfied +50111,3438,Male,Loyal Customer,10,Personal Travel,Eco,296,2,4,2,5,2,2,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +50112,112563,Female,Loyal Customer,52,Business travel,Business,3004,1,1,1,1,3,5,5,3,3,4,3,3,3,4,23,22.0,satisfied +50113,44457,Female,disloyal Customer,47,Business travel,Eco Plus,802,2,2,2,4,2,2,2,2,2,4,4,1,3,2,0,0.0,neutral or dissatisfied +50114,11133,Female,Loyal Customer,9,Personal Travel,Eco,74,5,4,5,2,3,5,4,3,3,2,5,5,5,3,0,0.0,satisfied +50115,81176,Female,Loyal Customer,60,Business travel,Business,980,2,2,2,2,2,4,5,4,4,4,4,5,4,4,39,17.0,satisfied +50116,25847,Female,disloyal Customer,11,Business travel,Eco,484,1,3,2,4,5,2,5,5,3,5,4,3,3,5,30,28.0,neutral or dissatisfied +50117,10682,Female,Loyal Customer,50,Business travel,Business,201,3,3,3,3,3,4,5,4,4,4,4,3,4,3,28,28.0,satisfied +50118,8795,Male,Loyal Customer,48,Business travel,Business,1771,4,4,2,2,5,3,4,4,4,4,4,4,4,4,52,47.0,neutral or dissatisfied +50119,106838,Female,disloyal Customer,34,Business travel,Eco,1733,2,1,1,4,2,2,2,2,4,4,2,2,3,2,1,8.0,neutral or dissatisfied +50120,39271,Female,disloyal Customer,50,Business travel,Eco,160,2,2,3,4,4,3,1,4,1,2,4,2,3,4,0,6.0,neutral or dissatisfied +50121,45306,Male,Loyal Customer,57,Business travel,Eco,175,5,5,5,5,5,5,5,5,1,4,1,5,4,5,0,1.0,satisfied +50122,18191,Female,Loyal Customer,34,Business travel,Eco,224,0,0,0,1,4,0,4,4,3,1,1,4,3,4,44,40.0,satisfied +50123,16217,Female,disloyal Customer,35,Business travel,Eco Plus,212,2,3,3,2,3,3,3,3,4,2,5,5,2,3,3,0.0,neutral or dissatisfied +50124,61526,Male,disloyal Customer,47,Personal Travel,Eco,2442,2,4,2,2,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +50125,58852,Female,disloyal Customer,21,Business travel,Eco,888,2,1,1,2,3,1,3,3,4,3,4,4,4,3,7,3.0,neutral or dissatisfied +50126,24168,Female,Loyal Customer,34,Business travel,Business,170,3,3,3,3,1,3,4,4,4,4,5,2,4,2,0,0.0,satisfied +50127,23576,Male,Loyal Customer,39,Business travel,Business,792,5,5,5,5,2,2,4,4,4,4,4,5,4,5,0,0.0,satisfied +50128,81134,Female,Loyal Customer,56,Personal Travel,Eco,991,3,4,3,2,3,5,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +50129,119155,Male,disloyal Customer,34,Business travel,Business,290,1,1,1,3,4,1,4,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +50130,63766,Female,Loyal Customer,53,Personal Travel,Business,1721,2,4,2,3,5,4,4,5,5,2,5,3,5,3,33,27.0,neutral or dissatisfied +50131,73172,Male,Loyal Customer,45,Business travel,Business,1258,5,5,3,5,3,5,5,4,4,4,4,4,4,3,8,0.0,satisfied +50132,55047,Female,Loyal Customer,36,Business travel,Business,1608,1,4,4,4,2,2,2,1,1,1,1,1,1,1,14,0.0,neutral or dissatisfied +50133,120709,Male,Loyal Customer,53,Business travel,Business,280,0,0,0,2,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +50134,69518,Female,Loyal Customer,64,Business travel,Business,3147,3,4,4,4,3,3,3,3,1,4,3,3,1,3,43,30.0,neutral or dissatisfied +50135,109355,Male,Loyal Customer,46,Business travel,Business,1046,1,1,1,1,2,5,5,5,5,5,5,3,5,3,39,36.0,satisfied +50136,114624,Male,Loyal Customer,41,Business travel,Business,1849,3,3,3,3,4,4,5,5,5,5,5,3,5,3,1,0.0,satisfied +50137,21405,Male,Loyal Customer,44,Business travel,Business,3150,3,1,1,1,1,3,1,3,3,3,3,1,3,1,12,41.0,neutral or dissatisfied +50138,17834,Male,Loyal Customer,48,Business travel,Eco Plus,1214,2,4,4,4,2,2,2,2,3,5,5,1,3,2,0,0.0,satisfied +50139,118925,Female,Loyal Customer,21,Personal Travel,Eco,570,2,1,2,2,3,2,3,3,3,2,2,4,2,3,0,0.0,neutral or dissatisfied +50140,80472,Female,Loyal Customer,33,Business travel,Business,2772,4,1,1,1,4,4,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +50141,9594,Female,Loyal Customer,19,Personal Travel,Eco,229,2,4,2,3,3,2,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +50142,65208,Male,Loyal Customer,43,Business travel,Business,3514,1,1,2,1,3,5,4,5,5,5,5,4,5,3,16,13.0,satisfied +50143,87187,Female,Loyal Customer,55,Business travel,Business,3390,4,1,1,1,5,4,4,4,4,4,4,2,4,2,2,0.0,neutral or dissatisfied +50144,65289,Male,Loyal Customer,32,Personal Travel,Eco Plus,224,2,5,2,2,1,2,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +50145,108919,Male,Loyal Customer,59,Personal Travel,Eco,1183,2,4,2,3,3,2,3,3,3,4,3,5,5,3,7,10.0,neutral or dissatisfied +50146,24639,Female,Loyal Customer,68,Business travel,Eco Plus,666,5,3,3,3,3,1,4,5,5,5,5,5,5,5,26,12.0,satisfied +50147,55941,Male,Loyal Customer,42,Business travel,Business,733,3,3,3,3,3,5,5,3,3,3,3,4,3,5,56,79.0,satisfied +50148,113947,Male,Loyal Customer,33,Business travel,Business,1728,4,4,4,4,4,4,4,4,3,3,3,3,5,4,5,0.0,satisfied +50149,50357,Male,Loyal Customer,52,Business travel,Eco,308,2,3,3,3,3,2,3,3,3,5,3,1,4,3,5,0.0,neutral or dissatisfied +50150,10751,Female,Loyal Customer,51,Business travel,Business,3674,1,1,1,1,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +50151,79822,Male,Loyal Customer,43,Business travel,Business,2149,1,1,1,1,5,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +50152,65874,Male,Loyal Customer,61,Personal Travel,Eco,1521,3,2,3,3,4,3,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +50153,26199,Female,Loyal Customer,30,Business travel,Business,3500,1,1,1,1,1,2,1,1,4,1,4,1,3,1,18,24.0,neutral or dissatisfied +50154,67907,Female,Loyal Customer,53,Personal Travel,Eco,1188,2,5,2,2,5,4,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +50155,128231,Female,Loyal Customer,33,Personal Travel,Eco,602,2,5,2,1,4,2,4,4,4,1,3,1,1,4,0,0.0,neutral or dissatisfied +50156,69803,Female,Loyal Customer,27,Business travel,Business,3431,1,4,3,3,1,1,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +50157,57496,Female,disloyal Customer,21,Business travel,Business,1075,5,0,5,1,2,5,2,2,5,3,4,5,4,2,0,0.0,satisfied +50158,42673,Male,Loyal Customer,27,Business travel,Business,3057,1,1,1,1,4,4,4,4,2,4,3,5,3,4,0,0.0,satisfied +50159,37663,Male,Loyal Customer,59,Personal Travel,Eco,1005,1,5,1,2,5,1,1,5,1,3,2,3,3,5,4,0.0,neutral or dissatisfied +50160,47929,Male,Loyal Customer,7,Personal Travel,Eco,550,1,2,1,4,5,1,3,5,3,2,4,1,3,5,0,12.0,neutral or dissatisfied +50161,28075,Male,Loyal Customer,40,Personal Travel,Eco,2607,4,2,4,3,4,4,4,1,1,1,3,4,1,4,98,74.0,neutral or dissatisfied +50162,51621,Male,Loyal Customer,39,Business travel,Eco,370,5,1,1,1,5,5,5,5,1,2,4,3,5,5,13,0.0,satisfied +50163,13132,Male,Loyal Customer,33,Business travel,Business,2802,3,3,3,3,4,4,4,4,4,1,4,5,2,4,4,3.0,satisfied +50164,107577,Male,Loyal Customer,31,Personal Travel,Eco,1521,3,3,3,4,2,3,1,2,4,1,2,4,4,2,6,8.0,neutral or dissatisfied +50165,126052,Female,Loyal Customer,42,Business travel,Business,3358,5,5,5,5,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +50166,114473,Male,disloyal Customer,23,Business travel,Business,446,1,1,1,3,3,1,1,3,2,4,2,2,3,3,66,64.0,neutral or dissatisfied +50167,68248,Male,Loyal Customer,53,Business travel,Eco,231,5,1,1,1,5,5,5,5,3,2,3,2,5,5,0,0.0,satisfied +50168,57575,Male,disloyal Customer,44,Business travel,Business,1597,4,4,4,2,4,4,4,4,4,3,3,5,5,4,21,4.0,satisfied +50169,86910,Male,Loyal Customer,34,Business travel,Business,3859,2,3,3,3,3,3,3,2,2,1,2,3,2,2,9,0.0,neutral or dissatisfied +50170,114127,Female,disloyal Customer,17,Business travel,Eco,862,5,5,5,1,2,5,2,2,3,3,4,4,4,2,0,0.0,satisfied +50171,61443,Male,Loyal Customer,58,Business travel,Business,2419,3,3,3,3,4,4,5,3,3,4,3,4,3,5,15,0.0,satisfied +50172,64172,Female,Loyal Customer,29,Personal Travel,Eco,989,4,5,4,1,4,4,4,4,5,3,4,5,4,4,25,5.0,satisfied +50173,17189,Male,Loyal Customer,62,Personal Travel,Eco,667,2,5,2,3,1,2,1,1,3,2,5,4,4,1,0,28.0,neutral or dissatisfied +50174,15515,Female,Loyal Customer,44,Business travel,Eco Plus,164,5,5,5,5,3,3,5,5,5,5,5,1,5,5,0,0.0,satisfied +50175,98192,Male,Loyal Customer,68,Business travel,Eco,327,3,5,5,5,3,3,3,3,4,2,4,2,4,3,1,0.0,neutral or dissatisfied +50176,59174,Female,Loyal Customer,65,Personal Travel,Eco Plus,1723,4,5,4,4,4,5,5,3,3,4,3,4,3,5,102,100.0,neutral or dissatisfied +50177,21685,Female,disloyal Customer,16,Business travel,Eco,708,2,2,2,3,3,2,3,3,4,3,3,2,3,3,0,0.0,neutral or dissatisfied +50178,7436,Male,Loyal Customer,28,Personal Travel,Eco,522,1,5,1,1,3,1,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +50179,20635,Female,Loyal Customer,22,Business travel,Business,3134,2,2,2,2,5,4,5,5,3,2,2,4,5,5,31,28.0,satisfied +50180,77390,Male,Loyal Customer,67,Business travel,Eco,190,3,5,5,5,3,3,3,3,3,4,3,3,3,3,71,42.0,neutral or dissatisfied +50181,35275,Female,Loyal Customer,52,Business travel,Eco,1056,5,2,5,5,4,5,1,5,5,5,5,2,5,5,39,28.0,satisfied +50182,103293,Male,Loyal Customer,44,Personal Travel,Eco,872,2,5,2,4,4,2,4,4,4,4,5,3,1,4,11,2.0,neutral or dissatisfied +50183,19503,Female,Loyal Customer,49,Business travel,Business,3269,3,1,1,1,2,1,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +50184,129410,Female,Loyal Customer,44,Business travel,Business,3076,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +50185,51788,Female,Loyal Customer,13,Personal Travel,Eco,370,2,2,2,2,3,2,5,3,1,1,3,2,2,3,0,0.0,neutral or dissatisfied +50186,119979,Female,Loyal Customer,70,Personal Travel,Eco,1009,2,5,2,4,4,4,5,4,4,2,1,4,4,5,0,0.0,neutral or dissatisfied +50187,53423,Male,Loyal Customer,25,Business travel,Business,2253,2,2,2,2,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +50188,95464,Female,Loyal Customer,43,Business travel,Business,2732,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +50189,128187,Female,Loyal Customer,36,Personal Travel,Eco,1849,3,1,3,2,3,3,3,3,1,2,1,3,2,3,3,10.0,neutral or dissatisfied +50190,46688,Male,Loyal Customer,42,Personal Travel,Eco,141,2,4,0,3,3,0,3,3,4,5,1,4,3,3,0,0.0,neutral or dissatisfied +50191,49973,Female,Loyal Customer,22,Business travel,Business,3341,4,2,2,2,4,4,4,4,2,4,4,1,3,4,22,4.0,neutral or dissatisfied +50192,17086,Male,disloyal Customer,36,Business travel,Eco,416,3,0,3,5,3,3,3,3,3,2,1,5,1,3,8,0.0,neutral or dissatisfied +50193,117012,Male,disloyal Customer,23,Business travel,Eco,646,4,3,4,4,4,4,1,4,4,2,3,4,4,4,15,9.0,neutral or dissatisfied +50194,43271,Female,disloyal Customer,23,Business travel,Eco,387,2,0,2,2,3,2,3,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +50195,105424,Male,disloyal Customer,26,Business travel,Eco,452,3,2,3,4,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +50196,79525,Female,Loyal Customer,39,Business travel,Business,762,5,5,5,5,5,5,5,5,5,5,5,5,5,5,37,36.0,satisfied +50197,33587,Male,Loyal Customer,41,Business travel,Business,3697,4,1,4,4,2,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +50198,95177,Male,Loyal Customer,20,Personal Travel,Eco,239,1,5,1,1,4,1,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +50199,110285,Female,Loyal Customer,39,Business travel,Business,2645,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +50200,39609,Male,Loyal Customer,48,Personal Travel,Eco,908,2,4,2,3,5,2,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +50201,70913,Female,Loyal Customer,47,Business travel,Business,3755,5,5,5,5,5,5,5,3,3,3,3,3,3,4,5,5.0,satisfied +50202,45963,Female,Loyal Customer,30,Business travel,Business,3034,3,3,2,3,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +50203,30493,Male,Loyal Customer,17,Personal Travel,Eco,627,2,4,2,1,5,2,5,5,5,5,4,4,5,5,0,13.0,neutral or dissatisfied +50204,23025,Female,disloyal Customer,24,Business travel,Eco,1020,3,3,3,1,5,3,4,5,4,1,5,1,1,5,0,0.0,neutral or dissatisfied +50205,123072,Female,disloyal Customer,30,Business travel,Business,650,5,4,4,2,2,4,5,2,4,5,4,3,5,2,2,2.0,satisfied +50206,10718,Male,Loyal Customer,32,Business travel,Business,2542,2,4,4,4,1,1,2,1,1,1,3,3,3,1,4,1.0,neutral or dissatisfied +50207,34420,Female,disloyal Customer,22,Business travel,Eco,728,1,1,1,4,3,1,3,3,1,5,3,1,3,3,41,38.0,neutral or dissatisfied +50208,41386,Male,Loyal Customer,38,Business travel,Eco,913,4,1,1,1,4,4,4,2,5,2,5,4,1,4,158,150.0,satisfied +50209,19499,Male,Loyal Customer,30,Business travel,Business,3175,3,3,3,3,2,3,2,2,1,5,1,2,4,2,49,36.0,satisfied +50210,59137,Female,Loyal Customer,49,Personal Travel,Eco,1723,3,5,3,3,5,5,5,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +50211,41668,Male,Loyal Customer,38,Business travel,Business,1798,3,3,3,3,2,3,2,4,4,4,4,2,4,2,0,0.0,satisfied +50212,54691,Female,Loyal Customer,46,Business travel,Business,3849,3,3,3,3,2,3,3,2,2,2,2,1,2,3,2,0.0,satisfied +50213,39372,Male,Loyal Customer,51,Business travel,Business,521,4,3,4,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +50214,92714,Male,Loyal Customer,43,Business travel,Business,1657,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +50215,74269,Female,Loyal Customer,50,Personal Travel,Business,2288,1,1,1,3,3,3,2,5,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +50216,22883,Female,Loyal Customer,58,Personal Travel,Eco,147,2,3,2,4,3,3,3,5,5,2,5,4,5,2,0,1.0,neutral or dissatisfied +50217,43049,Male,disloyal Customer,27,Business travel,Business,236,3,3,3,4,1,3,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +50218,69857,Female,Loyal Customer,40,Personal Travel,Eco,1055,5,5,5,3,1,5,1,1,4,4,4,4,4,1,0,0.0,satisfied +50219,20281,Male,Loyal Customer,10,Personal Travel,Eco,137,2,4,2,3,3,2,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +50220,25970,Female,Loyal Customer,12,Personal Travel,Eco,946,2,4,2,1,1,2,1,1,2,1,2,5,5,1,26,0.0,neutral or dissatisfied +50221,48550,Male,Loyal Customer,64,Personal Travel,Eco,850,3,4,3,1,2,3,2,2,5,2,2,4,1,2,0,1.0,neutral or dissatisfied +50222,15938,Female,Loyal Customer,75,Business travel,Business,128,4,1,1,1,5,4,3,2,2,2,4,2,2,4,0,8.0,neutral or dissatisfied +50223,45219,Male,Loyal Customer,30,Business travel,Business,1013,4,4,4,4,4,4,4,3,4,2,2,4,2,4,154,159.0,neutral or dissatisfied +50224,15669,Male,Loyal Customer,60,Business travel,Eco,641,4,5,5,5,4,4,4,4,1,5,1,3,3,4,5,14.0,satisfied +50225,105901,Female,disloyal Customer,28,Business travel,Business,283,3,3,3,3,4,3,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +50226,6082,Female,disloyal Customer,20,Business travel,Business,672,4,4,4,3,3,4,5,3,3,3,4,3,4,3,1,0.0,satisfied +50227,59968,Female,disloyal Customer,43,Business travel,Eco,537,3,3,3,1,3,3,3,3,3,4,5,3,3,3,0,0.0,neutral or dissatisfied +50228,26410,Female,Loyal Customer,37,Business travel,Business,1249,3,2,2,2,2,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +50229,10754,Male,disloyal Customer,45,Business travel,Eco,316,2,4,2,4,2,2,2,2,2,2,3,1,3,2,31,25.0,neutral or dissatisfied +50230,80976,Female,Loyal Customer,41,Business travel,Business,228,2,3,3,3,3,2,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +50231,2917,Male,Loyal Customer,47,Business travel,Business,3271,1,1,1,1,4,4,5,5,5,5,5,3,5,5,34,46.0,satisfied +50232,129524,Male,Loyal Customer,55,Business travel,Business,2342,4,3,4,4,5,5,4,4,4,4,4,4,4,5,51,52.0,satisfied +50233,6675,Female,Loyal Customer,43,Business travel,Business,3477,2,2,2,2,3,5,5,5,5,5,5,4,5,4,6,8.0,satisfied +50234,49482,Male,Loyal Customer,37,Business travel,Eco,110,5,3,3,3,5,5,5,5,4,3,5,4,1,5,0,0.0,satisfied +50235,46849,Female,disloyal Customer,22,Business travel,Eco,819,4,5,5,1,4,5,4,4,2,4,3,1,1,4,0,10.0,neutral or dissatisfied +50236,5244,Male,Loyal Customer,39,Business travel,Business,3072,1,4,4,4,2,3,4,1,1,1,1,2,1,4,25,27.0,neutral or dissatisfied +50237,78959,Female,Loyal Customer,51,Personal Travel,Business,356,4,1,2,4,4,4,3,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +50238,121102,Female,Loyal Customer,42,Business travel,Business,2521,5,5,5,5,5,5,5,5,4,5,4,5,3,5,68,58.0,satisfied +50239,61004,Male,Loyal Customer,47,Business travel,Business,2459,3,3,3,3,3,5,4,5,5,4,5,5,5,3,1,0.0,satisfied +50240,48749,Male,Loyal Customer,50,Business travel,Business,158,1,4,4,4,4,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +50241,26731,Female,Loyal Customer,30,Business travel,Eco Plus,515,5,4,4,4,5,5,5,5,1,4,3,4,2,5,0,0.0,satisfied +50242,83415,Female,Loyal Customer,57,Business travel,Business,2528,4,5,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +50243,29595,Male,Loyal Customer,64,Business travel,Eco,1448,1,5,5,5,1,1,1,1,1,4,4,2,3,1,1,7.0,neutral or dissatisfied +50244,74268,Female,Loyal Customer,40,Business travel,Business,2288,3,3,3,3,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +50245,65013,Female,Loyal Customer,63,Business travel,Eco,469,4,1,1,1,3,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +50246,44478,Male,Loyal Customer,36,Business travel,Business,589,3,3,3,3,1,3,1,5,5,5,5,2,5,1,25,13.0,satisfied +50247,6174,Male,Loyal Customer,41,Personal Travel,Eco,409,3,5,3,2,3,3,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +50248,59414,Male,Loyal Customer,46,Personal Travel,Eco,2556,4,5,4,1,5,4,5,5,3,4,5,4,5,5,4,0.0,neutral or dissatisfied +50249,114611,Female,Loyal Customer,59,Business travel,Business,446,4,4,4,4,2,4,5,4,4,4,4,5,4,5,48,40.0,satisfied +50250,127874,Female,disloyal Customer,25,Business travel,Eco,876,3,3,3,3,3,3,3,3,1,3,4,2,4,3,18,7.0,neutral or dissatisfied +50251,37524,Female,disloyal Customer,27,Business travel,Eco,1074,1,1,1,3,4,1,4,4,1,3,2,4,3,4,47,35.0,neutral or dissatisfied +50252,63882,Female,disloyal Customer,27,Business travel,Business,1158,2,2,2,5,5,2,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +50253,110686,Male,Loyal Customer,30,Personal Travel,Eco,1005,4,4,4,2,4,4,4,4,5,5,5,3,5,4,23,30.0,neutral or dissatisfied +50254,40521,Male,Loyal Customer,33,Personal Travel,Eco Plus,290,0,5,0,3,4,0,4,4,5,5,4,3,4,4,9,4.0,satisfied +50255,73974,Male,Loyal Customer,54,Personal Travel,Eco,2585,2,3,2,5,2,5,4,2,3,4,1,4,4,4,0,36.0,neutral or dissatisfied +50256,75695,Male,Loyal Customer,39,Business travel,Business,813,2,2,1,2,2,4,5,3,3,3,3,3,3,3,16,13.0,satisfied +50257,40676,Female,disloyal Customer,28,Business travel,Eco,584,1,0,2,2,5,2,5,5,2,5,2,4,2,5,0,0.0,neutral or dissatisfied +50258,6039,Male,Loyal Customer,26,Business travel,Eco,630,3,1,1,1,3,3,1,3,1,5,4,4,4,3,0,15.0,neutral or dissatisfied +50259,65447,Female,Loyal Customer,44,Business travel,Business,1067,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +50260,39279,Male,Loyal Customer,37,Business travel,Business,2222,4,4,4,4,1,2,5,5,5,5,4,1,5,5,0,0.0,satisfied +50261,32046,Male,Loyal Customer,41,Business travel,Eco,102,4,2,1,1,4,4,4,4,1,1,4,5,4,4,26,27.0,satisfied +50262,21521,Female,Loyal Customer,17,Personal Travel,Eco,399,0,4,0,4,2,0,2,2,3,4,5,4,5,2,0,0.0,satisfied +50263,83322,Male,Loyal Customer,60,Personal Travel,Eco,1671,2,4,2,4,3,2,3,3,4,2,4,2,3,3,0,0.0,neutral or dissatisfied +50264,94098,Female,Loyal Customer,42,Personal Travel,Business,293,1,4,1,3,2,5,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +50265,65846,Female,Loyal Customer,53,Business travel,Business,1389,2,2,2,2,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +50266,53223,Male,Loyal Customer,63,Personal Travel,Eco,589,4,5,4,2,5,4,5,5,4,3,5,5,4,5,0,0.0,satisfied +50267,5771,Female,Loyal Customer,44,Personal Travel,Eco,665,5,2,5,1,2,2,1,3,3,5,3,3,3,3,0,0.0,satisfied +50268,477,Male,Loyal Customer,57,Business travel,Business,1595,3,3,3,3,3,5,5,5,5,5,5,4,5,5,63,73.0,satisfied +50269,79800,Female,Loyal Customer,39,Business travel,Business,1035,2,2,2,2,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +50270,71154,Male,disloyal Customer,25,Business travel,Business,646,3,4,3,4,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +50271,45416,Male,Loyal Customer,61,Business travel,Eco,458,4,5,5,5,4,4,4,4,3,1,4,1,1,4,0,0.0,satisfied +50272,91640,Male,Loyal Customer,32,Personal Travel,Eco,1199,3,4,3,4,3,3,1,3,4,3,3,4,3,3,84,115.0,neutral or dissatisfied +50273,126333,Female,Loyal Customer,65,Personal Travel,Eco,468,2,5,2,3,1,1,5,5,5,2,5,3,5,2,31,57.0,neutral or dissatisfied +50274,87405,Female,Loyal Customer,19,Personal Travel,Eco,425,1,1,1,3,5,1,1,5,2,2,3,4,2,5,41,42.0,neutral or dissatisfied +50275,116788,Female,Loyal Customer,12,Personal Travel,Eco Plus,337,5,1,5,4,4,5,4,4,2,2,4,4,3,4,1,0.0,satisfied +50276,125296,Female,Loyal Customer,33,Business travel,Business,1842,3,5,5,5,2,4,4,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +50277,96038,Female,Loyal Customer,9,Business travel,Eco,795,3,4,4,4,3,2,2,3,1,3,4,4,4,3,21,10.0,neutral or dissatisfied +50278,91653,Female,Loyal Customer,55,Personal Travel,Eco,1352,3,5,3,1,3,5,4,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +50279,28041,Female,Loyal Customer,36,Personal Travel,Eco,2537,3,2,4,3,3,4,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +50280,109001,Female,disloyal Customer,48,Business travel,Business,1041,3,3,3,4,3,3,3,3,3,3,5,5,4,3,42,39.0,neutral or dissatisfied +50281,114159,Female,Loyal Customer,29,Business travel,Business,2993,3,5,1,5,3,3,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +50282,87807,Female,Loyal Customer,74,Business travel,Business,2578,1,4,4,4,4,2,2,2,2,2,1,3,2,4,0,22.0,neutral or dissatisfied +50283,34678,Male,Loyal Customer,38,Business travel,Eco,301,4,1,1,1,4,4,4,4,2,4,1,3,3,4,0,0.0,satisfied +50284,5046,Female,Loyal Customer,51,Business travel,Business,3437,0,5,0,4,5,5,5,5,5,5,2,4,5,4,1,2.0,satisfied +50285,23857,Female,Loyal Customer,11,Business travel,Business,1701,1,4,5,5,1,2,1,1,3,4,4,4,3,1,42,88.0,neutral or dissatisfied +50286,46765,Male,Loyal Customer,71,Business travel,Eco Plus,73,3,2,4,2,2,3,2,2,2,3,4,4,3,2,16,55.0,neutral or dissatisfied +50287,91500,Male,Loyal Customer,61,Personal Travel,Eco,391,2,5,4,1,5,4,5,5,5,5,4,5,4,5,0,1.0,neutral or dissatisfied +50288,20323,Female,disloyal Customer,24,Business travel,Eco,323,5,5,5,2,4,5,4,4,5,4,4,4,5,4,25,21.0,satisfied +50289,96477,Male,disloyal Customer,29,Business travel,Eco,302,3,4,3,4,4,3,1,4,4,3,3,2,4,4,18,6.0,neutral or dissatisfied +50290,52093,Male,Loyal Customer,22,Business travel,Business,3039,1,1,1,1,5,5,5,5,2,4,4,1,1,5,0,0.0,satisfied +50291,13529,Female,Loyal Customer,60,Business travel,Business,2573,3,3,3,3,5,5,4,5,5,5,3,5,5,4,13,3.0,satisfied +50292,125056,Female,Loyal Customer,53,Business travel,Business,1832,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,51.0,satisfied +50293,121025,Male,Loyal Customer,49,Personal Travel,Eco,861,0,4,1,4,4,1,4,4,2,1,4,4,3,4,0,0.0,satisfied +50294,28331,Female,disloyal Customer,52,Business travel,Eco,867,2,2,2,2,2,2,2,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +50295,115495,Female,disloyal Customer,35,Business travel,Eco,308,3,2,4,3,5,4,5,5,4,3,4,4,4,5,7,15.0,neutral or dissatisfied +50296,35932,Female,Loyal Customer,25,Personal Travel,Eco,2381,2,4,2,3,4,2,4,4,2,3,4,2,5,4,65,31.0,neutral or dissatisfied +50297,117762,Male,Loyal Customer,12,Business travel,Business,1670,1,1,4,1,1,1,1,1,4,4,4,2,3,1,0,0.0,neutral or dissatisfied +50298,56460,Male,Loyal Customer,58,Personal Travel,Eco,719,3,2,3,2,3,3,3,3,3,3,3,4,2,3,0,0.0,neutral or dissatisfied +50299,111309,Female,Loyal Customer,54,Business travel,Business,283,3,3,3,3,4,4,4,5,5,5,5,4,5,4,9,9.0,satisfied +50300,108704,Male,Loyal Customer,52,Business travel,Business,3976,1,1,1,1,2,5,4,5,5,4,5,3,5,4,5,0.0,satisfied +50301,107191,Female,disloyal Customer,24,Business travel,Eco,402,4,4,3,4,2,3,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +50302,69187,Male,Loyal Customer,26,Personal Travel,Eco,187,4,5,4,3,1,4,1,1,1,5,2,1,4,1,0,0.0,neutral or dissatisfied +50303,71246,Male,Loyal Customer,53,Business travel,Eco,733,4,2,2,2,4,4,4,4,1,5,4,2,3,4,0,0.0,neutral or dissatisfied +50304,110260,Female,Loyal Customer,58,Business travel,Business,3471,3,3,3,3,2,5,4,3,3,3,3,3,3,4,32,0.0,satisfied +50305,110765,Female,Loyal Customer,42,Business travel,Business,997,2,2,3,3,4,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +50306,7002,Female,disloyal Customer,25,Business travel,Business,234,3,5,3,2,2,3,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +50307,118880,Male,Loyal Customer,27,Personal Travel,Eco,1136,2,5,2,2,2,2,2,2,4,5,4,5,5,2,1,0.0,neutral or dissatisfied +50308,86032,Male,Loyal Customer,42,Personal Travel,Eco,447,3,4,4,2,1,4,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +50309,11409,Male,Loyal Customer,39,Business travel,Business,2111,0,4,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +50310,10683,Male,Loyal Customer,57,Business travel,Business,2768,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,1.0,satisfied +50311,7014,Female,Loyal Customer,16,Personal Travel,Eco,196,4,5,4,3,3,4,3,3,3,4,5,5,4,3,5,0.0,neutral or dissatisfied +50312,549,Male,Loyal Customer,32,Business travel,Business,113,4,4,4,4,4,4,5,4,5,3,5,4,4,4,0,0.0,satisfied +50313,50881,Female,Loyal Customer,64,Personal Travel,Eco,89,2,4,0,3,5,5,5,5,5,0,5,4,5,5,0,0.0,neutral or dissatisfied +50314,121919,Female,Loyal Customer,28,Personal Travel,Eco,449,2,5,3,3,1,3,1,1,4,3,5,4,5,1,2,0.0,neutral or dissatisfied +50315,118057,Female,Loyal Customer,72,Business travel,Eco,862,5,3,3,3,4,3,1,5,5,5,5,5,5,4,5,0.0,satisfied +50316,81784,Female,Loyal Customer,44,Business travel,Business,1416,3,5,5,5,3,3,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +50317,5483,Female,Loyal Customer,45,Business travel,Business,1801,1,1,1,1,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +50318,49281,Female,Loyal Customer,55,Business travel,Business,3077,4,4,4,4,1,3,1,5,5,5,5,3,5,4,0,0.0,satisfied +50319,34746,Female,Loyal Customer,58,Business travel,Business,3877,2,2,2,2,1,5,3,5,5,4,5,1,5,4,0,4.0,satisfied +50320,93907,Female,Loyal Customer,24,Personal Travel,Eco Plus,588,2,4,2,4,3,2,1,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +50321,15283,Female,Loyal Customer,64,Personal Travel,Eco,460,3,4,3,2,3,4,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +50322,31420,Male,Loyal Customer,54,Business travel,Business,1546,3,2,2,2,3,2,3,3,3,3,3,3,3,4,0,19.0,neutral or dissatisfied +50323,47638,Female,Loyal Customer,36,Business travel,Eco,1211,5,4,4,4,5,5,5,5,5,4,5,3,2,5,0,0.0,satisfied +50324,52999,Female,disloyal Customer,41,Business travel,Eco,1208,3,3,3,3,5,3,5,5,4,1,4,5,3,5,1,0.0,neutral or dissatisfied +50325,3936,Male,Loyal Customer,45,Business travel,Business,2638,2,2,2,2,4,5,5,5,5,5,5,3,5,3,34,28.0,satisfied +50326,114296,Male,Loyal Customer,44,Personal Travel,Eco,862,3,4,3,2,2,3,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +50327,112619,Male,Loyal Customer,65,Personal Travel,Eco,602,1,4,1,5,5,1,5,5,4,5,5,5,4,5,31,12.0,neutral or dissatisfied +50328,79549,Male,disloyal Customer,25,Business travel,Business,712,5,0,5,1,3,5,3,3,3,4,4,5,5,3,0,0.0,satisfied +50329,58807,Female,Loyal Customer,52,Personal Travel,Eco,1120,1,5,1,2,5,5,4,5,5,1,5,4,5,3,8,5.0,neutral or dissatisfied +50330,2807,Female,disloyal Customer,30,Business travel,Eco Plus,764,3,3,3,4,4,3,2,4,1,5,4,3,3,4,0,6.0,neutral or dissatisfied +50331,12913,Female,disloyal Customer,19,Business travel,Eco,456,2,2,2,3,1,2,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +50332,89386,Male,Loyal Customer,50,Business travel,Business,3114,4,4,4,4,5,5,4,5,5,5,4,3,5,3,0,6.0,satisfied +50333,19050,Female,Loyal Customer,15,Personal Travel,Eco,304,3,4,2,2,4,2,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +50334,125420,Female,Loyal Customer,9,Business travel,Business,735,2,1,1,1,2,2,2,2,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +50335,77077,Male,disloyal Customer,24,Business travel,Eco,991,4,4,4,1,2,4,2,2,1,2,5,1,4,2,2,0.0,neutral or dissatisfied +50336,108248,Male,Loyal Customer,55,Business travel,Business,2152,4,1,4,4,2,5,4,3,3,3,3,3,3,3,8,4.0,satisfied +50337,23045,Female,Loyal Customer,32,Personal Travel,Eco,833,4,4,3,3,1,3,1,1,4,3,4,5,5,1,43,23.0,neutral or dissatisfied +50338,45940,Male,Loyal Customer,53,Personal Travel,Eco,913,2,4,2,1,3,2,5,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +50339,93254,Male,disloyal Customer,26,Business travel,Business,1180,2,2,2,3,5,2,4,5,4,2,4,1,4,5,53,32.0,neutral or dissatisfied +50340,80261,Male,Loyal Customer,61,Personal Travel,Eco,1969,2,2,2,3,3,2,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +50341,61514,Male,Loyal Customer,66,Personal Travel,Eco,2288,3,1,3,3,3,3,3,2,4,2,3,3,3,3,146,105.0,neutral or dissatisfied +50342,28860,Male,Loyal Customer,44,Business travel,Business,3851,2,2,4,2,1,5,3,3,3,3,3,5,3,1,0,0.0,satisfied +50343,107402,Male,Loyal Customer,19,Business travel,Eco,717,2,5,5,5,2,3,3,2,2,1,3,4,3,2,29,11.0,neutral or dissatisfied +50344,62323,Male,Loyal Customer,46,Personal Travel,Eco,414,0,4,0,2,4,0,4,4,3,3,1,4,2,4,0,0.0,satisfied +50345,102917,Female,Loyal Customer,39,Business travel,Business,436,2,2,3,2,2,5,5,4,4,5,4,4,4,4,0,5.0,satisfied +50346,111754,Female,Loyal Customer,28,Business travel,Eco Plus,1085,2,5,3,5,2,2,2,2,3,4,4,4,3,2,27,13.0,neutral or dissatisfied +50347,102690,Female,disloyal Customer,33,Business travel,Eco,365,2,3,2,4,1,2,1,1,4,4,4,1,3,1,6,0.0,neutral or dissatisfied +50348,62254,Female,Loyal Customer,59,Business travel,Business,2425,1,1,1,1,2,3,5,3,3,3,3,3,3,5,1,0.0,satisfied +50349,31391,Female,Loyal Customer,51,Business travel,Eco Plus,834,5,2,2,2,5,5,5,2,1,3,5,5,2,5,104,149.0,satisfied +50350,8829,Female,Loyal Customer,59,Personal Travel,Eco,522,1,3,1,3,3,4,3,4,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +50351,126401,Male,Loyal Customer,46,Business travel,Business,2036,2,2,4,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +50352,7334,Male,Loyal Customer,35,Business travel,Business,606,4,4,4,4,2,5,4,4,4,4,4,4,4,4,34,28.0,satisfied +50353,117031,Male,Loyal Customer,41,Business travel,Business,2171,3,3,3,3,5,4,4,4,4,4,4,5,4,3,68,61.0,satisfied +50354,85077,Male,disloyal Customer,30,Business travel,Business,731,3,3,3,5,5,3,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +50355,87583,Male,Loyal Customer,53,Personal Travel,Eco,432,1,2,4,4,5,4,5,5,2,2,3,2,4,5,24,15.0,neutral or dissatisfied +50356,117539,Male,disloyal Customer,27,Business travel,Business,1020,4,4,4,1,1,4,1,1,3,4,4,4,4,1,0,0.0,satisfied +50357,10820,Female,disloyal Customer,26,Business travel,Eco,308,3,1,3,3,2,3,2,2,1,4,3,1,3,2,2,5.0,neutral or dissatisfied +50358,113730,Female,Loyal Customer,69,Personal Travel,Eco,386,1,5,1,5,5,5,4,5,5,1,5,4,5,3,31,29.0,neutral or dissatisfied +50359,74389,Male,Loyal Customer,56,Business travel,Business,1235,5,5,5,5,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +50360,113795,Male,Loyal Customer,59,Business travel,Business,236,2,2,2,2,5,5,5,5,5,5,5,4,5,5,16,0.0,satisfied +50361,45649,Female,Loyal Customer,15,Personal Travel,Eco,313,2,4,2,4,5,2,5,5,5,4,4,5,5,5,20,25.0,neutral or dissatisfied +50362,127491,Female,Loyal Customer,63,Personal Travel,Eco,2075,1,4,0,3,2,3,3,2,2,0,2,4,2,5,23,41.0,neutral or dissatisfied +50363,71177,Male,Loyal Customer,46,Business travel,Business,3405,3,5,5,5,3,2,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +50364,14512,Male,Loyal Customer,7,Personal Travel,Eco,328,4,1,4,1,2,4,2,2,2,1,1,1,1,2,0,0.0,neutral or dissatisfied +50365,9421,Male,Loyal Customer,51,Business travel,Business,2283,3,3,3,3,2,4,4,4,4,4,4,5,4,3,0,1.0,satisfied +50366,3536,Female,Loyal Customer,59,Personal Travel,Eco Plus,557,2,1,2,3,3,3,3,5,5,2,5,2,5,2,4,0.0,neutral or dissatisfied +50367,27568,Female,Loyal Customer,8,Personal Travel,Eco,987,1,4,1,3,1,1,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +50368,106200,Female,disloyal Customer,23,Business travel,Eco,436,1,0,1,1,1,1,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +50369,41531,Female,Loyal Customer,54,Business travel,Eco,1242,2,3,3,3,5,3,3,2,2,2,2,2,2,2,0,8.0,neutral or dissatisfied +50370,94524,Male,Loyal Customer,37,Business travel,Eco,319,3,2,5,2,3,3,3,3,4,5,3,3,4,3,76,56.0,neutral or dissatisfied +50371,68642,Female,Loyal Customer,41,Business travel,Business,3592,0,5,0,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +50372,190,Male,Loyal Customer,44,Business travel,Business,290,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +50373,127255,Female,Loyal Customer,42,Business travel,Business,1107,4,4,4,4,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +50374,64627,Male,Loyal Customer,31,Business travel,Business,247,2,4,2,2,5,5,5,5,4,4,5,3,5,5,0,6.0,satisfied +50375,31491,Male,Loyal Customer,23,Business travel,Business,853,5,5,5,5,4,4,4,4,1,3,3,5,3,4,21,15.0,satisfied +50376,105351,Female,Loyal Customer,37,Personal Travel,Eco,409,3,4,3,5,3,3,3,3,4,2,2,1,4,3,45,38.0,neutral or dissatisfied +50377,110252,Female,Loyal Customer,21,Personal Travel,Eco,1036,3,1,4,3,5,4,5,5,1,4,2,3,3,5,69,49.0,neutral or dissatisfied +50378,59726,Female,disloyal Customer,39,Business travel,Eco Plus,565,1,1,1,3,3,1,3,3,3,2,4,4,3,3,17,36.0,neutral or dissatisfied +50379,45978,Male,Loyal Customer,43,Business travel,Business,483,5,5,5,5,2,4,1,5,5,5,5,2,5,1,9,4.0,satisfied +50380,70588,Male,Loyal Customer,39,Business travel,Business,1258,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +50381,107727,Male,Loyal Customer,49,Personal Travel,Eco,251,2,5,2,2,2,2,2,2,5,2,4,3,4,2,7,1.0,neutral or dissatisfied +50382,81660,Male,Loyal Customer,22,Business travel,Business,907,5,5,5,5,4,4,4,4,3,2,4,4,5,4,0,13.0,satisfied +50383,97376,Female,Loyal Customer,24,Personal Travel,Eco,1020,2,3,2,3,2,2,2,2,4,3,2,4,3,2,0,0.0,neutral or dissatisfied +50384,103880,Male,Loyal Customer,25,Personal Travel,Eco,1048,1,4,1,2,2,1,2,2,4,2,4,3,5,2,15,1.0,neutral or dissatisfied +50385,99656,Male,Loyal Customer,45,Business travel,Business,650,2,4,4,4,2,3,3,2,2,2,2,1,2,2,56,73.0,neutral or dissatisfied +50386,99930,Female,disloyal Customer,45,Business travel,Eco,764,4,3,3,4,4,3,4,4,2,5,4,1,3,4,59,69.0,neutral or dissatisfied +50387,56978,Male,Loyal Customer,53,Personal Travel,Eco,2454,3,1,2,4,2,5,5,1,2,3,4,5,2,5,5,22.0,neutral or dissatisfied +50388,48719,Male,Loyal Customer,45,Business travel,Business,156,1,1,1,1,4,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +50389,82938,Female,Loyal Customer,29,Business travel,Eco Plus,594,4,2,2,2,4,4,4,4,4,2,4,3,1,4,0,0.0,satisfied +50390,64842,Female,Loyal Customer,41,Business travel,Business,247,1,1,1,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +50391,69829,Female,Loyal Customer,48,Business travel,Eco,1055,1,2,4,2,2,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +50392,116762,Male,Loyal Customer,70,Personal Travel,Eco Plus,337,4,3,4,4,3,4,3,3,3,2,4,1,4,3,77,62.0,neutral or dissatisfied +50393,56496,Female,Loyal Customer,51,Business travel,Business,1085,3,3,3,3,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +50394,106871,Female,Loyal Customer,43,Business travel,Business,577,4,4,4,4,4,5,4,2,2,2,2,5,2,5,1,0.0,satisfied +50395,30925,Female,Loyal Customer,50,Personal Travel,Eco,896,4,1,4,3,2,2,3,1,1,4,1,4,1,1,21,38.0,neutral or dissatisfied +50396,69364,Female,Loyal Customer,27,Business travel,Business,2608,3,3,3,3,3,3,3,3,3,5,5,5,4,3,0,44.0,satisfied +50397,38033,Male,Loyal Customer,29,Business travel,Eco,1185,4,2,2,2,4,4,4,4,5,3,3,4,4,4,0,0.0,satisfied +50398,62162,Female,disloyal Customer,22,Business travel,Eco,1289,3,3,3,4,4,3,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +50399,11190,Male,Loyal Customer,60,Personal Travel,Eco,224,1,2,1,3,4,1,5,4,2,4,3,2,2,4,43,42.0,neutral or dissatisfied +50400,5108,Male,Loyal Customer,41,Personal Travel,Eco,224,3,5,0,1,3,0,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +50401,48807,Male,Loyal Customer,50,Personal Travel,Business,250,3,4,3,4,2,5,5,4,4,3,4,3,4,4,80,73.0,neutral or dissatisfied +50402,7989,Female,Loyal Customer,36,Business travel,Business,125,0,4,0,4,4,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +50403,89096,Male,Loyal Customer,31,Business travel,Eco,1947,3,1,1,1,3,3,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +50404,16006,Female,Loyal Customer,52,Business travel,Business,3432,1,3,3,3,4,4,3,1,1,1,1,2,1,1,41,57.0,neutral or dissatisfied +50405,105409,Female,Loyal Customer,44,Business travel,Business,2351,1,1,1,1,2,5,5,4,4,4,4,4,4,3,22,4.0,satisfied +50406,7088,Female,Loyal Customer,51,Business travel,Business,1734,2,1,1,1,3,3,4,4,4,4,2,3,4,1,1,0.0,neutral or dissatisfied +50407,123880,Female,Loyal Customer,68,Business travel,Business,1968,4,4,4,4,5,3,2,4,4,4,3,4,4,3,0,0.0,satisfied +50408,19348,Male,disloyal Customer,52,Business travel,Eco,692,1,1,1,3,5,1,5,5,2,2,5,4,2,5,7,0.0,neutral or dissatisfied +50409,41744,Female,Loyal Customer,14,Personal Travel,Eco,695,2,2,2,4,3,2,5,3,3,1,3,3,4,3,16,5.0,neutral or dissatisfied +50410,66603,Female,Loyal Customer,70,Personal Travel,Eco,761,1,5,2,3,2,5,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +50411,12301,Female,Loyal Customer,50,Business travel,Business,253,0,0,0,4,4,4,4,4,4,4,4,5,4,2,0,0.0,satisfied +50412,83066,Male,Loyal Customer,43,Business travel,Business,1022,5,5,5,5,2,5,5,4,4,4,4,3,4,4,21,0.0,satisfied +50413,25200,Female,Loyal Customer,37,Business travel,Business,3560,3,3,3,3,4,3,2,3,3,3,3,4,3,4,18,20.0,neutral or dissatisfied +50414,101558,Female,Loyal Customer,51,Business travel,Business,2270,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,2.0,satisfied +50415,70091,Female,Loyal Customer,55,Business travel,Business,460,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +50416,45952,Female,Loyal Customer,21,Personal Travel,Eco,641,3,2,4,3,5,4,5,5,4,1,2,2,3,5,5,18.0,neutral or dissatisfied +50417,29673,Male,Loyal Customer,27,Business travel,Eco Plus,909,5,2,2,2,5,5,5,5,5,2,4,2,1,5,0,0.0,satisfied +50418,125806,Female,Loyal Customer,55,Business travel,Business,951,3,3,3,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +50419,83247,Female,Loyal Customer,19,Business travel,Eco,2079,2,4,4,4,1,2,2,2,2,1,2,2,3,2,313,296.0,neutral or dissatisfied +50420,100348,Male,Loyal Customer,70,Personal Travel,Eco,1204,2,4,2,2,4,2,4,4,4,2,3,5,2,4,0,0.0,neutral or dissatisfied +50421,83566,Female,Loyal Customer,44,Business travel,Business,2162,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +50422,82100,Male,Loyal Customer,37,Personal Travel,Eco,1276,1,4,1,4,5,1,2,5,4,5,4,3,5,5,25,25.0,neutral or dissatisfied +50423,19827,Female,disloyal Customer,34,Business travel,Eco,632,1,0,1,4,5,1,3,5,4,4,2,5,1,5,9,2.0,neutral or dissatisfied +50424,116145,Female,Loyal Customer,15,Personal Travel,Eco,446,2,5,2,3,2,1,1,3,3,5,5,1,3,1,231,235.0,neutral or dissatisfied +50425,106679,Female,disloyal Customer,37,Business travel,Business,451,1,1,1,2,1,1,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +50426,64137,Female,Loyal Customer,43,Business travel,Eco,989,2,1,1,1,2,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +50427,26933,Male,Loyal Customer,30,Personal Travel,Eco Plus,1874,3,1,4,4,4,4,4,4,4,1,3,4,4,4,7,31.0,neutral or dissatisfied +50428,82851,Female,Loyal Customer,52,Business travel,Eco,594,1,1,1,1,3,3,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +50429,111332,Male,Loyal Customer,41,Personal Travel,Eco,283,2,4,5,3,5,5,5,5,3,5,4,4,5,5,0,41.0,neutral or dissatisfied +50430,125783,Male,disloyal Customer,29,Business travel,Business,992,0,0,0,5,4,0,4,4,4,5,5,5,5,4,10,0.0,satisfied +50431,110427,Male,Loyal Customer,58,Business travel,Eco,919,2,3,3,3,2,2,2,2,2,1,3,3,3,2,47,41.0,neutral or dissatisfied +50432,72411,Male,Loyal Customer,44,Business travel,Business,3938,5,5,5,5,4,4,4,3,3,4,3,3,3,3,42,26.0,satisfied +50433,62941,Female,Loyal Customer,60,Business travel,Business,967,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +50434,20682,Female,Loyal Customer,16,Personal Travel,Eco,552,2,4,2,3,5,2,2,5,4,1,5,3,3,5,0,25.0,neutral or dissatisfied +50435,51160,Male,Loyal Customer,52,Personal Travel,Eco,363,2,5,2,1,4,2,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +50436,102681,Female,Loyal Customer,69,Business travel,Eco,255,2,1,1,1,5,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +50437,120357,Male,Loyal Customer,46,Business travel,Business,3553,4,4,4,4,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +50438,93944,Female,Loyal Customer,61,Personal Travel,Eco,507,0,5,0,4,2,4,4,1,1,0,1,4,1,3,24,14.0,satisfied +50439,11822,Male,Loyal Customer,46,Business travel,Business,986,1,1,1,1,2,4,5,4,4,4,4,4,4,4,3,34.0,satisfied +50440,85885,Male,Loyal Customer,28,Personal Travel,Eco,2172,3,2,2,4,3,2,3,3,1,4,4,3,3,3,15,13.0,neutral or dissatisfied +50441,62831,Female,Loyal Customer,47,Business travel,Business,2556,2,2,4,2,5,4,4,4,4,4,4,4,4,5,7,13.0,satisfied +50442,9374,Female,disloyal Customer,23,Business travel,Eco,441,2,4,3,1,4,3,4,4,2,5,2,2,1,4,0,0.0,neutral or dissatisfied +50443,40433,Male,disloyal Customer,21,Business travel,Eco,175,4,4,5,4,4,5,4,4,3,3,3,2,1,4,0,0.0,neutral or dissatisfied +50444,94385,Male,Loyal Customer,46,Business travel,Eco,248,2,2,2,2,2,2,2,2,1,2,3,1,3,2,0,6.0,neutral or dissatisfied +50445,66145,Male,Loyal Customer,30,Personal Travel,Eco,583,1,4,2,1,3,2,2,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +50446,120279,Female,Loyal Customer,57,Business travel,Business,1576,4,4,4,4,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +50447,66611,Female,Loyal Customer,50,Personal Travel,Eco,761,1,1,1,4,5,3,3,4,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +50448,76949,Male,disloyal Customer,25,Business travel,Eco,832,5,5,5,4,2,5,2,2,4,4,5,3,4,2,21,7.0,satisfied +50449,61894,Female,disloyal Customer,39,Business travel,Business,2521,3,3,3,3,3,3,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +50450,101966,Female,disloyal Customer,21,Business travel,Business,228,5,0,5,2,2,5,2,2,2,4,1,3,3,2,0,0.0,satisfied +50451,106727,Female,Loyal Customer,59,Business travel,Business,829,1,1,1,1,5,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +50452,38769,Female,Loyal Customer,46,Business travel,Eco,353,4,1,5,1,4,2,2,4,4,4,4,5,4,2,0,0.0,satisfied +50453,41102,Female,Loyal Customer,37,Business travel,Business,224,3,3,3,3,1,2,4,5,5,5,4,5,5,1,0,0.0,satisfied +50454,11944,Female,disloyal Customer,64,Business travel,Eco,781,3,4,4,3,3,4,3,3,1,3,4,1,4,3,85,82.0,neutral or dissatisfied +50455,111250,Female,Loyal Customer,41,Business travel,Business,1788,3,3,5,3,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +50456,49376,Male,disloyal Customer,34,Business travel,Eco,304,1,0,1,3,2,1,2,2,3,1,2,1,1,2,0,0.0,neutral or dissatisfied +50457,61417,Female,Loyal Customer,50,Business travel,Business,679,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +50458,39834,Female,Loyal Customer,64,Business travel,Business,1516,3,3,3,3,5,4,5,4,4,4,4,1,4,3,0,0.0,satisfied +50459,15132,Male,Loyal Customer,25,Business travel,Business,912,3,1,1,1,3,3,3,3,1,4,3,1,3,3,33,44.0,neutral or dissatisfied +50460,96474,Female,Loyal Customer,28,Business travel,Business,2196,2,2,2,2,4,4,4,4,5,2,4,4,4,4,10,0.0,satisfied +50461,111438,Female,disloyal Customer,45,Business travel,Business,1024,1,1,1,2,5,1,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +50462,31438,Female,Loyal Customer,57,Personal Travel,Eco Plus,1546,2,5,2,2,5,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +50463,44141,Male,Loyal Customer,15,Personal Travel,Eco,120,3,5,3,3,1,3,1,1,2,3,1,5,3,1,0,0.0,neutral or dissatisfied +50464,70456,Male,Loyal Customer,55,Business travel,Business,867,4,4,4,4,3,4,5,4,4,4,4,4,4,4,122,128.0,satisfied +50465,112284,Male,Loyal Customer,23,Personal Travel,Eco,1546,2,4,2,3,1,2,1,1,4,5,5,4,5,1,113,120.0,neutral or dissatisfied +50466,101378,Male,Loyal Customer,42,Business travel,Business,3887,2,2,4,2,2,4,5,5,5,5,5,5,5,4,24,15.0,satisfied +50467,110666,Female,Loyal Customer,44,Business travel,Business,829,3,3,3,3,2,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +50468,99378,Female,Loyal Customer,59,Business travel,Business,337,4,4,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +50469,104662,Female,disloyal Customer,30,Business travel,Business,641,2,2,2,4,1,2,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +50470,38242,Male,Loyal Customer,54,Business travel,Eco,1111,4,3,3,3,5,4,5,5,2,1,5,5,1,5,29,13.0,satisfied +50471,88268,Male,Loyal Customer,29,Business travel,Business,1929,5,5,2,5,3,3,3,3,4,4,4,4,5,3,20,13.0,satisfied +50472,98268,Male,disloyal Customer,35,Business travel,Business,1136,2,2,2,4,3,2,3,3,4,1,3,1,3,3,37,39.0,neutral or dissatisfied +50473,77254,Male,Loyal Customer,25,Personal Travel,Eco,1590,3,5,3,1,3,3,4,3,5,5,5,3,4,3,1,0.0,neutral or dissatisfied +50474,83152,Female,disloyal Customer,29,Business travel,Business,1084,4,4,4,3,5,4,5,5,3,2,4,5,5,5,101,110.0,satisfied +50475,94139,Female,Loyal Customer,50,Business travel,Business,1790,5,3,5,5,5,4,5,5,5,5,5,3,5,5,45,41.0,satisfied +50476,83311,Male,disloyal Customer,22,Business travel,Eco,816,4,4,4,3,4,4,4,4,4,2,5,5,4,4,1,0.0,neutral or dissatisfied +50477,81623,Female,Loyal Customer,55,Business travel,Business,3359,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,17.0,satisfied +50478,3108,Male,Loyal Customer,62,Personal Travel,Eco Plus,413,1,5,3,1,5,3,5,5,5,4,4,2,5,5,0,9.0,neutral or dissatisfied +50479,111105,Male,Loyal Customer,65,Business travel,Eco Plus,268,2,3,3,3,1,2,1,1,1,3,4,1,4,1,5,10.0,neutral or dissatisfied +50480,66321,Male,Loyal Customer,32,Personal Travel,Eco,852,2,5,2,3,5,2,5,5,4,2,4,4,4,5,11,12.0,neutral or dissatisfied +50481,92731,Male,disloyal Customer,10,Business travel,Eco,1276,1,1,1,3,5,1,5,5,4,1,3,3,3,5,0,31.0,neutral or dissatisfied +50482,94646,Female,disloyal Customer,48,Business travel,Eco,239,3,2,3,3,2,3,5,2,2,1,2,3,2,2,13,2.0,neutral or dissatisfied +50483,27399,Male,Loyal Customer,53,Business travel,Eco,679,4,5,5,5,4,4,4,4,4,3,1,3,5,4,0,0.0,satisfied +50484,33642,Male,Loyal Customer,11,Personal Travel,Eco,399,2,4,2,2,1,2,1,1,5,4,4,4,5,1,7,0.0,neutral or dissatisfied +50485,115250,Male,Loyal Customer,38,Business travel,Business,296,4,1,1,1,2,3,3,4,4,4,4,4,4,2,8,0.0,neutral or dissatisfied +50486,60199,Male,Loyal Customer,40,Business travel,Business,1709,1,1,1,1,4,3,5,4,4,4,4,4,4,4,0,19.0,satisfied +50487,61102,Male,Loyal Customer,70,Personal Travel,Eco,1546,3,4,3,3,4,3,4,4,5,4,4,5,5,4,0,1.0,neutral or dissatisfied +50488,89811,Female,Loyal Customer,39,Business travel,Business,944,1,1,4,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +50489,60886,Female,Loyal Customer,47,Personal Travel,Eco,1062,5,1,5,4,3,4,4,1,1,5,1,4,1,1,0,13.0,satisfied +50490,111834,Male,Loyal Customer,42,Business travel,Business,1005,4,4,4,4,4,5,4,3,3,5,3,4,3,1,0,0.0,satisfied +50491,81075,Male,Loyal Customer,39,Business travel,Business,1841,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,13.0,satisfied +50492,117730,Male,Loyal Customer,27,Business travel,Business,2891,3,3,3,3,4,4,4,4,3,5,4,4,4,4,176,173.0,satisfied +50493,89883,Female,Loyal Customer,23,Business travel,Business,1416,4,3,3,3,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +50494,46741,Female,Loyal Customer,20,Personal Travel,Eco,152,0,5,0,1,5,0,3,5,4,3,5,3,5,5,0,0.0,satisfied +50495,109300,Male,disloyal Customer,38,Business travel,Business,1136,3,3,3,4,5,3,5,5,3,4,4,5,5,5,8,0.0,neutral or dissatisfied +50496,53363,Male,disloyal Customer,41,Business travel,Eco,1452,1,1,1,3,1,1,4,1,4,1,3,1,5,1,0,7.0,neutral or dissatisfied +50497,36617,Female,Loyal Customer,53,Business travel,Eco,785,5,1,1,1,5,4,1,5,5,5,5,2,5,3,11,36.0,satisfied +50498,57630,Male,Loyal Customer,57,Business travel,Business,200,5,5,3,5,5,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +50499,44903,Female,Loyal Customer,22,Personal Travel,Eco,536,3,4,3,3,2,3,4,2,3,2,5,5,4,2,5,0.0,neutral or dissatisfied +50500,82302,Male,disloyal Customer,29,Business travel,Business,986,3,3,3,3,1,3,5,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +50501,119707,Female,Loyal Customer,36,Business travel,Business,1303,5,5,5,5,4,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +50502,93731,Male,Loyal Customer,43,Business travel,Eco Plus,630,3,2,5,2,3,3,3,3,2,2,4,1,4,3,33,47.0,neutral or dissatisfied +50503,12218,Male,Loyal Customer,36,Personal Travel,Business,201,4,4,4,3,1,3,3,3,3,4,3,4,3,4,0,0.0,satisfied +50504,89972,Female,Loyal Customer,70,Personal Travel,Eco,1416,2,5,2,1,4,4,2,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +50505,40622,Male,Loyal Customer,28,Personal Travel,Eco,391,1,4,1,1,3,1,4,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +50506,89414,Female,Loyal Customer,31,Business travel,Eco,151,1,5,2,5,1,1,1,1,1,5,3,2,4,1,11,10.0,neutral or dissatisfied +50507,111199,Male,disloyal Customer,26,Business travel,Business,1447,2,2,2,2,2,2,2,2,4,5,4,3,4,2,0,1.0,neutral or dissatisfied +50508,124180,Female,Loyal Customer,31,Business travel,Business,2089,1,1,1,1,2,2,2,2,3,2,3,4,4,2,0,0.0,satisfied +50509,86223,Male,disloyal Customer,27,Business travel,Eco,164,2,3,2,4,2,2,2,2,2,5,1,3,3,2,71,66.0,neutral or dissatisfied +50510,1083,Male,Loyal Customer,22,Personal Travel,Eco,354,5,3,5,3,3,5,5,3,1,2,4,4,3,3,0,0.0,satisfied +50511,84593,Male,Loyal Customer,24,Business travel,Business,2680,4,4,4,4,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +50512,3832,Female,Loyal Customer,18,Business travel,Business,3230,1,0,0,4,5,0,5,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +50513,129707,Male,Loyal Customer,39,Business travel,Business,337,1,1,4,1,4,5,4,4,4,4,4,4,4,4,3,8.0,satisfied +50514,85220,Male,disloyal Customer,20,Business travel,Eco,874,1,1,1,4,4,1,4,4,3,4,3,3,4,4,24,14.0,neutral or dissatisfied +50515,405,Male,Loyal Customer,59,Business travel,Business,309,3,2,2,2,3,2,2,3,3,3,3,2,3,4,48,55.0,neutral or dissatisfied +50516,29971,Female,Loyal Customer,15,Business travel,Business,2569,3,3,3,3,5,5,5,5,3,4,2,1,3,5,0,0.0,satisfied +50517,115913,Male,Loyal Customer,36,Business travel,Eco,446,1,5,3,5,1,1,1,1,4,3,3,4,3,1,18,39.0,neutral or dissatisfied +50518,52145,Female,disloyal Customer,16,Business travel,Business,370,0,0,0,4,2,0,2,2,3,5,5,5,4,2,0,0.0,satisfied +50519,47500,Male,Loyal Customer,7,Personal Travel,Eco,588,1,4,2,2,3,2,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +50520,56234,Female,Loyal Customer,48,Business travel,Business,1608,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,19.0,satisfied +50521,61264,Male,Loyal Customer,28,Personal Travel,Eco,948,1,5,1,3,1,1,1,1,2,5,5,4,4,1,27,17.0,neutral or dissatisfied +50522,14399,Male,Loyal Customer,29,Personal Travel,Eco,900,2,4,2,4,1,2,1,1,2,2,1,4,1,1,0,0.0,neutral or dissatisfied +50523,15300,Female,Loyal Customer,61,Business travel,Business,1923,4,4,4,4,5,3,3,5,5,5,3,1,5,4,0,0.0,satisfied +50524,123123,Female,Loyal Customer,17,Business travel,Business,507,4,1,1,1,4,4,4,4,1,4,4,1,4,4,3,4.0,neutral or dissatisfied +50525,37985,Male,Loyal Customer,40,Business travel,Eco,1091,4,5,5,5,4,4,4,4,1,3,3,5,1,4,0,0.0,satisfied +50526,104238,Female,disloyal Customer,20,Business travel,Eco,1276,3,3,3,2,4,3,4,4,4,1,3,2,2,4,106,108.0,neutral or dissatisfied +50527,39612,Female,Loyal Customer,59,Personal Travel,Eco,954,1,4,1,3,4,1,2,5,5,1,5,3,5,2,0,8.0,neutral or dissatisfied +50528,125882,Female,Loyal Customer,26,Personal Travel,Eco,992,4,4,4,4,4,4,5,4,4,5,5,4,5,4,0,5.0,satisfied +50529,89088,Female,Loyal Customer,60,Business travel,Business,1947,3,3,3,3,2,3,4,4,4,4,4,5,4,4,6,0.0,satisfied +50530,96059,Female,Loyal Customer,34,Business travel,Business,795,2,3,3,3,2,4,3,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +50531,70100,Male,disloyal Customer,27,Business travel,Eco,550,1,1,2,3,4,2,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +50532,11629,Female,Loyal Customer,73,Business travel,Eco Plus,468,5,5,5,5,4,1,5,4,4,5,4,2,4,5,20,5.0,satisfied +50533,77586,Female,disloyal Customer,26,Business travel,Business,813,3,0,3,4,3,3,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +50534,101786,Male,Loyal Customer,38,Business travel,Business,1521,5,5,3,5,4,4,5,5,5,5,5,3,5,4,9,0.0,satisfied +50535,41173,Male,Loyal Customer,35,Business travel,Eco Plus,224,3,5,3,3,3,3,3,3,3,4,4,3,4,3,4,6.0,neutral or dissatisfied +50536,11301,Male,Loyal Customer,14,Personal Travel,Eco,312,4,4,4,2,2,4,3,2,3,5,5,4,4,2,7,4.0,neutral or dissatisfied +50537,30453,Male,Loyal Customer,50,Business travel,Eco,991,3,5,5,5,3,3,3,3,1,4,4,4,4,3,11,2.0,neutral or dissatisfied +50538,78236,Female,Loyal Customer,49,Business travel,Business,259,0,0,0,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +50539,67712,Female,disloyal Customer,30,Business travel,Eco,1133,3,3,3,3,2,3,2,2,2,5,3,1,3,2,0,9.0,neutral or dissatisfied +50540,50175,Female,disloyal Customer,24,Business travel,Eco,373,1,2,1,3,1,1,1,1,1,5,3,3,4,1,2,0.0,neutral or dissatisfied +50541,72051,Male,Loyal Customer,43,Business travel,Business,2615,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +50542,41514,Female,Loyal Customer,38,Business travel,Business,1211,5,5,5,5,5,3,5,4,4,4,4,1,4,1,0,0.0,satisfied +50543,50433,Female,disloyal Customer,23,Business travel,Eco,109,5,5,5,1,4,5,4,4,1,1,1,4,4,4,0,0.0,satisfied +50544,28589,Female,Loyal Customer,51,Personal Travel,Eco,2603,3,1,3,4,3,4,4,2,4,4,3,4,1,4,0,3.0,neutral or dissatisfied +50545,56071,Female,Loyal Customer,40,Personal Travel,Eco,2586,1,3,1,3,1,3,3,1,1,2,2,3,3,3,0,0.0,neutral or dissatisfied +50546,21280,Male,Loyal Customer,30,Business travel,Business,692,3,3,3,3,2,2,2,2,3,4,3,5,2,2,45,23.0,satisfied +50547,30548,Female,disloyal Customer,32,Business travel,Eco,955,3,4,4,3,1,4,1,1,2,1,4,1,3,1,3,0.0,neutral or dissatisfied +50548,16842,Male,Loyal Customer,32,Personal Travel,Eco,645,3,4,3,1,5,3,1,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +50549,104830,Female,Loyal Customer,29,Business travel,Business,472,2,3,2,2,4,4,4,4,4,3,5,4,4,4,2,0.0,satisfied +50550,19177,Male,Loyal Customer,54,Business travel,Business,3110,5,5,3,5,3,3,3,5,5,5,5,4,5,4,129,130.0,satisfied +50551,116408,Male,Loyal Customer,7,Personal Travel,Eco,337,3,4,3,3,2,3,1,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +50552,43565,Female,Loyal Customer,40,Personal Travel,Eco Plus,637,4,5,4,2,4,4,4,4,4,4,4,3,4,4,42,54.0,neutral or dissatisfied +50553,285,Female,Loyal Customer,45,Business travel,Business,825,1,1,5,5,3,4,4,1,1,1,1,1,1,2,2,0.0,neutral or dissatisfied +50554,8887,Male,Loyal Customer,25,Personal Travel,Eco,622,3,4,3,4,5,3,5,5,4,2,5,3,4,5,18,17.0,neutral or dissatisfied +50555,68229,Male,Loyal Customer,63,Business travel,Business,3222,1,1,3,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +50556,34124,Female,disloyal Customer,28,Business travel,Eco,1046,2,2,2,3,1,2,1,1,3,1,4,1,3,1,104,90.0,neutral or dissatisfied +50557,88551,Male,Loyal Customer,35,Personal Travel,Eco,250,4,5,4,1,3,4,3,3,5,5,5,5,5,3,29,24.0,neutral or dissatisfied +50558,69398,Male,Loyal Customer,49,Business travel,Business,1096,3,3,3,3,2,5,5,4,4,5,4,3,4,3,8,45.0,satisfied +50559,63923,Male,Loyal Customer,55,Personal Travel,Eco,1192,1,2,1,4,3,1,3,3,3,1,2,4,4,3,0,3.0,neutral or dissatisfied +50560,115706,Male,disloyal Customer,21,Business travel,Eco,480,3,3,3,4,3,3,3,3,2,4,4,4,3,3,28,19.0,neutral or dissatisfied +50561,60537,Male,Loyal Customer,46,Personal Travel,Eco,641,4,4,4,3,2,4,1,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +50562,1455,Male,disloyal Customer,24,Business travel,Business,772,5,0,4,1,2,4,2,2,4,2,4,4,4,2,0,0.0,satisfied +50563,111640,Male,Loyal Customer,71,Business travel,Business,1558,1,2,2,2,3,4,4,1,1,1,1,3,1,1,10,0.0,neutral or dissatisfied +50564,29876,Female,Loyal Customer,35,Business travel,Eco,261,1,4,4,4,1,1,1,1,3,4,4,4,4,1,5,15.0,neutral or dissatisfied +50565,87680,Female,Loyal Customer,41,Business travel,Business,2292,2,2,2,2,3,1,1,2,2,2,2,3,2,1,0,4.0,neutral or dissatisfied +50566,35374,Female,Loyal Customer,53,Business travel,Eco,944,1,4,4,4,2,3,4,1,1,1,1,4,1,4,38,30.0,neutral or dissatisfied +50567,88695,Male,Loyal Customer,64,Personal Travel,Eco,404,1,4,1,2,3,1,3,3,5,3,4,3,4,3,98,90.0,neutral or dissatisfied +50568,57498,Female,Loyal Customer,50,Business travel,Business,1075,1,1,1,1,4,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +50569,81514,Female,Loyal Customer,39,Business travel,Business,1124,1,1,1,1,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +50570,50600,Male,Loyal Customer,44,Personal Travel,Eco,86,2,4,2,3,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +50571,98545,Male,Loyal Customer,42,Business travel,Eco Plus,402,3,3,3,3,3,3,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +50572,18264,Female,Loyal Customer,34,Personal Travel,Eco,179,3,4,3,3,1,3,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +50573,61442,Male,Loyal Customer,39,Business travel,Business,2288,4,4,3,4,3,5,5,3,3,3,3,4,3,4,0,1.0,satisfied +50574,98613,Female,Loyal Customer,55,Business travel,Business,2084,1,1,1,1,3,4,4,4,4,4,4,3,4,3,18,5.0,satisfied +50575,32898,Male,Loyal Customer,13,Personal Travel,Eco,163,2,5,0,1,4,0,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +50576,112364,Male,Loyal Customer,52,Business travel,Business,2063,2,2,2,2,3,5,5,4,4,4,4,5,4,5,123,130.0,satisfied +50577,45928,Female,Loyal Customer,31,Personal Travel,Eco,809,4,4,4,2,4,4,4,4,4,4,2,5,5,4,0,23.0,neutral or dissatisfied +50578,13813,Female,Loyal Customer,26,Personal Travel,Eco Plus,617,1,5,1,2,2,1,2,2,5,2,5,4,4,2,12,20.0,neutral or dissatisfied +50579,67974,Male,Loyal Customer,29,Business travel,Business,1464,3,3,3,3,2,2,2,2,3,3,5,4,4,2,0,0.0,satisfied +50580,20234,Male,Loyal Customer,30,Business travel,Eco,224,1,5,5,5,1,1,1,1,4,1,3,4,4,1,9,16.0,neutral or dissatisfied +50581,58907,Female,Loyal Customer,25,Business travel,Eco,488,4,3,3,3,4,4,5,4,4,2,5,5,3,4,0,5.0,satisfied +50582,51090,Female,Loyal Customer,10,Personal Travel,Eco,308,1,4,5,1,5,5,5,5,4,2,5,3,5,5,0,8.0,neutral or dissatisfied +50583,99062,Male,disloyal Customer,37,Business travel,Business,237,3,3,3,3,4,3,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +50584,43746,Male,Loyal Customer,53,Personal Travel,Business,481,1,5,1,3,2,2,3,5,5,1,5,3,5,5,113,,neutral or dissatisfied +50585,79605,Female,Loyal Customer,46,Business travel,Eco,712,3,3,3,3,5,4,3,3,3,3,3,2,3,3,0,9.0,neutral or dissatisfied +50586,99708,Male,Loyal Customer,45,Business travel,Business,667,3,3,2,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +50587,83087,Female,Loyal Customer,58,Business travel,Eco,727,2,3,3,3,5,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +50588,19587,Male,Loyal Customer,60,Personal Travel,Eco,108,4,5,4,4,5,4,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +50589,107525,Female,Loyal Customer,48,Personal Travel,Eco,838,5,4,5,3,5,4,4,1,1,5,1,3,1,4,14,2.0,satisfied +50590,46653,Male,disloyal Customer,17,Business travel,Eco,125,3,4,3,3,1,3,1,1,2,4,3,3,4,1,7,49.0,neutral or dissatisfied +50591,26526,Male,Loyal Customer,29,Business travel,Business,3667,2,2,2,2,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +50592,64900,Male,disloyal Customer,38,Business travel,Business,247,4,4,4,1,2,4,2,2,4,2,5,5,4,2,0,0.0,satisfied +50593,93507,Male,Loyal Customer,31,Personal Travel,Eco,1020,2,4,2,4,2,2,2,2,2,4,3,2,4,2,41,27.0,neutral or dissatisfied +50594,62371,Male,Loyal Customer,30,Business travel,Business,2704,1,1,1,1,5,5,5,5,5,2,3,5,5,5,51,23.0,satisfied +50595,24748,Female,Loyal Customer,53,Business travel,Business,432,2,5,2,2,3,1,1,4,4,4,4,4,4,5,0,3.0,satisfied +50596,94628,Female,Loyal Customer,44,Business travel,Business,3668,3,3,3,3,4,4,4,4,4,4,4,4,4,3,29,18.0,satisfied +50597,14000,Female,Loyal Customer,16,Personal Travel,Eco,160,2,4,2,3,3,2,3,3,3,4,4,1,4,3,0,17.0,neutral or dissatisfied +50598,86388,Female,Loyal Customer,40,Business travel,Eco,762,2,2,5,2,2,2,2,2,4,5,4,1,4,2,13,8.0,neutral or dissatisfied +50599,6514,Female,Loyal Customer,59,Business travel,Business,599,2,2,2,2,4,5,5,5,5,5,5,5,5,3,15,23.0,satisfied +50600,82077,Male,Loyal Customer,33,Business travel,Business,1740,3,3,3,3,5,5,5,5,3,2,4,5,4,5,6,0.0,satisfied +50601,54937,Female,Loyal Customer,39,Business travel,Business,1379,2,2,1,2,5,4,5,5,5,5,5,5,5,5,29,0.0,satisfied +50602,38165,Female,Loyal Customer,33,Personal Travel,Eco,1249,3,1,3,3,5,3,5,5,2,4,1,3,2,5,15,15.0,neutral or dissatisfied +50603,70327,Male,Loyal Customer,59,Business travel,Business,3163,2,2,2,2,3,4,3,2,2,2,2,4,2,4,2,0.0,neutral or dissatisfied +50604,112416,Male,disloyal Customer,22,Business travel,Eco,909,4,4,4,3,2,4,2,2,1,5,3,2,3,2,52,45.0,neutral or dissatisfied +50605,86198,Female,disloyal Customer,33,Business travel,Eco,356,2,4,2,3,4,2,4,4,2,5,3,2,4,4,40,35.0,neutral or dissatisfied +50606,47735,Female,Loyal Customer,30,Personal Travel,Business,329,2,5,2,2,1,2,1,1,3,1,1,3,3,1,0,0.0,neutral or dissatisfied +50607,84008,Male,Loyal Customer,11,Personal Travel,Eco,321,2,3,5,4,2,5,2,2,3,2,4,3,3,2,33,13.0,neutral or dissatisfied +50608,116000,Female,Loyal Customer,26,Personal Travel,Eco,446,3,1,3,2,3,3,3,3,4,2,2,2,3,3,17,1.0,neutral or dissatisfied +50609,65895,Female,disloyal Customer,20,Business travel,Eco,569,3,4,3,4,5,3,5,5,5,5,4,3,5,5,31,30.0,neutral or dissatisfied +50610,54632,Female,Loyal Customer,30,Business travel,Business,1924,4,4,4,4,3,4,3,3,5,5,1,5,5,3,0,0.0,satisfied +50611,126481,Female,Loyal Customer,34,Business travel,Business,1849,4,5,5,5,2,4,4,4,4,4,4,2,4,2,0,8.0,neutral or dissatisfied +50612,38330,Female,Loyal Customer,15,Business travel,Business,1696,2,1,2,2,3,4,3,3,3,4,4,3,4,3,0,0.0,satisfied +50613,60713,Male,Loyal Customer,54,Business travel,Business,1605,2,2,2,2,4,5,5,5,5,5,5,5,5,4,89,76.0,satisfied +50614,63165,Male,Loyal Customer,24,Business travel,Business,337,1,1,1,1,4,5,4,4,3,3,4,5,5,4,0,8.0,satisfied +50615,17010,Female,Loyal Customer,9,Personal Travel,Business,781,1,5,1,3,3,1,3,3,3,3,4,4,5,3,78,82.0,neutral or dissatisfied +50616,15961,Male,Loyal Customer,7,Personal Travel,Eco,528,2,2,2,3,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +50617,20710,Male,Loyal Customer,52,Personal Travel,Business,707,2,4,1,3,3,5,4,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +50618,79794,Male,Loyal Customer,60,Business travel,Business,950,2,2,1,2,5,5,5,5,5,5,5,5,5,5,0,17.0,satisfied +50619,126230,Male,Loyal Customer,41,Business travel,Business,1872,4,4,4,4,1,5,2,4,4,4,4,3,4,1,30,17.0,satisfied +50620,56178,Female,Loyal Customer,28,Personal Travel,Eco,1400,1,4,1,2,1,1,5,1,3,3,3,3,4,1,0,0.0,neutral or dissatisfied +50621,9805,Male,Loyal Customer,57,Business travel,Business,3150,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +50622,13635,Male,Loyal Customer,35,Business travel,Eco Plus,1014,2,3,3,3,2,2,2,2,4,4,3,2,3,2,4,16.0,neutral or dissatisfied +50623,116783,Male,Loyal Customer,55,Personal Travel,Eco Plus,325,4,4,4,4,4,2,2,5,3,3,5,2,1,2,168,160.0,neutral or dissatisfied +50624,14722,Female,Loyal Customer,39,Personal Travel,Eco,419,2,3,2,3,2,2,2,2,5,4,4,4,1,2,0,0.0,neutral or dissatisfied +50625,1858,Female,disloyal Customer,18,Business travel,Business,931,0,0,0,2,1,0,3,1,4,2,5,3,4,1,0,9.0,satisfied +50626,51469,Male,Loyal Customer,68,Business travel,Eco Plus,190,3,3,3,3,3,3,3,3,2,3,4,3,3,3,0,10.0,neutral or dissatisfied +50627,75242,Male,Loyal Customer,54,Personal Travel,Eco,1744,4,1,4,4,2,4,2,2,1,2,4,1,4,2,20,7.0,neutral or dissatisfied +50628,83440,Female,disloyal Customer,30,Business travel,Eco Plus,632,1,1,1,3,3,1,3,3,4,3,3,1,3,3,1,0.0,neutral or dissatisfied +50629,57068,Female,Loyal Customer,34,Business travel,Business,2065,2,3,3,3,1,2,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +50630,83635,Male,Loyal Customer,57,Business travel,Business,577,4,4,5,4,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +50631,59423,Female,Loyal Customer,39,Business travel,Business,2486,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +50632,37932,Male,Loyal Customer,50,Personal Travel,Eco,1068,3,5,3,3,3,3,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +50633,54797,Male,disloyal Customer,37,Business travel,Eco,775,2,1,1,1,4,1,4,4,2,3,3,2,2,4,0,4.0,neutral or dissatisfied +50634,13887,Male,Loyal Customer,51,Personal Travel,Eco,667,1,3,2,3,5,2,5,5,4,5,4,4,4,5,0,1.0,neutral or dissatisfied +50635,14926,Male,Loyal Customer,63,Personal Travel,Eco Plus,240,0,5,0,3,1,0,1,1,3,1,2,1,2,1,0,0.0,satisfied +50636,29247,Female,disloyal Customer,26,Business travel,Eco,569,3,0,3,2,5,3,5,5,1,4,4,2,1,5,0,0.0,neutral or dissatisfied +50637,115611,Male,Loyal Customer,43,Business travel,Eco,447,4,1,1,1,4,4,4,3,2,4,3,4,4,4,263,283.0,neutral or dissatisfied +50638,1214,Male,Loyal Customer,54,Personal Travel,Eco,140,4,3,4,1,4,4,4,4,3,3,3,1,2,4,0,0.0,satisfied +50639,39754,Male,Loyal Customer,48,Business travel,Business,521,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +50640,29973,Female,Loyal Customer,39,Business travel,Business,3987,1,5,5,5,3,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +50641,54757,Female,Loyal Customer,24,Business travel,Eco Plus,965,5,3,3,3,5,5,5,5,3,1,1,1,1,5,19,5.0,satisfied +50642,52608,Female,Loyal Customer,59,Business travel,Eco,160,2,1,1,1,1,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +50643,97777,Female,Loyal Customer,62,Business travel,Eco,471,3,4,4,4,1,3,2,3,3,3,3,4,3,4,26,34.0,neutral or dissatisfied +50644,110143,Female,Loyal Customer,42,Business travel,Business,2250,5,5,5,5,5,4,4,4,4,4,4,5,4,4,39,35.0,satisfied +50645,44050,Male,Loyal Customer,42,Personal Travel,Eco,287,3,5,3,3,3,3,3,3,2,2,4,2,1,3,0,0.0,neutral or dissatisfied +50646,65981,Male,Loyal Customer,67,Personal Travel,Eco,1372,3,4,3,1,5,3,5,5,4,4,5,4,4,5,9,0.0,neutral or dissatisfied +50647,32290,Female,Loyal Customer,40,Business travel,Business,2735,4,4,4,4,2,4,2,5,5,5,5,3,5,3,0,0.0,satisfied +50648,2578,Male,Loyal Customer,52,Business travel,Eco,227,2,3,3,3,2,2,2,2,3,2,2,3,1,2,0,0.0,neutral or dissatisfied +50649,12707,Male,Loyal Customer,31,Business travel,Business,1888,4,4,4,4,4,4,4,4,5,1,3,4,4,4,37,26.0,satisfied +50650,32904,Male,Loyal Customer,61,Personal Travel,Eco,163,2,5,2,3,2,2,4,2,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +50651,93874,Female,Loyal Customer,37,Business travel,Business,1994,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +50652,116134,Male,Loyal Customer,41,Personal Travel,Eco,308,4,4,4,3,5,4,5,5,3,5,4,5,5,5,2,0.0,neutral or dissatisfied +50653,100088,Male,Loyal Customer,61,Business travel,Eco Plus,220,4,5,5,5,3,4,3,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +50654,51034,Female,Loyal Customer,19,Personal Travel,Eco,363,1,1,1,4,1,1,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +50655,112597,Female,disloyal Customer,45,Business travel,Eco,602,2,1,1,2,3,1,1,3,1,5,3,2,3,3,34,25.0,neutral or dissatisfied +50656,64087,Female,Loyal Customer,18,Personal Travel,Eco,919,2,4,2,4,2,2,2,2,5,5,1,5,5,2,35,50.0,neutral or dissatisfied +50657,10628,Male,Loyal Customer,40,Business travel,Business,1891,5,4,5,5,2,4,5,5,5,5,5,3,5,3,37,30.0,satisfied +50658,45941,Female,Loyal Customer,68,Personal Travel,Eco,913,1,5,1,3,5,1,5,1,1,1,1,3,1,2,13,0.0,neutral or dissatisfied +50659,11504,Male,Loyal Customer,68,Personal Travel,Eco Plus,309,3,5,2,4,3,2,5,3,4,1,3,1,5,3,88,90.0,neutral or dissatisfied +50660,20204,Male,Loyal Customer,42,Business travel,Business,179,0,4,0,3,3,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +50661,25911,Female,Loyal Customer,49,Business travel,Business,3484,1,1,1,1,2,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +50662,67440,Male,Loyal Customer,36,Business travel,Eco,241,2,3,3,3,2,2,2,2,5,3,5,2,4,2,0,3.0,satisfied +50663,42705,Male,Loyal Customer,55,Personal Travel,Eco,627,4,5,4,2,3,4,3,3,5,3,5,4,4,3,0,19.0,neutral or dissatisfied +50664,106816,Female,Loyal Customer,32,Business travel,Business,1488,5,5,5,5,4,4,4,4,5,3,4,3,5,4,35,39.0,satisfied +50665,77210,Female,Loyal Customer,61,Personal Travel,Eco,2994,3,4,3,1,3,2,2,5,4,3,5,2,4,2,0,0.0,neutral or dissatisfied +50666,30738,Female,Loyal Customer,9,Personal Travel,Business,589,2,2,2,4,3,2,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +50667,70380,Male,Loyal Customer,49,Business travel,Business,1562,3,5,5,5,5,4,3,3,3,3,3,2,3,1,0,5.0,neutral or dissatisfied +50668,71572,Female,disloyal Customer,36,Business travel,Business,1182,3,3,3,4,2,3,1,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +50669,126290,Male,Loyal Customer,69,Personal Travel,Eco,328,4,2,4,4,4,4,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +50670,113302,Female,Loyal Customer,52,Business travel,Business,2882,1,1,1,1,4,4,4,4,4,4,4,5,4,4,39,31.0,satisfied +50671,93368,Male,Loyal Customer,27,Personal Travel,Eco,1024,3,5,3,3,4,3,4,4,5,3,5,4,4,4,21,14.0,neutral or dissatisfied +50672,108252,Male,Loyal Customer,44,Business travel,Business,2474,2,2,2,2,3,4,4,4,4,4,4,5,4,4,16,8.0,satisfied +50673,128561,Male,Loyal Customer,55,Personal Travel,Eco Plus,325,3,4,3,3,4,3,4,4,4,4,4,4,3,4,0,0.0,neutral or dissatisfied +50674,27682,Female,Loyal Customer,36,Business travel,Eco,1107,3,2,4,2,3,3,3,3,1,5,1,3,2,3,1,0.0,satisfied +50675,42543,Female,Loyal Customer,42,Business travel,Eco,1091,2,4,5,4,2,1,1,4,5,2,2,1,3,1,134,124.0,neutral or dissatisfied +50676,96904,Male,Loyal Customer,27,Personal Travel,Eco,928,4,5,4,1,5,4,5,5,5,3,4,4,5,5,0,0.0,satisfied +50677,128494,Male,Loyal Customer,60,Personal Travel,Eco,304,2,4,2,1,4,2,4,4,5,2,4,3,5,4,90,87.0,neutral or dissatisfied +50678,36880,Female,Loyal Customer,25,Business travel,Eco,1182,4,5,5,5,4,4,5,4,3,2,5,5,2,4,18,11.0,satisfied +50679,30559,Male,Loyal Customer,38,Personal Travel,Business,628,1,4,1,4,3,4,5,1,1,1,1,4,1,5,0,1.0,neutral or dissatisfied +50680,91000,Male,Loyal Customer,15,Personal Travel,Eco,581,1,4,1,2,4,1,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +50681,123148,Male,Loyal Customer,36,Business travel,Business,2651,1,5,5,5,5,3,3,1,1,1,1,4,1,1,0,11.0,neutral or dissatisfied +50682,486,Male,Loyal Customer,48,Business travel,Business,354,1,1,1,1,3,4,5,4,4,4,4,3,4,5,15,23.0,satisfied +50683,55110,Female,Loyal Customer,35,Personal Travel,Eco,1608,3,5,3,5,3,3,3,3,5,5,5,3,5,3,71,40.0,neutral or dissatisfied +50684,95292,Male,Loyal Customer,39,Personal Travel,Eco,239,2,4,2,3,4,2,5,4,1,2,4,3,5,4,5,13.0,neutral or dissatisfied +50685,16999,Female,Loyal Customer,25,Personal Travel,Eco Plus,843,3,4,3,5,4,3,4,4,3,4,4,4,5,4,0,22.0,neutral or dissatisfied +50686,63563,Female,Loyal Customer,39,Business travel,Business,1737,3,3,3,3,5,3,4,4,4,4,4,5,4,3,20,4.0,satisfied +50687,57155,Male,disloyal Customer,26,Business travel,Business,946,5,5,5,3,4,5,1,4,4,2,3,5,5,4,0,0.0,satisfied +50688,95390,Female,Loyal Customer,30,Personal Travel,Eco,441,3,4,5,5,2,5,2,2,4,5,4,2,4,2,0,0.0,neutral or dissatisfied +50689,27851,Female,Loyal Customer,36,Personal Travel,Eco,1448,4,4,4,5,1,4,4,1,1,3,3,4,2,1,0,0.0,neutral or dissatisfied +50690,77266,Female,Loyal Customer,58,Business travel,Business,1590,3,3,3,3,3,4,4,5,5,5,5,5,5,3,15,4.0,satisfied +50691,28384,Female,Loyal Customer,57,Personal Travel,Eco,763,1,4,1,3,5,1,2,5,5,1,5,4,5,2,0,0.0,neutral or dissatisfied +50692,45187,Male,Loyal Customer,20,Business travel,Eco,1437,5,3,3,3,5,5,4,5,4,2,2,2,4,5,118,102.0,satisfied +50693,117156,Female,Loyal Customer,69,Personal Travel,Eco,338,1,5,1,4,2,1,1,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +50694,104355,Female,disloyal Customer,30,Business travel,Eco Plus,409,2,2,2,5,5,2,5,5,5,5,2,5,3,5,0,0.0,neutral or dissatisfied +50695,103690,Male,Loyal Customer,44,Business travel,Business,1796,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +50696,105295,Female,Loyal Customer,53,Business travel,Business,738,1,1,5,1,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +50697,113556,Male,Loyal Customer,41,Business travel,Eco,407,3,4,4,4,3,4,3,3,4,1,3,3,4,3,23,17.0,neutral or dissatisfied +50698,88230,Female,Loyal Customer,52,Business travel,Business,1965,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +50699,33723,Female,Loyal Customer,45,Personal Travel,Eco,759,1,4,1,1,2,5,5,1,1,1,1,3,1,5,0,14.0,neutral or dissatisfied +50700,6875,Male,Loyal Customer,53,Business travel,Business,622,1,1,1,1,4,4,4,5,4,4,4,4,5,4,159,149.0,satisfied +50701,39698,Male,Loyal Customer,38,Personal Travel,Business,298,1,4,1,3,4,5,5,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +50702,84308,Male,Loyal Customer,35,Personal Travel,Eco,235,4,5,4,5,2,4,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +50703,25222,Male,Loyal Customer,57,Business travel,Eco,919,5,1,1,1,5,5,5,5,4,3,4,1,4,5,0,0.0,satisfied +50704,70937,Male,Loyal Customer,51,Business travel,Eco,612,2,2,2,2,1,2,1,1,2,2,4,3,4,1,0,0.0,neutral or dissatisfied +50705,47055,Female,disloyal Customer,38,Business travel,Eco,639,2,4,3,3,5,3,5,5,4,5,3,1,3,5,28,31.0,neutral or dissatisfied +50706,94456,Female,disloyal Customer,26,Business travel,Business,562,2,4,2,3,2,2,2,2,4,5,4,3,4,2,4,0.0,neutral or dissatisfied +50707,39878,Male,Loyal Customer,68,Personal Travel,Eco,272,4,4,4,3,1,4,3,1,2,2,4,2,3,1,0,2.0,satisfied +50708,84933,Male,Loyal Customer,56,Personal Travel,Eco,547,1,0,1,4,4,1,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +50709,104152,Female,Loyal Customer,42,Business travel,Business,2909,3,3,3,3,4,4,5,5,5,5,5,4,5,4,1,0.0,satisfied +50710,64989,Female,disloyal Customer,24,Business travel,Eco,282,2,0,2,4,3,2,3,3,4,4,2,4,2,3,27,24.0,neutral or dissatisfied +50711,22412,Female,disloyal Customer,26,Business travel,Eco,143,3,3,3,4,5,3,5,5,1,3,3,1,4,5,0,0.0,neutral or dissatisfied +50712,38385,Male,Loyal Customer,14,Personal Travel,Eco Plus,1133,3,3,3,3,3,3,3,3,2,5,2,3,4,3,0,11.0,neutral or dissatisfied +50713,98035,Male,Loyal Customer,11,Personal Travel,Eco Plus,1014,2,1,2,3,2,2,2,2,2,2,4,1,4,2,38,49.0,neutral or dissatisfied +50714,25376,Female,disloyal Customer,33,Business travel,Eco,591,3,3,2,3,3,2,3,3,1,3,3,3,3,3,3,23.0,neutral or dissatisfied +50715,101392,Female,Loyal Customer,39,Business travel,Business,3922,4,5,4,4,3,5,4,4,4,4,4,4,4,3,4,0.0,satisfied +50716,97361,Male,Loyal Customer,16,Personal Travel,Eco,1020,5,0,5,3,5,5,5,5,1,4,3,4,2,5,7,13.0,satisfied +50717,110777,Male,disloyal Customer,30,Business travel,Business,990,3,3,3,5,1,3,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +50718,55180,Male,Loyal Customer,56,Business travel,Business,1608,3,3,3,3,5,3,4,5,5,5,5,3,5,5,0,1.0,satisfied +50719,104940,Female,disloyal Customer,45,Business travel,Business,1180,2,2,2,3,5,2,5,5,5,4,4,5,5,5,7,0.0,neutral or dissatisfied +50720,38302,Female,disloyal Customer,28,Business travel,Eco,1027,2,3,3,4,2,1,1,2,1,5,5,1,5,1,125,146.0,neutral or dissatisfied +50721,62686,Male,Loyal Customer,26,Business travel,Business,2399,2,2,2,2,4,4,4,4,3,4,4,4,5,4,55,80.0,satisfied +50722,14587,Female,Loyal Customer,40,Business travel,Eco,1021,4,5,5,5,4,4,4,4,2,5,2,1,1,4,0,0.0,satisfied +50723,106004,Female,Loyal Customer,27,Business travel,Eco,1999,3,5,4,5,3,3,3,3,3,3,2,2,2,3,55,70.0,neutral or dissatisfied +50724,120549,Male,disloyal Customer,29,Business travel,Business,2176,4,4,4,3,5,4,5,5,3,4,5,4,5,5,36,29.0,satisfied +50725,53375,Female,Loyal Customer,68,Business travel,Eco,1052,5,2,2,2,3,1,3,5,5,5,5,1,5,5,0,0.0,satisfied +50726,106327,Male,Loyal Customer,35,Business travel,Eco,825,4,1,3,1,4,3,4,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +50727,120755,Female,Loyal Customer,50,Business travel,Business,2131,1,1,5,1,5,4,5,2,2,2,2,5,2,3,0,6.0,satisfied +50728,38116,Female,Loyal Customer,48,Business travel,Business,1237,3,3,3,3,3,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +50729,118226,Female,Loyal Customer,57,Personal Travel,Business,1587,2,4,2,5,5,5,5,4,4,2,4,3,4,5,0,13.0,neutral or dissatisfied +50730,94765,Female,Loyal Customer,52,Business travel,Business,233,1,1,3,1,5,4,4,5,5,4,5,4,5,3,0,0.0,satisfied +50731,101574,Female,Loyal Customer,43,Business travel,Business,2498,3,3,3,3,5,4,5,4,4,4,4,5,4,3,47,29.0,satisfied +50732,2752,Male,Loyal Customer,73,Business travel,Business,3178,4,1,1,1,4,4,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +50733,57602,Male,Loyal Customer,52,Business travel,Business,3512,2,2,2,2,3,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +50734,20141,Male,Loyal Customer,60,Business travel,Business,438,2,1,1,1,4,2,2,2,2,2,2,2,2,2,37,48.0,neutral or dissatisfied +50735,9084,Female,Loyal Customer,15,Personal Travel,Eco,173,2,5,0,4,4,0,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +50736,71755,Female,Loyal Customer,51,Business travel,Business,1744,1,1,1,1,2,3,5,4,4,4,4,3,4,5,25,15.0,satisfied +50737,98799,Male,disloyal Customer,54,Business travel,Business,1111,3,3,3,5,4,3,4,4,5,2,5,3,5,4,31,22.0,neutral or dissatisfied +50738,100653,Female,Loyal Customer,31,Personal Travel,Business,628,2,4,2,1,4,2,5,4,5,2,5,3,5,4,0,6.0,neutral or dissatisfied +50739,110441,Male,Loyal Customer,12,Personal Travel,Eco,925,0,5,0,3,5,0,5,5,3,3,5,3,5,5,13,6.0,satisfied +50740,95599,Male,Loyal Customer,47,Business travel,Business,822,3,3,5,3,5,5,5,2,2,2,2,5,2,3,14,0.0,satisfied +50741,65361,Male,Loyal Customer,39,Business travel,Eco,631,2,5,3,5,2,2,2,2,3,1,3,1,2,2,0,0.0,neutral or dissatisfied +50742,94978,Female,Loyal Customer,39,Business travel,Business,3694,1,5,5,5,3,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +50743,102287,Female,Loyal Customer,63,Business travel,Eco,488,3,4,4,4,3,2,2,4,4,3,4,1,4,4,30,17.0,neutral or dissatisfied +50744,27325,Male,Loyal Customer,58,Business travel,Eco,605,5,4,4,4,5,5,5,5,1,1,1,3,3,5,0,0.0,satisfied +50745,25416,Male,Loyal Customer,65,Personal Travel,Eco,990,3,1,4,4,3,4,3,3,1,2,4,1,3,3,6,0.0,neutral or dissatisfied +50746,59800,Female,Loyal Customer,26,Business travel,Business,1065,4,4,4,4,3,3,3,3,4,5,4,4,5,3,4,0.0,satisfied +50747,58835,Female,disloyal Customer,22,Business travel,Eco,864,4,4,4,4,4,4,4,4,3,5,3,1,4,4,0,0.0,neutral or dissatisfied +50748,77399,Male,Loyal Customer,63,Personal Travel,Eco,588,2,5,2,1,1,2,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +50749,112997,Female,disloyal Customer,41,Business travel,Eco,732,2,2,2,3,2,2,2,2,2,3,4,3,4,2,30,40.0,neutral or dissatisfied +50750,30927,Female,Loyal Customer,33,Business travel,Eco Plus,896,4,4,4,4,4,3,4,4,1,3,1,4,2,4,16,25.0,neutral or dissatisfied +50751,67524,Male,disloyal Customer,29,Business travel,Business,1235,2,2,2,4,4,2,4,4,1,5,3,2,3,4,0,3.0,neutral or dissatisfied +50752,10968,Female,Loyal Customer,57,Business travel,Eco,163,3,1,1,1,5,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +50753,33,Female,disloyal Customer,33,Business travel,Business,173,2,2,2,5,2,2,2,2,3,3,5,5,5,2,22,28.0,neutral or dissatisfied +50754,54728,Male,Loyal Customer,58,Personal Travel,Eco,965,1,4,1,3,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +50755,109701,Female,disloyal Customer,27,Business travel,Business,587,0,0,0,1,3,0,3,3,4,2,5,3,4,3,0,0.0,satisfied +50756,120742,Male,Loyal Customer,43,Business travel,Business,1850,4,4,4,4,3,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +50757,16616,Male,Loyal Customer,60,Personal Travel,Eco,1008,2,5,2,4,2,5,5,4,2,1,2,5,4,5,274,262.0,neutral or dissatisfied +50758,45407,Female,Loyal Customer,43,Business travel,Business,458,3,1,1,1,1,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +50759,123605,Female,Loyal Customer,28,Personal Travel,Eco,1773,1,5,0,5,3,0,3,3,4,5,5,4,2,3,0,0.0,neutral or dissatisfied +50760,64085,Female,Loyal Customer,67,Personal Travel,Eco,919,2,3,2,3,5,4,3,3,3,2,4,1,3,2,4,5.0,neutral or dissatisfied +50761,64720,Female,Loyal Customer,52,Business travel,Business,2046,5,5,5,5,3,4,5,5,5,5,5,5,5,3,4,0.0,satisfied +50762,39808,Female,Loyal Customer,55,Business travel,Business,3631,2,2,2,2,1,2,1,5,5,5,5,5,5,5,0,0.0,satisfied +50763,71044,Male,Loyal Customer,54,Business travel,Eco,802,3,1,3,3,3,3,3,3,1,4,4,1,4,3,28,28.0,neutral or dissatisfied +50764,23023,Female,disloyal Customer,38,Business travel,Eco,927,2,2,2,1,3,2,3,3,4,1,5,3,2,3,0,0.0,neutral or dissatisfied +50765,41536,Male,Loyal Customer,27,Business travel,Eco,1504,2,4,4,4,2,2,2,2,4,2,3,2,3,2,0,8.0,neutral or dissatisfied +50766,103062,Female,disloyal Customer,30,Business travel,Eco,687,3,3,3,3,3,3,2,3,1,4,1,4,5,3,0,0.0,neutral or dissatisfied +50767,95639,Female,Loyal Customer,47,Business travel,Business,484,4,4,4,4,4,4,5,5,5,5,5,5,5,5,6,1.0,satisfied +50768,75664,Female,Loyal Customer,58,Business travel,Business,1825,4,4,4,4,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +50769,46152,Female,disloyal Customer,36,Business travel,Eco,227,2,3,2,1,2,2,2,2,2,5,4,4,1,2,9,0.0,neutral or dissatisfied +50770,71792,Female,Loyal Customer,40,Business travel,Business,1744,4,4,4,4,4,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +50771,49605,Male,disloyal Customer,36,Business travel,Eco,250,3,5,3,4,3,3,3,3,5,3,2,4,5,3,0,0.0,neutral or dissatisfied +50772,52366,Male,Loyal Customer,50,Personal Travel,Eco,370,1,3,1,4,2,1,5,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +50773,17792,Female,Loyal Customer,45,Business travel,Eco,1075,4,1,5,1,4,4,3,4,4,4,4,4,4,3,66,63.0,neutral or dissatisfied +50774,23705,Male,Loyal Customer,27,Personal Travel,Eco,196,4,5,0,4,5,0,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +50775,89638,Male,Loyal Customer,29,Business travel,Business,944,2,5,5,5,2,2,2,2,4,3,3,2,4,2,729,717.0,neutral or dissatisfied +50776,113195,Male,Loyal Customer,56,Business travel,Business,236,0,1,1,4,3,5,4,2,2,2,2,3,2,4,9,2.0,satisfied +50777,93702,Male,Loyal Customer,43,Business travel,Business,1797,1,1,1,1,2,5,5,4,4,4,4,4,4,5,28,29.0,satisfied +50778,44132,Male,Loyal Customer,38,Business travel,Business,1620,5,5,5,5,1,3,2,4,4,4,3,5,4,5,0,0.0,satisfied +50779,33705,Male,Loyal Customer,57,Business travel,Business,3220,2,5,5,5,5,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +50780,78079,Female,Loyal Customer,49,Business travel,Eco Plus,227,4,5,5,5,3,3,3,4,4,4,4,3,4,3,22,10.0,neutral or dissatisfied +50781,25809,Male,Loyal Customer,28,Business travel,Business,1747,4,4,4,4,4,4,4,4,3,4,3,3,4,4,4,0.0,satisfied +50782,83125,Male,Loyal Customer,56,Personal Travel,Eco,957,1,5,1,3,3,1,3,3,5,2,4,3,5,3,4,0.0,neutral or dissatisfied +50783,21960,Male,Loyal Customer,29,Business travel,Business,3610,3,2,2,2,3,2,3,3,1,3,2,4,2,3,1,6.0,neutral or dissatisfied +50784,42916,Female,Loyal Customer,8,Personal Travel,Eco,200,5,4,5,1,1,5,1,1,4,5,2,5,1,1,0,0.0,satisfied +50785,100652,Male,Loyal Customer,68,Business travel,Business,1565,5,5,5,5,5,5,4,3,3,4,3,5,3,4,5,0.0,satisfied +50786,74908,Male,Loyal Customer,42,Business travel,Business,2475,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +50787,48728,Female,Loyal Customer,41,Business travel,Business,3422,5,2,5,5,4,4,4,3,3,4,4,4,3,5,0,0.0,satisfied +50788,96803,Female,Loyal Customer,47,Business travel,Business,571,1,2,4,2,4,3,3,1,1,1,1,4,1,1,19,13.0,neutral or dissatisfied +50789,40976,Female,Loyal Customer,43,Personal Travel,Eco,601,2,4,2,3,3,2,5,1,1,2,1,2,1,1,15,0.0,neutral or dissatisfied +50790,51344,Male,Loyal Customer,34,Business travel,Eco Plus,363,2,1,1,1,2,2,2,2,1,2,3,3,3,2,42,47.0,neutral or dissatisfied +50791,7195,Male,Loyal Customer,62,Business travel,Eco,139,2,1,1,1,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +50792,6531,Female,Loyal Customer,12,Personal Travel,Eco,599,4,3,3,4,5,3,1,5,4,1,4,2,3,5,0,0.0,satisfied +50793,86179,Male,Loyal Customer,30,Business travel,Business,306,2,4,2,4,2,2,2,2,2,2,3,4,3,2,28,28.0,neutral or dissatisfied +50794,6900,Male,Loyal Customer,43,Business travel,Business,3676,1,1,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +50795,23717,Male,Loyal Customer,18,Personal Travel,Eco,73,3,1,3,3,4,3,4,4,4,2,3,4,3,4,0,0.0,neutral or dissatisfied +50796,32038,Male,disloyal Customer,33,Business travel,Eco,102,3,4,2,5,1,2,1,1,1,4,5,4,5,1,0,1.0,neutral or dissatisfied +50797,102676,Male,Loyal Customer,31,Business travel,Business,2950,3,3,3,3,3,4,3,3,4,2,4,5,5,3,3,0.0,satisfied +50798,123852,Male,Loyal Customer,41,Business travel,Business,3758,3,3,4,3,5,5,4,4,4,4,4,4,4,3,14,3.0,satisfied +50799,89352,Male,disloyal Customer,85,Business travel,Business,1187,3,3,3,4,3,5,5,3,4,3,3,5,1,5,0,7.0,neutral or dissatisfied +50800,17138,Male,Loyal Customer,46,Business travel,Business,455,2,2,2,2,1,4,5,5,5,5,5,3,5,2,0,0.0,satisfied +50801,59490,Male,Loyal Customer,46,Personal Travel,Eco,901,2,5,2,2,1,2,1,1,2,3,1,2,5,1,25,13.0,neutral or dissatisfied +50802,52475,Female,Loyal Customer,12,Personal Travel,Eco Plus,651,2,4,2,1,4,2,4,4,3,3,3,5,4,4,113,94.0,neutral or dissatisfied +50803,53945,Male,Loyal Customer,32,Business travel,Business,2095,1,1,1,1,5,5,5,5,3,3,4,4,5,5,1,0.0,satisfied +50804,44633,Male,Loyal Customer,25,Business travel,Business,173,0,5,0,4,1,1,1,1,5,1,5,5,3,1,37,30.0,satisfied +50805,53390,Male,Loyal Customer,27,Personal Travel,Eco,1452,1,5,1,1,3,1,3,3,5,5,1,1,1,3,3,0.0,neutral or dissatisfied +50806,122095,Female,Loyal Customer,29,Personal Travel,Eco,130,2,4,2,2,2,2,2,2,4,3,4,4,4,2,22,19.0,neutral or dissatisfied +50807,55600,Female,Loyal Customer,36,Business travel,Eco,404,2,4,4,4,2,2,2,2,4,5,4,2,4,2,0,9.0,neutral or dissatisfied +50808,94585,Female,Loyal Customer,41,Business travel,Business,1907,2,2,2,2,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +50809,82135,Female,Loyal Customer,49,Business travel,Business,2235,3,3,3,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +50810,17507,Male,Loyal Customer,36,Business travel,Business,341,1,5,5,5,3,2,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +50811,48506,Male,Loyal Customer,64,Business travel,Business,737,4,4,4,4,2,4,3,4,4,4,4,1,4,4,3,6.0,neutral or dissatisfied +50812,47975,Female,Loyal Customer,50,Personal Travel,Eco,838,2,4,2,3,5,5,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +50813,127657,Female,Loyal Customer,47,Business travel,Business,2153,2,5,5,5,2,3,4,2,2,2,2,3,2,2,0,16.0,neutral or dissatisfied +50814,10096,Female,Loyal Customer,58,Business travel,Business,961,2,2,4,2,2,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +50815,27703,Female,Loyal Customer,54,Personal Travel,Eco Plus,1107,4,1,4,4,5,3,4,4,4,4,5,1,4,1,0,0.0,satisfied +50816,30898,Female,Loyal Customer,49,Personal Travel,Business,826,3,4,3,5,5,5,4,1,1,3,1,4,1,4,24,19.0,neutral or dissatisfied +50817,50558,Male,Loyal Customer,62,Personal Travel,Eco,373,1,5,1,4,1,1,1,1,4,2,3,3,4,1,11,10.0,neutral or dissatisfied +50818,14417,Female,Loyal Customer,34,Business travel,Eco,585,3,5,5,5,3,3,3,3,4,5,4,1,4,3,21,27.0,neutral or dissatisfied +50819,10161,Female,Loyal Customer,47,Personal Travel,Eco,1195,1,4,1,3,5,5,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +50820,82607,Female,Loyal Customer,48,Business travel,Business,2505,3,2,2,2,5,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +50821,22184,Female,disloyal Customer,29,Business travel,Eco,533,2,0,2,4,1,2,1,1,4,3,4,3,4,1,3,10.0,neutral or dissatisfied +50822,35399,Male,Loyal Customer,36,Business travel,Business,3363,1,2,2,2,2,1,1,1,2,3,4,1,4,1,252,245.0,neutral or dissatisfied +50823,94046,Male,disloyal Customer,22,Business travel,Business,189,4,0,3,4,3,3,3,3,4,5,4,4,4,3,15,10.0,satisfied +50824,72737,Female,Loyal Customer,27,Personal Travel,Eco Plus,985,4,5,4,2,2,4,2,2,4,3,4,5,5,2,8,9.0,neutral or dissatisfied +50825,114810,Male,disloyal Customer,27,Business travel,Business,362,2,2,2,4,3,2,3,3,5,2,4,5,4,3,7,9.0,neutral or dissatisfied +50826,79316,Male,Loyal Customer,19,Personal Travel,Eco,2248,2,4,2,5,1,2,1,1,3,2,3,5,5,1,0,0.0,neutral or dissatisfied +50827,38834,Female,Loyal Customer,37,Business travel,Eco Plus,353,4,4,3,4,4,4,4,4,4,5,2,3,3,4,7,20.0,satisfied +50828,85911,Female,Loyal Customer,65,Business travel,Business,3165,2,1,1,1,2,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +50829,95163,Male,Loyal Customer,24,Personal Travel,Eco,248,1,4,1,4,1,1,1,1,5,3,5,3,5,1,1,10.0,neutral or dissatisfied +50830,57142,Female,Loyal Customer,28,Business travel,Business,2065,4,4,4,4,4,4,4,4,5,3,4,5,4,4,0,0.0,satisfied +50831,63686,Male,Loyal Customer,47,Business travel,Business,2422,2,2,2,2,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +50832,43537,Male,Loyal Customer,46,Business travel,Business,2496,2,2,2,2,3,4,3,2,2,2,2,3,2,2,0,21.0,neutral or dissatisfied +50833,46355,Male,Loyal Customer,17,Business travel,Business,1013,3,3,3,3,3,3,3,3,3,4,5,4,4,3,0,0.0,satisfied +50834,10233,Male,Loyal Customer,55,Business travel,Business,2252,4,5,5,5,2,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +50835,97748,Female,Loyal Customer,39,Business travel,Business,1895,3,3,3,3,3,4,5,5,5,5,5,4,5,3,9,0.0,satisfied +50836,99575,Female,Loyal Customer,29,Business travel,Business,829,1,4,4,4,1,1,1,1,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +50837,34227,Female,Loyal Customer,31,Business travel,Eco Plus,1189,5,3,2,3,5,5,5,5,2,1,1,3,1,5,0,0.0,satisfied +50838,121154,Male,disloyal Customer,21,Business travel,Eco,2370,2,2,2,3,2,5,5,1,3,1,2,5,4,5,10,21.0,neutral or dissatisfied +50839,91027,Male,Loyal Customer,50,Personal Travel,Eco,240,1,5,1,4,4,1,4,4,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +50840,107719,Male,Loyal Customer,38,Business travel,Eco,405,2,2,4,2,2,2,2,2,3,3,4,4,3,2,24,24.0,neutral or dissatisfied +50841,121447,Male,Loyal Customer,31,Business travel,Eco,290,2,3,3,3,2,2,2,2,4,4,3,4,2,2,0,0.0,neutral or dissatisfied +50842,59296,Male,Loyal Customer,65,Personal Travel,Business,2486,4,3,4,1,1,1,2,1,1,4,1,3,1,1,0,0.0,neutral or dissatisfied +50843,35131,Male,Loyal Customer,30,Business travel,Business,2127,4,5,4,4,4,4,4,4,2,2,5,1,4,4,0,0.0,satisfied +50844,104145,Female,Loyal Customer,9,Personal Travel,Eco Plus,393,3,5,2,2,3,2,3,3,5,2,5,4,5,3,7,0.0,neutral or dissatisfied +50845,79551,Female,Loyal Customer,28,Business travel,Business,762,2,2,2,2,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +50846,25975,Female,disloyal Customer,23,Business travel,Eco Plus,946,2,0,2,4,5,2,5,5,1,3,1,1,5,5,1,9.0,neutral or dissatisfied +50847,9996,Female,Loyal Customer,37,Personal Travel,Eco,357,3,4,3,1,3,4,4,3,5,4,5,4,3,4,217,206.0,neutral or dissatisfied +50848,63122,Male,Loyal Customer,54,Business travel,Business,337,0,0,0,2,2,5,4,1,1,1,1,3,1,3,24,29.0,satisfied +50849,81332,Female,Loyal Customer,44,Business travel,Business,1299,5,5,5,5,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +50850,56392,Female,Loyal Customer,42,Business travel,Business,2632,2,2,2,2,4,4,4,5,5,4,5,4,5,3,0,12.0,satisfied +50851,70330,Female,Loyal Customer,42,Business travel,Business,2999,2,2,2,2,4,4,4,3,3,3,3,5,3,5,106,81.0,satisfied +50852,109684,Male,Loyal Customer,33,Personal Travel,Eco,802,3,2,3,2,3,3,3,3,2,5,3,1,2,3,0,0.0,neutral or dissatisfied +50853,5530,Male,Loyal Customer,62,Business travel,Eco,404,3,4,4,4,3,3,3,3,1,2,3,1,3,3,92,76.0,neutral or dissatisfied +50854,5352,Male,Loyal Customer,23,Business travel,Business,2315,4,3,3,3,4,4,4,4,1,4,3,1,3,4,0,0.0,neutral or dissatisfied +50855,127545,Male,disloyal Customer,36,Business travel,Eco,609,3,0,3,2,2,3,2,2,5,2,4,3,2,2,0,3.0,neutral or dissatisfied +50856,122705,Male,Loyal Customer,59,Personal Travel,Eco Plus,361,2,1,2,4,4,2,4,4,3,5,3,2,4,4,19,20.0,neutral or dissatisfied +50857,125528,Male,disloyal Customer,21,Business travel,Eco,226,3,0,3,2,3,3,3,3,4,4,5,4,4,3,1,0.0,neutral or dissatisfied +50858,114550,Male,Loyal Customer,33,Personal Travel,Business,480,4,5,3,2,2,3,2,2,1,1,2,4,2,2,6,5.0,neutral or dissatisfied +50859,4072,Male,Loyal Customer,51,Personal Travel,Eco Plus,483,4,4,4,5,3,4,3,3,2,3,3,5,1,3,0,0.0,neutral or dissatisfied +50860,97693,Female,Loyal Customer,64,Personal Travel,Eco Plus,491,2,5,2,4,5,1,3,4,4,2,4,3,4,5,9,27.0,neutral or dissatisfied +50861,31234,Male,Loyal Customer,62,Business travel,Eco,472,5,4,4,4,5,5,5,5,1,5,3,3,1,5,0,2.0,satisfied +50862,99465,Male,disloyal Customer,23,Business travel,Business,307,4,0,4,4,3,4,3,3,5,3,4,5,4,3,0,3.0,satisfied +50863,105680,Female,Loyal Customer,45,Business travel,Business,925,4,4,4,4,2,4,4,4,4,4,4,5,4,5,9,12.0,satisfied +50864,75368,Female,Loyal Customer,57,Business travel,Business,2486,3,3,3,3,5,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +50865,46610,Female,disloyal Customer,47,Business travel,Eco,73,1,1,1,3,1,1,1,1,1,2,3,3,2,1,0,0.0,neutral or dissatisfied +50866,36512,Female,Loyal Customer,29,Business travel,Business,1237,3,3,3,3,4,4,4,4,5,1,4,3,1,4,19,8.0,satisfied +50867,39246,Female,Loyal Customer,23,Business travel,Business,1740,0,5,0,4,5,5,5,5,4,3,1,3,5,5,0,0.0,satisfied +50868,20246,Female,Loyal Customer,47,Business travel,Business,137,1,2,4,2,2,4,3,1,1,1,1,4,1,3,0,1.0,neutral or dissatisfied +50869,31735,Male,Loyal Customer,50,Business travel,Eco Plus,853,5,5,5,5,5,5,5,5,3,4,5,2,3,5,0,21.0,satisfied +50870,63390,Male,Loyal Customer,25,Personal Travel,Eco,372,2,1,2,3,3,2,3,3,3,4,3,2,2,3,0,0.0,neutral or dissatisfied +50871,92055,Female,Loyal Customer,45,Business travel,Business,1532,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +50872,78324,Male,Loyal Customer,28,Business travel,Business,1547,1,1,1,1,5,5,5,5,4,2,4,4,4,5,0,1.0,satisfied +50873,34545,Female,disloyal Customer,39,Business travel,Business,998,2,3,3,4,3,3,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +50874,66256,Male,disloyal Customer,67,Personal Travel,Eco,460,2,2,2,3,4,2,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +50875,115315,Female,Loyal Customer,56,Business travel,Business,325,3,3,3,3,3,4,4,5,5,5,5,4,5,5,28,27.0,satisfied +50876,34767,Male,Loyal Customer,35,Business travel,Eco,301,5,1,1,1,5,5,5,5,5,1,2,1,1,5,0,0.0,satisfied +50877,75852,Female,Loyal Customer,66,Personal Travel,Eco,1437,1,1,1,3,1,3,3,2,2,1,2,2,2,1,53,40.0,neutral or dissatisfied +50878,118689,Male,Loyal Customer,53,Personal Travel,Eco,647,3,3,3,3,4,3,4,4,1,5,3,4,4,4,17,0.0,neutral or dissatisfied +50879,105817,Female,Loyal Customer,15,Personal Travel,Eco,787,2,5,2,5,2,2,2,2,4,5,5,4,5,2,85,80.0,neutral or dissatisfied +50880,103641,Female,Loyal Customer,40,Business travel,Business,3517,3,4,3,3,4,5,4,3,3,4,3,4,3,4,0,2.0,satisfied +50881,40764,Male,Loyal Customer,20,Business travel,Business,501,2,2,2,2,4,4,4,4,1,1,4,4,3,4,0,0.0,satisfied +50882,4612,Female,Loyal Customer,31,Business travel,Business,719,2,3,5,5,2,2,2,2,2,4,2,4,2,2,0,0.0,neutral or dissatisfied +50883,12140,Male,disloyal Customer,25,Business travel,Eco,1075,3,3,3,1,2,3,2,2,2,1,3,5,3,2,0,0.0,neutral or dissatisfied +50884,19285,Female,Loyal Customer,30,Business travel,Business,299,5,5,3,5,5,5,5,5,4,4,1,5,4,5,0,0.0,satisfied +50885,10285,Female,disloyal Customer,24,Business travel,Eco,316,3,1,3,4,3,3,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +50886,113126,Female,disloyal Customer,33,Business travel,Business,569,4,4,4,2,1,4,1,1,4,4,5,4,4,1,9,0.0,neutral or dissatisfied +50887,56540,Male,Loyal Customer,49,Business travel,Business,1085,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +50888,124150,Male,Loyal Customer,32,Personal Travel,Business,2133,2,4,2,5,3,2,3,3,3,3,5,4,2,3,130,122.0,neutral or dissatisfied +50889,73415,Female,disloyal Customer,30,Business travel,Eco,1197,2,2,2,4,5,2,5,5,3,1,4,4,4,5,0,0.0,neutral or dissatisfied +50890,33092,Female,Loyal Customer,31,Personal Travel,Eco,163,4,4,4,2,5,4,4,5,5,3,5,5,4,5,26,32.0,neutral or dissatisfied +50891,121842,Male,Loyal Customer,40,Business travel,Business,449,3,5,5,5,1,4,3,3,3,3,3,2,3,1,0,10.0,neutral or dissatisfied +50892,95603,Male,Loyal Customer,57,Business travel,Business,670,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +50893,111920,Female,Loyal Customer,39,Business travel,Business,2574,3,3,1,3,2,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +50894,25635,Male,Loyal Customer,37,Business travel,Business,266,3,3,3,3,4,1,1,4,4,4,4,5,4,4,59,56.0,satisfied +50895,121650,Male,Loyal Customer,36,Business travel,Business,2462,3,1,3,1,4,4,3,3,3,3,3,3,3,2,0,13.0,neutral or dissatisfied +50896,12478,Male,Loyal Customer,26,Personal Travel,Eco,192,3,4,0,4,3,0,5,3,3,4,5,4,5,3,0,1.0,neutral or dissatisfied +50897,103286,Male,Loyal Customer,46,Business travel,Business,872,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +50898,70558,Male,Loyal Customer,58,Business travel,Business,3219,3,3,3,3,3,4,5,3,3,3,3,5,3,3,57,43.0,satisfied +50899,67737,Male,Loyal Customer,46,Business travel,Eco,1171,3,4,4,4,3,3,3,3,4,2,4,4,4,3,0,21.0,neutral or dissatisfied +50900,86507,Male,Loyal Customer,29,Personal Travel,Eco,762,3,5,3,3,2,3,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +50901,97240,Male,Loyal Customer,42,Business travel,Business,296,1,1,3,1,2,5,5,5,5,5,5,3,5,3,8,0.0,satisfied +50902,81934,Male,Loyal Customer,46,Business travel,Business,1589,5,5,5,5,4,5,4,5,5,5,5,5,5,4,86,105.0,satisfied +50903,85492,Female,Loyal Customer,53,Personal Travel,Eco,106,3,5,3,2,2,2,5,1,1,3,1,3,1,1,3,2.0,neutral or dissatisfied +50904,91563,Female,Loyal Customer,9,Personal Travel,Eco,680,1,1,1,4,4,1,5,4,4,4,4,2,4,4,5,0.0,neutral or dissatisfied +50905,29496,Female,Loyal Customer,60,Business travel,Eco,707,1,5,5,5,5,3,3,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +50906,49897,Female,disloyal Customer,21,Business travel,Business,337,2,3,1,3,4,1,4,4,4,2,3,3,4,4,15,31.0,neutral or dissatisfied +50907,101935,Female,Loyal Customer,23,Business travel,Business,3832,2,2,2,2,4,4,4,4,5,3,4,4,5,4,0,2.0,satisfied +50908,24033,Female,Loyal Customer,75,Business travel,Business,427,5,5,5,5,5,3,1,5,5,5,5,2,5,4,0,0.0,satisfied +50909,1108,Female,Loyal Customer,51,Personal Travel,Eco,270,3,3,3,5,1,2,2,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +50910,11734,Female,Loyal Customer,54,Business travel,Business,1815,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +50911,89637,Male,Loyal Customer,26,Business travel,Business,1076,5,5,5,5,4,4,4,4,3,3,5,5,4,4,56,34.0,satisfied +50912,42967,Female,disloyal Customer,20,Business travel,Eco,259,1,0,1,4,2,1,2,2,2,5,2,4,5,2,0,7.0,neutral or dissatisfied +50913,41057,Female,Loyal Customer,52,Business travel,Eco Plus,989,4,1,1,1,3,3,5,5,5,4,5,4,5,4,0,6.0,satisfied +50914,15683,Female,Loyal Customer,64,Personal Travel,Eco,641,3,5,3,4,2,5,4,3,3,3,3,3,3,1,58,27.0,neutral or dissatisfied +50915,97026,Male,Loyal Customer,43,Business travel,Business,794,1,1,1,1,2,4,4,4,4,4,4,5,4,5,0,7.0,satisfied +50916,35607,Male,Loyal Customer,63,Personal Travel,Eco Plus,1076,3,4,3,4,2,3,2,2,3,4,5,4,4,2,0,11.0,neutral or dissatisfied +50917,105605,Female,disloyal Customer,30,Business travel,Business,883,1,1,1,3,1,1,1,1,5,5,5,4,5,1,15,0.0,neutral or dissatisfied +50918,120733,Female,Loyal Customer,47,Business travel,Business,1089,4,4,3,4,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +50919,87761,Male,disloyal Customer,61,Business travel,Business,214,4,4,4,3,5,4,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +50920,121626,Male,Loyal Customer,45,Personal Travel,Eco,912,4,3,3,3,1,3,1,1,3,2,4,2,3,1,0,0.0,satisfied +50921,30540,Female,Loyal Customer,58,Personal Travel,Eco Plus,701,2,5,2,3,2,5,5,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +50922,22609,Female,Loyal Customer,35,Business travel,Business,300,0,0,0,2,3,5,3,1,1,1,1,4,1,1,0,0.0,satisfied +50923,94539,Female,Loyal Customer,54,Business travel,Eco,562,3,1,5,5,5,3,3,3,3,3,3,3,3,4,17,17.0,neutral or dissatisfied +50924,12672,Male,Loyal Customer,26,Business travel,Business,3567,2,2,2,2,3,2,3,3,5,5,2,5,2,3,3,0.0,satisfied +50925,125980,Female,Loyal Customer,39,Business travel,Business,3405,2,3,3,3,3,4,3,2,2,2,2,4,2,1,6,0.0,neutral or dissatisfied +50926,14866,Female,Loyal Customer,38,Business travel,Eco,343,1,4,2,2,1,1,1,1,4,4,4,2,3,1,0,5.0,neutral or dissatisfied +50927,115882,Female,Loyal Customer,48,Business travel,Business,404,3,3,3,3,3,5,4,5,5,5,5,2,5,2,0,0.0,satisfied +50928,122874,Male,Loyal Customer,65,Personal Travel,Eco,226,4,5,4,3,5,4,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +50929,99996,Male,Loyal Customer,47,Business travel,Business,1780,0,1,1,3,5,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +50930,82192,Female,disloyal Customer,33,Business travel,Eco,1297,2,2,2,2,1,2,1,1,3,4,1,1,1,1,10,35.0,neutral or dissatisfied +50931,89506,Female,Loyal Customer,51,Business travel,Business,944,2,2,2,2,4,4,4,2,2,2,2,3,2,4,5,13.0,satisfied +50932,79836,Female,Loyal Customer,51,Business travel,Business,1076,5,5,5,5,5,5,5,5,4,4,5,5,5,5,318,301.0,satisfied +50933,65828,Female,disloyal Customer,24,Business travel,Eco,1389,2,2,2,4,1,2,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +50934,119148,Male,disloyal Customer,48,Business travel,Business,331,5,0,0,3,2,5,2,2,5,4,5,5,4,2,0,0.0,satisfied +50935,78981,Female,Loyal Customer,48,Business travel,Business,3639,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +50936,123627,Male,Loyal Customer,57,Business travel,Business,3699,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +50937,49048,Female,disloyal Customer,43,Business travel,Eco,89,1,5,1,1,1,1,1,1,5,3,4,3,3,1,27,30.0,neutral or dissatisfied +50938,79964,Female,Loyal Customer,41,Business travel,Business,680,1,1,1,1,3,3,3,1,1,1,1,3,1,1,44,36.0,neutral or dissatisfied +50939,92989,Male,Loyal Customer,39,Business travel,Eco,338,2,3,5,3,2,2,2,2,4,1,2,1,2,2,11,54.0,neutral or dissatisfied +50940,76756,Male,Loyal Customer,58,Business travel,Business,2618,2,3,3,3,3,3,3,2,2,2,2,2,2,3,24,8.0,neutral or dissatisfied +50941,68717,Male,Loyal Customer,69,Personal Travel,Eco,237,1,5,0,5,4,0,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +50942,58558,Female,Loyal Customer,40,Personal Travel,Eco,1514,2,3,2,2,5,2,5,5,3,3,5,4,2,5,0,0.0,neutral or dissatisfied +50943,100807,Female,Loyal Customer,38,Business travel,Business,472,2,1,1,1,3,3,3,2,2,2,2,1,2,4,31,27.0,neutral or dissatisfied +50944,91716,Male,disloyal Customer,28,Business travel,Business,590,1,1,1,5,4,1,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +50945,52982,Female,Loyal Customer,42,Personal Travel,Business,1190,3,4,3,2,4,5,5,5,5,3,5,3,5,5,26,29.0,neutral or dissatisfied +50946,69633,Female,Loyal Customer,57,Business travel,Business,2600,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +50947,33844,Female,Loyal Customer,9,Business travel,Eco,1562,3,3,3,3,3,3,1,3,3,3,4,2,3,3,10,0.0,neutral or dissatisfied +50948,78059,Female,Loyal Customer,37,Personal Travel,Eco,106,4,4,4,2,1,4,2,1,3,3,4,5,4,1,0,10.0,neutral or dissatisfied +50949,92252,Female,Loyal Customer,72,Business travel,Eco,170,5,2,2,2,3,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +50950,19318,Female,Loyal Customer,36,Business travel,Business,743,1,1,1,1,3,5,4,2,2,2,2,2,2,3,0,0.0,satisfied +50951,125673,Female,disloyal Customer,25,Business travel,Eco,759,2,2,2,3,2,4,4,3,2,4,4,4,3,4,168,175.0,neutral or dissatisfied +50952,109083,Male,Loyal Customer,13,Personal Travel,Eco,781,1,5,1,3,2,1,2,2,4,5,5,3,4,2,55,40.0,neutral or dissatisfied +50953,11173,Male,Loyal Customer,53,Personal Travel,Eco,312,2,1,2,3,5,2,5,5,2,1,3,4,4,5,31,43.0,neutral or dissatisfied +50954,14933,Male,Loyal Customer,38,Business travel,Business,554,3,3,3,3,2,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +50955,28648,Male,Loyal Customer,35,Personal Travel,Eco,2466,3,5,3,3,5,3,2,5,3,2,3,5,5,5,0,0.0,neutral or dissatisfied +50956,86519,Male,Loyal Customer,54,Personal Travel,Eco,712,2,2,2,3,1,2,1,1,1,3,3,4,4,1,4,0.0,neutral or dissatisfied +50957,80153,Female,Loyal Customer,49,Business travel,Business,2586,3,3,3,3,4,4,4,4,5,4,4,4,4,4,38,41.0,satisfied +50958,67828,Male,Loyal Customer,17,Business travel,Business,3207,2,2,2,2,5,5,5,5,1,2,3,4,3,5,0,0.0,satisfied +50959,87954,Female,Loyal Customer,51,Business travel,Business,1933,5,5,5,5,5,5,5,5,5,5,5,3,5,4,24,26.0,satisfied +50960,69969,Female,Loyal Customer,47,Business travel,Business,236,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +50961,63317,Female,disloyal Customer,37,Business travel,Eco,337,3,4,3,4,4,3,4,4,4,5,3,1,3,4,0,0.0,neutral or dissatisfied +50962,74938,Female,Loyal Customer,53,Business travel,Business,2475,1,4,4,4,3,2,2,1,1,1,1,2,1,3,57,34.0,neutral or dissatisfied +50963,68760,Male,disloyal Customer,27,Business travel,Business,926,2,2,2,3,5,2,5,5,3,4,5,4,4,5,3,0.0,neutral or dissatisfied +50964,17903,Male,Loyal Customer,41,Business travel,Eco,789,4,1,1,1,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +50965,22802,Female,disloyal Customer,41,Business travel,Business,302,3,3,3,4,2,3,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +50966,42064,Male,Loyal Customer,48,Personal Travel,Eco,116,2,5,2,1,4,2,4,4,1,4,3,1,3,4,0,1.0,neutral or dissatisfied +50967,96457,Male,Loyal Customer,55,Business travel,Business,2154,0,0,0,3,2,5,5,4,4,3,3,4,4,5,0,0.0,satisfied +50968,6539,Male,Loyal Customer,44,Business travel,Business,3736,3,3,3,3,5,3,4,3,3,3,3,4,3,4,22,24.0,neutral or dissatisfied +50969,114066,Male,disloyal Customer,37,Business travel,Business,2139,3,3,3,3,4,3,4,4,5,2,4,4,5,4,1,0.0,neutral or dissatisfied +50970,90385,Male,disloyal Customer,25,Business travel,Business,404,4,4,5,1,5,2,2,4,5,4,4,2,4,2,162,176.0,neutral or dissatisfied +50971,48175,Male,Loyal Customer,43,Business travel,Business,1556,3,3,3,3,4,3,4,2,5,4,5,4,3,4,140,125.0,satisfied +50972,97083,Male,Loyal Customer,23,Business travel,Business,1390,3,3,3,3,5,5,5,5,4,5,4,3,4,5,4,17.0,satisfied +50973,52869,Female,Loyal Customer,21,Business travel,Business,3461,3,3,3,3,5,5,5,5,4,4,1,2,4,5,32,30.0,satisfied +50974,65345,Female,Loyal Customer,49,Business travel,Business,631,1,1,4,1,4,5,5,4,4,4,4,3,4,3,82,77.0,satisfied +50975,114229,Female,disloyal Customer,22,Business travel,Eco,853,2,2,2,4,3,2,3,3,3,3,5,3,5,3,1,0.0,neutral or dissatisfied +50976,44801,Male,Loyal Customer,42,Business travel,Eco,1041,4,1,4,4,5,4,5,5,4,1,3,1,2,5,75,71.0,neutral or dissatisfied +50977,73281,Female,Loyal Customer,60,Business travel,Business,1197,1,1,1,1,2,4,5,4,4,5,4,4,4,3,24,,satisfied +50978,83392,Male,Loyal Customer,45,Business travel,Business,632,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +50979,17640,Female,disloyal Customer,29,Business travel,Eco,1008,5,5,5,4,3,5,3,3,4,3,3,3,5,3,0,0.0,satisfied +50980,88746,Male,Loyal Customer,54,Personal Travel,Eco,515,5,5,5,2,5,5,5,5,3,3,4,5,5,5,8,5.0,satisfied +50981,75265,Male,Loyal Customer,44,Personal Travel,Eco,1829,3,4,3,3,1,3,1,1,4,2,3,4,4,1,0,0.0,neutral or dissatisfied +50982,50231,Male,Loyal Customer,51,Business travel,Eco,109,3,1,1,1,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +50983,39541,Female,Loyal Customer,26,Business travel,Business,3530,2,2,2,2,4,4,4,4,5,4,3,1,1,4,0,0.0,satisfied +50984,89307,Male,Loyal Customer,70,Personal Travel,Eco,453,2,4,2,3,2,2,2,2,4,3,5,4,5,2,1,0.0,neutral or dissatisfied +50985,128068,Female,disloyal Customer,33,Business travel,Business,2979,2,2,2,1,2,5,5,3,2,5,4,5,4,5,4,17.0,neutral or dissatisfied +50986,126997,Male,Loyal Customer,31,Business travel,Business,651,2,4,4,4,2,2,2,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +50987,21733,Male,Loyal Customer,27,Business travel,Business,2714,2,2,5,2,4,4,4,4,4,3,2,4,2,4,0,0.0,satisfied +50988,120021,Female,Loyal Customer,67,Personal Travel,Eco,328,2,4,2,5,5,4,4,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +50989,30279,Female,Loyal Customer,10,Personal Travel,Eco,836,2,4,3,1,2,3,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +50990,9466,Female,Loyal Customer,11,Personal Travel,Eco,288,3,4,3,2,4,3,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +50991,49639,Female,Loyal Customer,48,Business travel,Eco,190,3,5,5,5,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +50992,55276,Male,Loyal Customer,45,Business travel,Business,1585,5,5,5,5,3,4,5,3,3,4,3,3,3,5,9,0.0,satisfied +50993,112438,Male,disloyal Customer,48,Business travel,Eco,967,3,3,3,2,4,3,4,4,3,2,2,2,2,4,12,8.0,neutral or dissatisfied +50994,128775,Female,Loyal Customer,54,Personal Travel,Eco,550,3,2,3,4,4,3,3,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +50995,37467,Male,disloyal Customer,25,Business travel,Eco,950,3,3,3,4,3,3,3,3,4,5,3,2,3,3,48,35.0,neutral or dissatisfied +50996,127336,Female,Loyal Customer,59,Business travel,Business,1719,5,5,5,5,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +50997,87223,Male,Loyal Customer,17,Personal Travel,Eco,946,1,3,2,3,3,2,3,3,3,5,3,1,3,3,90,83.0,neutral or dissatisfied +50998,76923,Female,Loyal Customer,50,Business travel,Business,1727,1,1,1,1,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +50999,116265,Female,Loyal Customer,64,Personal Travel,Eco,337,2,5,2,4,2,3,3,4,1,1,5,3,5,3,229,231.0,neutral or dissatisfied +51000,120047,Male,disloyal Customer,20,Business travel,Eco,356,2,0,2,5,1,2,1,1,4,4,5,4,5,1,0,7.0,neutral or dissatisfied +51001,105614,Male,Loyal Customer,48,Business travel,Business,883,1,1,1,1,2,4,4,4,4,4,4,4,4,4,85,69.0,satisfied +51002,72218,Female,Loyal Customer,60,Business travel,Business,3902,4,2,2,2,3,3,3,4,4,4,4,3,4,4,76,70.0,neutral or dissatisfied +51003,115273,Female,Loyal Customer,24,Business travel,Business,480,4,4,4,4,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +51004,21133,Female,Loyal Customer,45,Personal Travel,Eco,106,2,5,2,3,5,5,4,5,5,2,5,4,5,3,5,0.0,neutral or dissatisfied +51005,9238,Male,Loyal Customer,35,Business travel,Business,3328,4,5,5,5,3,4,3,1,4,3,4,3,3,3,158,160.0,neutral or dissatisfied +51006,84820,Male,disloyal Customer,24,Business travel,Eco,547,3,5,3,3,3,3,3,3,3,5,5,5,4,3,1,0.0,neutral or dissatisfied +51007,118521,Female,disloyal Customer,23,Business travel,Business,647,4,0,4,1,4,4,4,4,3,2,5,4,5,4,31,36.0,satisfied +51008,68377,Male,Loyal Customer,37,Business travel,Business,1833,4,4,4,4,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +51009,22916,Female,Loyal Customer,38,Business travel,Business,1789,3,3,3,3,5,2,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +51010,37533,Male,Loyal Customer,51,Business travel,Eco,1074,3,1,1,1,3,3,3,4,1,3,3,3,1,3,145,150.0,neutral or dissatisfied +51011,93036,Female,Loyal Customer,54,Business travel,Business,436,4,4,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +51012,103495,Female,disloyal Customer,36,Business travel,Eco Plus,440,3,3,3,5,1,3,1,1,2,1,2,1,4,1,0,0.0,neutral or dissatisfied +51013,111543,Female,Loyal Customer,33,Business travel,Business,1965,2,5,2,2,5,4,4,5,5,5,5,5,5,4,5,0.0,satisfied +51014,44714,Male,Loyal Customer,11,Personal Travel,Eco,160,1,5,1,2,3,1,3,3,4,3,4,5,4,3,67,68.0,neutral or dissatisfied +51015,3940,Male,Loyal Customer,59,Business travel,Business,765,1,1,1,1,4,4,5,5,5,5,5,5,5,5,13,8.0,satisfied +51016,84853,Male,Loyal Customer,55,Business travel,Business,147,4,4,4,4,4,4,3,4,4,4,4,1,4,1,119,124.0,neutral or dissatisfied +51017,25912,Male,Loyal Customer,9,Personal Travel,Business,594,4,1,4,2,2,4,2,2,2,5,1,3,1,2,4,0.0,satisfied +51018,87724,Female,Loyal Customer,61,Personal Travel,Eco Plus,606,3,5,3,2,3,4,4,1,1,3,2,5,1,3,0,2.0,neutral or dissatisfied +51019,2397,Female,Loyal Customer,29,Business travel,Business,604,2,3,3,3,2,2,2,2,2,1,4,2,4,2,5,17.0,neutral or dissatisfied +51020,46791,Female,disloyal Customer,42,Business travel,Business,737,1,1,1,5,5,1,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +51021,42418,Male,Loyal Customer,21,Business travel,Eco Plus,329,0,5,0,3,4,0,4,4,2,5,5,4,3,4,0,0.0,satisfied +51022,71917,Male,Loyal Customer,57,Personal Travel,Eco,1744,5,1,5,2,1,5,1,1,3,5,2,4,2,1,0,0.0,satisfied +51023,5449,Female,disloyal Customer,49,Business travel,Business,265,2,2,2,1,2,5,3,5,2,4,4,3,5,3,124,150.0,neutral or dissatisfied +51024,66548,Female,Loyal Customer,46,Business travel,Business,328,5,5,3,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +51025,101128,Female,Loyal Customer,60,Business travel,Business,3639,2,2,2,2,2,5,5,4,4,4,4,5,4,5,6,0.0,satisfied +51026,66972,Female,Loyal Customer,26,Business travel,Business,1121,2,2,4,2,5,5,5,5,4,4,4,3,5,5,29,26.0,satisfied +51027,95643,Female,Loyal Customer,57,Personal Travel,Eco Plus,756,4,5,4,2,2,5,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +51028,37514,Female,Loyal Customer,9,Business travel,Business,972,2,1,2,2,3,4,3,3,5,5,4,5,3,3,0,0.0,satisfied +51029,71541,Male,disloyal Customer,22,Business travel,Eco,1005,5,4,4,3,1,4,1,1,5,2,4,4,5,1,1,3.0,satisfied +51030,3995,Male,Loyal Customer,34,Business travel,Business,2879,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,1.0,satisfied +51031,904,Female,Loyal Customer,51,Business travel,Business,354,3,1,1,1,2,3,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +51032,29126,Male,Loyal Customer,66,Personal Travel,Eco,605,3,2,2,3,2,2,1,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +51033,122924,Male,Loyal Customer,62,Personal Travel,Business,468,3,4,3,5,5,3,2,5,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +51034,18958,Female,Loyal Customer,55,Business travel,Eco Plus,448,5,4,4,4,2,4,2,5,5,5,5,4,5,3,16,10.0,satisfied +51035,99048,Female,Loyal Customer,54,Business travel,Business,3307,1,1,1,1,2,5,4,4,4,4,4,3,4,5,67,62.0,satisfied +51036,10011,Female,Loyal Customer,24,Business travel,Business,3682,1,1,1,1,2,2,2,2,4,2,4,3,4,2,0,0.0,satisfied +51037,115053,Female,Loyal Customer,40,Business travel,Business,3785,4,4,4,4,5,4,4,5,5,5,5,3,5,4,17,5.0,satisfied +51038,64982,Male,Loyal Customer,56,Business travel,Business,3732,3,3,3,3,4,4,2,5,5,5,5,4,5,3,0,0.0,satisfied +51039,15258,Female,Loyal Customer,36,Personal Travel,Eco,583,3,4,3,5,3,3,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +51040,16332,Female,Loyal Customer,22,Personal Travel,Eco,628,3,5,3,1,3,3,3,3,2,4,1,3,5,3,0,0.0,neutral or dissatisfied +51041,3665,Male,Loyal Customer,51,Business travel,Business,431,1,1,1,1,2,4,4,4,4,4,4,4,4,5,0,1.0,satisfied +51042,27243,Male,Loyal Customer,59,Personal Travel,Eco,1024,3,5,3,3,4,3,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +51043,120072,Female,Loyal Customer,26,Business travel,Business,683,2,2,2,2,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +51044,117042,Male,Loyal Customer,60,Business travel,Business,338,5,5,5,5,3,4,5,5,5,5,5,3,5,4,24,16.0,satisfied +51045,40375,Male,Loyal Customer,46,Business travel,Eco,1250,3,1,1,1,3,3,3,3,1,3,3,1,2,3,11,9.0,neutral or dissatisfied +51046,12581,Female,disloyal Customer,25,Business travel,Eco,542,5,0,5,4,1,5,1,1,5,4,5,5,5,1,25,18.0,satisfied +51047,41071,Female,Loyal Customer,48,Business travel,Eco,429,5,4,4,4,5,5,2,5,5,5,5,2,5,5,2,1.0,satisfied +51048,41271,Male,Loyal Customer,23,Personal Travel,Eco,305,2,5,2,4,3,2,1,3,4,5,5,4,4,3,4,8.0,neutral or dissatisfied +51049,24060,Male,Loyal Customer,16,Personal Travel,Eco,562,3,5,4,3,1,4,1,1,3,3,4,4,5,1,29,30.0,neutral or dissatisfied +51050,45730,Male,Loyal Customer,30,Business travel,Eco Plus,852,2,4,4,4,2,2,2,1,3,3,4,2,4,2,139,152.0,neutral or dissatisfied +51051,46225,Female,Loyal Customer,22,Business travel,Eco,679,0,4,0,3,4,0,4,4,3,3,5,3,2,4,0,22.0,satisfied +51052,96722,Female,Loyal Customer,7,Personal Travel,Eco,696,2,5,2,3,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +51053,127004,Male,disloyal Customer,25,Business travel,Business,370,3,0,3,3,2,3,2,2,5,5,5,4,5,2,0,1.0,neutral or dissatisfied +51054,99349,Male,disloyal Customer,25,Business travel,Eco,1771,3,3,3,4,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +51055,38995,Female,Loyal Customer,39,Business travel,Eco,406,4,5,3,5,4,4,4,4,3,1,2,4,2,4,23,57.0,neutral or dissatisfied +51056,43471,Female,Loyal Customer,30,Business travel,Business,2873,3,2,3,3,3,3,3,3,3,4,2,1,3,3,42,84.0,neutral or dissatisfied +51057,73660,Male,disloyal Customer,38,Business travel,Business,204,5,5,5,1,5,5,1,5,5,2,4,3,4,5,3,12.0,satisfied +51058,85771,Female,Loyal Customer,11,Business travel,Business,666,2,2,3,3,2,2,2,2,4,4,4,2,3,2,1,9.0,neutral or dissatisfied +51059,58184,Female,disloyal Customer,31,Business travel,Eco,925,3,3,3,3,1,3,1,1,2,3,3,4,3,1,16,5.0,neutral or dissatisfied +51060,30241,Male,Loyal Customer,26,Personal Travel,Eco,826,2,5,2,4,5,2,2,5,4,4,4,4,4,5,11,48.0,neutral or dissatisfied +51061,19510,Male,Loyal Customer,66,Personal Travel,Eco,350,2,4,2,1,1,2,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +51062,107488,Female,Loyal Customer,50,Business travel,Business,3467,4,2,2,2,5,3,3,4,4,3,4,1,4,3,65,67.0,neutral or dissatisfied +51063,53475,Female,Loyal Customer,48,Business travel,Eco,2288,4,5,5,5,4,2,3,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +51064,115802,Male,Loyal Customer,23,Business travel,Business,2004,2,3,3,3,2,2,2,2,4,5,4,4,3,2,52,46.0,neutral or dissatisfied +51065,60693,Male,Loyal Customer,51,Business travel,Business,1605,4,4,4,4,2,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +51066,10501,Male,Loyal Customer,48,Business travel,Business,517,4,4,4,4,4,4,4,3,2,4,5,4,5,4,216,224.0,satisfied +51067,84377,Male,Loyal Customer,37,Business travel,Business,606,3,3,3,3,5,5,5,5,2,5,4,5,5,5,158,169.0,satisfied +51068,121672,Female,disloyal Customer,38,Business travel,Eco,328,1,0,0,5,4,0,4,4,2,1,2,5,2,4,12,4.0,neutral or dissatisfied +51069,93255,Male,disloyal Customer,36,Business travel,Business,1180,4,4,4,2,2,4,5,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +51070,111269,Female,Loyal Customer,42,Business travel,Business,459,1,1,1,1,5,4,5,5,5,5,5,4,5,3,27,22.0,satisfied +51071,115049,Female,Loyal Customer,40,Business travel,Business,296,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +51072,31357,Male,Loyal Customer,40,Business travel,Eco,589,4,2,2,2,4,4,4,4,2,2,4,2,4,4,0,0.0,satisfied +51073,111245,Male,Loyal Customer,50,Business travel,Business,1849,4,4,1,4,3,5,4,4,4,4,4,4,4,3,18,24.0,satisfied +51074,73187,Female,Loyal Customer,60,Business travel,Business,3644,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +51075,73710,Female,Loyal Customer,42,Business travel,Business,3202,2,3,3,3,5,2,2,1,1,1,2,3,1,3,1,0.0,neutral or dissatisfied +51076,11739,Male,Loyal Customer,42,Business travel,Business,2100,3,3,3,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +51077,102702,Male,disloyal Customer,16,Business travel,Eco,255,3,2,3,2,4,3,4,4,1,3,2,3,3,4,34,24.0,neutral or dissatisfied +51078,50499,Male,Loyal Customer,65,Personal Travel,Eco,86,4,5,4,5,4,4,4,4,2,1,4,4,5,4,0,0.0,neutral or dissatisfied +51079,27808,Female,Loyal Customer,20,Business travel,Business,3948,3,3,3,3,4,4,4,4,3,1,3,2,3,4,0,0.0,satisfied +51080,44808,Female,Loyal Customer,55,Business travel,Eco,1041,2,5,5,5,1,3,4,2,2,2,2,3,2,2,48,79.0,neutral or dissatisfied +51081,44117,Female,Loyal Customer,54,Business travel,Eco,198,5,1,1,1,1,1,2,5,5,5,5,4,5,1,0,0.0,satisfied +51082,74278,Male,Loyal Customer,9,Business travel,Business,2288,4,4,4,4,4,4,4,4,5,3,3,4,4,4,0,0.0,satisfied +51083,40059,Male,Loyal Customer,11,Personal Travel,Eco Plus,866,2,5,2,3,5,2,5,5,1,3,3,5,3,5,0,0.0,neutral or dissatisfied +51084,116657,Female,Loyal Customer,41,Business travel,Business,1640,2,2,2,2,4,5,5,4,4,4,4,4,4,3,11,0.0,satisfied +51085,125177,Male,Loyal Customer,55,Business travel,Business,651,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,2.0,satisfied +51086,102837,Male,Loyal Customer,40,Business travel,Business,2995,1,1,1,1,3,4,4,5,5,5,5,4,5,3,0,2.0,satisfied +51087,99345,Female,Loyal Customer,26,Business travel,Business,1771,4,2,5,2,4,3,4,4,2,1,3,4,3,4,0,6.0,neutral or dissatisfied +51088,50797,Female,Loyal Customer,49,Personal Travel,Eco,447,4,4,4,3,1,3,3,4,4,4,4,4,4,5,0,0.0,satisfied +51089,1924,Male,Loyal Customer,47,Business travel,Business,351,2,2,2,2,2,4,5,4,4,4,4,5,4,3,10,6.0,satisfied +51090,107272,Male,Loyal Customer,57,Business travel,Business,283,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +51091,19569,Female,Loyal Customer,47,Business travel,Business,3766,3,2,2,2,1,4,3,4,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +51092,35849,Female,Loyal Customer,39,Business travel,Business,3805,4,4,4,4,1,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +51093,73283,Male,Loyal Customer,42,Business travel,Business,2326,4,4,4,4,3,4,5,4,4,4,4,5,4,4,81,72.0,satisfied +51094,90596,Female,Loyal Customer,44,Business travel,Business,3580,5,5,5,5,2,4,4,5,5,4,5,3,5,5,6,7.0,satisfied +51095,111801,Female,Loyal Customer,35,Business travel,Business,3001,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +51096,126466,Male,disloyal Customer,34,Business travel,Business,1788,4,4,4,5,5,4,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +51097,36594,Female,disloyal Customer,26,Business travel,Eco,1121,3,4,4,3,1,4,1,1,4,3,1,5,4,1,0,0.0,neutral or dissatisfied +51098,53984,Female,Loyal Customer,40,Business travel,Eco,1825,4,1,1,1,4,4,4,4,3,5,4,1,5,4,4,0.0,satisfied +51099,110001,Female,disloyal Customer,36,Business travel,Business,1204,1,1,1,3,1,1,1,1,4,5,4,4,4,1,21,16.0,neutral or dissatisfied +51100,70249,Female,Loyal Customer,17,Business travel,Business,1592,3,3,3,3,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +51101,78763,Female,Loyal Customer,37,Business travel,Business,447,5,5,5,5,2,5,5,4,4,4,4,4,4,5,0,5.0,satisfied +51102,6594,Male,Loyal Customer,26,Personal Travel,Eco,607,3,4,3,4,2,3,2,2,3,5,5,4,5,2,60,78.0,neutral or dissatisfied +51103,24807,Female,Loyal Customer,28,Business travel,Eco,991,0,0,0,3,2,0,2,2,4,4,4,2,2,2,0,28.0,satisfied +51104,34466,Female,disloyal Customer,44,Business travel,Eco,266,4,2,4,3,4,4,4,4,2,4,3,2,3,4,0,0.0,satisfied +51105,102249,Female,Loyal Customer,59,Business travel,Eco,407,3,4,4,4,4,2,2,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +51106,19653,Male,disloyal Customer,39,Business travel,Business,363,2,2,2,4,1,2,1,1,3,5,4,4,4,1,4,0.0,neutral or dissatisfied +51107,90043,Female,Loyal Customer,60,Business travel,Business,1145,5,5,5,5,5,5,5,5,5,5,5,4,5,5,73,73.0,satisfied +51108,63114,Male,Loyal Customer,60,Personal Travel,Eco Plus,967,1,4,1,4,2,1,2,2,2,4,4,3,4,2,0,0.0,neutral or dissatisfied +51109,96837,Male,disloyal Customer,33,Business travel,Eco,571,2,3,2,4,4,2,4,4,3,1,3,4,3,4,10,3.0,neutral or dissatisfied +51110,34662,Female,Loyal Customer,49,Business travel,Business,264,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +51111,53903,Female,Loyal Customer,38,Personal Travel,Eco,140,0,2,0,2,2,0,3,2,1,1,1,2,3,2,6,0.0,satisfied +51112,69571,Female,disloyal Customer,30,Business travel,Eco,2586,2,2,2,4,2,4,4,1,3,3,4,4,2,4,0,0.0,neutral or dissatisfied +51113,27288,Male,Loyal Customer,33,Business travel,Business,671,3,3,3,3,5,5,5,5,2,5,3,4,3,5,0,0.0,satisfied +51114,45444,Male,Loyal Customer,44,Personal Travel,Eco Plus,649,2,3,2,1,1,2,1,1,2,3,3,1,2,1,63,51.0,neutral or dissatisfied +51115,56064,Male,Loyal Customer,41,Personal Travel,Eco,2586,2,5,2,2,2,1,1,1,3,5,4,1,2,1,17,0.0,neutral or dissatisfied +51116,7412,Male,Loyal Customer,43,Business travel,Business,552,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,5.0,satisfied +51117,25929,Male,Loyal Customer,39,Business travel,Eco,194,5,2,2,2,5,5,5,5,2,3,5,2,4,5,6,0.0,satisfied +51118,20214,Female,Loyal Customer,39,Business travel,Eco,228,3,5,5,5,3,3,3,3,3,2,4,1,4,3,3,0.0,satisfied +51119,79449,Male,Loyal Customer,37,Business travel,Business,2625,4,4,4,4,5,4,5,5,5,5,5,4,5,4,2,0.0,satisfied +51120,121240,Female,Loyal Customer,34,Business travel,Business,2075,2,1,1,1,1,2,4,2,2,2,2,3,2,2,80,81.0,neutral or dissatisfied +51121,89192,Male,Loyal Customer,35,Personal Travel,Eco,1947,4,5,4,3,1,4,1,1,5,2,4,4,5,1,2,0.0,satisfied +51122,12373,Male,disloyal Customer,37,Business travel,Eco,127,3,4,3,3,5,3,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +51123,114742,Female,Loyal Customer,58,Business travel,Business,3685,0,1,1,4,4,4,5,1,1,1,1,3,1,5,89,85.0,satisfied +51124,66469,Female,Loyal Customer,40,Business travel,Business,447,3,3,3,3,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +51125,97463,Male,disloyal Customer,29,Business travel,Business,822,4,4,4,2,5,4,5,5,4,3,5,3,4,5,11,11.0,satisfied +51126,31281,Male,Loyal Customer,50,Personal Travel,Eco,770,3,5,3,4,4,3,5,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +51127,116850,Female,Loyal Customer,52,Business travel,Business,1778,2,2,2,2,2,5,4,5,5,5,5,5,5,3,25,26.0,satisfied +51128,94123,Female,Loyal Customer,40,Business travel,Business,528,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +51129,106921,Male,Loyal Customer,36,Business travel,Eco,859,3,1,1,1,3,3,3,3,1,2,3,3,3,3,57,67.0,neutral or dissatisfied +51130,1647,Male,Loyal Customer,48,Business travel,Business,2349,5,5,5,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +51131,112201,Male,Loyal Customer,42,Business travel,Business,649,5,5,5,5,4,5,4,3,3,4,3,4,3,5,6,10.0,satisfied +51132,47382,Female,Loyal Customer,31,Business travel,Business,3912,4,2,5,2,4,4,4,4,1,2,3,2,4,4,43,32.0,neutral or dissatisfied +51133,5450,Female,Loyal Customer,57,Business travel,Business,2043,2,2,2,2,5,5,4,5,5,5,5,3,5,4,31,17.0,satisfied +51134,44380,Male,Loyal Customer,49,Personal Travel,Eco,229,2,5,2,2,2,2,2,2,5,3,5,4,4,2,0,8.0,neutral or dissatisfied +51135,82760,Male,Loyal Customer,45,Personal Travel,Eco,409,2,2,2,3,4,2,4,4,3,4,4,3,3,4,1,0.0,neutral or dissatisfied +51136,106311,Female,disloyal Customer,38,Business travel,Eco,598,0,0,0,1,3,0,1,3,3,3,5,3,1,3,0,0.0,satisfied +51137,44488,Male,Loyal Customer,44,Personal Travel,Eco,476,3,2,3,4,3,3,3,3,1,3,3,4,3,3,112,114.0,neutral or dissatisfied +51138,99316,Female,disloyal Customer,62,Business travel,Business,337,2,1,1,4,3,2,3,3,4,3,4,5,4,3,0,0.0,satisfied +51139,93872,Female,Loyal Customer,52,Business travel,Business,590,5,5,3,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +51140,126308,Male,Loyal Customer,62,Personal Travel,Eco,631,3,4,3,5,5,3,5,5,4,4,3,5,3,5,0,0.0,neutral or dissatisfied +51141,118996,Male,Loyal Customer,50,Business travel,Business,2211,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +51142,70657,Male,Loyal Customer,50,Personal Travel,Eco,946,1,1,1,3,3,1,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +51143,123356,Female,Loyal Customer,49,Business travel,Business,644,3,3,3,3,3,5,5,5,5,5,5,3,5,5,26,12.0,satisfied +51144,64559,Female,disloyal Customer,25,Business travel,Business,551,2,4,2,1,1,2,1,1,4,3,5,5,4,1,5,8.0,neutral or dissatisfied +51145,48593,Male,Loyal Customer,67,Personal Travel,Eco,853,2,5,3,5,2,3,2,2,3,4,4,3,4,2,0,14.0,neutral or dissatisfied +51146,82433,Male,Loyal Customer,55,Business travel,Business,502,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +51147,79586,Male,Loyal Customer,27,Business travel,Business,749,5,1,5,5,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +51148,27528,Male,Loyal Customer,43,Personal Travel,Eco,978,3,5,3,3,2,3,3,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +51149,129549,Male,disloyal Customer,17,Business travel,Eco,1411,3,3,3,4,4,3,4,4,5,5,3,1,5,4,0,0.0,neutral or dissatisfied +51150,51096,Female,Loyal Customer,57,Personal Travel,Eco,209,2,1,2,2,1,3,3,5,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +51151,690,Female,Loyal Customer,59,Business travel,Business,164,0,4,0,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +51152,35765,Male,Loyal Customer,35,Business travel,Business,200,1,1,1,1,5,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +51153,76795,Male,Loyal Customer,46,Business travel,Business,289,3,3,3,3,5,4,3,5,5,5,5,4,5,1,0,3.0,satisfied +51154,41963,Female,Loyal Customer,23,Business travel,Business,3530,3,3,3,3,4,4,4,4,2,2,1,3,4,4,0,0.0,satisfied +51155,8786,Male,Loyal Customer,49,Business travel,Business,1722,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,4.0,satisfied +51156,108933,Male,Loyal Customer,47,Personal Travel,Eco,1183,4,1,4,4,4,4,4,2,3,3,3,4,2,4,158,148.0,neutral or dissatisfied +51157,54912,Male,Loyal Customer,55,Business travel,Eco Plus,862,4,3,3,3,4,4,4,4,2,4,4,1,4,4,3,0.0,neutral or dissatisfied +51158,53909,Female,Loyal Customer,12,Personal Travel,Eco,191,2,3,2,3,2,2,2,2,4,2,1,3,1,2,1,8.0,neutral or dissatisfied +51159,9154,Female,Loyal Customer,47,Business travel,Business,3016,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +51160,72571,Male,Loyal Customer,51,Business travel,Eco,585,4,1,1,1,4,4,4,4,2,3,2,4,3,4,0,0.0,satisfied +51161,28538,Male,Loyal Customer,30,Business travel,Business,2640,3,3,3,3,3,3,3,3,5,2,4,3,1,3,0,10.0,neutral or dissatisfied +51162,5939,Female,Loyal Customer,25,Business travel,Business,1856,4,4,4,4,4,4,5,4,3,2,4,4,4,4,32,18.0,satisfied +51163,87203,Male,Loyal Customer,37,Business travel,Eco,546,3,2,2,2,3,3,3,3,3,2,4,1,4,3,0,0.0,neutral or dissatisfied +51164,7630,Female,Loyal Customer,34,Business travel,Business,604,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +51165,20388,Female,Loyal Customer,30,Business travel,Business,2421,2,2,2,2,4,4,4,4,4,1,4,3,3,4,0,0.0,satisfied +51166,17167,Male,disloyal Customer,23,Business travel,Eco,643,5,2,5,2,1,5,1,1,5,1,4,4,2,1,0,5.0,satisfied +51167,25325,Male,Loyal Customer,35,Business travel,Business,1699,4,4,4,4,1,1,2,4,4,4,4,1,4,4,0,5.0,satisfied +51168,91404,Male,Loyal Customer,29,Personal Travel,Eco,2218,2,2,2,4,2,2,2,2,4,5,4,1,4,2,8,6.0,neutral or dissatisfied +51169,29262,Female,disloyal Customer,25,Business travel,Eco,550,1,4,1,4,3,1,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +51170,33098,Female,Loyal Customer,24,Personal Travel,Eco,101,2,5,2,2,1,2,1,1,5,4,5,5,4,1,0,5.0,neutral or dissatisfied +51171,20016,Female,Loyal Customer,63,Business travel,Eco Plus,646,3,5,5,5,4,3,4,3,3,3,3,3,3,4,21,31.0,neutral or dissatisfied +51172,80680,Male,Loyal Customer,55,Personal Travel,Eco Plus,821,3,1,3,1,4,3,3,4,4,4,1,1,2,4,2,0.0,neutral or dissatisfied +51173,96040,Male,Loyal Customer,25,Business travel,Business,1069,2,2,2,2,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +51174,129158,Female,Loyal Customer,48,Business travel,Business,2864,1,1,1,1,3,5,4,4,4,4,4,4,4,3,17,0.0,satisfied +51175,72976,Male,Loyal Customer,32,Business travel,Eco,1096,4,3,4,3,4,3,4,4,2,3,4,2,3,4,0,0.0,neutral or dissatisfied +51176,112301,Female,Loyal Customer,36,Business travel,Eco,171,4,4,4,4,4,4,4,4,3,2,2,2,2,4,88,50.0,satisfied +51177,97092,Male,Loyal Customer,31,Business travel,Business,1390,1,3,3,3,1,1,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +51178,55168,Male,Loyal Customer,51,Personal Travel,Eco,1379,3,4,3,2,2,3,2,2,3,5,5,3,5,2,8,1.0,neutral or dissatisfied +51179,10716,Male,disloyal Customer,37,Business travel,Business,247,5,4,4,5,3,4,3,3,4,3,4,3,4,3,0,0.0,satisfied +51180,18878,Female,disloyal Customer,25,Business travel,Eco,448,2,0,2,4,5,2,3,5,2,2,2,5,4,5,0,3.0,neutral or dissatisfied +51181,106973,Female,disloyal Customer,23,Business travel,Business,937,5,3,5,2,5,5,5,5,4,4,4,4,5,5,0,0.0,satisfied +51182,125581,Female,disloyal Customer,39,Business travel,Business,226,2,2,2,4,2,2,2,2,5,4,5,3,5,2,3,0.0,neutral or dissatisfied +51183,109762,Female,Loyal Customer,46,Business travel,Business,1130,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +51184,24892,Female,Loyal Customer,48,Business travel,Eco,397,4,4,4,4,5,5,1,4,4,4,4,5,4,5,0,0.0,satisfied +51185,23366,Male,disloyal Customer,8,Business travel,Eco,1014,2,2,2,4,2,2,2,2,4,3,4,3,4,2,4,6.0,neutral or dissatisfied +51186,119387,Male,disloyal Customer,25,Business travel,Business,399,2,5,2,1,2,2,2,2,4,5,4,4,4,2,37,23.0,neutral or dissatisfied +51187,45308,Female,Loyal Customer,38,Business travel,Business,150,4,4,4,4,3,4,2,4,4,4,3,2,4,4,0,0.0,satisfied +51188,94706,Female,Loyal Customer,55,Business travel,Business,2391,2,2,2,2,2,5,5,4,4,4,4,4,4,4,6,0.0,satisfied +51189,31926,Female,Loyal Customer,41,Business travel,Business,216,2,4,4,4,5,4,4,1,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +51190,19638,Female,Loyal Customer,32,Personal Travel,Eco,717,2,5,2,2,2,4,3,2,1,4,3,3,3,3,119,142.0,neutral or dissatisfied +51191,9822,Male,disloyal Customer,21,Business travel,Business,451,4,5,4,3,5,4,5,5,5,2,5,4,4,5,22,38.0,satisfied +51192,108081,Male,disloyal Customer,24,Business travel,Eco,997,5,5,5,3,3,5,3,3,3,2,4,3,4,3,5,2.0,satisfied +51193,111845,Male,disloyal Customer,36,Business travel,Business,804,3,3,3,4,3,4,1,5,5,4,4,1,3,1,173,163.0,neutral or dissatisfied +51194,31536,Female,Loyal Customer,23,Personal Travel,Eco,967,4,5,4,5,2,4,2,2,4,4,5,4,5,2,0,0.0,satisfied +51195,54936,Male,Loyal Customer,62,Business travel,Business,3499,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +51196,118314,Female,Loyal Customer,51,Business travel,Business,602,4,4,3,4,4,4,5,5,5,5,5,5,5,4,48,34.0,satisfied +51197,126323,Male,Loyal Customer,41,Personal Travel,Eco,631,3,4,3,4,2,3,2,2,5,4,4,4,5,2,45,23.0,neutral or dissatisfied +51198,119641,Female,disloyal Customer,45,Business travel,Business,507,3,3,3,4,5,3,4,5,4,2,3,2,4,5,0,0.0,neutral or dissatisfied +51199,47203,Female,Loyal Customer,7,Personal Travel,Eco,954,4,4,4,1,1,4,1,1,5,3,5,1,1,1,16,4.0,satisfied +51200,82261,Female,Loyal Customer,39,Business travel,Business,1481,2,2,2,2,4,4,5,3,3,3,3,3,3,4,10,5.0,satisfied +51201,47582,Male,Loyal Customer,9,Personal Travel,Business,1464,1,5,1,4,1,1,5,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +51202,120840,Female,Loyal Customer,49,Business travel,Business,2920,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +51203,79134,Female,Loyal Customer,69,Business travel,Business,2489,2,2,2,2,4,5,4,4,4,4,4,4,4,5,16,13.0,satisfied +51204,28727,Female,Loyal Customer,45,Business travel,Eco Plus,2554,4,2,2,2,4,5,5,2,4,3,1,5,1,5,2,28.0,satisfied +51205,119597,Female,Loyal Customer,26,Business travel,Business,1979,3,1,1,1,3,3,3,3,1,5,3,4,4,3,4,0.0,neutral or dissatisfied +51206,62006,Male,Loyal Customer,47,Business travel,Business,2586,4,4,4,4,3,3,3,4,3,3,5,3,4,3,190,185.0,satisfied +51207,22969,Male,Loyal Customer,25,Business travel,Eco,641,1,3,3,3,1,1,1,2,1,2,3,1,4,1,203,206.0,neutral or dissatisfied +51208,24495,Male,Loyal Customer,42,Personal Travel,Eco,547,3,4,3,4,5,3,5,5,2,4,4,1,5,5,0,2.0,neutral or dissatisfied +51209,77213,Female,Loyal Customer,39,Personal Travel,Business,1590,3,4,3,5,5,5,4,2,2,3,2,3,2,4,5,0.0,neutral or dissatisfied +51210,34869,Male,Loyal Customer,25,Business travel,Business,2248,1,3,3,3,1,1,1,1,2,5,2,1,3,1,0,0.0,neutral or dissatisfied +51211,36869,Male,Loyal Customer,11,Personal Travel,Eco,273,2,3,2,4,3,2,3,3,1,3,4,1,4,3,0,1.0,neutral or dissatisfied +51212,21197,Female,Loyal Customer,43,Business travel,Eco,317,5,4,4,4,4,2,4,5,5,5,5,3,5,4,0,0.0,satisfied +51213,88709,Female,Loyal Customer,29,Personal Travel,Eco,404,2,3,2,1,2,2,5,2,4,3,4,2,5,2,11,9.0,neutral or dissatisfied +51214,43914,Female,Loyal Customer,58,Personal Travel,Eco,114,1,1,1,4,3,3,3,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +51215,182,Male,Loyal Customer,44,Business travel,Business,2569,4,4,4,4,2,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +51216,4796,Female,Loyal Customer,68,Personal Travel,Eco,438,2,5,2,4,2,3,4,3,2,5,4,4,5,4,362,356.0,neutral or dissatisfied +51217,90494,Male,Loyal Customer,47,Business travel,Business,404,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +51218,79076,Female,Loyal Customer,32,Personal Travel,Eco,356,3,5,3,3,1,3,1,1,5,2,4,5,5,1,9,5.0,neutral or dissatisfied +51219,26427,Male,Loyal Customer,47,Business travel,Eco,925,5,5,5,5,5,5,5,5,5,2,4,4,4,5,31,14.0,satisfied +51220,123559,Female,Loyal Customer,51,Business travel,Business,1773,4,2,4,4,5,4,5,5,5,5,5,5,5,4,12,0.0,satisfied +51221,25977,Male,Loyal Customer,58,Personal Travel,Eco Plus,946,2,4,2,4,1,2,1,1,1,5,4,2,3,1,28,6.0,neutral or dissatisfied +51222,97203,Male,Loyal Customer,36,Personal Travel,Eco,1313,3,5,3,4,2,3,3,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +51223,18290,Male,Loyal Customer,70,Business travel,Business,2754,3,1,1,1,4,3,4,3,3,3,3,4,3,2,0,33.0,neutral or dissatisfied +51224,123309,Male,Loyal Customer,49,Business travel,Business,650,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +51225,31574,Male,Loyal Customer,46,Business travel,Business,602,1,1,4,1,4,4,5,5,5,5,5,4,5,4,1,6.0,satisfied +51226,43183,Female,Loyal Customer,66,Business travel,Business,2611,4,5,5,5,4,2,1,4,4,4,4,3,4,1,108,94.0,neutral or dissatisfied +51227,36035,Male,Loyal Customer,54,Business travel,Business,3643,4,4,4,4,2,2,2,5,5,5,5,4,5,3,8,7.0,satisfied +51228,37315,Male,Loyal Customer,25,Business travel,Business,1813,3,3,3,3,5,5,5,5,5,2,2,5,4,5,68,57.0,satisfied +51229,125412,Female,disloyal Customer,25,Business travel,Business,735,2,4,3,4,3,3,4,3,1,2,3,2,3,3,12,0.0,neutral or dissatisfied +51230,106566,Male,Loyal Customer,60,Personal Travel,Eco,1024,2,5,2,1,5,2,5,5,5,4,5,3,4,5,1,5.0,neutral or dissatisfied +51231,39387,Female,disloyal Customer,25,Business travel,Eco,521,2,0,2,3,1,2,1,1,4,4,1,2,3,1,0,0.0,neutral or dissatisfied +51232,60224,Male,Loyal Customer,42,Business travel,Eco,1506,1,2,1,2,1,1,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +51233,15438,Female,Loyal Customer,42,Business travel,Eco,331,2,4,4,4,2,3,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +51234,36203,Male,disloyal Customer,26,Business travel,Eco,496,1,3,1,4,5,1,2,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +51235,15245,Male,Loyal Customer,27,Personal Travel,Eco,445,3,4,3,3,2,3,4,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +51236,47028,Female,Loyal Customer,21,Business travel,Eco,639,5,1,1,1,5,5,5,5,3,2,1,4,3,5,82,85.0,satisfied +51237,79172,Female,Loyal Customer,27,Business travel,Business,2422,1,1,1,1,4,4,4,4,3,3,4,3,5,4,30,0.0,satisfied +51238,129318,Female,disloyal Customer,30,Business travel,Business,2586,2,3,3,4,1,3,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +51239,125256,Female,Loyal Customer,68,Personal Travel,Eco,427,1,2,1,4,2,3,4,5,5,1,5,1,5,4,0,4.0,neutral or dissatisfied +51240,34655,Female,Loyal Customer,42,Business travel,Business,3842,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +51241,122835,Female,Loyal Customer,59,Business travel,Business,226,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +51242,13044,Female,Loyal Customer,56,Personal Travel,Eco,438,3,4,3,1,2,4,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +51243,78284,Male,Loyal Customer,21,Business travel,Business,1598,2,2,2,2,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +51244,87946,Male,Loyal Customer,15,Personal Travel,Business,240,3,5,0,5,3,0,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +51245,2108,Female,Loyal Customer,31,Business travel,Business,3107,3,3,2,2,3,3,3,3,2,4,3,3,2,3,0,0.0,neutral or dissatisfied +51246,25323,Female,disloyal Customer,22,Business travel,Eco,829,2,3,3,2,1,3,1,1,1,3,3,3,3,1,4,4.0,neutral or dissatisfied +51247,74335,Male,disloyal Customer,28,Business travel,Business,1235,3,3,3,4,4,3,3,4,2,1,4,3,3,4,26,21.0,neutral or dissatisfied +51248,48378,Male,Loyal Customer,58,Personal Travel,Eco,587,3,4,3,3,4,3,4,4,4,2,5,5,4,4,52,54.0,neutral or dissatisfied +51249,91619,Female,Loyal Customer,22,Business travel,Business,1340,4,4,4,4,3,4,3,3,5,4,5,4,5,3,111,103.0,satisfied +51250,114685,Female,Loyal Customer,36,Business travel,Business,1994,3,1,1,1,2,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +51251,5034,Female,Loyal Customer,51,Business travel,Business,1658,2,2,5,2,2,5,5,4,4,5,4,3,4,3,19,20.0,satisfied +51252,24259,Female,Loyal Customer,47,Personal Travel,Eco,302,2,4,2,3,2,5,5,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +51253,95714,Male,Loyal Customer,49,Business travel,Business,1619,2,2,2,2,3,5,5,4,4,4,5,5,4,3,2,0.0,satisfied +51254,101777,Male,Loyal Customer,12,Personal Travel,Business,1521,4,5,4,3,4,4,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +51255,33833,Male,Loyal Customer,62,Personal Travel,Business,1562,2,4,2,4,5,5,5,5,5,2,5,5,5,4,0,11.0,neutral or dissatisfied +51256,2328,Female,Loyal Customer,48,Personal Travel,Eco,691,1,4,1,5,3,5,5,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +51257,82319,Male,Loyal Customer,40,Business travel,Eco,610,2,5,5,5,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +51258,47752,Female,disloyal Customer,34,Business travel,Eco,329,3,0,3,4,3,3,3,3,1,2,5,1,3,3,0,0.0,neutral or dissatisfied +51259,62610,Female,Loyal Customer,30,Personal Travel,Eco,1723,3,4,3,4,5,3,2,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +51260,74063,Female,Loyal Customer,21,Business travel,Business,641,1,2,1,1,5,5,5,5,3,3,4,3,4,5,0,0.0,satisfied +51261,3693,Female,disloyal Customer,33,Business travel,Eco,427,1,2,1,4,4,1,4,4,1,2,3,4,3,4,0,0.0,neutral or dissatisfied +51262,20576,Female,Loyal Customer,39,Personal Travel,Eco,633,1,4,1,3,1,1,1,1,4,4,4,5,5,1,7,0.0,neutral or dissatisfied +51263,97985,Female,Loyal Customer,32,Personal Travel,Eco,616,1,4,1,3,2,1,2,2,1,2,1,4,2,2,2,4.0,neutral or dissatisfied +51264,87476,Female,Loyal Customer,40,Business travel,Business,321,2,2,2,2,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +51265,43094,Female,Loyal Customer,28,Personal Travel,Eco,192,2,5,2,4,5,2,3,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +51266,111352,Male,disloyal Customer,26,Business travel,Eco,777,2,2,2,4,2,2,2,2,2,5,4,3,4,2,0,12.0,neutral or dissatisfied +51267,31378,Male,Loyal Customer,28,Business travel,Business,895,5,5,5,5,2,2,2,2,3,5,5,4,4,2,0,0.0,satisfied +51268,83618,Female,Loyal Customer,40,Business travel,Eco,409,4,3,3,3,4,4,4,4,2,3,1,2,4,4,0,0.0,satisfied +51269,93099,Female,Loyal Customer,65,Business travel,Eco,641,1,2,2,2,4,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +51270,95806,Female,Loyal Customer,44,Business travel,Business,920,3,3,3,3,5,4,4,5,5,5,5,5,5,3,36,21.0,satisfied +51271,9018,Male,disloyal Customer,54,Business travel,Business,173,2,2,2,1,4,2,4,4,5,3,4,3,4,4,5,8.0,neutral or dissatisfied +51272,70536,Female,Loyal Customer,57,Business travel,Business,3162,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +51273,79517,Female,disloyal Customer,44,Business travel,Business,760,2,2,2,3,1,2,1,1,5,2,4,5,4,1,4,24.0,neutral or dissatisfied +51274,8410,Male,Loyal Customer,59,Business travel,Business,2726,1,1,1,1,4,5,5,3,3,3,3,5,3,4,0,4.0,satisfied +51275,94815,Female,Loyal Customer,29,Business travel,Business,2931,2,4,4,4,2,2,2,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +51276,40821,Female,Loyal Customer,33,Business travel,Business,590,3,2,2,2,5,3,3,3,3,3,3,3,3,4,0,7.0,neutral or dissatisfied +51277,35070,Female,Loyal Customer,56,Personal Travel,Business,944,0,3,1,3,1,1,1,1,1,1,5,5,1,2,0,0.0,satisfied +51278,123093,Female,Loyal Customer,21,Business travel,Business,3389,1,5,5,5,1,1,1,1,1,1,2,1,2,1,0,0.0,neutral or dissatisfied +51279,103130,Female,Loyal Customer,58,Business travel,Business,460,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +51280,14664,Male,Loyal Customer,17,Business travel,Eco Plus,162,5,5,5,5,5,5,3,5,4,5,5,5,2,5,0,0.0,satisfied +51281,86453,Male,Loyal Customer,42,Business travel,Business,3663,3,3,3,3,3,2,2,3,3,3,3,3,3,4,25,37.0,neutral or dissatisfied +51282,27141,Male,disloyal Customer,33,Business travel,Eco,1224,1,1,1,4,1,1,1,2,4,2,3,1,1,1,0,0.0,neutral or dissatisfied +51283,36694,Male,disloyal Customer,65,Personal Travel,Eco,1121,3,4,3,3,5,3,5,5,4,5,4,4,4,5,24,9.0,neutral or dissatisfied +51284,129575,Female,Loyal Customer,38,Business travel,Eco Plus,842,5,4,3,4,5,5,5,5,4,1,1,2,3,5,0,0.0,satisfied +51285,112378,Female,disloyal Customer,25,Business travel,Business,948,4,0,5,4,1,5,1,1,3,4,5,4,5,1,114,120.0,neutral or dissatisfied +51286,21010,Female,Loyal Customer,57,Business travel,Business,2013,0,4,0,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +51287,112375,Male,disloyal Customer,29,Business travel,Business,957,2,2,2,1,1,2,2,1,3,4,4,4,4,1,0,20.0,neutral or dissatisfied +51288,8643,Female,Loyal Customer,43,Business travel,Business,227,1,1,1,1,4,4,5,4,4,4,4,4,4,5,16,23.0,satisfied +51289,47754,Female,Loyal Customer,23,Business travel,Business,3614,5,5,5,5,5,5,5,5,2,1,5,3,1,5,0,0.0,satisfied +51290,117953,Male,Loyal Customer,52,Business travel,Business,365,4,4,3,4,1,4,1,5,5,4,5,5,5,5,0,0.0,satisfied +51291,49670,Male,Loyal Customer,59,Business travel,Business,2572,1,1,1,1,1,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +51292,71107,Female,Loyal Customer,47,Business travel,Business,2072,5,5,5,5,3,4,5,4,4,4,4,5,4,4,38,49.0,satisfied +51293,123849,Male,disloyal Customer,32,Business travel,Business,541,3,3,3,3,3,3,1,3,4,2,5,4,4,3,0,3.0,neutral or dissatisfied +51294,96663,Male,Loyal Customer,70,Personal Travel,Eco,937,3,3,3,3,4,3,5,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +51295,86623,Female,disloyal Customer,37,Business travel,Eco,746,2,2,2,4,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +51296,35454,Female,Loyal Customer,25,Personal Travel,Eco,1074,2,5,2,5,4,2,4,4,4,2,5,4,5,4,3,9.0,neutral or dissatisfied +51297,75884,Male,Loyal Customer,45,Business travel,Business,603,5,5,5,5,4,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +51298,129249,Female,Loyal Customer,48,Personal Travel,Eco,1235,3,5,3,1,4,5,5,2,2,3,3,4,2,3,5,0.0,neutral or dissatisfied +51299,102181,Male,Loyal Customer,44,Business travel,Business,236,0,0,0,5,4,5,4,2,2,2,2,3,2,5,30,12.0,satisfied +51300,16066,Male,disloyal Customer,36,Business travel,Eco,501,3,1,3,2,2,3,5,2,2,3,3,2,2,2,0,0.0,neutral or dissatisfied +51301,101007,Female,Loyal Customer,60,Business travel,Business,3282,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +51302,109058,Female,Loyal Customer,55,Business travel,Eco,571,2,5,5,5,5,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +51303,11081,Male,Loyal Customer,61,Personal Travel,Eco,316,2,3,2,4,2,2,2,2,2,1,3,2,4,2,0,10.0,neutral or dissatisfied +51304,11740,Male,Loyal Customer,49,Business travel,Business,429,4,2,2,2,4,3,2,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +51305,52254,Female,Loyal Customer,25,Business travel,Business,509,3,3,3,3,5,5,5,5,3,5,1,2,2,5,0,1.0,satisfied +51306,57984,Male,Loyal Customer,65,Personal Travel,Eco,589,3,2,3,4,4,3,5,4,4,3,3,2,3,4,23,34.0,neutral or dissatisfied +51307,118293,Female,Loyal Customer,31,Business travel,Business,2766,5,4,5,5,3,3,3,3,5,3,4,3,4,3,3,16.0,satisfied +51308,39917,Male,Loyal Customer,23,Personal Travel,Business,1086,4,5,4,3,5,4,5,5,3,5,5,4,5,5,32,4.0,neutral or dissatisfied +51309,93677,Female,Loyal Customer,25,Personal Travel,Eco,667,1,3,1,1,2,1,2,2,3,3,1,1,5,2,12,0.0,neutral or dissatisfied +51310,42937,Female,Loyal Customer,41,Business travel,Business,192,3,3,3,3,5,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +51311,33144,Female,Loyal Customer,43,Personal Travel,Eco,101,2,4,0,3,4,5,5,1,1,0,1,5,1,4,0,0.0,neutral or dissatisfied +51312,106497,Female,Loyal Customer,11,Business travel,Business,495,2,4,4,4,2,2,2,2,2,5,4,2,4,2,72,62.0,neutral or dissatisfied +51313,88916,Male,Loyal Customer,44,Personal Travel,Eco,859,2,4,2,5,2,2,2,2,3,4,4,5,4,2,129,114.0,neutral or dissatisfied +51314,51825,Male,Loyal Customer,50,Business travel,Eco Plus,493,4,4,4,4,4,4,4,4,5,2,4,4,1,4,0,0.0,satisfied +51315,119587,Male,Loyal Customer,48,Personal Travel,Eco,2276,2,5,2,1,2,4,4,4,2,4,4,4,3,4,0,11.0,neutral or dissatisfied +51316,26111,Male,Loyal Customer,14,Business travel,Business,2051,1,1,1,1,2,2,2,2,4,3,5,4,5,2,5,0.0,satisfied +51317,14043,Male,disloyal Customer,43,Business travel,Eco,106,2,4,2,2,5,2,5,5,2,1,2,2,5,5,0,0.0,neutral or dissatisfied +51318,104088,Female,Loyal Customer,17,Personal Travel,Eco,666,3,1,3,3,2,3,2,2,2,3,3,1,2,2,1,7.0,neutral or dissatisfied +51319,86260,Male,Loyal Customer,64,Personal Travel,Eco,356,3,5,3,3,4,3,4,4,2,5,3,3,4,4,41,21.0,neutral or dissatisfied +51320,26770,Female,Loyal Customer,38,Personal Travel,Eco Plus,859,3,5,2,1,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +51321,23964,Male,Loyal Customer,51,Business travel,Business,2623,2,5,3,5,4,3,3,2,2,1,2,4,2,2,32,27.0,neutral or dissatisfied +51322,45570,Male,disloyal Customer,23,Business travel,Business,1020,4,0,4,5,1,4,1,1,3,3,4,4,5,1,0,0.0,satisfied +51323,28252,Male,Loyal Customer,40,Business travel,Business,1542,4,4,4,4,3,4,5,4,4,4,4,4,4,3,10,0.0,satisfied +51324,6923,Male,Loyal Customer,45,Personal Travel,Eco,287,3,3,3,4,3,3,3,3,2,1,4,2,4,3,6,5.0,neutral or dissatisfied +51325,107229,Male,Loyal Customer,58,Business travel,Business,3154,2,2,2,2,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +51326,31091,Male,Loyal Customer,51,Business travel,Eco,1014,3,4,4,4,3,3,3,3,1,4,3,3,4,3,0,0.0,neutral or dissatisfied +51327,17506,Male,disloyal Customer,42,Business travel,Business,352,2,2,2,3,2,4,5,1,4,4,4,5,1,5,146,137.0,neutral or dissatisfied +51328,17972,Female,Loyal Customer,28,Business travel,Eco Plus,500,0,0,0,4,0,1,3,5,2,5,4,3,4,3,133,122.0,satisfied +51329,34259,Male,Loyal Customer,32,Personal Travel,Business,496,4,4,5,5,3,5,5,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +51330,120506,Female,Loyal Customer,47,Business travel,Eco Plus,449,4,1,1,1,3,3,3,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +51331,15885,Female,Loyal Customer,14,Personal Travel,Eco,332,2,5,2,2,5,2,5,5,5,3,3,2,3,5,0,0.0,neutral or dissatisfied +51332,77999,Male,disloyal Customer,27,Business travel,Business,214,4,4,4,2,5,4,2,5,4,4,2,1,3,5,17,14.0,neutral or dissatisfied +51333,59514,Female,Loyal Customer,42,Business travel,Business,2235,2,2,2,2,2,4,4,5,5,5,5,3,5,5,3,6.0,satisfied +51334,30251,Male,Loyal Customer,59,Business travel,Business,1024,3,3,3,3,5,4,5,5,5,5,5,4,5,3,10,4.0,satisfied +51335,106127,Male,Loyal Customer,31,Business travel,Business,2012,5,5,5,5,4,4,4,4,5,2,5,3,4,4,14,16.0,satisfied +51336,106081,Male,Loyal Customer,52,Business travel,Business,302,4,4,4,4,4,5,4,4,4,4,4,3,4,3,9,15.0,satisfied +51337,108298,Male,Loyal Customer,25,Business travel,Business,1750,1,1,1,1,5,5,5,5,5,2,3,4,4,5,0,0.0,satisfied +51338,103204,Female,disloyal Customer,30,Business travel,Business,1482,0,0,0,1,5,0,4,5,3,2,5,3,4,5,53,73.0,satisfied +51339,105889,Male,Loyal Customer,42,Business travel,Business,3225,0,0,0,4,5,4,4,5,5,5,5,4,5,4,37,40.0,satisfied +51340,45603,Female,Loyal Customer,25,Business travel,Business,230,0,0,0,3,4,4,4,4,5,2,1,5,1,4,15,73.0,satisfied +51341,17435,Female,Loyal Customer,46,Personal Travel,Eco,376,3,3,3,2,4,3,3,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +51342,121121,Male,Loyal Customer,43,Business travel,Business,2521,3,3,3,3,2,2,2,5,4,5,4,2,3,2,36,49.0,satisfied +51343,39963,Female,Loyal Customer,51,Personal Travel,Eco Plus,1195,3,4,3,5,3,4,4,3,3,3,3,4,3,4,7,0.0,neutral or dissatisfied +51344,23246,Male,Loyal Customer,61,Business travel,Eco,783,4,2,2,2,5,4,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +51345,67959,Female,disloyal Customer,27,Business travel,Business,1235,3,3,3,2,2,3,2,2,4,2,5,5,5,2,6,2.0,neutral or dissatisfied +51346,86822,Male,Loyal Customer,50,Business travel,Business,2975,2,1,2,1,5,2,3,2,2,2,2,2,2,3,23,22.0,neutral or dissatisfied +51347,75913,Male,Loyal Customer,68,Personal Travel,Eco,597,2,5,2,1,4,2,2,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +51348,44599,Female,Loyal Customer,12,Personal Travel,Business,566,3,5,3,5,2,3,2,2,3,4,4,4,5,2,0,21.0,neutral or dissatisfied +51349,7588,Male,Loyal Customer,50,Personal Travel,Eco,594,3,3,3,4,3,3,1,3,2,3,4,4,3,3,0,22.0,neutral or dissatisfied +51350,23631,Male,disloyal Customer,11,Business travel,Eco,793,4,4,4,4,3,4,3,3,4,4,4,1,4,3,6,15.0,neutral or dissatisfied +51351,41350,Male,Loyal Customer,37,Business travel,Eco Plus,964,3,4,4,4,3,3,3,3,1,3,4,2,3,3,4,17.0,neutral or dissatisfied +51352,91652,Male,Loyal Customer,31,Personal Travel,Eco,1312,2,1,2,3,5,2,5,5,1,3,2,2,3,5,16,12.0,neutral or dissatisfied +51353,30049,Female,Loyal Customer,32,Business travel,Eco,261,2,2,2,2,2,2,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +51354,35356,Male,disloyal Customer,29,Business travel,Eco,1035,1,1,1,3,1,1,1,1,4,5,4,1,4,1,77,73.0,neutral or dissatisfied +51355,107914,Female,Loyal Customer,65,Personal Travel,Eco,861,3,5,3,3,3,5,4,1,1,3,1,3,1,5,1,0.0,neutral or dissatisfied +51356,105296,Female,Loyal Customer,49,Business travel,Business,967,2,2,2,2,5,4,5,4,4,4,4,4,4,4,23,24.0,satisfied +51357,60440,Male,Loyal Customer,39,Business travel,Business,2484,4,4,4,4,5,4,4,3,3,2,3,5,3,5,1,0.0,satisfied +51358,11415,Male,disloyal Customer,26,Business travel,Business,517,4,3,3,3,5,3,5,5,4,4,5,3,4,5,0,21.0,satisfied +51359,95419,Male,Loyal Customer,58,Business travel,Business,1650,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +51360,74338,Female,Loyal Customer,15,Personal Travel,Business,1235,2,5,2,2,5,2,1,5,5,3,5,3,5,5,0,2.0,neutral or dissatisfied +51361,47458,Female,Loyal Customer,26,Personal Travel,Eco,532,2,5,2,3,5,2,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +51362,36570,Male,Loyal Customer,48,Business travel,Business,2588,3,3,3,3,3,3,3,3,2,3,3,3,2,3,167,223.0,neutral or dissatisfied +51363,93931,Male,Loyal Customer,48,Business travel,Business,3045,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +51364,110263,Male,disloyal Customer,23,Business travel,Eco,787,4,4,4,3,4,4,3,4,3,4,5,4,5,4,0,0.0,satisfied +51365,92415,Female,disloyal Customer,22,Business travel,Eco,1165,3,3,3,4,2,3,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +51366,102009,Female,Loyal Customer,55,Business travel,Business,414,3,3,3,3,3,4,4,4,4,4,4,5,4,3,3,0.0,satisfied +51367,13012,Female,disloyal Customer,35,Business travel,Eco,304,2,3,2,3,1,2,1,1,3,2,3,5,4,1,1,0.0,neutral or dissatisfied +51368,102034,Male,Loyal Customer,52,Business travel,Business,3112,1,1,1,1,5,5,4,5,5,5,5,5,5,3,29,34.0,satisfied +51369,59398,Male,Loyal Customer,52,Personal Travel,Eco,2556,2,2,2,4,2,2,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +51370,29809,Male,Loyal Customer,33,Business travel,Business,183,4,4,4,4,4,4,4,4,4,5,1,1,2,4,0,3.0,satisfied +51371,111128,Female,Loyal Customer,57,Business travel,Business,1180,3,3,3,3,5,4,4,3,3,4,3,4,3,3,18,0.0,satisfied +51372,126302,Male,Loyal Customer,37,Personal Travel,Eco,600,3,3,3,4,3,3,1,3,4,2,2,1,5,3,0,0.0,neutral or dissatisfied +51373,52754,Male,Loyal Customer,37,Business travel,Business,1874,4,4,2,4,4,4,4,4,4,4,4,3,4,4,20,4.0,satisfied +51374,59205,Female,Loyal Customer,57,Business travel,Business,1440,3,4,4,4,3,2,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +51375,49258,Female,disloyal Customer,37,Business travel,Eco,199,2,5,2,4,4,2,4,4,4,4,3,4,2,4,0,0.0,neutral or dissatisfied +51376,124519,Male,Loyal Customer,36,Business travel,Business,1276,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +51377,120331,Female,Loyal Customer,52,Business travel,Eco Plus,268,1,1,1,1,2,4,3,1,1,1,1,1,1,3,0,8.0,neutral or dissatisfied +51378,72504,Female,Loyal Customer,36,Business travel,Business,1017,1,1,3,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +51379,51317,Female,Loyal Customer,39,Business travel,Eco Plus,337,3,1,1,1,3,3,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +51380,86442,Female,Loyal Customer,54,Business travel,Eco,853,2,3,5,3,2,1,2,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +51381,129601,Female,Loyal Customer,51,Business travel,Business,337,1,1,1,1,2,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +51382,119708,Female,Loyal Customer,35,Business travel,Business,2740,2,4,4,4,4,2,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +51383,56209,Female,Loyal Customer,52,Personal Travel,Eco Plus,1400,3,1,3,4,4,4,3,4,4,3,4,3,4,1,54,50.0,neutral or dissatisfied +51384,10424,Male,Loyal Customer,55,Business travel,Business,191,4,4,5,4,2,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +51385,89492,Male,Loyal Customer,49,Business travel,Business,1931,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +51386,23370,Male,Loyal Customer,35,Business travel,Business,1014,2,1,1,1,4,3,4,2,2,2,2,2,2,3,3,15.0,neutral or dissatisfied +51387,76417,Female,disloyal Customer,44,Business travel,Eco,405,4,1,4,3,4,4,4,4,3,4,3,2,4,4,0,0.0,neutral or dissatisfied +51388,31307,Male,Loyal Customer,24,Business travel,Eco,680,5,1,1,1,5,5,3,5,3,2,3,4,1,5,10,22.0,satisfied +51389,80189,Male,Loyal Customer,41,Personal Travel,Eco,2475,1,4,1,1,1,1,1,4,5,3,5,1,4,1,0,1.0,neutral or dissatisfied +51390,94300,Male,Loyal Customer,42,Business travel,Business,2957,0,0,0,2,3,4,4,3,3,5,5,4,3,5,0,0.0,satisfied +51391,102183,Female,Loyal Customer,38,Business travel,Business,223,1,5,5,5,3,4,3,2,2,2,1,4,2,4,18,12.0,neutral or dissatisfied +51392,26092,Male,Loyal Customer,35,Business travel,Business,3045,2,2,2,2,2,4,3,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +51393,84980,Female,Loyal Customer,30,Business travel,Business,1590,2,2,2,2,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +51394,78409,Female,disloyal Customer,27,Business travel,Business,453,2,2,2,3,4,2,4,4,5,3,5,4,5,4,0,5.0,neutral or dissatisfied +51395,29052,Female,Loyal Customer,64,Personal Travel,Eco,954,4,1,4,3,3,4,4,2,2,4,2,1,2,3,0,0.0,satisfied +51396,29230,Male,Loyal Customer,27,Business travel,Business,2351,2,2,2,2,5,5,5,5,1,5,2,2,5,5,0,0.0,satisfied +51397,50151,Male,Loyal Customer,50,Business travel,Business,3256,2,5,5,5,4,4,3,0,0,1,2,4,0,3,0,0.0,neutral or dissatisfied +51398,71921,Female,Loyal Customer,53,Business travel,Business,1723,4,4,4,4,5,5,4,4,4,5,4,3,4,3,0,1.0,satisfied +51399,6878,Female,Loyal Customer,55,Business travel,Business,2950,2,2,2,2,5,2,1,2,2,2,2,4,2,2,9,3.0,neutral or dissatisfied +51400,3968,Female,Loyal Customer,30,Personal Travel,Eco,764,3,5,3,5,3,3,3,3,1,2,4,5,4,3,0,24.0,neutral or dissatisfied +51401,33813,Male,disloyal Customer,57,Business travel,Eco,750,1,1,1,2,3,1,3,3,2,4,3,1,2,3,2,8.0,neutral or dissatisfied +51402,56421,Male,disloyal Customer,22,Business travel,Business,719,5,0,5,1,2,5,2,2,5,2,4,5,4,2,12,3.0,satisfied +51403,54789,Male,disloyal Customer,24,Business travel,Eco,375,2,4,2,3,4,2,4,4,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +51404,92019,Female,disloyal Customer,23,Business travel,Eco,1005,1,1,1,3,5,1,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +51405,27874,Male,Loyal Customer,24,Business travel,Eco Plus,1448,3,2,2,2,3,3,3,3,4,5,4,2,3,3,0,8.0,neutral or dissatisfied +51406,61042,Female,Loyal Customer,35,Business travel,Business,1506,4,4,4,4,4,5,5,5,5,5,5,3,5,4,3,11.0,satisfied +51407,27327,Male,disloyal Customer,25,Business travel,Eco,679,0,0,0,3,1,0,1,1,2,2,4,3,5,1,49,38.0,satisfied +51408,51966,Female,Loyal Customer,65,Business travel,Business,347,0,0,0,1,4,1,3,4,4,4,4,4,4,2,0,0.0,satisfied +51409,53904,Female,Loyal Customer,11,Personal Travel,Eco,140,2,2,2,4,4,2,4,4,3,1,3,4,3,4,11,11.0,neutral or dissatisfied +51410,96327,Female,Loyal Customer,43,Business travel,Business,359,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +51411,54423,Female,Loyal Customer,26,Personal Travel,Eco,305,1,4,1,3,1,1,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +51412,59738,Female,Loyal Customer,51,Business travel,Business,1025,3,3,3,3,3,5,4,5,5,4,5,5,5,3,0,5.0,satisfied +51413,125975,Male,Loyal Customer,51,Business travel,Business,600,3,3,3,3,2,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +51414,99913,Male,Loyal Customer,48,Business travel,Business,1028,5,5,5,5,3,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +51415,107753,Female,Loyal Customer,30,Personal Travel,Eco,405,2,5,2,4,1,2,1,1,3,5,4,5,4,1,23,28.0,neutral or dissatisfied +51416,16265,Male,Loyal Customer,40,Business travel,Eco,631,1,5,3,5,1,1,1,3,4,3,4,1,4,1,123,134.0,neutral or dissatisfied +51417,513,Male,Loyal Customer,56,Business travel,Business,140,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +51418,16266,Male,disloyal Customer,27,Business travel,Eco,748,4,3,3,3,2,3,2,2,3,1,3,2,4,2,11,24.0,neutral or dissatisfied +51419,2290,Female,Loyal Customer,43,Business travel,Eco,630,3,1,1,1,1,3,3,3,3,3,3,3,3,3,0,4.0,neutral or dissatisfied +51420,85090,Male,Loyal Customer,51,Business travel,Business,3935,2,2,2,2,5,5,4,3,3,3,3,3,3,5,0,10.0,satisfied +51421,99309,Male,Loyal Customer,24,Business travel,Eco,337,3,3,3,3,3,3,3,3,2,4,4,4,4,3,8,2.0,neutral or dissatisfied +51422,94803,Male,Loyal Customer,46,Business travel,Business,1716,2,3,3,3,3,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +51423,16655,Female,disloyal Customer,22,Business travel,Business,488,1,1,1,3,1,1,1,1,4,4,2,1,3,1,0,0.0,neutral or dissatisfied +51424,121464,Male,Loyal Customer,37,Personal Travel,Eco,290,3,5,3,2,4,3,4,4,5,2,5,4,4,4,9,6.0,neutral or dissatisfied +51425,21159,Female,Loyal Customer,45,Personal Travel,Eco,954,1,5,1,2,5,5,5,4,4,1,3,3,4,4,88,68.0,neutral or dissatisfied +51426,51280,Male,Loyal Customer,39,Business travel,Eco Plus,262,4,1,5,1,4,4,4,4,2,4,3,4,3,4,5,8.0,neutral or dissatisfied +51427,7716,Female,Loyal Customer,40,Business travel,Business,2031,1,1,1,1,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +51428,52132,Male,disloyal Customer,24,Business travel,Eco,370,1,2,0,4,4,0,4,4,1,2,3,2,3,4,0,4.0,neutral or dissatisfied +51429,123313,Male,disloyal Customer,9,Business travel,Business,600,5,0,5,2,4,5,4,4,5,5,4,4,5,4,0,0.0,satisfied +51430,10228,Male,Loyal Customer,41,Business travel,Business,3341,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,1.0,satisfied +51431,29760,Female,Loyal Customer,53,Business travel,Business,3058,3,3,3,3,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +51432,86256,Male,Loyal Customer,25,Personal Travel,Eco,377,2,4,2,3,4,2,4,4,4,3,5,3,5,4,51,46.0,neutral or dissatisfied +51433,9073,Male,disloyal Customer,22,Business travel,Eco,108,3,3,3,3,4,3,4,4,3,2,3,4,4,4,0,0.0,neutral or dissatisfied +51434,52064,Male,Loyal Customer,42,Business travel,Eco,639,4,3,3,3,4,4,4,4,2,1,5,2,1,4,0,0.0,satisfied +51435,123615,Male,Loyal Customer,45,Personal Travel,Eco Plus,1773,1,5,1,1,1,1,1,1,5,4,3,4,4,1,0,0.0,neutral or dissatisfied +51436,98919,Male,Loyal Customer,42,Business travel,Business,543,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +51437,118304,Male,Loyal Customer,45,Business travel,Business,602,1,1,2,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +51438,77651,Male,Loyal Customer,53,Business travel,Business,731,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +51439,52044,Male,Loyal Customer,28,Personal Travel,Eco,1037,4,2,4,2,4,4,4,4,3,3,2,2,2,4,0,0.0,neutral or dissatisfied +51440,20645,Male,Loyal Customer,40,Business travel,Business,3229,2,5,5,5,2,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +51441,36639,Female,Loyal Customer,29,Personal Travel,Eco,1010,2,4,2,3,2,2,1,2,4,2,5,4,1,2,0,0.0,neutral or dissatisfied +51442,83088,Male,disloyal Customer,38,Business travel,Eco,583,2,0,2,4,2,2,2,2,5,4,1,4,5,2,0,2.0,neutral or dissatisfied +51443,43340,Female,Loyal Customer,27,Business travel,Eco,402,1,5,2,2,1,1,1,1,4,2,3,4,4,1,0,0.0,neutral or dissatisfied +51444,102486,Male,Loyal Customer,18,Personal Travel,Eco,386,2,4,2,1,3,2,3,3,4,5,2,2,2,3,91,84.0,neutral or dissatisfied +51445,6558,Male,Loyal Customer,56,Business travel,Business,3255,3,3,3,3,2,4,4,5,5,5,5,5,5,4,22,15.0,satisfied +51446,71334,Male,Loyal Customer,19,Personal Travel,Eco,1514,4,4,4,5,3,4,3,3,4,3,5,4,4,3,7,0.0,satisfied +51447,111006,Female,Loyal Customer,47,Business travel,Business,197,1,1,1,1,2,5,4,3,3,4,4,3,3,4,7,19.0,satisfied +51448,98331,Male,Loyal Customer,54,Business travel,Business,3604,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +51449,114062,Male,Loyal Customer,51,Business travel,Eco,1892,3,4,4,4,3,3,3,3,1,3,3,2,3,3,2,0.0,neutral or dissatisfied +51450,79944,Male,Loyal Customer,19,Business travel,Eco,950,4,1,1,1,4,4,3,4,4,4,3,1,3,4,65,53.0,neutral or dissatisfied +51451,20788,Female,Loyal Customer,39,Business travel,Business,2164,5,2,5,5,2,3,1,5,5,5,5,4,5,3,0,0.0,satisfied +51452,125560,Female,disloyal Customer,30,Business travel,Eco,226,2,1,2,3,3,2,3,3,2,5,3,4,4,3,0,10.0,neutral or dissatisfied +51453,71496,Female,Loyal Customer,57,Personal Travel,Business,1197,4,5,4,1,2,5,4,5,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +51454,28617,Female,Loyal Customer,47,Business travel,Business,2466,3,3,3,3,5,5,3,5,5,5,5,2,5,2,1,0.0,satisfied +51455,29017,Male,Loyal Customer,33,Business travel,Business,3749,2,4,4,4,2,2,2,2,3,5,1,1,2,2,29,23.0,neutral or dissatisfied +51456,104147,Female,disloyal Customer,26,Business travel,Business,349,2,0,2,4,1,2,1,1,3,2,4,5,5,1,84,70.0,neutral or dissatisfied +51457,28865,Female,Loyal Customer,38,Business travel,Business,3776,4,4,4,4,3,5,3,2,2,2,2,2,2,4,0,0.0,satisfied +51458,70789,Female,Loyal Customer,56,Business travel,Business,2212,1,1,1,1,1,2,2,1,1,1,1,2,1,2,33,49.0,neutral or dissatisfied +51459,56662,Female,Loyal Customer,22,Business travel,Business,2753,3,3,3,3,4,4,4,4,2,3,5,1,1,4,0,2.0,satisfied +51460,108228,Male,Loyal Customer,40,Business travel,Business,895,3,3,3,3,5,5,5,4,4,4,4,3,4,3,20,0.0,satisfied +51461,19167,Male,Loyal Customer,59,Business travel,Eco Plus,304,4,3,3,3,4,4,4,4,1,5,2,5,1,4,0,0.0,satisfied +51462,48725,Male,Loyal Customer,53,Business travel,Business,1924,2,2,2,2,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +51463,102801,Female,Loyal Customer,45,Business travel,Business,2455,2,2,2,2,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +51464,23073,Male,disloyal Customer,60,Business travel,Eco,1211,4,4,4,3,1,4,1,1,2,5,1,5,4,1,5,0.0,neutral or dissatisfied +51465,1990,Male,Loyal Customer,56,Personal Travel,Eco,295,1,5,5,3,3,5,4,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +51466,126034,Male,disloyal Customer,24,Business travel,Eco,650,2,5,2,2,3,2,2,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +51467,47096,Male,Loyal Customer,43,Personal Travel,Eco,351,3,5,3,2,4,3,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +51468,126826,Male,disloyal Customer,40,Business travel,Eco,1189,3,2,2,3,3,3,2,3,2,3,1,4,3,3,0,0.0,neutral or dissatisfied +51469,114704,Female,Loyal Customer,55,Business travel,Business,3586,4,4,5,4,4,4,5,4,4,4,4,5,4,3,0,6.0,satisfied +51470,32294,Female,disloyal Customer,38,Business travel,Eco,101,3,0,2,5,4,2,4,4,4,1,2,2,2,4,0,0.0,neutral or dissatisfied +51471,12317,Male,Loyal Customer,45,Business travel,Eco,192,5,4,4,4,5,5,5,5,5,3,5,4,3,5,39,45.0,satisfied +51472,52362,Male,Loyal Customer,66,Personal Travel,Eco,493,2,4,2,2,1,2,1,1,4,3,5,5,5,1,120,116.0,neutral or dissatisfied +51473,100093,Female,Loyal Customer,33,Business travel,Business,2674,2,1,3,1,3,3,4,2,2,2,2,3,2,1,52,54.0,neutral or dissatisfied +51474,108346,Female,Loyal Customer,23,Business travel,Business,1750,1,1,1,1,5,5,5,5,3,2,3,3,5,5,0,0.0,satisfied +51475,4801,Male,Loyal Customer,9,Personal Travel,Eco,315,1,4,1,1,3,1,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +51476,1338,Female,Loyal Customer,43,Business travel,Business,134,1,1,1,1,5,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +51477,73345,Female,Loyal Customer,48,Business travel,Business,1182,4,4,4,4,3,4,5,5,5,5,5,4,5,3,14,10.0,satisfied +51478,96104,Female,Loyal Customer,11,Personal Travel,Eco,1235,4,2,4,4,3,4,3,3,2,5,3,3,3,3,2,19.0,neutral or dissatisfied +51479,125524,Female,Loyal Customer,46,Business travel,Business,226,0,0,0,2,3,5,5,5,5,5,5,3,5,5,36,33.0,satisfied +51480,65673,Female,disloyal Customer,27,Business travel,Eco,861,2,2,2,4,2,2,2,2,2,4,4,1,4,2,2,0.0,neutral or dissatisfied +51481,6581,Female,Loyal Customer,49,Business travel,Business,207,3,4,4,4,1,3,4,3,3,3,3,4,3,2,50,42.0,neutral or dissatisfied +51482,33483,Male,Loyal Customer,67,Personal Travel,Eco,2422,3,5,3,3,1,3,1,1,5,4,5,5,4,1,44,52.0,neutral or dissatisfied +51483,72728,Male,Loyal Customer,50,Business travel,Eco Plus,518,5,4,4,4,5,5,5,5,2,4,4,2,2,5,0,1.0,satisfied +51484,29593,Female,disloyal Customer,28,Business travel,Eco,1448,3,3,3,4,5,3,5,5,4,3,4,4,3,5,0,0.0,neutral or dissatisfied +51485,103694,Female,disloyal Customer,44,Business travel,Eco,405,1,1,1,3,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +51486,89205,Male,Loyal Customer,17,Personal Travel,Eco,2139,4,5,3,4,3,3,3,3,4,4,3,5,4,3,11,0.0,neutral or dissatisfied +51487,35021,Female,Loyal Customer,37,Personal Travel,Eco,740,4,5,4,5,3,4,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +51488,9628,Female,Loyal Customer,52,Personal Travel,Eco Plus,283,2,4,2,4,4,4,3,1,1,2,1,2,1,2,48,48.0,neutral or dissatisfied +51489,104137,Female,Loyal Customer,42,Personal Travel,Eco,393,3,5,3,2,4,5,4,3,3,3,5,5,3,4,0,0.0,neutral or dissatisfied +51490,123243,Female,Loyal Customer,32,Personal Travel,Eco,590,2,4,1,4,5,1,5,5,5,4,4,3,4,5,0,3.0,neutral or dissatisfied +51491,122581,Male,Loyal Customer,46,Business travel,Business,3726,2,4,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +51492,110987,Male,Loyal Customer,40,Business travel,Business,3441,4,4,4,4,4,5,5,4,4,4,4,3,4,3,4,9.0,satisfied +51493,118867,Male,Loyal Customer,44,Personal Travel,Eco Plus,304,2,1,2,3,2,2,2,2,1,2,4,1,3,2,15,0.0,neutral or dissatisfied +51494,13477,Male,Loyal Customer,49,Personal Travel,Eco Plus,409,2,5,2,1,4,2,4,4,4,1,2,2,5,4,0,0.0,neutral or dissatisfied +51495,96034,Male,Loyal Customer,54,Business travel,Business,583,3,3,3,3,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +51496,127303,Male,Loyal Customer,35,Business travel,Business,1979,2,2,2,2,2,3,5,5,5,4,5,4,5,4,0,0.0,satisfied +51497,61826,Male,Loyal Customer,67,Personal Travel,Eco,1635,2,5,2,1,3,2,3,3,4,3,5,5,4,3,11,0.0,neutral or dissatisfied +51498,11147,Female,Loyal Customer,64,Personal Travel,Eco,163,2,5,2,5,2,5,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +51499,7668,Female,disloyal Customer,25,Business travel,Business,641,2,0,2,3,4,2,4,4,3,4,5,4,4,4,0,4.0,neutral or dissatisfied +51500,41431,Male,Loyal Customer,23,Personal Travel,Eco,809,3,2,3,3,3,4,4,2,2,3,3,4,4,4,152,164.0,neutral or dissatisfied +51501,52488,Female,Loyal Customer,15,Personal Travel,Eco Plus,651,1,0,1,4,2,1,2,2,4,5,4,3,4,2,3,0.0,neutral or dissatisfied +51502,59588,Female,Loyal Customer,52,Business travel,Business,1889,4,4,4,4,2,4,4,5,5,5,5,5,5,5,7,10.0,satisfied +51503,21203,Female,Loyal Customer,24,Business travel,Business,2050,5,5,5,5,4,4,3,4,3,4,1,4,5,4,0,0.0,satisfied +51504,16974,Male,Loyal Customer,33,Business travel,Eco,209,4,4,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +51505,78934,Female,Loyal Customer,54,Business travel,Eco,100,5,1,1,1,3,2,3,5,5,5,5,3,5,3,0,0.0,satisfied +51506,38055,Male,Loyal Customer,53,Business travel,Eco,1185,5,4,4,4,5,5,5,5,2,4,5,4,1,5,92,76.0,satisfied +51507,101398,Female,Loyal Customer,22,Business travel,Eco,486,3,1,3,1,3,3,2,3,3,3,2,4,3,3,0,1.0,neutral or dissatisfied +51508,40312,Female,Loyal Customer,52,Personal Travel,Eco,347,3,4,3,3,4,4,4,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +51509,39815,Female,disloyal Customer,22,Business travel,Eco,272,2,0,2,1,3,2,3,3,4,1,4,3,3,3,23,17.0,neutral or dissatisfied +51510,97602,Male,disloyal Customer,34,Business travel,Business,442,3,2,2,4,2,2,2,2,5,3,4,4,4,2,39,31.0,neutral or dissatisfied +51511,68837,Female,Loyal Customer,59,Personal Travel,Business,1061,2,1,2,2,4,3,2,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +51512,4397,Male,Loyal Customer,39,Personal Travel,Eco,618,4,5,4,2,2,4,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +51513,59500,Male,Loyal Customer,47,Personal Travel,Eco,758,4,4,4,3,4,4,4,4,3,3,5,4,5,4,35,23.0,neutral or dissatisfied +51514,127053,Male,Loyal Customer,30,Business travel,Business,647,1,3,3,3,1,1,1,1,4,5,3,4,3,1,6,9.0,neutral or dissatisfied +51515,21154,Male,disloyal Customer,24,Business travel,Eco,954,3,3,3,3,5,3,5,5,1,2,3,4,2,5,0,0.0,neutral or dissatisfied +51516,19240,Male,Loyal Customer,9,Business travel,Business,3963,3,1,1,1,3,3,3,4,2,4,3,3,2,3,215,216.0,neutral or dissatisfied +51517,87985,Female,Loyal Customer,55,Business travel,Business,3138,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +51518,96928,Male,Loyal Customer,44,Personal Travel,Eco Plus,1041,3,4,3,1,3,3,3,3,3,4,5,4,4,3,3,0.0,neutral or dissatisfied +51519,95393,Female,Loyal Customer,9,Personal Travel,Eco,148,3,5,3,3,5,3,5,5,5,5,4,4,4,5,16,5.0,neutral or dissatisfied +51520,101055,Female,Loyal Customer,53,Business travel,Business,2724,4,4,4,4,4,4,4,5,5,5,5,4,5,3,24,19.0,satisfied +51521,25905,Female,Loyal Customer,38,Business travel,Eco Plus,907,5,1,1,1,5,5,5,5,3,1,1,3,3,5,4,4.0,satisfied +51522,123388,Female,disloyal Customer,25,Business travel,Business,1337,1,1,1,3,2,1,2,2,3,3,3,1,2,2,4,19.0,neutral or dissatisfied +51523,21293,Male,Loyal Customer,54,Business travel,Business,692,2,2,2,2,1,4,3,2,2,2,2,2,2,2,21,11.0,neutral or dissatisfied +51524,47386,Male,disloyal Customer,72,Business travel,Eco,501,2,3,2,3,5,2,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +51525,111827,Male,Loyal Customer,43,Business travel,Business,1605,1,1,1,1,4,3,3,3,2,4,5,3,5,3,181,160.0,satisfied +51526,2622,Male,Loyal Customer,54,Business travel,Business,1974,5,5,5,5,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +51527,11706,Female,Loyal Customer,44,Business travel,Business,429,3,3,3,3,3,4,5,4,4,4,4,5,4,5,25,29.0,satisfied +51528,75927,Female,Loyal Customer,50,Business travel,Business,3474,4,4,4,4,2,5,5,3,3,4,5,4,3,4,0,0.0,satisfied +51529,77768,Female,Loyal Customer,20,Personal Travel,Eco,689,1,5,1,3,5,1,5,5,2,4,4,3,4,5,0,0.0,neutral or dissatisfied +51530,35585,Female,Loyal Customer,61,Business travel,Eco Plus,1097,4,4,4,4,2,5,3,4,4,4,4,5,4,2,18,28.0,satisfied +51531,42640,Female,Loyal Customer,37,Personal Travel,Eco,481,3,4,3,3,1,3,1,1,5,4,3,4,1,1,0,0.0,neutral or dissatisfied +51532,9998,Male,Loyal Customer,20,Personal Travel,Eco,508,2,4,3,2,5,3,5,5,2,2,3,2,3,5,2,0.0,neutral or dissatisfied +51533,33793,Male,Loyal Customer,60,Business travel,Business,1521,5,5,5,5,2,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +51534,68204,Female,Loyal Customer,18,Personal Travel,Business,432,2,4,2,5,2,2,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +51535,51405,Male,Loyal Customer,49,Personal Travel,Eco Plus,110,4,5,4,1,5,4,5,5,5,1,1,5,2,5,0,0.0,neutral or dissatisfied +51536,20365,Male,Loyal Customer,38,Personal Travel,Eco,287,4,4,4,2,4,4,4,4,4,5,5,5,5,4,11,0.0,satisfied +51537,103789,Female,disloyal Customer,38,Business travel,Business,1056,2,2,2,3,1,2,2,1,4,4,5,3,5,1,33,33.0,neutral or dissatisfied +51538,62874,Female,Loyal Customer,29,Personal Travel,Eco,2583,3,4,3,5,1,3,4,1,1,4,3,2,5,1,3,0.0,neutral or dissatisfied +51539,110478,Male,Loyal Customer,10,Personal Travel,Eco,842,4,1,4,3,1,4,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +51540,102076,Male,Loyal Customer,51,Business travel,Business,2374,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +51541,71075,Male,Loyal Customer,29,Personal Travel,Eco,802,1,3,1,4,1,1,1,1,3,4,4,3,4,1,7,21.0,neutral or dissatisfied +51542,18387,Female,Loyal Customer,19,Personal Travel,Eco,493,3,5,3,4,2,3,2,2,3,5,5,4,4,2,6,0.0,neutral or dissatisfied +51543,16442,Female,Loyal Customer,63,Business travel,Business,3767,2,3,3,3,1,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +51544,23355,Female,Loyal Customer,42,Personal Travel,Eco Plus,862,1,5,1,2,2,4,4,4,4,1,4,3,4,5,12,0.0,neutral or dissatisfied +51545,55273,Male,Loyal Customer,66,Business travel,Eco Plus,507,3,5,5,5,3,3,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +51546,31036,Male,Loyal Customer,35,Business travel,Eco,775,4,2,3,3,4,4,4,4,5,4,3,5,5,4,0,0.0,satisfied +51547,56980,Female,Loyal Customer,8,Personal Travel,Eco,2565,2,1,2,2,2,5,5,4,3,2,2,5,4,5,100,134.0,neutral or dissatisfied +51548,75867,Male,disloyal Customer,20,Business travel,Business,1972,5,0,5,3,3,5,3,3,5,2,4,3,5,3,0,0.0,satisfied +51549,16878,Male,Loyal Customer,47,Business travel,Eco,746,4,5,5,5,4,4,4,4,3,2,1,1,1,4,0,0.0,satisfied +51550,66821,Female,Loyal Customer,25,Business travel,Business,731,3,3,3,3,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +51551,38828,Female,Loyal Customer,47,Personal Travel,Eco,353,1,5,4,4,4,5,4,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +51552,67273,Female,Loyal Customer,64,Personal Travel,Eco,1119,4,5,3,1,2,5,4,4,4,3,4,4,4,4,0,1.0,neutral or dissatisfied +51553,118649,Female,Loyal Customer,34,Business travel,Business,1657,3,3,3,3,4,5,5,4,4,4,4,4,4,5,7,7.0,satisfied +51554,37559,Female,disloyal Customer,22,Business travel,Eco,1069,2,3,3,3,4,3,4,4,3,3,2,4,3,4,9,0.0,satisfied +51555,40300,Male,Loyal Customer,37,Personal Travel,Eco,402,4,5,4,3,3,4,3,3,5,4,5,4,4,3,0,1.0,neutral or dissatisfied +51556,14596,Male,Loyal Customer,9,Personal Travel,Eco,986,3,5,3,5,5,3,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +51557,116991,Female,Loyal Customer,49,Business travel,Business,2843,1,1,1,1,4,4,5,4,4,4,4,5,4,4,58,35.0,satisfied +51558,125892,Male,Loyal Customer,57,Personal Travel,Eco,861,2,4,2,3,2,2,2,2,4,2,5,4,4,2,5,0.0,neutral or dissatisfied +51559,65686,Female,Loyal Customer,53,Business travel,Business,3083,2,2,2,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +51560,5697,Female,disloyal Customer,39,Business travel,Eco,299,3,3,3,3,2,3,2,2,2,1,4,3,4,2,0,0.0,neutral or dissatisfied +51561,47205,Female,Loyal Customer,27,Personal Travel,Eco,965,3,1,3,3,3,3,1,3,3,3,2,3,3,3,0,1.0,neutral or dissatisfied +51562,42923,Female,Loyal Customer,57,Personal Travel,Eco,628,3,4,3,1,3,4,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +51563,118203,Male,Loyal Customer,32,Personal Travel,Eco,1444,3,4,3,3,1,3,1,1,4,4,3,2,3,1,19,3.0,neutral or dissatisfied +51564,64732,Female,disloyal Customer,22,Business travel,Eco,224,0,0,0,4,4,0,4,4,4,4,5,5,5,4,0,1.0,satisfied +51565,25044,Male,Loyal Customer,64,Personal Travel,Eco,1306,2,4,2,3,5,2,5,5,3,3,4,3,5,5,3,0.0,neutral or dissatisfied +51566,116509,Male,Loyal Customer,63,Personal Travel,Eco,308,2,4,3,2,5,3,5,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +51567,95191,Female,Loyal Customer,9,Personal Travel,Eco,192,2,5,2,3,3,2,3,3,4,4,5,3,4,3,10,16.0,neutral or dissatisfied +51568,62489,Male,Loyal Customer,40,Business travel,Business,1846,2,2,2,2,5,4,4,5,5,5,5,3,5,5,19,7.0,satisfied +51569,122776,Female,Loyal Customer,39,Business travel,Business,3868,3,4,4,4,4,4,3,3,3,2,3,3,3,2,4,0.0,neutral or dissatisfied +51570,123393,Male,Loyal Customer,42,Business travel,Eco,1337,1,4,4,4,2,1,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +51571,63586,Male,Loyal Customer,36,Business travel,Business,2133,3,1,1,1,1,1,2,3,3,3,3,2,3,1,68,57.0,neutral or dissatisfied +51572,80359,Female,disloyal Customer,42,Business travel,Business,422,2,2,2,1,3,2,3,3,5,4,4,4,5,3,0,0.0,satisfied +51573,120650,Male,disloyal Customer,49,Business travel,Business,280,3,3,3,4,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +51574,68115,Male,Loyal Customer,24,Personal Travel,Eco,868,3,5,3,3,4,3,4,4,5,5,4,3,4,4,48,41.0,neutral or dissatisfied +51575,74705,Male,Loyal Customer,37,Personal Travel,Eco,1242,3,4,3,1,5,3,2,5,5,4,3,5,4,5,0,0.0,neutral or dissatisfied +51576,94157,Male,Loyal Customer,56,Business travel,Business,562,4,4,4,4,4,5,4,5,5,5,5,4,5,5,24,20.0,satisfied +51577,100129,Male,disloyal Customer,26,Business travel,Business,468,1,1,1,4,5,1,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +51578,85994,Female,Loyal Customer,57,Business travel,Business,2492,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +51579,14524,Female,Loyal Customer,69,Business travel,Eco,362,2,3,3,3,2,3,3,2,2,2,2,3,2,2,9,32.0,neutral or dissatisfied +51580,9206,Female,Loyal Customer,31,Business travel,Business,3580,4,4,4,4,4,4,5,4,5,2,4,4,5,4,1,5.0,satisfied +51581,79189,Female,Loyal Customer,60,Business travel,Business,1990,2,2,2,2,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +51582,92369,Female,Loyal Customer,20,Business travel,Business,2116,1,3,3,3,1,1,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +51583,129187,Male,Loyal Customer,41,Business travel,Business,2419,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +51584,119014,Male,Loyal Customer,80,Business travel,Eco Plus,459,4,3,3,3,4,4,4,2,4,4,3,4,2,4,208,204.0,neutral or dissatisfied +51585,36750,Male,Loyal Customer,31,Business travel,Eco,2704,0,0,0,4,4,4,4,1,5,5,5,4,4,4,0,14.0,satisfied +51586,6851,Male,Loyal Customer,53,Business travel,Business,622,1,1,1,1,4,4,4,4,4,4,4,3,4,5,21,117.0,satisfied +51587,104617,Female,disloyal Customer,24,Business travel,Eco,861,1,2,2,2,3,2,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +51588,39515,Male,Loyal Customer,26,Business travel,Business,3454,3,5,5,5,3,3,3,3,1,4,2,1,3,3,108,92.0,neutral or dissatisfied +51589,120479,Male,Loyal Customer,55,Personal Travel,Eco,366,2,5,2,3,5,2,5,5,4,3,4,3,4,5,0,5.0,neutral or dissatisfied +51590,128184,Female,Loyal Customer,11,Personal Travel,Eco,1849,2,2,1,1,2,1,2,2,2,2,1,3,2,2,0,0.0,neutral or dissatisfied +51591,8296,Female,Loyal Customer,54,Business travel,Business,335,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +51592,91415,Male,disloyal Customer,50,Business travel,Eco,1050,4,4,4,3,3,4,3,3,1,4,4,1,4,3,1,7.0,neutral or dissatisfied +51593,12549,Male,Loyal Customer,16,Personal Travel,Eco,788,5,5,5,3,3,5,3,3,5,2,4,3,4,3,0,0.0,satisfied +51594,57873,Male,disloyal Customer,20,Business travel,Business,305,2,2,2,3,4,2,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +51595,104511,Female,Loyal Customer,28,Business travel,Business,1609,1,1,1,1,4,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +51596,72088,Female,Loyal Customer,25,Personal Travel,Eco,2486,4,4,4,1,1,4,1,1,2,2,4,2,4,1,0,0.0,satisfied +51597,39868,Female,disloyal Customer,37,Business travel,Eco,221,2,1,2,4,3,2,3,3,2,1,3,4,4,3,0,6.0,neutral or dissatisfied +51598,120226,Female,disloyal Customer,50,Business travel,Eco,903,3,3,3,1,5,3,5,5,1,1,4,3,2,5,0,0.0,neutral or dissatisfied +51599,73287,Male,Loyal Customer,51,Business travel,Business,1182,2,2,2,2,2,5,4,2,2,2,2,4,2,4,24,27.0,satisfied +51600,7736,Male,Loyal Customer,51,Business travel,Business,2617,2,2,2,2,4,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +51601,113977,Male,disloyal Customer,37,Business travel,Business,1838,2,2,2,1,3,2,3,3,5,3,4,4,5,3,4,2.0,neutral or dissatisfied +51602,114273,Female,disloyal Customer,34,Business travel,Eco,967,3,3,3,3,2,3,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +51603,28341,Male,disloyal Customer,21,Business travel,Eco,867,5,5,5,4,5,5,5,5,3,5,5,4,2,5,0,0.0,satisfied +51604,34496,Male,Loyal Customer,45,Personal Travel,Eco,1990,3,3,4,3,5,4,5,5,5,1,3,2,1,5,7,77.0,neutral or dissatisfied +51605,8165,Female,Loyal Customer,60,Business travel,Business,125,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +51606,34182,Male,Loyal Customer,47,Business travel,Eco,646,5,2,2,2,3,5,3,3,5,4,4,4,1,3,0,0.0,satisfied +51607,47802,Female,disloyal Customer,37,Business travel,Eco,834,3,3,3,1,5,3,5,5,4,2,3,1,2,5,4,0.0,neutral or dissatisfied +51608,102694,Female,Loyal Customer,73,Business travel,Business,3909,2,3,3,3,5,2,3,2,2,2,2,3,2,2,72,74.0,neutral or dissatisfied +51609,112866,Male,Loyal Customer,31,Business travel,Business,1497,4,4,4,4,4,4,4,4,5,2,5,5,4,4,0,0.0,satisfied +51610,48624,Female,Loyal Customer,51,Personal Travel,Eco Plus,819,3,3,3,5,4,3,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +51611,26460,Male,Loyal Customer,36,Business travel,Eco,387,5,1,1,1,5,5,5,5,3,5,2,2,4,5,0,0.0,satisfied +51612,84295,Male,Loyal Customer,40,Business travel,Business,235,0,0,0,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +51613,110740,Male,Loyal Customer,60,Business travel,Business,1503,2,4,2,2,2,4,4,4,4,5,4,3,4,3,0,25.0,satisfied +51614,86176,Male,Loyal Customer,61,Business travel,Business,226,3,3,3,3,4,4,4,5,5,5,5,5,5,3,14,8.0,satisfied +51615,63750,Male,Loyal Customer,44,Personal Travel,Eco,1660,2,2,2,4,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +51616,6562,Female,Loyal Customer,59,Business travel,Business,3795,1,1,3,1,3,4,4,4,4,4,4,5,4,3,9,0.0,satisfied +51617,95704,Female,Loyal Customer,45,Business travel,Business,3238,3,3,2,3,5,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +51618,127175,Female,Loyal Customer,16,Personal Travel,Eco,646,4,3,4,1,5,4,5,5,4,1,5,3,5,5,0,0.0,neutral or dissatisfied +51619,77754,Female,disloyal Customer,24,Business travel,Eco,413,5,4,5,2,3,5,3,3,1,4,1,4,1,3,0,0.0,satisfied +51620,30406,Female,Loyal Customer,30,Personal Travel,Eco,862,3,4,3,5,5,3,4,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +51621,103116,Male,Loyal Customer,25,Personal Travel,Eco,460,1,4,1,1,2,1,4,2,3,3,4,1,2,2,74,69.0,neutral or dissatisfied +51622,8651,Female,Loyal Customer,40,Business travel,Business,2758,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +51623,45335,Female,Loyal Customer,39,Business travel,Business,175,1,2,2,2,5,3,4,1,1,1,1,2,1,1,0,3.0,neutral or dissatisfied +51624,9938,Male,Loyal Customer,49,Business travel,Business,3783,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +51625,81484,Female,disloyal Customer,37,Business travel,Eco,128,1,0,1,4,2,1,4,2,4,4,1,5,4,2,0,0.0,neutral or dissatisfied +51626,69264,Female,Loyal Customer,21,Personal Travel,Eco,733,2,4,2,3,2,5,5,3,3,1,5,5,4,5,288,277.0,neutral or dissatisfied +51627,35376,Male,disloyal Customer,39,Business travel,Eco,828,4,4,4,3,5,4,5,5,5,5,5,4,2,5,0,0.0,neutral or dissatisfied +51628,69211,Female,disloyal Customer,29,Business travel,Business,733,4,4,4,4,5,4,2,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +51629,29167,Female,Loyal Customer,23,Business travel,Eco Plus,605,5,2,2,2,5,5,4,5,2,1,5,4,4,5,0,1.0,satisfied +51630,71249,Male,Loyal Customer,55,Business travel,Eco,733,1,4,4,4,2,1,2,2,3,3,3,4,3,2,16,6.0,neutral or dissatisfied +51631,33827,Male,Loyal Customer,23,Personal Travel,Eco Plus,1428,2,5,2,5,4,2,5,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +51632,45346,Female,Loyal Customer,24,Personal Travel,Eco,188,3,4,3,1,3,3,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +51633,6565,Female,Loyal Customer,42,Business travel,Business,2280,5,5,5,5,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +51634,5931,Male,Loyal Customer,65,Personal Travel,Eco,173,3,3,3,2,5,3,5,5,4,5,4,5,5,5,33,37.0,neutral or dissatisfied +51635,6485,Male,Loyal Customer,38,Business travel,Eco,557,2,2,2,2,2,2,2,2,2,4,4,3,3,2,0,24.0,neutral or dissatisfied +51636,77646,Female,Loyal Customer,53,Business travel,Business,2131,2,4,2,2,5,5,4,5,5,5,5,4,5,5,48,49.0,satisfied +51637,16354,Female,Loyal Customer,12,Personal Travel,Eco,160,2,4,0,1,3,0,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +51638,23937,Male,Loyal Customer,44,Business travel,Eco,771,3,2,2,2,3,3,3,3,2,4,3,5,2,3,74,84.0,satisfied +51639,26937,Male,Loyal Customer,39,Business travel,Business,2378,4,4,4,4,4,4,3,4,4,5,4,5,4,3,0,0.0,satisfied +51640,99870,Female,Loyal Customer,31,Business travel,Eco Plus,587,4,2,2,2,4,3,4,4,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +51641,71450,Female,Loyal Customer,50,Business travel,Business,3683,1,2,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +51642,72615,Female,Loyal Customer,44,Personal Travel,Eco,1119,1,1,1,3,4,3,4,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +51643,20712,Female,Loyal Customer,35,Business travel,Eco,765,4,1,2,1,4,4,4,4,5,2,2,1,1,4,8,5.0,satisfied +51644,59943,Male,disloyal Customer,14,Business travel,Eco,1085,3,2,2,1,1,2,1,1,5,3,5,3,4,1,12,0.0,neutral or dissatisfied +51645,83656,Male,Loyal Customer,47,Business travel,Business,3359,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +51646,32977,Female,Loyal Customer,26,Personal Travel,Eco,102,4,5,4,4,1,4,1,1,5,5,5,5,4,1,8,6.0,neutral or dissatisfied +51647,56897,Female,Loyal Customer,60,Business travel,Business,2454,1,1,1,1,4,4,4,5,4,3,4,4,4,4,47,35.0,satisfied +51648,87464,Male,Loyal Customer,53,Business travel,Business,2918,2,2,2,2,3,4,4,5,5,5,5,5,5,5,0,9.0,satisfied +51649,71652,Female,Loyal Customer,55,Personal Travel,Eco,1197,3,1,3,3,5,2,4,3,3,3,3,1,3,2,16,14.0,neutral or dissatisfied +51650,92370,Male,Loyal Customer,51,Business travel,Business,1892,2,2,2,2,5,3,5,3,3,3,3,3,3,4,0,0.0,satisfied +51651,126142,Male,disloyal Customer,27,Business travel,Business,590,2,2,2,2,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +51652,123804,Female,Loyal Customer,22,Business travel,Business,544,5,5,2,5,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +51653,78092,Male,Loyal Customer,21,Business travel,Business,684,3,3,3,3,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +51654,94172,Female,Loyal Customer,48,Business travel,Business,562,3,3,3,3,5,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +51655,57236,Male,Loyal Customer,43,Business travel,Business,3404,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,2.0,satisfied +51656,23595,Female,Loyal Customer,32,Personal Travel,Eco Plus,1024,1,5,1,4,1,5,5,4,4,5,5,5,3,5,240,227.0,neutral or dissatisfied +51657,3521,Male,Loyal Customer,21,Business travel,Business,3924,3,3,3,3,5,5,5,5,4,4,5,3,5,5,1,0.0,satisfied +51658,99015,Male,Loyal Customer,55,Personal Travel,Eco Plus,479,3,2,3,4,4,3,4,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +51659,84912,Female,Loyal Customer,18,Personal Travel,Eco,534,3,4,3,1,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +51660,12541,Male,Loyal Customer,43,Business travel,Business,3301,4,3,1,3,2,3,4,4,4,4,4,2,4,3,6,4.0,neutral or dissatisfied +51661,72039,Female,Loyal Customer,41,Business travel,Business,3784,2,2,2,2,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +51662,74018,Female,Loyal Customer,40,Business travel,Business,1471,1,1,1,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +51663,60323,Female,Loyal Customer,17,Business travel,Business,1024,2,2,2,2,5,5,5,5,3,4,5,4,5,5,0,12.0,satisfied +51664,5259,Female,Loyal Customer,42,Business travel,Eco,295,4,1,1,1,3,3,4,5,5,4,5,1,5,2,17,19.0,neutral or dissatisfied +51665,31290,Male,Loyal Customer,33,Business travel,Eco Plus,533,1,4,4,4,1,2,1,1,2,2,4,2,3,1,7,1.0,neutral or dissatisfied +51666,30376,Female,Loyal Customer,28,Business travel,Business,2212,4,4,2,4,3,5,3,3,5,3,4,3,3,3,96,98.0,satisfied +51667,7775,Female,Loyal Customer,55,Business travel,Eco,680,4,2,4,4,2,3,1,4,4,4,4,5,4,1,0,4.0,satisfied +51668,75067,Male,disloyal Customer,21,Business travel,Eco,801,2,2,2,3,2,5,5,4,3,3,3,5,3,5,231,227.0,neutral or dissatisfied +51669,121927,Male,Loyal Customer,43,Business travel,Business,449,3,3,3,3,2,4,4,5,5,5,5,3,5,3,45,42.0,satisfied +51670,47474,Male,Loyal Customer,66,Personal Travel,Eco,590,1,5,1,2,4,1,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +51671,77991,Female,Loyal Customer,65,Business travel,Business,332,0,0,0,2,4,5,4,3,3,3,3,3,3,3,9,5.0,satisfied +51672,61369,Female,Loyal Customer,51,Business travel,Business,679,1,1,1,1,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +51673,120505,Female,disloyal Customer,25,Business travel,Eco Plus,366,2,2,2,4,5,2,5,5,4,3,3,1,4,5,0,0.0,neutral or dissatisfied +51674,117275,Female,Loyal Customer,56,Business travel,Business,646,1,1,4,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +51675,28868,Male,Loyal Customer,23,Business travel,Business,954,2,2,2,2,4,4,4,4,1,1,1,5,2,4,0,0.0,satisfied +51676,45213,Female,disloyal Customer,20,Business travel,Eco,1013,4,4,4,2,2,4,2,2,4,2,2,5,4,2,7,8.0,satisfied +51677,87224,Female,Loyal Customer,11,Personal Travel,Eco,946,2,3,2,4,1,2,1,1,1,4,4,4,5,1,0,0.0,neutral or dissatisfied +51678,87564,Female,Loyal Customer,75,Business travel,Business,2142,3,3,3,3,1,3,3,3,3,3,3,4,3,2,11,0.0,neutral or dissatisfied +51679,48256,Female,Loyal Customer,49,Personal Travel,Eco,236,2,5,2,3,2,4,5,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +51680,85122,Female,disloyal Customer,13,Business travel,Eco,813,3,3,3,3,2,3,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +51681,26339,Female,Loyal Customer,46,Business travel,Business,834,5,5,5,5,4,1,1,4,4,4,4,2,4,5,1,2.0,satisfied +51682,9613,Female,Loyal Customer,13,Personal Travel,Eco,288,2,5,4,4,3,4,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +51683,29392,Male,Loyal Customer,26,Business travel,Eco,2417,0,4,0,2,3,0,3,3,4,1,5,5,2,3,0,0.0,satisfied +51684,4753,Male,Loyal Customer,65,Business travel,Business,2436,5,4,5,5,3,4,4,4,4,4,4,4,4,5,3,0.0,satisfied +51685,23267,Male,Loyal Customer,58,Business travel,Business,775,1,1,1,1,2,4,4,2,2,2,2,4,2,3,26,58.0,satisfied +51686,64597,Female,Loyal Customer,58,Business travel,Business,1951,0,0,0,2,5,5,5,5,5,5,5,4,5,3,8,0.0,satisfied +51687,114893,Male,Loyal Customer,48,Business travel,Business,3343,5,5,5,5,3,5,4,4,4,4,4,3,4,4,5,0.0,satisfied +51688,13960,Male,Loyal Customer,41,Personal Travel,Eco,192,1,5,1,1,3,1,4,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +51689,16076,Male,Loyal Customer,36,Personal Travel,Eco,744,2,4,2,4,5,2,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +51690,74624,Male,disloyal Customer,50,Business travel,Eco,1064,5,5,5,4,2,5,2,2,2,5,1,3,1,2,20,14.0,satisfied +51691,83128,Male,Loyal Customer,37,Personal Travel,Eco,983,1,4,1,4,4,1,4,4,3,5,4,1,3,4,12,0.0,neutral or dissatisfied +51692,20639,Male,Loyal Customer,55,Personal Travel,Eco,911,3,2,3,4,5,3,5,5,1,1,4,4,4,5,0,0.0,neutral or dissatisfied +51693,117138,Female,Loyal Customer,64,Personal Travel,Eco,651,1,4,0,1,1,2,1,1,1,0,1,3,1,2,28,9.0,neutral or dissatisfied +51694,24659,Male,Loyal Customer,30,Business travel,Business,3626,1,3,3,3,1,1,1,1,4,3,3,4,4,1,0,7.0,neutral or dissatisfied +51695,8390,Male,Loyal Customer,41,Business travel,Business,3298,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +51696,44700,Female,Loyal Customer,64,Personal Travel,Eco,67,2,5,2,3,4,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +51697,68907,Male,Loyal Customer,56,Personal Travel,Eco,1061,4,3,4,4,2,4,2,2,2,3,2,4,2,2,0,0.0,satisfied +51698,9699,Male,Loyal Customer,35,Personal Travel,Eco,199,3,4,3,4,3,3,3,3,5,3,4,4,5,3,38,42.0,neutral or dissatisfied +51699,88761,Male,Loyal Customer,23,Business travel,Business,594,3,3,3,3,3,3,3,3,5,4,5,3,5,3,53,36.0,satisfied +51700,7013,Female,Loyal Customer,38,Personal Travel,Eco,196,3,3,3,3,5,3,5,5,2,2,4,2,4,5,0,9.0,neutral or dissatisfied +51701,57449,Male,Loyal Customer,40,Business travel,Business,334,2,2,2,2,3,4,4,4,4,4,4,4,4,3,0,39.0,satisfied +51702,24830,Female,disloyal Customer,42,Business travel,Eco,861,3,2,2,3,4,2,4,4,2,1,5,2,1,4,0,0.0,neutral or dissatisfied +51703,114929,Female,Loyal Customer,43,Business travel,Business,417,5,5,5,5,4,4,5,2,2,2,2,4,2,4,37,31.0,satisfied +51704,92359,Female,Loyal Customer,62,Personal Travel,Eco Plus,2556,3,5,2,3,4,5,5,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +51705,98580,Male,Loyal Customer,54,Business travel,Business,861,5,2,5,5,3,4,5,1,1,2,1,4,1,5,98,113.0,satisfied +51706,125599,Female,Loyal Customer,29,Business travel,Business,1587,3,1,4,4,3,3,3,3,2,2,2,2,3,3,11,3.0,neutral or dissatisfied +51707,38383,Male,Loyal Customer,24,Business travel,Eco Plus,1180,4,3,3,3,4,5,5,4,4,5,5,1,5,4,0,0.0,satisfied +51708,76299,Female,Loyal Customer,39,Business travel,Business,2182,3,3,3,3,5,3,5,5,5,5,5,4,5,3,31,31.0,satisfied +51709,7606,Female,Loyal Customer,40,Business travel,Business,802,2,5,5,5,3,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +51710,11165,Female,Loyal Customer,51,Personal Travel,Eco,429,3,5,3,5,4,3,2,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +51711,89188,Female,Loyal Customer,48,Personal Travel,Eco,1892,2,3,2,3,4,3,4,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +51712,86098,Male,Loyal Customer,41,Business travel,Business,356,1,1,1,1,5,4,5,4,4,4,4,5,4,5,25,20.0,satisfied +51713,12419,Female,Loyal Customer,14,Personal Travel,Eco,192,4,4,4,4,3,4,3,3,3,4,5,5,4,3,76,74.0,neutral or dissatisfied +51714,109990,Female,Loyal Customer,67,Business travel,Eco Plus,765,5,1,1,1,1,3,4,5,5,5,5,1,5,5,14,5.0,satisfied +51715,9198,Female,Loyal Customer,44,Business travel,Business,227,2,4,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +51716,43224,Male,Loyal Customer,55,Personal Travel,Eco,423,3,1,3,3,1,3,1,1,3,2,3,4,3,1,13,23.0,neutral or dissatisfied +51717,95314,Female,Loyal Customer,43,Personal Travel,Eco,148,2,4,2,3,5,5,5,4,4,2,4,3,4,3,3,0.0,neutral or dissatisfied +51718,59250,Male,disloyal Customer,19,Business travel,Business,3801,3,2,3,4,3,4,5,4,5,2,3,5,2,5,0,0.0,neutral or dissatisfied +51719,18504,Male,Loyal Customer,61,Business travel,Business,3636,2,2,2,2,3,4,1,5,5,5,5,2,5,1,14,7.0,satisfied +51720,104214,Female,Loyal Customer,42,Business travel,Business,1928,2,2,2,2,2,5,5,5,5,5,5,3,5,5,77,75.0,satisfied +51721,69816,Female,Loyal Customer,46,Business travel,Business,3928,2,2,2,2,1,3,2,2,2,2,2,3,2,4,14,0.0,neutral or dissatisfied +51722,111862,Female,Loyal Customer,24,Business travel,Business,628,2,2,2,2,3,3,3,3,4,3,4,3,5,3,4,4.0,satisfied +51723,5049,Male,Loyal Customer,60,Business travel,Business,303,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +51724,70099,Female,disloyal Customer,19,Business travel,Eco,550,4,4,5,4,2,5,2,2,4,3,5,3,4,2,0,7.0,satisfied +51725,119021,Male,Loyal Customer,37,Business travel,Business,1460,5,5,5,5,4,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +51726,4913,Male,Loyal Customer,22,Business travel,Business,2001,2,2,2,2,5,4,5,5,5,3,5,3,4,5,0,0.0,satisfied +51727,74799,Female,Loyal Customer,46,Business travel,Eco Plus,1205,2,5,4,4,3,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +51728,55630,Female,Loyal Customer,26,Personal Travel,Eco,1824,3,4,2,3,2,2,5,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +51729,108455,Female,disloyal Customer,36,Business travel,Eco,1044,1,1,1,3,1,5,5,4,1,1,3,5,1,5,216,210.0,neutral or dissatisfied +51730,12347,Male,Loyal Customer,52,Business travel,Business,2584,2,2,2,2,2,2,2,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +51731,7708,Female,disloyal Customer,24,Business travel,Eco,604,4,4,4,4,4,1,1,4,5,4,5,1,3,1,360,409.0,satisfied +51732,47830,Male,disloyal Customer,52,Business travel,Eco,784,1,1,1,2,2,1,4,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +51733,3176,Female,Loyal Customer,51,Business travel,Business,693,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,52.0,satisfied +51734,79524,Female,Loyal Customer,53,Business travel,Business,3521,1,1,1,1,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +51735,52885,Female,disloyal Customer,37,Business travel,Eco,624,2,0,2,4,3,2,2,3,2,4,1,3,5,3,7,8.0,neutral or dissatisfied +51736,30914,Male,Loyal Customer,30,Business travel,Business,896,5,5,4,5,5,5,5,5,1,4,3,5,5,5,11,1.0,satisfied +51737,87089,Male,disloyal Customer,24,Business travel,Eco,194,5,0,5,2,5,5,5,5,3,1,3,1,5,5,0,0.0,satisfied +51738,66704,Male,Loyal Customer,22,Business travel,Business,3958,1,5,5,5,1,2,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +51739,52137,Male,Loyal Customer,39,Business travel,Business,3061,1,1,1,1,4,5,5,4,4,4,4,3,4,3,33,24.0,satisfied +51740,88366,Male,Loyal Customer,56,Business travel,Eco,404,1,2,1,2,2,1,2,2,1,3,2,1,3,2,0,2.0,neutral or dissatisfied +51741,75845,Male,Loyal Customer,21,Business travel,Eco,1437,4,1,5,1,4,4,1,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +51742,407,Female,Loyal Customer,32,Business travel,Business,164,2,4,4,4,1,1,2,1,1,1,4,4,4,1,0,0.0,neutral or dissatisfied +51743,75052,Male,Loyal Customer,24,Personal Travel,Eco,1592,0,3,0,1,3,0,3,3,4,2,5,5,5,3,93,86.0,satisfied +51744,7240,Female,Loyal Customer,48,Business travel,Business,3361,3,3,5,3,4,2,3,5,5,5,4,4,5,2,0,0.0,satisfied +51745,40374,Male,Loyal Customer,45,Business travel,Eco,1250,2,4,4,4,2,2,2,2,3,1,1,3,3,2,0,0.0,satisfied +51746,112199,Male,Loyal Customer,30,Business travel,Business,649,1,1,1,1,5,5,5,5,5,2,4,4,5,5,2,0.0,satisfied +51747,44489,Male,Loyal Customer,16,Personal Travel,Eco,476,3,4,3,3,2,3,2,2,1,2,3,1,3,2,17,11.0,neutral or dissatisfied +51748,56132,Female,Loyal Customer,48,Business travel,Business,1400,3,3,3,3,2,5,4,5,5,4,5,5,5,3,59,78.0,satisfied +51749,86466,Female,Loyal Customer,41,Business travel,Eco,394,4,1,1,1,4,4,4,4,5,3,3,4,4,4,6,0.0,satisfied +51750,30003,Male,disloyal Customer,27,Business travel,Eco,373,2,4,2,2,5,2,5,5,4,3,3,3,3,5,0,0.0,neutral or dissatisfied +51751,46757,Female,disloyal Customer,37,Business travel,Eco Plus,251,3,3,3,2,2,3,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +51752,41709,Female,Loyal Customer,55,Business travel,Business,1913,2,1,4,1,3,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +51753,118223,Male,Loyal Customer,39,Personal Travel,Eco,735,2,4,2,5,2,2,2,2,5,2,5,5,4,2,1,0.0,neutral or dissatisfied +51754,5428,Female,disloyal Customer,26,Business travel,Business,265,5,0,5,4,2,5,2,2,4,5,4,5,4,2,13,22.0,satisfied +51755,55585,Male,Loyal Customer,21,Personal Travel,Eco,1091,2,3,2,3,5,2,5,5,2,2,5,4,4,5,0,0.0,neutral or dissatisfied +51756,91095,Female,Loyal Customer,28,Personal Travel,Eco,271,1,5,1,5,3,1,1,3,1,1,2,3,3,3,0,0.0,neutral or dissatisfied +51757,77428,Female,Loyal Customer,25,Personal Travel,Eco,626,1,1,1,2,4,1,4,4,4,1,2,3,2,4,43,35.0,neutral or dissatisfied +51758,106267,Female,Loyal Customer,37,Personal Travel,Eco,1500,4,3,4,4,4,4,4,4,1,3,3,2,4,4,0,0.0,satisfied +51759,3282,Female,Loyal Customer,26,Personal Travel,Eco,479,3,1,3,3,3,3,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +51760,5845,Male,Loyal Customer,51,Business travel,Business,1020,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +51761,65692,Male,Loyal Customer,39,Business travel,Business,3015,1,1,1,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +51762,45673,Male,Loyal Customer,45,Business travel,Business,826,5,5,5,5,3,3,4,5,5,5,5,1,5,4,5,29.0,satisfied +51763,69253,Male,Loyal Customer,40,Business travel,Business,733,4,4,2,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +51764,102008,Male,disloyal Customer,56,Business travel,Business,223,2,2,2,2,5,2,5,5,4,4,5,4,5,5,10,10.0,neutral or dissatisfied +51765,32039,Male,Loyal Customer,33,Business travel,Business,3486,3,3,4,3,4,4,5,4,4,5,3,5,5,4,0,0.0,satisfied +51766,51414,Female,Loyal Customer,59,Personal Travel,Eco Plus,134,3,2,3,3,2,3,3,4,4,3,4,4,4,2,82,79.0,neutral or dissatisfied +51767,71602,Male,Loyal Customer,55,Business travel,Business,2388,4,1,1,1,2,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +51768,57217,Female,Loyal Customer,39,Business travel,Eco,1514,3,3,3,3,3,3,3,3,4,2,3,2,3,3,28,12.0,neutral or dissatisfied +51769,51117,Male,Loyal Customer,48,Personal Travel,Eco,373,3,3,4,4,1,4,1,1,2,4,1,3,2,1,0,0.0,neutral or dissatisfied +51770,86941,Female,Loyal Customer,61,Personal Travel,Business,907,3,4,3,3,4,4,4,3,3,3,3,2,3,4,16,0.0,neutral or dissatisfied +51771,126360,Male,Loyal Customer,8,Personal Travel,Eco,590,3,1,3,2,4,3,4,4,2,5,2,2,3,4,0,0.0,neutral or dissatisfied +51772,121373,Male,disloyal Customer,23,Business travel,Eco,1295,5,5,5,2,5,4,4,3,2,4,4,4,5,4,0,17.0,satisfied +51773,1466,Female,Loyal Customer,63,Personal Travel,Eco,772,3,4,4,4,2,5,1,3,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +51774,114119,Male,Loyal Customer,53,Personal Travel,Business,862,3,5,3,1,5,4,4,4,4,3,4,5,4,3,8,0.0,neutral or dissatisfied +51775,4770,Male,disloyal Customer,41,Business travel,Business,403,2,2,2,4,3,2,3,3,4,5,5,5,4,3,0,22.0,neutral or dissatisfied +51776,30821,Female,Loyal Customer,36,Business travel,Business,896,5,4,5,5,3,5,5,5,5,5,5,3,5,1,91,85.0,satisfied +51777,113709,Male,Loyal Customer,69,Personal Travel,Eco,236,1,1,1,3,4,1,4,4,1,2,4,4,4,4,1,0.0,neutral or dissatisfied +51778,19853,Male,Loyal Customer,46,Business travel,Business,2019,3,1,1,1,1,4,4,3,3,3,3,2,3,4,63,97.0,neutral or dissatisfied +51779,23721,Male,Loyal Customer,33,Personal Travel,Eco,73,4,4,4,4,1,4,1,1,3,4,3,4,4,1,0,0.0,neutral or dissatisfied +51780,88303,Male,disloyal Customer,36,Business travel,Business,271,2,1,1,5,3,1,1,3,5,3,4,5,4,3,104,101.0,neutral or dissatisfied +51781,123701,Female,Loyal Customer,46,Personal Travel,Eco,214,4,0,0,1,4,5,4,1,1,0,1,3,1,4,0,0.0,neutral or dissatisfied +51782,108674,Female,Loyal Customer,46,Business travel,Business,2721,1,2,1,1,5,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +51783,62753,Female,Loyal Customer,20,Business travel,Business,2556,3,3,3,3,5,5,5,5,5,4,5,5,4,5,0,9.0,satisfied +51784,96615,Female,disloyal Customer,30,Business travel,Eco,972,1,1,1,3,4,1,4,4,4,5,3,3,4,4,15,19.0,neutral or dissatisfied +51785,67138,Female,Loyal Customer,52,Business travel,Eco,964,3,3,2,2,4,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +51786,128335,Female,Loyal Customer,41,Business travel,Eco,651,3,3,3,3,3,3,3,3,2,3,3,2,3,3,38,31.0,neutral or dissatisfied +51787,37486,Female,disloyal Customer,36,Business travel,Eco,1005,1,0,0,2,3,0,5,3,2,1,3,5,2,3,20,10.0,neutral or dissatisfied +51788,86003,Male,Loyal Customer,32,Business travel,Business,432,1,1,1,1,5,5,5,5,3,2,5,5,4,5,0,5.0,satisfied +51789,100670,Male,disloyal Customer,24,Business travel,Eco,677,1,1,1,4,4,1,4,4,1,2,4,3,4,4,9,18.0,neutral or dissatisfied +51790,127200,Female,Loyal Customer,58,Business travel,Business,647,1,1,1,1,3,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +51791,70612,Male,Loyal Customer,55,Business travel,Business,3810,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +51792,102084,Female,Loyal Customer,57,Business travel,Business,397,4,4,4,4,4,4,4,4,3,5,4,4,3,4,151,152.0,satisfied +51793,25400,Female,disloyal Customer,24,Business travel,Eco,1105,4,4,4,3,3,4,5,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +51794,95474,Female,Loyal Customer,74,Business travel,Business,1968,5,5,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +51795,74782,Female,disloyal Customer,26,Business travel,Business,1438,5,5,5,1,3,5,3,3,5,3,5,4,5,3,0,0.0,satisfied +51796,36407,Male,Loyal Customer,59,Business travel,Business,2334,1,1,1,1,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +51797,82498,Male,Loyal Customer,35,Personal Travel,Eco,488,3,0,3,3,2,3,2,2,5,2,5,3,4,2,0,86.0,neutral or dissatisfied +51798,37974,Female,Loyal Customer,60,Business travel,Business,1185,3,3,3,3,4,4,4,5,5,5,5,3,5,5,19,5.0,satisfied +51799,126029,Male,Loyal Customer,53,Business travel,Business,507,3,3,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +51800,28345,Male,Loyal Customer,19,Personal Travel,Eco,867,2,1,2,3,3,2,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +51801,89363,Male,Loyal Customer,65,Personal Travel,Eco,1587,3,4,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +51802,102724,Female,Loyal Customer,17,Personal Travel,Eco,365,1,4,1,4,2,1,5,2,4,2,5,4,5,2,49,47.0,neutral or dissatisfied +51803,40138,Female,Loyal Customer,44,Personal Travel,Eco Plus,200,1,3,1,3,2,3,4,3,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +51804,5572,Male,Loyal Customer,60,Personal Travel,Eco,501,2,5,2,5,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +51805,80005,Male,Loyal Customer,70,Personal Travel,Eco,944,3,2,3,3,5,3,5,5,4,2,4,1,4,5,16,0.0,neutral or dissatisfied +51806,2934,Male,Loyal Customer,67,Personal Travel,Eco,859,2,5,2,1,2,2,2,2,5,2,5,3,5,2,26,29.0,neutral or dissatisfied +51807,78783,Female,Loyal Customer,37,Business travel,Business,2714,1,1,3,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +51808,88235,Female,Loyal Customer,25,Business travel,Business,3496,3,2,2,2,3,3,3,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +51809,75385,Male,Loyal Customer,47,Business travel,Business,2330,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +51810,8052,Female,disloyal Customer,52,Business travel,Business,530,3,3,3,3,4,3,5,4,3,3,4,4,5,4,0,0.0,satisfied +51811,77707,Female,Loyal Customer,27,Business travel,Business,696,1,3,3,3,1,2,1,1,4,3,4,4,4,1,1,0.0,neutral or dissatisfied +51812,95296,Male,Loyal Customer,56,Personal Travel,Eco,239,2,3,2,5,3,2,4,3,5,1,3,1,3,3,21,17.0,neutral or dissatisfied +51813,8340,Female,disloyal Customer,25,Business travel,Business,661,5,4,5,1,1,5,1,1,5,4,4,5,5,1,0,0.0,satisfied +51814,98196,Female,Loyal Customer,59,Business travel,Business,327,2,2,2,2,1,2,3,4,4,4,4,2,4,3,1,0.0,satisfied +51815,12186,Female,Loyal Customer,37,Personal Travel,Eco,986,3,4,3,3,4,3,4,4,5,5,5,4,5,4,9,0.0,neutral or dissatisfied +51816,34108,Female,Loyal Customer,40,Business travel,Business,1288,5,5,5,5,3,3,1,5,5,5,5,2,5,3,0,0.0,satisfied +51817,42158,Female,Loyal Customer,50,Personal Travel,Business,329,1,4,2,3,4,4,4,2,2,2,5,2,2,3,0,0.0,neutral or dissatisfied +51818,28268,Female,Loyal Customer,37,Business travel,Eco Plus,1542,4,2,2,2,4,4,4,4,3,4,5,2,1,4,0,0.0,satisfied +51819,15995,Female,disloyal Customer,24,Business travel,Business,780,2,3,2,2,5,2,4,5,4,1,3,2,2,5,5,28.0,neutral or dissatisfied +51820,12975,Female,Loyal Customer,43,Personal Travel,Business,374,3,4,3,3,3,4,1,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +51821,28304,Male,disloyal Customer,20,Business travel,Eco,867,3,3,3,2,3,3,3,3,3,1,3,5,5,3,0,0.0,neutral or dissatisfied +51822,63347,Female,Loyal Customer,21,Business travel,Eco,337,3,3,3,3,3,3,2,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +51823,20754,Male,Loyal Customer,66,Personal Travel,Eco,363,2,2,2,2,3,2,3,3,1,4,3,1,3,3,11,7.0,neutral or dissatisfied +51824,45089,Male,disloyal Customer,23,Business travel,Eco,196,4,3,4,3,2,4,2,2,1,5,3,1,4,2,7,4.0,neutral or dissatisfied +51825,26409,Female,Loyal Customer,42,Business travel,Eco,1249,2,3,3,3,4,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +51826,11587,Male,disloyal Customer,50,Business travel,Eco,657,1,1,1,3,3,1,3,3,2,4,4,1,4,3,20,19.0,neutral or dissatisfied +51827,98341,Male,disloyal Customer,29,Business travel,Business,1189,2,2,2,3,4,2,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +51828,92612,Female,Loyal Customer,39,Business travel,Business,2514,3,3,3,3,2,5,5,2,2,2,2,4,2,4,14,20.0,satisfied +51829,35467,Female,Loyal Customer,25,Personal Travel,Eco,1069,1,5,1,4,4,1,4,4,5,5,5,3,4,4,69,63.0,neutral or dissatisfied +51830,120079,Female,Loyal Customer,49,Business travel,Business,2049,5,5,5,5,2,1,2,4,4,4,4,5,4,4,0,0.0,satisfied +51831,98552,Male,Loyal Customer,41,Business travel,Business,861,3,3,3,3,5,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +51832,122674,Female,Loyal Customer,57,Business travel,Eco,361,2,4,4,4,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +51833,118703,Male,Loyal Customer,34,Personal Travel,Eco,621,0,5,1,2,4,1,4,4,4,5,4,4,4,4,5,0.0,satisfied +51834,82324,Female,Loyal Customer,38,Business travel,Business,2005,2,3,3,3,3,4,4,2,2,2,2,2,2,4,38,80.0,neutral or dissatisfied +51835,30715,Female,Loyal Customer,36,Business travel,Business,1123,3,3,3,3,1,1,4,5,5,5,5,2,5,1,0,0.0,satisfied +51836,66670,Male,Loyal Customer,32,Business travel,Business,978,3,4,5,4,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +51837,55096,Male,disloyal Customer,56,Business travel,Eco,1009,4,4,4,3,2,4,2,2,4,2,4,4,4,2,100,79.0,neutral or dissatisfied +51838,13824,Male,disloyal Customer,26,Business travel,Eco,594,1,5,1,3,3,1,3,3,4,3,2,1,5,3,0,0.0,neutral or dissatisfied +51839,10665,Female,Loyal Customer,58,Business travel,Business,2006,1,1,1,1,5,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +51840,119460,Male,Loyal Customer,14,Personal Travel,Business,759,3,5,3,1,5,3,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +51841,101946,Male,disloyal Customer,37,Business travel,Business,628,3,3,3,2,2,3,2,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +51842,81313,Male,Loyal Customer,36,Personal Travel,Business,1299,1,4,1,1,5,3,5,5,5,1,3,4,5,5,0,20.0,neutral or dissatisfied +51843,59240,Male,Loyal Customer,68,Business travel,Eco Plus,249,4,3,3,3,4,4,4,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +51844,85121,Male,Loyal Customer,43,Business travel,Eco,731,3,3,3,3,3,3,3,3,2,1,3,2,4,3,0,0.0,neutral or dissatisfied +51845,10944,Female,disloyal Customer,22,Business travel,Eco,134,2,2,2,3,5,2,2,5,3,1,3,1,3,5,103,114.0,neutral or dissatisfied +51846,107073,Female,Loyal Customer,70,Personal Travel,Eco,395,3,5,3,1,3,5,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +51847,100777,Female,Loyal Customer,16,Personal Travel,Eco,1411,4,5,4,4,4,4,5,4,1,5,2,5,1,5,30,136.0,satisfied +51848,37915,Female,Loyal Customer,15,Personal Travel,Eco,937,2,5,2,1,2,2,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +51849,128987,Male,Loyal Customer,41,Personal Travel,Eco,414,1,5,1,2,4,1,4,4,5,5,4,5,4,4,8,3.0,neutral or dissatisfied +51850,111927,Male,disloyal Customer,22,Business travel,Eco,472,4,4,4,4,5,4,5,5,3,5,5,5,5,5,4,2.0,satisfied +51851,57224,Male,Loyal Customer,22,Personal Travel,Eco,1514,2,4,2,4,5,2,5,5,5,2,5,4,3,5,15,7.0,neutral or dissatisfied +51852,24914,Male,disloyal Customer,38,Business travel,Eco,762,2,2,2,3,5,2,4,5,1,3,2,3,3,5,8,0.0,neutral or dissatisfied +51853,77749,Female,disloyal Customer,38,Business travel,Eco,331,1,1,1,4,1,1,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +51854,66654,Female,disloyal Customer,23,Business travel,Eco,802,4,4,4,2,3,4,3,3,5,5,5,3,5,3,57,40.0,neutral or dissatisfied +51855,129494,Male,Loyal Customer,27,Business travel,Business,1744,2,2,2,2,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +51856,67450,Female,Loyal Customer,34,Personal Travel,Eco,641,3,5,4,3,4,4,4,4,4,2,4,4,4,4,61,66.0,neutral or dissatisfied +51857,38285,Female,disloyal Customer,22,Business travel,Eco,1180,3,3,3,4,3,3,4,3,4,2,4,4,4,3,13,0.0,neutral or dissatisfied +51858,21915,Female,Loyal Customer,39,Business travel,Business,448,2,1,1,1,2,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +51859,68758,Male,Loyal Customer,45,Business travel,Business,3581,3,3,3,3,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +51860,79912,Male,Loyal Customer,15,Business travel,Business,3979,2,2,2,2,2,2,2,2,2,4,3,2,3,2,853,823.0,neutral or dissatisfied +51861,18889,Male,disloyal Customer,18,Business travel,Eco,500,4,3,4,2,2,4,2,2,5,4,3,3,3,2,0,0.0,neutral or dissatisfied +51862,63467,Female,Loyal Customer,25,Business travel,Business,2689,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +51863,37296,Male,Loyal Customer,35,Business travel,Business,1912,5,5,5,5,1,4,5,5,5,5,5,2,5,2,0,4.0,satisfied +51864,90466,Male,Loyal Customer,39,Business travel,Business,270,1,1,1,1,3,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +51865,54725,Male,Loyal Customer,32,Personal Travel,Eco,964,2,5,2,2,3,2,3,3,5,2,5,5,4,3,97,94.0,neutral or dissatisfied +51866,120063,Female,Loyal Customer,36,Business travel,Business,3200,5,5,5,5,3,4,5,3,3,3,3,5,3,5,21,37.0,satisfied +51867,19841,Female,Loyal Customer,13,Personal Travel,Eco Plus,594,1,3,1,2,2,1,2,2,1,1,3,4,2,2,14,12.0,neutral or dissatisfied +51868,45285,Male,Loyal Customer,46,Business travel,Business,222,5,5,5,5,3,4,4,5,5,5,5,1,5,3,0,0.0,satisfied +51869,11566,Male,Loyal Customer,46,Business travel,Business,2004,5,5,5,5,4,4,5,4,4,4,4,5,4,3,17,3.0,satisfied +51870,77993,Female,disloyal Customer,24,Business travel,Eco,227,1,4,1,2,3,1,1,3,5,5,4,5,5,3,4,1.0,neutral or dissatisfied +51871,39869,Female,disloyal Customer,40,Business travel,Business,272,3,2,2,2,5,2,5,5,5,1,5,2,1,5,0,0.0,neutral or dissatisfied +51872,67076,Female,disloyal Customer,22,Business travel,Business,1017,5,0,5,5,1,5,1,1,3,5,5,3,4,1,0,0.0,satisfied +51873,76011,Female,Loyal Customer,51,Business travel,Business,237,3,3,3,3,3,4,4,5,5,5,5,4,5,5,83,79.0,satisfied +51874,69820,Female,Loyal Customer,39,Business travel,Eco,1055,2,4,4,4,2,2,2,2,1,3,3,1,3,2,13,18.0,neutral or dissatisfied +51875,115707,Female,Loyal Customer,37,Business travel,Eco,337,3,1,1,1,3,3,3,3,2,3,2,3,3,3,43,39.0,neutral or dissatisfied +51876,89164,Male,Loyal Customer,68,Personal Travel,Eco,1947,2,5,2,3,3,2,3,3,5,5,5,4,4,3,1,28.0,neutral or dissatisfied +51877,53054,Female,Loyal Customer,41,Personal Travel,Eco,1208,3,4,3,2,4,3,2,4,2,4,5,4,1,4,11,0.0,neutral or dissatisfied +51878,35952,Male,Loyal Customer,38,Business travel,Eco,231,3,2,2,2,3,3,3,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +51879,41128,Female,disloyal Customer,56,Business travel,Eco,224,2,4,2,3,3,2,3,3,3,1,4,2,3,3,0,0.0,neutral or dissatisfied +51880,105399,Male,Loyal Customer,60,Personal Travel,Eco,369,2,1,4,2,3,4,3,3,2,4,2,3,3,3,10,,neutral or dissatisfied +51881,69918,Male,Loyal Customer,63,Personal Travel,Eco,1514,2,2,2,3,3,2,3,3,3,4,4,4,4,3,0,10.0,neutral or dissatisfied +51882,2232,Female,Loyal Customer,15,Personal Travel,Eco,642,3,1,3,3,5,3,3,5,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +51883,8791,Female,Loyal Customer,24,Business travel,Business,552,2,4,4,4,2,2,2,2,2,3,4,2,3,2,0,0.0,neutral or dissatisfied +51884,103935,Male,disloyal Customer,21,Business travel,Business,533,0,3,0,3,5,0,5,5,4,5,5,3,4,5,0,0.0,satisfied +51885,84254,Female,disloyal Customer,24,Business travel,Eco,724,2,2,2,4,1,2,1,1,3,3,4,4,4,1,3,0.0,neutral or dissatisfied +51886,69702,Male,disloyal Customer,26,Business travel,Business,1372,0,0,0,2,1,0,1,1,5,5,4,5,4,1,0,2.0,satisfied +51887,37869,Female,Loyal Customer,22,Business travel,Business,3751,4,4,5,5,4,4,4,4,1,5,3,3,3,4,13,24.0,neutral or dissatisfied +51888,54890,Female,Loyal Customer,10,Personal Travel,Eco,927,2,2,2,3,4,2,4,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +51889,60078,Female,Loyal Customer,11,Business travel,Business,3242,5,5,5,5,5,5,5,5,3,5,5,5,5,5,23,34.0,satisfied +51890,108785,Male,Loyal Customer,47,Business travel,Business,2629,4,4,4,4,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +51891,92214,Female,Loyal Customer,40,Personal Travel,Eco,1979,3,2,3,2,3,3,3,3,2,5,2,1,3,3,2,0.0,neutral or dissatisfied +51892,95569,Female,Loyal Customer,9,Personal Travel,Eco Plus,189,3,4,3,4,4,3,4,4,4,5,4,3,3,4,1,4.0,neutral or dissatisfied +51893,88958,Male,Loyal Customer,40,Business travel,Business,1340,2,3,3,3,2,3,3,2,2,2,2,2,2,2,0,1.0,neutral or dissatisfied +51894,42250,Female,Loyal Customer,42,Business travel,Eco,451,1,4,4,4,5,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +51895,105009,Male,Loyal Customer,34,Business travel,Business,361,5,5,5,5,4,5,5,5,5,5,5,5,5,3,2,1.0,satisfied +51896,30111,Male,Loyal Customer,19,Personal Travel,Eco,539,1,5,1,1,2,1,2,2,4,2,5,3,4,2,0,4.0,neutral or dissatisfied +51897,72376,Female,Loyal Customer,46,Business travel,Business,2645,1,1,1,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +51898,108895,Male,Loyal Customer,34,Business travel,Business,3082,2,2,2,2,4,5,4,5,5,5,5,5,5,3,12,6.0,satisfied +51899,104494,Male,Loyal Customer,45,Personal Travel,Eco,860,4,5,4,2,5,4,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +51900,21636,Female,Loyal Customer,10,Personal Travel,Eco,780,3,5,3,3,3,3,3,3,5,4,4,5,5,3,9,10.0,neutral or dissatisfied +51901,92552,Male,Loyal Customer,62,Personal Travel,Eco,1892,2,2,2,3,2,2,1,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +51902,5559,Female,disloyal Customer,23,Business travel,Business,588,0,0,0,1,2,0,2,2,3,3,4,5,4,2,57,65.0,satisfied +51903,90633,Female,Loyal Customer,33,Business travel,Business,3619,2,5,5,5,2,4,4,2,2,1,2,3,2,1,0,21.0,neutral or dissatisfied +51904,13696,Female,disloyal Customer,37,Business travel,Eco,483,3,4,3,4,5,3,5,5,5,1,4,2,2,5,5,2.0,neutral or dissatisfied +51905,51109,Male,Loyal Customer,9,Personal Travel,Eco,89,2,5,2,3,4,2,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +51906,24881,Female,Loyal Customer,70,Personal Travel,Eco,534,3,4,3,2,5,5,4,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +51907,97075,Female,Loyal Customer,53,Business travel,Business,1390,1,1,1,1,2,4,4,4,4,4,4,3,4,5,66,60.0,satisfied +51908,74126,Female,disloyal Customer,43,Business travel,Eco,641,2,2,2,3,1,2,1,1,3,3,4,3,4,1,2,23.0,neutral or dissatisfied +51909,70686,Female,Loyal Customer,53,Personal Travel,Eco,447,2,5,4,1,2,4,4,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +51910,119803,Male,Loyal Customer,23,Business travel,Business,2199,3,3,3,3,2,2,2,2,4,4,4,5,4,2,57,40.0,satisfied +51911,70497,Female,Loyal Customer,41,Business travel,Eco,467,3,1,5,5,3,3,3,3,1,5,2,1,2,3,0,27.0,satisfied +51912,76500,Female,Loyal Customer,53,Business travel,Business,2520,3,3,5,3,2,4,4,4,4,4,4,5,4,3,3,1.0,satisfied +51913,9071,Male,Loyal Customer,27,Business travel,Business,108,5,5,5,5,4,4,3,4,4,3,1,2,1,4,0,28.0,satisfied +51914,32155,Male,Loyal Customer,36,Business travel,Business,2697,5,5,5,5,2,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +51915,128220,Female,Loyal Customer,25,Business travel,Business,2444,2,5,5,5,2,3,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +51916,43211,Male,Loyal Customer,45,Business travel,Business,472,5,5,5,5,4,5,5,5,5,5,5,3,5,4,26,63.0,satisfied +51917,67442,Female,Loyal Customer,43,Business travel,Eco,321,3,2,4,2,3,2,2,3,3,3,3,2,3,2,3,0.0,neutral or dissatisfied +51918,13496,Male,Loyal Customer,42,Business travel,Business,227,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,15.0,satisfied +51919,41862,Male,Loyal Customer,20,Business travel,Business,1773,3,2,2,2,3,3,3,3,3,1,3,3,3,3,0,1.0,neutral or dissatisfied +51920,44833,Female,Loyal Customer,42,Personal Travel,Eco,462,3,3,3,2,1,2,1,5,5,3,5,3,5,2,0,9.0,neutral or dissatisfied +51921,81657,Male,Loyal Customer,46,Business travel,Business,3700,3,3,4,3,5,4,4,3,2,5,5,4,4,4,108,132.0,satisfied +51922,16949,Female,Loyal Customer,55,Personal Travel,Eco Plus,820,3,2,3,4,5,3,4,4,4,3,4,1,4,4,18,27.0,neutral or dissatisfied +51923,32219,Female,Loyal Customer,31,Business travel,Business,3226,0,4,0,4,5,5,5,5,2,3,4,4,5,5,0,0.0,satisfied +51924,76610,Male,Loyal Customer,47,Business travel,Business,1979,1,1,4,1,5,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +51925,11757,Male,disloyal Customer,38,Business travel,Eco,429,4,1,4,3,4,4,4,4,3,1,4,2,3,4,9,45.0,neutral or dissatisfied +51926,83304,Male,Loyal Customer,47,Personal Travel,Eco Plus,1956,4,1,4,2,3,4,3,3,3,3,1,2,2,3,0,0.0,satisfied +51927,51661,Male,Loyal Customer,35,Business travel,Eco,370,4,3,3,3,4,3,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +51928,32806,Male,Loyal Customer,38,Business travel,Business,3664,2,4,4,4,5,3,3,3,3,3,2,1,3,4,21,22.0,neutral or dissatisfied +51929,91035,Male,Loyal Customer,63,Personal Travel,Eco,581,3,4,2,3,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +51930,106439,Female,Loyal Customer,29,Business travel,Business,3052,4,5,5,5,4,4,4,4,3,5,2,4,2,4,7,8.0,neutral or dissatisfied +51931,1102,Female,Loyal Customer,16,Personal Travel,Eco,312,2,4,2,3,5,2,5,5,3,2,4,2,4,5,10,7.0,neutral or dissatisfied +51932,14506,Female,Loyal Customer,56,Business travel,Eco,328,4,4,4,4,2,1,5,4,4,4,4,5,4,5,0,0.0,satisfied +51933,97618,Female,disloyal Customer,32,Business travel,Business,764,2,2,2,3,4,2,4,4,5,3,4,3,5,4,14,15.0,neutral or dissatisfied +51934,8794,Female,disloyal Customer,26,Business travel,Eco,522,4,3,4,3,3,4,5,3,3,3,3,3,3,3,0,65.0,neutral or dissatisfied +51935,42561,Female,Loyal Customer,38,Business travel,Eco,622,4,1,5,5,4,4,4,4,3,1,3,5,5,4,0,0.0,satisfied +51936,119851,Male,Loyal Customer,38,Business travel,Business,512,3,3,3,3,2,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +51937,126587,Male,Loyal Customer,35,Business travel,Business,1337,1,1,3,1,4,5,5,5,5,5,5,3,5,3,0,17.0,satisfied +51938,118929,Female,Loyal Customer,42,Business travel,Eco Plus,587,4,1,5,5,1,3,2,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +51939,100349,Male,Loyal Customer,49,Personal Travel,Eco,1052,5,1,5,2,2,5,2,2,3,5,1,1,1,2,42,44.0,satisfied +51940,10379,Male,disloyal Customer,36,Business travel,Business,247,4,4,4,1,5,4,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +51941,57229,Male,Loyal Customer,69,Personal Travel,Eco,1514,3,3,4,3,3,4,3,3,2,1,3,3,4,3,0,1.0,neutral or dissatisfied +51942,6745,Female,Loyal Customer,37,Business travel,Business,3987,1,1,1,1,1,4,4,3,3,3,1,3,3,4,16,11.0,neutral or dissatisfied +51943,19941,Male,Loyal Customer,23,Personal Travel,Eco,343,1,4,1,1,5,1,5,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +51944,68560,Male,Loyal Customer,67,Personal Travel,Eco Plus,2136,5,5,5,4,4,5,4,4,3,2,4,4,5,4,0,0.0,satisfied +51945,31138,Female,Loyal Customer,58,Personal Travel,Eco,991,3,4,2,1,5,5,5,1,1,2,1,5,1,5,97,111.0,neutral or dissatisfied +51946,65803,Male,Loyal Customer,56,Business travel,Business,1389,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +51947,90722,Female,Loyal Customer,57,Business travel,Eco,404,3,3,3,3,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +51948,27210,Female,Loyal Customer,14,Personal Travel,Eco,2554,1,5,0,4,4,0,4,4,1,3,3,5,2,4,0,0.0,neutral or dissatisfied +51949,94059,Male,Loyal Customer,46,Business travel,Business,2496,4,4,4,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +51950,108474,Male,Loyal Customer,25,Business travel,Business,1440,5,5,5,5,4,4,4,4,5,5,5,5,4,4,57,105.0,satisfied +51951,107698,Male,disloyal Customer,27,Business travel,Eco,251,1,2,1,3,1,1,1,1,3,3,3,4,2,1,0,0.0,neutral or dissatisfied +51952,104625,Female,Loyal Customer,23,Business travel,Business,2328,2,2,2,2,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +51953,111490,Male,disloyal Customer,37,Business travel,Business,391,3,4,4,2,3,4,3,3,4,5,4,5,4,3,8,0.0,neutral or dissatisfied +51954,95087,Male,Loyal Customer,37,Personal Travel,Eco,192,2,5,2,4,2,2,2,2,5,5,4,5,4,2,19,18.0,neutral or dissatisfied +51955,34504,Female,Loyal Customer,35,Business travel,Business,1428,1,1,1,1,5,3,4,4,4,4,4,1,4,3,0,0.0,satisfied +51956,2623,Female,Loyal Customer,53,Business travel,Business,2377,4,4,4,4,5,5,4,5,5,5,5,5,5,5,33,38.0,satisfied +51957,3860,Female,Loyal Customer,43,Business travel,Business,650,4,4,4,4,2,5,4,5,5,4,5,3,5,3,12,17.0,satisfied +51958,71683,Male,Loyal Customer,58,Personal Travel,Eco,1197,2,4,2,3,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +51959,54989,Female,Loyal Customer,43,Business travel,Business,1609,5,5,5,5,2,4,4,5,5,5,5,3,5,4,11,0.0,satisfied +51960,64806,Female,Loyal Customer,39,Business travel,Business,2390,2,2,2,2,5,5,4,5,5,5,4,3,5,4,0,0.0,satisfied +51961,95325,Female,Loyal Customer,23,Personal Travel,Eco,277,4,4,4,3,2,4,3,2,3,4,4,5,5,2,9,0.0,neutral or dissatisfied +51962,7177,Female,Loyal Customer,52,Business travel,Business,1907,4,4,4,4,3,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +51963,75456,Female,Loyal Customer,55,Business travel,Business,830,4,4,4,4,3,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +51964,8209,Female,disloyal Customer,34,Business travel,Eco,530,3,2,3,3,4,3,4,4,4,5,4,4,3,4,0,3.0,neutral or dissatisfied +51965,58020,Female,Loyal Customer,58,Business travel,Eco,1721,3,5,3,5,3,3,4,3,3,3,3,4,3,1,46,35.0,neutral or dissatisfied +51966,40466,Female,Loyal Customer,34,Business travel,Business,2891,5,5,4,5,5,5,1,5,5,5,5,4,5,1,0,0.0,satisfied +51967,109069,Female,Loyal Customer,51,Business travel,Eco,449,2,4,4,4,5,3,4,2,2,2,2,1,2,4,11,10.0,neutral or dissatisfied +51968,28918,Male,Loyal Customer,52,Business travel,Eco,1050,3,1,1,1,2,3,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +51969,27663,Female,disloyal Customer,36,Business travel,Eco,1216,1,1,1,2,5,1,5,5,4,3,4,5,4,5,48,44.0,neutral or dissatisfied +51970,7417,Female,Loyal Customer,71,Business travel,Business,3745,4,4,4,4,3,4,4,1,5,3,2,4,1,4,123,162.0,neutral or dissatisfied +51971,64351,Female,Loyal Customer,50,Business travel,Business,1192,1,5,5,5,5,3,4,1,1,1,1,1,1,4,6,2.0,neutral or dissatisfied +51972,79780,Female,Loyal Customer,57,Personal Travel,Business,944,2,1,2,3,3,2,2,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +51973,56312,Female,Loyal Customer,41,Personal Travel,Business,200,1,2,1,4,1,4,4,4,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +51974,92227,Female,Loyal Customer,13,Personal Travel,Eco,1979,3,5,3,1,2,3,2,2,2,3,2,3,3,2,4,0.0,neutral or dissatisfied +51975,83385,Male,disloyal Customer,19,Business travel,Business,632,4,0,5,3,5,5,4,5,5,4,4,4,5,5,115,107.0,satisfied +51976,113348,Female,Loyal Customer,30,Business travel,Business,2879,3,3,3,3,4,4,4,4,5,4,4,4,5,4,7,5.0,satisfied +51977,117859,Male,Loyal Customer,55,Business travel,Business,255,3,3,3,3,2,4,4,4,4,5,4,3,4,4,1,0.0,satisfied +51978,45138,Female,disloyal Customer,30,Business travel,Eco,174,2,0,2,2,5,2,5,5,5,3,3,3,5,5,0,2.0,neutral or dissatisfied +51979,122152,Male,Loyal Customer,59,Business travel,Business,1521,3,3,3,3,4,5,4,5,5,5,5,5,5,5,25,20.0,satisfied +51980,74909,Male,disloyal Customer,28,Business travel,Business,2475,4,4,4,5,4,4,3,4,5,5,3,5,4,4,0,10.0,neutral or dissatisfied +51981,7908,Female,Loyal Customer,20,Business travel,Business,1020,3,5,5,5,3,3,3,3,3,3,4,2,3,3,65,56.0,neutral or dissatisfied +51982,72304,Female,Loyal Customer,29,Personal Travel,Eco,919,3,4,2,3,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +51983,28870,Male,Loyal Customer,51,Business travel,Eco,978,3,4,4,4,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +51984,44123,Female,disloyal Customer,27,Business travel,Eco,198,4,0,3,4,3,3,3,3,1,1,4,1,1,3,1,7.0,satisfied +51985,72757,Male,disloyal Customer,25,Business travel,Business,1045,2,4,2,3,4,2,4,4,3,4,4,3,5,4,3,7.0,neutral or dissatisfied +51986,118138,Male,Loyal Customer,44,Personal Travel,Eco,1488,3,4,3,3,3,3,3,3,4,4,5,5,4,3,28,7.0,neutral or dissatisfied +51987,44245,Female,Loyal Customer,44,Business travel,Eco,222,3,2,2,2,3,4,3,3,3,3,3,2,3,4,0,1.0,neutral or dissatisfied +51988,38197,Male,Loyal Customer,32,Business travel,Eco Plus,1220,4,2,2,2,4,4,4,4,3,3,2,1,5,4,0,0.0,satisfied +51989,37999,Male,Loyal Customer,60,Business travel,Business,1237,3,4,4,4,1,3,4,3,3,3,3,3,3,4,58,47.0,neutral or dissatisfied +51990,52432,Female,Loyal Customer,56,Personal Travel,Eco,455,2,4,2,3,5,5,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +51991,845,Male,Loyal Customer,46,Business travel,Business,3934,2,2,2,2,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +51992,119250,Female,Loyal Customer,58,Business travel,Business,3617,3,3,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +51993,67218,Male,Loyal Customer,44,Personal Travel,Eco,1121,0,4,0,3,3,0,3,3,4,3,4,5,5,3,1,0.0,satisfied +51994,58183,Female,Loyal Customer,40,Business travel,Business,925,4,4,2,4,4,4,4,5,5,5,5,3,5,3,0,6.0,satisfied +51995,10061,Male,disloyal Customer,25,Business travel,Business,596,2,0,2,2,3,2,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +51996,117520,Female,Loyal Customer,52,Business travel,Business,872,1,1,1,1,3,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +51997,21980,Female,Loyal Customer,60,Personal Travel,Eco,500,1,1,1,3,5,3,3,4,4,1,4,2,4,4,13,9.0,neutral or dissatisfied +51998,78503,Male,disloyal Customer,27,Business travel,Eco,666,3,5,3,2,2,3,2,2,1,3,3,3,5,2,13,100.0,neutral or dissatisfied +51999,59403,Male,Loyal Customer,69,Personal Travel,Eco,2447,1,0,1,3,1,1,1,1,4,2,4,3,5,1,2,0.0,neutral or dissatisfied +52000,62029,Male,disloyal Customer,15,Business travel,Eco,1390,5,5,5,2,4,5,4,4,5,4,3,5,4,4,48,42.0,satisfied +52001,99368,Male,Loyal Customer,36,Personal Travel,Eco,409,2,5,3,2,1,3,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +52002,80861,Female,Loyal Customer,67,Personal Travel,Eco,484,4,0,4,3,4,3,4,2,2,4,2,4,2,4,0,0.0,satisfied +52003,50178,Female,disloyal Customer,47,Business travel,Eco,86,4,3,5,4,1,5,1,1,3,5,1,5,4,1,0,0.0,satisfied +52004,18134,Male,Loyal Customer,62,Personal Travel,Eco Plus,120,2,2,2,3,2,2,2,2,2,1,4,2,4,2,0,23.0,neutral or dissatisfied +52005,48658,Female,Loyal Customer,42,Business travel,Business,3301,5,5,5,5,2,4,4,5,5,5,4,5,5,3,0,0.0,satisfied +52006,33585,Male,disloyal Customer,25,Business travel,Business,474,3,0,3,5,2,3,2,2,1,2,5,3,4,2,0,0.0,neutral or dissatisfied +52007,38592,Male,Loyal Customer,31,Business travel,Eco,231,4,4,4,4,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +52008,17354,Male,Loyal Customer,45,Business travel,Eco,163,2,5,5,5,2,2,2,2,4,2,4,1,3,2,32,27.0,neutral or dissatisfied +52009,397,Female,disloyal Customer,26,Business travel,Business,158,2,3,2,4,3,2,3,3,3,3,4,1,4,3,0,1.0,neutral or dissatisfied +52010,49036,Male,Loyal Customer,47,Business travel,Business,2105,0,5,0,1,1,5,5,4,4,1,1,4,4,3,43,40.0,satisfied +52011,74012,Male,Loyal Customer,60,Business travel,Business,1471,4,4,4,4,5,5,4,5,5,5,5,3,5,5,0,13.0,satisfied +52012,117467,Female,Loyal Customer,58,Business travel,Business,2494,4,4,4,4,2,4,4,4,4,5,4,5,4,4,49,44.0,satisfied +52013,703,Male,disloyal Customer,50,Business travel,Business,134,2,2,2,3,4,2,4,4,5,5,4,5,4,4,15,43.0,neutral or dissatisfied +52014,124141,Female,Loyal Customer,55,Personal Travel,Eco,529,2,5,2,3,5,5,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +52015,50233,Male,Loyal Customer,31,Business travel,Business,2572,2,2,2,2,3,3,2,3,2,2,4,4,4,3,19,33.0,neutral or dissatisfied +52016,89696,Male,Loyal Customer,45,Business travel,Business,1757,4,2,2,2,5,3,4,4,4,4,4,4,4,4,31,21.0,neutral or dissatisfied +52017,64125,Male,Loyal Customer,37,Personal Travel,Eco,2288,1,3,1,4,1,1,1,4,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +52018,8874,Female,disloyal Customer,30,Business travel,Eco,539,4,1,4,3,2,4,2,2,2,3,3,1,4,2,0,6.0,neutral or dissatisfied +52019,112741,Male,disloyal Customer,23,Business travel,Eco,671,2,2,2,5,4,2,4,4,3,3,4,3,4,4,3,0.0,neutral or dissatisfied +52020,74256,Male,Loyal Customer,27,Personal Travel,Eco,1709,4,5,4,1,5,4,5,5,1,2,4,2,3,5,0,0.0,satisfied +52021,105280,Female,Loyal Customer,13,Business travel,Business,738,5,5,5,5,3,3,3,3,4,5,5,3,4,3,0,0.0,satisfied +52022,81565,Female,Loyal Customer,33,Business travel,Business,2997,2,3,2,2,3,2,2,5,5,5,5,2,5,3,0,0.0,satisfied +52023,48873,Male,Loyal Customer,23,Business travel,Business,2794,4,5,5,5,4,3,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +52024,71783,Male,Loyal Customer,49,Business travel,Business,1723,5,5,5,5,2,3,5,4,4,4,4,3,4,5,20,11.0,satisfied +52025,83451,Male,disloyal Customer,13,Business travel,Eco,946,3,3,3,3,3,3,3,3,3,4,5,5,4,3,9,27.0,neutral or dissatisfied +52026,42474,Female,Loyal Customer,57,Business travel,Business,429,5,5,3,5,1,2,1,4,4,4,4,1,4,3,0,0.0,satisfied +52027,4818,Male,Loyal Customer,20,Business travel,Business,500,3,3,3,3,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +52028,68148,Female,disloyal Customer,41,Business travel,Business,597,3,4,4,3,5,3,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +52029,108582,Female,Loyal Customer,59,Business travel,Business,813,3,3,3,3,5,4,5,4,4,5,4,3,4,4,43,37.0,satisfied +52030,67790,Male,Loyal Customer,27,Business travel,Business,1464,4,4,4,4,5,5,5,5,4,5,4,3,5,5,14,3.0,satisfied +52031,4638,Male,Loyal Customer,55,Business travel,Business,2864,1,1,1,1,4,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +52032,16607,Female,disloyal Customer,24,Business travel,Eco,1008,4,4,4,4,5,4,5,5,2,5,4,2,4,5,114,99.0,neutral or dissatisfied +52033,52808,Male,disloyal Customer,23,Business travel,Eco,945,5,5,5,3,3,5,3,3,4,4,5,5,4,3,0,0.0,satisfied +52034,94375,Male,Loyal Customer,39,Business travel,Business,2898,0,0,0,4,3,5,5,3,3,3,3,3,3,4,8,5.0,satisfied +52035,38372,Male,Loyal Customer,10,Personal Travel,Eco,1111,2,4,2,3,2,2,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +52036,29140,Male,Loyal Customer,34,Personal Travel,Eco,1050,3,5,3,3,1,3,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +52037,74534,Female,Loyal Customer,42,Business travel,Business,1464,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +52038,6319,Female,Loyal Customer,50,Business travel,Business,1619,1,1,1,1,5,4,4,5,5,5,5,5,5,3,1,14.0,satisfied +52039,52425,Female,Loyal Customer,58,Personal Travel,Eco,598,2,4,2,5,5,4,4,4,4,2,3,4,4,4,0,20.0,neutral or dissatisfied +52040,79707,Female,Loyal Customer,54,Personal Travel,Eco,749,2,1,2,4,5,4,4,2,2,2,2,4,2,3,0,7.0,neutral or dissatisfied +52041,82340,Female,Loyal Customer,57,Business travel,Business,3903,4,4,4,4,3,4,5,4,4,4,4,5,4,3,0,18.0,satisfied +52042,67985,Female,Loyal Customer,35,Business travel,Eco Plus,1235,1,2,2,2,1,1,1,1,2,4,3,2,3,1,51,30.0,neutral or dissatisfied +52043,37376,Female,disloyal Customer,28,Business travel,Eco,1074,3,3,3,1,3,2,2,1,4,5,3,2,2,2,237,214.0,neutral or dissatisfied +52044,92330,Male,Loyal Customer,41,Business travel,Business,2556,1,1,1,1,4,4,4,3,2,4,5,4,4,4,0,11.0,satisfied +52045,73535,Female,Loyal Customer,39,Business travel,Business,3471,1,1,1,1,2,4,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +52046,118540,Female,Loyal Customer,44,Business travel,Business,1926,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,1.0,satisfied +52047,98259,Female,Loyal Customer,30,Business travel,Business,2513,3,3,3,3,3,3,3,3,1,4,2,3,2,3,0,0.0,neutral or dissatisfied +52048,32208,Female,Loyal Customer,50,Business travel,Business,3897,4,4,4,4,3,3,1,4,4,4,5,1,4,1,0,0.0,satisfied +52049,27675,Female,Loyal Customer,36,Business travel,Eco,1107,4,1,4,4,4,3,4,4,1,1,4,2,1,4,0,0.0,satisfied +52050,8029,Female,disloyal Customer,58,Business travel,Business,294,5,4,4,4,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +52051,52638,Female,Loyal Customer,52,Personal Travel,Eco,160,2,5,0,3,2,2,4,4,4,0,4,4,4,2,0,7.0,neutral or dissatisfied +52052,1195,Male,Loyal Customer,15,Personal Travel,Eco,134,2,1,2,4,4,2,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +52053,44696,Male,disloyal Customer,21,Business travel,Eco,173,1,3,1,4,3,1,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +52054,98366,Male,Loyal Customer,60,Personal Travel,Eco,1189,4,4,4,4,1,4,1,1,5,3,3,4,5,1,0,0.0,neutral or dissatisfied +52055,69764,Female,Loyal Customer,57,Personal Travel,Eco,1085,3,4,2,3,1,3,3,1,1,2,1,2,1,1,0,54.0,neutral or dissatisfied +52056,28703,Female,Loyal Customer,43,Personal Travel,Eco,2172,4,4,4,3,3,4,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +52057,68525,Male,Loyal Customer,44,Business travel,Business,3491,2,2,2,2,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +52058,23927,Female,Loyal Customer,23,Personal Travel,Eco,589,2,2,2,4,5,2,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +52059,26189,Female,disloyal Customer,21,Business travel,Eco,406,4,1,4,2,1,4,1,1,3,2,3,2,3,1,22,19.0,neutral or dissatisfied +52060,107933,Male,disloyal Customer,39,Business travel,Business,611,3,3,3,5,4,3,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +52061,40473,Male,disloyal Customer,35,Business travel,Eco,188,3,0,3,4,1,3,1,1,5,4,2,1,2,1,0,20.0,neutral or dissatisfied +52062,37608,Male,Loyal Customer,47,Personal Travel,Eco,1076,3,3,3,4,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +52063,76541,Male,Loyal Customer,38,Business travel,Business,481,3,2,2,2,4,2,3,3,3,3,3,2,3,3,0,3.0,neutral or dissatisfied +52064,24164,Female,Loyal Customer,33,Business travel,Eco,170,4,5,4,5,4,4,4,4,2,1,1,2,2,4,31,27.0,satisfied +52065,125200,Male,Loyal Customer,24,Business travel,Eco,651,5,2,2,2,5,4,2,5,2,2,4,1,4,5,2,0.0,neutral or dissatisfied +52066,102907,Female,Loyal Customer,60,Business travel,Business,3694,5,5,5,5,2,5,4,5,5,5,5,4,5,4,42,34.0,satisfied +52067,35543,Female,Loyal Customer,57,Personal Travel,Eco,1035,3,4,3,3,2,5,3,2,2,3,2,4,2,2,0,15.0,neutral or dissatisfied +52068,37092,Male,Loyal Customer,49,Business travel,Eco,1189,2,1,1,1,2,2,2,2,5,2,4,3,3,2,0,0.0,satisfied +52069,87059,Female,Loyal Customer,49,Business travel,Business,3955,3,3,3,3,5,5,4,5,5,5,5,4,5,3,59,49.0,satisfied +52070,18298,Female,Loyal Customer,63,Personal Travel,Eco,640,1,5,1,3,4,4,5,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +52071,125179,Male,Loyal Customer,40,Business travel,Business,651,2,5,5,5,4,2,3,2,2,2,2,3,2,2,8,0.0,neutral or dissatisfied +52072,129150,Female,Loyal Customer,50,Business travel,Business,679,2,2,2,2,2,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +52073,62863,Female,disloyal Customer,25,Business travel,Eco,1271,1,1,1,3,4,1,4,4,3,2,5,5,4,4,32,3.0,neutral or dissatisfied +52074,117064,Female,Loyal Customer,29,Business travel,Business,2307,2,2,4,2,3,3,3,3,3,5,5,3,4,3,8,0.0,satisfied +52075,95020,Male,Loyal Customer,65,Personal Travel,Eco,192,4,5,4,4,1,4,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +52076,122453,Male,Loyal Customer,40,Business travel,Business,1898,1,3,3,3,3,3,4,1,1,1,1,3,1,1,0,18.0,neutral or dissatisfied +52077,96875,Male,Loyal Customer,20,Personal Travel,Eco,849,3,4,3,3,2,3,2,2,3,2,4,3,5,2,0,1.0,neutral or dissatisfied +52078,88191,Female,Loyal Customer,37,Business travel,Business,2893,3,3,3,3,2,4,4,2,2,2,2,5,2,4,29,27.0,satisfied +52079,40519,Female,Loyal Customer,20,Business travel,Eco Plus,188,3,3,3,3,3,3,4,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +52080,76197,Male,disloyal Customer,9,Business travel,Eco,939,1,2,2,3,4,1,4,4,3,5,3,5,4,4,0,0.0,neutral or dissatisfied +52081,86866,Male,Loyal Customer,67,Personal Travel,Eco,484,1,0,1,3,3,1,3,3,5,4,5,1,3,3,0,0.0,neutral or dissatisfied +52082,81585,Female,Loyal Customer,41,Business travel,Business,334,2,3,2,2,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +52083,72676,Female,Loyal Customer,35,Personal Travel,Eco,1119,2,5,2,2,2,2,2,2,3,2,4,3,5,2,20,13.0,neutral or dissatisfied +52084,85049,Female,Loyal Customer,47,Business travel,Business,874,1,1,1,1,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +52085,85067,Male,Loyal Customer,58,Business travel,Business,1622,5,5,5,5,4,4,4,4,4,4,4,5,4,5,29,34.0,satisfied +52086,114531,Female,Loyal Customer,8,Personal Travel,Business,404,3,4,4,5,3,4,3,3,5,2,5,4,4,3,9,12.0,neutral or dissatisfied +52087,20932,Female,disloyal Customer,42,Business travel,Eco,721,4,4,4,3,4,4,2,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +52088,68595,Male,Loyal Customer,36,Personal Travel,Eco Plus,1616,3,5,3,4,2,3,2,2,4,3,3,5,5,2,2,0.0,neutral or dissatisfied +52089,51804,Male,Loyal Customer,65,Personal Travel,Eco,370,4,4,4,4,5,4,5,5,2,3,3,2,3,5,0,0.0,satisfied +52090,78948,Male,disloyal Customer,22,Business travel,Eco,226,3,0,3,2,3,3,3,3,4,4,5,4,5,3,21,25.0,neutral or dissatisfied +52091,71354,Female,Loyal Customer,56,Business travel,Business,258,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +52092,49149,Female,Loyal Customer,50,Business travel,Eco,109,4,1,1,1,2,3,1,4,4,4,4,1,4,2,15,21.0,satisfied +52093,101283,Male,Loyal Customer,48,Business travel,Business,2264,2,2,2,2,2,2,3,2,2,2,2,1,2,4,11,14.0,neutral or dissatisfied +52094,21643,Female,Loyal Customer,53,Personal Travel,Eco,853,1,5,1,5,2,1,2,1,1,1,5,1,1,5,0,0.0,neutral or dissatisfied +52095,103059,Female,Loyal Customer,49,Business travel,Business,2493,1,3,4,3,3,3,3,1,1,1,1,3,1,1,23,12.0,neutral or dissatisfied +52096,58976,Male,Loyal Customer,51,Business travel,Business,1726,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +52097,4977,Female,Loyal Customer,48,Business travel,Business,502,2,2,4,2,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +52098,6320,Male,disloyal Customer,27,Business travel,Business,315,4,3,3,3,4,3,1,4,4,2,4,3,4,4,55,49.0,satisfied +52099,100201,Male,Loyal Customer,37,Business travel,Eco Plus,325,5,5,3,3,5,4,5,5,2,5,3,1,3,5,91,89.0,neutral or dissatisfied +52100,121303,Male,Loyal Customer,25,Business travel,Business,1669,2,2,2,2,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +52101,101544,Male,Loyal Customer,66,Personal Travel,Eco,345,4,3,4,4,2,4,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +52102,61471,Male,disloyal Customer,11,Business travel,Eco,2419,3,3,3,4,4,3,4,4,2,2,4,2,4,4,8,0.0,neutral or dissatisfied +52103,2323,Female,Loyal Customer,30,Personal Travel,Eco,690,2,4,1,1,4,1,4,4,5,5,5,3,4,4,21,8.0,neutral or dissatisfied +52104,70305,Female,Loyal Customer,56,Business travel,Business,2622,4,4,4,4,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +52105,94231,Female,Loyal Customer,43,Business travel,Business,1858,2,2,2,2,2,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +52106,8152,Male,Loyal Customer,58,Business travel,Business,2011,0,4,0,1,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +52107,109703,Male,Loyal Customer,60,Business travel,Business,1510,3,3,2,3,5,4,5,3,3,4,3,4,3,4,2,0.0,satisfied +52108,70906,Female,Loyal Customer,11,Personal Travel,Eco,1721,2,1,2,3,4,2,2,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +52109,99329,Male,Loyal Customer,66,Personal Travel,Eco,337,3,5,3,5,1,3,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +52110,31251,Male,Loyal Customer,68,Personal Travel,Eco,524,4,1,4,4,5,4,5,5,3,3,4,3,4,5,14,19.0,neutral or dissatisfied +52111,67867,Male,Loyal Customer,50,Personal Travel,Eco,1235,3,5,3,4,4,3,3,4,1,5,3,5,3,4,0,0.0,neutral or dissatisfied +52112,105378,Male,Loyal Customer,17,Business travel,Business,3322,3,5,5,5,3,3,3,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +52113,19054,Female,Loyal Customer,51,Business travel,Business,3071,3,2,2,2,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +52114,79987,Male,Loyal Customer,9,Personal Travel,Eco,1096,3,4,3,4,1,3,1,1,4,2,4,1,4,1,0,3.0,neutral or dissatisfied +52115,124573,Male,Loyal Customer,48,Business travel,Business,1924,2,2,2,2,2,3,3,2,2,2,2,2,2,4,102,90.0,neutral or dissatisfied +52116,117108,Male,Loyal Customer,41,Business travel,Business,325,5,3,5,5,4,5,3,5,5,5,5,1,5,5,21,22.0,satisfied +52117,56365,Female,Loyal Customer,44,Personal Travel,Eco,200,2,4,2,1,3,4,5,4,4,2,4,5,4,3,9,120.0,neutral or dissatisfied +52118,56861,Female,Loyal Customer,45,Business travel,Business,2425,5,5,5,5,5,5,5,4,2,3,4,5,4,5,1,9.0,satisfied +52119,54885,Male,Loyal Customer,46,Personal Travel,Eco,862,3,4,3,3,1,3,1,1,4,2,4,4,5,1,68,52.0,neutral or dissatisfied +52120,117773,Male,Loyal Customer,31,Business travel,Business,1891,4,4,4,4,4,3,4,4,4,2,4,1,3,4,6,0.0,neutral or dissatisfied +52121,128357,Female,disloyal Customer,16,Business travel,Eco,621,5,2,5,2,4,5,4,4,5,3,4,5,5,4,0,13.0,satisfied +52122,90317,Male,disloyal Customer,20,Business travel,Eco,271,3,0,3,2,3,3,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +52123,29203,Female,Loyal Customer,39,Business travel,Business,2311,2,2,2,2,2,5,4,4,4,4,4,4,4,4,16,9.0,satisfied +52124,39424,Female,Loyal Customer,33,Business travel,Business,129,4,1,4,4,1,1,2,5,5,5,4,3,5,5,0,0.0,satisfied +52125,39455,Female,Loyal Customer,45,Personal Travel,Eco,129,1,2,1,3,3,1,3,4,4,1,4,3,4,2,0,13.0,neutral or dissatisfied +52126,22672,Male,disloyal Customer,39,Business travel,Eco,589,1,0,1,1,4,1,4,4,2,1,1,3,5,4,0,,neutral or dissatisfied +52127,100977,Male,Loyal Customer,47,Business travel,Business,1524,3,3,3,3,2,5,5,3,3,3,3,4,3,5,6,0.0,satisfied +52128,48730,Male,Loyal Customer,47,Business travel,Business,3405,3,3,3,3,3,5,5,4,4,4,4,5,4,3,34,28.0,satisfied +52129,89417,Male,Loyal Customer,25,Business travel,Business,134,0,4,0,3,4,4,4,4,5,2,4,5,5,4,8,0.0,satisfied +52130,31987,Female,Loyal Customer,47,Personal Travel,Business,102,2,2,2,3,1,3,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +52131,52133,Male,Loyal Customer,52,Business travel,Business,3356,4,4,5,4,5,5,4,4,4,4,4,3,4,4,102,94.0,satisfied +52132,104356,Female,Loyal Customer,33,Personal Travel,Eco Plus,409,2,4,2,3,2,2,2,2,2,4,3,1,4,2,6,17.0,neutral or dissatisfied +52133,17783,Male,Loyal Customer,41,Business travel,Eco,1075,2,1,1,1,2,2,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +52134,114536,Male,Loyal Customer,46,Personal Travel,Business,447,3,5,3,1,2,4,5,2,2,3,2,4,2,4,13,10.0,neutral or dissatisfied +52135,17374,Male,disloyal Customer,38,Business travel,Eco,637,2,0,2,3,3,2,3,3,2,4,5,2,3,3,0,22.0,neutral or dissatisfied +52136,92141,Male,Loyal Customer,43,Personal Travel,Eco,1532,3,5,3,2,5,3,5,5,3,2,5,5,4,5,5,0.0,neutral or dissatisfied +52137,77423,Male,Loyal Customer,27,Personal Travel,Eco,590,3,3,3,5,4,3,4,4,1,5,4,2,4,4,0,0.0,neutral or dissatisfied +52138,88613,Female,Loyal Customer,37,Personal Travel,Eco,545,4,5,4,1,1,4,1,1,1,5,1,1,1,1,48,58.0,neutral or dissatisfied +52139,34388,Female,Loyal Customer,25,Business travel,Business,728,4,1,4,1,4,4,4,4,4,3,3,3,4,4,6,3.0,neutral or dissatisfied +52140,86557,Female,Loyal Customer,25,Business travel,Business,2337,2,2,2,2,5,5,5,5,4,2,5,4,4,5,5,0.0,satisfied +52141,25208,Female,Loyal Customer,44,Business travel,Business,919,4,4,4,4,5,5,3,4,4,4,4,2,4,3,18,22.0,satisfied +52142,26082,Female,Loyal Customer,42,Business travel,Eco,591,3,5,5,5,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +52143,111688,Male,disloyal Customer,26,Business travel,Business,495,2,2,2,4,1,2,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +52144,45829,Female,Loyal Customer,27,Personal Travel,Eco,216,1,0,1,1,5,1,3,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +52145,34966,Male,disloyal Customer,18,Business travel,Eco,273,2,1,2,3,2,2,1,2,4,2,3,3,4,2,25,21.0,neutral or dissatisfied +52146,12016,Female,Loyal Customer,54,Business travel,Eco,376,5,1,1,1,5,1,3,5,5,5,5,2,5,4,42,39.0,satisfied +52147,38859,Female,Loyal Customer,65,Personal Travel,Eco Plus,2153,1,5,1,5,5,5,5,2,2,1,1,3,2,4,0,3.0,neutral or dissatisfied +52148,93893,Female,Loyal Customer,15,Personal Travel,Eco,588,2,5,2,3,2,2,2,2,4,2,5,4,5,2,7,14.0,neutral or dissatisfied +52149,125624,Female,Loyal Customer,48,Business travel,Business,2299,4,4,4,4,3,5,4,5,5,5,5,3,5,4,4,0.0,satisfied +52150,50548,Male,Loyal Customer,16,Personal Travel,Eco,153,4,4,4,2,2,4,3,2,4,4,4,4,4,2,0,0.0,satisfied +52151,43140,Female,Loyal Customer,26,Personal Travel,Eco Plus,236,4,5,4,1,4,4,4,4,5,2,4,5,5,4,21,21.0,neutral or dissatisfied +52152,34945,Female,Loyal Customer,7,Personal Travel,Eco,395,3,5,3,4,2,3,2,2,5,4,5,3,5,2,0,14.0,neutral or dissatisfied +52153,54590,Male,Loyal Customer,26,Business travel,Business,3058,3,3,3,3,4,4,4,4,4,2,5,4,5,4,8,5.0,satisfied +52154,91547,Female,Loyal Customer,16,Business travel,Business,3750,3,3,3,3,3,2,3,3,1,1,4,4,4,3,92,90.0,neutral or dissatisfied +52155,40465,Male,disloyal Customer,27,Business travel,Eco,188,3,1,3,4,2,3,2,2,1,3,4,4,3,2,0,0.0,neutral or dissatisfied +52156,68439,Female,Loyal Customer,68,Personal Travel,Eco Plus,1045,2,4,2,3,3,5,2,5,5,2,5,2,5,5,0,10.0,neutral or dissatisfied +52157,67656,Female,Loyal Customer,41,Business travel,Business,1235,2,1,1,1,2,2,1,2,2,2,2,3,2,2,49,36.0,neutral or dissatisfied +52158,76474,Female,Loyal Customer,26,Business travel,Business,2365,3,3,3,3,2,2,2,2,4,4,4,4,5,2,0,0.0,satisfied +52159,102128,Male,Loyal Customer,27,Business travel,Business,1579,4,2,2,2,4,4,4,4,2,1,3,1,4,4,3,0.0,neutral or dissatisfied +52160,67191,Female,Loyal Customer,21,Personal Travel,Eco,929,3,5,3,4,1,3,2,1,5,5,4,5,5,1,72,67.0,neutral or dissatisfied +52161,9585,Female,disloyal Customer,36,Business travel,Eco,288,1,2,1,3,2,1,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +52162,120108,Male,Loyal Customer,30,Business travel,Business,1576,3,3,3,3,3,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +52163,124910,Female,Loyal Customer,56,Business travel,Business,728,1,1,1,1,3,5,4,4,4,4,4,4,4,3,0,3.0,satisfied +52164,95406,Male,Loyal Customer,45,Personal Travel,Eco,239,2,2,2,3,4,2,4,4,4,3,4,1,3,4,8,12.0,neutral or dissatisfied +52165,74052,Male,Loyal Customer,16,Personal Travel,Eco,1194,2,4,2,1,4,2,1,4,5,4,5,3,4,4,3,13.0,neutral or dissatisfied +52166,63569,Male,Loyal Customer,51,Business travel,Business,1737,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +52167,27045,Female,Loyal Customer,38,Business travel,Business,1709,4,4,4,4,5,5,2,4,4,4,4,2,4,1,0,0.0,satisfied +52168,18103,Female,Loyal Customer,35,Personal Travel,Eco,610,1,4,1,3,3,1,3,3,5,1,1,3,3,3,0,7.0,neutral or dissatisfied +52169,56066,Male,Loyal Customer,68,Personal Travel,Eco,2586,2,2,2,2,2,3,3,4,1,2,3,3,1,3,3,16.0,neutral or dissatisfied +52170,117177,Male,Loyal Customer,66,Personal Travel,Eco,647,3,1,3,3,1,3,1,1,3,3,4,2,3,1,35,23.0,neutral or dissatisfied +52171,121054,Female,Loyal Customer,31,Personal Travel,Eco,993,1,2,1,3,5,1,5,5,4,3,4,4,3,5,0,0.0,neutral or dissatisfied +52172,104391,Female,Loyal Customer,9,Personal Travel,Eco Plus,228,3,5,3,3,3,3,3,3,2,3,5,4,5,3,42,38.0,neutral or dissatisfied +52173,11403,Female,Loyal Customer,31,Business travel,Business,216,2,2,2,2,4,4,5,4,5,4,4,3,5,4,8,9.0,satisfied +52174,36323,Female,Loyal Customer,75,Business travel,Business,187,2,5,5,5,5,4,4,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +52175,55024,Male,Loyal Customer,39,Business travel,Business,1635,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +52176,117039,Female,Loyal Customer,47,Business travel,Business,646,5,5,5,5,4,5,4,4,4,4,4,3,4,3,8,0.0,satisfied +52177,87511,Male,Loyal Customer,47,Personal Travel,Eco,373,4,4,4,4,4,2,2,3,5,5,5,2,3,2,301,294.0,neutral or dissatisfied +52178,119489,Female,Loyal Customer,51,Business travel,Business,2402,1,1,1,1,2,4,5,4,4,4,4,4,4,5,1,7.0,satisfied +52179,108294,Female,Loyal Customer,44,Personal Travel,Business,1728,3,4,3,3,2,4,4,1,1,3,1,3,1,4,15,16.0,neutral or dissatisfied +52180,60603,Male,disloyal Customer,37,Business travel,Business,991,1,1,1,3,5,1,5,5,5,4,5,4,5,5,1,0.0,neutral or dissatisfied +52181,99626,Female,Loyal Customer,29,Business travel,Business,2471,5,5,5,5,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +52182,112187,Male,Loyal Customer,14,Personal Travel,Eco,895,2,4,1,5,3,1,4,3,4,2,3,4,1,3,13,3.0,neutral or dissatisfied +52183,90848,Male,Loyal Customer,43,Business travel,Business,3079,4,5,5,5,1,3,3,4,4,4,4,2,4,2,20,11.0,neutral or dissatisfied +52184,9587,Female,disloyal Customer,20,Business travel,Eco,229,5,0,5,5,3,5,3,3,2,4,2,3,1,3,0,0.0,satisfied +52185,38362,Male,Loyal Customer,52,Personal Travel,Eco,1133,4,4,4,3,4,1,1,4,4,4,4,1,3,1,188,203.0,satisfied +52186,103884,Female,Loyal Customer,14,Personal Travel,Eco,882,2,2,2,3,1,2,1,1,1,4,3,1,4,1,0,0.0,neutral or dissatisfied +52187,98412,Male,Loyal Customer,59,Business travel,Business,675,5,5,5,5,3,5,5,4,4,4,4,5,4,4,35,30.0,satisfied +52188,18527,Male,Loyal Customer,23,Business travel,Business,201,3,3,3,3,5,5,5,5,4,3,3,3,4,5,0,0.0,satisfied +52189,94525,Female,Loyal Customer,37,Business travel,Business,2778,2,5,5,5,4,2,3,2,2,2,2,3,2,1,22,12.0,neutral or dissatisfied +52190,94855,Female,disloyal Customer,21,Business travel,Eco,562,2,0,2,4,5,2,5,5,5,2,4,4,4,5,4,0.0,neutral or dissatisfied +52191,77468,Female,Loyal Customer,53,Personal Travel,Eco,507,1,3,1,4,3,3,3,1,1,1,2,4,1,5,0,0.0,neutral or dissatisfied +52192,40666,Female,Loyal Customer,23,Business travel,Business,590,2,4,4,4,2,2,2,2,3,1,4,3,4,2,22,14.0,neutral or dissatisfied +52193,37650,Male,Loyal Customer,65,Personal Travel,Eco,1069,4,5,4,1,4,4,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +52194,129518,Male,Loyal Customer,44,Personal Travel,Eco Plus,1744,4,5,4,3,5,4,5,5,4,2,3,5,4,5,0,0.0,neutral or dissatisfied +52195,111460,Female,Loyal Customer,27,Personal Travel,Eco,836,1,4,1,4,5,1,3,5,4,2,5,4,5,5,21,34.0,neutral or dissatisfied +52196,39003,Female,Loyal Customer,35,Business travel,Business,2378,0,0,0,4,4,4,5,5,5,5,5,3,5,2,4,17.0,satisfied +52197,50453,Male,Loyal Customer,45,Business travel,Business,3446,5,5,5,5,5,2,2,5,5,5,5,5,5,5,0,0.0,satisfied +52198,33122,Female,Loyal Customer,52,Personal Travel,Eco,216,2,4,0,1,2,5,5,1,1,0,1,3,1,5,0,0.0,neutral or dissatisfied +52199,87419,Female,Loyal Customer,21,Personal Travel,Eco,425,2,0,2,5,1,2,1,1,2,2,3,1,2,1,4,0.0,neutral or dissatisfied +52200,73019,Male,Loyal Customer,39,Personal Travel,Eco,1035,1,4,1,2,1,1,1,1,4,2,4,3,4,1,0,2.0,neutral or dissatisfied +52201,101092,Male,Loyal Customer,33,Business travel,Business,3941,2,2,2,2,5,5,5,5,3,5,5,4,5,5,28,17.0,satisfied +52202,58711,Male,Loyal Customer,59,Business travel,Business,606,5,5,5,5,3,5,5,4,4,5,4,3,4,4,6,0.0,satisfied +52203,52680,Female,Loyal Customer,54,Personal Travel,Eco,119,0,4,0,3,1,3,2,1,1,0,3,1,1,3,0,0.0,satisfied +52204,105633,Male,Loyal Customer,43,Business travel,Business,925,5,5,5,5,5,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +52205,53030,Male,Loyal Customer,35,Business travel,Eco,1190,5,2,2,2,5,5,5,5,1,2,5,5,2,5,9,0.0,satisfied +52206,92260,Female,Loyal Customer,9,Personal Travel,Eco,1670,1,3,1,3,1,1,1,1,2,3,4,2,4,1,118,103.0,neutral or dissatisfied +52207,116061,Female,Loyal Customer,14,Personal Travel,Eco,373,3,4,3,2,1,3,2,1,4,3,3,2,5,1,0,0.0,neutral or dissatisfied +52208,82431,Male,Loyal Customer,46,Business travel,Business,502,4,4,4,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +52209,16486,Male,Loyal Customer,50,Business travel,Business,2934,2,2,4,2,5,1,2,4,4,4,4,1,4,5,31,24.0,satisfied +52210,43307,Female,Loyal Customer,40,Business travel,Eco,387,4,4,2,4,4,4,4,4,1,2,5,4,5,4,8,0.0,satisfied +52211,49208,Female,Loyal Customer,39,Business travel,Business,373,1,1,2,1,5,1,2,4,4,4,4,2,4,4,1,11.0,satisfied +52212,63440,Male,Loyal Customer,15,Personal Travel,Eco,447,4,2,4,4,5,4,5,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +52213,84105,Female,Loyal Customer,54,Business travel,Business,2036,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +52214,102872,Female,Loyal Customer,27,Business travel,Eco,472,2,2,2,2,2,2,2,2,1,4,4,2,1,2,244,239.0,neutral or dissatisfied +52215,3946,Male,Loyal Customer,41,Business travel,Business,765,4,1,4,4,5,4,4,4,4,4,4,3,4,5,9,113.0,satisfied +52216,43861,Female,Loyal Customer,35,Business travel,Business,255,2,2,3,2,5,4,4,5,5,5,5,1,5,2,0,4.0,satisfied +52217,117273,Female,Loyal Customer,16,Personal Travel,Eco,368,3,4,3,5,4,3,1,4,3,3,1,1,1,4,11,4.0,neutral or dissatisfied +52218,128522,Male,Loyal Customer,18,Personal Travel,Eco,651,3,3,3,3,3,3,1,3,3,4,3,1,1,3,11,22.0,neutral or dissatisfied +52219,72237,Male,disloyal Customer,23,Business travel,Eco,919,2,2,2,5,3,2,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +52220,61790,Male,Loyal Customer,7,Personal Travel,Eco,1609,4,2,4,3,4,4,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +52221,128461,Male,Loyal Customer,34,Personal Travel,Eco,651,2,3,2,3,2,2,2,2,3,3,4,3,3,2,112,108.0,neutral or dissatisfied +52222,118541,Male,Loyal Customer,39,Business travel,Eco,325,2,1,2,1,2,2,2,2,2,4,3,1,3,2,0,1.0,neutral or dissatisfied +52223,43056,Male,Loyal Customer,59,Business travel,Business,1599,2,3,3,3,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +52224,110487,Female,Loyal Customer,46,Personal Travel,Eco,883,2,3,2,4,2,3,4,4,4,2,4,4,4,5,0,9.0,neutral or dissatisfied +52225,102684,Male,Loyal Customer,52,Business travel,Business,3537,3,5,5,5,5,3,2,3,3,3,3,1,3,2,12,6.0,neutral or dissatisfied +52226,2287,Female,Loyal Customer,48,Business travel,Business,693,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +52227,98321,Female,Loyal Customer,37,Personal Travel,Eco,1547,1,1,1,3,3,1,5,3,2,2,3,1,3,3,87,93.0,neutral or dissatisfied +52228,45327,Female,disloyal Customer,25,Business travel,Eco,222,1,1,1,4,5,1,5,5,2,1,3,1,4,5,0,0.0,neutral or dissatisfied +52229,19158,Female,disloyal Customer,44,Business travel,Eco,304,2,2,2,3,3,2,3,3,4,4,4,1,4,3,33,16.0,neutral or dissatisfied +52230,35857,Male,Loyal Customer,25,Business travel,Business,1023,1,2,2,2,1,1,1,1,3,3,2,3,2,1,12,13.0,neutral or dissatisfied +52231,13626,Female,Loyal Customer,41,Business travel,Eco,1014,4,3,1,3,5,4,5,5,5,2,5,5,2,5,61,123.0,satisfied +52232,129159,Female,Loyal Customer,48,Business travel,Business,954,1,1,5,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +52233,2978,Male,Loyal Customer,40,Business travel,Business,3085,1,2,2,2,2,2,2,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +52234,97912,Female,Loyal Customer,15,Business travel,Business,1613,2,1,1,1,2,3,2,2,1,4,4,1,4,2,53,45.0,neutral or dissatisfied +52235,11055,Male,Loyal Customer,65,Personal Travel,Eco,316,2,1,2,3,5,2,5,5,2,1,3,2,3,5,0,0.0,neutral or dissatisfied +52236,25308,Female,disloyal Customer,30,Business travel,Eco,432,3,4,3,3,5,3,5,5,4,2,4,1,4,5,56,73.0,neutral or dissatisfied +52237,40146,Female,Loyal Customer,61,Personal Travel,Eco,840,2,5,2,3,3,5,4,1,1,2,1,3,1,4,93,97.0,neutral or dissatisfied +52238,27806,Male,Loyal Customer,39,Business travel,Business,1448,3,4,3,3,2,2,1,3,3,3,3,1,3,4,88,87.0,neutral or dissatisfied +52239,52293,Female,Loyal Customer,36,Business travel,Business,3760,4,4,4,4,3,4,2,3,3,4,3,5,3,4,0,,satisfied +52240,46995,Female,disloyal Customer,49,Business travel,Eco Plus,846,4,4,4,4,4,4,4,4,3,3,4,3,3,4,9,2.0,neutral or dissatisfied +52241,33292,Female,Loyal Customer,47,Personal Travel,Eco Plus,101,4,4,4,3,3,5,5,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +52242,125768,Female,Loyal Customer,30,Business travel,Business,2047,4,4,4,4,4,5,4,4,5,2,4,3,4,4,2,2.0,satisfied +52243,92149,Female,Loyal Customer,55,Business travel,Eco Plus,1532,1,1,1,1,1,3,3,1,1,1,1,1,1,2,4,6.0,neutral or dissatisfied +52244,69678,Male,Loyal Customer,21,Personal Travel,Eco,569,1,5,1,5,1,1,1,1,4,3,3,2,1,1,0,0.0,neutral or dissatisfied +52245,12583,Male,Loyal Customer,43,Business travel,Eco,542,2,4,4,4,2,2,2,2,2,4,4,5,1,2,0,0.0,satisfied +52246,113287,Female,Loyal Customer,38,Business travel,Business,386,2,2,2,2,2,4,4,5,5,5,5,3,5,4,9,9.0,satisfied +52247,73810,Female,Loyal Customer,35,Personal Travel,Eco Plus,192,3,4,3,4,2,3,2,2,3,3,5,4,5,2,6,5.0,neutral or dissatisfied +52248,57389,Female,Loyal Customer,31,Business travel,Business,1861,4,4,4,4,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +52249,115211,Female,Loyal Customer,57,Business travel,Eco,296,3,1,1,1,2,3,2,4,4,3,4,1,4,1,1,0.0,neutral or dissatisfied +52250,11095,Female,Loyal Customer,44,Personal Travel,Eco,224,3,4,0,2,4,4,4,5,5,0,4,5,5,5,33,24.0,neutral or dissatisfied +52251,15784,Male,Loyal Customer,69,Personal Travel,Eco,198,2,4,2,4,2,2,2,2,5,5,5,4,4,2,10,0.0,neutral or dissatisfied +52252,44430,Female,Loyal Customer,45,Business travel,Business,542,1,2,2,2,5,3,4,1,1,1,1,4,1,2,74,59.0,neutral or dissatisfied +52253,21314,Female,Loyal Customer,42,Personal Travel,Eco,620,2,5,2,3,2,4,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +52254,88495,Female,disloyal Customer,37,Business travel,Eco,444,3,5,3,4,1,3,1,1,4,3,4,1,4,1,5,0.0,neutral or dissatisfied +52255,11157,Male,Loyal Customer,58,Personal Travel,Eco,667,3,4,3,4,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +52256,38610,Male,Loyal Customer,38,Personal Travel,Eco,231,0,5,0,3,1,0,1,1,5,3,4,3,4,1,0,0.0,satisfied +52257,90090,Male,disloyal Customer,29,Business travel,Eco,957,3,3,3,4,1,3,1,1,1,4,3,4,3,1,0,0.0,neutral or dissatisfied +52258,105206,Female,Loyal Customer,27,Business travel,Business,1670,3,1,1,1,3,2,3,3,3,5,1,4,2,3,1,12.0,neutral or dissatisfied +52259,92312,Female,Loyal Customer,32,Business travel,Business,2556,1,4,1,1,5,5,5,5,4,5,5,3,5,5,5,0.0,satisfied +52260,112608,Male,Loyal Customer,35,Business travel,Business,3066,2,1,1,1,3,3,4,2,2,2,2,3,2,3,9,0.0,neutral or dissatisfied +52261,30844,Female,Loyal Customer,21,Business travel,Business,3869,3,3,3,3,3,3,3,3,4,2,3,3,3,3,27,16.0,neutral or dissatisfied +52262,29493,Female,disloyal Customer,28,Business travel,Eco,1107,3,2,2,4,3,2,3,3,2,1,2,3,3,3,0,0.0,neutral or dissatisfied +52263,75876,Male,disloyal Customer,23,Business travel,Eco,1972,2,2,2,2,3,2,2,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +52264,122236,Female,disloyal Customer,29,Business travel,Eco,546,2,2,2,3,2,2,2,2,3,1,4,3,3,2,0,0.0,neutral or dissatisfied +52265,82799,Female,Loyal Customer,55,Business travel,Business,235,3,3,3,3,3,5,5,5,5,5,5,3,5,3,12,2.0,satisfied +52266,1320,Male,Loyal Customer,54,Business travel,Business,3561,1,1,1,1,5,5,4,3,3,4,4,3,3,3,0,0.0,satisfied +52267,29702,Male,Loyal Customer,44,Personal Travel,Eco,1542,2,5,2,2,2,2,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +52268,99775,Female,Loyal Customer,28,Business travel,Business,632,4,4,3,4,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +52269,123320,Male,Loyal Customer,27,Business travel,Eco Plus,507,2,4,4,4,2,2,2,2,3,2,3,2,3,2,2,0.0,neutral or dissatisfied +52270,108099,Male,Loyal Customer,60,Business travel,Business,849,5,5,5,5,2,5,5,4,4,4,4,4,4,3,75,60.0,satisfied +52271,126519,Female,Loyal Customer,58,Business travel,Business,3262,3,3,3,3,4,5,4,4,4,4,5,4,4,3,1,0.0,satisfied +52272,110460,Female,Loyal Customer,20,Personal Travel,Eco,919,1,4,1,4,4,1,4,4,2,2,3,1,4,4,5,0.0,neutral or dissatisfied +52273,86311,Female,Loyal Customer,51,Business travel,Business,226,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,5.0,satisfied +52274,56621,Male,disloyal Customer,25,Business travel,Business,937,1,0,2,2,3,2,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +52275,79969,Female,Loyal Customer,26,Business travel,Eco,950,2,5,5,5,2,3,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +52276,90154,Male,disloyal Customer,37,Business travel,Eco,745,3,3,3,4,5,3,5,5,2,5,3,3,3,5,92,68.0,neutral or dissatisfied +52277,126833,Female,disloyal Customer,23,Business travel,Eco,1008,3,3,3,3,4,3,4,4,4,4,4,1,4,4,7,0.0,neutral or dissatisfied +52278,16685,Female,disloyal Customer,10,Business travel,Eco,488,3,2,3,4,3,3,3,3,1,5,3,1,3,3,93,63.0,neutral or dissatisfied +52279,85007,Female,Loyal Customer,48,Business travel,Business,1590,4,5,4,4,4,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +52280,85094,Male,disloyal Customer,24,Business travel,Eco,874,1,1,1,3,2,1,2,2,4,3,4,4,5,2,4,0.0,neutral or dissatisfied +52281,117281,Male,Loyal Customer,53,Business travel,Business,3907,1,1,4,1,3,4,4,4,4,4,4,3,4,4,88,63.0,satisfied +52282,121854,Male,Loyal Customer,39,Business travel,Business,337,3,3,3,3,5,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +52283,97019,Female,Loyal Customer,50,Business travel,Business,775,1,1,1,1,3,5,4,4,4,4,4,4,4,3,14,26.0,satisfied +52284,24104,Male,disloyal Customer,30,Business travel,Eco,779,1,2,2,1,5,2,5,5,3,1,3,1,3,5,30,34.0,neutral or dissatisfied +52285,29956,Male,Loyal Customer,36,Business travel,Business,2111,0,0,0,1,2,4,3,1,1,1,1,5,1,3,0,0.0,satisfied +52286,49159,Female,Loyal Customer,60,Business travel,Eco,372,4,1,1,1,5,4,3,4,4,4,4,2,4,2,0,9.0,satisfied +52287,26668,Male,Loyal Customer,46,Business travel,Business,2070,0,3,0,4,5,2,2,2,2,2,2,5,2,4,0,0.0,satisfied +52288,55883,Female,disloyal Customer,25,Business travel,Business,723,1,5,0,4,2,0,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +52289,17761,Male,Loyal Customer,35,Personal Travel,Eco Plus,456,2,4,2,1,3,2,3,3,3,2,5,4,4,3,62,81.0,neutral or dissatisfied +52290,73490,Male,Loyal Customer,8,Personal Travel,Eco,1197,3,1,3,2,2,3,2,2,3,5,1,2,1,2,1,0.0,neutral or dissatisfied +52291,100557,Female,disloyal Customer,36,Business travel,Eco Plus,711,2,2,2,3,3,2,3,3,2,2,3,2,4,3,24,9.0,neutral or dissatisfied +52292,17198,Female,Loyal Customer,21,Business travel,Business,694,2,2,2,2,4,5,4,4,4,2,2,5,3,4,0,0.0,satisfied +52293,64871,Male,Loyal Customer,39,Business travel,Eco,247,3,5,5,5,3,3,3,3,2,1,4,3,3,3,0,0.0,neutral or dissatisfied +52294,73103,Female,Loyal Customer,43,Business travel,Business,2174,3,3,3,3,4,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +52295,72923,Female,Loyal Customer,28,Business travel,Business,1096,2,2,2,2,2,2,2,2,3,4,5,4,5,2,0,0.0,satisfied +52296,26880,Female,Loyal Customer,24,Business travel,Eco,689,4,3,3,3,4,4,5,4,3,1,3,5,3,4,0,0.0,satisfied +52297,29486,Male,Loyal Customer,40,Business travel,Business,3017,2,1,5,1,4,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +52298,71611,Male,Loyal Customer,46,Business travel,Eco,1182,2,4,3,4,2,2,2,2,4,1,1,1,2,2,12,20.0,neutral or dissatisfied +52299,112294,Female,Loyal Customer,53,Business travel,Eco Plus,1506,3,5,5,5,1,3,4,3,3,3,3,2,3,4,26,14.0,neutral or dissatisfied +52300,111915,Male,Loyal Customer,48,Business travel,Business,3459,4,4,4,4,3,4,5,5,5,5,5,4,5,3,6,5.0,satisfied +52301,39430,Male,Loyal Customer,66,Business travel,Eco,129,5,1,1,1,5,5,5,5,5,1,3,5,4,5,0,1.0,satisfied +52302,106750,Male,Loyal Customer,39,Business travel,Business,437,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,4.0,satisfied +52303,92259,Female,Loyal Customer,37,Personal Travel,Eco,1670,4,4,4,2,4,4,4,4,3,4,2,3,3,4,26,17.0,neutral or dissatisfied +52304,30696,Female,Loyal Customer,30,Business travel,Business,680,3,3,3,3,4,4,4,4,4,2,1,4,3,4,0,1.0,satisfied +52305,103228,Female,Loyal Customer,28,Personal Travel,Eco,351,1,2,1,2,2,1,2,2,3,5,2,1,2,2,11,0.0,neutral or dissatisfied +52306,30440,Male,disloyal Customer,27,Business travel,Eco,914,3,3,3,3,5,3,5,5,4,3,5,2,1,5,0,0.0,neutral or dissatisfied +52307,86916,Female,Loyal Customer,36,Personal Travel,Eco,341,0,3,0,1,1,0,4,1,2,5,1,3,4,1,0,0.0,satisfied +52308,78111,Male,Loyal Customer,57,Business travel,Business,1619,4,4,4,4,5,3,5,3,3,4,3,5,3,3,0,0.0,satisfied +52309,70141,Female,Loyal Customer,64,Personal Travel,Eco,550,1,0,1,5,4,5,5,1,1,1,1,3,1,3,4,0.0,neutral or dissatisfied +52310,44312,Male,Loyal Customer,51,Business travel,Business,305,1,1,4,1,4,3,5,5,5,5,5,3,5,1,3,0.0,satisfied +52311,29294,Female,Loyal Customer,33,Business travel,Business,834,3,1,1,1,4,3,3,3,3,3,3,1,3,2,0,8.0,neutral or dissatisfied +52312,20583,Male,Loyal Customer,21,Personal Travel,Eco,633,2,5,2,4,2,2,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +52313,101073,Male,Loyal Customer,32,Business travel,Business,1069,2,2,2,2,4,4,4,4,5,3,4,4,4,4,9,0.0,satisfied +52314,103208,Male,Loyal Customer,63,Personal Travel,Eco,1482,2,5,1,4,3,1,3,3,3,2,4,4,4,3,13,3.0,neutral or dissatisfied +52315,85320,Female,Loyal Customer,32,Personal Travel,Eco,813,3,1,3,4,3,3,3,3,1,1,4,4,3,3,18,0.0,neutral or dissatisfied +52316,44385,Female,Loyal Customer,20,Personal Travel,Business,323,4,3,4,2,2,4,4,2,5,4,2,3,5,2,15,22.0,satisfied +52317,40386,Male,Loyal Customer,53,Business travel,Eco Plus,1250,3,3,3,3,3,3,3,3,4,3,5,2,4,3,11,0.0,satisfied +52318,73494,Male,Loyal Customer,39,Personal Travel,Eco,1182,2,5,3,2,2,3,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +52319,114676,Male,Loyal Customer,64,Business travel,Business,1995,2,2,2,2,4,4,5,5,5,5,5,3,5,4,37,36.0,satisfied +52320,97017,Male,Loyal Customer,51,Personal Travel,Eco,775,2,4,2,3,2,2,2,2,3,5,1,2,4,2,0,0.0,neutral or dissatisfied +52321,80407,Male,Loyal Customer,41,Business travel,Eco,1416,1,4,4,4,1,1,1,1,3,4,2,3,1,1,93,80.0,neutral or dissatisfied +52322,116778,Male,Loyal Customer,25,Personal Travel,Eco Plus,358,0,4,0,3,4,0,4,4,5,4,5,5,4,4,0,0.0,satisfied +52323,70359,Female,Loyal Customer,52,Business travel,Eco,1145,3,2,2,2,3,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +52324,31887,Male,disloyal Customer,27,Business travel,Business,2762,3,2,2,2,5,2,5,5,2,2,2,2,3,5,0,0.0,neutral or dissatisfied +52325,27971,Female,Loyal Customer,15,Personal Travel,Eco,1616,4,4,4,2,2,4,2,2,4,5,5,4,4,2,0,13.0,neutral or dissatisfied +52326,66917,Male,Loyal Customer,54,Business travel,Business,1770,2,2,2,2,5,5,4,5,5,4,5,5,5,3,5,8.0,satisfied +52327,24889,Male,Loyal Customer,39,Business travel,Business,3721,2,2,2,2,1,5,4,5,5,5,5,1,5,2,0,0.0,satisfied +52328,40311,Male,Loyal Customer,63,Personal Travel,Eco,347,3,5,3,3,2,3,2,2,5,3,5,1,5,2,11,6.0,neutral or dissatisfied +52329,51222,Female,disloyal Customer,23,Business travel,Business,447,3,1,3,3,1,3,1,1,4,5,4,1,3,1,7,3.0,neutral or dissatisfied +52330,5753,Male,disloyal Customer,48,Business travel,Business,859,1,1,1,2,4,1,4,4,4,5,5,5,4,4,0,20.0,neutral or dissatisfied +52331,84576,Male,Loyal Customer,45,Business travel,Business,1572,4,4,4,4,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +52332,77990,Female,Loyal Customer,42,Business travel,Business,332,0,0,0,4,3,4,4,2,2,2,2,4,2,5,20,24.0,satisfied +52333,93752,Female,Loyal Customer,16,Business travel,Business,3455,3,4,1,4,3,3,3,3,2,1,4,2,4,3,39,33.0,neutral or dissatisfied +52334,55970,Male,Loyal Customer,38,Business travel,Business,3854,3,5,5,5,5,4,4,3,3,3,3,2,3,4,25,29.0,neutral or dissatisfied +52335,66342,Female,Loyal Customer,29,Business travel,Business,2460,5,5,5,5,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +52336,56424,Male,Loyal Customer,56,Business travel,Business,719,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +52337,128493,Female,Loyal Customer,51,Personal Travel,Eco,325,5,5,5,3,3,1,4,2,2,5,2,3,2,1,0,0.0,satisfied +52338,45481,Male,disloyal Customer,49,Business travel,Eco,674,2,2,2,2,2,2,2,2,2,2,5,4,2,2,0,0.0,neutral or dissatisfied +52339,128421,Male,disloyal Customer,41,Business travel,Eco,304,3,1,3,3,5,3,5,5,1,4,4,4,3,5,4,0.0,neutral or dissatisfied +52340,42211,Male,Loyal Customer,46,Business travel,Business,784,1,2,2,2,5,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +52341,49807,Female,Loyal Customer,39,Business travel,Business,278,2,3,3,3,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +52342,68739,Male,Loyal Customer,72,Business travel,Business,2507,1,1,5,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +52343,123684,Male,Loyal Customer,40,Business travel,Eco,214,4,4,4,4,4,4,4,4,5,1,1,1,3,4,0,0.0,satisfied +52344,82527,Male,Loyal Customer,60,Personal Travel,Eco,1749,3,1,3,3,4,3,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +52345,121249,Female,disloyal Customer,40,Business travel,Business,2075,3,3,3,1,4,3,4,4,3,3,3,3,4,4,26,4.0,neutral or dissatisfied +52346,78482,Male,Loyal Customer,51,Business travel,Business,1914,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +52347,85421,Male,Loyal Customer,35,Business travel,Business,3550,0,0,0,3,5,5,5,4,4,4,4,3,4,4,41,38.0,satisfied +52348,19302,Male,Loyal Customer,50,Personal Travel,Eco,299,3,4,3,4,5,3,1,5,4,2,5,5,5,5,0,29.0,neutral or dissatisfied +52349,32607,Female,Loyal Customer,51,Business travel,Business,2190,3,1,1,1,5,4,3,2,2,2,3,4,2,2,0,4.0,neutral or dissatisfied +52350,81307,Female,Loyal Customer,36,Business travel,Business,2769,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +52351,104488,Female,disloyal Customer,25,Business travel,Eco,860,4,4,4,4,4,4,5,4,1,3,3,2,3,4,0,0.0,neutral or dissatisfied +52352,42374,Female,Loyal Customer,8,Personal Travel,Eco,726,2,5,2,4,1,2,1,1,4,3,1,5,5,1,0,0.0,neutral or dissatisfied +52353,21676,Female,Loyal Customer,48,Business travel,Eco,746,5,4,4,4,5,5,5,2,2,5,4,5,1,5,205,196.0,satisfied +52354,68736,Female,Loyal Customer,40,Business travel,Business,3799,2,2,2,2,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +52355,73551,Male,Loyal Customer,47,Business travel,Eco Plus,594,2,2,2,2,3,2,3,3,4,4,3,3,4,3,12,11.0,neutral or dissatisfied +52356,14365,Female,Loyal Customer,62,Personal Travel,Eco,948,3,3,3,2,5,3,3,2,2,3,2,2,2,2,0,7.0,neutral or dissatisfied +52357,57157,Male,Loyal Customer,32,Business travel,Business,1824,4,1,1,1,4,3,4,4,1,3,3,4,3,4,15,2.0,neutral or dissatisfied +52358,60333,Female,disloyal Customer,25,Business travel,Eco,836,3,3,3,4,2,3,2,2,4,2,3,2,3,2,19,13.0,neutral or dissatisfied +52359,4000,Female,disloyal Customer,59,Business travel,Business,483,3,3,3,1,1,3,1,1,4,5,5,5,5,1,125,120.0,neutral or dissatisfied +52360,94700,Male,Loyal Customer,57,Business travel,Eco,277,1,0,0,4,3,1,3,3,4,4,4,4,4,3,1,9.0,neutral or dissatisfied +52361,6440,Female,Loyal Customer,27,Personal Travel,Eco,240,1,4,1,3,3,1,3,3,3,4,5,5,5,3,25,33.0,neutral or dissatisfied +52362,108673,Female,Loyal Customer,48,Business travel,Business,177,2,5,5,5,4,3,3,2,2,2,2,3,2,3,58,55.0,neutral or dissatisfied +52363,51690,Female,Loyal Customer,47,Business travel,Eco,198,4,5,5,5,2,3,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +52364,29473,Female,Loyal Customer,56,Business travel,Business,1107,2,4,4,4,5,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +52365,85075,Male,disloyal Customer,36,Business travel,Business,874,1,0,0,5,2,0,4,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +52366,25785,Male,disloyal Customer,40,Business travel,Eco,762,2,2,2,1,4,2,4,4,4,2,2,3,4,4,1,0.0,neutral or dissatisfied +52367,82262,Female,Loyal Customer,47,Business travel,Business,1481,4,4,4,4,3,5,4,4,4,4,4,4,4,3,12,14.0,satisfied +52368,16708,Male,Loyal Customer,56,Business travel,Business,284,3,5,5,5,2,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +52369,114479,Male,Loyal Customer,34,Business travel,Business,2903,2,2,2,2,2,4,4,2,2,2,2,2,2,3,3,5.0,neutral or dissatisfied +52370,111,Female,Loyal Customer,39,Business travel,Business,2046,2,2,2,2,3,5,5,4,4,5,4,5,4,3,104,122.0,satisfied +52371,30425,Male,disloyal Customer,39,Business travel,Eco,614,2,3,3,4,2,3,2,2,1,1,4,2,4,2,14,7.0,neutral or dissatisfied +52372,57202,Female,disloyal Customer,28,Business travel,Business,1514,1,1,1,5,1,1,1,1,4,5,4,3,4,1,4,0.0,neutral or dissatisfied +52373,64203,Male,Loyal Customer,16,Personal Travel,Eco,853,3,4,3,5,3,3,3,3,5,2,5,5,4,3,12,21.0,neutral or dissatisfied +52374,117216,Female,Loyal Customer,60,Personal Travel,Eco,370,1,5,1,2,3,5,1,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +52375,57758,Female,Loyal Customer,45,Business travel,Business,2704,1,1,1,1,3,3,3,4,3,3,5,3,3,3,0,0.0,satisfied +52376,41743,Male,Loyal Customer,47,Personal Travel,Eco,700,3,4,3,4,3,3,4,3,4,2,4,5,1,3,0,0.0,neutral or dissatisfied +52377,58324,Female,disloyal Customer,20,Business travel,Eco,239,4,1,4,4,4,4,4,4,2,3,4,2,3,4,57,39.0,neutral or dissatisfied +52378,125380,Male,Loyal Customer,43,Business travel,Business,1440,3,3,4,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +52379,117544,Male,Loyal Customer,52,Business travel,Business,2914,5,5,5,5,4,4,5,4,4,4,4,4,4,3,14,0.0,satisfied +52380,113458,Female,disloyal Customer,20,Business travel,Eco,197,4,0,5,4,4,5,4,4,5,4,4,3,5,4,4,1.0,satisfied +52381,17422,Male,Loyal Customer,18,Business travel,Business,3769,2,4,4,4,2,2,2,2,1,4,3,3,4,2,122,106.0,neutral or dissatisfied +52382,28390,Male,Loyal Customer,27,Personal Travel,Eco,763,2,4,3,4,4,3,2,4,5,3,4,5,4,4,0,10.0,neutral or dissatisfied +52383,69292,Male,Loyal Customer,62,Business travel,Eco Plus,733,4,4,4,4,4,4,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +52384,128240,Male,Loyal Customer,52,Personal Travel,Eco,602,3,1,3,4,2,3,2,2,2,2,3,3,3,2,10,8.0,neutral or dissatisfied +52385,89048,Female,disloyal Customer,28,Business travel,Business,2139,1,1,1,3,3,1,3,3,5,4,4,5,4,3,4,0.0,neutral or dissatisfied +52386,26564,Male,Loyal Customer,39,Business travel,Business,406,2,5,2,5,4,2,2,2,2,2,2,3,2,4,23,17.0,neutral or dissatisfied +52387,87852,Female,Loyal Customer,59,Personal Travel,Eco,214,4,2,0,2,0,2,2,1,2,3,3,2,1,2,198,206.0,neutral or dissatisfied +52388,35723,Female,Loyal Customer,63,Business travel,Eco Plus,2465,4,1,1,1,4,4,4,3,5,4,1,4,3,4,0,0.0,satisfied +52389,76477,Male,Loyal Customer,60,Business travel,Business,2030,2,2,2,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +52390,64951,Male,Loyal Customer,25,Business travel,Business,190,1,2,4,4,2,2,1,2,4,3,4,4,3,2,0,0.0,neutral or dissatisfied +52391,92315,Female,Loyal Customer,59,Business travel,Business,2556,4,4,4,4,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +52392,108881,Female,disloyal Customer,22,Business travel,Eco,1183,2,2,2,2,3,2,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +52393,18658,Male,Loyal Customer,9,Personal Travel,Eco,201,3,1,3,2,4,3,2,4,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +52394,10552,Male,Loyal Customer,36,Business travel,Business,3118,2,2,2,2,2,5,5,5,5,5,5,3,5,3,20,39.0,satisfied +52395,9295,Male,Loyal Customer,42,Business travel,Eco Plus,1157,2,5,3,5,2,2,2,2,1,4,3,3,3,2,0,21.0,neutral or dissatisfied +52396,90451,Male,Loyal Customer,32,Business travel,Eco,240,4,4,4,4,4,4,4,4,1,2,3,3,4,4,0,35.0,neutral or dissatisfied +52397,44332,Male,Loyal Customer,55,Business travel,Eco,230,5,2,2,2,5,5,5,5,2,2,4,2,3,5,0,0.0,satisfied +52398,16464,Male,Loyal Customer,70,Personal Travel,Eco,529,2,4,2,4,4,2,4,4,5,3,5,3,5,4,101,76.0,neutral or dissatisfied +52399,113858,Female,disloyal Customer,34,Business travel,Eco,1214,2,2,2,4,5,2,5,5,2,3,3,4,4,5,5,11.0,neutral or dissatisfied +52400,92244,Female,disloyal Customer,34,Business travel,Eco,760,1,1,1,4,4,1,2,4,4,4,4,3,4,4,6,29.0,neutral or dissatisfied +52401,16968,Female,Loyal Customer,8,Personal Travel,Eco,195,2,4,2,2,5,2,5,5,2,1,3,2,4,5,0,0.0,neutral or dissatisfied +52402,114440,Female,Loyal Customer,68,Business travel,Business,325,4,4,2,4,3,4,4,4,4,3,4,1,4,3,35,24.0,neutral or dissatisfied +52403,71902,Female,Loyal Customer,16,Personal Travel,Eco,1744,3,4,4,3,5,4,5,5,2,4,3,2,4,5,3,12.0,neutral or dissatisfied +52404,88914,Female,Loyal Customer,58,Personal Travel,Eco,859,2,4,2,2,2,5,4,5,5,2,5,3,5,4,0,17.0,neutral or dissatisfied +52405,129644,Male,Loyal Customer,48,Business travel,Business,2336,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,2.0,satisfied +52406,114872,Male,Loyal Customer,43,Business travel,Business,1763,5,5,5,5,5,5,5,3,2,5,5,5,5,5,226,255.0,satisfied +52407,46383,Male,Loyal Customer,51,Business travel,Eco,1013,3,1,1,1,3,3,3,3,2,5,3,3,3,3,30,19.0,neutral or dissatisfied +52408,103307,Male,disloyal Customer,24,Business travel,Business,1371,0,4,0,3,2,0,2,2,3,2,5,3,4,2,0,5.0,satisfied +52409,88019,Female,disloyal Customer,38,Business travel,Business,406,2,2,2,2,1,2,1,1,4,2,4,3,5,1,0,5.0,neutral or dissatisfied +52410,402,Male,Loyal Customer,42,Business travel,Business,3824,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +52411,12221,Female,Loyal Customer,69,Personal Travel,Business,201,2,4,2,2,3,1,1,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +52412,5146,Female,Loyal Customer,47,Business travel,Eco,622,3,2,5,2,2,3,4,2,2,3,2,2,2,3,85,97.0,neutral or dissatisfied +52413,57707,Male,Loyal Customer,10,Personal Travel,Eco,867,3,5,2,2,2,2,2,2,5,2,5,4,5,2,0,3.0,neutral or dissatisfied +52414,87966,Female,Loyal Customer,36,Business travel,Business,271,0,0,0,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +52415,115835,Male,Loyal Customer,44,Business travel,Eco,480,5,4,4,4,5,5,5,5,2,5,3,3,4,5,0,3.0,satisfied +52416,81473,Male,disloyal Customer,11,Business travel,Eco,528,4,4,4,3,2,4,2,2,1,4,4,2,3,2,94,86.0,neutral or dissatisfied +52417,52267,Female,Loyal Customer,9,Business travel,Eco,651,2,2,2,2,2,2,2,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +52418,119662,Female,Loyal Customer,76,Business travel,Eco,107,2,5,5,5,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +52419,21569,Female,disloyal Customer,36,Business travel,Eco Plus,331,4,4,4,3,3,4,3,3,5,4,3,4,3,3,1,0.0,neutral or dissatisfied +52420,81764,Female,Loyal Customer,41,Business travel,Business,3050,4,4,4,4,5,5,5,4,4,4,4,4,4,3,8,0.0,satisfied +52421,57207,Female,Loyal Customer,53,Business travel,Business,1514,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +52422,35900,Male,Loyal Customer,40,Personal Travel,Eco Plus,937,4,4,4,3,1,4,1,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +52423,127485,Male,Loyal Customer,46,Business travel,Business,1536,3,3,3,3,4,1,1,5,5,5,5,4,5,2,0,0.0,satisfied +52424,112181,Female,Loyal Customer,35,Personal Travel,Eco,895,2,2,2,3,3,2,3,3,3,3,2,4,2,3,18,1.0,neutral or dissatisfied +52425,47689,Female,Loyal Customer,38,Personal Travel,Eco,1482,3,1,3,4,3,3,5,3,1,1,3,2,4,3,23,14.0,neutral or dissatisfied +52426,71840,Male,disloyal Customer,11,Business travel,Business,1829,4,0,4,2,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +52427,24876,Female,Loyal Customer,17,Personal Travel,Eco Plus,356,3,4,3,2,5,3,5,5,3,5,4,3,5,5,0,11.0,neutral or dissatisfied +52428,42150,Female,Loyal Customer,12,Personal Travel,Business,451,3,5,3,2,3,3,3,3,1,1,3,4,1,3,0,0.0,neutral or dissatisfied +52429,12345,Female,Loyal Customer,37,Business travel,Business,1721,1,1,1,1,4,1,2,4,4,4,5,5,4,2,0,0.0,satisfied +52430,103470,Female,Loyal Customer,41,Business travel,Business,2159,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +52431,96363,Female,Loyal Customer,34,Business travel,Business,1407,3,3,3,3,3,5,4,3,3,2,3,5,3,4,0,0.0,satisfied +52432,23675,Male,disloyal Customer,21,Business travel,Eco,251,0,0,0,4,2,0,3,2,5,1,3,3,1,2,0,0.0,satisfied +52433,69517,Female,Loyal Customer,23,Business travel,Business,2475,2,2,2,2,4,4,4,4,3,2,4,5,4,4,14,0.0,satisfied +52434,119175,Male,Loyal Customer,50,Business travel,Business,331,5,5,5,5,5,4,4,5,5,5,5,5,5,3,8,43.0,satisfied +52435,67468,Male,Loyal Customer,18,Personal Travel,Eco,678,2,5,2,1,5,2,5,5,4,5,5,4,4,5,17,22.0,neutral or dissatisfied +52436,73766,Male,Loyal Customer,35,Personal Travel,Eco,192,3,3,3,3,3,3,3,3,4,2,5,4,2,3,0,10.0,neutral or dissatisfied +52437,18070,Female,Loyal Customer,21,Personal Travel,Eco,605,2,2,2,3,2,2,2,2,3,1,3,1,3,2,95,90.0,neutral or dissatisfied +52438,6925,Female,Loyal Customer,49,Business travel,Business,265,3,3,4,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +52439,44802,Female,Loyal Customer,28,Business travel,Eco,802,0,0,0,1,2,0,3,2,2,1,3,4,3,2,2,0.0,satisfied +52440,78361,Male,Loyal Customer,24,Business travel,Business,726,1,0,0,4,4,0,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +52441,67624,Male,disloyal Customer,24,Business travel,Business,1188,4,0,4,1,5,4,1,5,4,4,4,4,4,5,0,0.0,satisfied +52442,96301,Male,Loyal Customer,34,Business travel,Business,546,4,4,4,4,5,4,4,5,5,5,5,3,5,5,2,2.0,satisfied +52443,91792,Male,Loyal Customer,39,Personal Travel,Eco,588,4,4,4,5,4,4,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +52444,66175,Male,Loyal Customer,46,Business travel,Business,3493,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +52445,34284,Female,Loyal Customer,22,Business travel,Business,2890,3,3,3,3,5,5,5,5,3,5,5,4,2,5,2,0.0,satisfied +52446,46729,Female,Loyal Customer,63,Personal Travel,Eco,125,3,4,0,3,3,2,1,1,1,0,1,2,1,4,0,0.0,neutral or dissatisfied +52447,92836,Female,Loyal Customer,37,Personal Travel,Eco,1541,1,5,1,2,2,1,2,2,3,5,5,5,5,2,1,10.0,neutral or dissatisfied +52448,69490,Female,Loyal Customer,19,Business travel,Eco Plus,1096,2,4,4,4,2,2,1,2,3,4,1,1,2,2,11,35.0,neutral or dissatisfied +52449,68532,Male,disloyal Customer,21,Business travel,Eco,1013,2,2,2,4,1,2,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +52450,93083,Male,Loyal Customer,41,Business travel,Eco,860,2,1,1,1,2,2,2,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +52451,16636,Male,Loyal Customer,23,Business travel,Eco,488,5,5,5,5,5,5,3,5,1,2,1,5,2,5,67,44.0,satisfied +52452,13099,Male,Loyal Customer,44,Business travel,Business,2783,1,1,1,1,4,2,2,5,5,5,5,4,5,1,0,0.0,satisfied +52453,82146,Male,Loyal Customer,58,Business travel,Business,237,0,1,1,2,4,5,5,5,5,5,5,4,5,4,52,60.0,satisfied +52454,82885,Male,disloyal Customer,27,Business travel,Eco,194,4,0,4,2,2,4,2,2,4,1,3,1,1,2,3,0.0,neutral or dissatisfied +52455,121367,Female,Loyal Customer,64,Personal Travel,Eco,1670,3,4,3,4,1,3,1,4,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +52456,19014,Male,Loyal Customer,33,Business travel,Business,3218,2,5,5,5,2,2,2,2,4,1,3,3,3,2,0,23.0,neutral or dissatisfied +52457,115780,Female,Loyal Customer,41,Business travel,Business,3729,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +52458,121231,Male,Loyal Customer,33,Business travel,Business,2075,3,3,3,3,4,5,4,4,5,5,3,5,4,4,0,0.0,satisfied +52459,68687,Female,Loyal Customer,57,Personal Travel,Eco,237,3,4,3,3,3,1,1,4,3,5,4,1,3,1,207,240.0,neutral or dissatisfied +52460,52841,Male,Loyal Customer,39,Business travel,Business,1918,3,3,1,3,4,2,2,5,5,5,5,3,5,3,0,0.0,satisfied +52461,100689,Male,Loyal Customer,44,Personal Travel,Eco,889,3,5,3,5,4,3,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +52462,638,Female,Loyal Customer,40,Business travel,Business,3123,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +52463,55720,Female,disloyal Customer,26,Business travel,Business,895,5,5,5,4,4,5,4,4,3,5,4,3,4,4,3,0.0,satisfied +52464,33675,Female,Loyal Customer,59,Business travel,Business,2738,1,1,4,1,4,4,4,4,4,4,4,3,4,3,44,60.0,satisfied +52465,38658,Male,Loyal Customer,46,Business travel,Business,2611,2,1,1,1,1,2,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +52466,62605,Male,Loyal Customer,48,Personal Travel,Eco,1846,5,4,5,4,1,5,1,1,4,5,2,3,3,1,0,0.0,satisfied +52467,110682,Male,Loyal Customer,36,Personal Travel,Eco,829,4,4,4,1,5,4,5,5,5,3,5,3,5,5,6,10.0,neutral or dissatisfied +52468,119737,Male,Loyal Customer,50,Personal Travel,Eco,1303,3,4,3,4,1,3,1,1,5,4,4,5,4,1,6,4.0,neutral or dissatisfied +52469,104038,Female,Loyal Customer,22,Business travel,Business,1262,2,5,2,2,2,3,2,2,2,3,2,3,3,2,0,0.0,neutral or dissatisfied +52470,46236,Male,Loyal Customer,22,Business travel,Business,752,3,1,1,1,3,3,3,3,2,2,4,3,3,3,4,5.0,neutral or dissatisfied +52471,28588,Male,Loyal Customer,48,Personal Travel,Eco,2562,2,4,2,3,1,2,5,1,4,1,2,3,4,1,0,0.0,neutral or dissatisfied +52472,80456,Male,Loyal Customer,39,Business travel,Business,1694,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +52473,78102,Female,Loyal Customer,39,Personal Travel,Eco,684,3,4,3,4,2,3,2,2,3,3,3,1,4,2,7,0.0,neutral or dissatisfied +52474,61248,Male,disloyal Customer,23,Business travel,Eco,462,0,5,0,4,4,0,4,4,1,1,5,3,4,4,61,46.0,satisfied +52475,100134,Female,Loyal Customer,44,Business travel,Business,3628,2,2,2,2,5,5,5,5,5,5,5,4,5,5,6,0.0,satisfied +52476,6629,Male,Loyal Customer,46,Personal Travel,Eco,719,4,4,4,1,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +52477,114402,Female,disloyal Customer,36,Business travel,Business,308,3,3,3,5,1,3,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +52478,19315,Female,Loyal Customer,64,Business travel,Eco,743,5,1,2,1,3,3,4,5,5,5,5,5,5,1,0,0.0,satisfied +52479,3802,Male,disloyal Customer,50,Business travel,Business,650,2,2,2,3,2,2,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +52480,91823,Male,disloyal Customer,21,Business travel,Eco,590,4,2,4,4,4,4,3,4,3,3,5,3,5,4,0,0.0,satisfied +52481,19728,Male,Loyal Customer,48,Personal Travel,Eco,409,1,3,1,4,1,1,1,1,1,1,4,4,3,1,1,0.0,neutral or dissatisfied +52482,111614,Male,Loyal Customer,41,Business travel,Business,1692,1,1,4,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +52483,124626,Female,Loyal Customer,22,Personal Travel,Eco,1671,2,5,2,4,2,2,2,2,2,2,1,1,2,2,10,0.0,neutral or dissatisfied +52484,4572,Female,Loyal Customer,62,Personal Travel,Eco Plus,561,3,2,3,2,2,2,2,1,1,3,1,3,1,1,0,7.0,neutral or dissatisfied +52485,106286,Male,Loyal Customer,19,Personal Travel,Eco,604,3,5,3,3,3,3,3,3,5,4,5,3,4,3,4,0.0,neutral or dissatisfied +52486,59283,Male,disloyal Customer,27,Business travel,Eco,918,5,5,5,3,5,1,1,5,3,3,4,1,1,1,0,0.0,satisfied +52487,124679,Female,disloyal Customer,61,Business travel,Eco,399,1,4,1,4,5,1,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +52488,112359,Male,disloyal Customer,16,Business travel,Eco,862,2,3,3,4,4,3,2,4,3,4,5,5,5,4,0,1.0,neutral or dissatisfied +52489,129628,Female,Loyal Customer,53,Business travel,Business,3193,1,1,1,1,5,5,4,4,4,3,4,5,4,4,0,0.0,satisfied +52490,57455,Female,Loyal Customer,30,Business travel,Business,3084,3,3,3,3,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +52491,104278,Male,Loyal Customer,65,Personal Travel,Eco,1733,4,5,5,3,4,5,4,4,2,3,4,4,4,4,0,0.0,satisfied +52492,91602,Female,Loyal Customer,43,Business travel,Business,1352,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +52493,109885,Female,Loyal Customer,31,Business travel,Business,3851,1,4,4,4,1,1,1,1,1,2,4,4,4,1,28,25.0,neutral or dissatisfied +52494,58489,Female,disloyal Customer,30,Business travel,Eco,719,1,1,1,4,2,1,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +52495,74099,Female,Loyal Customer,43,Business travel,Business,3651,4,4,4,4,4,5,4,4,4,3,4,5,4,4,4,7.0,satisfied +52496,71303,Male,Loyal Customer,21,Personal Travel,Business,1514,3,4,3,3,3,3,3,3,5,2,5,4,5,3,0,5.0,neutral or dissatisfied +52497,56273,Male,Loyal Customer,61,Personal Travel,Eco Plus,404,2,4,2,2,4,2,3,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +52498,60306,Male,Loyal Customer,48,Business travel,Business,1601,4,4,3,4,4,4,4,5,4,4,5,4,3,4,258,251.0,satisfied +52499,69932,Male,Loyal Customer,67,Personal Travel,Eco Plus,1514,1,4,1,3,2,1,2,2,3,5,3,5,4,2,0,0.0,neutral or dissatisfied +52500,106837,Male,Loyal Customer,53,Business travel,Business,1733,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +52501,34308,Male,Loyal Customer,53,Personal Travel,Eco,280,4,5,4,3,2,4,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +52502,68163,Female,Loyal Customer,55,Business travel,Business,2706,1,1,1,1,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +52503,6406,Female,Loyal Customer,19,Personal Travel,Eco,315,1,4,1,2,2,1,2,2,3,2,5,4,4,2,30,17.0,neutral or dissatisfied +52504,89081,Male,Loyal Customer,44,Business travel,Business,1947,3,3,3,3,5,3,4,5,5,5,5,5,5,3,0,25.0,satisfied +52505,118718,Female,Loyal Customer,65,Personal Travel,Eco,451,4,5,4,3,3,5,4,1,1,4,5,3,1,5,83,84.0,neutral or dissatisfied +52506,84217,Male,Loyal Customer,79,Business travel,Eco,432,4,3,3,3,4,4,4,1,3,2,3,4,1,4,136,125.0,neutral or dissatisfied +52507,79680,Male,Loyal Customer,55,Personal Travel,Eco,760,2,5,1,5,5,1,5,5,3,2,4,5,4,5,9,11.0,neutral or dissatisfied +52508,116769,Male,Loyal Customer,56,Personal Travel,Eco Plus,373,3,3,3,4,2,3,5,2,3,4,2,5,1,2,16,6.0,neutral or dissatisfied +52509,114768,Female,Loyal Customer,44,Business travel,Business,2669,3,3,3,3,2,4,4,4,4,4,4,4,4,4,50,38.0,satisfied +52510,106085,Female,disloyal Customer,40,Business travel,Business,302,2,2,2,3,4,2,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +52511,23288,Male,Loyal Customer,24,Business travel,Eco,641,5,4,5,4,5,5,5,5,2,2,1,5,5,5,0,0.0,satisfied +52512,87949,Female,Loyal Customer,13,Personal Travel,Business,223,2,5,0,5,3,0,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +52513,44237,Female,disloyal Customer,22,Business travel,Business,235,5,3,5,3,2,5,2,2,1,1,4,3,5,2,0,0.0,satisfied +52514,20673,Female,Loyal Customer,54,Business travel,Eco,552,3,4,4,4,1,4,4,4,4,3,4,4,4,2,70,68.0,neutral or dissatisfied +52515,36462,Female,Loyal Customer,70,Personal Travel,Eco,867,3,5,3,2,1,3,5,3,3,3,3,5,3,1,0,0.0,neutral or dissatisfied +52516,51854,Female,disloyal Customer,37,Business travel,Eco,438,3,0,3,1,5,3,5,5,2,5,5,1,1,5,0,0.0,neutral or dissatisfied +52517,21591,Female,disloyal Customer,44,Business travel,Eco,780,3,3,3,3,2,3,2,2,5,5,2,3,5,2,30,22.0,neutral or dissatisfied +52518,94912,Male,Loyal Customer,52,Business travel,Business,3201,2,2,2,2,1,1,5,5,5,4,3,5,5,3,10,19.0,satisfied +52519,57151,Female,Loyal Customer,39,Business travel,Business,1824,5,1,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +52520,60884,Male,Loyal Customer,24,Business travel,Business,3944,2,4,4,4,2,2,2,2,4,1,4,4,4,2,0,2.0,neutral or dissatisfied +52521,89770,Female,Loyal Customer,41,Personal Travel,Eco,1076,2,5,2,1,2,3,1,5,2,5,5,1,4,1,446,431.0,neutral or dissatisfied +52522,34359,Female,Loyal Customer,31,Business travel,Business,3690,1,1,1,1,1,1,1,1,3,4,3,3,2,1,15,3.0,neutral or dissatisfied +52523,100219,Male,Loyal Customer,30,Personal Travel,Eco Plus,762,4,5,4,4,3,4,3,3,4,5,3,2,5,3,11,14.0,neutral or dissatisfied +52524,62295,Female,Loyal Customer,47,Business travel,Business,2551,2,3,3,3,2,2,1,2,2,2,2,3,2,2,11,17.0,neutral or dissatisfied +52525,31407,Male,disloyal Customer,26,Business travel,Eco,1546,5,5,5,3,4,5,4,4,1,1,2,5,1,4,0,2.0,satisfied +52526,98604,Female,Loyal Customer,60,Business travel,Business,861,5,5,5,5,2,5,5,5,5,4,5,4,5,3,20,0.0,satisfied +52527,14382,Female,Loyal Customer,41,Business travel,Eco,789,2,2,2,2,2,2,2,2,4,5,2,4,2,2,0,0.0,neutral or dissatisfied +52528,77563,Female,Loyal Customer,44,Business travel,Business,3764,4,5,4,4,3,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +52529,34394,Female,disloyal Customer,29,Business travel,Eco,612,2,3,2,4,3,2,1,3,5,3,1,4,3,3,98,91.0,neutral or dissatisfied +52530,61342,Male,Loyal Customer,40,Business travel,Business,3208,1,1,1,1,5,5,5,4,4,4,4,5,4,3,47,43.0,satisfied +52531,122843,Male,Loyal Customer,49,Business travel,Business,3133,0,0,0,2,3,4,5,3,3,3,3,3,3,4,0,1.0,satisfied +52532,25714,Male,disloyal Customer,25,Business travel,Eco,447,3,0,3,1,5,3,4,5,3,3,3,2,4,5,21,23.0,neutral or dissatisfied +52533,1251,Male,Loyal Customer,28,Personal Travel,Eco,113,3,1,3,3,2,3,2,2,3,2,2,1,2,2,12,12.0,neutral or dissatisfied +52534,95910,Female,Loyal Customer,38,Business travel,Eco Plus,180,5,2,2,2,5,5,5,5,3,2,1,5,4,5,2,0.0,satisfied +52535,35864,Male,Loyal Customer,11,Personal Travel,Eco,1065,2,4,2,4,1,2,1,1,3,2,5,5,5,1,0,23.0,neutral or dissatisfied +52536,109968,Female,Loyal Customer,36,Personal Travel,Eco,1052,3,5,3,2,5,3,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +52537,97243,Male,Loyal Customer,58,Business travel,Business,2577,3,5,5,5,5,2,2,3,3,3,3,2,3,2,22,33.0,neutral or dissatisfied +52538,43256,Female,Loyal Customer,53,Business travel,Business,3047,4,4,4,4,4,5,2,4,4,4,4,2,4,3,0,0.0,satisfied +52539,5561,Male,Loyal Customer,52,Business travel,Business,3627,2,5,5,5,4,2,3,2,2,2,2,3,2,4,0,8.0,neutral or dissatisfied +52540,119766,Male,Loyal Customer,57,Business travel,Business,936,2,2,2,2,3,4,5,1,1,2,1,4,1,5,12,10.0,satisfied +52541,70542,Male,Loyal Customer,26,Business travel,Business,1258,1,1,1,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +52542,128770,Male,Loyal Customer,26,Personal Travel,Eco,550,2,3,2,1,4,2,4,4,5,5,3,3,5,4,0,4.0,neutral or dissatisfied +52543,10719,Female,disloyal Customer,26,Business travel,Business,316,3,0,3,1,4,3,5,4,5,3,5,3,5,4,12,9.0,neutral or dissatisfied +52544,14422,Male,Loyal Customer,65,Personal Travel,Eco,693,3,5,3,4,5,3,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +52545,21518,Male,Loyal Customer,18,Personal Travel,Eco,399,3,4,3,3,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +52546,40788,Female,Loyal Customer,43,Business travel,Eco,584,4,1,1,1,3,2,5,4,4,4,4,4,4,2,0,0.0,satisfied +52547,63027,Male,disloyal Customer,20,Business travel,Eco,862,5,4,4,1,3,4,3,3,4,4,5,3,5,3,1,0.0,satisfied +52548,10827,Male,disloyal Customer,16,Business travel,Eco,482,4,2,5,3,3,5,3,3,1,2,4,1,3,3,33,30.0,neutral or dissatisfied +52549,124031,Male,Loyal Customer,23,Personal Travel,Eco,184,3,5,0,4,2,0,1,2,5,4,1,5,1,2,0,0.0,neutral or dissatisfied +52550,15222,Male,disloyal Customer,39,Business travel,Eco,416,3,5,3,4,5,3,5,5,5,4,3,5,1,5,0,20.0,neutral or dissatisfied +52551,82093,Female,Loyal Customer,46,Business travel,Eco,1276,2,5,5,5,4,4,4,2,2,2,2,1,2,4,0,15.0,neutral or dissatisfied +52552,90458,Male,Loyal Customer,50,Business travel,Business,3727,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,5.0,satisfied +52553,55640,Female,Loyal Customer,41,Personal Travel,Eco,563,2,4,3,1,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +52554,35076,Male,Loyal Customer,14,Personal Travel,Business,972,3,5,3,4,1,3,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +52555,127980,Female,disloyal Customer,29,Business travel,Business,1149,2,3,3,2,4,3,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +52556,122186,Male,Loyal Customer,44,Business travel,Business,646,4,4,4,4,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +52557,106334,Male,Loyal Customer,16,Personal Travel,Eco,825,2,4,2,4,2,2,2,2,4,5,4,3,5,2,1,42.0,neutral or dissatisfied +52558,78721,Male,Loyal Customer,23,Business travel,Business,2639,5,5,5,5,4,4,4,4,5,3,4,5,4,4,20,7.0,satisfied +52559,87083,Male,Loyal Customer,59,Business travel,Eco,594,2,1,1,1,2,2,2,2,2,5,3,2,2,2,0,0.0,neutral or dissatisfied +52560,58735,Female,Loyal Customer,24,Business travel,Business,1005,5,5,5,5,4,4,4,4,4,2,5,5,5,4,12,12.0,satisfied +52561,93430,Female,Loyal Customer,59,Business travel,Business,697,4,4,4,4,2,5,4,5,5,5,5,3,5,4,100,85.0,satisfied +52562,51931,Male,Loyal Customer,27,Business travel,Business,2665,1,1,2,1,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +52563,109554,Female,Loyal Customer,41,Personal Travel,Eco,920,3,2,3,3,3,3,3,3,3,1,3,3,2,3,0,0.0,neutral or dissatisfied +52564,31977,Female,Loyal Customer,52,Business travel,Business,102,5,5,5,5,3,5,5,5,5,5,5,5,5,4,26,21.0,satisfied +52565,69389,Female,Loyal Customer,32,Business travel,Business,2024,4,4,4,4,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +52566,109586,Female,Loyal Customer,26,Business travel,Business,1937,4,4,4,4,4,4,4,4,5,4,5,5,4,4,49,50.0,satisfied +52567,99235,Female,Loyal Customer,26,Business travel,Eco,541,2,5,5,5,2,2,3,2,2,5,4,1,3,2,0,11.0,neutral or dissatisfied +52568,19506,Male,Loyal Customer,30,Business travel,Business,2801,4,4,4,4,5,4,5,5,3,1,4,1,2,5,60,,satisfied +52569,84808,Male,disloyal Customer,38,Business travel,Business,481,4,4,4,5,1,4,1,1,5,3,4,4,5,1,4,0.0,neutral or dissatisfied +52570,23294,Male,Loyal Customer,61,Business travel,Business,3074,2,2,2,2,2,3,3,4,4,4,4,5,4,4,29,29.0,satisfied +52571,129864,Female,Loyal Customer,39,Business travel,Business,2747,1,1,5,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +52572,96947,Male,Loyal Customer,52,Business travel,Business,2471,3,3,3,3,3,4,5,5,5,5,5,3,5,4,80,58.0,satisfied +52573,26862,Female,disloyal Customer,59,Business travel,Eco Plus,224,2,2,2,3,3,2,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +52574,9992,Male,Loyal Customer,12,Personal Travel,Eco,357,4,5,4,1,1,4,1,1,3,5,5,4,1,1,40,38.0,neutral or dissatisfied +52575,66006,Female,Loyal Customer,50,Business travel,Business,1345,1,5,1,1,3,5,5,5,5,5,5,5,5,3,3,0.0,satisfied +52576,45904,Male,disloyal Customer,23,Business travel,Eco,794,2,2,2,4,1,2,1,1,1,4,3,2,3,1,46,30.0,neutral or dissatisfied +52577,91687,Female,Loyal Customer,39,Business travel,Business,599,1,2,2,2,1,2,2,1,1,1,1,3,1,2,11,9.0,neutral or dissatisfied +52578,2369,Female,Loyal Customer,53,Personal Travel,Eco,925,3,5,3,2,5,4,4,2,2,3,2,4,2,5,29,9.0,neutral or dissatisfied +52579,101768,Male,Loyal Customer,53,Business travel,Business,1590,2,2,2,2,2,4,4,4,4,4,4,3,4,3,10,0.0,satisfied +52580,19759,Female,Loyal Customer,30,Business travel,Eco,462,1,1,1,1,1,1,1,1,4,1,3,3,3,1,61,64.0,neutral or dissatisfied +52581,67873,Male,Loyal Customer,32,Personal Travel,Eco,1205,3,4,3,4,4,3,4,4,5,5,2,5,5,4,59,36.0,neutral or dissatisfied +52582,17737,Female,disloyal Customer,37,Business travel,Eco,529,2,2,2,3,4,2,4,4,2,1,4,2,3,4,0,0.0,neutral or dissatisfied +52583,48162,Female,Loyal Customer,30,Business travel,Business,192,2,4,4,4,3,3,2,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +52584,29369,Male,Loyal Customer,23,Business travel,Business,2355,5,1,5,5,4,4,4,4,1,5,5,2,2,4,0,0.0,satisfied +52585,40452,Female,Loyal Customer,38,Business travel,Eco,150,4,3,3,3,4,4,4,4,3,4,2,2,2,4,0,0.0,satisfied +52586,4256,Male,Loyal Customer,54,Business travel,Business,502,5,5,5,5,3,5,5,4,4,4,4,4,4,5,5,31.0,satisfied +52587,32035,Male,disloyal Customer,24,Business travel,Eco,101,3,0,3,4,5,3,5,5,3,3,1,4,5,5,0,0.0,neutral or dissatisfied +52588,24585,Male,Loyal Customer,46,Business travel,Business,2516,1,1,1,1,2,1,4,5,5,5,5,1,5,3,0,21.0,satisfied +52589,70333,Female,Loyal Customer,39,Business travel,Business,2618,1,2,1,1,4,4,5,5,5,5,5,3,5,3,37,30.0,satisfied +52590,58295,Female,disloyal Customer,23,Business travel,Eco,413,5,0,5,2,1,5,1,1,4,2,5,5,4,1,3,16.0,satisfied +52591,124349,Female,Loyal Customer,57,Personal Travel,Business,575,4,4,4,2,5,5,5,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +52592,108114,Female,disloyal Customer,7,Business travel,Eco,849,1,2,2,2,2,2,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +52593,123005,Female,Loyal Customer,60,Business travel,Business,2602,3,3,3,3,2,5,5,4,4,4,4,5,4,5,22,23.0,satisfied +52594,73771,Male,Loyal Customer,51,Personal Travel,Eco,192,3,4,3,3,2,3,2,2,2,4,4,4,4,2,0,11.0,neutral or dissatisfied +52595,36336,Female,Loyal Customer,59,Personal Travel,Eco,187,2,5,2,3,5,4,5,2,2,2,2,4,2,3,76,86.0,neutral or dissatisfied +52596,75770,Female,Loyal Customer,64,Personal Travel,Eco,868,3,4,3,4,1,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +52597,19559,Male,Loyal Customer,70,Business travel,Business,108,3,2,2,2,4,4,3,2,2,2,3,2,2,2,2,0.0,neutral or dissatisfied +52598,86295,Female,Loyal Customer,36,Personal Travel,Eco,356,4,5,1,1,1,1,1,1,1,5,1,2,2,1,0,0.0,neutral or dissatisfied +52599,40096,Male,Loyal Customer,31,Business travel,Eco,200,4,4,4,4,4,4,4,4,2,1,1,3,2,4,0,0.0,satisfied +52600,78128,Male,Loyal Customer,38,Business travel,Business,2928,4,4,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +52601,123222,Male,Loyal Customer,53,Personal Travel,Eco,507,1,4,1,4,4,1,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +52602,59444,Female,Loyal Customer,51,Business travel,Business,811,5,5,2,5,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +52603,41477,Male,Loyal Customer,25,Business travel,Business,1464,1,1,1,1,5,5,5,5,5,5,1,2,1,5,23,26.0,satisfied +52604,46919,Female,disloyal Customer,24,Business travel,Business,846,1,1,1,4,2,1,2,2,3,3,3,3,3,2,4,30.0,neutral or dissatisfied +52605,34690,Female,Loyal Customer,38,Business travel,Eco,301,5,3,3,3,5,4,5,5,3,4,4,4,5,5,13,0.0,satisfied +52606,47126,Male,Loyal Customer,58,Business travel,Business,2500,5,5,5,5,2,5,5,4,4,4,4,3,4,4,108,100.0,satisfied +52607,113865,Female,disloyal Customer,35,Business travel,Eco,1363,4,4,4,2,1,4,1,1,5,1,3,1,4,1,25,0.0,neutral or dissatisfied +52608,91527,Female,disloyal Customer,28,Business travel,Business,680,2,2,2,5,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +52609,32779,Male,disloyal Customer,26,Business travel,Eco,101,4,0,4,3,4,4,4,4,4,2,3,3,2,4,0,9.0,neutral or dissatisfied +52610,44517,Female,Loyal Customer,57,Business travel,Eco,157,4,5,3,5,4,5,1,4,4,4,4,3,4,5,37,26.0,satisfied +52611,108032,Female,disloyal Customer,30,Business travel,Eco,306,4,2,4,3,2,4,3,2,2,3,3,2,4,2,0,5.0,neutral or dissatisfied +52612,56414,Male,Loyal Customer,50,Business travel,Business,2441,1,1,1,1,5,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +52613,38029,Male,Loyal Customer,50,Business travel,Eco,1249,4,3,3,3,3,4,3,3,4,4,4,4,1,3,0,0.0,satisfied +52614,93443,Female,Loyal Customer,36,Personal Travel,Eco,605,1,5,1,4,2,1,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +52615,16920,Female,Loyal Customer,30,Business travel,Eco Plus,746,4,5,5,5,4,4,4,4,1,3,5,1,4,4,0,0.0,satisfied +52616,95968,Female,Loyal Customer,50,Business travel,Business,583,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +52617,485,Male,Loyal Customer,39,Business travel,Business,2540,0,4,0,5,5,4,5,4,4,4,4,4,4,4,14,11.0,satisfied +52618,29103,Female,Loyal Customer,63,Personal Travel,Eco,1050,2,4,2,4,3,4,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +52619,51068,Female,Loyal Customer,12,Personal Travel,Eco,156,4,1,4,2,3,4,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +52620,26581,Male,Loyal Customer,57,Business travel,Eco,404,4,2,2,2,4,4,4,4,3,4,5,3,2,4,0,0.0,satisfied +52621,115197,Female,disloyal Customer,24,Business travel,Business,480,4,0,4,3,2,4,2,2,3,4,5,3,5,2,0,0.0,satisfied +52622,85770,Male,Loyal Customer,55,Business travel,Business,2766,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +52623,8792,Male,Loyal Customer,62,Business travel,Business,3313,3,2,2,2,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +52624,118433,Male,Loyal Customer,52,Business travel,Business,3309,0,0,0,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +52625,77093,Male,Loyal Customer,31,Business travel,Business,1481,4,4,4,4,4,4,4,4,5,3,5,4,4,4,86,111.0,satisfied +52626,114092,Female,Loyal Customer,12,Personal Travel,Eco,1947,1,5,0,2,5,0,5,5,3,4,3,5,4,5,0,7.0,neutral or dissatisfied +52627,126938,Male,Loyal Customer,37,Business travel,Business,338,0,0,0,3,2,4,4,1,1,1,1,5,1,4,10,6.0,satisfied +52628,102936,Female,Loyal Customer,21,Personal Travel,Eco,317,1,4,1,3,1,1,1,1,2,2,4,5,1,1,20,14.0,neutral or dissatisfied +52629,127100,Female,Loyal Customer,67,Personal Travel,Eco,370,5,4,5,3,2,4,4,1,1,5,1,2,1,3,0,2.0,satisfied +52630,33867,Female,Loyal Customer,70,Personal Travel,Eco,1562,2,5,2,2,3,4,4,1,1,2,1,3,1,5,35,24.0,neutral or dissatisfied +52631,9722,Male,Loyal Customer,22,Personal Travel,Eco,277,4,0,3,1,1,3,2,1,3,4,5,4,4,1,24,30.0,neutral or dissatisfied +52632,97800,Female,Loyal Customer,78,Business travel,Business,471,5,5,5,5,5,5,4,2,2,2,2,4,2,4,13,3.0,satisfied +52633,96917,Male,Loyal Customer,47,Personal Travel,Eco,849,2,4,2,3,1,2,1,1,5,3,4,5,4,1,6,0.0,neutral or dissatisfied +52634,92431,Female,Loyal Customer,24,Business travel,Business,2092,3,3,3,3,5,5,5,5,3,4,5,4,5,5,37,36.0,satisfied +52635,50044,Female,Loyal Customer,39,Business travel,Eco,421,4,5,2,5,4,4,4,4,1,4,1,4,1,4,0,0.0,satisfied +52636,3236,Female,Loyal Customer,27,Personal Travel,Business,479,1,2,1,3,4,1,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +52637,108925,Female,Loyal Customer,60,Personal Travel,Eco,1183,1,4,1,3,4,5,5,4,4,1,4,3,4,3,47,49.0,neutral or dissatisfied +52638,33376,Female,Loyal Customer,54,Personal Travel,Eco,2462,2,4,2,2,3,3,4,2,2,2,2,3,2,3,9,5.0,neutral or dissatisfied +52639,76792,Male,Loyal Customer,53,Business travel,Business,689,2,2,2,2,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +52640,20870,Female,Loyal Customer,54,Personal Travel,Eco,357,2,5,2,1,2,5,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +52641,12136,Female,disloyal Customer,26,Business travel,Business,1214,1,1,1,2,4,1,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +52642,8718,Male,Loyal Customer,52,Personal Travel,Eco,227,2,4,2,5,3,2,3,3,3,5,5,4,4,3,0,3.0,neutral or dissatisfied +52643,99355,Female,Loyal Customer,16,Personal Travel,Eco,1771,1,3,0,4,5,0,5,5,5,1,3,2,4,5,10,16.0,neutral or dissatisfied +52644,20970,Male,Loyal Customer,52,Personal Travel,Eco,689,3,4,3,3,1,3,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +52645,113223,Male,Loyal Customer,44,Business travel,Business,2581,2,1,1,1,1,3,2,1,1,1,2,4,1,2,0,0.0,neutral or dissatisfied +52646,71405,Male,Loyal Customer,39,Business travel,Business,2103,4,4,4,4,2,5,4,5,5,4,5,4,5,4,1,0.0,satisfied +52647,40907,Female,Loyal Customer,38,Personal Travel,Eco,558,3,5,3,4,2,3,5,2,3,4,3,4,5,2,0,0.0,neutral or dissatisfied +52648,34149,Male,Loyal Customer,37,Business travel,Eco,1046,5,5,5,5,5,4,5,5,2,4,3,5,4,5,0,0.0,satisfied +52649,26832,Male,Loyal Customer,36,Business travel,Eco,224,4,1,1,1,4,4,4,4,3,4,3,2,3,4,0,10.0,neutral or dissatisfied +52650,104792,Male,Loyal Customer,39,Business travel,Eco,787,5,2,2,2,5,4,5,5,1,4,4,3,4,5,9,5.0,neutral or dissatisfied +52651,45439,Male,Loyal Customer,22,Personal Travel,Eco,458,1,5,1,3,4,1,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +52652,80882,Female,Loyal Customer,59,Business travel,Eco Plus,484,2,5,5,5,1,3,3,2,2,2,2,2,2,1,1,0.0,neutral or dissatisfied +52653,24738,Male,Loyal Customer,54,Personal Travel,Business,528,2,2,2,4,5,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +52654,103677,Male,Loyal Customer,59,Business travel,Business,2637,4,4,4,4,5,5,5,3,3,4,3,4,3,4,16,1.0,satisfied +52655,78916,Female,Loyal Customer,49,Business travel,Business,2632,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +52656,108667,Female,Loyal Customer,50,Business travel,Business,484,3,3,3,3,4,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +52657,54668,Female,Loyal Customer,39,Business travel,Eco,965,2,4,4,4,2,3,2,2,1,5,4,3,2,2,0,0.0,satisfied +52658,32858,Male,Loyal Customer,35,Personal Travel,Eco,163,5,4,0,4,4,0,4,4,5,5,5,5,5,4,0,0.0,satisfied +52659,35509,Female,Loyal Customer,40,Personal Travel,Eco,1076,1,5,1,4,1,1,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +52660,27983,Male,disloyal Customer,41,Business travel,Eco,1238,3,3,3,3,4,3,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +52661,9818,Female,Loyal Customer,47,Business travel,Business,3557,5,5,2,5,4,4,4,5,5,5,5,5,5,4,27,53.0,satisfied +52662,46816,Female,Loyal Customer,32,Business travel,Business,2951,4,4,2,4,5,5,5,5,4,5,4,2,3,5,15,10.0,satisfied +52663,14667,Male,disloyal Customer,36,Business travel,Eco,416,2,5,3,1,4,3,4,4,4,3,3,3,4,4,0,0.0,neutral or dissatisfied +52664,7656,Male,disloyal Customer,8,Business travel,Business,767,2,0,2,3,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +52665,41409,Female,Loyal Customer,58,Personal Travel,Eco,927,3,1,4,3,1,4,3,3,3,4,4,1,3,3,4,15.0,neutral or dissatisfied +52666,110620,Female,disloyal Customer,28,Business travel,Eco,719,4,4,4,3,1,4,1,1,3,4,2,4,2,1,12,0.0,neutral or dissatisfied +52667,38295,Female,Loyal Customer,36,Business travel,Eco,2342,5,3,3,3,5,5,5,4,2,3,2,5,3,5,9,20.0,satisfied +52668,8050,Female,Loyal Customer,49,Business travel,Business,3840,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +52669,47655,Female,disloyal Customer,14,Business travel,Eco,1211,1,0,0,3,2,0,2,2,3,4,3,2,4,2,6,1.0,neutral or dissatisfied +52670,6120,Male,Loyal Customer,55,Business travel,Business,475,3,3,3,3,4,4,5,4,4,4,4,3,4,3,6,0.0,satisfied +52671,88604,Male,Loyal Customer,54,Personal Travel,Eco,404,3,3,3,3,2,3,1,2,1,5,4,3,4,2,9,3.0,neutral or dissatisfied +52672,108411,Female,Loyal Customer,34,Business travel,Business,544,2,2,2,2,3,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +52673,123357,Male,disloyal Customer,26,Business travel,Business,644,4,4,4,2,1,4,1,1,5,4,4,3,4,1,0,0.0,satisfied +52674,102727,Female,Loyal Customer,24,Personal Travel,Eco,365,3,5,3,4,5,3,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +52675,109369,Female,Loyal Customer,28,Business travel,Business,1189,2,2,2,2,3,4,3,3,3,2,5,3,5,3,0,0.0,satisfied +52676,57746,Male,Loyal Customer,45,Business travel,Business,2611,3,3,3,3,4,4,4,4,4,4,4,3,4,5,8,,satisfied +52677,88176,Male,Loyal Customer,33,Business travel,Business,2111,5,5,5,5,4,4,4,4,4,2,5,3,4,4,1,14.0,satisfied +52678,60973,Male,Loyal Customer,67,Personal Travel,Eco,888,3,1,3,2,2,3,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +52679,104925,Male,disloyal Customer,24,Business travel,Eco,210,4,5,4,1,1,4,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +52680,33583,Male,Loyal Customer,38,Business travel,Eco,413,4,3,3,3,4,4,4,4,2,2,5,1,1,4,0,0.0,satisfied +52681,7298,Male,Loyal Customer,52,Business travel,Business,135,5,5,5,5,4,5,4,4,4,5,5,4,4,3,0,0.0,satisfied +52682,120631,Female,disloyal Customer,40,Business travel,Business,280,4,5,5,3,5,5,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +52683,57637,Female,Loyal Customer,65,Business travel,Business,200,1,4,4,4,1,3,3,2,2,3,1,1,2,1,10,42.0,neutral or dissatisfied +52684,121000,Male,Loyal Customer,59,Personal Travel,Eco,993,1,4,1,2,1,1,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +52685,72460,Female,disloyal Customer,36,Business travel,Business,1017,3,3,3,4,2,3,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +52686,72137,Male,disloyal Customer,23,Business travel,Eco,731,1,1,1,3,2,1,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +52687,77183,Female,Loyal Customer,32,Business travel,Business,2502,0,0,0,2,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +52688,14015,Male,Loyal Customer,69,Business travel,Business,182,4,4,4,4,1,4,3,5,5,5,3,3,5,1,0,0.0,satisfied +52689,15305,Female,Loyal Customer,43,Business travel,Business,599,4,4,4,4,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +52690,42295,Male,Loyal Customer,55,Business travel,Eco,834,5,3,5,3,5,5,5,5,1,4,3,3,4,5,15,0.0,satisfied +52691,115832,Female,disloyal Customer,36,Business travel,Eco,308,3,0,3,4,4,3,4,4,1,4,1,3,1,4,0,2.0,neutral or dissatisfied +52692,3016,Male,disloyal Customer,9,Business travel,Eco,922,5,5,5,3,5,5,4,5,3,5,4,5,5,5,17,1.0,satisfied +52693,44452,Male,Loyal Customer,53,Personal Travel,Eco,1203,2,5,2,4,3,2,3,3,5,4,1,5,2,3,0,0.0,neutral or dissatisfied +52694,5495,Male,Loyal Customer,49,Business travel,Business,3580,1,4,4,4,4,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +52695,103521,Male,Loyal Customer,47,Business travel,Business,2066,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +52696,112803,Female,Loyal Customer,40,Business travel,Business,1390,3,1,1,1,2,4,4,3,3,3,3,1,3,3,92,90.0,neutral or dissatisfied +52697,472,Male,disloyal Customer,40,Business travel,Business,113,1,1,1,4,3,1,3,3,5,3,5,4,4,3,22,20.0,neutral or dissatisfied +52698,108310,Male,Loyal Customer,52,Business travel,Eco,1706,2,2,2,2,2,2,2,2,2,4,3,1,4,2,33,7.0,neutral or dissatisfied +52699,34322,Male,Loyal Customer,57,Business travel,Business,2454,1,1,1,1,5,5,1,3,3,4,3,5,3,5,25,10.0,satisfied +52700,109295,Female,Loyal Customer,46,Business travel,Business,1072,1,0,0,3,1,3,3,2,2,0,2,2,2,1,0,0.0,neutral or dissatisfied +52701,38344,Male,Loyal Customer,24,Business travel,Business,1173,4,4,1,1,4,4,4,4,3,1,4,1,3,4,7,34.0,neutral or dissatisfied +52702,1244,Female,Loyal Customer,56,Personal Travel,Eco,164,3,2,3,4,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +52703,11577,Male,disloyal Customer,8,Business travel,Eco,657,3,1,4,2,2,4,3,2,3,4,3,3,2,2,17,17.0,neutral or dissatisfied +52704,65562,Female,disloyal Customer,20,Business travel,Business,237,5,0,5,3,3,5,3,3,5,5,5,4,5,3,0,0.0,satisfied +52705,19317,Male,Loyal Customer,40,Business travel,Business,3588,2,2,2,2,4,1,2,5,5,4,5,2,5,1,0,0.0,satisfied +52706,125426,Male,Loyal Customer,36,Business travel,Eco,335,1,3,3,3,1,1,1,1,2,3,3,4,4,1,0,2.0,neutral or dissatisfied +52707,38538,Female,disloyal Customer,15,Business travel,Eco,1097,3,3,3,3,2,3,2,2,3,2,2,2,3,2,0,14.0,neutral or dissatisfied +52708,39232,Male,Loyal Customer,32,Business travel,Eco,67,5,4,4,4,5,5,5,5,5,4,3,5,1,5,0,0.0,satisfied +52709,127138,Male,Loyal Customer,47,Personal Travel,Eco,304,4,5,4,4,2,4,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +52710,9856,Female,disloyal Customer,26,Business travel,Eco,642,4,5,4,5,4,4,5,4,2,5,5,4,2,4,0,0.0,neutral or dissatisfied +52711,75344,Male,Loyal Customer,29,Personal Travel,Eco,2504,4,4,5,4,5,2,2,3,3,3,5,2,3,2,0,0.0,neutral or dissatisfied +52712,76776,Male,Loyal Customer,39,Business travel,Business,3136,2,2,5,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +52713,67523,Female,Loyal Customer,42,Business travel,Business,3064,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,4.0,satisfied +52714,1069,Female,Loyal Customer,67,Personal Travel,Eco,282,5,5,5,3,3,5,4,4,4,5,2,5,4,3,2,0.0,satisfied +52715,124768,Male,Loyal Customer,56,Business travel,Business,2108,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,33.0,satisfied +52716,9989,Male,Loyal Customer,40,Personal Travel,Eco,457,3,2,3,3,3,3,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +52717,36634,Female,disloyal Customer,39,Business travel,Eco,721,3,3,3,3,2,3,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +52718,112670,Female,Loyal Customer,48,Business travel,Business,723,3,3,3,3,4,4,4,4,4,4,4,5,4,3,8,0.0,satisfied +52719,79619,Female,disloyal Customer,45,Business travel,Eco,762,1,1,1,3,3,1,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +52720,36110,Male,Loyal Customer,70,Personal Travel,Eco Plus,399,2,5,2,3,4,2,4,4,4,4,4,4,4,4,0,16.0,neutral or dissatisfied +52721,77683,Female,Loyal Customer,57,Business travel,Business,2594,5,5,5,5,3,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +52722,2985,Male,disloyal Customer,37,Business travel,Business,987,2,3,3,5,4,3,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +52723,19991,Male,Loyal Customer,44,Business travel,Business,1727,5,5,5,5,5,2,2,5,5,5,5,1,5,4,0,0.0,satisfied +52724,61389,Female,disloyal Customer,26,Business travel,Business,679,4,4,4,3,3,4,3,3,3,5,5,5,4,3,22,4.0,neutral or dissatisfied +52725,47922,Male,Loyal Customer,37,Personal Travel,Eco,550,2,4,2,4,5,2,3,5,4,5,3,4,3,5,0,0.0,neutral or dissatisfied +52726,13028,Female,Loyal Customer,20,Personal Travel,Eco,438,1,4,1,2,5,1,5,5,4,2,5,5,5,5,8,1.0,neutral or dissatisfied +52727,55849,Male,Loyal Customer,19,Personal Travel,Eco,1416,0,3,0,3,4,0,4,4,2,2,4,3,4,4,0,0.0,satisfied +52728,83666,Male,Loyal Customer,30,Business travel,Business,577,5,5,5,5,4,4,4,4,5,4,5,5,4,4,1,0.0,satisfied +52729,19066,Female,Loyal Customer,32,Business travel,Eco,569,4,4,4,4,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +52730,122434,Male,Loyal Customer,42,Personal Travel,Eco,1916,1,5,1,1,4,1,4,4,5,4,5,4,4,4,1,11.0,neutral or dissatisfied +52731,29535,Female,Loyal Customer,56,Personal Travel,Eco Plus,2552,2,5,3,4,3,1,1,1,1,5,2,1,2,1,0,0.0,neutral or dissatisfied +52732,85019,Female,disloyal Customer,17,Business travel,Eco,949,4,4,4,1,1,4,1,1,2,3,5,5,4,1,0,0.0,satisfied +52733,69953,Male,Loyal Customer,50,Personal Travel,Eco,2174,2,1,2,4,5,2,5,5,4,4,4,4,4,5,23,0.0,neutral or dissatisfied +52734,30593,Male,Loyal Customer,22,Personal Travel,Eco Plus,628,2,4,2,3,3,2,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +52735,70816,Male,Loyal Customer,49,Personal Travel,Eco,624,1,5,1,4,3,1,3,3,3,2,5,4,5,3,0,23.0,neutral or dissatisfied +52736,2916,Female,Loyal Customer,44,Personal Travel,Eco Plus,409,2,3,3,4,5,4,3,1,1,3,1,4,1,2,0,0.0,neutral or dissatisfied +52737,123735,Female,disloyal Customer,35,Business travel,Business,96,3,3,3,4,2,3,2,2,4,3,4,1,4,2,0,15.0,neutral or dissatisfied +52738,74102,Male,Loyal Customer,46,Business travel,Business,3978,2,2,3,2,3,4,4,3,3,3,3,3,3,4,0,12.0,satisfied +52739,32359,Female,disloyal Customer,23,Business travel,Eco,102,2,4,2,4,2,2,2,2,3,4,4,1,4,2,21,24.0,neutral or dissatisfied +52740,7122,Male,Loyal Customer,65,Personal Travel,Eco Plus,157,2,4,2,2,4,2,3,4,3,3,5,3,4,4,71,73.0,neutral or dissatisfied +52741,118270,Female,disloyal Customer,41,Business travel,Business,602,5,5,5,5,2,5,2,2,3,3,5,3,5,2,30,35.0,satisfied +52742,106468,Male,Loyal Customer,32,Business travel,Business,3256,2,1,1,1,2,2,2,2,3,4,3,4,3,2,130,127.0,neutral or dissatisfied +52743,129568,Male,Loyal Customer,32,Business travel,Business,2583,4,4,4,4,4,5,4,4,4,3,4,4,5,4,9,5.0,satisfied +52744,92224,Male,Loyal Customer,21,Personal Travel,Eco,2079,1,1,0,4,5,0,5,5,4,1,4,2,4,5,40,12.0,neutral or dissatisfied +52745,37989,Female,Loyal Customer,16,Business travel,Business,2147,4,4,4,4,5,5,5,5,4,4,4,5,4,5,4,9.0,satisfied +52746,23567,Female,disloyal Customer,54,Business travel,Eco,1015,4,4,4,1,5,4,2,5,3,3,4,1,5,5,0,0.0,neutral or dissatisfied +52747,118007,Female,Loyal Customer,19,Business travel,Business,2855,2,2,2,2,5,5,5,5,3,3,4,5,5,5,20,11.0,satisfied +52748,52501,Male,Loyal Customer,30,Business travel,Business,2259,1,3,3,3,1,1,1,1,4,5,4,2,3,1,0,12.0,neutral or dissatisfied +52749,31519,Female,disloyal Customer,22,Business travel,Eco,967,2,2,2,4,5,2,5,5,2,3,3,2,3,5,12,15.0,neutral or dissatisfied +52750,50673,Female,Loyal Customer,68,Personal Travel,Eco,304,3,5,3,3,4,4,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +52751,114303,Male,Loyal Customer,49,Personal Travel,Eco,862,2,5,2,2,4,2,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +52752,88104,Male,Loyal Customer,39,Business travel,Business,1784,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +52753,22368,Male,Loyal Customer,21,Business travel,Business,1669,3,3,5,3,3,4,3,3,2,3,4,1,1,3,0,0.0,satisfied +52754,18021,Male,Loyal Customer,54,Business travel,Eco Plus,332,4,1,1,1,4,4,4,4,2,4,5,3,5,4,0,0.0,satisfied +52755,38003,Female,Loyal Customer,30,Business travel,Business,1249,1,1,1,1,5,5,5,5,5,1,5,4,5,5,22,15.0,satisfied +52756,97703,Male,Loyal Customer,52,Business travel,Eco,456,1,4,2,4,1,1,1,1,4,4,2,3,2,1,69,56.0,neutral or dissatisfied +52757,62835,Male,Loyal Customer,59,Business travel,Business,2615,5,5,5,5,5,4,4,5,5,5,5,4,5,4,3,0.0,satisfied +52758,60994,Male,Loyal Customer,29,Business travel,Business,649,1,1,4,1,5,5,5,5,3,5,5,4,5,5,24,9.0,satisfied +52759,118111,Male,Loyal Customer,37,Personal Travel,Eco,1999,4,5,4,3,5,4,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +52760,126936,Female,Loyal Customer,60,Business travel,Business,1778,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +52761,65983,Female,Loyal Customer,54,Personal Travel,Eco,1372,2,4,2,2,2,5,5,1,1,2,1,5,1,5,43,20.0,neutral or dissatisfied +52762,46124,Female,Loyal Customer,44,Business travel,Eco,516,5,1,1,1,5,4,5,3,3,5,3,1,3,1,1,0.0,satisfied +52763,54480,Female,Loyal Customer,29,Business travel,Business,925,3,3,3,3,4,4,4,4,1,1,4,1,3,4,40,62.0,satisfied +52764,102489,Male,Loyal Customer,39,Personal Travel,Eco,488,2,4,2,2,3,2,1,3,4,4,2,1,5,3,26,20.0,neutral or dissatisfied +52765,40491,Female,Loyal Customer,39,Personal Travel,Eco,461,2,5,2,4,5,2,5,5,2,3,3,2,4,5,0,0.0,neutral or dissatisfied +52766,54263,Male,Loyal Customer,27,Personal Travel,Eco,1222,4,2,4,3,5,4,5,5,2,5,3,1,4,5,0,5.0,neutral or dissatisfied +52767,76951,Female,Loyal Customer,42,Business travel,Business,1990,4,1,4,4,5,3,4,4,4,4,4,4,4,5,11,0.0,satisfied +52768,23704,Male,Loyal Customer,69,Personal Travel,Eco,152,3,4,0,3,5,0,3,5,4,5,4,3,3,5,0,0.0,neutral or dissatisfied +52769,25966,Female,Loyal Customer,33,Business travel,Eco,946,0,0,0,3,2,0,2,2,1,5,1,4,4,2,0,10.0,satisfied +52770,68727,Male,Loyal Customer,22,Business travel,Eco Plus,175,3,2,2,2,3,3,1,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +52771,88993,Female,Loyal Customer,49,Business travel,Business,2429,4,4,4,4,4,4,4,4,4,4,4,4,4,3,1,37.0,satisfied +52772,22218,Female,Loyal Customer,62,Personal Travel,Eco,633,2,5,2,3,2,4,4,4,4,2,4,4,4,4,55,50.0,neutral or dissatisfied +52773,11946,Female,Loyal Customer,54,Business travel,Eco,781,2,1,1,1,1,3,3,2,2,2,2,1,2,3,11,31.0,neutral or dissatisfied +52774,39956,Male,Loyal Customer,39,Personal Travel,Eco,1195,2,5,2,3,4,2,4,4,3,3,5,3,5,4,28,30.0,neutral or dissatisfied +52775,119826,Female,Loyal Customer,22,Business travel,Business,2788,4,4,4,4,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +52776,65802,Male,Loyal Customer,39,Business travel,Business,1391,2,2,5,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +52777,94714,Male,Loyal Customer,37,Business travel,Business,3577,4,4,3,4,4,4,4,4,4,5,4,5,4,4,10,0.0,satisfied +52778,72069,Male,disloyal Customer,29,Business travel,Eco,2556,2,2,2,3,4,2,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +52779,11774,Male,Loyal Customer,69,Personal Travel,Eco,429,1,3,1,4,2,1,2,2,5,5,4,4,5,2,22,15.0,neutral or dissatisfied +52780,61933,Female,Loyal Customer,47,Personal Travel,Eco,550,3,0,3,4,3,4,5,5,5,3,2,3,5,4,0,0.0,neutral or dissatisfied +52781,36138,Female,Loyal Customer,37,Business travel,Eco,1009,5,5,5,5,5,5,5,5,4,5,5,3,1,5,2,33.0,satisfied +52782,19519,Female,Loyal Customer,45,Personal Travel,Eco,977,2,4,2,5,5,5,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +52783,108434,Female,disloyal Customer,40,Business travel,Business,1444,2,2,2,2,2,2,2,2,4,5,5,5,5,2,8,13.0,neutral or dissatisfied +52784,107148,Female,Loyal Customer,32,Business travel,Business,668,3,3,5,3,5,5,5,5,3,5,4,3,5,5,0,2.0,satisfied +52785,16889,Female,Loyal Customer,25,Business travel,Business,746,3,4,4,4,3,3,3,3,2,3,3,2,3,3,0,9.0,neutral or dissatisfied +52786,2403,Male,Loyal Customer,43,Business travel,Business,641,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +52787,74513,Female,Loyal Customer,30,Business travel,Business,1438,5,5,5,5,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +52788,52582,Female,Loyal Customer,42,Business travel,Eco,119,5,4,3,4,1,2,1,5,5,5,5,4,5,2,0,0.0,satisfied +52789,109277,Female,Loyal Customer,16,Business travel,Business,2401,1,1,1,1,5,5,5,5,4,4,5,4,5,5,25,15.0,satisfied +52790,69392,Female,Loyal Customer,56,Business travel,Business,1096,2,5,5,5,3,3,4,2,2,2,2,3,2,3,57,52.0,neutral or dissatisfied +52791,34350,Female,Loyal Customer,32,Business travel,Business,2957,4,4,4,4,4,4,4,1,2,2,5,4,4,4,126,176.0,satisfied +52792,107241,Male,Loyal Customer,42,Business travel,Business,3586,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +52793,101864,Male,Loyal Customer,41,Business travel,Business,1747,1,1,1,1,5,4,5,5,5,5,5,3,5,4,20,34.0,satisfied +52794,34943,Male,Loyal Customer,17,Personal Travel,Eco,395,4,4,4,4,1,4,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +52795,24600,Male,disloyal Customer,22,Business travel,Eco,666,2,0,2,1,5,2,5,5,3,3,5,2,1,5,0,26.0,neutral or dissatisfied +52796,41612,Male,Loyal Customer,34,Personal Travel,Eco,1482,1,4,1,1,1,1,1,1,3,3,4,3,4,1,4,2.0,neutral or dissatisfied +52797,67879,Male,Loyal Customer,40,Personal Travel,Eco,1188,4,4,4,3,4,4,4,4,4,2,4,4,4,4,3,12.0,satisfied +52798,26176,Female,Loyal Customer,41,Business travel,Business,270,0,0,0,5,5,1,1,1,1,1,1,4,1,3,13,8.0,satisfied +52799,13790,Male,Loyal Customer,54,Personal Travel,Eco,837,2,5,2,3,3,2,2,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +52800,119917,Male,disloyal Customer,16,Business travel,Eco,1009,1,1,1,3,4,1,3,4,3,2,4,1,4,4,0,0.0,neutral or dissatisfied +52801,122961,Male,Loyal Customer,46,Business travel,Business,2914,3,3,3,3,4,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +52802,128092,Male,Loyal Customer,33,Personal Travel,Eco,2917,3,1,3,2,3,4,4,1,2,3,3,4,2,4,43,30.0,neutral or dissatisfied +52803,83883,Male,Loyal Customer,60,Personal Travel,Eco,1670,3,5,3,5,5,3,5,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +52804,113424,Female,Loyal Customer,49,Business travel,Business,1904,1,1,1,1,2,5,5,5,5,5,5,4,5,3,3,0.0,satisfied +52805,105107,Female,Loyal Customer,46,Business travel,Business,3727,5,5,5,5,3,4,5,4,4,4,4,5,4,5,31,52.0,satisfied +52806,41714,Female,Loyal Customer,38,Personal Travel,Eco,1262,5,5,5,3,3,5,3,3,4,5,4,5,5,3,0,0.0,satisfied +52807,95920,Male,Loyal Customer,53,Business travel,Business,1411,5,5,5,5,4,5,5,5,5,5,5,3,5,3,61,39.0,satisfied +52808,71332,Female,Loyal Customer,62,Business travel,Business,1114,4,4,4,4,5,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +52809,44710,Female,Loyal Customer,59,Personal Travel,Eco,268,3,3,3,3,5,4,4,4,4,3,4,4,4,3,10,8.0,neutral or dissatisfied +52810,63562,Male,Loyal Customer,48,Business travel,Business,1737,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +52811,119391,Male,Loyal Customer,55,Business travel,Business,399,5,5,5,5,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +52812,68151,Male,Loyal Customer,59,Business travel,Business,3810,2,2,2,2,3,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +52813,110525,Male,Loyal Customer,44,Business travel,Business,3525,4,4,4,4,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +52814,75328,Male,Loyal Customer,30,Business travel,Eco,2486,2,5,5,5,2,2,2,2,2,2,2,3,4,2,0,0.0,neutral or dissatisfied +52815,90295,Female,disloyal Customer,20,Business travel,Eco,479,0,0,0,1,4,0,4,4,1,1,1,3,1,4,0,0.0,satisfied +52816,69481,Female,disloyal Customer,27,Business travel,Business,1096,1,1,1,1,3,1,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +52817,72528,Female,Loyal Customer,34,Business travel,Business,1102,5,5,5,5,3,4,5,3,3,3,3,3,3,4,0,1.0,satisfied +52818,128717,Male,Loyal Customer,55,Business travel,Business,1464,2,2,3,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +52819,62784,Female,Loyal Customer,46,Business travel,Eco,1056,4,5,5,5,4,4,4,2,5,1,3,4,5,4,0,0.0,satisfied +52820,70664,Female,Loyal Customer,41,Business travel,Business,3796,3,2,3,3,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +52821,64695,Female,Loyal Customer,35,Business travel,Business,551,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +52822,99225,Female,disloyal Customer,22,Business travel,Eco,541,5,0,5,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +52823,98807,Female,Loyal Customer,43,Business travel,Business,1646,5,5,5,5,3,5,5,5,5,5,5,4,5,4,28,16.0,satisfied +52824,102830,Female,Loyal Customer,45,Business travel,Business,3631,3,5,5,5,4,3,4,3,3,3,3,1,3,3,2,4.0,neutral or dissatisfied +52825,87365,Male,Loyal Customer,47,Business travel,Business,1778,5,5,5,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +52826,54030,Female,Loyal Customer,41,Business travel,Business,1416,1,1,1,1,5,5,4,4,4,4,4,3,4,5,13,0.0,satisfied +52827,96078,Male,Loyal Customer,47,Personal Travel,Eco,1090,3,1,3,3,3,3,5,3,1,4,3,4,3,3,0,3.0,neutral or dissatisfied +52828,17137,Male,Loyal Customer,13,Personal Travel,Eco,423,1,3,1,3,4,1,4,4,1,2,5,2,4,4,7,26.0,neutral or dissatisfied +52829,74757,Male,Loyal Customer,9,Personal Travel,Eco,1205,3,4,4,4,2,4,2,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +52830,90477,Male,Loyal Customer,52,Business travel,Business,2774,2,2,2,2,5,5,4,4,4,4,4,5,4,4,13,32.0,satisfied +52831,34775,Male,Loyal Customer,47,Business travel,Business,1779,3,3,3,3,3,4,3,3,3,3,3,2,3,1,0,13.0,neutral or dissatisfied +52832,111946,Female,disloyal Customer,22,Business travel,Business,533,0,0,0,1,5,0,1,5,3,3,5,4,4,5,43,30.0,satisfied +52833,35280,Male,disloyal Customer,23,Business travel,Eco,1010,3,3,3,5,4,3,4,4,4,2,4,4,3,4,75,103.0,neutral or dissatisfied +52834,13209,Male,Loyal Customer,25,Business travel,Business,2382,5,5,5,5,4,4,4,5,2,5,5,4,4,4,231,218.0,satisfied +52835,20543,Male,disloyal Customer,23,Business travel,Eco,606,3,4,3,1,3,3,3,3,5,1,5,4,2,3,0,0.0,neutral or dissatisfied +52836,43652,Female,Loyal Customer,60,Business travel,Eco,695,4,4,4,4,1,4,2,4,4,4,4,2,4,2,36,25.0,satisfied +52837,52576,Female,Loyal Customer,61,Business travel,Eco,160,5,3,3,3,3,5,3,5,5,5,5,2,5,2,0,0.0,satisfied +52838,5232,Male,Loyal Customer,39,Business travel,Eco,383,3,1,1,1,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +52839,67405,Male,Loyal Customer,51,Business travel,Business,641,4,4,4,4,2,5,4,5,5,5,5,4,5,5,16,0.0,satisfied +52840,125139,Male,Loyal Customer,49,Business travel,Business,361,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +52841,86188,Male,disloyal Customer,36,Business travel,Business,226,1,1,1,1,2,1,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +52842,61731,Male,Loyal Customer,35,Business travel,Business,1379,5,5,2,5,3,4,2,2,2,2,2,5,2,2,0,0.0,satisfied +52843,65244,Female,Loyal Customer,41,Business travel,Business,3149,5,5,5,5,5,4,4,4,4,4,4,3,4,4,9,7.0,satisfied +52844,52326,Male,Loyal Customer,42,Business travel,Business,425,1,2,2,2,5,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +52845,4406,Male,Loyal Customer,35,Business travel,Business,762,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +52846,77227,Female,Loyal Customer,42,Business travel,Business,1590,5,4,5,5,3,4,5,5,5,5,5,5,5,4,42,22.0,satisfied +52847,92918,Female,Loyal Customer,59,Business travel,Business,151,1,3,3,3,3,4,3,3,3,3,1,3,3,1,0,0.0,neutral or dissatisfied +52848,65338,Female,Loyal Customer,30,Business travel,Business,3036,3,4,3,3,2,2,2,2,4,2,4,3,5,2,23,13.0,satisfied +52849,111472,Male,disloyal Customer,37,Business travel,Business,1024,3,3,3,3,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +52850,81597,Male,Loyal Customer,40,Business travel,Business,2174,4,4,4,4,3,5,4,4,4,4,4,5,4,3,0,4.0,satisfied +52851,55632,Female,disloyal Customer,23,Business travel,Eco,838,1,1,1,2,2,1,1,2,2,3,2,1,2,2,87,99.0,neutral or dissatisfied +52852,43519,Female,Loyal Customer,27,Business travel,Eco Plus,624,5,4,4,4,5,5,5,5,3,5,4,2,5,5,14,12.0,satisfied +52853,111084,Male,Loyal Customer,28,Personal Travel,Eco,319,3,4,3,4,1,3,1,1,4,5,5,3,4,1,0,1.0,neutral or dissatisfied +52854,88954,Male,Loyal Customer,24,Business travel,Business,1199,2,2,2,2,4,4,4,4,3,3,4,3,5,4,12,10.0,satisfied +52855,90501,Female,Loyal Customer,35,Business travel,Business,404,4,4,4,4,3,4,5,2,2,2,2,3,2,5,0,21.0,satisfied +52856,41789,Male,Loyal Customer,37,Business travel,Business,3999,0,0,0,4,3,5,1,4,4,5,5,1,4,2,0,0.0,satisfied +52857,116824,Female,Loyal Customer,37,Business travel,Business,3792,4,4,4,4,4,5,5,4,4,5,4,3,4,5,34,18.0,satisfied +52858,1440,Female,Loyal Customer,51,Business travel,Business,1866,2,2,4,2,3,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +52859,62623,Male,Loyal Customer,57,Personal Travel,Eco,1846,3,3,3,2,1,3,1,1,3,3,5,3,5,1,23,16.0,neutral or dissatisfied +52860,39082,Male,Loyal Customer,45,Business travel,Eco,984,5,3,3,3,5,5,5,5,5,5,5,3,2,5,0,0.0,satisfied +52861,96318,Female,Loyal Customer,23,Personal Travel,Eco Plus,546,1,5,1,3,2,1,2,2,4,1,1,1,2,2,0,0.0,neutral or dissatisfied +52862,82434,Male,disloyal Customer,45,Business travel,Business,502,3,4,4,1,3,3,3,3,3,3,5,4,4,3,0,2.0,neutral or dissatisfied +52863,129517,Female,Loyal Customer,46,Business travel,Business,1846,2,2,2,2,5,5,5,2,2,2,2,3,2,5,2,9.0,satisfied +52864,41791,Female,Loyal Customer,41,Business travel,Eco,196,4,4,4,4,5,4,5,5,1,4,5,5,4,5,0,0.0,satisfied +52865,121696,Female,disloyal Customer,33,Business travel,Eco,168,1,1,1,4,4,1,2,4,3,3,3,3,4,4,0,0.0,neutral or dissatisfied +52866,49772,Female,Loyal Customer,37,Business travel,Business,363,1,1,1,1,4,3,3,4,4,4,4,1,4,2,0,0.0,satisfied +52867,84665,Female,Loyal Customer,45,Business travel,Business,2182,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,6.0,satisfied +52868,81285,Male,Loyal Customer,29,Personal Travel,Eco,1029,1,4,1,5,3,1,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +52869,93550,Female,Loyal Customer,48,Business travel,Business,949,2,2,2,2,5,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +52870,52442,Male,Loyal Customer,66,Personal Travel,Eco,370,3,2,3,1,5,3,2,5,4,3,2,1,2,5,0,0.0,neutral or dissatisfied +52871,74628,Female,Loyal Customer,80,Business travel,Business,1766,4,4,4,4,2,1,5,5,5,5,5,5,5,4,5,0.0,satisfied +52872,11113,Male,Loyal Customer,13,Personal Travel,Eco,312,3,5,3,1,2,3,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +52873,20082,Female,Loyal Customer,16,Personal Travel,Eco Plus,528,2,5,2,1,5,2,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +52874,119652,Male,Loyal Customer,59,Business travel,Business,1839,1,4,4,4,4,3,4,1,1,2,1,3,1,4,12,9.0,neutral or dissatisfied +52875,50837,Male,Loyal Customer,51,Personal Travel,Eco,308,3,5,5,3,4,5,3,4,1,4,5,2,3,4,0,0.0,neutral or dissatisfied +52876,94957,Female,Loyal Customer,68,Business travel,Business,1819,3,3,3,3,3,3,1,5,5,5,5,4,5,5,0,0.0,satisfied +52877,122825,Female,Loyal Customer,39,Personal Travel,Eco,599,2,3,2,3,3,2,3,3,3,5,3,4,3,3,44,28.0,neutral or dissatisfied +52878,74889,Male,Loyal Customer,34,Personal Travel,Business,2475,1,5,1,3,4,5,4,1,1,1,1,5,1,4,0,,neutral or dissatisfied +52879,74961,Female,Loyal Customer,24,Personal Travel,Eco,2475,3,4,3,4,2,3,3,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +52880,17712,Female,Loyal Customer,64,Business travel,Eco Plus,311,4,3,3,3,4,2,4,4,4,4,4,3,4,5,0,18.0,satisfied +52881,1733,Female,Loyal Customer,56,Personal Travel,Eco,364,2,4,2,4,2,5,5,3,3,2,3,5,3,4,45,49.0,neutral or dissatisfied +52882,78745,Male,Loyal Customer,42,Business travel,Business,1851,1,1,1,1,5,5,5,3,2,5,4,5,4,5,153,149.0,satisfied +52883,67272,Female,Loyal Customer,38,Personal Travel,Eco,985,4,5,4,4,1,4,1,1,5,5,4,3,5,1,0,0.0,satisfied +52884,52581,Female,Loyal Customer,56,Business travel,Business,160,3,3,3,3,2,2,4,4,4,4,3,4,4,2,5,0.0,satisfied +52885,45091,Female,Loyal Customer,19,Personal Travel,Eco,196,1,4,1,1,5,1,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +52886,56900,Female,Loyal Customer,47,Business travel,Business,2454,4,4,1,4,4,3,3,4,3,3,5,3,4,3,0,0.0,satisfied +52887,121604,Female,Loyal Customer,11,Personal Travel,Eco,912,2,5,2,4,3,2,3,3,5,4,4,5,5,3,9,1.0,neutral or dissatisfied +52888,91944,Female,Loyal Customer,43,Personal Travel,Eco,2586,4,5,4,3,5,5,4,1,1,4,1,3,1,4,0,0.0,satisfied +52889,42212,Male,disloyal Customer,30,Business travel,Eco,748,4,4,4,4,5,4,5,5,1,2,2,5,1,5,0,0.0,satisfied +52890,86115,Female,disloyal Customer,20,Business travel,Eco,356,4,5,4,3,2,4,2,2,3,3,5,4,5,2,0,0.0,satisfied +52891,54122,Male,Loyal Customer,29,Business travel,Business,1372,5,5,5,5,2,2,2,2,3,1,3,5,5,2,45,14.0,satisfied +52892,49093,Male,Loyal Customer,31,Business travel,Eco,86,0,0,0,1,5,3,5,5,2,1,2,2,1,5,7,0.0,satisfied +52893,65152,Female,Loyal Customer,68,Personal Travel,Eco,551,2,3,2,3,5,4,5,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +52894,119693,Female,Loyal Customer,33,Business travel,Business,1649,4,4,4,4,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +52895,66629,Female,Loyal Customer,51,Personal Travel,Business,802,2,4,3,1,1,5,4,3,3,3,3,5,3,5,6,22.0,neutral or dissatisfied +52896,13004,Male,Loyal Customer,54,Business travel,Business,1957,4,4,4,4,1,1,4,5,5,5,5,2,5,4,44,35.0,satisfied +52897,47467,Male,Loyal Customer,14,Personal Travel,Eco,599,3,4,2,5,4,2,4,4,1,1,2,1,1,4,27,17.0,neutral or dissatisfied +52898,98630,Female,Loyal Customer,54,Business travel,Eco,992,3,1,5,5,4,4,3,3,3,3,3,4,3,1,29,17.0,neutral or dissatisfied +52899,5474,Female,Loyal Customer,41,Personal Travel,Eco,265,2,2,2,3,2,2,2,2,4,4,2,2,3,2,0,0.0,neutral or dissatisfied +52900,1794,Female,disloyal Customer,25,Business travel,Business,500,3,4,3,2,3,3,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +52901,67957,Male,disloyal Customer,25,Business travel,Eco,1235,2,2,2,1,5,2,5,5,3,3,5,5,5,5,1,0.0,neutral or dissatisfied +52902,12916,Male,Loyal Customer,55,Business travel,Eco,794,2,1,1,1,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +52903,90619,Male,Loyal Customer,53,Business travel,Business,1720,2,4,2,4,2,3,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +52904,84315,Female,Loyal Customer,48,Business travel,Business,606,5,5,5,5,4,5,5,4,4,4,4,4,4,3,5,5.0,satisfied +52905,65141,Female,Loyal Customer,15,Personal Travel,Eco,247,1,4,1,1,5,1,5,5,3,4,5,5,4,5,9,0.0,neutral or dissatisfied +52906,115045,Female,Loyal Customer,24,Business travel,Business,1752,4,2,2,2,4,4,4,4,1,5,2,2,3,4,0,2.0,neutral or dissatisfied +52907,105649,Male,Loyal Customer,47,Business travel,Business,919,2,2,2,2,5,4,4,4,4,4,4,3,4,4,6,12.0,satisfied +52908,101032,Male,Loyal Customer,25,Business travel,Business,867,4,4,4,4,5,5,5,5,5,3,4,4,4,5,0,0.0,satisfied +52909,5469,Female,Loyal Customer,10,Personal Travel,Eco,287,3,3,3,5,3,2,2,5,2,5,4,2,2,2,159,180.0,neutral or dissatisfied +52910,36142,Female,Loyal Customer,61,Personal Travel,Eco,1562,3,2,3,3,4,2,3,4,4,3,5,2,4,1,0,16.0,neutral or dissatisfied +52911,68896,Female,Loyal Customer,26,Business travel,Business,2174,1,1,1,1,4,5,4,4,2,4,3,2,5,4,8,0.0,satisfied +52912,109758,Female,Loyal Customer,37,Personal Travel,Eco Plus,587,2,4,2,3,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +52913,117733,Female,disloyal Customer,22,Business travel,Eco,833,4,4,4,3,4,4,4,4,3,5,4,4,5,4,16,0.0,satisfied +52914,57450,Female,Loyal Customer,57,Business travel,Business,334,0,0,0,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +52915,55294,Female,Loyal Customer,34,Personal Travel,Eco,1608,4,5,4,2,2,4,3,2,3,5,5,3,4,2,10,9.0,neutral or dissatisfied +52916,101635,Male,Loyal Customer,18,Personal Travel,Eco Plus,1139,1,5,1,4,4,1,4,4,5,4,3,3,5,4,12,7.0,neutral or dissatisfied +52917,57176,Male,Loyal Customer,44,Business travel,Eco,2227,2,2,2,2,2,2,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +52918,95866,Female,Loyal Customer,43,Business travel,Business,2006,5,5,5,5,2,5,5,4,4,4,4,3,4,4,28,36.0,satisfied +52919,3831,Male,disloyal Customer,30,Business travel,Eco,250,3,0,3,5,2,3,2,2,3,2,1,3,1,2,0,0.0,neutral or dissatisfied +52920,5924,Male,Loyal Customer,56,Personal Travel,Eco,67,4,5,4,1,1,4,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +52921,80529,Male,Loyal Customer,37,Business travel,Business,1678,1,1,2,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +52922,120572,Male,Loyal Customer,59,Personal Travel,Eco,2176,3,2,3,3,2,3,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +52923,128303,Male,Loyal Customer,47,Business travel,Business,3788,1,1,1,1,5,4,5,4,4,4,4,3,4,4,101,102.0,satisfied +52924,129322,Female,Loyal Customer,26,Business travel,Business,2475,3,3,3,3,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +52925,15393,Female,Loyal Customer,56,Business travel,Business,2729,1,3,3,3,1,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +52926,92089,Male,Loyal Customer,61,Business travel,Eco,1535,2,4,4,4,2,2,2,2,1,4,4,3,4,2,16,11.0,neutral or dissatisfied +52927,125163,Female,disloyal Customer,29,Business travel,Business,1089,4,4,4,1,4,4,4,4,4,4,5,5,4,4,45,59.0,satisfied +52928,47712,Female,Loyal Customer,36,Business travel,Eco Plus,1104,3,5,4,5,3,3,3,3,2,4,4,3,3,3,5,5.0,neutral or dissatisfied +52929,103175,Male,Loyal Customer,66,Personal Travel,Eco,491,5,5,5,1,3,5,3,3,1,4,1,2,4,3,10,0.0,satisfied +52930,89578,Male,Loyal Customer,55,Business travel,Business,1871,4,4,4,4,3,4,4,4,4,4,4,5,4,5,43,26.0,satisfied +52931,68594,Female,disloyal Customer,8,Business travel,Eco Plus,1616,2,1,2,3,4,2,4,4,4,1,2,1,3,4,0,30.0,neutral or dissatisfied +52932,83297,Male,Loyal Customer,65,Personal Travel,Eco,1979,4,4,4,4,4,4,2,4,3,5,3,4,5,4,30,3.0,satisfied +52933,117001,Female,Loyal Customer,56,Business travel,Business,3394,5,5,4,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +52934,42060,Male,Loyal Customer,10,Personal Travel,Eco,116,3,1,3,3,1,3,4,1,4,3,4,1,3,1,27,32.0,neutral or dissatisfied +52935,32950,Female,Loyal Customer,59,Personal Travel,Eco,163,1,2,1,3,5,4,3,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +52936,4303,Female,disloyal Customer,25,Business travel,Business,502,3,4,3,3,5,3,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +52937,90730,Female,Loyal Customer,34,Business travel,Business,1510,4,4,4,4,5,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +52938,82150,Male,Loyal Customer,50,Business travel,Business,311,0,0,0,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +52939,24584,Male,disloyal Customer,26,Business travel,Eco,526,2,0,2,4,2,2,2,2,1,3,4,2,2,2,0,0.0,neutral or dissatisfied +52940,36803,Female,Loyal Customer,34,Personal Travel,Eco,2704,2,4,2,4,2,2,2,3,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +52941,98468,Male,Loyal Customer,46,Business travel,Eco,210,2,1,1,1,2,2,2,2,2,1,3,2,4,2,0,7.0,neutral or dissatisfied +52942,5854,Male,Loyal Customer,31,Business travel,Business,1020,3,3,4,3,4,4,4,4,4,5,4,3,4,4,0,3.0,satisfied +52943,33102,Male,Loyal Customer,62,Personal Travel,Eco,163,1,3,1,4,2,1,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +52944,73574,Female,Loyal Customer,64,Business travel,Business,3094,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +52945,11530,Female,Loyal Customer,56,Business travel,Business,2046,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +52946,99301,Female,Loyal Customer,55,Business travel,Business,448,5,5,5,5,2,4,5,2,2,2,2,3,2,5,64,49.0,satisfied +52947,47363,Male,Loyal Customer,26,Business travel,Business,584,1,1,1,1,5,5,5,5,1,4,5,4,3,5,0,0.0,satisfied +52948,5885,Female,Loyal Customer,34,Business travel,Business,3328,3,3,3,3,3,4,4,4,4,4,5,4,4,5,89,122.0,satisfied +52949,26195,Male,disloyal Customer,38,Business travel,Eco,406,2,4,2,1,5,2,5,5,5,3,4,3,5,5,3,0.0,neutral or dissatisfied +52950,110828,Female,Loyal Customer,40,Business travel,Business,2786,3,3,4,3,4,4,5,4,4,5,4,3,4,4,36,42.0,satisfied +52951,44156,Female,Loyal Customer,19,Personal Travel,Business,229,4,4,4,2,2,4,5,2,4,4,4,5,5,2,1,7.0,neutral or dissatisfied +52952,113124,Male,Loyal Customer,51,Business travel,Business,3731,2,2,2,2,3,5,4,4,4,4,4,4,4,5,21,18.0,satisfied +52953,79489,Male,Loyal Customer,23,Personal Travel,Business,749,5,4,5,1,1,5,1,1,4,4,5,4,5,1,0,0.0,satisfied +52954,79860,Male,Loyal Customer,50,Business travel,Business,950,2,2,2,2,4,5,5,4,4,5,4,5,4,3,24,32.0,satisfied +52955,34526,Male,Loyal Customer,38,Business travel,Business,636,5,5,5,5,4,5,5,3,3,3,3,4,3,5,102,118.0,satisfied +52956,36596,Female,Loyal Customer,49,Business travel,Eco,1121,2,2,2,2,5,3,4,2,2,2,2,4,2,1,49,32.0,neutral or dissatisfied +52957,28393,Male,Loyal Customer,53,Personal Travel,Eco,763,2,4,2,4,4,2,4,4,3,4,2,4,1,4,11,22.0,neutral or dissatisfied +52958,22244,Male,Loyal Customer,23,Personal Travel,Business,83,4,5,0,3,5,0,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +52959,91641,Female,Loyal Customer,63,Personal Travel,Eco,1199,1,4,1,4,4,3,3,4,4,1,4,2,4,3,0,2.0,neutral or dissatisfied +52960,120432,Female,disloyal Customer,25,Business travel,Business,366,1,5,1,1,3,1,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +52961,73979,Male,Loyal Customer,27,Personal Travel,Eco,2218,1,5,1,5,3,1,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +52962,126635,Male,Loyal Customer,46,Business travel,Business,3531,4,4,4,4,5,5,5,5,5,5,5,4,5,5,8,0.0,satisfied +52963,84587,Female,disloyal Customer,35,Business travel,Business,669,3,3,3,2,4,3,4,4,3,5,2,3,2,4,10,13.0,neutral or dissatisfied +52964,72837,Female,Loyal Customer,54,Personal Travel,Eco,1013,2,1,2,3,3,4,4,2,2,2,2,4,2,1,28,25.0,neutral or dissatisfied +52965,32832,Female,disloyal Customer,24,Business travel,Business,201,3,1,3,4,1,3,4,1,4,2,4,2,3,1,6,12.0,neutral or dissatisfied +52966,68981,Male,Loyal Customer,70,Personal Travel,Eco,700,3,5,3,4,4,3,5,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +52967,127195,Female,Loyal Customer,20,Business travel,Business,651,1,1,3,1,3,3,3,3,5,4,5,3,4,3,0,0.0,satisfied +52968,33577,Male,disloyal Customer,22,Business travel,Eco,399,2,0,2,3,1,2,1,1,1,3,5,1,4,1,0,0.0,neutral or dissatisfied +52969,93830,Female,Loyal Customer,19,Business travel,Business,3489,3,3,3,3,3,3,3,3,2,2,3,3,3,3,6,0.0,neutral or dissatisfied +52970,70658,Male,Loyal Customer,34,Personal Travel,Eco,946,4,4,4,2,5,4,5,5,2,2,2,4,2,5,79,83.0,neutral or dissatisfied +52971,121116,Female,Loyal Customer,33,Business travel,Business,2370,2,2,2,2,4,4,4,5,3,4,4,4,3,4,0,0.0,satisfied +52972,84307,Male,Loyal Customer,13,Personal Travel,Eco,235,2,5,2,3,3,2,3,3,1,5,1,2,5,3,17,21.0,neutral or dissatisfied +52973,68420,Male,Loyal Customer,28,Personal Travel,Eco,1045,2,5,2,1,3,2,3,3,5,4,2,3,2,3,0,0.0,neutral or dissatisfied +52974,98240,Female,Loyal Customer,59,Business travel,Business,2070,4,4,4,4,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +52975,70644,Male,Loyal Customer,54,Business travel,Business,2126,2,2,2,2,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +52976,85667,Male,disloyal Customer,25,Business travel,Eco,903,2,2,2,2,3,2,3,3,4,5,2,1,3,3,1,0.0,neutral or dissatisfied +52977,111469,Male,Loyal Customer,65,Personal Travel,Eco,836,5,5,4,4,5,4,5,5,3,2,4,5,4,5,8,3.0,satisfied +52978,32320,Male,disloyal Customer,36,Business travel,Business,216,2,2,2,1,2,2,2,2,3,4,1,1,3,2,0,0.0,neutral or dissatisfied +52979,30658,Female,Loyal Customer,58,Personal Travel,Eco,533,1,4,1,3,3,5,4,3,3,1,3,4,3,3,102,99.0,neutral or dissatisfied +52980,126327,Male,Loyal Customer,27,Personal Travel,Eco,590,3,4,3,5,1,3,1,1,4,2,5,5,3,1,0,0.0,neutral or dissatisfied +52981,85215,Male,Loyal Customer,48,Business travel,Eco,689,2,4,3,4,2,2,2,2,1,5,3,2,4,2,14,0.0,neutral or dissatisfied +52982,93327,Female,disloyal Customer,39,Business travel,Business,287,1,1,1,3,3,1,3,3,3,5,3,1,4,3,0,0.0,neutral or dissatisfied +52983,108953,Female,Loyal Customer,53,Business travel,Business,1939,5,5,5,5,2,4,5,5,5,5,5,4,5,3,11,32.0,satisfied +52984,116750,Male,Loyal Customer,7,Personal Travel,Eco Plus,372,3,0,3,5,3,5,5,5,3,4,4,5,3,5,181,176.0,neutral or dissatisfied +52985,73543,Male,Loyal Customer,53,Personal Travel,Eco,594,1,5,2,2,5,2,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +52986,11430,Female,Loyal Customer,46,Business travel,Business,308,3,3,3,3,3,4,4,4,4,4,4,4,4,4,21,7.0,satisfied +52987,2517,Male,disloyal Customer,48,Business travel,Business,227,5,5,5,2,1,5,1,1,4,5,4,3,5,1,0,0.0,satisfied +52988,28973,Male,Loyal Customer,55,Business travel,Eco,605,4,5,5,5,4,4,4,4,3,1,4,1,3,4,0,0.0,neutral or dissatisfied +52989,7523,Female,Loyal Customer,41,Business travel,Business,762,1,1,5,1,5,4,5,5,5,5,5,4,5,3,10,0.0,satisfied +52990,28188,Male,Loyal Customer,35,Personal Travel,Eco,859,3,3,3,3,5,3,5,5,4,2,5,3,3,5,0,0.0,neutral or dissatisfied +52991,102240,Female,Loyal Customer,64,Business travel,Business,226,4,4,4,4,3,5,4,4,4,4,4,3,4,4,19,14.0,satisfied +52992,28999,Male,disloyal Customer,30,Business travel,Eco,978,3,3,3,3,1,3,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +52993,73009,Female,Loyal Customer,61,Personal Travel,Eco,1089,4,3,4,3,1,3,3,1,1,4,1,5,1,1,5,0.0,neutral or dissatisfied +52994,13068,Female,Loyal Customer,39,Business travel,Eco,936,4,5,5,5,4,4,4,4,5,1,4,3,2,4,0,0.0,satisfied +52995,127835,Male,Loyal Customer,18,Personal Travel,Eco,1262,1,5,0,2,3,0,3,3,4,4,3,4,5,3,0,0.0,neutral or dissatisfied +52996,61639,Female,Loyal Customer,46,Business travel,Eco,1346,1,0,0,4,1,3,3,2,2,1,4,4,2,4,0,8.0,neutral or dissatisfied +52997,78289,Female,disloyal Customer,25,Business travel,Business,1598,4,0,4,2,2,4,2,2,5,2,3,5,5,2,0,0.0,satisfied +52998,58762,Male,Loyal Customer,37,Business travel,Business,1005,1,5,1,1,2,5,5,4,4,4,4,5,4,4,95,96.0,satisfied +52999,64074,Male,Loyal Customer,61,Personal Travel,Eco,921,4,4,4,2,1,4,1,1,3,4,4,3,5,1,0,0.0,satisfied +53000,22153,Male,Loyal Customer,33,Business travel,Business,773,3,3,3,3,5,5,5,5,2,3,1,1,1,5,13,11.0,satisfied +53001,67279,Male,Loyal Customer,32,Personal Travel,Eco,929,3,4,3,3,4,3,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +53002,69442,Female,Loyal Customer,16,Personal Travel,Eco,1089,3,3,3,1,5,3,2,5,3,4,1,4,5,5,0,0.0,neutral or dissatisfied +53003,114475,Female,disloyal Customer,20,Business travel,Business,308,5,5,5,3,2,5,2,2,5,5,4,5,4,2,15,3.0,satisfied +53004,5533,Female,disloyal Customer,17,Business travel,Eco,404,0,0,0,2,5,0,5,5,2,4,1,3,1,5,0,0.0,satisfied +53005,4310,Male,disloyal Customer,23,Business travel,Eco,184,2,2,2,2,3,2,3,3,2,3,1,4,2,3,28,21.0,neutral or dissatisfied +53006,5496,Male,disloyal Customer,27,Business travel,Business,910,0,0,0,3,3,0,3,3,3,3,5,5,4,3,0,0.0,satisfied +53007,76509,Female,Loyal Customer,40,Business travel,Business,3080,4,4,4,4,4,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +53008,47860,Male,Loyal Customer,12,Business travel,Business,3548,2,1,1,1,2,2,2,2,2,4,3,2,4,2,0,3.0,neutral or dissatisfied +53009,22101,Male,disloyal Customer,39,Business travel,Business,694,3,3,3,4,3,3,1,3,4,3,5,4,4,3,71,62.0,neutral or dissatisfied +53010,110465,Female,Loyal Customer,62,Personal Travel,Eco,787,1,5,1,1,3,4,4,1,1,1,2,4,1,5,0,0.0,neutral or dissatisfied +53011,66355,Male,disloyal Customer,26,Business travel,Eco,986,3,3,3,3,5,3,3,5,1,5,4,2,4,5,1,19.0,neutral or dissatisfied +53012,118321,Female,disloyal Customer,22,Business travel,Eco,602,4,0,4,2,4,3,4,3,2,4,4,4,5,4,171,172.0,satisfied +53013,60132,Female,Loyal Customer,21,Business travel,Business,1012,2,2,2,2,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +53014,129269,Male,disloyal Customer,44,Business travel,Eco,2521,2,2,2,4,2,2,2,2,4,4,2,4,4,2,0,0.0,neutral or dissatisfied +53015,118533,Female,disloyal Customer,27,Business travel,Eco,651,2,3,2,4,5,2,5,5,1,3,3,2,4,5,10,7.0,neutral or dissatisfied +53016,41824,Female,Loyal Customer,37,Personal Travel,Eco,489,4,0,4,3,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +53017,129871,Female,disloyal Customer,23,Business travel,Business,337,2,2,2,4,5,2,5,5,2,1,4,2,4,5,46,58.0,neutral or dissatisfied +53018,99229,Female,disloyal Customer,51,Business travel,Business,541,1,1,1,1,3,1,3,3,4,2,4,3,5,3,39,30.0,neutral or dissatisfied +53019,68407,Female,Loyal Customer,45,Business travel,Business,2607,3,4,4,4,2,4,4,3,3,3,3,4,3,3,0,19.0,neutral or dissatisfied +53020,112097,Male,Loyal Customer,39,Business travel,Business,2263,2,4,4,4,4,3,4,2,2,2,2,4,2,4,9,0.0,neutral or dissatisfied +53021,80773,Female,Loyal Customer,48,Personal Travel,Eco Plus,629,3,5,3,4,4,4,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +53022,15525,Female,Loyal Customer,63,Personal Travel,Eco Plus,164,1,3,1,3,2,4,4,3,3,1,3,4,3,5,0,1.0,neutral or dissatisfied +53023,80319,Male,Loyal Customer,67,Personal Travel,Eco,746,2,4,2,4,2,2,2,2,5,4,5,3,4,2,0,4.0,neutral or dissatisfied +53024,93346,Male,Loyal Customer,19,Business travel,Business,1843,5,5,5,5,4,4,4,4,3,2,4,5,4,4,10,0.0,satisfied +53025,18052,Male,Loyal Customer,51,Business travel,Eco,488,2,1,1,1,2,2,2,2,2,1,3,1,2,2,67,77.0,neutral or dissatisfied +53026,58945,Male,Loyal Customer,54,Business travel,Business,3409,5,5,5,5,2,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +53027,36433,Male,Loyal Customer,12,Personal Travel,Eco,369,2,1,2,4,5,2,5,5,2,5,3,2,4,5,0,0.0,neutral or dissatisfied +53028,35875,Female,Loyal Customer,67,Personal Travel,Eco,937,4,5,4,1,1,4,1,5,5,4,5,2,5,1,8,0.0,satisfied +53029,118342,Female,disloyal Customer,37,Business travel,Eco,202,3,1,3,3,3,3,1,3,2,1,4,1,4,3,13,15.0,neutral or dissatisfied +53030,716,Female,disloyal Customer,37,Business travel,Business,134,2,2,2,3,1,2,1,1,2,4,4,2,4,1,78,73.0,neutral or dissatisfied +53031,49793,Male,disloyal Customer,16,Business travel,Eco,199,2,2,3,3,2,3,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +53032,90301,Male,Loyal Customer,48,Personal Travel,Eco,932,3,5,3,1,5,3,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +53033,113693,Male,Loyal Customer,50,Personal Travel,Eco,258,3,5,3,5,1,3,4,1,1,4,4,2,1,1,0,0.0,neutral or dissatisfied +53034,119743,Male,Loyal Customer,25,Personal Travel,Eco,1496,1,3,1,2,5,1,5,5,5,5,4,1,1,5,0,0.0,neutral or dissatisfied +53035,76156,Male,Loyal Customer,36,Business travel,Business,3234,3,5,5,5,3,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +53036,56535,Male,Loyal Customer,50,Business travel,Business,1068,5,5,5,5,5,4,4,4,4,4,4,3,4,4,57,49.0,satisfied +53037,98709,Female,Loyal Customer,29,Business travel,Eco Plus,992,3,2,2,2,3,2,3,3,1,4,4,1,3,3,96,87.0,neutral or dissatisfied +53038,73787,Male,disloyal Customer,25,Business travel,Business,204,5,5,5,4,3,5,3,3,5,4,4,4,4,3,0,0.0,satisfied +53039,67339,Female,disloyal Customer,36,Business travel,Business,1471,3,3,3,4,1,3,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +53040,128329,Male,Loyal Customer,38,Business travel,Business,1922,2,2,2,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +53041,57245,Male,Loyal Customer,49,Business travel,Business,804,4,4,1,4,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +53042,65995,Female,Loyal Customer,74,Business travel,Eco Plus,972,2,3,3,3,1,3,3,3,3,2,3,2,3,1,0,27.0,neutral or dissatisfied +53043,103762,Male,Loyal Customer,45,Business travel,Business,2144,1,1,1,1,5,5,4,3,3,3,3,4,3,5,28,16.0,satisfied +53044,33951,Male,Loyal Customer,23,Business travel,Eco Plus,1072,3,5,4,4,3,2,1,3,1,3,4,2,3,3,0,24.0,neutral or dissatisfied +53045,32834,Female,Loyal Customer,40,Personal Travel,Eco,101,2,4,2,5,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +53046,56756,Female,disloyal Customer,12,Business travel,Eco,1085,1,2,2,3,4,2,4,4,3,3,4,3,3,4,0,18.0,neutral or dissatisfied +53047,66793,Female,Loyal Customer,27,Personal Travel,Eco,3784,4,5,4,2,4,3,3,4,5,5,5,3,4,3,16,27.0,neutral or dissatisfied +53048,80514,Male,Loyal Customer,69,Personal Travel,Eco,1749,1,4,1,2,3,1,3,3,3,2,5,1,1,3,6,0.0,neutral or dissatisfied +53049,57598,Female,Loyal Customer,56,Business travel,Business,3053,3,3,3,3,5,4,5,5,5,5,5,4,5,4,33,23.0,satisfied +53050,62,Male,Loyal Customer,31,Business travel,Eco,173,2,5,5,5,2,2,2,1,4,3,4,2,3,2,151,186.0,neutral or dissatisfied +53051,124152,Male,Loyal Customer,57,Business travel,Business,2133,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,1.0,satisfied +53052,71905,Female,Loyal Customer,35,Personal Travel,Eco,1829,3,4,3,3,5,3,5,5,3,3,3,5,5,5,86,95.0,neutral or dissatisfied +53053,80860,Female,Loyal Customer,35,Personal Travel,Eco,484,3,4,1,2,4,1,5,4,1,4,1,4,4,4,8,2.0,neutral or dissatisfied +53054,39527,Female,Loyal Customer,70,Personal Travel,Eco,852,4,4,4,5,5,4,4,3,3,4,1,5,3,5,7,0.0,neutral or dissatisfied +53055,110082,Male,Loyal Customer,44,Business travel,Business,1048,3,3,3,3,2,4,4,4,4,5,4,3,4,3,0,6.0,satisfied +53056,694,Female,Loyal Customer,39,Business travel,Business,2242,5,5,5,5,4,4,4,4,4,5,4,4,4,4,212,208.0,satisfied +53057,52968,Male,Loyal Customer,26,Personal Travel,Eco,2306,3,5,3,3,2,3,1,2,4,2,4,5,4,2,3,0.0,neutral or dissatisfied +53058,108584,Male,Loyal Customer,45,Business travel,Business,696,2,2,2,2,2,4,4,4,4,4,4,4,4,5,3,7.0,satisfied +53059,64501,Female,Loyal Customer,24,Business travel,Business,3156,3,3,5,3,0,1,3,0,2,4,3,4,4,0,40,30.0,neutral or dissatisfied +53060,79399,Female,Loyal Customer,22,Business travel,Business,2503,5,1,2,2,5,4,5,5,4,3,2,4,2,5,114,126.0,neutral or dissatisfied +53061,65651,Male,Loyal Customer,42,Business travel,Business,1603,1,1,3,1,4,4,5,4,4,5,4,4,4,3,23,27.0,satisfied +53062,73326,Female,Loyal Customer,17,Business travel,Business,1005,4,4,4,4,4,4,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +53063,37576,Female,Loyal Customer,58,Business travel,Business,676,5,5,5,5,4,2,1,4,4,4,4,1,4,3,120,120.0,satisfied +53064,116631,Male,Loyal Customer,51,Business travel,Business,1663,0,0,0,1,5,5,5,5,5,1,1,4,5,4,0,0.0,satisfied +53065,30305,Male,Loyal Customer,60,Personal Travel,Eco,1476,3,4,2,3,4,2,4,4,5,3,4,5,4,4,4,19.0,neutral or dissatisfied +53066,84759,Male,Loyal Customer,45,Business travel,Business,1553,5,5,2,5,3,4,4,2,2,2,2,4,2,4,0,11.0,satisfied +53067,25941,Male,Loyal Customer,44,Business travel,Eco Plus,594,4,2,2,2,4,4,4,4,1,1,4,1,3,4,2,0.0,neutral or dissatisfied +53068,57183,Male,Loyal Customer,17,Personal Travel,Eco,2227,1,1,1,2,5,1,5,5,1,5,1,2,2,5,52,49.0,neutral or dissatisfied +53069,19493,Female,Loyal Customer,24,Business travel,Business,566,3,3,3,3,5,5,5,5,2,5,2,5,1,5,97,100.0,satisfied +53070,94879,Female,Loyal Customer,48,Business travel,Business,189,3,4,5,5,2,4,4,3,3,2,3,3,3,1,9,3.0,neutral or dissatisfied +53071,74209,Male,Loyal Customer,54,Personal Travel,Eco Plus,592,3,1,3,1,1,3,1,1,3,4,1,3,1,1,0,0.0,neutral or dissatisfied +53072,117227,Female,Loyal Customer,40,Personal Travel,Eco,621,1,5,1,1,2,1,2,2,3,2,5,4,4,2,12,2.0,neutral or dissatisfied +53073,16525,Male,Loyal Customer,72,Business travel,Eco,209,2,5,5,5,2,2,2,2,2,5,3,2,3,2,0,0.0,satisfied +53074,91116,Male,Loyal Customer,46,Personal Travel,Eco,404,4,3,4,4,3,4,5,3,1,2,1,2,4,3,37,10.0,neutral or dissatisfied +53075,13831,Female,Loyal Customer,43,Business travel,Business,594,4,2,2,2,5,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +53076,24675,Female,Loyal Customer,19,Business travel,Business,3453,1,2,2,2,1,1,1,1,2,1,3,2,3,1,0,0.0,neutral or dissatisfied +53077,123462,Male,disloyal Customer,24,Business travel,Eco,1173,1,1,1,3,2,1,2,2,4,3,3,5,5,2,12,6.0,neutral or dissatisfied +53078,49590,Female,Loyal Customer,60,Business travel,Eco,266,5,2,2,2,5,4,5,5,5,5,5,2,5,2,0,0.0,satisfied +53079,86234,Female,disloyal Customer,30,Personal Travel,Eco,356,5,1,5,4,5,5,5,5,3,2,3,4,4,5,0,0.0,satisfied +53080,25290,Female,Loyal Customer,70,Business travel,Business,321,2,5,5,5,3,2,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +53081,124255,Male,Loyal Customer,25,Business travel,Eco Plus,1916,2,1,1,1,2,2,3,2,4,4,4,2,3,2,0,0.0,neutral or dissatisfied +53082,119744,Male,Loyal Customer,17,Personal Travel,Eco,1303,1,5,1,5,2,1,2,2,3,2,3,4,4,2,75,73.0,neutral or dissatisfied +53083,20852,Female,Loyal Customer,39,Personal Travel,Eco,515,1,5,4,2,4,4,4,4,3,5,4,4,5,4,21,21.0,neutral or dissatisfied +53084,108058,Male,disloyal Customer,38,Business travel,Business,997,5,5,5,3,1,5,1,1,5,4,5,4,5,1,98,64.0,satisfied +53085,7490,Male,disloyal Customer,19,Business travel,Business,925,4,4,4,3,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +53086,127468,Female,Loyal Customer,43,Business travel,Business,2075,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +53087,1604,Male,Loyal Customer,15,Personal Travel,Eco,140,1,2,0,3,2,0,2,2,3,1,3,4,4,2,0,5.0,neutral or dissatisfied +53088,126696,Male,Loyal Customer,40,Business travel,Business,2521,3,3,3,3,4,5,5,4,4,4,4,4,4,3,0,12.0,satisfied +53089,43708,Female,Loyal Customer,33,Business travel,Eco,196,4,4,4,4,4,4,4,4,5,1,2,5,5,4,0,0.0,satisfied +53090,34831,Female,disloyal Customer,24,Business travel,Eco,301,5,0,5,3,4,5,4,4,2,2,3,4,4,4,30,2.0,satisfied +53091,76721,Female,Loyal Customer,52,Business travel,Business,1896,1,1,1,1,3,5,4,2,2,3,2,4,2,4,0,0.0,satisfied +53092,9667,Male,Loyal Customer,63,Business travel,Business,277,3,3,3,3,5,3,3,3,3,3,3,2,3,1,66,78.0,neutral or dissatisfied +53093,71662,Male,Loyal Customer,59,Personal Travel,Eco,1197,3,2,3,4,4,3,2,4,2,5,2,4,4,4,8,1.0,neutral or dissatisfied +53094,104347,Male,Loyal Customer,28,Personal Travel,Eco,409,2,5,2,2,3,2,3,3,4,4,3,4,4,3,0,74.0,neutral or dissatisfied +53095,25354,Male,Loyal Customer,57,Business travel,Business,1984,4,2,2,2,5,4,3,4,4,3,4,3,4,1,8,24.0,neutral or dissatisfied +53096,37779,Male,disloyal Customer,31,Business travel,Business,1069,1,1,1,4,1,2,2,4,1,3,3,2,2,2,126,175.0,neutral or dissatisfied +53097,114750,Female,Loyal Customer,45,Business travel,Business,2967,0,1,1,4,5,5,4,2,2,2,2,5,2,4,4,1.0,satisfied +53098,122247,Male,disloyal Customer,25,Business travel,Eco,141,2,0,2,4,1,2,1,1,5,5,4,5,1,1,4,6.0,neutral or dissatisfied +53099,111507,Male,Loyal Customer,60,Business travel,Business,3369,5,5,5,5,4,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +53100,42299,Female,Loyal Customer,8,Personal Travel,Eco,784,3,2,2,2,5,2,2,5,3,2,2,1,3,5,0,0.0,neutral or dissatisfied +53101,28837,Female,Loyal Customer,49,Business travel,Business,954,4,4,4,4,2,5,2,4,4,4,4,3,4,5,0,0.0,satisfied +53102,129681,Male,disloyal Customer,37,Business travel,Business,337,5,5,5,5,2,5,2,2,5,4,4,5,5,2,0,0.0,satisfied +53103,5033,Female,Loyal Customer,56,Business travel,Business,223,2,2,2,2,2,5,5,5,5,5,5,5,5,4,1,3.0,satisfied +53104,89245,Male,Loyal Customer,44,Personal Travel,Eco Plus,2139,4,5,4,5,5,4,5,5,4,1,5,4,5,5,0,0.0,neutral or dissatisfied +53105,11586,Female,Loyal Customer,58,Business travel,Business,3914,3,3,3,3,2,5,4,5,5,5,5,3,5,4,3,0.0,satisfied +53106,13592,Female,Loyal Customer,42,Personal Travel,Eco,106,3,4,3,2,2,4,5,4,4,3,2,3,4,5,0,0.0,neutral or dissatisfied +53107,61091,Male,Loyal Customer,20,Personal Travel,Eco,1546,4,4,4,4,4,4,4,4,3,3,4,4,4,4,5,2.0,neutral or dissatisfied +53108,38098,Female,Loyal Customer,52,Business travel,Eco,1197,3,5,5,5,4,4,4,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +53109,83113,Female,Loyal Customer,54,Personal Travel,Eco,983,3,1,2,3,2,4,4,5,5,2,5,1,5,4,0,0.0,neutral or dissatisfied +53110,103084,Male,Loyal Customer,45,Personal Travel,Eco,460,3,4,3,5,5,3,5,5,3,3,5,3,4,5,6,0.0,neutral or dissatisfied +53111,97814,Female,Loyal Customer,42,Business travel,Business,1766,3,3,5,3,3,4,4,3,3,3,3,3,3,2,3,0.0,neutral or dissatisfied +53112,28017,Female,Loyal Customer,35,Business travel,Eco,763,4,2,2,2,4,4,4,4,5,4,2,5,5,4,0,0.0,satisfied +53113,111661,Male,Loyal Customer,25,Business travel,Business,1516,4,4,4,4,3,4,3,3,4,4,4,4,5,3,4,7.0,satisfied +53114,129275,Male,Loyal Customer,18,Personal Travel,Eco,2521,1,4,1,4,2,1,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +53115,77856,Female,Loyal Customer,31,Personal Travel,Eco Plus,731,3,3,2,3,2,2,2,2,1,5,3,3,1,2,0,18.0,neutral or dissatisfied +53116,109662,Female,Loyal Customer,54,Business travel,Business,3486,5,5,5,5,2,4,5,4,4,4,4,4,4,3,12,1.0,satisfied +53117,68586,Male,Loyal Customer,68,Personal Travel,Eco,1616,2,4,1,2,1,1,1,1,3,2,3,3,5,1,0,0.0,neutral or dissatisfied +53118,103814,Female,Loyal Customer,35,Business travel,Business,3533,4,4,4,4,5,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +53119,18815,Male,Loyal Customer,41,Business travel,Business,3621,2,2,2,2,1,1,5,5,5,5,5,1,5,4,0,0.0,satisfied +53120,126178,Female,disloyal Customer,37,Business travel,Eco,328,1,1,1,1,5,1,5,5,1,4,2,4,2,5,0,37.0,neutral or dissatisfied +53121,127866,Female,Loyal Customer,30,Business travel,Business,1681,1,1,1,1,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +53122,51979,Female,Loyal Customer,42,Personal Travel,Eco,843,3,4,3,3,3,5,2,2,2,3,2,1,2,5,0,0.0,neutral or dissatisfied +53123,86335,Female,Loyal Customer,32,Personal Travel,Business,760,3,4,3,4,5,3,1,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +53124,54933,Female,Loyal Customer,51,Business travel,Business,1379,1,1,1,1,5,4,5,4,4,4,4,3,4,3,0,9.0,satisfied +53125,25634,Male,Loyal Customer,27,Business travel,Business,526,4,4,4,4,4,4,4,4,3,3,4,2,3,4,4,0.0,neutral or dissatisfied +53126,110804,Female,Loyal Customer,65,Personal Travel,Eco,990,2,4,2,5,5,5,4,1,1,2,1,4,1,3,4,0.0,neutral or dissatisfied +53127,2444,Female,disloyal Customer,8,Business travel,Eco Plus,604,2,3,2,3,2,2,2,2,3,3,4,3,4,2,0,43.0,neutral or dissatisfied +53128,79779,Male,Loyal Customer,33,Personal Travel,Business,950,2,0,2,3,2,2,2,2,4,1,4,3,1,2,20,31.0,neutral or dissatisfied +53129,4112,Male,Loyal Customer,58,Business travel,Business,3133,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +53130,71304,Male,Loyal Customer,40,Business travel,Business,1514,4,4,4,4,5,5,4,2,2,2,2,4,2,3,35,51.0,satisfied +53131,126272,Male,Loyal Customer,46,Personal Travel,Eco,468,4,5,4,2,5,4,5,5,4,4,4,4,4,5,39,35.0,satisfied +53132,93328,Female,Loyal Customer,45,Business travel,Business,3344,3,3,3,3,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +53133,9841,Female,Loyal Customer,40,Business travel,Business,3591,2,2,2,2,5,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +53134,113807,Male,Loyal Customer,63,Business travel,Business,2110,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +53135,117558,Male,Loyal Customer,40,Business travel,Business,1020,4,4,2,4,3,4,4,4,4,3,4,3,4,4,39,40.0,neutral or dissatisfied +53136,21209,Female,Loyal Customer,42,Business travel,Eco,317,2,3,3,3,1,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +53137,122393,Male,Loyal Customer,9,Personal Travel,Eco,529,4,4,5,1,5,5,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +53138,69568,Male,disloyal Customer,48,Business travel,Eco,2475,2,1,1,2,2,5,5,3,1,1,3,5,1,5,0,22.0,neutral or dissatisfied +53139,9344,Female,Loyal Customer,46,Business travel,Business,2082,4,4,4,4,3,5,5,5,5,5,5,4,5,5,8,0.0,satisfied +53140,57555,Male,Loyal Customer,39,Business travel,Business,1597,1,1,3,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +53141,57208,Male,Loyal Customer,42,Business travel,Business,1514,1,1,1,1,2,5,5,4,4,4,4,3,4,4,89,80.0,satisfied +53142,79653,Male,disloyal Customer,17,Business travel,Eco,760,1,1,1,3,3,1,3,3,2,3,5,2,3,3,0,0.0,neutral or dissatisfied +53143,35087,Male,Loyal Customer,32,Business travel,Business,3372,1,1,1,1,4,5,4,4,4,4,1,5,1,4,0,1.0,satisfied +53144,12235,Female,Loyal Customer,56,Business travel,Business,2669,1,1,1,1,1,1,1,5,5,5,3,4,5,1,53,47.0,satisfied +53145,45130,Male,Loyal Customer,28,Business travel,Business,3314,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +53146,63401,Male,Loyal Customer,17,Personal Travel,Eco,337,3,3,3,3,4,3,5,4,3,3,4,3,3,4,94,81.0,neutral or dissatisfied +53147,30607,Male,Loyal Customer,26,Personal Travel,Eco,472,2,5,2,5,2,2,2,2,4,4,5,3,4,2,0,2.0,neutral or dissatisfied +53148,8978,Female,disloyal Customer,22,Business travel,Eco,325,5,3,5,5,2,5,2,2,1,4,1,4,4,2,81,85.0,satisfied +53149,89841,Female,Loyal Customer,55,Business travel,Business,1416,2,2,2,2,3,5,5,3,3,3,3,3,3,4,0,8.0,satisfied +53150,2834,Male,Loyal Customer,42,Business travel,Business,501,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +53151,90519,Male,Loyal Customer,57,Business travel,Business,3306,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +53152,36770,Female,disloyal Customer,28,Business travel,Eco,1246,2,2,2,1,2,3,3,5,2,5,4,3,2,3,6,0.0,neutral or dissatisfied +53153,61602,Male,disloyal Customer,35,Business travel,Business,1609,2,2,2,3,5,2,3,5,4,5,5,4,5,5,0,1.0,neutral or dissatisfied +53154,1738,Male,Loyal Customer,61,Personal Travel,Eco,364,0,2,0,3,3,0,3,3,2,1,4,3,4,3,2,0.0,satisfied +53155,89820,Female,disloyal Customer,38,Business travel,Eco Plus,669,2,1,1,3,2,1,5,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +53156,22525,Female,Loyal Customer,30,Business travel,Eco Plus,143,0,0,0,5,3,0,3,3,3,2,5,1,4,3,0,5.0,satisfied +53157,1184,Female,Loyal Customer,45,Personal Travel,Eco,309,5,4,5,2,3,5,5,1,1,5,1,3,1,3,26,41.0,satisfied +53158,71278,Male,Loyal Customer,7,Personal Travel,Eco,733,2,3,2,5,3,2,3,3,5,4,5,4,4,3,3,0.0,neutral or dissatisfied +53159,85294,Male,Loyal Customer,8,Personal Travel,Eco,731,5,4,5,2,1,5,1,1,2,1,2,3,4,1,0,0.0,satisfied +53160,85175,Female,Loyal Customer,46,Business travel,Business,3430,1,1,1,1,2,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +53161,109786,Male,Loyal Customer,40,Business travel,Business,2029,1,1,2,1,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +53162,1294,Female,Loyal Customer,40,Personal Travel,Eco,282,3,4,3,5,1,3,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +53163,87636,Male,Loyal Customer,47,Business travel,Business,3798,3,3,3,3,2,5,5,4,4,4,4,4,4,3,111,100.0,satisfied +53164,90038,Female,Loyal Customer,40,Business travel,Business,957,5,5,5,5,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +53165,114938,Female,Loyal Customer,39,Business travel,Business,325,1,1,1,1,2,4,4,5,5,5,5,4,5,5,19,9.0,satisfied +53166,55912,Female,Loyal Customer,15,Personal Travel,Eco,733,2,2,2,2,5,2,5,5,2,5,3,3,3,5,0,0.0,neutral or dissatisfied +53167,77938,Female,disloyal Customer,61,Business travel,Business,332,4,4,4,4,3,4,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +53168,70163,Female,Loyal Customer,18,Personal Travel,Eco,550,0,3,0,1,3,0,5,3,2,3,4,2,1,3,0,0.0,satisfied +53169,54700,Female,disloyal Customer,9,Business travel,Eco,787,4,4,4,3,4,4,4,4,4,5,4,4,4,4,12,4.0,neutral or dissatisfied +53170,125979,Female,disloyal Customer,22,Business travel,Eco,631,2,0,2,2,2,2,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +53171,9080,Male,Loyal Customer,40,Personal Travel,Eco,173,3,3,0,3,0,3,5,5,1,1,1,5,5,5,399,432.0,neutral or dissatisfied +53172,101755,Female,Loyal Customer,16,Business travel,Business,1590,4,4,4,4,3,3,3,3,2,5,1,2,5,3,30,0.0,satisfied +53173,45111,Female,disloyal Customer,20,Business travel,Eco,84,3,0,3,2,4,3,5,4,2,5,5,2,2,4,0,0.0,neutral or dissatisfied +53174,76498,Male,Loyal Customer,48,Business travel,Business,534,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +53175,90064,Female,Loyal Customer,60,Business travel,Business,3866,4,4,4,4,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +53176,112337,Female,Loyal Customer,50,Business travel,Business,3931,1,1,1,1,4,5,5,2,2,2,2,3,2,3,9,5.0,satisfied +53177,5311,Male,Loyal Customer,41,Business travel,Business,2257,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +53178,121389,Female,Loyal Customer,64,Business travel,Business,3834,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +53179,66489,Male,Loyal Customer,19,Business travel,Business,3675,4,1,2,2,4,3,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +53180,33093,Female,Loyal Customer,21,Personal Travel,Eco,216,2,0,0,2,2,0,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +53181,122312,Female,Loyal Customer,36,Business travel,Business,573,3,3,4,3,4,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +53182,73160,Male,Loyal Customer,39,Business travel,Business,1145,1,2,2,2,4,3,4,1,1,1,1,1,1,3,0,9.0,neutral or dissatisfied +53183,65672,Female,disloyal Customer,30,Business travel,Eco,926,1,1,1,3,2,1,2,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +53184,103267,Male,Loyal Customer,30,Business travel,Eco,888,0,0,0,2,4,4,3,4,2,2,5,3,2,4,0,0.0,satisfied +53185,52498,Male,Loyal Customer,42,Business travel,Business,160,3,3,3,3,4,4,4,4,4,4,5,4,4,4,0,6.0,satisfied +53186,126157,Male,Loyal Customer,22,Business travel,Business,631,3,5,5,5,3,2,3,3,4,4,2,3,3,3,0,0.0,neutral or dissatisfied +53187,103417,Male,Loyal Customer,62,Personal Travel,Eco,237,3,2,3,2,1,3,1,1,3,5,2,1,2,1,6,21.0,neutral or dissatisfied +53188,120745,Female,Loyal Customer,48,Business travel,Business,3131,2,2,1,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +53189,90325,Male,Loyal Customer,49,Business travel,Business,240,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +53190,33474,Female,Loyal Customer,40,Business travel,Eco,2917,1,3,3,3,1,1,1,2,1,2,4,1,2,1,30,52.0,neutral or dissatisfied +53191,72428,Female,Loyal Customer,37,Business travel,Business,3805,4,4,4,4,3,5,5,5,5,5,5,4,5,4,5,10.0,satisfied +53192,124283,Male,disloyal Customer,24,Business travel,Business,601,4,0,4,4,1,4,1,1,5,4,5,4,4,1,0,0.0,satisfied +53193,126265,Female,Loyal Customer,22,Business travel,Eco,650,1,3,3,3,1,2,3,1,1,3,4,2,4,1,0,0.0,neutral or dissatisfied +53194,34273,Female,disloyal Customer,22,Business travel,Eco,496,5,4,5,4,5,5,5,5,1,1,4,4,2,5,0,0.0,satisfied +53195,92441,Male,Loyal Customer,29,Business travel,Business,1947,3,3,3,3,4,4,4,4,4,5,3,3,5,4,1,0.0,satisfied +53196,84438,Male,Loyal Customer,47,Business travel,Business,606,1,1,1,1,4,5,5,4,4,4,4,3,4,3,4,3.0,satisfied +53197,126861,Male,Loyal Customer,56,Personal Travel,Eco,2125,1,2,1,4,4,1,4,4,1,3,4,1,4,4,4,0.0,neutral or dissatisfied +53198,87875,Female,Loyal Customer,31,Business travel,Eco Plus,214,1,3,3,3,1,1,1,1,3,3,4,4,4,1,11,7.0,neutral or dissatisfied +53199,26622,Female,disloyal Customer,32,Business travel,Eco,545,3,4,3,1,5,3,5,5,5,1,3,1,1,5,0,0.0,neutral or dissatisfied +53200,80327,Female,Loyal Customer,26,Personal Travel,Eco,746,3,4,3,5,3,1,1,5,5,4,5,1,4,1,202,213.0,neutral or dissatisfied +53201,83414,Female,disloyal Customer,25,Business travel,Eco,632,4,2,4,2,3,4,1,3,3,1,3,3,2,3,0,0.0,neutral or dissatisfied +53202,97710,Male,Loyal Customer,40,Business travel,Business,3815,3,3,3,3,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +53203,93841,Female,Loyal Customer,25,Personal Travel,Eco,391,3,5,3,1,5,3,1,5,2,3,4,2,3,5,1,0.0,neutral or dissatisfied +53204,75218,Female,Loyal Customer,43,Business travel,Eco,1744,2,3,1,1,3,5,1,2,2,2,2,3,2,3,0,0.0,satisfied +53205,15380,Female,Loyal Customer,35,Business travel,Business,2298,4,4,4,4,5,5,5,5,1,1,2,5,3,5,271,272.0,satisfied +53206,85199,Female,disloyal Customer,25,Business travel,Eco,1282,1,1,1,3,5,1,5,5,2,3,4,1,4,5,21,14.0,neutral or dissatisfied +53207,112521,Male,Loyal Customer,25,Personal Travel,Eco,862,4,5,4,4,3,4,3,3,3,3,5,5,4,3,14,3.0,neutral or dissatisfied +53208,15428,Female,Loyal Customer,38,Business travel,Business,377,2,2,2,2,2,1,5,2,2,2,2,4,2,3,0,0.0,satisfied +53209,1979,Female,Loyal Customer,46,Personal Travel,Eco,351,2,4,2,5,2,5,4,2,2,2,4,5,2,3,23,28.0,neutral or dissatisfied +53210,81890,Female,Loyal Customer,54,Business travel,Business,1542,2,2,2,2,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +53211,108222,Female,Loyal Customer,11,Business travel,Eco Plus,777,4,1,1,1,4,4,2,4,3,2,3,4,4,4,3,14.0,neutral or dissatisfied +53212,80233,Female,disloyal Customer,36,Business travel,Eco,981,4,4,4,4,5,4,2,5,2,5,3,3,4,5,23,11.0,neutral or dissatisfied +53213,35888,Male,Loyal Customer,39,Personal Travel,Eco,937,2,5,2,1,5,2,5,5,4,3,2,2,5,5,16,42.0,neutral or dissatisfied +53214,111115,Male,Loyal Customer,53,Business travel,Business,2947,1,1,4,1,2,4,4,4,4,4,4,3,4,3,39,17.0,satisfied +53215,91948,Female,Loyal Customer,51,Personal Travel,Eco,2586,3,5,3,2,5,3,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +53216,87809,Female,disloyal Customer,44,Business travel,Eco,214,3,0,4,3,1,4,1,1,3,4,4,2,3,1,28,13.0,neutral or dissatisfied +53217,85686,Female,Loyal Customer,38,Business travel,Business,1547,3,3,5,3,5,5,4,5,5,5,5,3,5,3,0,14.0,satisfied +53218,18394,Female,Loyal Customer,44,Business travel,Business,378,3,3,3,3,2,5,1,4,4,4,4,2,4,4,0,0.0,satisfied +53219,112955,Male,Loyal Customer,11,Personal Travel,Eco,1476,2,4,2,3,3,2,3,3,3,3,3,3,5,3,6,10.0,neutral or dissatisfied +53220,112086,Female,Loyal Customer,70,Personal Travel,Eco,1491,1,4,1,5,2,2,3,2,2,1,2,4,2,2,21,10.0,neutral or dissatisfied +53221,88003,Female,Loyal Customer,41,Business travel,Business,545,2,2,2,2,5,4,4,4,4,4,4,3,4,3,73,67.0,satisfied +53222,120287,Female,Loyal Customer,41,Personal Travel,Eco,1576,3,4,3,3,1,3,1,1,3,2,3,4,4,1,15,6.0,neutral or dissatisfied +53223,82026,Male,Loyal Customer,63,Personal Travel,Eco,1522,5,4,5,2,4,5,4,4,4,2,4,3,5,4,0,0.0,satisfied +53224,22862,Male,Loyal Customer,44,Personal Travel,Eco,147,4,5,0,1,2,0,5,2,5,4,2,4,1,2,0,0.0,neutral or dissatisfied +53225,29341,Female,Loyal Customer,32,Business travel,Eco Plus,933,5,1,3,1,5,5,5,5,3,5,3,5,4,5,0,1.0,satisfied +53226,2172,Male,Loyal Customer,47,Business travel,Business,2531,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +53227,86334,Female,Loyal Customer,32,Personal Travel,Business,760,4,5,4,4,2,4,2,2,1,3,3,3,5,2,8,1.0,neutral or dissatisfied +53228,26030,Male,Loyal Customer,60,Personal Travel,Eco,321,3,5,3,4,1,3,3,1,5,2,2,4,3,1,7,0.0,neutral or dissatisfied +53229,70319,Male,Loyal Customer,35,Business travel,Eco,1501,3,4,2,2,3,3,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +53230,67803,Female,disloyal Customer,47,Business travel,Eco,771,3,3,3,2,1,3,1,1,3,2,3,3,1,1,9,4.0,neutral or dissatisfied +53231,90499,Male,Loyal Customer,30,Business travel,Business,1565,3,3,3,3,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +53232,121390,Male,Loyal Customer,49,Business travel,Business,331,0,0,0,4,2,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +53233,15653,Female,Loyal Customer,50,Business travel,Eco,258,1,2,2,2,1,1,1,3,2,4,3,1,4,1,123,159.0,neutral or dissatisfied +53234,110163,Female,Loyal Customer,43,Personal Travel,Eco,1072,4,5,4,1,4,5,4,3,3,4,3,4,3,4,82,79.0,neutral or dissatisfied +53235,127671,Male,Loyal Customer,31,Business travel,Business,2153,4,4,4,4,4,4,4,4,4,4,3,2,2,4,4,9.0,neutral or dissatisfied +53236,113399,Female,Loyal Customer,50,Business travel,Business,2041,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +53237,81327,Female,Loyal Customer,47,Business travel,Business,2935,4,4,1,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +53238,111729,Male,Loyal Customer,23,Business travel,Eco Plus,495,0,3,0,4,4,0,4,4,1,2,4,5,1,4,13,32.0,satisfied +53239,8174,Male,Loyal Customer,69,Business travel,Business,125,2,2,2,2,3,3,4,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +53240,117330,Female,Loyal Customer,48,Business travel,Business,393,1,1,1,1,4,5,5,2,2,3,2,3,2,3,0,0.0,satisfied +53241,7214,Female,disloyal Customer,23,Business travel,Eco,139,3,1,3,4,5,3,5,5,3,4,4,2,4,5,0,0.0,neutral or dissatisfied +53242,109871,Female,Loyal Customer,22,Business travel,Business,1204,2,3,3,3,2,2,2,2,2,4,4,1,3,2,13,15.0,neutral or dissatisfied +53243,87353,Male,Loyal Customer,70,Business travel,Business,425,3,5,5,5,3,3,3,3,3,3,3,2,3,2,4,0.0,neutral or dissatisfied +53244,15939,Male,disloyal Customer,36,Business travel,Eco,338,2,3,2,4,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +53245,3544,Male,Loyal Customer,61,Personal Travel,Business,227,1,4,1,3,2,4,4,2,2,1,4,1,2,4,4,0.0,neutral or dissatisfied +53246,90001,Female,Loyal Customer,43,Business travel,Business,2399,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +53247,70916,Male,Loyal Customer,59,Business travel,Business,612,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +53248,15802,Female,Loyal Customer,67,Personal Travel,Eco,282,4,4,4,1,5,5,5,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +53249,48280,Female,Loyal Customer,53,Personal Travel,Eco Plus,236,3,5,3,3,4,5,1,2,2,3,1,5,2,2,30,21.0,neutral or dissatisfied +53250,121539,Female,Loyal Customer,60,Business travel,Business,1625,3,1,1,1,1,3,4,3,3,2,3,3,3,2,9,10.0,neutral or dissatisfied +53251,102086,Male,Loyal Customer,43,Business travel,Business,3347,0,4,0,3,5,4,5,3,3,3,3,5,3,3,3,2.0,satisfied +53252,82358,Female,Loyal Customer,40,Business travel,Eco,453,1,2,1,2,1,2,1,1,2,4,4,1,4,1,4,50.0,neutral or dissatisfied +53253,53098,Male,Loyal Customer,58,Business travel,Business,1628,1,3,3,3,5,3,3,1,1,1,1,4,1,2,0,11.0,neutral or dissatisfied +53254,90369,Female,Loyal Customer,41,Business travel,Business,240,3,3,3,3,3,3,3,3,3,3,3,4,3,4,52,58.0,neutral or dissatisfied +53255,3067,Female,Loyal Customer,41,Business travel,Business,594,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +53256,125660,Male,Loyal Customer,22,Business travel,Business,814,2,4,4,4,2,2,2,2,4,3,3,3,3,2,0,0.0,neutral or dissatisfied +53257,103119,Female,Loyal Customer,66,Personal Travel,Eco,490,3,4,3,2,1,1,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +53258,120257,Male,Loyal Customer,26,Personal Travel,Eco Plus,1303,3,5,3,1,2,3,4,2,4,5,5,3,5,2,0,11.0,neutral or dissatisfied +53259,73712,Female,Loyal Customer,27,Business travel,Business,204,1,1,1,1,5,5,3,5,4,2,2,3,5,5,0,0.0,satisfied +53260,3956,Male,Loyal Customer,24,Business travel,Business,2959,1,4,4,4,1,1,1,1,2,3,3,2,4,1,29,55.0,neutral or dissatisfied +53261,129426,Male,Loyal Customer,46,Business travel,Business,3337,1,5,1,1,5,4,3,1,1,1,1,1,1,1,11,7.0,neutral or dissatisfied +53262,28325,Female,Loyal Customer,20,Business travel,Business,867,1,2,2,2,1,2,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +53263,94629,Female,Loyal Customer,77,Business travel,Business,2347,2,3,3,3,3,4,3,2,2,2,2,3,2,1,3,4.0,neutral or dissatisfied +53264,56251,Female,Loyal Customer,57,Business travel,Business,2172,3,3,3,3,4,4,5,4,4,4,4,4,4,4,12,12.0,satisfied +53265,8100,Male,disloyal Customer,23,Business travel,Business,402,4,0,4,3,5,4,5,5,5,4,4,3,4,5,0,11.0,satisfied +53266,76671,Male,Loyal Customer,43,Personal Travel,Eco,481,3,1,3,2,4,3,4,4,1,3,2,1,2,4,43,62.0,neutral or dissatisfied +53267,97568,Male,Loyal Customer,43,Business travel,Business,1563,0,0,0,5,3,5,5,2,2,2,2,4,2,4,80,74.0,satisfied +53268,30033,Male,Loyal Customer,46,Business travel,Business,2911,1,1,1,1,4,3,2,5,5,5,3,4,5,3,0,0.0,satisfied +53269,80958,Female,Loyal Customer,42,Personal Travel,Business,228,2,2,2,2,4,3,2,3,3,2,3,2,3,3,0,18.0,neutral or dissatisfied +53270,39349,Female,Loyal Customer,56,Business travel,Business,896,5,5,5,5,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +53271,30227,Female,Loyal Customer,47,Business travel,Eco,826,4,5,5,5,3,2,3,4,4,4,4,3,4,1,0,0.0,satisfied +53272,44899,Male,Loyal Customer,37,Business travel,Business,2984,2,1,1,1,4,2,1,3,3,3,2,2,3,2,72,109.0,neutral or dissatisfied +53273,11193,Male,Loyal Customer,41,Personal Travel,Eco,224,2,5,0,5,3,0,3,3,1,1,1,3,4,3,31,42.0,neutral or dissatisfied +53274,88005,Female,Loyal Customer,42,Business travel,Business,2066,5,5,5,5,5,5,5,4,4,4,4,5,4,5,23,10.0,satisfied +53275,45399,Male,Loyal Customer,72,Business travel,Business,2143,3,2,2,2,5,3,2,3,3,4,3,4,3,3,36,43.0,neutral or dissatisfied +53276,42956,Male,Loyal Customer,33,Business travel,Eco,236,4,4,4,4,4,4,4,4,2,3,2,5,4,4,0,14.0,satisfied +53277,104228,Male,Loyal Customer,48,Personal Travel,Eco,680,1,2,1,3,2,1,3,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +53278,36149,Female,Loyal Customer,48,Business travel,Eco,818,5,1,1,1,5,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +53279,124801,Male,Loyal Customer,25,Business travel,Business,280,2,5,5,5,2,2,2,4,4,4,3,2,2,2,178,221.0,neutral or dissatisfied +53280,73366,Female,Loyal Customer,35,Business travel,Business,2369,2,1,3,3,2,4,4,2,2,2,2,3,2,1,0,6.0,neutral or dissatisfied +53281,64120,Female,Loyal Customer,45,Business travel,Business,2311,2,2,2,2,5,5,5,4,4,5,5,5,3,5,0,21.0,satisfied +53282,26494,Female,Loyal Customer,8,Business travel,Business,3087,3,2,2,2,3,3,3,3,3,1,3,2,3,3,5,0.0,neutral or dissatisfied +53283,48686,Male,disloyal Customer,38,Business travel,Business,109,4,4,4,4,4,4,4,4,5,3,4,4,5,4,3,4.0,neutral or dissatisfied +53284,7923,Female,Loyal Customer,18,Personal Travel,Eco,1020,5,0,5,4,2,5,2,2,5,5,4,4,4,2,0,0.0,satisfied +53285,127539,Female,disloyal Customer,26,Business travel,Eco,1009,2,2,2,3,2,2,2,2,1,1,3,3,3,2,0,1.0,neutral or dissatisfied +53286,29889,Male,Loyal Customer,52,Business travel,Business,1532,3,3,3,3,2,2,5,4,4,4,4,1,4,4,0,0.0,satisfied +53287,71696,Female,Loyal Customer,55,Personal Travel,Eco,1197,2,5,2,3,3,3,5,2,2,2,2,4,2,3,15,5.0,neutral or dissatisfied +53288,72461,Male,Loyal Customer,34,Business travel,Business,2960,1,3,3,3,4,2,2,1,1,1,1,3,1,1,16,13.0,neutral or dissatisfied +53289,85606,Male,Loyal Customer,31,Personal Travel,Eco,153,1,5,1,1,3,1,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +53290,32466,Male,Loyal Customer,44,Business travel,Eco,101,5,3,3,3,5,5,5,5,5,4,1,2,4,5,0,5.0,satisfied +53291,106151,Female,Loyal Customer,36,Business travel,Eco,302,5,5,5,5,5,5,5,5,5,5,2,4,3,5,0,0.0,satisfied +53292,92258,Female,Loyal Customer,13,Personal Travel,Eco,1670,2,2,2,3,1,2,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +53293,52981,Male,Loyal Customer,25,Business travel,Business,2012,3,5,5,5,3,3,3,3,2,1,2,1,3,3,0,13.0,neutral or dissatisfied +53294,37435,Male,Loyal Customer,24,Business travel,Business,944,4,3,3,3,4,4,4,4,1,3,3,4,2,4,0,0.0,neutral or dissatisfied +53295,122549,Male,Loyal Customer,61,Business travel,Business,500,4,4,5,4,3,4,4,5,5,5,5,3,5,4,2,2.0,satisfied +53296,82777,Female,Loyal Customer,29,Personal Travel,Eco,926,4,4,4,1,4,4,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +53297,19026,Male,Loyal Customer,50,Personal Travel,Eco,788,5,3,5,3,3,5,3,3,1,1,3,4,2,3,0,0.0,satisfied +53298,64119,Male,Loyal Customer,38,Business travel,Eco,2288,4,4,4,4,3,4,4,3,5,3,4,4,2,4,0,0.0,neutral or dissatisfied +53299,33899,Female,Loyal Customer,44,Personal Travel,Eco,1226,2,5,2,3,1,3,4,1,1,2,1,2,1,3,7,11.0,neutral or dissatisfied +53300,44782,Male,Loyal Customer,36,Business travel,Business,1952,1,1,1,1,5,3,1,5,5,5,5,2,5,2,30,48.0,satisfied +53301,28939,Female,disloyal Customer,22,Business travel,Business,954,3,3,2,4,1,2,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +53302,86908,Female,Loyal Customer,48,Business travel,Business,2791,1,1,1,1,2,4,4,4,4,4,4,5,4,4,4,7.0,satisfied +53303,2861,Female,disloyal Customer,24,Business travel,Eco,409,4,0,4,4,2,4,2,2,4,5,4,4,4,2,0,0.0,satisfied +53304,39627,Male,Loyal Customer,43,Personal Travel,Eco,679,1,5,1,2,2,1,2,2,4,3,4,5,5,2,0,11.0,neutral or dissatisfied +53305,28734,Female,Loyal Customer,38,Personal Travel,Eco,2149,4,5,4,5,4,2,2,5,3,4,5,2,5,2,0,20.0,neutral or dissatisfied +53306,88976,Female,Loyal Customer,22,Personal Travel,Eco,1199,2,2,2,4,1,2,1,1,2,3,3,3,4,1,55,82.0,neutral or dissatisfied +53307,99684,Female,disloyal Customer,39,Business travel,Business,442,2,2,2,1,5,2,5,5,4,2,4,4,5,5,2,0.0,neutral or dissatisfied +53308,9876,Female,Loyal Customer,41,Business travel,Business,457,2,2,2,2,2,4,5,4,4,4,4,3,4,4,24,27.0,satisfied +53309,59186,Male,Loyal Customer,58,Personal Travel,Business,1440,5,4,5,4,4,5,4,5,5,5,3,3,5,5,14,14.0,satisfied +53310,80631,Female,Loyal Customer,49,Business travel,Business,3980,0,0,0,4,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +53311,9683,Female,disloyal Customer,20,Business travel,Eco,284,1,3,1,3,1,4,4,1,1,3,4,4,3,4,183,176.0,neutral or dissatisfied +53312,98292,Female,Loyal Customer,60,Personal Travel,Eco,1072,3,5,3,4,3,5,5,5,5,3,5,3,5,4,9,2.0,neutral or dissatisfied +53313,120157,Male,disloyal Customer,54,Business travel,Eco,878,4,4,4,4,4,4,4,4,3,1,3,4,5,4,0,0.0,satisfied +53314,42769,Male,Loyal Customer,43,Business travel,Business,493,1,1,1,1,4,5,1,5,5,5,5,2,5,5,0,0.0,satisfied +53315,2993,Female,Loyal Customer,37,Business travel,Business,3755,1,1,1,1,4,4,5,4,4,4,4,5,4,3,30,74.0,satisfied +53316,30224,Male,Loyal Customer,26,Business travel,Business,826,1,1,4,1,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +53317,59748,Male,disloyal Customer,22,Business travel,Eco,895,4,4,4,2,2,4,2,2,3,4,5,3,4,2,7,0.0,neutral or dissatisfied +53318,35778,Male,disloyal Customer,19,Business travel,Eco,200,2,0,3,2,1,3,1,1,2,3,4,1,1,1,0,0.0,neutral or dissatisfied +53319,112954,Male,Loyal Customer,67,Personal Travel,Eco,1211,4,4,4,3,2,4,2,2,1,5,4,2,4,2,8,13.0,neutral or dissatisfied +53320,53412,Male,Loyal Customer,47,Business travel,Business,2253,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +53321,35925,Female,Loyal Customer,24,Business travel,Business,2381,4,2,4,4,5,5,5,5,3,5,5,4,4,5,31,11.0,satisfied +53322,127071,Male,Loyal Customer,53,Business travel,Business,325,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +53323,80894,Female,Loyal Customer,25,Personal Travel,Eco Plus,692,4,4,4,2,4,4,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +53324,45350,Female,Loyal Customer,46,Personal Travel,Eco,188,3,4,3,3,3,5,4,2,2,3,2,3,2,4,3,0.0,neutral or dissatisfied +53325,61451,Male,Loyal Customer,33,Business travel,Business,2419,2,2,2,2,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +53326,44432,Male,Loyal Customer,30,Business travel,Eco,542,5,3,1,3,5,4,5,5,2,3,1,2,4,5,8,12.0,satisfied +53327,127377,Female,Loyal Customer,44,Business travel,Business,872,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,2.0,satisfied +53328,2178,Female,Loyal Customer,39,Business travel,Business,624,2,2,2,2,4,3,2,2,2,2,2,2,2,2,26,33.0,neutral or dissatisfied +53329,106654,Female,Loyal Customer,57,Business travel,Business,1590,3,3,3,3,4,4,4,5,4,4,5,4,5,4,146,164.0,satisfied +53330,53583,Female,disloyal Customer,24,Business travel,Eco,391,2,3,2,2,3,2,3,3,4,3,5,4,5,3,2,0.0,neutral or dissatisfied +53331,59123,Male,Loyal Customer,9,Personal Travel,Eco,1744,1,4,1,3,4,1,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +53332,107008,Male,disloyal Customer,20,Business travel,Eco,972,2,2,2,4,4,2,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +53333,54898,Female,Loyal Customer,23,Personal Travel,Eco,862,2,5,2,4,3,2,1,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +53334,16768,Female,Loyal Customer,56,Business travel,Eco,642,3,5,5,5,5,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +53335,105379,Female,disloyal Customer,24,Business travel,Eco,369,2,0,2,5,5,2,1,5,5,3,5,3,4,5,28,27.0,neutral or dissatisfied +53336,38575,Male,Loyal Customer,44,Personal Travel,Eco,2586,4,5,5,2,1,5,1,1,4,1,3,1,3,1,0,0.0,satisfied +53337,25158,Female,Loyal Customer,46,Business travel,Business,2106,4,4,4,4,2,5,2,5,5,5,5,1,5,1,72,74.0,satisfied +53338,13397,Male,Loyal Customer,22,Personal Travel,Eco,505,2,1,2,2,5,2,5,5,3,2,3,1,3,5,0,0.0,neutral or dissatisfied +53339,100832,Male,Loyal Customer,51,Business travel,Business,711,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +53340,99043,Male,Loyal Customer,57,Business travel,Business,2035,0,5,0,5,3,5,5,2,2,2,2,5,2,3,0,36.0,satisfied +53341,12855,Male,Loyal Customer,33,Personal Travel,Eco,528,3,2,3,3,4,3,4,4,2,4,4,1,4,4,22,19.0,neutral or dissatisfied +53342,69528,Female,Loyal Customer,44,Business travel,Business,2475,2,2,2,2,3,4,5,4,4,5,4,5,4,5,18,0.0,satisfied +53343,60330,Male,disloyal Customer,25,Business travel,Business,1024,1,5,1,1,5,1,5,5,5,3,4,5,5,5,0,8.0,neutral or dissatisfied +53344,122551,Female,Loyal Customer,48,Business travel,Eco,500,2,2,2,2,2,4,4,2,2,2,2,1,2,2,40,40.0,neutral or dissatisfied +53345,16081,Female,disloyal Customer,29,Business travel,Eco Plus,744,3,3,3,5,4,3,4,4,4,5,3,1,1,4,1,2.0,neutral or dissatisfied +53346,95085,Female,Loyal Customer,60,Personal Travel,Eco,496,5,5,4,1,2,4,4,2,2,4,2,3,2,5,0,0.0,satisfied +53347,127235,Female,Loyal Customer,14,Personal Travel,Eco,1460,3,5,3,3,4,3,4,4,4,3,5,4,4,4,5,0.0,neutral or dissatisfied +53348,2490,Male,Loyal Customer,30,Business travel,Business,1379,1,5,5,5,1,1,1,1,3,5,3,1,3,1,30,32.0,neutral or dissatisfied +53349,26551,Male,disloyal Customer,23,Business travel,Business,1105,4,0,4,4,1,4,1,1,4,2,4,5,4,1,0,0.0,satisfied +53350,39080,Male,Loyal Customer,31,Personal Travel,Business,984,3,3,3,3,2,3,5,2,5,1,5,2,2,2,0,0.0,neutral or dissatisfied +53351,35767,Male,Loyal Customer,33,Business travel,Business,2753,0,5,0,3,5,5,5,5,5,3,4,5,2,5,0,0.0,satisfied +53352,95225,Female,Loyal Customer,24,Personal Travel,Eco,248,1,5,0,4,2,0,2,2,3,3,5,3,4,2,1,0.0,neutral or dissatisfied +53353,129112,Male,Loyal Customer,42,Business travel,Business,2342,1,1,1,1,4,4,4,3,2,3,5,4,3,4,13,9.0,satisfied +53354,128729,Male,Loyal Customer,42,Personal Travel,Eco,1235,1,4,1,2,5,1,1,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +53355,33729,Female,Loyal Customer,54,Personal Travel,Eco,759,3,4,3,4,5,4,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +53356,46285,Female,disloyal Customer,23,Business travel,Eco Plus,624,3,1,3,3,2,3,4,2,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +53357,51491,Female,disloyal Customer,30,Business travel,Business,451,2,2,2,4,5,2,3,5,1,4,3,1,3,5,0,11.0,neutral or dissatisfied +53358,64056,Male,disloyal Customer,19,Business travel,Eco,921,0,0,0,2,5,0,4,5,3,2,5,5,5,5,0,0.0,satisfied +53359,36273,Male,Loyal Customer,53,Personal Travel,Eco,612,2,5,2,1,3,2,3,3,5,5,5,4,4,3,2,5.0,neutral or dissatisfied +53360,37391,Male,Loyal Customer,37,Business travel,Eco,1076,4,1,4,1,4,4,4,4,1,4,3,5,5,4,0,0.0,satisfied +53361,73902,Male,disloyal Customer,29,Business travel,Business,2342,2,2,2,1,4,2,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +53362,33988,Female,disloyal Customer,26,Business travel,Eco,1598,4,4,4,2,1,4,1,1,3,3,2,3,3,1,6,0.0,neutral or dissatisfied +53363,119049,Male,Loyal Customer,54,Business travel,Business,2279,2,2,2,2,2,5,5,5,5,5,5,4,5,4,0,13.0,satisfied +53364,96233,Female,Loyal Customer,62,Business travel,Eco,786,1,2,2,2,1,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +53365,46951,Male,disloyal Customer,56,Personal Travel,Eco,845,3,5,3,1,1,3,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +53366,62908,Female,Loyal Customer,44,Personal Travel,Business,862,3,3,3,3,2,4,3,5,5,3,5,2,5,1,13,0.0,neutral or dissatisfied +53367,44137,Female,Loyal Customer,80,Business travel,Business,2858,1,1,1,1,5,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +53368,14691,Male,Loyal Customer,27,Business travel,Eco,479,0,0,0,4,1,0,1,1,2,2,2,1,3,1,0,0.0,satisfied +53369,12071,Female,Loyal Customer,49,Personal Travel,Eco,351,1,5,1,3,2,5,4,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +53370,52492,Female,Loyal Customer,30,Personal Travel,Eco Plus,370,3,4,3,4,4,3,4,4,1,2,1,1,5,4,13,92.0,neutral or dissatisfied +53371,82879,Female,disloyal Customer,22,Business travel,Business,594,1,3,1,4,1,1,1,1,1,1,4,2,3,1,12,9.0,neutral or dissatisfied +53372,50224,Female,Loyal Customer,50,Business travel,Eco,86,2,2,2,2,3,1,1,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +53373,91782,Male,Loyal Customer,53,Personal Travel,Eco,532,3,4,3,2,1,3,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +53374,45838,Male,Loyal Customer,68,Personal Travel,Eco,517,1,5,1,5,5,1,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +53375,116936,Male,Loyal Customer,44,Business travel,Business,304,5,5,5,5,3,5,5,5,5,5,5,5,5,3,49,55.0,satisfied +53376,10839,Male,Loyal Customer,58,Business travel,Business,316,3,1,4,4,4,3,3,3,3,3,3,2,3,3,4,5.0,neutral or dissatisfied +53377,123884,Male,Loyal Customer,33,Business travel,Business,541,5,5,5,5,2,2,2,2,3,3,3,5,1,2,0,0.0,satisfied +53378,75191,Female,disloyal Customer,38,Business travel,Business,1652,3,3,3,4,5,3,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +53379,40325,Male,Loyal Customer,23,Business travel,Eco Plus,531,4,2,2,2,4,4,1,4,2,2,3,4,3,4,3,0.0,neutral or dissatisfied +53380,39288,Male,Loyal Customer,25,Personal Travel,Eco,108,3,2,3,2,5,3,3,5,3,2,3,1,2,5,0,0.0,neutral or dissatisfied +53381,92293,Female,disloyal Customer,40,Business travel,Business,1814,3,3,3,3,1,3,1,1,5,5,3,3,4,1,0,0.0,neutral or dissatisfied +53382,101870,Female,Loyal Customer,56,Business travel,Eco,1747,4,1,1,1,1,2,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +53383,101216,Female,Loyal Customer,18,Personal Travel,Eco,583,2,5,2,3,5,2,5,5,5,4,5,3,5,5,37,26.0,neutral or dissatisfied +53384,78400,Female,Loyal Customer,60,Personal Travel,Eco Plus,980,2,5,2,4,2,3,3,4,4,4,4,3,3,3,126,168.0,neutral or dissatisfied +53385,110390,Male,disloyal Customer,16,Business travel,Eco,787,3,3,3,4,3,3,3,3,1,3,4,1,4,3,16,4.0,neutral or dissatisfied +53386,55363,Female,disloyal Customer,51,Business travel,Eco,594,3,4,3,3,4,3,4,4,4,1,3,4,4,4,2,1.0,neutral or dissatisfied +53387,100859,Female,Loyal Customer,56,Personal Travel,Eco Plus,711,1,2,1,4,2,4,3,4,4,1,4,2,4,1,0,13.0,neutral or dissatisfied +53388,20020,Female,Loyal Customer,50,Business travel,Business,528,2,4,4,4,3,4,3,2,2,2,2,2,2,1,24,16.0,neutral or dissatisfied +53389,34423,Male,Loyal Customer,17,Personal Travel,Eco Plus,612,4,4,4,3,3,4,3,3,1,1,3,2,4,3,0,0.0,neutral or dissatisfied +53390,88632,Female,Loyal Customer,35,Personal Travel,Eco,515,2,4,4,5,1,4,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +53391,28625,Male,Loyal Customer,55,Business travel,Eco,2614,4,1,1,1,5,4,5,5,1,3,5,1,1,5,1,1.0,satisfied +53392,88892,Female,Loyal Customer,51,Business travel,Eco,859,2,4,4,4,2,2,2,1,4,3,4,2,2,2,132,119.0,neutral or dissatisfied +53393,43539,Male,Loyal Customer,30,Personal Travel,Eco,643,3,4,2,3,2,2,2,2,4,4,4,3,4,2,20,28.0,neutral or dissatisfied +53394,35268,Female,Loyal Customer,63,Business travel,Eco,1069,5,4,4,4,4,4,5,5,5,5,5,1,5,5,26,17.0,satisfied +53395,26624,Male,Loyal Customer,46,Business travel,Business,581,3,3,3,3,5,4,5,5,5,5,5,1,5,2,0,0.0,satisfied +53396,55715,Male,Loyal Customer,35,Personal Travel,Eco,895,4,5,4,1,3,4,3,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +53397,22162,Male,disloyal Customer,38,Business travel,Eco,606,2,0,2,3,4,2,1,4,5,1,1,2,3,4,29,32.0,neutral or dissatisfied +53398,65511,Male,Loyal Customer,13,Business travel,Business,1616,2,2,2,2,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +53399,30128,Female,Loyal Customer,18,Personal Travel,Eco,571,1,4,1,1,2,1,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +53400,18866,Female,Loyal Customer,47,Business travel,Eco,500,4,1,1,1,2,3,1,3,3,4,3,4,3,5,0,0.0,satisfied +53401,35673,Female,Loyal Customer,11,Business travel,Eco,2576,0,5,0,5,0,5,5,1,2,5,5,5,2,5,160,,satisfied +53402,19148,Male,Loyal Customer,59,Business travel,Eco,304,3,4,5,5,4,3,4,4,2,1,4,2,4,4,0,6.0,satisfied +53403,25064,Male,Loyal Customer,35,Personal Travel,Eco,594,2,3,3,3,2,3,2,2,3,2,5,4,4,2,10,1.0,neutral or dissatisfied +53404,81292,Female,Loyal Customer,15,Personal Travel,Eco,1020,3,1,3,2,4,3,4,4,3,4,3,1,2,4,15,46.0,neutral or dissatisfied +53405,128953,Female,Loyal Customer,68,Business travel,Eco,414,1,5,5,5,2,3,4,1,1,1,1,3,1,1,0,2.0,neutral or dissatisfied +53406,98215,Female,Loyal Customer,47,Business travel,Business,842,3,3,1,3,4,5,5,4,4,4,4,5,4,5,7,15.0,satisfied +53407,89645,Male,Loyal Customer,59,Business travel,Business,3568,4,2,2,2,2,4,3,4,4,4,4,1,4,2,2,0.0,neutral or dissatisfied +53408,24472,Female,Loyal Customer,37,Business travel,Eco,481,4,3,3,3,4,4,4,4,1,5,1,4,3,4,0,14.0,satisfied +53409,41586,Female,Loyal Customer,7,Personal Travel,Eco,1211,2,3,2,3,2,2,2,2,1,2,3,3,3,2,88,78.0,neutral or dissatisfied +53410,72569,Male,Loyal Customer,44,Business travel,Business,3113,2,2,2,2,4,5,5,4,4,4,4,1,4,1,3,0.0,satisfied +53411,33842,Female,Loyal Customer,22,Business travel,Business,1562,2,3,3,3,2,2,2,2,4,4,3,3,3,2,34,20.0,neutral or dissatisfied +53412,115562,Male,disloyal Customer,41,Business travel,Eco,404,2,1,2,2,3,2,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +53413,85997,Female,Loyal Customer,45,Business travel,Business,528,5,5,5,5,5,5,4,5,5,5,5,5,5,3,79,68.0,satisfied +53414,23107,Male,Loyal Customer,38,Business travel,Business,2976,0,0,0,1,1,2,2,5,5,5,5,2,5,4,0,0.0,satisfied +53415,29746,Male,Loyal Customer,53,Business travel,Business,234,0,0,0,4,3,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +53416,67730,Female,Loyal Customer,33,Business travel,Business,1464,3,3,3,3,5,5,5,4,4,4,4,3,4,5,47,42.0,satisfied +53417,69425,Male,Loyal Customer,73,Business travel,Eco,689,3,3,3,3,3,3,3,3,1,4,4,2,3,3,14,23.0,neutral or dissatisfied +53418,56187,Female,Loyal Customer,15,Personal Travel,Eco,1400,1,4,1,4,2,1,2,2,2,3,2,5,3,2,0,0.0,neutral or dissatisfied +53419,84694,Female,Loyal Customer,17,Personal Travel,Eco,2182,3,2,3,2,3,3,3,3,4,4,2,1,2,3,1,14.0,neutral or dissatisfied +53420,62915,Female,Loyal Customer,59,Business travel,Business,1988,2,2,2,2,4,4,4,4,4,4,4,4,4,3,114,106.0,satisfied +53421,105324,Male,Loyal Customer,47,Business travel,Business,452,2,2,2,2,2,4,4,5,5,5,5,5,5,3,32,21.0,satisfied +53422,60936,Female,Loyal Customer,39,Business travel,Business,3518,1,1,1,1,4,5,4,4,4,5,4,5,4,5,31,26.0,satisfied +53423,23677,Female,disloyal Customer,37,Business travel,Eco,251,2,4,2,3,2,2,2,2,3,1,4,3,1,2,0,0.0,neutral or dissatisfied +53424,127087,Male,Loyal Customer,24,Business travel,Eco,251,2,3,3,3,2,2,1,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +53425,104296,Male,Loyal Customer,47,Personal Travel,Eco,440,3,5,3,3,2,3,1,2,5,4,4,3,4,2,70,70.0,neutral or dissatisfied +53426,475,Female,Loyal Customer,59,Business travel,Business,3517,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +53427,23771,Female,Loyal Customer,19,Personal Travel,Business,438,1,1,3,4,2,3,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +53428,76930,Male,Loyal Customer,45,Business travel,Business,1823,1,1,1,1,5,4,4,4,4,5,4,4,4,4,5,0.0,satisfied +53429,106716,Female,disloyal Customer,20,Business travel,Eco,829,3,3,3,1,2,3,2,2,5,5,5,5,4,2,10,10.0,neutral or dissatisfied +53430,29249,Female,disloyal Customer,31,Business travel,Eco,933,1,0,0,3,2,0,2,2,4,4,3,3,2,2,0,0.0,neutral or dissatisfied +53431,88558,Female,Loyal Customer,67,Personal Travel,Eco,404,1,5,1,3,5,5,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +53432,111882,Male,Loyal Customer,60,Business travel,Eco,628,3,1,1,1,3,3,3,3,1,5,2,1,2,3,23,33.0,neutral or dissatisfied +53433,40487,Male,Loyal Customer,14,Personal Travel,Eco,188,1,5,1,4,1,5,5,5,3,4,5,5,5,5,148,129.0,neutral or dissatisfied +53434,24519,Male,Loyal Customer,11,Personal Travel,Eco Plus,516,3,5,4,2,5,4,4,5,4,4,1,2,5,5,0,22.0,neutral or dissatisfied +53435,1140,Female,Loyal Customer,40,Personal Travel,Eco,282,2,3,2,3,4,2,4,4,2,1,4,2,3,4,10,6.0,neutral or dissatisfied +53436,56049,Male,Loyal Customer,30,Business travel,Eco,2475,4,2,2,2,4,4,4,1,2,4,4,4,1,4,0,3.0,neutral or dissatisfied +53437,52053,Male,Loyal Customer,43,Business travel,Business,2724,4,4,5,4,1,2,2,2,2,2,2,3,2,2,0,0.0,satisfied +53438,79033,Female,Loyal Customer,50,Business travel,Business,3974,4,4,4,4,4,5,5,5,5,5,5,3,5,3,10,0.0,satisfied +53439,9657,Male,Loyal Customer,38,Business travel,Business,212,2,2,2,2,4,4,4,5,5,5,4,5,5,5,44,19.0,satisfied +53440,54811,Male,Loyal Customer,33,Business travel,Business,862,2,2,5,2,4,4,4,4,5,2,3,2,5,4,15,4.0,satisfied +53441,106045,Male,Loyal Customer,39,Business travel,Business,2865,3,2,2,2,3,2,3,3,3,3,3,3,3,3,13,26.0,neutral or dissatisfied +53442,86255,Female,Loyal Customer,21,Personal Travel,Eco,356,2,4,2,1,4,2,4,4,5,3,3,1,5,4,0,0.0,neutral or dissatisfied +53443,104500,Male,Loyal Customer,39,Business travel,Business,1609,3,3,2,3,5,5,5,3,3,4,3,4,3,3,1,1.0,satisfied +53444,82637,Male,Loyal Customer,46,Business travel,Business,2068,5,5,5,5,5,5,5,4,4,4,4,5,4,3,0,7.0,satisfied +53445,32470,Male,disloyal Customer,26,Business travel,Business,216,3,0,3,3,2,3,2,2,1,1,4,1,4,2,0,0.0,neutral or dissatisfied +53446,50710,Male,Loyal Customer,9,Personal Travel,Eco,89,2,4,2,1,5,2,5,5,4,3,4,5,4,5,0,9.0,neutral or dissatisfied +53447,52996,Male,Loyal Customer,53,Business travel,Business,1208,2,2,2,2,1,4,5,3,3,4,3,4,3,2,0,2.0,satisfied +53448,101482,Male,Loyal Customer,60,Business travel,Business,345,4,4,4,4,3,5,5,4,4,4,4,3,4,5,1,6.0,satisfied +53449,21527,Male,Loyal Customer,24,Personal Travel,Eco,306,2,4,2,3,4,2,4,4,3,3,5,3,5,4,4,0.0,neutral or dissatisfied +53450,56587,Male,Loyal Customer,55,Business travel,Business,997,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +53451,49812,Female,Loyal Customer,41,Business travel,Eco,373,4,4,4,4,4,4,4,4,1,1,3,1,4,4,6,0.0,satisfied +53452,6873,Male,Loyal Customer,31,Personal Travel,Eco,622,2,4,2,1,5,2,5,5,3,3,5,4,4,5,2,3.0,neutral or dissatisfied +53453,73723,Female,disloyal Customer,43,Business travel,Eco,192,1,4,1,2,1,1,1,1,4,4,4,4,3,1,21,12.0,neutral or dissatisfied +53454,81135,Male,Loyal Customer,69,Personal Travel,Eco,991,3,5,4,2,2,4,2,2,3,2,4,3,5,2,1,4.0,neutral or dissatisfied +53455,128216,Female,disloyal Customer,36,Business travel,Business,602,4,4,4,2,5,4,5,5,4,3,4,3,5,5,57,68.0,neutral or dissatisfied +53456,82076,Female,Loyal Customer,45,Business travel,Business,1276,1,1,4,1,2,4,5,4,4,4,4,3,4,4,7,0.0,satisfied +53457,92610,Female,Loyal Customer,13,Personal Travel,Eco Plus,2218,3,2,3,2,4,3,4,4,1,3,3,4,2,4,14,6.0,neutral or dissatisfied +53458,84,Female,Loyal Customer,9,Personal Travel,Eco,173,5,3,5,5,3,5,3,3,3,4,3,1,3,3,0,0.0,satisfied +53459,129875,Female,Loyal Customer,55,Personal Travel,Eco Plus,308,3,4,3,4,2,4,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +53460,4227,Female,Loyal Customer,56,Business travel,Business,1020,5,4,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +53461,58548,Female,Loyal Customer,33,Business travel,Eco,1514,4,1,1,1,4,4,4,4,2,5,3,4,2,4,6,0.0,neutral or dissatisfied +53462,58460,Male,Loyal Customer,40,Business travel,Business,2858,3,3,3,3,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +53463,11480,Female,Loyal Customer,35,Business travel,Eco Plus,158,3,4,4,4,3,3,3,3,4,2,4,3,4,3,39,32.0,neutral or dissatisfied +53464,54475,Male,Loyal Customer,52,Business travel,Eco,925,3,3,3,3,3,3,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +53465,43361,Male,Loyal Customer,68,Personal Travel,Eco,436,2,2,2,3,4,2,4,4,1,2,3,4,3,4,20,10.0,neutral or dissatisfied +53466,78885,Male,disloyal Customer,24,Business travel,Eco,750,4,4,4,1,1,4,1,1,5,5,5,4,4,1,0,0.0,satisfied +53467,9913,Male,Loyal Customer,27,Business travel,Business,1600,2,3,3,3,2,2,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +53468,117884,Female,Loyal Customer,52,Business travel,Business,3539,1,1,1,1,4,4,4,5,5,5,5,5,5,4,17,12.0,satisfied +53469,85792,Female,disloyal Customer,22,Business travel,Eco,666,3,0,3,5,2,3,2,2,4,5,4,5,4,2,1,0.0,neutral or dissatisfied +53470,32027,Male,Loyal Customer,60,Business travel,Business,3108,3,3,3,3,4,1,4,5,5,5,4,3,5,1,0,0.0,satisfied +53471,81595,Female,Loyal Customer,53,Business travel,Business,334,1,1,1,1,5,4,5,4,4,4,4,5,4,5,22,39.0,satisfied +53472,29248,Male,Loyal Customer,53,Business travel,Business,3204,1,1,4,1,5,1,4,4,4,4,4,1,4,2,0,0.0,satisfied +53473,79311,Female,Loyal Customer,10,Personal Travel,Eco,2248,2,5,2,2,2,2,2,2,3,4,5,4,5,2,24,23.0,neutral or dissatisfied +53474,13509,Female,Loyal Customer,43,Business travel,Business,214,4,4,4,4,2,3,5,4,4,4,4,4,4,1,6,17.0,satisfied +53475,10891,Female,Loyal Customer,39,Business travel,Business,216,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +53476,37510,Female,Loyal Customer,30,Business travel,Business,944,3,3,3,3,3,4,3,3,4,4,4,2,2,3,0,0.0,satisfied +53477,16526,Female,disloyal Customer,30,Business travel,Eco,209,1,2,1,2,3,1,3,3,4,3,3,4,2,3,47,59.0,neutral or dissatisfied +53478,83675,Female,Loyal Customer,45,Business travel,Eco,577,3,3,3,3,1,2,2,3,3,3,3,3,3,4,17,20.0,neutral or dissatisfied +53479,123652,Female,disloyal Customer,59,Business travel,Business,214,4,4,4,4,5,4,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +53480,116560,Female,Loyal Customer,12,Personal Travel,Eco,417,4,4,4,4,3,4,3,3,4,5,4,3,3,3,3,0.0,neutral or dissatisfied +53481,102782,Male,Loyal Customer,46,Business travel,Business,2909,1,1,1,1,3,4,4,4,4,4,4,3,4,4,7,1.0,satisfied +53482,30310,Male,Loyal Customer,55,Personal Travel,Eco,1476,3,4,4,4,4,4,4,4,5,3,3,4,4,4,0,0.0,neutral or dissatisfied +53483,114723,Female,disloyal Customer,24,Business travel,Eco,308,3,0,3,3,3,3,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +53484,69981,Male,Loyal Customer,56,Business travel,Business,2197,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +53485,27969,Male,Loyal Customer,49,Business travel,Eco Plus,1660,2,5,2,5,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +53486,127796,Female,Loyal Customer,58,Business travel,Business,1752,5,5,5,5,3,5,5,3,3,3,3,4,3,4,23,10.0,satisfied +53487,54426,Female,Loyal Customer,20,Personal Travel,Eco,305,3,4,3,4,2,3,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +53488,36080,Male,Loyal Customer,40,Personal Travel,Eco,399,2,1,2,4,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +53489,62990,Male,Loyal Customer,39,Business travel,Business,3221,1,1,1,1,3,4,5,5,5,5,5,3,5,3,14,10.0,satisfied +53490,79161,Female,Loyal Customer,70,Personal Travel,Eco,2239,3,5,3,4,3,5,4,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +53491,29650,Female,Loyal Customer,36,Personal Travel,Eco,1533,3,4,3,3,1,3,1,1,4,3,4,3,4,1,1,0.0,neutral or dissatisfied +53492,107523,Female,Loyal Customer,26,Personal Travel,Eco,838,3,4,3,2,2,3,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +53493,23905,Female,Loyal Customer,41,Business travel,Eco,579,3,5,5,5,3,3,3,3,2,5,4,4,4,3,0,1.0,neutral or dissatisfied +53494,105039,Female,Loyal Customer,34,Personal Travel,Eco,361,3,5,3,3,4,3,4,4,3,2,4,5,5,4,94,107.0,neutral or dissatisfied +53495,76594,Male,disloyal Customer,23,Business travel,Eco,547,1,5,1,1,4,1,3,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +53496,13744,Female,disloyal Customer,30,Business travel,Eco,384,3,3,4,4,1,4,1,1,1,5,3,2,4,1,30,15.0,neutral or dissatisfied +53497,51357,Male,Loyal Customer,37,Business travel,Eco Plus,89,4,1,1,1,4,4,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +53498,115009,Female,Loyal Customer,35,Business travel,Business,3967,5,5,5,5,4,5,5,4,4,4,4,5,4,5,25,20.0,satisfied +53499,95317,Female,Loyal Customer,55,Personal Travel,Eco,148,2,3,2,4,5,3,3,4,4,2,2,4,4,4,25,29.0,neutral or dissatisfied +53500,123787,Male,Loyal Customer,52,Business travel,Business,2144,4,4,4,4,4,4,5,4,4,5,4,4,4,5,0,3.0,satisfied +53501,26597,Male,Loyal Customer,25,Business travel,Eco,515,0,4,0,1,5,0,5,5,2,4,1,5,2,5,20,16.0,satisfied +53502,37760,Female,disloyal Customer,31,Business travel,Eco Plus,1056,3,3,3,4,2,3,2,2,3,4,4,1,3,2,0,0.0,neutral or dissatisfied +53503,75434,Female,disloyal Customer,29,Business travel,Eco,2218,1,1,1,3,4,1,4,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +53504,57951,Female,Loyal Customer,46,Business travel,Business,2233,3,3,5,3,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +53505,47999,Male,Loyal Customer,48,Business travel,Eco Plus,462,2,3,3,3,2,2,2,2,4,4,3,4,4,2,21,17.0,neutral or dissatisfied +53506,27395,Male,Loyal Customer,58,Business travel,Eco,978,4,5,5,5,4,4,4,4,2,1,4,3,5,4,0,0.0,satisfied +53507,92308,Female,Loyal Customer,23,Business travel,Business,2486,5,5,5,5,5,5,5,4,2,5,5,5,4,5,167,167.0,satisfied +53508,2000,Female,Loyal Customer,56,Business travel,Business,351,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +53509,114043,Female,disloyal Customer,20,Business travel,Eco,512,3,3,3,3,3,3,5,3,3,1,4,2,3,3,34,28.0,neutral or dissatisfied +53510,66218,Male,Loyal Customer,60,Business travel,Business,550,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +53511,31843,Female,disloyal Customer,27,Business travel,Eco,2640,3,3,3,2,4,3,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +53512,2555,Female,Loyal Customer,58,Business travel,Business,1805,3,3,3,3,3,4,5,5,5,5,5,3,5,5,12,15.0,satisfied +53513,49567,Male,disloyal Customer,38,Business travel,Eco,86,1,4,1,1,4,1,3,4,3,2,3,3,1,4,0,0.0,neutral or dissatisfied +53514,14979,Male,Loyal Customer,35,Business travel,Eco,1020,5,1,1,1,5,5,5,5,2,4,4,5,3,5,0,2.0,satisfied +53515,1075,Female,Loyal Customer,12,Personal Travel,Eco,229,2,5,2,1,5,2,5,5,3,3,4,3,4,5,17,14.0,neutral or dissatisfied +53516,103229,Female,Loyal Customer,23,Personal Travel,Eco,462,4,4,2,3,5,2,5,5,3,2,1,3,3,5,0,0.0,satisfied +53517,65633,Female,Loyal Customer,45,Personal Travel,Eco,237,2,1,2,2,1,2,2,2,2,2,2,4,2,3,24,24.0,neutral or dissatisfied +53518,40497,Female,Loyal Customer,10,Personal Travel,Eco,175,2,4,2,4,5,2,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +53519,48400,Male,disloyal Customer,20,Business travel,Eco,522,3,4,3,4,4,3,4,4,2,4,1,5,2,4,0,0.0,neutral or dissatisfied +53520,40927,Female,Loyal Customer,37,Business travel,Eco Plus,584,4,5,5,5,4,4,4,4,3,2,5,3,3,4,0,0.0,satisfied +53521,69094,Female,Loyal Customer,53,Personal Travel,Eco,1389,2,3,2,2,3,3,3,3,3,2,2,3,3,1,0,5.0,neutral or dissatisfied +53522,64368,Female,Loyal Customer,18,Personal Travel,Eco,1192,1,2,0,3,5,0,5,5,1,4,3,4,2,5,0,0.0,neutral or dissatisfied +53523,13445,Male,disloyal Customer,27,Business travel,Eco,475,2,5,2,4,3,2,3,3,1,3,1,3,5,3,0,0.0,neutral or dissatisfied +53524,81192,Female,Loyal Customer,49,Business travel,Eco Plus,980,2,3,3,3,4,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +53525,4267,Female,Loyal Customer,52,Business travel,Business,2840,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +53526,2028,Male,disloyal Customer,23,Business travel,Business,733,0,5,0,3,5,0,5,5,3,5,4,4,4,5,12,2.0,satisfied +53527,1927,Female,Loyal Customer,57,Business travel,Business,2694,1,1,4,1,5,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +53528,60627,Male,disloyal Customer,24,Business travel,Eco,1620,4,4,4,2,4,4,4,4,4,2,5,3,5,4,1,0.0,neutral or dissatisfied +53529,68548,Male,Loyal Customer,38,Personal Travel,Eco,1013,4,4,4,3,2,4,3,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +53530,68142,Female,Loyal Customer,56,Personal Travel,Eco Plus,868,3,5,3,1,5,3,3,4,4,3,4,4,4,4,0,3.0,neutral or dissatisfied +53531,105751,Female,Loyal Customer,38,Business travel,Business,3649,1,1,1,1,4,3,5,1,1,2,1,3,1,4,0,6.0,satisfied +53532,113307,Male,Loyal Customer,31,Business travel,Business,386,1,4,4,4,1,2,1,1,4,5,1,1,1,1,44,46.0,neutral or dissatisfied +53533,65449,Female,Loyal Customer,43,Business travel,Business,1067,1,0,0,4,5,3,4,1,1,0,1,3,1,2,31,45.0,neutral or dissatisfied +53534,1713,Male,Loyal Customer,41,Business travel,Business,1828,4,2,2,2,2,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +53535,10472,Male,disloyal Customer,21,Business travel,Eco,316,3,0,3,1,1,3,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +53536,119019,Male,Loyal Customer,48,Business travel,Business,1460,3,3,3,3,2,4,4,5,5,5,5,5,5,5,0,6.0,satisfied +53537,89334,Male,Loyal Customer,60,Business travel,Eco,1587,4,2,2,2,4,4,4,4,3,5,4,1,4,4,0,0.0,neutral or dissatisfied +53538,97223,Female,Loyal Customer,65,Personal Travel,Eco Plus,1129,1,4,1,3,1,4,3,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +53539,39141,Female,Loyal Customer,28,Personal Travel,Eco,252,3,4,0,4,5,0,5,5,1,1,4,4,3,5,0,0.0,neutral or dissatisfied +53540,56179,Male,Loyal Customer,64,Personal Travel,Eco,1400,4,3,3,3,1,3,1,1,1,4,4,2,4,1,25,0.0,neutral or dissatisfied +53541,55430,Female,disloyal Customer,44,Business travel,Business,2521,4,4,4,1,2,4,2,2,5,5,4,5,4,2,0,0.0,satisfied +53542,12929,Male,Loyal Customer,11,Personal Travel,Eco,359,2,5,2,2,3,2,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +53543,77467,Female,disloyal Customer,30,Business travel,Eco,507,2,2,2,4,3,2,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +53544,78226,Male,Loyal Customer,31,Personal Travel,Eco,192,4,1,4,3,3,4,3,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +53545,92713,Female,disloyal Customer,39,Business travel,Business,1276,4,4,4,1,2,4,2,2,3,4,5,5,5,2,12,10.0,satisfied +53546,76533,Female,Loyal Customer,54,Business travel,Business,2950,2,2,2,2,2,5,5,5,5,5,5,4,5,5,10,0.0,satisfied +53547,45849,Male,Loyal Customer,67,Personal Travel,Eco,391,2,4,2,4,4,2,5,4,4,1,1,2,4,4,1,19.0,neutral or dissatisfied +53548,120127,Male,Loyal Customer,48,Business travel,Business,1576,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +53549,31756,Male,Loyal Customer,47,Personal Travel,Business,602,3,4,3,3,2,3,4,4,4,3,4,3,4,4,18,17.0,neutral or dissatisfied +53550,117704,Male,Loyal Customer,41,Business travel,Eco,1009,1,2,2,2,1,1,1,1,3,1,4,3,3,1,0,0.0,neutral or dissatisfied +53551,105695,Female,disloyal Customer,30,Business travel,Eco,919,3,3,3,3,1,3,1,1,3,3,4,1,3,1,8,15.0,neutral or dissatisfied +53552,64573,Female,Loyal Customer,57,Business travel,Business,247,3,5,3,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +53553,100597,Male,Loyal Customer,69,Personal Travel,Business,718,5,5,5,4,5,4,5,4,4,5,4,3,4,3,7,0.0,satisfied +53554,111364,Male,Loyal Customer,48,Business travel,Business,1111,2,2,2,2,5,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +53555,7358,Female,Loyal Customer,26,Business travel,Business,783,2,2,2,2,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +53556,84096,Female,disloyal Customer,45,Business travel,Business,757,5,5,5,2,4,5,4,4,3,5,4,3,5,4,13,5.0,satisfied +53557,95145,Male,Loyal Customer,57,Personal Travel,Eco,248,2,5,2,3,2,2,2,2,3,5,4,4,5,2,28,19.0,neutral or dissatisfied +53558,41262,Female,Loyal Customer,52,Business travel,Eco Plus,852,5,4,4,4,5,5,5,5,5,5,5,1,5,2,0,0.0,satisfied +53559,252,Female,Loyal Customer,50,Personal Travel,Eco Plus,719,1,1,2,4,3,4,3,2,2,2,2,4,2,2,20,22.0,neutral or dissatisfied +53560,57126,Female,Loyal Customer,70,Personal Travel,Eco,1222,4,4,4,1,5,2,1,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +53561,111682,Female,Loyal Customer,24,Personal Travel,Eco Plus,991,3,4,3,1,5,3,5,5,4,2,5,5,4,5,0,5.0,neutral or dissatisfied +53562,123284,Male,Loyal Customer,29,Personal Travel,Eco,600,2,5,2,4,5,2,5,5,3,2,5,4,4,5,48,41.0,neutral or dissatisfied +53563,33971,Male,Loyal Customer,40,Business travel,Business,1598,1,1,1,1,5,4,5,5,5,5,5,2,5,5,0,0.0,satisfied +53564,107441,Female,Loyal Customer,8,Personal Travel,Eco,725,2,4,2,3,2,2,2,2,4,1,3,4,3,2,3,0.0,neutral or dissatisfied +53565,98064,Female,Loyal Customer,52,Business travel,Business,1449,1,1,1,1,4,4,4,4,4,4,4,3,4,3,11,9.0,satisfied +53566,43319,Female,disloyal Customer,20,Business travel,Eco,347,3,4,3,3,2,3,2,2,4,3,3,2,1,2,0,0.0,neutral or dissatisfied +53567,1253,Male,Loyal Customer,69,Personal Travel,Eco,354,2,4,3,3,2,3,2,2,5,2,5,5,5,2,15,9.0,neutral or dissatisfied +53568,101223,Female,Loyal Customer,29,Business travel,Business,1235,4,4,4,4,4,4,4,4,5,3,5,4,4,4,97,97.0,satisfied +53569,117494,Female,Loyal Customer,22,Business travel,Business,1645,2,3,3,3,2,2,2,2,2,1,4,3,4,2,0,0.0,neutral or dissatisfied +53570,121582,Female,disloyal Customer,29,Business travel,Eco,936,1,1,1,3,1,1,1,1,2,2,3,1,3,1,8,15.0,neutral or dissatisfied +53571,106822,Female,Loyal Customer,57,Business travel,Business,1488,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +53572,113071,Male,disloyal Customer,8,Business travel,Eco,543,4,4,4,4,3,4,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +53573,21364,Female,Loyal Customer,35,Business travel,Eco Plus,761,5,4,4,4,5,5,5,5,3,4,2,1,4,5,58,50.0,satisfied +53574,117754,Male,Loyal Customer,27,Business travel,Business,1670,2,2,2,2,2,2,2,2,5,5,4,5,5,2,19,17.0,satisfied +53575,107821,Male,disloyal Customer,19,Business travel,Business,349,2,2,2,4,3,2,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +53576,100967,Male,Loyal Customer,30,Personal Travel,Eco,1142,4,5,4,4,5,4,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +53577,73643,Female,Loyal Customer,33,Business travel,Eco,192,2,1,1,1,2,2,2,2,4,2,3,4,4,2,41,38.0,neutral or dissatisfied +53578,65839,Female,Loyal Customer,27,Business travel,Business,1389,2,5,5,5,2,2,2,2,2,2,4,2,3,2,8,0.0,neutral or dissatisfied +53579,64381,Male,Loyal Customer,48,Personal Travel,Eco,1158,4,4,4,1,2,4,2,2,1,4,4,3,3,2,15,7.0,neutral or dissatisfied +53580,52178,Female,Loyal Customer,40,Business travel,Business,2070,3,3,3,3,5,5,2,5,5,4,5,5,5,4,20,14.0,satisfied +53581,105147,Male,disloyal Customer,33,Business travel,Business,220,1,1,1,3,3,1,3,3,4,4,3,2,4,3,14,23.0,neutral or dissatisfied +53582,59543,Female,Loyal Customer,50,Business travel,Business,2940,4,4,4,4,4,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +53583,52824,Male,Loyal Customer,48,Personal Travel,Eco Plus,2402,2,4,2,3,5,2,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +53584,11935,Female,disloyal Customer,26,Business travel,Business,381,2,1,1,3,1,2,2,1,3,4,3,2,4,2,197,206.0,neutral or dissatisfied +53585,86359,Male,Loyal Customer,45,Business travel,Business,762,4,4,4,4,4,4,4,5,5,5,5,4,5,3,31,27.0,satisfied +53586,121639,Male,Loyal Customer,33,Business travel,Business,2156,3,3,3,3,2,2,2,2,5,3,5,4,4,2,0,2.0,satisfied +53587,33216,Female,Loyal Customer,39,Business travel,Eco Plus,216,5,3,3,3,5,5,5,5,3,5,5,1,5,5,0,0.0,satisfied +53588,34850,Male,Loyal Customer,47,Business travel,Eco,1826,4,2,4,2,4,4,4,4,5,4,4,1,5,4,7,0.0,satisfied +53589,45380,Female,Loyal Customer,34,Business travel,Eco Plus,150,3,4,4,4,3,3,3,3,3,5,4,1,3,3,5,7.0,neutral or dissatisfied +53590,88692,Male,Loyal Customer,44,Personal Travel,Eco,444,2,4,2,5,3,2,3,3,3,5,5,3,4,3,0,2.0,neutral or dissatisfied +53591,89476,Male,Loyal Customer,12,Personal Travel,Eco Plus,151,2,1,2,1,1,2,1,1,3,4,2,3,1,1,0,0.0,neutral or dissatisfied +53592,129125,Male,Loyal Customer,67,Personal Travel,Business,954,3,5,3,3,4,4,5,3,3,3,4,3,3,3,1,0.0,neutral or dissatisfied +53593,14480,Female,disloyal Customer,37,Business travel,Eco,495,2,0,2,1,4,2,4,4,4,2,2,4,5,4,58,45.0,neutral or dissatisfied +53594,63208,Female,Loyal Customer,55,Business travel,Business,2773,3,3,3,3,5,5,4,5,5,5,5,5,5,3,37,28.0,satisfied +53595,84427,Female,Loyal Customer,42,Personal Travel,Eco,591,4,5,4,1,2,5,5,4,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +53596,63515,Female,Loyal Customer,31,Business travel,Business,3532,2,2,2,2,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +53597,108623,Female,Loyal Customer,47,Personal Travel,Eco,696,0,3,0,2,2,3,5,2,2,0,2,1,2,4,0,0.0,satisfied +53598,65493,Male,Loyal Customer,9,Personal Travel,Eco,1067,2,4,2,5,4,2,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +53599,2924,Male,Loyal Customer,45,Business travel,Business,806,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,20.0,satisfied +53600,33396,Male,disloyal Customer,23,Business travel,Eco,771,3,2,2,3,2,3,4,2,4,5,4,5,2,2,0,0.0,neutral or dissatisfied +53601,75612,Female,Loyal Customer,38,Personal Travel,Eco,337,1,1,1,3,4,1,4,4,3,2,4,2,4,4,64,73.0,neutral or dissatisfied +53602,91257,Male,Loyal Customer,54,Personal Travel,Eco,406,0,4,0,3,2,0,2,2,3,5,4,4,4,2,0,0.0,satisfied +53603,93034,Male,disloyal Customer,39,Business travel,Business,317,5,5,5,3,3,5,2,3,4,5,4,4,5,3,21,12.0,satisfied +53604,73933,Male,Loyal Customer,46,Business travel,Business,2342,5,5,5,5,4,4,4,5,4,3,5,4,4,4,0,0.0,satisfied +53605,46234,Female,Loyal Customer,53,Business travel,Eco,524,3,5,5,5,5,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +53606,18154,Female,Loyal Customer,58,Business travel,Business,2893,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +53607,56889,Male,disloyal Customer,42,Business travel,Business,2425,4,4,4,1,4,5,3,5,5,5,5,3,5,3,348,300.0,satisfied +53608,31218,Female,Loyal Customer,41,Personal Travel,Eco,628,4,4,4,2,4,4,4,4,3,5,4,3,4,4,52,49.0,neutral or dissatisfied +53609,125133,Male,Loyal Customer,17,Personal Travel,Eco,361,2,4,2,4,2,2,4,2,4,4,5,5,5,2,0,6.0,neutral or dissatisfied +53610,25800,Male,Loyal Customer,62,Personal Travel,Eco,762,3,5,3,2,5,3,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +53611,106844,Male,Loyal Customer,7,Personal Travel,Eco,1733,3,4,3,2,2,3,2,2,5,3,3,5,4,2,68,93.0,neutral or dissatisfied +53612,70104,Female,disloyal Customer,36,Business travel,Business,460,2,2,2,4,2,2,2,2,4,4,4,3,4,2,32,7.0,neutral or dissatisfied +53613,5305,Male,Loyal Customer,57,Personal Travel,Eco,383,3,3,3,3,4,3,4,4,4,2,4,3,3,4,56,66.0,neutral or dissatisfied +53614,53163,Male,Loyal Customer,22,Personal Travel,Business,612,2,4,2,3,1,2,1,1,5,5,4,3,4,1,8,4.0,neutral or dissatisfied +53615,98814,Male,Loyal Customer,48,Business travel,Business,2868,5,5,1,5,5,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +53616,12635,Female,Loyal Customer,40,Business travel,Business,844,5,5,5,5,4,5,3,3,3,4,3,1,3,3,4,0.0,satisfied +53617,62968,Female,Loyal Customer,49,Business travel,Business,948,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +53618,121739,Female,Loyal Customer,9,Personal Travel,Eco,1475,3,1,3,2,3,3,3,3,4,1,3,2,2,3,0,11.0,neutral or dissatisfied +53619,117107,Female,Loyal Customer,41,Business travel,Business,2636,2,3,4,3,3,4,3,2,2,2,2,1,2,4,33,16.0,neutral or dissatisfied +53620,991,Male,Loyal Customer,40,Business travel,Eco,89,5,2,2,2,5,5,5,5,4,1,4,1,3,5,0,0.0,satisfied +53621,127096,Male,disloyal Customer,38,Business travel,Business,221,3,3,3,3,4,3,4,4,5,1,4,1,1,4,0,0.0,neutral or dissatisfied +53622,108776,Female,Loyal Customer,34,Business travel,Business,2919,2,1,1,1,3,2,2,2,2,2,2,3,2,2,25,6.0,neutral or dissatisfied +53623,118593,Male,Loyal Customer,54,Business travel,Business,304,3,1,1,1,2,3,3,3,3,3,3,3,3,4,0,3.0,neutral or dissatisfied +53624,95396,Male,Loyal Customer,24,Personal Travel,Eco,458,2,4,3,2,3,3,3,3,3,5,5,5,5,3,2,11.0,neutral or dissatisfied +53625,8816,Male,Loyal Customer,46,Personal Travel,Eco,522,4,5,2,4,1,2,1,1,3,4,5,5,5,1,10,6.0,neutral or dissatisfied +53626,78595,Female,Loyal Customer,33,Business travel,Business,2454,3,5,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +53627,23044,Male,disloyal Customer,27,Business travel,Eco,833,2,3,3,3,3,3,3,1,2,4,4,3,1,3,209,191.0,neutral or dissatisfied +53628,1584,Male,Loyal Customer,51,Business travel,Business,3395,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,4.0,satisfied +53629,61541,Female,Loyal Customer,54,Personal Travel,Eco,2288,2,1,2,2,3,1,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +53630,81076,Male,disloyal Customer,28,Business travel,Business,931,1,2,2,2,4,2,4,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +53631,100124,Female,Loyal Customer,43,Business travel,Business,3455,4,4,4,4,2,5,4,4,4,4,4,4,4,5,20,21.0,satisfied +53632,104444,Male,Loyal Customer,48,Business travel,Eco Plus,1041,3,1,1,1,3,3,3,2,1,4,3,3,1,3,118,134.0,neutral or dissatisfied +53633,24999,Female,Loyal Customer,7,Personal Travel,Eco,692,3,4,3,2,1,3,1,1,5,2,5,3,5,1,0,23.0,neutral or dissatisfied +53634,86795,Female,Loyal Customer,45,Business travel,Business,2737,4,4,5,4,2,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +53635,53494,Female,Loyal Customer,29,Personal Travel,Eco,2253,3,4,3,5,4,3,4,4,4,3,5,5,5,4,15,17.0,neutral or dissatisfied +53636,67667,Male,Loyal Customer,51,Business travel,Eco,1235,1,5,5,5,1,1,1,1,3,4,3,3,4,1,0,7.0,neutral or dissatisfied +53637,17169,Male,Loyal Customer,24,Business travel,Eco,643,4,3,3,3,4,4,3,4,4,2,2,4,1,4,0,0.0,satisfied +53638,71145,Male,disloyal Customer,24,Business travel,Eco,646,4,0,4,5,1,4,1,1,5,5,4,5,4,1,19,25.0,satisfied +53639,125821,Female,disloyal Customer,36,Business travel,Business,861,4,4,4,1,4,4,4,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +53640,55056,Female,Loyal Customer,42,Business travel,Business,1608,2,3,2,2,2,4,4,3,3,3,3,4,3,3,1,1.0,satisfied +53641,111343,Male,Loyal Customer,54,Personal Travel,Eco Plus,283,3,2,3,3,5,3,5,5,1,3,4,4,4,5,12,4.0,neutral or dissatisfied +53642,47274,Male,Loyal Customer,43,Business travel,Eco,588,5,2,2,2,5,5,5,5,4,2,1,5,4,5,50,38.0,satisfied +53643,106797,Female,disloyal Customer,20,Business travel,Eco,977,1,1,1,4,3,1,3,3,2,4,3,2,4,3,0,0.0,neutral or dissatisfied +53644,1240,Female,Loyal Customer,51,Personal Travel,Eco,354,4,3,2,5,4,5,5,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +53645,38,Female,Loyal Customer,51,Business travel,Business,215,4,4,4,4,3,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +53646,1523,Male,Loyal Customer,50,Business travel,Business,3675,3,3,1,3,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +53647,99881,Male,disloyal Customer,43,Business travel,Business,338,3,3,3,3,3,3,3,3,5,2,4,4,4,3,0,0.0,satisfied +53648,119472,Male,disloyal Customer,37,Business travel,Business,899,3,3,3,4,5,3,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +53649,78926,Male,Loyal Customer,58,Business travel,Business,1572,3,2,2,2,3,3,4,3,3,3,3,2,3,3,33,34.0,neutral or dissatisfied +53650,7394,Male,disloyal Customer,26,Business travel,Business,522,5,5,5,4,1,5,1,1,3,2,5,5,5,1,45,46.0,satisfied +53651,41876,Female,Loyal Customer,70,Personal Travel,Eco,925,3,5,3,3,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +53652,3150,Female,Loyal Customer,53,Personal Travel,Eco,140,4,4,4,4,3,5,5,2,2,4,2,3,2,5,0,0.0,satisfied +53653,29204,Female,disloyal Customer,38,Business travel,Business,2311,2,2,2,5,3,2,2,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +53654,81785,Male,Loyal Customer,56,Business travel,Business,1306,3,3,3,3,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +53655,105922,Female,Loyal Customer,47,Personal Travel,Eco Plus,283,4,4,4,2,4,5,4,5,5,4,4,4,5,4,37,31.0,satisfied +53656,80987,Male,Loyal Customer,20,Business travel,Business,3784,3,1,4,1,3,3,3,3,3,1,4,3,4,3,65,92.0,neutral or dissatisfied +53657,66705,Female,Loyal Customer,56,Business travel,Business,802,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +53658,120142,Male,Loyal Customer,45,Business travel,Business,1475,1,1,3,1,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +53659,71856,Male,Loyal Customer,54,Business travel,Eco,244,4,5,5,5,3,4,3,3,4,1,2,4,1,3,0,0.0,satisfied +53660,78155,Male,Loyal Customer,53,Business travel,Business,192,5,5,5,5,4,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +53661,113345,Male,Loyal Customer,54,Business travel,Business,1622,3,3,3,3,2,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +53662,6883,Male,Loyal Customer,39,Business travel,Business,1961,2,2,2,2,5,4,4,5,5,5,5,3,5,3,71,73.0,satisfied +53663,78338,Male,Loyal Customer,24,Business travel,Business,1547,2,1,1,1,2,2,2,2,1,4,2,3,1,2,0,0.0,neutral or dissatisfied +53664,32638,Female,Loyal Customer,36,Business travel,Business,101,5,5,5,5,5,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +53665,101074,Female,Loyal Customer,33,Business travel,Business,1069,2,2,2,2,2,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +53666,23030,Female,disloyal Customer,27,Business travel,Eco,927,2,2,2,3,4,2,4,4,4,4,4,1,4,4,89,103.0,neutral or dissatisfied +53667,75297,Female,Loyal Customer,70,Personal Travel,Eco Plus,1846,1,4,2,1,2,4,5,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +53668,83636,Male,Loyal Customer,24,Business travel,Business,1785,3,3,3,3,5,5,5,5,5,3,5,4,4,5,0,10.0,satisfied +53669,76308,Female,disloyal Customer,18,Business travel,Business,2182,5,0,5,2,5,5,5,5,4,4,3,5,5,5,0,0.0,satisfied +53670,39513,Female,Loyal Customer,18,Business travel,Business,3157,3,3,2,2,3,3,3,3,3,4,3,1,2,3,0,0.0,neutral or dissatisfied +53671,40321,Male,Loyal Customer,42,Business travel,Eco Plus,347,5,5,5,5,5,5,5,5,1,5,2,4,3,5,0,0.0,satisfied +53672,2650,Female,Loyal Customer,52,Business travel,Business,539,4,4,1,4,3,5,4,2,2,2,2,3,2,5,6,1.0,satisfied +53673,98300,Male,Loyal Customer,52,Personal Travel,Eco,1072,4,4,5,3,2,5,2,2,4,5,5,5,4,2,1,0.0,neutral or dissatisfied +53674,4696,Female,Loyal Customer,38,Personal Travel,Eco,364,1,5,1,2,2,1,2,2,5,3,4,4,5,2,0,12.0,neutral or dissatisfied +53675,111616,Female,disloyal Customer,25,Business travel,Business,1014,5,4,5,2,2,5,5,2,4,4,4,5,5,2,52,39.0,satisfied +53676,78998,Male,disloyal Customer,26,Business travel,Business,226,5,2,5,3,1,5,1,1,4,5,5,3,4,1,0,2.0,satisfied +53677,110376,Female,disloyal Customer,35,Business travel,Eco,663,4,1,4,3,1,4,1,1,3,1,4,4,4,1,0,3.0,neutral or dissatisfied +53678,804,Male,disloyal Customer,44,Business travel,Business,282,2,2,2,4,2,2,2,2,3,3,4,1,3,2,15,21.0,neutral or dissatisfied +53679,84335,Female,Loyal Customer,65,Business travel,Business,606,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +53680,62712,Female,Loyal Customer,38,Business travel,Business,2504,1,1,1,1,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +53681,52812,Male,disloyal Customer,37,Business travel,Eco,1247,3,3,3,2,3,3,3,3,3,4,2,3,3,3,0,13.0,neutral or dissatisfied +53682,27035,Female,Loyal Customer,16,Business travel,Eco Plus,867,4,1,3,1,4,4,2,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +53683,127523,Male,Loyal Customer,24,Business travel,Business,1009,5,5,5,5,2,2,2,2,5,2,4,3,5,2,6,0.0,satisfied +53684,101771,Male,Loyal Customer,53,Business travel,Business,1521,1,1,1,1,2,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +53685,4325,Female,Loyal Customer,29,Personal Travel,Eco,589,2,4,2,3,4,2,4,4,5,4,4,3,4,4,11,0.0,neutral or dissatisfied +53686,34434,Female,Loyal Customer,52,Personal Travel,Eco,680,5,4,5,1,4,4,5,1,1,5,1,3,1,4,0,0.0,satisfied +53687,40834,Male,disloyal Customer,27,Business travel,Eco,590,0,0,0,5,5,0,5,5,1,5,2,2,5,5,0,3.0,satisfied +53688,46802,Male,Loyal Customer,34,Business travel,Business,1809,3,3,5,3,3,3,3,4,4,4,4,5,4,3,29,16.0,satisfied +53689,95193,Female,Loyal Customer,40,Personal Travel,Eco,248,3,5,0,4,4,0,5,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +53690,29477,Male,Loyal Customer,46,Business travel,Eco,1107,1,4,4,4,2,1,2,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +53691,95185,Male,Loyal Customer,61,Personal Travel,Eco,239,2,5,2,1,4,2,4,4,4,5,2,4,1,4,3,0.0,neutral or dissatisfied +53692,44479,Female,disloyal Customer,42,Business travel,Eco,692,5,5,5,5,5,5,5,5,4,1,5,2,1,5,0,0.0,satisfied +53693,14091,Male,Loyal Customer,45,Business travel,Eco,201,2,2,2,2,1,2,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +53694,89704,Female,Loyal Customer,17,Personal Travel,Eco,1076,3,3,3,4,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +53695,39594,Male,disloyal Customer,39,Business travel,Business,220,1,1,1,3,1,1,1,1,3,2,5,2,3,1,0,0.0,neutral or dissatisfied +53696,35232,Male,Loyal Customer,42,Business travel,Eco,972,5,2,2,2,5,5,5,3,4,4,3,5,3,5,244,285.0,satisfied +53697,16060,Female,disloyal Customer,15,Business travel,Eco,501,2,1,2,4,4,2,4,4,2,4,3,4,4,4,0,0.0,neutral or dissatisfied +53698,62118,Male,Loyal Customer,26,Business travel,Business,2454,5,5,5,5,4,4,4,4,5,5,4,4,5,4,2,0.0,satisfied +53699,27438,Female,disloyal Customer,23,Business travel,Eco,978,3,3,3,2,3,3,3,3,2,3,4,4,5,3,0,0.0,neutral or dissatisfied +53700,880,Male,Loyal Customer,43,Business travel,Business,2505,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +53701,60143,Male,Loyal Customer,46,Business travel,Business,720,2,1,2,2,1,5,2,5,5,5,5,1,5,3,0,0.0,satisfied +53702,67548,Male,Loyal Customer,62,Personal Travel,Business,1171,2,4,2,3,3,3,5,4,4,2,4,4,4,3,3,0.0,neutral or dissatisfied +53703,15809,Female,Loyal Customer,58,Personal Travel,Eco,282,3,4,3,4,2,4,4,4,4,3,4,4,4,1,96,109.0,neutral or dissatisfied +53704,70431,Female,Loyal Customer,60,Business travel,Business,187,4,4,4,4,4,5,5,4,4,4,5,5,4,4,0,0.0,satisfied +53705,51409,Male,Loyal Customer,68,Personal Travel,Eco Plus,109,1,2,1,3,3,1,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +53706,56472,Male,Loyal Customer,47,Personal Travel,Eco Plus,719,2,4,3,1,3,1,1,4,4,5,5,1,4,1,396,403.0,neutral or dissatisfied +53707,8463,Female,Loyal Customer,13,Personal Travel,Eco,1379,2,5,2,2,4,2,4,4,3,5,2,5,3,4,0,0.0,neutral or dissatisfied +53708,114329,Male,Loyal Customer,61,Personal Travel,Eco,909,4,5,4,3,3,4,3,3,5,2,5,3,4,3,0,0.0,satisfied +53709,10401,Male,Loyal Customer,72,Business travel,Business,3928,4,4,4,4,5,4,5,5,5,5,5,4,5,3,10,5.0,satisfied +53710,104932,Male,Loyal Customer,68,Personal Travel,Eco,210,4,2,0,3,5,0,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +53711,97273,Female,Loyal Customer,34,Personal Travel,Eco Plus,296,2,5,2,2,1,2,1,1,3,5,5,4,5,1,2,0.0,neutral or dissatisfied +53712,63472,Male,Loyal Customer,16,Business travel,Eco Plus,337,2,1,1,1,2,2,3,2,2,3,3,3,3,2,43,23.0,neutral or dissatisfied +53713,85468,Female,Loyal Customer,52,Business travel,Eco,227,3,5,5,5,1,4,3,4,4,3,4,2,4,4,18,11.0,neutral or dissatisfied +53714,16113,Female,Loyal Customer,32,Business travel,Business,3922,1,1,1,1,3,3,3,3,1,5,1,2,2,3,28,36.0,satisfied +53715,101386,Male,disloyal Customer,25,Business travel,Eco,486,1,3,1,3,1,1,1,1,3,4,3,3,2,1,59,45.0,neutral or dissatisfied +53716,110703,Female,Loyal Customer,28,Business travel,Eco Plus,1005,4,3,3,3,4,4,4,4,2,4,4,4,3,4,64,61.0,neutral or dissatisfied +53717,58120,Female,Loyal Customer,62,Personal Travel,Eco,612,3,5,3,1,4,3,3,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +53718,47459,Male,Loyal Customer,14,Personal Travel,Eco,558,2,4,2,2,5,2,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +53719,94576,Female,disloyal Customer,18,Business travel,Eco,189,4,5,4,4,5,4,5,5,5,4,5,4,5,5,3,3.0,satisfied +53720,46282,Female,Loyal Customer,19,Business travel,Eco Plus,524,4,4,4,4,4,4,4,4,4,1,3,1,2,4,4,0.0,satisfied +53721,82936,Female,Loyal Customer,50,Business travel,Eco Plus,194,3,5,5,5,2,5,2,3,3,3,3,5,3,2,0,0.0,satisfied +53722,45880,Male,Loyal Customer,33,Business travel,Business,1924,3,3,3,3,5,5,5,5,5,4,4,1,1,5,33,36.0,satisfied +53723,20923,Female,disloyal Customer,25,Business travel,Eco,689,4,4,4,1,3,4,3,3,1,5,5,4,2,3,0,0.0,satisfied +53724,2411,Female,Loyal Customer,39,Business travel,Business,1504,5,5,3,5,3,2,1,5,5,4,5,5,5,2,0,0.0,satisfied +53725,70532,Male,Loyal Customer,38,Personal Travel,Business,1258,4,4,4,4,2,3,4,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +53726,55771,Male,Loyal Customer,41,Business travel,Business,3250,2,2,2,2,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +53727,111327,Female,Loyal Customer,36,Business travel,Business,283,3,3,3,3,1,5,1,5,5,5,5,5,5,3,10,2.0,satisfied +53728,46181,Female,Loyal Customer,14,Business travel,Eco Plus,516,3,2,2,2,3,3,3,3,2,1,3,1,3,3,12,51.0,neutral or dissatisfied +53729,1729,Female,Loyal Customer,36,Business travel,Business,2390,4,1,1,1,3,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +53730,105536,Female,Loyal Customer,44,Business travel,Eco,611,3,1,1,1,3,3,3,3,3,3,3,1,3,4,0,2.0,neutral or dissatisfied +53731,89214,Male,Loyal Customer,23,Personal Travel,Eco,1892,1,3,1,4,3,1,3,3,2,2,4,1,3,3,0,0.0,neutral or dissatisfied +53732,10258,Male,Loyal Customer,58,Personal Travel,Business,316,2,5,1,3,1,4,1,4,4,1,3,5,4,1,0,1.0,neutral or dissatisfied +53733,116734,Female,Loyal Customer,18,Personal Travel,Eco Plus,308,3,5,4,2,5,4,5,5,5,3,5,5,5,5,12,9.0,neutral or dissatisfied +53734,22857,Female,Loyal Customer,18,Personal Travel,Eco,170,2,2,2,4,2,2,1,2,3,3,4,3,3,2,27,23.0,neutral or dissatisfied +53735,38037,Male,disloyal Customer,22,Business travel,Eco,1121,2,3,3,3,1,3,1,1,5,4,4,2,1,1,54,37.0,neutral or dissatisfied +53736,116542,Female,Loyal Customer,60,Personal Travel,Eco,337,1,5,1,4,4,3,5,3,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +53737,55666,Female,disloyal Customer,25,Business travel,Business,927,3,2,3,3,3,4,4,3,5,3,3,4,2,4,230,221.0,neutral or dissatisfied +53738,101734,Male,Loyal Customer,36,Personal Travel,Eco Plus,1216,4,2,5,4,3,5,2,3,4,5,4,1,3,3,20,0.0,satisfied +53739,87728,Male,Loyal Customer,28,Personal Travel,Eco Plus,606,3,5,3,3,3,3,3,3,3,3,5,5,4,3,50,31.0,neutral or dissatisfied +53740,9986,Female,Loyal Customer,42,Personal Travel,Eco,457,3,4,3,1,1,4,2,3,3,3,3,1,3,5,0,0.0,neutral or dissatisfied +53741,15460,Female,disloyal Customer,39,Business travel,Eco,164,1,3,1,4,1,1,1,1,1,4,4,4,4,1,0,19.0,neutral or dissatisfied +53742,67738,Male,Loyal Customer,11,Business travel,Eco,1431,1,2,2,2,1,1,1,1,4,3,4,1,1,1,317,318.0,neutral or dissatisfied +53743,1456,Female,disloyal Customer,38,Business travel,Business,695,1,0,0,3,1,0,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +53744,51589,Female,Loyal Customer,21,Business travel,Business,370,1,5,5,5,1,1,1,1,3,1,2,4,3,1,7,8.0,neutral or dissatisfied +53745,51298,Male,Loyal Customer,33,Business travel,Eco Plus,156,3,2,2,2,3,3,3,3,2,2,3,4,3,3,21,23.0,neutral or dissatisfied +53746,3210,Female,Loyal Customer,34,Business travel,Business,585,4,2,4,4,5,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +53747,106817,Female,Loyal Customer,55,Business travel,Business,1488,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +53748,103281,Female,Loyal Customer,32,Business travel,Business,718,3,4,3,4,3,3,3,3,3,5,2,3,3,3,0,0.0,neutral or dissatisfied +53749,56111,Female,Loyal Customer,30,Personal Travel,Eco Plus,2402,2,3,2,3,2,4,4,2,1,3,4,4,3,4,0,0.0,neutral or dissatisfied +53750,9060,Female,disloyal Customer,25,Business travel,Eco,108,2,3,1,2,2,1,2,2,2,4,2,1,2,2,76,125.0,neutral or dissatisfied +53751,123938,Female,Loyal Customer,60,Personal Travel,Eco,544,3,5,3,4,4,4,3,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +53752,22761,Female,Loyal Customer,41,Business travel,Business,3901,4,4,4,4,2,2,5,5,5,5,5,4,5,5,0,0.0,satisfied +53753,82852,Female,Loyal Customer,35,Business travel,Business,2019,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +53754,51868,Female,Loyal Customer,7,Personal Travel,Eco Plus,552,3,1,3,4,5,3,2,5,3,1,4,3,4,5,88,102.0,neutral or dissatisfied +53755,82458,Male,disloyal Customer,37,Business travel,Eco,102,1,3,1,4,4,1,4,4,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +53756,119360,Female,Loyal Customer,47,Business travel,Business,399,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +53757,52767,Female,disloyal Customer,34,Business travel,Eco,1341,3,2,2,2,1,3,1,1,3,5,4,4,4,1,4,0.0,neutral or dissatisfied +53758,103469,Male,Loyal Customer,45,Business travel,Business,382,2,2,2,2,5,4,5,5,5,5,5,5,5,3,21,15.0,satisfied +53759,14507,Male,disloyal Customer,27,Business travel,Eco,328,1,5,1,4,3,1,3,3,1,1,5,5,3,3,42,28.0,neutral or dissatisfied +53760,54735,Female,Loyal Customer,70,Personal Travel,Eco,854,2,4,2,3,1,3,3,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +53761,81779,Male,Loyal Customer,53,Business travel,Business,2845,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +53762,7175,Male,Loyal Customer,55,Business travel,Business,135,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +53763,39462,Male,Loyal Customer,60,Personal Travel,Eco,129,4,0,4,1,2,4,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +53764,53237,Female,Loyal Customer,8,Personal Travel,Eco,589,4,5,4,2,1,4,1,1,5,5,5,3,4,1,0,2.0,neutral or dissatisfied +53765,36204,Female,Loyal Customer,34,Business travel,Business,3934,4,4,4,4,3,5,4,5,5,5,5,3,5,2,0,0.0,satisfied +53766,121426,Male,disloyal Customer,36,Business travel,Business,257,3,3,3,3,4,3,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +53767,9075,Female,Loyal Customer,56,Personal Travel,Eco,212,4,1,0,2,1,2,2,3,3,0,3,4,3,2,13,6.0,satisfied +53768,72854,Male,Loyal Customer,58,Business travel,Business,3795,5,5,5,5,2,4,5,4,4,5,4,4,4,3,8,9.0,satisfied +53769,119559,Female,Loyal Customer,68,Personal Travel,Eco,759,2,5,2,4,2,5,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +53770,76414,Male,disloyal Customer,38,Business travel,Business,405,3,3,3,5,3,3,3,3,4,2,5,5,5,3,48,38.0,neutral or dissatisfied +53771,118522,Male,Loyal Customer,61,Business travel,Eco,304,2,2,1,2,1,2,1,1,2,4,4,3,3,1,0,15.0,neutral or dissatisfied +53772,96312,Female,Loyal Customer,19,Personal Travel,Eco Plus,546,3,1,3,4,5,3,5,5,1,4,3,4,4,5,0,0.0,neutral or dissatisfied +53773,60014,Female,Loyal Customer,50,Personal Travel,Eco,1085,3,4,3,2,2,5,5,1,1,3,1,5,1,3,3,0.0,neutral or dissatisfied +53774,24387,Female,Loyal Customer,68,Personal Travel,Eco,669,4,4,4,1,5,4,4,2,2,4,2,4,2,3,0,0.0,satisfied +53775,33726,Male,Loyal Customer,27,Personal Travel,Eco,899,3,1,4,2,4,4,2,4,2,1,2,1,3,4,0,0.0,neutral or dissatisfied +53776,14994,Female,Loyal Customer,51,Business travel,Business,1598,4,4,4,4,3,2,4,5,5,5,5,1,5,1,2,0.0,satisfied +53777,53508,Female,Loyal Customer,23,Personal Travel,Eco,2253,3,4,3,1,3,1,2,4,3,4,5,2,4,2,0,22.0,neutral or dissatisfied +53778,57334,Female,Loyal Customer,46,Business travel,Business,2483,2,4,2,2,3,4,4,4,4,4,4,5,4,5,6,0.0,satisfied +53779,3206,Female,Loyal Customer,18,Personal Travel,Eco,693,2,4,2,3,5,2,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +53780,75441,Male,Loyal Customer,60,Business travel,Business,2330,1,1,1,1,3,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +53781,127984,Male,disloyal Customer,21,Business travel,Eco,749,1,1,1,2,4,1,4,4,3,3,1,2,4,4,0,0.0,neutral or dissatisfied +53782,129163,Male,Loyal Customer,50,Business travel,Business,554,1,3,3,3,1,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +53783,111322,Male,disloyal Customer,36,Business travel,Business,283,4,4,4,1,2,4,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +53784,98728,Female,Loyal Customer,39,Business travel,Business,1558,4,4,2,4,3,5,4,3,3,3,3,5,3,3,7,0.0,satisfied +53785,78404,Female,Loyal Customer,33,Business travel,Business,2328,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +53786,104730,Male,Loyal Customer,41,Business travel,Business,1407,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,7.0,satisfied +53787,34570,Female,Loyal Customer,21,Business travel,Business,1598,5,5,5,5,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +53788,30029,Female,Loyal Customer,46,Business travel,Business,171,0,4,0,1,1,3,3,3,3,3,3,2,3,5,0,0.0,satisfied +53789,79529,Male,disloyal Customer,30,Business travel,Business,749,3,3,3,3,4,3,4,4,3,5,4,5,5,4,0,2.0,neutral or dissatisfied +53790,97340,Female,disloyal Customer,21,Business travel,Business,347,1,3,1,4,5,1,3,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +53791,4377,Female,disloyal Customer,25,Business travel,Eco,607,1,3,1,4,1,1,1,1,3,3,3,3,3,1,66,57.0,neutral or dissatisfied +53792,63086,Male,Loyal Customer,32,Personal Travel,Eco,948,0,1,0,3,1,0,1,1,2,2,1,1,3,1,0,0.0,satisfied +53793,56259,Male,disloyal Customer,26,Business travel,Eco,404,4,1,4,3,3,4,3,3,3,1,4,3,3,3,0,0.0,neutral or dissatisfied +53794,25135,Female,Loyal Customer,46,Personal Travel,Eco,1249,2,3,2,2,1,3,3,4,4,2,4,3,4,2,0,8.0,neutral or dissatisfied +53795,36348,Male,Loyal Customer,47,Personal Travel,Eco,395,2,5,2,3,1,2,3,1,5,2,4,3,1,1,0,0.0,neutral or dissatisfied +53796,118764,Male,Loyal Customer,50,Personal Travel,Eco,338,2,5,3,1,5,3,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +53797,85420,Male,Loyal Customer,55,Business travel,Business,3656,5,5,5,5,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +53798,76114,Male,Loyal Customer,36,Personal Travel,Business,689,3,4,3,3,5,4,5,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +53799,84394,Male,Loyal Customer,60,Business travel,Business,2079,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +53800,124490,Female,Loyal Customer,43,Business travel,Business,3513,1,4,4,4,1,4,4,1,1,1,1,1,1,4,0,37.0,neutral or dissatisfied +53801,114782,Female,disloyal Customer,39,Business travel,Business,308,3,3,3,4,4,3,4,4,4,3,4,2,3,4,2,2.0,neutral or dissatisfied +53802,13003,Male,Loyal Customer,38,Business travel,Eco,438,5,1,1,1,5,5,5,5,2,1,1,3,1,5,0,0.0,satisfied +53803,38935,Female,Loyal Customer,36,Personal Travel,Eco,162,3,4,3,1,3,3,2,3,4,2,5,5,5,3,0,2.0,neutral or dissatisfied +53804,78415,Male,Loyal Customer,37,Business travel,Business,2630,2,3,3,3,2,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +53805,86538,Female,Loyal Customer,17,Personal Travel,Eco,712,3,5,3,2,2,3,2,2,5,5,4,3,4,2,0,5.0,neutral or dissatisfied +53806,55220,Male,disloyal Customer,22,Business travel,Business,1009,0,0,0,4,4,0,4,4,4,3,5,4,4,4,95,84.0,satisfied +53807,29516,Female,Loyal Customer,70,Personal Travel,Eco Plus,1107,3,3,3,3,5,3,3,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +53808,78795,Female,Loyal Customer,38,Business travel,Business,2572,1,1,1,1,5,5,3,5,5,5,5,5,5,3,99,111.0,satisfied +53809,50440,Male,Loyal Customer,36,Business travel,Business,89,4,4,4,4,3,5,4,5,5,5,3,5,5,2,0,4.0,satisfied +53810,67177,Male,Loyal Customer,24,Personal Travel,Eco,985,3,4,3,5,2,3,2,2,5,4,4,3,5,2,5,35.0,neutral or dissatisfied +53811,57390,Male,Loyal Customer,50,Business travel,Business,3170,1,1,1,1,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +53812,46143,Male,Loyal Customer,26,Business travel,Business,3265,2,1,1,1,2,2,2,2,4,3,3,3,3,2,15,17.0,neutral or dissatisfied +53813,112390,Male,disloyal Customer,28,Business travel,Business,909,1,0,0,2,2,0,2,2,4,5,5,3,5,2,35,35.0,neutral or dissatisfied +53814,124518,Male,Loyal Customer,40,Business travel,Business,1276,1,1,5,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +53815,119380,Female,disloyal Customer,25,Business travel,Business,399,4,0,4,2,5,4,5,5,3,2,4,5,5,5,0,0.0,satisfied +53816,31594,Female,disloyal Customer,29,Business travel,Eco,602,3,2,4,3,3,4,3,3,2,5,3,1,2,3,24,25.0,neutral or dissatisfied +53817,98626,Female,Loyal Customer,33,Business travel,Business,966,1,0,0,3,5,3,4,2,2,0,2,2,2,3,33,63.0,neutral or dissatisfied +53818,109696,Male,Loyal Customer,16,Business travel,Eco Plus,802,3,2,2,2,3,3,2,3,2,3,3,1,3,3,9,3.0,neutral or dissatisfied +53819,46942,Male,Loyal Customer,15,Personal Travel,Eco,776,3,4,3,1,1,3,1,1,3,4,4,5,5,1,21,0.0,neutral or dissatisfied +53820,100065,Female,Loyal Customer,36,Personal Travel,Eco,220,2,4,2,4,3,2,2,3,3,1,3,4,3,3,13,6.0,neutral or dissatisfied +53821,55527,Female,disloyal Customer,22,Business travel,Eco,550,3,0,3,1,1,3,1,1,4,2,5,4,4,1,2,0.0,neutral or dissatisfied +53822,16973,Male,Loyal Customer,32,Business travel,Business,3170,5,5,5,5,4,5,4,4,2,5,3,1,2,4,0,0.0,satisfied +53823,107146,Male,Loyal Customer,40,Business travel,Business,2264,2,2,2,2,4,4,4,4,3,4,5,4,3,4,156,139.0,satisfied +53824,20160,Female,Loyal Customer,32,Business travel,Business,403,4,4,4,4,5,5,5,5,4,2,3,5,4,5,0,0.0,satisfied +53825,55221,Male,Loyal Customer,40,Business travel,Business,1713,2,4,2,2,3,4,4,2,2,2,2,3,2,5,30,13.0,satisfied +53826,121292,Female,Loyal Customer,52,Business travel,Business,3790,2,1,1,1,4,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +53827,53994,Male,Loyal Customer,53,Business travel,Business,1825,1,2,3,3,4,2,3,1,1,1,1,2,1,3,0,12.0,neutral or dissatisfied +53828,26769,Male,Loyal Customer,33,Business travel,Eco Plus,859,2,4,5,4,2,2,2,2,3,5,3,4,3,2,9,13.0,neutral or dissatisfied +53829,126336,Male,Loyal Customer,50,Personal Travel,Eco,507,2,4,2,4,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +53830,27622,Female,Loyal Customer,22,Business travel,Eco Plus,605,5,1,3,1,5,5,3,5,4,4,1,3,2,5,0,4.0,satisfied +53831,42317,Female,Loyal Customer,20,Personal Travel,Eco,462,2,4,2,3,1,2,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +53832,86257,Female,Loyal Customer,27,Personal Travel,Eco,356,3,2,3,2,2,3,2,2,2,2,2,1,2,2,63,73.0,neutral or dissatisfied +53833,102083,Female,Loyal Customer,55,Business travel,Business,407,4,4,4,4,5,5,5,5,5,5,5,3,5,3,54,63.0,satisfied +53834,86593,Male,Loyal Customer,57,Business travel,Business,746,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +53835,61460,Male,Loyal Customer,52,Business travel,Business,2288,2,2,2,2,2,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +53836,74021,Female,Loyal Customer,24,Business travel,Business,1471,3,1,1,1,3,3,3,3,2,3,3,1,3,3,0,17.0,neutral or dissatisfied +53837,78757,Female,disloyal Customer,26,Business travel,Business,528,5,5,5,5,3,5,3,3,4,4,4,3,5,3,0,0.0,satisfied +53838,39746,Female,Loyal Customer,43,Personal Travel,Eco Plus,410,1,2,1,3,5,3,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +53839,88071,Male,Loyal Customer,41,Business travel,Business,581,2,2,5,2,2,4,5,5,5,5,5,3,5,4,6,4.0,satisfied +53840,19755,Male,disloyal Customer,26,Business travel,Eco,462,2,5,2,1,3,2,1,3,5,3,4,4,3,3,0,0.0,neutral or dissatisfied +53841,27534,Male,Loyal Customer,50,Personal Travel,Eco,1050,1,2,1,2,4,1,4,4,4,4,3,2,2,4,0,0.0,neutral or dissatisfied +53842,35150,Male,Loyal Customer,27,Business travel,Business,1069,5,5,5,5,5,5,5,5,2,2,5,5,3,5,14,14.0,satisfied +53843,121473,Male,Loyal Customer,42,Personal Travel,Eco,331,4,3,4,5,4,4,4,4,3,2,4,1,5,4,5,35.0,neutral or dissatisfied +53844,4975,Male,Loyal Customer,28,Business travel,Business,2296,1,3,3,3,1,1,1,1,3,2,4,3,4,1,13,0.0,neutral or dissatisfied +53845,48123,Male,Loyal Customer,39,Business travel,Business,236,0,0,0,2,1,2,2,4,4,4,4,4,4,2,4,0.0,satisfied +53846,56511,Female,Loyal Customer,42,Business travel,Business,3613,4,1,1,1,2,4,3,4,4,4,4,1,4,4,0,28.0,neutral or dissatisfied +53847,41079,Male,disloyal Customer,38,Business travel,Eco,429,2,4,2,1,1,2,1,1,2,3,2,4,4,1,0,0.0,neutral or dissatisfied +53848,78585,Female,Loyal Customer,35,Personal Travel,Eco,630,4,4,4,5,5,4,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +53849,51858,Male,Loyal Customer,34,Personal Travel,Eco,438,2,4,2,1,4,2,2,4,3,3,5,3,5,4,9,0.0,neutral or dissatisfied +53850,37297,Female,Loyal Customer,45,Business travel,Eco,1076,4,3,3,3,5,1,3,4,4,4,4,1,4,2,5,0.0,satisfied +53851,17912,Male,Loyal Customer,38,Business travel,Eco,900,4,4,4,4,4,4,4,4,1,2,3,1,3,4,0,10.0,neutral or dissatisfied +53852,125204,Female,Loyal Customer,51,Business travel,Eco,251,3,2,2,2,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +53853,115063,Female,disloyal Customer,47,Business travel,Business,447,2,2,2,1,4,2,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +53854,48598,Male,Loyal Customer,26,Personal Travel,Eco,737,2,5,2,2,1,2,1,1,5,4,5,4,4,1,63,72.0,neutral or dissatisfied +53855,47238,Female,Loyal Customer,34,Personal Travel,Eco Plus,748,2,5,2,2,4,2,2,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +53856,114161,Male,Loyal Customer,42,Business travel,Business,850,5,5,5,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +53857,75014,Male,Loyal Customer,45,Business travel,Business,3141,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +53858,58531,Female,Loyal Customer,41,Personal Travel,Eco,719,3,3,3,3,2,3,2,2,3,1,4,2,3,2,0,0.0,neutral or dissatisfied +53859,49677,Male,Loyal Customer,39,Business travel,Eco,308,4,3,3,3,4,4,4,4,5,3,2,5,1,4,0,0.0,satisfied +53860,41009,Male,Loyal Customer,34,Business travel,Eco Plus,1362,3,4,4,4,3,2,3,3,1,3,4,3,3,3,0,0.0,neutral or dissatisfied +53861,66796,Male,Loyal Customer,24,Personal Travel,Eco,3784,2,4,3,4,3,3,3,5,4,5,2,3,4,3,12,0.0,neutral or dissatisfied +53862,53481,Female,disloyal Customer,37,Business travel,Eco,788,2,2,2,3,1,2,1,1,3,2,3,4,4,1,1,0.0,neutral or dissatisfied +53863,107648,Male,Loyal Customer,55,Business travel,Business,2965,1,1,1,1,2,5,5,5,5,5,5,5,5,4,19,8.0,satisfied +53864,31025,Female,Loyal Customer,51,Business travel,Eco Plus,391,2,4,2,4,2,2,2,4,5,1,1,2,2,2,155,162.0,neutral or dissatisfied +53865,8682,Male,disloyal Customer,22,Business travel,Eco,181,4,3,4,4,3,4,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +53866,78011,Female,Loyal Customer,61,Business travel,Business,332,5,5,2,5,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +53867,116337,Female,Loyal Customer,19,Personal Travel,Eco,417,2,4,2,1,3,2,3,3,1,3,2,4,3,3,0,0.0,neutral or dissatisfied +53868,51132,Male,Loyal Customer,19,Personal Travel,Eco,250,3,5,3,1,4,3,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +53869,119265,Female,Loyal Customer,44,Business travel,Business,2348,2,2,5,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +53870,20187,Male,Loyal Customer,28,Business travel,Eco Plus,403,3,4,4,4,3,3,3,3,2,5,4,1,3,3,65,57.0,neutral or dissatisfied +53871,111299,Female,Loyal Customer,60,Business travel,Business,3415,3,2,2,2,3,3,3,3,3,3,3,4,3,2,24,24.0,neutral or dissatisfied +53872,80842,Male,Loyal Customer,40,Business travel,Eco,484,2,2,3,2,2,2,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +53873,20800,Female,disloyal Customer,32,Business travel,Eco,357,1,0,1,3,5,1,5,5,1,4,1,3,2,5,0,0.0,neutral or dissatisfied +53874,55446,Female,Loyal Customer,37,Personal Travel,Eco,2521,2,4,2,3,2,5,5,4,5,3,2,5,5,5,10,43.0,neutral or dissatisfied +53875,59995,Female,Loyal Customer,49,Personal Travel,Eco,1085,2,5,2,3,5,4,5,1,1,2,2,3,1,3,1,0.0,neutral or dissatisfied +53876,58634,Female,Loyal Customer,40,Business travel,Business,2031,1,1,1,1,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +53877,75448,Female,Loyal Customer,35,Business travel,Eco,2342,3,5,5,5,3,3,3,3,3,4,3,4,4,3,39,37.0,neutral or dissatisfied +53878,61492,Female,Loyal Customer,35,Business travel,Eco,2358,4,1,4,1,4,4,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +53879,3517,Female,Loyal Customer,49,Business travel,Business,2774,4,4,4,4,5,4,5,4,4,4,4,5,4,3,63,57.0,satisfied +53880,25103,Male,Loyal Customer,70,Business travel,Eco Plus,369,4,5,5,5,4,4,4,4,2,2,5,2,1,4,13,0.0,satisfied +53881,102345,Female,Loyal Customer,39,Business travel,Eco,391,1,4,4,4,1,1,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +53882,16763,Female,Loyal Customer,24,Business travel,Business,3848,1,2,2,2,1,1,1,1,1,4,2,2,2,1,77,74.0,neutral or dissatisfied +53883,99515,Female,disloyal Customer,20,Business travel,Business,283,5,4,5,3,1,5,1,1,3,2,5,5,5,1,0,0.0,satisfied +53884,113799,Female,Loyal Customer,35,Business travel,Eco Plus,226,1,4,4,4,1,1,1,1,1,2,4,4,4,1,9,4.0,neutral or dissatisfied +53885,96358,Male,Loyal Customer,33,Business travel,Eco Plus,1609,4,3,3,3,4,3,4,4,3,2,4,3,4,4,65,54.0,neutral or dissatisfied +53886,122192,Female,Loyal Customer,55,Business travel,Business,544,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +53887,32874,Female,Loyal Customer,60,Personal Travel,Eco,216,3,0,3,3,2,4,5,5,5,3,5,3,5,3,2,8.0,neutral or dissatisfied +53888,57452,Female,Loyal Customer,52,Business travel,Business,2722,0,0,0,3,5,5,4,5,5,5,5,5,5,4,3,10.0,satisfied +53889,84140,Male,Loyal Customer,19,Personal Travel,Eco,782,1,5,1,5,4,1,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +53890,24894,Male,Loyal Customer,27,Personal Travel,Eco,397,1,5,1,4,1,1,1,1,1,3,2,4,3,1,4,0.0,neutral or dissatisfied +53891,34150,Female,Loyal Customer,32,Business travel,Eco,1237,2,3,3,3,2,2,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +53892,88700,Female,Loyal Customer,44,Personal Travel,Eco,646,2,1,3,3,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +53893,90470,Male,Loyal Customer,40,Business travel,Business,3919,2,3,2,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +53894,108567,Male,disloyal Customer,30,Business travel,Eco,547,3,2,4,3,3,4,2,3,2,5,2,1,2,3,0,6.0,neutral or dissatisfied +53895,50579,Male,Loyal Customer,68,Personal Travel,Eco,158,2,2,0,3,1,0,1,1,1,3,4,4,4,1,87,94.0,neutral or dissatisfied +53896,31151,Male,Loyal Customer,28,Business travel,Business,1865,1,4,4,4,1,2,1,1,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +53897,15694,Female,Loyal Customer,58,Business travel,Business,2848,1,1,4,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +53898,22395,Female,Loyal Customer,46,Business travel,Business,1606,0,4,0,3,4,1,3,5,5,2,2,2,5,4,0,0.0,satisfied +53899,120379,Female,Loyal Customer,42,Business travel,Business,3415,4,4,4,4,2,4,5,5,5,5,5,3,5,5,5,12.0,satisfied +53900,72054,Male,Loyal Customer,57,Business travel,Business,2486,2,2,2,2,3,4,4,4,4,4,4,4,4,4,8,0.0,satisfied +53901,118306,Female,disloyal Customer,23,Business travel,Eco,602,0,5,0,3,5,0,5,5,3,2,4,4,5,5,5,1.0,satisfied +53902,24988,Male,Loyal Customer,53,Business travel,Eco,692,4,4,4,4,4,4,4,4,4,4,2,5,5,4,0,21.0,satisfied +53903,63301,Male,Loyal Customer,47,Business travel,Business,2761,2,3,3,3,5,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +53904,107292,Female,Loyal Customer,78,Business travel,Eco,283,3,3,3,3,3,3,3,4,1,3,2,3,3,3,259,243.0,neutral or dissatisfied +53905,117698,Male,Loyal Customer,24,Personal Travel,Eco,1814,4,5,4,3,1,4,1,1,4,4,4,3,4,1,69,54.0,neutral or dissatisfied +53906,114764,Female,Loyal Customer,51,Business travel,Business,2721,3,1,3,3,4,4,5,5,5,5,5,3,5,5,23,28.0,satisfied +53907,67602,Male,Loyal Customer,28,Business travel,Business,1523,2,2,2,2,5,5,5,5,3,5,5,5,4,5,5,27.0,satisfied +53908,44138,Female,Loyal Customer,69,Business travel,Eco,74,3,5,5,5,4,3,4,3,3,3,3,1,3,2,52,48.0,neutral or dissatisfied +53909,43587,Female,Loyal Customer,34,Business travel,Eco,228,4,4,4,4,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +53910,31585,Female,Loyal Customer,49,Business travel,Business,1805,5,5,5,5,4,2,4,5,5,4,5,3,5,1,2,0.0,satisfied +53911,104634,Female,Loyal Customer,25,Personal Travel,Eco,861,1,4,1,3,3,1,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +53912,89682,Female,Loyal Customer,72,Business travel,Business,3565,4,4,4,4,3,2,3,5,5,5,5,2,5,5,9,24.0,satisfied +53913,63532,Male,Loyal Customer,13,Business travel,Eco,1009,3,5,5,5,3,3,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +53914,25605,Male,disloyal Customer,25,Business travel,Eco,526,5,0,5,5,2,5,2,2,1,5,3,4,5,2,1,3.0,satisfied +53915,54424,Male,Loyal Customer,54,Personal Travel,Eco,305,3,3,3,1,5,3,5,5,2,5,1,2,4,5,0,0.0,neutral or dissatisfied +53916,127594,Male,Loyal Customer,43,Business travel,Business,1773,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,19.0,satisfied +53917,48824,Female,Loyal Customer,66,Personal Travel,Business,373,5,2,5,4,2,4,4,4,4,5,4,4,4,1,1,9.0,satisfied +53918,27977,Male,Loyal Customer,30,Business travel,Business,2378,5,5,5,5,4,4,4,4,2,3,4,3,4,4,0,0.0,satisfied +53919,18916,Male,Loyal Customer,35,Personal Travel,Eco,448,3,4,3,3,4,3,3,4,5,4,5,5,4,4,0,3.0,neutral or dissatisfied +53920,106773,Male,Loyal Customer,14,Personal Travel,Eco,837,3,5,3,2,1,3,1,1,4,1,3,2,4,1,7,1.0,neutral or dissatisfied +53921,35444,Male,Loyal Customer,11,Personal Travel,Eco,1032,3,5,3,1,1,3,1,1,5,5,4,5,4,1,0,11.0,neutral or dissatisfied +53922,67585,Male,Loyal Customer,32,Business travel,Business,1464,4,4,4,4,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +53923,25392,Female,Loyal Customer,46,Business travel,Business,1105,2,2,2,2,3,5,5,5,5,5,5,4,5,3,0,1.0,satisfied +53924,126824,Male,disloyal Customer,35,Business travel,Business,2125,3,3,3,3,3,3,3,3,4,3,4,4,5,3,9,0.0,neutral or dissatisfied +53925,12522,Male,Loyal Customer,49,Business travel,Business,1778,5,5,5,5,1,2,4,5,5,5,5,4,5,1,0,0.0,satisfied +53926,28988,Male,Loyal Customer,60,Business travel,Eco,1050,4,4,5,4,4,4,4,4,5,3,5,3,2,4,0,4.0,satisfied +53927,18289,Female,Loyal Customer,27,Business travel,Business,1591,5,5,5,5,3,3,3,3,1,5,2,1,3,3,0,0.0,satisfied +53928,89459,Female,Loyal Customer,59,Personal Travel,Eco,151,2,5,2,2,2,5,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +53929,99277,Male,disloyal Customer,39,Business travel,Eco,833,2,2,2,3,3,2,3,3,2,4,3,2,4,3,33,35.0,neutral or dissatisfied +53930,106918,Male,Loyal Customer,45,Business travel,Business,3950,1,4,4,4,3,3,4,1,1,1,1,4,1,2,25,0.0,neutral or dissatisfied +53931,5831,Male,Loyal Customer,55,Personal Travel,Eco,273,3,2,3,3,4,3,4,4,2,4,3,4,4,4,0,10.0,neutral or dissatisfied +53932,39248,Female,Loyal Customer,48,Business travel,Eco,67,5,4,2,4,5,1,2,5,5,5,5,5,5,1,0,8.0,satisfied +53933,110146,Female,Loyal Customer,30,Business travel,Business,1763,1,1,1,1,3,4,3,3,5,4,4,4,4,3,0,0.0,satisfied +53934,94874,Male,Loyal Customer,42,Business travel,Business,239,3,2,2,2,5,4,4,3,3,3,3,2,3,3,4,7.0,neutral or dissatisfied +53935,1665,Male,Loyal Customer,21,Personal Travel,Eco,435,3,4,3,3,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +53936,5281,Female,Loyal Customer,13,Personal Travel,Eco,285,1,4,1,1,4,1,4,4,3,5,5,3,4,4,0,11.0,neutral or dissatisfied +53937,124865,Female,disloyal Customer,65,Business travel,Business,280,2,2,2,2,2,2,5,2,4,5,5,4,5,2,0,5.0,neutral or dissatisfied +53938,63320,Male,Loyal Customer,65,Business travel,Eco,337,1,4,4,4,1,1,1,1,1,4,3,4,3,1,2,5.0,neutral or dissatisfied +53939,36557,Male,Loyal Customer,26,Business travel,Business,1197,4,4,4,4,4,4,4,4,2,3,4,2,1,4,0,0.0,satisfied +53940,59459,Female,Loyal Customer,43,Business travel,Business,758,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +53941,82739,Female,disloyal Customer,24,Business travel,Eco,409,2,4,2,2,4,2,3,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +53942,83270,Male,Loyal Customer,51,Business travel,Eco,2079,3,3,3,3,3,3,3,3,3,5,2,1,4,3,0,7.0,neutral or dissatisfied +53943,121005,Male,Loyal Customer,61,Personal Travel,Eco,861,2,2,1,2,4,1,2,4,1,4,2,4,3,4,0,26.0,neutral or dissatisfied +53944,117394,Male,Loyal Customer,33,Business travel,Business,544,5,5,5,5,4,4,4,4,4,3,5,5,5,4,0,5.0,satisfied +53945,21695,Male,Loyal Customer,7,Personal Travel,Eco,746,1,4,1,1,5,1,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +53946,128581,Female,Loyal Customer,31,Business travel,Business,2552,4,4,4,4,5,5,5,5,3,5,4,3,5,5,0,19.0,satisfied +53947,116153,Female,Loyal Customer,29,Personal Travel,Eco,337,5,4,5,1,4,5,4,4,5,3,4,5,5,4,0,4.0,satisfied +53948,103106,Female,Loyal Customer,17,Personal Travel,Eco,460,4,2,4,4,2,4,2,2,3,2,4,4,3,2,9,0.0,satisfied +53949,73648,Male,disloyal Customer,39,Business travel,Business,204,2,3,3,4,3,3,3,3,5,4,5,5,5,3,35,35.0,neutral or dissatisfied +53950,109695,Male,Loyal Customer,29,Business travel,Eco Plus,829,3,5,3,5,3,3,3,3,2,5,4,3,3,3,2,9.0,neutral or dissatisfied +53951,49495,Female,Loyal Customer,33,Business travel,Eco,77,4,1,2,2,4,5,4,4,1,4,5,3,1,4,0,0.0,satisfied +53952,34252,Female,disloyal Customer,26,Business travel,Eco,1397,4,4,4,5,1,4,1,1,2,2,3,1,2,1,15,0.0,neutral or dissatisfied +53953,124859,Female,Loyal Customer,48,Business travel,Business,280,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,43.0,satisfied +53954,116567,Male,Loyal Customer,59,Business travel,Business,3298,2,2,2,2,5,4,4,4,4,4,4,3,4,4,29,24.0,satisfied +53955,32998,Female,Loyal Customer,53,Personal Travel,Eco,102,3,5,3,2,2,4,5,1,1,3,1,5,1,5,0,4.0,neutral or dissatisfied +53956,27292,Male,Loyal Customer,43,Business travel,Eco,1050,5,2,2,2,5,5,5,5,2,4,5,2,5,5,0,0.0,satisfied +53957,100102,Male,Loyal Customer,41,Business travel,Business,3992,2,5,5,5,5,3,3,2,2,2,2,2,2,4,0,27.0,neutral or dissatisfied +53958,2388,Female,Loyal Customer,56,Business travel,Business,604,3,3,3,3,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +53959,83160,Male,Loyal Customer,47,Business travel,Business,3776,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +53960,63111,Male,Loyal Customer,59,Personal Travel,Eco Plus,948,3,1,3,3,4,3,4,4,1,3,3,4,2,4,0,0.0,neutral or dissatisfied +53961,56456,Male,Loyal Customer,38,Personal Travel,Eco,719,2,5,2,2,3,2,3,3,5,4,4,5,5,3,37,25.0,neutral or dissatisfied +53962,129811,Female,Loyal Customer,40,Personal Travel,Eco,337,3,4,5,5,4,5,4,4,5,5,5,5,5,4,48,41.0,neutral or dissatisfied +53963,76012,Female,disloyal Customer,24,Business travel,Business,237,4,5,4,4,4,1,1,5,2,5,5,1,5,1,202,188.0,satisfied +53964,101585,Male,disloyal Customer,75,Business travel,Eco,699,3,3,3,3,5,3,5,5,1,1,4,4,3,5,19,11.0,neutral or dissatisfied +53965,101657,Female,Loyal Customer,45,Personal Travel,Business,2106,2,2,2,3,1,4,4,2,2,2,2,4,2,4,0,27.0,neutral or dissatisfied +53966,22112,Male,Loyal Customer,36,Business travel,Eco,694,4,4,4,4,4,4,4,4,4,2,4,4,5,4,0,0.0,satisfied +53967,10894,Female,Loyal Customer,69,Business travel,Business,140,1,1,4,4,5,3,3,3,3,3,1,4,3,1,59,120.0,neutral or dissatisfied +53968,37734,Male,Loyal Customer,33,Personal Travel,Eco,944,1,4,1,4,3,1,3,3,1,5,3,2,4,3,43,51.0,neutral or dissatisfied +53969,30710,Male,Loyal Customer,56,Business travel,Business,2788,4,3,5,5,2,2,2,4,4,4,4,2,4,3,31,19.0,neutral or dissatisfied +53970,40713,Male,Loyal Customer,44,Business travel,Eco,626,4,2,2,2,4,4,4,4,4,1,1,4,1,4,0,5.0,satisfied +53971,110094,Female,disloyal Customer,22,Business travel,Business,882,5,2,5,3,2,5,2,2,5,2,5,5,5,2,3,0.0,satisfied +53972,109086,Female,Loyal Customer,56,Personal Travel,Eco,1105,4,5,3,3,5,4,4,1,1,3,1,4,1,5,2,0.0,neutral or dissatisfied +53973,98553,Female,Loyal Customer,42,Business travel,Business,3068,4,4,4,4,5,4,5,5,5,5,5,3,5,3,3,9.0,satisfied +53974,104864,Male,disloyal Customer,35,Business travel,Eco,327,2,2,2,4,5,2,5,5,1,4,3,2,4,5,11,19.0,neutral or dissatisfied +53975,40904,Male,Loyal Customer,49,Personal Travel,Eco,558,3,4,2,3,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +53976,47480,Female,Loyal Customer,24,Personal Travel,Eco,532,2,2,2,3,4,2,4,4,2,1,3,4,2,4,69,59.0,neutral or dissatisfied +53977,85308,Male,Loyal Customer,29,Personal Travel,Eco,689,3,4,3,3,5,3,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +53978,128430,Female,Loyal Customer,69,Business travel,Business,338,2,3,3,3,4,3,4,2,2,3,2,3,2,3,0,14.0,neutral or dissatisfied +53979,38141,Female,Loyal Customer,21,Personal Travel,Eco,1249,3,4,3,5,4,3,4,4,4,5,4,4,5,4,5,10.0,neutral or dissatisfied +53980,430,Female,Loyal Customer,24,Personal Travel,Business,140,3,5,3,3,2,3,2,2,1,1,1,1,4,2,74,76.0,neutral or dissatisfied +53981,72549,Male,Loyal Customer,44,Business travel,Eco,1119,2,2,2,2,2,2,2,2,1,5,3,4,3,2,18,27.0,neutral or dissatisfied +53982,58203,Female,disloyal Customer,26,Business travel,Business,925,1,4,0,3,2,0,2,2,3,2,5,4,4,2,18,0.0,neutral or dissatisfied +53983,102442,Female,Loyal Customer,11,Personal Travel,Eco,236,4,3,4,3,1,4,4,1,3,5,1,3,3,1,0,1.0,neutral or dissatisfied +53984,81922,Male,disloyal Customer,13,Business travel,Business,1532,3,0,4,4,2,4,2,2,2,2,4,4,4,2,0,7.0,neutral or dissatisfied +53985,126771,Female,disloyal Customer,21,Business travel,Eco,1336,1,2,2,3,5,1,5,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +53986,26139,Male,Loyal Customer,36,Business travel,Eco,270,5,5,5,5,5,5,5,5,4,2,4,2,3,5,14,7.0,satisfied +53987,3386,Male,disloyal Customer,24,Business travel,Business,315,4,0,4,3,2,4,2,2,4,5,5,5,4,2,9,12.0,satisfied +53988,76827,Male,disloyal Customer,14,Business travel,Eco,1186,3,3,3,2,2,3,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +53989,43463,Male,disloyal Customer,25,Business travel,Eco,752,5,5,5,3,1,5,5,1,2,3,2,4,4,1,7,0.0,satisfied +53990,74073,Male,Loyal Customer,65,Personal Travel,Business,641,3,5,3,4,5,5,5,3,3,3,5,5,3,4,0,0.0,neutral or dissatisfied +53991,62693,Male,Loyal Customer,27,Personal Travel,Business,2504,2,3,2,3,2,2,2,1,2,4,4,2,3,2,0,11.0,neutral or dissatisfied +53992,113253,Female,Loyal Customer,47,Business travel,Business,3360,4,4,4,4,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +53993,107762,Female,Loyal Customer,22,Personal Travel,Eco,405,1,4,1,2,3,1,3,3,2,4,4,2,5,3,0,0.0,neutral or dissatisfied +53994,103640,Male,Loyal Customer,37,Business travel,Business,405,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +53995,85334,Female,Loyal Customer,29,Business travel,Business,689,3,3,3,3,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +53996,77785,Male,Loyal Customer,27,Personal Travel,Eco,696,4,4,4,4,3,4,3,3,3,5,5,5,4,3,73,79.0,neutral or dissatisfied +53997,21582,Male,Loyal Customer,47,Personal Travel,Eco Plus,399,3,5,3,4,5,3,5,5,5,4,3,5,4,5,0,0.0,neutral or dissatisfied +53998,101090,Male,Loyal Customer,50,Business travel,Business,758,2,2,2,2,3,5,4,4,4,4,4,4,4,5,18,0.0,satisfied +53999,46563,Male,disloyal Customer,22,Business travel,Eco,196,2,4,2,5,4,2,3,4,1,4,3,5,5,4,4,0.0,neutral or dissatisfied +54000,54477,Male,Loyal Customer,40,Business travel,Business,3253,5,5,5,5,4,2,5,3,3,4,3,4,3,1,2,0.0,satisfied +54001,60518,Female,Loyal Customer,68,Personal Travel,Eco,862,2,4,2,3,4,5,4,2,2,2,2,4,2,4,14,0.0,neutral or dissatisfied +54002,69465,Female,Loyal Customer,53,Personal Travel,Eco,1096,3,1,3,3,2,3,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +54003,86405,Male,Loyal Customer,49,Business travel,Business,2811,3,4,3,3,4,5,4,5,5,5,5,5,5,4,5,0.0,satisfied +54004,56919,Male,Loyal Customer,45,Business travel,Business,2565,5,5,4,5,3,3,3,3,4,4,4,3,3,3,6,0.0,satisfied +54005,33987,Male,Loyal Customer,55,Business travel,Eco,1598,4,1,1,1,3,4,3,3,1,5,5,2,3,3,0,10.0,satisfied +54006,66707,Male,Loyal Customer,52,Business travel,Business,802,2,4,4,4,4,3,2,2,2,2,2,1,2,3,61,52.0,neutral or dissatisfied +54007,126915,Male,Loyal Customer,49,Business travel,Business,1865,5,5,5,5,4,4,5,3,3,3,3,5,3,3,117,97.0,satisfied +54008,24576,Male,Loyal Customer,30,Business travel,Eco Plus,874,4,5,5,5,4,4,4,4,3,1,5,1,3,4,0,0.0,satisfied +54009,122384,Female,Loyal Customer,25,Personal Travel,Eco,529,2,4,2,4,5,2,5,5,5,4,5,4,4,5,4,2.0,neutral or dissatisfied +54010,113063,Male,disloyal Customer,12,Business travel,Eco,479,2,4,2,4,3,2,3,3,4,3,3,3,3,3,3,0.0,neutral or dissatisfied +54011,60311,Male,Loyal Customer,50,Personal Travel,Eco,406,4,5,4,4,1,4,1,1,5,1,1,3,3,1,3,0.0,satisfied +54012,52836,Female,disloyal Customer,9,Business travel,Eco,1413,2,2,2,3,4,2,5,4,3,4,2,3,4,4,47,27.0,neutral or dissatisfied +54013,112990,Male,Loyal Customer,27,Business travel,Business,1797,2,2,2,2,4,4,4,4,3,2,4,3,5,4,17,0.0,satisfied +54014,96976,Male,Loyal Customer,49,Business travel,Eco,883,4,2,2,2,4,4,4,4,4,1,2,4,3,4,0,5.0,neutral or dissatisfied +54015,99734,Male,Loyal Customer,56,Business travel,Business,2089,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +54016,4339,Male,Loyal Customer,50,Business travel,Business,3141,1,1,1,1,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +54017,48979,Female,Loyal Customer,37,Business travel,Business,1702,0,4,0,4,5,5,5,2,2,2,2,3,2,4,47,54.0,satisfied +54018,128096,Female,Loyal Customer,41,Personal Travel,Eco,2917,2,3,2,2,2,2,2,2,4,4,3,4,2,2,2,,neutral or dissatisfied +54019,110996,Male,disloyal Customer,27,Business travel,Business,197,2,2,2,3,4,2,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +54020,90845,Female,Loyal Customer,72,Business travel,Business,2397,2,5,5,5,1,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +54021,40611,Female,Loyal Customer,65,Personal Travel,Eco,391,2,5,2,4,4,4,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +54022,129763,Male,disloyal Customer,16,Business travel,Eco,337,5,0,5,4,3,5,3,3,1,2,2,4,2,3,0,0.0,satisfied +54023,20003,Female,Loyal Customer,56,Business travel,Eco,599,3,5,5,5,3,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +54024,32081,Male,Loyal Customer,53,Business travel,Business,3200,3,3,3,3,2,5,4,5,5,5,4,3,5,4,0,0.0,satisfied +54025,58529,Female,Loyal Customer,34,Personal Travel,Eco,719,1,5,1,1,3,1,1,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +54026,79681,Male,Loyal Customer,45,Personal Travel,Eco,762,2,4,3,2,2,3,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +54027,10679,Male,Loyal Customer,33,Business travel,Business,2015,5,5,5,5,5,5,5,5,3,4,5,4,5,5,49,45.0,satisfied +54028,23711,Male,Loyal Customer,55,Personal Travel,Eco,251,3,3,3,4,1,3,1,1,4,3,3,4,4,1,0,7.0,neutral or dissatisfied +54029,115964,Male,Loyal Customer,36,Personal Travel,Eco,296,3,4,3,3,2,3,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +54030,113113,Male,Loyal Customer,45,Personal Travel,Eco,543,2,5,3,3,1,3,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +54031,20329,Male,Loyal Customer,44,Business travel,Eco,287,4,5,5,5,4,4,4,4,5,5,3,5,5,4,0,0.0,satisfied +54032,90225,Female,disloyal Customer,26,Business travel,Business,1127,2,2,2,3,1,2,1,1,4,5,5,5,5,1,4,0.0,neutral or dissatisfied +54033,31891,Male,Loyal Customer,22,Personal Travel,Eco,2762,3,0,3,3,5,3,5,5,5,3,4,1,2,5,27,0.0,neutral or dissatisfied +54034,75442,Female,disloyal Customer,24,Business travel,Eco,2342,1,1,1,3,4,1,5,4,3,4,4,4,3,4,2,0.0,neutral or dissatisfied +54035,44392,Male,Loyal Customer,47,Business travel,Business,2950,4,4,2,4,3,2,4,5,5,5,5,3,5,4,19,18.0,satisfied +54036,50967,Male,Loyal Customer,21,Personal Travel,Eco,262,3,3,0,2,3,0,3,3,3,1,3,2,1,3,0,0.0,neutral or dissatisfied +54037,100501,Female,Loyal Customer,54,Business travel,Business,1834,1,1,1,1,2,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +54038,46784,Female,Loyal Customer,59,Business travel,Business,833,4,4,4,4,2,4,5,3,3,4,3,3,3,3,0,3.0,satisfied +54039,48050,Male,Loyal Customer,14,Personal Travel,Eco,710,3,4,3,2,1,3,1,1,2,1,5,1,2,1,0,0.0,neutral or dissatisfied +54040,64206,Female,Loyal Customer,51,Personal Travel,Eco,853,2,3,2,3,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +54041,49725,Male,Loyal Customer,46,Business travel,Business,3809,2,2,2,2,4,3,5,5,5,5,4,2,5,3,0,4.0,satisfied +54042,110413,Female,Loyal Customer,31,Business travel,Business,3857,2,2,2,2,4,4,4,4,3,2,4,3,5,4,0,0.0,satisfied +54043,93383,Male,Loyal Customer,29,Business travel,Business,1549,5,5,2,5,5,5,5,5,5,4,4,5,5,5,13,8.0,satisfied +54044,46381,Female,Loyal Customer,23,Business travel,Business,1013,1,3,3,3,1,1,1,1,2,2,4,3,3,1,14,42.0,neutral or dissatisfied +54045,114095,Male,Loyal Customer,21,Personal Travel,Eco,1947,4,5,4,2,5,4,5,5,5,2,3,4,4,5,5,0.0,neutral or dissatisfied +54046,60088,Male,Loyal Customer,30,Business travel,Business,1005,3,3,3,3,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +54047,111231,Male,Loyal Customer,20,Personal Travel,Eco,1546,4,4,4,1,4,4,4,4,5,3,5,3,5,4,1,0.0,neutral or dissatisfied +54048,91717,Female,Loyal Customer,45,Business travel,Business,2845,4,4,3,4,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +54049,28357,Female,Loyal Customer,25,Business travel,Eco Plus,867,5,1,1,1,5,5,5,5,2,5,1,1,4,5,4,0.0,satisfied +54050,26783,Female,Loyal Customer,63,Personal Travel,Eco,1199,4,1,4,3,4,2,2,2,2,4,2,1,2,1,9,0.0,satisfied +54051,104492,Female,Loyal Customer,33,Personal Travel,Eco,860,1,5,1,1,1,1,1,1,4,2,5,3,5,1,75,46.0,neutral or dissatisfied +54052,81843,Female,Loyal Customer,38,Personal Travel,Eco,1310,2,4,2,4,5,2,1,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +54053,96580,Female,Loyal Customer,27,Personal Travel,Eco,333,3,2,5,3,5,5,5,5,1,4,2,4,3,5,46,33.0,neutral or dissatisfied +54054,98015,Male,Loyal Customer,63,Business travel,Business,1014,1,1,1,1,3,4,4,5,5,5,5,5,5,3,21,23.0,satisfied +54055,66463,Male,Loyal Customer,61,Personal Travel,Eco,1217,1,0,1,3,2,1,2,2,4,4,4,3,4,2,9,1.0,neutral or dissatisfied +54056,60167,Male,Loyal Customer,58,Personal Travel,Eco,1120,3,4,3,4,5,3,5,5,2,5,3,2,4,5,1,0.0,neutral or dissatisfied +54057,18365,Female,Loyal Customer,46,Business travel,Business,2290,2,3,3,3,3,3,3,3,3,3,2,1,3,4,32,32.0,neutral or dissatisfied +54058,60425,Female,Loyal Customer,49,Business travel,Business,2056,5,5,5,5,2,4,4,4,4,4,4,3,4,3,76,66.0,satisfied +54059,92542,Male,Loyal Customer,69,Personal Travel,Eco,2139,2,4,2,2,5,2,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +54060,49423,Female,Loyal Customer,39,Business travel,Eco,421,4,4,3,4,4,4,4,4,4,3,3,3,1,4,0,0.0,satisfied +54061,33505,Male,Loyal Customer,70,Personal Travel,Eco,965,4,5,4,3,4,4,4,4,4,5,5,5,4,4,0,10.0,neutral or dissatisfied +54062,14741,Male,Loyal Customer,48,Business travel,Eco,463,4,1,1,1,4,4,4,4,3,4,2,5,5,4,0,0.0,satisfied +54063,39138,Male,Loyal Customer,37,Personal Travel,Eco,190,2,4,2,1,1,2,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +54064,1643,Male,disloyal Customer,50,Business travel,Business,551,4,4,4,3,3,4,3,3,4,1,3,3,2,3,27,53.0,neutral or dissatisfied +54065,85922,Female,Loyal Customer,43,Personal Travel,Eco,761,4,4,4,5,5,4,4,5,5,4,5,3,5,4,78,81.0,neutral or dissatisfied +54066,112738,Female,disloyal Customer,44,Business travel,Business,671,2,2,2,3,4,2,4,4,3,5,4,3,4,4,0,0.0,satisfied +54067,74315,Female,Loyal Customer,40,Business travel,Business,1235,4,5,4,4,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +54068,114405,Female,Loyal Customer,49,Business travel,Business,342,1,5,1,1,3,4,5,4,4,4,4,3,4,4,9,6.0,satisfied +54069,6672,Male,disloyal Customer,22,Business travel,Eco,438,5,4,5,4,3,4,3,3,4,5,4,3,4,3,41,50.0,satisfied +54070,122757,Male,Loyal Customer,55,Personal Travel,Eco,651,2,5,2,2,1,2,1,1,2,3,2,3,4,1,0,0.0,neutral or dissatisfied +54071,43490,Male,Loyal Customer,49,Business travel,Business,3000,0,0,0,3,2,4,1,2,2,2,2,4,2,2,0,0.0,satisfied +54072,21026,Female,Loyal Customer,44,Business travel,Eco,106,4,2,2,2,1,1,5,4,4,4,4,4,4,4,43,42.0,satisfied +54073,35082,Female,Loyal Customer,55,Business travel,Business,1832,1,1,1,1,2,1,2,5,5,5,5,5,5,1,0,0.0,satisfied +54074,2781,Female,Loyal Customer,30,Business travel,Business,1911,1,3,3,3,1,1,1,1,1,2,4,4,3,1,43,44.0,neutral or dissatisfied +54075,72363,Male,Loyal Customer,47,Business travel,Business,985,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,12.0,satisfied +54076,103357,Male,Loyal Customer,59,Business travel,Business,342,3,3,3,3,3,4,4,5,5,5,5,5,5,3,3,2.0,satisfied +54077,27512,Male,disloyal Customer,35,Business travel,Eco,679,1,0,0,3,3,0,3,3,1,1,3,2,4,3,91,85.0,neutral or dissatisfied +54078,113154,Male,Loyal Customer,29,Business travel,Business,628,2,2,2,2,2,2,2,2,1,3,3,2,4,2,38,29.0,neutral or dissatisfied +54079,62352,Male,Loyal Customer,40,Personal Travel,Eco,1735,3,5,3,4,1,3,1,1,4,5,5,4,5,1,7,5.0,neutral or dissatisfied +54080,42593,Female,disloyal Customer,41,Business travel,Business,801,2,2,2,3,2,2,2,2,4,4,4,4,4,2,9,47.0,neutral or dissatisfied +54081,76243,Female,Loyal Customer,31,Personal Travel,Eco,1399,2,5,2,3,4,2,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +54082,51843,Male,Loyal Customer,63,Personal Travel,Eco Plus,493,1,3,2,4,3,2,3,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +54083,89851,Male,Loyal Customer,25,Business travel,Business,1416,2,2,2,2,3,4,3,3,4,3,5,5,4,3,0,0.0,satisfied +54084,9357,Male,Loyal Customer,44,Business travel,Business,3753,1,1,1,1,2,4,5,5,5,5,5,5,5,3,105,93.0,satisfied +54085,123271,Female,Loyal Customer,7,Personal Travel,Eco,468,1,5,1,3,5,1,2,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +54086,115579,Male,Loyal Customer,60,Business travel,Business,3176,2,5,5,5,4,2,2,2,2,2,2,4,2,3,5,0.0,neutral or dissatisfied +54087,45654,Female,Loyal Customer,7,Personal Travel,Eco,391,4,3,2,4,4,2,4,4,3,1,3,4,3,4,14,5.0,neutral or dissatisfied +54088,27922,Female,Loyal Customer,37,Personal Travel,Eco,689,1,5,1,5,4,1,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +54089,1335,Female,Loyal Customer,58,Business travel,Business,354,2,2,2,2,2,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +54090,71862,Female,disloyal Customer,30,Business travel,Eco,1652,1,1,1,3,1,1,1,1,3,1,3,1,3,1,2,8.0,neutral or dissatisfied +54091,39505,Female,disloyal Customer,37,Business travel,Eco,1024,1,1,1,3,1,1,1,1,4,4,3,1,4,1,21,21.0,neutral or dissatisfied +54092,101626,Male,Loyal Customer,19,Personal Travel,Eco,1371,1,2,1,4,2,1,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +54093,79799,Male,Loyal Customer,47,Business travel,Business,1010,3,3,3,3,2,5,5,4,4,4,4,4,4,4,23,0.0,satisfied +54094,15948,Male,Loyal Customer,29,Personal Travel,Eco,607,2,4,2,4,3,2,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +54095,86278,Female,Loyal Customer,8,Personal Travel,Eco,226,3,4,3,4,3,2,2,1,2,3,3,2,1,2,210,207.0,neutral or dissatisfied +54096,62681,Female,Loyal Customer,60,Personal Travel,Eco Plus,1726,3,4,3,2,3,5,5,5,4,3,5,5,5,5,178,145.0,neutral or dissatisfied +54097,112266,Male,Loyal Customer,45,Business travel,Eco,1703,4,5,4,4,4,4,4,4,3,2,2,1,4,4,39,28.0,neutral or dissatisfied +54098,72495,Female,disloyal Customer,22,Business travel,Eco,1102,3,4,4,3,5,4,5,5,1,4,2,1,3,5,1,6.0,neutral or dissatisfied +54099,41606,Male,Loyal Customer,39,Personal Travel,Eco,1334,4,4,4,4,4,4,4,4,4,4,5,4,5,4,6,3.0,neutral or dissatisfied +54100,111532,Female,Loyal Customer,37,Business travel,Business,2270,1,1,1,1,3,5,4,5,5,5,5,4,5,4,9,0.0,satisfied +54101,123107,Female,Loyal Customer,36,Business travel,Business,2903,1,4,4,4,2,3,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +54102,23439,Female,Loyal Customer,40,Business travel,Eco,576,5,3,3,3,5,5,5,5,5,4,2,3,2,5,0,0.0,satisfied +54103,102420,Male,Loyal Customer,44,Personal Travel,Eco,197,2,4,2,2,1,2,1,1,3,3,5,3,5,1,81,88.0,neutral or dissatisfied +54104,63971,Male,Loyal Customer,32,Business travel,Eco Plus,1192,4,4,4,4,4,4,4,4,4,5,4,2,3,4,0,11.0,neutral or dissatisfied +54105,112826,Male,disloyal Customer,45,Business travel,Business,1129,4,4,4,1,4,4,3,4,5,4,5,4,5,4,2,0.0,satisfied +54106,43668,Female,Loyal Customer,48,Business travel,Business,2795,3,3,3,3,5,3,4,3,3,3,3,1,3,4,0,3.0,neutral or dissatisfied +54107,15718,Male,Loyal Customer,36,Business travel,Business,3744,4,5,5,5,4,4,4,2,4,3,2,4,1,4,170,149.0,neutral or dissatisfied +54108,96742,Female,Loyal Customer,25,Business travel,Eco Plus,696,2,2,4,4,2,2,4,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +54109,105098,Female,Loyal Customer,47,Business travel,Business,289,1,1,1,1,3,4,5,5,5,4,5,5,5,5,69,70.0,satisfied +54110,62306,Male,disloyal Customer,17,Business travel,Eco,414,2,3,2,4,5,2,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +54111,23839,Male,Loyal Customer,14,Business travel,Business,3315,4,4,4,4,5,5,5,5,2,4,1,1,2,5,0,0.0,satisfied +54112,50406,Female,Loyal Customer,57,Business travel,Eco,372,1,5,5,5,5,4,4,1,1,1,1,4,1,4,0,6.0,neutral or dissatisfied +54113,122613,Male,Loyal Customer,38,Business travel,Business,328,3,3,3,3,5,4,4,3,3,3,3,1,3,2,95,81.0,neutral or dissatisfied +54114,34045,Female,Loyal Customer,57,Personal Travel,Eco Plus,1608,4,5,4,3,5,5,5,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +54115,6379,Male,disloyal Customer,22,Business travel,Business,315,5,0,5,3,4,5,4,4,4,5,4,3,4,4,0,2.0,satisfied +54116,77066,Female,disloyal Customer,21,Business travel,Eco,991,2,2,2,4,1,2,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +54117,50281,Female,Loyal Customer,20,Business travel,Business,373,3,5,5,5,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +54118,1630,Female,Loyal Customer,40,Business travel,Business,599,3,2,2,2,3,4,4,3,3,3,3,1,3,3,80,69.0,neutral or dissatisfied +54119,108638,Female,Loyal Customer,66,Personal Travel,Eco Plus,1547,1,5,1,2,5,3,5,5,5,1,2,3,5,3,3,0.0,neutral or dissatisfied +54120,14455,Female,disloyal Customer,40,Business travel,Business,674,3,4,4,3,2,4,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +54121,52592,Female,disloyal Customer,37,Business travel,Eco,119,3,0,3,3,1,3,1,1,2,5,4,2,1,1,0,0.0,neutral or dissatisfied +54122,5166,Male,Loyal Customer,57,Business travel,Business,3809,0,0,0,4,3,4,5,1,1,1,1,4,1,3,0,0.0,satisfied +54123,20315,Male,disloyal Customer,27,Business travel,Business,837,1,1,1,1,1,1,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +54124,56229,Female,Loyal Customer,17,Personal Travel,Eco,1585,2,3,2,4,3,2,3,3,4,4,2,1,3,3,9,0.0,neutral or dissatisfied +54125,82134,Female,disloyal Customer,35,Business travel,Business,311,4,4,4,3,3,4,2,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +54126,84537,Male,Loyal Customer,39,Business travel,Business,2504,4,3,1,3,3,3,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +54127,127824,Male,Loyal Customer,70,Personal Travel,Eco,1044,4,5,4,2,2,4,2,2,3,1,3,4,4,2,0,0.0,satisfied +54128,58500,Male,Loyal Customer,41,Business travel,Business,719,1,1,1,1,4,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +54129,91849,Female,Loyal Customer,30,Business travel,Business,1797,4,5,5,5,4,3,4,4,4,2,4,1,3,4,15,0.0,neutral or dissatisfied +54130,127341,Male,Loyal Customer,71,Business travel,Business,507,4,5,5,5,1,3,2,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +54131,100540,Female,Loyal Customer,46,Personal Travel,Eco,759,2,4,2,3,3,5,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +54132,15439,Male,disloyal Customer,25,Business travel,Eco,377,4,2,3,4,5,3,5,5,1,1,3,3,3,5,0,10.0,neutral or dissatisfied +54133,21682,Male,Loyal Customer,17,Business travel,Eco,746,1,1,5,1,1,1,2,1,4,4,4,4,4,1,65,61.0,neutral or dissatisfied +54134,120083,Male,Loyal Customer,31,Personal Travel,Eco,683,3,4,3,3,2,3,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +54135,44819,Female,Loyal Customer,13,Personal Travel,Eco,491,3,4,1,3,4,1,4,4,1,3,4,2,4,4,27,65.0,neutral or dissatisfied +54136,118154,Female,Loyal Customer,54,Business travel,Business,1444,3,3,3,3,5,4,5,5,5,5,5,5,5,4,17,3.0,satisfied +54137,8882,Female,disloyal Customer,29,Business travel,Eco,622,4,0,4,2,2,4,2,2,5,4,3,5,5,2,0,6.0,neutral or dissatisfied +54138,21419,Female,Loyal Customer,42,Business travel,Business,3669,2,2,5,2,1,1,4,4,4,4,4,1,4,1,0,0.0,satisfied +54139,70630,Male,Loyal Customer,27,Personal Travel,Eco,1217,3,4,3,1,4,3,3,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +54140,110510,Male,Loyal Customer,13,Personal Travel,Eco Plus,925,3,4,4,1,2,4,1,2,3,5,1,5,2,2,8,0.0,neutral or dissatisfied +54141,76943,Male,Loyal Customer,22,Business travel,Business,1990,5,5,5,5,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +54142,58075,Male,disloyal Customer,18,Business travel,Eco,589,4,4,4,4,4,4,4,4,2,1,4,1,3,4,26,16.0,neutral or dissatisfied +54143,40501,Male,Loyal Customer,58,Personal Travel,Eco,222,2,3,2,4,5,2,4,5,1,2,3,2,4,5,16,10.0,neutral or dissatisfied +54144,14139,Female,Loyal Customer,13,Personal Travel,Eco,413,3,4,2,2,5,2,5,5,5,2,4,4,5,5,101,93.0,neutral or dissatisfied +54145,35523,Male,Loyal Customer,57,Personal Travel,Eco,1069,4,5,4,4,3,4,3,3,3,2,4,4,4,3,0,0.0,satisfied +54146,22642,Female,Loyal Customer,18,Personal Travel,Eco,300,2,4,4,3,2,4,2,2,1,3,4,2,3,2,41,27.0,neutral or dissatisfied +54147,22515,Female,disloyal Customer,24,Business travel,Eco,145,2,3,2,3,5,2,5,5,4,2,4,3,4,5,57,52.0,neutral or dissatisfied +54148,103842,Male,Loyal Customer,41,Business travel,Business,882,1,1,1,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +54149,4436,Male,Loyal Customer,42,Business travel,Business,362,2,5,5,5,5,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +54150,26095,Male,Loyal Customer,36,Personal Travel,Eco,591,5,5,5,3,4,5,4,4,4,5,5,4,4,4,0,0.0,satisfied +54151,33941,Male,Loyal Customer,38,Business travel,Business,2220,2,5,3,5,2,2,2,4,4,4,4,2,4,2,165,155.0,neutral or dissatisfied +54152,106164,Male,Loyal Customer,24,Personal Travel,Eco,436,2,2,3,4,5,3,3,5,2,1,4,4,4,5,26,18.0,neutral or dissatisfied +54153,107829,Male,Loyal Customer,66,Personal Travel,Eco,349,2,4,2,4,4,2,4,4,1,1,4,2,4,4,0,4.0,neutral or dissatisfied +54154,3429,Male,Loyal Customer,41,Personal Travel,Eco,296,2,5,2,3,1,2,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +54155,65702,Female,Loyal Customer,11,Business travel,Eco,1061,3,3,3,3,3,3,2,3,4,5,4,2,3,3,0,0.0,neutral or dissatisfied +54156,106393,Male,disloyal Customer,28,Business travel,Business,551,4,4,4,3,1,4,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +54157,127142,Female,Loyal Customer,63,Personal Travel,Eco,325,1,1,1,3,3,3,2,3,3,1,4,3,3,2,0,7.0,neutral or dissatisfied +54158,2911,Male,disloyal Customer,27,Business travel,Business,409,2,2,2,1,1,2,1,1,3,2,5,4,4,1,0,1.0,neutral or dissatisfied +54159,72679,Female,Loyal Customer,20,Personal Travel,Eco,964,3,5,3,4,4,3,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +54160,103066,Male,disloyal Customer,25,Business travel,Business,287,2,1,2,4,1,2,1,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +54161,66163,Female,Loyal Customer,50,Business travel,Business,550,4,4,4,4,2,4,5,4,4,4,4,4,4,4,5,0.0,satisfied +54162,100198,Female,Loyal Customer,27,Business travel,Eco Plus,717,3,3,3,3,3,3,3,3,4,2,3,1,3,3,0,0.0,neutral or dissatisfied +54163,82834,Female,Loyal Customer,39,Business travel,Business,3613,1,1,1,1,2,4,5,4,4,4,4,4,4,4,3,5.0,satisfied +54164,965,Male,disloyal Customer,27,Business travel,Business,140,2,1,1,4,3,1,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +54165,56574,Female,Loyal Customer,40,Business travel,Business,1837,4,4,4,4,4,4,5,4,4,4,4,5,4,4,44,23.0,satisfied +54166,458,Male,Loyal Customer,43,Business travel,Business,113,5,5,5,5,5,4,4,5,5,5,4,4,5,4,0,0.0,satisfied +54167,96206,Male,Loyal Customer,35,Business travel,Eco,490,1,4,4,4,1,1,1,1,4,5,2,1,3,1,0,0.0,neutral or dissatisfied +54168,114912,Female,Loyal Customer,36,Business travel,Business,373,5,5,5,5,4,4,4,5,5,5,5,5,5,3,27,22.0,satisfied +54169,87957,Female,disloyal Customer,22,Business travel,Business,240,5,4,5,3,2,4,2,2,5,4,5,3,5,2,0,12.0,satisfied +54170,19762,Female,Loyal Customer,20,Personal Travel,Eco,462,5,2,5,3,4,5,4,4,2,4,3,1,4,4,0,0.0,satisfied +54171,64504,Female,Loyal Customer,48,Business travel,Business,247,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +54172,126511,Male,Loyal Customer,26,Business travel,Business,2560,2,2,2,2,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +54173,1956,Male,disloyal Customer,23,Business travel,Business,285,2,1,2,2,1,2,1,1,4,2,3,2,2,1,95,85.0,neutral or dissatisfied +54174,115895,Male,disloyal Customer,15,Business travel,Eco,337,3,4,3,3,2,3,2,2,3,1,3,2,3,2,27,23.0,neutral or dissatisfied +54175,104960,Male,Loyal Customer,46,Business travel,Business,314,0,0,0,3,3,4,5,4,4,4,4,4,4,3,0,1.0,satisfied +54176,71957,Male,Loyal Customer,49,Business travel,Business,1440,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +54177,71192,Male,Loyal Customer,28,Business travel,Business,733,5,5,5,5,5,5,5,5,5,3,4,4,5,5,14,0.0,satisfied +54178,128994,Male,Loyal Customer,20,Business travel,Eco Plus,414,5,2,2,2,5,5,3,5,4,2,5,4,1,5,0,0.0,satisfied +54179,91388,Female,Loyal Customer,38,Business travel,Eco,2158,4,4,4,4,4,4,4,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +54180,72902,Female,Loyal Customer,58,Business travel,Business,3780,3,1,1,1,1,3,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +54181,12492,Female,Loyal Customer,47,Business travel,Eco Plus,201,5,2,2,2,1,4,3,5,5,5,5,4,5,5,0,0.0,satisfied +54182,124416,Female,disloyal Customer,20,Business travel,Business,1044,0,2,0,3,2,0,2,2,5,2,4,4,4,2,7,11.0,satisfied +54183,66346,Female,Loyal Customer,55,Business travel,Business,986,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +54184,54837,Female,Loyal Customer,49,Business travel,Business,2886,4,4,4,4,2,5,5,5,5,5,5,4,5,5,5,3.0,satisfied +54185,18333,Female,disloyal Customer,25,Business travel,Eco,554,3,3,3,3,5,3,2,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +54186,108886,Male,disloyal Customer,35,Business travel,Business,1066,2,2,2,2,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +54187,43208,Male,Loyal Customer,32,Personal Travel,Eco,466,3,3,4,4,5,4,5,5,4,1,4,4,3,5,75,84.0,neutral or dissatisfied +54188,63677,Male,Loyal Customer,27,Business travel,Business,1627,2,3,3,3,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +54189,123788,Female,disloyal Customer,34,Business travel,Business,541,3,3,3,1,3,3,3,3,3,4,5,3,5,3,4,6.0,neutral or dissatisfied +54190,15749,Male,Loyal Customer,68,Business travel,Eco,461,5,4,4,4,5,5,5,5,2,2,4,2,2,5,0,0.0,satisfied +54191,67340,Female,Loyal Customer,46,Business travel,Eco,1471,4,3,2,3,4,1,4,4,4,4,4,2,4,3,1,6.0,satisfied +54192,112176,Female,Loyal Customer,31,Personal Travel,Eco,895,1,5,1,4,5,1,5,5,3,5,4,3,4,5,63,65.0,neutral or dissatisfied +54193,45679,Female,disloyal Customer,25,Business travel,Eco,896,4,4,4,1,4,4,4,4,3,3,4,5,4,4,5,3.0,neutral or dissatisfied +54194,87225,Female,Loyal Customer,8,Personal Travel,Eco,946,2,2,2,4,5,2,5,5,1,3,4,4,4,5,8,0.0,neutral or dissatisfied +54195,30762,Male,Loyal Customer,64,Business travel,Eco,683,2,1,1,1,2,2,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +54196,74960,Female,Loyal Customer,36,Business travel,Business,3299,2,2,3,2,4,1,1,5,5,5,5,4,5,3,0,0.0,satisfied +54197,112431,Female,disloyal Customer,28,Business travel,Business,862,5,4,4,1,3,4,3,3,5,4,4,4,5,3,0,0.0,satisfied +54198,105880,Female,Loyal Customer,43,Business travel,Business,283,5,5,4,5,5,5,5,5,5,4,5,4,5,4,2,0.0,satisfied +54199,88171,Male,Loyal Customer,57,Business travel,Business,3164,5,5,2,5,3,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +54200,1031,Female,disloyal Customer,19,Business travel,Eco,89,4,0,4,4,4,4,4,4,1,2,3,1,4,4,0,0.0,neutral or dissatisfied +54201,118885,Female,disloyal Customer,15,Business travel,Business,570,0,5,0,2,4,0,4,4,3,4,4,4,4,4,0,0.0,satisfied +54202,3902,Male,Loyal Customer,31,Personal Travel,Eco,213,1,5,1,4,2,1,2,2,2,1,1,2,3,2,0,0.0,neutral or dissatisfied +54203,18389,Male,Loyal Customer,53,Personal Travel,Eco,493,5,5,5,3,2,5,2,2,5,2,5,5,4,2,0,0.0,satisfied +54204,101333,Female,Loyal Customer,49,Business travel,Business,1771,5,5,4,5,3,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +54205,44070,Female,Loyal Customer,62,Business travel,Eco Plus,456,4,3,3,3,3,1,2,4,4,4,4,2,4,3,28,57.0,neutral or dissatisfied +54206,68433,Female,disloyal Customer,20,Business travel,Eco,1045,3,3,3,2,3,3,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +54207,25624,Female,Loyal Customer,12,Business travel,Business,3043,3,2,2,2,3,2,3,3,4,1,4,3,4,3,20,3.0,neutral or dissatisfied +54208,10837,Male,Loyal Customer,78,Business travel,Business,3953,2,4,5,4,3,3,3,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +54209,49143,Male,Loyal Customer,44,Business travel,Business,373,3,2,3,3,3,4,1,3,3,3,3,5,3,5,0,0.0,satisfied +54210,19192,Female,Loyal Customer,32,Business travel,Business,2304,4,4,4,4,5,5,5,5,5,4,3,2,3,5,0,0.0,satisfied +54211,92851,Female,Loyal Customer,46,Personal Travel,Eco Plus,1587,0,2,0,3,3,3,3,4,4,0,4,4,4,1,5,0.0,satisfied +54212,26071,Female,Loyal Customer,53,Business travel,Eco,591,2,2,2,2,3,3,5,2,2,2,2,4,2,3,14,33.0,satisfied +54213,34714,Female,Loyal Customer,58,Business travel,Business,3427,2,2,2,2,1,2,3,5,5,5,5,3,5,4,30,29.0,satisfied +54214,60348,Male,Loyal Customer,41,Personal Travel,Eco,1024,4,5,4,4,5,4,5,5,3,1,2,2,2,5,0,0.0,satisfied +54215,1032,Female,Loyal Customer,79,Business travel,Business,164,3,2,2,2,3,4,3,1,1,2,3,3,1,1,73,75.0,neutral or dissatisfied +54216,61875,Male,Loyal Customer,48,Business travel,Business,2521,1,1,1,1,5,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +54217,28248,Female,Loyal Customer,23,Business travel,Business,1542,3,3,3,3,4,4,4,4,4,5,4,3,4,4,0,4.0,satisfied +54218,102674,Male,Loyal Customer,27,Business travel,Business,255,3,3,3,3,4,4,4,4,4,5,5,4,5,4,1,0.0,satisfied +54219,9892,Female,Loyal Customer,41,Business travel,Business,2163,1,1,1,1,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +54220,89023,Male,Loyal Customer,50,Personal Travel,Business,1947,3,4,2,5,5,4,4,4,4,2,3,4,4,3,0,9.0,neutral or dissatisfied +54221,112808,Male,Loyal Customer,48,Business travel,Business,1497,2,2,2,2,3,5,4,5,5,5,5,4,5,4,14,14.0,satisfied +54222,54598,Female,Loyal Customer,51,Business travel,Business,3949,4,4,4,4,5,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +54223,45543,Male,disloyal Customer,56,Business travel,Eco,166,4,0,4,2,1,4,1,1,1,4,3,5,5,1,0,0.0,satisfied +54224,124204,Female,Loyal Customer,50,Business travel,Business,2176,1,1,1,1,3,3,5,4,4,3,4,4,4,5,11,0.0,satisfied +54225,21178,Female,disloyal Customer,36,Business travel,Eco,317,1,0,1,3,3,1,1,3,5,1,1,4,3,3,0,7.0,neutral or dissatisfied +54226,80989,Male,Loyal Customer,31,Business travel,Eco,228,0,0,0,3,1,0,1,1,4,2,1,4,4,1,0,2.0,satisfied +54227,59752,Female,Loyal Customer,49,Business travel,Business,895,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +54228,14321,Male,disloyal Customer,17,Business travel,Eco,429,4,0,3,5,2,3,4,2,1,3,1,2,2,2,0,0.0,neutral or dissatisfied +54229,18001,Female,disloyal Customer,23,Business travel,Eco,332,2,2,2,3,3,2,3,3,4,3,4,1,4,3,14,23.0,neutral or dissatisfied +54230,3038,Female,Loyal Customer,53,Business travel,Business,3913,5,5,2,5,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +54231,86685,Male,Loyal Customer,38,Personal Travel,Business,1747,3,4,3,5,2,4,4,1,1,3,1,4,1,5,50,32.0,neutral or dissatisfied +54232,111103,Female,Loyal Customer,69,Business travel,Eco Plus,197,1,1,4,4,4,2,2,1,1,1,1,2,1,1,32,27.0,neutral or dissatisfied +54233,21295,Male,disloyal Customer,26,Business travel,Eco,692,2,3,3,3,1,3,1,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +54234,44029,Male,Loyal Customer,52,Business travel,Business,2670,1,1,1,1,1,2,4,4,4,4,4,3,4,5,0,4.0,satisfied +54235,100283,Male,Loyal Customer,50,Business travel,Business,3701,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +54236,23435,Female,disloyal Customer,38,Business travel,Eco,516,3,0,4,4,4,4,4,4,1,5,3,4,4,4,7,11.0,neutral or dissatisfied +54237,15243,Female,Loyal Customer,57,Personal Travel,Eco,529,3,4,3,3,5,4,5,3,3,3,2,3,3,4,8,0.0,neutral or dissatisfied +54238,3482,Male,Loyal Customer,53,Business travel,Business,3183,1,1,1,1,3,5,4,4,4,4,4,5,4,3,94,70.0,satisfied +54239,37341,Male,Loyal Customer,27,Business travel,Eco,1074,5,4,5,4,5,5,5,5,1,4,1,2,4,5,0,0.0,satisfied +54240,25755,Male,Loyal Customer,22,Business travel,Business,3795,1,1,1,1,4,4,4,4,3,2,4,1,3,4,0,0.0,satisfied +54241,94853,Female,Loyal Customer,47,Business travel,Business,2687,1,1,1,1,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +54242,122162,Female,disloyal Customer,26,Business travel,Eco,541,1,0,2,3,3,2,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +54243,42443,Male,Loyal Customer,20,Personal Travel,Eco,1136,3,4,3,4,5,3,5,5,3,5,3,4,5,5,0,5.0,neutral or dissatisfied +54244,84981,Male,Loyal Customer,41,Business travel,Business,1590,4,4,4,4,3,5,4,2,2,2,2,3,2,3,40,37.0,satisfied +54245,54052,Female,Loyal Customer,25,Business travel,Business,1416,3,3,3,3,4,4,4,4,5,5,5,2,3,4,0,0.0,satisfied +54246,62188,Male,Loyal Customer,65,Business travel,Business,954,1,1,4,1,1,4,2,4,4,4,4,3,4,4,2,0.0,satisfied +54247,98201,Male,Loyal Customer,44,Personal Travel,Eco,327,3,1,3,4,3,3,3,3,2,2,4,2,4,3,7,11.0,neutral or dissatisfied +54248,28068,Female,disloyal Customer,24,Business travel,Eco,1327,3,2,2,2,3,3,3,1,5,3,4,3,1,3,0,0.0,satisfied +54249,43646,Male,Loyal Customer,41,Business travel,Business,1571,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +54250,45548,Female,Loyal Customer,65,Personal Travel,Eco,566,2,4,2,3,4,1,2,1,1,2,1,3,1,2,0,4.0,neutral or dissatisfied +54251,19304,Female,Loyal Customer,11,Personal Travel,Eco,196,3,5,3,3,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +54252,63503,Male,Loyal Customer,8,Personal Travel,Eco,1956,2,2,2,4,4,2,3,4,2,4,2,3,3,4,0,0.0,neutral or dissatisfied +54253,121873,Female,Loyal Customer,55,Business travel,Business,366,3,1,1,1,1,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +54254,67210,Female,Loyal Customer,46,Personal Travel,Eco,1121,2,5,2,4,3,5,5,2,2,2,3,5,2,5,19,13.0,neutral or dissatisfied +54255,108971,Female,disloyal Customer,25,Business travel,Business,667,3,0,3,2,3,3,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +54256,20255,Male,Loyal Customer,17,Business travel,Business,2234,2,5,5,5,2,1,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +54257,5891,Female,Loyal Customer,48,Business travel,Business,3108,5,5,5,5,3,5,5,5,5,5,5,5,5,3,48,39.0,satisfied +54258,39562,Female,Loyal Customer,53,Business travel,Eco,679,4,1,1,1,5,4,5,4,4,4,4,1,4,1,0,4.0,satisfied +54259,69464,Male,Loyal Customer,33,Personal Travel,Eco,1096,3,3,3,3,4,3,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +54260,10090,Female,Loyal Customer,55,Business travel,Business,763,2,2,2,2,2,4,4,3,3,3,3,5,3,4,0,6.0,satisfied +54261,11025,Male,disloyal Customer,24,Business travel,Eco,270,0,5,0,4,3,0,3,3,2,3,4,1,3,3,0,0.0,satisfied +54262,21311,Male,Loyal Customer,31,Personal Travel,Eco,620,2,5,2,5,1,2,1,1,4,5,4,4,4,1,41,30.0,neutral or dissatisfied +54263,8832,Female,Loyal Customer,46,Business travel,Business,3247,2,2,2,2,3,4,4,4,4,4,4,3,4,5,81,62.0,satisfied +54264,83737,Male,Loyal Customer,16,Personal Travel,Business,1183,3,4,3,4,3,3,3,3,3,5,4,4,5,3,57,69.0,neutral or dissatisfied +54265,29251,Female,Loyal Customer,14,Business travel,Eco,834,4,5,5,5,4,4,4,4,4,5,4,5,5,4,0,14.0,satisfied +54266,80139,Male,Loyal Customer,41,Business travel,Business,2475,1,1,1,1,4,4,4,5,5,4,5,4,3,4,4,12.0,satisfied +54267,38646,Male,Loyal Customer,47,Business travel,Eco,2588,4,4,4,4,4,4,4,2,5,3,3,4,5,4,187,165.0,satisfied +54268,96491,Male,Loyal Customer,80,Business travel,Business,436,2,1,3,1,5,4,4,2,2,2,2,1,2,1,10,6.0,neutral or dissatisfied +54269,6839,Female,Loyal Customer,64,Personal Travel,Eco,235,2,5,2,1,2,4,4,4,4,2,1,5,4,4,0,0.0,neutral or dissatisfied +54270,4804,Male,Loyal Customer,48,Personal Travel,Eco,438,3,1,3,4,5,3,5,5,3,2,4,3,4,5,40,36.0,neutral or dissatisfied +54271,112318,Male,Loyal Customer,49,Business travel,Business,2433,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +54272,8875,Female,Loyal Customer,54,Business travel,Business,3007,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +54273,55081,Female,disloyal Customer,42,Business travel,Business,1635,3,3,3,4,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +54274,23433,Male,Loyal Customer,17,Personal Travel,Business,488,2,2,4,4,2,4,2,2,4,3,4,4,3,2,19,18.0,neutral or dissatisfied +54275,23646,Male,Loyal Customer,44,Business travel,Business,1511,5,5,5,5,4,4,5,5,5,5,5,4,5,5,10,0.0,satisfied +54276,94344,Female,Loyal Customer,31,Business travel,Business,248,3,3,3,3,5,5,5,5,3,5,5,5,3,5,209,203.0,satisfied +54277,3830,Female,Loyal Customer,67,Business travel,Business,2953,2,4,4,4,1,4,3,2,2,2,2,4,2,2,14,0.0,neutral or dissatisfied +54278,80625,Male,Loyal Customer,43,Personal Travel,Eco Plus,236,1,4,1,3,4,1,4,4,4,4,5,3,4,4,0,5.0,neutral or dissatisfied +54279,118993,Male,Loyal Customer,35,Business travel,Eco,479,3,4,4,4,3,3,3,3,2,2,4,1,3,3,7,5.0,neutral or dissatisfied +54280,33246,Male,Loyal Customer,35,Business travel,Eco Plus,216,3,1,1,1,3,3,3,3,1,3,3,4,1,3,0,0.0,satisfied +54281,60559,Female,disloyal Customer,44,Business travel,Eco Plus,585,2,2,2,4,3,2,3,3,1,2,2,1,3,3,0,9.0,neutral or dissatisfied +54282,20376,Female,Loyal Customer,13,Personal Travel,Eco,323,1,2,1,3,5,1,5,5,3,1,3,2,2,5,0,0.0,neutral or dissatisfied +54283,52124,Female,Loyal Customer,15,Business travel,Eco Plus,639,1,1,1,1,1,1,3,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +54284,23755,Male,Loyal Customer,46,Business travel,Business,3794,1,1,1,1,4,4,3,1,1,1,1,4,1,3,81,83.0,neutral or dissatisfied +54285,35122,Male,Loyal Customer,28,Business travel,Business,3277,2,2,2,2,4,4,4,4,5,4,5,5,3,4,0,0.0,satisfied +54286,31538,Male,Loyal Customer,20,Personal Travel,Eco,846,1,2,1,4,2,1,1,2,2,1,4,3,3,2,1,0.0,neutral or dissatisfied +54287,36366,Male,Loyal Customer,46,Business travel,Business,3631,2,5,5,5,4,3,3,4,4,4,2,2,4,1,0,4.0,neutral or dissatisfied +54288,82305,Female,Loyal Customer,60,Business travel,Business,986,2,2,2,2,4,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +54289,42810,Male,Loyal Customer,24,Business travel,Business,1536,3,3,3,3,4,4,4,4,3,2,4,1,3,4,0,0.0,satisfied +54290,121253,Male,Loyal Customer,15,Business travel,Business,2075,3,1,1,1,3,3,3,2,5,4,3,3,4,3,463,503.0,neutral or dissatisfied +54291,47537,Female,Loyal Customer,65,Personal Travel,Eco,626,3,4,3,4,5,5,5,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +54292,65668,Male,disloyal Customer,30,Business travel,Business,861,3,3,3,3,1,3,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +54293,37787,Male,disloyal Customer,30,Business travel,Eco Plus,944,4,4,4,3,4,4,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +54294,65233,Male,Loyal Customer,66,Business travel,Business,247,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +54295,45254,Female,Loyal Customer,24,Personal Travel,Eco Plus,522,3,4,3,2,3,3,2,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +54296,30458,Female,Loyal Customer,24,Personal Travel,Eco,991,3,3,3,4,3,2,3,1,2,3,3,3,1,3,164,149.0,neutral or dissatisfied +54297,117796,Male,disloyal Customer,44,Business travel,Business,328,3,2,2,3,2,3,2,2,4,3,5,4,5,2,15,17.0,neutral or dissatisfied +54298,113886,Male,Loyal Customer,59,Business travel,Business,2329,1,1,1,1,5,4,4,4,4,4,4,4,4,5,12,0.0,satisfied +54299,85819,Male,Loyal Customer,26,Personal Travel,Eco,666,3,4,3,4,3,3,3,3,3,1,4,3,3,3,8,2.0,neutral or dissatisfied +54300,73354,Male,Loyal Customer,27,Business travel,Eco,1197,2,5,1,1,2,2,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +54301,55254,Female,Loyal Customer,51,Personal Travel,Eco,1009,1,2,1,4,1,2,2,2,2,3,3,2,3,2,180,233.0,neutral or dissatisfied +54302,114609,Female,Loyal Customer,60,Business travel,Business,308,2,2,3,2,4,4,4,4,4,4,4,5,4,4,58,55.0,satisfied +54303,70867,Female,Loyal Customer,24,Personal Travel,Eco,761,4,5,4,2,2,4,1,2,3,4,5,3,5,2,42,58.0,neutral or dissatisfied +54304,81324,Male,Loyal Customer,25,Business travel,Business,2821,2,2,2,2,5,5,5,5,3,3,4,5,5,5,21,7.0,satisfied +54305,16019,Male,Loyal Customer,40,Personal Travel,Eco,780,1,5,1,3,1,1,1,1,5,2,5,3,5,1,0,10.0,neutral or dissatisfied +54306,93878,Male,Loyal Customer,58,Business travel,Business,588,5,5,5,5,4,5,4,5,5,5,5,5,5,4,19,21.0,satisfied +54307,42615,Male,Loyal Customer,73,Business travel,Business,223,4,2,4,4,1,3,1,5,5,5,4,4,5,5,0,0.0,satisfied +54308,129033,Male,Loyal Customer,43,Business travel,Business,1846,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +54309,92317,Male,disloyal Customer,26,Business travel,Business,2615,4,4,4,4,4,3,3,4,5,5,5,3,5,3,0,14.0,satisfied +54310,12845,Female,Loyal Customer,51,Personal Travel,Eco,528,5,5,4,2,5,5,5,2,2,4,2,5,2,3,19,3.0,satisfied +54311,119996,Male,Loyal Customer,57,Business travel,Business,1733,5,5,4,5,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +54312,123404,Female,Loyal Customer,54,Business travel,Business,1337,1,1,1,1,4,4,5,4,4,4,4,3,4,4,5,16.0,satisfied +54313,23885,Female,Loyal Customer,29,Business travel,Business,589,4,2,4,4,2,2,2,2,3,1,1,3,2,2,0,0.0,satisfied +54314,7267,Female,Loyal Customer,15,Personal Travel,Eco,116,2,3,0,2,4,0,4,4,2,5,4,5,3,4,0,0.0,neutral or dissatisfied +54315,75016,Male,Loyal Customer,50,Business travel,Business,3831,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +54316,66539,Female,Loyal Customer,29,Business travel,Business,3359,1,1,1,1,5,5,5,5,4,2,5,5,4,5,74,75.0,satisfied +54317,23625,Male,Loyal Customer,45,Personal Travel,Business,793,4,1,4,3,3,3,4,2,2,4,2,1,2,4,0,29.0,neutral or dissatisfied +54318,53323,Female,Loyal Customer,54,Personal Travel,Eco,901,3,4,3,3,4,3,3,5,5,3,5,5,5,5,11,2.0,neutral or dissatisfied +54319,117718,Male,Loyal Customer,8,Personal Travel,Eco,1009,2,4,2,4,2,2,5,2,1,2,1,1,1,2,3,32.0,neutral or dissatisfied +54320,94448,Female,Loyal Customer,47,Business travel,Business,3888,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,2.0,satisfied +54321,39672,Female,disloyal Customer,28,Business travel,Eco Plus,476,1,1,1,2,3,1,3,3,4,3,3,2,3,3,0,5.0,neutral or dissatisfied +54322,110063,Male,Loyal Customer,29,Business travel,Eco Plus,1984,2,2,2,2,2,3,2,2,2,3,4,3,4,2,2,20.0,neutral or dissatisfied +54323,24498,Female,Loyal Customer,68,Personal Travel,Eco,547,1,0,1,3,5,3,5,2,2,1,2,5,2,3,15,33.0,neutral or dissatisfied +54324,10724,Female,Loyal Customer,57,Business travel,Business,2667,0,5,0,4,4,4,4,2,2,2,2,4,2,5,89,78.0,satisfied +54325,69600,Male,Loyal Customer,9,Personal Travel,Eco,2475,2,5,2,3,2,3,3,3,4,4,4,3,5,3,1,2.0,neutral or dissatisfied +54326,46661,Female,disloyal Customer,22,Business travel,Eco,125,3,1,3,3,2,3,5,2,3,2,4,1,4,2,10,7.0,neutral or dissatisfied +54327,64614,Female,Loyal Customer,31,Business travel,Business,224,1,3,3,3,2,2,1,2,1,4,1,4,1,2,71,98.0,neutral or dissatisfied +54328,60846,Female,Loyal Customer,65,Personal Travel,Eco,1754,2,3,2,3,4,2,3,3,3,2,3,3,3,3,0,14.0,neutral or dissatisfied +54329,74226,Male,Loyal Customer,54,Business travel,Business,1007,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +54330,5619,Female,Loyal Customer,51,Personal Travel,Eco,685,3,3,3,3,4,2,3,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +54331,61220,Female,Loyal Customer,13,Business travel,Business,1517,3,3,3,3,5,5,5,5,5,3,5,4,4,5,2,18.0,satisfied +54332,48839,Male,Loyal Customer,15,Personal Travel,Business,89,3,5,3,3,4,3,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +54333,50221,Female,Loyal Customer,37,Business travel,Business,3244,1,3,3,3,5,4,4,1,1,1,1,3,1,3,114,102.0,neutral or dissatisfied +54334,17923,Female,Loyal Customer,8,Personal Travel,Eco,789,3,4,3,4,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +54335,102446,Female,Loyal Customer,34,Personal Travel,Eco,386,3,4,3,3,1,3,1,1,4,5,5,4,4,1,16,11.0,neutral or dissatisfied +54336,18090,Female,Loyal Customer,36,Personal Travel,Eco,488,2,4,4,1,2,4,2,2,3,5,4,5,4,2,7,0.0,neutral or dissatisfied +54337,61833,Male,disloyal Customer,44,Business travel,Business,1303,3,3,3,5,2,3,3,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +54338,91029,Female,Loyal Customer,38,Personal Travel,Eco,515,2,5,2,3,5,2,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +54339,8137,Male,disloyal Customer,27,Business travel,Eco,530,4,3,4,3,5,4,5,5,3,2,3,1,4,5,7,7.0,neutral or dissatisfied +54340,65400,Male,Loyal Customer,63,Personal Travel,Eco,432,5,1,5,3,3,5,3,3,4,1,4,2,3,3,0,0.0,satisfied +54341,65670,Male,Loyal Customer,63,Business travel,Eco,926,3,3,3,3,2,3,2,2,1,4,3,3,3,2,6,0.0,neutral or dissatisfied +54342,18409,Female,Loyal Customer,54,Personal Travel,Eco,284,3,5,3,2,2,5,5,1,1,3,1,3,1,3,0,6.0,neutral or dissatisfied +54343,113309,Female,Loyal Customer,57,Business travel,Business,258,0,0,0,1,4,4,4,3,3,3,3,3,3,3,7,7.0,satisfied +54344,19607,Female,Loyal Customer,54,Business travel,Eco,416,2,5,2,5,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +54345,50386,Female,Loyal Customer,38,Business travel,Eco,337,4,5,5,5,4,4,4,4,4,3,2,1,4,4,0,3.0,satisfied +54346,101152,Male,Loyal Customer,48,Business travel,Business,1235,2,4,4,4,5,4,3,2,2,2,2,4,2,1,46,37.0,neutral or dissatisfied +54347,115991,Male,Loyal Customer,47,Personal Travel,Eco,371,4,3,4,4,1,4,1,1,2,4,5,1,2,1,0,4.0,neutral or dissatisfied +54348,10710,Female,disloyal Customer,48,Business travel,Business,295,4,4,4,2,2,4,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +54349,43038,Male,Loyal Customer,36,Business travel,Eco,236,4,2,1,1,4,3,4,4,5,1,1,2,4,4,5,0.0,satisfied +54350,92554,Female,Loyal Customer,35,Personal Travel,Eco,1892,3,4,3,3,2,3,3,2,3,4,3,4,3,2,0,11.0,neutral or dissatisfied +54351,90007,Female,Loyal Customer,13,Personal Travel,Business,1145,3,4,3,1,3,3,3,3,3,2,4,1,5,3,0,0.0,neutral or dissatisfied +54352,71224,Male,Loyal Customer,24,Business travel,Business,2941,2,2,2,2,3,3,3,3,4,2,5,3,5,3,0,0.0,satisfied +54353,122785,Female,Loyal Customer,26,Business travel,Business,1968,3,3,3,3,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +54354,79649,Female,Loyal Customer,47,Business travel,Eco,349,5,2,2,2,2,3,5,5,5,5,5,3,5,1,13,0.0,satisfied +54355,109573,Male,Loyal Customer,57,Personal Travel,Eco,992,4,4,4,1,2,4,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +54356,57896,Male,Loyal Customer,41,Business travel,Business,1925,1,1,3,1,5,4,4,5,5,5,5,5,5,5,7,0.0,satisfied +54357,14471,Male,Loyal Customer,63,Personal Travel,Eco,761,2,4,2,3,1,2,1,1,4,2,3,4,5,1,8,12.0,neutral or dissatisfied +54358,2571,Female,Loyal Customer,57,Business travel,Business,280,3,5,5,5,2,3,3,3,3,3,3,2,3,4,52,53.0,neutral or dissatisfied +54359,94327,Female,disloyal Customer,50,Business travel,Business,192,5,5,5,4,3,5,3,3,4,5,5,3,4,3,21,12.0,satisfied +54360,120766,Male,Loyal Customer,49,Business travel,Business,1853,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +54361,27935,Male,Loyal Customer,25,Business travel,Business,1874,1,1,1,1,2,2,2,2,5,5,3,5,2,2,0,0.0,satisfied +54362,18574,Female,disloyal Customer,20,Business travel,Eco,201,2,0,2,1,3,2,3,3,4,4,3,3,1,3,0,0.0,neutral or dissatisfied +54363,36846,Female,Loyal Customer,27,Personal Travel,Eco,369,1,2,5,4,5,5,5,5,4,3,4,2,3,5,0,0.0,neutral or dissatisfied +54364,76739,Female,Loyal Customer,48,Business travel,Business,3741,2,2,2,2,2,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +54365,49911,Female,Loyal Customer,35,Business travel,Business,3158,3,1,2,2,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +54366,111510,Female,Loyal Customer,76,Business travel,Eco,391,4,1,1,1,3,2,3,4,4,4,4,1,4,3,7,17.0,neutral or dissatisfied +54367,67103,Female,Loyal Customer,29,Business travel,Business,985,2,2,5,2,2,2,2,2,4,2,3,2,2,2,139,131.0,neutral or dissatisfied +54368,91357,Male,Loyal Customer,54,Personal Travel,Eco Plus,406,2,5,2,4,5,2,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +54369,93223,Female,disloyal Customer,28,Business travel,Business,1460,1,1,1,4,5,1,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +54370,67290,Female,Loyal Customer,38,Business travel,Business,1855,4,4,4,4,4,5,5,4,4,4,4,4,4,3,22,16.0,satisfied +54371,71239,Female,Loyal Customer,43,Business travel,Eco,733,3,3,3,3,2,4,3,3,3,3,3,4,3,3,56,36.0,neutral or dissatisfied +54372,111283,Female,Loyal Customer,23,Personal Travel,Eco,479,1,3,1,4,1,1,1,1,2,2,4,2,3,1,50,40.0,neutral or dissatisfied +54373,78879,Female,Loyal Customer,51,Personal Travel,Eco,223,5,4,5,1,4,4,4,3,3,5,3,4,3,3,0,0.0,satisfied +54374,77102,Female,Loyal Customer,57,Business travel,Business,1481,1,1,1,1,5,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +54375,127360,Female,Loyal Customer,8,Personal Travel,Eco,507,2,4,2,5,3,2,3,3,3,4,2,4,3,3,46,38.0,neutral or dissatisfied +54376,82245,Female,Loyal Customer,57,Business travel,Business,405,2,2,2,2,3,5,5,3,3,3,3,4,3,3,38,35.0,satisfied +54377,81942,Male,Loyal Customer,47,Business travel,Business,1454,5,5,4,5,3,4,5,4,4,5,4,4,4,4,1,0.0,satisfied +54378,80802,Male,Loyal Customer,48,Business travel,Business,2389,3,3,3,3,5,4,5,4,4,4,4,4,4,3,6,1.0,satisfied +54379,118875,Male,Loyal Customer,50,Business travel,Business,1136,3,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0.0,satisfied +54380,98226,Female,Loyal Customer,30,Business travel,Business,3931,2,1,2,2,4,4,4,4,3,3,5,5,4,4,0,0.0,satisfied +54381,112011,Male,Loyal Customer,50,Business travel,Business,3570,3,2,2,2,2,4,4,3,3,2,3,2,3,2,5,0.0,neutral or dissatisfied +54382,109820,Male,Loyal Customer,57,Business travel,Business,3430,2,2,2,2,5,4,4,4,4,4,4,3,4,3,3,4.0,satisfied +54383,20036,Male,Loyal Customer,50,Business travel,Business,1792,4,4,4,4,3,3,5,4,4,4,4,5,4,1,0,0.0,satisfied +54384,73031,Female,Loyal Customer,14,Personal Travel,Eco,1096,3,2,3,2,5,3,5,5,4,5,2,4,2,5,2,0.0,neutral or dissatisfied +54385,30233,Male,Loyal Customer,22,Business travel,Business,2443,1,5,3,5,1,1,1,1,1,4,3,2,4,1,0,7.0,neutral or dissatisfied +54386,142,Male,Loyal Customer,58,Business travel,Business,227,2,2,4,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +54387,58418,Female,Loyal Customer,42,Business travel,Business,3460,1,1,2,1,1,1,1,1,5,2,2,1,1,1,255,244.0,neutral or dissatisfied +54388,55932,Male,Loyal Customer,53,Personal Travel,Eco,733,1,4,1,3,5,1,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +54389,73918,Female,disloyal Customer,18,Business travel,Eco,1170,4,4,4,1,3,4,3,3,4,2,5,4,4,3,1,0.0,satisfied +54390,2078,Female,Loyal Customer,65,Business travel,Eco,412,4,3,3,3,4,1,1,3,3,4,3,1,3,2,10,2.0,satisfied +54391,4214,Female,Loyal Customer,29,Personal Travel,Eco,888,3,2,3,3,1,3,1,1,2,4,2,1,3,1,37,38.0,neutral or dissatisfied +54392,51534,Female,Loyal Customer,32,Business travel,Business,3683,2,2,2,2,4,4,4,5,1,2,2,4,1,4,170,164.0,satisfied +54393,39224,Male,Loyal Customer,36,Business travel,Business,268,5,5,5,5,1,4,1,4,4,4,4,1,4,1,0,0.0,satisfied +54394,67286,Male,Loyal Customer,62,Personal Travel,Eco,964,3,4,3,3,2,3,2,2,3,3,4,3,5,2,30,16.0,neutral or dissatisfied +54395,47767,Female,Loyal Customer,51,Business travel,Business,2756,5,5,5,5,3,2,3,4,4,4,4,5,4,3,2,21.0,satisfied +54396,93969,Female,disloyal Customer,29,Business travel,Business,1315,3,3,3,4,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +54397,57762,Male,Loyal Customer,57,Business travel,Business,2704,5,5,5,5,4,3,3,3,2,4,4,3,4,3,10,12.0,satisfied +54398,89591,Female,Loyal Customer,46,Business travel,Business,1069,2,2,2,2,2,4,4,5,5,5,5,4,5,5,23,3.0,satisfied +54399,32829,Female,Loyal Customer,37,Business travel,Eco,102,4,5,5,5,4,4,4,4,4,4,1,4,2,4,0,0.0,neutral or dissatisfied +54400,61271,Male,Loyal Customer,48,Personal Travel,Eco,967,4,4,4,1,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +54401,90377,Male,Loyal Customer,59,Business travel,Business,515,1,4,4,4,2,4,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +54402,75221,Male,Loyal Customer,35,Business travel,Eco,1846,5,4,4,4,5,5,5,5,3,3,2,3,4,5,0,0.0,satisfied +54403,57830,Male,Loyal Customer,14,Personal Travel,Eco Plus,622,2,4,3,3,4,3,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +54404,53643,Male,Loyal Customer,67,Personal Travel,Eco,1874,4,4,4,4,3,4,3,3,4,3,4,2,3,3,0,6.0,neutral or dissatisfied +54405,73011,Female,Loyal Customer,33,Personal Travel,Eco,1096,3,4,3,4,2,3,2,2,1,3,4,4,4,2,3,0.0,neutral or dissatisfied +54406,121907,Male,Loyal Customer,10,Personal Travel,Eco,366,1,5,1,5,1,1,1,1,3,1,4,4,5,1,0,0.0,neutral or dissatisfied +54407,35059,Male,disloyal Customer,25,Business travel,Eco,1010,2,2,2,4,1,2,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +54408,40242,Male,Loyal Customer,69,Business travel,Eco,463,2,4,4,4,2,2,2,2,2,2,3,4,3,2,0,11.0,neutral or dissatisfied +54409,79498,Female,disloyal Customer,49,Business travel,Business,762,3,3,3,3,1,3,1,1,4,5,5,4,4,1,10,24.0,neutral or dissatisfied +54410,47931,Male,Loyal Customer,30,Personal Travel,Eco,817,4,4,4,3,4,4,4,4,4,1,4,4,2,4,0,0.0,satisfied +54411,26848,Male,Loyal Customer,31,Business travel,Business,224,2,5,5,5,3,3,2,3,4,5,4,2,3,3,0,6.0,neutral or dissatisfied +54412,15449,Female,disloyal Customer,26,Business travel,Eco,331,4,2,4,3,3,4,4,3,2,3,4,3,4,3,50,49.0,neutral or dissatisfied +54413,56333,Male,Loyal Customer,65,Business travel,Business,200,1,2,2,2,2,3,4,2,2,2,1,1,2,2,42,34.0,neutral or dissatisfied +54414,21763,Male,Loyal Customer,48,Personal Travel,Business,341,2,4,2,5,2,4,4,5,3,4,5,4,4,4,174,,neutral or dissatisfied +54415,55505,Male,Loyal Customer,26,Personal Travel,Eco Plus,1739,3,5,3,2,2,3,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +54416,38870,Female,Loyal Customer,29,Personal Travel,Eco,2300,3,5,3,2,1,3,1,1,1,2,4,2,1,1,0,0.0,neutral or dissatisfied +54417,121845,Male,Loyal Customer,44,Business travel,Business,3511,2,2,2,2,4,5,5,4,4,5,4,4,4,4,0,21.0,satisfied +54418,123950,Female,disloyal Customer,36,Business travel,Eco Plus,141,1,1,1,4,4,1,4,4,1,3,3,2,3,4,39,20.0,neutral or dissatisfied +54419,29723,Female,Loyal Customer,30,Business travel,Business,2777,5,5,5,5,4,4,4,2,5,5,1,4,5,4,0,8.0,satisfied +54420,18818,Male,disloyal Customer,23,Business travel,Eco,551,4,0,4,5,4,4,4,4,5,3,1,3,2,4,0,0.0,satisfied +54421,34155,Male,disloyal Customer,22,Business travel,Eco,1046,3,2,2,4,1,2,1,1,3,3,3,3,4,1,0,0.0,neutral or dissatisfied +54422,42740,Male,Loyal Customer,13,Personal Travel,Eco,599,2,2,2,4,5,2,3,5,2,2,3,3,3,5,0,5.0,neutral or dissatisfied +54423,52705,Female,disloyal Customer,26,Business travel,Eco,584,3,4,3,4,2,3,2,2,2,5,3,1,4,2,17,29.0,neutral or dissatisfied +54424,72616,Male,Loyal Customer,19,Personal Travel,Eco,985,4,5,4,1,3,4,3,3,3,2,4,5,4,3,1,0.0,neutral or dissatisfied +54425,56449,Male,Loyal Customer,32,Personal Travel,Eco,719,3,5,3,3,2,3,2,2,5,3,4,3,5,2,12,0.0,neutral or dissatisfied +54426,47316,Female,disloyal Customer,22,Business travel,Eco,532,4,3,4,3,5,4,5,5,4,3,5,5,2,5,0,0.0,satisfied +54427,59188,Male,disloyal Customer,25,Business travel,Eco,1440,5,0,0,3,5,5,5,5,3,4,4,5,5,5,16,34.0,satisfied +54428,13582,Male,Loyal Customer,7,Personal Travel,Eco,106,2,1,2,2,5,2,2,5,2,1,2,4,3,5,0,0.0,neutral or dissatisfied +54429,46426,Female,Loyal Customer,45,Personal Travel,Eco,649,3,5,3,4,3,5,1,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +54430,9313,Female,Loyal Customer,34,Business travel,Business,2654,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +54431,87832,Male,Loyal Customer,67,Personal Travel,Eco,214,4,0,4,5,5,4,5,5,1,5,4,1,1,5,0,0.0,satisfied +54432,77599,Female,Loyal Customer,26,Business travel,Business,731,1,1,1,1,4,4,4,4,3,4,4,5,4,4,0,0.0,satisfied +54433,38326,Female,disloyal Customer,25,Business travel,Eco,1111,2,2,2,4,5,2,2,5,4,4,4,2,3,5,0,9.0,neutral or dissatisfied +54434,13219,Male,disloyal Customer,23,Business travel,Eco,771,1,1,1,1,4,1,1,4,3,5,2,4,4,4,7,21.0,neutral or dissatisfied +54435,62204,Male,Loyal Customer,53,Personal Travel,Eco,2565,2,5,2,4,5,2,5,5,2,2,5,2,2,5,38,36.0,neutral or dissatisfied +54436,119271,Male,disloyal Customer,23,Business travel,Business,214,5,5,5,2,4,5,4,4,4,2,5,5,4,4,10,60.0,satisfied +54437,42838,Male,Loyal Customer,33,Business travel,Eco,328,4,1,1,1,5,5,5,5,1,5,1,5,3,5,0,0.0,satisfied +54438,70367,Female,disloyal Customer,27,Business travel,Eco,1145,3,3,3,3,5,3,5,5,2,1,3,2,4,5,0,6.0,neutral or dissatisfied +54439,42397,Female,Loyal Customer,23,Business travel,Eco Plus,784,0,3,0,2,0,5,5,1,2,1,5,5,5,5,138,186.0,satisfied +54440,32139,Male,disloyal Customer,25,Business travel,Eco,101,2,5,1,1,4,1,4,4,1,5,5,3,2,4,0,2.0,neutral or dissatisfied +54441,90620,Male,Loyal Customer,26,Business travel,Business,3528,2,4,4,4,2,2,2,2,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +54442,6160,Male,Loyal Customer,38,Business travel,Business,2686,2,5,3,3,3,2,3,2,2,2,2,2,2,2,0,8.0,neutral or dissatisfied +54443,90267,Female,disloyal Customer,52,Business travel,Business,879,3,3,3,3,3,3,3,3,4,3,5,5,4,3,18,17.0,neutral or dissatisfied +54444,19775,Female,disloyal Customer,49,Business travel,Eco,667,1,0,1,5,2,1,5,2,1,2,1,5,4,2,36,30.0,neutral or dissatisfied +54445,105128,Male,Loyal Customer,32,Business travel,Business,3075,2,5,5,5,2,2,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +54446,81960,Male,Loyal Customer,55,Business travel,Business,1576,5,5,5,5,5,4,5,4,4,4,4,5,4,5,8,0.0,satisfied +54447,25807,Male,Loyal Customer,36,Personal Travel,Eco Plus,762,1,5,1,1,3,1,3,3,5,5,5,5,4,3,0,8.0,neutral or dissatisfied +54448,77447,Male,Loyal Customer,51,Business travel,Business,507,2,2,3,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +54449,5861,Female,Loyal Customer,65,Personal Travel,Eco,1020,3,3,3,2,2,4,1,5,5,3,5,1,5,1,0,2.0,neutral or dissatisfied +54450,105282,Male,Loyal Customer,48,Business travel,Business,2726,1,1,1,1,4,5,5,4,4,4,4,5,4,3,60,55.0,satisfied +54451,10566,Female,Loyal Customer,17,Business travel,Eco,295,1,1,0,4,2,0,2,2,3,2,3,3,3,2,3,5.0,neutral or dissatisfied +54452,37136,Female,Loyal Customer,27,Business travel,Business,3316,1,4,3,4,1,1,1,1,4,5,4,4,4,1,5,5.0,neutral or dissatisfied +54453,81142,Male,Loyal Customer,43,Personal Travel,Eco Plus,991,1,5,1,4,4,1,4,4,4,2,4,4,4,4,8,24.0,neutral or dissatisfied +54454,125680,Male,disloyal Customer,9,Business travel,Eco,814,3,3,3,1,3,3,4,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +54455,55448,Female,Loyal Customer,66,Personal Travel,Eco,2136,2,4,1,3,3,5,5,1,1,1,1,3,1,5,4,0.0,neutral or dissatisfied +54456,94265,Male,disloyal Customer,38,Business travel,Business,277,4,4,4,1,3,4,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +54457,34666,Female,disloyal Customer,26,Business travel,Business,209,3,3,3,4,1,3,1,1,2,2,4,2,4,1,6,88.0,neutral or dissatisfied +54458,78352,Male,Loyal Customer,69,Personal Travel,Eco,1547,1,5,1,4,3,1,5,3,3,2,4,4,4,3,122,111.0,neutral or dissatisfied +54459,25652,Female,Loyal Customer,68,Personal Travel,Eco,526,2,1,2,2,5,2,1,5,5,2,5,2,5,2,1,1.0,neutral or dissatisfied +54460,87066,Male,Loyal Customer,39,Business travel,Business,594,2,5,2,2,2,4,4,5,5,5,5,3,5,4,26,29.0,satisfied +54461,26762,Male,Loyal Customer,21,Personal Travel,Eco,859,2,5,2,4,1,2,1,1,5,5,1,4,4,1,0,5.0,neutral or dissatisfied +54462,10516,Male,Loyal Customer,62,Business travel,Business,1863,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +54463,128008,Male,Loyal Customer,60,Personal Travel,Eco,1488,1,4,1,3,3,1,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +54464,99253,Male,Loyal Customer,42,Business travel,Business,3399,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +54465,47343,Male,Loyal Customer,37,Business travel,Business,574,2,2,2,2,5,4,1,4,4,4,4,1,4,3,7,2.0,satisfied +54466,127451,Male,Loyal Customer,17,Business travel,Business,2075,4,4,4,4,2,2,2,2,5,3,5,3,5,2,0,0.0,satisfied +54467,97445,Female,Loyal Customer,52,Business travel,Business,822,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +54468,56443,Female,Loyal Customer,77,Business travel,Business,319,4,4,1,4,3,4,4,4,4,4,4,1,4,3,0,15.0,neutral or dissatisfied +54469,82040,Female,Loyal Customer,63,Personal Travel,Eco,1522,3,4,3,4,2,5,5,5,5,3,5,4,5,5,37,42.0,neutral or dissatisfied +54470,89981,Female,Loyal Customer,15,Business travel,Business,1857,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +54471,51616,Male,Loyal Customer,66,Business travel,Business,261,4,1,4,4,5,5,4,4,4,4,4,2,4,3,0,0.0,satisfied +54472,7143,Female,Loyal Customer,67,Business travel,Business,3442,5,5,5,5,4,5,5,5,5,5,5,4,5,5,27,15.0,satisfied +54473,80667,Male,disloyal Customer,22,Business travel,Eco,821,3,3,3,4,1,3,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +54474,53121,Male,disloyal Customer,19,Business travel,Eco,2065,3,3,3,4,4,3,4,4,3,2,3,3,4,4,4,11.0,neutral or dissatisfied +54475,28280,Male,Loyal Customer,52,Personal Travel,Eco,2402,3,4,3,3,2,3,4,2,5,3,5,3,5,2,36,17.0,neutral or dissatisfied +54476,81937,Male,Loyal Customer,30,Business travel,Business,1535,5,5,3,5,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +54477,65073,Female,Loyal Customer,13,Personal Travel,Eco,282,1,1,1,3,4,1,4,4,4,1,2,4,3,4,0,0.0,neutral or dissatisfied +54478,71725,Female,Loyal Customer,27,Personal Travel,Eco,1007,4,3,4,5,4,4,3,4,1,4,1,5,5,4,10,10.0,neutral or dissatisfied +54479,74786,Female,Loyal Customer,40,Business travel,Business,1438,3,3,3,3,3,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +54480,95370,Female,Loyal Customer,34,Personal Travel,Eco,248,4,4,4,5,5,4,1,5,5,3,5,3,5,5,2,0.0,neutral or dissatisfied +54481,101501,Male,disloyal Customer,26,Business travel,Business,345,3,2,4,4,1,4,3,1,1,3,4,2,4,1,56,49.0,neutral or dissatisfied +54482,118127,Female,Loyal Customer,52,Business travel,Business,1488,5,5,5,5,2,4,5,4,4,4,4,3,4,4,4,0.0,satisfied +54483,116661,Male,Loyal Customer,27,Business travel,Eco Plus,342,4,2,2,2,4,4,4,4,4,4,4,4,3,4,24,23.0,neutral or dissatisfied +54484,103265,Male,Loyal Customer,38,Business travel,Business,3258,2,3,3,3,5,4,4,2,2,2,2,3,2,4,107,122.0,neutral or dissatisfied +54485,5120,Male,Loyal Customer,47,Business travel,Business,122,0,4,0,3,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +54486,124016,Female,disloyal Customer,35,Business travel,Eco,184,1,0,0,4,4,0,4,4,3,4,2,2,5,4,0,0.0,neutral or dissatisfied +54487,29506,Male,Loyal Customer,14,Personal Travel,Eco,1107,3,5,3,2,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +54488,108207,Male,Loyal Customer,44,Business travel,Business,2612,5,5,5,5,3,4,5,4,4,4,4,3,4,5,29,22.0,satisfied +54489,60317,Female,Loyal Customer,55,Business travel,Business,1024,2,3,3,3,1,2,3,2,2,2,2,1,2,2,10,2.0,neutral or dissatisfied +54490,27296,Male,Loyal Customer,26,Business travel,Business,2093,1,1,3,1,4,4,4,4,2,4,3,4,1,4,0,0.0,satisfied +54491,69922,Male,Loyal Customer,17,Personal Travel,Eco,1514,1,2,1,4,4,1,4,4,4,2,3,3,4,4,39,18.0,neutral or dissatisfied +54492,53493,Male,Loyal Customer,41,Personal Travel,Eco,2288,0,2,0,3,4,0,4,4,3,5,3,1,3,4,0,0.0,satisfied +54493,41503,Male,Loyal Customer,25,Business travel,Business,2655,2,1,1,1,2,2,2,2,3,3,4,4,4,2,0,17.0,neutral or dissatisfied +54494,64692,Male,disloyal Customer,48,Business travel,Business,247,1,1,1,2,4,1,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +54495,97527,Female,Loyal Customer,50,Personal Travel,Eco,439,4,5,4,2,4,5,5,5,5,4,2,4,5,4,0,0.0,satisfied +54496,100371,Female,Loyal Customer,8,Personal Travel,Eco,1011,3,5,4,4,2,4,3,2,4,2,4,5,2,2,3,12.0,neutral or dissatisfied +54497,107343,Male,disloyal Customer,27,Business travel,Eco,584,3,2,3,2,4,3,4,4,1,5,2,1,2,4,10,0.0,neutral or dissatisfied +54498,102720,Male,Loyal Customer,23,Personal Travel,Eco,365,4,4,4,3,2,4,4,2,5,2,4,3,5,2,1,0.0,neutral or dissatisfied +54499,40586,Female,Loyal Customer,47,Business travel,Business,3166,2,2,3,2,4,1,4,5,5,5,5,2,5,2,7,0.0,satisfied +54500,72960,Female,Loyal Customer,39,Business travel,Business,3826,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +54501,24152,Female,disloyal Customer,20,Business travel,Eco,147,3,5,3,5,5,3,2,5,2,2,2,3,5,5,0,0.0,neutral or dissatisfied +54502,33383,Female,Loyal Customer,22,Personal Travel,Eco,2556,4,5,3,4,5,3,5,5,2,4,1,5,5,5,0,0.0,neutral or dissatisfied +54503,17070,Male,disloyal Customer,19,Business travel,Eco,282,2,2,2,3,1,2,1,1,3,1,3,1,3,1,1,0.0,neutral or dissatisfied +54504,99860,Male,Loyal Customer,18,Personal Travel,Eco,534,3,1,3,4,1,3,1,1,4,3,4,2,4,1,6,29.0,neutral or dissatisfied +54505,63360,Female,Loyal Customer,25,Personal Travel,Eco,337,1,4,1,4,4,1,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +54506,18403,Female,Loyal Customer,53,Business travel,Eco,284,5,4,4,4,3,2,2,5,5,5,5,4,5,5,0,0.0,satisfied +54507,59012,Female,Loyal Customer,35,Business travel,Eco,1744,2,3,3,3,2,2,2,2,1,4,4,1,3,2,5,10.0,neutral or dissatisfied +54508,125608,Male,Loyal Customer,42,Business travel,Business,2540,2,2,2,2,3,5,5,4,4,5,4,3,4,5,3,7.0,satisfied +54509,23058,Male,Loyal Customer,57,Business travel,Business,820,2,2,3,2,5,2,1,4,4,4,4,5,4,4,0,0.0,satisfied +54510,82833,Female,disloyal Customer,37,Business travel,Business,594,5,4,4,2,3,4,5,3,4,5,4,5,4,3,124,109.0,satisfied +54511,115686,Male,Loyal Customer,48,Business travel,Business,2392,3,3,3,3,3,3,4,3,3,3,3,2,3,1,14,17.0,neutral or dissatisfied +54512,55172,Female,Loyal Customer,45,Personal Travel,Eco,1379,3,1,3,3,3,2,2,5,5,3,5,1,5,1,0,95.0,neutral or dissatisfied +54513,70156,Male,Loyal Customer,56,Personal Travel,Eco,550,5,4,5,2,4,5,4,4,3,5,5,5,5,4,0,0.0,satisfied +54514,94064,Female,Loyal Customer,60,Business travel,Business,3967,2,5,1,5,1,3,4,2,2,2,2,1,2,3,8,1.0,neutral or dissatisfied +54515,83639,Male,Loyal Customer,22,Business travel,Business,2448,5,5,5,5,3,3,3,3,4,2,4,4,5,3,0,4.0,satisfied +54516,112068,Female,Loyal Customer,29,Business travel,Business,1491,1,1,1,1,5,5,5,5,3,5,4,3,5,5,50,53.0,satisfied +54517,117309,Female,disloyal Customer,36,Business travel,Eco Plus,325,2,2,2,3,4,2,4,4,4,5,3,3,3,4,0,0.0,neutral or dissatisfied +54518,88601,Male,Loyal Customer,43,Personal Travel,Eco,594,2,4,2,4,5,2,3,5,4,2,5,4,4,5,30,26.0,neutral or dissatisfied +54519,74958,Female,Loyal Customer,49,Business travel,Business,975,3,3,3,3,4,4,3,5,5,5,5,2,5,1,0,3.0,satisfied +54520,82692,Female,disloyal Customer,29,Business travel,Business,632,2,2,2,3,1,2,4,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +54521,39064,Male,Loyal Customer,39,Business travel,Business,784,4,4,4,4,4,5,5,3,3,3,3,2,3,3,80,69.0,satisfied +54522,105994,Female,Loyal Customer,46,Business travel,Business,1999,5,4,5,5,3,4,5,5,5,5,5,5,5,4,9,0.0,satisfied +54523,90968,Male,Loyal Customer,49,Business travel,Business,404,4,4,4,4,4,4,2,5,5,5,5,1,5,5,0,0.0,satisfied +54524,115674,Female,Loyal Customer,43,Business travel,Business,2949,1,3,3,3,5,3,3,1,1,1,1,3,1,4,41,31.0,neutral or dissatisfied +54525,53929,Male,Loyal Customer,54,Business travel,Eco Plus,140,3,1,1,1,3,3,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +54526,11185,Female,Loyal Customer,28,Personal Travel,Eco,216,2,4,0,4,2,0,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +54527,20861,Female,Loyal Customer,24,Personal Travel,Eco,534,1,4,1,1,4,1,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +54528,35508,Male,Loyal Customer,41,Personal Travel,Eco,1076,2,1,2,3,1,2,4,1,1,3,2,4,2,1,0,53.0,neutral or dissatisfied +54529,93766,Male,Loyal Customer,18,Personal Travel,Eco,368,2,4,1,4,2,1,2,2,2,1,2,1,1,2,0,0.0,neutral or dissatisfied +54530,119246,Female,Loyal Customer,45,Business travel,Eco Plus,257,1,3,3,3,4,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +54531,16379,Male,Loyal Customer,56,Personal Travel,Eco Plus,1325,1,5,1,1,1,1,3,1,4,5,4,4,5,1,35,66.0,neutral or dissatisfied +54532,85703,Female,Loyal Customer,61,Personal Travel,Eco,1547,2,4,2,4,5,4,5,3,3,2,4,5,3,3,0,0.0,neutral or dissatisfied +54533,84957,Female,Loyal Customer,36,Business travel,Eco Plus,481,2,5,5,5,2,2,2,2,4,1,4,2,3,2,9,9.0,neutral or dissatisfied +54534,43385,Male,Loyal Customer,49,Personal Travel,Eco,402,4,4,4,2,3,4,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +54535,29568,Female,Loyal Customer,42,Business travel,Eco,680,4,2,2,2,4,4,3,4,4,4,4,1,4,2,0,0.0,satisfied +54536,99833,Female,disloyal Customer,37,Business travel,Business,468,4,4,4,4,4,4,1,4,4,5,5,5,4,4,0,0.0,satisfied +54537,23953,Male,Loyal Customer,28,Business travel,Business,2440,3,3,3,3,4,4,4,4,5,1,1,3,2,4,0,0.0,satisfied +54538,33626,Female,Loyal Customer,36,Personal Travel,Eco,399,0,5,0,3,4,0,4,4,3,5,5,3,4,4,0,0.0,satisfied +54539,17832,Female,disloyal Customer,25,Business travel,Eco Plus,1075,4,5,4,3,2,4,2,2,3,3,2,4,5,2,0,0.0,neutral or dissatisfied +54540,65808,Female,Loyal Customer,44,Business travel,Business,1389,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,19.0,satisfied +54541,129399,Female,Loyal Customer,41,Personal Travel,Business,236,2,5,2,3,2,4,3,4,4,2,4,1,4,2,8,0.0,neutral or dissatisfied +54542,70925,Female,disloyal Customer,22,Business travel,Eco,612,2,4,2,2,1,2,1,1,5,2,4,3,4,1,89,78.0,neutral or dissatisfied +54543,15660,Male,disloyal Customer,28,Business travel,Eco,764,4,4,4,3,4,4,4,4,5,3,5,3,4,4,37,68.0,neutral or dissatisfied +54544,13459,Female,Loyal Customer,11,Personal Travel,Eco,409,1,2,1,3,5,1,4,5,2,5,3,2,2,5,0,0.0,neutral or dissatisfied +54545,127199,Male,Loyal Customer,44,Business travel,Business,355,4,4,4,4,4,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +54546,46629,Female,disloyal Customer,43,Business travel,Eco,125,4,2,3,4,3,3,3,3,4,5,3,3,4,3,45,47.0,neutral or dissatisfied +54547,97965,Female,Loyal Customer,49,Personal Travel,Eco,483,3,4,3,1,3,5,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +54548,99091,Male,Loyal Customer,40,Business travel,Business,2644,5,5,5,5,4,4,5,5,5,5,5,4,5,3,44,36.0,satisfied +54549,2742,Male,Loyal Customer,30,Business travel,Business,3179,3,5,5,5,3,3,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +54550,96370,Female,Loyal Customer,40,Business travel,Business,1407,4,4,5,4,5,5,4,4,4,4,4,3,4,4,15,0.0,satisfied +54551,76479,Male,Loyal Customer,39,Business travel,Business,2425,3,3,3,3,2,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +54552,123012,Female,disloyal Customer,20,Business travel,Eco,468,2,0,2,5,2,2,5,2,3,3,4,3,5,2,2,0.0,neutral or dissatisfied +54553,71143,Female,Loyal Customer,44,Business travel,Business,646,2,4,2,2,4,5,5,5,5,5,5,4,5,3,3,0.0,satisfied +54554,122981,Male,disloyal Customer,23,Business travel,Business,590,5,0,5,1,1,5,1,1,3,2,5,3,4,1,37,55.0,satisfied +54555,123266,Female,Loyal Customer,53,Personal Travel,Eco,650,3,3,3,2,2,3,2,3,3,3,3,2,3,4,2,29.0,neutral or dissatisfied +54556,16155,Female,Loyal Customer,31,Business travel,Business,284,0,0,0,1,2,2,2,2,4,5,3,4,1,2,0,0.0,satisfied +54557,90408,Male,disloyal Customer,42,Business travel,Business,404,3,3,3,4,1,3,5,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +54558,32455,Male,Loyal Customer,40,Business travel,Eco,163,5,5,5,5,5,5,5,5,1,2,2,2,1,5,0,0.0,satisfied +54559,84196,Male,Loyal Customer,47,Business travel,Business,3085,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +54560,58321,Female,Loyal Customer,23,Business travel,Eco,1739,1,5,5,5,2,2,1,4,5,4,4,1,1,1,188,169.0,neutral or dissatisfied +54561,86008,Male,Loyal Customer,35,Business travel,Business,447,4,3,3,3,4,4,3,4,4,4,4,1,4,2,0,1.0,neutral or dissatisfied +54562,110795,Female,Loyal Customer,39,Business travel,Business,3200,3,3,3,3,2,3,3,3,3,2,3,1,3,2,69,53.0,neutral or dissatisfied +54563,98806,Female,Loyal Customer,56,Business travel,Business,763,4,4,4,4,5,5,4,4,4,4,4,3,4,3,53,58.0,satisfied +54564,54803,Male,disloyal Customer,23,Business travel,Eco,862,2,1,1,1,4,1,4,4,1,3,3,2,4,4,15,25.0,neutral or dissatisfied +54565,23146,Male,Loyal Customer,31,Business travel,Business,2474,5,5,5,5,4,4,4,4,4,2,2,4,1,4,0,0.0,satisfied +54566,105329,Female,Loyal Customer,39,Business travel,Business,409,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,7.0,satisfied +54567,79268,Male,Loyal Customer,61,Personal Travel,Eco Plus,1598,1,2,1,3,4,1,4,4,2,1,3,2,4,4,32,71.0,neutral or dissatisfied +54568,125674,Male,disloyal Customer,38,Business travel,Eco,759,2,1,1,4,4,1,4,4,3,5,4,3,4,4,6,0.0,neutral or dissatisfied +54569,89929,Female,disloyal Customer,30,Business travel,Eco,947,2,2,2,5,4,2,4,4,5,5,1,1,3,4,0,0.0,neutral or dissatisfied +54570,85486,Male,Loyal Customer,60,Personal Travel,Eco,214,2,0,2,4,2,2,3,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +54571,18763,Male,Loyal Customer,45,Business travel,Business,551,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +54572,12286,Male,Loyal Customer,38,Business travel,Eco,201,3,5,5,5,3,3,3,3,5,5,2,5,1,3,0,0.0,satisfied +54573,66055,Female,disloyal Customer,21,Business travel,Eco,1055,1,1,1,3,2,1,2,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +54574,43494,Male,Loyal Customer,53,Personal Travel,Eco,752,3,5,3,2,4,3,4,4,3,3,4,3,5,4,11,4.0,neutral or dissatisfied +54575,48061,Female,Loyal Customer,44,Business travel,Business,2484,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +54576,123440,Female,Loyal Customer,29,Business travel,Business,2296,2,2,3,2,4,4,4,4,3,2,3,5,4,4,2,72.0,satisfied +54577,53592,Female,Loyal Customer,39,Personal Travel,Eco,599,3,2,3,3,5,3,5,5,4,2,3,4,3,5,5,0.0,neutral or dissatisfied +54578,78945,Male,Loyal Customer,51,Personal Travel,Eco Plus,500,4,4,4,5,2,4,2,2,5,3,4,5,5,2,26,7.0,neutral or dissatisfied +54579,89406,Female,Loyal Customer,36,Business travel,Business,3742,2,3,3,3,2,4,3,3,3,3,2,2,3,2,0,0.0,neutral or dissatisfied +54580,67994,Female,Loyal Customer,27,Personal Travel,Eco Plus,1205,4,5,4,3,4,4,4,4,5,2,4,4,4,4,4,0.0,neutral or dissatisfied +54581,120030,Female,Loyal Customer,45,Business travel,Business,3377,4,4,4,4,2,4,5,4,4,5,4,4,4,4,8,13.0,satisfied +54582,72962,Female,Loyal Customer,43,Business travel,Business,1089,3,3,3,3,2,4,5,4,4,4,4,3,4,3,24,16.0,satisfied +54583,88989,Female,disloyal Customer,34,Personal Travel,Eco,1184,1,5,1,3,4,1,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +54584,125793,Female,Loyal Customer,42,Business travel,Business,3145,1,4,1,1,4,4,5,3,3,3,3,5,3,4,0,50.0,satisfied +54585,16697,Male,Loyal Customer,42,Business travel,Business,1900,1,1,1,1,1,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +54586,42188,Female,Loyal Customer,50,Business travel,Business,2354,4,4,4,4,1,4,2,4,4,4,4,5,4,2,0,0.0,satisfied +54587,19687,Female,disloyal Customer,25,Business travel,Eco,491,4,0,4,3,1,4,1,1,3,5,5,2,5,1,0,0.0,neutral or dissatisfied +54588,115530,Female,Loyal Customer,62,Business travel,Eco,337,4,4,4,4,3,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +54589,18142,Male,Loyal Customer,24,Personal Travel,Eco,750,5,1,5,1,3,5,3,3,3,2,1,3,2,3,0,0.0,satisfied +54590,97992,Female,Loyal Customer,25,Business travel,Business,2139,3,3,1,3,4,5,4,4,3,5,4,5,4,4,13,6.0,satisfied +54591,20617,Female,Loyal Customer,42,Personal Travel,Eco,864,2,5,2,3,4,4,5,4,4,2,4,5,4,5,9,9.0,neutral or dissatisfied +54592,115415,Female,Loyal Customer,25,Business travel,Business,3405,2,5,5,5,2,2,2,2,4,5,3,2,2,2,1,0.0,neutral or dissatisfied +54593,104987,Female,Loyal Customer,47,Business travel,Eco,337,1,4,4,4,1,4,3,1,1,1,1,4,1,2,34,34.0,neutral or dissatisfied +54594,115795,Female,disloyal Customer,23,Business travel,Eco,325,0,0,0,1,2,0,2,2,3,4,5,3,3,2,0,0.0,satisfied +54595,82094,Female,disloyal Customer,21,Business travel,Eco,898,4,4,4,4,1,4,2,1,5,5,5,4,4,1,4,0.0,neutral or dissatisfied +54596,58433,Female,Loyal Customer,40,Personal Travel,Eco,733,4,2,3,3,3,4,4,4,5,3,4,4,4,4,158,155.0,satisfied +54597,70627,Male,Loyal Customer,12,Personal Travel,Eco,1217,2,1,2,2,5,2,3,5,3,2,2,2,3,5,0,0.0,neutral or dissatisfied +54598,30725,Male,Loyal Customer,47,Business travel,Business,3914,2,2,2,2,3,3,5,5,5,5,5,1,5,3,0,0.0,satisfied +54599,68260,Male,Loyal Customer,39,Personal Travel,Eco,631,3,4,3,2,5,3,5,5,4,4,4,4,5,5,8,25.0,neutral or dissatisfied +54600,35620,Female,Loyal Customer,57,Personal Travel,Eco Plus,950,3,3,2,3,1,4,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +54601,118311,Male,Loyal Customer,35,Business travel,Business,2107,2,2,2,2,4,3,4,2,2,2,2,3,2,4,0,5.0,neutral or dissatisfied +54602,120052,Male,Loyal Customer,43,Business travel,Business,237,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +54603,47667,Female,disloyal Customer,25,Business travel,Eco,869,1,1,1,5,4,1,1,4,3,2,3,1,5,4,14,2.0,neutral or dissatisfied +54604,559,Female,Loyal Customer,51,Business travel,Business,3447,0,5,0,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +54605,15192,Female,Loyal Customer,47,Business travel,Business,461,2,5,5,5,1,4,3,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +54606,39766,Female,Loyal Customer,23,Business travel,Business,546,4,4,4,4,4,3,4,4,5,5,1,4,5,4,0,1.0,satisfied +54607,47118,Male,Loyal Customer,27,Personal Travel,Eco,784,4,4,4,3,1,4,1,1,5,3,5,3,4,1,19,8.0,neutral or dissatisfied +54608,439,Female,Loyal Customer,57,Personal Travel,Business,134,4,3,4,2,3,3,5,2,2,4,4,4,2,4,6,7.0,neutral or dissatisfied +54609,19984,Male,Loyal Customer,55,Business travel,Eco,599,2,1,1,1,2,2,2,2,3,5,3,1,1,2,12,2.0,satisfied +54610,83198,Male,disloyal Customer,22,Business travel,Eco,1123,1,1,1,3,1,1,1,1,3,4,4,4,3,1,7,15.0,neutral or dissatisfied +54611,110083,Male,Loyal Customer,45,Business travel,Business,1242,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +54612,3253,Female,Loyal Customer,39,Business travel,Business,479,4,4,4,4,2,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +54613,122346,Female,Loyal Customer,54,Business travel,Business,2584,3,3,3,3,2,5,5,2,2,2,2,4,2,4,14,0.0,satisfied +54614,127613,Male,Loyal Customer,39,Business travel,Business,1773,1,4,4,4,4,2,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +54615,31940,Male,Loyal Customer,32,Business travel,Business,2265,4,4,4,4,4,4,4,4,4,2,5,4,4,4,0,6.0,satisfied +54616,1464,Female,Loyal Customer,19,Personal Travel,Eco,772,4,1,4,3,3,4,3,3,2,1,3,3,2,3,0,0.0,satisfied +54617,41628,Female,Loyal Customer,40,Business travel,Eco,438,5,3,3,3,5,5,5,5,3,4,5,2,2,5,0,0.0,satisfied +54618,8498,Male,Loyal Customer,59,Personal Travel,Business,862,4,5,4,4,5,4,5,3,3,4,2,4,3,5,0,0.0,neutral or dissatisfied +54619,115886,Female,Loyal Customer,43,Business travel,Business,3565,3,3,3,3,2,5,1,3,3,3,3,4,3,1,109,102.0,satisfied +54620,98607,Male,Loyal Customer,48,Business travel,Business,994,2,2,2,2,4,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +54621,23214,Female,Loyal Customer,46,Business travel,Business,2100,1,1,1,1,4,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +54622,47085,Male,Loyal Customer,31,Personal Travel,Eco,639,2,3,2,3,5,2,5,5,1,1,3,3,4,5,16,44.0,neutral or dissatisfied +54623,82663,Male,Loyal Customer,61,Personal Travel,Eco,120,0,5,0,3,3,0,3,3,5,2,3,5,3,3,0,0.0,satisfied +54624,44073,Male,Loyal Customer,45,Business travel,Business,651,5,5,5,5,4,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +54625,85283,Female,Loyal Customer,37,Personal Travel,Eco,813,5,0,5,4,4,5,4,4,3,5,4,5,4,4,8,5.0,satisfied +54626,33372,Female,Loyal Customer,13,Personal Travel,Eco,2409,1,1,0,4,4,0,4,4,2,2,3,4,3,4,0,0.0,neutral or dissatisfied +54627,68620,Female,Loyal Customer,48,Business travel,Business,3524,3,3,3,3,2,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +54628,2525,Female,Loyal Customer,46,Business travel,Business,280,3,3,1,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +54629,70195,Male,Loyal Customer,32,Business travel,Business,258,3,2,2,2,3,3,3,3,1,3,4,1,3,3,0,3.0,neutral or dissatisfied +54630,46930,Male,disloyal Customer,22,Business travel,Eco,337,5,0,5,1,5,5,5,5,1,3,3,2,1,5,0,0.0,satisfied +54631,709,Female,Loyal Customer,50,Business travel,Business,2390,4,4,4,4,4,4,5,5,5,5,4,3,5,5,0,5.0,satisfied +54632,73414,Female,disloyal Customer,22,Business travel,Business,1005,4,1,4,4,5,4,5,5,2,4,3,4,4,5,0,0.0,neutral or dissatisfied +54633,83670,Male,Loyal Customer,45,Business travel,Eco,577,3,3,3,3,3,3,3,3,2,1,2,1,3,3,0,5.0,neutral or dissatisfied +54634,3785,Female,Loyal Customer,60,Business travel,Business,3687,3,3,1,3,3,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +54635,24902,Female,Loyal Customer,21,Personal Travel,Business,762,4,4,4,3,4,4,4,4,5,1,1,2,2,4,16,22.0,neutral or dissatisfied +54636,91177,Male,Loyal Customer,15,Personal Travel,Eco,270,4,5,4,2,5,4,5,5,4,2,1,4,1,5,86,80.0,neutral or dissatisfied +54637,41818,Female,Loyal Customer,26,Personal Travel,Eco,257,3,4,0,3,5,0,5,5,1,1,3,4,4,5,11,4.0,neutral or dissatisfied +54638,60065,Male,disloyal Customer,24,Business travel,Business,1182,4,0,4,1,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +54639,41064,Male,Loyal Customer,58,Business travel,Business,2637,1,1,1,1,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +54640,77773,Female,Loyal Customer,52,Personal Travel,Eco,731,2,4,2,3,2,4,3,4,4,2,4,5,4,4,8,4.0,neutral or dissatisfied +54641,107990,Female,disloyal Customer,59,Business travel,Eco,271,3,1,3,3,1,3,1,1,1,4,3,3,2,1,59,52.0,neutral or dissatisfied +54642,121867,Female,Loyal Customer,55,Business travel,Business,1823,4,4,4,4,4,3,4,4,4,3,4,1,4,4,5,0.0,neutral or dissatisfied +54643,98973,Female,Loyal Customer,23,Personal Travel,Eco,569,4,4,4,2,4,4,1,4,3,5,4,5,5,4,67,63.0,satisfied +54644,12207,Male,Loyal Customer,40,Business travel,Business,201,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +54645,101235,Male,Loyal Customer,50,Business travel,Business,1587,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +54646,63507,Male,Loyal Customer,38,Business travel,Business,1009,1,1,2,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +54647,89358,Female,Loyal Customer,11,Personal Travel,Eco,1587,3,5,3,2,2,3,2,2,3,5,4,4,5,2,15,6.0,neutral or dissatisfied +54648,34910,Male,Loyal Customer,56,Business travel,Eco,187,2,5,5,5,2,2,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +54649,60209,Male,Loyal Customer,46,Business travel,Business,1703,1,1,1,1,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +54650,111484,Male,Loyal Customer,51,Personal Travel,Eco,1452,1,5,1,2,3,1,3,3,4,4,5,3,5,3,23,6.0,neutral or dissatisfied +54651,6742,Male,Loyal Customer,42,Business travel,Business,122,1,1,1,1,3,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +54652,76798,Male,Loyal Customer,48,Personal Travel,Eco,689,3,5,3,2,3,3,5,3,3,1,5,5,5,3,13,13.0,neutral or dissatisfied +54653,53130,Female,disloyal Customer,27,Business travel,Eco Plus,2065,2,2,2,1,1,2,1,1,4,4,5,3,1,1,0,1.0,neutral or dissatisfied +54654,80507,Male,Loyal Customer,45,Business travel,Eco,1749,4,2,2,2,4,4,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +54655,83049,Male,Loyal Customer,27,Business travel,Business,1890,3,3,3,3,3,3,3,3,3,1,4,4,3,3,0,0.0,neutral or dissatisfied +54656,83132,Male,Loyal Customer,48,Personal Travel,Eco,1127,1,4,1,5,1,1,1,1,4,2,5,3,5,1,32,33.0,neutral or dissatisfied +54657,71331,Male,Loyal Customer,50,Business travel,Business,1514,1,4,4,4,1,2,2,1,1,1,1,3,1,3,0,11.0,neutral or dissatisfied +54658,49761,Female,Loyal Customer,43,Business travel,Business,308,2,2,2,2,4,3,2,5,5,4,5,4,5,4,0,0.0,satisfied +54659,92614,Male,disloyal Customer,69,Business travel,Business,453,3,3,3,1,2,3,2,2,4,3,5,4,4,2,0,5.0,neutral or dissatisfied +54660,116127,Female,Loyal Customer,63,Personal Travel,Eco,308,2,3,2,4,5,5,4,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +54661,58043,Male,disloyal Customer,17,Business travel,Eco,589,1,3,1,4,3,1,1,3,3,3,4,1,4,3,10,7.0,neutral or dissatisfied +54662,81116,Female,Loyal Customer,34,Business travel,Business,2129,3,3,3,3,4,2,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +54663,117912,Male,Loyal Customer,39,Business travel,Business,255,1,1,1,1,5,4,5,5,5,5,5,3,5,5,93,85.0,satisfied +54664,117021,Female,Loyal Customer,40,Business travel,Business,3434,3,2,2,2,5,3,3,3,3,3,3,4,3,4,23,18.0,neutral or dissatisfied +54665,83422,Female,Loyal Customer,62,Personal Travel,Eco,632,3,5,3,2,4,4,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +54666,121195,Female,Loyal Customer,16,Personal Travel,Eco,2402,1,4,1,2,1,3,5,3,5,4,4,5,3,5,2,3.0,neutral or dissatisfied +54667,36381,Female,disloyal Customer,23,Business travel,Eco,200,2,3,2,4,2,1,1,2,1,3,3,1,2,1,287,274.0,neutral or dissatisfied +54668,100912,Male,Loyal Customer,44,Personal Travel,Eco,377,3,4,3,2,5,3,5,5,4,2,4,5,5,5,0,4.0,neutral or dissatisfied +54669,14630,Male,Loyal Customer,22,Personal Travel,Eco,541,4,5,4,4,2,4,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +54670,39621,Male,Loyal Customer,57,Personal Travel,Eco,908,2,5,2,3,4,2,4,4,4,5,1,1,3,4,0,0.0,neutral or dissatisfied +54671,112908,Male,Loyal Customer,60,Business travel,Eco,715,1,4,4,4,1,1,1,1,2,3,3,2,4,1,13,6.0,neutral or dissatisfied +54672,125497,Female,Loyal Customer,34,Business travel,Business,666,3,3,3,3,4,4,5,4,4,4,4,4,4,4,23,0.0,satisfied +54673,56696,Female,Loyal Customer,20,Personal Travel,Eco,1085,1,4,1,1,4,1,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +54674,17510,Male,Loyal Customer,41,Business travel,Business,2288,1,1,1,1,5,4,1,4,4,4,4,5,4,1,0,0.0,satisfied +54675,126564,Female,Loyal Customer,40,Business travel,Business,1558,1,1,4,1,4,4,4,4,4,4,4,5,4,3,30,15.0,satisfied +54676,60113,Male,Loyal Customer,60,Business travel,Business,1120,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +54677,83218,Female,Loyal Customer,56,Business travel,Business,2079,3,4,4,4,3,3,3,3,3,3,3,4,3,4,46,83.0,neutral or dissatisfied +54678,42282,Female,Loyal Customer,30,Business travel,Business,329,2,1,1,1,2,2,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +54679,116096,Female,Loyal Customer,61,Personal Travel,Eco,362,2,3,2,4,2,4,4,5,5,2,5,4,5,1,0,3.0,neutral or dissatisfied +54680,8959,Male,Loyal Customer,32,Business travel,Business,812,4,4,4,4,4,4,4,4,4,2,4,4,4,4,0,75.0,satisfied +54681,118509,Male,disloyal Customer,23,Business travel,Business,368,5,0,5,3,2,5,2,2,4,5,4,5,5,2,15,7.0,satisfied +54682,19226,Female,Loyal Customer,32,Personal Travel,Eco,459,3,4,3,3,3,5,5,3,5,4,4,5,3,5,364,381.0,neutral or dissatisfied +54683,10896,Female,Loyal Customer,28,Business travel,Business,667,2,3,2,2,2,1,2,2,4,2,3,3,2,2,0,0.0,neutral or dissatisfied +54684,32421,Female,Loyal Customer,44,Business travel,Business,3874,3,3,3,3,3,4,3,5,5,5,5,5,5,2,0,0.0,satisfied +54685,44309,Female,Loyal Customer,14,Personal Travel,Business,305,2,4,2,2,4,2,4,4,5,5,5,5,4,4,12,2.0,neutral or dissatisfied +54686,34644,Male,Loyal Customer,17,Personal Travel,Eco,541,4,5,4,1,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +54687,111533,Male,Loyal Customer,60,Business travel,Business,2106,5,5,5,5,4,5,4,4,4,5,4,5,4,5,5,0.0,satisfied +54688,16314,Male,Loyal Customer,41,Business travel,Business,2827,3,3,3,3,3,1,5,5,5,5,5,4,5,2,0,0.0,satisfied +54689,70454,Female,Loyal Customer,59,Business travel,Business,2071,4,1,4,4,2,4,5,4,4,4,4,3,4,5,46,64.0,satisfied +54690,251,Male,disloyal Customer,66,Personal Travel,Eco,719,3,2,3,2,3,2,2,3,3,2,3,2,1,2,193,205.0,neutral or dissatisfied +54691,110909,Male,Loyal Customer,30,Business travel,Business,581,2,3,3,3,2,2,2,2,4,1,3,2,4,2,0,0.0,neutral or dissatisfied +54692,47396,Female,disloyal Customer,62,Business travel,Eco,588,1,0,1,3,5,1,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +54693,123504,Female,disloyal Customer,33,Business travel,Eco,860,3,3,3,3,2,3,2,2,3,4,3,1,3,2,48,38.0,neutral or dissatisfied +54694,68828,Male,Loyal Customer,22,Business travel,Business,1995,3,3,1,3,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +54695,125622,Female,Loyal Customer,33,Business travel,Business,2399,1,1,3,1,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +54696,112452,Female,disloyal Customer,25,Business travel,Eco,957,2,2,2,3,2,2,2,2,3,1,4,3,3,2,58,71.0,neutral or dissatisfied +54697,72098,Female,Loyal Customer,19,Personal Travel,Eco,2486,0,4,0,3,2,0,2,2,3,3,4,1,4,2,19,0.0,satisfied +54698,85232,Female,Loyal Customer,52,Business travel,Business,3316,4,2,2,2,4,3,4,4,4,4,4,1,4,1,8,0.0,neutral or dissatisfied +54699,98660,Male,Loyal Customer,18,Personal Travel,Eco,952,4,2,3,3,1,3,1,1,3,4,3,2,4,1,0,0.0,satisfied +54700,14016,Male,Loyal Customer,63,Business travel,Eco,182,5,5,5,5,5,5,5,5,4,2,3,3,4,5,7,2.0,satisfied +54701,59417,Female,Loyal Customer,66,Personal Travel,Eco,2556,2,1,2,4,5,3,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +54702,87535,Male,Loyal Customer,10,Personal Travel,Eco Plus,373,1,4,2,1,2,2,2,2,5,4,5,4,4,2,90,99.0,neutral or dissatisfied +54703,64738,Female,Loyal Customer,50,Business travel,Eco,551,3,4,4,4,2,3,3,3,3,3,3,3,3,3,12,6.0,neutral or dissatisfied +54704,11038,Female,Loyal Customer,29,Personal Travel,Eco,201,1,5,1,3,5,1,5,5,4,3,3,4,4,5,0,8.0,neutral or dissatisfied +54705,17268,Female,Loyal Customer,50,Personal Travel,Eco,872,3,3,4,3,1,2,4,3,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +54706,57398,Male,Loyal Customer,48,Business travel,Business,472,3,3,3,3,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +54707,124803,Female,Loyal Customer,37,Business travel,Business,3738,2,4,4,4,4,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +54708,91441,Male,Loyal Customer,25,Business travel,Business,859,2,4,2,2,4,4,4,4,4,2,4,5,4,4,7,16.0,satisfied +54709,104773,Male,Loyal Customer,48,Business travel,Business,2207,4,4,4,4,3,5,5,4,4,5,4,4,4,4,7,1.0,satisfied +54710,2088,Male,Loyal Customer,13,Personal Travel,Eco,733,3,2,3,3,3,3,3,3,3,5,2,4,4,3,0,31.0,neutral or dissatisfied +54711,92531,Female,Loyal Customer,52,Personal Travel,Eco,1947,4,1,4,4,1,4,4,2,2,4,4,1,2,1,15,0.0,neutral or dissatisfied +54712,3309,Male,Loyal Customer,58,Business travel,Business,2513,0,0,0,4,3,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +54713,20733,Female,Loyal Customer,43,Business travel,Eco Plus,707,5,1,1,1,1,4,3,5,5,5,5,5,5,3,5,0.0,satisfied +54714,81712,Female,disloyal Customer,18,Business travel,Business,907,5,5,4,3,5,4,3,5,4,4,4,3,5,5,8,3.0,satisfied +54715,32411,Male,Loyal Customer,48,Business travel,Business,163,0,4,0,3,1,3,5,5,5,5,5,1,5,3,0,0.0,satisfied +54716,24579,Male,Loyal Customer,27,Personal Travel,Eco Plus,696,3,1,3,4,5,3,5,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +54717,125589,Male,disloyal Customer,24,Business travel,Eco,1006,2,2,2,4,4,2,4,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +54718,32295,Male,Loyal Customer,56,Business travel,Business,3454,5,5,5,5,1,1,3,5,5,5,5,4,5,5,0,0.0,satisfied +54719,74868,Female,Loyal Customer,43,Business travel,Business,2239,5,5,5,5,5,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +54720,826,Male,Loyal Customer,47,Business travel,Business,2880,2,5,5,5,3,1,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +54721,57187,Female,disloyal Customer,55,Business travel,Eco Plus,2227,3,3,3,2,4,3,4,4,2,5,3,4,3,4,14,0.0,neutral or dissatisfied +54722,123867,Male,Loyal Customer,14,Business travel,Business,2909,3,1,1,1,3,3,3,3,1,3,3,4,4,3,0,9.0,neutral or dissatisfied +54723,11106,Male,Loyal Customer,10,Personal Travel,Eco,166,2,4,2,1,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +54724,117868,Male,Loyal Customer,58,Business travel,Business,1556,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +54725,75957,Female,Loyal Customer,55,Business travel,Business,297,2,5,2,2,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +54726,105034,Male,Loyal Customer,54,Business travel,Eco,361,5,2,2,2,5,5,5,5,3,2,4,4,3,5,9,0.0,satisfied +54727,94313,Female,Loyal Customer,58,Business travel,Business,239,5,5,5,5,3,5,5,4,4,4,4,4,4,5,4,0.0,satisfied +54728,14005,Female,Loyal Customer,42,Business travel,Business,615,5,5,5,5,2,1,3,5,5,5,5,5,5,5,6,0.0,satisfied +54729,65306,Female,disloyal Customer,42,Business travel,Eco Plus,354,3,2,2,3,3,1,1,1,1,4,4,1,4,1,136,138.0,neutral or dissatisfied +54730,37010,Female,Loyal Customer,8,Personal Travel,Eco,759,5,5,5,1,1,5,1,1,2,1,4,3,5,1,0,0.0,satisfied +54731,46114,Female,disloyal Customer,20,Business travel,Eco Plus,801,2,4,2,3,4,2,4,4,4,2,3,2,4,4,48,71.0,neutral or dissatisfied +54732,46343,Female,Loyal Customer,20,Business travel,Business,692,4,5,5,5,4,4,4,4,4,5,4,2,4,4,15,15.0,neutral or dissatisfied +54733,25958,Female,Loyal Customer,46,Business travel,Eco,946,4,1,1,1,2,5,3,4,4,4,4,4,4,3,92,68.0,satisfied +54734,17429,Female,Loyal Customer,55,Business travel,Business,3912,0,1,1,1,5,1,4,5,5,5,5,5,5,1,9,0.0,satisfied +54735,28506,Male,Loyal Customer,35,Business travel,Business,2715,1,1,1,1,4,4,4,2,3,4,5,4,2,4,7,3.0,satisfied +54736,119384,Male,Loyal Customer,39,Business travel,Business,399,2,2,2,2,4,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +54737,5111,Male,disloyal Customer,68,Personal Travel,Eco,235,4,4,4,4,2,4,2,2,2,4,4,2,4,2,0,4.0,satisfied +54738,107850,Male,Loyal Customer,41,Business travel,Business,2472,0,0,0,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +54739,11842,Female,Loyal Customer,41,Business travel,Business,1091,3,3,1,3,3,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +54740,45966,Male,Loyal Customer,50,Business travel,Business,2293,1,1,1,1,2,2,1,3,3,3,3,4,3,4,5,31.0,satisfied +54741,29879,Male,Loyal Customer,39,Business travel,Business,571,4,4,3,4,1,1,5,4,4,4,4,2,4,4,0,0.0,satisfied +54742,72317,Male,Loyal Customer,67,Personal Travel,Eco Plus,919,1,2,1,3,3,1,4,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +54743,59507,Female,Loyal Customer,32,Business travel,Business,965,1,1,1,1,4,4,4,4,5,3,5,4,5,4,12,6.0,satisfied +54744,72040,Male,Loyal Customer,34,Business travel,Business,4243,4,4,4,4,5,5,5,5,5,4,5,5,4,5,0,4.0,satisfied +54745,5586,Female,Loyal Customer,43,Business travel,Business,685,3,3,3,3,2,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +54746,22520,Female,Loyal Customer,30,Business travel,Eco Plus,83,2,1,5,1,2,2,2,2,4,3,3,4,2,2,0,6.0,neutral or dissatisfied +54747,29808,Female,disloyal Customer,19,Business travel,Eco,571,0,0,0,4,2,0,1,2,4,2,5,5,1,2,0,0.0,satisfied +54748,62459,Male,disloyal Customer,55,Business travel,Business,1723,3,3,3,3,4,3,1,4,1,1,2,3,3,4,0,0.0,neutral or dissatisfied +54749,101597,Male,Loyal Customer,31,Business travel,Business,1139,2,2,2,2,4,5,4,4,4,3,4,5,4,4,19,8.0,satisfied +54750,11402,Male,disloyal Customer,23,Business travel,Eco,140,4,5,4,2,5,4,5,5,4,3,5,3,5,5,0,0.0,satisfied +54751,45639,Male,Loyal Customer,33,Personal Travel,Eco,260,2,2,2,2,2,2,2,2,2,4,3,1,2,2,0,0.0,neutral or dissatisfied +54752,88685,Female,Loyal Customer,42,Personal Travel,Eco,270,4,0,2,3,5,5,4,3,3,2,4,5,3,5,6,1.0,satisfied +54753,9430,Female,Loyal Customer,56,Business travel,Business,2440,2,2,2,2,4,5,5,5,5,5,5,5,5,5,39,29.0,satisfied +54754,5654,Female,Loyal Customer,53,Business travel,Business,436,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +54755,56204,Female,Loyal Customer,32,Business travel,Eco Plus,1400,4,4,4,4,4,4,4,4,1,4,4,1,4,4,43,38.0,neutral or dissatisfied +54756,96622,Male,Loyal Customer,34,Business travel,Business,2699,2,3,3,3,2,3,3,2,2,2,2,3,2,4,24,21.0,neutral or dissatisfied +54757,127145,Male,Loyal Customer,32,Personal Travel,Eco,370,1,4,1,4,2,1,2,2,2,3,4,4,3,2,72,66.0,neutral or dissatisfied +54758,120689,Female,Loyal Customer,29,Personal Travel,Eco,280,3,5,3,5,1,3,5,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +54759,17898,Female,Loyal Customer,63,Personal Travel,Eco Plus,371,4,4,4,3,1,3,4,3,3,4,3,3,3,1,0,0.0,neutral or dissatisfied +54760,62467,Female,Loyal Customer,39,Business travel,Business,1726,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +54761,30742,Female,Loyal Customer,21,Personal Travel,Eco,692,3,4,3,4,3,3,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +54762,20114,Female,disloyal Customer,38,Business travel,Eco,416,4,4,4,4,1,4,1,1,3,1,3,3,3,1,12,14.0,neutral or dissatisfied +54763,124129,Male,Loyal Customer,38,Personal Travel,Eco,529,4,4,4,2,4,4,4,4,3,4,5,4,4,4,2,3.0,satisfied +54764,13122,Male,Loyal Customer,40,Business travel,Eco,595,4,4,4,4,4,4,4,4,4,3,3,4,2,4,0,0.0,satisfied +54765,8854,Male,disloyal Customer,39,Business travel,Business,539,3,3,3,4,3,3,3,3,5,2,4,4,5,3,9,0.0,neutral or dissatisfied +54766,68354,Male,Loyal Customer,49,Business travel,Business,1598,2,5,5,5,5,2,4,2,2,2,2,4,2,2,52,27.0,neutral or dissatisfied +54767,119799,Female,Loyal Customer,54,Business travel,Business,936,5,5,5,5,5,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +54768,66488,Male,Loyal Customer,29,Business travel,Business,3065,3,3,3,3,3,3,3,3,3,4,4,3,5,3,0,0.0,satisfied +54769,99692,Male,disloyal Customer,18,Business travel,Eco,442,2,1,1,4,2,1,2,2,3,3,3,2,4,2,8,25.0,neutral or dissatisfied +54770,126030,Female,Loyal Customer,60,Business travel,Business,3585,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +54771,52322,Male,Loyal Customer,49,Business travel,Business,370,5,4,4,4,1,3,3,5,5,4,5,2,5,4,10,13.0,neutral or dissatisfied +54772,28751,Female,Loyal Customer,31,Business travel,Business,3466,3,3,3,3,4,4,4,4,1,5,1,1,5,4,0,9.0,satisfied +54773,50834,Female,Loyal Customer,60,Personal Travel,Eco,109,1,4,1,1,4,1,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +54774,15259,Male,Loyal Customer,41,Business travel,Eco Plus,416,5,1,1,1,5,5,5,5,4,2,5,1,4,5,0,0.0,satisfied +54775,54134,Female,disloyal Customer,23,Business travel,Eco,1400,2,2,2,3,4,2,4,4,2,4,3,4,3,4,12,12.0,neutral or dissatisfied +54776,118596,Male,Loyal Customer,51,Business travel,Business,2393,2,3,3,3,5,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +54777,21145,Male,Loyal Customer,26,Personal Travel,Eco Plus,106,2,4,2,1,2,2,3,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +54778,17126,Female,Loyal Customer,40,Business travel,Business,1817,1,1,2,1,4,5,5,4,4,4,4,2,4,5,68,68.0,satisfied +54779,76638,Male,Loyal Customer,53,Business travel,Eco,147,3,5,5,5,3,3,3,3,3,2,3,1,4,3,0,8.0,neutral or dissatisfied +54780,46501,Female,Loyal Customer,35,Business travel,Eco,125,5,2,2,2,5,5,5,5,5,4,3,1,5,5,45,71.0,satisfied +54781,33395,Female,Loyal Customer,31,Business travel,Business,2917,3,1,3,3,3,2,3,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +54782,22697,Male,Loyal Customer,46,Business travel,Eco,589,2,5,5,5,2,2,2,2,2,2,3,1,3,2,42,21.0,neutral or dissatisfied +54783,108274,Male,Loyal Customer,14,Personal Travel,Eco,895,2,4,2,3,1,2,1,1,2,2,2,1,4,1,9,0.0,neutral or dissatisfied +54784,75728,Female,Loyal Customer,33,Business travel,Business,1734,1,1,2,1,4,5,5,5,5,5,5,5,5,3,14,2.0,satisfied +54785,110971,Male,Loyal Customer,52,Business travel,Business,1846,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +54786,96881,Male,Loyal Customer,8,Personal Travel,Eco,781,3,5,3,3,5,3,3,5,1,1,2,1,1,5,0,0.0,neutral or dissatisfied +54787,125294,Male,Loyal Customer,46,Business travel,Business,4000,2,2,2,2,3,5,5,1,1,2,1,4,1,5,0,0.0,satisfied +54788,58929,Female,Loyal Customer,48,Personal Travel,Eco,888,1,5,1,3,2,4,2,3,3,1,3,3,3,2,27,9.0,neutral or dissatisfied +54789,47226,Female,disloyal Customer,28,Business travel,Eco Plus,908,1,1,1,1,4,1,1,4,1,3,5,5,4,4,0,0.0,neutral or dissatisfied +54790,33605,Female,Loyal Customer,39,Business travel,Business,399,3,3,3,3,5,1,3,4,4,5,4,3,4,3,0,0.0,satisfied +54791,52346,Male,Loyal Customer,42,Business travel,Eco,370,2,4,1,4,2,2,2,2,1,5,4,4,4,2,3,0.0,neutral or dissatisfied +54792,107902,Male,disloyal Customer,22,Business travel,Eco,861,4,5,5,3,4,5,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +54793,32434,Male,disloyal Customer,27,Business travel,Eco,121,2,4,1,3,5,1,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +54794,104807,Female,Loyal Customer,19,Personal Travel,Eco,587,4,5,4,3,5,4,1,5,5,5,4,4,5,5,16,8.0,neutral or dissatisfied +54795,13383,Male,Loyal Customer,57,Business travel,Eco,700,4,3,3,3,4,4,4,4,3,1,4,5,1,4,0,7.0,satisfied +54796,29789,Male,Loyal Customer,57,Business travel,Eco,261,4,3,3,3,4,4,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +54797,38766,Female,Loyal Customer,29,Business travel,Business,1713,1,1,1,1,5,5,5,5,2,5,5,5,5,5,4,8.0,satisfied +54798,34268,Female,disloyal Customer,20,Business travel,Eco,280,0,5,0,2,4,0,4,4,2,5,5,4,4,4,0,0.0,satisfied +54799,109350,Female,Loyal Customer,56,Business travel,Business,3883,5,5,5,5,4,5,5,4,4,5,4,4,4,3,25,8.0,satisfied +54800,87953,Male,Loyal Customer,27,Personal Travel,Business,646,2,1,2,2,4,2,5,4,2,3,1,2,2,4,0,0.0,neutral or dissatisfied +54801,5665,Female,Loyal Customer,45,Business travel,Business,2206,0,4,0,3,5,5,4,3,3,3,3,3,3,4,3,7.0,satisfied +54802,93844,Male,Loyal Customer,38,Personal Travel,Eco,391,2,4,2,3,5,2,5,5,4,3,5,3,5,5,45,41.0,neutral or dissatisfied +54803,115770,Male,Loyal Customer,42,Business travel,Eco,371,3,2,2,2,3,3,3,3,3,2,2,1,2,3,0,0.0,neutral or dissatisfied +54804,89277,Male,Loyal Customer,50,Business travel,Business,2027,5,5,5,5,2,4,4,5,5,5,5,3,5,4,1,6.0,satisfied +54805,3545,Male,Loyal Customer,42,Business travel,Business,3548,1,1,1,1,3,4,4,5,5,4,5,4,5,5,23,20.0,satisfied +54806,113847,Male,disloyal Customer,28,Business travel,Business,1363,0,0,0,3,5,0,5,5,5,2,4,3,5,5,6,0.0,satisfied +54807,24571,Male,Loyal Customer,24,Personal Travel,Eco,696,2,5,2,3,1,2,1,1,3,4,4,4,4,1,1,0.0,neutral or dissatisfied +54808,89772,Male,Loyal Customer,7,Personal Travel,Eco,944,3,3,3,3,3,5,5,1,2,2,5,5,1,5,230,227.0,neutral or dissatisfied +54809,76957,Male,Loyal Customer,31,Business travel,Business,1990,3,3,4,3,3,3,3,3,1,4,2,4,3,3,4,13.0,neutral or dissatisfied +54810,4439,Female,Loyal Customer,13,Personal Travel,Eco,762,2,5,2,1,1,2,1,1,4,4,5,4,4,1,7,5.0,neutral or dissatisfied +54811,114487,Female,Loyal Customer,51,Business travel,Business,3105,2,4,4,4,2,2,2,1,4,3,4,2,1,2,274,264.0,neutral or dissatisfied +54812,119537,Female,Loyal Customer,52,Personal Travel,Eco,814,4,4,4,3,2,5,5,2,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +54813,115992,Female,Loyal Customer,15,Personal Travel,Eco,325,0,4,0,3,2,0,2,2,2,4,1,3,3,2,11,3.0,satisfied +54814,68799,Male,Loyal Customer,52,Personal Travel,Eco,926,3,4,3,4,3,3,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +54815,71306,Female,Loyal Customer,45,Business travel,Business,1514,4,4,4,4,3,5,4,5,5,5,5,5,5,3,5,4.0,satisfied +54816,92600,Male,Loyal Customer,35,Business travel,Business,2218,2,5,5,5,1,1,2,2,2,2,2,4,2,4,0,8.0,neutral or dissatisfied +54817,122546,Female,Loyal Customer,28,Business travel,Eco,500,2,1,1,1,2,2,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +54818,69880,Female,Loyal Customer,55,Business travel,Business,2248,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +54819,62935,Female,Loyal Customer,59,Business travel,Business,1721,3,3,3,3,4,4,4,3,3,3,3,3,3,5,13,0.0,satisfied +54820,63241,Female,Loyal Customer,56,Business travel,Business,337,2,2,2,2,2,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +54821,25263,Male,disloyal Customer,44,Business travel,Eco,425,2,5,2,3,2,2,2,2,3,5,3,1,2,2,0,0.0,neutral or dissatisfied +54822,75173,Male,Loyal Customer,48,Business travel,Business,1652,1,4,4,4,5,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +54823,67784,Male,Loyal Customer,29,Business travel,Eco,1235,2,2,2,2,2,2,2,2,2,4,4,4,3,2,8,0.0,neutral or dissatisfied +54824,56399,Female,disloyal Customer,24,Business travel,Business,719,5,0,5,3,4,5,4,4,4,4,4,4,5,4,0,0.0,satisfied +54825,94847,Male,disloyal Customer,48,Business travel,Eco,248,3,4,3,3,5,3,5,5,3,1,3,1,4,5,38,37.0,neutral or dissatisfied +54826,99702,Female,Loyal Customer,27,Business travel,Business,2026,5,5,5,5,4,4,4,4,3,2,4,4,5,4,0,6.0,satisfied +54827,22675,Female,Loyal Customer,38,Business travel,Eco,589,3,1,1,1,3,3,3,3,1,1,2,2,1,3,66,53.0,neutral or dissatisfied +54828,97615,Female,Loyal Customer,38,Business travel,Business,764,1,1,1,1,2,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +54829,128663,Male,disloyal Customer,38,Business travel,Business,2442,3,3,3,1,3,5,5,4,2,5,5,5,4,5,0,7.0,neutral or dissatisfied +54830,111495,Male,Loyal Customer,41,Business travel,Business,2826,1,1,5,1,5,5,4,5,5,5,5,4,5,4,69,59.0,satisfied +54831,105213,Male,Loyal Customer,40,Business travel,Business,3341,1,1,1,1,3,4,4,5,5,5,5,5,5,4,31,16.0,satisfied +54832,93282,Male,Loyal Customer,20,Personal Travel,Eco,867,5,4,5,1,3,5,3,3,4,5,5,3,5,3,31,23.0,satisfied +54833,43063,Female,disloyal Customer,54,Business travel,Eco,259,2,4,2,4,3,2,4,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +54834,3810,Male,disloyal Customer,22,Business travel,Eco,650,5,0,5,2,2,5,4,2,5,3,5,3,4,2,39,36.0,satisfied +54835,38316,Male,Loyal Customer,43,Business travel,Business,1666,4,4,4,4,4,3,4,5,5,5,5,5,5,5,0,1.0,satisfied +54836,124905,Female,disloyal Customer,8,Business travel,Eco,728,1,1,1,3,3,1,3,3,4,5,3,1,4,3,11,9.0,neutral or dissatisfied +54837,113420,Female,Loyal Customer,38,Business travel,Eco,397,2,3,4,3,2,2,2,2,4,2,4,2,4,2,18,24.0,neutral or dissatisfied +54838,112831,Female,Loyal Customer,59,Business travel,Business,1476,5,5,5,5,4,5,5,5,5,5,5,4,5,5,8,0.0,satisfied +54839,85270,Male,Loyal Customer,62,Personal Travel,Eco,731,3,3,3,2,2,3,2,2,4,5,4,1,3,2,1,0.0,neutral or dissatisfied +54840,87483,Female,Loyal Customer,55,Business travel,Business,321,2,4,4,4,1,2,3,2,2,2,2,2,2,3,34,24.0,neutral or dissatisfied +54841,9903,Male,Loyal Customer,51,Business travel,Business,515,2,5,5,5,3,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +54842,122402,Male,Loyal Customer,28,Business travel,Eco Plus,529,2,5,5,5,2,2,2,2,2,2,4,4,3,2,37,26.0,neutral or dissatisfied +54843,20051,Female,Loyal Customer,49,Business travel,Business,473,2,2,2,2,1,2,1,4,4,4,4,3,4,2,0,0.0,satisfied +54844,45366,Female,Loyal Customer,47,Personal Travel,Eco,188,4,5,4,4,3,5,4,2,2,4,5,3,2,5,0,3.0,neutral or dissatisfied +54845,57058,Female,Loyal Customer,47,Personal Travel,Eco,2133,1,5,2,2,4,2,1,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +54846,125466,Female,Loyal Customer,9,Business travel,Business,2845,1,5,5,5,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +54847,17177,Male,Loyal Customer,49,Business travel,Eco,643,1,5,5,5,1,1,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +54848,95520,Female,disloyal Customer,18,Business travel,Eco Plus,189,1,2,1,3,2,1,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +54849,53175,Male,disloyal Customer,24,Business travel,Eco,589,4,0,4,4,2,4,2,2,1,2,1,3,1,2,0,0.0,satisfied +54850,65134,Female,Loyal Customer,70,Personal Travel,Eco,190,3,0,3,1,1,5,4,3,3,3,3,5,3,3,14,6.0,neutral or dissatisfied +54851,109113,Female,Loyal Customer,40,Business travel,Business,781,4,4,4,4,3,5,5,5,5,4,5,3,5,4,2,12.0,satisfied +54852,32535,Male,disloyal Customer,57,Business travel,Eco,101,2,0,2,1,2,2,2,2,3,4,2,2,1,2,0,0.0,neutral or dissatisfied +54853,90925,Male,Loyal Customer,39,Business travel,Eco,194,4,5,1,1,4,4,4,4,2,2,4,4,4,4,0,0.0,satisfied +54854,80878,Female,Loyal Customer,64,Personal Travel,Eco,484,1,0,1,1,1,3,1,2,2,1,2,4,2,3,15,3.0,neutral or dissatisfied +54855,104501,Male,disloyal Customer,50,Business travel,Business,1609,1,1,1,4,2,1,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +54856,96763,Female,Loyal Customer,47,Personal Travel,Business,816,3,1,3,3,1,2,2,3,3,3,3,3,3,2,43,28.0,neutral or dissatisfied +54857,32715,Female,disloyal Customer,36,Business travel,Eco,101,3,4,3,3,3,3,2,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +54858,122037,Male,Loyal Customer,44,Business travel,Business,130,1,3,3,3,1,1,2,3,3,3,1,3,3,2,17,15.0,neutral or dissatisfied +54859,68343,Female,Loyal Customer,28,Business travel,Business,1598,5,5,5,5,4,4,4,4,5,3,3,3,5,4,0,0.0,satisfied +54860,86331,Male,Loyal Customer,54,Personal Travel,Business,749,1,4,1,5,4,4,1,1,1,1,1,4,1,5,0,0.0,neutral or dissatisfied +54861,107059,Female,Loyal Customer,55,Business travel,Business,1744,4,2,2,2,4,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +54862,128779,Female,disloyal Customer,25,Business travel,Business,2248,3,0,3,1,3,1,1,3,2,5,5,1,3,1,28,55.0,neutral or dissatisfied +54863,81095,Female,Loyal Customer,38,Business travel,Eco Plus,931,3,1,1,1,3,3,3,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +54864,93100,Male,Loyal Customer,55,Business travel,Business,1538,0,0,0,3,5,3,4,3,3,1,1,3,3,5,5,0.0,satisfied +54865,111567,Female,disloyal Customer,24,Business travel,Eco,794,3,3,3,4,5,3,5,5,1,5,4,1,3,5,24,15.0,neutral or dissatisfied +54866,5171,Female,Loyal Customer,79,Business travel,Business,1900,2,2,1,1,5,2,2,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +54867,77980,Male,disloyal Customer,42,Business travel,Business,332,1,1,1,1,1,1,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +54868,112502,Female,Loyal Customer,37,Personal Travel,Eco,957,1,5,0,3,5,0,1,5,5,2,4,4,4,5,63,50.0,neutral or dissatisfied +54869,15824,Female,Loyal Customer,29,Personal Travel,Eco Plus,195,3,5,3,3,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +54870,3064,Male,Loyal Customer,37,Business travel,Business,3703,2,2,2,2,4,5,4,5,5,4,5,4,5,4,61,46.0,satisfied +54871,34301,Male,Loyal Customer,42,Personal Travel,Eco,280,3,5,3,4,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +54872,59084,Male,Loyal Customer,33,Business travel,Business,1744,3,5,3,3,3,3,3,2,2,5,1,3,4,3,192,169.0,satisfied +54873,21602,Female,disloyal Customer,20,Business travel,Eco,780,4,4,4,1,5,4,5,5,2,5,2,1,5,5,73,83.0,neutral or dissatisfied +54874,1841,Female,Loyal Customer,22,Personal Travel,Eco,408,1,1,1,4,3,1,1,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +54875,44634,Female,disloyal Customer,25,Business travel,Eco,67,3,0,2,4,4,2,4,4,2,3,5,4,1,4,0,1.0,neutral or dissatisfied +54876,25048,Female,Loyal Customer,59,Business travel,Eco,594,4,1,1,1,5,1,1,4,4,4,4,4,4,2,8,24.0,satisfied +54877,85287,Male,Loyal Customer,15,Personal Travel,Eco,874,1,0,1,4,4,1,4,4,3,4,2,3,1,4,0,0.0,neutral or dissatisfied +54878,15731,Female,Loyal Customer,38,Personal Travel,Eco,419,2,3,2,1,5,2,5,5,3,3,2,1,3,5,0,0.0,neutral or dissatisfied +54879,103019,Female,disloyal Customer,17,Business travel,Business,490,4,0,4,5,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +54880,105973,Female,Loyal Customer,21,Personal Travel,Eco,2295,1,4,1,4,1,3,3,1,2,3,4,3,1,3,158,130.0,neutral or dissatisfied +54881,76988,Male,disloyal Customer,37,Business travel,Business,368,2,2,2,2,5,2,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +54882,57215,Male,Loyal Customer,52,Business travel,Eco,1514,3,1,2,2,3,3,3,3,3,5,4,4,3,3,14,11.0,neutral or dissatisfied +54883,117225,Female,Loyal Customer,45,Personal Travel,Eco,370,3,3,4,3,3,3,1,2,2,4,2,3,2,5,6,2.0,neutral or dissatisfied +54884,45791,Female,Loyal Customer,59,Business travel,Business,3617,0,5,0,4,1,1,4,1,1,1,1,4,1,1,0,0.0,satisfied +54885,116886,Female,Loyal Customer,43,Business travel,Business,1741,5,1,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +54886,118014,Male,disloyal Customer,39,Business travel,Eco,637,3,5,3,5,3,3,3,3,4,3,2,3,2,3,1,0.0,neutral or dissatisfied +54887,76663,Male,Loyal Customer,30,Personal Travel,Eco,516,1,5,1,1,4,1,4,4,1,4,5,4,4,4,0,0.0,neutral or dissatisfied +54888,125297,Male,disloyal Customer,22,Business travel,Eco,678,3,3,3,4,3,3,3,3,1,3,4,1,3,3,11,2.0,neutral or dissatisfied +54889,637,Male,disloyal Customer,23,Business travel,Business,229,4,0,4,4,1,4,1,1,5,4,4,5,4,1,0,0.0,satisfied +54890,55235,Male,Loyal Customer,43,Business travel,Eco,1009,4,2,2,2,4,4,4,4,3,2,2,2,2,4,112,100.0,neutral or dissatisfied +54891,47687,Female,Loyal Customer,21,Personal Travel,Eco,1242,1,4,1,5,5,1,5,5,5,2,5,5,4,5,33,37.0,neutral or dissatisfied +54892,91744,Female,Loyal Customer,59,Business travel,Business,588,1,1,2,1,3,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +54893,35524,Female,Loyal Customer,16,Personal Travel,Eco,1144,2,5,2,3,4,2,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +54894,100316,Female,disloyal Customer,21,Business travel,Eco,1011,1,1,1,2,5,1,5,5,1,1,3,2,2,5,16,35.0,neutral or dissatisfied +54895,5650,Female,Loyal Customer,48,Business travel,Business,196,4,4,4,4,2,5,4,5,5,5,4,3,5,4,0,0.0,satisfied +54896,50034,Male,Loyal Customer,45,Business travel,Business,3653,2,4,4,4,2,3,3,3,3,3,2,4,3,1,7,0.0,neutral or dissatisfied +54897,110030,Male,Loyal Customer,17,Business travel,Eco Plus,1204,3,2,2,2,3,3,1,3,1,5,3,2,4,3,0,0.0,neutral or dissatisfied +54898,93017,Female,disloyal Customer,50,Business travel,Eco,1124,3,3,3,2,3,3,1,3,1,5,2,3,2,3,34,49.0,neutral or dissatisfied +54899,113228,Male,Loyal Customer,53,Business travel,Business,226,0,0,0,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +54900,87762,Female,Loyal Customer,51,Business travel,Business,214,2,2,4,2,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +54901,70245,Female,disloyal Customer,11,Business travel,Eco,1592,4,4,4,3,4,4,4,4,2,4,3,4,4,4,0,0.0,neutral or dissatisfied +54902,20657,Female,Loyal Customer,44,Business travel,Eco,552,4,3,3,3,3,2,2,4,4,4,4,3,4,3,16,20.0,satisfied +54903,4320,Female,disloyal Customer,25,Business travel,Eco,589,1,1,1,2,3,1,3,3,4,1,2,3,3,3,90,90.0,neutral or dissatisfied +54904,19780,Male,Loyal Customer,45,Business travel,Business,667,3,3,3,3,2,2,1,4,4,4,4,2,4,2,13,0.0,satisfied +54905,90166,Female,Loyal Customer,12,Personal Travel,Eco,983,2,3,2,3,3,2,3,3,3,5,4,5,4,3,41,27.0,neutral or dissatisfied +54906,97111,Male,Loyal Customer,45,Business travel,Eco,1390,4,4,4,4,4,4,4,4,3,3,3,2,2,4,1,0.0,neutral or dissatisfied +54907,63387,Female,Loyal Customer,70,Personal Travel,Eco,337,3,5,3,5,3,4,5,2,2,3,2,3,2,4,75,68.0,neutral or dissatisfied +54908,5706,Female,Loyal Customer,52,Personal Travel,Eco,299,3,5,3,5,3,4,5,1,1,3,1,5,1,5,8,10.0,neutral or dissatisfied +54909,81082,Male,Loyal Customer,37,Business travel,Eco,931,2,5,4,5,2,2,2,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +54910,76176,Female,Loyal Customer,23,Business travel,Eco Plus,289,5,1,1,1,5,5,4,5,5,3,1,5,4,5,17,5.0,satisfied +54911,13733,Female,disloyal Customer,24,Business travel,Eco,384,2,3,2,4,2,2,2,2,2,3,4,4,5,2,0,0.0,neutral or dissatisfied +54912,33337,Male,Loyal Customer,41,Business travel,Business,2614,3,3,4,3,3,3,1,5,5,5,5,2,5,1,0,0.0,satisfied +54913,72947,Female,Loyal Customer,55,Business travel,Business,3016,4,4,1,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +54914,72640,Male,Loyal Customer,22,Personal Travel,Eco,985,4,1,4,1,4,4,4,4,4,2,2,1,2,4,5,2.0,satisfied +54915,14690,Female,Loyal Customer,47,Business travel,Eco,419,4,2,2,2,5,1,1,4,4,4,4,2,4,4,0,0.0,satisfied +54916,29711,Female,Loyal Customer,45,Business travel,Eco,2304,2,1,1,1,1,5,4,2,2,2,2,2,2,3,0,0.0,satisfied +54917,117800,Female,Loyal Customer,46,Business travel,Business,1799,5,5,5,5,4,4,4,4,4,4,4,3,4,5,3,0.0,satisfied +54918,50410,Male,Loyal Customer,36,Business travel,Eco,308,4,2,2,2,4,3,4,4,4,3,4,3,3,4,0,0.0,neutral or dissatisfied +54919,65379,Male,Loyal Customer,58,Business travel,Eco,231,4,4,3,3,4,4,4,4,1,1,4,1,4,4,27,13.0,satisfied +54920,93796,Male,Loyal Customer,52,Business travel,Business,1709,3,4,3,3,5,4,4,4,4,4,4,4,4,5,6,5.0,satisfied +54921,56464,Male,Loyal Customer,51,Business travel,Business,1938,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +54922,22303,Female,Loyal Customer,56,Business travel,Business,83,5,5,5,5,3,4,3,5,5,5,5,3,5,1,0,0.0,satisfied +54923,46325,Male,Loyal Customer,50,Business travel,Eco,420,1,4,1,4,1,1,1,1,2,4,3,4,3,1,19,47.0,neutral or dissatisfied +54924,92230,Male,disloyal Customer,29,Business travel,Business,2079,0,1,1,2,5,1,5,5,5,3,4,5,5,5,0,1.0,satisfied +54925,56542,Male,Loyal Customer,53,Business travel,Business,1023,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +54926,129400,Male,disloyal Customer,20,Business travel,Business,414,4,0,4,2,1,4,1,1,5,2,5,5,4,1,0,0.0,satisfied +54927,71263,Male,Loyal Customer,26,Personal Travel,Eco,733,3,2,3,4,5,3,2,5,2,5,2,2,3,5,2,0.0,neutral or dissatisfied +54928,5592,Male,Loyal Customer,28,Personal Travel,Business,685,3,4,4,1,5,4,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +54929,9497,Female,disloyal Customer,23,Business travel,Eco,239,4,1,4,4,5,4,5,5,1,4,3,3,4,5,1,0.0,neutral or dissatisfied +54930,124334,Female,Loyal Customer,47,Business travel,Business,3392,5,5,5,5,4,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +54931,46866,Female,disloyal Customer,24,Business travel,Eco,853,0,0,0,3,3,0,3,3,5,1,2,1,1,3,0,48.0,satisfied +54932,104581,Male,Loyal Customer,22,Business travel,Eco,369,3,1,1,1,3,3,1,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +54933,38354,Male,disloyal Customer,11,Business travel,Business,1173,2,3,2,3,3,2,2,3,3,5,4,2,4,3,0,17.0,neutral or dissatisfied +54934,36347,Female,Loyal Customer,16,Personal Travel,Eco,395,3,4,3,2,2,3,1,2,3,2,4,5,4,2,14,6.0,neutral or dissatisfied +54935,54421,Female,Loyal Customer,25,Personal Travel,Eco,305,3,5,3,3,3,3,1,3,3,4,4,5,5,3,1,0.0,neutral or dissatisfied +54936,116921,Male,disloyal Customer,27,Business travel,Business,304,2,2,2,2,4,2,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +54937,108866,Female,Loyal Customer,40,Personal Travel,Eco,1892,2,2,2,2,5,2,5,5,2,2,3,1,2,5,0,,neutral or dissatisfied +54938,18378,Male,Loyal Customer,34,Business travel,Business,2164,4,4,4,4,1,1,1,4,4,4,4,2,4,1,117,103.0,neutral or dissatisfied +54939,22589,Male,Loyal Customer,30,Business travel,Business,1686,3,5,5,5,3,3,3,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +54940,30061,Female,Loyal Customer,23,Business travel,Business,261,5,5,5,5,5,5,5,5,1,1,1,2,5,5,0,3.0,satisfied +54941,110615,Male,disloyal Customer,29,Business travel,Business,727,3,3,3,4,1,3,5,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +54942,121599,Female,Loyal Customer,62,Personal Travel,Eco,912,2,4,2,2,3,4,4,1,1,2,1,4,1,4,22,106.0,neutral or dissatisfied +54943,97116,Female,Loyal Customer,30,Business travel,Business,1390,1,4,4,4,1,1,1,1,4,2,4,4,4,1,15,17.0,neutral or dissatisfied +54944,118386,Female,Loyal Customer,49,Business travel,Business,1659,5,5,4,5,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +54945,117311,Female,Loyal Customer,17,Business travel,Eco Plus,368,3,5,5,5,3,4,4,3,4,1,4,4,3,3,0,0.0,satisfied +54946,47201,Male,Loyal Customer,52,Business travel,Eco,679,5,1,1,1,5,5,5,5,3,1,2,4,4,5,0,0.0,satisfied +54947,89411,Male,disloyal Customer,33,Business travel,Eco,134,4,1,4,3,2,4,2,2,2,1,3,1,3,2,12,9.0,neutral or dissatisfied +54948,51668,Female,disloyal Customer,22,Business travel,Eco,493,3,0,3,3,2,3,2,2,3,1,2,4,1,2,0,0.0,neutral or dissatisfied +54949,15361,Female,Loyal Customer,25,Business travel,Business,3937,3,3,3,3,4,4,4,4,2,5,2,2,1,4,47,44.0,satisfied +54950,116724,Male,Loyal Customer,40,Business travel,Eco Plus,404,5,2,2,2,5,4,5,5,2,2,4,1,4,5,0,0.0,neutral or dissatisfied +54951,59170,Female,Loyal Customer,64,Personal Travel,Eco Plus,1846,3,4,2,1,1,4,2,5,5,2,3,4,5,3,12,0.0,neutral or dissatisfied +54952,38497,Female,Loyal Customer,39,Business travel,Eco,2475,5,2,4,2,5,5,5,5,5,3,5,5,2,5,14,0.0,satisfied +54953,112622,Male,Loyal Customer,32,Personal Travel,Eco,602,2,5,3,4,5,3,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +54954,14357,Female,disloyal Customer,23,Business travel,Eco Plus,395,1,5,1,4,3,1,5,3,4,5,4,4,1,3,0,0.0,neutral or dissatisfied +54955,34069,Male,Loyal Customer,9,Personal Travel,Eco,1674,3,4,3,4,4,3,4,4,3,5,4,1,4,4,0,0.0,neutral or dissatisfied +54956,48185,Female,Loyal Customer,34,Business travel,Business,3100,5,5,5,5,3,3,5,4,4,4,4,2,4,2,7,2.0,satisfied +54957,124908,Female,Loyal Customer,51,Business travel,Business,1748,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,25.0,satisfied +54958,6858,Male,Loyal Customer,58,Business travel,Business,3059,4,4,4,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +54959,72152,Male,Loyal Customer,37,Personal Travel,Eco,731,2,3,2,4,5,2,5,5,3,5,4,1,3,5,0,0.0,neutral or dissatisfied +54960,79247,Male,Loyal Customer,56,Business travel,Business,1598,4,4,4,4,4,4,4,5,2,4,5,4,5,4,193,189.0,satisfied +54961,90188,Male,Loyal Customer,27,Personal Travel,Eco,1145,3,4,3,2,5,3,5,5,4,3,3,4,4,5,0,7.0,neutral or dissatisfied +54962,57590,Female,Loyal Customer,30,Personal Travel,Eco,1597,2,2,2,4,3,2,2,3,2,1,2,4,3,3,10,30.0,neutral or dissatisfied +54963,18501,Female,disloyal Customer,40,Business travel,Business,127,2,2,2,4,5,2,5,5,2,4,2,3,4,5,0,0.0,neutral or dissatisfied +54964,79829,Female,Loyal Customer,53,Business travel,Business,3681,2,2,2,2,5,5,4,4,4,4,4,3,4,3,45,21.0,satisfied +54965,96994,Male,Loyal Customer,21,Personal Travel,Eco,359,2,5,2,3,2,2,2,2,5,3,5,4,5,2,20,35.0,neutral or dissatisfied +54966,121320,Male,Loyal Customer,29,Personal Travel,Eco,1009,4,4,4,2,4,4,4,4,1,2,4,3,3,4,0,0.0,neutral or dissatisfied +54967,107880,Female,Loyal Customer,10,Personal Travel,Eco,228,3,1,3,3,1,3,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +54968,107168,Female,Loyal Customer,44,Business travel,Business,3519,2,2,2,2,5,4,5,3,3,3,3,3,3,3,45,42.0,satisfied +54969,123542,Female,Loyal Customer,53,Business travel,Business,273,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,5.0,satisfied +54970,57785,Male,Loyal Customer,23,Personal Travel,Eco,2704,3,5,3,2,3,5,5,3,2,5,5,5,5,5,9,3.0,neutral or dissatisfied +54971,84523,Female,Loyal Customer,30,Business travel,Eco,2486,3,2,2,2,3,3,3,3,4,1,2,3,4,3,3,0.0,neutral or dissatisfied +54972,107702,Male,Loyal Customer,24,Business travel,Business,251,5,5,5,5,4,4,4,4,4,2,5,4,4,4,4,23.0,satisfied +54973,3224,Male,Loyal Customer,18,Business travel,Business,1980,3,5,5,5,3,3,3,3,4,2,3,4,3,3,41,52.0,neutral or dissatisfied +54974,43324,Female,Loyal Customer,38,Business travel,Eco,347,2,4,4,4,2,2,2,2,5,2,2,2,2,2,0,0.0,satisfied +54975,77407,Female,Loyal Customer,55,Personal Travel,Eco,599,2,2,2,4,3,3,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +54976,126923,Male,Loyal Customer,59,Personal Travel,Business,355,1,1,1,4,1,4,3,3,3,1,1,4,3,3,0,0.0,neutral or dissatisfied +54977,85291,Female,Loyal Customer,69,Personal Travel,Eco,731,4,1,4,4,2,3,3,5,5,4,5,4,5,1,3,0.0,satisfied +54978,79693,Male,Loyal Customer,8,Personal Travel,Eco,762,3,2,3,3,1,3,1,1,1,4,4,4,3,1,14,0.0,neutral or dissatisfied +54979,82664,Male,Loyal Customer,39,Personal Travel,Eco,120,3,5,3,2,2,3,2,2,1,4,1,2,5,2,26,18.0,neutral or dissatisfied +54980,21131,Female,Loyal Customer,36,Personal Travel,Eco,106,3,4,3,1,2,3,2,2,3,2,5,4,4,2,2,0.0,neutral or dissatisfied +54981,68972,Male,Loyal Customer,42,Business travel,Eco,300,4,1,1,1,4,4,4,4,2,4,1,2,5,4,4,0.0,satisfied +54982,564,Male,Loyal Customer,49,Business travel,Business,89,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +54983,52261,Female,Loyal Customer,15,Business travel,Business,3488,3,1,3,3,5,5,5,5,4,5,4,3,3,5,0,0.0,satisfied +54984,72654,Male,Loyal Customer,67,Personal Travel,Eco,1121,3,4,3,4,4,3,4,4,1,3,3,2,4,4,22,30.0,neutral or dissatisfied +54985,14978,Female,disloyal Customer,22,Business travel,Business,927,5,3,5,3,1,5,1,1,4,5,2,5,4,1,0,1.0,satisfied +54986,93737,Male,Loyal Customer,13,Personal Travel,Business,368,1,3,1,2,4,1,3,4,5,2,1,1,4,4,2,0.0,neutral or dissatisfied +54987,49028,Female,Loyal Customer,43,Business travel,Business,3124,4,1,4,4,2,5,1,5,5,5,3,2,5,2,2,0.0,satisfied +54988,67025,Male,Loyal Customer,26,Business travel,Business,3448,4,4,4,4,4,4,4,4,4,2,5,4,5,4,0,0.0,satisfied +54989,56525,Male,Loyal Customer,42,Business travel,Business,3241,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +54990,99637,Female,Loyal Customer,43,Personal Travel,Eco Plus,1154,2,5,2,4,5,4,4,4,4,2,4,4,4,3,0,19.0,neutral or dissatisfied +54991,12811,Female,Loyal Customer,30,Business travel,Business,2251,5,5,5,5,5,5,5,5,1,3,4,4,2,5,56,58.0,satisfied +54992,78032,Male,Loyal Customer,44,Personal Travel,Eco,332,4,4,4,4,2,4,2,2,3,3,5,5,5,2,0,0.0,satisfied +54993,40307,Female,Loyal Customer,41,Personal Travel,Eco,531,2,5,2,1,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +54994,111813,Male,Loyal Customer,43,Personal Travel,Eco,349,3,3,3,4,4,3,4,4,3,2,1,2,5,4,14,6.0,neutral or dissatisfied +54995,117297,Female,Loyal Customer,42,Business travel,Eco Plus,646,2,5,5,5,2,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +54996,103151,Male,Loyal Customer,26,Business travel,Business,491,4,4,4,4,4,4,4,4,5,4,4,3,5,4,15,4.0,satisfied +54997,3835,Male,Loyal Customer,59,Personal Travel,Eco,710,1,5,1,2,1,1,1,1,3,4,5,4,4,1,26,12.0,neutral or dissatisfied +54998,84597,Female,Loyal Customer,27,Business travel,Business,669,1,1,1,1,4,4,4,4,3,4,5,5,5,4,34,25.0,satisfied +54999,16124,Female,disloyal Customer,36,Business travel,Eco,325,3,3,3,4,4,3,4,4,2,2,4,3,4,4,44,33.0,neutral or dissatisfied +55000,127752,Male,Loyal Customer,67,Personal Travel,Eco,255,2,3,2,3,1,2,1,1,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +55001,87085,Female,disloyal Customer,40,Business travel,Business,640,4,4,4,2,2,4,2,2,4,2,5,3,4,2,1,0.0,satisfied +55002,4858,Female,disloyal Customer,21,Business travel,Eco,408,3,3,3,4,3,1,1,1,4,3,4,1,1,1,333,338.0,neutral or dissatisfied +55003,20814,Female,disloyal Customer,20,Business travel,Eco,357,1,0,1,1,5,1,5,5,2,3,4,1,1,5,0,0.0,neutral or dissatisfied +55004,89653,Female,Loyal Customer,51,Business travel,Business,1076,2,2,1,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +55005,84000,Female,Loyal Customer,38,Personal Travel,Eco,321,5,5,1,3,1,1,1,1,1,2,2,4,4,1,2,0.0,satisfied +55006,43441,Female,disloyal Customer,22,Business travel,Eco,679,3,3,3,2,4,3,4,4,2,4,4,2,4,4,0,8.0,neutral or dissatisfied +55007,117834,Female,Loyal Customer,32,Personal Travel,Eco,328,3,3,3,4,5,3,5,5,2,2,4,2,4,5,2,0.0,neutral or dissatisfied +55008,4239,Female,disloyal Customer,9,Business travel,Eco,1020,2,2,2,3,2,2,2,2,2,5,4,2,4,2,5,1.0,neutral or dissatisfied +55009,74293,Female,Loyal Customer,24,Personal Travel,Eco,2288,2,2,3,2,1,3,1,1,1,3,3,4,2,1,0,0.0,neutral or dissatisfied +55010,123127,Female,disloyal Customer,33,Business travel,Business,631,1,2,2,2,5,2,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +55011,78244,Female,Loyal Customer,42,Business travel,Eco Plus,259,4,2,2,2,3,3,4,4,4,4,4,1,4,1,0,4.0,neutral or dissatisfied +55012,94415,Male,Loyal Customer,56,Business travel,Business,528,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +55013,63759,Female,disloyal Customer,28,Business travel,Eco,779,3,3,3,3,2,3,2,2,3,4,2,4,3,2,63,62.0,neutral or dissatisfied +55014,95509,Female,Loyal Customer,33,Business travel,Eco Plus,189,1,4,4,4,1,2,1,1,1,3,4,3,4,1,45,40.0,neutral or dissatisfied +55015,73872,Male,Loyal Customer,23,Personal Travel,Business,2585,2,0,2,2,2,1,1,2,5,5,2,1,5,1,27,11.0,neutral or dissatisfied +55016,105472,Male,disloyal Customer,26,Business travel,Business,495,5,5,5,3,2,5,3,2,3,4,4,4,4,2,0,0.0,satisfied +55017,74229,Male,disloyal Customer,20,Business travel,Eco,888,4,4,4,3,3,4,3,3,4,4,4,3,4,3,0,0.0,satisfied +55018,44349,Male,Loyal Customer,31,Business travel,Eco Plus,308,5,4,4,4,5,4,5,5,4,4,5,1,3,5,30,15.0,satisfied +55019,10490,Male,Loyal Customer,58,Business travel,Business,2760,4,4,4,4,5,5,5,4,4,4,4,4,4,4,11,6.0,satisfied +55020,124946,Male,Loyal Customer,52,Business travel,Business,3213,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +55021,46119,Male,Loyal Customer,28,Business travel,Business,3841,3,3,3,3,4,4,4,4,2,4,2,4,1,4,0,0.0,satisfied +55022,60853,Female,Loyal Customer,16,Personal Travel,Eco,1754,3,5,3,2,5,3,5,5,5,1,3,5,5,5,0,0.0,neutral or dissatisfied +55023,66261,Male,Loyal Customer,49,Personal Travel,Eco,460,2,4,2,1,5,2,5,5,4,3,3,3,1,5,30,30.0,neutral or dissatisfied +55024,65811,Female,disloyal Customer,16,Business travel,Business,1389,4,4,4,2,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +55025,35975,Female,Loyal Customer,43,Business travel,Eco Plus,231,5,2,2,2,4,4,3,5,5,5,5,1,5,1,0,0.0,satisfied +55026,72942,Male,disloyal Customer,22,Business travel,Eco,1089,1,2,2,1,4,2,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +55027,66891,Male,Loyal Customer,59,Business travel,Business,2173,3,4,4,4,5,2,2,3,3,3,3,3,3,1,0,30.0,neutral or dissatisfied +55028,112053,Male,disloyal Customer,36,Business travel,Business,254,1,1,1,3,1,1,1,1,3,2,4,2,4,1,0,0.0,neutral or dissatisfied +55029,91883,Female,Loyal Customer,39,Business travel,Business,2475,3,3,3,3,5,4,5,5,5,4,5,5,5,3,6,0.0,satisfied +55030,81381,Male,Loyal Customer,31,Business travel,Business,874,3,3,2,3,3,3,3,3,3,2,5,3,5,3,15,1.0,satisfied +55031,96989,Female,disloyal Customer,34,Business travel,Eco,359,3,5,3,1,3,3,3,3,4,2,1,5,5,3,0,0.0,neutral or dissatisfied +55032,68961,Male,Loyal Customer,46,Business travel,Business,700,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +55033,12898,Male,Loyal Customer,35,Business travel,Business,1772,1,3,2,3,5,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +55034,63906,Female,Loyal Customer,55,Business travel,Eco,1172,4,2,4,2,2,2,3,4,4,4,4,1,4,1,4,0.0,satisfied +55035,98246,Male,Loyal Customer,37,Business travel,Business,1072,2,2,5,2,2,5,5,5,5,5,5,5,5,4,0,34.0,satisfied +55036,90328,Male,Loyal Customer,18,Business travel,Business,366,4,4,5,4,4,4,4,4,5,3,4,5,4,4,22,16.0,satisfied +55037,29311,Male,Loyal Customer,24,Personal Travel,Eco,873,2,4,2,1,4,2,4,4,2,3,4,4,5,4,92,107.0,neutral or dissatisfied +55038,81393,Female,Loyal Customer,60,Business travel,Business,474,1,1,1,1,4,4,1,5,5,4,5,5,5,3,0,0.0,satisfied +55039,17048,Female,Loyal Customer,47,Business travel,Eco,1134,4,3,3,3,2,5,3,4,4,4,4,1,4,5,0,0.0,satisfied +55040,43656,Male,disloyal Customer,26,Business travel,Eco,695,3,3,3,3,4,3,4,4,1,4,5,4,5,4,0,0.0,neutral or dissatisfied +55041,61795,Male,Loyal Customer,13,Personal Travel,Eco,1303,1,4,1,3,5,1,5,5,2,2,4,3,3,5,0,0.0,neutral or dissatisfied +55042,31004,Male,disloyal Customer,23,Business travel,Eco,391,3,3,3,3,1,3,1,1,2,1,3,4,3,1,15,31.0,neutral or dissatisfied +55043,37644,Male,Loyal Customer,33,Personal Travel,Eco,944,4,5,4,3,5,4,5,5,2,4,4,1,3,5,0,0.0,satisfied +55044,55647,Male,Loyal Customer,52,Business travel,Business,3381,5,5,5,5,5,5,5,4,4,4,4,5,4,5,80,63.0,satisfied +55045,116021,Female,Loyal Customer,48,Personal Travel,Eco,337,4,3,4,4,2,4,3,2,2,4,2,4,2,3,3,0.0,satisfied +55046,113217,Male,disloyal Customer,20,Business travel,Business,414,2,1,2,3,4,2,4,4,3,2,2,4,3,4,4,0.0,neutral or dissatisfied +55047,63998,Female,Loyal Customer,25,Business travel,Business,612,4,4,4,4,5,5,5,5,4,5,5,4,5,5,0,0.0,satisfied +55048,57178,Male,Loyal Customer,48,Business travel,Eco,727,4,3,3,3,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +55049,50700,Male,Loyal Customer,14,Personal Travel,Eco,86,2,5,0,1,4,0,4,4,3,5,4,4,4,4,45,45.0,neutral or dissatisfied +55050,67100,Male,Loyal Customer,41,Business travel,Business,2899,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +55051,106332,Male,Loyal Customer,59,Personal Travel,Eco,825,3,5,4,4,4,4,2,4,4,2,4,4,4,4,1,0.0,neutral or dissatisfied +55052,75291,Male,disloyal Customer,39,Business travel,Eco Plus,1846,2,2,2,3,3,2,3,3,4,5,2,4,3,3,6,0.0,neutral or dissatisfied +55053,16099,Female,Loyal Customer,61,Personal Travel,Eco,303,3,4,3,1,3,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +55054,107717,Male,Loyal Customer,39,Business travel,Business,251,2,1,1,1,1,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +55055,87796,Female,Loyal Customer,42,Business travel,Business,1622,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,2.0,satisfied +55056,54244,Female,disloyal Customer,28,Business travel,Eco,1222,2,2,2,2,3,2,3,3,4,1,2,3,2,3,13,20.0,neutral or dissatisfied +55057,59737,Male,Loyal Customer,47,Business travel,Business,895,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +55058,56011,Male,Loyal Customer,49,Business travel,Business,2586,5,5,5,5,5,5,5,4,5,5,4,5,3,5,60,51.0,satisfied +55059,42975,Male,Loyal Customer,40,Business travel,Business,1869,4,4,4,4,3,1,4,4,4,4,4,2,4,1,14,3.0,satisfied +55060,83726,Male,Loyal Customer,28,Business travel,Eco Plus,269,3,5,2,5,3,3,3,3,4,5,4,4,3,3,118,97.0,neutral or dissatisfied +55061,73620,Female,Loyal Customer,53,Business travel,Business,3236,0,4,0,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +55062,53578,Male,Loyal Customer,41,Personal Travel,Eco,1195,3,4,3,3,4,3,1,4,3,4,5,3,5,4,74,78.0,neutral or dissatisfied +55063,89032,Female,disloyal Customer,26,Business travel,Business,1377,5,5,5,3,5,5,5,5,4,5,5,5,4,5,1,5.0,satisfied +55064,39573,Male,Loyal Customer,26,Business travel,Business,965,1,5,5,5,1,1,1,1,4,2,3,3,4,1,0,0.0,neutral or dissatisfied +55065,7384,Female,Loyal Customer,14,Personal Travel,Business,552,4,1,5,3,5,5,5,5,3,4,4,2,3,5,0,0.0,satisfied +55066,41493,Female,disloyal Customer,66,Business travel,Eco,1036,1,1,1,4,1,1,1,3,3,3,1,1,5,1,134,134.0,neutral or dissatisfied +55067,114203,Male,Loyal Customer,33,Business travel,Business,3236,5,5,5,5,5,5,5,5,4,2,4,5,4,5,27,23.0,satisfied +55068,129402,Female,Loyal Customer,47,Business travel,Business,236,4,4,4,4,3,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +55069,45646,Female,Loyal Customer,63,Personal Travel,Eco,230,1,4,1,4,5,5,4,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +55070,4261,Female,Loyal Customer,31,Business travel,Business,502,3,3,5,3,4,4,4,4,4,3,4,3,5,4,0,16.0,satisfied +55071,30663,Female,Loyal Customer,64,Personal Travel,Eco,533,2,4,2,3,2,4,5,5,5,2,1,3,5,5,0,1.0,neutral or dissatisfied +55072,20451,Female,Loyal Customer,44,Business travel,Business,84,3,3,3,3,5,4,4,5,5,5,4,5,5,2,42,29.0,satisfied +55073,18414,Female,Loyal Customer,26,Business travel,Eco,750,3,2,3,2,3,3,3,3,2,3,3,3,1,3,0,141.0,neutral or dissatisfied +55074,79031,Male,Loyal Customer,74,Business travel,Business,2063,4,3,3,3,3,3,4,4,4,4,4,2,4,1,8,5.0,neutral or dissatisfied +55075,80869,Female,Loyal Customer,70,Personal Travel,Eco,484,2,5,2,2,2,4,3,2,2,2,2,3,2,4,0,16.0,neutral or dissatisfied +55076,129693,Male,Loyal Customer,56,Business travel,Business,3080,5,5,5,5,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +55077,42981,Female,disloyal Customer,23,Business travel,Business,259,5,1,5,3,2,5,2,2,3,4,2,4,4,2,0,0.0,satisfied +55078,44043,Male,Loyal Customer,77,Business travel,Business,237,3,3,3,3,5,3,4,3,3,2,3,3,3,2,0,2.0,neutral or dissatisfied +55079,53197,Male,Loyal Customer,34,Business travel,Business,2573,3,5,5,5,1,3,3,3,3,3,3,1,3,2,13,43.0,neutral or dissatisfied +55080,86126,Female,Loyal Customer,59,Business travel,Business,226,2,2,2,2,2,5,5,4,4,5,4,4,4,5,13,11.0,satisfied +55081,11833,Female,Loyal Customer,32,Personal Travel,Eco,986,4,5,4,3,2,4,2,2,3,2,4,3,4,2,2,0.0,neutral or dissatisfied +55082,4434,Female,Loyal Customer,31,Business travel,Eco,762,4,4,3,4,4,3,4,4,3,1,3,2,4,4,47,78.0,neutral or dissatisfied +55083,40488,Male,Loyal Customer,48,Personal Travel,Eco,188,2,4,0,3,4,0,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +55084,118150,Male,Loyal Customer,34,Business travel,Business,1444,3,3,3,3,3,5,5,4,4,4,4,3,4,5,14,2.0,satisfied +55085,125774,Female,Loyal Customer,48,Business travel,Business,3227,3,3,3,3,4,5,5,4,4,5,4,5,4,4,113,123.0,satisfied +55086,72230,Female,Loyal Customer,26,Business travel,Business,3484,5,5,5,5,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +55087,23004,Male,Loyal Customer,64,Personal Travel,Eco,489,4,4,4,5,3,4,3,3,2,3,1,2,1,3,0,0.0,neutral or dissatisfied +55088,104699,Male,disloyal Customer,37,Business travel,Eco,159,2,3,1,3,1,4,4,4,4,4,4,4,4,4,180,217.0,neutral or dissatisfied +55089,91431,Male,Loyal Customer,54,Personal Travel,Eco,549,2,4,2,3,1,2,1,1,3,4,4,5,4,1,30,11.0,neutral or dissatisfied +55090,75567,Female,disloyal Customer,44,Business travel,Business,337,2,1,1,3,3,2,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +55091,8892,Female,Loyal Customer,11,Personal Travel,Eco,622,2,5,2,3,4,2,4,4,5,2,4,5,4,4,6,1.0,neutral or dissatisfied +55092,99722,Female,Loyal Customer,23,Personal Travel,Business,255,4,3,4,2,4,4,4,4,4,2,5,2,4,4,0,0.0,neutral or dissatisfied +55093,10796,Female,Loyal Customer,60,Business travel,Business,2566,1,1,1,1,3,2,3,1,1,2,1,3,1,3,4,0.0,neutral or dissatisfied +55094,57039,Female,Loyal Customer,53,Personal Travel,Eco Plus,2454,2,4,2,3,2,2,2,3,4,4,4,2,3,2,0,0.0,neutral or dissatisfied +55095,1182,Male,Loyal Customer,41,Personal Travel,Eco,247,5,5,5,5,4,5,4,4,3,3,4,3,5,4,0,0.0,satisfied +55096,124368,Male,Loyal Customer,50,Business travel,Eco,575,2,2,2,2,3,2,3,3,4,4,3,1,2,3,0,0.0,neutral or dissatisfied +55097,19450,Female,Loyal Customer,30,Business travel,Eco,231,0,0,0,1,5,0,5,5,3,1,5,5,4,5,0,0.0,satisfied +55098,66807,Male,Loyal Customer,52,Business travel,Business,731,1,1,1,1,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +55099,84902,Male,Loyal Customer,70,Personal Travel,Eco,516,3,3,3,4,1,3,1,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +55100,18228,Female,Loyal Customer,60,Business travel,Business,2454,2,4,3,4,2,3,3,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +55101,104640,Male,Loyal Customer,48,Business travel,Business,1754,5,5,5,5,4,4,4,5,5,5,5,3,5,5,67,74.0,satisfied +55102,15436,Female,Loyal Customer,28,Business travel,Eco,399,2,4,4,4,2,2,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +55103,115883,Female,disloyal Customer,36,Business travel,Eco,308,3,0,3,2,4,3,4,4,5,2,3,1,1,4,0,0.0,neutral or dissatisfied +55104,71025,Male,disloyal Customer,29,Business travel,Eco,802,3,4,4,2,3,4,3,3,3,4,3,1,2,3,0,0.0,neutral or dissatisfied +55105,117077,Male,disloyal Customer,35,Business travel,Eco,304,1,2,1,4,3,1,3,3,3,3,4,4,4,3,8,14.0,neutral or dissatisfied +55106,30893,Male,Loyal Customer,44,Personal Travel,Eco,841,3,4,3,4,4,3,4,4,3,2,4,2,4,4,0,3.0,neutral or dissatisfied +55107,113731,Female,Loyal Customer,7,Personal Travel,Eco,236,0,5,0,4,4,0,4,4,5,4,5,4,4,4,16,2.0,satisfied +55108,8395,Male,Loyal Customer,26,Business travel,Eco,888,4,3,3,3,4,4,4,4,1,4,2,4,3,4,0,4.0,satisfied +55109,105771,Female,disloyal Customer,24,Business travel,Eco,883,2,2,2,3,3,2,3,3,2,5,4,2,3,3,11,8.0,neutral or dissatisfied +55110,106583,Female,disloyal Customer,37,Business travel,Eco,333,2,1,2,3,1,2,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +55111,81690,Male,Loyal Customer,57,Personal Travel,Eco,907,4,1,4,3,4,4,4,4,1,4,2,3,2,4,0,0.0,neutral or dissatisfied +55112,27108,Female,Loyal Customer,26,Business travel,Eco Plus,1721,3,4,4,4,3,2,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +55113,47770,Male,Loyal Customer,24,Business travel,Business,2283,1,1,1,1,4,4,4,4,2,2,3,3,4,4,12,7.0,satisfied +55114,55418,Male,Loyal Customer,55,Business travel,Eco,2254,4,5,5,5,4,4,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +55115,96334,Male,Loyal Customer,39,Business travel,Business,1609,3,3,3,3,4,5,4,4,4,4,4,5,4,3,47,58.0,satisfied +55116,67438,Female,disloyal Customer,17,Business travel,Eco,641,3,2,3,4,5,3,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +55117,110700,Male,Loyal Customer,10,Personal Travel,Eco,945,3,5,4,1,2,4,2,2,5,2,1,5,5,2,0,0.0,neutral or dissatisfied +55118,1011,Male,disloyal Customer,30,Business travel,Eco,89,4,4,4,4,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +55119,115381,Male,disloyal Customer,26,Business travel,Business,373,2,4,3,2,5,3,1,5,3,4,5,5,5,5,0,1.0,neutral or dissatisfied +55120,38611,Female,Loyal Customer,59,Personal Travel,Eco,231,3,5,3,2,4,4,5,5,5,3,5,4,5,3,0,2.0,neutral or dissatisfied +55121,88630,Male,Loyal Customer,66,Personal Travel,Eco,404,2,4,2,1,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +55122,116953,Female,Loyal Customer,38,Business travel,Business,646,3,3,3,3,3,4,4,5,5,4,5,4,5,5,36,28.0,satisfied +55123,101225,Male,Loyal Customer,52,Business travel,Business,1090,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +55124,17784,Male,Loyal Customer,27,Business travel,Business,1075,3,3,3,3,4,4,4,4,4,3,2,5,1,4,0,0.0,satisfied +55125,2029,Female,Loyal Customer,56,Business travel,Business,733,5,5,5,5,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +55126,79601,Female,disloyal Customer,9,Business travel,Eco,760,2,2,2,3,4,2,4,4,3,1,2,4,2,4,14,1.0,neutral or dissatisfied +55127,37957,Male,disloyal Customer,35,Business travel,Business,1010,3,3,3,2,3,3,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +55128,29659,Female,Loyal Customer,12,Personal Travel,Eco,680,4,4,4,5,4,4,4,4,4,2,5,3,4,4,43,51.0,neutral or dissatisfied +55129,11012,Female,Loyal Customer,39,Business travel,Business,201,4,4,4,4,1,2,4,5,5,4,3,4,5,5,7,1.0,satisfied +55130,90973,Male,Loyal Customer,66,Business travel,Business,3416,2,4,4,4,3,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +55131,1074,Female,Loyal Customer,63,Personal Travel,Eco,482,2,3,2,3,1,3,3,4,4,2,4,2,4,4,5,11.0,neutral or dissatisfied +55132,116220,Female,Loyal Customer,70,Personal Travel,Eco,390,2,2,2,3,5,4,4,5,5,2,3,2,5,2,5,3.0,neutral or dissatisfied +55133,29804,Female,Loyal Customer,35,Business travel,Business,3981,4,4,4,4,4,5,4,4,1,4,2,4,1,4,155,,satisfied +55134,62917,Female,Loyal Customer,26,Business travel,Business,2998,5,5,5,5,4,4,4,4,4,5,4,4,5,4,3,2.0,satisfied +55135,11498,Female,Loyal Customer,14,Personal Travel,Eco Plus,191,2,5,0,2,3,0,3,3,4,2,5,5,4,3,12,5.0,neutral or dissatisfied +55136,21889,Female,disloyal Customer,27,Business travel,Eco,551,3,5,3,2,2,3,2,2,3,4,3,4,2,2,0,5.0,neutral or dissatisfied +55137,69790,Male,disloyal Customer,19,Business travel,Eco,1055,4,4,4,4,1,4,1,1,3,5,4,3,4,1,0,6.0,neutral or dissatisfied +55138,62585,Female,Loyal Customer,30,Business travel,Eco,1744,3,4,4,4,3,3,3,3,3,1,4,1,3,3,19,17.0,neutral or dissatisfied +55139,29812,Male,Loyal Customer,54,Business travel,Business,261,2,2,2,2,2,5,4,4,4,4,4,2,4,3,0,0.0,satisfied +55140,51894,Female,Loyal Customer,53,Business travel,Eco,601,1,3,3,3,1,4,4,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +55141,63346,Female,Loyal Customer,51,Business travel,Eco,447,5,5,5,5,1,3,1,5,5,5,5,5,5,3,2,0.0,satisfied +55142,4196,Female,Loyal Customer,50,Business travel,Eco Plus,431,2,3,3,3,2,1,1,2,2,2,2,1,2,2,98,82.0,satisfied +55143,58636,Male,disloyal Customer,22,Business travel,Eco,867,3,3,3,2,2,3,1,2,5,5,4,5,5,2,3,0.0,neutral or dissatisfied +55144,39671,Female,Loyal Customer,39,Business travel,Eco Plus,476,4,4,4,4,4,4,4,4,5,5,1,5,5,4,0,5.0,satisfied +55145,44454,Male,Loyal Customer,40,Business travel,Business,2992,4,4,2,4,1,3,5,5,5,5,5,2,5,5,0,24.0,satisfied +55146,38543,Female,Loyal Customer,36,Business travel,Business,2569,4,5,5,5,2,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +55147,92818,Female,Loyal Customer,44,Business travel,Business,1587,2,3,3,3,2,2,2,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +55148,34351,Male,Loyal Customer,48,Business travel,Business,2381,4,4,2,4,1,3,3,4,4,4,4,1,4,1,0,0.0,satisfied +55149,80275,Female,Loyal Customer,28,Business travel,Business,746,3,4,4,4,3,3,3,3,1,4,4,2,3,3,10,17.0,neutral or dissatisfied +55150,68840,Male,Loyal Customer,29,Business travel,Business,3053,4,5,5,5,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +55151,88048,Male,Loyal Customer,47,Business travel,Business,1992,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +55152,55518,Female,Loyal Customer,19,Personal Travel,Eco,991,3,5,3,3,1,3,1,1,4,3,5,3,4,1,8,9.0,neutral or dissatisfied +55153,56999,Female,Loyal Customer,23,Personal Travel,Eco,2425,2,5,2,2,2,4,4,3,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +55154,124174,Male,Loyal Customer,27,Business travel,Business,2133,3,3,3,3,5,5,5,5,4,5,4,5,5,5,0,0.0,satisfied +55155,127528,Female,Loyal Customer,50,Business travel,Business,3007,3,5,3,3,4,5,5,4,4,4,4,5,4,5,0,10.0,satisfied +55156,50095,Female,Loyal Customer,56,Business travel,Eco,109,2,2,3,2,3,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +55157,67891,Male,Loyal Customer,10,Personal Travel,Eco,1126,2,3,2,3,1,2,1,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +55158,62584,Female,Loyal Customer,59,Business travel,Business,1846,1,1,1,1,2,3,5,4,4,4,4,5,4,4,0,0.0,satisfied +55159,48201,Male,Loyal Customer,61,Business travel,Eco,192,2,4,4,4,2,2,2,2,2,4,4,4,3,2,3,0.0,neutral or dissatisfied +55160,67326,Male,Loyal Customer,36,Personal Travel,Eco Plus,1102,2,5,1,2,2,1,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +55161,117897,Female,disloyal Customer,27,Business travel,Business,255,2,2,2,1,5,2,5,5,5,5,5,3,5,5,0,6.0,neutral or dissatisfied +55162,92154,Male,Loyal Customer,24,Business travel,Eco Plus,1189,5,5,5,5,5,5,5,5,3,5,2,2,3,5,0,0.0,satisfied +55163,96475,Male,Loyal Customer,41,Business travel,Business,444,1,1,1,1,3,5,5,5,5,5,5,3,5,5,2,0.0,satisfied +55164,71739,Female,Loyal Customer,26,Personal Travel,Business,1744,3,0,3,4,5,3,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +55165,105997,Male,disloyal Customer,23,Business travel,Business,1494,4,2,4,4,5,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +55166,109719,Female,Loyal Customer,43,Business travel,Eco,587,3,3,3,3,5,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +55167,74221,Male,Loyal Customer,58,Personal Travel,Eco,1746,3,2,3,3,3,1,1,4,2,4,4,1,1,1,277,255.0,neutral or dissatisfied +55168,63706,Male,Loyal Customer,22,Business travel,Business,1660,5,5,5,5,4,4,4,4,5,3,5,5,5,4,18,0.0,satisfied +55169,70355,Female,Loyal Customer,32,Business travel,Eco Plus,986,2,5,5,5,2,1,2,2,1,3,2,4,1,2,1,0.0,neutral or dissatisfied +55170,82387,Female,Loyal Customer,49,Business travel,Business,1704,1,1,1,1,4,4,4,3,3,4,5,4,5,4,138,134.0,satisfied +55171,115223,Female,Loyal Customer,60,Business travel,Business,1532,3,3,3,3,2,4,4,5,5,5,5,3,5,5,35,28.0,satisfied +55172,19570,Female,disloyal Customer,20,Business travel,Eco,173,3,0,4,4,1,4,1,1,2,5,4,3,3,1,40,52.0,neutral or dissatisfied +55173,59944,Female,Loyal Customer,19,Business travel,Business,937,3,3,3,3,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +55174,104729,Female,disloyal Customer,23,Business travel,Business,1407,4,0,4,1,4,4,4,4,5,3,5,3,5,4,2,0.0,satisfied +55175,107566,Female,Loyal Customer,12,Personal Travel,Eco,1521,2,4,2,5,2,2,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +55176,59166,Female,Loyal Customer,36,Business travel,Eco Plus,223,5,4,4,4,5,5,5,5,2,2,2,1,3,5,13,2.0,satisfied +55177,114001,Female,Loyal Customer,40,Personal Travel,Eco,1750,3,5,2,3,1,2,1,1,4,4,4,1,2,1,47,41.0,neutral or dissatisfied +55178,121042,Female,Loyal Customer,68,Personal Travel,Eco,861,2,5,2,1,1,2,3,5,5,2,5,4,5,4,0,29.0,neutral or dissatisfied +55179,68020,Male,Loyal Customer,18,Personal Travel,Eco,280,2,5,2,4,4,2,4,4,1,3,4,4,1,4,0,0.0,neutral or dissatisfied +55180,21549,Female,Loyal Customer,8,Personal Travel,Eco,399,1,2,1,4,2,1,2,2,1,4,4,4,3,2,0,0.0,neutral or dissatisfied +55181,84410,Male,Loyal Customer,70,Personal Travel,Eco,591,3,5,3,2,3,3,3,3,3,2,5,4,4,3,4,1.0,neutral or dissatisfied +55182,43268,Male,disloyal Customer,41,Business travel,Business,358,1,0,0,3,3,0,3,3,3,1,2,4,2,3,9,21.0,neutral or dissatisfied +55183,22191,Female,Loyal Customer,48,Business travel,Eco,373,1,4,3,4,5,3,4,1,1,1,1,1,1,3,3,0.0,neutral or dissatisfied +55184,102696,Male,Loyal Customer,55,Business travel,Business,255,1,2,3,3,2,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +55185,113598,Male,Loyal Customer,52,Business travel,Business,407,5,5,5,5,3,5,2,4,4,4,4,4,4,4,49,36.0,satisfied +55186,13483,Male,Loyal Customer,41,Business travel,Business,3655,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +55187,64873,Male,Loyal Customer,46,Business travel,Business,2537,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,3.0,satisfied +55188,99359,Female,Loyal Customer,71,Business travel,Eco Plus,1771,1,2,2,2,4,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +55189,28415,Male,disloyal Customer,17,Business travel,Eco,1399,4,3,3,3,1,4,1,1,4,1,5,4,3,1,0,0.0,satisfied +55190,3450,Female,Loyal Customer,35,Personal Travel,Eco,315,3,5,3,3,2,3,2,2,1,1,2,3,5,2,0,0.0,neutral or dissatisfied +55191,40222,Female,Loyal Customer,53,Business travel,Eco,436,1,1,1,1,1,4,3,1,1,1,1,3,1,1,0,8.0,neutral or dissatisfied +55192,37397,Female,disloyal Customer,26,Business travel,Eco,944,1,1,1,3,4,1,4,4,2,2,4,3,4,4,25,25.0,neutral or dissatisfied +55193,10336,Female,disloyal Customer,50,Business travel,Business,166,4,4,4,4,1,4,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +55194,27898,Male,Loyal Customer,45,Business travel,Business,2350,5,5,2,5,5,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +55195,61948,Male,Loyal Customer,38,Business travel,Business,2052,4,1,1,1,3,1,1,4,4,4,4,3,4,4,4,0.0,neutral or dissatisfied +55196,85441,Male,Loyal Customer,33,Business travel,Business,3937,3,3,4,3,3,3,3,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +55197,38084,Male,Loyal Customer,30,Business travel,Eco,1237,0,0,0,2,5,3,5,5,3,3,2,1,5,5,0,0.0,satisfied +55198,9436,Male,Loyal Customer,39,Business travel,Business,2762,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +55199,22451,Male,Loyal Customer,12,Personal Travel,Eco,143,2,5,2,2,5,2,2,5,2,4,3,3,1,5,0,0.0,neutral or dissatisfied +55200,65765,Female,Loyal Customer,54,Business travel,Business,936,3,3,2,3,2,5,4,5,5,5,5,5,5,4,2,0.0,satisfied +55201,128524,Female,Loyal Customer,66,Personal Travel,Eco,621,1,4,1,3,4,5,4,1,1,1,1,3,1,5,14,6.0,neutral or dissatisfied +55202,115787,Female,Loyal Customer,41,Business travel,Eco,296,2,3,3,3,2,2,2,2,1,1,4,3,4,2,0,0.0,neutral or dissatisfied +55203,8464,Female,Loyal Customer,34,Personal Travel,Eco,1379,3,3,4,3,1,4,1,1,3,1,3,2,3,1,2,0.0,neutral or dissatisfied +55204,35867,Male,Loyal Customer,51,Personal Travel,Eco,997,3,4,3,5,5,3,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +55205,72053,Female,disloyal Customer,28,Business travel,Business,2556,4,4,4,4,3,4,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +55206,82197,Female,Loyal Customer,19,Personal Travel,Eco,1927,4,5,4,2,5,4,5,5,4,2,3,4,4,5,1,12.0,neutral or dissatisfied +55207,50560,Male,Loyal Customer,46,Personal Travel,Eco,89,1,5,1,2,5,1,1,5,3,3,4,3,4,5,31,30.0,neutral or dissatisfied +55208,33368,Male,Loyal Customer,28,Personal Travel,Eco,2399,4,1,4,4,4,4,2,4,4,1,3,3,3,4,0,11.0,neutral or dissatisfied +55209,125638,Male,disloyal Customer,25,Business travel,Business,899,2,0,2,5,4,2,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +55210,106248,Female,Loyal Customer,22,Business travel,Business,3620,3,3,3,3,2,2,2,2,5,3,3,2,1,2,0,0.0,satisfied +55211,73090,Female,Loyal Customer,17,Personal Travel,Eco,1085,3,5,3,1,1,3,1,1,3,5,1,2,4,1,0,0.0,neutral or dissatisfied +55212,97421,Female,Loyal Customer,17,Personal Travel,Eco,570,5,1,5,4,5,5,5,5,2,1,3,4,4,5,0,0.0,satisfied +55213,26636,Female,Loyal Customer,63,Business travel,Business,1596,2,4,5,4,3,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +55214,21291,Female,Loyal Customer,29,Business travel,Business,2143,2,2,2,2,4,4,4,4,1,1,3,3,4,4,0,0.0,satisfied +55215,113835,Male,Loyal Customer,62,Personal Travel,Eco Plus,236,3,4,3,3,3,3,3,3,3,4,5,5,5,3,37,27.0,neutral or dissatisfied +55216,2378,Male,Loyal Customer,58,Business travel,Business,1729,2,2,2,2,2,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +55217,877,Female,disloyal Customer,27,Business travel,Business,312,4,4,4,1,5,4,5,5,3,4,4,4,5,5,0,0.0,satisfied +55218,111356,Female,Loyal Customer,45,Business travel,Eco Plus,377,5,2,2,2,3,1,4,5,5,5,5,2,5,4,3,3.0,satisfied +55219,97871,Male,Loyal Customer,57,Business travel,Business,1654,1,1,1,1,3,4,5,4,4,5,4,3,4,3,47,39.0,satisfied +55220,125176,Female,Loyal Customer,39,Business travel,Business,3230,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,14.0,satisfied +55221,3316,Female,Loyal Customer,66,Personal Travel,Business,315,2,5,2,2,5,5,4,2,2,2,2,4,2,3,4,72.0,neutral or dissatisfied +55222,106264,Male,disloyal Customer,23,Business travel,Business,1500,4,0,4,3,4,4,4,4,4,2,4,4,4,4,6,5.0,satisfied +55223,18847,Male,disloyal Customer,62,Business travel,Eco,503,3,2,2,2,3,2,1,3,1,4,3,4,2,3,0,0.0,neutral or dissatisfied +55224,27860,Female,Loyal Customer,44,Personal Travel,Eco,1448,1,2,1,2,5,1,1,5,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +55225,40629,Male,Loyal Customer,37,Personal Travel,Eco,517,4,5,4,2,4,4,4,4,5,3,4,5,5,4,67,81.0,neutral or dissatisfied +55226,112752,Male,Loyal Customer,49,Business travel,Business,1921,1,1,1,1,3,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +55227,39250,Male,Loyal Customer,56,Business travel,Business,173,3,3,3,3,1,3,4,5,5,5,4,2,5,4,0,0.0,satisfied +55228,72352,Male,Loyal Customer,38,Personal Travel,Business,1121,1,5,1,2,5,5,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +55229,59903,Male,Loyal Customer,52,Business travel,Business,3403,2,2,4,2,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +55230,14530,Male,disloyal Customer,24,Business travel,Business,368,4,2,4,2,5,4,5,5,1,2,3,3,3,5,0,0.0,neutral or dissatisfied +55231,36774,Male,Loyal Customer,42,Business travel,Business,2611,3,1,1,1,3,3,3,1,5,1,2,3,1,3,54,53.0,neutral or dissatisfied +55232,114018,Female,Loyal Customer,15,Personal Travel,Eco,1728,4,4,4,3,5,4,5,5,3,2,5,4,4,5,2,6.0,neutral or dissatisfied +55233,7117,Female,Loyal Customer,41,Personal Travel,Eco,157,3,1,0,4,4,0,4,4,3,2,3,2,4,4,0,0.0,neutral or dissatisfied +55234,1445,Male,Loyal Customer,56,Business travel,Business,772,1,1,1,1,3,4,5,5,5,4,5,5,5,5,0,4.0,satisfied +55235,105022,Male,Loyal Customer,34,Business travel,Business,255,2,2,2,2,3,5,5,4,4,4,4,3,4,5,28,21.0,satisfied +55236,9843,Male,disloyal Customer,25,Business travel,Business,642,5,0,5,1,5,5,5,5,4,4,4,4,4,5,50,35.0,satisfied +55237,53064,Female,Loyal Customer,45,Personal Travel,Eco,1172,4,4,4,4,3,5,5,3,3,4,5,5,3,5,31,34.0,neutral or dissatisfied +55238,85711,Female,Loyal Customer,38,Business travel,Business,1547,4,4,4,4,4,5,5,4,4,4,4,5,4,4,5,0.0,satisfied +55239,82425,Female,disloyal Customer,17,Business travel,Eco,502,4,1,4,3,1,4,1,1,4,3,2,2,2,1,1,19.0,neutral or dissatisfied +55240,22353,Male,Loyal Customer,20,Business travel,Eco,238,5,3,2,2,5,5,5,5,3,4,1,3,1,5,85,77.0,satisfied +55241,47673,Male,Loyal Customer,18,Personal Travel,Eco,715,4,2,4,3,1,4,1,1,4,4,4,3,4,1,3,4.0,satisfied +55242,61762,Male,Loyal Customer,8,Personal Travel,Eco,1379,2,4,2,4,4,2,4,4,4,5,5,4,5,4,0,0.0,neutral or dissatisfied +55243,46361,Male,disloyal Customer,25,Business travel,Eco,1013,4,4,4,3,1,4,1,1,2,2,5,2,3,1,35,21.0,neutral or dissatisfied +55244,129442,Male,Loyal Customer,68,Personal Travel,Eco,414,2,4,2,4,2,2,3,2,3,2,3,3,3,2,40,30.0,neutral or dissatisfied +55245,86039,Male,Loyal Customer,53,Personal Travel,Eco,447,1,5,5,2,1,5,1,1,1,1,2,2,2,1,81,66.0,neutral or dissatisfied +55246,60314,Male,disloyal Customer,39,Business travel,Business,1024,5,5,5,3,2,5,2,2,5,4,4,4,4,2,9,0.0,satisfied +55247,34085,Male,disloyal Customer,41,Business travel,Eco,751,1,1,1,2,3,1,3,3,5,2,4,1,5,3,0,5.0,neutral or dissatisfied +55248,23860,Male,disloyal Customer,41,Business travel,Eco,152,3,4,3,3,1,3,1,1,2,3,4,1,3,1,49,44.0,neutral or dissatisfied +55249,122281,Female,Loyal Customer,18,Personal Travel,Eco,546,3,4,2,4,2,2,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +55250,64782,Male,disloyal Customer,20,Business travel,Eco,247,1,0,2,2,2,2,2,2,3,4,5,3,5,2,0,4.0,neutral or dissatisfied +55251,101268,Female,Loyal Customer,70,Personal Travel,Eco,2176,3,4,3,2,3,1,1,4,4,3,3,1,4,1,207,176.0,neutral or dissatisfied +55252,9159,Female,disloyal Customer,32,Business travel,Eco,975,2,2,2,3,4,2,4,4,4,1,4,1,4,4,38,50.0,neutral or dissatisfied +55253,109771,Male,Loyal Customer,54,Business travel,Business,2762,1,5,5,5,1,1,1,1,1,1,1,2,1,1,106,101.0,neutral or dissatisfied +55254,20228,Male,Loyal Customer,34,Business travel,Eco,235,4,5,5,5,4,4,4,4,2,3,4,1,4,4,14,14.0,satisfied +55255,79528,Male,disloyal Customer,23,Business travel,Business,762,5,0,5,5,4,5,3,4,5,3,5,3,5,4,13,5.0,satisfied +55256,2545,Female,Loyal Customer,36,Business travel,Business,2799,0,0,0,4,5,5,5,5,5,5,5,5,5,3,46,40.0,satisfied +55257,105306,Female,Loyal Customer,65,Personal Travel,Eco,738,3,4,3,2,4,4,5,5,5,3,5,5,5,3,4,13.0,neutral or dissatisfied +55258,113109,Female,Loyal Customer,28,Personal Travel,Eco,543,2,5,2,3,2,2,2,2,3,4,4,3,2,2,53,56.0,neutral or dissatisfied +55259,36293,Male,Loyal Customer,49,Business travel,Business,187,1,1,1,1,3,1,5,5,5,5,3,5,5,4,11,0.0,satisfied +55260,19389,Female,Loyal Customer,36,Personal Travel,Eco,844,2,5,2,3,2,5,5,5,5,5,5,5,5,5,152,141.0,neutral or dissatisfied +55261,35162,Male,Loyal Customer,38,Business travel,Eco,1074,2,4,3,4,2,2,2,2,2,1,4,2,2,2,0,0.0,satisfied +55262,107595,Female,Loyal Customer,40,Business travel,Business,1596,1,1,1,1,5,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +55263,49617,Male,disloyal Customer,22,Business travel,Eco,262,2,0,2,3,4,2,4,4,3,5,4,5,2,4,0,0.0,neutral or dissatisfied +55264,68339,Male,Loyal Customer,55,Business travel,Business,1598,4,4,4,4,5,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +55265,72904,Male,Loyal Customer,44,Business travel,Business,2029,2,2,5,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +55266,56154,Male,Loyal Customer,29,Business travel,Eco,1400,3,3,3,3,3,3,3,3,1,5,4,1,3,3,3,0.0,neutral or dissatisfied +55267,99711,Female,Loyal Customer,40,Personal Travel,Eco,667,5,4,5,4,3,5,3,3,3,2,5,4,4,3,0,0.0,satisfied +55268,1817,Male,disloyal Customer,20,Business travel,Eco,408,3,2,3,4,2,3,2,2,4,5,3,3,4,2,9,0.0,neutral or dissatisfied +55269,117488,Female,Loyal Customer,23,Business travel,Business,507,3,4,3,4,3,3,3,3,2,5,3,4,4,3,0,0.0,neutral or dissatisfied +55270,48695,Female,Loyal Customer,44,Business travel,Business,2871,2,2,2,2,2,4,4,4,4,4,5,3,4,5,67,56.0,satisfied +55271,64417,Male,disloyal Customer,24,Business travel,Business,989,3,3,3,3,2,3,2,2,2,5,3,2,3,2,2,1.0,neutral or dissatisfied +55272,21990,Female,Loyal Customer,48,Personal Travel,Eco,551,2,4,2,5,2,5,2,1,1,2,3,2,1,5,0,4.0,neutral or dissatisfied +55273,19696,Female,Loyal Customer,54,Business travel,Eco,475,4,3,3,3,5,1,5,4,4,4,4,1,4,3,0,1.0,satisfied +55274,54169,Female,Loyal Customer,39,Business travel,Business,1504,4,1,1,1,1,2,2,4,4,3,4,3,4,4,55,13.0,neutral or dissatisfied +55275,31037,Female,Loyal Customer,20,Business travel,Eco,775,5,5,5,5,5,5,3,5,4,4,5,4,5,5,1,17.0,satisfied +55276,10817,Female,Loyal Customer,44,Business travel,Business,2635,2,2,2,2,4,5,5,5,5,5,4,5,5,3,0,4.0,satisfied +55277,94345,Female,Loyal Customer,42,Business travel,Business,248,5,5,5,5,3,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +55278,92371,Female,Loyal Customer,60,Business travel,Business,2139,2,3,3,3,1,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +55279,35039,Male,Loyal Customer,54,Business travel,Business,2052,1,1,1,1,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +55280,42695,Female,Loyal Customer,18,Personal Travel,Eco,604,3,4,3,2,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +55281,82424,Female,Loyal Customer,57,Business travel,Business,241,1,1,1,1,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +55282,47103,Male,Loyal Customer,24,Business travel,Eco Plus,639,0,3,0,1,2,0,2,2,5,5,3,3,3,2,1,5.0,satisfied +55283,89467,Male,Loyal Customer,39,Business travel,Business,151,4,4,4,4,3,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +55284,37330,Female,Loyal Customer,49,Business travel,Business,3578,2,2,2,2,4,2,4,3,3,2,3,5,3,5,0,0.0,satisfied +55285,76435,Male,Loyal Customer,64,Personal Travel,Eco,405,3,5,3,4,5,3,5,5,2,5,5,3,3,5,0,0.0,neutral or dissatisfied +55286,51847,Female,Loyal Customer,63,Personal Travel,Eco Plus,751,2,5,2,4,2,1,1,4,4,5,4,1,4,1,168,180.0,neutral or dissatisfied +55287,16056,Male,Loyal Customer,58,Business travel,Business,501,2,2,3,2,3,3,3,2,2,2,2,1,2,1,0,18.0,neutral or dissatisfied +55288,92390,Female,Loyal Customer,48,Business travel,Business,1892,5,5,2,5,2,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +55289,32117,Male,disloyal Customer,32,Business travel,Eco,163,1,3,1,5,5,1,1,5,3,1,3,5,3,5,0,10.0,neutral or dissatisfied +55290,21063,Male,Loyal Customer,64,Business travel,Eco,152,4,5,5,5,4,4,4,4,3,5,3,1,4,4,0,0.0,neutral or dissatisfied +55291,61009,Female,disloyal Customer,34,Business travel,Business,3414,3,2,2,2,2,3,2,3,3,3,5,2,5,2,3,16.0,neutral or dissatisfied +55292,69737,Female,Loyal Customer,52,Business travel,Business,1372,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +55293,111307,Female,Loyal Customer,60,Business travel,Business,3168,2,2,2,2,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +55294,3925,Male,Loyal Customer,14,Personal Travel,Eco,213,4,3,4,2,3,4,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +55295,29426,Female,Loyal Customer,35,Business travel,Business,2149,5,5,5,5,2,5,1,4,4,4,4,5,4,4,0,0.0,satisfied +55296,58197,Male,disloyal Customer,32,Business travel,Business,925,3,3,3,1,1,3,1,1,4,4,5,5,4,1,12,0.0,neutral or dissatisfied +55297,94871,Female,Loyal Customer,50,Business travel,Business,239,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +55298,14711,Male,Loyal Customer,7,Personal Travel,Eco,479,3,4,3,3,2,3,2,2,1,5,5,5,3,2,0,0.0,neutral or dissatisfied +55299,69276,Female,Loyal Customer,44,Personal Travel,Eco,733,3,2,3,3,1,3,3,2,2,3,1,3,2,3,88,95.0,neutral or dissatisfied +55300,46475,Female,disloyal Customer,23,Business travel,Business,125,3,1,3,4,1,3,1,1,4,1,3,2,4,1,65,63.0,neutral or dissatisfied +55301,81903,Male,Loyal Customer,19,Personal Travel,Eco,680,5,5,5,1,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +55302,128292,Male,Loyal Customer,25,Business travel,Business,651,2,2,2,2,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +55303,111193,Female,disloyal Customer,41,Business travel,Business,1546,2,2,2,2,3,2,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +55304,32205,Female,Loyal Customer,69,Business travel,Business,3932,0,4,0,3,5,1,3,5,5,5,5,2,5,4,0,0.0,satisfied +55305,60356,Female,Loyal Customer,37,Business travel,Business,1476,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +55306,128007,Male,Loyal Customer,34,Personal Travel,Eco,1488,2,4,2,2,5,2,5,5,5,4,3,3,5,5,0,0.0,neutral or dissatisfied +55307,92474,Male,Loyal Customer,31,Business travel,Business,2139,2,1,1,1,2,2,2,2,2,1,3,2,2,2,0,0.0,neutral or dissatisfied +55308,14463,Male,Loyal Customer,11,Personal Travel,Eco,674,3,5,3,3,1,3,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +55309,42174,Male,Loyal Customer,22,Business travel,Business,550,5,2,5,5,5,5,5,5,4,4,2,2,1,5,0,0.0,satisfied +55310,128966,Female,Loyal Customer,19,Personal Travel,Eco,414,4,5,2,3,5,2,5,5,1,1,4,1,1,5,11,21.0,satisfied +55311,91604,Female,Loyal Customer,48,Business travel,Business,1184,3,3,3,3,1,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +55312,104111,Female,Loyal Customer,30,Personal Travel,Eco,297,3,3,3,1,3,3,3,3,5,5,5,4,2,3,12,0.0,neutral or dissatisfied +55313,104411,Male,Loyal Customer,31,Business travel,Business,2847,4,4,4,4,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +55314,9427,Male,Loyal Customer,46,Business travel,Business,288,0,0,0,3,4,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +55315,2632,Female,Loyal Customer,46,Personal Travel,Eco Plus,280,2,0,2,2,4,4,5,3,3,2,3,5,3,5,61,62.0,neutral or dissatisfied +55316,101806,Male,disloyal Customer,62,Business travel,Eco,1521,2,2,2,2,1,2,1,1,2,3,2,1,2,1,32,14.0,neutral or dissatisfied +55317,43345,Female,Loyal Customer,65,Business travel,Business,347,3,3,1,3,1,2,2,4,4,4,4,4,4,4,0,5.0,satisfied +55318,79575,Male,disloyal Customer,35,Business travel,Eco,762,3,3,3,3,5,3,5,5,4,2,4,1,3,5,2,0.0,neutral or dissatisfied +55319,37176,Male,Loyal Customer,67,Personal Travel,Eco,1046,4,3,4,4,4,4,4,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +55320,59682,Male,Loyal Customer,32,Personal Travel,Eco,965,3,5,2,2,2,2,1,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +55321,82886,Male,Loyal Customer,53,Business travel,Business,1859,3,2,2,2,5,4,4,3,3,3,3,1,3,4,46,45.0,neutral or dissatisfied +55322,42549,Male,Loyal Customer,65,Personal Travel,Eco,1091,3,2,3,3,4,3,4,4,3,2,3,4,3,4,4,1.0,neutral or dissatisfied +55323,34761,Male,Loyal Customer,24,Business travel,Business,3309,4,4,4,4,4,4,4,4,2,4,1,4,2,4,0,0.0,satisfied +55324,89729,Male,Loyal Customer,68,Personal Travel,Eco,1089,2,3,2,1,2,2,2,2,2,5,4,1,1,2,0,0.0,neutral or dissatisfied +55325,41373,Male,Loyal Customer,29,Business travel,Eco,563,4,2,4,2,4,4,4,4,3,1,3,2,1,4,0,0.0,satisfied +55326,3950,Female,Loyal Customer,16,Business travel,Eco,764,3,4,5,5,3,3,4,3,4,2,3,2,3,3,0,7.0,neutral or dissatisfied +55327,104834,Male,Loyal Customer,57,Business travel,Business,426,5,5,5,5,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +55328,5484,Male,disloyal Customer,39,Business travel,Business,910,2,2,2,2,4,2,4,4,4,3,4,5,5,4,7,3.0,neutral or dissatisfied +55329,51234,Male,Loyal Customer,55,Business travel,Eco Plus,153,5,3,3,3,5,5,5,5,2,4,4,5,2,5,0,0.0,satisfied +55330,107769,Female,Loyal Customer,40,Business travel,Business,405,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +55331,66201,Female,Loyal Customer,37,Business travel,Business,2919,4,4,5,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +55332,82518,Female,Loyal Customer,48,Business travel,Eco,1749,2,4,5,4,3,2,3,1,1,2,1,1,1,2,10,8.0,neutral or dissatisfied +55333,24941,Female,Loyal Customer,52,Business travel,Business,1747,3,3,3,3,5,3,2,5,5,5,5,3,5,1,0,7.0,satisfied +55334,78755,Male,Loyal Customer,58,Business travel,Business,3338,3,3,3,3,4,5,4,5,5,5,5,4,5,5,0,26.0,satisfied +55335,124857,Female,Loyal Customer,47,Business travel,Business,280,4,3,4,4,3,4,5,5,5,5,5,3,5,5,35,40.0,satisfied +55336,120498,Male,Loyal Customer,58,Business travel,Business,1824,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +55337,18644,Male,Loyal Customer,53,Personal Travel,Eco,383,2,5,3,2,2,3,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +55338,4842,Female,Loyal Customer,40,Business travel,Business,2835,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +55339,4546,Female,disloyal Customer,38,Business travel,Eco,319,3,3,3,4,3,1,1,1,1,3,3,1,4,1,112,135.0,neutral or dissatisfied +55340,32387,Female,Loyal Customer,30,Business travel,Business,2537,3,1,5,1,1,1,3,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +55341,76216,Female,Loyal Customer,44,Business travel,Business,1399,3,3,3,3,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +55342,49792,Male,Loyal Customer,67,Business travel,Business,3094,4,3,3,3,1,4,3,3,3,3,4,4,3,2,32,23.0,neutral or dissatisfied +55343,8572,Female,disloyal Customer,23,Business travel,Eco,109,0,4,0,2,2,0,2,2,3,5,4,4,4,2,0,0.0,satisfied +55344,84420,Female,Loyal Customer,12,Personal Travel,Eco,591,2,4,2,2,2,2,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +55345,5077,Male,Loyal Customer,53,Business travel,Eco,235,4,1,1,1,5,4,5,5,3,5,3,4,3,5,0,0.0,neutral or dissatisfied +55346,126767,Female,Loyal Customer,33,Personal Travel,Eco,2521,2,5,1,5,5,1,2,5,4,2,5,2,2,5,0,0.0,neutral or dissatisfied +55347,106768,Female,Loyal Customer,48,Personal Travel,Eco,829,4,4,4,2,5,5,4,3,3,4,3,4,3,3,6,16.0,neutral or dissatisfied +55348,1049,Male,Loyal Customer,35,Business travel,Business,2622,5,5,5,5,4,2,1,5,5,5,3,4,5,4,0,0.0,satisfied +55349,6331,Female,Loyal Customer,44,Business travel,Business,315,3,3,3,3,4,4,4,5,5,4,5,4,3,4,238,287.0,satisfied +55350,104547,Female,Loyal Customer,69,Personal Travel,Eco,1256,3,1,3,2,2,1,2,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +55351,24481,Female,Loyal Customer,51,Business travel,Business,481,4,4,4,4,5,2,5,5,5,5,5,3,5,4,0,0.0,satisfied +55352,121761,Male,Loyal Customer,47,Personal Travel,Business,449,2,5,2,3,4,3,2,1,1,2,2,3,1,4,0,0.0,neutral or dissatisfied +55353,107956,Male,Loyal Customer,39,Business travel,Business,825,1,1,1,1,5,4,4,4,4,4,4,4,4,5,36,32.0,satisfied +55354,122235,Male,disloyal Customer,11,Business travel,Business,541,4,4,4,1,1,4,1,1,3,3,4,5,5,1,0,0.0,satisfied +55355,70150,Male,Loyal Customer,63,Personal Travel,Eco,550,2,0,2,3,3,2,3,3,3,5,4,3,5,3,0,2.0,neutral or dissatisfied +55356,84568,Female,Loyal Customer,66,Personal Travel,Eco,2556,1,1,1,4,1,4,3,1,1,1,1,2,1,2,0,4.0,neutral or dissatisfied +55357,18728,Male,Loyal Customer,36,Business travel,Eco,917,5,1,1,1,5,5,5,5,2,3,1,3,4,5,8,0.0,satisfied +55358,35528,Male,Loyal Customer,48,Personal Travel,Eco,972,2,4,3,1,3,3,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +55359,46639,Female,Loyal Customer,61,Business travel,Eco,212,5,2,5,2,2,4,1,5,5,5,5,3,5,1,0,0.0,satisfied +55360,124244,Female,disloyal Customer,15,Business travel,Eco,727,2,2,2,2,4,2,4,4,1,1,2,1,2,4,0,0.0,neutral or dissatisfied +55361,60160,Male,Loyal Customer,24,Personal Travel,Eco,1182,3,4,3,3,5,3,5,5,4,3,3,5,5,5,0,0.0,neutral or dissatisfied +55362,14997,Male,Loyal Customer,22,Business travel,Business,2458,4,2,2,2,4,4,4,4,3,3,4,4,3,4,0,7.0,neutral or dissatisfied +55363,44584,Female,Loyal Customer,13,Personal Travel,Eco,157,3,4,3,4,2,3,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +55364,94441,Male,Loyal Customer,47,Business travel,Business,248,0,0,0,4,4,4,4,5,5,5,5,4,5,5,11,13.0,satisfied +55365,23594,Female,Loyal Customer,30,Personal Travel,Eco,1024,3,5,3,2,5,3,5,5,2,3,4,2,3,5,4,9.0,neutral or dissatisfied +55366,72630,Female,Loyal Customer,12,Personal Travel,Eco,1119,4,4,4,1,3,4,3,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +55367,39687,Male,disloyal Customer,26,Business travel,Business,1063,3,3,3,4,3,3,3,3,3,3,3,2,3,3,57,,neutral or dissatisfied +55368,122242,Male,Loyal Customer,34,Business travel,Business,544,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +55369,129869,Female,disloyal Customer,18,Business travel,Eco,337,2,0,2,3,5,2,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +55370,95740,Male,Loyal Customer,49,Business travel,Business,237,4,5,3,5,4,2,2,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +55371,11666,Female,disloyal Customer,23,Business travel,Business,1117,5,4,5,3,2,5,2,2,3,5,4,4,4,2,0,0.0,satisfied +55372,47462,Female,Loyal Customer,60,Personal Travel,Eco,599,0,0,0,3,3,4,3,1,1,0,1,4,1,3,0,0.0,satisfied +55373,30520,Male,Loyal Customer,18,Business travel,Eco Plus,373,2,3,3,3,2,2,4,2,3,2,3,4,4,2,0,7.0,neutral or dissatisfied +55374,121620,Male,Loyal Customer,50,Personal Travel,Eco,912,3,3,3,3,5,3,2,5,3,5,2,4,5,5,13,3.0,neutral or dissatisfied +55375,39353,Female,Loyal Customer,49,Personal Travel,Business,896,0,4,0,4,3,4,4,3,3,0,5,2,3,4,0,0.0,satisfied +55376,127346,Female,disloyal Customer,20,Business travel,Eco,507,4,5,4,5,5,4,3,5,3,3,3,2,2,5,0,0.0,neutral or dissatisfied +55377,129257,Female,Loyal Customer,44,Business travel,Business,2820,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +55378,87598,Male,Loyal Customer,7,Personal Travel,Eco,432,1,4,1,3,1,1,1,1,5,2,5,5,4,1,8,2.0,neutral or dissatisfied +55379,97995,Female,Loyal Customer,23,Business travel,Business,612,5,3,5,5,5,5,5,5,5,4,5,4,4,5,29,26.0,satisfied +55380,84969,Female,Loyal Customer,66,Personal Travel,Eco Plus,547,2,5,2,1,4,4,4,4,4,2,4,4,4,5,2,0.0,neutral or dissatisfied +55381,27432,Female,Loyal Customer,43,Business travel,Eco,671,5,3,5,3,5,3,5,4,4,5,4,5,4,5,0,8.0,satisfied +55382,21914,Male,disloyal Customer,38,Business travel,Eco,448,3,3,3,4,1,3,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +55383,79558,Male,Loyal Customer,23,Business travel,Business,762,5,5,4,5,5,5,5,5,3,2,4,4,4,5,4,85.0,satisfied +55384,104363,Male,Loyal Customer,15,Personal Travel,Business,228,2,5,2,3,4,2,4,4,3,2,5,5,5,4,13,0.0,neutral or dissatisfied +55385,28355,Female,Loyal Customer,33,Personal Travel,Eco,867,3,2,3,3,1,3,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +55386,11690,Male,disloyal Customer,24,Business travel,Business,429,5,0,5,5,3,5,3,3,3,2,4,5,4,3,0,0.0,satisfied +55387,14114,Female,disloyal Customer,37,Business travel,Eco Plus,371,1,1,1,3,1,1,1,1,3,4,3,3,4,1,0,0.0,neutral or dissatisfied +55388,19238,Female,Loyal Customer,59,Business travel,Eco,782,4,3,3,3,5,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +55389,110317,Female,Loyal Customer,41,Business travel,Business,787,2,2,2,2,3,5,4,5,5,5,5,5,5,3,7,14.0,satisfied +55390,119669,Female,Loyal Customer,26,Personal Travel,Eco,507,2,4,2,1,4,2,3,4,4,4,4,3,4,4,5,3.0,neutral or dissatisfied +55391,45903,Female,Loyal Customer,26,Business travel,Business,2772,3,1,1,1,3,3,3,3,2,2,4,2,3,3,1,1.0,neutral or dissatisfied +55392,53683,Female,Loyal Customer,31,Business travel,Business,1968,2,2,2,2,5,5,5,5,3,1,1,2,3,5,0,1.0,satisfied +55393,22016,Female,Loyal Customer,39,Personal Travel,Eco,551,2,4,2,3,3,2,3,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +55394,77627,Female,Loyal Customer,35,Business travel,Business,1637,3,4,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +55395,129092,Female,Loyal Customer,55,Business travel,Business,2218,1,5,5,5,3,2,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +55396,81323,Male,Loyal Customer,41,Business travel,Business,1862,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +55397,127811,Male,Loyal Customer,42,Business travel,Business,1044,5,5,2,5,3,5,5,2,2,2,2,3,2,4,0,5.0,satisfied +55398,104374,Female,Loyal Customer,42,Business travel,Business,2685,3,5,5,5,3,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +55399,256,Male,disloyal Customer,22,Business travel,Business,612,5,4,5,1,2,5,2,2,5,3,5,3,5,2,92,99.0,satisfied +55400,36937,Male,Loyal Customer,58,Business travel,Eco Plus,467,5,5,5,5,5,5,5,5,3,3,4,3,5,5,12,4.0,satisfied +55401,10249,Male,Loyal Customer,61,Personal Travel,Business,316,2,4,2,4,3,4,3,3,3,2,3,4,3,1,12,9.0,neutral or dissatisfied +55402,103104,Male,Loyal Customer,61,Personal Travel,Eco,546,2,2,2,4,1,2,1,1,1,1,4,2,4,1,47,49.0,neutral or dissatisfied +55403,40306,Male,Loyal Customer,57,Personal Travel,Eco,347,1,5,1,1,2,1,2,2,2,2,1,2,4,2,0,0.0,neutral or dissatisfied +55404,99528,Male,Loyal Customer,41,Business travel,Business,802,2,2,2,2,2,5,4,5,5,5,5,5,5,5,24,15.0,satisfied +55405,120285,Male,Loyal Customer,50,Business travel,Eco,1176,3,5,5,5,3,3,3,3,4,2,1,4,2,3,1,2.0,neutral or dissatisfied +55406,79513,Female,disloyal Customer,25,Business travel,Business,762,0,5,0,1,4,5,4,4,3,2,4,5,4,4,0,0.0,satisfied +55407,52398,Male,Loyal Customer,22,Personal Travel,Eco,425,2,4,2,4,3,2,3,3,1,3,4,4,3,3,0,1.0,neutral or dissatisfied +55408,118970,Male,Loyal Customer,54,Personal Travel,Eco,570,1,4,1,4,1,1,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +55409,47951,Male,Loyal Customer,70,Personal Travel,Eco,846,1,5,1,2,4,1,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +55410,25875,Male,Loyal Customer,32,Business travel,Eco,907,4,4,4,4,4,4,4,4,4,4,4,5,2,4,0,1.0,satisfied +55411,42882,Female,Loyal Customer,38,Personal Travel,Eco,867,3,4,3,4,4,3,5,4,2,1,4,3,3,4,0,0.0,neutral or dissatisfied +55412,82560,Male,Loyal Customer,33,Business travel,Business,3223,2,2,2,2,2,2,2,2,5,5,5,5,4,2,62,50.0,satisfied +55413,39556,Male,Loyal Customer,25,Business travel,Business,954,4,4,4,4,4,4,4,4,1,3,5,3,5,4,1,0.0,satisfied +55414,77988,Female,Loyal Customer,39,Business travel,Business,1548,0,5,0,4,4,4,5,5,5,3,3,3,5,5,5,0.0,satisfied +55415,78105,Female,Loyal Customer,54,Personal Travel,Eco,684,3,1,3,2,5,3,2,2,2,3,2,1,2,4,0,8.0,neutral or dissatisfied +55416,106165,Female,Loyal Customer,19,Personal Travel,Eco,436,1,4,1,2,4,1,4,4,4,2,3,1,1,4,22,41.0,neutral or dissatisfied +55417,30149,Male,disloyal Customer,58,Personal Travel,Eco,253,3,4,3,5,2,3,2,2,1,5,5,1,4,2,2,53.0,neutral or dissatisfied +55418,74400,Female,Loyal Customer,27,Business travel,Business,1126,3,3,3,3,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +55419,17661,Male,Loyal Customer,12,Personal Travel,Eco,1008,1,4,1,4,4,1,4,4,1,5,3,3,4,4,37,22.0,neutral or dissatisfied +55420,30956,Male,Loyal Customer,41,Personal Travel,Eco,1024,3,4,3,4,2,3,1,2,3,2,5,5,4,2,19,29.0,neutral or dissatisfied +55421,76245,Male,Loyal Customer,30,Personal Travel,Eco,1175,2,4,2,2,2,2,5,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +55422,120685,Female,Loyal Customer,30,Personal Travel,Eco,280,3,4,3,2,3,3,3,5,4,5,5,3,5,3,196,197.0,neutral or dissatisfied +55423,4416,Female,Loyal Customer,29,Business travel,Business,2987,5,5,5,5,3,3,3,3,3,3,5,5,5,3,0,0.0,satisfied +55424,126281,Male,Loyal Customer,30,Personal Travel,Eco,650,3,4,3,3,3,3,3,3,2,2,4,4,2,3,0,0.0,neutral or dissatisfied +55425,128942,Male,Loyal Customer,31,Business travel,Business,3655,5,5,5,5,4,4,4,4,4,2,4,3,5,4,0,0.0,satisfied +55426,40882,Female,Loyal Customer,67,Personal Travel,Eco,588,4,4,4,3,3,5,4,3,3,4,3,4,3,4,15,5.0,satisfied +55427,19846,Male,Loyal Customer,36,Business travel,Eco,585,5,2,2,2,5,5,5,5,1,3,5,5,5,5,31,63.0,satisfied +55428,20836,Female,disloyal Customer,50,Business travel,Eco,457,3,4,3,4,2,3,2,2,2,1,3,2,3,2,0,0.0,neutral or dissatisfied +55429,24729,Female,disloyal Customer,25,Business travel,Eco Plus,406,3,3,3,4,4,3,4,4,2,5,4,1,3,4,1,,neutral or dissatisfied +55430,110230,Female,disloyal Customer,24,Business travel,Eco,1024,5,5,5,2,3,5,3,3,4,2,4,5,4,3,15,0.0,satisfied +55431,85934,Male,Loyal Customer,60,Business travel,Business,3108,2,1,1,1,5,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +55432,29692,Male,Loyal Customer,39,Business travel,Business,1542,4,4,4,4,1,5,1,4,4,4,4,3,4,5,0,11.0,satisfied +55433,44368,Female,Loyal Customer,58,Personal Travel,Eco,596,1,1,1,2,2,3,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +55434,14661,Female,disloyal Customer,27,Business travel,Eco Plus,112,3,3,3,3,3,3,2,3,2,5,5,3,2,3,49,40.0,neutral or dissatisfied +55435,72820,Female,Loyal Customer,59,Business travel,Business,2128,4,4,4,4,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +55436,128124,Female,Loyal Customer,56,Personal Travel,Eco,1587,4,5,4,3,4,4,4,4,4,4,4,3,4,3,4,0.0,neutral or dissatisfied +55437,46730,Male,Loyal Customer,45,Personal Travel,Eco,73,3,1,3,3,2,3,2,2,1,3,2,4,2,2,0,0.0,neutral or dissatisfied +55438,116182,Female,Loyal Customer,36,Personal Travel,Eco,447,3,3,3,1,3,3,1,3,2,1,2,5,4,3,0,0.0,neutral or dissatisfied +55439,72868,Female,disloyal Customer,68,Personal Travel,Eco,700,3,5,3,3,5,3,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +55440,57576,Male,Loyal Customer,52,Business travel,Business,1597,1,5,5,5,5,2,4,1,1,1,1,3,1,1,0,1.0,neutral or dissatisfied +55441,51522,Male,Loyal Customer,36,Business travel,Business,3302,1,3,3,3,5,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +55442,95113,Male,Loyal Customer,58,Personal Travel,Eco,239,3,1,3,4,2,3,2,2,1,1,4,4,3,2,32,26.0,neutral or dissatisfied +55443,77852,Male,Loyal Customer,47,Personal Travel,Eco Plus,696,3,4,3,4,3,3,3,3,3,2,5,3,5,3,43,46.0,neutral or dissatisfied +55444,30501,Female,Loyal Customer,44,Business travel,Business,484,1,2,2,2,5,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +55445,38579,Male,Loyal Customer,51,Personal Travel,Eco,2475,3,2,3,3,1,3,1,1,1,5,3,4,4,1,4,19.0,neutral or dissatisfied +55446,16144,Male,Loyal Customer,46,Personal Travel,Business,199,1,4,1,3,5,5,4,4,4,1,4,4,4,3,6,1.0,neutral or dissatisfied +55447,3303,Female,Loyal Customer,30,Business travel,Eco Plus,483,0,0,0,3,1,0,1,1,4,1,5,2,1,1,5,0.0,satisfied +55448,45494,Female,Loyal Customer,45,Personal Travel,Eco,522,4,4,4,3,3,4,5,5,5,4,5,3,5,4,23,39.0,neutral or dissatisfied +55449,83782,Male,Loyal Customer,46,Business travel,Business,2221,4,4,4,4,2,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +55450,87978,Male,Loyal Customer,44,Business travel,Business,3815,3,3,3,3,3,5,5,4,4,4,4,4,4,3,0,7.0,satisfied +55451,105179,Female,Loyal Customer,63,Personal Travel,Eco,220,3,3,3,3,4,2,3,3,3,3,3,5,3,1,23,11.0,neutral or dissatisfied +55452,57015,Male,Loyal Customer,61,Personal Travel,Eco,2425,3,2,3,3,3,3,3,4,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +55453,88517,Male,Loyal Customer,27,Personal Travel,Eco,515,4,5,4,1,3,4,3,3,5,4,5,4,5,3,18,0.0,neutral or dissatisfied +55454,30652,Male,Loyal Customer,18,Personal Travel,Eco,533,4,5,4,3,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +55455,101956,Female,disloyal Customer,38,Business travel,Eco,628,1,4,1,4,4,1,4,4,4,2,3,1,4,4,39,31.0,neutral or dissatisfied +55456,110217,Female,Loyal Customer,33,Personal Travel,Eco,1310,2,5,2,3,5,2,5,5,5,3,3,4,4,5,24,12.0,neutral or dissatisfied +55457,80196,Female,Loyal Customer,17,Personal Travel,Eco,2586,2,1,2,1,2,3,3,1,5,2,2,3,2,3,127,112.0,neutral or dissatisfied +55458,45550,Female,Loyal Customer,62,Personal Travel,Eco,566,3,4,3,4,3,4,5,2,2,3,2,4,2,4,77,69.0,neutral or dissatisfied +55459,98922,Female,Loyal Customer,60,Business travel,Business,569,1,2,2,2,4,3,2,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +55460,99000,Male,disloyal Customer,23,Business travel,Eco,479,2,4,2,1,4,2,4,4,3,5,4,4,4,4,123,119.0,neutral or dissatisfied +55461,1902,Male,Loyal Customer,40,Business travel,Business,2243,2,2,2,2,3,5,5,4,4,4,4,3,4,4,49,47.0,satisfied +55462,46890,Female,Loyal Customer,37,Business travel,Business,3979,5,5,5,5,3,1,4,4,4,4,4,2,4,3,7,5.0,satisfied +55463,115140,Male,Loyal Customer,60,Business travel,Business,2274,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +55464,27620,Male,Loyal Customer,46,Business travel,Eco Plus,954,4,4,4,4,4,4,4,4,1,2,1,1,5,4,0,0.0,satisfied +55465,70739,Female,Loyal Customer,48,Personal Travel,Eco,675,3,5,3,2,3,5,5,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +55466,90487,Female,Loyal Customer,60,Business travel,Business,250,0,0,0,2,4,4,5,4,4,5,5,4,4,3,0,0.0,satisfied +55467,92191,Male,Loyal Customer,19,Business travel,Business,1979,3,4,4,4,3,4,3,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +55468,68032,Male,Loyal Customer,52,Business travel,Business,2450,3,3,3,3,2,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +55469,26054,Male,Loyal Customer,35,Personal Travel,Eco,432,4,4,5,2,5,5,5,5,4,3,5,4,5,5,14,2.0,satisfied +55470,129616,Male,disloyal Customer,21,Business travel,Eco,447,2,5,2,4,2,2,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +55471,40679,Female,Loyal Customer,28,Business travel,Business,541,2,2,2,2,5,5,5,5,1,2,5,5,4,5,0,0.0,satisfied +55472,17552,Female,Loyal Customer,9,Personal Travel,Eco,908,2,5,2,4,5,2,3,5,5,4,5,4,5,5,0,7.0,neutral or dissatisfied +55473,61408,Female,Loyal Customer,27,Personal Travel,Eco,679,2,4,2,3,1,2,1,1,5,5,5,3,4,1,5,9.0,neutral or dissatisfied +55474,283,Male,disloyal Customer,40,Business travel,Business,802,4,4,4,1,2,4,2,2,3,2,4,4,5,2,11,4.0,satisfied +55475,126257,Male,disloyal Customer,21,Business travel,Eco,190,5,0,5,3,2,5,2,2,5,3,1,3,4,2,0,0.0,satisfied +55476,68732,Female,Loyal Customer,47,Personal Travel,Eco Plus,237,2,5,2,1,3,5,5,1,1,2,1,5,1,4,0,7.0,neutral or dissatisfied +55477,129225,Female,Loyal Customer,34,Business travel,Business,1464,2,2,3,2,4,5,5,3,3,4,3,4,3,5,2,0.0,satisfied +55478,61235,Female,disloyal Customer,34,Business travel,Eco,862,2,2,2,3,1,2,2,1,4,2,4,2,3,1,16,0.0,neutral or dissatisfied +55479,10670,Male,Loyal Customer,48,Business travel,Business,201,2,1,2,2,2,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +55480,36310,Male,disloyal Customer,24,Business travel,Eco,187,4,1,4,3,1,4,1,1,3,5,2,2,2,1,0,11.0,neutral or dissatisfied +55481,47305,Male,Loyal Customer,31,Business travel,Eco,558,0,0,0,3,4,0,1,4,5,1,2,5,4,4,0,0.0,satisfied +55482,15551,Female,Loyal Customer,59,Business travel,Business,3313,0,0,0,3,5,4,5,4,4,2,2,5,4,3,0,0.0,satisfied +55483,17102,Male,Loyal Customer,23,Personal Travel,Eco,416,3,5,3,4,3,3,3,3,3,4,2,2,2,3,0,0.0,neutral or dissatisfied +55484,128707,Female,Loyal Customer,54,Business travel,Business,1235,4,4,4,4,3,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +55485,81499,Female,Loyal Customer,29,Personal Travel,Eco,408,2,4,2,2,4,2,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +55486,115540,Female,Loyal Customer,38,Business travel,Business,2218,2,4,4,4,2,3,3,2,2,2,2,1,2,3,9,1.0,neutral or dissatisfied +55487,100965,Female,Loyal Customer,59,Personal Travel,Eco,1142,1,4,0,1,2,5,4,5,5,0,5,4,5,3,0,0.0,neutral or dissatisfied +55488,73920,Male,Loyal Customer,40,Business travel,Business,2330,2,2,5,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +55489,113985,Male,Loyal Customer,58,Business travel,Eco,1728,3,1,1,1,3,3,3,3,4,4,3,3,4,3,10,15.0,neutral or dissatisfied +55490,88253,Female,disloyal Customer,34,Business travel,Eco,270,2,4,2,3,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +55491,73975,Female,Loyal Customer,8,Personal Travel,Eco,2585,1,4,1,4,1,4,4,3,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +55492,68485,Female,disloyal Customer,29,Business travel,Eco,1067,2,2,2,3,1,2,1,1,3,3,3,1,4,1,3,0.0,neutral or dissatisfied +55493,33274,Female,Loyal Customer,40,Personal Travel,Eco Plus,101,1,4,0,1,4,0,4,4,3,2,4,4,4,4,0,2.0,neutral or dissatisfied +55494,64814,Female,Loyal Customer,45,Business travel,Eco,247,3,4,4,4,3,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +55495,77961,Female,Loyal Customer,36,Business travel,Business,332,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,3.0,satisfied +55496,63604,Female,disloyal Customer,23,Business travel,Business,1440,5,0,5,4,4,0,3,4,4,5,4,3,5,4,0,0.0,satisfied +55497,91022,Female,Loyal Customer,26,Personal Travel,Eco,442,3,5,3,3,4,3,4,4,4,1,2,3,5,4,0,0.0,neutral or dissatisfied +55498,109585,Male,Loyal Customer,38,Business travel,Business,3137,4,4,4,4,5,5,5,5,5,5,5,3,5,4,0,2.0,satisfied +55499,81678,Male,Loyal Customer,33,Business travel,Business,907,3,4,4,4,3,3,3,3,1,1,4,1,3,3,5,10.0,neutral or dissatisfied +55500,96026,Female,Loyal Customer,40,Business travel,Business,2218,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +55501,57037,Male,Loyal Customer,9,Personal Travel,Eco Plus,2454,1,2,1,4,1,2,2,3,4,3,3,2,4,2,36,6.0,neutral or dissatisfied +55502,77053,Female,Loyal Customer,52,Personal Travel,Eco,1156,1,4,1,4,2,4,4,4,4,1,4,2,4,2,2,0.0,neutral or dissatisfied +55503,6304,Male,Loyal Customer,66,Personal Travel,Business,296,2,4,2,3,3,5,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +55504,123522,Female,Loyal Customer,21,Personal Travel,Eco,2125,3,4,3,4,3,3,3,3,2,5,4,1,3,3,4,0.0,neutral or dissatisfied +55505,104554,Male,Loyal Customer,54,Personal Travel,Business,369,3,4,4,3,5,3,1,5,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +55506,82517,Male,disloyal Customer,27,Business travel,Eco,1749,1,0,0,4,4,1,4,4,1,1,2,3,3,4,22,49.0,neutral or dissatisfied +55507,102257,Female,Loyal Customer,44,Business travel,Business,2169,5,5,5,5,2,5,4,5,5,5,5,4,5,3,47,35.0,satisfied +55508,18096,Female,disloyal Customer,20,Business travel,Eco,488,2,3,2,4,2,2,2,2,4,4,4,1,3,2,67,60.0,neutral or dissatisfied +55509,120692,Male,Loyal Customer,51,Personal Travel,Eco,280,3,1,3,4,1,3,1,1,4,2,3,3,3,1,0,0.0,neutral or dissatisfied +55510,87785,Male,Loyal Customer,53,Business travel,Business,214,0,5,0,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +55511,94346,Male,Loyal Customer,33,Business travel,Business,1555,4,4,4,4,4,4,4,4,4,3,4,3,4,4,0,42.0,satisfied +55512,125285,Male,disloyal Customer,23,Business travel,Eco,678,3,3,3,3,3,3,4,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +55513,55073,Female,Loyal Customer,30,Business travel,Business,1635,2,3,3,3,2,2,2,2,3,1,2,2,4,2,0,0.0,neutral or dissatisfied +55514,112844,Male,Loyal Customer,60,Business travel,Business,1390,3,3,3,3,3,5,4,5,5,5,5,4,5,3,65,41.0,satisfied +55515,28938,Male,Loyal Customer,24,Business travel,Business,978,2,3,3,3,2,2,2,2,4,5,3,1,3,2,37,21.0,neutral or dissatisfied +55516,71184,Female,Loyal Customer,50,Business travel,Business,733,4,4,4,4,2,4,5,4,4,4,4,3,4,4,44,21.0,satisfied +55517,53589,Female,Loyal Customer,30,Business travel,Business,1768,1,1,1,1,5,5,5,1,3,4,3,5,2,5,151,134.0,satisfied +55518,129371,Male,Loyal Customer,35,Business travel,Business,2565,3,3,3,3,5,5,5,5,5,5,5,3,5,4,21,0.0,satisfied +55519,92880,Male,Loyal Customer,54,Business travel,Business,151,5,5,5,5,2,4,4,4,4,5,5,3,4,5,0,1.0,satisfied +55520,31114,Male,Loyal Customer,58,Business travel,Business,1765,2,2,2,2,3,1,5,5,5,5,5,3,5,1,0,16.0,satisfied +55521,39640,Male,disloyal Customer,50,Business travel,Eco,1297,3,3,3,3,2,3,2,2,5,3,5,2,3,2,112,101.0,neutral or dissatisfied +55522,70938,Female,disloyal Customer,52,Business travel,Eco,612,4,4,4,4,2,4,2,2,3,3,4,1,4,2,45,85.0,neutral or dissatisfied +55523,101259,Male,disloyal Customer,37,Business travel,Business,2176,1,1,1,3,3,1,1,3,4,5,4,4,5,3,52,61.0,neutral or dissatisfied +55524,41984,Male,Loyal Customer,44,Business travel,Business,2134,2,2,2,2,4,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +55525,128860,Female,Loyal Customer,40,Business travel,Business,2586,4,4,4,4,4,4,4,4,3,3,5,4,5,4,12,0.0,satisfied +55526,95108,Female,Loyal Customer,25,Personal Travel,Eco,319,3,4,3,4,2,3,2,2,2,1,5,5,2,2,0,0.0,neutral or dissatisfied +55527,119571,Female,Loyal Customer,50,Business travel,Business,3881,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +55528,65740,Female,disloyal Customer,40,Business travel,Business,936,1,1,1,4,5,1,5,5,3,2,3,1,3,5,39,39.0,neutral or dissatisfied +55529,90081,Female,Loyal Customer,50,Business travel,Business,2379,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,2.0,satisfied +55530,111984,Male,Loyal Customer,68,Personal Travel,Eco,770,4,4,4,1,5,4,5,5,4,3,5,4,5,5,45,38.0,neutral or dissatisfied +55531,59066,Male,Loyal Customer,29,Business travel,Business,1726,2,1,1,1,2,2,2,2,1,2,2,3,3,2,11,0.0,neutral or dissatisfied +55532,53576,Male,Loyal Customer,16,Business travel,Business,1195,4,4,5,4,5,5,5,5,4,5,1,1,3,5,5,0.0,satisfied +55533,60172,Male,Loyal Customer,34,Personal Travel,Eco,1144,3,3,3,3,1,3,1,1,2,5,4,5,5,1,9,0.0,neutral or dissatisfied +55534,124116,Male,Loyal Customer,40,Business travel,Business,529,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +55535,85186,Female,Loyal Customer,51,Business travel,Eco,689,3,2,2,2,4,4,3,3,3,3,3,3,3,3,10,19.0,neutral or dissatisfied +55536,41541,Male,Loyal Customer,43,Business travel,Business,1428,1,2,2,2,5,4,4,1,1,1,1,3,1,1,14,9.0,neutral or dissatisfied +55537,87779,Female,Loyal Customer,60,Business travel,Business,214,1,4,4,4,2,3,3,3,3,3,1,3,3,3,0,0.0,neutral or dissatisfied +55538,119679,Male,Loyal Customer,45,Business travel,Business,1325,4,4,4,4,3,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +55539,48605,Male,Loyal Customer,15,Personal Travel,Eco,916,3,1,3,2,2,3,2,2,4,3,2,1,2,2,0,0.0,neutral or dissatisfied +55540,18776,Female,Loyal Customer,50,Business travel,Business,448,1,1,1,1,1,3,3,5,5,5,5,2,5,1,63,50.0,satisfied +55541,12897,Female,Loyal Customer,53,Business travel,Business,979,4,4,4,4,4,4,1,5,5,5,5,4,5,5,0,0.0,satisfied +55542,62529,Male,disloyal Customer,27,Business travel,Business,1449,4,4,4,3,1,4,1,1,5,5,4,3,4,1,16,18.0,satisfied +55543,109431,Female,Loyal Customer,41,Business travel,Business,2727,2,2,2,2,4,4,3,2,2,2,2,4,2,4,1,0.0,neutral or dissatisfied +55544,39473,Male,Loyal Customer,42,Business travel,Eco,867,4,5,5,5,4,4,4,4,4,5,3,3,3,4,11,3.0,satisfied +55545,85453,Female,disloyal Customer,23,Business travel,Eco,152,1,1,1,4,4,1,1,4,2,1,4,3,3,4,8,16.0,neutral or dissatisfied +55546,125766,Female,Loyal Customer,37,Business travel,Business,992,2,2,2,2,3,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +55547,52550,Female,Loyal Customer,51,Business travel,Business,3562,0,3,0,3,5,4,1,5,5,5,5,1,5,4,0,0.0,satisfied +55548,3829,Female,Loyal Customer,31,Business travel,Business,2851,2,2,2,2,2,2,2,2,3,2,3,1,3,2,89,73.0,neutral or dissatisfied +55549,4747,Female,Loyal Customer,33,Personal Travel,Eco,888,3,2,3,4,3,3,3,3,4,2,3,2,3,3,51,16.0,neutral or dissatisfied +55550,8096,Male,Loyal Customer,39,Business travel,Business,125,5,5,5,5,2,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +55551,111222,Female,Loyal Customer,52,Business travel,Eco,1047,1,3,2,3,4,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +55552,18748,Male,disloyal Customer,20,Business travel,Eco,767,3,3,3,3,5,3,4,5,5,5,4,4,4,5,4,0.0,neutral or dissatisfied +55553,30794,Female,Loyal Customer,70,Business travel,Business,701,2,2,2,2,2,3,4,2,2,2,2,4,2,4,92,76.0,neutral or dissatisfied +55554,38864,Female,Loyal Customer,59,Business travel,Eco,2300,5,4,4,4,4,3,2,5,5,5,5,1,5,1,11,0.0,satisfied +55555,4451,Male,Loyal Customer,38,Business travel,Eco Plus,762,5,2,2,2,5,4,5,5,1,4,3,4,4,5,19,12.0,neutral or dissatisfied +55556,80151,Female,Loyal Customer,53,Business travel,Business,2475,1,5,5,5,2,1,1,2,4,3,2,1,4,1,6,6.0,neutral or dissatisfied +55557,27218,Male,Loyal Customer,53,Personal Travel,Business,1024,2,5,2,2,4,3,2,3,3,2,3,5,3,2,0,12.0,neutral or dissatisfied +55558,2079,Female,disloyal Customer,25,Business travel,Eco,412,5,2,5,3,1,5,1,1,2,4,5,2,1,1,0,0.0,satisfied +55559,75333,Female,Loyal Customer,50,Business travel,Business,3845,5,5,5,5,5,5,5,3,1,4,5,5,1,5,0,3.0,satisfied +55560,129633,Male,disloyal Customer,22,Business travel,Eco,308,3,4,3,2,2,3,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +55561,8953,Male,Loyal Customer,59,Business travel,Business,328,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +55562,79400,Female,disloyal Customer,18,Business travel,Eco,502,3,5,3,5,4,3,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +55563,78469,Male,Loyal Customer,46,Business travel,Business,3338,4,4,4,4,3,4,4,4,4,4,4,4,4,3,1,10.0,satisfied +55564,30769,Male,Loyal Customer,44,Business travel,Business,834,3,4,3,3,3,4,5,5,5,5,5,4,5,3,41,36.0,satisfied +55565,60678,Male,Loyal Customer,55,Business travel,Business,1728,4,4,4,4,3,4,5,5,5,5,5,5,5,5,6,0.0,satisfied +55566,19901,Female,Loyal Customer,60,Business travel,Business,315,2,2,2,2,1,2,5,4,4,4,4,3,4,5,0,0.0,satisfied +55567,111977,Male,Loyal Customer,16,Business travel,Business,770,1,1,5,1,1,1,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +55568,12891,Female,Loyal Customer,36,Business travel,Eco,359,5,3,3,3,5,5,5,5,5,3,5,1,1,5,8,18.0,satisfied +55569,38680,Male,Loyal Customer,10,Personal Travel,Eco,2689,3,5,3,3,4,3,4,4,4,4,4,5,5,4,0,3.0,neutral or dissatisfied +55570,100395,Male,Loyal Customer,34,Personal Travel,Eco,1073,4,5,3,1,5,3,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +55571,103148,Male,disloyal Customer,24,Business travel,Eco,491,2,4,2,4,3,2,3,3,4,5,5,3,5,3,0,7.0,neutral or dissatisfied +55572,92464,Female,disloyal Customer,28,Business travel,Eco,2139,3,3,3,1,5,3,5,5,3,2,1,3,2,5,4,0.0,neutral or dissatisfied +55573,11028,Female,Loyal Customer,22,Business travel,Eco,301,5,3,3,3,5,5,4,5,4,3,5,5,4,5,0,0.0,satisfied +55574,58091,Male,disloyal Customer,40,Business travel,Eco,589,3,1,3,3,4,3,4,4,2,5,3,1,4,4,16,4.0,neutral or dissatisfied +55575,70921,Female,Loyal Customer,39,Business travel,Business,2121,3,3,3,3,4,4,4,5,3,5,5,4,3,4,149,152.0,satisfied +55576,106840,Female,disloyal Customer,49,Business travel,Business,1132,5,5,5,5,3,5,3,3,3,3,4,3,4,3,28,1.0,satisfied +55577,61866,Male,Loyal Customer,53,Personal Travel,Business,2521,0,3,0,3,2,4,4,3,3,3,3,3,3,1,0,3.0,satisfied +55578,119340,Female,Loyal Customer,22,Personal Travel,Eco,214,4,3,4,4,4,4,4,4,3,2,1,2,1,4,0,0.0,satisfied +55579,48117,Female,Loyal Customer,54,Business travel,Eco,236,4,4,4,4,4,5,2,4,4,4,4,5,4,4,0,0.0,satisfied +55580,91355,Female,Loyal Customer,37,Personal Travel,Eco Plus,515,2,4,2,1,3,2,2,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +55581,110207,Male,disloyal Customer,24,Business travel,Eco,188,3,4,3,2,1,3,1,1,5,4,5,1,3,1,34,23.0,neutral or dissatisfied +55582,59071,Female,Loyal Customer,22,Business travel,Eco,1726,3,4,3,3,3,3,2,3,2,4,2,3,3,3,18,2.0,neutral or dissatisfied +55583,74241,Male,Loyal Customer,29,Business travel,Business,1709,3,5,5,5,3,3,3,3,2,4,4,1,4,3,0,0.0,neutral or dissatisfied +55584,112457,Female,disloyal Customer,35,Business travel,Eco,846,2,1,1,3,3,1,3,3,3,2,4,3,3,3,28,24.0,neutral or dissatisfied +55585,124791,Male,Loyal Customer,39,Business travel,Business,280,4,4,4,4,2,5,4,4,4,4,4,3,4,4,87,90.0,satisfied +55586,48056,Male,Loyal Customer,33,Personal Travel,Eco,677,4,4,4,4,1,4,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +55587,8325,Female,Loyal Customer,41,Personal Travel,Eco Plus,335,3,5,3,1,2,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +55588,125205,Male,Loyal Customer,43,Business travel,Business,3980,2,3,3,3,5,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +55589,17842,Male,disloyal Customer,21,Business travel,Eco,505,3,0,3,4,2,3,2,2,5,5,2,2,2,2,0,0.0,neutral or dissatisfied +55590,70760,Male,disloyal Customer,21,Business travel,Eco,328,3,0,3,1,1,3,1,1,5,4,4,5,5,1,23,113.0,neutral or dissatisfied +55591,111538,Male,Loyal Customer,50,Business travel,Business,2792,5,5,5,5,4,5,5,2,2,2,2,4,2,5,7,0.0,satisfied +55592,50108,Female,Loyal Customer,44,Business travel,Eco,421,2,2,2,2,2,2,2,2,2,2,2,2,2,2,110,139.0,neutral or dissatisfied +55593,60390,Female,Loyal Customer,76,Business travel,Business,1622,3,4,4,4,2,3,3,3,3,3,3,3,3,1,3,0.0,neutral or dissatisfied +55594,104529,Female,Loyal Customer,23,Business travel,Business,1613,2,4,4,4,2,2,2,2,1,4,4,2,4,2,1,0.0,neutral or dissatisfied +55595,8015,Male,disloyal Customer,20,Business travel,Eco,530,2,4,2,1,2,2,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +55596,45834,Male,Loyal Customer,35,Personal Travel,Eco,216,3,0,3,3,2,3,2,2,3,5,3,3,5,2,0,0.0,neutral or dissatisfied +55597,26097,Female,Loyal Customer,18,Personal Travel,Eco,591,4,5,3,3,5,3,5,5,5,5,4,3,5,5,0,2.0,neutral or dissatisfied +55598,52139,Male,disloyal Customer,39,Business travel,Business,493,5,5,5,3,3,5,3,3,3,4,4,5,5,3,9,0.0,satisfied +55599,24298,Male,Loyal Customer,66,Business travel,Eco Plus,134,2,1,1,1,1,2,1,1,4,4,3,2,5,1,0,0.0,satisfied +55600,66106,Male,Loyal Customer,49,Business travel,Business,3553,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +55601,28916,Male,Loyal Customer,56,Business travel,Business,672,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +55602,25782,Female,disloyal Customer,29,Business travel,Eco,762,2,2,2,1,1,2,1,1,5,1,4,1,5,1,0,0.0,neutral or dissatisfied +55603,103783,Female,Loyal Customer,42,Business travel,Business,3543,2,4,3,3,4,4,3,2,2,2,2,4,2,3,0,1.0,neutral or dissatisfied +55604,44973,Female,disloyal Customer,27,Business travel,Eco,118,2,0,2,4,2,2,5,2,2,4,3,5,5,2,0,0.0,neutral or dissatisfied +55605,78421,Female,Loyal Customer,60,Business travel,Business,453,3,3,3,3,5,5,5,3,3,3,3,3,3,5,2,0.0,satisfied +55606,101553,Female,Loyal Customer,27,Personal Travel,Eco,345,2,5,2,4,1,2,1,1,1,2,2,3,4,1,0,0.0,neutral or dissatisfied +55607,100319,Male,Loyal Customer,29,Business travel,Business,2419,5,5,5,5,2,2,2,2,3,3,5,5,4,2,0,0.0,satisfied +55608,23550,Male,Loyal Customer,49,Business travel,Eco,770,5,2,2,2,5,5,5,5,5,1,2,1,2,5,16,3.0,satisfied +55609,67578,Female,disloyal Customer,54,Business travel,Business,1235,4,4,4,2,1,4,1,1,3,4,4,3,4,1,38,17.0,satisfied +55610,32881,Female,Loyal Customer,53,Personal Travel,Eco,163,3,5,3,1,4,4,4,4,4,3,1,5,4,3,0,0.0,neutral or dissatisfied +55611,117659,Female,disloyal Customer,22,Business travel,Business,1449,4,5,4,4,1,4,1,1,4,4,4,4,4,1,27,22.0,satisfied +55612,31448,Male,Loyal Customer,44,Business travel,Business,3872,5,5,5,5,4,4,4,5,3,5,5,4,5,4,145,140.0,satisfied +55613,95624,Female,Loyal Customer,61,Personal Travel,Eco,756,1,5,1,2,2,4,5,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +55614,73802,Female,disloyal Customer,18,Business travel,Eco,204,3,0,2,2,5,2,5,5,4,5,3,2,3,5,0,0.0,neutral or dissatisfied +55615,38980,Male,disloyal Customer,22,Business travel,Business,230,0,0,0,1,4,0,4,4,1,4,5,1,2,4,0,0.0,satisfied +55616,119469,Male,Loyal Customer,39,Business travel,Business,2043,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +55617,36950,Male,Loyal Customer,45,Personal Travel,Business,901,3,3,3,1,5,4,2,3,3,3,3,4,3,2,0,29.0,neutral or dissatisfied +55618,85100,Female,disloyal Customer,32,Business travel,Business,874,2,2,2,3,5,2,5,5,5,3,5,3,5,5,4,0.0,neutral or dissatisfied +55619,51205,Female,disloyal Customer,61,Business travel,Eco Plus,326,3,3,3,4,3,3,3,3,5,5,2,1,3,3,71,77.0,neutral or dissatisfied +55620,17208,Female,Loyal Customer,49,Personal Travel,Eco,694,4,4,4,1,5,4,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +55621,56507,Male,Loyal Customer,58,Business travel,Business,1593,3,3,3,3,3,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +55622,93195,Male,disloyal Customer,30,Business travel,Business,896,4,4,4,3,4,4,4,4,4,3,5,3,5,4,0,25.0,neutral or dissatisfied +55623,93440,Female,disloyal Customer,24,Business travel,Business,271,4,0,4,3,2,4,2,2,2,5,1,1,2,2,50,45.0,satisfied +55624,91562,Male,Loyal Customer,44,Personal Travel,Eco,680,3,1,3,3,1,3,1,1,1,1,3,1,4,1,10,47.0,neutral or dissatisfied +55625,82708,Male,Loyal Customer,28,Personal Travel,Eco,632,4,5,4,1,2,4,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +55626,60721,Female,Loyal Customer,9,Personal Travel,Eco,1605,4,4,4,4,2,4,2,2,4,2,5,4,5,2,59,47.0,neutral or dissatisfied +55627,103843,Male,disloyal Customer,46,Business travel,Business,1072,3,3,3,3,3,3,5,3,3,3,4,1,4,3,10,0.0,neutral or dissatisfied +55628,14478,Male,Loyal Customer,22,Business travel,Business,2110,5,5,5,5,3,3,3,3,5,3,3,3,5,3,43,34.0,satisfied +55629,10453,Female,Loyal Customer,48,Business travel,Business,201,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +55630,124337,Male,Loyal Customer,61,Business travel,Business,1972,2,2,2,2,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +55631,5838,Female,disloyal Customer,37,Business travel,Eco Plus,273,1,1,1,4,4,1,3,4,2,3,3,3,3,4,0,0.0,neutral or dissatisfied +55632,128567,Female,Loyal Customer,44,Business travel,Business,3549,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +55633,31660,Male,disloyal Customer,25,Business travel,Eco,862,2,3,3,4,2,3,2,2,1,5,3,4,3,2,0,0.0,neutral or dissatisfied +55634,101537,Male,Loyal Customer,55,Personal Travel,Eco,345,4,4,4,3,5,4,5,5,5,2,5,5,5,5,7,0.0,neutral or dissatisfied +55635,112580,Male,Loyal Customer,52,Business travel,Business,2102,4,4,4,4,4,5,5,4,4,4,4,4,4,4,17,0.0,satisfied +55636,55718,Female,Loyal Customer,43,Business travel,Business,1601,3,3,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +55637,116662,Female,disloyal Customer,45,Business travel,Business,325,5,5,5,2,3,5,3,3,5,4,5,5,5,3,2,0.0,satisfied +55638,48241,Male,Loyal Customer,61,Personal Travel,Eco,236,3,5,3,2,2,3,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +55639,53468,Female,Loyal Customer,30,Business travel,Business,2419,2,2,2,2,2,2,2,2,1,2,3,3,3,2,4,11.0,neutral or dissatisfied +55640,121281,Female,Loyal Customer,15,Personal Travel,Eco Plus,2075,3,5,3,3,5,3,5,5,3,2,4,3,5,5,2,0.0,neutral or dissatisfied +55641,124215,Male,Loyal Customer,7,Personal Travel,Eco,2176,3,2,3,3,4,3,1,4,1,3,4,4,3,4,11,12.0,neutral or dissatisfied +55642,23028,Male,Loyal Customer,60,Business travel,Eco,927,5,1,1,1,5,5,5,5,1,1,1,4,2,5,0,0.0,satisfied +55643,93281,Female,Loyal Customer,53,Personal Travel,Eco,867,3,1,3,4,5,4,4,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +55644,9567,Female,Loyal Customer,41,Business travel,Business,288,3,1,1,1,3,3,3,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +55645,73925,Female,Loyal Customer,50,Business travel,Business,2342,3,3,3,3,2,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +55646,28430,Female,Loyal Customer,64,Business travel,Eco,2496,4,2,2,2,4,4,4,5,3,4,5,4,4,4,0,0.0,satisfied +55647,13443,Female,Loyal Customer,39,Business travel,Business,1763,2,2,2,2,4,5,3,4,4,4,4,2,4,2,0,0.0,satisfied +55648,109298,Male,Loyal Customer,47,Business travel,Business,2549,2,2,2,2,4,5,4,3,3,4,3,3,3,4,1,0.0,satisfied +55649,75193,Female,Loyal Customer,55,Business travel,Eco,1744,4,5,5,5,1,4,3,4,4,4,4,2,4,3,7,23.0,neutral or dissatisfied +55650,64633,Male,Loyal Customer,54,Business travel,Business,1521,5,5,5,5,4,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +55651,17276,Female,Loyal Customer,44,Business travel,Eco Plus,872,4,1,1,1,3,5,2,4,4,4,4,5,4,2,43,21.0,satisfied +55652,35503,Female,Loyal Customer,20,Personal Travel,Eco,1056,4,5,4,3,5,4,5,5,5,5,4,4,5,5,9,2.0,neutral or dissatisfied +55653,79959,Male,Loyal Customer,44,Business travel,Business,3849,4,3,3,3,1,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +55654,8924,Female,Loyal Customer,52,Business travel,Eco Plus,261,5,4,4,4,4,3,4,4,4,5,4,4,4,5,0,0.0,satisfied +55655,72458,Female,Loyal Customer,19,Business travel,Business,2274,1,1,4,1,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +55656,45302,Male,Loyal Customer,34,Business travel,Eco,150,5,5,5,5,5,5,5,5,3,4,5,2,1,5,0,0.0,satisfied +55657,107291,Male,Loyal Customer,44,Business travel,Business,2196,2,4,4,4,1,2,2,2,2,2,2,3,2,3,44,34.0,neutral or dissatisfied +55658,33826,Male,Loyal Customer,55,Business travel,Eco Plus,1521,1,5,5,5,1,1,1,1,2,3,3,1,3,1,0,0.0,neutral or dissatisfied +55659,29844,Male,Loyal Customer,50,Business travel,Eco,725,4,3,3,3,4,4,4,4,5,3,1,5,5,4,0,0.0,satisfied +55660,52000,Female,Loyal Customer,29,Business travel,Business,3736,2,3,5,3,2,2,2,2,1,2,3,4,4,2,0,8.0,neutral or dissatisfied +55661,39739,Female,Loyal Customer,49,Personal Travel,Eco,205,3,1,3,3,1,4,3,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +55662,67349,Male,Loyal Customer,11,Personal Travel,Eco,1471,2,4,2,3,3,2,4,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +55663,61718,Male,Loyal Customer,52,Business travel,Business,1464,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +55664,32249,Male,Loyal Customer,37,Business travel,Business,2042,1,1,1,1,2,4,3,4,4,4,5,2,4,4,0,0.0,satisfied +55665,45123,Female,Loyal Customer,45,Personal Travel,Eco,157,2,3,2,4,4,4,4,5,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +55666,57414,Male,Loyal Customer,51,Business travel,Business,3977,5,5,5,5,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +55667,14984,Female,Loyal Customer,67,Personal Travel,Eco,1080,4,5,4,1,3,4,5,5,5,4,4,4,5,5,0,11.0,neutral or dissatisfied +55668,115950,Female,Loyal Customer,32,Personal Travel,Eco,480,1,3,1,3,2,1,4,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +55669,46297,Male,Loyal Customer,29,Business travel,Business,2739,4,4,4,4,5,5,5,5,5,5,2,1,2,5,0,0.0,satisfied +55670,65568,Male,disloyal Customer,24,Business travel,Business,237,4,4,4,4,1,4,1,1,4,3,4,4,5,1,1,0.0,satisfied +55671,125906,Female,Loyal Customer,65,Personal Travel,Eco,920,4,2,4,4,3,3,4,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +55672,65654,Female,Loyal Customer,31,Business travel,Business,1021,2,2,2,2,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +55673,102305,Male,Loyal Customer,43,Business travel,Business,258,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +55674,67081,Female,Loyal Customer,46,Business travel,Business,1121,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +55675,6009,Female,Loyal Customer,62,Business travel,Business,2292,3,2,2,2,2,2,2,3,3,3,3,4,3,4,0,2.0,neutral or dissatisfied +55676,93441,Male,Loyal Customer,54,Personal Travel,Eco,672,2,4,2,1,3,2,2,3,3,5,4,4,4,3,9,0.0,neutral or dissatisfied +55677,115797,Male,Loyal Customer,62,Business travel,Eco,446,4,2,2,2,4,4,4,4,5,1,5,3,1,4,39,34.0,satisfied +55678,84513,Female,Loyal Customer,54,Business travel,Business,2556,2,2,2,2,2,4,5,2,2,3,2,4,2,3,3,0.0,satisfied +55679,53068,Male,Loyal Customer,48,Personal Travel,Eco,1208,3,3,3,4,4,3,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +55680,20421,Male,disloyal Customer,36,Business travel,Eco,299,3,2,4,4,5,4,5,5,2,1,3,4,4,5,49,45.0,neutral or dissatisfied +55681,126184,Female,Loyal Customer,52,Business travel,Business,2966,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,1.0,satisfied +55682,17908,Male,Loyal Customer,26,Business travel,Business,1548,4,4,4,4,5,5,5,5,1,4,1,3,1,5,27,33.0,satisfied +55683,114561,Female,Loyal Customer,64,Personal Travel,Business,404,3,5,3,3,4,5,5,3,3,3,2,3,3,3,1,0.0,neutral or dissatisfied +55684,36501,Female,Loyal Customer,42,Business travel,Eco,1121,5,2,1,2,1,4,2,5,5,5,5,4,5,5,58,46.0,satisfied +55685,81703,Female,Loyal Customer,37,Personal Travel,Eco,907,1,4,2,3,3,2,3,3,4,2,5,4,5,3,1,0.0,neutral or dissatisfied +55686,2891,Male,Loyal Customer,66,Personal Travel,Eco,409,3,4,3,2,3,3,1,3,5,5,4,5,4,3,32,41.0,neutral or dissatisfied +55687,13755,Female,Loyal Customer,24,Personal Travel,Eco,401,1,2,1,4,1,3,3,1,1,4,4,3,1,3,214,201.0,neutral or dissatisfied +55688,49681,Male,Loyal Customer,39,Business travel,Eco,110,4,1,1,1,4,4,4,4,2,3,3,4,1,4,0,0.0,satisfied +55689,80371,Male,Loyal Customer,53,Business travel,Business,422,5,5,5,5,3,4,4,4,4,3,4,5,4,5,0,0.0,satisfied +55690,106010,Female,Loyal Customer,23,Personal Travel,Eco,1999,2,3,1,1,2,1,2,2,2,1,5,3,1,2,14,24.0,neutral or dissatisfied +55691,95559,Female,Loyal Customer,70,Personal Travel,Eco Plus,239,2,3,2,3,1,3,3,2,2,2,5,2,2,1,1,1.0,neutral or dissatisfied +55692,99039,Male,Loyal Customer,10,Personal Travel,Eco Plus,1009,2,5,2,2,4,2,5,4,5,4,2,1,2,4,0,0.0,neutral or dissatisfied +55693,102381,Female,disloyal Customer,50,Business travel,Eco,223,2,4,2,3,1,2,1,1,2,1,4,3,4,1,0,0.0,neutral or dissatisfied +55694,63733,Female,Loyal Customer,61,Personal Travel,Eco,1660,3,3,4,3,2,5,3,3,3,4,3,5,3,1,0,0.0,neutral or dissatisfied +55695,79185,Male,Loyal Customer,50,Personal Travel,Eco,2422,1,2,1,4,1,4,4,2,2,3,3,4,2,4,0,0.0,neutral or dissatisfied +55696,18813,Male,Loyal Customer,47,Business travel,Business,500,3,3,3,3,4,3,3,3,3,3,3,1,3,4,0,1.0,neutral or dissatisfied +55697,63761,Male,Loyal Customer,48,Personal Travel,Eco,2422,2,5,2,5,4,2,5,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +55698,23427,Female,disloyal Customer,22,Business travel,Eco,1201,2,2,2,3,5,2,2,5,4,3,5,2,2,5,0,0.0,neutral or dissatisfied +55699,126526,Female,Loyal Customer,59,Business travel,Business,2079,2,5,5,5,5,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +55700,123913,Female,Loyal Customer,62,Personal Travel,Eco,544,4,5,4,4,2,1,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +55701,61469,Female,Loyal Customer,64,Business travel,Business,2253,4,5,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +55702,76969,Female,Loyal Customer,16,Personal Travel,Eco,1990,1,5,1,3,2,1,1,2,5,3,3,1,4,2,2,7.0,neutral or dissatisfied +55703,21903,Female,disloyal Customer,29,Business travel,Eco,503,3,4,3,4,4,3,4,4,3,4,2,3,3,4,0,0.0,neutral or dissatisfied +55704,35656,Female,Loyal Customer,31,Business travel,Eco,2569,5,5,5,5,5,5,5,2,4,5,4,5,1,5,29,13.0,satisfied +55705,61267,Male,Loyal Customer,68,Personal Travel,Eco,862,3,4,4,4,4,4,1,4,4,5,4,4,5,4,43,54.0,neutral or dissatisfied +55706,126470,Male,disloyal Customer,11,Business travel,Eco,1265,4,4,4,2,3,4,3,3,1,3,1,3,2,3,0,1.0,neutral or dissatisfied +55707,47982,Male,Loyal Customer,8,Personal Travel,Eco,834,4,4,4,3,2,4,1,2,1,3,1,4,3,2,0,0.0,neutral or dissatisfied +55708,27629,Male,Loyal Customer,25,Business travel,Eco Plus,697,4,5,5,5,4,4,4,4,3,1,5,1,3,4,0,0.0,satisfied +55709,61385,Male,Loyal Customer,53,Business travel,Eco,679,3,4,1,4,3,3,3,3,4,1,4,1,4,3,16,9.0,neutral or dissatisfied +55710,92981,Male,Loyal Customer,29,Business travel,Business,738,4,4,4,4,4,4,4,4,5,3,5,3,4,4,13,5.0,satisfied +55711,13617,Male,Loyal Customer,49,Business travel,Business,1014,2,2,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +55712,61144,Female,Loyal Customer,59,Business travel,Business,2635,5,5,1,5,2,5,5,5,5,5,5,5,5,4,7,0.0,satisfied +55713,72415,Female,disloyal Customer,31,Business travel,Eco,985,3,3,3,3,4,3,2,4,1,4,4,1,3,4,64,85.0,neutral or dissatisfied +55714,30781,Male,Loyal Customer,47,Business travel,Eco,895,5,2,2,2,5,5,5,5,5,5,5,3,1,5,0,0.0,satisfied +55715,43707,Male,Loyal Customer,45,Business travel,Business,489,3,5,5,5,2,4,3,3,3,3,3,2,3,1,7,0.0,neutral or dissatisfied +55716,97864,Male,disloyal Customer,38,Business travel,Business,391,2,3,3,3,2,3,2,2,5,3,5,5,4,2,43,23.0,neutral or dissatisfied +55717,65634,Male,Loyal Customer,29,Personal Travel,Eco,237,2,5,2,2,5,2,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +55718,24178,Female,Loyal Customer,42,Business travel,Business,151,3,3,3,3,5,3,3,4,4,4,4,2,4,5,106,104.0,satisfied +55719,17084,Female,Loyal Customer,43,Business travel,Business,3291,2,2,2,2,1,4,5,5,5,5,5,4,5,2,0,0.0,satisfied +55720,91295,Male,Loyal Customer,49,Business travel,Business,406,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +55721,104496,Male,Loyal Customer,40,Personal Travel,Eco,860,5,1,5,3,3,5,3,3,4,3,3,1,3,3,0,0.0,satisfied +55722,23336,Male,Loyal Customer,23,Personal Travel,Eco,563,4,4,4,1,1,4,1,1,3,3,4,4,4,1,52,54.0,neutral or dissatisfied +55723,98356,Male,Loyal Customer,29,Business travel,Business,1189,5,5,5,5,3,4,3,3,5,4,5,3,4,3,0,0.0,satisfied +55724,29184,Female,Loyal Customer,9,Personal Travel,Eco Plus,671,3,4,4,3,2,4,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +55725,32414,Female,Loyal Customer,29,Business travel,Business,3676,2,1,1,1,2,2,2,2,1,2,4,4,4,2,0,0.0,neutral or dissatisfied +55726,41631,Male,Loyal Customer,13,Personal Travel,Eco,374,1,3,1,3,2,1,2,2,1,3,4,4,3,2,102,101.0,neutral or dissatisfied +55727,94995,Male,Loyal Customer,23,Personal Travel,Eco,248,1,5,0,2,4,0,4,4,4,2,5,5,5,4,39,36.0,neutral or dissatisfied +55728,26021,Male,Loyal Customer,16,Personal Travel,Eco,425,4,3,5,4,3,5,3,3,5,3,4,5,4,3,7,0.0,satisfied +55729,48233,Female,Loyal Customer,21,Personal Travel,Eco,236,3,4,3,1,3,3,3,3,5,4,5,3,4,3,2,0.0,neutral or dissatisfied +55730,86392,Female,disloyal Customer,35,Business travel,Business,762,2,1,1,1,3,1,3,3,4,4,4,3,4,3,14,25.0,neutral or dissatisfied +55731,104420,Male,disloyal Customer,31,Business travel,Eco,1036,1,1,1,4,4,1,3,4,2,4,4,3,4,4,2,0.0,neutral or dissatisfied +55732,64670,Male,Loyal Customer,49,Business travel,Business,3846,3,3,3,3,5,4,5,4,4,4,4,5,4,4,66,60.0,satisfied +55733,103584,Female,Loyal Customer,45,Business travel,Business,2653,3,5,5,5,2,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +55734,40861,Female,Loyal Customer,31,Personal Travel,Eco,590,1,5,1,2,2,1,2,2,2,1,3,2,1,2,0,0.0,neutral or dissatisfied +55735,83462,Female,Loyal Customer,39,Business travel,Business,946,3,3,3,3,2,5,4,3,3,3,3,5,3,3,0,10.0,satisfied +55736,22236,Male,Loyal Customer,41,Business travel,Business,238,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +55737,25481,Male,Loyal Customer,34,Business travel,Business,3110,3,3,3,3,5,4,2,5,5,5,5,2,5,2,37,19.0,satisfied +55738,75513,Female,Loyal Customer,49,Business travel,Business,748,5,5,5,5,3,5,4,5,5,5,5,4,5,3,12,14.0,satisfied +55739,41287,Male,Loyal Customer,47,Business travel,Business,3137,4,2,4,2,3,4,4,4,4,4,4,3,4,2,0,5.0,neutral or dissatisfied +55740,89447,Female,Loyal Customer,65,Personal Travel,Eco,134,4,5,4,3,3,3,5,2,2,4,2,2,2,2,41,38.0,neutral or dissatisfied +55741,88813,Female,disloyal Customer,23,Business travel,Eco,581,3,2,3,3,1,3,1,1,3,4,4,2,3,1,10,25.0,neutral or dissatisfied +55742,92756,Female,Loyal Customer,53,Personal Travel,Eco,1276,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +55743,25589,Female,disloyal Customer,22,Business travel,Eco,474,4,0,4,3,5,4,5,5,3,4,2,1,1,5,27,19.0,satisfied +55744,39129,Female,Loyal Customer,69,Business travel,Eco,228,3,3,3,3,4,4,3,3,3,3,3,4,3,1,5,13.0,neutral or dissatisfied +55745,20433,Female,Loyal Customer,39,Business travel,Eco Plus,299,4,3,3,3,4,4,4,4,2,3,3,4,1,4,137,143.0,neutral or dissatisfied +55746,43613,Female,Loyal Customer,49,Business travel,Business,190,5,5,5,5,4,5,1,5,5,5,5,1,5,1,0,27.0,satisfied +55747,116465,Male,Loyal Customer,51,Personal Travel,Eco,417,3,4,5,3,3,5,2,3,5,1,3,2,3,3,3,4.0,neutral or dissatisfied +55748,68315,Male,disloyal Customer,27,Business travel,Business,863,4,5,5,2,3,5,3,3,4,4,5,3,4,3,0,0.0,satisfied +55749,53474,Male,Loyal Customer,8,Business travel,Business,2253,2,4,5,4,2,2,2,2,1,5,3,2,3,2,11,0.0,neutral or dissatisfied +55750,88540,Female,Loyal Customer,15,Personal Travel,Eco,594,3,5,3,1,1,3,1,1,5,2,2,3,3,1,4,8.0,neutral or dissatisfied +55751,46366,Male,Loyal Customer,48,Business travel,Business,3918,3,4,2,4,1,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +55752,53313,Male,Loyal Customer,9,Personal Travel,Eco,758,2,5,2,1,4,2,4,4,3,2,4,3,3,4,0,1.0,neutral or dissatisfied +55753,78398,Female,disloyal Customer,14,Business travel,Eco,980,5,5,5,3,3,5,3,3,5,5,5,3,5,3,0,0.0,satisfied +55754,47779,Female,Loyal Customer,52,Business travel,Business,3277,3,3,3,3,1,4,2,4,4,4,4,1,4,5,0,0.0,satisfied +55755,1557,Female,Loyal Customer,39,Personal Travel,Eco Plus,922,2,3,2,3,5,2,3,5,1,5,5,4,1,5,0,0.0,neutral or dissatisfied +55756,90629,Female,disloyal Customer,23,Business travel,Business,270,4,3,5,2,5,5,5,5,3,3,5,5,5,5,0,16.0,satisfied +55757,24697,Female,disloyal Customer,40,Business travel,Business,397,5,0,0,2,4,0,4,4,1,1,2,1,3,4,0,0.0,satisfied +55758,29257,Male,Loyal Customer,39,Business travel,Business,3304,4,4,4,4,5,5,2,5,5,5,5,3,5,5,0,0.0,satisfied +55759,21629,Female,Loyal Customer,44,Personal Travel,Eco,780,4,5,4,4,3,5,5,4,4,4,4,4,4,3,53,31.0,satisfied +55760,97582,Male,Loyal Customer,33,Personal Travel,Eco,337,1,5,3,3,5,3,5,5,4,3,4,3,4,5,26,14.0,neutral or dissatisfied +55761,17308,Male,disloyal Customer,25,Business travel,Eco,403,3,0,3,5,5,3,5,5,1,3,4,4,2,5,0,0.0,neutral or dissatisfied +55762,10595,Male,Loyal Customer,39,Business travel,Business,482,3,5,5,5,4,4,3,3,3,4,3,4,3,3,5,7.0,neutral or dissatisfied +55763,43155,Female,Loyal Customer,44,Business travel,Business,1368,5,4,5,5,3,3,1,5,5,5,5,2,5,2,0,0.0,satisfied +55764,71966,Female,Loyal Customer,53,Business travel,Business,1437,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +55765,24484,Male,disloyal Customer,24,Business travel,Eco,547,2,3,2,3,1,2,1,1,3,5,3,4,3,1,0,0.0,neutral or dissatisfied +55766,3476,Female,disloyal Customer,30,Business travel,Business,990,4,3,3,4,2,3,1,2,4,2,4,4,5,2,0,6.0,satisfied +55767,8789,Male,disloyal Customer,27,Business travel,Business,522,4,4,4,4,4,4,4,4,5,3,5,4,5,4,108,93.0,neutral or dissatisfied +55768,60885,Male,Loyal Customer,36,Business travel,Eco,662,4,3,3,3,4,4,4,4,2,1,3,2,4,4,5,0.0,neutral or dissatisfied +55769,77699,Male,Loyal Customer,54,Business travel,Business,1650,5,5,5,5,4,5,4,4,4,4,4,3,4,5,17,19.0,satisfied +55770,32244,Female,disloyal Customer,40,Business travel,Business,102,4,4,4,2,2,4,2,2,4,4,5,2,5,2,5,4.0,neutral or dissatisfied +55771,43426,Female,Loyal Customer,17,Business travel,Eco Plus,463,2,1,5,1,2,2,2,2,3,3,4,1,3,2,29,54.0,neutral or dissatisfied +55772,49242,Male,Loyal Customer,52,Business travel,Eco,308,5,1,1,1,5,5,5,5,2,1,5,3,5,5,0,0.0,satisfied +55773,108921,Male,Loyal Customer,49,Personal Travel,Eco,1183,4,4,4,3,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +55774,108104,Female,Loyal Customer,57,Business travel,Business,2125,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +55775,4677,Male,Loyal Customer,31,Business travel,Eco,364,3,2,2,2,3,2,3,3,2,1,4,3,4,3,6,1.0,neutral or dissatisfied +55776,79785,Male,Loyal Customer,41,Business travel,Business,2244,3,3,1,3,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +55777,83211,Male,Loyal Customer,53,Business travel,Business,1895,3,3,3,3,3,5,4,5,5,5,5,4,5,5,1,0.0,satisfied +55778,98826,Male,Loyal Customer,34,Personal Travel,Eco,763,4,5,4,1,4,2,4,3,5,5,4,4,5,4,177,178.0,satisfied +55779,121401,Female,disloyal Customer,39,Business travel,Business,331,1,1,1,2,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +55780,18104,Female,Loyal Customer,44,Personal Travel,Eco,610,1,5,1,1,2,5,5,4,4,1,4,5,4,5,5,0.0,neutral or dissatisfied +55781,39433,Male,Loyal Customer,39,Business travel,Eco,129,2,1,1,1,2,2,2,2,2,4,4,3,4,2,4,6.0,neutral or dissatisfied +55782,60972,Female,Loyal Customer,7,Personal Travel,Eco,888,3,1,3,3,5,3,5,5,3,5,3,3,4,5,1,23.0,neutral or dissatisfied +55783,34708,Female,disloyal Customer,39,Business travel,Business,209,1,2,2,1,3,2,3,3,2,3,5,4,4,3,83,75.0,neutral or dissatisfied +55784,12257,Female,Loyal Customer,44,Business travel,Business,3493,4,4,4,4,5,3,3,2,2,3,4,3,2,2,61,54.0,neutral or dissatisfied +55785,41739,Female,Loyal Customer,44,Business travel,Business,2887,4,4,4,4,2,5,5,5,5,5,5,1,5,3,0,8.0,satisfied +55786,53479,Female,Loyal Customer,35,Business travel,Eco,2288,4,3,3,3,4,5,4,4,4,4,3,5,5,4,3,8.0,satisfied +55787,53184,Male,Loyal Customer,24,Business travel,Business,1532,4,3,3,3,4,4,4,4,4,5,4,1,3,4,2,3.0,neutral or dissatisfied +55788,50546,Female,Loyal Customer,62,Personal Travel,Eco,86,1,5,1,5,1,1,1,4,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +55789,46288,Male,Loyal Customer,25,Personal Travel,Eco Plus,679,3,4,3,2,4,3,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +55790,28421,Male,Loyal Customer,26,Business travel,Business,1399,4,4,4,4,4,4,4,4,3,2,4,4,3,4,0,0.0,satisfied +55791,47778,Female,disloyal Customer,22,Business travel,Eco,838,4,4,4,2,2,4,2,2,1,2,2,2,5,2,0,0.0,satisfied +55792,52129,Female,Loyal Customer,44,Business travel,Business,2847,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,7.0,satisfied +55793,104959,Male,Loyal Customer,34,Business travel,Business,3684,5,5,3,5,4,5,4,4,4,4,4,3,4,3,4,5.0,satisfied +55794,105569,Female,disloyal Customer,27,Business travel,Business,577,5,5,5,4,3,5,3,3,5,3,4,4,5,3,0,5.0,satisfied +55795,94410,Female,disloyal Customer,22,Business travel,Eco,273,1,4,1,1,2,1,2,2,4,5,4,5,5,2,22,23.0,neutral or dissatisfied +55796,5824,Female,Loyal Customer,22,Personal Travel,Eco,157,2,5,2,2,3,2,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +55797,86462,Male,disloyal Customer,24,Business travel,Eco,760,2,2,2,3,5,2,5,5,1,1,3,1,4,5,105,109.0,neutral or dissatisfied +55798,3843,Female,Loyal Customer,19,Personal Travel,Eco,710,2,5,2,1,4,2,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +55799,4875,Female,Loyal Customer,48,Personal Travel,Eco,500,3,5,5,3,2,5,4,1,1,5,1,4,1,5,19,18.0,neutral or dissatisfied +55800,5246,Female,Loyal Customer,45,Business travel,Business,2364,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +55801,120743,Male,disloyal Customer,23,Business travel,Eco,588,4,5,4,2,2,4,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +55802,21484,Female,disloyal Customer,41,Business travel,Business,164,3,3,3,1,5,3,5,5,2,2,1,5,3,5,0,0.0,neutral or dissatisfied +55803,53480,Female,disloyal Customer,74,Business travel,Eco,858,2,2,2,4,2,1,1,1,3,3,3,1,1,1,0,37.0,neutral or dissatisfied +55804,116308,Female,Loyal Customer,13,Personal Travel,Eco,337,3,4,3,1,5,3,2,5,5,2,4,4,4,5,0,12.0,neutral or dissatisfied +55805,89341,Female,Loyal Customer,31,Business travel,Business,1587,2,5,5,5,2,2,2,2,1,5,2,3,2,2,2,0.0,neutral or dissatisfied +55806,90587,Male,Loyal Customer,46,Business travel,Business,406,3,3,1,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +55807,82759,Male,Loyal Customer,73,Business travel,Eco,409,3,1,1,1,3,3,3,2,1,4,3,3,2,3,192,182.0,neutral or dissatisfied +55808,22216,Male,Loyal Customer,66,Personal Travel,Eco,606,4,4,4,1,3,4,3,3,4,2,5,3,4,3,30,25.0,neutral or dissatisfied +55809,52087,Female,Loyal Customer,25,Business travel,Business,2582,2,2,2,2,2,1,2,2,1,5,4,3,4,2,0,6.0,neutral or dissatisfied +55810,11413,Male,Loyal Customer,56,Business travel,Business,3170,3,3,4,3,2,5,5,4,4,4,4,4,4,5,70,62.0,satisfied +55811,6397,Female,Loyal Customer,30,Business travel,Eco,240,0,0,0,1,3,0,3,3,2,4,5,3,1,3,0,0.0,satisfied +55812,78176,Male,Loyal Customer,36,Business travel,Eco,153,1,4,4,4,1,1,1,1,1,5,3,1,3,1,0,0.0,neutral or dissatisfied +55813,47930,Female,Loyal Customer,66,Personal Travel,Eco,329,1,4,1,3,2,3,4,2,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +55814,29065,Male,Loyal Customer,51,Personal Travel,Eco,679,2,5,2,4,5,2,5,5,5,3,4,4,5,5,75,77.0,neutral or dissatisfied +55815,11914,Female,Loyal Customer,37,Personal Travel,Eco,744,3,5,3,3,2,3,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +55816,21487,Male,Loyal Customer,27,Business travel,Business,164,2,2,2,2,5,5,5,5,5,5,3,4,5,5,0,0.0,satisfied +55817,123829,Male,disloyal Customer,22,Business travel,Business,541,4,0,4,4,3,4,3,3,3,2,5,4,5,3,0,0.0,satisfied +55818,58014,Female,Loyal Customer,57,Business travel,Business,1721,5,5,5,5,3,3,5,4,4,4,4,5,4,5,19,24.0,satisfied +55819,8046,Male,Loyal Customer,59,Business travel,Business,3064,5,5,5,5,5,4,4,5,5,5,5,4,5,5,5,0.0,satisfied +55820,93714,Male,Loyal Customer,41,Personal Travel,Eco,689,1,3,0,3,2,0,2,2,5,4,2,5,2,2,0,0.0,neutral or dissatisfied +55821,1625,Female,Loyal Customer,39,Business travel,Business,999,3,5,5,5,4,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +55822,86662,Female,Loyal Customer,54,Personal Travel,Eco,746,3,5,3,4,3,5,4,5,5,3,5,4,5,4,4,0.0,neutral or dissatisfied +55823,23772,Female,Loyal Customer,24,Personal Travel,Business,438,2,3,2,3,5,2,3,5,3,3,2,4,3,5,0,0.0,neutral or dissatisfied +55824,102878,Male,Loyal Customer,63,Personal Travel,Eco,472,1,4,1,4,2,1,2,2,1,3,5,2,4,2,24,41.0,neutral or dissatisfied +55825,39760,Female,disloyal Customer,21,Business travel,Eco,521,5,0,4,4,4,4,4,4,2,1,4,4,4,4,0,0.0,satisfied +55826,127469,Female,disloyal Customer,36,Business travel,Business,2075,1,1,1,3,4,1,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +55827,53333,Female,Loyal Customer,68,Personal Travel,Eco Plus,758,3,3,3,3,1,3,4,5,5,3,1,3,5,2,0,0.0,neutral or dissatisfied +55828,46246,Female,Loyal Customer,30,Business travel,Business,1699,3,3,3,3,3,3,3,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +55829,100748,Female,Loyal Customer,16,Personal Travel,Eco,328,4,0,4,3,1,4,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +55830,98464,Female,Loyal Customer,41,Business travel,Business,210,1,1,1,1,5,4,5,3,3,4,4,5,3,5,138,161.0,satisfied +55831,46702,Female,Loyal Customer,46,Personal Travel,Eco,125,4,3,4,4,1,5,1,3,3,4,3,4,3,2,0,0.0,satisfied +55832,80306,Male,Loyal Customer,48,Business travel,Business,746,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,1.0,satisfied +55833,17793,Female,Loyal Customer,47,Business travel,Eco,986,4,4,4,4,2,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +55834,52343,Female,Loyal Customer,63,Business travel,Eco,451,4,3,3,3,1,2,2,4,4,4,4,2,4,5,1,6.0,satisfied +55835,48385,Male,Loyal Customer,56,Personal Travel,Eco,522,3,5,3,4,3,3,3,3,4,5,5,5,5,3,6,14.0,neutral or dissatisfied +55836,107313,Female,Loyal Customer,41,Personal Travel,Eco,283,3,5,3,1,3,3,3,3,5,3,5,4,4,3,0,3.0,neutral or dissatisfied +55837,93445,Female,Loyal Customer,10,Personal Travel,Eco,697,2,4,2,1,1,2,1,1,3,5,5,5,4,1,6,5.0,neutral or dissatisfied +55838,89338,Female,Loyal Customer,31,Business travel,Eco,1587,2,1,4,4,2,3,2,2,1,3,3,1,4,2,11,4.0,neutral or dissatisfied +55839,51951,Female,Loyal Customer,35,Business travel,Business,2113,0,0,0,1,2,1,2,3,3,3,2,3,3,4,0,0.0,satisfied +55840,91815,Male,Loyal Customer,40,Personal Travel,Eco,626,2,2,2,3,2,2,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +55841,103536,Female,Loyal Customer,52,Business travel,Business,3416,4,4,5,4,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +55842,56895,Female,Loyal Customer,20,Business travel,Business,2454,5,5,5,5,5,5,5,5,4,3,5,3,4,5,124,109.0,satisfied +55843,67058,Female,Loyal Customer,33,Business travel,Business,985,1,1,1,1,3,5,5,4,4,4,4,3,4,5,16,6.0,satisfied +55844,89176,Female,Loyal Customer,59,Personal Travel,Eco,2139,4,3,4,2,2,1,3,2,2,4,2,4,2,1,5,0.0,neutral or dissatisfied +55845,95512,Female,Loyal Customer,58,Business travel,Business,677,2,2,2,2,4,4,4,4,4,4,4,5,4,5,14,0.0,satisfied +55846,24767,Male,Loyal Customer,65,Business travel,Business,432,3,4,4,4,1,3,3,3,3,3,3,2,3,1,0,6.0,neutral or dissatisfied +55847,72484,Male,Loyal Customer,47,Business travel,Business,3292,2,3,3,3,2,2,2,2,2,1,2,2,2,1,1,6.0,neutral or dissatisfied +55848,119812,Male,disloyal Customer,29,Business travel,Business,912,3,3,3,4,3,3,4,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +55849,109605,Female,Loyal Customer,43,Business travel,Business,808,3,3,1,3,4,4,5,4,4,4,4,3,4,5,12,8.0,satisfied +55850,81164,Male,Loyal Customer,45,Business travel,Business,3142,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,7.0,satisfied +55851,62326,Male,Loyal Customer,47,Personal Travel,Eco,414,4,3,4,4,5,4,5,5,4,3,4,2,4,5,0,0.0,satisfied +55852,36542,Female,Loyal Customer,37,Business travel,Eco,1249,5,3,3,3,5,5,5,5,5,4,4,3,3,5,0,0.0,satisfied +55853,59026,Male,disloyal Customer,31,Business travel,Business,1723,2,2,2,1,1,2,1,1,4,3,3,5,5,1,39,41.0,neutral or dissatisfied +55854,98037,Male,Loyal Customer,57,Business travel,Business,1797,1,1,1,1,2,3,4,5,5,5,5,5,5,5,1,3.0,satisfied +55855,13600,Female,Loyal Customer,57,Business travel,Eco Plus,152,3,4,4,4,2,1,2,4,4,3,4,5,4,1,0,0.0,satisfied +55856,71010,Male,Loyal Customer,59,Business travel,Business,2504,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +55857,116566,Male,Loyal Customer,55,Business travel,Business,480,3,3,3,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +55858,39521,Female,Loyal Customer,43,Personal Travel,Eco,1024,3,3,2,5,1,5,4,3,3,2,2,3,3,2,14,0.0,neutral or dissatisfied +55859,117945,Male,Loyal Customer,26,Business travel,Eco,365,4,5,1,5,4,4,2,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +55860,90703,Male,Loyal Customer,57,Business travel,Eco,515,3,3,3,3,3,3,3,3,3,1,3,2,4,3,4,1.0,neutral or dissatisfied +55861,19284,Male,Loyal Customer,38,Business travel,Eco,299,4,1,3,3,4,4,4,4,4,4,3,5,2,4,3,14.0,satisfied +55862,88952,Female,disloyal Customer,26,Business travel,Business,1184,2,2,2,2,2,2,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +55863,56759,Male,Loyal Customer,41,Business travel,Business,1520,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +55864,68492,Female,Loyal Customer,21,Personal Travel,Eco,1303,2,5,2,4,4,2,4,4,3,3,3,4,4,4,31,63.0,neutral or dissatisfied +55865,22330,Male,Loyal Customer,39,Business travel,Eco,208,4,4,4,4,4,4,4,4,1,2,1,5,4,4,30,22.0,satisfied +55866,39284,Male,Loyal Customer,52,Business travel,Eco,173,1,4,4,4,1,1,1,1,4,4,3,1,3,1,40,61.0,neutral or dissatisfied +55867,56649,Male,Loyal Customer,58,Business travel,Business,665,1,1,1,1,4,5,5,4,4,4,4,3,4,1,5,16.0,satisfied +55868,120179,Male,disloyal Customer,49,Business travel,Business,1927,5,5,5,3,2,5,2,2,5,5,3,3,5,2,48,30.0,satisfied +55869,29669,Female,Loyal Customer,61,Personal Travel,Eco,1448,2,5,2,3,5,4,5,3,3,2,2,2,3,2,5,0.0,neutral or dissatisfied +55870,12819,Female,disloyal Customer,26,Business travel,Eco,817,3,3,3,4,2,3,3,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +55871,98958,Female,Loyal Customer,54,Business travel,Business,2727,3,3,3,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +55872,31111,Female,Loyal Customer,65,Personal Travel,Eco,1474,2,5,2,3,4,4,4,5,5,2,5,5,5,4,35,34.0,neutral or dissatisfied +55873,46778,Female,Loyal Customer,42,Personal Travel,Eco Plus,125,3,3,0,4,4,4,4,2,2,0,3,1,2,2,119,100.0,neutral or dissatisfied +55874,71672,Male,Loyal Customer,24,Personal Travel,Eco,1012,3,2,3,4,5,3,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +55875,59989,Female,Loyal Customer,58,Personal Travel,Eco,937,1,4,1,2,4,5,5,5,5,1,5,3,5,5,31,23.0,neutral or dissatisfied +55876,116569,Male,Loyal Customer,56,Business travel,Business,447,2,2,2,2,4,4,4,3,3,3,3,3,3,4,41,50.0,satisfied +55877,122547,Male,Loyal Customer,24,Business travel,Eco,500,2,4,4,4,2,2,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +55878,20718,Male,Loyal Customer,47,Business travel,Eco,765,5,2,2,2,5,5,5,5,5,4,1,4,5,5,0,0.0,satisfied +55879,75954,Male,Loyal Customer,53,Business travel,Business,2305,3,5,5,5,3,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +55880,60859,Female,disloyal Customer,46,Business travel,Business,1491,1,1,1,4,1,1,2,1,4,3,5,3,4,1,5,0.0,neutral or dissatisfied +55881,76087,Female,Loyal Customer,25,Business travel,Business,2126,2,2,2,2,5,5,5,5,2,4,3,2,3,5,8,0.0,satisfied +55882,37977,Male,Loyal Customer,54,Business travel,Business,2890,5,5,4,5,4,4,5,5,5,5,5,4,5,4,16,1.0,satisfied +55883,29935,Female,disloyal Customer,24,Business travel,Business,571,5,0,5,4,1,5,1,1,3,1,4,2,4,1,0,0.0,satisfied +55884,75290,Male,Loyal Customer,47,Business travel,Business,1744,2,2,1,2,5,3,4,4,4,4,4,4,4,4,5,0.0,satisfied +55885,8122,Female,disloyal Customer,23,Business travel,Business,335,5,5,5,3,1,5,1,1,3,5,5,5,4,1,3,30.0,satisfied +55886,98068,Male,disloyal Customer,22,Business travel,Business,1449,0,0,0,3,2,0,2,2,4,5,4,5,5,2,7,12.0,satisfied +55887,73936,Male,disloyal Customer,28,Business travel,Eco,804,2,2,2,4,1,2,1,1,1,1,3,2,4,1,0,0.0,neutral or dissatisfied +55888,66206,Male,Loyal Customer,56,Business travel,Business,460,4,4,4,4,5,5,4,5,5,5,5,5,5,3,19,12.0,satisfied +55889,38549,Female,disloyal Customer,17,Business travel,Eco,1499,3,3,3,3,4,3,4,4,5,4,1,3,1,4,0,5.0,neutral or dissatisfied +55890,78834,Female,Loyal Customer,35,Personal Travel,Eco,528,3,5,3,1,3,3,4,3,4,4,4,3,4,3,0,6.0,neutral or dissatisfied +55891,6139,Female,disloyal Customer,20,Business travel,Eco,491,4,0,5,2,3,5,3,3,4,3,4,4,5,3,0,23.0,neutral or dissatisfied +55892,25919,Female,Loyal Customer,41,Business travel,Eco,594,4,4,4,4,4,4,4,4,1,4,2,3,3,4,7,4.0,satisfied +55893,17704,Male,disloyal Customer,45,Business travel,Eco,287,1,0,1,1,1,2,5,1,2,2,3,5,2,5,156,139.0,neutral or dissatisfied +55894,92377,Female,Loyal Customer,41,Personal Travel,Business,1947,1,5,1,2,2,4,5,2,2,1,3,5,2,4,0,0.0,neutral or dissatisfied +55895,113089,Female,disloyal Customer,47,Business travel,Eco,143,1,2,1,4,2,1,2,2,3,1,4,4,4,2,39,25.0,neutral or dissatisfied +55896,83051,Male,Loyal Customer,29,Business travel,Business,1127,4,4,4,4,4,4,4,4,4,3,4,3,4,4,8,0.0,satisfied +55897,102402,Female,Loyal Customer,54,Personal Travel,Eco,223,4,0,4,3,4,4,5,5,5,4,5,4,5,3,52,46.0,satisfied +55898,88980,Male,Loyal Customer,37,Personal Travel,Eco,1199,2,2,1,3,4,1,4,4,1,3,4,2,3,4,2,0.0,neutral or dissatisfied +55899,76491,Female,Loyal Customer,43,Business travel,Business,3818,2,2,2,2,4,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +55900,28474,Male,Loyal Customer,16,Business travel,Business,1721,3,1,1,1,3,3,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +55901,12538,Female,disloyal Customer,25,Business travel,Eco,828,1,1,1,3,5,1,2,5,2,5,2,2,2,5,0,0.0,neutral or dissatisfied +55902,87996,Male,disloyal Customer,37,Business travel,Business,250,5,5,5,3,3,5,3,3,4,3,4,4,4,3,0,0.0,satisfied +55903,22749,Female,disloyal Customer,20,Business travel,Eco,147,5,5,5,4,1,5,1,1,4,4,5,5,4,1,0,0.0,satisfied +55904,19838,Female,Loyal Customer,22,Business travel,Eco Plus,413,0,4,0,4,3,0,3,3,1,5,1,4,1,3,0,0.0,satisfied +55905,37558,Male,Loyal Customer,48,Business travel,Eco,669,1,5,5,5,2,1,2,2,2,2,3,1,4,2,110,125.0,neutral or dissatisfied +55906,9047,Female,Loyal Customer,34,Business travel,Business,2750,4,2,2,2,5,3,4,4,4,4,4,1,4,2,0,1.0,neutral or dissatisfied +55907,63894,Female,disloyal Customer,23,Business travel,Eco,1158,1,1,1,3,5,1,5,5,4,2,2,1,2,5,0,0.0,neutral or dissatisfied +55908,124083,Female,Loyal Customer,48,Personal Travel,Business,529,4,5,4,5,4,4,4,1,1,4,4,5,1,5,0,0.0,neutral or dissatisfied +55909,72133,Male,disloyal Customer,17,Business travel,Eco,731,1,1,1,3,3,1,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +55910,16852,Female,Loyal Customer,36,Business travel,Business,2253,3,3,3,3,1,3,5,4,4,4,4,1,4,5,0,0.0,satisfied +55911,82796,Male,Loyal Customer,50,Business travel,Business,235,2,2,2,2,2,4,5,5,5,5,5,3,5,3,3,0.0,satisfied +55912,3288,Female,Loyal Customer,10,Personal Travel,Eco,479,4,2,5,2,1,5,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +55913,61481,Male,Loyal Customer,49,Business travel,Business,2442,2,3,3,3,2,2,3,2,2,3,2,4,2,2,60,56.0,neutral or dissatisfied +55914,32181,Female,Loyal Customer,22,Business travel,Business,102,2,2,2,2,4,4,4,4,1,3,2,1,5,4,2,0.0,satisfied +55915,60203,Female,Loyal Customer,46,Business travel,Business,1546,4,4,1,4,2,5,5,3,3,2,3,4,3,3,9,2.0,satisfied +55916,66615,Male,Loyal Customer,43,Business travel,Business,2934,4,4,4,4,4,5,5,5,5,5,5,5,5,3,2,20.0,satisfied +55917,105079,Male,disloyal Customer,37,Business travel,Business,281,4,3,3,2,1,3,1,1,4,5,5,4,5,1,35,21.0,neutral or dissatisfied +55918,16448,Female,Loyal Customer,31,Business travel,Eco,416,3,2,2,2,3,4,3,3,2,2,3,2,4,3,4,0.0,neutral or dissatisfied +55919,85258,Male,Loyal Customer,42,Personal Travel,Eco,689,1,1,0,3,1,0,1,1,1,2,3,4,4,1,0,5.0,neutral or dissatisfied +55920,30236,Male,disloyal Customer,37,Business travel,Eco,496,2,5,2,5,5,2,5,5,3,3,5,4,2,5,59,72.0,neutral or dissatisfied +55921,81317,Female,disloyal Customer,25,Business travel,Business,1299,5,4,5,5,1,5,1,1,3,5,4,4,4,1,12,0.0,satisfied +55922,63058,Male,Loyal Customer,37,Personal Travel,Eco,862,1,3,1,4,1,1,1,1,5,4,4,2,1,1,0,0.0,neutral or dissatisfied +55923,43474,Female,Loyal Customer,44,Business travel,Business,594,3,3,3,3,1,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +55924,48068,Male,disloyal Customer,27,Business travel,Business,259,5,5,5,4,3,5,3,3,4,2,4,3,5,3,53,45.0,satisfied +55925,3809,Male,Loyal Customer,47,Business travel,Business,710,2,2,5,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +55926,73485,Female,Loyal Customer,11,Personal Travel,Eco,1005,1,4,1,4,3,1,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +55927,98148,Male,disloyal Customer,16,Business travel,Eco,562,4,0,4,3,3,4,1,3,5,3,4,4,5,3,26,19.0,satisfied +55928,5850,Female,Loyal Customer,21,Business travel,Business,2271,5,5,5,5,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +55929,32749,Male,Loyal Customer,42,Business travel,Eco,101,2,3,3,3,1,2,1,1,5,1,4,2,3,1,0,4.0,satisfied +55930,31149,Female,Loyal Customer,47,Business travel,Business,1782,5,1,5,5,3,1,4,4,4,4,4,1,4,4,124,112.0,satisfied +55931,122090,Male,Loyal Customer,41,Personal Travel,Eco,130,0,4,0,4,1,0,1,1,2,5,3,1,4,1,0,0.0,satisfied +55932,72116,Female,Loyal Customer,31,Business travel,Business,3468,4,4,4,4,2,2,2,2,3,2,4,5,5,2,0,0.0,satisfied +55933,20685,Female,disloyal Customer,26,Business travel,Business,584,1,4,1,4,5,1,2,5,1,4,3,3,3,5,0,0.0,neutral or dissatisfied +55934,31848,Male,disloyal Customer,29,Business travel,Business,2640,1,1,1,4,2,1,2,2,4,5,4,1,3,2,58,10.0,neutral or dissatisfied +55935,17397,Female,Loyal Customer,36,Business travel,Business,3745,3,3,3,3,3,2,5,4,4,4,4,1,4,2,0,0.0,satisfied +55936,77243,Male,disloyal Customer,29,Business travel,Business,1590,4,4,4,3,3,4,3,3,3,2,4,5,4,3,0,0.0,satisfied +55937,101025,Male,Loyal Customer,51,Personal Travel,Eco,867,2,4,2,3,3,2,3,3,5,4,2,2,5,3,2,17.0,neutral or dissatisfied +55938,11897,Male,Loyal Customer,33,Business travel,Business,1905,4,4,4,4,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +55939,84871,Female,Loyal Customer,9,Personal Travel,Eco,516,3,2,3,4,4,3,2,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +55940,21728,Male,Loyal Customer,21,Business travel,Eco,563,0,4,0,2,3,0,1,3,5,2,4,3,5,3,2,0.0,satisfied +55941,87264,Female,Loyal Customer,24,Business travel,Business,577,1,1,1,1,4,4,4,4,5,2,4,5,4,4,7,4.0,satisfied +55942,46811,Female,Loyal Customer,55,Business travel,Eco,846,4,5,5,5,5,1,4,4,4,4,4,2,4,3,0,0.0,satisfied +55943,35448,Female,Loyal Customer,66,Personal Travel,Eco,1028,3,4,3,3,3,5,5,3,3,3,3,4,3,5,17,10.0,neutral or dissatisfied +55944,55913,Female,Loyal Customer,62,Personal Travel,Eco,473,3,4,3,4,3,1,1,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +55945,92624,Female,Loyal Customer,44,Business travel,Business,2709,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +55946,127577,Male,Loyal Customer,65,Personal Travel,Eco,1670,1,1,2,3,3,2,3,3,2,2,3,1,2,3,13,55.0,neutral or dissatisfied +55947,107630,Male,Loyal Customer,17,Personal Travel,Eco,423,4,0,4,2,4,4,4,4,3,2,3,3,2,4,16,1.0,satisfied +55948,105254,Male,Loyal Customer,23,Business travel,Business,2106,1,3,3,3,1,1,1,1,1,4,3,1,4,1,219,190.0,neutral or dissatisfied +55949,4830,Male,Loyal Customer,54,Business travel,Business,408,2,2,2,2,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +55950,111664,Male,disloyal Customer,27,Business travel,Eco,991,2,3,3,4,4,3,4,4,2,5,3,1,3,4,18,12.0,neutral or dissatisfied +55951,26362,Male,disloyal Customer,45,Business travel,Eco,991,1,1,1,3,2,1,5,2,5,5,2,2,4,2,8,0.0,neutral or dissatisfied +55952,6623,Male,Loyal Customer,25,Business travel,Eco,719,2,1,1,1,2,2,4,2,1,5,4,2,4,2,20,80.0,neutral or dissatisfied +55953,5791,Male,Loyal Customer,59,Business travel,Business,1993,4,4,4,4,4,5,4,5,5,5,4,4,5,5,0,0.0,satisfied +55954,127275,Female,Loyal Customer,16,Personal Travel,Eco,1107,2,4,2,4,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +55955,47866,Male,disloyal Customer,24,Business travel,Eco,329,2,0,2,4,2,2,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +55956,113039,Male,Loyal Customer,31,Business travel,Business,3748,3,1,3,3,4,4,4,4,5,2,4,3,5,4,22,18.0,satisfied +55957,16262,Female,Loyal Customer,36,Business travel,Eco,946,4,1,1,1,4,4,4,4,5,3,3,1,2,4,0,0.0,satisfied +55958,43884,Female,Loyal Customer,60,Business travel,Business,144,2,3,3,3,4,4,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +55959,106329,Male,disloyal Customer,29,Business travel,Eco,825,1,1,1,3,2,1,2,2,2,4,2,1,3,2,0,0.0,neutral or dissatisfied +55960,99899,Male,Loyal Customer,31,Personal Travel,Eco,738,3,4,3,4,1,3,2,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +55961,78518,Female,Loyal Customer,45,Personal Travel,Eco,666,3,4,4,4,3,4,5,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +55962,118908,Male,Loyal Customer,16,Personal Travel,Eco,570,4,4,4,3,1,4,1,1,5,5,4,4,5,1,4,0.0,satisfied +55963,23544,Female,Loyal Customer,60,Business travel,Eco Plus,423,2,2,2,2,2,3,3,2,2,2,2,4,2,1,0,16.0,neutral or dissatisfied +55964,18159,Female,Loyal Customer,26,Personal Travel,Eco,430,2,5,2,5,1,2,1,1,5,3,3,5,3,1,0,0.0,neutral or dissatisfied +55965,75244,Female,Loyal Customer,14,Personal Travel,Eco,1846,2,0,2,5,5,2,5,5,5,5,5,5,4,5,2,0.0,neutral or dissatisfied +55966,43763,Female,Loyal Customer,29,Business travel,Business,481,5,5,5,5,5,4,5,5,3,3,4,4,4,5,27,43.0,neutral or dissatisfied +55967,77637,Female,Loyal Customer,21,Business travel,Business,1522,2,3,3,3,2,2,2,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +55968,93081,Female,Loyal Customer,46,Business travel,Business,3064,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +55969,30302,Male,Loyal Customer,47,Business travel,Eco,1076,4,3,3,3,4,4,4,4,3,1,1,1,1,4,0,0.0,satisfied +55970,38310,Female,Loyal Customer,23,Personal Travel,Eco,2583,3,3,3,2,3,1,1,5,1,4,1,1,4,1,98,96.0,neutral or dissatisfied +55971,67866,Male,Loyal Customer,45,Personal Travel,Eco,1431,2,5,2,4,2,2,2,2,3,5,3,4,5,2,0,4.0,neutral or dissatisfied +55972,101244,Female,Loyal Customer,46,Personal Travel,Eco,1587,2,5,2,3,3,3,5,2,2,2,2,4,2,4,13,9.0,neutral or dissatisfied +55973,75818,Female,Loyal Customer,55,Personal Travel,Eco Plus,813,2,2,2,3,1,3,4,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +55974,74698,Female,Loyal Customer,48,Personal Travel,Eco,1464,1,4,1,3,2,3,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +55975,52630,Male,Loyal Customer,55,Business travel,Eco,119,5,2,4,2,5,5,5,5,1,1,1,5,1,5,0,0.0,satisfied +55976,88014,Female,Loyal Customer,45,Business travel,Business,3771,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +55977,96018,Female,disloyal Customer,35,Business travel,Eco,795,3,3,3,3,4,3,4,4,1,2,2,4,2,4,4,38.0,neutral or dissatisfied +55978,41376,Male,Loyal Customer,49,Business travel,Business,3471,2,4,3,4,2,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +55979,78574,Female,disloyal Customer,25,Business travel,Eco,630,1,2,1,3,2,1,2,2,4,2,4,1,3,2,61,52.0,neutral or dissatisfied +55980,118196,Female,Loyal Customer,16,Personal Travel,Eco,1444,2,5,2,5,4,2,4,4,4,2,5,3,4,4,0,19.0,neutral or dissatisfied +55981,117761,Female,Loyal Customer,42,Business travel,Business,1670,2,1,3,1,2,1,2,2,2,2,2,1,2,4,54,27.0,neutral or dissatisfied +55982,56396,Female,Loyal Customer,48,Business travel,Business,719,4,4,4,4,3,5,4,4,4,4,4,3,4,3,120,124.0,satisfied +55983,38429,Male,Loyal Customer,38,Personal Travel,Eco,965,3,4,3,3,1,3,1,1,2,4,4,4,3,1,0,0.0,neutral or dissatisfied +55984,117839,Male,Loyal Customer,26,Personal Travel,Eco Plus,328,1,4,3,3,5,3,5,5,1,2,4,4,4,5,0,0.0,neutral or dissatisfied +55985,14102,Male,Loyal Customer,32,Personal Travel,Eco,371,3,1,4,3,2,4,3,2,1,1,4,2,4,2,0,6.0,neutral or dissatisfied +55986,85826,Male,Loyal Customer,46,Personal Travel,Eco,526,4,5,4,2,4,4,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +55987,45477,Female,Loyal Customer,19,Business travel,Business,1952,4,3,3,3,4,4,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +55988,25194,Female,Loyal Customer,9,Personal Travel,Eco,577,1,4,1,3,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +55989,112746,Male,Loyal Customer,41,Business travel,Business,2405,4,4,4,4,4,4,5,4,4,4,5,4,4,5,10,7.0,satisfied +55990,33209,Female,Loyal Customer,36,Business travel,Eco Plus,216,4,4,4,4,4,4,4,4,4,3,2,1,3,4,10,13.0,satisfied +55991,11798,Female,Loyal Customer,20,Business travel,Eco Plus,429,3,4,4,4,3,3,3,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +55992,30250,Female,Loyal Customer,50,Business travel,Business,1846,1,2,2,2,5,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +55993,60601,Male,disloyal Customer,52,Business travel,Business,991,5,5,5,4,5,4,4,4,3,5,5,4,4,4,200,192.0,satisfied +55994,103071,Female,Loyal Customer,33,Business travel,Business,2282,1,2,2,2,2,1,1,4,3,4,3,1,4,1,140,152.0,neutral or dissatisfied +55995,66951,Male,Loyal Customer,44,Business travel,Business,3426,2,2,2,2,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +55996,46396,Female,Loyal Customer,62,Personal Travel,Eco,1013,2,4,2,2,1,1,5,4,4,2,4,4,4,2,30,28.0,neutral or dissatisfied +55997,101134,Male,Loyal Customer,53,Business travel,Business,1090,3,3,2,3,4,5,4,4,4,4,4,3,4,4,4,8.0,satisfied +55998,25880,Male,Loyal Customer,35,Business travel,Eco,907,3,3,3,3,3,3,3,3,5,4,5,5,5,3,98,79.0,satisfied +55999,9653,Female,Loyal Customer,54,Business travel,Business,199,5,5,4,5,2,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +56000,53897,Female,Loyal Customer,36,Personal Travel,Eco,140,3,4,3,4,1,3,1,1,1,5,2,4,4,1,0,0.0,neutral or dissatisfied +56001,92107,Female,Loyal Customer,10,Personal Travel,Eco,1532,4,3,4,3,2,4,2,2,2,3,3,1,2,2,118,91.0,neutral or dissatisfied +56002,117866,Male,disloyal Customer,26,Business travel,Business,255,4,0,4,2,5,4,5,5,4,2,5,3,5,5,24,19.0,satisfied +56003,44790,Female,Loyal Customer,42,Personal Travel,Eco,1250,3,4,3,4,5,3,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +56004,72878,Male,Loyal Customer,23,Business travel,Business,3350,2,2,2,2,3,3,3,3,5,4,5,5,4,3,6,6.0,satisfied +56005,90758,Male,Loyal Customer,63,Business travel,Business,3490,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +56006,124936,Male,Loyal Customer,10,Personal Travel,Eco,728,3,5,3,4,3,3,3,3,3,3,5,2,5,3,3,18.0,neutral or dissatisfied +56007,8999,Female,Loyal Customer,27,Personal Travel,Eco,297,1,3,1,2,2,1,3,2,1,1,4,4,3,2,6,0.0,neutral or dissatisfied +56008,27308,Female,Loyal Customer,41,Business travel,Eco,605,5,5,5,5,5,5,5,5,3,3,2,2,2,5,7,14.0,satisfied +56009,49665,Male,Loyal Customer,44,Business travel,Eco,373,4,1,1,1,4,4,4,4,3,1,4,2,2,4,0,0.0,satisfied +56010,53104,Male,Loyal Customer,36,Personal Travel,Eco,1628,3,4,3,1,4,3,4,4,4,5,5,3,4,4,44,30.0,neutral or dissatisfied +56011,79711,Female,Loyal Customer,70,Personal Travel,Eco,762,3,5,3,5,3,5,4,2,2,3,2,3,2,5,66,73.0,neutral or dissatisfied +56012,7886,Male,Loyal Customer,45,Personal Travel,Eco,948,1,2,1,3,2,1,2,2,2,4,4,2,3,2,72,77.0,neutral or dissatisfied +56013,117194,Female,Loyal Customer,55,Personal Travel,Eco,369,4,3,3,2,5,2,2,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +56014,107570,Female,Loyal Customer,25,Personal Travel,Eco,1521,3,1,3,4,1,3,2,1,2,3,4,4,4,1,44,28.0,neutral or dissatisfied +56015,74375,Female,Loyal Customer,56,Business travel,Business,1431,5,5,5,5,3,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +56016,10299,Male,Loyal Customer,46,Business travel,Business,1865,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +56017,52188,Male,disloyal Customer,27,Business travel,Eco,370,2,5,2,4,1,2,1,1,1,3,5,5,5,1,0,0.0,neutral or dissatisfied +56018,33331,Female,Loyal Customer,27,Business travel,Business,2556,5,5,5,5,5,5,5,5,2,5,4,3,4,5,0,0.0,satisfied +56019,49104,Male,disloyal Customer,43,Business travel,Eco,109,3,4,3,1,3,3,3,3,4,1,4,3,2,3,8,3.0,neutral or dissatisfied +56020,85248,Male,Loyal Customer,47,Personal Travel,Eco,813,3,3,3,3,4,3,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +56021,1949,Male,Loyal Customer,46,Business travel,Business,2038,1,4,4,4,2,4,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +56022,59711,Female,Loyal Customer,51,Business travel,Business,965,1,1,1,1,2,5,4,5,5,5,5,5,5,4,1,18.0,satisfied +56023,119830,Female,Loyal Customer,55,Business travel,Business,2164,3,3,3,3,5,5,4,4,4,4,4,5,4,3,8,0.0,satisfied +56024,82620,Male,Loyal Customer,62,Personal Travel,Eco,528,3,5,3,3,3,3,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +56025,48855,Male,Loyal Customer,67,Personal Travel,Business,86,3,4,3,3,4,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +56026,3230,Female,disloyal Customer,21,Business travel,Eco,479,2,4,2,3,3,2,3,3,1,4,3,1,4,3,22,13.0,neutral or dissatisfied +56027,76005,Male,Loyal Customer,52,Business travel,Business,3562,0,0,0,2,2,5,5,5,5,4,4,3,5,5,0,0.0,satisfied +56028,39811,Female,Loyal Customer,22,Business travel,Eco,221,4,4,4,4,4,4,4,4,2,3,5,3,2,4,0,0.0,satisfied +56029,42365,Female,Loyal Customer,35,Personal Travel,Eco,451,2,5,2,3,4,2,4,4,4,3,1,4,3,4,0,0.0,neutral or dissatisfied +56030,47958,Female,Loyal Customer,41,Personal Travel,Eco,748,1,3,1,1,2,1,2,2,5,3,4,1,2,2,0,0.0,neutral or dissatisfied +56031,14669,Female,disloyal Customer,22,Business travel,Eco,416,1,2,1,4,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +56032,65428,Female,disloyal Customer,12,Business travel,Eco,745,3,3,3,4,3,3,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +56033,91790,Female,Loyal Customer,51,Personal Travel,Eco,588,3,5,3,5,2,5,5,2,2,3,2,5,2,4,0,5.0,neutral or dissatisfied +56034,119932,Male,disloyal Customer,39,Business travel,Eco,1009,4,5,5,3,5,5,5,5,3,2,4,1,3,5,0,0.0,neutral or dissatisfied +56035,34079,Male,Loyal Customer,50,Business travel,Eco Plus,174,5,2,3,2,5,5,5,5,2,3,1,3,3,5,7,0.0,satisfied +56036,81926,Female,Loyal Customer,46,Business travel,Business,1522,2,3,3,3,4,4,3,2,2,2,2,3,2,3,0,5.0,neutral or dissatisfied +56037,51110,Male,Loyal Customer,53,Personal Travel,Eco,109,3,0,3,3,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +56038,120373,Male,Loyal Customer,46,Business travel,Business,3824,1,1,1,1,4,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +56039,43942,Male,Loyal Customer,16,Personal Travel,Eco Plus,199,3,5,0,3,5,0,5,5,5,3,5,3,5,5,4,,neutral or dissatisfied +56040,33508,Male,Loyal Customer,58,Personal Travel,Eco,965,2,5,2,2,3,2,3,3,5,5,5,3,4,3,46,38.0,neutral or dissatisfied +56041,46582,Female,Loyal Customer,42,Business travel,Business,3014,1,3,3,3,1,2,3,2,2,2,1,4,2,1,30,32.0,neutral or dissatisfied +56042,76104,Female,disloyal Customer,27,Business travel,Business,669,2,2,2,5,2,2,2,2,5,2,5,5,5,2,57,33.0,neutral or dissatisfied +56043,22482,Female,Loyal Customer,8,Personal Travel,Eco,143,1,5,1,4,3,1,2,3,2,3,3,3,5,3,0,0.0,neutral or dissatisfied +56044,25745,Female,Loyal Customer,48,Business travel,Eco,356,5,2,3,2,4,1,5,5,5,5,5,3,5,4,26,18.0,satisfied +56045,61282,Male,Loyal Customer,24,Personal Travel,Eco,967,1,4,1,3,2,1,2,2,5,1,1,2,3,2,6,0.0,neutral or dissatisfied +56046,109714,Female,Loyal Customer,31,Business travel,Business,534,5,5,5,5,3,3,3,3,4,2,4,3,5,3,18,16.0,satisfied +56047,74874,Male,Loyal Customer,51,Personal Travel,Eco,2239,1,1,1,3,3,1,3,3,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +56048,7510,Male,disloyal Customer,32,Business travel,Business,762,1,1,1,4,4,1,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +56049,24022,Female,disloyal Customer,15,Business travel,Eco,562,4,5,4,3,3,4,3,3,4,5,4,1,3,3,0,0.0,satisfied +56050,35183,Male,Loyal Customer,15,Business travel,Eco,828,3,3,3,3,3,4,3,2,4,4,3,3,3,3,342,364.0,neutral or dissatisfied +56051,43249,Male,Loyal Customer,59,Business travel,Business,2698,5,5,5,5,4,1,5,5,5,5,5,3,5,2,0,0.0,satisfied +56052,128767,Male,Loyal Customer,43,Business travel,Business,150,3,3,3,3,3,2,2,5,5,5,5,4,5,2,0,0.0,satisfied +56053,69697,Male,Loyal Customer,44,Business travel,Business,1372,3,3,3,3,5,5,5,3,4,5,4,5,3,5,394,407.0,satisfied +56054,13031,Female,Loyal Customer,66,Personal Travel,Eco,374,2,4,2,5,2,3,1,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +56055,124594,Female,Loyal Customer,18,Personal Travel,Eco,500,3,4,4,5,3,4,3,3,3,3,5,3,5,3,0,5.0,neutral or dissatisfied +56056,6947,Male,disloyal Customer,27,Business travel,Eco,501,2,4,2,3,2,2,2,2,1,3,4,4,4,2,9,0.0,neutral or dissatisfied +56057,107255,Female,Loyal Customer,36,Business travel,Business,283,4,4,4,4,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +56058,39957,Male,Loyal Customer,63,Personal Travel,Eco,1195,0,5,0,4,3,0,3,3,4,2,3,1,3,3,0,0.0,satisfied +56059,62767,Female,disloyal Customer,23,Business travel,Eco,2486,3,3,3,3,2,3,2,2,2,2,2,2,3,2,6,1.0,neutral or dissatisfied +56060,44071,Female,Loyal Customer,54,Business travel,Eco,651,5,5,2,5,1,1,4,5,5,5,5,2,5,5,0,0.0,satisfied +56061,67634,Female,Loyal Customer,42,Business travel,Business,1431,5,5,4,5,3,4,4,4,4,4,4,5,4,3,17,44.0,satisfied +56062,53716,Female,Loyal Customer,15,Personal Travel,Eco,1190,5,5,5,3,3,5,3,3,3,2,5,5,5,3,0,15.0,satisfied +56063,80145,Female,disloyal Customer,26,Business travel,Business,2475,5,5,5,5,5,3,3,3,3,5,4,3,5,3,0,2.0,satisfied +56064,60501,Female,Loyal Customer,58,Business travel,Business,1929,2,5,5,5,1,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +56065,114131,Male,Loyal Customer,32,Business travel,Eco,957,3,4,4,4,3,3,3,3,1,5,3,3,3,3,0,10.0,neutral or dissatisfied +56066,59075,Male,Loyal Customer,20,Business travel,Eco,1846,2,1,1,1,2,2,3,2,3,1,3,2,3,2,51,41.0,neutral or dissatisfied +56067,87795,Male,Loyal Customer,33,Business travel,Eco,214,2,2,2,2,2,2,2,2,2,4,4,2,4,2,168,156.0,neutral or dissatisfied +56068,9511,Male,Loyal Customer,64,Personal Travel,Eco,239,3,4,3,4,1,3,1,1,4,5,5,1,4,1,0,0.0,neutral or dissatisfied +56069,119354,Male,Loyal Customer,20,Personal Travel,Eco Plus,214,2,0,0,4,3,0,3,3,1,2,2,1,3,3,0,0.0,neutral or dissatisfied +56070,9338,Female,Loyal Customer,48,Business travel,Business,1936,3,3,3,3,4,5,4,2,2,2,2,3,2,4,0,4.0,satisfied +56071,55343,Female,Loyal Customer,26,Personal Travel,Eco,1325,2,5,2,5,4,2,1,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +56072,63583,Female,Loyal Customer,53,Business travel,Business,2133,5,5,5,5,4,3,5,5,5,5,5,5,5,4,5,0.0,satisfied +56073,43009,Female,Loyal Customer,28,Business travel,Business,236,2,2,2,2,4,4,4,4,5,3,3,3,2,4,0,2.0,satisfied +56074,46703,Male,Loyal Customer,68,Personal Travel,Eco,125,2,4,2,3,1,2,1,1,1,3,2,5,5,1,14,10.0,neutral or dissatisfied +56075,99208,Female,Loyal Customer,48,Business travel,Business,3131,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +56076,54578,Male,Loyal Customer,27,Business travel,Business,3904,3,3,3,3,5,5,5,4,4,3,3,5,5,5,0,0.0,satisfied +56077,116845,Female,Loyal Customer,48,Personal Travel,Business,338,2,2,0,4,2,3,3,4,4,0,5,2,4,3,14,11.0,neutral or dissatisfied +56078,87460,Female,Loyal Customer,28,Business travel,Business,321,5,5,5,5,4,4,4,4,3,3,5,4,5,4,2,0.0,satisfied +56079,75635,Male,Loyal Customer,48,Business travel,Business,3567,5,5,5,5,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +56080,60116,Male,Loyal Customer,28,Business travel,Business,3854,3,5,5,5,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +56081,111677,Female,Loyal Customer,42,Personal Travel,Eco,991,3,5,3,3,3,4,5,3,3,3,3,3,3,3,27,39.0,neutral or dissatisfied +56082,86077,Male,Loyal Customer,39,Business travel,Business,3357,1,1,1,1,4,4,4,4,4,4,4,3,4,4,11,7.0,satisfied +56083,26980,Male,disloyal Customer,54,Business travel,Eco,867,2,2,2,2,4,2,2,4,1,3,2,1,5,4,0,0.0,neutral or dissatisfied +56084,18170,Female,disloyal Customer,24,Business travel,Eco,363,5,0,5,5,5,5,5,5,4,2,2,5,2,5,0,1.0,satisfied +56085,59549,Male,Loyal Customer,49,Business travel,Business,964,1,1,1,1,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +56086,92367,Female,Loyal Customer,41,Business travel,Business,1947,1,1,1,1,4,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +56087,101979,Male,Loyal Customer,35,Personal Travel,Eco,628,2,3,2,2,2,2,2,2,1,1,3,3,3,2,3,0.0,neutral or dissatisfied +56088,83315,Female,Loyal Customer,72,Business travel,Business,1671,1,3,3,3,4,2,4,1,1,1,1,1,1,1,4,0.0,neutral or dissatisfied +56089,112170,Female,Loyal Customer,60,Personal Travel,Eco,895,0,1,0,3,4,3,4,2,2,0,2,4,2,1,10,2.0,satisfied +56090,24534,Male,Loyal Customer,44,Business travel,Business,874,3,2,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +56091,111121,Male,Loyal Customer,58,Business travel,Business,1050,5,5,5,5,5,4,5,4,4,4,4,4,4,3,37,25.0,satisfied +56092,60565,Female,Loyal Customer,30,Personal Travel,Eco Plus,775,2,2,2,4,5,2,5,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +56093,5997,Male,Loyal Customer,21,Business travel,Business,690,3,3,3,3,3,3,3,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +56094,1691,Male,Loyal Customer,52,Personal Travel,Business,489,3,2,3,4,3,4,3,3,3,3,3,1,3,2,0,6.0,neutral or dissatisfied +56095,6633,Female,Loyal Customer,14,Personal Travel,Eco,719,0,5,0,4,1,0,1,1,5,2,5,3,4,1,0,0.0,satisfied +56096,20495,Female,disloyal Customer,24,Business travel,Eco,139,2,1,2,3,3,2,2,3,4,2,4,3,4,3,79,76.0,neutral or dissatisfied +56097,101845,Female,Loyal Customer,45,Business travel,Business,2800,2,2,2,2,2,4,4,4,4,4,4,4,4,5,71,65.0,satisfied +56098,55808,Female,disloyal Customer,12,Business travel,Eco,1416,3,3,3,3,3,3,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +56099,98469,Female,Loyal Customer,59,Personal Travel,Eco,210,4,4,4,3,1,4,4,1,1,4,1,4,1,2,0,0.0,satisfied +56100,71389,Female,disloyal Customer,32,Business travel,Business,258,2,2,2,2,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +56101,70358,Female,Loyal Customer,47,Business travel,Business,2557,4,4,3,4,5,5,5,4,2,5,4,5,4,5,131,125.0,satisfied +56102,49032,Female,disloyal Customer,25,Business travel,Eco,209,3,2,3,4,4,3,5,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +56103,117929,Female,disloyal Customer,37,Business travel,Eco,365,4,4,5,4,5,5,5,1,2,3,3,5,3,5,220,225.0,neutral or dissatisfied +56104,2686,Male,Loyal Customer,15,Personal Travel,Eco Plus,622,5,5,5,3,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +56105,100190,Male,Loyal Customer,66,Personal Travel,Eco,725,3,3,3,3,2,3,5,2,2,1,4,4,3,2,10,19.0,neutral or dissatisfied +56106,94741,Female,Loyal Customer,39,Business travel,Business,3762,3,4,3,4,5,3,2,3,3,3,3,2,3,1,46,44.0,neutral or dissatisfied +56107,118,Male,Loyal Customer,32,Business travel,Business,562,5,5,5,5,4,4,4,4,4,2,2,4,3,4,183,192.0,satisfied +56108,22741,Male,Loyal Customer,28,Business travel,Eco,170,5,2,2,2,5,5,5,5,5,5,3,1,1,5,0,0.0,satisfied +56109,34762,Male,disloyal Customer,41,Business travel,Eco,301,2,2,2,3,2,2,2,2,4,3,4,4,4,2,38,27.0,neutral or dissatisfied +56110,42033,Female,disloyal Customer,33,Business travel,Eco,106,4,0,3,3,1,3,1,1,4,2,2,3,5,1,0,0.0,neutral or dissatisfied +56111,119084,Female,Loyal Customer,39,Business travel,Business,2895,3,3,5,3,3,4,5,4,4,4,4,5,4,4,31,5.0,satisfied +56112,100321,Male,Loyal Customer,50,Business travel,Business,971,1,5,4,5,5,4,4,1,1,1,1,1,1,2,4,16.0,neutral or dissatisfied +56113,27064,Female,Loyal Customer,24,Business travel,Business,1399,5,5,2,5,5,5,5,5,3,5,1,1,3,5,0,0.0,satisfied +56114,34088,Female,Loyal Customer,67,Personal Travel,Eco,2072,2,4,2,3,5,4,4,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +56115,79843,Male,Loyal Customer,46,Business travel,Business,2156,2,2,4,2,3,4,4,5,5,5,5,5,5,3,27,22.0,satisfied +56116,100666,Male,Loyal Customer,24,Business travel,Business,677,2,2,2,2,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +56117,121543,Female,Loyal Customer,60,Business travel,Business,912,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +56118,42421,Male,Loyal Customer,64,Personal Travel,Eco Plus,817,2,3,2,1,4,2,5,4,1,4,1,3,5,4,0,0.0,neutral or dissatisfied +56119,84958,Male,Loyal Customer,20,Personal Travel,Eco Plus,534,4,3,4,2,4,4,4,4,4,3,2,1,3,4,0,0.0,satisfied +56120,84656,Male,Loyal Customer,60,Business travel,Business,682,4,4,4,4,4,4,5,2,2,2,2,5,2,5,0,11.0,satisfied +56121,20824,Female,disloyal Customer,39,Business travel,Business,457,1,1,1,3,1,1,1,1,1,1,3,2,4,1,0,0.0,neutral or dissatisfied +56122,105476,Female,Loyal Customer,53,Personal Travel,Eco,495,3,5,3,3,1,4,1,5,5,3,5,3,5,5,15,21.0,neutral or dissatisfied +56123,47173,Male,disloyal Customer,25,Business travel,Eco,620,1,0,1,2,4,1,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +56124,15152,Female,Loyal Customer,32,Personal Travel,Eco,912,0,5,0,1,3,0,5,3,5,4,4,4,4,3,3,0.0,satisfied +56125,125811,Female,disloyal Customer,31,Business travel,Eco,1013,3,3,3,3,1,3,1,1,4,3,3,3,4,1,0,,neutral or dissatisfied +56126,20143,Male,Loyal Customer,34,Business travel,Business,1771,4,4,5,4,5,3,2,3,3,4,3,4,3,1,5,24.0,satisfied +56127,29913,Female,Loyal Customer,43,Business travel,Business,3132,4,4,4,4,2,5,5,5,5,5,5,5,5,1,0,2.0,satisfied +56128,125744,Female,Loyal Customer,49,Business travel,Business,861,2,3,3,3,1,2,2,2,2,2,2,1,2,4,17,3.0,neutral or dissatisfied +56129,38905,Female,Loyal Customer,46,Business travel,Business,2091,4,4,4,4,3,5,3,5,5,5,4,3,5,5,0,0.0,satisfied +56130,5893,Female,Loyal Customer,54,Business travel,Eco,212,2,3,3,3,1,3,3,2,2,2,2,1,2,4,5,2.0,neutral or dissatisfied +56131,101856,Male,Loyal Customer,49,Business travel,Eco,119,2,4,4,4,3,2,3,3,5,5,4,1,1,3,0,0.0,satisfied +56132,87231,Female,Loyal Customer,46,Business travel,Business,946,3,3,4,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +56133,109068,Female,disloyal Customer,20,Business travel,Business,449,1,1,1,4,1,1,1,1,1,3,4,3,4,1,2,9.0,neutral or dissatisfied +56134,12787,Male,Loyal Customer,63,Personal Travel,Business,489,4,2,4,3,5,4,4,2,2,4,2,4,2,3,25,22.0,neutral or dissatisfied +56135,54024,Female,Loyal Customer,28,Personal Travel,Eco,1091,2,5,2,3,3,2,3,3,3,4,5,3,2,3,0,0.0,neutral or dissatisfied +56136,81220,Female,Loyal Customer,16,Personal Travel,Eco,1426,1,2,1,3,5,1,5,5,4,3,2,4,4,5,0,0.0,neutral or dissatisfied +56137,123621,Male,Loyal Customer,57,Business travel,Business,214,5,5,5,5,4,5,4,4,4,4,5,3,4,3,0,45.0,satisfied +56138,54359,Male,Loyal Customer,37,Business travel,Business,3905,4,3,3,3,1,3,4,4,4,4,4,3,4,2,69,34.0,neutral or dissatisfied +56139,5626,Female,Loyal Customer,44,Personal Travel,Eco,685,3,5,3,4,3,4,5,2,2,3,4,5,2,3,18,23.0,neutral or dissatisfied +56140,12299,Female,Loyal Customer,53,Business travel,Business,3009,4,4,4,4,2,1,1,4,4,4,5,1,4,1,0,0.0,satisfied +56141,108557,Male,Loyal Customer,9,Business travel,Business,2795,1,4,4,4,1,1,1,1,3,1,3,3,3,1,4,0.0,neutral or dissatisfied +56142,94774,Female,Loyal Customer,37,Business travel,Business,277,4,5,5,5,4,2,2,4,4,4,4,3,4,3,24,21.0,neutral or dissatisfied +56143,2592,Female,Loyal Customer,24,Personal Travel,Eco,227,2,4,0,2,1,0,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +56144,101701,Male,disloyal Customer,39,Business travel,Business,1624,4,4,4,4,3,4,3,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +56145,88305,Male,Loyal Customer,30,Business travel,Business,2908,1,1,5,1,5,4,5,5,4,4,4,3,4,5,2,0.0,satisfied +56146,55792,Male,Loyal Customer,57,Business travel,Business,2760,3,4,4,4,2,3,3,1,4,4,3,3,1,3,0,19.0,neutral or dissatisfied +56147,60643,Male,Loyal Customer,39,Business travel,Business,1620,2,2,4,2,4,5,4,4,4,4,4,3,4,4,0,36.0,satisfied +56148,14262,Male,Loyal Customer,36,Business travel,Business,429,5,5,5,5,3,1,3,5,5,5,5,5,5,1,0,0.0,satisfied +56149,81415,Female,Loyal Customer,65,Business travel,Business,2068,5,5,3,5,4,5,5,4,4,4,4,5,4,3,0,,satisfied +56150,16740,Female,Loyal Customer,45,Personal Travel,Eco,1167,3,4,3,3,3,3,3,1,1,3,1,1,1,3,5,0.0,neutral or dissatisfied +56151,109291,Male,Loyal Customer,47,Business travel,Business,3429,4,1,4,4,3,4,4,5,5,5,5,4,5,5,19,43.0,satisfied +56152,9564,Male,Loyal Customer,49,Business travel,Business,1755,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +56153,902,Male,disloyal Customer,47,Business travel,Business,113,1,1,1,3,4,1,1,4,1,3,4,2,3,4,0,0.0,neutral or dissatisfied +56154,63238,Female,disloyal Customer,62,Business travel,Business,447,2,2,2,5,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +56155,32530,Female,disloyal Customer,27,Business travel,Eco,163,1,3,1,4,5,1,5,5,4,1,4,4,4,5,7,9.0,neutral or dissatisfied +56156,126358,Male,Loyal Customer,58,Personal Travel,Eco,468,3,3,3,2,2,3,2,2,1,1,2,3,4,2,6,11.0,neutral or dissatisfied +56157,58862,Female,Loyal Customer,46,Business travel,Business,888,1,1,1,1,5,4,4,4,4,5,4,3,4,5,10,20.0,satisfied +56158,18462,Female,Loyal Customer,48,Business travel,Business,2919,5,5,5,5,4,3,3,5,5,5,5,2,5,2,0,0.0,satisfied +56159,19521,Female,Loyal Customer,57,Business travel,Business,3382,1,1,1,1,4,4,5,4,4,5,5,4,4,3,0,0.0,satisfied +56160,18431,Male,Loyal Customer,56,Business travel,Business,3980,4,4,4,4,3,5,5,4,4,4,4,5,4,3,8,9.0,satisfied +56161,87304,Male,Loyal Customer,70,Personal Travel,Eco,577,4,5,4,4,4,4,4,4,3,4,5,5,5,4,51,63.0,neutral or dissatisfied +56162,87416,Female,Loyal Customer,57,Personal Travel,Eco,425,3,0,3,2,5,4,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +56163,60404,Female,Loyal Customer,22,Personal Travel,Eco,1452,2,3,2,4,3,2,3,3,2,3,4,1,2,3,25,22.0,neutral or dissatisfied +56164,9874,Male,disloyal Customer,27,Business travel,Business,534,1,1,1,1,1,1,1,1,5,3,4,4,5,1,55,54.0,neutral or dissatisfied +56165,7627,Female,Loyal Customer,29,Personal Travel,Business,604,5,4,5,5,4,5,1,4,5,4,4,4,4,4,0,4.0,satisfied +56166,41870,Male,Loyal Customer,49,Business travel,Eco Plus,483,4,2,2,2,5,4,5,5,5,1,5,1,4,5,0,0.0,satisfied +56167,123759,Female,Loyal Customer,39,Business travel,Business,2674,2,2,5,2,3,4,5,4,4,4,4,5,4,3,97,98.0,satisfied +56168,33604,Male,disloyal Customer,33,Business travel,Eco,413,4,3,4,3,5,4,2,5,4,4,1,2,2,5,40,30.0,neutral or dissatisfied +56169,113169,Male,Loyal Customer,36,Business travel,Business,1504,1,2,2,2,1,4,3,1,1,1,1,2,1,1,2,0.0,neutral or dissatisfied +56170,129501,Female,Loyal Customer,46,Business travel,Business,1846,1,1,1,1,2,5,4,5,5,5,5,3,5,3,2,9.0,satisfied +56171,123177,Female,Loyal Customer,39,Business travel,Eco,328,4,2,2,2,4,4,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +56172,19021,Male,Loyal Customer,64,Personal Travel,Eco,788,3,5,3,1,2,3,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +56173,47488,Female,Loyal Customer,65,Personal Travel,Eco,584,4,4,4,2,5,4,5,2,2,4,2,3,2,5,1,1.0,neutral or dissatisfied +56174,101594,Male,Loyal Customer,41,Business travel,Business,1139,3,3,3,3,4,5,4,5,5,5,5,5,5,3,5,0.0,satisfied +56175,22591,Male,disloyal Customer,20,Business travel,Eco,300,2,0,2,4,4,2,1,4,5,1,3,4,5,4,0,0.0,neutral or dissatisfied +56176,4864,Male,Loyal Customer,30,Personal Travel,Eco,500,1,4,1,4,4,1,4,4,1,2,3,4,4,4,15,6.0,neutral or dissatisfied +56177,109798,Female,disloyal Customer,20,Business travel,Business,1073,5,5,5,4,5,5,5,5,3,2,5,5,5,5,52,29.0,satisfied +56178,104998,Male,Loyal Customer,37,Personal Travel,Eco,314,1,4,1,5,4,1,4,4,4,2,4,5,5,4,15,13.0,neutral or dissatisfied +56179,51745,Female,Loyal Customer,23,Personal Travel,Eco,261,2,4,2,4,5,2,5,5,1,1,3,4,1,5,0,0.0,neutral or dissatisfied +56180,37019,Male,Loyal Customer,51,Personal Travel,Eco,759,3,3,4,3,4,4,3,4,5,3,3,5,2,4,0,0.0,neutral or dissatisfied +56181,36979,Male,Loyal Customer,45,Business travel,Business,759,1,1,2,1,3,2,3,4,4,4,4,1,4,4,14,4.0,satisfied +56182,25846,Male,Loyal Customer,30,Business travel,Business,3133,2,2,2,2,4,4,4,4,5,4,2,1,3,4,9,0.0,satisfied +56183,116132,Female,Loyal Customer,70,Personal Travel,Eco,337,1,4,1,2,4,5,4,4,4,1,4,5,4,3,2,0.0,neutral or dissatisfied +56184,90571,Male,Loyal Customer,42,Business travel,Business,2488,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +56185,67874,Male,Loyal Customer,47,Personal Travel,Eco,1464,3,5,3,3,5,3,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +56186,30244,Male,Loyal Customer,44,Personal Travel,Eco,896,1,5,1,4,3,1,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +56187,21530,Female,Loyal Customer,56,Personal Travel,Eco,399,4,4,4,3,5,4,4,1,1,4,1,5,1,5,0,0.0,neutral or dissatisfied +56188,2541,Female,Loyal Customer,56,Business travel,Business,280,4,4,4,4,4,5,4,5,5,5,5,4,5,3,10,4.0,satisfied +56189,77130,Male,Loyal Customer,39,Personal Travel,Eco Plus,1481,3,4,4,4,1,4,1,1,5,5,5,5,3,1,0,0.0,neutral or dissatisfied +56190,44793,Male,Loyal Customer,41,Business travel,Eco Plus,1250,5,4,4,4,5,5,5,5,5,1,4,1,3,5,19,20.0,satisfied +56191,51649,Male,Loyal Customer,44,Business travel,Business,2760,2,4,4,4,3,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +56192,76060,Female,Loyal Customer,45,Business travel,Business,3560,4,4,4,4,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +56193,71689,Male,Loyal Customer,70,Personal Travel,Eco,1182,5,4,5,1,4,5,4,4,3,4,3,3,4,4,0,0.0,satisfied +56194,72201,Female,Loyal Customer,23,Personal Travel,Eco,594,5,4,5,5,4,5,4,4,4,2,3,1,4,4,0,5.0,satisfied +56195,57286,Female,Loyal Customer,44,Business travel,Business,2033,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +56196,29429,Female,Loyal Customer,44,Business travel,Business,2149,3,3,4,3,4,5,1,4,4,4,4,1,4,3,0,0.0,satisfied +56197,73435,Male,Loyal Customer,39,Personal Travel,Eco,1182,1,5,2,4,2,2,2,2,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +56198,2485,Female,Loyal Customer,33,Business travel,Business,1379,3,3,3,3,2,5,5,3,3,4,3,4,3,4,0,8.0,satisfied +56199,90087,Male,Loyal Customer,46,Business travel,Eco,957,1,2,2,2,1,1,1,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +56200,79565,Female,Loyal Customer,47,Business travel,Business,3724,3,3,3,3,4,4,5,5,5,5,5,4,5,4,11,42.0,satisfied +56201,20524,Female,Loyal Customer,24,Business travel,Business,2944,3,3,3,3,4,4,4,4,1,2,4,1,4,4,7,0.0,satisfied +56202,16109,Male,Loyal Customer,15,Business travel,Business,725,3,5,5,5,3,3,3,3,4,1,3,1,4,3,11,8.0,neutral or dissatisfied +56203,34804,Female,Loyal Customer,19,Personal Travel,Eco,264,1,2,1,3,3,1,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +56204,40044,Male,disloyal Customer,40,Business travel,Eco,926,4,4,4,4,1,4,1,1,4,1,4,1,3,1,2,0.0,satisfied +56205,24625,Male,Loyal Customer,38,Business travel,Business,3185,5,5,2,5,1,2,2,4,4,4,5,1,4,4,0,0.0,satisfied +56206,94376,Male,Loyal Customer,51,Business travel,Business,3529,3,3,3,3,5,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +56207,70746,Female,Loyal Customer,27,Personal Travel,Eco,675,5,4,5,3,1,5,1,1,1,5,3,1,4,1,0,0.0,satisfied +56208,112881,Male,disloyal Customer,50,Business travel,Business,1476,3,2,2,4,4,3,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +56209,50731,Male,Loyal Customer,18,Personal Travel,Eco,109,3,3,3,4,5,3,5,5,1,3,4,1,3,5,0,2.0,neutral or dissatisfied +56210,27643,Male,Loyal Customer,10,Personal Travel,Eco Plus,679,2,4,2,3,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +56211,97204,Male,Loyal Customer,16,Personal Travel,Eco,1390,3,4,3,4,3,3,3,3,5,4,5,4,5,3,12,0.0,neutral or dissatisfied +56212,74186,Male,Loyal Customer,48,Personal Travel,Eco,641,2,1,2,4,1,2,1,1,4,2,4,2,3,1,2,0.0,neutral or dissatisfied +56213,8315,Female,Loyal Customer,37,Business travel,Eco Plus,294,2,4,4,4,2,2,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +56214,108423,Female,Loyal Customer,46,Business travel,Business,1444,2,2,2,2,3,5,5,4,4,4,4,4,4,5,19,14.0,satisfied +56215,103211,Female,disloyal Customer,24,Business travel,Eco,351,3,0,3,3,5,3,5,5,5,2,4,4,5,5,10,0.0,neutral or dissatisfied +56216,103865,Female,Loyal Customer,48,Personal Travel,Eco,1072,1,4,1,3,5,5,5,3,3,1,5,4,3,5,0,1.0,neutral or dissatisfied +56217,84400,Female,Loyal Customer,48,Business travel,Business,1858,3,4,4,4,5,4,3,3,3,3,3,2,3,3,73,79.0,neutral or dissatisfied +56218,75018,Female,Loyal Customer,44,Business travel,Business,2119,5,5,5,5,5,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +56219,41956,Female,Loyal Customer,31,Business travel,Business,2174,3,2,3,3,2,2,2,2,4,3,2,5,3,2,0,0.0,satisfied +56220,110645,Male,Loyal Customer,34,Business travel,Business,837,5,5,5,5,5,5,4,4,4,5,4,5,4,5,84,77.0,satisfied +56221,7879,Male,disloyal Customer,27,Business travel,Business,948,1,1,1,4,3,1,1,3,5,3,4,4,4,3,46,28.0,neutral or dissatisfied +56222,24990,Female,Loyal Customer,51,Business travel,Business,484,2,4,4,4,4,3,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +56223,128158,Female,disloyal Customer,35,Business travel,Eco,1788,2,1,1,3,5,2,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +56224,36316,Male,Loyal Customer,53,Business travel,Eco,395,3,4,4,4,3,3,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +56225,59730,Male,Loyal Customer,29,Personal Travel,Eco Plus,964,3,4,3,3,2,3,2,2,4,4,4,3,5,2,8,0.0,neutral or dissatisfied +56226,124797,Male,Loyal Customer,38,Business travel,Eco,280,1,3,3,3,1,1,1,1,3,4,3,4,4,1,16,35.0,neutral or dissatisfied +56227,114281,Female,Loyal Customer,10,Personal Travel,Eco,853,3,4,3,3,3,4,4,4,5,4,4,4,5,4,372,368.0,neutral or dissatisfied +56228,56369,Female,Loyal Customer,39,Personal Travel,Eco,200,3,2,3,4,2,3,2,2,1,5,4,4,3,2,1,0.0,neutral or dissatisfied +56229,84973,Female,Loyal Customer,40,Business travel,Business,1590,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +56230,19182,Female,Loyal Customer,31,Business travel,Business,2223,5,5,5,5,5,5,5,5,4,4,2,5,1,5,0,0.0,satisfied +56231,51599,Male,Loyal Customer,31,Business travel,Eco,493,5,1,1,1,5,5,5,5,1,5,1,3,2,5,0,0.0,satisfied +56232,64556,Male,disloyal Customer,22,Business travel,Business,224,4,0,5,4,1,5,1,1,3,5,4,5,5,1,31,33.0,satisfied +56233,72107,Female,Loyal Customer,46,Personal Travel,Eco Plus,2556,4,1,4,1,4,2,2,2,2,4,5,1,2,3,0,0.0,neutral or dissatisfied +56234,6173,Female,Loyal Customer,60,Personal Travel,Eco,409,3,4,3,4,3,3,3,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +56235,18236,Male,Loyal Customer,45,Business travel,Business,179,1,1,1,1,2,5,3,5,5,5,5,4,5,2,0,0.0,satisfied +56236,76085,Male,Loyal Customer,33,Business travel,Business,2688,1,5,2,5,1,1,1,1,3,4,3,4,4,1,14,8.0,neutral or dissatisfied +56237,17829,Male,Loyal Customer,41,Business travel,Eco Plus,1075,4,1,1,1,5,4,5,5,4,3,4,2,1,5,0,0.0,satisfied +56238,104242,Female,Loyal Customer,42,Business travel,Business,1276,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +56239,11145,Male,Loyal Customer,51,Personal Travel,Eco,247,3,4,0,2,3,0,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +56240,108824,Male,Loyal Customer,26,Business travel,Business,2595,3,3,3,3,4,4,4,4,5,4,5,3,5,4,5,0.0,satisfied +56241,126646,Female,Loyal Customer,25,Business travel,Business,602,2,2,2,2,4,4,4,4,3,4,5,4,5,4,2,0.0,satisfied +56242,64319,Male,Loyal Customer,33,Business travel,Business,2669,3,1,4,4,3,3,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +56243,47978,Female,Loyal Customer,10,Personal Travel,Eco,838,1,4,1,4,5,1,4,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +56244,40419,Female,Loyal Customer,57,Business travel,Business,1936,2,2,2,2,1,4,2,5,5,5,4,1,5,4,0,0.0,satisfied +56245,101209,Male,Loyal Customer,53,Personal Travel,Eco,583,2,4,2,3,2,2,2,2,3,4,4,5,5,2,93,77.0,neutral or dissatisfied +56246,88420,Female,Loyal Customer,41,Business travel,Business,2136,4,4,4,4,2,4,4,4,4,4,4,1,4,3,6,4.0,neutral or dissatisfied +56247,128418,Female,Loyal Customer,15,Business travel,Business,647,2,4,4,4,2,2,2,2,3,2,4,1,3,2,17,27.0,neutral or dissatisfied +56248,15379,Male,Loyal Customer,45,Business travel,Eco,306,5,4,4,4,5,5,5,5,1,5,2,1,2,5,1,0.0,satisfied +56249,9659,Male,disloyal Customer,48,Business travel,Business,212,4,4,4,3,4,4,2,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +56250,123370,Male,Loyal Customer,36,Personal Travel,Eco,644,5,5,5,3,4,5,4,4,3,2,4,5,4,4,22,17.0,satisfied +56251,32019,Female,disloyal Customer,28,Business travel,Eco,102,4,5,4,5,5,4,5,5,1,3,1,3,4,5,0,0.0,neutral or dissatisfied +56252,67195,Male,Loyal Customer,24,Personal Travel,Eco,1121,3,5,3,3,1,3,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +56253,100729,Male,disloyal Customer,38,Business travel,Eco,328,3,1,3,4,1,3,3,1,2,2,4,4,3,1,21,20.0,neutral or dissatisfied +56254,90187,Female,Loyal Customer,28,Personal Travel,Eco,983,2,4,2,3,5,2,1,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +56255,118823,Male,disloyal Customer,33,Business travel,Business,647,2,2,2,2,5,2,5,5,5,4,5,5,5,5,30,29.0,neutral or dissatisfied +56256,21421,Male,Loyal Customer,23,Business travel,Business,331,1,5,5,5,1,1,1,1,1,4,4,1,4,1,91,73.0,neutral or dissatisfied +56257,34712,Female,disloyal Customer,20,Business travel,Eco,209,3,3,3,3,4,3,4,4,5,5,3,2,3,4,24,14.0,neutral or dissatisfied +56258,97132,Female,Loyal Customer,49,Business travel,Business,3370,1,1,1,1,5,2,2,1,1,1,1,3,1,2,13,13.0,neutral or dissatisfied +56259,103102,Male,Loyal Customer,10,Personal Travel,Eco,328,1,1,3,3,2,3,2,2,4,2,4,4,3,2,0,0.0,neutral or dissatisfied +56260,95779,Female,Loyal Customer,40,Personal Travel,Eco,181,4,4,0,2,3,0,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +56261,21678,Male,Loyal Customer,68,Business travel,Business,746,3,5,3,5,3,3,4,3,3,3,3,1,3,2,130,129.0,neutral or dissatisfied +56262,4720,Male,Loyal Customer,26,Business travel,Business,3332,4,4,4,4,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +56263,60219,Male,Loyal Customer,28,Business travel,Business,1703,5,5,5,5,5,4,5,5,3,5,3,4,4,5,0,0.0,satisfied +56264,5937,Male,Loyal Customer,40,Business travel,Business,1588,3,3,3,3,4,4,4,4,4,4,4,5,4,5,46,48.0,satisfied +56265,88965,Male,Loyal Customer,31,Business travel,Business,3204,3,3,3,3,3,3,3,3,3,2,2,2,3,3,0,11.0,neutral or dissatisfied +56266,128809,Female,Loyal Customer,44,Business travel,Business,2475,4,4,4,4,4,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +56267,57302,Female,disloyal Customer,65,Business travel,Business,236,3,3,3,3,2,3,2,2,2,4,4,4,3,2,48,38.0,neutral or dissatisfied +56268,48717,Female,Loyal Customer,52,Business travel,Business,2892,4,4,5,4,2,4,4,5,5,5,4,4,5,4,9,13.0,satisfied +56269,1477,Female,Loyal Customer,62,Personal Travel,Eco Plus,695,5,4,5,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +56270,56031,Male,Loyal Customer,42,Business travel,Business,2586,2,5,5,5,2,2,2,2,1,2,3,2,3,2,7,34.0,neutral or dissatisfied +56271,34294,Female,Loyal Customer,57,Personal Travel,Eco,496,2,5,5,3,2,4,4,1,1,5,4,4,1,3,0,0.0,neutral or dissatisfied +56272,40809,Female,disloyal Customer,24,Business travel,Eco,558,1,4,1,3,1,1,1,1,3,3,4,1,3,1,22,18.0,neutral or dissatisfied +56273,111544,Male,Loyal Customer,59,Business travel,Business,775,5,5,4,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +56274,78818,Male,Loyal Customer,58,Personal Travel,Eco,447,1,5,1,2,4,1,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +56275,117638,Female,Loyal Customer,9,Personal Travel,Eco,872,4,4,3,4,4,3,4,4,2,5,3,4,3,4,16,14.0,neutral or dissatisfied +56276,65730,Male,Loyal Customer,41,Business travel,Business,2499,5,5,5,5,3,4,4,4,4,4,4,5,4,3,3,1.0,satisfied +56277,108456,Female,disloyal Customer,18,Business travel,Eco,1444,4,4,4,3,1,4,1,1,3,2,4,1,4,1,16,21.0,neutral or dissatisfied +56278,21218,Male,Loyal Customer,60,Personal Travel,Eco,192,5,5,5,1,5,5,5,5,3,4,5,3,5,5,0,0.0,satisfied +56279,105698,Male,disloyal Customer,32,Business travel,Business,925,3,3,3,4,1,3,2,1,5,2,4,5,5,1,4,16.0,neutral or dissatisfied +56280,39839,Male,Loyal Customer,37,Business travel,Eco,272,4,3,3,3,4,4,4,4,5,5,2,5,4,4,0,0.0,satisfied +56281,127580,Male,Loyal Customer,58,Business travel,Business,1773,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +56282,27396,Female,Loyal Customer,26,Business travel,Eco,605,0,5,0,3,2,0,1,2,4,2,5,3,3,2,0,0.0,satisfied +56283,108596,Female,Loyal Customer,61,Business travel,Eco,696,4,5,5,5,3,3,3,5,5,4,5,2,5,3,36,39.0,neutral or dissatisfied +56284,67354,Female,Loyal Customer,35,Personal Travel,Eco,1471,3,4,3,4,4,3,4,4,4,3,4,4,5,4,16,0.0,neutral or dissatisfied +56285,11438,Male,Loyal Customer,10,Business travel,Eco Plus,482,3,4,4,4,3,3,1,3,2,5,3,3,4,3,1,6.0,neutral or dissatisfied +56286,49751,Female,disloyal Customer,59,Business travel,Eco,86,1,0,1,3,3,1,4,3,3,4,1,2,5,3,17,16.0,neutral or dissatisfied +56287,80079,Female,Loyal Customer,23,Business travel,Business,3076,1,1,1,1,5,5,5,5,4,5,4,5,4,5,0,9.0,satisfied +56288,28094,Male,Loyal Customer,63,Personal Travel,Business,933,3,1,3,3,4,3,3,2,2,3,2,2,2,3,13,0.0,neutral or dissatisfied +56289,20452,Male,disloyal Customer,40,Business travel,Eco,84,3,3,3,2,1,3,1,1,2,4,2,2,3,1,103,103.0,neutral or dissatisfied +56290,5982,Female,disloyal Customer,22,Business travel,Eco,1041,5,5,5,4,3,5,3,3,5,5,4,3,4,3,0,0.0,satisfied +56291,16058,Female,Loyal Customer,40,Business travel,Eco,744,4,2,2,2,4,4,4,4,2,3,4,1,3,4,6,0.0,satisfied +56292,50681,Female,Loyal Customer,16,Personal Travel,Eco,209,4,2,4,4,4,4,4,4,4,1,4,3,3,4,0,0.0,neutral or dissatisfied +56293,53817,Male,Loyal Customer,47,Business travel,Business,140,0,4,0,2,3,2,2,4,4,4,4,3,4,1,18,27.0,satisfied +56294,10637,Male,Loyal Customer,41,Business travel,Business,2798,3,3,3,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +56295,18436,Male,Loyal Customer,39,Business travel,Business,2697,0,4,0,4,4,5,5,1,1,1,1,3,1,5,0,17.0,satisfied +56296,86977,Male,Loyal Customer,64,Business travel,Business,907,1,1,1,1,1,3,3,1,1,1,1,2,1,4,5,0.0,neutral or dissatisfied +56297,87020,Male,Loyal Customer,59,Business travel,Business,3862,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +56298,114152,Female,Loyal Customer,27,Business travel,Business,2272,2,2,5,2,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +56299,124696,Female,disloyal Customer,37,Business travel,Eco,399,1,1,1,3,2,1,2,2,3,1,3,4,3,2,0,3.0,neutral or dissatisfied +56300,110491,Female,Loyal Customer,41,Personal Travel,Eco,663,3,5,3,2,3,3,2,3,1,3,2,3,3,3,26,12.0,neutral or dissatisfied +56301,111494,Male,Loyal Customer,41,Business travel,Business,2169,3,3,3,3,5,4,5,4,4,4,4,3,4,5,37,30.0,satisfied +56302,1778,Female,disloyal Customer,30,Business travel,Business,408,3,3,3,1,3,3,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +56303,110641,Male,Loyal Customer,23,Business travel,Business,2442,3,3,3,3,5,4,5,5,4,5,5,4,4,5,0,0.0,satisfied +56304,62369,Female,Loyal Customer,40,Business travel,Business,2704,4,4,5,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +56305,33535,Female,Loyal Customer,45,Business travel,Business,2351,3,3,3,3,5,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +56306,32304,Male,disloyal Customer,38,Business travel,Business,216,4,4,4,4,4,4,4,4,2,4,4,2,2,4,6,12.0,satisfied +56307,108990,Male,disloyal Customer,27,Business travel,Business,1041,4,4,4,2,5,4,4,5,4,4,4,5,4,5,0,0.0,satisfied +56308,56596,Female,Loyal Customer,46,Business travel,Business,3117,1,1,2,1,3,5,4,4,4,4,4,4,4,3,36,48.0,satisfied +56309,72403,Male,Loyal Customer,58,Business travel,Business,964,3,3,3,3,5,5,4,1,1,2,1,3,1,4,85,84.0,satisfied +56310,20504,Female,Loyal Customer,22,Personal Travel,Eco,130,2,0,0,4,1,0,1,1,5,5,5,3,2,1,0,21.0,neutral or dissatisfied +56311,6242,Male,disloyal Customer,21,Business travel,Eco,594,3,2,3,4,2,3,2,2,3,3,3,2,3,2,1,0.0,neutral or dissatisfied +56312,33091,Female,Loyal Customer,36,Personal Travel,Eco,163,4,4,4,4,3,4,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +56313,24737,Male,Loyal Customer,43,Business travel,Business,2029,1,2,2,2,4,3,3,1,1,1,1,1,1,2,0,6.0,neutral or dissatisfied +56314,61133,Male,Loyal Customer,21,Personal Travel,Business,853,2,4,2,3,5,2,5,5,3,2,4,4,4,5,0,3.0,neutral or dissatisfied +56315,128964,Female,Loyal Customer,62,Business travel,Eco,414,5,2,2,2,3,1,4,5,5,5,5,2,5,3,96,90.0,satisfied +56316,90552,Male,disloyal Customer,25,Business travel,Business,240,2,0,3,4,2,3,4,2,4,4,4,4,5,2,4,3.0,neutral or dissatisfied +56317,121463,Male,Loyal Customer,38,Personal Travel,Eco,257,1,3,1,3,2,1,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +56318,9404,Female,Loyal Customer,21,Personal Travel,Business,1027,2,5,2,1,5,2,5,5,3,4,5,3,4,5,0,1.0,neutral or dissatisfied +56319,125105,Female,Loyal Customer,24,Business travel,Business,361,3,2,2,2,3,3,3,3,4,5,3,1,3,3,0,12.0,neutral or dissatisfied +56320,49043,Female,Loyal Customer,36,Business travel,Business,337,5,5,5,5,5,3,3,4,4,4,4,2,4,4,16,23.0,satisfied +56321,17251,Female,disloyal Customer,24,Business travel,Eco,692,3,2,2,3,4,2,4,4,2,4,4,2,4,4,15,2.0,neutral or dissatisfied +56322,127121,Male,Loyal Customer,24,Personal Travel,Eco,651,4,4,4,3,2,4,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +56323,29857,Male,Loyal Customer,30,Business travel,Business,1943,2,2,2,2,5,5,5,5,5,3,3,4,3,5,0,5.0,satisfied +56324,83879,Male,Loyal Customer,59,Business travel,Business,1670,5,5,5,5,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +56325,53993,Female,Loyal Customer,33,Business travel,Eco,1825,4,4,4,4,4,4,4,4,2,1,5,3,1,4,14,0.0,satisfied +56326,4465,Male,Loyal Customer,57,Business travel,Eco,605,1,3,3,3,1,1,1,1,4,5,4,3,3,1,21,18.0,neutral or dissatisfied +56327,66624,Male,Loyal Customer,52,Business travel,Business,802,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +56328,57809,Male,Loyal Customer,35,Personal Travel,Eco,1235,3,5,3,1,5,3,5,5,3,2,3,5,5,5,0,0.0,neutral or dissatisfied +56329,56113,Female,Loyal Customer,27,Business travel,Business,1400,4,4,4,4,5,5,5,5,5,5,5,5,5,5,0,5.0,satisfied +56330,77174,Male,Loyal Customer,67,Personal Travel,Eco,1355,0,2,0,3,2,0,2,2,4,3,3,3,4,2,0,0.0,satisfied +56331,22056,Female,Loyal Customer,48,Business travel,Business,2133,1,1,1,1,4,4,1,5,5,5,5,3,5,4,72,61.0,satisfied +56332,113924,Female,Loyal Customer,64,Personal Travel,Eco,1670,2,4,2,3,2,2,3,4,4,2,4,4,4,1,3,0.0,neutral or dissatisfied +56333,36096,Female,Loyal Customer,49,Personal Travel,Eco,399,3,4,3,3,3,4,5,4,4,3,4,4,4,5,6,13.0,neutral or dissatisfied +56334,26881,Male,Loyal Customer,44,Business travel,Eco,689,2,2,2,2,2,2,2,2,4,1,3,4,2,2,0,0.0,satisfied +56335,10143,Male,disloyal Customer,22,Business travel,Business,1157,2,4,2,3,4,2,4,4,4,5,3,3,4,4,13,4.0,neutral or dissatisfied +56336,127880,Male,Loyal Customer,65,Personal Travel,Eco,1276,2,4,2,5,1,2,1,1,3,5,4,3,4,1,0,1.0,neutral or dissatisfied +56337,77705,Male,Loyal Customer,10,Business travel,Business,731,4,4,4,4,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +56338,121774,Female,Loyal Customer,63,Business travel,Business,337,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +56339,113239,Male,Loyal Customer,70,Personal Travel,Business,197,2,5,2,3,5,1,1,3,3,2,3,1,3,5,2,0.0,neutral or dissatisfied +56340,59447,Female,Loyal Customer,53,Business travel,Business,1637,2,2,2,2,3,5,5,4,4,4,4,5,4,5,25,35.0,satisfied +56341,1303,Female,Loyal Customer,53,Personal Travel,Eco,309,2,3,4,3,3,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +56342,109040,Female,Loyal Customer,29,Business travel,Business,849,3,3,3,3,3,3,3,3,2,5,4,2,3,3,22,8.0,neutral or dissatisfied +56343,115836,Female,Loyal Customer,71,Business travel,Eco,337,5,1,1,1,3,4,1,5,5,5,5,5,5,1,0,0.0,satisfied +56344,97062,Female,Loyal Customer,29,Business travel,Business,1357,4,4,4,4,4,4,4,4,4,3,5,3,5,4,3,0.0,satisfied +56345,81282,Male,Loyal Customer,48,Business travel,Business,3948,5,5,5,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +56346,125113,Male,disloyal Customer,26,Business travel,Business,361,3,3,3,1,3,3,1,3,4,3,4,3,2,3,0,0.0,neutral or dissatisfied +56347,80724,Male,Loyal Customer,31,Business travel,Business,448,5,5,5,5,2,3,2,2,4,2,5,3,4,2,0,3.0,satisfied +56348,100546,Male,Loyal Customer,9,Business travel,Eco Plus,580,2,4,3,3,2,1,4,2,3,5,4,4,4,2,31,15.0,neutral or dissatisfied +56349,59617,Male,Loyal Customer,55,Business travel,Eco,964,2,1,3,1,2,2,2,2,2,3,4,1,4,2,0,0.0,neutral or dissatisfied +56350,74902,Male,Loyal Customer,27,Business travel,Business,2586,4,4,4,4,4,4,4,4,4,4,5,3,4,4,4,0.0,satisfied +56351,34765,Female,Loyal Customer,67,Business travel,Business,264,4,5,5,5,1,4,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +56352,51139,Female,Loyal Customer,13,Personal Travel,Eco,373,2,1,3,3,5,3,5,5,4,3,2,4,3,5,0,0.0,neutral or dissatisfied +56353,35255,Male,disloyal Customer,24,Business travel,Eco,1035,1,1,1,3,4,1,4,4,5,1,2,3,2,4,0,0.0,neutral or dissatisfied +56354,127127,Female,Loyal Customer,34,Personal Travel,Eco,338,2,5,2,1,3,2,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +56355,62570,Female,Loyal Customer,25,Business travel,Business,1726,1,4,4,4,1,1,1,1,2,5,3,3,4,1,14,0.0,neutral or dissatisfied +56356,4680,Female,Loyal Customer,55,Personal Travel,Eco,364,5,5,5,3,5,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +56357,65548,Male,Loyal Customer,58,Business travel,Business,3884,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +56358,129468,Male,Loyal Customer,33,Business travel,Business,2704,3,3,3,3,4,4,4,4,5,3,4,5,4,4,3,21.0,satisfied +56359,73697,Male,Loyal Customer,54,Business travel,Eco,192,2,4,4,4,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +56360,41646,Female,disloyal Customer,45,Business travel,Eco,347,1,0,1,4,3,1,4,3,2,4,2,2,1,3,0,9.0,neutral or dissatisfied +56361,6701,Male,Loyal Customer,56,Business travel,Business,2071,3,1,1,1,3,3,3,3,3,3,3,3,3,2,40,33.0,neutral or dissatisfied +56362,16503,Male,Loyal Customer,15,Personal Travel,Eco,246,1,4,1,4,4,1,2,4,3,3,5,3,5,4,0,5.0,neutral or dissatisfied +56363,41430,Male,Loyal Customer,42,Personal Travel,Eco,809,1,4,1,3,5,1,5,5,3,3,3,3,4,5,66,52.0,neutral or dissatisfied +56364,74344,Male,Loyal Customer,52,Personal Travel,Business,1188,2,5,2,1,2,4,5,1,1,2,1,3,1,5,21,9.0,neutral or dissatisfied +56365,9367,Male,Loyal Customer,41,Business travel,Eco,401,2,5,5,5,2,2,2,1,2,3,3,2,3,2,30,134.0,neutral or dissatisfied +56366,3897,Male,Loyal Customer,60,Business travel,Eco,213,4,2,2,2,4,4,4,4,3,2,4,3,1,4,27,24.0,satisfied +56367,13909,Male,Loyal Customer,38,Business travel,Eco,192,4,1,4,1,4,4,4,4,5,3,3,5,5,4,0,0.0,satisfied +56368,37556,Male,Loyal Customer,35,Business travel,Eco,1076,4,2,2,2,4,4,4,4,3,5,2,1,5,4,0,0.0,satisfied +56369,82165,Male,Loyal Customer,35,Personal Travel,Eco,311,3,5,5,3,1,5,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +56370,125948,Female,Loyal Customer,26,Personal Travel,Eco,992,4,4,3,4,4,3,5,4,3,4,4,4,4,4,110,107.0,neutral or dissatisfied +56371,118810,Female,Loyal Customer,30,Personal Travel,Eco,621,3,4,3,5,4,3,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +56372,11601,Female,Loyal Customer,33,Personal Travel,Eco,771,5,5,5,3,3,5,2,3,4,5,4,5,5,3,103,98.0,satisfied +56373,128654,Female,Loyal Customer,53,Business travel,Business,2442,4,4,4,4,5,5,5,3,2,5,5,5,3,5,137,166.0,satisfied +56374,26495,Female,Loyal Customer,21,Business travel,Business,829,5,5,5,5,4,4,4,4,5,5,2,2,2,4,0,0.0,satisfied +56375,82568,Male,Loyal Customer,37,Business travel,Business,528,4,4,3,4,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +56376,13938,Female,Loyal Customer,47,Business travel,Business,317,3,1,1,1,4,4,3,3,3,3,3,4,3,4,19,6.0,neutral or dissatisfied +56377,26834,Female,Loyal Customer,45,Business travel,Eco,224,5,3,3,3,3,5,2,5,5,5,5,3,5,5,0,0.0,satisfied +56378,82656,Female,Loyal Customer,46,Business travel,Business,2279,5,5,4,5,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +56379,53915,Male,Loyal Customer,50,Personal Travel,Eco,191,2,4,2,3,2,2,3,2,4,4,5,4,5,2,0,7.0,neutral or dissatisfied +56380,108795,Female,Loyal Customer,29,Personal Travel,Eco,581,1,5,1,3,1,1,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +56381,125479,Female,Loyal Customer,61,Personal Travel,Eco,2979,4,4,4,3,4,2,2,5,2,3,5,2,4,2,0,0.0,satisfied +56382,129359,Male,Loyal Customer,9,Personal Travel,Eco Plus,2475,1,1,1,3,1,1,5,1,1,2,3,1,3,1,6,15.0,neutral or dissatisfied +56383,46117,Male,Loyal Customer,35,Business travel,Business,604,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +56384,50158,Female,Loyal Customer,33,Business travel,Business,78,5,5,4,5,1,3,4,5,5,5,5,2,5,5,0,0.0,satisfied +56385,58417,Male,disloyal Customer,27,Business travel,Eco,733,3,3,3,4,3,3,3,3,3,2,4,4,4,3,2,8.0,neutral or dissatisfied +56386,90032,Male,Loyal Customer,53,Business travel,Business,2923,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +56387,34481,Male,Loyal Customer,62,Personal Travel,Eco,266,3,4,3,2,3,3,3,3,2,2,1,2,3,3,0,0.0,neutral or dissatisfied +56388,78501,Female,Loyal Customer,55,Business travel,Eco,126,3,1,1,1,3,3,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +56389,42079,Female,disloyal Customer,19,Business travel,Eco,116,4,4,4,4,2,4,2,2,3,3,3,2,3,2,0,5.0,neutral or dissatisfied +56390,122025,Female,Loyal Customer,73,Business travel,Business,2047,2,3,3,3,2,3,4,4,4,4,2,3,4,2,3,12.0,neutral or dissatisfied +56391,10577,Male,disloyal Customer,17,Business travel,Eco,429,1,4,1,3,2,1,2,2,1,4,3,4,3,2,23,18.0,neutral or dissatisfied +56392,44411,Female,Loyal Customer,41,Personal Travel,Eco,265,3,3,0,2,2,0,2,2,4,4,5,3,4,2,49,77.0,neutral or dissatisfied +56393,88214,Male,Loyal Customer,53,Business travel,Business,366,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +56394,41352,Female,Loyal Customer,47,Business travel,Business,3892,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +56395,29990,Male,disloyal Customer,28,Business travel,Eco,261,1,3,1,2,3,1,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +56396,60980,Male,Loyal Customer,7,Personal Travel,Eco,888,2,3,2,1,2,2,2,2,5,1,4,4,3,2,0,18.0,neutral or dissatisfied +56397,27804,Male,Loyal Customer,57,Business travel,Business,2495,1,5,5,5,2,4,3,1,1,1,1,4,1,2,128,128.0,neutral or dissatisfied +56398,88662,Female,Loyal Customer,33,Personal Travel,Eco,545,2,3,2,2,3,2,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +56399,120677,Male,disloyal Customer,55,Business travel,Business,280,5,2,2,1,4,5,4,4,4,2,4,3,3,4,0,0.0,satisfied +56400,6479,Female,Loyal Customer,22,Business travel,Business,557,5,5,4,5,4,5,4,4,4,5,5,5,5,4,0,6.0,satisfied +56401,90888,Male,Loyal Customer,61,Business travel,Eco,270,4,3,3,3,4,4,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +56402,127530,Male,Loyal Customer,50,Business travel,Business,3281,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +56403,81012,Male,Loyal Customer,51,Business travel,Business,3743,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +56404,37154,Male,disloyal Customer,23,Business travel,Eco,646,2,0,2,5,3,2,3,3,4,2,4,1,2,3,0,2.0,neutral or dissatisfied +56405,127861,Female,Loyal Customer,26,Business travel,Business,1894,2,2,2,2,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +56406,100931,Female,Loyal Customer,23,Personal Travel,Eco,838,3,5,3,4,2,3,2,2,5,4,5,5,5,2,32,11.0,neutral or dissatisfied +56407,116389,Female,Loyal Customer,54,Personal Travel,Eco,373,3,0,3,3,5,1,5,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +56408,108767,Female,disloyal Customer,37,Business travel,Business,581,3,2,2,4,4,2,3,4,4,5,4,3,5,4,3,0.0,satisfied +56409,105585,Male,Loyal Customer,67,Personal Travel,Eco,577,4,2,4,2,1,4,1,1,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +56410,48196,Female,disloyal Customer,42,Business travel,Eco,236,3,0,3,5,1,3,1,1,3,3,4,2,3,1,0,0.0,neutral or dissatisfied +56411,104007,Male,Loyal Customer,39,Personal Travel,Eco,1489,3,3,3,3,1,3,1,1,3,5,3,2,4,1,61,56.0,neutral or dissatisfied +56412,87715,Female,Loyal Customer,53,Business travel,Business,2180,4,4,4,4,2,5,4,5,5,5,5,4,5,4,90,99.0,satisfied +56413,42545,Male,Loyal Customer,34,Business travel,Business,1091,2,2,2,2,4,2,3,5,5,5,5,3,5,1,0,0.0,satisfied +56414,15509,Female,Loyal Customer,41,Personal Travel,Eco,377,4,5,4,2,4,4,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +56415,29268,Female,disloyal Customer,27,Business travel,Eco,834,3,3,3,3,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +56416,107338,Male,disloyal Customer,22,Business travel,Eco,632,3,4,3,3,2,3,3,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +56417,23371,Female,Loyal Customer,48,Business travel,Eco,1014,3,1,1,1,3,4,4,3,3,3,3,2,3,4,25,31.0,neutral or dissatisfied +56418,46541,Male,Loyal Customer,70,Business travel,Business,3490,2,2,2,2,1,3,1,4,4,4,4,1,4,4,23,25.0,satisfied +56419,63913,Male,disloyal Customer,18,Business travel,Business,1192,2,4,2,3,3,2,3,3,1,5,4,4,4,3,0,2.0,neutral or dissatisfied +56420,50203,Female,Loyal Customer,57,Business travel,Eco,89,2,4,4,4,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +56421,11948,Female,Loyal Customer,30,Business travel,Business,781,2,4,4,4,2,2,2,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +56422,28129,Female,Loyal Customer,54,Business travel,Business,3455,4,4,4,4,2,1,2,5,5,5,5,2,5,5,0,0.0,satisfied +56423,123903,Female,Loyal Customer,20,Personal Travel,Eco,544,3,4,5,2,5,5,5,5,4,2,1,4,1,5,0,0.0,neutral or dissatisfied +56424,666,Female,disloyal Customer,26,Business travel,Business,164,3,0,3,4,4,3,2,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +56425,24921,Male,disloyal Customer,21,Business travel,Eco,762,3,3,3,3,2,3,2,2,2,4,4,3,3,2,0,0.0,neutral or dissatisfied +56426,73955,Male,Loyal Customer,70,Personal Travel,Eco,2267,4,5,4,2,3,4,3,3,3,3,5,4,4,3,0,4.0,satisfied +56427,114007,Female,Loyal Customer,45,Personal Travel,Eco,1844,1,4,1,4,5,4,4,4,4,1,4,3,4,3,34,28.0,neutral or dissatisfied +56428,68050,Female,Loyal Customer,56,Business travel,Business,813,4,2,4,4,2,4,4,5,5,4,5,5,5,5,81,70.0,satisfied +56429,7148,Female,disloyal Customer,29,Business travel,Business,139,5,5,5,4,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +56430,108468,Female,Loyal Customer,70,Personal Travel,Eco,1444,2,3,2,1,5,1,3,5,5,2,5,1,5,5,31,16.0,neutral or dissatisfied +56431,124535,Female,Loyal Customer,53,Business travel,Business,3310,1,1,1,1,5,5,5,5,5,4,5,3,5,4,1,0.0,satisfied +56432,32060,Male,Loyal Customer,60,Business travel,Eco,101,4,2,5,5,4,4,4,4,3,3,3,3,1,4,23,23.0,satisfied +56433,112906,Male,Loyal Customer,14,Business travel,Business,1390,2,2,2,2,2,2,2,2,2,1,3,2,3,2,70,67.0,neutral or dissatisfied +56434,102206,Male,Loyal Customer,49,Business travel,Business,1985,0,4,0,4,3,5,5,3,3,3,3,5,3,5,31,27.0,satisfied +56435,73470,Male,Loyal Customer,51,Personal Travel,Eco,1120,2,4,2,4,2,5,5,5,5,4,4,5,3,5,90,134.0,neutral or dissatisfied +56436,31003,Female,disloyal Customer,32,Business travel,Eco,391,2,5,2,1,4,2,4,4,3,4,4,5,3,4,82,79.0,neutral or dissatisfied +56437,115299,Female,Loyal Customer,39,Business travel,Business,325,1,1,3,1,3,5,4,4,4,4,4,4,4,3,1,1.0,satisfied +56438,13148,Female,Loyal Customer,68,Personal Travel,Eco,562,2,4,2,5,2,4,2,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +56439,108466,Female,Loyal Customer,32,Personal Travel,Eco,1444,3,0,3,1,2,3,2,2,5,5,5,4,4,2,59,69.0,neutral or dissatisfied +56440,68793,Male,Loyal Customer,20,Business travel,Business,1021,2,1,1,1,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +56441,76647,Female,Loyal Customer,66,Personal Travel,Eco,547,3,4,3,4,5,2,4,4,4,3,1,4,4,4,7,3.0,neutral or dissatisfied +56442,57904,Female,disloyal Customer,63,Business travel,Eco,305,4,1,4,2,2,4,2,2,4,5,1,3,2,2,0,0.0,neutral or dissatisfied +56443,15489,Male,Loyal Customer,59,Personal Travel,Eco,306,2,2,2,3,5,2,5,5,1,2,4,2,4,5,0,0.0,neutral or dissatisfied +56444,33536,Female,Loyal Customer,60,Business travel,Business,2029,4,4,4,4,3,4,5,5,5,5,5,4,5,5,37,39.0,satisfied +56445,39793,Male,Loyal Customer,59,Business travel,Business,272,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,10.0,satisfied +56446,13685,Male,Loyal Customer,33,Personal Travel,Eco,954,2,4,2,1,1,2,1,1,3,5,5,3,4,1,99,74.0,neutral or dissatisfied +56447,77587,Female,disloyal Customer,28,Business travel,Business,689,1,1,1,3,1,1,1,1,3,4,4,3,4,1,0,17.0,neutral or dissatisfied +56448,106831,Female,Loyal Customer,52,Business travel,Business,1733,1,1,1,1,3,3,5,5,5,5,5,4,5,4,22,17.0,satisfied +56449,96690,Female,Loyal Customer,43,Business travel,Business,2132,3,3,3,3,5,4,5,3,3,4,3,5,3,3,15,13.0,satisfied +56450,44565,Female,Loyal Customer,57,Business travel,Business,157,1,1,1,1,1,1,3,5,5,5,3,3,5,4,0,0.0,satisfied +56451,43892,Male,disloyal Customer,16,Business travel,Eco,174,1,1,1,3,5,1,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +56452,103610,Female,Loyal Customer,30,Personal Travel,Business,405,1,4,1,4,3,1,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +56453,108102,Male,Loyal Customer,31,Business travel,Business,3871,3,3,4,3,4,4,4,4,5,5,4,5,5,4,2,0.0,satisfied +56454,38590,Female,Loyal Customer,56,Business travel,Business,1850,1,1,1,1,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +56455,50340,Female,Loyal Customer,40,Business travel,Business,1610,3,3,3,3,4,2,4,3,3,4,5,1,3,3,0,0.0,satisfied +56456,77693,Female,disloyal Customer,25,Business travel,Business,696,3,4,3,2,5,3,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +56457,79142,Female,Loyal Customer,46,Personal Travel,Eco Plus,226,2,1,2,2,1,2,1,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +56458,5203,Male,Loyal Customer,54,Business travel,Business,293,5,5,5,5,2,5,4,4,4,5,4,4,4,3,20,21.0,satisfied +56459,15848,Male,Loyal Customer,9,Personal Travel,Eco,888,1,4,1,3,2,1,5,2,2,1,4,2,3,2,13,0.0,neutral or dissatisfied +56460,97867,Female,disloyal Customer,32,Business travel,Business,401,4,4,4,2,4,4,4,4,3,2,4,4,4,4,12,4.0,neutral or dissatisfied +56461,111621,Male,Loyal Customer,62,Personal Travel,Eco,1014,2,3,2,4,5,2,5,5,4,2,4,1,3,5,33,27.0,neutral or dissatisfied +56462,126905,Male,Loyal Customer,51,Business travel,Business,370,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +56463,71675,Female,Loyal Customer,31,Personal Travel,Eco,1197,2,5,2,4,1,2,1,1,1,5,4,3,5,1,0,0.0,neutral or dissatisfied +56464,110072,Female,disloyal Customer,19,Business travel,Eco,1242,2,2,2,1,2,2,2,2,3,3,5,3,5,2,8,0.0,satisfied +56465,5247,Male,disloyal Customer,25,Business travel,Eco,383,1,3,1,2,3,1,3,3,4,5,3,2,2,3,12,12.0,neutral or dissatisfied +56466,85266,Male,Loyal Customer,53,Personal Travel,Eco,689,3,5,3,4,4,3,4,4,4,2,5,4,5,4,2,0.0,neutral or dissatisfied +56467,80965,Male,Loyal Customer,52,Business travel,Business,3785,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +56468,75966,Female,Loyal Customer,58,Business travel,Business,297,4,3,3,3,3,3,3,4,4,3,4,1,4,3,0,1.0,neutral or dissatisfied +56469,41828,Female,Loyal Customer,62,Personal Travel,Eco,489,4,1,4,2,4,2,3,1,1,4,1,4,1,1,0,0.0,neutral or dissatisfied +56470,102954,Male,Loyal Customer,52,Personal Travel,Eco,719,2,5,2,5,1,2,2,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +56471,62903,Male,Loyal Customer,27,Personal Travel,Business,862,2,2,2,4,1,2,1,1,4,3,4,3,3,1,12,12.0,neutral or dissatisfied +56472,83746,Female,Loyal Customer,41,Business travel,Business,3705,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +56473,110251,Female,Loyal Customer,26,Personal Travel,Eco,1147,2,5,2,3,2,1,2,5,2,5,5,2,5,2,154,139.0,neutral or dissatisfied +56474,23537,Male,disloyal Customer,38,Business travel,Business,472,2,2,2,3,5,2,4,5,3,3,3,3,2,5,85,72.0,neutral or dissatisfied +56475,77529,Male,Loyal Customer,42,Personal Travel,Eco,1310,4,4,4,4,4,5,3,5,3,4,5,3,3,3,183,183.0,satisfied +56476,4541,Male,Loyal Customer,39,Business travel,Business,719,4,4,4,4,2,5,4,4,4,4,4,4,4,3,47,54.0,satisfied +56477,125394,Male,disloyal Customer,45,Business travel,Business,1440,3,3,3,3,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +56478,30044,Male,Loyal Customer,19,Business travel,Eco,539,3,1,1,1,3,3,1,3,3,5,3,3,3,3,12,14.0,neutral or dissatisfied +56479,80497,Female,Loyal Customer,58,Business travel,Business,1749,2,2,2,2,3,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +56480,110364,Female,Loyal Customer,68,Business travel,Business,3535,4,2,5,2,2,3,3,4,4,4,4,4,4,3,31,21.0,neutral or dissatisfied +56481,66506,Male,Loyal Customer,41,Business travel,Business,447,1,1,1,1,2,2,1,4,4,4,4,4,4,2,0,0.0,satisfied +56482,64916,Male,Loyal Customer,52,Business travel,Business,224,4,5,5,5,1,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +56483,104686,Male,Loyal Customer,44,Business travel,Business,159,0,5,0,3,2,4,4,4,4,4,1,4,4,4,36,39.0,satisfied +56484,56878,Female,Loyal Customer,45,Business travel,Business,2454,2,2,2,2,5,5,5,4,5,5,4,5,3,5,39,46.0,satisfied +56485,61955,Male,disloyal Customer,20,Business travel,Eco,829,3,3,3,3,4,3,4,4,3,1,3,1,4,4,46,16.0,neutral or dissatisfied +56486,21440,Female,Loyal Customer,22,Business travel,Business,331,0,0,0,2,3,3,3,3,4,4,3,5,2,3,0,0.0,satisfied +56487,113498,Female,Loyal Customer,47,Business travel,Business,197,2,5,4,4,1,2,3,1,1,1,2,2,1,1,0,0.0,neutral or dissatisfied +56488,91083,Male,Loyal Customer,32,Personal Travel,Eco,594,4,3,4,4,5,4,4,5,2,2,3,4,3,5,4,5.0,neutral or dissatisfied +56489,124119,Female,Loyal Customer,40,Business travel,Business,2543,4,4,4,4,5,5,4,3,3,3,3,5,3,3,1,0.0,satisfied +56490,112744,Male,Loyal Customer,47,Business travel,Business,3796,4,4,4,4,5,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +56491,29285,Female,Loyal Customer,31,Business travel,Business,834,2,1,5,1,2,2,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +56492,45858,Female,Loyal Customer,59,Personal Travel,Eco Plus,391,1,3,1,5,1,2,3,4,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +56493,122759,Female,Loyal Customer,36,Personal Travel,Eco,651,3,4,3,3,1,3,1,1,3,3,5,4,1,1,9,1.0,neutral or dissatisfied +56494,86943,Male,Loyal Customer,37,Business travel,Business,2094,1,1,1,1,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +56495,10871,Female,Loyal Customer,37,Business travel,Business,140,5,5,5,5,4,4,5,4,4,5,5,3,4,5,6,0.0,satisfied +56496,51133,Male,Loyal Customer,37,Personal Travel,Eco,134,3,3,3,4,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +56497,3096,Male,Loyal Customer,47,Personal Travel,Eco,678,2,4,1,3,3,1,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +56498,51957,Male,disloyal Customer,40,Business travel,Eco,843,4,4,4,3,3,4,3,3,1,4,4,1,3,3,0,0.0,satisfied +56499,29735,Male,Loyal Customer,49,Business travel,Business,3854,1,1,1,1,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +56500,82581,Male,Loyal Customer,50,Business travel,Business,2725,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,2.0,satisfied +56501,15090,Male,Loyal Customer,64,Business travel,Business,322,2,3,3,3,5,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +56502,90476,Female,disloyal Customer,39,Business travel,Business,406,2,2,2,3,3,2,3,3,4,5,5,4,5,3,0,4.0,neutral or dissatisfied +56503,78876,Male,Loyal Customer,32,Business travel,Business,3510,4,3,4,4,4,4,5,4,3,4,4,5,5,4,0,0.0,satisfied +56504,100521,Female,Loyal Customer,43,Personal Travel,Eco,759,2,5,2,3,5,5,5,1,1,2,1,5,1,3,24,14.0,neutral or dissatisfied +56505,78673,Male,Loyal Customer,60,Business travel,Business,674,1,1,1,1,4,4,5,2,2,2,2,4,2,4,0,14.0,satisfied +56506,112066,Female,Loyal Customer,20,Business travel,Business,1491,5,5,5,5,4,4,4,4,4,2,5,3,4,4,21,8.0,satisfied +56507,48314,Male,Loyal Customer,48,Business travel,Eco Plus,1499,3,1,1,1,3,3,3,3,2,2,2,4,2,3,12,11.0,satisfied +56508,16844,Female,Loyal Customer,34,Business travel,Eco Plus,645,4,1,1,1,4,4,4,4,4,2,3,1,5,4,89,82.0,satisfied +56509,28224,Male,Loyal Customer,49,Personal Travel,Eco Plus,873,3,4,3,3,3,3,3,3,4,3,3,3,4,3,0,0.0,neutral or dissatisfied +56510,67320,Female,Loyal Customer,8,Personal Travel,Eco Plus,985,2,1,2,1,4,2,4,4,3,1,2,2,2,4,0,0.0,neutral or dissatisfied +56511,36431,Male,disloyal Customer,39,Business travel,Eco,369,2,2,2,4,3,2,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +56512,123838,Female,disloyal Customer,26,Business travel,Business,541,3,0,3,5,5,3,5,5,3,4,4,3,4,5,5,6.0,neutral or dissatisfied +56513,113562,Female,Loyal Customer,59,Business travel,Business,1585,4,5,5,5,3,4,4,2,2,2,4,4,2,1,0,0.0,neutral or dissatisfied +56514,74001,Male,Loyal Customer,21,Personal Travel,Eco,1972,1,4,0,2,1,0,1,1,5,3,5,4,4,1,16,3.0,neutral or dissatisfied +56515,72585,Female,disloyal Customer,44,Business travel,Eco,721,2,2,2,4,1,2,2,1,4,1,4,1,1,1,0,0.0,neutral or dissatisfied +56516,72774,Male,disloyal Customer,22,Business travel,Business,1045,5,4,5,5,5,5,5,5,4,3,5,5,5,5,17,9.0,satisfied +56517,119454,Male,Loyal Customer,40,Business travel,Business,3866,2,2,2,2,4,4,4,3,3,3,3,4,3,4,17,15.0,satisfied +56518,73716,Female,Loyal Customer,65,Business travel,Eco,192,5,2,2,2,1,5,5,5,5,5,5,1,5,4,0,0.0,satisfied +56519,2324,Male,Loyal Customer,39,Personal Travel,Eco,630,1,2,1,4,3,1,5,3,3,5,4,3,3,3,2,1.0,neutral or dissatisfied +56520,1277,Male,Loyal Customer,52,Personal Travel,Eco,89,3,4,3,5,1,3,3,1,1,2,3,1,5,1,16,13.0,neutral or dissatisfied +56521,98956,Male,Loyal Customer,41,Business travel,Business,3516,5,5,2,5,4,5,4,4,4,5,4,3,4,5,3,0.0,satisfied +56522,127203,Female,Loyal Customer,61,Business travel,Eco Plus,304,5,5,5,5,2,5,1,5,5,5,5,5,5,1,4,22.0,satisfied +56523,48213,Female,Loyal Customer,40,Personal Travel,Eco,391,2,4,2,4,5,2,5,5,3,4,5,4,5,5,58,65.0,neutral or dissatisfied +56524,45265,Male,Loyal Customer,51,Business travel,Business,150,1,1,1,1,3,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +56525,11024,Female,disloyal Customer,20,Business travel,Eco,316,1,0,1,4,5,1,5,5,1,3,2,1,2,5,4,0.0,neutral or dissatisfied +56526,65340,Female,Loyal Customer,48,Business travel,Business,631,2,2,2,2,3,4,4,3,3,4,3,5,3,3,3,0.0,satisfied +56527,34393,Male,disloyal Customer,26,Business travel,Eco,612,3,2,2,3,4,2,4,4,4,3,3,4,4,4,0,21.0,neutral or dissatisfied +56528,5460,Female,Loyal Customer,57,Personal Travel,Eco,265,3,5,3,1,4,5,1,5,5,3,5,2,5,5,0,0.0,neutral or dissatisfied +56529,67877,Female,Loyal Customer,8,Personal Travel,Eco,1188,2,2,2,3,2,2,2,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +56530,114751,Female,Loyal Customer,56,Business travel,Business,446,5,5,2,5,2,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +56531,42000,Female,disloyal Customer,26,Business travel,Eco,116,1,0,1,4,3,1,2,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +56532,101563,Male,Loyal Customer,47,Business travel,Eco Plus,345,1,1,1,1,1,1,1,1,2,5,4,1,4,1,6,10.0,neutral or dissatisfied +56533,57997,Female,Loyal Customer,61,Business travel,Eco,1943,2,2,2,2,5,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +56534,126783,Female,Loyal Customer,67,Personal Travel,Business,2077,5,4,4,2,3,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +56535,14532,Female,Loyal Customer,35,Business travel,Business,288,3,3,3,3,4,1,5,4,4,4,4,2,4,1,0,0.0,satisfied +56536,14683,Male,Loyal Customer,55,Business travel,Business,317,4,3,3,3,3,1,2,4,4,4,4,1,4,1,16,21.0,neutral or dissatisfied +56537,99356,Male,Loyal Customer,63,Personal Travel,Eco,1771,1,2,1,3,1,1,1,1,4,4,3,2,3,1,0,6.0,neutral or dissatisfied +56538,83650,Female,Loyal Customer,52,Business travel,Business,1945,3,3,3,3,4,5,4,5,5,5,5,3,5,4,4,19.0,satisfied +56539,94810,Female,disloyal Customer,40,Business travel,Business,458,3,3,3,1,3,3,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +56540,86582,Female,Loyal Customer,59,Business travel,Eco,1269,2,4,4,4,5,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +56541,66871,Female,Loyal Customer,64,Business travel,Eco Plus,331,5,3,3,3,2,1,4,5,5,5,5,1,5,4,38,35.0,satisfied +56542,26141,Male,disloyal Customer,38,Business travel,Eco,404,1,0,2,5,4,2,4,4,2,2,5,2,4,4,0,1.0,neutral or dissatisfied +56543,6823,Female,Loyal Customer,29,Personal Travel,Eco,122,3,2,3,2,3,3,2,3,1,1,3,2,2,3,0,0.0,neutral or dissatisfied +56544,45861,Male,Loyal Customer,57,Business travel,Business,563,2,2,2,2,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +56545,8112,Male,Loyal Customer,30,Business travel,Business,2748,1,1,1,1,1,1,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +56546,89551,Male,Loyal Customer,49,Business travel,Business,3651,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +56547,22853,Male,Loyal Customer,44,Personal Travel,Eco,151,3,2,3,3,5,3,5,5,3,1,4,1,4,5,66,54.0,neutral or dissatisfied +56548,57013,Female,Loyal Customer,54,Personal Travel,Eco,2434,3,4,2,2,2,4,4,4,3,4,4,4,3,4,2,5.0,neutral or dissatisfied +56549,107468,Female,Loyal Customer,67,Personal Travel,Eco,1121,1,4,1,1,5,5,4,5,5,1,5,3,5,3,49,57.0,neutral or dissatisfied +56550,96886,Female,Loyal Customer,13,Personal Travel,Eco,781,1,4,1,4,5,1,5,5,3,5,4,4,4,5,15,6.0,neutral or dissatisfied +56551,45898,Male,Loyal Customer,43,Business travel,Business,913,4,4,4,4,5,1,1,3,3,3,3,2,3,1,30,12.0,satisfied +56552,122761,Male,Loyal Customer,67,Personal Travel,Eco,651,3,3,3,4,4,3,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +56553,34317,Male,Loyal Customer,9,Personal Travel,Eco Plus,280,3,5,3,3,5,3,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +56554,53779,Male,Loyal Customer,49,Business travel,Business,191,3,3,3,3,5,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +56555,53812,Male,Loyal Customer,41,Business travel,Business,191,0,5,0,4,1,3,1,5,5,2,2,1,5,1,0,2.0,satisfied +56556,55916,Male,Loyal Customer,33,Personal Travel,Eco,733,3,2,3,1,4,3,4,4,3,2,1,2,1,4,0,0.0,neutral or dissatisfied +56557,79950,Female,Loyal Customer,12,Business travel,Business,1035,2,5,5,5,2,2,2,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +56558,11042,Female,Loyal Customer,19,Personal Travel,Eco,312,4,2,4,3,2,4,2,2,1,3,3,3,4,2,16,10.0,satisfied +56559,102943,Female,Loyal Customer,45,Business travel,Business,2966,4,1,1,1,5,4,4,4,4,4,4,1,4,2,29,33.0,neutral or dissatisfied +56560,4860,Male,Loyal Customer,38,Business travel,Business,100,5,5,5,5,2,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +56561,11182,Male,Loyal Customer,67,Personal Travel,Eco,224,1,4,0,3,5,0,5,5,3,2,4,4,4,5,36,28.0,neutral or dissatisfied +56562,37480,Female,Loyal Customer,37,Business travel,Business,3793,2,5,5,5,2,3,3,2,2,2,2,3,2,4,111,112.0,neutral or dissatisfied +56563,49106,Male,Loyal Customer,59,Business travel,Business,3820,3,3,3,3,2,2,4,4,4,4,5,1,4,5,0,0.0,satisfied +56564,120754,Female,Loyal Customer,48,Business travel,Business,678,2,2,2,2,5,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +56565,69750,Male,Loyal Customer,30,Business travel,Business,1880,4,2,2,2,4,4,4,4,3,2,2,1,3,4,1,11.0,neutral or dissatisfied +56566,39437,Female,disloyal Customer,40,Business travel,Business,129,1,1,1,3,4,1,4,4,2,5,4,1,4,4,0,0.0,neutral or dissatisfied +56567,36441,Female,Loyal Customer,32,Personal Travel,Eco,369,5,4,5,2,3,5,3,3,5,3,1,2,3,3,0,0.0,satisfied +56568,89891,Female,disloyal Customer,29,Business travel,Business,1306,3,3,3,3,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +56569,4290,Male,Loyal Customer,50,Personal Travel,Eco,502,4,5,4,3,1,4,1,1,5,3,5,3,5,1,6,17.0,neutral or dissatisfied +56570,9773,Female,disloyal Customer,27,Business travel,Eco,383,2,1,2,2,4,2,4,4,1,2,2,1,2,4,4,0.0,neutral or dissatisfied +56571,12457,Male,Loyal Customer,69,Personal Travel,Eco,253,1,4,1,2,5,1,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +56572,58070,Female,disloyal Customer,22,Business travel,Business,589,4,4,4,5,1,4,4,1,4,4,4,4,5,1,2,15.0,satisfied +56573,72786,Female,Loyal Customer,58,Business travel,Business,2278,5,5,5,5,5,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +56574,91946,Female,Loyal Customer,22,Personal Travel,Eco,2475,1,4,0,3,4,0,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +56575,69913,Male,Loyal Customer,26,Personal Travel,Eco,1671,1,1,2,2,4,2,4,4,3,3,2,1,3,4,0,0.0,neutral or dissatisfied +56576,122063,Male,Loyal Customer,64,Business travel,Eco,130,2,4,4,4,1,2,1,1,1,3,1,3,4,1,16,8.0,satisfied +56577,15753,Male,Loyal Customer,19,Business travel,Business,3515,2,4,2,2,4,4,4,4,4,3,1,4,1,4,0,0.0,satisfied +56578,29137,Male,Loyal Customer,43,Personal Travel,Eco,671,2,5,2,3,5,2,5,5,2,4,5,1,4,5,0,0.0,neutral or dissatisfied +56579,1689,Female,disloyal Customer,62,Business travel,Business,364,2,2,2,4,5,2,3,5,4,2,4,2,4,5,1,4.0,neutral or dissatisfied +56580,119257,Male,disloyal Customer,26,Business travel,Business,214,0,5,0,4,4,0,2,4,4,2,4,5,5,4,0,0.0,satisfied +56581,60439,Female,Loyal Customer,32,Business travel,Business,862,3,3,3,3,3,3,3,3,4,2,4,4,4,3,0,20.0,neutral or dissatisfied +56582,32539,Female,disloyal Customer,39,Business travel,Eco,102,1,1,1,4,1,1,1,1,2,4,3,3,4,1,0,0.0,neutral or dissatisfied +56583,72202,Female,Loyal Customer,64,Personal Travel,Eco Plus,594,2,4,2,4,5,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +56584,15580,Female,Loyal Customer,21,Business travel,Business,228,0,0,0,2,5,5,5,5,3,1,3,5,3,5,0,0.0,satisfied +56585,17368,Female,Loyal Customer,38,Business travel,Eco Plus,563,3,3,3,3,3,3,3,3,3,2,5,4,5,3,61,47.0,satisfied +56586,117505,Male,Loyal Customer,12,Personal Travel,Eco,507,1,4,1,2,3,1,4,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +56587,51194,Male,Loyal Customer,59,Business travel,Eco Plus,308,2,5,2,5,2,2,2,2,2,1,1,4,3,2,0,0.0,satisfied +56588,26554,Male,Loyal Customer,50,Business travel,Eco Plus,1105,4,4,4,4,4,4,4,4,5,2,5,3,5,4,0,3.0,satisfied +56589,83637,Female,Loyal Customer,45,Business travel,Business,1684,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +56590,59303,Male,Loyal Customer,43,Business travel,Business,2447,3,3,3,3,3,3,5,3,3,3,3,4,3,3,31,5.0,satisfied +56591,1501,Male,Loyal Customer,70,Personal Travel,Eco,835,1,4,0,2,5,0,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +56592,56478,Male,disloyal Customer,42,Business travel,Business,4963,2,2,2,5,2,1,1,3,3,4,5,1,4,1,1,25.0,neutral or dissatisfied +56593,10797,Male,Loyal Customer,28,Business travel,Business,312,5,5,5,5,5,5,5,5,5,3,4,4,4,5,52,48.0,satisfied +56594,19109,Male,Loyal Customer,43,Business travel,Business,323,0,0,0,4,2,1,4,4,4,4,4,2,4,3,3,32.0,satisfied +56595,47730,Female,Loyal Customer,60,Business travel,Business,3913,3,3,3,3,2,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +56596,122562,Male,Loyal Customer,23,Personal Travel,Eco,500,4,4,4,2,3,4,3,3,5,4,4,3,5,3,0,0.0,satisfied +56597,67639,Female,disloyal Customer,19,Business travel,Eco,1188,4,4,4,3,3,4,3,3,3,3,4,4,4,3,0,0.0,satisfied +56598,93572,Female,Loyal Customer,55,Business travel,Business,3218,2,2,2,2,2,5,4,5,5,5,4,4,5,5,6,1.0,satisfied +56599,86245,Female,Loyal Customer,44,Personal Travel,Eco,377,5,3,5,2,1,2,3,5,5,5,5,1,5,1,0,0.0,satisfied +56600,76818,Female,Loyal Customer,56,Business travel,Business,1851,5,5,5,5,2,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +56601,96665,Male,Loyal Customer,7,Personal Travel,Eco,1036,1,5,2,3,1,2,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +56602,87869,Female,Loyal Customer,48,Business travel,Business,2683,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +56603,68397,Male,disloyal Customer,50,Business travel,Business,1045,5,5,5,3,4,5,4,4,4,5,5,3,5,4,0,0.0,satisfied +56604,15701,Male,Loyal Customer,36,Business travel,Business,3753,2,2,2,2,4,4,4,3,3,4,3,2,3,2,92,88.0,satisfied +56605,92763,Female,Loyal Customer,27,Business travel,Eco Plus,1276,1,3,4,3,1,1,1,1,1,3,4,3,4,1,0,0.0,neutral or dissatisfied +56606,85388,Male,Loyal Customer,39,Business travel,Business,2654,2,2,2,2,5,5,5,4,4,4,4,3,4,5,18,13.0,satisfied +56607,86330,Male,Loyal Customer,25,Business travel,Business,762,2,2,2,2,2,2,2,2,2,5,3,1,4,2,3,29.0,neutral or dissatisfied +56608,123520,Male,Loyal Customer,69,Personal Travel,Eco,2077,3,5,3,3,4,3,1,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +56609,48665,Male,Loyal Customer,45,Business travel,Business,250,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +56610,86728,Male,Loyal Customer,50,Personal Travel,Eco,1747,3,0,3,2,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +56611,69443,Female,Loyal Customer,37,Personal Travel,Eco,1096,2,1,2,3,1,2,1,1,4,2,3,2,2,1,0,0.0,neutral or dissatisfied +56612,45279,Male,Loyal Customer,22,Business travel,Business,3008,5,5,5,5,4,4,4,4,2,3,2,1,5,4,0,0.0,satisfied +56613,101157,Female,Loyal Customer,52,Business travel,Business,3163,5,5,4,5,2,5,5,4,4,4,4,5,4,4,11,3.0,satisfied +56614,113419,Female,Loyal Customer,49,Business travel,Business,3955,4,4,4,4,2,5,5,5,5,5,5,3,5,3,21,18.0,satisfied +56615,82250,Female,Loyal Customer,10,Personal Travel,Eco Plus,405,1,4,1,4,4,1,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +56616,17979,Male,Loyal Customer,58,Business travel,Business,2322,4,4,4,4,3,4,5,5,5,5,5,4,5,4,58,50.0,satisfied +56617,85040,Female,Loyal Customer,45,Business travel,Business,2857,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +56618,117599,Male,Loyal Customer,43,Business travel,Business,1020,3,1,1,1,2,3,3,3,3,3,3,1,3,3,24,5.0,neutral or dissatisfied +56619,92399,Female,Loyal Customer,45,Business travel,Business,1947,1,1,1,1,3,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +56620,13153,Female,Loyal Customer,25,Personal Travel,Eco,595,4,4,4,4,3,4,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +56621,12460,Female,Loyal Customer,28,Personal Travel,Eco,127,2,4,2,1,4,2,1,4,3,3,3,4,5,4,5,0.0,neutral or dissatisfied +56622,606,Male,Loyal Customer,46,Business travel,Business,134,3,4,4,4,2,4,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +56623,38445,Male,Loyal Customer,13,Personal Travel,Eco,588,5,4,5,2,2,4,2,2,5,2,5,5,4,2,0,0.0,satisfied +56624,41847,Male,Loyal Customer,57,Business travel,Business,483,3,3,3,3,3,5,2,4,4,4,4,5,4,1,0,0.0,satisfied +56625,46975,Female,Loyal Customer,45,Personal Travel,Eco,737,4,5,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +56626,93206,Male,Loyal Customer,46,Business travel,Business,1756,1,1,1,1,4,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +56627,125894,Female,Loyal Customer,53,Personal Travel,Eco,992,5,4,5,4,5,4,5,4,4,5,4,5,4,4,28,20.0,satisfied +56628,61357,Male,Loyal Customer,40,Business travel,Business,3278,5,3,5,5,3,5,5,4,4,4,4,4,4,4,27,27.0,satisfied +56629,47584,Female,Loyal Customer,47,Business travel,Eco,1504,4,5,5,5,1,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +56630,47122,Female,Loyal Customer,42,Personal Travel,Eco Plus,737,2,4,2,2,4,4,5,4,4,2,4,3,4,5,60,52.0,neutral or dissatisfied +56631,65090,Male,Loyal Customer,20,Personal Travel,Eco,247,3,5,3,4,4,3,4,4,3,3,5,5,5,4,21,21.0,neutral or dissatisfied +56632,109741,Female,Loyal Customer,52,Personal Travel,Eco,680,4,4,4,3,4,4,5,2,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +56633,56591,Female,Loyal Customer,59,Business travel,Business,1023,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +56634,116920,Female,Loyal Customer,28,Business travel,Business,621,4,4,4,4,4,4,4,4,3,4,5,3,4,4,8,22.0,satisfied +56635,87388,Male,Loyal Customer,57,Business travel,Business,3931,4,3,3,3,3,3,3,4,4,4,4,1,4,4,0,4.0,neutral or dissatisfied +56636,9914,Male,Loyal Customer,55,Business travel,Business,3614,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +56637,53925,Male,Loyal Customer,42,Business travel,Eco Plus,191,4,1,1,1,4,4,4,4,5,2,1,4,5,4,0,0.0,satisfied +56638,70253,Male,Loyal Customer,33,Business travel,Business,1592,3,3,3,3,4,4,4,4,5,1,3,2,5,4,0,0.0,satisfied +56639,101408,Female,Loyal Customer,67,Personal Travel,Eco,486,4,1,4,3,2,3,3,3,3,4,3,3,3,3,11,2.0,neutral or dissatisfied +56640,119930,Male,Loyal Customer,55,Business travel,Business,868,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +56641,128045,Female,disloyal Customer,25,Business travel,Business,735,1,5,1,2,1,1,1,1,4,5,5,4,5,1,16,7.0,neutral or dissatisfied +56642,107301,Female,Loyal Customer,70,Personal Travel,Eco,283,3,5,3,3,5,4,4,2,2,3,2,5,2,4,18,12.0,neutral or dissatisfied +56643,89097,Male,Loyal Customer,37,Business travel,Business,1892,5,5,5,5,3,4,4,3,3,3,3,4,3,3,1,0.0,satisfied +56644,101646,Female,Loyal Customer,10,Personal Travel,Eco,1749,1,4,1,3,3,1,1,3,3,1,3,3,3,3,1,0.0,neutral or dissatisfied +56645,98739,Male,Loyal Customer,43,Business travel,Eco,1290,4,1,1,1,3,4,3,3,5,3,3,2,2,3,0,0.0,satisfied +56646,34575,Male,Loyal Customer,26,Business travel,Business,1598,4,3,3,3,4,4,4,1,4,2,3,4,2,4,123,141.0,neutral or dissatisfied +56647,31932,Male,Loyal Customer,40,Business travel,Business,3105,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +56648,74873,Male,Loyal Customer,62,Business travel,Eco,2239,1,4,4,4,1,1,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +56649,49422,Male,Loyal Customer,53,Business travel,Eco,209,4,3,3,3,4,4,4,4,1,3,3,3,4,4,0,0.0,satisfied +56650,128609,Female,Loyal Customer,58,Business travel,Eco,679,2,1,1,1,4,3,3,3,3,2,3,2,3,1,77,60.0,neutral or dissatisfied +56651,98305,Male,Loyal Customer,51,Business travel,Business,1565,4,4,4,4,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +56652,88802,Male,Loyal Customer,35,Business travel,Business,1731,5,5,5,5,2,5,4,5,5,5,5,5,5,4,15,4.0,satisfied +56653,17964,Male,Loyal Customer,70,Personal Travel,Eco,500,3,1,3,3,2,3,2,2,1,3,3,4,2,2,0,0.0,neutral or dissatisfied +56654,34399,Female,Loyal Customer,42,Business travel,Business,2015,2,2,2,2,1,3,3,4,4,4,5,5,4,3,0,0.0,satisfied +56655,106403,Female,Loyal Customer,68,Personal Travel,Eco,488,4,4,4,3,4,5,5,5,5,4,5,3,5,5,31,23.0,satisfied +56656,111647,Female,Loyal Customer,58,Personal Travel,Eco,1558,2,5,2,4,3,4,4,5,5,2,5,5,5,3,7,0.0,neutral or dissatisfied +56657,94887,Male,Loyal Customer,29,Business travel,Business,562,1,1,3,3,1,1,1,1,2,5,4,2,3,1,6,8.0,neutral or dissatisfied +56658,87327,Female,disloyal Customer,22,Business travel,Business,1027,2,3,2,3,4,2,4,4,4,3,4,4,3,4,7,0.0,neutral or dissatisfied +56659,49610,Male,disloyal Customer,23,Business travel,Eco,110,4,0,4,1,4,4,3,4,2,2,5,1,4,4,0,3.0,satisfied +56660,107895,Male,Loyal Customer,39,Business travel,Business,861,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +56661,41149,Female,Loyal Customer,25,Personal Travel,Eco,224,3,4,3,3,2,3,2,2,3,2,5,5,4,2,0,8.0,neutral or dissatisfied +56662,4386,Male,Loyal Customer,36,Personal Travel,Eco,607,2,5,2,4,2,4,4,4,5,4,4,4,3,4,139,195.0,neutral or dissatisfied +56663,81603,Female,Loyal Customer,31,Business travel,Eco,334,1,2,2,2,1,1,1,1,1,1,3,3,4,1,0,20.0,neutral or dissatisfied +56664,62930,Male,disloyal Customer,26,Business travel,Business,967,4,4,4,4,2,4,2,2,3,4,5,5,5,2,0,2.0,satisfied +56665,22117,Male,Loyal Customer,48,Business travel,Business,3497,0,1,1,1,5,5,5,3,3,4,4,1,3,1,0,0.0,satisfied +56666,11284,Male,Loyal Customer,11,Personal Travel,Eco,247,1,4,1,4,5,1,5,5,3,3,5,3,4,5,23,22.0,neutral or dissatisfied +56667,7360,Female,Loyal Customer,38,Personal Travel,Business,783,3,4,3,2,2,4,4,3,3,3,3,5,3,4,27,22.0,neutral or dissatisfied +56668,42605,Male,Loyal Customer,47,Personal Travel,Business,546,2,2,2,4,3,4,4,2,2,2,2,1,2,3,73,52.0,neutral or dissatisfied +56669,13800,Male,Loyal Customer,11,Personal Travel,Eco,595,2,4,2,3,3,2,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +56670,66695,Female,Loyal Customer,42,Business travel,Eco,978,2,3,3,3,2,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +56671,63632,Male,Loyal Customer,41,Business travel,Eco,602,2,5,5,5,2,2,2,2,4,4,4,2,3,2,1,0.0,neutral or dissatisfied +56672,78252,Male,disloyal Customer,23,Business travel,Eco,903,2,2,2,4,3,2,2,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +56673,45227,Female,Loyal Customer,33,Business travel,Business,2970,3,2,2,2,2,3,3,3,3,3,3,2,3,1,10,18.0,neutral or dissatisfied +56674,31532,Female,Loyal Customer,61,Personal Travel,Eco,862,2,5,2,1,2,4,5,1,1,2,1,4,1,5,0,10.0,neutral or dissatisfied +56675,122109,Male,Loyal Customer,38,Personal Travel,Eco,83,4,3,0,3,1,0,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +56676,75259,Female,Loyal Customer,9,Personal Travel,Eco,1744,2,4,2,2,1,2,1,1,4,2,3,4,5,1,1,32.0,neutral or dissatisfied +56677,79170,Female,disloyal Customer,27,Business travel,Business,2422,1,1,1,4,1,1,1,4,3,4,4,1,4,1,0,0.0,neutral or dissatisfied +56678,56325,Female,Loyal Customer,47,Business travel,Business,3322,5,5,5,5,2,4,5,5,5,5,5,4,5,3,37,49.0,satisfied +56679,65773,Male,Loyal Customer,58,Business travel,Business,1389,4,4,4,4,2,4,5,4,4,4,4,4,4,3,13,10.0,satisfied +56680,117044,Female,Loyal Customer,47,Business travel,Business,2861,3,3,3,3,3,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +56681,95928,Male,Loyal Customer,43,Business travel,Business,1500,2,2,2,2,1,3,4,4,4,4,4,5,4,3,18,2.0,satisfied +56682,101113,Female,Loyal Customer,33,Business travel,Business,583,4,3,3,3,3,4,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +56683,127386,Female,Loyal Customer,44,Business travel,Business,1978,1,1,3,1,5,4,5,2,2,3,2,4,2,4,0,0.0,satisfied +56684,27452,Female,Loyal Customer,77,Business travel,Business,1682,1,3,3,3,3,2,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +56685,90350,Female,Loyal Customer,25,Business travel,Business,270,0,0,0,3,3,3,3,3,3,2,5,3,5,3,0,8.0,satisfied +56686,82103,Male,Loyal Customer,63,Personal Travel,Eco,1276,3,4,3,4,5,3,1,5,3,2,3,4,5,5,0,0.0,neutral or dissatisfied +56687,95304,Female,Loyal Customer,69,Personal Travel,Eco,189,3,4,3,3,2,5,4,4,4,3,4,3,4,3,13,18.0,neutral or dissatisfied +56688,116402,Female,Loyal Customer,68,Personal Travel,Eco,371,4,0,4,3,3,2,3,3,3,4,3,1,3,4,19,9.0,neutral or dissatisfied +56689,54042,Male,Loyal Customer,36,Business travel,Business,1416,4,4,4,4,1,5,5,3,3,4,3,4,3,1,0,0.0,satisfied +56690,43332,Female,Loyal Customer,36,Business travel,Eco,347,5,5,5,5,5,5,5,5,5,2,1,3,3,5,0,0.0,satisfied +56691,52228,Female,Loyal Customer,57,Business travel,Eco,355,4,4,4,4,4,5,1,4,4,4,4,4,4,1,0,0.0,satisfied +56692,90984,Female,Loyal Customer,38,Business travel,Business,270,1,3,5,5,4,3,4,1,1,1,1,3,1,3,0,11.0,neutral or dissatisfied +56693,51208,Female,disloyal Customer,37,Business travel,Eco Plus,109,2,2,2,2,4,2,5,4,1,5,4,4,1,4,0,0.0,neutral or dissatisfied +56694,122559,Male,Loyal Customer,48,Personal Travel,Eco,500,3,4,3,3,3,3,3,3,1,1,3,1,3,3,0,0.0,neutral or dissatisfied +56695,33409,Female,Loyal Customer,25,Business travel,Eco,2355,4,1,2,2,4,4,4,4,2,5,4,1,1,4,0,4.0,satisfied +56696,114289,Female,Loyal Customer,18,Personal Travel,Eco,957,4,5,4,3,1,4,4,1,3,5,5,3,4,1,0,5.0,satisfied +56697,94827,Male,disloyal Customer,36,Business travel,Eco,239,3,1,3,4,3,3,3,3,3,1,3,2,3,3,22,19.0,neutral or dissatisfied +56698,98760,Male,Loyal Customer,60,Business travel,Eco,2075,2,5,5,5,2,2,2,2,4,1,1,2,4,2,137,99.0,neutral or dissatisfied +56699,6231,Female,disloyal Customer,25,Business travel,Business,678,3,0,3,5,5,3,5,5,3,3,5,5,4,5,2,0.0,neutral or dissatisfied +56700,110716,Female,disloyal Customer,18,Business travel,Eco,849,3,3,3,2,3,3,3,3,3,2,5,4,5,3,6,0.0,neutral or dissatisfied +56701,18933,Male,Loyal Customer,35,Personal Travel,Eco,448,2,4,2,3,5,2,5,5,1,3,3,4,4,5,0,0.0,neutral or dissatisfied +56702,54976,Male,Loyal Customer,47,Business travel,Business,1504,4,4,4,4,5,4,5,5,5,5,5,5,5,3,48,40.0,satisfied +56703,41644,Female,Loyal Customer,36,Business travel,Eco,843,4,5,5,5,4,4,4,4,5,1,2,5,1,4,0,0.0,satisfied +56704,65714,Male,disloyal Customer,38,Business travel,Business,936,2,2,2,4,1,2,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +56705,76525,Female,Loyal Customer,51,Business travel,Business,2565,2,2,5,2,3,4,5,4,4,4,4,5,4,4,30,33.0,satisfied +56706,92834,Male,Loyal Customer,30,Personal Travel,Eco,1541,1,5,1,3,2,1,2,2,2,3,4,1,5,2,0,0.0,neutral or dissatisfied +56707,105631,Female,disloyal Customer,40,Business travel,Business,883,3,4,4,2,4,4,4,4,2,4,3,4,3,4,16,9.0,neutral or dissatisfied +56708,47065,Female,Loyal Customer,34,Business travel,Business,1634,3,4,4,4,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +56709,59892,Female,Loyal Customer,60,Business travel,Business,2148,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +56710,114977,Female,Loyal Customer,56,Business travel,Business,337,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,2.0,satisfied +56711,85374,Female,disloyal Customer,25,Business travel,Business,214,5,4,5,3,2,5,2,2,5,5,4,4,4,2,0,1.0,satisfied +56712,58646,Female,Loyal Customer,29,Business travel,Business,2884,4,4,4,4,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +56713,81377,Female,Loyal Customer,50,Personal Travel,Business,874,1,2,1,4,4,4,4,3,3,1,3,3,3,3,16,,neutral or dissatisfied +56714,58865,Male,Loyal Customer,41,Business travel,Business,888,1,1,1,1,2,4,5,4,4,4,4,3,4,3,19,4.0,satisfied +56715,40762,Male,Loyal Customer,41,Business travel,Business,3754,4,4,4,4,1,1,5,4,4,4,4,3,4,3,0,0.0,satisfied +56716,98150,Male,disloyal Customer,20,Business travel,Business,562,4,0,4,3,3,4,3,3,3,3,4,3,4,3,0,0.0,satisfied +56717,107227,Female,disloyal Customer,26,Business travel,Business,583,2,2,2,3,1,2,1,1,4,5,3,3,3,1,6,0.0,neutral or dissatisfied +56718,3677,Female,Loyal Customer,57,Business travel,Business,544,2,4,4,4,3,3,3,2,2,2,2,3,2,4,0,16.0,neutral or dissatisfied +56719,72928,Male,disloyal Customer,21,Business travel,Eco,944,1,1,1,4,2,1,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +56720,34843,Male,Loyal Customer,62,Personal Travel,Eco Plus,301,2,4,2,5,1,2,1,1,4,3,5,2,3,1,0,0.0,neutral or dissatisfied +56721,42115,Male,disloyal Customer,10,Business travel,Eco,991,3,3,3,4,5,3,5,5,1,5,4,3,3,5,1,0.0,neutral or dissatisfied +56722,103863,Male,Loyal Customer,26,Personal Travel,Eco,882,4,1,4,4,1,4,2,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +56723,111020,Male,Loyal Customer,40,Business travel,Business,3808,2,1,1,1,4,2,4,2,5,3,3,4,4,4,218,212.0,neutral or dissatisfied +56724,81548,Female,disloyal Customer,25,Business travel,Business,1124,1,0,1,4,1,1,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +56725,54827,Male,disloyal Customer,29,Business travel,Eco,862,4,4,4,4,5,4,5,5,2,5,3,2,3,5,2,0.0,neutral or dissatisfied +56726,86657,Male,Loyal Customer,54,Personal Travel,Eco,746,3,2,3,4,5,3,5,5,4,1,3,2,4,5,99,101.0,neutral or dissatisfied +56727,104669,Female,Loyal Customer,39,Personal Travel,Eco,641,3,5,3,2,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +56728,3607,Female,Loyal Customer,42,Personal Travel,Eco,999,3,3,3,3,5,5,5,1,1,3,1,4,1,4,0,5.0,neutral or dissatisfied +56729,32517,Female,disloyal Customer,33,Business travel,Eco,102,1,4,1,1,1,1,1,1,3,3,2,5,1,1,0,1.0,neutral or dissatisfied +56730,49257,Female,Loyal Customer,58,Business travel,Business,262,1,1,1,1,3,5,3,4,4,4,4,4,4,1,1,0.0,satisfied +56731,1518,Female,disloyal Customer,27,Business travel,Business,862,3,3,3,4,1,3,1,1,3,2,4,3,4,1,33,28.0,neutral or dissatisfied +56732,5398,Male,Loyal Customer,7,Personal Travel,Eco,733,1,5,1,1,5,1,2,5,2,2,3,5,2,5,0,0.0,neutral or dissatisfied +56733,108139,Male,disloyal Customer,55,Business travel,Eco,597,1,4,1,3,3,1,3,3,1,3,5,2,4,3,5,0.0,neutral or dissatisfied +56734,27569,Female,Loyal Customer,57,Personal Travel,Eco,1050,5,5,5,1,2,4,5,2,2,5,2,3,2,4,0,0.0,satisfied +56735,122985,Female,Loyal Customer,44,Business travel,Business,3955,3,3,3,3,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +56736,102661,Male,Loyal Customer,31,Business travel,Business,601,4,1,5,1,4,3,4,4,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +56737,84782,Male,disloyal Customer,20,Business travel,Eco,516,4,0,5,3,5,5,5,5,3,3,5,5,5,5,0,11.0,neutral or dissatisfied +56738,96855,Male,Loyal Customer,45,Business travel,Business,3815,1,0,0,3,5,4,4,2,2,0,2,1,2,1,71,72.0,neutral or dissatisfied +56739,50816,Female,Loyal Customer,8,Personal Travel,Eco,158,2,5,2,4,5,2,5,5,4,4,4,5,4,5,30,22.0,neutral or dissatisfied +56740,37414,Male,disloyal Customer,27,Business travel,Business,1118,2,2,2,3,2,2,4,2,4,2,3,2,2,2,111,106.0,neutral or dissatisfied +56741,116813,Female,Loyal Customer,59,Business travel,Business,3864,3,3,3,3,2,5,4,5,5,5,5,5,5,5,11,9.0,satisfied +56742,23900,Male,Loyal Customer,48,Business travel,Eco,579,2,2,4,4,2,2,2,2,2,2,3,2,2,2,0,0.0,neutral or dissatisfied +56743,95831,Female,Loyal Customer,54,Business travel,Business,2788,2,4,4,4,2,4,4,2,2,2,2,2,2,3,9,14.0,neutral or dissatisfied +56744,2668,Male,Loyal Customer,53,Business travel,Eco,222,1,2,4,4,1,1,1,1,4,1,3,3,4,1,4,7.0,neutral or dissatisfied +56745,31580,Male,Loyal Customer,33,Business travel,Business,3286,1,1,1,1,4,4,4,4,2,5,2,5,1,4,0,0.0,satisfied +56746,79147,Female,Loyal Customer,10,Personal Travel,Eco Plus,356,2,5,2,2,1,2,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +56747,78267,Female,Loyal Customer,35,Personal Travel,Eco,903,4,4,4,3,5,4,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +56748,99790,Male,disloyal Customer,43,Business travel,Business,632,5,5,5,5,2,5,2,2,5,3,4,4,5,2,0,0.0,satisfied +56749,3337,Male,disloyal Customer,25,Business travel,Eco,296,1,1,1,4,2,1,2,2,3,3,4,3,4,2,52,59.0,neutral or dissatisfied +56750,71494,Male,Loyal Customer,59,Personal Travel,Business,1182,0,5,0,2,2,3,4,1,1,0,4,3,1,3,0,0.0,satisfied +56751,61536,Female,Loyal Customer,46,Personal Travel,Eco,2442,2,2,2,3,4,3,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +56752,94181,Female,Loyal Customer,24,Business travel,Business,562,1,1,1,1,4,4,4,4,5,2,5,3,4,4,64,51.0,satisfied +56753,88473,Male,Loyal Customer,70,Business travel,Business,2654,1,1,1,1,2,3,5,4,4,4,4,2,4,4,32,41.0,satisfied +56754,28983,Female,Loyal Customer,25,Business travel,Business,1890,3,2,2,2,3,3,3,3,1,5,3,2,4,3,0,0.0,neutral or dissatisfied +56755,55106,Male,Loyal Customer,54,Personal Travel,Eco,1609,5,5,5,3,2,5,3,2,5,2,3,3,5,2,0,0.0,satisfied +56756,42020,Female,Loyal Customer,52,Business travel,Eco,116,5,4,4,4,4,4,2,5,5,5,5,2,5,5,0,0.0,satisfied +56757,12393,Female,Loyal Customer,29,Business travel,Eco,262,4,5,5,5,4,4,4,4,5,5,2,4,3,4,0,0.0,satisfied +56758,10541,Female,Loyal Customer,40,Business travel,Business,2034,0,0,0,5,2,5,5,5,5,5,5,3,5,5,31,39.0,satisfied +56759,128750,Male,Loyal Customer,24,Business travel,Eco Plus,2402,2,3,3,3,2,1,2,2,5,4,4,2,2,2,0,0.0,neutral or dissatisfied +56760,14844,Female,Loyal Customer,35,Personal Travel,Business,315,2,4,2,3,2,5,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +56761,76627,Female,disloyal Customer,41,Business travel,Business,147,2,2,2,2,3,2,3,3,5,1,5,2,3,3,0,0.0,neutral or dissatisfied +56762,84235,Female,Loyal Customer,41,Personal Travel,Eco,432,0,4,0,3,4,0,4,4,2,4,4,2,4,4,0,0.0,satisfied +56763,2051,Male,Loyal Customer,36,Business travel,Business,3846,3,3,3,3,2,2,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +56764,24182,Male,Loyal Customer,26,Business travel,Business,170,2,2,2,2,4,4,4,4,1,2,2,4,1,4,26,21.0,satisfied +56765,6635,Female,Loyal Customer,51,Business travel,Business,416,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +56766,94641,Male,disloyal Customer,30,Business travel,Eco,496,3,4,3,3,5,3,5,5,4,3,3,2,4,5,76,60.0,neutral or dissatisfied +56767,10663,Female,Loyal Customer,52,Business travel,Business,316,0,0,0,4,1,1,3,5,4,5,5,3,3,3,298,287.0,satisfied +56768,73905,Male,Loyal Customer,54,Business travel,Business,2218,3,3,3,3,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +56769,7561,Male,Loyal Customer,48,Personal Travel,Eco,606,2,4,2,5,4,2,2,4,5,4,5,5,3,4,0,0.0,neutral or dissatisfied +56770,117244,Female,Loyal Customer,31,Personal Travel,Eco,325,3,5,3,2,5,3,5,5,5,5,5,4,3,5,34,29.0,neutral or dissatisfied +56771,105271,Female,Loyal Customer,14,Personal Travel,Eco,2106,1,2,1,2,1,1,1,1,2,3,2,3,3,1,0,10.0,neutral or dissatisfied +56772,118641,Female,Loyal Customer,26,Business travel,Eco,621,1,4,4,4,1,2,2,1,4,3,3,2,3,1,0,0.0,neutral or dissatisfied +56773,71563,Male,Loyal Customer,39,Business travel,Business,3867,4,4,4,4,2,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +56774,57924,Male,Loyal Customer,17,Personal Travel,Eco,305,3,4,2,4,2,2,2,2,5,4,2,4,3,2,0,1.0,neutral or dissatisfied +56775,44316,Female,Loyal Customer,27,Business travel,Business,837,4,4,4,4,4,4,4,4,4,2,3,2,1,4,130,124.0,satisfied +56776,70154,Male,Loyal Customer,46,Personal Travel,Eco,550,2,3,2,4,4,2,4,4,1,1,4,4,3,4,3,5.0,neutral or dissatisfied +56777,64870,Male,Loyal Customer,53,Business travel,Business,2893,1,1,1,1,2,3,3,1,1,1,1,1,1,1,3,0.0,neutral or dissatisfied +56778,124986,Male,Loyal Customer,36,Business travel,Business,3337,4,1,1,1,3,3,4,2,2,2,4,3,2,3,6,0.0,neutral or dissatisfied +56779,32389,Male,Loyal Customer,62,Business travel,Business,101,1,1,1,1,4,5,5,4,4,4,3,1,4,2,0,0.0,satisfied +56780,83181,Female,Loyal Customer,42,Business travel,Business,549,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +56781,113413,Male,Loyal Customer,52,Business travel,Eco,226,2,4,4,4,2,2,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +56782,88335,Male,Loyal Customer,37,Business travel,Eco,250,4,3,3,3,4,3,4,4,4,5,3,2,4,4,0,0.0,neutral or dissatisfied +56783,9031,Female,Loyal Customer,47,Business travel,Business,1679,4,4,4,4,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +56784,79692,Male,Loyal Customer,37,Personal Travel,Eco,762,3,2,3,3,2,3,2,2,1,1,4,4,3,2,0,0.0,neutral or dissatisfied +56785,70840,Male,Loyal Customer,57,Business travel,Business,3572,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +56786,107218,Female,Loyal Customer,57,Personal Travel,Eco Plus,402,3,4,3,3,2,5,5,5,5,3,5,5,5,4,4,0.0,neutral or dissatisfied +56787,70533,Female,Loyal Customer,37,Personal Travel,Business,1258,3,4,3,2,5,5,4,3,3,3,2,5,3,4,65,90.0,neutral or dissatisfied +56788,6774,Female,Loyal Customer,45,Business travel,Business,2688,3,3,3,3,5,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +56789,101087,Male,Loyal Customer,55,Business travel,Business,1090,3,3,3,3,2,5,4,3,3,3,3,5,3,3,22,19.0,satisfied +56790,83539,Female,Loyal Customer,39,Business travel,Business,2849,2,2,2,2,2,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +56791,101654,Male,Loyal Customer,55,Business travel,Eco Plus,233,3,1,5,1,3,3,3,1,4,4,4,3,4,3,324,290.0,neutral or dissatisfied +56792,8705,Male,Loyal Customer,7,Personal Travel,Eco,280,3,4,3,3,3,3,5,3,3,2,5,4,5,3,0,86.0,neutral or dissatisfied +56793,7584,Male,Loyal Customer,46,Personal Travel,Eco,594,4,2,4,3,4,4,4,4,1,5,3,2,3,4,0,0.0,satisfied +56794,45495,Male,Loyal Customer,64,Personal Travel,Eco,522,3,5,3,3,5,3,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +56795,45066,Female,Loyal Customer,22,Personal Travel,Eco,342,2,3,2,1,4,2,4,4,5,1,5,3,4,4,43,40.0,neutral or dissatisfied +56796,63760,Male,Loyal Customer,40,Business travel,Business,2422,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +56797,22962,Male,disloyal Customer,18,Business travel,Eco,1041,4,4,4,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +56798,111047,Female,disloyal Customer,40,Business travel,Business,197,3,3,3,4,2,3,2,2,3,5,4,4,4,2,20,9.0,neutral or dissatisfied +56799,30284,Male,Loyal Customer,45,Business travel,Eco Plus,1024,3,2,2,2,2,3,2,2,3,4,3,3,3,2,10,10.0,neutral or dissatisfied +56800,19068,Male,Loyal Customer,31,Business travel,Business,2033,1,1,1,1,4,4,4,4,4,1,1,4,2,4,38,31.0,satisfied +56801,126929,Female,Loyal Customer,38,Business travel,Business,3389,4,4,4,4,5,4,4,3,3,2,3,5,3,3,0,0.0,satisfied +56802,6194,Male,Loyal Customer,50,Business travel,Business,2992,1,1,1,1,2,5,4,2,2,2,2,4,2,4,51,45.0,satisfied +56803,112636,Female,disloyal Customer,29,Business travel,Eco Plus,602,4,4,4,4,4,4,4,4,5,4,5,2,4,4,1,0.0,neutral or dissatisfied +56804,107559,Male,disloyal Customer,54,Business travel,Eco,1242,1,1,1,4,2,1,2,2,4,2,4,1,4,2,5,0.0,neutral or dissatisfied +56805,4182,Male,Loyal Customer,39,Personal Travel,Eco,427,1,2,3,4,4,3,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +56806,112867,Male,Loyal Customer,62,Business travel,Business,715,4,4,4,4,3,5,5,4,4,4,4,3,4,3,10,3.0,satisfied +56807,114280,Female,Loyal Customer,60,Personal Travel,Eco,853,2,5,3,2,5,4,5,5,5,3,5,4,5,4,29,15.0,neutral or dissatisfied +56808,33212,Male,Loyal Customer,59,Business travel,Eco Plus,101,2,5,5,5,2,2,2,2,3,5,5,5,2,2,0,3.0,satisfied +56809,13840,Female,Loyal Customer,50,Personal Travel,Eco,628,1,4,1,3,3,5,5,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +56810,121140,Female,disloyal Customer,25,Business travel,Business,1014,5,0,5,4,2,5,4,2,5,2,3,4,5,2,2,0.0,satisfied +56811,34744,Female,Loyal Customer,42,Business travel,Eco,301,2,5,3,5,2,3,3,5,1,1,2,3,5,3,134,122.0,satisfied +56812,79738,Male,Loyal Customer,22,Business travel,Eco Plus,760,2,1,3,3,2,2,1,2,2,3,3,1,3,2,49,47.0,neutral or dissatisfied +56813,64864,Male,Loyal Customer,60,Business travel,Business,2052,2,2,2,2,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +56814,56784,Female,Loyal Customer,33,Personal Travel,Eco Plus,1085,4,4,5,2,2,5,1,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +56815,39490,Female,Loyal Customer,43,Personal Travel,Eco,867,4,4,4,4,4,3,2,3,3,4,3,3,3,1,0,1.0,neutral or dissatisfied +56816,105038,Male,Loyal Customer,58,Personal Travel,Eco,361,0,5,0,3,4,0,4,4,5,4,4,3,4,4,11,15.0,satisfied +56817,44153,Female,Loyal Customer,28,Personal Travel,Eco Plus,98,4,5,0,3,1,0,1,1,3,4,5,5,5,1,0,11.0,neutral or dissatisfied +56818,42709,Female,disloyal Customer,24,Business travel,Eco,516,0,0,0,5,3,0,3,3,1,2,2,1,5,3,0,0.0,satisfied +56819,51648,Female,Loyal Customer,39,Business travel,Business,1958,2,3,3,3,4,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +56820,19262,Male,Loyal Customer,38,Business travel,Business,2610,4,4,4,4,2,2,4,4,4,4,4,2,4,2,0,0.0,satisfied +56821,89785,Female,Loyal Customer,10,Personal Travel,Eco,1096,3,4,3,1,4,3,4,4,1,4,3,3,1,4,0,0.0,neutral or dissatisfied +56822,9650,Male,disloyal Customer,59,Business travel,Business,199,3,3,3,2,1,3,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +56823,113667,Female,Loyal Customer,40,Personal Travel,Eco,488,2,4,2,2,4,2,2,4,3,5,4,4,5,4,1,0.0,neutral or dissatisfied +56824,32620,Male,Loyal Customer,48,Business travel,Business,163,3,5,5,5,5,4,3,2,2,2,3,3,2,4,5,7.0,neutral or dissatisfied +56825,59697,Male,Loyal Customer,42,Personal Travel,Eco,861,3,5,3,3,3,3,3,3,5,3,5,4,5,3,3,0.0,neutral or dissatisfied +56826,30383,Female,Loyal Customer,28,Business travel,Eco,775,4,3,4,4,4,4,4,4,2,4,5,1,2,4,0,7.0,satisfied +56827,25014,Male,disloyal Customer,26,Business travel,Eco,907,3,3,3,2,5,3,4,5,3,1,1,1,4,5,7,2.0,neutral or dissatisfied +56828,39971,Female,Loyal Customer,58,Business travel,Business,1404,1,2,3,2,5,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +56829,36751,Male,Loyal Customer,44,Business travel,Business,2611,5,5,5,5,4,4,4,4,5,3,2,4,5,4,21,10.0,satisfied +56830,57489,Female,Loyal Customer,58,Business travel,Business,1075,2,1,1,1,4,1,1,2,2,2,2,1,2,2,13,10.0,neutral or dissatisfied +56831,30941,Female,Loyal Customer,49,Business travel,Eco,1024,2,2,2,2,4,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +56832,46443,Female,Loyal Customer,47,Personal Travel,Eco,1304,2,5,2,3,3,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +56833,50723,Female,Loyal Customer,26,Personal Travel,Eco,109,2,2,2,4,5,2,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +56834,45929,Female,Loyal Customer,16,Personal Travel,Eco,641,2,4,2,2,5,2,5,5,3,5,4,5,4,5,27,12.0,neutral or dissatisfied +56835,69369,Female,Loyal Customer,16,Business travel,Eco,1096,3,4,4,4,3,3,3,3,3,3,3,4,4,3,29,39.0,neutral or dissatisfied +56836,126174,Female,disloyal Customer,37,Business travel,Eco,590,3,2,2,4,5,2,5,5,4,1,4,2,4,5,0,3.0,neutral or dissatisfied +56837,53597,Male,disloyal Customer,25,Business travel,Eco,993,3,3,3,1,3,5,5,1,2,5,4,5,2,5,15,3.0,neutral or dissatisfied +56838,81480,Male,disloyal Customer,56,Business travel,Eco,128,3,5,3,4,1,3,1,1,1,2,5,4,4,1,4,0.0,neutral or dissatisfied +56839,127814,Male,Loyal Customer,62,Business travel,Eco,1262,3,1,1,1,3,3,3,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +56840,42248,Female,Loyal Customer,16,Business travel,Eco,834,1,3,3,3,1,1,2,1,2,3,4,3,3,1,67,54.0,neutral or dissatisfied +56841,76730,Male,Loyal Customer,47,Business travel,Eco Plus,147,3,4,4,4,3,3,3,1,2,3,4,3,3,3,184,176.0,neutral or dissatisfied +56842,15219,Male,disloyal Customer,21,Business travel,Eco,445,0,5,0,4,3,0,3,3,3,2,1,5,4,3,0,10.0,satisfied +56843,76396,Male,Loyal Customer,14,Personal Travel,Eco,931,1,4,1,4,4,1,4,4,3,4,4,5,4,4,73,83.0,neutral or dissatisfied +56844,12865,Male,Loyal Customer,53,Business travel,Eco Plus,489,2,2,3,2,2,2,2,2,1,4,3,3,3,2,16,6.0,neutral or dissatisfied +56845,103923,Male,disloyal Customer,49,Business travel,Business,770,2,2,2,1,2,2,2,2,5,5,5,3,5,2,77,68.0,neutral or dissatisfied +56846,1801,Male,Loyal Customer,45,Business travel,Business,408,4,4,3,4,2,5,4,5,5,5,5,5,5,3,0,4.0,satisfied +56847,54434,Male,Loyal Customer,42,Personal Travel,Eco,305,1,4,1,1,5,1,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +56848,59881,Male,disloyal Customer,28,Business travel,Business,1085,0,0,0,5,5,0,5,5,5,5,5,3,5,5,0,0.0,satisfied +56849,6281,Female,Loyal Customer,58,Business travel,Business,2078,2,5,5,5,1,4,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +56850,125039,Male,Loyal Customer,24,Business travel,Business,2300,2,1,1,1,2,2,2,2,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +56851,117354,Female,Loyal Customer,41,Business travel,Business,2378,2,2,2,2,4,5,5,4,4,5,4,3,4,5,42,38.0,satisfied +56852,10845,Female,Loyal Customer,77,Business travel,Business,3708,3,1,1,1,1,2,2,3,3,3,3,4,3,3,77,69.0,neutral or dissatisfied +56853,105384,Female,disloyal Customer,21,Business travel,Eco,369,1,2,1,4,1,1,1,1,3,2,4,2,4,1,0,0.0,neutral or dissatisfied +56854,41361,Male,Loyal Customer,30,Business travel,Business,2992,4,4,4,4,3,4,3,3,4,4,1,4,3,3,0,13.0,satisfied +56855,117995,Female,Loyal Customer,37,Business travel,Eco Plus,255,4,5,3,5,4,4,4,4,2,5,3,4,1,4,8,6.0,satisfied +56856,44662,Female,disloyal Customer,33,Business travel,Eco,67,2,0,2,1,5,2,3,5,3,5,1,4,5,5,0,0.0,neutral or dissatisfied +56857,85684,Female,Loyal Customer,34,Business travel,Business,1547,2,5,5,5,2,2,2,4,5,3,4,2,1,2,252,234.0,neutral or dissatisfied +56858,122830,Male,Loyal Customer,25,Business travel,Business,2977,4,4,4,4,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +56859,70181,Male,Loyal Customer,53,Business travel,Business,1833,3,3,3,3,2,4,5,5,5,5,5,4,5,4,0,17.0,satisfied +56860,56868,Female,Loyal Customer,44,Business travel,Business,2425,2,2,5,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +56861,80683,Female,Loyal Customer,56,Business travel,Business,2243,1,1,4,1,2,5,5,4,4,4,4,3,4,3,0,4.0,satisfied +56862,18661,Female,Loyal Customer,13,Personal Travel,Eco,253,3,5,3,2,4,3,3,4,3,3,5,1,3,4,0,0.0,neutral or dissatisfied +56863,1070,Male,Loyal Customer,54,Personal Travel,Eco,396,3,5,3,1,2,3,2,2,4,3,5,5,4,2,0,20.0,neutral or dissatisfied +56864,79099,Male,Loyal Customer,28,Personal Travel,Eco,356,2,2,2,3,2,2,2,2,1,5,4,1,3,2,6,5.0,neutral or dissatisfied +56865,35600,Female,disloyal Customer,25,Business travel,Eco Plus,669,0,0,0,5,1,0,1,1,5,2,5,1,5,1,0,0.0,satisfied +56866,80707,Male,Loyal Customer,33,Personal Travel,Eco,748,2,4,2,5,1,2,5,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +56867,4952,Male,Loyal Customer,45,Business travel,Business,3921,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,15.0,satisfied +56868,18602,Female,Loyal Customer,45,Business travel,Eco,253,4,3,3,3,2,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +56869,84082,Female,Loyal Customer,49,Personal Travel,Eco,773,2,4,2,4,4,5,5,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +56870,22522,Female,disloyal Customer,36,Business travel,Eco Plus,145,2,2,2,3,4,2,1,4,4,5,5,1,4,4,0,0.0,neutral or dissatisfied +56871,72414,Female,Loyal Customer,53,Business travel,Business,3268,3,3,3,3,4,5,4,4,4,4,4,4,4,3,13,25.0,satisfied +56872,91168,Female,Loyal Customer,52,Personal Travel,Eco,646,2,1,2,2,5,3,2,4,4,2,3,4,4,1,52,40.0,neutral or dissatisfied +56873,55155,Female,Loyal Customer,15,Personal Travel,Eco,1635,3,5,3,4,5,3,5,5,3,3,5,5,5,5,7,0.0,neutral or dissatisfied +56874,8245,Male,Loyal Customer,48,Personal Travel,Eco,335,2,1,2,4,1,2,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +56875,108157,Male,Loyal Customer,52,Personal Travel,Eco,990,3,2,3,3,5,3,5,5,2,1,3,2,3,5,53,28.0,neutral or dissatisfied +56876,44383,Female,Loyal Customer,53,Business travel,Business,323,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,1.0,satisfied +56877,47823,Male,Loyal Customer,33,Business travel,Business,2088,3,3,3,3,5,4,5,5,2,4,3,1,2,5,3,3.0,satisfied +56878,121533,Male,Loyal Customer,55,Business travel,Business,2875,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,4.0,satisfied +56879,32736,Female,Loyal Customer,44,Business travel,Eco,216,4,1,1,1,5,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +56880,93020,Male,Loyal Customer,69,Personal Travel,Eco,1524,2,4,2,4,3,2,3,3,1,2,2,2,4,3,36,15.0,neutral or dissatisfied +56881,64128,Female,Loyal Customer,9,Personal Travel,Eco,2288,3,2,4,3,3,4,1,3,1,5,4,3,3,3,28,17.0,neutral or dissatisfied +56882,46010,Female,disloyal Customer,39,Business travel,Business,300,3,3,3,3,4,3,4,4,2,4,3,4,4,4,23,39.0,neutral or dissatisfied +56883,89229,Male,Loyal Customer,54,Business travel,Business,2092,1,1,1,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +56884,82954,Male,Loyal Customer,44,Business travel,Business,3939,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +56885,84997,Male,Loyal Customer,58,Business travel,Business,1590,5,5,5,5,2,3,5,4,4,4,4,3,4,3,29,7.0,satisfied +56886,3014,Female,Loyal Customer,49,Business travel,Business,2813,3,4,4,4,5,2,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +56887,103481,Female,Loyal Customer,52,Business travel,Business,3138,2,2,4,2,4,4,4,4,4,4,4,5,4,3,13,18.0,satisfied +56888,56406,Male,Loyal Customer,52,Business travel,Business,2461,4,4,1,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +56889,107764,Female,Loyal Customer,56,Personal Travel,Eco,251,3,5,3,3,3,4,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +56890,26433,Female,Loyal Customer,31,Business travel,Business,2467,1,1,1,1,4,4,4,4,5,4,1,1,2,4,0,21.0,satisfied +56891,23431,Male,Loyal Customer,41,Business travel,Business,1716,4,4,4,4,5,4,4,4,4,4,4,3,4,4,5,0.0,satisfied +56892,28749,Female,Loyal Customer,35,Business travel,Business,1024,4,2,1,2,4,3,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +56893,38185,Female,Loyal Customer,23,Personal Travel,Eco,1010,3,4,3,4,5,3,5,5,3,5,4,1,3,5,0,0.0,neutral or dissatisfied +56894,75621,Male,Loyal Customer,48,Personal Travel,Eco,337,2,4,2,3,2,2,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +56895,18623,Female,Loyal Customer,19,Personal Travel,Eco,253,3,3,3,4,1,3,1,1,1,5,3,2,3,1,11,38.0,neutral or dissatisfied +56896,50631,Female,Loyal Customer,23,Personal Travel,Eco,190,3,5,3,3,3,3,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +56897,42210,Male,disloyal Customer,39,Business travel,Eco,834,2,2,2,2,4,2,4,4,4,5,2,1,1,4,0,0.0,neutral or dissatisfied +56898,116236,Female,Loyal Customer,67,Personal Travel,Eco,446,2,3,2,2,5,3,3,1,1,2,2,1,1,1,0,0.0,neutral or dissatisfied +56899,65809,Female,Loyal Customer,51,Business travel,Business,1389,3,3,3,3,2,5,5,4,4,4,4,4,4,3,38,8.0,satisfied +56900,60705,Female,Loyal Customer,52,Business travel,Business,1605,4,4,4,4,3,4,5,3,3,2,3,5,3,4,96,106.0,satisfied +56901,41121,Male,Loyal Customer,28,Business travel,Eco,140,4,4,4,4,4,4,4,4,1,5,2,2,3,4,19,27.0,neutral or dissatisfied +56902,64232,Female,Loyal Customer,27,Business travel,Business,1660,4,4,4,4,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +56903,5424,Male,Loyal Customer,25,Business travel,Eco Plus,589,4,3,1,3,4,4,4,4,1,1,3,4,4,4,5,7.0,neutral or dissatisfied +56904,61065,Male,Loyal Customer,34,Business travel,Business,1506,1,5,4,5,2,2,1,1,1,1,1,2,1,4,1,0.0,neutral or dissatisfied +56905,123800,Male,disloyal Customer,23,Business travel,Eco,544,4,4,4,5,1,4,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +56906,117635,Female,Loyal Customer,56,Personal Travel,Eco,872,1,1,1,2,1,2,3,4,4,1,4,3,4,4,1,0.0,neutral or dissatisfied +56907,42886,Female,disloyal Customer,44,Business travel,Business,368,1,1,1,4,1,1,1,1,1,2,3,1,3,1,0,17.0,neutral or dissatisfied +56908,100092,Male,Loyal Customer,53,Business travel,Business,2569,5,5,5,5,2,4,5,4,4,5,4,4,4,3,61,69.0,satisfied +56909,53607,Male,Loyal Customer,31,Business travel,Eco,1874,4,1,1,1,4,4,4,4,2,5,5,2,2,4,2,0.0,satisfied +56910,102137,Female,disloyal Customer,22,Business travel,Business,236,5,0,5,4,2,5,2,2,5,2,5,4,4,2,27,18.0,satisfied +56911,108867,Male,Loyal Customer,65,Personal Travel,Eco,1892,2,1,2,3,2,2,2,2,3,3,2,4,2,2,28,10.0,neutral or dissatisfied +56912,57032,Female,Loyal Customer,52,Business travel,Business,2425,3,3,3,3,5,5,5,5,3,4,4,5,3,5,0,0.0,satisfied +56913,92673,Male,Loyal Customer,60,Business travel,Business,507,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +56914,18864,Male,Loyal Customer,36,Business travel,Eco,448,4,2,2,2,4,5,4,4,1,2,5,2,1,4,0,0.0,satisfied +56915,42113,Female,Loyal Customer,9,Business travel,Eco,991,4,3,3,3,4,4,3,4,3,3,4,1,4,4,6,23.0,neutral or dissatisfied +56916,56177,Female,Loyal Customer,21,Personal Travel,Eco,1400,4,4,4,2,2,4,2,2,3,4,3,3,5,2,5,0.0,neutral or dissatisfied +56917,114484,Female,Loyal Customer,59,Business travel,Business,3160,3,4,4,4,4,4,3,3,3,3,3,3,3,1,21,17.0,neutral or dissatisfied +56918,7349,Male,disloyal Customer,42,Business travel,Business,864,4,4,4,4,4,4,4,4,3,4,4,3,5,4,78,71.0,satisfied +56919,18964,Female,Loyal Customer,32,Business travel,Eco Plus,503,2,1,1,1,2,2,2,2,3,1,3,4,4,2,47,35.0,neutral or dissatisfied +56920,27163,Male,Loyal Customer,23,Business travel,Business,3341,3,5,3,3,5,5,5,1,1,1,2,5,5,5,0,0.0,satisfied +56921,89141,Female,disloyal Customer,21,Business travel,Eco,1178,4,4,4,3,4,1,2,3,5,4,4,2,1,2,76,102.0,neutral or dissatisfied +56922,29089,Male,Loyal Customer,56,Personal Travel,Eco,954,3,2,3,3,4,3,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +56923,104340,Male,Loyal Customer,9,Personal Travel,Eco,452,4,5,4,3,2,4,2,2,2,3,3,5,3,2,0,0.0,satisfied +56924,66545,Female,Loyal Customer,44,Business travel,Business,2935,3,3,3,3,4,5,5,4,4,4,4,4,4,4,32,27.0,satisfied +56925,118902,Male,Loyal Customer,43,Business travel,Business,3132,5,5,5,5,2,4,4,5,5,5,5,4,5,3,9,0.0,satisfied +56926,42921,Female,disloyal Customer,24,Business travel,Eco,404,1,0,1,5,1,1,1,1,4,5,5,2,2,1,0,0.0,neutral or dissatisfied +56927,51701,Female,disloyal Customer,40,Business travel,Business,370,2,2,2,3,3,2,3,3,1,1,5,2,5,3,0,0.0,neutral or dissatisfied +56928,86197,Female,disloyal Customer,38,Business travel,Eco,226,3,1,3,3,1,3,1,1,3,1,4,2,4,1,30,37.0,neutral or dissatisfied +56929,25375,Male,Loyal Customer,22,Business travel,Business,2841,2,2,2,2,3,3,3,3,4,5,1,3,1,3,0,0.0,satisfied +56930,85551,Female,Loyal Customer,48,Business travel,Business,259,2,2,2,2,5,4,5,4,4,4,4,5,4,4,6,1.0,satisfied +56931,12165,Female,Loyal Customer,37,Business travel,Eco,986,3,4,4,4,3,3,3,3,3,3,4,5,3,3,0,0.0,satisfied +56932,110192,Female,Loyal Customer,29,Personal Travel,Eco,1056,3,4,3,2,2,3,2,2,2,2,4,3,1,2,40,30.0,neutral or dissatisfied +56933,112268,Male,disloyal Customer,22,Business travel,Eco,1703,3,3,3,3,2,3,2,2,4,2,2,2,4,2,0,0.0,neutral or dissatisfied +56934,75027,Female,Loyal Customer,62,Business travel,Eco,236,3,1,3,3,5,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +56935,2897,Male,Loyal Customer,30,Personal Travel,Eco,409,1,5,1,2,3,1,3,3,4,5,5,3,4,3,0,4.0,neutral or dissatisfied +56936,80109,Male,disloyal Customer,65,Business travel,Eco,126,2,1,2,2,2,5,1,2,3,1,1,1,3,1,195,184.0,neutral or dissatisfied +56937,71029,Male,disloyal Customer,20,Business travel,Eco,802,3,3,3,4,4,3,2,4,5,3,4,4,5,4,14,0.0,neutral or dissatisfied +56938,59460,Male,Loyal Customer,29,Business travel,Business,758,2,2,2,2,4,3,4,4,3,5,5,3,5,4,7,0.0,satisfied +56939,89077,Female,Loyal Customer,33,Business travel,Business,1947,4,5,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +56940,23156,Male,Loyal Customer,38,Personal Travel,Eco,300,4,4,4,3,3,4,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +56941,61320,Female,disloyal Customer,29,Business travel,Eco Plus,862,3,3,3,4,1,3,1,1,3,5,3,1,4,1,1,0.0,neutral or dissatisfied +56942,36046,Male,Loyal Customer,75,Business travel,Eco,399,3,2,2,2,3,3,3,3,4,4,3,3,3,3,8,30.0,neutral or dissatisfied +56943,30117,Male,Loyal Customer,47,Personal Travel,Eco,261,4,4,0,4,3,0,3,3,4,2,3,1,3,3,21,25.0,neutral or dissatisfied +56944,11507,Male,Loyal Customer,61,Personal Travel,Eco Plus,163,1,5,1,2,3,1,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +56945,84663,Female,Loyal Customer,39,Business travel,Business,2182,3,3,3,3,2,4,4,4,4,4,4,5,4,4,1,15.0,satisfied +56946,51637,Female,Loyal Customer,66,Business travel,Business,2928,3,1,1,1,5,3,4,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +56947,61992,Male,Loyal Customer,36,Business travel,Business,2586,4,4,4,4,2,4,5,5,5,5,5,5,5,5,7,11.0,satisfied +56948,85791,Male,Loyal Customer,26,Business travel,Eco,666,1,2,2,2,1,2,1,1,4,3,2,1,2,1,215,232.0,neutral or dissatisfied +56949,1605,Female,Loyal Customer,13,Personal Travel,Eco,140,3,3,3,3,5,3,5,5,2,5,4,4,3,5,0,0.0,neutral or dissatisfied +56950,91959,Female,Loyal Customer,59,Personal Travel,Eco,2586,3,2,3,3,2,3,3,1,1,3,2,2,1,1,0,0.0,neutral or dissatisfied +56951,41455,Male,Loyal Customer,47,Business travel,Business,3282,4,4,4,4,3,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +56952,26890,Female,Loyal Customer,48,Personal Travel,Eco,689,2,4,2,3,5,5,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +56953,70527,Male,Loyal Customer,23,Business travel,Business,1258,3,3,3,3,4,4,4,4,5,2,4,3,4,4,0,3.0,satisfied +56954,8235,Female,Loyal Customer,40,Personal Travel,Eco,530,2,5,2,3,1,2,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +56955,90031,Female,Loyal Customer,40,Business travel,Business,3380,2,2,4,2,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +56956,111720,Male,Loyal Customer,69,Personal Travel,Eco,495,3,5,3,5,5,3,5,5,4,5,4,3,5,5,21,9.0,neutral or dissatisfied +56957,95710,Female,Loyal Customer,42,Business travel,Business,3445,4,4,4,4,5,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +56958,103458,Male,disloyal Customer,37,Business travel,Business,393,5,5,5,4,1,5,1,1,5,2,5,4,4,1,19,0.0,satisfied +56959,56303,Male,Loyal Customer,41,Business travel,Business,2227,1,1,1,1,3,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +56960,16699,Male,Loyal Customer,53,Business travel,Business,2186,3,5,5,5,4,3,3,3,3,3,3,1,3,1,0,8.0,neutral or dissatisfied +56961,38526,Female,Loyal Customer,20,Business travel,Business,2586,5,1,5,5,5,4,5,5,4,4,5,3,1,5,0,0.0,satisfied +56962,59860,Male,Loyal Customer,43,Business travel,Business,1860,3,3,2,3,4,4,4,5,5,5,5,5,5,3,25,7.0,satisfied +56963,9853,Male,disloyal Customer,26,Business travel,Business,717,3,3,3,4,1,3,2,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +56964,6584,Male,Loyal Customer,61,Business travel,Business,207,0,4,0,2,1,2,2,3,3,3,3,1,3,4,0,0.0,satisfied +56965,119532,Male,Loyal Customer,16,Personal Travel,Eco,899,3,5,3,2,3,3,5,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +56966,78520,Female,Loyal Customer,63,Personal Travel,Eco,526,1,4,4,3,5,4,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +56967,9185,Male,Loyal Customer,54,Business travel,Eco,363,2,4,4,4,2,2,2,2,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +56968,81932,Male,Loyal Customer,68,Personal Travel,Business,1454,2,2,2,4,4,4,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +56969,124094,Female,Loyal Customer,54,Business travel,Business,2077,4,4,4,4,3,5,4,5,5,5,5,3,5,4,30,0.0,satisfied +56970,28738,Female,Loyal Customer,31,Business travel,Business,1988,3,3,1,3,3,4,3,3,1,1,4,4,2,3,0,0.0,satisfied +56971,30940,Male,Loyal Customer,61,Business travel,Business,1024,4,2,4,4,3,5,3,4,4,4,4,1,4,4,4,0.0,satisfied +56972,38229,Male,disloyal Customer,21,Business travel,Business,1111,4,2,5,3,4,5,4,4,5,2,4,5,5,4,11,4.0,satisfied +56973,103412,Male,Loyal Customer,50,Business travel,Business,3636,2,2,2,2,2,4,3,2,2,2,2,2,2,1,0,1.0,neutral or dissatisfied +56974,61371,Male,Loyal Customer,56,Business travel,Business,1618,2,2,2,2,5,5,5,3,3,4,3,3,3,3,5,0.0,satisfied +56975,61360,Female,Loyal Customer,44,Business travel,Business,2405,4,4,4,4,4,5,4,2,2,2,2,5,2,5,58,66.0,satisfied +56976,48336,Female,disloyal Customer,23,Business travel,Eco,522,4,3,4,4,3,4,3,3,4,3,5,1,4,3,95,105.0,neutral or dissatisfied +56977,3371,Male,Loyal Customer,56,Business travel,Business,3473,2,2,2,2,4,4,4,5,5,5,5,3,5,3,0,16.0,satisfied +56978,26341,Male,Loyal Customer,58,Business travel,Eco,834,1,3,3,3,1,1,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +56979,23138,Female,Loyal Customer,57,Business travel,Business,3847,4,4,4,4,3,1,2,5,5,4,3,5,5,5,0,1.0,satisfied +56980,99563,Female,Loyal Customer,49,Business travel,Business,1735,3,3,3,3,5,4,5,5,5,5,5,5,5,3,3,0.0,satisfied +56981,119583,Male,Loyal Customer,37,Business travel,Business,2276,1,1,1,1,3,3,3,5,4,5,5,3,4,3,0,0.0,satisfied +56982,92161,Male,disloyal Customer,22,Business travel,Eco,1277,3,3,3,3,1,3,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +56983,34776,Female,Loyal Customer,69,Personal Travel,Eco,264,3,2,3,4,1,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +56984,40237,Male,disloyal Customer,36,Business travel,Eco,387,2,2,2,3,3,2,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +56985,123000,Female,disloyal Customer,21,Business travel,Eco,468,2,0,1,1,4,1,4,4,3,3,5,3,4,4,0,13.0,neutral or dissatisfied +56986,102430,Male,Loyal Customer,39,Personal Travel,Eco,397,2,1,2,3,3,2,3,3,2,3,4,3,4,3,10,5.0,neutral or dissatisfied +56987,119952,Male,disloyal Customer,64,Business travel,Business,1009,5,5,5,4,2,5,2,2,5,5,5,4,4,2,0,3.0,satisfied +56988,44152,Male,Loyal Customer,18,Personal Travel,Eco Plus,198,1,4,1,5,5,1,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +56989,3648,Female,disloyal Customer,23,Business travel,Eco,431,4,0,4,5,4,4,4,4,4,2,5,4,4,4,29,29.0,neutral or dissatisfied +56990,86951,Male,disloyal Customer,28,Business travel,Business,907,1,1,1,3,2,1,3,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +56991,51558,Female,Loyal Customer,55,Business travel,Business,2821,1,1,1,1,3,2,3,5,5,5,5,1,5,2,0,0.0,satisfied +56992,10676,Female,disloyal Customer,35,Business travel,Eco,301,3,4,3,4,5,3,5,5,1,4,4,3,3,5,0,0.0,neutral or dissatisfied +56993,69719,Male,Loyal Customer,39,Business travel,Eco,972,2,4,4,4,2,2,2,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +56994,31215,Male,Loyal Customer,45,Personal Travel,Eco,628,2,4,2,3,5,2,2,5,1,4,3,1,4,5,0,0.0,neutral or dissatisfied +56995,46158,Male,Loyal Customer,66,Personal Travel,Eco,516,5,1,5,2,2,5,5,2,1,5,3,3,2,2,0,20.0,satisfied +56996,27062,Female,Loyal Customer,57,Business travel,Eco,1399,4,2,2,2,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +56997,34251,Female,Loyal Customer,42,Business travel,Eco,1666,4,1,1,1,5,4,4,4,4,4,4,5,4,3,11,0.0,satisfied +56998,49690,Female,Loyal Customer,39,Business travel,Eco,207,5,3,3,3,5,5,5,5,2,1,3,4,2,5,0,0.0,satisfied +56999,75243,Male,Loyal Customer,33,Personal Travel,Eco,1744,3,4,3,2,2,3,2,2,3,2,5,4,4,2,32,9.0,neutral or dissatisfied +57000,90462,Male,disloyal Customer,23,Business travel,Eco,594,3,0,3,3,1,3,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +57001,102035,Female,Loyal Customer,43,Business travel,Business,3247,3,3,3,3,5,3,2,3,3,3,3,2,3,1,0,26.0,neutral or dissatisfied +57002,33651,Female,Loyal Customer,34,Personal Travel,Eco,399,1,4,1,3,2,1,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +57003,105117,Male,Loyal Customer,47,Business travel,Business,2809,0,1,1,2,5,5,4,5,5,5,5,5,5,4,9,14.0,satisfied +57004,100603,Female,Loyal Customer,49,Business travel,Eco,718,1,1,1,1,4,3,3,1,1,1,1,3,1,4,26,32.0,neutral or dissatisfied +57005,42163,Male,disloyal Customer,42,Business travel,Eco,451,2,5,2,4,5,2,5,5,4,3,4,3,5,5,72,59.0,neutral or dissatisfied +57006,3002,Female,Loyal Customer,35,Business travel,Business,2336,5,5,5,5,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +57007,3356,Female,disloyal Customer,25,Business travel,Eco,296,1,1,1,4,3,1,3,3,2,4,4,3,4,3,48,58.0,neutral or dissatisfied +57008,93344,Female,Loyal Customer,42,Business travel,Business,1024,2,2,3,2,2,4,4,4,4,4,4,4,4,3,50,42.0,satisfied +57009,79451,Male,Loyal Customer,55,Business travel,Business,2174,3,2,2,2,2,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +57010,1972,Female,Loyal Customer,43,Personal Travel,Eco,351,1,3,1,4,2,4,3,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +57011,32850,Female,Loyal Customer,41,Personal Travel,Eco,101,5,5,5,1,1,5,1,1,3,4,5,4,4,1,0,0.0,satisfied +57012,79180,Female,Loyal Customer,45,Business travel,Eco,2422,2,5,5,5,2,2,2,1,3,3,2,2,4,2,0,2.0,neutral or dissatisfied +57013,124557,Female,disloyal Customer,40,Business travel,Business,453,2,2,2,3,4,2,4,4,4,3,4,4,5,4,0,3.0,neutral or dissatisfied +57014,2381,Female,Loyal Customer,39,Business travel,Business,3314,3,3,3,3,2,4,5,4,4,4,4,4,4,5,0,17.0,satisfied +57015,109844,Male,Loyal Customer,29,Business travel,Business,971,1,2,2,2,1,1,1,1,1,4,3,1,4,1,39,15.0,neutral or dissatisfied +57016,78422,Female,Loyal Customer,57,Business travel,Business,453,5,5,5,5,4,4,5,4,4,4,4,5,4,5,3,4.0,satisfied +57017,48585,Male,Loyal Customer,10,Personal Travel,Eco,848,2,5,2,3,3,2,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +57018,37571,Female,Loyal Customer,34,Business travel,Business,2314,2,3,3,3,2,1,2,2,2,2,2,3,2,3,30,18.0,neutral or dissatisfied +57019,39891,Male,Loyal Customer,65,Personal Travel,Eco,184,4,1,4,3,4,4,4,4,3,1,4,3,4,4,0,0.0,neutral or dissatisfied +57020,37910,Male,Loyal Customer,19,Personal Travel,Eco,997,2,5,2,5,2,2,2,2,4,3,5,4,5,2,2,0.0,neutral or dissatisfied +57021,10642,Male,Loyal Customer,47,Business travel,Eco,224,4,5,5,5,4,4,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +57022,67913,Female,Loyal Customer,51,Personal Travel,Eco,1235,3,4,3,3,2,3,3,3,3,3,3,4,3,3,14,6.0,neutral or dissatisfied +57023,55846,Male,Loyal Customer,50,Personal Travel,Eco,1416,3,1,3,3,1,3,1,1,2,5,3,2,2,1,0,0.0,neutral or dissatisfied +57024,95402,Female,Loyal Customer,24,Personal Travel,Eco,562,1,5,1,1,3,1,3,3,4,5,5,3,5,3,27,28.0,neutral or dissatisfied +57025,19222,Male,Loyal Customer,36,Business travel,Business,459,2,2,2,2,1,3,2,4,4,4,4,1,4,3,0,0.0,satisfied +57026,77293,Female,Loyal Customer,41,Business travel,Business,2905,5,5,5,5,4,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +57027,129155,Female,Loyal Customer,60,Business travel,Eco,679,2,5,5,5,5,1,1,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +57028,33014,Male,Loyal Customer,13,Personal Travel,Eco,102,3,5,3,4,2,3,2,2,4,5,5,4,4,2,2,2.0,neutral or dissatisfied +57029,22852,Male,Loyal Customer,66,Personal Travel,Eco,302,3,4,3,5,2,3,2,2,3,3,3,4,5,2,0,0.0,neutral or dissatisfied +57030,72588,Male,disloyal Customer,43,Business travel,Eco,719,2,2,2,4,4,2,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +57031,103924,Male,Loyal Customer,29,Business travel,Business,3044,5,5,5,5,4,4,4,4,5,5,4,4,4,4,78,73.0,satisfied +57032,4431,Male,Loyal Customer,58,Business travel,Business,2311,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +57033,29351,Male,Loyal Customer,43,Personal Travel,Eco,2588,2,5,2,3,2,4,3,3,2,4,5,3,3,3,153,177.0,neutral or dissatisfied +57034,46920,Male,Loyal Customer,54,Business travel,Eco,964,4,1,1,1,4,4,4,4,5,4,3,4,1,4,0,0.0,satisfied +57035,14649,Female,disloyal Customer,23,Business travel,Eco,162,5,0,4,4,4,4,4,4,2,1,1,1,1,4,33,27.0,satisfied +57036,1619,Male,disloyal Customer,38,Business travel,Business,999,1,1,1,2,1,1,1,1,4,4,4,3,5,1,20,9.0,neutral or dissatisfied +57037,107295,Female,Loyal Customer,36,Personal Travel,Eco,307,4,5,4,3,2,4,2,2,1,3,1,1,5,2,60,71.0,neutral or dissatisfied +57038,64660,Female,Loyal Customer,56,Business travel,Business,469,2,2,2,2,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +57039,32415,Male,disloyal Customer,33,Business travel,Business,216,2,2,2,1,4,2,2,4,3,5,4,2,4,4,0,0.0,neutral or dissatisfied +57040,25825,Male,Loyal Customer,17,Business travel,Eco Plus,1747,2,5,5,5,2,2,3,2,2,5,3,1,4,2,12,14.0,neutral or dissatisfied +57041,34524,Female,Loyal Customer,63,Personal Travel,Eco,1428,2,4,2,3,5,2,5,1,1,2,1,3,1,4,0,29.0,neutral or dissatisfied +57042,66848,Male,Loyal Customer,59,Personal Travel,Eco,731,3,2,3,4,5,3,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +57043,66157,Male,disloyal Customer,21,Business travel,Business,550,5,0,5,4,4,0,4,4,3,5,5,4,4,4,21,20.0,satisfied +57044,66760,Male,Loyal Customer,37,Personal Travel,Eco,802,2,5,2,3,4,2,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +57045,97554,Female,Loyal Customer,60,Personal Travel,Eco Plus,675,4,5,4,3,2,2,3,2,2,4,2,2,2,1,50,32.0,neutral or dissatisfied +57046,90111,Female,disloyal Customer,12,Business travel,Eco,1086,4,4,4,4,3,4,3,3,4,3,4,4,3,3,12,0.0,neutral or dissatisfied +57047,98385,Male,Loyal Customer,53,Business travel,Business,1131,5,5,1,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +57048,82675,Female,Loyal Customer,37,Personal Travel,Business,632,4,5,4,2,4,4,5,1,1,4,1,4,1,3,0,0.0,satisfied +57049,87382,Female,disloyal Customer,33,Business travel,Eco,425,2,3,3,4,5,3,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +57050,48193,Female,Loyal Customer,48,Business travel,Eco,236,1,1,1,1,5,4,3,1,1,1,1,4,1,2,0,6.0,neutral or dissatisfied +57051,70891,Female,Loyal Customer,49,Business travel,Business,1721,2,2,3,2,2,4,4,4,4,4,4,4,4,4,117,115.0,satisfied +57052,47400,Male,Loyal Customer,56,Business travel,Business,3355,3,3,3,3,2,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +57053,96325,Male,Loyal Customer,60,Business travel,Business,3998,3,3,2,3,4,4,4,5,5,5,5,3,5,4,40,37.0,satisfied +57054,85047,Female,disloyal Customer,28,Business travel,Business,696,4,4,4,4,5,4,5,5,3,3,5,3,5,5,0,0.0,satisfied +57055,87469,Female,Loyal Customer,49,Business travel,Business,3996,2,2,2,2,5,4,5,5,5,5,5,5,5,3,46,56.0,satisfied +57056,32056,Female,Loyal Customer,52,Business travel,Eco,102,4,4,4,4,3,1,4,5,5,4,5,5,5,3,0,10.0,satisfied +57057,40210,Female,Loyal Customer,59,Business travel,Business,3328,4,4,4,4,2,1,5,5,5,5,5,3,5,3,0,1.0,satisfied +57058,67789,Female,Loyal Customer,60,Business travel,Business,1205,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,3.0,satisfied +57059,100821,Female,disloyal Customer,19,Business travel,Eco,711,2,2,2,5,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +57060,54399,Male,Loyal Customer,32,Business travel,Business,3202,2,2,2,2,4,4,4,4,3,5,4,4,2,4,14,0.0,satisfied +57061,17317,Male,Loyal Customer,19,Personal Travel,Eco,403,1,4,1,3,3,1,3,3,4,4,4,5,4,3,0,8.0,neutral or dissatisfied +57062,33270,Male,Loyal Customer,38,Personal Travel,Eco Plus,102,1,5,1,1,4,1,1,4,3,2,3,5,4,4,0,8.0,neutral or dissatisfied +57063,84333,Male,Loyal Customer,47,Business travel,Business,1964,4,4,4,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +57064,85355,Female,Loyal Customer,13,Personal Travel,Eco Plus,874,3,1,3,3,3,3,3,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +57065,9434,Female,disloyal Customer,21,Business travel,Eco,288,4,0,4,1,5,4,4,5,4,2,4,3,4,5,0,0.0,satisfied +57066,59745,Female,Loyal Customer,40,Business travel,Business,2291,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +57067,28668,Male,Loyal Customer,43,Business travel,Eco Plus,2417,5,5,5,5,5,5,5,5,5,2,5,3,3,5,0,0.0,satisfied +57068,92651,Male,Loyal Customer,38,Personal Travel,Eco,453,2,1,2,3,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +57069,32184,Male,Loyal Customer,29,Business travel,Business,2610,0,4,0,1,2,2,2,2,5,4,4,5,5,2,0,0.0,satisfied +57070,12061,Female,Loyal Customer,52,Personal Travel,Eco,376,2,4,2,3,4,5,4,2,2,2,3,4,2,4,0,0.0,neutral or dissatisfied +57071,7864,Female,disloyal Customer,42,Business travel,Business,948,5,5,5,4,4,5,4,4,4,4,5,4,4,4,1,0.0,satisfied +57072,26926,Male,Loyal Customer,12,Personal Travel,Eco,1770,3,4,3,3,1,3,1,1,2,4,1,4,1,1,0,11.0,neutral or dissatisfied +57073,96751,Female,Loyal Customer,54,Business travel,Business,2448,3,3,1,3,2,4,4,4,4,5,4,5,4,3,3,8.0,satisfied +57074,20823,Male,Loyal Customer,33,Business travel,Business,1566,2,3,3,3,2,2,2,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +57075,90667,Female,Loyal Customer,55,Business travel,Business,3025,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +57076,35553,Male,Loyal Customer,51,Personal Travel,Eco,1069,3,3,3,2,1,3,1,1,3,5,3,2,2,1,0,0.0,neutral or dissatisfied +57077,88895,Male,Loyal Customer,30,Business travel,Business,1634,2,3,2,2,5,5,5,5,3,2,4,5,4,5,2,0.0,satisfied +57078,470,Male,Loyal Customer,43,Business travel,Business,1634,3,2,3,3,5,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +57079,90143,Male,disloyal Customer,38,Business travel,Eco,583,3,4,2,3,2,2,2,2,4,2,4,2,3,2,70,50.0,neutral or dissatisfied +57080,8766,Male,disloyal Customer,25,Business travel,Business,522,4,0,3,3,5,3,5,5,3,5,5,3,5,5,0,0.0,satisfied +57081,98382,Female,Loyal Customer,37,Personal Travel,Business,1131,2,2,2,3,4,4,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +57082,98644,Male,Loyal Customer,57,Business travel,Eco,920,3,2,2,2,3,3,3,1,4,3,4,3,3,3,160,182.0,neutral or dissatisfied +57083,11041,Male,Loyal Customer,51,Personal Travel,Eco,158,3,5,3,4,1,3,2,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +57084,27885,Male,disloyal Customer,48,Business travel,Eco,969,2,2,2,5,5,2,5,5,5,2,3,2,2,5,0,0.0,neutral or dissatisfied +57085,61708,Male,Loyal Customer,26,Business travel,Business,1608,3,3,5,3,2,2,2,2,5,3,3,4,4,2,26,16.0,satisfied +57086,46568,Male,Loyal Customer,45,Business travel,Business,125,3,3,3,3,3,2,2,4,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +57087,18519,Male,Loyal Customer,30,Business travel,Business,2881,3,3,3,3,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +57088,10443,Female,disloyal Customer,20,Business travel,Business,191,5,0,5,4,2,5,2,2,4,2,4,4,4,2,16,18.0,satisfied +57089,128383,Male,Loyal Customer,54,Business travel,Business,647,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +57090,85023,Female,Loyal Customer,37,Personal Travel,Eco,1590,4,4,4,4,3,4,3,3,3,5,3,5,4,3,87,69.0,neutral or dissatisfied +57091,63698,Female,Loyal Customer,37,Personal Travel,Eco,853,1,4,1,2,5,1,5,5,3,2,5,4,5,5,0,23.0,neutral or dissatisfied +57092,90507,Female,Loyal Customer,37,Business travel,Business,404,2,4,4,4,1,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +57093,40335,Male,Loyal Customer,37,Personal Travel,Eco Plus,463,4,5,4,3,2,4,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +57094,5805,Female,Loyal Customer,34,Business travel,Business,157,4,4,4,4,1,3,4,1,1,1,4,2,1,3,0,0.0,neutral or dissatisfied +57095,69753,Female,Loyal Customer,14,Personal Travel,Eco,1085,2,1,2,3,4,2,4,4,3,4,4,3,3,4,13,4.0,neutral or dissatisfied +57096,127428,Female,Loyal Customer,56,Personal Travel,Eco,1009,2,4,2,2,3,5,5,4,4,2,2,3,4,4,0,0.0,neutral or dissatisfied +57097,122914,Male,Loyal Customer,46,Business travel,Business,328,0,0,0,3,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +57098,67856,Male,Loyal Customer,50,Personal Travel,Eco,1438,4,5,4,4,2,4,2,2,3,3,4,3,4,2,0,0.0,satisfied +57099,37422,Female,Loyal Customer,43,Business travel,Eco,944,5,2,2,2,3,5,4,4,4,5,4,1,4,2,0,0.0,satisfied +57100,13855,Female,Loyal Customer,51,Business travel,Eco Plus,583,2,2,2,2,2,2,4,2,2,2,2,3,2,2,0,12.0,satisfied +57101,2053,Male,Loyal Customer,33,Business travel,Business,2860,3,3,4,3,4,4,4,4,5,4,5,3,5,4,0,7.0,satisfied +57102,104288,Female,Loyal Customer,32,Business travel,Business,440,4,2,2,2,4,3,4,4,3,3,3,4,4,4,0,28.0,neutral or dissatisfied +57103,42574,Female,Loyal Customer,66,Business travel,Eco,315,1,1,2,2,2,2,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +57104,61776,Female,Loyal Customer,64,Personal Travel,Eco,1635,0,5,0,3,4,5,4,2,2,0,2,3,2,3,0,0.0,satisfied +57105,24118,Female,Loyal Customer,62,Business travel,Eco,184,5,3,3,3,4,2,3,5,5,5,5,5,5,3,3,0.0,satisfied +57106,89255,Male,Loyal Customer,54,Business travel,Business,453,2,2,2,2,3,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +57107,57239,Female,disloyal Customer,25,Business travel,Business,228,3,0,3,1,3,3,3,3,4,2,5,3,5,3,15,3.0,neutral or dissatisfied +57108,101517,Male,disloyal Customer,46,Personal Travel,Eco,345,3,4,3,4,5,3,5,5,5,5,4,3,5,5,13,11.0,neutral or dissatisfied +57109,96200,Male,Loyal Customer,59,Business travel,Eco,687,2,2,2,2,3,2,3,3,3,5,3,4,3,3,4,3.0,neutral or dissatisfied +57110,14175,Female,disloyal Customer,12,Business travel,Eco,692,4,4,4,4,2,4,2,2,2,3,4,4,3,2,0,0.0,satisfied +57111,125012,Female,Loyal Customer,35,Personal Travel,Eco,184,2,3,2,3,4,2,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +57112,88493,Male,Loyal Customer,55,Business travel,Business,3764,4,4,4,4,5,1,3,5,5,5,5,4,5,1,0,0.0,satisfied +57113,94467,Female,disloyal Customer,49,Business travel,Business,187,3,3,3,3,2,3,2,2,4,4,4,3,4,2,4,5.0,neutral or dissatisfied +57114,91968,Female,Loyal Customer,51,Personal Travel,Eco,2586,3,2,3,4,2,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +57115,123697,Female,Loyal Customer,36,Personal Travel,Eco,214,2,0,2,1,3,2,3,3,4,4,3,3,2,3,0,0.0,neutral or dissatisfied +57116,51939,Male,Loyal Customer,41,Business travel,Business,3639,3,3,3,3,4,2,5,4,4,4,4,1,4,1,0,0.0,satisfied +57117,15888,Female,Loyal Customer,58,Personal Travel,Eco,332,4,4,4,1,5,5,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +57118,127158,Male,Loyal Customer,28,Personal Travel,Eco,621,1,3,1,4,3,1,3,3,4,2,2,5,2,3,26,19.0,neutral or dissatisfied +57119,90950,Male,disloyal Customer,36,Business travel,Eco,246,2,4,2,4,5,2,5,5,3,3,1,3,1,5,0,0.0,neutral or dissatisfied +57120,113056,Female,Loyal Customer,42,Business travel,Business,1642,1,1,1,1,2,5,4,4,4,4,4,4,4,5,124,123.0,satisfied +57121,85418,Female,disloyal Customer,26,Business travel,Eco,214,2,2,2,4,2,2,2,2,3,4,3,1,4,2,55,48.0,neutral or dissatisfied +57122,19699,Male,disloyal Customer,38,Business travel,Eco,409,2,0,2,1,2,2,2,2,5,2,2,3,5,2,1,0.0,neutral or dissatisfied +57123,70173,Male,Loyal Customer,53,Business travel,Business,3140,3,3,3,3,3,5,5,4,4,4,4,4,4,5,12,15.0,satisfied +57124,57690,Male,Loyal Customer,60,Business travel,Business,867,5,5,5,5,5,4,4,4,4,4,4,5,4,3,3,0.0,satisfied +57125,28204,Male,Loyal Customer,58,Personal Travel,Eco,834,3,5,3,3,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +57126,100478,Female,disloyal Customer,30,Business travel,Business,759,4,4,4,4,2,4,2,2,3,2,5,5,5,2,23,17.0,satisfied +57127,106952,Male,Loyal Customer,48,Business travel,Business,2518,2,2,2,2,5,5,5,5,5,5,5,4,5,3,17,21.0,satisfied +57128,99367,Male,Loyal Customer,17,Personal Travel,Eco,409,2,4,2,3,5,2,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +57129,18348,Male,Loyal Customer,43,Business travel,Eco,200,2,2,5,2,2,2,2,2,4,1,3,3,4,2,6,0.0,neutral or dissatisfied +57130,94729,Male,Loyal Customer,44,Business travel,Business,2185,0,0,0,3,3,4,4,2,2,2,4,4,2,4,0,0.0,satisfied +57131,24688,Female,disloyal Customer,27,Business travel,Eco,761,2,2,2,3,3,2,5,3,4,2,3,5,3,3,0,5.0,neutral or dissatisfied +57132,84251,Female,Loyal Customer,40,Business travel,Business,1814,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,3.0,satisfied +57133,58231,Female,Loyal Customer,52,Personal Travel,Eco,925,2,5,3,2,5,5,4,4,4,3,4,4,4,4,15,21.0,neutral or dissatisfied +57134,124359,Female,Loyal Customer,57,Business travel,Business,3426,1,1,1,1,5,5,5,2,2,3,2,4,2,4,0,0.0,satisfied +57135,67970,Female,Loyal Customer,51,Business travel,Business,1464,4,3,4,4,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +57136,72269,Male,disloyal Customer,9,Business travel,Eco,921,1,1,1,3,1,1,1,1,1,4,4,2,3,1,29,24.0,neutral or dissatisfied +57137,92663,Male,Loyal Customer,54,Personal Travel,Eco Plus,453,2,5,2,2,3,2,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +57138,118221,Female,disloyal Customer,21,Business travel,Eco,735,4,4,4,2,2,4,2,2,4,4,2,2,3,2,43,34.0,neutral or dissatisfied +57139,29939,Male,Loyal Customer,21,Business travel,Business,234,3,4,4,4,3,3,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +57140,17227,Female,Loyal Customer,29,Business travel,Business,2425,3,3,3,3,5,5,5,5,2,4,3,3,2,5,1,14.0,satisfied +57141,104159,Male,Loyal Customer,15,Business travel,Eco,349,3,3,3,3,3,3,1,3,4,5,2,3,3,3,13,18.0,neutral or dissatisfied +57142,21212,Male,Loyal Customer,16,Business travel,Eco,153,2,2,2,2,2,2,2,2,1,1,2,1,2,2,10,12.0,neutral or dissatisfied +57143,74514,Male,Loyal Customer,58,Business travel,Business,2436,4,4,4,4,4,5,5,3,3,3,3,4,3,5,22,9.0,satisfied +57144,123585,Male,Loyal Customer,16,Personal Travel,Eco,1773,2,2,1,2,1,1,4,1,2,5,2,4,3,1,0,0.0,neutral or dissatisfied +57145,99115,Male,Loyal Customer,24,Personal Travel,Eco,237,1,5,1,4,5,1,3,5,5,4,4,5,4,5,33,44.0,neutral or dissatisfied +57146,38138,Female,Loyal Customer,67,Personal Travel,Eco,1010,5,3,5,2,4,2,4,1,1,5,1,1,1,4,7,0.0,satisfied +57147,80823,Male,Loyal Customer,56,Business travel,Eco,692,2,1,1,1,2,2,2,2,4,4,3,2,2,2,9,0.0,neutral or dissatisfied +57148,82968,Male,Loyal Customer,50,Business travel,Business,1127,2,2,2,2,2,4,4,2,2,3,2,5,2,5,0,0.0,satisfied +57149,18881,Male,Loyal Customer,55,Business travel,Eco,503,3,5,5,5,2,3,2,2,3,3,3,1,4,2,3,21.0,neutral or dissatisfied +57150,106869,Male,Loyal Customer,32,Business travel,Business,2606,2,1,1,1,2,2,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +57151,40942,Male,Loyal Customer,41,Personal Travel,Eco Plus,501,1,3,1,4,1,1,1,1,1,1,3,1,4,1,0,0.0,neutral or dissatisfied +57152,71070,Male,Loyal Customer,57,Personal Travel,Eco,802,4,3,3,2,4,3,1,4,2,1,4,4,3,4,10,17.0,neutral or dissatisfied +57153,89468,Female,disloyal Customer,44,Business travel,Eco Plus,151,1,1,1,4,1,1,1,1,1,1,4,3,4,1,0,6.0,neutral or dissatisfied +57154,116653,Female,disloyal Customer,32,Business travel,Business,308,2,2,2,1,5,2,5,5,3,3,4,3,5,5,31,13.0,neutral or dissatisfied +57155,100133,Male,Loyal Customer,40,Business travel,Business,468,3,3,3,3,5,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +57156,12566,Male,Loyal Customer,15,Business travel,Eco Plus,871,4,5,5,5,4,4,3,4,3,1,3,4,2,4,21,15.0,satisfied +57157,4889,Male,disloyal Customer,22,Business travel,Business,408,4,0,4,1,2,4,5,2,3,3,5,3,5,2,0,8.0,satisfied +57158,111861,Male,Loyal Customer,29,Business travel,Business,2515,1,0,0,4,4,0,4,4,1,5,4,3,3,4,0,28.0,neutral or dissatisfied +57159,85605,Female,Loyal Customer,65,Personal Travel,Eco,153,2,4,0,1,2,4,4,4,4,0,4,3,4,5,0,0.0,neutral or dissatisfied +57160,36918,Male,Loyal Customer,46,Business travel,Business,340,0,0,0,2,1,5,1,3,3,2,2,4,3,5,0,43.0,satisfied +57161,37170,Male,Loyal Customer,12,Personal Travel,Eco,1046,2,5,2,2,5,2,5,5,4,5,4,5,4,5,37,24.0,neutral or dissatisfied +57162,84066,Male,Loyal Customer,50,Business travel,Business,2230,3,3,3,3,2,5,4,5,5,5,5,5,5,4,11,0.0,satisfied +57163,85680,Male,Loyal Customer,42,Business travel,Business,1547,1,1,1,1,5,4,4,4,4,4,4,5,4,4,28,26.0,satisfied +57164,48667,Male,Loyal Customer,44,Business travel,Business,373,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +57165,124133,Female,Loyal Customer,21,Personal Travel,Eco,529,2,5,2,5,2,2,5,2,5,4,5,3,4,2,0,4.0,neutral or dissatisfied +57166,58204,Male,Loyal Customer,34,Business travel,Business,925,2,2,2,2,4,5,5,5,5,5,5,3,5,4,14,0.0,satisfied +57167,86767,Female,Loyal Customer,61,Business travel,Business,1640,3,4,4,4,3,3,3,3,3,3,3,2,3,2,4,2.0,neutral or dissatisfied +57168,116054,Male,Loyal Customer,64,Personal Travel,Eco,446,3,4,3,4,4,3,4,4,3,4,4,4,4,4,11,7.0,neutral or dissatisfied +57169,57772,Male,disloyal Customer,34,Business travel,Business,2704,3,3,3,3,3,5,5,3,1,4,3,5,1,5,4,9.0,neutral or dissatisfied +57170,115012,Female,Loyal Customer,41,Business travel,Business,3234,4,4,4,4,5,5,5,5,5,5,5,3,5,3,94,92.0,satisfied +57171,44682,Male,Loyal Customer,31,Business travel,Business,3758,1,4,4,4,1,2,1,1,3,5,4,1,3,1,68,56.0,neutral or dissatisfied +57172,74468,Female,Loyal Customer,56,Business travel,Business,1205,4,4,4,4,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +57173,13689,Female,Loyal Customer,43,Business travel,Business,483,2,5,2,2,1,1,1,3,3,4,3,2,3,4,40,59.0,satisfied +57174,57846,Male,Loyal Customer,28,Business travel,Business,1491,3,3,3,3,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +57175,90903,Female,Loyal Customer,41,Business travel,Business,581,2,2,2,2,1,3,3,2,2,1,2,1,2,1,0,0.0,neutral or dissatisfied +57176,91668,Male,Loyal Customer,11,Personal Travel,Eco Plus,1352,3,5,3,3,4,3,4,4,4,3,3,4,5,4,0,0.0,neutral or dissatisfied +57177,41122,Male,Loyal Customer,56,Business travel,Business,667,4,1,1,1,1,4,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +57178,69496,Female,Loyal Customer,58,Personal Travel,Eco Plus,1089,4,2,4,3,3,4,4,5,5,4,5,1,5,4,21,0.0,neutral or dissatisfied +57179,122435,Male,Loyal Customer,7,Personal Travel,Eco,1916,4,5,4,3,3,4,3,3,3,2,4,4,4,3,0,2.0,neutral or dissatisfied +57180,51536,Female,Loyal Customer,23,Business travel,Eco,751,5,2,2,2,5,5,3,5,5,1,1,2,3,5,0,3.0,satisfied +57181,50366,Female,Loyal Customer,53,Business travel,Business,2275,4,4,4,4,2,3,1,5,5,5,5,2,5,1,0,0.0,satisfied +57182,93689,Female,Loyal Customer,44,Business travel,Business,1452,2,2,2,2,3,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +57183,37765,Female,Loyal Customer,22,Business travel,Eco Plus,989,4,3,4,3,4,4,3,4,5,4,2,3,1,4,0,0.0,satisfied +57184,86579,Female,Loyal Customer,36,Business travel,Business,1269,3,3,3,3,5,4,4,3,3,3,3,2,3,3,57,43.0,neutral or dissatisfied +57185,93646,Male,Loyal Customer,58,Business travel,Business,3528,4,4,2,4,3,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +57186,53758,Female,disloyal Customer,21,Business travel,Business,1195,0,0,0,4,1,0,1,1,3,5,2,5,1,1,0,0.0,satisfied +57187,4907,Male,Loyal Customer,56,Business travel,Business,1838,2,2,4,2,2,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +57188,19614,Female,disloyal Customer,38,Business travel,Eco,416,2,2,2,4,5,2,2,5,1,2,3,3,4,5,46,41.0,neutral or dissatisfied +57189,66440,Male,Loyal Customer,56,Business travel,Business,1845,4,4,4,4,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +57190,23710,Male,Loyal Customer,19,Personal Travel,Eco,196,4,5,4,3,1,4,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +57191,48934,Male,Loyal Customer,37,Business travel,Eco,156,5,1,1,1,5,5,5,5,5,3,2,1,2,5,0,0.0,satisfied +57192,31286,Male,Loyal Customer,62,Personal Travel,Eco,665,3,2,3,3,5,3,5,5,3,5,4,2,4,5,0,2.0,neutral or dissatisfied +57193,41403,Female,disloyal Customer,26,Business travel,Eco,563,4,0,4,5,4,4,4,4,1,5,4,3,5,4,0,0.0,satisfied +57194,126022,Male,disloyal Customer,22,Business travel,Business,631,5,2,5,1,2,5,2,2,5,5,4,5,5,2,0,0.0,satisfied +57195,76869,Male,Loyal Customer,59,Business travel,Business,1927,3,2,2,2,4,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +57196,110664,Female,disloyal Customer,30,Business travel,Eco,837,1,1,1,3,5,1,2,5,2,1,4,4,3,5,0,0.0,neutral or dissatisfied +57197,63329,Female,Loyal Customer,24,Business travel,Business,2337,3,3,3,3,3,4,3,3,1,5,2,5,5,3,8,3.0,satisfied +57198,92050,Female,Loyal Customer,45,Business travel,Business,1589,5,5,5,5,2,3,5,3,3,4,3,5,3,3,0,0.0,satisfied +57199,127877,Female,Loyal Customer,58,Personal Travel,Eco,1276,4,5,4,4,4,4,4,3,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +57200,4665,Female,Loyal Customer,55,Business travel,Business,2879,3,5,5,5,3,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +57201,76468,Female,Loyal Customer,49,Business travel,Business,534,1,1,1,1,5,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +57202,129654,Female,Loyal Customer,45,Business travel,Business,2498,0,0,0,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +57203,92228,Male,Loyal Customer,13,Personal Travel,Eco,1979,2,3,1,4,2,1,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +57204,34523,Female,Loyal Customer,42,Personal Travel,Eco,1521,1,4,1,1,2,5,5,1,1,1,1,5,1,3,1,0.0,neutral or dissatisfied +57205,25515,Male,disloyal Customer,56,Business travel,Eco,481,2,3,2,3,5,2,1,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +57206,110186,Female,Loyal Customer,17,Personal Travel,Eco,882,1,4,1,4,1,1,1,1,2,2,3,4,4,1,66,62.0,neutral or dissatisfied +57207,123905,Male,Loyal Customer,61,Personal Travel,Eco,544,2,1,2,4,4,2,4,4,3,3,4,2,3,4,0,0.0,neutral or dissatisfied +57208,31566,Male,Loyal Customer,33,Business travel,Eco Plus,853,1,5,5,5,1,1,1,1,4,4,3,3,3,1,92,94.0,neutral or dissatisfied +57209,128000,Female,disloyal Customer,27,Business travel,Eco,1465,1,1,1,1,5,1,5,5,3,4,3,4,5,5,21,31.0,neutral or dissatisfied +57210,118211,Female,disloyal Customer,54,Business travel,Business,1440,4,4,4,3,2,4,2,2,3,5,5,5,5,2,5,0.0,satisfied +57211,101518,Female,Loyal Customer,39,Personal Travel,Eco,345,2,4,2,1,5,2,5,5,4,4,1,3,1,5,9,4.0,neutral or dissatisfied +57212,54601,Female,disloyal Customer,42,Business travel,Business,854,2,3,3,4,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +57213,124015,Male,Loyal Customer,36,Business travel,Business,184,0,4,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +57214,6747,Female,Loyal Customer,53,Personal Travel,Business,223,1,3,1,1,1,2,2,5,5,1,5,2,5,1,1,42.0,neutral or dissatisfied +57215,106184,Male,disloyal Customer,65,Personal Travel,Eco,436,3,4,3,4,4,3,4,4,5,2,4,3,5,4,46,33.0,neutral or dissatisfied +57216,37907,Female,Loyal Customer,32,Business travel,Business,1068,1,1,1,1,4,4,4,4,5,2,5,3,3,4,8,0.0,satisfied +57217,22307,Female,disloyal Customer,29,Business travel,Eco,208,4,0,4,2,5,4,1,5,2,4,5,5,5,5,0,1.0,satisfied +57218,104746,Male,Loyal Customer,36,Business travel,Business,942,4,4,4,4,2,2,4,5,5,4,5,4,5,1,16,0.0,satisfied +57219,127543,Female,disloyal Customer,25,Business travel,Eco,1009,1,2,2,4,2,2,5,2,4,2,4,3,3,2,0,13.0,neutral or dissatisfied +57220,125999,Male,Loyal Customer,52,Personal Travel,Business,600,3,0,3,3,4,5,3,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +57221,92764,Male,Loyal Customer,51,Personal Travel,Eco Plus,1276,4,5,3,1,5,3,5,5,5,3,4,5,4,5,0,0.0,satisfied +57222,45899,Female,Loyal Customer,22,Business travel,Eco,913,3,3,4,3,3,3,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +57223,12152,Male,disloyal Customer,10,Business travel,Eco,1075,5,5,5,4,4,5,4,4,1,5,2,3,4,4,0,0.0,satisfied +57224,107085,Male,Loyal Customer,50,Personal Travel,Eco Plus,395,0,4,0,3,1,0,1,1,4,4,4,3,4,1,0,0.0,satisfied +57225,27368,Male,Loyal Customer,42,Business travel,Business,2672,5,5,5,5,3,3,4,2,2,2,2,1,2,1,0,3.0,satisfied +57226,117924,Female,disloyal Customer,27,Business travel,Eco,365,3,2,3,4,4,3,4,4,3,3,4,1,3,4,3,0.0,neutral or dissatisfied +57227,67599,Male,Loyal Customer,60,Business travel,Business,3416,5,5,5,5,4,4,5,5,5,5,5,4,5,3,14,0.0,satisfied +57228,58235,Female,Loyal Customer,20,Personal Travel,Eco,925,1,2,1,4,3,1,4,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +57229,60513,Male,Loyal Customer,22,Personal Travel,Eco,862,3,1,3,4,4,3,1,4,2,3,3,1,3,4,27,0.0,neutral or dissatisfied +57230,62336,Female,Loyal Customer,7,Personal Travel,Eco,236,2,5,2,3,3,2,3,3,1,1,3,4,2,3,0,0.0,neutral or dissatisfied +57231,55983,Female,Loyal Customer,60,Business travel,Business,1620,3,3,3,3,2,5,5,4,4,4,4,3,4,5,22,12.0,satisfied +57232,21410,Male,Loyal Customer,46,Business travel,Business,331,4,4,4,4,4,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +57233,108639,Female,Loyal Customer,36,Business travel,Business,1823,3,3,3,3,2,4,5,4,4,4,4,4,4,4,56,49.0,satisfied +57234,6240,Female,disloyal Customer,18,Business travel,Eco,594,3,2,3,3,3,3,5,3,4,3,3,1,4,3,7,21.0,neutral or dissatisfied +57235,28720,Female,Loyal Customer,54,Personal Travel,Eco,2717,1,4,1,1,1,3,3,5,5,4,5,3,4,3,0,12.0,neutral or dissatisfied +57236,83004,Male,Loyal Customer,56,Business travel,Business,1145,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,15.0,satisfied +57237,102654,Male,disloyal Customer,23,Business travel,Eco,365,1,0,1,2,2,1,2,2,4,3,5,3,4,2,22,20.0,neutral or dissatisfied +57238,54747,Female,Loyal Customer,62,Personal Travel,Eco,956,3,5,3,3,2,5,5,5,5,3,5,4,5,5,41,42.0,neutral or dissatisfied +57239,39795,Male,Loyal Customer,33,Personal Travel,Business,272,3,0,3,5,5,3,2,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +57240,75028,Female,Loyal Customer,47,Business travel,Eco,236,4,5,5,5,2,3,1,4,4,4,4,3,4,4,0,0.0,satisfied +57241,18200,Male,Loyal Customer,18,Business travel,Business,228,3,3,3,3,5,5,5,5,5,2,2,2,5,5,0,0.0,satisfied +57242,89479,Female,Loyal Customer,14,Personal Travel,Business,1931,5,5,5,2,4,5,1,4,5,3,5,4,5,4,1,0.0,satisfied +57243,59727,Female,Loyal Customer,45,Personal Travel,Eco Plus,854,2,5,2,2,2,4,4,2,2,2,2,5,2,5,13,7.0,neutral or dissatisfied +57244,96544,Male,Loyal Customer,51,Personal Travel,Eco,436,3,5,3,3,5,3,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +57245,121475,Male,Loyal Customer,32,Personal Travel,Eco,331,2,5,2,5,3,2,3,3,4,2,1,4,3,3,0,0.0,neutral or dissatisfied +57246,40770,Male,Loyal Customer,54,Business travel,Business,2600,5,5,5,5,1,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +57247,52570,Male,Loyal Customer,31,Business travel,Business,3324,2,2,2,2,4,4,4,4,4,2,5,4,1,4,0,0.0,satisfied +57248,52377,Female,Loyal Customer,23,Personal Travel,Eco,237,4,4,4,3,4,4,2,4,4,5,5,4,4,4,0,13.0,neutral or dissatisfied +57249,100236,Female,Loyal Customer,52,Personal Travel,Business,1092,1,1,0,3,1,3,4,5,5,0,5,3,5,3,96,127.0,neutral or dissatisfied +57250,64292,Male,Loyal Customer,42,Business travel,Business,3222,5,5,5,5,5,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +57251,84298,Male,Loyal Customer,58,Business travel,Business,2563,5,5,5,5,2,4,5,4,4,4,4,3,4,5,57,36.0,satisfied +57252,44675,Female,Loyal Customer,36,Business travel,Eco,173,2,3,4,4,2,2,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +57253,1357,Female,disloyal Customer,32,Business travel,Business,312,2,2,2,2,5,2,5,5,3,3,4,4,4,5,11,20.0,neutral or dissatisfied +57254,65750,Male,Loyal Customer,50,Personal Travel,Eco,1061,2,5,3,3,4,3,4,4,4,2,5,4,5,4,5,0.0,neutral or dissatisfied +57255,52741,Female,Loyal Customer,49,Business travel,Business,2306,2,2,2,2,1,3,1,3,3,4,3,3,3,1,8,0.0,satisfied +57256,43761,Female,Loyal Customer,46,Business travel,Business,2861,2,4,4,4,3,2,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +57257,107857,Female,Loyal Customer,49,Business travel,Business,3320,2,2,2,2,2,5,5,5,5,5,5,3,5,5,53,56.0,satisfied +57258,32571,Female,Loyal Customer,65,Business travel,Business,163,2,2,2,2,5,3,4,4,4,4,5,4,4,1,0,0.0,satisfied +57259,45153,Female,disloyal Customer,26,Business travel,Eco,130,2,3,2,5,3,2,2,3,3,4,5,4,3,3,85,91.0,neutral or dissatisfied +57260,41245,Male,Loyal Customer,22,Business travel,Eco,643,4,4,4,4,4,4,4,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +57261,2952,Male,Loyal Customer,67,Business travel,Business,1624,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,7.0,satisfied +57262,51161,Male,Loyal Customer,46,Personal Travel,Eco,109,3,3,0,3,1,0,1,1,2,5,4,3,3,1,43,37.0,neutral or dissatisfied +57263,13799,Female,Loyal Customer,24,Personal Travel,Eco,450,2,2,2,2,2,2,2,2,2,5,3,1,2,2,0,5.0,neutral or dissatisfied +57264,69622,Female,Loyal Customer,59,Personal Travel,Eco Plus,2475,5,4,5,3,4,4,4,3,4,4,4,4,2,4,0,0.0,satisfied +57265,90512,Male,Loyal Customer,52,Business travel,Business,404,3,3,3,3,3,5,5,5,5,5,5,4,5,4,129,107.0,satisfied +57266,41254,Female,Loyal Customer,37,Business travel,Business,2908,5,5,5,5,4,2,2,3,3,3,3,3,3,5,0,13.0,satisfied +57267,2840,Female,Loyal Customer,28,Business travel,Business,409,4,4,5,4,4,4,4,1,2,3,4,4,3,4,227,208.0,neutral or dissatisfied +57268,129175,Female,Loyal Customer,16,Personal Travel,Eco,679,4,4,4,2,4,4,1,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +57269,96721,Female,Loyal Customer,26,Personal Travel,Eco,813,4,4,4,4,1,4,1,1,4,5,3,2,4,1,4,0.0,satisfied +57270,18006,Female,disloyal Customer,20,Business travel,Eco,618,2,1,2,3,3,2,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +57271,3979,Female,Loyal Customer,24,Business travel,Eco,340,3,3,4,3,3,3,4,3,3,1,4,3,3,3,0,10.0,neutral or dissatisfied +57272,45483,Female,Loyal Customer,8,Business travel,Business,1738,2,1,2,2,2,2,2,2,3,5,3,4,4,2,4,3.0,neutral or dissatisfied +57273,27428,Female,Loyal Customer,43,Business travel,Business,3749,1,1,1,1,2,4,2,3,3,3,3,5,3,2,1,0.0,satisfied +57274,115114,Female,Loyal Customer,42,Business travel,Business,1812,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +57275,121191,Female,Loyal Customer,64,Personal Travel,Eco,2370,3,5,3,4,2,4,4,2,2,3,1,3,2,4,0,0.0,neutral or dissatisfied +57276,118322,Female,disloyal Customer,26,Business travel,Business,602,1,1,1,2,1,1,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +57277,75232,Female,Loyal Customer,9,Personal Travel,Eco,1726,2,5,2,1,3,2,3,3,4,2,5,2,2,3,0,0.0,neutral or dissatisfied +57278,125690,Female,disloyal Customer,38,Business travel,Eco,492,2,1,2,4,5,2,5,5,1,3,3,3,4,5,14,8.0,neutral or dissatisfied +57279,110626,Female,Loyal Customer,38,Personal Travel,Eco,727,1,3,2,3,4,2,4,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +57280,79328,Male,Loyal Customer,28,Business travel,Business,1020,4,4,4,4,5,5,5,5,5,5,4,3,4,5,0,14.0,satisfied +57281,84212,Male,disloyal Customer,22,Business travel,Eco,432,2,5,2,2,2,2,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +57282,123841,Male,Loyal Customer,58,Business travel,Business,3534,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +57283,83962,Female,Loyal Customer,53,Business travel,Business,373,1,1,2,2,5,2,2,1,1,1,1,1,1,3,58,63.0,neutral or dissatisfied +57284,8318,Female,Loyal Customer,8,Personal Travel,Eco Plus,125,2,1,2,3,4,2,1,4,2,1,3,4,4,4,0,0.0,neutral or dissatisfied +57285,11373,Female,Loyal Customer,8,Personal Travel,Eco,224,3,3,3,3,3,3,4,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +57286,112212,Female,Loyal Customer,29,Business travel,Business,1537,4,4,5,4,4,4,4,4,5,2,4,5,4,4,15,0.0,satisfied +57287,39402,Female,Loyal Customer,22,Business travel,Business,521,3,3,3,3,4,4,4,4,4,4,2,5,1,4,0,7.0,satisfied +57288,125364,Female,Loyal Customer,11,Personal Travel,Eco,599,2,1,2,4,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +57289,129153,Female,disloyal Customer,20,Business travel,Eco,679,1,1,1,3,1,1,1,1,2,5,2,4,2,1,0,0.0,neutral or dissatisfied +57290,34248,Female,Loyal Customer,35,Business travel,Business,1666,1,1,1,1,1,5,4,4,4,4,4,2,4,1,14,0.0,satisfied +57291,49668,Male,disloyal Customer,21,Business travel,Eco,337,2,5,2,2,5,2,4,5,3,4,3,1,4,5,0,0.0,neutral or dissatisfied +57292,65676,Male,Loyal Customer,20,Personal Travel,Eco,926,1,5,0,3,3,0,3,3,1,3,3,3,3,3,0,7.0,neutral or dissatisfied +57293,15411,Male,Loyal Customer,42,Business travel,Business,3816,2,2,2,2,2,4,4,5,5,5,5,2,5,3,0,0.0,satisfied +57294,49515,Male,Loyal Customer,37,Business travel,Business,2887,2,4,4,4,1,3,3,3,3,3,2,1,3,3,36,22.0,neutral or dissatisfied +57295,89971,Male,Loyal Customer,51,Personal Travel,Eco,1416,4,1,4,2,5,4,4,5,4,4,2,2,1,5,23,10.0,neutral or dissatisfied +57296,112272,Male,disloyal Customer,16,Business travel,Eco,1138,2,2,2,4,2,2,2,2,4,3,4,3,4,2,100,94.0,neutral or dissatisfied +57297,13065,Female,Loyal Customer,43,Business travel,Eco,936,2,1,1,1,5,4,2,2,2,2,2,2,2,2,9,14.0,satisfied +57298,98007,Male,Loyal Customer,66,Personal Travel,Eco Plus,722,2,2,2,3,4,2,5,4,3,1,4,3,3,4,1,0.0,neutral or dissatisfied +57299,81436,Female,Loyal Customer,39,Personal Travel,Eco,393,3,4,3,5,2,3,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +57300,75210,Male,Loyal Customer,32,Business travel,Business,1723,2,3,3,3,2,2,2,2,4,3,2,1,3,2,13,1.0,neutral or dissatisfied +57301,9442,Female,Loyal Customer,49,Business travel,Business,3487,0,0,0,3,3,5,4,3,3,3,3,5,3,5,15,3.0,satisfied +57302,97487,Female,Loyal Customer,43,Business travel,Eco,670,2,5,5,5,5,4,3,2,2,2,2,2,2,4,2,4.0,neutral or dissatisfied +57303,49731,Female,Loyal Customer,33,Business travel,Business,2476,1,1,1,1,3,4,4,1,1,1,1,2,1,1,18,19.0,neutral or dissatisfied +57304,74155,Male,Loyal Customer,24,Personal Travel,Eco,721,0,1,0,3,3,0,2,3,2,2,3,4,3,3,0,0.0,satisfied +57305,22968,Female,Loyal Customer,25,Business travel,Eco,817,4,1,1,1,4,4,3,4,1,1,2,2,5,4,0,0.0,satisfied +57306,54767,Female,Loyal Customer,60,Business travel,Eco Plus,956,2,2,2,2,3,4,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +57307,65348,Male,Loyal Customer,51,Business travel,Business,3182,3,3,3,3,2,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +57308,13276,Male,Loyal Customer,32,Personal Travel,Eco,468,3,5,3,1,5,3,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +57309,111488,Male,disloyal Customer,42,Business travel,Business,391,2,2,2,3,4,2,3,4,3,3,2,4,3,4,48,40.0,neutral or dissatisfied +57310,82994,Male,Loyal Customer,54,Business travel,Business,2371,2,2,4,2,3,4,4,4,4,4,4,4,4,4,7,28.0,satisfied +57311,112659,Female,Loyal Customer,9,Personal Travel,Business,697,2,2,3,3,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +57312,33935,Male,disloyal Customer,49,Business travel,Business,1072,4,4,4,2,4,4,4,4,5,4,2,1,3,4,11,4.0,satisfied +57313,64521,Female,Loyal Customer,28,Personal Travel,Business,190,2,2,2,3,3,2,5,3,3,2,3,4,3,3,6,11.0,neutral or dissatisfied +57314,47657,Female,Loyal Customer,37,Business travel,Business,1428,3,3,3,3,4,3,2,5,5,5,5,5,5,2,0,0.0,satisfied +57315,76204,Female,Loyal Customer,70,Personal Travel,Eco,2422,2,1,2,2,2,2,2,1,1,2,1,2,1,1,92,81.0,neutral or dissatisfied +57316,87840,Male,Loyal Customer,8,Personal Travel,Eco,214,2,4,2,4,5,2,5,5,4,3,3,1,1,5,0,7.0,neutral or dissatisfied +57317,80844,Male,Loyal Customer,58,Business travel,Eco,484,3,5,2,5,3,3,3,3,1,3,4,1,3,3,11,26.0,neutral or dissatisfied +57318,34238,Male,Loyal Customer,24,Business travel,Eco Plus,1189,4,5,5,5,4,4,5,4,5,2,4,1,5,4,0,0.0,satisfied +57319,8931,Male,Loyal Customer,9,Personal Travel,Eco,984,1,3,0,2,5,0,5,5,3,4,3,4,2,5,26,26.0,neutral or dissatisfied +57320,54470,Male,disloyal Customer,29,Business travel,Eco,925,5,5,5,4,3,5,3,3,1,2,2,3,3,3,0,0.0,satisfied +57321,99466,Male,Loyal Customer,34,Business travel,Business,3224,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +57322,42920,Female,disloyal Customer,27,Business travel,Eco,628,2,4,2,4,1,2,1,1,4,3,4,1,3,1,8,5.0,neutral or dissatisfied +57323,12387,Female,Loyal Customer,33,Business travel,Business,2456,5,5,5,5,1,5,2,4,4,4,4,2,4,3,0,0.0,satisfied +57324,59178,Female,disloyal Customer,29,Business travel,Business,1846,3,3,3,1,3,3,4,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +57325,57538,Female,Loyal Customer,47,Personal Travel,Eco,413,4,5,3,5,3,4,4,2,2,3,1,4,2,5,9,0.0,satisfied +57326,113333,Female,Loyal Customer,52,Business travel,Business,3897,1,1,1,1,3,4,5,5,5,5,5,3,5,4,33,37.0,satisfied +57327,8895,Female,Loyal Customer,51,Business travel,Eco Plus,622,2,1,5,1,4,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +57328,42730,Female,Loyal Customer,29,Business travel,Business,2838,2,2,2,2,5,5,5,5,2,2,5,5,4,5,4,0.0,satisfied +57329,104248,Male,Loyal Customer,55,Business travel,Business,1996,5,4,2,4,4,4,3,5,5,4,5,1,5,1,14,16.0,neutral or dissatisfied +57330,4064,Male,Loyal Customer,32,Personal Travel,Eco,419,4,5,4,4,5,4,5,5,2,1,1,1,4,5,0,0.0,satisfied +57331,20132,Male,Loyal Customer,35,Personal Travel,Eco,466,2,4,2,2,4,2,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +57332,71209,Male,Loyal Customer,30,Business travel,Business,3835,1,2,2,2,1,1,1,1,2,1,3,4,4,1,5,0.0,neutral or dissatisfied +57333,80259,Male,Loyal Customer,49,Business travel,Eco,469,5,4,4,4,5,5,5,5,2,4,1,1,3,5,0,0.0,satisfied +57334,3465,Male,Loyal Customer,36,Personal Travel,Eco Plus,240,1,4,0,2,5,0,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +57335,70307,Female,Loyal Customer,41,Business travel,Business,3842,4,2,2,2,3,3,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +57336,124075,Male,Loyal Customer,43,Business travel,Business,328,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +57337,78096,Female,disloyal Customer,36,Business travel,Business,655,4,4,4,1,1,4,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +57338,60432,Female,Loyal Customer,18,Business travel,Business,641,5,5,5,5,4,4,4,4,4,2,5,5,5,4,0,6.0,satisfied +57339,60289,Male,Loyal Customer,24,Business travel,Business,1954,1,1,1,1,4,4,4,4,4,4,5,5,5,4,58,54.0,satisfied +57340,3368,Male,Loyal Customer,37,Business travel,Business,2637,2,2,2,2,2,5,5,4,4,4,4,4,4,4,0,4.0,satisfied +57341,103790,Female,Loyal Customer,56,Business travel,Business,882,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +57342,39207,Male,Loyal Customer,35,Business travel,Business,2258,5,5,4,5,2,5,4,4,4,4,5,5,4,4,0,113.0,satisfied +57343,82905,Female,Loyal Customer,45,Personal Travel,Eco,640,4,5,4,3,2,4,4,1,1,4,1,4,1,4,9,8.0,neutral or dissatisfied +57344,64745,Male,Loyal Customer,40,Business travel,Eco,224,1,2,5,5,1,1,1,1,2,2,4,4,4,1,0,7.0,neutral or dissatisfied +57345,49154,Female,disloyal Customer,37,Business travel,Eco,134,2,5,2,5,1,2,2,1,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +57346,35729,Female,Loyal Customer,7,Personal Travel,Eco Plus,2586,3,2,3,3,3,4,4,1,2,3,3,4,4,4,0,0.0,neutral or dissatisfied +57347,93341,Female,Loyal Customer,22,Business travel,Business,2967,2,3,3,3,2,2,2,2,1,2,3,2,4,2,0,12.0,neutral or dissatisfied +57348,98145,Female,Loyal Customer,42,Business travel,Business,562,5,5,5,5,3,5,4,4,4,4,4,5,4,3,3,0.0,satisfied +57349,80279,Male,Loyal Customer,32,Business travel,Business,2685,4,4,4,4,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +57350,54286,Female,disloyal Customer,14,Business travel,Eco,1075,4,4,4,2,1,4,1,1,3,2,5,4,1,1,6,1.0,neutral or dissatisfied +57351,52201,Female,disloyal Customer,46,Business travel,Eco,370,2,0,2,3,5,2,4,5,1,5,5,2,4,5,0,0.0,neutral or dissatisfied +57352,55998,Female,Loyal Customer,42,Business travel,Business,2475,1,1,1,1,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +57353,91307,Female,Loyal Customer,24,Business travel,Eco Plus,404,1,4,4,4,1,1,4,1,4,1,4,2,3,1,1,0.0,neutral or dissatisfied +57354,39731,Female,Loyal Customer,33,Personal Travel,Eco,320,3,3,3,3,4,3,4,4,2,1,4,5,2,4,0,0.0,neutral or dissatisfied +57355,47312,Female,Loyal Customer,30,Business travel,Eco,541,4,1,5,1,4,4,4,4,4,3,3,3,4,4,0,0.0,satisfied +57356,24405,Female,Loyal Customer,29,Business travel,Business,2714,2,2,1,2,4,4,4,4,1,1,3,4,5,4,0,0.0,satisfied +57357,73061,Male,Loyal Customer,24,Personal Travel,Eco Plus,1035,3,4,3,3,5,3,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +57358,25937,Female,Loyal Customer,55,Personal Travel,Eco,594,3,3,3,5,2,4,1,4,4,3,4,4,4,5,8,10.0,neutral or dissatisfied +57359,77590,Male,disloyal Customer,25,Business travel,Business,813,5,5,5,1,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +57360,343,Female,Loyal Customer,58,Personal Travel,Eco,821,3,4,3,4,2,4,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +57361,54292,Male,Loyal Customer,64,Business travel,Business,3345,2,1,1,1,3,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +57362,48232,Female,Loyal Customer,12,Personal Travel,Eco,391,4,4,4,2,3,4,4,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +57363,10925,Male,Loyal Customer,30,Business travel,Business,2175,1,1,1,1,5,4,5,5,5,2,5,5,5,5,0,0.0,satisfied +57364,122934,Female,Loyal Customer,25,Business travel,Business,650,4,4,4,4,4,5,4,4,4,5,5,5,4,4,0,16.0,satisfied +57365,46944,Male,Loyal Customer,23,Personal Travel,Eco,666,2,5,2,1,3,2,1,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +57366,16947,Male,Loyal Customer,47,Personal Travel,Eco,820,2,4,2,3,5,2,5,5,1,5,3,2,4,5,0,0.0,neutral or dissatisfied +57367,100567,Male,Loyal Customer,23,Business travel,Business,486,4,4,4,4,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +57368,38916,Female,Loyal Customer,65,Business travel,Eco,320,1,1,1,1,3,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +57369,41912,Male,Loyal Customer,50,Business travel,Eco,129,5,5,5,5,5,5,5,5,1,5,5,2,1,5,0,0.0,satisfied +57370,41860,Female,Loyal Customer,42,Business travel,Eco,300,3,5,5,5,3,3,3,3,3,3,3,4,3,1,41,52.0,neutral or dissatisfied +57371,127357,Male,Loyal Customer,58,Personal Travel,Eco,507,3,5,3,2,1,3,2,1,4,5,5,3,4,1,6,0.0,neutral or dissatisfied +57372,119818,Male,Loyal Customer,32,Business travel,Eco,912,4,1,2,2,4,4,4,4,1,1,3,1,3,4,3,0.0,neutral or dissatisfied +57373,44887,Male,Loyal Customer,17,Personal Travel,Eco,557,1,5,1,3,3,1,3,3,5,2,1,4,4,3,127,115.0,neutral or dissatisfied +57374,57473,Female,disloyal Customer,25,Business travel,Eco,680,1,1,1,3,3,1,1,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +57375,22544,Female,Loyal Customer,48,Business travel,Eco Plus,145,5,3,5,5,1,5,4,5,5,5,5,1,5,1,0,0.0,satisfied +57376,71937,Male,Loyal Customer,53,Personal Travel,Eco Plus,1744,1,4,1,4,2,1,3,2,1,1,2,4,3,2,2,0.0,neutral or dissatisfied +57377,91459,Male,Loyal Customer,60,Business travel,Eco,859,3,4,4,4,4,3,4,4,4,4,3,3,2,4,16,44.0,neutral or dissatisfied +57378,85627,Female,Loyal Customer,31,Personal Travel,Eco,259,3,3,3,2,1,3,1,1,1,3,4,2,2,1,3,4.0,neutral or dissatisfied +57379,63903,Male,disloyal Customer,25,Business travel,Eco,758,4,4,4,4,5,4,2,5,5,5,2,5,5,5,0,57.0,neutral or dissatisfied +57380,69430,Female,Loyal Customer,43,Business travel,Business,3228,5,3,5,5,1,5,1,4,4,4,4,3,4,3,21,0.0,satisfied +57381,93125,Female,Loyal Customer,39,Business travel,Business,1066,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +57382,45794,Female,Loyal Customer,36,Business travel,Business,2503,3,1,1,1,2,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +57383,60911,Female,Loyal Customer,26,Personal Travel,Eco,589,2,4,2,4,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +57384,4400,Female,Loyal Customer,35,Personal Travel,Eco,618,4,3,5,2,4,5,4,4,3,5,5,1,1,4,0,11.0,neutral or dissatisfied +57385,97207,Female,Loyal Customer,32,Business travel,Business,1313,3,2,3,3,5,5,5,5,3,5,5,3,4,5,0,5.0,satisfied +57386,30281,Female,Loyal Customer,59,Personal Travel,Eco,1024,1,4,1,5,5,5,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +57387,36946,Female,Loyal Customer,36,Personal Travel,Eco,718,4,4,4,4,2,4,5,2,2,5,3,4,3,2,3,11.0,neutral or dissatisfied +57388,17017,Female,Loyal Customer,47,Business travel,Business,781,2,5,5,5,2,2,2,4,2,3,3,2,1,2,146,133.0,neutral or dissatisfied +57389,75216,Male,Loyal Customer,62,Business travel,Eco,223,2,3,3,3,2,2,2,2,2,2,4,1,3,2,16,7.0,neutral or dissatisfied +57390,110014,Female,Loyal Customer,51,Business travel,Business,3731,2,4,4,4,2,3,3,2,2,2,2,3,2,3,29,35.0,neutral or dissatisfied +57391,69621,Female,Loyal Customer,31,Personal Travel,Eco Plus,2475,1,5,1,3,1,3,3,3,4,5,5,3,3,3,0,1.0,neutral or dissatisfied +57392,93448,Female,Loyal Customer,8,Personal Travel,Eco,697,1,5,1,2,2,1,2,2,1,2,3,5,5,2,0,0.0,neutral or dissatisfied +57393,129622,Female,Loyal Customer,47,Business travel,Business,2134,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,25.0,satisfied +57394,3364,Female,Loyal Customer,48,Business travel,Business,3544,2,3,3,3,1,2,3,2,2,2,2,1,2,4,0,11.0,neutral or dissatisfied +57395,114108,Female,Loyal Customer,57,Business travel,Business,846,1,1,1,1,2,5,4,5,5,5,5,3,5,5,24,34.0,satisfied +57396,108812,Female,Loyal Customer,49,Business travel,Business,1503,4,4,4,4,4,5,5,5,5,5,5,3,5,3,16,21.0,satisfied +57397,89888,Male,disloyal Customer,39,Business travel,Business,1487,2,2,2,4,4,2,4,4,4,5,5,4,4,4,0,22.0,neutral or dissatisfied +57398,54431,Male,Loyal Customer,37,Personal Travel,Eco,305,0,4,0,1,5,0,5,5,4,2,4,3,2,5,0,0.0,satisfied +57399,116514,Female,Loyal Customer,64,Personal Travel,Eco,371,4,3,4,4,4,4,3,5,5,4,5,4,5,3,0,0.0,satisfied +57400,100106,Male,Loyal Customer,30,Business travel,Business,725,3,3,3,3,4,4,4,4,5,5,4,3,5,4,0,1.0,satisfied +57401,86477,Male,Loyal Customer,61,Business travel,Business,362,1,1,1,1,2,5,4,4,4,4,4,4,4,1,39,77.0,satisfied +57402,22822,Female,Loyal Customer,47,Business travel,Business,147,2,4,4,4,3,2,3,2,4,3,2,3,1,3,195,200.0,neutral or dissatisfied +57403,123306,Female,disloyal Customer,45,Business travel,Business,328,5,5,5,4,2,5,1,2,4,4,5,3,5,2,0,3.0,satisfied +57404,107573,Female,Loyal Customer,47,Personal Travel,Eco,1521,4,4,4,1,5,4,5,3,3,4,3,3,3,5,2,0.0,satisfied +57405,95160,Male,Loyal Customer,54,Personal Travel,Eco,248,4,5,4,5,2,4,2,2,4,3,4,5,5,2,6,0.0,neutral or dissatisfied +57406,8952,Female,Loyal Customer,12,Personal Travel,Eco,328,2,3,3,3,5,3,5,5,2,4,3,4,3,5,27,22.0,neutral or dissatisfied +57407,86576,Female,Loyal Customer,41,Business travel,Business,3163,2,1,4,1,3,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +57408,110334,Male,Loyal Customer,35,Business travel,Business,3810,3,3,3,3,3,5,4,5,5,5,5,4,5,4,17,8.0,satisfied +57409,120707,Female,Loyal Customer,40,Personal Travel,Eco,280,4,4,4,3,4,4,4,4,4,4,4,4,4,4,0,4.0,neutral or dissatisfied +57410,114398,Female,Loyal Customer,30,Business travel,Business,480,1,1,1,1,5,5,5,5,3,4,4,3,5,5,21,17.0,satisfied +57411,111017,Male,Loyal Customer,61,Business travel,Business,3639,1,1,1,1,4,5,5,5,5,4,5,3,5,3,0,7.0,satisfied +57412,318,Female,disloyal Customer,29,Business travel,Business,853,2,2,2,3,1,2,1,1,2,5,3,3,3,1,0,10.0,neutral or dissatisfied +57413,97834,Male,Loyal Customer,68,Personal Travel,Eco,395,2,5,2,2,4,2,3,4,5,5,4,5,5,4,17,20.0,neutral or dissatisfied +57414,120587,Female,disloyal Customer,11,Business travel,Business,980,4,0,4,5,5,4,5,5,3,2,5,4,4,5,0,0.0,satisfied +57415,103146,Female,Loyal Customer,24,Personal Travel,Eco Plus,460,2,5,2,1,2,2,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +57416,60709,Female,Loyal Customer,41,Business travel,Business,1605,3,4,4,4,4,4,4,3,3,3,3,3,3,2,47,25.0,neutral or dissatisfied +57417,61258,Male,Loyal Customer,24,Personal Travel,Eco,948,2,2,2,4,1,2,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +57418,22301,Male,disloyal Customer,48,Business travel,Eco,208,4,5,3,5,1,3,1,1,4,3,2,3,3,1,103,96.0,neutral or dissatisfied +57419,93614,Male,Loyal Customer,43,Business travel,Business,2480,5,5,4,5,3,4,5,2,2,3,2,4,2,5,1,0.0,satisfied +57420,90804,Female,Loyal Customer,50,Business travel,Business,3295,3,1,1,1,3,4,4,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +57421,36036,Male,Loyal Customer,53,Business travel,Eco,399,4,1,1,1,4,4,4,4,5,2,5,3,5,4,59,56.0,satisfied +57422,45252,Male,Loyal Customer,69,Personal Travel,Eco,552,1,1,1,2,4,1,4,4,3,5,3,3,2,4,0,0.0,neutral or dissatisfied +57423,6952,Female,Loyal Customer,34,Personal Travel,Eco,501,4,4,4,4,3,4,5,3,5,4,4,3,5,3,4,1.0,satisfied +57424,84953,Female,Loyal Customer,23,Business travel,Eco Plus,534,4,5,5,5,4,4,2,4,3,1,3,4,4,4,0,0.0,neutral or dissatisfied +57425,95734,Male,Loyal Customer,45,Business travel,Business,237,5,5,5,5,4,5,5,5,5,5,5,3,5,4,2,0.0,satisfied +57426,127783,Female,Loyal Customer,41,Business travel,Eco,637,4,2,2,2,4,4,4,4,3,4,4,5,2,4,0,0.0,satisfied +57427,78207,Female,Loyal Customer,57,Personal Travel,Eco,153,4,5,4,2,3,4,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +57428,39403,Female,disloyal Customer,22,Business travel,Eco,121,3,4,3,3,1,3,1,1,3,1,3,2,3,1,0,0.0,neutral or dissatisfied +57429,129835,Male,Loyal Customer,9,Personal Travel,Eco,447,2,4,2,3,3,2,3,3,3,3,4,3,4,3,3,5.0,neutral or dissatisfied +57430,125040,Male,disloyal Customer,28,Business travel,Eco,2300,2,3,3,4,2,2,2,1,1,2,3,2,2,2,0,0.0,neutral or dissatisfied +57431,16627,Male,Loyal Customer,45,Business travel,Eco Plus,1008,2,5,5,5,2,2,2,2,5,5,5,4,3,2,0,0.0,satisfied +57432,44401,Male,disloyal Customer,21,Business travel,Eco,342,3,0,2,4,1,2,1,1,2,5,1,1,4,1,0,0.0,neutral or dissatisfied +57433,103593,Female,Loyal Customer,37,Personal Travel,Eco,451,3,4,2,5,3,2,2,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +57434,116562,Male,Loyal Customer,7,Personal Travel,Eco,358,5,4,5,2,3,5,3,3,4,5,4,4,5,3,0,2.0,satisfied +57435,105045,Female,Loyal Customer,11,Personal Travel,Eco,255,3,3,0,4,1,0,1,1,5,2,4,5,5,1,2,0.0,neutral or dissatisfied +57436,87822,Female,Loyal Customer,45,Business travel,Business,1600,3,2,2,2,4,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +57437,76860,Female,disloyal Customer,22,Business travel,Eco,1262,1,1,1,4,2,1,5,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +57438,63228,Male,Loyal Customer,57,Business travel,Business,3666,0,0,0,3,5,4,4,3,3,3,3,4,3,5,6,0.0,satisfied +57439,27024,Female,Loyal Customer,28,Personal Travel,Eco,867,2,4,2,4,5,2,4,5,2,5,3,4,3,5,0,0.0,neutral or dissatisfied +57440,8355,Female,Loyal Customer,39,Business travel,Business,3254,5,5,5,5,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +57441,21807,Female,Loyal Customer,65,Personal Travel,Eco,241,3,4,3,3,2,4,5,4,4,3,4,5,4,4,0,2.0,neutral or dissatisfied +57442,89033,Male,Loyal Customer,30,Business travel,Business,1947,4,4,4,4,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +57443,109898,Female,disloyal Customer,39,Business travel,Eco,611,2,0,2,1,4,2,4,4,1,2,1,1,4,4,0,0.0,neutral or dissatisfied +57444,65512,Male,Loyal Customer,55,Business travel,Business,1616,5,5,5,5,4,4,4,4,4,4,4,5,4,4,43,48.0,satisfied +57445,41054,Male,Loyal Customer,50,Business travel,Eco Plus,989,5,4,5,4,5,5,5,5,4,1,1,1,4,5,0,0.0,satisfied +57446,62492,Male,Loyal Customer,28,Business travel,Business,1744,1,1,1,1,4,4,4,4,4,3,3,4,5,4,6,0.0,satisfied +57447,8845,Male,Loyal Customer,58,Business travel,Business,1371,5,5,5,5,2,5,5,4,4,4,4,4,4,4,9,31.0,satisfied +57448,122174,Male,Loyal Customer,23,Business travel,Business,2024,4,4,4,4,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +57449,120445,Male,Loyal Customer,17,Personal Travel,Eco,449,4,3,1,4,4,1,3,4,1,3,1,5,2,4,0,16.0,satisfied +57450,42055,Female,Loyal Customer,38,Personal Travel,Eco,116,3,1,0,4,1,0,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +57451,53182,Female,Loyal Customer,19,Business travel,Eco,589,5,2,2,2,5,5,5,5,1,1,4,4,2,5,103,92.0,satisfied +57452,50954,Female,Loyal Customer,44,Personal Travel,Eco,89,1,4,1,4,5,5,4,2,2,1,2,5,2,5,14,6.0,neutral or dissatisfied +57453,44937,Female,Loyal Customer,53,Business travel,Business,3019,3,3,3,3,1,1,3,5,5,5,5,2,5,1,12,50.0,satisfied +57454,80100,Female,Loyal Customer,34,Business travel,Business,1620,5,5,5,5,3,3,3,5,3,5,5,3,5,3,273,308.0,satisfied +57455,113163,Female,disloyal Customer,24,Business travel,Eco,628,2,4,3,4,5,3,5,5,2,2,4,1,3,5,20,13.0,neutral or dissatisfied +57456,44314,Male,Loyal Customer,33,Business travel,Eco Plus,305,0,0,0,2,3,0,1,3,4,3,2,4,5,3,0,0.0,satisfied +57457,58842,Female,Loyal Customer,21,Business travel,Eco Plus,1005,1,4,4,4,1,1,2,1,4,1,4,4,3,1,1,11.0,neutral or dissatisfied +57458,127694,Male,Loyal Customer,36,Business travel,Business,2133,4,4,4,4,4,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +57459,68836,Female,Loyal Customer,59,Personal Travel,Business,1061,2,4,2,1,5,4,4,3,3,2,3,5,3,3,0,7.0,neutral or dissatisfied +57460,123073,Female,Loyal Customer,25,Business travel,Eco,507,4,1,1,1,4,4,1,4,2,3,4,1,3,4,0,26.0,neutral or dissatisfied +57461,79488,Male,Loyal Customer,18,Personal Travel,Business,749,3,2,3,3,2,3,2,2,4,2,3,1,4,2,16,9.0,neutral or dissatisfied +57462,10489,Female,Loyal Customer,23,Business travel,Business,1931,3,3,3,3,4,4,4,4,4,3,4,5,4,4,30,23.0,satisfied +57463,93467,Male,disloyal Customer,30,Business travel,Business,723,4,4,4,3,1,4,1,1,3,4,5,4,5,1,6,1.0,satisfied +57464,93063,Female,Loyal Customer,41,Business travel,Business,297,2,3,3,3,3,2,3,2,2,2,2,4,2,1,0,21.0,neutral or dissatisfied +57465,14765,Female,Loyal Customer,64,Personal Travel,Eco,533,3,4,3,4,5,4,4,2,2,3,4,3,2,5,122,103.0,neutral or dissatisfied +57466,2803,Male,Loyal Customer,46,Personal Travel,Eco,764,2,3,2,3,1,2,1,1,5,1,3,2,3,1,0,0.0,neutral or dissatisfied +57467,125167,Male,Loyal Customer,64,Business travel,Eco,1089,1,3,3,3,1,1,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +57468,54369,Female,disloyal Customer,22,Business travel,Eco,1235,5,5,5,4,2,5,2,2,2,1,2,3,2,2,0,0.0,satisfied +57469,66045,Female,Loyal Customer,35,Business travel,Business,1055,1,1,1,1,3,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +57470,17659,Female,disloyal Customer,22,Business travel,Eco,1008,3,3,3,3,2,3,2,2,4,1,1,4,5,2,0,0.0,neutral or dissatisfied +57471,8329,Male,Loyal Customer,45,Business travel,Business,2141,3,3,3,3,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +57472,113020,Female,Loyal Customer,40,Business travel,Business,2279,1,3,3,3,3,3,3,1,1,1,1,2,1,2,0,1.0,neutral or dissatisfied +57473,14328,Female,Loyal Customer,27,Personal Travel,Eco,429,3,3,3,3,4,3,4,4,2,3,4,4,2,4,0,0.0,neutral or dissatisfied +57474,68663,Male,Loyal Customer,39,Business travel,Business,3176,1,1,1,1,3,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +57475,93141,Female,Loyal Customer,33,Business travel,Business,1544,2,4,4,4,4,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +57476,39937,Male,Loyal Customer,30,Business travel,Business,2009,4,4,4,4,4,4,4,4,4,2,1,3,1,4,0,0.0,satisfied +57477,68239,Male,Loyal Customer,39,Business travel,Eco,432,3,4,4,4,3,2,3,3,2,1,2,2,3,3,0,2.0,neutral or dissatisfied +57478,114706,Male,disloyal Customer,42,Business travel,Business,417,4,4,4,3,2,4,2,2,4,2,4,3,5,2,0,8.0,satisfied +57479,70397,Female,Loyal Customer,38,Business travel,Business,1162,3,5,5,5,1,3,4,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +57480,97196,Male,Loyal Customer,18,Personal Travel,Eco,1313,4,5,4,5,1,4,1,1,5,3,5,4,5,1,20,11.0,neutral or dissatisfied +57481,19845,Female,disloyal Customer,25,Business travel,Eco,693,3,3,3,3,1,3,2,1,4,2,5,2,3,1,19,15.0,neutral or dissatisfied +57482,112957,Male,Loyal Customer,11,Personal Travel,Eco,715,4,5,4,3,2,4,2,2,5,3,5,5,5,2,8,0.0,satisfied +57483,95970,Female,Loyal Customer,58,Business travel,Business,1090,2,2,3,2,3,4,5,4,4,4,4,3,4,4,0,2.0,satisfied +57484,8567,Female,disloyal Customer,61,Business travel,Business,308,4,4,4,3,3,4,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +57485,49742,Female,Loyal Customer,33,Business travel,Eco,262,0,0,0,3,3,0,3,3,2,2,1,3,5,3,0,0.0,satisfied +57486,100928,Female,Loyal Customer,30,Personal Travel,Eco,838,5,5,5,4,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +57487,27154,Female,Loyal Customer,45,Business travel,Business,2701,3,5,5,5,3,3,3,2,4,2,4,3,1,3,0,0.0,neutral or dissatisfied +57488,97902,Male,Loyal Customer,46,Business travel,Business,3237,4,4,4,4,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +57489,19256,Male,Loyal Customer,55,Business travel,Eco,802,4,2,2,2,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +57490,3493,Male,Loyal Customer,12,Personal Travel,Eco,1080,5,4,5,5,3,4,3,3,4,4,5,3,4,3,0,0.0,satisfied +57491,100396,Male,Loyal Customer,64,Personal Travel,Eco,1073,4,5,4,5,4,4,5,4,3,3,5,4,5,4,0,12.0,neutral or dissatisfied +57492,90026,Female,Loyal Customer,46,Business travel,Business,3472,2,2,2,2,3,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +57493,62304,Male,disloyal Customer,24,Business travel,Eco,414,1,3,1,2,2,1,2,2,2,4,3,1,3,2,19,18.0,neutral or dissatisfied +57494,86432,Female,disloyal Customer,39,Business travel,Business,712,3,3,3,4,1,3,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +57495,125516,Male,Loyal Customer,63,Personal Travel,Eco Plus,666,1,5,1,4,4,1,5,4,4,1,1,3,5,4,0,2.0,neutral or dissatisfied +57496,14830,Male,Loyal Customer,21,Personal Travel,Eco,314,2,4,2,1,2,2,2,2,3,5,4,3,5,2,1,23.0,neutral or dissatisfied +57497,82307,Female,Loyal Customer,10,Personal Travel,Eco,986,4,5,4,5,5,4,5,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +57498,14980,Male,Loyal Customer,59,Business travel,Eco,927,1,4,4,4,1,1,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +57499,6993,Female,disloyal Customer,38,Business travel,Eco,234,3,2,3,2,1,3,1,1,2,3,2,2,3,1,7,1.0,neutral or dissatisfied +57500,64090,Female,Loyal Customer,48,Personal Travel,Eco,919,1,3,1,3,5,4,3,3,3,1,3,2,3,2,11,2.0,neutral or dissatisfied +57501,97433,Female,Loyal Customer,49,Business travel,Business,570,4,4,3,4,3,4,5,4,4,5,4,5,4,5,1,0.0,satisfied +57502,121662,Female,Loyal Customer,42,Business travel,Business,2641,3,3,2,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +57503,47629,Male,Loyal Customer,23,Business travel,Business,1504,5,5,5,5,4,4,4,4,3,1,1,4,3,4,9,0.0,satisfied +57504,1298,Male,Loyal Customer,55,Personal Travel,Eco,89,2,5,2,3,3,2,3,3,1,3,5,3,4,3,4,0.0,neutral or dissatisfied +57505,69767,Female,Loyal Customer,43,Business travel,Eco Plus,1085,1,3,3,3,3,3,3,1,1,1,1,4,1,2,59,61.0,neutral or dissatisfied +57506,58132,Female,Loyal Customer,45,Personal Travel,Eco Plus,589,3,4,3,3,2,4,5,3,3,3,3,4,3,4,8,0.0,neutral or dissatisfied +57507,33533,Male,Loyal Customer,22,Personal Travel,Eco Plus,228,3,4,3,3,3,3,5,3,5,3,4,4,3,3,4,34.0,neutral or dissatisfied +57508,64367,Male,Loyal Customer,52,Personal Travel,Eco,1192,3,5,3,2,2,3,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +57509,10451,Male,Loyal Customer,52,Business travel,Business,3571,4,4,4,4,2,4,5,4,4,4,4,5,4,5,1,0.0,satisfied +57510,129548,Male,Loyal Customer,78,Business travel,Eco,842,2,4,4,4,2,2,2,2,3,2,4,3,4,2,66,52.0,neutral or dissatisfied +57511,95934,Female,Loyal Customer,32,Personal Travel,Eco,1504,4,2,4,1,5,4,5,5,1,1,2,1,1,5,17,0.0,satisfied +57512,28866,Male,Loyal Customer,30,Business travel,Business,3540,4,4,4,4,5,5,5,5,4,1,4,2,2,5,0,10.0,satisfied +57513,13299,Male,Loyal Customer,25,Personal Travel,Eco Plus,657,4,4,3,4,2,3,4,2,3,5,4,3,3,2,5,0.0,satisfied +57514,100872,Male,Loyal Customer,15,Personal Travel,Eco,1605,1,5,1,2,3,1,3,3,4,3,5,4,4,3,45,21.0,neutral or dissatisfied +57515,129840,Male,Loyal Customer,56,Personal Travel,Eco,337,2,3,2,2,2,2,2,2,5,4,5,3,3,2,0,0.0,neutral or dissatisfied +57516,39668,Female,Loyal Customer,54,Personal Travel,Eco,476,5,4,1,3,2,3,4,4,4,1,4,1,4,4,0,0.0,satisfied +57517,127529,Male,Loyal Customer,37,Business travel,Business,1009,5,5,5,5,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +57518,37718,Male,Loyal Customer,34,Personal Travel,Eco,1028,2,3,2,4,2,2,2,2,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +57519,2548,Female,Loyal Customer,39,Business travel,Eco,227,3,1,1,1,3,3,3,3,3,2,3,4,4,3,6,5.0,neutral or dissatisfied +57520,48191,Female,Loyal Customer,43,Business travel,Business,3785,3,3,3,3,4,4,3,1,1,2,3,3,1,4,0,0.0,neutral or dissatisfied +57521,51870,Male,Loyal Customer,25,Business travel,Eco,771,4,3,3,3,4,4,5,4,1,4,4,2,3,4,0,0.0,satisfied +57522,71983,Male,disloyal Customer,36,Business travel,Eco,1040,2,2,2,1,4,2,4,4,1,3,1,5,3,4,12,0.0,neutral or dissatisfied +57523,17820,Male,Loyal Customer,22,Personal Travel,Eco,1075,3,5,3,3,4,3,4,4,3,5,4,1,4,4,30,5.0,neutral or dissatisfied +57524,46218,Male,Loyal Customer,28,Business travel,Business,752,4,4,3,4,4,4,4,4,3,5,4,4,1,4,20,40.0,satisfied +57525,86503,Male,Loyal Customer,25,Personal Travel,Eco,749,1,2,1,3,3,1,4,3,2,1,3,1,4,3,13,13.0,neutral or dissatisfied +57526,31778,Male,Loyal Customer,53,Personal Travel,Eco,602,2,4,2,5,2,2,2,2,1,2,3,4,4,2,4,8.0,neutral or dissatisfied +57527,79208,Male,disloyal Customer,48,Business travel,Eco,794,1,2,2,3,3,1,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +57528,20797,Female,Loyal Customer,60,Business travel,Eco,457,4,4,4,4,4,2,1,5,5,4,5,1,5,3,0,0.0,satisfied +57529,77697,Male,Loyal Customer,24,Business travel,Business,1728,1,1,1,1,4,4,4,4,4,5,4,3,4,4,1,0.0,satisfied +57530,91101,Female,Loyal Customer,52,Personal Travel,Eco,404,1,4,1,2,2,4,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +57531,49658,Male,Loyal Customer,65,Business travel,Eco,109,3,5,2,5,3,3,3,3,2,3,1,3,2,3,0,0.0,neutral or dissatisfied +57532,122342,Female,Loyal Customer,23,Business travel,Business,1662,4,4,4,4,5,5,5,5,4,5,4,4,4,5,18,23.0,satisfied +57533,30981,Female,Loyal Customer,46,Business travel,Business,1476,4,4,4,4,2,1,3,4,4,4,4,5,4,4,0,0.0,satisfied +57534,125514,Male,Loyal Customer,46,Business travel,Business,1923,4,4,4,4,3,4,5,4,4,4,4,5,4,4,4,3.0,satisfied +57535,128193,Female,Loyal Customer,52,Personal Travel,Eco Plus,1849,5,4,5,1,4,5,1,3,3,5,3,2,3,4,0,0.0,satisfied +57536,109067,Male,Loyal Customer,80,Business travel,Eco,572,3,5,5,5,3,3,3,3,4,1,4,2,3,3,12,30.0,neutral or dissatisfied +57537,91720,Male,disloyal Customer,24,Business travel,Business,590,5,5,5,2,4,5,4,4,3,2,4,3,5,4,0,0.0,satisfied +57538,128194,Female,Loyal Customer,9,Personal Travel,Eco Plus,1849,3,1,3,2,2,3,2,2,2,2,3,2,2,2,0,7.0,neutral or dissatisfied +57539,35435,Female,Loyal Customer,35,Personal Travel,Eco,1028,4,4,4,4,4,5,5,3,4,5,5,5,5,5,187,197.0,neutral or dissatisfied +57540,24492,Male,Loyal Customer,46,Business travel,Business,147,2,2,2,2,5,4,4,5,5,5,3,1,5,5,0,0.0,satisfied +57541,113675,Female,Loyal Customer,43,Personal Travel,Eco,258,4,2,4,3,4,3,4,1,1,4,1,1,1,1,6,5.0,neutral or dissatisfied +57542,89342,Female,Loyal Customer,51,Business travel,Business,1587,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +57543,35304,Male,Loyal Customer,48,Business travel,Eco,1028,5,4,4,4,5,5,5,5,1,2,1,5,1,5,0,0.0,satisfied +57544,4518,Female,disloyal Customer,23,Business travel,Eco,435,2,0,2,4,5,2,3,5,5,4,5,1,5,5,0,0.0,neutral or dissatisfied +57545,117114,Female,Loyal Customer,52,Business travel,Eco,647,2,5,1,1,2,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +57546,68781,Female,Loyal Customer,43,Business travel,Business,926,1,1,1,1,3,5,5,4,4,5,4,5,4,3,23,34.0,satisfied +57547,108782,Female,Loyal Customer,36,Business travel,Eco,404,4,5,5,5,4,4,4,4,1,4,3,3,4,4,45,51.0,neutral or dissatisfied +57548,67532,Male,Loyal Customer,39,Business travel,Business,3631,1,2,2,2,2,3,3,1,1,1,1,2,1,4,12,8.0,neutral or dissatisfied +57549,116846,Male,Loyal Customer,70,Personal Travel,Business,647,3,4,3,1,2,2,3,3,3,3,3,5,3,4,1,0.0,neutral or dissatisfied +57550,99869,Male,Loyal Customer,55,Business travel,Business,1760,3,3,3,3,4,4,4,5,5,5,5,5,5,5,7,5.0,satisfied +57551,70838,Female,Loyal Customer,41,Business travel,Business,761,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +57552,125938,Female,Loyal Customer,15,Personal Travel,Eco,920,1,3,1,3,1,1,1,1,2,2,4,3,4,1,0,8.0,neutral or dissatisfied +57553,54958,Female,Loyal Customer,50,Business travel,Business,1635,1,1,1,1,4,5,5,3,3,2,3,5,3,5,12,7.0,satisfied +57554,33598,Male,disloyal Customer,22,Business travel,Eco,399,2,0,3,5,1,3,1,1,2,3,4,1,5,1,0,0.0,neutral or dissatisfied +57555,81664,Female,Loyal Customer,41,Business travel,Business,907,3,3,3,3,5,4,5,4,4,4,4,4,4,5,11,2.0,satisfied +57556,115592,Male,Loyal Customer,51,Business travel,Business,480,1,1,1,1,5,4,5,3,3,3,3,5,3,5,0,3.0,satisfied +57557,19549,Female,disloyal Customer,44,Business travel,Eco,212,3,0,3,4,3,4,4,1,4,1,2,4,3,4,145,148.0,neutral or dissatisfied +57558,110495,Male,Loyal Customer,22,Personal Travel,Eco,842,3,3,3,2,4,3,1,4,1,3,2,3,4,4,7,2.0,neutral or dissatisfied +57559,42848,Female,Loyal Customer,24,Business travel,Business,2818,4,4,4,4,4,3,4,4,4,2,3,1,4,4,1,18.0,neutral or dissatisfied +57560,62963,Female,disloyal Customer,20,Business travel,Eco,967,5,5,5,3,3,5,3,3,3,3,5,5,4,3,4,0.0,satisfied +57561,129873,Female,Loyal Customer,44,Personal Travel,Eco Plus,308,3,4,3,1,5,4,4,3,3,3,3,3,3,5,0,22.0,neutral or dissatisfied +57562,114213,Male,Loyal Customer,25,Business travel,Eco,819,1,3,3,3,1,1,3,1,2,3,3,3,3,1,2,13.0,neutral or dissatisfied +57563,81525,Female,disloyal Customer,16,Business travel,Eco,1124,3,3,3,4,5,3,5,5,2,1,4,1,4,5,0,8.0,neutral or dissatisfied +57564,72699,Male,Loyal Customer,20,Personal Travel,Eco,964,1,2,1,4,4,1,4,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +57565,23950,Male,Loyal Customer,34,Business travel,Business,936,3,3,3,3,2,2,5,4,4,4,4,4,4,5,26,14.0,satisfied +57566,45678,Male,disloyal Customer,25,Business travel,Eco,896,1,1,1,1,3,1,5,3,4,5,5,3,1,3,4,10.0,neutral or dissatisfied +57567,50280,Male,Loyal Customer,42,Business travel,Business,3075,4,3,3,3,4,3,4,4,4,4,4,4,4,1,71,66.0,neutral or dissatisfied +57568,103575,Male,Loyal Customer,50,Personal Travel,Eco,689,0,4,0,1,1,0,1,1,4,4,4,4,5,1,0,0.0,satisfied +57569,20602,Female,Loyal Customer,12,Business travel,Eco Plus,773,5,5,5,5,5,5,4,5,5,1,3,5,5,5,0,3.0,satisfied +57570,28349,Male,Loyal Customer,27,Personal Travel,Eco,867,2,5,3,1,4,3,4,4,4,4,2,2,4,4,27,28.0,neutral or dissatisfied +57571,27701,Female,disloyal Customer,29,Business travel,Eco Plus,1107,2,2,2,1,1,2,1,1,2,2,5,3,4,1,0,0.0,neutral or dissatisfied +57572,63036,Male,Loyal Customer,23,Business travel,Eco,567,3,5,5,5,3,3,1,3,2,2,3,3,4,3,20,16.0,neutral or dissatisfied +57573,56271,Female,Loyal Customer,50,Business travel,Business,404,3,3,3,3,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +57574,70604,Male,Loyal Customer,34,Personal Travel,Eco,2611,3,2,3,3,3,5,5,1,5,3,2,5,4,5,0,6.0,neutral or dissatisfied +57575,64747,Male,Loyal Customer,56,Business travel,Business,224,3,3,3,3,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +57576,50735,Female,Loyal Customer,68,Personal Travel,Eco,308,2,5,2,2,5,5,5,2,2,2,2,5,2,4,68,64.0,neutral or dissatisfied +57577,88994,Female,disloyal Customer,19,Business travel,Eco Plus,1199,2,3,2,3,5,2,5,5,3,4,3,3,3,5,84,109.0,neutral or dissatisfied +57578,9796,Female,disloyal Customer,21,Business travel,Eco,383,1,2,1,4,3,1,3,3,3,5,4,2,3,3,36,26.0,neutral or dissatisfied +57579,1152,Female,Loyal Customer,41,Personal Travel,Eco,354,1,3,1,3,2,1,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +57580,33050,Male,Loyal Customer,23,Personal Travel,Eco,101,3,4,3,3,2,3,2,2,1,2,2,3,3,2,1,3.0,neutral or dissatisfied +57581,86210,Male,Loyal Customer,51,Business travel,Business,2042,2,2,2,2,4,5,4,4,4,4,4,4,4,4,8,0.0,satisfied +57582,123406,Female,disloyal Customer,29,Business travel,Eco,1337,3,3,3,3,5,3,5,5,2,2,3,2,3,5,0,0.0,neutral or dissatisfied +57583,119439,Male,Loyal Customer,69,Personal Travel,Eco,399,2,3,2,3,3,2,1,3,4,4,2,2,1,3,3,0.0,neutral or dissatisfied +57584,44665,Male,Loyal Customer,38,Business travel,Eco,67,4,5,5,5,4,4,4,4,3,5,4,2,2,4,0,0.0,satisfied +57585,67062,Female,Loyal Customer,50,Business travel,Eco,1121,3,5,5,5,5,4,4,3,3,3,3,4,3,2,4,0.0,neutral or dissatisfied +57586,46954,Male,Loyal Customer,64,Personal Travel,Eco,737,3,1,3,2,3,3,4,3,1,2,2,4,1,3,14,24.0,neutral or dissatisfied +57587,36843,Male,Loyal Customer,34,Personal Travel,Eco,369,2,4,2,1,5,2,5,5,4,2,5,3,3,5,0,0.0,neutral or dissatisfied +57588,96860,Female,Loyal Customer,47,Business travel,Eco,816,3,1,2,1,4,3,2,3,3,3,3,3,3,1,23,8.0,neutral or dissatisfied +57589,29976,Male,Loyal Customer,19,Business travel,Business,2561,3,5,5,5,3,3,3,3,2,3,4,2,4,3,0,3.0,neutral or dissatisfied +57590,57851,Male,Loyal Customer,51,Business travel,Business,2329,3,3,3,3,4,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +57591,19375,Female,Loyal Customer,22,Personal Travel,Eco,476,1,4,1,3,1,1,1,1,4,5,2,3,4,1,0,0.0,neutral or dissatisfied +57592,122026,Female,Loyal Customer,42,Business travel,Business,3162,4,5,5,5,5,4,4,1,1,1,4,2,1,4,0,0.0,neutral or dissatisfied +57593,51930,Male,disloyal Customer,39,Business travel,Business,347,1,1,1,4,2,1,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +57594,11589,Male,disloyal Customer,51,Business travel,Eco,468,1,2,0,2,5,0,5,5,4,4,2,4,3,5,125,118.0,neutral or dissatisfied +57595,42021,Female,Loyal Customer,45,Business travel,Eco,241,4,2,4,2,1,1,4,4,4,4,4,1,4,4,0,0.0,satisfied +57596,54583,Male,disloyal Customer,14,Business travel,Business,3904,2,4,3,4,3,5,5,4,5,4,4,5,1,5,9,12.0,neutral or dissatisfied +57597,39146,Female,Loyal Customer,16,Personal Travel,Eco,252,4,4,4,2,3,4,3,3,5,3,4,5,4,3,0,0.0,satisfied +57598,59239,Male,Loyal Customer,39,Personal Travel,Eco,649,1,3,1,5,5,1,5,5,4,2,1,2,1,5,13,8.0,neutral or dissatisfied +57599,87879,Female,Loyal Customer,49,Business travel,Eco Plus,214,2,1,1,1,1,3,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +57600,10969,Male,disloyal Customer,25,Business travel,Eco,163,3,0,3,4,3,3,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +57601,106122,Female,Loyal Customer,54,Business travel,Business,3238,3,3,3,3,3,5,5,4,4,4,4,3,4,4,15,6.0,satisfied +57602,127221,Male,Loyal Customer,45,Business travel,Eco Plus,370,5,5,5,5,5,5,5,5,3,2,1,4,2,5,0,0.0,satisfied +57603,24898,Female,Loyal Customer,73,Business travel,Eco Plus,397,2,2,2,2,1,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +57604,66150,Male,Loyal Customer,41,Business travel,Business,1645,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +57605,38054,Male,Loyal Customer,24,Business travel,Business,3818,3,3,4,3,4,4,4,4,1,2,3,1,2,4,1,1.0,satisfied +57606,28874,Male,Loyal Customer,26,Business travel,Eco,1050,3,2,2,2,3,4,3,3,2,4,3,3,1,3,0,0.0,satisfied +57607,11958,Male,Loyal Customer,48,Business travel,Business,1728,2,2,2,2,3,5,5,4,4,5,4,5,4,4,0,9.0,satisfied +57608,32915,Male,Loyal Customer,32,Personal Travel,Eco,101,2,5,2,5,3,2,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +57609,90795,Male,Loyal Customer,44,Business travel,Business,2701,3,5,5,5,5,4,3,3,3,3,3,3,3,4,3,7.0,neutral or dissatisfied +57610,20252,Male,Loyal Customer,69,Business travel,Business,2230,1,1,1,1,1,3,4,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +57611,73518,Female,Loyal Customer,44,Business travel,Business,594,3,3,3,3,5,4,5,5,5,4,5,5,5,4,0,2.0,satisfied +57612,86068,Male,Loyal Customer,43,Business travel,Business,2130,4,4,4,4,2,5,5,3,3,4,3,3,3,4,5,0.0,satisfied +57613,104470,Male,Loyal Customer,66,Personal Travel,Eco,1123,2,4,2,1,1,2,1,1,3,2,3,3,4,1,0,8.0,neutral or dissatisfied +57614,62582,Female,Loyal Customer,29,Business travel,Eco,1846,2,2,2,2,2,2,2,2,3,3,4,3,3,2,16,6.0,neutral or dissatisfied +57615,1782,Female,Loyal Customer,53,Business travel,Business,408,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +57616,79269,Male,Loyal Customer,49,Business travel,Business,2454,1,1,1,1,3,4,4,3,3,4,4,4,5,4,340,341.0,satisfied +57617,95266,Male,Loyal Customer,63,Personal Travel,Eco,239,1,5,1,1,3,1,3,3,3,2,3,4,1,3,36,27.0,neutral or dissatisfied +57618,114828,Male,Loyal Customer,58,Business travel,Business,3891,3,3,3,3,1,3,4,3,3,3,3,4,3,1,1,0.0,neutral or dissatisfied +57619,46704,Male,Loyal Customer,7,Personal Travel,Eco,73,1,5,0,1,4,0,4,4,3,2,3,3,4,4,69,84.0,neutral or dissatisfied +57620,99981,Female,Loyal Customer,56,Business travel,Business,281,4,1,1,1,4,3,4,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +57621,43958,Female,Loyal Customer,11,Personal Travel,Eco,257,3,2,3,3,1,3,1,1,1,5,3,3,3,1,0,4.0,neutral or dissatisfied +57622,121713,Female,Loyal Customer,61,Personal Travel,Eco,683,2,3,2,4,1,3,4,2,2,2,2,5,2,3,0,6.0,neutral or dissatisfied +57623,79226,Female,Loyal Customer,21,Personal Travel,Eco Plus,1990,0,2,0,3,5,2,5,5,3,1,3,2,4,5,27,8.0,satisfied +57624,119397,Female,Loyal Customer,33,Business travel,Business,399,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +57625,1928,Female,Loyal Customer,60,Business travel,Business,3952,4,4,4,4,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +57626,22299,Female,Loyal Customer,30,Business travel,Eco,143,4,4,4,4,4,4,4,4,3,5,4,3,3,4,0,0.0,satisfied +57627,58765,Male,Loyal Customer,29,Business travel,Business,1120,2,2,2,2,5,5,5,5,3,5,4,4,4,5,66,54.0,satisfied +57628,70499,Male,Loyal Customer,31,Personal Travel,Eco,867,1,1,1,3,3,1,3,3,4,1,4,4,4,3,95,121.0,neutral or dissatisfied +57629,20454,Female,Loyal Customer,25,Business travel,Business,2475,2,2,2,2,4,4,4,4,3,3,1,5,2,4,5,0.0,satisfied +57630,15473,Female,Loyal Customer,58,Personal Travel,Eco,331,2,5,2,2,3,5,4,2,2,2,4,5,2,5,0,0.0,neutral or dissatisfied +57631,58326,Male,Loyal Customer,36,Business travel,Eco,239,5,2,2,2,5,5,5,5,3,2,5,3,1,5,19,0.0,satisfied +57632,120603,Female,Loyal Customer,70,Personal Travel,Eco Plus,980,2,3,2,3,2,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +57633,127237,Female,Loyal Customer,54,Business travel,Business,1460,1,1,1,1,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +57634,10029,Male,Loyal Customer,28,Business travel,Business,667,3,3,3,3,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +57635,22548,Male,Loyal Customer,53,Business travel,Business,300,0,0,0,3,1,1,1,5,3,5,4,1,5,1,214,228.0,satisfied +57636,103077,Male,Loyal Customer,37,Personal Travel,Eco,460,4,4,2,3,1,2,1,1,2,3,1,3,3,1,0,0.0,neutral or dissatisfied +57637,122015,Male,Loyal Customer,49,Business travel,Business,2842,1,1,1,1,4,4,5,4,4,5,5,4,4,5,0,0.0,satisfied +57638,76212,Male,Loyal Customer,42,Business travel,Business,2333,1,4,4,4,3,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +57639,113658,Male,Loyal Customer,9,Personal Travel,Eco,223,1,4,1,1,3,1,5,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +57640,109059,Female,Loyal Customer,45,Business travel,Business,1581,2,5,5,5,2,3,4,2,2,2,2,4,2,2,24,13.0,neutral or dissatisfied +57641,17278,Male,Loyal Customer,16,Personal Travel,Eco Plus,872,4,5,4,4,4,4,4,4,1,2,5,3,2,4,16,28.0,neutral or dissatisfied +57642,28961,Male,Loyal Customer,56,Business travel,Business,3162,1,1,1,1,5,3,3,4,4,4,4,2,4,5,0,0.0,satisfied +57643,84456,Male,disloyal Customer,39,Business travel,Eco,290,2,1,2,2,5,2,1,5,4,3,2,4,2,5,0,0.0,neutral or dissatisfied +57644,82551,Male,disloyal Customer,37,Business travel,Business,528,4,4,4,5,4,4,4,4,5,4,4,3,5,4,0,16.0,satisfied +57645,40721,Male,disloyal Customer,22,Business travel,Eco,590,0,0,0,3,1,0,1,1,4,5,2,5,5,1,3,18.0,satisfied +57646,61010,Female,Loyal Customer,53,Business travel,Business,3414,3,3,3,3,5,5,5,3,5,4,5,5,3,5,5,0.0,satisfied +57647,66550,Male,Loyal Customer,26,Business travel,Business,2213,2,4,4,4,2,1,2,2,1,2,3,4,3,2,6,5.0,neutral or dissatisfied +57648,38450,Female,Loyal Customer,35,Business travel,Business,1504,5,5,2,5,3,5,5,4,4,4,4,3,4,1,0,0.0,satisfied +57649,52617,Male,disloyal Customer,33,Business travel,Eco,160,3,4,3,3,5,3,5,5,5,1,2,4,4,5,0,0.0,neutral or dissatisfied +57650,92108,Male,Loyal Customer,59,Personal Travel,Eco,1517,2,5,2,3,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +57651,82710,Female,Loyal Customer,68,Personal Travel,Eco,632,3,4,3,3,2,4,5,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +57652,103800,Female,disloyal Customer,23,Business travel,Eco,882,4,4,4,1,4,4,4,4,4,5,4,3,5,4,21,28.0,neutral or dissatisfied +57653,116093,Female,Loyal Customer,55,Personal Travel,Eco,308,4,4,4,3,2,3,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +57654,113423,Male,Loyal Customer,58,Business travel,Business,2946,0,5,0,3,4,4,5,5,5,5,5,5,5,3,37,46.0,satisfied +57655,74755,Female,Loyal Customer,54,Personal Travel,Eco,1235,3,4,3,5,2,3,4,5,5,3,5,4,5,3,52,42.0,neutral or dissatisfied +57656,98112,Female,Loyal Customer,55,Business travel,Business,2185,1,1,1,1,5,4,4,3,3,4,3,5,3,3,0,6.0,satisfied +57657,15041,Male,Loyal Customer,43,Business travel,Eco,576,5,2,2,2,5,5,5,5,3,1,1,4,2,5,0,0.0,satisfied +57658,92492,Female,disloyal Customer,54,Business travel,Eco,639,1,2,1,1,2,1,2,2,1,4,1,2,2,2,5,13.0,neutral or dissatisfied +57659,122229,Female,Loyal Customer,50,Business travel,Business,1961,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +57660,55090,Male,disloyal Customer,23,Business travel,Eco,1504,2,2,2,3,4,2,4,4,3,3,1,5,3,4,6,12.0,satisfied +57661,76749,Male,Loyal Customer,70,Personal Travel,Eco,205,1,3,1,1,3,1,3,3,4,4,1,3,2,3,0,0.0,neutral or dissatisfied +57662,42475,Female,Loyal Customer,68,Business travel,Eco,429,4,2,2,2,5,3,2,4,4,4,4,1,4,2,0,0.0,satisfied +57663,105572,Male,Loyal Customer,53,Business travel,Eco,577,2,1,1,1,2,2,2,2,1,2,3,3,3,2,26,11.0,neutral or dissatisfied +57664,81319,Male,disloyal Customer,24,Business travel,Business,1299,4,5,4,5,3,4,2,3,3,3,5,5,5,3,15,66.0,satisfied +57665,102357,Male,Loyal Customer,44,Business travel,Eco,391,2,5,5,5,2,2,2,2,2,5,3,4,4,2,22,19.0,neutral or dissatisfied +57666,87233,Male,Loyal Customer,56,Business travel,Eco Plus,946,2,3,3,3,2,2,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +57667,88031,Female,Loyal Customer,49,Business travel,Business,3292,2,2,2,2,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +57668,33443,Male,Loyal Customer,43,Personal Travel,Eco,2462,3,4,3,1,3,3,3,5,2,5,5,3,5,3,0,0.0,neutral or dissatisfied +57669,99903,Female,Loyal Customer,63,Personal Travel,Eco,738,2,4,2,1,3,4,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +57670,33875,Male,Loyal Customer,35,Business travel,Business,3855,3,3,3,3,4,4,4,4,4,4,4,5,4,4,14,23.0,satisfied +57671,71320,Male,disloyal Customer,27,Business travel,Eco,1514,2,2,2,3,3,2,2,3,1,1,3,1,3,3,93,131.0,neutral or dissatisfied +57672,8423,Female,Loyal Customer,43,Business travel,Business,3150,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +57673,92475,Female,Loyal Customer,49,Business travel,Business,1947,3,3,3,3,2,4,4,4,4,4,4,4,4,3,8,0.0,satisfied +57674,93727,Male,Loyal Customer,15,Personal Travel,Eco,630,4,5,4,5,5,4,5,5,5,3,4,4,4,5,11,0.0,neutral or dissatisfied +57675,111336,Male,Loyal Customer,27,Personal Travel,Eco,283,4,5,4,4,3,4,4,3,3,2,5,4,4,3,0,0.0,satisfied +57676,89402,Male,disloyal Customer,57,Business travel,Eco,134,3,2,3,4,2,3,2,2,3,4,4,1,4,2,0,2.0,neutral or dissatisfied +57677,101328,Female,Loyal Customer,9,Business travel,Eco Plus,986,3,2,2,2,3,3,1,3,4,1,3,1,4,3,43,29.0,neutral or dissatisfied +57678,113395,Female,Loyal Customer,40,Business travel,Business,407,3,3,3,3,5,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +57679,21662,Female,disloyal Customer,44,Business travel,Eco,708,1,1,1,2,2,1,4,2,5,1,5,5,2,2,22,38.0,neutral or dissatisfied +57680,77561,Male,Loyal Customer,43,Business travel,Business,2444,5,5,5,5,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +57681,116890,Male,Loyal Customer,58,Business travel,Business,3957,0,0,0,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +57682,58190,Female,disloyal Customer,25,Business travel,Business,925,4,5,3,4,2,3,2,2,4,4,4,4,4,2,3,0.0,satisfied +57683,80522,Female,Loyal Customer,49,Business travel,Business,1749,5,5,5,5,3,5,4,4,4,4,4,3,4,3,49,57.0,satisfied +57684,128714,Female,Loyal Customer,60,Business travel,Business,1464,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +57685,128107,Female,Loyal Customer,53,Business travel,Business,1587,1,1,1,1,4,5,5,5,5,5,5,3,5,5,2,0.0,satisfied +57686,55175,Female,Loyal Customer,44,Personal Travel,Eco,1609,2,4,1,1,2,4,4,3,3,1,3,3,3,4,11,9.0,neutral or dissatisfied +57687,117814,Male,Loyal Customer,45,Personal Travel,Eco,328,5,5,5,5,2,5,2,2,5,3,4,3,4,2,0,0.0,satisfied +57688,44557,Male,Loyal Customer,48,Business travel,Eco Plus,157,4,1,3,1,5,4,5,5,1,5,5,5,2,5,0,0.0,satisfied +57689,23658,Male,Loyal Customer,43,Business travel,Eco,196,4,2,2,2,4,4,4,4,3,1,2,3,1,4,0,3.0,satisfied +57690,34709,Male,Loyal Customer,36,Business travel,Eco,264,5,3,3,3,5,5,5,5,2,3,2,5,2,5,0,0.0,satisfied +57691,92378,Female,Loyal Customer,26,Personal Travel,Business,2092,1,0,1,2,1,1,1,1,4,3,1,4,3,1,0,0.0,neutral or dissatisfied +57692,9099,Male,Loyal Customer,41,Business travel,Business,765,5,5,5,5,5,5,5,5,5,5,5,4,5,3,6,0.0,satisfied +57693,118410,Female,disloyal Customer,49,Business travel,Business,646,3,3,3,2,4,3,2,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +57694,44507,Male,Loyal Customer,23,Personal Travel,Eco,503,2,5,2,1,1,2,1,1,3,3,5,4,4,1,29,18.0,neutral or dissatisfied +57695,79027,Male,disloyal Customer,55,Business travel,Business,226,2,2,2,3,3,2,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +57696,26919,Male,Loyal Customer,49,Personal Travel,Eco,1874,2,4,2,3,3,2,3,3,2,1,2,5,2,3,14,6.0,neutral or dissatisfied +57697,123043,Female,disloyal Customer,22,Business travel,Eco,507,2,0,3,2,3,3,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +57698,94843,Male,disloyal Customer,44,Business travel,Eco,239,4,2,4,3,3,4,3,3,1,5,4,3,4,3,5,0.0,neutral or dissatisfied +57699,117061,Female,disloyal Customer,39,Business travel,Business,325,3,3,3,3,2,3,2,2,2,2,4,3,4,2,0,2.0,neutral or dissatisfied +57700,53047,Male,Loyal Customer,57,Personal Travel,Eco,1190,3,5,3,1,5,3,5,5,3,4,4,4,4,5,33,49.0,neutral or dissatisfied +57701,12513,Female,Loyal Customer,60,Business travel,Business,3250,2,2,2,2,4,5,5,5,5,5,5,4,5,4,25,36.0,satisfied +57702,16581,Male,Loyal Customer,59,Personal Travel,Eco,872,3,3,3,3,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +57703,63590,Female,Loyal Customer,80,Business travel,Business,633,5,1,3,1,5,3,3,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +57704,123538,Female,Loyal Customer,37,Business travel,Business,1773,2,2,2,2,5,5,4,5,5,5,5,4,5,3,18,0.0,satisfied +57705,38015,Male,Loyal Customer,50,Business travel,Eco,1249,5,1,1,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +57706,76954,Female,Loyal Customer,49,Business travel,Business,1990,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +57707,98130,Male,Loyal Customer,26,Personal Travel,Eco,472,2,3,2,3,2,2,4,2,5,3,1,2,4,2,0,0.0,neutral or dissatisfied +57708,126400,Female,disloyal Customer,20,Business travel,Eco,631,1,0,1,1,2,1,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +57709,26664,Female,Loyal Customer,44,Business travel,Eco,545,2,3,3,3,4,3,3,1,1,2,1,1,1,4,10,14.0,neutral or dissatisfied +57710,121511,Male,Loyal Customer,38,Personal Travel,Eco,1727,2,4,1,3,3,1,2,3,3,1,3,1,1,3,0,0.0,neutral or dissatisfied +57711,86701,Male,Loyal Customer,50,Business travel,Business,1747,1,1,1,1,3,3,5,3,3,3,3,3,3,5,0,0.0,satisfied +57712,89840,Female,Loyal Customer,48,Business travel,Business,2532,5,5,3,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +57713,114843,Female,disloyal Customer,44,Business travel,Business,337,3,3,3,2,1,3,1,1,3,3,4,5,4,1,11,0.0,neutral or dissatisfied +57714,32933,Female,Loyal Customer,53,Personal Travel,Eco,102,2,4,2,3,4,5,4,2,2,2,2,3,2,3,3,5.0,neutral or dissatisfied +57715,115074,Female,Loyal Customer,37,Business travel,Business,3828,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +57716,9904,Male,Loyal Customer,47,Business travel,Business,3157,2,2,2,2,3,4,5,1,1,2,1,3,1,3,98,103.0,satisfied +57717,113205,Female,Loyal Customer,35,Business travel,Business,2863,5,5,5,5,4,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +57718,127188,Male,Loyal Customer,55,Business travel,Eco Plus,304,2,1,3,1,3,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +57719,95161,Female,Loyal Customer,61,Personal Travel,Eco,239,3,5,3,4,3,5,5,5,5,3,5,5,5,4,27,26.0,neutral or dissatisfied +57720,59404,Male,Loyal Customer,57,Personal Travel,Eco,2504,2,2,2,4,5,2,5,5,1,5,4,1,4,5,4,0.0,neutral or dissatisfied +57721,57832,Female,Loyal Customer,52,Personal Travel,Eco Plus,622,3,5,3,4,5,4,4,4,4,3,4,3,4,4,0,20.0,neutral or dissatisfied +57722,2284,Male,disloyal Customer,25,Business travel,Eco,691,3,4,4,3,4,4,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +57723,24798,Female,Loyal Customer,37,Personal Travel,Eco Plus,528,2,5,2,5,5,2,5,5,3,5,4,4,4,5,59,83.0,neutral or dissatisfied +57724,93382,Female,Loyal Customer,42,Business travel,Business,723,5,1,5,5,2,5,5,5,5,4,5,4,5,5,1,22.0,satisfied +57725,22133,Male,Loyal Customer,78,Business travel,Business,2480,1,5,5,5,5,3,3,1,1,2,1,3,1,1,32,32.0,neutral or dissatisfied +57726,94392,Female,Loyal Customer,46,Business travel,Business,3335,0,0,0,5,3,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +57727,121921,Female,disloyal Customer,25,Business travel,Business,449,3,0,3,4,4,3,4,4,3,4,4,5,4,4,19,10.0,neutral or dissatisfied +57728,61350,Female,Loyal Customer,50,Business travel,Eco,602,2,4,4,4,1,4,3,2,2,2,2,2,2,2,16,14.0,neutral or dissatisfied +57729,25874,Female,Loyal Customer,38,Business travel,Business,1711,3,3,3,3,4,5,2,5,5,5,5,4,5,1,7,0.0,satisfied +57730,47264,Male,Loyal Customer,38,Personal Travel,Business,588,4,4,3,2,5,5,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +57731,18168,Male,Loyal Customer,26,Personal Travel,Business,231,1,4,1,3,2,1,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +57732,94190,Female,Loyal Customer,37,Business travel,Business,3386,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,3.0,satisfied +57733,95902,Female,Loyal Customer,68,Personal Travel,Eco,580,2,5,2,3,3,5,5,3,3,2,3,4,3,4,5,3.0,neutral or dissatisfied +57734,69796,Male,Loyal Customer,56,Business travel,Business,1055,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,1.0,satisfied +57735,69347,Male,Loyal Customer,27,Business travel,Business,1089,2,2,2,2,5,5,5,4,3,5,5,5,5,5,215,254.0,satisfied +57736,77387,Male,Loyal Customer,44,Business travel,Business,188,4,2,2,2,4,3,3,3,3,3,4,3,3,4,35,29.0,neutral or dissatisfied +57737,58982,Female,Loyal Customer,37,Business travel,Business,1744,1,1,1,1,5,3,5,5,5,4,5,4,5,4,0,22.0,satisfied +57738,4915,Male,Loyal Customer,7,Business travel,Business,1020,1,1,1,1,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +57739,74704,Female,Loyal Customer,19,Personal Travel,Eco,1464,3,5,3,4,4,3,4,4,3,4,5,4,4,4,42,27.0,neutral or dissatisfied +57740,1815,Male,Loyal Customer,65,Business travel,Business,408,3,4,4,4,2,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +57741,4291,Female,Loyal Customer,8,Personal Travel,Eco,502,2,3,2,3,2,2,3,2,1,3,3,1,4,2,0,0.0,neutral or dissatisfied +57742,108585,Male,Loyal Customer,40,Business travel,Business,813,3,3,3,3,4,5,5,2,2,3,2,5,2,4,12,7.0,satisfied +57743,10436,Male,disloyal Customer,25,Business travel,Business,201,4,0,4,1,5,4,5,5,4,5,4,4,4,5,0,0.0,satisfied +57744,11445,Female,Loyal Customer,22,Business travel,Eco Plus,163,4,4,3,3,4,4,3,4,4,2,2,3,3,4,0,0.0,neutral or dissatisfied +57745,86306,Female,disloyal Customer,22,Business travel,Eco,356,0,0,0,2,3,0,3,3,5,2,5,5,5,3,0,0.0,satisfied +57746,125300,Female,Loyal Customer,59,Business travel,Business,678,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +57747,57188,Male,Loyal Customer,55,Business travel,Business,2227,5,5,5,5,2,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +57748,99876,Female,Loyal Customer,34,Business travel,Eco,1436,4,4,4,4,4,4,4,4,2,4,5,2,5,4,3,1.0,satisfied +57749,72503,Female,Loyal Customer,26,Business travel,Business,1121,3,3,3,3,4,4,4,4,4,4,5,5,4,4,2,0.0,satisfied +57750,70691,Male,Loyal Customer,24,Personal Travel,Eco,447,2,4,3,3,4,3,5,4,2,2,3,1,3,4,0,26.0,neutral or dissatisfied +57751,60576,Male,Loyal Customer,33,Business travel,Business,1290,3,3,3,3,3,3,3,3,3,1,3,3,3,3,0,1.0,neutral or dissatisfied +57752,77819,Male,Loyal Customer,11,Personal Travel,Eco,813,2,2,3,4,1,3,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +57753,13309,Male,disloyal Customer,32,Business travel,Eco,448,1,2,1,2,5,1,5,5,3,5,2,1,3,5,27,25.0,neutral or dissatisfied +57754,106480,Female,Loyal Customer,41,Business travel,Business,1624,4,4,4,4,3,3,4,4,4,4,4,4,4,4,36,22.0,neutral or dissatisfied +57755,26877,Female,Loyal Customer,7,Business travel,Eco Plus,2329,2,5,5,5,2,2,4,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +57756,35871,Female,Loyal Customer,8,Personal Travel,Eco,997,3,5,3,3,4,3,1,4,1,3,2,5,5,4,42,54.0,neutral or dissatisfied +57757,29781,Female,Loyal Customer,33,Personal Travel,Business,548,1,1,1,2,3,1,2,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +57758,33830,Female,disloyal Customer,23,Business travel,Business,1562,0,0,0,1,1,0,1,1,4,5,5,4,5,1,0,0.0,satisfied +57759,40573,Female,disloyal Customer,30,Business travel,Eco,391,2,0,2,2,1,2,1,1,1,2,3,4,1,1,0,0.0,neutral or dissatisfied +57760,78200,Female,Loyal Customer,34,Business travel,Business,2542,5,5,5,5,5,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +57761,50790,Male,Loyal Customer,34,Personal Travel,Eco,86,1,4,1,3,4,1,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +57762,81431,Female,Loyal Customer,34,Personal Travel,Eco,393,4,5,4,4,3,4,3,3,1,1,5,2,5,3,0,0.0,neutral or dissatisfied +57763,113429,Female,Loyal Customer,32,Business travel,Business,3067,2,3,3,3,2,2,2,2,3,2,4,2,4,2,5,6.0,neutral or dissatisfied +57764,12592,Male,Loyal Customer,42,Business travel,Business,2035,3,5,5,5,1,4,3,3,3,3,3,1,3,1,7,10.0,neutral or dissatisfied +57765,45449,Female,Loyal Customer,60,Business travel,Business,674,3,3,3,3,4,4,4,5,5,4,5,5,5,3,37,25.0,satisfied +57766,27822,Female,disloyal Customer,37,Business travel,Eco,1048,3,3,3,4,1,3,1,1,1,5,3,1,4,1,0,0.0,neutral or dissatisfied +57767,127611,Male,disloyal Customer,29,Business travel,Business,1488,5,5,5,4,4,5,4,4,4,3,4,3,4,4,0,0.0,satisfied +57768,3719,Female,Loyal Customer,14,Personal Travel,Eco,431,3,5,3,1,1,3,1,1,2,5,3,4,4,1,0,0.0,neutral or dissatisfied +57769,17172,Male,disloyal Customer,25,Business travel,Eco,643,4,0,4,4,3,4,3,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +57770,81287,Female,Loyal Customer,62,Personal Travel,Eco,1020,4,4,4,4,5,4,3,5,5,4,5,3,5,4,46,18.0,neutral or dissatisfied +57771,36942,Female,disloyal Customer,37,Business travel,Eco,718,3,3,3,3,3,3,3,3,4,3,3,1,3,3,3,12.0,neutral or dissatisfied +57772,109874,Male,Loyal Customer,19,Business travel,Business,1522,2,2,2,2,4,4,4,4,3,3,5,4,4,4,8,0.0,satisfied +57773,52974,Female,Loyal Customer,10,Personal Travel,Eco,2306,3,5,2,5,2,1,1,4,3,3,5,1,4,1,39,91.0,neutral or dissatisfied +57774,76502,Female,disloyal Customer,24,Business travel,Business,534,0,0,0,4,4,0,3,4,5,2,5,4,4,4,19,15.0,satisfied +57775,79462,Female,Loyal Customer,73,Business travel,Eco,783,4,5,5,5,4,1,4,4,4,4,4,2,4,3,0,0.0,satisfied +57776,91109,Female,Loyal Customer,15,Personal Travel,Eco,594,1,5,1,5,3,1,2,3,2,3,1,3,3,3,0,0.0,neutral or dissatisfied +57777,83511,Male,Loyal Customer,65,Personal Travel,Eco,946,1,3,1,3,4,1,4,4,2,3,3,3,3,4,2,8.0,neutral or dissatisfied +57778,34464,Female,disloyal Customer,37,Business travel,Business,266,3,3,3,3,4,3,4,4,2,2,4,1,3,4,112,109.0,neutral or dissatisfied +57779,97046,Female,Loyal Customer,32,Personal Travel,Business,1129,2,5,2,4,1,2,2,1,4,5,3,3,4,1,2,0.0,neutral or dissatisfied +57780,123050,Male,Loyal Customer,29,Business travel,Business,1510,3,1,2,1,3,3,3,3,3,2,4,4,4,3,21,39.0,neutral or dissatisfied +57781,22892,Male,Loyal Customer,49,Business travel,Eco Plus,170,5,2,5,2,5,5,5,5,2,1,3,3,3,5,38,43.0,satisfied +57782,91316,Male,disloyal Customer,36,Business travel,Business,404,4,5,5,5,2,5,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +57783,104708,Female,disloyal Customer,39,Business travel,Business,1865,1,1,1,1,1,1,1,1,5,5,5,3,5,1,19,13.0,neutral or dissatisfied +57784,55751,Male,Loyal Customer,33,Business travel,Business,1737,1,3,3,3,1,1,1,1,2,4,2,2,3,1,0,24.0,neutral or dissatisfied +57785,103606,Male,Loyal Customer,51,Business travel,Business,251,2,4,4,4,1,4,3,2,2,2,2,1,2,3,0,6.0,neutral or dissatisfied +57786,100279,Female,Loyal Customer,51,Business travel,Business,3955,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,2.0,satisfied +57787,94105,Male,Loyal Customer,52,Personal Travel,Business,239,2,5,2,4,3,5,5,5,5,2,5,5,5,3,0,7.0,neutral or dissatisfied +57788,83957,Male,Loyal Customer,52,Business travel,Business,373,3,5,3,3,4,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +57789,46536,Male,Loyal Customer,50,Business travel,Business,125,4,4,4,4,5,2,3,4,4,4,3,1,4,5,6,8.0,satisfied +57790,2884,Male,Loyal Customer,65,Personal Travel,Eco,491,4,0,4,1,2,4,2,2,5,2,5,4,5,2,0,29.0,neutral or dissatisfied +57791,19039,Female,Loyal Customer,37,Business travel,Eco Plus,388,5,2,2,2,5,5,5,5,5,3,5,1,5,5,0,1.0,satisfied +57792,106698,Female,Loyal Customer,69,Business travel,Business,516,3,5,5,5,4,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +57793,18472,Male,Loyal Customer,33,Business travel,Eco,305,5,2,2,2,5,5,5,5,2,4,5,2,5,5,0,0.0,satisfied +57794,54429,Male,Loyal Customer,29,Personal Travel,Eco,305,3,5,3,5,2,3,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +57795,13812,Male,disloyal Customer,24,Business travel,Eco,617,3,2,3,2,3,3,3,3,2,1,1,1,1,3,4,51.0,neutral or dissatisfied +57796,80388,Male,Loyal Customer,39,Personal Travel,Eco,368,1,5,1,4,5,1,5,5,5,1,1,5,4,5,0,0.0,neutral or dissatisfied +57797,85563,Female,Loyal Customer,64,Business travel,Business,2010,1,1,1,1,3,2,2,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +57798,5367,Female,Loyal Customer,44,Business travel,Eco,785,2,3,3,3,4,3,2,2,2,2,2,4,2,4,0,29.0,neutral or dissatisfied +57799,61961,Male,Loyal Customer,20,Personal Travel,Eco,2161,4,5,4,4,1,4,1,1,5,2,4,5,4,1,0,0.0,satisfied +57800,10452,Female,Loyal Customer,54,Business travel,Business,158,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +57801,106697,Male,Loyal Customer,29,Business travel,Business,1519,2,4,2,2,5,5,5,5,5,3,5,5,4,5,6,4.0,satisfied +57802,24907,Male,Loyal Customer,43,Business travel,Eco,762,5,4,4,4,4,5,4,4,4,2,4,4,2,4,18,0.0,satisfied +57803,22886,Female,Loyal Customer,19,Personal Travel,Eco,134,1,5,1,2,4,1,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +57804,95816,Male,Loyal Customer,44,Business travel,Business,1428,4,4,4,4,3,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +57805,93227,Female,Loyal Customer,67,Business travel,Eco,1060,4,3,3,3,4,1,2,4,4,4,4,2,4,3,15,1.0,satisfied +57806,105127,Male,Loyal Customer,59,Business travel,Business,281,2,2,2,2,3,4,4,2,2,2,2,3,2,2,22,16.0,neutral or dissatisfied +57807,59497,Male,Loyal Customer,47,Personal Travel,Eco,811,3,3,4,1,4,4,4,4,3,1,2,3,1,4,0,0.0,neutral or dissatisfied +57808,10239,Female,Loyal Customer,60,Personal Travel,Business,458,0,4,0,4,4,3,4,3,3,0,3,1,3,4,20,4.0,satisfied +57809,61078,Female,Loyal Customer,29,Business travel,Business,1546,1,1,1,1,1,2,1,1,2,1,3,1,3,1,13,0.0,neutral or dissatisfied +57810,117644,Female,Loyal Customer,49,Business travel,Business,2252,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +57811,126626,Female,disloyal Customer,26,Business travel,Business,602,3,5,3,2,5,3,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +57812,123046,Female,disloyal Customer,38,Business travel,Business,468,3,3,3,4,3,3,3,3,3,4,5,3,5,3,4,0.0,neutral or dissatisfied +57813,48843,Female,Loyal Customer,35,Personal Travel,Business,421,1,3,5,3,1,2,4,3,3,5,3,5,3,5,25,42.0,neutral or dissatisfied +57814,26344,Female,Loyal Customer,21,Personal Travel,Eco,834,4,4,4,2,4,4,5,4,4,2,3,1,1,4,0,0.0,satisfied +57815,55502,Male,Loyal Customer,68,Personal Travel,Eco,1739,1,5,1,3,2,1,2,2,5,3,3,5,4,2,1,20.0,neutral or dissatisfied +57816,5946,Male,disloyal Customer,40,Business travel,Business,612,3,4,4,1,3,4,5,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +57817,17821,Female,Loyal Customer,54,Personal Travel,Eco,1075,3,4,4,3,2,4,5,1,1,4,1,5,1,5,0,5.0,neutral or dissatisfied +57818,99482,Male,Loyal Customer,73,Business travel,Eco,283,1,2,5,2,1,1,1,1,1,2,4,4,3,1,0,0.0,neutral or dissatisfied +57819,93833,Male,Loyal Customer,22,Business travel,Business,3742,3,5,4,5,3,3,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +57820,128263,Male,Loyal Customer,36,Business travel,Business,2451,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +57821,12687,Male,Loyal Customer,45,Business travel,Business,1634,4,4,4,4,3,2,2,2,2,2,2,4,2,4,19,13.0,satisfied +57822,91820,Male,Loyal Customer,42,Business travel,Business,3708,2,2,2,2,2,4,5,4,4,3,4,4,4,5,3,6.0,satisfied +57823,47283,Male,Loyal Customer,35,Business travel,Eco,584,4,4,4,4,4,4,4,4,3,5,1,3,5,4,0,0.0,satisfied +57824,29129,Male,Loyal Customer,64,Personal Travel,Eco,1050,4,4,4,1,2,4,5,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +57825,71464,Male,Loyal Customer,39,Personal Travel,Eco,867,2,0,2,5,3,2,3,3,3,2,4,5,3,3,0,0.0,neutral or dissatisfied +57826,61348,Male,Loyal Customer,44,Business travel,Business,2684,5,5,5,5,5,4,4,4,4,5,4,4,4,3,39,27.0,satisfied +57827,6339,Male,Loyal Customer,39,Business travel,Business,1634,5,5,5,5,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +57828,6168,Male,Loyal Customer,32,Business travel,Business,491,2,2,2,2,2,2,2,2,2,4,3,2,3,2,30,17.0,neutral or dissatisfied +57829,73181,Female,disloyal Customer,28,Business travel,Business,1258,2,2,2,4,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +57830,33055,Male,Loyal Customer,13,Personal Travel,Eco,163,3,5,0,4,1,0,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +57831,128275,Male,Loyal Customer,11,Personal Travel,Business,651,3,3,3,4,3,3,3,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +57832,11862,Male,disloyal Customer,25,Business travel,Eco,1042,2,2,2,3,5,2,5,5,4,2,4,3,3,5,29,8.0,neutral or dissatisfied +57833,66215,Male,Loyal Customer,25,Business travel,Business,3455,5,5,5,5,5,4,5,5,3,5,5,3,4,5,0,0.0,satisfied +57834,98428,Female,Loyal Customer,40,Personal Travel,Eco,2176,3,2,3,3,4,3,4,4,2,2,4,2,4,4,22,24.0,neutral or dissatisfied +57835,99654,Female,Loyal Customer,15,Business travel,Business,3854,3,2,2,2,3,3,3,3,3,5,4,1,3,3,0,0.0,neutral or dissatisfied +57836,123910,Female,Loyal Customer,65,Personal Travel,Eco,546,1,5,1,5,3,2,5,2,2,1,1,1,2,2,28,29.0,neutral or dissatisfied +57837,117662,Male,Loyal Customer,47,Business travel,Business,1449,5,5,5,5,2,5,4,5,5,5,5,4,5,4,22,0.0,satisfied +57838,51274,Female,Loyal Customer,51,Business travel,Eco Plus,86,4,3,3,3,3,1,4,5,5,4,5,2,5,2,0,10.0,satisfied +57839,40416,Male,Loyal Customer,41,Business travel,Eco,290,4,1,1,1,4,4,4,4,2,3,1,1,4,4,0,0.0,satisfied +57840,120332,Male,Loyal Customer,17,Business travel,Eco Plus,268,3,2,2,2,3,3,1,3,3,4,4,4,4,3,0,65.0,neutral or dissatisfied +57841,128917,Female,Loyal Customer,59,Business travel,Business,1995,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +57842,18340,Male,disloyal Customer,29,Business travel,Eco,474,2,2,3,3,2,3,2,2,3,5,3,3,4,2,0,45.0,neutral or dissatisfied +57843,116660,Female,disloyal Customer,64,Business travel,Business,358,5,5,5,3,3,5,3,3,3,4,5,5,4,3,0,0.0,satisfied +57844,52411,Male,Loyal Customer,64,Personal Travel,Eco,451,1,2,4,3,1,4,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +57845,4788,Male,Loyal Customer,56,Personal Travel,Eco,258,3,3,3,1,1,3,1,1,3,1,4,2,2,1,82,86.0,neutral or dissatisfied +57846,107656,Female,Loyal Customer,55,Business travel,Business,3606,4,4,1,4,3,4,5,5,5,5,5,5,5,5,12,0.0,satisfied +57847,84769,Female,Loyal Customer,49,Business travel,Business,3845,1,1,1,1,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +57848,12728,Female,disloyal Customer,24,Business travel,Eco,289,2,0,2,1,1,2,1,1,5,2,1,2,3,1,0,4.0,neutral or dissatisfied +57849,69310,Male,Loyal Customer,48,Personal Travel,Business,1096,4,4,4,5,5,5,1,5,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +57850,7982,Female,Loyal Customer,41,Business travel,Business,335,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +57851,89738,Female,Loyal Customer,22,Personal Travel,Eco,1035,3,5,3,2,3,3,3,3,3,3,4,3,5,3,0,3.0,neutral or dissatisfied +57852,74674,Female,Loyal Customer,25,Personal Travel,Eco,1464,5,5,5,3,4,5,4,4,5,2,5,4,5,4,7,0.0,satisfied +57853,39540,Female,Loyal Customer,54,Business travel,Eco,620,5,2,5,5,3,1,1,5,5,5,5,2,5,3,0,0.0,satisfied +57854,100182,Female,Loyal Customer,11,Personal Travel,Eco,717,2,4,2,1,2,2,3,2,5,4,1,3,5,2,20,10.0,neutral or dissatisfied +57855,67807,Male,Loyal Customer,39,Business travel,Eco,835,5,4,4,4,5,5,5,5,5,2,4,1,5,5,2,74.0,satisfied +57856,57030,Male,Loyal Customer,31,Business travel,Eco Plus,2425,1,4,2,2,1,1,1,3,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +57857,20011,Male,Loyal Customer,55,Personal Travel,Eco,589,3,4,3,4,3,3,3,3,1,3,4,4,4,3,62,68.0,neutral or dissatisfied +57858,59200,Male,Loyal Customer,29,Business travel,Eco,1440,1,2,2,2,1,1,1,1,1,5,1,4,1,1,48,33.0,neutral or dissatisfied +57859,46214,Female,disloyal Customer,22,Business travel,Eco,752,3,3,3,1,2,3,2,2,4,2,1,2,3,2,19,8.0,neutral or dissatisfied +57860,74587,Male,disloyal Customer,55,Business travel,Eco,1205,2,2,2,3,2,2,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +57861,14377,Female,Loyal Customer,52,Business travel,Business,789,5,5,5,5,4,5,5,5,5,5,5,3,5,4,33,34.0,satisfied +57862,4370,Male,disloyal Customer,27,Business travel,Business,528,1,1,1,3,3,1,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +57863,93991,Female,Loyal Customer,30,Personal Travel,Eco,1218,1,0,1,4,3,1,1,3,4,2,5,3,5,3,3,0.0,neutral or dissatisfied +57864,105646,Male,disloyal Customer,17,Business travel,Eco,842,4,3,3,2,3,3,3,3,4,2,5,3,4,3,21,14.0,satisfied +57865,22090,Male,Loyal Customer,23,Business travel,Business,782,1,1,1,1,3,4,3,3,2,5,2,4,2,3,16,7.0,satisfied +57866,67527,Female,disloyal Customer,27,Business travel,Business,1171,3,3,3,4,3,3,3,3,1,1,4,3,3,3,0,0.0,neutral or dissatisfied +57867,99998,Male,disloyal Customer,42,Business travel,Business,281,5,5,5,4,4,5,4,4,5,3,4,4,5,4,34,36.0,satisfied +57868,108424,Male,Loyal Customer,43,Business travel,Business,1444,1,5,5,5,5,4,3,1,1,2,1,3,1,3,0,10.0,neutral or dissatisfied +57869,116642,Female,Loyal Customer,39,Business travel,Business,3447,4,1,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +57870,29420,Female,Loyal Customer,30,Business travel,Eco Plus,2355,0,0,0,1,3,0,3,3,4,1,1,3,1,3,0,0.0,satisfied +57871,30353,Female,Loyal Customer,44,Business travel,Business,2811,1,1,1,1,3,2,3,5,5,5,5,4,5,3,119,124.0,satisfied +57872,124744,Male,Loyal Customer,53,Personal Travel,Eco Plus,399,3,5,3,3,4,3,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +57873,46140,Female,Loyal Customer,25,Business travel,Business,627,5,5,5,5,5,5,5,5,2,1,3,1,3,5,1,1.0,satisfied +57874,65674,Female,Loyal Customer,53,Business travel,Business,3942,5,5,5,5,3,2,5,5,5,5,5,4,5,2,88,124.0,satisfied +57875,21901,Female,disloyal Customer,23,Business travel,Eco,551,3,0,3,1,5,3,5,5,1,3,3,4,5,5,5,0.0,neutral or dissatisfied +57876,48877,Male,Loyal Customer,38,Business travel,Eco,109,5,1,1,1,5,5,5,5,1,5,5,1,5,5,0,0.0,satisfied +57877,24491,Female,disloyal Customer,37,Business travel,Eco,147,2,0,2,2,5,2,5,5,1,2,5,1,3,5,22,15.0,neutral or dissatisfied +57878,42858,Male,Loyal Customer,60,Personal Travel,Eco,328,2,5,2,5,1,2,1,1,2,4,5,4,3,1,0,4.0,neutral or dissatisfied +57879,84742,Male,Loyal Customer,48,Business travel,Business,547,1,1,2,1,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +57880,53322,Female,Loyal Customer,27,Personal Travel,Eco,921,2,4,2,1,3,2,3,3,4,5,5,3,4,3,11,2.0,neutral or dissatisfied +57881,112415,Female,disloyal Customer,30,Business travel,Eco,846,3,3,3,4,2,3,2,2,2,1,3,2,3,2,11,0.0,neutral or dissatisfied +57882,39111,Male,Loyal Customer,37,Business travel,Business,2012,1,1,1,1,3,1,4,4,4,4,4,4,4,4,56,58.0,satisfied +57883,28547,Female,Loyal Customer,10,Personal Travel,Eco,2677,2,5,2,1,3,2,3,3,5,1,3,3,3,3,0,0.0,neutral or dissatisfied +57884,61439,Male,Loyal Customer,55,Business travel,Business,2253,4,4,4,4,4,3,4,4,4,5,4,4,4,4,3,0.0,satisfied +57885,122583,Male,Loyal Customer,33,Business travel,Business,728,5,5,5,5,3,4,3,3,5,2,5,4,5,3,0,0.0,satisfied +57886,23130,Male,disloyal Customer,37,Business travel,Business,223,4,4,4,1,2,4,2,2,1,3,3,5,1,2,0,0.0,neutral or dissatisfied +57887,107304,Male,Loyal Customer,51,Personal Travel,Eco,283,5,5,5,2,3,5,4,3,3,4,4,5,4,3,0,0.0,satisfied +57888,72758,Male,Loyal Customer,43,Business travel,Business,1719,3,3,5,5,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +57889,22167,Female,disloyal Customer,34,Business travel,Eco,773,2,2,2,3,4,2,4,4,4,1,3,5,1,4,3,10.0,neutral or dissatisfied +57890,69540,Male,Loyal Customer,55,Business travel,Business,2475,5,5,5,5,5,4,4,5,3,4,4,4,5,4,6,13.0,satisfied +57891,96499,Female,Loyal Customer,33,Business travel,Business,436,2,1,1,1,5,4,4,2,2,2,2,4,2,3,7,11.0,neutral or dissatisfied +57892,102352,Male,Loyal Customer,40,Business travel,Business,2246,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +57893,80828,Male,disloyal Customer,22,Business travel,Eco,484,2,1,2,1,5,2,5,5,2,4,1,4,1,5,20,12.0,neutral or dissatisfied +57894,123782,Female,Loyal Customer,30,Business travel,Business,2185,3,3,3,3,2,2,2,2,5,2,5,3,4,2,0,0.0,satisfied +57895,82966,Male,Loyal Customer,54,Business travel,Business,3314,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +57896,6036,Male,Loyal Customer,65,Business travel,Business,691,2,2,2,2,4,1,2,2,2,3,2,4,2,4,37,13.0,neutral or dissatisfied +57897,13069,Male,Loyal Customer,34,Business travel,Business,3364,2,3,3,3,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +57898,19288,Female,Loyal Customer,37,Business travel,Business,2696,0,5,0,3,5,5,4,1,1,1,1,3,1,5,0,0.0,satisfied +57899,45220,Male,Loyal Customer,53,Business travel,Business,3286,2,2,3,2,1,4,2,4,4,4,4,3,4,2,34,22.0,satisfied +57900,56059,Male,Loyal Customer,37,Personal Travel,Eco,2475,4,5,4,2,4,3,3,3,3,4,5,3,4,3,1,27.0,neutral or dissatisfied +57901,10170,Female,disloyal Customer,38,Business travel,Business,667,2,2,2,1,5,2,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +57902,43580,Male,Loyal Customer,66,Personal Travel,Eco,1499,3,4,2,3,3,2,3,3,3,1,1,5,3,3,0,0.0,neutral or dissatisfied +57903,112747,Female,Loyal Customer,55,Personal Travel,Business,590,2,5,2,3,4,5,4,4,4,2,4,3,4,4,22,14.0,neutral or dissatisfied +57904,69550,Male,disloyal Customer,21,Business travel,Eco,1133,3,2,2,1,2,3,3,4,2,3,4,3,3,3,0,12.0,neutral or dissatisfied +57905,2733,Male,Loyal Customer,37,Business travel,Business,2767,1,1,5,1,2,5,5,5,5,5,5,5,5,5,41,47.0,satisfied +57906,78239,Male,disloyal Customer,30,Business travel,Eco Plus,259,1,1,1,2,1,1,1,1,3,5,3,1,3,1,0,14.0,neutral or dissatisfied +57907,88530,Female,Loyal Customer,35,Personal Travel,Eco,581,1,4,1,3,1,1,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +57908,75875,Female,Loyal Customer,50,Business travel,Business,1972,2,2,2,2,5,5,5,5,5,5,5,3,5,3,2,0.0,satisfied +57909,51681,Female,Loyal Customer,72,Business travel,Business,3465,3,4,4,4,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +57910,110692,Male,Loyal Customer,45,Personal Travel,Eco,829,2,5,2,4,5,2,2,5,3,4,4,4,5,5,2,0.0,neutral or dissatisfied +57911,46735,Male,Loyal Customer,47,Personal Travel,Eco,152,1,4,1,4,5,1,5,5,3,5,4,3,4,5,51,46.0,neutral or dissatisfied +57912,48381,Male,Loyal Customer,32,Personal Travel,Eco,522,4,4,4,3,4,4,4,4,5,4,4,5,5,4,106,104.0,neutral or dissatisfied +57913,75984,Female,Loyal Customer,21,Personal Travel,Eco,297,1,2,1,3,5,1,5,5,1,3,4,2,3,5,0,0.0,neutral or dissatisfied +57914,15818,Female,disloyal Customer,26,Business travel,Eco Plus,282,1,5,0,3,1,0,3,1,4,5,5,1,4,1,0,0.0,neutral or dissatisfied +57915,77489,Female,Loyal Customer,37,Business travel,Business,1643,3,1,1,1,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +57916,61994,Female,Loyal Customer,51,Business travel,Business,2586,2,2,2,2,3,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +57917,9928,Male,Loyal Customer,36,Business travel,Eco,508,3,3,2,3,3,3,3,2,3,4,3,3,3,3,143,148.0,neutral or dissatisfied +57918,26077,Male,Loyal Customer,56,Business travel,Business,591,5,5,5,5,4,5,4,2,2,2,2,3,2,4,21,16.0,satisfied +57919,117876,Male,Loyal Customer,45,Business travel,Business,3801,4,4,4,4,3,4,5,4,4,4,4,3,4,5,11,2.0,satisfied +57920,30175,Female,Loyal Customer,20,Personal Travel,Eco,213,2,4,2,1,4,2,4,4,3,2,2,2,4,4,0,0.0,neutral or dissatisfied +57921,71866,Male,Loyal Customer,48,Personal Travel,Eco,1744,2,5,2,4,2,4,4,3,2,4,5,4,3,4,185,177.0,neutral or dissatisfied +57922,126829,Female,Loyal Customer,29,Business travel,Eco,2296,3,2,2,2,3,3,3,3,4,3,4,2,3,3,10,0.0,neutral or dissatisfied +57923,114932,Male,Loyal Customer,39,Business travel,Business,2446,4,4,3,4,3,5,5,4,4,5,4,4,4,3,60,57.0,satisfied +57924,30859,Male,Loyal Customer,34,Business travel,Business,1506,2,2,2,2,5,1,1,5,5,4,5,1,5,5,0,0.0,satisfied +57925,67670,Female,Loyal Customer,42,Business travel,Eco,1235,1,1,1,1,3,4,4,1,1,1,1,2,1,3,5,2.0,neutral or dissatisfied +57926,111263,Male,disloyal Customer,36,Business travel,Business,459,1,1,1,1,5,1,5,5,3,2,5,3,4,5,22,18.0,neutral or dissatisfied +57927,13773,Female,Loyal Customer,47,Business travel,Business,925,5,5,5,5,4,2,1,4,4,4,4,5,4,3,88,85.0,satisfied +57928,29544,Female,Loyal Customer,42,Personal Travel,Business,1533,3,2,3,3,1,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +57929,54959,Female,disloyal Customer,24,Business travel,Eco,796,3,3,3,1,1,3,1,1,4,2,3,4,5,1,8,1.0,neutral or dissatisfied +57930,8341,Female,Loyal Customer,28,Personal Travel,Eco,661,2,1,2,3,2,2,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +57931,4444,Male,Loyal Customer,17,Personal Travel,Eco,762,4,2,4,4,1,4,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +57932,31275,Female,disloyal Customer,28,Business travel,Eco,533,2,1,2,3,2,2,2,2,4,4,3,3,3,2,0,4.0,neutral or dissatisfied +57933,73450,Male,Loyal Customer,20,Personal Travel,Eco,1120,2,4,2,4,2,2,2,2,4,4,5,3,4,2,19,65.0,neutral or dissatisfied +57934,95,Female,Loyal Customer,7,Personal Travel,Eco Plus,173,2,5,0,2,2,0,2,2,5,2,5,3,5,2,18,35.0,neutral or dissatisfied +57935,80197,Female,Loyal Customer,60,Personal Travel,Eco,2475,4,1,4,2,3,2,1,3,3,4,1,2,3,1,6,0.0,neutral or dissatisfied +57936,39389,Male,Loyal Customer,36,Business travel,Business,1937,3,3,3,3,1,1,3,4,4,4,4,3,4,5,0,0.0,satisfied +57937,86536,Male,Loyal Customer,33,Personal Travel,Eco,749,2,4,2,4,3,2,3,3,2,4,1,2,5,3,0,0.0,neutral or dissatisfied +57938,104861,Female,Loyal Customer,42,Business travel,Business,327,4,5,5,5,1,4,3,4,4,4,4,4,4,3,13,6.0,neutral or dissatisfied +57939,59350,Male,Loyal Customer,50,Business travel,Business,2449,1,1,3,1,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +57940,112122,Male,Loyal Customer,55,Business travel,Business,977,5,5,5,5,5,4,5,2,2,2,2,4,2,5,0,14.0,satisfied +57941,26682,Male,Loyal Customer,22,Personal Travel,Eco,404,2,4,3,2,4,3,4,4,3,2,4,5,5,4,6,17.0,neutral or dissatisfied +57942,48961,Female,Loyal Customer,43,Business travel,Business,3727,2,2,2,2,3,4,2,3,3,4,3,1,3,5,0,0.0,satisfied +57943,43133,Male,Loyal Customer,44,Business travel,Eco Plus,236,2,4,4,4,2,2,2,2,2,4,3,2,3,2,28,16.0,neutral or dissatisfied +57944,13263,Female,disloyal Customer,22,Business travel,Eco,257,2,0,2,5,3,2,4,3,1,1,2,1,5,3,10,3.0,neutral or dissatisfied +57945,120137,Male,Loyal Customer,39,Business travel,Business,1475,1,3,1,1,3,5,5,4,4,4,4,3,4,3,0,10.0,satisfied +57946,1725,Female,Loyal Customer,44,Business travel,Business,2173,3,3,3,3,4,2,3,3,3,3,3,4,3,3,56,63.0,neutral or dissatisfied +57947,32266,Male,Loyal Customer,56,Business travel,Business,2651,2,2,2,2,5,5,2,5,5,5,3,2,5,3,0,3.0,satisfied +57948,87618,Male,Loyal Customer,43,Business travel,Business,1615,4,4,4,4,2,4,5,2,2,2,2,4,2,5,73,61.0,satisfied +57949,62277,Male,Loyal Customer,49,Business travel,Business,2279,2,2,2,2,2,4,5,3,3,3,3,5,3,4,6,0.0,satisfied +57950,119686,Female,Loyal Customer,58,Business travel,Business,3629,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +57951,83283,Female,Loyal Customer,53,Personal Travel,Eco,2079,3,3,2,3,2,2,1,4,4,4,3,1,2,1,104,150.0,neutral or dissatisfied +57952,31002,Male,disloyal Customer,62,Business travel,Eco,391,3,0,3,5,3,3,5,3,4,4,5,5,1,3,24,20.0,neutral or dissatisfied +57953,52109,Male,Loyal Customer,41,Personal Travel,Eco,438,4,5,4,1,5,4,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +57954,57533,Female,disloyal Customer,23,Business travel,Eco,413,3,3,3,3,4,3,4,4,4,3,3,3,3,4,47,30.0,neutral or dissatisfied +57955,73387,Female,Loyal Customer,52,Business travel,Eco,1197,2,4,4,4,1,4,3,2,2,2,2,1,2,2,21,24.0,neutral or dissatisfied +57956,90892,Male,disloyal Customer,33,Business travel,Business,366,3,2,2,3,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +57957,62886,Male,Loyal Customer,29,Business travel,Business,2362,4,4,4,4,5,5,5,5,5,5,5,5,5,5,0,6.0,satisfied +57958,52959,Male,disloyal Customer,48,Business travel,Eco,2306,3,3,3,4,1,3,1,1,3,1,4,4,2,1,0,0.0,neutral or dissatisfied +57959,117319,Female,Loyal Customer,33,Personal Travel,Eco Plus,647,1,1,1,3,3,1,3,3,4,1,3,3,2,3,0,0.0,neutral or dissatisfied +57960,44537,Female,Loyal Customer,51,Business travel,Business,3787,1,4,4,4,1,3,3,3,3,3,1,2,3,3,12,0.0,neutral or dissatisfied +57961,12236,Male,Loyal Customer,54,Business travel,Business,2308,2,2,3,2,1,2,3,5,5,5,5,3,5,1,0,0.0,satisfied +57962,81998,Male,Loyal Customer,39,Business travel,Business,1517,2,2,3,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +57963,12343,Female,Loyal Customer,47,Business travel,Business,3637,1,1,1,1,4,1,1,5,5,5,5,3,5,2,0,0.0,satisfied +57964,99286,Female,Loyal Customer,28,Personal Travel,Eco,833,2,5,2,3,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +57965,101663,Female,Loyal Customer,48,Business travel,Business,2106,1,0,0,1,3,1,1,1,1,0,1,4,1,2,97,84.0,neutral or dissatisfied +57966,62078,Female,disloyal Customer,24,Business travel,Business,2586,5,4,5,3,1,4,1,1,4,5,4,3,5,1,0,0.0,satisfied +57967,2709,Female,Loyal Customer,20,Personal Travel,Eco,562,2,4,1,2,1,4,4,5,2,4,5,4,4,4,175,186.0,neutral or dissatisfied +57968,121022,Male,Loyal Customer,26,Personal Travel,Eco,992,3,5,3,1,5,3,5,5,5,5,4,4,5,5,18,64.0,neutral or dissatisfied +57969,128099,Male,Loyal Customer,50,Personal Travel,Eco,2917,4,4,3,3,3,3,3,4,4,3,5,3,4,3,0,13.0,neutral or dissatisfied +57970,84816,Male,Loyal Customer,41,Business travel,Business,547,4,4,4,4,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +57971,67394,Female,disloyal Customer,25,Business travel,Eco,592,4,3,4,4,1,4,1,1,3,4,4,1,4,1,2,12.0,neutral or dissatisfied +57972,47883,Male,disloyal Customer,22,Business travel,Eco,846,3,3,3,2,3,3,4,3,2,3,1,2,4,3,0,0.0,neutral or dissatisfied +57973,4905,Male,Loyal Customer,41,Business travel,Business,2625,5,5,5,5,3,5,5,4,4,4,4,5,4,5,15,9.0,satisfied +57974,51893,Female,Loyal Customer,38,Business travel,Business,2767,1,0,0,3,2,3,3,1,1,0,1,3,1,1,0,0.0,neutral or dissatisfied +57975,99283,Male,Loyal Customer,39,Business travel,Business,535,1,1,1,1,4,5,5,5,5,5,5,4,5,5,4,0.0,satisfied +57976,103011,Male,disloyal Customer,25,Business travel,Business,546,4,2,4,3,2,4,2,2,5,4,5,5,5,2,1,0.0,satisfied +57977,68803,Female,Loyal Customer,24,Personal Travel,Eco,861,2,2,2,1,2,2,2,2,2,3,2,1,2,2,44,42.0,neutral or dissatisfied +57978,25444,Female,disloyal Customer,20,Business travel,Eco,669,2,1,2,2,5,2,2,5,2,5,2,2,2,5,34,28.0,neutral or dissatisfied +57979,338,Female,Loyal Customer,57,Personal Travel,Eco,853,4,5,4,3,3,4,4,4,4,4,4,4,4,3,0,9.0,neutral or dissatisfied +57980,56230,Male,Loyal Customer,26,Personal Travel,Eco,1585,2,1,2,1,4,2,1,4,2,1,1,1,2,4,10,0.0,neutral or dissatisfied +57981,127622,Female,disloyal Customer,55,Business travel,Eco,1773,3,3,3,3,4,3,4,4,3,4,2,1,3,4,0,0.0,neutral or dissatisfied +57982,103514,Female,Loyal Customer,67,Personal Travel,Eco,1047,4,4,4,3,5,4,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +57983,13815,Male,disloyal Customer,23,Business travel,Business,628,3,3,4,2,4,1,1,2,4,2,3,1,4,1,194,218.0,neutral or dissatisfied +57984,120564,Male,Loyal Customer,35,Personal Travel,Eco,2176,3,4,3,4,4,3,4,4,1,1,2,4,3,4,3,4.0,neutral or dissatisfied +57985,33674,Female,Loyal Customer,25,Business travel,Business,2367,5,5,5,5,2,2,2,2,5,4,4,5,5,2,0,0.0,satisfied +57986,1344,Male,Loyal Customer,44,Business travel,Business,1537,3,3,3,3,2,4,4,5,5,5,4,3,5,4,8,8.0,satisfied +57987,100030,Female,Loyal Customer,64,Business travel,Business,3346,4,4,4,4,1,3,3,3,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +57988,69173,Male,disloyal Customer,28,Business travel,Eco,187,1,0,1,4,4,1,4,4,5,5,5,1,4,4,3,0.0,neutral or dissatisfied +57989,32397,Female,disloyal Customer,24,Business travel,Eco,101,3,2,3,4,4,3,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +57990,112832,Female,Loyal Customer,40,Business travel,Business,1497,3,3,3,3,4,5,4,4,4,4,4,4,4,4,16,0.0,satisfied +57991,102075,Female,Loyal Customer,33,Business travel,Business,407,5,5,5,5,3,4,5,4,4,4,4,4,4,3,13,6.0,satisfied +57992,101208,Female,Loyal Customer,32,Personal Travel,Eco,1069,1,4,1,1,4,1,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +57993,51904,Male,Loyal Customer,37,Business travel,Eco,201,4,5,5,5,4,4,4,4,4,2,3,5,1,4,8,0.0,satisfied +57994,29884,Female,Loyal Customer,20,Business travel,Business,571,2,2,2,2,4,4,4,4,2,4,3,3,4,4,0,1.0,satisfied +57995,87597,Female,Loyal Customer,7,Personal Travel,Eco,432,1,4,2,3,4,2,4,4,4,1,5,3,2,4,0,0.0,neutral or dissatisfied +57996,4309,Male,Loyal Customer,46,Business travel,Business,2131,3,3,3,3,3,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +57997,71795,Female,Loyal Customer,58,Business travel,Business,1744,2,2,2,2,2,4,5,4,4,4,4,3,4,5,5,0.0,satisfied +57998,59636,Male,Loyal Customer,48,Business travel,Business,2427,2,2,2,2,5,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +57999,82020,Female,Loyal Customer,40,Personal Travel,Eco,1532,3,5,2,2,1,2,1,1,3,5,3,4,5,1,1,0.0,neutral or dissatisfied +58000,93044,Male,Loyal Customer,68,Business travel,Business,3314,4,2,2,2,3,2,1,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +58001,81503,Male,Loyal Customer,31,Personal Travel,Eco,528,2,5,2,5,1,2,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +58002,94894,Female,Loyal Customer,40,Business travel,Business,3391,3,4,1,4,4,3,3,2,2,2,3,4,2,2,0,0.0,neutral or dissatisfied +58003,96822,Female,Loyal Customer,49,Business travel,Business,781,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +58004,77147,Female,Loyal Customer,45,Business travel,Business,1865,5,5,5,5,2,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +58005,83945,Male,disloyal Customer,44,Business travel,Business,373,4,4,4,1,2,4,5,2,3,3,5,3,4,2,0,0.0,satisfied +58006,64274,Male,Loyal Customer,49,Business travel,Business,3077,3,3,3,3,2,5,5,5,5,5,5,5,5,3,9,0.0,satisfied +58007,129280,Female,Loyal Customer,70,Personal Travel,Business,550,2,0,2,2,3,4,4,5,5,2,2,4,5,5,0,0.0,neutral or dissatisfied +58008,84903,Female,Loyal Customer,63,Personal Travel,Eco,547,2,3,2,4,4,5,2,1,1,2,1,3,1,3,39,32.0,neutral or dissatisfied +58009,25439,Female,disloyal Customer,28,Business travel,Eco,669,2,2,2,4,5,2,5,5,3,4,4,3,3,5,13,4.0,neutral or dissatisfied +58010,90051,Female,Loyal Customer,47,Business travel,Business,2275,4,4,4,4,5,4,5,4,4,4,4,3,4,3,3,0.0,satisfied +58011,48327,Female,Loyal Customer,53,Business travel,Business,522,1,1,1,1,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +58012,54278,Female,Loyal Customer,46,Personal Travel,Eco,1222,2,1,3,3,4,3,3,5,5,3,4,4,5,4,13,2.0,neutral or dissatisfied +58013,1593,Female,Loyal Customer,37,Personal Travel,Eco,140,3,2,0,3,3,0,3,3,4,4,4,2,4,3,20,34.0,neutral or dissatisfied +58014,115630,Male,Loyal Customer,68,Business travel,Business,446,4,2,2,2,2,3,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +58015,13164,Female,disloyal Customer,26,Business travel,Eco Plus,562,2,1,1,4,3,1,3,3,1,1,4,2,3,3,6,29.0,neutral or dissatisfied +58016,25870,Male,Loyal Customer,59,Personal Travel,Eco Plus,692,3,4,3,1,5,3,5,5,3,4,4,5,5,5,43,56.0,neutral or dissatisfied +58017,5704,Female,Loyal Customer,47,Personal Travel,Eco,147,2,4,2,1,5,5,5,4,4,2,5,3,4,3,0,8.0,neutral or dissatisfied +58018,42347,Male,Loyal Customer,34,Personal Travel,Eco,550,1,4,1,1,4,1,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +58019,67251,Female,Loyal Customer,15,Personal Travel,Eco,1119,3,4,4,1,4,4,4,4,3,4,4,3,4,4,3,0.0,neutral or dissatisfied +58020,118101,Female,Loyal Customer,50,Business travel,Business,1999,5,5,5,5,3,5,5,4,4,4,4,4,4,5,3,0.0,satisfied +58021,83606,Male,disloyal Customer,27,Business travel,Business,409,5,5,5,1,3,5,3,3,4,5,5,3,5,3,0,0.0,satisfied +58022,100978,Female,Loyal Customer,54,Business travel,Business,1524,2,5,5,5,3,4,3,2,2,2,2,1,2,2,41,23.0,neutral or dissatisfied +58023,1719,Male,Loyal Customer,41,Business travel,Business,364,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +58024,108613,Female,Loyal Customer,45,Personal Travel,Eco,696,3,3,3,4,2,4,3,1,1,3,1,1,1,4,108,116.0,neutral or dissatisfied +58025,75673,Male,Loyal Customer,53,Business travel,Business,3933,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,42.0,satisfied +58026,71641,Female,Loyal Customer,31,Personal Travel,Eco,1197,4,4,4,3,3,4,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +58027,116805,Male,Loyal Customer,49,Business travel,Business,3145,3,3,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +58028,53063,Female,Loyal Customer,70,Personal Travel,Eco,1208,2,4,2,3,3,4,3,1,1,2,1,3,1,3,39,53.0,neutral or dissatisfied +58029,75482,Male,Loyal Customer,44,Personal Travel,Eco,2218,2,1,2,2,1,2,1,1,1,4,3,4,3,1,0,0.0,neutral or dissatisfied +58030,60661,Female,Loyal Customer,45,Personal Travel,Eco,1620,2,4,2,4,2,3,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +58031,68254,Male,Loyal Customer,26,Personal Travel,Eco,432,4,4,4,3,4,4,4,4,3,2,1,5,5,4,0,0.0,satisfied +58032,73370,Female,disloyal Customer,57,Business travel,Business,1144,5,5,5,1,3,5,3,3,4,2,5,4,5,3,0,0.0,satisfied +58033,17917,Female,disloyal Customer,26,Business travel,Eco,389,4,2,4,2,1,4,4,1,1,5,2,1,1,1,51,54.0,neutral or dissatisfied +58034,40742,Male,Loyal Customer,40,Business travel,Business,590,1,1,1,1,4,5,5,5,5,5,5,4,5,3,12,9.0,satisfied +58035,70026,Male,disloyal Customer,20,Business travel,Eco,583,2,2,2,3,5,2,5,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +58036,18358,Female,Loyal Customer,36,Personal Travel,Business,169,2,5,2,3,3,4,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +58037,60043,Male,Loyal Customer,31,Business travel,Business,1797,5,5,5,5,3,4,3,3,4,2,5,3,5,3,0,0.0,satisfied +58038,115332,Female,Loyal Customer,42,Business travel,Business,325,0,0,0,4,3,5,4,5,5,5,5,4,5,5,77,78.0,satisfied +58039,48101,Female,Loyal Customer,44,Business travel,Business,2495,5,5,5,5,4,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +58040,59321,Female,Loyal Customer,26,Business travel,Business,2486,4,4,4,4,2,2,2,2,3,3,4,4,5,2,13,0.0,satisfied +58041,68272,Male,Loyal Customer,54,Business travel,Business,631,2,2,5,2,3,4,5,4,4,4,4,4,4,5,6,0.0,satisfied +58042,62869,Male,Loyal Customer,53,Business travel,Business,3230,1,5,5,5,1,4,4,1,1,1,1,3,1,4,3,0.0,neutral or dissatisfied +58043,249,Male,disloyal Customer,20,Business travel,Eco,319,2,0,2,2,5,2,5,5,1,5,5,2,3,5,0,0.0,neutral or dissatisfied +58044,14806,Female,disloyal Customer,56,Business travel,Eco,95,3,2,3,3,3,3,5,3,1,3,3,4,4,3,3,0.0,neutral or dissatisfied +58045,103807,Male,Loyal Customer,44,Business travel,Business,1991,2,2,2,2,5,4,5,5,5,5,5,5,5,4,4,0.0,satisfied +58046,21856,Female,Loyal Customer,25,Business travel,Business,1823,3,3,3,3,4,4,4,4,3,2,5,1,2,4,0,0.0,satisfied +58047,38990,Female,Loyal Customer,56,Business travel,Business,3150,5,5,5,5,2,3,2,5,5,5,5,4,5,5,0,2.0,satisfied +58048,124084,Male,Loyal Customer,34,Personal Travel,Business,529,4,4,4,4,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +58049,25458,Male,Loyal Customer,26,Business travel,Eco Plus,669,1,1,4,1,1,1,2,1,4,3,2,1,3,1,0,0.0,neutral or dissatisfied +58050,33616,Female,disloyal Customer,22,Business travel,Eco,399,3,1,3,3,2,3,2,2,2,3,4,4,4,2,52,46.0,neutral or dissatisfied +58051,86159,Male,Loyal Customer,42,Business travel,Business,3015,1,1,1,1,2,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +58052,46401,Female,Loyal Customer,64,Personal Travel,Eco Plus,1081,4,4,4,2,3,2,3,4,4,4,4,5,4,1,81,85.0,neutral or dissatisfied +58053,60530,Male,Loyal Customer,65,Personal Travel,Eco,862,4,5,4,3,3,4,3,3,4,3,4,4,1,3,3,0.0,neutral or dissatisfied +58054,102693,Male,Loyal Customer,34,Business travel,Business,3695,2,2,2,2,4,2,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +58055,127093,Female,disloyal Customer,28,Business travel,Eco,370,1,3,1,3,1,1,1,1,3,3,3,1,3,1,0,1.0,neutral or dissatisfied +58056,49876,Male,Loyal Customer,55,Business travel,Business,373,2,2,2,2,3,4,1,4,4,4,4,4,4,2,0,0.0,satisfied +58057,63424,Male,Loyal Customer,12,Personal Travel,Eco,337,2,4,3,3,2,3,2,2,4,2,5,5,5,2,0,1.0,neutral or dissatisfied +58058,12284,Male,disloyal Customer,27,Business travel,Eco,253,2,3,2,4,4,2,4,4,3,2,4,2,3,4,0,8.0,neutral or dissatisfied +58059,74128,Male,Loyal Customer,33,Business travel,Business,1843,3,3,3,3,2,2,2,2,3,2,5,3,5,2,59,64.0,satisfied +58060,39169,Male,Loyal Customer,53,Business travel,Business,2387,4,4,4,4,4,3,3,1,1,1,4,4,1,1,0,0.0,neutral or dissatisfied +58061,54585,Male,Loyal Customer,42,Business travel,Business,965,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +58062,105873,Male,disloyal Customer,24,Business travel,Business,787,0,4,0,1,5,0,5,5,3,4,5,3,5,5,25,11.0,satisfied +58063,102669,Female,Loyal Customer,48,Business travel,Business,3586,5,5,5,5,4,5,4,3,3,4,3,5,3,5,7,0.0,satisfied +58064,157,Male,Loyal Customer,60,Business travel,Business,3415,1,3,3,3,1,3,4,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +58065,45145,Female,Loyal Customer,65,Business travel,Eco,174,3,3,3,3,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +58066,48584,Female,Loyal Customer,68,Personal Travel,Eco,833,2,5,2,2,3,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +58067,18397,Female,disloyal Customer,44,Business travel,Business,284,3,3,3,3,3,3,3,3,5,5,5,4,4,3,0,23.0,neutral or dissatisfied +58068,14051,Female,Loyal Customer,32,Personal Travel,Eco,335,3,4,3,2,5,3,4,5,3,4,4,4,5,5,0,16.0,neutral or dissatisfied +58069,37294,Male,Loyal Customer,36,Business travel,Eco,944,2,3,3,3,2,2,2,2,2,3,4,2,5,2,0,1.0,satisfied +58070,116488,Male,Loyal Customer,67,Personal Travel,Eco,404,3,5,4,3,4,4,4,4,4,2,4,5,4,4,10,6.0,neutral or dissatisfied +58071,99583,Female,Loyal Customer,68,Personal Travel,Eco,829,0,5,1,1,3,4,4,4,4,1,2,5,4,3,0,4.0,satisfied +58072,46534,Male,Loyal Customer,71,Business travel,Eco,73,5,1,5,1,5,5,5,5,1,4,5,1,2,5,0,5.0,satisfied +58073,84005,Female,Loyal Customer,31,Personal Travel,Eco,373,1,3,1,4,4,1,5,4,2,1,2,4,3,4,12,14.0,neutral or dissatisfied +58074,109546,Male,Loyal Customer,10,Personal Travel,Eco,861,2,4,2,3,2,2,2,2,5,2,4,4,5,2,32,15.0,neutral or dissatisfied +58075,61832,Male,Loyal Customer,52,Business travel,Business,1464,2,2,2,2,2,5,5,2,2,3,2,4,2,4,0,0.0,satisfied +58076,84165,Male,Loyal Customer,32,Business travel,Eco Plus,503,4,2,2,2,4,4,4,1,1,4,3,4,1,4,266,270.0,neutral or dissatisfied +58077,68971,Male,Loyal Customer,74,Business travel,Business,300,3,3,3,3,3,5,2,4,4,4,4,1,4,2,0,0.0,satisfied +58078,100745,Male,Loyal Customer,17,Personal Travel,Eco,328,2,2,2,2,2,4,4,2,3,2,2,4,4,4,137,130.0,neutral or dissatisfied +58079,94594,Male,disloyal Customer,27,Business travel,Business,323,5,5,5,1,5,5,5,5,5,4,4,5,5,5,0,0.0,satisfied +58080,21663,Male,Loyal Customer,30,Business travel,Business,3800,1,1,1,1,4,4,4,4,3,5,4,5,1,4,0,7.0,satisfied +58081,73365,Female,Loyal Customer,40,Business travel,Eco,1197,2,2,2,2,2,2,2,2,3,5,2,2,2,2,34,37.0,neutral or dissatisfied +58082,56118,Female,Loyal Customer,47,Business travel,Business,1504,3,1,1,1,4,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +58083,20638,Male,Loyal Customer,46,Business travel,Business,911,2,1,1,1,4,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +58084,122065,Female,Loyal Customer,47,Business travel,Business,185,4,2,2,2,4,4,3,2,2,3,4,3,2,4,0,0.0,neutral or dissatisfied +58085,87862,Female,Loyal Customer,52,Personal Travel,Eco,214,3,0,0,2,2,4,5,5,5,0,5,5,5,5,1,6.0,neutral or dissatisfied +58086,39062,Male,Loyal Customer,49,Business travel,Business,2386,3,4,4,4,5,3,2,3,3,3,3,2,3,2,46,57.0,neutral or dissatisfied +58087,111659,Female,Loyal Customer,54,Business travel,Business,2502,5,5,5,5,3,5,4,4,4,4,4,5,4,3,3,0.0,satisfied +58088,103743,Male,Loyal Customer,43,Business travel,Business,405,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +58089,34596,Female,disloyal Customer,39,Business travel,Eco,998,3,3,3,3,4,3,4,4,2,4,3,4,3,4,0,2.0,neutral or dissatisfied +58090,123437,Male,disloyal Customer,40,Business travel,Business,2296,1,2,2,5,1,2,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +58091,13570,Female,Loyal Customer,69,Personal Travel,Eco,214,2,3,2,4,4,4,4,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +58092,33235,Male,disloyal Customer,38,Business travel,Business,216,4,4,4,4,4,4,4,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +58093,55814,Female,Loyal Customer,43,Business travel,Business,1416,3,3,3,3,2,5,4,2,2,2,2,3,2,5,0,6.0,satisfied +58094,38181,Male,Loyal Customer,9,Personal Travel,Eco,1237,1,4,1,3,2,1,2,2,5,4,4,4,4,2,47,28.0,neutral or dissatisfied +58095,121744,Female,Loyal Customer,56,Personal Travel,Eco,1475,2,5,2,3,4,3,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +58096,41074,Male,Loyal Customer,55,Business travel,Business,3932,3,3,3,3,4,5,3,5,5,5,4,1,5,4,9,3.0,satisfied +58097,90128,Male,Loyal Customer,49,Business travel,Eco,1086,3,3,3,3,3,3,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +58098,118661,Female,disloyal Customer,36,Business travel,Eco,451,2,4,2,3,2,2,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +58099,3990,Male,Loyal Customer,14,Personal Travel,Business,425,2,4,5,1,3,5,3,3,4,5,4,3,5,3,3,20.0,neutral or dissatisfied +58100,51885,Female,Loyal Customer,25,Business travel,Business,1917,1,1,1,1,4,4,4,4,5,3,3,4,5,4,2,3.0,satisfied +58101,33219,Female,Loyal Customer,32,Business travel,Eco Plus,101,3,5,5,5,3,3,3,3,3,5,3,2,3,3,0,1.0,neutral or dissatisfied +58102,80244,Female,disloyal Customer,57,Business travel,Eco,1269,3,3,3,3,5,3,5,5,3,2,3,4,4,5,8,0.0,neutral or dissatisfied +58103,64276,Female,Loyal Customer,52,Business travel,Business,3295,1,1,1,1,5,4,4,5,5,5,5,4,5,5,9,0.0,satisfied +58104,104072,Male,Loyal Customer,41,Business travel,Business,1634,3,5,4,5,3,2,1,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +58105,34733,Male,Loyal Customer,67,Business travel,Business,3561,5,5,5,5,3,4,5,4,4,4,3,3,4,5,0,0.0,satisfied +58106,12771,Female,Loyal Customer,42,Business travel,Eco Plus,289,1,4,5,4,3,4,3,1,1,1,1,2,1,1,108,93.0,neutral or dissatisfied +58107,54513,Female,Loyal Customer,37,Business travel,Business,3138,2,1,1,1,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +58108,8647,Male,Loyal Customer,57,Business travel,Business,3107,4,4,4,4,5,5,5,5,5,5,5,5,5,3,106,104.0,satisfied +58109,50915,Male,Loyal Customer,59,Personal Travel,Eco,153,3,4,3,5,4,3,4,4,3,4,4,3,4,4,0,8.0,neutral or dissatisfied +58110,115320,Female,Loyal Customer,57,Business travel,Eco,446,2,4,2,4,4,4,3,2,2,2,2,3,2,2,8,0.0,neutral or dissatisfied +58111,35127,Female,disloyal Customer,54,Business travel,Eco,950,2,2,2,5,3,2,5,3,1,4,2,4,2,3,10,26.0,neutral or dissatisfied +58112,12076,Female,disloyal Customer,23,Business travel,Eco Plus,376,0,0,0,1,2,0,2,2,2,4,2,1,4,2,0,0.0,satisfied +58113,60326,Female,Loyal Customer,37,Business travel,Business,1024,2,2,2,2,2,5,4,4,4,4,4,4,4,5,17,14.0,satisfied +58114,20099,Male,Loyal Customer,39,Business travel,Eco,466,5,3,5,3,5,5,5,5,2,3,3,5,2,5,120,120.0,satisfied +58115,42501,Male,Loyal Customer,37,Business travel,Business,1619,2,2,2,2,5,2,3,5,5,5,5,4,5,1,8,0.0,satisfied +58116,89027,Female,disloyal Customer,16,Business travel,Eco,857,3,3,3,2,2,3,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +58117,85778,Male,Loyal Customer,53,Business travel,Business,2697,2,2,2,2,5,5,4,2,2,2,2,3,2,5,6,0.0,satisfied +58118,106182,Female,Loyal Customer,31,Personal Travel,Eco,444,3,4,3,1,5,3,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +58119,85059,Female,Loyal Customer,50,Business travel,Business,3528,1,1,1,1,5,4,5,5,5,5,5,4,5,4,34,20.0,satisfied +58120,83633,Male,Loyal Customer,27,Personal Travel,Eco Plus,409,1,1,4,4,2,4,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +58121,37468,Male,Loyal Customer,41,Business travel,Eco,1069,4,2,2,2,4,4,4,4,3,1,1,1,2,4,27,50.0,neutral or dissatisfied +58122,30554,Male,Loyal Customer,56,Personal Travel,Eco Plus,896,5,5,5,5,3,5,3,3,4,2,4,3,5,3,0,4.0,satisfied +58123,116896,Male,Loyal Customer,42,Business travel,Eco,304,3,5,5,5,3,3,3,3,4,4,4,3,4,3,48,38.0,neutral or dissatisfied +58124,106586,Male,Loyal Customer,58,Personal Travel,Eco,333,2,5,5,2,5,5,5,5,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +58125,105501,Male,disloyal Customer,16,Business travel,Eco,516,2,2,1,4,3,1,3,3,2,4,3,4,4,3,1,0.0,neutral or dissatisfied +58126,126070,Female,Loyal Customer,57,Business travel,Business,468,1,1,1,1,4,5,5,4,4,4,4,5,4,5,41,37.0,satisfied +58127,38615,Male,Loyal Customer,8,Personal Travel,Eco,231,2,5,0,3,1,0,5,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +58128,124098,Female,Loyal Customer,46,Business travel,Business,3346,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +58129,2101,Male,Loyal Customer,39,Personal Travel,Eco,812,2,1,2,3,3,2,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +58130,62571,Female,disloyal Customer,27,Business travel,Eco,1115,2,2,2,3,3,2,3,3,3,2,3,3,3,3,6,0.0,neutral or dissatisfied +58131,24836,Female,Loyal Customer,65,Personal Travel,Eco,861,2,5,2,4,5,4,5,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +58132,78134,Male,Loyal Customer,16,Personal Travel,Business,259,4,3,4,4,1,4,1,1,3,2,4,1,4,1,24,13.0,neutral or dissatisfied +58133,75416,Male,Loyal Customer,32,Business travel,Business,2218,3,3,3,3,3,4,3,3,5,5,5,3,5,3,0,0.0,satisfied +58134,32215,Female,Loyal Customer,42,Business travel,Eco,101,5,2,2,2,3,3,3,5,5,5,5,2,5,3,3,7.0,satisfied +58135,119002,Female,disloyal Customer,37,Business travel,Eco,459,2,2,3,2,3,3,2,3,3,3,3,2,3,3,0,6.0,neutral or dissatisfied +58136,68508,Male,Loyal Customer,58,Personal Travel,Eco,1303,1,5,1,5,1,1,3,1,3,5,4,3,4,1,0,7.0,neutral or dissatisfied +58137,89795,Female,Loyal Customer,53,Personal Travel,Eco,1069,3,4,3,3,5,4,4,4,4,3,4,5,4,5,15,11.0,neutral or dissatisfied +58138,13123,Male,Loyal Customer,48,Business travel,Business,562,1,0,0,3,3,3,4,5,5,0,5,4,5,3,5,15.0,neutral or dissatisfied +58139,126885,Female,Loyal Customer,21,Personal Travel,Eco,2125,1,3,2,3,1,2,4,1,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +58140,11860,Female,Loyal Customer,53,Business travel,Eco,912,2,4,4,4,1,2,3,2,2,2,2,3,2,3,4,5.0,neutral or dissatisfied +58141,59401,Male,Loyal Customer,18,Personal Travel,Eco,2338,4,2,4,3,2,4,2,2,4,3,4,3,4,2,38,1.0,neutral or dissatisfied +58142,82795,Male,Loyal Customer,38,Business travel,Business,3833,0,0,0,1,2,4,5,3,3,2,2,4,3,5,0,0.0,satisfied +58143,47046,Female,Loyal Customer,71,Business travel,Business,3752,2,5,3,5,1,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +58144,12031,Male,Loyal Customer,33,Business travel,Business,376,4,4,5,4,5,5,5,5,4,3,4,1,1,5,40,39.0,satisfied +58145,29289,Female,Loyal Customer,29,Business travel,Business,834,1,2,2,2,1,1,1,1,4,5,2,4,2,1,0,0.0,neutral or dissatisfied +58146,27542,Male,Loyal Customer,15,Personal Travel,Eco,679,3,5,3,3,1,3,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +58147,90915,Female,Loyal Customer,55,Business travel,Business,270,5,5,5,5,2,2,3,5,5,5,5,3,5,5,0,0.0,satisfied +58148,87520,Female,Loyal Customer,44,Personal Travel,Eco,321,3,2,3,3,3,3,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +58149,78486,Female,disloyal Customer,22,Business travel,Business,666,5,0,5,2,5,5,5,5,3,3,5,4,5,5,0,0.0,satisfied +58150,116156,Female,Loyal Customer,48,Personal Travel,Eco,447,3,5,3,3,5,4,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +58151,122509,Male,disloyal Customer,27,Business travel,Eco,930,3,2,2,3,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +58152,67560,Male,disloyal Customer,35,Business travel,Business,1464,1,1,1,3,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +58153,119492,Female,Loyal Customer,50,Business travel,Business,2165,4,5,5,5,2,2,1,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +58154,61835,Male,Loyal Customer,32,Business travel,Business,1379,2,2,2,2,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +58155,83476,Male,Loyal Customer,47,Business travel,Business,946,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +58156,31321,Male,Loyal Customer,26,Personal Travel,Eco,680,3,4,3,1,2,3,2,2,5,3,5,4,5,2,0,11.0,neutral or dissatisfied +58157,72266,Male,Loyal Customer,22,Business travel,Eco,919,3,3,5,3,3,3,2,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +58158,91331,Female,Loyal Customer,60,Personal Travel,Eco Plus,404,2,4,2,1,2,5,5,1,1,2,5,4,1,3,77,108.0,neutral or dissatisfied +58159,38469,Male,disloyal Customer,25,Business travel,Eco,846,2,2,2,3,2,2,2,2,5,4,1,2,3,2,4,3.0,neutral or dissatisfied +58160,95129,Female,Loyal Customer,12,Personal Travel,Eco,189,1,5,1,2,4,1,4,4,1,5,1,4,4,4,58,63.0,neutral or dissatisfied +58161,3338,Female,Loyal Customer,40,Business travel,Eco,240,2,2,2,2,2,2,2,2,4,3,4,1,4,2,0,8.0,neutral or dissatisfied +58162,90623,Female,Loyal Customer,67,Business travel,Business,404,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,7.0,satisfied +58163,97517,Female,Loyal Customer,45,Business travel,Business,2414,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,17.0,satisfied +58164,118768,Male,Loyal Customer,59,Personal Travel,Eco,370,2,3,2,2,5,2,5,5,1,2,3,4,3,5,28,27.0,neutral or dissatisfied +58165,87567,Female,disloyal Customer,25,Business travel,Eco,432,2,3,2,3,1,2,1,1,2,3,4,4,3,1,32,23.0,neutral or dissatisfied +58166,25085,Male,Loyal Customer,24,Business travel,Business,549,2,2,3,2,5,5,5,5,3,3,3,1,5,5,0,1.0,satisfied +58167,49304,Male,Loyal Customer,44,Business travel,Eco,266,5,5,5,5,4,5,4,4,2,5,5,1,4,4,0,14.0,satisfied +58168,121065,Female,Loyal Customer,56,Business travel,Business,2892,2,2,2,2,5,4,4,2,2,2,2,4,2,3,34,24.0,satisfied +58169,76595,Male,Loyal Customer,37,Business travel,Business,1862,2,2,2,2,4,4,4,2,2,2,2,3,2,2,38,26.0,neutral or dissatisfied +58170,39476,Male,Loyal Customer,38,Business travel,Business,3161,1,1,5,1,5,1,2,2,2,2,2,4,2,2,0,0.0,satisfied +58171,84627,Female,Loyal Customer,37,Personal Travel,Eco,669,4,5,4,3,1,4,3,1,3,2,4,3,5,1,31,27.0,neutral or dissatisfied +58172,120784,Female,Loyal Customer,63,Personal Travel,Eco,678,4,2,4,4,3,4,3,2,2,4,2,2,2,4,15,25.0,neutral or dissatisfied +58173,50228,Male,Loyal Customer,39,Business travel,Business,89,2,2,5,2,4,2,4,4,4,4,5,2,4,1,0,0.0,satisfied +58174,50610,Male,Loyal Customer,58,Personal Travel,Eco,199,4,1,0,3,5,0,3,5,3,4,2,1,3,5,0,0.0,neutral or dissatisfied +58175,27853,Female,Loyal Customer,35,Personal Travel,Eco,909,1,4,1,5,3,1,3,3,3,3,3,3,1,3,70,,neutral or dissatisfied +58176,4551,Female,Loyal Customer,36,Personal Travel,Eco Plus,719,2,5,3,3,4,3,4,4,4,1,3,4,1,4,6,11.0,neutral or dissatisfied +58177,114372,Male,Loyal Customer,28,Business travel,Business,957,3,3,3,3,5,5,5,5,5,2,4,3,5,5,0,1.0,satisfied +58178,37960,Female,Loyal Customer,49,Business travel,Business,1185,2,2,2,2,5,5,4,5,5,5,5,5,5,3,28,17.0,satisfied +58179,68554,Female,Loyal Customer,69,Personal Travel,Business,2136,1,5,1,4,2,5,4,1,1,1,1,4,1,3,0,1.0,neutral or dissatisfied +58180,46932,Male,Loyal Customer,77,Business travel,Business,3583,2,4,5,4,1,1,2,2,2,2,2,1,2,3,0,39.0,neutral or dissatisfied +58181,120700,Male,Loyal Customer,61,Personal Travel,Eco,280,1,4,1,2,4,1,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +58182,72966,Male,disloyal Customer,24,Business travel,Business,1096,5,0,5,4,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +58183,36084,Female,Loyal Customer,58,Personal Travel,Eco,399,2,5,3,1,4,4,5,4,4,3,4,5,4,5,15,12.0,neutral or dissatisfied +58184,127932,Male,Loyal Customer,62,Personal Travel,Eco,2300,3,4,3,4,3,3,3,3,3,4,4,5,5,3,0,5.0,neutral or dissatisfied +58185,75718,Female,disloyal Customer,29,Business travel,Business,868,4,4,4,1,4,4,2,4,5,5,4,5,4,4,16,13.0,satisfied +58186,81275,Male,Loyal Customer,60,Business travel,Business,1020,2,3,3,3,2,3,3,2,2,2,2,2,2,1,29,6.0,neutral or dissatisfied +58187,13334,Male,Loyal Customer,19,Business travel,Business,748,3,4,4,4,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +58188,74824,Male,Loyal Customer,57,Personal Travel,Eco Plus,1126,2,4,2,4,5,2,1,5,3,3,4,4,5,5,9,0.0,neutral or dissatisfied +58189,100391,Female,Loyal Customer,33,Personal Travel,Eco,1034,2,5,2,2,5,2,2,5,3,2,4,5,4,5,26,21.0,neutral or dissatisfied +58190,97360,Male,Loyal Customer,67,Business travel,Eco,620,4,2,5,2,4,4,4,4,5,3,1,3,4,4,6,0.0,satisfied +58191,117603,Female,Loyal Customer,47,Business travel,Business,1782,3,1,1,1,5,3,4,3,3,2,3,3,3,2,23,16.0,neutral or dissatisfied +58192,15912,Female,Loyal Customer,40,Business travel,Business,3096,2,2,2,2,4,5,5,4,4,4,4,4,4,1,0,8.0,satisfied +58193,110305,Male,disloyal Customer,38,Business travel,Business,919,3,3,3,2,1,3,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +58194,101366,Female,Loyal Customer,64,Personal Travel,Eco,2237,4,5,3,1,2,5,5,5,5,3,5,4,5,4,7,0.0,satisfied +58195,43027,Female,disloyal Customer,37,Business travel,Eco,173,1,3,1,3,4,1,4,4,2,3,1,4,2,4,0,0.0,neutral or dissatisfied +58196,40060,Male,disloyal Customer,14,Business travel,Business,866,5,0,5,4,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +58197,81757,Male,disloyal Customer,36,Business travel,Eco,1416,1,1,1,3,4,1,4,4,2,1,2,2,3,4,2,21.0,neutral or dissatisfied +58198,61316,Female,Loyal Customer,26,Business travel,Business,909,5,5,4,5,4,4,4,4,5,5,4,4,4,4,2,0.0,satisfied +58199,105493,Female,Loyal Customer,46,Business travel,Business,516,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +58200,72703,Female,disloyal Customer,26,Business travel,Business,929,5,5,5,1,4,0,4,4,3,3,5,5,4,4,0,0.0,satisfied +58201,1529,Male,Loyal Customer,42,Business travel,Business,3725,2,2,2,2,2,4,4,3,3,4,3,4,3,4,10,9.0,satisfied +58202,91336,Male,Loyal Customer,49,Personal Travel,Eco Plus,406,3,4,3,4,4,3,2,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +58203,118737,Male,Loyal Customer,11,Personal Travel,Eco,621,1,5,1,4,4,1,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +58204,104854,Female,Loyal Customer,53,Business travel,Business,2170,0,0,0,1,3,4,5,4,4,4,4,5,4,5,18,7.0,satisfied +58205,22186,Female,Loyal Customer,36,Business travel,Eco,633,1,3,2,3,1,1,1,1,4,5,3,3,4,1,56,44.0,neutral or dissatisfied +58206,124339,Male,Loyal Customer,21,Business travel,Business,3815,4,4,4,4,3,3,3,3,4,3,5,4,4,3,0,0.0,satisfied +58207,62630,Female,Loyal Customer,14,Personal Travel,Eco,1846,1,4,1,1,5,1,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +58208,72397,Female,Loyal Customer,71,Business travel,Business,3404,3,3,2,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +58209,74997,Male,Loyal Customer,20,Business travel,Business,2454,2,2,2,2,2,2,2,2,3,3,4,4,5,2,0,0.0,satisfied +58210,65487,Female,Loyal Customer,59,Personal Travel,Eco,1303,3,5,3,3,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +58211,76394,Female,Loyal Customer,22,Personal Travel,Eco,931,3,5,3,3,5,3,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +58212,2384,Female,Loyal Customer,44,Business travel,Business,2076,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +58213,122101,Male,Loyal Customer,48,Personal Travel,Eco,130,4,4,4,1,5,4,5,5,1,1,2,3,1,5,0,2.0,neutral or dissatisfied +58214,24707,Female,disloyal Customer,44,Business travel,Eco,397,1,4,1,3,4,1,4,4,2,3,4,4,4,4,0,0.0,neutral or dissatisfied +58215,92759,Female,Loyal Customer,65,Personal Travel,Eco,1276,4,2,4,4,4,2,2,3,3,2,4,2,3,2,401,435.0,neutral or dissatisfied +58216,92301,Male,Loyal Customer,41,Business travel,Business,2486,2,2,2,2,3,5,5,5,5,5,5,4,5,3,0,3.0,satisfied +58217,50813,Male,Loyal Customer,8,Personal Travel,Eco,86,1,5,0,2,5,0,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +58218,80174,Female,Loyal Customer,33,Business travel,Eco,2475,3,5,5,5,3,3,3,3,1,4,4,3,1,3,0,10.0,neutral or dissatisfied +58219,20616,Male,Loyal Customer,29,Personal Travel,Eco,864,1,1,1,3,4,1,4,4,3,1,4,1,3,4,0,1.0,neutral or dissatisfied +58220,125947,Female,Loyal Customer,13,Personal Travel,Eco,951,1,3,1,2,3,1,3,3,3,2,3,3,5,3,2,8.0,neutral or dissatisfied +58221,109655,Female,Loyal Customer,25,Business travel,Business,2406,1,5,5,5,1,1,1,1,3,1,3,4,4,1,13,12.0,neutral or dissatisfied +58222,115577,Female,Loyal Customer,38,Business travel,Eco,372,4,2,2,2,4,4,4,4,4,3,3,1,3,4,127,131.0,neutral or dissatisfied +58223,123168,Male,disloyal Customer,23,Business travel,Eco,590,2,2,3,3,2,3,3,2,4,1,4,2,4,2,0,7.0,neutral or dissatisfied +58224,85621,Male,Loyal Customer,57,Personal Travel,Eco,259,1,4,1,4,3,1,3,3,2,1,4,5,3,3,2,8.0,neutral or dissatisfied +58225,6654,Male,Loyal Customer,50,Business travel,Business,3545,4,4,4,4,3,4,5,4,4,5,4,4,4,5,6,65.0,satisfied +58226,104724,Female,Loyal Customer,32,Business travel,Business,2695,5,5,2,5,4,4,4,4,5,5,5,4,4,4,6,13.0,satisfied +58227,78785,Female,disloyal Customer,26,Business travel,Eco,447,2,1,2,4,1,2,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +58228,45674,Female,disloyal Customer,27,Business travel,Eco,896,3,3,3,3,5,3,2,5,2,5,5,3,2,5,0,0.0,neutral or dissatisfied +58229,21823,Female,Loyal Customer,58,Business travel,Eco,907,3,4,4,4,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +58230,42010,Male,Loyal Customer,22,Business travel,Business,241,1,1,1,1,5,5,5,5,5,1,4,3,4,5,0,0.0,satisfied +58231,61876,Male,Loyal Customer,51,Business travel,Business,2521,1,1,1,1,2,5,4,4,4,4,4,4,4,4,80,63.0,satisfied +58232,123444,Male,Loyal Customer,29,Business travel,Business,2125,1,1,1,1,5,5,5,5,3,2,4,5,5,5,9,14.0,satisfied +58233,45762,Female,Loyal Customer,57,Business travel,Eco,216,3,2,2,2,1,1,3,3,3,3,3,2,3,2,0,0.0,satisfied +58234,103188,Female,Loyal Customer,17,Personal Travel,Business,814,3,5,3,2,2,3,3,2,3,4,5,4,5,2,24,28.0,neutral or dissatisfied +58235,20983,Male,Loyal Customer,18,Personal Travel,Eco,689,2,5,2,3,4,2,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +58236,85402,Male,Loyal Customer,58,Business travel,Business,2352,3,3,3,3,4,5,4,4,4,4,4,5,4,4,22,16.0,satisfied +58237,21897,Male,Loyal Customer,26,Business travel,Business,3840,2,2,2,2,4,4,4,4,4,4,5,2,5,4,7,10.0,satisfied +58238,32710,Female,Loyal Customer,44,Business travel,Business,3961,0,3,0,2,4,2,5,3,3,3,3,3,3,2,0,0.0,satisfied +58239,98851,Male,Loyal Customer,16,Personal Travel,Business,1751,2,5,2,1,1,2,1,1,3,2,2,5,4,1,0,0.0,neutral or dissatisfied +58240,86693,Female,Loyal Customer,43,Business travel,Business,1747,2,2,2,2,2,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +58241,25011,Male,Loyal Customer,41,Business travel,Business,3098,1,2,2,2,1,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +58242,1680,Male,Loyal Customer,41,Personal Travel,Eco,561,4,5,4,1,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +58243,116029,Female,Loyal Customer,44,Personal Travel,Eco,325,2,1,2,4,1,4,4,3,3,2,3,1,3,4,25,18.0,neutral or dissatisfied +58244,16062,Male,Loyal Customer,46,Business travel,Business,744,1,1,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +58245,72977,Female,disloyal Customer,8,Business travel,Eco,1096,2,2,2,3,4,2,4,4,2,2,4,4,4,4,0,3.0,neutral or dissatisfied +58246,44268,Male,Loyal Customer,38,Personal Travel,Eco,118,4,5,4,1,5,4,5,5,5,4,2,2,1,5,0,13.0,neutral or dissatisfied +58247,128115,Male,Loyal Customer,54,Business travel,Business,1587,4,4,4,4,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +58248,51830,Male,Loyal Customer,45,Business travel,Eco Plus,425,5,3,3,3,5,5,5,5,3,4,5,2,1,5,0,0.0,satisfied +58249,120877,Female,Loyal Customer,25,Business travel,Business,992,1,4,4,4,1,1,1,1,3,1,3,1,3,1,0,3.0,neutral or dissatisfied +58250,98415,Female,Loyal Customer,52,Business travel,Business,2176,4,4,4,4,4,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +58251,112654,Male,Loyal Customer,55,Business travel,Business,3690,5,5,2,5,4,4,4,5,5,5,5,3,5,3,2,0.0,satisfied +58252,5338,Female,Loyal Customer,56,Business travel,Business,2176,3,3,3,3,5,5,5,5,2,5,5,5,3,5,118,161.0,satisfied +58253,48030,Female,Loyal Customer,47,Business travel,Eco,984,4,1,1,1,3,5,2,4,4,4,4,1,4,5,0,0.0,satisfied +58254,97591,Male,Loyal Customer,45,Business travel,Business,2004,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +58255,81659,Female,disloyal Customer,29,Business travel,Business,907,5,4,4,3,5,4,5,5,4,4,4,5,4,5,10,11.0,satisfied +58256,93288,Male,Loyal Customer,65,Personal Travel,Eco,867,4,4,4,3,2,4,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +58257,93172,Male,Loyal Customer,55,Personal Travel,Eco,1066,1,4,1,5,4,1,5,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +58258,10066,Female,Loyal Customer,56,Business travel,Business,596,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +58259,89040,Female,disloyal Customer,29,Business travel,Business,1473,4,3,3,2,5,3,5,5,5,4,3,5,4,5,16,0.0,satisfied +58260,77359,Male,disloyal Customer,23,Business travel,Eco,590,0,3,0,1,4,0,4,4,3,3,5,4,5,4,0,3.0,satisfied +58261,95494,Male,Loyal Customer,61,Business travel,Business,293,0,0,0,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +58262,54617,Female,Loyal Customer,36,Business travel,Business,3237,2,2,2,2,5,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +58263,81832,Male,Loyal Customer,13,Personal Travel,Eco,1416,3,1,3,3,3,3,3,3,1,4,3,4,3,3,19,13.0,neutral or dissatisfied +58264,117321,Female,Loyal Customer,36,Personal Travel,Eco Plus,304,0,4,0,1,1,0,1,1,3,4,4,3,5,1,4,0.0,satisfied +58265,71745,Female,Loyal Customer,58,Business travel,Business,1723,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,4.0,satisfied +58266,5975,Female,Loyal Customer,22,Personal Travel,Business,925,2,4,2,3,5,2,5,5,3,3,5,3,4,5,87,94.0,neutral or dissatisfied +58267,86691,Male,Loyal Customer,49,Business travel,Business,1747,3,3,3,3,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +58268,28568,Female,Loyal Customer,39,Business travel,Business,2562,2,2,2,2,5,3,4,4,4,3,4,3,4,3,0,0.0,satisfied +58269,3021,Male,Loyal Customer,50,Business travel,Eco,522,3,2,2,2,3,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +58270,34949,Female,Loyal Customer,45,Personal Travel,Eco,395,3,5,3,3,2,5,4,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +58271,107774,Female,Loyal Customer,80,Business travel,Business,2101,3,5,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +58272,121880,Male,Loyal Customer,11,Personal Travel,Eco,449,4,3,4,2,2,4,1,2,2,1,2,2,5,2,0,0.0,satisfied +58273,69368,Female,Loyal Customer,33,Business travel,Business,3046,2,2,2,2,5,4,5,2,2,3,2,4,2,3,0,0.0,satisfied +58274,3602,Male,Loyal Customer,21,Personal Travel,Eco,999,5,1,5,1,1,5,1,1,1,3,1,3,2,1,7,43.0,satisfied +58275,106492,Male,Loyal Customer,53,Business travel,Business,3421,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +58276,86277,Female,Loyal Customer,16,Personal Travel,Eco,356,2,1,2,3,4,2,3,4,3,4,3,4,3,4,1,0.0,neutral or dissatisfied +58277,119466,Female,Loyal Customer,32,Business travel,Business,814,5,5,5,5,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +58278,53374,Female,Loyal Customer,60,Business travel,Business,2852,4,4,4,4,4,2,2,5,5,4,5,3,5,4,1,0.0,satisfied +58279,10907,Female,Loyal Customer,41,Business travel,Business,482,2,4,4,4,4,4,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +58280,80264,Female,Loyal Customer,39,Business travel,Business,2363,5,5,5,5,5,4,4,4,4,4,4,5,4,4,63,48.0,satisfied +58281,25250,Female,disloyal Customer,10,Business travel,Eco Plus,787,1,2,1,3,4,1,4,4,2,2,3,3,4,4,1,13.0,neutral or dissatisfied +58282,11473,Female,disloyal Customer,36,Business travel,Eco Plus,295,2,3,3,1,4,3,4,4,1,5,4,5,2,4,4,0.0,neutral or dissatisfied +58283,43239,Female,Loyal Customer,40,Business travel,Business,3200,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +58284,42683,Female,Loyal Customer,38,Business travel,Eco,516,4,4,5,4,4,4,4,4,2,5,1,1,1,4,0,5.0,satisfied +58285,21704,Male,Loyal Customer,54,Personal Travel,Eco,746,2,4,2,2,2,2,2,2,1,1,5,2,4,2,0,0.0,neutral or dissatisfied +58286,5294,Male,Loyal Customer,67,Personal Travel,Eco,190,2,1,2,3,1,2,1,1,1,4,3,4,4,1,0,0.0,neutral or dissatisfied +58287,110914,Male,disloyal Customer,30,Business travel,Eco,404,3,4,3,4,3,3,3,3,3,5,4,2,4,3,24,17.0,neutral or dissatisfied +58288,125086,Female,Loyal Customer,37,Business travel,Eco,361,2,4,4,4,2,2,2,2,1,2,4,3,4,2,0,27.0,neutral or dissatisfied +58289,51617,Male,disloyal Customer,23,Business travel,Eco,451,3,0,3,2,5,3,5,5,4,5,4,5,2,5,0,0.0,neutral or dissatisfied +58290,7044,Female,Loyal Customer,51,Personal Travel,Eco Plus,299,2,5,3,4,5,5,5,3,3,3,3,5,3,5,9,9.0,neutral or dissatisfied +58291,95289,Female,Loyal Customer,9,Personal Travel,Eco,441,3,5,3,4,1,3,1,1,4,2,1,4,3,1,8,7.0,neutral or dissatisfied +58292,29691,Male,Loyal Customer,37,Business travel,Business,1542,2,2,2,2,4,4,4,5,5,5,5,2,5,3,0,0.0,satisfied +58293,80832,Female,Loyal Customer,21,Business travel,Business,692,1,5,5,5,1,1,1,1,4,1,3,3,4,1,111,102.0,neutral or dissatisfied +58294,88331,Male,Loyal Customer,23,Business travel,Business,1659,3,3,3,3,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +58295,64164,Male,Loyal Customer,67,Personal Travel,Eco,989,1,5,1,2,3,1,3,3,3,2,4,5,5,3,31,3.0,neutral or dissatisfied +58296,112211,Male,Loyal Customer,43,Business travel,Business,1199,3,3,3,3,4,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +58297,114002,Male,Loyal Customer,7,Personal Travel,Eco,1728,5,5,5,5,3,5,3,3,1,4,5,1,4,3,0,0.0,satisfied +58298,118858,Female,Loyal Customer,57,Personal Travel,Eco Plus,621,2,1,2,2,2,2,2,1,1,2,1,1,1,3,0,7.0,neutral or dissatisfied +58299,103442,Male,Loyal Customer,38,Personal Travel,Business,393,2,4,2,1,4,5,5,5,5,2,1,3,5,4,0,0.0,neutral or dissatisfied +58300,23517,Female,Loyal Customer,69,Business travel,Business,3581,5,5,5,5,3,1,1,5,5,5,5,4,5,4,0,0.0,satisfied +58301,99448,Male,Loyal Customer,38,Business travel,Business,3441,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,3.0,satisfied +58302,58732,Male,Loyal Customer,48,Business travel,Business,2582,1,1,1,1,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +58303,20476,Male,Loyal Customer,55,Business travel,Business,130,0,4,0,4,4,4,5,1,1,1,1,5,1,5,19,13.0,satisfied +58304,127538,Male,Loyal Customer,50,Business travel,Business,3976,3,3,3,3,5,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +58305,21175,Male,Loyal Customer,55,Personal Travel,Business,192,3,3,3,4,2,3,3,1,1,3,1,2,1,4,15,14.0,neutral or dissatisfied +58306,34361,Female,disloyal Customer,29,Business travel,Eco,427,1,2,1,4,4,1,4,4,4,5,3,4,3,4,0,0.0,neutral or dissatisfied +58307,76844,Male,Loyal Customer,53,Business travel,Business,1902,4,4,4,4,2,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +58308,28706,Female,Loyal Customer,14,Personal Travel,Business,2554,4,4,4,4,4,1,3,5,2,4,5,3,3,3,0,0.0,neutral or dissatisfied +58309,51113,Male,Loyal Customer,66,Personal Travel,Eco,250,4,4,4,3,2,4,2,2,2,4,4,3,4,2,0,0.0,neutral or dissatisfied +58310,93221,Male,disloyal Customer,38,Business travel,Eco,1460,1,1,1,3,3,1,3,3,2,2,3,3,4,3,1,15.0,neutral or dissatisfied +58311,114962,Male,disloyal Customer,22,Business travel,Business,362,4,0,4,2,4,4,4,4,5,4,4,5,4,4,13,4.0,satisfied +58312,61615,Male,disloyal Customer,27,Business travel,Business,1635,4,4,4,2,2,4,2,2,3,3,4,3,4,2,44,33.0,satisfied +58313,78077,Male,Loyal Customer,18,Business travel,Business,2073,1,1,1,1,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +58314,7955,Female,Loyal Customer,40,Business travel,Business,594,2,2,4,2,3,5,4,5,5,5,5,5,5,4,20,16.0,satisfied +58315,42395,Male,Loyal Customer,28,Business travel,Eco Plus,834,5,1,3,1,5,5,5,5,4,1,4,1,3,5,0,13.0,satisfied +58316,107328,Male,Loyal Customer,54,Business travel,Business,3111,5,5,5,5,4,5,5,4,4,4,4,3,4,3,4,0.0,satisfied +58317,40585,Male,Loyal Customer,39,Business travel,Business,411,3,2,3,2,5,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +58318,58365,Male,Loyal Customer,39,Business travel,Business,599,5,5,5,5,3,4,4,2,2,2,2,4,2,3,59,61.0,satisfied +58319,28121,Female,Loyal Customer,41,Business travel,Eco,550,5,2,2,2,5,5,5,1,5,3,2,5,3,5,248,268.0,satisfied +58320,32161,Female,Loyal Customer,44,Business travel,Business,1788,3,3,5,3,5,4,1,4,4,4,3,2,4,5,0,0.0,satisfied +58321,83091,Female,Loyal Customer,56,Business travel,Eco,1127,1,2,2,2,3,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +58322,39438,Female,Loyal Customer,85,Business travel,Business,1689,3,5,5,5,2,3,2,4,4,3,4,2,3,2,0,0.0,neutral or dissatisfied +58323,105229,Female,disloyal Customer,23,Business travel,Eco,377,2,4,2,4,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +58324,102299,Female,Loyal Customer,50,Business travel,Eco,407,3,2,2,2,2,3,4,4,4,3,4,4,4,3,33,15.0,neutral or dissatisfied +58325,118706,Female,Loyal Customer,68,Personal Travel,Eco,646,2,2,2,3,4,3,2,2,2,2,2,2,2,1,0,1.0,neutral or dissatisfied +58326,127378,Male,Loyal Customer,42,Business travel,Business,3391,2,2,2,2,3,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +58327,27058,Female,Loyal Customer,57,Personal Travel,Eco Plus,1709,3,1,3,4,4,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +58328,59475,Male,Loyal Customer,58,Business travel,Business,758,1,1,3,1,2,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +58329,16860,Male,Loyal Customer,25,Business travel,Business,3689,5,5,5,5,5,5,5,5,2,2,1,3,4,5,16,17.0,satisfied +58330,27647,Male,Loyal Customer,60,Personal Travel,Eco Plus,937,2,5,2,2,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +58331,27671,Male,Loyal Customer,33,Business travel,Business,2322,1,1,1,1,5,5,5,5,4,1,3,2,4,5,0,0.0,satisfied +58332,20597,Male,Loyal Customer,62,Business travel,Eco Plus,633,1,2,2,2,1,1,1,1,1,4,4,1,3,1,0,8.0,neutral or dissatisfied +58333,123641,Male,disloyal Customer,38,Business travel,Business,214,3,2,2,1,5,2,3,5,5,3,5,5,4,5,0,0.0,satisfied +58334,121804,Male,Loyal Customer,50,Business travel,Business,337,0,0,0,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +58335,119493,Female,Loyal Customer,55,Business travel,Business,1524,3,3,3,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +58336,28841,Male,Loyal Customer,25,Business travel,Business,697,2,2,1,2,4,4,4,4,4,3,4,2,3,4,0,0.0,satisfied +58337,109459,Male,Loyal Customer,40,Business travel,Business,3159,2,2,2,2,5,4,4,5,5,5,5,4,5,5,6,0.0,satisfied +58338,26861,Male,Loyal Customer,39,Business travel,Eco Plus,224,3,4,4,4,3,3,3,3,2,4,2,2,1,3,59,63.0,satisfied +58339,12255,Male,Loyal Customer,51,Business travel,Eco,127,5,5,5,5,5,5,5,5,5,1,5,1,3,5,0,0.0,satisfied +58340,128375,Male,Loyal Customer,25,Business travel,Business,1670,1,1,1,1,1,1,1,1,3,4,3,2,4,1,20,16.0,neutral or dissatisfied +58341,38832,Female,Loyal Customer,52,Business travel,Eco Plus,353,4,1,4,1,2,4,3,4,4,4,4,1,4,1,0,0.0,satisfied +58342,59441,Male,Loyal Customer,23,Business travel,Business,606,2,2,2,2,2,2,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +58343,94658,Male,disloyal Customer,59,Business travel,Business,192,3,3,3,4,4,3,4,4,5,3,5,5,5,4,3,0.0,satisfied +58344,54902,Female,Loyal Customer,64,Personal Travel,Eco,862,2,4,2,3,4,4,5,5,5,2,5,3,5,5,1,0.0,neutral or dissatisfied +58345,46160,Female,Loyal Customer,27,Personal Travel,Eco,604,0,5,0,1,0,3,3,5,5,4,5,3,5,3,180,175.0,satisfied +58346,126549,Male,Loyal Customer,25,Personal Travel,Eco,644,3,1,3,4,4,3,4,4,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +58347,113718,Male,Loyal Customer,62,Personal Travel,Eco,397,5,1,5,1,2,5,2,2,3,2,2,4,1,2,3,0.0,satisfied +58348,5245,Male,Loyal Customer,45,Business travel,Business,285,1,0,0,3,3,2,3,4,4,0,2,2,4,3,18,11.0,neutral or dissatisfied +58349,15850,Male,Loyal Customer,47,Business travel,Business,2419,1,2,2,2,3,4,4,1,1,1,1,1,1,3,10,0.0,neutral or dissatisfied +58350,101603,Female,disloyal Customer,21,Business travel,Eco,1139,2,3,3,1,4,3,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +58351,80122,Female,disloyal Customer,41,Business travel,Business,973,5,5,5,5,5,1,1,3,2,4,4,1,5,1,0,0.0,satisfied +58352,86447,Male,disloyal Customer,18,Business travel,Business,749,4,4,4,3,2,4,2,2,3,3,4,5,4,2,0,0.0,satisfied +58353,63589,Male,Loyal Customer,42,Business travel,Business,2133,2,2,2,2,2,4,4,2,2,2,2,5,2,4,9,0.0,satisfied +58354,85032,Male,Loyal Customer,22,Personal Travel,Eco,1590,4,5,4,2,3,4,3,3,1,4,5,3,1,3,0,0.0,neutral or dissatisfied +58355,75587,Male,Loyal Customer,15,Business travel,Business,3495,4,5,5,5,4,4,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +58356,99754,Male,Loyal Customer,26,Personal Travel,Eco,255,4,4,0,1,2,0,2,2,4,4,5,5,4,2,10,12.0,satisfied +58357,93980,Male,disloyal Customer,28,Business travel,Eco,1218,3,4,4,4,1,4,1,1,4,2,3,3,4,1,1,0.0,neutral or dissatisfied +58358,66969,Female,Loyal Customer,42,Business travel,Business,2930,5,5,5,5,5,5,5,4,4,4,4,3,4,4,8,11.0,satisfied +58359,82553,Male,Loyal Customer,47,Business travel,Business,528,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,7.0,satisfied +58360,82386,Male,Loyal Customer,53,Business travel,Business,3833,1,1,3,1,3,3,3,4,5,4,5,3,4,3,152,166.0,satisfied +58361,109391,Female,Loyal Customer,50,Personal Travel,Eco,1046,3,4,3,3,4,5,4,4,4,3,4,3,4,5,36,30.0,neutral or dissatisfied +58362,24909,Female,Loyal Customer,39,Business travel,Business,3165,1,1,1,1,3,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +58363,57080,Female,disloyal Customer,24,Business travel,Eco,1222,3,3,3,4,3,3,1,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +58364,33767,Female,Loyal Customer,29,Business travel,Eco,1990,5,1,2,1,5,5,5,5,5,1,5,1,1,5,39,38.0,satisfied +58365,14648,Female,Loyal Customer,34,Business travel,Business,162,4,4,4,4,3,2,4,5,5,5,5,1,5,2,0,0.0,satisfied +58366,61053,Male,Loyal Customer,52,Business travel,Business,1709,3,3,3,3,5,5,5,5,5,5,5,4,5,4,1,10.0,satisfied +58367,3641,Female,Loyal Customer,46,Business travel,Business,427,4,4,4,4,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +58368,44774,Male,Loyal Customer,47,Business travel,Eco,1250,5,5,5,5,5,5,5,5,4,3,3,1,1,5,0,4.0,satisfied +58369,89928,Female,Loyal Customer,31,Business travel,Eco,1487,2,1,3,1,2,2,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +58370,72889,Male,Loyal Customer,48,Business travel,Business,2837,2,1,1,1,1,4,4,2,2,2,2,4,2,1,12,13.0,neutral or dissatisfied +58371,111381,Male,Loyal Customer,26,Business travel,Business,2319,4,4,4,4,4,4,4,4,5,4,5,4,4,4,0,3.0,satisfied +58372,25288,Male,Loyal Customer,25,Business travel,Business,3036,1,1,1,1,4,4,4,4,3,4,3,2,3,4,5,9.0,satisfied +58373,121816,Male,Loyal Customer,52,Business travel,Business,3471,3,2,2,2,4,3,4,3,3,3,3,4,3,1,6,30.0,neutral or dissatisfied +58374,8843,Male,Loyal Customer,37,Business travel,Business,3913,5,5,5,5,3,5,5,5,5,5,5,4,5,4,23,42.0,satisfied +58375,84352,Female,Loyal Customer,59,Business travel,Business,1971,2,1,1,1,3,4,4,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +58376,74631,Male,Loyal Customer,71,Business travel,Business,2327,1,1,1,1,5,4,2,4,4,4,4,2,4,2,0,0.0,satisfied +58377,69574,Female,Loyal Customer,73,Business travel,Eco,1086,3,1,1,1,3,3,3,1,5,3,4,3,3,3,0,0.0,neutral or dissatisfied +58378,37991,Male,disloyal Customer,22,Business travel,Eco,1249,4,4,4,5,4,4,5,4,5,1,5,2,5,4,1,0.0,neutral or dissatisfied +58379,90063,Male,Loyal Customer,22,Business travel,Business,1084,3,3,3,3,3,3,3,3,4,3,3,3,3,3,4,0.0,neutral or dissatisfied +58380,66931,Female,Loyal Customer,50,Business travel,Business,929,4,4,3,4,2,5,4,4,4,4,4,5,4,4,30,38.0,satisfied +58381,60618,Male,disloyal Customer,38,Business travel,Business,1201,4,4,4,1,4,4,1,4,3,5,4,5,5,4,0,0.0,satisfied +58382,71372,Female,Loyal Customer,34,Business travel,Business,258,1,2,2,2,3,2,2,1,1,1,1,4,1,4,5,7.0,neutral or dissatisfied +58383,97016,Male,Loyal Customer,34,Personal Travel,Eco,775,4,3,4,4,3,4,3,3,2,4,3,1,4,3,2,3.0,neutral or dissatisfied +58384,99334,Female,Loyal Customer,43,Personal Travel,Eco,337,1,4,3,3,4,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +58385,18517,Female,Loyal Customer,54,Business travel,Business,253,2,5,5,5,1,3,3,2,2,2,2,2,2,2,73,78.0,neutral or dissatisfied +58386,52231,Male,disloyal Customer,25,Business travel,Eco,370,2,5,2,1,4,2,4,4,2,2,3,4,1,4,0,0.0,neutral or dissatisfied +58387,71378,Male,Loyal Customer,39,Business travel,Business,2244,3,2,2,2,2,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +58388,121910,Male,Loyal Customer,20,Personal Travel,Eco,337,2,4,2,2,1,2,1,1,2,2,4,1,2,1,6,0.0,neutral or dissatisfied +58389,12933,Female,Loyal Customer,17,Personal Travel,Eco,456,1,2,1,4,1,1,1,1,2,4,3,2,4,1,3,6.0,neutral or dissatisfied +58390,22952,Male,Loyal Customer,53,Business travel,Eco,817,5,2,2,2,5,5,5,5,2,3,4,2,5,5,0,0.0,satisfied +58391,16896,Male,Loyal Customer,22,Personal Travel,Eco,708,2,4,1,2,1,3,3,3,5,4,5,3,4,3,206,219.0,neutral or dissatisfied +58392,51138,Female,Loyal Customer,70,Personal Travel,Eco,209,4,2,4,3,2,3,3,2,2,4,2,4,2,2,10,3.0,neutral or dissatisfied +58393,3275,Male,Loyal Customer,54,Business travel,Eco,479,4,1,1,1,4,4,4,4,1,2,5,4,4,4,14,13.0,satisfied +58394,122799,Female,Loyal Customer,63,Business travel,Business,599,4,4,4,4,2,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +58395,1054,Male,Loyal Customer,18,Personal Travel,Eco,396,5,4,3,1,2,3,2,2,5,3,5,5,5,2,0,0.0,satisfied +58396,116034,Female,Loyal Customer,15,Personal Travel,Eco,308,4,5,2,1,1,2,1,1,3,4,4,4,4,1,15,14.0,neutral or dissatisfied +58397,108167,Female,Loyal Customer,25,Personal Travel,Eco,997,1,5,1,1,4,1,4,4,4,4,5,3,4,4,37,21.0,neutral or dissatisfied +58398,122172,Male,disloyal Customer,24,Business travel,Eco,544,5,0,5,3,4,5,4,4,5,4,4,4,5,4,0,20.0,satisfied +58399,68143,Female,Loyal Customer,52,Business travel,Business,3857,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +58400,79297,Male,Loyal Customer,32,Business travel,Business,2248,2,2,2,2,5,5,5,5,4,4,3,3,4,5,0,0.0,satisfied +58401,9130,Female,Loyal Customer,41,Business travel,Business,765,5,5,5,5,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +58402,84503,Male,Loyal Customer,9,Business travel,Business,2504,3,1,1,1,3,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +58403,118853,Male,Loyal Customer,10,Personal Travel,Eco Plus,621,4,4,4,3,2,4,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +58404,16240,Male,Loyal Customer,29,Business travel,Business,748,4,4,4,4,4,4,4,4,3,3,5,1,5,4,0,0.0,satisfied +58405,105494,Female,Loyal Customer,36,Business travel,Eco,116,5,2,2,2,5,5,5,5,2,3,2,3,1,5,17,58.0,satisfied +58406,75139,Female,Loyal Customer,32,Business travel,Business,1723,2,2,2,2,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +58407,87050,Male,Loyal Customer,57,Business travel,Business,1551,4,4,2,4,5,5,5,4,4,4,4,4,4,4,23,32.0,satisfied +58408,59731,Male,Loyal Customer,40,Personal Travel,Eco Plus,787,2,4,2,1,2,2,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +58409,15555,Male,Loyal Customer,38,Personal Travel,Business,296,3,3,3,4,3,4,4,2,4,4,3,4,2,4,240,224.0,neutral or dissatisfied +58410,68846,Male,Loyal Customer,43,Business travel,Business,936,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +58411,69878,Male,Loyal Customer,54,Business travel,Business,2248,1,1,1,1,5,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +58412,104464,Female,disloyal Customer,22,Business travel,Business,1015,5,3,5,3,3,5,3,3,1,3,5,4,4,3,0,0.0,satisfied +58413,59734,Female,Loyal Customer,32,Personal Travel,Eco Plus,787,4,4,4,2,3,4,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +58414,50991,Female,Loyal Customer,49,Personal Travel,Eco,190,2,2,2,3,3,4,4,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +58415,66859,Male,Loyal Customer,21,Personal Travel,Eco,731,3,2,3,3,2,3,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +58416,70824,Female,Loyal Customer,21,Personal Travel,Eco Plus,624,1,4,1,2,3,1,3,3,4,2,2,5,5,3,10,0.0,neutral or dissatisfied +58417,119688,Female,Loyal Customer,47,Business travel,Business,1303,5,5,5,5,3,4,5,3,3,4,3,5,3,3,0,4.0,satisfied +58418,46350,Female,Loyal Customer,63,Personal Travel,Eco Plus,589,2,2,2,3,2,4,4,4,4,2,4,1,4,2,0,1.0,neutral or dissatisfied +58419,126064,Male,Loyal Customer,38,Business travel,Business,3428,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +58420,5087,Male,disloyal Customer,25,Business travel,Business,224,2,4,3,3,3,3,3,3,2,5,4,2,4,3,0,2.0,neutral or dissatisfied +58421,33557,Male,Loyal Customer,35,Business travel,Business,399,2,2,2,2,1,1,5,4,4,4,4,2,4,1,39,61.0,satisfied +58422,122784,Male,Loyal Customer,32,Business travel,Business,2218,1,1,1,1,5,5,5,5,5,5,5,3,5,5,7,4.0,satisfied +58423,30605,Male,Loyal Customer,32,Personal Travel,Eco,472,3,2,3,1,4,3,4,4,4,2,1,2,2,4,10,9.0,neutral or dissatisfied +58424,194,Female,Loyal Customer,46,Business travel,Business,3556,2,2,2,2,3,4,4,5,5,5,5,3,5,3,128,117.0,satisfied +58425,118171,Male,Loyal Customer,41,Business travel,Business,1440,5,5,5,5,3,4,4,2,2,2,2,5,2,5,7,0.0,satisfied +58426,39252,Female,Loyal Customer,63,Business travel,Business,173,3,3,2,3,1,2,2,2,2,3,3,4,2,1,0,0.0,neutral or dissatisfied +58427,69797,Male,Loyal Customer,59,Business travel,Business,1960,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +58428,95158,Male,Loyal Customer,39,Personal Travel,Eco,189,2,5,2,3,5,2,4,5,4,4,4,5,4,5,2,0.0,neutral or dissatisfied +58429,63912,Female,Loyal Customer,22,Business travel,Business,792,1,1,1,1,2,2,2,2,1,4,1,5,3,2,20,1.0,satisfied +58430,89684,Male,disloyal Customer,21,Business travel,Eco,647,4,0,4,4,3,4,3,3,3,2,1,4,2,3,0,0.0,neutral or dissatisfied +58431,58960,Female,Loyal Customer,38,Business travel,Business,1846,1,1,4,1,2,5,4,5,5,5,5,4,5,4,56,64.0,satisfied +58432,8178,Male,Loyal Customer,42,Business travel,Business,125,1,1,1,1,1,1,1,4,4,2,3,1,2,1,192,185.0,neutral or dissatisfied +58433,105962,Female,disloyal Customer,37,Business travel,Business,2329,3,3,3,3,3,5,5,4,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +58434,65703,Male,Loyal Customer,16,Business travel,Business,936,1,1,1,1,1,1,1,1,1,3,3,1,4,1,0,0.0,neutral or dissatisfied +58435,112995,Male,Loyal Customer,52,Business travel,Business,1797,1,2,2,2,4,2,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +58436,28510,Male,Loyal Customer,29,Business travel,Business,2715,5,5,5,5,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +58437,113110,Male,Loyal Customer,24,Personal Travel,Eco,543,3,5,3,2,4,3,4,4,4,4,5,4,5,4,6,0.0,neutral or dissatisfied +58438,106362,Female,disloyal Customer,25,Business travel,Business,488,2,4,2,3,2,2,2,2,3,4,4,5,4,2,38,36.0,neutral or dissatisfied +58439,12774,Female,Loyal Customer,52,Personal Travel,Eco Plus,721,1,5,0,4,1,3,5,4,4,0,2,4,4,3,0,0.0,neutral or dissatisfied +58440,105129,Male,disloyal Customer,34,Business travel,Business,281,2,2,2,3,5,2,5,5,3,3,4,3,5,5,1,0.0,neutral or dissatisfied +58441,6726,Female,Loyal Customer,42,Business travel,Business,268,0,0,0,3,3,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +58442,127148,Male,Loyal Customer,24,Personal Travel,Eco,621,5,5,5,3,4,5,2,4,4,2,5,3,4,4,0,0.0,satisfied +58443,116233,Female,Loyal Customer,33,Personal Travel,Eco,337,3,4,3,4,5,3,5,5,5,1,1,2,4,5,118,119.0,neutral or dissatisfied +58444,12331,Female,Loyal Customer,32,Business travel,Business,192,1,1,1,1,5,5,4,5,2,3,3,4,4,5,61,53.0,satisfied +58445,18278,Female,disloyal Customer,33,Business travel,Eco Plus,346,4,4,4,3,5,4,5,5,1,4,3,3,3,5,8,0.0,neutral or dissatisfied +58446,70,Female,Loyal Customer,49,Business travel,Business,3213,4,3,3,3,3,4,4,1,1,1,4,1,1,3,68,59.0,neutral or dissatisfied +58447,22608,Female,Loyal Customer,58,Business travel,Eco,223,5,5,5,5,1,4,3,5,5,5,5,2,5,5,26,20.0,satisfied +58448,122009,Female,Loyal Customer,39,Business travel,Business,2205,2,2,5,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +58449,128472,Male,Loyal Customer,43,Personal Travel,Eco,621,1,5,1,5,1,1,1,1,5,1,1,2,1,1,0,0.0,neutral or dissatisfied +58450,88910,Male,disloyal Customer,70,Personal Travel,Eco,859,1,5,1,4,3,1,3,3,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +58451,106802,Female,disloyal Customer,37,Business travel,Eco,577,1,4,1,4,5,1,5,5,4,4,3,2,3,5,23,18.0,neutral or dissatisfied +58452,6868,Male,Loyal Customer,63,Personal Travel,Eco,622,3,5,3,1,5,3,5,5,5,2,4,5,5,5,70,105.0,neutral or dissatisfied +58453,107974,Female,disloyal Customer,37,Business travel,Eco,425,4,0,4,2,1,4,1,1,2,2,2,5,4,1,0,0.0,neutral or dissatisfied +58454,121839,Female,Loyal Customer,43,Business travel,Business,366,2,5,3,5,1,3,4,2,2,2,2,3,2,2,0,26.0,neutral or dissatisfied +58455,39316,Male,Loyal Customer,16,Personal Travel,Eco,268,4,2,4,4,4,4,3,4,2,2,4,2,3,4,0,0.0,satisfied +58456,6282,Male,Loyal Customer,21,Business travel,Business,693,3,3,3,3,5,5,5,5,1,4,2,2,1,5,0,0.0,satisfied +58457,109811,Male,Loyal Customer,36,Business travel,Business,2596,3,3,5,3,2,4,5,4,4,4,4,5,4,4,4,0.0,satisfied +58458,87758,Female,Loyal Customer,35,Business travel,Business,214,3,3,3,3,3,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +58459,107532,Female,Loyal Customer,56,Business travel,Business,1521,5,5,4,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +58460,72958,Female,disloyal Customer,42,Business travel,Business,1096,5,5,5,2,4,5,4,4,4,3,4,4,4,4,0,0.0,satisfied +58461,36956,Male,Loyal Customer,10,Personal Travel,Business,899,2,4,2,1,5,2,5,5,5,2,5,4,5,5,48,41.0,neutral or dissatisfied +58462,57248,Male,Loyal Customer,40,Business travel,Business,2613,1,1,1,1,4,4,4,4,4,4,4,4,4,4,8,0.0,satisfied +58463,69801,Male,Loyal Customer,52,Business travel,Business,1345,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +58464,10957,Male,Loyal Customer,52,Business travel,Business,2233,1,1,1,1,3,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +58465,86972,Male,Loyal Customer,45,Business travel,Business,2721,1,1,1,1,2,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +58466,61449,Female,Loyal Customer,57,Business travel,Business,2288,2,2,2,2,5,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +58467,26426,Male,Loyal Customer,24,Business travel,Eco,925,4,2,2,2,4,4,3,4,2,1,3,1,4,4,0,0.0,satisfied +58468,128239,Male,Loyal Customer,33,Personal Travel,Eco,602,1,4,1,3,2,1,2,2,4,4,4,5,4,2,12,16.0,neutral or dissatisfied +58469,10001,Male,Loyal Customer,45,Personal Travel,Eco,534,1,4,1,4,3,1,3,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +58470,116254,Female,Loyal Customer,44,Personal Travel,Eco,390,4,2,4,4,1,4,3,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +58471,64184,Female,disloyal Customer,23,Business travel,Eco,1047,3,3,3,3,3,5,5,4,5,3,4,5,4,5,165,170.0,neutral or dissatisfied +58472,82314,Female,disloyal Customer,25,Business travel,Business,456,2,0,2,2,3,2,3,3,4,3,4,5,5,3,0,6.0,neutral or dissatisfied +58473,72066,Female,Loyal Customer,22,Business travel,Business,2486,1,4,4,4,1,1,1,1,4,3,2,2,4,1,6,0.0,neutral or dissatisfied +58474,79287,Male,Loyal Customer,37,Business travel,Business,2248,4,1,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +58475,80956,Female,Loyal Customer,46,Business travel,Business,2942,3,3,3,3,4,5,4,5,5,5,5,4,5,5,1,0.0,satisfied +58476,41351,Female,Loyal Customer,14,Personal Travel,Eco Plus,861,4,4,3,5,2,3,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +58477,25710,Male,Loyal Customer,39,Business travel,Eco,447,4,5,5,5,4,4,4,4,3,5,3,1,4,4,0,0.0,neutral or dissatisfied +58478,60061,Female,Loyal Customer,60,Business travel,Business,3043,3,3,4,3,2,5,5,3,3,4,3,4,3,4,6,0.0,satisfied +58479,125777,Female,disloyal Customer,23,Business travel,Business,951,4,0,5,3,1,5,1,1,5,5,4,4,4,1,0,1.0,satisfied +58480,94187,Female,Loyal Customer,52,Business travel,Business,1880,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +58481,47598,Male,Loyal Customer,23,Business travel,Eco,715,0,3,0,5,3,0,3,3,4,1,3,4,3,3,0,14.0,satisfied +58482,20174,Female,Loyal Customer,48,Personal Travel,Eco,258,1,5,0,2,5,3,5,5,5,0,5,5,5,5,14,23.0,neutral or dissatisfied +58483,86831,Male,Loyal Customer,25,Business travel,Business,692,2,2,2,2,2,2,2,2,4,3,1,1,2,2,63,59.0,neutral or dissatisfied +58484,56722,Male,Loyal Customer,27,Personal Travel,Eco,937,1,4,1,4,4,1,4,4,3,3,4,3,4,4,72,88.0,neutral or dissatisfied +58485,36969,Female,Loyal Customer,46,Business travel,Eco,759,5,1,3,1,4,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +58486,34006,Female,Loyal Customer,58,Business travel,Business,1576,3,1,1,1,4,2,2,3,3,3,3,4,3,4,34,34.0,neutral or dissatisfied +58487,105396,Male,Loyal Customer,39,Personal Travel,Eco,369,1,5,1,5,1,1,4,1,4,2,4,1,5,1,14,0.0,neutral or dissatisfied +58488,48784,Male,disloyal Customer,50,Business travel,Business,326,5,5,5,5,1,5,1,1,3,4,5,4,5,1,0,6.0,satisfied +58489,65884,Male,Loyal Customer,50,Personal Travel,Eco Plus,1389,2,2,2,4,1,2,1,1,1,3,4,1,3,1,15,4.0,neutral or dissatisfied +58490,122968,Male,disloyal Customer,22,Business travel,Eco,507,2,4,2,3,3,2,3,3,5,2,4,3,4,3,10,6.0,neutral or dissatisfied +58491,46648,Female,disloyal Customer,20,Business travel,Eco,73,1,0,1,2,3,1,2,3,4,1,3,1,2,3,0,17.0,neutral or dissatisfied +58492,75961,Male,Loyal Customer,49,Business travel,Business,2851,2,2,2,2,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +58493,71810,Male,Loyal Customer,30,Business travel,Business,1726,3,5,4,5,3,3,3,3,1,5,3,2,4,3,52,83.0,neutral or dissatisfied +58494,81698,Male,Loyal Customer,21,Personal Travel,Eco,907,1,5,1,3,1,2,2,5,4,4,4,2,4,2,134,116.0,neutral or dissatisfied +58495,31890,Female,Loyal Customer,32,Business travel,Eco,2762,4,3,4,4,4,4,4,4,3,4,3,5,3,4,0,0.0,satisfied +58496,38835,Female,Loyal Customer,41,Business travel,Eco Plus,387,2,3,3,3,2,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +58497,101105,Male,disloyal Customer,23,Business travel,Eco,1235,4,4,4,3,3,4,3,3,4,3,4,5,5,3,0,0.0,satisfied +58498,42556,Female,Loyal Customer,38,Personal Travel,Eco Plus,1174,2,5,2,4,1,2,4,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +58499,79976,Male,Loyal Customer,45,Business travel,Business,2044,5,5,5,5,1,3,5,4,4,4,4,4,4,1,0,0.0,satisfied +58500,66642,Male,Loyal Customer,45,Business travel,Business,2672,4,4,4,4,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +58501,18634,Female,Loyal Customer,51,Personal Travel,Eco,190,2,4,2,1,2,2,5,2,2,2,2,4,2,2,3,0.0,neutral or dissatisfied +58502,35963,Male,Loyal Customer,43,Business travel,Eco,231,1,3,3,3,1,1,1,1,2,1,3,3,4,1,0,0.0,neutral or dissatisfied +58503,30555,Female,Loyal Customer,41,Personal Travel,Eco Plus,1026,2,5,1,2,4,4,4,5,5,1,5,4,5,4,84,92.0,neutral or dissatisfied +58504,31158,Female,Loyal Customer,18,Personal Travel,Eco,495,3,1,3,4,5,3,2,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +58505,111241,Male,Loyal Customer,73,Business travel,Eco Plus,203,1,1,3,1,2,1,2,2,1,5,3,4,3,2,3,0.0,neutral or dissatisfied +58506,44840,Female,Loyal Customer,59,Business travel,Eco,760,3,5,5,5,1,4,4,3,3,3,3,2,3,2,0,6.0,neutral or dissatisfied +58507,70081,Female,Loyal Customer,41,Business travel,Business,460,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +58508,1977,Female,Loyal Customer,15,Personal Travel,Eco,285,3,5,3,1,2,3,2,2,3,5,4,4,5,2,1,0.0,neutral or dissatisfied +58509,5945,Female,Loyal Customer,27,Personal Travel,Business,642,4,5,4,4,4,3,3,3,4,4,5,3,5,3,83,150.0,satisfied +58510,96518,Female,Loyal Customer,20,Personal Travel,Eco,436,4,1,4,4,5,4,5,5,3,2,3,4,4,5,0,0.0,satisfied +58511,89778,Female,Loyal Customer,48,Personal Travel,Eco,1010,2,4,2,3,4,3,4,2,2,2,2,4,2,4,0,5.0,neutral or dissatisfied +58512,32069,Female,Loyal Customer,54,Business travel,Business,1581,2,2,2,2,5,3,4,5,5,5,4,4,5,5,0,0.0,satisfied +58513,45725,Female,Loyal Customer,63,Personal Travel,Eco,852,3,4,3,2,2,5,4,5,5,3,3,5,5,5,12,0.0,neutral or dissatisfied +58514,102248,Female,Loyal Customer,54,Business travel,Business,3513,0,0,0,2,3,5,5,1,1,1,1,3,1,5,19,20.0,satisfied +58515,96955,Male,Loyal Customer,28,Business travel,Business,794,5,5,5,5,4,4,4,5,2,5,5,4,5,4,152,150.0,satisfied +58516,91409,Female,Loyal Customer,64,Personal Travel,Business,1050,3,1,2,3,4,3,3,5,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +58517,50770,Female,Loyal Customer,17,Personal Travel,Eco,373,3,5,3,2,2,3,2,2,4,4,5,4,2,2,0,2.0,neutral or dissatisfied +58518,6906,Male,Loyal Customer,16,Personal Travel,Eco,287,3,2,3,3,1,3,5,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +58519,6407,Female,Loyal Customer,38,Personal Travel,Eco,296,2,4,2,4,1,2,1,1,3,4,3,3,4,1,1,6.0,neutral or dissatisfied +58520,75636,Female,Loyal Customer,35,Business travel,Business,337,4,4,3,4,5,4,5,4,4,4,4,5,4,4,14,0.0,satisfied +58521,87537,Female,Loyal Customer,69,Personal Travel,Eco Plus,304,3,5,3,3,2,5,4,1,1,3,4,4,1,3,0,0.0,neutral or dissatisfied +58522,10033,Female,Loyal Customer,60,Business travel,Business,3648,4,4,4,4,2,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +58523,105157,Female,disloyal Customer,22,Business travel,Eco,281,4,0,4,2,5,4,5,5,3,3,2,4,1,5,0,10.0,satisfied +58524,69927,Male,Loyal Customer,30,Business travel,Business,1514,2,2,5,2,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +58525,103766,Male,disloyal Customer,23,Business travel,Business,979,5,5,5,4,2,5,2,2,5,2,4,4,4,2,108,98.0,satisfied +58526,17901,Male,Loyal Customer,66,Personal Travel,Business,789,3,4,3,4,3,4,5,3,3,3,3,3,3,4,15,2.0,neutral or dissatisfied +58527,3707,Female,Loyal Customer,50,Personal Travel,Eco,544,3,5,3,3,4,5,1,4,4,3,3,5,4,4,0,0.0,neutral or dissatisfied +58528,82106,Female,Loyal Customer,61,Personal Travel,Eco,1276,2,5,2,1,4,4,4,3,3,2,3,5,3,4,31,24.0,neutral or dissatisfied +58529,64726,Female,disloyal Customer,33,Business travel,Business,190,1,0,0,4,3,0,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +58530,7969,Female,Loyal Customer,21,Personal Travel,Eco,594,2,3,2,5,3,2,2,3,2,5,5,5,5,3,0,0.0,neutral or dissatisfied +58531,84858,Female,disloyal Customer,25,Business travel,Eco,547,3,0,4,3,5,4,5,5,2,4,4,4,2,5,0,0.0,neutral or dissatisfied +58532,56557,Male,Loyal Customer,40,Business travel,Business,2429,4,4,4,4,4,5,5,3,3,3,3,5,3,3,121,105.0,satisfied +58533,88119,Male,disloyal Customer,37,Business travel,Business,404,5,5,5,1,4,5,4,4,4,3,4,5,4,4,25,22.0,satisfied +58534,107927,Male,Loyal Customer,47,Business travel,Business,2520,1,1,1,1,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +58535,126629,Female,Loyal Customer,48,Business travel,Business,3385,2,2,2,2,3,5,4,5,5,5,5,4,5,4,94,84.0,satisfied +58536,113945,Female,Loyal Customer,50,Business travel,Business,1706,5,5,5,5,4,5,5,5,5,5,5,4,5,4,24,8.0,satisfied +58537,13674,Male,disloyal Customer,33,Personal Travel,Eco,462,3,4,2,1,5,2,5,5,3,3,5,5,4,5,0,9.0,neutral or dissatisfied +58538,79748,Male,Loyal Customer,14,Personal Travel,Eco Plus,749,3,3,3,1,4,3,4,4,3,4,2,4,2,4,7,11.0,neutral or dissatisfied +58539,60451,Male,Loyal Customer,48,Business travel,Business,934,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +58540,67182,Male,Loyal Customer,16,Personal Travel,Eco,985,2,5,2,1,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +58541,46510,Female,Loyal Customer,46,Business travel,Business,125,2,2,2,2,4,1,1,4,4,4,4,3,4,3,7,3.0,satisfied +58542,70779,Male,Loyal Customer,52,Business travel,Business,328,1,2,1,1,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +58543,22702,Female,Loyal Customer,54,Personal Travel,Eco,579,2,1,2,3,4,3,3,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +58544,120879,Female,Loyal Customer,59,Business travel,Business,920,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +58545,60634,Male,Loyal Customer,25,Business travel,Business,1620,3,3,3,3,4,4,4,4,5,4,5,3,5,4,82,57.0,satisfied +58546,109221,Male,disloyal Customer,24,Business travel,Eco,616,3,2,2,3,4,2,4,4,2,3,3,1,3,4,81,59.0,neutral or dissatisfied +58547,48900,Female,Loyal Customer,32,Business travel,Business,1826,3,3,3,3,4,4,4,4,2,1,2,5,1,4,112,110.0,satisfied +58548,110084,Male,disloyal Customer,23,Business travel,Eco,979,2,2,2,3,5,2,5,5,3,4,4,3,5,5,40,54.0,neutral or dissatisfied +58549,34656,Male,Loyal Customer,59,Business travel,Business,301,5,2,5,5,4,4,4,5,5,5,5,3,5,4,2,5.0,satisfied +58550,121011,Female,Loyal Customer,59,Personal Travel,Eco,951,3,3,3,1,5,4,4,4,4,3,5,1,4,2,0,25.0,neutral or dissatisfied +58551,9376,Male,Loyal Customer,15,Personal Travel,Eco,401,4,1,4,3,3,4,1,3,4,3,4,1,3,3,0,0.0,neutral or dissatisfied +58552,40996,Female,disloyal Customer,26,Business travel,Eco,1362,5,5,5,1,5,5,5,5,2,1,1,5,4,5,20,9.0,satisfied +58553,23971,Male,disloyal Customer,25,Business travel,Eco,596,1,0,1,4,1,1,1,1,4,1,4,1,1,1,0,0.0,neutral or dissatisfied +58554,50070,Male,Loyal Customer,55,Business travel,Business,199,2,2,2,2,5,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +58555,109192,Female,Loyal Customer,22,Business travel,Business,616,1,5,5,5,1,1,1,1,3,1,4,4,4,1,17,11.0,neutral or dissatisfied +58556,27546,Female,Loyal Customer,15,Personal Travel,Eco,954,2,4,2,4,3,2,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +58557,75541,Male,disloyal Customer,44,Business travel,Business,337,4,4,4,3,1,4,1,1,5,4,5,5,5,1,0,0.0,satisfied +58558,83249,Male,Loyal Customer,42,Business travel,Business,1979,2,4,4,4,4,3,4,2,2,2,2,3,2,1,5,48.0,neutral or dissatisfied +58559,50162,Female,disloyal Customer,44,Business travel,Eco,110,1,1,1,2,1,1,1,1,4,3,2,2,2,1,11,6.0,neutral or dissatisfied +58560,96091,Male,Loyal Customer,39,Personal Travel,Eco,1090,4,4,4,1,4,2,2,2,3,3,1,2,4,2,199,203.0,neutral or dissatisfied +58561,83561,Female,Loyal Customer,60,Business travel,Business,3533,4,4,4,4,5,5,4,5,5,5,5,3,5,5,0,5.0,satisfied +58562,46557,Female,Loyal Customer,53,Business travel,Eco,125,4,2,2,2,2,5,5,4,4,4,4,1,4,4,8,13.0,satisfied +58563,79584,Female,Loyal Customer,28,Business travel,Business,3125,4,4,4,4,4,4,4,4,3,4,5,5,5,4,45,23.0,satisfied +58564,1873,Male,disloyal Customer,30,Business travel,Business,931,3,3,3,3,2,3,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +58565,58456,Female,Loyal Customer,35,Business travel,Business,733,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +58566,26261,Male,Loyal Customer,42,Business travel,Business,859,3,3,3,3,2,4,5,4,4,4,4,4,4,5,22,16.0,satisfied +58567,36367,Male,Loyal Customer,38,Business travel,Eco,200,4,5,5,5,4,4,4,4,2,2,4,1,5,4,0,0.0,satisfied +58568,24693,Male,Loyal Customer,49,Personal Travel,Eco Plus,761,1,4,1,3,2,1,4,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +58569,112527,Female,Loyal Customer,69,Personal Travel,Eco,909,2,5,2,4,3,3,1,4,4,2,4,1,4,4,5,0.0,neutral or dissatisfied +58570,111790,Male,Loyal Customer,49,Personal Travel,Eco,1620,3,5,4,1,5,4,5,5,3,5,3,5,5,5,49,36.0,neutral or dissatisfied +58571,11591,Female,Loyal Customer,51,Business travel,Business,1610,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,5.0,satisfied +58572,121268,Female,Loyal Customer,55,Personal Travel,Eco,1814,3,3,3,3,3,3,3,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +58573,67669,Female,Loyal Customer,46,Business travel,Business,1313,5,5,5,5,5,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +58574,1772,Male,Loyal Customer,55,Business travel,Business,408,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +58575,26129,Male,Loyal Customer,56,Business travel,Business,3638,1,1,1,1,1,1,5,4,4,4,4,4,4,3,18,16.0,satisfied +58576,10018,Male,Loyal Customer,55,Personal Travel,Eco Plus,534,2,5,2,3,3,2,3,3,3,5,5,3,4,3,24,4.0,neutral or dissatisfied +58577,70473,Female,disloyal Customer,26,Business travel,Business,867,4,4,4,1,4,4,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +58578,28244,Male,Loyal Customer,70,Personal Travel,Eco,1009,3,4,3,4,3,3,5,3,1,1,3,3,4,3,0,25.0,neutral or dissatisfied +58579,29460,Female,Loyal Customer,46,Personal Travel,Eco,421,2,4,2,4,2,2,2,5,5,2,5,1,5,1,0,0.0,neutral or dissatisfied +58580,82931,Male,Loyal Customer,47,Business travel,Business,594,3,3,3,3,3,4,5,5,5,4,5,5,5,3,43,100.0,satisfied +58581,9674,Male,disloyal Customer,48,Business travel,Business,199,3,3,3,3,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +58582,62716,Male,Loyal Customer,36,Business travel,Business,2486,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +58583,78270,Male,Loyal Customer,38,Business travel,Business,903,1,1,1,1,3,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +58584,64694,Male,Loyal Customer,54,Business travel,Business,3662,5,5,5,5,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +58585,52032,Female,Loyal Customer,37,Personal Travel,Eco,328,4,2,4,3,1,4,1,1,3,2,4,1,3,1,0,0.0,satisfied +58586,53513,Female,Loyal Customer,18,Personal Travel,Eco,2358,3,5,3,5,2,3,2,2,3,5,3,3,4,2,9,0.0,neutral or dissatisfied +58587,74665,Female,Loyal Customer,48,Personal Travel,Eco,1438,0,5,0,3,3,4,4,4,4,0,2,5,4,3,8,0.0,satisfied +58588,104103,Female,Loyal Customer,54,Business travel,Business,297,3,3,3,3,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +58589,85312,Female,Loyal Customer,66,Personal Travel,Eco,689,4,4,4,3,4,5,5,5,5,4,5,3,5,3,3,0.0,neutral or dissatisfied +58590,118241,Female,Loyal Customer,60,Personal Travel,Eco,1587,2,4,1,4,3,4,5,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +58591,127258,Female,Loyal Customer,55,Business travel,Business,1020,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +58592,71945,Female,Loyal Customer,44,Business travel,Business,1440,5,5,5,5,3,5,5,4,4,4,4,5,4,4,51,45.0,satisfied +58593,30385,Male,disloyal Customer,79,Business travel,Eco,462,3,4,3,3,4,3,4,4,2,1,2,4,3,4,0,0.0,neutral or dissatisfied +58594,114875,Male,Loyal Customer,54,Business travel,Business,390,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +58595,115032,Male,disloyal Customer,58,Business travel,Business,447,4,4,4,4,5,4,5,5,4,2,4,4,5,5,41,21.0,satisfied +58596,64891,Female,Loyal Customer,41,Business travel,Business,247,0,0,0,1,5,4,4,1,1,1,1,5,1,4,0,0.0,satisfied +58597,126859,Male,Loyal Customer,17,Personal Travel,Eco,2296,3,5,3,1,2,3,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +58598,67537,Male,disloyal Customer,29,Business travel,Business,1235,1,1,1,4,1,1,1,1,4,4,3,4,3,1,2,0.0,neutral or dissatisfied +58599,81251,Male,Loyal Customer,52,Personal Travel,Business,1020,3,2,3,3,3,3,3,4,2,2,3,3,3,3,155,174.0,neutral or dissatisfied +58600,120663,Male,Loyal Customer,22,Business travel,Business,3684,1,3,3,3,1,1,1,1,3,4,3,1,4,1,0,0.0,neutral or dissatisfied +58601,34134,Female,Loyal Customer,35,Business travel,Business,1189,3,3,3,3,1,4,4,5,5,5,5,2,5,1,0,0.0,satisfied +58602,12409,Female,disloyal Customer,25,Business travel,Eco,192,1,4,2,3,4,2,1,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +58603,11197,Male,Loyal Customer,59,Personal Travel,Eco,667,3,5,3,3,1,3,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +58604,35422,Female,Loyal Customer,17,Personal Travel,Eco,1041,0,1,0,3,1,4,4,3,1,3,4,4,1,4,427,440.0,satisfied +58605,46215,Male,Loyal Customer,45,Business travel,Business,594,4,4,4,4,1,4,2,4,4,4,4,3,4,1,0,0.0,satisfied +58606,15905,Female,Loyal Customer,69,Business travel,Eco Plus,260,1,0,0,4,1,4,3,4,4,1,4,2,4,2,69,55.0,neutral or dissatisfied +58607,70344,Male,Loyal Customer,18,Personal Travel,Eco,986,3,4,3,2,3,3,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +58608,33643,Female,Loyal Customer,38,Personal Travel,Eco,399,3,4,3,3,5,3,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +58609,19258,Male,disloyal Customer,57,Business travel,Eco,802,3,3,3,1,5,3,5,5,3,2,1,2,2,5,9,0.0,neutral or dissatisfied +58610,55115,Female,Loyal Customer,11,Personal Travel,Eco,1504,1,4,1,2,4,1,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +58611,123344,Male,Loyal Customer,35,Personal Travel,Eco Plus,468,2,4,2,4,2,2,2,2,5,2,5,4,5,2,0,1.0,neutral or dissatisfied +58612,40494,Female,Loyal Customer,16,Personal Travel,Eco,461,4,5,4,2,2,4,2,2,2,3,1,5,5,2,0,0.0,neutral or dissatisfied +58613,15244,Male,Loyal Customer,11,Personal Travel,Eco,445,3,4,3,2,3,3,3,3,5,4,5,3,4,3,7,15.0,neutral or dissatisfied +58614,29114,Male,Loyal Customer,13,Personal Travel,Eco,954,3,3,3,3,2,3,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +58615,120897,Male,Loyal Customer,53,Business travel,Business,3270,4,4,4,4,2,5,5,3,3,3,3,4,3,5,1,0.0,satisfied +58616,27027,Female,Loyal Customer,8,Personal Travel,Eco,867,1,5,1,2,5,1,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +58617,118457,Male,Loyal Customer,40,Business travel,Business,3764,1,1,1,1,5,4,5,5,5,5,5,3,5,5,3,0.0,satisfied +58618,20676,Male,Loyal Customer,51,Business travel,Business,1615,1,1,1,1,3,1,1,5,5,5,4,1,5,2,0,1.0,satisfied +58619,120977,Male,Loyal Customer,56,Business travel,Eco,742,1,3,3,3,1,1,1,1,4,1,4,2,3,1,14,13.0,neutral or dissatisfied +58620,68192,Female,Loyal Customer,66,Business travel,Eco Plus,197,5,5,5,5,2,2,4,5,5,5,5,3,5,1,9,5.0,satisfied +58621,72282,Male,Loyal Customer,45,Business travel,Eco,521,4,4,4,4,4,4,4,4,4,3,3,2,3,4,0,0.0,satisfied +58622,124590,Female,Loyal Customer,45,Business travel,Business,2850,1,1,1,1,2,5,5,4,4,4,4,5,4,3,2,0.0,satisfied +58623,41383,Female,Loyal Customer,38,Business travel,Eco,563,3,4,4,4,3,3,3,3,1,2,2,1,3,3,0,0.0,neutral or dissatisfied +58624,19245,Male,Loyal Customer,36,Personal Travel,Eco,782,5,4,5,4,1,5,3,1,3,2,5,4,4,1,0,0.0,satisfied +58625,4393,Male,Loyal Customer,25,Personal Travel,Eco,473,2,1,2,4,5,2,5,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +58626,94764,Female,Loyal Customer,51,Business travel,Business,1812,1,5,5,5,1,2,2,3,3,3,1,3,3,1,0,0.0,neutral or dissatisfied +58627,26028,Female,Loyal Customer,27,Personal Travel,Eco,321,3,5,3,1,4,3,4,4,2,3,3,1,2,4,13,8.0,neutral or dissatisfied +58628,102070,Male,Loyal Customer,35,Business travel,Business,3465,2,2,2,2,5,5,5,5,5,5,5,5,5,5,4,0.0,satisfied +58629,7639,Female,Loyal Customer,40,Business travel,Eco,767,1,0,0,4,4,0,4,4,1,5,4,1,4,4,0,8.0,neutral or dissatisfied +58630,72533,Female,disloyal Customer,19,Business travel,Business,918,0,5,0,5,1,0,1,1,5,5,5,3,4,1,0,0.0,satisfied +58631,128440,Female,Loyal Customer,46,Business travel,Business,338,2,4,2,4,3,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +58632,36358,Female,Loyal Customer,34,Business travel,Business,2602,2,2,4,2,2,1,2,5,5,4,4,2,5,4,0,0.0,satisfied +58633,122947,Male,Loyal Customer,60,Business travel,Business,3492,2,3,2,2,4,4,5,4,4,5,4,3,4,3,68,76.0,satisfied +58634,85228,Female,Loyal Customer,47,Business travel,Business,413,5,5,5,5,2,5,3,4,4,4,4,3,4,4,0,0.0,satisfied +58635,5129,Female,Loyal Customer,22,Personal Travel,Eco Plus,235,4,4,4,1,2,4,5,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +58636,24194,Male,Loyal Customer,55,Business travel,Business,2316,4,4,4,4,1,2,2,5,5,4,3,5,5,4,3,0.0,satisfied +58637,53947,Male,disloyal Customer,48,Business travel,Eco,1325,2,2,2,4,2,2,2,2,4,5,3,4,1,2,51,37.0,neutral or dissatisfied +58638,90164,Male,Loyal Customer,35,Personal Travel,Eco,1084,2,4,2,1,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +58639,17498,Female,Loyal Customer,39,Business travel,Eco,341,2,5,5,5,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +58640,78376,Male,disloyal Customer,47,Business travel,Business,980,4,4,4,1,2,4,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +58641,28878,Female,disloyal Customer,30,Business travel,Eco,697,1,1,1,2,1,1,1,1,3,5,1,3,1,1,0,6.0,neutral or dissatisfied +58642,104298,Female,Loyal Customer,37,Personal Travel,Eco,440,4,4,2,4,1,2,1,1,5,3,4,5,4,1,11,0.0,neutral or dissatisfied +58643,28724,Female,Loyal Customer,51,Personal Travel,Eco,2554,2,5,3,4,3,2,2,2,4,4,2,2,2,2,0,0.0,neutral or dissatisfied +58644,39654,Female,Loyal Customer,79,Business travel,Eco,736,4,4,3,4,5,2,3,4,4,4,4,1,4,1,0,0.0,satisfied +58645,48583,Male,Loyal Customer,22,Personal Travel,Eco,776,4,4,4,4,4,4,4,4,4,3,5,3,5,4,20,52.0,neutral or dissatisfied +58646,67319,Female,Loyal Customer,35,Personal Travel,Eco Plus,1121,3,4,3,2,5,3,3,5,3,3,5,4,5,5,14,0.0,neutral or dissatisfied +58647,117268,Male,Loyal Customer,27,Personal Travel,Eco,370,2,0,2,4,5,2,1,5,4,4,4,5,5,5,0,0.0,neutral or dissatisfied +58648,79481,Male,Loyal Customer,44,Business travel,Business,2337,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,3.0,satisfied +58649,48395,Female,Loyal Customer,27,Personal Travel,Eco,749,4,4,4,1,2,4,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +58650,19897,Female,disloyal Customer,37,Business travel,Eco,296,3,1,3,3,5,3,5,5,2,5,4,2,3,5,32,28.0,neutral or dissatisfied +58651,87044,Female,Loyal Customer,41,Business travel,Business,2187,5,5,5,5,3,4,4,4,4,4,4,4,4,4,17,6.0,satisfied +58652,96100,Female,Loyal Customer,24,Personal Travel,Eco,1069,3,5,3,1,3,3,3,3,3,2,5,3,4,3,0,4.0,neutral or dissatisfied +58653,97469,Female,Loyal Customer,44,Business travel,Business,822,1,1,1,1,3,5,4,3,3,4,3,4,3,5,0,12.0,satisfied +58654,27766,Male,Loyal Customer,30,Business travel,Eco,680,5,5,5,5,5,5,5,5,4,2,5,2,5,5,0,0.0,satisfied +58655,42385,Male,Loyal Customer,34,Personal Travel,Eco,550,2,5,3,2,5,3,5,5,4,2,4,5,5,5,10,11.0,neutral or dissatisfied +58656,128762,Male,disloyal Customer,33,Business travel,Eco,550,3,2,3,3,3,3,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +58657,1547,Male,Loyal Customer,54,Personal Travel,Eco,862,3,5,3,3,1,3,1,1,3,3,5,5,4,1,10,5.0,neutral or dissatisfied +58658,89197,Female,Loyal Customer,65,Personal Travel,Eco,2092,2,0,2,5,2,4,5,4,4,2,4,3,4,5,1,0.0,neutral or dissatisfied +58659,91996,Male,Loyal Customer,66,Personal Travel,Eco,236,4,5,4,4,5,4,5,5,5,2,5,3,5,5,0,0.0,satisfied +58660,72470,Female,Loyal Customer,45,Business travel,Business,985,1,1,1,1,4,4,5,5,5,5,5,3,5,5,2,0.0,satisfied +58661,37413,Male,disloyal Customer,25,Business travel,Business,1097,0,0,0,2,2,0,3,2,4,5,5,1,3,2,86,124.0,satisfied +58662,27713,Female,Loyal Customer,67,Business travel,Business,1448,3,3,3,3,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +58663,47287,Female,Loyal Customer,48,Business travel,Business,541,4,4,4,4,1,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +58664,85786,Female,Loyal Customer,58,Business travel,Business,2196,3,3,3,3,4,5,4,2,2,2,2,4,2,5,1,0.0,satisfied +58665,34332,Female,Loyal Customer,40,Business travel,Eco,846,5,3,5,3,5,5,5,5,5,4,1,3,2,5,0,0.0,satisfied +58666,8150,Female,Loyal Customer,37,Business travel,Business,2239,4,1,4,4,3,4,5,4,4,4,5,4,4,4,2,0.0,satisfied +58667,59359,Female,disloyal Customer,25,Business travel,Eco,1484,2,2,2,3,4,2,4,4,1,5,2,4,4,4,0,0.0,neutral or dissatisfied +58668,56783,Male,Loyal Customer,9,Personal Travel,Eco Plus,1023,3,4,3,4,2,3,2,2,2,3,5,4,5,2,0,0.0,neutral or dissatisfied +58669,50963,Male,Loyal Customer,11,Personal Travel,Eco,109,1,3,1,1,1,1,1,1,2,5,3,4,4,1,47,32.0,neutral or dissatisfied +58670,35446,Female,Loyal Customer,23,Personal Travel,Eco,944,2,4,2,2,4,2,4,4,4,4,5,5,4,4,5,0.0,neutral or dissatisfied +58671,124063,Female,disloyal Customer,35,Business travel,Eco,2153,1,2,2,3,1,2,2,1,3,1,3,2,2,2,0,0.0,neutral or dissatisfied +58672,124913,Female,Loyal Customer,62,Business travel,Eco,728,3,2,2,2,2,2,3,3,3,3,3,3,3,1,0,12.0,neutral or dissatisfied +58673,52384,Male,Loyal Customer,35,Personal Travel,Eco,425,4,4,4,4,5,4,5,5,2,5,4,4,3,5,0,0.0,satisfied +58674,118557,Female,Loyal Customer,11,Business travel,Business,1611,3,1,1,1,3,3,3,3,4,1,4,3,3,3,0,0.0,neutral or dissatisfied +58675,121235,Male,disloyal Customer,36,Business travel,Business,2075,1,1,1,5,4,1,4,4,5,2,5,4,5,4,30,29.0,neutral or dissatisfied +58676,103323,Male,Loyal Customer,64,Business travel,Business,3142,1,1,1,1,1,1,1,3,3,4,3,3,3,1,0,0.0,satisfied +58677,63345,Female,Loyal Customer,47,Business travel,Eco,372,4,5,5,5,2,2,1,4,4,4,4,3,4,2,66,,neutral or dissatisfied +58678,64366,Female,Loyal Customer,57,Personal Travel,Eco,1172,1,4,0,3,3,5,5,3,3,0,4,3,3,5,26,6.0,neutral or dissatisfied +58679,29284,Male,Loyal Customer,43,Business travel,Business,2411,3,3,3,3,5,1,3,5,5,5,5,4,5,2,0,0.0,satisfied +58680,113010,Male,Loyal Customer,11,Personal Travel,Eco,1751,5,2,5,3,2,5,2,2,2,4,3,1,3,2,0,0.0,satisfied +58681,127966,Male,Loyal Customer,55,Personal Travel,Eco,1999,4,4,4,1,5,4,5,5,5,4,5,5,4,5,4,0.0,satisfied +58682,789,Female,Loyal Customer,40,Business travel,Business,3553,3,1,3,3,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +58683,20394,Female,Loyal Customer,41,Business travel,Eco,459,3,3,3,3,3,3,3,3,4,5,3,2,2,3,0,0.0,neutral or dissatisfied +58684,116915,Male,Loyal Customer,43,Business travel,Business,3497,3,2,3,3,5,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +58685,28705,Male,Loyal Customer,41,Business travel,Eco Plus,2172,4,3,3,3,4,4,4,4,1,5,5,1,2,4,0,0.0,satisfied +58686,121690,Male,Loyal Customer,17,Personal Travel,Eco,328,4,2,4,2,1,4,1,1,2,5,1,3,2,1,47,35.0,neutral or dissatisfied +58687,26319,Female,Loyal Customer,45,Business travel,Business,3101,4,4,4,4,1,5,4,4,4,4,4,2,4,4,5,0.0,satisfied +58688,55587,Female,disloyal Customer,28,Business travel,Business,1091,4,4,4,2,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +58689,88585,Female,Loyal Customer,25,Personal Travel,Eco,442,2,4,2,3,3,2,3,3,3,2,5,3,5,3,5,0.0,neutral or dissatisfied +58690,12336,Male,Loyal Customer,35,Business travel,Business,3776,4,1,1,1,2,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +58691,43317,Male,Loyal Customer,32,Business travel,Business,531,5,2,2,2,5,4,5,5,2,4,4,4,4,5,0,0.0,neutral or dissatisfied +58692,125702,Female,Loyal Customer,68,Personal Travel,Eco,759,4,4,4,4,5,4,2,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +58693,17419,Female,disloyal Customer,43,Business travel,Eco,376,2,2,2,2,2,2,2,2,1,2,3,3,3,2,2,0.0,neutral or dissatisfied +58694,12690,Male,Loyal Customer,42,Business travel,Eco,803,5,5,5,5,5,5,5,5,2,5,5,3,3,5,0,0.0,satisfied +58695,100000,Female,disloyal Customer,24,Business travel,Business,289,4,0,4,3,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +58696,7274,Female,Loyal Customer,17,Personal Travel,Eco,130,2,0,2,3,2,2,2,2,5,4,4,3,5,2,29,38.0,neutral or dissatisfied +58697,17131,Female,disloyal Customer,36,Business travel,Eco,423,2,5,2,3,4,2,4,4,1,4,4,2,5,4,0,0.0,neutral or dissatisfied +58698,114357,Male,Loyal Customer,35,Business travel,Business,2653,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +58699,22796,Female,Loyal Customer,17,Business travel,Business,134,3,3,3,3,1,1,3,1,4,5,3,1,3,1,32,15.0,neutral or dissatisfied +58700,120377,Female,Loyal Customer,48,Business travel,Business,1947,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,1.0,satisfied +58701,47682,Male,Loyal Customer,30,Personal Travel,Eco,1269,1,4,1,3,5,1,5,5,5,5,4,4,5,5,18,33.0,neutral or dissatisfied +58702,26953,Male,Loyal Customer,22,Business travel,Business,867,3,2,4,2,3,3,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +58703,72924,Male,Loyal Customer,16,Business travel,Business,3400,3,3,3,3,4,4,4,5,3,4,5,4,3,4,133,129.0,satisfied +58704,10726,Female,Loyal Customer,63,Business travel,Business,3986,1,3,3,3,5,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +58705,78069,Male,Loyal Customer,37,Personal Travel,Eco,332,3,4,3,3,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +58706,3023,Male,Loyal Customer,11,Personal Travel,Eco,922,2,5,2,3,3,2,3,3,4,2,5,5,4,3,0,2.0,neutral or dissatisfied +58707,116342,Female,Loyal Customer,26,Personal Travel,Eco,480,3,1,5,3,1,5,1,1,4,4,4,3,3,1,27,17.0,neutral or dissatisfied +58708,36832,Male,Loyal Customer,48,Business travel,Eco,369,2,1,1,1,2,2,2,2,5,5,1,5,4,2,0,0.0,satisfied +58709,124727,Male,Loyal Customer,67,Personal Travel,Eco,399,2,4,5,4,2,5,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +58710,9463,Male,Loyal Customer,68,Personal Travel,Eco,299,1,5,1,3,3,1,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +58711,49851,Male,Loyal Customer,33,Business travel,Business,363,2,2,2,2,5,5,5,5,3,1,1,5,3,5,0,0.0,satisfied +58712,111302,Male,disloyal Customer,24,Business travel,Eco,283,3,0,3,4,1,3,1,1,3,5,4,3,5,1,29,33.0,neutral or dissatisfied +58713,87056,Female,disloyal Customer,24,Business travel,Business,594,0,4,0,3,2,0,3,2,4,3,4,3,4,2,11,10.0,satisfied +58714,60847,Male,Loyal Customer,41,Personal Travel,Eco,1754,1,1,2,3,1,2,1,1,2,2,3,1,4,1,33,11.0,neutral or dissatisfied +58715,54534,Female,Loyal Customer,67,Personal Travel,Eco,925,2,5,2,3,3,5,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +58716,107213,Female,Loyal Customer,52,Business travel,Business,402,1,1,1,1,2,4,4,4,4,4,4,3,4,3,11,0.0,satisfied +58717,74481,Female,Loyal Customer,44,Business travel,Business,2249,4,4,4,4,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +58718,95784,Male,Loyal Customer,62,Personal Travel,Eco,453,2,5,2,3,3,2,3,3,4,3,1,3,5,3,0,13.0,neutral or dissatisfied +58719,76161,Female,Loyal Customer,19,Personal Travel,Eco,546,4,1,4,4,4,4,4,4,4,4,3,2,4,4,0,0.0,satisfied +58720,40220,Male,disloyal Customer,26,Business travel,Eco,387,2,3,2,5,4,2,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +58721,76421,Female,Loyal Customer,44,Business travel,Business,3471,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +58722,117712,Female,Loyal Customer,59,Business travel,Business,1009,1,1,1,1,2,5,4,3,3,2,3,5,3,5,3,0.0,satisfied +58723,98472,Female,Loyal Customer,43,Personal Travel,Eco,210,2,2,2,4,2,3,3,4,4,2,4,4,4,1,44,48.0,neutral or dissatisfied +58724,81921,Male,Loyal Customer,50,Business travel,Business,1532,2,2,2,2,2,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +58725,5001,Female,Loyal Customer,48,Business travel,Eco,502,3,1,3,3,3,3,3,3,2,4,4,3,1,3,116,162.0,neutral or dissatisfied +58726,14046,Female,Loyal Customer,33,Business travel,Business,3283,0,5,0,2,2,2,2,3,3,2,2,3,3,3,0,0.0,satisfied +58727,128702,Male,disloyal Customer,27,Business travel,Business,1464,2,2,2,1,5,2,5,5,3,3,5,5,5,5,66,92.0,neutral or dissatisfied +58728,85208,Male,Loyal Customer,57,Business travel,Eco,689,4,5,5,5,3,4,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +58729,27000,Male,Loyal Customer,32,Business travel,Eco,867,4,4,4,4,4,5,4,4,5,5,1,1,4,4,0,1.0,satisfied +58730,89203,Male,Loyal Customer,19,Personal Travel,Eco,1892,3,5,3,2,4,3,4,4,5,3,3,1,3,4,0,0.0,neutral or dissatisfied +58731,51359,Female,disloyal Customer,34,Business travel,Eco Plus,156,2,2,2,3,4,2,4,4,1,3,4,4,3,4,41,30.0,neutral or dissatisfied +58732,115594,Male,Loyal Customer,43,Business travel,Business,480,2,4,4,4,1,1,1,2,2,2,2,4,2,3,16,19.0,neutral or dissatisfied +58733,114190,Male,Loyal Customer,50,Business travel,Business,846,3,3,3,3,4,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +58734,47949,Male,Loyal Customer,21,Personal Travel,Eco,784,5,3,5,4,1,5,1,1,1,1,4,1,3,1,0,0.0,satisfied +58735,87372,Female,Loyal Customer,66,Business travel,Business,1652,4,3,3,3,5,2,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +58736,62259,Female,disloyal Customer,49,Business travel,Business,1388,4,4,4,4,2,4,2,2,4,2,5,4,5,2,3,0.0,satisfied +58737,95526,Female,Loyal Customer,20,Personal Travel,Eco Plus,239,1,2,1,4,5,1,5,5,1,3,3,3,4,5,0,0.0,neutral or dissatisfied +58738,17415,Male,Loyal Customer,52,Business travel,Business,376,4,5,5,5,3,4,4,4,4,4,4,2,4,1,1,0.0,neutral or dissatisfied +58739,2645,Female,Loyal Customer,50,Business travel,Business,622,1,1,1,1,5,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +58740,38900,Female,Loyal Customer,41,Business travel,Business,162,3,3,3,3,3,5,2,5,5,5,5,2,5,1,0,0.0,satisfied +58741,33960,Female,Loyal Customer,39,Business travel,Business,1598,2,2,2,2,3,5,5,5,5,5,5,4,5,3,74,53.0,satisfied +58742,83797,Male,Loyal Customer,58,Business travel,Business,2569,5,5,3,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +58743,12784,Female,Loyal Customer,24,Personal Travel,Business,528,4,5,4,1,5,4,5,5,3,5,5,4,4,5,0,0.0,satisfied +58744,11195,Female,Loyal Customer,62,Personal Travel,Eco,301,3,3,3,1,3,5,5,4,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +58745,13819,Male,Loyal Customer,28,Business travel,Business,594,1,3,3,3,1,2,1,1,4,5,4,2,4,1,0,4.0,neutral or dissatisfied +58746,100083,Female,Loyal Customer,35,Personal Travel,Eco Plus,289,1,4,1,5,4,1,4,4,5,3,4,5,4,4,8,1.0,neutral or dissatisfied +58747,35693,Female,disloyal Customer,20,Business travel,Eco,2586,2,2,2,3,2,4,4,1,5,4,4,4,3,4,95,104.0,neutral or dissatisfied +58748,15298,Female,Loyal Customer,36,Business travel,Eco,612,2,1,4,1,2,3,2,2,2,3,3,3,4,2,29,25.0,neutral or dissatisfied +58749,1632,Male,Loyal Customer,27,Personal Travel,Eco,999,5,3,5,3,4,5,5,4,4,1,5,1,3,4,5,0.0,satisfied +58750,78506,Male,Loyal Customer,41,Business travel,Eco,666,2,1,4,1,2,2,2,2,2,4,3,3,4,2,25,19.0,neutral or dissatisfied +58751,78530,Male,Loyal Customer,44,Personal Travel,Eco,666,4,4,4,2,3,4,2,3,4,1,5,1,1,3,0,0.0,neutral or dissatisfied +58752,24180,Female,Loyal Customer,39,Business travel,Business,3366,1,1,1,1,4,1,2,5,5,5,4,1,5,2,0,0.0,satisfied +58753,58143,Female,Loyal Customer,39,Business travel,Business,2506,2,3,3,3,1,4,4,2,2,2,2,2,2,2,6,11.0,neutral or dissatisfied +58754,36737,Female,Loyal Customer,58,Business travel,Eco,1754,4,3,3,3,3,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +58755,22577,Female,Loyal Customer,47,Business travel,Eco,300,4,3,3,3,2,4,2,4,4,4,4,2,4,3,0,0.0,satisfied +58756,30191,Female,Loyal Customer,38,Business travel,Eco Plus,95,4,3,3,3,4,4,4,4,2,1,3,4,3,4,0,0.0,satisfied +58757,114217,Male,Loyal Customer,50,Business travel,Business,3038,2,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0.0,satisfied +58758,53070,Male,Loyal Customer,12,Personal Travel,Eco,1208,2,1,1,3,4,1,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +58759,82902,Male,Loyal Customer,19,Personal Travel,Eco,594,4,5,4,3,3,4,1,3,1,1,2,5,4,3,0,0.0,neutral or dissatisfied +58760,24792,Female,Loyal Customer,57,Personal Travel,Eco,447,1,5,1,3,3,4,5,3,3,1,3,3,3,5,1,0.0,neutral or dissatisfied +58761,2171,Male,Loyal Customer,46,Business travel,Business,685,1,1,1,1,3,4,5,1,1,2,1,4,1,4,0,0.0,satisfied +58762,8812,Female,Loyal Customer,22,Business travel,Business,1518,2,2,4,2,4,4,4,4,2,4,1,2,1,4,0,0.0,satisfied +58763,87516,Female,Loyal Customer,11,Personal Travel,Eco,321,0,1,0,3,3,0,3,3,1,2,3,2,3,3,0,0.0,satisfied +58764,88175,Female,Loyal Customer,41,Business travel,Business,3303,5,4,5,5,3,4,4,5,5,5,5,3,5,4,0,2.0,satisfied +58765,78319,Male,Loyal Customer,57,Business travel,Business,1547,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +58766,119835,Female,Loyal Customer,10,Business travel,Business,936,2,4,4,4,2,1,2,2,2,3,4,1,3,2,0,0.0,neutral or dissatisfied +58767,971,Female,disloyal Customer,22,Business travel,Business,102,2,4,2,4,2,2,2,2,3,2,4,4,3,2,5,14.0,neutral or dissatisfied +58768,68059,Female,Loyal Customer,38,Business travel,Business,813,2,2,2,2,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +58769,128170,Male,Loyal Customer,60,Business travel,Business,1788,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +58770,35695,Male,Loyal Customer,46,Business travel,Business,2637,1,1,1,1,1,1,1,1,5,4,3,1,2,1,0,11.0,neutral or dissatisfied +58771,92485,Male,Loyal Customer,54,Business travel,Eco,2139,2,4,4,4,2,2,2,2,1,4,3,3,3,2,3,0.0,neutral or dissatisfied +58772,121430,Male,disloyal Customer,21,Business travel,Eco,331,2,5,2,2,1,2,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +58773,44543,Female,Loyal Customer,25,Personal Travel,Eco,157,5,1,5,3,3,5,3,3,2,5,3,3,3,3,1,0.0,satisfied +58774,46055,Male,Loyal Customer,7,Personal Travel,Eco,991,4,4,4,3,3,4,3,3,3,4,4,4,4,3,0,11.0,neutral or dissatisfied +58775,26304,Male,Loyal Customer,49,Personal Travel,Eco Plus,1199,0,2,0,2,2,0,2,2,2,4,3,4,3,2,0,0.0,satisfied +58776,109757,Female,Loyal Customer,40,Personal Travel,Eco Plus,534,2,5,2,2,5,2,5,5,3,5,5,5,5,5,0,2.0,neutral or dissatisfied +58777,37482,Male,Loyal Customer,64,Business travel,Business,3957,2,4,4,4,3,4,4,2,2,3,2,1,2,2,29,9.0,neutral or dissatisfied +58778,128337,Male,Loyal Customer,55,Business travel,Business,2475,5,5,5,5,3,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +58779,4692,Male,Loyal Customer,9,Personal Travel,Eco,489,3,0,3,5,1,3,4,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +58780,48013,Male,Loyal Customer,32,Personal Travel,Eco Plus,451,2,4,2,2,5,2,5,5,4,5,5,3,5,5,76,72.0,neutral or dissatisfied +58781,107518,Male,Loyal Customer,57,Business travel,Business,2140,2,1,1,1,1,3,4,2,2,2,2,2,2,3,1,3.0,neutral or dissatisfied +58782,66832,Male,Loyal Customer,53,Business travel,Business,731,5,5,4,5,3,4,5,5,5,5,5,4,5,3,51,38.0,satisfied +58783,114852,Male,Loyal Customer,38,Business travel,Business,308,4,4,4,4,3,5,5,4,4,4,4,3,4,4,47,40.0,satisfied +58784,104429,Male,disloyal Customer,20,Business travel,Business,1147,3,2,2,4,1,2,1,1,2,5,4,4,4,1,17,0.0,neutral or dissatisfied +58785,50122,Male,Loyal Customer,46,Business travel,Eco,109,3,1,5,1,4,3,4,4,2,5,3,2,3,4,35,28.0,neutral or dissatisfied +58786,60976,Female,Loyal Customer,43,Personal Travel,Eco,888,3,4,4,2,3,4,5,4,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +58787,18107,Male,disloyal Customer,30,Business travel,Eco,651,3,5,3,1,2,3,1,2,2,4,1,5,2,2,0,0.0,neutral or dissatisfied +58788,27887,Male,Loyal Customer,52,Business travel,Business,2329,5,5,5,5,2,4,1,4,4,4,4,3,4,4,15,0.0,satisfied +58789,82227,Female,Loyal Customer,52,Business travel,Business,405,3,2,2,2,4,3,4,3,3,3,3,4,3,3,3,5.0,neutral or dissatisfied +58790,99080,Female,Loyal Customer,42,Business travel,Business,1543,5,5,5,5,3,4,4,2,2,2,2,4,2,4,7,8.0,satisfied +58791,9288,Male,Loyal Customer,20,Personal Travel,Eco,1190,2,4,2,1,2,1,1,4,2,3,4,1,3,1,198,,neutral or dissatisfied +58792,44176,Male,Loyal Customer,36,Business travel,Eco,157,4,4,4,4,4,4,4,4,2,4,4,5,2,4,5,0.0,satisfied +58793,1103,Female,Loyal Customer,22,Personal Travel,Eco,354,3,5,3,3,3,3,1,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +58794,84445,Male,Loyal Customer,63,Personal Travel,Eco Plus,606,3,4,3,3,2,3,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +58795,46984,Female,Loyal Customer,70,Personal Travel,Eco,850,3,5,3,1,5,4,5,1,1,3,1,4,1,5,9,0.0,neutral or dissatisfied +58796,68369,Male,Loyal Customer,52,Business travel,Business,3974,1,1,1,1,5,4,5,5,5,4,5,4,5,3,34,27.0,satisfied +58797,76487,Female,Loyal Customer,40,Business travel,Business,534,3,5,3,3,4,4,5,5,5,5,5,4,5,3,3,0.0,satisfied +58798,115605,Female,Loyal Customer,70,Business travel,Business,446,1,1,1,1,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +58799,25159,Female,Loyal Customer,60,Business travel,Business,2106,1,1,1,1,2,4,3,1,1,1,1,2,1,4,24,27.0,neutral or dissatisfied +58800,13351,Female,Loyal Customer,14,Business travel,Business,2835,3,1,1,1,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +58801,89715,Male,Loyal Customer,64,Personal Travel,Eco,950,1,4,1,2,3,1,3,3,5,1,5,4,5,3,2,0.0,neutral or dissatisfied +58802,13511,Male,disloyal Customer,21,Business travel,Eco,152,3,0,3,1,3,3,2,3,3,5,1,2,5,3,0,0.0,neutral or dissatisfied +58803,68300,Female,Loyal Customer,57,Business travel,Business,1797,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +58804,30711,Male,Loyal Customer,29,Personal Travel,Eco,464,0,5,0,2,1,0,1,1,5,5,5,3,4,1,14,5.0,satisfied +58805,45347,Male,Loyal Customer,23,Personal Travel,Eco,222,1,4,1,4,1,1,1,1,2,1,4,3,3,1,28,12.0,neutral or dissatisfied +58806,115912,Female,disloyal Customer,27,Business travel,Eco,390,2,0,2,4,5,2,5,5,3,1,2,3,3,5,18,18.0,neutral or dissatisfied +58807,59003,Male,Loyal Customer,41,Business travel,Business,1846,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,17.0,satisfied +58808,97707,Female,Loyal Customer,47,Personal Travel,Eco,456,3,5,3,3,4,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +58809,57307,Female,Loyal Customer,7,Personal Travel,Business,236,3,5,0,4,3,0,2,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +58810,87016,Male,Loyal Customer,24,Personal Travel,Eco Plus,907,3,4,3,3,3,3,1,3,5,5,4,5,4,3,50,35.0,neutral or dissatisfied +58811,33817,Male,Loyal Customer,58,Personal Travel,Eco,1428,2,2,2,4,1,2,1,1,4,4,4,1,4,1,54,37.0,neutral or dissatisfied +58812,105514,Female,Loyal Customer,50,Business travel,Business,2624,2,2,2,2,4,5,5,5,5,5,5,3,5,4,9,30.0,satisfied +58813,8537,Female,disloyal Customer,29,Business travel,Business,109,3,3,3,4,4,3,3,4,4,3,5,3,4,4,3,2.0,neutral or dissatisfied +58814,76172,Male,Loyal Customer,30,Personal Travel,Eco,689,2,1,2,3,4,2,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +58815,69962,Male,Loyal Customer,44,Personal Travel,Eco,2174,3,4,3,3,3,3,3,3,2,1,4,3,3,3,0,0.0,neutral or dissatisfied +58816,44342,Male,Loyal Customer,31,Personal Travel,Eco,230,1,5,0,1,4,0,4,4,5,5,4,4,4,4,58,43.0,neutral or dissatisfied +58817,41513,Female,Loyal Customer,50,Business travel,Eco,1242,5,4,5,4,5,4,4,2,2,5,5,4,1,4,134,147.0,satisfied +58818,103141,Female,Loyal Customer,61,Personal Travel,Eco Plus,546,2,4,2,5,3,4,2,2,2,2,2,2,2,5,55,53.0,neutral or dissatisfied +58819,9605,Female,Loyal Customer,64,Personal Travel,Eco,229,1,5,1,5,2,5,4,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +58820,10398,Male,Loyal Customer,41,Business travel,Business,667,5,5,4,5,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +58821,95441,Female,Loyal Customer,43,Business travel,Business,3166,2,2,2,2,2,5,4,4,4,4,4,4,4,3,8,0.0,satisfied +58822,7789,Male,Loyal Customer,52,Business travel,Business,1735,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,5.0,satisfied +58823,70298,Male,Loyal Customer,53,Personal Travel,Eco,852,2,4,2,2,1,2,1,1,3,3,4,4,5,1,11,16.0,neutral or dissatisfied +58824,95362,Female,Loyal Customer,39,Personal Travel,Eco,248,1,4,0,3,1,0,5,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +58825,18498,Female,Loyal Customer,35,Business travel,Business,190,2,2,2,2,4,2,4,5,5,5,5,3,5,1,0,0.0,satisfied +58826,7062,Female,Loyal Customer,45,Business travel,Business,157,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +58827,106828,Female,Loyal Customer,36,Business travel,Eco Plus,1488,1,4,4,4,1,1,1,1,1,2,4,3,3,1,3,0.0,neutral or dissatisfied +58828,102255,Male,Loyal Customer,39,Business travel,Business,226,0,0,0,5,4,4,5,2,2,2,2,4,2,5,8,0.0,satisfied +58829,108123,Male,Loyal Customer,50,Business travel,Business,2204,2,2,2,2,5,5,4,2,2,2,2,4,2,5,0,4.0,satisfied +58830,45404,Female,Loyal Customer,61,Business travel,Eco,458,4,4,4,4,2,4,3,4,4,4,4,5,4,3,0,0.0,satisfied +58831,13002,Female,Loyal Customer,52,Business travel,Business,2579,2,2,2,2,3,3,5,5,5,5,5,5,5,1,0,0.0,satisfied +58832,116047,Male,Loyal Customer,9,Personal Travel,Eco,337,3,3,3,4,3,3,3,3,4,1,3,4,3,3,10,2.0,neutral or dissatisfied +58833,80088,Male,Loyal Customer,11,Personal Travel,Eco Plus,1010,3,2,3,3,4,3,4,4,1,4,2,2,3,4,45,43.0,neutral or dissatisfied +58834,100778,Male,Loyal Customer,69,Personal Travel,Eco,1411,3,2,3,4,3,3,1,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +58835,89621,Female,Loyal Customer,40,Business travel,Business,2561,2,2,2,2,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +58836,30881,Female,Loyal Customer,41,Personal Travel,Eco,1546,3,4,3,4,3,1,1,2,5,4,3,1,4,1,132,145.0,neutral or dissatisfied +58837,45675,Female,disloyal Customer,28,Business travel,Eco,896,1,2,2,5,2,2,1,2,3,3,1,1,1,2,2,8.0,neutral or dissatisfied +58838,43516,Female,Loyal Customer,58,Personal Travel,Eco,679,3,4,4,1,5,5,2,5,5,4,1,5,5,3,4,3.0,neutral or dissatisfied +58839,101648,Male,Loyal Customer,35,Personal Travel,Eco,1749,2,2,2,4,3,2,5,3,4,3,3,3,3,3,17,0.0,neutral or dissatisfied +58840,105149,Male,disloyal Customer,30,Business travel,Eco,289,2,2,2,3,4,2,3,4,2,2,3,3,3,4,0,0.0,neutral or dissatisfied +58841,45155,Male,Loyal Customer,50,Business travel,Business,3298,2,2,2,2,1,3,3,4,4,4,4,4,4,2,0,0.0,satisfied +58842,103516,Female,Loyal Customer,62,Personal Travel,Eco,1256,3,4,3,3,2,3,4,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +58843,8040,Male,Loyal Customer,55,Business travel,Business,125,2,2,2,2,4,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +58844,125198,Male,Loyal Customer,22,Business travel,Business,651,1,2,2,2,1,1,1,1,4,2,3,3,4,1,27,25.0,neutral or dissatisfied +58845,111517,Male,Loyal Customer,59,Personal Travel,Eco,391,1,5,1,1,1,1,1,1,5,4,4,3,4,1,21,22.0,neutral or dissatisfied +58846,105406,Female,Loyal Customer,29,Personal Travel,Eco,369,2,1,5,3,5,5,5,5,2,4,3,4,3,5,0,0.0,neutral or dissatisfied +58847,35617,Male,Loyal Customer,31,Personal Travel,Eco Plus,1144,2,5,2,2,4,2,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +58848,24822,Female,disloyal Customer,37,Business travel,Eco,894,3,3,3,1,2,3,2,2,1,1,3,2,1,2,0,0.0,neutral or dissatisfied +58849,103909,Female,Loyal Customer,51,Business travel,Business,133,0,5,0,5,2,4,5,5,5,5,5,5,5,3,38,66.0,satisfied +58850,112185,Male,Loyal Customer,57,Personal Travel,Eco,895,3,4,3,3,1,3,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +58851,124003,Female,disloyal Customer,43,Business travel,Eco,184,2,3,2,2,5,2,5,5,4,2,3,1,3,5,0,0.0,neutral or dissatisfied +58852,60683,Male,Loyal Customer,63,Business travel,Business,1005,1,5,5,5,2,3,4,1,1,1,1,2,1,1,3,0.0,neutral or dissatisfied +58853,111636,Female,disloyal Customer,30,Business travel,Business,1558,5,5,5,1,4,5,4,4,4,3,5,5,4,4,0,0.0,satisfied +58854,125967,Male,disloyal Customer,41,Business travel,Business,328,3,4,4,3,3,4,5,3,5,5,4,5,4,5,206,208.0,satisfied +58855,49082,Male,Loyal Customer,41,Business travel,Eco,156,2,5,5,5,2,2,2,2,4,1,4,5,2,2,36,28.0,satisfied +58856,71245,Female,disloyal Customer,32,Business travel,Business,733,3,3,3,2,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +58857,90810,Male,disloyal Customer,59,Business travel,Business,271,1,1,1,3,1,1,1,1,1,5,4,3,4,1,0,8.0,neutral or dissatisfied +58858,7411,Female,Loyal Customer,42,Business travel,Business,522,5,2,5,5,5,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +58859,127568,Female,Loyal Customer,29,Business travel,Business,1670,4,2,2,2,4,4,4,4,2,1,4,4,4,4,2,30.0,neutral or dissatisfied +58860,54535,Female,Loyal Customer,15,Personal Travel,Eco,925,1,4,1,3,1,1,1,1,5,2,4,5,5,1,7,0.0,neutral or dissatisfied +58861,62012,Female,disloyal Customer,35,Business travel,Business,2586,2,1,1,2,2,1,4,2,5,3,4,5,4,2,32,4.0,neutral or dissatisfied +58862,24586,Male,disloyal Customer,52,Business travel,Eco,526,3,0,4,4,2,4,2,2,2,4,4,5,2,2,0,0.0,neutral or dissatisfied +58863,48703,Female,Loyal Customer,46,Business travel,Business,2099,3,3,3,3,3,4,4,4,4,4,4,5,4,3,49,40.0,satisfied +58864,41650,Female,Loyal Customer,30,Business travel,Business,1545,3,3,4,3,5,5,5,5,2,4,5,2,5,5,0,11.0,satisfied +58865,107323,Male,Loyal Customer,41,Business travel,Business,584,1,1,1,1,2,5,5,5,5,5,5,3,5,5,12,5.0,satisfied +58866,111214,Male,disloyal Customer,42,Business travel,Eco,1419,3,3,3,3,1,3,1,1,4,5,2,4,2,1,0,0.0,neutral or dissatisfied +58867,28364,Male,Loyal Customer,24,Business travel,Eco Plus,954,3,4,4,4,3,3,1,3,4,3,3,1,2,3,0,0.0,neutral or dissatisfied +58868,123781,Male,Loyal Customer,59,Business travel,Business,3644,3,3,3,3,4,5,5,5,5,5,5,4,5,3,0,6.0,satisfied +58869,83952,Female,Loyal Customer,49,Business travel,Business,2529,1,1,1,1,5,5,4,5,5,4,5,3,5,4,15,0.0,satisfied +58870,45198,Male,Loyal Customer,60,Business travel,Eco,1120,5,1,1,1,5,5,5,5,3,3,5,4,2,5,12,0.0,satisfied +58871,19471,Female,disloyal Customer,39,Business travel,Business,177,1,1,1,4,1,1,1,1,4,1,2,5,3,1,0,0.0,neutral or dissatisfied +58872,8117,Male,Loyal Customer,39,Business travel,Business,530,1,4,3,4,3,4,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +58873,34571,Male,Loyal Customer,51,Business travel,Eco,1598,3,5,5,5,3,3,3,3,3,1,1,4,2,3,0,16.0,neutral or dissatisfied +58874,57082,Female,Loyal Customer,42,Business travel,Business,2154,2,2,2,2,3,5,5,2,2,2,2,4,2,5,0,10.0,satisfied +58875,52633,Female,Loyal Customer,33,Business travel,Eco,160,3,5,5,5,3,3,3,3,2,5,1,2,2,3,61,59.0,neutral or dissatisfied +58876,16471,Female,Loyal Customer,33,Business travel,Eco Plus,416,0,0,0,2,4,0,4,4,4,4,5,1,2,4,0,0.0,satisfied +58877,28879,Male,Loyal Customer,48,Business travel,Business,3816,3,2,4,2,2,3,4,3,3,3,3,1,3,2,2,0.0,neutral or dissatisfied +58878,11034,Female,Loyal Customer,24,Business travel,Eco,191,2,4,1,4,2,2,2,2,3,2,4,3,3,2,2,6.0,neutral or dissatisfied +58879,82948,Male,Loyal Customer,47,Business travel,Business,957,2,4,3,4,1,3,3,2,2,2,2,2,2,2,0,9.0,neutral or dissatisfied +58880,126610,Female,Loyal Customer,29,Personal Travel,Eco,1337,3,2,3,3,4,3,1,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +58881,2288,Male,Loyal Customer,54,Business travel,Business,3958,1,0,0,3,1,3,3,4,4,0,4,4,4,3,0,0.0,neutral or dissatisfied +58882,14276,Male,Loyal Customer,43,Business travel,Eco,395,5,2,2,2,5,5,5,5,1,1,2,5,2,5,0,0.0,satisfied +58883,99243,Male,Loyal Customer,47,Personal Travel,Eco,495,5,5,5,2,4,5,4,4,3,5,4,4,4,4,4,1.0,satisfied +58884,87808,Male,Loyal Customer,51,Business travel,Business,1895,1,4,4,4,1,3,3,3,3,3,1,3,3,1,0,0.0,neutral or dissatisfied +58885,80850,Female,disloyal Customer,35,Business travel,Eco,692,3,3,3,2,1,3,1,1,1,5,3,5,1,1,0,0.0,neutral or dissatisfied +58886,96797,Male,Loyal Customer,51,Business travel,Business,3647,2,2,2,2,4,3,3,2,2,2,2,3,2,1,8,11.0,neutral or dissatisfied +58887,32368,Female,disloyal Customer,56,Business travel,Eco,102,1,2,1,3,1,1,1,1,3,4,3,4,2,1,0,0.0,neutral or dissatisfied +58888,129773,Female,Loyal Customer,60,Personal Travel,Eco,337,2,4,2,5,4,4,4,2,2,2,2,5,2,4,2,3.0,neutral or dissatisfied +58889,77745,Female,disloyal Customer,27,Business travel,Eco,874,1,1,1,4,5,1,5,5,1,4,3,2,4,5,27,15.0,neutral or dissatisfied +58890,10770,Female,Loyal Customer,34,Business travel,Business,2596,1,1,1,1,5,5,4,4,4,4,4,5,4,3,57,53.0,satisfied +58891,126310,Male,Loyal Customer,27,Personal Travel,Eco,328,2,4,2,5,4,2,4,4,4,5,4,5,5,4,1,0.0,neutral or dissatisfied +58892,63751,Male,Loyal Customer,22,Personal Travel,Eco,1660,3,1,3,3,4,3,4,4,2,5,3,4,2,4,32,22.0,neutral or dissatisfied +58893,65483,Female,Loyal Customer,30,Business travel,Business,1564,4,4,4,4,4,4,4,4,2,1,2,3,2,4,2,0.0,satisfied +58894,11352,Male,Loyal Customer,17,Personal Travel,Eco,201,3,1,0,2,3,0,3,3,1,2,2,3,3,3,4,3.0,neutral or dissatisfied +58895,126080,Female,disloyal Customer,18,Business travel,Eco,650,4,0,4,2,4,4,4,4,4,2,4,3,5,4,0,0.0,satisfied +58896,40239,Male,Loyal Customer,35,Business travel,Eco,463,4,4,4,4,4,4,4,4,3,1,4,2,5,4,0,0.0,satisfied +58897,95226,Male,Loyal Customer,13,Personal Travel,Eco,239,3,5,3,2,4,3,4,4,1,4,4,1,3,4,4,0.0,neutral or dissatisfied +58898,44829,Female,Loyal Customer,42,Business travel,Business,462,4,3,1,1,2,3,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +58899,35796,Male,Loyal Customer,18,Personal Travel,Eco,200,2,5,2,3,1,2,1,1,3,5,1,5,1,1,0,0.0,neutral or dissatisfied +58900,122945,Male,disloyal Customer,39,Business travel,Business,468,3,3,3,3,2,3,5,2,3,5,5,3,4,2,43,48.0,neutral or dissatisfied +58901,98521,Male,Loyal Customer,35,Personal Travel,Eco,402,5,3,5,1,1,5,1,1,5,3,3,5,5,1,0,0.0,satisfied +58902,120387,Male,disloyal Customer,29,Business travel,Business,366,4,3,3,3,4,3,4,4,3,4,4,3,5,4,0,15.0,satisfied +58903,82718,Female,Loyal Customer,67,Personal Travel,Eco,632,5,5,5,4,4,5,5,2,2,5,2,4,2,4,0,0.0,satisfied +58904,77943,Male,disloyal Customer,22,Business travel,Business,214,5,0,5,5,3,5,3,3,5,4,4,3,4,3,54,53.0,satisfied +58905,10924,Female,Loyal Customer,33,Business travel,Eco,312,1,1,1,1,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +58906,87103,Female,Loyal Customer,26,Personal Travel,Eco,594,3,4,3,4,1,3,1,1,1,5,3,1,3,1,0,0.0,neutral or dissatisfied +58907,113887,Male,disloyal Customer,35,Business travel,Business,2295,1,1,1,1,2,1,2,2,4,4,5,3,4,2,12,14.0,neutral or dissatisfied +58908,47024,Male,Loyal Customer,23,Business travel,Eco,639,5,2,2,2,5,5,5,5,2,2,1,1,5,5,2,1.0,satisfied +58909,126480,Female,Loyal Customer,55,Business travel,Business,1788,3,3,3,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +58910,120492,Female,Loyal Customer,46,Personal Travel,Eco,366,2,5,2,4,4,5,3,3,3,2,1,1,3,2,0,0.0,neutral or dissatisfied +58911,72296,Male,Loyal Customer,54,Personal Travel,Eco,919,3,4,3,2,5,3,4,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +58912,12325,Female,Loyal Customer,58,Business travel,Eco,262,4,4,4,4,2,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +58913,82495,Male,Loyal Customer,26,Personal Travel,Eco,488,3,5,3,2,5,3,5,5,5,5,5,4,5,5,0,2.0,neutral or dissatisfied +58914,118698,Female,Loyal Customer,56,Personal Travel,Eco,304,4,2,4,4,1,3,4,3,3,4,3,2,3,1,4,0.0,satisfied +58915,34802,Female,Loyal Customer,34,Personal Travel,Eco,301,2,4,2,2,3,2,3,3,4,4,4,4,1,3,3,36.0,neutral or dissatisfied +58916,90585,Male,Loyal Customer,40,Business travel,Business,404,1,1,4,1,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +58917,30532,Female,Loyal Customer,52,Business travel,Business,683,1,1,1,1,5,5,5,3,1,4,5,5,1,5,242,263.0,satisfied +58918,115118,Female,Loyal Customer,32,Business travel,Business,3226,3,3,1,3,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +58919,62116,Female,disloyal Customer,28,Business travel,Business,2565,4,5,5,5,4,5,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +58920,25562,Male,disloyal Customer,36,Business travel,Eco,874,3,4,4,3,1,4,4,1,5,5,2,3,2,1,30,18.0,neutral or dissatisfied +58921,115729,Female,disloyal Customer,44,Business travel,Eco,337,1,3,1,3,5,1,5,5,4,4,2,2,2,5,0,0.0,neutral or dissatisfied +58922,104762,Male,Loyal Customer,29,Personal Travel,Eco,1246,1,5,1,4,2,1,1,2,3,5,4,5,5,2,8,18.0,neutral or dissatisfied +58923,37696,Male,Loyal Customer,36,Personal Travel,Eco,1080,3,4,3,4,2,3,2,2,4,3,4,5,4,2,105,89.0,neutral or dissatisfied +58924,101056,Female,Loyal Customer,21,Business travel,Business,2682,2,2,2,2,5,5,5,3,2,4,5,5,5,5,153,141.0,satisfied +58925,26391,Female,Loyal Customer,58,Personal Travel,Eco,534,3,4,3,2,4,5,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +58926,89043,Female,Loyal Customer,47,Business travel,Business,1947,2,2,5,2,3,3,5,4,4,4,4,5,4,5,5,0.0,satisfied +58927,19535,Female,Loyal Customer,50,Business travel,Eco,212,5,2,2,2,2,3,2,5,5,5,5,1,5,5,62,53.0,satisfied +58928,50450,Female,Loyal Customer,57,Business travel,Business,3938,3,1,1,1,4,4,4,3,3,2,3,3,3,4,0,6.0,neutral or dissatisfied +58929,33735,Female,Loyal Customer,8,Personal Travel,Eco,759,1,5,1,3,1,1,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +58930,39109,Male,Loyal Customer,43,Business travel,Business,3716,0,4,0,3,5,3,1,4,4,3,3,2,4,1,0,0.0,satisfied +58931,94114,Female,Loyal Customer,40,Personal Travel,Business,677,3,3,3,3,4,3,4,3,3,3,2,3,3,4,0,0.0,neutral or dissatisfied +58932,82849,Female,disloyal Customer,25,Business travel,Business,640,4,4,4,3,1,4,1,1,5,2,4,5,5,1,81,73.0,satisfied +58933,14246,Male,Loyal Customer,41,Personal Travel,Eco,1027,1,5,1,2,3,1,1,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +58934,88403,Female,Loyal Customer,36,Business travel,Business,3129,4,3,3,3,4,4,3,4,4,4,4,3,4,3,26,29.0,neutral or dissatisfied +58935,90815,Female,Loyal Customer,44,Business travel,Business,594,2,5,5,5,1,1,1,2,2,2,2,3,2,1,0,8.0,neutral or dissatisfied +58936,112466,Female,disloyal Customer,41,Business travel,Business,557,3,3,3,3,5,3,2,5,1,5,4,4,4,5,21,9.0,neutral or dissatisfied +58937,31553,Female,Loyal Customer,60,Personal Travel,Eco,853,4,4,4,2,2,4,4,3,3,4,2,5,3,3,11,7.0,neutral or dissatisfied +58938,28428,Female,Loyal Customer,50,Business travel,Business,2042,3,4,4,4,3,3,3,4,1,3,3,3,1,3,0,0.0,neutral or dissatisfied +58939,70618,Female,Loyal Customer,37,Business travel,Eco,1217,1,0,0,3,1,0,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +58940,107476,Male,Loyal Customer,40,Business travel,Business,1546,1,1,2,1,3,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +58941,43071,Male,Loyal Customer,41,Personal Travel,Eco,192,1,3,0,5,3,0,3,3,4,3,1,2,5,3,0,0.0,neutral or dissatisfied +58942,48479,Male,Loyal Customer,42,Business travel,Eco,850,5,1,3,3,5,5,5,5,5,2,3,1,4,5,27,35.0,satisfied +58943,40520,Female,Loyal Customer,77,Business travel,Eco Plus,175,1,5,5,5,2,3,3,2,2,1,2,4,2,1,57,52.0,neutral or dissatisfied +58944,94649,Female,Loyal Customer,59,Business travel,Business,3036,4,4,4,4,3,4,4,5,5,5,5,3,5,3,15,16.0,satisfied +58945,129448,Male,Loyal Customer,53,Personal Travel,Eco,414,2,5,5,4,1,5,1,1,5,2,2,4,3,1,57,45.0,neutral or dissatisfied +58946,50332,Male,Loyal Customer,57,Business travel,Eco,109,2,1,1,1,2,2,2,2,2,2,4,5,2,2,7,11.0,satisfied +58947,21400,Female,Loyal Customer,41,Business travel,Eco,331,4,4,4,4,4,4,4,4,1,4,1,3,4,4,0,0.0,satisfied +58948,19101,Female,Loyal Customer,59,Business travel,Eco,323,1,1,1,1,1,1,1,4,3,4,3,1,1,1,150,153.0,neutral or dissatisfied +58949,125961,Male,Loyal Customer,24,Personal Travel,Eco Plus,920,2,3,2,4,4,2,4,4,3,2,3,3,3,4,0,5.0,neutral or dissatisfied +58950,72651,Male,Loyal Customer,58,Personal Travel,Eco,1121,2,4,2,1,1,2,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +58951,20802,Male,disloyal Customer,22,Business travel,Eco,534,2,3,2,4,3,2,3,3,3,2,2,1,5,3,0,0.0,neutral or dissatisfied +58952,18302,Female,Loyal Customer,43,Personal Travel,Business,1024,3,5,3,2,2,3,4,2,2,3,2,4,2,2,0,21.0,neutral or dissatisfied +58953,11192,Male,Loyal Customer,16,Personal Travel,Eco,517,3,5,3,2,2,3,2,2,4,5,5,4,5,2,0,8.0,neutral or dissatisfied +58954,299,Male,Loyal Customer,41,Business travel,Business,590,2,2,2,2,3,5,4,5,5,5,5,5,5,3,45,50.0,satisfied +58955,121,Female,Loyal Customer,38,Personal Travel,Eco,562,2,1,2,2,5,2,4,5,3,3,2,1,3,5,0,6.0,neutral or dissatisfied +58956,107938,Male,Loyal Customer,32,Personal Travel,Eco,611,3,4,3,4,4,3,5,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +58957,39200,Male,Loyal Customer,33,Business travel,Business,173,4,4,4,4,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +58958,77192,Female,Loyal Customer,23,Personal Travel,Eco,290,2,5,2,1,3,2,2,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +58959,65698,Male,Loyal Customer,45,Personal Travel,Business,1061,1,4,1,2,5,5,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +58960,11830,Male,Loyal Customer,13,Personal Travel,Eco,986,3,5,4,3,3,4,3,3,3,3,4,5,4,3,22,14.0,neutral or dissatisfied +58961,88258,Female,Loyal Customer,43,Business travel,Eco,406,4,4,4,4,3,3,3,4,4,4,4,1,4,3,0,15.0,neutral or dissatisfied +58962,126038,Female,Loyal Customer,43,Business travel,Business,1805,5,5,5,5,3,5,5,4,4,4,4,4,4,3,77,86.0,satisfied +58963,115494,Male,Loyal Customer,61,Business travel,Business,1524,2,2,2,2,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +58964,1564,Female,Loyal Customer,62,Personal Travel,Business,140,1,4,1,5,4,5,4,4,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +58965,14561,Male,Loyal Customer,39,Business travel,Business,1021,3,3,3,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +58966,38169,Female,Loyal Customer,67,Personal Travel,Eco,1121,2,5,2,4,4,5,4,3,3,2,3,4,3,5,38,24.0,neutral or dissatisfied +58967,113041,Female,Loyal Customer,52,Business travel,Business,2722,5,5,5,5,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +58968,83839,Female,Loyal Customer,43,Business travel,Eco,425,2,3,3,3,3,4,3,2,2,2,2,2,2,1,33,28.0,neutral or dissatisfied +58969,124817,Female,disloyal Customer,22,Business travel,Eco,280,4,2,4,4,3,4,3,3,1,4,4,2,4,3,17,43.0,neutral or dissatisfied +58970,18235,Female,disloyal Customer,20,Business travel,Eco,346,4,0,4,2,1,4,1,1,3,5,5,2,1,1,1,0.0,satisfied +58971,601,Female,Loyal Customer,57,Business travel,Business,2939,0,0,0,2,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +58972,27847,Male,Loyal Customer,33,Personal Travel,Eco,1533,2,5,2,4,5,2,5,5,3,5,3,5,4,5,0,0.0,neutral or dissatisfied +58973,64932,Female,Loyal Customer,62,Business travel,Eco,190,3,4,4,4,5,4,3,3,3,3,3,2,3,2,10,13.0,neutral or dissatisfied +58974,8677,Male,Loyal Customer,26,Business travel,Eco,280,2,1,4,1,2,2,3,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +58975,4447,Male,Loyal Customer,14,Personal Travel,Eco,762,3,4,3,2,1,3,5,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +58976,115004,Female,Loyal Customer,47,Business travel,Business,358,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +58977,34056,Female,disloyal Customer,22,Business travel,Eco,1303,2,2,2,1,3,2,3,3,5,4,3,4,5,3,0,0.0,neutral or dissatisfied +58978,48626,Female,Loyal Customer,11,Personal Travel,Eco Plus,833,2,5,2,1,3,2,2,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +58979,97268,Female,Loyal Customer,53,Personal Travel,Eco,393,3,4,3,1,4,5,5,3,3,3,4,4,3,3,0,1.0,neutral or dissatisfied +58980,61628,Female,Loyal Customer,60,Business travel,Business,1303,3,3,2,3,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +58981,37716,Female,Loyal Customer,17,Personal Travel,Eco,1035,1,3,1,3,5,1,5,5,3,3,3,3,4,5,16,18.0,neutral or dissatisfied +58982,111561,Female,Loyal Customer,34,Business travel,Eco,775,3,4,4,4,3,3,3,3,1,3,4,3,4,3,64,60.0,neutral or dissatisfied +58983,48989,Female,Loyal Customer,63,Business travel,Business,308,0,0,0,1,3,5,4,5,5,2,2,2,5,2,0,7.0,satisfied +58984,36636,Male,Loyal Customer,59,Personal Travel,Eco,1220,4,2,4,3,1,4,1,1,4,4,2,4,3,1,0,0.0,neutral or dissatisfied +58985,1441,Female,Loyal Customer,44,Business travel,Business,2938,3,3,3,3,2,4,5,2,2,2,2,3,2,5,5,0.0,satisfied +58986,33303,Male,Loyal Customer,16,Personal Travel,Eco Plus,163,3,4,3,2,5,3,1,5,5,2,5,3,4,5,6,4.0,neutral or dissatisfied +58987,94763,Female,disloyal Customer,24,Business travel,Eco,248,2,1,2,4,2,2,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +58988,95100,Male,Loyal Customer,54,Personal Travel,Eco,496,1,4,5,2,1,5,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +58989,85446,Female,disloyal Customer,38,Business travel,Eco,214,3,2,3,4,5,3,3,5,4,2,4,1,3,5,71,68.0,neutral or dissatisfied +58990,26785,Male,Loyal Customer,54,Personal Travel,Eco,1199,3,3,4,2,1,4,1,1,2,5,3,4,3,1,4,0.0,neutral or dissatisfied +58991,72753,Female,Loyal Customer,22,Personal Travel,Eco,806,4,5,4,2,5,4,5,5,1,2,5,3,1,5,6,0.0,neutral or dissatisfied +58992,92292,Female,Loyal Customer,57,Business travel,Business,1814,5,5,3,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +58993,111329,Male,Loyal Customer,23,Personal Travel,Eco,283,2,2,2,4,1,2,3,1,1,1,3,4,3,1,7,3.0,neutral or dissatisfied +58994,22966,Female,disloyal Customer,30,Business travel,Eco,817,3,3,3,4,1,3,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +58995,10954,Male,Loyal Customer,56,Business travel,Business,1593,4,4,4,4,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +58996,18098,Male,disloyal Customer,24,Business travel,Eco,610,2,0,2,4,3,2,3,3,4,5,2,2,1,3,0,0.0,neutral or dissatisfied +58997,44582,Male,Loyal Customer,30,Business travel,Business,157,2,2,2,2,4,4,3,4,3,5,5,4,5,4,2,0.0,satisfied +58998,12696,Female,Loyal Customer,51,Business travel,Eco,721,4,4,4,4,3,5,5,4,4,4,4,2,4,5,3,2.0,satisfied +58999,19550,Female,disloyal Customer,40,Business travel,Business,108,3,3,3,4,5,3,5,5,1,3,4,4,3,5,0,0.0,neutral or dissatisfied +59000,129313,Male,Loyal Customer,50,Business travel,Business,2378,1,1,1,1,5,4,5,4,4,4,4,4,4,3,28,25.0,satisfied +59001,81487,Male,Loyal Customer,9,Personal Travel,Eco,408,4,5,4,2,2,4,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +59002,37617,Female,Loyal Customer,35,Personal Travel,Eco,1076,2,4,1,5,5,1,5,5,5,3,4,3,4,5,5,0.0,neutral or dissatisfied +59003,19731,Female,Loyal Customer,70,Personal Travel,Eco,475,1,4,1,1,1,5,5,1,1,1,1,5,1,5,63,50.0,neutral or dissatisfied +59004,41213,Female,disloyal Customer,56,Business travel,Eco,691,2,2,2,5,1,2,2,1,5,5,2,1,1,1,4,0.0,neutral or dissatisfied +59005,24237,Female,Loyal Customer,17,Business travel,Business,3880,2,5,5,5,2,2,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +59006,81403,Female,Loyal Customer,16,Personal Travel,Eco Plus,874,3,2,3,4,1,3,1,1,2,3,3,2,3,1,3,16.0,neutral or dissatisfied +59007,107276,Male,disloyal Customer,36,Business travel,Business,283,3,3,3,4,5,3,5,5,3,1,4,1,3,5,0,0.0,neutral or dissatisfied +59008,14047,Female,Loyal Customer,19,Personal Travel,Eco,363,3,5,3,3,5,3,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +59009,71799,Male,Loyal Customer,34,Business travel,Business,1846,3,3,3,3,3,4,5,4,4,4,4,4,4,5,1,0.0,satisfied +59010,67536,Female,Loyal Customer,52,Business travel,Business,1188,3,2,2,2,4,3,2,3,3,3,3,4,3,4,0,12.0,neutral or dissatisfied +59011,108069,Male,Loyal Customer,40,Business travel,Business,3160,4,3,4,4,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +59012,2694,Female,Loyal Customer,40,Business travel,Business,2405,2,2,2,2,3,5,5,4,4,4,4,3,4,3,35,40.0,satisfied +59013,76149,Female,disloyal Customer,50,Business travel,Eco,689,2,2,2,4,4,2,2,4,4,2,3,3,4,4,4,3.0,neutral or dissatisfied +59014,95168,Female,Loyal Customer,50,Personal Travel,Eco,239,2,5,0,1,4,4,4,5,5,0,5,4,5,5,19,16.0,neutral or dissatisfied +59015,93690,Female,Loyal Customer,72,Business travel,Eco,1452,3,1,5,5,3,2,2,3,3,3,3,1,3,2,0,8.0,neutral or dissatisfied +59016,38340,Male,disloyal Customer,22,Business travel,Eco,1050,1,1,1,2,4,1,4,4,2,3,1,4,5,4,0,32.0,neutral or dissatisfied +59017,24305,Male,Loyal Customer,32,Business travel,Eco Plus,151,1,5,5,5,1,1,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +59018,53672,Female,Loyal Customer,43,Business travel,Eco,1208,5,1,4,1,4,3,5,5,5,5,5,1,5,5,16,0.0,satisfied +59019,19023,Female,Loyal Customer,30,Personal Travel,Eco,828,3,5,3,3,5,3,5,5,5,5,5,5,5,5,22,39.0,neutral or dissatisfied +59020,76285,Female,Loyal Customer,23,Business travel,Business,1927,2,2,2,2,4,4,4,4,5,4,3,4,5,4,21,24.0,satisfied +59021,128875,Male,disloyal Customer,20,Business travel,Eco,2565,3,3,3,1,3,5,5,4,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +59022,53353,Female,disloyal Customer,30,Business travel,Eco,1445,3,3,3,3,5,3,2,5,2,4,2,1,3,5,19,16.0,neutral or dissatisfied +59023,42818,Male,Loyal Customer,52,Personal Travel,Eco,896,3,4,3,1,3,3,3,3,3,1,1,4,5,3,0,9.0,neutral or dissatisfied +59024,110394,Male,Loyal Customer,51,Business travel,Business,3013,2,2,5,2,4,5,4,5,5,5,5,3,5,3,96,88.0,satisfied +59025,92586,Female,disloyal Customer,28,Business travel,Business,2342,4,3,3,3,3,3,1,3,5,2,3,4,5,3,0,5.0,satisfied +59026,47329,Male,Loyal Customer,50,Business travel,Eco,584,5,1,1,1,5,5,5,5,4,1,3,3,1,5,0,0.0,satisfied +59027,85411,Male,Loyal Customer,47,Business travel,Business,3907,5,5,4,5,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +59028,122183,Female,Loyal Customer,56,Business travel,Business,544,4,4,4,4,3,5,4,4,4,4,4,3,4,5,8,10.0,satisfied +59029,80811,Male,Loyal Customer,20,Business travel,Business,484,3,3,3,3,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +59030,112656,Female,Loyal Customer,43,Business travel,Business,2901,5,2,5,5,5,4,4,5,5,5,5,5,5,4,68,73.0,satisfied +59031,58942,Male,Loyal Customer,54,Business travel,Business,1588,1,1,1,1,5,5,5,3,3,3,3,4,3,3,1,3.0,satisfied +59032,4482,Male,Loyal Customer,20,Personal Travel,Eco,1147,2,4,2,2,5,2,5,5,5,3,3,3,4,5,0,36.0,neutral or dissatisfied +59033,73950,Male,Loyal Customer,70,Business travel,Business,830,3,3,3,3,5,5,5,5,2,1,2,5,1,5,0,0.0,satisfied +59034,11084,Male,Loyal Customer,49,Personal Travel,Eco,295,2,4,2,1,2,2,4,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +59035,70096,Female,Loyal Customer,43,Business travel,Business,1677,4,4,4,4,5,4,4,5,5,4,5,4,5,5,0,4.0,satisfied +59036,65060,Male,Loyal Customer,16,Personal Travel,Eco,247,4,5,4,4,1,4,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +59037,44449,Female,Loyal Customer,46,Business travel,Business,803,3,1,1,1,1,3,3,3,3,3,3,3,3,1,0,7.0,neutral or dissatisfied +59038,31383,Male,Loyal Customer,39,Business travel,Business,895,2,2,2,2,3,5,2,4,4,4,4,4,4,2,64,56.0,satisfied +59039,44563,Female,Loyal Customer,10,Personal Travel,Business,177,3,4,3,2,1,3,1,1,2,3,1,2,4,1,0,0.0,neutral or dissatisfied +59040,107754,Male,Loyal Customer,32,Personal Travel,Eco,405,3,2,3,3,4,3,4,4,2,1,3,4,4,4,0,2.0,neutral or dissatisfied +59041,60506,Male,Loyal Customer,46,Personal Travel,Eco,862,1,4,1,4,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +59042,33752,Female,disloyal Customer,34,Business travel,Eco,266,3,0,3,3,2,3,2,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +59043,111969,Male,Loyal Customer,15,Business travel,Business,2131,2,2,2,2,2,2,2,2,3,5,3,2,4,2,32,33.0,neutral or dissatisfied +59044,31752,Male,Loyal Customer,16,Business travel,Business,771,1,3,3,3,1,1,1,1,2,2,4,2,3,1,0,7.0,neutral or dissatisfied +59045,116471,Female,Loyal Customer,17,Personal Travel,Eco,308,2,3,2,3,5,2,4,5,2,1,3,2,4,5,15,11.0,neutral or dissatisfied +59046,54139,Male,Loyal Customer,22,Business travel,Business,1372,4,2,2,2,4,3,4,4,1,1,4,2,4,4,0,0.0,neutral or dissatisfied +59047,82464,Female,Loyal Customer,38,Personal Travel,Eco,502,2,5,4,1,1,4,2,1,3,2,4,4,5,1,28,19.0,neutral or dissatisfied +59048,106133,Female,Loyal Customer,55,Business travel,Business,3942,3,3,3,3,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +59049,111814,Male,Loyal Customer,20,Personal Travel,Eco,349,3,4,3,4,3,3,3,3,3,4,5,4,4,3,2,2.0,neutral or dissatisfied +59050,76857,Female,Loyal Customer,68,Personal Travel,Eco,989,1,4,1,1,5,4,4,5,5,1,5,5,5,4,0,0.0,neutral or dissatisfied +59051,45637,Female,Loyal Customer,42,Personal Travel,Eco,230,3,2,3,4,3,4,4,5,5,3,5,4,5,3,5,11.0,neutral or dissatisfied +59052,32553,Female,Loyal Customer,55,Business travel,Eco,216,3,3,3,3,5,3,4,2,2,3,2,3,2,1,0,4.0,neutral or dissatisfied +59053,40789,Female,disloyal Customer,22,Business travel,Business,588,4,4,4,5,5,4,5,5,4,1,3,5,5,5,0,2.0,satisfied +59054,50598,Male,Loyal Customer,67,Personal Travel,Eco,373,4,3,4,3,1,4,1,1,4,4,2,3,3,1,0,0.0,neutral or dissatisfied +59055,50759,Female,Loyal Customer,11,Personal Travel,Eco,209,3,5,3,1,5,3,5,5,3,1,5,1,1,5,42,56.0,neutral or dissatisfied +59056,80578,Male,Loyal Customer,42,Personal Travel,Eco,1747,1,2,1,4,3,1,3,3,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +59057,66908,Female,Loyal Customer,54,Personal Travel,Business,1119,3,5,3,4,2,5,4,1,1,3,1,4,1,4,12,4.0,neutral or dissatisfied +59058,102185,Female,Loyal Customer,30,Business travel,Business,2430,3,3,3,3,4,4,4,4,5,3,5,4,4,4,0,7.0,satisfied +59059,34947,Male,Loyal Customer,22,Personal Travel,Eco,187,2,5,2,4,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +59060,113215,Male,Loyal Customer,59,Business travel,Business,3091,1,1,1,1,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +59061,115341,Male,disloyal Customer,25,Business travel,Business,358,4,0,4,4,4,4,4,4,3,5,4,4,4,4,16,15.0,satisfied +59062,126042,Female,Loyal Customer,41,Business travel,Business,468,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,2.0,satisfied +59063,41527,Male,disloyal Customer,29,Business travel,Eco,1464,4,4,4,4,4,4,4,4,3,1,1,2,1,4,9,2.0,neutral or dissatisfied +59064,114270,Female,disloyal Customer,29,Business travel,Eco,846,2,2,2,4,1,2,1,1,3,1,3,2,3,1,0,6.0,neutral or dissatisfied +59065,111972,Male,Loyal Customer,38,Business travel,Business,370,2,2,2,2,4,4,4,3,3,4,3,3,3,1,7,10.0,satisfied +59066,79534,Male,Loyal Customer,20,Business travel,Business,3370,5,5,5,5,4,5,4,4,5,4,4,5,4,4,1,0.0,satisfied +59067,89935,Male,Loyal Customer,25,Personal Travel,Eco,1487,4,5,4,2,5,4,5,5,4,5,5,4,5,5,0,0.0,satisfied +59068,20270,Female,disloyal Customer,26,Business travel,Eco,137,1,1,1,3,1,1,1,1,2,4,3,3,3,1,57,55.0,neutral or dissatisfied +59069,52883,Female,Loyal Customer,56,Business travel,Eco,436,2,1,1,1,5,1,2,2,2,2,2,2,2,3,0,12.0,neutral or dissatisfied +59070,75356,Female,Loyal Customer,41,Business travel,Business,2556,5,5,5,5,5,5,5,5,2,4,5,5,3,5,14,38.0,satisfied +59071,71617,Female,Loyal Customer,29,Business travel,Business,1742,1,1,1,1,1,1,1,1,2,3,4,4,4,1,42,39.0,neutral or dissatisfied +59072,84736,Male,Loyal Customer,45,Business travel,Business,534,5,5,5,5,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +59073,62760,Male,disloyal Customer,19,Business travel,Eco,1353,4,5,5,5,3,4,3,3,4,3,3,4,5,3,3,5.0,neutral or dissatisfied +59074,40504,Male,Loyal Customer,16,Personal Travel,Eco,461,2,4,2,3,2,2,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +59075,82939,Female,Loyal Customer,44,Personal Travel,Eco Plus,594,3,1,3,2,5,1,1,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +59076,86454,Male,Loyal Customer,41,Business travel,Eco,712,2,4,4,4,2,2,2,2,3,3,4,1,4,2,0,18.0,neutral or dissatisfied +59077,80762,Female,disloyal Customer,19,Business travel,Eco,440,4,0,4,3,1,4,1,1,4,5,4,5,4,1,0,0.0,satisfied +59078,121125,Male,Loyal Customer,60,Business travel,Business,2521,1,1,1,1,5,4,4,5,2,5,4,4,3,4,0,9.0,satisfied +59079,124957,Male,Loyal Customer,33,Business travel,Business,184,1,1,1,1,5,5,4,5,3,2,5,4,5,5,0,0.0,satisfied +59080,78331,Female,Loyal Customer,48,Business travel,Business,1547,4,4,4,4,4,5,5,4,4,4,4,4,4,4,13,4.0,satisfied +59081,20481,Male,Loyal Customer,38,Business travel,Eco,139,5,4,4,4,5,5,5,5,2,1,4,3,4,5,0,0.0,satisfied +59082,12936,Female,Loyal Customer,66,Personal Travel,Eco,563,2,3,2,3,2,3,3,1,1,2,2,1,1,4,9,0.0,neutral or dissatisfied +59083,104855,Male,disloyal Customer,40,Business travel,Business,327,5,5,5,1,5,5,5,5,3,2,5,3,5,5,5,0.0,satisfied +59084,85476,Female,Loyal Customer,45,Business travel,Business,1933,2,2,2,2,3,2,4,3,3,4,3,4,3,5,0,0.0,satisfied +59085,47558,Female,Loyal Customer,51,Business travel,Eco Plus,599,3,2,5,2,2,3,4,2,2,3,2,1,2,3,1,0.0,neutral or dissatisfied +59086,75975,Male,Loyal Customer,46,Business travel,Business,297,3,3,3,3,5,4,4,3,3,3,3,4,3,4,20,32.0,neutral or dissatisfied +59087,45472,Female,Loyal Customer,72,Business travel,Business,3779,3,2,2,2,1,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +59088,105836,Male,Loyal Customer,68,Personal Travel,Eco,787,1,5,1,2,4,1,3,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +59089,96617,Male,Loyal Customer,57,Business travel,Business,3326,2,2,4,2,2,5,5,4,4,5,4,4,4,4,48,66.0,satisfied +59090,40134,Male,Loyal Customer,50,Business travel,Eco Plus,200,5,5,5,5,5,5,5,5,5,2,3,1,2,5,0,0.0,satisfied +59091,74455,Male,disloyal Customer,34,Business travel,Eco,1112,2,2,2,3,5,2,5,5,2,3,4,1,4,5,0,0.0,neutral or dissatisfied +59092,93420,Male,Loyal Customer,36,Business travel,Eco,697,3,4,4,4,3,3,3,3,4,3,4,3,3,3,18,4.0,neutral or dissatisfied +59093,129671,Male,Loyal Customer,38,Business travel,Eco,447,2,2,2,2,2,2,2,2,2,3,4,4,4,2,5,6.0,neutral or dissatisfied +59094,63374,Male,Loyal Customer,52,Personal Travel,Eco,337,1,2,5,3,5,5,5,5,2,2,3,2,3,5,0,0.0,neutral or dissatisfied +59095,38846,Female,Loyal Customer,45,Business travel,Eco Plus,354,4,4,4,4,1,4,2,4,4,4,4,2,4,5,0,5.0,satisfied +59096,73393,Female,Loyal Customer,40,Business travel,Business,1182,1,4,4,4,4,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +59097,82337,Female,Loyal Customer,43,Business travel,Business,3159,4,4,3,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +59098,12462,Male,Loyal Customer,21,Personal Travel,Eco,383,2,3,4,2,4,4,4,2,5,3,3,4,4,4,145,165.0,neutral or dissatisfied +59099,29873,Female,Loyal Customer,44,Business travel,Business,3728,4,4,4,4,1,4,2,3,3,4,3,4,3,5,0,0.0,satisfied +59100,106970,Female,Loyal Customer,25,Business travel,Business,1837,1,5,5,5,1,1,1,1,1,2,3,2,2,1,0,0.0,neutral or dissatisfied +59101,34146,Female,Loyal Customer,18,Business travel,Business,1971,1,1,1,1,4,4,4,4,1,5,2,3,4,4,0,2.0,satisfied +59102,104921,Female,Loyal Customer,46,Business travel,Business,3993,5,5,5,5,4,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +59103,99095,Male,disloyal Customer,16,Business travel,Eco,181,4,0,3,1,2,3,2,2,3,2,4,3,4,2,0,0.0,satisfied +59104,105941,Male,Loyal Customer,50,Personal Travel,Eco,1491,2,4,2,3,4,2,4,4,4,2,3,3,3,4,0,4.0,neutral or dissatisfied +59105,107515,Female,disloyal Customer,24,Business travel,Eco,838,3,3,3,3,2,3,5,2,3,2,4,3,4,2,18,0.0,neutral or dissatisfied +59106,127179,Male,Loyal Customer,33,Personal Travel,Eco,647,2,4,2,5,1,2,1,1,5,3,5,4,5,1,48,45.0,neutral or dissatisfied +59107,6790,Male,disloyal Customer,17,Business travel,Business,223,4,1,4,4,4,4,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +59108,125157,Female,Loyal Customer,44,Business travel,Business,2690,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +59109,7138,Male,Loyal Customer,33,Personal Travel,Business,130,2,2,0,2,1,0,1,1,4,5,3,4,2,1,0,0.0,neutral or dissatisfied +59110,55046,Male,disloyal Customer,34,Business travel,Business,1609,3,3,3,1,4,3,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +59111,24800,Female,Loyal Customer,16,Personal Travel,Eco Plus,432,2,4,5,1,5,5,5,5,4,2,4,3,4,5,1,62.0,neutral or dissatisfied +59112,35958,Female,disloyal Customer,25,Business travel,Eco,231,4,2,4,3,4,4,4,4,4,4,3,3,3,4,0,0.0,neutral or dissatisfied +59113,14913,Male,Loyal Customer,39,Personal Travel,Eco,240,2,5,2,2,1,2,1,1,1,4,1,2,4,1,0,34.0,neutral or dissatisfied +59114,98939,Female,Loyal Customer,37,Business travel,Business,543,2,2,3,2,4,5,5,5,5,5,5,3,5,3,2,3.0,satisfied +59115,74523,Male,Loyal Customer,52,Business travel,Business,1235,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +59116,105281,Female,Loyal Customer,44,Business travel,Business,738,1,1,1,1,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +59117,72177,Female,Loyal Customer,41,Business travel,Business,594,2,2,2,2,5,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +59118,10283,Male,disloyal Customer,32,Business travel,Business,301,1,1,1,4,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +59119,42562,Female,Loyal Customer,61,Business travel,Eco Plus,226,5,3,3,3,4,2,1,5,5,5,5,1,5,5,6,17.0,satisfied +59120,29984,Female,Loyal Customer,36,Business travel,Business,204,0,3,0,2,4,1,1,5,5,2,2,5,5,2,0,0.0,satisfied +59121,20715,Female,disloyal Customer,32,Business travel,Eco,707,1,1,1,2,3,1,3,3,4,3,2,3,3,3,0,0.0,neutral or dissatisfied +59122,12885,Male,disloyal Customer,22,Business travel,Eco,563,1,3,2,2,3,2,3,3,1,5,2,4,5,3,0,10.0,neutral or dissatisfied +59123,16975,Male,Loyal Customer,45,Business travel,Eco,209,2,5,5,5,3,2,3,3,1,5,3,4,4,3,67,53.0,neutral or dissatisfied +59124,107875,Male,Loyal Customer,42,Personal Travel,Eco,228,5,2,5,4,5,5,5,5,4,5,4,1,4,5,0,1.0,satisfied +59125,76246,Male,Loyal Customer,49,Personal Travel,Eco,1399,2,4,1,3,2,1,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +59126,76485,Male,Loyal Customer,31,Business travel,Business,547,3,3,3,3,5,5,5,5,4,3,4,3,4,5,3,8.0,satisfied +59127,122366,Female,Loyal Customer,52,Business travel,Eco,529,1,2,5,2,3,3,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +59128,112193,Male,Loyal Customer,56,Business travel,Eco Plus,895,1,0,0,4,1,1,1,1,1,5,3,3,4,1,5,0.0,neutral or dissatisfied +59129,59124,Female,Loyal Customer,28,Personal Travel,Eco,1744,1,2,1,3,1,4,4,4,5,3,3,4,3,4,138,106.0,neutral or dissatisfied +59130,112958,Male,Loyal Customer,24,Personal Travel,Eco,715,2,4,2,4,5,2,5,5,4,2,5,3,5,5,4,0.0,neutral or dissatisfied +59131,64123,Male,Loyal Customer,69,Personal Travel,Eco,2288,4,3,4,2,4,5,5,2,2,1,3,5,2,5,0,0.0,neutral or dissatisfied +59132,96495,Female,disloyal Customer,23,Business travel,Eco,436,1,0,1,3,2,1,2,2,3,2,5,3,4,2,17,0.0,neutral or dissatisfied +59133,52167,Female,Loyal Customer,36,Business travel,Business,509,3,3,3,3,2,5,4,5,5,5,5,4,5,1,0,0.0,satisfied +59134,49598,Male,Loyal Customer,54,Business travel,Business,3958,2,2,2,2,4,3,1,4,4,4,4,3,4,2,0,12.0,satisfied +59135,72235,Female,disloyal Customer,48,Business travel,Business,919,5,5,5,2,5,5,5,5,3,5,5,4,4,5,0,4.0,satisfied +59136,55732,Female,disloyal Customer,22,Business travel,Eco,946,4,4,4,3,4,4,4,4,5,2,3,5,4,4,8,0.0,neutral or dissatisfied +59137,44180,Female,Loyal Customer,31,Business travel,Eco,157,5,1,1,1,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +59138,54272,Female,Loyal Customer,16,Personal Travel,Eco,1222,1,0,2,4,4,2,4,4,5,3,5,5,5,4,1,0.0,neutral or dissatisfied +59139,108858,Female,Loyal Customer,23,Business travel,Business,447,3,3,3,3,5,5,5,5,5,1,1,2,3,5,27,1.0,satisfied +59140,3591,Male,Loyal Customer,58,Business travel,Business,1682,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +59141,35464,Female,Loyal Customer,32,Personal Travel,Eco,944,2,5,1,4,5,1,4,5,3,2,3,3,3,5,31,35.0,neutral or dissatisfied +59142,42498,Female,Loyal Customer,34,Business travel,Business,3362,1,1,1,1,3,3,5,5,5,5,5,1,5,2,0,17.0,satisfied +59143,77790,Male,Loyal Customer,15,Personal Travel,Eco,696,4,4,4,3,3,4,3,3,1,4,4,4,4,3,0,1.0,neutral or dissatisfied +59144,79260,Male,Loyal Customer,47,Personal Travel,Eco,1598,3,4,3,4,5,3,5,5,4,2,3,3,5,5,0,0.0,neutral or dissatisfied +59145,85673,Female,Loyal Customer,23,Personal Travel,Eco,903,3,2,3,3,3,3,1,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +59146,115999,Male,Loyal Customer,35,Personal Travel,Eco,337,1,4,1,1,1,1,1,1,4,4,5,5,5,1,0,1.0,neutral or dissatisfied +59147,126532,Male,disloyal Customer,22,Business travel,Eco,644,3,1,3,4,3,3,3,3,4,1,3,4,3,3,6,0.0,neutral or dissatisfied +59148,123333,Male,Loyal Customer,28,Personal Travel,Eco Plus,468,4,3,4,4,4,4,4,4,1,3,3,4,3,4,0,0.0,satisfied +59149,25172,Female,Loyal Customer,36,Personal Travel,Eco,369,2,5,2,1,2,2,1,2,1,1,3,3,2,2,0,0.0,neutral or dissatisfied +59150,98492,Male,Loyal Customer,37,Business travel,Business,668,5,5,5,5,5,5,5,5,5,5,5,4,5,4,14,28.0,satisfied +59151,115867,Female,disloyal Customer,20,Business travel,Eco,390,5,3,5,4,1,5,1,1,2,1,5,2,5,1,2,0.0,satisfied +59152,105811,Female,Loyal Customer,44,Personal Travel,Eco,842,4,4,4,4,1,4,4,5,5,4,5,3,5,3,4,0.0,neutral or dissatisfied +59153,118527,Female,Loyal Customer,48,Business travel,Business,369,5,5,5,5,4,5,5,4,4,4,4,3,4,3,7,0.0,satisfied +59154,67324,Male,Loyal Customer,24,Personal Travel,Eco Plus,985,2,5,2,3,4,2,4,4,4,3,4,3,5,4,6,0.0,neutral or dissatisfied +59155,82092,Female,Loyal Customer,49,Business travel,Eco,1276,2,4,4,4,2,2,2,3,2,3,3,2,1,2,133,157.0,neutral or dissatisfied +59156,39472,Female,Loyal Customer,38,Business travel,Business,867,2,2,2,2,1,1,3,4,4,4,4,1,4,1,3,0.0,satisfied +59157,1460,Female,Loyal Customer,59,Business travel,Business,695,2,5,4,4,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +59158,53003,Female,disloyal Customer,50,Business travel,Eco,1190,2,2,2,2,5,2,1,5,2,2,3,3,4,5,0,8.0,neutral or dissatisfied +59159,125548,Male,Loyal Customer,45,Business travel,Business,2266,2,4,4,4,5,3,4,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +59160,35011,Female,Loyal Customer,23,Business travel,Eco Plus,1182,3,5,5,5,3,3,2,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +59161,109617,Male,Loyal Customer,28,Business travel,Business,2382,2,2,2,2,2,2,2,2,4,2,5,3,4,2,38,41.0,satisfied +59162,87433,Male,Loyal Customer,55,Personal Travel,Eco Plus,425,2,3,2,4,5,2,5,5,1,2,2,2,3,5,11,0.0,neutral or dissatisfied +59163,50126,Female,Loyal Customer,51,Business travel,Business,250,1,5,5,5,5,1,2,1,1,2,1,3,1,1,42,64.0,neutral or dissatisfied +59164,46375,Male,Loyal Customer,45,Business travel,Eco,911,5,3,3,3,5,5,5,5,4,1,1,3,5,5,0,0.0,satisfied +59165,8201,Female,Loyal Customer,58,Business travel,Business,3004,1,5,5,5,1,4,3,3,3,3,1,4,3,4,6,9.0,neutral or dissatisfied +59166,88218,Female,disloyal Customer,37,Business travel,Business,404,2,2,2,4,1,2,4,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +59167,34386,Female,Loyal Customer,54,Business travel,Eco,612,4,4,4,4,4,3,4,4,4,4,4,4,4,4,8,6.0,neutral or dissatisfied +59168,29594,Female,Loyal Customer,8,Business travel,Business,3039,1,4,4,4,1,1,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +59169,37653,Male,Loyal Customer,37,Personal Travel,Eco,1074,4,1,4,3,3,4,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +59170,3686,Female,Loyal Customer,53,Business travel,Business,427,2,2,2,2,3,4,5,3,3,3,3,4,3,4,1,0.0,satisfied +59171,45769,Female,Loyal Customer,25,Business travel,Business,391,5,5,5,5,3,3,3,3,3,3,5,5,1,3,17,10.0,satisfied +59172,78063,Female,Loyal Customer,55,Personal Travel,Eco,332,1,2,1,3,4,4,4,2,2,1,3,2,2,1,0,0.0,neutral or dissatisfied +59173,42796,Male,Loyal Customer,44,Business travel,Business,677,1,1,1,1,3,4,4,5,5,5,5,5,5,5,5,6.0,satisfied +59174,52246,Male,Loyal Customer,39,Business travel,Business,2344,5,5,3,5,3,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +59175,82614,Male,Loyal Customer,45,Business travel,Business,3192,1,5,2,2,3,1,2,1,1,2,1,4,1,2,5,8.0,neutral or dissatisfied +59176,25117,Male,Loyal Customer,36,Personal Travel,Eco,946,3,4,3,2,5,3,5,5,3,5,4,2,1,5,23,59.0,neutral or dissatisfied +59177,106268,Male,disloyal Customer,30,Business travel,Eco Plus,1500,3,3,3,4,3,3,3,3,3,2,4,1,3,3,0,0.0,neutral or dissatisfied +59178,31777,Female,Loyal Customer,7,Personal Travel,Eco,602,2,5,2,4,3,2,3,3,1,1,3,4,5,3,9,1.0,neutral or dissatisfied +59179,106945,Female,disloyal Customer,36,Business travel,Business,937,3,3,3,2,1,3,2,1,3,3,5,3,5,1,69,47.0,neutral or dissatisfied +59180,86771,Female,Loyal Customer,49,Business travel,Business,484,2,2,5,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +59181,84780,Female,disloyal Customer,23,Business travel,Business,547,5,3,5,1,4,5,3,4,3,3,5,5,4,4,0,0.0,satisfied +59182,23647,Female,Loyal Customer,20,Business travel,Business,3471,4,1,4,4,5,5,4,5,3,4,5,4,5,5,0,0.0,satisfied +59183,90021,Female,disloyal Customer,48,Business travel,Business,983,1,1,1,5,2,1,2,2,5,4,4,5,4,2,14,0.0,neutral or dissatisfied +59184,92309,Male,Loyal Customer,42,Business travel,Business,2486,5,5,5,5,5,5,5,5,2,3,5,5,5,5,0,11.0,satisfied +59185,15293,Female,Loyal Customer,36,Business travel,Eco Plus,460,5,5,5,5,5,5,5,5,1,1,4,3,2,5,0,0.0,satisfied +59186,60017,Male,Loyal Customer,65,Personal Travel,Eco,1023,2,2,2,2,4,2,4,4,2,4,2,3,3,4,0,0.0,neutral or dissatisfied +59187,44394,Male,Loyal Customer,24,Business travel,Business,2348,3,4,4,4,3,3,3,3,1,3,1,3,2,3,8,17.0,neutral or dissatisfied +59188,45309,Female,Loyal Customer,54,Business travel,Business,3620,5,5,5,5,3,1,1,5,5,4,5,3,5,2,22,9.0,satisfied +59189,54867,Female,Loyal Customer,37,Business travel,Eco,862,1,5,2,2,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +59190,57867,Female,disloyal Customer,40,Business travel,Business,955,1,1,1,2,4,1,4,4,4,1,3,2,2,4,26,12.0,neutral or dissatisfied +59191,127999,Female,Loyal Customer,36,Business travel,Business,1088,5,5,5,5,2,2,4,5,5,5,5,3,5,2,0,0.0,satisfied +59192,24006,Female,Loyal Customer,42,Business travel,Eco,595,3,4,5,4,3,3,4,3,3,3,3,3,3,2,2,3.0,neutral or dissatisfied +59193,113512,Female,Loyal Customer,40,Business travel,Business,226,0,0,0,1,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +59194,86279,Male,Loyal Customer,39,Personal Travel,Eco,306,1,5,1,4,2,1,4,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +59195,5066,Male,Loyal Customer,54,Business travel,Business,137,4,4,4,4,4,4,4,4,4,4,4,5,4,3,23,14.0,satisfied +59196,87449,Female,Loyal Customer,33,Business travel,Business,3850,0,0,0,5,3,5,5,3,3,3,3,4,3,4,11,6.0,satisfied +59197,27129,Male,Loyal Customer,47,Business travel,Business,2701,1,1,1,1,4,4,4,5,1,4,3,4,5,4,0,0.0,satisfied +59198,46769,Female,Loyal Customer,35,Personal Travel,Eco Plus,125,1,4,1,4,3,1,3,3,1,4,3,4,2,3,7,9.0,neutral or dissatisfied +59199,50182,Male,Loyal Customer,60,Business travel,Eco,89,4,5,5,5,4,4,4,4,3,4,4,1,4,4,4,10.0,neutral or dissatisfied +59200,32598,Female,Loyal Customer,39,Business travel,Eco,102,1,1,1,1,1,2,1,1,4,2,3,2,4,1,14,19.0,neutral or dissatisfied +59201,46991,Male,Loyal Customer,42,Business travel,Eco Plus,819,4,1,1,1,4,4,4,4,1,3,2,5,5,4,2,107.0,satisfied +59202,98638,Male,Loyal Customer,55,Business travel,Business,3988,4,4,4,4,4,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +59203,125884,Female,Loyal Customer,14,Personal Travel,Eco,951,4,5,4,2,3,4,3,3,4,3,2,1,2,3,0,0.0,neutral or dissatisfied +59204,66400,Male,disloyal Customer,24,Business travel,Eco,1052,1,1,1,4,2,1,2,2,4,2,5,4,5,2,2,0.0,neutral or dissatisfied +59205,51156,Female,Loyal Customer,61,Personal Travel,Eco,109,4,3,4,3,4,3,3,2,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +59206,99890,Male,Loyal Customer,55,Business travel,Business,738,4,4,2,4,4,4,4,5,5,5,5,3,5,3,0,5.0,satisfied +59207,86424,Male,Loyal Customer,48,Business travel,Business,2834,2,2,5,2,4,5,4,4,4,4,4,4,4,5,17,24.0,satisfied +59208,28768,Male,Loyal Customer,52,Business travel,Eco Plus,1024,3,3,3,3,3,3,3,3,3,5,4,3,3,3,0,8.0,neutral or dissatisfied +59209,57607,Female,Loyal Customer,43,Business travel,Business,2312,3,3,3,3,4,4,4,4,4,4,5,4,4,5,1,0.0,satisfied +59210,83483,Male,disloyal Customer,26,Business travel,Eco,946,2,2,2,3,2,2,2,2,3,4,3,2,3,2,5,20.0,neutral or dissatisfied +59211,119111,Female,Loyal Customer,61,Personal Travel,Eco,1107,2,4,2,2,2,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +59212,8604,Male,Loyal Customer,48,Business travel,Eco Plus,109,4,2,4,2,4,4,4,4,1,3,5,2,4,4,4,13.0,satisfied +59213,70028,Male,Loyal Customer,56,Business travel,Business,3050,1,1,1,1,3,4,5,4,4,3,4,3,4,3,0,0.0,satisfied +59214,104304,Female,Loyal Customer,22,Personal Travel,Eco Plus,382,2,4,2,3,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +59215,65107,Male,Loyal Customer,69,Personal Travel,Eco,224,3,4,3,3,5,3,5,5,3,5,4,4,5,5,1,0.0,neutral or dissatisfied +59216,34249,Female,Loyal Customer,20,Business travel,Business,1666,5,5,5,5,4,4,4,4,4,4,3,2,2,4,19,15.0,satisfied +59217,125504,Female,Loyal Customer,35,Personal Travel,Eco,666,2,5,2,2,3,2,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +59218,104341,Female,Loyal Customer,18,Personal Travel,Eco,409,1,3,1,3,2,1,4,2,4,4,3,5,3,2,0,5.0,neutral or dissatisfied +59219,99511,Female,Loyal Customer,35,Personal Travel,Eco,307,2,3,2,1,3,2,3,3,4,5,3,4,5,3,4,0.0,neutral or dissatisfied +59220,113624,Female,Loyal Customer,15,Personal Travel,Eco,407,3,5,3,5,4,3,4,4,2,5,5,4,1,4,3,0.0,neutral or dissatisfied +59221,121079,Male,Loyal Customer,23,Personal Travel,Eco Plus,861,4,4,4,2,5,4,5,5,4,4,5,5,4,5,0,37.0,neutral or dissatisfied +59222,52195,Male,Loyal Customer,34,Business travel,Business,1856,5,5,5,5,3,4,3,4,4,5,4,5,4,3,27,16.0,satisfied +59223,53512,Female,Loyal Customer,63,Personal Travel,Eco,2288,3,5,3,2,5,3,3,1,1,3,1,3,1,2,3,5.0,neutral or dissatisfied +59224,63339,Male,disloyal Customer,36,Business travel,Eco,447,4,2,4,4,4,4,1,4,1,1,3,1,3,4,13,46.0,neutral or dissatisfied +59225,118255,Female,disloyal Customer,31,Business travel,Business,1849,2,2,2,2,3,2,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +59226,52886,Male,Loyal Customer,17,Business travel,Business,2248,1,5,5,5,1,1,1,1,4,3,3,4,3,1,0,9.0,neutral or dissatisfied +59227,114297,Female,Loyal Customer,43,Personal Travel,Eco,819,1,3,1,3,2,4,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +59228,28598,Male,Loyal Customer,52,Business travel,Business,2541,3,1,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +59229,123752,Male,Loyal Customer,32,Business travel,Business,546,4,4,4,4,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +59230,98351,Male,Loyal Customer,42,Business travel,Business,3488,2,2,4,2,1,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +59231,48896,Female,Loyal Customer,35,Business travel,Business,2102,0,0,0,3,1,4,4,5,5,5,5,3,5,2,0,33.0,satisfied +59232,106936,Female,Loyal Customer,41,Business travel,Business,2552,1,1,1,1,3,4,4,4,4,4,4,4,4,3,24,24.0,satisfied +59233,86471,Female,disloyal Customer,25,Business travel,Eco,762,1,1,1,5,1,1,1,1,1,4,1,1,5,1,0,0.0,neutral or dissatisfied +59234,22590,Male,disloyal Customer,37,Business travel,Business,223,3,3,3,3,5,3,5,5,1,2,4,4,4,5,0,0.0,neutral or dissatisfied +59235,96093,Male,Loyal Customer,20,Personal Travel,Eco,1069,2,2,2,4,4,2,4,4,4,1,4,4,4,4,21,7.0,neutral or dissatisfied +59236,64780,Male,disloyal Customer,21,Business travel,Eco,247,4,0,4,4,4,4,4,4,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +59237,24471,Female,disloyal Customer,14,Business travel,Eco,516,1,1,2,3,2,2,2,2,4,3,3,1,4,2,0,19.0,neutral or dissatisfied +59238,87102,Male,Loyal Customer,32,Personal Travel,Eco,640,2,4,2,5,1,2,1,1,3,2,5,5,4,1,1,0.0,neutral or dissatisfied +59239,126782,Male,Loyal Customer,33,Business travel,Business,2077,2,3,3,3,2,2,2,2,4,3,4,1,4,2,0,6.0,neutral or dissatisfied +59240,95064,Female,Loyal Customer,13,Personal Travel,Eco,293,3,4,4,3,3,4,3,3,5,2,5,3,5,3,76,72.0,neutral or dissatisfied +59241,36236,Male,Loyal Customer,37,Personal Travel,Eco,496,4,4,2,2,5,2,5,5,5,4,5,4,4,5,0,2.0,satisfied +59242,21399,Male,Loyal Customer,30,Business travel,Business,331,5,5,5,5,5,5,5,5,4,2,5,2,5,5,0,0.0,satisfied +59243,78973,Male,Loyal Customer,36,Business travel,Business,356,5,1,5,5,3,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +59244,22757,Male,Loyal Customer,50,Business travel,Business,134,4,4,4,4,2,1,4,4,4,4,5,3,4,3,15,28.0,satisfied +59245,129118,Male,disloyal Customer,24,Business travel,Eco,679,5,5,5,3,3,5,5,3,4,4,5,5,5,3,0,0.0,satisfied +59246,94527,Female,Loyal Customer,52,Business travel,Business,293,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +59247,49029,Female,disloyal Customer,25,Business travel,Eco,373,4,4,4,5,4,4,4,4,1,4,2,3,4,4,0,1.0,neutral or dissatisfied +59248,59249,Female,Loyal Customer,42,Business travel,Eco,3801,3,3,3,3,3,3,3,2,5,2,3,3,4,3,0,48.0,neutral or dissatisfied +59249,16229,Female,Loyal Customer,22,Business travel,Business,266,5,5,5,5,5,5,5,5,4,4,4,1,3,5,0,0.0,satisfied +59250,71607,Male,Loyal Customer,52,Business travel,Eco,1197,2,4,4,4,2,2,2,2,1,3,3,1,4,2,20,41.0,neutral or dissatisfied +59251,128203,Female,disloyal Customer,19,Business travel,Business,602,4,4,5,3,2,5,2,2,5,5,5,4,4,2,0,0.0,satisfied +59252,102188,Male,disloyal Customer,23,Business travel,Business,414,0,3,0,5,1,0,1,1,4,5,4,5,4,1,6,2.0,satisfied +59253,102547,Female,Loyal Customer,67,Personal Travel,Eco,386,1,1,1,2,5,2,2,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +59254,88638,Female,Loyal Customer,67,Personal Travel,Eco,404,2,4,2,3,4,4,5,1,1,2,1,5,1,5,3,0.0,neutral or dissatisfied +59255,106624,Female,disloyal Customer,40,Business travel,Business,306,3,3,3,3,3,3,3,5,4,5,5,3,3,3,187,188.0,neutral or dissatisfied +59256,98326,Female,Loyal Customer,16,Personal Travel,Business,1189,0,5,0,3,5,0,5,5,4,3,5,5,4,5,0,0.0,satisfied +59257,63199,Male,Loyal Customer,59,Business travel,Business,337,0,0,0,2,4,5,5,1,1,1,1,3,1,3,0,0.0,satisfied +59258,101280,Male,Loyal Customer,35,Business travel,Business,3514,2,2,2,2,5,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +59259,106312,Female,Loyal Customer,35,Personal Travel,Eco,998,3,2,3,4,2,3,2,2,1,1,3,2,3,2,11,0.0,neutral or dissatisfied +59260,63491,Male,Loyal Customer,53,Business travel,Business,651,2,2,2,2,2,5,5,4,4,4,4,5,4,5,7,0.0,satisfied +59261,38227,Male,Loyal Customer,38,Business travel,Eco Plus,849,4,3,3,3,4,4,4,4,3,2,5,4,2,4,0,0.0,satisfied +59262,78251,Male,Loyal Customer,50,Business travel,Business,3901,1,1,1,1,2,5,5,5,5,5,5,3,5,3,8,4.0,satisfied +59263,39397,Male,Loyal Customer,29,Business travel,Business,2042,1,1,1,1,5,5,5,5,4,3,3,4,1,5,0,0.0,satisfied +59264,106375,Female,disloyal Customer,25,Business travel,Eco,551,2,2,2,4,2,2,2,2,1,5,3,4,3,2,95,85.0,neutral or dissatisfied +59265,54238,Male,Loyal Customer,36,Business travel,Business,2568,3,1,1,1,2,3,3,3,3,3,3,1,3,3,49,39.0,neutral or dissatisfied +59266,118021,Male,Loyal Customer,59,Business travel,Business,3672,2,2,2,2,5,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +59267,67271,Female,Loyal Customer,53,Personal Travel,Eco,1121,2,4,2,3,3,5,4,5,5,2,5,3,5,4,1,0.0,neutral or dissatisfied +59268,34460,Female,Loyal Customer,29,Personal Travel,Eco,228,0,2,0,3,1,0,1,1,2,1,3,1,3,1,0,0.0,satisfied +59269,41181,Female,Loyal Customer,33,Business travel,Business,3177,4,4,4,4,4,3,5,3,3,3,3,5,3,4,21,16.0,satisfied +59270,117016,Male,Loyal Customer,36,Business travel,Business,2731,4,5,5,5,1,2,2,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +59271,54319,Male,Loyal Customer,45,Business travel,Business,1597,2,5,3,5,4,2,3,2,2,2,2,4,2,1,1,0.0,neutral or dissatisfied +59272,44412,Male,Loyal Customer,20,Personal Travel,Eco,323,2,5,2,3,2,2,2,2,3,4,4,3,3,2,0,13.0,neutral or dissatisfied +59273,36513,Male,Loyal Customer,29,Business travel,Business,1237,3,3,2,3,4,4,4,4,4,3,3,3,1,4,0,0.0,satisfied +59274,53158,Male,Loyal Customer,46,Business travel,Business,642,4,2,4,4,5,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +59275,16775,Male,Loyal Customer,61,Business travel,Business,242,3,5,5,5,4,4,3,3,3,3,3,2,3,1,0,12.0,neutral or dissatisfied +59276,53935,Female,Loyal Customer,48,Business travel,Business,2007,5,5,5,5,4,3,4,3,3,4,3,4,3,5,1,0.0,satisfied +59277,39882,Male,Loyal Customer,18,Personal Travel,Eco,272,1,0,1,5,2,1,4,2,5,4,5,3,5,2,0,1.0,neutral or dissatisfied +59278,963,Male,Loyal Customer,60,Business travel,Business,3358,0,4,0,2,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +59279,58331,Female,Loyal Customer,23,Personal Travel,Eco,1739,1,1,1,3,4,1,4,4,2,2,2,3,2,4,19,18.0,neutral or dissatisfied +59280,122991,Female,Loyal Customer,48,Business travel,Business,1778,3,3,2,3,4,4,4,4,4,4,4,4,4,3,12,12.0,satisfied +59281,115545,Male,Loyal Customer,40,Business travel,Business,480,2,2,2,2,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +59282,123225,Female,Loyal Customer,63,Personal Travel,Eco,328,2,5,2,1,5,4,3,2,2,2,5,3,2,5,2,0.0,neutral or dissatisfied +59283,103851,Female,Loyal Customer,22,Business travel,Business,3546,1,1,3,1,3,3,3,3,3,3,1,1,3,3,0,0.0,satisfied +59284,85431,Male,disloyal Customer,35,Business travel,Business,332,4,4,4,1,2,4,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +59285,56752,Male,Loyal Customer,59,Business travel,Business,997,4,4,4,4,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +59286,46300,Male,Loyal Customer,61,Personal Travel,Eco,637,4,4,4,3,1,4,1,1,3,2,5,5,4,1,1,16.0,neutral or dissatisfied +59287,50719,Female,Loyal Customer,57,Personal Travel,Eco,109,3,0,3,1,4,4,5,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +59288,123650,Male,Loyal Customer,51,Business travel,Business,3985,0,4,0,3,4,5,4,5,5,5,5,4,5,3,14,2.0,satisfied +59289,58745,Male,disloyal Customer,25,Business travel,Eco,1012,3,3,3,2,2,3,2,2,5,5,5,3,4,2,12,0.0,neutral or dissatisfied +59290,124612,Female,Loyal Customer,46,Business travel,Business,1671,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +59291,122249,Male,disloyal Customer,40,Business travel,Eco,141,1,0,1,3,2,1,2,2,3,5,3,2,2,2,0,0.0,neutral or dissatisfied +59292,63802,Male,disloyal Customer,21,Business travel,Eco,221,5,0,5,1,5,5,5,5,4,5,2,5,5,5,9,0.0,satisfied +59293,79365,Female,Loyal Customer,23,Business travel,Business,502,2,5,2,2,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +59294,112481,Male,Loyal Customer,33,Personal Travel,Eco,819,1,1,1,3,1,1,1,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +59295,13693,Male,Loyal Customer,59,Business travel,Eco,483,3,2,2,2,3,3,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +59296,55993,Female,Loyal Customer,50,Business travel,Business,2475,4,5,5,5,4,4,4,2,4,4,3,4,2,4,6,26.0,neutral or dissatisfied +59297,119931,Female,disloyal Customer,22,Business travel,Eco,1009,4,4,4,3,1,4,1,1,3,4,5,3,5,1,0,0.0,satisfied +59298,105003,Male,Loyal Customer,40,Business travel,Business,3099,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +59299,38307,Female,Loyal Customer,28,Personal Travel,Eco,2583,2,3,3,3,3,5,5,2,1,4,3,5,2,5,31,68.0,neutral or dissatisfied +59300,93515,Female,Loyal Customer,22,Business travel,Eco Plus,1107,3,3,3,3,3,3,3,3,1,3,4,1,4,3,11,3.0,neutral or dissatisfied +59301,3151,Male,Loyal Customer,59,Personal Travel,Eco,140,4,4,4,4,2,4,2,2,3,4,2,4,3,2,0,0.0,neutral or dissatisfied +59302,28125,Female,disloyal Customer,28,Business travel,Eco,550,4,4,4,1,2,4,2,2,2,4,5,2,3,2,43,30.0,neutral or dissatisfied +59303,61649,Female,Loyal Customer,40,Business travel,Business,1379,3,2,2,2,2,4,4,3,3,4,3,3,3,3,85,64.0,neutral or dissatisfied +59304,56120,Female,Loyal Customer,43,Personal Travel,Business,1372,3,4,3,3,2,3,3,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +59305,98623,Female,Loyal Customer,36,Business travel,Eco,966,1,2,2,2,1,1,1,1,3,4,4,3,3,1,0,0.0,neutral or dissatisfied +59306,64699,Female,Loyal Customer,48,Business travel,Business,3469,0,0,0,2,4,5,5,1,1,1,1,3,1,5,0,0.0,satisfied +59307,111505,Female,Loyal Customer,45,Business travel,Eco,391,3,3,3,3,1,3,3,3,3,3,3,2,3,1,15,37.0,neutral or dissatisfied +59308,33970,Male,disloyal Customer,21,Business travel,Eco,1598,4,4,4,3,4,4,4,4,3,2,3,5,2,4,0,0.0,neutral or dissatisfied +59309,31954,Male,Loyal Customer,42,Business travel,Business,3335,2,2,2,2,5,4,4,1,1,1,2,3,1,4,0,0.0,neutral or dissatisfied +59310,92254,Female,Loyal Customer,19,Personal Travel,Eco,1670,3,3,4,2,2,4,2,2,1,3,2,2,4,2,17,8.0,neutral or dissatisfied +59311,40336,Female,Loyal Customer,44,Personal Travel,Eco Plus,463,3,5,3,3,2,2,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +59312,31429,Male,Loyal Customer,35,Personal Travel,Eco,1506,4,5,4,2,4,4,5,4,4,5,4,3,5,4,2,0.0,neutral or dissatisfied +59313,94785,Male,Loyal Customer,59,Business travel,Business,3051,0,4,0,3,4,4,5,4,4,3,3,4,4,3,7,0.0,satisfied +59314,24330,Female,Loyal Customer,49,Personal Travel,Eco,1048,4,4,4,3,5,4,5,1,1,4,1,5,1,3,0,0.0,satisfied +59315,34341,Male,Loyal Customer,17,Business travel,Eco,846,4,2,2,2,4,4,5,4,1,1,5,5,4,4,0,0.0,satisfied +59316,86761,Female,Loyal Customer,68,Personal Travel,Eco,821,4,5,4,3,1,5,4,3,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +59317,70178,Female,Loyal Customer,61,Business travel,Business,258,2,5,5,5,3,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +59318,13124,Male,disloyal Customer,21,Business travel,Eco,427,3,2,2,3,2,2,5,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +59319,4668,Female,disloyal Customer,26,Business travel,Eco,489,2,3,2,3,2,2,1,2,1,5,4,3,4,2,0,6.0,neutral or dissatisfied +59320,114371,Female,Loyal Customer,56,Business travel,Eco Plus,846,4,4,4,4,4,3,3,3,3,3,3,3,4,3,161,147.0,neutral or dissatisfied +59321,60642,Female,Loyal Customer,47,Business travel,Business,1620,5,5,5,5,2,4,5,4,4,4,4,5,4,3,67,58.0,satisfied +59322,54843,Male,Loyal Customer,23,Business travel,Business,3390,4,4,3,4,4,4,4,4,5,5,5,5,5,4,0,19.0,satisfied +59323,67622,Female,disloyal Customer,22,Business travel,Business,1171,4,0,4,3,2,4,2,2,4,4,5,5,5,2,0,0.0,satisfied +59324,121114,Male,Loyal Customer,20,Business travel,Business,2370,3,3,3,3,4,4,4,3,3,3,5,4,4,4,0,0.0,satisfied +59325,79884,Female,Loyal Customer,24,Business travel,Eco,1096,2,4,4,4,2,2,1,2,2,3,3,4,4,2,30,36.0,neutral or dissatisfied +59326,108390,Male,Loyal Customer,21,Personal Travel,Eco,1844,3,4,3,1,1,3,1,1,5,2,3,5,4,1,52,49.0,neutral or dissatisfied +59327,126941,Female,Loyal Customer,51,Business travel,Business,2198,4,4,4,4,4,4,5,5,5,4,5,5,5,3,3,10.0,satisfied +59328,52275,Female,Loyal Customer,40,Business travel,Eco,455,1,1,1,1,1,1,1,1,1,3,3,1,2,1,0,0.0,neutral or dissatisfied +59329,20326,Male,Loyal Customer,42,Business travel,Business,287,0,0,0,4,4,4,4,2,2,2,2,5,2,4,72,64.0,satisfied +59330,3856,Female,Loyal Customer,48,Business travel,Eco Plus,710,3,3,3,3,4,4,4,3,3,3,3,4,3,1,7,19.0,neutral or dissatisfied +59331,97637,Female,disloyal Customer,42,Business travel,Business,1587,4,4,4,4,4,4,4,4,4,3,5,5,5,4,2,13.0,neutral or dissatisfied +59332,93890,Male,Loyal Customer,51,Business travel,Business,588,4,1,4,4,5,4,4,4,4,4,4,3,4,5,3,0.0,satisfied +59333,49589,Male,Loyal Customer,58,Business travel,Business,110,5,5,4,5,4,1,4,4,4,4,5,4,4,2,39,42.0,satisfied +59334,98845,Male,Loyal Customer,64,Personal Travel,Business,1482,3,1,3,3,2,3,2,5,5,3,2,2,5,1,14,0.0,neutral or dissatisfied +59335,32776,Female,Loyal Customer,54,Business travel,Business,3148,5,5,3,5,4,2,3,5,5,5,3,2,5,2,1,0.0,satisfied +59336,46609,Male,disloyal Customer,26,Business travel,Eco,125,3,1,2,2,5,2,5,5,3,4,3,2,2,5,35,28.0,neutral or dissatisfied +59337,48373,Female,Loyal Customer,70,Personal Travel,Eco,522,2,5,2,2,5,4,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +59338,76657,Female,Loyal Customer,26,Personal Travel,Eco,481,3,4,3,1,5,3,5,5,2,4,5,1,3,5,0,0.0,neutral or dissatisfied +59339,123118,Male,Loyal Customer,31,Business travel,Business,2473,2,2,2,2,2,3,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +59340,123499,Male,Loyal Customer,41,Business travel,Business,796,4,4,4,4,2,5,2,5,5,4,5,4,5,3,0,0.0,satisfied +59341,31373,Female,disloyal Customer,74,Business travel,Eco,577,2,1,3,4,5,3,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +59342,15448,Male,Loyal Customer,48,Business travel,Business,164,4,1,1,1,2,3,4,4,4,4,4,4,4,2,10,13.0,neutral or dissatisfied +59343,100382,Female,Loyal Customer,24,Personal Travel,Eco,1011,3,1,3,3,5,3,3,5,2,5,4,3,3,5,9,13.0,neutral or dissatisfied +59344,11917,Female,Loyal Customer,57,Personal Travel,Eco,744,4,5,5,2,2,4,5,1,1,5,1,4,1,4,0,4.0,neutral or dissatisfied +59345,11556,Male,Loyal Customer,47,Business travel,Business,1847,5,5,5,5,3,4,4,4,4,4,4,3,4,5,0,1.0,satisfied +59346,41282,Male,Loyal Customer,56,Business travel,Business,788,2,2,4,2,1,4,3,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +59347,72144,Male,Loyal Customer,12,Personal Travel,Eco,731,1,4,1,5,1,1,1,1,1,3,3,4,3,1,31,10.0,neutral or dissatisfied +59348,83562,Female,disloyal Customer,37,Business travel,Business,936,3,3,3,3,3,3,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +59349,10356,Male,Loyal Customer,52,Business travel,Business,3326,4,4,4,4,5,5,5,5,5,5,5,4,5,5,16,24.0,satisfied +59350,49530,Male,Loyal Customer,35,Business travel,Business,421,2,2,4,2,4,4,5,4,4,4,4,2,4,1,0,0.0,satisfied +59351,62613,Female,Loyal Customer,21,Personal Travel,Eco,1744,2,1,2,3,1,2,1,1,4,3,2,4,3,1,0,0.0,neutral or dissatisfied +59352,69416,Male,Loyal Customer,46,Business travel,Business,3815,1,1,5,1,3,3,4,5,5,5,5,3,5,5,8,0.0,satisfied +59353,85114,Male,Loyal Customer,56,Business travel,Business,2746,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +59354,5364,Male,disloyal Customer,24,Business travel,Business,785,0,0,0,4,4,0,4,4,3,5,4,3,4,4,0,1.0,satisfied +59355,24263,Male,Loyal Customer,66,Personal Travel,Eco,170,2,5,2,4,3,2,4,3,5,2,3,1,4,3,34,26.0,neutral or dissatisfied +59356,65069,Male,Loyal Customer,40,Personal Travel,Eco,190,4,5,4,1,5,4,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +59357,119349,Male,Loyal Customer,47,Business travel,Business,2288,4,4,4,4,3,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +59358,37061,Female,Loyal Customer,52,Business travel,Business,2831,3,3,3,3,4,4,5,4,4,4,4,3,4,2,0,0.0,satisfied +59359,101579,Male,Loyal Customer,44,Business travel,Business,3754,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,8.0,satisfied +59360,102716,Female,Loyal Customer,31,Personal Travel,Eco,601,1,4,1,4,1,1,1,1,3,2,4,3,1,1,0,0.0,neutral or dissatisfied +59361,95549,Male,Loyal Customer,50,Personal Travel,Eco Plus,189,2,3,0,5,5,0,5,5,1,5,2,4,3,5,19,0.0,neutral or dissatisfied +59362,86404,Male,Loyal Customer,45,Business travel,Business,3154,4,4,4,4,4,5,5,5,5,5,5,4,5,4,0,20.0,satisfied +59363,127492,Male,Loyal Customer,30,Personal Travel,Eco,2075,3,4,3,1,1,3,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +59364,53739,Male,Loyal Customer,44,Personal Travel,Eco,1190,3,5,2,1,4,2,1,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +59365,57643,Male,Loyal Customer,77,Business travel,Eco,200,3,2,4,2,4,3,4,4,3,3,2,4,2,4,0,0.0,neutral or dissatisfied +59366,19357,Male,disloyal Customer,40,Business travel,Eco,692,1,1,1,4,4,1,4,4,2,2,3,2,3,4,5,0.0,neutral or dissatisfied +59367,76478,Female,Loyal Customer,43,Business travel,Business,2887,1,1,1,1,4,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +59368,116624,Female,Loyal Customer,55,Business travel,Business,404,1,1,1,1,4,4,4,4,4,4,4,5,4,5,5,4.0,satisfied +59369,35917,Male,Loyal Customer,9,Personal Travel,Eco,2248,2,4,2,3,2,2,2,2,4,3,5,5,5,2,46,37.0,neutral or dissatisfied +59370,57152,Male,Loyal Customer,40,Business travel,Eco,1824,5,3,3,3,5,4,5,5,1,4,3,4,3,5,4,13.0,neutral or dissatisfied +59371,110432,Female,disloyal Customer,36,Business travel,Eco,398,3,4,3,3,1,3,1,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +59372,117437,Female,disloyal Customer,44,Business travel,Business,1107,1,0,0,1,3,1,3,3,3,4,5,4,5,3,13,14.0,neutral or dissatisfied +59373,72763,Female,Loyal Customer,55,Business travel,Business,1045,1,1,1,1,3,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +59374,17011,Female,Loyal Customer,19,Personal Travel,Business,781,3,2,3,4,4,3,5,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +59375,29597,Male,Loyal Customer,25,Business travel,Business,1448,4,4,4,4,4,4,4,4,3,3,5,1,4,4,0,0.0,satisfied +59376,83120,Female,Loyal Customer,51,Personal Travel,Eco,957,1,4,1,2,2,4,4,2,2,1,3,3,2,3,0,1.0,neutral or dissatisfied +59377,86986,Male,Loyal Customer,59,Personal Travel,Eco,907,5,4,5,4,4,5,4,4,3,5,5,5,5,4,0,6.0,satisfied +59378,103705,Female,Loyal Customer,7,Personal Travel,Eco,405,0,3,0,2,1,0,1,1,2,2,5,1,2,1,0,0.0,satisfied +59379,126375,Male,Loyal Customer,39,Personal Travel,Eco,507,3,5,3,3,4,3,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +59380,102454,Female,Loyal Customer,25,Personal Travel,Eco,414,2,3,2,4,4,2,1,4,5,4,5,5,3,4,8,18.0,neutral or dissatisfied +59381,122113,Male,Loyal Customer,47,Business travel,Business,130,4,4,4,4,3,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +59382,128661,Male,disloyal Customer,37,Business travel,Business,2288,1,1,1,4,5,1,5,5,4,4,4,3,5,5,3,5.0,neutral or dissatisfied +59383,44932,Female,Loyal Customer,25,Personal Travel,Business,334,4,2,4,3,3,4,3,3,2,5,4,1,4,3,8,0.0,neutral or dissatisfied +59384,2508,Female,disloyal Customer,42,Business travel,Business,280,4,4,4,3,2,4,2,2,2,1,3,3,3,2,85,85.0,neutral or dissatisfied +59385,30067,Female,Loyal Customer,39,Business travel,Business,399,5,5,5,5,3,4,5,4,4,4,4,2,4,1,0,0.0,satisfied +59386,41840,Male,Loyal Customer,7,Personal Travel,Eco,462,3,4,1,3,4,1,4,4,4,2,2,4,4,4,0,16.0,neutral or dissatisfied +59387,43134,Male,Loyal Customer,39,Business travel,Eco Plus,192,4,5,5,5,4,4,4,4,2,3,2,4,4,4,0,0.0,satisfied +59388,119104,Female,Loyal Customer,55,Business travel,Eco,707,1,0,0,1,4,1,2,3,3,1,5,1,3,2,6,0.0,neutral or dissatisfied +59389,9125,Female,Loyal Customer,32,Personal Travel,Eco,765,1,4,1,1,1,1,1,1,4,4,4,5,5,1,0,1.0,neutral or dissatisfied +59390,69439,Male,Loyal Customer,67,Personal Travel,Eco,1096,1,2,0,4,2,0,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +59391,76527,Male,Loyal Customer,68,Business travel,Business,1891,3,3,3,3,2,4,4,3,3,3,3,3,3,4,0,4.0,neutral or dissatisfied +59392,116889,Male,disloyal Customer,26,Business travel,Business,338,4,4,3,1,3,3,3,3,4,4,5,5,5,3,4,0.0,satisfied +59393,83431,Female,Loyal Customer,20,Personal Travel,Eco,632,1,3,2,1,3,2,3,3,5,2,5,4,4,3,1,0.0,neutral or dissatisfied +59394,112650,Female,Loyal Customer,25,Personal Travel,Eco,1756,3,5,3,5,5,3,5,5,2,1,4,4,4,5,0,12.0,neutral or dissatisfied +59395,3703,Male,Loyal Customer,50,Personal Travel,Eco,431,2,5,4,2,2,4,2,2,3,5,4,4,5,2,6,9.0,neutral or dissatisfied +59396,82244,Female,Loyal Customer,34,Business travel,Business,3342,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +59397,103489,Male,Loyal Customer,38,Personal Travel,Eco,440,3,4,3,2,3,3,4,3,3,3,4,5,4,3,7,0.0,neutral or dissatisfied +59398,33648,Male,Loyal Customer,49,Personal Travel,Eco,399,2,5,2,5,5,2,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +59399,9624,Female,Loyal Customer,39,Business travel,Eco Plus,292,1,3,3,3,1,2,1,1,2,4,3,3,4,1,4,0.0,neutral or dissatisfied +59400,19414,Male,disloyal Customer,43,Business travel,Eco,645,2,0,2,4,4,2,1,4,4,4,4,4,4,4,21,13.0,neutral or dissatisfied +59401,88782,Male,Loyal Customer,57,Business travel,Business,3428,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +59402,33673,Male,Loyal Customer,45,Business travel,Business,899,4,4,4,4,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +59403,83190,Male,Loyal Customer,47,Business travel,Business,1823,1,1,1,1,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +59404,49866,Male,disloyal Customer,30,Business travel,Eco,86,2,2,2,4,5,2,5,5,2,1,3,2,4,5,0,0.0,neutral or dissatisfied +59405,79677,Male,Loyal Customer,40,Personal Travel,Eco,760,1,4,1,4,2,1,2,2,5,4,5,4,4,2,7,0.0,neutral or dissatisfied +59406,59243,Female,disloyal Customer,33,Business travel,Eco,4817,3,2,2,1,3,1,1,2,5,5,3,1,5,1,9,0.0,neutral or dissatisfied +59407,83628,Female,Loyal Customer,53,Personal Travel,Eco,409,3,4,3,2,4,5,5,4,4,3,4,2,4,3,8,0.0,neutral or dissatisfied +59408,126082,Male,Loyal Customer,43,Business travel,Business,600,1,1,5,1,3,5,5,2,2,2,2,5,2,4,1,0.0,satisfied +59409,96125,Male,Loyal Customer,14,Personal Travel,Eco Plus,758,2,5,2,4,2,2,3,2,3,3,5,4,5,2,8,0.0,neutral or dissatisfied +59410,77384,Female,disloyal Customer,23,Business travel,Eco,190,4,5,4,2,4,4,4,4,2,3,4,3,2,4,0,0.0,satisfied +59411,99774,Male,Loyal Customer,57,Business travel,Business,1524,3,3,3,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +59412,25811,Male,Loyal Customer,40,Business travel,Business,1747,5,5,5,5,2,4,3,5,5,5,5,5,5,3,0,5.0,satisfied +59413,126921,Male,Loyal Customer,42,Personal Travel,Business,338,2,4,2,2,2,3,2,2,2,2,2,5,2,2,0,0.0,neutral or dissatisfied +59414,119192,Female,Loyal Customer,47,Business travel,Business,2254,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +59415,35567,Female,Loyal Customer,31,Business travel,Eco Plus,1028,0,0,0,1,2,0,2,2,5,1,1,2,2,2,0,0.0,satisfied +59416,99902,Female,Loyal Customer,18,Personal Travel,Eco,738,1,5,1,3,2,1,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +59417,15821,Female,Loyal Customer,54,Business travel,Eco Plus,143,3,3,3,3,5,3,5,2,2,3,2,1,2,1,0,0.0,satisfied +59418,69886,Male,Loyal Customer,36,Business travel,Business,2284,4,3,3,3,2,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +59419,77729,Male,disloyal Customer,35,Business travel,Business,874,2,2,2,3,1,2,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +59420,121036,Female,Loyal Customer,37,Personal Travel,Eco,920,3,4,2,3,3,2,3,3,4,3,5,5,5,3,1,0.0,neutral or dissatisfied +59421,27059,Female,Loyal Customer,52,Business travel,Business,1399,3,4,4,4,1,3,4,3,3,3,3,4,3,4,0,8.0,neutral or dissatisfied +59422,97596,Female,Loyal Customer,63,Business travel,Business,2771,2,2,2,2,3,5,5,5,5,5,5,4,5,5,2,0.0,satisfied +59423,25151,Male,Loyal Customer,38,Business travel,Eco Plus,406,2,3,3,3,2,2,2,2,4,1,3,2,3,2,12,34.0,neutral or dissatisfied +59424,100940,Male,disloyal Customer,25,Business travel,Business,1142,5,0,5,5,1,0,1,1,4,3,4,5,5,1,4,8.0,satisfied +59425,53143,Male,Loyal Customer,12,Personal Travel,Eco,413,5,5,5,1,5,5,3,5,3,2,4,4,5,5,0,7.0,satisfied +59426,99675,Male,Loyal Customer,42,Business travel,Business,442,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +59427,122224,Male,disloyal Customer,22,Business travel,Eco,544,2,2,2,3,4,2,3,4,1,1,2,3,3,4,0,0.0,neutral or dissatisfied +59428,73566,Female,Loyal Customer,40,Business travel,Business,1912,2,1,1,1,2,4,4,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +59429,95346,Male,Loyal Customer,56,Personal Travel,Eco,148,4,1,4,3,4,4,4,4,1,4,3,3,3,4,0,0.0,satisfied +59430,121010,Female,Loyal Customer,34,Personal Travel,Eco,920,4,4,4,5,4,4,5,4,3,5,5,5,4,4,9,0.0,satisfied +59431,5661,Male,Loyal Customer,55,Business travel,Business,1802,1,1,5,1,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +59432,84747,Female,disloyal Customer,26,Business travel,Business,547,2,0,1,1,3,1,2,3,3,3,4,4,4,3,38,29.0,neutral or dissatisfied +59433,71323,Female,Loyal Customer,50,Business travel,Business,1514,5,5,5,5,3,5,4,4,4,5,4,4,4,3,1,0.0,satisfied +59434,23167,Male,Loyal Customer,17,Personal Travel,Eco,250,2,5,0,3,4,0,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +59435,49551,Male,Loyal Customer,42,Business travel,Business,3418,0,3,0,1,5,5,5,5,5,5,5,1,5,3,10,3.0,satisfied +59436,7164,Female,Loyal Customer,36,Business travel,Business,2988,2,2,2,2,2,4,4,3,3,3,2,2,3,2,0,16.0,neutral or dissatisfied +59437,38552,Female,Loyal Customer,36,Business travel,Business,975,2,4,4,4,3,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +59438,22619,Female,Loyal Customer,47,Personal Travel,Eco,300,2,4,2,3,2,4,4,2,2,2,2,5,2,5,29,24.0,neutral or dissatisfied +59439,18132,Male,Loyal Customer,65,Personal Travel,Eco,120,4,3,4,2,3,4,1,3,4,3,1,5,2,3,47,42.0,satisfied +59440,75247,Female,Loyal Customer,20,Personal Travel,Eco,1744,3,4,3,4,5,3,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +59441,45114,Female,Loyal Customer,55,Business travel,Eco,177,2,1,1,1,1,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +59442,63269,Male,Loyal Customer,35,Business travel,Eco,447,4,3,3,3,4,4,4,4,3,3,4,1,4,4,98,114.0,neutral or dissatisfied +59443,112091,Male,disloyal Customer,22,Business travel,Eco,1062,2,2,2,4,3,2,3,3,4,4,4,3,4,3,66,39.0,neutral or dissatisfied +59444,83323,Male,Loyal Customer,22,Personal Travel,Eco,1671,1,1,1,3,1,1,1,1,2,5,4,1,3,1,0,9.0,neutral or dissatisfied +59445,116691,Male,disloyal Customer,24,Business travel,Business,333,5,0,5,5,5,5,5,5,5,5,5,4,4,5,3,0.0,satisfied +59446,117921,Female,Loyal Customer,37,Business travel,Business,601,5,5,5,5,4,5,5,5,5,4,5,5,5,5,10,3.0,satisfied +59447,113357,Female,disloyal Customer,59,Business travel,Business,236,4,4,4,3,4,4,4,4,5,2,4,4,4,4,14,24.0,satisfied +59448,65834,Male,Loyal Customer,30,Business travel,Business,1389,2,2,2,2,4,4,4,4,4,4,5,5,4,4,0,3.0,satisfied +59449,38222,Male,Loyal Customer,63,Personal Travel,Eco Plus,1121,4,4,4,4,3,4,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +59450,47882,Male,Loyal Customer,53,Business travel,Business,329,1,1,1,1,2,3,5,5,5,4,5,3,5,4,0,0.0,satisfied +59451,100615,Male,disloyal Customer,23,Business travel,Business,1121,4,0,4,1,1,4,3,1,4,3,4,3,5,1,0,0.0,satisfied +59452,62245,Female,Loyal Customer,58,Personal Travel,Eco,2454,5,1,5,3,4,3,3,3,3,5,3,1,3,1,0,0.0,satisfied +59453,34651,Male,Loyal Customer,42,Personal Travel,Eco,427,2,0,2,2,3,2,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +59454,26995,Male,Loyal Customer,23,Business travel,Business,1710,4,4,4,4,4,4,4,4,4,3,2,2,5,4,0,5.0,satisfied +59455,97368,Male,Loyal Customer,39,Personal Travel,Eco,1020,2,3,2,3,5,2,5,5,5,2,4,1,3,5,44,37.0,neutral or dissatisfied +59456,112567,Male,disloyal Customer,25,Business travel,Business,602,1,0,1,4,5,1,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +59457,17279,Female,Loyal Customer,34,Personal Travel,Eco Plus,872,2,1,2,3,5,2,5,5,2,4,2,4,3,5,94,67.0,neutral or dissatisfied +59458,73994,Female,Loyal Customer,48,Business travel,Business,1972,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,8.0,satisfied +59459,41295,Male,Loyal Customer,21,Business travel,Business,3470,2,2,2,2,5,5,5,5,2,4,2,3,4,5,18,10.0,satisfied +59460,126386,Male,Loyal Customer,68,Personal Travel,Eco,631,2,1,2,2,4,2,3,4,4,3,3,3,3,4,0,0.0,neutral or dissatisfied +59461,40720,Female,Loyal Customer,44,Business travel,Business,3259,1,1,1,1,1,4,2,5,5,5,5,4,5,3,0,0.0,satisfied +59462,23778,Female,Loyal Customer,47,Business travel,Eco,374,5,5,5,5,2,4,1,5,5,5,5,2,5,1,55,44.0,satisfied +59463,89893,Female,Loyal Customer,51,Business travel,Business,1416,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +59464,89964,Female,Loyal Customer,7,Personal Travel,Eco,1306,4,5,4,3,1,4,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +59465,24791,Female,Loyal Customer,33,Personal Travel,Eco,528,4,2,1,3,5,1,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +59466,43054,Female,disloyal Customer,38,Business travel,Eco,391,2,4,1,3,3,1,3,3,1,5,3,1,4,3,10,0.0,neutral or dissatisfied +59467,38951,Male,Loyal Customer,24,Personal Travel,Eco Plus,162,3,5,3,4,3,3,5,3,3,3,4,3,5,3,0,6.0,neutral or dissatisfied +59468,38928,Female,disloyal Customer,22,Business travel,Eco,298,4,3,4,3,5,4,5,5,4,5,4,4,3,5,4,5.0,neutral or dissatisfied +59469,108914,Male,Loyal Customer,17,Business travel,Eco,1183,2,4,4,4,2,1,3,2,4,5,4,2,3,2,19,25.0,neutral or dissatisfied +59470,62709,Male,Loyal Customer,28,Business travel,Business,2399,4,2,4,4,5,5,5,5,3,4,3,4,4,5,21,23.0,satisfied +59471,39998,Male,Loyal Customer,41,Business travel,Business,618,5,5,5,5,4,4,4,3,3,3,3,5,3,5,0,,satisfied +59472,30465,Male,Loyal Customer,53,Business travel,Business,495,5,5,2,5,5,3,4,4,4,4,4,5,4,1,0,0.0,satisfied +59473,1818,Female,Loyal Customer,30,Business travel,Eco,408,3,1,1,1,3,3,3,3,2,2,4,1,3,3,8,6.0,neutral or dissatisfied +59474,28407,Female,Loyal Customer,22,Personal Travel,Eco,1709,3,5,3,4,5,3,5,5,4,3,2,5,4,5,3,0.0,neutral or dissatisfied +59475,43363,Male,Loyal Customer,70,Personal Travel,Eco,436,4,5,4,2,4,4,5,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +59476,123876,Male,Loyal Customer,43,Business travel,Eco,141,5,4,4,4,5,5,5,5,1,2,5,1,5,5,6,0.0,satisfied +59477,72174,Female,Loyal Customer,36,Business travel,Business,594,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +59478,33221,Male,Loyal Customer,30,Business travel,Eco Plus,101,2,2,2,2,2,2,2,2,1,2,4,4,3,2,81,76.0,neutral or dissatisfied +59479,31700,Male,Loyal Customer,32,Personal Travel,Eco,846,0,5,0,4,5,0,1,5,4,5,5,3,5,5,8,2.0,satisfied +59480,86915,Male,Loyal Customer,73,Business travel,Eco,352,2,4,3,4,2,2,2,2,1,1,1,2,4,2,0,0.0,satisfied +59481,59384,Female,Loyal Customer,59,Personal Travel,Eco,2556,3,4,3,2,4,5,1,1,1,3,2,5,1,4,6,0.0,neutral or dissatisfied +59482,63801,Male,Loyal Customer,59,Business travel,Business,1721,4,4,4,4,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +59483,101163,Male,Loyal Customer,24,Business travel,Business,1090,3,5,5,5,3,3,3,3,4,3,4,4,3,3,5,0.0,neutral or dissatisfied +59484,83921,Male,Loyal Customer,58,Business travel,Business,304,4,5,5,5,1,3,3,4,4,4,4,4,4,2,13,27.0,neutral or dissatisfied +59485,19839,Female,Loyal Customer,42,Business travel,Eco Plus,594,5,3,3,3,3,4,2,5,5,5,5,4,5,1,0,0.0,satisfied +59486,107738,Male,Loyal Customer,62,Personal Travel,Eco,251,2,1,2,4,2,2,2,2,1,3,4,3,3,2,40,33.0,neutral or dissatisfied +59487,53811,Female,disloyal Customer,30,Business travel,Eco,191,3,4,3,1,3,3,3,3,2,1,3,4,1,3,19,10.0,neutral or dissatisfied +59488,22540,Male,Loyal Customer,49,Personal Travel,Eco Plus,83,4,5,4,1,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +59489,1750,Female,Loyal Customer,18,Personal Travel,Eco,364,3,4,5,3,2,5,2,2,5,2,4,3,4,2,0,5.0,neutral or dissatisfied +59490,105557,Female,disloyal Customer,36,Business travel,Business,577,1,1,1,4,2,1,2,2,2,3,3,4,3,2,0,0.0,neutral or dissatisfied +59491,101290,Male,Loyal Customer,38,Business travel,Eco,363,5,4,4,4,5,5,5,5,4,5,1,2,3,5,0,0.0,satisfied +59492,38225,Male,Loyal Customer,12,Personal Travel,Eco Plus,1091,1,4,1,5,4,1,4,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +59493,126723,Female,Loyal Customer,51,Business travel,Business,2402,4,4,4,4,5,4,4,2,2,2,2,3,2,3,4,0.0,satisfied +59494,80563,Male,Loyal Customer,41,Business travel,Business,1747,2,2,2,2,5,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +59495,57444,Male,Loyal Customer,60,Personal Travel,Business,334,2,4,2,1,5,4,4,4,4,2,4,3,4,4,3,4.0,neutral or dissatisfied +59496,44893,Male,Loyal Customer,50,Business travel,Eco,536,2,1,1,1,1,2,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +59497,38746,Male,Loyal Customer,39,Business travel,Business,2304,4,4,3,4,1,1,1,4,4,4,4,2,4,4,0,0.0,satisfied +59498,65095,Male,Loyal Customer,43,Personal Travel,Eco,247,3,1,3,3,4,3,4,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +59499,60606,Male,Loyal Customer,42,Business travel,Business,991,2,2,1,2,3,4,5,4,4,4,4,4,4,5,3,0.0,satisfied +59500,2466,Female,Loyal Customer,42,Personal Travel,Eco,773,4,3,4,2,5,3,3,5,5,4,4,1,5,3,0,3.0,neutral or dissatisfied +59501,120516,Female,Loyal Customer,10,Personal Travel,Eco Plus,337,2,5,3,3,3,3,3,3,5,5,4,5,5,3,0,2.0,neutral or dissatisfied +59502,127379,Male,disloyal Customer,17,Business travel,Business,1009,4,5,3,3,2,3,2,2,5,5,4,3,5,2,17,3.0,satisfied +59503,94992,Male,Loyal Customer,9,Personal Travel,Eco,148,2,2,2,4,3,2,3,3,2,4,3,2,4,3,10,5.0,neutral or dissatisfied +59504,526,Female,Loyal Customer,55,Business travel,Business,1827,5,5,5,5,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +59505,38898,Male,disloyal Customer,37,Business travel,Eco,205,5,0,4,4,1,4,5,1,4,4,4,5,2,1,0,0.0,satisfied +59506,93990,Male,Loyal Customer,61,Personal Travel,Eco,1218,3,0,3,4,3,3,1,3,1,5,3,4,3,3,107,82.0,neutral or dissatisfied +59507,87127,Male,Loyal Customer,31,Personal Travel,Eco,594,3,2,3,4,3,3,3,3,1,2,4,1,3,3,2,0.0,neutral or dissatisfied +59508,34110,Female,Loyal Customer,45,Business travel,Eco,1189,4,5,5,5,2,5,1,4,4,4,4,5,4,1,0,0.0,satisfied +59509,73364,Male,Loyal Customer,26,Business travel,Business,3338,2,1,1,1,2,2,2,2,4,1,4,3,3,2,0,0.0,neutral or dissatisfied +59510,56830,Female,Loyal Customer,24,Personal Travel,Eco,1605,2,4,2,1,3,2,3,3,5,2,5,3,5,3,1,0.0,neutral or dissatisfied +59511,107122,Female,Loyal Customer,38,Business travel,Eco,842,2,3,3,3,2,2,2,2,2,4,3,2,4,2,88,108.0,neutral or dissatisfied +59512,35789,Male,Loyal Customer,37,Personal Travel,Eco,200,2,4,2,1,1,2,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +59513,7845,Male,Loyal Customer,58,Business travel,Business,2781,1,1,1,1,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +59514,6903,Female,Loyal Customer,27,Business travel,Eco,265,4,1,1,1,4,4,4,4,4,3,4,5,3,4,0,0.0,satisfied +59515,4392,Female,Loyal Customer,29,Personal Travel,Eco,607,2,5,2,3,3,2,3,3,5,5,5,5,5,3,9,0.0,neutral or dissatisfied +59516,70243,Male,Loyal Customer,51,Business travel,Eco,1592,2,3,3,3,2,2,2,2,1,2,2,3,3,2,27,8.0,neutral or dissatisfied +59517,106389,Male,Loyal Customer,47,Business travel,Business,551,2,2,2,2,4,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +59518,126594,Female,disloyal Customer,49,Business travel,Business,1337,3,3,3,1,3,3,3,3,5,2,4,5,5,3,13,64.0,neutral or dissatisfied +59519,102072,Female,Loyal Customer,60,Business travel,Business,2401,5,5,5,5,2,5,4,5,5,4,5,5,5,5,20,6.0,satisfied +59520,18871,Male,Loyal Customer,21,Business travel,Business,2676,3,1,2,1,3,3,3,3,1,2,3,3,2,3,0,0.0,neutral or dissatisfied +59521,80315,Female,Loyal Customer,56,Personal Travel,Eco,746,3,1,3,3,4,3,2,5,5,3,3,2,5,3,0,0.0,neutral or dissatisfied +59522,78633,Male,Loyal Customer,60,Business travel,Business,1953,4,2,2,2,5,2,4,4,4,4,4,4,4,3,0,1.0,neutral or dissatisfied +59523,1711,Female,Loyal Customer,57,Business travel,Business,2445,1,1,1,1,4,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +59524,11342,Female,Loyal Customer,44,Personal Travel,Eco,429,3,1,3,3,1,3,2,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +59525,88583,Female,Loyal Customer,19,Personal Travel,Eco,404,3,3,3,3,3,3,3,3,1,2,4,1,3,3,0,1.0,neutral or dissatisfied +59526,110610,Male,Loyal Customer,48,Business travel,Business,3928,4,4,4,4,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +59527,25205,Male,Loyal Customer,47,Business travel,Eco,925,4,4,4,4,5,4,5,5,2,4,4,1,1,5,0,5.0,satisfied +59528,50655,Male,Loyal Customer,39,Personal Travel,Eco,190,3,4,3,1,2,3,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +59529,23599,Female,Loyal Customer,33,Business travel,Business,3504,2,5,5,5,3,4,4,2,2,2,2,4,2,4,25,14.0,neutral or dissatisfied +59530,4588,Female,Loyal Customer,51,Business travel,Eco,416,3,5,5,5,3,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +59531,43022,Male,disloyal Customer,55,Business travel,Eco,192,1,3,1,2,5,1,4,5,4,5,2,1,2,5,0,0.0,neutral or dissatisfied +59532,112158,Male,Loyal Customer,24,Business travel,Business,3993,2,5,5,5,2,2,2,2,1,3,3,3,4,2,23,27.0,neutral or dissatisfied +59533,63143,Male,Loyal Customer,32,Personal Travel,Business,337,1,2,1,3,3,1,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +59534,89157,Male,Loyal Customer,70,Personal Travel,Eco,2092,2,2,2,4,3,2,1,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +59535,108526,Female,Loyal Customer,47,Business travel,Business,649,5,5,5,5,2,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +59536,2972,Female,Loyal Customer,68,Personal Travel,Eco Plus,737,1,4,1,3,3,5,4,2,2,1,1,3,2,3,0,0.0,neutral or dissatisfied +59537,28300,Female,Loyal Customer,44,Business travel,Eco,867,4,1,1,1,5,3,2,4,4,4,4,2,4,4,0,0.0,satisfied +59538,125353,Male,Loyal Customer,56,Business travel,Business,599,3,3,3,3,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +59539,17702,Female,Loyal Customer,63,Business travel,Business,2397,2,2,2,2,2,5,3,4,4,4,4,4,4,3,0,0.0,satisfied +59540,32959,Male,Loyal Customer,45,Personal Travel,Eco,121,1,1,1,4,2,1,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +59541,44536,Male,disloyal Customer,47,Business travel,Eco,157,2,3,2,3,4,2,4,4,3,3,4,4,3,4,45,48.0,neutral or dissatisfied +59542,39707,Female,Loyal Customer,39,Business travel,Business,2501,0,0,0,5,3,1,5,2,2,2,3,1,2,1,21,10.0,satisfied +59543,55384,Male,Loyal Customer,45,Personal Travel,Eco,594,1,3,1,4,3,1,3,3,1,4,2,5,3,3,0,0.0,neutral or dissatisfied +59544,16986,Female,Loyal Customer,11,Business travel,Eco,610,5,1,1,1,5,5,5,5,5,4,1,2,5,5,82,65.0,satisfied +59545,74410,Female,Loyal Customer,41,Business travel,Business,1464,2,2,4,2,2,4,5,3,3,3,3,3,3,4,1,0.0,satisfied +59546,30057,Male,Loyal Customer,48,Business travel,Eco,213,2,3,3,3,2,2,2,2,3,4,1,1,5,2,0,0.0,satisfied +59547,64965,Female,disloyal Customer,41,Business travel,Business,224,3,3,3,4,3,2,2,1,4,4,5,2,2,2,262,256.0,satisfied +59548,129790,Male,Loyal Customer,64,Personal Travel,Eco,447,4,5,4,3,2,4,2,2,1,5,5,4,3,2,0,0.0,neutral or dissatisfied +59549,3195,Female,Loyal Customer,25,Personal Travel,Eco,693,2,5,2,4,3,2,3,3,3,2,5,3,4,3,12,29.0,neutral or dissatisfied +59550,60969,Female,Loyal Customer,46,Personal Travel,Eco,888,5,5,5,1,3,5,5,2,2,5,2,5,2,4,0,0.0,satisfied +59551,1555,Female,disloyal Customer,25,Business travel,Business,987,1,0,1,3,1,1,5,1,3,2,5,3,4,1,2,0.0,neutral or dissatisfied +59552,24521,Male,Loyal Customer,20,Personal Travel,Eco Plus,481,2,3,2,4,5,2,1,5,1,1,4,2,3,5,0,0.0,neutral or dissatisfied +59553,105544,Female,Loyal Customer,15,Personal Travel,Eco,611,3,4,3,1,1,3,1,1,5,4,5,3,5,1,14,5.0,neutral or dissatisfied +59554,79866,Male,Loyal Customer,48,Business travel,Business,950,4,4,3,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +59555,19644,Female,Loyal Customer,60,Business travel,Eco Plus,531,1,1,1,1,5,3,3,1,1,1,1,4,1,4,37,30.0,neutral or dissatisfied +59556,15347,Male,Loyal Customer,29,Business travel,Business,3914,3,1,1,1,3,3,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +59557,117898,Female,Loyal Customer,52,Business travel,Business,1677,1,1,1,1,2,4,4,4,4,4,4,3,4,3,20,13.0,satisfied +59558,127911,Female,Loyal Customer,52,Personal Travel,Eco,1671,2,5,2,3,5,1,4,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +59559,39329,Female,Loyal Customer,20,Personal Travel,Eco Plus,67,2,5,2,4,2,4,4,3,3,4,5,4,3,4,228,232.0,neutral or dissatisfied +59560,28679,Female,Loyal Customer,57,Business travel,Business,2797,1,1,1,1,5,5,5,2,5,4,4,5,1,5,0,0.0,satisfied +59561,36828,Female,Loyal Customer,39,Business travel,Business,369,2,2,2,2,4,3,5,4,4,4,4,5,4,1,0,0.0,satisfied +59562,84304,Male,Loyal Customer,52,Personal Travel,Eco,235,3,5,3,4,3,3,3,3,4,4,4,5,5,3,2,7.0,neutral or dissatisfied +59563,90349,Female,disloyal Customer,32,Business travel,Business,271,3,3,3,4,3,3,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +59564,129673,Male,disloyal Customer,38,Business travel,Business,337,5,5,5,1,5,5,5,5,5,5,4,3,5,5,18,5.0,satisfied +59565,128789,Male,Loyal Customer,34,Business travel,Business,2475,3,3,3,3,3,3,3,4,3,5,4,3,4,3,0,0.0,satisfied +59566,33077,Male,Loyal Customer,57,Personal Travel,Eco,101,5,3,5,3,3,5,3,3,5,3,4,2,5,3,0,0.0,satisfied +59567,33462,Male,Loyal Customer,51,Personal Travel,Eco Plus,2556,2,4,2,2,2,5,5,5,2,3,5,5,5,5,3,22.0,neutral or dissatisfied +59568,10256,Male,Loyal Customer,12,Personal Travel,Business,134,1,1,1,4,1,3,5,2,1,4,3,5,2,5,156,168.0,neutral or dissatisfied +59569,65612,Male,Loyal Customer,52,Personal Travel,Eco,175,2,4,0,2,4,0,4,4,3,3,4,4,4,4,4,11.0,neutral or dissatisfied +59570,20517,Female,Loyal Customer,30,Business travel,Business,3185,4,4,4,4,4,4,4,4,3,3,4,5,5,4,0,4.0,satisfied +59571,30528,Female,Loyal Customer,39,Business travel,Business,2807,2,2,2,2,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +59572,52321,Male,Loyal Customer,25,Business travel,Business,3369,1,1,1,1,2,2,2,2,1,2,3,2,4,2,0,0.0,satisfied +59573,70175,Male,disloyal Customer,25,Business travel,Business,258,4,0,4,1,4,4,4,4,5,3,5,3,4,4,4,0.0,satisfied +59574,110791,Female,Loyal Customer,56,Business travel,Eco,766,4,1,1,1,3,3,5,4,4,4,4,1,4,4,18,7.0,satisfied +59575,82034,Male,Loyal Customer,56,Personal Travel,Eco,1532,3,4,3,4,2,3,2,2,1,1,2,3,4,2,0,0.0,neutral or dissatisfied +59576,91368,Female,Loyal Customer,8,Personal Travel,Eco Plus,444,3,5,3,5,1,3,1,1,5,5,5,3,5,1,8,0.0,neutral or dissatisfied +59577,59532,Male,Loyal Customer,45,Business travel,Business,854,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,2.0,satisfied +59578,5635,Female,disloyal Customer,28,Business travel,Business,436,5,5,5,5,1,5,1,1,3,2,4,3,5,1,0,0.0,satisfied +59579,123453,Male,Loyal Customer,57,Business travel,Business,2125,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +59580,44927,Female,Loyal Customer,22,Business travel,Business,403,3,1,1,1,3,3,3,3,1,2,3,3,3,3,119,107.0,neutral or dissatisfied +59581,108283,Male,Loyal Customer,15,Personal Travel,Eco Plus,895,1,5,2,3,4,2,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +59582,48054,Male,Loyal Customer,42,Personal Travel,Eco,677,3,1,3,3,4,3,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +59583,105956,Male,Loyal Customer,36,Business travel,Business,2329,1,1,5,1,2,4,5,5,5,5,5,5,5,5,10,12.0,satisfied +59584,90654,Male,Loyal Customer,61,Business travel,Business,3154,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,6.0,satisfied +59585,108749,Male,Loyal Customer,42,Business travel,Business,3965,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +59586,16346,Male,Loyal Customer,38,Business travel,Business,160,5,5,5,5,4,3,5,4,4,4,3,5,4,1,0,0.0,satisfied +59587,10986,Male,Loyal Customer,52,Business travel,Business,316,1,1,1,1,1,3,3,3,3,4,3,5,3,3,0,0.0,satisfied +59588,95086,Male,Loyal Customer,31,Personal Travel,Eco,323,1,3,1,5,3,1,1,3,3,2,2,1,2,3,26,26.0,neutral or dissatisfied +59589,92316,Male,disloyal Customer,42,Business travel,Business,2556,2,2,2,5,2,3,3,3,3,4,5,3,3,3,25,27.0,neutral or dissatisfied +59590,113021,Male,disloyal Customer,25,Business travel,Business,569,3,4,3,3,2,3,2,2,5,3,4,3,5,2,1,0.0,neutral or dissatisfied +59591,60981,Male,Loyal Customer,39,Personal Travel,Eco,888,3,3,3,3,2,3,2,2,5,2,4,1,1,2,2,0.0,neutral or dissatisfied +59592,73876,Female,Loyal Customer,28,Business travel,Business,2218,2,2,2,2,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +59593,40554,Female,Loyal Customer,49,Business travel,Business,3864,3,2,2,2,3,4,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +59594,78360,Male,Loyal Customer,60,Business travel,Business,2949,2,2,2,2,4,4,4,5,5,5,5,4,5,5,8,11.0,satisfied +59595,85761,Male,Loyal Customer,54,Business travel,Business,2563,5,5,2,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +59596,101341,Male,Loyal Customer,65,Personal Travel,Eco Plus,1771,4,1,4,2,4,4,5,4,2,5,3,1,2,4,0,0.0,neutral or dissatisfied +59597,116073,Male,Loyal Customer,66,Personal Travel,Eco,404,1,4,1,4,4,1,4,4,3,5,5,3,4,4,8,13.0,neutral or dissatisfied +59598,116592,Female,Loyal Customer,40,Business travel,Business,337,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +59599,63361,Female,Loyal Customer,41,Personal Travel,Eco,372,5,4,5,2,2,5,2,2,3,2,5,3,5,2,0,0.0,satisfied +59600,82714,Female,Loyal Customer,22,Personal Travel,Eco,632,2,5,2,4,5,2,4,5,4,4,4,5,1,5,9,0.0,neutral or dissatisfied +59601,93593,Female,disloyal Customer,39,Business travel,Business,159,5,5,5,3,4,5,4,4,3,2,4,4,4,4,40,44.0,satisfied +59602,22759,Female,Loyal Customer,58,Business travel,Eco,302,4,4,4,4,4,3,2,4,4,4,4,1,4,5,3,5.0,satisfied +59603,88973,Male,disloyal Customer,26,Business travel,Eco,1199,2,2,2,3,4,2,4,4,3,1,3,3,4,4,0,3.0,neutral or dissatisfied +59604,63439,Female,Loyal Customer,45,Personal Travel,Eco,447,2,5,2,2,4,1,2,1,1,2,1,4,1,1,13,0.0,neutral or dissatisfied +59605,68118,Male,Loyal Customer,17,Personal Travel,Eco,868,3,4,3,3,1,3,1,1,2,4,3,2,3,1,0,2.0,neutral or dissatisfied +59606,22321,Male,disloyal Customer,33,Business travel,Eco,143,1,3,1,3,5,1,2,5,5,3,5,1,1,5,0,31.0,neutral or dissatisfied +59607,27299,Male,disloyal Customer,22,Business travel,Eco,679,5,5,5,3,3,0,3,3,1,4,5,2,2,3,0,0.0,satisfied +59608,85027,Male,Loyal Customer,57,Personal Travel,Eco,1590,3,1,3,3,5,3,5,5,2,4,2,3,3,5,0,0.0,neutral or dissatisfied +59609,115367,Male,disloyal Customer,27,Business travel,Eco,417,1,2,1,4,3,1,5,3,3,1,3,2,4,3,37,35.0,neutral or dissatisfied +59610,56671,Male,Loyal Customer,29,Personal Travel,Eco,1065,5,4,5,4,5,5,5,5,4,4,5,5,5,5,7,17.0,satisfied +59611,62804,Male,Loyal Customer,50,Personal Travel,Eco,2399,2,4,2,4,2,3,3,3,3,4,4,3,4,3,4,37.0,neutral or dissatisfied +59612,129724,Female,disloyal Customer,42,Business travel,Eco,447,2,3,2,4,3,2,3,3,4,4,3,1,4,3,0,6.0,neutral or dissatisfied +59613,71870,Male,Loyal Customer,8,Personal Travel,Eco,1744,2,5,1,4,2,1,2,2,4,2,3,4,5,2,26,17.0,neutral or dissatisfied +59614,120976,Female,Loyal Customer,25,Business travel,Business,1013,3,2,2,2,3,3,3,3,3,3,4,2,3,3,50,73.0,neutral or dissatisfied +59615,92704,Female,Loyal Customer,45,Personal Travel,Eco Plus,507,2,4,4,5,2,5,5,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +59616,112609,Male,Loyal Customer,45,Business travel,Eco,202,2,2,2,2,2,2,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +59617,27868,Female,Loyal Customer,41,Business travel,Eco Plus,1448,5,4,4,4,1,3,4,5,5,5,5,1,5,2,0,0.0,satisfied +59618,63035,Female,Loyal Customer,36,Business travel,Business,2050,1,0,0,3,5,3,4,3,3,0,1,4,3,3,5,13.0,neutral or dissatisfied +59619,94387,Female,Loyal Customer,47,Business travel,Business,3605,4,4,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +59620,110617,Male,Loyal Customer,30,Business travel,Business,3411,5,5,2,5,2,2,2,2,5,4,5,3,5,2,15,22.0,satisfied +59621,125093,Female,Loyal Customer,44,Business travel,Business,361,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +59622,45435,Male,disloyal Customer,39,Business travel,Eco,458,2,3,2,3,4,2,4,4,1,2,3,2,4,4,116,122.0,neutral or dissatisfied +59623,113803,Male,Loyal Customer,40,Business travel,Eco Plus,407,4,2,2,2,4,4,4,4,2,5,3,2,4,4,11,6.0,neutral or dissatisfied +59624,111418,Female,Loyal Customer,60,Business travel,Business,896,4,4,4,4,4,5,5,4,4,4,4,5,4,5,5,14.0,satisfied +59625,77327,Female,Loyal Customer,41,Business travel,Business,599,1,1,1,1,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +59626,28601,Male,Loyal Customer,23,Personal Travel,Business,2614,3,1,3,3,4,3,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +59627,14393,Female,Loyal Customer,40,Business travel,Business,900,4,1,1,1,3,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +59628,6689,Male,disloyal Customer,25,Business travel,Eco,403,3,1,3,3,5,3,5,5,4,5,3,1,3,5,15,6.0,neutral or dissatisfied +59629,60925,Male,Loyal Customer,41,Business travel,Business,888,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +59630,68806,Female,Loyal Customer,13,Personal Travel,Eco,926,1,4,1,3,3,1,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +59631,17555,Female,Loyal Customer,43,Business travel,Eco Plus,570,2,1,1,1,1,3,3,1,1,2,1,4,1,4,54,46.0,neutral or dissatisfied +59632,116715,Female,Loyal Customer,22,Business travel,Eco Plus,417,1,3,3,3,1,1,1,1,3,3,3,3,4,1,2,0.0,neutral or dissatisfied +59633,100932,Male,Loyal Customer,29,Personal Travel,Eco,838,3,4,3,3,2,3,2,2,3,2,5,4,5,2,18,18.0,neutral or dissatisfied +59634,110995,Female,Loyal Customer,53,Business travel,Business,3184,2,2,2,2,4,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +59635,111831,Female,Loyal Customer,54,Business travel,Business,1605,4,4,4,4,5,5,5,5,2,4,5,5,4,5,223,200.0,satisfied +59636,71446,Female,disloyal Customer,39,Business travel,Business,867,4,5,5,4,2,5,2,2,5,3,4,4,4,2,13,10.0,neutral or dissatisfied +59637,1176,Female,Loyal Customer,61,Personal Travel,Eco,89,1,1,1,3,1,3,3,5,5,1,2,3,5,2,0,0.0,neutral or dissatisfied +59638,27866,Female,disloyal Customer,35,Business travel,Eco Plus,1448,2,2,2,4,4,2,4,4,1,4,3,2,2,4,0,0.0,neutral or dissatisfied +59639,39825,Female,disloyal Customer,32,Business travel,Eco,272,3,0,3,4,4,3,4,4,1,3,5,1,5,4,0,0.0,neutral or dissatisfied +59640,83019,Male,Loyal Customer,37,Business travel,Business,2489,4,4,4,4,2,5,5,5,5,5,5,4,5,4,11,1.0,satisfied +59641,11871,Female,Loyal Customer,55,Personal Travel,Eco,1042,5,5,4,4,2,5,4,2,2,4,2,4,2,5,0,0.0,satisfied +59642,2125,Female,Loyal Customer,47,Business travel,Business,3584,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +59643,16383,Female,disloyal Customer,34,Business travel,Eco,463,1,0,1,2,1,1,1,1,4,5,2,5,1,1,5,8.0,neutral or dissatisfied +59644,30758,Female,Loyal Customer,53,Personal Travel,Eco Plus,977,3,5,3,3,5,4,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +59645,12733,Female,Loyal Customer,16,Personal Travel,Eco,696,3,4,3,4,2,3,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +59646,64360,Male,disloyal Customer,38,Business travel,Eco,792,1,1,1,4,5,1,5,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +59647,56651,Female,Loyal Customer,59,Business travel,Eco,1085,2,5,5,5,2,3,3,2,2,2,2,2,2,1,0,29.0,neutral or dissatisfied +59648,17362,Male,Loyal Customer,30,Personal Travel,Eco,563,4,2,4,3,3,4,3,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +59649,56914,Male,Loyal Customer,39,Business travel,Business,2454,2,2,2,2,5,5,5,3,5,4,4,5,3,5,0,0.0,satisfied +59650,121974,Male,Loyal Customer,55,Business travel,Business,3664,2,2,2,2,2,4,5,5,5,5,4,3,5,3,88,91.0,satisfied +59651,81084,Female,Loyal Customer,22,Business travel,Business,3492,1,1,1,1,4,4,4,4,5,4,4,4,4,4,16,11.0,satisfied +59652,101532,Male,Loyal Customer,50,Personal Travel,Eco,345,2,4,2,1,5,2,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +59653,61209,Male,Loyal Customer,50,Business travel,Business,3766,5,2,5,5,2,4,4,4,4,5,4,5,4,3,35,19.0,satisfied +59654,47450,Female,Loyal Customer,64,Personal Travel,Eco,558,1,2,1,4,3,4,4,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +59655,101669,Female,Loyal Customer,24,Personal Travel,Eco,2106,5,5,5,3,2,5,2,2,1,1,5,4,5,2,0,8.0,satisfied +59656,69596,Female,Loyal Customer,68,Personal Travel,Eco,2475,2,1,2,4,2,2,2,1,3,3,4,2,3,2,1,0.0,neutral or dissatisfied +59657,95925,Male,Loyal Customer,70,Business travel,Eco,1411,2,1,1,1,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +59658,71570,Female,disloyal Customer,14,Business travel,Eco,1197,3,3,3,2,3,3,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +59659,56911,Male,Loyal Customer,47,Business travel,Business,2454,5,5,5,5,5,5,5,5,2,5,4,5,5,5,9,0.0,satisfied +59660,34161,Female,Loyal Customer,43,Business travel,Eco,1046,1,0,0,3,3,3,4,4,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +59661,37882,Female,Loyal Customer,39,Business travel,Business,2299,1,3,3,3,1,4,3,1,1,1,1,1,1,1,0,1.0,neutral or dissatisfied +59662,31190,Female,Loyal Customer,33,Business travel,Business,1708,4,4,4,4,3,1,2,2,2,2,2,2,2,2,6,19.0,satisfied +59663,66698,Female,Loyal Customer,65,Business travel,Business,2149,4,3,2,3,2,3,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +59664,18116,Male,Loyal Customer,13,Personal Travel,Eco,629,1,1,1,1,3,1,3,3,3,4,1,2,1,3,39,18.0,neutral or dissatisfied +59665,128206,Female,disloyal Customer,25,Business travel,Business,602,1,0,1,2,5,1,2,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +59666,100408,Female,Loyal Customer,49,Business travel,Business,2905,5,5,5,5,5,4,4,2,2,2,2,3,2,5,4,24.0,satisfied +59667,26898,Female,disloyal Customer,23,Business travel,Business,1215,5,0,5,1,1,5,1,1,3,2,5,4,5,1,0,0.0,satisfied +59668,76810,Female,Loyal Customer,45,Personal Travel,Eco,546,3,3,3,2,1,2,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +59669,7620,Female,Loyal Customer,8,Business travel,Eco Plus,802,1,2,5,2,1,1,1,1,1,4,3,2,3,1,0,0.0,neutral or dissatisfied +59670,8445,Male,Loyal Customer,41,Personal Travel,Eco,590,3,3,4,4,4,4,5,4,1,4,4,1,2,4,1,13.0,neutral or dissatisfied +59671,111284,Female,Loyal Customer,53,Personal Travel,Eco,459,4,5,4,4,5,5,4,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +59672,108594,Female,Loyal Customer,47,Business travel,Business,696,4,4,2,4,4,5,5,4,4,4,4,5,4,4,1,12.0,satisfied +59673,6271,Male,disloyal Customer,43,Business travel,Eco,693,4,4,4,4,4,4,4,4,3,1,3,4,4,4,126,117.0,neutral or dissatisfied +59674,18040,Female,Loyal Customer,39,Business travel,Business,3725,5,1,5,5,5,5,1,4,4,4,4,4,4,1,0,0.0,satisfied +59675,97856,Female,Loyal Customer,54,Business travel,Business,3281,3,5,5,5,4,3,4,3,3,3,3,4,3,4,19,7.0,neutral or dissatisfied +59676,127437,Male,Loyal Customer,19,Personal Travel,Eco,868,4,3,4,4,5,4,5,5,5,5,1,5,5,5,0,15.0,neutral or dissatisfied +59677,112688,Male,Loyal Customer,44,Business travel,Business,3764,3,3,2,3,5,5,5,4,4,4,4,4,4,3,12,0.0,satisfied +59678,56885,Female,Loyal Customer,44,Business travel,Business,2454,5,5,5,5,4,4,4,5,4,5,5,4,4,4,0,0.0,satisfied +59679,45562,Female,Loyal Customer,49,Business travel,Business,2266,4,3,4,4,4,4,5,4,4,4,4,1,4,1,28,,satisfied +59680,80126,Female,Loyal Customer,55,Business travel,Business,2475,5,5,4,5,5,5,5,3,4,3,4,5,3,5,0,0.0,satisfied +59681,60021,Female,Loyal Customer,70,Personal Travel,Eco,1085,1,5,1,2,4,4,5,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +59682,62392,Female,disloyal Customer,37,Business travel,Eco,1204,1,1,1,2,3,1,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +59683,46739,Female,Loyal Customer,57,Personal Travel,Eco,125,2,3,2,4,5,2,2,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +59684,123340,Female,Loyal Customer,61,Personal Travel,Eco Plus,468,3,5,3,3,4,4,5,4,4,3,4,5,4,5,5,0.0,neutral or dissatisfied +59685,51348,Female,Loyal Customer,32,Business travel,Eco Plus,262,4,3,1,3,4,4,4,4,5,1,3,5,5,4,0,9.0,satisfied +59686,127805,Male,disloyal Customer,28,Business travel,Eco,1262,3,3,3,3,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +59687,84429,Male,Loyal Customer,65,Personal Travel,Eco,591,3,3,3,4,4,3,3,4,5,3,1,2,5,4,0,0.0,neutral or dissatisfied +59688,3048,Female,Loyal Customer,49,Personal Travel,Eco,489,4,3,4,3,2,4,3,2,2,4,3,3,2,3,0,0.0,neutral or dissatisfied +59689,41949,Male,Loyal Customer,44,Business travel,Business,618,2,3,3,3,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +59690,115997,Male,Loyal Customer,24,Personal Travel,Eco,342,4,5,4,1,3,4,3,3,2,1,4,5,3,3,37,30.0,satisfied +59691,90097,Female,disloyal Customer,44,Business travel,Eco,1127,1,1,1,3,4,1,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +59692,45604,Male,Loyal Customer,31,Business travel,Eco,113,5,5,5,5,5,5,5,5,5,2,3,1,1,5,95,121.0,satisfied +59693,13986,Male,Loyal Customer,57,Personal Travel,Eco,372,3,0,3,4,4,3,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +59694,2880,Male,Loyal Customer,42,Personal Travel,Eco,409,1,5,1,5,4,1,1,4,3,2,4,1,4,4,0,20.0,neutral or dissatisfied +59695,24683,Female,Loyal Customer,45,Business travel,Business,761,4,4,4,4,3,1,4,4,4,4,4,4,4,1,25,22.0,satisfied +59696,17905,Female,disloyal Customer,24,Business travel,Eco,900,2,2,2,2,3,2,3,3,1,3,5,1,2,3,0,0.0,neutral or dissatisfied +59697,35343,Female,Loyal Customer,23,Business travel,Eco,1056,2,3,3,3,2,3,2,2,3,5,4,3,3,2,0,0.0,neutral or dissatisfied +59698,55905,Male,Loyal Customer,36,Business travel,Business,723,2,3,3,3,4,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +59699,34792,Female,Loyal Customer,48,Personal Travel,Eco,301,3,4,3,4,4,5,4,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +59700,38135,Male,Loyal Customer,39,Business travel,Business,837,2,4,2,4,4,4,4,2,2,2,2,1,2,4,19,7.0,neutral or dissatisfied +59701,128116,Male,Loyal Customer,28,Business travel,Business,1587,1,1,2,1,4,4,4,4,5,4,4,3,4,4,4,1.0,satisfied +59702,26415,Male,Loyal Customer,50,Personal Travel,Eco Plus,1249,3,2,3,4,3,3,3,3,4,2,4,4,4,3,8,0.0,neutral or dissatisfied +59703,12785,Female,Loyal Customer,23,Personal Travel,Business,817,3,2,3,3,2,3,5,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +59704,129048,Female,Loyal Customer,42,Business travel,Business,1744,3,2,2,2,5,1,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +59705,127268,Male,disloyal Customer,34,Business travel,Business,1107,2,2,2,1,3,2,3,3,4,3,2,1,3,3,0,0.0,neutral or dissatisfied +59706,76446,Male,Loyal Customer,48,Business travel,Business,516,1,1,1,1,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +59707,34841,Male,Loyal Customer,22,Personal Travel,Eco Plus,301,3,5,5,4,2,5,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +59708,12467,Male,Loyal Customer,59,Personal Travel,Eco,285,5,4,5,3,1,5,1,1,4,5,1,3,2,1,0,0.0,satisfied +59709,56119,Male,Loyal Customer,25,Personal Travel,Business,1400,4,2,3,3,5,3,5,5,2,4,3,3,4,5,3,0.0,neutral or dissatisfied +59710,107012,Male,Loyal Customer,47,Business travel,Business,3827,3,3,3,3,3,5,5,4,4,4,4,3,4,3,10,13.0,satisfied +59711,45648,Male,Loyal Customer,66,Personal Travel,Eco,230,2,3,2,2,1,2,1,1,1,4,2,3,3,1,0,0.0,neutral or dissatisfied +59712,12163,Male,disloyal Customer,27,Business travel,Business,1075,3,2,2,4,4,2,4,4,1,1,4,1,3,4,0,3.0,neutral or dissatisfied +59713,88729,Male,Loyal Customer,36,Personal Travel,Eco,404,1,2,1,4,3,1,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +59714,118388,Male,disloyal Customer,16,Business travel,Eco,651,1,5,1,4,1,5,5,4,5,5,5,5,4,5,192,185.0,neutral or dissatisfied +59715,78344,Female,Loyal Customer,43,Business travel,Business,3281,4,4,4,4,4,1,5,5,5,5,5,5,5,2,0,0.0,satisfied +59716,71815,Female,disloyal Customer,41,Business travel,Eco,1744,3,3,3,4,4,3,4,4,4,3,3,1,4,4,0,0.0,neutral or dissatisfied +59717,45519,Male,Loyal Customer,45,Business travel,Eco,689,3,1,1,1,3,3,3,3,3,4,3,2,4,3,31,29.0,neutral or dissatisfied +59718,98951,Male,disloyal Customer,18,Business travel,Eco,569,2,4,2,3,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +59719,99927,Male,Loyal Customer,44,Business travel,Business,3742,3,4,4,4,5,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +59720,58401,Female,Loyal Customer,47,Business travel,Business,3477,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +59721,47626,Female,disloyal Customer,17,Business travel,Eco,1504,4,5,5,3,5,4,2,5,3,1,1,4,4,5,0,0.0,satisfied +59722,13825,Female,Loyal Customer,23,Business travel,Business,594,5,5,5,5,5,5,5,5,4,4,1,5,2,5,0,12.0,satisfied +59723,114882,Female,disloyal Customer,35,Business travel,Business,342,2,2,2,3,3,2,4,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +59724,44121,Male,Loyal Customer,42,Business travel,Eco,120,1,3,3,3,1,1,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +59725,108891,Female,Loyal Customer,59,Business travel,Business,3843,5,5,5,5,2,5,5,4,4,4,4,4,4,3,55,51.0,satisfied +59726,27349,Female,disloyal Customer,27,Business travel,Eco,987,2,2,2,1,5,2,5,5,1,5,1,2,2,5,1,0.0,neutral or dissatisfied +59727,11732,Male,Loyal Customer,23,Business travel,Business,395,3,2,2,2,3,3,3,3,4,2,3,4,2,3,56,55.0,neutral or dissatisfied +59728,120741,Male,Loyal Customer,10,Personal Travel,Business,588,3,4,3,2,4,3,4,4,1,5,4,1,3,4,113,112.0,neutral or dissatisfied +59729,88750,Male,Loyal Customer,23,Personal Travel,Eco,442,3,5,3,3,2,3,2,2,3,4,5,3,4,2,3,0.0,neutral or dissatisfied +59730,48681,Male,Loyal Customer,45,Business travel,Business,2025,3,3,3,3,5,4,5,4,4,4,5,5,4,4,0,0.0,satisfied +59731,16119,Female,Loyal Customer,53,Business travel,Eco,725,1,3,3,3,3,4,4,1,1,1,1,4,1,1,12,22.0,neutral or dissatisfied +59732,38235,Female,Loyal Customer,36,Business travel,Business,2855,1,1,1,1,5,4,3,5,5,5,5,5,5,3,36,9.0,satisfied +59733,110997,Male,Loyal Customer,51,Business travel,Business,1820,3,3,3,3,3,5,5,4,4,4,4,3,4,3,5,1.0,satisfied +59734,21646,Male,Loyal Customer,49,Business travel,Eco Plus,794,4,1,1,1,4,4,4,4,5,5,5,2,4,4,0,0.0,satisfied +59735,82188,Female,Loyal Customer,58,Business travel,Business,1927,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,18.0,satisfied +59736,82757,Female,disloyal Customer,17,Business travel,Eco,409,4,3,4,4,3,4,3,3,4,2,3,4,3,3,87,78.0,neutral or dissatisfied +59737,19070,Male,disloyal Customer,24,Business travel,Eco,569,2,2,2,4,3,2,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +59738,112437,Female,disloyal Customer,29,Business travel,Eco,853,1,1,1,4,3,1,3,3,4,2,4,3,3,3,5,21.0,neutral or dissatisfied +59739,124863,Male,Loyal Customer,54,Business travel,Business,280,0,0,0,4,4,5,4,2,2,1,1,4,2,5,0,0.0,satisfied +59740,121527,Male,Loyal Customer,40,Business travel,Business,3870,2,2,2,2,4,4,5,3,3,3,3,3,3,4,48,41.0,satisfied +59741,118965,Female,Loyal Customer,41,Business travel,Business,570,5,5,5,5,2,4,4,5,5,5,5,3,5,4,4,13.0,satisfied +59742,4536,Female,Loyal Customer,49,Business travel,Business,3299,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +59743,71582,Male,disloyal Customer,23,Business travel,Eco,1197,4,5,5,1,4,5,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +59744,94107,Male,Loyal Customer,58,Personal Travel,Business,248,3,2,3,3,4,3,3,5,5,3,5,1,5,3,20,19.0,neutral or dissatisfied +59745,50620,Male,Loyal Customer,51,Personal Travel,Eco,134,0,1,0,4,5,0,5,5,1,5,3,1,3,5,2,12.0,satisfied +59746,55507,Male,Loyal Customer,41,Business travel,Business,3726,4,4,1,4,2,5,5,2,2,2,2,4,2,4,30,9.0,satisfied +59747,42608,Female,Loyal Customer,24,Business travel,Eco,481,0,5,0,2,4,0,4,4,3,1,4,4,3,4,21,85.0,satisfied +59748,17037,Female,Loyal Customer,48,Business travel,Business,2010,2,2,2,2,3,3,4,2,2,2,2,5,2,3,5,13.0,satisfied +59749,77433,Female,Loyal Customer,45,Personal Travel,Eco,590,2,4,2,4,4,4,4,5,5,2,1,4,5,5,25,27.0,neutral or dissatisfied +59750,55569,Female,Loyal Customer,60,Personal Travel,Eco,395,0,5,0,3,4,4,5,1,1,0,1,4,1,3,0,0.0,satisfied +59751,31606,Male,Loyal Customer,41,Personal Travel,Eco,602,2,4,2,3,4,2,4,4,4,3,5,4,4,4,29,72.0,neutral or dissatisfied +59752,80904,Female,Loyal Customer,34,Business travel,Business,341,0,0,0,2,4,4,5,5,5,3,3,4,5,3,1,5.0,satisfied +59753,28615,Male,disloyal Customer,29,Business travel,Eco,1180,3,3,3,3,4,3,4,4,1,2,4,4,5,4,0,0.0,neutral or dissatisfied +59754,121717,Female,Loyal Customer,21,Personal Travel,Eco,683,4,5,3,2,3,3,3,3,4,2,4,4,5,3,0,0.0,satisfied +59755,80241,Male,Loyal Customer,50,Business travel,Business,1269,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +59756,81821,Male,disloyal Customer,25,Business travel,Eco,1416,3,2,2,4,1,3,1,1,2,5,4,4,3,1,86,96.0,neutral or dissatisfied +59757,124554,Female,Loyal Customer,15,Personal Travel,Eco Plus,1276,3,4,3,2,2,3,2,2,3,5,3,5,4,2,0,7.0,neutral or dissatisfied +59758,48207,Male,Loyal Customer,39,Business travel,Eco,236,3,2,4,2,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +59759,1746,Female,Loyal Customer,39,Personal Travel,Eco,364,4,3,4,4,1,4,1,1,4,3,2,4,3,1,93,97.0,neutral or dissatisfied +59760,113285,Male,Loyal Customer,57,Business travel,Business,1853,3,3,3,3,4,4,5,4,4,4,5,3,4,4,2,0.0,satisfied +59761,6180,Female,Loyal Customer,30,Personal Travel,Eco,501,3,4,3,3,1,3,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +59762,88330,Male,Loyal Customer,39,Business travel,Business,515,3,3,3,3,5,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +59763,9807,Female,Loyal Customer,40,Business travel,Business,1832,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +59764,24795,Female,Loyal Customer,31,Personal Travel,Eco,432,5,5,5,4,2,5,2,2,3,3,5,2,1,2,0,0.0,satisfied +59765,28062,Male,Loyal Customer,36,Business travel,Business,2631,4,4,4,4,5,5,5,1,1,4,5,5,1,5,0,30.0,satisfied +59766,69453,Female,Loyal Customer,44,Personal Travel,Eco,1089,2,3,2,1,4,5,4,2,2,2,2,4,2,4,21,0.0,neutral or dissatisfied +59767,95963,Female,Loyal Customer,55,Business travel,Business,3252,3,3,3,3,2,4,5,5,5,4,5,5,5,4,12,0.0,satisfied +59768,12965,Male,Loyal Customer,54,Personal Travel,Eco Plus,563,4,5,4,4,5,4,5,5,3,2,5,5,4,5,1,0.0,neutral or dissatisfied +59769,114455,Male,Loyal Customer,44,Business travel,Business,3551,4,4,4,4,5,5,4,5,5,5,5,3,5,4,19,9.0,satisfied +59770,6617,Female,Loyal Customer,64,Personal Travel,Eco Plus,473,3,3,1,3,3,1,3,3,3,1,3,4,3,5,7,0.0,neutral or dissatisfied +59771,54355,Male,Loyal Customer,43,Business travel,Eco,1235,5,4,4,4,5,5,5,5,4,3,3,4,5,5,0,0.0,satisfied +59772,6832,Female,Loyal Customer,22,Personal Travel,Eco,122,2,4,0,4,3,0,3,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +59773,13778,Female,Loyal Customer,47,Business travel,Eco,925,4,3,3,3,1,4,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +59774,25868,Female,Loyal Customer,38,Business travel,Eco Plus,484,4,1,1,1,4,3,4,4,3,2,3,1,2,4,32,27.0,neutral or dissatisfied +59775,20161,Female,disloyal Customer,39,Business travel,Business,258,4,4,4,3,5,4,5,5,4,5,3,3,5,5,0,0.0,satisfied +59776,65864,Female,Loyal Customer,61,Personal Travel,Eco,1389,1,5,0,3,2,4,4,3,3,0,3,4,3,4,0,0.0,neutral or dissatisfied +59777,59616,Female,disloyal Customer,38,Business travel,Eco,854,3,3,3,4,3,3,5,3,2,4,3,4,3,3,11,7.0,neutral or dissatisfied +59778,55987,Female,Loyal Customer,43,Business travel,Business,2586,5,5,5,5,5,5,5,5,2,5,5,5,4,5,15,33.0,satisfied +59779,117271,Male,Loyal Customer,7,Personal Travel,Eco,621,1,4,1,4,2,1,2,2,2,2,1,3,5,2,0,0.0,neutral or dissatisfied +59780,11677,Male,Loyal Customer,46,Business travel,Business,2182,0,4,0,2,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +59781,84793,Female,Loyal Customer,56,Business travel,Business,1999,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +59782,54269,Male,Loyal Customer,41,Personal Travel,Eco,1222,1,0,1,4,2,1,2,2,2,3,5,2,4,2,0,0.0,neutral or dissatisfied +59783,96287,Female,Loyal Customer,23,Personal Travel,Eco,546,3,1,3,3,5,3,5,5,3,2,4,1,3,5,8,13.0,neutral or dissatisfied +59784,103630,Male,Loyal Customer,45,Business travel,Business,1946,2,2,2,2,4,5,5,5,5,5,5,4,5,5,28,29.0,satisfied +59785,10313,Female,Loyal Customer,40,Business travel,Business,2306,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +59786,5410,Female,Loyal Customer,57,Personal Travel,Eco,785,4,4,4,3,4,5,4,4,4,4,4,5,4,4,0,7.0,neutral or dissatisfied +59787,102618,Female,Loyal Customer,18,Personal Travel,Eco,1294,1,4,1,2,1,1,1,1,5,5,3,3,5,1,9,21.0,neutral or dissatisfied +59788,32600,Female,Loyal Customer,68,Business travel,Business,3844,1,5,5,5,4,4,4,3,3,3,1,3,3,2,0,0.0,neutral or dissatisfied +59789,93018,Male,Loyal Customer,50,Business travel,Business,1124,3,1,1,1,3,2,2,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +59790,100814,Female,disloyal Customer,24,Business travel,Eco,1167,2,2,2,2,2,2,2,2,4,5,4,3,2,2,0,0.0,neutral or dissatisfied +59791,10479,Male,Loyal Customer,36,Business travel,Business,3163,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +59792,52011,Male,disloyal Customer,41,Business travel,Eco,328,1,5,1,3,3,1,3,3,4,3,5,2,4,3,0,0.0,neutral or dissatisfied +59793,17873,Male,Loyal Customer,37,Business travel,Business,2684,1,0,0,2,3,3,2,3,3,0,5,1,3,3,0,6.0,neutral or dissatisfied +59794,97304,Male,disloyal Customer,23,Business travel,Eco,843,3,3,3,4,3,4,4,5,5,5,5,4,3,4,134,120.0,neutral or dissatisfied +59795,21615,Female,Loyal Customer,45,Business travel,Business,794,1,1,1,1,3,2,2,2,2,2,2,1,2,4,8,2.0,satisfied +59796,97148,Male,Loyal Customer,38,Business travel,Business,3144,1,2,2,2,5,4,4,1,1,1,1,3,1,3,0,2.0,neutral or dissatisfied +59797,98318,Female,Loyal Customer,32,Business travel,Business,1547,4,1,1,1,4,4,4,4,4,3,3,3,2,4,4,13.0,neutral or dissatisfied +59798,36128,Male,disloyal Customer,23,Business travel,Eco,1562,1,1,1,3,5,1,5,5,2,2,2,3,1,5,14,0.0,neutral or dissatisfied +59799,12416,Male,Loyal Customer,68,Personal Travel,Eco,190,3,3,0,4,1,0,1,1,4,3,4,2,3,1,20,30.0,neutral or dissatisfied +59800,20261,Female,disloyal Customer,36,Business travel,Eco,228,3,0,3,2,3,3,3,3,2,3,4,5,1,3,0,0.0,neutral or dissatisfied +59801,3574,Male,Loyal Customer,40,Personal Travel,Eco,227,3,2,3,3,5,3,5,5,2,5,4,1,4,5,1,15.0,neutral or dissatisfied +59802,73713,Female,Loyal Customer,42,Business travel,Business,2927,2,2,2,2,4,2,5,4,4,4,4,2,4,2,1,0.0,satisfied +59803,1556,Female,Loyal Customer,64,Business travel,Business,987,5,3,3,3,4,3,3,5,5,4,5,3,5,1,2,7.0,neutral or dissatisfied +59804,104510,Male,Loyal Customer,41,Business travel,Business,1609,4,4,4,4,2,5,5,5,5,5,5,5,5,5,11,0.0,satisfied +59805,129420,Male,disloyal Customer,26,Business travel,Business,236,3,4,3,3,1,3,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +59806,3031,Female,disloyal Customer,27,Business travel,Business,862,3,2,2,3,2,2,4,2,3,5,5,5,5,2,8,11.0,neutral or dissatisfied +59807,1463,Male,Loyal Customer,34,Business travel,Business,772,4,4,4,4,1,3,5,5,5,5,5,4,5,4,0,3.0,satisfied +59808,69282,Female,Loyal Customer,59,Personal Travel,Eco,733,1,5,1,3,3,3,5,2,2,1,2,4,2,3,0,9.0,neutral or dissatisfied +59809,6371,Male,disloyal Customer,58,Business travel,Eco,296,2,1,2,3,1,2,1,1,4,4,3,2,3,1,43,46.0,neutral or dissatisfied +59810,112694,Male,disloyal Customer,26,Business travel,Eco,605,2,3,2,4,5,2,5,5,4,5,3,3,4,5,3,0.0,neutral or dissatisfied +59811,32615,Female,disloyal Customer,30,Business travel,Eco,101,3,1,3,3,4,3,4,4,1,3,4,2,4,4,0,2.0,neutral or dissatisfied +59812,57850,Male,Loyal Customer,38,Business travel,Business,2457,1,1,2,1,3,3,3,4,4,3,4,3,4,3,0,0.0,satisfied +59813,9446,Male,Loyal Customer,38,Business travel,Eco,288,2,2,2,2,2,2,2,2,2,1,4,1,4,2,7,0.0,neutral or dissatisfied +59814,67714,Female,Loyal Customer,63,Business travel,Business,1235,3,5,5,5,3,4,3,3,3,3,3,3,3,4,39,24.0,neutral or dissatisfied +59815,81043,Female,Loyal Customer,50,Business travel,Eco,1399,1,2,2,2,4,3,4,1,1,1,1,1,1,4,0,5.0,neutral or dissatisfied +59816,84552,Female,Loyal Customer,16,Personal Travel,Eco,2486,2,1,1,3,4,1,5,4,1,1,1,2,3,4,2,4.0,neutral or dissatisfied +59817,91629,Male,Loyal Customer,44,Business travel,Business,2216,4,4,4,4,2,4,5,4,4,4,4,5,4,3,1,0.0,satisfied +59818,93372,Female,Loyal Customer,65,Personal Travel,Eco,1024,2,1,2,2,3,2,1,3,3,2,3,1,3,1,8,0.0,neutral or dissatisfied +59819,115881,Female,Loyal Customer,62,Business travel,Business,3855,5,5,5,5,1,4,3,5,5,5,5,1,5,5,0,0.0,satisfied +59820,5525,Female,disloyal Customer,19,Business travel,Eco,431,2,1,2,4,2,4,5,1,3,4,4,5,3,5,103,242.0,neutral or dissatisfied +59821,36850,Male,Loyal Customer,44,Business travel,Eco Plus,369,3,3,3,3,3,3,3,3,1,2,3,2,4,3,7,0.0,neutral or dissatisfied +59822,83458,Female,disloyal Customer,27,Business travel,Eco,946,3,3,3,3,4,3,3,4,4,3,3,2,4,4,9,1.0,neutral or dissatisfied +59823,83607,Female,Loyal Customer,40,Business travel,Business,2089,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +59824,54957,Male,Loyal Customer,44,Business travel,Business,1346,1,1,1,1,5,5,5,4,4,4,4,3,4,4,3,0.0,satisfied +59825,82198,Female,Loyal Customer,44,Personal Travel,Eco,1927,4,5,4,3,4,4,5,2,2,4,2,5,2,3,0,0.0,satisfied +59826,69000,Male,disloyal Customer,23,Business travel,Business,1389,4,5,3,3,5,3,5,5,4,2,5,5,5,5,0,0.0,satisfied +59827,111195,Male,Loyal Customer,45,Business travel,Business,1506,4,4,4,4,3,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +59828,108361,Male,Loyal Customer,46,Business travel,Eco,344,4,4,4,4,4,4,4,4,3,4,4,4,4,4,75,65.0,satisfied +59829,43536,Female,disloyal Customer,18,Business travel,Eco,643,2,0,2,3,1,2,1,1,5,3,1,3,4,1,53,46.0,neutral or dissatisfied +59830,10399,Female,disloyal Customer,32,Business travel,Business,667,1,1,1,3,4,1,4,4,4,2,4,5,4,4,2,0.0,neutral or dissatisfied +59831,105087,Male,Loyal Customer,37,Business travel,Business,3984,4,4,4,4,2,5,5,4,4,4,5,3,4,3,14,1.0,satisfied +59832,70798,Male,Loyal Customer,60,Personal Travel,Eco,328,1,3,4,5,4,4,5,4,2,4,1,3,5,4,0,5.0,neutral or dissatisfied +59833,113105,Female,Loyal Customer,57,Personal Travel,Eco,543,1,0,1,3,5,5,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +59834,126074,Male,Loyal Customer,41,Business travel,Business,1949,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +59835,98181,Male,disloyal Customer,20,Business travel,Business,327,4,0,4,2,3,4,3,3,3,5,5,5,5,3,16,6.0,satisfied +59836,49019,Male,Loyal Customer,41,Business travel,Business,308,3,3,3,3,1,3,2,5,5,5,5,2,5,1,0,0.0,satisfied +59837,75327,Male,Loyal Customer,57,Business travel,Business,2504,4,4,4,4,3,3,3,4,4,3,4,3,4,3,0,5.0,satisfied +59838,25071,Male,Loyal Customer,50,Business travel,Business,3309,2,2,2,2,3,4,4,5,5,5,5,4,5,5,35,33.0,satisfied +59839,40866,Male,Loyal Customer,68,Personal Travel,Eco,590,3,3,3,3,5,3,4,5,3,4,3,3,2,5,20,10.0,neutral or dissatisfied +59840,30627,Female,Loyal Customer,44,Personal Travel,Business,770,3,4,3,3,2,4,4,2,2,3,2,4,2,5,8,71.0,neutral or dissatisfied +59841,126774,Female,Loyal Customer,30,Business travel,Eco Plus,2402,2,1,1,1,2,2,2,2,1,1,3,3,4,2,3,0.0,neutral or dissatisfied +59842,23386,Male,Loyal Customer,41,Business travel,Business,2223,4,4,4,4,1,2,4,5,5,5,5,5,5,1,9,4.0,satisfied +59843,58774,Male,Loyal Customer,44,Business travel,Eco,1012,1,2,1,2,1,1,1,2,4,2,3,1,1,1,256,257.0,neutral or dissatisfied +59844,5114,Male,Loyal Customer,10,Personal Travel,Eco,224,3,4,0,2,3,0,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +59845,47171,Female,Loyal Customer,28,Business travel,Business,954,1,3,3,3,1,1,1,1,2,2,3,2,3,1,52,56.0,neutral or dissatisfied +59846,61094,Female,Loyal Customer,65,Personal Travel,Eco,1703,3,2,4,4,2,3,3,1,1,4,1,4,1,4,1,11.0,neutral or dissatisfied +59847,24315,Male,Loyal Customer,50,Business travel,Business,1048,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +59848,32916,Male,Loyal Customer,45,Personal Travel,Eco,163,2,5,2,1,3,2,3,3,1,1,4,5,4,3,0,0.0,neutral or dissatisfied +59849,23436,Male,Loyal Customer,52,Business travel,Business,516,2,1,2,2,1,2,3,2,2,2,2,4,2,4,104,94.0,satisfied +59850,90972,Female,disloyal Customer,22,Business travel,Business,545,0,0,0,3,4,0,4,4,2,1,4,1,5,4,1,4.0,satisfied +59851,64741,Female,disloyal Customer,26,Business travel,Business,282,5,0,5,3,1,5,1,1,3,2,5,4,4,1,0,0.0,satisfied +59852,17921,Male,disloyal Customer,34,Personal Travel,Eco,789,2,5,2,2,5,2,1,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +59853,73208,Male,Loyal Customer,11,Personal Travel,Eco,1258,2,1,2,3,4,2,4,4,3,5,1,1,3,4,17,20.0,neutral or dissatisfied +59854,12089,Female,disloyal Customer,24,Business travel,Eco,1034,4,4,4,4,4,4,4,4,3,2,5,3,4,4,7,0.0,satisfied +59855,29703,Male,Loyal Customer,16,Personal Travel,Eco,1542,2,4,2,1,1,2,1,1,4,3,3,3,5,1,0,0.0,neutral or dissatisfied +59856,125901,Female,Loyal Customer,9,Personal Travel,Eco,1013,4,5,4,5,4,4,4,4,5,4,1,4,2,4,12,68.0,neutral or dissatisfied +59857,12695,Male,Loyal Customer,40,Business travel,Eco,689,5,1,1,1,5,5,5,5,2,4,2,1,2,5,0,7.0,satisfied +59858,35800,Female,Loyal Customer,52,Personal Travel,Eco Plus,200,4,4,0,4,5,5,3,4,4,0,5,3,4,5,0,0.0,neutral or dissatisfied +59859,22844,Female,Loyal Customer,43,Personal Travel,Eco,302,1,5,1,4,2,4,4,1,1,1,5,3,1,5,0,9.0,neutral or dissatisfied +59860,8690,Female,Loyal Customer,52,Business travel,Business,3386,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,4.0,satisfied +59861,40766,Male,disloyal Customer,21,Business travel,Eco,588,2,0,2,4,2,2,2,2,2,3,4,5,1,2,2,0.0,neutral or dissatisfied +59862,7061,Female,Loyal Customer,74,Business travel,Business,3256,3,3,3,3,2,5,4,5,5,5,5,5,5,5,75,131.0,satisfied +59863,110638,Male,Loyal Customer,60,Business travel,Business,945,1,4,4,4,2,3,4,1,1,1,1,4,1,2,7,16.0,neutral or dissatisfied +59864,66240,Female,Loyal Customer,45,Business travel,Eco,150,4,5,5,5,5,3,1,4,4,4,4,2,4,1,0,0.0,satisfied +59865,69716,Male,Loyal Customer,52,Business travel,Business,972,1,1,1,1,2,4,5,4,4,4,4,5,4,2,0,5.0,satisfied +59866,3161,Male,Loyal Customer,23,Business travel,Business,3392,2,2,5,2,2,3,2,2,1,1,3,4,4,2,0,30.0,neutral or dissatisfied +59867,59345,Male,Loyal Customer,60,Business travel,Business,2615,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +59868,29081,Male,Loyal Customer,70,Personal Travel,Eco,954,3,4,3,4,5,3,5,5,2,1,4,2,4,5,15,26.0,neutral or dissatisfied +59869,8369,Male,disloyal Customer,48,Business travel,Eco,773,1,1,1,3,2,1,4,2,3,2,4,4,3,2,0,0.0,neutral or dissatisfied +59870,57144,Male,Loyal Customer,27,Business travel,Eco Plus,1222,2,5,5,5,2,2,2,2,2,3,3,1,3,2,4,0.0,neutral or dissatisfied +59871,42656,Female,Loyal Customer,49,Personal Travel,Eco Plus,546,3,1,2,3,3,4,3,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +59872,29504,Male,Loyal Customer,11,Personal Travel,Eco,1107,3,2,3,3,3,3,3,3,1,4,3,1,2,3,0,0.0,neutral or dissatisfied +59873,49716,Female,Loyal Customer,23,Business travel,Business,2222,1,2,5,2,4,4,1,4,1,1,3,3,3,4,7,12.0,neutral or dissatisfied +59874,105546,Male,Loyal Customer,48,Personal Travel,Eco,611,1,2,0,3,4,0,3,4,4,2,2,4,3,4,0,0.0,neutral or dissatisfied +59875,112824,Female,Loyal Customer,56,Business travel,Business,1313,2,2,2,2,3,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +59876,6992,Female,disloyal Customer,23,Business travel,Eco,147,5,4,5,2,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +59877,31428,Female,Loyal Customer,51,Personal Travel,Eco,1546,2,5,2,1,3,4,4,3,3,2,3,3,3,4,3,0.0,neutral or dissatisfied +59878,89635,Male,Loyal Customer,43,Business travel,Business,950,3,3,3,3,2,5,5,4,4,4,4,3,4,4,121,131.0,satisfied +59879,27945,Female,Loyal Customer,55,Business travel,Eco,1660,1,3,3,3,1,2,4,1,1,1,1,2,1,2,13,55.0,neutral or dissatisfied +59880,39205,Female,disloyal Customer,25,Business travel,Business,67,1,0,1,5,3,1,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +59881,105724,Male,Loyal Customer,47,Business travel,Eco,663,3,2,2,2,3,3,3,3,1,3,3,4,3,3,9,21.0,neutral or dissatisfied +59882,58655,Female,Loyal Customer,51,Personal Travel,Eco,867,3,5,4,4,5,5,1,1,1,4,1,4,1,4,32,88.0,neutral or dissatisfied +59883,101997,Male,Loyal Customer,17,Personal Travel,Eco,628,3,5,3,3,1,3,2,1,3,4,4,4,4,1,64,62.0,neutral or dissatisfied +59884,66173,Male,disloyal Customer,45,Business travel,Eco,460,1,3,1,2,3,1,3,3,1,3,3,2,3,3,0,12.0,neutral or dissatisfied +59885,15108,Male,Loyal Customer,66,Business travel,Eco Plus,239,4,4,4,4,4,4,4,4,1,1,2,4,3,4,0,0.0,satisfied +59886,6211,Female,disloyal Customer,62,Business travel,Business,462,1,1,1,2,1,1,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +59887,112314,Male,Loyal Customer,54,Business travel,Business,3248,3,3,2,3,3,4,4,5,5,5,5,5,5,4,17,7.0,satisfied +59888,66754,Female,Loyal Customer,44,Personal Travel,Eco,802,3,1,3,3,3,4,4,5,5,3,2,2,5,4,0,0.0,neutral or dissatisfied +59889,42215,Male,Loyal Customer,46,Business travel,Business,2698,3,3,3,3,4,3,3,3,3,3,3,4,3,3,0,21.0,neutral or dissatisfied +59890,68312,Male,Loyal Customer,42,Business travel,Business,2165,1,1,4,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +59891,58480,Female,Loyal Customer,41,Business travel,Business,3574,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +59892,115841,Male,Loyal Customer,41,Business travel,Eco,337,3,1,1,1,3,3,3,3,1,4,3,4,4,3,85,86.0,neutral or dissatisfied +59893,812,Female,disloyal Customer,22,Business travel,Business,229,2,3,2,3,2,2,2,2,1,4,3,4,3,2,37,37.0,neutral or dissatisfied +59894,62936,Male,disloyal Customer,35,Business travel,Business,909,3,3,3,4,5,3,5,5,3,2,4,4,4,5,0,8.0,neutral or dissatisfied +59895,43165,Male,Loyal Customer,28,Personal Travel,Eco,840,1,5,1,4,2,1,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +59896,443,Male,Loyal Customer,35,Personal Travel,Business,247,1,4,0,2,4,4,4,3,3,0,3,5,3,5,0,0.0,neutral or dissatisfied +59897,3805,Male,Loyal Customer,49,Business travel,Business,650,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +59898,982,Female,Loyal Customer,30,Business travel,Business,2129,3,3,3,3,4,4,4,4,3,2,1,1,4,4,0,0.0,satisfied +59899,26658,Female,Loyal Customer,64,Business travel,Eco,115,1,4,4,4,3,4,3,1,1,1,1,3,1,4,65,61.0,neutral or dissatisfied +59900,54944,Male,Loyal Customer,58,Business travel,Business,1608,1,1,1,1,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +59901,123281,Male,Loyal Customer,25,Personal Travel,Eco,631,2,5,2,1,2,2,4,2,2,4,5,1,4,2,0,0.0,neutral or dissatisfied +59902,79874,Female,Loyal Customer,45,Business travel,Business,1890,3,3,4,3,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +59903,110789,Male,disloyal Customer,39,Business travel,Eco,597,2,0,2,1,2,2,2,2,1,3,5,2,5,2,9,5.0,neutral or dissatisfied +59904,58944,Female,Loyal Customer,49,Business travel,Business,888,5,5,5,5,5,5,5,5,5,5,5,3,5,5,5,0.0,satisfied +59905,98769,Female,Loyal Customer,60,Personal Travel,Eco,2075,2,5,2,3,3,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +59906,101851,Male,Loyal Customer,56,Business travel,Business,2662,4,4,4,4,2,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +59907,80453,Male,Loyal Customer,54,Business travel,Business,1299,4,4,5,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +59908,40763,Male,Loyal Customer,33,Business travel,Eco,590,0,0,0,1,3,0,3,3,1,1,3,3,1,3,73,55.0,satisfied +59909,63120,Male,Loyal Customer,55,Business travel,Business,447,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +59910,8800,Male,Loyal Customer,60,Business travel,Business,2823,1,1,1,1,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +59911,126154,Female,Loyal Customer,52,Business travel,Business,507,4,4,4,4,4,5,4,4,4,4,4,5,4,3,0,5.0,satisfied +59912,115986,Female,Loyal Customer,66,Personal Travel,Eco,337,2,4,2,3,3,4,4,4,4,2,3,4,4,5,76,72.0,neutral or dissatisfied +59913,11043,Female,Loyal Customer,43,Personal Travel,Eco,247,0,5,0,4,5,4,4,1,1,0,5,3,1,3,0,12.0,satisfied +59914,104895,Male,Loyal Customer,31,Business travel,Business,1565,1,1,1,1,5,5,5,5,3,3,5,4,5,5,7,17.0,satisfied +59915,104143,Male,Loyal Customer,39,Personal Travel,Eco,393,4,5,4,3,2,4,5,2,4,4,4,5,2,2,0,0.0,neutral or dissatisfied +59916,69357,Male,disloyal Customer,25,Business travel,Eco,1035,3,3,3,5,5,3,5,5,3,3,5,3,4,5,56,109.0,neutral or dissatisfied +59917,38153,Male,Loyal Customer,39,Personal Travel,Eco,1010,3,4,3,3,5,3,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +59918,85144,Female,disloyal Customer,28,Business travel,Eco,731,1,1,1,4,3,1,3,3,4,5,3,2,4,3,83,95.0,neutral or dissatisfied +59919,113107,Male,Loyal Customer,7,Personal Travel,Eco,479,2,3,2,4,2,2,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +59920,91697,Female,Loyal Customer,32,Business travel,Business,590,2,2,2,2,5,5,5,5,5,3,5,4,5,5,11,6.0,satisfied +59921,120790,Female,Loyal Customer,70,Personal Travel,Eco,678,2,4,2,1,5,5,5,3,3,2,3,3,3,4,0,1.0,neutral or dissatisfied +59922,113720,Female,Loyal Customer,55,Personal Travel,Eco,397,2,2,2,3,5,4,3,1,1,2,1,3,1,2,24,13.0,neutral or dissatisfied +59923,7005,Male,disloyal Customer,16,Business travel,Eco,234,4,3,4,3,2,4,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +59924,117871,Female,Loyal Customer,60,Business travel,Business,1933,2,2,2,2,3,5,4,3,3,3,3,5,3,4,85,80.0,satisfied +59925,113367,Female,Loyal Customer,49,Business travel,Business,414,1,1,3,1,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +59926,19538,Male,Loyal Customer,33,Business travel,Eco,108,5,2,2,2,5,5,5,5,3,1,4,1,2,5,0,17.0,satisfied +59927,110079,Female,Loyal Customer,16,Personal Travel,Business,1072,4,5,4,3,2,4,2,2,5,4,4,5,4,2,31,25.0,neutral or dissatisfied +59928,18478,Female,Loyal Customer,29,Business travel,Eco,201,5,1,1,1,5,5,5,5,2,2,4,5,5,5,0,0.0,satisfied +59929,40345,Male,disloyal Customer,25,Business travel,Eco,920,2,2,2,3,4,2,4,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +59930,21141,Female,Loyal Customer,56,Business travel,Eco Plus,106,1,2,2,2,2,4,3,1,1,1,1,2,1,1,7,0.0,neutral or dissatisfied +59931,23884,Male,Loyal Customer,23,Business travel,Eco,589,1,1,1,1,1,1,1,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +59932,76582,Female,Loyal Customer,49,Business travel,Business,2380,1,3,2,3,3,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +59933,63780,Female,Loyal Customer,34,Business travel,Business,1721,1,1,1,1,2,4,4,1,1,1,1,2,1,1,33,4.0,neutral or dissatisfied +59934,107254,Female,disloyal Customer,21,Business travel,Business,283,4,1,4,5,3,4,1,3,4,3,5,4,5,3,1,0.0,satisfied +59935,114837,Male,Loyal Customer,32,Business travel,Business,2353,2,2,2,2,4,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +59936,53248,Female,Loyal Customer,71,Business travel,Eco Plus,612,4,2,2,2,1,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +59937,109190,Male,disloyal Customer,19,Business travel,Eco,483,3,4,3,3,5,3,5,5,1,2,4,2,4,5,0,0.0,neutral or dissatisfied +59938,21023,Male,Loyal Customer,35,Business travel,Eco,152,5,5,5,5,5,5,5,5,5,4,5,2,4,5,41,38.0,satisfied +59939,28040,Female,Loyal Customer,37,Business travel,Eco,1037,3,5,5,5,3,3,3,3,1,5,4,2,3,3,0,11.0,neutral or dissatisfied +59940,101593,Male,Loyal Customer,40,Business travel,Business,1371,5,5,5,5,4,4,4,5,5,5,5,5,5,5,26,13.0,satisfied +59941,96361,Female,Loyal Customer,47,Business travel,Business,1246,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +59942,57761,Female,disloyal Customer,35,Business travel,Business,2704,2,2,2,4,2,3,4,3,4,5,4,4,4,4,0,12.0,neutral or dissatisfied +59943,95842,Male,Loyal Customer,45,Business travel,Business,1675,2,2,2,2,4,4,4,5,5,5,5,4,5,3,5,0.0,satisfied +59944,93666,Female,Loyal Customer,53,Business travel,Business,542,1,1,2,1,4,5,4,5,5,5,5,3,5,3,15,31.0,satisfied +59945,106959,Male,Loyal Customer,53,Business travel,Business,937,2,2,2,2,4,4,4,4,4,4,4,3,4,3,3,10.0,satisfied +59946,62699,Female,Loyal Customer,40,Business travel,Business,2504,4,4,4,4,4,4,4,4,5,5,4,4,3,4,429,417.0,satisfied +59947,39123,Male,Loyal Customer,36,Business travel,Business,190,4,5,4,4,4,1,4,4,4,4,4,3,4,4,0,0.0,satisfied +59948,14282,Female,Loyal Customer,45,Business travel,Business,429,4,4,4,4,5,5,4,3,3,3,3,2,3,2,0,0.0,satisfied +59949,35354,Female,disloyal Customer,24,Business travel,Eco,1056,4,4,4,3,4,4,4,4,3,1,2,3,4,4,0,0.0,satisfied +59950,6958,Male,Loyal Customer,17,Business travel,Eco Plus,501,2,3,3,3,2,2,1,2,4,1,3,4,3,2,0,10.0,neutral or dissatisfied +59951,94248,Female,disloyal Customer,54,Business travel,Business,189,3,3,3,1,2,3,2,2,4,5,4,5,4,2,84,73.0,neutral or dissatisfied +59952,60767,Female,disloyal Customer,24,Business travel,Business,804,0,0,0,3,5,0,5,5,5,5,4,4,5,5,3,0.0,satisfied +59953,20567,Male,Loyal Customer,62,Business travel,Business,633,1,2,2,2,4,1,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +59954,48937,Male,Loyal Customer,55,Business travel,Eco,109,5,5,5,5,5,5,5,5,1,5,3,4,3,5,0,0.0,satisfied +59955,86371,Female,Loyal Customer,52,Business travel,Business,2995,5,4,5,5,3,4,5,4,4,4,4,4,4,5,14,18.0,satisfied +59956,20741,Female,Loyal Customer,37,Business travel,Business,3987,4,1,4,1,5,4,3,4,4,4,4,2,4,2,0,3.0,neutral or dissatisfied +59957,124074,Female,Loyal Customer,53,Personal Travel,Eco Plus,2153,3,4,3,3,4,3,4,4,4,3,4,5,4,5,0,6.0,neutral or dissatisfied +59958,59696,Male,Loyal Customer,48,Personal Travel,Eco,854,4,4,4,4,2,4,4,2,4,4,5,4,4,2,22,31.0,neutral or dissatisfied +59959,66491,Female,Loyal Customer,34,Business travel,Business,3768,3,3,4,4,4,3,3,3,3,3,3,3,3,1,26,20.0,neutral or dissatisfied +59960,65476,Male,Loyal Customer,57,Business travel,Business,3109,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +59961,6578,Male,Loyal Customer,30,Business travel,Business,3092,3,2,2,2,3,3,3,3,1,1,1,1,2,3,14,14.0,neutral or dissatisfied +59962,72011,Female,Loyal Customer,67,Personal Travel,Eco Plus,1437,3,2,3,3,4,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +59963,45241,Female,Loyal Customer,59,Personal Travel,Eco,1013,3,4,3,5,3,3,5,4,4,3,1,1,4,4,6,61.0,neutral or dissatisfied +59964,55431,Female,Loyal Customer,34,Business travel,Business,2521,4,4,4,4,4,4,4,4,5,5,4,4,5,4,52,48.0,satisfied +59965,41003,Male,Loyal Customer,19,Personal Travel,Eco,1362,4,4,5,3,1,5,1,1,3,5,4,3,5,1,28,21.0,neutral or dissatisfied +59966,112905,Female,Loyal Customer,27,Business travel,Business,2093,4,3,3,3,4,4,4,4,1,2,4,1,3,4,13,4.0,neutral or dissatisfied +59967,108816,Male,Loyal Customer,63,Business travel,Eco Plus,115,4,1,1,1,4,4,4,4,4,4,4,4,4,4,0,2.0,satisfied +59968,101797,Male,Loyal Customer,36,Business travel,Business,1521,4,4,5,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +59969,15225,Male,disloyal Customer,22,Business travel,Eco,529,4,1,4,2,5,4,5,5,5,2,3,1,5,5,31,7.0,satisfied +59970,119518,Female,disloyal Customer,22,Business travel,Eco,814,4,4,4,4,4,4,4,4,4,4,4,2,4,4,47,39.0,neutral or dissatisfied +59971,28941,Female,disloyal Customer,45,Business travel,Eco,987,1,1,1,1,5,1,5,5,1,3,5,2,5,5,0,0.0,neutral or dissatisfied +59972,42995,Male,Loyal Customer,53,Business travel,Business,1565,5,5,5,5,5,5,5,4,4,4,5,5,4,1,0,0.0,satisfied +59973,32043,Female,Loyal Customer,52,Business travel,Business,3389,4,4,4,4,4,2,4,4,4,4,3,4,4,4,5,20.0,satisfied +59974,34912,Male,Loyal Customer,44,Business travel,Business,3647,5,5,2,5,1,3,4,5,5,5,5,5,5,2,0,0.0,satisfied +59975,17863,Female,Loyal Customer,45,Business travel,Eco,371,5,5,5,5,5,5,5,3,5,3,4,5,1,5,133,120.0,satisfied +59976,115124,Male,Loyal Customer,52,Business travel,Business,2348,3,2,2,2,5,4,4,3,3,3,3,2,3,1,17,21.0,neutral or dissatisfied +59977,67809,Female,Loyal Customer,45,Business travel,Eco,913,1,3,3,3,3,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +59978,22074,Male,Loyal Customer,47,Personal Travel,Eco,321,3,3,3,2,4,3,4,4,3,5,2,3,2,4,0,0.0,neutral or dissatisfied +59979,30612,Male,Loyal Customer,46,Business travel,Eco Plus,472,4,3,3,3,4,4,4,4,1,4,2,5,2,4,0,0.0,satisfied +59980,17295,Female,Loyal Customer,46,Business travel,Business,403,5,5,5,5,1,4,5,4,4,4,4,1,4,3,0,0.0,satisfied +59981,77161,Male,Loyal Customer,53,Business travel,Business,1450,2,3,3,3,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +59982,123394,Female,Loyal Customer,30,Business travel,Business,1337,1,1,1,1,3,4,3,3,3,3,5,3,4,3,0,0.0,satisfied +59983,25365,Male,disloyal Customer,24,Business travel,Eco,591,0,5,0,4,2,0,2,2,3,4,5,4,2,2,0,0.0,satisfied +59984,30312,Female,Loyal Customer,24,Personal Travel,Eco,1476,3,4,3,2,4,3,4,4,4,5,2,5,2,4,0,0.0,neutral or dissatisfied +59985,116513,Female,Loyal Customer,56,Personal Travel,Eco,296,1,2,1,4,1,3,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +59986,96360,Male,Loyal Customer,58,Personal Travel,Eco Plus,1609,4,5,4,2,5,4,5,5,5,4,5,5,4,5,2,0.0,satisfied +59987,40974,Male,Loyal Customer,43,Personal Travel,Eco,507,2,1,2,4,5,2,5,5,1,5,4,1,4,5,0,5.0,neutral or dissatisfied +59988,114317,Female,Loyal Customer,52,Personal Travel,Eco,846,4,3,4,1,2,3,2,5,5,4,5,2,5,4,0,0.0,satisfied +59989,65243,Female,disloyal Customer,29,Business travel,Business,469,2,2,2,3,4,2,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +59990,68368,Male,disloyal Customer,28,Business travel,Business,1045,4,4,4,3,1,4,1,1,4,2,4,4,4,1,0,0.0,satisfied +59991,61420,Male,disloyal Customer,30,Business travel,Business,2358,3,3,3,3,3,3,3,3,1,1,4,3,3,3,0,0.0,neutral or dissatisfied +59992,73211,Male,Loyal Customer,14,Personal Travel,Eco,1258,1,4,1,3,4,1,4,4,5,5,4,3,4,4,0,10.0,neutral or dissatisfied +59993,123189,Female,Loyal Customer,9,Personal Travel,Eco,631,2,4,2,1,3,2,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +59994,78438,Male,disloyal Customer,25,Business travel,Business,526,1,0,1,4,5,1,5,5,4,5,5,4,5,5,0,16.0,neutral or dissatisfied +59995,70248,Male,Loyal Customer,45,Business travel,Eco,1592,1,5,2,5,1,1,1,1,2,5,2,4,3,1,0,0.0,neutral or dissatisfied +59996,58710,Male,Loyal Customer,26,Business travel,Business,2161,5,4,4,4,5,4,5,5,3,2,4,2,3,5,0,0.0,neutral or dissatisfied +59997,5295,Female,Loyal Customer,26,Personal Travel,Eco,293,2,1,2,4,2,2,2,2,4,5,3,4,3,2,11,18.0,neutral or dissatisfied +59998,103751,Male,Loyal Customer,17,Business travel,Eco Plus,405,5,5,5,5,5,5,4,5,4,3,1,3,3,5,0,0.0,satisfied +59999,24160,Female,Loyal Customer,39,Business travel,Business,1732,1,1,1,1,5,1,3,4,4,4,4,1,4,5,14,14.0,satisfied +60000,12666,Male,Loyal Customer,24,Business travel,Eco,689,5,1,1,1,5,4,5,5,4,3,5,4,4,5,3,0.0,satisfied +60001,127243,Male,Loyal Customer,49,Business travel,Business,2718,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,9.0,satisfied +60002,23458,Male,disloyal Customer,23,Business travel,Eco,576,3,4,3,3,4,3,2,4,3,2,3,1,5,4,0,0.0,neutral or dissatisfied +60003,34894,Female,Loyal Customer,39,Business travel,Eco,395,5,5,5,5,5,5,5,5,2,4,3,3,1,5,0,0.0,satisfied +60004,122144,Male,Loyal Customer,59,Business travel,Business,546,1,1,2,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +60005,127920,Male,Loyal Customer,52,Business travel,Business,2300,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +60006,14995,Female,Loyal Customer,71,Business travel,Business,1201,3,3,5,3,4,2,1,4,4,4,4,3,4,2,11,0.0,satisfied +60007,60368,Female,Loyal Customer,33,Business travel,Business,1476,5,5,3,5,4,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +60008,46587,Female,Loyal Customer,50,Business travel,Eco,212,5,5,5,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +60009,16219,Male,Loyal Customer,50,Business travel,Eco Plus,212,5,1,3,1,4,5,4,4,2,5,3,2,3,4,0,0.0,satisfied +60010,10406,Female,Loyal Customer,70,Business travel,Business,316,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +60011,93190,Female,Loyal Customer,24,Business travel,Business,3108,4,4,4,4,4,4,4,4,5,4,5,5,5,4,0,21.0,satisfied +60012,55950,Female,Loyal Customer,42,Business travel,Business,1620,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,16.0,satisfied +60013,120153,Male,Loyal Customer,24,Business travel,Business,2378,5,5,5,5,5,5,5,5,4,4,5,5,5,5,2,0.0,satisfied +60014,115158,Female,Loyal Customer,56,Business travel,Business,3122,1,1,1,1,3,5,5,2,2,2,2,4,2,4,2,3.0,satisfied +60015,104787,Female,Loyal Customer,31,Business travel,Business,587,3,3,3,3,3,3,3,3,4,5,5,3,5,3,102,,satisfied +60016,129785,Female,Loyal Customer,36,Personal Travel,Eco,337,1,1,5,4,3,5,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +60017,24020,Female,Loyal Customer,29,Business travel,Business,2616,1,5,5,5,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +60018,78872,Male,Loyal Customer,28,Personal Travel,Eco,1995,2,2,1,3,3,1,1,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +60019,50758,Female,Loyal Customer,63,Personal Travel,Eco,78,2,5,0,2,4,5,5,5,5,0,4,5,5,4,0,0.0,neutral or dissatisfied +60020,3571,Female,Loyal Customer,54,Personal Travel,Eco,227,3,4,3,3,3,4,4,3,3,3,3,5,3,5,0,6.0,neutral or dissatisfied +60021,25036,Male,Loyal Customer,70,Personal Travel,Eco,907,1,3,2,2,3,2,3,3,1,3,2,3,3,3,0,23.0,neutral or dissatisfied +60022,86112,Female,Loyal Customer,52,Business travel,Business,356,5,5,5,5,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +60023,108365,Male,Loyal Customer,21,Personal Travel,Eco,1855,2,1,2,3,3,2,5,3,1,2,4,3,3,3,70,60.0,neutral or dissatisfied +60024,59472,Female,Loyal Customer,33,Business travel,Business,758,4,4,4,4,5,5,5,5,5,5,5,4,5,5,11,0.0,satisfied +60025,154,Female,Loyal Customer,41,Business travel,Business,2731,4,4,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +60026,114661,Female,Loyal Customer,27,Business travel,Business,342,0,0,0,5,5,5,5,5,5,5,4,4,4,5,0,0.0,satisfied +60027,120987,Female,Loyal Customer,30,Business travel,Business,2684,2,4,4,4,2,2,2,2,3,3,3,4,3,2,2,3.0,neutral or dissatisfied +60028,37888,Female,Loyal Customer,59,Business travel,Business,937,1,3,3,3,5,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +60029,64849,Female,Loyal Customer,68,Business travel,Business,190,0,5,0,2,3,4,5,4,4,4,2,5,4,3,0,0.0,satisfied +60030,120747,Male,Loyal Customer,63,Personal Travel,Business,678,0,4,0,4,2,5,4,1,1,0,1,3,1,5,0,0.0,satisfied +60031,43804,Female,Loyal Customer,37,Business travel,Business,448,3,3,1,3,2,4,1,4,4,4,4,3,4,2,60,51.0,satisfied +60032,67515,Female,disloyal Customer,28,Business travel,Business,1235,5,5,5,3,2,5,2,2,4,4,5,5,4,2,0,0.0,satisfied +60033,68035,Female,Loyal Customer,41,Business travel,Business,2868,1,3,3,3,3,4,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +60034,55799,Male,Loyal Customer,50,Business travel,Business,1416,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,10.0,satisfied +60035,98548,Male,Loyal Customer,69,Personal Travel,Eco Plus,402,1,4,1,3,4,1,4,4,4,2,4,3,5,4,11,6.0,neutral or dissatisfied +60036,19979,Male,Loyal Customer,31,Business travel,Business,3553,3,2,4,2,3,3,3,3,1,5,3,1,4,3,33,16.0,neutral or dissatisfied +60037,32326,Female,Loyal Customer,49,Business travel,Business,101,1,4,4,4,3,4,3,2,2,2,1,1,2,3,11,14.0,neutral or dissatisfied +60038,58317,Female,Loyal Customer,72,Business travel,Eco,1739,4,4,4,4,3,1,3,4,4,4,4,2,4,3,25,15.0,neutral or dissatisfied +60039,90650,Female,disloyal Customer,25,Business travel,Business,581,3,0,3,2,4,3,3,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +60040,89690,Male,Loyal Customer,51,Business travel,Business,3925,2,5,5,5,3,1,1,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +60041,38137,Female,Loyal Customer,51,Personal Travel,Eco,1121,5,5,5,3,4,3,4,5,5,5,1,4,5,4,0,0.0,satisfied +60042,71954,Male,Loyal Customer,60,Business travel,Business,1440,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,4.0,satisfied +60043,123088,Female,disloyal Customer,27,Business travel,Business,590,2,2,2,2,3,2,3,3,4,4,4,4,5,3,15,0.0,neutral or dissatisfied +60044,18704,Female,Loyal Customer,33,Business travel,Eco Plus,127,2,4,4,4,2,2,2,2,1,4,3,2,4,2,75,58.0,neutral or dissatisfied +60045,13166,Female,disloyal Customer,43,Business travel,Eco Plus,162,4,3,3,2,2,4,2,2,4,2,1,2,1,2,80,75.0,neutral or dissatisfied +60046,106294,Female,Loyal Customer,58,Business travel,Business,3392,4,4,4,4,3,4,4,4,4,4,4,3,4,4,33,13.0,satisfied +60047,17372,Female,disloyal Customer,38,Business travel,Eco,637,3,3,2,1,1,2,1,1,3,1,2,3,4,1,17,21.0,neutral or dissatisfied +60048,111118,Male,disloyal Customer,22,Business travel,Business,1111,5,3,5,4,1,5,1,1,5,3,5,5,5,1,86,84.0,satisfied +60049,29921,Male,Loyal Customer,27,Business travel,Business,399,3,5,5,5,3,3,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +60050,103965,Female,Loyal Customer,41,Personal Travel,Eco,533,2,5,2,4,5,2,4,5,5,4,4,4,4,5,4,0.0,neutral or dissatisfied +60051,54559,Female,Loyal Customer,22,Personal Travel,Eco,925,4,5,4,3,2,4,3,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +60052,103570,Female,Loyal Customer,59,Business travel,Eco,604,3,3,3,3,2,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +60053,88623,Male,Loyal Customer,53,Personal Travel,Eco,515,3,4,3,4,5,3,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +60054,79578,Female,Loyal Customer,60,Business travel,Business,760,3,3,4,3,2,4,4,4,4,4,4,3,4,3,0,4.0,satisfied +60055,18898,Female,disloyal Customer,30,Business travel,Eco,100,3,3,3,3,2,3,2,2,2,5,3,1,2,2,0,0.0,neutral or dissatisfied +60056,16675,Female,Loyal Customer,32,Personal Travel,Eco,488,3,1,2,3,5,2,5,5,3,3,2,2,4,5,0,0.0,neutral or dissatisfied +60057,28054,Female,Loyal Customer,47,Business travel,Business,2193,3,4,4,4,3,3,3,1,2,3,3,3,3,3,0,9.0,neutral or dissatisfied +60058,72822,Male,Loyal Customer,22,Business travel,Business,1013,2,3,3,3,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +60059,120095,Male,Loyal Customer,41,Business travel,Business,1576,3,3,4,3,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +60060,94761,Female,Loyal Customer,49,Business travel,Eco,441,2,5,1,5,5,4,3,2,2,2,2,4,2,3,17,10.0,neutral or dissatisfied +60061,44538,Female,Loyal Customer,54,Personal Travel,Eco,157,5,4,5,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +60062,62937,Female,Loyal Customer,41,Business travel,Business,2796,2,2,2,2,3,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +60063,12024,Male,Loyal Customer,44,Business travel,Eco,376,3,4,4,4,3,3,3,3,2,5,3,4,3,3,6,1.0,satisfied +60064,94997,Female,Loyal Customer,37,Personal Travel,Eco,319,1,1,1,3,5,1,5,5,3,2,4,1,4,5,13,8.0,neutral or dissatisfied +60065,22362,Female,disloyal Customer,38,Business travel,Eco,143,3,2,3,4,1,3,1,1,4,4,3,3,3,1,0,0.0,neutral or dissatisfied +60066,30561,Female,disloyal Customer,51,Business travel,Eco,628,2,5,3,5,3,3,3,3,4,1,5,4,3,3,0,0.0,neutral or dissatisfied +60067,83791,Male,Loyal Customer,42,Business travel,Business,2152,4,4,4,4,2,5,4,4,4,5,4,4,4,5,10,2.0,satisfied +60068,48265,Male,Loyal Customer,42,Business travel,Eco Plus,192,4,5,5,5,4,4,4,4,1,1,4,5,1,4,0,1.0,satisfied +60069,100026,Male,disloyal Customer,21,Business travel,Business,281,4,0,4,5,1,4,1,1,4,4,4,5,4,1,0,2.0,satisfied +60070,16524,Female,disloyal Customer,44,Business travel,Eco,209,1,5,1,2,4,1,4,4,1,3,2,5,5,4,0,0.0,neutral or dissatisfied +60071,1451,Female,disloyal Customer,47,Business travel,Business,772,3,3,3,1,2,3,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +60072,80717,Female,Loyal Customer,60,Business travel,Business,3347,2,3,3,3,1,1,1,2,2,2,2,2,2,3,0,37.0,neutral or dissatisfied +60073,118273,Female,Loyal Customer,40,Business travel,Business,2740,1,1,1,1,5,4,4,4,4,4,5,5,4,3,26,9.0,satisfied +60074,2549,Female,disloyal Customer,22,Business travel,Eco,304,3,4,3,4,5,3,5,5,3,4,3,3,4,5,5,2.0,neutral or dissatisfied +60075,22964,Male,Loyal Customer,28,Business travel,Business,2776,1,2,2,2,1,1,1,1,2,3,3,2,4,1,45,22.0,neutral or dissatisfied +60076,37281,Female,Loyal Customer,27,Business travel,Business,1914,5,5,5,5,4,4,4,4,5,5,2,1,1,4,0,0.0,satisfied +60077,20743,Male,Loyal Customer,51,Business travel,Business,363,1,1,1,1,5,1,3,2,2,2,2,2,2,1,0,0.0,satisfied +60078,89924,Male,Loyal Customer,38,Business travel,Business,1101,4,4,4,4,4,4,2,5,5,5,5,2,5,3,0,0.0,satisfied +60079,29178,Female,Loyal Customer,26,Business travel,Eco Plus,679,4,3,3,3,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +60080,106812,Male,Loyal Customer,54,Business travel,Business,1488,5,5,5,5,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +60081,75956,Male,Loyal Customer,22,Business travel,Business,1887,2,3,4,3,2,3,2,2,1,5,4,2,4,2,0,0.0,neutral or dissatisfied +60082,113724,Female,Loyal Customer,48,Personal Travel,Eco,223,2,4,2,2,2,5,5,1,1,2,1,4,1,3,23,10.0,neutral or dissatisfied +60083,48287,Male,Loyal Customer,16,Personal Travel,Eco Plus,391,3,5,3,4,5,3,5,5,5,3,4,5,5,5,6,5.0,neutral or dissatisfied +60084,44838,Female,Loyal Customer,51,Business travel,Eco,760,5,3,4,3,2,4,2,5,5,5,5,2,5,4,0,0.0,satisfied +60085,126013,Male,Loyal Customer,48,Business travel,Business,3296,2,2,2,2,3,5,4,5,5,5,5,3,5,4,30,19.0,satisfied +60086,802,Male,Loyal Customer,47,Business travel,Business,134,2,3,3,3,4,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +60087,46864,Female,disloyal Customer,30,Business travel,Eco,737,1,1,1,3,2,1,2,2,3,2,1,2,1,2,0,6.0,neutral or dissatisfied +60088,71546,Male,disloyal Customer,21,Business travel,Eco,1005,2,2,2,3,5,2,2,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +60089,41259,Male,Loyal Customer,64,Personal Travel,Eco,1034,3,2,3,3,3,3,3,3,4,4,3,2,4,3,0,5.0,neutral or dissatisfied +60090,105212,Female,Loyal Customer,21,Personal Travel,Business,377,4,4,4,5,5,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +60091,95215,Female,Loyal Customer,56,Personal Travel,Eco,323,3,4,3,4,5,3,4,5,5,3,5,2,5,2,3,0.0,neutral or dissatisfied +60092,84071,Female,Loyal Customer,53,Business travel,Eco,932,3,3,3,3,4,4,3,4,4,3,4,4,4,4,34,45.0,neutral or dissatisfied +60093,86076,Female,Loyal Customer,57,Personal Travel,Eco Plus,447,2,2,2,4,3,3,3,4,4,2,3,4,4,1,3,3.0,neutral or dissatisfied +60094,92231,Male,Loyal Customer,46,Business travel,Business,1956,4,4,4,4,3,3,4,3,3,4,3,5,3,5,5,0.0,satisfied +60095,50062,Female,Loyal Customer,43,Business travel,Eco,86,5,2,2,2,2,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +60096,57624,Male,Loyal Customer,40,Business travel,Business,200,1,1,1,1,5,4,5,5,5,5,4,4,5,4,8,9.0,satisfied +60097,87403,Male,Loyal Customer,29,Personal Travel,Eco,425,4,5,4,1,1,4,1,1,3,2,5,3,4,1,21,19.0,neutral or dissatisfied +60098,120834,Female,disloyal Customer,23,Business travel,Business,992,5,5,5,2,5,5,5,5,3,4,4,4,4,5,0,1.0,satisfied +60099,56186,Female,Loyal Customer,53,Personal Travel,Eco,1400,3,1,3,3,3,4,3,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +60100,27687,Female,Loyal Customer,41,Business travel,Eco,1107,1,2,2,2,1,1,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +60101,119081,Female,Loyal Customer,48,Business travel,Business,1107,4,4,4,4,4,5,5,4,4,4,4,5,4,3,8,0.0,satisfied +60102,59594,Female,Loyal Customer,39,Business travel,Business,3535,4,4,4,4,3,5,5,5,5,5,5,4,5,5,1,40.0,satisfied +60103,66134,Female,Loyal Customer,8,Personal Travel,Eco,583,1,5,1,1,2,1,3,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +60104,61335,Female,Loyal Customer,40,Business travel,Business,2059,4,4,4,4,4,4,5,4,4,4,4,5,4,5,6,0.0,satisfied +60105,73084,Male,disloyal Customer,22,Business travel,Eco,1085,3,3,3,4,3,4,4,1,4,3,4,4,2,4,131,152.0,neutral or dissatisfied +60106,33130,Male,Loyal Customer,14,Personal Travel,Eco,102,4,4,4,4,3,4,3,3,2,4,4,5,1,3,0,0.0,neutral or dissatisfied +60107,94276,Male,Loyal Customer,39,Business travel,Business,1791,3,3,3,3,3,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +60108,108219,Male,Loyal Customer,42,Personal Travel,Eco,777,2,3,2,4,2,2,3,2,5,3,3,3,4,2,26,23.0,neutral or dissatisfied +60109,115488,Male,disloyal Customer,37,Business travel,Eco,308,2,2,2,3,3,2,3,3,4,2,4,4,4,3,14,24.0,neutral or dissatisfied +60110,116060,Male,Loyal Customer,43,Personal Travel,Eco,333,3,4,3,2,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +60111,62041,Male,Loyal Customer,59,Business travel,Business,2475,2,2,2,2,2,2,2,1,1,3,4,2,3,2,157,171.0,neutral or dissatisfied +60112,104100,Male,Loyal Customer,45,Business travel,Business,297,1,1,1,1,4,5,4,5,5,4,5,3,5,3,0,5.0,satisfied +60113,37021,Female,Loyal Customer,64,Business travel,Eco Plus,814,4,4,4,4,1,1,1,4,4,4,4,2,4,2,77,68.0,satisfied +60114,16237,Male,Loyal Customer,13,Personal Travel,Business,631,1,4,1,1,1,1,1,1,3,2,4,5,5,1,94,82.0,neutral or dissatisfied +60115,44532,Female,disloyal Customer,37,Business travel,Eco,157,3,0,3,4,4,3,4,4,4,3,2,1,1,4,0,0.0,neutral or dissatisfied +60116,106440,Male,Loyal Customer,57,Business travel,Business,1914,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +60117,108342,Male,disloyal Customer,28,Business travel,Eco,1288,2,2,2,3,5,2,2,5,4,3,3,2,3,5,7,7.0,neutral or dissatisfied +60118,41289,Male,Loyal Customer,52,Personal Travel,Eco,542,1,5,1,3,1,1,2,1,4,5,5,3,4,1,0,6.0,neutral or dissatisfied +60119,9530,Female,Loyal Customer,42,Business travel,Business,2073,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +60120,62411,Female,disloyal Customer,56,Business travel,Eco Plus,1204,3,3,3,3,4,3,3,4,2,5,1,4,4,4,0,0.0,neutral or dissatisfied +60121,29440,Female,Loyal Customer,45,Business travel,Eco,421,4,3,3,3,2,3,4,3,3,4,3,3,3,1,0,0.0,satisfied +60122,19386,Female,Loyal Customer,68,Personal Travel,Eco,844,3,5,3,3,2,4,4,1,1,3,3,3,1,5,13,14.0,neutral or dissatisfied +60123,11916,Male,Loyal Customer,62,Personal Travel,Eco,744,3,3,3,5,4,3,1,4,2,3,3,3,3,4,12,3.0,neutral or dissatisfied +60124,21103,Female,Loyal Customer,42,Business travel,Eco,106,4,5,5,5,3,3,1,4,4,4,4,4,4,3,0,0.0,satisfied +60125,107991,Male,Loyal Customer,51,Business travel,Business,271,5,5,5,5,5,5,4,4,4,4,4,3,4,3,6,0.0,satisfied +60126,45246,Female,disloyal Customer,29,Business travel,Eco Plus,1081,2,2,2,1,4,2,4,4,3,3,1,3,4,4,17,24.0,neutral or dissatisfied +60127,1907,Female,Loyal Customer,58,Business travel,Business,2116,4,4,4,4,5,5,4,5,5,5,4,4,5,5,9,11.0,satisfied +60128,30328,Female,Loyal Customer,59,Business travel,Eco,391,4,4,4,4,3,1,2,4,4,4,4,5,4,3,0,0.0,satisfied +60129,47749,Female,disloyal Customer,25,Business travel,Eco,834,3,3,3,5,2,3,2,2,2,4,4,4,4,2,0,2.0,neutral or dissatisfied +60130,30484,Female,disloyal Customer,18,Business travel,Business,627,0,4,0,3,1,0,1,1,5,5,5,4,4,1,0,0.0,satisfied +60131,109909,Male,Loyal Customer,35,Business travel,Eco,971,3,4,5,4,2,3,3,2,5,3,3,3,1,3,373,358.0,neutral or dissatisfied +60132,112953,Female,Loyal Customer,11,Personal Travel,Eco,1497,3,5,3,3,2,3,2,2,4,2,4,3,5,2,4,0.0,neutral or dissatisfied +60133,72796,Female,Loyal Customer,28,Personal Travel,Eco,1045,2,5,2,1,3,2,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +60134,23126,Female,disloyal Customer,40,Business travel,Business,300,3,3,3,3,1,3,1,1,5,3,4,4,1,1,0,7.0,neutral or dissatisfied +60135,9740,Female,disloyal Customer,27,Business travel,Business,908,3,3,3,5,4,3,1,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +60136,56982,Male,Loyal Customer,67,Personal Travel,Eco,2565,0,4,0,3,4,1,1,2,1,4,4,1,2,1,32,0.0,satisfied +60137,60392,Female,Loyal Customer,78,Business travel,Business,1845,4,4,4,4,3,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +60138,75091,Male,Loyal Customer,39,Business travel,Business,1846,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +60139,123919,Male,Loyal Customer,70,Personal Travel,Eco,544,1,4,1,5,1,1,4,1,5,3,3,3,4,1,43,24.0,neutral or dissatisfied +60140,8788,Male,Loyal Customer,34,Business travel,Business,522,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +60141,80270,Female,Loyal Customer,60,Business travel,Business,2071,2,2,2,2,5,5,4,4,4,4,4,5,4,5,4,0.0,satisfied +60142,21366,Female,Loyal Customer,11,Personal Travel,Eco Plus,761,1,4,1,4,1,1,1,1,5,5,5,4,5,1,73,104.0,neutral or dissatisfied +60143,106814,Female,Loyal Customer,55,Business travel,Business,1488,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +60144,35908,Male,disloyal Customer,21,Business travel,Eco,1322,1,1,1,1,5,1,4,5,5,3,3,2,4,5,40,34.0,neutral or dissatisfied +60145,122664,Male,disloyal Customer,22,Business travel,Business,361,5,0,5,3,1,5,1,1,3,2,4,3,4,1,29,30.0,satisfied +60146,22635,Male,Loyal Customer,24,Personal Travel,Eco,300,2,5,2,4,3,2,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +60147,21803,Female,disloyal Customer,21,Business travel,Eco,341,3,4,3,2,4,3,4,4,2,5,4,3,2,4,0,0.0,neutral or dissatisfied +60148,100695,Female,Loyal Customer,60,Personal Travel,Eco,677,2,5,2,2,4,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +60149,68378,Female,Loyal Customer,44,Business travel,Business,1507,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +60150,27258,Male,disloyal Customer,28,Business travel,Business,672,4,3,3,1,3,3,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +60151,108393,Male,disloyal Customer,44,Business travel,Business,894,4,4,4,3,2,4,2,2,3,3,3,4,4,2,17,20.0,satisfied +60152,125940,Female,Loyal Customer,48,Personal Travel,Eco,742,1,5,2,1,5,5,4,4,4,2,4,4,4,5,21,7.0,neutral or dissatisfied +60153,35109,Male,Loyal Customer,40,Business travel,Business,1028,1,1,1,1,4,2,4,3,3,3,3,1,3,5,0,0.0,satisfied +60154,9902,Male,Loyal Customer,48,Business travel,Business,515,5,2,5,5,5,4,5,5,5,5,5,4,5,5,0,5.0,satisfied +60155,119631,Male,Loyal Customer,33,Business travel,Business,1727,4,4,4,4,4,4,4,4,4,2,3,5,5,4,0,0.0,satisfied +60156,84342,Female,Loyal Customer,30,Business travel,Business,1843,2,2,2,2,3,3,3,3,3,2,5,5,4,3,0,0.0,satisfied +60157,54669,Male,disloyal Customer,25,Business travel,Eco,854,3,3,3,3,5,3,5,5,5,4,3,2,2,5,2,23.0,neutral or dissatisfied +60158,55695,Male,disloyal Customer,54,Business travel,Eco,1062,2,1,1,4,2,1,2,2,4,5,3,3,4,2,0,19.0,neutral or dissatisfied +60159,86241,Female,Loyal Customer,22,Personal Travel,Eco,306,3,5,3,2,3,3,3,3,2,1,2,2,3,3,22,19.0,neutral or dissatisfied +60160,87647,Female,Loyal Customer,55,Business travel,Business,3879,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +60161,2431,Female,Loyal Customer,44,Personal Travel,Eco,604,2,5,2,4,4,5,5,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +60162,18203,Male,disloyal Customer,22,Business travel,Eco,235,3,0,3,2,4,3,4,4,3,1,3,3,1,4,1,0.0,neutral or dissatisfied +60163,61750,Male,Loyal Customer,24,Personal Travel,Eco,1635,3,4,3,5,2,3,2,2,5,3,5,4,5,2,41,70.0,neutral or dissatisfied +60164,107944,Male,Loyal Customer,55,Personal Travel,Eco,611,3,4,3,2,2,3,2,2,5,5,2,3,4,2,2,0.0,neutral or dissatisfied +60165,63869,Female,Loyal Customer,46,Business travel,Business,3754,3,3,3,3,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +60166,20091,Female,Loyal Customer,52,Business travel,Eco,416,4,2,2,2,2,5,4,5,5,4,5,3,5,2,0,0.0,satisfied +60167,127743,Female,Loyal Customer,54,Business travel,Business,601,3,2,2,2,2,3,4,3,3,3,3,3,3,2,18,21.0,neutral or dissatisfied +60168,115650,Female,Loyal Customer,45,Business travel,Eco,296,3,5,5,5,2,4,4,3,3,3,3,3,3,1,9,0.0,neutral or dissatisfied +60169,64968,Female,disloyal Customer,47,Business travel,Eco,469,2,3,3,4,1,3,1,1,4,2,4,5,2,1,0,0.0,neutral or dissatisfied +60170,124405,Male,disloyal Customer,28,Business travel,Business,1044,4,3,3,2,2,3,2,2,3,5,5,5,4,2,0,2.0,satisfied +60171,21006,Male,Loyal Customer,25,Personal Travel,Eco Plus,689,2,4,2,1,2,2,2,2,1,5,2,2,5,2,0,0.0,neutral or dissatisfied +60172,94623,Male,Loyal Customer,38,Business travel,Eco,239,1,2,2,2,1,1,1,1,4,5,3,1,3,1,26,24.0,neutral or dissatisfied +60173,23623,Male,Loyal Customer,70,Personal Travel,Eco Plus,977,1,5,1,1,3,1,3,3,3,4,5,5,5,3,2,3.0,neutral or dissatisfied +60174,127628,Female,disloyal Customer,25,Business travel,Business,763,4,4,4,1,1,4,1,1,5,5,3,4,4,1,0,0.0,satisfied +60175,13672,Female,Loyal Customer,47,Personal Travel,Eco,462,2,4,4,2,2,5,3,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +60176,6033,Male,Loyal Customer,30,Business travel,Business,2885,5,5,5,5,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +60177,5063,Female,disloyal Customer,25,Business travel,Business,235,3,5,3,1,4,3,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +60178,50573,Female,Loyal Customer,44,Personal Travel,Eco,77,3,4,3,2,4,4,5,5,5,3,5,3,5,5,38,30.0,neutral or dissatisfied +60179,96672,Male,Loyal Customer,27,Personal Travel,Eco,937,2,4,2,4,5,2,1,5,3,2,5,2,4,5,50,49.0,neutral or dissatisfied +60180,122234,Male,Loyal Customer,51,Business travel,Eco,541,2,3,3,3,2,2,2,2,3,1,3,2,2,2,6,14.0,neutral or dissatisfied +60181,76971,Female,disloyal Customer,9,Business travel,Eco,1990,1,1,1,3,4,1,4,4,3,1,2,2,4,4,0,0.0,neutral or dissatisfied +60182,2048,Male,Loyal Customer,40,Business travel,Business,785,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +60183,4980,Male,disloyal Customer,21,Business travel,Eco,502,3,2,4,4,2,4,2,2,1,4,4,3,3,2,0,13.0,neutral or dissatisfied +60184,101647,Male,Loyal Customer,46,Personal Travel,Eco,1733,4,5,4,3,4,4,4,4,4,2,4,4,4,4,7,0.0,satisfied +60185,78692,Female,disloyal Customer,29,Business travel,Business,761,0,0,0,3,5,0,5,5,5,2,4,4,4,5,0,0.0,satisfied +60186,99699,Male,Loyal Customer,12,Personal Travel,Eco,442,1,4,1,3,2,1,2,2,1,4,2,2,4,2,0,0.0,neutral or dissatisfied +60187,94813,Female,Loyal Customer,65,Business travel,Business,239,2,3,5,3,3,3,2,2,2,2,2,1,2,1,20,24.0,neutral or dissatisfied +60188,100031,Female,disloyal Customer,58,Business travel,Business,277,4,4,4,3,5,4,1,5,4,5,4,5,4,5,0,0.0,satisfied +60189,92662,Male,disloyal Customer,23,Business travel,Business,453,5,0,5,2,2,5,2,2,4,5,4,3,5,2,0,0.0,satisfied +60190,105272,Male,Loyal Customer,61,Personal Travel,Eco,2106,4,5,3,2,5,3,5,5,1,2,1,5,1,5,0,24.0,neutral or dissatisfied +60191,113925,Female,disloyal Customer,13,Business travel,Business,969,5,0,5,3,4,5,4,4,3,4,3,4,5,4,0,0.0,satisfied +60192,4798,Female,Loyal Customer,12,Personal Travel,Eco,438,4,5,2,5,2,5,1,5,3,4,5,1,4,1,113,165.0,neutral or dissatisfied +60193,101239,Female,Loyal Customer,45,Business travel,Business,1587,1,5,5,5,1,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +60194,129133,Female,Loyal Customer,26,Business travel,Business,1917,4,4,5,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +60195,14197,Male,Loyal Customer,22,Business travel,Eco,714,4,1,5,1,4,4,5,4,3,1,1,4,2,4,0,0.0,satisfied +60196,37259,Male,disloyal Customer,38,Business travel,Business,1076,3,3,3,4,1,3,1,1,3,5,3,2,4,1,40,33.0,neutral or dissatisfied +60197,85414,Male,Loyal Customer,51,Business travel,Business,3179,5,3,5,5,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +60198,61114,Male,Loyal Customer,30,Personal Travel,Eco Plus,1546,1,1,1,3,1,1,1,1,3,1,2,2,4,1,0,0.0,neutral or dissatisfied +60199,110112,Male,Loyal Customer,52,Business travel,Business,882,5,5,5,5,2,4,4,2,2,2,2,4,2,4,0,15.0,satisfied +60200,18598,Female,Loyal Customer,72,Business travel,Business,192,2,3,3,3,2,2,3,2,2,2,2,2,2,3,0,9.0,neutral or dissatisfied +60201,56300,Female,Loyal Customer,69,Personal Travel,Eco,2227,3,4,3,3,1,3,4,2,2,3,2,3,2,1,21,0.0,neutral or dissatisfied +60202,105383,Male,Loyal Customer,60,Business travel,Business,369,2,2,1,2,2,2,3,2,2,2,2,3,2,2,38,41.0,neutral or dissatisfied +60203,124963,Female,Loyal Customer,72,Business travel,Business,3122,0,5,0,5,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +60204,100118,Male,Loyal Customer,43,Business travel,Business,725,2,2,2,2,4,5,5,3,3,3,3,5,3,5,88,64.0,satisfied +60205,95324,Female,Loyal Customer,50,Personal Travel,Eco,189,2,4,2,5,5,4,4,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +60206,6365,Female,Loyal Customer,37,Business travel,Eco,315,2,5,5,5,2,2,2,3,4,4,3,2,2,2,153,227.0,neutral or dissatisfied +60207,76901,Male,Loyal Customer,31,Business travel,Business,630,1,1,1,1,4,4,4,4,5,1,1,1,2,4,0,0.0,satisfied +60208,123084,Male,Loyal Customer,36,Business travel,Business,650,2,1,1,1,4,3,4,2,2,2,2,3,2,3,0,5.0,neutral or dissatisfied +60209,39093,Male,Loyal Customer,11,Personal Travel,Eco,984,2,4,2,4,2,2,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +60210,4230,Female,Loyal Customer,57,Business travel,Business,1020,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +60211,84689,Male,Loyal Customer,12,Personal Travel,Eco,2182,3,2,3,3,4,3,4,4,3,5,4,3,3,4,8,6.0,neutral or dissatisfied +60212,68744,Female,Loyal Customer,38,Business travel,Business,1021,3,3,3,3,3,5,5,5,5,5,5,5,5,5,30,23.0,satisfied +60213,35410,Male,disloyal Customer,17,Business travel,Eco,972,3,3,3,3,1,3,1,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +60214,83050,Female,disloyal Customer,23,Business travel,Eco,1127,3,3,3,3,2,3,4,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +60215,123185,Female,Loyal Customer,31,Personal Travel,Eco,600,4,2,4,4,2,4,4,2,1,5,2,2,4,2,76,59.0,neutral or dissatisfied +60216,4368,Male,Loyal Customer,60,Business travel,Business,473,1,4,4,4,5,3,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +60217,102680,Male,Loyal Customer,67,Business travel,Business,365,4,4,4,4,5,5,4,5,5,5,5,5,5,4,15,0.0,satisfied +60218,10341,Male,Loyal Customer,57,Business travel,Business,312,3,3,3,3,3,5,5,4,4,4,4,5,4,3,13,12.0,satisfied +60219,31964,Female,Loyal Customer,36,Business travel,Business,1638,2,2,3,2,2,5,5,4,4,4,5,3,4,4,0,0.0,satisfied +60220,17125,Female,Loyal Customer,46,Business travel,Business,1886,3,3,3,3,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +60221,51785,Male,Loyal Customer,21,Personal Travel,Eco,370,4,3,4,3,2,4,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +60222,117140,Female,Loyal Customer,56,Personal Travel,Eco,304,4,3,4,3,1,4,3,4,4,4,4,1,4,3,5,0.0,neutral or dissatisfied +60223,66804,Female,disloyal Customer,23,Business travel,Eco,731,2,3,3,1,4,3,4,4,4,3,5,4,4,4,5,0.0,neutral or dissatisfied +60224,29901,Male,Loyal Customer,28,Business travel,Business,3544,3,3,4,3,3,4,4,3,2,2,5,2,1,3,0,0.0,satisfied +60225,80024,Female,Loyal Customer,67,Personal Travel,Eco,950,2,4,2,1,4,4,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +60226,25123,Female,Loyal Customer,54,Business travel,Eco Plus,946,5,3,3,3,2,4,4,5,5,5,5,1,5,3,2,0.0,satisfied +60227,68766,Female,Loyal Customer,53,Business travel,Business,2396,5,5,5,5,2,5,5,4,4,4,4,5,4,3,13,23.0,satisfied +60228,115486,Female,disloyal Customer,21,Business travel,Eco,362,1,3,1,4,4,1,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +60229,120753,Female,Loyal Customer,28,Business travel,Business,678,5,5,5,5,5,5,5,5,3,5,4,3,4,5,0,3.0,satisfied +60230,119090,Female,Loyal Customer,56,Business travel,Business,1107,2,2,2,2,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +60231,61444,Male,disloyal Customer,35,Business travel,Business,2288,3,4,4,3,4,4,2,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +60232,119451,Female,Loyal Customer,42,Business travel,Business,759,2,2,3,2,3,3,3,2,2,2,2,4,2,1,0,7.0,neutral or dissatisfied +60233,74216,Male,Loyal Customer,57,Business travel,Business,1746,5,5,5,5,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +60234,92928,Male,Loyal Customer,41,Business travel,Business,2029,4,5,1,5,4,3,4,2,2,1,4,2,2,2,0,0.0,neutral or dissatisfied +60235,33804,Female,Loyal Customer,36,Business travel,Business,1428,5,5,5,5,1,2,2,5,5,5,5,3,5,2,6,2.0,satisfied +60236,46789,Female,Loyal Customer,46,Business travel,Business,2321,1,1,1,1,3,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +60237,100568,Male,Loyal Customer,50,Business travel,Business,486,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +60238,50914,Female,Loyal Customer,63,Personal Travel,Eco,373,3,1,3,4,3,3,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +60239,4886,Female,disloyal Customer,62,Business travel,Business,408,2,2,2,5,1,2,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +60240,115856,Female,Loyal Customer,22,Business travel,Business,2803,2,2,2,2,5,5,5,5,5,4,5,1,2,5,49,29.0,satisfied +60241,29828,Female,Loyal Customer,25,Business travel,Business,571,3,3,1,3,4,4,4,4,3,4,1,4,4,4,0,0.0,satisfied +60242,51248,Male,Loyal Customer,59,Business travel,Eco Plus,89,5,4,4,4,5,5,5,5,1,5,3,2,5,5,0,0.0,satisfied +60243,11884,Male,Loyal Customer,23,Personal Travel,Eco,1042,1,4,2,2,4,2,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +60244,41793,Male,disloyal Customer,24,Business travel,Eco,489,4,0,3,3,4,3,4,4,4,3,3,4,1,4,0,0.0,neutral or dissatisfied +60245,59862,Female,Loyal Customer,21,Business travel,Business,2031,4,4,5,4,2,2,2,2,3,4,4,5,4,2,1,0.0,satisfied +60246,99653,Male,Loyal Customer,43,Business travel,Business,2106,5,5,5,5,4,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +60247,20643,Male,Loyal Customer,33,Personal Travel,Eco Plus,911,4,4,5,3,3,5,3,3,4,4,4,5,5,3,11,0.0,satisfied +60248,122980,Female,Loyal Customer,52,Business travel,Business,3656,4,4,4,4,3,4,5,4,4,4,4,3,4,3,8,41.0,satisfied +60249,33698,Female,Loyal Customer,25,Business travel,Business,3043,5,5,5,5,5,4,5,5,1,2,5,1,1,5,1,0.0,satisfied +60250,93927,Female,Loyal Customer,25,Business travel,Business,507,3,3,3,3,5,5,5,5,5,4,5,4,4,5,37,37.0,satisfied +60251,68053,Male,disloyal Customer,23,Business travel,Eco,813,3,3,3,3,3,3,3,3,5,2,4,4,4,3,2,9.0,neutral or dissatisfied +60252,112207,Female,Loyal Customer,51,Business travel,Business,799,3,3,3,3,4,4,4,2,2,3,2,3,2,3,14,15.0,satisfied +60253,77814,Female,Loyal Customer,53,Personal Travel,Eco,813,2,2,3,4,1,2,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +60254,3909,Male,Loyal Customer,44,Personal Travel,Eco,213,2,0,0,3,5,0,3,5,5,5,3,4,4,5,6,83.0,neutral or dissatisfied +60255,104502,Female,Loyal Customer,39,Business travel,Business,1609,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +60256,101187,Male,Loyal Customer,50,Personal Travel,Eco,583,2,5,2,3,2,2,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +60257,113486,Female,disloyal Customer,23,Business travel,Eco,258,2,1,2,3,2,2,3,2,3,5,3,2,3,2,0,6.0,neutral or dissatisfied +60258,95248,Male,Loyal Customer,56,Personal Travel,Eco,562,3,5,3,2,2,3,2,2,4,2,5,5,4,2,2,0.0,neutral or dissatisfied +60259,82256,Male,Loyal Customer,54,Business travel,Business,1481,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,8.0,satisfied +60260,45482,Male,Loyal Customer,26,Business travel,Business,522,3,4,4,4,3,3,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +60261,30997,Male,Loyal Customer,45,Business travel,Business,2585,4,4,4,4,1,3,4,5,5,5,5,2,5,4,0,0.0,satisfied +60262,949,Female,Loyal Customer,78,Business travel,Business,1800,1,4,4,4,5,3,3,3,3,4,1,1,3,2,26,20.0,neutral or dissatisfied +60263,103707,Male,Loyal Customer,30,Personal Travel,Eco,405,2,5,3,1,4,3,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +60264,872,Male,Loyal Customer,43,Business travel,Business,309,1,4,4,4,2,3,4,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +60265,102651,Female,Loyal Customer,52,Business travel,Business,3312,0,0,0,2,5,5,5,4,4,4,4,5,4,5,3,0.0,satisfied +60266,88885,Female,Loyal Customer,25,Business travel,Business,859,3,3,3,3,3,3,3,3,4,3,5,4,5,3,42,18.0,satisfied +60267,12210,Female,Loyal Customer,49,Business travel,Business,3982,4,3,3,3,1,3,3,4,4,4,4,4,4,3,0,3.0,neutral or dissatisfied +60268,52088,Male,Loyal Customer,57,Business travel,Business,3413,2,3,3,3,4,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +60269,9443,Male,Loyal Customer,23,Business travel,Business,1692,2,1,1,1,2,2,2,1,4,4,4,2,2,2,195,195.0,neutral or dissatisfied +60270,43269,Female,Loyal Customer,28,Business travel,Business,436,2,2,4,2,5,5,5,5,1,4,5,4,4,5,0,6.0,satisfied +60271,18408,Male,disloyal Customer,27,Business travel,Business,284,3,3,3,1,1,3,1,1,4,3,1,3,1,1,0,0.0,neutral or dissatisfied +60272,31915,Female,Loyal Customer,48,Business travel,Business,3069,0,4,0,3,4,4,5,4,4,4,4,4,4,4,0,11.0,satisfied +60273,11936,Male,disloyal Customer,34,Business travel,Business,781,3,3,3,2,4,3,4,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +60274,88111,Male,Loyal Customer,41,Business travel,Business,1896,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +60275,107865,Male,Loyal Customer,34,Business travel,Business,2561,2,2,2,2,2,4,5,4,4,4,4,4,4,1,3,6.0,satisfied +60276,113397,Male,Loyal Customer,58,Business travel,Business,3114,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,2.0,satisfied +60277,123119,Male,disloyal Customer,39,Business travel,Eco,600,3,1,3,3,5,3,5,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +60278,9540,Female,Loyal Customer,33,Business travel,Business,2876,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +60279,45410,Male,Loyal Customer,62,Business travel,Eco,458,4,4,4,4,4,4,4,4,3,5,3,5,4,4,47,38.0,satisfied +60280,80560,Male,disloyal Customer,13,Business travel,Eco,740,3,3,3,4,1,3,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +60281,23697,Female,Loyal Customer,40,Business travel,Eco,73,1,1,1,1,1,1,1,1,4,1,4,3,3,1,1,24.0,neutral or dissatisfied +60282,9283,Female,Loyal Customer,53,Business travel,Eco,1201,3,3,3,3,2,4,4,3,3,3,3,2,3,2,0,13.0,neutral or dissatisfied +60283,65430,Female,Loyal Customer,41,Personal Travel,Eco,2165,4,1,4,3,2,4,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +60284,13694,Male,Loyal Customer,27,Business travel,Eco,300,3,5,5,5,3,3,3,3,2,4,4,3,3,3,0,0.0,neutral or dissatisfied +60285,67380,Female,Loyal Customer,20,Business travel,Business,2587,3,3,3,3,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +60286,119762,Male,Loyal Customer,19,Personal Travel,Eco Plus,1325,1,4,1,4,1,1,1,1,4,5,3,4,3,1,0,8.0,neutral or dissatisfied +60287,109274,Female,Loyal Customer,33,Business travel,Eco Plus,793,2,3,1,3,2,2,2,2,3,5,3,3,3,2,22,18.0,neutral or dissatisfied +60288,116165,Male,Loyal Customer,49,Personal Travel,Eco,362,2,5,2,4,4,2,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +60289,46796,Male,Loyal Customer,7,Personal Travel,Business,853,2,4,3,4,1,3,4,1,4,5,4,3,4,1,29,24.0,neutral or dissatisfied +60290,79903,Male,Loyal Customer,23,Business travel,Business,1005,3,3,3,3,5,5,5,5,3,2,5,4,5,5,12,11.0,satisfied +60291,120324,Female,Loyal Customer,61,Personal Travel,Eco,268,1,3,1,2,1,5,3,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +60292,21519,Male,Loyal Customer,34,Personal Travel,Eco,433,2,5,2,3,3,2,3,3,3,4,4,3,5,3,62,51.0,neutral or dissatisfied +60293,80801,Female,Loyal Customer,32,Business travel,Business,2195,4,4,4,4,5,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +60294,42061,Male,Loyal Customer,24,Personal Travel,Eco,106,3,5,3,3,2,3,5,2,4,5,4,4,5,2,5,0.0,neutral or dissatisfied +60295,120280,Female,Loyal Customer,37,Business travel,Business,3987,3,1,3,3,5,1,1,5,5,5,5,4,5,5,10,23.0,satisfied +60296,107399,Male,Loyal Customer,51,Business travel,Business,717,3,3,3,3,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +60297,24634,Female,Loyal Customer,59,Personal Travel,Eco,526,2,4,2,3,2,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +60298,127403,Female,Loyal Customer,40,Business travel,Business,868,1,1,1,1,5,5,4,4,4,4,4,3,4,3,10,0.0,satisfied +60299,84948,Female,disloyal Customer,25,Business travel,Business,547,2,0,1,5,3,1,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +60300,94342,Female,Loyal Customer,45,Business travel,Eco,277,1,5,5,5,5,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +60301,121221,Male,Loyal Customer,44,Business travel,Business,2075,4,4,4,4,4,4,5,4,4,4,4,5,4,5,38,29.0,satisfied +60302,29499,Male,Loyal Customer,42,Personal Travel,Eco,1107,3,5,3,1,5,3,5,5,4,5,4,5,3,5,1,0.0,neutral or dissatisfied +60303,90479,Female,Loyal Customer,49,Business travel,Business,3829,3,3,2,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +60304,127546,Female,disloyal Customer,26,Business travel,Eco,1009,1,1,1,3,2,1,2,2,2,4,3,2,3,2,2,0.0,neutral or dissatisfied +60305,96430,Female,Loyal Customer,12,Personal Travel,Business,436,3,5,3,3,5,3,5,5,5,3,4,5,5,5,4,0.0,neutral or dissatisfied +60306,4660,Female,Loyal Customer,61,Business travel,Business,2569,2,3,3,3,5,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +60307,13274,Female,Loyal Customer,54,Personal Travel,Eco,772,1,4,1,1,3,2,1,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +60308,37980,Female,Loyal Customer,51,Personal Travel,Business,1185,2,5,2,1,2,5,5,4,4,2,4,5,4,4,19,3.0,neutral or dissatisfied +60309,121147,Male,Loyal Customer,55,Business travel,Eco,2521,4,4,4,4,4,4,4,3,3,1,2,4,4,4,0,0.0,neutral or dissatisfied +60310,101292,Female,disloyal Customer,30,Business travel,Eco,763,3,3,3,3,2,3,2,2,1,1,3,2,3,2,45,41.0,neutral or dissatisfied +60311,126828,Female,Loyal Customer,28,Business travel,Business,2296,2,4,4,4,2,2,2,2,3,3,2,3,4,2,0,0.0,neutral or dissatisfied +60312,120346,Male,Loyal Customer,29,Business travel,Business,2786,2,1,1,1,2,2,2,2,2,5,3,4,3,2,5,6.0,neutral or dissatisfied +60313,75238,Male,Loyal Customer,69,Personal Travel,Eco,1723,2,4,2,3,1,2,1,1,3,3,4,3,4,1,31,5.0,neutral or dissatisfied +60314,73695,Male,Loyal Customer,31,Business travel,Business,3099,2,5,5,5,2,2,2,2,4,3,3,2,3,2,2,6.0,neutral or dissatisfied +60315,96481,Female,Loyal Customer,56,Business travel,Business,2801,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +60316,102159,Female,Loyal Customer,37,Business travel,Business,258,3,2,2,2,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +60317,977,Male,Loyal Customer,39,Business travel,Business,3907,1,4,4,4,4,2,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +60318,104018,Male,disloyal Customer,22,Business travel,Business,862,4,3,4,4,4,4,4,4,1,1,3,1,3,4,81,46.0,neutral or dissatisfied +60319,33581,Female,Loyal Customer,51,Business travel,Eco,399,5,5,2,5,2,3,3,5,5,5,5,1,5,5,0,0.0,satisfied +60320,45977,Male,disloyal Customer,47,Business travel,Eco,483,2,0,2,3,3,2,2,3,1,3,2,1,4,3,1,0.0,neutral or dissatisfied +60321,77470,Male,Loyal Customer,34,Personal Travel,Eco,507,3,4,3,3,1,3,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +60322,15382,Male,disloyal Customer,56,Business travel,Eco,164,4,2,4,4,3,4,3,3,3,2,3,2,3,3,54,49.0,neutral or dissatisfied +60323,113470,Female,Loyal Customer,55,Business travel,Business,1595,0,4,0,3,4,5,4,2,2,2,2,4,2,3,25,15.0,satisfied +60324,31820,Male,Loyal Customer,38,Personal Travel,Business,2762,4,4,4,1,4,1,1,1,2,5,2,1,5,1,0,14.0,satisfied +60325,44978,Male,Loyal Customer,40,Business travel,Eco,118,2,1,1,1,2,2,2,2,1,1,1,5,3,2,0,10.0,satisfied +60326,65161,Female,Loyal Customer,16,Personal Travel,Eco,224,2,5,2,3,5,2,5,5,5,2,5,3,4,5,26,18.0,neutral or dissatisfied +60327,114302,Female,Loyal Customer,9,Personal Travel,Eco,909,1,1,1,4,3,1,3,3,3,4,3,3,4,3,24,15.0,neutral or dissatisfied +60328,118254,Female,disloyal Customer,37,Business travel,Eco,1788,3,3,3,4,3,3,3,3,3,2,3,4,4,3,12,7.0,neutral or dissatisfied +60329,6192,Female,Loyal Customer,14,Personal Travel,Eco,409,1,5,1,2,5,1,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +60330,116223,Female,Loyal Customer,62,Personal Travel,Eco,337,3,4,3,5,2,5,4,2,2,3,1,4,2,4,0,0.0,neutral or dissatisfied +60331,625,Male,Loyal Customer,46,Business travel,Business,102,1,1,1,1,5,4,5,4,4,4,4,3,4,3,101,98.0,satisfied +60332,113817,Female,Loyal Customer,62,Personal Travel,Eco Plus,414,5,2,5,3,2,4,3,5,5,5,1,4,5,4,35,20.0,satisfied +60333,39792,Male,disloyal Customer,22,Business travel,Eco,272,3,4,3,3,3,3,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +60334,41061,Female,Loyal Customer,46,Business travel,Business,140,1,1,1,1,4,5,4,5,5,5,4,4,5,3,30,29.0,satisfied +60335,33036,Male,Loyal Customer,39,Personal Travel,Eco,201,1,3,1,2,2,1,4,2,3,4,2,4,4,2,0,0.0,neutral or dissatisfied +60336,80286,Male,disloyal Customer,32,Business travel,Eco,746,3,3,3,4,2,3,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +60337,95598,Female,disloyal Customer,48,Business travel,Eco,670,1,1,1,3,2,1,5,2,4,1,2,2,3,2,8,10.0,neutral or dissatisfied +60338,22436,Male,Loyal Customer,66,Personal Travel,Eco,208,2,2,2,2,5,2,5,5,2,3,2,2,2,5,0,0.0,neutral or dissatisfied +60339,46665,Female,Loyal Customer,48,Business travel,Business,1824,5,5,4,5,1,1,2,4,4,4,5,4,4,2,0,2.0,satisfied +60340,6542,Male,Loyal Customer,59,Business travel,Business,218,4,4,4,4,5,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +60341,63090,Male,Loyal Customer,49,Business travel,Business,2728,5,2,5,5,5,4,5,4,4,4,4,4,4,4,6,12.0,satisfied +60342,87401,Female,Loyal Customer,54,Personal Travel,Eco,425,2,2,2,3,5,1,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +60343,104942,Male,disloyal Customer,38,Business travel,Business,1180,2,2,2,4,5,2,5,5,3,3,5,3,5,5,19,17.0,neutral or dissatisfied +60344,113665,Female,Loyal Customer,22,Personal Travel,Eco,223,3,4,3,1,5,3,3,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +60345,5379,Female,Loyal Customer,36,Business travel,Eco,412,2,1,1,1,2,1,2,2,2,1,3,3,4,2,0,0.0,neutral or dissatisfied +60346,39735,Female,Loyal Customer,55,Personal Travel,Eco,205,1,4,1,4,2,2,3,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +60347,44433,Female,Loyal Customer,32,Personal Travel,Eco,542,4,1,4,2,1,4,1,1,3,3,3,3,3,1,0,0.0,satisfied +60348,66502,Male,Loyal Customer,42,Business travel,Eco,447,4,5,5,5,3,4,3,3,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +60349,9459,Male,Loyal Customer,35,Personal Travel,Eco,362,3,4,3,3,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +60350,14983,Male,Loyal Customer,68,Personal Travel,Eco,927,3,3,3,3,4,3,4,4,3,3,4,1,4,4,0,41.0,neutral or dissatisfied +60351,89838,Female,Loyal Customer,57,Business travel,Business,1416,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,2.0,satisfied +60352,21414,Female,Loyal Customer,37,Business travel,Business,2185,2,2,2,2,5,5,2,4,4,4,4,4,4,3,18,13.0,satisfied +60353,9890,Male,disloyal Customer,38,Business travel,Business,508,1,0,0,4,5,0,5,5,3,4,5,5,4,5,17,28.0,neutral or dissatisfied +60354,68670,Male,Loyal Customer,53,Business travel,Business,2597,0,4,0,3,4,5,4,4,4,4,2,4,4,3,0,0.0,satisfied +60355,32912,Female,Loyal Customer,15,Personal Travel,Eco,216,3,2,0,3,3,0,4,3,1,5,4,3,4,3,0,0.0,neutral or dissatisfied +60356,125944,Female,Loyal Customer,9,Personal Travel,Eco,861,3,2,3,3,2,3,2,2,4,1,3,1,3,2,13,0.0,neutral or dissatisfied +60357,20767,Female,Loyal Customer,49,Personal Travel,Business,357,3,3,3,1,2,4,1,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +60358,119984,Male,Loyal Customer,54,Personal Travel,Eco,868,2,1,2,3,3,2,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +60359,80219,Male,Loyal Customer,60,Business travel,Business,2153,5,2,5,5,5,4,4,4,4,4,4,3,4,4,14,0.0,satisfied +60360,103558,Female,Loyal Customer,70,Personal Travel,Eco,967,3,4,3,2,5,4,4,5,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +60361,67230,Male,Loyal Customer,19,Personal Travel,Eco,1119,4,4,4,2,4,4,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +60362,48740,Male,Loyal Customer,58,Business travel,Business,1679,5,5,5,5,3,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +60363,33217,Male,disloyal Customer,25,Business travel,Eco Plus,101,4,5,4,4,1,4,1,1,5,1,2,1,2,1,0,1.0,neutral or dissatisfied +60364,40383,Male,Loyal Customer,60,Personal Travel,Eco,1250,1,3,1,1,3,1,3,3,3,1,1,4,5,3,0,0.0,neutral or dissatisfied +60365,19351,Female,Loyal Customer,40,Business travel,Business,3106,2,2,2,2,2,4,3,2,2,3,2,4,2,3,106,125.0,neutral or dissatisfied +60366,3407,Female,Loyal Customer,29,Personal Travel,Eco,315,5,5,5,4,2,5,2,2,4,5,4,3,4,2,0,13.0,satisfied +60367,112231,Female,Loyal Customer,33,Personal Travel,Eco Plus,1199,2,1,1,2,2,1,2,2,1,3,3,1,3,2,4,,neutral or dissatisfied +60368,62466,Female,Loyal Customer,57,Business travel,Business,1846,4,4,4,4,5,3,5,4,4,4,4,5,4,4,16,4.0,satisfied +60369,115395,Male,Loyal Customer,58,Business travel,Business,2959,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +60370,25967,Female,Loyal Customer,33,Personal Travel,Eco,946,1,1,1,3,4,1,4,4,3,3,3,1,3,4,6,0.0,neutral or dissatisfied +60371,53924,Male,Loyal Customer,35,Business travel,Eco Plus,140,5,3,3,3,5,4,5,5,1,5,4,3,5,5,0,0.0,satisfied +60372,127708,Male,Loyal Customer,47,Business travel,Business,1778,4,4,4,4,5,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +60373,15930,Male,Loyal Customer,25,Business travel,Eco,738,3,5,5,5,3,3,3,2,5,4,3,3,4,3,420,416.0,neutral or dissatisfied +60374,74437,Male,Loyal Customer,37,Business travel,Business,1679,3,5,4,5,3,3,3,1,1,3,2,3,2,3,133,119.0,neutral or dissatisfied +60375,63184,Male,Loyal Customer,33,Business travel,Eco,447,1,0,0,3,4,0,4,4,1,2,4,1,4,4,52,53.0,neutral or dissatisfied +60376,107049,Female,Loyal Customer,48,Business travel,Eco,480,3,1,1,1,3,3,3,1,3,1,1,3,1,3,169,134.0,neutral or dissatisfied +60377,15255,Male,Loyal Customer,34,Personal Travel,Eco,416,3,5,3,1,2,3,2,2,5,3,4,4,2,2,0,8.0,neutral or dissatisfied +60378,97374,Male,Loyal Customer,67,Personal Travel,Eco,843,3,5,2,1,1,2,1,1,5,4,4,4,5,1,33,24.0,neutral or dissatisfied +60379,107560,Male,Loyal Customer,55,Business travel,Eco,1521,4,5,5,5,4,4,4,4,4,1,4,1,4,4,12,12.0,neutral or dissatisfied +60380,44183,Male,Loyal Customer,71,Business travel,Business,157,2,2,2,2,3,3,4,5,5,5,3,3,5,2,1,6.0,satisfied +60381,118933,Female,disloyal Customer,28,Business travel,Business,1618,1,1,1,1,2,1,2,2,5,4,5,4,5,2,2,9.0,neutral or dissatisfied +60382,31273,Male,disloyal Customer,22,Business travel,Eco,533,3,0,3,2,4,3,4,4,4,1,4,3,3,4,0,0.0,neutral or dissatisfied +60383,61518,Male,Loyal Customer,36,Personal Travel,Eco,2442,3,4,3,5,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +60384,5835,Female,Loyal Customer,27,Business travel,Business,273,1,1,1,1,5,4,5,5,5,3,4,5,5,5,0,0.0,satisfied +60385,95041,Male,Loyal Customer,17,Personal Travel,Eco,239,3,4,3,3,4,3,1,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +60386,73678,Female,Loyal Customer,35,Business travel,Business,1753,0,5,0,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +60387,57789,Female,Loyal Customer,28,Personal Travel,Eco,2704,3,4,4,3,4,5,4,4,3,4,4,4,4,4,3,0.0,neutral or dissatisfied +60388,53422,Male,Loyal Customer,43,Business travel,Business,2419,2,2,2,2,4,5,5,2,4,5,3,5,4,5,53,62.0,satisfied +60389,58632,Female,disloyal Customer,25,Business travel,Business,867,0,5,0,2,1,0,1,1,4,4,4,5,4,1,5,0.0,satisfied +60390,47979,Male,Loyal Customer,45,Personal Travel,Eco,462,1,5,1,3,5,1,5,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +60391,125395,Female,disloyal Customer,62,Business travel,Eco,1272,2,2,2,3,4,2,4,4,3,4,2,4,2,4,13,26.0,neutral or dissatisfied +60392,40203,Male,disloyal Customer,72,Business travel,Eco,387,2,0,2,1,4,2,4,4,2,5,3,4,4,4,5,0.0,neutral or dissatisfied +60393,112477,Female,Loyal Customer,60,Personal Travel,Eco,819,4,1,4,3,3,2,3,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +60394,34497,Female,Loyal Customer,48,Personal Travel,Eco,1990,4,3,5,3,3,3,3,5,5,5,5,1,5,2,0,0.0,neutral or dissatisfied +60395,91461,Male,Loyal Customer,41,Business travel,Business,859,1,1,2,1,2,4,5,4,4,4,4,4,4,5,0,2.0,satisfied +60396,86500,Female,Loyal Customer,9,Personal Travel,Eco,760,2,4,2,3,1,2,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +60397,13018,Female,disloyal Customer,20,Business travel,Eco,438,3,0,4,1,5,4,3,5,4,5,4,4,3,5,0,0.0,neutral or dissatisfied +60398,10054,Male,Loyal Customer,51,Business travel,Eco Plus,326,3,1,1,1,3,3,3,3,1,5,3,4,3,3,15,13.0,neutral or dissatisfied +60399,41717,Male,Loyal Customer,22,Business travel,Eco Plus,1262,5,3,3,3,5,5,5,5,4,1,1,1,2,5,0,1.0,satisfied +60400,67365,Female,Loyal Customer,26,Business travel,Business,1516,3,3,3,3,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +60401,46284,Female,disloyal Customer,24,Business travel,Eco,679,1,1,1,1,4,1,4,4,4,5,5,3,5,4,0,2.0,neutral or dissatisfied +60402,13463,Male,Loyal Customer,66,Personal Travel,Eco,409,1,5,1,5,2,1,2,2,1,5,2,5,4,2,0,0.0,neutral or dissatisfied +60403,96278,Male,disloyal Customer,69,Personal Travel,Eco,666,2,3,2,4,4,2,4,4,3,2,2,2,4,4,7,0.0,neutral or dissatisfied +60404,82619,Male,Loyal Customer,29,Personal Travel,Eco,528,1,4,1,4,2,1,2,2,1,4,5,2,5,2,0,0.0,neutral or dissatisfied +60405,13973,Female,Loyal Customer,48,Business travel,Eco Plus,192,5,5,5,5,3,1,4,5,5,5,5,4,5,4,0,0.0,satisfied +60406,29671,Female,Loyal Customer,30,Personal Travel,Eco,1448,3,4,4,3,4,4,4,4,3,4,3,2,4,4,0,4.0,neutral or dissatisfied +60407,123985,Female,Loyal Customer,47,Business travel,Business,2940,4,4,3,4,3,4,5,3,3,4,5,5,3,3,0,0.0,satisfied +60408,95104,Female,Loyal Customer,56,Personal Travel,Eco,239,2,2,2,4,3,3,3,4,4,2,5,3,4,2,9,33.0,neutral or dissatisfied +60409,59993,Female,Loyal Customer,45,Personal Travel,Eco,997,2,5,2,4,2,4,4,2,2,2,2,3,2,5,13,20.0,neutral or dissatisfied +60410,122990,Male,Loyal Customer,49,Business travel,Business,2816,3,3,3,3,5,5,5,3,3,3,3,3,3,5,13,40.0,satisfied +60411,3106,Female,Loyal Customer,50,Business travel,Business,2154,5,3,5,5,3,5,4,5,5,5,5,3,5,4,88,107.0,satisfied +60412,80636,Female,disloyal Customer,21,Business travel,Eco,282,2,3,2,3,1,2,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +60413,127448,Female,Loyal Customer,30,Personal Travel,Eco Plus,1009,3,4,3,2,4,3,4,4,3,4,2,1,5,4,0,0.0,neutral or dissatisfied +60414,71992,Male,Loyal Customer,16,Personal Travel,Eco,1440,3,4,3,1,4,3,4,4,5,5,3,5,5,4,49,30.0,neutral or dissatisfied +60415,85859,Male,Loyal Customer,7,Personal Travel,Eco Plus,666,2,3,2,1,1,2,1,1,4,3,5,4,5,1,0,,neutral or dissatisfied +60416,74893,Female,Loyal Customer,52,Business travel,Business,2475,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +60417,70325,Male,Loyal Customer,48,Business travel,Business,986,2,3,3,3,5,2,3,2,2,2,2,2,2,4,55,50.0,neutral or dissatisfied +60418,49438,Female,Loyal Customer,43,Business travel,Eco,421,5,1,1,1,1,1,5,3,3,5,3,4,3,5,0,0.0,satisfied +60419,84735,Male,Loyal Customer,56,Business travel,Business,3367,5,5,5,5,4,4,5,4,4,4,4,4,4,5,9,10.0,satisfied +60420,63040,Male,Loyal Customer,42,Personal Travel,Eco,776,4,1,4,2,1,4,1,1,4,3,1,1,2,1,25,4.0,neutral or dissatisfied +60421,32370,Female,Loyal Customer,36,Business travel,Business,2724,3,3,3,3,3,2,5,5,5,5,3,4,5,5,0,0.0,satisfied +60422,13379,Female,Loyal Customer,35,Business travel,Eco Plus,946,4,4,4,4,4,4,4,4,4,5,2,3,5,4,15,0.0,satisfied +60423,15998,Male,Loyal Customer,45,Business travel,Business,1541,3,2,2,2,2,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +60424,111928,Male,Loyal Customer,36,Business travel,Business,770,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +60425,31775,Female,Loyal Customer,36,Personal Travel,Eco,602,2,3,2,2,3,2,2,3,5,3,5,2,3,3,0,0.0,neutral or dissatisfied +60426,73385,Female,Loyal Customer,34,Business travel,Business,2764,2,4,4,4,2,3,3,2,2,1,2,1,2,1,30,21.0,neutral or dissatisfied +60427,102138,Male,disloyal Customer,39,Business travel,Business,414,3,3,3,5,2,3,2,2,5,5,4,4,4,2,20,11.0,neutral or dissatisfied +60428,87491,Female,disloyal Customer,64,Business travel,Eco,321,3,1,4,4,4,4,1,4,4,1,4,2,4,4,13,4.0,neutral or dissatisfied +60429,12413,Female,disloyal Customer,24,Business travel,Eco,285,2,0,2,1,3,2,1,3,1,2,4,1,5,3,0,0.0,neutral or dissatisfied +60430,68061,Female,Loyal Customer,19,Business travel,Business,1800,4,4,4,4,4,4,4,4,4,5,5,5,4,4,6,0.0,satisfied +60431,107490,Male,Loyal Customer,54,Business travel,Eco,711,3,3,3,3,3,3,3,3,2,1,1,1,1,3,0,0.0,neutral or dissatisfied +60432,35348,Female,Loyal Customer,35,Business travel,Eco,944,2,3,3,3,2,2,2,2,4,4,2,3,2,2,55,50.0,neutral or dissatisfied +60433,18169,Female,Loyal Customer,45,Business travel,Business,2236,2,1,1,1,5,2,3,2,2,2,2,2,2,2,84,,neutral or dissatisfied +60434,60244,Female,Loyal Customer,36,Personal Travel,Eco,1709,5,4,5,1,1,5,1,1,5,5,4,2,3,1,16,3.0,satisfied +60435,97044,Female,Loyal Customer,41,Personal Travel,Business,1476,4,4,4,5,5,5,4,1,1,4,1,4,1,4,57,45.0,satisfied +60436,47867,Male,Loyal Customer,35,Business travel,Business,2464,2,2,2,2,2,4,4,2,2,2,2,3,2,2,17,7.0,neutral or dissatisfied +60437,30179,Male,disloyal Customer,32,Business travel,Eco Plus,261,3,3,3,4,3,3,3,3,3,3,3,4,3,3,7,0.0,neutral or dissatisfied +60438,112319,Male,Loyal Customer,49,Business travel,Business,2524,2,2,2,2,3,2,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +60439,17143,Male,disloyal Customer,30,Business travel,Eco,696,4,5,5,4,2,5,2,2,4,1,5,4,5,2,0,0.0,satisfied +60440,19035,Male,Loyal Customer,48,Business travel,Eco Plus,788,4,2,2,2,4,4,4,4,2,3,3,5,2,4,0,0.0,satisfied +60441,124431,Female,Loyal Customer,67,Personal Travel,Eco,1044,1,3,2,1,2,1,3,5,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +60442,93136,Male,disloyal Customer,21,Business travel,Business,1066,3,1,4,3,1,4,1,1,4,5,2,1,3,1,28,16.0,neutral or dissatisfied +60443,29862,Male,disloyal Customer,26,Business travel,Eco,548,1,4,1,4,5,1,5,5,4,5,3,1,3,5,0,2.0,neutral or dissatisfied +60444,79216,Male,Loyal Customer,50,Personal Travel,Eco,1990,1,1,1,3,1,1,1,1,4,2,3,1,2,1,0,12.0,neutral or dissatisfied +60445,106713,Male,Loyal Customer,48,Business travel,Business,3761,4,4,4,4,5,5,4,4,4,4,4,4,4,5,1,2.0,satisfied +60446,61034,Female,disloyal Customer,30,Business travel,Business,1546,0,0,0,2,2,0,2,2,4,5,5,4,5,2,3,31.0,satisfied +60447,72048,Female,Loyal Customer,49,Business travel,Business,2486,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +60448,71669,Female,Loyal Customer,70,Personal Travel,Eco,1182,3,4,3,3,5,3,2,4,4,3,4,3,4,1,0,3.0,neutral or dissatisfied +60449,71435,Male,Loyal Customer,47,Business travel,Business,3068,5,5,5,5,2,4,5,4,4,4,4,4,4,4,15,0.0,satisfied +60450,112329,Male,Loyal Customer,41,Business travel,Business,557,1,1,1,1,5,4,5,5,5,5,5,5,5,3,14,29.0,satisfied +60451,14235,Female,Loyal Customer,43,Business travel,Business,3828,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +60452,67043,Female,disloyal Customer,35,Business travel,Eco,1121,3,4,4,3,3,4,3,3,4,3,3,4,3,3,53,30.0,neutral or dissatisfied +60453,65956,Male,disloyal Customer,26,Business travel,Eco,1372,1,1,1,4,2,1,1,2,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +60454,66413,Female,Loyal Customer,63,Personal Travel,Eco,1562,4,4,4,4,2,5,5,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +60455,97328,Female,Loyal Customer,42,Business travel,Business,2005,2,2,2,2,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +60456,50671,Female,Loyal Customer,29,Personal Travel,Eco,266,2,0,2,2,5,2,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +60457,94156,Male,Loyal Customer,47,Business travel,Business,2650,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +60458,13191,Female,Loyal Customer,59,Business travel,Eco,419,2,1,3,3,3,2,3,2,2,2,2,4,2,4,13,9.0,neutral or dissatisfied +60459,46507,Female,Loyal Customer,39,Business travel,Business,125,1,1,1,1,2,5,2,5,5,5,5,1,5,2,0,0.0,satisfied +60460,127731,Male,disloyal Customer,9,Business travel,Eco,601,3,0,3,1,5,3,2,5,4,2,5,3,4,5,0,1.0,neutral or dissatisfied +60461,77751,Male,disloyal Customer,40,Business travel,Eco,413,1,0,1,1,5,1,1,5,3,2,2,2,1,5,0,0.0,neutral or dissatisfied +60462,90216,Male,Loyal Customer,36,Personal Travel,Eco,1127,3,5,3,4,4,3,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +60463,42241,Male,Loyal Customer,50,Business travel,Eco,834,4,5,5,5,4,4,4,4,1,5,2,1,1,4,0,0.0,satisfied +60464,117132,Male,Loyal Customer,35,Personal Travel,Eco,621,1,4,1,4,3,1,4,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +60465,24232,Female,disloyal Customer,34,Business travel,Eco,302,1,2,1,4,1,1,1,1,1,1,3,2,4,1,0,0.0,neutral or dissatisfied +60466,24712,Male,Loyal Customer,43,Business travel,Eco,549,5,1,1,1,5,5,5,5,2,3,1,3,1,5,0,0.0,satisfied +60467,12493,Female,Loyal Customer,35,Business travel,Eco Plus,285,5,4,4,4,5,5,5,5,5,3,1,3,2,5,0,0.0,satisfied +60468,88875,Male,Loyal Customer,58,Business travel,Business,859,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +60469,85874,Female,Loyal Customer,47,Business travel,Business,2172,2,2,2,2,2,4,5,4,4,4,4,3,4,5,5,0.0,satisfied +60470,50085,Female,Loyal Customer,34,Business travel,Business,2957,1,4,4,4,2,4,4,3,3,3,1,1,3,3,73,69.0,neutral or dissatisfied +60471,7186,Male,Loyal Customer,42,Business travel,Business,3797,0,4,1,4,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +60472,62198,Male,Loyal Customer,21,Personal Travel,Eco,2565,3,4,3,1,2,3,1,2,4,5,3,4,5,2,9,0.0,neutral or dissatisfied +60473,52720,Female,Loyal Customer,50,Business travel,Eco,406,3,1,3,3,2,4,1,3,3,3,3,1,3,1,0,0.0,satisfied +60474,98555,Male,Loyal Customer,36,Business travel,Business,3740,2,2,2,2,5,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +60475,7500,Female,Loyal Customer,28,Business travel,Eco Plus,925,2,4,4,4,2,2,2,2,1,3,3,1,3,2,7,5.0,neutral or dissatisfied +60476,17240,Male,Loyal Customer,35,Business travel,Business,1953,3,3,3,3,5,5,5,2,5,5,2,5,3,5,142,123.0,satisfied +60477,15966,Female,disloyal Customer,19,Business travel,Eco Plus,607,4,0,4,4,4,1,2,5,4,4,3,2,1,2,142,145.0,neutral or dissatisfied +60478,11656,Female,Loyal Customer,34,Business travel,Eco,837,4,1,1,1,4,4,4,4,4,4,2,2,3,4,0,0.0,satisfied +60479,37519,Male,Loyal Customer,43,Business travel,Business,1638,3,1,5,1,5,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +60480,119525,Male,Loyal Customer,59,Business travel,Business,359,2,2,2,2,1,2,1,2,2,3,2,2,2,4,6,49.0,neutral or dissatisfied +60481,122,Male,Loyal Customer,17,Personal Travel,Eco,562,4,4,4,3,4,4,3,4,4,2,5,3,4,4,3,6.0,neutral or dissatisfied +60482,58160,Male,disloyal Customer,29,Business travel,Business,925,4,4,4,1,4,4,5,4,5,4,5,4,5,4,21,25.0,satisfied +60483,118377,Female,Loyal Customer,23,Business travel,Business,621,3,3,3,3,5,5,5,5,5,3,4,4,5,5,0,3.0,satisfied +60484,25035,Male,Loyal Customer,50,Personal Travel,Eco,907,3,1,3,3,2,3,2,2,1,4,4,4,4,2,0,8.0,neutral or dissatisfied +60485,102779,Female,Loyal Customer,45,Business travel,Business,3795,1,0,0,4,2,3,3,4,4,0,4,3,4,3,13,4.0,neutral or dissatisfied +60486,86611,Male,disloyal Customer,28,Business travel,Business,746,3,3,3,3,1,3,1,1,5,4,5,4,4,1,8,20.0,neutral or dissatisfied +60487,48231,Female,Loyal Customer,22,Personal Travel,Eco,259,2,1,2,4,1,2,1,1,4,4,4,4,3,1,30,28.0,neutral or dissatisfied +60488,44000,Female,Loyal Customer,53,Business travel,Eco,349,4,4,4,4,3,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +60489,62472,Female,Loyal Customer,22,Business travel,Business,1781,3,5,3,3,5,5,5,5,5,5,4,3,5,5,3,0.0,satisfied +60490,77113,Female,Loyal Customer,43,Business travel,Eco,1081,4,3,3,3,5,3,4,4,4,4,4,1,4,5,0,0.0,satisfied +60491,88644,Female,Loyal Customer,64,Personal Travel,Eco,366,4,5,1,4,3,4,3,4,4,1,4,2,4,5,0,0.0,satisfied +60492,20307,Female,disloyal Customer,45,Business travel,Eco,622,0,0,0,2,3,0,3,3,3,2,3,2,2,3,75,69.0,satisfied +60493,89433,Male,Loyal Customer,63,Personal Travel,Eco,302,1,5,1,3,1,1,1,1,3,5,5,5,4,1,12,6.0,neutral or dissatisfied +60494,99883,Male,disloyal Customer,26,Business travel,Business,738,5,5,5,2,3,5,1,3,5,4,4,4,4,3,0,13.0,satisfied +60495,5370,Male,disloyal Customer,26,Business travel,Eco,785,3,3,3,3,3,3,2,3,3,4,3,2,4,3,0,0.0,neutral or dissatisfied +60496,23401,Female,Loyal Customer,15,Personal Travel,Eco,300,3,3,3,4,1,3,1,1,4,2,3,1,3,1,19,30.0,neutral or dissatisfied +60497,77965,Female,Loyal Customer,47,Business travel,Business,3790,3,2,4,2,3,3,3,3,3,3,3,4,3,4,6,0.0,neutral or dissatisfied +60498,116836,Male,Loyal Customer,49,Business travel,Business,369,2,2,2,2,2,3,3,2,2,2,2,2,2,2,80,69.0,neutral or dissatisfied +60499,116204,Female,Loyal Customer,49,Personal Travel,Eco,373,3,4,3,4,1,3,2,4,4,3,5,3,4,3,3,0.0,neutral or dissatisfied +60500,110763,Male,disloyal Customer,25,Business travel,Eco,997,2,2,2,4,1,2,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +60501,109804,Male,Loyal Customer,55,Business travel,Business,1033,2,2,2,2,4,5,5,3,3,3,3,4,3,5,15,6.0,satisfied +60502,38008,Male,Loyal Customer,11,Business travel,Business,1237,3,3,3,3,5,5,5,5,4,1,2,3,1,5,0,0.0,satisfied +60503,113563,Male,disloyal Customer,36,Business travel,Business,223,3,3,3,3,4,3,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +60504,21393,Female,Loyal Customer,25,Business travel,Business,2238,3,2,3,3,4,4,3,4,3,4,3,3,4,4,0,0.0,satisfied +60505,119671,Female,Loyal Customer,54,Business travel,Business,2190,5,5,5,5,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +60506,98653,Female,Loyal Customer,54,Business travel,Business,3419,5,5,5,5,2,5,2,4,4,4,4,2,4,5,0,0.0,satisfied +60507,74265,Female,disloyal Customer,29,Business travel,Eco,748,2,2,2,4,4,2,4,4,3,3,4,2,4,4,35,35.0,neutral or dissatisfied +60508,126593,Female,disloyal Customer,27,Business travel,Business,1337,3,4,4,2,2,4,2,2,3,4,4,3,5,2,23,20.0,neutral or dissatisfied +60509,59448,Female,Loyal Customer,26,Business travel,Business,811,5,5,5,5,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +60510,70955,Male,Loyal Customer,50,Personal Travel,Eco Plus,612,2,5,2,3,5,2,5,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +60511,65609,Female,disloyal Customer,22,Business travel,Eco,175,1,0,1,3,3,1,2,3,1,1,5,4,2,3,0,0.0,neutral or dissatisfied +60512,105047,Male,Loyal Customer,57,Personal Travel,Eco,255,2,5,2,3,2,2,2,2,4,5,5,2,5,2,2,0.0,neutral or dissatisfied +60513,62389,Female,Loyal Customer,39,Business travel,Business,1204,1,1,1,1,2,3,4,1,1,1,1,2,1,3,0,10.0,neutral or dissatisfied +60514,115047,Male,Loyal Customer,46,Business travel,Business,2492,4,4,4,4,5,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +60515,24312,Male,Loyal Customer,47,Personal Travel,Eco Plus,151,1,5,1,5,1,1,1,1,4,2,4,4,4,1,19,12.0,neutral or dissatisfied +60516,38277,Male,Loyal Customer,50,Personal Travel,Eco,1111,2,5,1,2,1,3,5,3,4,5,4,5,3,5,579,561.0,neutral or dissatisfied +60517,94391,Male,Loyal Customer,54,Business travel,Business,189,2,2,4,2,5,5,5,4,4,4,5,3,4,4,0,0.0,satisfied +60518,90576,Male,Loyal Customer,44,Business travel,Business,581,4,1,4,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +60519,49296,Female,Loyal Customer,51,Business travel,Business,86,4,4,4,4,3,1,1,5,5,5,5,3,5,1,0,0.0,satisfied +60520,115471,Female,Loyal Customer,34,Business travel,Business,447,3,5,5,5,5,4,3,3,3,3,3,2,3,1,79,81.0,neutral or dissatisfied +60521,4526,Male,disloyal Customer,23,Business travel,Eco,677,2,2,2,2,4,2,2,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +60522,26136,Male,Loyal Customer,22,Business travel,Eco,515,0,5,0,3,3,0,1,3,2,3,5,5,2,3,5,6.0,satisfied +60523,72892,Male,disloyal Customer,57,Business travel,Business,689,2,2,2,3,4,2,4,4,1,5,3,3,3,4,114,93.0,neutral or dissatisfied +60524,39131,Male,Loyal Customer,32,Business travel,Eco,190,5,2,2,2,5,5,5,5,1,3,5,1,1,5,0,0.0,satisfied +60525,105219,Female,Loyal Customer,32,Business travel,Business,377,3,3,5,3,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +60526,4789,Male,Loyal Customer,45,Personal Travel,Eco,438,3,4,3,1,2,3,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +60527,61082,Male,Loyal Customer,48,Business travel,Business,2636,4,4,4,4,2,4,1,4,4,5,3,1,4,4,0,0.0,satisfied +60528,56469,Male,Loyal Customer,35,Personal Travel,Eco Plus,719,5,4,5,3,5,4,5,5,3,5,4,3,4,5,0,0.0,satisfied +60529,109513,Male,disloyal Customer,47,Business travel,Eco,993,4,5,5,3,5,5,5,5,2,4,3,4,2,5,0,0.0,neutral or dissatisfied +60530,117719,Male,Loyal Customer,44,Business travel,Business,3102,3,3,3,3,5,5,4,4,4,4,4,5,4,3,41,54.0,satisfied +60531,35282,Female,Loyal Customer,69,Business travel,Eco,1035,5,1,1,1,4,5,1,5,5,5,5,4,5,1,0,0.0,satisfied +60532,40719,Female,Loyal Customer,39,Business travel,Business,584,4,4,4,4,1,3,2,3,3,3,3,3,3,5,0,0.0,satisfied +60533,1559,Female,Loyal Customer,24,Personal Travel,Eco Plus,862,3,1,3,2,3,3,3,3,2,1,1,3,1,3,29,18.0,neutral or dissatisfied +60534,122003,Male,disloyal Customer,21,Business travel,Eco,130,2,4,2,4,3,2,3,3,3,4,5,5,5,3,15,18.0,neutral or dissatisfied +60535,37757,Male,Loyal Customer,45,Business travel,Eco Plus,1069,4,1,1,1,5,4,5,5,2,3,5,3,2,5,15,18.0,satisfied +60536,88607,Male,Loyal Customer,67,Personal Travel,Eco,594,2,5,2,2,5,2,5,5,2,2,5,4,1,5,3,6.0,neutral or dissatisfied +60537,87453,Female,Loyal Customer,45,Business travel,Business,1566,0,0,0,1,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +60538,22227,Female,disloyal Customer,22,Business travel,Eco Plus,633,3,3,3,4,5,3,5,5,3,2,4,4,3,5,34,20.0,neutral or dissatisfied +60539,15186,Male,Loyal Customer,18,Business travel,Eco,544,4,5,5,5,4,4,4,4,1,4,4,5,3,4,77,49.0,satisfied +60540,12643,Male,Loyal Customer,51,Personal Travel,Eco,844,2,5,2,2,2,2,2,2,5,4,4,3,4,2,2,0.0,neutral or dissatisfied +60541,13852,Male,Loyal Customer,22,Business travel,Business,2106,4,4,1,4,5,5,5,5,4,2,2,2,4,5,14,2.0,satisfied +60542,14434,Male,Loyal Customer,40,Business travel,Eco,674,5,3,3,3,5,5,5,5,4,5,1,5,4,5,5,4.0,satisfied +60543,4288,Female,Loyal Customer,29,Personal Travel,Eco,502,4,5,5,5,2,5,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +60544,58874,Female,Loyal Customer,43,Business travel,Business,888,3,3,3,3,5,5,4,3,3,3,3,3,3,3,107,115.0,satisfied +60545,89991,Male,Loyal Customer,50,Business travel,Business,2982,3,3,3,3,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +60546,41065,Female,Loyal Customer,64,Business travel,Business,3240,1,1,1,1,5,3,2,1,1,1,1,4,1,4,93,86.0,neutral or dissatisfied +60547,77857,Male,Loyal Customer,14,Personal Travel,Eco Plus,813,4,4,3,4,5,3,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +60548,16433,Female,Loyal Customer,28,Business travel,Business,3098,2,2,5,2,2,2,2,2,1,4,3,1,3,2,0,5.0,neutral or dissatisfied +60549,87820,Male,Loyal Customer,47,Business travel,Business,214,2,2,4,2,5,3,3,1,1,2,2,1,1,2,0,0.0,neutral or dissatisfied +60550,106570,Female,disloyal Customer,24,Business travel,Eco,1506,2,2,2,4,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +60551,39034,Male,Loyal Customer,69,Personal Travel,Eco,230,2,4,2,2,1,2,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +60552,61972,Female,Loyal Customer,48,Business travel,Business,2586,5,5,5,5,2,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +60553,21520,Female,Loyal Customer,66,Personal Travel,Eco,399,3,3,3,2,4,1,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +60554,4424,Male,disloyal Customer,34,Business travel,Business,762,4,4,4,4,5,4,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +60555,101692,Female,Loyal Customer,62,Business travel,Eco,1100,4,5,5,5,2,1,2,4,4,4,4,3,4,3,14,0.0,neutral or dissatisfied +60556,128276,Male,Loyal Customer,38,Personal Travel,Business,338,1,4,1,4,2,5,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +60557,74281,Female,Loyal Customer,44,Business travel,Business,2288,4,4,4,4,5,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +60558,21482,Female,disloyal Customer,22,Business travel,Eco,164,2,2,2,3,2,2,2,2,4,2,4,3,3,2,97,85.0,neutral or dissatisfied +60559,68592,Male,Loyal Customer,34,Business travel,Eco Plus,1616,4,1,1,1,4,3,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +60560,677,Female,disloyal Customer,24,Business travel,Eco,309,1,5,1,2,4,1,2,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +60561,14772,Female,Loyal Customer,22,Business travel,Eco,694,5,1,1,1,5,5,3,5,3,2,2,3,1,5,0,0.0,satisfied +60562,56827,Male,Loyal Customer,36,Personal Travel,Eco,1605,2,5,2,3,4,2,4,4,4,2,4,4,4,4,5,29.0,neutral or dissatisfied +60563,93173,Female,Loyal Customer,30,Personal Travel,Eco,1183,3,4,3,3,5,3,2,5,4,2,3,3,5,5,16,12.0,neutral or dissatisfied +60564,116815,Male,Loyal Customer,27,Business travel,Business,3588,2,2,2,2,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +60565,62677,Female,Loyal Customer,24,Personal Travel,Eco Plus,1744,3,5,3,3,3,3,3,3,4,5,5,5,5,3,13,0.0,neutral or dissatisfied +60566,67303,Male,Loyal Customer,38,Business travel,Eco Plus,1121,2,4,4,4,2,3,2,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +60567,88200,Female,Loyal Customer,50,Business travel,Business,250,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +60568,107815,Female,Loyal Customer,61,Business travel,Eco,349,1,0,0,3,1,4,3,4,4,1,4,1,4,4,2,0.0,neutral or dissatisfied +60569,87813,Male,Loyal Customer,58,Business travel,Business,214,2,2,2,2,3,4,5,5,5,5,4,5,5,4,9,1.0,satisfied +60570,74588,Male,Loyal Customer,39,Business travel,Business,1438,4,4,4,4,1,3,4,4,4,3,4,2,4,2,0,1.0,neutral or dissatisfied +60571,8062,Female,Loyal Customer,35,Business travel,Business,2162,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,12.0,satisfied +60572,121682,Female,Loyal Customer,65,Personal Travel,Eco,511,5,5,5,4,2,5,5,1,1,5,2,4,1,3,0,0.0,satisfied +60573,18659,Male,Loyal Customer,62,Personal Travel,Eco,253,3,5,3,2,4,3,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +60574,98712,Female,Loyal Customer,31,Business travel,Business,993,5,5,5,5,4,4,4,4,5,5,4,3,4,4,0,3.0,satisfied +60575,92000,Female,disloyal Customer,24,Business travel,Eco,236,2,3,2,3,2,2,2,2,3,1,4,4,4,2,4,0.0,neutral or dissatisfied +60576,125238,Female,disloyal Customer,22,Business travel,Eco,749,2,2,2,3,4,2,4,4,2,4,3,1,4,4,0,13.0,neutral or dissatisfied +60577,43916,Female,Loyal Customer,28,Personal Travel,Eco,153,1,2,0,2,4,0,4,4,2,3,1,1,1,4,0,0.0,neutral or dissatisfied +60578,93438,Female,Loyal Customer,76,Business travel,Business,205,2,2,2,2,1,5,2,4,4,4,5,3,4,4,0,0.0,satisfied +60579,35604,Male,Loyal Customer,58,Personal Travel,Eco Plus,950,3,4,3,4,4,3,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +60580,42595,Male,Loyal Customer,37,Personal Travel,Eco,1154,2,4,2,4,4,2,4,4,2,2,2,1,4,4,20,41.0,neutral or dissatisfied +60581,45890,Female,disloyal Customer,41,Business travel,Eco,641,1,5,1,5,3,1,2,3,3,2,4,5,3,3,21,13.0,neutral or dissatisfied +60582,55139,Female,Loyal Customer,56,Personal Travel,Eco,1379,3,5,3,2,4,4,4,3,3,3,4,3,3,4,18,1.0,neutral or dissatisfied +60583,57131,Male,Loyal Customer,66,Personal Travel,Eco,1222,1,2,1,4,2,1,2,2,2,4,3,3,4,2,0,0.0,neutral or dissatisfied +60584,96317,Female,Loyal Customer,52,Personal Travel,Eco Plus,328,3,5,5,4,4,4,4,2,2,5,2,5,2,2,21,17.0,neutral or dissatisfied +60585,58338,Male,Loyal Customer,25,Business travel,Business,315,4,3,3,3,4,4,4,4,2,1,4,3,3,4,0,10.0,neutral or dissatisfied +60586,95273,Male,Loyal Customer,52,Personal Travel,Eco,323,4,3,4,3,4,4,4,4,5,5,5,2,4,4,1,0.0,neutral or dissatisfied +60587,99021,Male,Loyal Customer,30,Personal Travel,Business,1009,2,4,2,1,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +60588,2965,Female,Loyal Customer,38,Personal Travel,Eco,835,3,5,3,3,5,3,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +60589,40915,Male,Loyal Customer,36,Personal Travel,Eco,584,1,1,2,2,3,2,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +60590,57163,Female,Loyal Customer,47,Business travel,Business,2227,1,1,1,1,2,3,5,5,5,5,5,3,5,3,2,0.0,satisfied +60591,84885,Male,Loyal Customer,31,Personal Travel,Eco,516,2,4,2,3,2,2,2,2,1,5,2,1,2,2,23,20.0,neutral or dissatisfied +60592,92576,Female,Loyal Customer,44,Business travel,Business,1892,5,5,5,5,4,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +60593,70174,Female,Loyal Customer,42,Business travel,Business,258,0,0,0,3,4,5,4,3,2,4,4,4,3,4,183,187.0,satisfied +60594,48010,Male,Loyal Customer,20,Personal Travel,Eco Plus,329,2,4,2,2,1,2,1,1,5,2,1,5,5,1,0,0.0,neutral or dissatisfied +60595,103026,Male,Loyal Customer,61,Business travel,Eco,786,1,1,1,1,1,1,1,1,3,2,2,2,3,1,33,26.0,neutral or dissatisfied +60596,70905,Female,Loyal Customer,53,Personal Travel,Eco,1721,0,4,0,4,4,5,5,3,3,0,5,5,3,5,84,86.0,satisfied +60597,106595,Female,Loyal Customer,46,Business travel,Business,986,2,2,2,2,3,4,5,3,3,4,3,5,3,5,47,41.0,satisfied +60598,34883,Female,Loyal Customer,41,Personal Travel,Eco Plus,2248,4,4,4,5,4,1,1,4,1,3,3,1,3,1,14,28.0,neutral or dissatisfied +60599,115879,Male,Loyal Customer,31,Business travel,Business,1609,5,5,5,5,5,5,5,5,5,3,4,2,4,5,0,0.0,satisfied +60600,4748,Male,Loyal Customer,21,Personal Travel,Eco,888,4,1,4,4,4,4,4,4,1,4,3,1,4,4,0,0.0,neutral or dissatisfied +60601,38703,Male,Loyal Customer,36,Business travel,Business,2583,3,4,4,4,3,3,3,4,1,1,2,3,1,3,192,179.0,neutral or dissatisfied +60602,106,Male,disloyal Customer,24,Business travel,Business,562,4,0,4,2,5,4,4,5,5,4,5,3,4,5,96,95.0,satisfied +60603,127478,Female,Loyal Customer,27,Business travel,Business,2075,2,2,2,2,2,2,2,2,3,4,2,1,4,2,0,0.0,neutral or dissatisfied +60604,53554,Female,Loyal Customer,54,Personal Travel,Eco,1956,1,5,1,4,1,1,1,1,2,2,5,1,3,1,140,94.0,neutral or dissatisfied +60605,105870,Male,Loyal Customer,31,Personal Travel,Eco Plus,925,1,4,1,5,2,1,2,2,3,3,5,4,4,2,44,17.0,neutral or dissatisfied +60606,114761,Female,disloyal Customer,32,Business travel,Business,342,2,2,2,1,2,2,2,2,4,2,4,3,5,2,72,71.0,neutral or dissatisfied +60607,40402,Female,Loyal Customer,42,Business travel,Business,188,2,2,2,2,4,3,3,3,3,3,2,2,3,4,0,1.0,neutral or dissatisfied +60608,50568,Male,Loyal Customer,38,Personal Travel,Eco,86,2,4,2,4,4,2,1,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +60609,27307,Male,Loyal Customer,25,Business travel,Business,954,3,3,3,3,4,4,4,4,2,3,2,1,1,4,0,0.0,satisfied +60610,41721,Female,Loyal Customer,9,Personal Travel,Business,695,2,4,1,2,2,1,2,2,3,2,5,3,4,2,1,0.0,neutral or dissatisfied +60611,96468,Female,Loyal Customer,58,Business travel,Business,436,1,1,1,1,2,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +60612,41084,Male,Loyal Customer,43,Business travel,Business,667,2,2,2,2,3,4,5,4,4,4,4,4,4,4,34,32.0,satisfied +60613,112021,Female,Loyal Customer,38,Business travel,Business,3385,2,2,2,2,1,3,4,2,2,2,2,3,2,3,5,0.0,neutral or dissatisfied +60614,29825,Female,Loyal Customer,60,Business travel,Business,2414,2,2,2,2,1,3,4,3,3,4,5,1,3,3,0,0.0,satisfied +60615,1042,Male,Loyal Customer,37,Business travel,Business,3988,5,5,5,5,5,5,1,4,4,4,4,3,4,2,0,0.0,satisfied +60616,113088,Male,Loyal Customer,25,Business travel,Business,3093,1,3,3,3,1,1,1,1,3,5,3,2,4,1,6,0.0,neutral or dissatisfied +60617,20374,Female,Loyal Customer,39,Personal Travel,Eco,265,2,2,0,4,2,0,2,2,2,4,4,4,4,2,57,49.0,neutral or dissatisfied +60618,51014,Male,Loyal Customer,26,Personal Travel,Eco,109,3,4,3,4,5,3,5,5,3,3,5,2,1,5,7,0.0,neutral or dissatisfied +60619,27074,Female,disloyal Customer,29,Business travel,Eco Plus,1399,2,2,2,3,1,2,1,1,1,3,3,3,3,1,0,26.0,neutral or dissatisfied +60620,24336,Male,disloyal Customer,15,Business travel,Eco,634,1,5,1,4,4,1,3,4,5,1,3,4,3,4,34,39.0,neutral or dissatisfied +60621,48481,Male,disloyal Customer,30,Business travel,Eco,819,0,0,0,2,2,0,1,2,1,1,5,1,5,2,12,0.0,satisfied +60622,15652,Male,Loyal Customer,37,Business travel,Eco,258,5,2,2,2,5,5,5,5,3,4,3,5,5,5,0,0.0,satisfied +60623,70804,Male,Loyal Customer,41,Personal Travel,Eco Plus,328,3,0,3,3,4,3,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +60624,124288,Female,Loyal Customer,49,Business travel,Business,3555,3,4,4,4,5,4,4,3,3,3,3,1,3,2,0,2.0,neutral or dissatisfied +60625,46171,Male,Loyal Customer,67,Personal Travel,Eco,604,3,4,3,3,4,3,4,4,5,3,5,4,5,4,0,3.0,neutral or dissatisfied +60626,37383,Female,disloyal Customer,27,Business travel,Eco,1056,1,1,1,4,3,1,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +60627,80783,Female,Loyal Customer,31,Business travel,Business,692,5,5,5,5,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +60628,10514,Female,disloyal Customer,40,Business travel,Business,247,4,4,4,2,3,4,2,3,5,5,4,3,4,3,34,31.0,neutral or dissatisfied +60629,33646,Female,Loyal Customer,37,Personal Travel,Eco,399,3,2,3,3,1,3,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +60630,109409,Female,Loyal Customer,56,Business travel,Business,994,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +60631,58463,Female,Loyal Customer,56,Personal Travel,Eco Plus,733,4,5,4,3,5,3,4,5,5,4,5,3,5,3,3,0.0,neutral or dissatisfied +60632,33477,Male,Loyal Customer,31,Business travel,Business,2422,2,2,2,2,5,5,5,5,5,5,5,1,2,5,14,5.0,satisfied +60633,38297,Male,disloyal Customer,20,Business travel,Eco,717,2,2,2,3,2,2,2,4,3,5,5,2,4,2,0,29.0,neutral or dissatisfied +60634,22848,Male,Loyal Customer,38,Personal Travel,Eco,302,3,1,3,3,2,3,2,2,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +60635,28656,Male,Loyal Customer,44,Personal Travel,Eco,2614,3,5,3,3,4,3,4,4,5,5,3,3,4,4,0,0.0,neutral or dissatisfied +60636,79897,Male,Loyal Customer,29,Business travel,Business,2147,3,3,3,3,5,5,5,5,5,5,4,4,4,5,0,38.0,satisfied +60637,126116,Female,disloyal Customer,27,Business travel,Business,328,1,1,1,5,1,1,3,5,5,4,5,3,4,3,171,159.0,neutral or dissatisfied +60638,100311,Male,disloyal Customer,19,Business travel,Eco,971,4,4,4,4,3,4,3,3,2,1,3,4,4,3,29,31.0,neutral or dissatisfied +60639,8866,Female,Loyal Customer,50,Business travel,Business,3829,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,12.0,satisfied +60640,29279,Male,disloyal Customer,27,Business travel,Eco,859,3,3,3,3,5,3,5,5,4,5,2,4,3,5,79,76.0,neutral or dissatisfied +60641,119495,Male,Loyal Customer,51,Business travel,Business,759,2,3,3,3,5,4,4,2,2,2,2,2,2,4,0,2.0,neutral or dissatisfied +60642,108053,Male,Loyal Customer,66,Personal Travel,Eco,591,4,5,5,2,3,5,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +60643,122474,Male,Loyal Customer,35,Business travel,Business,3023,1,2,2,2,3,2,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +60644,25986,Male,disloyal Customer,34,Business travel,Eco,577,2,0,2,1,2,2,2,2,5,3,4,1,2,2,0,0.0,neutral or dissatisfied +60645,74205,Male,Loyal Customer,52,Business travel,Eco Plus,721,3,1,4,1,3,3,3,3,3,5,3,1,3,3,1,0.0,neutral or dissatisfied +60646,18285,Male,Loyal Customer,25,Business travel,Eco,705,0,4,0,3,1,0,1,1,2,3,3,1,4,1,0,0.0,satisfied +60647,94236,Female,Loyal Customer,43,Business travel,Business,248,0,0,0,4,4,4,5,3,3,2,2,4,3,4,20,15.0,satisfied +60648,116195,Male,Loyal Customer,41,Personal Travel,Eco,447,4,3,4,3,4,4,4,4,2,1,1,1,2,4,33,26.0,neutral or dissatisfied +60649,18257,Female,Loyal Customer,19,Personal Travel,Eco,179,4,4,4,4,5,4,5,5,4,4,4,4,4,5,0,14.0,satisfied +60650,123509,Female,Loyal Customer,23,Personal Travel,Eco,2296,3,4,3,3,3,2,2,3,2,5,5,2,3,2,0,9.0,neutral or dissatisfied +60651,61458,Female,Loyal Customer,53,Business travel,Business,2419,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +60652,113853,Male,Loyal Customer,47,Business travel,Business,1592,2,2,2,2,2,4,5,5,5,5,5,5,5,5,25,0.0,satisfied +60653,101587,Female,Loyal Customer,31,Personal Travel,Eco,1099,3,1,3,4,5,3,5,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +60654,49244,Female,Loyal Customer,37,Business travel,Business,2380,1,1,1,1,5,2,3,5,5,5,4,3,5,2,17,16.0,satisfied +60655,91305,Female,disloyal Customer,21,Business travel,Business,271,5,4,5,1,1,5,1,1,3,3,5,5,5,1,0,0.0,satisfied +60656,64822,Female,Loyal Customer,56,Business travel,Business,2657,1,1,1,1,2,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +60657,25228,Male,disloyal Customer,30,Business travel,Eco,925,5,5,5,1,3,5,3,3,4,2,4,1,5,3,0,4.0,satisfied +60658,69989,Male,Loyal Customer,49,Business travel,Eco,236,4,3,3,3,4,4,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +60659,95681,Female,Loyal Customer,37,Business travel,Business,2287,1,1,1,1,2,4,4,5,5,5,4,4,5,4,0,0.0,satisfied +60660,21954,Female,Loyal Customer,49,Business travel,Eco,551,4,1,1,1,5,2,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +60661,68044,Male,Loyal Customer,35,Business travel,Business,868,4,4,3,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +60662,101172,Male,Loyal Customer,39,Business travel,Business,1090,3,3,3,3,3,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +60663,42345,Male,Loyal Customer,28,Personal Travel,Eco,550,2,1,2,3,3,2,3,3,3,2,2,1,2,3,0,10.0,neutral or dissatisfied +60664,53489,Female,Loyal Customer,62,Personal Travel,Eco,2288,3,4,3,5,3,3,2,2,2,3,2,1,2,5,40,35.0,neutral or dissatisfied +60665,67925,Male,Loyal Customer,32,Personal Travel,Eco,1205,5,3,5,2,5,5,5,5,5,3,1,4,3,5,0,0.0,satisfied +60666,63612,Female,Loyal Customer,65,Business travel,Business,1440,2,3,3,3,2,2,2,2,2,2,2,2,2,1,68,83.0,neutral or dissatisfied +60667,128448,Male,disloyal Customer,36,Business travel,Eco,325,3,0,3,1,1,3,1,1,3,1,5,3,5,1,0,0.0,neutral or dissatisfied +60668,128270,Male,Loyal Customer,44,Business travel,Business,3966,3,4,4,4,5,3,3,3,3,3,3,2,3,1,60,67.0,neutral or dissatisfied +60669,92976,Female,disloyal Customer,24,Business travel,Eco,738,2,2,2,3,4,2,4,4,4,3,4,5,4,4,26,21.0,neutral or dissatisfied +60670,38747,Female,Loyal Customer,30,Business travel,Business,3659,3,1,1,1,3,3,3,3,3,1,3,1,4,3,0,4.0,neutral or dissatisfied +60671,73894,Male,disloyal Customer,42,Business travel,Business,2342,3,3,3,2,3,2,2,4,3,4,5,2,5,2,38,71.0,neutral or dissatisfied +60672,44677,Male,Loyal Customer,59,Business travel,Business,3023,5,5,5,5,5,2,4,4,4,4,3,3,4,4,0,0.0,satisfied +60673,12038,Male,Loyal Customer,62,Business travel,Business,2923,5,5,5,5,5,4,3,4,4,4,4,3,4,3,0,0.0,satisfied +60674,42340,Male,Loyal Customer,31,Personal Travel,Eco,834,1,5,1,2,1,1,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +60675,57095,Male,Loyal Customer,36,Business travel,Business,1837,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +60676,122062,Female,Loyal Customer,61,Business travel,Business,3258,1,1,1,1,1,1,2,5,5,5,4,2,5,4,6,11.0,satisfied +60677,62951,Female,disloyal Customer,25,Business travel,Business,967,0,0,0,4,3,0,3,3,5,2,4,5,4,3,11,5.0,satisfied +60678,59819,Female,Loyal Customer,45,Personal Travel,Business,1085,3,5,2,3,3,4,5,4,4,2,4,4,4,3,23,0.0,neutral or dissatisfied +60679,64459,Female,Loyal Customer,56,Business travel,Business,989,5,5,5,5,2,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +60680,23471,Male,disloyal Customer,36,Business travel,Eco,176,1,3,1,4,3,1,2,3,2,1,3,3,3,3,16,17.0,neutral or dissatisfied +60681,122607,Female,Loyal Customer,29,Business travel,Business,2947,5,1,1,1,5,4,5,5,2,2,3,3,4,5,0,0.0,neutral or dissatisfied +60682,36384,Male,Loyal Customer,59,Personal Travel,Eco,200,3,5,3,3,1,3,1,1,1,4,1,4,4,1,0,0.0,neutral or dissatisfied +60683,32956,Female,Loyal Customer,48,Personal Travel,Eco,102,2,4,2,4,2,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +60684,53953,Male,disloyal Customer,39,Business travel,Eco,1325,3,3,3,1,3,3,4,3,2,2,2,5,5,3,37,21.0,satisfied +60685,11053,Female,Loyal Customer,58,Personal Travel,Eco,308,2,4,2,3,4,4,5,5,5,2,5,5,5,5,5,9.0,neutral or dissatisfied +60686,113699,Male,Loyal Customer,18,Personal Travel,Eco,197,2,4,2,1,5,2,5,5,4,3,5,5,5,5,1,7.0,neutral or dissatisfied +60687,126834,Female,Loyal Customer,66,Business travel,Eco,2125,4,4,4,4,4,2,3,4,4,4,4,1,4,3,1,0.0,neutral or dissatisfied +60688,93517,Male,Loyal Customer,19,Personal Travel,Eco Plus,1020,3,4,3,1,1,3,1,1,2,4,2,5,1,1,5,0.0,neutral or dissatisfied +60689,32118,Male,disloyal Customer,33,Business travel,Eco,163,4,0,5,4,4,5,2,4,1,2,3,2,5,4,0,0.0,neutral or dissatisfied +60690,5213,Female,disloyal Customer,36,Business travel,Business,293,2,2,2,5,2,2,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +60691,35563,Female,disloyal Customer,13,Business travel,Eco Plus,1118,2,0,2,4,3,2,3,3,5,1,3,2,4,3,17,27.0,neutral or dissatisfied +60692,1403,Male,Loyal Customer,44,Personal Travel,Eco Plus,89,2,4,2,3,4,2,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +60693,40454,Male,disloyal Customer,32,Business travel,Eco,290,2,5,2,3,5,2,5,5,2,4,4,5,1,5,0,0.0,neutral or dissatisfied +60694,24562,Male,disloyal Customer,36,Business travel,Eco,474,3,5,3,3,4,3,1,4,2,5,3,2,3,4,0,5.0,neutral or dissatisfied +60695,69853,Female,Loyal Customer,43,Personal Travel,Eco,1055,1,2,1,3,4,3,3,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +60696,8465,Female,Loyal Customer,34,Personal Travel,Eco,1379,0,4,0,3,4,0,4,4,5,5,3,4,5,4,17,1.0,satisfied +60697,65716,Female,disloyal Customer,26,Business travel,Business,1061,2,2,2,2,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +60698,68630,Male,Loyal Customer,59,Business travel,Business,3790,0,0,0,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +60699,67089,Male,Loyal Customer,45,Business travel,Business,3953,4,4,4,4,2,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +60700,28146,Male,Loyal Customer,49,Business travel,Business,2926,3,4,4,4,2,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +60701,86508,Male,Loyal Customer,19,Personal Travel,Eco,760,5,3,5,3,5,5,4,5,2,3,4,1,3,5,4,0.0,satisfied +60702,120444,Male,Loyal Customer,57,Personal Travel,Eco,449,2,3,3,3,2,3,2,2,5,5,5,1,1,2,0,0.0,neutral or dissatisfied +60703,63947,Male,Loyal Customer,66,Personal Travel,Eco,1192,5,5,5,3,1,5,1,1,5,4,3,5,4,1,5,21.0,satisfied +60704,89005,Male,disloyal Customer,50,Business travel,Business,1892,4,4,4,5,4,4,4,4,4,2,4,4,5,4,0,0.0,satisfied +60705,54462,Female,Loyal Customer,48,Business travel,Eco,925,4,2,2,2,1,1,2,5,5,4,5,4,5,4,4,0.0,satisfied +60706,115750,Female,Loyal Customer,53,Business travel,Business,3637,3,1,1,1,2,3,4,3,3,3,3,3,3,2,24,10.0,neutral or dissatisfied +60707,42043,Male,Loyal Customer,62,Business travel,Business,2542,1,5,1,5,2,3,3,3,3,3,1,3,3,4,0,0.0,neutral or dissatisfied +60708,55589,Female,Loyal Customer,64,Personal Travel,Eco,1839,3,4,3,1,3,4,4,1,1,3,1,4,1,3,30,10.0,neutral or dissatisfied +60709,122504,Male,Loyal Customer,46,Business travel,Business,930,2,2,2,2,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +60710,45881,Male,Loyal Customer,42,Business travel,Business,2788,4,4,4,4,4,3,4,3,3,4,3,5,3,4,16,4.0,satisfied +60711,3501,Female,Loyal Customer,70,Personal Travel,Eco,990,5,1,5,3,4,3,3,4,4,5,3,2,4,1,0,0.0,satisfied +60712,78301,Female,Loyal Customer,26,Personal Travel,Eco,1598,4,4,4,2,5,4,5,5,3,4,3,4,4,5,0,0.0,satisfied +60713,75465,Male,Loyal Customer,63,Personal Travel,Eco,2342,3,2,3,2,1,3,3,1,3,4,2,1,2,1,0,0.0,neutral or dissatisfied +60714,102871,Male,Loyal Customer,51,Business travel,Business,2935,3,1,3,3,1,3,3,3,3,3,3,1,3,4,19,27.0,neutral or dissatisfied +60715,47489,Male,Loyal Customer,40,Personal Travel,Eco,541,4,4,4,5,2,4,1,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +60716,13201,Female,Loyal Customer,34,Personal Travel,Eco,542,3,4,3,5,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +60717,5773,Male,Loyal Customer,38,Personal Travel,Eco,665,3,4,3,4,5,3,5,5,1,3,5,2,4,5,0,0.0,neutral or dissatisfied +60718,18024,Male,Loyal Customer,46,Business travel,Business,3282,2,3,4,4,4,3,2,2,2,2,2,3,2,4,0,24.0,neutral or dissatisfied +60719,105513,Male,disloyal Customer,25,Business travel,Business,611,4,0,4,2,4,4,4,4,5,4,4,3,4,4,2,0.0,satisfied +60720,39932,Female,disloyal Customer,24,Business travel,Eco,1195,2,3,3,3,3,3,3,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +60721,23974,Male,Loyal Customer,55,Business travel,Eco,596,2,3,3,3,2,2,2,2,3,3,4,5,4,2,0,0.0,satisfied +60722,48158,Female,Loyal Customer,31,Business travel,Eco,391,0,0,0,2,3,0,3,3,1,2,3,1,2,3,0,0.0,satisfied +60723,109528,Male,Loyal Customer,46,Business travel,Eco,861,3,2,2,2,3,3,3,3,2,1,1,1,1,3,10,0.0,neutral or dissatisfied +60724,105335,Female,Loyal Customer,56,Business travel,Business,452,3,3,3,3,5,5,5,4,4,4,4,4,4,4,3,0.0,satisfied +60725,56092,Female,Loyal Customer,17,Personal Travel,Eco Plus,2586,0,4,0,1,0,4,4,3,5,3,5,4,4,4,0,1.0,satisfied +60726,102200,Female,Loyal Customer,49,Business travel,Business,3919,1,1,1,1,5,5,4,5,5,5,5,5,5,5,10,0.0,satisfied +60727,87251,Female,Loyal Customer,33,Business travel,Business,3784,1,1,1,1,3,4,5,4,4,5,4,4,4,5,5,7.0,satisfied +60728,61630,Male,Loyal Customer,52,Business travel,Business,1504,1,1,1,1,3,5,5,4,4,4,4,5,4,5,7,0.0,satisfied +60729,30994,Female,Loyal Customer,23,Business travel,Business,391,4,5,4,4,3,4,3,3,1,1,2,4,2,3,44,68.0,satisfied +60730,113002,Male,disloyal Customer,26,Business travel,Eco,1797,4,4,4,3,5,4,1,5,2,5,2,1,4,5,0,0.0,neutral or dissatisfied +60731,15859,Female,Loyal Customer,29,Business travel,Business,2829,3,3,3,3,5,5,5,5,1,1,3,3,5,5,17,36.0,satisfied +60732,10318,Female,Loyal Customer,54,Business travel,Business,1510,1,1,1,1,3,4,5,4,4,5,5,3,4,5,0,0.0,satisfied +60733,104186,Female,Loyal Customer,48,Personal Travel,Eco,349,3,4,5,4,5,4,4,5,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +60734,67761,Male,Loyal Customer,48,Business travel,Eco,1431,1,2,2,2,1,1,1,1,4,1,2,4,2,1,0,3.0,neutral or dissatisfied +60735,83103,Male,Loyal Customer,32,Personal Travel,Eco,1127,4,4,4,3,3,4,3,3,3,5,3,5,4,3,0,0.0,neutral or dissatisfied +60736,46115,Female,Loyal Customer,26,Personal Travel,Eco Plus,1201,3,1,4,2,1,4,1,1,4,5,2,3,3,1,0,0.0,neutral or dissatisfied +60737,5420,Female,disloyal Customer,20,Business travel,Eco,589,2,0,2,3,3,2,3,3,1,2,1,2,3,3,20,0.0,neutral or dissatisfied +60738,76355,Male,Loyal Customer,29,Business travel,Business,1851,4,1,1,1,4,3,4,4,2,3,4,4,4,4,0,0.0,neutral or dissatisfied +60739,2300,Female,Loyal Customer,40,Business travel,Business,690,4,2,4,2,3,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +60740,101921,Male,Loyal Customer,23,Business travel,Eco Plus,1984,0,1,1,1,0,1,2,0,1,4,4,4,3,0,0,0.0,neutral or dissatisfied +60741,73885,Female,Loyal Customer,60,Business travel,Business,2342,3,3,4,3,4,4,4,4,4,4,4,5,4,4,8,0.0,satisfied +60742,102991,Female,Loyal Customer,44,Business travel,Business,2862,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +60743,48949,Female,Loyal Customer,63,Business travel,Business,2681,1,1,1,1,5,4,1,5,5,5,5,2,5,1,5,0.0,satisfied +60744,28631,Female,Loyal Customer,15,Business travel,Business,2417,1,1,1,1,5,5,5,5,1,4,5,1,1,5,8,0.0,satisfied +60745,88515,Female,Loyal Customer,23,Personal Travel,Eco,250,0,5,0,2,2,0,2,2,2,5,4,4,1,2,70,72.0,satisfied +60746,17106,Male,Loyal Customer,29,Personal Travel,Eco,416,4,5,3,4,4,3,3,4,2,2,4,3,2,4,0,0.0,neutral or dissatisfied +60747,124732,Male,Loyal Customer,25,Personal Travel,Eco,399,3,3,3,3,1,3,1,1,1,3,3,1,3,1,13,13.0,neutral or dissatisfied +60748,56308,Male,Loyal Customer,29,Personal Travel,Eco,1882,1,2,1,4,5,1,5,5,3,4,3,4,4,5,0,0.0,neutral or dissatisfied +60749,89642,Male,Loyal Customer,39,Business travel,Business,2050,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +60750,26695,Female,Loyal Customer,69,Personal Travel,Eco,404,2,5,4,2,4,5,4,3,3,4,3,3,3,4,9,0.0,neutral or dissatisfied +60751,112565,Female,Loyal Customer,47,Personal Travel,Business,602,0,5,0,3,4,4,5,4,4,0,1,5,4,4,26,12.0,satisfied +60752,14605,Male,Loyal Customer,30,Business travel,Business,448,3,3,3,3,4,4,4,4,1,1,4,1,2,4,0,5.0,satisfied +60753,99427,Female,Loyal Customer,23,Personal Travel,Eco,337,3,5,3,4,5,3,5,5,4,2,4,3,5,5,0,1.0,neutral or dissatisfied +60754,111397,Male,Loyal Customer,41,Personal Travel,Eco,1180,3,5,3,4,2,3,2,2,3,5,4,4,4,2,8,36.0,neutral or dissatisfied +60755,29166,Male,Loyal Customer,55,Business travel,Eco Plus,679,4,5,2,5,4,4,4,4,1,1,2,4,4,4,54,68.0,satisfied +60756,102579,Female,Loyal Customer,50,Business travel,Business,414,5,5,5,5,2,4,4,3,3,3,3,3,3,5,1,0.0,satisfied +60757,99659,Female,Loyal Customer,72,Business travel,Business,3184,2,3,2,2,1,3,4,4,4,4,4,1,4,2,0,0.0,satisfied +60758,70429,Female,disloyal Customer,38,Business travel,Business,187,3,3,3,3,5,3,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +60759,117166,Male,Loyal Customer,37,Personal Travel,Eco,647,3,3,3,3,2,3,5,2,5,1,3,3,1,2,67,53.0,neutral or dissatisfied +60760,128201,Female,Loyal Customer,33,Business travel,Business,1606,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +60761,15881,Male,Loyal Customer,41,Personal Travel,Eco,332,4,1,2,4,1,2,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +60762,128881,Female,Loyal Customer,51,Business travel,Business,2565,1,1,1,1,3,3,3,3,5,3,5,3,4,3,61,67.0,satisfied +60763,3883,Male,Loyal Customer,46,Business travel,Business,2241,3,3,3,3,3,4,4,5,5,5,5,5,5,5,35,49.0,satisfied +60764,28344,Male,Loyal Customer,53,Personal Travel,Eco,867,3,4,2,3,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +60765,39346,Female,Loyal Customer,49,Business travel,Business,826,3,3,3,3,2,4,5,3,3,3,3,3,3,5,0,25.0,satisfied +60766,7340,Female,Loyal Customer,28,Business travel,Business,606,3,1,1,1,3,3,3,3,3,3,4,1,4,3,52,46.0,neutral or dissatisfied +60767,42273,Female,disloyal Customer,26,Business travel,Eco,784,3,3,3,5,5,3,5,5,1,3,3,2,1,5,0,0.0,neutral or dissatisfied +60768,124144,Male,disloyal Customer,25,Business travel,Eco Plus,529,3,4,2,4,2,2,1,2,3,3,4,4,3,2,25,26.0,neutral or dissatisfied +60769,45775,Male,Loyal Customer,35,Business travel,Business,391,1,1,1,1,2,3,3,5,5,5,5,4,5,5,3,0.0,satisfied +60770,15412,Male,Loyal Customer,46,Business travel,Business,433,4,4,4,4,2,2,1,4,4,4,4,3,4,5,0,0.0,satisfied +60771,117076,Female,disloyal Customer,29,Business travel,Eco,647,2,2,2,3,5,2,4,5,3,3,3,3,3,5,29,27.0,neutral or dissatisfied +60772,126957,Female,Loyal Customer,44,Business travel,Business,2028,0,0,0,3,2,4,4,1,1,1,1,5,1,4,0,0.0,satisfied +60773,12902,Female,Loyal Customer,23,Business travel,Business,674,5,5,5,5,4,4,4,4,1,3,1,2,5,4,30,59.0,satisfied +60774,37802,Male,Loyal Customer,52,Personal Travel,Eco Plus,1028,1,5,1,3,2,1,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +60775,41605,Female,Loyal Customer,26,Personal Travel,Eco,1428,1,4,1,3,2,1,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +60776,83127,Male,Loyal Customer,13,Personal Travel,Eco,957,1,5,1,3,5,1,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +60777,2166,Male,disloyal Customer,29,Business travel,Business,685,4,4,4,1,5,4,5,5,5,4,4,4,5,5,0,17.0,satisfied +60778,125465,Female,Loyal Customer,53,Business travel,Business,2860,3,2,4,4,5,2,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +60779,46078,Female,Loyal Customer,59,Business travel,Eco,541,4,1,1,1,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +60780,34992,Male,Loyal Customer,52,Business travel,Eco,1182,4,4,4,4,5,4,5,5,5,2,4,4,3,5,0,0.0,satisfied +60781,36111,Female,Loyal Customer,65,Personal Travel,Eco Plus,413,1,4,2,3,3,5,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +60782,128380,Female,Loyal Customer,41,Business travel,Business,1905,0,0,0,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +60783,114553,Male,Loyal Customer,47,Personal Travel,Business,362,2,5,2,3,4,4,4,4,4,2,4,3,4,3,4,0.0,neutral or dissatisfied +60784,122313,Male,disloyal Customer,39,Business travel,Business,544,4,4,4,4,4,4,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +60785,73376,Male,Loyal Customer,56,Business travel,Business,3464,4,4,3,4,2,5,5,5,5,5,5,4,5,4,3,4.0,satisfied +60786,98541,Male,Loyal Customer,8,Personal Travel,Eco,402,1,4,5,2,3,5,3,3,3,2,5,4,5,3,19,17.0,neutral or dissatisfied +60787,4590,Male,Loyal Customer,30,Business travel,Business,416,3,1,1,1,3,3,3,3,1,1,4,4,4,3,0,10.0,neutral or dissatisfied +60788,57247,Male,Loyal Customer,54,Business travel,Business,628,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +60789,8475,Female,disloyal Customer,9,Business travel,Eco,1187,4,4,4,3,1,4,1,1,1,3,4,3,4,1,0,0.0,neutral or dissatisfied +60790,71144,Female,Loyal Customer,24,Business travel,Business,3948,2,2,2,2,3,3,3,3,5,5,4,5,4,3,14,12.0,satisfied +60791,95687,Female,Loyal Customer,45,Business travel,Business,419,4,4,4,4,3,5,4,4,4,4,4,5,4,4,3,1.0,satisfied +60792,29173,Female,disloyal Customer,24,Business travel,Business,1050,2,1,2,4,3,2,3,3,2,5,4,2,4,3,0,0.0,neutral or dissatisfied +60793,31260,Female,Loyal Customer,38,Business travel,Business,533,1,1,1,1,5,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +60794,101129,Male,disloyal Customer,36,Business travel,Business,583,2,2,2,3,4,2,4,4,4,5,4,3,5,4,1,0.0,neutral or dissatisfied +60795,101762,Female,Loyal Customer,66,Personal Travel,Eco,1590,2,4,3,3,4,4,1,4,4,3,4,4,4,2,38,33.0,neutral or dissatisfied +60796,43569,Male,Loyal Customer,42,Business travel,Business,1499,1,1,4,1,4,1,3,2,2,2,2,3,2,4,0,0.0,satisfied +60797,97916,Male,Loyal Customer,51,Business travel,Business,2998,3,3,3,3,3,3,2,3,3,3,3,3,3,2,32,34.0,neutral or dissatisfied +60798,45178,Male,Loyal Customer,54,Business travel,Eco Plus,174,5,4,4,4,5,5,5,5,4,3,5,4,2,5,0,0.0,satisfied +60799,23873,Female,Loyal Customer,47,Personal Travel,Eco Plus,552,2,4,2,3,4,3,3,4,4,2,4,4,4,2,0,26.0,neutral or dissatisfied +60800,9676,Male,Loyal Customer,58,Business travel,Eco,284,1,1,1,1,1,1,1,4,2,4,4,1,1,1,235,230.0,neutral or dissatisfied +60801,42620,Female,Loyal Customer,37,Business travel,Eco,546,4,2,2,2,4,4,4,4,3,5,3,3,1,4,0,0.0,satisfied +60802,69471,Male,Loyal Customer,60,Personal Travel,Eco,1096,3,4,4,5,1,4,1,1,4,5,4,3,5,1,0,48.0,neutral or dissatisfied +60803,15404,Male,Loyal Customer,39,Business travel,Eco,164,5,4,4,4,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +60804,11883,Female,Loyal Customer,40,Personal Travel,Eco,912,3,5,3,2,1,3,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +60805,52435,Male,Loyal Customer,50,Personal Travel,Eco,370,5,4,1,4,2,1,2,2,1,3,3,1,3,2,0,0.0,satisfied +60806,71124,Male,Loyal Customer,45,Business travel,Business,1739,3,3,3,3,2,3,4,5,5,5,5,3,5,3,22,12.0,satisfied +60807,69708,Male,Loyal Customer,30,Business travel,Business,1372,1,4,2,4,1,2,1,1,2,5,2,3,2,1,25,0.0,neutral or dissatisfied +60808,47640,Male,disloyal Customer,37,Business travel,Eco,715,2,3,3,4,1,3,1,1,4,4,3,5,5,1,0,0.0,neutral or dissatisfied +60809,4408,Female,Loyal Customer,54,Business travel,Business,2551,4,2,4,4,5,4,5,2,2,2,2,3,2,5,19,42.0,satisfied +60810,35487,Male,Loyal Customer,26,Personal Travel,Eco,1069,2,4,2,3,3,2,3,3,3,2,4,4,4,3,10,3.0,neutral or dissatisfied +60811,128977,Male,Loyal Customer,44,Personal Travel,Eco,414,3,5,3,5,3,3,3,3,4,2,5,2,3,3,98,109.0,neutral or dissatisfied +60812,66528,Male,Loyal Customer,61,Personal Travel,Eco Plus,447,1,4,2,5,3,2,3,3,4,5,4,4,5,3,4,0.0,neutral or dissatisfied +60813,100640,Male,Loyal Customer,41,Business travel,Business,349,3,1,1,1,1,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +60814,30316,Male,Loyal Customer,32,Business travel,Business,3919,2,2,2,2,4,4,4,5,4,1,5,4,2,4,137,148.0,satisfied +60815,47276,Male,Loyal Customer,52,Business travel,Eco,558,4,3,3,3,4,4,4,4,1,4,3,4,3,4,0,0.0,satisfied +60816,64084,Male,Loyal Customer,29,Personal Travel,Eco,919,2,5,2,5,4,2,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +60817,16578,Male,Loyal Customer,40,Business travel,Business,472,2,2,2,2,1,1,5,4,4,4,4,2,4,3,0,0.0,satisfied +60818,56628,Male,Loyal Customer,44,Business travel,Business,2612,2,3,3,3,1,3,3,2,2,2,2,1,2,2,8,0.0,neutral or dissatisfied +60819,19733,Female,Loyal Customer,56,Personal Travel,Eco,475,3,1,3,3,1,3,2,5,5,3,5,1,5,3,0,0.0,neutral or dissatisfied +60820,21796,Male,Loyal Customer,34,Business travel,Business,2506,2,4,4,4,2,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +60821,23235,Male,Loyal Customer,69,Personal Travel,Eco,116,2,4,0,4,0,3,3,1,1,3,4,3,3,3,166,167.0,neutral or dissatisfied +60822,7465,Female,Loyal Customer,57,Business travel,Business,1766,5,5,3,5,4,5,5,5,5,5,5,3,5,3,0,37.0,satisfied +60823,73798,Female,disloyal Customer,20,Business travel,Eco,192,0,4,0,4,4,0,4,4,3,2,5,5,5,4,0,0.0,satisfied +60824,116622,Female,Loyal Customer,57,Business travel,Business,2916,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +60825,97875,Female,Loyal Customer,26,Business travel,Business,616,4,4,4,4,4,4,4,4,3,3,4,3,5,4,19,30.0,satisfied +60826,108091,Male,Loyal Customer,56,Business travel,Business,997,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +60827,61506,Male,Loyal Customer,33,Business travel,Business,2253,2,2,2,2,4,4,4,4,3,3,3,3,2,4,14,10.0,satisfied +60828,40425,Male,Loyal Customer,48,Business travel,Eco,175,2,4,4,4,2,2,2,2,5,3,2,4,5,2,0,0.0,satisfied +60829,47146,Male,disloyal Customer,18,Business travel,Eco,954,1,1,1,4,3,1,1,3,3,1,3,4,4,3,108,119.0,neutral or dissatisfied +60830,129545,Male,Loyal Customer,43,Business travel,Business,2583,3,2,2,2,3,4,4,3,3,3,3,3,3,1,31,28.0,neutral or dissatisfied +60831,22896,Male,disloyal Customer,49,Business travel,Eco Plus,302,5,5,5,1,3,5,3,3,1,4,1,2,4,3,0,0.0,satisfied +60832,104179,Female,Loyal Customer,24,Personal Travel,Eco,349,3,4,3,4,5,3,5,5,4,3,4,5,5,5,3,0.0,neutral or dissatisfied +60833,109009,Female,Loyal Customer,24,Business travel,Business,3392,1,1,3,1,4,4,4,4,4,4,4,4,5,4,12,2.0,satisfied +60834,97926,Male,Loyal Customer,39,Business travel,Business,2350,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +60835,31748,Male,Loyal Customer,70,Personal Travel,Eco Plus,967,5,5,5,3,3,5,3,3,3,2,5,4,5,3,0,0.0,satisfied +60836,30562,Female,Loyal Customer,43,Business travel,Business,2754,3,3,3,3,3,5,2,4,4,4,4,5,4,4,0,0.0,satisfied +60837,116730,Male,Loyal Customer,62,Personal Travel,Eco Plus,372,3,0,3,1,5,3,5,5,4,5,5,5,3,5,72,65.0,neutral or dissatisfied +60838,12949,Female,Loyal Customer,32,Personal Travel,Eco,359,3,4,3,1,2,3,2,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +60839,39568,Male,disloyal Customer,35,Business travel,Eco,954,3,3,3,4,4,3,4,4,2,3,4,2,5,4,0,7.0,neutral or dissatisfied +60840,59143,Female,Loyal Customer,15,Personal Travel,Eco,1846,2,5,1,4,2,1,4,2,3,3,4,3,5,2,1,0.0,neutral or dissatisfied +60841,51360,Male,disloyal Customer,25,Business travel,Eco Plus,109,2,0,2,2,3,2,3,3,5,4,1,3,3,3,0,0.0,neutral or dissatisfied +60842,18666,Male,Loyal Customer,49,Personal Travel,Eco,190,1,1,0,4,4,0,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +60843,100626,Male,Loyal Customer,52,Business travel,Business,349,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,6.0,satisfied +60844,126880,Female,Loyal Customer,39,Personal Travel,Eco,2296,2,2,2,3,4,2,4,4,1,5,3,4,2,4,0,0.0,neutral or dissatisfied +60845,93429,Male,disloyal Customer,30,Business travel,Eco,697,1,1,1,3,3,1,3,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +60846,14449,Female,Loyal Customer,22,Business travel,Eco,674,1,1,1,1,1,1,3,1,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +60847,55266,Male,Loyal Customer,48,Business travel,Business,2007,3,3,3,3,2,5,5,5,5,4,5,4,5,5,4,3.0,satisfied +60848,106040,Female,Loyal Customer,60,Business travel,Business,452,5,5,5,5,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +60849,32453,Male,Loyal Customer,36,Business travel,Business,3634,5,5,5,5,2,4,1,5,5,5,4,5,5,1,0,0.0,satisfied +60850,60845,Male,Loyal Customer,45,Personal Travel,Eco,1754,5,3,5,3,4,5,4,4,2,4,4,4,4,4,0,0.0,satisfied +60851,62551,Female,Loyal Customer,29,Business travel,Business,1744,2,2,2,2,2,2,2,2,4,1,3,3,4,2,4,5.0,neutral or dissatisfied +60852,122145,Male,Loyal Customer,43,Business travel,Business,3162,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +60853,117664,Female,Loyal Customer,55,Business travel,Business,1449,4,4,4,4,4,5,4,4,4,5,4,3,4,5,3,0.0,satisfied +60854,84233,Female,Loyal Customer,16,Personal Travel,Eco,432,3,5,3,4,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +60855,16626,Female,Loyal Customer,29,Business travel,Eco Plus,1008,3,2,2,2,3,3,3,3,3,2,4,3,3,3,21,27.0,neutral or dissatisfied +60856,18525,Female,disloyal Customer,22,Business travel,Eco,262,3,0,3,4,4,3,4,4,3,1,4,2,4,4,0,0.0,neutral or dissatisfied +60857,66243,Female,Loyal Customer,54,Business travel,Eco,460,3,3,3,3,4,1,1,2,2,3,2,3,2,5,0,3.0,satisfied +60858,77047,Female,Loyal Customer,29,Business travel,Eco,1156,4,5,5,5,4,4,4,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +60859,82405,Female,Loyal Customer,59,Personal Travel,Eco,500,3,5,3,4,4,4,5,4,4,3,4,4,4,5,17,23.0,neutral or dissatisfied +60860,20868,Male,Loyal Customer,63,Personal Travel,Eco,534,0,5,0,4,1,0,2,1,3,2,1,1,2,1,6,1.0,satisfied +60861,95157,Male,Loyal Customer,25,Personal Travel,Eco,277,2,1,2,3,4,2,3,4,2,1,3,1,3,4,0,0.0,neutral or dissatisfied +60862,111335,Female,Loyal Customer,58,Personal Travel,Eco,283,3,4,3,4,2,5,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +60863,152,Female,Loyal Customer,51,Business travel,Business,3424,3,4,4,4,5,3,3,3,3,3,3,4,3,4,44,42.0,neutral or dissatisfied +60864,24922,Female,Loyal Customer,43,Business travel,Eco,362,3,5,5,5,3,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +60865,112093,Female,disloyal Customer,21,Business travel,Eco,1062,4,4,4,3,1,4,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +60866,16123,Female,Loyal Customer,60,Business travel,Business,1531,2,5,5,5,2,2,2,1,3,4,4,2,4,2,140,133.0,neutral or dissatisfied +60867,44320,Female,disloyal Customer,23,Business travel,Eco,318,1,5,1,3,4,1,4,4,3,5,5,3,5,4,39,70.0,neutral or dissatisfied +60868,83425,Female,Loyal Customer,24,Personal Travel,Eco,632,5,5,5,2,5,5,1,5,4,4,5,4,4,5,0,0.0,satisfied +60869,54014,Female,Loyal Customer,23,Business travel,Eco,1091,5,2,3,3,5,5,3,5,1,5,4,2,1,5,0,0.0,satisfied +60870,77328,Male,Loyal Customer,49,Business travel,Business,3296,4,4,4,4,2,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +60871,51645,Male,disloyal Customer,34,Business travel,Eco,237,3,0,3,3,4,3,4,4,3,2,4,2,5,4,0,0.0,neutral or dissatisfied +60872,40870,Female,Loyal Customer,31,Personal Travel,Eco,558,4,3,4,4,1,4,1,1,3,1,4,2,4,1,0,0.0,neutral or dissatisfied +60873,29917,Male,Loyal Customer,50,Business travel,Eco,253,4,2,2,2,4,4,4,2,5,1,3,4,3,4,348,351.0,satisfied +60874,67014,Female,Loyal Customer,33,Business travel,Business,3425,4,4,4,4,5,4,5,4,4,4,4,5,4,3,8,13.0,satisfied +60875,99673,Male,Loyal Customer,52,Business travel,Business,3229,4,4,4,4,3,5,5,4,4,4,4,4,4,4,20,6.0,satisfied +60876,23867,Male,Loyal Customer,55,Personal Travel,Eco,552,2,0,2,4,3,2,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +60877,70336,Female,Loyal Customer,53,Business travel,Eco,986,3,1,1,1,1,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +60878,108572,Male,Loyal Customer,34,Personal Travel,Business,696,3,4,3,3,2,4,5,1,1,3,1,3,1,5,51,50.0,neutral or dissatisfied +60879,8160,Male,Loyal Customer,62,Business travel,Business,530,3,2,2,2,4,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +60880,55314,Female,Loyal Customer,39,Business travel,Business,3273,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,11.0,satisfied +60881,46623,Male,Loyal Customer,56,Business travel,Business,73,4,4,4,4,4,5,3,5,5,5,4,2,5,5,0,0.0,satisfied +60882,50413,Female,Loyal Customer,48,Business travel,Eco,193,3,5,5,5,2,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +60883,102023,Female,Loyal Customer,41,Business travel,Business,3937,4,4,4,4,2,5,4,3,3,3,3,4,3,5,57,57.0,satisfied +60884,508,Female,Loyal Customer,38,Business travel,Business,3690,4,4,4,4,4,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +60885,39097,Male,Loyal Customer,36,Personal Travel,Eco Plus,984,5,5,5,2,2,5,2,2,4,5,4,4,4,2,10,0.0,satisfied +60886,23917,Male,Loyal Customer,25,Personal Travel,Eco,589,4,3,5,2,2,5,3,2,2,3,2,3,2,2,0,0.0,satisfied +60887,92129,Female,Loyal Customer,20,Personal Travel,Eco,1522,3,4,3,3,2,3,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +60888,101286,Female,Loyal Customer,55,Business travel,Business,763,3,4,4,4,2,3,3,3,3,3,3,4,3,4,4,0.0,neutral or dissatisfied +60889,47920,Male,Loyal Customer,44,Personal Travel,Eco,462,2,5,2,1,4,2,4,4,4,3,4,3,4,4,0,8.0,neutral or dissatisfied +60890,1414,Female,Loyal Customer,56,Personal Travel,Eco Plus,309,2,5,3,3,5,5,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +60891,58171,Female,disloyal Customer,45,Business travel,Business,925,2,3,3,3,2,2,2,2,3,2,4,3,5,2,31,9.0,neutral or dissatisfied +60892,53544,Female,Loyal Customer,60,Personal Travel,Eco Plus,2419,2,5,1,4,1,1,1,3,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +60893,106972,Male,Loyal Customer,21,Business travel,Business,3740,2,2,2,2,5,5,5,5,3,3,5,4,5,5,6,1.0,satisfied +60894,17232,Male,disloyal Customer,25,Business travel,Eco,872,2,1,1,4,2,1,2,2,1,4,3,2,5,2,0,0.0,neutral or dissatisfied +60895,35278,Female,Loyal Customer,29,Business travel,Business,1076,2,2,2,2,3,2,3,3,5,3,5,5,4,3,5,0.0,satisfied +60896,31986,Male,Loyal Customer,17,Personal Travel,Business,101,0,4,0,3,1,0,1,1,4,4,4,3,4,1,0,0.0,satisfied +60897,10597,Male,Loyal Customer,51,Business travel,Business,429,5,5,4,5,4,4,4,5,5,5,5,5,5,4,0,1.0,satisfied +60898,1067,Female,Loyal Customer,27,Personal Travel,Eco,102,4,3,4,2,4,4,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +60899,100004,Male,disloyal Customer,37,Business travel,Business,220,2,3,3,2,2,3,2,2,3,2,5,3,5,2,14,21.0,neutral or dissatisfied +60900,86190,Female,disloyal Customer,59,Business travel,Business,226,3,3,3,3,5,3,3,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +60901,35772,Female,disloyal Customer,23,Business travel,Eco,200,4,3,4,4,4,4,1,4,1,4,4,4,3,4,61,63.0,neutral or dissatisfied +60902,67019,Male,Loyal Customer,50,Business travel,Business,3503,5,5,3,5,4,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +60903,120843,Male,Loyal Customer,57,Business travel,Business,2170,4,4,4,4,2,4,4,4,4,4,4,3,4,4,3,20.0,satisfied +60904,125153,Male,Loyal Customer,51,Personal Travel,Eco,1999,2,5,2,3,1,2,1,1,3,2,4,4,5,1,1,62.0,neutral or dissatisfied +60905,119415,Male,disloyal Customer,18,Business travel,Eco,399,3,3,3,4,3,3,3,3,3,1,4,1,3,3,0,29.0,neutral or dissatisfied +60906,121172,Female,Loyal Customer,60,Personal Travel,Eco,2402,5,4,5,3,5,2,2,5,2,4,5,2,4,2,4,4.0,satisfied +60907,61590,Female,disloyal Customer,29,Business travel,Business,1379,4,4,4,4,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +60908,63280,Female,Loyal Customer,57,Business travel,Business,3130,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +60909,89110,Female,disloyal Customer,7,Business travel,Eco,1386,4,4,4,4,2,4,2,2,3,2,5,4,5,2,4,0.0,neutral or dissatisfied +60910,68317,Female,disloyal Customer,43,Business travel,Business,832,4,4,4,3,5,4,5,5,4,3,4,3,5,5,0,0.0,satisfied +60911,61387,Female,Loyal Customer,25,Business travel,Business,679,2,2,2,2,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +60912,85847,Female,Loyal Customer,47,Business travel,Business,526,4,4,5,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +60913,90161,Male,Loyal Customer,40,Personal Travel,Eco,983,4,1,4,3,3,4,4,3,3,3,3,1,3,3,0,0.0,satisfied +60914,94841,Female,Loyal Customer,56,Business travel,Business,248,3,3,2,3,4,4,3,3,3,3,3,4,3,3,23,17.0,neutral or dissatisfied +60915,53854,Female,Loyal Customer,61,Business travel,Business,2976,5,2,5,5,5,2,4,5,5,5,5,5,5,5,0,0.0,satisfied +60916,98465,Male,disloyal Customer,38,Business travel,Business,210,3,3,3,4,1,3,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +60917,70559,Male,disloyal Customer,36,Business travel,Eco,1258,3,3,3,4,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +60918,72075,Female,disloyal Customer,55,Business travel,Business,873,5,5,5,1,5,5,4,5,3,5,3,5,5,5,0,0.0,satisfied +60919,62043,Male,Loyal Customer,30,Business travel,Business,2586,4,4,4,4,4,4,4,4,3,3,5,4,4,4,26,3.0,satisfied +60920,112936,Male,Loyal Customer,64,Personal Travel,Eco,1390,2,4,2,5,3,2,3,3,4,5,3,4,4,3,4,0.0,neutral or dissatisfied +60921,35825,Male,Loyal Customer,40,Business travel,Business,937,5,5,1,5,4,2,5,4,4,4,4,3,4,1,0,0.0,satisfied +60922,21340,Male,disloyal Customer,40,Business travel,Eco,674,3,3,3,3,2,3,2,2,2,5,1,5,1,2,0,0.0,neutral or dissatisfied +60923,32746,Female,Loyal Customer,32,Business travel,Eco,101,5,5,2,5,5,5,5,5,5,5,4,1,2,5,0,0.0,satisfied +60924,125326,Female,Loyal Customer,19,Business travel,Business,3320,5,5,5,5,5,5,5,5,3,4,5,4,5,5,0,11.0,satisfied +60925,10881,Male,Loyal Customer,50,Business travel,Business,229,2,4,4,4,5,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +60926,114111,Female,disloyal Customer,20,Business travel,Business,853,5,3,5,1,1,5,1,1,3,3,4,3,5,1,1,0.0,satisfied +60927,119086,Female,Loyal Customer,49,Business travel,Business,1107,5,5,5,5,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +60928,69388,Female,Loyal Customer,54,Business travel,Business,3894,3,2,2,2,5,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +60929,71495,Male,Loyal Customer,43,Personal Travel,Business,1120,1,4,1,1,5,4,4,4,4,1,4,5,4,3,3,0.0,neutral or dissatisfied +60930,13155,Female,Loyal Customer,20,Personal Travel,Eco,427,4,2,4,3,5,4,5,5,2,1,3,4,4,5,22,15.0,neutral or dissatisfied +60931,78238,Female,Loyal Customer,59,Business travel,Business,3132,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,1.0,satisfied +60932,38451,Male,disloyal Customer,28,Business travel,Eco,1226,3,3,3,4,3,3,3,3,3,2,5,4,1,3,15,17.0,neutral or dissatisfied +60933,8623,Male,Loyal Customer,31,Business travel,Business,3252,1,1,1,1,4,4,4,4,5,3,4,3,4,4,19,29.0,satisfied +60934,15968,Male,Loyal Customer,57,Business travel,Eco Plus,528,5,3,2,3,5,5,5,5,1,1,4,5,5,5,0,15.0,satisfied +60935,107953,Male,Loyal Customer,28,Personal Travel,Eco Plus,611,2,3,2,2,4,2,4,4,4,3,2,2,5,4,0,15.0,neutral or dissatisfied +60936,91971,Female,disloyal Customer,19,Business travel,Eco,1364,5,4,4,3,4,5,4,4,3,2,4,4,5,4,0,0.0,satisfied +60937,21764,Male,Loyal Customer,31,Business travel,Eco,341,3,3,3,3,5,5,5,5,3,3,1,2,3,5,0,0.0,satisfied +60938,54788,Female,disloyal Customer,39,Business travel,Business,862,1,1,1,3,2,1,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +60939,73969,Female,Loyal Customer,15,Personal Travel,Eco,2342,2,1,2,2,4,2,4,4,1,4,2,1,3,4,1,6.0,neutral or dissatisfied +60940,59966,Female,disloyal Customer,56,Business travel,Eco,597,2,5,2,3,4,2,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +60941,100849,Female,Loyal Customer,43,Personal Travel,Eco,711,2,3,2,4,5,3,2,3,3,2,3,1,3,3,0,3.0,neutral or dissatisfied +60942,111122,Male,disloyal Customer,27,Business travel,Business,1050,2,2,2,3,3,2,1,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +60943,57407,Female,Loyal Customer,48,Business travel,Business,3540,2,2,2,2,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +60944,119684,Male,Loyal Customer,28,Personal Travel,Business,1496,3,5,3,3,2,3,2,2,4,2,3,4,5,2,41,48.0,neutral or dissatisfied +60945,119092,Female,Loyal Customer,65,Business travel,Business,1993,3,4,4,4,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +60946,35668,Female,Loyal Customer,28,Business travel,Business,2586,2,2,2,2,4,4,4,4,1,1,5,4,3,4,0,0.0,satisfied +60947,82824,Female,disloyal Customer,24,Business travel,Business,594,5,5,5,1,5,5,5,5,5,4,5,4,5,5,0,5.0,satisfied +60948,55755,Female,Loyal Customer,62,Personal Travel,Eco,1737,3,5,3,3,3,5,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +60949,27444,Female,Loyal Customer,29,Business travel,Business,3270,3,1,4,1,3,3,3,3,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +60950,12064,Female,Loyal Customer,32,Personal Travel,Eco,351,2,4,2,3,1,2,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +60951,7478,Male,Loyal Customer,48,Business travel,Business,2114,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +60952,106381,Female,disloyal Customer,28,Business travel,Business,488,4,4,4,3,5,4,5,5,5,2,5,5,5,5,71,85.0,satisfied +60953,74660,Female,Loyal Customer,35,Personal Travel,Eco,1205,1,3,0,4,4,0,4,4,3,5,3,3,3,4,5,0.0,neutral or dissatisfied +60954,5265,Female,Loyal Customer,50,Personal Travel,Eco,351,0,4,0,1,5,5,5,5,5,0,4,5,5,4,0,0.0,satisfied +60955,119905,Male,Loyal Customer,40,Personal Travel,Eco Plus,912,3,5,3,5,1,3,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +60956,39756,Male,Loyal Customer,55,Business travel,Business,2961,2,2,2,2,4,2,5,4,4,4,4,5,4,2,0,43.0,satisfied +60957,27150,Male,disloyal Customer,21,Business travel,Eco,1262,3,3,3,2,3,3,3,1,2,2,2,3,3,3,0,0.0,neutral or dissatisfied +60958,8402,Female,disloyal Customer,48,Business travel,Business,737,3,3,3,2,5,3,5,5,5,2,4,5,4,5,72,54.0,neutral or dissatisfied +60959,128197,Male,Loyal Customer,59,Business travel,Business,602,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +60960,38631,Male,Loyal Customer,22,Business travel,Business,2689,5,5,4,5,2,2,2,2,2,1,4,2,3,2,1,0.0,satisfied +60961,45387,Male,Loyal Customer,11,Personal Travel,Eco Plus,222,1,3,0,3,2,0,2,2,1,3,2,2,4,2,0,0.0,neutral or dissatisfied +60962,108266,Male,Loyal Customer,48,Personal Travel,Eco,895,5,4,5,1,3,5,3,3,1,3,3,4,5,3,0,0.0,satisfied +60963,81647,Male,disloyal Customer,27,Business travel,Eco,907,3,3,3,4,4,3,4,4,1,4,3,2,4,4,10,4.0,neutral or dissatisfied +60964,65977,Female,disloyal Customer,30,Business travel,Eco,1372,2,2,2,3,4,2,4,4,4,4,3,1,4,4,0,0.0,neutral or dissatisfied +60965,31983,Male,disloyal Customer,19,Business travel,Eco,163,3,0,3,5,5,3,3,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +60966,67751,Female,Loyal Customer,44,Business travel,Business,2657,4,4,4,4,5,4,5,3,3,3,3,4,3,3,5,0.0,satisfied +60967,49606,Male,disloyal Customer,57,Business travel,Eco,153,1,5,1,5,4,1,4,4,3,4,5,2,4,4,33,27.0,neutral or dissatisfied +60968,101193,Male,Loyal Customer,9,Personal Travel,Eco,775,3,3,3,3,4,3,5,4,3,4,3,2,4,4,100,93.0,neutral or dissatisfied +60969,127682,Female,Loyal Customer,42,Business travel,Eco,328,3,1,1,1,5,2,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +60970,61568,Male,Loyal Customer,48,Business travel,Business,1379,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +60971,64176,Female,Loyal Customer,25,Business travel,Business,3918,2,2,2,2,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +60972,127507,Female,Loyal Customer,30,Personal Travel,Eco,1814,4,3,4,1,4,4,4,4,2,4,4,1,2,4,0,0.0,neutral or dissatisfied +60973,30027,Male,disloyal Customer,50,Business travel,Business,234,2,1,1,2,3,2,3,3,2,2,5,4,1,3,0,0.0,neutral or dissatisfied +60974,13830,Female,disloyal Customer,36,Business travel,Eco,628,3,1,3,4,4,3,3,4,1,1,4,4,4,4,0,0.0,neutral or dissatisfied +60975,78575,Male,Loyal Customer,39,Business travel,Business,630,2,2,2,2,2,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +60976,62073,Female,Loyal Customer,61,Personal Travel,Eco,2475,2,5,2,3,4,4,5,1,1,2,1,3,1,4,1,0.0,neutral or dissatisfied +60977,109652,Male,Loyal Customer,23,Business travel,Business,3449,5,5,5,5,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +60978,23738,Female,disloyal Customer,25,Business travel,Eco,602,2,0,2,1,4,2,4,4,2,3,4,3,3,4,61,89.0,neutral or dissatisfied +60979,90611,Female,Loyal Customer,57,Business travel,Business,3481,2,2,4,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +60980,101217,Female,Loyal Customer,8,Personal Travel,Eco,1069,3,4,3,2,2,3,3,2,4,2,4,4,4,2,25,19.0,neutral or dissatisfied +60981,107718,Male,Loyal Customer,47,Business travel,Business,3200,0,0,0,3,5,1,3,4,4,4,4,4,4,2,0,0.0,satisfied +60982,108885,Male,Loyal Customer,28,Personal Travel,Business,1183,4,2,4,3,2,4,2,2,1,4,2,2,3,2,31,28.0,neutral or dissatisfied +60983,30134,Female,Loyal Customer,12,Personal Travel,Eco,399,2,5,2,2,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +60984,101801,Male,disloyal Customer,36,Business travel,Business,1521,3,3,3,1,3,3,3,3,3,2,4,5,4,3,21,6.0,neutral or dissatisfied +60985,82636,Female,Loyal Customer,37,Business travel,Business,528,5,4,5,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +60986,89723,Male,Loyal Customer,56,Personal Travel,Eco,1096,4,2,4,2,1,4,1,1,2,1,2,2,2,1,4,0.0,neutral or dissatisfied +60987,86281,Male,Loyal Customer,13,Personal Travel,Eco,356,5,2,5,4,3,5,3,3,2,4,3,2,4,3,5,0.0,satisfied +60988,23203,Female,Loyal Customer,45,Personal Travel,Eco Plus,223,1,4,0,2,3,4,4,5,5,0,1,4,5,4,86,76.0,neutral or dissatisfied +60989,126380,Male,Loyal Customer,18,Personal Travel,Eco,590,4,5,3,3,4,3,4,4,3,5,5,5,4,4,5,5.0,neutral or dissatisfied +60990,107593,Female,disloyal Customer,21,Business travel,Business,423,0,0,0,1,3,0,4,3,4,2,4,4,5,3,0,3.0,satisfied +60991,60814,Male,disloyal Customer,22,Business travel,Eco,455,4,1,4,2,2,4,4,2,4,4,2,1,2,2,6,20.0,neutral or dissatisfied +60992,104798,Female,Loyal Customer,25,Business travel,Eco,787,3,4,4,4,3,3,1,3,4,1,3,3,3,3,38,33.0,neutral or dissatisfied +60993,109979,Female,Loyal Customer,48,Personal Travel,Eco,1034,3,4,3,4,4,4,5,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +60994,53024,Male,Loyal Customer,54,Business travel,Eco,1208,5,4,2,4,4,5,4,4,4,2,4,5,5,4,0,0.0,satisfied +60995,85899,Male,Loyal Customer,26,Business travel,Business,761,2,2,2,2,3,4,3,3,3,4,5,4,5,3,121,108.0,satisfied +60996,17497,Female,disloyal Customer,36,Business travel,Eco,352,1,3,1,4,2,1,5,2,4,3,2,4,3,2,0,0.0,neutral or dissatisfied +60997,84475,Male,Loyal Customer,30,Personal Travel,Eco,1142,2,5,1,3,2,1,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +60998,79065,Female,disloyal Customer,20,Business travel,Eco,356,3,0,2,3,1,2,1,1,1,2,4,3,4,1,0,0.0,neutral or dissatisfied +60999,59037,Female,disloyal Customer,55,Business travel,Business,1744,2,2,2,3,5,2,5,5,3,2,3,5,4,5,28,0.0,neutral or dissatisfied +61000,73491,Female,Loyal Customer,29,Personal Travel,Eco,1182,2,4,3,2,5,3,5,5,3,3,5,3,5,5,0,3.0,neutral or dissatisfied +61001,41126,Female,Loyal Customer,51,Business travel,Eco,316,2,5,5,5,3,2,2,2,2,2,2,1,2,3,0,5.0,neutral or dissatisfied +61002,28024,Male,Loyal Customer,22,Business travel,Eco,363,3,2,3,2,3,3,3,3,4,3,4,4,4,3,0,2.0,neutral or dissatisfied +61003,124188,Female,Loyal Customer,68,Business travel,Business,676,4,4,4,4,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +61004,37379,Male,disloyal Customer,21,Business travel,Business,1076,3,3,3,4,3,4,4,4,5,4,4,4,1,4,157,161.0,neutral or dissatisfied +61005,22669,Female,Loyal Customer,51,Business travel,Business,2182,3,3,3,3,4,1,2,4,4,4,4,5,4,2,0,0.0,satisfied +61006,47706,Female,Loyal Customer,56,Business travel,Eco Plus,1504,5,4,4,4,1,2,5,3,3,5,3,2,3,4,0,3.0,satisfied +61007,39017,Female,disloyal Customer,23,Business travel,Business,230,0,0,0,1,3,0,3,3,1,2,3,1,1,3,0,0.0,satisfied +61008,581,Male,disloyal Customer,25,Business travel,Business,164,4,0,4,4,5,4,1,5,5,5,4,4,5,5,47,57.0,satisfied +61009,29418,Male,Loyal Customer,23,Business travel,Business,2614,5,5,3,5,4,4,4,4,1,4,5,4,5,4,0,8.0,satisfied +61010,91683,Female,Loyal Customer,22,Business travel,Business,2739,5,5,5,5,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +61011,75693,Male,Loyal Customer,43,Business travel,Business,868,2,2,2,2,2,4,4,4,4,4,4,4,4,3,44,25.0,satisfied +61012,54276,Male,Loyal Customer,34,Personal Travel,Eco,1222,3,3,3,4,2,3,2,2,1,5,4,2,4,2,2,27.0,neutral or dissatisfied +61013,13550,Male,Loyal Customer,32,Business travel,Business,227,3,5,5,5,3,3,3,3,1,3,3,2,3,3,0,0.0,neutral or dissatisfied +61014,115823,Male,disloyal Customer,23,Business travel,Eco,417,2,4,1,2,2,1,2,2,5,5,4,1,2,2,8,0.0,neutral or dissatisfied +61015,25162,Female,Loyal Customer,8,Personal Travel,Eco,2106,4,3,4,3,5,4,5,5,3,2,2,3,2,5,1,0.0,satisfied +61016,90878,Female,disloyal Customer,24,Business travel,Eco,404,1,1,1,3,2,1,2,2,1,5,3,3,4,2,1,5.0,neutral or dissatisfied +61017,16769,Female,Loyal Customer,30,Business travel,Business,1538,4,4,4,4,4,4,4,4,5,1,2,1,2,4,0,6.0,satisfied +61018,20899,Female,Loyal Customer,44,Business travel,Business,2144,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,8.0,satisfied +61019,110708,Male,Loyal Customer,43,Personal Travel,Eco Plus,945,3,2,3,3,5,3,5,5,2,5,3,2,4,5,58,52.0,neutral or dissatisfied +61020,90297,Female,Loyal Customer,17,Personal Travel,Eco,773,2,1,2,2,2,2,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +61021,61672,Male,Loyal Customer,46,Business travel,Business,1379,2,5,5,5,3,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +61022,13464,Male,Loyal Customer,49,Personal Travel,Eco,409,2,4,2,5,3,2,1,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +61023,124085,Female,Loyal Customer,17,Personal Travel,Business,529,2,5,2,3,4,2,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +61024,24443,Male,Loyal Customer,51,Business travel,Business,2647,1,1,1,1,1,4,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +61025,32136,Female,disloyal Customer,25,Business travel,Eco,216,2,0,2,3,4,2,4,4,4,5,3,1,3,4,0,5.0,neutral or dissatisfied +61026,93582,Female,disloyal Customer,47,Business travel,Eco,159,3,3,3,3,5,3,5,5,1,1,2,5,5,5,0,0.0,neutral or dissatisfied +61027,102191,Male,disloyal Customer,21,Business travel,Eco,397,3,2,3,3,2,3,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +61028,7105,Female,Loyal Customer,57,Personal Travel,Eco,157,3,4,3,2,5,4,5,5,5,3,5,4,5,5,47,41.0,neutral or dissatisfied +61029,116947,Female,Loyal Customer,39,Business travel,Business,368,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +61030,84026,Female,Loyal Customer,47,Business travel,Business,2260,3,3,3,3,2,4,5,5,5,4,5,3,5,3,1,15.0,satisfied +61031,33978,Female,Loyal Customer,60,Business travel,Eco,1576,5,3,3,3,2,4,2,5,5,5,5,2,5,2,0,0.0,satisfied +61032,77245,Female,Loyal Customer,18,Business travel,Business,1590,1,3,3,3,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +61033,106295,Female,disloyal Customer,26,Business travel,Business,998,5,5,5,2,3,5,3,3,5,5,5,5,4,3,9,0.0,satisfied +61034,69904,Female,Loyal Customer,56,Business travel,Business,1514,2,1,2,2,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +61035,58341,Female,Loyal Customer,38,Business travel,Business,1925,4,2,2,2,2,3,3,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +61036,14421,Female,Loyal Customer,12,Personal Travel,Eco,693,2,5,2,5,3,2,3,3,3,3,4,4,4,3,1,1.0,neutral or dissatisfied +61037,39039,Female,Loyal Customer,9,Personal Travel,Eco,230,5,5,5,5,3,5,3,3,5,5,5,3,4,3,0,0.0,satisfied +61038,11448,Female,Loyal Customer,54,Business travel,Eco Plus,166,4,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +61039,69669,Female,Loyal Customer,18,Personal Travel,Eco,569,2,4,2,4,4,2,4,4,5,4,5,3,5,4,0,10.0,neutral or dissatisfied +61040,32528,Male,disloyal Customer,26,Business travel,Eco,101,4,4,4,3,3,4,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +61041,37747,Female,Loyal Customer,40,Business travel,Eco Plus,1056,3,5,2,5,3,3,3,3,2,3,1,3,5,3,0,0.0,satisfied +61042,99270,Male,disloyal Customer,36,Business travel,Business,935,3,3,3,4,1,3,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +61043,10528,Male,Loyal Customer,56,Business travel,Business,2209,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +61044,78249,Male,Loyal Customer,52,Business travel,Business,3826,2,3,2,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +61045,98912,Male,Loyal Customer,55,Business travel,Business,543,2,2,2,2,5,4,4,2,2,2,2,4,2,5,12,6.0,satisfied +61046,34806,Male,Loyal Customer,50,Personal Travel,Eco,301,1,4,1,1,3,1,3,3,3,3,4,5,4,3,0,18.0,neutral or dissatisfied +61047,66527,Male,Loyal Customer,48,Personal Travel,Eco Plus,447,4,5,2,2,4,2,4,4,2,1,5,4,3,4,13,8.0,neutral or dissatisfied +61048,50893,Male,Loyal Customer,22,Personal Travel,Eco,134,3,2,3,4,4,3,4,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +61049,60487,Male,Loyal Customer,53,Business travel,Business,985,4,4,4,4,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +61050,77288,Male,Loyal Customer,58,Personal Travel,Eco,1931,2,2,1,2,3,1,3,3,4,1,2,2,1,3,4,0.0,neutral or dissatisfied +61051,100048,Female,Loyal Customer,58,Personal Travel,Eco,281,4,2,4,2,3,3,2,4,4,4,4,4,4,2,2,0.0,satisfied +61052,23437,Male,Loyal Customer,44,Business travel,Eco,576,3,3,3,3,4,3,4,4,1,1,4,2,2,4,0,10.0,satisfied +61053,103017,Male,Loyal Customer,51,Business travel,Business,460,4,4,4,4,2,4,4,5,5,5,5,3,5,5,35,34.0,satisfied +61054,116338,Female,Loyal Customer,59,Personal Travel,Eco,417,3,3,2,3,2,5,3,4,4,2,2,2,4,3,32,32.0,neutral or dissatisfied +61055,59661,Male,Loyal Customer,57,Personal Travel,Eco,854,2,4,2,2,5,2,1,5,5,3,4,3,5,5,1,6.0,neutral or dissatisfied +61056,121298,Female,Loyal Customer,42,Business travel,Business,1009,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +61057,90529,Male,Loyal Customer,54,Business travel,Business,3621,2,2,2,2,5,5,4,2,2,3,2,4,2,5,0,0.0,satisfied +61058,108303,Male,Loyal Customer,46,Business travel,Business,1838,2,2,2,2,2,3,4,4,4,4,4,4,4,5,30,27.0,satisfied +61059,10062,Female,Loyal Customer,55,Business travel,Business,596,1,1,3,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +61060,59775,Female,Loyal Customer,33,Business travel,Business,2686,3,3,4,3,4,1,5,5,5,5,5,2,5,4,24,68.0,satisfied +61061,35643,Male,Loyal Customer,24,Personal Travel,Business,2586,3,4,3,2,3,4,4,4,4,4,5,4,4,4,14,0.0,neutral or dissatisfied +61062,14958,Female,Loyal Customer,54,Personal Travel,Eco,528,4,1,4,2,1,2,2,1,1,4,2,1,1,1,101,72.0,neutral or dissatisfied +61063,313,Male,disloyal Customer,30,Business travel,Business,821,4,4,4,1,3,4,4,3,5,4,5,4,4,3,25,36.0,neutral or dissatisfied +61064,111966,Female,Loyal Customer,19,Business travel,Business,1997,2,5,5,5,2,2,2,2,3,2,3,4,4,2,18,11.0,neutral or dissatisfied +61065,45090,Male,Loyal Customer,57,Personal Travel,Eco,196,3,4,3,2,5,3,5,5,5,4,3,2,3,5,6,29.0,neutral or dissatisfied +61066,78342,Female,disloyal Customer,26,Business travel,Eco,1547,3,3,3,2,5,3,5,5,1,5,2,3,3,5,0,0.0,neutral or dissatisfied +61067,113892,Female,disloyal Customer,25,Business travel,Business,2295,3,5,3,2,4,3,4,4,3,5,4,3,4,4,1,0.0,neutral or dissatisfied +61068,72125,Male,Loyal Customer,35,Business travel,Business,731,5,3,5,5,2,5,5,4,4,4,4,3,4,4,2,1.0,satisfied +61069,57749,Female,Loyal Customer,44,Business travel,Business,2704,1,4,3,3,1,1,1,2,1,4,3,1,1,1,27,39.0,neutral or dissatisfied +61070,64961,Female,disloyal Customer,40,Business travel,Business,354,4,3,3,1,4,3,4,4,3,5,3,3,5,4,0,0.0,satisfied +61071,107617,Female,Loyal Customer,76,Business travel,Eco,423,3,3,3,3,5,2,2,4,4,3,4,2,4,1,22,13.0,neutral or dissatisfied +61072,80880,Male,Loyal Customer,47,Business travel,Business,692,3,3,3,3,4,4,4,5,5,5,5,5,5,3,13,1.0,satisfied +61073,66230,Female,Loyal Customer,60,Business travel,Business,1823,2,1,4,4,1,3,2,2,2,2,2,3,2,2,32,46.0,neutral or dissatisfied +61074,57220,Female,Loyal Customer,51,Business travel,Business,3892,2,3,3,3,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +61075,100432,Female,Loyal Customer,65,Personal Travel,Eco,1620,1,5,1,4,4,4,4,1,1,1,1,5,1,4,4,0.0,neutral or dissatisfied +61076,73474,Female,Loyal Customer,13,Personal Travel,Eco,1144,2,4,2,1,2,2,2,2,5,3,4,5,5,2,13,6.0,neutral or dissatisfied +61077,99017,Male,Loyal Customer,38,Business travel,Eco Plus,543,3,4,4,4,3,3,3,3,2,3,4,2,4,3,21,6.0,neutral or dissatisfied +61078,118174,Male,disloyal Customer,21,Business travel,Eco,853,3,3,3,3,5,3,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +61079,50676,Male,Loyal Customer,27,Personal Travel,Eco,109,5,5,5,2,1,5,1,1,5,3,4,5,4,1,0,0.0,satisfied +61080,13039,Male,Loyal Customer,55,Personal Travel,Eco,374,3,4,3,3,3,2,2,4,3,4,5,2,5,2,202,182.0,neutral or dissatisfied +61081,126201,Male,Loyal Customer,33,Business travel,Business,1555,3,3,3,3,3,3,3,3,1,1,4,3,3,3,9,1.0,neutral or dissatisfied +61082,47282,Female,Loyal Customer,48,Business travel,Business,532,5,5,5,5,3,5,1,5,5,5,5,5,5,2,0,0.0,satisfied +61083,89111,Female,Loyal Customer,42,Business travel,Business,1892,4,4,4,4,3,3,5,4,4,4,4,5,4,3,0,12.0,satisfied +61084,72233,Male,Loyal Customer,44,Business travel,Business,3302,4,4,4,4,4,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +61085,79994,Male,Loyal Customer,63,Personal Travel,Eco,950,1,0,1,4,5,1,5,5,4,2,5,3,4,5,1,0.0,neutral or dissatisfied +61086,127206,Male,Loyal Customer,65,Business travel,Eco Plus,221,3,5,5,5,3,3,3,3,1,2,1,5,1,3,0,0.0,satisfied +61087,112347,Female,Loyal Customer,40,Business travel,Business,853,1,1,1,1,2,5,4,5,5,5,5,3,5,3,31,17.0,satisfied +61088,86437,Female,disloyal Customer,25,Business travel,Eco,712,2,2,2,3,5,2,2,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +61089,32459,Male,Loyal Customer,44,Business travel,Eco,163,1,4,4,4,1,1,1,1,1,2,4,3,3,1,0,0.0,neutral or dissatisfied +61090,24467,Male,Loyal Customer,30,Business travel,Business,516,4,4,1,4,5,5,5,5,3,2,4,5,2,5,0,15.0,satisfied +61091,91529,Female,Loyal Customer,24,Business travel,Business,680,2,2,2,2,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +61092,40047,Male,disloyal Customer,20,Business travel,Eco,866,2,2,2,3,2,2,2,2,3,2,3,4,2,2,1,0.0,neutral or dissatisfied +61093,66844,Male,Loyal Customer,68,Personal Travel,Eco,731,3,1,3,2,2,3,2,2,4,2,1,1,1,2,13,0.0,neutral or dissatisfied +61094,5043,Male,Loyal Customer,42,Business travel,Business,235,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +61095,30633,Female,disloyal Customer,39,Business travel,Business,770,5,5,5,3,3,5,3,3,5,4,1,1,1,3,13,19.0,satisfied +61096,16928,Female,Loyal Customer,17,Business travel,Business,820,4,4,3,4,4,4,4,4,3,1,2,2,1,4,5,2.0,satisfied +61097,110350,Female,disloyal Customer,20,Business travel,Business,925,4,5,4,3,4,4,4,4,5,5,4,3,4,4,17,6.0,satisfied +61098,112412,Female,Loyal Customer,48,Business travel,Business,2397,3,3,3,3,3,4,5,5,5,5,5,3,5,5,27,44.0,satisfied +61099,82491,Male,Loyal Customer,30,Business travel,Eco,488,3,4,4,4,3,3,3,3,2,3,3,1,3,3,0,0.0,neutral or dissatisfied +61100,121958,Male,Loyal Customer,8,Personal Travel,Eco,430,3,3,3,3,4,3,4,4,3,1,3,1,2,4,0,0.0,neutral or dissatisfied +61101,39755,Female,Loyal Customer,20,Personal Travel,Business,521,5,5,5,1,2,5,2,2,4,5,4,4,4,2,0,0.0,satisfied +61102,61696,Male,disloyal Customer,20,Business travel,Eco,1346,4,4,4,1,2,4,2,2,3,4,5,3,5,2,2,0.0,satisfied +61103,124177,Male,disloyal Customer,38,Business travel,Business,589,3,2,2,3,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +61104,46526,Female,Loyal Customer,41,Business travel,Eco,73,5,1,1,1,5,5,5,5,2,1,1,2,1,5,56,82.0,satisfied +61105,11918,Male,Loyal Customer,38,Personal Travel,Eco,744,1,3,1,4,1,1,1,1,5,3,3,5,3,1,0,14.0,neutral or dissatisfied +61106,88039,Male,Loyal Customer,31,Business travel,Business,3951,5,5,5,5,5,5,5,5,4,2,4,5,5,5,26,15.0,satisfied +61107,34793,Male,Loyal Customer,53,Personal Travel,Eco,209,1,2,1,4,3,1,3,3,4,3,3,3,3,3,0,2.0,neutral or dissatisfied +61108,110873,Female,disloyal Customer,27,Business travel,Business,581,1,1,1,4,1,1,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +61109,122932,Female,Loyal Customer,50,Business travel,Business,2867,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,10.0,satisfied +61110,124424,Female,disloyal Customer,44,Business travel,Eco,862,1,1,1,4,4,1,4,4,1,4,4,3,1,4,0,0.0,neutral or dissatisfied +61111,123245,Male,Loyal Customer,38,Personal Travel,Eco,631,2,3,1,2,3,1,3,3,3,2,3,4,3,3,40,48.0,neutral or dissatisfied +61112,12470,Male,Loyal Customer,35,Personal Travel,Eco,190,2,1,2,4,3,2,3,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +61113,116939,Female,Loyal Customer,59,Business travel,Business,2626,5,1,5,5,3,5,5,4,4,4,4,3,4,5,7,0.0,satisfied +61114,107999,Male,Loyal Customer,42,Business travel,Eco,271,4,4,4,4,3,4,3,3,5,3,2,4,4,3,4,3.0,satisfied +61115,107770,Female,Loyal Customer,33,Business travel,Business,2853,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +61116,73847,Male,Loyal Customer,51,Business travel,Business,1709,2,5,2,5,2,2,2,2,2,2,2,2,2,3,1,2.0,neutral or dissatisfied +61117,101484,Female,disloyal Customer,25,Business travel,Business,345,3,0,2,5,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +61118,106895,Female,Loyal Customer,29,Personal Travel,Eco,577,1,5,1,4,1,3,3,4,4,5,5,3,4,3,42,219.0,neutral or dissatisfied +61119,73857,Female,Loyal Customer,38,Personal Travel,Eco,1709,3,3,3,4,2,3,2,2,2,2,3,1,3,2,1,0.0,neutral or dissatisfied +61120,84890,Female,Loyal Customer,65,Personal Travel,Eco,547,3,0,3,1,3,1,1,4,4,3,4,5,4,1,53,35.0,neutral or dissatisfied +61121,23635,Female,Loyal Customer,57,Business travel,Eco,793,2,1,1,1,4,3,3,2,2,2,2,3,2,3,51,32.0,neutral or dissatisfied +61122,58420,Female,Loyal Customer,25,Business travel,Eco,733,2,5,3,3,2,2,1,2,1,5,3,2,3,2,61,53.0,neutral or dissatisfied +61123,42725,Female,Loyal Customer,70,Personal Travel,Eco,1042,4,4,4,4,4,5,3,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +61124,60950,Male,Loyal Customer,28,Business travel,Business,2163,3,3,4,3,3,3,3,3,1,3,4,3,4,3,11,0.0,neutral or dissatisfied +61125,68796,Male,Loyal Customer,43,Business travel,Business,621,3,3,3,3,1,4,3,3,3,3,3,3,3,3,16,19.0,neutral or dissatisfied +61126,126211,Female,Loyal Customer,59,Business travel,Business,2473,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +61127,73601,Male,disloyal Customer,56,Business travel,Business,192,3,4,4,3,2,3,2,2,4,3,5,4,5,2,0,4.0,neutral or dissatisfied +61128,55877,Male,disloyal Customer,50,Business travel,Business,473,3,3,3,2,5,3,4,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +61129,11500,Female,Loyal Customer,57,Personal Travel,Eco Plus,247,2,5,2,2,2,5,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +61130,75131,Male,disloyal Customer,28,Business travel,Business,1726,2,1,1,3,2,1,2,2,5,3,5,4,5,2,17,3.0,neutral or dissatisfied +61131,59076,Male,Loyal Customer,66,Business travel,Business,1555,1,0,0,3,2,4,3,1,1,0,1,1,1,1,0,0.0,neutral or dissatisfied +61132,39926,Female,Loyal Customer,40,Business travel,Business,1964,4,4,4,4,1,4,2,5,5,5,5,2,5,4,0,0.0,satisfied +61133,6881,Female,disloyal Customer,61,Business travel,Business,265,1,1,1,3,2,1,2,2,5,3,5,4,4,2,3,16.0,neutral or dissatisfied +61134,50836,Male,Loyal Customer,9,Personal Travel,Eco,308,4,4,4,1,4,4,1,4,4,2,4,4,5,4,0,0.0,satisfied +61135,96562,Male,disloyal Customer,61,Business travel,Business,333,3,3,3,1,3,3,3,3,5,2,5,5,4,3,6,0.0,neutral or dissatisfied +61136,6025,Male,Loyal Customer,38,Business travel,Business,672,5,5,5,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +61137,16780,Male,Loyal Customer,49,Personal Travel,Eco,642,2,2,2,3,3,2,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +61138,35831,Male,Loyal Customer,43,Business travel,Business,2697,1,1,1,1,1,1,5,4,4,4,4,1,4,2,0,0.0,satisfied +61139,58919,Male,Loyal Customer,27,Personal Travel,Eco,888,2,5,2,4,2,2,2,2,5,5,4,4,5,2,42,9.0,neutral or dissatisfied +61140,86307,Male,Loyal Customer,59,Business travel,Eco Plus,356,1,3,3,3,1,1,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +61141,40568,Male,Loyal Customer,69,Business travel,Business,2134,1,1,1,1,4,2,3,4,4,4,4,5,4,3,0,0.0,satisfied +61142,3174,Male,Loyal Customer,53,Business travel,Business,2902,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +61143,45713,Female,Loyal Customer,60,Business travel,Eco,1068,2,4,5,4,3,1,2,2,2,2,2,4,2,3,0,11.0,neutral or dissatisfied +61144,84921,Female,Loyal Customer,18,Personal Travel,Eco,547,3,5,3,1,5,3,5,5,4,1,5,3,3,5,0,0.0,neutral or dissatisfied +61145,126399,Male,Loyal Customer,31,Business travel,Eco Plus,507,3,5,5,5,3,3,3,3,4,2,4,1,4,3,0,15.0,neutral or dissatisfied +61146,101794,Male,Loyal Customer,23,Business travel,Business,1521,1,1,5,1,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +61147,126851,Male,disloyal Customer,37,Business travel,Eco,796,1,2,2,3,2,2,3,2,2,5,1,4,5,2,0,0.0,neutral or dissatisfied +61148,73612,Male,Loyal Customer,37,Business travel,Business,204,3,3,3,3,3,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +61149,127051,Female,Loyal Customer,79,Business travel,Business,338,4,4,4,4,3,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +61150,13126,Female,disloyal Customer,36,Business travel,Eco,427,4,2,4,4,1,4,1,1,4,2,4,4,3,1,0,0.0,neutral or dissatisfied +61151,120759,Female,Loyal Customer,44,Business travel,Business,1943,1,1,1,1,5,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +61152,61941,Female,disloyal Customer,20,Business travel,Business,1014,4,1,4,4,5,4,2,5,4,5,4,3,5,5,0,0.0,satisfied +61153,21938,Female,Loyal Customer,46,Business travel,Eco,551,2,5,5,5,4,3,3,2,2,2,2,2,2,4,0,1.0,neutral or dissatisfied +61154,25656,Female,disloyal Customer,30,Business travel,Eco,761,1,1,1,3,1,1,1,1,1,3,2,4,4,1,0,0.0,neutral or dissatisfied +61155,38353,Male,disloyal Customer,22,Business travel,Eco,1173,3,4,4,3,2,4,2,2,2,5,2,3,3,2,7,12.0,neutral or dissatisfied +61156,78206,Female,Loyal Customer,19,Personal Travel,Eco,192,3,4,3,3,3,3,1,3,4,3,5,5,4,3,29,20.0,neutral or dissatisfied +61157,109843,Female,disloyal Customer,25,Business travel,Eco,1011,4,4,4,4,2,4,2,2,2,4,4,1,4,2,13,8.0,neutral or dissatisfied +61158,107870,Female,disloyal Customer,40,Business travel,Business,228,4,4,4,5,3,4,3,3,2,1,5,2,4,3,0,0.0,neutral or dissatisfied +61159,50036,Male,Loyal Customer,52,Business travel,Eco,77,3,1,1,1,2,3,2,2,3,4,4,2,4,2,0,1.0,satisfied +61160,96529,Female,Loyal Customer,59,Personal Travel,Eco,302,3,5,3,1,4,4,4,2,2,3,5,4,2,5,4,0.0,neutral or dissatisfied +61161,42313,Male,Loyal Customer,46,Personal Travel,Eco,550,3,0,2,1,5,2,3,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +61162,26385,Female,Loyal Customer,53,Personal Travel,Eco Plus,861,3,3,3,2,4,1,5,4,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +61163,109699,Female,Loyal Customer,53,Personal Travel,Eco Plus,802,1,4,1,4,1,3,4,1,1,1,1,3,1,3,21,14.0,neutral or dissatisfied +61164,25093,Male,Loyal Customer,35,Business travel,Business,1522,1,1,1,1,2,1,1,4,4,4,4,2,4,2,109,83.0,satisfied +61165,75325,Female,Loyal Customer,40,Business travel,Business,2486,5,5,4,5,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +61166,24196,Male,disloyal Customer,25,Business travel,Eco,302,1,4,1,4,3,1,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +61167,102999,Female,Loyal Customer,25,Business travel,Business,786,2,2,2,2,5,5,5,5,5,2,5,3,5,5,30,0.0,satisfied +61168,59409,Female,Loyal Customer,60,Personal Travel,Eco,2367,1,4,1,1,5,5,4,2,2,1,2,5,2,5,5,0.0,neutral or dissatisfied +61169,60759,Female,disloyal Customer,26,Business travel,Business,628,5,5,5,3,4,5,4,4,4,5,4,4,5,4,6,0.0,satisfied +61170,77042,Female,Loyal Customer,49,Business travel,Business,3814,2,2,2,2,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +61171,2346,Female,Loyal Customer,80,Business travel,Eco Plus,525,3,1,1,1,3,3,4,3,3,3,3,1,3,2,3,0.0,neutral or dissatisfied +61172,32262,Female,disloyal Customer,44,Business travel,Eco,101,3,0,2,2,3,2,3,3,1,4,1,1,2,3,2,15.0,neutral or dissatisfied +61173,93148,Male,Loyal Customer,45,Business travel,Business,1183,4,2,2,2,4,3,4,4,4,4,4,1,4,4,3,10.0,neutral or dissatisfied +61174,115941,Male,Loyal Customer,41,Personal Travel,Eco,337,4,4,4,4,5,4,5,5,5,5,5,3,5,5,39,33.0,satisfied +61175,67930,Male,Loyal Customer,56,Personal Travel,Eco,1464,4,4,4,1,4,4,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +61176,23901,Female,Loyal Customer,59,Business travel,Eco,589,3,2,2,2,1,3,4,4,4,3,4,3,4,3,27,11.0,neutral or dissatisfied +61177,92785,Male,Loyal Customer,34,Personal Travel,Eco,1671,2,3,2,3,2,2,2,2,3,3,3,2,4,2,22,10.0,neutral or dissatisfied +61178,119322,Male,Loyal Customer,62,Personal Travel,Eco,214,3,4,3,1,5,3,2,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +61179,93423,Female,Loyal Customer,25,Business travel,Business,3580,1,5,5,5,1,1,1,1,2,5,4,1,4,1,0,4.0,neutral or dissatisfied +61180,61038,Female,disloyal Customer,41,Business travel,Business,1124,4,4,4,3,2,4,2,2,4,2,3,5,4,2,120,119.0,satisfied +61181,35499,Male,Loyal Customer,13,Personal Travel,Eco,1102,3,3,3,1,5,3,5,5,4,5,3,5,3,5,1,2.0,neutral or dissatisfied +61182,51883,Female,Loyal Customer,26,Business travel,Business,507,2,5,5,5,2,2,2,2,1,4,4,1,4,2,0,2.0,neutral or dissatisfied +61183,1745,Male,Loyal Customer,38,Personal Travel,Eco,327,2,3,2,2,4,2,4,4,4,3,4,3,5,4,59,63.0,neutral or dissatisfied +61184,8092,Male,Loyal Customer,43,Business travel,Business,3346,3,5,5,5,5,2,2,3,3,3,3,3,3,3,90,88.0,neutral or dissatisfied +61185,117068,Male,Loyal Customer,22,Business travel,Eco,646,2,5,5,5,2,2,4,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +61186,11499,Male,Loyal Customer,62,Personal Travel,Eco Plus,247,2,4,2,3,5,2,5,5,3,2,5,5,5,5,9,10.0,neutral or dissatisfied +61187,112600,Female,disloyal Customer,25,Business travel,Business,602,5,0,5,1,1,5,1,1,4,5,5,5,4,1,19,25.0,satisfied +61188,72357,Male,Loyal Customer,9,Personal Travel,Business,985,2,4,2,3,5,2,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +61189,90789,Female,Loyal Customer,62,Business travel,Business,406,2,5,5,5,2,3,4,2,2,2,2,1,2,1,2,7.0,neutral or dissatisfied +61190,24692,Female,Loyal Customer,53,Personal Travel,Eco,761,3,3,3,4,3,2,2,5,5,3,5,5,5,3,0,17.0,neutral or dissatisfied +61191,1048,Male,disloyal Customer,27,Business travel,Eco,158,2,2,2,3,2,2,2,2,3,5,4,4,4,2,0,2.0,neutral or dissatisfied +61192,123820,Male,disloyal Customer,21,Business travel,Eco,544,3,4,3,4,3,3,2,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +61193,91649,Male,Loyal Customer,33,Personal Travel,Eco,1199,2,1,2,4,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +61194,103852,Female,Loyal Customer,60,Business travel,Business,482,3,4,4,4,2,3,3,4,3,4,3,3,4,3,171,149.0,neutral or dissatisfied +61195,66747,Female,Loyal Customer,17,Personal Travel,Eco,802,3,4,3,3,2,3,2,2,4,2,5,2,4,2,0,0.0,neutral or dissatisfied +61196,2448,Female,Loyal Customer,23,Personal Travel,Eco Plus,604,3,4,3,4,3,3,3,3,4,4,5,4,4,3,20,23.0,neutral or dissatisfied +61197,39009,Male,Loyal Customer,69,Business travel,Business,2531,2,2,5,2,3,4,3,2,2,2,2,2,2,4,0,9.0,neutral or dissatisfied +61198,26049,Female,Loyal Customer,30,Business travel,Business,2907,1,1,1,1,3,3,3,3,5,1,5,5,4,3,8,0.0,satisfied +61199,31165,Female,Loyal Customer,50,Business travel,Business,627,4,4,4,4,3,3,2,3,3,3,3,2,3,2,25,27.0,satisfied +61200,103952,Female,Loyal Customer,37,Business travel,Eco,370,4,3,3,3,4,4,4,4,3,2,3,2,3,4,22,11.0,neutral or dissatisfied +61201,2429,Male,Loyal Customer,41,Personal Travel,Eco,604,3,4,3,4,1,3,1,1,3,2,5,4,4,1,12,12.0,neutral or dissatisfied +61202,67671,Female,Loyal Customer,53,Business travel,Business,3354,2,2,2,2,3,4,4,4,4,4,4,4,4,3,10,13.0,satisfied +61203,63294,Female,Loyal Customer,39,Business travel,Business,2655,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +61204,119038,Male,Loyal Customer,30,Business travel,Business,2378,4,4,4,4,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +61205,30330,Female,Loyal Customer,37,Business travel,Business,391,1,1,1,1,4,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +61206,795,Female,disloyal Customer,44,Business travel,Business,354,3,2,2,3,5,3,5,5,1,4,2,2,3,5,22,20.0,neutral or dissatisfied +61207,46935,Male,disloyal Customer,34,Business travel,Eco,844,3,4,4,1,2,4,2,2,5,3,1,3,2,2,0,0.0,neutral or dissatisfied +61208,241,Male,Loyal Customer,22,Business travel,Business,2689,2,2,2,2,5,5,5,5,4,3,5,4,5,5,10,27.0,satisfied +61209,40935,Female,disloyal Customer,52,Business travel,Eco Plus,590,2,2,2,3,1,2,1,1,3,1,3,3,2,1,0,0.0,neutral or dissatisfied +61210,62033,Female,Loyal Customer,56,Business travel,Business,2475,4,4,4,4,4,3,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +61211,14130,Female,Loyal Customer,19,Business travel,Business,2392,5,5,5,5,4,4,4,4,1,2,5,1,2,4,48,55.0,satisfied +61212,121935,Female,Loyal Customer,44,Personal Travel,Eco Plus,366,5,5,5,2,5,3,2,4,4,5,2,2,4,4,1,0.0,satisfied +61213,119453,Male,Loyal Customer,46,Business travel,Business,1978,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +61214,38023,Female,Loyal Customer,58,Business travel,Business,1237,4,2,2,2,3,3,2,4,4,4,4,1,4,4,42,47.0,neutral or dissatisfied +61215,36414,Female,Loyal Customer,33,Business travel,Business,369,1,1,1,1,5,2,3,3,3,4,3,1,3,4,0,0.0,satisfied +61216,6246,Female,Loyal Customer,13,Personal Travel,Eco,413,2,4,2,4,2,2,2,2,4,1,3,1,4,2,4,1.0,neutral or dissatisfied +61217,35419,Female,disloyal Customer,25,Business travel,Eco,1118,2,2,2,1,4,2,4,4,3,2,5,4,3,4,0,0.0,neutral or dissatisfied +61218,25681,Female,Loyal Customer,29,Business travel,Eco Plus,761,3,3,3,3,3,4,3,3,3,1,1,5,3,3,16,12.0,satisfied +61219,51365,Male,Loyal Customer,22,Personal Travel,Eco Plus,326,2,5,2,2,4,2,4,4,2,1,4,5,2,4,3,4.0,neutral or dissatisfied +61220,5583,Female,Loyal Customer,41,Personal Travel,Eco Plus,501,2,3,2,4,5,4,2,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +61221,80240,Male,Loyal Customer,42,Business travel,Business,1269,5,5,1,5,2,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +61222,97021,Male,Loyal Customer,32,Business travel,Business,3960,3,3,3,3,4,5,4,4,5,4,4,5,5,4,0,0.0,satisfied +61223,109149,Female,Loyal Customer,47,Business travel,Business,3496,4,4,4,4,2,4,5,4,4,4,4,3,4,5,19,6.0,satisfied +61224,71932,Male,Loyal Customer,51,Business travel,Eco Plus,1744,4,1,1,1,4,4,4,4,2,1,2,2,3,4,76,57.0,neutral or dissatisfied +61225,77686,Female,Loyal Customer,26,Business travel,Business,3404,1,2,2,2,1,1,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +61226,124427,Female,Loyal Customer,20,Personal Travel,Eco,1262,3,5,3,1,3,3,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +61227,37728,Male,Loyal Customer,27,Personal Travel,Eco,1028,3,4,3,4,5,3,3,5,3,3,4,5,4,5,15,5.0,neutral or dissatisfied +61228,1724,Male,disloyal Customer,20,Business travel,Eco,327,4,4,4,1,4,4,4,4,5,4,4,5,5,4,16,10.0,satisfied +61229,121238,Male,disloyal Customer,62,Business travel,Business,2075,2,2,2,1,1,2,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +61230,68086,Female,Loyal Customer,41,Business travel,Business,868,2,2,5,2,2,4,4,5,5,5,5,5,5,4,18,14.0,satisfied +61231,30641,Female,disloyal Customer,25,Business travel,Eco,533,5,0,5,4,3,5,3,3,1,2,1,2,2,3,0,4.0,satisfied +61232,99088,Male,Loyal Customer,40,Business travel,Business,2039,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +61233,48155,Male,Loyal Customer,41,Business travel,Business,173,4,4,4,4,3,2,5,4,4,4,4,1,4,1,0,0.0,satisfied +61234,48093,Male,Loyal Customer,50,Business travel,Eco,259,5,2,2,2,5,5,5,5,3,3,1,2,2,5,30,26.0,satisfied +61235,36826,Male,Loyal Customer,41,Business travel,Business,369,1,1,1,1,1,1,1,3,3,3,3,1,3,4,0,0.0,satisfied +61236,104061,Male,Loyal Customer,16,Personal Travel,Eco,1262,3,5,3,5,5,3,5,5,5,4,3,5,5,5,4,0.0,neutral or dissatisfied +61237,25469,Male,Loyal Customer,45,Business travel,Business,547,1,1,1,1,3,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +61238,17272,Female,Loyal Customer,14,Personal Travel,Eco,872,2,0,2,3,2,2,2,2,3,5,5,5,5,2,0,12.0,neutral or dissatisfied +61239,3369,Male,Loyal Customer,46,Business travel,Business,240,0,0,0,3,3,5,5,1,1,1,1,5,1,5,0,0.0,satisfied +61240,5900,Male,Loyal Customer,30,Business travel,Business,3156,2,4,4,4,1,1,2,1,2,2,3,2,3,1,0,0.0,neutral or dissatisfied +61241,64355,Male,Loyal Customer,36,Business travel,Business,3035,2,2,2,2,2,2,2,4,4,4,4,5,4,1,0,0.0,satisfied +61242,41663,Female,Loyal Customer,29,Business travel,Business,1616,1,3,4,3,1,1,1,1,2,1,4,3,4,1,24,9.0,neutral or dissatisfied +61243,34586,Female,Loyal Customer,46,Business travel,Eco,1617,2,2,5,5,3,2,2,2,2,2,2,4,2,1,11,13.0,neutral or dissatisfied +61244,129800,Male,Loyal Customer,27,Personal Travel,Eco,337,3,4,2,2,5,2,5,5,5,5,5,3,5,5,121,115.0,neutral or dissatisfied +61245,105754,Female,disloyal Customer,22,Business travel,Eco,842,3,3,3,1,1,3,1,1,3,1,1,1,1,1,0,7.0,neutral or dissatisfied +61246,71473,Female,Loyal Customer,25,Business travel,Business,3611,2,4,4,4,2,2,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +61247,17826,Male,Loyal Customer,42,Personal Travel,Eco,1149,2,5,2,3,5,2,5,5,4,3,4,4,4,5,10,3.0,neutral or dissatisfied +61248,97961,Male,Loyal Customer,66,Personal Travel,Eco,793,0,5,0,2,0,2,2,4,5,4,5,2,4,2,143,142.0,satisfied +61249,104893,Male,Loyal Customer,40,Business travel,Business,1565,3,3,5,3,5,4,5,5,5,5,5,5,5,5,11,23.0,satisfied +61250,27807,Male,Loyal Customer,32,Business travel,Eco,909,4,1,1,1,4,4,4,4,4,5,4,3,3,4,3,0.0,neutral or dissatisfied +61251,108483,Female,Loyal Customer,60,Business travel,Eco,570,4,2,2,2,5,3,2,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +61252,120140,Female,disloyal Customer,38,Business travel,Business,1475,1,1,1,4,4,1,4,4,4,2,5,3,4,4,29,23.0,neutral or dissatisfied +61253,70132,Male,Loyal Customer,62,Business travel,Business,2085,5,2,2,2,2,4,3,5,5,4,5,1,5,2,61,57.0,neutral or dissatisfied +61254,112578,Female,Loyal Customer,56,Business travel,Business,602,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +61255,23569,Female,disloyal Customer,20,Business travel,Eco,1015,1,1,1,3,4,1,4,4,1,4,4,2,3,4,2,36.0,neutral or dissatisfied +61256,50398,Female,Loyal Customer,16,Business travel,Business,373,3,2,2,2,3,3,3,3,4,1,3,2,4,3,12,0.0,neutral or dissatisfied +61257,101033,Male,Loyal Customer,57,Business travel,Eco Plus,406,4,4,4,4,4,4,4,4,5,2,3,1,3,4,68,67.0,satisfied +61258,19509,Male,Loyal Customer,49,Business travel,Business,2678,2,5,5,5,2,2,1,2,2,2,2,2,2,4,51,25.0,neutral or dissatisfied +61259,120233,Male,Loyal Customer,34,Personal Travel,Eco,1303,2,4,2,2,4,2,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +61260,24039,Female,Loyal Customer,37,Personal Travel,Eco,595,1,4,1,3,3,1,3,3,4,4,4,4,1,3,8,0.0,neutral or dissatisfied +61261,40051,Male,Loyal Customer,24,Personal Travel,Eco,866,3,3,3,4,2,3,2,2,4,1,3,1,3,2,0,13.0,neutral or dissatisfied +61262,68888,Female,Loyal Customer,9,Business travel,Eco,936,3,4,4,4,3,4,3,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +61263,104476,Female,Loyal Customer,56,Business travel,Eco,1671,4,3,5,3,3,2,3,4,4,4,4,2,4,1,2,0.0,neutral or dissatisfied +61264,89000,Female,Loyal Customer,62,Personal Travel,Eco Plus,1199,1,5,1,2,4,4,1,5,5,1,5,1,5,4,3,1.0,neutral or dissatisfied +61265,1736,Male,Loyal Customer,53,Personal Travel,Eco,364,2,4,2,1,3,2,3,3,4,4,5,4,5,3,0,6.0,neutral or dissatisfied +61266,58781,Female,disloyal Customer,57,Business travel,Eco,1012,1,0,0,4,3,0,3,3,1,3,3,1,3,3,0,3.0,neutral or dissatisfied +61267,1937,Female,Loyal Customer,60,Business travel,Business,3534,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +61268,68783,Male,disloyal Customer,49,Business travel,Business,926,4,4,4,1,1,4,1,1,4,2,5,5,5,1,0,0.0,satisfied +61269,106711,Female,Loyal Customer,54,Business travel,Eco Plus,516,4,4,4,4,2,4,3,4,4,4,4,2,4,4,17,16.0,neutral or dissatisfied +61270,84002,Male,Loyal Customer,40,Personal Travel,Eco,321,1,4,1,4,5,1,3,5,4,3,4,1,2,5,0,0.0,neutral or dissatisfied +61271,24755,Female,disloyal Customer,20,Business travel,Eco,447,2,0,2,4,5,2,5,5,5,1,3,3,2,5,0,0.0,neutral or dissatisfied +61272,78853,Male,Loyal Customer,74,Business travel,Eco Plus,128,4,4,4,4,4,4,4,4,3,1,4,1,2,4,0,0.0,satisfied +61273,11339,Male,Loyal Customer,23,Personal Travel,Eco,458,2,3,2,2,1,2,2,1,3,5,5,1,3,1,0,0.0,neutral or dissatisfied +61274,65286,Male,Loyal Customer,27,Personal Travel,Eco Plus,354,3,5,3,1,3,3,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +61275,29792,Female,Loyal Customer,33,Business travel,Business,2814,4,4,4,4,5,2,1,2,2,2,2,4,2,4,0,0.0,satisfied +61276,60549,Male,Loyal Customer,30,Business travel,Business,862,3,3,3,3,5,5,5,5,5,5,5,4,4,5,10,0.0,satisfied +61277,78686,Female,Loyal Customer,22,Personal Travel,Eco,674,2,2,2,3,3,2,3,3,1,1,3,2,3,3,0,33.0,neutral or dissatisfied +61278,60493,Female,disloyal Customer,20,Business travel,Eco,641,1,1,0,3,1,0,1,1,1,4,2,1,3,1,5,0.0,neutral or dissatisfied +61279,39723,Female,Loyal Customer,44,Business travel,Business,320,4,4,4,4,5,1,2,5,5,5,5,4,5,4,0,2.0,satisfied +61280,127848,Female,Loyal Customer,48,Business travel,Business,2658,3,3,3,3,4,4,5,2,2,3,2,4,2,3,11,14.0,satisfied +61281,64018,Female,Loyal Customer,41,Business travel,Business,919,4,4,3,4,3,5,5,4,4,4,4,4,4,5,0,19.0,satisfied +61282,95166,Male,Loyal Customer,47,Personal Travel,Eco,248,2,4,2,4,5,2,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +61283,94324,Male,Loyal Customer,55,Business travel,Business,3251,2,2,2,2,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +61284,57170,Male,Loyal Customer,25,Business travel,Business,2227,1,2,2,2,1,1,1,1,2,5,2,1,4,1,0,0.0,neutral or dissatisfied +61285,42638,Female,Loyal Customer,21,Personal Travel,Eco,546,5,3,5,3,2,5,3,2,5,1,4,2,2,2,71,80.0,satisfied +61286,32525,Male,Loyal Customer,44,Business travel,Business,2591,5,5,5,5,3,3,3,5,5,5,4,2,5,2,0,0.0,satisfied +61287,4376,Female,Loyal Customer,53,Business travel,Business,2418,3,4,4,4,3,3,3,3,5,2,2,3,4,3,930,952.0,neutral or dissatisfied +61288,43705,Female,Loyal Customer,65,Business travel,Eco,196,1,5,5,5,2,2,2,1,1,1,1,3,1,3,0,12.0,neutral or dissatisfied +61289,43584,Female,disloyal Customer,21,Business travel,Eco,228,2,4,2,3,4,2,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +61290,52285,Female,Loyal Customer,22,Business travel,Eco,370,3,3,3,3,3,3,2,3,4,2,4,1,4,3,0,16.0,neutral or dissatisfied +61291,47810,Male,Loyal Customer,32,Business travel,Business,3497,3,3,3,3,5,5,5,5,3,2,5,2,4,5,0,0.0,satisfied +61292,85810,Male,Loyal Customer,39,Personal Travel,Eco,666,4,1,4,4,1,4,1,1,1,5,3,2,3,1,0,0.0,neutral or dissatisfied +61293,115353,Male,Loyal Customer,60,Business travel,Business,1811,5,5,5,5,2,5,4,4,4,4,4,4,4,5,7,0.0,satisfied +61294,109529,Female,Loyal Customer,60,Business travel,Business,434,2,4,2,2,3,2,4,4,4,4,4,4,4,2,0,0.0,satisfied +61295,94220,Female,Loyal Customer,39,Business travel,Business,2495,2,2,2,2,3,4,5,5,5,5,5,3,5,3,111,110.0,satisfied +61296,39664,Male,Loyal Customer,43,Business travel,Business,2145,3,3,3,3,2,1,4,5,5,4,5,3,5,2,0,0.0,satisfied +61297,95544,Female,Loyal Customer,54,Personal Travel,Eco Plus,187,1,5,1,1,2,4,5,2,2,1,2,3,2,4,16,10.0,neutral or dissatisfied +61298,96087,Male,Loyal Customer,64,Personal Travel,Eco,758,2,3,2,2,4,2,4,4,4,3,2,2,2,4,10,0.0,neutral or dissatisfied +61299,76755,Male,Loyal Customer,60,Business travel,Business,1517,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +61300,114666,Female,Loyal Customer,32,Business travel,Business,373,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +61301,114972,Male,disloyal Customer,26,Business travel,Business,373,2,5,2,2,5,2,5,5,5,3,4,3,4,5,7,13.0,neutral or dissatisfied +61302,89512,Female,disloyal Customer,26,Business travel,Business,1076,3,3,3,3,3,3,5,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +61303,108602,Male,Loyal Customer,22,Business travel,Business,1982,2,2,1,1,2,2,2,2,2,2,3,2,3,2,67,67.0,neutral or dissatisfied +61304,62673,Female,Loyal Customer,65,Business travel,Eco Plus,1726,3,3,3,3,3,1,3,3,3,3,3,2,3,4,3,0.0,neutral or dissatisfied +61305,56040,Male,disloyal Customer,23,Business travel,Eco,782,4,5,5,4,4,5,5,3,5,2,3,5,4,5,0,4.0,neutral or dissatisfied +61306,2547,Male,Loyal Customer,41,Business travel,Business,3712,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +61307,63831,Male,Loyal Customer,52,Business travel,Business,1192,2,2,2,2,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +61308,36772,Female,Loyal Customer,31,Business travel,Business,2588,2,2,2,2,4,4,4,2,4,3,2,4,5,4,65,102.0,satisfied +61309,62247,Male,Loyal Customer,18,Personal Travel,Eco,2454,1,5,2,3,4,2,4,4,4,2,4,5,4,4,9,0.0,neutral or dissatisfied +61310,4903,Male,Loyal Customer,49,Business travel,Business,1959,1,1,1,1,4,4,4,4,4,4,5,4,4,4,1017,1011.0,satisfied +61311,9475,Female,Loyal Customer,57,Personal Travel,Eco Plus,310,3,5,3,2,3,5,5,2,2,3,4,3,2,4,0,0.0,neutral or dissatisfied +61312,22135,Female,disloyal Customer,21,Business travel,Eco,350,1,3,1,3,4,1,4,4,1,4,3,1,4,4,18,10.0,neutral or dissatisfied +61313,18975,Male,disloyal Customer,34,Business travel,Eco,792,3,3,3,4,4,3,4,4,5,3,3,3,5,4,71,74.0,neutral or dissatisfied +61314,68603,Female,Loyal Customer,41,Business travel,Eco,1739,2,5,5,5,2,2,2,2,3,1,2,3,4,2,1,0.0,neutral or dissatisfied +61315,65460,Male,Loyal Customer,39,Business travel,Business,2887,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +61316,55367,Female,Loyal Customer,43,Business travel,Business,3711,2,2,2,2,5,4,4,4,4,4,4,3,4,3,12,28.0,satisfied +61317,124472,Female,Loyal Customer,25,Personal Travel,Eco,980,4,3,4,4,2,4,2,2,2,2,3,4,4,2,12,9.0,neutral or dissatisfied +61318,43679,Female,Loyal Customer,15,Personal Travel,Business,196,1,4,1,2,3,1,3,3,5,4,5,3,4,3,3,0.0,neutral or dissatisfied +61319,65957,Female,disloyal Customer,44,Business travel,Business,1372,4,4,4,3,2,4,2,2,3,3,5,4,5,2,12,0.0,satisfied +61320,93729,Male,Loyal Customer,17,Personal Travel,Eco,630,1,5,1,2,1,2,2,4,3,5,5,2,4,2,156,157.0,neutral or dissatisfied +61321,120991,Female,Loyal Customer,40,Business travel,Business,920,3,4,2,4,3,3,3,3,3,3,3,1,3,2,3,5.0,neutral or dissatisfied +61322,10650,Male,Loyal Customer,56,Business travel,Business,1617,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +61323,102399,Female,disloyal Customer,23,Business travel,Eco,258,3,3,4,4,3,4,3,3,1,2,4,4,4,3,6,0.0,neutral or dissatisfied +61324,90017,Male,disloyal Customer,17,Business travel,Eco,1145,4,4,4,1,2,4,2,2,3,2,5,3,5,2,0,1.0,satisfied +61325,26381,Female,Loyal Customer,17,Personal Travel,Eco,894,4,4,4,4,3,4,3,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +61326,10961,Female,Loyal Customer,38,Business travel,Business,2648,5,5,5,5,2,2,3,5,5,5,4,3,5,3,14,3.0,satisfied +61327,118830,Male,Loyal Customer,40,Business travel,Eco Plus,647,1,5,5,5,1,1,1,1,1,5,3,4,3,1,56,52.0,neutral or dissatisfied +61328,57333,Male,disloyal Customer,26,Business travel,Eco,414,2,3,2,4,1,2,1,1,3,4,4,1,4,1,0,0.0,neutral or dissatisfied +61329,74110,Female,Loyal Customer,43,Business travel,Business,2437,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,53.0,satisfied +61330,16380,Female,Loyal Customer,47,Business travel,Business,2642,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +61331,6758,Female,Loyal Customer,42,Business travel,Business,2644,4,4,1,4,3,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +61332,127535,Male,Loyal Customer,63,Business travel,Business,2197,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +61333,31047,Male,Loyal Customer,30,Business travel,Business,775,5,2,5,5,5,5,5,5,1,3,1,2,1,5,0,0.0,satisfied +61334,109626,Female,Loyal Customer,59,Business travel,Business,3646,4,5,4,4,5,4,4,5,5,5,5,3,5,4,12,4.0,satisfied +61335,62299,Female,Loyal Customer,50,Business travel,Business,3558,0,0,0,1,2,5,5,1,1,1,1,3,1,4,0,0.0,satisfied +61336,72009,Female,Loyal Customer,25,Personal Travel,Eco Plus,1440,3,4,3,3,3,4,4,5,5,4,4,4,3,4,187,194.0,neutral or dissatisfied +61337,24957,Female,Loyal Customer,45,Business travel,Eco,226,5,1,1,1,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +61338,1208,Female,Loyal Customer,69,Personal Travel,Eco,134,1,4,0,3,4,4,3,1,1,0,1,4,1,2,10,0.0,neutral or dissatisfied +61339,19717,Female,disloyal Customer,16,Business travel,Eco,409,3,4,3,4,4,3,4,4,4,3,4,2,4,4,62,94.0,neutral or dissatisfied +61340,57186,Female,Loyal Customer,44,Business travel,Business,2227,4,4,4,4,3,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +61341,92789,Female,Loyal Customer,39,Business travel,Business,1671,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +61342,55350,Male,Loyal Customer,45,Business travel,Business,594,5,5,5,5,3,4,4,5,5,5,5,3,5,3,42,36.0,satisfied +61343,53041,Male,disloyal Customer,39,Business travel,Eco,790,4,4,4,3,2,4,2,2,4,1,4,4,5,2,23,0.0,satisfied +61344,71301,Male,Loyal Customer,33,Business travel,Business,1514,3,3,2,2,3,3,3,3,3,2,3,2,4,3,0,,neutral or dissatisfied +61345,17575,Male,Loyal Customer,45,Business travel,Eco,634,2,3,3,3,2,2,2,2,2,2,3,1,5,2,42,31.0,satisfied +61346,119346,Male,Loyal Customer,35,Business travel,Business,2926,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +61347,84642,Female,Loyal Customer,68,Personal Travel,Eco Plus,669,3,5,3,2,3,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +61348,116908,Female,Loyal Customer,54,Business travel,Business,304,0,0,0,1,4,5,5,4,4,4,4,5,4,5,45,42.0,satisfied +61349,111229,Female,Loyal Customer,48,Personal Travel,Eco,1447,3,1,3,3,4,4,4,5,5,3,2,3,5,4,0,0.0,neutral or dissatisfied +61350,11997,Male,Loyal Customer,42,Personal Travel,Eco,667,3,4,4,1,3,4,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +61351,58410,Male,disloyal Customer,50,Business travel,Business,473,3,3,3,3,1,3,1,1,3,4,4,5,4,1,5,0.0,neutral or dissatisfied +61352,61616,Female,disloyal Customer,21,Business travel,Business,1303,5,0,5,4,2,5,2,2,3,2,4,3,5,2,16,0.0,satisfied +61353,31592,Female,Loyal Customer,40,Business travel,Eco,602,3,1,1,1,3,4,3,3,3,4,2,1,4,3,6,9.0,satisfied +61354,111786,Male,Loyal Customer,68,Personal Travel,Eco,1620,3,5,3,1,4,3,5,4,4,5,5,4,5,4,60,55.0,neutral or dissatisfied +61355,7406,Female,Loyal Customer,40,Business travel,Business,522,3,3,3,3,5,4,5,5,5,5,5,5,5,5,81,130.0,satisfied +61356,91699,Female,Loyal Customer,44,Business travel,Business,3080,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +61357,100559,Female,Loyal Customer,28,Business travel,Business,486,3,3,3,3,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +61358,61562,Female,Loyal Customer,23,Personal Travel,Eco Plus,2288,2,5,2,1,2,2,2,2,2,4,3,3,2,2,0,0.0,neutral or dissatisfied +61359,78433,Female,Loyal Customer,55,Business travel,Business,2630,2,2,2,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +61360,43036,Male,Loyal Customer,50,Business travel,Eco,192,4,2,2,2,4,4,4,4,3,2,5,4,4,4,6,0.0,satisfied +61361,12827,Female,Loyal Customer,24,Business travel,Eco,489,2,2,2,2,2,2,3,2,3,3,3,2,4,2,0,6.0,neutral or dissatisfied +61362,51270,Male,Loyal Customer,51,Business travel,Eco Plus,326,5,5,5,5,5,5,5,5,2,3,3,2,4,5,0,0.0,satisfied +61363,48152,Male,Loyal Customer,43,Business travel,Eco,259,5,3,3,3,5,5,5,5,5,5,2,2,5,5,0,0.0,satisfied +61364,93823,Male,disloyal Customer,34,Business travel,Business,391,3,3,3,2,1,3,1,1,4,5,4,4,5,1,18,12.0,neutral or dissatisfied +61365,107173,Male,Loyal Customer,29,Business travel,Business,1826,1,1,1,1,5,5,5,5,5,3,4,5,5,5,19,0.0,satisfied +61366,100237,Male,Loyal Customer,44,Personal Travel,Business,1052,4,4,4,4,2,5,5,5,5,4,5,5,5,4,0,2.0,neutral or dissatisfied +61367,13252,Male,Loyal Customer,46,Business travel,Business,3363,3,3,3,3,2,3,4,3,3,3,3,2,3,4,14,42.0,neutral or dissatisfied +61368,13597,Male,Loyal Customer,35,Personal Travel,Eco,227,1,5,0,1,5,0,5,5,5,4,4,5,5,5,0,18.0,neutral or dissatisfied +61369,114836,Male,Loyal Customer,37,Business travel,Business,308,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,8.0,satisfied +61370,75331,Female,Loyal Customer,49,Business travel,Business,2556,4,5,5,5,4,4,4,2,4,1,1,4,4,4,0,7.0,neutral or dissatisfied +61371,60123,Male,Loyal Customer,41,Business travel,Business,1182,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +61372,41511,Male,disloyal Customer,13,Business travel,Eco,1235,4,4,4,3,2,4,4,2,5,3,5,2,5,2,0,9.0,satisfied +61373,124163,Female,Loyal Customer,57,Business travel,Business,2133,1,1,1,1,4,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +61374,42910,Female,Loyal Customer,39,Personal Travel,Eco,368,3,5,3,1,2,3,2,2,3,2,5,1,5,2,0,0.0,neutral or dissatisfied +61375,13296,Female,Loyal Customer,13,Business travel,Eco Plus,657,1,3,3,3,2,3,1,4,5,3,4,1,2,1,201,186.0,neutral or dissatisfied +61376,25717,Male,Loyal Customer,50,Business travel,Eco,447,4,3,3,3,4,4,4,4,3,5,5,3,4,4,30,26.0,satisfied +61377,27648,Female,Loyal Customer,54,Personal Travel,Eco Plus,697,3,4,3,2,3,3,1,4,4,3,4,2,4,3,17,6.0,neutral or dissatisfied +61378,23320,Female,Loyal Customer,61,Business travel,Business,3440,5,5,5,5,3,2,3,5,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +61379,3220,Female,disloyal Customer,23,Business travel,Business,1187,4,3,4,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +61380,90130,Female,Loyal Customer,44,Business travel,Eco,1145,1,2,2,2,1,2,2,3,3,3,3,2,1,2,152,151.0,neutral or dissatisfied +61381,82875,Male,disloyal Customer,22,Business travel,Business,594,4,0,4,3,5,4,5,5,3,4,4,3,5,5,0,0.0,satisfied +61382,86127,Female,disloyal Customer,34,Business travel,Business,306,2,2,2,2,4,2,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +61383,35710,Male,Loyal Customer,43,Personal Travel,Eco,2475,3,4,3,4,3,1,1,3,2,3,4,1,5,1,11,0.0,neutral or dissatisfied +61384,41923,Female,disloyal Customer,30,Business travel,Eco,129,4,1,5,4,1,5,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +61385,40330,Female,disloyal Customer,37,Business travel,Eco Plus,347,2,2,2,2,4,2,4,4,2,2,2,3,3,4,0,0.0,neutral or dissatisfied +61386,129389,Male,Loyal Customer,53,Personal Travel,Eco Plus,2454,1,1,1,3,2,1,2,2,4,5,3,4,2,2,9,0.0,neutral or dissatisfied +61387,18357,Female,disloyal Customer,30,Business travel,Eco Plus,314,0,0,0,4,2,0,2,2,5,3,1,4,2,2,0,0.0,satisfied +61388,90961,Female,disloyal Customer,26,Business travel,Eco,366,4,0,4,3,2,4,2,2,2,3,1,4,2,2,0,0.0,neutral or dissatisfied +61389,98264,Female,Loyal Customer,60,Business travel,Business,1896,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +61390,106875,Female,Loyal Customer,54,Business travel,Eco,577,3,4,4,4,1,4,4,3,3,3,3,4,3,4,0,10.0,neutral or dissatisfied +61391,23503,Female,Loyal Customer,45,Business travel,Business,349,3,3,3,3,2,2,3,4,4,4,4,1,4,1,0,0.0,satisfied +61392,14516,Female,Loyal Customer,58,Business travel,Eco,288,4,5,5,5,4,3,4,4,4,4,4,1,4,3,6,1.0,satisfied +61393,26893,Male,Loyal Customer,43,Personal Travel,Eco,689,3,3,3,3,5,3,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +61394,126725,Male,Loyal Customer,45,Business travel,Business,2402,2,1,2,2,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +61395,63187,Male,Loyal Customer,39,Business travel,Business,2712,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +61396,73117,Female,Loyal Customer,50,Personal Travel,Eco,2174,5,4,5,3,2,4,5,2,2,5,2,5,2,5,0,0.0,satisfied +61397,99610,Female,Loyal Customer,45,Personal Travel,Eco Plus,802,4,3,4,4,1,4,4,4,4,4,5,2,4,1,0,0.0,satisfied +61398,101842,Female,Loyal Customer,65,Personal Travel,Eco Plus,1521,2,2,2,2,3,1,2,4,4,2,4,4,4,3,1,0.0,neutral or dissatisfied +61399,66363,Male,Loyal Customer,21,Personal Travel,Eco,986,2,5,2,1,4,2,4,4,4,3,5,3,5,4,23,25.0,neutral or dissatisfied +61400,62972,Female,Loyal Customer,30,Business travel,Business,2753,4,4,4,4,4,4,4,4,1,3,1,3,2,4,2,8.0,neutral or dissatisfied +61401,76107,Male,Loyal Customer,22,Business travel,Eco Plus,669,2,1,1,1,2,2,4,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +61402,11475,Male,Loyal Customer,20,Business travel,Eco Plus,216,4,3,3,3,4,4,3,4,2,3,1,4,4,4,11,5.0,satisfied +61403,57947,Male,Loyal Customer,7,Personal Travel,Business,1062,2,4,2,3,2,2,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +61404,5355,Male,disloyal Customer,48,Business travel,Business,785,5,5,5,4,1,5,5,1,3,4,4,4,5,1,0,0.0,satisfied +61405,124760,Female,Loyal Customer,54,Business travel,Business,3639,1,1,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +61406,49197,Female,Loyal Customer,50,Business travel,Business,110,5,3,5,5,2,1,1,3,3,4,4,4,3,2,22,24.0,satisfied +61407,63468,Female,Loyal Customer,17,Business travel,Eco Plus,372,3,5,5,5,3,3,3,3,4,2,4,1,3,3,0,3.0,neutral or dissatisfied +61408,2031,Female,disloyal Customer,29,Business travel,Business,785,2,2,2,4,4,2,3,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +61409,19,Female,Loyal Customer,11,Personal Travel,Eco,853,3,5,3,2,5,3,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +61410,1147,Male,Loyal Customer,47,Personal Travel,Eco,164,1,4,0,2,5,0,5,5,4,2,4,3,4,5,0,3.0,neutral or dissatisfied +61411,15647,Female,Loyal Customer,45,Personal Travel,Eco Plus,296,2,4,2,2,4,4,4,5,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +61412,5595,Male,disloyal Customer,23,Business travel,Eco,685,0,0,0,1,1,0,1,1,4,4,4,5,5,1,0,0.0,satisfied +61413,20545,Male,Loyal Customer,53,Business travel,Eco,633,5,1,4,1,5,5,5,5,4,3,4,1,5,5,12,3.0,satisfied +61414,99405,Male,disloyal Customer,22,Business travel,Eco,337,1,2,1,3,4,1,4,4,2,1,4,1,3,4,0,0.0,neutral or dissatisfied +61415,128208,Female,disloyal Customer,37,Business travel,Business,602,2,2,2,2,2,2,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +61416,36260,Female,Loyal Customer,55,Business travel,Eco,612,1,5,5,5,4,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +61417,79518,Male,Loyal Customer,46,Business travel,Business,1948,4,4,2,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +61418,107325,Female,Loyal Customer,63,Personal Travel,Business,632,3,2,3,4,1,3,4,4,4,3,4,2,4,4,17,0.0,neutral or dissatisfied +61419,92086,Male,Loyal Customer,12,Business travel,Business,1532,2,2,2,2,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +61420,45043,Male,Loyal Customer,63,Business travel,Business,265,5,5,5,5,5,2,2,5,5,5,5,4,5,5,10,2.0,satisfied +61421,32551,Female,disloyal Customer,33,Business travel,Eco,102,2,1,2,4,5,2,2,5,4,1,3,2,4,5,0,15.0,neutral or dissatisfied +61422,120193,Male,Loyal Customer,57,Business travel,Business,1496,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,15.0,satisfied +61423,115212,Female,Loyal Customer,35,Business travel,Business,3943,2,2,2,2,4,5,5,3,3,3,3,3,3,3,10,2.0,satisfied +61424,77877,Male,Loyal Customer,64,Personal Travel,Eco,1416,2,4,2,1,1,2,1,1,4,4,5,3,2,1,8,20.0,neutral or dissatisfied +61425,47390,Female,disloyal Customer,26,Business travel,Eco,584,2,1,2,4,1,2,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +61426,40765,Male,Loyal Customer,29,Business travel,Business,1959,2,3,3,3,2,2,2,2,4,2,2,3,3,2,0,0.0,neutral or dissatisfied +61427,51070,Female,Loyal Customer,30,Personal Travel,Eco,373,2,5,2,4,3,2,3,3,1,3,3,4,1,3,0,7.0,neutral or dissatisfied +61428,25532,Male,Loyal Customer,38,Personal Travel,Eco,516,2,5,5,1,3,5,1,3,2,4,2,3,1,3,0,0.0,neutral or dissatisfied +61429,127852,Female,Loyal Customer,50,Personal Travel,Business,1276,3,4,3,2,5,4,5,3,3,3,1,3,3,4,0,4.0,neutral or dissatisfied +61430,110719,Male,Loyal Customer,42,Business travel,Business,3703,5,5,4,5,5,4,4,4,4,5,4,4,4,4,9,8.0,satisfied +61431,113014,Male,Loyal Customer,42,Business travel,Business,1797,2,2,2,2,4,4,5,5,5,5,5,5,5,3,10,0.0,satisfied +61432,112986,Female,Loyal Customer,22,Business travel,Business,1797,4,5,5,5,4,4,4,4,3,2,4,2,4,4,0,0.0,neutral or dissatisfied +61433,80764,Female,Loyal Customer,66,Personal Travel,Eco,629,2,5,2,3,2,4,5,1,1,2,1,5,1,4,0,4.0,neutral or dissatisfied +61434,37720,Female,Loyal Customer,12,Personal Travel,Eco,944,3,4,3,3,4,3,4,4,2,5,2,5,3,4,0,3.0,neutral or dissatisfied +61435,95849,Female,Loyal Customer,28,Business travel,Business,3885,3,3,3,3,4,4,4,4,4,4,4,5,5,4,6,12.0,satisfied +61436,10484,Female,Loyal Customer,44,Business travel,Business,2192,3,3,3,3,4,5,5,4,4,5,4,4,4,3,27,23.0,satisfied +61437,62647,Female,Loyal Customer,13,Personal Travel,Eco,1744,2,5,2,2,1,2,1,1,5,2,5,3,4,1,3,16.0,neutral or dissatisfied +61438,93175,Female,Loyal Customer,30,Personal Travel,Eco,1075,2,4,2,3,1,2,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +61439,16751,Female,Loyal Customer,54,Business travel,Eco,569,5,5,4,5,4,1,5,5,5,5,5,1,5,3,0,10.0,satisfied +61440,72389,Male,Loyal Customer,28,Business travel,Business,964,5,5,5,5,4,4,4,4,5,5,4,3,5,4,0,8.0,satisfied +61441,69037,Male,Loyal Customer,45,Business travel,Business,1389,5,5,5,5,5,4,5,5,5,5,5,5,5,3,25,7.0,satisfied +61442,19613,Male,Loyal Customer,65,Business travel,Business,3785,2,2,3,2,2,3,4,5,5,5,5,5,5,2,0,0.0,satisfied +61443,74456,Male,Loyal Customer,36,Business travel,Business,1242,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +61444,127836,Female,Loyal Customer,36,Personal Travel,Eco,1044,2,4,3,4,2,3,2,2,5,5,4,3,5,2,12,9.0,neutral or dissatisfied +61445,88617,Male,Loyal Customer,25,Personal Travel,Eco,270,1,2,1,4,2,1,2,2,1,2,4,3,4,2,9,10.0,neutral or dissatisfied +61446,89105,Male,Loyal Customer,66,Business travel,Eco,1947,1,2,5,5,1,1,1,1,1,3,2,1,3,1,0,0.0,neutral or dissatisfied +61447,109193,Female,Loyal Customer,22,Business travel,Business,2159,3,4,4,4,3,3,3,3,2,3,3,3,4,3,9,10.0,neutral or dissatisfied +61448,40333,Female,Loyal Customer,69,Personal Travel,Eco Plus,531,1,4,1,3,5,5,4,2,2,1,1,3,2,3,0,8.0,neutral or dissatisfied +61449,38624,Male,Loyal Customer,38,Personal Travel,Business,2602,1,4,1,1,5,3,5,2,2,1,2,4,2,4,40,1.0,neutral or dissatisfied +61450,99643,Female,Loyal Customer,12,Business travel,Business,1670,3,1,1,1,3,3,3,3,2,4,2,2,4,3,12,6.0,neutral or dissatisfied +61451,107721,Female,Loyal Customer,77,Business travel,Business,1512,1,3,3,3,1,4,4,1,1,1,1,3,1,4,22,29.0,neutral or dissatisfied +61452,119753,Male,Loyal Customer,19,Personal Travel,Eco,1303,4,5,4,1,2,4,2,2,4,5,5,3,4,2,35,35.0,neutral or dissatisfied +61453,126012,Male,Loyal Customer,44,Business travel,Business,590,2,2,2,2,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +61454,27829,Female,Loyal Customer,56,Personal Travel,Eco,1533,5,5,5,2,3,3,4,2,2,5,2,4,2,4,0,0.0,satisfied +61455,41138,Female,Loyal Customer,19,Personal Travel,Eco,191,1,5,1,5,5,1,5,5,5,3,5,5,5,5,1,1.0,neutral or dissatisfied +61456,48629,Female,disloyal Customer,50,Business travel,Business,109,1,1,1,4,1,1,1,1,4,4,5,3,5,1,0,13.0,neutral or dissatisfied +61457,47314,Female,Loyal Customer,39,Business travel,Eco,599,4,4,4,4,4,4,4,4,4,4,2,1,4,4,70,65.0,satisfied +61458,15371,Female,Loyal Customer,31,Business travel,Eco,433,3,5,5,5,3,4,3,3,1,3,2,2,2,3,13,1.0,satisfied +61459,114543,Male,Loyal Customer,21,Personal Travel,Business,447,1,4,1,5,5,1,5,5,4,2,4,3,5,5,86,66.0,neutral or dissatisfied +61460,118935,Female,Loyal Customer,55,Business travel,Eco,1618,4,4,4,4,1,4,3,5,5,4,5,2,5,1,22,0.0,neutral or dissatisfied +61461,30678,Female,Loyal Customer,32,Business travel,Business,680,2,2,2,2,5,5,5,2,4,5,5,5,2,5,100,170.0,satisfied +61462,74011,Male,Loyal Customer,41,Personal Travel,Business,1471,3,5,3,1,2,5,4,3,3,3,3,5,3,5,2,14.0,neutral or dissatisfied +61463,15679,Male,Loyal Customer,16,Business travel,Business,563,2,2,2,2,4,4,4,4,5,3,5,2,2,4,0,7.0,satisfied +61464,49481,Male,disloyal Customer,27,Business travel,Eco,250,3,5,3,5,5,3,3,5,5,4,3,1,5,5,89,101.0,neutral or dissatisfied +61465,97295,Female,disloyal Customer,38,Business travel,Business,347,3,3,3,3,3,3,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +61466,24864,Male,disloyal Customer,40,Business travel,Business,356,1,1,1,1,3,1,4,3,2,2,4,1,2,3,0,0.0,neutral or dissatisfied +61467,104059,Male,Loyal Customer,67,Personal Travel,Eco,1262,1,5,1,1,5,1,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +61468,73436,Male,Loyal Customer,22,Personal Travel,Eco,1144,3,4,3,4,2,3,4,2,5,2,3,5,4,2,0,0.0,neutral or dissatisfied +61469,52867,Female,Loyal Customer,44,Business travel,Business,1024,2,2,2,2,1,2,1,2,2,2,2,1,2,4,0,0.0,satisfied +61470,115059,Male,Loyal Customer,33,Business travel,Business,342,5,5,5,5,4,5,4,4,3,3,4,3,5,4,13,5.0,satisfied +61471,42429,Male,Loyal Customer,32,Personal Travel,Eco Plus,817,3,4,3,4,5,3,3,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +61472,65403,Male,Loyal Customer,46,Personal Travel,Eco,631,1,4,1,4,3,1,4,3,4,5,5,4,4,3,14,55.0,neutral or dissatisfied +61473,84014,Female,Loyal Customer,59,Personal Travel,Eco,321,3,2,3,4,4,4,4,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +61474,24856,Female,disloyal Customer,33,Business travel,Business,356,3,3,3,5,3,3,3,3,3,5,5,4,5,3,0,3.0,neutral or dissatisfied +61475,126270,Female,Loyal Customer,36,Business travel,Eco,190,2,2,2,2,2,2,2,2,1,2,3,3,3,2,0,0.0,neutral or dissatisfied +61476,43216,Female,Loyal Customer,57,Business travel,Business,472,3,2,3,3,4,2,5,4,4,4,4,3,4,1,5,10.0,satisfied +61477,50901,Male,Loyal Customer,17,Personal Travel,Eco,304,3,4,3,5,1,3,3,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +61478,58689,Male,Loyal Customer,53,Business travel,Business,299,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,6.0,satisfied +61479,15093,Female,Loyal Customer,24,Business travel,Business,2143,0,0,0,3,1,1,1,1,5,4,3,5,1,1,86,82.0,satisfied +61480,90378,Female,Loyal Customer,35,Business travel,Business,1879,4,2,2,2,5,4,3,4,4,4,4,3,4,3,13,14.0,neutral or dissatisfied +61481,78782,Female,disloyal Customer,27,Business travel,Eco,528,4,4,4,3,3,4,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +61482,72036,Female,Loyal Customer,38,Personal Travel,Eco,3784,1,1,1,3,1,4,4,2,4,2,2,4,2,4,0,0.0,neutral or dissatisfied +61483,61565,Male,Loyal Customer,38,Personal Travel,Eco Plus,2288,3,1,2,3,1,2,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +61484,107056,Female,Loyal Customer,71,Business travel,Business,3439,3,1,5,1,3,1,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +61485,33519,Female,Loyal Customer,61,Personal Travel,Eco Plus,1554,2,2,2,3,2,4,3,5,5,2,5,3,5,1,0,2.0,neutral or dissatisfied +61486,76094,Male,Loyal Customer,38,Personal Travel,Eco,707,3,5,3,5,4,3,4,4,5,2,5,5,5,4,3,0.0,neutral or dissatisfied +61487,36191,Female,Loyal Customer,55,Personal Travel,Business,280,3,3,4,3,3,2,2,3,3,4,1,1,3,2,0,0.0,neutral or dissatisfied +61488,73250,Female,disloyal Customer,28,Business travel,Eco,675,3,3,3,3,2,3,4,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +61489,122541,Male,Loyal Customer,51,Business travel,Business,500,5,5,5,5,5,5,4,3,3,3,3,4,3,4,64,50.0,satisfied +61490,101592,Male,Loyal Customer,40,Business travel,Business,2907,2,2,2,2,2,5,5,5,5,5,5,5,5,3,3,0.0,satisfied +61491,104721,Male,Loyal Customer,39,Business travel,Business,1342,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +61492,128485,Female,Loyal Customer,16,Personal Travel,Eco,647,3,5,3,5,2,3,2,2,2,4,5,4,3,2,0,0.0,neutral or dissatisfied +61493,28134,Male,Loyal Customer,48,Business travel,Business,569,1,1,1,1,2,2,5,4,4,3,4,3,4,1,0,0.0,satisfied +61494,20747,Female,Loyal Customer,37,Personal Travel,Eco,363,2,3,2,2,3,2,3,3,3,1,2,3,2,3,22,8.0,neutral or dissatisfied +61495,47907,Male,Loyal Customer,25,Business travel,Eco,348,3,2,2,2,3,3,4,3,1,1,4,3,4,3,19,10.0,neutral or dissatisfied +61496,117858,Male,Loyal Customer,50,Business travel,Business,1630,0,0,0,2,4,4,5,5,5,5,5,3,5,3,6,2.0,satisfied +61497,73314,Male,disloyal Customer,27,Business travel,Business,1120,4,3,3,3,4,3,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +61498,67689,Male,Loyal Customer,28,Business travel,Business,1610,2,2,2,2,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +61499,120,Male,Loyal Customer,40,Business travel,Business,3043,4,2,2,2,3,4,4,1,1,1,4,1,1,2,38,29.0,neutral or dissatisfied +61500,89958,Male,Loyal Customer,29,Personal Travel,Eco,1306,2,3,2,3,4,2,4,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +61501,121961,Female,disloyal Customer,50,Business travel,Business,430,2,1,1,1,2,2,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +61502,38163,Female,Loyal Customer,34,Personal Travel,Eco,1237,3,4,3,4,2,3,2,2,3,4,1,1,5,2,34,25.0,neutral or dissatisfied +61503,53211,Male,Loyal Customer,28,Business travel,Business,2837,4,5,5,5,4,4,4,4,3,1,2,3,3,4,34,37.0,neutral or dissatisfied +61504,30270,Male,Loyal Customer,25,Business travel,Business,1805,2,3,3,3,2,2,2,2,3,1,3,3,4,2,8,0.0,neutral or dissatisfied +61505,19736,Male,Loyal Customer,56,Personal Travel,Eco,475,3,4,3,3,5,3,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +61506,111353,Male,disloyal Customer,30,Business travel,Eco,777,2,2,2,5,2,2,2,2,3,5,1,3,5,2,0,0.0,neutral or dissatisfied +61507,57486,Male,Loyal Customer,63,Personal Travel,Eco,1589,1,5,0,2,3,0,3,3,3,4,5,4,5,3,0,43.0,neutral or dissatisfied +61508,90696,Female,Loyal Customer,67,Business travel,Eco,444,1,2,2,2,5,4,4,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +61509,109604,Male,Loyal Customer,54,Business travel,Business,829,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +61510,87031,Female,Loyal Customer,51,Business travel,Business,640,2,2,5,2,3,4,4,3,3,4,3,4,3,4,28,20.0,satisfied +61511,28566,Female,Loyal Customer,44,Business travel,Business,2562,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +61512,30929,Male,Loyal Customer,22,Personal Travel,Eco Plus,896,3,4,3,3,4,3,2,4,2,2,2,3,3,4,19,28.0,neutral or dissatisfied +61513,18902,Female,Loyal Customer,35,Personal Travel,Eco,448,5,5,5,1,4,5,4,4,3,4,5,3,5,4,47,44.0,satisfied +61514,50038,Female,Loyal Customer,31,Business travel,Business,190,3,3,3,3,4,4,4,4,2,2,4,1,4,4,0,0.0,satisfied +61515,76637,Male,Loyal Customer,36,Business travel,Business,3318,5,5,5,5,1,3,4,5,5,5,3,5,5,3,9,0.0,satisfied +61516,74769,Male,Loyal Customer,42,Personal Travel,Eco,1431,1,4,1,5,2,1,5,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +61517,54625,Female,Loyal Customer,46,Business travel,Business,854,5,5,5,5,4,5,1,4,4,4,4,5,4,5,0,0.0,satisfied +61518,8135,Female,disloyal Customer,23,Business travel,Eco,402,3,3,3,3,1,3,2,1,1,4,4,2,4,1,0,1.0,neutral or dissatisfied +61519,56669,Female,Loyal Customer,35,Personal Travel,Eco,1065,1,5,1,1,5,1,1,5,3,3,5,5,4,5,11,0.0,neutral or dissatisfied +61520,51835,Female,disloyal Customer,18,Business travel,Eco Plus,369,2,4,2,3,3,2,5,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +61521,124183,Female,Loyal Customer,34,Personal Travel,Eco,2089,3,5,3,1,3,3,2,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +61522,87408,Female,Loyal Customer,56,Personal Travel,Eco,425,5,0,5,3,1,3,5,2,2,5,5,5,2,2,2,3.0,satisfied +61523,94848,Female,disloyal Customer,33,Business travel,Eco,189,3,4,2,4,3,2,1,3,3,3,3,4,3,3,4,10.0,neutral or dissatisfied +61524,54383,Female,Loyal Customer,68,Business travel,Business,305,4,4,4,4,5,3,3,4,4,4,4,3,4,2,0,0.0,satisfied +61525,15969,Female,Loyal Customer,25,Business travel,Eco Plus,607,4,3,3,3,4,4,3,4,5,3,5,4,3,4,8,0.0,satisfied +61526,44077,Male,Loyal Customer,45,Business travel,Business,3769,4,3,3,3,1,3,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +61527,25167,Female,disloyal Customer,39,Business travel,Business,369,1,1,1,5,1,1,1,1,1,5,1,2,3,1,0,0.0,neutral or dissatisfied +61528,83676,Male,disloyal Customer,43,Business travel,Business,577,3,3,3,2,3,5,5,5,4,5,5,5,3,5,921,924.0,neutral or dissatisfied +61529,20869,Male,Loyal Customer,41,Personal Travel,Eco,534,1,5,1,5,5,1,3,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +61530,66387,Male,disloyal Customer,49,Business travel,Business,1562,4,5,5,3,2,4,2,2,3,4,5,3,5,2,1,4.0,satisfied +61531,73932,Male,Loyal Customer,64,Business travel,Business,2342,1,1,1,1,3,2,3,1,1,1,1,4,1,4,3,0.0,neutral or dissatisfied +61532,50854,Male,Loyal Customer,35,Personal Travel,Eco,326,4,4,4,4,5,4,5,5,3,3,4,2,4,5,0,10.0,neutral or dissatisfied +61533,21059,Female,Loyal Customer,56,Business travel,Business,227,5,5,5,5,5,1,3,5,5,5,5,3,5,1,7,0.0,satisfied +61534,38739,Female,disloyal Customer,26,Business travel,Eco,353,2,5,2,4,4,2,1,4,2,3,5,1,4,4,8,3.0,neutral or dissatisfied +61535,90558,Female,Loyal Customer,49,Business travel,Business,270,3,3,3,3,5,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +61536,13167,Female,Loyal Customer,24,Personal Travel,Eco Plus,427,5,2,5,4,3,5,3,3,3,1,4,4,4,3,0,0.0,satisfied +61537,14775,Female,Loyal Customer,26,Business travel,Eco,694,4,1,2,2,4,4,5,4,5,3,2,4,3,4,0,0.0,satisfied +61538,31313,Female,Loyal Customer,59,Business travel,Eco,680,1,2,2,2,2,3,3,1,1,1,1,2,1,4,9,38.0,neutral or dissatisfied +61539,65817,Male,Loyal Customer,31,Business travel,Eco,1417,1,4,4,4,1,1,1,1,3,1,3,1,2,1,0,0.0,neutral or dissatisfied +61540,97968,Male,Loyal Customer,19,Personal Travel,Eco,483,4,1,4,3,5,4,5,5,2,3,3,1,3,5,30,38.0,neutral or dissatisfied +61541,28899,Male,Loyal Customer,41,Business travel,Eco,978,2,3,3,3,2,2,2,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +61542,122612,Female,disloyal Customer,40,Business travel,Business,328,3,3,3,1,3,3,3,3,1,3,3,2,2,3,0,0.0,neutral or dissatisfied +61543,4503,Male,Loyal Customer,52,Business travel,Business,435,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +61544,53619,Female,Loyal Customer,48,Business travel,Business,1874,4,4,2,4,2,4,4,5,5,5,5,2,5,3,45,50.0,satisfied +61545,52021,Male,Loyal Customer,64,Business travel,Business,328,0,0,0,1,2,5,4,5,5,5,5,2,5,1,0,0.0,satisfied +61546,63459,Female,Loyal Customer,61,Business travel,Business,337,1,1,1,1,2,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +61547,112869,Male,Loyal Customer,55,Business travel,Business,1357,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +61548,116243,Male,Loyal Customer,15,Personal Travel,Eco,358,2,4,2,2,5,2,5,5,3,4,4,5,4,5,3,0.0,neutral or dissatisfied +61549,80548,Male,Loyal Customer,56,Business travel,Business,1747,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +61550,69101,Female,disloyal Customer,27,Business travel,Business,1389,5,5,5,4,2,5,2,2,4,2,5,5,5,2,75,103.0,satisfied +61551,71941,Male,Loyal Customer,59,Business travel,Business,1846,5,5,5,5,3,3,5,5,5,5,5,5,5,4,0,3.0,satisfied +61552,79073,Female,Loyal Customer,66,Business travel,Business,3421,3,3,3,3,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +61553,67818,Female,Loyal Customer,59,Business travel,Eco,835,4,4,2,4,4,4,5,4,4,4,4,3,4,3,3,0.0,satisfied +61554,112648,Female,Loyal Customer,39,Personal Travel,Eco,1756,2,5,2,4,5,2,5,5,1,5,3,5,3,5,0,1.0,neutral or dissatisfied +61555,104276,Female,Loyal Customer,49,Business travel,Business,1643,3,3,3,3,1,3,3,3,3,3,3,2,3,3,18,34.0,neutral or dissatisfied +61556,40892,Female,Loyal Customer,31,Personal Travel,Eco,584,2,4,2,2,2,2,1,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +61557,73243,Male,Loyal Customer,9,Business travel,Business,1890,1,1,4,1,4,4,4,4,4,2,4,4,5,4,0,0.0,satisfied +61558,52597,Female,Loyal Customer,22,Business travel,Business,160,1,5,5,5,1,1,1,1,3,2,3,2,4,1,0,0.0,neutral or dissatisfied +61559,28677,Female,disloyal Customer,21,Business travel,Eco,1108,3,3,3,2,3,4,4,5,4,3,5,4,1,4,0,0.0,neutral or dissatisfied +61560,121741,Female,Loyal Customer,69,Personal Travel,Eco,1475,3,4,3,3,1,2,3,5,5,3,5,4,5,3,0,3.0,neutral or dissatisfied +61561,67989,Male,Loyal Customer,45,Personal Travel,Eco Plus,1188,4,2,4,3,2,4,2,2,4,3,1,3,2,2,0,0.0,neutral or dissatisfied +61562,71622,Male,disloyal Customer,35,Business travel,Eco,1197,3,3,3,1,1,3,1,1,4,4,5,2,1,1,0,0.0,neutral or dissatisfied +61563,63576,Female,Loyal Customer,47,Business travel,Business,2133,1,1,1,1,4,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +61564,106180,Male,Loyal Customer,61,Personal Travel,Eco,436,2,4,2,5,3,2,3,3,5,5,4,3,5,3,24,24.0,neutral or dissatisfied +61565,114261,Female,disloyal Customer,37,Business travel,Eco,548,4,2,4,3,3,4,3,3,4,5,4,1,3,3,10,6.0,neutral or dissatisfied +61566,62711,Female,Loyal Customer,58,Business travel,Business,2399,2,5,2,2,3,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +61567,39269,Female,disloyal Customer,25,Business travel,Eco,67,1,2,1,2,4,1,4,4,1,2,1,1,2,4,0,0.0,neutral or dissatisfied +61568,13036,Male,Loyal Customer,49,Personal Travel,Eco,374,3,4,3,4,3,3,1,3,2,2,2,2,5,3,0,0.0,neutral or dissatisfied +61569,102900,Female,Loyal Customer,32,Personal Travel,Eco,1037,1,4,0,1,5,0,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +61570,101230,Female,Loyal Customer,55,Business travel,Business,1235,5,5,5,5,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +61571,75929,Male,Loyal Customer,21,Personal Travel,Eco,205,3,1,0,2,5,0,5,5,4,5,2,4,2,5,0,0.0,neutral or dissatisfied +61572,85654,Male,Loyal Customer,49,Personal Travel,Eco Plus,153,2,4,2,3,5,2,5,5,4,2,5,4,4,5,12,8.0,neutral or dissatisfied +61573,107341,Male,Loyal Customer,49,Business travel,Business,2609,3,3,4,3,3,5,4,5,5,4,5,5,5,5,50,37.0,satisfied +61574,15385,Female,Loyal Customer,55,Business travel,Business,377,2,3,2,2,1,2,1,5,5,4,5,1,5,1,11,0.0,satisfied +61575,11638,Male,disloyal Customer,37,Business travel,Business,835,5,5,5,3,3,5,3,3,4,4,4,3,5,3,24,26.0,satisfied +61576,2818,Male,Loyal Customer,52,Business travel,Business,2800,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +61577,90665,Female,Loyal Customer,55,Business travel,Business,271,4,4,4,4,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +61578,52522,Male,Loyal Customer,31,Business travel,Business,2468,0,4,1,1,1,1,1,1,3,5,1,1,3,1,0,0.0,satisfied +61579,99901,Female,Loyal Customer,24,Personal Travel,Eco,738,1,4,1,3,3,1,2,3,4,4,5,3,5,3,51,61.0,neutral or dissatisfied +61580,66511,Male,Loyal Customer,8,Personal Travel,Eco,447,3,5,3,1,2,3,2,2,4,2,1,3,2,2,0,0.0,neutral or dissatisfied +61581,111826,Male,Loyal Customer,52,Business travel,Business,1605,2,4,4,4,2,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +61582,22166,Female,Loyal Customer,43,Business travel,Business,3272,4,2,4,4,4,4,4,3,1,2,4,4,2,4,144,148.0,satisfied +61583,107824,Male,disloyal Customer,61,Personal Travel,Eco,349,4,5,4,2,5,4,5,5,3,3,5,4,4,5,0,0.0,satisfied +61584,21237,Female,Loyal Customer,11,Personal Travel,Eco,192,1,5,0,4,4,0,4,4,3,3,5,4,5,4,8,4.0,neutral or dissatisfied +61585,55261,Female,disloyal Customer,30,Business travel,Eco,1571,1,2,2,3,3,1,3,3,1,1,3,3,3,3,45,37.0,neutral or dissatisfied +61586,7954,Male,disloyal Customer,39,Business travel,Eco,594,2,2,2,3,3,2,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +61587,88827,Male,Loyal Customer,44,Personal Travel,Eco Plus,406,4,4,4,1,2,4,2,2,4,5,4,4,5,2,1,0.0,neutral or dissatisfied +61588,6840,Male,Loyal Customer,57,Personal Travel,Eco,235,3,4,3,2,4,3,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +61589,54655,Female,Loyal Customer,59,Business travel,Eco,854,1,3,3,3,3,4,4,1,1,1,1,2,1,1,6,0.0,neutral or dissatisfied +61590,88095,Male,Loyal Customer,40,Business travel,Business,2189,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,2.0,satisfied +61591,55869,Female,Loyal Customer,40,Business travel,Business,528,4,4,4,4,5,5,4,4,4,4,4,5,4,5,30,8.0,satisfied +61592,110200,Female,Loyal Customer,34,Personal Travel,Eco Plus,869,4,1,4,4,4,5,4,3,2,4,4,4,4,4,185,170.0,neutral or dissatisfied +61593,55685,Male,Loyal Customer,38,Business travel,Business,1025,5,5,5,5,3,5,4,3,3,4,3,4,3,4,4,17.0,satisfied +61594,39789,Female,Loyal Customer,45,Business travel,Business,3675,4,1,1,1,1,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +61595,37871,Female,Loyal Customer,43,Business travel,Business,3876,2,1,1,1,1,2,3,2,2,1,2,4,2,4,70,66.0,neutral or dissatisfied +61596,54544,Male,Loyal Customer,41,Personal Travel,Eco,925,2,2,2,4,3,2,3,3,3,3,3,3,3,3,64,53.0,neutral or dissatisfied +61597,86680,Female,Loyal Customer,30,Business travel,Business,1747,2,2,2,2,5,5,5,5,4,5,4,3,5,5,83,84.0,satisfied +61598,54713,Male,Loyal Customer,29,Personal Travel,Eco,854,0,4,0,4,0,2,2,3,3,5,5,2,5,2,158,222.0,satisfied +61599,18607,Female,disloyal Customer,80,Business travel,Eco,201,2,4,2,5,4,2,4,4,4,3,5,2,2,4,0,0.0,neutral or dissatisfied +61600,60075,Female,Loyal Customer,32,Business travel,Business,3473,4,4,4,4,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +61601,53346,Female,Loyal Customer,31,Business travel,Business,1452,5,5,5,5,4,4,4,4,4,1,3,5,3,4,25,11.0,satisfied +61602,26399,Male,disloyal Customer,24,Business travel,Eco,957,1,1,1,2,2,1,3,2,1,4,3,3,2,2,0,0.0,neutral or dissatisfied +61603,46399,Female,Loyal Customer,68,Personal Travel,Eco,1081,2,3,2,1,3,1,3,3,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +61604,85883,Male,Loyal Customer,43,Business travel,Business,2172,1,1,1,1,4,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +61605,73859,Female,Loyal Customer,25,Personal Travel,Eco,1810,1,4,1,4,4,1,1,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +61606,85097,Female,Loyal Customer,31,Business travel,Business,813,4,4,4,4,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +61607,78528,Male,Loyal Customer,11,Personal Travel,Eco,666,2,4,2,4,5,2,5,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +61608,52410,Male,Loyal Customer,30,Personal Travel,Eco,237,5,4,0,3,3,0,3,3,3,4,4,1,4,3,1,3.0,satisfied +61609,15142,Female,Loyal Customer,45,Business travel,Eco,912,1,4,5,4,5,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +61610,103471,Female,Loyal Customer,40,Business travel,Business,1560,3,3,3,3,5,4,5,4,4,3,4,5,4,3,42,42.0,satisfied +61611,26608,Female,Loyal Customer,46,Business travel,Business,3601,5,5,5,5,4,2,5,4,4,5,4,1,4,1,2,0.0,satisfied +61612,16556,Male,Loyal Customer,23,Business travel,Eco,872,4,5,5,5,4,4,4,4,3,5,4,5,4,4,117,126.0,satisfied +61613,3680,Female,disloyal Customer,22,Business travel,Eco,431,1,4,1,4,3,1,4,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +61614,24604,Female,Loyal Customer,27,Business travel,Business,2700,1,2,2,2,1,1,1,1,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +61615,25659,Male,Loyal Customer,38,Business travel,Eco,761,2,5,5,5,2,2,2,2,4,2,2,5,3,2,36,26.0,satisfied +61616,2505,Female,Loyal Customer,54,Business travel,Business,1652,1,1,1,1,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +61617,126547,Male,Loyal Customer,62,Personal Travel,Eco,644,3,4,3,3,4,3,1,4,3,3,1,4,2,4,1,4.0,neutral or dissatisfied +61618,57098,Male,Loyal Customer,53,Business travel,Business,2232,1,1,5,1,3,5,4,5,5,5,5,4,5,4,8,17.0,satisfied +61619,118905,Male,Loyal Customer,42,Business travel,Eco,570,4,5,5,5,4,4,4,4,2,4,3,4,2,4,0,0.0,neutral or dissatisfied +61620,118474,Male,Loyal Customer,42,Business travel,Business,370,1,4,4,4,2,3,4,1,1,1,1,4,1,1,0,2.0,neutral or dissatisfied +61621,103207,Male,Loyal Customer,35,Business travel,Business,1482,4,4,4,4,1,4,3,5,5,5,5,5,5,1,23,4.0,satisfied +61622,80784,Male,Loyal Customer,41,Business travel,Business,692,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,17.0,satisfied +61623,85871,Female,Loyal Customer,44,Business travel,Business,2172,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,8.0,satisfied +61624,6124,Female,disloyal Customer,21,Business travel,Eco,501,5,0,5,5,3,5,4,3,4,4,4,5,5,3,0,7.0,satisfied +61625,48537,Female,disloyal Customer,23,Business travel,Eco,444,4,3,4,4,1,4,1,1,4,5,3,4,4,1,0,6.0,neutral or dissatisfied +61626,70831,Female,Loyal Customer,67,Personal Travel,Business,761,1,5,1,5,3,4,4,4,4,1,4,3,4,5,4,0.0,neutral or dissatisfied +61627,103680,Female,disloyal Customer,16,Business travel,Eco,405,2,2,2,4,3,2,3,3,3,1,4,3,4,3,0,0.0,neutral or dissatisfied +61628,22042,Male,Loyal Customer,61,Personal Travel,Eco Plus,551,2,4,3,4,5,3,5,5,1,5,3,3,4,5,0,0.0,neutral or dissatisfied +61629,17248,Female,disloyal Customer,30,Business travel,Eco,872,3,3,3,3,4,3,4,4,4,3,3,1,3,4,17,8.0,neutral or dissatisfied +61630,36451,Female,Loyal Customer,39,Business travel,Business,867,1,4,4,4,4,4,3,1,1,1,1,2,1,1,27,7.0,neutral or dissatisfied +61631,23091,Male,Loyal Customer,45,Personal Travel,Eco,864,5,5,5,1,1,5,1,1,3,4,4,5,5,1,0,0.0,satisfied +61632,58212,Male,Loyal Customer,37,Personal Travel,Eco,925,1,2,1,3,4,1,4,4,2,3,3,1,4,4,5,0.0,neutral or dissatisfied +61633,53548,Male,Loyal Customer,26,Business travel,Eco,1956,5,5,5,5,5,5,5,5,5,3,5,3,5,5,0,0.0,satisfied +61634,125984,Male,Loyal Customer,59,Personal Travel,Business,507,3,1,3,4,1,4,4,3,3,3,3,4,3,2,14,37.0,neutral or dissatisfied +61635,40457,Male,Loyal Customer,37,Business travel,Business,222,1,1,5,1,1,5,4,4,4,4,4,1,4,5,0,0.0,satisfied +61636,62944,Male,Loyal Customer,69,Business travel,Business,3766,4,1,1,1,1,3,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +61637,117141,Male,Loyal Customer,19,Personal Travel,Eco,621,3,4,3,4,3,3,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +61638,88364,Male,Loyal Customer,30,Business travel,Business,545,3,3,3,3,3,3,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +61639,96400,Female,Loyal Customer,80,Business travel,Business,3709,2,5,5,5,1,4,3,2,2,2,2,4,2,4,31,22.0,neutral or dissatisfied +61640,31785,Female,disloyal Customer,27,Business travel,Eco Plus,602,3,3,3,3,5,3,5,5,2,4,4,2,3,5,28,19.0,neutral or dissatisfied +61641,71431,Male,Loyal Customer,49,Business travel,Business,3353,2,2,2,2,3,5,4,4,4,4,4,5,4,3,73,68.0,satisfied +61642,35955,Female,disloyal Customer,36,Business travel,Eco,231,3,1,2,3,1,2,1,1,2,5,4,3,4,1,0,0.0,neutral or dissatisfied +61643,63629,Female,Loyal Customer,51,Business travel,Business,602,5,5,5,5,5,5,5,4,4,4,4,3,4,5,24,29.0,satisfied +61644,42779,Female,Loyal Customer,23,Business travel,Business,744,4,4,4,4,4,4,4,1,3,2,2,4,3,4,295,274.0,neutral or dissatisfied +61645,35236,Female,Loyal Customer,56,Business travel,Eco,944,2,3,2,3,1,3,3,2,2,2,2,4,2,4,19,10.0,neutral or dissatisfied +61646,2756,Male,Loyal Customer,8,Personal Travel,Eco,772,3,3,3,2,5,3,5,5,3,2,3,3,2,5,0,0.0,neutral or dissatisfied +61647,74728,Male,Loyal Customer,53,Personal Travel,Eco,1431,4,5,4,3,3,4,3,3,4,5,3,3,4,3,1,0.0,satisfied +61648,88439,Male,Loyal Customer,70,Business travel,Business,271,1,1,2,1,3,4,4,4,4,4,4,4,4,5,0,2.0,satisfied +61649,69567,Female,Loyal Customer,35,Business travel,Eco,2475,4,5,5,5,4,4,4,4,4,4,4,4,1,4,1,18.0,neutral or dissatisfied +61650,83340,Female,Loyal Customer,48,Business travel,Business,3145,3,3,3,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +61651,11049,Male,Loyal Customer,13,Personal Travel,Eco,247,3,5,0,3,2,0,2,2,3,5,4,5,4,2,38,31.0,neutral or dissatisfied +61652,3118,Male,disloyal Customer,29,Business travel,Eco,1013,3,3,3,3,1,3,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +61653,84740,Male,Loyal Customer,48,Business travel,Business,547,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +61654,24084,Female,Loyal Customer,47,Business travel,Eco,854,3,2,2,2,5,1,5,3,3,3,3,3,3,3,0,0.0,satisfied +61655,7281,Female,Loyal Customer,67,Personal Travel,Eco,135,1,2,1,3,3,4,3,3,3,1,1,3,3,4,102,91.0,neutral or dissatisfied +61656,63001,Female,Loyal Customer,55,Business travel,Business,909,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +61657,85572,Female,Loyal Customer,47,Business travel,Business,192,4,4,4,4,2,4,4,5,5,5,5,4,5,5,47,36.0,satisfied +61658,66390,Male,Loyal Customer,44,Business travel,Business,1562,3,3,3,3,4,5,5,5,5,5,5,5,5,3,1,0.0,satisfied +61659,104933,Female,Loyal Customer,44,Personal Travel,Eco,210,4,1,0,3,5,3,3,3,3,0,1,4,3,4,71,79.0,neutral or dissatisfied +61660,5757,Male,Loyal Customer,61,Business travel,Business,3992,3,3,3,3,2,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +61661,76743,Female,Loyal Customer,43,Business travel,Business,205,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +61662,31641,Male,Loyal Customer,50,Business travel,Eco,846,4,4,4,4,4,4,4,4,2,3,5,3,4,4,0,0.0,satisfied +61663,35042,Female,disloyal Customer,24,Business travel,Eco,1069,5,5,5,3,1,5,1,1,5,2,4,3,5,1,0,13.0,satisfied +61664,86719,Female,Loyal Customer,75,Business travel,Eco,247,4,1,1,1,2,4,2,4,4,4,4,3,4,3,5,0.0,satisfied +61665,98813,Female,disloyal Customer,22,Business travel,Eco,763,2,2,2,4,3,2,5,3,3,3,3,1,4,3,8,15.0,neutral or dissatisfied +61666,100502,Female,Loyal Customer,26,Business travel,Business,2237,3,3,3,3,3,4,3,3,4,3,4,3,4,3,0,0.0,satisfied +61667,25694,Female,Loyal Customer,22,Business travel,Business,2369,5,5,5,5,4,4,4,4,2,3,4,4,1,4,0,0.0,satisfied +61668,18343,Female,Loyal Customer,47,Business travel,Eco,563,3,1,1,1,4,2,3,3,3,3,3,1,3,4,0,13.0,neutral or dissatisfied +61669,12405,Male,Loyal Customer,20,Business travel,Eco,201,5,4,4,4,5,5,5,5,4,3,5,5,1,5,0,5.0,satisfied +61670,113685,Female,Loyal Customer,25,Personal Travel,Eco,223,4,2,0,1,5,0,5,5,1,1,2,1,2,5,45,29.0,neutral or dissatisfied +61671,40285,Male,Loyal Customer,54,Personal Travel,Eco,436,2,4,2,2,2,2,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +61672,44723,Female,Loyal Customer,26,Personal Travel,Eco,108,5,4,5,5,5,5,5,5,5,4,5,3,4,5,0,0.0,satisfied +61673,69008,Female,Loyal Customer,46,Business travel,Business,1521,5,5,5,5,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +61674,34026,Male,Loyal Customer,18,Personal Travel,Eco,1576,3,5,3,1,5,3,4,5,3,5,4,4,4,5,0,2.0,neutral or dissatisfied +61675,58886,Female,Loyal Customer,44,Business travel,Business,888,1,2,5,2,5,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +61676,18884,Male,Loyal Customer,41,Business travel,Eco,503,3,5,3,5,3,3,3,3,3,5,3,2,3,3,0,2.0,neutral or dissatisfied +61677,29629,Male,Loyal Customer,37,Business travel,Business,1048,5,5,5,5,2,1,2,4,4,4,4,5,4,2,0,3.0,satisfied +61678,98119,Female,disloyal Customer,27,Business travel,Eco,472,2,2,2,3,1,2,1,1,4,3,3,1,4,1,103,108.0,neutral or dissatisfied +61679,39303,Male,Loyal Customer,34,Personal Travel,Eco,67,1,4,1,3,1,5,5,4,5,5,4,5,3,5,202,194.0,neutral or dissatisfied +61680,96834,Female,Loyal Customer,42,Business travel,Business,849,2,1,1,1,2,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +61681,18673,Male,Loyal Customer,23,Personal Travel,Eco,201,3,3,3,3,5,3,5,5,2,1,3,1,4,5,0,0.0,neutral or dissatisfied +61682,113274,Female,disloyal Customer,25,Business travel,Business,223,4,0,4,1,1,4,1,1,4,4,4,4,4,1,20,17.0,satisfied +61683,27861,Female,Loyal Customer,53,Personal Travel,Eco,1448,2,3,2,3,3,5,4,5,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +61684,98882,Female,Loyal Customer,28,Personal Travel,Eco,991,3,4,3,4,5,3,5,5,5,5,5,4,5,5,22,14.0,neutral or dissatisfied +61685,80313,Male,Loyal Customer,38,Business travel,Eco,346,3,5,5,5,3,3,3,3,1,1,1,4,1,3,0,21.0,satisfied +61686,46378,Male,Loyal Customer,15,Business travel,Business,3493,5,5,5,5,5,5,5,5,2,5,1,3,4,5,0,0.0,satisfied +61687,88655,Male,Loyal Customer,57,Personal Travel,Eco,404,4,3,4,1,3,4,3,3,5,5,3,4,2,3,0,0.0,satisfied +61688,53533,Female,disloyal Customer,41,Business travel,Eco Plus,2419,3,3,3,1,3,4,4,1,1,4,1,4,1,4,10,26.0,neutral or dissatisfied +61689,74003,Male,Loyal Customer,43,Personal Travel,Eco,1972,1,5,1,5,3,1,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +61690,3841,Male,Loyal Customer,32,Personal Travel,Eco,650,4,5,4,4,3,4,3,3,5,3,3,2,3,3,18,9.0,neutral or dissatisfied +61691,24871,Female,disloyal Customer,45,Business travel,Eco,356,2,3,2,3,3,2,3,3,1,1,4,2,3,3,0,0.0,neutral or dissatisfied +61692,53599,Female,Loyal Customer,39,Business travel,Business,3801,2,2,2,2,4,4,4,2,1,3,2,4,4,4,0,0.0,satisfied +61693,3179,Female,Loyal Customer,8,Business travel,Business,585,2,1,2,1,2,2,2,2,1,1,4,3,3,2,3,0.0,neutral or dissatisfied +61694,47281,Male,Loyal Customer,42,Business travel,Business,599,3,3,3,3,4,5,1,5,5,5,5,1,5,4,25,26.0,satisfied +61695,97140,Male,Loyal Customer,12,Business travel,Business,1390,2,2,2,2,4,4,4,4,4,3,4,4,4,4,15,0.0,satisfied +61696,1495,Female,Loyal Customer,47,Business travel,Business,835,2,4,4,4,2,4,3,2,2,2,2,4,2,4,0,23.0,neutral or dissatisfied +61697,44767,Female,disloyal Customer,20,Business travel,Eco,1250,4,4,4,1,4,5,5,5,3,5,1,5,2,5,196,170.0,satisfied +61698,79096,Female,Loyal Customer,43,Personal Travel,Eco,226,4,5,4,1,3,5,4,5,5,4,5,3,5,3,0,1.0,neutral or dissatisfied +61699,109717,Female,Loyal Customer,56,Business travel,Eco,534,4,1,1,1,3,4,4,4,4,4,4,4,4,1,15,6.0,neutral or dissatisfied +61700,12436,Male,Loyal Customer,38,Personal Travel,Eco,253,3,4,3,5,4,3,4,4,4,1,1,1,3,4,0,3.0,neutral or dissatisfied +61701,125446,Male,disloyal Customer,27,Business travel,Business,2917,2,2,2,3,1,2,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +61702,84109,Male,Loyal Customer,44,Business travel,Business,1900,2,2,2,2,3,4,4,4,4,4,4,5,4,3,1,6.0,satisfied +61703,15348,Male,disloyal Customer,37,Business travel,Business,433,3,3,3,4,5,3,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +61704,125417,Female,Loyal Customer,40,Business travel,Eco,735,3,3,3,3,3,3,3,3,3,5,4,2,3,3,0,0.0,neutral or dissatisfied +61705,71073,Female,Loyal Customer,34,Personal Travel,Eco,802,1,5,1,3,1,1,1,1,3,2,3,1,4,1,0,0.0,neutral or dissatisfied +61706,115898,Male,Loyal Customer,23,Business travel,Business,3395,4,5,5,5,4,4,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +61707,125406,Female,Loyal Customer,58,Personal Travel,Eco,1440,1,4,1,1,5,3,5,5,5,1,5,5,5,5,2,0.0,neutral or dissatisfied +61708,100477,Female,Loyal Customer,52,Business travel,Business,1855,3,3,3,3,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +61709,76443,Female,disloyal Customer,23,Business travel,Eco Plus,405,3,2,3,4,3,3,3,3,4,2,4,2,4,3,5,6.0,neutral or dissatisfied +61710,122556,Male,Loyal Customer,28,Personal Travel,Eco,500,2,4,2,1,4,2,5,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +61711,99474,Male,Loyal Customer,46,Business travel,Eco,283,3,3,3,3,3,3,3,3,3,3,3,3,3,3,8,10.0,neutral or dissatisfied +61712,124460,Male,Loyal Customer,55,Business travel,Business,3530,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +61713,31632,Female,Loyal Customer,60,Business travel,Eco,776,4,3,3,3,3,1,5,4,4,4,4,3,4,3,12,3.0,satisfied +61714,58217,Male,Loyal Customer,50,Personal Travel,Eco,925,0,4,0,1,3,0,3,3,3,2,5,1,5,3,0,0.0,satisfied +61715,34459,Male,Loyal Customer,22,Personal Travel,Eco,228,3,4,3,4,2,3,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +61716,39601,Male,Loyal Customer,46,Personal Travel,Eco,908,0,3,0,1,5,0,3,5,1,5,1,3,2,5,0,0.0,satisfied +61717,23749,Male,disloyal Customer,14,Business travel,Business,1083,2,2,2,3,3,2,3,3,1,3,4,1,4,3,8,9.0,neutral or dissatisfied +61718,86469,Female,Loyal Customer,60,Business travel,Business,2078,4,4,4,4,5,2,3,4,4,4,4,2,4,4,0,0.0,satisfied +61719,106602,Male,Loyal Customer,47,Business travel,Business,1501,1,1,1,1,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +61720,10723,Female,disloyal Customer,15,Business travel,Eco,312,3,4,3,3,5,3,5,5,4,3,4,4,4,5,75,87.0,neutral or dissatisfied +61721,119601,Female,disloyal Customer,26,Business travel,Eco,1345,3,3,3,2,3,3,3,3,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +61722,53371,Male,Loyal Customer,32,Business travel,Business,1452,1,1,1,1,5,5,5,5,3,4,5,2,4,5,2,0.0,satisfied +61723,48700,Female,Loyal Customer,59,Business travel,Business,86,0,4,0,5,2,5,5,1,1,1,1,4,1,3,8,3.0,satisfied +61724,97860,Male,Loyal Customer,67,Personal Travel,Business,616,3,5,3,1,1,3,5,3,3,3,3,5,3,1,27,26.0,neutral or dissatisfied +61725,43241,Female,disloyal Customer,38,Business travel,Business,436,2,2,2,3,4,2,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +61726,6954,Female,Loyal Customer,52,Personal Travel,Eco,501,3,2,3,4,5,3,3,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +61727,36339,Male,Loyal Customer,35,Personal Travel,Eco,187,5,5,0,5,2,0,2,2,4,3,5,4,5,2,0,0.0,satisfied +61728,43791,Female,disloyal Customer,27,Business travel,Eco Plus,546,3,3,3,4,5,3,3,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +61729,79967,Male,Loyal Customer,49,Business travel,Eco,544,3,1,1,1,3,3,3,3,1,5,4,5,5,3,0,0.0,satisfied +61730,63373,Male,Loyal Customer,9,Personal Travel,Eco,337,3,1,3,3,3,3,3,3,2,1,2,4,2,3,23,20.0,neutral or dissatisfied +61731,24102,Female,disloyal Customer,26,Business travel,Eco,584,4,5,3,2,4,3,2,4,4,2,4,1,2,4,0,0.0,neutral or dissatisfied +61732,125717,Female,Loyal Customer,29,Personal Travel,Eco,857,3,1,3,4,3,3,3,3,1,4,4,1,3,3,38,16.0,neutral or dissatisfied +61733,46263,Female,Loyal Customer,68,Personal Travel,Eco,524,2,3,2,5,4,4,5,4,4,2,4,5,4,4,119,118.0,neutral or dissatisfied +61734,82081,Female,Loyal Customer,29,Business travel,Business,1276,3,3,3,3,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +61735,80741,Female,Loyal Customer,37,Personal Travel,Eco,393,0,2,0,3,3,0,3,3,3,5,4,4,4,3,0,0.0,satisfied +61736,114250,Female,Loyal Customer,28,Business travel,Business,1557,2,4,2,2,2,2,2,2,1,2,3,2,4,2,20,20.0,neutral or dissatisfied +61737,82564,Male,disloyal Customer,27,Business travel,Business,528,4,4,4,2,2,4,2,2,4,4,4,3,4,2,4,0.0,satisfied +61738,100852,Male,Loyal Customer,41,Personal Travel,Eco,711,2,5,2,3,4,2,5,4,4,2,2,2,1,4,0,0.0,neutral or dissatisfied +61739,104749,Male,disloyal Customer,35,Business travel,Eco,1342,1,1,1,4,1,1,1,1,3,5,3,3,4,1,69,67.0,neutral or dissatisfied +61740,64922,Female,disloyal Customer,34,Business travel,Eco,282,2,3,2,4,4,2,4,4,1,3,4,2,3,4,6,7.0,neutral or dissatisfied +61741,30211,Male,Loyal Customer,58,Personal Travel,Eco Plus,399,4,4,4,4,5,4,5,5,3,5,3,4,1,5,0,0.0,neutral or dissatisfied +61742,58536,Male,Loyal Customer,50,Personal Travel,Eco Plus,719,4,5,4,3,3,4,3,3,5,4,5,4,5,3,3,4.0,satisfied +61743,1775,Female,Loyal Customer,43,Business travel,Business,408,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +61744,119435,Male,Loyal Customer,32,Personal Travel,Eco,399,1,5,1,1,3,1,2,3,4,4,5,5,5,3,3,26.0,neutral or dissatisfied +61745,58393,Male,disloyal Customer,24,Business travel,Eco,733,3,3,3,3,4,3,2,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +61746,98198,Male,Loyal Customer,28,Personal Travel,Eco,327,1,0,2,1,3,2,3,3,3,4,5,5,5,3,25,27.0,neutral or dissatisfied +61747,100631,Female,Loyal Customer,56,Business travel,Business,2509,3,3,3,3,4,5,5,3,3,4,3,4,3,5,27,36.0,satisfied +61748,98890,Female,Loyal Customer,29,Business travel,Eco Plus,991,3,3,3,3,3,3,3,3,3,4,3,1,3,3,9,0.0,neutral or dissatisfied +61749,76690,Female,Loyal Customer,35,Personal Travel,Eco,516,3,1,3,4,4,3,4,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +61750,64511,Female,Loyal Customer,11,Personal Travel,Business,190,3,3,3,3,3,3,3,3,1,3,2,3,2,3,17,5.0,neutral or dissatisfied +61751,92465,Male,Loyal Customer,24,Business travel,Business,1947,3,4,4,4,3,3,3,3,4,1,1,3,1,3,370,341.0,neutral or dissatisfied +61752,97331,Female,Loyal Customer,30,Business travel,Eco,1020,2,2,2,2,2,2,2,2,2,1,2,2,3,2,36,35.0,neutral or dissatisfied +61753,103075,Male,Loyal Customer,61,Personal Travel,Eco,460,3,5,3,3,3,3,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +61754,79332,Female,disloyal Customer,23,Business travel,Eco,1020,1,1,1,3,1,1,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +61755,71386,Female,Loyal Customer,20,Personal Travel,Eco,258,4,3,4,4,2,4,2,2,3,5,4,1,4,2,2,0.0,neutral or dissatisfied +61756,45164,Male,Loyal Customer,35,Business travel,Eco,139,2,1,1,1,2,2,2,2,3,1,4,3,3,2,0,6.0,neutral or dissatisfied +61757,123451,Female,disloyal Customer,27,Business travel,Business,2125,3,3,3,2,3,3,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +61758,26220,Female,Loyal Customer,13,Personal Travel,Eco,515,3,1,3,3,2,3,2,2,1,3,3,1,3,2,39,48.0,neutral or dissatisfied +61759,103093,Female,Loyal Customer,47,Personal Travel,Eco,687,1,4,1,3,3,5,5,3,3,1,3,5,3,4,62,49.0,neutral or dissatisfied +61760,14028,Female,Loyal Customer,41,Business travel,Business,3106,4,2,4,4,5,1,5,4,4,4,4,5,4,4,129,107.0,satisfied +61761,85424,Male,Loyal Customer,58,Business travel,Business,3681,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +61762,78758,Female,disloyal Customer,30,Business travel,Eco,432,2,3,2,3,2,2,2,2,3,2,4,4,3,2,6,4.0,neutral or dissatisfied +61763,65755,Female,Loyal Customer,41,Personal Travel,Eco,1061,4,4,4,4,4,4,2,4,3,4,4,4,5,4,7,0.0,neutral or dissatisfied +61764,125162,Female,Loyal Customer,47,Business travel,Business,2518,5,5,5,5,2,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +61765,47804,Female,Loyal Customer,33,Business travel,Business,412,2,2,2,2,4,5,5,5,5,5,5,2,5,2,0,0.0,satisfied +61766,13080,Male,Loyal Customer,57,Business travel,Business,595,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +61767,32061,Female,Loyal Customer,58,Business travel,Business,1510,0,5,1,3,3,3,2,2,2,2,2,2,2,1,0,0.0,satisfied +61768,34033,Male,Loyal Customer,24,Business travel,Eco Plus,1576,3,3,3,3,3,4,3,3,4,4,2,1,3,3,0,0.0,satisfied +61769,68464,Female,Loyal Customer,48,Business travel,Business,2684,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +61770,113648,Female,Loyal Customer,39,Personal Travel,Eco,226,2,4,2,1,5,2,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +61771,2297,Male,Loyal Customer,19,Business travel,Business,3205,2,5,5,5,2,2,2,2,3,4,4,1,3,2,0,6.0,neutral or dissatisfied +61772,120930,Male,Loyal Customer,36,Business travel,Business,2614,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,11.0,satisfied +61773,35820,Female,Loyal Customer,51,Business travel,Eco,1023,4,3,3,3,2,3,4,4,4,4,4,2,4,2,0,0.0,satisfied +61774,118379,Female,Loyal Customer,41,Business travel,Business,2926,1,1,1,1,5,5,5,3,5,5,4,5,4,5,159,157.0,satisfied +61775,23702,Female,Loyal Customer,40,Business travel,Eco,212,5,3,3,3,5,5,5,5,4,1,2,4,3,5,15,8.0,satisfied +61776,23889,Male,Loyal Customer,43,Business travel,Eco,589,4,3,3,3,4,4,4,4,3,3,1,3,3,4,0,0.0,satisfied +61777,33998,Female,Loyal Customer,36,Business travel,Eco,1576,1,4,1,4,1,1,1,1,3,4,2,2,3,1,0,2.0,neutral or dissatisfied +61778,81684,Male,Loyal Customer,39,Business travel,Business,907,3,3,3,3,1,2,3,3,3,3,3,3,3,1,10,5.0,neutral or dissatisfied +61779,118300,Female,Loyal Customer,26,Business travel,Business,639,2,2,2,2,5,5,5,5,4,3,4,4,4,5,17,11.0,satisfied +61780,17024,Female,disloyal Customer,13,Personal Travel,Eco,781,1,5,1,5,5,1,3,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +61781,60405,Male,Loyal Customer,25,Personal Travel,Eco,1452,3,5,3,2,3,3,3,3,5,5,4,5,4,3,13,8.0,neutral or dissatisfied +61782,40640,Male,Loyal Customer,17,Personal Travel,Eco Plus,391,4,4,4,4,4,4,4,4,4,5,4,1,3,4,0,0.0,satisfied +61783,120438,Female,disloyal Customer,24,Business travel,Business,337,4,5,4,4,1,4,1,1,2,1,3,2,3,1,4,5.0,satisfied +61784,40384,Female,Loyal Customer,20,Personal Travel,Eco,1250,2,2,2,3,3,2,1,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +61785,36320,Female,Loyal Customer,39,Business travel,Business,3509,5,3,5,5,2,4,5,5,5,5,4,4,5,3,32,47.0,satisfied +61786,22851,Female,Loyal Customer,7,Personal Travel,Eco,302,5,2,1,3,5,1,5,5,2,4,3,3,4,5,0,0.0,satisfied +61787,68165,Female,disloyal Customer,25,Business travel,Business,603,4,4,5,4,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +61788,51722,Male,Loyal Customer,20,Personal Travel,Eco,651,4,1,4,4,4,1,1,4,4,4,4,1,2,1,144,137.0,neutral or dissatisfied +61789,102256,Female,Loyal Customer,51,Business travel,Business,258,3,2,2,2,1,2,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +61790,66353,Male,Loyal Customer,24,Business travel,Eco,986,2,3,3,3,2,2,3,2,2,2,4,1,3,2,34,12.0,neutral or dissatisfied +61791,89569,Male,Loyal Customer,41,Business travel,Business,1710,2,2,2,2,4,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +61792,127917,Male,Loyal Customer,9,Personal Travel,Eco Plus,1671,3,3,3,2,4,3,4,4,1,4,1,2,5,4,0,0.0,neutral or dissatisfied +61793,34695,Female,Loyal Customer,46,Business travel,Eco,209,5,3,3,3,5,2,4,5,5,5,5,2,5,5,32,38.0,satisfied +61794,35835,Male,Loyal Customer,56,Business travel,Business,4000,1,1,1,1,4,5,3,4,4,4,4,1,4,5,47,55.0,satisfied +61795,90645,Male,disloyal Customer,24,Business travel,Business,581,0,0,0,1,4,0,5,4,4,4,4,3,4,4,0,0.0,satisfied +61796,85772,Male,Loyal Customer,30,Business travel,Business,1802,1,1,1,1,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +61797,4791,Male,Loyal Customer,15,Personal Travel,Eco,403,3,5,4,3,4,4,4,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +61798,29799,Female,Loyal Customer,62,Business travel,Business,2989,2,2,4,2,4,3,5,4,4,4,4,5,4,2,0,0.0,satisfied +61799,89055,Male,Loyal Customer,42,Business travel,Business,2116,5,5,2,5,5,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +61800,4437,Female,Loyal Customer,19,Personal Travel,Eco,762,1,5,1,4,4,1,4,4,3,3,4,4,4,4,102,112.0,neutral or dissatisfied +61801,46088,Female,Loyal Customer,60,Personal Travel,Eco,541,2,4,2,1,3,4,4,5,5,2,5,5,5,4,37,25.0,neutral or dissatisfied +61802,49545,Male,Loyal Customer,32,Business travel,Eco,308,5,1,1,1,5,5,5,5,2,1,5,1,3,5,0,0.0,satisfied +61803,112845,Female,Loyal Customer,58,Business travel,Business,3206,4,4,4,4,5,4,5,2,2,2,2,4,2,4,9,0.0,satisfied +61804,29293,Male,disloyal Customer,37,Business travel,Eco,859,4,4,4,3,4,4,4,4,4,2,4,5,3,4,0,0.0,neutral or dissatisfied +61805,3981,Female,Loyal Customer,23,Business travel,Business,1993,2,5,5,5,2,2,2,2,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +61806,62363,Male,Loyal Customer,40,Business travel,Business,2704,2,2,2,2,4,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +61807,95637,Female,Loyal Customer,53,Personal Travel,Eco,756,1,5,1,1,3,5,4,1,1,1,1,5,1,5,39,29.0,neutral or dissatisfied +61808,2810,Male,disloyal Customer,21,Business travel,Eco,491,1,0,1,3,4,1,4,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +61809,117181,Male,Loyal Customer,45,Personal Travel,Eco,370,4,4,4,1,2,4,2,2,4,2,5,5,5,2,44,28.0,neutral or dissatisfied +61810,11101,Female,Loyal Customer,47,Personal Travel,Eco,216,1,4,1,4,2,4,4,4,4,1,4,2,4,1,4,12.0,neutral or dissatisfied +61811,28170,Male,disloyal Customer,37,Business travel,Eco,434,2,2,2,3,5,2,5,5,3,1,3,2,4,5,19,14.0,neutral or dissatisfied +61812,91725,Female,Loyal Customer,52,Business travel,Business,590,2,2,2,2,2,5,5,3,3,3,3,3,3,4,1,0.0,satisfied +61813,92303,Female,Loyal Customer,51,Business travel,Business,1056,4,4,4,4,5,5,5,3,3,5,5,5,3,5,0,18.0,satisfied +61814,125272,Male,disloyal Customer,27,Business travel,Business,1088,3,3,3,1,2,3,2,2,3,1,2,1,1,2,0,9.0,neutral or dissatisfied +61815,9355,Male,disloyal Customer,38,Business travel,Business,401,3,3,3,2,5,3,5,5,4,3,4,4,4,5,26,14.0,satisfied +61816,122105,Female,Loyal Customer,21,Personal Travel,Eco,130,5,3,5,4,4,5,5,4,4,1,4,2,3,4,4,0.0,satisfied +61817,87899,Female,Loyal Customer,54,Business travel,Business,594,5,5,5,5,2,5,4,4,4,4,4,4,4,3,10,27.0,satisfied +61818,69317,Male,Loyal Customer,39,Business travel,Business,1096,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +61819,13062,Male,Loyal Customer,26,Business travel,Eco,936,5,4,4,4,5,5,3,5,4,3,4,2,5,5,0,43.0,satisfied +61820,41208,Female,Loyal Customer,24,Business travel,Business,3581,3,2,2,2,3,3,3,3,2,3,4,2,4,3,8,3.0,neutral or dissatisfied +61821,22610,Female,Loyal Customer,36,Business travel,Eco,223,5,2,2,2,5,4,5,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +61822,7383,Female,disloyal Customer,72,Business travel,Business,122,3,3,3,4,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +61823,88942,Female,Loyal Customer,56,Business travel,Business,1340,3,3,3,3,2,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +61824,127166,Female,Loyal Customer,49,Personal Travel,Eco,651,1,2,1,3,3,1,3,4,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +61825,92298,Female,disloyal Customer,46,Business travel,Business,2556,3,3,3,3,1,3,1,1,4,5,5,5,5,1,1,0.0,neutral or dissatisfied +61826,68065,Male,Loyal Customer,31,Business travel,Business,1616,5,5,5,5,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +61827,47424,Female,Loyal Customer,57,Business travel,Eco,184,5,1,2,1,1,3,3,5,5,5,5,5,5,1,0,0.0,satisfied +61828,93463,Male,Loyal Customer,12,Personal Travel,Eco,605,4,4,4,4,5,4,5,5,4,5,5,3,5,5,6,0.0,satisfied +61829,5969,Female,Loyal Customer,57,Business travel,Business,672,4,3,2,3,2,2,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +61830,58437,Female,Loyal Customer,68,Personal Travel,Eco,473,1,3,1,3,5,4,3,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +61831,129583,Female,Loyal Customer,52,Business travel,Business,1711,2,2,2,2,5,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +61832,23619,Female,Loyal Customer,64,Business travel,Business,977,5,5,5,5,2,4,2,4,4,3,4,4,4,4,0,0.0,satisfied +61833,111152,Female,Loyal Customer,64,Personal Travel,Eco,1173,3,5,3,1,5,5,5,3,3,3,3,5,3,5,79,80.0,neutral or dissatisfied +61834,65545,Male,Loyal Customer,7,Personal Travel,Business,237,2,5,2,4,1,2,1,1,4,2,4,5,5,1,2,0.0,neutral or dissatisfied +61835,95430,Female,Loyal Customer,41,Business travel,Business,2259,4,4,4,4,3,5,5,5,5,5,5,4,5,3,112,102.0,satisfied +61836,128297,Male,disloyal Customer,17,Business travel,Eco,621,3,0,3,3,1,3,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +61837,45121,Male,Loyal Customer,57,Personal Travel,Eco,157,2,5,0,2,5,0,5,5,4,5,5,5,4,5,8,0.0,neutral or dissatisfied +61838,20165,Female,disloyal Customer,20,Business travel,Eco,438,3,4,3,3,3,3,3,3,2,3,3,4,4,3,95,104.0,neutral or dissatisfied +61839,36071,Male,disloyal Customer,22,Business travel,Eco,413,2,0,2,5,1,2,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +61840,94727,Male,Loyal Customer,38,Business travel,Business,2034,4,4,2,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +61841,34702,Male,Loyal Customer,64,Business travel,Business,301,1,1,1,1,4,2,4,5,5,5,5,3,5,4,111,113.0,satisfied +61842,116409,Male,Loyal Customer,15,Personal Travel,Eco,325,2,4,2,2,2,2,5,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +61843,86867,Female,Loyal Customer,33,Personal Travel,Eco,692,3,5,3,4,3,3,2,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +61844,83749,Male,Loyal Customer,29,Business travel,Business,1183,3,4,4,4,3,3,3,3,2,5,4,2,4,3,0,0.0,neutral or dissatisfied +61845,97224,Female,Loyal Customer,32,Personal Travel,Eco Plus,1357,1,5,1,3,5,1,5,5,5,4,4,4,4,5,3,13.0,neutral or dissatisfied +61846,121848,Female,Loyal Customer,46,Business travel,Eco,449,3,1,1,1,3,3,3,4,4,3,4,4,4,2,4,0.0,neutral or dissatisfied +61847,116171,Male,Loyal Customer,55,Personal Travel,Eco,373,3,0,3,5,4,3,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +61848,47063,Female,Loyal Customer,68,Business travel,Business,351,3,2,2,2,4,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +61849,107849,Female,Loyal Customer,70,Personal Travel,Eco Plus,349,2,4,2,4,2,4,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +61850,40652,Female,disloyal Customer,22,Business travel,Eco,541,2,4,2,5,3,2,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +61851,62717,Male,Loyal Customer,49,Business travel,Business,2556,2,2,3,2,5,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +61852,35741,Female,disloyal Customer,42,Business travel,Eco,2153,4,4,4,4,4,4,4,4,1,3,3,1,1,4,2,0.0,neutral or dissatisfied +61853,76329,Male,Loyal Customer,47,Personal Travel,Eco,2182,4,3,5,2,3,5,3,3,4,3,3,5,3,3,1,0.0,neutral or dissatisfied +61854,29170,Male,Loyal Customer,41,Business travel,Eco Plus,978,5,3,5,3,5,5,5,5,2,1,3,3,2,5,0,0.0,satisfied +61855,69869,Female,disloyal Customer,29,Business travel,Eco Plus,655,4,4,4,4,5,4,5,5,3,5,3,2,3,5,0,0.0,neutral or dissatisfied +61856,37360,Female,Loyal Customer,45,Business travel,Eco,1041,4,2,2,2,4,4,2,4,4,4,4,3,4,3,0,0.0,satisfied +61857,50777,Female,Loyal Customer,14,Personal Travel,Eco,109,2,5,2,3,5,2,5,5,3,3,4,2,5,5,0,0.0,neutral or dissatisfied +61858,44311,Male,Loyal Customer,57,Business travel,Business,1966,1,4,4,4,3,3,4,1,1,2,1,3,1,3,4,3.0,neutral or dissatisfied +61859,106643,Female,Loyal Customer,45,Business travel,Business,861,2,1,2,2,4,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +61860,83583,Female,Loyal Customer,69,Personal Travel,Eco,936,4,3,5,3,3,2,2,5,5,5,2,3,5,3,0,0.0,neutral or dissatisfied +61861,21073,Male,Loyal Customer,39,Business travel,Business,3755,3,3,3,3,5,5,5,5,5,5,1,5,5,5,151,150.0,satisfied +61862,81508,Female,Loyal Customer,58,Personal Travel,Eco Plus,528,3,4,3,4,5,4,4,2,2,3,2,3,2,4,47,25.0,neutral or dissatisfied +61863,25577,Female,Loyal Customer,45,Business travel,Eco,696,3,5,5,5,4,4,4,2,2,3,2,4,2,2,1,0.0,neutral or dissatisfied +61864,2535,Female,Loyal Customer,44,Business travel,Business,2749,0,5,0,2,3,4,5,5,5,5,5,4,5,3,0,12.0,satisfied +61865,31860,Male,disloyal Customer,27,Business travel,Business,1299,4,4,4,3,3,4,3,3,3,3,5,3,4,3,27,17.0,satisfied +61866,33645,Female,Loyal Customer,60,Personal Travel,Eco,399,2,2,2,2,5,2,2,5,5,2,5,4,5,2,33,30.0,neutral or dissatisfied +61867,46960,Female,Loyal Customer,12,Personal Travel,Eco,848,2,5,2,4,1,2,1,1,5,2,4,3,4,1,0,3.0,neutral or dissatisfied +61868,56693,Male,Loyal Customer,11,Personal Travel,Eco,937,2,5,2,2,2,2,2,2,4,2,5,4,4,2,11,0.0,neutral or dissatisfied +61869,13389,Female,Loyal Customer,23,Business travel,Business,2712,2,1,1,1,2,2,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +61870,86976,Female,disloyal Customer,11,Business travel,Eco,907,2,2,2,5,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +61871,58024,Female,Loyal Customer,59,Personal Travel,Eco,1721,3,3,3,4,4,4,4,4,4,3,4,1,4,3,9,0.0,neutral or dissatisfied +61872,93425,Female,disloyal Customer,33,Business travel,Eco,672,3,3,3,1,5,3,5,5,3,5,2,3,1,5,1,0.0,neutral or dissatisfied +61873,210,Female,disloyal Customer,27,Business travel,Eco,213,4,2,4,1,2,4,2,2,2,1,1,4,1,2,6,4.0,neutral or dissatisfied +61874,38956,Male,Loyal Customer,37,Business travel,Eco,1265,5,4,4,4,5,5,5,5,5,4,5,1,4,5,0,0.0,satisfied +61875,32330,Male,Loyal Customer,37,Business travel,Eco,163,3,2,3,3,3,3,3,3,4,2,3,3,4,3,0,3.0,neutral or dissatisfied +61876,77783,Male,Loyal Customer,44,Personal Travel,Eco,731,3,1,2,3,2,2,4,2,1,3,2,1,2,2,0,0.0,neutral or dissatisfied +61877,59769,Female,disloyal Customer,25,Business travel,Eco,895,4,4,4,4,3,4,3,3,1,4,3,2,3,3,21,9.0,neutral or dissatisfied +61878,38203,Male,Loyal Customer,38,Business travel,Eco Plus,1249,4,4,4,4,4,5,4,4,5,1,3,4,4,4,0,12.0,satisfied +61879,103273,Male,Loyal Customer,33,Personal Travel,Eco,888,5,4,5,4,4,5,4,4,5,4,4,4,4,4,7,0.0,satisfied +61880,64629,Male,disloyal Customer,24,Business travel,Eco,247,4,5,4,4,2,4,2,2,5,5,5,5,5,2,0,0.0,satisfied +61881,117357,Male,Loyal Customer,50,Business travel,Business,2303,3,5,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +61882,44087,Female,disloyal Customer,44,Business travel,Business,257,3,3,3,3,4,3,4,4,4,3,4,4,3,4,20,7.0,neutral or dissatisfied +61883,13372,Male,Loyal Customer,47,Personal Travel,Eco,748,2,4,2,1,2,2,2,2,4,3,1,1,2,2,43,18.0,neutral or dissatisfied +61884,384,Male,Loyal Customer,43,Business travel,Business,102,1,1,1,1,5,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +61885,44375,Female,Loyal Customer,43,Business travel,Eco Plus,596,4,5,5,5,5,2,2,4,4,4,4,4,4,4,14,23.0,neutral or dissatisfied +61886,26022,Male,Loyal Customer,35,Business travel,Eco Plus,425,1,5,2,5,1,1,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +61887,20550,Female,Loyal Customer,34,Business travel,Business,3790,3,4,2,4,2,4,4,3,3,3,3,1,3,4,26,27.0,neutral or dissatisfied +61888,99894,Female,disloyal Customer,23,Business travel,Eco,738,0,0,0,2,2,0,2,2,3,4,5,2,4,2,0,0.0,satisfied +61889,85511,Male,Loyal Customer,12,Personal Travel,Eco,214,3,1,3,3,5,3,5,5,3,1,3,3,2,5,0,0.0,neutral or dissatisfied +61890,47815,Female,Loyal Customer,19,Business travel,Business,2429,1,1,1,1,5,5,5,5,2,1,4,3,2,5,0,0.0,satisfied +61891,121803,Female,Loyal Customer,45,Business travel,Business,3783,2,3,2,2,2,4,5,4,4,5,4,5,4,3,88,84.0,satisfied +61892,63564,Male,disloyal Customer,23,Business travel,Eco,1357,4,4,4,3,2,4,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +61893,12270,Male,Loyal Customer,55,Business travel,Business,192,5,1,5,5,2,4,2,5,5,5,3,4,5,3,6,0.0,satisfied +61894,36137,Female,Loyal Customer,40,Business travel,Business,2910,1,1,1,1,3,1,1,1,1,1,1,3,1,4,0,45.0,neutral or dissatisfied +61895,7870,Male,Loyal Customer,44,Business travel,Business,2000,1,1,1,1,5,5,4,5,5,5,5,5,5,3,0,2.0,satisfied +61896,38501,Female,Loyal Customer,22,Business travel,Business,2465,1,1,1,1,4,4,4,4,3,2,5,2,4,4,0,0.0,satisfied +61897,109491,Male,Loyal Customer,55,Business travel,Business,951,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +61898,15738,Female,Loyal Customer,38,Personal Travel,Eco,419,2,4,2,3,1,2,1,1,2,4,2,4,4,1,0,0.0,neutral or dissatisfied +61899,46910,Male,Loyal Customer,42,Business travel,Eco,833,3,4,4,4,3,3,3,3,2,2,3,4,3,3,55,39.0,neutral or dissatisfied +61900,56771,Female,Loyal Customer,61,Business travel,Eco Plus,597,4,2,2,2,1,3,3,4,4,4,4,3,4,5,14,14.0,satisfied +61901,28539,Female,Loyal Customer,71,Business travel,Eco,1215,5,5,2,2,3,5,5,5,5,5,5,4,5,1,0,0.0,satisfied +61902,129348,Male,Loyal Customer,50,Personal Travel,Eco,2586,3,4,3,2,1,3,1,1,4,5,3,3,5,1,0,1.0,neutral or dissatisfied +61903,27533,Male,Loyal Customer,16,Personal Travel,Eco,978,3,5,3,5,2,3,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +61904,111999,Female,disloyal Customer,23,Business travel,Eco,533,4,4,4,3,3,4,3,3,3,3,5,3,4,3,71,65.0,satisfied +61905,68848,Female,disloyal Customer,24,Business travel,Business,936,5,2,5,2,2,5,2,2,3,3,4,5,5,2,0,0.0,satisfied +61906,11255,Female,Loyal Customer,60,Personal Travel,Eco,316,3,0,3,1,2,5,5,4,4,3,4,3,4,5,7,2.0,neutral or dissatisfied +61907,91579,Male,disloyal Customer,37,Business travel,Eco,723,1,2,2,3,1,2,1,1,2,3,3,4,4,1,0,7.0,neutral or dissatisfied +61908,42515,Male,Loyal Customer,71,Business travel,Business,1384,3,3,3,3,2,1,3,4,4,4,4,2,4,2,0,16.0,satisfied +61909,88488,Male,disloyal Customer,38,Business travel,Business,270,4,3,3,3,2,3,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +61910,81366,Male,Loyal Customer,46,Business travel,Business,3947,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +61911,128951,Male,Loyal Customer,39,Business travel,Business,1663,3,2,2,2,3,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +61912,122680,Male,Loyal Customer,43,Business travel,Business,361,2,4,4,4,5,2,3,2,2,2,2,4,2,4,17,57.0,neutral or dissatisfied +61913,59141,Female,Loyal Customer,48,Personal Travel,Eco,1846,2,4,2,1,2,5,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +61914,106104,Female,disloyal Customer,26,Business travel,Business,436,4,3,3,2,4,3,4,4,5,4,5,4,5,4,0,0.0,satisfied +61915,81083,Female,Loyal Customer,51,Business travel,Business,3895,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +61916,126751,Male,Loyal Customer,45,Personal Travel,Eco,2521,3,4,3,4,4,3,4,4,3,5,3,3,4,4,0,12.0,neutral or dissatisfied +61917,81520,Male,Loyal Customer,37,Business travel,Business,2463,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +61918,40398,Male,Loyal Customer,59,Business travel,Business,150,3,3,3,3,1,3,2,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +61919,102971,Female,Loyal Customer,38,Personal Travel,Business,328,2,4,2,2,1,4,4,4,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +61920,85091,Male,disloyal Customer,25,Business travel,Business,874,2,0,2,2,3,2,4,3,5,5,4,3,4,3,4,7.0,neutral or dissatisfied +61921,43695,Male,Loyal Customer,23,Business travel,Business,489,3,3,3,3,4,4,4,4,3,2,1,1,3,4,3,23.0,satisfied +61922,55496,Male,Loyal Customer,26,Business travel,Eco,1739,2,2,2,2,2,2,2,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +61923,16682,Male,Loyal Customer,52,Business travel,Eco Plus,605,4,4,4,4,4,4,4,4,2,4,1,1,2,4,3,0.0,satisfied +61924,72437,Male,Loyal Customer,41,Business travel,Business,1017,1,1,1,1,2,5,5,4,4,5,4,5,4,4,16,37.0,satisfied +61925,79764,Female,Loyal Customer,49,Business travel,Business,950,2,2,2,2,5,4,4,4,4,4,4,3,4,5,3,72.0,satisfied +61926,107672,Female,disloyal Customer,36,Business travel,Business,251,3,3,3,3,5,3,5,5,5,4,4,3,5,5,6,1.0,neutral or dissatisfied +61927,107284,Male,Loyal Customer,41,Business travel,Business,2189,0,0,0,5,3,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +61928,169,Male,Loyal Customer,35,Personal Travel,Eco,227,2,3,2,3,4,2,4,4,4,4,1,3,3,4,0,10.0,neutral or dissatisfied +61929,121999,Male,Loyal Customer,57,Business travel,Business,130,3,3,3,3,4,4,5,4,4,4,5,3,4,3,0,0.0,satisfied +61930,51752,Female,Loyal Customer,54,Personal Travel,Eco,451,5,2,5,4,3,4,4,4,4,5,4,2,4,2,0,0.0,satisfied +61931,79227,Male,Loyal Customer,58,Personal Travel,Eco Plus,1990,3,4,3,2,4,3,4,4,3,1,3,5,4,4,8,7.0,neutral or dissatisfied +61932,39019,Female,disloyal Customer,47,Business travel,Eco,113,3,4,3,4,4,3,4,4,4,5,4,1,4,4,0,0.0,neutral or dissatisfied +61933,120208,Female,disloyal Customer,27,Business travel,Eco,1496,2,2,2,4,1,2,1,1,3,3,4,3,4,1,74,82.0,neutral or dissatisfied +61934,128583,Male,disloyal Customer,34,Business travel,Business,2552,3,3,3,3,3,1,1,3,3,4,5,1,3,1,0,20.0,neutral or dissatisfied +61935,25019,Female,Loyal Customer,33,Business travel,Business,907,3,1,3,3,4,2,5,5,5,5,5,1,5,1,0,0.0,satisfied +61936,57754,Female,Loyal Customer,52,Business travel,Business,2704,3,4,3,3,5,5,5,3,5,3,5,5,4,5,1,0.0,satisfied +61937,5641,Male,Loyal Customer,51,Business travel,Business,2337,4,2,2,2,5,3,4,3,3,2,4,1,3,3,0,0.0,neutral or dissatisfied +61938,87574,Male,disloyal Customer,30,Business travel,Eco,432,2,0,2,5,1,2,1,1,3,2,3,1,5,1,88,82.0,neutral or dissatisfied +61939,40587,Female,disloyal Customer,21,Business travel,Eco,391,2,2,2,4,1,2,1,1,4,2,3,3,3,1,27,39.0,neutral or dissatisfied +61940,70131,Female,Loyal Customer,31,Business travel,Business,460,1,1,1,1,4,4,4,4,5,4,3,3,3,4,0,7.0,satisfied +61941,5562,Female,Loyal Customer,63,Business travel,Eco,501,1,4,4,4,1,3,3,2,2,1,2,3,2,3,32,20.0,neutral or dissatisfied +61942,1174,Male,Loyal Customer,12,Personal Travel,Eco,229,3,5,3,2,3,3,1,3,5,4,4,4,5,3,0,5.0,neutral or dissatisfied +61943,73600,Female,Loyal Customer,55,Business travel,Business,2129,5,5,5,5,3,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +61944,100045,Female,Loyal Customer,11,Personal Travel,Eco,277,1,4,1,2,2,1,2,2,3,2,4,3,3,2,12,14.0,neutral or dissatisfied +61945,81346,Male,disloyal Customer,26,Business travel,Eco,899,2,2,2,3,2,2,2,2,1,2,5,2,4,2,0,4.0,neutral or dissatisfied +61946,108025,Male,disloyal Customer,25,Business travel,Business,306,3,0,3,5,3,3,3,3,5,3,4,3,5,3,24,26.0,neutral or dissatisfied +61947,28177,Male,Loyal Customer,36,Personal Travel,Eco,933,2,4,2,2,3,2,3,3,3,4,5,4,4,3,0,2.0,neutral or dissatisfied +61948,97738,Male,disloyal Customer,36,Business travel,Business,587,3,3,3,1,5,3,5,5,3,4,4,4,4,5,1,0.0,neutral or dissatisfied +61949,118805,Female,Loyal Customer,30,Personal Travel,Eco,370,2,2,2,2,3,2,3,3,1,4,3,3,2,3,54,48.0,neutral or dissatisfied +61950,57708,Male,Loyal Customer,31,Personal Travel,Eco,867,2,2,2,4,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +61951,92771,Female,disloyal Customer,46,Business travel,Eco,1365,2,2,2,3,1,2,1,1,3,1,2,4,3,1,0,0.0,neutral or dissatisfied +61952,14115,Female,Loyal Customer,69,Personal Travel,Eco Plus,425,3,5,3,3,4,5,4,2,2,3,2,4,2,4,3,9.0,neutral or dissatisfied +61953,74133,Male,Loyal Customer,30,Business travel,Business,2308,3,3,3,3,3,3,3,3,5,4,4,3,4,3,0,0.0,satisfied +61954,85025,Female,Loyal Customer,56,Personal Travel,Eco,1590,1,2,0,2,2,2,2,4,4,0,4,1,4,1,0,25.0,neutral or dissatisfied +61955,97208,Female,disloyal Customer,35,Business travel,Business,1357,4,4,4,3,4,4,4,4,4,3,4,4,5,4,17,25.0,neutral or dissatisfied +61956,40296,Female,Loyal Customer,37,Personal Travel,Eco,463,5,5,5,2,1,5,1,1,1,4,2,4,3,1,0,0.0,satisfied +61957,119448,Female,Loyal Customer,33,Business travel,Business,3940,4,4,4,4,3,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +61958,48842,Male,Loyal Customer,10,Personal Travel,Business,109,4,5,4,4,3,4,3,3,4,2,1,5,4,3,0,0.0,neutral or dissatisfied +61959,62321,Female,Loyal Customer,36,Personal Travel,Eco,414,3,1,3,3,3,3,1,3,1,1,2,1,3,3,0,0.0,neutral or dissatisfied +61960,51836,Female,Loyal Customer,70,Business travel,Eco Plus,261,4,5,5,5,3,3,4,4,4,4,4,1,4,1,1,1.0,neutral or dissatisfied +61961,44982,Male,disloyal Customer,42,Business travel,Business,224,3,3,3,1,4,3,4,4,3,1,4,3,1,4,60,55.0,neutral or dissatisfied +61962,92996,Female,disloyal Customer,8,Business travel,Eco Plus,738,3,3,3,4,3,3,3,3,3,2,4,1,3,3,2,5.0,neutral or dissatisfied +61963,49739,Male,Loyal Customer,42,Business travel,Eco,109,3,2,1,2,3,3,3,3,1,1,1,2,2,3,0,0.0,neutral or dissatisfied +61964,38642,Female,disloyal Customer,27,Business travel,Eco,2611,4,4,4,2,2,4,2,2,3,5,4,1,1,2,0,0.0,neutral or dissatisfied +61965,74593,Female,disloyal Customer,49,Business travel,Business,1205,2,2,2,2,4,2,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +61966,28622,Male,Loyal Customer,32,Business travel,Eco,2541,5,5,5,5,5,5,5,5,4,1,4,3,4,5,30,17.0,satisfied +61967,69920,Female,Loyal Customer,32,Personal Travel,Eco,1514,2,5,3,2,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +61968,31169,Male,Loyal Customer,48,Business travel,Business,3813,4,5,2,5,2,3,3,4,4,4,4,4,4,4,93,86.0,neutral or dissatisfied +61969,5165,Female,Loyal Customer,56,Business travel,Business,285,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +61970,40197,Male,Loyal Customer,57,Business travel,Eco,387,4,1,1,1,4,4,4,4,4,2,3,2,3,4,0,0.0,satisfied +61971,41338,Male,Loyal Customer,42,Personal Travel,Eco,689,2,4,2,4,1,2,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +61972,49370,Female,Loyal Customer,50,Business travel,Business,1777,4,4,4,4,2,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +61973,6477,Female,Loyal Customer,21,Personal Travel,Eco Plus,315,3,4,3,5,4,3,4,4,5,2,5,5,4,4,28,20.0,neutral or dissatisfied +61974,98702,Female,Loyal Customer,62,Personal Travel,Eco,920,1,5,1,3,5,4,5,2,2,1,2,3,2,4,55,48.0,neutral or dissatisfied +61975,110101,Male,Loyal Customer,57,Business travel,Business,1072,4,4,4,4,5,5,4,5,5,5,5,5,5,3,14,4.0,satisfied +61976,102698,Male,Loyal Customer,50,Business travel,Eco,255,3,1,1,1,4,3,4,4,1,5,3,1,3,4,0,0.0,neutral or dissatisfied +61977,119729,Female,disloyal Customer,30,Business travel,Eco,1030,2,3,3,3,1,3,1,1,1,2,3,3,3,1,2,10.0,neutral or dissatisfied +61978,37166,Female,Loyal Customer,44,Personal Travel,Eco,1046,4,5,3,1,4,4,4,3,3,3,1,3,3,3,0,0.0,neutral or dissatisfied +61979,18139,Female,Loyal Customer,33,Business travel,Business,2722,2,5,2,2,4,4,2,2,2,2,2,4,2,5,25,10.0,satisfied +61980,37628,Female,Loyal Customer,11,Personal Travel,Eco,944,3,3,3,1,2,3,1,2,3,5,4,5,3,2,120,103.0,neutral or dissatisfied +61981,96861,Female,Loyal Customer,39,Business travel,Business,3110,2,3,2,2,3,5,4,4,4,4,4,1,4,3,33,25.0,satisfied +61982,60825,Female,Loyal Customer,33,Personal Travel,Eco,524,1,4,3,5,3,3,3,3,4,4,4,4,5,3,0,2.0,neutral or dissatisfied +61983,102963,Female,Loyal Customer,24,Business travel,Business,546,5,5,4,5,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +61984,96085,Male,Loyal Customer,11,Personal Travel,Eco,1090,2,4,2,3,2,2,2,2,1,5,1,4,2,2,0,0.0,neutral or dissatisfied +61985,28785,Female,Loyal Customer,39,Business travel,Business,2684,2,2,4,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +61986,894,Male,disloyal Customer,26,Business travel,Business,89,4,3,4,4,4,4,3,4,1,1,3,2,4,4,29,25.0,neutral or dissatisfied +61987,128282,Female,Loyal Customer,44,Business travel,Business,1688,1,1,1,1,5,4,4,5,5,5,5,4,5,4,13,13.0,satisfied +61988,126975,Female,disloyal Customer,34,Business travel,Business,338,1,1,1,4,3,1,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +61989,7582,Female,Loyal Customer,12,Business travel,Business,594,3,1,1,1,3,3,3,3,3,3,4,4,3,3,0,0.0,neutral or dissatisfied +61990,50556,Male,Loyal Customer,25,Personal Travel,Eco,209,2,2,2,3,3,2,3,3,1,4,4,2,4,3,41,33.0,neutral or dissatisfied +61991,8678,Female,disloyal Customer,48,Business travel,Business,304,5,5,5,2,3,5,3,3,5,5,5,4,4,3,0,0.0,satisfied +61992,10607,Female,Loyal Customer,30,Business travel,Business,667,4,4,3,4,3,4,3,3,5,3,4,4,4,3,0,0.0,satisfied +61993,125798,Female,Loyal Customer,47,Business travel,Business,992,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +61994,23352,Male,Loyal Customer,28,Business travel,Eco Plus,563,5,1,1,1,5,5,5,5,3,1,5,5,2,5,0,0.0,satisfied +61995,51777,Female,Loyal Customer,45,Personal Travel,Eco,370,1,2,1,2,5,2,2,3,3,1,3,1,3,4,54,47.0,neutral or dissatisfied +61996,94686,Female,Loyal Customer,60,Business travel,Business,3939,2,2,2,2,5,5,4,5,5,5,4,5,5,3,33,26.0,satisfied +61997,61373,Female,Loyal Customer,57,Business travel,Business,679,3,3,3,3,2,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +61998,64669,Male,Loyal Customer,46,Business travel,Business,1895,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,1.0,satisfied +61999,29228,Female,Loyal Customer,26,Business travel,Business,2346,5,2,5,5,5,5,5,5,2,5,1,5,5,5,0,0.0,satisfied +62000,73234,Female,Loyal Customer,40,Business travel,Eco Plus,946,3,1,1,1,3,3,3,3,4,1,2,4,2,3,0,0.0,neutral or dissatisfied +62001,36581,Female,Loyal Customer,33,Business travel,Business,2873,2,3,3,3,2,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +62002,35238,Male,Loyal Customer,22,Business travel,Business,972,3,1,1,1,3,3,3,3,2,3,2,1,2,3,12,52.0,neutral or dissatisfied +62003,126044,Female,Loyal Customer,31,Business travel,Business,3234,1,1,5,1,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +62004,111400,Female,Loyal Customer,31,Personal Travel,Eco,1050,2,5,2,5,4,2,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +62005,86901,Male,disloyal Customer,38,Business travel,Business,352,4,4,4,5,2,4,2,2,5,2,4,3,4,2,52,40.0,satisfied +62006,22876,Male,Loyal Customer,14,Personal Travel,Eco,147,3,5,3,3,1,3,1,1,3,5,5,4,3,1,0,0.0,neutral or dissatisfied +62007,47337,Male,Loyal Customer,36,Business travel,Business,1714,2,2,2,2,3,4,5,5,5,5,5,4,5,1,0,0.0,satisfied +62008,102168,Male,disloyal Customer,23,Business travel,Business,197,5,5,5,3,3,5,3,3,3,3,5,4,4,3,86,73.0,satisfied +62009,52710,Male,Loyal Customer,56,Business travel,Business,2049,4,1,1,1,3,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +62010,64634,Female,Loyal Customer,58,Business travel,Business,2274,1,1,1,1,4,4,5,5,5,5,5,4,5,4,54,86.0,satisfied +62011,25234,Male,Loyal Customer,60,Personal Travel,Eco,919,4,5,4,2,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +62012,8709,Female,Loyal Customer,25,Personal Travel,Eco,280,1,3,1,4,3,1,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +62013,33454,Female,Loyal Customer,32,Personal Travel,Eco,2556,4,3,4,4,4,2,2,3,3,3,4,2,3,2,39,52.0,neutral or dissatisfied +62014,41558,Male,disloyal Customer,25,Business travel,Eco,869,1,1,1,4,1,1,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +62015,95724,Female,disloyal Customer,33,Business travel,Business,181,2,2,2,5,5,2,5,5,5,5,4,3,4,5,5,17.0,neutral or dissatisfied +62016,70936,Male,disloyal Customer,22,Business travel,Eco,612,3,1,3,4,3,3,3,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +62017,97187,Female,Loyal Customer,44,Personal Travel,Eco,1211,0,4,0,3,3,4,5,2,2,0,2,4,2,4,0,0.0,satisfied +62018,15038,Female,Loyal Customer,13,Business travel,Business,488,3,3,3,3,3,3,3,3,3,1,3,2,3,3,23,28.0,neutral or dissatisfied +62019,91312,Male,Loyal Customer,31,Business travel,Eco Plus,545,2,2,5,5,2,2,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +62020,118476,Male,disloyal Customer,37,Business travel,Business,646,3,3,3,3,4,3,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +62021,56760,Female,Loyal Customer,50,Business travel,Business,1928,5,5,5,5,5,4,5,5,5,5,5,5,5,3,3,0.0,satisfied +62022,117120,Female,Loyal Customer,37,Business travel,Eco,368,2,2,2,2,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +62023,83723,Female,Loyal Customer,49,Business travel,Business,269,3,3,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +62024,16104,Female,Loyal Customer,68,Personal Travel,Eco,303,3,5,3,3,3,4,4,5,5,3,5,5,5,4,5,18.0,neutral or dissatisfied +62025,40394,Male,disloyal Customer,32,Business travel,Business,290,1,1,1,4,2,1,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +62026,15303,Female,Loyal Customer,32,Personal Travel,Eco,612,2,1,3,2,3,3,3,3,3,4,1,3,2,3,0,0.0,neutral or dissatisfied +62027,115869,Female,disloyal Customer,39,Business travel,Eco,358,1,1,1,3,4,1,4,4,2,1,3,3,4,4,27,30.0,neutral or dissatisfied +62028,127514,Female,disloyal Customer,31,Business travel,Eco Plus,1814,3,3,3,3,4,3,5,4,4,1,4,2,4,4,90,76.0,neutral or dissatisfied +62029,25676,Male,Loyal Customer,44,Personal Travel,Eco,761,4,2,4,3,4,4,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +62030,29603,Male,disloyal Customer,37,Business travel,Eco,1252,2,2,2,3,2,2,2,2,2,5,2,3,2,2,0,1.0,neutral or dissatisfied +62031,28695,Female,Loyal Customer,43,Business travel,Business,2182,2,5,5,5,2,3,4,2,2,2,2,4,2,2,5,0.0,neutral or dissatisfied +62032,54680,Female,disloyal Customer,28,Business travel,Eco,965,4,4,4,4,4,4,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +62033,62943,Female,Loyal Customer,60,Business travel,Eco,967,2,5,1,5,2,4,4,2,2,2,2,3,2,1,33,25.0,neutral or dissatisfied +62034,102274,Female,disloyal Customer,24,Business travel,Business,258,5,0,5,1,2,5,2,2,3,2,4,5,4,2,4,0.0,satisfied +62035,36852,Male,Loyal Customer,30,Personal Travel,Eco Plus,369,2,3,2,4,4,2,4,4,2,4,3,4,4,4,0,0.0,neutral or dissatisfied +62036,11227,Female,disloyal Customer,31,Personal Travel,Eco,429,3,4,3,3,5,3,5,5,3,1,3,4,3,5,69,60.0,neutral or dissatisfied +62037,13235,Male,Loyal Customer,58,Business travel,Business,1698,1,4,4,4,5,3,2,1,1,1,1,1,1,3,52,40.0,neutral or dissatisfied +62038,91741,Female,Loyal Customer,52,Business travel,Business,626,5,5,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +62039,127434,Male,Loyal Customer,67,Personal Travel,Eco,868,3,2,3,3,4,3,4,4,3,4,2,1,2,4,0,0.0,neutral or dissatisfied +62040,26124,Male,Loyal Customer,53,Personal Travel,Business,404,4,5,5,3,5,3,3,1,3,5,2,3,2,3,61,134.0,neutral or dissatisfied +62041,40518,Female,Loyal Customer,51,Business travel,Eco Plus,461,5,4,4,4,4,1,1,5,5,5,5,2,5,1,0,0.0,satisfied +62042,101963,Female,Loyal Customer,48,Business travel,Eco,628,1,1,1,1,2,3,2,1,1,1,1,1,1,3,80,70.0,neutral or dissatisfied +62043,55750,Male,Loyal Customer,47,Business travel,Business,1737,3,3,3,3,2,4,5,2,2,2,2,4,2,4,2,0.0,satisfied +62044,107954,Male,Loyal Customer,36,Business travel,Business,2418,5,4,4,4,3,2,3,5,5,4,5,3,5,2,22,16.0,neutral or dissatisfied +62045,11772,Female,Loyal Customer,34,Personal Travel,Eco,395,1,5,1,3,2,1,2,2,3,5,5,3,5,2,10,5.0,neutral or dissatisfied +62046,96654,Female,Loyal Customer,10,Personal Travel,Eco,937,2,4,1,2,4,1,4,4,5,2,5,3,5,4,4,17.0,neutral or dissatisfied +62047,99037,Male,Loyal Customer,65,Personal Travel,Eco,1009,3,5,3,5,2,3,2,2,4,2,5,3,4,2,10,9.0,neutral or dissatisfied +62048,124756,Female,Loyal Customer,48,Business travel,Business,2463,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +62049,119554,Male,Loyal Customer,18,Personal Travel,Eco,759,2,4,2,1,2,2,2,2,3,2,4,4,4,2,72,78.0,neutral or dissatisfied +62050,29239,Female,Loyal Customer,45,Business travel,Eco,834,2,5,5,5,2,4,1,1,1,2,1,4,1,4,0,0.0,satisfied +62051,17313,Female,Loyal Customer,18,Business travel,Business,1960,3,2,2,2,3,3,3,4,3,4,3,3,2,3,184,183.0,neutral or dissatisfied +62052,122020,Female,disloyal Customer,33,Business travel,Eco,130,2,4,1,4,5,1,5,5,4,1,3,4,4,5,1,6.0,neutral or dissatisfied +62053,120258,Female,Loyal Customer,62,Business travel,Business,2884,5,5,5,5,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +62054,82204,Female,Loyal Customer,58,Business travel,Business,1902,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +62055,129531,Female,Loyal Customer,29,Business travel,Eco,2342,2,4,4,4,2,2,2,2,4,4,3,2,3,2,9,25.0,neutral or dissatisfied +62056,9737,Female,disloyal Customer,23,Business travel,Eco,926,5,5,5,3,1,5,1,1,5,4,5,5,5,1,23,3.0,satisfied +62057,23390,Male,disloyal Customer,27,Business travel,Eco,300,4,0,4,2,4,4,1,4,4,5,3,4,5,4,20,11.0,neutral or dissatisfied +62058,121918,Male,Loyal Customer,39,Personal Travel,Eco,337,1,5,1,3,1,1,1,1,1,2,2,2,3,1,0,0.0,neutral or dissatisfied +62059,73923,Male,Loyal Customer,40,Business travel,Business,2342,2,2,2,2,3,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +62060,39074,Male,disloyal Customer,25,Business travel,Business,1174,5,0,4,5,3,4,1,3,4,1,2,3,1,3,0,0.0,satisfied +62061,101543,Female,Loyal Customer,67,Personal Travel,Eco,345,2,3,2,3,1,3,4,2,2,2,2,4,2,1,8,0.0,neutral or dissatisfied +62062,114988,Female,Loyal Customer,57,Business travel,Business,2603,4,4,5,4,4,4,4,5,5,5,5,4,5,4,118,114.0,satisfied +62063,21537,Female,Loyal Customer,21,Personal Travel,Eco,377,2,4,2,1,3,2,3,3,3,5,4,4,4,3,7,20.0,neutral or dissatisfied +62064,60482,Female,Loyal Customer,26,Business travel,Business,1947,4,4,4,4,4,4,4,4,4,3,4,5,4,4,2,0.0,satisfied +62065,26550,Male,Loyal Customer,59,Personal Travel,Eco,1105,2,3,2,5,3,2,3,3,5,5,5,4,2,3,0,0.0,neutral or dissatisfied +62066,32165,Female,disloyal Customer,24,Business travel,Eco,102,0,5,0,1,3,5,3,3,4,1,3,5,1,3,11,12.0,satisfied +62067,89673,Female,Loyal Customer,43,Business travel,Business,1089,4,4,4,4,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +62068,110871,Female,disloyal Customer,37,Business travel,Business,404,4,4,4,3,5,4,5,5,4,4,5,5,5,5,35,27.0,satisfied +62069,70139,Male,Loyal Customer,66,Personal Travel,Eco,460,3,5,3,2,3,3,1,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +62070,28019,Female,Loyal Customer,7,Business travel,Business,3395,4,4,4,4,5,5,5,5,5,1,2,1,3,5,0,0.0,satisfied +62071,46365,Male,disloyal Customer,37,Business travel,Eco,1013,2,1,1,3,3,1,3,3,4,4,3,4,3,3,35,32.0,neutral or dissatisfied +62072,73459,Male,Loyal Customer,56,Personal Travel,Eco,1012,3,5,3,4,1,3,1,1,5,3,4,2,4,1,0,0.0,neutral or dissatisfied +62073,61947,Male,Loyal Customer,49,Business travel,Business,2052,2,2,2,2,1,2,3,2,2,2,2,1,2,1,10,0.0,neutral or dissatisfied +62074,21835,Female,disloyal Customer,45,Business travel,Business,503,3,3,3,5,4,3,4,4,5,2,4,5,5,4,8,3.0,neutral or dissatisfied +62075,35020,Female,Loyal Customer,52,Personal Travel,Eco,740,3,4,3,2,3,4,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +62076,85351,Male,Loyal Customer,29,Business travel,Eco Plus,874,3,2,2,2,3,3,3,3,3,1,3,3,3,3,56,50.0,neutral or dissatisfied +62077,11565,Female,Loyal Customer,25,Business travel,Business,1853,3,5,5,5,3,3,3,3,2,2,4,4,3,3,13,15.0,neutral or dissatisfied +62078,16355,Male,Loyal Customer,33,Business travel,Eco Plus,160,0,0,0,2,2,0,2,2,1,2,5,5,4,2,4,0.0,satisfied +62079,50248,Male,Loyal Customer,47,Business travel,Business,2769,3,3,3,3,1,3,3,4,4,3,3,1,4,1,0,0.0,neutral or dissatisfied +62080,8142,Male,Loyal Customer,39,Business travel,Business,530,2,2,2,2,5,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +62081,97008,Male,Loyal Customer,26,Personal Travel,Eco,883,3,2,3,4,3,3,3,3,4,1,4,3,3,3,4,7.0,neutral or dissatisfied +62082,26090,Male,disloyal Customer,21,Business travel,Eco,591,2,1,2,3,2,2,2,2,4,5,3,2,3,2,30,27.0,neutral or dissatisfied +62083,12224,Male,Loyal Customer,22,Personal Travel,Business,253,2,1,2,2,4,2,4,4,2,3,3,2,2,4,0,0.0,neutral or dissatisfied +62084,17191,Male,Loyal Customer,51,Personal Travel,Eco,643,2,4,2,3,1,2,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +62085,15415,Female,Loyal Customer,36,Business travel,Business,2498,1,1,1,1,4,4,4,1,1,1,1,3,1,3,0,8.0,neutral or dissatisfied +62086,6507,Female,Loyal Customer,34,Business travel,Business,599,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +62087,11687,Female,Loyal Customer,55,Business travel,Business,3850,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +62088,6267,Male,disloyal Customer,30,Business travel,Business,693,0,0,0,1,2,0,2,2,5,4,5,5,4,2,19,32.0,satisfied +62089,94856,Male,disloyal Customer,24,Business travel,Business,233,2,2,2,3,2,2,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +62090,6693,Female,Loyal Customer,54,Business travel,Business,315,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +62091,103631,Female,Loyal Customer,43,Business travel,Business,405,4,4,4,4,4,4,5,5,5,5,5,4,5,5,16,15.0,satisfied +62092,8089,Female,Loyal Customer,60,Business travel,Business,3661,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +62093,34295,Male,Loyal Customer,50,Personal Travel,Eco,496,3,5,2,4,4,2,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +62094,91423,Female,disloyal Customer,25,Business travel,Business,549,1,4,1,5,4,1,1,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +62095,12988,Female,Loyal Customer,52,Business travel,Business,2262,5,5,5,5,1,3,2,3,3,3,3,4,3,4,0,0.0,satisfied +62096,54082,Female,Loyal Customer,69,Business travel,Eco,1016,2,3,3,3,1,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +62097,109493,Female,Loyal Customer,55,Business travel,Business,834,1,1,1,1,5,5,4,4,4,4,4,4,4,3,78,68.0,satisfied +62098,9730,Female,Loyal Customer,42,Business travel,Eco,926,2,3,3,3,2,2,2,4,2,4,4,2,3,2,122,195.0,neutral or dissatisfied +62099,30188,Male,Loyal Customer,61,Business travel,Eco Plus,253,4,3,3,3,4,4,4,4,4,5,1,1,3,4,0,0.0,satisfied +62100,85981,Female,Loyal Customer,41,Business travel,Eco,432,1,1,1,1,1,1,1,1,3,4,3,2,3,1,52,49.0,neutral or dissatisfied +62101,67337,Male,disloyal Customer,43,Business travel,Business,1471,5,5,5,4,5,5,5,5,4,2,4,5,4,5,0,0.0,satisfied +62102,1694,Female,disloyal Customer,33,Business travel,Business,364,4,4,4,4,1,4,1,1,5,5,5,3,5,1,0,11.0,neutral or dissatisfied +62103,72534,Male,Loyal Customer,43,Business travel,Eco,1017,1,1,1,1,1,1,1,1,4,5,3,4,2,1,0,0.0,neutral or dissatisfied +62104,57526,Male,Loyal Customer,33,Business travel,Eco,413,4,5,2,5,4,4,4,4,4,3,3,3,4,4,19,24.0,neutral or dissatisfied +62105,114858,Female,Loyal Customer,57,Business travel,Business,337,3,5,3,3,5,4,5,3,3,4,3,4,3,4,24,21.0,satisfied +62106,97759,Male,Loyal Customer,67,Personal Travel,Eco,587,2,5,2,3,1,2,1,1,4,3,5,5,5,1,79,64.0,neutral or dissatisfied +62107,78511,Female,Loyal Customer,54,Business travel,Eco,126,5,3,3,3,3,4,2,5,5,5,5,2,5,2,0,0.0,satisfied +62108,120284,Female,disloyal Customer,44,Business travel,Eco,1176,3,3,3,4,1,3,1,1,4,5,4,1,3,1,10,27.0,neutral or dissatisfied +62109,21132,Male,Loyal Customer,59,Personal Travel,Eco,106,2,4,2,2,1,2,1,1,3,5,5,1,3,1,3,17.0,neutral or dissatisfied +62110,72937,Male,Loyal Customer,54,Business travel,Business,1096,4,4,4,4,3,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +62111,2518,Female,Loyal Customer,34,Business travel,Business,2149,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +62112,108012,Male,Loyal Customer,26,Business travel,Business,1560,1,1,1,1,4,4,4,4,3,5,5,5,5,4,17,9.0,satisfied +62113,57620,Female,Loyal Customer,52,Business travel,Business,2971,0,4,0,2,1,1,1,5,4,4,5,1,3,1,147,139.0,satisfied +62114,56808,Female,Loyal Customer,50,Business travel,Business,1725,2,2,2,2,4,4,4,4,4,5,4,3,4,3,4,10.0,satisfied +62115,16870,Male,Loyal Customer,36,Business travel,Business,746,2,2,2,2,1,4,2,4,4,4,4,4,4,3,32,23.0,satisfied +62116,19852,Male,Loyal Customer,26,Business travel,Business,2880,4,4,4,4,4,4,4,4,2,3,3,2,4,4,3,0.0,neutral or dissatisfied +62117,72327,Female,disloyal Customer,20,Business travel,Eco,985,3,3,3,3,2,3,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +62118,1428,Female,Loyal Customer,45,Business travel,Business,2978,3,2,2,2,4,3,3,2,2,2,3,3,2,2,0,0.0,neutral or dissatisfied +62119,102821,Male,Loyal Customer,52,Personal Travel,Eco,342,3,4,2,3,1,2,1,1,5,5,5,4,5,1,9,24.0,neutral or dissatisfied +62120,82404,Male,Loyal Customer,31,Personal Travel,Eco,500,4,4,3,5,4,3,4,4,4,2,4,5,4,4,0,0.0,satisfied +62121,46544,Male,Loyal Customer,59,Business travel,Business,212,0,3,0,4,3,4,2,5,5,5,5,4,5,2,0,0.0,satisfied +62122,32107,Female,Loyal Customer,32,Business travel,Eco,101,5,1,1,1,5,5,5,5,4,2,5,4,3,5,0,11.0,satisfied +62123,15072,Male,disloyal Customer,41,Business travel,Business,322,2,3,3,1,5,2,5,5,5,2,4,4,4,5,0,4.0,satisfied +62124,106119,Female,Loyal Customer,54,Business travel,Business,1685,2,4,2,2,3,4,5,4,4,4,4,3,4,3,31,20.0,satisfied +62125,4772,Male,Loyal Customer,47,Business travel,Business,403,3,3,3,3,2,4,4,4,4,4,4,4,4,4,111,101.0,satisfied +62126,19949,Male,Loyal Customer,53,Personal Travel,Eco,296,2,4,2,3,1,2,1,1,3,5,5,4,5,1,43,38.0,neutral or dissatisfied +62127,87556,Male,disloyal Customer,27,Business travel,Business,432,2,2,2,2,4,2,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +62128,98997,Female,Loyal Customer,63,Personal Travel,Eco,479,1,5,5,1,5,5,2,4,4,5,4,2,4,5,12,8.0,neutral or dissatisfied +62129,17562,Male,Loyal Customer,44,Business travel,Eco,1034,5,5,5,5,5,5,5,5,4,5,1,1,2,5,0,0.0,satisfied +62130,128698,Female,Loyal Customer,47,Business travel,Business,1235,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +62131,84802,Female,Loyal Customer,58,Business travel,Eco,547,3,4,4,4,3,4,4,3,3,3,3,4,3,3,7,11.0,neutral or dissatisfied +62132,119876,Female,Loyal Customer,56,Personal Travel,Eco,912,1,4,1,5,4,5,5,2,2,1,2,5,2,4,0,19.0,neutral or dissatisfied +62133,101091,Female,Loyal Customer,54,Business travel,Business,1069,4,4,4,4,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +62134,69819,Female,disloyal Customer,25,Business travel,Eco,1055,1,1,1,4,2,1,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +62135,99038,Female,Loyal Customer,45,Personal Travel,Eco,1009,3,4,3,4,4,1,1,3,3,3,3,5,3,4,43,36.0,neutral or dissatisfied +62136,6949,Male,disloyal Customer,39,Business travel,Eco,188,1,0,0,3,5,0,2,5,5,5,1,1,2,5,0,0.0,neutral or dissatisfied +62137,89287,Female,Loyal Customer,41,Business travel,Business,3839,3,1,1,1,3,3,3,2,1,3,3,3,4,3,289,285.0,neutral or dissatisfied +62138,4933,Male,Loyal Customer,45,Business travel,Business,1700,2,2,2,2,3,3,3,2,2,2,2,3,2,1,7,0.0,neutral or dissatisfied +62139,100823,Male,Loyal Customer,35,Business travel,Business,3322,1,5,1,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +62140,59210,Female,Loyal Customer,55,Personal Travel,Eco,1440,4,1,4,3,5,4,3,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +62141,68144,Male,Loyal Customer,48,Business travel,Business,597,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +62142,77228,Female,disloyal Customer,27,Business travel,Business,1590,5,5,5,1,3,5,5,3,3,3,5,3,4,3,0,0.0,satisfied +62143,94160,Female,Loyal Customer,53,Business travel,Business,189,4,2,4,4,5,5,4,5,5,4,4,4,5,4,5,16.0,satisfied +62144,53616,Male,Loyal Customer,36,Business travel,Eco,1874,1,3,3,3,1,2,1,1,3,2,4,4,5,1,33,53.0,satisfied +62145,9758,Female,Loyal Customer,40,Personal Travel,Business,456,2,2,2,4,3,3,4,3,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +62146,6979,Female,disloyal Customer,20,Business travel,Business,299,4,3,4,3,3,4,4,3,5,5,5,5,5,3,0,5.0,satisfied +62147,2142,Female,Loyal Customer,45,Business travel,Business,1617,3,3,4,3,1,3,3,3,3,2,3,2,3,3,6,0.0,neutral or dissatisfied +62148,39213,Male,Loyal Customer,52,Business travel,Business,2066,3,3,3,3,3,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +62149,71832,Female,Loyal Customer,11,Business travel,Business,1744,4,3,3,3,4,4,4,4,4,2,4,4,4,4,0,9.0,neutral or dissatisfied +62150,93806,Female,Loyal Customer,14,Personal Travel,Eco Plus,1259,3,4,3,5,3,3,5,5,3,3,4,5,5,5,145,123.0,neutral or dissatisfied +62151,78849,Female,Loyal Customer,39,Business travel,Eco Plus,432,2,2,2,2,2,2,2,2,3,2,2,2,3,2,0,0.0,neutral or dissatisfied +62152,8521,Female,Loyal Customer,69,Personal Travel,Eco,862,1,3,1,3,1,2,3,4,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +62153,30836,Male,Loyal Customer,28,Personal Travel,Eco,896,3,4,3,1,3,3,3,3,5,3,5,4,5,3,91,77.0,neutral or dissatisfied +62154,58077,Female,disloyal Customer,27,Business travel,Eco,612,1,4,1,4,4,1,4,4,2,4,4,1,3,4,17,25.0,neutral or dissatisfied +62155,11547,Female,Loyal Customer,49,Personal Travel,Business,657,3,5,3,1,3,4,3,4,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +62156,66612,Female,Loyal Customer,24,Personal Travel,Eco,761,1,4,1,4,1,1,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +62157,33623,Male,Loyal Customer,74,Business travel,Business,399,2,1,1,1,2,4,4,2,2,2,2,1,2,4,28,24.0,neutral or dissatisfied +62158,41811,Female,disloyal Customer,27,Business travel,Eco,489,2,3,2,3,3,2,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +62159,42894,Male,Loyal Customer,68,Business travel,Business,2066,3,5,5,5,2,2,3,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +62160,79277,Male,Loyal Customer,46,Business travel,Business,2248,5,5,5,5,5,3,4,5,5,5,5,5,5,4,6,0.0,satisfied +62161,38872,Female,Loyal Customer,66,Business travel,Business,1726,4,4,4,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +62162,95850,Male,disloyal Customer,23,Business travel,Business,580,5,2,5,1,4,5,4,4,5,5,5,4,5,4,19,11.0,satisfied +62163,63928,Female,Loyal Customer,53,Personal Travel,Eco,1192,2,4,2,3,4,4,4,4,4,2,4,4,4,4,0,1.0,neutral or dissatisfied +62164,25195,Male,Loyal Customer,23,Business travel,Eco Plus,577,5,2,2,2,5,5,5,5,3,1,2,2,2,5,0,0.0,satisfied +62165,28717,Female,disloyal Customer,21,Business travel,Eco,1069,4,4,4,4,4,2,2,3,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +62166,24438,Male,Loyal Customer,30,Business travel,Eco Plus,634,5,3,3,3,5,5,5,5,2,4,5,2,5,5,0,0.0,satisfied +62167,129095,Male,Loyal Customer,55,Business travel,Business,2342,5,5,5,5,4,5,4,4,4,4,4,5,4,4,5,1.0,satisfied +62168,128289,Male,Loyal Customer,49,Business travel,Business,370,2,2,2,2,4,5,5,4,4,4,4,4,4,4,0,7.0,satisfied +62169,27340,Male,Loyal Customer,23,Business travel,Business,671,3,3,3,3,4,4,4,4,2,5,1,2,2,4,0,0.0,satisfied +62170,56942,Male,Loyal Customer,57,Business travel,Business,2434,3,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0.0,satisfied +62171,37212,Male,Loyal Customer,29,Business travel,Business,2029,2,2,2,2,4,4,4,4,4,5,4,5,5,4,53,50.0,satisfied +62172,95311,Female,Loyal Customer,33,Personal Travel,Eco,248,4,4,4,1,2,4,2,2,5,3,4,3,4,2,0,1.0,neutral or dissatisfied +62173,104731,Male,Loyal Customer,28,Business travel,Business,1407,3,1,3,3,2,2,2,2,3,2,5,3,5,2,10,0.0,satisfied +62174,5182,Male,Loyal Customer,36,Business travel,Eco,293,3,5,5,5,3,3,3,3,2,3,4,1,3,3,2,0.0,neutral or dissatisfied +62175,20842,Male,Loyal Customer,8,Personal Travel,Eco,508,4,5,4,1,3,4,3,3,4,2,5,3,5,3,0,0.0,satisfied +62176,113691,Female,Loyal Customer,13,Personal Travel,Eco,236,1,1,1,2,4,1,4,4,4,1,3,2,3,4,0,0.0,neutral or dissatisfied +62177,110574,Male,Loyal Customer,26,Business travel,Business,2346,2,4,4,4,2,2,2,2,1,3,4,1,4,2,49,44.0,neutral or dissatisfied +62178,127075,Male,Loyal Customer,18,Business travel,Business,1809,4,4,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +62179,18994,Male,Loyal Customer,28,Personal Travel,Eco,388,3,5,3,2,3,3,3,3,4,2,4,5,5,3,67,56.0,neutral or dissatisfied +62180,89905,Female,disloyal Customer,27,Business travel,Business,1310,3,3,3,3,4,3,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +62181,29393,Female,Loyal Customer,53,Business travel,Business,2466,4,4,4,4,5,5,5,3,2,3,2,5,4,5,0,0.0,satisfied +62182,114199,Female,Loyal Customer,50,Business travel,Business,1912,3,3,3,3,3,5,5,5,5,5,5,3,5,3,20,18.0,satisfied +62183,83576,Male,Loyal Customer,31,Business travel,Business,2988,1,4,4,4,1,1,1,1,1,3,4,2,4,1,0,0.0,neutral or dissatisfied +62184,81526,Male,Loyal Customer,34,Business travel,Business,1124,2,2,3,2,2,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +62185,113728,Male,Loyal Customer,13,Personal Travel,Eco,386,2,4,5,4,2,5,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +62186,40280,Female,Loyal Customer,34,Personal Travel,Eco,436,2,5,2,4,2,2,2,2,4,2,5,3,4,2,13,26.0,neutral or dissatisfied +62187,15953,Male,Loyal Customer,14,Personal Travel,Eco,723,1,5,1,1,2,1,2,2,2,2,2,1,3,2,32,32.0,neutral or dissatisfied +62188,117408,Female,disloyal Customer,22,Business travel,Eco,1136,2,2,2,4,3,2,3,3,1,4,4,1,3,3,60,52.0,neutral or dissatisfied +62189,7387,Male,Loyal Customer,22,Business travel,Business,1844,4,4,4,4,5,5,5,5,5,4,4,5,3,5,147,205.0,satisfied +62190,75991,Female,Loyal Customer,47,Personal Travel,Eco,228,1,4,1,3,1,4,4,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +62191,10255,Female,Loyal Customer,17,Personal Travel,Business,224,3,1,3,2,3,3,2,3,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +62192,31475,Male,Loyal Customer,26,Business travel,Business,3906,2,2,2,2,4,4,4,4,4,5,1,4,5,4,31,78.0,satisfied +62193,48467,Female,Loyal Customer,32,Business travel,Business,2537,2,2,2,2,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +62194,118022,Female,disloyal Customer,25,Business travel,Business,1044,2,5,2,5,2,2,3,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +62195,3467,Female,Loyal Customer,12,Personal Travel,Eco Plus,296,4,3,4,3,1,4,5,1,2,2,4,3,4,1,0,7.0,neutral or dissatisfied +62196,118113,Male,Loyal Customer,38,Business travel,Business,1300,4,4,4,4,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +62197,121170,Male,Loyal Customer,58,Personal Travel,Eco,2402,3,4,3,3,3,5,4,4,5,5,4,4,3,4,0,0.0,neutral or dissatisfied +62198,72793,Female,Loyal Customer,48,Business travel,Business,645,4,4,4,4,2,5,2,2,2,2,2,4,2,3,0,0.0,satisfied +62199,66403,Male,disloyal Customer,27,Business travel,Business,1562,2,2,2,3,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +62200,118434,Male,disloyal Customer,44,Business travel,Business,338,3,3,3,1,5,3,5,5,5,2,4,4,4,5,1,0.0,neutral or dissatisfied +62201,22953,Male,Loyal Customer,44,Business travel,Business,817,3,3,3,3,1,2,1,5,5,5,5,5,5,3,2,0.0,satisfied +62202,129849,Female,Loyal Customer,21,Personal Travel,Eco,337,2,4,3,3,1,3,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +62203,29450,Male,Loyal Customer,38,Business travel,Business,1710,2,2,5,2,3,4,4,2,2,2,2,2,2,1,3,12.0,neutral or dissatisfied +62204,33507,Female,Loyal Customer,17,Personal Travel,Eco,965,3,5,4,4,3,4,5,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +62205,7482,Male,Loyal Customer,46,Business travel,Business,925,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +62206,96629,Male,Loyal Customer,32,Business travel,Eco,937,3,1,1,1,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +62207,79841,Male,Loyal Customer,43,Business travel,Business,1903,3,3,3,3,2,5,4,3,3,3,3,5,3,5,0,21.0,satisfied +62208,70993,Female,Loyal Customer,59,Business travel,Business,978,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +62209,36494,Female,Loyal Customer,37,Business travel,Business,3355,2,2,4,2,1,3,3,2,2,2,2,4,2,3,0,6.0,neutral or dissatisfied +62210,28555,Male,Loyal Customer,21,Personal Travel,Eco,2640,3,5,3,1,5,3,5,5,2,3,5,3,5,5,28,0.0,neutral or dissatisfied +62211,22034,Female,Loyal Customer,19,Personal Travel,Eco Plus,551,1,3,1,2,3,1,3,3,4,5,1,4,5,3,6,0.0,neutral or dissatisfied +62212,115201,Female,Loyal Customer,39,Business travel,Business,3624,1,3,1,1,2,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +62213,82158,Female,Loyal Customer,47,Business travel,Eco,237,2,3,3,3,4,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +62214,45815,Male,Loyal Customer,33,Personal Travel,Eco,391,3,5,3,1,5,3,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +62215,92992,Female,Loyal Customer,20,Personal Travel,Eco,738,4,5,5,3,4,5,2,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +62216,26263,Female,Loyal Customer,31,Business travel,Business,859,3,3,5,3,4,4,4,4,3,2,4,5,4,4,3,2.0,satisfied +62217,81685,Male,Loyal Customer,41,Business travel,Business,2652,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +62218,86899,Male,Loyal Customer,50,Business travel,Business,352,1,1,1,1,3,4,5,4,4,4,4,4,4,5,4,0.0,satisfied +62219,112089,Male,Loyal Customer,69,Personal Travel,Eco,1491,1,4,1,3,2,1,2,2,2,5,4,4,3,2,24,12.0,neutral or dissatisfied +62220,24531,Male,disloyal Customer,25,Business travel,Eco Plus,892,2,2,2,4,1,2,1,1,1,4,3,2,3,1,0,3.0,neutral or dissatisfied +62221,34159,Female,Loyal Customer,28,Business travel,Business,1189,1,2,5,2,1,1,1,1,1,3,3,3,3,1,29,18.0,neutral or dissatisfied +62222,93236,Male,Loyal Customer,18,Personal Travel,Eco,1694,2,4,2,4,2,2,2,2,3,5,1,2,2,2,0,0.0,neutral or dissatisfied +62223,20113,Male,Loyal Customer,60,Business travel,Business,466,1,0,0,3,5,3,4,2,2,0,2,3,2,3,4,0.0,neutral or dissatisfied +62224,122141,Male,disloyal Customer,24,Business travel,Eco,541,4,0,4,4,4,4,4,4,4,5,5,3,5,4,0,35.0,neutral or dissatisfied +62225,33712,Male,Loyal Customer,37,Personal Travel,Eco,805,2,4,2,3,2,2,4,2,1,1,2,1,4,2,0,0.0,neutral or dissatisfied +62226,93389,Male,disloyal Customer,34,Business travel,Business,671,2,2,2,3,4,2,4,4,4,3,4,4,5,4,8,9.0,neutral or dissatisfied +62227,6301,Female,Loyal Customer,41,Business travel,Business,1555,0,0,0,4,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +62228,96828,Female,Loyal Customer,43,Business travel,Business,957,3,4,4,4,5,4,3,3,3,3,3,1,3,3,3,0.0,neutral or dissatisfied +62229,90121,Female,Loyal Customer,56,Business travel,Business,3714,1,1,1,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +62230,116532,Male,Loyal Customer,27,Personal Travel,Eco,404,2,5,4,3,1,4,1,1,3,4,4,4,4,1,1,0.0,neutral or dissatisfied +62231,17872,Female,disloyal Customer,16,Business travel,Eco,425,4,2,5,2,4,5,5,4,4,2,3,5,5,4,0,0.0,satisfied +62232,108549,Female,Loyal Customer,16,Business travel,Eco Plus,512,2,4,2,4,2,2,1,2,3,3,4,4,4,2,12,17.0,neutral or dissatisfied +62233,10502,Female,Loyal Customer,31,Business travel,Business,2270,5,3,5,5,5,5,4,5,5,3,4,3,5,5,18,11.0,satisfied +62234,121185,Female,Loyal Customer,51,Personal Travel,Eco,2521,2,4,2,4,2,1,1,3,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +62235,124914,Female,Loyal Customer,29,Business travel,Business,3051,2,4,4,4,2,2,2,2,3,1,2,1,2,2,0,0.0,neutral or dissatisfied +62236,7332,Male,Loyal Customer,47,Business travel,Business,2862,1,1,5,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +62237,13047,Female,Loyal Customer,33,Personal Travel,Eco,304,2,4,2,3,1,2,1,1,4,4,4,3,5,1,67,110.0,neutral or dissatisfied +62238,51565,Male,Loyal Customer,35,Business travel,Eco,261,5,2,2,2,5,5,5,5,2,4,2,5,1,5,0,0.0,satisfied +62239,112152,Female,Loyal Customer,39,Business travel,Business,895,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +62240,96196,Female,disloyal Customer,26,Business travel,Business,546,3,4,3,3,1,3,1,1,4,3,4,5,4,1,3,11.0,neutral or dissatisfied +62241,32407,Male,disloyal Customer,39,Business travel,Eco,84,2,4,2,1,4,2,4,4,1,3,4,2,4,4,0,0.0,neutral or dissatisfied +62242,37643,Male,Loyal Customer,9,Personal Travel,Eco,1028,1,5,1,3,4,1,4,4,4,2,5,5,5,4,1,0.0,neutral or dissatisfied +62243,46239,Male,Loyal Customer,48,Business travel,Business,3075,4,4,4,4,1,5,2,4,4,4,4,1,4,3,0,0.0,satisfied +62244,117,Male,Loyal Customer,39,Business travel,Business,1553,4,4,4,4,1,3,3,5,5,5,4,5,5,5,0,0.0,satisfied +62245,69562,Male,Loyal Customer,28,Business travel,Business,2475,3,1,1,1,3,2,3,3,4,2,4,2,3,3,0,5.0,neutral or dissatisfied +62246,120323,Male,Loyal Customer,14,Personal Travel,Eco,268,3,1,3,3,1,3,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +62247,76597,Male,Loyal Customer,25,Business travel,Eco,481,2,2,2,2,2,2,4,2,4,4,4,2,3,2,56,61.0,neutral or dissatisfied +62248,6649,Female,Loyal Customer,13,Personal Travel,Eco,416,3,2,1,4,4,1,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +62249,85552,Female,disloyal Customer,26,Business travel,Eco,259,3,4,2,4,2,2,4,2,3,2,4,3,4,2,9,10.0,neutral or dissatisfied +62250,27949,Male,Loyal Customer,21,Business travel,Business,1660,2,2,2,2,2,2,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +62251,62214,Female,Loyal Customer,37,Personal Travel,Eco,2454,3,1,3,3,2,3,1,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +62252,26378,Male,Loyal Customer,54,Personal Travel,Eco,829,3,4,4,3,3,4,5,3,4,4,5,5,4,3,39,33.0,neutral or dissatisfied +62253,85462,Female,disloyal Customer,38,Business travel,Eco,214,3,4,3,3,4,3,4,4,3,5,4,1,4,4,0,3.0,neutral or dissatisfied +62254,93586,Male,Loyal Customer,57,Personal Travel,Eco,159,3,5,3,3,1,3,1,1,3,4,4,5,4,1,83,82.0,neutral or dissatisfied +62255,45060,Female,disloyal Customer,33,Business travel,Eco,342,2,3,2,3,4,2,4,4,3,2,3,4,3,4,84,84.0,neutral or dissatisfied +62256,96549,Female,disloyal Customer,27,Business travel,Eco Plus,436,1,0,0,3,4,0,4,4,4,4,4,4,4,4,21,3.0,neutral or dissatisfied +62257,110526,Male,Loyal Customer,67,Personal Travel,Business,551,2,3,2,2,3,3,2,3,3,2,3,3,3,4,0,9.0,neutral or dissatisfied +62258,85159,Male,Loyal Customer,31,Business travel,Eco,731,3,4,4,4,3,3,3,3,3,2,3,2,4,3,28,20.0,neutral or dissatisfied +62259,124403,Male,Loyal Customer,50,Personal Travel,Business,1262,2,4,2,3,2,4,4,4,4,2,4,4,4,4,7,8.0,neutral or dissatisfied +62260,106701,Female,Loyal Customer,28,Business travel,Business,516,2,1,1,1,2,2,2,2,3,3,3,2,3,2,54,42.0,neutral or dissatisfied +62261,80271,Male,Loyal Customer,41,Business travel,Business,2449,5,5,2,5,4,4,4,3,3,5,4,4,3,4,114,155.0,satisfied +62262,33276,Male,Loyal Customer,60,Personal Travel,Eco Plus,163,2,2,2,3,3,2,5,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +62263,37731,Male,Loyal Customer,54,Personal Travel,Eco,1047,3,4,3,4,4,3,4,4,5,5,5,3,5,4,20,0.0,neutral or dissatisfied +62264,34042,Female,Loyal Customer,18,Business travel,Business,1608,5,5,5,5,4,4,4,4,2,3,3,4,2,4,0,0.0,satisfied +62265,83504,Male,Loyal Customer,42,Personal Travel,Eco,946,4,4,4,4,5,4,5,5,3,3,5,5,4,5,0,0.0,satisfied +62266,113710,Male,Loyal Customer,65,Personal Travel,Eco,236,3,2,3,3,1,3,1,1,3,2,2,2,2,1,2,0.0,neutral or dissatisfied +62267,92773,Male,disloyal Customer,42,Business travel,Business,1671,4,4,4,3,4,4,4,4,3,3,3,5,4,4,0,0.0,satisfied +62268,112258,Female,disloyal Customer,54,Business travel,Eco,1506,2,2,2,4,4,2,2,4,2,5,3,4,4,4,26,8.0,neutral or dissatisfied +62269,38981,Female,Loyal Customer,40,Business travel,Eco,230,4,1,1,1,4,4,4,4,5,1,3,4,2,4,0,0.0,satisfied +62270,125868,Male,disloyal Customer,22,Business travel,Business,920,0,0,0,1,5,0,5,5,3,5,4,5,5,5,0,0.0,satisfied +62271,81271,Female,Loyal Customer,60,Business travel,Business,1020,4,5,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +62272,54031,Male,Loyal Customer,41,Business travel,Business,1416,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +62273,112002,Female,Loyal Customer,18,Business travel,Eco Plus,770,3,5,5,5,3,3,2,3,1,1,3,4,4,3,56,47.0,neutral or dissatisfied +62274,101381,Female,disloyal Customer,20,Business travel,Eco,486,4,0,4,5,3,4,3,3,5,2,4,5,5,3,3,18.0,satisfied +62275,110410,Male,Loyal Customer,24,Business travel,Business,3037,3,3,3,3,3,3,3,3,3,2,2,4,2,3,0,0.0,neutral or dissatisfied +62276,123859,Female,disloyal Customer,21,Business travel,Eco,603,1,0,1,3,3,1,5,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +62277,116443,Male,Loyal Customer,63,Personal Travel,Eco,447,4,5,4,1,3,4,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +62278,9168,Female,Loyal Customer,51,Business travel,Business,2457,2,4,2,2,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +62279,6444,Male,Loyal Customer,36,Personal Travel,Eco,296,5,4,5,4,4,5,4,4,1,2,4,1,4,4,0,0.0,satisfied +62280,66866,Male,Loyal Customer,53,Business travel,Business,2530,2,2,2,2,3,5,4,5,5,5,5,3,5,4,37,51.0,satisfied +62281,121132,Female,disloyal Customer,40,Business travel,Business,853,5,5,5,3,5,5,5,5,5,5,5,3,5,5,12,0.0,satisfied +62282,60263,Male,Loyal Customer,44,Business travel,Eco Plus,1709,3,5,5,5,3,3,3,3,4,5,2,2,3,3,16,0.0,neutral or dissatisfied +62283,71132,Male,Loyal Customer,67,Personal Travel,Eco,1739,2,4,2,2,4,2,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +62284,101027,Male,Loyal Customer,68,Personal Travel,Eco,564,2,4,2,4,4,2,2,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +62285,30367,Male,Loyal Customer,69,Business travel,Eco,641,4,1,3,3,5,4,5,5,3,5,3,5,1,5,0,0.0,satisfied +62286,3691,Female,Loyal Customer,46,Business travel,Business,3518,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +62287,64963,Female,disloyal Customer,24,Business travel,Eco,190,2,5,2,4,1,2,1,1,3,1,3,3,1,1,0,2.0,neutral or dissatisfied +62288,75137,Female,Loyal Customer,53,Business travel,Business,1846,2,2,2,2,5,4,4,5,5,5,5,5,5,4,3,0.0,satisfied +62289,94926,Male,disloyal Customer,26,Business travel,Eco,248,3,4,3,4,5,3,5,5,1,4,4,2,4,5,8,5.0,neutral or dissatisfied +62290,126662,Male,Loyal Customer,30,Personal Travel,Eco,602,3,5,3,2,4,3,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +62291,12494,Male,Loyal Customer,60,Business travel,Eco Plus,383,2,4,4,4,2,2,2,2,4,1,4,1,3,2,12,11.0,neutral or dissatisfied +62292,70109,Female,Loyal Customer,39,Business travel,Eco,550,3,4,4,4,3,3,3,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +62293,103262,Male,disloyal Customer,42,Business travel,Business,888,2,3,3,3,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +62294,10396,Male,Loyal Customer,56,Business travel,Business,2274,1,2,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +62295,96050,Male,Loyal Customer,47,Business travel,Business,2632,2,1,1,1,2,3,3,2,2,2,2,1,2,1,0,1.0,neutral or dissatisfied +62296,13708,Male,Loyal Customer,48,Business travel,Business,401,4,4,4,4,4,5,5,5,5,5,5,5,5,5,7,12.0,satisfied +62297,70229,Male,Loyal Customer,34,Personal Travel,Eco,1068,1,5,1,3,5,1,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +62298,105478,Male,Loyal Customer,10,Personal Travel,Eco,495,3,4,2,4,3,2,3,3,4,2,5,4,5,3,10,10.0,neutral or dissatisfied +62299,77755,Male,Loyal Customer,61,Business travel,Eco,289,2,4,4,4,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +62300,35382,Female,Loyal Customer,44,Business travel,Eco,676,4,5,5,5,4,4,4,2,3,3,4,4,1,4,107,132.0,satisfied +62301,11290,Female,Loyal Customer,44,Personal Travel,Eco,312,1,5,5,1,4,5,4,5,5,5,5,4,5,4,47,51.0,neutral or dissatisfied +62302,84830,Male,disloyal Customer,23,Business travel,Eco,534,3,1,4,4,4,4,4,4,4,5,3,1,4,4,0,1.0,neutral or dissatisfied +62303,88578,Female,Loyal Customer,28,Personal Travel,Eco,404,1,4,1,3,4,1,4,4,4,5,3,3,3,4,8,0.0,neutral or dissatisfied +62304,89185,Female,Loyal Customer,28,Personal Travel,Eco,1892,5,3,5,3,4,5,4,4,1,4,3,2,4,4,0,8.0,satisfied +62305,52563,Male,Loyal Customer,39,Business travel,Eco,160,4,4,4,4,4,4,4,4,1,5,5,3,1,4,0,0.0,satisfied +62306,18014,Male,Loyal Customer,23,Personal Travel,Eco,489,2,5,2,3,3,2,3,3,1,2,4,5,4,3,0,0.0,neutral or dissatisfied +62307,36102,Male,Loyal Customer,53,Personal Travel,Eco,413,3,4,3,4,5,3,5,5,5,5,4,3,4,5,0,15.0,neutral or dissatisfied +62308,54216,Female,Loyal Customer,53,Business travel,Business,1222,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +62309,103748,Female,disloyal Customer,38,Business travel,Business,405,2,2,2,1,3,2,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +62310,127510,Male,Loyal Customer,11,Personal Travel,Eco,2075,4,5,4,1,4,4,4,4,5,5,5,3,4,4,12,0.0,satisfied +62311,11150,Male,Loyal Customer,64,Personal Travel,Eco,316,3,5,3,2,1,3,1,1,1,4,1,3,2,1,0,0.0,neutral or dissatisfied +62312,22695,Female,Loyal Customer,40,Business travel,Eco,589,3,2,2,2,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +62313,10951,Male,Loyal Customer,35,Business travel,Business,301,3,3,3,3,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +62314,82099,Male,Loyal Customer,48,Personal Travel,Eco,1276,2,5,2,3,5,2,5,5,4,3,5,4,5,5,26,20.0,neutral or dissatisfied +62315,73981,Female,Loyal Customer,28,Business travel,Business,2330,2,2,3,2,3,3,3,5,5,5,5,3,5,3,99,105.0,satisfied +62316,105011,Female,Loyal Customer,58,Business travel,Business,3645,5,5,5,5,3,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +62317,5546,Male,Loyal Customer,69,Personal Travel,Eco,431,1,4,1,1,4,1,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +62318,45974,Male,Loyal Customer,23,Business travel,Eco Plus,872,0,3,0,1,1,0,1,1,5,1,1,1,2,1,0,5.0,satisfied +62319,57124,Male,Loyal Customer,54,Personal Travel,Eco,1222,4,1,4,4,4,4,4,4,4,2,4,3,4,4,12,9.0,neutral or dissatisfied +62320,41243,Female,Loyal Customer,34,Business travel,Business,2818,5,5,5,5,5,2,3,5,5,5,5,1,5,5,0,0.0,satisfied +62321,8297,Female,disloyal Customer,25,Business travel,Business,530,3,0,2,1,4,2,5,4,5,4,4,5,4,4,2,3.0,neutral or dissatisfied +62322,48443,Female,Loyal Customer,24,Business travel,Eco,964,5,5,5,5,5,4,3,5,5,3,4,2,5,5,82,65.0,satisfied +62323,63904,Male,Loyal Customer,44,Business travel,Business,2797,1,1,1,1,1,5,2,4,4,4,4,2,4,3,0,0.0,satisfied +62324,1962,Male,Loyal Customer,33,Business travel,Business,383,3,3,3,3,4,4,4,4,3,5,4,4,3,4,6,25.0,satisfied +62325,19714,Female,Loyal Customer,41,Business travel,Business,3094,2,3,3,3,3,3,4,2,2,2,2,2,2,3,128,115.0,neutral or dissatisfied +62326,83844,Female,Loyal Customer,28,Personal Travel,Eco,425,3,0,3,1,3,3,3,3,5,5,4,4,4,3,21,16.0,neutral or dissatisfied +62327,114711,Female,Loyal Customer,59,Business travel,Business,2811,1,1,1,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +62328,66675,Female,Loyal Customer,26,Business travel,Business,2421,2,4,4,4,2,2,2,2,2,5,4,4,4,2,0,10.0,neutral or dissatisfied +62329,112112,Female,Loyal Customer,46,Business travel,Business,2146,4,5,5,5,3,3,2,4,4,4,4,4,4,2,35,28.0,neutral or dissatisfied +62330,110940,Male,Loyal Customer,50,Personal Travel,Eco,406,4,4,4,3,1,4,1,1,5,2,1,3,1,1,0,0.0,neutral or dissatisfied +62331,12786,Male,Loyal Customer,16,Personal Travel,Business,489,1,3,1,3,1,1,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +62332,113464,Male,Loyal Customer,46,Business travel,Business,223,1,1,1,1,5,4,3,2,2,2,1,3,2,2,0,0.0,neutral or dissatisfied +62333,52059,Female,disloyal Customer,21,Business travel,Eco,351,5,0,5,3,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +62334,22654,Male,Loyal Customer,45,Business travel,Eco Plus,300,5,2,2,2,5,5,5,5,5,2,2,4,3,5,12,5.0,satisfied +62335,17648,Male,Loyal Customer,39,Business travel,Business,1896,2,2,2,2,2,2,3,4,4,4,4,1,4,5,14,3.0,satisfied +62336,26462,Male,Loyal Customer,38,Personal Travel,Eco,842,5,2,5,2,5,3,3,1,3,2,3,3,2,3,176,189.0,satisfied +62337,80468,Male,Loyal Customer,41,Business travel,Eco,1299,3,4,4,4,2,3,2,2,1,3,2,2,2,2,0,0.0,neutral or dissatisfied +62338,87851,Female,Loyal Customer,14,Personal Travel,Eco,214,2,1,2,4,3,2,3,3,3,2,5,4,1,3,0,0.0,neutral or dissatisfied +62339,81146,Male,disloyal Customer,30,Business travel,Business,1310,2,3,3,2,1,3,1,1,3,3,5,3,5,1,65,49.0,neutral or dissatisfied +62340,17052,Female,disloyal Customer,35,Business travel,Eco,1134,1,1,1,3,3,1,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +62341,3598,Male,Loyal Customer,54,Business travel,Eco,999,3,5,5,5,3,3,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +62342,66250,Male,Loyal Customer,19,Personal Travel,Eco,550,2,4,2,3,3,2,3,3,3,3,4,5,5,3,14,9.0,neutral or dissatisfied +62343,95076,Male,Loyal Customer,67,Personal Travel,Eco,248,2,4,2,3,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +62344,115308,Female,disloyal Customer,38,Business travel,Eco,446,2,3,2,2,3,2,4,3,2,4,3,1,2,3,16,17.0,neutral or dissatisfied +62345,14940,Male,disloyal Customer,24,Business travel,Eco,554,2,0,2,1,1,2,1,1,2,3,3,2,5,1,0,7.0,neutral or dissatisfied +62346,10771,Male,Loyal Customer,47,Business travel,Eco,191,3,4,4,4,3,3,3,3,3,1,3,4,3,3,10,9.0,neutral or dissatisfied +62347,92382,Male,Loyal Customer,26,Business travel,Business,2139,2,2,2,2,5,5,5,5,3,5,4,4,5,5,1,0.0,satisfied +62348,56337,Female,Loyal Customer,40,Business travel,Eco,200,4,3,3,3,4,4,4,4,3,1,4,3,4,4,0,49.0,neutral or dissatisfied +62349,77797,Female,Loyal Customer,49,Personal Travel,Eco,813,1,0,1,4,3,4,5,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +62350,108894,Male,Loyal Customer,31,Business travel,Business,1075,3,3,3,3,4,4,4,4,5,3,5,5,4,4,31,36.0,satisfied +62351,51189,Male,Loyal Customer,39,Business travel,Eco Plus,337,5,4,4,4,5,5,5,5,3,2,4,2,5,5,0,0.0,satisfied +62352,29245,Male,Loyal Customer,47,Business travel,Eco,859,5,5,5,5,5,5,5,5,1,5,2,5,2,5,25,23.0,satisfied +62353,15878,Male,Loyal Customer,18,Personal Travel,Eco,241,3,5,0,2,5,0,2,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +62354,18879,Male,Loyal Customer,41,Business travel,Eco,500,1,3,2,3,1,1,1,1,4,4,4,4,3,1,11,8.0,neutral or dissatisfied +62355,51493,Male,Loyal Customer,20,Personal Travel,Business,651,5,4,5,1,1,4,1,1,2,4,5,1,5,1,20,6.0,satisfied +62356,22748,Male,Loyal Customer,52,Business travel,Business,1595,0,0,0,4,3,5,1,5,5,5,5,5,5,5,0,0.0,satisfied +62357,14461,Female,Loyal Customer,56,Business travel,Eco,674,4,2,1,2,1,4,4,4,4,4,4,1,4,2,16,11.0,satisfied +62358,41263,Male,Loyal Customer,19,Personal Travel,Eco Plus,852,3,5,3,5,5,3,5,5,5,5,4,5,5,5,16,6.0,neutral or dissatisfied +62359,56363,Female,Loyal Customer,15,Personal Travel,Eco,200,1,1,1,4,5,1,5,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +62360,104456,Male,Loyal Customer,47,Business travel,Business,2418,1,1,1,1,4,5,4,4,4,4,4,4,4,3,12,4.0,satisfied +62361,68895,Male,Loyal Customer,46,Business travel,Business,536,4,4,4,4,1,1,1,4,4,4,4,5,4,2,0,0.0,satisfied +62362,93193,Female,Loyal Customer,55,Business travel,Business,3437,4,4,4,4,5,4,5,4,4,4,4,5,4,5,5,41.0,satisfied +62363,12309,Female,Loyal Customer,37,Business travel,Eco,305,4,2,2,2,4,4,4,4,4,1,3,4,3,4,12,11.0,neutral or dissatisfied +62364,64657,Male,Loyal Customer,44,Business travel,Business,551,1,1,1,1,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +62365,99155,Male,disloyal Customer,28,Business travel,Eco,986,3,3,3,3,2,3,2,2,4,2,3,4,4,2,21,26.0,neutral or dissatisfied +62366,47079,Female,Loyal Customer,59,Personal Travel,Eco,438,2,5,2,4,5,5,4,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +62367,121566,Male,Loyal Customer,64,Business travel,Business,1582,3,4,4,4,1,3,3,3,3,2,3,3,3,2,21,1.0,neutral or dissatisfied +62368,25006,Female,Loyal Customer,48,Business travel,Eco Plus,692,2,4,4,4,4,1,3,2,2,2,2,2,2,4,60,55.0,satisfied +62369,1317,Male,Loyal Customer,49,Business travel,Business,89,0,4,0,1,3,5,4,3,3,3,3,3,3,5,21,15.0,satisfied +62370,11022,Female,Loyal Customer,51,Business travel,Business,3635,1,3,3,3,3,2,2,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +62371,60826,Male,Loyal Customer,63,Personal Travel,Eco Plus,524,2,2,3,3,4,3,4,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +62372,591,Female,Loyal Customer,56,Business travel,Business,1507,0,0,0,3,3,5,5,2,2,3,3,4,2,3,10,12.0,satisfied +62373,23614,Male,Loyal Customer,60,Business travel,Business,2131,5,5,3,5,5,3,4,5,5,5,5,1,5,1,0,0.0,satisfied +62374,50747,Male,Loyal Customer,11,Personal Travel,Eco,199,3,4,0,2,4,0,4,4,5,2,5,3,5,4,14,14.0,neutral or dissatisfied +62375,63229,Female,disloyal Customer,27,Business travel,Eco,447,2,3,2,4,4,2,4,4,4,4,3,2,4,4,7,5.0,neutral or dissatisfied +62376,120932,Female,disloyal Customer,36,Business travel,Business,993,2,1,1,3,1,1,5,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +62377,13518,Female,Loyal Customer,50,Business travel,Business,152,1,2,2,2,5,2,3,2,2,2,1,1,2,1,0,15.0,neutral or dissatisfied +62378,48976,Female,Loyal Customer,34,Business travel,Business,373,2,2,2,2,1,4,3,4,4,4,4,4,4,5,0,5.0,satisfied +62379,128334,Female,Loyal Customer,28,Business travel,Business,3612,4,4,4,4,4,5,4,4,5,3,4,4,5,4,0,0.0,satisfied +62380,118056,Male,disloyal Customer,25,Business travel,Eco,1262,3,3,3,4,3,3,3,3,3,4,3,4,3,3,20,1.0,neutral or dissatisfied +62381,69610,Male,Loyal Customer,27,Personal Travel,Eco,2475,2,2,2,4,2,2,2,2,2,5,3,3,4,2,4,0.0,neutral or dissatisfied +62382,126620,Male,Loyal Customer,41,Personal Travel,Business,602,3,2,3,4,4,4,4,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +62383,56107,Male,Loyal Customer,58,Personal Travel,Eco,2402,4,5,4,2,4,3,3,5,2,4,4,3,3,3,3,0.0,satisfied +62384,39412,Female,Loyal Customer,25,Business travel,Eco Plus,521,4,1,1,1,4,4,4,4,4,4,5,4,3,4,0,0.0,satisfied +62385,64586,Male,Loyal Customer,54,Business travel,Business,2887,1,1,5,1,5,5,5,3,3,4,5,5,3,5,1,0.0,satisfied +62386,121729,Male,Loyal Customer,35,Business travel,Business,1475,4,4,4,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +62387,84673,Female,disloyal Customer,10,Business travel,Eco,980,3,3,3,3,5,3,5,5,2,1,4,3,4,5,43,21.0,neutral or dissatisfied +62388,24817,Male,Loyal Customer,57,Business travel,Business,3041,2,5,5,5,4,4,3,2,2,2,2,4,2,2,3,9.0,neutral or dissatisfied +62389,21473,Female,disloyal Customer,22,Business travel,Eco,306,3,0,3,2,1,3,1,1,4,5,1,3,5,1,0,0.0,neutral or dissatisfied +62390,117835,Female,Loyal Customer,49,Personal Travel,Eco,328,3,2,3,4,1,4,3,3,3,3,4,3,3,1,1,0.0,neutral or dissatisfied +62391,30716,Female,Loyal Customer,35,Business travel,Eco,1123,3,2,2,2,4,3,3,3,2,3,1,3,3,3,194,188.0,satisfied +62392,123110,Male,disloyal Customer,30,Business travel,Eco,631,2,3,3,3,5,3,5,5,4,5,4,1,4,5,15,0.0,neutral or dissatisfied +62393,81050,Female,Loyal Customer,35,Personal Travel,Eco,1399,4,4,4,1,4,4,4,4,5,2,3,3,5,4,0,0.0,satisfied +62394,56871,Female,disloyal Customer,35,Business travel,Business,2565,2,2,2,4,2,5,5,3,3,4,5,5,3,5,5,0.0,neutral or dissatisfied +62395,75548,Female,Loyal Customer,54,Business travel,Business,3460,4,4,4,4,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +62396,54350,Female,disloyal Customer,27,Business travel,Eco,1235,3,4,4,2,4,4,4,4,5,5,1,1,3,4,0,0.0,neutral or dissatisfied +62397,96686,Female,Loyal Customer,41,Business travel,Business,696,2,2,2,2,3,4,5,4,4,4,4,4,4,3,3,0.0,satisfied +62398,26156,Female,Loyal Customer,50,Business travel,Business,581,1,0,0,3,5,3,3,5,5,0,5,3,5,4,8,2.0,neutral or dissatisfied +62399,68984,Female,Loyal Customer,46,Business travel,Business,2239,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +62400,11263,Male,Loyal Customer,24,Personal Travel,Eco,309,0,5,0,5,2,0,2,2,3,3,4,4,5,2,0,0.0,satisfied +62401,43175,Male,Loyal Customer,44,Personal Travel,Eco,781,2,5,2,2,3,2,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +62402,101028,Female,Loyal Customer,32,Personal Travel,Eco,867,1,5,0,3,3,0,3,3,1,2,2,4,3,3,0,0.0,neutral or dissatisfied +62403,108829,Female,Loyal Customer,54,Business travel,Business,1894,3,3,3,3,3,4,5,5,5,5,5,4,5,5,5,0.0,satisfied +62404,22746,Male,Loyal Customer,45,Business travel,Eco,147,4,3,3,3,4,4,4,4,2,4,2,1,2,4,0,0.0,satisfied +62405,12275,Female,Loyal Customer,41,Business travel,Business,253,0,0,0,4,2,1,5,2,2,2,4,1,2,1,0,0.0,satisfied +62406,57076,Female,Loyal Customer,68,Personal Travel,Eco Plus,2065,1,4,1,1,3,3,4,1,1,1,1,3,1,3,5,0.0,neutral or dissatisfied +62407,44242,Male,Loyal Customer,22,Business travel,Eco,222,3,3,3,3,3,3,1,3,1,1,2,1,2,3,0,13.0,neutral or dissatisfied +62408,127354,Female,Loyal Customer,36,Personal Travel,Eco,507,1,3,1,4,4,1,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +62409,30400,Male,Loyal Customer,54,Personal Travel,Eco,641,1,4,1,2,5,1,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +62410,22383,Female,disloyal Customer,26,Business travel,Eco,145,4,0,3,2,4,3,4,4,5,5,2,2,1,4,0,0.0,satisfied +62411,17871,Female,Loyal Customer,47,Business travel,Business,371,3,3,3,3,4,2,4,4,4,4,4,1,4,2,0,0.0,satisfied +62412,91923,Female,Loyal Customer,40,Business travel,Business,2586,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +62413,67055,Female,disloyal Customer,24,Business travel,Eco,985,3,2,2,2,5,2,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +62414,82083,Male,Loyal Customer,43,Business travel,Business,3965,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +62415,95587,Male,disloyal Customer,26,Business travel,Business,484,2,2,2,1,3,2,3,3,3,5,4,5,5,3,1,0.0,neutral or dissatisfied +62416,77883,Male,Loyal Customer,36,Business travel,Business,3382,1,2,5,2,4,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +62417,100211,Female,Loyal Customer,67,Business travel,Business,762,4,3,3,3,3,3,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +62418,57109,Male,Loyal Customer,60,Business travel,Business,2869,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +62419,103282,Male,Loyal Customer,37,Personal Travel,Eco,718,4,4,4,2,3,4,3,3,3,4,4,5,4,3,21,20.0,neutral or dissatisfied +62420,86050,Female,Loyal Customer,57,Personal Travel,Eco,528,1,5,5,5,3,5,4,5,5,5,3,3,5,4,0,0.0,neutral or dissatisfied +62421,42243,Female,Loyal Customer,54,Business travel,Business,834,2,3,3,3,2,4,3,2,2,3,2,4,2,2,0,3.0,neutral or dissatisfied +62422,77138,Female,Loyal Customer,68,Business travel,Business,605,3,3,3,3,1,5,5,4,4,5,4,1,4,1,0,0.0,satisfied +62423,21526,Female,Loyal Customer,12,Personal Travel,Eco,399,4,4,4,1,2,4,2,2,4,2,4,4,5,2,0,0.0,satisfied +62424,12954,Female,disloyal Customer,21,Business travel,Business,641,4,3,4,1,3,4,3,3,4,4,2,4,5,3,0,0.0,satisfied +62425,3417,Male,Loyal Customer,53,Personal Travel,Eco,296,3,4,3,2,4,3,4,4,3,4,4,4,4,4,46,33.0,neutral or dissatisfied +62426,124724,Male,Loyal Customer,35,Personal Travel,Eco,399,2,4,2,5,4,2,4,4,5,2,5,4,5,4,0,14.0,neutral or dissatisfied +62427,77060,Male,Loyal Customer,62,Personal Travel,Business,991,3,3,3,4,4,4,4,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +62428,75518,Female,disloyal Customer,27,Business travel,Eco Plus,748,3,3,3,3,1,3,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +62429,457,Female,Loyal Customer,48,Business travel,Business,3945,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,18.0,satisfied +62430,71417,Male,Loyal Customer,48,Business travel,Business,1708,2,2,2,2,2,4,4,2,2,2,2,3,2,3,19,22.0,satisfied +62431,126527,Female,disloyal Customer,9,Business travel,Business,644,3,3,3,3,1,3,1,1,3,3,3,2,2,1,1,10.0,neutral or dissatisfied +62432,96264,Female,Loyal Customer,45,Personal Travel,Eco,328,4,3,4,4,5,3,3,2,2,4,2,3,2,2,5,,neutral or dissatisfied +62433,102016,Female,Loyal Customer,33,Business travel,Business,2954,3,3,3,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +62434,15639,Female,disloyal Customer,37,Business travel,Eco Plus,283,2,2,2,3,1,2,1,1,1,5,4,3,4,1,61,50.0,neutral or dissatisfied +62435,40998,Male,Loyal Customer,38,Business travel,Eco,1362,4,4,3,4,4,4,4,4,4,4,5,4,5,4,1,0.0,satisfied +62436,72277,Male,disloyal Customer,38,Business travel,Eco,519,2,4,2,3,1,2,1,1,2,2,3,1,1,1,0,0.0,neutral or dissatisfied +62437,21735,Female,Loyal Customer,27,Business travel,Business,563,3,3,3,3,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +62438,55198,Male,Loyal Customer,19,Personal Travel,Eco Plus,1379,1,1,1,4,2,1,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +62439,106813,Female,Loyal Customer,46,Business travel,Business,1488,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,10.0,satisfied +62440,117944,Male,disloyal Customer,24,Business travel,Eco,601,1,1,1,3,2,1,2,2,1,3,4,2,4,2,43,36.0,neutral or dissatisfied +62441,73303,Male,Loyal Customer,37,Business travel,Business,2883,2,2,2,2,5,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +62442,44615,Female,Loyal Customer,31,Personal Travel,Eco,566,3,5,3,3,5,3,5,5,5,4,5,5,5,5,0,1.0,neutral or dissatisfied +62443,66607,Male,Loyal Customer,34,Personal Travel,Eco,761,2,4,2,3,4,2,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +62444,55929,Male,Loyal Customer,42,Personal Travel,Eco,528,2,5,4,1,5,4,1,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +62445,35403,Female,Loyal Customer,16,Business travel,Eco,1035,4,3,3,3,4,4,2,4,1,3,3,1,4,4,32,19.0,neutral or dissatisfied +62446,72505,Female,Loyal Customer,57,Business travel,Business,1119,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +62447,128386,Female,disloyal Customer,37,Business travel,Eco,646,2,2,2,4,2,2,2,2,3,5,4,3,3,2,0,0.0,neutral or dissatisfied +62448,113280,Female,Loyal Customer,52,Business travel,Business,2922,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +62449,68582,Female,Loyal Customer,28,Personal Travel,Eco,1616,1,5,0,3,4,0,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +62450,44149,Female,Loyal Customer,57,Business travel,Eco Plus,98,4,3,3,3,2,2,5,4,4,4,4,3,4,5,0,0.0,satisfied +62451,34554,Male,Loyal Customer,36,Business travel,Eco,1598,4,4,4,4,4,4,4,4,5,1,5,5,1,4,29,12.0,satisfied +62452,13940,Female,Loyal Customer,21,Business travel,Business,1998,3,1,1,1,3,3,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +62453,86308,Male,Loyal Customer,54,Business travel,Business,1924,1,1,3,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +62454,58174,Male,disloyal Customer,17,Business travel,Eco,925,4,4,4,3,4,4,5,4,3,2,4,5,5,4,14,20.0,neutral or dissatisfied +62455,61775,Female,Loyal Customer,13,Personal Travel,Eco,1379,1,5,1,3,1,1,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +62456,15856,Female,Loyal Customer,52,Business travel,Eco,332,3,1,1,1,2,3,2,2,2,3,2,4,2,1,0,22.0,satisfied +62457,124299,Male,Loyal Customer,40,Business travel,Business,255,0,0,0,3,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +62458,20378,Male,Loyal Customer,68,Personal Travel,Eco,287,2,4,2,1,4,2,4,4,4,3,5,3,5,4,100,84.0,neutral or dissatisfied +62459,46068,Female,Loyal Customer,44,Business travel,Eco,495,4,1,1,1,1,4,3,3,3,4,3,1,3,1,0,0.0,satisfied +62460,92935,Male,Loyal Customer,50,Personal Travel,Eco,134,3,1,3,1,4,3,1,4,3,4,1,3,2,4,0,7.0,neutral or dissatisfied +62461,107631,Female,Loyal Customer,49,Personal Travel,Eco,423,2,3,2,4,1,3,3,4,4,2,2,4,4,3,49,33.0,neutral or dissatisfied +62462,124229,Female,disloyal Customer,35,Business travel,Business,1916,3,3,3,2,1,3,4,1,4,3,3,5,4,1,1,0.0,neutral or dissatisfied +62463,126825,Female,Loyal Customer,53,Business travel,Business,2125,2,2,2,2,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +62464,73476,Female,Loyal Customer,39,Personal Travel,Eco,1120,2,4,2,3,5,2,5,5,3,3,4,5,5,5,9,5.0,neutral or dissatisfied +62465,33994,Female,Loyal Customer,38,Business travel,Eco,1598,2,2,2,2,2,2,2,2,4,4,3,2,4,2,148,139.0,neutral or dissatisfied +62466,101556,Male,Loyal Customer,42,Personal Travel,Eco,345,4,4,4,4,1,4,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +62467,86352,Female,disloyal Customer,23,Business travel,Eco,762,3,3,3,2,2,3,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +62468,40323,Female,disloyal Customer,38,Business travel,Eco Plus,347,2,2,2,3,5,2,5,5,3,4,3,4,4,5,69,52.0,neutral or dissatisfied +62469,91036,Male,Loyal Customer,59,Personal Travel,Eco,581,3,5,3,2,1,3,5,1,4,2,4,4,5,1,0,2.0,neutral or dissatisfied +62470,80970,Male,Loyal Customer,40,Business travel,Business,1803,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +62471,68590,Female,Loyal Customer,28,Personal Travel,Eco,1616,4,4,4,1,2,4,2,2,4,4,3,5,4,2,2,3.0,neutral or dissatisfied +62472,112055,Female,Loyal Customer,41,Business travel,Business,1754,2,2,2,2,5,4,4,5,5,5,5,4,5,4,13,0.0,satisfied +62473,50865,Female,Loyal Customer,37,Personal Travel,Eco,109,3,5,0,3,3,0,2,3,3,2,5,3,5,3,89,91.0,neutral or dissatisfied +62474,110445,Female,Loyal Customer,24,Personal Travel,Eco,787,3,5,3,3,5,3,5,5,5,4,4,5,5,5,18,2.0,neutral or dissatisfied +62475,64845,Male,Loyal Customer,41,Business travel,Business,1912,4,3,3,3,1,2,2,4,4,3,4,3,4,3,74,65.0,neutral or dissatisfied +62476,128120,Male,Loyal Customer,68,Business travel,Business,1587,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +62477,40637,Female,Loyal Customer,57,Business travel,Eco Plus,391,4,1,5,5,2,4,5,4,4,4,4,2,4,2,4,3.0,satisfied +62478,30469,Male,Loyal Customer,9,Personal Travel,Eco,495,3,4,3,2,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +62479,41642,Female,Loyal Customer,67,Personal Travel,Business,936,3,4,3,2,2,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +62480,31599,Female,Loyal Customer,26,Personal Travel,Eco,602,4,3,4,4,5,4,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +62481,20061,Female,Loyal Customer,10,Personal Travel,Eco,738,4,5,4,3,4,4,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +62482,18636,Male,Loyal Customer,53,Personal Travel,Eco,262,5,2,0,4,5,0,5,5,4,4,3,4,4,5,0,0.0,satisfied +62483,77782,Female,Loyal Customer,30,Personal Travel,Eco,696,2,5,2,1,2,2,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +62484,77931,Male,Loyal Customer,70,Business travel,Business,2247,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +62485,4015,Male,Loyal Customer,60,Business travel,Business,1938,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +62486,3140,Female,Loyal Customer,48,Business travel,Eco,140,2,4,4,4,2,1,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +62487,108105,Male,Loyal Customer,42,Business travel,Business,1166,2,2,2,2,2,4,4,4,4,4,4,3,4,3,29,4.0,satisfied +62488,117180,Male,Loyal Customer,69,Personal Travel,Eco,646,4,3,4,2,5,4,5,5,1,3,2,3,2,5,0,0.0,neutral or dissatisfied +62489,74536,Male,Loyal Customer,55,Business travel,Business,1235,5,5,5,5,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +62490,120788,Male,Loyal Customer,9,Personal Travel,Eco,678,2,4,2,3,3,2,5,3,5,4,4,4,5,3,84,68.0,neutral or dissatisfied +62491,102545,Female,Loyal Customer,30,Personal Travel,Eco,386,2,2,2,3,4,2,4,4,4,3,3,2,3,4,10,0.0,neutral or dissatisfied +62492,5083,Female,Loyal Customer,69,Business travel,Business,3662,3,5,5,5,1,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +62493,97750,Female,Loyal Customer,26,Business travel,Eco,587,1,4,4,4,1,1,1,1,3,5,3,1,3,1,29,32.0,neutral or dissatisfied +62494,33946,Female,Loyal Customer,36,Business travel,Business,1951,1,0,0,4,1,4,4,2,2,0,2,1,2,3,0,0.0,neutral or dissatisfied +62495,50467,Female,disloyal Customer,35,Business travel,Eco,250,1,1,1,3,4,1,5,4,1,1,4,2,4,4,3,0.0,neutral or dissatisfied +62496,61754,Female,Loyal Customer,39,Personal Travel,Eco,1379,5,4,5,1,3,5,3,3,3,2,4,4,5,3,0,0.0,satisfied +62497,110048,Female,Loyal Customer,30,Business travel,Eco,2173,4,1,1,1,4,4,4,4,4,1,2,4,3,4,0,0.0,neutral or dissatisfied +62498,66620,Male,Loyal Customer,50,Business travel,Business,802,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +62499,36160,Female,Loyal Customer,33,Business travel,Business,1674,3,1,3,3,1,5,2,5,5,5,5,1,5,5,0,12.0,satisfied +62500,49444,Male,Loyal Customer,37,Business travel,Eco,373,4,3,3,3,4,4,4,4,2,4,3,3,5,4,8,0.0,satisfied +62501,92938,Male,Loyal Customer,8,Personal Travel,Eco,134,2,2,0,3,3,0,3,3,3,5,2,2,2,3,0,0.0,neutral or dissatisfied +62502,104105,Female,Loyal Customer,51,Business travel,Business,2064,2,5,1,1,3,4,4,2,2,1,2,1,2,1,12,2.0,neutral or dissatisfied +62503,117624,Female,Loyal Customer,32,Personal Travel,Eco,347,3,4,3,4,1,3,1,1,4,4,4,3,5,1,53,50.0,neutral or dissatisfied +62504,75644,Female,Loyal Customer,60,Business travel,Business,3041,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,,satisfied +62505,46706,Male,Loyal Customer,58,Personal Travel,Eco,73,1,5,1,3,3,1,3,3,2,3,5,4,3,3,0,0.0,neutral or dissatisfied +62506,44863,Female,Loyal Customer,51,Business travel,Eco Plus,693,5,1,1,1,2,4,1,5,5,5,5,4,5,2,0,57.0,satisfied +62507,100596,Male,Loyal Customer,7,Personal Travel,Eco Plus,486,4,3,4,2,2,4,1,2,1,5,3,4,2,2,0,0.0,neutral or dissatisfied +62508,27088,Female,Loyal Customer,46,Personal Travel,Eco,2496,1,5,1,1,5,3,1,3,3,1,5,3,3,1,0,0.0,neutral or dissatisfied +62509,82807,Male,Loyal Customer,51,Business travel,Business,235,5,5,5,5,2,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +62510,69454,Female,Loyal Customer,14,Personal Travel,Eco,1096,2,4,2,1,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +62511,22604,Female,Loyal Customer,47,Business travel,Business,300,1,2,2,2,1,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +62512,29377,Female,Loyal Customer,45,Business travel,Business,2457,3,2,2,2,3,3,3,2,5,4,4,3,4,3,25,24.0,neutral or dissatisfied +62513,44333,Female,Loyal Customer,60,Business travel,Business,230,2,2,1,2,3,4,5,5,5,5,5,3,5,1,0,0.0,satisfied +62514,121959,Female,Loyal Customer,30,Personal Travel,Eco,347,2,5,2,4,3,2,3,3,4,2,5,3,4,3,72,80.0,neutral or dissatisfied +62515,62559,Male,Loyal Customer,26,Business travel,Business,1744,3,3,3,3,5,5,5,5,5,3,3,3,4,5,0,0.0,satisfied +62516,106520,Male,Loyal Customer,49,Business travel,Business,3141,3,3,3,3,4,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +62517,15457,Female,disloyal Customer,28,Business travel,Eco,331,2,4,2,3,5,2,5,5,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +62518,17376,Male,Loyal Customer,38,Business travel,Eco,770,4,1,1,1,4,4,4,4,2,2,2,3,3,4,0,30.0,satisfied +62519,49274,Female,disloyal Customer,23,Business travel,Eco,89,4,0,4,4,4,4,4,4,4,4,5,2,1,4,0,0.0,satisfied +62520,93278,Male,Loyal Customer,22,Personal Travel,Eco,564,2,4,2,4,2,2,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +62521,67577,Female,disloyal Customer,20,Business travel,Eco,1235,2,2,2,5,4,2,1,4,3,5,4,4,5,4,5,0.0,satisfied +62522,75521,Female,Loyal Customer,43,Business travel,Business,1916,5,3,5,5,3,4,4,4,4,4,4,4,4,3,5,0.0,satisfied +62523,16748,Female,Loyal Customer,31,Business travel,Business,1802,4,4,5,4,4,5,4,4,2,4,5,2,1,4,4,0.0,satisfied +62524,98840,Male,Loyal Customer,35,Personal Travel,Eco,444,0,4,0,3,2,0,2,2,5,4,4,4,5,2,2,3.0,satisfied +62525,97766,Male,Loyal Customer,37,Business travel,Business,471,2,2,2,2,3,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +62526,32158,Female,disloyal Customer,39,Business travel,Eco,102,2,0,2,3,5,2,5,5,2,5,2,3,2,5,0,0.0,neutral or dissatisfied +62527,74119,Male,Loyal Customer,44,Business travel,Business,641,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,14.0,satisfied +62528,98254,Male,disloyal Customer,46,Business travel,Business,1072,2,2,2,3,2,2,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +62529,124851,Female,Loyal Customer,31,Personal Travel,Eco,280,1,5,4,1,4,4,1,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +62530,84042,Male,Loyal Customer,22,Personal Travel,Business,773,3,4,2,2,2,2,2,2,3,2,5,3,4,2,13,69.0,neutral or dissatisfied +62531,13565,Male,Loyal Customer,41,Personal Travel,Eco,152,4,5,4,1,5,4,5,5,5,3,4,4,5,5,0,9.0,neutral or dissatisfied +62532,12227,Female,Loyal Customer,62,Personal Travel,Business,127,2,1,2,3,4,1,3,3,3,2,3,4,3,2,16,13.0,neutral or dissatisfied +62533,401,Female,Loyal Customer,36,Business travel,Business,1818,4,4,4,4,2,4,4,5,5,5,5,5,5,5,0,4.0,satisfied +62534,111914,Male,disloyal Customer,21,Business travel,Eco,472,0,0,0,4,3,0,3,3,5,4,4,5,4,3,79,75.0,satisfied +62535,109570,Female,Loyal Customer,47,Personal Travel,Eco,861,2,1,2,3,1,4,3,4,4,2,2,1,4,1,0,3.0,neutral or dissatisfied +62536,60064,Male,Loyal Customer,43,Business travel,Business,1182,5,5,5,5,3,4,4,4,4,4,4,5,4,4,17,0.0,satisfied +62537,98546,Female,disloyal Customer,23,Business travel,Eco Plus,402,5,0,5,5,3,5,1,3,1,2,2,4,3,3,0,0.0,satisfied +62538,77511,Female,Loyal Customer,45,Business travel,Business,1521,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +62539,30282,Male,Loyal Customer,71,Business travel,Eco Plus,836,2,3,3,3,1,2,1,1,1,4,2,3,2,1,0,0.0,neutral or dissatisfied +62540,38365,Female,Loyal Customer,25,Personal Travel,Eco,1050,2,4,2,2,2,2,2,2,3,5,5,4,4,2,15,17.0,neutral or dissatisfied +62541,57342,Female,disloyal Customer,20,Business travel,Eco,414,4,3,4,3,2,4,3,2,4,5,4,3,4,2,11,8.0,neutral or dissatisfied +62542,128250,Female,disloyal Customer,22,Business travel,Business,338,4,5,3,2,1,3,1,1,4,2,4,4,5,1,46,36.0,satisfied +62543,42017,Female,Loyal Customer,68,Business travel,Business,2131,2,2,3,2,2,4,3,5,5,5,3,5,5,3,0,0.0,satisfied +62544,51576,Female,disloyal Customer,20,Business travel,Eco,451,1,0,1,3,3,1,3,3,2,4,1,5,1,3,0,0.0,neutral or dissatisfied +62545,7542,Male,Loyal Customer,41,Personal Travel,Eco,762,3,5,3,3,1,3,1,1,4,5,5,4,5,1,0,12.0,neutral or dissatisfied +62546,3276,Female,Loyal Customer,67,Business travel,Business,425,3,3,3,3,3,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +62547,73668,Male,Loyal Customer,31,Business travel,Business,204,1,1,1,1,1,1,1,1,1,1,3,1,3,1,0,7.0,neutral or dissatisfied +62548,30304,Male,Loyal Customer,44,Business travel,Business,1630,3,1,1,1,3,1,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +62549,56160,Male,disloyal Customer,9,Business travel,Eco,1400,3,3,3,3,2,3,2,2,4,2,3,2,4,2,0,4.0,neutral or dissatisfied +62550,96401,Male,Loyal Customer,37,Business travel,Eco,846,3,4,4,4,3,3,3,3,2,3,4,2,3,3,0,0.0,neutral or dissatisfied +62551,91892,Male,Loyal Customer,36,Business travel,Business,2475,2,1,1,1,5,3,4,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +62552,62481,Female,disloyal Customer,30,Business travel,Business,1744,3,3,3,1,1,3,1,1,4,2,4,4,5,1,18,37.0,neutral or dissatisfied +62553,44173,Female,Loyal Customer,37,Business travel,Business,3236,0,5,0,1,2,5,1,3,3,3,3,2,3,4,0,0.0,satisfied +62554,124456,Female,Loyal Customer,56,Business travel,Business,980,1,1,1,1,2,5,5,5,5,5,5,4,5,5,15,4.0,satisfied +62555,96290,Female,Loyal Customer,24,Personal Travel,Eco,546,4,2,4,3,1,4,1,1,1,1,4,2,3,1,0,0.0,satisfied +62556,1864,Male,Loyal Customer,34,Business travel,Business,3801,3,3,3,3,2,4,4,5,5,5,5,5,5,3,8,0.0,satisfied +62557,104495,Male,Loyal Customer,31,Personal Travel,Eco,860,1,4,1,4,1,1,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +62558,91181,Male,Loyal Customer,62,Personal Travel,Eco,404,1,4,1,4,5,1,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +62559,67242,Male,Loyal Customer,17,Personal Travel,Eco,1121,2,4,2,4,5,2,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +62560,24343,Female,Loyal Customer,42,Business travel,Eco,634,2,2,2,2,3,3,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +62561,79731,Female,disloyal Customer,35,Business travel,Business,712,1,0,0,1,4,0,4,4,5,4,4,4,4,4,0,7.0,neutral or dissatisfied +62562,37047,Female,Loyal Customer,8,Personal Travel,Eco,1105,3,0,3,4,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +62563,113794,Female,Loyal Customer,60,Business travel,Business,386,1,1,1,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +62564,98794,Male,Loyal Customer,56,Personal Travel,Eco,630,3,4,3,3,2,3,2,2,5,2,5,1,5,2,10,12.0,neutral or dissatisfied +62565,65405,Male,Loyal Customer,60,Personal Travel,Eco,631,1,5,1,2,5,1,5,5,4,4,5,2,4,5,3,1.0,neutral or dissatisfied +62566,43365,Female,Loyal Customer,64,Personal Travel,Eco,347,2,5,2,4,4,4,4,5,5,2,4,3,5,4,0,6.0,neutral or dissatisfied +62567,17876,Female,Loyal Customer,14,Personal Travel,Eco,425,1,3,1,3,2,1,4,2,2,1,3,2,4,2,11,0.0,neutral or dissatisfied +62568,37762,Male,Loyal Customer,26,Business travel,Eco Plus,1011,4,2,2,2,4,4,3,4,1,2,3,3,3,4,0,1.0,neutral or dissatisfied +62569,125838,Male,Loyal Customer,44,Business travel,Business,3481,5,5,4,5,3,5,4,4,4,5,4,5,4,5,0,0.0,satisfied +62570,107526,Male,Loyal Customer,44,Personal Travel,Eco,838,1,5,1,2,3,1,3,3,3,3,4,4,4,3,19,0.0,neutral or dissatisfied +62571,81108,Male,Loyal Customer,54,Business travel,Business,1700,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +62572,70780,Male,Loyal Customer,39,Business travel,Business,2344,5,5,5,5,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +62573,69072,Female,disloyal Customer,36,Business travel,Eco,989,3,3,3,4,3,3,3,3,5,3,4,3,3,3,206,201.0,neutral or dissatisfied +62574,88603,Male,Loyal Customer,55,Personal Travel,Eco,545,2,1,2,3,5,2,5,5,1,3,2,1,2,5,40,46.0,neutral or dissatisfied +62575,113692,Male,Loyal Customer,18,Personal Travel,Eco,414,2,2,2,3,3,2,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +62576,47149,Female,disloyal Customer,34,Business travel,Eco,679,1,1,1,2,4,1,4,4,5,5,2,4,5,4,6,0.0,neutral or dissatisfied +62577,30415,Male,Loyal Customer,23,Business travel,Eco Plus,641,4,4,4,4,4,4,1,4,1,1,3,2,3,4,0,6.0,neutral or dissatisfied +62578,23180,Male,Loyal Customer,60,Personal Travel,Eco,300,4,5,4,2,2,4,1,2,3,5,1,1,5,2,0,6.0,neutral or dissatisfied +62579,59870,Male,Loyal Customer,43,Business travel,Business,1085,5,5,5,5,3,5,4,2,2,2,2,3,2,4,17,0.0,satisfied +62580,71356,Female,Loyal Customer,51,Business travel,Business,3857,0,0,0,4,5,4,5,1,1,1,1,4,1,5,0,0.0,satisfied +62581,60854,Female,Loyal Customer,34,Personal Travel,Eco,1754,0,4,0,4,2,0,2,2,3,1,4,3,3,2,0,0.0,satisfied +62582,53170,Male,Loyal Customer,28,Business travel,Eco,589,0,0,0,3,5,0,5,5,5,3,4,1,2,5,2,0.0,satisfied +62583,24976,Male,Loyal Customer,60,Business travel,Eco,484,5,3,3,3,5,5,5,5,2,3,4,1,2,5,16,1.0,satisfied +62584,116146,Female,Loyal Customer,54,Personal Travel,Eco,447,3,4,3,3,3,5,5,3,3,3,4,3,3,4,42,43.0,neutral or dissatisfied +62585,98668,Male,Loyal Customer,9,Personal Travel,Eco,834,3,2,3,2,2,3,2,2,1,2,3,2,2,2,0,17.0,neutral or dissatisfied +62586,13566,Male,Loyal Customer,68,Personal Travel,Eco,227,2,4,0,4,5,0,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +62587,128648,Male,Loyal Customer,30,Business travel,Eco Plus,679,4,3,3,3,4,4,4,4,4,3,5,5,4,4,0,0.0,satisfied +62588,100331,Female,Loyal Customer,45,Business travel,Eco,1165,3,4,4,4,5,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +62589,51164,Female,Loyal Customer,14,Personal Travel,Eco,209,2,4,0,3,2,0,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +62590,50635,Female,Loyal Customer,13,Personal Travel,Eco,308,1,1,1,4,3,1,4,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +62591,116169,Female,Loyal Customer,56,Personal Travel,Eco,417,3,2,3,3,2,3,3,1,1,3,1,1,1,4,29,35.0,neutral or dissatisfied +62592,13853,Male,disloyal Customer,29,Business travel,Eco,636,1,2,1,3,1,1,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +62593,46760,Female,Loyal Customer,36,Business travel,Eco Plus,73,1,3,3,3,1,1,1,1,2,3,3,4,3,1,0,11.0,neutral or dissatisfied +62594,50314,Female,Loyal Customer,43,Business travel,Business,2972,2,2,5,2,3,4,3,4,4,4,2,4,4,3,12,25.0,neutral or dissatisfied +62595,114390,Male,Loyal Customer,57,Business travel,Business,1898,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +62596,66418,Female,Loyal Customer,45,Personal Travel,Eco,1562,2,4,2,4,2,5,4,2,2,2,2,4,2,3,19,1.0,neutral or dissatisfied +62597,35981,Female,Loyal Customer,66,Business travel,Business,3205,0,0,0,5,5,1,4,3,3,3,3,5,3,5,0,0.0,satisfied +62598,17910,Male,Loyal Customer,47,Business travel,Business,1863,2,2,2,2,1,1,4,3,3,3,3,2,3,3,0,0.0,satisfied +62599,121545,Male,disloyal Customer,25,Business travel,Business,936,1,5,1,1,3,1,5,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +62600,121181,Female,Loyal Customer,39,Personal Travel,Eco,2521,3,3,2,5,2,3,3,4,3,4,5,3,1,3,6,52.0,neutral or dissatisfied +62601,52332,Male,Loyal Customer,39,Business travel,Business,451,5,5,2,5,1,1,5,5,5,5,5,5,5,1,0,0.0,satisfied +62602,16831,Female,Loyal Customer,33,Personal Travel,Eco,645,2,4,2,3,5,2,1,5,3,3,4,5,5,5,29,12.0,neutral or dissatisfied +62603,92267,Female,Loyal Customer,33,Business travel,Business,1900,2,2,2,2,3,3,5,5,5,5,5,4,5,4,1,0.0,satisfied +62604,8655,Female,Loyal Customer,40,Business travel,Business,1745,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +62605,43588,Female,disloyal Customer,26,Business travel,Eco,228,3,5,3,1,4,3,2,4,1,1,1,2,2,4,0,8.0,neutral or dissatisfied +62606,98765,Female,Loyal Customer,64,Personal Travel,Eco,1814,2,4,3,3,3,4,4,2,2,3,2,5,2,4,10,,neutral or dissatisfied +62607,40693,Female,Loyal Customer,27,Business travel,Business,1717,5,5,5,5,4,4,4,4,5,4,4,1,4,4,0,0.0,satisfied +62608,36550,Male,Loyal Customer,46,Business travel,Eco,1121,5,5,5,5,5,5,5,5,3,2,1,4,3,5,0,0.0,satisfied +62609,65164,Male,Loyal Customer,53,Personal Travel,Eco,551,4,1,4,4,1,4,4,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +62610,32100,Female,disloyal Customer,57,Business travel,Eco,101,4,0,4,1,2,4,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +62611,56985,Male,Loyal Customer,42,Personal Travel,Eco,2565,3,1,3,2,3,1,1,1,3,1,2,1,4,1,8,0.0,neutral or dissatisfied +62612,118100,Female,Loyal Customer,54,Business travel,Business,1999,3,3,3,3,3,4,5,4,4,4,4,4,4,4,11,0.0,satisfied +62613,25471,Female,disloyal Customer,25,Business travel,Eco,516,1,4,1,1,5,1,5,5,1,4,2,4,5,5,0,16.0,neutral or dissatisfied +62614,128886,Male,Loyal Customer,45,Business travel,Business,2454,2,2,2,2,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +62615,104035,Male,Loyal Customer,45,Business travel,Business,3597,1,1,1,1,4,5,5,5,5,5,5,4,5,4,39,35.0,satisfied +62616,110726,Female,Loyal Customer,43,Business travel,Business,2880,1,1,1,1,4,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +62617,69813,Male,Loyal Customer,22,Business travel,Business,2027,1,2,2,2,1,1,1,1,1,5,2,2,2,1,8,0.0,neutral or dissatisfied +62618,109509,Male,Loyal Customer,44,Business travel,Business,2695,5,5,5,5,4,5,4,5,5,4,5,3,5,4,9,15.0,satisfied +62619,74290,Female,Loyal Customer,47,Business travel,Business,2212,5,1,5,5,5,1,3,5,5,5,5,1,5,5,0,0.0,satisfied +62620,15681,Female,Loyal Customer,18,Personal Travel,Eco,617,3,3,3,4,4,3,4,4,4,5,3,4,3,4,0,0.0,neutral or dissatisfied +62621,120832,Male,disloyal Customer,22,Business travel,Eco,992,1,0,0,1,4,0,4,4,5,3,4,3,4,4,21,18.0,neutral or dissatisfied +62622,5175,Female,Loyal Customer,44,Personal Travel,Business,351,1,5,3,4,2,5,5,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +62623,67808,Female,Loyal Customer,56,Business travel,Business,1064,3,2,3,3,4,4,5,4,4,4,4,3,4,1,57,46.0,satisfied +62624,87142,Female,Loyal Customer,40,Business travel,Eco Plus,594,3,1,1,1,3,3,3,3,4,3,3,4,3,3,48,31.0,neutral or dissatisfied +62625,86615,Male,Loyal Customer,46,Business travel,Business,1758,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +62626,15006,Female,Loyal Customer,46,Business travel,Business,3703,3,3,5,3,4,5,5,5,5,5,5,3,5,5,52,86.0,satisfied +62627,69934,Male,Loyal Customer,25,Business travel,Business,2174,2,4,4,4,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +62628,10610,Female,Loyal Customer,58,Business travel,Business,667,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +62629,71876,Female,Loyal Customer,28,Personal Travel,Eco,1723,1,4,0,1,4,0,4,4,5,2,5,5,4,4,20,25.0,neutral or dissatisfied +62630,60934,Female,Loyal Customer,54,Business travel,Business,2689,4,4,2,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +62631,96981,Female,Loyal Customer,54,Business travel,Eco,775,2,5,4,5,2,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +62632,44674,Male,disloyal Customer,56,Business travel,Eco,67,2,0,2,5,1,2,1,1,2,2,3,4,1,1,0,0.0,neutral or dissatisfied +62633,120074,Female,Loyal Customer,60,Business travel,Business,683,2,2,2,2,3,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +62634,78070,Female,Loyal Customer,51,Business travel,Business,2867,3,3,5,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +62635,69300,Female,Loyal Customer,33,Business travel,Business,1096,5,5,5,5,5,4,4,4,4,3,4,4,4,5,28,54.0,satisfied +62636,28466,Male,Loyal Customer,51,Business travel,Eco Plus,2588,4,3,3,3,4,4,4,1,5,2,4,4,3,4,0,2.0,neutral or dissatisfied +62637,22903,Male,Loyal Customer,52,Personal Travel,Eco Plus,147,1,5,1,2,1,1,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +62638,94159,Female,disloyal Customer,32,Business travel,Business,148,4,4,4,3,3,4,5,3,3,3,5,3,5,3,0,13.0,neutral or dissatisfied +62639,102637,Female,Loyal Customer,58,Business travel,Business,3780,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,5.0,satisfied +62640,85529,Male,Loyal Customer,68,Personal Travel,Business,259,4,3,4,4,5,5,1,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +62641,413,Male,Loyal Customer,53,Business travel,Business,1822,2,1,4,4,1,2,3,1,1,1,2,3,1,3,0,0.0,neutral or dissatisfied +62642,40992,Female,Loyal Customer,33,Personal Travel,Eco,984,2,5,2,4,5,2,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +62643,87512,Female,Loyal Customer,8,Personal Travel,Eco,373,4,3,2,4,4,2,4,4,2,3,3,3,4,4,102,94.0,neutral or dissatisfied +62644,65959,Male,Loyal Customer,26,Business travel,Business,1372,1,1,1,1,5,5,5,5,5,5,5,4,5,5,55,76.0,satisfied +62645,126665,Male,Loyal Customer,35,Business travel,Eco Plus,602,1,2,2,2,1,1,1,1,4,5,2,4,2,1,1,0.0,neutral or dissatisfied +62646,1883,Male,Loyal Customer,8,Personal Travel,Eco,931,4,4,4,4,5,4,4,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +62647,110188,Male,Loyal Customer,50,Personal Travel,Eco,869,1,5,1,2,3,1,3,3,4,5,3,1,3,3,0,0.0,neutral or dissatisfied +62648,122953,Female,Loyal Customer,47,Business travel,Business,507,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,1.0,satisfied +62649,41260,Female,Loyal Customer,16,Personal Travel,Eco,852,4,4,4,3,5,4,2,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +62650,33065,Male,Loyal Customer,59,Personal Travel,Eco,163,2,4,0,3,1,0,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +62651,124992,Female,Loyal Customer,52,Business travel,Business,2531,2,2,2,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +62652,28431,Male,Loyal Customer,40,Business travel,Business,2496,1,1,1,1,4,4,4,5,2,5,4,4,5,4,0,0.0,satisfied +62653,16827,Male,Loyal Customer,49,Personal Travel,Eco,645,3,4,3,2,4,3,2,4,4,4,5,4,4,4,61,73.0,neutral or dissatisfied +62654,29300,Male,disloyal Customer,24,Business travel,Eco,859,4,4,4,2,2,4,2,2,3,5,5,2,5,2,0,0.0,satisfied +62655,87350,Female,Loyal Customer,52,Business travel,Business,425,2,2,2,2,2,5,5,4,4,4,4,5,4,3,49,45.0,satisfied +62656,68471,Female,Loyal Customer,39,Business travel,Business,1303,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +62657,56606,Male,Loyal Customer,55,Business travel,Business,2387,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +62658,34433,Male,Loyal Customer,44,Personal Travel,Eco,680,2,5,1,2,3,1,3,3,4,2,5,4,5,3,17,14.0,neutral or dissatisfied +62659,115070,Male,disloyal Customer,25,Business travel,Business,404,3,0,3,4,3,3,3,3,5,5,5,5,5,3,2,0.0,neutral or dissatisfied +62660,2577,Male,Loyal Customer,37,Business travel,Eco,227,4,3,3,3,4,3,4,4,2,3,1,4,1,4,0,0.0,satisfied +62661,5855,Female,Loyal Customer,54,Business travel,Business,1020,3,5,5,5,2,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +62662,122837,Female,Loyal Customer,19,Business travel,Business,226,3,3,3,3,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +62663,72543,Male,disloyal Customer,18,Business travel,Business,1121,0,5,0,3,5,0,5,5,4,2,5,3,5,5,22,0.0,satisfied +62664,8982,Female,Loyal Customer,41,Personal Travel,Eco,725,2,4,2,3,2,2,2,2,5,5,4,2,2,2,128,112.0,neutral or dissatisfied +62665,101628,Female,Loyal Customer,10,Personal Travel,Eco,1139,2,4,2,4,5,2,5,5,3,2,5,3,4,5,0,15.0,neutral or dissatisfied +62666,100723,Female,disloyal Customer,24,Business travel,Eco,328,5,0,4,1,2,4,2,2,5,4,5,5,5,2,31,25.0,satisfied +62667,85010,Female,disloyal Customer,13,Business travel,Eco,1590,3,3,3,3,5,3,5,5,1,1,2,2,4,5,7,14.0,neutral or dissatisfied +62668,37093,Female,Loyal Customer,51,Business travel,Business,1801,3,3,3,3,3,4,3,5,5,5,5,1,5,4,0,0.0,satisfied +62669,95307,Male,Loyal Customer,26,Personal Travel,Eco,293,3,4,3,3,2,3,2,2,5,5,4,5,5,2,2,0.0,neutral or dissatisfied +62670,50479,Female,disloyal Customer,23,Business travel,Business,373,3,1,2,4,4,2,4,4,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +62671,115989,Female,Loyal Customer,26,Personal Travel,Eco,417,1,2,1,4,2,1,2,2,2,5,3,4,3,2,7,8.0,neutral or dissatisfied +62672,48509,Female,Loyal Customer,69,Business travel,Business,2191,3,2,2,2,1,4,3,3,3,2,3,2,3,3,0,4.0,neutral or dissatisfied +62673,86129,Male,Loyal Customer,52,Business travel,Business,356,5,5,5,5,5,4,4,3,3,3,3,3,3,4,21,16.0,satisfied +62674,7669,Female,Loyal Customer,42,Business travel,Business,767,4,4,4,4,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +62675,32521,Male,Loyal Customer,31,Business travel,Eco,216,4,5,5,5,4,4,4,4,3,5,1,4,5,4,0,9.0,satisfied +62676,81563,Female,Loyal Customer,55,Business travel,Eco,936,2,1,1,1,2,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +62677,100999,Male,disloyal Customer,23,Business travel,Eco,867,2,2,2,4,1,2,1,1,4,3,5,3,5,1,78,61.0,neutral or dissatisfied +62678,116019,Female,Loyal Customer,12,Personal Travel,Eco,372,3,4,3,3,2,3,2,2,3,1,3,3,3,2,7,0.0,neutral or dissatisfied +62679,28653,Male,Loyal Customer,34,Personal Travel,Eco,2541,4,5,4,2,2,4,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +62680,85622,Male,Loyal Customer,7,Personal Travel,Eco,317,4,5,4,2,5,4,5,5,2,5,1,3,5,5,0,2.0,satisfied +62681,57897,Male,Loyal Customer,60,Business travel,Business,305,1,1,1,1,4,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +62682,38938,Male,Loyal Customer,22,Personal Travel,Eco,205,2,2,2,2,1,2,1,1,1,5,2,4,2,1,8,12.0,neutral or dissatisfied +62683,43716,Female,Loyal Customer,18,Personal Travel,Eco,489,4,3,3,3,3,3,3,3,4,3,3,3,4,3,0,6.0,neutral or dissatisfied +62684,31071,Male,Loyal Customer,66,Personal Travel,Eco,775,3,5,3,2,2,3,5,2,3,3,4,4,4,2,0,7.0,neutral or dissatisfied +62685,97452,Female,Loyal Customer,59,Business travel,Business,670,3,3,3,3,2,5,5,4,4,4,4,5,4,5,13,16.0,satisfied +62686,119720,Female,Loyal Customer,59,Business travel,Business,1325,3,3,4,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +62687,36748,Female,Loyal Customer,34,Business travel,Business,2611,2,2,2,2,2,2,2,1,2,4,4,2,3,2,2,10.0,neutral or dissatisfied +62688,121260,Female,Loyal Customer,15,Personal Travel,Eco,2075,4,5,5,3,4,5,4,4,5,1,4,3,1,4,4,33.0,satisfied +62689,117728,Female,Loyal Customer,41,Business travel,Business,3847,2,2,2,2,4,4,5,5,5,5,5,5,5,3,5,0.0,satisfied +62690,68498,Female,Loyal Customer,19,Personal Travel,Eco,1067,1,5,1,4,5,1,5,5,5,2,4,3,5,5,11,9.0,neutral or dissatisfied +62691,60104,Female,Loyal Customer,60,Business travel,Business,2247,4,4,4,4,2,2,2,4,4,4,4,2,3,2,190,200.0,satisfied +62692,48573,Female,Loyal Customer,17,Personal Travel,Eco,819,2,4,2,2,3,2,3,3,3,4,1,1,2,3,94,99.0,neutral or dissatisfied +62693,2710,Female,Loyal Customer,7,Personal Travel,Eco,562,2,2,2,4,5,2,5,5,1,4,3,1,3,5,12,9.0,neutral or dissatisfied +62694,21298,Female,disloyal Customer,26,Business travel,Eco,692,2,2,2,3,1,2,1,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +62695,14353,Female,Loyal Customer,53,Business travel,Eco Plus,429,5,2,2,2,5,3,3,5,5,5,5,1,5,3,6,19.0,satisfied +62696,10851,Male,Loyal Customer,32,Business travel,Business,1904,2,1,1,1,2,2,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +62697,19402,Female,Loyal Customer,49,Business travel,Business,261,3,3,3,3,4,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +62698,90306,Male,Loyal Customer,30,Personal Travel,Eco,879,3,2,3,2,2,3,4,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +62699,94108,Female,Loyal Customer,62,Personal Travel,Business,341,2,5,2,3,3,5,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +62700,68814,Male,Loyal Customer,49,Personal Travel,Eco,861,4,4,4,4,5,4,5,5,3,2,5,4,4,5,8,0.0,neutral or dissatisfied +62701,43322,Female,Loyal Customer,49,Business travel,Business,2909,3,5,4,5,2,2,3,3,3,3,3,4,3,3,0,2.0,neutral or dissatisfied +62702,88756,Male,Loyal Customer,39,Business travel,Business,406,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +62703,11662,Female,Loyal Customer,14,Personal Travel,Eco Plus,878,5,3,5,3,3,5,3,3,2,4,2,3,3,3,5,0.0,satisfied +62704,121378,Female,Loyal Customer,36,Business travel,Business,2279,3,3,3,3,3,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +62705,47789,Male,Loyal Customer,31,Business travel,Business,834,1,5,5,5,1,1,1,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +62706,26132,Male,Loyal Customer,43,Business travel,Eco,406,5,2,2,2,5,5,5,5,1,4,4,1,1,5,2,0.0,satisfied +62707,43873,Male,Loyal Customer,59,Business travel,Business,3147,2,2,5,2,2,4,2,4,4,4,5,1,4,1,10,6.0,satisfied +62708,44886,Female,Loyal Customer,52,Personal Travel,Eco,557,3,3,3,4,1,3,3,2,2,3,5,2,2,2,12,4.0,neutral or dissatisfied +62709,79511,Female,Loyal Customer,45,Business travel,Business,2222,4,4,4,4,5,4,4,5,5,5,5,5,5,3,12,6.0,satisfied +62710,62825,Female,Loyal Customer,62,Personal Travel,Eco,2367,1,5,1,3,1,2,2,1,1,5,1,2,3,2,195,170.0,neutral or dissatisfied +62711,39503,Male,Loyal Customer,41,Business travel,Eco,1068,5,2,3,2,5,5,5,5,2,3,4,5,3,5,10,2.0,satisfied +62712,55345,Male,Loyal Customer,50,Business travel,Business,3376,3,3,3,3,4,4,5,5,5,5,5,4,5,4,4,1.0,satisfied +62713,25702,Male,Loyal Customer,52,Business travel,Eco,432,5,4,4,4,5,5,5,5,5,2,3,3,1,5,1,0.0,satisfied +62714,42822,Male,Loyal Customer,50,Business travel,Eco Plus,677,2,2,2,2,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +62715,62452,Female,Loyal Customer,40,Business travel,Business,1723,5,5,5,5,4,4,5,5,5,4,5,5,5,5,1,5.0,satisfied +62716,106607,Female,Loyal Customer,51,Business travel,Eco,189,3,4,4,4,5,4,4,3,3,3,3,4,3,2,0,9.0,neutral or dissatisfied +62717,115808,Female,Loyal Customer,50,Business travel,Eco,480,3,2,4,4,5,4,5,3,3,3,3,4,3,4,13,0.0,satisfied +62718,14409,Male,disloyal Customer,30,Business travel,Eco,693,3,3,3,3,4,3,4,4,3,1,4,3,3,4,0,0.0,neutral or dissatisfied +62719,47014,Female,Loyal Customer,39,Personal Travel,Eco,616,2,5,2,4,3,2,5,3,1,2,1,1,5,3,1,1.0,neutral or dissatisfied +62720,74956,Male,Loyal Customer,40,Business travel,Eco,2586,5,3,3,3,5,5,5,5,3,3,4,3,1,5,7,0.0,satisfied +62721,22945,Male,Loyal Customer,58,Business travel,Business,2049,3,3,3,3,1,2,3,4,4,4,4,3,4,4,0,0.0,satisfied +62722,83756,Male,Loyal Customer,48,Personal Travel,Eco,1183,1,5,1,1,1,1,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +62723,30433,Female,Loyal Customer,52,Business travel,Business,2088,1,1,1,1,4,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +62724,70063,Female,Loyal Customer,59,Business travel,Business,3497,4,4,4,4,2,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +62725,69220,Male,Loyal Customer,20,Business travel,Business,733,3,3,3,3,5,5,5,5,3,3,4,3,4,5,0,0.0,satisfied +62726,6941,Male,Loyal Customer,42,Business travel,Business,3228,5,5,5,5,4,5,5,5,5,4,5,3,5,4,57,51.0,satisfied +62727,91328,Female,Loyal Customer,37,Business travel,Eco Plus,271,3,5,1,1,3,3,3,4,5,4,4,3,3,3,222,220.0,neutral or dissatisfied +62728,61675,Female,Loyal Customer,45,Business travel,Business,1346,1,2,2,2,5,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +62729,114241,Male,Loyal Customer,39,Business travel,Business,2006,4,4,4,4,3,4,4,4,4,4,4,3,4,3,2,2.0,satisfied +62730,16027,Male,Loyal Customer,58,Personal Travel,Eco,722,2,4,2,2,2,2,2,2,5,1,1,2,1,2,108,103.0,neutral or dissatisfied +62731,48743,Male,Loyal Customer,42,Business travel,Business,421,5,5,2,5,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +62732,66995,Male,Loyal Customer,25,Business travel,Business,1119,2,2,2,2,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +62733,126551,Male,Loyal Customer,70,Personal Travel,Eco,644,4,3,4,3,5,4,3,5,2,1,4,2,4,5,4,0.0,satisfied +62734,64408,Male,Loyal Customer,52,Business travel,Business,1158,4,4,4,4,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +62735,83429,Female,Loyal Customer,7,Personal Travel,Eco,632,2,5,2,3,4,2,4,4,4,5,4,3,4,4,0,23.0,neutral or dissatisfied +62736,75615,Male,Loyal Customer,22,Personal Travel,Eco,337,0,5,0,1,5,0,5,5,5,2,4,5,5,5,0,0.0,satisfied +62737,58115,Female,Loyal Customer,25,Personal Travel,Eco,612,2,5,2,5,5,2,5,5,4,2,5,5,5,5,4,0.0,neutral or dissatisfied +62738,47132,Female,Loyal Customer,46,Personal Travel,Business,965,2,4,2,3,3,4,4,3,3,2,3,3,3,4,12,2.0,neutral or dissatisfied +62739,92453,Male,Loyal Customer,45,Business travel,Business,1947,1,1,1,1,5,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +62740,70399,Female,Loyal Customer,37,Business travel,Business,2532,2,2,2,2,4,1,1,3,3,4,3,5,3,4,0,0.0,satisfied +62741,54967,Male,disloyal Customer,25,Business travel,Business,1379,0,5,0,3,4,0,4,4,3,4,4,5,4,4,0,0.0,satisfied +62742,29895,Female,Loyal Customer,44,Business travel,Business,1511,1,4,4,4,1,4,4,4,4,4,1,2,4,3,0,0.0,neutral or dissatisfied +62743,33682,Female,Loyal Customer,39,Business travel,Eco,759,4,3,3,3,4,4,4,4,1,3,1,4,1,4,0,11.0,satisfied +62744,11436,Male,Loyal Customer,56,Business travel,Business,1599,5,5,5,5,4,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +62745,59783,Male,Loyal Customer,45,Personal Travel,Eco,1062,3,5,3,3,1,3,5,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +62746,127975,Female,Loyal Customer,44,Business travel,Business,1149,3,3,5,3,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +62747,54746,Male,Loyal Customer,13,Personal Travel,Eco,854,2,1,2,4,4,2,4,4,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +62748,2737,Female,Loyal Customer,53,Business travel,Business,695,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,14.0,satisfied +62749,63076,Male,Loyal Customer,16,Personal Travel,Eco,967,3,2,3,4,1,3,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +62750,3321,Female,Loyal Customer,52,Business travel,Business,315,5,5,3,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +62751,56341,Male,Loyal Customer,47,Business travel,Eco,200,3,3,3,3,3,3,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +62752,25552,Male,Loyal Customer,31,Personal Travel,Eco Plus,547,4,0,4,2,1,4,4,1,5,4,2,1,3,1,0,0.0,neutral or dissatisfied +62753,6599,Male,Loyal Customer,27,Personal Travel,Eco,607,2,4,2,3,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +62754,20456,Female,Loyal Customer,35,Business travel,Business,2525,4,1,1,1,1,3,3,2,2,2,4,1,2,4,0,0.0,neutral or dissatisfied +62755,28490,Male,Loyal Customer,22,Personal Travel,Eco Plus,1739,2,5,2,3,5,2,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +62756,97816,Male,disloyal Customer,28,Business travel,Business,395,4,4,4,5,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +62757,70878,Female,Loyal Customer,52,Business travel,Business,2944,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +62758,15983,Female,Loyal Customer,34,Business travel,Business,1799,4,4,4,4,5,5,1,5,5,4,5,2,5,4,0,0.0,satisfied +62759,37857,Male,Loyal Customer,44,Business travel,Business,3129,3,3,3,3,3,5,4,2,2,2,2,1,2,3,1,36.0,satisfied +62760,90290,Male,Loyal Customer,36,Business travel,Eco,373,4,1,1,1,4,4,4,4,1,4,2,5,5,4,0,0.0,satisfied +62761,119813,Male,Loyal Customer,48,Business travel,Business,936,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +62762,127758,Male,Loyal Customer,16,Personal Travel,Eco,255,3,3,3,3,2,3,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +62763,124326,Female,Loyal Customer,40,Personal Travel,Eco,255,4,3,4,4,3,4,1,3,3,3,4,3,4,3,0,5.0,satisfied +62764,62756,Female,Loyal Customer,24,Business travel,Business,2556,2,3,3,3,2,2,2,4,5,4,3,2,1,2,1,8.0,neutral or dissatisfied +62765,64048,Male,Loyal Customer,24,Business travel,Business,3516,1,1,1,1,2,2,2,2,5,5,4,4,5,2,0,6.0,satisfied +62766,69452,Female,Loyal Customer,16,Personal Travel,Eco,1096,1,0,1,2,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +62767,121553,Male,disloyal Customer,30,Business travel,Business,912,4,5,5,1,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +62768,98031,Female,Loyal Customer,44,Personal Travel,Eco,1014,2,5,2,2,5,3,1,5,5,2,5,5,5,2,117,119.0,neutral or dissatisfied +62769,51038,Male,Loyal Customer,10,Personal Travel,Eco,86,4,4,0,4,5,0,5,5,1,2,1,2,2,5,0,2.0,satisfied +62770,66388,Male,Loyal Customer,58,Business travel,Business,1562,2,2,2,2,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +62771,127551,Female,Loyal Customer,36,Personal Travel,Eco,1009,2,2,2,4,1,2,1,1,3,3,3,1,3,1,60,55.0,neutral or dissatisfied +62772,115147,Male,Loyal Customer,41,Business travel,Business,3233,3,3,3,3,3,4,5,5,5,5,5,4,5,5,12,5.0,satisfied +62773,22446,Male,Loyal Customer,14,Personal Travel,Eco,143,2,4,0,3,3,0,5,3,2,3,4,3,4,3,23,26.0,neutral or dissatisfied +62774,80251,Male,Loyal Customer,50,Business travel,Business,1809,5,5,5,5,3,4,4,3,3,3,3,3,3,4,5,0.0,satisfied +62775,101038,Female,disloyal Customer,26,Business travel,Business,368,2,3,3,4,1,3,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +62776,98398,Male,Loyal Customer,42,Business travel,Business,675,5,5,5,5,3,4,4,4,4,4,4,5,4,3,74,62.0,satisfied +62777,72185,Male,disloyal Customer,51,Business travel,Eco,594,3,1,3,3,2,3,2,2,4,1,3,2,4,2,0,0.0,neutral or dissatisfied +62778,5462,Female,Loyal Customer,16,Personal Travel,Eco,265,2,4,2,3,4,2,4,4,2,5,3,3,3,4,0,0.0,neutral or dissatisfied +62779,24918,Female,Loyal Customer,32,Business travel,Business,1867,1,5,5,5,1,1,1,1,1,1,3,3,3,1,40,34.0,neutral or dissatisfied +62780,36165,Female,Loyal Customer,63,Business travel,Business,1674,4,3,3,3,1,1,2,4,4,4,4,1,4,3,0,8.0,neutral or dissatisfied +62781,38629,Female,Loyal Customer,41,Business travel,Business,2704,4,4,2,4,5,4,2,4,4,4,4,4,4,3,29,9.0,satisfied +62782,75552,Female,Loyal Customer,32,Business travel,Business,2407,1,1,1,1,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +62783,85961,Female,Loyal Customer,58,Business travel,Business,3955,2,2,2,2,5,5,5,3,5,4,5,5,4,5,205,206.0,satisfied +62784,50742,Female,Loyal Customer,21,Personal Travel,Eco,337,2,5,2,4,3,2,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +62785,28444,Male,Loyal Customer,65,Personal Travel,Eco,2496,2,2,2,4,2,2,2,3,4,4,3,2,2,2,0,0.0,neutral or dissatisfied +62786,110874,Male,Loyal Customer,19,Business travel,Business,581,1,1,1,1,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +62787,128946,Female,disloyal Customer,38,Business travel,Business,414,2,2,2,4,1,2,1,1,5,3,5,4,5,1,0,4.0,neutral or dissatisfied +62788,50569,Male,Loyal Customer,53,Personal Travel,Eco,372,2,0,2,2,3,2,3,3,5,1,4,2,4,3,42,38.0,neutral or dissatisfied +62789,80661,Female,Loyal Customer,59,Business travel,Business,821,2,2,2,2,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +62790,95071,Female,Loyal Customer,35,Personal Travel,Eco,192,4,3,4,4,4,4,4,4,3,1,4,3,4,4,0,4.0,neutral or dissatisfied +62791,5102,Female,Loyal Customer,37,Personal Travel,Eco,122,1,4,1,2,3,1,3,3,5,1,2,1,5,3,0,0.0,neutral or dissatisfied +62792,32012,Male,disloyal Customer,38,Business travel,Eco,163,4,0,4,3,1,4,1,1,5,4,2,3,2,1,0,0.0,neutral or dissatisfied +62793,27109,Female,Loyal Customer,55,Business travel,Eco Plus,1721,1,3,3,3,1,1,1,4,5,2,3,1,2,1,204,196.0,neutral or dissatisfied +62794,4828,Male,Loyal Customer,41,Business travel,Business,3206,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +62795,92257,Male,Loyal Customer,49,Personal Travel,Eco,1670,1,4,1,2,3,1,3,3,2,3,5,2,3,3,0,0.0,neutral or dissatisfied +62796,23218,Female,Loyal Customer,18,Personal Travel,Eco,326,2,1,2,4,2,4,4,2,1,4,3,4,1,4,306,306.0,neutral or dissatisfied +62797,8513,Male,Loyal Customer,51,Business travel,Business,862,3,4,4,4,3,4,3,3,3,3,3,4,3,4,25,10.0,neutral or dissatisfied +62798,14700,Male,Loyal Customer,54,Business travel,Eco,424,5,3,3,3,5,5,5,5,5,1,1,1,3,5,0,0.0,satisfied +62799,47550,Male,disloyal Customer,27,Business travel,Eco Plus,541,3,3,3,3,3,3,3,3,1,5,1,5,4,3,9,10.0,neutral or dissatisfied +62800,89438,Female,Loyal Customer,12,Personal Travel,Eco,151,2,4,2,3,3,2,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +62801,98236,Female,Loyal Customer,48,Business travel,Business,1986,2,2,4,2,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +62802,22692,Male,Loyal Customer,45,Business travel,Business,589,1,3,3,3,2,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +62803,119827,Male,Loyal Customer,53,Business travel,Business,936,3,3,3,3,5,4,5,5,5,5,5,3,5,3,4,3.0,satisfied +62804,67798,Female,disloyal Customer,42,Business travel,Business,1464,2,3,3,5,5,2,4,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +62805,67854,Male,Loyal Customer,67,Personal Travel,Eco,1188,3,3,3,1,5,3,1,5,2,1,5,1,4,5,14,6.0,neutral or dissatisfied +62806,11513,Female,Loyal Customer,36,Personal Travel,Eco Plus,429,3,3,5,3,4,5,4,4,5,5,1,5,3,4,0,0.0,neutral or dissatisfied +62807,66123,Male,disloyal Customer,25,Business travel,Business,583,2,0,2,1,2,2,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +62808,16639,Male,Loyal Customer,23,Business travel,Business,3905,4,4,4,4,5,5,5,5,1,4,3,4,5,5,7,0.0,satisfied +62809,64582,Female,Loyal Customer,41,Business travel,Business,2729,1,1,3,1,3,4,4,4,4,4,4,4,4,5,22,9.0,satisfied +62810,80804,Female,disloyal Customer,26,Business travel,Business,692,2,4,2,2,4,2,2,4,3,4,5,5,5,4,11,20.0,neutral or dissatisfied +62811,49784,Male,disloyal Customer,16,Business travel,Eco,86,1,2,1,4,5,1,1,5,2,4,3,3,3,5,83,73.0,neutral or dissatisfied +62812,42521,Female,Loyal Customer,43,Personal Travel,Eco,1384,3,5,3,3,5,3,4,1,1,3,1,4,1,4,38,79.0,neutral or dissatisfied +62813,118403,Female,Loyal Customer,26,Personal Travel,Business,368,2,5,2,4,1,2,1,1,5,2,1,2,3,1,0,0.0,neutral or dissatisfied +62814,129700,Male,Loyal Customer,40,Business travel,Business,337,5,5,5,5,3,5,4,4,4,4,4,5,4,3,12,0.0,satisfied +62815,95691,Female,Loyal Customer,49,Business travel,Business,237,2,1,2,2,4,3,3,2,2,2,2,2,2,2,3,8.0,neutral or dissatisfied +62816,105036,Female,Loyal Customer,60,Business travel,Business,361,1,1,1,1,1,5,1,5,5,5,5,5,5,5,7,5.0,satisfied +62817,76750,Female,Loyal Customer,41,Personal Travel,Eco,205,5,4,0,4,3,0,3,3,3,3,1,3,3,3,5,0.0,satisfied +62818,45471,Female,Loyal Customer,53,Business travel,Business,674,3,3,3,3,3,3,3,4,4,4,4,2,4,2,0,0.0,satisfied +62819,125782,Male,Loyal Customer,39,Business travel,Business,992,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +62820,17847,Male,Loyal Customer,57,Business travel,Business,2865,2,2,1,2,5,5,4,5,5,5,5,3,5,5,25,16.0,satisfied +62821,2272,Male,Loyal Customer,29,Business travel,Business,2561,4,4,4,4,4,4,4,4,3,2,4,4,5,4,50,45.0,satisfied +62822,113895,Male,disloyal Customer,42,Business travel,Eco,2329,2,2,2,3,2,2,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +62823,128040,Female,Loyal Customer,7,Personal Travel,Eco,1440,4,4,4,2,5,4,5,5,3,4,4,4,5,5,2,12.0,neutral or dissatisfied +62824,103818,Female,Loyal Customer,48,Business travel,Business,2422,2,2,2,2,2,4,5,4,4,4,4,5,4,3,5,11.0,satisfied +62825,91332,Male,Loyal Customer,64,Personal Travel,Eco Plus,581,3,4,3,3,5,3,2,5,4,2,4,3,4,5,71,60.0,neutral or dissatisfied +62826,73564,Male,Loyal Customer,47,Business travel,Business,2583,0,5,0,2,3,5,5,4,4,5,5,5,4,4,0,0.0,satisfied +62827,28403,Female,disloyal Customer,39,Business travel,Eco,209,2,3,2,1,3,2,3,3,2,3,2,5,3,3,0,0.0,neutral or dissatisfied +62828,46520,Male,Loyal Customer,52,Business travel,Eco,73,2,5,5,5,2,2,2,2,4,3,3,1,1,2,0,0.0,satisfied +62829,3200,Male,Loyal Customer,68,Personal Travel,Eco,585,2,5,3,2,5,3,5,5,3,4,4,3,5,5,10,18.0,neutral or dissatisfied +62830,46636,Male,disloyal Customer,25,Business travel,Eco,125,2,2,2,3,3,2,3,3,2,3,3,2,2,3,45,61.0,neutral or dissatisfied +62831,75894,Male,Loyal Customer,48,Business travel,Business,597,3,3,3,3,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +62832,114048,Female,Loyal Customer,24,Personal Travel,Eco,512,2,5,2,2,1,2,1,1,5,4,4,3,5,1,12,3.0,neutral or dissatisfied +62833,120679,Female,Loyal Customer,62,Business travel,Business,3673,4,4,3,4,3,5,1,4,4,4,4,2,4,3,0,0.0,satisfied +62834,38257,Female,Loyal Customer,33,Business travel,Eco,1173,4,5,4,5,4,4,4,4,3,4,2,2,5,4,0,0.0,satisfied +62835,110007,Male,Loyal Customer,56,Business travel,Business,2444,5,5,5,5,5,5,5,4,3,5,4,5,4,5,165,133.0,satisfied +62836,63973,Male,Loyal Customer,43,Business travel,Eco Plus,1192,2,1,1,1,2,2,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +62837,36141,Female,Loyal Customer,17,Personal Travel,Eco,1698,2,3,2,3,1,2,1,1,2,4,3,3,4,1,8,6.0,neutral or dissatisfied +62838,119433,Female,Loyal Customer,14,Personal Travel,Eco,399,2,4,2,2,5,2,5,5,4,5,5,2,2,5,0,0.0,neutral or dissatisfied +62839,35623,Female,Loyal Customer,52,Personal Travel,Eco Plus,1056,3,4,3,2,3,2,4,3,3,3,3,2,3,2,76,92.0,neutral or dissatisfied +62840,119806,Male,Loyal Customer,55,Business travel,Business,936,3,3,3,3,5,5,4,5,5,5,5,5,5,3,0,3.0,satisfied +62841,68565,Female,Loyal Customer,46,Business travel,Business,1616,4,4,5,4,5,3,5,5,5,5,5,5,5,4,7,0.0,satisfied +62842,95467,Male,Loyal Customer,32,Business travel,Eco Plus,528,2,5,5,5,2,2,2,2,1,3,2,2,2,2,74,65.0,neutral or dissatisfied +62843,12482,Male,Loyal Customer,12,Personal Travel,Eco,201,3,1,0,4,3,0,3,3,2,3,4,1,3,3,23,14.0,neutral or dissatisfied +62844,29817,Female,disloyal Customer,27,Business travel,Eco,261,2,0,2,2,3,2,2,3,4,2,2,5,1,3,0,0.0,neutral or dissatisfied +62845,109423,Female,disloyal Customer,13,Business travel,Business,861,3,2,3,3,3,1,1,1,1,3,4,1,2,1,378,424.0,neutral or dissatisfied +62846,126017,Male,Loyal Customer,37,Business travel,Business,468,1,3,3,3,2,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +62847,46585,Male,Loyal Customer,41,Business travel,Eco,125,2,3,4,3,2,2,2,2,1,3,3,4,3,2,30,27.0,neutral or dissatisfied +62848,81127,Male,Loyal Customer,50,Personal Travel,Eco,991,4,4,4,5,1,4,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +62849,94293,Female,disloyal Customer,48,Business travel,Business,239,1,0,0,1,3,1,1,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +62850,15414,Male,disloyal Customer,36,Business travel,Eco,399,2,3,2,4,4,2,1,4,1,4,3,2,3,4,0,0.0,neutral or dissatisfied +62851,5052,Male,Loyal Customer,50,Business travel,Business,235,5,5,5,5,3,5,4,4,4,4,4,4,4,3,27,40.0,satisfied +62852,20264,Female,disloyal Customer,30,Business travel,Eco,224,2,5,2,4,4,2,4,4,5,2,3,2,4,4,2,0.0,neutral or dissatisfied +62853,67377,Female,Loyal Customer,60,Business travel,Business,592,4,4,4,4,2,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +62854,14579,Female,Loyal Customer,54,Business travel,Business,2818,3,5,5,5,3,3,3,3,3,3,3,1,3,4,0,13.0,neutral or dissatisfied +62855,19337,Male,Loyal Customer,21,Personal Travel,Eco,694,1,4,1,4,2,1,2,2,4,4,5,3,5,2,88,78.0,neutral or dissatisfied +62856,92351,Female,Loyal Customer,16,Personal Travel,Eco,2486,4,5,4,4,5,4,5,5,3,4,4,4,5,5,36,16.0,neutral or dissatisfied +62857,47100,Male,Loyal Customer,53,Personal Travel,Eco,438,2,2,2,3,3,2,3,3,3,4,2,1,3,3,0,0.0,neutral or dissatisfied +62858,120804,Male,disloyal Customer,33,Business travel,Business,666,3,3,3,4,2,3,2,2,3,3,4,4,4,2,0,1.0,neutral or dissatisfied +62859,105986,Male,Loyal Customer,25,Personal Travel,Eco Plus,2295,3,2,3,4,5,3,5,5,4,3,3,4,4,5,16,0.0,neutral or dissatisfied +62860,124381,Female,Loyal Customer,55,Personal Travel,Eco,808,2,4,2,3,1,3,3,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +62861,93365,Female,Loyal Customer,40,Personal Travel,Eco,836,2,5,2,4,3,2,3,3,3,3,4,3,4,3,1,0.0,neutral or dissatisfied +62862,27393,Male,Loyal Customer,64,Business travel,Business,3544,4,4,4,4,1,1,1,5,5,5,5,5,5,2,0,0.0,satisfied +62863,93023,Male,Loyal Customer,39,Personal Travel,Eco,1524,2,5,2,3,1,2,1,1,3,2,3,4,4,1,29,48.0,neutral or dissatisfied +62864,118470,Female,Loyal Customer,51,Business travel,Business,2001,1,1,1,1,5,4,4,3,3,4,3,4,3,3,2,12.0,satisfied +62865,30906,Female,Loyal Customer,46,Business travel,Eco,896,5,3,5,5,5,5,2,5,5,5,5,4,5,5,7,14.0,satisfied +62866,118636,Female,Loyal Customer,52,Business travel,Business,368,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,2.0,satisfied +62867,51597,Female,disloyal Customer,26,Business travel,Eco,751,3,3,3,3,3,3,5,3,5,1,1,2,2,3,0,0.0,neutral or dissatisfied +62868,60417,Female,Loyal Customer,48,Business travel,Business,1998,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +62869,89385,Female,Loyal Customer,48,Business travel,Business,3407,5,5,4,5,5,5,5,3,3,4,4,3,3,3,0,0.0,satisfied +62870,32764,Male,disloyal Customer,38,Business travel,Eco,101,4,4,4,2,2,4,5,2,1,4,5,1,4,2,0,4.0,neutral or dissatisfied +62871,122123,Female,disloyal Customer,17,Business travel,Eco,130,3,4,3,4,3,3,3,3,1,5,3,1,4,3,5,0.0,neutral or dissatisfied +62872,20687,Female,disloyal Customer,40,Business travel,Business,584,4,4,4,3,4,4,4,4,1,1,1,3,4,4,0,0.0,satisfied +62873,33259,Female,Loyal Customer,36,Personal Travel,Eco Plus,216,1,0,1,4,4,1,4,4,3,1,1,2,1,4,0,0.0,neutral or dissatisfied +62874,37711,Female,Loyal Customer,57,Personal Travel,Eco,1047,1,4,1,1,2,4,5,4,4,1,4,4,4,5,11,0.0,neutral or dissatisfied +62875,103343,Female,Loyal Customer,65,Personal Travel,Eco,1139,4,5,3,2,2,5,4,1,1,3,1,4,1,5,7,0.0,neutral or dissatisfied +62876,94929,Male,Loyal Customer,40,Business travel,Eco,319,5,1,5,1,5,5,5,5,4,1,5,2,2,5,0,0.0,satisfied +62877,33335,Female,disloyal Customer,34,Business travel,Eco,2556,1,1,1,4,2,1,2,2,5,1,5,1,3,2,15,0.0,neutral or dissatisfied +62878,53081,Female,Loyal Customer,31,Business travel,Business,1571,2,2,2,2,5,5,5,5,3,3,4,4,4,5,119,96.0,satisfied +62879,54072,Female,Loyal Customer,52,Business travel,Business,1416,1,1,1,1,3,3,4,1,1,1,1,2,1,3,70,65.0,neutral or dissatisfied +62880,52745,Male,Loyal Customer,39,Business travel,Eco,806,5,2,2,2,5,5,5,5,3,1,5,2,1,5,93,77.0,satisfied +62881,113662,Female,Loyal Customer,20,Personal Travel,Eco,258,3,1,3,4,5,3,5,5,2,5,3,4,4,5,5,4.0,neutral or dissatisfied +62882,55562,Male,Loyal Customer,10,Business travel,Eco Plus,550,1,4,4,4,1,1,1,1,2,1,3,1,3,1,12,10.0,neutral or dissatisfied +62883,67922,Female,Loyal Customer,39,Personal Travel,Eco,1171,3,5,3,3,4,3,4,4,5,5,3,4,5,4,16,14.0,neutral or dissatisfied +62884,99147,Male,Loyal Customer,55,Personal Travel,Eco Plus,419,3,4,3,3,5,3,5,5,5,1,3,2,5,5,0,0.0,neutral or dissatisfied +62885,31042,Male,Loyal Customer,30,Business travel,Business,2696,3,4,4,4,3,3,3,3,1,1,4,1,3,3,0,6.0,neutral or dissatisfied +62886,121564,Female,Loyal Customer,61,Business travel,Eco,1095,3,2,2,2,1,3,4,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +62887,87773,Male,Loyal Customer,39,Business travel,Business,3045,2,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +62888,89576,Male,Loyal Customer,31,Business travel,Business,2413,5,5,5,5,3,4,3,3,5,2,4,5,5,3,0,0.0,satisfied +62889,44959,Female,disloyal Customer,39,Business travel,Business,349,4,4,4,2,3,4,3,3,2,5,3,1,1,3,0,0.0,neutral or dissatisfied +62890,117983,Male,Loyal Customer,35,Personal Travel,Eco,601,1,1,1,3,5,1,5,5,4,4,3,2,3,5,17,3.0,neutral or dissatisfied +62891,81805,Female,disloyal Customer,26,Business travel,Eco,1310,2,2,2,3,1,2,1,1,2,1,3,3,3,1,0,34.0,neutral or dissatisfied +62892,36523,Male,Loyal Customer,19,Business travel,Business,1197,4,4,4,4,3,4,3,3,1,3,3,4,1,3,0,7.0,satisfied +62893,89520,Male,Loyal Customer,53,Personal Travel,Business,1096,4,2,4,4,4,4,4,2,2,4,2,1,2,3,1,0.0,neutral or dissatisfied +62894,106627,Female,disloyal Customer,40,Business travel,Business,306,4,4,4,3,4,4,5,4,4,2,5,5,4,4,0,0.0,satisfied +62895,2480,Male,Loyal Customer,59,Business travel,Business,1379,3,1,1,1,4,3,3,3,3,3,3,2,3,1,1,0.0,neutral or dissatisfied +62896,115287,Female,disloyal Customer,62,Business travel,Business,446,3,3,3,1,2,3,1,2,4,2,5,3,4,2,61,55.0,neutral or dissatisfied +62897,43433,Male,Loyal Customer,68,Personal Travel,Eco,748,1,4,1,3,2,1,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +62898,75737,Female,disloyal Customer,25,Business travel,Eco,868,2,2,2,3,4,2,4,4,2,4,2,1,3,4,2,8.0,neutral or dissatisfied +62899,85300,Male,Loyal Customer,15,Personal Travel,Eco,813,3,0,3,2,4,3,3,4,5,2,4,1,5,4,1,0.0,neutral or dissatisfied +62900,62519,Male,Loyal Customer,25,Business travel,Business,1846,2,5,5,5,2,2,2,2,2,5,4,4,3,2,0,27.0,neutral or dissatisfied +62901,10190,Male,disloyal Customer,35,Business travel,Business,309,2,2,2,2,5,2,5,5,5,5,5,4,4,5,8,4.0,neutral or dissatisfied +62902,51793,Female,Loyal Customer,24,Personal Travel,Eco,370,2,3,2,4,5,2,5,5,3,2,4,3,4,5,31,26.0,neutral or dissatisfied +62903,55159,Female,Loyal Customer,8,Personal Travel,Eco,1635,3,5,3,5,1,3,1,1,4,4,5,5,5,1,2,11.0,neutral or dissatisfied +62904,23543,Male,Loyal Customer,27,Personal Travel,Eco,423,1,3,1,3,4,1,4,4,4,5,4,4,3,4,5,40.0,neutral or dissatisfied +62905,1646,Male,Loyal Customer,55,Business travel,Business,1589,2,2,2,2,5,5,4,5,5,4,5,3,5,5,5,0.0,satisfied +62906,94061,Female,Loyal Customer,56,Business travel,Business,1841,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +62907,63474,Male,Loyal Customer,19,Personal Travel,Eco Plus,337,2,4,2,2,2,2,2,2,4,4,1,2,5,2,5,0.0,neutral or dissatisfied +62908,40802,Female,disloyal Customer,26,Business travel,Eco,532,2,3,2,3,3,2,3,3,5,2,3,2,3,3,0,0.0,neutral or dissatisfied +62909,12932,Male,Loyal Customer,67,Personal Travel,Eco,563,3,4,3,3,1,3,1,1,5,5,4,4,4,1,2,4.0,neutral or dissatisfied +62910,8993,Female,Loyal Customer,49,Business travel,Business,297,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +62911,68456,Female,Loyal Customer,30,Business travel,Business,2473,4,4,4,4,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +62912,55568,Female,Loyal Customer,47,Business travel,Eco,395,5,2,5,5,1,1,5,5,5,5,5,1,5,5,0,0.0,satisfied +62913,59973,Female,Loyal Customer,51,Business travel,Business,2002,5,5,5,5,3,2,4,5,5,4,5,3,5,1,0,0.0,satisfied +62914,39000,Male,Loyal Customer,40,Business travel,Business,3452,5,5,5,5,1,5,1,5,5,5,5,5,5,4,0,0.0,satisfied +62915,22649,Female,disloyal Customer,48,Business travel,Eco Plus,300,1,1,1,5,4,1,3,4,5,3,3,1,1,4,15,0.0,neutral or dissatisfied +62916,1922,Female,Loyal Customer,41,Business travel,Business,3009,0,0,0,3,3,4,4,5,5,5,5,3,5,3,5,6.0,satisfied +62917,96553,Male,Loyal Customer,17,Business travel,Eco Plus,302,2,5,5,5,2,2,3,2,1,1,3,3,3,2,21,4.0,neutral or dissatisfied +62918,80314,Female,disloyal Customer,55,Business travel,Eco,346,2,2,2,3,5,2,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +62919,21303,Male,Loyal Customer,18,Personal Travel,Eco,692,1,5,1,3,4,1,2,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +62920,8270,Female,Loyal Customer,56,Personal Travel,Eco,125,1,1,1,2,4,2,2,1,1,1,4,2,1,2,0,0.0,neutral or dissatisfied +62921,80177,Male,disloyal Customer,50,Business travel,Eco,975,1,1,1,4,1,4,1,1,2,3,4,1,3,1,0,3.0,neutral or dissatisfied +62922,84146,Male,Loyal Customer,39,Business travel,Business,3107,1,1,3,1,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +62923,11156,Male,Loyal Customer,31,Personal Travel,Eco,247,1,5,0,3,1,0,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +62924,50214,Male,Loyal Customer,69,Business travel,Eco,109,4,3,4,3,4,4,4,4,3,1,1,5,2,4,11,4.0,satisfied +62925,126707,Male,Loyal Customer,46,Business travel,Business,2370,5,5,5,5,2,4,5,5,5,5,5,5,5,3,0,4.0,satisfied +62926,6410,Female,Loyal Customer,31,Personal Travel,Eco,315,2,5,2,3,3,2,4,3,5,2,4,5,5,3,6,6.0,neutral or dissatisfied +62927,121193,Male,Loyal Customer,57,Personal Travel,Eco,2521,1,3,1,3,1,4,4,3,1,2,3,4,1,4,160,165.0,neutral or dissatisfied +62928,60120,Male,disloyal Customer,9,Business travel,Eco,1005,3,3,3,3,2,3,2,2,1,2,4,3,4,2,0,0.0,neutral or dissatisfied +62929,73261,Female,Loyal Customer,51,Personal Travel,Eco,675,3,1,3,3,4,4,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +62930,122244,Male,Loyal Customer,44,Business travel,Business,2771,1,1,3,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +62931,47185,Female,Loyal Customer,29,Business travel,Business,2133,3,2,2,2,3,3,3,3,3,5,4,3,4,3,12,0.0,neutral or dissatisfied +62932,24671,Male,Loyal Customer,49,Business travel,Business,2379,5,5,5,5,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +62933,71685,Female,Loyal Customer,68,Personal Travel,Eco,1197,3,4,3,2,5,4,4,5,5,3,5,3,5,3,59,48.0,neutral or dissatisfied +62934,20416,Female,Loyal Customer,69,Business travel,Business,196,1,2,4,2,2,1,2,1,1,1,1,4,1,4,16,21.0,neutral or dissatisfied +62935,121938,Male,Loyal Customer,35,Business travel,Eco,2282,3,4,4,4,3,3,3,3,2,5,4,1,4,3,6,8.0,neutral or dissatisfied +62936,28262,Male,Loyal Customer,51,Personal Travel,Eco,1542,3,4,3,4,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +62937,113409,Male,Loyal Customer,45,Business travel,Business,3798,1,1,1,1,4,5,4,5,5,5,5,3,5,4,5,1.0,satisfied +62938,43002,Female,disloyal Customer,22,Business travel,Eco,259,4,0,4,3,5,4,5,5,3,3,3,3,2,5,0,0.0,neutral or dissatisfied +62939,89264,Female,disloyal Customer,39,Business travel,Business,453,4,3,3,3,3,3,3,3,3,2,5,4,5,3,3,0.0,neutral or dissatisfied +62940,39342,Female,disloyal Customer,39,Business travel,Eco,374,4,5,4,1,3,4,3,3,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +62941,35394,Female,disloyal Customer,37,Business travel,Eco,676,1,1,1,4,4,1,4,4,2,5,3,2,3,4,0,7.0,neutral or dissatisfied +62942,35858,Male,Loyal Customer,75,Business travel,Business,3694,4,4,4,4,3,3,5,3,3,2,3,4,3,5,0,0.0,satisfied +62943,7137,Male,Loyal Customer,7,Personal Travel,Business,135,5,0,5,1,3,5,3,3,2,2,1,2,2,3,0,0.0,satisfied +62944,12378,Female,disloyal Customer,21,Business travel,Eco,262,4,4,3,5,3,3,3,3,1,3,3,1,3,3,0,0.0,satisfied +62945,33611,Male,Loyal Customer,60,Business travel,Eco,399,3,2,4,2,3,3,3,3,2,5,3,4,4,3,66,58.0,neutral or dissatisfied +62946,111310,Male,disloyal Customer,49,Business travel,Business,283,2,2,2,4,5,2,5,5,4,4,4,5,4,5,5,10.0,neutral or dissatisfied +62947,83433,Male,Loyal Customer,49,Business travel,Business,2841,2,2,2,2,4,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +62948,16150,Female,disloyal Customer,57,Business travel,Eco,277,1,0,1,3,4,1,4,4,4,2,5,1,3,4,0,0.0,neutral or dissatisfied +62949,125854,Female,disloyal Customer,24,Business travel,Eco,920,2,2,2,3,4,2,1,4,3,4,3,2,4,4,0,0.0,neutral or dissatisfied +62950,127829,Male,Loyal Customer,60,Personal Travel,Eco,1044,1,4,2,2,3,2,5,3,5,5,5,2,4,3,0,2.0,neutral or dissatisfied +62951,68167,Male,disloyal Customer,9,Business travel,Business,603,0,0,0,1,4,0,4,4,4,3,5,3,5,4,0,0.0,satisfied +62952,63014,Female,Loyal Customer,52,Business travel,Business,2111,3,2,2,2,1,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +62953,111789,Male,Loyal Customer,17,Personal Travel,Eco,1620,2,5,2,2,1,2,1,1,5,3,4,3,5,1,37,18.0,neutral or dissatisfied +62954,117642,Female,Loyal Customer,32,Personal Travel,Eco,1020,2,2,2,3,2,2,2,2,2,3,2,2,3,2,0,0.0,neutral or dissatisfied +62955,123901,Male,disloyal Customer,47,Personal Travel,Eco,544,2,4,2,2,2,2,2,2,4,5,2,2,4,2,0,0.0,neutral or dissatisfied +62956,22940,Male,Loyal Customer,33,Business travel,Business,817,2,2,2,2,4,5,4,4,5,3,5,4,4,4,0,0.0,satisfied +62957,88431,Male,disloyal Customer,47,Business travel,Eco,404,2,0,2,3,1,2,1,1,4,3,3,2,4,1,0,9.0,neutral or dissatisfied +62958,2211,Female,Loyal Customer,54,Business travel,Business,3274,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,4.0,satisfied +62959,111550,Male,Loyal Customer,53,Business travel,Business,794,2,2,2,2,2,5,4,5,5,5,5,5,5,4,42,37.0,satisfied +62960,96832,Female,disloyal Customer,40,Business travel,Business,571,2,2,2,3,1,2,1,1,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +62961,115079,Male,Loyal Customer,20,Business travel,Business,404,3,1,1,1,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +62962,84276,Female,Loyal Customer,57,Business travel,Business,334,2,2,2,2,4,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +62963,4799,Female,Loyal Customer,29,Personal Travel,Eco,403,5,5,5,3,4,5,4,4,5,2,4,3,5,4,0,0.0,satisfied +62964,22791,Male,Loyal Customer,44,Business travel,Eco,134,3,2,2,2,2,3,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +62965,74967,Male,Loyal Customer,28,Personal Travel,Eco,2475,3,3,4,4,2,4,2,2,2,1,4,4,3,2,59,25.0,neutral or dissatisfied +62966,62430,Female,Loyal Customer,11,Personal Travel,Eco,1670,3,5,3,4,5,3,5,5,3,1,5,1,2,5,4,0.0,neutral or dissatisfied +62967,97885,Male,Loyal Customer,22,Business travel,Business,2938,2,2,2,2,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +62968,97745,Male,Loyal Customer,56,Business travel,Business,2654,3,3,3,3,3,5,4,5,5,5,5,3,5,3,3,4.0,satisfied +62969,107244,Male,Loyal Customer,59,Business travel,Business,1758,4,2,2,2,4,2,1,4,4,4,4,4,4,4,91,,neutral or dissatisfied +62970,1266,Female,Loyal Customer,52,Personal Travel,Eco,354,5,5,5,3,5,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +62971,84671,Female,Loyal Customer,50,Business travel,Business,2182,3,3,3,3,3,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +62972,68269,Female,Loyal Customer,16,Personal Travel,Eco,432,2,2,4,3,4,4,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +62973,68678,Male,disloyal Customer,24,Business travel,Eco,237,3,2,3,4,3,3,3,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +62974,65490,Male,Loyal Customer,59,Personal Travel,Eco,1067,3,2,3,3,4,3,5,4,3,5,4,1,3,4,24,27.0,neutral or dissatisfied +62975,110062,Male,Loyal Customer,40,Business travel,Business,1984,1,1,4,1,5,4,5,4,4,4,4,3,4,5,41,24.0,satisfied +62976,20019,Female,Loyal Customer,34,Business travel,Business,2110,4,4,4,4,4,4,5,4,4,4,4,4,4,3,5,0.0,satisfied +62977,25494,Female,Loyal Customer,28,Business travel,Eco,547,1,4,4,4,1,1,1,1,4,2,4,3,4,1,11,0.0,neutral or dissatisfied +62978,29076,Female,Loyal Customer,56,Personal Travel,Eco,679,1,4,1,4,5,5,4,3,3,1,3,5,3,3,10,11.0,neutral or dissatisfied +62979,122213,Male,disloyal Customer,15,Business travel,Eco,546,2,1,2,3,2,2,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +62980,33662,Male,Loyal Customer,38,Business travel,Eco Plus,399,5,5,5,5,5,5,5,5,4,4,2,4,2,5,0,0.0,satisfied +62981,59512,Female,Loyal Customer,46,Business travel,Business,2985,3,2,2,2,2,3,4,3,3,3,3,1,3,4,1,0.0,neutral or dissatisfied +62982,24862,Male,Loyal Customer,48,Business travel,Eco,356,5,1,4,1,5,5,5,5,3,3,3,5,1,5,12,11.0,satisfied +62983,86426,Female,Loyal Customer,77,Business travel,Business,3580,3,1,1,1,5,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +62984,42964,Female,Loyal Customer,56,Business travel,Eco,391,2,1,3,1,2,4,5,2,2,2,2,1,2,1,0,0.0,satisfied +62985,114376,Male,Loyal Customer,54,Personal Travel,Eco Plus,819,3,3,3,4,5,3,5,5,1,1,3,1,3,5,29,27.0,neutral or dissatisfied +62986,2857,Female,Loyal Customer,46,Business travel,Business,3006,4,1,1,1,5,4,3,4,4,4,4,4,4,4,18,13.0,neutral or dissatisfied +62987,16061,Male,Loyal Customer,29,Business travel,Business,3882,1,5,5,5,1,1,1,1,3,1,4,4,3,1,15,6.0,neutral or dissatisfied +62988,41276,Female,Loyal Customer,68,Business travel,Eco,812,3,4,3,4,4,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +62989,48376,Male,Loyal Customer,51,Personal Travel,Eco,522,2,2,2,4,2,2,2,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +62990,24195,Female,Loyal Customer,58,Business travel,Eco,302,4,2,1,1,4,4,3,4,4,4,4,1,4,4,0,6.0,neutral or dissatisfied +62991,23465,Female,Loyal Customer,32,Business travel,Business,576,2,3,5,3,2,2,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +62992,32523,Male,Loyal Customer,46,Business travel,Business,3059,1,1,1,1,4,2,2,5,5,5,4,4,5,3,0,0.0,satisfied +62993,91917,Male,Loyal Customer,50,Business travel,Business,2446,5,2,5,5,5,5,4,5,5,5,5,3,5,5,37,17.0,satisfied +62994,99943,Male,disloyal Customer,22,Business travel,Business,1465,4,0,4,3,4,4,4,4,4,5,3,5,5,4,0,0.0,satisfied +62995,88990,Male,Loyal Customer,26,Personal Travel,Eco,1312,2,1,2,2,4,2,4,4,2,4,2,2,3,4,9,0.0,neutral or dissatisfied +62996,9260,Male,Loyal Customer,58,Business travel,Business,3658,2,2,2,2,3,4,4,5,5,5,4,5,5,4,21,22.0,satisfied +62997,12245,Female,Loyal Customer,34,Business travel,Business,3752,4,4,4,4,1,4,2,5,5,5,4,3,5,3,89,91.0,satisfied +62998,123347,Male,Loyal Customer,48,Business travel,Business,644,2,2,2,2,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +62999,76931,Female,disloyal Customer,29,Business travel,Eco,1217,3,3,3,4,2,3,2,2,4,2,3,1,3,2,12,3.0,neutral or dissatisfied +63000,16547,Male,disloyal Customer,25,Business travel,Eco,1092,3,3,3,4,2,3,2,2,5,5,4,3,4,2,13,26.0,neutral or dissatisfied +63001,3912,Male,Loyal Customer,15,Personal Travel,Eco,213,2,5,2,4,5,2,5,5,4,4,4,3,5,5,0,29.0,neutral or dissatisfied +63002,7569,Female,Loyal Customer,34,Business travel,Business,594,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +63003,86310,Female,Loyal Customer,57,Business travel,Business,356,2,2,2,2,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +63004,119105,Male,Loyal Customer,18,Business travel,Business,3299,3,1,1,1,3,3,3,3,3,3,3,1,4,3,18,2.0,neutral or dissatisfied +63005,41186,Female,Loyal Customer,45,Personal Travel,Eco,429,1,4,1,3,4,4,4,5,5,1,5,1,5,3,6,4.0,neutral or dissatisfied +63006,50008,Male,Loyal Customer,63,Business travel,Eco,209,2,2,2,2,2,2,2,2,2,2,3,2,2,2,31,48.0,neutral or dissatisfied +63007,116656,Male,Loyal Customer,33,Business travel,Eco Plus,308,2,1,1,1,2,2,2,2,1,5,4,3,4,2,0,0.0,neutral or dissatisfied +63008,54260,Female,Loyal Customer,20,Personal Travel,Eco,1222,3,4,3,3,4,3,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +63009,49279,Male,Loyal Customer,39,Business travel,Eco,190,5,4,4,4,5,5,5,4,2,4,4,5,2,5,183,189.0,satisfied +63010,17694,Female,Loyal Customer,18,Business travel,Business,680,5,5,5,5,4,4,4,3,4,5,2,4,4,4,595,589.0,satisfied +63011,123623,Male,Loyal Customer,33,Personal Travel,Business,214,4,0,4,3,3,4,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +63012,8966,Female,Loyal Customer,60,Business travel,Business,2428,2,4,2,2,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +63013,48570,Female,Loyal Customer,52,Personal Travel,Eco,846,1,5,1,1,2,3,2,3,3,1,3,1,3,1,7,4.0,neutral or dissatisfied +63014,83034,Male,Loyal Customer,47,Business travel,Business,1086,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +63015,53399,Female,Loyal Customer,23,Business travel,Business,2419,3,5,5,5,3,3,3,3,1,1,2,1,3,3,27,0.0,neutral or dissatisfied +63016,115957,Male,Loyal Customer,14,Personal Travel,Eco,447,4,1,4,3,5,4,5,5,1,3,4,1,4,5,7,0.0,neutral or dissatisfied +63017,100091,Male,disloyal Customer,26,Business travel,Business,523,3,3,3,2,5,3,5,5,4,5,5,4,5,5,31,37.0,neutral or dissatisfied +63018,110036,Male,Loyal Customer,44,Business travel,Business,1741,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,15.0,satisfied +63019,58784,Male,Loyal Customer,38,Business travel,Eco,1012,1,0,0,3,0,3,3,4,3,4,3,3,1,3,162,156.0,neutral or dissatisfied +63020,473,Male,Loyal Customer,57,Business travel,Business,1760,0,4,0,4,3,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +63021,86524,Male,Loyal Customer,46,Personal Travel,Eco,760,3,4,3,3,3,3,3,3,5,5,5,3,4,3,1,0.0,neutral or dissatisfied +63022,117774,Female,Loyal Customer,41,Personal Travel,Eco,1891,1,2,1,3,5,1,5,5,1,1,4,1,3,5,37,4.0,neutral or dissatisfied +63023,99488,Female,Loyal Customer,51,Personal Travel,Eco,283,2,5,2,3,5,5,5,2,2,2,2,5,2,3,27,26.0,neutral or dissatisfied +63024,109908,Female,Loyal Customer,53,Business travel,Eco,804,1,3,3,3,2,3,3,1,1,1,1,1,1,1,10,0.0,neutral or dissatisfied +63025,93214,Female,disloyal Customer,22,Business travel,Eco,1845,3,3,3,4,2,3,2,2,4,1,4,3,4,2,31,15.0,neutral or dissatisfied +63026,19308,Female,Loyal Customer,14,Personal Travel,Eco Plus,299,3,4,3,3,3,3,3,3,3,3,5,3,5,3,0,0.0,neutral or dissatisfied +63027,8908,Male,Loyal Customer,42,Business travel,Business,510,4,1,4,4,2,4,3,4,4,3,4,2,4,3,36,13.0,neutral or dissatisfied +63028,23879,Female,Loyal Customer,47,Business travel,Eco,589,5,3,3,3,1,4,2,5,5,5,5,4,5,1,0,0.0,satisfied +63029,108831,Female,disloyal Customer,20,Business travel,Eco,1199,1,0,0,1,3,0,4,3,3,3,5,4,4,3,0,7.0,neutral or dissatisfied +63030,76915,Male,Loyal Customer,40,Business travel,Business,630,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +63031,85383,Male,Loyal Customer,37,Personal Travel,Business,332,3,4,3,4,4,5,5,2,2,3,2,4,2,3,17,18.0,neutral or dissatisfied +63032,50164,Male,disloyal Customer,37,Business travel,Eco,89,2,0,2,1,3,2,1,3,5,1,4,2,2,3,0,0.0,neutral or dissatisfied +63033,85555,Female,disloyal Customer,20,Business travel,Business,192,5,5,5,1,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +63034,53680,Male,Loyal Customer,35,Business travel,Eco,1190,5,1,1,1,5,5,5,5,3,5,5,4,3,5,0,0.0,satisfied +63035,16202,Male,Loyal Customer,67,Personal Travel,Eco,199,3,2,3,3,4,3,4,4,1,1,4,1,3,4,67,49.0,neutral or dissatisfied +63036,5607,Male,Loyal Customer,61,Business travel,Business,2002,4,4,4,4,4,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +63037,121092,Female,Loyal Customer,46,Business travel,Business,1558,3,3,3,3,5,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +63038,30076,Male,Loyal Customer,68,Personal Travel,Eco,204,4,4,4,4,5,4,5,5,2,5,1,3,2,5,0,5.0,satisfied +63039,39927,Female,Loyal Customer,43,Business travel,Eco,989,4,4,4,4,2,2,3,4,4,4,4,2,4,2,0,0.0,satisfied +63040,4295,Female,Loyal Customer,65,Personal Travel,Eco,502,3,4,3,3,2,4,4,5,5,3,2,5,5,3,51,36.0,neutral or dissatisfied +63041,51381,Female,Loyal Customer,35,Personal Travel,Eco Plus,337,3,4,3,4,3,3,3,3,4,4,4,3,5,3,0,11.0,neutral or dissatisfied +63042,7455,Female,disloyal Customer,39,Business travel,Business,552,3,3,3,5,3,3,4,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +63043,116721,Female,Loyal Customer,56,Business travel,Eco Plus,372,5,1,1,1,1,5,3,5,5,5,5,5,5,3,4,0.0,satisfied +63044,11692,Female,Loyal Customer,49,Business travel,Business,1810,0,5,0,4,4,5,4,2,2,2,2,4,2,5,11,12.0,satisfied +63045,125897,Male,Loyal Customer,54,Personal Travel,Eco,920,3,4,3,1,5,3,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +63046,13792,Female,disloyal Customer,42,Business travel,Eco Plus,837,2,2,2,3,5,2,5,5,2,3,1,5,3,5,0,20.0,neutral or dissatisfied +63047,41442,Female,disloyal Customer,30,Business travel,Eco Plus,913,1,1,1,4,3,1,5,3,2,1,3,4,4,3,4,4.0,neutral or dissatisfied +63048,69590,Male,Loyal Customer,12,Personal Travel,Eco,2586,3,3,3,2,3,1,1,3,5,4,2,1,4,1,0,0.0,neutral or dissatisfied +63049,42619,Male,disloyal Customer,27,Business travel,Eco,546,1,0,1,4,4,1,4,4,5,5,2,1,5,4,0,0.0,neutral or dissatisfied +63050,103644,Male,Loyal Customer,43,Business travel,Business,3163,3,3,3,3,2,5,4,5,5,4,5,4,5,3,6,0.0,satisfied +63051,121507,Male,Loyal Customer,16,Business travel,Business,1727,2,2,2,2,4,4,4,4,4,4,3,3,5,4,0,0.0,satisfied +63052,30743,Female,Loyal Customer,36,Business travel,Business,2935,5,5,5,5,4,1,4,5,5,5,5,2,5,5,0,0.0,satisfied +63053,123775,Male,Loyal Customer,35,Business travel,Business,544,3,3,4,3,3,5,4,5,5,5,5,4,5,4,2,0.0,satisfied +63054,52004,Male,Loyal Customer,37,Business travel,Business,1891,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +63055,60599,Female,Loyal Customer,46,Personal Travel,Eco Plus,1558,4,3,4,3,3,3,3,4,4,4,4,4,4,4,5,0.0,neutral or dissatisfied +63056,120493,Male,Loyal Customer,33,Personal Travel,Eco,366,2,2,2,3,1,2,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +63057,91510,Male,Loyal Customer,28,Business travel,Business,1620,5,5,2,5,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +63058,126489,Female,Loyal Customer,19,Personal Travel,Eco,1849,3,5,3,4,5,3,5,5,5,4,4,1,4,5,45,42.0,neutral or dissatisfied +63059,119307,Male,Loyal Customer,63,Business travel,Business,1855,2,5,5,5,3,3,3,4,4,4,2,3,4,3,0,0.0,neutral or dissatisfied +63060,45266,Female,Loyal Customer,48,Business travel,Business,290,0,0,0,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +63061,1360,Male,Loyal Customer,60,Business travel,Business,309,2,4,5,4,1,3,3,2,2,2,2,1,2,1,0,1.0,neutral or dissatisfied +63062,84512,Male,Loyal Customer,58,Business travel,Business,2486,3,3,1,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +63063,103080,Male,Loyal Customer,24,Personal Travel,Eco,546,3,5,3,1,5,3,5,5,3,3,5,4,3,5,0,2.0,neutral or dissatisfied +63064,74444,Female,Loyal Customer,56,Business travel,Business,1438,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +63065,50010,Male,Loyal Customer,31,Business travel,Eco,86,4,4,4,4,4,4,4,4,3,3,1,2,5,4,0,0.0,satisfied +63066,104934,Female,Loyal Customer,50,Business travel,Business,3616,4,4,4,4,2,5,5,4,4,4,5,4,4,3,26,26.0,satisfied +63067,111526,Female,Loyal Customer,57,Business travel,Business,775,5,5,5,5,3,4,5,4,4,4,4,3,4,5,10,11.0,satisfied +63068,56287,Male,disloyal Customer,22,Business travel,Eco,2227,4,4,4,3,2,4,2,2,4,2,1,1,3,2,0,7.0,neutral or dissatisfied +63069,111934,Female,disloyal Customer,24,Business travel,Eco,533,2,5,3,2,2,3,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +63070,122976,Male,Loyal Customer,44,Business travel,Business,1666,5,5,5,5,4,4,5,2,2,2,2,3,2,3,76,75.0,satisfied +63071,121239,Female,Loyal Customer,56,Business travel,Eco,2075,2,4,4,4,3,4,4,2,2,2,2,1,2,4,2,0.0,neutral or dissatisfied +63072,73051,Male,Loyal Customer,51,Business travel,Business,1096,5,5,5,5,3,4,5,4,4,4,4,5,4,3,4,0.0,satisfied +63073,88937,Female,Loyal Customer,38,Business travel,Business,2032,2,2,2,2,2,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +63074,104820,Female,Loyal Customer,44,Personal Travel,Business,472,2,5,2,1,4,4,5,5,5,2,5,5,5,4,7,5.0,neutral or dissatisfied +63075,109072,Female,Loyal Customer,38,Personal Travel,Eco,849,4,4,4,3,5,4,5,5,3,4,4,4,4,5,5,8.0,satisfied +63076,36972,Male,Loyal Customer,29,Business travel,Business,2076,3,2,3,3,4,4,4,3,4,5,5,4,5,4,131,119.0,satisfied +63077,87989,Female,Loyal Customer,40,Business travel,Business,3137,5,5,5,5,4,4,5,5,5,5,5,3,5,5,24,25.0,satisfied +63078,2822,Male,disloyal Customer,20,Business travel,Eco,491,4,4,4,4,3,4,3,3,4,2,5,5,4,3,0,0.0,satisfied +63079,18951,Male,Loyal Customer,51,Personal Travel,Eco,500,3,5,3,2,2,3,1,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +63080,49103,Female,Loyal Customer,44,Business travel,Business,308,3,3,3,3,4,4,3,4,4,4,4,5,4,1,7,10.0,satisfied +63081,101977,Male,Loyal Customer,26,Personal Travel,Eco,628,2,3,2,4,1,2,1,1,3,1,3,3,3,1,12,12.0,neutral or dissatisfied +63082,1862,Male,Loyal Customer,48,Business travel,Business,931,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +63083,69130,Male,Loyal Customer,27,Personal Travel,Eco,1598,4,2,3,4,2,3,2,2,3,2,2,3,3,2,0,0.0,neutral or dissatisfied +63084,90900,Male,Loyal Customer,55,Business travel,Business,581,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +63085,758,Female,disloyal Customer,20,Business travel,Eco,134,4,4,4,2,2,4,2,2,3,3,5,3,4,2,34,21.0,neutral or dissatisfied +63086,9709,Female,Loyal Customer,66,Personal Travel,Eco,277,1,5,1,3,2,4,2,1,1,1,1,4,1,3,0,1.0,neutral or dissatisfied +63087,78689,Female,Loyal Customer,44,Personal Travel,Eco,674,3,4,3,1,2,2,3,5,5,3,5,1,5,4,5,0.0,neutral or dissatisfied +63088,69602,Female,Loyal Customer,61,Personal Travel,Eco,2586,2,2,2,3,2,4,4,3,5,3,3,4,4,4,0,0.0,neutral or dissatisfied +63089,69054,Female,Loyal Customer,28,Business travel,Business,1389,3,2,2,2,3,3,3,3,1,2,3,1,3,3,0,13.0,neutral or dissatisfied +63090,88759,Female,Loyal Customer,22,Business travel,Business,3335,2,2,2,2,4,4,4,4,4,2,4,4,5,4,18,18.0,satisfied +63091,46349,Female,disloyal Customer,49,Business travel,Eco Plus,692,4,4,4,2,5,4,5,5,2,3,5,4,3,5,28,48.0,satisfied +63092,37392,Male,Loyal Customer,47,Business travel,Business,2506,1,1,1,1,5,5,4,5,5,5,5,2,5,1,0,14.0,satisfied +63093,82921,Female,Loyal Customer,39,Business travel,Business,1771,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +63094,14903,Male,Loyal Customer,46,Personal Travel,Eco,343,2,4,2,2,3,2,3,3,4,2,4,5,4,3,0,8.0,neutral or dissatisfied +63095,89276,Male,Loyal Customer,44,Business travel,Business,2813,5,2,5,5,5,5,4,4,4,4,4,5,4,5,0,3.0,satisfied +63096,63626,Female,Loyal Customer,30,Business travel,Business,3830,5,5,5,5,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +63097,21614,Female,Loyal Customer,61,Business travel,Business,2949,4,2,2,2,4,4,3,4,4,4,4,1,4,1,33,23.0,neutral or dissatisfied +63098,24170,Female,disloyal Customer,26,Business travel,Eco,302,3,2,3,4,4,3,5,4,1,4,3,1,4,4,0,19.0,neutral or dissatisfied +63099,117887,Male,Loyal Customer,48,Business travel,Business,2038,3,3,3,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +63100,45440,Female,Loyal Customer,11,Personal Travel,Eco,649,1,4,1,5,3,1,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +63101,63617,Female,disloyal Customer,39,Business travel,Business,1440,3,2,2,2,4,2,4,4,2,2,2,3,2,4,33,35.0,neutral or dissatisfied +63102,60680,Male,disloyal Customer,20,Business travel,Eco,1605,3,3,3,2,1,3,1,1,3,5,3,5,5,1,3,0.0,neutral or dissatisfied +63103,12675,Female,Loyal Customer,42,Business travel,Business,2542,3,3,3,3,3,2,1,3,3,3,3,1,3,5,21,18.0,satisfied +63104,31336,Female,Loyal Customer,60,Personal Travel,Eco,1062,5,4,5,4,5,4,5,1,1,5,1,3,1,3,0,2.0,satisfied +63105,9153,Male,Loyal Customer,54,Personal Travel,Eco,227,3,4,0,3,0,1,1,5,5,4,5,1,3,1,236,237.0,neutral or dissatisfied +63106,11637,Female,disloyal Customer,29,Business travel,Business,835,4,4,4,5,4,3,3,3,3,5,4,3,5,3,179,177.0,neutral or dissatisfied +63107,47782,Female,disloyal Customer,23,Business travel,Eco,451,3,5,3,3,3,3,5,3,3,4,4,5,3,3,55,41.0,neutral or dissatisfied +63108,102403,Male,Loyal Customer,35,Personal Travel,Eco,386,1,4,1,5,4,1,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +63109,118523,Female,Loyal Customer,35,Business travel,Business,370,4,4,4,4,4,5,4,4,4,4,4,4,4,3,15,5.0,satisfied +63110,9486,Female,Loyal Customer,32,Business travel,Business,224,4,4,4,4,5,5,5,5,3,5,5,3,4,5,36,81.0,satisfied +63111,25173,Male,Loyal Customer,64,Personal Travel,Eco,369,1,4,2,3,5,2,5,5,1,1,4,2,4,5,6,15.0,neutral or dissatisfied +63112,71283,Female,Loyal Customer,42,Personal Travel,Eco,733,1,1,1,4,3,5,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +63113,15726,Male,disloyal Customer,26,Business travel,Eco,424,1,2,1,4,1,5,5,2,3,3,4,5,2,5,491,485.0,neutral or dissatisfied +63114,74154,Female,Loyal Customer,31,Business travel,Business,641,3,1,1,1,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +63115,32625,Female,Loyal Customer,62,Business travel,Eco,101,3,4,4,4,5,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +63116,127604,Male,Loyal Customer,58,Business travel,Business,1773,1,1,1,1,5,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +63117,83647,Male,Loyal Customer,56,Business travel,Business,2826,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,2.0,satisfied +63118,111471,Female,Loyal Customer,64,Personal Travel,Eco,836,2,3,2,3,5,2,2,1,1,2,1,3,1,3,13,18.0,neutral or dissatisfied +63119,46670,Female,disloyal Customer,24,Business travel,Eco,73,4,0,4,1,2,4,2,2,2,5,5,1,4,2,0,0.0,neutral or dissatisfied +63120,74537,Male,Loyal Customer,65,Business travel,Business,1126,1,3,3,3,4,4,3,1,1,1,1,3,1,4,53,63.0,neutral or dissatisfied +63121,48589,Male,Loyal Customer,60,Personal Travel,Eco,845,2,2,2,3,2,2,2,2,4,4,4,3,3,2,1,11.0,neutral or dissatisfied +63122,125970,Male,disloyal Customer,29,Business travel,Business,631,3,3,3,3,3,3,3,3,4,4,4,5,5,3,37,20.0,neutral or dissatisfied +63123,71135,Female,Loyal Customer,52,Business travel,Business,1739,4,4,2,4,5,5,4,5,5,4,5,5,5,3,60,36.0,satisfied +63124,37918,Female,Loyal Customer,57,Personal Travel,Eco,1023,1,0,1,2,2,4,5,2,2,1,2,3,2,5,45,57.0,neutral or dissatisfied +63125,71836,Male,Loyal Customer,34,Business travel,Business,1846,2,2,2,2,2,4,3,2,2,2,2,1,2,1,34,36.0,neutral or dissatisfied +63126,50977,Female,Loyal Customer,22,Personal Travel,Eco,266,1,5,1,3,2,1,2,2,3,1,1,4,4,2,0,0.0,neutral or dissatisfied +63127,102481,Male,Loyal Customer,21,Personal Travel,Eco,397,2,5,2,4,2,2,2,2,3,3,4,4,4,2,3,0.0,neutral or dissatisfied +63128,106810,Male,Loyal Customer,57,Business travel,Business,1488,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,4.0,satisfied +63129,122443,Female,disloyal Customer,20,Business travel,Eco,808,3,3,3,2,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +63130,81257,Male,Loyal Customer,40,Business travel,Business,1020,4,4,4,4,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +63131,22077,Male,Loyal Customer,48,Business travel,Eco Plus,321,4,5,5,5,3,4,3,3,1,5,2,5,2,3,0,0.0,satisfied +63132,28876,Female,disloyal Customer,29,Business travel,Eco,978,1,1,1,4,5,1,5,5,3,2,3,2,1,5,0,0.0,neutral or dissatisfied +63133,125357,Male,Loyal Customer,18,Business travel,Business,599,1,1,3,1,5,4,5,5,4,1,2,2,5,5,0,0.0,satisfied +63134,121322,Male,Loyal Customer,67,Personal Travel,Eco,1009,3,3,3,4,3,3,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +63135,57394,Female,Loyal Customer,8,Personal Travel,Eco,472,4,5,4,3,1,4,1,1,3,2,5,3,4,1,55,50.0,satisfied +63136,84195,Female,Loyal Customer,52,Business travel,Business,2253,1,1,1,1,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +63137,38959,Female,Loyal Customer,41,Business travel,Business,1757,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +63138,31342,Male,Loyal Customer,40,Business travel,Business,1819,1,1,1,1,2,4,4,4,4,4,4,3,4,4,55,49.0,satisfied +63139,22629,Female,Loyal Customer,68,Personal Travel,Eco,223,4,2,4,3,2,3,3,2,2,4,2,3,2,1,0,2.0,neutral or dissatisfied +63140,62890,Male,Loyal Customer,37,Business travel,Business,2532,1,1,1,1,3,4,4,5,5,5,5,5,5,4,2,4.0,satisfied +63141,8554,Male,Loyal Customer,32,Business travel,Business,3457,4,4,4,4,5,5,4,5,4,3,4,3,4,5,111,115.0,satisfied +63142,56388,Male,Loyal Customer,49,Business travel,Business,1167,2,4,5,5,3,1,2,2,2,2,2,3,2,3,9,9.0,neutral or dissatisfied +63143,59121,Male,Loyal Customer,33,Personal Travel,Eco,1744,2,5,2,2,2,2,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +63144,67441,Female,Loyal Customer,57,Business travel,Eco,192,2,3,3,3,2,1,1,2,2,2,2,4,2,3,8,4.0,satisfied +63145,73128,Male,Loyal Customer,59,Personal Travel,Business,1068,5,4,4,2,5,5,4,4,4,4,4,4,4,3,1,2.0,satisfied +63146,102788,Female,Loyal Customer,33,Personal Travel,Eco,1099,3,3,3,4,3,3,3,3,3,2,4,1,4,3,0,0.0,neutral or dissatisfied +63147,68321,Male,disloyal Customer,43,Business travel,Business,2165,2,2,2,5,2,2,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +63148,122018,Male,Loyal Customer,60,Business travel,Business,3342,1,3,1,1,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +63149,5440,Male,disloyal Customer,37,Business travel,Eco,265,2,2,2,4,5,2,5,5,1,3,4,4,3,5,0,0.0,neutral or dissatisfied +63150,113404,Male,Loyal Customer,56,Business travel,Eco,197,1,2,2,2,1,1,1,1,2,2,4,3,3,1,0,0.0,neutral or dissatisfied +63151,118981,Male,disloyal Customer,25,Business travel,Business,479,5,4,5,5,5,5,5,5,5,5,5,5,5,5,6,0.0,satisfied +63152,59015,Female,disloyal Customer,35,Business travel,Eco,1085,1,1,1,3,3,1,3,3,4,4,3,2,3,3,0,9.0,neutral or dissatisfied +63153,90856,Female,Loyal Customer,26,Business travel,Business,594,3,2,2,2,3,3,3,3,1,2,4,3,3,3,0,0.0,neutral or dissatisfied +63154,60282,Female,Loyal Customer,60,Business travel,Business,2583,5,5,5,5,4,4,4,5,3,4,5,4,5,4,0,0.0,satisfied +63155,54235,Female,disloyal Customer,24,Business travel,Eco,1222,5,5,5,4,5,5,3,5,3,3,3,5,5,5,7,0.0,satisfied +63156,10981,Male,Loyal Customer,46,Business travel,Eco,191,3,1,1,1,3,3,3,3,1,2,1,4,3,3,0,0.0,satisfied +63157,7234,Female,Loyal Customer,38,Business travel,Business,2999,2,2,2,2,5,1,4,5,5,5,4,2,5,4,0,0.0,satisfied +63158,15316,Male,Loyal Customer,47,Business travel,Eco,599,1,2,5,2,1,1,1,1,1,3,3,3,3,1,96,85.0,neutral or dissatisfied +63159,17383,Male,Loyal Customer,61,Personal Travel,Eco,637,3,5,3,2,5,3,5,5,3,3,5,4,4,5,48,46.0,neutral or dissatisfied +63160,88519,Female,Loyal Customer,22,Personal Travel,Eco,250,2,5,2,2,3,2,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +63161,49996,Female,Loyal Customer,34,Business travel,Eco,199,4,4,4,4,4,3,4,4,2,1,3,3,2,4,0,0.0,neutral or dissatisfied +63162,45360,Male,Loyal Customer,49,Personal Travel,Eco,188,5,2,5,3,4,5,5,4,2,3,2,4,3,4,0,0.0,satisfied +63163,112435,Male,Loyal Customer,36,Business travel,Eco,862,5,5,5,5,5,4,5,5,4,3,4,1,3,5,0,0.0,neutral or dissatisfied +63164,123831,Male,Loyal Customer,41,Business travel,Business,544,1,1,1,1,4,5,5,5,5,4,5,5,5,4,0,2.0,satisfied +63165,118681,Male,Loyal Customer,22,Business travel,Eco,369,4,1,1,1,4,4,3,4,1,3,3,5,5,4,0,0.0,satisfied +63166,76999,Female,Loyal Customer,39,Business travel,Business,3012,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +63167,100727,Male,Loyal Customer,37,Business travel,Business,328,2,4,4,4,5,4,3,2,2,2,2,4,2,1,0,4.0,neutral or dissatisfied +63168,38211,Male,Loyal Customer,52,Business travel,Eco Plus,1237,2,3,1,1,2,2,2,2,4,1,2,5,2,2,0,0.0,satisfied +63169,51798,Male,Loyal Customer,16,Personal Travel,Eco,237,1,5,0,5,4,0,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +63170,64768,Female,Loyal Customer,37,Business travel,Business,224,1,3,4,4,2,2,3,2,2,2,1,1,2,3,22,15.0,neutral or dissatisfied +63171,89221,Male,Loyal Customer,57,Personal Travel,Eco,1947,3,4,4,1,5,4,2,5,5,2,4,3,4,5,112,89.0,neutral or dissatisfied +63172,20633,Male,Loyal Customer,30,Business travel,Business,2911,2,2,3,2,4,3,4,4,4,5,5,5,3,4,1,25.0,satisfied +63173,95649,Male,Loyal Customer,25,Business travel,Business,2028,2,2,2,2,4,4,4,4,5,3,4,5,4,4,15,7.0,satisfied +63174,117035,Male,Loyal Customer,45,Business travel,Business,3048,3,3,4,3,5,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +63175,97275,Female,Loyal Customer,30,Business travel,Business,1841,3,3,3,3,5,5,5,5,4,4,4,5,5,5,16,5.0,satisfied +63176,99687,Female,Loyal Customer,61,Business travel,Business,2569,2,4,4,4,1,3,4,2,2,2,2,4,2,1,6,0.0,neutral or dissatisfied +63177,8547,Female,Loyal Customer,42,Business travel,Business,3156,3,3,3,3,2,5,5,4,4,5,5,3,4,3,20,20.0,satisfied +63178,102918,Male,Loyal Customer,58,Business travel,Business,436,1,1,1,1,5,5,4,4,4,4,4,4,4,3,21,25.0,satisfied +63179,21491,Female,Loyal Customer,24,Personal Travel,Eco,399,2,5,2,3,1,2,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +63180,102739,Female,Loyal Customer,14,Personal Travel,Eco,365,1,5,5,1,1,5,1,1,4,4,4,4,5,1,19,17.0,neutral or dissatisfied +63181,45552,Male,Loyal Customer,72,Business travel,Eco Plus,508,2,1,1,1,2,2,2,2,2,2,4,2,4,2,0,0.0,satisfied +63182,75298,Male,Loyal Customer,31,Personal Travel,Eco Plus,1726,3,5,4,3,4,2,1,4,4,5,5,1,3,1,469,443.0,neutral or dissatisfied +63183,78521,Male,Loyal Customer,20,Personal Travel,Eco,666,1,5,1,1,2,1,2,2,3,2,5,2,4,2,0,14.0,neutral or dissatisfied +63184,109792,Female,disloyal Customer,22,Business travel,Business,1033,5,4,5,2,4,5,4,4,4,3,5,3,5,4,0,0.0,satisfied +63185,57063,Male,Loyal Customer,57,Personal Travel,Eco Plus,2133,2,4,2,3,3,2,3,3,5,4,5,4,4,3,1,21.0,neutral or dissatisfied +63186,114215,Male,Loyal Customer,54,Business travel,Business,862,2,4,4,4,3,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +63187,124240,Male,Loyal Customer,46,Business travel,Business,1916,3,1,1,1,2,2,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +63188,113343,Male,disloyal Customer,36,Business travel,Business,258,4,4,4,4,4,4,4,4,5,4,5,5,4,4,16,6.0,neutral or dissatisfied +63189,55816,Female,Loyal Customer,60,Business travel,Business,1416,1,1,1,1,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +63190,114660,Female,Loyal Customer,37,Business travel,Business,3955,5,5,5,5,3,4,5,3,3,3,3,5,3,5,13,7.0,satisfied +63191,34874,Female,Loyal Customer,54,Business travel,Business,2248,2,3,3,3,3,2,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +63192,66610,Male,Loyal Customer,31,Personal Travel,Eco,761,4,4,4,1,5,4,5,5,5,4,4,5,5,5,41,30.0,neutral or dissatisfied +63193,101795,Male,Loyal Customer,72,Business travel,Business,1521,4,2,2,2,2,3,3,4,4,4,4,4,4,2,0,35.0,neutral or dissatisfied +63194,55016,Male,Loyal Customer,48,Business travel,Business,1379,3,3,3,3,5,4,4,4,4,4,4,4,4,4,73,66.0,satisfied +63195,90407,Male,Loyal Customer,51,Business travel,Business,2429,3,3,3,3,3,4,4,5,5,5,5,4,5,3,13,11.0,satisfied +63196,20725,Female,Loyal Customer,13,Personal Travel,Eco,765,3,5,3,3,2,3,2,2,5,2,5,3,4,2,11,0.0,neutral or dissatisfied +63197,79085,Female,Loyal Customer,24,Personal Travel,Eco,356,1,5,1,1,1,1,1,1,3,3,4,5,4,1,0,3.0,neutral or dissatisfied +63198,67102,Female,Loyal Customer,44,Business travel,Business,1121,2,5,5,5,2,3,3,2,2,2,2,4,2,3,1,10.0,neutral or dissatisfied +63199,25600,Male,Loyal Customer,51,Personal Travel,Eco,874,3,3,3,3,5,3,5,5,4,5,4,4,3,5,31,67.0,neutral or dissatisfied +63200,28576,Female,Loyal Customer,50,Business travel,Business,2607,3,3,3,3,2,4,1,2,2,3,2,2,2,2,0,0.0,satisfied +63201,21326,Male,Loyal Customer,49,Personal Travel,Business,674,2,4,2,2,2,5,5,3,3,2,5,3,3,5,0,0.0,neutral or dissatisfied +63202,125013,Female,Loyal Customer,41,Personal Travel,Eco,184,2,4,2,1,5,2,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +63203,34198,Female,Loyal Customer,33,Personal Travel,Eco,1046,1,4,1,1,2,1,2,2,4,2,5,5,5,2,22,23.0,neutral or dissatisfied +63204,76845,Male,disloyal Customer,28,Business travel,Eco,989,2,2,2,1,5,2,5,5,1,3,1,2,2,5,19,4.0,neutral or dissatisfied +63205,39235,Female,Loyal Customer,38,Business travel,Eco,67,5,4,4,4,5,5,5,5,5,3,3,1,2,5,0,0.0,satisfied +63206,12834,Female,disloyal Customer,21,Business travel,Business,417,0,4,0,3,5,0,5,5,2,3,3,5,2,5,0,0.0,satisfied +63207,55277,Female,Loyal Customer,42,Business travel,Business,1608,3,4,3,3,3,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +63208,939,Female,disloyal Customer,17,Business travel,Business,229,3,3,3,3,2,3,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +63209,56383,Female,Loyal Customer,8,Personal Travel,Eco Plus,200,4,4,4,2,3,4,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +63210,91025,Female,Loyal Customer,64,Personal Travel,Eco,404,3,2,3,3,3,2,2,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +63211,106026,Male,Loyal Customer,44,Business travel,Business,2295,3,3,3,3,1,3,2,3,3,3,3,1,3,2,7,23.0,neutral or dissatisfied +63212,12318,Female,Loyal Customer,43,Business travel,Eco,201,5,3,3,3,5,2,4,5,5,5,5,5,5,5,0,0.0,satisfied +63213,85731,Female,Loyal Customer,52,Business travel,Business,2032,4,4,2,4,5,4,5,4,4,4,4,5,4,3,0,8.0,satisfied +63214,71257,Female,Loyal Customer,51,Personal Travel,Eco,733,0,3,0,3,3,4,5,2,2,0,2,2,2,2,0,0.0,satisfied +63215,9109,Male,Loyal Customer,52,Business travel,Eco,765,3,1,1,1,2,3,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +63216,75777,Female,Loyal Customer,9,Personal Travel,Eco,868,3,5,3,3,5,3,5,5,4,3,3,3,3,5,0,0.0,neutral or dissatisfied +63217,72147,Male,Loyal Customer,66,Personal Travel,Eco,731,3,1,3,1,2,3,2,2,1,4,2,3,1,2,0,0.0,neutral or dissatisfied +63218,83325,Male,Loyal Customer,67,Personal Travel,Eco,1671,2,4,2,2,3,2,3,3,4,5,1,1,3,3,0,5.0,neutral or dissatisfied +63219,22537,Female,Loyal Customer,63,Personal Travel,Eco Plus,214,1,2,1,3,5,3,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +63220,49300,Male,disloyal Customer,38,Business travel,Eco,89,3,4,4,4,1,4,1,1,4,3,1,3,3,1,52,46.0,neutral or dissatisfied +63221,38477,Male,Loyal Customer,56,Personal Travel,Eco,846,2,4,2,1,3,2,3,3,4,3,5,4,5,3,31,25.0,neutral or dissatisfied +63222,30637,Male,Loyal Customer,53,Business travel,Eco,533,4,5,5,5,4,4,4,4,5,3,4,5,3,4,1,3.0,satisfied +63223,128972,Female,Loyal Customer,36,Personal Travel,Eco,414,2,2,2,4,2,1,2,3,1,4,3,2,1,2,147,157.0,neutral or dissatisfied +63224,108044,Male,disloyal Customer,25,Business travel,Business,591,2,4,2,1,1,2,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +63225,109640,Female,Loyal Customer,46,Business travel,Business,3818,3,5,3,3,3,4,4,5,5,5,5,5,5,4,0,15.0,satisfied +63226,55500,Male,Loyal Customer,46,Personal Travel,Eco,1739,3,1,3,4,2,3,2,2,4,4,2,2,4,2,0,1.0,neutral or dissatisfied +63227,21161,Male,Loyal Customer,60,Personal Travel,Eco,954,1,5,1,3,4,1,4,4,2,1,2,3,5,4,0,0.0,neutral or dissatisfied +63228,92218,Male,Loyal Customer,14,Personal Travel,Eco,1956,4,0,4,3,2,4,4,2,3,3,4,4,4,2,19,8.0,neutral or dissatisfied +63229,121237,Male,disloyal Customer,8,Business travel,Eco,2075,3,3,3,3,1,3,1,1,3,4,2,2,3,1,0,0.0,neutral or dissatisfied +63230,41416,Female,Loyal Customer,67,Personal Travel,Eco,563,3,4,3,4,5,5,5,4,4,3,4,5,4,5,18,7.0,neutral or dissatisfied +63231,69460,Female,Loyal Customer,13,Personal Travel,Eco,1096,2,3,2,3,1,2,1,1,4,5,3,2,4,1,49,33.0,neutral or dissatisfied +63232,2557,Female,disloyal Customer,25,Business travel,Eco,280,1,4,1,4,4,1,4,4,3,3,4,4,4,4,36,35.0,neutral or dissatisfied +63233,28616,Female,disloyal Customer,22,Business travel,Eco,806,2,2,2,4,5,2,5,5,2,2,4,4,1,5,0,0.0,neutral or dissatisfied +63234,44191,Female,disloyal Customer,33,Business travel,Eco,128,3,1,3,3,1,3,1,1,2,5,3,2,4,1,0,0.0,neutral or dissatisfied +63235,53905,Female,Loyal Customer,13,Personal Travel,Eco,140,4,3,4,3,5,4,5,5,1,5,2,1,3,5,3,0.0,neutral or dissatisfied +63236,126900,Male,Loyal Customer,8,Business travel,Business,2125,5,5,5,5,4,4,4,4,3,2,3,4,5,4,0,0.0,satisfied +63237,1029,Female,Loyal Customer,47,Business travel,Business,2739,2,2,2,2,3,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +63238,37477,Female,disloyal Customer,24,Business travel,Eco,1069,1,1,1,3,3,1,1,3,4,2,4,3,3,3,61,51.0,neutral or dissatisfied +63239,87617,Male,disloyal Customer,43,Business travel,Business,606,1,1,1,1,1,1,1,1,3,4,5,5,5,1,5,17.0,neutral or dissatisfied +63240,10204,Female,disloyal Customer,22,Business travel,Eco,517,5,0,5,4,4,5,4,4,5,5,5,3,4,4,54,51.0,satisfied +63241,124262,Female,Loyal Customer,16,Personal Travel,Eco Plus,1916,4,2,4,3,4,4,3,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +63242,32798,Male,Loyal Customer,36,Business travel,Business,2737,1,1,1,1,2,4,1,4,4,4,3,1,4,2,0,4.0,satisfied +63243,17226,Male,disloyal Customer,26,Business travel,Eco,872,1,1,1,3,4,1,1,4,3,3,2,5,3,4,55,30.0,neutral or dissatisfied +63244,75420,Female,Loyal Customer,41,Business travel,Business,2218,2,4,5,4,5,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +63245,11580,Female,disloyal Customer,36,Business travel,Eco,468,2,4,2,3,5,2,5,5,2,2,3,3,4,5,0,6.0,neutral or dissatisfied +63246,129296,Female,Loyal Customer,9,Personal Travel,Eco,550,3,0,3,4,4,3,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +63247,43396,Female,Loyal Customer,54,Personal Travel,Eco,347,3,5,3,4,2,2,3,3,3,3,3,3,3,1,0,7.0,neutral or dissatisfied +63248,20817,Male,disloyal Customer,35,Business travel,Eco,515,4,3,5,3,1,5,1,1,1,3,4,3,3,1,0,0.0,neutral or dissatisfied +63249,20240,Male,Loyal Customer,34,Business travel,Business,1784,3,3,3,3,1,3,4,3,3,4,5,5,3,2,62,78.0,satisfied +63250,69429,Male,Loyal Customer,52,Business travel,Business,2095,4,4,4,4,1,5,2,4,4,4,4,3,4,4,0,0.0,satisfied +63251,10902,Female,disloyal Customer,32,Business travel,Eco,295,1,1,1,3,3,1,3,3,4,5,3,2,4,3,19,17.0,neutral or dissatisfied +63252,121436,Male,Loyal Customer,41,Business travel,Business,1631,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,5.0,satisfied +63253,107861,Male,disloyal Customer,48,Business travel,Business,228,3,3,3,4,2,3,1,2,1,3,4,3,3,2,11,6.0,neutral or dissatisfied +63254,54709,Female,Loyal Customer,25,Business travel,Business,2369,2,2,2,2,5,5,5,5,4,5,2,1,5,5,0,0.0,satisfied +63255,98551,Male,disloyal Customer,27,Business travel,Business,861,2,2,2,4,3,2,1,3,3,3,4,5,4,3,17,27.0,neutral or dissatisfied +63256,86660,Female,Loyal Customer,45,Personal Travel,Eco,746,2,4,1,3,5,4,3,2,2,1,2,3,2,1,2,0.0,neutral or dissatisfied +63257,19564,Male,Loyal Customer,47,Business travel,Business,173,2,3,2,3,1,4,3,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +63258,57656,Male,Loyal Customer,58,Personal Travel,Eco,200,2,4,2,3,2,2,2,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +63259,127665,Female,Loyal Customer,45,Business travel,Business,2153,1,1,1,1,5,3,5,3,3,3,3,4,3,3,5,33.0,satisfied +63260,11435,Female,Loyal Customer,44,Business travel,Eco Plus,201,4,1,1,1,2,2,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +63261,20568,Female,Loyal Customer,24,Business travel,Eco,773,3,1,1,1,3,3,1,3,3,5,4,3,3,3,0,0.0,neutral or dissatisfied +63262,213,Male,Loyal Customer,16,Business travel,Business,213,3,5,3,5,2,2,3,2,1,5,4,1,3,2,0,0.0,neutral or dissatisfied +63263,39308,Female,Loyal Customer,60,Personal Travel,Eco,67,1,4,1,4,3,4,4,3,3,1,3,3,3,3,0,13.0,neutral or dissatisfied +63264,53861,Male,Loyal Customer,38,Business travel,Business,224,5,5,3,5,3,4,1,4,4,4,4,2,4,2,0,0.0,satisfied +63265,41465,Male,Loyal Customer,27,Business travel,Eco,1211,3,2,2,2,5,5,5,5,2,3,5,3,3,5,4,23.0,satisfied +63266,111875,Male,Loyal Customer,23,Business travel,Business,1835,3,3,5,3,3,3,3,3,1,2,4,2,4,3,11,12.0,neutral or dissatisfied +63267,8113,Female,disloyal Customer,40,Business travel,Business,294,4,4,4,4,4,4,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +63268,56488,Female,disloyal Customer,25,Business travel,Business,1023,2,5,2,5,3,2,3,3,3,3,5,5,4,3,0,9.0,neutral or dissatisfied +63269,52785,Female,Loyal Customer,39,Business travel,Business,1874,5,5,5,5,4,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +63270,43218,Female,Loyal Customer,31,Business travel,Business,2357,3,5,5,5,3,3,3,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +63271,60664,Female,Loyal Customer,18,Personal Travel,Eco,1620,2,5,2,2,2,2,2,2,3,5,3,3,5,2,1,0.0,neutral or dissatisfied +63272,46738,Male,Loyal Customer,64,Personal Travel,Eco,125,1,2,1,3,2,1,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +63273,123967,Female,Loyal Customer,48,Business travel,Business,3336,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +63274,8648,Male,Loyal Customer,57,Business travel,Business,3428,4,4,4,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +63275,49164,Male,Loyal Customer,42,Business travel,Business,2094,2,2,2,2,4,2,2,5,5,5,5,1,5,1,0,0.0,satisfied +63276,7723,Female,Loyal Customer,43,Business travel,Business,806,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +63277,120268,Female,Loyal Customer,34,Business travel,Business,1576,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +63278,3626,Female,disloyal Customer,19,Business travel,Eco,544,3,4,3,4,5,3,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +63279,119337,Female,Loyal Customer,60,Personal Travel,Eco,214,1,3,1,3,2,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +63280,47914,Female,Loyal Customer,40,Personal Travel,Eco,834,4,5,4,2,1,4,1,1,5,5,5,4,5,1,30,17.0,neutral or dissatisfied +63281,50919,Female,Loyal Customer,31,Personal Travel,Eco,89,1,4,1,3,3,1,3,3,4,3,3,5,4,3,0,2.0,neutral or dissatisfied +63282,66660,Female,Loyal Customer,40,Business travel,Business,1698,2,2,2,2,3,5,4,5,5,5,5,3,5,3,8,8.0,satisfied +63283,44324,Female,Loyal Customer,48,Business travel,Eco,788,5,1,1,1,1,3,4,5,5,5,5,3,5,2,10,19.0,satisfied +63284,85112,Female,Loyal Customer,29,Business travel,Business,3561,3,3,3,3,4,4,4,4,5,4,5,3,5,4,1,0.0,satisfied +63285,126444,Male,disloyal Customer,41,Business travel,Business,1001,4,4,4,2,3,4,3,3,3,3,4,5,4,3,0,10.0,satisfied +63286,71442,Male,Loyal Customer,58,Business travel,Eco,867,3,5,5,5,3,3,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +63287,123191,Male,Loyal Customer,51,Personal Travel,Eco,328,3,4,3,4,1,3,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +63288,100480,Female,Loyal Customer,47,Business travel,Business,2045,3,4,1,4,4,3,4,3,3,3,3,4,3,4,87,78.0,neutral or dissatisfied +63289,105509,Female,Loyal Customer,51,Business travel,Business,611,4,4,4,4,5,5,5,4,4,4,4,3,4,4,30,52.0,satisfied +63290,26401,Male,Loyal Customer,67,Personal Travel,Eco,957,4,4,5,3,3,5,3,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +63291,89159,Male,Loyal Customer,43,Personal Travel,Eco,1947,2,2,2,2,1,2,1,1,2,4,2,1,1,1,27,46.0,neutral or dissatisfied +63292,22510,Male,Loyal Customer,18,Business travel,Eco Plus,143,5,1,1,1,5,5,3,5,1,2,5,5,5,5,1,0.0,satisfied +63293,103118,Male,Loyal Customer,10,Personal Travel,Eco,490,3,4,3,3,2,3,2,2,5,1,2,1,2,2,3,0.0,neutral or dissatisfied +63294,11280,Female,Loyal Customer,42,Personal Travel,Eco,301,1,4,1,5,5,4,5,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +63295,111849,Female,Loyal Customer,48,Business travel,Business,2567,1,4,1,1,4,5,4,5,5,5,5,4,5,4,32,26.0,satisfied +63296,53304,Male,disloyal Customer,18,Business travel,Eco,758,0,0,0,3,2,0,2,2,1,4,1,5,3,2,0,3.0,satisfied +63297,51019,Male,Loyal Customer,7,Personal Travel,Eco,421,5,1,2,2,2,2,2,2,4,5,2,4,2,2,0,0.0,satisfied +63298,61355,Male,Loyal Customer,14,Personal Travel,Eco,602,4,3,3,2,4,3,2,4,5,1,3,2,5,4,3,0.0,neutral or dissatisfied +63299,33686,Male,Loyal Customer,35,Business travel,Business,2374,2,2,2,2,4,3,1,4,4,4,4,4,4,4,79,69.0,satisfied +63300,126856,Female,Loyal Customer,8,Personal Travel,Eco,2296,4,5,4,4,3,4,3,3,3,2,5,5,4,3,22,6.0,satisfied +63301,109907,Male,disloyal Customer,23,Business travel,Eco,692,1,1,1,4,4,1,4,4,3,3,3,2,3,4,33,21.0,neutral or dissatisfied +63302,43522,Female,disloyal Customer,19,Business travel,Eco,752,3,3,3,4,2,3,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +63303,126228,Female,disloyal Customer,22,Business travel,Business,107,4,0,3,2,3,3,4,3,5,4,5,2,3,3,0,0.0,satisfied +63304,29078,Male,Loyal Customer,12,Personal Travel,Eco,1050,2,1,2,2,3,2,3,3,3,4,2,2,2,3,16,18.0,neutral or dissatisfied +63305,89647,Female,disloyal Customer,20,Business travel,Eco,950,3,3,3,2,3,3,3,3,1,2,3,1,2,3,0,0.0,neutral or dissatisfied +63306,32376,Female,disloyal Customer,21,Business travel,Eco,101,4,4,5,4,5,5,5,5,4,5,4,1,2,5,5,7.0,neutral or dissatisfied +63307,41451,Female,disloyal Customer,46,Business travel,Business,1235,4,4,4,4,3,4,3,3,3,2,4,5,4,3,6,10.0,satisfied +63308,86269,Male,Loyal Customer,56,Personal Travel,Eco,226,3,4,3,2,4,3,4,4,5,4,4,4,5,4,0,10.0,neutral or dissatisfied +63309,61261,Male,Loyal Customer,31,Personal Travel,Eco,862,3,4,3,4,3,2,5,3,2,4,4,5,3,5,139,164.0,neutral or dissatisfied +63310,91758,Female,Loyal Customer,22,Business travel,Business,599,2,4,4,4,2,1,2,2,3,3,4,3,3,2,0,4.0,neutral or dissatisfied +63311,7006,Male,Loyal Customer,50,Business travel,Eco,299,3,5,5,5,2,3,2,2,2,5,5,1,1,2,0,2.0,satisfied +63312,4653,Female,Loyal Customer,69,Business travel,Eco,364,2,5,5,5,1,4,4,2,2,2,2,2,2,4,11,2.0,neutral or dissatisfied +63313,105442,Female,disloyal Customer,22,Business travel,Business,998,0,0,0,5,3,0,3,3,4,4,5,3,4,3,5,13.0,satisfied +63314,33510,Male,Loyal Customer,27,Business travel,Eco Plus,965,5,1,1,1,5,5,5,5,1,3,5,4,2,5,0,2.0,satisfied +63315,38738,Female,Loyal Customer,59,Business travel,Business,2490,1,1,4,1,1,4,4,4,4,4,4,5,4,2,0,1.0,satisfied +63316,48799,Female,disloyal Customer,35,Business travel,Business,250,3,3,3,2,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +63317,61322,Female,Loyal Customer,27,Business travel,Eco Plus,967,3,4,4,4,3,3,3,3,1,4,4,4,4,3,46,21.0,neutral or dissatisfied +63318,61382,Male,Loyal Customer,53,Business travel,Business,679,3,2,2,2,5,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +63319,10317,Female,Loyal Customer,55,Business travel,Business,1965,0,4,0,5,3,4,4,3,3,3,3,5,3,5,54,55.0,satisfied +63320,7660,Male,Loyal Customer,57,Business travel,Business,767,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,3.0,satisfied +63321,72451,Male,Loyal Customer,25,Business travel,Business,1119,5,5,5,5,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +63322,8546,Male,Loyal Customer,42,Business travel,Business,109,0,5,0,2,5,5,5,4,4,4,4,4,4,4,9,8.0,satisfied +63323,125358,Male,Loyal Customer,31,Personal Travel,Eco,599,4,5,3,4,1,3,1,1,1,1,3,1,2,1,0,7.0,neutral or dissatisfied +63324,122827,Male,Loyal Customer,37,Business travel,Business,599,2,2,1,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +63325,27728,Female,Loyal Customer,38,Business travel,Eco,680,5,1,1,1,5,5,5,5,4,3,5,1,4,5,0,3.0,satisfied +63326,37096,Male,Loyal Customer,55,Business travel,Business,2004,2,2,2,2,4,5,5,4,4,4,4,1,4,4,18,14.0,satisfied +63327,15182,Female,Loyal Customer,59,Personal Travel,Eco,416,1,2,1,4,2,3,3,4,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +63328,126765,Female,Loyal Customer,38,Personal Travel,Eco,2402,1,1,1,3,4,1,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +63329,104352,Female,Loyal Customer,17,Personal Travel,Eco,409,3,3,3,4,1,3,1,1,2,4,2,4,4,1,3,0.0,neutral or dissatisfied +63330,9103,Female,Loyal Customer,43,Business travel,Business,707,2,5,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +63331,123977,Female,disloyal Customer,26,Business travel,Business,184,0,5,0,4,1,0,1,1,5,2,4,3,5,1,43,49.0,satisfied +63332,8354,Female,Loyal Customer,37,Personal Travel,Eco,783,2,1,2,2,5,2,5,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +63333,69519,Male,Loyal Customer,17,Personal Travel,Business,2475,1,4,1,4,1,5,1,1,2,3,3,1,3,1,0,0.0,neutral or dissatisfied +63334,50170,Male,Loyal Customer,49,Business travel,Eco,250,4,4,3,4,4,4,4,4,3,3,4,2,3,4,0,0.0,neutral or dissatisfied +63335,41167,Male,disloyal Customer,30,Business travel,Eco Plus,667,2,2,2,2,3,2,3,3,4,3,1,2,2,3,41,27.0,neutral or dissatisfied +63336,18928,Male,Loyal Customer,15,Personal Travel,Eco,503,2,5,2,5,5,2,5,5,4,5,5,5,4,5,43,46.0,neutral or dissatisfied +63337,44621,Male,disloyal Customer,47,Business travel,Eco,977,2,3,3,3,3,3,2,3,2,1,3,1,4,3,31,24.0,neutral or dissatisfied +63338,50384,Male,Loyal Customer,48,Business travel,Business,2805,0,3,0,4,5,5,4,2,2,5,3,4,5,4,182,179.0,satisfied +63339,52622,Female,Loyal Customer,39,Business travel,Business,1549,3,3,3,3,2,3,1,5,5,5,3,2,5,4,0,5.0,satisfied +63340,92100,Female,disloyal Customer,33,Business travel,Eco,809,1,1,1,4,5,1,5,5,4,4,2,3,2,5,0,0.0,neutral or dissatisfied +63341,72213,Male,Loyal Customer,47,Business travel,Business,2221,2,2,2,2,2,5,5,4,4,4,4,4,4,4,26,13.0,satisfied +63342,126068,Female,Loyal Customer,22,Business travel,Business,3958,2,2,2,2,5,5,5,5,3,4,4,3,4,5,0,2.0,satisfied +63343,2147,Female,Loyal Customer,22,Personal Travel,Eco Plus,404,2,5,2,2,3,2,3,3,5,4,4,3,5,3,7,8.0,neutral or dissatisfied +63344,115192,Male,disloyal Customer,28,Business travel,Business,325,2,2,2,4,2,2,4,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +63345,82298,Male,disloyal Customer,24,Business travel,Eco,986,1,1,1,4,1,1,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +63346,75158,Male,disloyal Customer,34,Business travel,Business,1723,3,3,3,5,3,3,4,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +63347,97372,Female,Loyal Customer,35,Personal Travel,Eco,347,2,5,2,1,2,2,2,2,5,4,4,4,5,2,17,17.0,neutral or dissatisfied +63348,89727,Male,Loyal Customer,52,Personal Travel,Eco,1096,3,4,3,1,3,1,5,1,4,4,1,5,1,5,202,197.0,neutral or dissatisfied +63349,11789,Male,Loyal Customer,29,Personal Travel,Eco,429,4,1,4,3,5,4,5,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +63350,78144,Female,Loyal Customer,64,Business travel,Business,3143,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +63351,96176,Male,disloyal Customer,25,Business travel,Business,546,5,0,5,1,1,5,1,1,4,4,5,4,4,1,0,0.0,satisfied +63352,18569,Female,disloyal Customer,27,Business travel,Eco,253,2,4,1,3,3,1,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +63353,47485,Female,Loyal Customer,64,Personal Travel,Eco,558,3,2,3,4,5,4,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +63354,79175,Female,disloyal Customer,46,Business travel,Business,2422,4,4,4,4,4,1,5,5,4,4,5,5,4,5,204,190.0,satisfied +63355,45205,Female,Loyal Customer,57,Business travel,Eco,1013,5,5,4,5,3,5,4,5,5,5,5,5,5,3,38,36.0,satisfied +63356,76560,Male,Loyal Customer,19,Business travel,Business,2153,2,1,1,1,2,3,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +63357,84683,Male,Loyal Customer,45,Personal Travel,Eco,2182,3,3,3,4,5,3,5,5,4,4,4,3,3,5,3,2.0,neutral or dissatisfied +63358,111983,Male,Loyal Customer,40,Personal Travel,Eco,533,3,2,3,3,2,3,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +63359,19156,Male,Loyal Customer,48,Business travel,Eco,304,5,1,1,1,5,5,5,5,4,2,3,4,2,5,0,0.0,satisfied +63360,128587,Female,disloyal Customer,29,Business travel,Business,2552,5,5,5,2,2,5,2,2,5,4,3,5,4,2,0,0.0,satisfied +63361,40168,Male,Loyal Customer,46,Business travel,Business,402,4,4,4,4,1,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +63362,26567,Male,Loyal Customer,26,Business travel,Business,515,2,2,2,2,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +63363,40129,Male,Loyal Customer,49,Personal Travel,Eco,422,3,4,3,3,3,3,3,3,5,1,3,5,4,3,0,0.0,neutral or dissatisfied +63364,112582,Male,Loyal Customer,58,Business travel,Business,602,1,1,1,1,4,4,5,4,4,4,4,5,4,3,0,3.0,satisfied +63365,99761,Male,Loyal Customer,32,Personal Travel,Eco,255,1,5,1,2,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +63366,39253,Female,Loyal Customer,40,Business travel,Business,3858,1,1,2,1,4,5,1,4,4,5,3,2,4,3,0,0.0,satisfied +63367,27412,Female,Loyal Customer,42,Business travel,Eco,605,4,4,4,4,1,2,2,4,4,4,4,4,4,5,0,0.0,satisfied +63368,116637,Male,Loyal Customer,28,Business travel,Eco Plus,480,1,3,3,3,1,1,1,1,4,2,1,3,2,1,0,2.0,neutral or dissatisfied +63369,90113,Male,Loyal Customer,44,Business travel,Eco,957,1,1,1,1,1,1,1,1,4,3,3,1,4,1,0,0.0,neutral or dissatisfied +63370,38500,Male,Loyal Customer,32,Business travel,Business,2446,5,5,5,5,4,4,4,4,3,4,3,5,2,4,30,15.0,satisfied +63371,90997,Male,Loyal Customer,29,Personal Travel,Eco,646,3,1,3,3,2,3,2,2,3,5,2,2,2,2,0,0.0,neutral or dissatisfied +63372,51573,Male,Loyal Customer,45,Business travel,Business,2387,4,4,5,4,5,2,2,5,5,5,5,5,5,5,39,35.0,satisfied +63373,98629,Male,Loyal Customer,62,Business travel,Eco,966,3,2,2,2,4,3,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +63374,4819,Female,Loyal Customer,61,Personal Travel,Business,500,2,4,2,3,4,5,4,1,1,2,1,5,1,5,9,3.0,neutral or dissatisfied +63375,24565,Male,Loyal Customer,44,Personal Travel,Eco,696,4,4,4,3,4,4,1,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +63376,48612,Female,disloyal Customer,27,Business travel,Eco Plus,737,1,1,1,3,4,1,1,4,5,3,2,3,2,4,15,,neutral or dissatisfied +63377,30947,Male,Loyal Customer,29,Business travel,Business,3772,2,2,2,2,5,4,5,5,2,1,1,2,4,5,88,75.0,satisfied +63378,7136,Male,Loyal Customer,50,Personal Travel,Business,130,2,2,0,4,1,3,3,4,4,0,4,4,4,1,0,16.0,neutral or dissatisfied +63379,46753,Female,disloyal Customer,23,Business travel,Eco Plus,141,5,4,5,2,4,5,5,4,4,5,5,2,3,4,10,5.0,satisfied +63380,36664,Male,Loyal Customer,8,Personal Travel,Eco,1121,3,5,3,3,5,3,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +63381,8734,Female,Loyal Customer,42,Business travel,Business,1820,3,3,3,3,5,5,5,4,4,4,5,5,5,5,173,166.0,satisfied +63382,107854,Male,disloyal Customer,27,Business travel,Business,228,3,3,3,1,4,3,2,4,4,5,4,4,5,4,85,,neutral or dissatisfied +63383,104234,Male,Loyal Customer,57,Business travel,Business,1631,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +63384,56093,Male,Loyal Customer,40,Business travel,Business,1628,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +63385,93561,Male,Loyal Customer,53,Business travel,Eco Plus,719,2,3,3,3,2,2,2,2,2,3,3,1,2,2,0,3.0,neutral or dissatisfied +63386,23817,Male,Loyal Customer,61,Personal Travel,Eco,374,2,0,2,3,1,2,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +63387,95983,Female,Loyal Customer,53,Business travel,Business,1235,5,5,5,5,3,4,4,5,5,4,5,4,5,5,8,5.0,satisfied +63388,1333,Female,disloyal Customer,24,Business travel,Eco,134,3,0,3,2,3,3,2,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +63389,43438,Female,Loyal Customer,53,Business travel,Business,679,5,5,5,5,5,4,4,3,2,4,4,4,4,4,235,243.0,satisfied +63390,55937,Female,Loyal Customer,70,Business travel,Eco Plus,333,5,3,3,3,1,1,2,5,5,5,5,1,5,2,11,4.0,satisfied +63391,129742,Female,Loyal Customer,49,Business travel,Business,1529,4,4,1,4,4,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +63392,113911,Female,Loyal Customer,18,Business travel,Business,2295,3,3,3,3,4,4,4,4,4,5,5,4,4,4,52,22.0,satisfied +63393,77413,Male,Loyal Customer,8,Personal Travel,Eco,626,2,5,2,3,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +63394,32841,Male,Loyal Customer,70,Personal Travel,Eco,163,3,4,3,3,4,3,2,4,1,2,3,2,3,4,0,0.0,neutral or dissatisfied +63395,105395,Female,Loyal Customer,28,Personal Travel,Eco,369,2,1,2,4,4,2,2,4,4,4,3,2,4,4,1,0.0,neutral or dissatisfied +63396,96659,Female,Loyal Customer,28,Personal Travel,Eco,937,3,4,3,1,2,3,5,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +63397,14999,Female,Loyal Customer,68,Business travel,Business,1201,2,2,2,2,5,1,5,4,4,4,4,5,4,5,0,0.0,satisfied +63398,48426,Male,disloyal Customer,27,Business travel,Eco,844,1,1,1,3,3,1,2,3,2,1,2,3,5,3,0,0.0,neutral or dissatisfied +63399,113632,Female,Loyal Customer,12,Personal Travel,Eco,223,5,4,5,1,5,5,2,5,5,4,5,3,5,5,7,4.0,satisfied +63400,98637,Female,Loyal Customer,46,Business travel,Business,3319,4,1,1,1,1,4,3,4,4,4,4,3,4,2,3,7.0,neutral or dissatisfied +63401,66040,Male,Loyal Customer,53,Business travel,Business,2090,5,5,5,5,3,5,4,5,5,5,5,4,5,4,0,3.0,satisfied +63402,15067,Female,Loyal Customer,7,Personal Travel,Eco,576,4,4,4,4,4,4,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +63403,17301,Male,Loyal Customer,56,Business travel,Business,3497,1,1,1,1,2,4,4,2,2,2,2,3,2,4,14,21.0,satisfied +63404,59637,Male,Loyal Customer,52,Business travel,Business,787,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +63405,13752,Female,Loyal Customer,66,Personal Travel,Eco,441,3,4,3,3,5,3,1,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +63406,48236,Male,Loyal Customer,41,Personal Travel,Eco,259,0,5,0,4,1,0,1,1,5,2,5,2,1,1,0,0.0,satisfied +63407,70222,Female,Loyal Customer,47,Business travel,Business,2547,2,2,2,2,5,5,4,2,2,2,2,5,2,5,1,0.0,satisfied +63408,126094,Female,disloyal Customer,25,Business travel,Business,600,4,2,4,3,3,4,3,3,3,4,4,4,5,3,28,17.0,satisfied +63409,90797,Female,Loyal Customer,53,Business travel,Business,2153,2,5,3,3,3,3,2,2,2,1,2,2,2,2,0,13.0,neutral or dissatisfied +63410,93529,Male,Loyal Customer,79,Business travel,Business,2032,3,4,4,4,4,3,3,3,3,3,3,2,3,2,2,8.0,neutral or dissatisfied +63411,108527,Female,Loyal Customer,42,Business travel,Eco,649,2,4,4,4,4,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +63412,116196,Female,Loyal Customer,12,Personal Travel,Eco,325,4,2,4,4,5,4,5,5,1,1,4,1,3,5,0,0.0,satisfied +63413,22699,Female,Loyal Customer,61,Business travel,Business,3395,2,2,2,2,1,2,3,4,4,4,4,4,4,5,0,0.0,satisfied +63414,106928,Female,Loyal Customer,57,Personal Travel,Eco,1259,4,5,4,4,5,4,4,3,3,4,5,3,3,5,45,41.0,neutral or dissatisfied +63415,66936,Female,Loyal Customer,30,Business travel,Business,1619,3,3,5,3,5,5,5,5,4,4,5,4,5,5,0,0.0,satisfied +63416,17062,Male,Loyal Customer,26,Business travel,Eco Plus,1134,5,3,3,3,5,5,5,5,2,1,4,2,4,5,0,0.0,satisfied +63417,119582,Male,Loyal Customer,50,Business travel,Business,2276,5,5,5,5,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +63418,29064,Male,Loyal Customer,60,Personal Travel,Eco,978,3,4,3,4,5,3,5,5,3,2,3,2,3,5,0,16.0,neutral or dissatisfied +63419,114575,Male,Loyal Customer,43,Business travel,Business,1526,2,5,5,5,2,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +63420,65979,Female,Loyal Customer,10,Personal Travel,Eco,1372,4,4,4,2,5,4,5,5,3,3,4,5,4,5,0,0.0,satisfied +63421,10983,Male,disloyal Customer,22,Business travel,Eco,163,2,0,2,4,5,2,5,5,3,1,5,2,4,5,14,5.0,neutral or dissatisfied +63422,120003,Female,Loyal Customer,58,Business travel,Business,2907,4,4,4,4,5,5,5,4,4,4,5,5,4,5,180,208.0,satisfied +63423,11464,Male,Loyal Customer,59,Business travel,Eco Plus,201,2,1,1,1,1,2,1,1,1,3,4,1,3,1,0,0.0,neutral or dissatisfied +63424,127031,Female,Loyal Customer,60,Business travel,Eco,370,4,5,5,5,2,4,4,4,4,4,4,4,4,2,15,6.0,neutral or dissatisfied +63425,122076,Female,Loyal Customer,64,Personal Travel,Eco,130,1,5,1,5,3,5,5,4,4,1,4,4,4,5,1,0.0,neutral or dissatisfied +63426,81893,Female,Loyal Customer,58,Business travel,Business,680,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +63427,68160,Male,Loyal Customer,16,Business travel,Eco,603,4,5,5,5,4,4,2,4,2,2,3,1,3,4,23,10.0,neutral or dissatisfied +63428,112918,Female,Loyal Customer,24,Business travel,Business,3415,3,3,2,3,3,3,3,3,3,2,3,1,4,3,0,5.0,neutral or dissatisfied +63429,15783,Male,Loyal Customer,17,Personal Travel,Eco,198,2,2,2,3,4,2,4,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +63430,122197,Female,disloyal Customer,24,Business travel,Business,541,4,5,4,4,2,4,2,2,3,2,5,3,4,2,0,0.0,satisfied +63431,55347,Female,Loyal Customer,40,Business travel,Business,594,3,3,3,3,2,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +63432,51628,Male,Loyal Customer,53,Business travel,Business,493,3,4,4,4,5,3,4,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +63433,101822,Female,Loyal Customer,13,Personal Travel,Eco,1521,0,5,1,3,2,1,2,2,4,5,4,5,4,2,0,0.0,satisfied +63434,46057,Female,Loyal Customer,12,Personal Travel,Eco,996,1,4,1,4,4,1,4,4,3,3,5,5,5,4,52,68.0,neutral or dissatisfied +63435,17586,Female,Loyal Customer,28,Personal Travel,Eco,852,2,5,3,1,5,3,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +63436,63585,Female,disloyal Customer,27,Business travel,Eco,995,3,3,3,3,5,3,5,5,4,1,3,1,4,5,0,0.0,neutral or dissatisfied +63437,23404,Female,Loyal Customer,59,Personal Travel,Eco,483,2,1,2,4,4,4,3,2,2,2,2,4,2,3,103,102.0,neutral or dissatisfied +63438,74681,Female,Loyal Customer,70,Personal Travel,Eco,1171,1,2,1,3,1,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +63439,67135,Male,Loyal Customer,25,Business travel,Eco,1017,2,3,3,3,2,2,1,2,3,1,4,1,4,2,0,21.0,neutral or dissatisfied +63440,33733,Male,Loyal Customer,19,Personal Travel,Eco,899,0,4,0,1,2,0,2,2,5,5,4,5,5,2,6,0.0,satisfied +63441,84237,Male,Loyal Customer,34,Business travel,Business,432,5,5,5,5,4,4,5,4,4,4,4,5,4,4,4,30.0,satisfied +63442,56088,Female,Loyal Customer,19,Business travel,Eco Plus,2586,3,5,5,5,4,5,3,2,5,1,1,3,3,3,52,91.0,satisfied +63443,9897,Female,Loyal Customer,41,Business travel,Business,457,1,1,1,1,5,5,4,5,5,5,5,3,5,3,0,3.0,satisfied +63444,50181,Male,disloyal Customer,54,Business travel,Eco,153,1,0,1,3,5,1,3,5,4,4,5,1,4,5,0,0.0,neutral or dissatisfied +63445,115446,Male,Loyal Customer,54,Business travel,Business,2038,1,1,1,1,4,4,4,4,4,4,4,5,4,3,2,0.0,satisfied +63446,22877,Female,Loyal Customer,24,Personal Travel,Eco,147,4,1,4,2,2,4,2,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +63447,8824,Female,Loyal Customer,69,Personal Travel,Eco,552,2,4,2,3,3,4,5,4,4,2,4,3,4,5,0,10.0,neutral or dissatisfied +63448,83579,Female,disloyal Customer,23,Business travel,Eco,936,0,0,0,4,4,0,1,4,5,5,5,3,4,4,0,0.0,satisfied +63449,125587,Female,Loyal Customer,35,Personal Travel,Business,1587,2,5,2,3,5,5,4,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +63450,35691,Male,Loyal Customer,51,Business travel,Business,2586,3,3,3,3,4,4,4,4,3,2,4,4,3,4,0,14.0,satisfied +63451,28533,Male,disloyal Customer,24,Business travel,Eco,1149,1,1,1,3,1,1,1,1,1,5,3,4,4,1,0,0.0,neutral or dissatisfied +63452,125672,Female,Loyal Customer,19,Business travel,Eco,814,3,4,4,4,3,3,4,3,4,2,3,4,3,3,0,8.0,neutral or dissatisfied +63453,96906,Male,Loyal Customer,28,Personal Travel,Eco,1041,1,5,1,1,5,1,3,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +63454,69910,Female,disloyal Customer,27,Business travel,Eco,1067,4,4,4,3,4,4,4,4,3,4,4,1,4,4,0,0.0,neutral or dissatisfied +63455,32675,Female,Loyal Customer,67,Business travel,Eco,101,4,5,5,5,3,3,2,4,4,4,4,3,4,4,2,14.0,neutral or dissatisfied +63456,69741,Male,Loyal Customer,32,Personal Travel,Business,1085,1,4,1,1,4,1,4,4,4,3,4,4,4,4,7,0.0,neutral or dissatisfied +63457,116612,Female,disloyal Customer,39,Business travel,Business,325,2,2,2,4,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +63458,111891,Male,Loyal Customer,21,Personal Travel,Eco,628,4,5,4,3,4,4,5,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +63459,7828,Female,Loyal Customer,36,Personal Travel,Eco,650,2,4,2,3,1,2,1,1,4,4,5,2,1,1,36,38.0,neutral or dissatisfied +63460,26963,Male,Loyal Customer,35,Business travel,Business,2768,1,1,1,1,5,2,2,5,5,5,5,5,5,3,0,13.0,satisfied +63461,64155,Male,Loyal Customer,43,Business travel,Business,3396,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +63462,44325,Male,Loyal Customer,37,Business travel,Business,2865,1,1,1,1,3,3,5,4,4,4,4,2,4,2,0,0.0,satisfied +63463,120383,Male,Loyal Customer,57,Business travel,Business,3850,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +63464,34811,Female,Loyal Customer,49,Personal Travel,Eco,264,1,1,1,2,4,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +63465,81265,Male,Loyal Customer,29,Business travel,Business,3911,4,4,4,4,5,5,5,5,4,3,4,4,5,5,0,21.0,satisfied +63466,81069,Male,disloyal Customer,23,Business travel,Eco,931,2,2,2,4,4,2,4,4,1,1,3,4,4,4,2,5.0,neutral or dissatisfied +63467,58538,Female,Loyal Customer,34,Business travel,Business,1514,2,2,2,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +63468,7829,Female,Loyal Customer,33,Personal Travel,Eco,650,1,5,1,2,2,1,2,2,5,3,4,1,2,2,0,0.0,neutral or dissatisfied +63469,4499,Male,disloyal Customer,19,Business travel,Business,551,5,0,5,3,1,5,1,1,5,2,4,4,5,1,8,4.0,satisfied +63470,28736,Male,Loyal Customer,42,Business travel,Eco,1024,5,5,2,5,5,5,5,5,5,5,3,5,2,5,0,31.0,satisfied +63471,75761,Male,Loyal Customer,54,Personal Travel,Eco,813,5,3,5,1,4,5,4,4,4,1,4,2,5,4,0,0.0,satisfied +63472,26165,Male,Loyal Customer,52,Business travel,Business,515,4,4,4,4,5,2,5,5,5,4,5,5,5,5,28,22.0,satisfied +63473,87619,Female,Loyal Customer,41,Business travel,Business,606,5,5,5,5,2,4,5,5,5,4,5,3,5,4,26,23.0,satisfied +63474,10462,Male,disloyal Customer,26,Business travel,Business,429,1,0,1,5,5,1,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +63475,16309,Female,Loyal Customer,23,Business travel,Business,628,2,3,3,3,2,2,2,2,4,4,4,2,3,2,30,22.0,neutral or dissatisfied +63476,89960,Male,Loyal Customer,68,Personal Travel,Eco,1310,1,3,1,4,4,1,4,4,2,4,2,4,4,4,2,0.0,neutral or dissatisfied +63477,93679,Female,disloyal Customer,27,Business travel,Business,542,2,2,2,3,5,2,5,5,5,5,5,4,4,5,8,4.0,neutral or dissatisfied +63478,57020,Male,Loyal Customer,53,Personal Travel,Eco,2565,1,1,1,3,3,1,1,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +63479,110416,Male,Loyal Customer,52,Business travel,Business,2171,3,3,3,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +63480,30126,Female,Loyal Customer,46,Personal Travel,Eco,399,3,5,3,3,4,4,5,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +63481,88868,Male,Loyal Customer,33,Business travel,Business,859,4,4,4,4,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +63482,79521,Male,Loyal Customer,40,Business travel,Business,3925,1,1,1,1,5,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +63483,7118,Male,Loyal Customer,37,Business travel,Eco Plus,177,1,2,4,2,1,1,1,3,5,4,4,1,4,1,110,144.0,neutral or dissatisfied +63484,30339,Male,Loyal Customer,15,Business travel,Business,391,2,4,4,4,2,3,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +63485,117284,Male,disloyal Customer,36,Business travel,Business,368,2,2,2,4,3,2,3,3,3,5,5,5,5,3,26,25.0,neutral or dissatisfied +63486,114114,Male,Loyal Customer,56,Business travel,Business,909,4,4,4,4,2,4,5,5,5,5,5,5,5,3,4,0.0,satisfied +63487,119419,Male,Loyal Customer,27,Personal Travel,Eco,399,5,1,5,2,3,5,3,3,4,3,1,1,2,3,0,0.0,satisfied +63488,85642,Male,Loyal Customer,46,Business travel,Business,259,0,0,0,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +63489,95091,Female,Loyal Customer,36,Personal Travel,Eco,248,4,4,4,4,2,4,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +63490,3086,Female,Loyal Customer,55,Business travel,Business,2809,1,1,5,1,4,5,4,4,4,4,4,3,4,5,106,93.0,satisfied +63491,114842,Female,disloyal Customer,35,Business travel,Business,342,2,2,2,3,5,2,5,5,5,4,4,5,4,5,18,16.0,neutral or dissatisfied +63492,18508,Female,Loyal Customer,33,Business travel,Business,305,1,0,0,4,2,3,4,5,5,0,3,2,5,4,1,0.0,neutral or dissatisfied +63493,40143,Male,Loyal Customer,50,Business travel,Business,1618,2,2,2,2,2,4,3,5,5,5,5,4,5,5,0,0.0,satisfied +63494,123477,Female,Loyal Customer,38,Business travel,Business,2125,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +63495,15183,Female,Loyal Customer,50,Business travel,Eco,544,5,4,4,4,2,5,4,5,5,5,5,1,5,2,0,0.0,satisfied +63496,53093,Female,Loyal Customer,35,Business travel,Business,1883,0,4,0,1,3,1,4,3,3,3,2,5,3,3,1,0.0,satisfied +63497,111402,Male,Loyal Customer,20,Personal Travel,Eco,1111,3,5,4,3,5,4,5,5,4,4,5,5,5,5,0,2.0,neutral or dissatisfied +63498,15027,Female,Loyal Customer,47,Business travel,Business,2322,5,5,5,5,4,4,5,5,5,5,5,2,5,4,30,23.0,satisfied +63499,46912,Male,Loyal Customer,24,Business travel,Eco,737,1,1,1,1,1,1,1,1,2,5,3,4,3,1,73,49.0,neutral or dissatisfied +63500,32495,Female,Loyal Customer,55,Business travel,Business,3025,4,4,4,4,3,3,3,5,5,5,3,2,5,3,0,7.0,satisfied +63501,128897,Female,Loyal Customer,67,Personal Travel,Eco,2454,2,4,2,3,2,1,1,2,5,3,3,1,2,1,1,1.0,neutral or dissatisfied +63502,53358,Female,disloyal Customer,25,Business travel,Eco,1320,2,2,2,4,4,2,4,4,2,4,3,3,2,4,7,1.0,neutral or dissatisfied +63503,123468,Female,Loyal Customer,52,Business travel,Business,2077,4,4,4,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +63504,80713,Female,disloyal Customer,24,Business travel,Eco,920,3,3,3,3,3,3,3,3,2,3,4,2,4,3,0,0.0,neutral or dissatisfied +63505,54009,Male,Loyal Customer,12,Personal Travel,Eco,395,2,2,2,4,3,2,3,3,4,3,3,4,3,3,126,115.0,neutral or dissatisfied +63506,5581,Female,disloyal Customer,33,Business travel,Eco Plus,588,2,2,2,3,2,2,2,2,1,4,4,1,3,2,0,14.0,neutral or dissatisfied +63507,71781,Male,Loyal Customer,47,Business travel,Business,1846,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +63508,38711,Male,disloyal Customer,21,Business travel,Eco,1282,3,3,3,4,5,3,5,5,3,2,3,2,3,5,3,4.0,neutral or dissatisfied +63509,100700,Female,Loyal Customer,23,Personal Travel,Eco,628,1,5,1,4,1,1,1,1,5,5,4,4,5,1,0,29.0,neutral or dissatisfied +63510,70122,Male,Loyal Customer,42,Business travel,Eco,460,2,3,3,3,2,2,2,2,4,4,3,2,2,2,29,11.0,neutral or dissatisfied +63511,39444,Female,Loyal Customer,70,Personal Travel,Eco,129,3,3,3,1,3,5,4,4,4,3,4,4,4,5,0,12.0,neutral or dissatisfied +63512,97586,Male,Loyal Customer,27,Personal Travel,Eco,337,3,3,3,4,3,3,3,3,3,3,4,4,4,3,12,7.0,neutral or dissatisfied +63513,71324,Male,Loyal Customer,41,Business travel,Business,1514,4,3,3,3,5,4,4,4,4,4,4,2,4,4,0,5.0,neutral or dissatisfied +63514,101339,Female,Loyal Customer,19,Personal Travel,Eco,1771,4,2,4,3,1,4,2,1,3,2,2,1,3,1,0,0.0,neutral or dissatisfied +63515,5443,Female,disloyal Customer,23,Business travel,Business,265,1,4,0,3,3,0,3,3,1,1,4,4,4,3,0,6.0,neutral or dissatisfied +63516,106908,Female,disloyal Customer,22,Business travel,Eco,1259,3,3,3,4,2,3,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +63517,262,Male,Loyal Customer,63,Personal Travel,Business,802,2,4,2,1,2,4,4,4,4,2,5,5,4,4,0,6.0,neutral or dissatisfied +63518,90410,Female,Loyal Customer,50,Business travel,Business,1694,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +63519,65503,Male,Loyal Customer,27,Business travel,Eco Plus,1303,3,1,2,1,3,3,3,3,1,4,4,2,3,3,0,31.0,neutral or dissatisfied +63520,26278,Female,Loyal Customer,56,Personal Travel,Eco,859,3,5,3,2,3,4,3,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +63521,106707,Male,Loyal Customer,9,Personal Travel,Eco,516,3,1,3,4,1,3,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +63522,115739,Female,Loyal Customer,60,Business travel,Business,3915,2,5,5,5,5,4,4,2,2,2,2,1,2,1,86,88.0,neutral or dissatisfied +63523,44548,Female,Loyal Customer,60,Personal Travel,Eco,157,1,2,1,2,4,3,2,3,3,1,3,2,3,3,0,3.0,neutral or dissatisfied +63524,105075,Male,Loyal Customer,25,Business travel,Eco,281,2,2,2,2,2,2,3,2,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +63525,124819,Female,Loyal Customer,47,Business travel,Business,3967,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +63526,113825,Male,Loyal Customer,60,Personal Travel,Eco Plus,386,3,4,3,3,1,3,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +63527,89826,Male,Loyal Customer,20,Personal Travel,Eco Plus,950,4,2,3,3,4,3,4,4,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +63528,65727,Female,disloyal Customer,31,Business travel,Eco,1061,1,1,1,4,4,1,4,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +63529,118930,Male,Loyal Customer,22,Business travel,Business,1618,5,5,5,5,4,4,4,4,4,5,3,3,5,4,21,22.0,satisfied +63530,7016,Male,Loyal Customer,25,Personal Travel,Eco,299,2,2,2,3,3,2,3,3,1,5,4,1,3,3,42,37.0,neutral or dissatisfied +63531,108898,Male,disloyal Customer,25,Business travel,Business,1183,4,4,4,2,2,4,2,2,3,5,5,5,4,2,3,1.0,satisfied +63532,107141,Female,disloyal Customer,23,Business travel,Business,668,0,0,0,3,1,0,1,1,3,4,4,5,5,1,38,47.0,satisfied +63533,53767,Female,disloyal Customer,10,Business travel,Eco,1195,2,2,2,4,2,2,2,2,2,5,4,1,3,2,59,54.0,neutral or dissatisfied +63534,11262,Female,Loyal Customer,40,Personal Travel,Eco,140,3,5,3,4,3,3,3,3,5,2,2,1,2,3,0,0.0,neutral or dissatisfied +63535,27183,Female,Loyal Customer,70,Personal Travel,Eco,2677,4,2,4,3,4,2,2,3,5,2,3,2,3,2,0,0.0,satisfied +63536,19019,Female,Loyal Customer,48,Business travel,Eco,388,5,5,5,5,1,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +63537,67033,Female,disloyal Customer,30,Business travel,Business,985,2,2,2,4,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +63538,76940,Female,Loyal Customer,52,Business travel,Business,1990,3,3,3,3,2,5,4,5,5,5,5,4,5,5,10,0.0,satisfied +63539,120005,Male,Loyal Customer,46,Business travel,Business,328,5,5,5,5,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +63540,58310,Female,Loyal Customer,23,Business travel,Eco,1739,3,4,4,4,3,3,3,3,2,3,3,3,4,3,0,41.0,neutral or dissatisfied +63541,100693,Female,Loyal Customer,58,Personal Travel,Eco,677,3,5,3,3,1,1,1,5,5,3,2,3,5,1,18,16.0,neutral or dissatisfied +63542,45595,Female,Loyal Customer,37,Business travel,Business,230,3,2,3,2,1,2,2,3,3,3,3,3,3,3,14,18.0,neutral or dissatisfied +63543,43741,Female,Loyal Customer,10,Personal Travel,Eco,622,5,4,5,3,3,5,3,3,4,2,4,3,4,3,0,2.0,satisfied +63544,81469,Female,Loyal Customer,61,Business travel,Eco,528,3,3,3,3,5,2,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +63545,71439,Female,disloyal Customer,37,Business travel,Business,867,4,4,4,3,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +63546,50951,Male,Loyal Customer,14,Personal Travel,Eco,77,3,4,3,3,1,3,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +63547,115408,Male,Loyal Customer,43,Business travel,Business,480,3,4,4,4,3,3,3,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +63548,95197,Female,Loyal Customer,9,Personal Travel,Eco,192,2,4,2,1,3,2,2,3,3,4,5,4,5,3,48,32.0,neutral or dissatisfied +63549,14411,Male,Loyal Customer,29,Business travel,Business,3591,3,3,3,3,5,5,5,5,3,3,2,4,4,5,0,13.0,satisfied +63550,95683,Male,Loyal Customer,47,Business travel,Business,2419,2,1,1,1,1,3,3,2,2,2,2,4,2,3,5,5.0,neutral or dissatisfied +63551,100163,Female,Loyal Customer,60,Business travel,Eco,468,1,2,2,2,5,3,3,1,1,1,1,2,1,4,20,16.0,neutral or dissatisfied +63552,36490,Female,Loyal Customer,41,Personal Travel,Business,1249,2,5,2,5,3,3,4,5,5,2,5,4,5,3,45,72.0,neutral or dissatisfied +63553,24296,Female,disloyal Customer,55,Business travel,Eco Plus,147,2,2,2,4,5,2,4,5,3,4,2,3,1,5,63,59.0,neutral or dissatisfied +63554,109262,Female,Loyal Customer,25,Business travel,Eco Plus,612,1,5,2,5,1,1,4,1,1,4,3,1,3,1,0,0.0,neutral or dissatisfied +63555,49828,Male,disloyal Customer,15,Business travel,Eco,373,3,3,3,3,4,3,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +63556,86753,Male,Loyal Customer,37,Personal Travel,Eco,821,0,4,0,3,4,0,4,4,1,2,3,3,4,4,0,0.0,satisfied +63557,80572,Female,disloyal Customer,30,Business travel,Eco,1747,1,2,2,3,4,1,4,4,4,3,2,3,3,4,26,13.0,neutral or dissatisfied +63558,71955,Male,Loyal Customer,40,Business travel,Business,1440,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +63559,22222,Female,Loyal Customer,31,Business travel,Eco Plus,773,5,4,4,4,5,5,5,5,1,3,5,4,1,5,29,17.0,satisfied +63560,10715,Female,disloyal Customer,37,Business travel,Eco,201,2,1,2,4,1,2,1,1,1,5,3,3,3,1,0,0.0,neutral or dissatisfied +63561,24206,Male,disloyal Customer,37,Business travel,Eco,170,3,5,3,2,1,3,1,1,4,3,5,3,1,1,1,4.0,neutral or dissatisfied +63562,123263,Female,Loyal Customer,9,Personal Travel,Eco,590,5,4,5,1,1,5,1,1,3,5,2,2,3,1,0,0.0,satisfied +63563,11934,Male,disloyal Customer,38,Business travel,Business,781,3,3,3,4,1,3,1,1,5,3,4,3,5,1,15,20.0,neutral or dissatisfied +63564,61788,Female,Loyal Customer,51,Personal Travel,Eco,1303,2,5,2,5,3,5,4,5,5,2,5,5,5,5,5,1.0,neutral or dissatisfied +63565,103780,Female,Loyal Customer,50,Business travel,Business,2549,1,1,1,1,5,4,4,5,5,5,5,4,5,4,17,8.0,satisfied +63566,27118,Female,Loyal Customer,59,Business travel,Business,2688,3,3,3,3,5,5,5,3,5,5,3,5,1,5,0,0.0,satisfied +63567,63704,Male,Loyal Customer,21,Business travel,Business,3255,2,2,2,2,3,2,3,3,5,2,4,4,4,3,4,3.0,satisfied +63568,20341,Female,disloyal Customer,38,Business travel,Eco,265,2,1,2,2,2,2,2,2,2,1,2,4,2,2,47,40.0,neutral or dissatisfied +63569,98669,Female,Loyal Customer,58,Personal Travel,Eco,834,1,5,1,3,5,5,5,5,5,1,5,5,5,5,69,87.0,neutral or dissatisfied +63570,93845,Female,Loyal Customer,58,Personal Travel,Eco,391,2,3,1,4,3,4,1,3,3,1,3,5,3,2,0,4.0,neutral or dissatisfied +63571,115430,Female,Loyal Customer,24,Business travel,Eco,362,1,5,4,5,1,1,4,1,1,4,4,4,4,1,44,35.0,neutral or dissatisfied +63572,12098,Female,Loyal Customer,36,Business travel,Business,1034,3,3,3,3,4,1,5,4,4,4,4,5,4,3,0,0.0,satisfied +63573,61846,Female,Loyal Customer,26,Business travel,Eco Plus,1379,2,1,1,1,2,2,2,2,1,4,3,2,3,2,10,1.0,neutral or dissatisfied +63574,54946,Male,Loyal Customer,42,Personal Travel,Business,1379,4,4,3,1,3,5,5,2,2,3,4,5,2,4,28,24.0,neutral or dissatisfied +63575,61390,Male,Loyal Customer,44,Business travel,Business,3366,1,1,1,1,3,2,2,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +63576,45817,Female,Loyal Customer,7,Personal Travel,Eco,517,5,4,5,2,2,5,2,2,3,5,4,5,4,2,58,97.0,satisfied +63577,129542,Female,Loyal Customer,49,Business travel,Eco,2342,4,1,5,1,1,4,3,4,4,4,4,2,4,1,0,12.0,neutral or dissatisfied +63578,121565,Female,Loyal Customer,16,Business travel,Business,2548,3,3,3,3,5,4,5,5,4,4,4,4,5,5,11,0.0,satisfied +63579,9381,Female,Loyal Customer,28,Personal Travel,Eco,401,2,4,2,5,4,2,1,4,3,2,5,3,4,4,20,22.0,neutral or dissatisfied +63580,19169,Female,Loyal Customer,68,Business travel,Eco Plus,304,4,2,1,2,4,4,3,3,3,4,3,5,3,2,0,0.0,satisfied +63581,18817,Female,disloyal Customer,27,Business travel,Eco,448,3,4,3,4,1,3,2,1,2,2,1,2,5,1,0,0.0,neutral or dissatisfied +63582,102180,Female,Loyal Customer,45,Business travel,Business,258,5,5,5,5,2,5,4,5,5,5,5,3,5,4,22,17.0,satisfied +63583,88507,Female,disloyal Customer,19,Business travel,Eco,594,1,2,2,4,4,2,4,4,1,5,3,2,3,4,0,0.0,neutral or dissatisfied +63584,75128,Male,disloyal Customer,25,Business travel,Eco,1244,2,1,1,1,3,1,3,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +63585,31541,Male,Loyal Customer,31,Personal Travel,Eco,776,1,5,1,1,1,1,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +63586,97434,Female,Loyal Customer,29,Business travel,Eco Plus,587,1,2,2,2,1,1,1,1,4,1,3,2,3,1,1,0.0,neutral or dissatisfied +63587,7539,Female,Loyal Customer,69,Personal Travel,Eco,762,3,3,3,4,3,4,4,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +63588,59790,Female,Loyal Customer,33,Business travel,Business,927,5,5,5,5,2,4,5,5,5,5,5,3,5,3,15,0.0,satisfied +63589,66547,Female,Loyal Customer,46,Business travel,Business,1691,2,2,2,2,2,5,5,4,4,4,4,5,4,5,5,1.0,satisfied +63590,61423,Male,Loyal Customer,49,Business travel,Business,2288,3,3,3,3,2,4,5,4,4,4,4,3,4,5,32,21.0,satisfied +63591,52383,Male,Loyal Customer,7,Personal Travel,Eco,370,5,1,5,3,3,5,3,3,3,5,4,3,5,3,1,0.0,satisfied +63592,23068,Male,Loyal Customer,50,Personal Travel,Eco,820,4,5,4,2,5,4,5,5,2,5,1,4,5,5,0,0.0,neutral or dissatisfied +63593,70151,Female,Loyal Customer,25,Personal Travel,Eco,460,4,3,4,3,5,4,1,5,4,4,2,4,3,5,0,0.0,neutral or dissatisfied +63594,58590,Male,Loyal Customer,49,Business travel,Business,3437,1,4,1,1,2,5,5,4,4,5,4,5,4,3,1,0.0,satisfied +63595,71940,Female,Loyal Customer,27,Personal Travel,Eco Plus,1744,2,5,1,3,3,1,3,3,5,4,3,5,5,3,2,1.0,neutral or dissatisfied +63596,93066,Male,Loyal Customer,35,Business travel,Eco,297,2,1,3,1,2,2,2,2,1,4,3,2,4,2,0,18.0,neutral or dissatisfied +63597,24059,Female,Loyal Customer,34,Personal Travel,Eco,427,3,4,3,2,5,3,2,5,4,1,5,5,2,5,0,0.0,neutral or dissatisfied +63598,81437,Male,Loyal Customer,28,Business travel,Business,1734,4,4,4,4,2,2,2,2,3,2,4,3,4,2,0,0.0,satisfied +63599,9058,Female,Loyal Customer,51,Business travel,Eco,173,2,3,3,3,3,2,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +63600,100722,Male,disloyal Customer,32,Business travel,Eco,328,2,2,2,3,4,2,1,4,2,1,4,1,3,4,23,44.0,neutral or dissatisfied +63601,65129,Female,Loyal Customer,12,Personal Travel,Eco,282,3,3,3,4,1,3,5,1,1,1,1,2,4,1,0,0.0,neutral or dissatisfied +63602,106758,Female,Loyal Customer,50,Personal Travel,Eco,945,3,4,3,1,4,1,4,3,3,3,3,1,3,4,0,8.0,neutral or dissatisfied +63603,76422,Male,Loyal Customer,41,Business travel,Business,2225,2,4,4,4,3,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +63604,98082,Male,Loyal Customer,24,Business travel,Business,3719,5,5,5,5,5,5,5,5,5,4,5,4,5,5,18,21.0,satisfied +63605,70117,Female,Loyal Customer,22,Business travel,Business,2051,2,4,4,4,2,3,2,2,2,4,4,1,4,2,22,53.0,neutral or dissatisfied +63606,11592,Male,Loyal Customer,44,Business travel,Business,468,4,4,4,4,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +63607,24641,Male,Loyal Customer,46,Business travel,Eco Plus,526,4,5,5,5,4,4,4,4,1,3,4,1,2,4,83,101.0,satisfied +63608,33704,Male,disloyal Customer,27,Business travel,Eco,805,3,3,3,3,3,3,3,3,3,1,2,3,3,3,0,0.0,neutral or dissatisfied +63609,62382,Female,Loyal Customer,52,Business travel,Business,2704,2,3,3,3,1,2,4,2,2,2,2,4,2,3,1,0.0,neutral or dissatisfied +63610,21899,Male,Loyal Customer,50,Business travel,Eco,503,2,2,2,2,2,2,2,2,5,1,4,3,4,2,12,11.0,satisfied +63611,54754,Male,Loyal Customer,9,Personal Travel,Eco,854,2,4,2,2,1,2,1,1,5,3,4,5,5,1,30,19.0,neutral or dissatisfied +63612,80004,Male,Loyal Customer,67,Personal Travel,Eco,1069,1,5,1,5,5,1,5,5,3,3,4,5,5,5,1,3.0,neutral or dissatisfied +63613,61851,Female,Loyal Customer,41,Personal Travel,Eco Plus,1379,2,5,2,3,2,5,4,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +63614,91621,Female,Loyal Customer,41,Business travel,Eco,1199,3,1,1,1,2,3,2,2,1,5,4,2,4,2,0,42.0,neutral or dissatisfied +63615,96162,Female,Loyal Customer,58,Business travel,Business,2950,3,3,3,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +63616,90405,Male,Loyal Customer,50,Personal Travel,Business,406,1,5,1,5,2,5,5,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +63617,97190,Male,Loyal Customer,38,Personal Travel,Eco,1476,3,4,3,2,1,3,1,1,5,4,5,3,4,1,0,6.0,neutral or dissatisfied +63618,103219,Male,Loyal Customer,50,Business travel,Business,2441,0,0,0,5,5,4,5,1,1,1,1,3,1,3,15,0.0,satisfied +63619,94028,Female,disloyal Customer,32,Business travel,Business,239,3,3,3,5,2,3,2,2,4,3,4,4,5,2,7,12.0,neutral or dissatisfied +63620,106986,Male,Loyal Customer,24,Personal Travel,Eco,972,1,4,1,1,4,1,4,4,5,2,5,4,4,4,21,16.0,neutral or dissatisfied +63621,125760,Male,Loyal Customer,52,Business travel,Business,861,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +63622,104365,Female,disloyal Customer,10,Personal Travel,Business,228,1,4,1,1,4,1,3,4,2,5,5,5,2,4,1,9.0,neutral or dissatisfied +63623,78286,Female,Loyal Customer,25,Business travel,Business,1598,3,4,4,4,3,3,3,4,5,4,3,3,2,3,139,128.0,neutral or dissatisfied +63624,28828,Male,Loyal Customer,23,Business travel,Business,1579,5,5,5,5,5,5,5,5,4,3,1,4,2,5,0,11.0,satisfied +63625,14982,Female,Loyal Customer,19,Personal Travel,Eco,927,3,4,3,2,5,3,5,5,5,4,4,5,5,5,0,7.0,neutral or dissatisfied +63626,3630,Male,Loyal Customer,33,Business travel,Business,431,5,5,5,5,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +63627,47518,Male,Loyal Customer,34,Personal Travel,Eco,558,4,4,4,3,5,4,5,5,2,1,3,1,4,5,0,0.0,neutral or dissatisfied +63628,23188,Female,Loyal Customer,24,Personal Travel,Eco,250,3,3,3,4,2,3,1,2,1,2,3,4,4,2,4,17.0,neutral or dissatisfied +63629,20610,Female,Loyal Customer,16,Business travel,Business,2884,3,3,3,3,3,4,3,3,3,5,1,1,3,3,63,62.0,satisfied +63630,32680,Male,disloyal Customer,24,Business travel,Business,216,4,0,4,3,2,4,2,2,4,3,3,3,4,2,32,32.0,neutral or dissatisfied +63631,2630,Female,Loyal Customer,46,Business travel,Eco Plus,280,5,3,3,3,5,4,1,5,5,5,5,1,5,1,0,0.0,satisfied +63632,109063,Female,Loyal Customer,56,Business travel,Eco,849,3,4,4,4,3,3,3,3,3,3,3,2,3,4,28,23.0,neutral or dissatisfied +63633,28136,Male,Loyal Customer,53,Business travel,Eco,834,2,2,2,2,2,2,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +63634,13644,Male,Loyal Customer,54,Business travel,Business,196,1,1,1,1,4,4,4,4,5,4,5,4,3,4,152,138.0,satisfied +63635,127544,Female,Loyal Customer,61,Business travel,Business,1009,2,1,5,5,4,2,3,2,2,2,2,1,2,2,0,6.0,neutral or dissatisfied +63636,116189,Male,Loyal Customer,35,Personal Travel,Eco,342,3,4,3,4,3,3,3,3,1,2,3,3,4,3,25,22.0,neutral or dissatisfied +63637,61457,Male,Loyal Customer,39,Business travel,Business,2419,1,1,1,1,4,3,5,5,5,5,5,5,5,5,14,1.0,satisfied +63638,82199,Male,Loyal Customer,40,Business travel,Business,1927,1,1,1,1,2,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +63639,65099,Male,Loyal Customer,39,Personal Travel,Eco,247,2,1,0,2,5,0,5,5,3,5,2,4,2,5,0,6.0,neutral or dissatisfied +63640,52325,Female,Loyal Customer,41,Business travel,Business,2948,3,1,2,1,4,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +63641,47177,Male,Loyal Customer,30,Business travel,Business,2207,1,1,1,1,1,1,1,1,1,2,3,4,4,1,76,56.0,neutral or dissatisfied +63642,34976,Female,disloyal Customer,37,Business travel,Eco,273,2,3,1,3,5,1,5,5,4,1,3,1,3,5,35,36.0,neutral or dissatisfied +63643,17170,Male,Loyal Customer,29,Business travel,Business,643,4,4,4,4,4,4,4,4,2,1,4,2,3,4,0,14.0,neutral or dissatisfied +63644,5708,Male,Loyal Customer,28,Personal Travel,Eco,436,4,5,4,3,1,4,1,1,5,3,5,3,5,1,7,0.0,neutral or dissatisfied +63645,53168,Female,disloyal Customer,20,Business travel,Eco,612,1,5,2,2,2,2,3,2,2,4,4,4,2,2,17,11.0,neutral or dissatisfied +63646,51325,Female,Loyal Customer,28,Business travel,Eco Plus,109,5,3,3,3,5,5,5,5,2,2,1,1,3,5,0,0.0,satisfied +63647,103178,Male,Loyal Customer,65,Personal Travel,Eco,491,3,4,3,4,4,3,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +63648,11248,Male,Loyal Customer,51,Personal Travel,Eco,295,2,5,2,2,1,2,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +63649,73851,Female,disloyal Customer,42,Business travel,Eco,209,3,0,3,5,1,3,1,1,2,5,2,1,4,1,2,0.0,neutral or dissatisfied +63650,89693,Female,disloyal Customer,72,Business travel,Eco,689,3,3,3,1,2,3,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +63651,66635,Female,Loyal Customer,60,Business travel,Business,802,4,4,3,4,4,5,4,3,3,3,3,4,3,5,0,3.0,satisfied +63652,120403,Female,Loyal Customer,58,Business travel,Business,1591,1,1,1,1,3,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +63653,121640,Female,Loyal Customer,58,Business travel,Business,1748,4,4,4,4,5,5,5,5,5,5,5,5,5,3,84,52.0,satisfied +63654,91647,Male,Loyal Customer,58,Personal Travel,Eco,1199,4,4,4,2,1,4,1,1,3,4,5,3,2,1,61,33.0,neutral or dissatisfied +63655,129706,Female,Loyal Customer,30,Business travel,Business,3676,1,2,2,2,1,2,1,1,4,1,3,4,4,1,38,33.0,neutral or dissatisfied +63656,66863,Female,Loyal Customer,18,Personal Travel,Eco,731,3,3,4,3,3,4,3,3,1,4,3,4,3,3,0,28.0,neutral or dissatisfied +63657,64147,Male,Loyal Customer,49,Business travel,Business,3256,4,4,4,4,2,4,4,5,5,5,5,5,5,3,21,0.0,satisfied +63658,115634,Male,disloyal Customer,20,Business travel,Eco,373,2,0,2,2,2,2,2,2,5,5,4,5,5,2,2,0.0,neutral or dissatisfied +63659,47536,Female,Loyal Customer,32,Personal Travel,Eco,584,3,5,3,4,5,3,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +63660,35780,Female,Loyal Customer,60,Business travel,Business,200,5,5,5,5,3,4,1,4,4,4,4,4,4,4,0,0.0,satisfied +63661,70956,Female,Loyal Customer,50,Business travel,Business,3480,4,4,4,4,2,4,5,5,5,4,5,5,5,3,0,14.0,satisfied +63662,129807,Male,Loyal Customer,37,Personal Travel,Eco,447,4,3,4,4,3,4,4,3,1,4,2,5,5,3,0,0.0,neutral or dissatisfied +63663,83064,Male,disloyal Customer,48,Business travel,Business,983,5,5,5,2,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +63664,65841,Female,Loyal Customer,54,Business travel,Business,1389,4,4,4,4,4,5,4,3,3,3,3,4,3,3,0,3.0,satisfied +63665,89305,Female,Loyal Customer,56,Personal Travel,Eco,453,3,4,3,4,1,4,5,3,3,3,3,1,3,2,129,131.0,neutral or dissatisfied +63666,71784,Male,Loyal Customer,59,Business travel,Business,1726,2,2,2,2,4,3,5,5,5,5,5,5,5,3,0,0.0,satisfied +63667,22119,Female,Loyal Customer,64,Personal Travel,Eco,743,2,2,2,2,5,3,3,4,4,2,4,3,4,1,57,57.0,neutral or dissatisfied +63668,54676,Male,Loyal Customer,45,Business travel,Business,2502,2,4,4,4,2,4,3,2,2,2,2,2,2,4,39,33.0,neutral or dissatisfied +63669,37994,Female,Loyal Customer,20,Business travel,Business,3648,2,2,2,2,5,5,5,5,4,3,4,1,4,5,0,0.0,satisfied +63670,61165,Male,Loyal Customer,49,Business travel,Business,967,3,3,3,3,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +63671,125175,Male,Loyal Customer,41,Business travel,Business,3328,4,4,4,4,2,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +63672,44323,Female,Loyal Customer,25,Business travel,Business,871,2,2,2,2,5,5,5,5,2,4,5,1,4,5,0,26.0,satisfied +63673,88586,Male,Loyal Customer,40,Personal Travel,Eco,545,1,4,1,2,5,1,5,5,3,1,2,2,4,5,0,1.0,neutral or dissatisfied +63674,91006,Male,Loyal Customer,35,Personal Travel,Eco,442,1,2,1,3,3,1,3,3,3,1,3,3,4,3,0,1.0,neutral or dissatisfied +63675,26121,Female,Loyal Customer,65,Personal Travel,Business,581,3,5,3,3,5,4,5,1,1,3,1,4,1,4,4,0.0,neutral or dissatisfied +63676,26604,Female,Loyal Customer,54,Business travel,Eco,406,4,1,1,1,4,4,4,3,4,4,5,4,1,4,180,196.0,satisfied +63677,126372,Female,Loyal Customer,29,Personal Travel,Eco,600,2,4,3,4,3,3,3,3,3,3,4,4,5,3,40,23.0,neutral or dissatisfied +63678,37380,Female,disloyal Customer,26,Business travel,Eco,1028,3,2,2,3,3,2,3,3,1,4,3,2,4,3,108,100.0,neutral or dissatisfied +63679,68279,Male,Loyal Customer,39,Business travel,Eco Plus,231,2,5,5,5,2,2,2,2,5,2,4,2,4,2,14,12.0,satisfied +63680,113380,Female,disloyal Customer,65,Business travel,Business,236,2,2,2,5,5,2,5,5,5,3,4,5,5,5,0,16.0,neutral or dissatisfied +63681,89499,Male,disloyal Customer,24,Business travel,Eco,684,3,3,3,3,4,3,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +63682,78436,Female,Loyal Customer,27,Business travel,Business,3044,1,1,1,1,5,5,5,5,3,2,5,4,4,5,14,10.0,satisfied +63683,44606,Male,Loyal Customer,41,Business travel,Business,566,3,3,3,3,5,2,2,4,4,4,4,1,4,4,11,11.0,satisfied +63684,69117,Female,Loyal Customer,33,Business travel,Business,1598,3,3,3,3,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +63685,120796,Female,Loyal Customer,39,Business travel,Business,2890,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +63686,113273,Male,Loyal Customer,40,Business travel,Business,1836,1,1,1,1,2,5,5,5,5,5,5,4,5,4,61,61.0,satisfied +63687,89008,Male,disloyal Customer,21,Business travel,Business,1947,5,0,5,3,4,5,4,4,4,5,4,5,5,4,1,9.0,satisfied +63688,54836,Male,Loyal Customer,47,Business travel,Business,1558,4,4,5,4,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +63689,32138,Female,disloyal Customer,23,Business travel,Eco,101,5,0,5,1,4,5,4,4,5,1,1,4,5,4,0,0.0,satisfied +63690,25456,Female,Loyal Customer,19,Personal Travel,Eco,669,3,3,3,1,3,3,3,3,4,5,5,2,2,3,1,0.0,neutral or dissatisfied +63691,3113,Female,Loyal Customer,46,Business travel,Business,3294,3,3,3,3,1,3,4,3,3,3,3,4,3,3,15,19.0,neutral or dissatisfied +63692,73124,Female,Loyal Customer,41,Personal Travel,Eco,2174,3,3,3,3,1,3,1,1,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +63693,100179,Female,Loyal Customer,9,Personal Travel,Eco,725,3,3,2,4,1,2,1,1,1,2,4,3,3,1,0,0.0,neutral or dissatisfied +63694,101810,Female,disloyal Customer,30,Business travel,Business,1680,5,5,5,4,3,5,3,3,4,4,5,5,4,3,8,0.0,satisfied +63695,96578,Male,Loyal Customer,13,Personal Travel,Eco,333,3,5,3,3,3,3,3,3,3,2,5,4,4,3,8,21.0,neutral or dissatisfied +63696,75823,Female,Loyal Customer,58,Personal Travel,Business,1440,3,3,2,4,2,2,3,4,4,2,1,1,4,4,3,0.0,neutral or dissatisfied +63697,71099,Male,Loyal Customer,9,Personal Travel,Eco Plus,802,2,5,2,5,1,2,1,1,3,5,1,4,4,1,27,9.0,neutral or dissatisfied +63698,39692,Female,Loyal Customer,40,Business travel,Business,1463,5,5,4,5,4,4,4,5,2,5,3,4,1,4,154,163.0,satisfied +63699,111361,Male,disloyal Customer,23,Business travel,Eco,1180,1,1,1,4,4,1,5,4,4,2,4,3,5,4,0,10.0,neutral or dissatisfied +63700,49107,Male,Loyal Customer,42,Business travel,Business,238,2,2,2,2,3,4,5,4,4,5,4,5,4,1,61,60.0,satisfied +63701,67612,Male,Loyal Customer,44,Business travel,Business,1205,4,4,4,4,5,4,5,4,4,4,4,3,4,3,21,4.0,satisfied +63702,99551,Male,Loyal Customer,56,Business travel,Business,1581,1,1,1,1,3,4,4,5,5,5,5,3,5,4,9,6.0,satisfied +63703,115818,Male,disloyal Customer,25,Business travel,Eco,308,2,3,2,3,2,2,2,2,2,1,4,1,3,2,19,23.0,neutral or dissatisfied +63704,96346,Male,disloyal Customer,16,Business travel,Eco,1343,3,3,3,4,1,3,1,1,1,1,4,3,3,1,0,3.0,neutral or dissatisfied +63705,66601,Female,Loyal Customer,59,Business travel,Business,3652,5,5,5,5,5,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +63706,121145,Female,disloyal Customer,48,Business travel,Business,2521,2,2,2,4,4,2,3,4,4,2,3,5,4,4,72,,neutral or dissatisfied +63707,55323,Male,Loyal Customer,41,Business travel,Business,1325,1,2,2,2,3,4,3,1,1,1,1,1,1,4,2,10.0,neutral or dissatisfied +63708,107053,Male,Loyal Customer,51,Business travel,Business,3592,1,1,1,1,3,4,1,3,3,5,3,1,3,1,43,55.0,satisfied +63709,3141,Male,Loyal Customer,51,Business travel,Business,3874,1,3,3,3,5,2,2,3,3,3,1,3,3,2,0,0.0,neutral or dissatisfied +63710,69428,Male,Loyal Customer,24,Business travel,Business,2829,4,4,4,4,5,5,5,5,3,4,1,2,1,5,0,0.0,satisfied +63711,69771,Male,Loyal Customer,34,Business travel,Business,2454,1,1,1,1,5,5,5,4,4,4,4,3,4,5,19,0.0,satisfied +63712,123295,Male,Loyal Customer,48,Business travel,Business,650,4,4,4,4,4,4,4,4,4,4,4,3,4,4,68,63.0,satisfied +63713,86028,Female,Loyal Customer,59,Personal Travel,Eco,447,4,4,4,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +63714,117471,Male,Loyal Customer,42,Personal Travel,Business,507,2,3,2,4,3,1,4,2,2,2,1,3,2,1,5,0.0,neutral or dissatisfied +63715,36412,Male,Loyal Customer,22,Business travel,Business,1619,5,5,1,5,4,4,4,4,3,4,5,1,2,4,0,0.0,satisfied +63716,113193,Female,Loyal Customer,46,Business travel,Business,3229,2,2,2,2,5,5,5,3,3,4,4,5,4,5,199,194.0,satisfied +63717,15772,Male,disloyal Customer,26,Business travel,Eco,254,2,2,2,3,4,2,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +63718,2929,Male,Loyal Customer,52,Business travel,Business,3153,2,3,3,3,4,2,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +63719,92106,Male,Loyal Customer,16,Personal Travel,Eco,1532,3,5,3,3,5,3,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +63720,86014,Female,Loyal Customer,56,Business travel,Business,1651,3,4,4,4,4,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +63721,100692,Male,Loyal Customer,43,Personal Travel,Eco,677,1,3,1,1,5,1,5,5,1,4,4,5,4,5,6,18.0,neutral or dissatisfied +63722,2999,Female,Loyal Customer,27,Business travel,Business,1739,4,3,4,4,5,5,5,5,5,4,4,3,5,5,0,0.0,satisfied +63723,108158,Female,Loyal Customer,50,Personal Travel,Eco,1166,2,4,2,1,3,4,4,5,5,2,5,5,5,4,41,30.0,neutral or dissatisfied +63724,45207,Female,Loyal Customer,38,Business travel,Business,3348,3,3,3,3,3,4,3,4,4,4,4,3,4,4,25,22.0,satisfied +63725,3269,Male,Loyal Customer,32,Business travel,Business,3498,3,5,5,5,3,3,3,3,3,1,3,4,4,3,9,33.0,neutral or dissatisfied +63726,121830,Male,disloyal Customer,33,Business travel,Business,337,3,3,3,5,2,3,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +63727,37304,Male,Loyal Customer,39,Business travel,Business,1711,3,3,3,3,1,4,5,5,5,5,5,2,5,3,0,1.0,satisfied +63728,89627,Male,Loyal Customer,45,Business travel,Business,3923,3,3,4,3,4,4,4,4,4,4,4,4,4,4,11,11.0,satisfied +63729,105987,Male,disloyal Customer,38,Business travel,Business,912,2,2,2,2,5,2,2,5,3,3,4,4,4,5,45,55.0,satisfied +63730,60279,Female,Loyal Customer,36,Personal Travel,Eco,2446,3,3,3,4,3,3,3,4,2,5,5,3,2,3,27,35.0,neutral or dissatisfied +63731,49410,Male,Loyal Customer,30,Business travel,Business,109,1,1,4,1,5,5,5,5,1,1,5,5,5,5,41,40.0,satisfied +63732,74300,Male,Loyal Customer,47,Business travel,Eco Plus,788,1,1,1,1,1,1,1,1,2,1,4,1,4,1,18,4.0,neutral or dissatisfied +63733,76911,Male,Loyal Customer,60,Business travel,Business,630,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +63734,83136,Male,Loyal Customer,27,Personal Travel,Eco,983,3,4,3,1,1,3,2,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +63735,78245,Male,Loyal Customer,19,Business travel,Eco Plus,153,2,2,2,2,2,2,1,2,2,4,3,1,4,2,70,64.0,neutral or dissatisfied +63736,123371,Male,Loyal Customer,16,Personal Travel,Eco,644,3,1,3,2,5,3,5,5,1,3,2,1,3,5,1,0.0,neutral or dissatisfied +63737,96915,Male,Loyal Customer,41,Personal Travel,Eco,1041,1,5,1,1,4,1,1,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +63738,20178,Female,Loyal Customer,54,Personal Travel,Eco,438,2,4,4,2,4,5,4,4,4,4,4,3,4,5,11,5.0,neutral or dissatisfied +63739,119714,Female,Loyal Customer,45,Business travel,Business,1325,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,5.0,satisfied +63740,73545,Female,Loyal Customer,17,Personal Travel,Eco,594,3,4,3,4,5,3,5,5,2,5,4,2,4,5,21,9.0,neutral or dissatisfied +63741,1693,Male,Loyal Customer,39,Business travel,Business,3028,1,1,1,1,5,4,5,2,2,2,2,3,2,4,7,9.0,satisfied +63742,86018,Male,Loyal Customer,31,Business travel,Business,3272,3,3,3,3,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +63743,95845,Female,Loyal Customer,53,Business travel,Business,580,2,2,2,2,4,5,4,5,5,5,5,5,5,3,2,0.0,satisfied +63744,95880,Male,Loyal Customer,37,Business travel,Business,3960,3,2,3,2,2,4,3,3,3,2,3,4,3,1,9,8.0,neutral or dissatisfied +63745,10389,Female,Loyal Customer,36,Business travel,Business,2086,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +63746,113254,Female,Loyal Customer,46,Business travel,Business,3407,0,0,0,1,2,5,5,5,5,5,5,5,5,4,10,4.0,satisfied +63747,107066,Male,Loyal Customer,69,Personal Travel,Eco,480,3,5,3,3,4,3,4,4,3,2,1,5,3,4,28,48.0,neutral or dissatisfied +63748,107500,Female,Loyal Customer,59,Personal Travel,Eco,711,5,3,5,4,3,2,1,3,3,5,4,3,3,4,21,24.0,satisfied +63749,102198,Female,Loyal Customer,42,Business travel,Business,3175,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +63750,61242,Female,Loyal Customer,46,Business travel,Eco,862,4,1,1,1,4,2,1,4,4,4,4,3,4,2,0,9.0,neutral or dissatisfied +63751,65189,Male,Loyal Customer,11,Personal Travel,Eco,247,1,3,1,2,5,1,4,5,4,4,2,1,3,5,0,0.0,neutral or dissatisfied +63752,64970,Male,Loyal Customer,53,Business travel,Business,1835,4,4,4,4,4,3,2,5,5,5,5,1,5,1,0,0.0,satisfied +63753,58805,Male,Loyal Customer,47,Personal Travel,Eco,1005,3,4,3,3,4,3,4,4,3,5,5,5,4,4,29,31.0,neutral or dissatisfied +63754,117222,Male,Loyal Customer,11,Personal Travel,Eco,370,3,2,3,2,1,3,1,1,2,1,3,4,3,1,70,71.0,neutral or dissatisfied +63755,101672,Female,Loyal Customer,51,Personal Travel,Eco,2106,4,5,4,1,3,5,1,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +63756,42167,Female,Loyal Customer,40,Business travel,Eco,550,4,4,4,4,4,4,4,4,4,2,1,1,5,4,0,0.0,satisfied +63757,29833,Female,Loyal Customer,49,Business travel,Business,261,2,2,2,2,4,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +63758,2005,Female,Loyal Customer,33,Business travel,Eco Plus,293,1,1,1,1,1,1,1,1,3,4,3,1,4,1,50,53.0,neutral or dissatisfied +63759,35398,Female,Loyal Customer,62,Business travel,Business,3375,4,1,1,1,3,3,4,4,4,4,4,2,4,4,26,36.0,neutral or dissatisfied +63760,53202,Male,Loyal Customer,41,Business travel,Eco,612,5,2,5,5,5,5,5,5,1,4,3,4,3,5,1,0.0,satisfied +63761,74244,Male,Loyal Customer,59,Personal Travel,Business,1709,3,3,4,2,3,2,4,3,3,4,3,3,3,5,0,17.0,neutral or dissatisfied +63762,77303,Female,Loyal Customer,46,Business travel,Business,2131,5,5,5,5,4,4,5,5,5,5,5,5,5,4,48,22.0,satisfied +63763,45722,Female,Loyal Customer,36,Business travel,Business,624,2,3,3,3,5,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +63764,99650,Male,Loyal Customer,52,Business travel,Business,3527,4,4,4,4,2,2,2,5,3,4,4,2,3,2,199,254.0,satisfied +63765,24061,Male,Loyal Customer,33,Personal Travel,Eco,562,1,5,1,2,1,1,1,1,3,5,5,1,3,1,0,0.0,neutral or dissatisfied +63766,125328,Female,Loyal Customer,36,Business travel,Business,599,3,3,3,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +63767,94314,Male,Loyal Customer,57,Business travel,Business,323,1,1,1,1,5,4,5,5,5,5,5,5,5,4,2,0.0,satisfied +63768,81185,Female,disloyal Customer,25,Business travel,Eco,980,3,3,3,3,5,3,5,5,3,2,3,3,3,5,62,50.0,neutral or dissatisfied +63769,11758,Female,disloyal Customer,24,Business travel,Eco,395,2,2,2,4,2,2,2,2,4,1,3,4,4,2,8,10.0,neutral or dissatisfied +63770,14764,Female,Loyal Customer,19,Personal Travel,Eco,533,2,1,2,3,2,4,4,1,4,3,4,4,4,4,156,162.0,neutral or dissatisfied +63771,49122,Male,Loyal Customer,72,Business travel,Eco,421,4,5,5,5,4,4,4,4,5,5,3,4,5,4,12,2.0,satisfied +63772,71466,Female,Loyal Customer,20,Personal Travel,Eco,867,1,4,1,3,3,1,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +63773,103098,Male,Loyal Customer,24,Personal Travel,Eco,490,4,3,4,2,2,4,1,2,1,5,5,3,3,2,16,14.0,neutral or dissatisfied +63774,95940,Male,Loyal Customer,59,Business travel,Business,2985,2,2,2,2,4,5,5,4,4,4,4,5,4,5,22,30.0,satisfied +63775,58659,Female,Loyal Customer,61,Personal Travel,Eco,867,3,2,3,4,5,3,3,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +63776,12085,Female,Loyal Customer,68,Personal Travel,Eco Plus,376,3,4,3,5,3,5,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +63777,114945,Male,Loyal Customer,43,Business travel,Business,446,2,2,2,2,4,4,4,2,2,2,2,2,2,1,0,,neutral or dissatisfied +63778,61848,Female,Loyal Customer,38,Business travel,Eco Plus,1635,3,1,1,1,3,3,3,3,2,4,4,4,3,3,17,9.0,neutral or dissatisfied +63779,11180,Male,Loyal Customer,55,Personal Travel,Eco,224,4,4,4,1,2,4,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +63780,47366,Male,Loyal Customer,54,Business travel,Business,599,5,3,3,3,4,3,2,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +63781,87668,Female,disloyal Customer,18,Business travel,Eco,606,3,3,3,4,1,3,1,1,2,3,3,4,4,1,0,11.0,neutral or dissatisfied +63782,90506,Male,Loyal Customer,40,Business travel,Business,2579,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +63783,42606,Female,Loyal Customer,64,Personal Travel,Business,546,4,3,1,3,5,4,4,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +63784,72154,Male,Loyal Customer,61,Personal Travel,Eco,731,1,2,1,3,5,1,5,5,1,1,2,2,3,5,45,29.0,neutral or dissatisfied +63785,47910,Male,disloyal Customer,21,Business travel,Eco,451,3,1,2,4,3,2,3,3,4,1,4,4,4,3,21,19.0,neutral or dissatisfied +63786,25164,Male,Loyal Customer,36,Business travel,Eco,967,4,1,1,1,4,4,4,4,1,4,3,4,3,4,23,6.0,neutral or dissatisfied +63787,120527,Female,Loyal Customer,30,Business travel,Eco,96,1,5,5,5,1,2,1,1,1,4,3,3,3,1,0,2.0,neutral or dissatisfied +63788,27500,Male,disloyal Customer,72,Business travel,Business,279,4,4,4,2,1,4,1,1,1,4,2,3,5,1,0,0.0,satisfied +63789,122781,Female,Loyal Customer,51,Business travel,Business,599,1,1,1,1,4,4,5,4,4,4,4,5,4,3,28,46.0,satisfied +63790,65904,Female,disloyal Customer,27,Business travel,Business,569,1,1,1,4,1,1,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +63791,70874,Male,Loyal Customer,18,Personal Travel,Eco,761,1,5,2,3,5,2,5,5,5,3,5,3,4,5,0,13.0,neutral or dissatisfied +63792,95957,Male,Loyal Customer,49,Personal Travel,Business,1069,2,4,2,3,5,5,4,5,5,2,5,4,5,3,8,10.0,neutral or dissatisfied +63793,104575,Male,disloyal Customer,37,Business travel,Eco,369,1,3,1,3,3,1,3,3,4,5,4,2,4,3,55,53.0,neutral or dissatisfied +63794,51292,Male,Loyal Customer,41,Business travel,Eco Plus,89,5,2,2,2,5,5,5,5,2,3,1,2,4,5,0,0.0,satisfied +63795,46408,Male,Loyal Customer,60,Business travel,Eco,649,5,1,1,1,5,5,5,5,2,5,2,5,3,5,84,92.0,satisfied +63796,48006,Male,Loyal Customer,63,Business travel,Eco Plus,412,2,5,5,5,2,2,2,2,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +63797,2370,Male,Loyal Customer,44,Business travel,Business,2574,2,2,4,2,4,4,5,5,5,5,5,3,5,4,38,34.0,satisfied +63798,79867,Female,Loyal Customer,29,Business travel,Business,1794,2,2,5,2,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +63799,103746,Male,Loyal Customer,40,Business travel,Business,2738,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,3.0,satisfied +63800,53886,Male,Loyal Customer,57,Personal Travel,Eco,224,2,5,0,1,4,0,3,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +63801,74243,Male,Loyal Customer,59,Business travel,Business,1709,3,2,2,2,5,1,1,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +63802,32589,Male,Loyal Customer,39,Business travel,Business,3483,4,4,4,4,5,5,5,5,5,5,3,3,5,2,8,9.0,satisfied +63803,29525,Male,Loyal Customer,30,Business travel,Business,3940,1,3,3,3,1,1,1,1,2,2,3,2,4,1,0,13.0,neutral or dissatisfied +63804,15535,Female,Loyal Customer,50,Business travel,Eco,812,3,5,4,4,2,5,1,3,3,3,3,2,3,4,0,0.0,satisfied +63805,20720,Female,Loyal Customer,35,Business travel,Business,765,4,4,4,4,1,5,3,5,5,5,5,4,5,4,0,0.0,satisfied +63806,36430,Female,Loyal Customer,55,Business travel,Eco,369,5,1,1,1,3,5,1,5,5,5,5,5,5,2,0,0.0,satisfied +63807,20758,Female,Loyal Customer,43,Business travel,Business,2737,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,7.0,satisfied +63808,26135,Female,Loyal Customer,29,Business travel,Business,3002,4,4,1,4,4,4,4,4,1,3,3,4,3,4,1,0.0,satisfied +63809,26416,Female,Loyal Customer,11,Personal Travel,Eco Plus,1249,2,5,2,1,2,2,2,2,5,4,4,3,4,2,106,119.0,neutral or dissatisfied +63810,42867,Female,Loyal Customer,48,Business travel,Eco,867,5,1,1,1,1,3,1,5,5,5,5,1,5,5,8,14.0,satisfied +63811,125424,Male,Loyal Customer,36,Business travel,Business,3963,3,2,4,2,1,4,3,3,3,3,3,1,3,3,6,0.0,neutral or dissatisfied +63812,31365,Female,Loyal Customer,71,Business travel,Eco Plus,692,3,5,5,5,2,4,4,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +63813,64169,Female,Loyal Customer,58,Personal Travel,Eco,989,3,5,3,4,2,5,5,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +63814,123268,Male,Loyal Customer,19,Personal Travel,Eco,631,3,4,3,4,5,3,5,5,3,4,5,5,5,5,0,7.0,neutral or dissatisfied +63815,16919,Female,Loyal Customer,36,Business travel,Eco Plus,708,4,5,5,5,4,5,4,4,3,4,3,4,2,4,20,3.0,satisfied +63816,58446,Female,Loyal Customer,41,Personal Travel,Eco,733,3,4,3,3,2,3,2,2,4,3,4,1,1,2,14,0.0,neutral or dissatisfied +63817,14419,Male,disloyal Customer,21,Business travel,Eco,585,3,3,3,2,2,3,2,2,3,2,1,5,4,2,0,0.0,neutral or dissatisfied +63818,952,Female,Loyal Customer,57,Business travel,Business,1583,0,0,0,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +63819,126105,Male,disloyal Customer,52,Business travel,Eco,600,1,2,1,3,3,1,3,3,2,4,3,4,4,3,2,9.0,neutral or dissatisfied +63820,112328,Female,disloyal Customer,20,Business travel,Eco,846,1,1,1,5,1,1,1,1,3,5,4,3,5,1,8,0.0,neutral or dissatisfied +63821,56857,Female,Loyal Customer,46,Business travel,Business,2565,2,2,2,2,5,5,5,5,2,4,5,5,4,5,0,0.0,satisfied +63822,8750,Male,disloyal Customer,38,Business travel,Business,1147,4,4,4,5,4,4,3,4,3,2,5,3,4,4,1,0.0,satisfied +63823,49808,Male,disloyal Customer,39,Business travel,Eco,209,4,0,4,4,4,4,1,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +63824,75941,Male,Loyal Customer,64,Personal Travel,Business,297,2,4,2,3,5,4,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +63825,78510,Female,disloyal Customer,30,Business travel,Eco,526,2,4,2,3,2,2,2,2,4,5,3,3,3,2,22,22.0,neutral or dissatisfied +63826,75542,Male,Loyal Customer,59,Business travel,Business,3918,1,1,4,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +63827,67413,Male,Loyal Customer,25,Business travel,Eco,641,3,4,4,4,3,2,3,1,4,3,2,3,3,3,148,145.0,neutral or dissatisfied +63828,27499,Male,Loyal Customer,44,Business travel,Business,2883,5,5,5,5,4,1,5,4,4,4,4,2,4,3,3,0.0,satisfied +63829,97614,Female,Loyal Customer,58,Business travel,Business,3213,2,2,2,2,2,4,4,3,3,3,3,3,3,5,1,11.0,satisfied +63830,107383,Male,Loyal Customer,57,Business travel,Business,3470,5,5,5,5,4,4,5,2,2,2,2,3,2,3,6,0.0,satisfied +63831,61959,Female,Loyal Customer,64,Personal Travel,Eco,2161,4,5,4,2,3,4,5,5,5,4,5,4,5,5,16,45.0,satisfied +63832,52036,Male,Loyal Customer,60,Business travel,Eco Plus,328,2,4,4,4,2,2,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +63833,65569,Male,Loyal Customer,48,Business travel,Business,3076,2,2,4,2,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +63834,106754,Male,Loyal Customer,44,Business travel,Business,605,1,0,0,3,2,3,3,3,3,0,2,3,3,3,0,7.0,neutral or dissatisfied +63835,65374,Female,Loyal Customer,37,Business travel,Business,631,2,2,2,2,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +63836,126065,Male,Loyal Customer,56,Business travel,Business,600,2,1,2,2,3,4,4,4,4,4,4,4,4,4,92,82.0,satisfied +63837,74742,Male,Loyal Customer,53,Personal Travel,Eco,1431,1,5,1,3,4,1,4,4,3,2,3,5,5,4,0,0.0,neutral or dissatisfied +63838,47589,Female,Loyal Customer,44,Business travel,Eco,1211,4,4,4,4,4,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +63839,79961,Male,Loyal Customer,18,Business travel,Eco,950,4,1,1,1,4,4,1,4,3,5,4,2,3,4,0,0.0,neutral or dissatisfied +63840,84964,Female,Loyal Customer,47,Personal Travel,Eco Plus,534,4,5,4,3,5,4,4,1,1,4,1,3,1,5,0,3.0,neutral or dissatisfied +63841,220,Male,Loyal Customer,31,Personal Travel,Eco,290,3,4,3,3,3,3,3,3,1,4,4,5,4,3,25,42.0,neutral or dissatisfied +63842,34898,Male,Loyal Customer,49,Business travel,Eco,395,2,2,3,2,2,2,2,2,3,5,5,3,3,2,39,19.0,satisfied +63843,103183,Male,Loyal Customer,33,Business travel,Business,2445,3,3,3,3,5,5,5,5,3,3,4,5,4,5,18,38.0,satisfied +63844,62066,Male,Loyal Customer,43,Personal Travel,Eco,2586,2,4,2,4,5,2,4,5,4,4,3,3,4,5,54,48.0,neutral or dissatisfied +63845,78298,Male,Loyal Customer,41,Personal Travel,Eco,1598,4,5,4,3,5,4,3,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +63846,10184,Female,Loyal Customer,53,Business travel,Business,3919,2,2,2,2,5,5,5,5,5,5,5,5,5,4,20,18.0,satisfied +63847,12447,Female,Loyal Customer,35,Personal Travel,Eco,253,4,4,4,3,1,4,5,1,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +63848,39597,Male,Loyal Customer,43,Business travel,Eco,545,5,4,4,4,5,5,5,5,5,2,4,2,3,5,0,0.0,satisfied +63849,127505,Male,Loyal Customer,23,Personal Travel,Eco,2075,2,4,2,5,2,2,4,2,3,5,1,2,5,2,6,10.0,neutral or dissatisfied +63850,43409,Female,disloyal Customer,39,Business travel,Business,402,4,4,4,3,4,4,1,4,1,4,4,5,3,4,0,0.0,satisfied +63851,56044,Female,Loyal Customer,30,Business travel,Business,2586,1,1,1,1,4,4,4,5,4,4,4,4,5,4,0,0.0,satisfied +63852,72649,Female,Loyal Customer,26,Personal Travel,Eco,985,3,4,3,4,3,3,3,3,4,4,5,4,4,3,13,8.0,neutral or dissatisfied +63853,22532,Female,Loyal Customer,29,Personal Travel,Eco Plus,143,2,5,2,5,2,2,2,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +63854,69494,Female,Loyal Customer,63,Personal Travel,Eco Plus,1096,1,0,1,5,2,4,5,2,2,1,4,1,2,4,0,24.0,neutral or dissatisfied +63855,56565,Female,disloyal Customer,19,Business travel,Business,1023,5,0,5,1,1,5,4,1,3,5,5,4,4,1,0,0.0,satisfied +63856,89640,Male,disloyal Customer,26,Business travel,Business,1096,4,4,4,3,1,4,1,1,1,2,4,1,3,1,0,0.0,neutral or dissatisfied +63857,49841,Female,Loyal Customer,46,Business travel,Business,337,4,4,4,4,2,4,3,5,5,5,5,3,5,3,0,0.0,satisfied +63858,112291,Male,Loyal Customer,35,Business travel,Business,1703,4,4,4,4,5,4,4,4,4,4,4,3,4,3,7,0.0,satisfied +63859,74639,Female,Loyal Customer,44,Business travel,Eco,1171,2,4,4,4,2,3,4,2,2,2,2,4,2,3,10,6.0,neutral or dissatisfied +63860,37858,Male,Loyal Customer,36,Business travel,Eco,1065,2,3,3,3,2,2,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +63861,9028,Female,Loyal Customer,29,Business travel,Business,3079,2,2,2,2,4,5,4,4,3,3,4,4,4,4,0,0.0,satisfied +63862,58252,Female,disloyal Customer,39,Business travel,Business,925,3,3,3,4,2,3,2,2,1,5,4,2,4,2,0,0.0,neutral or dissatisfied +63863,55060,Male,Loyal Customer,41,Business travel,Business,1379,1,1,1,1,4,4,4,4,4,4,4,3,4,5,68,51.0,satisfied +63864,87212,Female,Loyal Customer,51,Personal Travel,Eco,946,2,4,2,4,3,3,3,5,5,2,4,2,5,4,4,0.0,neutral or dissatisfied +63865,12415,Male,Loyal Customer,54,Personal Travel,Eco,201,5,4,5,3,2,5,2,2,1,4,4,1,1,2,1,0.0,satisfied +63866,91141,Male,Loyal Customer,60,Personal Travel,Eco,404,3,3,3,4,3,3,3,3,2,2,4,2,4,3,15,0.0,neutral or dissatisfied +63867,122272,Female,Loyal Customer,69,Personal Travel,Eco,544,3,2,3,3,3,4,4,2,2,3,3,3,2,1,0,0.0,neutral or dissatisfied +63868,68821,Male,Loyal Customer,57,Business travel,Eco Plus,461,5,2,2,2,5,5,5,5,4,1,5,3,3,5,0,0.0,satisfied +63869,119881,Female,Loyal Customer,27,Personal Travel,Eco,912,2,3,2,4,1,2,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +63870,18388,Female,Loyal Customer,19,Personal Travel,Eco,493,3,5,3,1,1,3,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +63871,115396,Female,Loyal Customer,35,Business travel,Business,447,1,4,4,4,1,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +63872,123260,Male,Loyal Customer,58,Personal Travel,Eco,590,1,4,1,3,2,1,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +63873,109764,Male,disloyal Customer,36,Business travel,Business,1092,2,3,3,3,1,3,3,1,4,3,5,4,5,1,20,15.0,neutral or dissatisfied +63874,6644,Male,Loyal Customer,58,Business travel,Business,3224,4,4,4,4,5,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +63875,74025,Female,Loyal Customer,27,Business travel,Business,1471,1,1,1,1,3,4,3,3,3,3,4,4,4,3,0,0.0,satisfied +63876,85534,Female,Loyal Customer,50,Business travel,Business,153,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +63877,79837,Female,Loyal Customer,28,Business travel,Business,1069,2,2,2,2,2,3,2,2,3,2,4,3,3,2,0,13.0,neutral or dissatisfied +63878,40458,Female,disloyal Customer,25,Business travel,Eco,150,2,0,2,3,4,2,2,4,4,1,3,1,4,4,0,0.0,neutral or dissatisfied +63879,107620,Male,Loyal Customer,30,Business travel,Business,423,4,5,5,5,4,4,4,4,2,3,3,3,4,4,40,39.0,neutral or dissatisfied +63880,60903,Male,disloyal Customer,24,Business travel,Business,589,4,0,3,2,4,3,4,4,5,4,5,5,4,4,37,33.0,satisfied +63881,28140,Female,Loyal Customer,41,Business travel,Business,569,4,5,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +63882,7252,Female,Loyal Customer,68,Personal Travel,Eco,116,3,4,3,3,1,3,2,4,4,3,4,2,4,5,0,19.0,neutral or dissatisfied +63883,100943,Male,Loyal Customer,47,Business travel,Business,1142,5,4,5,5,4,5,5,5,3,4,5,5,5,5,88,141.0,satisfied +63884,115796,Female,Loyal Customer,53,Business travel,Eco,308,4,1,1,1,4,4,4,4,4,4,4,4,4,1,38,39.0,satisfied +63885,8056,Male,Loyal Customer,48,Business travel,Business,3655,3,3,3,3,2,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +63886,38645,Female,Loyal Customer,26,Business travel,Business,2611,4,4,4,4,4,4,4,4,3,5,5,2,2,4,6,9.0,satisfied +63887,84296,Female,Loyal Customer,34,Business travel,Business,235,2,5,5,5,4,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +63888,65891,Female,Loyal Customer,15,Business travel,Business,569,2,2,2,2,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +63889,25573,Male,Loyal Customer,43,Business travel,Eco,696,5,1,1,1,5,5,5,5,3,3,2,4,4,5,60,47.0,satisfied +63890,41852,Male,Loyal Customer,52,Business travel,Eco,483,2,5,5,5,2,2,2,2,4,5,4,1,3,2,5,0.0,neutral or dissatisfied +63891,32763,Female,Loyal Customer,50,Business travel,Eco,101,2,2,2,2,1,2,1,2,2,2,2,4,2,2,0,2.0,satisfied +63892,31375,Female,Loyal Customer,24,Personal Travel,Eco,977,1,4,0,4,3,0,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +63893,117034,Female,disloyal Customer,22,Business travel,Eco,647,1,4,1,4,4,1,4,4,1,1,3,1,4,4,0,0.0,neutral or dissatisfied +63894,122448,Male,Loyal Customer,53,Business travel,Business,575,5,5,5,5,3,5,5,4,4,4,4,3,4,3,69,64.0,satisfied +63895,59426,Female,disloyal Customer,29,Business travel,Eco Plus,2556,1,1,1,3,2,1,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +63896,9679,Female,disloyal Customer,25,Business travel,Eco,277,2,2,2,4,2,2,1,2,2,4,3,1,3,2,0,29.0,neutral or dissatisfied +63897,89580,Female,Loyal Customer,36,Business travel,Business,3322,4,4,4,4,3,5,5,3,3,4,3,3,3,5,25,42.0,satisfied +63898,124128,Male,disloyal Customer,36,Business travel,Eco,129,4,4,4,2,5,4,5,5,3,5,3,4,1,5,0,,neutral or dissatisfied +63899,113953,Male,disloyal Customer,30,Business travel,Business,1844,1,1,1,1,4,1,4,4,4,3,4,3,5,4,3,6.0,neutral or dissatisfied +63900,119214,Male,Loyal Customer,68,Personal Travel,Eco,257,0,4,0,3,5,0,5,5,5,5,2,3,5,5,6,18.0,satisfied +63901,78808,Male,Loyal Customer,10,Personal Travel,Eco,447,2,5,2,1,4,2,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +63902,27103,Male,Loyal Customer,33,Business travel,Eco,1721,1,0,0,4,5,0,5,5,3,4,4,4,4,5,3,5.0,neutral or dissatisfied +63903,67895,Female,Loyal Customer,32,Personal Travel,Eco,1235,1,1,1,2,3,1,3,3,2,4,2,2,1,3,0,0.0,neutral or dissatisfied +63904,51711,Male,Loyal Customer,77,Business travel,Business,2039,1,1,1,1,2,1,1,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +63905,108932,Male,Loyal Customer,62,Personal Travel,Eco,1075,2,4,2,1,5,2,5,5,3,4,4,4,5,5,88,88.0,neutral or dissatisfied +63906,69332,Female,Loyal Customer,19,Business travel,Business,1968,3,2,3,3,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +63907,80167,Female,Loyal Customer,60,Business travel,Business,2586,2,5,5,5,2,2,2,3,1,4,4,2,1,2,0,0.0,neutral or dissatisfied +63908,123968,Male,Loyal Customer,52,Business travel,Business,184,0,5,0,3,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +63909,10412,Male,Loyal Customer,55,Business travel,Business,429,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +63910,114315,Male,Loyal Customer,48,Personal Travel,Eco,819,4,3,4,4,5,4,5,5,1,1,4,1,3,5,0,0.0,neutral or dissatisfied +63911,79495,Female,Loyal Customer,57,Business travel,Business,3173,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +63912,97057,Female,Loyal Customer,51,Business travel,Business,3510,4,4,4,4,2,4,4,5,5,4,5,5,5,3,18,29.0,satisfied +63913,127656,Male,disloyal Customer,30,Business travel,Business,2153,2,2,2,3,5,2,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +63914,15479,Male,Loyal Customer,29,Personal Travel,Eco,164,1,5,1,4,4,1,3,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +63915,707,Male,disloyal Customer,55,Business travel,Business,113,4,4,4,3,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +63916,87600,Male,Loyal Customer,53,Business travel,Business,432,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +63917,109184,Male,disloyal Customer,22,Business travel,Eco,483,4,0,4,4,5,4,5,5,3,5,4,5,4,5,0,0.0,satisfied +63918,71427,Female,Loyal Customer,43,Business travel,Eco,867,1,4,4,4,4,4,3,1,1,1,1,1,1,2,0,18.0,neutral or dissatisfied +63919,67079,Female,disloyal Customer,35,Business travel,Business,964,1,1,1,3,4,1,2,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +63920,123299,Male,Loyal Customer,46,Business travel,Business,1816,2,2,2,2,2,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +63921,10197,Female,Loyal Customer,38,Business travel,Business,201,0,5,0,4,4,5,5,4,4,4,4,5,4,3,9,11.0,satisfied +63922,66389,Female,Loyal Customer,50,Business travel,Business,1562,3,3,1,3,3,5,4,2,2,2,2,3,2,5,6,2.0,satisfied +63923,108269,Male,Loyal Customer,9,Personal Travel,Eco,895,1,5,1,2,2,1,2,2,5,4,4,4,4,2,98,95.0,neutral or dissatisfied +63924,72646,Female,Loyal Customer,17,Personal Travel,Eco,1119,1,4,1,3,5,1,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +63925,16351,Male,Loyal Customer,26,Personal Travel,Eco,160,3,1,3,3,5,3,5,5,4,5,3,4,4,5,7,0.0,neutral or dissatisfied +63926,90794,Male,Loyal Customer,48,Business travel,Business,545,3,3,3,3,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +63927,32188,Female,Loyal Customer,38,Business travel,Eco,102,3,4,4,4,3,3,3,3,3,2,2,3,1,3,0,1.0,satisfied +63928,1710,Female,Loyal Customer,56,Business travel,Business,364,2,2,2,2,5,5,4,3,3,3,3,5,3,5,0,3.0,satisfied +63929,67245,Female,Loyal Customer,24,Personal Travel,Eco,1119,2,4,2,3,3,2,2,3,4,5,5,4,4,3,57,54.0,neutral or dissatisfied +63930,72485,Female,Loyal Customer,41,Business travel,Business,2656,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +63931,51031,Male,Loyal Customer,20,Personal Travel,Eco,78,3,5,3,3,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +63932,49874,Male,Loyal Customer,37,Business travel,Business,372,2,5,5,5,3,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +63933,89792,Female,Loyal Customer,18,Personal Travel,Eco,1096,2,1,2,4,5,2,5,5,1,4,3,1,3,5,57,39.0,neutral or dissatisfied +63934,24036,Male,Loyal Customer,65,Personal Travel,Eco,562,3,5,3,4,5,3,5,5,3,5,4,5,5,5,21,26.0,neutral or dissatisfied +63935,815,Male,Loyal Customer,40,Business travel,Business,158,0,4,0,5,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +63936,85172,Male,Loyal Customer,58,Business travel,Business,1282,3,3,3,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +63937,126534,Male,Loyal Customer,41,Business travel,Business,644,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +63938,59334,Male,Loyal Customer,32,Business travel,Business,2367,5,1,5,5,4,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +63939,87859,Male,Loyal Customer,14,Personal Travel,Eco,214,3,1,3,1,2,3,2,2,4,4,1,3,2,2,0,0.0,neutral or dissatisfied +63940,22789,Male,Loyal Customer,60,Business travel,Business,302,2,2,4,2,2,2,5,4,4,4,4,2,4,4,33,19.0,satisfied +63941,88641,Female,Loyal Customer,60,Personal Travel,Eco,581,2,4,2,4,3,3,4,2,2,2,2,1,2,2,3,3.0,neutral or dissatisfied +63942,36448,Female,Loyal Customer,13,Personal Travel,Eco,1368,1,4,0,3,2,0,2,2,5,3,5,5,4,2,0,3.0,neutral or dissatisfied +63943,25424,Female,Loyal Customer,51,Business travel,Business,2441,1,1,5,1,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +63944,63531,Female,Loyal Customer,42,Business travel,Business,3569,2,2,2,2,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +63945,119013,Male,Loyal Customer,20,Business travel,Business,2409,5,5,5,5,5,4,5,5,3,3,4,3,5,5,1,4.0,satisfied +63946,115583,Female,Loyal Customer,42,Business travel,Business,3097,2,1,1,1,5,4,3,2,2,2,2,4,2,4,4,5.0,neutral or dissatisfied +63947,45517,Male,Loyal Customer,24,Business travel,Eco,689,1,4,2,4,1,1,2,1,3,1,4,2,3,1,0,0.0,neutral or dissatisfied +63948,128078,Male,Loyal Customer,43,Business travel,Business,2860,5,5,5,5,4,4,4,5,3,3,5,4,3,4,26,19.0,satisfied +63949,40899,Female,Loyal Customer,35,Personal Travel,Eco,501,3,5,3,3,5,3,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +63950,79126,Male,Loyal Customer,57,Personal Travel,Eco,306,3,4,3,2,5,3,2,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +63951,84023,Female,Loyal Customer,64,Personal Travel,Eco,321,4,3,4,3,5,3,4,2,2,4,3,2,2,1,0,0.0,satisfied +63952,84821,Female,disloyal Customer,30,Business travel,Eco,547,3,3,3,2,4,3,3,4,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +63953,50496,Male,Loyal Customer,41,Personal Travel,Eco,109,3,2,3,4,4,3,3,4,4,5,3,4,4,4,30,31.0,neutral or dissatisfied +63954,81772,Female,Loyal Customer,34,Business travel,Business,3141,3,3,3,3,4,4,4,3,4,4,4,4,3,4,164,143.0,satisfied +63955,35919,Female,Loyal Customer,16,Business travel,Eco Plus,2248,0,3,0,2,2,0,2,2,3,2,4,3,4,2,0,0.0,satisfied +63956,25669,Female,disloyal Customer,24,Business travel,Business,761,5,4,5,3,4,5,5,4,2,4,1,4,4,4,3,0.0,satisfied +63957,36349,Female,Loyal Customer,49,Business travel,Eco Plus,187,4,4,4,4,3,4,4,4,4,4,4,3,4,1,13,10.0,neutral or dissatisfied +63958,68301,Female,disloyal Customer,44,Business travel,Eco,1797,1,1,1,2,2,1,3,2,2,2,1,1,2,2,0,0.0,neutral or dissatisfied +63959,19152,Male,Loyal Customer,42,Business travel,Business,321,1,2,2,2,4,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +63960,117426,Male,Loyal Customer,38,Business travel,Eco,1060,5,4,4,4,5,5,5,5,3,4,1,1,4,5,0,0.0,satisfied +63961,25363,Male,Loyal Customer,33,Business travel,Business,2292,5,5,5,5,3,3,3,3,1,5,2,4,3,3,17,0.0,satisfied +63962,29343,Male,Loyal Customer,15,Business travel,Eco Plus,550,4,5,4,5,4,4,3,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +63963,126079,Female,Loyal Customer,42,Business travel,Business,600,2,5,5,5,5,4,3,2,2,2,2,3,2,2,1,0.0,neutral or dissatisfied +63964,121357,Female,Loyal Customer,68,Personal Travel,Eco Plus,430,1,4,3,3,2,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +63965,76056,Male,Loyal Customer,24,Business travel,Business,669,4,4,4,4,5,5,5,5,5,5,5,5,4,5,64,64.0,satisfied +63966,38727,Male,Loyal Customer,41,Business travel,Business,3854,0,1,1,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +63967,123696,Male,Loyal Customer,25,Personal Travel,Eco,214,1,5,1,2,3,1,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +63968,86367,Female,Loyal Customer,56,Business travel,Business,2181,4,4,4,4,2,4,5,4,4,4,4,5,4,3,19,20.0,satisfied +63969,65847,Male,disloyal Customer,25,Business travel,Eco,989,4,4,4,3,5,4,5,5,2,1,2,2,5,5,0,0.0,satisfied +63970,2625,Female,Loyal Customer,43,Business travel,Business,304,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +63971,15274,Male,Loyal Customer,52,Business travel,Business,460,1,0,0,4,3,4,4,4,4,0,1,1,4,3,0,0.0,neutral or dissatisfied +63972,2090,Male,Loyal Customer,46,Personal Travel,Eco,812,3,2,3,4,3,3,3,3,1,1,3,1,3,3,0,0.0,neutral or dissatisfied +63973,126056,Male,disloyal Customer,27,Business travel,Business,507,2,2,2,1,5,2,5,5,3,3,4,5,5,5,0,5.0,neutral or dissatisfied +63974,104779,Female,Loyal Customer,7,Personal Travel,Business,587,4,4,4,3,2,4,4,2,4,2,4,5,5,2,73,98.0,neutral or dissatisfied +63975,14518,Male,Loyal Customer,25,Business travel,Eco,310,4,4,4,4,4,4,5,4,2,3,2,3,2,4,24,25.0,satisfied +63976,8517,Female,Loyal Customer,26,Personal Travel,Eco,862,0,4,0,2,1,0,1,1,4,5,4,5,4,1,0,4.0,satisfied +63977,34611,Female,Loyal Customer,26,Personal Travel,Eco,1576,2,5,3,1,2,3,2,2,3,5,5,3,5,2,1,8.0,neutral or dissatisfied +63978,41047,Male,Loyal Customer,41,Personal Travel,Eco,1086,3,5,3,3,1,3,1,1,3,2,4,5,5,1,0,13.0,neutral or dissatisfied +63979,39890,Male,Loyal Customer,7,Personal Travel,Eco,272,4,4,4,3,2,4,2,2,3,2,4,3,5,2,0,5.0,neutral or dissatisfied +63980,21673,Female,disloyal Customer,22,Business travel,Eco,746,0,0,0,3,3,0,3,3,2,3,5,2,2,3,26,3.0,satisfied +63981,100687,Female,Loyal Customer,38,Business travel,Business,489,2,2,3,2,4,2,5,3,3,3,3,1,3,4,17,19.0,satisfied +63982,90998,Male,Loyal Customer,20,Personal Travel,Eco,271,3,0,3,2,2,3,5,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +63983,3876,Male,Loyal Customer,39,Business travel,Business,1819,5,5,5,5,5,4,4,5,5,4,5,3,5,5,61,75.0,satisfied +63984,76958,Female,disloyal Customer,14,Business travel,Eco,1990,2,2,2,3,2,2,2,2,2,2,2,1,4,2,0,0.0,neutral or dissatisfied +63985,102903,Female,Loyal Customer,17,Personal Travel,Eco,1037,3,1,3,4,4,3,4,4,4,4,4,2,4,4,0,12.0,neutral or dissatisfied +63986,63297,Male,disloyal Customer,42,Business travel,Business,372,1,1,1,5,1,1,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +63987,63658,Female,Loyal Customer,42,Business travel,Business,2405,3,3,2,3,4,4,5,5,5,5,5,5,5,4,29,19.0,satisfied +63988,29754,Female,Loyal Customer,55,Business travel,Business,2018,1,0,5,0,4,4,4,1,1,1,1,3,1,4,0,0.0,satisfied +63989,92297,Male,Loyal Customer,52,Personal Travel,Eco,1814,2,5,2,1,3,2,3,3,5,4,3,4,4,3,0,0.0,neutral or dissatisfied +63990,49165,Female,Loyal Customer,60,Business travel,Eco,372,5,2,2,2,2,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +63991,112299,Male,disloyal Customer,49,Business travel,Eco,1102,4,4,4,1,1,4,1,1,4,4,1,4,1,1,56,43.0,neutral or dissatisfied +63992,94081,Male,Loyal Customer,46,Business travel,Business,2551,1,1,1,1,3,5,5,3,3,3,3,5,3,5,3,0.0,satisfied +63993,82236,Male,Loyal Customer,65,Personal Travel,Eco,405,2,1,2,4,5,2,5,5,1,2,3,1,4,5,3,0.0,neutral or dissatisfied +63994,77681,Female,Loyal Customer,29,Business travel,Business,2611,2,2,2,2,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +63995,109831,Male,disloyal Customer,29,Business travel,Business,971,4,4,4,4,4,4,2,4,3,3,5,4,5,4,0,0.0,satisfied +63996,44998,Female,Loyal Customer,66,Business travel,Business,2573,3,5,5,5,1,2,2,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +63997,33657,Male,Loyal Customer,48,Business travel,Eco Plus,399,5,4,4,4,5,5,5,5,5,3,3,3,2,5,0,0.0,satisfied +63998,56141,Male,disloyal Customer,28,Business travel,Business,1504,1,1,1,1,5,1,1,5,4,2,4,5,4,5,24,0.0,neutral or dissatisfied +63999,29717,Male,disloyal Customer,33,Business travel,Business,2777,1,1,1,1,4,1,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +64000,27055,Female,Loyal Customer,47,Personal Travel,Eco,1489,5,5,5,4,5,3,5,2,2,5,2,1,2,1,0,0.0,satisfied +64001,19965,Male,Loyal Customer,32,Business travel,Business,1736,4,4,4,4,3,2,3,3,2,5,4,3,5,3,38,31.0,satisfied +64002,52758,Female,Loyal Customer,14,Personal Travel,Business,1874,3,1,4,4,4,4,4,4,3,1,3,3,3,4,12,0.0,neutral or dissatisfied +64003,59873,Female,disloyal Customer,29,Business travel,Business,1068,3,3,3,3,2,3,2,2,3,5,5,3,4,2,95,77.0,neutral or dissatisfied +64004,67553,Male,Loyal Customer,21,Personal Travel,Business,1438,3,2,3,4,5,3,5,5,3,3,4,1,3,5,20,36.0,neutral or dissatisfied +64005,108779,Female,Loyal Customer,61,Business travel,Eco,404,2,5,5,5,4,4,3,2,2,2,2,2,2,2,7,0.0,neutral or dissatisfied +64006,89158,Male,Loyal Customer,33,Personal Travel,Eco,2139,1,5,0,3,5,0,5,5,5,5,3,3,5,5,0,0.0,neutral or dissatisfied +64007,119772,Female,Loyal Customer,48,Business travel,Business,912,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,2.0,satisfied +64008,12490,Male,Loyal Customer,45,Business travel,Eco Plus,253,2,3,3,3,2,2,2,2,2,3,3,3,3,2,0,0.0,neutral or dissatisfied +64009,98466,Male,Loyal Customer,54,Business travel,Business,3039,2,3,5,5,3,2,4,2,1,4,3,4,2,4,326,317.0,neutral or dissatisfied +64010,1828,Female,Loyal Customer,50,Personal Travel,Eco,408,4,4,4,4,3,5,4,4,4,4,3,4,4,5,0,2.0,neutral or dissatisfied +64011,30088,Male,Loyal Customer,56,Personal Travel,Eco,160,3,5,0,2,0,2,2,4,4,4,4,2,4,2,319,317.0,neutral or dissatisfied +64012,85944,Male,Loyal Customer,41,Business travel,Business,3968,3,3,3,3,5,4,4,5,5,5,5,5,5,4,6,13.0,satisfied +64013,21936,Male,Loyal Customer,42,Business travel,Eco,500,4,5,5,5,4,4,4,4,5,3,4,5,5,4,0,0.0,satisfied +64014,121026,Female,Loyal Customer,41,Personal Travel,Eco,861,1,4,1,5,2,1,5,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +64015,117732,Male,disloyal Customer,28,Business travel,Business,833,4,4,4,1,3,4,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +64016,18568,Male,disloyal Customer,25,Business travel,Eco,383,1,2,1,3,3,1,3,3,2,3,4,4,3,3,0,8.0,neutral or dissatisfied +64017,93756,Male,Loyal Customer,40,Business travel,Business,2354,1,1,1,1,5,3,3,1,1,1,1,4,1,4,26,21.0,neutral or dissatisfied +64018,70279,Male,Loyal Customer,44,Business travel,Business,1872,3,3,4,3,4,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +64019,21240,Female,Loyal Customer,39,Personal Travel,Eco,317,2,4,3,1,1,3,1,1,3,1,1,1,5,1,0,0.0,neutral or dissatisfied +64020,24716,Male,Loyal Customer,47,Personal Travel,Eco,549,1,0,1,1,4,1,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +64021,8679,Female,Loyal Customer,34,Business travel,Business,2169,2,5,5,5,1,3,4,2,2,2,2,2,2,3,9,8.0,neutral or dissatisfied +64022,91405,Male,Loyal Customer,70,Personal Travel,Eco,2342,4,3,4,3,4,4,4,4,2,1,4,3,3,4,0,0.0,satisfied +64023,43576,Female,Loyal Customer,31,Business travel,Business,1499,1,1,1,1,4,4,4,4,4,5,4,5,1,4,11,0.0,satisfied +64024,44955,Male,Loyal Customer,8,Personal Travel,Eco,334,1,4,1,3,5,1,5,5,4,2,3,1,3,5,69,49.0,neutral or dissatisfied +64025,58240,Female,Loyal Customer,58,Business travel,Business,3090,5,3,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +64026,83081,Female,Loyal Customer,40,Business travel,Eco,745,4,1,1,1,4,4,4,4,2,5,4,5,3,4,0,0.0,satisfied +64027,68881,Male,disloyal Customer,21,Business travel,Business,936,5,0,5,3,1,5,1,1,3,2,4,4,4,1,0,10.0,satisfied +64028,88137,Female,Loyal Customer,27,Business travel,Business,2680,3,3,3,3,4,4,4,4,3,5,4,4,5,4,42,33.0,satisfied +64029,13998,Female,disloyal Customer,39,Business travel,Eco,160,2,5,2,3,5,2,5,5,3,3,4,3,3,5,11,0.0,neutral or dissatisfied +64030,115314,Male,Loyal Customer,42,Business travel,Eco,447,3,2,3,2,3,3,3,3,4,1,3,4,2,3,30,24.0,neutral or dissatisfied +64031,106259,Male,disloyal Customer,23,Business travel,Eco,1500,5,5,5,4,4,5,2,4,5,4,4,4,5,4,0,0.0,satisfied +64032,88572,Female,Loyal Customer,44,Personal Travel,Eco,444,3,4,1,3,3,3,5,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +64033,34916,Male,Loyal Customer,26,Business travel,Business,2450,3,4,4,4,1,1,3,1,4,2,2,4,3,1,0,0.0,neutral or dissatisfied +64034,111207,Female,Loyal Customer,15,Business travel,Business,1546,3,3,3,3,4,4,4,4,3,3,4,3,4,4,20,16.0,satisfied +64035,17875,Male,Loyal Customer,56,Business travel,Business,2312,4,3,3,3,2,4,3,4,4,4,4,4,4,3,1,30.0,neutral or dissatisfied +64036,27372,Male,Loyal Customer,30,Business travel,Business,2065,1,1,1,1,5,5,5,5,4,4,2,2,2,5,0,0.0,satisfied +64037,29047,Female,Loyal Customer,68,Personal Travel,Eco,954,2,2,2,3,5,4,3,4,4,2,4,2,4,3,0,5.0,neutral or dissatisfied +64038,49020,Male,disloyal Customer,26,Business travel,Eco,109,5,0,5,4,4,5,4,4,5,3,3,1,1,4,8,15.0,satisfied +64039,74047,Female,disloyal Customer,20,Business travel,Eco,1194,2,2,2,3,2,2,2,2,2,3,3,3,4,2,0,41.0,neutral or dissatisfied +64040,56821,Female,Loyal Customer,39,Business travel,Eco,1005,2,1,1,1,2,2,2,2,3,4,3,1,3,2,99,82.0,neutral or dissatisfied +64041,27479,Male,disloyal Customer,47,Business travel,Eco,978,2,2,2,3,1,2,1,1,1,1,3,2,3,1,0,0.0,neutral or dissatisfied +64042,7521,Male,disloyal Customer,29,Business travel,Business,762,1,1,1,1,3,1,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +64043,36286,Female,Loyal Customer,47,Business travel,Business,395,5,5,5,5,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +64044,689,Female,Loyal Customer,43,Business travel,Business,3102,0,4,0,1,3,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +64045,8282,Male,Loyal Customer,62,Personal Travel,Eco,294,4,5,4,2,5,4,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +64046,56967,Male,disloyal Customer,33,Business travel,Eco,768,2,2,2,4,2,4,4,1,3,3,3,4,4,4,11,8.0,neutral or dissatisfied +64047,34272,Male,Loyal Customer,29,Business travel,Business,496,5,5,5,5,2,2,2,2,5,2,5,5,1,2,45,29.0,satisfied +64048,3958,Female,Loyal Customer,60,Personal Travel,Eco,764,1,2,0,2,3,3,2,2,2,0,2,3,2,4,19,27.0,neutral or dissatisfied +64049,98102,Female,Loyal Customer,24,Personal Travel,Eco,265,4,3,0,4,1,0,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +64050,46860,Female,disloyal Customer,21,Business travel,Eco,844,4,3,3,3,2,3,2,2,1,4,3,5,3,2,0,0.0,satisfied +64051,88904,Female,Loyal Customer,27,Personal Travel,Eco,859,5,2,5,4,5,5,5,5,2,2,4,3,4,5,0,0.0,satisfied +64052,84150,Male,Loyal Customer,58,Business travel,Business,1355,5,5,5,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +64053,74636,Female,Loyal Customer,58,Business travel,Business,1506,3,3,3,3,3,2,1,4,4,4,4,1,4,3,17,8.0,satisfied +64054,83691,Female,Loyal Customer,8,Personal Travel,Eco,577,4,5,4,5,2,4,1,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +64055,40259,Female,Loyal Customer,43,Business travel,Eco,463,4,4,4,4,5,1,4,4,4,4,4,2,4,4,0,0.0,satisfied +64056,19740,Male,Loyal Customer,17,Business travel,Eco Plus,409,4,3,3,3,4,2,4,3,1,3,4,4,3,4,437,518.0,neutral or dissatisfied +64057,15734,Female,Loyal Customer,36,Personal Travel,Eco,419,3,4,3,4,2,3,2,2,1,3,4,3,4,2,63,92.0,neutral or dissatisfied +64058,64423,Female,Loyal Customer,50,Business travel,Business,989,5,5,5,5,5,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +64059,80914,Female,Loyal Customer,47,Business travel,Business,2789,4,4,5,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +64060,13857,Female,Loyal Customer,30,Business travel,Business,3241,2,2,2,2,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +64061,29484,Male,Loyal Customer,42,Business travel,Eco,1107,2,1,1,1,2,2,2,2,1,5,2,1,2,2,0,0.0,neutral or dissatisfied +64062,93493,Male,Loyal Customer,66,Business travel,Eco,1020,1,2,2,2,1,1,1,1,4,5,4,1,4,1,90,79.0,neutral or dissatisfied +64063,17130,Female,Loyal Customer,45,Business travel,Eco,472,5,3,3,3,4,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +64064,3045,Female,disloyal Customer,36,Business travel,Eco,489,4,3,4,3,1,4,1,1,1,2,4,3,4,1,0,4.0,neutral or dissatisfied +64065,51250,Male,Loyal Customer,53,Business travel,Eco Plus,373,4,1,1,1,4,4,4,4,2,3,5,3,3,4,0,0.0,satisfied +64066,114905,Male,Loyal Customer,58,Business travel,Business,3103,4,4,4,4,4,5,4,5,5,4,5,4,5,5,0,9.0,satisfied +64067,11178,Female,Loyal Customer,44,Personal Travel,Eco,201,3,4,0,3,4,3,3,1,1,0,1,4,1,1,4,0.0,neutral or dissatisfied +64068,21462,Female,Loyal Customer,65,Business travel,Eco,377,4,1,3,1,1,4,1,4,4,4,4,3,4,4,2,1.0,satisfied +64069,79442,Male,Loyal Customer,62,Personal Travel,Eco,187,1,5,1,3,3,1,3,3,4,3,1,4,5,3,5,0.0,neutral or dissatisfied +64070,42781,Male,Loyal Customer,27,Business travel,Eco Plus,744,5,3,3,3,5,5,5,5,5,5,3,5,4,5,29,36.0,satisfied +64071,128428,Male,Loyal Customer,28,Business travel,Business,355,3,5,5,5,3,3,3,3,1,3,4,2,3,3,0,1.0,neutral or dissatisfied +64072,110554,Female,Loyal Customer,21,Business travel,Business,2626,1,1,1,1,4,4,4,4,3,3,5,4,4,4,26,25.0,satisfied +64073,95807,Female,disloyal Customer,27,Business travel,Business,1050,5,5,5,3,1,5,1,1,5,2,5,4,4,1,29,14.0,satisfied +64074,60783,Male,Loyal Customer,47,Business travel,Business,628,3,3,3,3,2,4,5,4,4,5,4,3,4,5,3,0.0,satisfied +64075,20029,Female,Loyal Customer,16,Business travel,Business,2864,4,4,5,4,4,4,4,4,5,5,5,3,3,4,22,13.0,satisfied +64076,31268,Male,Loyal Customer,22,Business travel,Business,2367,3,3,3,3,1,2,1,1,5,1,3,2,3,1,0,4.0,satisfied +64077,85952,Male,Loyal Customer,69,Business travel,Business,3857,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +64078,33248,Male,Loyal Customer,38,Business travel,Eco Plus,102,5,3,3,3,5,5,5,5,3,1,4,3,5,5,0,0.0,satisfied +64079,70528,Male,disloyal Customer,23,Business travel,Eco,1258,1,0,0,5,4,0,4,4,4,5,4,3,4,4,0,19.0,neutral or dissatisfied +64080,71789,Female,Loyal Customer,44,Business travel,Business,1846,1,1,1,1,2,5,5,4,4,4,4,5,4,5,4,8.0,satisfied +64081,23152,Male,Loyal Customer,58,Business travel,Eco,246,5,4,4,4,5,5,5,5,2,5,1,4,1,5,0,0.0,satisfied +64082,32152,Female,Loyal Customer,39,Business travel,Eco,102,3,5,5,5,3,3,3,3,4,5,1,2,4,3,0,0.0,satisfied +64083,10680,Female,Loyal Customer,39,Business travel,Business,312,0,0,0,4,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +64084,29583,Male,Loyal Customer,28,Business travel,Business,680,5,5,5,5,1,2,1,1,4,1,3,1,4,1,0,0.0,satisfied +64085,118069,Male,Loyal Customer,66,Business travel,Business,1044,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +64086,104972,Female,Loyal Customer,50,Business travel,Business,3332,3,3,3,3,3,4,5,4,4,4,4,3,4,4,39,34.0,satisfied +64087,70023,Male,Loyal Customer,53,Business travel,Business,3935,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +64088,43531,Male,Loyal Customer,42,Business travel,Eco,920,2,3,3,3,2,2,2,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +64089,128272,Female,Loyal Customer,41,Business travel,Business,1754,3,3,3,3,4,5,4,5,5,5,4,4,5,4,53,49.0,satisfied +64090,19709,Female,disloyal Customer,24,Business travel,Eco,475,5,0,5,1,5,5,5,5,2,3,1,3,3,5,0,0.0,satisfied +64091,54008,Male,Loyal Customer,20,Personal Travel,Eco,395,2,4,2,3,5,2,5,5,4,5,3,3,4,5,3,0.0,neutral or dissatisfied +64092,26768,Female,Loyal Customer,22,Business travel,Eco Plus,859,3,1,1,1,3,3,1,3,4,5,3,2,3,3,0,12.0,neutral or dissatisfied +64093,30640,Female,disloyal Customer,23,Business travel,Eco,533,3,3,3,3,4,3,4,4,4,2,3,2,2,4,0,1.0,neutral or dissatisfied +64094,85360,Female,Loyal Customer,21,Personal Travel,Eco Plus,813,3,4,3,3,3,3,3,3,4,5,4,5,4,3,1,0.0,neutral or dissatisfied +64095,25853,Male,Loyal Customer,47,Personal Travel,Eco,692,1,4,1,4,3,1,5,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +64096,96257,Female,Loyal Customer,42,Personal Travel,Eco,546,2,3,1,3,4,3,4,5,5,1,5,2,5,1,18,7.0,neutral or dissatisfied +64097,24866,Male,Loyal Customer,24,Business travel,Business,356,3,5,5,5,3,3,3,3,4,5,3,1,4,3,0,0.0,neutral or dissatisfied +64098,84946,Male,Loyal Customer,54,Business travel,Business,2190,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +64099,117552,Female,Loyal Customer,43,Business travel,Business,3897,2,2,2,2,4,4,4,5,5,5,5,4,5,5,12,0.0,satisfied +64100,40443,Female,disloyal Customer,20,Business travel,Eco,290,3,0,3,1,5,3,5,5,1,2,4,3,5,5,0,0.0,neutral or dissatisfied +64101,75046,Male,Loyal Customer,55,Business travel,Business,1592,4,4,4,4,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +64102,15936,Male,Loyal Customer,7,Business travel,Business,723,2,1,2,1,2,3,2,2,3,3,3,1,3,2,1,11.0,neutral or dissatisfied +64103,48171,Female,Loyal Customer,47,Business travel,Business,3232,3,4,4,4,2,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +64104,21976,Male,Loyal Customer,65,Personal Travel,Eco,448,2,1,2,3,5,2,5,5,2,4,3,3,3,5,11,28.0,neutral or dissatisfied +64105,3684,Male,Loyal Customer,56,Business travel,Business,3373,5,5,5,5,2,5,4,5,5,5,5,4,5,3,21,42.0,satisfied +64106,42300,Female,Loyal Customer,14,Personal Travel,Eco,451,2,1,2,3,2,2,2,2,4,3,3,3,3,2,0,6.0,neutral or dissatisfied +64107,7771,Female,disloyal Customer,25,Business travel,Business,1080,2,5,2,5,2,2,4,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +64108,15384,Male,Loyal Customer,26,Business travel,Eco,164,5,2,4,4,5,5,5,5,2,2,3,1,5,5,0,0.0,satisfied +64109,7051,Male,Loyal Customer,47,Business travel,Business,177,2,4,4,4,1,3,3,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +64110,104869,Female,disloyal Customer,39,Business travel,Business,327,3,3,3,2,2,3,2,2,4,4,3,2,2,2,21,20.0,neutral or dissatisfied +64111,72839,Female,Loyal Customer,10,Personal Travel,Eco,1013,1,3,1,4,4,1,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +64112,39806,Male,disloyal Customer,30,Business travel,Business,272,3,3,3,1,1,3,1,1,5,1,2,4,4,1,11,0.0,neutral or dissatisfied +64113,30333,Female,Loyal Customer,29,Business travel,Business,2415,5,1,1,1,5,4,5,5,4,2,3,4,3,5,22,17.0,neutral or dissatisfied +64114,67221,Female,Loyal Customer,22,Personal Travel,Eco,1119,2,4,2,5,2,2,2,2,4,4,5,4,4,2,4,0.0,neutral or dissatisfied +64115,117823,Male,Loyal Customer,60,Personal Travel,Eco,328,2,5,3,1,3,3,3,3,5,5,4,5,4,3,13,10.0,neutral or dissatisfied +64116,48389,Female,Loyal Customer,63,Personal Travel,Eco,674,4,4,4,1,4,5,5,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +64117,778,Male,Loyal Customer,42,Business travel,Business,2211,1,1,1,1,3,2,2,3,3,3,1,4,3,1,56,51.0,neutral or dissatisfied +64118,89262,Female,Loyal Customer,56,Business travel,Business,453,5,5,5,5,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +64119,20191,Female,Loyal Customer,61,Personal Travel,Eco,677,2,4,2,4,4,3,4,5,5,2,5,4,5,2,28,23.0,neutral or dissatisfied +64120,73004,Male,Loyal Customer,30,Personal Travel,Eco,1096,1,1,1,3,1,1,1,2,3,4,3,1,1,1,179,166.0,neutral or dissatisfied +64121,77431,Female,Loyal Customer,67,Personal Travel,Eco,626,3,4,3,3,4,4,4,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +64122,10704,Male,Loyal Customer,55,Business travel,Business,312,1,1,4,1,4,4,5,4,4,4,4,4,4,5,77,80.0,satisfied +64123,127457,Female,Loyal Customer,47,Business travel,Business,2075,3,3,3,3,4,5,5,4,4,4,4,3,4,4,0,8.0,satisfied +64124,25534,Female,Loyal Customer,24,Personal Travel,Eco,516,3,3,3,2,1,3,1,1,2,1,3,2,5,1,34,26.0,neutral or dissatisfied +64125,87494,Male,Loyal Customer,19,Business travel,Business,2206,3,3,3,3,3,3,3,3,3,4,3,2,4,3,81,72.0,neutral or dissatisfied +64126,763,Female,Loyal Customer,40,Business travel,Business,3184,3,3,3,3,2,4,5,4,4,4,5,4,4,3,0,0.0,satisfied +64127,88877,Male,disloyal Customer,39,Business travel,Business,859,5,4,4,4,2,4,2,2,5,2,5,5,4,2,0,0.0,satisfied +64128,1590,Female,Loyal Customer,66,Personal Travel,Eco,140,5,2,5,4,5,4,4,2,2,5,2,2,2,1,0,0.0,satisfied +64129,50347,Female,disloyal Customer,38,Business travel,Eco,372,2,2,3,2,1,3,1,1,3,1,1,2,1,1,0,4.0,neutral or dissatisfied +64130,15863,Male,Loyal Customer,47,Business travel,Eco,241,4,1,1,1,4,4,4,4,4,2,3,4,4,4,0,0.0,satisfied +64131,90452,Female,Loyal Customer,56,Business travel,Business,404,4,4,4,4,2,4,4,4,4,4,4,3,4,3,4,0.0,satisfied +64132,125908,Female,Loyal Customer,65,Personal Travel,Eco,1013,2,2,2,4,2,4,4,4,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +64133,66508,Female,Loyal Customer,36,Personal Travel,Eco,447,2,4,2,1,1,2,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +64134,113371,Male,Loyal Customer,34,Business travel,Business,397,5,5,5,5,2,5,4,4,4,4,4,3,4,4,17,14.0,satisfied +64135,81331,Male,Loyal Customer,39,Business travel,Business,3825,2,2,3,2,4,4,5,4,4,5,4,4,4,4,12,7.0,satisfied +64136,25404,Male,Loyal Customer,52,Business travel,Eco,990,2,4,4,4,2,2,2,2,3,1,3,2,3,2,45,101.0,neutral or dissatisfied +64137,78846,Female,Loyal Customer,51,Business travel,Business,1981,3,3,3,3,3,4,5,5,5,5,5,5,5,3,6,10.0,satisfied +64138,70136,Male,Loyal Customer,80,Business travel,Eco,460,2,3,3,3,2,2,2,2,1,2,4,3,3,2,22,9.0,neutral or dissatisfied +64139,49511,Male,Loyal Customer,53,Business travel,Business,326,1,1,1,1,1,5,5,4,4,4,4,5,4,4,2,6.0,satisfied +64140,2970,Female,Loyal Customer,27,Business travel,Eco Plus,835,2,3,3,3,2,2,2,2,3,4,3,3,3,2,15,2.0,neutral or dissatisfied +64141,6392,Male,disloyal Customer,37,Business travel,Eco,315,2,3,2,3,5,2,3,5,1,3,3,2,4,5,0,0.0,neutral or dissatisfied +64142,26645,Male,Loyal Customer,48,Business travel,Eco,404,3,2,2,2,3,3,3,3,4,5,2,3,2,3,0,18.0,neutral or dissatisfied +64143,32646,Male,disloyal Customer,22,Business travel,Eco,216,2,5,1,2,2,1,2,2,2,4,1,2,3,2,0,0.0,neutral or dissatisfied +64144,121771,Female,Loyal Customer,41,Business travel,Business,2539,1,1,1,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +64145,45081,Male,Loyal Customer,69,Personal Travel,Eco Plus,588,2,5,2,3,2,2,2,2,5,2,4,3,5,2,7,0.0,neutral or dissatisfied +64146,19513,Female,Loyal Customer,28,Personal Travel,Eco,350,3,4,3,1,5,3,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +64147,97989,Female,Loyal Customer,11,Personal Travel,Eco,483,2,4,2,1,4,2,3,4,4,4,4,4,4,4,22,16.0,neutral or dissatisfied +64148,66373,Male,Loyal Customer,22,Business travel,Eco Plus,986,3,5,5,5,3,3,2,3,1,1,4,1,3,3,126,119.0,neutral or dissatisfied +64149,37612,Female,Loyal Customer,9,Personal Travel,Eco,1056,4,4,4,1,3,4,2,3,4,5,4,4,4,3,70,50.0,neutral or dissatisfied +64150,12316,Male,Loyal Customer,48,Business travel,Eco,201,1,3,3,3,1,1,1,1,3,4,3,1,4,1,47,42.0,neutral or dissatisfied +64151,54720,Male,Loyal Customer,43,Personal Travel,Eco,854,1,3,1,2,3,1,3,3,2,2,3,3,2,3,34,19.0,neutral or dissatisfied +64152,68307,Male,Loyal Customer,35,Personal Travel,Eco,1797,2,5,2,3,4,2,4,4,3,4,3,5,5,4,3,0.0,neutral or dissatisfied +64153,129641,Male,Loyal Customer,48,Business travel,Business,3948,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +64154,46287,Male,Loyal Customer,36,Personal Travel,Eco Plus,679,3,3,3,5,1,3,1,1,3,4,1,2,1,1,0,0.0,neutral or dissatisfied +64155,91862,Male,Loyal Customer,42,Business travel,Eco,1995,2,4,4,4,2,2,2,2,3,2,3,3,4,2,0,3.0,neutral or dissatisfied +64156,82460,Male,Loyal Customer,61,Personal Travel,Eco,502,5,5,5,1,5,5,5,5,3,2,5,5,5,5,0,3.0,satisfied +64157,24239,Female,disloyal Customer,30,Business travel,Eco,147,3,1,3,3,1,3,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +64158,83845,Female,Loyal Customer,35,Personal Travel,Eco,425,2,0,2,1,1,2,1,1,5,3,5,3,5,1,27,18.0,neutral or dissatisfied +64159,44904,Female,Loyal Customer,11,Personal Travel,Eco Plus,536,3,5,3,1,3,5,5,3,2,5,4,5,5,5,165,179.0,neutral or dissatisfied +64160,41152,Female,Loyal Customer,26,Personal Travel,Eco,140,1,0,1,1,1,1,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +64161,23580,Female,Loyal Customer,41,Personal Travel,Eco,792,4,4,5,3,5,5,5,5,4,5,5,4,4,5,7,16.0,neutral or dissatisfied +64162,17953,Female,Loyal Customer,35,Business travel,Eco,500,4,4,3,3,4,4,4,4,5,4,4,3,2,4,11,0.0,satisfied +64163,105231,Male,Loyal Customer,34,Business travel,Eco,377,2,2,5,5,2,2,2,2,3,1,3,2,3,2,24,21.0,neutral or dissatisfied +64164,121972,Male,disloyal Customer,29,Business travel,Business,130,1,1,1,1,2,1,2,2,4,3,5,3,5,2,0,3.0,neutral or dissatisfied +64165,6099,Female,Loyal Customer,7,Personal Travel,Eco Plus,630,1,2,1,3,5,1,3,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +64166,74525,Male,Loyal Customer,37,Business travel,Business,1464,3,3,3,3,3,5,4,4,4,5,4,5,4,3,0,6.0,satisfied +64167,90204,Male,Loyal Customer,66,Personal Travel,Eco,1127,1,4,1,2,4,1,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +64168,35879,Female,Loyal Customer,54,Personal Travel,Eco,937,3,4,3,4,3,4,4,2,2,3,2,4,2,1,47,32.0,neutral or dissatisfied +64169,39997,Female,Loyal Customer,45,Business travel,Business,525,3,4,3,3,5,4,5,5,5,5,5,3,5,3,19,31.0,satisfied +64170,69062,Male,disloyal Customer,26,Business travel,Business,1389,1,1,1,1,3,1,3,3,3,2,5,5,5,3,57,80.0,neutral or dissatisfied +64171,21979,Male,Loyal Customer,48,Personal Travel,Eco,503,3,3,1,4,3,1,3,3,4,3,4,3,3,3,25,27.0,neutral or dissatisfied +64172,86996,Female,Loyal Customer,44,Personal Travel,Eco,907,3,1,4,3,3,2,3,3,3,4,3,1,3,3,0,1.0,neutral or dissatisfied +64173,80397,Male,Loyal Customer,65,Personal Travel,Eco,368,2,5,2,3,3,2,3,3,5,5,5,2,2,3,0,0.0,neutral or dissatisfied +64174,50328,Male,Loyal Customer,46,Business travel,Eco,308,5,1,1,1,5,5,5,5,3,2,5,5,2,5,0,0.0,satisfied +64175,125864,Female,Loyal Customer,35,Business travel,Business,2121,1,5,5,5,3,3,2,1,1,1,1,4,1,3,35,82.0,neutral or dissatisfied +64176,123523,Female,Loyal Customer,44,Personal Travel,Eco,2296,4,4,4,3,3,3,5,2,2,4,2,4,2,4,23,13.0,neutral or dissatisfied +64177,61752,Female,Loyal Customer,43,Personal Travel,Eco,1635,4,4,4,4,5,3,4,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +64178,62076,Male,Loyal Customer,52,Business travel,Business,2586,2,2,2,2,3,3,5,2,2,2,2,3,2,5,88,64.0,satisfied +64179,88164,Male,disloyal Customer,22,Business travel,Eco,594,3,0,3,3,2,3,2,2,5,4,5,3,4,2,18,25.0,neutral or dissatisfied +64180,27792,Male,Loyal Customer,52,Business travel,Eco,1448,5,4,3,4,5,5,5,5,3,3,5,4,3,5,0,0.0,satisfied +64181,70005,Female,Loyal Customer,34,Personal Travel,Eco,236,4,2,0,4,5,0,5,5,3,3,4,1,3,5,56,44.0,neutral or dissatisfied +64182,74607,Male,disloyal Customer,49,Business travel,Eco,1205,1,1,1,3,5,1,5,5,4,1,2,1,3,5,58,49.0,neutral or dissatisfied +64183,55870,Male,disloyal Customer,23,Business travel,Eco,528,5,0,5,1,2,5,2,2,4,4,4,3,5,2,0,25.0,satisfied +64184,44600,Female,disloyal Customer,23,Business travel,Eco,508,4,4,4,1,3,4,3,3,3,4,3,4,5,3,0,0.0,satisfied +64185,33877,Male,Loyal Customer,66,Business travel,Business,994,1,0,0,3,3,3,4,1,1,0,1,2,1,4,0,0.0,neutral or dissatisfied +64186,120611,Male,disloyal Customer,24,Business travel,Eco,453,3,0,3,2,3,3,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +64187,69658,Female,Loyal Customer,55,Business travel,Business,1727,1,1,3,1,3,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +64188,120485,Male,Loyal Customer,14,Personal Travel,Eco,449,5,5,5,1,1,5,1,1,5,2,4,4,4,1,1,0.0,satisfied +64189,128852,Female,Loyal Customer,43,Personal Travel,Eco,2475,4,4,4,2,4,5,5,1,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +64190,127788,Female,Loyal Customer,60,Personal Travel,Eco,1037,2,4,2,1,3,5,4,4,4,2,4,4,4,3,23,14.0,neutral or dissatisfied +64191,46820,Female,disloyal Customer,37,Business travel,Eco,850,4,4,4,2,5,4,5,5,4,5,1,1,2,5,0,12.0,neutral or dissatisfied +64192,91513,Female,Loyal Customer,31,Business travel,Eco,1620,5,1,1,1,5,5,5,5,3,4,5,3,1,5,15,38.0,satisfied +64193,38402,Female,Loyal Customer,46,Personal Travel,Eco,1754,4,4,4,4,1,4,4,3,3,4,3,4,3,4,0,7.0,satisfied +64194,44640,Female,Loyal Customer,54,Business travel,Eco,268,4,3,3,3,2,2,3,4,4,4,4,1,4,4,58,55.0,satisfied +64195,52207,Female,Loyal Customer,49,Business travel,Business,3793,4,4,2,4,3,5,1,5,5,5,5,4,5,4,25,16.0,satisfied +64196,128246,Male,Loyal Customer,11,Personal Travel,Eco Plus,602,3,4,3,4,1,3,1,1,4,4,4,2,3,1,0,0.0,neutral or dissatisfied +64197,28501,Female,Loyal Customer,48,Business travel,Business,2681,2,3,2,2,1,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +64198,56851,Female,Loyal Customer,34,Business travel,Business,2434,1,1,1,1,5,4,4,4,3,3,5,4,5,4,19,8.0,satisfied +64199,126816,Male,Loyal Customer,49,Business travel,Business,2125,2,3,1,3,2,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +64200,23719,Male,Loyal Customer,41,Personal Travel,Eco,73,1,3,1,1,3,1,3,3,5,1,4,2,4,3,4,0.0,neutral or dissatisfied +64201,73189,Male,Loyal Customer,47,Business travel,Business,1258,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +64202,126406,Male,Loyal Customer,29,Business travel,Business,2630,2,2,2,2,4,5,4,4,5,5,4,4,5,4,0,0.0,satisfied +64203,59006,Female,Loyal Customer,40,Business travel,Business,1846,5,5,5,5,4,5,4,4,4,4,4,4,4,5,10,6.0,satisfied +64204,69941,Male,disloyal Customer,29,Business travel,Business,1116,4,4,4,4,2,4,2,2,3,2,5,5,4,2,0,0.0,satisfied +64205,108275,Male,Loyal Customer,64,Personal Travel,Eco,895,1,5,1,1,4,1,4,4,4,4,4,4,5,4,1,0.0,neutral or dissatisfied +64206,98401,Female,Loyal Customer,48,Business travel,Business,675,5,5,5,5,2,4,5,4,4,4,4,5,4,3,18,12.0,satisfied +64207,85930,Female,Loyal Customer,57,Business travel,Business,432,2,2,2,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +64208,124545,Male,Loyal Customer,7,Personal Travel,Eco,1276,4,4,4,2,3,4,3,3,3,5,5,4,4,3,0,0.0,satisfied +64209,35574,Male,disloyal Customer,29,Business travel,Eco Plus,828,3,3,3,5,1,3,2,1,5,2,2,2,1,1,0,3.0,neutral or dissatisfied +64210,5953,Male,Loyal Customer,46,Business travel,Business,1970,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +64211,20658,Female,Loyal Customer,24,Business travel,Business,522,5,5,4,5,2,3,2,2,4,5,3,5,3,2,35,15.0,satisfied +64212,5128,Female,Loyal Customer,25,Business travel,Eco Plus,235,2,2,2,2,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +64213,127291,Male,Loyal Customer,49,Business travel,Business,2538,3,3,3,3,4,5,5,4,4,5,4,3,4,5,0,1.0,satisfied +64214,113293,Male,disloyal Customer,24,Business travel,Eco,386,3,0,3,3,4,3,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +64215,125321,Male,Loyal Customer,52,Business travel,Business,599,2,2,2,2,5,5,4,5,5,5,5,5,5,5,3,2.0,satisfied +64216,53799,Male,Loyal Customer,37,Business travel,Business,2833,1,1,1,1,5,4,5,4,4,4,4,5,4,3,9,4.0,satisfied +64217,128082,Male,Loyal Customer,23,Business travel,Business,2845,3,2,4,4,3,3,3,1,3,2,3,3,3,3,0,14.0,neutral or dissatisfied +64218,21734,Female,Loyal Customer,44,Business travel,Business,563,1,1,1,1,3,4,5,2,2,3,2,2,2,3,4,0.0,satisfied +64219,129244,Male,disloyal Customer,30,Business travel,Eco,1464,4,4,4,1,3,4,3,3,2,5,3,3,4,3,14,5.0,neutral or dissatisfied +64220,73631,Male,Loyal Customer,52,Business travel,Business,2391,1,1,4,1,4,5,5,5,5,5,5,4,5,5,17,10.0,satisfied +64221,85714,Female,Loyal Customer,39,Business travel,Business,1547,4,4,4,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +64222,24681,Male,Loyal Customer,52,Business travel,Business,3791,3,3,3,3,4,1,4,5,5,5,5,4,5,4,0,0.0,satisfied +64223,55933,Male,Loyal Customer,17,Personal Travel,Eco,733,1,1,1,3,4,1,4,4,2,1,3,4,3,4,0,21.0,neutral or dissatisfied +64224,39972,Female,Loyal Customer,37,Business travel,Eco,1262,2,2,2,2,2,2,2,2,1,2,5,3,2,2,0,0.0,satisfied +64225,66901,Male,Loyal Customer,8,Personal Travel,Business,1121,1,4,1,2,5,1,3,5,4,3,5,3,4,5,0,7.0,neutral or dissatisfied +64226,37697,Male,Loyal Customer,53,Personal Travel,Eco,1005,2,1,2,2,1,2,1,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +64227,81628,Male,Loyal Customer,35,Personal Travel,Eco,1142,3,5,3,2,5,3,4,5,5,3,4,2,4,5,0,0.0,neutral or dissatisfied +64228,25972,Female,Loyal Customer,40,Personal Travel,Eco,946,2,1,2,4,4,2,4,4,1,2,4,1,3,4,6,0.0,neutral or dissatisfied +64229,33145,Female,Loyal Customer,54,Personal Travel,Eco,201,3,5,3,3,4,3,5,2,2,3,2,5,2,5,3,3.0,neutral or dissatisfied +64230,128858,Male,Loyal Customer,50,Business travel,Business,2475,2,2,2,2,4,5,5,5,2,5,4,5,5,5,10,16.0,satisfied +64231,122233,Male,Loyal Customer,25,Business travel,Eco,541,2,4,4,4,2,3,3,2,1,5,3,4,3,2,3,15.0,neutral or dissatisfied +64232,110003,Male,Loyal Customer,55,Business travel,Business,2093,1,1,1,1,4,5,5,4,4,4,4,3,4,5,32,7.0,satisfied +64233,6426,Male,Loyal Customer,39,Personal Travel,Eco,296,2,3,1,4,2,1,5,2,2,2,3,3,4,2,1,8.0,neutral or dissatisfied +64234,88352,Female,disloyal Customer,38,Business travel,Eco,250,2,1,2,4,5,2,5,5,4,4,3,4,3,5,0,0.0,neutral or dissatisfied +64235,8426,Female,Loyal Customer,38,Business travel,Business,2173,1,1,3,1,3,5,1,4,4,4,4,3,4,1,10,0.0,satisfied +64236,25396,Male,Loyal Customer,55,Business travel,Eco,990,4,5,5,5,4,4,4,4,3,3,3,3,4,4,5,0.0,neutral or dissatisfied +64237,95548,Male,Loyal Customer,67,Personal Travel,Eco Plus,189,3,5,3,3,4,3,3,4,3,3,5,3,5,4,28,23.0,neutral or dissatisfied +64238,13467,Male,Loyal Customer,68,Personal Travel,Eco,409,2,5,2,2,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +64239,129029,Female,Loyal Customer,45,Business travel,Business,2611,4,4,4,4,4,4,4,3,5,3,4,4,3,4,1,5.0,satisfied +64240,49411,Male,Loyal Customer,62,Business travel,Business,3719,5,5,5,5,1,3,1,5,5,5,4,4,5,3,0,0.0,satisfied +64241,78474,Male,Loyal Customer,57,Business travel,Business,2604,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +64242,19108,Male,Loyal Customer,54,Business travel,Eco,323,4,3,3,3,4,4,4,4,4,2,2,5,5,4,0,0.0,satisfied +64243,24734,Male,Loyal Customer,62,Business travel,Business,2999,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,7.0,satisfied +64244,9202,Male,Loyal Customer,56,Business travel,Business,3074,0,0,0,2,4,4,4,5,5,2,2,2,5,4,0,0.0,satisfied +64245,86962,Male,Loyal Customer,38,Business travel,Business,3867,5,5,1,5,4,5,5,4,4,4,4,4,4,3,0,13.0,satisfied +64246,111930,Male,disloyal Customer,22,Business travel,Business,770,4,0,4,3,1,4,1,1,5,4,4,3,4,1,0,0.0,satisfied +64247,122920,Male,Loyal Customer,39,Personal Travel,Business,650,2,3,2,3,1,1,1,5,5,2,5,1,5,4,0,1.0,neutral or dissatisfied +64248,60216,Male,Loyal Customer,49,Business travel,Business,1506,4,4,2,4,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +64249,103511,Female,Loyal Customer,24,Business travel,Business,1047,1,5,2,5,1,1,1,1,3,1,3,3,4,1,22,20.0,neutral or dissatisfied +64250,78903,Female,Loyal Customer,42,Business travel,Business,1708,3,3,3,3,5,5,5,2,2,3,2,5,2,5,0,0.0,satisfied +64251,127500,Male,Loyal Customer,11,Personal Travel,Eco,1814,2,5,2,3,4,2,4,4,3,3,4,3,5,4,5,0.0,neutral or dissatisfied +64252,98819,Female,Loyal Customer,40,Business travel,Business,444,3,5,5,5,2,2,2,3,3,3,3,4,3,2,13,4.0,neutral or dissatisfied +64253,67917,Female,Loyal Customer,69,Personal Travel,Eco,1188,2,5,2,1,4,3,4,4,4,2,4,5,4,5,9,18.0,neutral or dissatisfied +64254,12514,Male,Loyal Customer,58,Personal Travel,Business,812,4,1,4,4,3,3,4,2,2,4,2,4,2,1,0,0.0,satisfied +64255,86781,Male,Loyal Customer,30,Business travel,Business,3431,2,2,2,2,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +64256,66281,Female,Loyal Customer,44,Business travel,Business,2258,1,1,1,1,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +64257,101627,Female,Loyal Customer,22,Personal Travel,Eco,1371,3,4,3,1,5,3,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +64258,106123,Female,Loyal Customer,41,Business travel,Business,302,4,4,4,4,2,5,5,4,4,4,4,5,4,4,30,64.0,satisfied +64259,17007,Male,Loyal Customer,46,Business travel,Business,1612,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +64260,5786,Male,Loyal Customer,44,Business travel,Business,1685,1,1,1,1,3,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +64261,74947,Male,Loyal Customer,45,Business travel,Business,2475,3,5,5,5,3,3,3,2,5,4,4,3,4,3,171,164.0,neutral or dissatisfied +64262,66293,Male,Loyal Customer,24,Business travel,Business,3820,2,1,1,1,2,2,2,2,4,1,3,1,4,2,13,17.0,neutral or dissatisfied +64263,46149,Male,Loyal Customer,45,Business travel,Eco,627,4,1,1,1,4,4,4,1,2,2,3,4,1,4,167,168.0,neutral or dissatisfied +64264,96711,Female,Loyal Customer,39,Business travel,Business,1914,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +64265,57763,Female,Loyal Customer,40,Business travel,Business,2611,1,1,1,1,5,5,5,4,4,5,5,5,5,5,14,6.0,satisfied +64266,59074,Male,disloyal Customer,30,Business travel,Eco,889,4,4,4,1,3,4,3,3,2,1,3,3,4,3,24,0.0,neutral or dissatisfied +64267,58953,Female,disloyal Customer,28,Business travel,Business,1726,5,5,5,4,5,5,5,5,4,5,4,5,5,5,0,0.0,satisfied +64268,57757,Male,Loyal Customer,16,Business travel,Business,2704,4,4,4,4,4,4,4,4,2,3,5,4,5,4,2,0.0,satisfied +64269,42157,Male,Loyal Customer,65,Personal Travel,Business,817,3,5,3,1,5,5,4,4,4,3,4,4,4,5,0,3.0,neutral or dissatisfied +64270,86423,Female,disloyal Customer,25,Business travel,Business,762,1,0,1,1,1,1,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +64271,46909,Male,Loyal Customer,36,Business travel,Business,844,1,1,1,1,2,1,3,4,4,4,4,4,4,2,0,0.0,satisfied +64272,110746,Male,Loyal Customer,45,Business travel,Business,2969,1,1,1,1,5,4,5,4,4,4,4,5,4,4,36,48.0,satisfied +64273,86640,Female,Loyal Customer,63,Business travel,Eco,746,2,2,2,2,4,2,3,2,2,2,2,2,2,2,35,20.0,neutral or dissatisfied +64274,30718,Female,disloyal Customer,31,Business travel,Eco,1123,2,2,2,3,1,2,1,1,2,2,4,2,4,1,0,0.0,neutral or dissatisfied +64275,30237,Female,Loyal Customer,47,Business travel,Business,3752,1,4,4,4,2,3,4,1,1,1,1,1,1,1,9,95.0,neutral or dissatisfied +64276,51768,Female,Loyal Customer,42,Personal Travel,Eco,370,4,5,4,2,1,3,2,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +64277,100194,Female,Loyal Customer,44,Personal Travel,Eco,725,4,2,4,4,3,4,4,3,3,4,3,3,3,1,0,0.0,neutral or dissatisfied +64278,83919,Male,disloyal Customer,25,Business travel,Business,373,2,0,2,2,5,2,3,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +64279,98884,Male,Loyal Customer,27,Personal Travel,Eco,991,4,4,4,3,4,4,4,4,4,4,4,3,5,4,106,102.0,neutral or dissatisfied +64280,7311,Male,Loyal Customer,60,Business travel,Eco Plus,116,3,2,2,2,3,3,3,3,4,3,3,4,4,3,1,0.0,neutral or dissatisfied +64281,75159,Male,disloyal Customer,42,Business travel,Business,975,5,4,4,3,1,5,1,1,3,3,3,5,4,1,0,30.0,satisfied +64282,105321,Male,Loyal Customer,50,Business travel,Business,528,4,4,4,4,3,5,4,4,4,4,4,4,4,3,43,37.0,satisfied +64283,64800,Male,disloyal Customer,18,Business travel,Eco,282,4,4,5,3,4,5,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +64284,61598,Male,Loyal Customer,41,Business travel,Business,1346,3,3,3,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +64285,118209,Female,Loyal Customer,51,Business travel,Business,1444,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +64286,92513,Male,Loyal Customer,45,Personal Travel,Eco,1919,2,5,2,3,5,2,5,5,5,5,5,4,5,5,5,0.0,neutral or dissatisfied +64287,34628,Male,Loyal Customer,9,Personal Travel,Business,541,1,5,1,5,3,1,3,3,3,2,2,1,2,3,117,119.0,neutral or dissatisfied +64288,49270,Male,disloyal Customer,21,Business travel,Eco,308,5,0,5,3,1,5,5,1,2,4,2,4,2,1,0,0.0,satisfied +64289,3947,Female,Loyal Customer,37,Business travel,Business,764,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +64290,118555,Male,Loyal Customer,59,Business travel,Eco,304,3,5,5,5,3,3,3,3,1,1,3,4,3,3,4,0.0,neutral or dissatisfied +64291,5575,Male,Loyal Customer,14,Personal Travel,Eco,501,2,4,2,1,4,2,4,4,5,5,5,4,4,4,0,12.0,neutral or dissatisfied +64292,75452,Female,Loyal Customer,56,Business travel,Eco,842,4,5,1,5,4,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +64293,117966,Female,Loyal Customer,22,Personal Travel,Eco,255,2,4,2,3,4,2,5,4,1,4,2,3,1,4,13,4.0,neutral or dissatisfied +64294,90807,Female,Loyal Customer,71,Business travel,Business,366,2,3,3,3,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +64295,8163,Female,Loyal Customer,21,Business travel,Business,2497,2,2,2,2,5,5,4,5,4,4,4,3,4,5,0,0.0,satisfied +64296,127674,Female,Loyal Customer,13,Personal Travel,Eco,2153,5,5,5,1,4,5,4,4,2,5,5,4,4,4,0,0.0,satisfied +64297,47176,Female,Loyal Customer,40,Business travel,Business,3229,1,1,1,1,3,4,3,1,1,1,1,2,1,2,11,1.0,neutral or dissatisfied +64298,126278,Male,Loyal Customer,20,Personal Travel,Eco,631,2,5,2,2,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +64299,120807,Female,Loyal Customer,47,Business travel,Business,2431,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +64300,2869,Female,Loyal Customer,22,Business travel,Business,475,5,5,5,5,4,3,4,4,2,2,4,1,2,4,0,0.0,satisfied +64301,105652,Female,Loyal Customer,53,Business travel,Business,2554,4,4,5,4,5,5,4,5,5,5,5,5,5,3,16,0.0,satisfied +64302,86309,Female,Loyal Customer,54,Business travel,Eco Plus,306,3,3,3,3,4,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +64303,126543,Male,Loyal Customer,22,Business travel,Eco,644,3,1,1,1,3,3,1,3,2,3,3,1,4,3,7,10.0,neutral or dissatisfied +64304,64790,Male,Loyal Customer,59,Business travel,Business,190,3,3,3,3,4,3,3,2,2,2,3,3,2,3,1,3.0,neutral or dissatisfied +64305,50217,Male,disloyal Customer,21,Business travel,Eco,89,2,2,2,3,1,2,1,1,3,4,3,3,4,1,0,2.0,neutral or dissatisfied +64306,108777,Female,Loyal Customer,24,Business travel,Business,3871,2,3,3,3,2,3,2,2,2,1,4,3,4,2,0,0.0,neutral or dissatisfied +64307,119530,Male,Loyal Customer,52,Personal Travel,Eco,759,4,5,4,2,2,4,2,2,4,3,5,5,5,2,2,0.0,neutral or dissatisfied +64308,129574,Male,Loyal Customer,51,Business travel,Eco Plus,842,5,4,4,4,5,5,5,5,3,3,1,5,2,5,47,35.0,satisfied +64309,22811,Female,Loyal Customer,67,Business travel,Business,3850,4,5,5,5,1,2,2,4,4,4,4,4,4,4,67,70.0,neutral or dissatisfied +64310,97801,Male,Loyal Customer,53,Business travel,Business,3062,1,1,1,1,2,5,4,4,4,4,4,3,4,3,41,44.0,satisfied +64311,63473,Female,Loyal Customer,50,Personal Travel,Eco Plus,337,3,3,3,3,1,1,1,3,3,3,3,4,3,5,43,29.0,neutral or dissatisfied +64312,89174,Male,Loyal Customer,11,Personal Travel,Eco,1947,4,5,4,2,3,4,5,3,4,3,3,3,4,3,14,0.0,neutral or dissatisfied +64313,123013,Male,Loyal Customer,51,Business travel,Business,2129,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +64314,20181,Male,Loyal Customer,70,Personal Travel,Eco,403,4,5,4,3,4,4,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +64315,24568,Female,Loyal Customer,32,Personal Travel,Eco,696,0,4,0,1,2,0,2,2,5,3,5,3,5,2,0,0.0,satisfied +64316,68730,Male,Loyal Customer,47,Personal Travel,Eco Plus,237,2,4,2,2,1,2,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +64317,65255,Female,disloyal Customer,22,Business travel,Eco,190,4,2,4,3,4,4,4,4,2,4,4,2,4,4,0,0.0,neutral or dissatisfied +64318,718,Female,disloyal Customer,47,Business travel,Business,89,2,2,2,5,4,2,2,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +64319,129124,Male,Loyal Customer,46,Business travel,Business,279,5,5,5,5,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +64320,51908,Female,Loyal Customer,49,Personal Travel,Eco,601,5,4,5,2,1,1,4,5,5,5,5,3,5,4,0,0.0,satisfied +64321,26299,Male,Loyal Customer,19,Business travel,Business,2990,2,1,3,1,2,2,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +64322,8350,Male,Loyal Customer,46,Personal Travel,Eco,783,1,4,1,3,2,1,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +64323,36732,Male,Loyal Customer,44,Business travel,Business,1754,4,4,4,4,3,5,4,5,5,5,5,4,5,2,0,29.0,satisfied +64324,41277,Male,Loyal Customer,29,Business travel,Business,2928,5,5,5,5,5,4,5,5,5,1,1,5,2,5,0,0.0,satisfied +64325,15181,Female,Loyal Customer,47,Personal Travel,Eco,416,3,2,3,4,2,4,4,1,1,3,3,3,1,3,22,14.0,neutral or dissatisfied +64326,88999,Male,Loyal Customer,61,Personal Travel,Eco Plus,1199,2,5,2,1,2,2,2,2,3,4,1,1,2,2,4,31.0,neutral or dissatisfied +64327,42102,Male,Loyal Customer,47,Business travel,Eco,996,5,1,1,1,5,5,5,5,4,2,2,2,5,5,80,54.0,satisfied +64328,40298,Female,Loyal Customer,65,Personal Travel,Eco,463,3,4,3,1,5,5,5,1,1,3,5,3,1,4,0,7.0,neutral or dissatisfied +64329,62728,Male,Loyal Customer,50,Business travel,Business,2486,2,1,2,2,4,4,4,5,3,3,4,4,4,4,34,23.0,satisfied +64330,99737,Female,Loyal Customer,47,Business travel,Business,3598,0,0,0,1,5,4,4,2,2,2,2,5,2,4,20,26.0,satisfied +64331,18882,Male,disloyal Customer,39,Business travel,Eco,448,1,4,1,3,5,1,5,5,4,5,4,4,4,5,22,31.0,neutral or dissatisfied +64332,96600,Male,Loyal Customer,48,Business travel,Business,937,5,5,5,5,2,4,5,4,4,4,4,4,4,4,14,8.0,satisfied +64333,4879,Female,Loyal Customer,45,Personal Travel,Eco,408,3,1,3,4,2,3,4,1,1,3,1,3,1,1,2,15.0,neutral or dissatisfied +64334,74850,Female,Loyal Customer,27,Business travel,Business,2136,4,4,4,4,5,5,5,5,3,5,5,4,5,5,0,0.0,satisfied +64335,75524,Male,Loyal Customer,56,Business travel,Business,3809,3,3,3,3,4,5,4,5,5,4,5,4,5,3,0,13.0,satisfied +64336,91791,Female,Loyal Customer,36,Personal Travel,Eco,590,3,5,3,3,2,3,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +64337,83821,Female,Loyal Customer,54,Business travel,Business,425,3,3,5,3,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +64338,25558,Male,Loyal Customer,32,Business travel,Business,2291,5,5,5,5,4,4,4,4,2,4,1,1,2,4,22,10.0,satisfied +64339,29401,Female,Loyal Customer,14,Personal Travel,Eco,2404,2,3,2,2,2,2,2,5,1,5,2,2,2,2,0,0.0,neutral or dissatisfied +64340,20667,Female,Loyal Customer,46,Business travel,Eco,522,5,1,1,1,5,4,3,5,5,5,5,3,5,2,0,0.0,satisfied +64341,32945,Male,Loyal Customer,49,Personal Travel,Eco,216,3,0,3,5,5,3,5,5,3,3,5,1,5,5,0,0.0,neutral or dissatisfied +64342,3937,Male,Loyal Customer,41,Business travel,Business,765,2,2,2,2,4,5,5,4,4,5,4,4,4,4,0,27.0,satisfied +64343,43013,Female,Loyal Customer,39,Business travel,Business,3045,0,0,0,5,4,1,2,5,5,5,5,1,5,3,0,0.0,satisfied +64344,120666,Female,Loyal Customer,37,Business travel,Business,280,0,0,0,3,5,5,5,5,5,2,2,3,5,4,0,7.0,satisfied +64345,121772,Female,Loyal Customer,59,Business travel,Business,3959,3,3,5,3,5,4,4,2,2,2,2,4,2,4,5,49.0,satisfied +64346,39537,Male,Loyal Customer,36,Personal Travel,Business,954,4,5,4,4,3,5,5,2,2,4,3,5,2,5,0,5.0,satisfied +64347,41926,Female,Loyal Customer,78,Business travel,Eco,129,4,2,2,2,4,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +64348,37721,Male,Loyal Customer,55,Personal Travel,Eco,1028,2,5,2,3,3,2,5,3,3,2,4,4,4,3,19,8.0,neutral or dissatisfied +64349,21374,Female,Loyal Customer,53,Business travel,Eco,554,3,3,3,3,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +64350,10906,Female,disloyal Customer,23,Business travel,Eco,517,2,1,2,2,2,2,2,2,2,2,3,2,2,2,0,0.0,neutral or dissatisfied +64351,124774,Male,Loyal Customer,44,Business travel,Business,2842,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +64352,33865,Female,Loyal Customer,26,Personal Travel,Eco,1698,2,1,2,3,3,2,3,3,3,4,4,3,4,3,26,38.0,neutral or dissatisfied +64353,23540,Female,Loyal Customer,11,Personal Travel,Eco,423,2,2,2,4,2,1,1,2,3,3,4,1,1,1,186,184.0,neutral or dissatisfied +64354,36002,Male,Loyal Customer,47,Business travel,Business,2341,4,3,3,3,1,3,4,4,4,4,4,4,4,4,0,8.0,neutral or dissatisfied +64355,52998,Male,Loyal Customer,48,Business travel,Eco,1208,5,1,1,1,5,5,5,5,3,5,3,3,2,5,8,0.0,satisfied +64356,35297,Male,Loyal Customer,34,Business travel,Business,3625,4,4,4,4,2,3,4,4,4,3,4,4,4,2,0,0.0,satisfied +64357,12000,Male,disloyal Customer,21,Business travel,Eco Plus,643,5,4,5,4,5,5,5,5,2,5,2,5,5,5,0,0.0,satisfied +64358,38193,Male,Loyal Customer,61,Personal Travel,Eco,1249,3,5,3,2,4,3,4,4,3,4,5,3,5,4,2,0.0,neutral or dissatisfied +64359,2262,Female,Loyal Customer,60,Business travel,Business,1558,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +64360,50189,Female,disloyal Customer,25,Business travel,Eco,209,3,0,3,3,3,3,3,3,3,4,5,2,3,3,0,0.0,neutral or dissatisfied +64361,127009,Male,Loyal Customer,57,Business travel,Business,1914,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +64362,11050,Male,Loyal Customer,53,Personal Travel,Eco,201,2,1,2,4,2,2,2,2,2,3,3,4,4,2,35,36.0,neutral or dissatisfied +64363,64446,Male,Loyal Customer,64,Business travel,Business,989,2,4,4,4,1,4,4,2,2,2,2,2,2,3,10,4.0,neutral or dissatisfied +64364,103468,Female,Loyal Customer,48,Personal Travel,Eco Plus,393,2,1,2,4,1,3,4,5,5,2,5,1,5,3,3,0.0,neutral or dissatisfied +64365,56148,Female,Loyal Customer,39,Business travel,Business,1400,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +64366,37853,Female,Loyal Customer,21,Business travel,Eco,1023,3,3,2,3,3,4,5,3,2,3,2,2,1,3,41,14.0,satisfied +64367,64544,Male,disloyal Customer,34,Business travel,Business,469,3,3,3,2,3,3,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +64368,63253,Male,Loyal Customer,47,Business travel,Business,2437,1,1,1,1,3,5,5,5,5,5,5,4,5,5,14,0.0,satisfied +64369,122993,Female,disloyal Customer,48,Business travel,Business,328,5,5,5,4,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +64370,7930,Male,disloyal Customer,11,Business travel,Eco,864,3,3,3,3,2,3,2,2,3,5,4,2,3,2,34,37.0,neutral or dissatisfied +64371,37271,Male,Loyal Customer,40,Business travel,Business,3324,3,1,3,3,2,3,1,4,4,4,4,5,4,5,10,0.0,satisfied +64372,58150,Male,Loyal Customer,41,Business travel,Business,2069,4,4,3,4,3,4,5,4,4,4,4,5,4,4,51,51.0,satisfied +64373,25511,Female,Loyal Customer,50,Business travel,Business,1765,4,4,1,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +64374,19502,Male,Loyal Customer,47,Business travel,Eco,566,3,4,4,4,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +64375,78160,Male,Loyal Customer,49,Business travel,Business,259,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,4.0,satisfied +64376,29086,Female,Loyal Customer,22,Personal Travel,Eco,956,3,5,3,1,4,3,4,4,4,5,4,5,4,4,2,0.0,neutral or dissatisfied +64377,11759,Female,Loyal Customer,31,Business travel,Business,3790,5,5,4,5,5,5,5,5,4,5,3,4,2,5,0,8.0,satisfied +64378,72321,Female,Loyal Customer,39,Business travel,Business,2981,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +64379,121393,Male,Loyal Customer,55,Business travel,Business,2679,3,2,2,2,4,2,2,3,3,3,3,3,3,3,2,1.0,neutral or dissatisfied +64380,113004,Female,Loyal Customer,43,Personal Travel,Eco,1797,4,4,4,1,4,3,4,5,5,4,5,5,5,3,33,15.0,neutral or dissatisfied +64381,36404,Female,Loyal Customer,30,Business travel,Eco Plus,632,3,2,1,2,3,3,3,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +64382,125651,Female,disloyal Customer,28,Business travel,Business,759,1,1,1,1,3,1,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +64383,124955,Female,Loyal Customer,64,Personal Travel,Business,184,3,5,3,3,5,5,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +64384,83207,Female,Loyal Customer,8,Personal Travel,Eco,1123,2,5,2,3,2,2,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +64385,65772,Male,disloyal Customer,22,Business travel,Business,1389,5,0,5,3,3,5,3,3,3,4,4,3,4,3,3,2.0,satisfied +64386,118090,Female,Loyal Customer,16,Personal Travel,Eco,1276,1,5,1,4,3,1,3,3,3,5,3,5,5,3,14,0.0,neutral or dissatisfied +64387,24149,Male,Loyal Customer,60,Business travel,Eco,147,4,3,5,5,4,4,4,4,4,4,1,1,5,4,46,50.0,satisfied +64388,9907,Female,disloyal Customer,38,Business travel,Business,457,4,4,4,4,2,4,2,2,3,2,5,4,5,2,9,8.0,satisfied +64389,31768,Male,Loyal Customer,27,Business travel,Business,2936,3,5,4,5,3,3,3,3,1,5,3,2,4,3,10,0.0,neutral or dissatisfied +64390,18233,Male,Loyal Customer,33,Business travel,Business,2294,5,5,5,5,4,4,4,4,4,4,5,2,2,4,0,0.0,satisfied +64391,90775,Male,Loyal Customer,51,Business travel,Business,1521,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +64392,94553,Male,Loyal Customer,39,Business travel,Business,239,2,5,5,5,2,4,4,2,2,2,2,2,2,4,51,55.0,neutral or dissatisfied +64393,118940,Female,Loyal Customer,25,Business travel,Business,1618,4,4,4,4,4,4,4,4,5,3,3,4,5,4,0,10.0,satisfied +64394,106426,Male,Loyal Customer,52,Personal Travel,Eco,551,2,4,2,5,3,2,3,3,5,1,2,4,4,3,4,0.0,neutral or dissatisfied +64395,61066,Male,Loyal Customer,36,Business travel,Eco,1546,2,5,1,5,2,2,2,2,2,5,2,4,3,2,0,0.0,neutral or dissatisfied +64396,3945,Male,disloyal Customer,25,Business travel,Business,765,3,0,3,4,3,5,5,4,3,4,5,5,3,5,172,172.0,neutral or dissatisfied +64397,21888,Male,disloyal Customer,27,Business travel,Eco,503,3,5,3,3,3,3,3,3,4,3,3,4,1,3,0,0.0,neutral or dissatisfied +64398,43149,Female,Loyal Customer,31,Personal Travel,Eco Plus,236,3,3,3,5,3,3,3,3,3,2,2,5,5,3,0,5.0,neutral or dissatisfied +64399,70986,Female,Loyal Customer,40,Business travel,Business,802,3,3,3,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +64400,96876,Female,Loyal Customer,59,Personal Travel,Eco,781,2,5,2,4,5,4,5,1,1,2,2,4,1,5,1,0.0,neutral or dissatisfied +64401,34058,Female,Loyal Customer,32,Business travel,Business,1674,3,3,3,3,3,3,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +64402,105896,Female,Loyal Customer,56,Business travel,Business,3644,4,2,2,2,4,4,4,2,4,3,4,4,2,4,108,153.0,neutral or dissatisfied +64403,86417,Male,disloyal Customer,21,Business travel,Eco,760,3,3,3,4,3,5,5,3,2,3,4,5,1,5,345,350.0,neutral or dissatisfied +64404,67941,Male,Loyal Customer,39,Personal Travel,Eco,1235,2,1,2,2,2,2,2,2,2,5,3,4,2,2,8,6.0,neutral or dissatisfied +64405,71586,Male,disloyal Customer,60,Business travel,Business,1144,1,1,1,3,3,1,3,3,4,1,2,4,2,3,73,81.0,neutral or dissatisfied +64406,46792,Male,Loyal Customer,42,Business travel,Business,3065,2,1,1,1,1,4,4,2,2,1,2,2,2,4,0,11.0,neutral or dissatisfied +64407,104646,Male,Loyal Customer,31,Business travel,Business,1754,4,4,4,4,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +64408,35823,Female,disloyal Customer,36,Business travel,Eco,1065,4,4,4,2,5,4,5,5,4,4,1,1,2,5,0,0.0,neutral or dissatisfied +64409,41826,Female,Loyal Customer,38,Personal Travel,Eco,257,0,5,0,3,3,0,3,3,3,1,5,2,3,3,0,0.0,satisfied +64410,112137,Male,disloyal Customer,21,Business travel,Eco,895,1,0,0,3,2,0,2,2,3,3,5,4,5,2,1,0.0,neutral or dissatisfied +64411,96161,Male,Loyal Customer,44,Business travel,Business,1575,2,1,2,2,2,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +64412,87824,Female,Loyal Customer,44,Business travel,Eco,214,4,3,3,3,4,5,1,4,4,4,4,5,4,3,6,0.0,satisfied +64413,90417,Male,Loyal Customer,34,Business travel,Business,594,4,4,5,4,4,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +64414,5351,Male,disloyal Customer,32,Business travel,Business,812,2,2,2,3,2,2,5,2,4,2,5,4,4,2,22,69.0,neutral or dissatisfied +64415,34132,Male,Loyal Customer,44,Business travel,Business,3795,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +64416,124827,Female,Loyal Customer,35,Business travel,Eco,280,4,5,5,5,4,5,4,4,5,2,1,5,4,4,52,59.0,satisfied +64417,99596,Male,Loyal Customer,50,Personal Travel,Eco,1025,2,5,2,1,3,2,3,3,5,3,4,5,4,3,7,20.0,neutral or dissatisfied +64418,15728,Female,Loyal Customer,60,Personal Travel,Eco,419,4,5,5,4,4,2,4,2,2,5,2,4,2,3,0,12.0,neutral or dissatisfied +64419,97094,Female,disloyal Customer,20,Business travel,Business,1242,4,0,4,2,4,4,4,4,5,2,5,4,5,4,25,24.0,satisfied +64420,42940,Male,Loyal Customer,67,Business travel,Business,2443,1,1,5,1,2,5,5,5,5,5,4,3,5,5,0,4.0,satisfied +64421,28850,Female,disloyal Customer,14,Business travel,Eco,978,3,3,3,4,4,3,5,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +64422,84063,Male,Loyal Customer,62,Business travel,Eco,757,2,3,3,3,2,2,2,2,1,2,3,2,3,2,0,0.0,neutral or dissatisfied +64423,40150,Male,Loyal Customer,55,Business travel,Business,358,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +64424,68390,Male,disloyal Customer,26,Business travel,Business,1045,1,1,1,5,4,1,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +64425,123679,Male,disloyal Customer,36,Business travel,Business,214,4,4,4,3,3,4,5,3,1,4,2,4,2,3,4,3.0,neutral or dissatisfied +64426,39623,Female,Loyal Customer,18,Personal Travel,Eco,945,3,4,3,1,2,3,4,2,4,2,4,3,2,2,0,10.0,neutral or dissatisfied +64427,75404,Female,Loyal Customer,42,Business travel,Business,2342,1,1,4,1,2,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +64428,6046,Female,Loyal Customer,23,Business travel,Business,630,1,1,1,1,5,5,5,5,2,5,4,5,5,5,0,0.0,satisfied +64429,113164,Male,Loyal Customer,60,Business travel,Business,2142,2,2,2,2,3,5,5,3,3,3,3,5,3,3,2,0.0,satisfied +64430,96595,Female,Loyal Customer,37,Personal Travel,Eco,861,4,5,4,2,5,4,5,5,5,4,5,4,4,5,4,5.0,neutral or dissatisfied +64431,45058,Female,Loyal Customer,46,Business travel,Business,3126,0,0,0,1,4,4,3,2,2,2,2,5,2,5,0,0.0,satisfied +64432,27833,Male,Loyal Customer,41,Personal Travel,Eco,1533,1,1,1,3,4,1,4,4,4,3,1,4,2,4,0,0.0,neutral or dissatisfied +64433,72818,Female,Loyal Customer,42,Personal Travel,Eco Plus,1045,2,2,2,3,2,4,4,4,4,2,4,2,4,1,1,0.0,neutral or dissatisfied +64434,94925,Female,Loyal Customer,39,Business travel,Eco,233,5,2,2,2,5,5,5,5,5,4,5,2,1,5,3,0.0,satisfied +64435,54488,Female,disloyal Customer,30,Business travel,Eco,925,3,3,3,2,5,3,5,5,1,3,1,5,2,5,0,0.0,neutral or dissatisfied +64436,108792,Male,disloyal Customer,29,Business travel,Eco,406,2,0,3,1,1,3,1,1,1,3,4,5,1,1,7,0.0,neutral or dissatisfied +64437,61873,Male,Loyal Customer,51,Business travel,Business,2521,2,2,4,2,4,5,4,5,5,5,5,5,5,3,5,0.0,satisfied +64438,97683,Female,Loyal Customer,40,Business travel,Business,3926,2,2,4,2,4,5,5,4,4,4,4,4,4,4,25,31.0,satisfied +64439,78601,Male,Loyal Customer,37,Personal Travel,Eco,2454,3,4,3,3,5,3,4,5,1,2,3,1,3,5,0,0.0,neutral or dissatisfied +64440,9731,Male,Loyal Customer,38,Business travel,Eco,926,1,4,4,4,1,1,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +64441,128137,Female,Loyal Customer,53,Business travel,Business,1788,2,4,4,4,4,2,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +64442,118369,Female,Loyal Customer,58,Personal Travel,Eco Plus,602,3,4,3,4,1,5,5,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +64443,111133,Male,Loyal Customer,39,Business travel,Business,1180,5,5,2,5,3,5,5,5,5,5,5,3,5,3,58,40.0,satisfied +64444,65643,Male,Loyal Customer,47,Business travel,Business,926,3,3,3,3,3,5,5,5,5,5,5,3,5,4,3,0.0,satisfied +64445,13237,Male,Loyal Customer,37,Business travel,Eco,468,3,1,1,1,3,3,3,3,4,2,3,2,3,3,0,16.0,neutral or dissatisfied +64446,2565,Female,Loyal Customer,31,Business travel,Business,2597,1,3,3,3,1,1,1,1,2,4,4,3,3,1,0,0.0,neutral or dissatisfied +64447,104357,Male,Loyal Customer,47,Personal Travel,Eco Plus,452,3,5,3,5,3,3,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +64448,81884,Female,Loyal Customer,43,Business travel,Business,2480,2,2,2,2,2,5,4,4,4,4,4,3,4,5,6,4.0,satisfied +64449,17327,Female,Loyal Customer,56,Personal Travel,Eco,403,3,4,3,4,2,4,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +64450,13100,Male,Loyal Customer,48,Business travel,Business,427,3,3,3,3,2,2,2,4,4,4,4,1,4,5,1,0.0,satisfied +64451,74466,Female,disloyal Customer,22,Business travel,Eco,1235,4,4,4,4,5,4,5,5,3,5,4,4,5,5,0,0.0,satisfied +64452,69982,Female,Loyal Customer,58,Business travel,Business,236,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,9.0,satisfied +64453,23079,Female,Loyal Customer,58,Business travel,Business,1024,2,2,4,2,5,4,4,4,3,4,5,4,5,4,259,248.0,satisfied +64454,56081,Female,Loyal Customer,24,Personal Travel,Eco,2475,2,4,2,5,2,4,4,1,1,4,5,4,1,4,12,66.0,neutral or dissatisfied +64455,93901,Female,Loyal Customer,42,Personal Travel,Eco,588,3,5,3,4,4,5,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +64456,108626,Male,Loyal Customer,60,Personal Travel,Eco Plus,813,2,2,2,4,5,2,5,5,3,5,4,2,3,5,0,0.0,neutral or dissatisfied +64457,57730,Female,disloyal Customer,23,Business travel,Eco,1048,2,2,2,4,3,2,3,3,5,2,5,3,4,3,1,0.0,satisfied +64458,83784,Female,disloyal Customer,50,Business travel,Business,425,4,4,4,1,3,4,3,3,5,2,5,4,4,3,10,6.0,satisfied +64459,109587,Female,Loyal Customer,48,Business travel,Business,2187,3,3,3,3,4,4,4,5,5,4,5,3,5,5,3,0.0,satisfied +64460,71534,Male,Loyal Customer,42,Business travel,Business,3612,1,1,1,1,3,4,5,4,4,4,4,5,4,5,13,17.0,satisfied +64461,107520,Male,Loyal Customer,11,Personal Travel,Eco,838,3,5,3,3,5,3,5,5,4,2,4,5,5,5,53,40.0,neutral or dissatisfied +64462,68484,Female,Loyal Customer,19,Business travel,Business,3615,3,3,3,3,5,5,5,5,3,3,4,3,4,5,0,0.0,satisfied +64463,118603,Female,Loyal Customer,45,Business travel,Business,621,3,3,3,3,4,4,5,4,4,4,4,5,4,5,19,14.0,satisfied +64464,68637,Female,disloyal Customer,26,Business travel,Business,175,1,1,1,1,4,1,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +64465,109723,Female,disloyal Customer,11,Business travel,Eco,587,2,1,2,4,5,2,2,5,4,2,3,2,4,5,40,36.0,neutral or dissatisfied +64466,1575,Male,Loyal Customer,39,Business travel,Business,3704,4,3,3,3,5,4,4,2,2,2,4,2,2,1,19,12.0,neutral or dissatisfied +64467,87693,Female,Loyal Customer,31,Personal Travel,Eco,591,3,5,4,4,4,4,4,4,1,2,1,2,3,4,19,11.0,neutral or dissatisfied +64468,65793,Female,Loyal Customer,53,Business travel,Business,1389,1,1,1,1,2,4,5,4,4,4,4,3,4,3,22,26.0,satisfied +64469,2730,Male,disloyal Customer,25,Business travel,Business,772,0,0,0,3,4,0,4,4,4,4,4,3,5,4,0,0.0,satisfied +64470,42906,Female,disloyal Customer,36,Business travel,Eco,368,1,2,1,4,5,1,5,5,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +64471,4144,Male,Loyal Customer,39,Business travel,Business,431,2,2,2,2,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +64472,86702,Male,Loyal Customer,47,Business travel,Business,1747,1,1,1,1,2,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +64473,119599,Male,Loyal Customer,56,Business travel,Business,1979,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +64474,57546,Female,Loyal Customer,53,Personal Travel,Eco,413,3,2,3,2,1,2,2,5,5,3,5,2,5,1,0,0.0,neutral or dissatisfied +64475,66813,Male,Loyal Customer,58,Business travel,Business,731,5,5,5,5,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +64476,128641,Female,Loyal Customer,63,Personal Travel,Eco,679,3,4,3,2,3,4,5,1,1,3,1,4,1,5,8,0.0,neutral or dissatisfied +64477,98024,Male,Loyal Customer,48,Business travel,Business,1014,3,4,4,4,2,3,2,3,3,3,3,2,3,3,0,1.0,neutral or dissatisfied +64478,17390,Male,Loyal Customer,52,Personal Travel,Business,351,1,4,1,5,3,4,5,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +64479,109822,Female,disloyal Customer,47,Business travel,Business,1073,5,5,5,2,5,5,5,5,3,5,5,5,4,5,0,5.0,satisfied +64480,56899,Female,disloyal Customer,17,Business travel,Eco,1153,4,4,4,3,4,4,3,5,2,4,4,3,3,3,19,10.0,satisfied +64481,53210,Female,Loyal Customer,16,Business travel,Business,612,2,3,3,3,2,2,2,2,1,3,3,4,4,2,33,33.0,neutral or dissatisfied +64482,31721,Female,Loyal Customer,60,Personal Travel,Eco,846,1,5,0,4,2,5,4,2,2,0,2,4,2,4,11,20.0,neutral or dissatisfied +64483,36019,Female,Loyal Customer,42,Business travel,Business,399,2,2,2,2,5,4,5,4,4,4,4,1,4,4,25,27.0,satisfied +64484,127242,Female,Loyal Customer,37,Business travel,Business,1712,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,10.0,satisfied +64485,108428,Male,Loyal Customer,58,Business travel,Business,1444,2,2,3,2,2,4,5,4,4,4,4,4,4,4,26,31.0,satisfied +64486,92263,Male,disloyal Customer,24,Business travel,Eco,536,4,0,4,5,2,4,2,2,4,5,4,5,4,2,7,0.0,satisfied +64487,56793,Female,Loyal Customer,28,Business travel,Business,1605,2,1,2,2,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +64488,66057,Female,disloyal Customer,54,Business travel,Eco,655,5,0,5,1,2,5,2,2,5,4,1,4,1,2,0,0.0,satisfied +64489,288,Female,Loyal Customer,42,Personal Travel,Eco Plus,802,3,3,2,1,3,5,1,5,5,2,5,4,5,4,74,74.0,neutral or dissatisfied +64490,77136,Female,disloyal Customer,22,Business travel,Eco,1060,3,3,3,3,5,3,5,5,3,2,4,3,4,5,2,0.0,neutral or dissatisfied +64491,48495,Female,Loyal Customer,39,Business travel,Eco,846,5,2,2,2,5,5,5,5,1,4,2,5,4,5,39,30.0,satisfied +64492,75435,Male,disloyal Customer,27,Business travel,Business,1233,0,0,0,4,4,0,4,4,4,3,4,3,5,4,0,0.0,satisfied +64493,93170,Male,Loyal Customer,16,Personal Travel,Eco,1066,3,4,3,3,4,3,4,4,5,4,5,3,4,4,36,37.0,neutral or dissatisfied +64494,109363,Male,Loyal Customer,59,Business travel,Business,1189,1,1,1,1,3,5,5,4,4,4,4,3,4,4,33,9.0,satisfied +64495,91559,Female,Loyal Customer,52,Personal Travel,Eco,680,2,5,2,4,5,5,5,1,1,2,1,3,1,5,77,67.0,neutral or dissatisfied +64496,90910,Female,Loyal Customer,63,Business travel,Eco,515,4,2,3,3,4,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +64497,104817,Male,Loyal Customer,56,Business travel,Business,426,5,5,5,5,2,4,4,4,4,4,4,5,4,3,81,71.0,satisfied +64498,119118,Male,Loyal Customer,66,Personal Travel,Eco,1107,2,4,2,1,2,2,2,2,2,3,5,2,1,2,0,0.0,neutral or dissatisfied +64499,20121,Female,Loyal Customer,25,Business travel,Business,1586,2,2,2,2,5,5,5,5,3,4,5,1,3,5,98,100.0,satisfied +64500,33525,Male,Loyal Customer,41,Business travel,Business,1826,3,3,3,3,3,3,5,5,5,5,5,2,5,1,0,4.0,satisfied +64501,4188,Female,disloyal Customer,38,Business travel,Business,431,2,1,1,4,5,1,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +64502,127214,Female,Loyal Customer,19,Personal Travel,Eco Plus,370,2,0,2,3,3,2,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +64503,92613,Male,Loyal Customer,53,Business travel,Business,453,4,5,5,5,5,3,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +64504,49168,Male,Loyal Customer,30,Business travel,Business,78,4,4,4,4,5,5,3,5,3,5,4,2,2,5,0,0.0,satisfied +64505,108401,Male,Loyal Customer,60,Personal Travel,Eco Plus,1750,4,3,4,4,3,4,1,3,4,5,3,2,4,3,0,11.0,neutral or dissatisfied +64506,9976,Male,Loyal Customer,26,Personal Travel,Eco,534,2,4,2,3,3,2,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +64507,106720,Male,Loyal Customer,56,Business travel,Business,3601,5,5,2,5,4,4,4,5,5,5,5,5,5,3,85,88.0,satisfied +64508,120430,Female,disloyal Customer,23,Business travel,Eco,449,2,0,2,4,2,2,1,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +64509,28894,Male,Loyal Customer,31,Business travel,Business,956,5,5,5,5,4,4,4,4,2,1,3,3,2,4,0,0.0,satisfied +64510,62952,Female,Loyal Customer,34,Business travel,Eco,846,3,2,2,2,3,3,3,3,1,4,3,2,3,3,9,5.0,neutral or dissatisfied +64511,109387,Male,Loyal Customer,31,Personal Travel,Eco,1189,3,4,2,4,5,2,5,5,3,2,5,4,4,5,21,5.0,neutral or dissatisfied +64512,118285,Male,Loyal Customer,40,Business travel,Business,1919,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +64513,112846,Male,disloyal Customer,23,Business travel,Business,1357,4,0,4,5,4,4,4,4,3,3,5,5,4,4,0,0.0,satisfied +64514,52336,Male,Loyal Customer,80,Business travel,Business,3336,2,3,3,3,4,3,4,2,2,3,2,2,2,4,56,51.0,neutral or dissatisfied +64515,48357,Male,Loyal Customer,19,Business travel,Business,522,4,4,4,4,5,5,5,5,5,2,3,4,1,5,0,0.0,satisfied +64516,79346,Female,Loyal Customer,36,Business travel,Eco,620,3,4,4,4,3,3,3,3,2,1,3,2,3,3,21,56.0,neutral or dissatisfied +64517,101085,Male,Loyal Customer,29,Business travel,Business,1235,2,2,2,2,5,5,5,5,5,5,4,3,4,5,36,44.0,satisfied +64518,105187,Female,Loyal Customer,66,Personal Travel,Eco,289,1,5,1,1,5,4,4,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +64519,47442,Male,Loyal Customer,45,Business travel,Eco,141,4,2,2,2,4,4,4,4,1,1,4,4,3,4,1,0.0,satisfied +64520,113038,Male,Loyal Customer,42,Business travel,Business,3125,5,5,5,5,2,4,5,5,5,5,5,3,5,3,2,0.0,satisfied +64521,45976,Female,Loyal Customer,15,Business travel,Business,483,1,1,1,1,1,1,1,1,1,5,4,2,4,1,0,0.0,neutral or dissatisfied +64522,28338,Male,Loyal Customer,68,Business travel,Eco,867,3,4,4,4,3,3,3,3,4,3,3,4,2,3,22,23.0,neutral or dissatisfied +64523,79607,Male,disloyal Customer,22,Business travel,Eco,762,5,5,5,5,4,5,4,4,5,3,4,3,4,4,22,7.0,satisfied +64524,32899,Female,Loyal Customer,12,Personal Travel,Eco,216,1,4,0,3,5,0,3,5,3,2,5,3,5,5,16,18.0,neutral or dissatisfied +64525,49576,Male,Loyal Customer,57,Business travel,Business,89,0,4,0,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +64526,89002,Female,Loyal Customer,46,Business travel,Business,1947,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +64527,88367,Female,Loyal Customer,31,Business travel,Business,545,3,4,4,4,3,3,3,3,4,4,3,2,2,3,0,0.0,neutral or dissatisfied +64528,110231,Male,Loyal Customer,38,Business travel,Business,1036,3,3,3,3,4,5,5,4,4,4,4,5,4,4,19,7.0,satisfied +64529,27525,Male,Loyal Customer,60,Personal Travel,Eco,672,5,4,4,4,4,4,4,4,1,3,3,4,2,4,0,0.0,satisfied +64530,62532,Male,Loyal Customer,49,Business travel,Business,1744,3,3,3,3,2,4,5,3,3,4,3,3,3,3,9,5.0,satisfied +64531,26454,Female,Loyal Customer,56,Business travel,Eco,925,2,4,4,4,5,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +64532,71004,Male,disloyal Customer,23,Business travel,Eco,802,3,3,3,2,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +64533,116686,Female,Loyal Customer,54,Business travel,Eco Plus,325,1,1,1,1,2,2,3,1,1,1,1,1,1,3,92,90.0,neutral or dissatisfied +64534,48709,Male,Loyal Customer,44,Business travel,Business,308,3,4,3,3,2,5,4,4,4,4,4,3,4,3,24,24.0,satisfied +64535,25025,Male,Loyal Customer,37,Business travel,Eco,907,5,2,2,2,5,4,5,5,1,4,3,2,4,5,0,11.0,neutral or dissatisfied +64536,87827,Male,disloyal Customer,38,Business travel,Business,214,1,1,1,1,4,1,3,4,1,4,2,3,5,4,0,0.0,neutral or dissatisfied +64537,107487,Female,Loyal Customer,47,Business travel,Eco,711,1,5,5,5,1,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +64538,46876,Male,Loyal Customer,43,Business travel,Eco,845,5,5,5,5,5,5,5,5,5,1,2,1,2,5,0,0.0,satisfied +64539,23284,Male,Loyal Customer,35,Business travel,Eco,563,4,4,4,4,4,4,4,4,5,1,5,3,1,4,113,104.0,satisfied +64540,29121,Male,Loyal Customer,33,Personal Travel,Eco,605,4,5,4,3,4,4,4,4,1,3,5,2,5,4,0,0.0,satisfied +64541,52739,Male,Loyal Customer,50,Business travel,Eco,2306,4,5,5,5,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +64542,24041,Female,Loyal Customer,32,Personal Travel,Eco,595,3,2,4,3,2,4,2,2,3,2,3,2,2,2,3,0.0,neutral or dissatisfied +64543,42464,Female,Loyal Customer,80,Business travel,Eco Plus,526,3,3,3,3,1,4,3,3,3,3,3,3,3,3,0,6.0,neutral or dissatisfied +64544,24650,Female,Loyal Customer,44,Business travel,Business,873,4,4,4,4,5,5,1,4,4,4,4,1,4,1,0,0.0,satisfied +64545,63787,Female,Loyal Customer,47,Business travel,Business,2966,1,1,1,1,4,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +64546,107434,Male,Loyal Customer,30,Personal Travel,Eco,725,1,4,1,4,3,1,3,3,3,5,2,2,2,3,25,0.0,neutral or dissatisfied +64547,55927,Female,Loyal Customer,64,Personal Travel,Eco,723,1,5,0,2,1,4,4,4,4,0,5,3,4,2,0,0.0,neutral or dissatisfied +64548,96974,Female,Loyal Customer,43,Business travel,Business,883,1,1,2,1,4,5,4,5,5,5,5,5,5,4,0,10.0,satisfied +64549,109637,Female,Loyal Customer,48,Business travel,Business,1597,5,5,5,5,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +64550,50222,Female,Loyal Customer,39,Business travel,Eco,109,5,5,5,5,5,5,5,5,1,2,4,2,4,5,0,0.0,satisfied +64551,6631,Female,Loyal Customer,24,Personal Travel,Eco,719,2,4,2,4,2,1,1,3,2,5,5,1,4,1,264,261.0,neutral or dissatisfied +64552,53747,Female,Loyal Customer,11,Personal Travel,Eco Plus,1208,3,3,3,2,2,3,1,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +64553,106744,Female,Loyal Customer,27,Business travel,Business,3344,2,2,2,2,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +64554,12139,Female,Loyal Customer,31,Business travel,Business,1075,2,2,2,2,4,4,4,4,3,1,2,5,5,4,0,11.0,satisfied +64555,32670,Male,Loyal Customer,32,Business travel,Business,3280,2,2,2,2,2,2,2,2,2,5,3,1,2,2,15,21.0,neutral or dissatisfied +64556,42714,Male,Loyal Customer,55,Personal Travel,Eco Plus,604,2,5,2,4,4,2,4,4,3,4,4,3,4,4,93,81.0,neutral or dissatisfied +64557,99343,Female,disloyal Customer,41,Business travel,Eco,1771,3,3,3,3,2,3,2,2,4,4,2,3,4,2,20,23.0,neutral or dissatisfied +64558,74932,Male,Loyal Customer,35,Business travel,Eco,2446,2,3,3,3,2,3,2,2,4,1,1,4,2,2,0,0.0,neutral or dissatisfied +64559,72129,Male,Loyal Customer,9,Business travel,Eco,731,3,4,4,4,3,2,4,3,1,1,4,1,3,3,2,0.0,neutral or dissatisfied +64560,55842,Female,Loyal Customer,11,Personal Travel,Eco,1416,2,5,2,5,2,1,1,2,3,1,1,1,2,1,201,216.0,neutral or dissatisfied +64561,54101,Male,Loyal Customer,56,Business travel,Eco Plus,1416,4,1,1,1,5,4,5,5,4,5,3,4,3,5,0,0.0,satisfied +64562,63400,Female,Loyal Customer,14,Personal Travel,Eco,337,4,5,4,2,2,4,1,2,3,5,4,3,4,2,0,7.0,neutral or dissatisfied +64563,77547,Male,Loyal Customer,23,Business travel,Business,2935,5,5,5,5,4,4,4,4,5,1,4,1,5,4,10,1.0,satisfied +64564,27706,Female,Loyal Customer,23,Business travel,Business,1448,4,4,4,4,4,4,4,4,3,3,5,4,5,4,0,0.0,satisfied +64565,76341,Female,Loyal Customer,58,Business travel,Business,954,5,5,5,5,2,5,5,4,4,4,4,4,4,5,14,8.0,satisfied +64566,104636,Male,disloyal Customer,45,Business travel,Business,861,4,4,4,1,4,4,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +64567,88681,Female,Loyal Customer,29,Personal Travel,Eco,404,5,4,5,4,3,5,3,3,4,4,4,3,4,3,18,0.0,satisfied +64568,109264,Male,Loyal Customer,39,Personal Travel,Eco Plus,401,3,5,3,1,1,3,1,1,4,4,5,4,4,1,27,20.0,neutral or dissatisfied +64569,55980,Female,Loyal Customer,30,Personal Travel,Eco,1620,2,4,2,1,2,2,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +64570,22834,Female,Loyal Customer,31,Business travel,Business,2645,5,5,5,5,5,5,4,5,3,1,1,5,4,5,23,13.0,satisfied +64571,35944,Male,Loyal Customer,41,Business travel,Business,231,2,2,2,2,3,4,4,4,4,4,4,1,4,5,0,0.0,satisfied +64572,108904,Female,Loyal Customer,53,Business travel,Business,3529,1,2,2,2,4,3,3,1,1,1,1,2,1,3,9,11.0,neutral or dissatisfied +64573,88670,Female,Loyal Customer,8,Personal Travel,Eco,581,2,5,2,3,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +64574,78272,Female,Loyal Customer,48,Business travel,Business,1598,4,4,4,4,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +64575,15110,Male,Loyal Customer,57,Personal Travel,Business,1042,4,5,5,3,2,5,4,1,1,5,1,3,1,4,0,0.0,satisfied +64576,47566,Female,Loyal Customer,41,Personal Travel,Eco Plus,532,4,4,3,5,5,4,5,3,3,3,3,4,3,5,0,3.0,neutral or dissatisfied +64577,87249,Male,disloyal Customer,33,Business travel,Business,577,2,2,2,2,2,2,2,2,4,4,4,4,4,2,1,4.0,neutral or dissatisfied +64578,33452,Male,Loyal Customer,57,Personal Travel,Eco,2399,1,4,1,5,4,1,3,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +64579,91542,Male,Loyal Customer,22,Business travel,Business,3592,1,1,1,1,1,1,1,1,3,2,3,1,3,1,9,36.0,neutral or dissatisfied +64580,55079,Male,disloyal Customer,31,Business travel,Eco,1608,3,3,3,3,4,3,4,4,3,2,3,4,4,4,0,9.0,neutral or dissatisfied +64581,91847,Male,Loyal Customer,72,Business travel,Eco,1797,4,2,2,2,4,4,4,4,1,5,3,2,2,4,26,30.0,neutral or dissatisfied +64582,2193,Female,Loyal Customer,34,Personal Travel,Eco,624,2,2,2,3,5,2,5,5,4,2,3,2,3,5,0,2.0,neutral or dissatisfied +64583,41207,Female,Loyal Customer,28,Business travel,Business,1091,4,4,4,4,4,4,4,4,5,1,3,3,4,4,0,2.0,satisfied +64584,42696,Male,Loyal Customer,10,Personal Travel,Eco,604,4,5,4,3,2,4,2,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +64585,42943,Male,Loyal Customer,28,Personal Travel,Business,236,2,2,2,3,4,2,4,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +64586,85324,Female,Loyal Customer,21,Personal Travel,Eco,813,1,0,1,3,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +64587,58414,Male,Loyal Customer,36,Business travel,Eco,733,4,5,5,5,4,4,4,4,2,1,3,1,3,4,1,0.0,neutral or dissatisfied +64588,119572,Female,Loyal Customer,40,Business travel,Eco Plus,759,1,5,5,5,1,1,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +64589,42023,Male,Loyal Customer,37,Business travel,Business,2693,2,4,4,4,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +64590,86436,Male,Loyal Customer,31,Business travel,Business,1682,4,1,1,1,4,4,4,4,4,4,3,4,4,4,10,9.0,neutral or dissatisfied +64591,100649,Female,disloyal Customer,39,Business travel,Business,349,3,4,4,1,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +64592,112450,Female,Loyal Customer,45,Business travel,Eco,853,2,2,2,2,2,3,3,2,2,2,2,4,2,2,10,0.0,neutral or dissatisfied +64593,37662,Male,Loyal Customer,25,Personal Travel,Eco,1069,3,5,3,3,1,3,1,1,5,3,4,4,4,1,49,29.0,neutral or dissatisfied +64594,80236,Female,Loyal Customer,50,Business travel,Business,1269,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +64595,49557,Female,Loyal Customer,54,Business travel,Business,372,1,1,1,1,4,1,4,4,4,3,4,3,4,1,48,31.0,satisfied +64596,129369,Male,Loyal Customer,19,Business travel,Business,2565,3,3,3,3,4,5,4,4,3,5,4,3,5,4,1,0.0,satisfied +64597,42081,Female,Loyal Customer,17,Personal Travel,Eco Plus,106,5,1,5,2,3,5,3,3,4,4,3,3,2,3,0,5.0,satisfied +64598,78565,Male,Loyal Customer,34,Business travel,Business,2928,3,3,2,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +64599,52033,Female,Loyal Customer,23,Personal Travel,Eco,328,2,2,2,3,4,2,3,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +64600,122441,Male,Loyal Customer,42,Business travel,Business,3363,5,5,1,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +64601,65812,Male,disloyal Customer,28,Business travel,Eco,1444,3,3,3,3,5,3,5,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +64602,78744,Female,Loyal Customer,31,Business travel,Business,3387,1,1,4,1,1,1,1,1,3,4,4,4,4,1,0,6.0,neutral or dissatisfied +64603,80252,Female,disloyal Customer,22,Business travel,Business,1269,0,5,0,3,1,0,1,1,5,5,4,4,4,1,0,0.0,satisfied +64604,113872,Female,Loyal Customer,52,Personal Travel,Eco,1489,3,3,3,4,4,3,3,4,4,3,4,2,4,3,23,11.0,neutral or dissatisfied +64605,112878,Female,Loyal Customer,40,Business travel,Eco,1357,1,0,0,4,1,0,1,1,1,1,4,4,3,1,3,0.0,neutral or dissatisfied +64606,8894,Male,Loyal Customer,55,Business travel,Business,622,3,3,2,3,4,4,5,5,5,5,5,3,5,4,4,2.0,satisfied +64607,94004,Female,Loyal Customer,51,Business travel,Business,3619,5,4,5,5,2,4,5,4,4,4,4,3,4,4,18,41.0,satisfied +64608,2587,Female,Loyal Customer,44,Personal Travel,Eco,227,2,4,2,1,5,5,3,4,4,2,4,1,4,5,19,24.0,neutral or dissatisfied +64609,32895,Female,Loyal Customer,37,Personal Travel,Eco,84,3,3,3,2,2,3,2,2,3,4,2,2,3,2,5,9.0,neutral or dissatisfied +64610,96174,Male,Loyal Customer,23,Business travel,Business,2661,2,2,2,2,5,5,5,5,5,3,5,3,4,5,0,0.0,satisfied +64611,100372,Male,Loyal Customer,41,Personal Travel,Eco,1165,1,4,1,3,5,1,5,5,3,3,4,4,4,5,9,8.0,neutral or dissatisfied +64612,58076,Female,disloyal Customer,25,Business travel,Business,589,2,5,2,3,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +64613,118680,Male,Loyal Customer,55,Business travel,Business,3732,4,4,4,4,2,5,4,4,4,5,4,5,4,3,27,22.0,satisfied +64614,123995,Female,disloyal Customer,19,Business travel,Business,184,0,0,0,3,5,0,5,5,5,5,5,3,4,5,0,0.0,satisfied +64615,88450,Male,Loyal Customer,42,Business travel,Eco,240,3,5,5,5,3,3,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +64616,58730,Female,disloyal Customer,19,Business travel,Eco,1182,3,3,3,3,2,3,2,2,4,5,5,4,4,2,43,49.0,neutral or dissatisfied +64617,87958,Male,Loyal Customer,23,Business travel,Business,270,2,2,2,2,4,4,4,4,3,3,5,4,4,4,65,60.0,satisfied +64618,8173,Female,Loyal Customer,56,Business travel,Business,125,2,2,2,2,4,3,3,2,2,2,2,1,2,1,0,1.0,neutral or dissatisfied +64619,110038,Female,disloyal Customer,27,Business travel,Business,2039,1,1,1,3,5,1,2,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +64620,27852,Male,Loyal Customer,60,Personal Travel,Eco,1448,3,2,4,3,5,4,5,5,4,5,3,4,4,5,0,0.0,neutral or dissatisfied +64621,127942,Female,Loyal Customer,28,Business travel,Eco Plus,2300,1,3,3,3,1,1,1,1,4,2,4,4,3,1,0,0.0,neutral or dissatisfied +64622,27894,Female,Loyal Customer,59,Personal Travel,Eco,2329,4,4,4,5,1,4,3,1,1,4,1,2,1,4,0,0.0,neutral or dissatisfied +64623,112151,Female,disloyal Customer,24,Business travel,Eco,895,4,4,4,1,2,4,2,2,5,2,5,5,5,2,0,0.0,satisfied +64624,83192,Male,Loyal Customer,50,Business travel,Business,1123,4,4,4,4,5,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +64625,123507,Male,Loyal Customer,61,Personal Travel,Eco,2125,4,3,4,4,5,4,5,5,5,2,5,3,3,5,0,0.0,neutral or dissatisfied +64626,119253,Female,Loyal Customer,46,Business travel,Business,3498,2,2,2,2,5,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +64627,18248,Male,Loyal Customer,49,Personal Travel,Eco,179,2,5,2,4,2,2,3,3,2,4,4,3,3,3,152,162.0,neutral or dissatisfied +64628,112671,Female,Loyal Customer,31,Business travel,Business,723,4,4,4,4,5,5,5,5,3,4,4,4,5,5,1,0.0,satisfied +64629,36054,Female,Loyal Customer,45,Business travel,Business,3973,1,1,2,1,3,3,2,5,5,5,5,5,5,2,0,0.0,satisfied +64630,96189,Male,Loyal Customer,27,Business travel,Business,786,5,5,5,5,3,3,3,3,5,2,4,4,4,3,0,5.0,satisfied +64631,31875,Female,Loyal Customer,52,Business travel,Business,4983,3,5,5,5,3,3,3,3,3,3,5,3,2,3,16,0.0,satisfied +64632,23176,Female,Loyal Customer,35,Personal Travel,Eco,300,3,5,3,3,5,3,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +64633,68106,Male,Loyal Customer,18,Personal Travel,Eco,813,1,4,1,3,4,1,4,4,3,1,3,1,4,4,7,0.0,neutral or dissatisfied +64634,97367,Female,Loyal Customer,33,Personal Travel,Eco,872,1,1,1,3,2,1,2,2,2,3,1,1,3,2,44,46.0,neutral or dissatisfied +64635,16107,Female,Loyal Customer,38,Business travel,Eco Plus,349,5,1,1,1,5,5,5,5,1,3,5,2,4,5,0,0.0,satisfied +64636,25630,Male,disloyal Customer,26,Business travel,Eco,526,3,2,3,4,4,3,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +64637,33710,Female,Loyal Customer,56,Business travel,Eco,414,4,2,2,2,1,5,3,3,3,4,3,2,3,3,0,0.0,satisfied +64638,22835,Female,Loyal Customer,66,Business travel,Business,302,5,5,5,5,4,4,2,4,4,4,4,4,4,2,0,0.0,satisfied +64639,90472,Female,disloyal Customer,45,Business travel,Business,581,2,2,2,4,1,2,4,1,3,2,4,4,4,1,0,0.0,satisfied +64640,52251,Male,Loyal Customer,51,Business travel,Eco,370,5,4,4,4,5,5,5,5,5,1,4,3,1,5,22,24.0,satisfied +64641,60480,Male,disloyal Customer,45,Business travel,Business,862,1,2,2,1,4,1,4,4,5,4,5,3,5,4,4,4.0,neutral or dissatisfied +64642,15216,Female,Loyal Customer,55,Business travel,Business,2946,5,5,4,5,5,1,1,5,5,5,5,4,5,3,14,0.0,satisfied +64643,17385,Female,Loyal Customer,22,Personal Travel,Eco,637,4,5,4,1,3,4,3,3,3,4,5,5,5,3,58,45.0,neutral or dissatisfied +64644,54818,Female,Loyal Customer,30,Business travel,Business,1636,1,1,1,1,4,4,4,4,2,1,3,1,4,4,0,0.0,satisfied +64645,99308,Female,disloyal Customer,23,Business travel,Eco,448,3,2,3,1,3,3,3,3,1,2,1,3,1,3,4,0.0,neutral or dissatisfied +64646,30767,Female,Loyal Customer,18,Business travel,Eco,936,2,5,5,5,2,2,2,2,3,3,4,3,4,2,0,1.0,neutral or dissatisfied +64647,2010,Male,Loyal Customer,41,Personal Travel,Eco Plus,190,4,4,4,3,5,4,5,5,4,5,4,4,5,5,86,118.0,neutral or dissatisfied +64648,106689,Male,disloyal Customer,34,Business travel,Business,516,2,2,2,4,2,2,2,2,4,2,5,4,4,2,8,17.0,neutral or dissatisfied +64649,125069,Male,Loyal Customer,49,Business travel,Business,3317,4,4,4,4,5,5,4,2,2,3,2,4,2,4,0,0.0,satisfied +64650,103870,Male,Loyal Customer,25,Personal Travel,Eco,869,3,2,3,4,1,3,4,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +64651,81395,Male,Loyal Customer,12,Personal Travel,Eco,1013,4,5,4,3,3,4,4,3,3,4,1,5,5,3,9,0.0,neutral or dissatisfied +64652,60285,Male,Loyal Customer,49,Business travel,Business,783,1,1,1,1,5,4,4,4,4,4,4,5,4,4,3,4.0,satisfied +64653,66924,Female,Loyal Customer,45,Business travel,Business,2871,1,1,1,1,5,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +64654,38807,Female,Loyal Customer,36,Personal Travel,Eco,387,2,4,2,2,1,2,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +64655,40815,Male,Loyal Customer,69,Business travel,Business,2764,1,4,4,4,1,4,3,1,1,1,1,1,1,3,29,15.0,neutral or dissatisfied +64656,16802,Female,Loyal Customer,43,Business travel,Business,645,1,1,1,1,3,5,5,4,4,4,4,5,4,5,9,5.0,satisfied +64657,13843,Female,Loyal Customer,47,Personal Travel,Eco,628,3,4,3,5,2,5,4,4,4,3,1,3,4,5,0,0.0,neutral or dissatisfied +64658,6128,Female,Loyal Customer,40,Business travel,Business,409,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +64659,20914,Female,Loyal Customer,55,Business travel,Eco,689,4,2,2,2,2,4,1,4,4,4,4,3,4,2,52,51.0,satisfied +64660,45446,Male,Loyal Customer,57,Business travel,Business,3975,1,1,1,1,5,5,5,3,2,4,4,5,5,5,228,219.0,satisfied +64661,98974,Female,Loyal Customer,61,Personal Travel,Eco,543,2,5,2,3,5,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +64662,34665,Male,Loyal Customer,35,Business travel,Business,264,2,2,2,2,2,5,4,4,4,4,4,5,4,5,2,7.0,satisfied +64663,76053,Male,Loyal Customer,42,Business travel,Business,3177,3,3,3,3,4,4,4,3,3,3,3,4,3,4,3,36.0,satisfied +64664,80998,Female,Loyal Customer,69,Personal Travel,Eco,297,4,2,4,3,4,4,4,1,1,4,1,3,1,4,36,21.0,neutral or dissatisfied +64665,66188,Male,Loyal Customer,29,Business travel,Business,3833,3,3,3,3,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +64666,16100,Male,Loyal Customer,46,Personal Travel,Eco,303,1,5,1,4,4,1,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +64667,106074,Female,Loyal Customer,42,Business travel,Business,3226,0,0,0,1,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +64668,116609,Female,disloyal Customer,21,Business travel,Business,325,4,4,4,4,2,4,2,2,5,2,4,5,5,2,1,0.0,satisfied +64669,99841,Female,disloyal Customer,30,Business travel,Eco,534,3,1,3,3,2,3,2,2,3,5,2,1,3,2,25,19.0,neutral or dissatisfied +64670,61858,Female,Loyal Customer,48,Personal Travel,Eco Plus,1504,1,5,0,4,5,2,3,5,5,0,5,3,5,1,0,0.0,neutral or dissatisfied +64671,107538,Female,Loyal Customer,37,Business travel,Business,1521,5,5,3,5,5,5,4,2,2,2,2,4,2,3,10,0.0,satisfied +64672,90282,Female,Loyal Customer,66,Business travel,Business,3363,2,2,1,2,4,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +64673,43854,Female,Loyal Customer,45,Business travel,Business,3364,3,3,3,3,3,1,4,4,4,4,5,5,4,4,0,24.0,satisfied +64674,109084,Female,Loyal Customer,58,Personal Travel,Eco,781,2,5,2,2,2,2,1,5,5,2,5,2,5,2,0,0.0,neutral or dissatisfied +64675,64588,Female,Loyal Customer,58,Business travel,Business,3033,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +64676,65976,Male,disloyal Customer,75,Business travel,Eco,972,2,2,2,1,4,2,4,4,5,3,4,5,1,4,0,0.0,neutral or dissatisfied +64677,12609,Female,Loyal Customer,29,Business travel,Eco Plus,542,3,5,5,5,3,3,3,3,2,1,3,4,4,3,86,89.0,neutral or dissatisfied +64678,77639,Male,Loyal Customer,45,Business travel,Eco,874,2,4,4,4,2,2,2,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +64679,78197,Female,disloyal Customer,33,Business travel,Eco,153,3,1,3,3,1,3,1,1,3,2,3,1,4,1,44,54.0,neutral or dissatisfied +64680,20087,Male,disloyal Customer,34,Business travel,Business,416,2,2,2,2,4,2,4,4,3,4,5,5,4,4,77,65.0,neutral or dissatisfied +64681,114400,Female,Loyal Customer,55,Business travel,Business,362,2,2,1,2,2,5,4,5,5,5,5,4,5,4,3,7.0,satisfied +64682,19724,Female,Loyal Customer,7,Personal Travel,Eco,409,2,4,2,5,5,2,5,5,4,5,4,4,4,5,7,0.0,neutral or dissatisfied +64683,52455,Female,Loyal Customer,53,Business travel,Eco Plus,237,5,2,5,2,4,5,2,5,5,5,5,4,5,1,0,0.0,satisfied +64684,70275,Male,Loyal Customer,54,Business travel,Business,852,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +64685,57815,Female,Loyal Customer,54,Business travel,Business,3330,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,28.0,satisfied +64686,26705,Male,Loyal Customer,42,Personal Travel,Eco,406,3,3,3,3,2,3,5,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +64687,95075,Female,Loyal Customer,19,Personal Travel,Eco,248,4,4,4,2,2,4,2,2,5,2,5,4,5,2,0,0.0,satisfied +64688,52779,Female,Loyal Customer,50,Business travel,Eco,1874,2,4,4,4,1,2,3,2,2,2,2,1,2,4,4,0.0,neutral or dissatisfied +64689,116394,Male,Loyal Customer,49,Personal Travel,Eco,337,3,4,3,2,4,3,4,4,5,1,2,3,3,4,0,0.0,neutral or dissatisfied +64690,12080,Female,Loyal Customer,26,Business travel,Eco Plus,376,4,4,4,4,5,5,4,5,1,2,4,3,1,5,0,0.0,satisfied +64691,38743,Female,Loyal Customer,22,Business travel,Eco,354,1,3,3,3,1,1,4,1,2,3,3,4,4,1,27,19.0,neutral or dissatisfied +64692,86264,Male,Loyal Customer,58,Personal Travel,Eco,356,5,4,5,2,2,5,2,2,3,4,5,4,5,2,12,0.0,satisfied +64693,124874,Male,Loyal Customer,42,Business travel,Business,3959,2,2,2,2,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +64694,66883,Male,Loyal Customer,54,Business travel,Business,2368,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +64695,69412,Male,Loyal Customer,59,Business travel,Business,1096,2,2,2,2,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +64696,86957,Female,Loyal Customer,56,Business travel,Business,907,2,2,2,2,5,4,5,4,4,4,4,5,4,5,28,15.0,satisfied +64697,17760,Female,disloyal Customer,19,Business travel,Eco Plus,456,2,2,2,4,2,1,1,4,4,4,4,1,2,1,141,127.0,neutral or dissatisfied +64698,46907,Female,Loyal Customer,34,Business travel,Business,2347,4,4,4,4,5,5,2,4,4,4,4,4,4,5,7,0.0,satisfied +64699,83798,Female,Loyal Customer,60,Business travel,Business,2584,1,1,1,1,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +64700,30040,Female,Loyal Customer,48,Business travel,Business,253,1,5,5,5,2,3,3,1,1,1,1,1,1,2,37,30.0,neutral or dissatisfied +64701,9235,Female,Loyal Customer,42,Business travel,Business,2307,3,2,2,2,3,3,4,3,3,3,3,4,3,4,0,3.0,neutral or dissatisfied +64702,106889,Male,Loyal Customer,39,Business travel,Business,2297,4,1,1,1,3,3,3,2,2,2,4,4,2,4,40,28.0,neutral or dissatisfied +64703,100863,Female,Loyal Customer,52,Business travel,Business,1605,3,3,5,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +64704,36842,Male,Loyal Customer,29,Personal Travel,Eco,369,5,1,5,4,5,5,5,5,3,2,3,2,4,5,0,0.0,satisfied +64705,72350,Male,Loyal Customer,45,Business travel,Business,3458,3,5,5,5,4,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +64706,76987,Male,Loyal Customer,46,Business travel,Business,368,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +64707,103411,Male,Loyal Customer,57,Business travel,Business,237,2,4,4,4,2,4,4,2,2,2,2,3,2,2,58,58.0,neutral or dissatisfied +64708,118068,Male,disloyal Customer,36,Business travel,Business,1044,2,2,2,2,2,2,2,2,5,4,5,5,5,2,53,53.0,neutral or dissatisfied +64709,90054,Female,disloyal Customer,40,Business travel,Business,957,5,5,5,3,4,5,5,4,3,4,5,5,4,4,11,23.0,satisfied +64710,88092,Female,Loyal Customer,47,Business travel,Business,1861,5,5,5,5,4,5,5,4,4,4,4,3,4,4,23,17.0,satisfied +64711,20918,Female,Loyal Customer,45,Business travel,Business,1735,1,1,1,1,2,4,1,4,4,5,4,1,4,1,0,0.0,satisfied +64712,2253,Female,Loyal Customer,44,Business travel,Business,2736,4,4,4,4,5,4,4,5,5,5,5,3,5,5,10,15.0,satisfied +64713,109199,Female,disloyal Customer,20,Business travel,Eco,612,3,4,3,3,2,3,1,2,4,4,4,2,3,2,20,16.0,neutral or dissatisfied +64714,92425,Male,Loyal Customer,39,Business travel,Business,1947,3,3,3,3,2,3,5,4,4,4,4,4,4,5,27,14.0,satisfied +64715,105606,Female,Loyal Customer,46,Business travel,Business,2749,2,1,1,1,2,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +64716,55894,Male,Loyal Customer,44,Business travel,Business,1903,5,5,5,5,5,5,4,4,4,4,4,5,4,4,0,1.0,satisfied +64717,41424,Male,Loyal Customer,67,Personal Travel,Eco,809,3,4,3,4,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +64718,38806,Female,Loyal Customer,31,Personal Travel,Eco,353,1,5,1,3,4,1,4,4,3,2,4,2,5,4,0,0.0,neutral or dissatisfied +64719,123642,Male,Loyal Customer,57,Business travel,Business,214,5,5,5,5,2,5,5,4,4,4,5,4,4,4,0,0.0,satisfied +64720,6288,Male,Loyal Customer,62,Personal Travel,Eco,585,3,5,3,2,3,3,3,3,3,5,4,3,4,3,39,32.0,neutral or dissatisfied +64721,53293,Male,Loyal Customer,34,Business travel,Eco,758,5,1,1,1,5,5,5,5,1,4,5,4,4,5,0,0.0,satisfied +64722,110794,Female,Loyal Customer,17,Business travel,Business,3898,1,1,1,1,4,4,4,4,4,2,2,2,2,4,0,5.0,satisfied +64723,106642,Male,Loyal Customer,42,Business travel,Business,2653,2,2,1,2,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +64724,75419,Male,Loyal Customer,43,Business travel,Business,2218,3,3,2,3,2,3,5,5,5,5,5,5,5,3,0,3.0,satisfied +64725,55000,Male,disloyal Customer,36,Business travel,Business,1635,3,2,2,1,1,2,1,1,4,5,3,5,4,1,0,0.0,neutral or dissatisfied +64726,73694,Male,Loyal Customer,48,Business travel,Business,204,4,3,3,3,4,3,3,3,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +64727,77333,Male,Loyal Customer,23,Business travel,Business,2257,2,2,2,2,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +64728,63214,Male,Loyal Customer,53,Business travel,Business,447,4,4,4,4,2,4,4,5,5,5,5,5,5,3,8,0.0,satisfied +64729,120887,Male,Loyal Customer,48,Business travel,Business,2915,4,4,4,4,3,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +64730,104424,Female,Loyal Customer,48,Business travel,Eco,1024,3,5,5,5,1,3,2,3,3,3,3,4,3,1,0,15.0,neutral or dissatisfied +64731,36008,Male,Loyal Customer,47,Business travel,Business,2576,1,1,4,1,3,3,4,5,5,5,5,4,5,2,14,48.0,satisfied +64732,52110,Male,Loyal Customer,18,Personal Travel,Eco,639,4,4,3,4,2,3,2,2,5,2,5,5,5,2,0,5.0,neutral or dissatisfied +64733,47397,Male,Loyal Customer,31,Business travel,Business,532,3,1,1,1,3,3,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +64734,74913,Male,Loyal Customer,49,Business travel,Eco,2475,3,4,4,4,3,3,3,3,1,2,4,2,3,3,4,10.0,neutral or dissatisfied +64735,94298,Female,disloyal Customer,20,Business travel,Eco,239,4,0,4,4,1,4,3,1,3,3,5,3,4,1,0,0.0,satisfied +64736,20510,Female,disloyal Customer,22,Business travel,Eco,130,2,3,1,1,2,1,2,2,4,4,2,5,5,2,5,20.0,neutral or dissatisfied +64737,102840,Male,Loyal Customer,44,Business travel,Business,423,4,4,4,4,4,4,4,4,4,4,4,5,4,3,100,96.0,satisfied +64738,122536,Female,Loyal Customer,44,Business travel,Business,3922,1,1,2,1,2,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +64739,103523,Male,Loyal Customer,29,Business travel,Business,1641,1,1,5,1,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +64740,67375,Female,Loyal Customer,34,Business travel,Business,641,1,1,1,1,4,4,4,5,5,5,5,5,5,5,7,0.0,satisfied +64741,30001,Male,Loyal Customer,51,Business travel,Business,539,3,3,5,3,4,5,3,5,5,5,5,5,5,3,13,2.0,satisfied +64742,63828,Male,Loyal Customer,52,Business travel,Business,3227,4,4,4,4,3,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +64743,96556,Male,Loyal Customer,51,Personal Travel,Eco Plus,436,4,3,5,3,3,5,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +64744,55820,Female,Loyal Customer,40,Business travel,Business,1416,1,1,1,1,4,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +64745,97531,Male,Loyal Customer,18,Personal Travel,Eco,265,2,2,2,3,2,2,2,2,4,2,3,4,2,2,7,29.0,neutral or dissatisfied +64746,95698,Female,Loyal Customer,58,Business travel,Business,3834,0,1,1,5,3,4,4,2,2,2,2,3,2,4,15,7.0,satisfied +64747,32365,Male,Loyal Customer,39,Business travel,Eco,101,5,3,3,3,5,5,5,5,1,2,1,2,5,5,0,0.0,satisfied +64748,83465,Male,Loyal Customer,44,Business travel,Business,946,1,1,1,1,2,5,4,5,5,5,5,3,5,4,8,5.0,satisfied +64749,60301,Male,Loyal Customer,50,Business travel,Business,2436,4,4,4,4,1,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +64750,29481,Male,Loyal Customer,39,Business travel,Eco,1107,5,3,1,3,5,5,5,5,4,3,4,4,5,5,36,37.0,satisfied +64751,33801,Male,Loyal Customer,53,Business travel,Eco,1428,4,4,3,3,4,4,4,4,1,2,3,4,3,4,0,0.0,satisfied +64752,34371,Female,Loyal Customer,37,Business travel,Eco Plus,427,2,2,5,2,2,2,2,2,1,5,3,1,4,2,33,51.0,neutral or dissatisfied +64753,77454,Female,Loyal Customer,44,Business travel,Business,2211,1,1,1,1,5,4,4,2,2,2,2,3,2,4,0,5.0,satisfied +64754,82417,Male,Loyal Customer,31,Business travel,Business,2391,5,5,5,5,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +64755,126718,Female,Loyal Customer,40,Business travel,Business,2402,2,3,3,3,4,3,2,2,2,2,2,3,2,2,18,21.0,neutral or dissatisfied +64756,55326,Male,Loyal Customer,26,Business travel,Business,2195,5,1,4,4,5,4,5,5,1,1,3,4,3,5,3,0.0,neutral or dissatisfied +64757,14519,Male,Loyal Customer,42,Business travel,Business,288,4,4,3,4,4,1,2,4,4,4,4,5,4,1,90,91.0,satisfied +64758,92796,Female,Loyal Customer,50,Personal Travel,Business,1541,1,4,1,3,2,4,4,5,5,1,5,5,5,3,26,21.0,neutral or dissatisfied +64759,93003,Female,Loyal Customer,56,Business travel,Business,1524,3,3,3,3,2,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +64760,112149,Female,Loyal Customer,54,Business travel,Eco,895,4,1,1,1,4,3,4,4,4,4,4,4,4,1,0,13.0,neutral or dissatisfied +64761,89010,Female,Loyal Customer,50,Business travel,Business,1947,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,3.0,satisfied +64762,1001,Male,Loyal Customer,52,Business travel,Eco,89,5,2,2,2,5,5,5,5,1,3,2,2,4,5,0,0.0,satisfied +64763,69436,Male,Loyal Customer,14,Personal Travel,Eco,1096,2,0,1,5,5,1,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +64764,102374,Male,Loyal Customer,43,Business travel,Eco,223,5,1,1,1,5,5,5,5,1,4,1,4,4,5,32,30.0,satisfied +64765,33699,Female,disloyal Customer,45,Business travel,Eco,899,3,3,3,4,5,3,5,5,2,5,3,3,4,5,22,22.0,neutral or dissatisfied +64766,49696,Male,Loyal Customer,41,Business travel,Eco,190,3,2,2,2,3,3,3,3,2,4,3,2,4,3,56,37.0,neutral or dissatisfied +64767,91610,Male,Loyal Customer,53,Business travel,Business,2818,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +64768,32227,Male,Loyal Customer,48,Business travel,Business,3998,2,2,2,2,1,2,4,5,5,5,4,5,5,2,0,2.0,satisfied +64769,36239,Female,Loyal Customer,58,Business travel,Eco Plus,496,2,3,3,3,1,3,3,2,2,2,2,4,2,3,0,18.0,neutral or dissatisfied +64770,109535,Female,disloyal Customer,15,Business travel,Eco,992,4,4,4,4,1,4,1,1,4,3,3,2,3,1,38,29.0,neutral or dissatisfied +64771,11879,Male,Loyal Customer,20,Personal Travel,Eco,912,2,4,2,2,3,2,5,3,4,5,5,3,5,3,15,4.0,neutral or dissatisfied +64772,102581,Female,Loyal Customer,36,Business travel,Eco Plus,386,4,1,2,1,4,4,4,4,3,4,3,1,4,4,5,0.0,neutral or dissatisfied +64773,72020,Male,Loyal Customer,45,Business travel,Business,3711,5,5,5,5,2,2,2,3,3,4,4,2,5,2,12,7.0,satisfied +64774,86408,Male,Loyal Customer,60,Business travel,Business,2483,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +64775,115363,Female,disloyal Customer,26,Business travel,Eco,362,3,4,3,4,1,3,1,1,4,3,3,4,3,1,13,12.0,neutral or dissatisfied +64776,92879,Male,Loyal Customer,49,Business travel,Business,3632,4,2,4,4,3,4,4,5,5,5,5,3,5,4,0,11.0,satisfied +64777,33431,Male,Loyal Customer,56,Business travel,Business,2614,4,4,4,4,1,3,3,5,5,5,5,2,5,3,0,0.0,satisfied +64778,105789,Male,Loyal Customer,36,Personal Travel,Eco,787,4,4,4,4,2,4,2,2,4,4,4,3,4,2,3,0.0,neutral or dissatisfied +64779,123836,Female,Loyal Customer,59,Business travel,Business,3478,5,5,5,5,3,5,5,5,5,5,5,4,5,4,0,5.0,satisfied +64780,45080,Male,Loyal Customer,70,Personal Travel,Eco,588,1,4,1,1,1,4,4,5,5,4,5,4,5,4,88,158.0,neutral or dissatisfied +64781,90922,Male,Loyal Customer,23,Business travel,Business,270,5,5,5,5,5,5,5,5,1,1,3,2,4,5,0,0.0,satisfied +64782,75340,Female,Loyal Customer,46,Personal Travel,Eco,2504,2,1,2,2,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +64783,94235,Male,Loyal Customer,40,Business travel,Business,3888,3,3,3,3,5,4,5,5,5,5,5,4,5,3,2,7.0,satisfied +64784,40508,Female,Loyal Customer,70,Personal Travel,Eco,188,2,4,2,3,5,5,5,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +64785,3445,Female,Loyal Customer,29,Personal Travel,Eco,240,2,4,2,4,1,2,1,1,5,3,4,4,5,1,41,41.0,neutral or dissatisfied +64786,85988,Female,disloyal Customer,15,Business travel,Eco,432,2,3,1,4,1,1,1,1,3,4,3,4,4,1,0,0.0,neutral or dissatisfied +64787,62800,Female,Loyal Customer,49,Personal Travel,Eco,2556,2,4,2,3,2,5,5,5,5,5,4,5,5,5,0,14.0,neutral or dissatisfied +64788,50624,Female,Loyal Customer,7,Personal Travel,Eco,86,1,2,1,4,3,1,4,3,2,2,4,4,4,3,94,89.0,neutral or dissatisfied +64789,13110,Male,Loyal Customer,35,Business travel,Business,2175,5,5,5,5,2,5,4,5,5,5,5,2,5,1,58,50.0,satisfied +64790,13142,Male,Loyal Customer,66,Personal Travel,Eco,427,1,3,1,4,4,1,4,4,3,4,4,2,4,4,14,14.0,neutral or dissatisfied +64791,31873,Female,Loyal Customer,50,Business travel,Business,4983,4,4,4,4,4,4,4,2,2,4,4,4,3,4,0,0.0,satisfied +64792,41769,Male,Loyal Customer,14,Business travel,Eco,872,3,2,3,2,3,3,4,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +64793,71790,Male,Loyal Customer,27,Business travel,Business,1744,1,2,2,2,1,1,1,1,3,1,2,4,3,1,0,4.0,neutral or dissatisfied +64794,112679,Female,Loyal Customer,30,Business travel,Business,3311,1,1,1,1,2,2,2,2,4,2,4,3,4,2,0,0.0,satisfied +64795,86303,Male,Loyal Customer,62,Business travel,Business,226,3,3,3,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +64796,64861,Male,Loyal Customer,32,Business travel,Business,2656,2,2,2,2,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +64797,119008,Female,Loyal Customer,47,Personal Travel,Eco,459,4,2,4,3,3,4,3,2,2,4,2,4,2,1,2,,satisfied +64798,1875,Female,Loyal Customer,60,Business travel,Business,3819,1,1,1,1,4,5,5,4,4,5,4,3,4,5,4,0.0,satisfied +64799,26795,Female,Loyal Customer,51,Business travel,Business,2139,3,3,3,3,4,4,4,5,5,5,5,5,5,3,10,0.0,satisfied +64800,99281,Female,disloyal Customer,13,Business travel,Eco,935,2,2,2,5,3,2,4,3,3,3,4,4,4,3,8,1.0,neutral or dissatisfied +64801,44379,Male,Loyal Customer,61,Personal Travel,Eco,229,4,4,4,1,5,4,3,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +64802,98909,Male,disloyal Customer,22,Business travel,Eco,543,3,0,3,1,3,3,3,3,5,5,5,3,5,3,19,8.0,neutral or dissatisfied +64803,63596,Female,Loyal Customer,44,Business travel,Business,2133,2,2,2,2,3,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +64804,7637,Female,Loyal Customer,43,Business travel,Business,641,5,5,5,5,5,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +64805,42534,Male,Loyal Customer,46,Business travel,Business,3469,2,2,2,2,3,5,4,4,4,4,4,3,4,3,60,41.0,satisfied +64806,25213,Female,disloyal Customer,25,Business travel,Eco,925,1,1,1,4,2,1,2,2,3,5,3,1,3,2,9,0.0,neutral or dissatisfied +64807,44113,Male,Loyal Customer,47,Business travel,Eco Plus,473,2,5,5,5,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +64808,91258,Male,Loyal Customer,14,Personal Travel,Eco,404,3,4,2,1,4,2,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +64809,14224,Male,Loyal Customer,49,Personal Travel,Eco,692,4,4,4,3,4,4,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +64810,126304,Female,Loyal Customer,23,Personal Travel,Eco,631,3,5,3,1,2,3,4,2,4,3,2,1,2,2,0,0.0,neutral or dissatisfied +64811,125319,Female,Loyal Customer,50,Business travel,Business,599,5,5,5,5,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +64812,49902,Female,Loyal Customer,63,Business travel,Eco,109,3,5,4,4,1,1,2,3,3,3,3,3,3,1,6,9.0,neutral or dissatisfied +64813,73840,Female,disloyal Customer,28,Business travel,Business,1709,4,4,4,4,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +64814,111945,Male,Loyal Customer,55,Business travel,Business,3181,2,2,2,2,4,5,5,5,5,5,5,5,5,4,3,0.0,satisfied +64815,19804,Male,Loyal Customer,69,Personal Travel,Business,528,3,4,3,3,5,3,3,2,2,3,2,1,2,4,50,35.0,neutral or dissatisfied +64816,42909,Female,Loyal Customer,45,Personal Travel,Eco,200,4,3,4,2,2,3,5,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +64817,104868,Male,disloyal Customer,35,Business travel,Business,327,3,3,3,5,4,3,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +64818,38643,Female,Loyal Customer,38,Business travel,Eco,2611,3,1,1,1,3,3,3,3,3,1,4,3,3,3,30,5.0,neutral or dissatisfied +64819,36820,Male,Loyal Customer,64,Business travel,Business,369,2,5,5,5,5,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +64820,48015,Male,Loyal Customer,27,Personal Travel,Eco Plus,838,4,3,4,3,5,4,5,5,2,1,4,4,3,5,0,0.0,neutral or dissatisfied +64821,92268,Male,Loyal Customer,45,Business travel,Business,2036,5,5,5,5,3,3,4,5,5,5,5,5,5,3,6,0.0,satisfied +64822,7784,Female,Loyal Customer,31,Business travel,Business,3747,1,1,1,1,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +64823,85854,Female,disloyal Customer,30,Business travel,Eco Plus,666,3,3,3,1,5,3,5,5,4,4,3,2,2,5,5,0.0,neutral or dissatisfied +64824,102329,Male,Loyal Customer,55,Business travel,Business,3072,0,5,0,3,3,4,4,3,3,4,4,5,3,3,9,0.0,satisfied +64825,126311,Female,Loyal Customer,25,Personal Travel,Eco,590,3,4,3,3,4,3,1,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +64826,37346,Female,disloyal Customer,37,Business travel,Eco,950,2,2,2,4,1,2,1,1,4,4,2,1,5,1,0,0.0,neutral or dissatisfied +64827,92206,Male,disloyal Customer,38,Business travel,Eco,456,3,3,2,4,2,5,4,2,3,3,3,4,4,4,156,158.0,neutral or dissatisfied +64828,125052,Female,Loyal Customer,32,Business travel,Business,2300,3,3,3,3,5,5,5,5,5,4,5,4,5,5,1,0.0,satisfied +64829,128339,Female,disloyal Customer,22,Business travel,Eco,370,2,1,2,4,2,2,2,2,1,4,4,1,4,2,4,8.0,neutral or dissatisfied +64830,110392,Female,Loyal Customer,31,Business travel,Business,1704,1,5,1,1,4,4,4,4,4,2,4,4,4,4,12,9.0,satisfied +64831,106503,Male,Loyal Customer,61,Personal Travel,Eco,495,2,5,2,3,1,2,1,1,5,3,1,3,3,1,105,88.0,neutral or dissatisfied +64832,85398,Female,disloyal Customer,20,Business travel,Eco,214,2,0,2,1,3,2,5,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +64833,41955,Female,disloyal Customer,33,Business travel,Eco,618,2,0,2,1,2,2,2,2,5,2,2,2,3,2,0,0.0,neutral or dissatisfied +64834,38388,Female,Loyal Customer,62,Personal Travel,Eco Plus,1180,3,5,3,3,2,5,5,3,3,3,3,3,3,5,0,15.0,neutral or dissatisfied +64835,115894,Female,Loyal Customer,24,Business travel,Eco,337,5,5,5,5,5,5,4,5,1,4,2,1,2,5,0,0.0,satisfied +64836,93607,Male,Loyal Customer,54,Business travel,Business,577,3,3,3,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +64837,4746,Female,Loyal Customer,7,Personal Travel,Eco,888,2,5,2,3,5,2,5,5,5,3,4,4,4,5,0,4.0,neutral or dissatisfied +64838,106532,Female,disloyal Customer,36,Business travel,Business,271,4,4,4,2,3,4,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +64839,58468,Male,Loyal Customer,53,Business travel,Business,3395,3,4,4,4,2,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +64840,84484,Male,disloyal Customer,18,Business travel,Eco,730,5,5,5,3,4,5,4,4,3,3,4,5,5,4,0,0.0,satisfied +64841,123984,Female,Loyal Customer,32,Business travel,Business,1865,4,4,4,4,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +64842,46294,Female,Loyal Customer,55,Business travel,Eco,770,5,4,4,4,2,2,2,5,5,5,5,2,5,4,5,12.0,satisfied +64843,102337,Female,disloyal Customer,36,Business travel,Business,397,3,2,2,3,1,2,1,1,3,5,4,3,5,1,6,1.0,neutral or dissatisfied +64844,55544,Female,Loyal Customer,27,Business travel,Business,550,3,4,4,4,3,3,3,3,3,5,2,1,3,3,2,0.0,neutral or dissatisfied +64845,129278,Male,Loyal Customer,58,Business travel,Business,2402,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +64846,109867,Male,Loyal Customer,35,Business travel,Business,3102,1,1,1,1,2,4,4,1,1,1,1,2,1,3,20,15.0,neutral or dissatisfied +64847,10567,Female,disloyal Customer,44,Business travel,Business,316,5,5,5,3,2,5,4,2,5,3,5,3,5,2,50,47.0,satisfied +64848,84652,Female,Loyal Customer,44,Business travel,Business,363,2,3,1,3,5,3,3,2,2,2,2,1,2,1,1,1.0,neutral or dissatisfied +64849,49769,Female,Loyal Customer,54,Business travel,Eco,109,2,4,4,4,5,4,4,2,2,2,2,1,2,3,0,6.0,neutral or dissatisfied +64850,29048,Male,Loyal Customer,34,Personal Travel,Eco,978,2,5,2,3,2,2,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +64851,1420,Male,Loyal Customer,58,Personal Travel,Eco Plus,89,3,3,3,4,4,3,4,4,4,3,3,1,4,4,2,17.0,neutral or dissatisfied +64852,33825,Female,Loyal Customer,53,Business travel,Eco Plus,1521,2,4,4,4,5,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +64853,7549,Male,Loyal Customer,51,Business travel,Business,2639,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +64854,60156,Male,Loyal Customer,56,Personal Travel,Eco,1005,3,5,3,2,1,3,1,1,2,4,3,4,2,1,10,25.0,neutral or dissatisfied +64855,50566,Male,Loyal Customer,66,Personal Travel,Eco,373,5,5,5,5,2,5,2,2,4,1,1,4,5,2,9,0.0,satisfied +64856,23978,Female,Loyal Customer,39,Business travel,Eco Plus,596,4,4,4,4,4,4,4,4,5,5,2,3,3,4,46,43.0,satisfied +64857,76599,Male,disloyal Customer,27,Business travel,Eco,534,4,4,4,4,4,4,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +64858,36766,Female,Loyal Customer,28,Business travel,Eco,2704,0,0,0,5,0,4,3,2,5,5,5,3,4,3,0,2.0,satisfied +64859,6137,Male,Loyal Customer,71,Business travel,Eco,409,3,4,4,4,3,3,3,3,4,3,4,3,2,3,112,133.0,neutral or dissatisfied +64860,46835,Female,Loyal Customer,50,Business travel,Eco,737,5,3,3,3,1,2,5,5,5,5,5,3,5,5,0,0.0,satisfied +64861,8357,Male,disloyal Customer,23,Business travel,Business,701,4,0,4,2,1,4,1,1,4,4,5,5,4,1,0,0.0,satisfied +64862,127921,Male,Loyal Customer,50,Business travel,Business,2300,1,1,4,1,2,5,4,5,5,4,5,4,5,4,18,40.0,satisfied +64863,105667,Male,Loyal Customer,46,Business travel,Business,2582,2,2,2,2,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +64864,23956,Female,Loyal Customer,56,Personal Travel,Eco,936,0,4,0,4,5,4,4,2,2,0,2,3,2,1,0,0.0,satisfied +64865,64688,Female,Loyal Customer,55,Business travel,Business,2233,2,2,2,2,5,5,4,4,4,4,4,4,4,5,3,4.0,satisfied +64866,75445,Female,disloyal Customer,17,Business travel,Eco,1240,2,2,2,4,4,2,4,4,4,4,2,4,3,4,2,0.0,neutral or dissatisfied +64867,114239,Male,disloyal Customer,27,Business travel,Eco,909,1,1,1,2,5,1,5,5,4,4,2,1,2,5,0,15.0,neutral or dissatisfied +64868,112685,Male,disloyal Customer,26,Business travel,Business,697,5,4,4,3,1,4,1,1,4,2,4,3,4,1,34,33.0,satisfied +64869,24744,Male,Loyal Customer,49,Business travel,Eco,432,5,4,4,4,5,5,5,5,4,1,1,3,4,5,0,0.0,satisfied +64870,21679,Male,Loyal Customer,20,Business travel,Eco,746,4,1,1,1,4,5,3,4,1,5,5,2,1,4,0,0.0,satisfied +64871,53717,Female,Loyal Customer,64,Personal Travel,Eco,1190,3,4,3,1,2,3,4,3,3,3,3,3,3,4,23,0.0,neutral or dissatisfied +64872,32177,Female,Loyal Customer,45,Business travel,Eco,201,5,5,3,5,2,5,1,5,5,5,5,5,5,5,0,3.0,satisfied +64873,21813,Male,Loyal Customer,51,Personal Travel,Eco,352,2,5,4,3,4,4,5,4,5,2,4,5,4,4,63,56.0,neutral or dissatisfied +64874,127264,Female,Loyal Customer,33,Business travel,Business,3924,4,4,4,4,4,3,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +64875,81743,Female,Loyal Customer,41,Business travel,Business,1416,4,4,4,4,3,4,4,5,5,5,5,3,5,3,55,41.0,satisfied +64876,67106,Male,Loyal Customer,52,Business travel,Eco,929,2,5,5,5,2,2,2,2,1,1,2,2,3,2,23,8.0,neutral or dissatisfied +64877,91118,Female,Loyal Customer,34,Personal Travel,Eco,270,1,1,2,4,1,2,1,1,4,5,4,2,3,1,0,0.0,neutral or dissatisfied +64878,45417,Female,Loyal Customer,36,Business travel,Business,2983,3,2,2,2,3,2,3,3,3,3,3,4,3,4,38,23.0,neutral or dissatisfied +64879,116056,Female,Loyal Customer,19,Personal Travel,Eco,337,4,5,4,4,2,4,1,2,4,2,4,3,4,2,8,4.0,satisfied +64880,91488,Male,Loyal Customer,48,Business travel,Business,1639,3,3,4,3,3,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +64881,47116,Female,Loyal Customer,51,Personal Travel,Eco,737,4,1,4,2,5,2,1,2,2,4,2,3,2,1,39,48.0,neutral or dissatisfied +64882,115537,Male,disloyal Customer,40,Business travel,Business,325,1,1,1,2,5,1,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +64883,129543,Female,Loyal Customer,27,Business travel,Business,2342,3,1,4,1,3,3,3,3,1,2,2,2,3,3,8,0.0,neutral or dissatisfied +64884,128572,Male,Loyal Customer,40,Personal Travel,Eco Plus,110,4,4,4,4,3,4,3,3,4,4,5,2,1,3,0,0.0,neutral or dissatisfied +64885,114878,Female,Loyal Customer,52,Business travel,Business,1773,3,3,3,3,4,4,4,4,4,5,4,3,4,4,49,27.0,satisfied +64886,19475,Male,disloyal Customer,37,Business travel,Eco,177,2,4,2,4,5,2,4,5,1,3,5,3,5,5,0,0.0,neutral or dissatisfied +64887,41881,Female,Loyal Customer,13,Personal Travel,Eco,760,3,4,3,2,4,3,2,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +64888,64493,Male,Loyal Customer,17,Business travel,Business,2852,3,1,3,1,3,3,3,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +64889,16166,Female,Loyal Customer,37,Business travel,Business,2910,5,5,5,5,3,5,3,4,4,4,3,3,4,5,0,0.0,satisfied +64890,115714,Female,Loyal Customer,36,Business travel,Business,3127,3,2,2,2,5,3,4,3,3,3,3,3,3,2,69,62.0,neutral or dissatisfied +64891,96850,Female,Loyal Customer,43,Business travel,Eco,781,3,5,5,5,5,2,3,3,3,3,3,1,3,1,10,4.0,neutral or dissatisfied +64892,91637,Female,Loyal Customer,36,Personal Travel,Eco,1199,1,4,1,1,4,1,4,4,1,1,4,1,4,4,0,4.0,neutral or dissatisfied +64893,75334,Female,Loyal Customer,16,Business travel,Eco,2486,5,5,5,5,5,5,5,4,5,4,5,5,1,5,0,35.0,satisfied +64894,115737,Male,disloyal Customer,36,Business travel,Eco,325,4,2,4,4,1,4,1,1,2,1,4,1,3,1,59,48.0,neutral or dissatisfied +64895,85675,Male,Loyal Customer,41,Personal Travel,Eco,903,2,5,2,2,2,2,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +64896,74116,Female,disloyal Customer,29,Business travel,Business,721,2,2,2,4,5,2,5,5,5,4,4,5,4,5,3,0.0,neutral or dissatisfied +64897,112449,Female,Loyal Customer,16,Business travel,Business,2402,2,2,2,2,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +64898,56002,Female,Loyal Customer,40,Business travel,Business,2475,1,1,3,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +64899,72857,Male,Loyal Customer,37,Business travel,Business,700,1,1,1,1,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +64900,40165,Male,disloyal Customer,24,Business travel,Eco,463,5,5,5,2,2,5,2,2,5,5,5,5,4,2,0,9.0,satisfied +64901,7363,Female,Loyal Customer,56,Business travel,Business,3568,1,1,1,1,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +64902,65547,Female,Loyal Customer,49,Business travel,Business,2808,4,4,4,4,3,5,5,4,4,4,4,5,4,4,28,19.0,satisfied +64903,53097,Female,Loyal Customer,54,Personal Travel,Eco,224,3,4,3,1,3,4,3,5,5,3,5,1,5,5,0,3.0,neutral or dissatisfied +64904,34267,Female,disloyal Customer,22,Business travel,Eco,496,2,3,2,4,3,2,3,3,2,5,2,1,2,3,0,0.0,neutral or dissatisfied +64905,92942,Female,Loyal Customer,27,Personal Travel,Eco,151,5,5,0,3,5,0,1,5,5,3,4,3,5,5,0,0.0,satisfied +64906,59901,Female,Loyal Customer,39,Business travel,Business,3124,5,5,5,5,2,4,5,5,5,5,5,4,5,4,24,11.0,satisfied +64907,11398,Female,Loyal Customer,40,Business travel,Business,3659,2,2,2,2,2,5,4,5,5,5,4,3,5,3,2,0.0,satisfied +64908,51285,Male,Loyal Customer,44,Business travel,Eco Plus,109,4,3,3,3,4,4,4,4,3,1,2,1,3,4,0,0.0,satisfied +64909,80074,Female,Loyal Customer,26,Business travel,Business,3186,2,2,2,2,5,5,5,5,3,4,5,5,4,5,299,285.0,satisfied +64910,56646,Male,Loyal Customer,46,Business travel,Eco,537,5,2,2,2,5,5,5,5,2,5,1,1,2,5,18,0.0,satisfied +64911,17579,Male,Loyal Customer,19,Personal Travel,Eco,1034,2,4,2,2,5,2,3,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +64912,83326,Male,Loyal Customer,52,Business travel,Business,1671,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +64913,102909,Female,Loyal Customer,28,Personal Travel,Business,317,3,5,3,2,4,3,4,4,3,5,4,1,5,4,0,0.0,neutral or dissatisfied +64914,35791,Female,Loyal Customer,30,Personal Travel,Eco,200,2,2,0,2,4,0,4,4,1,4,2,4,1,4,0,23.0,neutral or dissatisfied +64915,68813,Female,Loyal Customer,49,Personal Travel,Eco,926,3,4,2,5,3,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +64916,114173,Male,Loyal Customer,50,Business travel,Business,2043,3,3,3,3,3,4,5,4,4,4,4,4,4,4,5,0.0,satisfied +64917,49603,Female,Loyal Customer,41,Business travel,Business,199,3,3,3,3,1,1,3,4,4,4,4,2,4,4,0,0.0,satisfied +64918,96890,Male,Loyal Customer,59,Personal Travel,Eco,972,3,5,3,2,2,3,5,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +64919,55494,Male,disloyal Customer,24,Business travel,Eco,1739,1,1,1,3,5,1,5,5,3,3,2,2,4,5,0,0.0,neutral or dissatisfied +64920,105055,Male,Loyal Customer,50,Personal Travel,Eco,361,4,5,4,3,4,4,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +64921,85640,Male,Loyal Customer,33,Personal Travel,Eco,259,2,3,0,4,4,0,4,4,2,2,1,1,5,4,0,0.0,neutral or dissatisfied +64922,81817,Female,Loyal Customer,27,Business travel,Business,1598,4,4,4,4,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +64923,16898,Male,Loyal Customer,70,Personal Travel,Eco,746,1,2,1,4,2,1,5,2,1,3,3,4,4,2,45,49.0,neutral or dissatisfied +64924,109080,Male,Loyal Customer,64,Personal Travel,Eco,928,3,3,3,1,1,3,1,1,4,3,4,1,4,1,19,17.0,neutral or dissatisfied +64925,107527,Female,disloyal Customer,16,Business travel,Eco Plus,838,3,1,3,4,2,3,2,2,2,5,3,2,3,2,1,0.0,neutral or dissatisfied +64926,128595,Female,Loyal Customer,43,Business travel,Business,954,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +64927,110261,Female,disloyal Customer,40,Business travel,Business,663,4,4,4,3,1,4,1,1,3,2,4,5,5,1,0,0.0,satisfied +64928,50902,Female,Loyal Customer,10,Personal Travel,Eco,86,4,2,4,3,4,4,4,4,2,1,4,1,3,4,0,0.0,neutral or dissatisfied +64929,40155,Female,Loyal Customer,38,Business travel,Business,358,2,2,4,2,5,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +64930,89065,Male,disloyal Customer,50,Business travel,Business,1947,3,3,3,1,1,3,1,1,4,2,3,5,4,1,0,6.0,neutral or dissatisfied +64931,39529,Male,Loyal Customer,35,Business travel,Eco Plus,852,5,3,3,3,5,5,5,5,1,5,5,4,4,5,80,57.0,satisfied +64932,68795,Male,Loyal Customer,34,Business travel,Business,861,2,2,2,2,4,3,2,5,5,5,5,4,5,4,0,0.0,satisfied +64933,54869,Female,Loyal Customer,56,Business travel,Business,1724,2,2,2,2,1,5,1,5,5,5,5,1,5,5,0,0.0,satisfied +64934,72765,Male,Loyal Customer,59,Business travel,Business,1045,1,1,4,1,2,4,5,2,2,2,2,4,2,4,9,0.0,satisfied +64935,110377,Male,Loyal Customer,25,Business travel,Business,2615,3,3,3,3,3,3,3,3,5,2,4,3,4,3,16,6.0,satisfied +64936,16736,Female,Loyal Customer,17,Personal Travel,Eco,1167,1,5,1,2,3,1,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +64937,68521,Female,Loyal Customer,46,Business travel,Business,2560,2,1,3,3,2,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +64938,86636,Female,Loyal Customer,62,Business travel,Business,746,2,4,1,1,2,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +64939,125914,Female,Loyal Customer,37,Personal Travel,Eco,993,1,4,1,1,5,1,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +64940,34927,Male,Loyal Customer,38,Business travel,Business,1581,4,4,4,4,5,5,5,3,3,3,3,2,3,1,11,11.0,satisfied +64941,40850,Female,Loyal Customer,62,Personal Travel,Eco,501,4,5,4,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +64942,27379,Female,disloyal Customer,27,Business travel,Eco,605,2,5,2,1,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +64943,117914,Female,Loyal Customer,64,Business travel,Business,365,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +64944,24383,Female,disloyal Customer,33,Business travel,Eco,669,1,1,1,3,5,1,5,5,4,3,3,4,3,5,0,7.0,neutral or dissatisfied +64945,40634,Female,Loyal Customer,47,Business travel,Eco Plus,216,5,3,3,3,1,3,1,5,5,5,5,1,5,1,0,0.0,satisfied +64946,73067,Female,Loyal Customer,48,Business travel,Business,2089,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +64947,44672,Male,Loyal Customer,69,Business travel,Business,3358,2,4,4,4,2,3,4,3,3,3,2,1,3,1,0,27.0,neutral or dissatisfied +64948,11660,Male,Loyal Customer,67,Personal Travel,Eco,925,2,5,2,2,2,5,5,3,2,1,4,5,5,5,182,162.0,neutral or dissatisfied +64949,93426,Female,disloyal Customer,36,Business travel,Business,605,3,3,3,3,5,3,5,5,3,3,4,4,5,5,15,3.0,neutral or dissatisfied +64950,9053,Male,Loyal Customer,40,Business travel,Business,1922,2,2,5,2,5,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +64951,17966,Female,Loyal Customer,15,Personal Travel,Eco,500,3,4,3,1,3,3,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +64952,99166,Male,Loyal Customer,10,Business travel,Business,986,4,3,3,3,4,4,4,4,3,3,2,3,3,4,7,8.0,neutral or dissatisfied +64953,99087,Male,Loyal Customer,54,Business travel,Business,3128,5,5,5,5,2,5,5,4,4,4,4,4,4,4,3,0.0,satisfied +64954,118750,Male,Loyal Customer,56,Personal Travel,Eco,325,4,5,4,3,4,4,4,4,1,2,2,4,3,4,0,4.0,satisfied +64955,83710,Male,Loyal Customer,45,Personal Travel,Eco,577,4,4,4,5,1,4,1,1,5,5,4,4,4,1,6,7.0,neutral or dissatisfied +64956,59566,Female,Loyal Customer,41,Business travel,Business,2246,1,1,1,1,2,5,5,4,4,5,4,3,4,3,27,20.0,satisfied +64957,37371,Female,Loyal Customer,34,Business travel,Business,1074,3,3,3,3,2,5,1,3,3,4,3,1,3,5,34,1.0,satisfied +64958,117560,Male,disloyal Customer,61,Business travel,Business,347,4,4,4,3,1,4,1,1,3,4,4,4,4,1,0,0.0,satisfied +64959,124136,Male,Loyal Customer,52,Personal Travel,Eco,529,1,5,2,1,4,2,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +64960,64101,Male,Loyal Customer,66,Personal Travel,Eco,919,3,3,3,3,5,3,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +64961,28162,Male,disloyal Customer,43,Business travel,Eco,169,2,0,2,3,1,2,1,1,3,4,2,3,3,1,0,0.0,neutral or dissatisfied +64962,15629,Female,Loyal Customer,20,Personal Travel,Eco,296,4,4,4,3,1,4,1,1,5,4,5,4,4,1,11,4.0,neutral or dissatisfied +64963,70934,Female,disloyal Customer,33,Business travel,Business,612,2,2,2,3,2,2,5,2,5,4,5,3,4,2,10,9.0,neutral or dissatisfied +64964,123634,Female,Loyal Customer,47,Business travel,Business,214,1,1,1,1,5,5,5,5,5,5,4,5,5,5,0,10.0,satisfied +64965,71413,Male,Loyal Customer,29,Personal Travel,Eco,334,3,5,3,1,1,3,1,1,1,1,4,3,5,1,56,54.0,neutral or dissatisfied +64966,36,Female,Loyal Customer,42,Business travel,Business,2884,5,2,5,5,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +64967,80575,Male,Loyal Customer,54,Business travel,Business,1747,3,5,5,5,2,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +64968,31654,Male,Loyal Customer,55,Business travel,Business,853,2,2,2,2,1,1,3,4,4,4,4,4,4,3,0,0.0,satisfied +64969,102347,Female,disloyal Customer,22,Business travel,Eco,223,3,3,3,4,4,3,3,4,1,2,3,3,4,4,22,14.0,neutral or dissatisfied +64970,85191,Female,Loyal Customer,54,Business travel,Business,696,4,3,3,3,3,2,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +64971,64337,Female,Loyal Customer,35,Business travel,Business,2650,2,3,1,3,5,2,3,2,2,2,2,2,2,4,45,35.0,neutral or dissatisfied +64972,28744,Male,Loyal Customer,37,Business travel,Business,1024,2,2,2,2,1,3,1,5,5,5,5,3,5,4,0,14.0,satisfied +64973,76692,Male,Loyal Customer,39,Personal Travel,Eco,547,2,2,2,3,2,2,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +64974,19884,Male,Loyal Customer,47,Business travel,Eco,296,4,4,4,4,4,4,4,4,1,2,1,4,2,4,0,0.0,satisfied +64975,109422,Female,Loyal Customer,52,Business travel,Business,966,4,4,4,4,2,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +64976,74629,Female,Loyal Customer,39,Business travel,Business,3894,2,2,5,2,1,5,3,5,5,5,5,1,5,5,0,7.0,satisfied +64977,93548,Female,Loyal Customer,27,Business travel,Business,719,5,5,5,5,5,5,5,5,5,4,5,5,4,5,0,0.0,satisfied +64978,107042,Female,disloyal Customer,33,Business travel,Business,395,4,4,4,4,4,4,4,4,5,2,5,5,5,4,20,0.0,neutral or dissatisfied +64979,30129,Male,Loyal Customer,10,Personal Travel,Eco,539,3,5,3,1,4,3,5,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +64980,118115,Female,Loyal Customer,70,Personal Travel,Eco,1300,2,4,1,3,2,4,5,1,1,1,2,3,1,5,14,0.0,neutral or dissatisfied +64981,117344,Male,Loyal Customer,16,Business travel,Business,296,4,4,1,4,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +64982,110341,Female,Loyal Customer,38,Business travel,Business,925,1,1,1,1,4,4,4,5,5,5,5,3,5,3,54,33.0,satisfied +64983,37797,Female,Loyal Customer,40,Business travel,Eco Plus,641,2,4,1,4,2,2,2,2,2,3,4,3,4,2,51,45.0,neutral or dissatisfied +64984,95022,Female,Loyal Customer,14,Personal Travel,Eco,293,5,5,5,3,1,5,1,1,3,4,4,3,5,1,16,13.0,satisfied +64985,5729,Female,Loyal Customer,28,Personal Travel,Eco Plus,299,3,2,3,2,4,3,4,4,3,3,1,4,2,4,0,0.0,neutral or dissatisfied +64986,38062,Male,disloyal Customer,22,Business travel,Eco,1249,2,2,2,3,4,2,4,4,1,5,3,1,3,4,0,6.0,neutral or dissatisfied +64987,91876,Male,Loyal Customer,49,Business travel,Business,2446,4,5,5,5,4,4,4,1,5,2,4,4,3,4,136,129.0,neutral or dissatisfied +64988,40804,Male,disloyal Customer,29,Business travel,Eco,599,3,3,3,3,5,3,5,5,3,4,4,4,4,5,58,38.0,neutral or dissatisfied +64989,121732,Male,Loyal Customer,38,Business travel,Business,1475,2,4,4,4,1,3,3,2,2,2,2,2,2,3,0,8.0,neutral or dissatisfied +64990,88897,Female,disloyal Customer,29,Business travel,Eco,859,3,3,3,4,4,3,4,4,4,1,3,3,3,4,2,0.0,neutral or dissatisfied +64991,71953,Male,Loyal Customer,45,Business travel,Business,1440,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,10.0,satisfied +64992,66845,Male,Loyal Customer,24,Personal Travel,Eco,731,4,1,4,3,2,4,2,2,4,3,4,1,3,2,2,0.0,neutral or dissatisfied +64993,114141,Male,Loyal Customer,55,Business travel,Business,3900,2,5,5,5,2,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +64994,59311,Female,disloyal Customer,49,Business travel,Business,2556,4,4,4,3,4,4,4,4,5,4,3,4,4,4,60,25.0,satisfied +64995,114712,Female,Loyal Customer,54,Business travel,Eco,447,3,5,5,5,5,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +64996,428,Female,Loyal Customer,40,Business travel,Business,1654,4,3,3,3,3,4,4,1,1,2,4,3,1,4,0,0.0,neutral or dissatisfied +64997,33070,Female,Loyal Customer,27,Personal Travel,Eco,101,3,5,3,1,1,3,4,1,3,2,2,5,2,1,0,0.0,neutral or dissatisfied +64998,32709,Male,Loyal Customer,85,Business travel,Business,1666,3,1,1,1,3,3,3,4,2,4,3,3,1,3,0,5.0,neutral or dissatisfied +64999,113926,Male,Loyal Customer,35,Personal Travel,Eco Plus,1670,3,2,3,2,3,3,3,3,4,1,3,2,2,3,14,0.0,neutral or dissatisfied +65000,126091,Female,Loyal Customer,56,Business travel,Business,1827,3,3,3,3,2,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +65001,113121,Female,Loyal Customer,11,Personal Travel,Eco,543,2,5,2,4,3,2,1,3,4,2,4,4,5,3,40,29.0,neutral or dissatisfied +65002,109689,Female,Loyal Customer,31,Personal Travel,Eco,829,1,4,1,4,3,1,3,3,4,4,4,4,4,3,11,0.0,neutral or dissatisfied +65003,58906,Male,Loyal Customer,59,Business travel,Eco,888,3,5,5,5,3,3,3,3,2,5,3,1,4,3,2,0.0,neutral or dissatisfied +65004,62390,Female,disloyal Customer,37,Business travel,Eco,1204,2,2,2,4,3,2,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +65005,102466,Female,Loyal Customer,57,Personal Travel,Eco,407,2,5,2,2,3,3,4,2,2,2,2,5,2,5,23,4.0,neutral or dissatisfied +65006,106648,Female,disloyal Customer,10,Business travel,Eco,861,3,3,3,3,3,3,5,3,2,3,3,5,4,5,263,257.0,neutral or dissatisfied +65007,86619,Female,Loyal Customer,31,Business travel,Business,746,3,3,3,3,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +65008,108421,Female,Loyal Customer,41,Business travel,Business,1444,2,2,3,2,4,5,4,3,3,3,3,5,3,5,2,0.0,satisfied +65009,121755,Female,Loyal Customer,42,Business travel,Business,2895,4,4,4,4,5,5,5,5,5,5,5,4,5,5,20,7.0,satisfied +65010,57073,Female,Loyal Customer,9,Personal Travel,Eco,2065,1,4,1,1,1,2,2,4,5,4,4,2,3,2,144,117.0,neutral or dissatisfied +65011,4581,Male,Loyal Customer,51,Business travel,Business,3598,3,3,3,3,4,5,4,5,5,5,5,5,5,3,84,91.0,satisfied +65012,68403,Female,Loyal Customer,58,Business travel,Business,2869,4,4,4,4,5,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +65013,103739,Female,Loyal Customer,36,Personal Travel,Eco,405,2,3,2,4,5,2,2,5,1,1,5,5,3,5,10,10.0,neutral or dissatisfied +65014,68957,Male,Loyal Customer,51,Business travel,Business,1875,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,4.0,satisfied +65015,84158,Female,Loyal Customer,50,Business travel,Business,3444,2,2,3,2,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +65016,125822,Female,disloyal Customer,34,Business travel,Business,920,1,1,1,1,5,1,5,5,3,4,5,3,5,5,81,120.0,neutral or dissatisfied +65017,128674,Female,disloyal Customer,28,Business travel,Eco,733,1,1,1,3,1,1,3,3,1,4,3,3,2,3,0,13.0,neutral or dissatisfied +65018,17364,Male,Loyal Customer,17,Personal Travel,Eco,563,2,4,2,3,1,2,1,1,5,3,4,4,4,1,0,13.0,neutral or dissatisfied +65019,30100,Female,Loyal Customer,58,Personal Travel,Eco,399,3,2,3,2,3,2,3,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +65020,79722,Male,Loyal Customer,65,Personal Travel,Eco,760,2,5,2,1,1,2,1,1,1,5,2,3,4,1,0,0.0,neutral or dissatisfied +65021,48227,Male,Loyal Customer,55,Personal Travel,Eco,236,4,5,4,4,4,4,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +65022,13549,Male,Loyal Customer,43,Business travel,Business,2696,2,5,5,5,4,4,4,2,2,2,2,3,2,3,0,10.0,neutral or dissatisfied +65023,122609,Female,disloyal Customer,27,Business travel,Eco,728,2,2,2,4,5,2,5,5,1,4,3,1,4,5,1,0.0,neutral or dissatisfied +65024,85613,Male,Loyal Customer,65,Personal Travel,Eco,259,1,4,1,3,2,1,2,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +65025,112183,Female,Loyal Customer,45,Personal Travel,Eco,895,2,5,2,4,4,3,2,2,2,2,2,1,2,3,11,0.0,neutral or dissatisfied +65026,28027,Female,Loyal Customer,42,Personal Travel,Eco,763,2,4,2,3,2,4,5,2,2,2,4,3,2,3,0,0.0,neutral or dissatisfied +65027,117171,Female,Loyal Customer,21,Personal Travel,Eco,369,3,3,4,2,4,4,4,4,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +65028,44231,Female,disloyal Customer,61,Business travel,Eco,359,2,1,2,3,3,2,3,3,2,3,4,3,4,3,0,0.0,neutral or dissatisfied +65029,127847,Male,Loyal Customer,42,Business travel,Business,3001,2,2,2,2,3,4,5,5,5,5,5,3,5,3,0,15.0,satisfied +65030,46518,Male,Loyal Customer,40,Business travel,Eco,125,3,1,1,1,3,3,3,3,2,1,3,1,3,3,8,6.0,satisfied +65031,17627,Female,Loyal Customer,44,Business travel,Business,1905,5,5,5,5,4,5,1,5,5,5,5,4,5,3,0,0.0,satisfied +65032,58175,Male,Loyal Customer,56,Business travel,Eco,925,2,4,3,4,2,2,2,2,1,2,4,1,4,2,0,0.0,neutral or dissatisfied +65033,77876,Female,Loyal Customer,62,Personal Travel,Eco,1416,1,4,1,3,4,4,5,1,1,1,1,3,1,1,0,1.0,neutral or dissatisfied +65034,58318,Female,Loyal Customer,46,Business travel,Eco,1739,1,3,3,3,4,3,2,1,1,1,1,1,1,3,36,4.0,neutral or dissatisfied +65035,9884,Female,disloyal Customer,27,Business travel,Business,515,3,3,3,2,5,3,5,5,4,5,4,3,4,5,0,7.0,neutral or dissatisfied +65036,91664,Male,Loyal Customer,37,Business travel,Eco Plus,1340,3,1,1,1,3,4,3,3,2,2,4,1,3,3,5,2.0,neutral or dissatisfied +65037,36363,Female,Loyal Customer,46,Business travel,Business,3736,5,5,5,5,2,1,4,5,5,5,5,4,5,3,21,31.0,satisfied +65038,46478,Male,Loyal Customer,51,Personal Travel,Business,125,1,2,1,4,3,4,4,4,4,1,1,2,4,3,18,21.0,neutral or dissatisfied +65039,87431,Female,Loyal Customer,21,Personal Travel,Eco Plus,425,1,2,1,3,4,1,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +65040,112194,Female,Loyal Customer,31,Personal Travel,Eco Plus,895,1,5,1,2,5,1,5,5,4,2,4,4,5,5,5,0.0,neutral or dissatisfied +65041,10527,Female,Loyal Customer,40,Business travel,Business,224,5,5,5,5,5,4,5,5,5,5,5,5,5,5,9,0.0,satisfied +65042,111913,Female,Loyal Customer,42,Business travel,Business,472,4,4,4,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +65043,60675,Female,disloyal Customer,28,Business travel,Eco Plus,1620,3,3,3,4,5,3,5,5,1,4,2,2,4,5,36,17.0,neutral or dissatisfied +65044,123128,Female,Loyal Customer,51,Business travel,Business,3117,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +65045,88489,Female,disloyal Customer,56,Business travel,Eco,270,1,0,2,2,3,2,3,3,5,5,5,2,2,3,0,0.0,neutral or dissatisfied +65046,55577,Male,Loyal Customer,51,Business travel,Business,2773,3,3,5,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +65047,6864,Female,disloyal Customer,22,Business travel,Business,622,5,0,5,3,4,5,4,4,5,5,4,5,4,4,0,0.0,satisfied +65048,55378,Male,Loyal Customer,42,Business travel,Business,2584,4,4,4,4,3,3,3,4,4,3,4,4,4,2,4,0.0,neutral or dissatisfied +65049,79647,Male,Loyal Customer,56,Business travel,Eco,760,2,3,2,3,2,2,2,2,4,4,1,3,5,2,0,0.0,satisfied +65050,417,Female,Loyal Customer,36,Business travel,Business,2474,1,1,1,1,3,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +65051,44241,Female,disloyal Customer,21,Business travel,Eco,118,3,2,3,3,2,3,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +65052,125391,Female,disloyal Customer,22,Business travel,Eco,1099,4,4,4,3,1,4,1,1,3,2,5,3,5,1,0,0.0,satisfied +65053,17569,Female,Loyal Customer,34,Business travel,Business,2508,2,3,3,3,2,1,2,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +65054,58163,Female,Loyal Customer,51,Business travel,Business,2293,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +65055,91023,Female,Loyal Customer,53,Personal Travel,Eco,223,3,4,3,5,3,4,5,3,3,3,5,3,3,4,0,0.0,neutral or dissatisfied +65056,120359,Male,Loyal Customer,47,Business travel,Business,366,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +65057,10420,Female,Loyal Customer,37,Business travel,Business,301,3,4,4,4,4,3,3,3,3,3,3,1,3,1,79,59.0,neutral or dissatisfied +65058,68212,Female,Loyal Customer,54,Business travel,Business,432,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +65059,94710,Male,Loyal Customer,21,Business travel,Business,2014,3,1,5,5,3,3,3,3,1,3,3,4,3,3,22,16.0,neutral or dissatisfied +65060,52905,Female,disloyal Customer,28,Business travel,Eco,679,2,2,2,2,1,2,3,1,2,3,2,3,3,1,46,39.0,neutral or dissatisfied +65061,14138,Male,disloyal Customer,47,Business travel,Business,232,1,1,1,4,5,1,2,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +65062,114679,Female,Loyal Customer,42,Business travel,Business,337,2,2,2,2,2,5,4,5,5,5,5,3,5,4,58,57.0,satisfied +65063,37423,Female,Loyal Customer,24,Business travel,Business,2582,3,3,5,3,5,5,5,5,4,1,4,1,3,5,0,0.0,satisfied +65064,47940,Female,Loyal Customer,32,Personal Travel,Eco,329,3,5,3,3,2,3,2,2,4,5,3,5,1,2,3,0.0,neutral or dissatisfied +65065,52331,Male,Loyal Customer,49,Business travel,Business,3036,2,5,5,5,5,4,3,2,2,2,2,1,2,3,0,14.0,neutral or dissatisfied +65066,110693,Female,Loyal Customer,32,Personal Travel,Eco,829,4,4,4,1,3,4,2,3,3,5,5,4,5,3,5,0.0,neutral or dissatisfied +65067,33770,Male,Loyal Customer,15,Business travel,Eco,1990,3,5,2,2,3,3,1,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +65068,105958,Male,Loyal Customer,26,Business travel,Business,2295,3,3,3,3,2,2,2,3,4,5,4,2,4,2,17,11.0,satisfied +65069,127201,Male,Loyal Customer,51,Business travel,Business,325,1,1,4,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +65070,108787,Female,disloyal Customer,21,Business travel,Eco,404,2,1,2,3,4,2,4,4,3,4,3,1,3,4,0,6.0,neutral or dissatisfied +65071,40598,Male,Loyal Customer,25,Personal Travel,Eco,216,0,5,0,3,5,0,5,5,3,2,5,4,5,5,0,0.0,satisfied +65072,38399,Male,disloyal Customer,26,Business travel,Eco,1754,2,2,2,2,3,2,3,3,2,2,3,3,3,3,69,52.0,neutral or dissatisfied +65073,25045,Male,disloyal Customer,20,Business travel,Eco,594,5,3,5,2,1,5,1,1,2,3,3,1,1,1,1,0.0,satisfied +65074,129160,Male,Loyal Customer,42,Business travel,Eco,554,5,1,1,1,5,5,5,5,1,3,4,1,4,5,34,34.0,satisfied +65075,264,Female,Loyal Customer,43,Business travel,Business,3967,5,5,5,5,3,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +65076,32842,Female,Loyal Customer,36,Personal Travel,Eco,101,4,1,4,2,3,4,3,3,2,2,1,2,2,3,24,21.0,satisfied +65077,32509,Female,disloyal Customer,26,Business travel,Eco,101,3,1,3,4,5,3,5,5,1,3,3,1,3,5,0,6.0,neutral or dissatisfied +65078,64912,Male,Loyal Customer,50,Business travel,Eco,551,1,3,3,3,1,1,1,1,1,3,4,2,4,1,0,0.0,neutral or dissatisfied +65079,30344,Female,Loyal Customer,61,Personal Travel,Eco,391,1,4,1,2,2,4,4,5,5,1,5,3,5,5,0,9.0,neutral or dissatisfied +65080,121982,Male,Loyal Customer,46,Business travel,Business,130,1,1,1,1,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +65081,16443,Male,Loyal Customer,45,Business travel,Business,3423,4,1,1,1,2,3,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +65082,105357,Male,Loyal Customer,38,Personal Travel,Eco,409,2,5,2,5,2,2,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +65083,11792,Female,Loyal Customer,32,Personal Travel,Eco,175,2,5,2,1,1,2,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +65084,32599,Male,Loyal Customer,37,Business travel,Business,3041,2,5,5,5,2,3,2,3,3,3,2,3,3,4,0,1.0,neutral or dissatisfied +65085,107182,Male,disloyal Customer,15,Business travel,Business,668,5,0,5,5,3,5,3,3,4,3,4,5,4,3,0,0.0,satisfied +65086,48051,Female,Loyal Customer,17,Personal Travel,Eco,677,3,4,3,1,5,3,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +65087,46773,Male,Loyal Customer,57,Personal Travel,Eco Plus,196,3,3,3,1,2,3,3,2,5,1,4,1,3,2,50,45.0,neutral or dissatisfied +65088,90855,Male,Loyal Customer,44,Business travel,Business,270,3,2,2,2,3,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +65089,53477,Female,Loyal Customer,52,Business travel,Business,3177,4,4,4,4,4,4,4,3,1,3,1,4,2,4,77,65.0,satisfied +65090,127586,Male,disloyal Customer,23,Business travel,Eco,1019,4,4,4,2,4,4,4,4,3,5,5,5,5,4,0,4.0,satisfied +65091,85916,Female,disloyal Customer,24,Business travel,Eco,274,3,5,3,2,1,3,1,1,5,1,5,2,4,1,17,22.0,neutral or dissatisfied +65092,49849,Female,disloyal Customer,72,Business travel,Eco,308,2,0,2,1,1,2,1,1,4,5,5,1,4,1,93,91.0,neutral or dissatisfied +65093,76183,Male,Loyal Customer,54,Business travel,Business,2422,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +65094,4425,Female,Loyal Customer,57,Business travel,Business,3760,5,5,5,5,4,4,5,3,3,4,3,4,3,5,0,13.0,satisfied +65095,18702,Male,Loyal Customer,23,Business travel,Eco Plus,383,5,4,4,4,5,5,5,5,5,1,5,3,1,5,9,5.0,satisfied +65096,9489,Male,Loyal Customer,42,Business travel,Eco,239,3,3,4,4,3,3,3,3,2,1,3,4,4,3,0,0.0,neutral or dissatisfied +65097,123301,Male,Loyal Customer,35,Business travel,Business,590,4,3,4,4,2,5,4,4,4,4,4,4,4,4,12,103.0,satisfied +65098,72568,Male,disloyal Customer,27,Business travel,Business,1121,3,3,3,3,3,3,3,3,2,5,3,2,1,3,3,1.0,neutral or dissatisfied +65099,10691,Male,Loyal Customer,39,Business travel,Business,2415,4,4,4,4,4,4,5,4,4,4,4,3,4,4,6,13.0,satisfied +65100,37947,Male,Loyal Customer,29,Business travel,Eco Plus,1065,1,1,1,1,1,1,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +65101,73433,Male,Loyal Customer,10,Personal Travel,Eco,1120,3,5,2,2,3,2,3,3,5,3,5,4,5,3,105,111.0,neutral or dissatisfied +65102,90110,Female,Loyal Customer,48,Business travel,Eco,1127,2,4,4,4,2,1,2,2,2,2,2,3,2,1,19,20.0,neutral or dissatisfied +65103,120902,Female,disloyal Customer,52,Business travel,Eco,861,1,1,1,4,4,1,4,4,1,1,4,1,4,4,0,1.0,neutral or dissatisfied +65104,118046,Female,Loyal Customer,47,Business travel,Eco,1044,2,2,2,2,5,4,3,2,2,2,2,2,2,4,5,8.0,neutral or dissatisfied +65105,103375,Female,Loyal Customer,37,Business travel,Business,1847,3,3,3,3,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +65106,53192,Male,Loyal Customer,57,Business travel,Eco,612,2,4,4,4,2,2,2,2,3,5,4,3,1,2,30,36.0,satisfied +65107,38730,Female,disloyal Customer,41,Business travel,Business,353,5,4,4,2,1,5,1,1,1,4,1,1,4,1,0,0.0,satisfied +65108,66260,Female,Loyal Customer,35,Personal Travel,Eco,550,4,2,4,3,2,4,5,2,2,5,1,1,3,2,0,0.0,neutral or dissatisfied +65109,45727,Male,Loyal Customer,63,Personal Travel,Eco,852,1,4,1,4,1,1,1,1,5,5,4,3,4,1,48,77.0,neutral or dissatisfied +65110,88344,Male,Loyal Customer,48,Business travel,Eco,271,3,1,1,1,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +65111,59703,Female,Loyal Customer,49,Personal Travel,Eco,964,4,4,4,1,5,5,4,2,2,4,3,3,2,5,0,0.0,neutral or dissatisfied +65112,34922,Female,Loyal Customer,36,Business travel,Business,3080,3,3,3,3,2,1,1,5,5,5,5,2,5,1,20,0.0,satisfied +65113,6376,Male,Loyal Customer,53,Business travel,Business,296,3,3,3,3,5,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +65114,94303,Female,Loyal Customer,38,Business travel,Business,189,0,5,0,2,4,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +65115,34196,Female,Loyal Customer,67,Personal Travel,Eco,1129,2,1,2,3,5,2,4,5,5,2,5,2,5,3,2,0.0,neutral or dissatisfied +65116,85683,Male,Loyal Customer,39,Business travel,Business,1547,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +65117,75177,Female,Loyal Customer,27,Business travel,Business,1846,2,2,2,2,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +65118,34232,Male,Loyal Customer,37,Business travel,Eco Plus,1046,1,1,1,1,1,1,1,3,4,4,3,1,1,1,123,138.0,neutral or dissatisfied +65119,99842,Female,Loyal Customer,35,Business travel,Eco,587,4,4,4,4,4,4,4,4,3,4,4,3,1,4,7,0.0,satisfied +65120,23373,Male,Loyal Customer,61,Personal Travel,Eco,1014,3,2,3,4,2,3,2,2,1,5,4,1,4,2,0,0.0,neutral or dissatisfied +65121,79428,Male,Loyal Customer,28,Personal Travel,Eco,502,2,4,2,4,1,2,1,1,3,4,3,3,3,1,0,37.0,neutral or dissatisfied +65122,61134,Female,Loyal Customer,18,Personal Travel,Business,862,4,5,5,4,4,5,4,4,4,1,4,3,3,4,0,0.0,neutral or dissatisfied +65123,70300,Male,Loyal Customer,58,Business travel,Business,334,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +65124,13220,Male,Loyal Customer,43,Business travel,Business,657,4,4,4,4,1,2,5,4,4,4,4,2,4,5,0,0.0,satisfied +65125,44860,Female,disloyal Customer,10,Business travel,Eco,585,1,0,1,3,4,1,2,4,1,2,5,3,5,4,0,2.0,neutral or dissatisfied +65126,128005,Male,Loyal Customer,29,Personal Travel,Eco,1488,1,1,1,2,4,1,5,4,3,1,3,2,3,4,6,3.0,neutral or dissatisfied +65127,64707,Female,disloyal Customer,13,Business travel,Business,551,0,0,0,5,3,0,3,3,3,4,5,4,5,3,76,69.0,satisfied +65128,122769,Male,Loyal Customer,44,Business travel,Business,427,3,4,4,4,3,4,3,3,3,3,3,2,3,1,87,76.0,neutral or dissatisfied +65129,45837,Female,Loyal Customer,46,Personal Travel,Eco,216,1,0,1,2,2,2,3,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +65130,25226,Male,Loyal Customer,30,Business travel,Business,3190,5,5,5,5,2,2,2,2,4,3,3,2,4,2,0,0.0,satisfied +65131,74430,Female,Loyal Customer,26,Business travel,Business,1205,5,5,5,5,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +65132,7998,Female,disloyal Customer,14,Business travel,Eco,530,3,4,2,4,3,2,3,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +65133,117930,Female,Loyal Customer,25,Business travel,Business,1716,1,1,1,1,2,2,2,2,3,5,4,5,5,2,0,0.0,satisfied +65134,27612,Female,Loyal Customer,44,Personal Travel,Eco,954,4,5,4,3,3,3,4,2,2,4,5,2,2,1,0,10.0,neutral or dissatisfied +65135,41762,Female,Loyal Customer,32,Personal Travel,Eco,491,2,2,2,4,1,2,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +65136,114381,Female,Loyal Customer,52,Personal Travel,Eco Plus,948,4,4,4,4,3,2,3,3,3,4,3,3,3,4,0,0.0,satisfied +65137,106101,Male,Loyal Customer,57,Business travel,Business,3370,2,2,3,2,3,5,5,4,4,4,4,4,4,5,18,8.0,satisfied +65138,93285,Female,Loyal Customer,32,Personal Travel,Eco,564,2,4,2,1,3,2,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +65139,34432,Male,Loyal Customer,45,Personal Travel,Eco,680,2,1,2,4,5,2,1,5,3,4,4,2,3,5,0,2.0,neutral or dissatisfied +65140,74963,Male,Loyal Customer,28,Personal Travel,Eco,2475,1,4,1,3,2,1,2,2,4,5,3,5,5,2,55,42.0,neutral or dissatisfied +65141,10365,Male,Loyal Customer,53,Business travel,Business,2902,1,1,1,1,4,5,5,4,4,4,4,3,4,5,122,110.0,satisfied +65142,59058,Male,disloyal Customer,71,Business travel,Eco,1080,2,2,2,2,1,2,1,1,2,1,2,3,2,1,3,11.0,neutral or dissatisfied +65143,2963,Male,Loyal Customer,62,Personal Travel,Eco,737,3,4,3,3,3,3,3,3,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +65144,1734,Male,Loyal Customer,38,Personal Travel,Eco,489,5,2,2,4,4,2,4,4,2,4,3,3,3,4,0,0.0,satisfied +65145,46564,Male,disloyal Customer,36,Business travel,Eco,125,2,0,2,1,3,2,4,3,4,5,1,4,3,3,0,0.0,neutral or dissatisfied +65146,85998,Male,Loyal Customer,53,Business travel,Business,2488,1,1,1,1,4,4,5,2,2,2,2,5,2,5,0,4.0,satisfied +65147,6438,Male,Loyal Customer,67,Personal Travel,Eco,315,3,4,3,4,5,3,5,5,1,3,4,3,4,5,6,0.0,neutral or dissatisfied +65148,76438,Female,Loyal Customer,45,Personal Travel,Eco,405,2,4,4,3,4,1,1,3,2,4,5,1,3,1,148,137.0,neutral or dissatisfied +65149,15021,Female,Loyal Customer,46,Personal Travel,Eco,557,3,4,3,1,4,5,5,5,5,3,5,5,5,3,14,24.0,neutral or dissatisfied +65150,85493,Male,Loyal Customer,42,Personal Travel,Eco,332,3,2,3,4,5,3,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +65151,73044,Male,Loyal Customer,66,Personal Travel,Eco,1035,5,4,5,5,5,5,5,5,5,3,4,5,4,5,0,0.0,satisfied +65152,98738,Female,Loyal Customer,23,Business travel,Business,1558,3,3,3,3,3,3,3,3,1,5,3,1,3,3,6,4.0,neutral or dissatisfied +65153,14843,Male,Loyal Customer,68,Personal Travel,Business,240,4,4,4,5,3,4,4,3,3,4,4,3,3,3,0,0.0,satisfied +65154,90075,Female,Loyal Customer,42,Business travel,Business,983,2,2,2,2,3,5,5,4,4,5,4,3,4,3,4,0.0,satisfied +65155,97931,Male,Loyal Customer,55,Business travel,Business,2917,2,2,2,2,2,5,5,5,5,5,5,5,5,5,6,10.0,satisfied +65156,41726,Female,Loyal Customer,45,Business travel,Eco,695,4,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +65157,92285,Female,Loyal Customer,36,Personal Travel,Eco,2036,4,4,4,2,3,4,3,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +65158,31403,Female,Loyal Customer,9,Personal Travel,Eco Plus,1199,2,3,2,1,1,2,1,1,5,5,5,2,1,1,15,15.0,neutral or dissatisfied +65159,52600,Male,Loyal Customer,27,Business travel,Business,160,2,2,2,2,5,5,5,5,3,5,4,1,1,5,0,0.0,satisfied +65160,53470,Female,Loyal Customer,77,Business travel,Eco,2288,3,1,1,1,4,3,2,3,3,3,3,3,3,3,47,28.0,neutral or dissatisfied +65161,26822,Male,Loyal Customer,37,Business travel,Business,2069,3,3,3,3,3,5,4,5,5,5,4,2,5,1,0,0.0,satisfied +65162,95425,Female,disloyal Customer,40,Business travel,Business,239,2,2,2,5,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +65163,108850,Male,Loyal Customer,43,Business travel,Business,2139,4,4,4,4,2,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +65164,98482,Male,Loyal Customer,53,Business travel,Business,2264,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +65165,36411,Female,disloyal Customer,37,Business travel,Eco,369,1,4,1,4,5,1,5,5,3,1,1,3,3,5,0,0.0,neutral or dissatisfied +65166,99680,Female,Loyal Customer,33,Business travel,Business,3010,5,5,5,5,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +65167,15294,Male,Loyal Customer,32,Personal Travel,Eco Plus,500,2,5,5,1,1,5,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +65168,7184,Female,Loyal Customer,57,Business travel,Eco,139,3,5,5,5,3,2,3,4,4,3,4,1,4,1,0,4.0,neutral or dissatisfied +65169,108059,Female,Loyal Customer,40,Business travel,Business,2847,1,1,1,1,5,5,5,4,4,4,4,5,4,5,7,0.0,satisfied +65170,35669,Male,Loyal Customer,35,Business travel,Eco,2475,4,5,5,5,4,4,4,1,1,5,2,4,5,4,0,4.0,satisfied +65171,86848,Male,Loyal Customer,43,Personal Travel,Eco,692,2,5,2,2,2,2,2,2,4,3,2,5,5,2,48,37.0,neutral or dissatisfied +65172,36057,Female,Loyal Customer,61,Business travel,Business,413,3,5,5,5,4,2,3,3,3,3,3,1,3,4,20,33.0,neutral or dissatisfied +65173,26223,Male,Loyal Customer,24,Personal Travel,Eco,581,3,5,3,5,4,3,4,4,3,5,4,3,5,4,53,58.0,neutral or dissatisfied +65174,86869,Female,Loyal Customer,57,Business travel,Business,484,2,2,2,2,3,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +65175,82783,Male,disloyal Customer,22,Business travel,Eco,231,4,4,4,5,2,4,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +65176,89173,Male,Loyal Customer,45,Personal Travel,Eco,1892,3,2,3,3,4,3,4,4,2,5,3,3,4,4,0,0.0,neutral or dissatisfied +65177,92745,Male,Loyal Customer,69,Personal Travel,Eco,1276,3,4,3,3,5,3,5,5,5,2,4,3,3,5,0,0.0,neutral or dissatisfied +65178,88173,Male,Loyal Customer,35,Business travel,Business,442,4,4,4,4,2,5,4,3,3,3,3,5,3,4,0,7.0,satisfied +65179,84430,Male,Loyal Customer,38,Personal Travel,Eco,591,3,4,2,2,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +65180,79080,Male,Loyal Customer,38,Personal Travel,Eco,356,4,1,4,3,3,4,3,3,4,4,4,4,3,3,8,2.0,satisfied +65181,61153,Male,Loyal Customer,57,Business travel,Business,2814,5,4,5,5,4,4,4,4,4,4,4,3,4,3,15,14.0,satisfied +65182,38002,Female,Loyal Customer,37,Business travel,Eco,1010,5,5,5,5,5,4,5,5,4,3,5,4,4,5,0,0.0,satisfied +65183,8259,Female,Loyal Customer,49,Personal Travel,Eco,402,2,5,2,2,4,4,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +65184,74305,Female,Loyal Customer,40,Business travel,Business,2215,5,5,5,5,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +65185,50313,Male,Loyal Customer,49,Business travel,Business,2276,3,5,5,5,3,3,2,4,4,4,3,4,4,4,0,8.0,neutral or dissatisfied +65186,79941,Female,Loyal Customer,47,Business travel,Business,2935,4,4,4,4,5,4,4,2,2,2,2,3,2,5,13,0.0,satisfied +65187,66785,Male,Loyal Customer,28,Business travel,Business,3711,1,3,3,3,1,1,1,4,5,3,3,1,3,1,0,0.0,neutral or dissatisfied +65188,4426,Female,Loyal Customer,42,Business travel,Business,762,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +65189,41920,Male,Loyal Customer,30,Business travel,Eco,129,2,1,1,1,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +65190,51778,Female,Loyal Customer,66,Personal Travel,Eco,509,1,5,1,1,4,4,4,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +65191,8587,Male,Loyal Customer,19,Personal Travel,Eco,109,3,5,3,4,1,3,1,1,4,2,2,2,1,1,51,51.0,neutral or dissatisfied +65192,97216,Male,Loyal Customer,43,Business travel,Eco Plus,1129,1,5,5,5,1,1,1,1,4,1,3,1,3,1,11,7.0,neutral or dissatisfied +65193,20169,Female,disloyal Customer,30,Business travel,Eco,258,3,0,3,3,3,3,3,3,2,3,4,1,2,3,0,0.0,neutral or dissatisfied +65194,26954,Female,Loyal Customer,44,Business travel,Business,867,4,4,4,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +65195,10130,Female,Loyal Customer,40,Personal Travel,Eco,946,2,3,2,4,4,2,4,4,5,3,1,3,4,4,0,0.0,neutral or dissatisfied +65196,30447,Male,Loyal Customer,31,Business travel,Business,1956,2,2,2,2,3,3,3,3,3,5,3,3,1,3,0,0.0,satisfied +65197,97752,Male,Loyal Customer,44,Business travel,Business,3879,4,4,4,4,3,5,4,4,4,5,4,5,4,5,6,0.0,satisfied +65198,46531,Female,disloyal Customer,20,Business travel,Eco,196,5,0,5,3,4,5,3,4,2,3,5,1,2,4,0,0.0,satisfied +65199,35995,Male,Loyal Customer,31,Business travel,Eco Plus,2496,4,4,4,4,4,4,4,1,3,2,4,4,4,4,20,31.0,neutral or dissatisfied +65200,91026,Male,Loyal Customer,47,Personal Travel,Eco,404,2,1,2,3,2,2,4,2,2,3,3,3,4,2,0,0.0,neutral or dissatisfied +65201,944,Female,Loyal Customer,46,Business travel,Business,2605,2,4,4,4,2,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +65202,32727,Female,Loyal Customer,37,Business travel,Eco,216,2,1,3,1,2,2,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +65203,122316,Female,Loyal Customer,47,Business travel,Business,1555,5,5,5,5,4,5,4,4,4,4,4,3,4,4,0,29.0,satisfied +65204,5025,Male,Loyal Customer,19,Personal Travel,Business,137,3,0,3,3,2,3,1,2,3,5,4,1,3,2,20,37.0,neutral or dissatisfied +65205,11733,Female,disloyal Customer,22,Business travel,Business,429,5,5,5,3,1,5,1,1,5,3,5,4,4,1,0,7.0,satisfied +65206,84797,Female,Loyal Customer,56,Business travel,Business,2916,1,1,5,1,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +65207,111408,Female,Loyal Customer,62,Business travel,Eco Plus,650,4,1,2,1,4,1,1,4,4,4,4,2,4,4,5,0.0,satisfied +65208,65701,Male,Loyal Customer,51,Business travel,Business,3559,4,1,4,4,2,4,4,4,4,4,4,4,4,5,16,0.0,satisfied +65209,7296,Male,Loyal Customer,32,Personal Travel,Eco,139,3,3,3,3,1,3,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +65210,121409,Male,disloyal Customer,27,Business travel,Business,290,2,3,3,4,1,3,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +65211,81357,Female,Loyal Customer,45,Personal Travel,Eco,1299,2,5,2,4,4,4,5,1,1,2,1,4,1,5,0,6.0,neutral or dissatisfied +65212,113446,Female,Loyal Customer,51,Business travel,Business,2006,5,5,5,5,2,2,2,5,2,5,4,2,3,2,145,142.0,satisfied +65213,101415,Female,Loyal Customer,57,Personal Travel,Eco,486,2,4,3,3,4,4,4,5,5,3,5,3,5,1,1,0.0,neutral or dissatisfied +65214,54723,Male,Loyal Customer,44,Personal Travel,Eco,854,2,4,2,3,3,2,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +65215,7181,Male,Loyal Customer,40,Business travel,Eco,130,2,2,2,2,2,2,2,2,2,3,2,4,3,2,0,0.0,neutral or dissatisfied +65216,115520,Female,Loyal Customer,51,Business travel,Business,3820,4,4,4,4,3,5,5,3,3,4,3,4,3,5,31,24.0,satisfied +65217,994,Female,Loyal Customer,38,Business travel,Business,3827,3,3,3,3,2,4,1,4,4,4,5,5,4,4,0,0.0,satisfied +65218,76462,Female,Loyal Customer,57,Personal Travel,Business,481,3,1,3,3,2,2,2,3,3,3,3,3,3,3,0,34.0,neutral or dissatisfied +65219,32223,Male,Loyal Customer,66,Business travel,Business,201,2,2,2,2,2,1,2,4,4,4,3,2,4,1,0,0.0,satisfied +65220,6052,Female,Loyal Customer,24,Personal Travel,Eco,1041,1,5,1,4,1,1,1,1,4,5,4,4,4,1,1,27.0,neutral or dissatisfied +65221,25496,Female,Loyal Customer,40,Business travel,Business,547,3,3,3,3,5,4,4,4,4,5,4,3,4,1,38,15.0,satisfied +65222,120770,Female,disloyal Customer,8,Business travel,Eco,678,3,3,3,3,3,3,2,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +65223,117149,Male,Loyal Customer,31,Personal Travel,Eco,304,1,5,1,1,4,1,4,4,5,3,5,3,5,4,6,0.0,neutral or dissatisfied +65224,48731,Male,Loyal Customer,57,Business travel,Business,193,3,3,3,3,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +65225,52790,Male,Loyal Customer,65,Business travel,Eco,374,4,2,1,2,4,4,4,4,4,5,5,1,5,4,0,0.0,satisfied +65226,94399,Male,disloyal Customer,23,Business travel,Business,192,4,2,4,4,2,4,2,2,5,3,4,3,4,2,7,0.0,satisfied +65227,34888,Female,Loyal Customer,44,Business travel,Business,2181,5,5,5,5,4,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +65228,33399,Female,Loyal Customer,40,Business travel,Business,2556,2,2,2,2,4,4,4,3,3,4,5,4,3,4,319,295.0,satisfied +65229,124816,Female,Loyal Customer,75,Business travel,Business,1869,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +65230,11208,Female,Loyal Customer,40,Personal Travel,Eco,224,3,2,3,3,2,3,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +65231,5645,Female,Loyal Customer,15,Personal Travel,Business,299,1,4,1,1,5,1,5,5,4,2,5,5,5,5,18,14.0,neutral or dissatisfied +65232,22254,Male,Loyal Customer,34,Business travel,Business,143,0,3,0,3,5,2,2,3,3,3,3,5,3,5,0,0.0,satisfied +65233,69406,Male,Loyal Customer,31,Business travel,Business,3525,5,5,5,5,5,5,5,5,3,3,5,4,5,5,0,0.0,satisfied +65234,44066,Male,Loyal Customer,25,Personal Travel,Eco,456,2,5,2,4,1,2,1,1,5,4,5,4,4,1,30,65.0,neutral or dissatisfied +65235,85399,Female,disloyal Customer,26,Business travel,Business,332,2,2,2,5,4,2,4,4,3,2,4,4,5,4,0,7.0,neutral or dissatisfied +65236,80239,Male,Loyal Customer,30,Business travel,Business,3189,3,3,3,3,5,5,5,5,3,2,4,5,4,5,0,0.0,satisfied +65237,90897,Male,Loyal Customer,26,Business travel,Business,270,2,5,5,5,2,2,2,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +65238,87436,Female,Loyal Customer,57,Business travel,Business,3953,5,5,5,5,4,4,4,4,4,4,4,4,4,4,30,28.0,satisfied +65239,53970,Male,Loyal Customer,67,Personal Travel,Eco,1117,3,5,3,5,3,3,3,3,5,5,5,5,4,3,38,13.0,neutral or dissatisfied +65240,126440,Male,Loyal Customer,36,Personal Travel,Eco Plus,631,3,4,4,1,1,4,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +65241,36684,Female,Loyal Customer,47,Personal Travel,Eco,1185,2,5,2,3,3,3,4,5,5,2,5,5,5,3,0,27.0,neutral or dissatisfied +65242,39961,Female,Loyal Customer,51,Business travel,Eco Plus,1086,4,5,5,5,2,4,3,3,3,4,3,4,3,3,0,0.0,satisfied +65243,71097,Male,Loyal Customer,16,Personal Travel,Eco Plus,802,3,5,3,3,2,3,2,2,4,5,5,3,1,2,13,21.0,neutral or dissatisfied +65244,62994,Female,Loyal Customer,58,Business travel,Eco,862,3,1,4,1,1,3,4,4,4,3,4,4,4,1,32,24.0,neutral or dissatisfied +65245,77816,Female,Loyal Customer,9,Personal Travel,Eco,696,3,5,3,1,3,4,4,2,2,2,1,4,3,4,134,121.0,neutral or dissatisfied +65246,27729,Male,Loyal Customer,26,Business travel,Business,1448,3,3,3,3,4,4,4,4,5,5,3,2,3,4,0,0.0,satisfied +65247,36037,Male,disloyal Customer,22,Business travel,Eco,474,4,0,4,3,4,2,2,2,5,4,1,2,5,2,164,226.0,satisfied +65248,112286,Male,Loyal Customer,53,Personal Travel,Eco,1703,1,2,2,3,4,2,4,4,4,5,4,4,3,4,22,3.0,neutral or dissatisfied +65249,22508,Female,Loyal Customer,38,Business travel,Eco Plus,145,4,5,5,5,4,4,4,4,1,1,4,4,4,4,35,32.0,satisfied +65250,70860,Male,Loyal Customer,49,Business travel,Business,761,3,1,4,1,1,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +65251,26819,Male,Loyal Customer,44,Business travel,Eco,224,5,5,5,5,5,5,5,5,1,1,3,4,4,5,0,0.0,satisfied +65252,79847,Male,Loyal Customer,31,Business travel,Business,3157,5,5,5,5,5,5,5,5,5,3,5,3,4,5,0,0.0,satisfied +65253,11037,Female,Loyal Customer,35,Personal Travel,Eco,312,5,4,4,1,2,4,3,2,4,5,4,4,4,2,14,22.0,satisfied +65254,81717,Female,disloyal Customer,25,Business travel,Business,1416,2,0,2,1,5,2,5,5,4,5,4,3,4,5,18,17.0,neutral or dissatisfied +65255,115763,Male,Loyal Customer,65,Business travel,Business,1695,3,3,3,3,4,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +65256,20565,Female,Loyal Customer,46,Business travel,Business,533,1,4,4,4,4,4,3,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +65257,113091,Female,disloyal Customer,18,Business travel,Eco,543,1,3,1,4,2,1,2,2,4,5,4,1,3,2,29,33.0,neutral or dissatisfied +65258,37086,Male,disloyal Customer,27,Business travel,Business,1189,2,2,2,2,3,2,2,3,1,3,3,3,3,3,15,11.0,neutral or dissatisfied +65259,88829,Female,Loyal Customer,54,Personal Travel,Eco Plus,545,3,1,3,2,1,3,2,4,4,3,4,4,4,1,43,51.0,neutral or dissatisfied +65260,92306,Female,Loyal Customer,8,Personal Travel,Business,2556,3,2,3,4,3,1,1,1,2,3,4,1,1,1,0,0.0,neutral or dissatisfied +65261,72834,Female,Loyal Customer,25,Business travel,Eco,1013,3,2,2,2,3,2,2,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +65262,122794,Male,Loyal Customer,16,Business travel,Eco,599,1,3,3,3,1,1,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +65263,2293,Female,Loyal Customer,49,Business travel,Business,1834,2,1,1,1,3,4,4,2,2,2,2,1,2,4,0,15.0,neutral or dissatisfied +65264,12389,Female,disloyal Customer,29,Business travel,Eco,190,1,3,1,4,2,1,2,2,5,2,3,1,5,2,0,0.0,neutral or dissatisfied +65265,962,Male,Loyal Customer,40,Business travel,Business,2556,1,5,5,5,1,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +65266,36011,Male,Loyal Customer,31,Business travel,Business,3325,5,5,5,5,4,4,4,4,4,1,1,4,5,4,0,0.0,satisfied +65267,108231,Female,Loyal Customer,47,Business travel,Business,2983,4,4,4,4,4,5,5,4,4,4,4,4,4,3,26,37.0,satisfied +65268,121939,Male,Loyal Customer,70,Personal Travel,Eco,2282,3,0,3,2,3,1,5,2,1,5,4,5,1,5,0,14.0,neutral or dissatisfied +65269,2367,Female,Loyal Customer,57,Personal Travel,Eco,925,1,4,1,1,3,4,5,5,5,1,5,5,5,3,5,1.0,neutral or dissatisfied +65270,91895,Male,Loyal Customer,39,Business travel,Business,2586,3,1,5,1,3,3,4,3,3,3,3,2,3,2,0,20.0,neutral or dissatisfied +65271,7496,Female,Loyal Customer,24,Personal Travel,Eco,925,2,4,1,4,1,1,1,1,3,4,4,4,4,1,0,3.0,neutral or dissatisfied +65272,40468,Female,Loyal Customer,53,Business travel,Eco,222,4,4,4,4,2,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +65273,109145,Male,Loyal Customer,59,Business travel,Business,616,5,5,5,5,2,5,5,4,4,4,4,3,4,3,31,26.0,satisfied +65274,31743,Female,disloyal Customer,7,Business travel,Eco Plus,862,3,3,2,4,4,2,4,4,2,4,4,2,3,4,3,0.0,neutral or dissatisfied +65275,71974,Male,Loyal Customer,39,Business travel,Business,1440,2,1,1,1,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +65276,1935,Female,Loyal Customer,39,Business travel,Business,1993,1,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +65277,111957,Male,Loyal Customer,40,Business travel,Business,3987,1,5,1,1,5,5,5,4,4,4,4,3,4,4,22,14.0,satisfied +65278,56339,Female,Loyal Customer,33,Business travel,Business,1649,5,5,3,5,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +65279,14280,Female,Loyal Customer,24,Business travel,Business,429,1,1,1,1,4,4,4,4,5,4,4,1,2,4,75,76.0,satisfied +65280,92540,Male,Loyal Customer,59,Personal Travel,Eco,1947,2,4,2,1,4,2,5,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +65281,126271,Male,Loyal Customer,20,Personal Travel,Eco,600,5,1,5,4,2,5,2,2,4,1,4,2,4,2,0,5.0,satisfied +65282,38111,Female,disloyal Customer,36,Business travel,Eco,1249,3,2,2,3,3,2,3,3,4,4,2,3,4,3,90,71.0,neutral or dissatisfied +65283,109234,Male,Loyal Customer,34,Personal Travel,Eco,391,2,5,2,3,5,2,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +65284,112545,Male,Loyal Customer,35,Business travel,Eco Plus,846,1,3,2,2,1,1,1,1,4,4,4,2,4,1,25,21.0,neutral or dissatisfied +65285,126175,Male,disloyal Customer,22,Business travel,Eco,328,5,4,5,2,4,5,4,4,5,2,5,4,5,4,0,18.0,satisfied +65286,112568,Male,disloyal Customer,23,Business travel,Eco,639,4,0,4,4,4,4,5,4,4,4,4,4,4,4,25,3.0,satisfied +65287,78668,Female,Loyal Customer,38,Personal Travel,Business,761,2,4,2,3,5,5,4,5,5,2,3,5,5,3,0,0.0,neutral or dissatisfied +65288,126376,Male,Loyal Customer,60,Personal Travel,Eco,507,3,4,3,4,2,3,3,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +65289,84847,Male,Loyal Customer,23,Business travel,Business,1879,1,1,2,2,1,1,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +65290,18041,Female,Loyal Customer,43,Business travel,Business,488,4,4,4,4,2,5,1,4,4,4,4,5,4,3,0,0.0,satisfied +65291,101174,Male,disloyal Customer,41,Business travel,Eco,690,4,4,4,3,2,4,2,2,3,4,3,2,4,2,5,0.0,neutral or dissatisfied +65292,21921,Male,Loyal Customer,30,Business travel,Business,2640,1,1,1,1,5,5,5,5,5,1,5,2,3,5,1,2.0,satisfied +65293,76242,Female,Loyal Customer,34,Personal Travel,Eco,1399,4,4,3,3,5,3,1,5,5,2,5,3,5,5,0,0.0,satisfied +65294,56750,Male,Loyal Customer,60,Business travel,Business,1085,2,3,2,2,3,5,4,5,5,5,5,3,5,5,4,0.0,satisfied +65295,105345,Male,Loyal Customer,16,Business travel,Business,3602,1,1,1,1,4,4,4,4,3,2,1,2,4,4,0,0.0,satisfied +65296,125436,Female,Loyal Customer,51,Business travel,Eco Plus,735,1,1,1,1,4,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +65297,72194,Male,Loyal Customer,13,Personal Travel,Eco,594,5,4,5,3,4,5,4,4,5,4,4,5,3,4,0,0.0,satisfied +65298,24725,Male,disloyal Customer,64,Business travel,Eco,406,3,0,3,5,2,3,2,2,1,5,2,3,3,2,0,0.0,neutral or dissatisfied +65299,55303,Female,Loyal Customer,72,Business travel,Business,2072,4,4,2,4,2,3,5,4,4,5,4,4,4,4,2,9.0,satisfied +65300,5264,Male,disloyal Customer,16,Business travel,Eco,351,2,1,3,3,5,3,5,5,4,4,4,1,4,5,0,0.0,neutral or dissatisfied +65301,58954,Male,Loyal Customer,41,Business travel,Business,1744,2,2,3,2,5,5,4,5,5,5,5,3,5,3,8,0.0,satisfied +65302,27357,Female,Loyal Customer,49,Business travel,Business,1794,4,4,4,4,2,5,4,4,4,4,4,5,4,5,16,4.0,satisfied +65303,72173,Male,Loyal Customer,41,Business travel,Business,594,2,2,2,2,3,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +65304,119197,Male,Loyal Customer,47,Business travel,Business,2767,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +65305,51327,Male,Loyal Customer,33,Business travel,Eco Plus,421,4,3,3,3,4,4,4,4,1,1,5,2,4,4,0,2.0,satisfied +65306,15887,Male,Loyal Customer,40,Personal Travel,Eco,618,3,5,3,4,5,3,1,5,5,2,4,3,5,5,35,8.0,neutral or dissatisfied +65307,13632,Male,Loyal Customer,54,Business travel,Business,2973,2,5,4,5,3,4,3,2,2,3,2,3,2,4,66,53.0,neutral or dissatisfied +65308,24096,Female,Loyal Customer,31,Personal Travel,Eco,554,4,4,4,3,4,4,2,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +65309,11426,Female,Loyal Customer,32,Business travel,Eco Plus,247,2,2,2,2,2,3,2,2,3,1,3,4,4,2,29,38.0,neutral or dissatisfied +65310,111631,Female,disloyal Customer,57,Business travel,Business,1558,3,3,3,3,5,3,5,5,5,5,4,4,5,5,0,1.0,satisfied +65311,117119,Male,Loyal Customer,24,Business travel,Business,1862,4,4,4,4,5,5,5,5,4,3,2,1,4,5,11,4.0,satisfied +65312,25595,Male,Loyal Customer,29,Personal Travel,Eco,874,1,2,1,3,2,1,1,2,1,2,3,1,4,2,0,3.0,neutral or dissatisfied +65313,12458,Female,Loyal Customer,18,Personal Travel,Eco,305,4,3,1,3,3,1,3,3,1,1,3,4,3,3,0,15.0,neutral or dissatisfied +65314,110016,Male,Loyal Customer,53,Business travel,Business,1653,3,1,1,1,3,3,4,3,3,3,3,2,3,3,7,0.0,neutral or dissatisfied +65315,124762,Female,Loyal Customer,36,Business travel,Business,1845,4,4,4,4,2,4,5,5,5,5,5,4,5,5,9,5.0,satisfied +65316,106191,Male,Loyal Customer,36,Personal Travel,Eco,302,3,5,3,1,5,3,5,5,3,2,4,4,5,5,1,0.0,neutral or dissatisfied +65317,91550,Male,Loyal Customer,32,Business travel,Business,680,1,1,1,1,3,5,3,3,3,2,1,3,4,3,2,0.0,satisfied +65318,127455,Female,disloyal Customer,48,Business travel,Business,1264,2,2,2,3,2,2,2,2,4,4,5,5,5,2,0,0.0,satisfied +65319,60221,Female,disloyal Customer,25,Business travel,Business,1703,2,4,2,1,2,5,5,3,3,5,4,5,4,5,192,188.0,neutral or dissatisfied +65320,92817,Female,Loyal Customer,48,Business travel,Eco,1587,4,2,2,2,4,4,3,4,4,4,4,4,4,3,10,0.0,neutral or dissatisfied +65321,80906,Male,Loyal Customer,23,Business travel,Business,352,0,0,0,1,1,1,1,1,4,3,5,3,4,1,2,4.0,satisfied +65322,73337,Male,Loyal Customer,56,Business travel,Business,1197,3,3,3,3,3,4,4,5,5,5,5,5,5,3,2,0.0,satisfied +65323,61508,Female,Loyal Customer,45,Personal Travel,Eco,2288,2,4,2,4,3,4,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +65324,41401,Female,Loyal Customer,55,Business travel,Business,913,2,1,1,1,4,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +65325,24583,Male,Loyal Customer,45,Business travel,Eco,526,5,3,3,3,5,5,5,5,3,4,1,2,4,5,0,0.0,satisfied +65326,43523,Female,Loyal Customer,17,Personal Travel,Eco Plus,679,2,4,2,2,5,2,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +65327,54576,Female,Loyal Customer,25,Business travel,Eco Plus,925,0,4,0,1,4,0,5,4,4,5,2,5,5,4,4,0.0,satisfied +65328,91626,Male,Loyal Customer,43,Business travel,Business,1899,3,5,5,5,2,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +65329,28771,Male,Loyal Customer,44,Business travel,Business,937,5,5,5,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +65330,11432,Male,Loyal Customer,50,Business travel,Eco Plus,429,2,2,2,2,2,2,2,2,1,5,3,3,2,2,4,0.0,neutral or dissatisfied +65331,37822,Female,Loyal Customer,60,Business travel,Business,2777,4,4,4,4,3,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +65332,120904,Female,Loyal Customer,47,Business travel,Business,992,4,1,4,4,3,5,4,5,5,5,5,5,5,5,0,11.0,satisfied +65333,64986,Male,disloyal Customer,25,Business travel,Eco,551,3,4,4,5,4,4,4,4,2,1,3,1,2,4,0,0.0,neutral or dissatisfied +65334,42945,Female,Loyal Customer,57,Personal Travel,Business,259,2,1,0,3,2,3,3,3,3,0,3,1,3,3,0,1.0,neutral or dissatisfied +65335,108445,Male,Loyal Customer,55,Business travel,Business,1444,3,3,3,3,2,4,3,3,3,3,3,1,3,1,1,9.0,neutral or dissatisfied +65336,10208,Female,Loyal Customer,51,Business travel,Business,429,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,10.0,satisfied +65337,119124,Female,Loyal Customer,60,Business travel,Business,2338,4,4,4,4,2,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +65338,35008,Female,Loyal Customer,23,Business travel,Eco Plus,1182,5,2,2,2,5,5,5,5,5,1,4,3,1,5,0,0.0,satisfied +65339,43111,Female,Loyal Customer,66,Personal Travel,Eco,391,1,4,1,4,1,3,2,1,1,1,1,5,1,2,0,0.0,neutral or dissatisfied +65340,49126,Male,Loyal Customer,57,Business travel,Business,3510,5,5,5,5,5,4,5,4,4,4,4,1,4,1,6,0.0,satisfied +65341,33480,Female,Loyal Customer,41,Business travel,Eco,2422,4,4,4,4,4,4,4,4,5,2,5,1,5,4,22,1.0,satisfied +65342,55567,Female,disloyal Customer,36,Business travel,Eco,395,3,0,3,2,5,3,5,5,5,2,5,5,3,5,0,0.0,neutral or dissatisfied +65343,129192,Female,Loyal Customer,45,Business travel,Business,2419,5,5,5,5,2,3,5,4,4,4,4,4,4,3,13,3.0,satisfied +65344,97185,Male,Loyal Customer,35,Personal Travel,Eco,1497,3,5,3,4,5,3,5,5,4,4,3,4,5,5,8,4.0,neutral or dissatisfied +65345,2488,Female,Loyal Customer,57,Business travel,Business,1379,4,4,4,4,4,4,5,5,5,4,5,4,5,3,2,0.0,satisfied +65346,82156,Female,Loyal Customer,42,Business travel,Business,3757,4,4,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +65347,112526,Male,Loyal Customer,46,Personal Travel,Eco,853,3,4,3,2,3,5,5,4,2,5,5,5,4,5,167,169.0,neutral or dissatisfied +65348,2445,Male,Loyal Customer,45,Business travel,Business,604,4,4,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +65349,127941,Male,Loyal Customer,51,Business travel,Business,2300,5,5,5,5,4,5,5,4,4,4,4,3,4,4,20,0.0,satisfied +65350,123674,Female,Loyal Customer,54,Business travel,Business,3845,0,5,0,3,4,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +65351,21766,Female,Loyal Customer,28,Business travel,Eco,352,4,5,5,5,4,5,4,4,5,1,1,3,1,4,0,0.0,satisfied +65352,10485,Male,Loyal Customer,40,Business travel,Business,3136,4,4,4,4,5,5,5,3,5,4,5,5,5,5,162,157.0,satisfied +65353,85119,Male,Loyal Customer,61,Business travel,Business,1626,3,2,2,2,2,4,4,3,3,3,3,4,3,2,0,2.0,neutral or dissatisfied +65354,26392,Male,disloyal Customer,28,Business travel,Eco,957,2,2,2,3,4,2,4,4,5,1,5,2,3,4,5,4.0,neutral or dissatisfied +65355,47970,Female,Loyal Customer,33,Personal Travel,Eco,451,2,5,2,1,3,2,3,3,1,2,1,5,2,3,10,18.0,neutral or dissatisfied +65356,59953,Female,Loyal Customer,27,Business travel,Business,2297,4,5,5,5,4,4,4,3,2,4,3,4,2,4,200,175.0,neutral or dissatisfied +65357,34791,Female,Loyal Customer,58,Personal Travel,Eco,301,3,4,3,2,3,5,2,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +65358,95253,Male,Loyal Customer,62,Personal Travel,Eco,189,3,5,0,4,4,0,4,4,1,3,1,2,3,4,16,10.0,neutral or dissatisfied +65359,90524,Female,Loyal Customer,51,Business travel,Business,1517,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +65360,45083,Female,Loyal Customer,35,Business travel,Eco,196,4,2,2,2,4,4,4,4,4,3,2,3,4,4,9,0.0,satisfied +65361,113427,Female,disloyal Customer,29,Business travel,Business,414,5,5,5,4,1,5,1,1,4,3,4,4,4,1,0,0.0,satisfied +65362,95514,Male,Loyal Customer,39,Business travel,Eco Plus,248,4,1,1,1,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +65363,77609,Female,Loyal Customer,48,Business travel,Business,813,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +65364,35670,Female,disloyal Customer,27,Business travel,Eco,2465,2,2,2,3,2,3,3,1,4,2,2,3,3,3,10,10.0,neutral or dissatisfied +65365,2511,Male,Loyal Customer,30,Personal Travel,Business,304,3,3,3,2,4,3,4,4,2,4,1,4,1,4,0,0.0,neutral or dissatisfied +65366,111733,Female,Loyal Customer,58,Business travel,Business,1224,4,4,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +65367,64649,Male,disloyal Customer,50,Business travel,Eco,190,4,2,4,4,5,4,5,5,4,3,3,3,4,5,18,12.0,neutral or dissatisfied +65368,29795,Female,Loyal Customer,30,Business travel,Business,95,4,4,4,4,3,4,3,3,4,1,4,5,4,3,2,16.0,satisfied +65369,110830,Male,Loyal Customer,48,Business travel,Business,2877,2,2,3,2,3,5,4,2,2,2,2,5,2,3,130,124.0,satisfied +65370,30957,Male,Loyal Customer,11,Personal Travel,Eco,836,3,1,3,1,4,3,4,4,1,5,1,3,2,4,27,31.0,neutral or dissatisfied +65371,46037,Male,Loyal Customer,46,Business travel,Business,996,3,3,3,3,2,5,5,4,4,5,4,4,4,3,0,4.0,satisfied +65372,41136,Female,Loyal Customer,65,Business travel,Business,3341,1,1,5,1,2,4,2,5,5,5,5,1,5,4,0,0.0,satisfied +65373,89508,Male,disloyal Customer,25,Business travel,Business,950,2,0,2,2,3,2,3,3,3,5,4,3,4,3,26,4.0,neutral or dissatisfied +65374,31309,Male,Loyal Customer,49,Business travel,Eco,680,5,5,5,5,5,5,5,5,2,4,1,2,3,5,0,0.0,satisfied +65375,78406,Male,Loyal Customer,54,Business travel,Business,453,3,3,3,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +65376,102006,Male,Loyal Customer,48,Business travel,Eco Plus,804,3,2,4,2,3,3,3,3,2,3,3,3,4,3,5,3.0,neutral or dissatisfied +65377,82501,Female,Loyal Customer,48,Business travel,Business,1749,5,5,5,5,4,3,5,4,4,4,4,5,4,3,39,45.0,satisfied +65378,94705,Female,Loyal Customer,38,Business travel,Eco,189,3,3,3,3,3,3,3,3,3,2,3,4,4,3,0,1.0,neutral or dissatisfied +65379,95199,Female,Loyal Customer,58,Personal Travel,Eco,187,4,4,0,3,3,4,5,2,2,0,2,3,2,4,13,3.0,neutral or dissatisfied +65380,66348,Female,Loyal Customer,40,Business travel,Eco,986,3,4,4,4,3,3,3,3,4,4,2,3,2,3,0,0.0,neutral or dissatisfied +65381,97796,Male,Loyal Customer,37,Personal Travel,Eco,471,3,5,3,5,5,3,5,5,1,3,3,5,3,5,0,0.0,neutral or dissatisfied +65382,1587,Male,disloyal Customer,19,Business travel,Business,140,2,3,2,4,5,2,5,5,1,1,4,2,3,5,0,0.0,neutral or dissatisfied +65383,107422,Male,Loyal Customer,52,Business travel,Business,325,2,3,1,3,4,4,4,2,2,2,2,3,2,3,85,87.0,neutral or dissatisfied +65384,19090,Male,Loyal Customer,22,Personal Travel,Eco,296,3,1,3,4,3,3,2,3,4,1,4,3,3,3,0,0.0,neutral or dissatisfied +65385,10587,Male,Loyal Customer,59,Business travel,Business,295,0,0,0,1,4,5,4,2,2,3,3,3,2,4,60,51.0,satisfied +65386,124568,Female,Loyal Customer,56,Personal Travel,Eco,453,1,4,1,3,5,5,4,4,4,1,5,5,4,4,0,0.0,neutral or dissatisfied +65387,30021,Male,Loyal Customer,40,Business travel,Eco,571,3,1,1,1,3,2,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +65388,27216,Male,Loyal Customer,31,Business travel,Business,3070,4,4,4,4,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +65389,49777,Male,Loyal Customer,42,Business travel,Business,3469,2,2,2,2,5,5,2,5,5,4,4,4,5,5,0,0.0,satisfied +65390,7959,Male,Loyal Customer,46,Business travel,Eco,594,3,3,3,3,3,3,3,3,1,1,4,4,4,3,0,6.0,neutral or dissatisfied +65391,34633,Male,Loyal Customer,50,Business travel,Eco,427,4,1,1,1,3,4,3,3,4,1,1,4,2,3,0,0.0,satisfied +65392,79105,Male,Loyal Customer,25,Personal Travel,Eco,377,3,5,3,2,5,3,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +65393,2847,Female,Loyal Customer,24,Business travel,Business,3663,2,4,4,4,2,2,2,2,2,3,4,1,3,2,0,0.0,neutral or dissatisfied +65394,53048,Female,Loyal Customer,63,Personal Travel,Eco,1190,2,5,2,1,5,4,5,3,3,2,3,5,3,4,32,16.0,neutral or dissatisfied +65395,81528,Male,Loyal Customer,57,Business travel,Business,2165,5,5,5,5,5,5,5,4,4,4,4,4,4,3,2,1.0,satisfied +65396,33634,Male,Loyal Customer,21,Personal Travel,Eco,399,5,2,5,2,3,5,3,3,1,5,2,4,3,3,0,0.0,satisfied +65397,62946,Male,disloyal Customer,46,Business travel,Business,967,5,5,5,1,3,5,5,3,5,2,4,4,4,3,0,0.0,satisfied +65398,77900,Male,Loyal Customer,65,Business travel,Business,1771,2,3,3,3,5,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +65399,113306,Male,Loyal Customer,37,Business travel,Business,2598,2,2,2,2,2,4,4,4,4,4,4,4,4,4,6,5.0,satisfied +65400,23215,Male,Loyal Customer,53,Business travel,Business,326,2,2,2,2,4,3,3,4,4,4,4,2,4,2,0,0.0,satisfied +65401,69908,Female,disloyal Customer,38,Business travel,Business,1671,3,3,3,2,1,3,1,1,4,5,4,3,4,1,4,0.0,neutral or dissatisfied +65402,116445,Male,Loyal Customer,37,Personal Travel,Eco,296,3,4,3,1,3,3,1,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +65403,119741,Female,disloyal Customer,61,Personal Travel,Eco,1303,3,4,3,3,4,3,4,4,3,4,4,3,5,4,89,88.0,neutral or dissatisfied +65404,115106,Male,disloyal Customer,20,Business travel,Eco,404,3,0,3,1,2,3,2,2,5,3,4,4,5,2,13,14.0,neutral or dissatisfied +65405,82316,Male,Loyal Customer,26,Business travel,Business,456,3,3,3,3,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +65406,105553,Male,Loyal Customer,46,Personal Travel,Eco,611,2,5,1,4,1,1,1,1,4,2,5,4,5,1,0,2.0,neutral or dissatisfied +65407,86537,Female,Loyal Customer,8,Personal Travel,Eco,712,2,5,2,2,4,2,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +65408,87189,Female,Loyal Customer,45,Business travel,Business,1549,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +65409,38833,Female,Loyal Customer,60,Business travel,Eco Plus,353,5,2,2,2,5,5,4,5,5,5,5,5,5,1,0,0.0,satisfied +65410,49087,Male,Loyal Customer,42,Business travel,Business,372,3,3,3,3,4,2,5,5,5,5,5,4,5,5,0,0.0,satisfied +65411,77429,Female,Loyal Customer,42,Personal Travel,Eco,584,4,5,4,5,3,4,5,1,1,4,1,5,1,3,0,0.0,satisfied +65412,37589,Female,Loyal Customer,43,Business travel,Business,3487,5,5,5,5,1,4,3,4,4,5,4,1,4,4,16,14.0,satisfied +65413,65971,Female,Loyal Customer,23,Business travel,Business,1372,2,2,2,2,2,2,2,2,3,5,3,4,4,2,39,23.0,neutral or dissatisfied +65414,116568,Female,Loyal Customer,58,Business travel,Business,337,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +65415,29152,Female,disloyal Customer,38,Business travel,Eco Plus,987,3,2,2,2,3,2,3,3,3,5,5,4,3,3,0,0.0,neutral or dissatisfied +65416,87959,Male,Loyal Customer,54,Business travel,Business,2903,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +65417,93800,Female,disloyal Customer,36,Business travel,Eco,859,4,4,4,4,4,4,4,4,1,4,3,2,4,4,25,39.0,neutral or dissatisfied +65418,75172,Female,disloyal Customer,16,Business travel,Eco,1744,1,1,1,4,4,1,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +65419,1127,Male,Loyal Customer,19,Personal Travel,Eco,158,2,4,2,4,4,2,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +65420,109056,Male,disloyal Customer,31,Business travel,Eco,957,2,2,2,4,4,2,4,4,4,2,4,3,4,4,15,22.0,neutral or dissatisfied +65421,98241,Female,Loyal Customer,44,Business travel,Business,1072,1,1,1,1,2,4,5,5,5,5,5,3,5,3,37,38.0,satisfied +65422,85831,Female,Loyal Customer,64,Personal Travel,Eco,666,1,5,1,4,3,5,2,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +65423,11697,Female,Loyal Customer,55,Business travel,Business,3591,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +65424,65053,Female,Loyal Customer,21,Personal Travel,Eco,551,4,5,4,3,2,4,2,2,1,1,3,1,1,2,0,0.0,neutral or dissatisfied +65425,97940,Female,Loyal Customer,48,Business travel,Eco,483,2,5,5,5,5,4,3,2,2,2,2,1,2,4,26,4.0,neutral or dissatisfied +65426,105839,Male,Loyal Customer,36,Personal Travel,Eco,842,2,4,2,3,3,2,3,3,5,1,4,1,1,3,93,125.0,neutral or dissatisfied +65427,8925,Male,Loyal Customer,54,Business travel,Business,2107,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +65428,8825,Female,Loyal Customer,35,Personal Travel,Eco,552,2,4,2,4,2,2,2,2,1,2,3,3,3,2,6,1.0,neutral or dissatisfied +65429,30677,Female,Loyal Customer,51,Business travel,Business,2100,5,5,5,5,3,3,3,5,5,4,5,5,5,2,0,3.0,satisfied +65430,106019,Male,disloyal Customer,44,Business travel,Business,682,2,3,3,5,3,2,5,3,3,3,5,4,4,3,24,2.0,neutral or dissatisfied +65431,59710,Male,Loyal Customer,59,Business travel,Business,2809,5,2,5,5,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +65432,37911,Male,Loyal Customer,44,Personal Travel,Eco,1023,4,5,4,2,2,4,2,2,5,1,3,3,4,2,0,0.0,satisfied +65433,64708,Male,Loyal Customer,33,Business travel,Business,2882,5,5,5,5,4,5,5,4,5,5,4,4,5,4,0,0.0,satisfied +65434,13170,Female,Loyal Customer,48,Personal Travel,Eco Plus,595,4,3,4,4,4,3,4,4,4,4,4,2,4,4,0,14.0,neutral or dissatisfied +65435,20832,Female,disloyal Customer,29,Business travel,Eco,357,1,0,2,3,3,2,2,3,4,1,4,2,5,3,0,0.0,neutral or dissatisfied +65436,3615,Male,Loyal Customer,52,Business travel,Business,544,4,4,4,4,3,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +65437,40080,Male,Loyal Customer,18,Personal Travel,Eco,493,3,5,3,4,3,3,1,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +65438,105795,Male,Loyal Customer,45,Personal Travel,Eco,842,3,5,3,2,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +65439,50334,Female,Loyal Customer,50,Business travel,Business,109,5,5,5,5,4,2,2,4,4,4,5,1,4,5,0,21.0,satisfied +65440,127625,Female,disloyal Customer,40,Business travel,Business,1773,2,2,2,4,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +65441,111770,Male,Loyal Customer,28,Business travel,Business,1620,3,3,3,3,5,5,5,5,4,2,5,5,5,5,60,111.0,satisfied +65442,75556,Female,Loyal Customer,50,Business travel,Business,2955,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +65443,6895,Male,Loyal Customer,47,Business travel,Business,3716,0,0,0,4,2,5,4,2,2,2,2,3,2,3,68,79.0,satisfied +65444,48273,Male,Loyal Customer,36,Business travel,Eco Plus,391,2,1,2,1,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +65445,87510,Male,Loyal Customer,31,Personal Travel,Eco,321,3,3,3,4,3,3,3,3,3,3,1,2,4,3,0,0.0,neutral or dissatisfied +65446,117687,Male,Loyal Customer,44,Business travel,Business,1814,4,4,4,4,4,4,4,5,5,5,5,5,5,3,25,0.0,satisfied +65447,78792,Female,Loyal Customer,45,Business travel,Business,447,1,1,4,1,5,2,4,2,2,2,2,2,2,5,0,0.0,satisfied +65448,1133,Male,Loyal Customer,58,Personal Travel,Eco,113,1,4,1,4,1,1,1,1,4,5,2,3,5,1,0,0.0,neutral or dissatisfied +65449,37887,Female,Loyal Customer,45,Business travel,Eco,937,3,5,5,5,1,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +65450,93918,Female,Loyal Customer,53,Business travel,Business,1672,2,1,2,2,2,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +65451,48421,Female,Loyal Customer,40,Business travel,Business,3559,5,4,5,5,1,2,2,5,5,5,5,1,5,4,0,0.0,satisfied +65452,124172,Female,Loyal Customer,56,Personal Travel,Eco,2133,3,4,3,4,2,3,4,2,2,3,5,3,2,4,0,0.0,neutral or dissatisfied +65453,27251,Female,Loyal Customer,41,Business travel,Business,2047,1,1,1,1,5,5,5,5,5,5,5,4,5,3,6,0.0,satisfied +65454,94579,Female,Loyal Customer,43,Business travel,Business,273,0,0,0,5,3,4,5,4,4,4,4,4,4,3,21,22.0,satisfied +65455,10995,Female,disloyal Customer,40,Business travel,Business,224,3,3,3,3,4,3,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +65456,43860,Male,Loyal Customer,34,Business travel,Eco,153,0,0,0,3,1,0,1,1,4,1,2,5,3,1,0,0.0,satisfied +65457,13553,Female,Loyal Customer,63,Business travel,Eco,152,5,5,5,5,4,4,4,4,4,5,4,5,4,1,0,0.0,satisfied +65458,71483,Female,Loyal Customer,40,Business travel,Business,1197,4,4,4,4,5,4,5,2,2,2,2,3,2,4,4,2.0,satisfied +65459,56362,Female,Loyal Customer,32,Personal Travel,Eco,200,3,2,3,4,5,3,5,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +65460,7837,Female,Loyal Customer,45,Personal Travel,Eco Plus,710,1,5,1,4,2,4,5,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +65461,118172,Male,Loyal Customer,26,Business travel,Business,1444,2,2,2,2,4,4,4,4,4,3,5,4,5,4,11,13.0,satisfied +65462,15373,Female,Loyal Customer,43,Business travel,Business,377,5,5,5,5,4,5,4,4,4,4,4,2,4,5,2,0.0,satisfied +65463,34842,Female,Loyal Customer,7,Personal Travel,Eco Plus,264,4,4,0,4,0,5,5,1,1,3,3,5,4,5,169,158.0,neutral or dissatisfied +65464,27214,Male,Loyal Customer,23,Personal Travel,Eco Plus,2554,3,1,3,4,4,3,5,4,2,2,4,3,4,4,5,7.0,neutral or dissatisfied +65465,74425,Female,Loyal Customer,59,Business travel,Business,3875,5,5,2,5,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +65466,81326,Female,Loyal Customer,49,Business travel,Business,3319,1,1,1,1,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +65467,39030,Female,Loyal Customer,64,Personal Travel,Eco,113,2,4,2,4,2,4,2,5,5,2,5,5,5,2,0,8.0,neutral or dissatisfied +65468,76991,Female,Loyal Customer,59,Personal Travel,Business,368,2,4,4,2,1,5,5,2,2,4,2,4,2,1,20,16.0,neutral or dissatisfied +65469,23650,Male,Loyal Customer,31,Personal Travel,Business,73,3,3,3,3,4,3,4,4,3,2,4,2,1,4,0,0.0,neutral or dissatisfied +65470,10121,Male,Loyal Customer,23,Business travel,Business,3205,4,4,4,4,5,5,5,5,3,3,5,4,5,5,0,0.0,satisfied +65471,66352,Female,Loyal Customer,57,Business travel,Business,3504,5,5,5,5,3,5,5,4,4,4,4,3,4,5,6,4.0,satisfied +65472,105520,Female,disloyal Customer,24,Business travel,Business,611,3,1,3,2,5,3,1,5,1,3,2,2,3,5,51,71.0,neutral or dissatisfied +65473,6972,Female,Loyal Customer,49,Business travel,Business,2650,3,3,3,3,2,5,5,4,4,4,5,4,4,3,66,55.0,satisfied +65474,31292,Male,Loyal Customer,25,Business travel,Eco Plus,533,5,1,1,1,5,5,4,5,2,3,3,2,2,5,3,0.0,satisfied +65475,114497,Female,Loyal Customer,30,Business travel,Business,3926,5,5,5,5,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +65476,93435,Female,Loyal Customer,65,Business travel,Business,3822,3,3,3,3,1,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +65477,86498,Male,Loyal Customer,45,Personal Travel,Eco,762,4,3,4,3,5,4,5,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +65478,57742,Male,Loyal Customer,40,Business travel,Business,2704,3,3,3,3,5,5,5,3,4,3,5,5,4,5,63,54.0,satisfied +65479,2304,Female,Loyal Customer,48,Business travel,Eco,230,4,4,4,4,2,5,1,4,4,4,4,4,4,5,12,18.0,satisfied +65480,111653,Female,disloyal Customer,22,Business travel,Eco,1558,1,0,0,4,5,1,5,5,4,4,3,4,4,5,18,10.0,neutral or dissatisfied +65481,110899,Male,Loyal Customer,41,Business travel,Business,404,1,2,2,2,4,4,4,1,1,1,1,1,1,2,9,2.0,neutral or dissatisfied +65482,106668,Female,Loyal Customer,43,Business travel,Eco Plus,1190,2,4,4,4,4,5,1,2,2,2,2,5,2,3,0,12.0,satisfied +65483,122171,Male,disloyal Customer,23,Business travel,Eco,544,5,4,5,4,3,5,3,3,4,2,5,3,4,3,0,0.0,satisfied +65484,19323,Male,Loyal Customer,53,Business travel,Eco,743,5,1,3,3,5,5,5,5,2,1,5,1,2,5,68,67.0,satisfied +65485,98744,Male,Loyal Customer,20,Personal Travel,Eco,1558,1,5,1,1,5,1,5,5,4,3,3,5,5,5,6,0.0,neutral or dissatisfied +65486,26340,Female,Loyal Customer,23,Business travel,Eco,834,3,4,4,4,3,3,1,3,4,4,2,2,2,3,0,0.0,neutral or dissatisfied +65487,40481,Male,Loyal Customer,14,Personal Travel,Eco,222,5,5,0,1,3,0,3,3,3,3,2,3,2,3,4,0.0,satisfied +65488,59004,Male,Loyal Customer,52,Business travel,Business,1726,2,2,2,2,4,3,5,5,5,5,5,5,5,5,26,18.0,satisfied +65489,583,Female,Loyal Customer,58,Business travel,Business,164,1,1,1,1,5,5,4,5,5,5,4,5,5,4,0,0.0,satisfied +65490,91596,Male,Loyal Customer,20,Personal Travel,Business,1312,1,5,1,1,2,1,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +65491,33864,Female,Loyal Customer,22,Personal Travel,Eco,1562,4,5,4,1,1,4,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +65492,109788,Female,Loyal Customer,54,Business travel,Business,1092,2,2,2,2,5,5,5,2,2,2,2,4,2,3,27,4.0,satisfied +65493,2259,Female,Loyal Customer,55,Business travel,Business,690,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +65494,10150,Female,Loyal Customer,7,Personal Travel,Eco,1157,2,5,2,2,1,2,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +65495,27236,Female,Loyal Customer,45,Personal Travel,Eco,1024,2,4,2,2,5,4,4,5,5,2,2,5,5,3,0,0.0,neutral or dissatisfied +65496,21657,Male,Loyal Customer,29,Personal Travel,Business,708,2,3,2,3,3,2,3,3,2,5,3,4,4,3,15,5.0,neutral or dissatisfied +65497,57626,Male,Loyal Customer,57,Business travel,Business,3263,5,5,5,5,3,4,4,5,5,5,5,5,5,4,1,0.0,satisfied +65498,122319,Male,Loyal Customer,22,Business travel,Eco Plus,541,2,5,5,5,2,2,1,2,2,5,4,2,3,2,0,0.0,neutral or dissatisfied +65499,100599,Female,Loyal Customer,45,Business travel,Business,718,4,4,4,4,4,4,4,5,5,5,5,5,5,3,6,2.0,satisfied +65500,118028,Male,disloyal Customer,37,Business travel,Business,1044,3,3,3,4,2,3,1,2,3,4,4,4,4,2,0,2.0,neutral or dissatisfied +65501,104199,Female,disloyal Customer,15,Business travel,Eco,1310,3,3,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +65502,67586,Male,Loyal Customer,23,Business travel,Business,1205,3,3,3,3,3,3,3,3,4,2,4,3,4,3,0,0.0,satisfied +65503,74406,Male,disloyal Customer,26,Business travel,Business,1205,5,5,5,2,5,2,2,4,4,4,4,2,3,2,452,444.0,satisfied +65504,73217,Male,Loyal Customer,54,Business travel,Business,1718,1,1,1,1,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +65505,77960,Male,disloyal Customer,33,Business travel,Business,214,2,2,2,5,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +65506,73674,Female,disloyal Customer,18,Business travel,Eco,192,2,0,2,3,5,2,2,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +65507,57052,Female,Loyal Customer,36,Business travel,Business,2133,2,5,5,5,5,1,1,2,2,2,2,1,2,4,17,26.0,neutral or dissatisfied +65508,20479,Female,Loyal Customer,42,Business travel,Eco,130,3,3,3,3,2,4,4,3,3,3,3,4,3,3,0,7.0,satisfied +65509,28997,Male,disloyal Customer,47,Business travel,Eco,954,2,2,2,3,5,2,5,5,1,1,4,3,4,5,0,16.0,neutral or dissatisfied +65510,71305,Female,Loyal Customer,41,Business travel,Business,1514,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,19.0,satisfied +65511,101818,Male,disloyal Customer,30,Business travel,Eco,1121,2,2,2,1,1,2,1,1,3,1,2,3,3,1,5,0.0,neutral or dissatisfied +65512,51509,Female,Loyal Customer,62,Business travel,Business,261,1,1,1,1,2,4,1,4,4,4,4,2,4,5,0,7.0,satisfied +65513,5699,Male,Loyal Customer,51,Business travel,Eco,234,2,2,2,2,2,2,2,2,1,5,1,2,4,2,0,0.0,neutral or dissatisfied +65514,115243,Female,disloyal Customer,20,Business travel,Business,446,5,2,5,3,2,2,2,2,3,5,4,3,5,2,2,1.0,satisfied +65515,647,Female,Loyal Customer,37,Business travel,Business,1535,4,4,4,4,2,5,5,5,5,5,5,4,5,3,45,62.0,satisfied +65516,100148,Male,Loyal Customer,65,Business travel,Eco,725,2,3,4,3,2,2,2,2,2,5,3,2,3,2,8,0.0,neutral or dissatisfied +65517,100121,Male,disloyal Customer,24,Business travel,Eco,468,3,4,3,3,2,3,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +65518,78552,Female,Loyal Customer,54,Business travel,Eco Plus,526,2,4,4,4,2,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +65519,17328,Female,disloyal Customer,32,Business travel,Eco Plus,403,2,2,2,3,2,2,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +65520,6551,Male,disloyal Customer,38,Business travel,Business,618,4,4,4,3,2,4,2,2,3,5,4,3,4,2,7,0.0,satisfied +65521,18273,Male,Loyal Customer,41,Personal Travel,Eco,228,3,3,3,1,4,3,4,4,5,4,1,3,3,4,25,68.0,neutral or dissatisfied +65522,129718,Female,disloyal Customer,38,Business travel,Eco,337,3,2,3,4,4,3,4,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +65523,26251,Male,Loyal Customer,46,Business travel,Eco Plus,270,4,1,1,1,4,4,4,4,3,2,4,4,3,4,26,9.0,satisfied +65524,56182,Male,Loyal Customer,51,Personal Travel,Eco,1504,5,4,5,2,1,5,1,1,4,5,4,4,4,1,0,1.0,satisfied +65525,35874,Male,Loyal Customer,67,Personal Travel,Eco,1068,3,5,2,3,4,2,4,4,5,2,2,4,3,4,0,0.0,neutral or dissatisfied +65526,35979,Female,Loyal Customer,31,Business travel,Business,2184,2,2,2,2,5,5,5,5,2,5,4,4,1,5,0,0.0,satisfied +65527,84078,Male,Loyal Customer,65,Business travel,Eco,357,4,4,4,4,4,4,4,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +65528,33027,Male,Loyal Customer,39,Personal Travel,Eco,216,1,5,1,5,4,1,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +65529,77776,Female,Loyal Customer,40,Personal Travel,Eco,731,1,4,1,4,2,1,2,2,2,4,5,5,1,2,0,6.0,neutral or dissatisfied +65530,41264,Female,disloyal Customer,45,Business travel,Business,1075,2,2,2,4,5,2,5,5,4,3,3,1,4,5,0,6.0,neutral or dissatisfied +65531,125340,Male,Loyal Customer,51,Business travel,Business,2416,4,4,4,4,3,4,5,5,5,5,5,5,5,3,67,80.0,satisfied +65532,40440,Female,disloyal Customer,55,Business travel,Eco,188,2,2,2,3,2,2,2,2,2,4,3,3,4,2,0,0.0,neutral or dissatisfied +65533,51001,Female,Loyal Customer,23,Personal Travel,Eco,250,4,5,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +65534,102334,Male,disloyal Customer,19,Business travel,Eco,488,1,3,1,2,1,1,1,1,4,1,3,2,2,1,22,14.0,neutral or dissatisfied +65535,123174,Female,Loyal Customer,61,Business travel,Business,2388,0,5,0,1,3,1,2,2,2,2,2,3,2,1,4,0.0,satisfied +65536,33800,Male,Loyal Customer,27,Business travel,Business,1521,1,1,1,1,4,4,4,4,5,4,3,5,1,4,8,44.0,satisfied +65537,114887,Male,Loyal Customer,37,Business travel,Business,2990,3,3,3,3,4,5,4,4,4,4,4,4,4,3,111,129.0,satisfied +65538,63874,Male,Loyal Customer,31,Business travel,Business,2278,2,2,2,2,2,2,2,2,3,2,5,3,4,2,33,23.0,satisfied +65539,66487,Female,Loyal Customer,60,Business travel,Business,2201,5,5,2,5,5,5,5,4,5,5,5,5,4,5,138,179.0,satisfied +65540,65059,Female,Loyal Customer,18,Personal Travel,Eco,190,3,5,0,3,3,0,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +65541,40357,Male,Loyal Customer,62,Personal Travel,Business,1250,3,3,3,3,5,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +65542,117491,Female,Loyal Customer,38,Business travel,Business,1522,1,2,2,2,5,3,4,1,1,1,1,3,1,3,3,0.0,neutral or dissatisfied +65543,20006,Female,Loyal Customer,38,Business travel,Eco,189,2,1,1,1,2,2,2,2,1,2,4,1,4,2,0,0.0,neutral or dissatisfied +65544,129667,Male,disloyal Customer,61,Business travel,Eco,337,3,2,4,4,2,4,2,2,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +65545,20740,Male,Loyal Customer,37,Business travel,Business,363,3,3,3,3,5,5,5,3,4,2,2,5,4,5,141,126.0,satisfied +65546,33953,Male,Loyal Customer,47,Business travel,Eco Plus,672,4,3,3,3,5,4,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +65547,110835,Male,Loyal Customer,55,Personal Travel,Eco Plus,1105,2,1,3,4,3,3,3,3,1,4,3,1,3,3,0,1.0,neutral or dissatisfied +65548,44815,Male,Loyal Customer,50,Personal Travel,Eco,802,2,2,2,4,4,2,4,4,1,2,4,1,3,4,17,0.0,neutral or dissatisfied +65549,34217,Female,Loyal Customer,27,Personal Travel,Eco,1189,3,4,3,1,5,3,5,5,4,3,4,3,4,5,27,33.0,neutral or dissatisfied +65550,20392,Female,Loyal Customer,10,Business travel,Business,588,1,3,1,3,1,1,1,1,3,5,4,4,3,1,52,45.0,neutral or dissatisfied +65551,60701,Female,disloyal Customer,55,Business travel,Business,1605,4,4,4,2,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +65552,74086,Female,Loyal Customer,23,Business travel,Business,2966,4,2,4,4,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +65553,93459,Male,Loyal Customer,52,Personal Travel,Eco,723,2,4,3,3,3,3,3,3,5,4,4,4,4,3,22,15.0,neutral or dissatisfied +65554,40953,Male,disloyal Customer,23,Business travel,Eco,507,2,3,2,1,4,2,4,4,5,5,4,5,2,4,0,0.0,neutral or dissatisfied +65555,106534,Male,Loyal Customer,40,Business travel,Business,3231,1,1,4,4,2,4,3,1,1,1,1,3,1,3,12,52.0,neutral or dissatisfied +65556,120818,Male,Loyal Customer,14,Personal Travel,Eco,666,2,3,2,4,4,2,5,4,3,2,1,3,5,4,0,0.0,neutral or dissatisfied +65557,124894,Female,disloyal Customer,26,Business travel,Business,728,4,4,4,1,2,4,2,2,4,5,5,5,4,2,0,0.0,satisfied +65558,53382,Male,Loyal Customer,15,Personal Travel,Eco,1452,3,2,3,2,5,3,5,5,2,2,1,2,2,5,0,0.0,neutral or dissatisfied +65559,17878,Female,Loyal Customer,62,Personal Travel,Eco,425,0,0,0,1,4,4,4,1,1,0,1,3,1,4,0,0.0,satisfied +65560,70478,Female,Loyal Customer,38,Business travel,Business,3192,2,2,3,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +65561,127935,Male,Loyal Customer,51,Personal Travel,Eco,2300,2,4,2,4,5,2,5,5,4,3,3,5,5,5,1,0.0,neutral or dissatisfied +65562,63561,Female,disloyal Customer,20,Business travel,Eco Plus,1009,2,0,2,3,3,2,2,3,3,1,3,3,3,3,2,0.0,neutral or dissatisfied +65563,45367,Female,Loyal Customer,27,Personal Travel,Eco,188,2,4,2,3,3,2,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +65564,61319,Male,Loyal Customer,51,Business travel,Business,2776,4,4,3,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +65565,111042,Male,disloyal Customer,36,Business travel,Eco,197,2,2,2,2,5,2,5,5,2,4,1,1,1,5,42,46.0,neutral or dissatisfied +65566,14089,Female,Loyal Customer,34,Business travel,Business,425,4,4,4,4,2,3,5,5,5,5,5,1,5,5,0,1.0,satisfied +65567,74253,Female,Loyal Customer,30,Personal Travel,Eco,1709,3,3,3,4,4,3,4,4,5,3,1,1,4,4,24,33.0,neutral or dissatisfied +65568,100708,Female,disloyal Customer,38,Business travel,Business,328,3,3,3,3,4,3,1,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +65569,9846,Female,Loyal Customer,25,Business travel,Business,2685,3,3,3,3,3,3,3,3,5,4,5,5,4,3,0,1.0,satisfied +65570,57315,Female,Loyal Customer,42,Business travel,Business,414,5,5,1,5,5,5,4,4,4,4,4,5,4,4,11,0.0,satisfied +65571,95348,Male,Loyal Customer,63,Personal Travel,Eco,293,3,5,3,3,5,3,5,5,4,4,5,5,4,5,6,5.0,neutral or dissatisfied +65572,59041,Male,Loyal Customer,34,Business travel,Business,1744,2,1,1,1,2,1,2,2,2,2,2,1,2,4,52,62.0,neutral or dissatisfied +65573,49887,Female,disloyal Customer,37,Business travel,Eco,153,3,1,3,4,4,3,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +65574,94258,Female,Loyal Customer,35,Business travel,Business,3855,2,2,2,2,3,5,5,5,5,5,4,5,5,5,11,8.0,satisfied +65575,81229,Male,Loyal Customer,48,Business travel,Business,2963,0,5,0,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +65576,104368,Male,Loyal Customer,34,Business travel,Business,228,4,4,4,4,2,5,4,5,5,5,5,4,5,3,52,65.0,satisfied +65577,79370,Male,Loyal Customer,42,Business travel,Business,3609,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +65578,127968,Female,Loyal Customer,54,Business travel,Business,1999,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +65579,78159,Male,disloyal Customer,48,Business travel,Business,192,3,3,3,1,5,3,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +65580,115062,Male,Loyal Customer,80,Business travel,Business,2689,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +65581,14706,Female,Loyal Customer,27,Business travel,Business,419,3,2,4,2,3,3,3,3,1,5,3,2,4,3,49,47.0,neutral or dissatisfied +65582,37174,Male,Loyal Customer,69,Personal Travel,Eco,1189,2,5,2,5,2,2,1,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +65583,22724,Male,Loyal Customer,57,Business travel,Business,147,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +65584,4755,Male,disloyal Customer,21,Business travel,Business,403,3,3,3,2,1,3,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +65585,68004,Female,disloyal Customer,49,Business travel,Business,304,3,3,3,2,4,3,5,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +65586,45257,Male,Loyal Customer,44,Personal Travel,Eco,584,3,2,3,3,3,3,3,3,4,4,4,4,4,3,0,5.0,neutral or dissatisfied +65587,51351,Female,disloyal Customer,18,Business travel,Eco Plus,86,3,0,3,3,1,3,2,1,4,1,4,5,1,1,0,2.0,neutral or dissatisfied +65588,86758,Female,Loyal Customer,8,Personal Travel,Eco,821,3,5,3,2,4,3,4,4,4,4,1,3,4,4,29,15.0,neutral or dissatisfied +65589,80211,Male,Loyal Customer,14,Personal Travel,Eco Plus,2475,3,5,4,2,2,4,2,2,3,3,3,5,5,2,0,0.0,neutral or dissatisfied +65590,106027,Female,disloyal Customer,29,Business travel,Business,682,1,1,1,3,2,1,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +65591,31793,Female,Loyal Customer,51,Business travel,Business,2640,3,5,5,5,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +65592,50140,Male,disloyal Customer,27,Business travel,Eco,77,1,3,1,4,2,1,2,2,3,1,4,4,3,2,33,33.0,neutral or dissatisfied +65593,65461,Male,Loyal Customer,25,Business travel,Business,3367,5,5,5,5,4,4,4,4,4,3,5,3,5,4,11,0.0,satisfied +65594,92887,Female,Loyal Customer,40,Business travel,Business,3670,1,1,1,1,4,4,5,3,3,4,5,4,3,3,0,0.0,satisfied +65595,2241,Female,Loyal Customer,48,Business travel,Business,1041,2,2,2,2,3,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +65596,17634,Male,Loyal Customer,65,Personal Travel,Eco Plus,980,3,4,4,2,4,4,4,4,4,2,5,3,5,4,15,20.0,neutral or dissatisfied +65597,83338,Female,Loyal Customer,27,Personal Travel,Eco Plus,2105,1,0,1,2,4,1,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +65598,58547,Male,Loyal Customer,41,Business travel,Business,1514,4,4,4,4,2,5,5,4,4,4,4,4,4,4,31,27.0,satisfied +65599,91200,Male,Loyal Customer,15,Personal Travel,Eco,581,1,4,1,1,2,1,2,2,4,4,5,4,4,2,19,18.0,neutral or dissatisfied +65600,8702,Female,Loyal Customer,22,Business travel,Business,2497,4,3,4,4,4,4,4,4,3,2,4,1,5,4,0,0.0,satisfied +65601,85478,Male,disloyal Customer,24,Business travel,Eco,332,1,1,0,4,2,0,2,2,4,2,3,3,3,2,4,4.0,neutral or dissatisfied +65602,69042,Female,Loyal Customer,47,Business travel,Business,1389,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +65603,38999,Female,Loyal Customer,24,Business travel,Business,2746,3,5,5,5,3,3,3,3,4,2,3,1,3,3,0,18.0,neutral or dissatisfied +65604,129648,Female,Loyal Customer,53,Business travel,Business,337,1,1,4,1,4,5,4,4,4,4,4,4,4,3,0,9.0,satisfied +65605,85718,Male,Loyal Customer,51,Business travel,Business,1963,3,3,3,3,2,5,5,4,4,5,4,3,4,5,27,36.0,satisfied +65606,89257,Female,Loyal Customer,48,Business travel,Business,453,4,4,4,4,3,4,5,3,3,2,3,4,3,5,0,0.0,satisfied +65607,47704,Male,Loyal Customer,66,Personal Travel,Eco,1482,2,4,2,4,1,2,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +65608,37145,Male,Loyal Customer,47,Business travel,Business,3174,3,2,2,2,2,2,3,3,3,3,3,2,3,4,6,0.0,neutral or dissatisfied +65609,98766,Male,Loyal Customer,43,Personal Travel,Eco,1814,2,5,2,2,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +65610,82889,Male,Loyal Customer,15,Personal Travel,Eco,594,2,3,2,3,1,2,1,1,3,3,4,2,3,1,0,0.0,neutral or dissatisfied +65611,28047,Female,Loyal Customer,29,Business travel,Business,1739,2,2,2,2,5,4,5,5,5,2,3,3,2,5,81,115.0,satisfied +65612,118080,Female,Loyal Customer,41,Business travel,Business,1276,2,2,2,2,2,5,4,3,3,4,3,4,3,4,3,7.0,satisfied +65613,52005,Male,disloyal Customer,37,Business travel,Eco,328,3,0,3,4,4,3,1,4,2,4,1,3,5,4,11,15.0,neutral or dissatisfied +65614,89047,Male,Loyal Customer,40,Business travel,Business,1892,4,4,4,4,4,3,4,4,4,4,4,3,4,3,6,0.0,satisfied +65615,120099,Male,Loyal Customer,24,Business travel,Business,1576,5,5,5,5,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +65616,59328,Male,Loyal Customer,27,Business travel,Business,2556,3,3,2,3,4,4,4,4,3,5,5,4,3,4,312,265.0,satisfied +65617,125578,Female,Loyal Customer,46,Business travel,Business,3116,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +65618,70966,Female,Loyal Customer,38,Personal Travel,Business,802,2,2,2,3,1,3,3,3,3,2,3,2,3,2,18,23.0,neutral or dissatisfied +65619,113457,Male,Loyal Customer,53,Business travel,Business,223,0,4,0,1,2,4,5,1,1,1,1,4,1,5,0,0.0,satisfied +65620,60963,Female,Loyal Customer,11,Business travel,Business,888,2,2,2,2,5,5,5,5,4,4,4,5,4,5,2,0.0,satisfied +65621,106641,Female,Loyal Customer,70,Personal Travel,Eco Plus,306,2,4,2,4,2,4,5,4,4,2,4,3,4,3,1,0.0,neutral or dissatisfied +65622,49825,Female,Loyal Customer,55,Business travel,Eco,86,1,2,2,2,1,3,3,2,2,1,2,1,2,4,26,34.0,neutral or dissatisfied +65623,127777,Female,Loyal Customer,57,Business travel,Business,3122,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +65624,73752,Female,Loyal Customer,44,Personal Travel,Eco,204,4,5,4,3,4,4,1,4,4,4,4,2,4,5,0,0.0,neutral or dissatisfied +65625,25060,Female,Loyal Customer,70,Personal Travel,Eco,594,2,3,2,3,5,5,5,3,3,2,3,4,3,3,24,10.0,neutral or dissatisfied +65626,24668,Male,Loyal Customer,67,Personal Travel,Eco Plus,834,3,4,3,2,3,3,3,3,4,4,5,3,3,3,298,312.0,neutral or dissatisfied +65627,80380,Female,disloyal Customer,22,Business travel,Eco,368,4,5,4,4,1,4,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +65628,42359,Male,Loyal Customer,49,Personal Travel,Eco,748,1,1,1,3,5,1,5,5,2,2,3,4,3,5,0,0.0,neutral or dissatisfied +65629,72496,Female,Loyal Customer,51,Business travel,Eco,985,2,4,4,4,2,2,2,4,5,4,4,2,2,2,192,225.0,neutral or dissatisfied +65630,63243,Male,disloyal Customer,34,Business travel,Business,372,1,1,1,2,4,1,2,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +65631,39048,Male,disloyal Customer,24,Business travel,Eco Plus,313,4,0,5,2,2,5,3,2,4,3,1,4,3,2,0,3.0,satisfied +65632,91239,Female,Loyal Customer,21,Personal Travel,Eco,404,1,4,1,4,2,1,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +65633,48060,Male,Loyal Customer,44,Personal Travel,Eco Plus,677,3,3,3,3,2,3,2,2,4,5,3,1,3,2,0,6.0,neutral or dissatisfied +65634,106177,Female,Loyal Customer,47,Personal Travel,Eco,302,2,1,2,3,5,3,4,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +65635,49071,Female,Loyal Customer,48,Business travel,Eco,337,5,5,1,5,3,3,1,5,5,5,5,2,5,3,0,0.0,satisfied +65636,105040,Female,Loyal Customer,23,Personal Travel,Eco,255,1,5,0,5,5,0,5,5,5,2,2,5,5,5,25,21.0,neutral or dissatisfied +65637,13684,Female,Loyal Customer,28,Personal Travel,Eco,954,3,3,3,3,2,3,4,2,2,1,4,2,3,2,2,0.0,neutral or dissatisfied +65638,42842,Female,Loyal Customer,43,Business travel,Business,3073,4,4,4,4,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +65639,126192,Male,Loyal Customer,53,Business travel,Eco,600,4,4,4,4,4,4,4,4,2,1,3,1,2,4,0,0.0,neutral or dissatisfied +65640,32238,Male,Loyal Customer,39,Business travel,Business,101,2,2,5,2,5,1,3,5,5,5,3,5,5,4,0,0.0,satisfied +65641,68830,Male,Loyal Customer,54,Business travel,Business,3250,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +65642,30166,Female,Loyal Customer,63,Personal Travel,Eco,183,3,4,3,2,5,1,4,2,2,3,2,2,2,2,1,11.0,neutral or dissatisfied +65643,109034,Female,Loyal Customer,26,Business travel,Business,1568,2,2,2,2,5,5,5,5,4,4,5,3,5,5,29,6.0,satisfied +65644,65005,Male,disloyal Customer,24,Business travel,Eco,247,2,2,2,3,3,2,3,3,4,1,3,1,3,3,20,7.0,neutral or dissatisfied +65645,78676,Male,disloyal Customer,42,Business travel,Business,761,2,2,2,1,2,2,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +65646,71155,Male,Loyal Customer,15,Business travel,Business,3925,5,5,5,5,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +65647,2163,Male,Loyal Customer,54,Business travel,Business,685,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,8.0,satisfied +65648,81796,Male,disloyal Customer,23,Business travel,Eco,1306,4,4,4,3,1,4,1,1,3,4,2,1,2,1,0,0.0,neutral or dissatisfied +65649,69203,Male,Loyal Customer,39,Business travel,Business,733,5,5,2,5,2,4,5,4,4,4,4,3,4,4,91,90.0,satisfied +65650,110211,Female,disloyal Customer,28,Business travel,Eco,1310,2,2,2,3,3,2,3,3,3,4,4,2,4,3,15,8.0,neutral or dissatisfied +65651,78110,Male,Loyal Customer,50,Business travel,Business,1797,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +65652,94954,Female,Loyal Customer,79,Business travel,Eco,162,5,4,4,4,1,3,4,5,5,5,5,4,5,1,0,0.0,satisfied +65653,96389,Male,disloyal Customer,39,Business travel,Business,1246,4,4,4,1,5,4,5,5,3,5,4,3,5,5,15,15.0,satisfied +65654,86320,Male,Loyal Customer,54,Business travel,Business,331,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,2.0,satisfied +65655,5779,Male,Loyal Customer,10,Personal Travel,Business,157,4,4,4,5,1,4,1,1,4,2,5,3,5,1,3,96.0,satisfied +65656,89351,Male,Loyal Customer,38,Business travel,Business,1962,2,2,2,2,1,5,2,5,5,5,5,1,5,4,0,0.0,satisfied +65657,11408,Male,Loyal Customer,61,Business travel,Business,1936,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +65658,105447,Female,Loyal Customer,9,Business travel,Business,2116,3,4,4,4,3,3,3,3,2,5,3,4,3,3,5,13.0,neutral or dissatisfied +65659,48911,Male,Loyal Customer,42,Business travel,Business,89,2,5,5,5,1,3,4,3,3,3,2,2,3,3,0,0.0,neutral or dissatisfied +65660,22129,Female,Loyal Customer,51,Business travel,Business,2945,3,5,5,5,4,2,3,3,3,3,3,4,3,4,27,23.0,neutral or dissatisfied +65661,70933,Male,Loyal Customer,46,Business travel,Business,3835,4,4,2,4,5,4,4,4,4,4,4,5,4,4,30,42.0,satisfied +65662,43883,Male,disloyal Customer,48,Business travel,Eco,199,3,3,3,1,1,3,1,1,1,3,3,2,2,1,5,0.0,neutral or dissatisfied +65663,128820,Male,Loyal Customer,56,Business travel,Business,2475,2,5,2,5,2,2,2,1,3,1,3,2,2,2,0,8.0,neutral or dissatisfied +65664,116331,Female,Loyal Customer,33,Personal Travel,Eco,373,1,4,1,4,2,1,3,2,1,1,3,2,3,2,57,50.0,neutral or dissatisfied +65665,39659,Male,Loyal Customer,35,Personal Travel,Eco,288,2,4,2,1,5,2,5,5,3,3,4,4,4,5,7,7.0,neutral or dissatisfied +65666,126186,Female,Loyal Customer,45,Business travel,Business,2767,4,2,4,4,2,5,4,5,5,5,5,4,5,5,1,2.0,satisfied +65667,100801,Female,Loyal Customer,10,Personal Travel,Eco,748,5,4,4,2,5,4,5,5,3,3,4,3,4,5,0,0.0,satisfied +65668,96424,Male,Loyal Customer,15,Personal Travel,Eco Plus,1342,3,5,3,5,4,3,4,4,5,4,3,4,5,4,39,27.0,neutral or dissatisfied +65669,11810,Male,disloyal Customer,23,Business travel,Business,429,4,5,4,3,4,4,2,4,5,3,5,5,5,4,0,0.0,satisfied +65670,4251,Female,Loyal Customer,40,Business travel,Business,1020,2,2,2,2,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +65671,103867,Female,Loyal Customer,54,Personal Travel,Eco,882,3,5,3,3,1,5,2,2,2,3,2,3,2,1,0,1.0,neutral or dissatisfied +65672,47034,Male,Loyal Customer,40,Business travel,Business,2654,4,3,3,3,3,3,3,4,4,4,4,3,4,3,33,29.0,neutral or dissatisfied +65673,71461,Male,Loyal Customer,39,Personal Travel,Eco,867,3,2,3,4,5,3,4,5,2,5,4,4,3,5,0,13.0,neutral or dissatisfied +65674,99947,Male,Loyal Customer,73,Business travel,Business,3869,4,5,5,5,2,3,3,4,4,4,4,3,4,2,100,81.0,neutral or dissatisfied +65675,6235,Female,Loyal Customer,52,Business travel,Business,3512,5,5,5,5,3,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +65676,26182,Male,disloyal Customer,16,Business travel,Eco,404,1,0,1,2,4,1,4,4,4,4,3,2,3,4,0,0.0,neutral or dissatisfied +65677,74180,Female,Loyal Customer,52,Personal Travel,Eco,592,3,5,3,2,1,2,1,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +65678,89054,Male,Loyal Customer,53,Business travel,Business,2139,1,1,1,1,4,4,4,2,2,2,2,3,2,3,19,3.0,satisfied +65679,18759,Female,Loyal Customer,48,Business travel,Eco,1039,5,2,2,2,5,3,3,2,5,5,5,3,4,3,410,397.0,satisfied +65680,65288,Female,Loyal Customer,58,Personal Travel,Eco Plus,551,3,3,3,3,4,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +65681,76068,Male,disloyal Customer,30,Business travel,Business,669,1,1,1,5,2,1,5,2,4,4,4,3,5,2,35,25.0,neutral or dissatisfied +65682,110688,Male,Loyal Customer,47,Personal Travel,Eco,945,4,4,4,4,5,4,2,5,4,1,3,1,3,5,0,5.0,neutral or dissatisfied +65683,90958,Male,Loyal Customer,53,Business travel,Business,1616,1,1,1,1,1,4,1,5,5,5,5,5,5,5,0,0.0,satisfied +65684,23777,Female,Loyal Customer,22,Business travel,Eco,438,5,5,5,5,5,5,5,5,1,1,2,1,2,5,0,0.0,satisfied +65685,39452,Male,Loyal Customer,69,Personal Travel,Eco,129,4,0,4,1,5,4,5,5,3,3,5,3,4,5,2,9.0,neutral or dissatisfied +65686,55787,Female,Loyal Customer,44,Business travel,Business,2400,5,5,5,5,4,4,4,3,4,3,4,4,3,4,0,0.0,satisfied +65687,14058,Male,Loyal Customer,45,Business travel,Business,319,0,0,0,1,2,4,2,1,1,1,1,5,1,5,108,82.0,satisfied +65688,92758,Male,Loyal Customer,59,Personal Travel,Eco,1276,3,5,3,3,2,3,2,2,4,4,5,3,4,2,0,11.0,neutral or dissatisfied +65689,119909,Male,Loyal Customer,37,Business travel,Business,3281,3,3,2,3,3,4,5,4,4,4,4,3,4,3,6,49.0,satisfied +65690,108686,Male,Loyal Customer,57,Business travel,Business,2514,1,1,4,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +65691,69461,Male,Loyal Customer,23,Personal Travel,Eco,944,1,3,1,4,5,1,5,5,2,5,4,2,2,5,86,81.0,neutral or dissatisfied +65692,124351,Male,Loyal Customer,40,Business travel,Business,2019,3,3,5,3,5,5,5,4,4,4,4,4,4,3,0,10.0,satisfied +65693,77220,Female,disloyal Customer,35,Business travel,Business,1590,2,2,2,3,1,2,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +65694,10697,Male,Loyal Customer,28,Business travel,Business,316,3,3,3,3,5,5,5,5,3,2,4,4,4,5,1,0.0,satisfied +65695,92646,Male,Loyal Customer,61,Personal Travel,Eco,453,4,3,4,4,1,4,1,1,4,2,3,2,4,1,0,11.0,neutral or dissatisfied +65696,128815,Female,disloyal Customer,34,Business travel,Business,2475,1,1,1,1,1,3,3,3,3,5,5,3,5,3,5,7.0,neutral or dissatisfied +65697,58413,Male,Loyal Customer,41,Business travel,Business,3092,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +65698,18760,Male,Loyal Customer,38,Business travel,Eco,926,3,2,2,2,3,3,3,2,5,4,4,3,4,3,157,146.0,neutral or dissatisfied +65699,30192,Male,Loyal Customer,22,Business travel,Eco Plus,725,3,3,3,3,3,4,3,3,2,1,3,3,3,3,0,8.0,neutral or dissatisfied +65700,115375,Male,Loyal Customer,48,Business travel,Business,333,2,2,2,2,4,5,4,4,4,4,4,5,4,5,22,13.0,satisfied +65701,111094,Female,Loyal Customer,45,Business travel,Business,319,1,1,1,1,4,5,4,4,4,4,4,4,4,5,33,40.0,satisfied +65702,18605,Male,Loyal Customer,45,Business travel,Eco,383,1,4,4,4,1,2,2,4,2,3,4,2,1,2,137,129.0,neutral or dissatisfied +65703,101737,Male,disloyal Customer,54,Business travel,Business,1190,2,2,2,1,1,2,1,1,3,4,5,5,4,1,7,4.0,neutral or dissatisfied +65704,103139,Female,Loyal Customer,67,Personal Travel,Eco Plus,546,3,3,3,3,1,3,4,2,2,3,2,2,2,3,29,16.0,neutral or dissatisfied +65705,11905,Male,disloyal Customer,25,Business travel,Business,501,4,5,4,3,5,4,5,5,4,4,4,5,5,5,0,5.0,satisfied +65706,81900,Female,Loyal Customer,55,Business travel,Eco,680,1,3,3,3,1,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +65707,26596,Female,Loyal Customer,51,Business travel,Eco,581,2,2,2,2,5,4,3,2,2,2,2,2,2,1,0,1.0,satisfied +65708,98325,Male,disloyal Customer,24,Business travel,Business,1046,4,0,4,4,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +65709,8610,Male,Loyal Customer,32,Business travel,Business,1371,3,3,3,3,4,4,4,4,4,3,4,5,5,4,20,44.0,satisfied +65710,104109,Female,Loyal Customer,61,Personal Travel,Eco,297,1,4,1,4,5,4,5,4,4,1,4,3,4,5,0,1.0,neutral or dissatisfied +65711,127444,Male,disloyal Customer,27,Business travel,Eco Plus,609,4,4,4,4,2,4,2,2,5,5,3,2,5,2,0,0.0,neutral or dissatisfied +65712,76790,Male,disloyal Customer,52,Business travel,Eco,546,3,2,3,2,5,3,5,5,4,4,3,4,3,5,3,13.0,neutral or dissatisfied +65713,12102,Male,Loyal Customer,33,Business travel,Eco,1034,0,0,0,2,2,0,2,2,4,3,3,1,4,2,21,7.0,satisfied +65714,2875,Male,Loyal Customer,13,Personal Travel,Eco,409,2,4,2,2,4,2,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +65715,35068,Female,Loyal Customer,57,Business travel,Business,3321,1,1,4,1,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +65716,8641,Female,Loyal Customer,44,Business travel,Business,280,4,5,4,4,2,4,5,5,5,5,5,3,5,3,5,3.0,satisfied +65717,51332,Female,Loyal Customer,30,Business travel,Eco Plus,308,0,0,0,2,1,0,1,1,3,4,5,4,1,1,0,0.0,satisfied +65718,86463,Male,Loyal Customer,58,Business travel,Eco,712,3,2,2,2,3,3,3,3,2,5,3,4,3,3,5,0.0,neutral or dissatisfied +65719,72077,Female,Loyal Customer,42,Business travel,Eco,2486,2,4,4,4,1,2,3,2,2,2,2,2,2,4,43,27.0,neutral or dissatisfied +65720,71479,Female,Loyal Customer,40,Business travel,Business,4243,2,2,2,2,4,4,4,5,4,3,5,4,4,4,27,36.0,satisfied +65721,102111,Male,Loyal Customer,41,Business travel,Business,2505,3,3,3,3,4,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +65722,123964,Female,Loyal Customer,54,Business travel,Business,3646,3,3,3,3,4,5,4,5,5,5,5,4,5,4,48,53.0,satisfied +65723,26585,Male,Loyal Customer,35,Business travel,Business,404,3,3,3,3,1,2,4,4,4,4,4,4,4,5,0,0.0,satisfied +65724,114583,Male,disloyal Customer,39,Business travel,Business,480,1,1,1,1,1,1,4,1,3,5,5,3,5,1,30,15.0,neutral or dissatisfied +65725,26147,Male,disloyal Customer,45,Business travel,Eco,581,3,0,3,3,5,3,5,5,2,1,4,1,4,5,0,0.0,neutral or dissatisfied +65726,86839,Female,disloyal Customer,50,Business travel,Eco,484,4,4,4,3,2,4,2,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +65727,34750,Female,Loyal Customer,20,Business travel,Business,3618,2,3,3,3,3,2,2,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +65728,102126,Male,Loyal Customer,54,Business travel,Business,1543,1,1,1,1,3,5,5,5,5,5,5,4,5,4,17,14.0,satisfied +65729,47142,Female,disloyal Customer,34,Business travel,Eco,908,1,1,1,3,5,1,5,5,2,5,4,5,3,5,0,0.0,neutral or dissatisfied +65730,84832,Female,Loyal Customer,42,Business travel,Business,481,1,2,2,2,2,4,3,1,1,1,1,4,1,4,26,30.0,neutral or dissatisfied +65731,60262,Female,disloyal Customer,24,Business travel,Eco,1703,4,4,4,4,3,4,3,3,4,3,4,4,5,3,1,0.0,neutral or dissatisfied +65732,26659,Male,Loyal Customer,36,Business travel,Business,145,0,5,0,3,4,5,3,4,4,4,4,4,4,5,0,0.0,satisfied +65733,117949,Female,disloyal Customer,25,Business travel,Business,255,2,5,2,4,2,2,1,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +65734,55103,Male,Loyal Customer,62,Business travel,Business,2531,1,1,3,3,5,3,3,2,2,3,1,3,2,1,0,0.0,neutral or dissatisfied +65735,8739,Female,disloyal Customer,44,Business travel,Business,181,5,5,5,5,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +65736,22039,Male,Loyal Customer,23,Personal Travel,Eco Plus,448,2,4,2,4,3,2,3,3,1,1,3,5,5,3,0,0.0,neutral or dissatisfied +65737,65917,Female,Loyal Customer,54,Business travel,Business,3095,3,4,4,4,4,3,2,3,3,2,3,2,3,4,0,11.0,neutral or dissatisfied +65738,78379,Female,Loyal Customer,33,Business travel,Business,2521,2,2,2,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +65739,62425,Female,disloyal Customer,29,Business travel,Eco,1911,1,2,2,3,1,1,1,1,3,1,4,1,4,1,104,89.0,neutral or dissatisfied +65740,104227,Male,Loyal Customer,21,Personal Travel,Eco,680,2,1,2,2,2,2,2,2,2,1,3,3,2,2,7,1.0,neutral or dissatisfied +65741,83842,Female,Loyal Customer,65,Personal Travel,Eco,425,4,0,4,2,2,5,5,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +65742,41615,Male,Loyal Customer,35,Business travel,Eco Plus,1235,5,1,1,1,5,5,5,5,5,5,5,2,4,5,4,0.0,satisfied +65743,16102,Female,Loyal Customer,35,Personal Travel,Eco,349,1,2,1,3,4,1,2,4,1,4,3,4,3,4,0,3.0,neutral or dissatisfied +65744,81148,Male,disloyal Customer,8,Business travel,Business,1310,2,0,2,3,3,2,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +65745,28944,Male,Loyal Customer,38,Business travel,Business,1672,3,3,5,3,3,1,3,4,4,4,4,4,4,5,0,13.0,satisfied +65746,84998,Male,Loyal Customer,29,Business travel,Business,1590,2,5,5,5,2,2,2,2,2,4,4,1,4,2,0,1.0,neutral or dissatisfied +65747,47766,Male,Loyal Customer,57,Business travel,Eco,838,4,5,5,5,4,4,4,4,2,1,4,2,1,4,0,0.0,satisfied +65748,37400,Male,disloyal Customer,22,Business travel,Eco,1118,4,4,4,3,2,4,2,2,4,2,5,1,4,2,31,13.0,satisfied +65749,39368,Male,Loyal Customer,28,Personal Travel,Eco,896,4,5,4,3,2,4,2,2,3,2,5,3,5,2,0,0.0,satisfied +65750,85335,Male,Loyal Customer,46,Business travel,Business,3424,3,3,3,3,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +65751,62213,Male,Loyal Customer,9,Personal Travel,Eco,2425,2,5,2,1,2,2,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +65752,87698,Male,Loyal Customer,34,Personal Travel,Eco,591,2,2,2,2,4,2,4,4,2,4,3,3,3,4,0,1.0,neutral or dissatisfied +65753,61860,Male,Loyal Customer,65,Personal Travel,Eco Plus,1346,2,5,1,3,2,1,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +65754,65422,Female,Loyal Customer,52,Business travel,Business,2165,5,5,2,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +65755,8881,Female,Loyal Customer,18,Business travel,Business,539,3,4,4,4,3,2,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +65756,103363,Female,Loyal Customer,48,Business travel,Business,2086,2,2,2,2,5,5,5,4,4,4,4,3,4,4,27,26.0,satisfied +65757,103786,Male,Loyal Customer,39,Business travel,Business,1072,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +65758,9281,Male,Loyal Customer,29,Business travel,Eco,1190,4,3,3,3,4,4,4,4,2,4,3,2,3,4,2,0.0,neutral or dissatisfied +65759,124234,Male,Loyal Customer,40,Business travel,Business,1916,5,5,5,5,3,3,3,3,4,4,4,3,5,3,185,160.0,satisfied +65760,94494,Male,Loyal Customer,54,Business travel,Business,3419,5,5,5,5,2,4,5,5,5,5,4,4,5,3,2,0.0,satisfied +65761,29580,Female,Loyal Customer,32,Business travel,Business,1448,4,4,4,4,4,4,4,4,1,5,2,5,5,4,0,0.0,satisfied +65762,4336,Female,disloyal Customer,26,Business travel,Business,607,2,4,2,2,5,2,5,5,5,3,5,3,5,5,4,6.0,neutral or dissatisfied +65763,105596,Male,Loyal Customer,53,Business travel,Business,919,1,1,1,1,2,5,4,4,4,4,4,3,4,4,74,84.0,satisfied +65764,43020,Female,disloyal Customer,30,Business travel,Eco,259,2,0,2,3,5,2,5,5,4,1,2,5,1,5,0,0.0,neutral or dissatisfied +65765,32531,Female,Loyal Customer,37,Business travel,Eco,102,4,5,5,5,4,5,4,4,5,1,2,4,3,4,0,0.0,satisfied +65766,129253,Female,Loyal Customer,16,Personal Travel,Eco,1464,2,4,2,2,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +65767,4413,Male,Loyal Customer,48,Business travel,Business,1962,1,1,1,1,4,4,5,3,3,3,3,3,3,5,130,118.0,satisfied +65768,117217,Male,Loyal Customer,62,Personal Travel,Eco,304,4,5,4,2,2,4,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +65769,39404,Male,Loyal Customer,50,Business travel,Business,3836,3,5,5,5,2,4,3,3,3,3,3,3,3,2,0,6.0,neutral or dissatisfied +65770,14802,Female,Loyal Customer,71,Business travel,Eco,133,3,3,3,3,2,4,3,3,3,3,3,4,3,2,5,0.0,neutral or dissatisfied +65771,8108,Female,Loyal Customer,43,Business travel,Business,3150,2,2,2,2,2,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +65772,11911,Female,Loyal Customer,25,Business travel,Business,344,3,3,2,3,3,3,3,3,3,1,3,3,3,3,4,19.0,neutral or dissatisfied +65773,642,Female,Loyal Customer,52,Business travel,Business,2216,1,1,1,1,2,5,5,4,4,4,5,4,4,3,0,3.0,satisfied +65774,7633,Male,disloyal Customer,50,Business travel,Business,604,3,3,3,2,5,3,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +65775,79587,Female,Loyal Customer,12,Business travel,Business,3556,2,5,5,5,2,2,2,2,4,5,4,3,4,2,25,14.0,neutral or dissatisfied +65776,4664,Male,Loyal Customer,49,Business travel,Business,3281,2,5,5,5,2,2,2,1,5,3,3,2,1,2,131,118.0,neutral or dissatisfied +65777,79907,Male,Loyal Customer,38,Business travel,Business,1080,5,5,5,5,5,5,5,2,2,2,2,5,2,3,65,103.0,satisfied +65778,91658,Female,Loyal Customer,10,Personal Travel,Eco,1199,1,5,1,2,3,1,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +65779,73750,Female,Loyal Customer,50,Personal Travel,Eco,204,1,1,1,4,1,3,3,4,4,1,1,4,4,4,15,10.0,neutral or dissatisfied +65780,84384,Female,Loyal Customer,43,Business travel,Business,2673,1,1,1,1,3,2,3,1,1,1,1,3,1,3,53,37.0,neutral or dissatisfied +65781,98251,Female,Loyal Customer,40,Business travel,Business,1136,2,2,2,2,5,4,4,4,4,4,4,3,4,3,65,103.0,satisfied +65782,5984,Female,Loyal Customer,48,Business travel,Business,3440,4,4,4,4,4,4,4,4,4,5,4,4,4,4,193,199.0,satisfied +65783,3580,Male,Loyal Customer,34,Personal Travel,Eco Plus,227,1,5,1,4,4,1,4,4,3,2,5,5,4,4,5,3.0,neutral or dissatisfied +65784,41521,Female,Loyal Customer,54,Business travel,Business,1428,3,5,3,3,3,1,5,4,4,4,4,4,4,4,0,0.0,satisfied +65785,85207,Female,Loyal Customer,25,Business travel,Business,3434,3,2,2,2,3,2,3,3,3,2,3,4,4,3,20,17.0,neutral or dissatisfied +65786,70641,Female,Loyal Customer,40,Business travel,Business,946,5,4,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +65787,124659,Female,Loyal Customer,32,Business travel,Business,1687,5,5,5,5,3,4,3,3,3,2,4,3,4,3,0,0.0,satisfied +65788,38534,Male,disloyal Customer,22,Business travel,Eco,2475,4,4,4,3,1,4,1,1,2,3,4,2,4,1,37,18.0,neutral or dissatisfied +65789,10200,Female,Loyal Customer,38,Business travel,Business,295,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +65790,128659,Male,Loyal Customer,45,Business travel,Business,2419,2,2,5,2,4,4,4,3,4,4,4,4,3,4,0,7.0,satisfied +65791,73492,Male,Loyal Customer,16,Personal Travel,Eco,1197,3,5,3,4,2,3,2,2,5,5,3,3,5,2,0,0.0,neutral or dissatisfied +65792,86153,Female,Loyal Customer,49,Business travel,Business,2177,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +65793,27272,Male,disloyal Customer,38,Business travel,Business,578,2,2,2,3,4,2,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +65794,72559,Female,Loyal Customer,55,Business travel,Eco,985,2,2,2,2,3,4,3,2,2,2,2,2,2,4,0,4.0,neutral or dissatisfied +65795,9862,Female,Loyal Customer,13,Personal Travel,Eco,531,1,4,1,2,3,1,1,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +65796,119918,Male,Loyal Customer,11,Personal Travel,Business,868,3,4,3,3,2,3,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +65797,84703,Female,Loyal Customer,44,Business travel,Business,2272,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +65798,10849,Male,Loyal Customer,40,Business travel,Business,2015,2,4,4,4,4,4,4,3,3,3,2,1,3,2,38,45.0,neutral or dissatisfied +65799,97686,Female,disloyal Customer,26,Business travel,Eco Plus,272,4,4,4,3,5,4,5,5,2,1,4,3,3,5,5,7.0,neutral or dissatisfied +65800,115162,Female,Loyal Customer,31,Business travel,Business,3676,5,5,5,5,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +65801,117979,Male,Loyal Customer,7,Personal Travel,Eco,255,4,0,4,1,4,4,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +65802,43442,Male,disloyal Customer,32,Business travel,Eco,679,3,3,3,4,4,3,4,4,3,4,3,4,3,4,82,79.0,neutral or dissatisfied +65803,47711,Male,Loyal Customer,26,Business travel,Eco Plus,1464,3,2,2,2,3,3,4,3,1,4,4,4,4,3,5,0.0,neutral or dissatisfied +65804,27504,Female,Loyal Customer,63,Business travel,Business,2645,3,2,2,2,4,3,4,3,3,3,3,4,3,4,4,0.0,neutral or dissatisfied +65805,28377,Male,disloyal Customer,26,Business travel,Eco,763,4,3,3,3,5,3,5,5,3,3,3,1,3,5,16,7.0,neutral or dissatisfied +65806,64344,Female,disloyal Customer,27,Business travel,Business,1192,3,2,2,5,3,2,3,3,4,5,4,3,5,3,3,9.0,neutral or dissatisfied +65807,73503,Male,Loyal Customer,34,Business travel,Business,1197,2,2,2,2,5,5,4,4,4,4,4,5,4,4,35,20.0,satisfied +65808,120785,Male,Loyal Customer,48,Personal Travel,Eco,678,2,1,2,4,4,2,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +65809,22297,Male,disloyal Customer,33,Business travel,Eco,145,3,0,3,1,3,3,3,3,2,4,4,4,2,3,0,0.0,neutral or dissatisfied +65810,4636,Male,Loyal Customer,45,Business travel,Business,3229,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +65811,20400,Female,Loyal Customer,9,Personal Travel,Eco,459,1,5,1,3,2,1,3,2,4,5,4,4,5,2,0,11.0,neutral or dissatisfied +65812,111574,Male,Loyal Customer,45,Business travel,Eco,483,3,1,1,1,3,3,3,3,1,4,4,1,4,3,1,0.0,neutral or dissatisfied +65813,39187,Female,Loyal Customer,9,Personal Travel,Eco,237,1,1,1,3,3,1,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +65814,5008,Female,Loyal Customer,61,Personal Travel,Eco,502,1,3,1,3,1,4,4,1,1,1,4,1,1,3,19,31.0,neutral or dissatisfied +65815,111295,Male,Loyal Customer,53,Business travel,Business,2297,3,3,5,3,5,5,5,5,5,5,4,5,5,5,22,22.0,satisfied +65816,9349,Male,Loyal Customer,44,Business travel,Business,441,4,4,4,4,2,4,5,4,4,4,4,3,4,5,23,57.0,satisfied +65817,118267,Female,Loyal Customer,60,Business travel,Business,3321,1,1,1,1,3,4,5,4,4,4,4,3,4,5,9,2.0,satisfied +65818,79088,Female,Loyal Customer,60,Personal Travel,Eco,226,2,4,2,3,4,5,5,5,5,2,2,4,5,3,0,0.0,neutral or dissatisfied +65819,92723,Male,Loyal Customer,33,Business travel,Business,1672,3,3,1,3,4,4,4,4,5,3,5,5,4,4,0,3.0,satisfied +65820,52141,Female,Loyal Customer,42,Business travel,Business,598,1,1,1,1,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +65821,81667,Male,disloyal Customer,38,Business travel,Business,907,2,2,2,2,4,2,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +65822,78736,Male,Loyal Customer,50,Business travel,Business,2034,2,2,2,2,5,4,5,5,5,5,5,3,5,3,9,19.0,satisfied +65823,54815,Male,Loyal Customer,41,Business travel,Business,2530,4,4,5,4,1,2,2,4,4,4,4,3,4,4,100,97.0,satisfied +65824,61003,Male,Loyal Customer,34,Business travel,Business,649,3,3,3,3,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +65825,48892,Female,Loyal Customer,55,Business travel,Eco,363,4,5,5,5,4,1,3,5,5,4,5,3,5,5,0,0.0,satisfied +65826,57868,Male,disloyal Customer,48,Business travel,Business,305,3,3,3,3,3,5,5,3,3,3,3,5,2,5,180,169.0,neutral or dissatisfied +65827,72886,Female,disloyal Customer,21,Business travel,Eco,1089,5,5,5,3,3,5,3,3,5,5,4,5,5,3,0,0.0,satisfied +65828,77984,Female,Loyal Customer,56,Business travel,Business,214,4,5,4,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +65829,81488,Female,disloyal Customer,25,Personal Travel,Eco,528,4,4,3,4,4,3,4,4,3,3,3,4,3,4,0,0.0,satisfied +65830,23509,Male,Loyal Customer,41,Business travel,Eco,303,5,3,3,3,5,5,5,5,4,3,3,5,5,5,0,0.0,satisfied +65831,109256,Male,Loyal Customer,62,Business travel,Eco Plus,612,2,5,5,5,2,2,2,2,3,3,3,2,2,2,174,177.0,neutral or dissatisfied +65832,83877,Male,Loyal Customer,45,Business travel,Business,1670,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,4.0,satisfied +65833,36987,Female,Loyal Customer,12,Business travel,Business,759,3,2,2,2,3,3,3,3,1,3,3,3,3,3,0,0.0,neutral or dissatisfied +65834,15421,Male,Loyal Customer,30,Business travel,Eco,399,0,0,0,5,3,0,3,3,2,4,1,5,1,3,0,0.0,satisfied +65835,40258,Female,disloyal Customer,25,Business travel,Eco,531,2,4,1,2,2,1,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +65836,53387,Male,Loyal Customer,22,Personal Travel,Eco,1452,3,1,3,3,2,3,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +65837,108072,Male,Loyal Customer,23,Business travel,Business,2656,4,4,4,4,3,3,3,3,3,2,5,5,5,3,93,82.0,satisfied +65838,12050,Female,Loyal Customer,69,Business travel,Business,376,2,5,5,5,2,3,4,2,2,2,2,4,2,3,4,0.0,neutral or dissatisfied +65839,51936,Male,Loyal Customer,45,Business travel,Eco,936,5,2,2,2,5,5,5,5,3,5,5,1,2,5,0,0.0,satisfied +65840,5150,Male,disloyal Customer,27,Business travel,Eco,622,2,0,2,4,4,2,4,4,5,3,1,3,3,4,28,42.0,neutral or dissatisfied +65841,24318,Male,Loyal Customer,44,Personal Travel,Business,1048,3,2,3,3,2,4,4,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +65842,90028,Female,Loyal Customer,51,Business travel,Business,1084,2,2,2,2,4,4,4,4,4,4,4,3,4,3,0,2.0,satisfied +65843,48319,Female,Loyal Customer,41,Business travel,Business,1203,5,5,5,5,5,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +65844,101475,Male,Loyal Customer,52,Business travel,Business,345,0,0,0,3,2,4,5,2,2,2,2,4,2,5,11,15.0,satisfied +65845,57653,Male,Loyal Customer,9,Personal Travel,Eco,200,2,4,2,4,4,2,4,4,4,2,5,5,5,4,9,0.0,neutral or dissatisfied +65846,91634,Male,Loyal Customer,57,Business travel,Eco,799,3,3,3,3,3,3,3,3,1,1,1,1,2,3,0,15.0,neutral or dissatisfied +65847,98525,Female,Loyal Customer,12,Personal Travel,Eco,402,5,5,4,4,2,4,2,2,4,4,4,3,4,2,0,0.0,satisfied +65848,91693,Female,Loyal Customer,52,Business travel,Business,590,2,2,2,2,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +65849,46844,Male,Loyal Customer,38,Business travel,Business,1812,4,4,4,4,2,5,1,4,4,4,4,3,4,2,1,0.0,satisfied +65850,50324,Female,Loyal Customer,46,Business travel,Business,109,0,4,0,4,1,5,5,3,3,3,3,1,3,2,0,0.0,satisfied +65851,4728,Female,Loyal Customer,43,Business travel,Business,888,3,3,3,3,5,5,4,2,2,2,2,4,2,5,5,3.0,satisfied +65852,106162,Male,Loyal Customer,60,Personal Travel,Eco,302,2,4,2,4,3,2,3,3,5,1,1,5,2,3,0,0.0,neutral or dissatisfied +65853,91121,Female,Loyal Customer,43,Personal Travel,Eco,581,1,5,1,2,3,4,4,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +65854,37695,Female,Loyal Customer,11,Personal Travel,Eco,828,2,5,3,4,3,3,3,3,3,3,5,3,5,3,0,0.0,neutral or dissatisfied +65855,120059,Female,Loyal Customer,45,Personal Travel,Eco,237,4,5,0,2,4,4,5,3,3,0,3,3,3,4,0,0.0,neutral or dissatisfied +65856,38509,Female,Loyal Customer,36,Business travel,Business,2446,1,1,4,1,4,5,1,3,3,3,3,4,3,5,0,0.0,satisfied +65857,114441,Male,disloyal Customer,37,Business travel,Business,446,4,4,4,5,1,4,1,1,3,3,4,5,5,1,0,2.0,neutral or dissatisfied +65858,110019,Male,Loyal Customer,46,Personal Travel,Eco,1204,4,4,5,4,4,5,4,4,1,4,4,2,3,4,53,33.0,neutral or dissatisfied +65859,56656,Female,disloyal Customer,37,Business travel,Eco,685,3,3,3,4,1,3,1,1,3,1,4,3,3,1,13,0.0,neutral or dissatisfied +65860,29375,Female,Loyal Customer,26,Business travel,Eco,2349,1,2,3,3,2,2,1,2,1,1,2,1,4,1,0,7.0,neutral or dissatisfied +65861,56743,Female,Loyal Customer,65,Personal Travel,Eco,1065,3,5,2,4,2,4,5,5,5,2,5,3,5,4,0,3.0,neutral or dissatisfied +65862,30108,Male,Loyal Customer,59,Personal Travel,Eco,539,1,2,1,3,2,1,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +65863,39157,Female,Loyal Customer,53,Business travel,Business,2787,1,1,1,1,4,1,5,4,4,4,4,5,4,1,0,8.0,satisfied +65864,71530,Female,Loyal Customer,53,Business travel,Business,1182,3,3,3,3,3,5,5,4,4,4,4,5,4,5,56,62.0,satisfied +65865,9579,Male,Loyal Customer,66,Business travel,Eco,228,4,2,2,2,3,4,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +65866,74713,Male,Loyal Customer,54,Personal Travel,Eco,1242,1,5,1,2,1,1,1,1,4,4,5,4,4,1,24,19.0,neutral or dissatisfied +65867,44880,Male,Loyal Customer,59,Personal Travel,Eco,240,2,5,0,2,3,0,4,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +65868,72195,Male,Loyal Customer,23,Personal Travel,Eco,594,2,3,2,3,4,2,5,4,3,4,5,2,3,4,0,0.0,neutral or dissatisfied +65869,93849,Female,Loyal Customer,63,Personal Travel,Eco,391,3,4,3,2,4,5,3,1,1,3,1,1,1,3,31,35.0,neutral or dissatisfied +65870,2845,Male,Loyal Customer,38,Business travel,Business,3227,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +65871,67521,Female,Loyal Customer,18,Business travel,Business,1753,1,2,2,2,1,1,1,1,3,4,3,3,3,1,32,32.0,neutral or dissatisfied +65872,72945,Male,Loyal Customer,31,Business travel,Business,1879,4,4,4,4,4,4,4,4,3,4,4,5,4,4,109,129.0,satisfied +65873,155,Female,disloyal Customer,17,Business travel,Business,227,4,3,4,3,5,4,5,5,1,2,4,4,4,5,0,11.0,neutral or dissatisfied +65874,28257,Female,disloyal Customer,29,Business travel,Eco,1542,2,2,2,4,3,2,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +65875,59152,Male,disloyal Customer,30,Business travel,Business,1101,4,3,3,4,1,3,2,1,3,2,4,3,4,1,8,0.0,satisfied +65876,16022,Female,Loyal Customer,63,Personal Travel,Eco,722,3,4,3,1,4,5,3,2,2,3,2,5,2,2,0,0.0,neutral or dissatisfied +65877,123664,Male,disloyal Customer,40,Business travel,Business,214,3,3,3,3,4,3,4,4,2,1,4,3,3,4,0,0.0,neutral or dissatisfied +65878,45132,Male,Loyal Customer,36,Business travel,Business,174,2,2,2,2,2,5,4,5,5,5,5,3,5,3,19,11.0,satisfied +65879,64876,Female,Loyal Customer,43,Business travel,Business,3843,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +65880,20136,Female,Loyal Customer,54,Business travel,Eco Plus,466,3,4,4,4,4,2,2,3,3,3,3,3,3,1,29,25.0,neutral or dissatisfied +65881,103472,Male,Loyal Customer,44,Business travel,Business,2118,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +65882,18918,Female,Loyal Customer,70,Personal Travel,Eco,448,2,2,2,2,2,2,3,1,1,2,1,1,1,4,0,1.0,neutral or dissatisfied +65883,81804,Male,Loyal Customer,47,Business travel,Business,1501,2,2,2,2,2,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +65884,54273,Male,Loyal Customer,28,Personal Travel,Eco,1222,3,5,3,3,1,3,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +65885,57127,Female,Loyal Customer,53,Personal Travel,Eco,1222,2,4,2,3,1,3,2,4,4,2,4,5,4,5,58,45.0,neutral or dissatisfied +65886,7867,Female,Loyal Customer,51,Business travel,Business,948,2,2,2,2,5,5,5,3,3,3,3,3,3,3,2,0.0,satisfied +65887,41667,Male,Loyal Customer,62,Business travel,Business,347,1,1,1,1,2,5,3,5,5,5,5,3,5,4,0,0.0,satisfied +65888,89923,Male,disloyal Customer,25,Business travel,Business,1101,5,0,5,4,4,5,4,4,4,1,3,1,1,4,0,0.0,satisfied +65889,78722,Female,Loyal Customer,46,Business travel,Business,1831,5,5,5,5,3,5,4,5,5,5,5,5,5,4,0,1.0,satisfied +65890,38031,Male,disloyal Customer,38,Business travel,Eco,1237,3,4,4,2,2,4,2,2,4,1,1,1,1,2,64,66.0,neutral or dissatisfied +65891,96348,Female,disloyal Customer,68,Business travel,Eco,1009,2,2,2,4,4,2,4,4,2,4,3,4,3,4,14,0.0,neutral or dissatisfied +65892,58435,Female,Loyal Customer,68,Personal Travel,Eco,723,3,3,2,5,5,2,3,3,3,2,3,2,3,3,107,115.0,neutral or dissatisfied +65893,115934,Female,Loyal Customer,77,Business travel,Business,2187,4,4,4,4,5,2,5,5,5,4,5,3,5,5,1,0.0,satisfied +65894,86349,Female,disloyal Customer,30,Business travel,Business,712,2,2,2,3,2,2,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +65895,2864,Female,Loyal Customer,56,Business travel,Eco,409,4,4,4,4,1,4,3,4,4,4,4,1,4,3,0,0.0,satisfied +65896,87662,Female,Loyal Customer,56,Business travel,Business,1533,3,3,3,3,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +65897,77777,Female,Loyal Customer,24,Personal Travel,Eco,874,3,0,4,4,3,4,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +65898,19336,Male,Loyal Customer,8,Personal Travel,Eco,694,3,4,2,2,2,1,1,4,3,5,5,1,5,1,181,158.0,neutral or dissatisfied +65899,1051,Male,disloyal Customer,16,Business travel,Eco,247,0,4,0,2,3,0,3,3,4,2,5,1,5,3,0,0.0,satisfied +65900,11924,Female,Loyal Customer,45,Personal Travel,Eco,744,5,4,5,1,1,1,5,4,4,5,4,4,4,5,0,0.0,satisfied +65901,77737,Female,Loyal Customer,60,Business travel,Business,689,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +65902,51689,Male,Loyal Customer,30,Business travel,Business,651,2,3,2,2,4,4,4,4,1,1,4,4,3,4,0,0.0,satisfied +65903,70958,Male,Loyal Customer,44,Business travel,Business,3479,3,3,3,3,4,4,5,5,5,5,5,3,5,3,30,6.0,satisfied +65904,28909,Male,Loyal Customer,29,Business travel,Business,3491,1,1,1,1,4,5,4,4,5,2,4,4,1,4,0,3.0,satisfied +65905,42927,Female,disloyal Customer,37,Business travel,Business,236,2,2,2,1,3,2,3,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +65906,117797,Male,Loyal Customer,44,Business travel,Business,2392,1,2,2,2,3,1,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +65907,113540,Male,disloyal Customer,22,Business travel,Eco,223,4,2,4,4,1,4,1,1,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +65908,7952,Female,Loyal Customer,55,Business travel,Business,594,1,1,3,1,2,4,5,5,5,5,5,4,5,4,0,4.0,satisfied +65909,39800,Female,disloyal Customer,22,Business travel,Eco,272,2,4,2,3,2,2,5,2,1,4,5,4,3,2,0,0.0,neutral or dissatisfied +65910,565,Male,Loyal Customer,62,Business travel,Business,3235,4,4,2,4,2,5,4,4,4,4,4,5,4,3,19,18.0,satisfied +65911,65756,Female,Loyal Customer,11,Personal Travel,Eco,936,3,5,3,3,2,3,2,2,4,5,5,3,4,2,6,0.0,neutral or dissatisfied +65912,62579,Female,disloyal Customer,24,Business travel,Eco,1157,2,2,2,3,3,2,3,3,3,1,2,2,3,3,10,0.0,neutral or dissatisfied +65913,887,Female,Loyal Customer,41,Business travel,Business,3080,2,2,2,2,5,4,4,4,4,3,2,3,4,1,0,6.0,neutral or dissatisfied +65914,76295,Male,Loyal Customer,44,Business travel,Business,2182,3,5,5,5,2,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +65915,23432,Male,Loyal Customer,37,Personal Travel,Business,576,3,5,3,1,2,4,4,5,5,3,1,5,5,4,45,44.0,neutral or dissatisfied +65916,16178,Female,Loyal Customer,37,Business travel,Business,212,0,3,0,2,3,4,2,1,1,1,1,5,1,2,0,0.0,satisfied +65917,96854,Male,Loyal Customer,42,Business travel,Business,2388,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +65918,1856,Male,disloyal Customer,37,Business travel,Business,931,4,4,4,2,2,4,2,2,4,3,5,4,5,2,0,0.0,satisfied +65919,17589,Female,Loyal Customer,58,Business travel,Eco Plus,1034,2,1,1,1,3,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +65920,120338,Female,disloyal Customer,22,Business travel,Eco,449,4,0,4,2,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +65921,94814,Male,Loyal Customer,37,Business travel,Business,2379,1,1,1,1,2,4,4,1,1,1,1,1,1,1,6,1.0,neutral or dissatisfied +65922,115312,Female,Loyal Customer,51,Business travel,Business,342,3,3,3,3,4,4,4,5,5,4,5,5,5,4,2,8.0,satisfied +65923,6081,Female,Loyal Customer,55,Business travel,Business,3768,3,3,4,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +65924,91670,Female,Loyal Customer,46,Personal Travel,Eco Plus,1312,1,5,1,3,5,5,4,3,3,1,3,3,3,3,11,4.0,neutral or dissatisfied +65925,60948,Female,disloyal Customer,30,Business travel,Business,888,0,0,0,2,3,0,3,3,5,3,4,5,5,3,0,2.0,satisfied +65926,113312,Male,Loyal Customer,45,Business travel,Business,397,2,1,1,1,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +65927,115639,Female,Loyal Customer,56,Business travel,Business,3567,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +65928,129774,Male,Loyal Customer,58,Personal Travel,Eco,447,3,5,3,5,2,3,2,2,5,3,5,4,4,2,9,0.0,neutral or dissatisfied +65929,112605,Female,disloyal Customer,13,Business travel,Eco,602,2,2,3,3,1,3,1,1,1,2,3,2,4,1,0,0.0,neutral or dissatisfied +65930,72486,Female,Loyal Customer,41,Business travel,Business,1121,2,2,2,2,4,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +65931,110993,Male,Loyal Customer,56,Business travel,Business,3107,4,4,4,4,2,4,4,5,5,5,5,3,5,4,23,10.0,satisfied +65932,81465,Female,Loyal Customer,23,Business travel,Business,528,3,2,2,2,3,3,3,3,3,4,3,1,4,3,9,5.0,neutral or dissatisfied +65933,82769,Female,Loyal Customer,36,Business travel,Business,1655,5,5,5,5,3,4,4,2,2,2,2,3,2,5,2,8.0,satisfied +65934,86595,Female,Loyal Customer,51,Business travel,Business,746,4,4,4,4,4,4,5,5,5,5,5,4,5,5,0,5.0,satisfied +65935,34401,Female,Loyal Customer,44,Business travel,Eco,212,2,2,2,2,5,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +65936,64479,Female,Loyal Customer,44,Business travel,Business,2919,2,2,2,2,4,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +65937,35319,Male,Loyal Customer,53,Business travel,Eco,1076,3,5,5,5,3,3,3,3,1,5,3,3,3,3,0,0.0,neutral or dissatisfied +65938,29080,Male,Loyal Customer,33,Personal Travel,Eco,978,1,5,1,1,1,1,4,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +65939,4382,Male,Loyal Customer,17,Personal Travel,Eco,607,5,4,4,5,2,4,2,2,3,5,4,3,4,2,0,0.0,satisfied +65940,94480,Female,Loyal Customer,47,Business travel,Business,677,1,1,1,1,2,4,5,5,5,5,5,3,5,4,10,0.0,satisfied +65941,102923,Female,Loyal Customer,43,Business travel,Business,1912,1,1,1,1,3,5,5,4,4,4,4,3,4,3,4,0.0,satisfied +65942,24432,Male,Loyal Customer,15,Personal Travel,Eco,634,3,4,3,4,5,3,5,5,3,1,3,4,3,5,0,18.0,neutral or dissatisfied +65943,85587,Female,Loyal Customer,60,Business travel,Business,3464,5,5,2,5,4,4,4,4,4,4,4,4,4,4,3,0.0,satisfied +65944,41594,Male,Loyal Customer,23,Personal Travel,Eco,1482,1,1,0,3,4,0,4,4,1,2,2,3,3,4,46,59.0,neutral or dissatisfied +65945,89093,Female,Loyal Customer,29,Business travel,Business,1947,4,4,4,4,5,5,5,5,5,4,5,3,5,5,4,0.0,satisfied +65946,72644,Male,Loyal Customer,46,Personal Travel,Eco,918,2,4,2,5,1,2,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +65947,106076,Female,Loyal Customer,33,Business travel,Business,2270,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +65948,36900,Male,disloyal Customer,27,Business travel,Eco,2072,3,3,3,3,5,3,5,5,3,4,3,2,2,5,0,0.0,neutral or dissatisfied +65949,116938,Female,Loyal Customer,57,Business travel,Business,325,0,0,0,4,3,4,5,3,3,2,2,5,3,5,11,16.0,satisfied +65950,76132,Male,Loyal Customer,59,Business travel,Business,546,5,5,5,5,3,4,4,4,4,5,4,3,4,5,0,1.0,satisfied +65951,125273,Male,Loyal Customer,64,Personal Travel,Eco,1488,3,2,3,1,2,3,2,2,2,5,1,1,2,2,0,5.0,neutral or dissatisfied +65952,118747,Female,Loyal Customer,58,Personal Travel,Eco,621,2,4,2,4,5,5,5,5,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +65953,80304,Female,Loyal Customer,23,Business travel,Eco,746,1,5,5,5,1,1,2,1,4,3,3,3,3,1,13,0.0,neutral or dissatisfied +65954,49118,Female,Loyal Customer,45,Business travel,Business,373,1,1,1,1,1,5,1,4,4,5,4,2,4,5,80,68.0,satisfied +65955,30163,Male,Loyal Customer,56,Personal Travel,Eco,253,4,2,0,3,5,0,5,5,4,5,3,3,4,5,0,0.0,neutral or dissatisfied +65956,12920,Female,disloyal Customer,25,Business travel,Eco,563,3,0,3,3,1,3,1,1,3,1,2,5,2,1,0,0.0,neutral or dissatisfied +65957,102805,Male,Loyal Customer,52,Business travel,Business,2466,0,0,0,1,5,4,5,5,5,5,5,4,5,5,5,0.0,satisfied +65958,39465,Female,Loyal Customer,51,Business travel,Eco Plus,129,5,3,3,3,2,5,3,5,5,5,5,1,5,3,0,0.0,satisfied +65959,49682,Male,Loyal Customer,55,Business travel,Business,266,0,0,0,3,1,2,2,1,1,1,5,4,1,3,0,0.0,satisfied +65960,121083,Female,Loyal Customer,70,Personal Travel,Eco Plus,1013,1,1,2,4,4,4,4,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +65961,73355,Female,Loyal Customer,47,Business travel,Eco,1182,2,4,5,5,1,3,3,2,2,2,2,2,2,4,0,6.0,neutral or dissatisfied +65962,124810,Female,disloyal Customer,27,Business travel,Eco,280,2,4,2,4,4,2,4,4,2,2,4,4,4,4,0,38.0,neutral or dissatisfied +65963,56474,Female,Loyal Customer,54,Personal Travel,Business,4963,2,2,2,3,2,5,5,4,1,3,3,5,2,5,2,5.0,neutral or dissatisfied +65964,98885,Female,Loyal Customer,8,Personal Travel,Eco,991,3,4,3,4,2,3,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +65965,33401,Female,Loyal Customer,56,Business travel,Business,2556,3,3,3,3,4,4,4,4,4,4,4,5,4,5,6,0.0,satisfied +65966,36876,Male,Loyal Customer,40,Business travel,Eco,1182,3,5,5,5,3,4,3,3,5,3,5,5,1,3,11,5.0,satisfied +65967,138,Male,Loyal Customer,45,Business travel,Business,2374,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +65968,32162,Male,Loyal Customer,64,Business travel,Business,2308,2,2,2,2,5,3,5,4,4,4,5,3,4,3,0,4.0,satisfied +65969,53511,Female,Loyal Customer,14,Personal Travel,Eco,2253,3,5,3,1,3,4,1,4,5,5,4,1,3,1,20,34.0,neutral or dissatisfied +65970,12601,Female,Loyal Customer,20,Personal Travel,Eco,542,2,5,3,4,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +65971,89126,Female,Loyal Customer,37,Business travel,Business,1892,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +65972,117497,Female,disloyal Customer,27,Business travel,Eco,507,1,0,0,5,5,0,5,5,3,1,4,3,3,5,36,28.0,neutral or dissatisfied +65973,127132,Male,Loyal Customer,65,Personal Travel,Eco,651,3,5,3,2,3,3,3,3,4,2,4,3,4,3,0,1.0,neutral or dissatisfied +65974,7413,Female,Loyal Customer,44,Business travel,Business,3686,2,2,2,2,5,5,5,5,5,5,5,4,5,5,63,55.0,satisfied +65975,2075,Female,disloyal Customer,35,Business travel,Eco,785,2,2,2,4,1,2,1,1,1,1,4,4,4,1,6,4.0,neutral or dissatisfied +65976,65880,Male,Loyal Customer,60,Business travel,Business,1389,1,1,1,1,4,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +65977,76255,Male,Loyal Customer,41,Business travel,Business,1399,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +65978,67293,Male,Loyal Customer,53,Business travel,Business,2700,3,3,2,3,3,4,5,4,4,4,4,5,4,4,44,35.0,satisfied +65979,4361,Female,disloyal Customer,25,Business travel,Business,528,5,0,5,5,1,5,1,1,5,2,4,4,4,1,0,0.0,satisfied +65980,109614,Female,disloyal Customer,29,Business travel,Business,930,3,3,3,1,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +65981,70155,Male,Loyal Customer,8,Personal Travel,Eco,460,2,5,2,5,2,2,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +65982,102570,Male,Loyal Customer,53,Business travel,Business,1666,3,3,3,3,2,4,5,4,4,4,4,5,4,4,22,34.0,satisfied +65983,22554,Male,Loyal Customer,44,Business travel,Business,223,3,3,4,3,4,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +65984,23243,Female,Loyal Customer,50,Business travel,Business,1579,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +65985,86289,Female,Loyal Customer,34,Personal Travel,Eco,356,1,4,1,2,2,1,2,2,4,5,5,5,5,2,7,9.0,neutral or dissatisfied +65986,63124,Male,Loyal Customer,43,Business travel,Business,1553,1,1,1,1,4,5,4,3,3,3,3,5,3,4,24,12.0,satisfied +65987,39425,Female,Loyal Customer,43,Business travel,Eco,129,5,1,1,1,5,2,1,4,4,5,4,4,4,5,14,12.0,satisfied +65988,99452,Female,Loyal Customer,36,Business travel,Business,283,1,1,1,1,3,5,4,5,5,5,5,3,5,3,17,20.0,satisfied +65989,105531,Female,Loyal Customer,53,Business travel,Business,3306,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +65990,2298,Female,Loyal Customer,27,Business travel,Business,691,3,4,2,4,3,3,3,3,3,4,4,2,4,3,6,8.0,neutral or dissatisfied +65991,85968,Male,Loyal Customer,43,Business travel,Business,3562,2,2,4,2,3,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +65992,56455,Male,Loyal Customer,34,Personal Travel,Eco,719,2,4,2,3,3,2,2,3,5,4,1,3,5,3,3,23.0,neutral or dissatisfied +65993,34880,Male,Loyal Customer,39,Personal Travel,Eco,2248,2,5,2,1,4,2,4,4,5,1,3,4,4,4,19,59.0,neutral or dissatisfied +65994,55185,Female,Loyal Customer,11,Business travel,Eco Plus,1635,2,2,2,2,2,2,2,2,3,4,2,3,4,2,22,10.0,neutral or dissatisfied +65995,12365,Female,Loyal Customer,63,Business travel,Eco,305,3,4,4,4,3,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +65996,120909,Male,disloyal Customer,27,Business travel,Business,920,3,3,3,4,2,3,2,2,5,4,4,3,5,2,13,0.0,neutral or dissatisfied +65997,117905,Female,Loyal Customer,55,Business travel,Business,255,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +65998,32569,Female,Loyal Customer,38,Business travel,Eco,163,4,1,1,1,4,4,4,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +65999,100122,Female,Loyal Customer,45,Business travel,Business,2493,4,4,4,4,3,5,5,4,4,4,4,3,4,5,0,10.0,satisfied +66000,62586,Female,Loyal Customer,30,Business travel,Business,1726,1,1,1,1,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +66001,50633,Female,Loyal Customer,49,Personal Travel,Eco,109,3,5,3,1,3,4,5,4,4,3,4,4,4,4,21,8.0,neutral or dissatisfied +66002,11189,Male,Loyal Customer,50,Personal Travel,Eco,316,3,3,3,1,4,3,4,4,5,2,2,3,1,4,0,3.0,neutral or dissatisfied +66003,45990,Female,Loyal Customer,31,Business travel,Eco,483,2,2,2,2,2,2,2,2,4,3,4,1,4,2,13,3.0,neutral or dissatisfied +66004,22709,Female,Loyal Customer,42,Personal Travel,Eco,579,2,3,2,3,3,5,1,1,1,2,1,5,1,5,32,27.0,neutral or dissatisfied +66005,40089,Male,Loyal Customer,45,Business travel,Eco,200,4,4,4,4,4,4,4,4,5,3,1,1,1,4,6,6.0,satisfied +66006,72755,Male,Loyal Customer,23,Personal Travel,Eco,806,1,4,1,4,2,1,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +66007,31230,Female,disloyal Customer,45,Business travel,Business,472,4,3,3,4,3,4,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +66008,34673,Male,Loyal Customer,47,Business travel,Eco,209,5,3,3,3,5,5,5,5,2,2,3,1,1,5,25,20.0,satisfied +66009,55780,Male,Loyal Customer,36,Personal Travel,Eco,646,2,1,2,2,2,2,4,2,4,4,2,4,1,2,0,0.0,neutral or dissatisfied +66010,96646,Female,Loyal Customer,53,Business travel,Business,1975,5,5,5,5,3,2,5,5,5,5,5,3,5,1,0,0.0,satisfied +66011,34094,Female,Loyal Customer,50,Business travel,Business,1046,2,2,2,2,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +66012,106516,Male,Loyal Customer,44,Business travel,Business,3283,2,2,2,2,3,4,5,4,4,4,4,5,4,4,27,18.0,satisfied +66013,58986,Female,Loyal Customer,46,Business travel,Business,1744,3,3,5,3,3,3,5,5,5,5,5,4,5,5,46,42.0,satisfied +66014,81916,Male,disloyal Customer,25,Business travel,Eco,949,2,2,2,1,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +66015,114085,Female,disloyal Customer,47,Business travel,Eco,392,1,4,1,4,1,2,2,1,2,4,3,2,3,2,142,116.0,neutral or dissatisfied +66016,47233,Male,Loyal Customer,45,Business travel,Eco Plus,954,2,2,3,3,2,2,2,2,1,5,2,3,1,2,0,0.0,satisfied +66017,32417,Male,Loyal Customer,37,Business travel,Eco,216,4,5,5,5,4,4,4,4,4,1,3,5,5,4,0,1.0,satisfied +66018,61840,Female,disloyal Customer,25,Business travel,Eco Plus,1635,3,3,3,4,4,3,4,4,1,4,4,2,3,4,36,15.0,neutral or dissatisfied +66019,69258,Male,Loyal Customer,19,Business travel,Business,1903,1,4,4,4,1,1,1,1,3,2,3,4,2,1,0,0.0,neutral or dissatisfied +66020,42992,Male,Loyal Customer,33,Business travel,Business,259,4,4,4,4,3,4,3,3,1,4,4,1,2,3,21,21.0,satisfied +66021,31975,Female,disloyal Customer,27,Business travel,Business,101,4,4,4,2,4,4,4,4,3,5,4,3,5,4,0,0.0,satisfied +66022,85185,Male,Loyal Customer,59,Business travel,Business,2874,1,1,1,1,2,4,4,4,4,4,4,5,4,5,2,5.0,satisfied +66023,57259,Female,Loyal Customer,41,Business travel,Business,1960,4,4,2,4,4,4,5,4,4,4,4,5,4,4,1,13.0,satisfied +66024,30497,Male,Loyal Customer,48,Personal Travel,Eco,627,2,5,2,4,4,2,4,4,5,2,4,5,5,4,0,1.0,neutral or dissatisfied +66025,31073,Female,Loyal Customer,44,Personal Travel,Eco,641,1,5,2,2,2,5,5,3,3,2,3,3,3,4,55,56.0,neutral or dissatisfied +66026,66809,Male,Loyal Customer,51,Business travel,Business,731,2,2,2,2,5,5,5,4,4,3,4,3,4,3,12,15.0,satisfied +66027,126032,Male,disloyal Customer,27,Business travel,Business,650,2,2,2,1,3,2,5,3,3,2,4,4,4,3,38,38.0,neutral or dissatisfied +66028,85250,Female,Loyal Customer,34,Personal Travel,Eco,689,4,4,4,5,3,4,1,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +66029,33696,Female,disloyal Customer,25,Business travel,Eco,899,2,2,2,3,4,2,4,4,2,1,1,2,1,4,5,7.0,neutral or dissatisfied +66030,76615,Male,Loyal Customer,50,Business travel,Eco,534,4,3,3,3,4,4,4,4,3,1,1,1,1,4,5,7.0,neutral or dissatisfied +66031,95600,Female,disloyal Customer,37,Business travel,Eco,484,1,1,1,4,3,1,4,3,1,3,3,1,3,3,36,24.0,neutral or dissatisfied +66032,51199,Male,Loyal Customer,54,Business travel,Eco Plus,86,4,3,3,3,4,4,4,4,3,1,3,4,4,4,13,20.0,satisfied +66033,119638,Female,Loyal Customer,54,Business travel,Business,1727,4,4,4,4,4,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +66034,49485,Male,Loyal Customer,61,Business travel,Business,3037,1,1,1,1,1,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +66035,102980,Female,Loyal Customer,41,Business travel,Business,2597,2,2,1,2,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +66036,14309,Male,Loyal Customer,51,Business travel,Business,1718,2,2,2,2,2,4,4,2,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +66037,106843,Male,disloyal Customer,42,Business travel,Business,233,3,3,3,3,2,3,2,2,3,1,3,3,3,2,2,0.0,neutral or dissatisfied +66038,69713,Female,Loyal Customer,44,Business travel,Eco,1372,2,5,3,3,1,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +66039,46453,Male,Loyal Customer,57,Business travel,Business,3176,3,3,4,3,3,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +66040,73907,Male,Loyal Customer,44,Business travel,Eco,2218,4,4,4,4,4,4,4,4,2,5,2,1,3,4,0,0.0,neutral or dissatisfied +66041,12471,Male,Loyal Customer,16,Personal Travel,Eco,201,3,1,3,3,3,3,4,3,4,1,2,2,3,3,0,0.0,neutral or dissatisfied +66042,92061,Female,Loyal Customer,58,Business travel,Business,1535,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +66043,83972,Male,disloyal Customer,25,Business travel,Business,373,3,5,3,3,5,3,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +66044,71014,Female,Loyal Customer,60,Business travel,Business,2333,4,1,4,4,3,5,5,5,5,5,5,5,5,3,16,25.0,satisfied +66045,25622,Female,Loyal Customer,35,Business travel,Eco,526,4,1,1,1,4,3,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +66046,87177,Male,Loyal Customer,54,Business travel,Eco,946,3,3,3,3,3,3,3,3,4,4,3,1,3,3,7,13.0,neutral or dissatisfied +66047,111595,Male,Loyal Customer,24,Business travel,Business,3835,1,1,1,1,4,4,4,4,3,4,5,5,4,4,38,45.0,satisfied +66048,66632,Female,Loyal Customer,44,Personal Travel,Business,802,3,2,3,3,3,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +66049,46390,Female,Loyal Customer,30,Personal Travel,Eco,1081,4,1,4,3,2,4,2,2,2,3,4,1,3,2,7,5.0,neutral or dissatisfied +66050,66274,Female,Loyal Customer,23,Business travel,Business,2743,1,1,1,1,5,5,5,5,4,3,4,4,4,5,8,14.0,satisfied +66051,10649,Female,disloyal Customer,32,Business travel,Eco,201,4,4,5,4,3,5,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +66052,14860,Male,Loyal Customer,43,Business travel,Business,2146,0,0,0,3,1,5,5,3,3,3,3,2,3,3,0,0.0,satisfied +66053,93824,Male,Loyal Customer,47,Business travel,Eco,391,1,1,1,1,1,1,1,1,2,1,2,4,2,1,21,17.0,neutral or dissatisfied +66054,26159,Male,Loyal Customer,34,Business travel,Business,515,3,3,3,3,1,1,5,4,4,4,4,2,4,5,4,0.0,satisfied +66055,97042,Male,Loyal Customer,45,Business travel,Business,1768,3,3,3,3,2,3,4,3,3,3,3,4,3,2,118,116.0,neutral or dissatisfied +66056,81798,Male,disloyal Customer,41,Business travel,Eco,1310,2,2,2,2,2,2,2,2,1,4,3,3,2,2,47,35.0,neutral or dissatisfied +66057,58809,Female,Loyal Customer,19,Personal Travel,Eco,1005,1,4,1,5,5,1,5,5,5,2,4,4,4,5,35,20.0,neutral or dissatisfied +66058,47325,Male,Loyal Customer,29,Business travel,Business,1960,5,3,3,3,5,4,5,5,2,5,4,4,4,5,0,0.0,neutral or dissatisfied +66059,47161,Female,disloyal Customer,39,Business travel,Business,965,2,2,2,1,3,2,3,3,1,5,4,3,4,3,0,0.0,neutral or dissatisfied +66060,80402,Female,Loyal Customer,48,Business travel,Business,1416,4,4,4,4,1,3,4,4,4,4,4,2,4,1,2,0.0,neutral or dissatisfied +66061,58879,Male,Loyal Customer,43,Business travel,Business,2585,3,3,1,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +66062,35359,Female,Loyal Customer,51,Business travel,Business,1076,3,3,3,3,2,2,3,4,4,4,4,4,4,4,9,0.0,satisfied +66063,44265,Male,Loyal Customer,17,Personal Travel,Eco,359,3,2,3,4,3,3,4,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +66064,9181,Female,Loyal Customer,10,Personal Travel,Eco Plus,416,1,3,1,4,2,1,3,2,5,3,5,2,1,2,26,18.0,neutral or dissatisfied +66065,7811,Female,disloyal Customer,38,Business travel,Business,650,4,4,4,2,4,4,4,4,4,2,4,3,5,4,0,12.0,satisfied +66066,110757,Male,disloyal Customer,47,Business travel,Business,990,4,4,4,4,4,4,4,4,3,3,4,5,5,4,9,13.0,neutral or dissatisfied +66067,49517,Male,Loyal Customer,41,Business travel,Business,2047,3,3,3,3,5,5,5,5,5,5,5,2,5,3,0,0.0,satisfied +66068,50910,Male,Loyal Customer,26,Personal Travel,Eco,421,3,4,3,2,1,3,1,1,5,2,1,4,2,1,23,34.0,neutral or dissatisfied +66069,106789,Female,Loyal Customer,37,Business travel,Business,977,3,2,2,2,3,3,2,3,3,2,3,1,3,3,20,18.0,neutral or dissatisfied +66070,28310,Female,Loyal Customer,35,Business travel,Eco,867,5,2,2,2,5,5,5,5,3,1,5,5,2,5,0,0.0,satisfied +66071,89018,Female,Loyal Customer,44,Business travel,Business,2139,4,4,4,4,2,2,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +66072,72726,Female,Loyal Customer,61,Business travel,Eco Plus,719,1,4,4,4,5,4,3,1,1,1,1,4,1,4,9,6.0,neutral or dissatisfied +66073,109954,Female,Loyal Customer,42,Personal Travel,Eco,1204,3,5,3,2,5,1,4,5,5,3,5,3,5,5,12,2.0,neutral or dissatisfied +66074,44853,Female,Loyal Customer,30,Personal Travel,Eco,413,3,4,3,4,3,3,3,3,4,2,5,5,4,3,17,16.0,neutral or dissatisfied +66075,7762,Female,Loyal Customer,44,Business travel,Business,2308,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,9.0,satisfied +66076,21681,Female,Loyal Customer,50,Business travel,Business,708,3,2,2,2,2,3,2,3,3,3,3,2,3,4,42,34.0,neutral or dissatisfied +66077,116737,Female,Loyal Customer,10,Personal Travel,Eco Plus,373,2,5,2,4,1,2,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +66078,27293,Female,Loyal Customer,40,Business travel,Eco,978,5,2,2,2,5,5,5,5,3,1,3,4,1,5,11,16.0,satisfied +66079,57779,Female,Loyal Customer,68,Personal Travel,Eco,2704,3,4,4,4,4,2,3,2,2,4,3,3,3,3,0,7.0,neutral or dissatisfied +66080,126213,Female,Loyal Customer,30,Business travel,Business,1509,3,2,2,2,3,3,3,3,4,2,3,4,4,3,25,27.0,neutral or dissatisfied +66081,72824,Male,Loyal Customer,60,Business travel,Business,2609,3,3,3,3,4,4,5,4,4,4,4,3,4,4,3,0.0,satisfied +66082,109174,Male,Loyal Customer,50,Business travel,Business,616,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +66083,64268,Male,Loyal Customer,23,Business travel,Business,1192,2,3,2,2,4,4,4,4,5,4,4,5,5,4,1,0.0,satisfied +66084,50654,Female,Loyal Customer,18,Personal Travel,Eco,262,2,3,2,4,2,2,2,2,5,5,5,3,3,2,0,3.0,neutral or dissatisfied +66085,25971,Female,Loyal Customer,16,Personal Travel,Eco,946,2,3,2,1,2,2,2,2,5,2,3,1,1,2,0,0.0,neutral or dissatisfied +66086,69127,Male,Loyal Customer,69,Personal Travel,Eco,1598,3,4,3,1,4,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +66087,41310,Female,Loyal Customer,38,Business travel,Business,802,4,4,4,4,1,5,2,5,5,5,5,4,5,3,0,0.0,satisfied +66088,107541,Male,Loyal Customer,46,Business travel,Business,1521,4,4,4,4,2,4,4,4,4,4,4,4,4,3,16,0.0,satisfied +66089,16514,Male,Loyal Customer,64,Business travel,Eco Plus,143,4,2,2,2,4,4,4,4,3,3,4,2,5,4,0,0.0,satisfied +66090,18814,Female,Loyal Customer,51,Business travel,Business,3003,4,4,4,4,3,3,4,3,3,3,3,3,3,1,0,0.0,satisfied +66091,99858,Female,Loyal Customer,41,Personal Travel,Eco,587,4,4,4,3,2,4,2,2,4,4,4,2,3,2,8,0.0,neutral or dissatisfied +66092,67092,Male,Loyal Customer,55,Business travel,Business,1121,4,4,4,4,3,4,4,4,4,4,4,5,4,5,2,0.0,satisfied +66093,30120,Male,Loyal Customer,38,Personal Travel,Eco,183,3,1,3,3,1,3,1,1,4,5,4,4,3,1,0,0.0,neutral or dissatisfied +66094,116088,Male,Loyal Customer,15,Personal Travel,Eco,447,2,4,2,2,1,2,1,1,4,4,5,4,4,1,52,38.0,neutral or dissatisfied +66095,28110,Female,Loyal Customer,28,Business travel,Business,1643,5,5,5,5,3,4,3,3,4,1,1,4,3,3,0,0.0,satisfied +66096,102336,Male,disloyal Customer,33,Business travel,Eco,197,3,1,3,3,5,3,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +66097,48343,Male,disloyal Customer,25,Business travel,Eco,522,2,0,3,2,2,3,2,2,4,5,3,3,2,2,17,17.0,neutral or dissatisfied +66098,85707,Female,Loyal Customer,42,Personal Travel,Eco,1547,4,5,4,3,4,5,5,1,1,4,1,3,1,3,0,0.0,satisfied +66099,46240,Female,disloyal Customer,27,Business travel,Eco,455,1,3,1,3,5,1,5,5,4,3,3,2,4,5,7,1.0,neutral or dissatisfied +66100,45613,Male,disloyal Customer,36,Business travel,Eco,406,1,2,1,3,2,1,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +66101,121099,Male,Loyal Customer,48,Business travel,Business,1558,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,3.0,satisfied +66102,44591,Male,Loyal Customer,47,Personal Travel,Eco,177,2,5,2,3,4,2,5,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +66103,64655,Male,Loyal Customer,50,Business travel,Business,247,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +66104,99138,Male,Loyal Customer,10,Personal Travel,Eco,237,2,5,2,2,1,2,1,1,4,2,4,4,5,1,34,25.0,neutral or dissatisfied +66105,96776,Male,disloyal Customer,48,Business travel,Business,928,2,2,2,1,1,2,1,1,4,4,5,5,5,1,46,31.0,neutral or dissatisfied +66106,30262,Female,Loyal Customer,30,Business travel,Business,1024,2,2,2,2,4,4,4,4,1,2,3,5,5,4,0,1.0,satisfied +66107,25358,Male,Loyal Customer,31,Business travel,Eco,591,0,0,0,3,4,0,4,4,3,1,2,4,5,4,3,0.0,satisfied +66108,3306,Female,disloyal Customer,38,Business travel,Business,240,2,2,2,3,3,2,3,3,5,4,5,4,5,3,11,20.0,neutral or dissatisfied +66109,14483,Female,Loyal Customer,35,Business travel,Eco,541,5,1,1,1,5,5,5,5,4,5,2,2,3,5,0,3.0,satisfied +66110,39470,Male,Loyal Customer,35,Business travel,Business,867,5,5,3,5,3,3,3,2,2,3,3,3,1,3,610,593.0,satisfied +66111,89901,Male,Loyal Customer,44,Business travel,Eco,1306,2,1,1,1,2,2,2,2,3,5,1,1,2,2,7,1.0,neutral or dissatisfied +66112,55265,Male,Loyal Customer,52,Business travel,Business,2007,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,15.0,satisfied +66113,93158,Male,disloyal Customer,37,Business travel,Eco,666,1,1,1,4,4,1,4,4,3,4,4,4,3,4,16,9.0,neutral or dissatisfied +66114,15344,Male,Loyal Customer,46,Business travel,Business,164,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,11.0,satisfied +66115,64032,Male,Loyal Customer,48,Business travel,Business,919,1,5,2,5,1,4,4,1,1,2,1,4,1,4,0,8.0,neutral or dissatisfied +66116,83708,Female,Loyal Customer,42,Personal Travel,Eco,577,3,4,3,3,3,4,5,2,2,3,4,5,2,5,0,0.0,neutral or dissatisfied +66117,2728,Male,Loyal Customer,25,Business travel,Business,3616,5,5,5,5,2,2,2,2,3,4,4,4,5,2,0,0.0,satisfied +66118,55785,Female,Loyal Customer,48,Business travel,Business,2400,4,4,4,4,3,5,5,4,4,4,4,3,4,5,5,0.0,satisfied +66119,86983,Male,Loyal Customer,18,Business travel,Eco,907,2,1,1,1,2,2,2,2,4,1,4,4,4,2,0,7.0,neutral or dissatisfied +66120,120803,Female,Loyal Customer,55,Business travel,Business,1708,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +66121,91178,Female,Loyal Customer,24,Personal Travel,Eco,594,3,4,3,2,5,3,2,5,4,3,5,5,1,5,0,0.0,neutral or dissatisfied +66122,38447,Female,Loyal Customer,43,Business travel,Business,1226,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,2.0,satisfied +66123,4409,Female,Loyal Customer,44,Business travel,Business,762,4,4,2,4,3,4,5,4,4,4,4,4,4,5,0,3.0,satisfied +66124,40571,Male,Loyal Customer,56,Business travel,Eco,216,5,5,2,5,5,5,5,5,3,3,2,1,4,5,0,0.0,satisfied +66125,28397,Female,Loyal Customer,48,Business travel,Eco,1709,4,4,4,4,4,3,2,3,3,4,3,3,3,1,112,118.0,satisfied +66126,76366,Male,Loyal Customer,33,Business travel,Business,931,4,4,4,4,3,3,3,3,4,5,4,4,5,3,0,0.0,satisfied +66127,72761,Male,Loyal Customer,24,Business travel,Business,3645,1,4,1,1,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +66128,22252,Male,Loyal Customer,43,Business travel,Business,3290,5,5,5,5,5,4,4,4,4,4,5,5,4,2,0,0.0,satisfied +66129,27134,Female,Loyal Customer,27,Business travel,Business,2640,4,4,4,4,4,4,4,3,3,5,2,4,3,4,0,0.0,satisfied +66130,129298,Female,Loyal Customer,52,Business travel,Business,550,5,5,5,5,3,5,5,3,3,4,3,4,3,4,0,4.0,satisfied +66131,75023,Male,Loyal Customer,23,Business travel,Business,236,2,2,2,2,2,2,2,2,1,3,3,1,4,2,7,0.0,neutral or dissatisfied +66132,31058,Male,Loyal Customer,22,Business travel,Eco,641,5,4,4,4,5,5,3,5,4,1,4,1,3,5,0,0.0,satisfied +66133,8499,Male,Loyal Customer,49,Business travel,Business,1696,4,4,4,4,4,5,4,4,4,4,4,4,4,5,28,14.0,satisfied +66134,77263,Female,Loyal Customer,52,Business travel,Business,1590,2,2,3,2,4,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +66135,118400,Male,disloyal Customer,50,Business travel,Business,451,2,1,1,5,1,2,1,1,5,3,4,4,4,1,3,0.0,satisfied +66136,102151,Male,disloyal Customer,25,Business travel,Business,226,4,4,4,1,1,4,1,1,5,5,4,3,4,1,2,0.0,satisfied +66137,89007,Female,Loyal Customer,33,Business travel,Business,1892,2,2,2,2,5,4,5,5,5,5,5,4,5,4,7,0.0,satisfied +66138,17939,Female,Loyal Customer,30,Business travel,Business,3354,4,4,4,4,4,5,4,4,3,5,5,5,1,4,0,0.0,satisfied +66139,86656,Male,Loyal Customer,60,Personal Travel,Eco,746,3,4,3,4,5,3,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +66140,26086,Male,Loyal Customer,30,Business travel,Business,3565,1,2,5,2,1,1,1,1,4,2,3,3,3,1,0,0.0,neutral or dissatisfied +66141,65499,Female,disloyal Customer,26,Business travel,Business,1067,5,5,5,3,4,5,4,4,3,2,5,3,5,4,0,0.0,satisfied +66142,99264,Female,disloyal Customer,37,Business travel,Business,935,3,3,3,2,2,3,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +66143,23732,Female,Loyal Customer,52,Business travel,Business,771,1,1,4,1,4,1,4,5,5,4,5,5,5,1,0,0.0,satisfied +66144,69169,Male,Loyal Customer,39,Business travel,Business,2990,1,1,1,1,2,5,4,4,4,4,5,4,4,3,7,10.0,satisfied +66145,43666,Male,Loyal Customer,49,Business travel,Eco,700,4,3,3,3,4,4,4,4,3,4,2,2,5,4,3,9.0,satisfied +66146,127963,Female,Loyal Customer,61,Personal Travel,Eco,1999,3,4,3,2,4,4,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +66147,92159,Male,Loyal Customer,37,Personal Travel,Eco Plus,1454,2,5,2,4,4,2,4,4,5,3,3,5,5,4,0,1.0,neutral or dissatisfied +66148,18792,Male,Loyal Customer,56,Business travel,Business,448,5,5,5,5,3,2,2,4,4,4,4,1,4,2,0,0.0,satisfied +66149,71247,Male,Loyal Customer,26,Business travel,Business,733,5,5,5,5,3,3,3,3,4,4,4,5,5,3,0,0.0,satisfied +66150,25047,Male,Loyal Customer,21,Business travel,Business,3545,4,3,4,4,5,5,5,5,3,1,2,4,2,5,14,84.0,satisfied +66151,5447,Male,disloyal Customer,62,Business travel,Business,265,2,2,2,3,2,3,3,3,1,3,2,3,3,3,127,195.0,neutral or dissatisfied +66152,13373,Male,Loyal Customer,58,Personal Travel,Eco,748,2,4,2,5,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +66153,13338,Male,Loyal Customer,36,Business travel,Eco,748,4,5,5,5,4,4,4,4,1,3,3,3,3,4,0,0.0,satisfied +66154,14013,Female,Loyal Customer,45,Business travel,Eco,182,4,5,5,5,5,1,5,4,4,4,4,2,4,3,0,0.0,satisfied +66155,34659,Male,Loyal Customer,44,Business travel,Business,2560,3,4,3,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +66156,116772,Female,Loyal Customer,42,Personal Travel,Eco Plus,342,2,5,2,2,2,5,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +66157,35531,Male,Loyal Customer,57,Personal Travel,Eco,972,2,4,2,2,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +66158,27912,Male,Loyal Customer,38,Business travel,Eco Plus,2311,4,3,4,3,4,4,4,2,1,3,5,4,2,4,0,4.0,satisfied +66159,10803,Male,Loyal Customer,18,Business travel,Business,316,1,4,4,4,1,1,1,1,1,5,4,4,3,1,0,3.0,neutral or dissatisfied +66160,70453,Male,Loyal Customer,45,Business travel,Business,187,0,4,0,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +66161,20700,Female,Loyal Customer,25,Business travel,Business,510,3,4,4,4,3,3,3,3,4,3,3,3,2,3,0,0.0,neutral or dissatisfied +66162,83354,Female,Loyal Customer,57,Business travel,Business,1124,2,1,2,2,5,4,4,5,5,5,5,5,5,5,0,1.0,satisfied +66163,106343,Male,Loyal Customer,45,Business travel,Business,2321,5,5,5,5,2,5,4,3,3,3,3,4,3,5,65,58.0,satisfied +66164,37567,Male,disloyal Customer,27,Business travel,Business,1165,2,2,2,4,3,2,3,3,2,2,4,4,1,3,0,0.0,neutral or dissatisfied +66165,9947,Male,Loyal Customer,40,Business travel,Business,3673,3,4,4,4,3,4,4,3,3,3,3,2,3,1,20,12.0,neutral or dissatisfied +66166,72135,Female,Loyal Customer,23,Business travel,Business,2207,2,3,3,3,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +66167,49715,Female,Loyal Customer,50,Business travel,Eco,89,2,3,3,3,3,1,5,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +66168,39158,Male,Loyal Customer,62,Business travel,Business,1638,2,2,2,2,3,1,2,5,5,5,5,1,5,1,0,0.0,satisfied +66169,35601,Male,Loyal Customer,36,Business travel,Eco Plus,674,2,5,5,5,2,2,2,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +66170,10929,Male,Loyal Customer,40,Business travel,Business,1988,4,4,4,4,5,4,3,1,1,2,4,2,1,2,0,0.0,neutral or dissatisfied +66171,48168,Female,Loyal Customer,48,Business travel,Eco,414,1,4,4,4,2,3,2,1,1,1,1,1,1,4,58,62.0,neutral or dissatisfied +66172,17545,Male,Loyal Customer,24,Business travel,Business,970,2,2,2,2,4,4,4,5,2,5,1,4,5,4,173,184.0,satisfied +66173,100193,Male,Loyal Customer,7,Personal Travel,Eco,725,3,5,3,5,1,3,1,1,1,4,1,1,2,1,0,4.0,neutral or dissatisfied +66174,100550,Female,Loyal Customer,50,Personal Travel,Eco Plus,580,4,5,4,3,2,3,5,4,4,4,4,3,4,3,32,8.0,satisfied +66175,68695,Male,Loyal Customer,57,Personal Travel,Eco,175,2,4,0,4,3,0,4,3,3,1,1,3,5,3,0,0.0,neutral or dissatisfied +66176,38279,Female,Loyal Customer,46,Personal Travel,Eco,1111,3,4,3,3,5,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +66177,126459,Female,Loyal Customer,42,Business travel,Business,1972,2,2,2,2,3,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +66178,118628,Female,Loyal Customer,46,Business travel,Eco,325,4,2,2,2,3,4,3,4,4,4,4,1,4,4,5,2.0,neutral or dissatisfied +66179,3105,Male,Loyal Customer,12,Personal Travel,Eco,594,0,3,0,3,1,0,1,1,1,1,3,1,4,1,0,0.0,satisfied +66180,1164,Male,Loyal Customer,56,Personal Travel,Eco,102,2,4,2,2,5,2,5,5,5,4,4,4,4,5,0,2.0,neutral or dissatisfied +66181,119962,Female,Loyal Customer,54,Business travel,Business,468,2,1,1,1,5,3,3,2,2,2,2,4,2,2,0,6.0,neutral or dissatisfied +66182,97014,Male,Loyal Customer,9,Personal Travel,Eco,359,3,4,3,3,3,3,3,3,3,4,5,3,5,3,39,43.0,neutral or dissatisfied +66183,128938,Female,Loyal Customer,39,Business travel,Business,3085,4,4,4,4,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +66184,106385,Male,Loyal Customer,59,Business travel,Business,2391,2,2,2,2,3,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +66185,80885,Male,Loyal Customer,51,Business travel,Eco Plus,692,2,4,4,4,2,2,2,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +66186,31584,Female,Loyal Customer,45,Business travel,Eco,602,5,4,4,4,4,2,5,5,5,5,5,5,5,3,0,25.0,satisfied +66187,96458,Male,Loyal Customer,39,Business travel,Business,3582,4,4,4,4,4,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +66188,86230,Male,Loyal Customer,43,Business travel,Eco,306,4,1,3,3,4,4,4,4,3,3,2,1,4,4,0,0.0,satisfied +66189,18744,Male,disloyal Customer,16,Business travel,Business,1167,4,2,4,3,2,4,2,2,1,2,4,3,3,2,0,10.0,neutral or dissatisfied +66190,52022,Female,Loyal Customer,48,Business travel,Eco,328,2,3,3,3,1,3,3,2,2,2,2,1,2,4,0,8.0,neutral or dissatisfied +66191,6140,Female,disloyal Customer,37,Business travel,Business,491,4,4,4,2,2,4,2,2,4,4,4,3,5,2,1,13.0,satisfied +66192,123204,Female,Loyal Customer,49,Personal Travel,Eco,468,3,4,2,2,4,4,4,3,3,2,3,4,3,4,17,24.0,neutral or dissatisfied +66193,98009,Female,Loyal Customer,58,Business travel,Business,2390,2,2,2,2,4,4,4,4,5,5,4,4,3,4,183,185.0,satisfied +66194,33059,Male,Loyal Customer,53,Personal Travel,Eco,101,3,4,0,2,3,0,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +66195,69427,Female,Loyal Customer,47,Business travel,Business,2446,1,5,5,5,1,1,1,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +66196,7616,Male,Loyal Customer,20,Personal Travel,Eco,825,1,5,1,4,1,1,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +66197,58724,Male,Loyal Customer,69,Personal Travel,Business,1005,2,2,2,4,2,3,3,3,3,2,3,3,3,2,110,104.0,neutral or dissatisfied +66198,110273,Male,disloyal Customer,21,Business travel,Eco,925,2,2,2,4,2,2,2,2,1,3,4,1,3,2,1,0.0,neutral or dissatisfied +66199,97074,Male,Loyal Customer,25,Business travel,Business,1390,1,1,1,1,3,4,3,3,3,5,5,5,4,3,15,3.0,satisfied +66200,96061,Female,Loyal Customer,18,Business travel,Business,795,5,5,5,5,4,4,4,4,3,2,4,1,1,4,2,0.0,satisfied +66201,3135,Female,Loyal Customer,39,Business travel,Business,3033,0,4,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +66202,76888,Female,Loyal Customer,50,Business travel,Business,630,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +66203,15502,Male,Loyal Customer,63,Personal Travel,Eco,377,4,4,4,2,3,4,3,3,5,4,5,3,4,3,0,0.0,neutral or dissatisfied +66204,113123,Male,Loyal Customer,47,Business travel,Business,479,4,4,4,4,2,5,5,3,3,3,3,4,3,5,3,0.0,satisfied +66205,139,Female,Loyal Customer,69,Business travel,Business,3261,3,5,5,5,4,4,3,3,3,3,3,2,3,1,3,3.0,neutral or dissatisfied +66206,123715,Male,Loyal Customer,14,Personal Travel,Eco,214,5,4,5,3,3,5,3,3,5,2,1,5,3,3,0,0.0,satisfied +66207,80051,Male,Loyal Customer,11,Personal Travel,Eco,1010,3,5,3,2,5,3,3,5,1,1,4,2,3,5,0,26.0,neutral or dissatisfied +66208,67724,Female,Loyal Customer,40,Business travel,Business,1431,2,2,2,2,5,4,4,4,4,4,4,3,4,5,30,38.0,satisfied +66209,73827,Male,Loyal Customer,61,Personal Travel,Eco,1194,1,5,1,5,4,1,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +66210,9012,Female,Loyal Customer,51,Business travel,Business,160,2,2,4,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +66211,6592,Female,Loyal Customer,36,Personal Travel,Eco,607,3,5,3,1,5,3,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +66212,61591,Male,disloyal Customer,23,Business travel,Eco,1379,4,4,4,2,5,4,5,5,5,3,5,5,4,5,83,81.0,satisfied +66213,5836,Male,Loyal Customer,42,Business travel,Eco Plus,157,2,5,4,5,2,2,2,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +66214,15157,Male,Loyal Customer,45,Personal Travel,Eco,1042,3,2,3,3,2,3,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +66215,77919,Male,disloyal Customer,24,Business travel,Eco,214,1,2,1,3,3,1,3,3,2,4,3,3,3,3,0,10.0,neutral or dissatisfied +66216,36669,Female,Loyal Customer,63,Personal Travel,Eco,1237,3,5,3,5,4,3,5,2,2,3,2,4,2,3,0,51.0,neutral or dissatisfied +66217,30858,Male,Loyal Customer,16,Business travel,Eco,1703,0,4,0,3,4,0,4,4,2,1,4,5,5,4,0,0.0,satisfied +66218,53581,Male,Loyal Customer,10,Business travel,Eco Plus,1195,5,2,2,2,5,5,4,5,4,1,4,3,5,5,0,0.0,satisfied +66219,21382,Male,Loyal Customer,65,Business travel,Business,1564,1,1,4,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +66220,84900,Male,Loyal Customer,49,Personal Travel,Eco,547,2,5,2,3,3,2,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +66221,61185,Female,Loyal Customer,21,Business travel,Business,2321,3,3,3,3,4,4,4,4,4,5,4,5,4,4,13,28.0,satisfied +66222,61916,Male,Loyal Customer,24,Business travel,Eco,550,1,5,2,5,1,1,1,1,2,3,2,4,3,1,0,0.0,neutral or dissatisfied +66223,26700,Male,Loyal Customer,15,Personal Travel,Eco,545,2,5,2,5,2,2,2,2,1,5,5,4,3,2,0,0.0,neutral or dissatisfied +66224,112839,Male,Loyal Customer,42,Business travel,Business,1390,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +66225,122223,Female,disloyal Customer,8,Business travel,Eco,544,1,2,1,4,5,1,5,5,2,2,4,2,4,5,0,0.0,neutral or dissatisfied +66226,67284,Male,Loyal Customer,20,Personal Travel,Eco,1121,1,5,0,1,3,0,4,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +66227,112952,Male,Loyal Customer,12,Personal Travel,Eco,1313,3,2,3,3,5,3,5,5,2,3,3,1,2,5,6,0.0,neutral or dissatisfied +66228,70859,Male,Loyal Customer,12,Business travel,Eco,761,3,3,3,3,3,3,2,3,3,5,4,3,3,3,29,10.0,neutral or dissatisfied +66229,48968,Male,disloyal Customer,23,Business travel,Business,363,0,3,0,1,5,0,3,5,2,2,4,5,4,5,2,0.0,satisfied +66230,40236,Male,Loyal Customer,63,Business travel,Eco,463,5,2,2,2,5,5,5,5,1,3,5,1,1,5,0,0.0,satisfied +66231,33473,Male,Loyal Customer,36,Business travel,Business,2917,1,1,1,1,4,4,4,2,4,3,4,4,3,4,0,24.0,satisfied +66232,21635,Female,Loyal Customer,50,Personal Travel,Eco,780,2,3,2,3,3,2,1,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +66233,121302,Female,Loyal Customer,59,Business travel,Business,3314,2,2,1,2,3,4,4,5,5,5,5,4,5,3,0,8.0,satisfied +66234,392,Male,Loyal Customer,52,Business travel,Business,1938,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,31.0,satisfied +66235,54233,Male,Loyal Customer,24,Business travel,Business,1222,1,1,1,1,5,5,5,5,3,2,1,4,4,5,21,26.0,satisfied +66236,33277,Female,Loyal Customer,32,Personal Travel,Eco Plus,216,4,4,4,2,3,4,3,3,4,5,5,3,5,3,0,8.0,neutral or dissatisfied +66237,115624,Female,disloyal Customer,26,Business travel,Business,390,2,4,2,5,3,2,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +66238,86836,Female,Loyal Customer,47,Business travel,Eco,484,5,3,3,3,2,1,2,5,5,5,5,1,5,5,0,0.0,satisfied +66239,22685,Female,Loyal Customer,32,Business travel,Business,3622,3,3,3,3,4,4,4,4,2,5,2,2,4,4,0,0.0,satisfied +66240,52641,Male,Loyal Customer,35,Personal Travel,Eco,119,3,1,3,3,4,3,4,4,3,4,3,2,4,4,0,0.0,neutral or dissatisfied +66241,16602,Male,Loyal Customer,26,Business travel,Eco,1008,4,3,1,3,4,4,3,4,5,2,3,1,2,4,4,0.0,satisfied +66242,81674,Male,Loyal Customer,29,Business travel,Business,2978,4,4,4,4,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +66243,120778,Female,Loyal Customer,21,Personal Travel,Eco,678,3,5,3,3,5,3,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +66244,29180,Female,disloyal Customer,35,Business travel,Eco Plus,978,2,2,2,1,2,2,2,2,3,4,3,5,3,2,0,0.0,neutral or dissatisfied +66245,70634,Male,Loyal Customer,52,Business travel,Business,1217,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,12.0,satisfied +66246,94152,Female,Loyal Customer,56,Business travel,Business,233,1,1,1,1,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +66247,36352,Female,Loyal Customer,46,Business travel,Eco Plus,395,5,3,3,3,2,1,4,5,5,5,5,4,5,5,0,0.0,satisfied +66248,117409,Female,Loyal Customer,33,Business travel,Business,1766,4,4,4,4,4,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +66249,64320,Male,Loyal Customer,32,Business travel,Business,1158,5,5,5,5,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +66250,72530,Male,disloyal Customer,16,Business travel,Eco,929,5,5,5,3,3,5,3,3,4,2,4,5,5,3,0,0.0,satisfied +66251,97500,Male,Loyal Customer,21,Personal Travel,Eco,756,1,4,1,4,4,1,4,4,3,2,4,4,5,4,5,0.0,neutral or dissatisfied +66252,72702,Female,Loyal Customer,48,Business travel,Business,2351,5,5,5,5,5,4,5,2,2,2,2,4,2,3,72,72.0,satisfied +66253,38150,Male,Loyal Customer,41,Personal Travel,Eco,1010,1,5,1,4,5,1,5,5,2,3,4,1,2,5,0,0.0,neutral or dissatisfied +66254,53250,Female,Loyal Customer,47,Business travel,Eco Plus,612,4,2,2,2,2,4,4,4,4,4,4,2,4,2,43,36.0,neutral or dissatisfied +66255,53220,Female,Loyal Customer,41,Business travel,Eco,212,4,1,5,1,4,4,4,4,2,2,4,3,4,4,3,15.0,neutral or dissatisfied +66256,18469,Male,Loyal Customer,35,Business travel,Business,2661,3,5,5,5,2,3,2,3,4,4,3,2,3,2,388,380.0,neutral or dissatisfied +66257,87621,Female,disloyal Customer,16,Business travel,Business,591,4,4,4,3,3,4,3,3,3,5,4,4,4,3,0,0.0,satisfied +66258,100587,Male,Loyal Customer,47,Personal Travel,Eco,486,2,5,2,3,4,2,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +66259,17958,Male,Loyal Customer,43,Business travel,Eco,460,3,5,2,5,3,3,3,3,4,1,4,3,3,3,0,10.0,neutral or dissatisfied +66260,24005,Female,Loyal Customer,63,Business travel,Eco,427,2,3,2,3,3,4,3,1,1,2,1,4,1,2,13,14.0,neutral or dissatisfied +66261,57481,Female,Loyal Customer,30,Business travel,Business,1589,2,2,2,2,5,5,5,5,3,3,5,5,5,5,16,11.0,satisfied +66262,66198,Male,Loyal Customer,59,Business travel,Business,3846,4,2,2,2,1,3,3,4,4,4,4,2,4,4,4,7.0,neutral or dissatisfied +66263,54328,Male,Loyal Customer,43,Personal Travel,Eco,1597,2,4,2,4,2,2,5,2,3,3,5,3,5,2,0,13.0,neutral or dissatisfied +66264,96814,Female,Loyal Customer,55,Business travel,Business,2038,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +66265,53125,Male,Loyal Customer,20,Personal Travel,Eco,2065,2,2,2,4,3,2,3,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +66266,56094,Male,disloyal Customer,49,Business travel,Business,1628,1,2,2,3,3,1,1,3,4,5,3,3,5,3,6,1.0,neutral or dissatisfied +66267,4428,Female,disloyal Customer,11,Business travel,Eco,762,2,2,2,4,2,2,2,2,4,4,3,3,4,2,0,4.0,neutral or dissatisfied +66268,41316,Male,Loyal Customer,40,Business travel,Business,1622,1,1,1,1,4,3,4,1,1,1,1,2,1,4,19,29.0,neutral or dissatisfied +66269,128589,Male,Loyal Customer,36,Business travel,Business,2552,4,4,4,4,3,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +66270,7419,Male,disloyal Customer,29,Business travel,Eco,522,2,3,2,3,2,2,5,2,4,4,2,1,2,2,0,0.0,neutral or dissatisfied +66271,50993,Male,Loyal Customer,16,Personal Travel,Eco,89,2,5,2,5,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +66272,89898,Female,Loyal Customer,39,Business travel,Eco,1310,2,2,2,2,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +66273,2252,Male,Loyal Customer,58,Business travel,Business,1925,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +66274,105362,Female,Loyal Customer,16,Personal Travel,Eco Plus,452,1,4,1,5,5,1,5,5,4,5,5,3,4,5,17,13.0,neutral or dissatisfied +66275,53602,Female,Loyal Customer,59,Business travel,Business,1874,1,1,1,1,3,3,5,5,5,5,5,5,5,3,0,9.0,satisfied +66276,116238,Female,Loyal Customer,30,Personal Travel,Eco,342,3,3,3,3,5,3,5,5,3,4,3,4,5,5,0,0.0,neutral or dissatisfied +66277,1221,Female,Loyal Customer,14,Personal Travel,Eco,134,4,5,0,3,2,0,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +66278,96972,Female,Loyal Customer,54,Business travel,Business,2353,1,1,1,1,2,4,5,5,5,5,5,3,5,5,3,0.0,satisfied +66279,117786,Male,Loyal Customer,58,Business travel,Business,328,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +66280,33803,Male,Loyal Customer,30,Business travel,Eco,1521,4,3,3,3,4,4,4,4,5,3,1,2,3,4,20,26.0,satisfied +66281,45144,Male,Loyal Customer,57,Business travel,Eco,174,5,4,4,4,5,5,5,5,1,2,3,4,2,5,48,49.0,satisfied +66282,10010,Female,Loyal Customer,39,Personal Travel,Eco,508,4,4,4,3,5,4,5,5,3,4,4,1,4,5,0,0.0,satisfied +66283,50364,Male,Loyal Customer,25,Business travel,Business,3017,2,1,1,1,3,3,2,3,1,4,4,4,3,3,28,19.0,neutral or dissatisfied +66284,129416,Male,disloyal Customer,35,Business travel,Business,414,2,2,2,1,3,2,3,3,3,4,5,3,5,3,78,73.0,neutral or dissatisfied +66285,97781,Male,Loyal Customer,50,Business travel,Business,3466,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +66286,118148,Female,Loyal Customer,43,Business travel,Business,1444,3,3,3,3,2,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +66287,16893,Male,disloyal Customer,16,Business travel,Eco,746,3,3,3,3,3,3,3,3,2,3,4,3,4,3,26,14.0,neutral or dissatisfied +66288,40872,Female,Loyal Customer,42,Personal Travel,Eco,590,3,2,3,3,2,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +66289,36331,Male,Loyal Customer,76,Business travel,Business,187,0,5,0,2,3,4,4,3,3,3,3,5,3,2,0,2.0,satisfied +66290,23660,Male,Loyal Customer,35,Business travel,Business,251,3,1,3,3,2,3,3,4,4,5,4,4,4,3,61,52.0,satisfied +66291,125140,Male,Loyal Customer,26,Personal Travel,Eco Plus,361,2,5,2,1,5,2,5,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +66292,84425,Male,Loyal Customer,50,Personal Travel,Eco,606,4,5,4,4,4,4,4,4,2,5,4,4,5,4,109,153.0,neutral or dissatisfied +66293,53649,Male,Loyal Customer,47,Business travel,Eco Plus,1874,5,5,5,5,5,5,5,5,2,3,4,5,2,5,20,3.0,satisfied +66294,126138,Female,Loyal Customer,42,Business travel,Business,3651,3,3,3,3,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +66295,129424,Male,Loyal Customer,36,Business travel,Business,2835,3,3,3,3,4,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +66296,120555,Male,Loyal Customer,60,Business travel,Eco,2176,1,5,5,5,1,1,1,4,1,4,4,1,1,1,75,97.0,neutral or dissatisfied +66297,41613,Male,Loyal Customer,42,Business travel,Eco Plus,715,5,3,3,3,5,5,5,5,5,2,3,5,3,5,1,9.0,satisfied +66298,122567,Male,Loyal Customer,60,Business travel,Business,500,3,3,2,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +66299,26280,Male,Loyal Customer,42,Personal Travel,Eco,859,4,1,4,3,3,4,3,3,1,4,2,3,2,3,13,0.0,satisfied +66300,19010,Female,Loyal Customer,43,Business travel,Eco,828,2,3,3,3,2,4,3,2,2,2,2,1,2,4,31,50.0,neutral or dissatisfied +66301,26985,Female,disloyal Customer,23,Business travel,Eco,867,2,2,2,3,1,2,1,1,4,4,5,1,5,1,2,0.0,neutral or dissatisfied +66302,111671,Male,disloyal Customer,22,Business travel,Eco,991,2,2,2,3,5,2,5,5,2,1,2,5,4,5,0,0.0,neutral or dissatisfied +66303,33180,Female,Loyal Customer,50,Business travel,Eco Plus,101,4,5,5,5,2,4,4,4,4,4,4,5,4,5,5,25.0,satisfied +66304,42599,Male,Loyal Customer,35,Business travel,Eco,866,3,1,1,1,3,4,3,3,1,2,3,2,5,3,8,40.0,satisfied +66305,67690,Female,Loyal Customer,54,Business travel,Business,1464,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,1.0,satisfied +66306,115374,Female,disloyal Customer,33,Business travel,Business,337,3,3,3,4,1,3,1,1,5,5,4,5,4,1,47,26.0,neutral or dissatisfied +66307,48680,Male,Loyal Customer,39,Business travel,Business,86,5,5,5,5,2,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +66308,36851,Male,Loyal Customer,68,Personal Travel,Eco Plus,369,5,5,1,3,3,1,3,3,1,4,4,2,3,3,30,21.0,satisfied +66309,125240,Male,Loyal Customer,36,Personal Travel,Eco,1149,4,5,4,5,3,4,3,3,4,5,4,4,5,3,0,0.0,satisfied +66310,118235,Female,disloyal Customer,46,Business travel,Eco,853,3,3,3,4,1,3,1,1,1,4,4,3,4,1,35,24.0,neutral or dissatisfied +66311,8642,Male,Loyal Customer,39,Business travel,Business,3222,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +66312,88468,Female,Loyal Customer,32,Business travel,Business,2615,1,5,5,5,1,1,1,1,4,5,4,1,4,1,3,0.0,neutral or dissatisfied +66313,3803,Male,disloyal Customer,48,Business travel,Business,650,2,1,1,4,1,2,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +66314,25380,Male,Loyal Customer,37,Business travel,Eco,191,1,2,2,2,1,1,1,1,2,2,4,2,3,1,9,2.0,neutral or dissatisfied +66315,63614,Female,Loyal Customer,24,Business travel,Eco,1440,2,2,2,2,2,2,1,2,1,1,2,4,3,2,0,0.0,neutral or dissatisfied +66316,33038,Male,Loyal Customer,34,Personal Travel,Eco,101,1,2,1,3,2,1,3,2,3,1,3,2,2,2,0,3.0,neutral or dissatisfied +66317,46005,Female,Loyal Customer,52,Personal Travel,Eco,483,1,3,1,3,1,2,4,3,3,1,3,1,3,3,7,14.0,neutral or dissatisfied +66318,34274,Male,Loyal Customer,51,Business travel,Business,280,2,2,2,2,5,4,2,5,5,5,5,4,5,3,37,14.0,satisfied +66319,111995,Male,Loyal Customer,62,Personal Travel,Eco,770,2,4,2,1,5,2,5,5,3,4,4,4,5,5,40,29.0,neutral or dissatisfied +66320,6466,Female,Loyal Customer,35,Business travel,Eco Plus,240,4,3,4,4,4,4,4,4,3,2,3,4,4,4,0,0.0,neutral or dissatisfied +66321,107219,Male,Loyal Customer,65,Personal Travel,Eco Plus,402,3,4,3,1,4,3,4,4,4,2,4,5,5,4,38,24.0,neutral or dissatisfied +66322,117191,Male,Loyal Customer,29,Personal Travel,Eco,646,1,5,1,2,5,1,5,5,2,1,2,5,1,5,0,0.0,neutral or dissatisfied +66323,120958,Female,Loyal Customer,32,Business travel,Business,1888,2,2,1,2,4,4,4,4,3,5,5,4,4,4,0,3.0,satisfied +66324,120446,Female,Loyal Customer,69,Personal Travel,Eco,366,1,5,1,3,1,1,1,2,2,1,4,5,2,4,61,49.0,neutral or dissatisfied +66325,29213,Male,Loyal Customer,10,Personal Travel,Eco,2311,2,1,2,4,5,2,5,5,1,1,4,3,4,5,0,0.0,neutral or dissatisfied +66326,28905,Male,Loyal Customer,32,Business travel,Eco,987,5,2,5,2,5,5,5,5,1,1,3,1,2,5,0,0.0,satisfied +66327,122134,Female,Loyal Customer,48,Business travel,Business,3026,2,1,5,1,3,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +66328,89548,Female,Loyal Customer,42,Business travel,Business,3310,5,2,5,5,5,5,4,4,4,4,4,4,4,5,20,0.0,satisfied +66329,60318,Female,Loyal Customer,31,Personal Travel,Business,1024,2,4,2,3,2,2,2,2,3,5,4,3,4,2,17,17.0,neutral or dissatisfied +66330,11196,Female,Loyal Customer,33,Personal Travel,Eco,308,4,1,4,4,4,4,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +66331,118656,Female,Loyal Customer,57,Business travel,Business,646,4,4,4,4,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +66332,119709,Female,Loyal Customer,25,Business travel,Business,2260,4,4,4,4,4,4,4,4,2,4,4,4,4,4,0,1.0,neutral or dissatisfied +66333,35484,Male,Loyal Customer,52,Personal Travel,Eco,1028,3,5,3,3,2,3,2,2,5,5,4,4,5,2,13,0.0,neutral or dissatisfied +66334,94906,Male,Loyal Customer,47,Business travel,Eco,248,5,4,4,4,5,5,5,5,3,5,5,3,3,5,0,0.0,satisfied +66335,42790,Female,Loyal Customer,45,Business travel,Business,2814,3,3,3,3,3,4,4,5,5,5,5,4,5,3,100,91.0,satisfied +66336,71123,Female,disloyal Customer,25,Business travel,Business,1739,2,0,2,1,3,2,3,3,4,2,5,5,4,3,3,3.0,neutral or dissatisfied +66337,8155,Male,Loyal Customer,53,Business travel,Eco,530,3,5,5,5,3,3,3,3,2,4,4,4,4,3,0,8.0,neutral or dissatisfied +66338,82704,Female,Loyal Customer,41,Business travel,Business,3091,3,5,5,5,2,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +66339,42947,Female,disloyal Customer,25,Business travel,Eco,236,3,0,3,2,5,3,5,5,2,5,5,5,3,5,2,4.0,neutral or dissatisfied +66340,104609,Male,Loyal Customer,52,Business travel,Eco Plus,369,3,4,2,2,3,3,3,3,1,1,2,3,2,3,0,0.0,neutral or dissatisfied +66341,23470,Male,Loyal Customer,55,Business travel,Eco,516,1,1,1,1,1,1,1,1,2,1,4,2,4,1,37,31.0,neutral or dissatisfied +66342,125270,Female,Loyal Customer,32,Business travel,Business,1488,1,1,4,1,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +66343,52934,Male,Loyal Customer,33,Personal Travel,Eco,679,1,4,1,5,1,1,1,1,5,5,4,3,5,1,7,1.0,neutral or dissatisfied +66344,46219,Female,Loyal Customer,24,Business travel,Business,2368,5,5,5,5,4,4,4,4,3,1,3,1,5,4,20,1.0,satisfied +66345,3344,Female,disloyal Customer,34,Business travel,Business,315,3,3,3,3,5,3,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +66346,95241,Female,Loyal Customer,17,Personal Travel,Eco,187,4,4,4,1,3,4,3,3,5,3,5,5,5,3,19,16.0,neutral or dissatisfied +66347,21343,Male,Loyal Customer,51,Business travel,Eco,674,3,1,1,1,4,3,4,4,4,1,2,4,3,4,96,89.0,neutral or dissatisfied +66348,83823,Female,Loyal Customer,55,Business travel,Business,3381,3,3,3,3,5,5,5,2,2,3,2,3,2,3,0,0.0,satisfied +66349,74708,Female,Loyal Customer,66,Personal Travel,Eco,1242,3,5,3,1,3,4,5,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +66350,8193,Female,Loyal Customer,71,Business travel,Business,125,3,4,3,4,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +66351,68764,Male,Loyal Customer,59,Business travel,Business,926,4,4,4,4,4,4,5,5,5,5,5,4,5,4,5,52.0,satisfied +66352,58967,Female,disloyal Customer,27,Business travel,Business,1846,2,2,2,5,3,2,3,3,4,3,5,4,4,3,45,0.0,neutral or dissatisfied +66353,93873,Male,disloyal Customer,51,Business travel,Business,588,4,4,4,3,2,4,1,2,4,5,4,3,4,2,8,0.0,satisfied +66354,17509,Female,Loyal Customer,55,Business travel,Business,241,5,3,5,5,4,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +66355,68734,Female,Loyal Customer,49,Business travel,Business,585,2,4,4,4,5,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +66356,84500,Male,Loyal Customer,14,Personal Travel,Eco,4502,3,1,3,3,3,2,2,2,4,4,4,2,1,2,32,30.0,neutral or dissatisfied +66357,56599,Female,disloyal Customer,26,Business travel,Business,937,3,5,4,2,5,4,5,5,5,3,5,4,5,5,9,3.0,neutral or dissatisfied +66358,105170,Male,Loyal Customer,70,Personal Travel,Eco,289,2,4,2,1,1,2,1,1,5,4,4,5,4,1,2,0.0,neutral or dissatisfied +66359,79042,Male,Loyal Customer,36,Business travel,Eco,377,3,3,3,3,3,3,3,3,4,4,3,2,3,3,5,0.0,neutral or dissatisfied +66360,48548,Male,Loyal Customer,28,Personal Travel,Eco,916,4,1,4,2,4,4,4,4,1,4,3,4,2,4,0,0.0,neutral or dissatisfied +66361,53530,Female,Loyal Customer,48,Business travel,Eco Plus,2253,3,2,3,3,1,3,4,3,3,3,3,5,3,4,7,0.0,satisfied +66362,9595,Female,Loyal Customer,66,Personal Travel,Eco,228,2,5,2,5,4,4,4,4,4,2,4,3,4,4,0,2.0,neutral or dissatisfied +66363,56554,Male,disloyal Customer,35,Business travel,Business,1065,2,2,2,4,5,2,5,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +66364,42293,Female,Loyal Customer,52,Business travel,Business,3452,4,5,5,5,4,4,4,2,5,4,4,4,3,4,351,393.0,neutral or dissatisfied +66365,123776,Male,disloyal Customer,25,Business travel,Business,646,2,5,2,4,1,2,5,1,5,3,5,4,4,1,6,12.0,neutral or dissatisfied +66366,89616,Male,Loyal Customer,68,Business travel,Business,2586,3,1,5,5,2,4,3,3,3,3,3,1,3,4,1,0.0,neutral or dissatisfied +66367,13415,Female,Loyal Customer,37,Business travel,Business,2304,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,10.0,satisfied +66368,127176,Male,Loyal Customer,8,Personal Travel,Eco,338,5,5,4,4,5,4,5,5,3,2,4,3,5,5,0,0.0,satisfied +66369,32169,Male,Loyal Customer,31,Business travel,Eco,101,4,4,4,4,4,4,4,4,3,1,4,1,4,4,0,0.0,satisfied +66370,123304,Female,Loyal Customer,37,Business travel,Business,3558,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +66371,32897,Female,Loyal Customer,15,Personal Travel,Eco,163,5,3,5,3,4,5,4,4,2,5,3,4,4,4,3,4.0,satisfied +66372,55241,Female,disloyal Customer,25,Business travel,Eco,1009,2,2,2,3,1,2,1,1,1,3,3,3,3,1,14,26.0,neutral or dissatisfied +66373,128185,Female,Loyal Customer,20,Personal Travel,Eco,1972,2,2,2,3,1,2,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +66374,64294,Female,Loyal Customer,43,Business travel,Business,2788,2,2,2,2,3,4,4,4,4,4,4,4,4,5,3,5.0,satisfied +66375,94601,Male,disloyal Customer,24,Business travel,Eco,189,5,0,5,4,2,5,2,2,3,3,4,4,4,2,0,0.0,satisfied +66376,114388,Male,Loyal Customer,56,Business travel,Business,1806,2,2,2,2,4,5,5,4,4,4,4,5,4,3,37,41.0,satisfied +66377,5195,Male,Loyal Customer,48,Business travel,Business,285,1,1,1,1,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +66378,89798,Female,Loyal Customer,34,Personal Travel,Eco,1096,3,4,3,4,2,3,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +66379,113539,Male,Loyal Customer,43,Business travel,Business,3724,1,1,1,1,5,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +66380,13001,Male,disloyal Customer,20,Business travel,Eco,438,4,0,4,5,2,4,5,2,4,4,2,4,3,2,0,0.0,satisfied +66381,84541,Male,Loyal Customer,46,Business travel,Eco,1056,4,2,2,2,4,4,4,4,1,3,2,2,4,4,5,0.0,satisfied +66382,81243,Male,disloyal Customer,25,Business travel,Business,980,0,0,0,5,1,0,1,1,4,3,4,4,5,1,0,0.0,satisfied +66383,92721,Female,Loyal Customer,57,Business travel,Business,2239,5,5,5,5,4,5,5,4,4,4,4,4,4,4,0,2.0,satisfied +66384,17533,Male,disloyal Customer,24,Business travel,Eco,252,1,0,1,1,3,1,3,3,4,4,3,2,4,3,9,5.0,neutral or dissatisfied +66385,111571,Male,Loyal Customer,77,Business travel,Eco,375,4,3,3,3,4,4,4,4,1,2,3,4,2,4,148,156.0,satisfied +66386,126463,Female,disloyal Customer,21,Business travel,Eco,718,2,2,2,1,5,2,5,5,4,5,3,4,5,5,18,2.0,neutral or dissatisfied +66387,44660,Female,Loyal Customer,24,Business travel,Business,3889,1,2,2,2,4,4,1,4,1,2,3,4,4,4,0,27.0,neutral or dissatisfied +66388,36713,Female,disloyal Customer,48,Business travel,Eco Plus,1121,3,2,2,3,5,3,5,5,5,4,1,1,5,5,16,23.0,neutral or dissatisfied +66389,50412,Female,Loyal Customer,42,Business travel,Business,3667,3,3,3,3,5,3,4,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +66390,52554,Male,Loyal Customer,33,Business travel,Business,110,0,4,0,4,5,5,5,5,4,4,2,1,2,5,0,0.0,satisfied +66391,87003,Female,Loyal Customer,66,Personal Travel,Eco,907,0,4,0,3,5,5,4,5,5,0,5,5,5,4,5,0.0,satisfied +66392,4866,Male,Loyal Customer,16,Personal Travel,Eco,408,3,5,3,3,1,3,1,1,3,3,5,5,4,1,0,12.0,neutral or dissatisfied +66393,126185,Female,Loyal Customer,50,Business travel,Eco,631,4,4,2,2,1,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +66394,109994,Male,Loyal Customer,22,Personal Travel,Eco Plus,1204,3,4,3,1,1,3,1,1,2,2,3,1,1,1,41,46.0,neutral or dissatisfied +66395,35930,Male,Loyal Customer,50,Business travel,Eco,2381,1,2,2,2,1,1,1,1,2,4,1,4,2,1,0,0.0,neutral or dissatisfied +66396,120626,Male,Loyal Customer,39,Business travel,Business,280,0,0,0,2,4,4,5,2,2,3,3,3,2,5,0,0.0,satisfied +66397,87307,Male,Loyal Customer,24,Personal Travel,Eco,577,2,1,2,3,5,2,5,5,1,1,3,4,3,5,15,6.0,neutral or dissatisfied +66398,76724,Female,Loyal Customer,53,Business travel,Business,1672,3,1,3,3,4,5,5,5,5,5,5,4,5,5,0,2.0,satisfied +66399,129276,Male,Loyal Customer,27,Personal Travel,Eco,2521,4,4,3,3,4,3,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +66400,2132,Female,Loyal Customer,57,Business travel,Eco,431,1,2,2,2,5,4,3,1,1,1,1,4,1,4,3,0.0,neutral or dissatisfied +66401,2539,Female,Loyal Customer,41,Business travel,Business,2239,0,0,0,3,3,5,5,5,5,5,5,3,5,5,0,2.0,satisfied +66402,124477,Male,Loyal Customer,24,Business travel,Business,980,1,1,1,1,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +66403,31136,Female,Loyal Customer,9,Personal Travel,Eco,991,3,5,3,3,2,3,2,2,4,5,5,5,5,2,16,11.0,neutral or dissatisfied +66404,127761,Female,Loyal Customer,66,Personal Travel,Eco,255,3,5,3,4,4,5,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +66405,27779,Male,disloyal Customer,45,Business travel,Eco,740,3,3,3,4,5,3,1,5,3,5,3,4,4,5,0,0.0,neutral or dissatisfied +66406,75774,Male,Loyal Customer,43,Personal Travel,Eco,868,3,2,3,3,2,3,2,2,1,5,4,2,4,2,0,9.0,neutral or dissatisfied +66407,60985,Female,Loyal Customer,60,Business travel,Business,888,3,3,3,3,3,5,4,4,4,4,4,4,4,4,0,3.0,satisfied +66408,48920,Female,Loyal Customer,32,Business travel,Business,86,5,5,5,5,4,4,5,4,4,4,5,1,1,4,0,14.0,satisfied +66409,48484,Female,Loyal Customer,32,Business travel,Business,3681,1,1,1,1,1,1,1,1,3,1,3,2,2,1,6,12.0,neutral or dissatisfied +66410,23478,Male,Loyal Customer,45,Personal Travel,Eco,488,2,5,5,4,5,5,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +66411,122775,Female,disloyal Customer,19,Business travel,Eco,599,0,4,0,5,3,0,4,3,5,3,5,5,4,3,4,2.0,satisfied +66412,67315,Male,Loyal Customer,42,Business travel,Eco Plus,585,4,4,4,4,4,4,4,4,3,4,5,4,4,4,1,0.0,satisfied +66413,99188,Male,Loyal Customer,30,Personal Travel,Eco,462,1,5,1,1,1,4,4,1,3,5,3,4,2,4,211,225.0,neutral or dissatisfied +66414,47409,Female,Loyal Customer,46,Business travel,Business,2520,2,5,5,5,2,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +66415,101896,Female,disloyal Customer,20,Business travel,Business,1280,0,3,0,3,4,3,4,4,3,4,5,3,4,4,0,0.0,satisfied +66416,97588,Male,Loyal Customer,51,Business travel,Eco Plus,448,1,2,2,2,1,1,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +66417,68208,Male,disloyal Customer,19,Business travel,Business,631,0,0,1,4,5,1,5,5,5,4,4,5,4,5,0,0.0,satisfied +66418,30138,Male,Loyal Customer,38,Personal Travel,Eco,548,4,0,4,1,5,4,5,5,1,5,4,2,4,5,0,0.0,neutral or dissatisfied +66419,110532,Male,disloyal Customer,33,Business travel,Business,551,1,1,1,4,2,1,2,2,5,4,4,4,4,2,3,0.0,neutral or dissatisfied +66420,4531,Male,Loyal Customer,46,Business travel,Business,2998,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +66421,22725,Male,disloyal Customer,37,Business travel,Business,302,2,2,2,2,1,2,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +66422,10131,Female,Loyal Customer,56,Personal Travel,Eco,946,5,3,5,4,5,3,1,1,1,5,1,3,1,1,0,,satisfied +66423,118903,Male,Loyal Customer,48,Business travel,Business,587,3,3,3,3,2,4,4,5,5,5,5,5,5,4,1,0.0,satisfied +66424,106770,Male,Loyal Customer,60,Personal Travel,Eco,829,2,4,2,5,3,2,3,3,5,2,4,4,4,3,37,25.0,neutral or dissatisfied +66425,15336,Male,Loyal Customer,8,Personal Travel,Eco,599,1,2,1,3,4,1,4,4,3,3,3,3,4,4,0,0.0,neutral or dissatisfied +66426,9472,Female,Loyal Customer,46,Business travel,Business,299,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,18.0,satisfied +66427,52801,Male,disloyal Customer,26,Business travel,Eco Plus,1874,3,2,2,3,4,2,4,4,5,1,3,1,2,4,10,0.0,neutral or dissatisfied +66428,110773,Male,disloyal Customer,26,Business travel,Business,1166,3,3,3,2,3,3,4,4,2,5,5,4,4,4,154,,neutral or dissatisfied +66429,115995,Male,Loyal Customer,41,Personal Travel,Eco,371,1,2,1,4,4,1,1,4,3,2,2,4,3,4,28,29.0,neutral or dissatisfied +66430,69395,Male,Loyal Customer,67,Business travel,Business,1089,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +66431,126225,Female,Loyal Customer,48,Business travel,Business,200,3,3,2,3,3,2,3,5,5,5,5,3,5,2,0,11.0,satisfied +66432,31214,Female,Loyal Customer,46,Personal Travel,Eco,628,3,4,3,3,2,5,5,5,5,3,5,5,5,4,41,33.0,neutral or dissatisfied +66433,85448,Female,Loyal Customer,59,Business travel,Business,3337,2,2,4,2,2,5,5,4,4,4,5,4,4,4,18,17.0,satisfied +66434,127666,Female,disloyal Customer,27,Business travel,Business,2153,3,3,3,1,4,3,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +66435,89003,Female,Loyal Customer,51,Business travel,Business,1919,4,4,2,4,5,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +66436,91632,Male,disloyal Customer,8,Business travel,Eco,1340,3,4,4,4,4,3,4,4,2,1,4,2,3,4,54,34.0,neutral or dissatisfied +66437,101257,Male,disloyal Customer,30,Business travel,Business,2176,1,1,1,4,5,1,1,5,4,3,5,4,5,5,15,3.0,neutral or dissatisfied +66438,47634,Female,Loyal Customer,47,Business travel,Eco,1504,4,1,1,1,5,3,2,4,4,4,4,4,4,4,2,10.0,satisfied +66439,98784,Male,Loyal Customer,40,Business travel,Business,630,4,4,3,4,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +66440,14973,Female,Loyal Customer,44,Business travel,Eco,1080,3,2,2,2,1,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +66441,94818,Male,Loyal Customer,32,Business travel,Business,189,4,5,5,5,2,1,4,2,3,2,4,4,4,2,7,8.0,neutral or dissatisfied +66442,50131,Female,Loyal Customer,39,Business travel,Business,86,1,4,4,4,5,4,3,2,2,3,1,3,2,2,0,22.0,neutral or dissatisfied +66443,99439,Male,Loyal Customer,33,Business travel,Business,2214,3,3,3,3,4,4,4,3,4,4,5,4,5,4,207,208.0,satisfied +66444,37842,Male,Loyal Customer,58,Business travel,Eco,937,4,5,5,5,4,4,4,4,1,4,3,1,3,4,0,0.0,satisfied +66445,3061,Female,Loyal Customer,70,Personal Travel,Eco,340,3,4,3,5,3,5,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +66446,40557,Female,Loyal Customer,56,Business travel,Business,3361,4,4,4,4,4,4,1,5,5,5,5,1,5,5,0,0.0,satisfied +66447,31074,Female,Loyal Customer,54,Personal Travel,Eco,862,3,4,3,2,1,3,4,5,5,3,5,4,5,1,18,31.0,neutral or dissatisfied +66448,8290,Female,Loyal Customer,51,Personal Travel,Eco,402,4,2,4,4,5,3,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +66449,70823,Female,Loyal Customer,61,Business travel,Eco Plus,624,3,3,3,3,1,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +66450,16918,Female,Loyal Customer,54,Business travel,Eco Plus,346,3,2,2,2,2,4,3,4,4,3,4,1,4,2,0,2.0,neutral or dissatisfied +66451,106629,Female,disloyal Customer,25,Business travel,Eco,306,3,2,3,4,1,3,1,1,2,5,4,3,4,1,48,52.0,neutral or dissatisfied +66452,108513,Male,Loyal Customer,54,Business travel,Business,3149,4,4,4,4,3,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +66453,107285,Female,Loyal Customer,43,Business travel,Eco,283,4,2,2,2,5,4,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +66454,90586,Male,Loyal Customer,22,Business travel,Business,3879,3,2,2,2,3,3,3,3,3,1,4,4,3,3,45,49.0,neutral or dissatisfied +66455,73279,Male,Loyal Customer,52,Personal Travel,Business,1182,2,4,2,3,3,3,4,4,4,2,4,4,4,4,0,8.0,neutral or dissatisfied +66456,72870,Male,Loyal Customer,52,Personal Travel,Eco,700,2,4,2,4,3,2,4,3,5,5,5,5,4,3,22,3.0,neutral or dissatisfied +66457,99579,Female,Loyal Customer,35,Business travel,Business,2000,2,2,2,2,5,2,2,5,5,5,5,2,5,4,3,19.0,satisfied +66458,82575,Female,Loyal Customer,60,Business travel,Business,3315,5,5,5,5,3,5,4,3,3,3,3,4,3,4,1,5.0,satisfied +66459,20463,Female,Loyal Customer,61,Personal Travel,Eco,177,4,5,0,3,5,5,5,4,4,0,4,5,4,3,55,40.0,neutral or dissatisfied +66460,118536,Male,Loyal Customer,60,Business travel,Business,2068,2,3,3,3,4,2,3,2,2,2,2,2,2,4,47,31.0,neutral or dissatisfied +66461,89542,Female,Loyal Customer,43,Business travel,Business,3043,2,2,2,2,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +66462,21964,Male,disloyal Customer,36,Business travel,Eco,448,3,0,3,2,2,3,2,2,4,1,3,4,5,2,53,43.0,neutral or dissatisfied +66463,108379,Female,Loyal Customer,10,Personal Travel,Eco,1844,4,5,4,3,4,4,4,4,3,3,4,4,4,4,67,46.0,neutral or dissatisfied +66464,72579,Female,disloyal Customer,35,Business travel,Eco,1119,1,1,1,4,4,1,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +66465,32354,Male,disloyal Customer,21,Business travel,Eco,102,4,0,5,4,4,5,1,4,4,1,4,5,3,4,0,0.0,satisfied +66466,78285,Female,Loyal Customer,57,Business travel,Business,1598,3,3,3,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +66467,102266,Male,Loyal Customer,56,Business travel,Business,1904,1,1,2,1,2,4,4,1,1,2,1,2,1,3,1,0.0,neutral or dissatisfied +66468,75481,Female,Loyal Customer,60,Personal Travel,Eco,2218,3,2,3,4,5,3,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +66469,129020,Female,Loyal Customer,36,Business travel,Business,1583,1,5,1,5,1,1,1,1,2,3,4,1,2,1,0,0.0,neutral or dissatisfied +66470,106518,Male,Loyal Customer,48,Business travel,Business,271,5,5,5,5,3,5,5,4,4,4,4,5,4,5,7,5.0,satisfied +66471,127839,Female,Loyal Customer,57,Business travel,Business,1262,4,4,4,4,4,5,4,4,4,4,4,4,4,4,0,5.0,satisfied +66472,112444,Female,Loyal Customer,46,Business travel,Business,862,3,3,3,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +66473,109767,Male,Loyal Customer,30,Business travel,Business,1092,3,3,3,3,4,4,4,4,4,3,4,3,5,4,1,6.0,satisfied +66474,91277,Female,Loyal Customer,49,Business travel,Business,2781,4,4,4,4,5,5,4,4,4,5,4,5,4,3,42,40.0,satisfied +66475,5516,Male,disloyal Customer,25,Business travel,Business,404,1,0,1,1,1,1,1,1,5,5,5,3,4,1,6,11.0,neutral or dissatisfied +66476,82031,Male,Loyal Customer,36,Personal Travel,Eco,1535,5,4,4,1,1,4,1,1,4,2,5,4,5,1,0,0.0,satisfied +66477,111639,Female,Loyal Customer,23,Business travel,Business,1558,2,1,4,1,2,3,2,2,1,1,4,1,3,2,118,124.0,neutral or dissatisfied +66478,24290,Female,Loyal Customer,26,Personal Travel,Eco,302,4,3,4,3,4,4,4,4,2,5,4,2,2,4,0,0.0,satisfied +66479,82752,Male,Loyal Customer,44,Business travel,Eco,409,4,2,5,5,4,4,4,4,4,5,3,3,3,4,33,43.0,neutral or dissatisfied +66480,81098,Female,Loyal Customer,50,Business travel,Business,591,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +66481,86843,Female,Loyal Customer,35,Personal Travel,Eco,692,1,1,1,3,5,1,5,5,2,4,4,3,4,5,0,23.0,neutral or dissatisfied +66482,111252,Male,disloyal Customer,29,Business travel,Eco,1849,3,3,3,3,1,3,1,1,4,2,4,4,4,1,12,34.0,neutral or dissatisfied +66483,46008,Male,Loyal Customer,27,Business travel,Eco Plus,483,4,4,4,4,5,5,5,5,5,1,1,3,4,5,4,17.0,satisfied +66484,124879,Male,Loyal Customer,61,Personal Travel,Business,728,3,1,3,4,1,3,3,4,4,3,4,3,4,4,13,14.0,neutral or dissatisfied +66485,25686,Female,Loyal Customer,48,Personal Travel,Business,528,3,5,3,4,5,5,4,2,2,3,2,4,2,5,34,19.0,neutral or dissatisfied +66486,4010,Female,Loyal Customer,36,Business travel,Business,3596,2,2,2,2,3,4,5,4,4,5,4,4,4,4,0,4.0,satisfied +66487,55954,Female,Loyal Customer,42,Business travel,Business,1620,3,3,5,3,5,5,5,5,5,4,5,5,5,5,3,5.0,satisfied +66488,100195,Female,Loyal Customer,27,Personal Travel,Eco,717,2,5,2,3,4,2,4,4,1,5,3,5,4,4,0,0.0,neutral or dissatisfied +66489,7602,Male,Loyal Customer,20,Business travel,Business,825,3,1,1,1,3,2,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +66490,94142,Female,Loyal Customer,55,Business travel,Business,3384,2,2,2,2,5,5,5,4,4,4,5,4,4,5,16,17.0,satisfied +66491,122709,Female,Loyal Customer,20,Personal Travel,Eco,813,2,0,2,2,4,2,4,4,4,2,5,5,4,4,2,2.0,neutral or dissatisfied +66492,17083,Female,disloyal Customer,28,Business travel,Eco,416,4,0,4,5,1,4,1,1,3,2,3,2,5,1,0,11.0,neutral or dissatisfied +66493,85865,Female,Loyal Customer,57,Personal Travel,Business,2172,5,4,5,2,4,5,4,2,2,5,2,3,2,3,0,0.0,satisfied +66494,59555,Male,Loyal Customer,49,Business travel,Business,1831,3,3,3,3,2,5,4,5,5,5,5,4,5,3,75,92.0,satisfied +66495,105689,Male,Loyal Customer,51,Business travel,Eco,919,3,2,2,2,4,3,4,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +66496,45453,Female,Loyal Customer,25,Personal Travel,Business,587,2,1,2,2,1,2,1,1,4,5,2,1,3,1,0,0.0,neutral or dissatisfied +66497,28269,Female,Loyal Customer,48,Personal Travel,Business,2402,3,4,3,1,4,1,3,2,2,3,2,2,2,2,0,16.0,neutral or dissatisfied +66498,49847,Male,Loyal Customer,17,Business travel,Eco,209,2,4,4,4,2,2,1,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +66499,46126,Male,Loyal Customer,21,Business travel,Business,3940,4,4,4,4,3,3,3,3,4,4,1,3,3,3,115,95.0,satisfied +66500,112473,Male,Loyal Customer,66,Personal Travel,Eco,862,3,3,3,2,5,3,5,5,3,2,2,4,1,5,6,18.0,neutral or dissatisfied +66501,12222,Female,Loyal Customer,60,Personal Travel,Business,253,4,5,4,3,2,2,3,5,5,4,3,2,5,1,0,0.0,neutral or dissatisfied +66502,60137,Female,disloyal Customer,38,Business travel,Eco,1012,1,1,1,3,2,1,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +66503,105999,Male,Loyal Customer,52,Business travel,Business,1999,4,4,4,4,3,4,4,4,4,4,4,5,4,3,24,16.0,satisfied +66504,114573,Female,Loyal Customer,57,Business travel,Business,446,4,4,4,4,2,4,5,2,2,2,2,3,2,5,0,2.0,satisfied +66505,107363,Female,Loyal Customer,10,Personal Travel,Eco,632,2,4,2,4,2,2,2,2,4,4,3,2,4,2,9,7.0,neutral or dissatisfied +66506,66786,Male,Loyal Customer,60,Business travel,Business,3784,4,4,4,4,5,5,5,3,4,3,4,5,5,5,1,0.0,satisfied +66507,77603,Male,Loyal Customer,49,Business travel,Business,813,4,4,4,4,5,5,4,5,5,5,5,5,5,5,5,0.0,satisfied +66508,10375,Male,Loyal Customer,29,Business travel,Business,312,3,3,2,3,4,4,4,4,4,2,4,5,5,4,0,12.0,satisfied +66509,92692,Female,Loyal Customer,34,Personal Travel,Eco,507,2,4,2,5,5,2,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +66510,68617,Male,Loyal Customer,45,Business travel,Business,1714,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +66511,82903,Female,Loyal Customer,58,Personal Travel,Eco,594,0,3,0,4,3,1,4,1,1,0,1,3,1,3,0,0.0,satisfied +66512,70268,Female,Loyal Customer,32,Business travel,Business,3720,4,4,4,4,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +66513,41905,Male,Loyal Customer,58,Business travel,Eco,129,3,4,4,4,3,3,3,3,5,5,3,1,1,3,0,0.0,satisfied +66514,6827,Male,Loyal Customer,36,Personal Travel,Eco,303,2,4,4,2,2,4,2,2,5,5,5,5,4,2,1,0.0,neutral or dissatisfied +66515,72781,Male,disloyal Customer,25,Business travel,Eco,1045,3,3,3,4,1,3,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +66516,70343,Male,Loyal Customer,23,Personal Travel,Eco,986,2,5,2,2,2,2,3,2,4,2,5,5,5,2,0,9.0,neutral or dissatisfied +66517,50138,Female,Loyal Customer,52,Business travel,Business,337,3,2,2,2,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +66518,76231,Male,disloyal Customer,10,Business travel,Eco,1399,3,3,3,3,3,3,3,3,1,1,3,3,3,3,47,40.0,neutral or dissatisfied +66519,64057,Male,Loyal Customer,51,Business travel,Business,1694,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +66520,52887,Male,Loyal Customer,45,Personal Travel,Eco,1024,3,1,3,4,4,3,2,4,2,4,3,1,4,4,2,0.0,neutral or dissatisfied +66521,109709,Male,Loyal Customer,34,Business travel,Business,2849,4,2,4,4,5,4,4,2,2,2,2,3,2,3,1,0.0,satisfied +66522,118082,Male,Loyal Customer,32,Business travel,Business,3177,1,1,1,1,5,5,5,5,4,4,4,3,5,5,0,13.0,satisfied +66523,82513,Male,Loyal Customer,55,Business travel,Business,1749,3,4,1,1,4,2,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +66524,19682,Female,Loyal Customer,19,Business travel,Business,491,5,3,5,5,4,4,4,4,2,2,1,2,3,4,0,0.0,satisfied +66525,103398,Female,Loyal Customer,39,Business travel,Business,2992,4,4,4,4,2,4,3,4,4,4,4,4,4,1,12,16.0,neutral or dissatisfied +66526,96764,Male,Loyal Customer,36,Personal Travel,Business,849,2,5,3,3,5,4,5,4,4,3,2,4,4,5,12,14.0,neutral or dissatisfied +66527,78900,Female,Loyal Customer,45,Business travel,Business,2026,4,4,4,4,3,4,5,4,4,4,4,4,4,4,2,31.0,satisfied +66528,29632,Male,Loyal Customer,60,Business travel,Eco,1133,3,4,1,1,3,3,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +66529,66252,Female,Loyal Customer,35,Personal Travel,Eco,550,3,0,3,3,3,3,1,3,4,2,5,3,5,3,26,95.0,neutral or dissatisfied +66530,84684,Male,Loyal Customer,37,Personal Travel,Eco,2182,0,5,0,3,5,0,5,5,4,2,1,1,1,5,9,17.0,satisfied +66531,39595,Female,Loyal Customer,42,Business travel,Business,508,2,2,2,2,5,2,1,2,2,2,2,4,2,4,3,0.0,neutral or dissatisfied +66532,1421,Male,Loyal Customer,11,Personal Travel,Eco Plus,270,4,0,4,5,3,4,2,3,4,5,4,3,5,3,12,0.0,satisfied +66533,89482,Female,Loyal Customer,42,Business travel,Business,1931,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +66534,127531,Female,Loyal Customer,34,Business travel,Business,3428,1,1,5,1,4,5,5,3,3,3,3,4,3,3,0,5.0,satisfied +66535,13639,Female,Loyal Customer,10,Business travel,Business,835,1,1,1,1,5,5,5,5,3,2,4,2,4,5,0,0.0,satisfied +66536,47719,Male,Loyal Customer,8,Business travel,Eco Plus,1504,4,4,4,4,4,4,3,4,3,4,2,4,2,4,0,0.0,satisfied +66537,113551,Male,Loyal Customer,43,Business travel,Eco,197,3,5,5,5,2,3,2,2,1,2,4,1,4,2,0,0.0,neutral or dissatisfied +66538,113873,Male,Loyal Customer,11,Personal Travel,Eco,1592,4,4,5,4,5,5,5,5,4,5,4,4,4,5,25,40.0,neutral or dissatisfied +66539,765,Male,Loyal Customer,59,Business travel,Business,2394,4,4,3,4,3,4,4,4,4,4,4,5,4,4,4,8.0,satisfied +66540,45195,Female,Loyal Customer,30,Business travel,Business,606,2,1,2,1,2,2,2,2,2,1,3,1,3,2,1,26.0,neutral or dissatisfied +66541,88407,Male,Loyal Customer,45,Business travel,Business,240,2,1,1,1,2,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +66542,94075,Male,Loyal Customer,54,Business travel,Business,189,3,3,3,3,4,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +66543,37124,Male,Loyal Customer,41,Business travel,Business,3949,3,3,3,3,5,5,3,3,3,3,3,1,3,1,0,0.0,satisfied +66544,63197,Female,Loyal Customer,47,Business travel,Business,3758,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +66545,104287,Female,Loyal Customer,42,Business travel,Business,1875,5,5,5,5,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +66546,25460,Male,Loyal Customer,30,Business travel,Eco Plus,669,5,4,3,4,5,5,5,5,5,1,1,3,3,5,0,0.0,satisfied +66547,71365,Female,Loyal Customer,53,Business travel,Business,2945,0,0,0,1,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +66548,101680,Male,Loyal Customer,33,Business travel,Business,1500,3,3,3,3,5,4,5,5,5,5,5,5,5,5,20,0.0,satisfied +66549,44588,Male,Loyal Customer,48,Personal Travel,Eco,84,2,4,2,3,5,2,5,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +66550,69875,Male,Loyal Customer,54,Business travel,Business,2248,1,1,1,1,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +66551,113459,Male,disloyal Customer,23,Business travel,Business,223,1,3,1,4,5,1,5,5,4,4,4,1,4,5,22,19.0,neutral or dissatisfied +66552,113342,Male,Loyal Customer,39,Business travel,Business,2172,0,0,0,5,2,5,4,3,3,5,5,4,3,3,10,20.0,satisfied +66553,1993,Male,Loyal Customer,39,Personal Travel,Eco,293,4,4,4,1,4,4,4,4,4,2,5,3,4,4,47,43.0,neutral or dissatisfied +66554,13894,Female,Loyal Customer,55,Personal Travel,Eco Plus,760,3,4,3,5,5,5,5,3,3,3,3,5,3,4,11,16.0,neutral or dissatisfied +66555,52460,Female,Loyal Customer,57,Business travel,Eco Plus,370,4,5,5,5,4,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +66556,99434,Female,Loyal Customer,24,Personal Travel,Eco,337,3,4,3,4,3,3,3,3,3,4,3,5,2,3,0,0.0,neutral or dissatisfied +66557,124832,Female,Loyal Customer,61,Personal Travel,Eco,280,3,5,3,3,3,5,4,2,2,3,2,3,2,3,14,11.0,neutral or dissatisfied +66558,88233,Female,Loyal Customer,22,Business travel,Business,250,5,5,5,5,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +66559,62851,Female,Loyal Customer,65,Personal Travel,Business,2446,3,4,3,4,4,2,4,2,2,3,3,4,2,2,11,0.0,neutral or dissatisfied +66560,123310,Female,Loyal Customer,31,Business travel,Business,2956,4,4,4,4,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +66561,62615,Female,Loyal Customer,53,Personal Travel,Eco,1723,1,4,1,4,4,5,4,5,5,1,5,3,5,5,58,58.0,neutral or dissatisfied +66562,9772,Female,Loyal Customer,45,Business travel,Business,383,1,1,5,1,5,4,4,4,4,4,4,3,4,3,1,0.0,satisfied +66563,47911,Female,Loyal Customer,34,Personal Travel,Eco,748,0,5,0,3,5,0,3,5,4,4,5,4,4,5,60,56.0,satisfied +66564,35716,Female,Loyal Customer,8,Personal Travel,Eco,2475,1,3,1,4,1,4,4,4,3,3,3,4,4,4,0,0.0,neutral or dissatisfied +66565,1382,Male,Loyal Customer,37,Business travel,Eco Plus,140,4,2,2,2,4,4,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +66566,111431,Female,Loyal Customer,63,Personal Travel,Eco,896,3,5,3,2,3,3,1,1,1,3,1,3,1,1,7,0.0,neutral or dissatisfied +66567,111411,Female,Loyal Customer,35,Business travel,Business,1671,2,2,2,2,5,4,4,5,5,5,5,4,5,5,5,0.0,satisfied +66568,128168,Female,Loyal Customer,55,Business travel,Business,1972,3,4,4,4,2,4,4,3,3,3,3,2,3,2,2,0.0,neutral or dissatisfied +66569,65991,Male,disloyal Customer,26,Business travel,Eco Plus,1372,1,1,1,2,1,1,1,1,1,2,3,3,2,1,0,0.0,neutral or dissatisfied +66570,61577,Male,Loyal Customer,49,Business travel,Business,1379,4,1,5,1,1,4,3,4,4,4,4,3,4,2,6,13.0,neutral or dissatisfied +66571,38039,Male,Loyal Customer,37,Business travel,Business,1249,3,4,5,4,1,4,4,3,3,3,3,3,3,2,17,0.0,neutral or dissatisfied +66572,9541,Male,Loyal Customer,44,Business travel,Business,3702,5,5,5,5,5,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +66573,29349,Female,Loyal Customer,18,Personal Travel,Eco,2588,3,4,3,2,3,3,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +66574,51299,Female,Loyal Customer,54,Business travel,Eco Plus,89,5,2,2,2,2,2,4,5,5,5,5,5,5,5,0,0.0,satisfied +66575,63807,Male,Loyal Customer,38,Business travel,Eco,1224,4,1,4,1,4,4,4,4,4,3,2,4,1,4,32,2.0,satisfied +66576,44835,Male,Loyal Customer,39,Business travel,Eco Plus,462,4,1,1,1,4,4,4,4,2,2,4,3,3,4,11,16.0,satisfied +66577,43207,Male,Loyal Customer,58,Personal Travel,Eco,416,2,5,2,2,3,2,3,3,4,1,4,5,3,3,65,62.0,neutral or dissatisfied +66578,76434,Female,Loyal Customer,51,Personal Travel,Eco,405,1,5,1,1,4,4,4,4,4,1,4,5,4,5,13,10.0,neutral or dissatisfied +66579,82383,Male,Loyal Customer,59,Business travel,Business,501,2,5,2,2,4,4,4,5,5,5,5,4,5,4,0,10.0,satisfied +66580,46186,Male,Loyal Customer,49,Business travel,Business,3317,2,2,2,2,3,5,4,4,4,4,4,5,4,5,33,35.0,satisfied +66581,21525,Female,Loyal Customer,50,Personal Travel,Eco,399,2,4,2,4,4,4,4,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +66582,33178,Male,Loyal Customer,8,Personal Travel,Eco,163,1,4,1,4,4,1,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +66583,107799,Male,Loyal Customer,41,Business travel,Business,3942,4,4,4,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +66584,71761,Female,Loyal Customer,54,Business travel,Business,1846,1,1,1,1,3,4,4,4,4,4,4,3,4,4,9,0.0,satisfied +66585,120758,Male,Loyal Customer,58,Business travel,Business,678,3,3,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +66586,25098,Female,Loyal Customer,56,Business travel,Business,3626,3,1,1,1,4,3,2,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +66587,79372,Male,Loyal Customer,38,Business travel,Business,502,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +66588,94454,Male,disloyal Customer,44,Business travel,Business,441,5,5,5,2,2,5,2,2,5,2,4,4,4,2,22,19.0,satisfied +66589,104702,Female,Loyal Customer,57,Personal Travel,Eco,159,3,4,3,2,4,4,5,4,4,3,4,3,4,4,21,9.0,neutral or dissatisfied +66590,19053,Male,Loyal Customer,60,Business travel,Business,642,1,1,1,1,2,5,4,4,4,4,4,4,4,5,0,14.0,satisfied +66591,60572,Male,Loyal Customer,43,Business travel,Business,1714,3,1,3,1,4,4,3,3,3,3,3,2,3,4,16,0.0,neutral or dissatisfied +66592,115247,Male,disloyal Customer,25,Business travel,Business,358,5,0,5,2,4,5,4,4,5,2,4,4,5,4,0,0.0,satisfied +66593,80280,Female,Loyal Customer,39,Business travel,Business,746,3,3,3,3,4,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +66594,47499,Female,Loyal Customer,7,Personal Travel,Eco,532,4,5,4,4,3,4,3,3,4,3,5,3,5,3,1,4.0,neutral or dissatisfied +66595,126663,Female,Loyal Customer,55,Business travel,Business,602,3,3,4,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +66596,26457,Male,Loyal Customer,24,Business travel,Business,2577,4,4,4,4,5,5,5,5,4,4,3,5,3,5,0,0.0,satisfied +66597,128441,Female,Loyal Customer,50,Business travel,Business,3820,2,5,5,5,5,2,1,2,2,2,2,4,2,2,23,54.0,neutral or dissatisfied +66598,87839,Female,Loyal Customer,38,Personal Travel,Eco,214,1,4,1,4,5,1,5,5,1,1,3,1,3,5,20,17.0,neutral or dissatisfied +66599,39791,Male,Loyal Customer,48,Business travel,Business,221,3,1,1,1,5,3,4,3,3,3,3,4,3,4,0,11.0,neutral or dissatisfied +66600,58737,Male,Loyal Customer,53,Business travel,Business,1012,5,5,5,5,4,4,4,5,5,4,5,4,3,4,175,174.0,satisfied +66601,120231,Male,Loyal Customer,38,Business travel,Business,3634,3,5,3,5,3,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +66602,77550,Male,Loyal Customer,38,Business travel,Business,3290,3,1,1,1,5,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +66603,14663,Female,Loyal Customer,39,Business travel,Eco Plus,162,3,4,4,4,3,3,3,3,3,5,5,1,3,3,0,0.0,satisfied +66604,48539,Female,disloyal Customer,47,Business travel,Eco,548,2,2,2,3,1,2,1,1,3,3,4,2,3,1,5,2.0,neutral or dissatisfied +66605,116978,Male,Loyal Customer,57,Business travel,Business,646,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +66606,16666,Male,Loyal Customer,51,Personal Travel,Eco,488,3,0,3,3,3,3,1,3,4,5,3,3,5,3,0,0.0,neutral or dissatisfied +66607,13715,Male,Loyal Customer,40,Business travel,Business,2978,4,4,4,4,1,3,1,3,3,2,3,3,3,4,0,0.0,satisfied +66608,87830,Female,Loyal Customer,36,Business travel,Eco,143,4,3,3,3,4,4,4,4,3,1,5,3,2,4,2,0.0,satisfied +66609,15560,Female,disloyal Customer,20,Business travel,Eco,229,4,0,4,4,5,4,5,5,1,2,4,4,3,5,0,16.0,satisfied +66610,95741,Male,disloyal Customer,23,Business travel,Eco,181,1,3,1,3,3,1,3,3,2,5,2,3,3,3,3,0.0,neutral or dissatisfied +66611,106331,Male,Loyal Customer,21,Business travel,Eco,825,4,2,2,2,4,4,3,4,5,2,1,4,3,4,7,5.0,satisfied +66612,118635,Female,disloyal Customer,28,Business travel,Eco,369,1,3,1,3,2,1,2,2,1,5,4,4,3,2,20,11.0,neutral or dissatisfied +66613,108068,Male,Loyal Customer,42,Personal Travel,Business,849,3,4,3,3,4,4,4,4,4,3,4,4,4,3,24,16.0,neutral or dissatisfied +66614,18456,Female,Loyal Customer,35,Business travel,Eco,190,4,3,3,3,4,4,4,4,4,4,5,2,5,4,0,0.0,satisfied +66615,15485,Female,Loyal Customer,21,Personal Travel,Eco,306,2,4,2,3,3,2,1,3,5,2,4,3,4,3,8,0.0,neutral or dissatisfied +66616,80984,Male,Loyal Customer,39,Business travel,Business,3411,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +66617,51749,Male,Loyal Customer,16,Personal Travel,Eco,370,2,1,2,3,5,2,5,5,1,4,3,1,3,5,0,0.0,neutral or dissatisfied +66618,105755,Male,Loyal Customer,52,Business travel,Eco,525,4,2,4,2,4,4,4,4,2,4,3,3,5,4,27,11.0,satisfied +66619,109426,Female,Loyal Customer,43,Personal Travel,Business,861,1,4,1,1,2,5,4,5,5,1,5,3,5,4,80,62.0,neutral or dissatisfied +66620,129148,Female,Loyal Customer,42,Business travel,Business,954,3,3,3,3,3,3,4,3,3,3,3,3,3,2,1,0.0,neutral or dissatisfied +66621,69226,Male,Loyal Customer,27,Business travel,Business,733,3,3,3,3,4,4,4,4,5,5,4,4,4,4,0,2.0,satisfied +66622,20356,Male,Loyal Customer,39,Business travel,Eco,265,5,4,3,4,5,4,5,5,2,5,5,1,1,5,0,0.0,satisfied +66623,102741,Female,Loyal Customer,29,Personal Travel,Eco,255,2,3,2,2,2,2,2,2,4,5,4,2,1,2,56,49.0,neutral or dissatisfied +66624,45177,Female,Loyal Customer,42,Business travel,Eco Plus,174,5,4,4,4,4,1,2,5,5,5,5,3,5,1,0,15.0,satisfied +66625,96587,Male,Loyal Customer,52,Business travel,Business,2108,3,3,3,3,2,4,4,5,5,5,5,5,5,4,0,3.0,satisfied +66626,19945,Female,Loyal Customer,19,Personal Travel,Eco,240,2,4,2,1,2,2,2,2,4,4,4,5,5,2,28,16.0,neutral or dissatisfied +66627,79300,Male,Loyal Customer,63,Business travel,Eco,2248,1,2,2,2,1,1,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +66628,5933,Female,Loyal Customer,32,Personal Travel,Eco,212,3,4,3,3,5,3,5,5,5,2,5,3,3,5,0,0.0,neutral or dissatisfied +66629,35159,Female,disloyal Customer,18,Business travel,Eco,1056,5,5,5,2,4,5,4,4,3,5,1,5,5,4,0,14.0,satisfied +66630,31847,Female,disloyal Customer,28,Business travel,Eco,2640,2,2,2,4,3,2,5,3,3,2,4,1,4,3,54,27.0,neutral or dissatisfied +66631,72024,Male,Loyal Customer,21,Business travel,Business,3711,2,2,2,2,5,5,5,3,3,3,4,5,3,5,40,20.0,satisfied +66632,42138,Female,disloyal Customer,42,Business travel,Business,817,3,3,3,1,2,3,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +66633,21621,Female,Loyal Customer,48,Business travel,Business,3733,1,1,1,1,2,4,3,1,1,1,1,3,1,1,3,0.0,neutral or dissatisfied +66634,15278,Female,disloyal Customer,23,Business travel,Eco,501,2,3,2,4,4,2,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +66635,1571,Female,Loyal Customer,44,Business travel,Business,140,0,4,0,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +66636,48001,Female,Loyal Customer,57,Business travel,Eco Plus,817,2,1,1,1,1,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +66637,60785,Female,Loyal Customer,42,Business travel,Eco Plus,228,1,2,2,2,4,4,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +66638,92305,Male,Loyal Customer,70,Personal Travel,Business,2556,5,1,5,4,5,2,4,3,3,5,3,1,3,3,1,0.0,satisfied +66639,114158,Female,Loyal Customer,42,Business travel,Business,1672,3,3,3,3,4,4,4,3,3,3,3,4,3,4,28,12.0,satisfied +66640,5938,Female,Loyal Customer,58,Business travel,Business,173,5,5,4,5,5,5,5,5,5,5,4,3,5,4,4,10.0,satisfied +66641,89843,Female,Loyal Customer,48,Business travel,Business,1416,4,4,4,4,5,3,4,4,4,3,4,1,4,3,113,120.0,neutral or dissatisfied +66642,47875,Female,Loyal Customer,35,Business travel,Business,2264,1,3,3,3,3,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +66643,126431,Female,Loyal Customer,15,Business travel,Eco Plus,631,0,5,0,1,3,5,3,3,4,2,2,5,3,3,0,0.0,satisfied +66644,87396,Female,Loyal Customer,56,Business travel,Eco,425,3,4,4,4,2,1,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +66645,36419,Female,disloyal Customer,17,Business travel,Eco,369,1,3,1,3,4,1,4,4,1,5,4,2,4,4,36,46.0,neutral or dissatisfied +66646,40346,Female,Loyal Customer,42,Business travel,Business,1428,4,4,4,4,2,3,5,4,4,4,4,2,4,2,1,0.0,satisfied +66647,13906,Female,Loyal Customer,37,Business travel,Eco,192,4,3,3,3,4,4,4,4,5,4,1,3,5,4,0,0.0,satisfied +66648,24326,Female,Loyal Customer,29,Business travel,Business,3857,1,5,5,5,1,2,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +66649,30973,Male,Loyal Customer,40,Business travel,Business,1476,4,4,4,4,4,4,3,5,5,5,5,1,5,1,0,0.0,satisfied +66650,73122,Male,Loyal Customer,38,Personal Travel,Eco,2174,3,0,3,5,2,3,3,2,4,5,5,5,4,2,2,15.0,neutral or dissatisfied +66651,5144,Female,Loyal Customer,52,Business travel,Business,622,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +66652,123818,Male,disloyal Customer,15,Business travel,Eco,541,2,4,2,4,2,2,2,2,4,2,5,5,4,2,7,8.0,neutral or dissatisfied +66653,50075,Male,Loyal Customer,45,Business travel,Business,109,2,4,4,4,3,3,3,1,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +66654,109505,Female,Loyal Customer,36,Business travel,Business,834,3,3,3,3,3,3,4,3,3,3,3,1,3,1,1,0.0,neutral or dissatisfied +66655,49425,Female,disloyal Customer,25,Business travel,Eco,266,1,0,1,4,4,1,4,4,5,3,3,5,4,4,0,0.0,neutral or dissatisfied +66656,22005,Male,Loyal Customer,59,Personal Travel,Eco,448,2,2,2,3,5,2,5,5,3,2,4,2,3,5,0,0.0,neutral or dissatisfied +66657,5365,Female,Loyal Customer,30,Business travel,Business,812,2,2,2,2,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +66658,123537,Female,Loyal Customer,44,Personal Travel,Eco Plus,2077,4,4,4,5,4,5,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +66659,99163,Male,Loyal Customer,44,Business travel,Eco,1076,3,3,3,3,3,3,3,3,2,3,4,3,3,3,0,6.0,neutral or dissatisfied +66660,74118,Male,Loyal Customer,57,Business travel,Business,3257,3,3,3,3,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +66661,8154,Male,Loyal Customer,14,Business travel,Business,1720,3,4,4,4,3,3,3,3,1,5,4,4,3,3,27,23.0,neutral or dissatisfied +66662,70053,Female,Loyal Customer,62,Personal Travel,Eco,583,3,5,3,3,2,5,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +66663,19196,Male,disloyal Customer,22,Business travel,Eco,542,3,4,3,4,5,3,5,5,1,3,3,1,3,5,0,0.0,neutral or dissatisfied +66664,64338,Female,Loyal Customer,43,Business travel,Business,2506,3,4,4,4,5,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +66665,110926,Female,Loyal Customer,27,Personal Travel,Eco,581,0,4,0,3,4,0,4,4,4,4,5,4,4,4,0,0.0,satisfied +66666,116234,Female,Loyal Customer,59,Personal Travel,Eco,337,1,1,1,4,5,4,4,1,1,1,5,4,1,2,90,70.0,neutral or dissatisfied +66667,17973,Male,Loyal Customer,43,Business travel,Eco Plus,460,4,4,4,4,4,4,4,4,2,4,2,2,3,4,0,0.0,satisfied +66668,118542,Female,Loyal Customer,24,Business travel,Business,3307,3,4,4,4,3,2,3,3,4,2,3,3,3,3,42,38.0,neutral or dissatisfied +66669,120253,Female,Loyal Customer,43,Business travel,Business,1697,2,2,2,2,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +66670,62517,Male,Loyal Customer,56,Business travel,Business,1846,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +66671,112370,Male,Loyal Customer,57,Business travel,Business,957,2,2,5,2,5,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +66672,87815,Male,Loyal Customer,54,Business travel,Business,2144,4,4,4,4,4,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +66673,82459,Male,Loyal Customer,58,Business travel,Eco,102,5,2,2,2,5,5,5,5,1,3,1,1,3,5,0,0.0,satisfied +66674,100447,Female,Loyal Customer,27,Business travel,Eco,1180,1,2,2,2,1,1,1,1,3,2,3,1,4,1,11,12.0,neutral or dissatisfied +66675,26787,Female,Loyal Customer,61,Personal Travel,Eco Plus,1199,2,1,1,4,2,3,4,3,3,1,3,3,3,1,6,0.0,neutral or dissatisfied +66676,35231,Female,disloyal Customer,39,Business travel,Business,944,3,3,3,2,3,3,3,3,5,4,5,1,5,3,0,15.0,neutral or dissatisfied +66677,58475,Female,Loyal Customer,28,Business travel,Business,719,2,4,4,4,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +66678,113324,Male,disloyal Customer,22,Business travel,Business,386,4,0,4,5,1,4,1,1,5,2,4,5,5,1,1,0.0,satisfied +66679,64299,Male,disloyal Customer,29,Business travel,Business,1172,0,0,0,2,1,0,1,1,5,5,5,3,5,1,0,0.0,satisfied +66680,59858,Female,Loyal Customer,29,Business travel,Business,2732,4,4,4,4,2,2,2,2,3,3,5,4,4,2,0,0.0,satisfied +66681,46241,Male,disloyal Customer,45,Business travel,Eco,524,2,3,2,2,3,2,3,3,4,1,2,3,3,3,31,25.0,neutral or dissatisfied +66682,34821,Male,Loyal Customer,46,Personal Travel,Eco,209,2,3,0,2,1,0,1,1,5,4,1,4,1,1,0,0.0,neutral or dissatisfied +66683,74295,Male,Loyal Customer,39,Personal Travel,Eco,2288,3,2,3,3,3,3,4,3,4,5,4,3,4,3,6,0.0,neutral or dissatisfied +66684,118473,Male,Loyal Customer,56,Business travel,Business,325,4,4,4,4,5,5,4,4,4,4,4,3,4,4,6,5.0,satisfied +66685,6217,Male,Loyal Customer,70,Personal Travel,Business,413,2,5,2,3,2,5,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +66686,70880,Male,Loyal Customer,30,Personal Travel,Eco Plus,761,2,4,2,3,2,2,2,2,4,4,2,2,5,2,0,0.0,neutral or dissatisfied +66687,82238,Male,Loyal Customer,55,Personal Travel,Eco,405,1,4,1,1,5,1,2,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +66688,26981,Male,Loyal Customer,58,Business travel,Eco,867,4,5,5,5,4,4,4,4,4,5,3,5,3,4,0,0.0,satisfied +66689,622,Male,Loyal Customer,43,Business travel,Business,229,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +66690,37627,Female,Loyal Customer,68,Personal Travel,Eco,1069,3,4,3,4,2,5,4,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +66691,89630,Female,disloyal Customer,30,Business travel,Eco,944,3,3,3,3,1,3,1,1,2,2,4,3,3,1,0,0.0,neutral or dissatisfied +66692,38636,Male,Loyal Customer,46,Business travel,Business,2611,5,2,5,5,2,5,2,3,3,3,3,4,3,2,15,2.0,satisfied +66693,70323,Female,Loyal Customer,44,Business travel,Business,986,1,1,5,1,3,5,4,3,3,4,3,5,3,3,35,68.0,satisfied +66694,61906,Male,Loyal Customer,58,Business travel,Eco,550,3,5,2,5,3,3,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +66695,121375,Female,Loyal Customer,49,Business travel,Business,2279,3,3,3,3,5,5,5,4,3,3,4,5,5,5,0,6.0,satisfied +66696,64132,Female,Loyal Customer,54,Business travel,Business,989,2,2,2,2,5,4,4,3,3,2,3,3,3,5,0,0.0,satisfied +66697,20794,Female,disloyal Customer,51,Business travel,Eco,508,4,2,3,4,3,3,3,3,1,2,5,2,1,3,4,0.0,satisfied +66698,93914,Male,Loyal Customer,42,Business travel,Business,1697,1,1,1,1,5,5,5,3,3,4,3,5,3,3,59,55.0,satisfied +66699,64888,Female,Loyal Customer,43,Business travel,Business,2795,5,5,5,5,2,5,5,5,5,5,5,3,5,5,0,2.0,satisfied +66700,90894,Male,Loyal Customer,57,Business travel,Eco,406,2,4,2,2,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +66701,25235,Female,Loyal Customer,8,Personal Travel,Eco,919,3,4,3,4,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +66702,88491,Male,Loyal Customer,22,Business travel,Business,1991,2,1,1,1,2,2,2,2,3,1,3,3,3,2,13,18.0,neutral or dissatisfied +66703,97415,Male,Loyal Customer,30,Business travel,Business,1932,1,1,1,1,5,5,5,5,4,4,4,3,5,5,16,31.0,satisfied +66704,72635,Female,Loyal Customer,59,Personal Travel,Eco,929,2,4,2,3,2,5,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +66705,84203,Female,disloyal Customer,28,Business travel,Business,432,1,1,1,4,3,1,3,3,5,5,4,3,5,3,6,39.0,neutral or dissatisfied +66706,80322,Female,Loyal Customer,68,Personal Travel,Eco,746,3,4,2,3,3,5,4,5,5,2,5,4,5,5,0,10.0,neutral or dissatisfied +66707,51807,Female,Loyal Customer,61,Personal Travel,Eco,237,3,5,0,3,3,5,5,5,5,0,5,4,5,3,0,0.0,neutral or dissatisfied +66708,47780,Male,Loyal Customer,39,Business travel,Eco,550,5,2,2,2,5,5,5,5,3,5,3,3,2,5,89,73.0,satisfied +66709,8309,Female,disloyal Customer,24,Business travel,Eco Plus,530,4,4,4,3,3,4,4,3,4,3,4,3,4,3,21,32.0,neutral or dissatisfied +66710,1999,Male,Loyal Customer,48,Personal Travel,Eco,351,3,4,3,2,2,3,2,2,4,4,4,3,4,2,0,3.0,neutral or dissatisfied +66711,86209,Female,Loyal Customer,62,Business travel,Business,306,1,1,1,1,2,2,3,1,1,1,1,2,1,2,10,5.0,neutral or dissatisfied +66712,10564,Male,disloyal Customer,59,Business travel,Eco,429,2,2,2,2,3,2,3,3,1,3,3,3,2,3,19,14.0,neutral or dissatisfied +66713,64653,Female,Loyal Customer,31,Business travel,Business,2931,1,2,2,2,1,1,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +66714,113569,Male,Loyal Customer,52,Business travel,Business,2902,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +66715,90937,Male,disloyal Customer,41,Business travel,Eco,115,5,5,5,5,3,5,1,3,3,5,1,1,1,3,0,0.0,satisfied +66716,93355,Male,disloyal Customer,37,Business travel,Eco,836,1,1,1,1,3,1,3,3,2,3,2,2,2,3,78,60.0,neutral or dissatisfied +66717,86150,Male,Loyal Customer,41,Business travel,Eco,226,3,2,2,2,3,3,3,3,4,2,4,2,4,3,3,0.0,neutral or dissatisfied +66718,123640,Male,Loyal Customer,56,Business travel,Business,2414,5,5,5,5,4,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +66719,16374,Male,Loyal Customer,36,Business travel,Eco,1215,4,4,4,4,4,4,4,4,4,4,2,5,2,4,0,0.0,satisfied +66720,14354,Female,disloyal Customer,23,Business travel,Eco Plus,429,4,5,4,4,2,4,2,2,3,5,3,4,1,2,0,0.0,neutral or dissatisfied +66721,42575,Male,Loyal Customer,47,Business travel,Business,240,4,2,2,2,2,3,2,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +66722,103684,Female,Loyal Customer,47,Business travel,Business,3959,2,4,4,4,3,3,4,2,2,2,2,1,2,1,19,16.0,neutral or dissatisfied +66723,30653,Female,Loyal Customer,49,Personal Travel,Eco,533,2,4,2,2,4,4,5,5,5,2,5,3,5,4,0,3.0,neutral or dissatisfied +66724,40685,Male,disloyal Customer,24,Business travel,Eco,584,5,0,5,1,1,5,1,1,4,4,5,3,3,1,2,0.0,satisfied +66725,31790,Male,Loyal Customer,14,Business travel,Eco,2677,4,3,3,3,4,5,4,3,1,3,2,4,1,4,12,65.0,satisfied +66726,115044,Male,Loyal Customer,25,Business travel,Business,372,4,4,4,4,4,4,4,4,1,5,3,3,4,4,11,4.0,neutral or dissatisfied +66727,3662,Female,Loyal Customer,47,Business travel,Business,3376,2,2,5,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +66728,98643,Male,Loyal Customer,39,Business travel,Eco,834,2,4,4,4,2,2,2,2,3,4,2,3,2,2,13,8.0,neutral or dissatisfied +66729,92384,Female,Loyal Customer,28,Business travel,Business,1947,1,1,3,1,4,4,4,4,4,3,3,3,5,4,0,5.0,satisfied +66730,54435,Female,Loyal Customer,14,Personal Travel,Eco,305,4,5,4,2,3,4,3,3,4,5,4,2,1,3,0,0.0,neutral or dissatisfied +66731,50847,Female,Loyal Customer,60,Personal Travel,Eco,109,4,4,4,3,5,5,5,3,3,4,3,5,3,3,0,0.0,neutral or dissatisfied +66732,31425,Male,Loyal Customer,9,Personal Travel,Eco,1546,1,4,2,2,3,2,3,3,5,5,3,5,4,3,0,0.0,neutral or dissatisfied +66733,84163,Female,Loyal Customer,26,Personal Travel,Eco,503,3,5,3,1,5,3,5,5,5,3,5,3,4,5,36,39.0,neutral or dissatisfied +66734,104507,Female,disloyal Customer,27,Business travel,Eco,1009,4,4,4,3,3,4,1,3,2,4,1,4,1,3,0,4.0,satisfied +66735,109747,Female,Loyal Customer,15,Personal Travel,Eco,587,3,2,3,3,1,3,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +66736,44560,Female,Loyal Customer,70,Personal Travel,Eco Plus,157,3,3,3,3,1,3,4,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +66737,91935,Female,Loyal Customer,30,Business travel,Business,2475,2,1,3,1,2,2,2,4,2,4,4,2,1,2,748,720.0,neutral or dissatisfied +66738,3284,Male,Loyal Customer,60,Personal Travel,Eco,419,3,4,3,3,3,1,1,1,5,4,1,1,2,1,209,256.0,neutral or dissatisfied +66739,38940,Female,Loyal Customer,42,Personal Travel,Eco,162,2,4,2,5,4,4,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +66740,112160,Female,Loyal Customer,25,Business travel,Business,895,1,3,1,1,1,1,1,1,3,4,4,4,3,1,38,34.0,neutral or dissatisfied +66741,24760,Male,Loyal Customer,43,Business travel,Eco,447,3,2,2,2,3,3,3,3,4,2,5,3,1,3,0,7.0,satisfied +66742,39700,Male,disloyal Customer,35,Business travel,Eco,410,3,5,2,2,5,2,1,5,3,3,1,2,2,5,9,4.0,neutral or dissatisfied +66743,4284,Female,Loyal Customer,40,Personal Travel,Eco,502,2,5,2,1,4,2,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +66744,106392,Female,Loyal Customer,58,Business travel,Eco,674,3,4,4,4,3,3,3,4,4,3,4,4,4,3,14,18.0,neutral or dissatisfied +66745,45224,Female,Loyal Customer,42,Business travel,Business,2874,4,4,4,4,1,4,4,5,5,5,5,3,5,2,2,0.0,satisfied +66746,55243,Male,Loyal Customer,10,Personal Travel,Eco,1009,3,4,3,2,1,3,1,1,1,4,1,2,2,1,10,0.0,neutral or dissatisfied +66747,26807,Female,Loyal Customer,27,Personal Travel,Eco,2139,1,5,1,5,5,1,5,5,4,3,3,3,5,5,34,3.0,neutral or dissatisfied +66748,7758,Female,disloyal Customer,21,Business travel,Business,1013,0,0,0,5,2,0,2,2,5,2,4,4,4,2,17,20.0,satisfied +66749,34833,Female,Loyal Customer,53,Business travel,Eco Plus,209,4,4,4,4,2,3,1,4,4,4,4,3,4,4,0,0.0,satisfied +66750,80408,Male,Loyal Customer,63,Personal Travel,Eco,1416,3,3,2,3,2,2,2,2,2,2,5,4,4,2,0,0.0,neutral or dissatisfied +66751,74959,Male,Loyal Customer,23,Business travel,Business,2831,3,1,3,1,3,3,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +66752,67876,Male,Loyal Customer,62,Personal Travel,Eco,1235,2,3,3,3,4,3,2,4,3,3,2,1,4,4,57,50.0,neutral or dissatisfied +66753,114124,Male,Loyal Customer,43,Business travel,Business,2804,2,2,5,2,3,4,5,5,5,5,5,3,5,4,3,3.0,satisfied +66754,106687,Male,Loyal Customer,27,Business travel,Business,516,3,3,3,3,5,5,5,5,4,5,4,5,5,5,92,88.0,satisfied +66755,108317,Male,disloyal Customer,44,Business travel,Business,1844,3,3,3,1,4,3,1,4,5,2,4,3,5,4,15,0.0,neutral or dissatisfied +66756,99766,Male,Loyal Customer,27,Personal Travel,Eco,255,4,4,4,4,4,4,4,4,5,4,1,1,1,4,39,43.0,neutral or dissatisfied +66757,27982,Male,Loyal Customer,39,Business travel,Eco,2350,5,3,3,3,5,5,5,5,2,3,5,4,2,5,0,0.0,satisfied +66758,54230,Male,Loyal Customer,40,Business travel,Business,3907,4,4,4,4,5,1,1,4,4,4,4,4,4,2,0,1.0,satisfied +66759,63661,Male,disloyal Customer,44,Business travel,Eco,1409,4,4,4,3,3,4,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +66760,38682,Female,disloyal Customer,33,Business travel,Eco Plus,2704,2,2,2,5,5,2,5,5,5,2,4,3,4,5,40,44.0,neutral or dissatisfied +66761,48453,Female,Loyal Customer,41,Business travel,Business,3517,4,4,4,4,4,5,4,4,4,4,4,3,4,3,8,0.0,satisfied +66762,17568,Male,disloyal Customer,35,Business travel,Eco,1034,4,3,3,3,2,3,2,2,2,4,3,3,4,2,31,29.0,neutral or dissatisfied +66763,120725,Female,Loyal Customer,63,Personal Travel,Eco,90,4,5,0,5,2,2,2,4,4,0,4,2,4,3,2,0.0,satisfied +66764,106635,Female,Loyal Customer,42,Personal Travel,Eco,306,4,5,4,4,5,4,5,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +66765,64433,Male,disloyal Customer,42,Business travel,Business,989,2,3,3,4,2,2,2,2,4,2,4,3,4,2,4,6.0,neutral or dissatisfied +66766,24776,Female,Loyal Customer,50,Business travel,Business,432,1,2,2,2,5,4,3,1,1,1,1,1,1,1,2,26.0,neutral or dissatisfied +66767,29963,Female,disloyal Customer,23,Business travel,Eco,95,3,4,3,2,2,3,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +66768,106382,Female,Loyal Customer,49,Business travel,Business,3587,5,5,5,5,4,4,5,5,5,5,5,3,5,5,5,0.0,satisfied +66769,84695,Female,disloyal Customer,26,Business travel,Business,2182,2,2,2,3,4,2,4,4,4,4,3,5,5,4,0,0.0,neutral or dissatisfied +66770,21479,Male,Loyal Customer,38,Business travel,Business,164,2,5,5,5,4,3,4,3,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +66771,98126,Male,Loyal Customer,46,Personal Travel,Eco,472,1,3,1,1,4,1,4,4,3,1,2,2,1,4,14,5.0,neutral or dissatisfied +66772,30377,Male,Loyal Customer,42,Business travel,Eco,641,2,5,3,5,2,2,2,2,3,3,4,4,4,2,40,34.0,neutral or dissatisfied +66773,50755,Female,Loyal Customer,47,Personal Travel,Eco,156,1,4,1,3,5,4,5,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +66774,79991,Male,Loyal Customer,37,Personal Travel,Eco,950,2,2,2,3,4,2,4,4,2,1,3,1,3,4,0,0.0,neutral or dissatisfied +66775,89465,Female,Loyal Customer,58,Business travel,Business,134,1,1,1,1,4,5,5,4,4,4,5,5,4,4,17,17.0,satisfied +66776,27002,Female,Loyal Customer,36,Business travel,Eco,867,3,4,4,4,3,4,3,3,2,1,5,2,3,3,0,3.0,satisfied +66777,24406,Male,Loyal Customer,31,Business travel,Business,3874,5,5,2,5,3,3,3,3,4,5,5,1,1,3,4,13.0,satisfied +66778,79946,Female,Loyal Customer,64,Business travel,Business,1010,1,3,3,3,1,1,1,4,5,3,4,1,2,1,118,194.0,neutral or dissatisfied +66779,84263,Male,Loyal Customer,57,Business travel,Business,334,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,3.0,satisfied +66780,53262,Male,Loyal Customer,59,Business travel,Business,2021,3,3,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +66781,61347,Female,Loyal Customer,45,Business travel,Business,602,1,1,1,1,5,4,4,4,4,4,4,5,4,5,5,4.0,satisfied +66782,68284,Male,Loyal Customer,57,Business travel,Business,806,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +66783,110090,Female,disloyal Customer,36,Business travel,Business,882,2,2,2,3,4,2,4,4,4,2,5,4,5,4,23,19.0,neutral or dissatisfied +66784,117605,Female,Loyal Customer,43,Business travel,Eco,843,4,2,2,2,1,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +66785,59650,Male,disloyal Customer,17,Business travel,Eco,965,3,2,2,4,5,2,5,5,1,5,4,3,3,5,18,22.0,neutral or dissatisfied +66786,86714,Female,disloyal Customer,17,Business travel,Business,1747,4,0,4,4,1,4,1,1,3,2,4,4,5,1,0,0.0,satisfied +66787,27015,Female,Loyal Customer,56,Personal Travel,Eco,867,3,5,3,2,3,3,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +66788,78295,Male,Loyal Customer,50,Personal Travel,Eco,1598,1,5,1,1,3,1,3,3,4,2,3,5,4,3,0,0.0,neutral or dissatisfied +66789,12649,Female,Loyal Customer,47,Personal Travel,Eco,844,2,5,3,3,2,5,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +66790,105050,Male,Loyal Customer,33,Personal Travel,Eco,255,2,1,2,3,2,2,2,2,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +66791,6696,Female,Loyal Customer,37,Business travel,Eco,258,1,2,2,2,1,1,1,1,3,3,4,2,3,1,15,15.0,neutral or dissatisfied +66792,44608,Male,disloyal Customer,24,Business travel,Eco,566,4,1,4,2,5,4,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +66793,117865,Female,Loyal Customer,63,Personal Travel,Business,365,3,5,3,2,3,5,5,4,2,4,5,5,3,5,174,188.0,neutral or dissatisfied +66794,36436,Female,Loyal Customer,39,Personal Travel,Eco,369,5,3,5,3,5,5,5,5,2,4,3,3,3,5,0,0.0,satisfied +66795,55747,Male,disloyal Customer,36,Business travel,Business,1737,1,1,1,3,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +66796,54497,Male,Loyal Customer,57,Business travel,Business,2590,1,4,4,4,2,3,3,1,1,1,1,1,1,4,66,62.0,neutral or dissatisfied +66797,59425,Female,Loyal Customer,47,Business travel,Business,2556,3,3,4,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +66798,71286,Male,Loyal Customer,55,Business travel,Business,733,1,1,5,1,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +66799,9869,Female,Loyal Customer,57,Business travel,Eco Plus,531,3,1,1,1,4,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +66800,2188,Male,disloyal Customer,34,Business travel,Eco,624,3,0,3,1,2,3,2,2,4,4,1,2,2,2,0,0.0,neutral or dissatisfied +66801,38083,Female,Loyal Customer,48,Business travel,Business,1220,5,5,5,5,2,1,2,5,5,5,5,3,5,4,0,0.0,satisfied +66802,97271,Male,Loyal Customer,59,Business travel,Business,3570,0,0,0,2,2,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +66803,51363,Male,Loyal Customer,37,Business travel,Eco Plus,110,4,3,4,3,4,4,4,4,1,4,4,5,4,4,0,0.0,satisfied +66804,126998,Male,Loyal Customer,41,Business travel,Business,1768,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +66805,6022,Male,Loyal Customer,22,Business travel,Business,630,2,2,2,2,2,2,2,2,3,5,3,2,4,2,6,23.0,neutral or dissatisfied +66806,54372,Female,disloyal Customer,38,Business travel,Business,305,2,2,2,3,1,2,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +66807,101732,Female,Loyal Customer,44,Personal Travel,Eco,1216,1,3,1,3,1,2,3,5,5,1,5,1,5,1,23,0.0,neutral or dissatisfied +66808,23731,Female,Loyal Customer,50,Business travel,Eco,771,4,2,2,2,3,3,4,4,4,4,4,2,4,3,66,125.0,satisfied +66809,12256,Female,Loyal Customer,66,Business travel,Business,3393,1,1,1,1,3,2,2,4,4,4,4,2,4,4,0,0.0,satisfied +66810,116383,Male,Loyal Customer,23,Personal Travel,Eco,325,1,2,1,4,2,1,2,2,1,2,3,3,3,2,34,18.0,neutral or dissatisfied +66811,80412,Male,Loyal Customer,40,Business travel,Business,2248,4,4,4,4,2,3,5,5,5,5,5,3,5,4,0,5.0,satisfied +66812,65985,Male,Loyal Customer,55,Personal Travel,Eco,1372,4,5,4,3,4,4,2,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +66813,86191,Female,Loyal Customer,46,Business travel,Business,3109,2,2,2,2,5,2,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +66814,31834,Female,Loyal Customer,48,Personal Travel,Eco,2762,5,0,5,3,5,2,2,2,1,4,5,2,3,2,0,16.0,satisfied +66815,61719,Female,Loyal Customer,40,Business travel,Business,1464,4,4,4,4,5,5,5,4,4,3,4,3,4,4,0,0.0,satisfied +66816,3000,Female,Loyal Customer,44,Business travel,Business,3357,1,1,1,1,3,4,5,4,4,4,4,5,4,3,7,10.0,satisfied +66817,117255,Female,Loyal Customer,49,Personal Travel,Eco,646,2,4,2,4,2,4,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +66818,75224,Male,disloyal Customer,72,Business travel,Eco,244,1,2,1,3,3,1,2,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +66819,16813,Male,Loyal Customer,15,Business travel,Business,2730,1,3,5,5,1,1,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +66820,129292,Female,Loyal Customer,66,Personal Travel,Eco,550,2,0,2,1,3,5,4,4,4,2,4,3,4,5,3,1.0,neutral or dissatisfied +66821,126388,Male,Loyal Customer,50,Personal Travel,Eco,600,4,2,4,4,1,4,4,1,3,2,3,3,4,1,0,0.0,satisfied +66822,14491,Male,Loyal Customer,49,Personal Travel,Eco,541,1,5,1,1,4,1,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +66823,21156,Female,disloyal Customer,25,Business travel,Eco,954,3,3,3,4,5,3,5,5,4,5,4,4,3,5,20,0.0,neutral or dissatisfied +66824,3158,Male,Loyal Customer,44,Business travel,Business,2408,4,4,4,4,3,4,5,3,3,4,3,3,3,5,0,4.0,satisfied +66825,68262,Male,Loyal Customer,25,Personal Travel,Eco,432,2,2,2,2,2,2,3,2,3,2,3,2,3,2,80,92.0,neutral or dissatisfied +66826,74819,Male,Loyal Customer,21,Personal Travel,Eco Plus,1235,1,1,0,3,4,0,4,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +66827,24746,Female,disloyal Customer,50,Business travel,Eco,528,3,0,3,4,2,3,3,2,3,4,2,4,1,2,0,0.0,neutral or dissatisfied +66828,37249,Male,Loyal Customer,11,Personal Travel,Business,950,3,3,3,2,4,3,4,4,1,1,4,1,2,4,95,,neutral or dissatisfied +66829,105855,Male,Loyal Customer,21,Business travel,Business,1975,5,5,5,5,5,4,5,5,5,5,4,4,4,5,119,104.0,satisfied +66830,5632,Female,Loyal Customer,43,Business travel,Business,2341,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,17.0,satisfied +66831,114022,Female,disloyal Customer,25,Business travel,Eco Plus,1728,3,2,3,2,3,3,3,3,4,2,2,1,2,3,0,0.0,neutral or dissatisfied +66832,29236,Male,Loyal Customer,23,Business travel,Business,1921,2,2,2,2,4,4,4,4,3,2,4,4,2,4,0,0.0,satisfied +66833,31051,Female,Loyal Customer,31,Business travel,Business,3370,3,1,1,1,3,3,3,3,2,1,2,2,2,3,56,50.0,neutral or dissatisfied +66834,109197,Female,disloyal Customer,20,Business travel,Eco,612,0,0,0,4,2,0,2,2,3,4,5,5,5,2,2,3.0,satisfied +66835,62079,Male,Loyal Customer,51,Business travel,Business,2475,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,10.0,satisfied +66836,86164,Female,disloyal Customer,22,Business travel,Eco,356,1,1,1,4,1,1,1,1,3,4,3,2,4,1,26,9.0,neutral or dissatisfied +66837,126002,Female,disloyal Customer,25,Business travel,Business,600,3,0,3,1,5,3,4,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +66838,78991,Male,Loyal Customer,54,Business travel,Business,377,3,3,5,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +66839,64764,Female,disloyal Customer,59,Business travel,Business,190,2,2,2,2,5,2,1,5,3,3,4,3,4,5,55,74.0,neutral or dissatisfied +66840,42738,Male,Loyal Customer,34,Personal Travel,Eco,536,1,4,1,3,2,1,5,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +66841,27445,Male,Loyal Customer,44,Business travel,Business,2823,4,4,4,4,4,4,3,4,4,3,4,3,4,3,0,0.0,satisfied +66842,74491,Female,Loyal Customer,49,Business travel,Business,1464,3,1,3,3,3,4,5,4,4,4,4,4,4,4,4,0.0,satisfied +66843,11148,Female,Loyal Customer,66,Personal Travel,Eco,308,2,3,2,1,4,4,3,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +66844,124260,Male,Loyal Customer,44,Personal Travel,Eco Plus,1916,2,4,3,3,4,3,3,4,1,2,5,4,5,4,0,0.0,neutral or dissatisfied +66845,53271,Female,Loyal Customer,50,Business travel,Business,2002,1,1,1,1,5,1,1,5,5,5,5,1,5,4,0,6.0,satisfied +66846,69191,Female,Loyal Customer,20,Personal Travel,Eco,187,4,4,4,2,1,4,1,1,4,3,5,3,4,1,0,0.0,satisfied +66847,90763,Female,Loyal Customer,42,Business travel,Business,3264,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +66848,103253,Male,Loyal Customer,53,Business travel,Business,667,3,2,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +66849,28766,Female,Loyal Customer,34,Personal Travel,Eco,1024,3,3,3,4,5,3,5,5,2,5,3,1,5,5,0,0.0,neutral or dissatisfied +66850,81820,Female,Loyal Customer,39,Business travel,Eco,1016,4,5,5,5,4,4,4,4,4,2,3,2,3,4,0,0.0,satisfied +66851,123501,Female,disloyal Customer,63,Business travel,Eco,796,2,2,2,3,2,4,3,3,4,3,3,3,3,3,57,62.0,neutral or dissatisfied +66852,28528,Male,Loyal Customer,44,Business travel,Business,2677,2,2,2,2,2,3,4,5,5,5,5,1,5,2,0,0.0,satisfied +66853,116611,Female,Loyal Customer,43,Business travel,Business,3681,1,1,2,1,3,4,5,4,4,5,4,3,4,5,14,10.0,satisfied +66854,83985,Male,Loyal Customer,54,Business travel,Business,321,3,4,4,4,5,3,3,3,3,3,3,4,3,4,0,3.0,neutral or dissatisfied +66855,76120,Male,Loyal Customer,41,Business travel,Business,546,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +66856,17229,Male,disloyal Customer,39,Business travel,Eco,872,1,0,0,1,2,0,2,2,3,5,3,5,5,2,18,36.0,neutral or dissatisfied +66857,42029,Male,Loyal Customer,44,Business travel,Business,116,3,3,3,3,4,4,1,5,5,5,5,5,5,4,16,25.0,satisfied +66858,128844,Male,Loyal Customer,36,Personal Travel,Eco,2475,4,4,4,3,4,3,3,1,4,4,4,3,3,3,32,32.0,neutral or dissatisfied +66859,125554,Female,disloyal Customer,25,Business travel,Business,226,0,0,0,1,1,0,1,1,4,2,5,4,5,1,0,0.0,satisfied +66860,16461,Female,Loyal Customer,52,Personal Travel,Eco,529,1,3,1,3,4,4,4,1,1,1,4,3,1,4,42,28.0,neutral or dissatisfied +66861,49926,Female,Loyal Customer,43,Business travel,Business,1999,0,5,0,1,3,2,5,2,2,2,2,2,2,4,4,22.0,satisfied +66862,23605,Male,Loyal Customer,45,Personal Travel,Eco,589,4,4,4,2,5,4,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +66863,20846,Male,Loyal Customer,55,Personal Travel,Eco,457,5,5,5,3,1,5,1,1,4,2,5,2,4,1,0,3.0,satisfied +66864,88931,Male,Loyal Customer,57,Business travel,Business,3123,5,5,5,5,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +66865,56860,Male,disloyal Customer,23,Business travel,Eco,2454,3,3,3,1,3,2,3,5,5,4,4,3,3,3,3,24.0,neutral or dissatisfied +66866,76214,Male,Loyal Customer,51,Business travel,Business,2179,5,5,2,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +66867,71892,Female,Loyal Customer,61,Personal Travel,Eco,1744,4,2,4,3,1,4,4,5,5,4,5,2,5,1,96,91.0,neutral or dissatisfied +66868,68186,Female,Loyal Customer,17,Personal Travel,Eco,597,3,0,3,3,4,3,4,4,2,1,4,1,1,4,0,0.0,neutral or dissatisfied +66869,122097,Male,Loyal Customer,68,Personal Travel,Eco,130,1,5,1,1,4,1,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +66870,118844,Male,Loyal Customer,69,Business travel,Eco Plus,251,4,4,2,4,4,4,4,4,4,1,3,1,4,4,0,0.0,neutral or dissatisfied +66871,24025,Male,Loyal Customer,53,Business travel,Eco,595,2,5,5,5,2,2,2,2,1,5,3,3,4,2,14,42.0,neutral or dissatisfied +66872,128147,Female,Loyal Customer,53,Business travel,Business,1849,3,3,3,3,2,4,4,3,3,4,3,4,3,4,0,6.0,satisfied +66873,8615,Male,Loyal Customer,45,Personal Travel,Eco,1371,2,5,2,2,5,2,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +66874,82562,Female,Loyal Customer,48,Business travel,Business,3924,3,3,3,3,3,5,5,5,5,5,5,5,5,3,61,45.0,satisfied +66875,72826,Female,Loyal Customer,43,Business travel,Eco,1013,1,2,2,2,2,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +66876,108146,Male,Loyal Customer,36,Business travel,Business,1712,1,1,1,1,3,3,1,5,5,5,5,4,5,4,0,0.0,satisfied +66877,112224,Male,Loyal Customer,25,Personal Travel,Eco,1199,2,1,2,4,1,2,1,1,4,4,3,4,3,1,27,64.0,neutral or dissatisfied +66878,90136,Male,Loyal Customer,21,Business travel,Business,1910,5,5,5,5,3,4,3,3,5,3,4,5,4,3,0,0.0,satisfied +66879,115697,Male,disloyal Customer,26,Business travel,Eco,337,2,1,2,2,1,2,1,1,4,3,2,3,3,1,1,0.0,neutral or dissatisfied +66880,119314,Male,Loyal Customer,35,Business travel,Business,2613,4,2,3,2,1,4,4,1,1,1,4,1,1,1,78,62.0,neutral or dissatisfied +66881,66752,Female,disloyal Customer,51,Personal Travel,Eco,978,3,5,3,2,5,3,5,5,5,2,5,3,4,5,2,20.0,neutral or dissatisfied +66882,25001,Female,Loyal Customer,24,Personal Travel,Eco,484,3,0,3,5,3,3,3,3,4,5,4,3,4,3,20,0.0,neutral or dissatisfied +66883,55550,Female,Loyal Customer,23,Personal Travel,Eco,550,1,1,1,3,2,1,2,2,2,3,4,3,4,2,31,24.0,neutral or dissatisfied +66884,11725,Female,disloyal Customer,23,Business travel,Business,429,0,0,0,5,2,0,1,2,3,3,4,3,5,2,2,3.0,satisfied +66885,57352,Male,Loyal Customer,33,Business travel,Business,3600,2,2,4,2,5,5,5,5,4,4,1,3,5,5,0,0.0,satisfied +66886,129789,Male,Loyal Customer,44,Personal Travel,Eco,308,2,4,2,3,3,2,1,3,3,3,5,3,5,3,6,0.0,neutral or dissatisfied +66887,92419,Female,Loyal Customer,50,Business travel,Business,1947,3,3,3,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +66888,86543,Female,Loyal Customer,58,Personal Travel,Eco,853,3,3,3,2,4,5,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +66889,21650,Female,disloyal Customer,20,Business travel,Business,746,4,3,4,3,5,4,1,5,4,5,4,5,5,5,16,0.0,satisfied +66890,118835,Male,Loyal Customer,28,Business travel,Eco Plus,647,1,1,1,1,1,1,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +66891,105560,Female,Loyal Customer,36,Personal Travel,Business,577,4,5,4,1,4,5,4,1,1,4,1,5,1,4,0,6.0,neutral or dissatisfied +66892,117883,Female,Loyal Customer,40,Business travel,Business,2110,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +66893,53835,Female,Loyal Customer,67,Business travel,Business,2796,2,1,1,1,1,3,3,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +66894,116018,Male,Loyal Customer,7,Personal Travel,Eco,308,2,5,2,5,5,2,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +66895,34084,Male,disloyal Customer,27,Business travel,Eco,1059,2,2,2,3,2,2,2,2,5,3,5,5,5,2,41,60.0,neutral or dissatisfied +66896,40722,Male,disloyal Customer,23,Business travel,Eco,558,0,0,0,3,3,0,3,3,4,4,1,4,3,3,0,0.0,satisfied +66897,5348,Male,disloyal Customer,25,Business travel,Business,812,3,0,3,1,1,3,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +66898,6600,Female,Loyal Customer,45,Personal Travel,Eco,618,2,5,2,2,3,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +66899,60605,Female,Loyal Customer,52,Business travel,Business,991,3,3,3,3,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +66900,25241,Female,Loyal Customer,69,Personal Travel,Eco,919,3,5,3,4,2,5,5,5,5,3,5,3,5,4,72,55.0,neutral or dissatisfied +66901,90076,Male,disloyal Customer,26,Business travel,Business,1084,4,4,4,1,2,4,2,2,5,4,5,5,4,2,3,16.0,satisfied +66902,117310,Male,Loyal Customer,55,Business travel,Eco Plus,338,4,5,5,5,4,4,4,4,4,1,5,3,3,4,0,0.0,satisfied +66903,47840,Male,disloyal Customer,28,Business travel,Eco,834,3,3,3,3,2,3,2,2,4,1,3,2,4,2,0,1.0,neutral or dissatisfied +66904,34846,Male,Loyal Customer,8,Personal Travel,Eco Plus,264,3,3,3,4,4,3,4,4,2,5,4,3,2,4,0,0.0,neutral or dissatisfied +66905,28295,Female,Loyal Customer,44,Business travel,Eco,867,4,4,4,4,1,4,5,4,4,4,4,3,4,4,0,3.0,satisfied +66906,8013,Female,disloyal Customer,37,Business travel,Business,125,3,3,3,3,5,3,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +66907,107281,Male,Loyal Customer,60,Business travel,Eco,283,3,1,1,1,3,3,3,3,4,3,4,4,3,3,42,32.0,neutral or dissatisfied +66908,39782,Male,Loyal Customer,49,Business travel,Eco Plus,546,4,3,3,3,4,4,4,4,2,5,3,3,4,4,0,0.0,satisfied +66909,45216,Male,Loyal Customer,57,Business travel,Business,911,3,3,3,3,5,2,5,4,4,4,4,5,4,3,5,0.0,satisfied +66910,84458,Female,Loyal Customer,42,Business travel,Business,290,0,0,0,3,5,3,3,2,2,2,2,5,2,1,0,0.0,satisfied +66911,20849,Male,Loyal Customer,62,Personal Travel,Eco,534,1,4,1,3,1,1,4,1,5,4,4,5,5,1,7,0.0,neutral or dissatisfied +66912,37973,Female,Loyal Customer,51,Business travel,Business,1010,1,4,4,4,3,4,3,1,1,1,1,3,1,2,35,28.0,neutral or dissatisfied +66913,64328,Male,Loyal Customer,29,Business travel,Eco,1192,1,3,4,3,1,1,1,1,3,4,4,4,4,1,23,20.0,neutral or dissatisfied +66914,92410,Female,Loyal Customer,59,Business travel,Business,1947,4,4,4,4,5,3,4,4,4,4,4,3,4,3,46,75.0,satisfied +66915,27018,Female,Loyal Customer,20,Personal Travel,Eco,867,4,5,3,3,2,3,4,2,5,4,5,1,2,2,0,3.0,neutral or dissatisfied +66916,101382,Female,Loyal Customer,38,Business travel,Business,486,1,1,2,1,2,4,4,5,5,5,5,5,5,4,11,2.0,satisfied +66917,23652,Female,Loyal Customer,13,Personal Travel,Business,251,1,2,0,4,1,0,1,1,3,5,3,4,3,1,4,0.0,neutral or dissatisfied +66918,105827,Female,Loyal Customer,51,Personal Travel,Eco,919,2,4,3,1,3,4,5,4,4,3,4,4,4,5,4,8.0,neutral or dissatisfied +66919,63421,Female,Loyal Customer,70,Personal Travel,Eco,447,3,5,3,5,3,5,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +66920,116914,Female,disloyal Customer,21,Business travel,Eco,325,5,0,4,2,5,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +66921,5180,Male,disloyal Customer,22,Business travel,Business,293,0,5,1,1,5,1,5,5,3,2,5,3,4,5,12,3.0,satisfied +66922,23380,Male,Loyal Customer,53,Business travel,Eco Plus,1014,4,3,3,3,4,4,4,4,4,4,2,5,2,4,39,38.0,satisfied +66923,110253,Male,Loyal Customer,34,Business travel,Business,1024,4,4,4,4,2,5,4,3,3,4,3,5,3,5,39,41.0,satisfied +66924,112013,Male,disloyal Customer,43,Business travel,Business,680,2,2,2,1,3,2,5,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +66925,46804,Female,Loyal Customer,32,Business travel,Business,2213,3,3,3,3,2,2,2,2,3,5,2,5,4,2,6,0.0,satisfied +66926,101812,Male,Loyal Customer,42,Business travel,Eco,1521,2,1,1,1,2,2,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +66927,32189,Female,Loyal Customer,46,Business travel,Eco,102,4,4,4,4,4,5,3,4,4,4,4,3,4,1,0,1.0,satisfied +66928,32930,Male,Loyal Customer,32,Personal Travel,Eco,163,3,3,3,3,5,3,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +66929,17787,Female,Loyal Customer,23,Business travel,Business,1629,2,2,2,2,3,3,3,3,2,5,1,2,1,3,5,12.0,satisfied +66930,15790,Male,Loyal Customer,38,Personal Travel,Eco Plus,254,1,3,0,2,2,0,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +66931,1641,Male,Loyal Customer,48,Business travel,Business,1533,1,1,4,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +66932,27456,Female,disloyal Customer,30,Business travel,Eco,671,3,3,3,1,4,3,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +66933,17149,Female,Loyal Customer,31,Business travel,Business,696,3,3,3,3,4,4,4,4,3,3,3,2,2,4,0,0.0,satisfied +66934,94205,Female,disloyal Customer,33,Business travel,Business,562,2,2,2,2,5,2,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +66935,46259,Male,Loyal Customer,8,Personal Travel,Eco,455,1,4,1,4,4,1,4,4,5,2,4,4,4,4,15,8.0,neutral or dissatisfied +66936,126557,Male,Loyal Customer,35,Personal Travel,Eco,644,3,5,3,5,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +66937,16910,Female,Loyal Customer,14,Personal Travel,Eco,746,1,4,1,5,2,1,2,2,4,5,5,4,5,2,116,126.0,neutral or dissatisfied +66938,29981,Female,Loyal Customer,55,Business travel,Eco,234,3,4,4,4,5,2,1,3,3,3,3,1,3,5,61,,satisfied +66939,14385,Male,Loyal Customer,28,Business travel,Eco,900,4,1,1,1,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +66940,8368,Female,Loyal Customer,45,Business travel,Business,722,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +66941,21085,Male,Loyal Customer,47,Business travel,Business,2629,2,2,2,2,5,3,3,5,5,5,3,5,5,3,0,0.0,satisfied +66942,104908,Female,Loyal Customer,54,Personal Travel,Eco,1565,4,4,5,3,2,4,5,1,1,5,1,3,1,5,17,29.0,neutral or dissatisfied +66943,78009,Female,disloyal Customer,27,Business travel,Business,214,2,1,1,2,4,1,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +66944,127619,Male,Loyal Customer,41,Business travel,Business,1773,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,6.0,satisfied +66945,119009,Male,Loyal Customer,34,Personal Travel,Eco,459,1,5,1,2,3,1,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +66946,43770,Male,Loyal Customer,44,Business travel,Eco,546,2,5,5,5,3,2,3,3,1,5,3,3,4,3,12,2.0,neutral or dissatisfied +66947,116810,Female,Loyal Customer,58,Business travel,Business,2850,3,5,3,3,2,4,4,2,2,2,2,3,2,4,15,12.0,satisfied +66948,120206,Female,disloyal Customer,22,Business travel,Eco,1325,3,3,3,1,4,3,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +66949,38841,Male,Loyal Customer,25,Business travel,Eco Plus,353,4,1,1,1,4,4,4,4,3,4,5,2,5,4,0,0.0,satisfied +66950,50942,Male,Loyal Customer,19,Personal Travel,Eco,109,3,4,3,2,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +66951,60287,Female,disloyal Customer,44,Business travel,Business,783,3,3,3,4,4,3,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +66952,10802,Female,Loyal Customer,36,Business travel,Business,396,2,4,4,4,2,4,3,2,2,2,2,4,2,4,87,83.0,neutral or dissatisfied +66953,125230,Female,disloyal Customer,23,Business travel,Eco,1149,3,3,3,2,1,3,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +66954,57443,Female,Loyal Customer,35,Business travel,Business,1660,4,5,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +66955,48410,Female,Loyal Customer,44,Business travel,Business,1842,1,5,5,5,1,3,3,1,1,1,1,1,1,2,6,0.0,neutral or dissatisfied +66956,70377,Female,Loyal Customer,59,Business travel,Business,1562,3,3,3,3,5,5,4,5,5,4,5,4,5,4,2,0.0,satisfied +66957,57678,Male,Loyal Customer,39,Business travel,Business,1956,4,4,3,4,3,4,4,3,3,3,3,5,3,5,5,0.0,satisfied +66958,125080,Male,Loyal Customer,51,Business travel,Business,361,3,3,3,3,5,4,4,4,4,4,4,5,4,4,1,0.0,satisfied +66959,17335,Male,Loyal Customer,54,Business travel,Eco,563,5,4,4,4,5,5,5,5,4,2,3,4,4,5,27,63.0,satisfied +66960,92900,Female,Loyal Customer,57,Business travel,Business,2182,4,4,4,4,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +66961,7675,Female,Loyal Customer,42,Business travel,Eco,604,2,4,4,4,3,2,1,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +66962,102951,Female,Loyal Customer,25,Business travel,Business,3380,3,4,4,4,3,3,3,3,1,5,2,4,2,3,18,12.0,neutral or dissatisfied +66963,64369,Male,Loyal Customer,29,Personal Travel,Eco,1192,2,4,2,5,3,2,1,3,1,1,5,5,2,3,54,43.0,neutral or dissatisfied +66964,35284,Female,Loyal Customer,27,Business travel,Business,1074,1,1,1,1,5,5,5,5,1,4,3,1,4,5,0,0.0,satisfied +66965,124978,Female,Loyal Customer,47,Business travel,Business,184,1,1,1,1,3,4,5,4,4,4,5,5,4,3,4,0.0,satisfied +66966,58360,Male,Loyal Customer,41,Personal Travel,Eco,646,4,4,4,3,2,4,2,2,1,4,4,1,4,2,0,0.0,satisfied +66967,92847,Male,Loyal Customer,54,Business travel,Business,1587,5,5,5,5,5,5,5,4,4,4,4,5,4,4,26,33.0,satisfied +66968,103342,Male,Loyal Customer,58,Personal Travel,Eco,1139,2,3,2,2,1,2,1,1,3,1,5,4,1,1,0,22.0,neutral or dissatisfied +66969,101428,Male,disloyal Customer,36,Business travel,Business,345,1,1,1,4,1,1,1,1,4,5,4,2,4,1,0,0.0,neutral or dissatisfied +66970,20886,Male,Loyal Customer,59,Personal Travel,Eco Plus,457,2,3,2,3,1,2,1,1,3,3,3,1,4,1,34,37.0,neutral or dissatisfied +66971,79016,Female,Loyal Customer,57,Business travel,Business,226,0,0,0,4,2,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +66972,7306,Female,Loyal Customer,38,Business travel,Eco Plus,116,1,2,2,2,1,2,1,1,3,1,4,3,3,1,0,0.0,neutral or dissatisfied +66973,184,Male,Loyal Customer,44,Business travel,Business,2497,0,4,0,2,4,5,4,1,1,1,1,3,1,5,0,0.0,satisfied +66974,4093,Male,Loyal Customer,48,Business travel,Business,427,3,3,3,3,3,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +66975,61224,Female,disloyal Customer,23,Business travel,Eco,846,2,2,2,4,5,2,4,5,1,1,3,4,4,5,0,0.0,neutral or dissatisfied +66976,117840,Male,Loyal Customer,62,Personal Travel,Eco Plus,328,4,2,4,3,4,4,3,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +66977,106626,Male,Loyal Customer,48,Business travel,Business,306,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,9.0,satisfied +66978,31262,Male,Loyal Customer,35,Business travel,Eco,770,3,4,5,4,3,3,3,3,2,3,4,5,5,3,3,0.0,satisfied +66979,106533,Male,Loyal Customer,52,Business travel,Business,321,2,4,4,4,1,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +66980,113537,Female,disloyal Customer,26,Business travel,Business,407,4,4,4,4,2,4,2,2,3,2,5,4,4,2,0,0.0,satisfied +66981,115372,Female,disloyal Customer,34,Business travel,Business,373,1,1,1,5,1,1,1,1,4,3,4,5,4,1,9,11.0,neutral or dissatisfied +66982,62838,Female,disloyal Customer,30,Business travel,Eco Plus,2504,3,3,3,4,3,5,3,1,2,2,3,3,1,3,8,20.0,neutral or dissatisfied +66983,16472,Male,Loyal Customer,17,Business travel,Eco Plus,529,3,2,2,2,3,4,5,3,1,3,1,2,2,3,24,15.0,satisfied +66984,21058,Male,Loyal Customer,43,Business travel,Business,227,1,1,3,1,5,5,3,4,4,4,4,4,4,5,1,5.0,satisfied +66985,34208,Male,Loyal Customer,66,Personal Travel,Eco,1189,2,3,2,4,1,2,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +66986,5754,Female,Loyal Customer,32,Business travel,Business,642,1,3,3,3,1,1,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +66987,76876,Male,Loyal Customer,49,Business travel,Business,2999,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +66988,63800,Male,Loyal Customer,20,Personal Travel,Eco,1721,2,4,2,5,1,2,1,1,5,4,4,5,5,1,20,0.0,neutral or dissatisfied +66989,84398,Male,Loyal Customer,37,Business travel,Business,191,3,1,1,1,3,4,4,3,3,3,3,1,3,3,8,45.0,neutral or dissatisfied +66990,102093,Male,Loyal Customer,44,Business travel,Business,236,5,5,5,5,4,5,5,5,5,5,5,5,5,4,15,46.0,satisfied +66991,39509,Male,Loyal Customer,54,Business travel,Business,3162,4,4,4,4,4,1,4,4,4,4,4,5,4,1,0,0.0,satisfied +66992,127302,Male,disloyal Customer,21,Business travel,Business,1108,4,5,4,2,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +66993,109383,Male,Loyal Customer,17,Business travel,Business,2177,3,3,3,3,4,4,4,4,3,1,1,4,5,4,6,0.0,satisfied +66994,26390,Male,disloyal Customer,18,Business travel,Eco,534,1,1,1,1,4,1,4,4,4,2,2,4,2,4,0,0.0,neutral or dissatisfied +66995,19275,Female,Loyal Customer,30,Business travel,Business,2321,3,3,3,3,5,5,5,5,2,1,4,1,1,5,2,0.0,satisfied +66996,103736,Female,Loyal Customer,36,Personal Travel,Eco,251,1,4,1,1,1,1,1,1,4,3,2,4,1,1,0,0.0,neutral or dissatisfied +66997,28661,Male,Loyal Customer,21,Personal Travel,Eco,2404,1,4,1,2,3,1,3,3,5,1,3,3,3,3,0,0.0,neutral or dissatisfied +66998,79905,Male,Loyal Customer,28,Business travel,Business,2151,1,3,3,3,1,2,1,1,1,4,4,2,4,1,95,82.0,neutral or dissatisfied +66999,448,Male,Loyal Customer,48,Business travel,Business,2607,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +67000,20620,Male,disloyal Customer,35,Business travel,Eco Plus,864,3,3,3,4,2,3,2,2,1,2,4,3,4,2,21,7.0,neutral or dissatisfied +67001,87590,Female,Loyal Customer,50,Personal Travel,Eco,432,4,5,4,4,4,4,5,4,4,4,4,5,4,3,1,10.0,neutral or dissatisfied +67002,5832,Female,Loyal Customer,14,Personal Travel,Eco,273,2,4,2,1,3,2,5,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +67003,94284,Female,Loyal Customer,45,Business travel,Business,2038,5,5,5,5,5,4,4,4,4,5,4,5,4,4,17,9.0,satisfied +67004,21226,Male,Loyal Customer,60,Personal Travel,Eco,192,3,5,3,2,1,3,1,1,3,4,5,5,4,1,7,1.0,neutral or dissatisfied +67005,90811,Female,disloyal Customer,34,Business travel,Eco,240,2,2,2,3,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +67006,119538,Female,Loyal Customer,43,Personal Travel,Eco,759,2,5,3,3,4,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +67007,111315,Female,Loyal Customer,60,Business travel,Eco,283,1,1,1,1,5,3,3,1,1,1,1,2,1,1,2,4.0,neutral or dissatisfied +67008,107574,Male,Loyal Customer,12,Personal Travel,Eco,1521,2,4,2,3,3,2,3,3,4,3,3,5,5,3,32,34.0,neutral or dissatisfied +67009,33334,Male,Loyal Customer,48,Business travel,Eco,2355,4,1,2,2,4,4,4,4,4,3,4,1,5,4,0,0.0,satisfied +67010,129302,Male,Loyal Customer,46,Business travel,Business,2475,1,1,1,1,3,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +67011,4945,Male,Loyal Customer,29,Personal Travel,Eco,334,2,5,2,5,2,2,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +67012,119890,Male,Loyal Customer,15,Personal Travel,Eco,912,2,5,2,4,3,2,3,3,4,5,4,5,4,3,4,0.0,neutral or dissatisfied +67013,47612,Female,Loyal Customer,38,Business travel,Business,2030,3,3,5,3,5,4,3,4,4,4,4,1,4,3,12,16.0,satisfied +67014,20403,Male,Loyal Customer,47,Business travel,Eco Plus,459,2,2,5,5,2,2,2,2,1,3,5,1,4,2,0,0.0,satisfied +67015,6602,Female,Loyal Customer,44,Personal Travel,Eco,528,2,3,2,1,5,4,1,3,3,2,3,3,3,3,9,0.0,neutral or dissatisfied +67016,31160,Female,Loyal Customer,31,Business travel,Business,3413,4,4,2,4,4,4,4,4,3,4,2,1,1,4,0,0.0,satisfied +67017,102689,Male,Loyal Customer,39,Business travel,Eco,255,3,5,5,5,3,3,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +67018,19200,Female,Loyal Customer,57,Personal Travel,Eco,542,2,4,3,2,4,3,5,5,5,3,5,1,5,5,6,10.0,neutral or dissatisfied +67019,96011,Male,Loyal Customer,37,Business travel,Business,758,5,5,5,5,4,5,5,5,5,5,5,5,5,4,2,3.0,satisfied +67020,23775,Female,disloyal Customer,20,Business travel,Eco,438,4,0,4,3,3,4,3,3,3,3,2,1,3,3,0,0.0,neutral or dissatisfied +67021,60857,Male,disloyal Customer,50,Business travel,Business,1491,2,2,2,2,4,2,2,4,4,3,4,4,4,4,0,0.0,satisfied +67022,73671,Female,disloyal Customer,68,Business travel,Eco,192,1,2,1,4,5,1,5,5,1,5,3,4,3,5,0,0.0,neutral or dissatisfied +67023,77928,Male,Loyal Customer,43,Business travel,Business,214,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +67024,48008,Male,Loyal Customer,71,Business travel,Eco Plus,384,3,5,3,5,3,3,3,3,3,2,4,3,3,3,0,7.0,neutral or dissatisfied +67025,25154,Female,disloyal Customer,21,Business travel,Eco,2106,4,4,4,2,5,4,5,5,4,5,5,1,5,5,28,32.0,satisfied +67026,26994,Female,Loyal Customer,23,Business travel,Business,954,1,1,1,1,4,4,4,4,5,3,1,3,3,4,0,11.0,satisfied +67027,48890,Male,disloyal Customer,20,Business travel,Eco,89,2,5,2,4,2,2,2,2,5,1,3,1,3,2,0,2.0,neutral or dissatisfied +67028,48016,Male,Loyal Customer,29,Personal Travel,Eco Plus,329,2,4,2,5,5,2,5,5,3,3,4,2,5,5,8,0.0,neutral or dissatisfied +67029,2579,Male,Loyal Customer,33,Business travel,Business,3512,0,0,0,2,3,3,3,3,3,2,2,4,3,3,0,1.0,satisfied +67030,98823,Female,Loyal Customer,50,Business travel,Business,1920,5,5,5,5,3,4,4,3,3,2,3,5,3,3,0,0.0,satisfied +67031,121489,Female,Loyal Customer,42,Personal Travel,Eco,331,4,5,5,3,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +67032,53828,Male,Loyal Customer,45,Business travel,Business,140,3,1,1,1,4,3,3,3,3,3,3,3,3,3,4,0.0,neutral or dissatisfied +67033,95124,Female,Loyal Customer,32,Personal Travel,Eco,248,3,5,0,2,2,0,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +67034,17023,Female,Loyal Customer,48,Personal Travel,Eco,781,2,5,3,1,5,5,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +67035,77290,Female,Loyal Customer,39,Business travel,Business,391,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +67036,14584,Male,Loyal Customer,55,Business travel,Business,1021,1,2,2,2,5,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +67037,4509,Female,Loyal Customer,58,Personal Travel,Eco,551,1,5,1,1,5,3,3,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +67038,16085,Male,Loyal Customer,38,Business travel,Business,303,3,3,3,3,1,3,1,5,5,5,5,2,5,5,35,36.0,satisfied +67039,541,Male,Loyal Customer,54,Business travel,Business,2494,0,0,0,5,4,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +67040,38000,Female,Loyal Customer,26,Business travel,Business,3198,1,1,1,1,4,4,4,4,1,1,4,2,3,4,0,0.0,satisfied +67041,77418,Male,Loyal Customer,26,Personal Travel,Eco,588,3,3,3,5,5,3,4,5,3,2,1,1,2,5,0,0.0,neutral or dissatisfied +67042,87036,Female,Loyal Customer,48,Business travel,Business,2885,2,2,2,2,4,4,5,4,4,5,4,3,4,4,8,0.0,satisfied +67043,32616,Female,disloyal Customer,20,Business travel,Eco,102,1,0,1,2,1,1,1,1,2,3,5,2,5,1,0,0.0,neutral or dissatisfied +67044,20768,Female,Loyal Customer,21,Business travel,Business,534,3,3,3,3,4,4,4,4,2,5,3,2,3,4,0,0.0,satisfied +67045,91655,Male,Loyal Customer,29,Personal Travel,Eco,1312,4,5,4,4,2,4,5,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +67046,47479,Female,Loyal Customer,17,Personal Travel,Eco,590,3,5,3,2,3,3,3,3,3,2,4,5,5,3,0,4.0,neutral or dissatisfied +67047,92401,Male,Loyal Customer,51,Business travel,Business,1919,3,3,3,3,5,3,4,2,2,2,2,3,2,4,7,0.0,satisfied +67048,62462,Male,Loyal Customer,40,Personal Travel,Business,1846,2,2,2,1,1,1,2,5,5,2,5,3,5,1,2,27.0,neutral or dissatisfied +67049,17477,Male,Loyal Customer,36,Business travel,Eco,241,4,5,5,5,4,4,4,4,4,3,2,3,2,4,0,0.0,satisfied +67050,129168,Male,Loyal Customer,36,Personal Travel,Eco,679,3,4,3,3,2,3,2,2,3,2,5,5,5,2,23,11.0,neutral or dissatisfied +67051,99871,Male,Loyal Customer,36,Personal Travel,Eco Plus,680,4,4,4,1,3,4,3,3,5,5,5,4,5,3,14,6.0,neutral or dissatisfied +67052,69314,Female,Loyal Customer,38,Personal Travel,Business,1089,2,5,2,3,4,1,4,5,5,2,5,1,5,5,5,0.0,neutral or dissatisfied +67053,102379,Male,Loyal Customer,53,Business travel,Eco,258,1,2,4,2,1,1,1,1,1,3,4,2,4,1,5,0.0,neutral or dissatisfied +67054,36017,Male,Loyal Customer,23,Business travel,Eco,399,0,3,0,5,3,0,3,3,4,5,1,5,4,3,0,0.0,satisfied +67055,4532,Female,disloyal Customer,16,Business travel,Eco,677,4,4,4,3,4,4,4,4,3,1,3,4,4,4,26,18.0,neutral or dissatisfied +67056,19300,Female,disloyal Customer,15,Business travel,Eco,299,3,2,3,3,1,3,5,1,3,1,3,4,3,1,4,10.0,neutral or dissatisfied +67057,61071,Female,disloyal Customer,24,Business travel,Eco,1141,4,4,4,3,2,4,2,2,3,5,4,1,4,2,8,3.0,neutral or dissatisfied +67058,76441,Female,Loyal Customer,64,Personal Travel,Eco,405,3,4,3,4,5,5,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +67059,38519,Female,disloyal Customer,42,Business travel,Eco,2465,3,3,3,4,2,3,5,2,3,1,3,4,2,2,0,0.0,neutral or dissatisfied +67060,106726,Female,Loyal Customer,48,Business travel,Business,1837,5,5,5,5,3,5,4,4,4,4,4,5,4,4,52,51.0,satisfied +67061,28600,Male,Loyal Customer,60,Business travel,Business,2889,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +67062,96319,Female,Loyal Customer,47,Business travel,Business,359,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +67063,87914,Female,Loyal Customer,48,Business travel,Business,404,5,5,5,5,2,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +67064,69273,Male,Loyal Customer,24,Personal Travel,Eco,733,1,3,1,4,5,1,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +67065,117892,Female,Loyal Customer,45,Business travel,Business,3813,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,2.0,satisfied +67066,85895,Female,Loyal Customer,40,Business travel,Business,761,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +67067,119852,Female,disloyal Customer,21,Business travel,Eco,912,0,1,1,1,4,1,4,4,3,2,2,5,4,4,0,0.0,satisfied +67068,108740,Female,Loyal Customer,41,Business travel,Business,404,2,1,5,1,4,4,3,2,2,2,2,1,2,2,8,10.0,neutral or dissatisfied +67069,45801,Female,disloyal Customer,24,Business travel,Eco,517,1,4,1,4,1,1,1,1,3,3,3,2,3,1,28,13.0,neutral or dissatisfied +67070,49179,Male,Loyal Customer,53,Business travel,Eco,278,4,5,5,5,4,4,4,4,4,5,2,4,1,4,0,0.0,satisfied +67071,6041,Male,disloyal Customer,32,Business travel,Eco,690,3,3,3,3,3,3,3,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +67072,35805,Male,disloyal Customer,23,Business travel,Business,1068,2,1,1,2,5,1,5,5,1,1,2,3,1,5,0,0.0,neutral or dissatisfied +67073,64676,Male,Loyal Customer,55,Business travel,Business,247,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +67074,34376,Female,Loyal Customer,32,Personal Travel,Business,728,4,5,4,3,2,4,2,2,4,2,4,2,3,2,0,0.0,neutral or dissatisfied +67075,71205,Female,Loyal Customer,49,Business travel,Business,2613,2,2,2,2,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +67076,33228,Male,Loyal Customer,38,Business travel,Eco Plus,102,4,3,3,3,4,4,4,4,3,2,5,2,1,4,0,0.0,satisfied +67077,84669,Male,Loyal Customer,21,Business travel,Business,2182,2,2,2,2,4,5,4,4,4,4,4,4,5,4,64,46.0,satisfied +67078,43617,Male,disloyal Customer,26,Business travel,Business,228,1,3,1,3,1,1,1,1,2,2,3,3,3,1,0,4.0,neutral or dissatisfied +67079,100633,Male,Loyal Customer,46,Business travel,Business,1503,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +67080,50886,Male,Loyal Customer,66,Personal Travel,Eco,109,3,2,3,3,4,3,4,4,1,2,4,1,3,4,0,2.0,neutral or dissatisfied +67081,60267,Male,Loyal Customer,69,Personal Travel,Eco Plus,1506,3,3,2,4,3,2,3,3,2,2,3,1,1,3,50,40.0,neutral or dissatisfied +67082,37390,Female,disloyal Customer,25,Business travel,Eco,1035,2,2,2,2,1,2,5,1,1,3,4,2,2,1,60,84.0,neutral or dissatisfied +67083,3943,Male,Loyal Customer,38,Business travel,Business,764,3,3,3,3,4,5,4,5,5,5,5,5,5,5,1,8.0,satisfied +67084,129392,Male,Loyal Customer,59,Business travel,Business,414,3,3,3,3,3,4,5,5,5,5,5,3,5,5,3,0.0,satisfied +67085,122202,Female,Loyal Customer,39,Business travel,Business,3601,1,1,1,1,3,5,4,4,4,4,4,5,4,3,5,0.0,satisfied +67086,80559,Male,disloyal Customer,38,Business travel,Business,1386,4,4,4,3,2,4,2,2,3,2,5,5,4,2,0,0.0,satisfied +67087,126048,Male,Loyal Customer,49,Business travel,Business,3492,1,1,1,1,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +67088,103315,Female,Loyal Customer,53,Business travel,Business,1371,3,3,3,3,2,5,5,5,5,4,5,3,5,5,31,40.0,satisfied +67089,60611,Male,Loyal Customer,20,Personal Travel,Eco,991,3,5,4,2,5,4,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +67090,22291,Female,Loyal Customer,31,Business travel,Business,208,0,4,0,2,4,4,4,4,3,3,4,2,3,4,0,0.0,satisfied +67091,57040,Male,Loyal Customer,51,Personal Travel,Eco Plus,2565,3,1,3,4,3,5,5,1,1,4,3,5,2,5,38,24.0,neutral or dissatisfied +67092,23047,Male,Loyal Customer,11,Business travel,Eco Plus,833,4,4,5,4,4,4,1,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +67093,38745,Female,Loyal Customer,39,Business travel,Eco,354,3,4,4,4,3,3,3,3,2,3,3,2,3,3,0,0.0,neutral or dissatisfied +67094,48066,Male,Loyal Customer,56,Business travel,Business,3989,1,1,4,1,2,5,4,5,5,4,5,3,5,4,6,4.0,satisfied +67095,41147,Male,Loyal Customer,37,Personal Travel,Eco,295,1,2,1,3,4,1,4,4,1,2,4,2,4,4,0,0.0,neutral or dissatisfied +67096,64029,Female,Loyal Customer,34,Business travel,Business,1590,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,4.0,satisfied +67097,107175,Female,disloyal Customer,19,Business travel,Eco,402,2,2,2,4,1,2,1,1,2,5,4,3,3,1,9,8.0,neutral or dissatisfied +67098,78315,Male,Loyal Customer,51,Business travel,Business,2404,2,2,2,2,4,3,3,3,4,4,5,3,5,3,0,3.0,satisfied +67099,117235,Male,Loyal Customer,29,Personal Travel,Eco,646,1,4,1,3,3,1,3,3,1,3,3,2,3,3,78,73.0,neutral or dissatisfied +67100,1223,Male,Loyal Customer,58,Personal Travel,Eco,309,4,2,4,3,3,4,3,3,2,3,4,4,3,3,0,0.0,neutral or dissatisfied +67101,294,Male,Loyal Customer,17,Personal Travel,Eco,1250,3,2,3,3,1,3,1,1,2,3,3,3,4,1,11,12.0,neutral or dissatisfied +67102,32882,Male,Loyal Customer,62,Personal Travel,Eco,101,2,5,2,1,2,2,2,2,5,3,5,2,2,2,0,0.0,neutral or dissatisfied +67103,129591,Female,Loyal Customer,54,Personal Travel,Business,337,2,4,2,4,1,3,4,2,2,2,5,1,2,1,0,0.0,neutral or dissatisfied +67104,49776,Male,Loyal Customer,45,Business travel,Business,2544,0,4,0,1,5,1,1,2,2,2,2,5,2,3,0,0.0,satisfied +67105,100959,Male,Loyal Customer,42,Personal Travel,Eco,1204,5,5,5,4,1,5,5,1,1,2,1,3,1,1,0,0.0,satisfied +67106,115293,Male,disloyal Customer,29,Business travel,Business,446,5,5,5,3,4,5,4,4,3,3,4,3,5,4,22,22.0,satisfied +67107,97850,Female,Loyal Customer,56,Business travel,Business,1848,4,4,4,4,3,4,5,3,3,3,3,5,3,3,55,61.0,satisfied +67108,123768,Male,Loyal Customer,31,Business travel,Business,544,3,5,5,5,3,3,3,3,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +67109,50956,Male,Loyal Customer,32,Personal Travel,Eco,156,4,4,4,1,2,4,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +67110,112914,Male,Loyal Customer,38,Business travel,Eco,990,5,5,5,5,5,5,5,5,5,3,3,2,3,5,0,0.0,satisfied +67111,125064,Female,Loyal Customer,61,Personal Travel,Eco,90,5,4,5,3,2,4,3,2,2,5,2,2,2,3,0,0.0,satisfied +67112,33327,Male,disloyal Customer,36,Business travel,Eco,1119,3,3,3,3,5,3,5,5,1,4,3,4,2,5,0,0.0,neutral or dissatisfied +67113,28722,Male,Loyal Customer,40,Personal Travel,Eco,2554,2,5,2,1,2,5,5,4,3,5,4,5,4,5,32,10.0,neutral or dissatisfied +67114,124694,Male,disloyal Customer,58,Business travel,Eco,399,1,1,1,3,3,1,3,3,3,5,4,4,3,3,88,109.0,neutral or dissatisfied +67115,121128,Male,Loyal Customer,50,Business travel,Business,2402,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +67116,29379,Male,Loyal Customer,36,Business travel,Eco,2457,4,5,5,5,4,4,4,4,1,3,3,4,3,4,0,6.0,satisfied +67117,10199,Female,disloyal Customer,21,Business travel,Eco,316,1,5,1,2,3,1,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +67118,69786,Male,Loyal Customer,29,Personal Travel,Business,1055,4,5,4,4,4,4,4,4,3,4,4,3,5,4,63,54.0,neutral or dissatisfied +67119,128810,Male,Loyal Customer,53,Business travel,Business,2475,4,4,4,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +67120,39725,Female,disloyal Customer,23,Business travel,Eco,162,2,3,2,3,2,2,2,2,3,2,3,2,3,2,0,2.0,neutral or dissatisfied +67121,6691,Female,Loyal Customer,54,Business travel,Business,3303,3,3,3,3,2,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +67122,39343,Male,Loyal Customer,30,Business travel,Business,774,3,5,5,5,3,3,3,3,1,4,4,4,4,3,0,36.0,neutral or dissatisfied +67123,11976,Male,Loyal Customer,30,Business travel,Business,2044,2,2,2,2,4,4,4,4,5,5,4,5,4,4,73,60.0,satisfied +67124,40112,Female,disloyal Customer,23,Business travel,Eco,422,3,5,3,4,5,3,5,5,2,3,3,4,5,5,0,2.0,neutral or dissatisfied +67125,78125,Female,Loyal Customer,47,Personal Travel,Eco Plus,1797,3,5,3,3,3,4,5,3,3,3,5,3,3,3,0,0.0,neutral or dissatisfied +67126,83348,Male,Loyal Customer,51,Business travel,Eco Plus,187,2,4,4,4,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +67127,93674,Female,Loyal Customer,49,Personal Travel,Eco,667,3,3,3,3,2,3,3,2,2,3,2,1,2,2,10,13.0,neutral or dissatisfied +67128,46180,Female,disloyal Customer,20,Business travel,Eco,627,2,0,1,4,4,1,4,4,4,5,1,1,3,4,10,14.0,neutral or dissatisfied +67129,74500,Male,Loyal Customer,50,Business travel,Eco,1242,1,3,3,3,2,1,2,2,3,5,3,2,4,2,111,97.0,neutral or dissatisfied +67130,32052,Female,Loyal Customer,34,Business travel,Eco,216,4,5,5,5,4,4,4,4,1,2,3,4,1,4,0,0.0,satisfied +67131,67977,Male,Loyal Customer,22,Business travel,Eco Plus,1431,3,1,2,1,3,3,3,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +67132,9375,Male,Loyal Customer,58,Business travel,Eco,441,2,4,4,4,2,2,2,2,2,4,3,1,3,2,9,2.0,neutral or dissatisfied +67133,8790,Female,disloyal Customer,35,Business travel,Eco,522,3,2,3,4,3,3,3,3,1,1,3,1,3,3,80,88.0,neutral or dissatisfied +67134,78658,Female,Loyal Customer,24,Business travel,Business,2172,3,3,3,3,4,4,4,3,4,4,4,4,5,4,202,191.0,satisfied +67135,5017,Male,Loyal Customer,11,Personal Travel,Eco Plus,502,2,4,2,4,4,2,3,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +67136,49067,Male,Loyal Customer,53,Business travel,Business,1552,3,3,3,3,3,5,1,4,4,5,4,3,4,2,8,3.0,satisfied +67137,84643,Female,Loyal Customer,53,Personal Travel,Eco Plus,669,2,4,1,4,2,4,4,1,1,1,1,3,1,5,15,4.0,neutral or dissatisfied +67138,127856,Male,Loyal Customer,53,Business travel,Business,2895,1,1,1,1,3,5,4,4,4,4,4,4,4,3,0,2.0,satisfied +67139,28064,Female,Loyal Customer,23,Business travel,Eco,2562,4,1,1,1,4,3,4,5,2,5,5,4,3,4,0,0.0,satisfied +67140,49072,Female,Loyal Customer,57,Business travel,Business,2239,1,1,2,1,3,1,2,5,5,4,5,5,5,4,4,12.0,satisfied +67141,38531,Male,Loyal Customer,61,Business travel,Business,2475,3,2,2,2,3,4,4,3,3,2,3,3,3,4,0,14.0,neutral or dissatisfied +67142,99898,Male,Loyal Customer,28,Personal Travel,Eco,738,3,4,2,4,4,2,3,4,3,4,4,3,5,4,7,2.0,neutral or dissatisfied +67143,59958,Female,disloyal Customer,38,Business travel,Eco,1023,1,1,1,4,4,1,4,4,2,5,3,4,4,4,1,0.0,neutral or dissatisfied +67144,86743,Male,Loyal Customer,49,Business travel,Business,821,1,1,1,1,4,5,5,5,5,5,5,4,5,5,14,0.0,satisfied +67145,107746,Female,Loyal Customer,40,Personal Travel,Eco,251,3,5,3,3,3,3,3,3,3,3,1,2,2,3,0,0.0,neutral or dissatisfied +67146,102349,Male,Loyal Customer,50,Business travel,Business,3268,1,5,5,5,3,3,3,1,1,1,1,1,1,1,18,16.0,neutral or dissatisfied +67147,120306,Female,disloyal Customer,34,Business travel,Business,268,1,1,1,2,1,1,1,1,3,3,5,4,4,1,0,10.0,neutral or dissatisfied +67148,112805,Male,disloyal Customer,19,Business travel,Business,715,4,0,4,3,5,4,5,5,3,5,4,4,5,5,14,0.0,satisfied +67149,47123,Female,Loyal Customer,51,Business travel,Business,3807,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +67150,72982,Female,Loyal Customer,48,Business travel,Eco,1096,3,3,3,3,4,3,3,3,3,3,3,4,3,3,38,47.0,neutral or dissatisfied +67151,30586,Male,Loyal Customer,34,Personal Travel,Eco,628,2,5,2,1,2,2,2,2,5,4,4,3,4,2,0,1.0,neutral or dissatisfied +67152,116167,Female,Loyal Customer,55,Personal Travel,Eco,446,2,4,2,4,5,5,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +67153,17970,Female,Loyal Customer,65,Personal Travel,Eco,500,5,4,5,3,2,1,4,5,5,5,5,2,5,4,13,2.0,satisfied +67154,5092,Male,Loyal Customer,52,Business travel,Eco,122,5,1,1,1,5,5,5,5,3,1,2,2,1,5,0,0.0,satisfied +67155,88090,Female,Loyal Customer,50,Business travel,Business,3423,4,4,4,4,5,5,4,5,5,5,5,3,5,4,16,18.0,satisfied +67156,10546,Male,Loyal Customer,58,Business travel,Business,3993,4,4,4,4,4,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +67157,108996,Male,disloyal Customer,39,Business travel,Business,849,4,3,3,4,4,3,4,4,3,5,5,5,5,4,13,15.0,satisfied +67158,47898,Female,Loyal Customer,41,Business travel,Business,2977,3,1,1,1,3,3,4,3,3,2,3,1,3,4,60,61.0,neutral or dissatisfied +67159,82926,Male,Loyal Customer,59,Business travel,Business,2424,5,5,5,5,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +67160,34440,Female,Loyal Customer,35,Personal Travel,Eco,2422,3,5,3,4,3,3,3,1,3,4,3,3,5,3,0,19.0,neutral or dissatisfied +67161,54213,Female,Loyal Customer,37,Personal Travel,Eco Plus,1400,2,3,1,4,4,1,4,4,2,1,5,2,4,4,41,64.0,neutral or dissatisfied +67162,25523,Female,Loyal Customer,62,Personal Travel,Eco,547,3,4,3,4,2,3,3,4,4,3,4,3,4,3,25,48.0,neutral or dissatisfied +67163,118185,Female,Loyal Customer,51,Business travel,Business,1440,5,5,3,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +67164,63836,Female,Loyal Customer,30,Business travel,Business,1691,5,5,5,5,2,2,2,2,4,5,4,4,5,2,0,0.0,satisfied +67165,70648,Male,disloyal Customer,35,Business travel,Business,946,1,1,1,3,2,1,1,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +67166,87323,Male,Loyal Customer,55,Business travel,Business,3747,4,4,4,4,4,4,4,4,4,4,4,3,4,3,20,15.0,satisfied +67167,32284,Male,Loyal Customer,60,Business travel,Eco,101,5,4,4,4,5,5,5,5,4,5,2,5,2,5,4,6.0,satisfied +67168,124049,Male,Loyal Customer,39,Business travel,Business,2153,4,4,4,4,4,4,4,5,5,5,5,4,5,5,0,7.0,satisfied +67169,46923,Male,Loyal Customer,51,Business travel,Eco,376,5,4,4,4,5,5,5,5,4,1,1,3,5,5,16,0.0,satisfied +67170,16478,Male,Loyal Customer,36,Personal Travel,Eco Plus,445,4,5,4,3,4,4,4,4,3,2,5,3,5,4,21,14.0,neutral or dissatisfied +67171,37848,Male,Loyal Customer,67,Business travel,Business,997,2,2,2,2,1,4,1,5,5,5,5,5,5,1,24,4.0,satisfied +67172,57270,Female,Loyal Customer,36,Business travel,Business,404,2,4,4,4,4,3,3,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +67173,122117,Female,disloyal Customer,26,Business travel,Business,130,2,4,2,4,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +67174,89064,Female,Loyal Customer,34,Business travel,Business,1892,4,4,2,4,4,5,5,4,4,4,4,5,4,4,29,37.0,satisfied +67175,104390,Female,Loyal Customer,61,Personal Travel,Eco Plus,228,3,4,3,3,4,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +67176,123553,Female,Loyal Customer,47,Business travel,Business,1773,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,4.0,satisfied +67177,27784,Male,Loyal Customer,48,Business travel,Business,1448,2,1,5,1,3,3,2,2,2,2,2,2,2,1,115,109.0,neutral or dissatisfied +67178,97676,Male,Loyal Customer,59,Personal Travel,Eco,491,3,3,3,3,3,3,3,3,4,4,3,1,4,3,5,11.0,neutral or dissatisfied +67179,63740,Female,Loyal Customer,17,Personal Travel,Eco,1660,3,0,3,1,2,3,2,2,5,4,5,3,4,2,8,0.0,neutral or dissatisfied +67180,98432,Female,Loyal Customer,18,Personal Travel,Eco,1910,3,4,3,1,5,3,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +67181,8551,Male,disloyal Customer,39,Business travel,Business,109,2,2,2,2,2,2,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +67182,127488,Male,Loyal Customer,69,Personal Travel,Eco,2075,4,4,5,3,4,5,4,4,1,4,4,4,2,4,42,25.0,neutral or dissatisfied +67183,96145,Female,Loyal Customer,27,Business travel,Business,546,3,3,5,3,3,3,3,3,4,4,4,5,4,3,11,7.0,satisfied +67184,83761,Male,Loyal Customer,60,Personal Travel,Eco,1039,2,5,2,1,2,2,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +67185,100572,Female,disloyal Customer,10,Business travel,Eco,486,3,4,3,4,5,3,5,5,3,5,5,3,4,5,1,7.0,neutral or dissatisfied +67186,53131,Female,Loyal Customer,58,Personal Travel,Eco Plus,2065,3,4,3,3,3,3,5,4,4,3,5,4,4,4,1,2.0,neutral or dissatisfied +67187,50918,Female,Loyal Customer,58,Personal Travel,Eco,421,0,3,0,3,3,3,3,4,4,0,4,3,4,3,0,0.0,satisfied +67188,26701,Male,Loyal Customer,7,Personal Travel,Eco,406,2,5,3,5,3,3,3,3,2,3,1,1,1,3,0,16.0,neutral or dissatisfied +67189,95405,Female,Loyal Customer,17,Personal Travel,Eco,239,3,1,3,4,3,3,3,3,4,1,4,3,4,3,1,0.0,neutral or dissatisfied +67190,24777,Female,disloyal Customer,62,Business travel,Eco,432,3,2,3,3,2,3,2,2,1,1,4,4,4,2,0,0.0,neutral or dissatisfied +67191,100936,Male,Loyal Customer,50,Business travel,Business,2464,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +67192,47844,Female,Loyal Customer,41,Business travel,Eco,550,3,5,5,5,3,3,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +67193,61963,Male,Loyal Customer,40,Business travel,Business,2052,5,5,5,5,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +67194,61949,Male,Loyal Customer,34,Business travel,Business,2161,1,1,3,3,1,2,3,1,1,2,1,4,1,2,40,24.0,neutral or dissatisfied +67195,85811,Female,Loyal Customer,7,Personal Travel,Eco,620,3,2,3,1,3,3,3,3,1,4,1,3,2,3,1,0.0,neutral or dissatisfied +67196,100532,Male,Loyal Customer,28,Personal Travel,Eco,580,3,4,3,3,2,3,3,2,3,2,1,2,1,2,0,0.0,neutral or dissatisfied +67197,11272,Male,Loyal Customer,16,Personal Travel,Eco,316,2,3,2,4,5,2,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +67198,599,Female,Loyal Customer,39,Business travel,Business,3269,1,1,1,1,2,4,4,5,5,4,4,4,5,5,0,0.0,satisfied +67199,28796,Female,Loyal Customer,42,Personal Travel,Business,987,2,3,2,3,2,3,3,3,3,2,3,3,3,4,4,27.0,neutral or dissatisfied +67200,98577,Male,Loyal Customer,30,Business travel,Business,3616,3,3,3,3,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +67201,113885,Female,Loyal Customer,30,Personal Travel,Eco Plus,1363,3,5,3,1,1,3,1,1,3,5,3,5,4,1,5,23.0,neutral or dissatisfied +67202,72867,Male,Loyal Customer,69,Personal Travel,Eco,700,2,4,2,3,1,2,5,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +67203,81607,Female,Loyal Customer,38,Business travel,Eco,334,2,1,1,1,2,2,2,2,2,2,4,4,3,2,3,27.0,neutral or dissatisfied +67204,58934,Female,Loyal Customer,22,Personal Travel,Eco,888,3,3,3,3,5,3,5,5,1,2,1,3,4,5,10,6.0,neutral or dissatisfied +67205,53254,Male,Loyal Customer,35,Personal Travel,Eco Plus,612,3,5,3,3,5,3,4,5,3,2,4,5,4,5,3,12.0,neutral or dissatisfied +67206,9013,Male,Loyal Customer,44,Business travel,Business,160,4,4,4,4,3,4,4,5,5,5,4,3,5,4,33,40.0,satisfied +67207,115456,Male,Loyal Customer,41,Business travel,Business,3206,2,5,5,5,1,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +67208,88294,Female,Loyal Customer,44,Business travel,Business,581,1,1,1,1,2,4,5,2,2,2,2,3,2,4,14,4.0,satisfied +67209,17744,Male,disloyal Customer,23,Business travel,Eco,456,3,4,3,4,4,3,4,4,3,2,4,2,3,4,100,84.0,neutral or dissatisfied +67210,18352,Female,Loyal Customer,40,Business travel,Business,3194,3,1,2,1,2,3,4,3,3,3,3,1,3,4,106,88.0,neutral or dissatisfied +67211,55634,Female,Loyal Customer,46,Business travel,Business,2771,1,1,1,1,4,4,5,2,2,3,2,4,2,5,0,0.0,satisfied +67212,38713,Male,Loyal Customer,29,Personal Travel,Eco,2342,2,5,2,4,4,2,4,4,4,3,2,4,1,4,0,25.0,neutral or dissatisfied +67213,59719,Female,disloyal Customer,47,Business travel,Eco Plus,854,2,2,2,3,2,2,3,2,3,4,4,2,4,2,22,13.0,neutral or dissatisfied +67214,23633,Male,Loyal Customer,27,Business travel,Business,3634,2,2,2,2,5,5,5,5,4,5,4,3,3,5,0,0.0,satisfied +67215,76684,Male,Loyal Customer,55,Personal Travel,Eco,481,2,1,2,3,3,2,3,3,1,1,2,1,2,3,0,0.0,neutral or dissatisfied +67216,100771,Male,Loyal Customer,29,Business travel,Eco,1411,2,1,1,1,2,2,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +67217,63252,Female,Loyal Customer,30,Business travel,Business,1503,4,4,4,4,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +67218,23283,Male,Loyal Customer,31,Business travel,Business,1743,1,1,1,1,5,5,5,5,5,1,3,2,5,5,1,0.0,satisfied +67219,37241,Female,Loyal Customer,67,Personal Travel,Business,1005,3,5,3,3,3,4,4,5,5,3,5,5,5,4,7,10.0,neutral or dissatisfied +67220,23133,Male,Loyal Customer,43,Business travel,Business,2944,4,1,4,1,3,3,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +67221,95116,Male,Loyal Customer,70,Personal Travel,Eco,441,1,2,1,3,5,1,1,5,2,1,2,2,2,5,0,0.0,neutral or dissatisfied +67222,5673,Male,Loyal Customer,39,Business travel,Business,299,3,3,3,3,2,5,5,5,5,5,5,4,5,5,15,7.0,satisfied +67223,62217,Male,Loyal Customer,12,Personal Travel,Eco,2454,4,1,4,3,5,4,5,5,4,5,2,1,2,5,15,0.0,neutral or dissatisfied +67224,4358,Male,Loyal Customer,46,Business travel,Business,3441,4,4,4,4,5,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +67225,26654,Male,Loyal Customer,15,Business travel,Business,2447,3,3,3,3,5,5,5,5,1,5,3,4,4,5,0,0.0,satisfied +67226,77186,Male,Loyal Customer,69,Business travel,Eco,290,2,5,5,5,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +67227,129539,Female,Loyal Customer,28,Business travel,Business,2342,3,3,2,3,3,3,3,3,3,5,3,1,3,3,6,9.0,neutral or dissatisfied +67228,97719,Female,Loyal Customer,59,Business travel,Business,3005,2,2,2,2,3,5,5,5,5,5,5,3,5,3,0,17.0,satisfied +67229,100905,Male,Loyal Customer,48,Personal Travel,Eco,377,2,4,3,3,5,3,5,5,3,2,4,3,4,5,0,7.0,neutral or dissatisfied +67230,93847,Male,Loyal Customer,65,Personal Travel,Eco,391,5,1,5,3,3,5,3,3,3,1,3,2,4,3,0,0.0,satisfied +67231,20532,Male,disloyal Customer,39,Business travel,Eco,565,1,0,1,5,4,1,5,4,2,1,2,3,4,4,12,0.0,neutral or dissatisfied +67232,115945,Male,Loyal Customer,10,Personal Travel,Eco,337,4,4,4,2,5,4,5,5,4,5,4,4,4,5,0,0.0,satisfied +67233,1391,Female,Loyal Customer,8,Personal Travel,Eco Plus,282,3,2,3,3,1,3,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +67234,19715,Male,Loyal Customer,67,Business travel,Business,3068,3,4,4,4,3,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +67235,42401,Female,Loyal Customer,38,Business travel,Eco Plus,462,4,5,5,5,4,4,4,4,3,3,1,1,2,4,0,7.0,satisfied +67236,48109,Female,Loyal Customer,42,Business travel,Business,3565,0,0,0,4,1,1,1,4,4,4,4,3,4,2,13,0.0,satisfied +67237,75183,Female,Loyal Customer,48,Business travel,Business,1744,2,3,3,3,3,4,4,2,2,1,2,4,2,2,18,3.0,neutral or dissatisfied +67238,19292,Male,disloyal Customer,36,Business travel,Eco,196,1,0,1,3,5,1,5,5,5,4,1,3,3,5,0,0.0,neutral or dissatisfied +67239,66060,Male,Loyal Customer,64,Personal Travel,Eco,1055,1,4,1,4,3,1,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +67240,124483,Male,Loyal Customer,47,Business travel,Business,2440,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +67241,1534,Male,Loyal Customer,43,Business travel,Business,3653,1,1,1,1,2,4,4,1,1,2,1,2,1,2,13,8.0,neutral or dissatisfied +67242,96757,Female,Loyal Customer,28,Business travel,Business,849,5,5,5,5,5,5,5,5,4,5,5,4,4,5,33,9.0,satisfied +67243,44119,Male,Loyal Customer,51,Business travel,Business,3683,3,3,5,3,1,4,2,4,4,4,3,3,4,2,0,0.0,satisfied +67244,32974,Male,Loyal Customer,19,Personal Travel,Eco,102,4,5,4,1,1,4,1,1,3,4,4,4,5,1,3,1.0,neutral or dissatisfied +67245,125785,Male,Loyal Customer,57,Business travel,Business,2724,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,18.0,satisfied +67246,123769,Female,Loyal Customer,46,Business travel,Business,2427,3,5,5,5,1,2,2,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +67247,81806,Male,disloyal Customer,41,Business travel,Eco,1306,2,2,2,3,5,2,5,5,4,4,4,1,4,5,76,66.0,neutral or dissatisfied +67248,11529,Female,Loyal Customer,68,Personal Travel,Eco Plus,191,2,5,2,4,2,4,4,5,5,2,5,3,5,4,4,0.0,neutral or dissatisfied +67249,26732,Female,Loyal Customer,35,Business travel,Eco Plus,270,3,3,3,3,3,3,3,3,1,2,2,4,2,3,18,14.0,neutral or dissatisfied +67250,36742,Male,Loyal Customer,38,Personal Travel,Eco,1754,2,4,2,3,1,2,5,1,1,2,1,4,4,1,7,0.0,neutral or dissatisfied +67251,127484,Female,Loyal Customer,60,Business travel,Business,2512,4,4,4,4,5,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +67252,6730,Female,disloyal Customer,45,Business travel,Business,334,2,2,2,4,1,2,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +67253,19081,Female,Loyal Customer,29,Business travel,Eco Plus,642,1,5,5,5,1,1,1,1,3,2,4,1,4,1,33,64.0,neutral or dissatisfied +67254,88785,Male,Loyal Customer,30,Business travel,Business,581,5,5,5,5,4,4,4,4,3,4,5,4,4,4,20,11.0,satisfied +67255,75638,Male,disloyal Customer,22,Business travel,Eco,280,4,0,4,4,5,4,5,5,5,5,5,5,4,5,22,10.0,satisfied +67256,42147,Female,Loyal Customer,50,Business travel,Business,3273,1,3,3,3,1,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +67257,72970,Male,Loyal Customer,46,Business travel,Business,2589,3,3,3,3,4,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +67258,128856,Female,disloyal Customer,36,Business travel,Business,2586,2,2,2,4,2,2,2,3,4,4,5,2,4,2,2,0.0,neutral or dissatisfied +67259,98361,Female,Loyal Customer,51,Business travel,Business,2500,5,5,5,5,2,4,3,5,5,5,5,3,5,3,11,0.0,satisfied +67260,59931,Female,Loyal Customer,47,Business travel,Business,1562,4,4,4,4,3,4,4,5,5,5,5,3,5,5,11,0.0,satisfied +67261,17361,Male,Loyal Customer,27,Personal Travel,Eco,563,4,5,4,4,2,4,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +67262,23202,Female,Loyal Customer,16,Personal Travel,Eco Plus,300,2,5,2,3,4,2,4,4,3,2,5,3,5,4,31,28.0,neutral or dissatisfied +67263,48823,Female,Loyal Customer,58,Personal Travel,Business,308,1,4,1,3,5,4,5,4,4,1,4,3,4,4,13,20.0,neutral or dissatisfied +67264,60655,Female,Loyal Customer,46,Business travel,Eco,1620,1,1,1,1,1,4,3,1,1,1,1,1,1,3,4,10.0,neutral or dissatisfied +67265,24393,Male,Loyal Customer,64,Personal Travel,Eco,669,2,4,2,4,5,2,1,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +67266,5221,Male,Loyal Customer,58,Business travel,Business,3109,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +67267,62718,Female,Loyal Customer,51,Business travel,Eco,2556,4,5,4,5,4,4,4,4,5,4,3,4,3,4,3,0.0,neutral or dissatisfied +67268,16788,Male,Loyal Customer,8,Business travel,Eco Plus,569,4,1,1,1,4,4,5,4,2,1,1,3,5,4,0,0.0,satisfied +67269,53080,Male,Loyal Customer,39,Personal Travel,Eco Plus,1190,2,5,2,3,4,2,4,4,4,4,3,5,4,4,27,34.0,neutral or dissatisfied +67270,33421,Female,Loyal Customer,40,Business travel,Eco,2462,2,4,4,4,2,2,2,1,3,5,5,2,4,2,0,16.0,satisfied +67271,70569,Male,Loyal Customer,67,Personal Travel,Eco,1258,3,4,3,1,3,3,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +67272,69256,Female,Loyal Customer,49,Business travel,Business,733,4,4,4,4,4,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +67273,116105,Female,Loyal Customer,20,Personal Travel,Eco,333,3,5,3,3,1,3,1,1,5,3,5,4,5,1,77,83.0,neutral or dissatisfied +67274,126451,Female,Loyal Customer,57,Business travel,Business,1972,2,2,2,2,5,1,2,2,2,2,2,2,2,1,0,10.0,neutral or dissatisfied +67275,51760,Male,Loyal Customer,58,Personal Travel,Eco,509,2,4,2,3,3,2,2,3,4,5,5,3,5,3,24,7.0,neutral or dissatisfied +67276,28883,Male,disloyal Customer,18,Business travel,Eco,671,4,4,4,3,2,4,2,2,1,1,2,3,4,2,0,0.0,satisfied +67277,54575,Female,Loyal Customer,10,Personal Travel,Eco Plus,802,3,1,3,3,2,3,2,2,2,3,2,1,3,2,0,0.0,neutral or dissatisfied +67278,94959,Female,Loyal Customer,16,Business travel,Business,3672,3,5,5,5,3,3,3,3,2,1,4,1,3,3,44,40.0,neutral or dissatisfied +67279,91829,Female,Loyal Customer,23,Business travel,Business,588,2,2,2,2,3,3,3,3,5,2,4,3,4,3,56,49.0,satisfied +67280,42664,Female,Loyal Customer,28,Business travel,Business,604,1,1,1,1,1,2,1,1,4,4,3,3,4,1,0,0.0,neutral or dissatisfied +67281,90037,Male,Loyal Customer,34,Business travel,Business,1127,1,1,1,1,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +67282,36736,Male,Loyal Customer,43,Business travel,Business,1754,3,5,5,5,4,3,3,3,3,3,3,1,3,1,5,5.0,neutral or dissatisfied +67283,37971,Female,Loyal Customer,41,Business travel,Business,1249,3,2,2,2,1,3,4,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +67284,50216,Female,disloyal Customer,26,Business travel,Eco,109,2,1,2,3,1,2,1,1,1,4,3,3,4,1,14,10.0,neutral or dissatisfied +67285,50004,Male,Loyal Customer,35,Business travel,Business,86,3,2,2,2,2,3,3,1,1,1,3,2,1,3,0,0.0,neutral or dissatisfied +67286,117403,Female,Loyal Customer,43,Personal Travel,Business,1136,5,5,5,1,4,5,4,1,1,5,1,5,1,5,0,1.0,satisfied +67287,64796,Female,disloyal Customer,33,Business travel,Business,551,3,3,3,2,4,3,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +67288,2154,Male,Loyal Customer,48,Business travel,Business,2541,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +67289,63200,Male,Loyal Customer,54,Business travel,Business,447,4,4,4,4,4,4,5,5,5,5,5,5,5,4,4,8.0,satisfied +67290,48263,Female,disloyal Customer,28,Personal Travel,Eco,236,3,4,0,3,3,0,3,3,3,5,4,2,3,3,9,0.0,neutral or dissatisfied +67291,67911,Male,Loyal Customer,7,Personal Travel,Eco,1464,3,3,3,4,4,3,1,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +67292,49167,Female,Loyal Customer,61,Business travel,Business,190,5,5,5,5,3,3,1,3,3,4,5,4,3,1,15,18.0,satisfied +67293,116024,Female,Loyal Customer,67,Personal Travel,Eco,417,1,3,1,4,3,4,4,4,4,1,4,5,4,4,23,16.0,neutral or dissatisfied +67294,44108,Female,Loyal Customer,35,Personal Travel,Eco,408,3,5,3,3,3,3,1,3,5,2,4,3,4,3,27,14.0,neutral or dissatisfied +67295,37870,Male,Loyal Customer,35,Business travel,Business,937,3,1,4,1,1,4,4,3,3,3,3,1,3,1,18,14.0,neutral or dissatisfied +67296,81340,Female,disloyal Customer,39,Business travel,Business,1299,1,1,1,3,5,1,5,5,4,4,4,2,3,5,35,21.0,neutral or dissatisfied +67297,25238,Male,Loyal Customer,52,Personal Travel,Eco,919,3,4,3,2,4,3,4,4,3,3,5,4,4,4,11,9.0,neutral or dissatisfied +67298,67096,Female,Loyal Customer,40,Business travel,Business,964,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +67299,30674,Male,Loyal Customer,56,Business travel,Eco,680,4,2,3,2,4,4,4,4,4,3,5,5,4,4,1,0.0,satisfied +67300,30979,Female,disloyal Customer,25,Business travel,Eco,1294,3,3,3,1,3,3,3,3,3,1,1,3,2,3,0,0.0,neutral or dissatisfied +67301,86237,Female,Loyal Customer,40,Personal Travel,Eco,356,3,5,3,3,5,3,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +67302,129301,Female,Loyal Customer,58,Business travel,Business,2586,5,5,5,5,5,3,5,2,2,2,2,3,2,4,0,0.0,satisfied +67303,4281,Female,Loyal Customer,76,Business travel,Business,2061,4,4,4,4,4,1,4,4,4,4,3,4,4,4,0,0.0,satisfied +67304,51393,Male,Loyal Customer,19,Personal Travel,Eco Plus,89,2,3,2,1,4,2,1,4,1,2,5,5,3,4,0,0.0,neutral or dissatisfied +67305,30810,Female,Loyal Customer,44,Business travel,Business,799,3,5,5,5,1,4,4,3,3,3,3,2,3,3,34,30.0,neutral or dissatisfied +67306,73633,Male,Loyal Customer,51,Business travel,Business,192,0,5,0,1,2,4,4,3,3,3,3,5,3,5,1,13.0,satisfied +67307,32504,Female,Loyal Customer,50,Business travel,Business,3433,1,1,4,1,3,3,3,5,5,5,4,2,5,3,3,0.0,satisfied +67308,81867,Female,Loyal Customer,53,Business travel,Business,3924,2,2,2,2,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +67309,53775,Male,Loyal Customer,65,Business travel,Business,3801,5,5,5,5,5,5,4,4,4,4,5,4,4,3,30,21.0,satisfied +67310,102861,Female,Loyal Customer,16,Personal Travel,Eco Plus,423,3,4,3,3,1,3,1,1,4,1,2,1,1,1,7,11.0,neutral or dissatisfied +67311,124165,Male,disloyal Customer,17,Business travel,Eco,2133,2,2,2,3,2,2,2,2,1,4,4,4,4,2,0,11.0,neutral or dissatisfied +67312,67379,Male,Loyal Customer,53,Business travel,Business,3636,2,2,2,2,3,5,5,5,5,4,5,4,5,3,44,43.0,satisfied +67313,58485,Male,disloyal Customer,25,Business travel,Business,719,5,4,5,5,2,5,4,2,3,4,5,4,4,2,65,45.0,satisfied +67314,73173,Female,disloyal Customer,24,Business travel,Business,1258,4,4,4,3,2,4,2,2,5,5,5,3,4,2,3,0.0,satisfied +67315,96246,Female,Loyal Customer,55,Personal Travel,Eco,546,2,4,4,4,2,4,4,3,3,4,3,3,3,3,1,0.0,neutral or dissatisfied +67316,11122,Female,Loyal Customer,44,Personal Travel,Eco,312,3,4,3,4,3,4,3,1,1,3,1,3,1,3,95,86.0,neutral or dissatisfied +67317,88986,Male,Loyal Customer,46,Personal Travel,Eco,1199,2,4,2,3,5,2,5,5,5,2,3,4,4,5,0,0.0,neutral or dissatisfied +67318,43479,Female,Loyal Customer,46,Business travel,Business,2551,1,1,1,1,5,3,3,1,1,2,1,3,1,1,42,60.0,neutral or dissatisfied +67319,19293,Female,disloyal Customer,40,Business travel,Business,299,3,3,3,3,5,3,5,5,1,3,4,3,3,5,10,9.0,neutral or dissatisfied +67320,91665,Male,Loyal Customer,61,Business travel,Eco Plus,1199,4,3,3,3,4,4,4,1,4,3,4,4,2,4,342,366.0,neutral or dissatisfied +67321,70651,Female,disloyal Customer,32,Business travel,Business,946,3,3,3,3,5,3,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +67322,25182,Female,Loyal Customer,30,Business travel,Business,577,2,5,5,5,2,2,2,2,4,1,2,3,2,2,0,0.0,neutral or dissatisfied +67323,23751,Female,Loyal Customer,28,Business travel,Business,3048,4,4,4,4,2,2,2,2,4,4,1,3,5,2,33,27.0,satisfied +67324,94776,Female,Loyal Customer,55,Business travel,Eco,441,1,3,3,3,3,2,2,1,1,1,1,3,1,1,3,8.0,neutral or dissatisfied +67325,105580,Male,Loyal Customer,52,Personal Travel,Eco,577,3,3,3,4,1,3,1,1,2,2,4,2,4,1,10,23.0,neutral or dissatisfied +67326,67444,Male,Loyal Customer,35,Personal Travel,Eco,678,4,3,4,4,2,4,4,2,4,4,5,1,4,2,0,20.0,satisfied +67327,44185,Female,Loyal Customer,41,Business travel,Business,157,2,2,3,2,3,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +67328,46326,Female,disloyal Customer,54,Business travel,Eco,420,4,4,4,5,2,4,2,2,2,3,4,3,2,2,12,25.0,satisfied +67329,64050,Female,disloyal Customer,35,Business travel,Business,921,2,2,2,3,4,2,1,4,3,3,4,5,5,4,7,0.0,neutral or dissatisfied +67330,20423,Male,Loyal Customer,39,Business travel,Eco,299,4,2,3,2,4,4,4,4,5,3,5,2,1,4,0,0.0,satisfied +67331,32778,Male,Loyal Customer,16,Business travel,Business,216,4,4,4,4,5,5,3,5,4,3,4,1,2,5,0,0.0,satisfied +67332,104841,Female,Loyal Customer,63,Personal Travel,Eco,426,2,3,3,3,1,4,4,1,1,3,1,1,1,3,33,20.0,neutral or dissatisfied +67333,116900,Male,Loyal Customer,40,Business travel,Business,370,5,4,5,5,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +67334,77537,Male,Loyal Customer,48,Business travel,Business,1881,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +67335,87274,Male,disloyal Customer,26,Business travel,Eco,577,4,4,3,4,3,3,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +67336,116565,Female,Loyal Customer,52,Business travel,Business,1584,4,4,4,4,4,5,5,2,2,2,2,3,2,5,3,0.0,satisfied +67337,29530,Male,Loyal Customer,21,Personal Travel,Eco,1009,1,3,1,5,5,1,5,5,5,3,4,2,5,5,4,0.0,neutral or dissatisfied +67338,119824,Male,Loyal Customer,26,Business travel,Business,2997,4,4,4,4,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +67339,27947,Female,Loyal Customer,23,Business travel,Eco,1874,0,5,0,2,3,0,3,3,5,1,4,1,2,3,0,0.0,satisfied +67340,117083,Male,disloyal Customer,36,Business travel,Eco,304,3,3,2,3,3,2,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +67341,83106,Male,Loyal Customer,53,Personal Travel,Eco,983,3,1,3,3,1,3,4,1,3,5,4,1,4,1,4,0.0,neutral or dissatisfied +67342,40356,Male,disloyal Customer,38,Business travel,Business,850,3,3,3,4,1,3,5,1,2,4,3,1,4,1,0,,neutral or dissatisfied +67343,20514,Male,Loyal Customer,33,Personal Travel,Eco Plus,139,2,3,2,3,2,2,5,2,3,1,4,4,3,2,31,36.0,neutral or dissatisfied +67344,2954,Male,Loyal Customer,56,Business travel,Business,3635,3,3,3,3,2,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +67345,123744,Female,disloyal Customer,37,Business travel,Business,96,2,2,2,1,2,2,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +67346,26908,Female,disloyal Customer,23,Business travel,Eco,1109,5,5,5,1,3,5,3,3,2,5,3,2,5,3,14,18.0,satisfied +67347,73964,Female,Loyal Customer,27,Personal Travel,Eco,2342,5,3,5,3,5,3,3,2,5,3,2,3,4,3,0,0.0,satisfied +67348,117777,Male,Loyal Customer,57,Business travel,Business,1912,5,5,5,5,3,3,5,5,5,5,5,3,5,5,12,16.0,satisfied +67349,28582,Female,disloyal Customer,36,Business travel,Eco,1103,3,3,3,3,2,3,2,2,5,5,3,2,1,2,0,0.0,neutral or dissatisfied +67350,120114,Male,Loyal Customer,40,Business travel,Business,1576,3,3,3,3,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +67351,985,Female,disloyal Customer,25,Business travel,Eco,282,2,3,2,2,1,2,1,1,2,1,5,5,5,1,0,0.0,neutral or dissatisfied +67352,68360,Female,Loyal Customer,25,Business travel,Business,2072,4,4,4,4,3,3,3,3,4,4,3,4,5,3,0,0.0,satisfied +67353,125756,Female,Loyal Customer,58,Business travel,Business,2818,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +67354,58870,Male,Loyal Customer,36,Business travel,Business,2934,4,4,4,4,5,5,5,5,5,5,5,5,5,4,4,7.0,satisfied +67355,29297,Male,Loyal Customer,34,Business travel,Business,3947,4,4,4,4,4,4,1,2,2,2,2,4,2,5,0,8.0,satisfied +67356,121719,Male,Loyal Customer,50,Personal Travel,Eco,683,1,4,1,4,5,1,5,5,3,3,4,4,4,5,10,23.0,neutral or dissatisfied +67357,46708,Female,Loyal Customer,42,Personal Travel,Eco,125,2,3,2,2,3,2,4,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +67358,32267,Female,Loyal Customer,46,Business travel,Business,102,2,2,2,2,3,2,5,5,5,5,4,4,5,3,0,0.0,satisfied +67359,59038,Male,Loyal Customer,9,Business travel,Business,1723,1,3,5,3,1,1,1,1,2,4,1,3,2,1,30,31.0,neutral or dissatisfied +67360,96530,Female,Loyal Customer,67,Personal Travel,Eco,436,2,3,2,4,1,4,3,4,4,2,4,1,4,4,20,12.0,neutral or dissatisfied +67361,25344,Female,Loyal Customer,29,Personal Travel,Eco Plus,829,2,4,2,3,4,2,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +67362,65252,Female,disloyal Customer,16,Business travel,Eco Plus,469,1,1,1,3,4,1,4,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +67363,30136,Female,Loyal Customer,23,Personal Travel,Eco,204,2,5,2,5,4,2,4,4,3,3,1,2,3,4,0,0.0,neutral or dissatisfied +67364,82418,Female,disloyal Customer,26,Business travel,Business,502,2,0,2,3,3,2,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +67365,62120,Female,Loyal Customer,44,Business travel,Business,2565,3,3,3,3,2,3,5,5,5,5,5,5,5,3,12,0.0,satisfied +67366,128262,Male,Loyal Customer,50,Business travel,Business,3572,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +67367,36461,Female,disloyal Customer,35,Personal Travel,Eco,867,1,3,1,5,5,1,4,5,4,1,1,1,3,5,0,5.0,neutral or dissatisfied +67368,117961,Female,Loyal Customer,33,Business travel,Business,2072,2,4,5,5,1,3,4,2,2,2,2,3,2,1,27,20.0,neutral or dissatisfied +67369,121491,Male,Loyal Customer,62,Personal Travel,Eco,290,1,4,1,2,1,1,1,1,3,2,5,4,1,1,0,0.0,neutral or dissatisfied +67370,3763,Male,Loyal Customer,24,Business travel,Business,599,2,2,2,2,2,2,2,3,3,4,4,2,5,2,172,156.0,satisfied +67371,103958,Male,Loyal Customer,50,Personal Travel,Eco,533,2,5,2,1,2,2,5,2,4,5,4,4,5,2,38,27.0,neutral or dissatisfied +67372,62818,Female,Loyal Customer,57,Personal Travel,Eco,2486,2,3,2,3,5,3,5,3,3,2,5,5,3,4,0,0.0,neutral or dissatisfied +67373,20958,Female,Loyal Customer,57,Business travel,Eco,803,3,1,2,1,4,3,3,3,3,3,3,4,3,2,55,51.0,neutral or dissatisfied +67374,27790,Male,Loyal Customer,48,Business travel,Eco,1448,2,1,1,1,2,2,2,2,1,2,2,2,2,2,0,0.0,neutral or dissatisfied +67375,108851,Male,Loyal Customer,31,Business travel,Business,2139,1,1,1,1,5,5,5,5,5,3,4,3,4,5,46,42.0,satisfied +67376,55925,Female,Loyal Customer,58,Personal Travel,Eco,473,2,2,2,4,5,4,4,1,1,2,1,1,1,2,2,0.0,neutral or dissatisfied +67377,86856,Male,Loyal Customer,17,Personal Travel,Eco,484,3,0,3,1,5,3,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +67378,74697,Female,Loyal Customer,19,Personal Travel,Eco,1171,3,5,3,3,4,3,3,4,3,5,5,5,4,4,40,10.0,neutral or dissatisfied +67379,90798,Female,Loyal Customer,41,Business travel,Business,2951,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +67380,97870,Male,Loyal Customer,52,Business travel,Business,2747,1,1,1,1,4,4,4,3,3,3,3,5,3,5,9,7.0,satisfied +67381,11400,Female,Loyal Customer,39,Business travel,Business,2595,0,5,0,4,5,5,5,1,1,1,1,4,1,3,3,1.0,satisfied +67382,123934,Female,Loyal Customer,36,Personal Travel,Eco,544,3,4,3,1,5,3,1,5,3,2,5,3,1,5,0,23.0,neutral or dissatisfied +67383,98664,Female,Loyal Customer,50,Personal Travel,Eco,920,4,3,4,3,5,4,3,2,2,4,5,3,2,2,28,19.0,neutral or dissatisfied +67384,118529,Female,Loyal Customer,55,Business travel,Eco,325,2,2,2,2,4,3,3,3,3,2,3,1,3,2,2,6.0,neutral or dissatisfied +67385,14886,Female,disloyal Customer,45,Business travel,Eco,315,4,0,4,4,5,4,5,5,2,5,4,1,3,5,0,0.0,satisfied +67386,81676,Male,Loyal Customer,59,Business travel,Business,2491,2,1,1,1,1,2,3,2,2,2,2,1,2,3,5,0.0,neutral or dissatisfied +67387,80030,Male,Loyal Customer,38,Personal Travel,Eco,950,3,1,3,4,5,3,5,5,3,4,3,3,4,5,55,46.0,neutral or dissatisfied +67388,25670,Female,Loyal Customer,35,Personal Travel,Eco,761,2,1,2,4,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +67389,125898,Male,Loyal Customer,15,Personal Travel,Eco,1013,4,3,4,4,3,4,1,3,1,1,4,4,4,3,21,17.0,neutral or dissatisfied +67390,116126,Male,Loyal Customer,28,Personal Travel,Eco,390,3,5,3,3,4,3,4,4,4,5,5,3,5,4,22,14.0,neutral or dissatisfied +67391,8159,Female,Loyal Customer,23,Business travel,Business,3956,3,1,1,1,3,3,3,3,1,5,3,3,2,3,22,26.0,neutral or dissatisfied +67392,104793,Male,Loyal Customer,40,Business travel,Business,3609,3,3,3,3,3,5,5,5,5,5,5,5,5,3,3,5.0,satisfied +67393,124293,Male,Loyal Customer,49,Business travel,Eco,601,4,5,5,5,4,4,4,4,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +67394,30654,Female,Loyal Customer,65,Personal Travel,Eco,533,3,4,3,2,3,5,5,4,4,3,4,5,4,4,0,15.0,neutral or dissatisfied +67395,38381,Female,disloyal Customer,25,Business travel,Eco Plus,1180,3,0,3,4,4,3,4,4,4,5,3,3,3,4,0,0.0,neutral or dissatisfied +67396,78908,Male,Loyal Customer,52,Business travel,Business,930,5,5,5,5,2,4,5,5,5,5,5,4,5,5,17,0.0,satisfied +67397,98224,Female,Loyal Customer,39,Personal Travel,Eco Plus,842,0,5,0,2,2,0,2,2,5,4,5,5,5,2,1,0.0,satisfied +67398,63737,Female,Loyal Customer,17,Personal Travel,Eco,1660,2,4,2,4,2,2,2,2,4,4,3,1,3,2,15,0.0,neutral or dissatisfied +67399,98745,Male,Loyal Customer,13,Personal Travel,Eco,1558,2,4,2,3,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +67400,53990,Female,Loyal Customer,53,Business travel,Business,1825,1,5,5,5,3,3,2,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +67401,55143,Female,Loyal Customer,46,Personal Travel,Eco,1635,3,5,3,3,4,4,4,5,5,3,4,4,5,3,0,6.0,neutral or dissatisfied +67402,125443,Female,Loyal Customer,48,Personal Travel,Business,2917,5,2,4,4,2,3,4,4,4,4,4,2,4,1,0,0.0,satisfied +67403,6973,Male,Loyal Customer,38,Business travel,Business,196,4,4,4,4,2,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +67404,65694,Male,disloyal Customer,25,Business travel,Business,1061,2,0,2,5,1,2,1,1,4,3,4,4,4,1,11,0.0,neutral or dissatisfied +67405,106190,Male,Loyal Customer,23,Personal Travel,Eco,436,1,4,1,1,3,1,3,3,3,5,4,5,5,3,2,0.0,neutral or dissatisfied +67406,119637,Female,Loyal Customer,20,Personal Travel,Eco,1727,1,5,1,3,1,1,1,1,1,3,5,4,3,1,0,0.0,neutral or dissatisfied +67407,116162,Male,Loyal Customer,45,Personal Travel,Eco,417,3,1,3,3,3,3,4,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +67408,94938,Female,disloyal Customer,20,Business travel,Eco,189,5,3,5,2,2,5,2,2,4,5,1,4,4,2,1,0.0,satisfied +67409,120645,Male,Loyal Customer,51,Business travel,Business,280,0,0,0,1,3,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +67410,77714,Male,Loyal Customer,29,Business travel,Business,2829,4,4,1,4,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +67411,87080,Male,disloyal Customer,23,Business travel,Eco,594,3,0,3,4,4,3,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +67412,5308,Male,Loyal Customer,21,Personal Travel,Eco,351,2,5,2,4,3,2,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +67413,103760,Male,Loyal Customer,47,Business travel,Business,2288,3,3,1,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +67414,7341,Female,Loyal Customer,54,Business travel,Eco,606,2,3,3,3,1,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +67415,61040,Male,disloyal Customer,24,Business travel,Eco,753,3,3,3,4,2,3,2,2,3,3,5,3,4,2,2,2.0,neutral or dissatisfied +67416,13315,Female,Loyal Customer,50,Personal Travel,Eco Plus,448,3,1,3,3,2,3,3,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +67417,110576,Female,disloyal Customer,20,Business travel,Eco,488,4,2,4,3,3,4,3,3,2,3,2,2,3,3,0,11.0,neutral or dissatisfied +67418,78777,Male,disloyal Customer,25,Business travel,Business,528,5,0,5,4,4,5,4,4,3,5,4,5,5,4,0,0.0,satisfied +67419,62407,Male,Loyal Customer,24,Personal Travel,Eco,2704,2,3,2,3,3,2,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +67420,3993,Male,Loyal Customer,57,Business travel,Business,3474,5,5,5,5,5,5,4,4,4,4,4,5,4,4,0,13.0,satisfied +67421,88443,Male,Loyal Customer,19,Business travel,Eco,406,4,1,4,1,4,4,3,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +67422,35209,Female,disloyal Customer,28,Business travel,Eco,1076,2,2,2,1,3,2,3,3,5,3,4,3,5,3,9,27.0,neutral or dissatisfied +67423,35774,Male,Loyal Customer,51,Business travel,Eco,200,4,1,5,1,4,4,4,4,4,5,4,3,3,4,0,0.0,satisfied +67424,62777,Male,Loyal Customer,68,Business travel,Business,3535,3,3,3,3,4,4,4,3,1,2,3,4,5,4,0,1.0,satisfied +67425,77004,Male,disloyal Customer,40,Business travel,Business,368,2,2,2,2,2,2,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +67426,71912,Female,Loyal Customer,15,Personal Travel,Eco,1723,2,5,2,2,2,2,2,2,3,2,3,4,5,2,12,13.0,neutral or dissatisfied +67427,83548,Female,Loyal Customer,22,Business travel,Business,1121,3,3,5,3,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +67428,54716,Male,Loyal Customer,64,Personal Travel,Eco,787,1,2,1,1,2,1,2,2,4,5,1,4,1,2,0,0.0,neutral or dissatisfied +67429,55800,Female,Loyal Customer,44,Business travel,Business,1416,1,5,5,5,3,2,1,1,1,1,1,2,1,1,125,86.0,neutral or dissatisfied +67430,88270,Male,Loyal Customer,22,Business travel,Business,515,4,4,4,4,5,5,5,5,5,5,4,3,4,5,12,3.0,satisfied +67431,16641,Female,Loyal Customer,41,Business travel,Business,2913,2,5,5,5,5,3,4,2,2,1,2,2,2,1,0,14.0,neutral or dissatisfied +67432,44483,Female,disloyal Customer,23,Business travel,Eco,589,2,2,2,3,3,2,2,3,3,1,3,2,4,3,24,15.0,neutral or dissatisfied +67433,56707,Male,Loyal Customer,45,Personal Travel,Eco,1023,4,2,5,3,4,5,3,4,2,4,3,3,4,4,0,3.0,neutral or dissatisfied +67434,105262,Male,Loyal Customer,43,Business travel,Business,2106,5,1,5,5,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +67435,109436,Female,Loyal Customer,60,Business travel,Business,1712,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +67436,95564,Male,Loyal Customer,65,Personal Travel,Eco Plus,677,2,5,2,4,1,2,1,1,3,4,4,4,4,1,21,4.0,neutral or dissatisfied +67437,72557,Male,Loyal Customer,60,Business travel,Business,2728,1,2,1,1,2,4,4,1,1,2,1,3,1,4,0,0.0,satisfied +67438,44854,Female,Loyal Customer,41,Business travel,Business,2246,4,4,1,4,2,5,5,4,4,5,4,3,4,3,13,21.0,satisfied +67439,2113,Female,Loyal Customer,34,Business travel,Business,3036,4,2,4,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +67440,43455,Male,Loyal Customer,40,Business travel,Business,2313,1,1,1,1,5,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +67441,6582,Male,Loyal Customer,42,Business travel,Business,207,4,4,4,4,4,5,3,4,4,4,4,3,4,1,0,0.0,satisfied +67442,90427,Female,disloyal Customer,26,Business travel,Business,515,4,5,4,3,2,4,3,2,5,4,4,5,4,2,25,40.0,neutral or dissatisfied +67443,9054,Female,disloyal Customer,17,Business travel,Business,212,5,3,5,1,2,5,2,2,3,2,4,3,5,2,3,0.0,satisfied +67444,110699,Male,Loyal Customer,21,Personal Travel,Eco,829,1,5,1,3,5,1,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +67445,17304,Female,Loyal Customer,43,Business travel,Eco,403,5,3,3,3,5,5,5,1,3,1,3,5,3,5,167,176.0,satisfied +67446,118029,Female,disloyal Customer,54,Business travel,Business,1262,3,3,3,2,4,3,4,4,3,5,5,3,4,4,51,46.0,neutral or dissatisfied +67447,17613,Female,Loyal Customer,74,Business travel,Eco,326,4,3,5,5,5,5,5,4,4,4,4,4,4,2,0,0.0,satisfied +67448,13603,Male,Loyal Customer,30,Business travel,Eco Plus,152,5,5,5,5,5,5,5,5,3,1,1,3,3,5,0,0.0,satisfied +67449,22223,Male,Loyal Customer,29,Business travel,Eco Plus,565,0,0,0,2,2,0,3,2,1,5,4,5,5,2,0,0.0,satisfied +67450,85599,Female,Loyal Customer,63,Business travel,Eco,259,4,1,1,1,3,2,5,4,4,4,4,3,4,5,0,1.0,satisfied +67451,78341,Female,Loyal Customer,46,Business travel,Eco,1547,3,2,5,2,2,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +67452,116247,Male,Loyal Customer,12,Personal Travel,Eco,373,1,4,1,2,3,1,3,3,5,2,1,5,1,3,0,0.0,neutral or dissatisfied +67453,879,Female,Loyal Customer,80,Business travel,Business,229,4,5,5,5,5,3,3,4,4,4,4,4,4,1,2,0.0,neutral or dissatisfied +67454,96338,Male,disloyal Customer,31,Business travel,Business,1609,1,0,0,4,5,0,5,5,5,3,3,4,4,5,39,3.0,neutral or dissatisfied +67455,91172,Female,Loyal Customer,57,Personal Travel,Eco,404,2,5,2,3,4,5,4,1,1,2,1,5,1,4,0,13.0,neutral or dissatisfied +67456,66000,Female,disloyal Customer,27,Business travel,Business,1055,1,1,1,4,1,1,1,1,1,4,3,3,4,1,5,0.0,neutral or dissatisfied +67457,17162,Male,Loyal Customer,47,Business travel,Eco,643,4,2,2,2,4,4,4,4,4,4,2,3,4,4,90,89.0,satisfied +67458,72168,Male,Loyal Customer,52,Personal Travel,Eco Plus,731,2,1,2,2,1,2,4,1,1,4,2,4,3,1,6,24.0,neutral or dissatisfied +67459,104247,Male,Loyal Customer,28,Business travel,Business,1780,3,3,3,3,5,5,5,5,3,2,4,5,5,5,9,0.0,satisfied +67460,2594,Female,Loyal Customer,63,Personal Travel,Eco,227,0,2,0,4,2,4,3,4,4,0,5,4,4,2,0,0.0,satisfied +67461,68776,Male,Loyal Customer,27,Business travel,Business,1793,4,5,5,5,4,3,4,4,2,3,3,2,4,4,22,26.0,neutral or dissatisfied +67462,128908,Female,disloyal Customer,25,Business travel,Business,870,5,0,5,1,3,5,3,3,5,4,4,4,5,3,0,2.0,satisfied +67463,97681,Female,Loyal Customer,44,Personal Travel,Eco,491,3,5,3,4,5,5,5,4,4,3,4,4,4,5,45,33.0,neutral or dissatisfied +67464,10017,Female,Loyal Customer,62,Personal Travel,Eco Plus,508,3,5,3,5,5,4,5,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +67465,54525,Male,Loyal Customer,29,Personal Travel,Eco,925,2,4,2,4,4,2,4,4,5,1,2,1,1,4,0,0.0,neutral or dissatisfied +67466,88832,Male,Loyal Customer,36,Personal Travel,Eco Plus,270,4,3,4,4,2,4,1,2,4,4,4,1,4,2,0,0.0,satisfied +67467,46448,Female,Loyal Customer,59,Business travel,Business,3146,4,4,4,4,3,5,5,4,4,4,4,5,4,3,3,2.0,satisfied +67468,78825,Female,Loyal Customer,26,Personal Travel,Eco,554,1,5,1,2,3,1,3,3,3,4,5,4,5,3,12,2.0,neutral or dissatisfied +67469,4662,Female,disloyal Customer,23,Business travel,Eco,364,2,1,2,2,2,2,2,2,4,1,2,4,3,2,0,14.0,neutral or dissatisfied +67470,48159,Male,disloyal Customer,37,Business travel,Eco,391,3,0,3,4,5,3,5,5,4,4,5,1,2,5,0,0.0,neutral or dissatisfied +67471,27521,Male,Loyal Customer,18,Personal Travel,Eco,697,2,5,2,1,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +67472,7083,Male,Loyal Customer,37,Business travel,Business,3997,1,1,4,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +67473,21113,Male,Loyal Customer,69,Personal Travel,Eco,106,1,5,1,3,2,1,2,2,4,3,4,4,5,2,69,73.0,neutral or dissatisfied +67474,42193,Female,Loyal Customer,59,Business travel,Eco,451,2,2,2,2,1,5,5,3,3,2,3,4,3,5,0,2.0,satisfied +67475,111459,Female,Loyal Customer,41,Personal Travel,Eco,836,3,4,3,1,4,3,2,4,4,5,5,4,5,4,18,21.0,neutral or dissatisfied +67476,118032,Male,disloyal Customer,29,Business travel,Business,1044,5,5,5,1,4,5,4,4,3,5,5,3,4,4,0,0.0,satisfied +67477,81524,Male,Loyal Customer,36,Business travel,Business,3472,4,4,4,4,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +67478,102523,Female,Loyal Customer,16,Personal Travel,Eco,414,2,1,2,2,4,2,4,4,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +67479,7725,Female,Loyal Customer,60,Business travel,Business,406,3,3,4,3,1,4,5,2,2,2,2,5,2,3,0,1.0,satisfied +67480,96697,Female,disloyal Customer,42,Business travel,Business,696,3,3,3,1,5,3,5,5,3,3,5,3,4,5,47,52.0,satisfied +67481,20811,Male,Loyal Customer,28,Business travel,Business,508,2,4,5,4,2,2,2,2,3,5,1,1,2,2,0,0.0,neutral or dissatisfied +67482,100585,Male,Loyal Customer,63,Personal Travel,Eco,486,1,5,1,4,2,1,3,2,4,2,5,5,4,2,1,0.0,neutral or dissatisfied +67483,41951,Female,disloyal Customer,17,Business travel,Eco,575,1,0,1,3,5,1,5,5,3,4,2,2,1,5,0,0.0,neutral or dissatisfied +67484,46838,Male,Loyal Customer,59,Business travel,Eco,846,2,4,4,4,2,2,2,2,1,4,3,3,3,2,11,10.0,satisfied +67485,9002,Male,Loyal Customer,43,Business travel,Business,1566,5,5,5,5,5,5,5,4,4,4,4,4,4,3,12,0.0,satisfied +67486,121396,Male,Loyal Customer,45,Personal Travel,Business,331,4,5,2,5,4,3,5,4,4,2,5,1,4,3,0,3.0,neutral or dissatisfied +67487,55204,Male,Loyal Customer,22,Personal Travel,Eco Plus,1635,3,5,3,2,5,3,1,5,3,2,5,4,4,5,9,0.0,neutral or dissatisfied +67488,47332,Male,disloyal Customer,22,Business travel,Eco,599,0,0,0,1,2,0,2,2,1,4,1,4,5,2,3,0.0,satisfied +67489,61083,Male,disloyal Customer,20,Business travel,Eco,1062,5,5,5,5,5,5,1,5,4,1,2,5,2,5,0,0.0,satisfied +67490,93287,Female,Loyal Customer,44,Personal Travel,Eco,867,2,5,2,3,2,2,2,4,4,2,4,1,4,1,29,35.0,neutral or dissatisfied +67491,11427,Female,Loyal Customer,57,Business travel,Eco Plus,158,3,3,4,4,1,3,4,3,3,3,3,4,3,3,99,93.0,neutral or dissatisfied +67492,6940,Female,Loyal Customer,42,Business travel,Eco,501,2,1,1,1,4,4,3,3,3,2,3,4,3,4,0,22.0,neutral or dissatisfied +67493,72509,Male,disloyal Customer,15,Business travel,Eco,918,3,3,3,4,4,3,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +67494,127850,Female,Loyal Customer,41,Personal Travel,Business,1276,3,1,3,3,1,3,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +67495,87722,Male,Loyal Customer,25,Business travel,Business,591,1,1,1,1,5,4,5,5,4,2,5,4,5,5,1,0.0,satisfied +67496,20775,Male,Loyal Customer,36,Business travel,Business,515,5,5,5,5,2,3,3,5,5,5,5,4,5,3,43,26.0,satisfied +67497,90467,Male,Loyal Customer,35,Business travel,Business,271,0,0,0,4,5,5,5,3,3,3,3,5,3,5,18,16.0,satisfied +67498,1297,Male,Loyal Customer,59,Personal Travel,Eco,113,3,5,3,1,3,3,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +67499,62477,Female,disloyal Customer,41,Business travel,Business,1846,1,1,1,2,3,1,4,3,5,5,5,5,4,3,7,11.0,neutral or dissatisfied +67500,70942,Male,disloyal Customer,20,Business travel,Eco,612,2,0,2,3,4,2,4,4,5,3,2,5,4,4,2,0.0,neutral or dissatisfied +67501,140,Male,Loyal Customer,31,Business travel,Business,3538,4,4,4,4,4,4,4,4,4,5,4,4,5,4,0,5.0,satisfied +67502,104827,Female,Loyal Customer,44,Business travel,Business,472,5,5,5,5,3,5,5,5,5,5,5,3,5,3,36,29.0,satisfied +67503,77326,Female,Loyal Customer,49,Business travel,Business,590,5,5,5,5,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +67504,116916,Female,Loyal Customer,44,Business travel,Business,2092,3,3,3,3,4,5,5,5,5,4,5,4,5,4,17,25.0,satisfied +67505,125165,Male,Loyal Customer,60,Business travel,Business,2063,3,3,3,3,3,4,4,4,4,4,4,3,4,5,18,0.0,satisfied +67506,83479,Male,Loyal Customer,24,Business travel,Business,3713,3,3,3,3,4,4,4,4,4,2,4,5,5,4,4,0.0,satisfied +67507,101540,Female,Loyal Customer,58,Personal Travel,Eco,345,1,4,1,1,2,4,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +67508,48049,Male,Loyal Customer,30,Personal Travel,Eco,710,5,2,5,3,1,5,1,1,3,1,4,2,3,1,0,4.0,satisfied +67509,44762,Male,Loyal Customer,38,Business travel,Business,2156,4,4,4,4,1,1,3,5,5,5,5,1,5,5,13,18.0,satisfied +67510,115384,Male,Loyal Customer,37,Business travel,Business,2117,4,4,4,4,5,4,4,4,4,4,4,5,4,4,3,1.0,satisfied +67511,96895,Female,Loyal Customer,64,Personal Travel,Eco,781,4,2,4,3,1,3,3,3,3,4,5,3,3,3,63,57.0,neutral or dissatisfied +67512,83359,Female,Loyal Customer,56,Business travel,Business,2741,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +67513,86846,Female,Loyal Customer,50,Personal Travel,Eco,484,1,2,1,2,2,3,5,4,4,1,4,4,4,3,15,0.0,neutral or dissatisfied +67514,92826,Female,disloyal Customer,31,Business travel,Eco,1311,3,3,3,2,3,3,3,3,4,4,1,4,2,3,0,0.0,neutral or dissatisfied +67515,112024,Male,Loyal Customer,48,Business travel,Eco,680,1,1,3,1,1,1,1,1,2,3,3,1,3,1,6,7.0,neutral or dissatisfied +67516,83303,Male,disloyal Customer,36,Business travel,Eco Plus,579,2,2,2,2,3,2,3,3,5,1,3,2,4,3,0,0.0,neutral or dissatisfied +67517,23936,Male,Loyal Customer,63,Business travel,Business,616,4,4,4,4,5,1,3,3,3,5,3,3,3,3,0,0.0,satisfied +67518,111170,Female,Loyal Customer,48,Business travel,Business,1546,2,4,5,4,4,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +67519,29055,Female,Loyal Customer,43,Personal Travel,Eco,954,5,1,4,1,4,4,1,5,5,4,5,5,5,1,102,81.0,satisfied +67520,90288,Male,Loyal Customer,39,Business travel,Eco,757,3,3,3,3,3,3,3,3,4,2,2,4,2,3,0,0.0,neutral or dissatisfied +67521,58356,Female,Loyal Customer,41,Business travel,Business,1766,2,2,2,2,4,4,4,2,2,2,2,3,2,2,1,0.0,neutral or dissatisfied +67522,99351,Female,Loyal Customer,19,Personal Travel,Eco,1771,3,2,3,2,3,3,3,3,3,1,2,2,3,3,0,0.0,neutral or dissatisfied +67523,1122,Female,Loyal Customer,15,Personal Travel,Eco,134,3,4,3,3,5,3,5,5,2,1,4,2,2,5,0,0.0,neutral or dissatisfied +67524,75248,Male,Loyal Customer,28,Personal Travel,Eco,1723,3,4,3,3,4,3,4,4,4,5,4,5,4,4,44,25.0,neutral or dissatisfied +67525,81613,Female,Loyal Customer,29,Personal Travel,Eco,334,2,5,2,3,5,2,1,5,3,2,5,3,5,5,109,97.0,neutral or dissatisfied +67526,69458,Female,Loyal Customer,24,Personal Travel,Eco,1096,3,4,3,2,1,3,1,1,3,5,5,4,5,1,23,10.0,neutral or dissatisfied +67527,17827,Male,Loyal Customer,42,Personal Travel,Eco,1042,4,5,4,2,1,4,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +67528,45344,Female,Loyal Customer,54,Personal Travel,Eco,461,1,5,1,3,3,5,5,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +67529,46751,Male,Loyal Customer,50,Personal Travel,Eco,125,3,3,3,4,3,3,3,3,1,2,3,3,3,3,3,8.0,neutral or dissatisfied +67530,4845,Female,Loyal Customer,69,Business travel,Business,408,3,4,4,4,3,4,3,3,3,3,3,2,3,4,0,8.0,neutral or dissatisfied +67531,100275,Male,Loyal Customer,40,Business travel,Business,3525,2,2,2,2,3,4,4,4,4,4,4,5,4,4,37,45.0,satisfied +67532,100147,Male,Loyal Customer,54,Business travel,Business,2129,2,3,3,3,4,3,4,2,2,2,2,2,2,2,84,77.0,neutral or dissatisfied +67533,122191,Male,Loyal Customer,31,Business travel,Business,546,5,5,5,5,4,4,4,4,3,3,5,4,4,4,7,0.0,satisfied +67534,59390,Female,Loyal Customer,35,Personal Travel,Eco,2504,3,5,2,5,3,2,3,3,5,4,3,4,1,3,7,0.0,neutral or dissatisfied +67535,56010,Female,Loyal Customer,56,Business travel,Business,2475,4,4,4,4,5,5,5,3,3,4,4,5,3,5,1,10.0,satisfied +67536,49916,Female,Loyal Customer,32,Business travel,Business,2364,0,0,0,4,1,1,1,1,5,4,5,1,3,1,8,0.0,satisfied +67537,14950,Female,disloyal Customer,25,Business travel,Eco,554,2,5,2,3,3,2,3,3,1,2,1,1,5,3,0,0.0,neutral or dissatisfied +67538,10434,Male,disloyal Customer,38,Business travel,Business,216,3,3,3,4,4,3,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +67539,20693,Male,disloyal Customer,28,Business travel,Eco,584,2,4,2,1,2,2,2,5,1,3,5,2,5,2,209,207.0,neutral or dissatisfied +67540,95380,Female,Loyal Customer,27,Personal Travel,Eco,562,2,4,2,4,3,2,3,3,5,4,5,4,5,3,43,36.0,neutral or dissatisfied +67541,29512,Female,Loyal Customer,9,Business travel,Eco Plus,1107,4,3,5,3,4,4,5,4,4,1,5,2,2,4,0,0.0,satisfied +67542,41731,Female,disloyal Customer,28,Business travel,Eco,695,1,1,1,2,4,1,4,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +67543,55537,Female,Loyal Customer,37,Business travel,Business,2437,1,2,2,2,4,4,3,1,1,1,1,2,1,4,6,8.0,neutral or dissatisfied +67544,71003,Female,Loyal Customer,39,Business travel,Business,802,4,4,4,4,2,5,5,5,5,5,5,4,5,3,57,74.0,satisfied +67545,26325,Female,Loyal Customer,69,Personal Travel,Eco,892,3,5,3,3,4,5,4,4,4,3,4,3,4,3,30,44.0,neutral or dissatisfied +67546,11991,Female,Loyal Customer,23,Personal Travel,Eco,643,3,4,3,3,5,3,5,5,4,3,1,2,5,5,0,3.0,neutral or dissatisfied +67547,41326,Male,Loyal Customer,40,Personal Travel,Eco Plus,978,4,5,4,3,5,4,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +67548,114312,Male,Loyal Customer,44,Personal Travel,Eco,967,3,4,3,4,1,3,1,1,5,5,4,5,5,1,9,0.0,neutral or dissatisfied +67549,19058,Male,Loyal Customer,50,Personal Travel,Business,569,3,4,3,3,5,5,5,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +67550,89209,Male,Loyal Customer,70,Personal Travel,Eco,2139,1,5,2,2,1,2,1,1,5,2,3,4,4,1,28,19.0,neutral or dissatisfied +67551,97013,Female,Loyal Customer,68,Personal Travel,Eco,794,1,4,1,1,5,4,5,2,2,1,2,4,2,5,4,10.0,neutral or dissatisfied +67552,74165,Male,Loyal Customer,26,Personal Travel,Eco,641,2,5,2,3,5,2,5,5,4,3,5,5,5,5,15,7.0,neutral or dissatisfied +67553,6130,Female,disloyal Customer,50,Business travel,Business,491,3,3,3,2,1,3,5,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +67554,32085,Female,Loyal Customer,36,Business travel,Eco,163,5,1,1,1,5,5,5,5,3,1,2,1,2,5,0,0.0,satisfied +67555,79241,Female,Loyal Customer,49,Business travel,Business,1598,3,3,3,3,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +67556,35655,Male,Loyal Customer,47,Business travel,Business,2586,1,1,4,1,4,5,5,4,5,5,3,5,3,5,5,2.0,satisfied +67557,33491,Male,Loyal Customer,49,Personal Travel,Eco,2496,2,1,2,3,4,2,4,4,1,1,4,1,4,4,0,0.0,neutral or dissatisfied +67558,99425,Female,Loyal Customer,9,Personal Travel,Eco,337,3,3,3,4,2,3,2,2,1,4,3,3,3,2,0,4.0,neutral or dissatisfied +67559,38860,Male,Loyal Customer,58,Business travel,Business,2300,3,3,3,3,3,4,5,4,4,4,4,5,4,4,44,15.0,satisfied +67560,1350,Male,Loyal Customer,39,Business travel,Business,2036,2,2,2,2,2,4,5,5,5,4,5,5,5,3,7,0.0,satisfied +67561,38035,Male,Loyal Customer,31,Business travel,Business,3053,1,1,1,1,2,2,2,2,3,3,4,4,2,2,0,0.0,satisfied +67562,34672,Male,Loyal Customer,14,Personal Travel,Business,301,3,3,4,4,3,4,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +67563,42699,Male,Loyal Customer,28,Personal Travel,Eco,516,3,3,2,3,4,2,4,4,1,4,3,5,1,4,0,0.0,neutral or dissatisfied +67564,1476,Female,Loyal Customer,18,Personal Travel,Eco Plus,695,2,4,2,3,1,2,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +67565,117911,Female,Loyal Customer,56,Business travel,Business,3488,2,2,2,2,5,4,5,5,5,5,5,4,5,4,17,6.0,satisfied +67566,107028,Female,Loyal Customer,46,Business travel,Business,3838,5,5,5,5,2,5,4,4,4,4,4,3,4,5,1,0.0,satisfied +67567,74820,Male,Loyal Customer,53,Personal Travel,Eco Plus,1126,4,4,4,2,4,4,1,4,5,3,4,4,4,4,5,0.0,neutral or dissatisfied +67568,81034,Male,Loyal Customer,19,Business travel,Business,1399,2,2,2,2,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +67569,9022,Female,Loyal Customer,48,Business travel,Business,3158,2,2,4,2,2,5,4,4,4,4,5,3,4,3,4,0.0,satisfied +67570,65237,Female,disloyal Customer,27,Business travel,Business,282,4,4,4,1,5,4,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +67571,36796,Male,Loyal Customer,44,Personal Travel,Eco,2611,3,3,2,1,2,5,5,2,5,5,1,5,5,5,21,17.0,neutral or dissatisfied +67572,8904,Female,Loyal Customer,34,Business travel,Business,510,5,5,5,5,5,5,5,4,5,4,5,5,3,5,137,135.0,satisfied +67573,20908,Female,disloyal Customer,40,Business travel,Business,689,2,2,2,3,4,2,4,4,2,4,4,1,5,4,0,0.0,neutral or dissatisfied +67574,13422,Male,Loyal Customer,44,Business travel,Eco,409,5,1,1,1,5,5,5,5,5,2,5,2,1,5,31,61.0,satisfied +67575,3885,Female,Loyal Customer,46,Business travel,Business,290,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +67576,91565,Female,Loyal Customer,16,Personal Travel,Eco,680,1,5,1,4,5,1,5,5,3,2,5,3,4,5,0,3.0,neutral or dissatisfied +67577,12879,Male,Loyal Customer,19,Business travel,Business,563,3,2,2,2,3,3,3,3,4,3,4,3,4,3,1,0.0,neutral or dissatisfied +67578,17211,Female,Loyal Customer,43,Business travel,Business,3582,1,1,1,1,4,5,5,4,4,4,4,5,4,2,0,0.0,satisfied +67579,83232,Female,Loyal Customer,28,Business travel,Business,1979,1,1,1,1,3,2,3,3,4,2,4,4,4,3,54,21.0,satisfied +67580,37204,Female,Loyal Customer,29,Personal Travel,Eco Plus,1189,3,4,3,5,1,3,3,1,4,3,4,4,4,1,0,12.0,neutral or dissatisfied +67581,84617,Male,Loyal Customer,45,Business travel,Eco,307,4,2,2,2,4,4,4,4,5,1,2,1,5,4,26,21.0,satisfied +67582,111464,Male,Loyal Customer,31,Personal Travel,Eco,836,2,3,2,2,4,2,2,4,3,1,2,2,3,4,12,16.0,neutral or dissatisfied +67583,15296,Female,Loyal Customer,30,Personal Travel,Eco Plus,500,4,4,4,3,4,4,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +67584,7320,Male,Loyal Customer,35,Personal Travel,Eco Plus,135,3,0,3,3,5,3,5,5,4,2,5,5,5,5,53,44.0,neutral or dissatisfied +67585,79765,Female,Loyal Customer,59,Business travel,Business,3444,3,3,3,3,2,5,4,4,4,4,4,5,4,5,47,42.0,satisfied +67586,50835,Male,Loyal Customer,12,Personal Travel,Eco,250,3,4,3,3,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +67587,43711,Male,Loyal Customer,65,Personal Travel,Eco,489,2,1,2,4,5,2,5,5,2,4,4,3,4,5,37,26.0,neutral or dissatisfied +67588,106084,Female,Loyal Customer,48,Business travel,Business,1663,5,5,5,5,4,4,4,2,2,2,2,5,2,4,36,33.0,satisfied +67589,49735,Male,disloyal Customer,26,Business travel,Eco,109,2,3,2,3,1,2,1,1,1,2,3,1,4,1,0,0.0,neutral or dissatisfied +67590,129060,Female,Loyal Customer,28,Personal Travel,Eco,1744,2,4,2,3,4,2,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +67591,87606,Female,Loyal Customer,35,Business travel,Business,2319,4,4,4,4,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +67592,127404,Male,disloyal Customer,45,Business travel,Eco,1009,3,3,3,2,4,3,4,4,3,2,2,3,2,4,0,0.0,neutral or dissatisfied +67593,96555,Male,Loyal Customer,22,Personal Travel,Eco Plus,302,3,4,4,5,4,4,4,4,3,4,4,3,5,4,11,6.0,neutral or dissatisfied +67594,68516,Male,Loyal Customer,43,Business travel,Business,678,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +67595,22168,Female,Loyal Customer,49,Business travel,Business,533,2,2,2,2,5,4,5,5,5,5,5,3,5,2,0,0.0,satisfied +67596,92395,Male,Loyal Customer,40,Business travel,Business,1892,4,4,4,4,4,4,4,3,3,4,5,4,5,4,182,221.0,satisfied +67597,56386,Male,Loyal Customer,53,Business travel,Business,1167,2,3,3,3,3,3,4,2,2,2,2,2,2,2,63,49.0,neutral or dissatisfied +67598,66672,Male,disloyal Customer,37,Business travel,Business,802,2,3,3,3,2,3,3,2,3,4,4,3,5,2,99,101.0,neutral or dissatisfied +67599,62193,Female,disloyal Customer,33,Business travel,Eco,2565,4,4,4,4,3,4,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +67600,108430,Male,Loyal Customer,53,Business travel,Business,1444,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +67601,14987,Male,Loyal Customer,44,Personal Travel,Eco,1025,2,5,2,4,4,2,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +67602,46344,Male,Loyal Customer,18,Business travel,Business,589,4,4,4,4,5,5,5,5,3,3,2,4,4,5,0,0.0,satisfied +67603,81701,Male,Loyal Customer,22,Personal Travel,Eco,907,4,5,4,5,3,4,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +67604,92349,Female,Loyal Customer,26,Personal Travel,Eco,2556,5,1,5,2,1,5,1,1,1,5,1,4,2,1,0,0.0,satisfied +67605,27345,Male,Loyal Customer,48,Business travel,Eco,679,5,1,4,1,5,5,5,5,3,2,3,3,2,5,22,4.0,satisfied +67606,70281,Male,Loyal Customer,39,Business travel,Eco,852,3,1,1,1,3,3,3,3,4,5,3,2,3,3,95,81.0,neutral or dissatisfied +67607,21722,Female,Loyal Customer,22,Personal Travel,Eco Plus,821,4,0,4,2,3,4,3,3,5,5,4,3,5,3,11,0.0,neutral or dissatisfied +67608,53825,Female,Loyal Customer,53,Business travel,Business,191,4,4,4,4,1,5,4,5,5,5,5,4,5,5,4,0.0,satisfied +67609,19919,Female,disloyal Customer,42,Business travel,Eco,343,3,3,4,4,2,4,2,2,5,4,5,1,4,2,7,0.0,neutral or dissatisfied +67610,52416,Female,Loyal Customer,26,Personal Travel,Eco,370,2,2,2,3,1,2,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +67611,37235,Male,disloyal Customer,40,Business travel,Business,610,2,1,1,3,4,1,4,4,4,3,4,3,4,4,1,5.0,satisfied +67612,1748,Female,Loyal Customer,19,Personal Travel,Eco,364,3,5,2,3,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +67613,89092,Male,Loyal Customer,46,Business travel,Business,1947,5,5,5,5,4,4,4,5,5,5,5,4,5,4,5,0.0,satisfied +67614,38093,Female,disloyal Customer,20,Business travel,Eco,1197,1,2,2,4,2,5,5,1,2,3,4,5,1,5,233,274.0,neutral or dissatisfied +67615,49980,Male,Loyal Customer,32,Business travel,Business,209,4,1,1,1,2,2,4,2,1,4,4,4,4,2,0,4.0,neutral or dissatisfied +67616,39759,Male,disloyal Customer,27,Business travel,Eco,521,2,3,3,3,5,3,5,5,1,2,5,2,5,5,0,0.0,neutral or dissatisfied +67617,81481,Female,disloyal Customer,24,Business travel,Business,528,4,0,4,2,4,4,4,4,1,3,2,2,4,4,0,0.0,satisfied +67618,90285,Female,Loyal Customer,51,Business travel,Business,757,2,2,2,2,4,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +67619,36735,Female,Loyal Customer,10,Business travel,Eco,1754,1,4,1,1,1,1,3,1,3,1,4,1,3,1,0,7.0,neutral or dissatisfied +67620,27273,Female,disloyal Customer,22,Business travel,Eco,650,1,5,1,3,5,1,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +67621,38717,Male,Loyal Customer,51,Business travel,Eco Plus,2342,4,1,1,1,3,4,3,3,2,4,5,1,5,3,48,39.0,satisfied +67622,63545,Male,Loyal Customer,60,Personal Travel,Eco,1009,4,2,4,3,3,4,3,3,2,4,3,1,3,3,0,0.0,satisfied +67623,112886,Male,disloyal Customer,20,Business travel,Business,1164,0,1,0,3,1,0,1,1,3,3,4,3,5,1,41,16.0,satisfied +67624,6768,Male,Loyal Customer,52,Business travel,Business,122,0,5,0,2,2,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +67625,25037,Male,Loyal Customer,44,Personal Travel,Eco,907,3,4,3,1,5,3,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +67626,62694,Female,Loyal Customer,38,Personal Travel,Business,2556,4,4,4,5,4,4,4,2,1,1,4,4,1,4,8,3.0,neutral or dissatisfied +67627,37073,Male,Loyal Customer,8,Personal Travel,Eco,1188,1,4,1,4,4,1,4,4,5,5,4,5,4,4,7,0.0,neutral or dissatisfied +67628,38585,Male,disloyal Customer,21,Business travel,Eco,1429,2,2,2,1,4,2,4,4,3,3,3,1,2,4,46,24.0,neutral or dissatisfied +67629,44694,Male,disloyal Customer,20,Business travel,Business,67,2,2,2,4,4,2,3,4,2,2,4,3,4,4,11,36.0,neutral or dissatisfied +67630,9197,Male,disloyal Customer,39,Business travel,Business,227,3,3,3,3,5,3,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +67631,63091,Female,Loyal Customer,57,Business travel,Business,862,5,5,5,5,4,4,4,4,2,5,4,4,3,4,151,142.0,satisfied +67632,70506,Female,Loyal Customer,70,Personal Travel,Eco,867,2,5,2,1,4,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +67633,112400,Male,disloyal Customer,22,Business travel,Eco,846,2,1,1,3,2,1,3,2,5,2,5,4,4,2,24,19.0,neutral or dissatisfied +67634,124220,Female,Loyal Customer,14,Personal Travel,Eco Plus,2176,3,2,4,3,3,4,5,3,4,5,3,1,3,3,0,14.0,neutral or dissatisfied +67635,27458,Female,disloyal Customer,28,Business travel,Eco,954,2,2,2,3,1,2,1,1,5,2,5,3,3,1,0,0.0,neutral or dissatisfied +67636,68706,Male,Loyal Customer,51,Personal Travel,Eco,175,1,4,1,3,4,1,4,4,5,5,5,5,5,4,5,5.0,neutral or dissatisfied +67637,63972,Female,Loyal Customer,43,Business travel,Business,3875,5,5,5,5,5,4,4,2,2,2,2,4,2,5,68,41.0,satisfied +67638,95336,Male,Loyal Customer,54,Personal Travel,Eco,239,3,4,3,4,2,3,4,2,3,4,5,3,2,2,0,0.0,neutral or dissatisfied +67639,101492,Female,Loyal Customer,43,Business travel,Eco,345,2,4,4,4,5,3,3,2,2,2,2,4,2,4,8,6.0,neutral or dissatisfied +67640,42456,Female,Loyal Customer,33,Personal Travel,Eco,926,1,4,0,2,3,0,3,3,5,5,4,4,4,3,1,5.0,neutral or dissatisfied +67641,54015,Female,disloyal Customer,22,Business travel,Eco,1091,1,1,1,4,2,1,2,2,2,5,3,3,1,2,0,0.0,neutral or dissatisfied +67642,27188,Male,Loyal Customer,41,Business travel,Eco Plus,2677,2,2,2,2,2,3,3,3,2,4,4,3,3,3,0,0.0,satisfied +67643,87603,Female,disloyal Customer,36,Business travel,Eco Plus,432,3,3,3,4,2,3,2,2,4,3,3,4,3,2,96,87.0,neutral or dissatisfied +67644,34503,Male,Loyal Customer,40,Business travel,Business,1521,3,3,3,3,4,3,3,4,4,4,4,5,4,4,3,8.0,satisfied +67645,116976,Female,disloyal Customer,22,Business travel,Eco,646,3,0,3,3,4,3,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +67646,67549,Male,Loyal Customer,7,Personal Travel,Business,1438,1,3,1,3,3,1,3,3,3,1,2,3,3,3,0,0.0,neutral or dissatisfied +67647,66076,Male,Loyal Customer,34,Personal Travel,Eco,1345,4,5,4,2,3,4,3,3,4,4,5,5,5,3,4,6.0,neutral or dissatisfied +67648,84848,Female,Loyal Customer,9,Business travel,Business,2978,3,3,3,3,3,3,3,3,5,3,4,3,4,3,0,0.0,satisfied +67649,34513,Male,Loyal Customer,46,Personal Travel,Eco,1428,3,5,3,2,2,3,4,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +67650,755,Female,Loyal Customer,50,Business travel,Business,134,4,5,4,4,3,5,5,5,5,4,4,3,5,3,0,0.0,satisfied +67651,27194,Male,Loyal Customer,55,Personal Travel,Eco Plus,2677,3,4,3,3,3,3,3,1,3,3,1,3,2,3,0,12.0,neutral or dissatisfied +67652,31180,Male,Loyal Customer,27,Business travel,Business,1620,1,4,4,4,1,1,1,1,1,2,3,2,3,1,70,72.0,neutral or dissatisfied +67653,71895,Female,Loyal Customer,29,Personal Travel,Eco,1744,3,5,3,3,4,3,3,4,5,4,5,5,5,4,1,0.0,neutral or dissatisfied +67654,39358,Male,Loyal Customer,47,Business travel,Eco,826,5,1,5,1,5,5,5,5,2,4,2,4,4,5,0,6.0,satisfied +67655,87542,Female,disloyal Customer,22,Business travel,Business,782,4,2,4,3,2,4,2,2,4,2,4,5,5,2,5,0.0,satisfied +67656,114410,Female,Loyal Customer,45,Business travel,Business,2370,1,1,1,1,3,4,4,5,5,5,5,5,5,4,13,10.0,satisfied +67657,119144,Male,Loyal Customer,32,Personal Travel,Eco,119,1,1,1,2,3,1,3,3,1,4,3,1,3,3,39,36.0,neutral or dissatisfied +67658,43575,Female,disloyal Customer,10,Business travel,Eco,1499,3,3,3,4,1,3,1,1,1,2,3,3,3,1,0,4.0,neutral or dissatisfied +67659,25436,Female,Loyal Customer,50,Business travel,Business,2717,1,1,1,1,1,3,1,2,2,2,2,3,2,5,23,13.0,satisfied +67660,117276,Male,Loyal Customer,57,Business travel,Business,304,0,0,0,3,5,4,4,3,3,3,3,4,3,5,13,13.0,satisfied +67661,27901,Female,Loyal Customer,56,Personal Travel,Eco,2350,3,1,3,2,3,4,4,1,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +67662,56943,Male,Loyal Customer,49,Business travel,Eco,2434,3,5,5,5,3,3,3,1,3,3,4,3,4,3,24,12.0,neutral or dissatisfied +67663,56622,Male,Loyal Customer,42,Business travel,Business,1065,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +67664,90543,Female,Loyal Customer,32,Business travel,Business,366,1,1,1,1,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +67665,79117,Male,Loyal Customer,47,Personal Travel,Eco,356,2,1,2,4,2,2,2,2,4,4,3,3,3,2,0,0.0,neutral or dissatisfied +67666,3595,Male,Loyal Customer,26,Business travel,Eco,999,0,2,3,2,0,1,3,0,4,4,4,2,3,0,0,0.0,neutral or dissatisfied +67667,111182,Female,Loyal Customer,60,Business travel,Business,1506,4,4,4,4,4,5,4,5,5,5,5,3,5,3,8,0.0,satisfied +67668,16959,Male,Loyal Customer,22,Business travel,Business,1131,4,4,4,4,5,5,5,5,1,3,3,3,4,5,0,0.0,satisfied +67669,10781,Female,disloyal Customer,34,Business travel,Business,482,3,3,3,1,3,3,3,3,4,3,4,4,5,3,0,4.0,neutral or dissatisfied +67670,60332,Male,Loyal Customer,47,Business travel,Business,1024,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +67671,32826,Male,Loyal Customer,63,Business travel,Business,102,1,1,1,1,2,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +67672,89746,Male,Loyal Customer,58,Personal Travel,Eco,1010,3,1,3,2,5,3,3,5,4,4,2,3,2,5,11,0.0,neutral or dissatisfied +67673,19640,Male,Loyal Customer,20,Personal Travel,Eco,717,1,3,1,2,3,1,3,3,4,5,3,4,1,3,42,33.0,neutral or dissatisfied +67674,15365,Male,Loyal Customer,38,Business travel,Business,399,4,4,4,4,3,5,5,4,4,4,4,4,4,2,0,1.0,satisfied +67675,31626,Female,Loyal Customer,25,Business travel,Eco,967,0,5,0,3,2,0,5,2,5,2,2,3,3,2,79,96.0,satisfied +67676,116963,Female,Loyal Customer,60,Business travel,Business,2639,1,1,1,1,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +67677,7858,Female,Loyal Customer,59,Business travel,Business,3559,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +67678,96533,Male,Loyal Customer,36,Personal Travel,Eco,444,2,4,2,3,4,2,4,4,4,2,5,4,4,4,12,7.0,neutral or dissatisfied +67679,125048,Female,Loyal Customer,59,Personal Travel,Eco,2300,5,5,5,5,5,3,3,5,5,3,5,3,5,3,11,3.0,satisfied +67680,110265,Male,Loyal Customer,35,Business travel,Business,787,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +67681,125387,Male,Loyal Customer,49,Business travel,Eco,1440,2,4,3,3,2,2,2,2,2,4,3,3,2,2,0,0.0,neutral or dissatisfied +67682,70551,Female,Loyal Customer,40,Business travel,Business,2753,4,4,4,4,2,3,4,4,4,3,4,3,4,3,0,11.0,neutral or dissatisfied +67683,40420,Male,Loyal Customer,41,Business travel,Business,2214,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +67684,52738,Female,Loyal Customer,61,Business travel,Business,2306,2,1,1,1,1,3,4,2,2,2,2,3,2,2,28,1.0,neutral or dissatisfied +67685,118243,Male,Loyal Customer,33,Business travel,Business,1849,3,4,4,4,3,3,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +67686,110683,Male,Loyal Customer,19,Personal Travel,Eco,945,4,2,4,4,4,4,2,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +67687,11017,Male,Loyal Customer,55,Business travel,Business,247,3,2,2,2,5,3,3,3,3,3,3,3,3,1,0,9.0,neutral or dissatisfied +67688,93776,Male,disloyal Customer,23,Business travel,Eco,1166,4,4,4,3,2,4,2,2,4,2,3,5,4,2,10,2.0,neutral or dissatisfied +67689,95115,Female,Loyal Customer,48,Personal Travel,Eco,677,2,5,2,3,3,4,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +67690,41240,Female,Loyal Customer,59,Personal Travel,Eco,781,2,4,2,3,3,5,4,4,4,2,1,5,4,3,0,8.0,neutral or dissatisfied +67691,86598,Male,Loyal Customer,58,Business travel,Business,1925,2,1,1,1,5,3,3,2,2,2,2,2,2,1,34,26.0,neutral or dissatisfied +67692,66137,Male,Loyal Customer,26,Personal Travel,Eco,583,3,5,3,5,2,3,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +67693,120295,Male,Loyal Customer,49,Business travel,Business,268,1,5,5,5,4,2,2,1,1,1,1,3,1,4,0,8.0,neutral or dissatisfied +67694,84647,Male,Loyal Customer,14,Personal Travel,Business,363,2,4,2,2,4,2,4,4,4,4,4,3,4,4,1,8.0,neutral or dissatisfied +67695,52304,Male,Loyal Customer,41,Business travel,Eco,751,1,2,2,2,1,1,1,1,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +67696,42935,Male,Loyal Customer,33,Business travel,Business,1997,5,5,5,5,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +67697,106473,Female,Loyal Customer,29,Personal Travel,Eco,1300,3,4,3,3,5,3,1,5,5,5,4,4,5,5,14,4.0,neutral or dissatisfied +67698,91785,Female,Loyal Customer,21,Personal Travel,Eco,626,5,2,5,4,5,5,5,5,3,4,3,4,4,5,0,0.0,satisfied +67699,27270,Male,Loyal Customer,41,Business travel,Business,679,4,4,4,4,2,4,5,4,4,4,4,5,4,5,1,0.0,satisfied +67700,106756,Male,Loyal Customer,27,Business travel,Business,1005,4,1,1,1,4,4,4,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +67701,49718,Female,Loyal Customer,51,Business travel,Eco,326,5,2,2,2,4,2,2,5,5,5,5,4,5,5,0,0.0,satisfied +67702,13579,Female,Loyal Customer,36,Personal Travel,Eco,227,1,5,1,1,1,1,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +67703,129432,Male,Loyal Customer,48,Business travel,Business,236,5,5,4,5,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +67704,43564,Female,Loyal Customer,54,Personal Travel,Eco,770,2,5,2,2,2,4,4,4,4,2,1,4,4,3,5,2.0,neutral or dissatisfied +67705,20601,Male,Loyal Customer,65,Personal Travel,Eco Plus,606,3,5,3,3,4,3,3,4,4,3,5,5,5,4,2,0.0,neutral or dissatisfied +67706,124396,Male,Loyal Customer,15,Business travel,Eco Plus,808,1,5,5,5,1,1,2,1,1,1,3,1,4,1,0,8.0,neutral or dissatisfied +67707,57715,Male,disloyal Customer,47,Business travel,Eco Plus,867,3,3,3,3,1,3,1,1,2,3,3,1,3,1,0,8.0,neutral or dissatisfied +67708,80690,Female,disloyal Customer,26,Business travel,Business,874,2,2,2,3,4,2,4,4,4,2,4,4,5,4,21,40.0,neutral or dissatisfied +67709,106166,Female,Loyal Customer,7,Personal Travel,Eco,436,2,4,2,4,2,2,2,2,5,2,5,4,5,2,0,2.0,neutral or dissatisfied +67710,1465,Male,Loyal Customer,40,Personal Travel,Eco,772,2,3,2,3,2,2,2,2,3,1,2,5,5,2,68,67.0,neutral or dissatisfied +67711,7540,Female,Loyal Customer,17,Personal Travel,Eco,762,1,5,1,4,3,1,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +67712,99278,Male,Loyal Customer,35,Business travel,Business,833,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +67713,12073,Male,Loyal Customer,65,Personal Travel,Eco,376,1,5,1,1,5,1,5,5,4,4,5,3,4,5,0,,neutral or dissatisfied +67714,67267,Male,Loyal Customer,43,Personal Travel,Eco,1119,4,4,3,4,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +67715,109284,Female,Loyal Customer,23,Personal Travel,Business,1188,2,5,2,2,5,2,5,5,1,3,4,4,1,5,0,0.0,neutral or dissatisfied +67716,112439,Female,Loyal Customer,55,Business travel,Business,819,4,5,5,5,2,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +67717,76774,Male,disloyal Customer,37,Business travel,Business,689,5,5,5,5,4,5,4,4,5,5,4,4,4,4,0,1.0,satisfied +67718,46339,Female,Loyal Customer,38,Business travel,Business,1710,3,3,3,3,4,3,3,4,4,4,4,2,4,4,16,19.0,satisfied +67719,68639,Male,Loyal Customer,25,Business travel,Business,237,5,5,5,5,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +67720,57992,Female,Loyal Customer,19,Personal Travel,Eco Plus,844,3,5,3,2,1,3,1,1,4,5,5,5,4,1,8,0.0,neutral or dissatisfied +67721,15655,Female,Loyal Customer,58,Personal Travel,Eco,258,2,5,2,2,1,1,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +67722,124989,Female,disloyal Customer,27,Business travel,Eco,184,3,1,3,3,5,3,1,5,3,1,4,4,4,5,0,0.0,neutral or dissatisfied +67723,84025,Female,Loyal Customer,55,Business travel,Business,2007,5,5,5,5,2,4,5,4,4,4,4,5,4,3,19,3.0,satisfied +67724,110116,Male,Loyal Customer,43,Business travel,Business,1056,1,1,1,1,5,5,5,4,4,4,4,5,4,3,47,51.0,satisfied +67725,98200,Male,Loyal Customer,64,Personal Travel,Eco,327,5,0,3,3,5,3,4,5,5,4,5,4,4,5,0,0.0,satisfied +67726,110388,Male,disloyal Customer,25,Business travel,Eco,883,4,4,4,3,2,4,2,2,1,2,3,1,4,2,0,9.0,neutral or dissatisfied +67727,64394,Female,Loyal Customer,67,Personal Travel,Eco,1158,1,5,2,4,2,5,5,1,1,2,1,4,1,3,12,5.0,neutral or dissatisfied +67728,124135,Male,Loyal Customer,46,Personal Travel,Eco,529,2,5,2,4,2,2,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +67729,76292,Male,Loyal Customer,70,Personal Travel,Eco,2677,4,4,4,5,4,5,5,3,4,4,4,5,3,5,0,0.0,neutral or dissatisfied +67730,29388,Male,Loyal Customer,38,Business travel,Eco,2614,5,3,3,3,5,5,5,1,4,5,1,5,3,5,0,0.0,satisfied +67731,86006,Male,Loyal Customer,37,Business travel,Business,1800,5,5,2,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +67732,76746,Female,Loyal Customer,53,Business travel,Eco,205,4,5,5,5,1,3,4,4,4,4,4,3,4,3,0,5.0,neutral or dissatisfied +67733,44376,Female,Loyal Customer,42,Business travel,Business,2759,0,0,0,3,3,4,4,4,4,1,1,5,4,3,0,0.0,satisfied +67734,82685,Female,Loyal Customer,45,Business travel,Business,632,1,1,1,1,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +67735,57537,Female,Loyal Customer,39,Business travel,Business,2205,3,4,4,4,5,4,4,3,3,3,3,3,3,1,33,28.0,neutral or dissatisfied +67736,28571,Male,Loyal Customer,43,Business travel,Business,2562,4,4,4,4,3,4,5,5,5,5,5,2,5,2,0,0.0,satisfied +67737,11014,Female,disloyal Customer,17,Business travel,Eco,163,3,4,3,4,2,3,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +67738,43168,Male,Loyal Customer,58,Personal Travel,Eco,840,1,4,1,3,2,1,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +67739,36117,Female,Loyal Customer,32,Business travel,Eco,1562,5,5,5,5,5,5,5,5,4,2,1,1,3,5,24,15.0,satisfied +67740,72741,Male,Loyal Customer,12,Personal Travel,Eco Plus,1017,3,5,3,3,4,3,3,4,4,1,3,3,5,4,11,0.0,neutral or dissatisfied +67741,24897,Male,Loyal Customer,55,Business travel,Eco Plus,397,5,5,3,5,5,5,5,5,3,5,2,2,1,5,0,0.0,satisfied +67742,53944,Male,Loyal Customer,31,Business travel,Business,1117,5,1,5,5,5,5,5,5,5,3,4,5,4,5,1,0.0,satisfied +67743,37129,Female,disloyal Customer,17,Business travel,Eco,1189,2,2,2,4,4,2,4,4,1,3,4,3,3,4,1,0.0,neutral or dissatisfied +67744,36299,Female,Loyal Customer,33,Business travel,Eco,187,4,2,5,2,5,5,5,5,3,2,1,3,4,5,4,0.0,satisfied +67745,74123,Male,Loyal Customer,55,Business travel,Business,3713,5,5,5,5,3,4,4,3,3,3,3,5,3,5,71,116.0,satisfied +67746,111189,Male,disloyal Customer,22,Business travel,Eco,1142,2,2,2,3,4,2,4,4,3,5,5,3,4,4,6,0.0,neutral or dissatisfied +67747,70034,Male,Loyal Customer,46,Business travel,Eco,583,2,4,1,1,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +67748,9768,Female,disloyal Customer,36,Business travel,Eco,529,1,3,1,3,1,1,1,1,4,1,3,1,4,1,0,0.0,neutral or dissatisfied +67749,98103,Male,Loyal Customer,63,Business travel,Business,1723,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,2.0,satisfied +67750,67658,Male,Loyal Customer,56,Business travel,Business,2406,3,3,3,3,2,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +67751,10904,Male,Loyal Customer,53,Business travel,Business,3264,0,0,0,3,3,4,4,4,4,4,1,5,4,4,7,0.0,satisfied +67752,106175,Female,Loyal Customer,12,Personal Travel,Eco,436,4,5,4,1,4,4,4,4,4,4,5,5,4,4,15,15.0,neutral or dissatisfied +67753,35687,Male,disloyal Customer,39,Business travel,Eco,982,2,2,2,4,2,2,3,2,1,1,2,4,3,2,0,0.0,neutral or dissatisfied +67754,64195,Female,Loyal Customer,45,Business travel,Business,1827,4,4,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +67755,5826,Female,Loyal Customer,20,Personal Travel,Eco,273,1,0,1,1,5,1,5,5,4,4,1,3,4,5,0,0.0,neutral or dissatisfied +67756,1219,Male,Loyal Customer,20,Personal Travel,Eco,134,1,0,1,2,1,5,5,5,2,5,5,5,3,5,244,236.0,neutral or dissatisfied +67757,74412,Female,Loyal Customer,57,Business travel,Business,1431,1,1,1,1,2,5,4,4,4,4,4,4,4,4,6,0.0,satisfied +67758,4168,Male,Loyal Customer,19,Personal Travel,Eco,427,2,4,2,4,3,2,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +67759,83389,Male,Loyal Customer,56,Business travel,Business,3466,2,2,2,2,5,4,4,4,4,4,4,5,4,5,4,13.0,satisfied +67760,38617,Male,Loyal Customer,24,Personal Travel,Eco,231,4,4,0,5,4,0,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +67761,71086,Male,Loyal Customer,47,Personal Travel,Eco,802,1,5,1,3,5,1,5,5,3,1,1,2,4,5,22,42.0,neutral or dissatisfied +67762,116464,Female,Loyal Customer,21,Personal Travel,Eco,390,1,5,1,2,5,1,5,5,3,1,2,3,1,5,0,0.0,neutral or dissatisfied +67763,45249,Male,disloyal Customer,49,Business travel,Eco Plus,911,4,4,4,4,1,4,1,1,1,5,4,1,4,1,0,0.0,neutral or dissatisfied +67764,6436,Female,Loyal Customer,60,Personal Travel,Eco,296,1,4,1,5,4,5,4,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +67765,24995,Male,Loyal Customer,33,Business travel,Eco,692,2,5,5,5,2,2,2,2,4,4,4,1,3,2,20,52.0,neutral or dissatisfied +67766,28363,Male,Loyal Customer,16,Personal Travel,Eco Plus,954,1,5,1,2,3,1,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +67767,31880,Male,Loyal Customer,67,Personal Travel,Eco Plus,4983,5,5,5,4,5,1,1,1,3,5,5,1,3,1,0,0.0,satisfied +67768,66272,Female,Loyal Customer,24,Business travel,Business,460,4,4,4,4,4,4,4,4,3,5,4,5,5,4,0,1.0,satisfied +67769,17032,Male,Loyal Customer,42,Business travel,Eco Plus,781,5,3,3,3,5,5,5,5,5,1,2,1,5,5,30,14.0,satisfied +67770,76633,Female,Loyal Customer,36,Business travel,Eco,134,1,2,2,2,1,2,1,1,3,5,4,2,3,1,0,0.0,neutral or dissatisfied +67771,122895,Female,Loyal Customer,31,Personal Travel,Eco Plus,226,1,4,1,4,3,1,4,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +67772,88984,Male,Loyal Customer,35,Personal Travel,Eco,1199,4,4,4,2,5,4,5,5,2,3,1,2,4,5,0,0.0,neutral or dissatisfied +67773,26039,Female,disloyal Customer,28,Business travel,Eco,432,3,5,3,3,2,3,2,2,5,5,4,1,1,2,0,0.0,neutral or dissatisfied +67774,123183,Female,Loyal Customer,15,Personal Travel,Eco,631,5,3,5,5,3,5,3,3,5,3,2,3,3,3,52,64.0,satisfied +67775,78962,Female,Loyal Customer,39,Business travel,Business,356,1,1,1,1,4,4,4,4,3,4,5,4,5,4,180,185.0,satisfied +67776,58734,Male,Loyal Customer,57,Business travel,Business,1957,2,2,2,2,3,5,5,5,5,5,5,3,5,5,11,34.0,satisfied +67777,101071,Male,Loyal Customer,39,Business travel,Business,368,1,1,1,1,2,5,5,5,5,5,5,3,5,5,6,4.0,satisfied +67778,118076,Male,Loyal Customer,31,Business travel,Business,2480,5,5,5,5,4,4,4,4,3,5,5,3,5,4,80,72.0,satisfied +67779,19406,Female,Loyal Customer,17,Personal Travel,Eco,660,1,4,1,4,4,1,5,4,3,4,4,3,3,4,84,110.0,neutral or dissatisfied +67780,111169,Male,Loyal Customer,52,Business travel,Business,1447,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +67781,4911,Female,Loyal Customer,36,Business travel,Eco,1020,4,5,5,5,4,4,4,4,2,3,4,2,4,4,7,0.0,neutral or dissatisfied +67782,110247,Female,Loyal Customer,19,Personal Travel,Eco,1138,3,5,3,2,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +67783,95205,Male,Loyal Customer,13,Personal Travel,Eco,189,4,5,4,3,4,4,4,4,2,2,2,2,1,4,0,0.0,neutral or dissatisfied +67784,2015,Female,Loyal Customer,47,Business travel,Business,2603,1,1,1,1,2,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +67785,77208,Female,Loyal Customer,54,Personal Travel,Eco,2994,3,4,3,3,3,3,3,1,3,4,3,3,4,3,0,4.0,neutral or dissatisfied +67786,70044,Female,Loyal Customer,41,Personal Travel,Eco,583,1,5,1,4,5,1,5,5,5,2,4,4,5,5,0,10.0,neutral or dissatisfied +67787,4407,Male,Loyal Customer,56,Business travel,Business,1923,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,3.0,satisfied +67788,72238,Male,Loyal Customer,39,Business travel,Business,919,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +67789,24289,Male,Loyal Customer,37,Personal Travel,Eco,134,3,0,3,4,5,3,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +67790,22312,Male,disloyal Customer,44,Business travel,Eco,143,1,0,0,2,3,0,3,3,4,1,3,4,5,3,0,0.0,neutral or dissatisfied +67791,129099,Male,Loyal Customer,66,Personal Travel,Eco,2583,3,5,3,5,3,1,1,5,1,4,3,1,5,1,0,0.0,neutral or dissatisfied +67792,76247,Male,Loyal Customer,34,Personal Travel,Eco,1399,2,4,2,4,3,2,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +67793,85292,Male,Loyal Customer,29,Personal Travel,Eco,813,1,0,1,2,4,1,4,4,2,2,3,3,5,4,0,0.0,neutral or dissatisfied +67794,89984,Male,disloyal Customer,22,Business travel,Eco,1310,2,2,2,3,5,2,4,5,3,1,3,3,3,5,2,13.0,neutral or dissatisfied +67795,124412,Female,Loyal Customer,58,Business travel,Business,1044,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +67796,119868,Male,Loyal Customer,31,Personal Travel,Eco,936,1,5,2,3,1,2,1,1,5,1,2,2,2,1,13,20.0,neutral or dissatisfied +67797,96350,Male,Loyal Customer,70,Personal Travel,Eco,1609,1,4,0,1,5,0,5,5,3,4,3,3,5,5,0,0.0,neutral or dissatisfied +67798,52904,Male,Loyal Customer,24,Business travel,Business,679,5,5,5,5,5,5,5,5,3,1,4,3,5,5,0,24.0,satisfied +67799,116605,Male,Loyal Customer,60,Business travel,Business,3753,3,3,3,3,5,5,5,4,4,4,4,4,4,5,5,2.0,satisfied +67800,101838,Female,Loyal Customer,16,Personal Travel,Eco,1521,3,5,3,4,2,3,2,2,1,1,5,4,5,2,0,0.0,neutral or dissatisfied +67801,89611,Female,Loyal Customer,33,Business travel,Business,2120,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +67802,72387,Female,disloyal Customer,26,Business travel,Business,1121,4,4,4,1,2,4,4,2,4,2,4,3,5,2,21,13.0,satisfied +67803,99072,Female,Loyal Customer,49,Business travel,Business,2198,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +67804,37549,Male,Loyal Customer,56,Business travel,Business,1076,3,1,1,1,5,4,3,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +67805,36967,Female,disloyal Customer,35,Business travel,Eco,759,2,2,2,3,5,2,3,5,5,4,1,4,4,5,0,0.0,neutral or dissatisfied +67806,121798,Female,Loyal Customer,41,Business travel,Business,337,4,4,4,4,5,4,4,4,4,4,4,4,4,4,71,43.0,satisfied +67807,88608,Male,Loyal Customer,53,Personal Travel,Eco,444,2,5,3,3,4,3,4,4,3,2,4,4,4,4,68,104.0,neutral or dissatisfied +67808,121973,Female,Loyal Customer,31,Business travel,Business,130,4,4,4,4,5,5,5,5,4,2,5,5,4,5,12,13.0,satisfied +67809,59454,Female,Loyal Customer,50,Business travel,Business,1622,4,4,4,4,3,4,5,5,5,5,5,3,5,5,6,13.0,satisfied +67810,115362,Female,Loyal Customer,47,Business travel,Business,1768,3,3,3,3,5,4,5,5,5,5,5,3,5,3,8,0.0,satisfied +67811,55242,Female,Loyal Customer,62,Business travel,Eco,609,4,5,2,2,1,4,4,4,4,4,4,2,4,4,0,0.0,satisfied +67812,44668,Female,Loyal Customer,47,Business travel,Business,3200,1,1,1,1,4,3,2,4,4,4,4,3,4,2,0,0.0,satisfied +67813,93910,Female,Loyal Customer,34,Personal Travel,Business,507,0,4,0,3,4,4,5,2,2,0,2,5,2,4,89,76.0,satisfied +67814,40235,Male,Loyal Customer,48,Business travel,Eco,347,4,3,3,3,4,4,4,4,2,3,3,4,1,4,0,0.0,satisfied +67815,31335,Female,Loyal Customer,33,Business travel,Business,1062,1,1,1,1,4,2,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +67816,127754,Female,Loyal Customer,49,Personal Travel,Eco,601,3,4,3,2,2,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +67817,125063,Female,Loyal Customer,41,Personal Travel,Eco,90,2,2,2,3,2,2,2,2,2,3,3,3,3,2,0,0.0,neutral or dissatisfied +67818,27817,Female,Loyal Customer,25,Business travel,Business,280,2,2,3,2,3,4,3,3,4,2,2,2,4,3,0,0.0,satisfied +67819,10667,Female,Loyal Customer,34,Business travel,Business,316,3,4,3,4,4,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +67820,7211,Female,disloyal Customer,27,Business travel,Eco,130,4,2,4,3,3,4,4,3,3,4,2,1,2,3,32,41.0,neutral or dissatisfied +67821,56372,Male,Loyal Customer,69,Personal Travel,Eco,200,3,4,3,3,4,3,3,4,1,1,4,4,4,4,0,0.0,neutral or dissatisfied +67822,99322,Female,Loyal Customer,68,Personal Travel,Eco,448,3,4,2,2,5,4,4,4,4,2,5,3,4,4,43,40.0,neutral or dissatisfied +67823,68526,Male,disloyal Customer,28,Business travel,Business,1013,2,1,1,3,3,1,5,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +67824,65608,Male,disloyal Customer,41,Business travel,Eco,175,4,0,4,2,5,4,5,5,5,1,1,5,2,5,0,0.0,satisfied +67825,23602,Female,Loyal Customer,31,Business travel,Business,692,1,1,2,2,1,1,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +67826,52782,Male,Loyal Customer,26,Business travel,Business,1874,3,3,3,3,4,4,4,4,4,3,4,5,2,4,0,0.0,satisfied +67827,108604,Male,Loyal Customer,26,Business travel,Eco,696,2,1,1,1,2,2,1,2,3,3,2,3,2,2,9,0.0,neutral or dissatisfied +67828,67531,Female,Loyal Customer,24,Business travel,Business,1235,4,4,5,4,5,5,5,5,5,2,5,5,4,5,0,0.0,satisfied +67829,71463,Male,Loyal Customer,62,Personal Travel,Eco,867,3,1,3,4,3,3,4,3,4,5,4,3,4,3,73,96.0,neutral or dissatisfied +67830,65757,Female,Loyal Customer,11,Personal Travel,Eco,936,2,3,2,4,1,2,1,1,3,3,4,4,4,1,8,0.0,neutral or dissatisfied +67831,48785,Male,Loyal Customer,47,Business travel,Business,2400,1,2,1,1,5,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +67832,113066,Female,Loyal Customer,35,Business travel,Business,2521,1,4,4,4,5,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +67833,96732,Female,Loyal Customer,44,Personal Travel,Eco,696,4,3,4,3,5,4,3,2,2,4,2,2,2,1,0,0.0,neutral or dissatisfied +67834,76110,Female,Loyal Customer,59,Business travel,Business,2142,4,4,2,4,5,5,5,4,4,4,4,3,4,3,0,2.0,satisfied +67835,39471,Male,Loyal Customer,55,Business travel,Eco,867,4,4,5,5,4,4,4,4,2,1,5,4,4,4,19,0.0,satisfied +67836,73290,Male,Loyal Customer,43,Business travel,Business,1197,3,3,3,3,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +67837,87942,Female,Loyal Customer,15,Personal Travel,Business,515,2,4,2,4,5,2,5,5,3,5,4,5,5,5,0,7.0,neutral or dissatisfied +67838,5174,Female,Loyal Customer,43,Personal Travel,Business,190,4,4,4,1,1,2,2,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +67839,125794,Male,Loyal Customer,50,Business travel,Business,951,2,4,4,4,3,3,3,2,2,2,2,3,2,4,65,54.0,neutral or dissatisfied +67840,86638,Female,disloyal Customer,38,Business travel,Business,746,1,1,1,5,5,1,5,5,4,2,4,4,4,5,9,5.0,neutral or dissatisfied +67841,73938,Male,Loyal Customer,11,Business travel,Business,2585,3,2,2,2,3,3,3,2,5,2,3,3,3,3,29,24.0,neutral or dissatisfied +67842,114743,Male,disloyal Customer,23,Business travel,Business,480,4,3,5,3,1,5,1,1,4,2,4,5,5,1,0,6.0,satisfied +67843,37732,Female,Loyal Customer,49,Personal Travel,Eco,1074,1,5,1,4,2,4,5,1,1,1,1,3,1,3,29,,neutral or dissatisfied +67844,120421,Female,disloyal Customer,21,Business travel,Business,449,4,2,4,2,2,4,2,2,1,3,3,1,2,2,0,0.0,neutral or dissatisfied +67845,4763,Male,Loyal Customer,54,Business travel,Business,2351,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,8.0,satisfied +67846,35261,Male,disloyal Customer,22,Business travel,Business,1076,0,0,0,3,5,0,5,5,2,4,2,2,3,5,16,14.0,satisfied +67847,50223,Female,Loyal Customer,43,Business travel,Business,421,4,2,3,2,5,4,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +67848,18166,Female,Loyal Customer,8,Personal Travel,Eco,430,3,4,3,5,3,3,1,3,3,3,5,3,4,3,20,17.0,neutral or dissatisfied +67849,113614,Female,Loyal Customer,36,Personal Travel,Eco,407,2,5,3,3,3,3,3,3,2,2,5,2,3,3,0,0.0,neutral or dissatisfied +67850,71893,Male,Loyal Customer,44,Personal Travel,Eco,1846,2,2,2,4,2,2,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +67851,21135,Male,Loyal Customer,46,Personal Travel,Eco,106,2,4,2,3,2,2,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +67852,96773,Male,Loyal Customer,43,Business travel,Business,1627,3,3,3,3,3,4,4,4,4,5,4,3,4,5,80,70.0,satisfied +67853,127504,Male,Loyal Customer,40,Personal Travel,Eco,1814,4,3,4,1,5,4,5,5,1,4,3,4,3,5,0,0.0,satisfied +67854,41278,Female,Loyal Customer,41,Business travel,Eco,812,4,4,4,4,4,4,4,4,5,1,4,4,2,4,0,0.0,satisfied +67855,129116,Female,Loyal Customer,36,Personal Travel,Eco Plus,2583,4,3,4,3,4,3,3,3,5,5,3,3,1,3,0,5.0,satisfied +67856,87134,Female,Loyal Customer,68,Personal Travel,Eco,645,3,5,3,2,2,1,3,4,4,3,4,4,4,2,42,17.0,neutral or dissatisfied +67857,79960,Female,disloyal Customer,37,Business travel,Eco,544,2,4,2,4,1,2,1,1,1,5,4,1,3,1,15,20.0,neutral or dissatisfied +67858,99137,Male,Loyal Customer,14,Personal Travel,Eco,181,1,5,0,2,2,0,3,2,5,2,5,4,4,2,14,12.0,neutral or dissatisfied +67859,103386,Male,Loyal Customer,54,Business travel,Business,237,4,4,4,4,5,5,4,4,4,4,4,4,4,3,65,60.0,satisfied +67860,11961,Female,Loyal Customer,60,Business travel,Business,643,2,2,2,2,2,5,5,4,4,4,4,5,4,3,9,1.0,satisfied +67861,34156,Female,Loyal Customer,40,Business travel,Eco,1046,3,1,1,1,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +67862,108,Male,Loyal Customer,43,Business travel,Business,562,4,3,3,3,1,4,3,4,4,4,4,2,4,1,45,51.0,neutral or dissatisfied +67863,20489,Male,disloyal Customer,21,Business travel,Eco,139,3,1,3,2,4,3,4,4,1,4,3,3,2,4,23,19.0,neutral or dissatisfied +67864,46723,Female,Loyal Customer,65,Personal Travel,Eco,141,3,2,3,4,5,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +67865,30905,Female,Loyal Customer,42,Business travel,Business,2331,2,2,2,2,4,4,2,4,4,4,4,3,4,3,0,0.0,satisfied +67866,27628,Female,disloyal Customer,31,Business travel,Eco Plus,956,3,3,3,3,3,3,3,3,5,5,2,3,5,3,0,0.0,neutral or dissatisfied +67867,10709,Female,Loyal Customer,79,Business travel,Business,1713,4,1,1,1,2,4,3,4,4,4,4,3,4,1,47,65.0,neutral or dissatisfied +67868,20330,Male,Loyal Customer,40,Business travel,Business,265,0,0,0,4,5,3,3,5,5,5,5,1,5,1,0,0.0,satisfied +67869,57153,Male,Loyal Customer,44,Business travel,Business,1824,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +67870,28479,Female,disloyal Customer,11,Business travel,Eco Plus,1721,3,4,4,4,1,4,1,1,3,5,2,3,3,1,62,96.0,neutral or dissatisfied +67871,116370,Male,Loyal Customer,37,Personal Travel,Eco,404,1,4,1,3,1,1,3,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +67872,77055,Male,Loyal Customer,51,Business travel,Business,991,1,1,1,1,2,5,4,4,4,4,4,3,4,4,4,0.0,satisfied +67873,25680,Male,Loyal Customer,58,Business travel,Eco Plus,761,3,4,4,4,3,3,3,3,4,1,3,3,4,3,0,19.0,satisfied +67874,8532,Female,Loyal Customer,48,Personal Travel,Eco Plus,862,2,4,1,4,3,4,4,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +67875,75815,Male,Loyal Customer,28,Personal Travel,Eco Plus,868,3,2,2,4,4,2,4,4,2,2,3,3,4,4,14,10.0,neutral or dissatisfied +67876,106830,Female,Loyal Customer,42,Personal Travel,Eco Plus,1488,1,3,1,3,3,4,1,5,5,1,5,2,5,4,10,10.0,neutral or dissatisfied +67877,58058,Female,Loyal Customer,17,Business travel,Business,612,3,3,2,3,4,4,4,4,3,4,4,3,5,4,5,8.0,satisfied +67878,74810,Female,Loyal Customer,61,Business travel,Eco Plus,771,2,2,5,2,2,3,3,2,2,2,2,2,2,1,0,4.0,neutral or dissatisfied +67879,97129,Female,Loyal Customer,10,Business travel,Business,3963,1,1,1,1,1,1,1,1,4,1,2,4,2,1,5,0.0,neutral or dissatisfied +67880,79497,Female,Loyal Customer,50,Business travel,Business,760,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,2.0,satisfied +67881,96567,Male,Loyal Customer,46,Business travel,Business,333,4,4,4,4,2,4,5,5,5,5,5,3,5,5,8,0.0,satisfied +67882,28791,Female,Loyal Customer,54,Personal Travel,Business,605,3,4,3,2,3,5,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +67883,68843,Female,Loyal Customer,52,Business travel,Business,3766,4,4,5,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +67884,94883,Male,disloyal Customer,26,Business travel,Eco,528,4,4,4,3,1,4,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +67885,59701,Male,Loyal Customer,10,Personal Travel,Eco,965,5,2,5,4,5,5,5,5,4,3,3,1,3,5,0,5.0,satisfied +67886,79060,Male,disloyal Customer,36,Business travel,Business,356,2,2,2,3,3,2,4,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +67887,10118,Female,Loyal Customer,57,Personal Travel,Eco,984,5,5,5,3,5,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +67888,97202,Male,Loyal Customer,66,Personal Travel,Eco,1390,4,4,4,3,4,4,1,4,3,5,4,5,4,4,66,51.0,neutral or dissatisfied +67889,78525,Male,Loyal Customer,18,Personal Travel,Eco,526,4,4,5,4,2,5,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +67890,105230,Female,Loyal Customer,66,Business travel,Business,377,3,4,4,4,5,2,3,3,3,3,3,2,3,3,65,57.0,neutral or dissatisfied +67891,81065,Female,Loyal Customer,54,Business travel,Business,2712,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +67892,30496,Male,Loyal Customer,11,Personal Travel,Eco,516,2,5,2,4,3,2,3,3,2,4,3,4,5,3,15,49.0,neutral or dissatisfied +67893,8337,Male,Loyal Customer,39,Business travel,Business,3653,2,2,2,2,5,4,4,4,4,4,4,4,4,4,25,23.0,satisfied +67894,14326,Male,Loyal Customer,30,Personal Travel,Eco,429,1,4,2,4,3,2,3,3,3,5,2,3,1,3,5,0.0,neutral or dissatisfied +67895,53908,Male,Loyal Customer,40,Personal Travel,Eco,140,3,4,3,3,4,3,4,4,1,1,3,2,4,4,4,0.0,neutral or dissatisfied +67896,42482,Male,Loyal Customer,26,Business travel,Eco,693,5,2,2,2,5,5,4,5,4,3,4,4,1,5,12,3.0,satisfied +67897,31330,Male,Loyal Customer,26,Business travel,Business,1699,3,3,1,3,3,3,3,3,1,3,4,3,4,3,4,0.0,satisfied +67898,180,Male,Loyal Customer,56,Business travel,Business,2975,0,5,0,2,5,5,5,5,5,5,5,3,5,5,0,13.0,satisfied +67899,8258,Female,Loyal Customer,34,Personal Travel,Eco,294,3,4,3,3,4,3,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +67900,23882,Female,Loyal Customer,25,Business travel,Eco,579,1,2,2,2,1,1,1,1,3,4,4,1,3,1,51,77.0,neutral or dissatisfied +67901,76766,Female,disloyal Customer,42,Business travel,Business,689,2,2,2,3,5,2,5,5,5,3,5,3,5,5,3,0.0,neutral or dissatisfied +67902,26672,Male,Loyal Customer,56,Personal Travel,Eco,270,2,0,2,4,2,2,3,2,3,5,5,4,4,2,17,16.0,neutral or dissatisfied +67903,50064,Male,Loyal Customer,25,Business travel,Business,337,2,2,2,2,2,2,2,2,3,2,4,4,3,2,28,19.0,neutral or dissatisfied +67904,109394,Male,Loyal Customer,59,Personal Travel,Eco,1046,3,5,3,3,3,3,3,3,5,2,4,5,4,3,22,16.0,neutral or dissatisfied +67905,80128,Male,Loyal Customer,27,Business travel,Business,2475,1,1,1,1,5,5,5,3,4,4,5,5,4,5,0,19.0,satisfied +67906,82359,Male,Loyal Customer,69,Personal Travel,Eco,453,2,5,3,3,4,3,4,4,2,5,5,4,3,4,0,0.0,neutral or dissatisfied +67907,41930,Female,Loyal Customer,26,Personal Travel,Eco,129,4,0,4,4,4,4,4,4,3,4,4,3,5,4,0,3.0,neutral or dissatisfied +67908,71868,Male,Loyal Customer,69,Personal Travel,Eco,1829,3,5,3,5,5,3,3,5,5,5,3,4,4,5,0,0.0,neutral or dissatisfied +67909,94430,Male,disloyal Customer,25,Business travel,Business,189,3,4,3,1,3,3,3,3,3,4,4,5,4,3,7,0.0,neutral or dissatisfied +67910,118437,Female,Loyal Customer,27,Business travel,Business,3720,3,3,3,3,4,4,4,4,5,3,5,3,4,4,6,0.0,satisfied +67911,48299,Female,Loyal Customer,32,Business travel,Eco,1499,0,0,0,2,3,0,3,3,1,1,2,5,2,3,94,76.0,satisfied +67912,27041,Female,Loyal Customer,27,Business travel,Business,1489,2,2,2,2,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +67913,88648,Male,Loyal Customer,67,Personal Travel,Eco,515,2,4,3,4,2,3,2,2,3,2,5,4,5,2,0,9.0,neutral or dissatisfied +67914,40903,Male,Loyal Customer,51,Personal Travel,Eco,584,3,4,3,3,5,3,2,5,4,4,5,4,5,5,29,8.0,neutral or dissatisfied +67915,83092,Male,Loyal Customer,48,Business travel,Eco,557,2,5,5,5,2,2,2,2,4,4,3,2,3,2,45,66.0,neutral or dissatisfied +67916,28413,Female,Loyal Customer,27,Personal Travel,Business,1399,0,5,0,4,5,0,5,5,5,2,4,4,5,5,1,0.0,satisfied +67917,69838,Female,Loyal Customer,51,Business travel,Business,655,1,1,1,1,5,1,5,4,4,4,4,3,4,1,7,1.0,satisfied +67918,92695,Male,Loyal Customer,58,Personal Travel,Eco,507,2,4,2,4,3,2,4,3,5,4,4,4,4,3,0,0.0,neutral or dissatisfied +67919,94469,Female,Loyal Customer,41,Business travel,Business,1728,0,1,1,3,4,5,5,2,2,2,2,4,2,3,5,0.0,satisfied +67920,77260,Male,Loyal Customer,7,Personal Travel,Eco,1590,1,4,1,5,3,1,3,3,5,4,4,3,4,3,0,4.0,neutral or dissatisfied +67921,31784,Female,Loyal Customer,39,Personal Travel,Eco,602,2,5,2,2,1,2,1,1,4,4,4,3,5,1,19,18.0,neutral or dissatisfied +67922,45627,Female,Loyal Customer,41,Business travel,Business,2331,2,3,3,3,1,4,3,2,2,3,2,4,2,3,82,100.0,neutral or dissatisfied +67923,79377,Male,Loyal Customer,57,Business travel,Business,2995,2,2,2,2,3,4,5,5,5,5,5,5,5,5,0,7.0,satisfied +67924,125079,Male,Loyal Customer,56,Business travel,Business,361,4,4,4,4,5,4,5,4,4,4,4,3,4,5,24,19.0,satisfied +67925,121332,Male,Loyal Customer,45,Personal Travel,Eco Plus,1009,2,5,2,3,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +67926,120164,Female,disloyal Customer,20,Business travel,Eco,119,0,0,0,1,4,0,3,4,5,5,4,4,5,4,0,0.0,satisfied +67927,74621,Female,Loyal Customer,53,Business travel,Eco,835,3,5,5,5,1,4,3,3,3,3,3,2,3,1,19,7.0,neutral or dissatisfied +67928,62109,Female,Loyal Customer,56,Business travel,Business,2565,3,3,3,3,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +67929,60109,Male,disloyal Customer,23,Business travel,Eco,1005,5,5,5,3,5,5,1,5,5,2,5,3,5,5,1,0.0,satisfied +67930,46341,Male,Loyal Customer,26,Business travel,Business,692,2,3,2,2,4,4,4,4,1,4,1,4,4,4,1,0.0,satisfied +67931,87317,Female,Loyal Customer,48,Business travel,Business,2370,5,5,4,5,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +67932,35665,Male,Loyal Customer,45,Business travel,Business,2569,3,3,3,3,5,5,5,4,4,5,1,5,2,5,17,41.0,satisfied +67933,54539,Male,Loyal Customer,59,Personal Travel,Eco,925,1,4,1,5,2,1,2,2,3,2,5,3,4,2,12,6.0,neutral or dissatisfied +67934,42821,Male,Loyal Customer,41,Personal Travel,Eco,677,2,2,2,3,2,2,2,2,3,5,2,3,2,2,0,15.0,neutral or dissatisfied +67935,6665,Male,Loyal Customer,60,Business travel,Business,3921,2,2,2,2,5,4,5,2,2,2,2,3,2,5,67,60.0,satisfied +67936,99170,Female,Loyal Customer,56,Personal Travel,Eco,986,4,4,5,2,5,5,5,2,2,5,2,3,2,4,14,11.0,neutral or dissatisfied +67937,35507,Female,Loyal Customer,65,Personal Travel,Eco,1069,1,4,0,2,2,4,5,1,1,0,1,5,1,3,0,0.0,neutral or dissatisfied +67938,7329,Male,Loyal Customer,56,Personal Travel,Business,606,3,2,3,4,3,4,3,1,1,3,1,1,1,2,24,5.0,neutral or dissatisfied +67939,54049,Female,Loyal Customer,25,Business travel,Business,1416,1,1,5,1,4,5,4,4,3,2,4,1,3,4,29,15.0,satisfied +67940,105964,Female,disloyal Customer,48,Business travel,Eco,841,3,3,3,4,5,3,4,5,3,5,4,1,4,5,121,117.0,neutral or dissatisfied +67941,86863,Female,Loyal Customer,22,Personal Travel,Eco,484,4,3,4,3,2,4,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +67942,5906,Female,Loyal Customer,61,Business travel,Business,2006,4,4,4,4,2,4,1,5,5,5,5,3,5,5,0,0.0,satisfied +67943,54449,Female,Loyal Customer,31,Business travel,Business,2722,1,1,1,1,4,4,4,4,3,5,1,5,5,4,21,9.0,satisfied +67944,58947,Female,Loyal Customer,19,Business travel,Eco Plus,888,2,1,1,1,2,2,2,2,2,2,4,2,4,2,52,44.0,neutral or dissatisfied +67945,16031,Female,Loyal Customer,40,Personal Travel,Eco,780,2,3,2,1,2,2,2,2,5,4,4,1,3,2,0,0.0,neutral or dissatisfied +67946,23416,Female,Loyal Customer,27,Business travel,Business,495,1,4,3,4,1,2,1,1,2,3,3,3,3,1,8,11.0,neutral or dissatisfied +67947,68771,Male,Loyal Customer,27,Business travel,Business,3221,4,4,4,4,4,5,4,4,4,2,5,4,5,4,53,46.0,satisfied +67948,63896,Female,disloyal Customer,22,Business travel,Eco,1158,1,1,1,3,3,1,3,3,4,2,4,4,4,3,0,8.0,neutral or dissatisfied +67949,50492,Female,Loyal Customer,43,Personal Travel,Eco,156,4,4,4,5,3,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +67950,111422,Male,disloyal Customer,23,Business travel,Eco,896,3,3,3,3,4,3,4,4,2,4,4,3,3,4,26,17.0,neutral or dissatisfied +67951,25643,Female,Loyal Customer,49,Personal Travel,Eco,666,3,2,3,4,5,3,3,5,5,3,5,1,5,4,12,0.0,neutral or dissatisfied +67952,102040,Female,disloyal Customer,47,Business travel,Business,386,4,4,4,5,5,4,5,5,5,2,5,5,5,5,48,40.0,neutral or dissatisfied +67953,69677,Male,Loyal Customer,55,Personal Travel,Eco,569,3,1,3,2,4,3,2,4,1,5,1,4,1,4,0,0.0,neutral or dissatisfied +67954,53437,Male,Loyal Customer,49,Business travel,Business,2419,3,3,3,3,1,4,4,3,3,4,3,5,3,4,18,12.0,satisfied +67955,119164,Female,Loyal Customer,45,Business travel,Business,2684,3,3,3,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +67956,27606,Female,Loyal Customer,22,Personal Travel,Eco,679,2,5,2,1,5,2,5,5,3,3,4,3,4,5,4,17.0,neutral or dissatisfied +67957,86095,Female,disloyal Customer,43,Business travel,Business,164,2,2,2,3,4,2,4,4,4,5,2,3,3,4,25,13.0,neutral or dissatisfied +67958,99031,Female,Loyal Customer,42,Business travel,Eco,1009,2,4,4,4,2,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +67959,112734,Female,Loyal Customer,58,Business travel,Business,671,5,5,5,5,5,5,4,4,4,4,4,4,4,3,10,5.0,satisfied +67960,53062,Male,Loyal Customer,57,Personal Travel,Eco,1208,2,2,2,4,5,2,3,5,1,5,3,3,3,5,0,0.0,neutral or dissatisfied +67961,115133,Male,disloyal Customer,36,Business travel,Business,390,2,2,2,2,3,2,2,3,3,4,4,4,5,3,44,43.0,neutral or dissatisfied +67962,35678,Male,Loyal Customer,35,Business travel,Eco,2475,5,3,3,3,5,5,5,5,2,1,4,4,1,5,0,0.0,satisfied +67963,68752,Female,Loyal Customer,42,Business travel,Business,3277,2,2,2,2,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +67964,53525,Female,Loyal Customer,43,Personal Travel,Eco,2288,3,2,3,3,3,4,4,4,4,3,2,4,4,2,120,91.0,neutral or dissatisfied +67965,83042,Male,Loyal Customer,31,Business travel,Business,1022,2,2,2,2,3,4,3,3,4,2,5,5,5,3,5,25.0,satisfied +67966,120556,Female,Loyal Customer,69,Business travel,Business,1938,4,2,2,2,3,1,1,4,4,4,4,1,4,4,0,14.0,neutral or dissatisfied +67967,70021,Female,Loyal Customer,53,Business travel,Eco,583,4,4,4,4,2,4,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +67968,102766,Female,disloyal Customer,10,Business travel,Eco,1618,3,3,3,3,2,3,2,2,2,1,1,1,2,2,33,18.0,neutral or dissatisfied +67969,55161,Male,Loyal Customer,52,Personal Travel,Eco,1379,1,5,0,3,3,0,2,3,5,1,1,4,3,3,10,18.0,neutral or dissatisfied +67970,66584,Female,disloyal Customer,29,Business travel,Business,761,5,4,4,3,2,4,2,2,3,3,5,5,5,2,0,0.0,satisfied +67971,29120,Female,Loyal Customer,31,Personal Travel,Eco,978,4,5,5,1,2,5,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +67972,85540,Female,Loyal Customer,49,Business travel,Business,317,3,2,3,3,3,5,4,4,4,4,4,5,4,5,13,5.0,satisfied +67973,106232,Male,Loyal Customer,69,Personal Travel,Eco,471,1,4,1,2,5,1,5,5,5,5,5,4,5,5,115,103.0,neutral or dissatisfied +67974,67122,Female,Loyal Customer,15,Business travel,Business,1813,2,3,3,3,2,2,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +67975,48511,Female,Loyal Customer,50,Business travel,Eco,819,5,3,3,3,1,2,4,5,5,5,5,3,5,1,2,0.0,satisfied +67976,44614,Male,Loyal Customer,36,Personal Travel,Eco,508,4,3,4,1,5,4,5,5,3,3,1,3,2,5,0,0.0,neutral or dissatisfied +67977,3436,Female,Loyal Customer,55,Personal Travel,Eco,296,4,4,4,2,4,5,5,2,2,4,2,4,2,3,0,8.0,neutral or dissatisfied +67978,16932,Male,disloyal Customer,9,Business travel,Eco,820,4,4,4,3,4,4,2,1,2,3,3,2,4,2,156,144.0,neutral or dissatisfied +67979,110348,Female,Loyal Customer,42,Business travel,Business,2889,5,5,5,5,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +67980,51728,Male,Loyal Customer,25,Personal Travel,Eco,369,1,5,1,4,3,1,3,3,2,5,1,2,3,3,111,118.0,neutral or dissatisfied +67981,106179,Female,Loyal Customer,41,Personal Travel,Eco,302,2,4,2,5,1,2,1,1,4,4,4,5,5,1,33,28.0,neutral or dissatisfied +67982,118670,Female,disloyal Customer,17,Business travel,Eco,338,3,4,3,3,4,3,4,4,3,2,4,4,4,4,14,0.0,neutral or dissatisfied +67983,10409,Female,Loyal Customer,53,Business travel,Business,429,3,3,3,3,3,5,5,4,4,4,4,3,4,3,3,0.0,satisfied +67984,59510,Female,Loyal Customer,40,Business travel,Business,3829,5,5,5,5,4,5,4,4,4,5,4,5,4,4,14,0.0,satisfied +67985,87465,Female,Loyal Customer,62,Business travel,Business,2493,5,5,5,5,2,5,4,4,4,4,4,4,4,4,8,8.0,satisfied +67986,11359,Female,Loyal Customer,43,Personal Travel,Eco,308,2,4,2,3,4,4,3,2,2,2,3,3,2,2,0,0.0,neutral or dissatisfied +67987,122178,Male,Loyal Customer,31,Business travel,Business,541,4,4,4,4,2,2,2,2,4,5,5,4,5,2,0,0.0,satisfied +67988,45949,Male,Loyal Customer,46,Personal Travel,Eco,913,3,4,3,2,5,3,5,5,3,2,1,2,4,5,0,0.0,neutral or dissatisfied +67989,116431,Female,Loyal Customer,10,Personal Travel,Eco,373,2,4,2,2,4,2,4,4,2,4,4,5,2,4,30,21.0,neutral or dissatisfied +67990,56389,Male,Loyal Customer,33,Business travel,Business,1167,4,3,3,3,4,4,4,4,3,4,3,3,4,4,1,0.0,neutral or dissatisfied +67991,118711,Female,Loyal Customer,66,Personal Travel,Eco,338,5,3,1,2,3,2,4,2,2,1,2,5,2,5,16,16.0,satisfied +67992,81811,Male,Loyal Customer,48,Business travel,Business,1501,3,2,2,2,3,3,4,3,3,3,3,4,3,1,2,7.0,neutral or dissatisfied +67993,47532,Female,Loyal Customer,61,Personal Travel,Eco,599,1,2,1,3,4,3,4,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +67994,28217,Male,Loyal Customer,30,Business travel,Eco Plus,834,3,1,1,1,3,4,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +67995,5002,Male,Loyal Customer,44,Business travel,Eco,502,3,4,5,4,2,3,2,2,3,1,3,2,2,2,0,0.0,neutral or dissatisfied +67996,89190,Male,Loyal Customer,51,Personal Travel,Eco,1892,4,3,4,4,3,4,3,3,2,5,3,2,4,3,80,,neutral or dissatisfied +67997,101500,Female,Loyal Customer,31,Business travel,Eco,345,3,4,4,4,3,3,3,3,1,1,3,2,3,3,25,18.0,neutral or dissatisfied +67998,96819,Female,disloyal Customer,42,Business travel,Business,849,1,1,1,2,1,1,1,1,4,5,5,5,4,1,105,95.0,neutral or dissatisfied +67999,88890,Male,disloyal Customer,38,Business travel,Eco,859,3,4,4,2,1,4,4,1,1,4,2,3,3,1,35,19.0,neutral or dissatisfied +68000,68826,Male,Loyal Customer,45,Business travel,Business,1995,2,2,2,2,3,5,5,5,5,5,5,4,5,3,39,55.0,satisfied +68001,31392,Female,disloyal Customer,28,Business travel,Eco Plus,895,4,4,4,4,2,4,1,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +68002,16164,Male,Loyal Customer,35,Business travel,Business,199,5,5,5,5,1,1,4,4,4,4,4,3,4,4,0,0.0,satisfied +68003,56432,Male,disloyal Customer,27,Business travel,Eco,719,3,3,3,2,4,3,4,4,2,2,2,3,3,4,1,9.0,neutral or dissatisfied +68004,38028,Female,Loyal Customer,32,Business travel,Eco,1121,4,3,3,3,4,4,4,4,3,3,5,1,3,4,10,14.0,satisfied +68005,92932,Male,Loyal Customer,45,Business travel,Business,151,2,3,2,2,2,4,1,4,4,4,3,2,4,1,0,1.0,satisfied +68006,37027,Male,Loyal Customer,47,Business travel,Business,3414,3,3,3,3,2,4,5,4,4,4,4,4,4,4,32,18.0,satisfied +68007,92414,Male,Loyal Customer,39,Business travel,Business,1947,5,5,5,5,4,5,4,5,5,5,5,4,5,3,8,0.0,satisfied +68008,74673,Male,Loyal Customer,36,Personal Travel,Eco,1171,1,5,1,1,3,1,5,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +68009,27680,Female,disloyal Customer,23,Business travel,Eco,1107,2,2,2,2,5,2,5,5,2,2,3,4,3,5,3,8.0,neutral or dissatisfied +68010,103623,Male,Loyal Customer,43,Business travel,Business,251,5,5,5,5,2,4,4,4,4,4,4,5,4,3,67,65.0,satisfied +68011,82613,Male,Loyal Customer,38,Business travel,Business,408,2,2,2,2,2,2,4,4,4,4,4,3,4,3,0,0.0,satisfied +68012,6911,Male,Loyal Customer,39,Personal Travel,Eco,265,2,1,2,3,5,2,3,5,3,3,1,2,3,5,2,17.0,neutral or dissatisfied +68013,129216,Female,disloyal Customer,22,Business travel,Eco,1388,2,2,2,4,2,2,2,2,4,3,3,2,3,2,13,12.0,neutral or dissatisfied +68014,89371,Male,Loyal Customer,54,Business travel,Business,3414,0,5,0,1,2,4,4,3,3,3,3,4,3,4,1,0.0,satisfied +68015,128212,Male,Loyal Customer,27,Business travel,Business,3122,3,3,3,3,4,4,4,4,5,2,5,4,5,4,1,0.0,satisfied +68016,43926,Female,Loyal Customer,41,Personal Travel,Eco,174,2,5,2,5,4,2,4,4,3,2,4,5,4,4,33,38.0,neutral or dissatisfied +68017,100985,Male,Loyal Customer,15,Business travel,Eco Plus,1524,0,3,0,3,5,0,5,5,2,3,4,2,3,5,6,0.0,satisfied +68018,30603,Male,Loyal Customer,48,Business travel,Eco,472,2,2,2,2,2,2,2,2,3,2,3,4,3,2,0,8.0,neutral or dissatisfied +68019,123199,Female,Loyal Customer,30,Personal Travel,Eco,600,2,5,2,1,5,2,5,5,5,3,4,4,5,5,86,88.0,neutral or dissatisfied +68020,72581,Female,Loyal Customer,49,Business travel,Business,585,2,1,1,1,1,1,2,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +68021,574,Male,disloyal Customer,25,Business travel,Business,113,5,3,5,2,4,5,4,4,5,2,4,5,5,4,0,0.0,satisfied +68022,128664,Female,Loyal Customer,56,Business travel,Business,2288,3,3,3,3,4,4,4,4,2,5,5,4,4,4,0,8.0,satisfied +68023,72013,Male,Loyal Customer,32,Personal Travel,Business,3711,3,5,3,3,3,2,2,5,4,3,4,2,3,2,57,33.0,neutral or dissatisfied +68024,88512,Male,Loyal Customer,56,Business travel,Eco,404,4,5,5,5,4,4,4,4,2,4,2,5,2,4,0,0.0,satisfied +68025,10488,Female,Loyal Customer,52,Business travel,Business,3613,5,5,5,5,5,5,5,4,4,4,5,4,4,4,0,0.0,satisfied +68026,99853,Female,Loyal Customer,15,Personal Travel,Eco,680,4,5,4,3,5,4,5,5,4,4,4,3,5,5,5,0.0,satisfied +68027,89384,Female,Loyal Customer,39,Business travel,Business,151,2,2,2,2,3,5,5,5,5,5,4,3,5,5,3,0.0,satisfied +68028,29679,Male,Loyal Customer,56,Business travel,Eco Plus,909,2,5,5,5,2,2,2,2,4,5,4,4,4,2,28,21.0,neutral or dissatisfied +68029,46176,Female,Loyal Customer,67,Personal Travel,Eco,604,2,4,2,3,4,5,5,3,3,2,3,5,3,4,0,6.0,neutral or dissatisfied +68030,124030,Female,Loyal Customer,23,Personal Travel,Eco,184,1,2,1,4,5,1,5,5,1,4,3,1,4,5,0,0.0,neutral or dissatisfied +68031,116620,Female,Loyal Customer,40,Business travel,Business,2292,1,1,1,1,3,4,4,4,4,4,4,3,4,3,6,0.0,satisfied +68032,2800,Female,Loyal Customer,47,Personal Travel,Eco,764,4,4,4,5,3,4,4,1,1,4,1,5,1,4,0,0.0,satisfied +68033,64686,Female,Loyal Customer,50,Business travel,Business,2523,0,0,0,4,5,5,4,4,4,4,3,3,4,5,97,89.0,satisfied +68034,77996,Female,disloyal Customer,37,Business travel,Eco,332,1,1,1,4,5,1,5,5,1,5,3,3,4,5,20,7.0,neutral or dissatisfied +68035,28792,Male,Loyal Customer,21,Personal Travel,Business,697,3,5,4,3,4,4,2,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +68036,79245,Female,disloyal Customer,23,Business travel,Business,1598,4,4,5,3,3,5,3,3,5,2,3,3,4,3,0,13.0,satisfied +68037,799,Male,Loyal Customer,55,Business travel,Business,2389,1,1,1,1,2,5,5,5,5,5,5,4,5,4,37,28.0,satisfied +68038,16732,Male,Loyal Customer,51,Business travel,Business,3528,5,5,5,5,2,2,1,4,4,4,4,3,4,4,10,14.0,satisfied +68039,624,Female,Loyal Customer,39,Business travel,Business,1766,2,2,2,2,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +68040,106390,Female,disloyal Customer,24,Business travel,Eco,551,4,1,4,3,5,4,5,5,3,4,4,4,3,5,0,0.0,neutral or dissatisfied +68041,126993,Female,Loyal Customer,57,Business travel,Business,3662,3,3,3,3,3,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +68042,49379,Female,Loyal Customer,25,Business travel,Business,337,2,5,1,5,2,2,2,2,2,4,4,2,4,2,0,0.0,neutral or dissatisfied +68043,60273,Male,Loyal Customer,57,Business travel,Business,2446,3,3,3,3,4,3,3,3,3,5,4,3,3,3,211,221.0,satisfied +68044,125377,Male,disloyal Customer,24,Business travel,Eco,1440,2,2,2,4,2,2,5,2,4,4,4,3,5,2,0,0.0,satisfied +68045,86072,Female,Loyal Customer,41,Personal Travel,Eco Plus,554,3,4,3,3,2,5,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +68046,49844,Female,Loyal Customer,57,Business travel,Business,363,2,5,5,5,4,2,2,2,2,2,2,2,2,4,0,3.0,neutral or dissatisfied +68047,57054,Male,Loyal Customer,70,Personal Travel,Eco,2133,3,1,2,3,2,2,2,2,2,1,3,2,3,2,0,0.0,neutral or dissatisfied +68048,89806,Female,Loyal Customer,56,Business travel,Business,3768,3,3,3,3,5,4,5,4,4,4,4,5,4,3,30,65.0,satisfied +68049,109013,Male,Loyal Customer,60,Business travel,Business,3693,5,5,5,5,5,4,5,5,5,5,5,3,5,3,47,44.0,satisfied +68050,120746,Female,Loyal Customer,32,Business travel,Business,3275,5,5,5,5,5,5,5,5,3,5,4,3,5,5,118,109.0,satisfied +68051,43221,Male,Loyal Customer,45,Personal Travel,Eco,423,2,2,2,4,1,2,1,1,1,3,4,3,3,1,0,7.0,neutral or dissatisfied +68052,120921,Female,disloyal Customer,26,Business travel,Eco,861,4,4,4,3,3,4,3,3,4,3,3,1,3,3,0,16.0,neutral or dissatisfied +68053,98873,Female,Loyal Customer,45,Business travel,Business,991,2,3,2,2,5,5,4,5,5,5,5,3,5,3,4,3.0,satisfied +68054,80886,Female,disloyal Customer,24,Business travel,Eco Plus,692,1,2,1,3,3,1,3,3,2,1,4,1,3,3,2,7.0,neutral or dissatisfied +68055,33330,Female,disloyal Customer,16,Business travel,Eco,1232,3,3,3,1,1,3,1,1,3,1,3,4,1,1,2,0.0,neutral or dissatisfied +68056,96800,Female,disloyal Customer,25,Business travel,Eco,781,3,2,2,3,1,2,1,1,2,1,4,2,4,1,32,52.0,neutral or dissatisfied +68057,36901,Male,Loyal Customer,36,Business travel,Business,2072,4,4,4,4,5,5,4,4,4,4,4,1,4,4,0,0.0,satisfied +68058,61834,Female,Loyal Customer,44,Business travel,Business,1608,5,5,5,5,4,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +68059,109364,Female,Loyal Customer,33,Business travel,Business,3200,2,2,3,2,5,4,5,5,5,5,5,5,5,5,4,0.0,satisfied +68060,25530,Male,Loyal Customer,68,Personal Travel,Eco,481,3,3,5,4,4,5,4,4,2,2,3,3,3,4,0,0.0,neutral or dissatisfied +68061,44980,Female,Loyal Customer,40,Business travel,Eco,359,4,2,5,2,4,5,4,4,5,4,1,2,4,4,7,0.0,satisfied +68062,64480,Female,Loyal Customer,37,Business travel,Business,2384,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +68063,1709,Male,Loyal Customer,45,Business travel,Business,364,2,2,2,2,3,5,5,4,4,4,4,3,4,4,52,54.0,satisfied +68064,43415,Male,Loyal Customer,29,Business travel,Eco Plus,531,1,3,3,3,1,2,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +68065,19079,Male,Loyal Customer,66,Personal Travel,Eco,642,1,2,1,4,1,1,1,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +68066,22821,Female,Loyal Customer,39,Business travel,Business,147,2,5,5,5,4,4,4,2,2,2,2,4,2,3,84,73.0,neutral or dissatisfied +68067,18080,Male,Loyal Customer,48,Personal Travel,Eco,488,5,0,4,3,5,4,1,5,3,5,4,3,4,5,0,0.0,satisfied +68068,95992,Female,Loyal Customer,49,Business travel,Business,1235,3,3,3,3,3,4,4,5,5,4,5,5,5,4,53,57.0,satisfied +68069,56873,Female,disloyal Customer,33,Business travel,Business,2454,1,1,1,2,1,5,1,3,5,4,4,1,5,1,0,1.0,neutral or dissatisfied +68070,98154,Male,Loyal Customer,35,Business travel,Business,3774,2,2,5,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +68071,65349,Male,disloyal Customer,33,Business travel,Business,432,3,3,3,5,4,3,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +68072,98860,Female,disloyal Customer,25,Business travel,Eco,1751,1,1,1,1,5,1,5,5,1,5,4,2,4,5,1,0.0,neutral or dissatisfied +68073,126903,Female,Loyal Customer,18,Personal Travel,Eco Plus,2077,3,2,3,4,1,3,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +68074,75805,Male,Loyal Customer,41,Business travel,Eco Plus,813,3,3,3,3,3,3,3,3,4,5,4,1,3,3,65,67.0,neutral or dissatisfied +68075,128871,Female,Loyal Customer,38,Business travel,Business,2454,5,5,5,5,4,4,4,3,5,4,4,4,5,4,29,53.0,satisfied +68076,63684,Male,Loyal Customer,54,Personal Travel,Eco Plus,1047,3,5,3,2,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +68077,111345,Male,Loyal Customer,57,Business travel,Business,1956,4,5,4,4,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +68078,105878,Female,Loyal Customer,53,Business travel,Business,283,4,4,3,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +68079,14986,Male,Loyal Customer,52,Personal Travel,Eco,927,3,3,3,3,3,3,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +68080,70714,Male,Loyal Customer,25,Business travel,Business,1863,3,3,3,3,4,4,4,4,4,2,5,4,5,4,0,0.0,satisfied +68081,111277,Female,disloyal Customer,50,Business travel,Eco,479,2,3,3,4,3,3,5,3,2,3,3,2,4,3,1,12.0,neutral or dissatisfied +68082,3245,Female,Loyal Customer,57,Business travel,Business,3685,3,3,3,3,5,4,4,4,4,4,4,4,4,4,22,7.0,satisfied +68083,85256,Male,Loyal Customer,54,Personal Travel,Eco,696,2,4,2,1,2,2,2,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +68084,86227,Female,disloyal Customer,30,Business travel,Eco,356,4,3,3,5,2,3,2,2,4,2,1,1,2,2,0,0.0,neutral or dissatisfied +68085,26224,Male,Loyal Customer,32,Personal Travel,Eco,515,1,4,1,1,5,1,5,5,5,2,5,4,5,5,22,13.0,neutral or dissatisfied +68086,10243,Male,Loyal Customer,35,Personal Travel,Business,224,1,3,1,3,2,3,4,1,1,1,1,3,1,1,4,2.0,neutral or dissatisfied +68087,3612,Male,Loyal Customer,58,Business travel,Business,3154,1,1,1,1,2,4,4,5,5,5,5,5,5,4,8,2.0,satisfied +68088,6908,Female,Loyal Customer,19,Personal Travel,Eco,265,3,1,3,3,3,3,3,2,2,4,3,3,2,3,76,148.0,neutral or dissatisfied +68089,60386,Male,Loyal Customer,34,Business travel,Business,1452,2,2,2,2,3,4,5,5,5,5,5,3,5,5,3,0.0,satisfied +68090,55959,Female,Loyal Customer,33,Business travel,Business,1620,3,3,3,3,3,4,5,4,4,4,4,5,4,5,60,60.0,satisfied +68091,120441,Male,disloyal Customer,24,Business travel,Eco,366,2,4,2,3,3,2,3,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +68092,17814,Female,Loyal Customer,16,Personal Travel,Eco,1075,4,5,4,3,4,4,4,4,3,2,5,4,5,4,2,0.0,satisfied +68093,97007,Male,Loyal Customer,46,Personal Travel,Eco,883,1,2,1,1,4,1,4,4,4,2,4,3,3,4,0,0.0,neutral or dissatisfied +68094,20945,Male,Loyal Customer,59,Business travel,Eco,721,4,1,1,1,4,4,4,4,3,4,4,1,5,4,0,0.0,satisfied +68095,44895,Female,Loyal Customer,10,Business travel,Eco,536,3,1,1,1,3,4,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +68096,24140,Male,Loyal Customer,46,Personal Travel,Business,151,4,5,4,3,5,5,4,4,4,4,4,3,4,3,0,1.0,neutral or dissatisfied +68097,23892,Female,Loyal Customer,35,Business travel,Business,579,2,4,3,4,5,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +68098,23559,Male,Loyal Customer,35,Business travel,Business,3392,2,4,4,4,3,4,4,2,2,3,2,3,2,1,4,0.0,neutral or dissatisfied +68099,43017,Female,disloyal Customer,34,Business travel,Eco,259,2,0,2,1,3,2,3,3,3,5,1,4,3,3,0,0.0,neutral or dissatisfied +68100,12650,Male,Loyal Customer,70,Personal Travel,Eco,844,1,4,1,3,2,1,2,2,3,3,4,3,5,2,0,2.0,neutral or dissatisfied +68101,75937,Female,Loyal Customer,39,Business travel,Business,1572,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +68102,92860,Female,disloyal Customer,19,Business travel,Eco,801,4,4,4,5,5,4,5,5,3,3,5,5,5,5,10,48.0,neutral or dissatisfied +68103,59125,Female,Loyal Customer,33,Personal Travel,Eco,1744,3,4,2,3,3,2,4,3,4,2,5,4,4,3,4,3.0,neutral or dissatisfied +68104,48828,Male,Loyal Customer,24,Personal Travel,Business,110,2,4,2,4,4,2,4,4,4,1,3,4,3,4,1,0.0,neutral or dissatisfied +68105,57164,Male,Loyal Customer,40,Business travel,Business,2227,1,1,1,1,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +68106,70218,Female,Loyal Customer,30,Business travel,Business,2865,1,1,1,1,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +68107,78013,Male,Loyal Customer,68,Business travel,Business,1712,2,1,1,1,5,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +68108,88591,Female,Loyal Customer,48,Personal Travel,Eco,444,3,4,3,3,2,4,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +68109,126732,Female,disloyal Customer,25,Business travel,Business,2402,5,2,5,2,2,5,2,2,3,5,5,3,4,2,0,0.0,satisfied +68110,41820,Female,Loyal Customer,58,Personal Travel,Eco,257,3,3,3,4,3,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +68111,121425,Male,disloyal Customer,23,Business travel,Eco,331,5,0,5,2,3,0,3,3,3,3,5,4,5,3,0,0.0,satisfied +68112,56521,Male,Loyal Customer,34,Business travel,Business,1068,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,,satisfied +68113,117389,Male,Loyal Customer,37,Business travel,Eco,912,3,2,2,2,3,3,3,3,4,2,3,1,4,3,2,0.0,neutral or dissatisfied +68114,62261,Female,Loyal Customer,60,Business travel,Business,2425,5,5,4,5,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +68115,16745,Male,Loyal Customer,50,Business travel,Business,569,3,3,3,3,3,5,5,5,5,5,5,3,5,4,63,62.0,satisfied +68116,116531,Female,Loyal Customer,52,Personal Travel,Eco,417,1,4,3,4,3,3,3,4,4,3,4,3,4,1,22,9.0,neutral or dissatisfied +68117,62377,Female,Loyal Customer,43,Business travel,Business,2704,4,4,4,4,5,4,5,5,5,5,5,3,5,3,2,0.0,satisfied +68118,88448,Male,Loyal Customer,26,Business travel,Business,2009,1,3,2,3,1,1,1,1,2,2,3,2,4,1,0,0.0,neutral or dissatisfied +68119,18873,Male,Loyal Customer,36,Business travel,Business,1609,3,3,3,3,1,3,3,4,4,5,4,2,4,3,0,0.0,satisfied +68120,32731,Male,Loyal Customer,38,Business travel,Business,3499,2,3,3,3,1,4,4,3,3,3,2,1,3,3,0,3.0,neutral or dissatisfied +68121,101338,Female,Loyal Customer,30,Personal Travel,Eco,1771,3,2,4,3,1,4,2,1,2,1,4,2,4,1,21,2.0,neutral or dissatisfied +68122,114763,Female,Loyal Customer,52,Business travel,Business,371,5,5,4,5,2,4,5,4,4,4,4,4,4,4,10,9.0,satisfied +68123,26019,Female,Loyal Customer,28,Personal Travel,Eco,425,3,0,3,1,4,3,4,4,4,4,4,5,4,4,16,24.0,neutral or dissatisfied +68124,15972,Female,Loyal Customer,33,Personal Travel,Eco Plus,738,2,2,2,3,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +68125,17309,Female,Loyal Customer,42,Business travel,Eco,403,1,2,2,2,3,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +68126,129219,Female,Loyal Customer,42,Business travel,Business,1464,4,4,4,4,2,5,5,3,3,3,3,4,3,4,41,28.0,satisfied +68127,24015,Male,disloyal Customer,22,Business travel,Eco,562,3,3,2,4,3,2,3,3,3,3,3,4,3,3,0,6.0,neutral or dissatisfied +68128,87315,Female,Loyal Customer,55,Business travel,Eco Plus,577,4,4,3,4,3,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +68129,101260,Female,disloyal Customer,31,Business travel,Business,1910,3,3,3,3,5,3,5,5,5,4,3,4,4,5,58,35.0,neutral or dissatisfied +68130,58624,Female,Loyal Customer,29,Business travel,Business,867,3,3,3,3,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +68131,48028,Male,disloyal Customer,22,Business travel,Eco,1384,1,1,1,4,5,1,5,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +68132,90614,Male,disloyal Customer,20,Business travel,Eco,404,3,5,3,5,5,3,5,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +68133,44757,Male,Loyal Customer,52,Business travel,Business,3034,3,3,3,3,4,4,5,5,5,5,5,3,5,4,12,0.0,satisfied +68134,117633,Female,Loyal Customer,45,Personal Travel,Eco,843,3,5,3,2,2,3,4,4,4,3,4,4,4,2,25,17.0,neutral or dissatisfied +68135,76780,Male,disloyal Customer,32,Business travel,Business,546,2,2,2,3,2,2,1,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +68136,27614,Female,Loyal Customer,48,Personal Travel,Eco,679,1,1,1,3,5,4,4,3,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +68137,64684,Female,disloyal Customer,22,Business travel,Eco,190,2,4,2,4,2,2,2,2,5,3,5,4,5,2,6,2.0,neutral or dissatisfied +68138,95752,Female,Loyal Customer,47,Business travel,Eco,237,4,2,2,2,2,3,4,4,4,4,4,1,4,4,13,11.0,neutral or dissatisfied +68139,123660,Female,Loyal Customer,49,Business travel,Eco,214,2,2,2,2,5,3,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +68140,75477,Male,Loyal Customer,56,Personal Travel,Eco,2585,3,4,4,2,1,4,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +68141,38088,Male,Loyal Customer,61,Business travel,Eco,1185,2,2,2,2,2,2,2,2,1,1,4,2,4,2,18,0.0,neutral or dissatisfied +68142,57613,Female,disloyal Customer,25,Business travel,Business,200,3,5,3,2,5,3,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +68143,93828,Female,Loyal Customer,40,Business travel,Eco,391,3,1,1,1,3,3,3,3,2,2,4,2,4,3,36,18.0,neutral or dissatisfied +68144,9712,Male,Loyal Customer,44,Personal Travel,Eco,199,4,5,4,4,4,4,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +68145,63883,Male,Loyal Customer,43,Business travel,Eco,1158,2,2,2,2,2,2,2,2,2,2,4,4,3,2,14,15.0,neutral or dissatisfied +68146,15265,Male,Loyal Customer,55,Business travel,Business,3924,3,5,2,5,1,3,4,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +68147,80474,Male,Loyal Customer,53,Personal Travel,Eco,1299,4,5,4,4,5,4,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +68148,31141,Male,Loyal Customer,44,Personal Travel,Eco,996,4,5,4,3,4,4,3,4,3,2,5,4,5,4,11,5.0,neutral or dissatisfied +68149,82516,Male,Loyal Customer,30,Business travel,Business,1749,2,3,4,3,2,2,2,2,1,3,2,4,3,2,47,41.0,neutral or dissatisfied +68150,5686,Male,Loyal Customer,48,Business travel,Business,2511,1,1,1,1,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +68151,70214,Male,Loyal Customer,28,Personal Travel,Eco,258,5,4,5,3,4,5,4,4,4,1,4,4,3,4,0,0.0,satisfied +68152,24403,Male,Loyal Customer,22,Business travel,Eco,634,4,1,1,1,4,5,4,4,5,1,3,4,2,4,0,2.0,satisfied +68153,1707,Female,Loyal Customer,40,Business travel,Business,327,3,3,3,3,2,5,5,4,4,4,4,5,4,5,8,11.0,satisfied +68154,87749,Male,disloyal Customer,27,Business travel,Business,214,2,2,2,3,4,2,5,4,5,3,4,4,4,4,37,15.0,neutral or dissatisfied +68155,31459,Male,Loyal Customer,61,Business travel,Business,2532,5,5,5,5,2,5,5,4,4,4,4,1,4,4,11,10.0,satisfied +68156,73755,Female,Loyal Customer,66,Personal Travel,Eco,192,3,5,3,5,4,4,5,4,4,3,3,5,4,4,52,51.0,neutral or dissatisfied +68157,125902,Female,Loyal Customer,28,Personal Travel,Eco,993,1,4,0,5,1,0,1,1,4,5,5,5,4,1,0,5.0,neutral or dissatisfied +68158,53336,Female,disloyal Customer,26,Business travel,Business,1452,1,1,1,2,1,1,1,1,3,3,5,3,5,1,0,2.0,neutral or dissatisfied +68159,71566,Female,disloyal Customer,20,Business travel,Eco,1197,3,3,3,1,1,3,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +68160,86218,Male,Loyal Customer,39,Business travel,Eco,226,4,1,1,1,4,4,4,4,5,4,4,5,2,4,11,4.0,satisfied +68161,56206,Male,Loyal Customer,38,Business travel,Business,1400,4,4,4,4,2,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +68162,118420,Male,Loyal Customer,60,Business travel,Business,369,2,2,2,2,2,4,5,5,5,5,5,5,5,4,18,20.0,satisfied +68163,72427,Female,Loyal Customer,51,Business travel,Business,1794,2,2,2,2,4,4,4,4,4,4,4,5,4,3,13,15.0,satisfied +68164,34975,Female,Loyal Customer,47,Business travel,Eco,273,5,4,4,4,4,1,1,5,5,5,5,5,5,3,0,0.0,satisfied +68165,68632,Male,disloyal Customer,37,Business travel,Business,175,4,4,4,5,3,4,3,3,5,3,5,4,4,3,0,3.0,neutral or dissatisfied +68166,72479,Female,disloyal Customer,22,Business travel,Eco,964,1,1,1,3,3,1,4,3,5,5,5,3,4,3,3,0.0,neutral or dissatisfied +68167,61872,Male,disloyal Customer,38,Business travel,Business,1406,5,5,5,3,4,5,4,4,3,4,5,4,5,4,14,1.0,satisfied +68168,45000,Male,Loyal Customer,66,Business travel,Business,1646,1,1,1,1,2,3,2,5,5,5,5,2,5,5,0,0.0,satisfied +68169,127910,Male,Loyal Customer,19,Personal Travel,Eco,1671,2,3,2,3,5,2,5,5,1,2,1,5,3,5,0,0.0,neutral or dissatisfied +68170,71053,Male,Loyal Customer,27,Business travel,Business,802,3,5,5,5,3,3,3,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +68171,19888,Female,Loyal Customer,39,Business travel,Business,240,5,5,5,5,5,4,2,4,4,4,4,1,4,3,73,64.0,satisfied +68172,102079,Male,Loyal Customer,56,Business travel,Business,3181,1,1,1,1,5,5,4,5,5,5,5,4,5,4,8,0.0,satisfied +68173,37479,Male,disloyal Customer,22,Business travel,Eco,1069,1,1,1,2,5,1,5,5,3,2,2,2,2,5,0,0.0,neutral or dissatisfied +68174,72869,Male,Loyal Customer,51,Personal Travel,Eco,700,3,4,3,2,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +68175,63873,Female,Loyal Customer,20,Business travel,Business,2143,5,5,5,5,5,5,5,5,3,4,4,4,4,5,6,6.0,satisfied +68176,107477,Male,Loyal Customer,42,Business travel,Business,1675,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +68177,127311,Female,Loyal Customer,27,Personal Travel,Eco,1979,3,3,3,3,3,3,3,3,5,2,1,1,4,3,0,0.0,neutral or dissatisfied +68178,62695,Female,Loyal Customer,14,Personal Travel,Business,2615,3,5,3,5,3,3,3,3,4,2,4,3,5,3,89,73.0,neutral or dissatisfied +68179,74115,Male,Loyal Customer,31,Business travel,Business,592,5,5,5,5,5,4,5,5,5,2,5,5,5,5,0,0.0,satisfied +68180,16835,Female,Loyal Customer,33,Personal Travel,Eco,645,2,4,2,2,2,2,2,2,3,2,5,2,4,2,0,0.0,neutral or dissatisfied +68181,39416,Male,Loyal Customer,28,Business travel,Business,129,4,4,3,4,5,5,4,5,5,3,4,5,4,5,0,5.0,satisfied +68182,82014,Female,disloyal Customer,17,Business travel,Eco,859,2,2,2,3,3,2,2,3,1,4,4,3,4,3,39,17.0,neutral or dissatisfied +68183,93648,Male,disloyal Customer,23,Business travel,Eco,547,4,5,4,2,3,4,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +68184,14176,Male,Loyal Customer,36,Business travel,Business,2612,4,4,4,4,1,5,2,5,5,5,5,1,5,1,16,42.0,satisfied +68185,49226,Female,Loyal Customer,27,Business travel,Eco,89,5,1,2,1,5,5,5,5,1,2,4,1,4,5,0,0.0,satisfied +68186,23766,Male,Loyal Customer,54,Business travel,Business,1563,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +68187,91511,Female,disloyal Customer,62,Business travel,Eco,1075,2,2,2,2,4,2,4,4,2,4,1,2,3,4,0,0.0,neutral or dissatisfied +68188,73772,Female,Loyal Customer,8,Personal Travel,Eco,192,2,2,2,4,5,2,5,5,4,5,4,4,4,5,19,10.0,neutral or dissatisfied +68189,112410,Male,disloyal Customer,21,Business travel,Business,846,0,5,0,4,0,5,1,5,5,5,4,1,3,1,316,336.0,satisfied +68190,100709,Male,Loyal Customer,60,Business travel,Business,2879,2,4,4,4,3,3,4,2,2,2,2,1,2,4,9,22.0,neutral or dissatisfied +68191,42663,Female,Loyal Customer,23,Business travel,Business,1500,1,1,1,1,4,4,4,4,3,2,5,4,5,4,81,87.0,satisfied +68192,52534,Male,disloyal Customer,38,Business travel,Eco,160,0,3,0,1,5,0,5,5,1,5,5,2,5,5,1,0.0,satisfied +68193,125004,Female,disloyal Customer,35,Business travel,Eco,184,3,3,2,5,1,2,4,1,1,3,5,3,3,1,0,0.0,neutral or dissatisfied +68194,65229,Male,Loyal Customer,46,Business travel,Eco Plus,469,1,4,4,4,1,1,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +68195,38100,Male,Loyal Customer,32,Business travel,Business,1249,2,1,1,1,2,2,2,2,2,5,4,3,4,2,12,13.0,neutral or dissatisfied +68196,73877,Male,Loyal Customer,58,Business travel,Business,2585,3,3,3,3,4,4,4,5,4,3,4,4,4,4,16,39.0,satisfied +68197,121645,Female,Loyal Customer,37,Personal Travel,Eco Plus,912,2,4,2,2,2,2,2,2,4,3,4,3,1,2,0,0.0,neutral or dissatisfied +68198,129090,Female,Loyal Customer,41,Business travel,Business,2218,2,5,5,5,2,2,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +68199,94861,Female,Loyal Customer,43,Business travel,Business,2333,3,3,3,3,2,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +68200,13070,Female,disloyal Customer,21,Business travel,Eco,936,4,4,4,3,5,4,4,5,1,2,4,1,4,5,0,5.0,neutral or dissatisfied +68201,16467,Female,Loyal Customer,48,Personal Travel,Eco,416,1,2,1,3,5,3,3,3,3,1,2,2,3,1,0,0.0,neutral or dissatisfied +68202,5506,Female,Loyal Customer,36,Personal Travel,Eco,948,4,3,4,3,4,4,4,4,3,4,4,1,3,4,0,0.0,neutral or dissatisfied +68203,47284,Female,Loyal Customer,25,Business travel,Eco,590,3,5,5,5,3,4,4,3,3,1,1,3,4,3,0,0.0,satisfied +68204,65284,Female,Loyal Customer,57,Personal Travel,Eco Plus,190,1,2,1,4,5,4,3,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +68205,108214,Male,Loyal Customer,57,Business travel,Eco,777,2,1,1,1,2,2,2,2,2,3,3,4,3,2,5,22.0,neutral or dissatisfied +68206,43538,Male,Loyal Customer,44,Business travel,Business,3603,4,5,3,5,3,2,3,4,4,4,4,2,4,4,12,20.0,neutral or dissatisfied +68207,76764,Male,disloyal Customer,45,Business travel,Business,689,2,2,2,5,5,2,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +68208,89498,Female,disloyal Customer,22,Business travel,Business,684,4,0,4,2,2,4,2,2,5,4,4,5,4,2,40,46.0,satisfied +68209,21186,Male,Loyal Customer,49,Business travel,Eco,317,4,5,3,5,3,4,3,3,2,2,5,5,2,3,0,0.0,satisfied +68210,65026,Male,Loyal Customer,43,Personal Travel,Eco,190,4,5,4,2,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +68211,78594,Female,Loyal Customer,19,Business travel,Business,2454,3,3,3,3,3,2,3,3,2,4,2,3,3,3,0,0.0,neutral or dissatisfied +68212,56345,Female,Loyal Customer,34,Business travel,Business,200,2,2,2,2,5,3,3,3,3,3,2,4,3,4,0,59.0,neutral or dissatisfied +68213,93177,Male,Loyal Customer,62,Personal Travel,Eco,1183,2,4,2,4,1,2,1,1,1,3,2,2,3,1,0,24.0,neutral or dissatisfied +68214,70017,Male,disloyal Customer,24,Business travel,Eco,583,4,0,4,2,4,4,4,4,3,5,5,5,5,4,0,0.0,satisfied +68215,120588,Male,Loyal Customer,9,Business travel,Business,980,3,1,1,1,3,3,3,3,2,5,2,3,3,3,0,36.0,neutral or dissatisfied +68216,55445,Male,Loyal Customer,66,Personal Travel,Eco,2521,2,4,2,4,2,2,2,4,2,2,4,2,2,2,173,164.0,neutral or dissatisfied +68217,104684,Male,disloyal Customer,22,Business travel,Eco,159,3,1,3,3,3,3,3,3,2,4,3,2,4,3,0,0.0,neutral or dissatisfied +68218,6959,Female,Loyal Customer,52,Personal Travel,Eco Plus,588,3,5,3,3,2,5,5,2,2,3,2,3,2,3,18,70.0,neutral or dissatisfied +68219,85788,Female,Loyal Customer,53,Business travel,Business,3955,2,2,5,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +68220,107414,Male,Loyal Customer,64,Business travel,Eco,725,3,3,3,3,3,3,3,3,2,2,3,3,3,3,9,37.0,neutral or dissatisfied +68221,61461,Male,Loyal Customer,59,Business travel,Business,2288,2,2,2,2,2,3,4,4,4,4,4,5,4,4,8,0.0,satisfied +68222,14752,Female,disloyal Customer,12,Business travel,Eco,533,3,3,4,3,1,4,1,1,4,1,4,3,3,1,4,15.0,neutral or dissatisfied +68223,2292,Male,Loyal Customer,44,Business travel,Business,1041,1,2,2,2,3,4,3,1,1,1,1,4,1,4,85,80.0,neutral or dissatisfied +68224,55722,Female,Loyal Customer,55,Personal Travel,Eco Plus,1062,3,4,3,3,3,5,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +68225,119203,Female,Loyal Customer,44,Business travel,Business,257,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +68226,121391,Female,Loyal Customer,63,Business travel,Business,3828,0,0,0,1,5,5,4,1,1,1,1,5,1,3,0,0.0,satisfied +68227,104261,Male,Loyal Customer,52,Business travel,Business,2377,4,4,4,4,3,4,5,4,4,4,4,4,4,5,5,0.0,satisfied +68228,113495,Female,disloyal Customer,36,Business travel,Eco,236,2,1,2,4,4,2,1,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +68229,79825,Female,Loyal Customer,46,Business travel,Business,1552,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +68230,11080,Male,Loyal Customer,34,Personal Travel,Eco,316,3,0,4,2,4,1,1,5,4,5,4,1,3,1,184,206.0,neutral or dissatisfied +68231,48787,Female,Loyal Customer,29,Business travel,Business,199,1,5,5,5,4,4,1,4,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +68232,100713,Female,Loyal Customer,57,Business travel,Business,1722,2,2,2,2,2,4,5,5,5,5,5,4,5,5,45,56.0,satisfied +68233,108234,Male,Loyal Customer,31,Business travel,Business,3991,2,2,2,2,2,2,2,2,4,5,4,3,4,2,0,0.0,satisfied +68234,72180,Female,Loyal Customer,52,Business travel,Business,2355,3,3,5,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +68235,90105,Female,disloyal Customer,20,Business travel,Eco,957,4,4,4,3,5,4,5,5,4,5,3,2,4,5,0,7.0,neutral or dissatisfied +68236,71162,Male,Loyal Customer,57,Personal Travel,Eco,646,2,5,2,4,4,2,4,4,1,5,4,4,2,4,11,3.0,neutral or dissatisfied +68237,90628,Male,Loyal Customer,42,Business travel,Business,3228,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +68238,68510,Female,Loyal Customer,48,Business travel,Business,3566,3,3,3,3,3,4,5,2,2,2,2,5,2,5,5,7.0,satisfied +68239,48590,Female,Loyal Customer,52,Personal Travel,Eco,909,2,5,2,3,1,4,2,5,5,2,5,3,5,4,9,0.0,neutral or dissatisfied +68240,82520,Female,Loyal Customer,44,Business travel,Business,1749,4,4,4,4,4,3,5,4,4,4,4,4,4,4,6,1.0,satisfied +68241,68709,Male,Loyal Customer,19,Personal Travel,Eco,237,2,4,2,4,1,2,1,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +68242,86785,Male,Loyal Customer,48,Business travel,Business,2247,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,5.0,satisfied +68243,86530,Male,Loyal Customer,45,Personal Travel,Eco,760,2,4,2,1,3,2,3,3,1,3,4,3,4,3,100,103.0,neutral or dissatisfied +68244,75387,Female,Loyal Customer,46,Business travel,Business,2342,3,3,3,3,4,3,5,2,2,2,2,5,2,5,0,0.0,satisfied +68245,39976,Male,Loyal Customer,52,Business travel,Eco,1404,2,3,5,3,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +68246,89589,Male,Loyal Customer,50,Business travel,Business,1089,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +68247,8044,Female,disloyal Customer,24,Business travel,Eco,402,5,4,5,5,1,5,1,1,3,3,5,4,4,1,26,24.0,satisfied +68248,100819,Female,disloyal Customer,24,Business travel,Eco,711,1,1,1,2,4,1,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +68249,13120,Male,disloyal Customer,20,Business travel,Eco,427,1,0,1,2,4,1,4,4,4,3,1,4,4,4,3,0.0,neutral or dissatisfied +68250,16156,Male,disloyal Customer,48,Business travel,Eco,199,2,4,2,3,5,2,4,5,2,1,2,4,5,5,25,33.0,neutral or dissatisfied +68251,1254,Female,Loyal Customer,41,Personal Travel,Eco,354,3,5,4,2,3,4,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +68252,1842,Male,Loyal Customer,57,Personal Travel,Eco,408,2,4,2,3,4,2,5,4,4,5,5,5,5,4,3,0.0,neutral or dissatisfied +68253,78328,Female,Loyal Customer,44,Business travel,Business,1547,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,1.0,satisfied +68254,69115,Male,disloyal Customer,46,Business travel,Business,1598,5,5,5,1,1,5,1,1,3,4,3,5,4,1,0,0.0,satisfied +68255,30420,Male,Loyal Customer,42,Business travel,Business,2122,4,5,5,5,2,3,3,4,4,3,4,2,4,1,0,19.0,neutral or dissatisfied +68256,110739,Male,Loyal Customer,55,Business travel,Business,3140,3,4,3,3,3,5,5,4,4,4,4,3,4,5,6,6.0,satisfied +68257,12586,Male,Loyal Customer,25,Business travel,Business,542,4,4,4,4,5,5,5,5,5,3,5,4,2,5,0,12.0,satisfied +68258,121644,Male,Loyal Customer,69,Personal Travel,Eco Plus,912,1,4,1,2,4,1,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +68259,50007,Male,Loyal Customer,38,Business travel,Business,2317,5,5,5,5,4,2,1,5,5,4,5,4,5,2,0,0.0,satisfied +68260,128039,Female,Loyal Customer,63,Personal Travel,Eco,1440,1,4,1,2,3,3,4,2,2,1,5,5,2,3,0,1.0,neutral or dissatisfied +68261,126408,Female,disloyal Customer,21,Business travel,Business,650,0,0,1,3,1,1,1,1,5,5,5,4,5,1,3,2.0,satisfied +68262,42127,Male,Loyal Customer,53,Personal Travel,Eco,991,1,2,1,2,4,1,4,4,4,2,3,3,3,4,15,38.0,neutral or dissatisfied +68263,111200,Male,Loyal Customer,49,Business travel,Business,1506,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +68264,38663,Male,disloyal Customer,25,Business travel,Eco,1088,3,3,3,3,5,3,3,5,2,4,4,1,2,5,0,0.0,neutral or dissatisfied +68265,87427,Male,Loyal Customer,24,Business travel,Eco Plus,425,4,1,1,1,4,3,2,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +68266,33983,Female,disloyal Customer,27,Business travel,Eco,1366,1,1,1,1,1,1,1,1,3,5,3,3,5,1,0,0.0,neutral or dissatisfied +68267,51587,Female,Loyal Customer,33,Business travel,Business,493,3,2,2,2,4,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +68268,86928,Female,Loyal Customer,32,Personal Travel,Eco,352,3,5,3,1,2,3,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +68269,12568,Male,Loyal Customer,25,Business travel,Eco Plus,788,5,2,2,2,5,4,5,5,3,2,2,5,4,5,0,0.0,satisfied +68270,20328,Female,Loyal Customer,66,Personal Travel,Business,323,4,3,4,4,1,3,3,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +68271,82899,Female,Loyal Customer,62,Personal Travel,Eco,594,1,3,1,3,2,4,3,2,2,1,2,4,2,3,0,5.0,neutral or dissatisfied +68272,86581,Male,disloyal Customer,27,Business travel,Eco,869,3,3,3,1,5,3,5,5,2,4,3,2,5,5,44,31.0,neutral or dissatisfied +68273,93555,Male,Loyal Customer,30,Business travel,Business,3090,5,5,5,5,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +68274,125309,Female,Loyal Customer,50,Personal Travel,Eco,678,1,2,1,3,1,4,3,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +68275,69116,Male,Loyal Customer,42,Business travel,Business,1598,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0,1.0,satisfied +68276,19309,Male,Loyal Customer,39,Personal Travel,Eco Plus,196,1,4,1,3,5,1,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +68277,126043,Female,Loyal Customer,29,Business travel,Business,3124,3,3,3,3,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +68278,98859,Female,Loyal Customer,47,Business travel,Eco,1751,1,5,5,5,2,4,4,1,1,1,1,2,1,3,0,16.0,neutral or dissatisfied +68279,60669,Male,Loyal Customer,40,Personal Travel,Eco,1620,3,4,3,3,3,3,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +68280,57596,Female,Loyal Customer,61,Personal Travel,Eco Plus,1597,4,5,4,2,4,4,5,1,1,4,1,5,1,4,49,38.0,neutral or dissatisfied +68281,29041,Male,Loyal Customer,19,Personal Travel,Eco,954,5,4,5,3,5,4,5,5,5,3,5,5,5,5,0,4.0,satisfied +68282,91304,Male,Loyal Customer,28,Business travel,Eco Plus,581,1,2,2,2,1,1,1,1,2,5,3,2,4,1,0,7.0,neutral or dissatisfied +68283,25677,Female,Loyal Customer,36,Personal Travel,Eco,761,3,4,3,4,5,3,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +68284,76839,Female,Loyal Customer,48,Business travel,Business,1087,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +68285,116576,Male,Loyal Customer,43,Business travel,Business,308,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +68286,10473,Male,disloyal Customer,20,Business travel,Business,312,4,4,4,1,3,4,3,3,5,5,5,4,5,3,37,39.0,satisfied +68287,100622,Male,Loyal Customer,32,Personal Travel,Eco,1121,2,5,2,3,2,2,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +68288,17895,Male,disloyal Customer,22,Business travel,Eco,425,1,1,1,3,4,1,4,4,3,1,2,3,3,4,0,0.0,neutral or dissatisfied +68289,17789,Male,disloyal Customer,22,Business travel,Eco,1075,3,3,3,2,3,3,1,3,1,5,4,4,3,3,105,119.0,neutral or dissatisfied +68290,94021,Female,Loyal Customer,59,Business travel,Business,2345,1,1,1,1,5,4,5,4,4,4,4,5,4,4,13,4.0,satisfied +68291,103573,Female,Loyal Customer,39,Business travel,Business,3531,2,2,2,2,4,2,4,5,5,4,5,3,5,3,1,21.0,satisfied +68292,67310,Female,Loyal Customer,47,Business travel,Eco Plus,1119,2,1,1,1,3,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +68293,124734,Female,Loyal Customer,20,Personal Travel,Eco,399,3,3,3,3,2,3,2,2,4,4,5,3,2,2,0,0.0,neutral or dissatisfied +68294,51426,Female,Loyal Customer,18,Personal Travel,Eco Plus,326,1,2,1,3,2,1,3,2,3,4,1,3,3,2,0,6.0,neutral or dissatisfied +68295,570,Male,disloyal Customer,40,Business travel,Business,164,1,1,1,5,3,1,3,3,4,4,5,5,4,3,29,24.0,neutral or dissatisfied +68296,56962,Female,disloyal Customer,26,Business travel,Eco,2454,2,2,2,2,5,2,5,5,3,4,1,4,1,5,3,0.0,neutral or dissatisfied +68297,60355,Female,disloyal Customer,28,Business travel,Business,1452,4,4,4,1,2,4,2,2,5,5,5,5,5,2,11,0.0,neutral or dissatisfied +68298,106320,Female,Loyal Customer,58,Business travel,Business,825,2,2,2,2,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +68299,99108,Male,disloyal Customer,80,Business travel,Eco,181,4,3,4,3,1,4,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +68300,40973,Female,Loyal Customer,13,Personal Travel,Eco,601,3,4,3,1,4,3,2,4,2,4,5,2,4,4,0,0.0,neutral or dissatisfied +68301,78046,Male,Loyal Customer,58,Personal Travel,Eco,214,1,0,1,5,3,1,3,3,5,4,4,5,5,3,6,4.0,neutral or dissatisfied +68302,96065,Male,Loyal Customer,40,Personal Travel,Eco,1090,1,4,2,3,4,2,1,4,4,3,4,2,4,4,63,59.0,neutral or dissatisfied +68303,106939,Male,disloyal Customer,37,Business travel,Business,972,4,4,4,1,3,4,3,3,4,4,4,4,5,3,4,0.0,satisfied +68304,31579,Male,disloyal Customer,11,Business travel,Eco,602,2,0,2,3,3,2,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +68305,113360,Female,Loyal Customer,48,Business travel,Business,386,4,1,4,4,3,5,4,2,2,2,2,5,2,3,2,0.0,satisfied +68306,104571,Female,Loyal Customer,47,Business travel,Business,369,1,1,1,1,4,4,5,4,4,4,4,3,4,4,9,5.0,satisfied +68307,10988,Male,Loyal Customer,58,Business travel,Business,1820,5,5,5,5,2,5,2,3,3,3,3,4,3,2,6,4.0,satisfied +68308,94022,Female,Loyal Customer,52,Business travel,Business,248,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +68309,110654,Female,Loyal Customer,49,Business travel,Business,1998,2,2,3,2,4,4,4,5,5,5,5,3,5,4,16,5.0,satisfied +68310,75345,Female,Loyal Customer,48,Personal Travel,Eco,2486,3,4,3,3,1,5,3,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +68311,57534,Male,Loyal Customer,67,Business travel,Business,2232,3,4,4,4,4,3,3,3,3,3,3,2,3,2,0,2.0,neutral or dissatisfied +68312,83201,Female,Loyal Customer,36,Personal Travel,Eco,1123,4,5,4,5,1,4,1,1,4,4,4,5,4,1,0,21.0,neutral or dissatisfied +68313,32447,Male,Loyal Customer,32,Business travel,Eco,163,5,4,4,4,5,5,5,5,5,1,2,2,2,5,0,0.0,satisfied +68314,76821,Male,Loyal Customer,54,Business travel,Business,1851,3,3,3,3,2,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +68315,39888,Female,Loyal Customer,37,Personal Travel,Eco,272,2,1,4,2,3,4,3,3,4,4,1,4,2,3,0,0.0,neutral or dissatisfied +68316,122157,Male,Loyal Customer,44,Business travel,Eco,541,1,4,4,4,1,1,1,1,4,2,3,4,4,1,2,12.0,neutral or dissatisfied +68317,68899,Female,Loyal Customer,70,Personal Travel,Eco,936,4,4,4,4,3,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +68318,99612,Male,Loyal Customer,45,Personal Travel,Eco Plus,802,2,3,1,2,3,1,3,3,3,4,1,5,4,3,0,33.0,neutral or dissatisfied +68319,14261,Female,disloyal Customer,34,Business travel,Eco,429,3,5,3,5,5,3,5,5,2,1,1,3,3,5,9,8.0,neutral or dissatisfied +68320,49552,Male,Loyal Customer,44,Business travel,Eco,158,2,3,3,3,2,2,2,2,1,3,4,3,4,2,0,0.0,satisfied +68321,120330,Male,Loyal Customer,50,Business travel,Business,268,2,2,2,2,5,5,5,5,5,5,5,3,5,4,16,13.0,satisfied +68322,108515,Female,disloyal Customer,22,Business travel,Eco,119,4,3,4,3,1,4,3,1,3,4,2,1,5,1,0,0.0,satisfied +68323,12434,Female,Loyal Customer,30,Personal Travel,Eco,253,5,4,0,3,4,0,4,4,3,5,4,1,3,4,0,0.0,satisfied +68324,32445,Male,Loyal Customer,67,Business travel,Eco,216,4,1,4,1,4,4,4,4,3,5,3,2,3,4,0,3.0,satisfied +68325,107663,Male,Loyal Customer,47,Business travel,Business,2263,4,4,3,4,3,4,4,5,5,5,5,4,5,5,31,24.0,satisfied +68326,1263,Female,Loyal Customer,47,Personal Travel,Eco,282,3,4,3,1,5,1,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +68327,114120,Female,Loyal Customer,43,Personal Travel,Business,846,3,3,4,4,4,3,4,1,1,4,1,2,1,2,2,20.0,neutral or dissatisfied +68328,58149,Female,disloyal Customer,40,Business travel,Business,925,4,4,4,1,5,4,5,5,5,3,4,4,4,5,0,0.0,satisfied +68329,13072,Female,Loyal Customer,46,Personal Travel,Eco,936,2,5,2,3,3,5,1,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +68330,68130,Female,Loyal Customer,20,Personal Travel,Eco,868,3,1,3,3,4,3,4,4,2,2,4,3,3,4,14,17.0,neutral or dissatisfied +68331,50746,Male,Loyal Customer,22,Personal Travel,Eco,421,3,3,3,3,2,3,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +68332,70589,Female,Loyal Customer,24,Personal Travel,Eco Plus,1258,2,4,2,3,2,2,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +68333,95126,Male,Loyal Customer,70,Personal Travel,Eco,239,2,2,0,3,0,3,3,3,2,4,3,3,4,3,358,354.0,neutral or dissatisfied +68334,59474,Male,Loyal Customer,25,Business travel,Business,2756,2,1,1,1,2,1,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +68335,72429,Female,Loyal Customer,28,Business travel,Business,985,1,3,3,3,1,1,1,1,2,4,3,1,3,1,0,17.0,neutral or dissatisfied +68336,81763,Male,disloyal Customer,20,Business travel,Eco,1310,1,1,1,5,1,1,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +68337,115891,Male,Loyal Customer,37,Business travel,Business,417,2,2,2,2,5,4,2,5,5,5,5,5,5,4,70,56.0,satisfied +68338,100242,Male,disloyal Customer,37,Business travel,Business,1033,3,3,3,2,1,3,1,1,4,2,4,4,4,1,19,13.0,neutral or dissatisfied +68339,47646,Female,Loyal Customer,45,Business travel,Business,1482,2,4,4,4,5,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +68340,15649,Female,Loyal Customer,14,Personal Travel,Eco Plus,288,2,5,2,2,5,2,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +68341,126815,Male,Loyal Customer,64,Business travel,Eco,2296,4,2,2,2,4,4,4,4,2,4,3,3,3,4,0,0.0,neutral or dissatisfied +68342,60383,Female,Loyal Customer,45,Business travel,Business,1452,4,4,5,4,3,4,4,5,5,5,5,5,5,5,39,11.0,satisfied +68343,117880,Female,Loyal Customer,34,Business travel,Business,2544,0,0,0,5,2,4,4,5,5,5,5,3,5,3,68,72.0,satisfied +68344,22378,Female,Loyal Customer,49,Business travel,Business,238,4,2,2,2,2,3,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +68345,83994,Female,Loyal Customer,30,Business travel,Business,2304,3,2,2,2,3,3,3,3,1,2,4,1,3,3,32,28.0,neutral or dissatisfied +68346,72187,Female,Loyal Customer,42,Business travel,Business,594,3,3,3,3,4,4,5,5,5,5,5,3,5,4,12,0.0,satisfied +68347,102217,Male,Loyal Customer,56,Business travel,Business,2489,1,2,2,2,3,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +68348,42793,Male,Loyal Customer,55,Business travel,Eco Plus,349,3,4,5,4,3,3,3,3,3,2,3,3,3,3,0,0.0,satisfied +68349,64913,Female,Loyal Customer,25,Business travel,Business,3234,2,4,4,4,2,2,2,2,4,2,3,4,3,2,9,0.0,neutral or dissatisfied +68350,53574,Female,Loyal Customer,41,Business travel,Business,1577,2,5,5,5,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +68351,104333,Male,Loyal Customer,44,Business travel,Business,3238,1,1,1,1,2,2,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +68352,84007,Male,Loyal Customer,9,Personal Travel,Eco,373,2,4,2,4,3,2,3,3,5,3,4,4,1,3,0,0.0,neutral or dissatisfied +68353,124071,Female,Loyal Customer,15,Personal Travel,Eco,2153,2,5,2,1,2,3,3,5,5,5,5,3,4,3,0,10.0,neutral or dissatisfied +68354,98199,Female,Loyal Customer,45,Personal Travel,Eco,327,3,0,3,2,4,5,4,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +68355,26674,Male,Loyal Customer,20,Personal Travel,Eco,406,2,5,2,3,5,2,5,5,4,2,5,3,4,5,2,0.0,neutral or dissatisfied +68356,16625,Female,disloyal Customer,36,Business travel,Eco Plus,1008,2,2,2,4,1,2,1,1,4,4,4,3,3,1,25,5.0,neutral or dissatisfied +68357,44164,Female,Loyal Customer,38,Business travel,Eco,229,5,1,1,1,5,5,5,5,5,3,1,4,4,5,0,0.0,satisfied +68358,50670,Female,Loyal Customer,27,Personal Travel,Eco,86,3,5,3,1,5,3,5,5,3,3,5,5,4,5,48,42.0,neutral or dissatisfied +68359,12353,Female,disloyal Customer,20,Business travel,Eco,127,5,0,5,4,4,5,4,4,1,3,3,5,4,4,0,0.0,satisfied +68360,59977,Female,Loyal Customer,65,Personal Travel,Eco,1023,5,4,5,5,3,4,4,4,4,5,1,4,4,1,1,0.0,satisfied +68361,38379,Female,Loyal Customer,11,Personal Travel,Eco,1050,2,5,2,3,5,2,4,5,4,4,4,4,5,5,3,0.0,neutral or dissatisfied +68362,109473,Female,Loyal Customer,58,Business travel,Business,2215,3,3,3,3,2,5,4,5,5,5,5,4,5,4,55,58.0,satisfied +68363,77830,Male,Loyal Customer,25,Personal Travel,Eco,874,2,4,2,1,3,2,3,3,5,5,3,4,4,3,0,6.0,neutral or dissatisfied +68364,98708,Female,Loyal Customer,41,Business travel,Business,834,1,1,1,1,4,4,4,4,4,4,4,5,4,4,7,4.0,satisfied +68365,97106,Male,disloyal Customer,25,Business travel,Business,1211,0,0,0,5,1,0,1,1,4,3,4,5,4,1,0,0.0,satisfied +68366,20723,Male,Loyal Customer,14,Personal Travel,Eco,707,4,5,4,4,5,4,3,5,4,1,5,3,4,5,18,1.0,satisfied +68367,126328,Male,Loyal Customer,9,Personal Travel,Eco,631,5,3,5,3,4,5,4,4,5,1,1,2,1,4,0,0.0,satisfied +68368,107912,Female,Loyal Customer,64,Personal Travel,Eco,861,3,5,3,4,5,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +68369,711,Male,Loyal Customer,36,Business travel,Business,89,4,4,4,4,5,5,5,4,2,5,5,5,4,5,134,129.0,satisfied +68370,42361,Male,Loyal Customer,63,Personal Travel,Eco,451,3,5,5,2,2,5,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +68371,89711,Female,Loyal Customer,39,Personal Travel,Eco,1069,1,5,0,2,3,0,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +68372,92430,Female,Loyal Customer,34,Business travel,Business,1919,2,4,2,2,1,2,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +68373,107838,Male,Loyal Customer,35,Personal Travel,Eco,349,2,4,2,2,4,2,4,4,4,4,5,3,5,4,2,0.0,neutral or dissatisfied +68374,41374,Female,Loyal Customer,46,Business travel,Business,3149,5,5,5,5,4,3,3,5,5,5,5,1,5,3,0,4.0,satisfied +68375,85519,Male,Loyal Customer,33,Business travel,Eco Plus,332,2,4,4,4,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +68376,119966,Male,Loyal Customer,14,Personal Travel,Eco,868,2,4,2,3,1,2,1,1,3,5,3,4,3,1,0,0.0,neutral or dissatisfied +68377,67541,Female,Loyal Customer,22,Business travel,Business,1464,3,3,3,3,5,5,5,5,4,5,4,3,4,5,0,8.0,satisfied +68378,76013,Male,Loyal Customer,40,Business travel,Business,3655,4,4,4,4,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +68379,111948,Female,disloyal Customer,8,Business travel,Eco,770,2,2,2,4,3,2,4,3,4,2,3,1,3,3,103,77.0,neutral or dissatisfied +68380,113012,Female,Loyal Customer,34,Business travel,Business,1797,1,1,5,1,3,5,5,4,4,4,4,5,4,4,5,6.0,satisfied +68381,82912,Female,Loyal Customer,63,Personal Travel,Eco,594,4,4,4,3,5,1,2,5,5,4,3,5,5,3,7,0.0,neutral or dissatisfied +68382,18668,Male,Loyal Customer,32,Personal Travel,Eco,253,1,2,1,3,3,1,3,3,3,4,3,4,3,3,6,40.0,neutral or dissatisfied +68383,44987,Female,disloyal Customer,25,Business travel,Eco,235,2,5,2,3,4,2,4,4,4,2,2,1,3,4,0,0.0,neutral or dissatisfied +68384,77098,Female,Loyal Customer,43,Business travel,Eco,1481,2,4,4,4,2,1,2,2,2,2,2,1,2,1,4,11.0,neutral or dissatisfied +68385,55162,Male,Loyal Customer,51,Personal Travel,Eco,1464,4,5,4,4,4,4,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +68386,87191,Male,Loyal Customer,57,Business travel,Eco,946,2,3,3,3,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +68387,120941,Male,Loyal Customer,42,Business travel,Business,861,2,2,2,2,5,4,5,5,5,5,5,4,5,5,1,3.0,satisfied +68388,90199,Female,Loyal Customer,43,Personal Travel,Eco,957,2,5,3,3,4,5,5,5,5,3,5,5,5,3,1,0.0,neutral or dissatisfied +68389,18936,Male,Loyal Customer,53,Personal Travel,Eco,448,2,2,2,4,5,2,5,5,3,5,4,1,4,5,5,10.0,neutral or dissatisfied +68390,81530,Female,disloyal Customer,64,Business travel,Eco,1124,3,3,3,4,4,3,1,4,2,1,3,2,4,4,29,24.0,neutral or dissatisfied +68391,116434,Male,Loyal Customer,32,Personal Travel,Eco,372,2,0,2,5,5,2,5,5,5,4,5,4,4,5,14,0.0,neutral or dissatisfied +68392,111551,Male,Loyal Customer,25,Business travel,Business,794,1,1,1,1,5,5,5,5,5,4,5,4,4,5,14,6.0,satisfied +68393,51186,Female,Loyal Customer,25,Business travel,Eco Plus,109,0,5,0,4,5,0,1,5,1,1,1,2,4,5,0,20.0,satisfied +68394,65661,Female,Loyal Customer,44,Business travel,Business,1021,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +68395,116577,Female,Loyal Customer,46,Business travel,Business,3925,2,2,2,2,4,4,4,5,5,5,5,3,5,4,50,41.0,satisfied +68396,17998,Female,disloyal Customer,20,Business travel,Eco,332,1,4,1,3,2,1,2,2,2,2,3,3,3,2,106,109.0,neutral or dissatisfied +68397,17621,Male,Loyal Customer,27,Business travel,Business,2464,1,1,1,1,1,1,1,1,4,3,4,3,4,1,55,61.0,neutral or dissatisfied +68398,23308,Female,disloyal Customer,29,Business travel,Eco,794,3,3,3,2,5,3,5,5,4,1,2,2,2,5,0,,neutral or dissatisfied +68399,103982,Female,disloyal Customer,18,Business travel,Eco,715,3,3,3,2,2,3,2,2,3,3,3,3,5,2,0,0.0,neutral or dissatisfied +68400,127734,Male,disloyal Customer,37,Business travel,Business,255,2,2,2,1,4,2,4,4,3,3,4,5,5,4,0,0.0,satisfied +68401,15443,Female,disloyal Customer,29,Business travel,Eco,377,3,4,3,4,3,3,3,3,5,4,3,3,2,3,156,143.0,neutral or dissatisfied +68402,50116,Female,disloyal Customer,49,Business travel,Eco,250,4,5,4,3,3,4,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +68403,11886,Female,disloyal Customer,24,Business travel,Eco,912,5,5,5,3,1,3,1,1,5,4,5,3,5,1,0,0.0,satisfied +68404,5954,Female,Loyal Customer,43,Business travel,Business,1250,3,3,3,3,4,5,4,4,4,4,4,3,4,3,9,5.0,satisfied +68405,37403,Male,Loyal Customer,57,Business travel,Eco,944,4,5,5,5,4,4,4,4,2,5,4,5,2,4,0,0.0,satisfied +68406,125244,Female,disloyal Customer,29,Business travel,Eco Plus,1149,2,2,2,3,4,2,4,4,4,4,3,4,3,4,0,15.0,neutral or dissatisfied +68407,129649,Female,Loyal Customer,38,Business travel,Business,308,3,3,3,3,4,3,3,4,2,4,5,3,4,3,135,134.0,satisfied +68408,82025,Female,Loyal Customer,32,Personal Travel,Eco,1535,3,5,3,2,5,3,5,5,5,2,4,3,5,5,0,4.0,neutral or dissatisfied +68409,24134,Female,Loyal Customer,23,Business travel,Eco Plus,584,0,4,0,1,3,0,3,3,1,2,2,2,4,3,0,0.0,satisfied +68410,34028,Male,Loyal Customer,55,Personal Travel,Eco,1598,4,1,5,3,2,5,2,2,2,5,1,2,3,2,41,16.0,neutral or dissatisfied +68411,123278,Female,Loyal Customer,65,Personal Travel,Eco,507,3,1,3,4,5,4,4,4,4,3,2,4,4,3,0,0.0,neutral or dissatisfied +68412,81370,Male,disloyal Customer,24,Business travel,Business,282,4,5,4,3,1,4,1,1,5,5,4,3,4,1,0,0.0,satisfied +68413,24770,Male,Loyal Customer,31,Business travel,Business,3252,1,2,2,2,1,2,1,1,1,4,3,2,3,1,0,0.0,neutral or dissatisfied +68414,817,Male,Loyal Customer,51,Business travel,Business,102,1,1,1,1,3,4,5,5,5,5,4,3,5,5,0,0.0,satisfied +68415,22999,Male,Loyal Customer,18,Personal Travel,Eco,817,3,0,3,1,3,3,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +68416,119843,Female,Loyal Customer,45,Business travel,Business,1691,5,5,5,5,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +68417,88397,Male,Loyal Customer,47,Business travel,Eco,581,2,1,2,1,2,2,2,2,3,1,4,2,4,2,0,2.0,neutral or dissatisfied +68418,113330,Male,Loyal Customer,40,Business travel,Business,1906,5,5,5,5,5,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +68419,49070,Female,Loyal Customer,36,Business travel,Business,2943,1,1,1,1,2,1,4,3,3,4,3,5,3,3,83,80.0,satisfied +68420,48758,Male,Loyal Customer,41,Business travel,Business,250,3,4,4,4,3,3,3,3,3,3,3,2,3,3,29,4.0,neutral or dissatisfied +68421,78100,Male,Loyal Customer,65,Business travel,Business,684,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +68422,112306,Female,Loyal Customer,42,Business travel,Business,967,2,2,2,2,5,5,4,2,2,2,2,5,2,3,33,16.0,satisfied +68423,42887,Female,Loyal Customer,35,Business travel,Business,200,2,2,2,2,3,1,3,4,4,4,5,5,4,3,1,0.0,satisfied +68424,79182,Female,Loyal Customer,66,Personal Travel,Eco,2422,1,5,1,2,1,3,3,3,5,4,4,3,5,3,13,6.0,neutral or dissatisfied +68425,32384,Female,Loyal Customer,42,Business travel,Business,2921,4,4,4,4,1,2,2,5,5,5,5,1,5,5,0,0.0,satisfied +68426,27582,Female,Loyal Customer,67,Personal Travel,Eco,697,3,5,3,1,5,1,4,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +68427,78538,Male,Loyal Customer,61,Personal Travel,Eco,666,3,2,3,3,1,3,1,1,4,1,3,2,3,1,13,36.0,neutral or dissatisfied +68428,74068,Female,Loyal Customer,8,Business travel,Business,2615,2,5,5,5,2,2,2,2,1,4,3,3,3,2,6,38.0,neutral or dissatisfied +68429,115337,Female,disloyal Customer,45,Business travel,Eco,342,4,3,4,4,1,4,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +68430,45428,Male,disloyal Customer,25,Business travel,Eco,649,1,4,2,4,3,2,2,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +68431,70509,Male,Loyal Customer,21,Personal Travel,Eco,867,1,5,2,2,1,2,1,1,1,4,3,2,5,1,0,0.0,neutral or dissatisfied +68432,109478,Male,Loyal Customer,57,Business travel,Business,2472,3,3,3,3,3,5,4,5,5,5,5,3,5,4,25,20.0,satisfied +68433,58066,Male,Loyal Customer,30,Business travel,Business,2305,2,2,2,2,5,5,5,5,4,4,4,5,5,5,11,0.0,satisfied +68434,39384,Female,disloyal Customer,30,Business travel,Eco,546,1,4,1,4,3,1,3,3,2,1,3,1,1,3,0,16.0,neutral or dissatisfied +68435,98982,Female,Loyal Customer,25,Personal Travel,Eco,543,3,5,3,4,1,3,3,1,1,1,4,2,1,1,51,45.0,neutral or dissatisfied +68436,107271,Male,Loyal Customer,44,Business travel,Eco,307,1,3,3,3,1,1,1,1,3,5,3,3,4,1,7,5.0,neutral or dissatisfied +68437,96482,Male,Loyal Customer,46,Business travel,Business,436,5,5,4,5,4,4,4,4,4,4,4,4,4,4,4,0.0,satisfied +68438,113727,Male,Loyal Customer,39,Personal Travel,Eco,236,2,5,2,2,2,2,2,2,5,4,4,5,5,2,95,92.0,neutral or dissatisfied +68439,72157,Female,Loyal Customer,8,Personal Travel,Eco,731,3,2,3,3,4,3,4,4,1,1,4,2,3,4,0,0.0,neutral or dissatisfied +68440,95350,Male,Loyal Customer,63,Personal Travel,Eco,248,4,5,4,3,1,4,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +68441,78839,Female,Loyal Customer,64,Personal Travel,Eco,554,2,4,2,1,5,4,4,1,1,2,1,3,1,4,12,41.0,neutral or dissatisfied +68442,93354,Male,Loyal Customer,29,Business travel,Business,1024,2,2,2,2,4,4,4,4,3,2,5,3,4,4,15,13.0,satisfied +68443,51595,Female,Loyal Customer,35,Business travel,Eco,370,4,5,3,5,4,3,4,4,4,4,3,3,4,4,27,44.0,neutral or dissatisfied +68444,81513,Female,Loyal Customer,20,Business travel,Business,3258,1,1,1,1,4,4,4,4,5,4,5,3,5,4,23,15.0,satisfied +68445,103302,Male,Loyal Customer,42,Business travel,Business,2333,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +68446,43928,Male,Loyal Customer,52,Personal Travel,Eco,255,3,5,3,4,1,3,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +68447,85162,Female,disloyal Customer,45,Business travel,Business,689,3,3,3,3,1,3,1,1,4,5,4,3,5,1,0,9.0,neutral or dissatisfied +68448,44144,Male,Loyal Customer,39,Personal Travel,Eco,98,3,5,0,1,2,0,1,2,4,2,4,4,5,2,0,4.0,neutral or dissatisfied +68449,40657,Female,Loyal Customer,37,Business travel,Business,3972,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +68450,57273,Female,Loyal Customer,45,Personal Travel,Eco,628,2,4,2,1,2,5,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +68451,87908,Female,Loyal Customer,49,Business travel,Business,444,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,3.0,satisfied +68452,16434,Male,Loyal Customer,49,Business travel,Eco,445,3,2,2,2,3,3,3,3,1,3,4,2,3,3,21,26.0,neutral or dissatisfied +68453,34952,Female,Loyal Customer,64,Personal Travel,Eco,187,3,2,3,3,3,3,3,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +68454,87149,Female,Loyal Customer,11,Personal Travel,Eco Plus,594,2,2,3,4,5,3,5,5,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +68455,103638,Female,Loyal Customer,47,Business travel,Business,251,4,4,4,4,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +68456,98787,Male,Loyal Customer,27,Business travel,Business,630,5,5,5,5,4,4,4,4,3,4,4,5,5,4,0,2.0,satisfied +68457,3132,Female,Loyal Customer,60,Business travel,Business,2320,0,5,0,5,3,5,4,1,1,1,1,5,1,5,34,33.0,satisfied +68458,103992,Female,Loyal Customer,39,Business travel,Business,1592,1,1,1,1,1,3,3,1,1,1,1,1,1,3,30,24.0,neutral or dissatisfied +68459,50338,Female,Loyal Customer,48,Business travel,Business,3800,5,5,5,5,5,3,1,4,4,4,3,4,4,1,0,5.0,satisfied +68460,15757,Female,Loyal Customer,46,Personal Travel,Eco,461,1,5,1,3,5,5,4,5,5,1,2,4,5,3,0,0.0,neutral or dissatisfied +68461,51144,Female,Loyal Customer,44,Personal Travel,Eco,373,2,4,2,5,2,3,4,3,3,2,3,3,3,1,8,1.0,neutral or dissatisfied +68462,74559,Female,Loyal Customer,14,Business travel,Business,1464,2,2,2,2,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +68463,82123,Male,Loyal Customer,46,Business travel,Business,2519,1,3,3,3,2,1,1,4,2,1,1,1,2,1,30,44.0,neutral or dissatisfied +68464,11117,Female,Loyal Customer,24,Personal Travel,Eco,316,3,4,3,3,3,3,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +68465,23360,Male,disloyal Customer,27,Business travel,Business,1162,4,4,4,3,5,4,5,5,1,5,4,3,3,5,0,0.0,neutral or dissatisfied +68466,6998,Male,Loyal Customer,47,Business travel,Business,1589,3,1,1,1,5,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +68467,8189,Male,Loyal Customer,47,Business travel,Business,3259,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +68468,20231,Male,disloyal Customer,57,Business travel,Business,228,2,2,2,2,5,2,5,5,5,3,3,1,2,5,0,0.0,satisfied +68469,106786,Female,Loyal Customer,57,Personal Travel,Eco Plus,829,4,5,4,1,4,5,4,5,5,4,2,5,5,5,29,18.0,neutral or dissatisfied +68470,61995,Male,Loyal Customer,30,Business travel,Business,2586,4,4,4,4,5,5,5,5,4,4,3,4,4,5,0,0.0,satisfied +68471,103646,Male,Loyal Customer,52,Business travel,Business,2264,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +68472,30219,Female,Loyal Customer,22,Personal Travel,Eco Plus,183,3,4,0,2,4,0,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +68473,54771,Male,Loyal Customer,68,Business travel,Eco Plus,965,4,3,3,3,4,4,4,4,3,3,4,3,4,4,67,61.0,neutral or dissatisfied +68474,122465,Male,Loyal Customer,25,Business travel,Business,2855,4,4,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +68475,126377,Male,Loyal Customer,28,Personal Travel,Eco,328,5,2,5,3,2,5,2,2,2,3,4,2,3,2,0,0.0,satisfied +68476,80864,Female,Loyal Customer,66,Personal Travel,Eco,692,1,5,1,3,5,4,4,3,3,1,3,4,3,3,10,0.0,neutral or dissatisfied +68477,50086,Male,Loyal Customer,36,Business travel,Business,1548,2,4,4,4,1,3,3,2,2,2,2,2,2,2,11,19.0,neutral or dissatisfied +68478,81914,Female,Loyal Customer,44,Business travel,Business,1589,4,4,4,4,5,3,5,3,3,4,3,3,3,5,0,0.0,satisfied +68479,11815,Male,Loyal Customer,59,Business travel,Business,2752,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,8.0,satisfied +68480,37735,Female,Loyal Customer,47,Personal Travel,Eco,1028,1,5,1,3,4,4,4,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +68481,98062,Female,Loyal Customer,21,Personal Travel,Business,1449,2,3,2,3,1,2,1,1,2,2,3,4,4,1,59,38.0,neutral or dissatisfied +68482,110470,Female,Loyal Customer,18,Personal Travel,Eco,925,3,5,3,3,5,3,5,5,4,2,4,4,4,5,2,7.0,neutral or dissatisfied +68483,59607,Male,Loyal Customer,39,Business travel,Business,2687,4,4,4,4,5,4,4,4,4,4,4,3,4,4,26,11.0,satisfied +68484,81408,Male,Loyal Customer,56,Business travel,Business,3037,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +68485,78057,Female,Loyal Customer,62,Personal Travel,Eco,214,2,3,2,4,1,3,3,5,5,2,5,3,5,2,0,16.0,neutral or dissatisfied +68486,2013,Female,Loyal Customer,56,Business travel,Business,733,2,2,2,2,2,5,4,2,2,2,2,3,2,5,7,5.0,satisfied +68487,114602,Female,Loyal Customer,41,Business travel,Business,2438,3,3,3,3,2,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +68488,4039,Female,Loyal Customer,18,Business travel,Business,483,2,1,1,1,2,2,2,2,3,3,3,3,4,2,10,12.0,neutral or dissatisfied +68489,81339,Female,Loyal Customer,47,Business travel,Eco,1299,3,5,5,5,1,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +68490,119690,Male,Loyal Customer,28,Business travel,Business,1496,2,2,2,2,2,2,2,2,4,5,5,3,4,2,0,0.0,satisfied +68491,111014,Male,Loyal Customer,50,Business travel,Business,197,2,2,2,2,3,4,5,5,5,5,4,3,5,3,10,14.0,satisfied +68492,88796,Male,Loyal Customer,56,Business travel,Business,444,3,3,3,3,5,5,4,5,5,4,5,5,5,5,1,0.0,satisfied +68493,109785,Male,disloyal Customer,22,Business travel,Business,1011,4,5,4,1,1,4,1,1,4,4,5,3,5,1,4,0.0,satisfied +68494,116633,Male,Loyal Customer,44,Business travel,Eco Plus,372,3,4,4,4,3,3,3,3,2,3,4,2,3,3,10,8.0,neutral or dissatisfied +68495,21373,Male,disloyal Customer,33,Business travel,Eco,554,1,3,1,3,3,1,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +68496,110737,Female,Loyal Customer,59,Business travel,Business,1105,3,3,3,3,4,5,4,3,3,3,3,4,3,3,23,15.0,satisfied +68497,57061,Female,Loyal Customer,20,Personal Travel,Eco,2133,2,3,2,5,2,2,5,2,2,1,2,1,1,2,0,0.0,neutral or dissatisfied +68498,32204,Male,Loyal Customer,36,Business travel,Business,2435,2,2,2,2,3,5,1,4,4,4,4,2,4,4,0,0.0,satisfied +68499,72284,Male,Loyal Customer,25,Personal Travel,Eco,919,2,5,2,3,2,2,2,2,5,4,5,5,5,2,1,0.0,neutral or dissatisfied +68500,76268,Male,Loyal Customer,31,Business travel,Business,1927,2,4,4,4,2,3,2,2,4,4,4,3,4,2,0,1.0,neutral or dissatisfied +68501,63306,Male,Loyal Customer,48,Business travel,Business,3284,2,1,1,1,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +68502,113176,Male,Loyal Customer,65,Personal Travel,Eco,677,2,5,1,3,2,1,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +68503,125737,Male,disloyal Customer,36,Business travel,Business,992,1,1,1,3,3,1,3,3,4,3,3,3,3,3,109,108.0,neutral or dissatisfied +68504,88526,Female,Loyal Customer,44,Personal Travel,Eco,581,3,5,3,3,5,4,5,5,5,3,5,4,5,5,1,0.0,neutral or dissatisfied +68505,125695,Female,Loyal Customer,53,Personal Travel,Eco,759,5,4,5,3,3,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +68506,125612,Male,Loyal Customer,23,Business travel,Business,2094,1,1,1,1,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +68507,106054,Male,Loyal Customer,68,Personal Travel,Eco,452,2,4,2,3,5,2,5,5,3,4,5,4,4,5,0,107.0,neutral or dissatisfied +68508,79173,Male,disloyal Customer,22,Business travel,Eco,1023,5,5,5,3,5,1,3,3,5,4,5,3,5,3,8,19.0,satisfied +68509,40579,Male,Loyal Customer,26,Business travel,Business,2279,5,5,5,5,4,4,4,4,1,5,3,5,5,4,0,0.0,satisfied +68510,36221,Male,disloyal Customer,27,Business travel,Eco,96,1,1,1,3,2,1,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +68511,46123,Female,Loyal Customer,28,Business travel,Eco,604,4,1,1,1,4,4,4,4,2,4,4,4,5,4,0,0.0,satisfied +68512,25796,Male,Loyal Customer,10,Personal Travel,Eco,762,2,5,2,1,3,2,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +68513,83374,Male,Loyal Customer,54,Personal Travel,Eco,1124,3,5,3,5,5,3,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +68514,99393,Female,disloyal Customer,22,Business travel,Eco,337,4,0,4,2,3,4,3,3,4,4,4,4,5,3,23,19.0,neutral or dissatisfied +68515,15074,Female,Loyal Customer,38,Business travel,Business,224,3,3,3,3,5,5,3,5,5,5,5,3,5,2,0,0.0,satisfied +68516,37386,Male,disloyal Customer,27,Business travel,Business,1118,1,1,1,2,1,1,2,1,4,1,5,1,2,1,0,0.0,neutral or dissatisfied +68517,89951,Female,Loyal Customer,18,Personal Travel,Eco,1416,3,4,3,3,3,3,1,3,4,5,1,2,1,3,0,0.0,neutral or dissatisfied +68518,18992,Male,Loyal Customer,21,Personal Travel,Eco,388,1,4,1,5,5,1,1,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +68519,65926,Male,Loyal Customer,16,Personal Travel,Eco,569,3,5,3,1,4,3,4,4,1,1,2,4,2,4,9,7.0,neutral or dissatisfied +68520,109712,Male,Loyal Customer,43,Business travel,Business,587,4,4,4,4,5,5,5,5,5,4,5,5,5,5,93,78.0,satisfied +68521,15327,Male,Loyal Customer,37,Business travel,Eco,199,5,5,5,5,5,5,5,5,3,3,1,3,3,5,11,15.0,satisfied +68522,71400,Female,Loyal Customer,53,Business travel,Business,334,3,3,4,3,3,5,4,5,5,5,5,3,5,4,43,47.0,satisfied +68523,7692,Female,Loyal Customer,24,Personal Travel,Eco,641,3,5,3,2,1,3,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +68524,78401,Female,Loyal Customer,49,Business travel,Business,453,1,1,1,1,2,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +68525,121915,Male,Loyal Customer,62,Personal Travel,Eco,366,3,5,3,3,1,3,1,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +68526,92454,Male,Loyal Customer,32,Business travel,Business,2092,4,4,4,4,4,4,4,4,3,5,3,4,5,4,0,0.0,satisfied +68527,107287,Male,Loyal Customer,60,Business travel,Business,283,3,5,5,5,5,4,3,3,3,3,3,4,3,3,7,56.0,neutral or dissatisfied +68528,105347,Female,Loyal Customer,37,Personal Travel,Eco,409,2,3,2,2,2,2,2,2,5,4,3,1,2,2,0,0.0,neutral or dissatisfied +68529,93761,Male,Loyal Customer,17,Personal Travel,Eco,368,3,5,3,2,3,3,3,3,1,3,4,4,1,3,0,0.0,neutral or dissatisfied +68530,104348,Female,Loyal Customer,23,Personal Travel,Eco,409,3,5,4,3,3,4,3,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +68531,117590,Female,Loyal Customer,33,Business travel,Business,872,3,2,2,2,1,1,1,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +68532,19185,Male,Loyal Customer,39,Personal Travel,Eco Plus,1069,0,5,0,4,5,0,5,5,3,3,5,1,5,5,0,0.0,satisfied +68533,57727,Female,Loyal Customer,41,Business travel,Business,1754,1,1,1,1,2,4,5,5,5,5,5,5,5,3,0,5.0,satisfied +68534,37729,Female,Loyal Customer,60,Personal Travel,Eco,1005,4,4,4,2,1,3,2,2,2,4,2,5,2,3,0,0.0,satisfied +68535,47722,Male,disloyal Customer,37,Business travel,Business,784,5,5,5,4,1,5,1,1,3,5,4,5,5,1,0,0.0,satisfied +68536,31072,Female,Loyal Customer,14,Personal Travel,Eco,862,3,4,3,3,2,3,2,2,3,3,5,4,4,2,58,39.0,neutral or dissatisfied +68537,95421,Male,Loyal Customer,60,Business travel,Business,293,1,1,1,1,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +68538,105737,Female,disloyal Customer,17,Business travel,Eco,787,4,3,3,4,5,3,5,5,4,3,4,1,3,5,11,24.0,neutral or dissatisfied +68539,9468,Male,Loyal Customer,38,Personal Travel,Eco,288,1,5,1,3,2,1,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +68540,4693,Female,Loyal Customer,56,Personal Travel,Eco,489,2,1,2,3,4,3,3,5,5,2,1,3,5,4,0,0.0,neutral or dissatisfied +68541,24435,Male,Loyal Customer,32,Business travel,Eco Plus,634,5,5,3,5,5,5,5,5,1,2,1,1,4,5,0,0.0,satisfied +68542,94625,Male,disloyal Customer,30,Business travel,Business,189,2,1,1,4,5,1,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +68543,27839,Male,Loyal Customer,66,Personal Travel,Eco,1533,2,4,2,3,1,2,4,1,5,5,5,3,4,1,2,0.0,neutral or dissatisfied +68544,19571,Male,Loyal Customer,37,Business travel,Eco,212,2,5,1,5,2,2,2,2,2,2,4,4,3,2,2,0.0,neutral or dissatisfied +68545,41030,Male,Loyal Customer,50,Business travel,Business,1086,2,2,2,2,2,3,5,5,5,5,5,5,5,5,0,1.0,satisfied +68546,65140,Female,Loyal Customer,18,Personal Travel,Eco,469,2,4,2,5,1,2,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +68547,94796,Female,Loyal Customer,31,Business travel,Business,3916,4,4,4,4,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +68548,112895,Female,Loyal Customer,51,Business travel,Business,1642,1,1,1,1,5,5,4,5,5,5,5,3,5,3,12,0.0,satisfied +68549,112229,Female,Loyal Customer,31,Personal Travel,Eco,1199,0,1,0,3,2,0,3,2,1,4,2,1,2,2,13,0.0,satisfied +68550,103813,Female,Loyal Customer,60,Business travel,Business,3949,1,1,1,1,4,5,4,4,4,4,4,3,4,4,16,8.0,satisfied +68551,28182,Male,Loyal Customer,53,Personal Travel,Eco,550,3,0,3,4,5,3,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +68552,51183,Female,Loyal Customer,29,Business travel,Eco Plus,266,4,5,5,5,4,4,4,4,3,1,2,2,4,4,105,94.0,satisfied +68553,80977,Female,Loyal Customer,59,Business travel,Business,1958,2,1,1,1,4,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +68554,9029,Male,Loyal Customer,57,Business travel,Business,173,2,2,3,2,2,5,4,4,4,4,5,5,4,5,0,4.0,satisfied +68555,88880,Male,disloyal Customer,28,Business travel,Business,859,3,3,3,4,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +68556,25042,Female,disloyal Customer,26,Business travel,Eco Plus,507,3,3,3,5,3,3,3,3,4,4,3,5,4,3,0,0.0,neutral or dissatisfied +68557,20506,Female,Loyal Customer,8,Personal Travel,Eco,139,3,3,3,4,1,3,3,1,2,1,3,4,3,1,43,52.0,neutral or dissatisfied +68558,35638,Female,Loyal Customer,40,Personal Travel,Eco,1626,4,5,4,4,4,4,5,4,5,4,4,3,5,4,0,9.0,neutral or dissatisfied +68559,107757,Male,Loyal Customer,29,Personal Travel,Eco,466,3,4,3,1,2,3,2,2,4,5,4,4,4,2,27,14.0,neutral or dissatisfied +68560,122189,Female,Loyal Customer,25,Business travel,Business,3424,3,3,3,3,2,2,2,2,5,5,5,4,5,2,0,16.0,satisfied +68561,109556,Female,Loyal Customer,49,Personal Travel,Eco,861,3,4,3,3,3,4,5,3,3,3,4,3,3,5,62,54.0,neutral or dissatisfied +68562,12706,Female,Loyal Customer,40,Business travel,Eco,803,4,2,2,2,4,4,4,4,4,1,4,1,3,4,0,0.0,neutral or dissatisfied +68563,106729,Male,disloyal Customer,26,Business travel,Business,1005,2,2,2,4,2,2,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +68564,82960,Female,Loyal Customer,45,Business travel,Business,1084,3,3,3,3,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +68565,68911,Male,Loyal Customer,53,Personal Travel,Eco,1061,3,4,3,3,1,3,1,1,4,2,5,3,4,1,3,0.0,neutral or dissatisfied +68566,110175,Female,Loyal Customer,63,Personal Travel,Eco,882,1,0,1,2,3,4,5,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +68567,122886,Female,Loyal Customer,69,Personal Travel,Eco,226,3,4,3,3,4,5,4,2,2,3,1,3,2,4,0,0.0,neutral or dissatisfied +68568,59499,Male,Loyal Customer,31,Personal Travel,Eco,921,3,4,2,2,4,2,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +68569,97201,Male,Loyal Customer,50,Personal Travel,Eco,1390,3,4,3,3,4,3,5,4,5,3,5,1,4,4,0,0.0,neutral or dissatisfied +68570,4268,Female,Loyal Customer,50,Business travel,Eco,502,3,5,5,5,2,3,3,3,3,3,3,3,3,4,0,12.0,neutral or dissatisfied +68571,46533,Male,Loyal Customer,39,Business travel,Eco,73,4,5,4,5,4,4,4,4,5,3,4,4,3,4,28,41.0,satisfied +68572,55213,Male,Loyal Customer,53,Business travel,Business,1998,2,2,2,2,4,4,4,4,4,4,4,5,4,4,19,0.0,satisfied +68573,27717,Male,Loyal Customer,51,Personal Travel,Business,1448,4,4,4,1,1,4,2,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +68574,85820,Male,Loyal Customer,29,Personal Travel,Eco,526,2,1,4,2,3,4,4,3,3,3,2,1,1,3,19,29.0,neutral or dissatisfied +68575,94417,Male,Loyal Customer,56,Business travel,Business,2375,0,0,0,2,5,5,5,5,5,5,5,4,5,5,121,110.0,satisfied +68576,27170,Male,Loyal Customer,11,Personal Travel,Eco,2640,3,3,3,1,3,1,1,2,4,3,4,1,3,1,0,5.0,neutral or dissatisfied +68577,94939,Male,Loyal Customer,36,Business travel,Business,2965,4,4,3,4,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +68578,60883,Male,Loyal Customer,46,Business travel,Business,1667,1,1,3,1,2,5,4,2,2,2,2,4,2,3,4,0.0,satisfied +68579,68720,Female,Loyal Customer,41,Business travel,Business,2537,1,1,5,1,5,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +68580,51452,Male,Loyal Customer,45,Personal Travel,Eco Plus,86,2,5,2,4,3,2,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +68581,9034,Female,Loyal Customer,50,Business travel,Business,3596,0,5,0,1,4,5,4,5,5,5,5,4,5,4,23,16.0,satisfied +68582,84247,Male,Loyal Customer,61,Personal Travel,Eco Plus,432,2,3,2,3,1,2,1,1,4,4,3,2,3,1,21,9.0,neutral or dissatisfied +68583,94736,Male,Loyal Customer,37,Business travel,Business,2494,4,4,4,4,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +68584,29011,Male,Loyal Customer,38,Business travel,Business,2796,2,2,2,2,5,3,4,2,2,2,2,3,2,4,0,7.0,neutral or dissatisfied +68585,74617,Male,Loyal Customer,72,Business travel,Business,1722,2,1,1,1,3,4,4,2,2,2,2,1,2,3,0,7.0,neutral or dissatisfied +68586,98533,Male,Loyal Customer,64,Personal Travel,Eco,668,2,5,2,4,5,2,5,5,3,2,5,4,5,5,23,17.0,neutral or dissatisfied +68587,128526,Female,Loyal Customer,46,Personal Travel,Eco,647,3,3,3,4,2,4,3,3,3,3,3,2,3,4,0,1.0,neutral or dissatisfied +68588,53285,Male,Loyal Customer,11,Business travel,Business,758,4,3,4,4,5,5,5,5,3,4,5,2,5,5,15,8.0,satisfied +68589,101825,Female,Loyal Customer,22,Personal Travel,Eco,1521,4,4,4,4,1,4,5,1,3,2,4,1,4,1,0,0.0,satisfied +68590,7914,Male,Loyal Customer,33,Business travel,Business,1020,1,1,4,1,5,5,5,5,5,5,3,1,1,5,0,0.0,satisfied +68591,85908,Male,Loyal Customer,67,Business travel,Business,761,4,4,4,4,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +68592,96218,Female,disloyal Customer,25,Business travel,Eco,328,4,1,4,2,4,4,4,4,2,2,2,2,2,4,17,19.0,neutral or dissatisfied +68593,69142,Male,disloyal Customer,28,Business travel,Eco,1322,2,2,2,3,1,2,1,1,3,3,3,2,3,1,44,46.0,neutral or dissatisfied +68594,31054,Female,Loyal Customer,54,Business travel,Eco,862,5,1,1,1,1,5,5,5,5,5,5,4,5,2,0,0.0,satisfied +68595,4883,Female,Loyal Customer,57,Personal Travel,Eco,408,4,4,4,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +68596,40455,Male,Loyal Customer,55,Business travel,Eco,222,3,1,4,1,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +68597,15620,Male,Loyal Customer,62,Personal Travel,Eco,228,4,1,4,4,1,4,1,1,4,4,4,1,3,1,0,0.0,neutral or dissatisfied +68598,68940,Male,Loyal Customer,55,Business travel,Eco,246,3,5,5,5,3,3,3,3,1,3,3,2,2,3,0,0.0,satisfied +68599,76738,Female,disloyal Customer,22,Business travel,Business,205,5,0,5,4,5,5,4,5,5,2,5,5,4,5,3,0.0,satisfied +68600,60265,Male,Loyal Customer,28,Personal Travel,Eco Plus,1506,2,4,2,3,2,2,2,2,1,2,3,4,3,2,7,32.0,neutral or dissatisfied +68601,9310,Male,Loyal Customer,49,Business travel,Business,3233,4,4,4,4,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +68602,36839,Female,disloyal Customer,42,Business travel,Eco,369,3,4,3,3,2,3,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +68603,119068,Female,Loyal Customer,27,Personal Travel,Business,1020,2,0,2,4,4,2,4,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +68604,14407,Male,Loyal Customer,43,Business travel,Eco Plus,389,3,2,2,2,3,3,3,3,2,1,4,4,3,3,54,32.0,neutral or dissatisfied +68605,94228,Female,Loyal Customer,48,Business travel,Business,2984,0,0,0,3,3,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +68606,60869,Female,Loyal Customer,7,Personal Travel,Eco,1491,3,4,3,3,1,3,1,1,1,5,2,2,1,1,0,0.0,neutral or dissatisfied +68607,21534,Female,Loyal Customer,24,Personal Travel,Eco,377,4,5,4,1,5,4,1,5,5,3,4,3,4,5,2,0.0,neutral or dissatisfied +68608,61200,Female,Loyal Customer,41,Business travel,Business,3528,5,5,5,5,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +68609,119428,Female,Loyal Customer,34,Personal Travel,Eco,399,4,5,4,2,5,4,2,5,4,3,5,5,4,5,5,0.0,neutral or dissatisfied +68610,124211,Female,Loyal Customer,42,Personal Travel,Eco,2176,5,2,4,4,5,3,3,2,2,4,2,2,2,1,0,0.0,satisfied +68611,30381,Male,Loyal Customer,65,Business travel,Eco,641,3,2,2,2,3,3,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +68612,764,Male,Loyal Customer,43,Business travel,Business,309,4,4,4,4,4,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +68613,113629,Male,Loyal Customer,30,Personal Travel,Eco,414,2,3,2,3,2,2,2,2,3,3,4,2,4,2,3,0.0,neutral or dissatisfied +68614,30176,Male,Loyal Customer,35,Personal Travel,Eco,183,4,2,4,3,5,4,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +68615,11505,Male,Loyal Customer,33,Personal Travel,Eco Plus,270,2,4,2,2,5,2,2,5,3,4,5,3,4,5,0,3.0,neutral or dissatisfied +68616,117740,Female,disloyal Customer,38,Business travel,Eco,535,2,3,2,3,2,2,2,2,3,5,4,2,3,2,31,,neutral or dissatisfied +68617,89835,Male,Loyal Customer,33,Personal Travel,Eco Plus,950,4,5,4,4,3,4,3,3,3,2,3,4,4,3,0,62.0,neutral or dissatisfied +68618,57505,Female,Loyal Customer,19,Personal Travel,Eco,1075,2,5,2,1,5,2,3,5,3,3,5,4,4,5,3,28.0,neutral or dissatisfied +68619,118139,Male,disloyal Customer,28,Business travel,Business,1444,2,2,2,3,3,2,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +68620,653,Male,disloyal Customer,27,Business travel,Business,482,4,4,4,2,2,4,2,2,3,2,4,3,5,2,0,0.0,satisfied +68621,66522,Female,Loyal Customer,49,Business travel,Business,447,4,4,4,4,2,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +68622,56844,Male,Loyal Customer,44,Business travel,Business,2565,4,1,4,4,4,4,4,5,3,4,4,4,5,4,0,0.0,satisfied +68623,71098,Male,Loyal Customer,58,Personal Travel,Eco Plus,802,4,5,4,4,2,4,2,2,4,5,5,3,5,2,0,0.0,satisfied +68624,7749,Male,Loyal Customer,39,Business travel,Business,3708,1,1,1,1,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +68625,37369,Male,Loyal Customer,43,Business travel,Eco,1069,2,5,5,5,2,2,2,2,1,3,2,4,4,2,18,0.0,satisfied +68626,105545,Female,Loyal Customer,18,Personal Travel,Eco,611,2,1,3,3,4,3,4,4,4,1,2,4,2,4,0,0.0,neutral or dissatisfied +68627,128125,Female,Loyal Customer,32,Personal Travel,Eco,1587,2,5,2,4,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +68628,1198,Female,Loyal Customer,7,Personal Travel,Eco,158,3,4,3,2,4,3,4,4,4,4,5,3,4,4,0,12.0,neutral or dissatisfied +68629,47591,Male,Loyal Customer,36,Business travel,Eco,1334,5,3,3,3,5,5,5,5,4,2,5,3,3,5,0,0.0,satisfied +68630,34373,Female,disloyal Customer,27,Business travel,Eco Plus,541,5,5,5,2,5,5,2,5,1,1,3,3,1,5,0,0.0,satisfied +68631,85817,Male,Loyal Customer,21,Personal Travel,Eco,666,1,4,1,4,1,2,3,3,2,5,4,3,5,3,133,119.0,neutral or dissatisfied +68632,106638,Female,Loyal Customer,38,Personal Travel,Eco,306,2,5,2,3,4,2,4,4,4,4,4,4,5,4,0,11.0,neutral or dissatisfied +68633,48277,Female,disloyal Customer,19,Business travel,Eco Plus,236,3,2,3,3,1,3,1,1,1,2,4,2,4,1,42,37.0,neutral or dissatisfied +68634,36180,Male,Loyal Customer,12,Personal Travel,Eco,1674,2,1,2,1,2,2,2,2,3,2,2,4,1,2,6,21.0,neutral or dissatisfied +68635,101636,Male,disloyal Customer,44,Business travel,Business,1733,2,2,2,4,5,2,5,5,2,5,2,1,4,5,51,44.0,neutral or dissatisfied +68636,16901,Female,Loyal Customer,33,Personal Travel,Eco,746,4,3,4,3,1,4,1,1,4,4,4,3,3,1,0,17.0,neutral or dissatisfied +68637,31008,Female,Loyal Customer,44,Business travel,Business,2918,1,5,5,5,5,3,2,1,1,1,1,1,1,2,31,30.0,neutral or dissatisfied +68638,116698,Male,Loyal Customer,70,Business travel,Eco Plus,325,4,3,4,4,3,4,3,3,4,5,3,2,3,3,21,19.0,neutral or dissatisfied +68639,102220,Male,Loyal Customer,48,Business travel,Business,386,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +68640,71711,Male,Loyal Customer,70,Personal Travel,Eco Plus,1120,3,1,3,3,1,3,1,1,2,1,4,4,3,1,86,71.0,neutral or dissatisfied +68641,72196,Male,Loyal Customer,16,Personal Travel,Eco,594,2,3,2,4,4,2,1,4,2,5,4,3,4,4,5,0.0,neutral or dissatisfied +68642,89252,Female,Loyal Customer,27,Personal Travel,Eco Plus,1947,4,5,4,1,1,4,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +68643,15280,Male,Loyal Customer,11,Personal Travel,Eco,500,2,5,2,1,1,2,1,1,1,5,1,2,4,1,0,3.0,neutral or dissatisfied +68644,53604,Male,Loyal Customer,30,Business travel,Business,1874,1,1,1,1,5,5,5,5,4,5,4,3,4,5,4,0.0,satisfied +68645,128117,Female,disloyal Customer,12,Business travel,Eco,1587,3,2,2,5,5,3,2,5,3,3,4,4,5,5,0,0.0,satisfied +68646,75276,Male,Loyal Customer,10,Personal Travel,Eco,1744,2,4,2,3,4,2,3,4,3,3,5,4,4,4,15,0.0,neutral or dissatisfied +68647,77072,Female,disloyal Customer,22,Business travel,Eco,991,2,2,2,4,4,2,4,4,4,3,4,2,3,4,0,0.0,neutral or dissatisfied +68648,78641,Male,Loyal Customer,49,Business travel,Business,2172,2,2,2,2,4,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +68649,11144,Male,Loyal Customer,30,Personal Travel,Eco,316,4,3,4,5,4,4,4,4,2,4,4,5,1,4,0,0.0,neutral or dissatisfied +68650,124239,Male,disloyal Customer,24,Business travel,Eco,1255,2,2,2,3,1,2,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +68651,125949,Female,Loyal Customer,12,Personal Travel,Eco,920,3,1,2,4,4,2,4,4,4,5,3,3,4,4,0,0.0,neutral or dissatisfied +68652,85354,Male,Loyal Customer,47,Business travel,Eco Plus,289,4,1,1,1,3,4,3,3,4,4,2,4,3,3,3,1.0,satisfied +68653,87515,Male,Loyal Customer,60,Personal Travel,Eco,373,3,1,3,4,4,3,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +68654,85909,Female,Loyal Customer,25,Business travel,Business,3444,3,1,1,1,3,3,3,3,4,3,4,1,3,3,0,0.0,neutral or dissatisfied +68655,40011,Female,Loyal Customer,22,Business travel,Business,575,1,1,1,1,5,4,5,5,5,2,3,2,3,5,0,24.0,satisfied +68656,66343,Female,Loyal Customer,44,Business travel,Eco,986,1,2,2,2,3,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +68657,125367,Male,Loyal Customer,20,Personal Travel,Eco,599,1,4,1,3,2,1,5,2,1,3,3,3,4,2,0,4.0,neutral or dissatisfied +68658,45816,Female,Loyal Customer,7,Personal Travel,Eco,411,5,5,2,2,3,2,1,3,5,5,4,4,4,3,0,0.0,satisfied +68659,57199,Male,Loyal Customer,49,Business travel,Business,1514,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +68660,119886,Male,Loyal Customer,43,Personal Travel,Eco,912,2,1,3,3,2,3,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +68661,42448,Female,disloyal Customer,25,Business travel,Eco,866,1,0,0,5,5,0,5,5,2,5,4,5,2,5,0,0.0,neutral or dissatisfied +68662,74574,Male,Loyal Customer,12,Business travel,Business,1464,3,4,4,4,3,3,3,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +68663,115485,Male,Loyal Customer,50,Business travel,Business,1967,3,3,2,3,2,4,5,5,5,5,5,5,5,3,3,0.0,satisfied +68664,39285,Male,disloyal Customer,19,Business travel,Business,67,0,3,0,4,4,0,4,4,1,4,4,5,1,4,0,0.0,satisfied +68665,104795,Female,Loyal Customer,58,Business travel,Business,587,4,4,4,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +68666,109895,Female,Loyal Customer,49,Business travel,Eco,765,2,4,1,4,3,3,1,2,2,2,2,2,2,3,2,0.0,satisfied +68667,18853,Male,Loyal Customer,53,Business travel,Eco,448,5,2,2,2,5,5,5,5,2,2,3,5,1,5,0,0.0,satisfied +68668,45635,Female,Loyal Customer,50,Personal Travel,Eco,230,4,4,4,3,3,5,4,2,2,4,5,3,2,5,0,0.0,satisfied +68669,104294,Female,Loyal Customer,57,Business travel,Eco,382,3,3,3,3,2,4,5,3,3,3,3,2,3,1,3,0.0,satisfied +68670,78893,Male,Loyal Customer,45,Business travel,Business,1727,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +68671,9925,Male,Loyal Customer,55,Business travel,Eco,508,3,4,4,4,3,3,3,3,4,4,2,4,3,3,0,0.0,neutral or dissatisfied +68672,129546,Male,Loyal Customer,48,Business travel,Eco,2342,3,2,4,4,3,3,3,3,1,3,3,4,4,3,12,4.0,neutral or dissatisfied +68673,112920,Female,disloyal Customer,24,Business travel,Eco,1357,4,4,4,2,1,4,1,1,5,3,1,5,1,1,0,0.0,neutral or dissatisfied +68674,74853,Female,Loyal Customer,26,Business travel,Eco Plus,2136,3,2,2,2,3,3,2,3,2,2,3,2,4,3,0,10.0,neutral or dissatisfied +68675,57692,Female,Loyal Customer,38,Business travel,Business,867,2,2,2,2,2,5,4,4,4,4,4,5,4,3,121,124.0,satisfied +68676,121395,Female,Loyal Customer,61,Personal Travel,Business,290,5,4,5,4,5,5,4,1,1,5,5,3,1,5,0,2.0,satisfied +68677,86284,Male,Loyal Customer,56,Personal Travel,Eco,356,2,4,2,3,1,2,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +68678,122786,Male,Loyal Customer,59,Business travel,Business,3770,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +68679,82436,Male,Loyal Customer,49,Business travel,Business,3360,2,1,1,1,1,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +68680,91754,Male,Loyal Customer,34,Business travel,Business,2692,3,5,4,5,1,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +68681,120088,Female,Loyal Customer,44,Business travel,Business,2225,4,4,4,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +68682,115498,Female,disloyal Customer,25,Business travel,Business,358,4,0,4,3,1,4,1,1,4,3,5,5,5,1,0,0.0,satisfied +68683,73396,Male,Loyal Customer,36,Business travel,Business,1197,3,2,2,2,4,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +68684,45882,Female,disloyal Customer,25,Business travel,Eco,913,2,2,2,1,2,2,2,2,3,5,1,2,2,2,7,18.0,neutral or dissatisfied +68685,57384,Female,Loyal Customer,45,Business travel,Business,3344,1,1,1,1,5,5,5,4,3,5,5,5,3,5,163,157.0,satisfied +68686,92596,Male,Loyal Customer,24,Business travel,Business,2218,2,2,2,2,4,4,4,4,3,2,5,4,5,4,0,0.0,satisfied +68687,73562,Female,disloyal Customer,27,Business travel,Business,192,4,4,4,3,5,4,1,5,5,4,4,5,5,5,0,0.0,satisfied +68688,3330,Male,Loyal Customer,51,Business travel,Business,315,0,0,0,2,3,4,4,4,4,4,2,5,4,4,0,0.0,satisfied +68689,71513,Female,Loyal Customer,42,Business travel,Business,3538,3,3,3,3,5,5,5,4,4,4,4,3,4,5,1,0.0,satisfied +68690,79929,Male,Loyal Customer,36,Business travel,Eco,1096,2,5,5,5,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +68691,99983,Female,Loyal Customer,38,Personal Travel,Business,281,3,4,3,3,3,4,4,2,2,3,2,3,2,5,16,13.0,neutral or dissatisfied +68692,62984,Male,Loyal Customer,44,Business travel,Business,853,4,5,5,5,3,2,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +68693,25104,Male,disloyal Customer,27,Business travel,Eco Plus,369,2,2,2,4,5,2,5,5,1,4,4,4,1,5,4,0.0,neutral or dissatisfied +68694,99989,Male,Loyal Customer,30,Business travel,Business,3082,0,0,0,3,4,5,5,4,4,5,4,5,5,4,17,6.0,satisfied +68695,116755,Female,Loyal Customer,7,Personal Travel,Eco Plus,337,4,5,4,4,5,4,5,5,3,5,4,4,5,5,26,19.0,neutral or dissatisfied +68696,115637,Female,disloyal Customer,69,Business travel,Eco,417,1,1,1,3,2,1,2,2,1,3,4,4,4,2,4,5.0,neutral or dissatisfied +68697,5703,Female,Loyal Customer,69,Personal Travel,Eco,196,5,1,5,2,1,1,2,3,3,5,3,4,3,1,0,3.0,satisfied +68698,77488,Female,disloyal Customer,23,Business travel,Business,989,5,0,5,3,2,5,2,2,3,3,4,4,5,2,106,94.0,satisfied +68699,85709,Female,Loyal Customer,44,Personal Travel,Eco,1547,2,4,2,5,2,5,4,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +68700,65132,Female,Loyal Customer,34,Personal Travel,Eco,551,1,3,1,3,2,1,2,2,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +68701,65741,Female,Loyal Customer,50,Business travel,Business,936,2,4,4,4,5,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +68702,13360,Female,disloyal Customer,38,Business travel,Eco,348,3,1,3,3,3,3,5,3,3,5,3,1,4,3,0,6.0,neutral or dissatisfied +68703,32288,Male,Loyal Customer,30,Business travel,Eco,101,4,3,3,3,4,4,4,4,4,1,1,5,4,4,0,0.0,satisfied +68704,34050,Female,Loyal Customer,53,Business travel,Business,1674,1,1,1,1,4,4,4,5,5,4,5,1,5,5,4,0.0,satisfied +68705,58936,Male,Loyal Customer,69,Personal Travel,Eco,888,1,1,1,3,4,1,4,4,3,4,3,4,4,4,2,0.0,neutral or dissatisfied +68706,124933,Male,Loyal Customer,62,Personal Travel,Eco,728,1,2,1,4,4,1,4,4,1,4,3,3,3,4,46,41.0,neutral or dissatisfied +68707,87385,Male,Loyal Customer,48,Business travel,Business,425,1,4,4,4,5,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +68708,109501,Male,Loyal Customer,26,Business travel,Business,3469,5,5,5,5,4,4,4,4,4,3,5,3,4,4,0,4.0,satisfied +68709,16153,Female,disloyal Customer,54,Business travel,Eco,199,1,5,1,1,2,1,2,2,1,2,2,2,2,2,0,0.0,neutral or dissatisfied +68710,33780,Male,Loyal Customer,56,Business travel,Eco,588,4,1,1,1,4,4,4,4,4,3,4,1,5,4,1,0.0,satisfied +68711,5298,Female,Loyal Customer,34,Personal Travel,Eco,285,3,1,3,3,4,3,4,4,4,2,4,3,4,4,0,,neutral or dissatisfied +68712,36590,Male,disloyal Customer,25,Business travel,Eco,1249,4,5,5,4,1,5,3,1,3,1,5,3,3,1,0,0.0,satisfied +68713,128142,Female,Loyal Customer,68,Personal Travel,Business,1849,3,4,3,4,2,3,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +68714,50856,Male,Loyal Customer,55,Personal Travel,Eco,110,3,3,3,4,5,3,5,5,5,4,1,1,1,5,0,0.0,neutral or dissatisfied +68715,85824,Female,Loyal Customer,36,Personal Travel,Eco,526,3,4,4,3,2,4,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +68716,99375,Male,Loyal Customer,39,Business travel,Business,3852,5,5,5,5,4,5,5,5,5,5,5,3,5,4,29,28.0,satisfied +68717,103732,Female,Loyal Customer,39,Personal Travel,Eco,405,2,4,2,3,2,2,4,2,4,2,5,3,4,2,7,11.0,neutral or dissatisfied +68718,34858,Male,Loyal Customer,20,Personal Travel,Eco Plus,1826,3,4,4,2,4,4,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +68719,841,Female,Loyal Customer,58,Business travel,Business,2808,3,2,2,2,4,3,4,3,3,3,3,2,3,4,11,6.0,neutral or dissatisfied +68720,518,Female,disloyal Customer,15,Business travel,Eco,247,2,0,2,3,4,2,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +68721,113233,Male,disloyal Customer,20,Business travel,Eco,407,3,3,3,3,3,3,2,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +68722,9766,Male,disloyal Customer,22,Business travel,Eco,383,5,4,5,1,1,5,1,1,3,2,5,3,4,1,0,12.0,satisfied +68723,81401,Female,Loyal Customer,44,Business travel,Business,2380,5,5,5,5,4,4,4,5,5,5,5,3,5,3,13,0.0,satisfied +68724,113913,Male,Loyal Customer,22,Business travel,Eco Plus,2295,3,2,2,2,3,3,3,3,2,4,2,2,4,3,3,0.0,neutral or dissatisfied +68725,9392,Female,disloyal Customer,26,Business travel,Eco,372,4,2,4,2,3,4,2,3,1,3,2,2,2,3,3,0.0,neutral or dissatisfied +68726,66443,Male,disloyal Customer,24,Business travel,Eco,1217,5,5,5,1,1,5,1,1,5,4,5,3,4,1,0,0.0,satisfied +68727,16691,Male,Loyal Customer,31,Business travel,Eco,200,0,0,0,1,4,0,4,4,3,1,5,2,5,4,0,0.0,satisfied +68728,83692,Female,Loyal Customer,59,Personal Travel,Eco,577,2,3,2,4,5,3,3,5,5,2,5,2,5,1,14,66.0,neutral or dissatisfied +68729,129660,Male,Loyal Customer,54,Business travel,Business,3325,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +68730,2306,Male,Loyal Customer,39,Business travel,Business,272,0,0,0,3,2,1,5,5,5,5,5,4,5,3,0,0.0,satisfied +68731,25122,Male,Loyal Customer,58,Personal Travel,Eco,946,1,4,1,4,3,1,3,3,1,2,5,2,5,3,0,5.0,neutral or dissatisfied +68732,123991,Male,disloyal Customer,38,Business travel,Business,184,3,3,3,5,3,3,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +68733,3722,Female,Loyal Customer,17,Personal Travel,Eco,427,2,2,2,3,3,2,3,3,4,2,4,2,3,3,15,15.0,neutral or dissatisfied +68734,115461,Female,Loyal Customer,22,Business travel,Eco,308,3,2,3,3,3,3,1,3,2,5,3,3,4,3,14,12.0,neutral or dissatisfied +68735,31906,Female,Loyal Customer,31,Business travel,Business,3271,4,4,4,4,3,4,4,3,3,5,5,3,4,3,1,5.0,satisfied +68736,94358,Male,disloyal Customer,24,Business travel,Business,293,5,0,5,3,4,5,4,4,5,4,4,3,4,4,0,0.0,satisfied +68737,14255,Female,disloyal Customer,33,Business travel,Business,429,3,3,3,3,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +68738,9214,Female,Loyal Customer,56,Business travel,Business,3179,1,1,1,1,5,4,4,5,5,5,4,3,5,5,9,18.0,satisfied +68739,23016,Male,Loyal Customer,59,Business travel,Eco Plus,489,1,1,1,1,2,1,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +68740,109542,Female,Loyal Customer,63,Personal Travel,Eco,861,3,4,4,2,3,4,5,3,3,4,3,3,3,3,6,7.0,neutral or dissatisfied +68741,89959,Female,Loyal Customer,26,Personal Travel,Eco,1310,4,5,4,3,5,4,3,5,5,2,5,4,5,5,0,1.0,neutral or dissatisfied +68742,6637,Female,Loyal Customer,46,Business travel,Business,2386,2,2,3,2,2,5,5,5,5,5,5,5,5,3,0,2.0,satisfied +68743,24964,Male,Loyal Customer,65,Personal Travel,Eco,226,2,5,0,4,3,0,3,3,4,2,5,5,5,3,1,0.0,neutral or dissatisfied +68744,101681,Male,Loyal Customer,59,Business travel,Business,1500,2,2,2,2,3,5,4,4,4,5,4,5,4,5,4,7.0,satisfied +68745,102506,Female,Loyal Customer,49,Personal Travel,Eco,236,3,4,3,4,4,5,5,5,5,3,5,5,5,4,121,122.0,neutral or dissatisfied +68746,52118,Male,Loyal Customer,40,Business travel,Eco Plus,639,3,5,5,5,3,3,3,3,4,2,4,5,4,3,38,25.0,satisfied +68747,21710,Male,Loyal Customer,49,Personal Travel,Eco,746,2,3,2,2,4,2,5,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +68748,50309,Female,Loyal Customer,58,Business travel,Business,1904,1,3,3,3,2,3,4,1,1,1,1,4,1,4,0,8.0,neutral or dissatisfied +68749,59331,Female,Loyal Customer,62,Business travel,Business,2447,2,1,1,1,4,2,1,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +68750,118009,Male,Loyal Customer,38,Business travel,Business,3182,2,3,3,3,3,3,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +68751,91003,Female,Loyal Customer,67,Personal Travel,Eco,404,2,5,2,3,4,5,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +68752,7603,Male,Loyal Customer,27,Business travel,Business,825,2,5,4,5,2,2,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +68753,128531,Male,Loyal Customer,46,Personal Travel,Eco,370,3,5,3,4,2,3,2,2,1,4,4,3,4,2,0,0.0,neutral or dissatisfied +68754,99372,Female,Loyal Customer,54,Business travel,Business,2667,1,1,1,1,2,4,4,4,4,5,4,3,4,3,1,8.0,satisfied +68755,129737,Male,Loyal Customer,37,Business travel,Business,1944,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +68756,102117,Female,disloyal Customer,27,Business travel,Business,414,1,1,1,2,5,1,5,5,3,2,5,3,4,5,29,19.0,neutral or dissatisfied +68757,15430,Male,Loyal Customer,43,Business travel,Business,2728,2,1,1,1,4,3,3,2,2,2,2,1,2,2,56,40.0,neutral or dissatisfied +68758,76361,Male,Loyal Customer,59,Business travel,Business,3322,2,2,2,2,5,5,4,3,3,3,3,5,3,3,0,3.0,satisfied +68759,110667,Female,Loyal Customer,18,Business travel,Eco,1005,1,3,1,1,1,1,2,1,1,1,2,1,3,1,29,31.0,neutral or dissatisfied +68760,106143,Male,disloyal Customer,23,Business travel,Eco,302,2,1,1,3,1,1,1,1,3,3,3,1,2,1,8,10.0,neutral or dissatisfied +68761,54107,Female,Loyal Customer,41,Business travel,Business,1400,3,3,3,3,2,5,4,4,4,5,4,3,4,4,0,4.0,satisfied +68762,55402,Male,Loyal Customer,23,Business travel,Business,1558,4,4,2,4,4,4,4,4,4,3,5,4,4,4,6,0.0,satisfied +68763,40429,Male,Loyal Customer,28,Business travel,Business,3850,1,1,1,1,5,5,4,5,1,2,3,5,2,5,0,22.0,satisfied +68764,45984,Female,disloyal Customer,22,Business travel,Business,483,5,0,5,2,5,5,5,5,4,4,1,1,3,5,0,19.0,satisfied +68765,22211,Male,Loyal Customer,44,Personal Travel,Eco,533,2,2,2,4,3,2,3,3,2,1,3,4,4,3,35,36.0,neutral or dissatisfied +68766,72618,Male,Loyal Customer,68,Personal Travel,Eco,1102,1,4,1,1,4,1,4,4,1,1,1,3,3,4,102,89.0,neutral or dissatisfied +68767,64399,Male,Loyal Customer,64,Personal Travel,Eco,1172,1,5,2,4,5,2,5,5,3,5,4,4,5,5,26,16.0,neutral or dissatisfied +68768,90319,Male,Loyal Customer,36,Business travel,Business,3376,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +68769,129427,Male,disloyal Customer,46,Business travel,Eco,414,3,3,3,3,4,3,4,4,1,5,3,1,3,4,4,0.0,neutral or dissatisfied +68770,27720,Male,Loyal Customer,50,Business travel,Eco,1448,5,1,5,1,5,5,5,5,2,2,2,5,4,5,7,32.0,satisfied +68771,61030,Male,Loyal Customer,43,Business travel,Business,1546,4,4,2,4,2,5,4,3,3,3,3,3,3,3,0,2.0,satisfied +68772,72398,Female,Loyal Customer,39,Business travel,Business,918,4,4,4,4,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +68773,66452,Male,disloyal Customer,34,Business travel,Eco,1217,3,3,3,3,3,3,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +68774,27691,Male,Loyal Customer,61,Personal Travel,Eco,1107,5,5,5,4,1,5,1,1,3,5,4,3,5,1,0,0.0,satisfied +68775,66842,Male,Loyal Customer,37,Business travel,Eco,331,3,1,3,1,3,2,3,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +68776,68593,Female,Loyal Customer,32,Business travel,Eco Plus,1616,3,2,2,2,3,3,3,3,2,3,1,2,3,3,1,0.0,neutral or dissatisfied +68777,80868,Male,Loyal Customer,67,Personal Travel,Eco,484,1,0,1,4,5,1,5,5,4,2,5,3,4,5,1,1.0,neutral or dissatisfied +68778,91662,Male,disloyal Customer,23,Business travel,Eco,1199,4,4,4,3,3,4,5,3,3,2,4,5,5,3,0,0.0,satisfied +68779,29209,Female,Loyal Customer,38,Business travel,Eco,2311,1,5,5,5,1,1,1,1,1,2,2,4,3,1,5,0.0,neutral or dissatisfied +68780,122115,Female,Loyal Customer,42,Business travel,Business,2467,0,4,0,4,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +68781,60295,Female,Loyal Customer,13,Personal Travel,Eco,783,4,5,4,3,3,4,1,3,5,5,4,3,5,3,0,3.0,neutral or dissatisfied +68782,89361,Female,Loyal Customer,12,Personal Travel,Eco,1541,2,4,3,2,3,3,3,3,4,2,4,4,4,3,23,4.0,neutral or dissatisfied +68783,9439,Female,disloyal Customer,26,Business travel,Business,288,3,4,3,2,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +68784,55635,Female,disloyal Customer,37,Business travel,Business,563,2,2,2,4,5,2,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +68785,55042,Female,Loyal Customer,40,Business travel,Business,1635,2,2,2,2,4,4,4,4,4,4,4,3,4,4,15,0.0,satisfied +68786,29141,Male,Loyal Customer,7,Personal Travel,Eco,937,3,4,3,2,3,3,3,3,2,4,4,5,2,3,0,0.0,neutral or dissatisfied +68787,47471,Male,Loyal Customer,32,Personal Travel,Eco,588,4,5,4,4,4,4,4,4,3,3,4,5,5,4,44,44.0,neutral or dissatisfied +68788,98195,Female,Loyal Customer,62,Business travel,Eco,327,4,1,5,1,5,2,4,4,4,4,4,5,4,5,12,0.0,satisfied +68789,85389,Male,Loyal Customer,46,Business travel,Business,3128,3,3,3,3,4,5,4,3,3,4,5,5,3,3,0,0.0,satisfied +68790,87748,Male,Loyal Customer,37,Business travel,Business,3643,1,1,1,1,4,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +68791,102998,Male,disloyal Customer,32,Business travel,Business,687,4,4,4,5,4,4,4,4,3,3,4,5,5,4,46,27.0,neutral or dissatisfied +68792,4812,Female,Loyal Customer,64,Personal Travel,Eco Plus,438,2,4,5,3,5,5,5,5,5,5,5,5,5,3,14,9.0,neutral or dissatisfied +68793,12053,Female,Loyal Customer,76,Business travel,Business,376,1,1,1,1,2,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +68794,36620,Male,Loyal Customer,50,Business travel,Business,811,5,5,5,5,4,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +68795,69013,Female,Loyal Customer,26,Business travel,Business,1389,4,4,4,4,4,4,4,4,3,2,5,4,5,4,4,0.0,satisfied +68796,14636,Female,Loyal Customer,23,Business travel,Business,363,3,5,5,5,3,3,3,3,2,2,1,1,1,3,0,0.0,neutral or dissatisfied +68797,127350,Female,Loyal Customer,46,Business travel,Eco,107,5,4,4,4,3,4,3,5,5,5,5,2,5,5,0,0.0,satisfied +68798,27010,Female,Loyal Customer,58,Business travel,Eco,954,4,1,1,1,3,4,1,4,4,4,4,2,4,4,0,0.0,satisfied +68799,59959,Female,Loyal Customer,29,Business travel,Business,2429,3,3,3,3,3,3,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +68800,115725,Male,Loyal Customer,47,Business travel,Business,372,2,2,2,2,2,4,5,4,4,5,4,5,4,4,0,2.0,satisfied +68801,126636,Female,Loyal Customer,50,Business travel,Business,602,3,2,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +68802,104780,Male,Loyal Customer,38,Personal Travel,Business,587,4,4,4,3,3,5,4,1,1,4,1,3,1,5,29,18.0,neutral or dissatisfied +68803,39067,Male,Loyal Customer,39,Business travel,Business,3331,5,5,5,5,1,3,1,4,4,4,4,5,4,4,47,35.0,satisfied +68804,34054,Female,Loyal Customer,36,Business travel,Eco,1674,5,5,4,5,5,5,5,5,3,1,4,2,1,5,0,0.0,satisfied +68805,76466,Male,Loyal Customer,24,Business travel,Business,3288,5,5,5,5,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +68806,19828,Female,Loyal Customer,55,Business travel,Eco,654,2,1,4,4,1,3,4,2,2,2,2,3,2,1,43,54.0,neutral or dissatisfied +68807,98019,Male,disloyal Customer,28,Business travel,Business,1014,2,2,2,3,5,2,5,5,3,3,5,4,4,5,33,33.0,neutral or dissatisfied +68808,5231,Female,Loyal Customer,49,Business travel,Business,3843,5,5,5,5,5,4,5,5,5,5,5,3,5,5,6,0.0,satisfied +68809,69729,Female,Loyal Customer,37,Personal Travel,Eco,1372,1,1,1,3,1,4,4,2,1,4,4,4,2,4,231,250.0,neutral or dissatisfied +68810,39300,Male,Loyal Customer,42,Personal Travel,Eco,67,3,1,3,4,5,3,5,5,3,1,3,1,4,5,0,5.0,neutral or dissatisfied +68811,101303,Female,Loyal Customer,50,Business travel,Business,3215,1,1,1,1,5,5,5,5,5,5,5,4,5,4,26,22.0,satisfied +68812,112349,Male,disloyal Customer,24,Business travel,Eco,862,4,4,4,2,4,4,4,4,3,2,5,3,4,4,0,0.0,satisfied +68813,18210,Male,disloyal Customer,25,Business travel,Eco,137,2,0,2,2,1,2,4,1,5,5,3,4,5,1,6,46.0,neutral or dissatisfied +68814,112235,Male,disloyal Customer,29,Business travel,Business,1546,2,2,2,3,5,2,5,5,3,2,5,3,4,5,10,5.0,neutral or dissatisfied +68815,36971,Male,Loyal Customer,45,Business travel,Eco,759,2,3,3,3,2,2,2,2,3,3,5,2,2,2,173,151.0,satisfied +68816,48599,Male,Loyal Customer,19,Personal Travel,Eco,776,5,5,5,4,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +68817,82661,Male,Loyal Customer,15,Personal Travel,Eco,120,2,4,2,3,1,2,1,1,1,4,3,1,2,1,3,0.0,neutral or dissatisfied +68818,55861,Male,Loyal Customer,53,Personal Travel,Eco,419,5,4,5,3,5,5,5,5,1,3,4,2,4,5,0,0.0,satisfied +68819,96343,Female,Loyal Customer,45,Business travel,Business,1609,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +68820,87302,Female,Loyal Customer,21,Personal Travel,Eco,577,2,1,2,3,5,2,5,5,1,3,3,3,3,5,7,0.0,neutral or dissatisfied +68821,34143,Male,Loyal Customer,45,Business travel,Eco,1237,2,4,4,4,2,2,2,2,4,5,2,1,3,2,27,24.0,neutral or dissatisfied +68822,76862,Female,Loyal Customer,42,Business travel,Eco Plus,1262,3,4,4,4,4,3,4,3,3,3,3,3,3,4,7,0.0,neutral or dissatisfied +68823,28102,Male,disloyal Customer,28,Business travel,Eco,859,3,4,4,3,5,4,5,5,4,3,4,5,4,5,0,7.0,neutral or dissatisfied +68824,94100,Female,Loyal Customer,55,Personal Travel,Business,562,3,5,3,3,4,5,5,5,5,3,2,5,5,3,8,8.0,neutral or dissatisfied +68825,114506,Male,Loyal Customer,25,Business travel,Business,2863,0,0,0,1,1,1,3,1,5,5,5,5,5,1,0,0.0,satisfied +68826,63825,Female,Loyal Customer,56,Business travel,Business,1192,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +68827,16169,Female,disloyal Customer,26,Business travel,Eco,277,1,5,1,3,1,1,1,1,5,4,5,5,4,1,7,8.0,neutral or dissatisfied +68828,51209,Male,Loyal Customer,37,Business travel,Eco Plus,158,5,1,1,1,5,5,5,5,4,1,4,2,1,5,0,0.0,satisfied +68829,52661,Male,Loyal Customer,63,Personal Travel,Eco,119,2,5,2,2,5,2,3,5,5,5,4,1,5,5,0,0.0,neutral or dissatisfied +68830,125427,Male,Loyal Customer,75,Business travel,Business,2713,4,4,4,4,3,4,3,5,5,5,5,2,5,3,0,0.0,satisfied +68831,9531,Female,Loyal Customer,45,Business travel,Business,2407,4,4,4,4,2,5,4,4,4,5,4,5,4,4,85,57.0,satisfied +68832,43756,Male,disloyal Customer,28,Business travel,Eco,546,4,5,4,1,5,4,1,5,4,3,3,2,1,5,0,0.0,satisfied +68833,64853,Female,Loyal Customer,50,Business travel,Business,551,2,1,1,1,1,3,4,2,2,2,2,1,2,4,77,59.0,neutral or dissatisfied +68834,123661,Male,disloyal Customer,32,Business travel,Business,214,1,1,1,3,5,1,5,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +68835,55857,Female,Loyal Customer,68,Business travel,Eco Plus,1416,3,4,4,4,1,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +68836,2851,Male,Loyal Customer,40,Business travel,Business,2219,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +68837,88260,Female,Loyal Customer,42,Business travel,Business,2693,4,4,4,4,3,4,4,3,3,3,3,4,3,5,23,15.0,satisfied +68838,77966,Female,disloyal Customer,23,Business travel,Business,332,5,2,4,2,1,4,1,1,4,2,5,4,5,1,7,0.0,satisfied +68839,123294,Female,Loyal Customer,50,Business travel,Business,468,1,5,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +68840,25374,Male,Loyal Customer,42,Business travel,Eco,591,5,5,5,5,5,5,5,5,3,1,3,5,2,5,0,0.0,satisfied +68841,123188,Male,Loyal Customer,52,Personal Travel,Eco,507,2,1,2,3,2,2,2,2,2,2,2,1,3,2,3,14.0,neutral or dissatisfied +68842,7944,Male,Loyal Customer,27,Business travel,Business,3781,3,3,3,3,5,5,5,5,5,4,5,5,5,5,41,42.0,satisfied +68843,93337,Male,Loyal Customer,47,Business travel,Business,836,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +68844,77492,Female,disloyal Customer,24,Business travel,Eco,989,3,3,3,4,2,3,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +68845,45938,Female,Loyal Customer,36,Personal Travel,Eco,913,4,4,4,1,3,4,3,3,5,4,4,4,4,3,6,13.0,neutral or dissatisfied +68846,101902,Female,Loyal Customer,37,Business travel,Business,1591,1,1,1,1,1,1,4,4,4,4,4,4,4,3,0,0.0,satisfied +68847,49129,Male,disloyal Customer,44,Business travel,Eco,109,5,0,5,4,4,5,4,4,2,1,5,5,4,4,5,9.0,satisfied +68848,81648,Male,disloyal Customer,23,Business travel,Eco,907,4,4,4,1,3,4,1,3,3,5,5,5,4,3,78,93.0,neutral or dissatisfied +68849,50775,Female,Loyal Customer,42,Personal Travel,Eco,109,2,4,0,1,3,4,1,2,2,0,2,1,2,5,0,0.0,neutral or dissatisfied +68850,28940,Male,Loyal Customer,37,Business travel,Eco,605,4,3,3,3,4,5,4,4,4,5,4,3,2,4,0,0.0,satisfied +68851,116851,Female,Loyal Customer,59,Business travel,Business,2435,2,2,2,2,5,4,5,5,5,5,5,5,5,4,23,15.0,satisfied +68852,43366,Male,Loyal Customer,50,Personal Travel,Eco,387,1,5,1,5,3,1,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +68853,43753,Female,Loyal Customer,37,Business travel,Business,2277,3,3,3,3,1,3,4,5,5,5,5,5,5,5,0,26.0,satisfied +68854,87521,Male,Loyal Customer,55,Personal Travel,Eco,321,4,3,5,2,2,5,2,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +68855,14495,Male,Loyal Customer,26,Personal Travel,Eco Plus,541,2,5,3,4,2,3,2,2,4,4,5,3,5,2,0,2.0,neutral or dissatisfied +68856,108371,Male,Loyal Customer,15,Personal Travel,Eco,1844,2,5,2,1,2,4,4,3,4,3,4,4,3,4,131,112.0,neutral or dissatisfied +68857,48532,Male,Loyal Customer,52,Business travel,Eco,453,5,2,4,4,5,5,5,5,2,1,3,1,2,5,0,4.0,satisfied +68858,45033,Male,Loyal Customer,42,Business travel,Eco,837,2,2,2,2,2,2,2,2,3,1,3,4,4,2,29,65.0,neutral or dissatisfied +68859,65700,Female,disloyal Customer,45,Business travel,Business,936,2,2,2,1,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +68860,67236,Male,Loyal Customer,49,Personal Travel,Eco,985,2,4,2,3,4,2,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +68861,60839,Female,disloyal Customer,44,Business travel,Business,1754,2,3,3,2,4,2,2,4,4,2,3,3,5,4,0,0.0,neutral or dissatisfied +68862,79439,Male,Loyal Customer,41,Business travel,Business,187,1,2,2,2,4,3,2,2,2,2,1,4,2,1,26,21.0,neutral or dissatisfied +68863,116097,Female,Loyal Customer,50,Personal Travel,Eco,337,4,5,4,1,4,5,5,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +68864,122818,Female,Loyal Customer,68,Personal Travel,Eco,599,2,3,2,4,4,3,4,1,1,2,1,1,1,4,93,89.0,neutral or dissatisfied +68865,50392,Female,Loyal Customer,79,Business travel,Business,3136,2,2,2,2,2,3,4,2,2,2,2,4,2,4,91,78.0,neutral or dissatisfied +68866,98809,Male,Loyal Customer,44,Business travel,Business,2073,1,4,1,1,4,4,4,4,4,4,4,4,4,4,7,5.0,satisfied +68867,105312,Female,disloyal Customer,16,Business travel,Business,738,4,0,4,1,3,4,4,3,3,2,4,3,5,3,37,39.0,satisfied +68868,48575,Male,Loyal Customer,9,Personal Travel,Eco,737,3,4,3,4,5,3,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +68869,41067,Female,Loyal Customer,61,Personal Travel,Business,224,4,3,4,2,3,3,2,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +68870,22637,Male,Loyal Customer,33,Personal Travel,Eco,300,3,4,3,1,3,5,5,3,4,5,5,5,4,5,158,150.0,neutral or dissatisfied +68871,77017,Female,Loyal Customer,52,Business travel,Business,3231,3,3,3,3,5,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +68872,74787,Female,Loyal Customer,49,Business travel,Business,2748,3,3,3,3,3,5,5,5,5,5,5,4,5,5,0,8.0,satisfied +68873,96786,Male,disloyal Customer,24,Business travel,Eco,781,4,4,4,1,4,4,4,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +68874,14077,Female,Loyal Customer,22,Business travel,Business,3103,2,3,3,3,2,2,2,2,1,2,3,1,4,2,2,0.0,neutral or dissatisfied +68875,108262,Female,Loyal Customer,35,Business travel,Business,895,5,5,5,5,4,3,5,5,5,5,5,4,5,3,9,15.0,satisfied +68876,112745,Male,Loyal Customer,30,Business travel,Business,1555,3,2,2,2,3,3,3,3,1,3,3,1,3,3,32,25.0,neutral or dissatisfied +68877,9378,Female,Loyal Customer,42,Personal Travel,Eco,401,3,5,3,3,3,4,4,1,1,3,1,5,1,3,105,96.0,neutral or dissatisfied +68878,94122,Female,Loyal Customer,25,Business travel,Business,248,1,1,1,1,4,4,4,4,4,2,5,5,5,4,2,0.0,satisfied +68879,23962,Male,Loyal Customer,33,Personal Travel,Eco,639,1,2,1,4,3,1,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +68880,117402,Female,Loyal Customer,56,Business travel,Business,3745,3,3,4,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +68881,58573,Female,Loyal Customer,46,Business travel,Business,403,5,5,5,5,3,4,5,4,4,4,4,3,4,3,7,0.0,satisfied +68882,73078,Male,disloyal Customer,39,Business travel,Business,1085,2,2,2,4,2,2,2,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +68883,128563,Male,Loyal Customer,16,Personal Travel,Eco Plus,304,3,1,0,4,4,0,1,4,2,1,4,1,4,4,80,69.0,neutral or dissatisfied +68884,94544,Female,Loyal Customer,57,Business travel,Business,293,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +68885,73293,Female,Loyal Customer,52,Business travel,Business,1197,1,1,1,1,3,4,5,3,3,3,3,5,3,3,18,34.0,satisfied +68886,102190,Female,Loyal Customer,30,Business travel,Eco,197,4,2,2,2,4,3,4,4,2,4,4,2,3,4,47,38.0,neutral or dissatisfied +68887,122578,Female,Loyal Customer,21,Business travel,Business,728,4,4,2,4,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +68888,22061,Female,disloyal Customer,44,Business travel,Eco,321,0,4,0,2,2,0,2,2,4,5,1,3,5,2,0,0.0,satisfied +68889,77592,Male,Loyal Customer,59,Business travel,Business,813,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +68890,109524,Female,Loyal Customer,25,Business travel,Eco,434,4,5,5,5,4,4,5,4,4,5,1,5,3,4,44,34.0,satisfied +68891,26955,Female,Loyal Customer,46,Business travel,Business,2305,1,1,1,1,3,5,4,5,5,5,5,5,5,4,8,3.0,satisfied +68892,5436,Female,Loyal Customer,51,Business travel,Business,265,2,2,5,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +68893,120925,Male,Loyal Customer,42,Business travel,Eco,920,3,4,4,4,3,3,3,3,4,5,3,3,3,3,4,0.0,neutral or dissatisfied +68894,67700,Female,Loyal Customer,47,Business travel,Business,2554,2,2,2,2,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +68895,38867,Female,disloyal Customer,28,Business travel,Eco,1029,4,4,4,4,4,4,1,4,1,2,4,2,4,4,124,113.0,neutral or dissatisfied +68896,68141,Male,Loyal Customer,14,Personal Travel,Eco Plus,868,4,4,4,1,3,4,3,3,3,2,5,1,2,3,0,0.0,satisfied +68897,102213,Male,Loyal Customer,48,Business travel,Eco,236,2,2,2,2,2,2,2,2,2,3,4,4,3,2,40,28.0,neutral or dissatisfied +68898,125373,Female,Loyal Customer,14,Personal Travel,Business,1440,3,4,3,3,3,3,3,3,5,3,3,4,5,3,0,6.0,neutral or dissatisfied +68899,129732,Male,disloyal Customer,22,Business travel,Eco,337,3,0,4,3,5,4,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +68900,112561,Female,Loyal Customer,20,Personal Travel,Eco Plus,819,3,4,3,5,3,3,3,3,3,4,5,1,4,3,4,1.0,neutral or dissatisfied +68901,110345,Female,Loyal Customer,39,Business travel,Business,663,1,1,1,1,4,4,4,5,5,5,4,4,3,4,336,327.0,satisfied +68902,100613,Female,Loyal Customer,60,Personal Travel,Eco,1670,2,0,2,4,1,3,2,5,5,2,5,3,5,4,8,9.0,neutral or dissatisfied +68903,74600,Female,Loyal Customer,58,Business travel,Business,1431,5,5,5,5,2,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +68904,72969,Female,Loyal Customer,37,Business travel,Eco,1096,3,3,3,3,3,3,3,3,3,4,2,4,3,3,0,0.0,neutral or dissatisfied +68905,46632,Female,Loyal Customer,55,Business travel,Eco,125,4,4,4,4,2,1,4,4,4,4,4,5,4,5,0,0.0,satisfied +68906,94493,Female,Loyal Customer,38,Business travel,Eco,192,3,3,3,3,3,3,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +68907,14573,Female,Loyal Customer,39,Business travel,Business,2124,3,2,2,2,1,2,3,3,3,3,3,4,3,2,40,56.0,neutral or dissatisfied +68908,29313,Female,Loyal Customer,66,Personal Travel,Eco,569,3,5,3,2,5,4,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +68909,50640,Female,Loyal Customer,7,Personal Travel,Eco,156,1,4,1,5,1,2,2,5,3,4,4,2,3,2,134,121.0,neutral or dissatisfied +68910,127804,Female,disloyal Customer,28,Business travel,Business,1262,3,3,3,4,4,3,4,4,3,2,5,3,5,4,0,13.0,neutral or dissatisfied +68911,8467,Male,Loyal Customer,53,Business travel,Business,1379,2,2,2,2,2,5,5,5,5,5,5,4,5,3,14,5.0,satisfied +68912,93568,Male,disloyal Customer,43,Business travel,Business,159,5,5,5,2,4,5,4,4,4,3,4,3,5,4,31,31.0,satisfied +68913,8522,Male,Loyal Customer,70,Personal Travel,Eco,737,3,5,3,2,2,3,2,2,5,2,5,4,4,2,0,,neutral or dissatisfied +68914,35015,Female,Loyal Customer,21,Business travel,Business,740,3,3,3,3,5,5,5,5,2,1,5,4,3,5,0,0.0,satisfied +68915,107019,Male,Loyal Customer,58,Business travel,Business,2813,1,1,1,1,2,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +68916,36648,Female,Loyal Customer,38,Personal Travel,Eco,1249,2,2,2,3,1,2,1,1,4,2,3,4,3,1,5,18.0,neutral or dissatisfied +68917,62320,Male,Loyal Customer,32,Personal Travel,Eco,414,2,3,1,3,2,1,2,2,1,2,3,4,4,2,3,0.0,neutral or dissatisfied +68918,99237,Female,Loyal Customer,57,Business travel,Eco,141,4,3,3,3,5,5,3,4,4,4,4,2,4,2,0,0.0,satisfied +68919,110361,Female,Loyal Customer,43,Business travel,Business,2473,2,4,4,4,2,2,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +68920,10188,Male,Loyal Customer,43,Business travel,Business,295,4,4,4,4,2,4,4,5,5,5,5,4,5,5,3,0.0,satisfied +68921,59132,Male,Loyal Customer,22,Personal Travel,Eco,1846,1,0,1,4,2,1,2,2,2,4,3,1,3,2,68,78.0,neutral or dissatisfied +68922,38437,Male,Loyal Customer,28,Business travel,Business,2277,5,5,5,5,4,4,4,4,1,2,3,3,5,4,0,0.0,satisfied +68923,63657,Male,Loyal Customer,32,Business travel,Business,2405,5,1,5,5,2,2,2,2,4,2,5,5,4,2,4,0.0,satisfied +68924,112723,Male,Loyal Customer,63,Personal Travel,Eco,697,1,4,2,1,1,2,1,1,4,4,5,4,5,1,29,13.0,neutral or dissatisfied +68925,43964,Male,Loyal Customer,40,Business travel,Eco,596,5,5,4,5,5,4,5,5,3,1,2,4,4,5,0,0.0,satisfied +68926,81396,Female,Loyal Customer,48,Personal Travel,Eco,874,3,2,3,2,3,2,2,3,5,3,3,2,4,2,159,156.0,neutral or dissatisfied +68927,22440,Male,Loyal Customer,26,Personal Travel,Eco,143,3,4,0,5,3,0,3,3,3,1,4,2,3,3,64,62.0,neutral or dissatisfied +68928,107178,Female,disloyal Customer,38,Business travel,Eco,402,2,2,2,3,5,2,5,5,1,3,4,3,4,5,67,64.0,neutral or dissatisfied +68929,8695,Male,Loyal Customer,39,Business travel,Eco,181,5,5,5,5,5,5,5,5,3,4,2,3,3,5,0,0.0,satisfied +68930,104460,Female,disloyal Customer,57,Business travel,Eco,1123,4,4,4,3,2,4,2,2,4,5,3,2,3,2,0,0.0,neutral or dissatisfied +68931,69627,Male,Loyal Customer,34,Business travel,Business,3999,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +68932,29802,Male,Loyal Customer,38,Business travel,Eco,548,5,2,2,2,5,5,5,5,1,3,3,4,1,5,1,0.0,satisfied +68933,100952,Male,Loyal Customer,35,Business travel,Business,2033,5,5,5,5,2,4,5,3,3,3,3,5,3,4,0,6.0,satisfied +68934,40042,Female,Loyal Customer,25,Business travel,Business,2075,5,5,4,5,2,2,2,2,2,3,5,2,2,2,0,1.0,satisfied +68935,10098,Male,Loyal Customer,20,Business travel,Business,2043,3,3,3,3,3,3,3,3,1,4,2,1,3,3,0,3.0,neutral or dissatisfied +68936,84999,Female,Loyal Customer,41,Business travel,Business,1590,5,5,5,5,4,3,5,3,3,4,3,3,3,5,16,4.0,satisfied +68937,90741,Female,Loyal Customer,40,Business travel,Business,404,5,5,5,5,5,5,4,2,2,2,2,3,2,4,43,44.0,satisfied +68938,71204,Female,Loyal Customer,56,Business travel,Business,3663,3,3,3,3,3,4,5,4,4,4,4,3,4,5,88,84.0,satisfied +68939,10387,Female,Loyal Customer,45,Business travel,Business,316,5,2,5,5,3,4,5,4,4,4,4,5,4,4,58,55.0,satisfied +68940,123962,Male,disloyal Customer,36,Business travel,Business,184,2,2,2,2,3,2,3,3,3,3,5,3,5,3,0,0.0,neutral or dissatisfied +68941,53179,Male,disloyal Customer,23,Business travel,Eco,612,5,0,5,1,2,5,2,2,3,3,4,2,2,2,0,0.0,satisfied +68942,8452,Female,Loyal Customer,39,Business travel,Business,1379,4,4,4,4,3,4,5,4,4,4,4,4,4,4,11,0.0,satisfied +68943,45374,Male,Loyal Customer,58,Business travel,Eco Plus,188,4,2,2,2,4,4,4,4,5,2,4,3,1,4,38,39.0,satisfied +68944,14082,Female,disloyal Customer,50,Business travel,Eco,201,3,0,3,1,5,3,5,5,5,2,5,2,4,5,3,0.0,neutral or dissatisfied +68945,60753,Male,Loyal Customer,39,Business travel,Business,804,5,3,5,5,3,5,5,1,1,2,1,4,1,3,4,0.0,satisfied +68946,22704,Female,Loyal Customer,41,Personal Travel,Eco,589,3,1,4,4,5,4,5,5,3,4,3,2,3,5,4,8.0,neutral or dissatisfied +68947,89519,Male,Loyal Customer,44,Personal Travel,Business,950,1,3,1,3,5,3,3,4,4,1,4,4,4,1,0,67.0,neutral or dissatisfied +68948,81586,Female,Loyal Customer,43,Business travel,Business,334,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +68949,83959,Female,disloyal Customer,24,Business travel,Eco,304,3,0,3,3,4,3,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +68950,108047,Male,Loyal Customer,42,Business travel,Eco,591,2,3,3,3,2,2,2,2,1,4,3,1,3,2,0,12.0,neutral or dissatisfied +68951,124570,Male,Loyal Customer,27,Business travel,Business,500,4,5,4,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +68952,42153,Male,Loyal Customer,60,Personal Travel,Business,817,2,3,2,4,4,3,3,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +68953,127672,Male,Loyal Customer,58,Business travel,Business,2153,2,1,4,4,4,2,4,2,2,2,2,4,2,2,2,15.0,neutral or dissatisfied +68954,43674,Female,Loyal Customer,67,Personal Travel,Eco,695,1,4,1,3,5,5,4,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +68955,40932,Female,Loyal Customer,25,Business travel,Eco Plus,599,2,4,4,4,2,2,3,2,1,5,4,4,4,2,37,37.0,neutral or dissatisfied +68956,57292,Female,Loyal Customer,32,Personal Travel,Eco Plus,628,2,4,3,4,5,3,5,5,5,4,4,5,5,5,5,0.0,neutral or dissatisfied +68957,92707,Female,Loyal Customer,30,Business travel,Business,2153,2,2,2,2,4,4,4,4,3,4,5,5,5,4,14,20.0,satisfied +68958,89168,Male,Loyal Customer,29,Personal Travel,Eco,1947,3,4,3,2,3,3,3,3,5,2,3,4,4,3,0,0.0,neutral or dissatisfied +68959,112214,Male,Loyal Customer,54,Business travel,Business,2625,2,2,2,2,4,4,4,4,4,4,4,4,4,3,29,22.0,satisfied +68960,48488,Female,Loyal Customer,38,Business travel,Eco,844,2,5,5,5,2,2,2,2,1,1,5,2,4,2,0,0.0,satisfied +68961,35587,Female,Loyal Customer,33,Business travel,Eco Plus,1028,4,3,3,3,4,4,4,4,1,3,5,5,4,4,0,0.0,satisfied +68962,29355,Male,Loyal Customer,27,Business travel,Eco,2541,0,0,0,5,0,5,5,3,5,3,1,5,4,5,0,21.0,satisfied +68963,13691,Male,Loyal Customer,23,Business travel,Business,1759,3,3,3,3,4,4,4,4,2,3,5,3,3,4,0,0.0,satisfied +68964,13087,Female,Loyal Customer,33,Business travel,Business,3724,3,3,3,3,4,1,2,2,2,2,2,2,2,3,0,0.0,satisfied +68965,8511,Male,disloyal Customer,38,Business travel,Eco,862,2,2,2,3,2,2,2,2,1,4,4,2,3,2,29,3.0,neutral or dissatisfied +68966,128634,Male,Loyal Customer,33,Personal Travel,Eco,679,2,5,2,3,3,2,3,3,3,5,3,3,2,3,0,0.0,neutral or dissatisfied +68967,1705,Male,disloyal Customer,24,Business travel,Business,364,4,2,4,5,4,4,2,4,3,4,4,4,5,4,0,0.0,satisfied +68968,70193,Female,Loyal Customer,17,Business travel,Business,258,2,3,3,3,2,2,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +68969,101847,Female,disloyal Customer,27,Business travel,Business,519,4,4,4,3,3,4,3,3,5,5,4,3,5,3,42,48.0,satisfied +68970,11853,Male,disloyal Customer,22,Business travel,Business,1042,4,0,4,1,1,4,2,1,5,3,4,3,4,1,0,0.0,satisfied +68971,115478,Male,Loyal Customer,56,Business travel,Eco,337,1,4,4,4,1,1,1,1,2,3,3,4,3,1,63,55.0,neutral or dissatisfied +68972,92225,Female,Loyal Customer,20,Personal Travel,Eco,2079,3,0,3,3,2,3,2,2,4,5,5,5,5,2,9,0.0,neutral or dissatisfied +68973,34451,Female,Loyal Customer,63,Personal Travel,Eco,228,4,5,4,1,1,1,3,4,4,4,4,1,4,3,0,0.0,satisfied +68974,97891,Female,disloyal Customer,26,Business travel,Eco,793,2,2,2,4,4,2,4,4,2,1,3,3,3,4,29,30.0,neutral or dissatisfied +68975,19326,Male,disloyal Customer,28,Business travel,Eco,694,5,4,4,5,5,4,5,5,3,4,4,2,3,5,0,0.0,satisfied +68976,86413,Female,Loyal Customer,21,Business travel,Business,762,3,3,3,3,4,5,4,4,4,5,5,4,4,4,19,0.0,satisfied +68977,58828,Male,Loyal Customer,55,Business travel,Business,1182,2,2,2,2,3,5,5,3,3,4,3,4,3,4,31,14.0,satisfied +68978,79460,Female,Loyal Customer,50,Business travel,Business,3820,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +68979,79301,Male,disloyal Customer,27,Business travel,Business,2248,2,3,3,4,4,3,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +68980,53467,Male,Loyal Customer,42,Business travel,Business,2253,3,1,1,1,3,3,3,4,2,2,4,3,2,3,152,151.0,neutral or dissatisfied +68981,46231,Male,disloyal Customer,18,Business travel,Eco,679,2,2,2,2,2,2,2,2,3,4,2,3,5,2,12,14.0,neutral or dissatisfied +68982,100990,Male,Loyal Customer,46,Business travel,Business,3346,3,1,4,1,2,3,3,3,3,3,3,3,3,3,23,17.0,neutral or dissatisfied +68983,97592,Male,Loyal Customer,47,Business travel,Business,2263,2,2,2,2,4,5,5,4,4,5,4,4,4,3,24,6.0,satisfied +68984,126858,Female,Loyal Customer,67,Personal Travel,Eco,2296,4,5,4,1,3,4,4,5,5,4,5,3,5,5,13,23.0,neutral or dissatisfied +68985,27564,Female,Loyal Customer,24,Personal Travel,Eco,1050,4,4,4,3,2,4,2,2,3,2,4,2,3,2,0,0.0,satisfied +68986,48184,Female,Loyal Customer,31,Business travel,Eco,236,4,3,3,3,4,4,4,4,1,5,3,2,3,4,0,0.0,neutral or dissatisfied +68987,77087,Male,Loyal Customer,60,Business travel,Business,991,3,3,5,3,3,4,5,2,2,2,2,5,2,3,2,0.0,satisfied +68988,62707,Male,Loyal Customer,34,Business travel,Business,2447,3,3,2,3,4,4,4,4,2,4,5,4,5,4,0,0.0,satisfied +68989,65567,Female,Loyal Customer,35,Business travel,Business,237,2,4,4,4,5,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +68990,120864,Male,Loyal Customer,28,Business travel,Business,2219,1,1,1,1,4,4,4,4,3,4,4,3,5,4,18,1.0,satisfied +68991,108649,Male,Loyal Customer,39,Business travel,Business,1747,1,1,1,1,2,3,5,5,5,5,5,3,5,4,34,36.0,satisfied +68992,96168,Female,Loyal Customer,43,Business travel,Business,1770,5,5,5,5,5,5,4,4,4,4,4,4,4,3,17,8.0,satisfied +68993,43941,Male,Loyal Customer,43,Personal Travel,Eco Plus,153,2,5,2,3,4,2,4,4,5,4,5,4,5,4,19,14.0,neutral or dissatisfied +68994,30813,Female,Loyal Customer,7,Personal Travel,Eco Plus,1199,2,4,2,2,3,2,3,3,3,3,4,4,2,3,57,51.0,neutral or dissatisfied +68995,79547,Female,disloyal Customer,42,Business travel,Business,712,5,5,5,3,3,5,5,3,5,5,4,3,5,3,0,0.0,satisfied +68996,103055,Male,Loyal Customer,72,Business travel,Business,3528,2,5,5,5,3,2,3,2,2,2,2,4,2,3,29,19.0,neutral or dissatisfied +68997,76700,Female,Loyal Customer,31,Personal Travel,Eco,534,3,4,3,3,4,3,4,4,5,4,4,4,5,4,0,31.0,neutral or dissatisfied +68998,22081,Female,Loyal Customer,30,Business travel,Business,3292,5,5,5,5,4,4,4,4,3,2,2,2,1,4,4,0.0,satisfied +68999,115640,Male,Loyal Customer,39,Business travel,Business,3216,3,1,1,1,3,4,4,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +69000,45658,Male,Loyal Customer,60,Business travel,Eco Plus,260,4,2,2,2,3,4,3,3,2,2,2,1,4,3,0,3.0,satisfied +69001,115447,Female,Loyal Customer,34,Business travel,Business,447,5,5,5,5,3,5,5,5,5,5,5,3,5,5,61,55.0,satisfied +69002,107564,Male,Loyal Customer,20,Personal Travel,Eco,1521,1,2,1,2,4,1,4,4,4,4,2,4,3,4,3,45.0,neutral or dissatisfied +69003,104652,Female,Loyal Customer,58,Personal Travel,Eco,1754,4,3,4,4,4,3,2,3,3,4,1,1,3,4,0,0.0,neutral or dissatisfied +69004,62155,Male,Loyal Customer,40,Business travel,Business,2565,1,1,1,1,4,3,4,3,3,2,3,4,3,5,0,0.0,satisfied +69005,31703,Female,Loyal Customer,26,Personal Travel,Eco,853,2,4,2,2,1,2,1,1,3,5,4,3,4,1,24,12.0,neutral or dissatisfied +69006,73692,Male,Loyal Customer,46,Business travel,Business,204,1,1,5,1,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +69007,122512,Male,Loyal Customer,59,Personal Travel,Eco,930,2,5,2,3,2,2,2,2,3,5,4,5,5,2,10,0.0,neutral or dissatisfied +69008,102759,Female,Loyal Customer,50,Business travel,Business,1618,1,0,0,4,5,3,4,3,3,0,4,3,3,4,22,2.0,neutral or dissatisfied +69009,20164,Female,Loyal Customer,22,Business travel,Business,2577,3,4,4,4,3,3,3,3,1,1,3,2,2,3,15,66.0,neutral or dissatisfied +69010,18375,Male,Loyal Customer,41,Personal Travel,Eco Plus,169,5,4,5,1,3,5,3,3,3,3,5,3,4,3,0,0.0,satisfied +69011,47075,Male,Loyal Customer,7,Personal Travel,Eco,639,3,5,3,2,3,3,3,3,3,5,5,3,4,3,42,29.0,neutral or dissatisfied +69012,14665,Male,Loyal Customer,41,Business travel,Business,2601,3,3,3,3,5,4,4,4,4,4,4,3,4,5,12,23.0,satisfied +69013,55482,Male,Loyal Customer,59,Business travel,Business,2434,1,1,1,1,2,5,4,2,2,2,2,5,2,5,0,4.0,satisfied +69014,36305,Female,disloyal Customer,24,Business travel,Eco,395,4,0,4,5,2,4,2,2,1,3,4,3,4,2,0,10.0,neutral or dissatisfied +69015,7025,Female,Loyal Customer,67,Personal Travel,Eco,436,3,4,3,2,3,5,5,1,1,3,1,5,1,3,54,55.0,neutral or dissatisfied +69016,121411,Male,Loyal Customer,52,Business travel,Eco,257,3,4,4,4,3,3,3,3,4,4,4,3,4,3,0,3.0,neutral or dissatisfied +69017,85812,Female,Loyal Customer,55,Personal Travel,Eco,666,5,4,5,1,3,4,4,4,4,5,4,3,4,5,8,2.0,satisfied +69018,123035,Female,Loyal Customer,39,Business travel,Business,2675,1,1,1,1,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +69019,41618,Female,Loyal Customer,8,Business travel,Eco Plus,1504,0,3,0,1,3,0,3,3,3,1,1,5,4,3,0,0.0,satisfied +69020,68331,Female,Loyal Customer,70,Personal Travel,Eco,2165,3,4,4,3,2,3,5,5,5,4,5,5,5,4,22,31.0,neutral or dissatisfied +69021,10405,Female,Loyal Customer,58,Business travel,Business,2182,4,1,4,4,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +69022,81920,Male,disloyal Customer,20,Business travel,Business,1576,3,4,3,4,5,3,4,5,2,3,4,4,3,5,0,5.0,neutral or dissatisfied +69023,46549,Male,Loyal Customer,60,Business travel,Business,125,1,1,4,1,1,2,1,5,5,5,4,2,5,3,18,19.0,satisfied +69024,27213,Female,Loyal Customer,24,Personal Travel,Eco Plus,2554,3,4,3,2,1,3,1,1,3,2,3,3,5,1,2,0.0,neutral or dissatisfied +69025,50254,Male,disloyal Customer,50,Business travel,Eco,109,2,2,2,4,5,2,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +69026,22578,Male,disloyal Customer,26,Business travel,Business,223,2,0,2,3,4,2,3,4,1,2,3,5,3,4,110,96.0,neutral or dissatisfied +69027,15154,Female,Loyal Customer,65,Personal Travel,Eco,1042,2,4,2,2,4,5,4,2,2,2,2,5,2,5,111,86.0,neutral or dissatisfied +69028,80562,Female,Loyal Customer,54,Business travel,Business,1747,2,3,3,3,4,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +69029,115264,Male,disloyal Customer,24,Business travel,Business,325,5,0,5,3,1,5,1,1,4,4,4,3,5,1,0,4.0,satisfied +69030,40604,Female,Loyal Customer,51,Personal Travel,Eco,391,4,5,2,2,4,5,5,5,5,2,5,3,5,5,0,0.0,satisfied +69031,94946,Male,disloyal Customer,35,Business travel,Eco,187,3,4,3,4,1,3,1,1,3,4,3,2,3,1,1,0.0,neutral or dissatisfied +69032,126841,Male,disloyal Customer,9,Business travel,Eco,1493,1,1,1,4,5,1,5,5,3,5,4,2,3,5,0,0.0,neutral or dissatisfied +69033,20947,Female,Loyal Customer,51,Business travel,Eco,689,3,3,3,3,4,5,3,3,3,3,3,2,3,1,0,0.0,satisfied +69034,33424,Male,disloyal Customer,14,Business travel,Eco,2409,3,2,2,3,3,3,3,3,4,1,2,1,4,3,57,44.0,neutral or dissatisfied +69035,124806,Female,Loyal Customer,38,Business travel,Business,2290,0,0,0,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +69036,114347,Female,Loyal Customer,25,Personal Travel,Eco,862,2,4,2,5,4,2,4,4,5,2,5,5,5,4,5,0.0,neutral or dissatisfied +69037,105064,Male,Loyal Customer,43,Business travel,Business,3222,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +69038,63619,Male,disloyal Customer,39,Business travel,Eco,1040,3,3,3,2,2,3,3,2,5,2,5,4,2,2,0,0.0,neutral or dissatisfied +69039,110824,Male,Loyal Customer,36,Personal Travel,Eco,997,1,5,1,3,1,1,1,1,4,3,4,3,5,1,0,4.0,neutral or dissatisfied +69040,40262,Female,disloyal Customer,15,Business travel,Eco,358,3,5,3,3,2,3,2,2,2,2,1,3,1,2,48,,neutral or dissatisfied +69041,13180,Male,Loyal Customer,57,Business travel,Business,419,1,1,1,1,1,2,1,2,2,2,2,5,2,1,0,3.0,satisfied +69042,86949,Male,Loyal Customer,41,Business travel,Business,907,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +69043,29060,Male,Loyal Customer,49,Personal Travel,Eco,954,1,5,1,3,1,1,1,1,1,2,4,1,5,1,0,0.0,neutral or dissatisfied +69044,121835,Male,Loyal Customer,56,Business travel,Business,449,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +69045,122505,Female,Loyal Customer,21,Business travel,Business,3041,3,3,3,3,2,2,2,2,3,4,5,4,4,2,2,36.0,satisfied +69046,27162,Male,Loyal Customer,68,Business travel,Eco,1201,4,1,1,1,4,4,4,5,1,2,3,4,1,4,4,0.0,neutral or dissatisfied +69047,13109,Male,Loyal Customer,35,Business travel,Business,2192,2,2,2,2,4,5,1,4,4,4,4,4,4,4,18,3.0,satisfied +69048,88842,Female,Loyal Customer,16,Personal Travel,Eco Plus,404,2,2,2,4,5,2,5,5,3,2,3,4,4,5,16,14.0,neutral or dissatisfied +69049,93002,Male,Loyal Customer,37,Business travel,Business,1524,5,5,5,5,3,4,4,4,4,4,4,5,4,3,23,11.0,satisfied +69050,61748,Female,Loyal Customer,54,Personal Travel,Eco,1303,0,5,0,1,4,4,5,2,2,0,4,3,2,3,25,41.0,satisfied +69051,26990,Female,Loyal Customer,30,Business travel,Business,3166,4,4,4,4,5,5,5,5,5,2,4,4,3,5,0,0.0,satisfied +69052,28247,Male,Loyal Customer,40,Business travel,Business,1542,2,4,4,4,2,3,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +69053,48718,Female,Loyal Customer,57,Business travel,Business,86,0,5,0,4,4,4,4,1,1,1,1,3,1,3,20,28.0,satisfied +69054,95437,Female,Loyal Customer,41,Business travel,Business,441,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +69055,103550,Female,Loyal Customer,69,Personal Travel,Eco,738,2,5,2,4,4,4,5,3,3,2,5,4,3,3,4,0.0,neutral or dissatisfied +69056,85933,Male,disloyal Customer,43,Business travel,Business,554,2,1,1,2,4,2,5,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +69057,55092,Female,disloyal Customer,73,Business travel,Eco,135,2,4,2,4,1,2,1,1,2,3,4,2,4,1,119,115.0,neutral or dissatisfied +69058,56781,Male,Loyal Customer,29,Personal Travel,Eco Plus,1068,1,3,1,1,4,1,4,4,2,4,3,5,3,4,34,44.0,neutral or dissatisfied +69059,95060,Female,Loyal Customer,47,Personal Travel,Eco,319,3,3,1,1,5,4,2,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +69060,85634,Female,Loyal Customer,43,Personal Travel,Eco,259,2,3,2,1,1,1,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +69061,117078,Female,Loyal Customer,59,Business travel,Business,1672,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +69062,119473,Male,Loyal Customer,60,Business travel,Business,3183,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +69063,69254,Male,Loyal Customer,59,Business travel,Business,2069,3,3,3,3,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +69064,81444,Female,Loyal Customer,28,Business travel,Business,528,5,5,5,5,2,2,2,2,3,4,4,5,4,2,0,1.0,satisfied +69065,101638,Male,disloyal Customer,23,Business travel,Eco,888,4,5,5,3,2,5,2,2,5,2,5,3,5,2,5,6.0,satisfied +69066,84626,Female,Loyal Customer,58,Personal Travel,Eco,669,1,4,1,3,4,4,4,1,1,1,1,3,1,4,27,14.0,neutral or dissatisfied +69067,86520,Male,Loyal Customer,32,Personal Travel,Eco,762,1,3,1,2,5,1,5,5,1,3,3,4,3,5,11,11.0,neutral or dissatisfied +69068,1749,Male,Loyal Customer,35,Personal Travel,Eco,364,3,2,3,3,4,3,4,4,4,2,4,4,3,4,0,4.0,neutral or dissatisfied +69069,50199,Female,disloyal Customer,19,Business travel,Eco,190,3,2,3,4,3,3,3,3,2,1,3,3,3,3,87,77.0,neutral or dissatisfied +69070,24421,Female,Loyal Customer,38,Business travel,Business,634,3,3,3,3,3,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +69071,118094,Male,disloyal Customer,24,Business travel,Eco,1036,5,5,5,4,5,5,5,5,5,4,4,4,4,5,27,16.0,satisfied +69072,22280,Male,Loyal Customer,59,Business travel,Eco,83,4,3,3,3,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +69073,109047,Female,disloyal Customer,23,Business travel,Eco,994,5,5,5,1,1,5,1,1,4,2,4,3,5,1,0,0.0,satisfied +69074,36464,Female,Loyal Customer,52,Personal Travel,Eco,867,2,4,2,5,5,4,4,5,5,2,5,3,5,4,5,7.0,neutral or dissatisfied +69075,105214,Male,Loyal Customer,47,Business travel,Business,1649,4,4,3,4,5,5,4,2,2,2,2,4,2,3,5,0.0,satisfied +69076,75675,Male,disloyal Customer,39,Business travel,Business,813,1,1,1,2,5,1,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +69077,110009,Female,Loyal Customer,54,Business travel,Business,2710,1,1,1,1,3,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +69078,84664,Male,Loyal Customer,46,Business travel,Business,2182,3,3,3,3,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +69079,70014,Male,Loyal Customer,21,Personal Travel,Eco Plus,236,3,5,3,2,5,3,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +69080,9875,Male,Loyal Customer,58,Business travel,Business,357,1,1,1,1,3,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +69081,8030,Female,disloyal Customer,18,Business travel,Eco,530,0,2,0,4,3,0,5,3,5,2,5,5,5,3,5,4.0,satisfied +69082,74106,Female,Loyal Customer,40,Business travel,Business,2707,5,5,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +69083,108001,Female,Loyal Customer,44,Personal Travel,Eco,271,4,4,3,3,1,3,3,3,3,3,3,1,3,4,16,15.0,neutral or dissatisfied +69084,100929,Male,Loyal Customer,42,Personal Travel,Eco,838,2,1,2,2,3,2,3,3,4,2,3,4,3,3,10,0.0,neutral or dissatisfied +69085,6508,Male,disloyal Customer,45,Business travel,Business,599,4,3,3,3,4,4,5,4,4,3,5,5,4,4,8,1.0,neutral or dissatisfied +69086,72891,Female,disloyal Customer,21,Business travel,Eco,1096,3,3,3,4,5,3,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +69087,39280,Male,Loyal Customer,41,Business travel,Business,3881,3,3,3,3,5,1,2,5,5,5,4,2,5,5,14,0.0,satisfied +69088,30130,Female,Loyal Customer,12,Personal Travel,Eco,31,3,4,3,4,1,3,1,1,1,1,2,5,1,1,12,8.0,neutral or dissatisfied +69089,62683,Female,Loyal Customer,46,Business travel,Eco Plus,1846,2,4,4,4,1,2,3,2,2,2,2,2,2,3,1,28.0,neutral or dissatisfied +69090,55067,Male,disloyal Customer,31,Business travel,Eco,1608,1,1,1,2,4,1,4,4,3,2,1,4,2,4,49,49.0,neutral or dissatisfied +69091,25591,Male,Loyal Customer,42,Personal Travel,Eco,696,0,5,0,2,3,0,3,3,3,4,4,3,5,3,10,0.0,satisfied +69092,3037,Male,Loyal Customer,51,Business travel,Business,3537,3,5,5,5,4,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +69093,120720,Female,Loyal Customer,40,Business travel,Eco,90,4,2,2,2,4,4,4,4,2,4,4,3,3,4,0,0.0,neutral or dissatisfied +69094,85371,Male,disloyal Customer,24,Business travel,Business,214,4,2,4,4,1,4,1,1,4,5,4,5,4,1,0,0.0,satisfied +69095,115896,Female,Loyal Customer,24,Business travel,Business,2708,0,0,0,3,3,3,3,3,2,3,1,5,2,3,0,0.0,satisfied +69096,76850,Male,Loyal Customer,80,Business travel,Business,3005,3,5,5,5,1,4,4,3,3,3,3,4,3,2,6,9.0,neutral or dissatisfied +69097,23678,Female,Loyal Customer,77,Business travel,Business,251,1,1,1,1,4,4,3,3,3,4,3,5,3,1,0,0.0,satisfied +69098,53900,Female,Loyal Customer,13,Personal Travel,Eco,191,2,5,0,5,4,0,4,4,3,5,5,4,5,4,5,0.0,neutral or dissatisfied +69099,1116,Male,Loyal Customer,59,Personal Travel,Eco,229,3,5,3,1,1,3,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +69100,42510,Male,Loyal Customer,47,Business travel,Business,1384,1,1,1,1,3,4,5,5,5,5,5,4,5,4,0,11.0,satisfied +69101,125986,Male,Loyal Customer,29,Personal Travel,Business,650,3,1,3,2,3,3,2,3,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +69102,16299,Male,Loyal Customer,70,Personal Travel,Eco Plus,748,1,5,1,3,1,1,1,1,1,5,4,2,2,1,0,7.0,neutral or dissatisfied +69103,95519,Female,Loyal Customer,38,Business travel,Eco Plus,319,1,5,5,5,1,1,1,1,4,1,3,3,4,1,0,10.0,neutral or dissatisfied +69104,120136,Male,disloyal Customer,25,Business travel,Business,1475,4,5,4,4,4,4,4,4,3,2,4,4,4,4,1,0.0,satisfied +69105,29820,Female,Loyal Customer,32,Business travel,Business,571,2,2,2,2,4,4,4,4,5,4,1,3,4,4,12,4.0,satisfied +69106,96656,Male,Loyal Customer,39,Personal Travel,Eco,937,2,4,2,3,5,2,4,5,2,4,3,2,4,5,3,0.0,neutral or dissatisfied +69107,62059,Male,Loyal Customer,70,Personal Travel,Eco,2475,4,3,4,3,1,4,1,1,2,1,5,4,1,1,0,0.0,neutral or dissatisfied +69108,86793,Female,Loyal Customer,55,Business travel,Business,3252,5,5,5,5,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +69109,94450,Female,Loyal Customer,56,Business travel,Business,2745,0,5,0,4,5,5,4,5,5,5,5,4,5,5,24,19.0,satisfied +69110,25352,Female,Loyal Customer,41,Business travel,Business,2080,2,2,2,2,4,4,4,3,5,4,5,4,5,4,276,298.0,satisfied +69111,80787,Male,disloyal Customer,28,Business travel,Business,692,5,5,5,1,2,5,2,2,3,5,4,3,5,2,0,0.0,satisfied +69112,54047,Male,disloyal Customer,27,Business travel,Eco,1416,1,2,2,1,3,1,3,3,4,5,3,1,5,3,0,0.0,neutral or dissatisfied +69113,122557,Male,Loyal Customer,24,Personal Travel,Eco,500,4,3,4,3,1,4,1,1,2,1,4,2,3,1,0,0.0,neutral or dissatisfied +69114,127774,Male,Loyal Customer,36,Personal Travel,Eco Plus,601,5,4,5,1,5,5,5,5,5,5,2,2,3,5,0,0.0,satisfied +69115,103025,Male,disloyal Customer,24,Business travel,Eco,546,1,2,1,4,2,1,2,2,4,5,3,3,4,2,60,52.0,neutral or dissatisfied +69116,17676,Female,Loyal Customer,28,Personal Travel,Eco,282,2,5,2,5,2,2,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +69117,96260,Female,Loyal Customer,58,Personal Travel,Eco,490,3,5,3,5,1,2,2,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +69118,48649,Male,Loyal Customer,63,Business travel,Business,190,4,4,4,4,5,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +69119,7060,Male,Loyal Customer,45,Business travel,Business,3173,4,4,4,4,2,5,4,3,3,4,5,4,3,5,35,76.0,satisfied +69120,127889,Male,Loyal Customer,23,Business travel,Business,1671,1,1,1,1,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +69121,128731,Female,disloyal Customer,20,Personal Travel,Eco,1504,2,5,2,1,5,2,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +69122,84110,Female,Loyal Customer,41,Business travel,Business,1900,1,1,1,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +69123,78709,Female,Loyal Customer,11,Personal Travel,Business,554,2,5,2,5,4,2,4,4,4,3,5,3,4,4,0,2.0,neutral or dissatisfied +69124,27578,Female,Loyal Customer,9,Personal Travel,Eco,679,0,3,0,3,3,0,3,3,3,4,3,2,3,3,0,1.0,satisfied +69125,117532,Female,Loyal Customer,31,Business travel,Business,3331,2,2,2,2,5,4,5,5,4,5,5,5,4,5,53,51.0,satisfied +69126,2719,Female,Loyal Customer,8,Business travel,Business,2048,5,5,5,5,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +69127,41700,Female,Loyal Customer,33,Business travel,Eco Plus,347,4,1,1,1,4,4,4,4,3,2,2,2,2,4,0,0.0,satisfied +69128,70692,Female,Loyal Customer,57,Business travel,Business,2403,1,1,1,1,4,4,5,5,5,5,5,4,5,3,1,0.0,satisfied +69129,49430,Male,Loyal Customer,47,Business travel,Business,3239,0,3,0,1,5,3,1,4,4,4,4,3,4,3,0,10.0,satisfied +69130,15644,Female,Loyal Customer,8,Personal Travel,Eco Plus,229,3,5,3,4,4,3,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +69131,58168,Female,Loyal Customer,47,Business travel,Business,3984,2,2,5,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +69132,113376,Female,Loyal Customer,51,Business travel,Business,414,1,1,1,1,5,5,5,2,2,2,2,3,2,4,127,124.0,satisfied +69133,92044,Female,Loyal Customer,31,Business travel,Business,1535,1,1,1,1,4,4,4,4,4,4,5,3,5,4,8,12.0,satisfied +69134,126231,Female,Loyal Customer,33,Business travel,Eco,328,0,0,0,3,4,0,4,4,3,4,3,1,2,4,0,3.0,satisfied +69135,39282,Male,Loyal Customer,52,Business travel,Eco,67,1,1,1,1,1,1,1,1,3,4,4,2,3,1,0,0.0,neutral or dissatisfied +69136,117056,Male,disloyal Customer,17,Business travel,Eco,338,4,1,4,3,4,4,5,4,1,3,3,4,3,4,6,1.0,neutral or dissatisfied +69137,62342,Female,Loyal Customer,30,Business travel,Eco Plus,236,3,1,1,1,3,3,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +69138,71732,Male,Loyal Customer,56,Business travel,Business,1723,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +69139,99481,Female,Loyal Customer,51,Business travel,Business,307,0,0,0,2,5,2,1,1,1,1,1,3,1,2,16,22.0,satisfied +69140,70118,Male,disloyal Customer,69,Business travel,Eco,460,3,4,3,4,3,3,4,3,4,3,3,2,3,3,1,0.0,neutral or dissatisfied +69141,82653,Female,Loyal Customer,53,Business travel,Business,120,3,3,3,3,3,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +69142,63675,Male,disloyal Customer,47,Business travel,Business,1047,3,3,3,3,3,3,1,3,3,4,4,5,4,3,0,0.0,satisfied +69143,60626,Male,Loyal Customer,58,Business travel,Business,1620,1,1,1,1,5,5,4,5,5,5,5,3,5,5,58,67.0,satisfied +69144,63975,Male,Loyal Customer,22,Business travel,Eco Plus,1192,0,3,0,3,2,0,2,2,5,1,5,2,1,2,0,0.0,satisfied +69145,119655,Female,Loyal Customer,25,Business travel,Eco,507,3,3,3,3,3,3,2,3,3,5,4,1,3,3,73,63.0,neutral or dissatisfied +69146,19618,Male,Loyal Customer,61,Personal Travel,Eco,416,3,4,1,2,2,1,2,2,2,5,1,4,1,2,0,0.0,neutral or dissatisfied +69147,20377,Male,Loyal Customer,42,Personal Travel,Eco,287,3,3,3,4,2,3,2,2,2,2,5,2,2,2,26,23.0,neutral or dissatisfied +69148,55968,Female,Loyal Customer,44,Business travel,Eco,1620,2,4,1,4,5,4,3,1,1,2,1,4,1,2,5,0.0,neutral or dissatisfied +69149,64804,Female,Loyal Customer,56,Business travel,Business,2643,3,3,3,3,4,2,3,3,3,3,3,2,3,2,49,56.0,neutral or dissatisfied +69150,51506,Male,disloyal Customer,27,Business travel,Eco,451,3,0,3,3,1,3,1,1,2,4,4,4,3,1,0,0.0,neutral or dissatisfied +69151,39415,Female,Loyal Customer,59,Business travel,Business,2083,2,2,4,2,2,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +69152,58995,Female,Loyal Customer,47,Business travel,Business,1846,4,4,2,4,3,4,5,4,4,4,4,3,4,3,32,66.0,satisfied +69153,18460,Male,Loyal Customer,48,Business travel,Eco,253,5,2,4,4,5,5,5,5,4,2,4,1,1,5,0,0.0,satisfied +69154,65554,Male,Loyal Customer,35,Business travel,Business,1786,1,1,1,1,2,4,4,4,4,4,4,3,4,3,3,5.0,satisfied +69155,120737,Male,Loyal Customer,25,Personal Travel,Eco,1089,4,3,4,3,3,4,3,3,4,2,1,3,1,3,0,0.0,satisfied +69156,102140,Male,Loyal Customer,56,Business travel,Business,407,3,3,3,3,5,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +69157,115864,Female,disloyal Customer,26,Business travel,Eco,373,4,3,4,1,4,4,4,4,3,5,4,5,5,4,0,10.0,satisfied +69158,12087,Female,Loyal Customer,42,Business travel,Business,3731,2,2,2,2,4,5,5,4,4,4,4,4,4,3,1,10.0,satisfied +69159,1957,Male,disloyal Customer,21,Business travel,Eco,351,3,0,3,4,4,3,4,4,3,4,3,2,3,4,29,44.0,neutral or dissatisfied +69160,118052,Male,Loyal Customer,61,Business travel,Business,1044,2,3,2,2,5,3,3,2,2,2,2,3,2,3,31,15.0,neutral or dissatisfied +69161,100258,Male,Loyal Customer,28,Business travel,Business,3477,2,2,5,2,5,5,5,5,5,5,4,4,5,5,0,6.0,satisfied +69162,81369,Male,Loyal Customer,32,Business travel,Business,282,3,1,3,3,4,4,4,4,4,5,4,3,4,4,15,1.0,satisfied +69163,27127,Male,Loyal Customer,43,Business travel,Business,2677,5,5,5,5,2,2,2,5,2,3,2,2,2,2,0,0.0,satisfied +69164,18398,Male,disloyal Customer,36,Business travel,Business,284,3,3,3,4,2,3,2,2,2,2,3,3,1,2,0,0.0,neutral or dissatisfied +69165,75352,Female,disloyal Customer,19,Business travel,Eco,878,4,4,4,3,4,4,4,4,4,3,3,5,4,4,15,0.0,satisfied +69166,58495,Female,Loyal Customer,29,Business travel,Business,719,4,2,2,2,4,4,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +69167,20487,Male,Loyal Customer,42,Business travel,Business,130,1,3,3,3,2,3,4,2,2,1,1,3,2,3,5,12.0,neutral or dissatisfied +69168,16638,Female,disloyal Customer,25,Business travel,Eco,488,2,4,2,4,2,2,2,2,1,3,5,3,2,2,0,0.0,neutral or dissatisfied +69169,79997,Male,Loyal Customer,38,Personal Travel,Eco,1076,3,5,3,2,2,3,5,2,4,3,5,3,5,2,12,34.0,neutral or dissatisfied +69170,99885,Male,disloyal Customer,25,Business travel,Business,738,0,0,0,2,1,0,1,1,5,4,4,5,5,1,96,65.0,satisfied +69171,37469,Female,disloyal Customer,28,Business travel,Eco,950,3,3,3,3,5,3,5,5,5,1,2,5,5,5,0,0.0,neutral or dissatisfied +69172,42394,Female,disloyal Customer,52,Business travel,Eco Plus,834,3,3,3,3,4,3,4,4,4,5,4,2,2,4,0,8.0,neutral or dissatisfied +69173,11932,Female,disloyal Customer,29,Business travel,Business,781,3,3,3,1,3,3,3,3,5,4,5,3,4,3,243,253.0,neutral or dissatisfied +69174,1696,Female,Loyal Customer,55,Business travel,Business,1730,1,1,1,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +69175,55495,Male,Loyal Customer,60,Business travel,Business,1739,3,3,3,3,3,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +69176,118117,Female,Loyal Customer,14,Personal Travel,Eco,1300,1,2,0,3,2,0,2,2,1,4,2,4,4,2,0,20.0,neutral or dissatisfied +69177,43991,Female,Loyal Customer,49,Business travel,Business,3716,2,2,2,2,3,4,5,3,3,3,3,1,3,1,12,1.0,satisfied +69178,116634,Male,Loyal Customer,80,Business travel,Business,358,5,5,5,5,4,4,5,5,5,5,5,5,5,4,8,0.0,satisfied +69179,104826,Male,Loyal Customer,58,Business travel,Business,2625,5,5,5,5,3,4,5,4,4,4,4,4,4,4,35,37.0,satisfied +69180,38891,Female,Loyal Customer,17,Personal Travel,Business,410,3,3,3,5,4,3,4,4,5,5,1,5,5,4,0,4.0,neutral or dissatisfied +69181,77420,Male,Loyal Customer,66,Personal Travel,Eco,588,3,4,3,1,4,3,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +69182,37053,Female,Loyal Customer,34,Personal Travel,Business,1188,1,4,1,4,1,2,4,4,4,1,4,2,4,1,41,29.0,neutral or dissatisfied +69183,46710,Female,Loyal Customer,12,Personal Travel,Eco,125,3,1,3,3,1,3,1,1,1,1,4,1,4,1,1,0.0,neutral or dissatisfied +69184,102864,Male,disloyal Customer,45,Business travel,Business,472,2,2,2,3,4,2,2,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +69185,48293,Male,Loyal Customer,44,Business travel,Eco,1499,2,5,5,5,1,2,1,1,2,1,5,5,3,1,44,36.0,satisfied +69186,101300,Female,Loyal Customer,56,Personal Travel,Eco,763,4,4,4,4,1,4,4,3,3,4,3,2,3,3,17,22.0,neutral or dissatisfied +69187,8294,Female,Loyal Customer,26,Personal Travel,Eco,335,3,4,3,3,1,3,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +69188,7666,Female,disloyal Customer,29,Business travel,Business,767,3,3,3,4,2,3,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +69189,54491,Female,Loyal Customer,47,Business travel,Eco,925,3,5,5,5,1,4,5,3,3,3,3,5,3,1,17,28.0,satisfied +69190,86797,Male,Loyal Customer,48,Business travel,Business,3134,3,3,3,3,2,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +69191,82278,Male,Loyal Customer,8,Personal Travel,Eco,1481,3,5,3,4,2,3,2,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +69192,129379,Female,Loyal Customer,72,Business travel,Business,2565,3,1,1,1,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +69193,77981,Male,Loyal Customer,49,Business travel,Business,1640,3,3,3,3,5,4,4,5,5,4,5,5,5,3,0,18.0,satisfied +69194,51610,Female,Loyal Customer,58,Business travel,Eco,493,4,2,2,2,2,2,3,4,4,4,4,4,4,1,0,0.0,satisfied +69195,16348,Female,Loyal Customer,53,Business travel,Business,1715,2,2,2,2,5,5,5,4,4,4,4,2,4,4,0,1.0,satisfied +69196,1230,Male,Loyal Customer,34,Personal Travel,Eco,113,2,5,2,2,3,2,3,3,2,1,3,2,1,3,0,0.0,neutral or dissatisfied +69197,87858,Female,Loyal Customer,9,Personal Travel,Eco,214,1,3,0,3,1,0,1,1,4,4,3,2,4,1,0,0.0,neutral or dissatisfied +69198,54993,Female,Loyal Customer,45,Business travel,Business,1635,4,4,4,4,4,3,4,5,5,5,5,3,5,3,8,0.0,satisfied +69199,50483,Male,Loyal Customer,37,Business travel,Business,1979,3,3,3,3,5,3,3,4,4,4,4,2,4,1,0,0.0,satisfied +69200,124901,Male,Loyal Customer,34,Business travel,Business,3612,2,3,3,3,1,4,3,2,2,2,2,2,2,3,19,28.0,neutral or dissatisfied +69201,10467,Female,Loyal Customer,59,Business travel,Business,3539,0,5,1,2,3,4,5,3,3,3,3,5,3,4,64,55.0,satisfied +69202,83869,Female,disloyal Customer,26,Business travel,Eco Plus,425,1,0,0,4,1,0,1,1,3,2,3,2,4,1,0,0.0,neutral or dissatisfied +69203,111333,Male,Loyal Customer,64,Personal Travel,Eco,283,1,4,1,4,3,1,4,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +69204,112256,Female,disloyal Customer,39,Business travel,Business,1546,4,5,5,1,1,5,1,1,1,1,2,1,1,1,58,35.0,neutral or dissatisfied +69205,69209,Female,Loyal Customer,55,Business travel,Business,3169,5,5,5,5,4,5,4,3,3,4,3,5,3,5,6,11.0,satisfied +69206,100515,Female,disloyal Customer,22,Business travel,Business,580,3,2,3,3,2,3,2,2,1,1,3,2,3,2,94,77.0,neutral or dissatisfied +69207,124804,Male,Loyal Customer,64,Business travel,Business,3992,3,3,4,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +69208,55148,Female,Loyal Customer,49,Personal Travel,Eco,1635,1,4,1,1,3,3,4,3,3,1,3,5,3,4,22,51.0,neutral or dissatisfied +69209,25518,Male,Loyal Customer,31,Business travel,Business,3904,4,4,5,4,5,5,5,5,3,3,1,4,5,5,0,0.0,satisfied +69210,40689,Female,Loyal Customer,41,Business travel,Eco,501,4,5,5,5,4,4,4,4,1,2,1,4,5,4,0,0.0,satisfied +69211,48844,Female,Loyal Customer,66,Personal Travel,Business,86,3,5,3,5,3,5,4,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +69212,122275,Male,Loyal Customer,8,Personal Travel,Eco,541,2,4,2,1,4,2,4,4,5,4,5,3,5,4,1,0.0,neutral or dissatisfied +69213,111828,Male,Loyal Customer,47,Business travel,Business,1605,5,5,1,5,4,4,5,4,4,4,4,3,4,5,127,126.0,satisfied +69214,84060,Male,Loyal Customer,57,Business travel,Business,757,1,1,1,1,2,5,4,5,5,5,5,3,5,3,2,0.0,satisfied +69215,75312,Male,Loyal Customer,42,Business travel,Business,2615,1,1,5,1,3,3,3,3,3,3,4,3,5,3,0,0.0,satisfied +69216,79025,Female,Loyal Customer,28,Business travel,Eco,356,3,4,4,4,3,3,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +69217,78807,Male,Loyal Customer,56,Personal Travel,Eco,432,2,5,2,2,1,2,1,1,1,1,4,5,4,1,29,40.0,neutral or dissatisfied +69218,47153,Male,disloyal Customer,32,Business travel,Eco,954,2,2,2,1,3,2,5,3,1,4,5,2,3,3,26,13.0,neutral or dissatisfied +69219,7598,Female,Loyal Customer,40,Business travel,Business,1695,5,5,5,5,4,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +69220,70124,Female,Loyal Customer,57,Business travel,Business,3904,2,4,2,2,5,4,4,4,4,4,4,3,4,4,0,4.0,satisfied +69221,82500,Female,Loyal Customer,33,Personal Travel,Eco Plus,488,4,2,4,3,2,4,2,2,4,4,2,4,3,2,0,0.0,neutral or dissatisfied +69222,98497,Female,Loyal Customer,56,Business travel,Business,668,4,4,4,4,3,4,4,5,5,5,5,5,5,3,47,51.0,satisfied +69223,23781,Male,disloyal Customer,42,Business travel,Eco,438,3,4,3,1,5,3,5,5,5,3,4,2,4,5,13,8.0,neutral or dissatisfied +69224,26047,Female,Loyal Customer,39,Business travel,Eco,432,3,4,3,4,3,4,3,3,1,3,1,3,5,3,0,0.0,satisfied +69225,102975,Male,Loyal Customer,53,Business travel,Business,490,4,4,4,4,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +69226,41968,Male,Loyal Customer,24,Business travel,Business,3993,4,1,1,1,4,4,4,4,2,1,3,4,4,4,0,0.0,neutral or dissatisfied +69227,3587,Male,Loyal Customer,42,Business travel,Business,2188,5,5,5,5,2,5,4,2,2,2,2,3,2,4,0,10.0,satisfied +69228,37319,Male,Loyal Customer,24,Business travel,Eco,1074,4,3,3,3,4,3,4,1,2,5,1,4,2,4,135,129.0,satisfied +69229,99032,Male,Loyal Customer,14,Business travel,Business,3564,1,1,1,1,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +69230,27385,Female,disloyal Customer,30,Business travel,Eco,679,3,3,3,4,1,3,1,1,3,1,3,3,4,1,130,117.0,neutral or dissatisfied +69231,885,Female,Loyal Customer,45,Business travel,Business,3477,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +69232,39354,Male,Loyal Customer,45,Business travel,Business,2992,4,4,4,4,1,3,3,5,5,5,5,3,5,2,3,0.0,satisfied +69233,117861,Male,disloyal Customer,21,Business travel,Eco,255,1,1,1,2,5,1,5,5,1,3,3,2,3,5,0,0.0,neutral or dissatisfied +69234,75968,Male,Loyal Customer,68,Business travel,Business,228,1,1,1,1,5,4,5,4,4,4,4,4,4,4,0,4.0,satisfied +69235,84623,Female,Loyal Customer,7,Personal Travel,Eco,669,3,4,2,3,5,2,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +69236,125712,Male,Loyal Customer,28,Personal Travel,Eco,857,2,4,2,1,2,2,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +69237,128477,Male,Loyal Customer,68,Personal Travel,Eco,651,2,4,2,1,3,2,3,3,5,4,3,5,4,3,17,11.0,neutral or dissatisfied +69238,92237,Female,Loyal Customer,53,Business travel,Business,1670,5,5,5,5,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +69239,8969,Male,Loyal Customer,41,Business travel,Business,2684,5,5,5,5,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +69240,52635,Female,disloyal Customer,27,Business travel,Eco,119,2,2,3,4,3,3,3,3,2,1,4,1,4,3,0,7.0,neutral or dissatisfied +69241,113294,Female,Loyal Customer,50,Business travel,Business,3254,5,5,5,5,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +69242,114807,Male,Loyal Customer,16,Business travel,Business,3104,2,2,5,2,5,5,5,5,4,3,5,5,5,5,0,3.0,satisfied +69243,125982,Male,Loyal Customer,25,Business travel,Business,2041,1,2,2,2,1,1,1,1,1,3,3,1,3,1,25,27.0,neutral or dissatisfied +69244,85222,Male,Loyal Customer,11,Business travel,Business,813,1,4,4,4,1,1,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +69245,101111,Male,Loyal Customer,22,Business travel,Business,3472,1,1,1,1,5,5,5,5,4,3,5,5,5,5,29,14.0,satisfied +69246,74637,Male,Loyal Customer,31,Business travel,Business,1205,2,3,3,3,2,2,2,2,4,3,3,1,4,2,27,0.0,neutral or dissatisfied +69247,50,Male,disloyal Customer,27,Business travel,Business,108,4,4,4,4,5,4,5,5,3,4,4,5,5,5,0,0.0,satisfied +69248,49961,Female,Loyal Customer,34,Business travel,Business,110,1,4,4,4,4,3,2,4,4,4,1,2,4,1,0,0.0,neutral or dissatisfied +69249,64218,Female,Loyal Customer,7,Personal Travel,Business,1660,4,0,5,5,4,5,4,4,5,2,5,4,5,4,29,25.0,neutral or dissatisfied +69250,7641,Male,Loyal Customer,49,Business travel,Business,3536,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +69251,129859,Female,Loyal Customer,22,Business travel,Eco Plus,308,3,2,2,2,3,3,2,3,4,5,4,1,3,3,0,7.0,neutral or dissatisfied +69252,100489,Male,Loyal Customer,47,Business travel,Business,3244,1,4,4,4,4,3,4,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +69253,37029,Male,Loyal Customer,34,Personal Travel,Business,994,1,5,0,3,5,5,5,5,5,0,5,3,5,4,0,0.0,neutral or dissatisfied +69254,12548,Male,Loyal Customer,38,Business travel,Eco,388,1,4,3,4,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +69255,84886,Female,Loyal Customer,10,Personal Travel,Eco,516,4,4,4,1,5,4,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +69256,100027,Male,Loyal Customer,51,Business travel,Business,3909,3,3,3,3,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +69257,118142,Male,Loyal Customer,51,Business travel,Business,1440,4,4,4,4,5,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +69258,98040,Male,Loyal Customer,39,Business travel,Business,1797,3,3,2,3,5,4,4,5,5,5,5,5,5,5,46,51.0,satisfied +69259,114610,Male,Loyal Customer,61,Business travel,Business,3605,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +69260,37185,Female,Loyal Customer,24,Personal Travel,Eco,1189,3,4,3,1,2,3,2,2,5,4,3,4,4,2,110,116.0,neutral or dissatisfied +69261,81068,Male,Loyal Customer,9,Personal Travel,Business,931,4,4,3,4,4,3,4,4,4,4,5,3,4,4,44,39.0,neutral or dissatisfied +69262,110904,Male,disloyal Customer,20,Business travel,Business,404,4,0,4,2,5,4,5,5,3,2,5,5,4,5,16,5.0,satisfied +69263,60921,Male,disloyal Customer,24,Business travel,Eco,888,3,3,3,1,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +69264,37270,Female,disloyal Customer,27,Business travel,Eco,1010,3,3,3,3,5,3,5,5,3,3,4,2,3,5,39,36.0,neutral or dissatisfied +69265,57938,Male,Loyal Customer,45,Business travel,Business,837,4,4,5,4,4,4,4,5,5,4,5,4,4,4,233,229.0,satisfied +69266,116739,Female,Loyal Customer,16,Personal Travel,Eco Plus,342,4,4,4,1,1,4,1,1,5,5,5,4,4,1,9,0.0,satisfied +69267,18481,Male,disloyal Customer,30,Business travel,Eco,253,2,3,2,4,3,2,4,3,1,4,2,2,1,3,0,0.0,neutral or dissatisfied +69268,67057,Male,Loyal Customer,16,Business travel,Business,2161,4,4,4,4,3,3,3,3,3,5,5,5,5,3,0,0.0,satisfied +69269,65908,Female,Loyal Customer,52,Business travel,Business,2663,5,5,5,5,5,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +69270,2352,Male,Loyal Customer,36,Personal Travel,Business,925,4,3,5,4,4,3,3,2,2,5,2,3,2,2,6,13.0,neutral or dissatisfied +69271,58438,Female,Loyal Customer,34,Personal Travel,Eco,733,2,2,2,3,4,2,3,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +69272,16272,Female,Loyal Customer,70,Personal Travel,Eco,946,2,3,3,3,5,3,3,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +69273,23529,Male,Loyal Customer,49,Business travel,Business,3971,4,1,4,4,4,4,4,4,4,4,4,5,4,3,38,56.0,satisfied +69274,118574,Female,Loyal Customer,41,Business travel,Eco,646,4,3,3,3,4,4,4,4,2,2,4,4,3,4,53,44.0,neutral or dissatisfied +69275,17470,Male,Loyal Customer,52,Personal Travel,Business,341,2,5,2,4,2,4,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +69276,6259,Male,Loyal Customer,42,Business travel,Business,1990,4,4,2,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +69277,26801,Female,Loyal Customer,23,Business travel,Business,1947,2,5,5,5,2,2,2,2,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +69278,83062,Male,Loyal Customer,57,Business travel,Eco,983,4,4,4,4,4,4,4,4,4,1,4,4,3,4,0,0.0,neutral or dissatisfied +69279,51403,Male,Loyal Customer,60,Personal Travel,Eco Plus,308,3,5,3,2,2,3,5,2,3,3,5,4,4,2,30,20.0,neutral or dissatisfied +69280,97300,Female,Loyal Customer,47,Business travel,Business,2923,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,8.0,satisfied +69281,112965,Female,Loyal Customer,45,Personal Travel,Eco,1164,2,4,2,2,4,4,5,4,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +69282,91393,Female,Loyal Customer,38,Business travel,Business,2218,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,1.0,satisfied +69283,124506,Female,Loyal Customer,47,Personal Travel,Eco,930,5,4,5,3,5,5,5,2,2,4,2,3,2,4,0,0.0,satisfied +69284,57889,Female,Loyal Customer,63,Business travel,Business,2490,5,5,5,5,5,5,5,5,5,5,5,3,5,3,10,37.0,satisfied +69285,44822,Female,Loyal Customer,34,Personal Travel,Eco Plus,491,3,1,3,4,3,3,3,3,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +69286,123902,Male,Loyal Customer,62,Personal Travel,Eco,541,1,5,1,1,3,1,3,3,4,4,4,5,5,3,7,0.0,neutral or dissatisfied +69287,13318,Female,disloyal Customer,10,Business travel,Business,764,1,2,1,3,5,1,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +69288,119103,Male,Loyal Customer,47,Business travel,Business,3404,2,2,1,2,1,3,3,4,4,4,4,3,4,5,0,0.0,satisfied +69289,1443,Female,Loyal Customer,47,Business travel,Business,695,5,4,5,5,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +69290,106815,Female,disloyal Customer,34,Business travel,Business,1488,3,3,3,2,1,3,1,1,5,5,4,3,5,1,37,45.0,neutral or dissatisfied +69291,120241,Male,Loyal Customer,29,Personal Travel,Eco,1303,3,1,3,3,2,3,2,2,3,1,2,4,3,2,0,5.0,neutral or dissatisfied +69292,30818,Male,Loyal Customer,24,Business travel,Business,851,3,4,4,4,3,3,3,3,1,2,3,2,4,3,28,40.0,neutral or dissatisfied +69293,35030,Female,disloyal Customer,28,Business travel,Business,718,4,4,4,2,1,4,1,1,4,5,4,4,4,1,0,0.0,satisfied +69294,12899,Female,Loyal Customer,24,Business travel,Business,641,2,2,2,2,4,4,4,3,3,1,4,4,5,4,205,185.0,satisfied +69295,27937,Female,disloyal Customer,25,Business travel,Eco,1770,3,3,3,4,3,3,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +69296,109906,Male,Loyal Customer,45,Business travel,Eco,673,2,1,1,1,3,2,3,3,4,2,4,2,4,3,88,73.0,neutral or dissatisfied +69297,3628,Male,Loyal Customer,58,Business travel,Business,427,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +69298,128204,Male,disloyal Customer,51,Business travel,Business,602,4,5,5,2,3,4,3,3,5,3,5,4,5,3,0,0.0,satisfied +69299,36660,Female,Loyal Customer,16,Personal Travel,Eco,1121,1,4,1,3,1,1,1,5,3,5,4,1,4,1,156,141.0,neutral or dissatisfied +69300,37402,Male,Loyal Customer,22,Business travel,Business,1028,2,2,2,2,3,3,3,3,1,2,5,1,4,3,70,53.0,satisfied +69301,91833,Male,Loyal Customer,48,Business travel,Eco Plus,626,4,1,3,3,4,4,4,4,1,1,3,1,4,4,8,9.0,neutral or dissatisfied +69302,54889,Female,Loyal Customer,52,Personal Travel,Eco,641,2,4,1,3,2,4,4,4,4,1,4,4,4,4,23,9.0,neutral or dissatisfied +69303,27486,Female,Loyal Customer,52,Business travel,Eco,954,5,2,2,2,2,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +69304,88909,Male,Loyal Customer,67,Personal Travel,Eco,859,5,4,5,2,2,5,2,2,5,2,5,3,4,2,0,0.0,satisfied +69305,85092,Female,Loyal Customer,50,Business travel,Business,731,3,3,3,3,5,5,5,4,4,5,5,5,3,5,199,284.0,satisfied +69306,16394,Female,Loyal Customer,61,Business travel,Business,1986,1,3,4,3,4,1,5,1,3,2,2,5,1,5,172,171.0,neutral or dissatisfied +69307,66739,Male,Loyal Customer,45,Personal Travel,Eco,802,3,1,3,1,2,3,4,2,3,3,1,1,1,2,110,113.0,neutral or dissatisfied +69308,84942,Female,Loyal Customer,25,Personal Travel,Eco,481,0,1,0,3,2,0,2,2,1,4,4,4,3,2,0,0.0,satisfied +69309,30547,Female,Loyal Customer,51,Business travel,Eco,955,2,3,3,3,2,3,2,2,2,2,2,2,2,4,0,0.0,satisfied +69310,1996,Male,Loyal Customer,30,Personal Travel,Eco,293,3,4,3,4,3,3,3,3,3,5,5,3,4,3,118,116.0,neutral or dissatisfied +69311,119143,Female,Loyal Customer,44,Personal Travel,Eco,119,3,3,3,3,4,5,4,4,4,3,4,3,4,4,3,47.0,neutral or dissatisfied +69312,40767,Male,Loyal Customer,51,Business travel,Eco,532,5,5,5,5,5,5,5,5,1,2,3,4,1,5,0,0.0,satisfied +69313,24814,Male,Loyal Customer,34,Business travel,Business,991,3,5,5,5,1,2,2,3,3,2,3,4,3,1,9,3.0,neutral or dissatisfied +69314,35158,Male,Loyal Customer,44,Business travel,Eco,944,3,5,5,5,3,3,3,3,3,1,1,3,1,3,9,0.0,satisfied +69315,83630,Male,Loyal Customer,12,Personal Travel,Eco,409,2,5,2,3,2,2,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +69316,35084,Male,Loyal Customer,35,Business travel,Eco,1041,4,2,2,2,4,4,4,4,4,3,1,2,2,4,0,0.0,satisfied +69317,75654,Female,Loyal Customer,67,Business travel,Business,304,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +69318,76440,Female,Loyal Customer,32,Personal Travel,Eco,405,3,3,3,4,3,3,3,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +69319,65943,Female,Loyal Customer,60,Business travel,Business,1372,1,1,1,1,4,4,4,2,2,2,2,5,2,3,4,0.0,satisfied +69320,39877,Female,Loyal Customer,23,Personal Travel,Eco,272,2,4,2,3,5,2,5,5,5,4,4,5,5,5,0,11.0,neutral or dissatisfied +69321,15503,Female,Loyal Customer,33,Personal Travel,Eco,399,2,4,5,2,1,5,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +69322,5477,Female,Loyal Customer,54,Business travel,Business,287,5,5,5,5,2,4,4,5,5,5,5,3,5,4,41,27.0,satisfied +69323,51023,Female,disloyal Customer,18,Personal Travel,Eco,266,5,0,5,1,2,5,2,2,4,5,5,3,5,2,0,0.0,satisfied +69324,120404,Male,Loyal Customer,56,Business travel,Business,2908,2,2,2,2,4,4,5,3,3,4,3,4,3,3,0,4.0,satisfied +69325,2202,Female,Loyal Customer,41,Personal Travel,Eco,624,4,3,4,3,5,4,5,5,4,2,3,3,4,5,0,5.0,neutral or dissatisfied +69326,102967,Male,Loyal Customer,50,Business travel,Business,2644,2,5,5,5,2,4,3,2,2,2,2,3,2,3,9,0.0,neutral or dissatisfied +69327,15869,Male,Loyal Customer,56,Business travel,Business,2576,3,3,3,3,4,3,5,5,5,5,5,2,5,1,0,0.0,satisfied +69328,66239,Male,Loyal Customer,56,Business travel,Eco,150,1,1,4,1,1,1,1,1,4,5,3,1,4,1,0,3.0,neutral or dissatisfied +69329,56491,Male,Loyal Customer,69,Business travel,Business,937,3,3,3,3,4,4,5,4,4,4,4,4,4,3,16,0.0,satisfied +69330,17207,Male,Loyal Customer,57,Personal Travel,Eco,694,2,4,2,2,1,2,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +69331,63128,Female,Loyal Customer,47,Business travel,Business,447,1,2,2,2,4,4,3,1,1,1,1,3,1,1,3,0.0,neutral or dissatisfied +69332,36647,Male,Loyal Customer,43,Personal Travel,Eco,1237,4,4,4,3,2,4,4,2,4,4,3,2,4,2,0,31.0,satisfied +69333,63260,Male,Loyal Customer,44,Business travel,Business,3208,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +69334,7147,Female,Loyal Customer,49,Business travel,Business,2577,4,4,4,4,4,4,4,3,2,4,4,4,3,4,139,150.0,satisfied +69335,126412,Male,Loyal Customer,24,Business travel,Business,600,2,2,2,2,4,4,4,4,4,3,4,4,4,4,1,0.0,satisfied +69336,80703,Female,Loyal Customer,42,Personal Travel,Eco,874,2,5,2,4,3,5,4,3,3,2,1,4,3,3,0,0.0,neutral or dissatisfied +69337,6501,Female,Loyal Customer,49,Business travel,Business,1654,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +69338,74013,Female,disloyal Customer,48,Business travel,Business,1471,4,4,4,1,5,4,5,5,5,5,4,3,4,5,0,6.0,satisfied +69339,107535,Female,Loyal Customer,60,Business travel,Business,1521,3,3,3,3,2,4,4,4,4,4,4,3,4,5,60,56.0,satisfied +69340,79273,Male,Loyal Customer,55,Personal Travel,Eco,2454,3,2,3,4,3,2,4,1,1,4,4,4,1,4,0,0.0,neutral or dissatisfied +69341,127898,Male,Loyal Customer,40,Business travel,Business,1671,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +69342,98743,Male,Loyal Customer,21,Personal Travel,Eco,1290,1,5,0,1,5,0,3,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +69343,51998,Female,Loyal Customer,30,Business travel,Business,1951,3,4,4,4,3,3,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +69344,100328,Male,Loyal Customer,24,Business travel,Business,1999,3,1,1,1,3,3,3,3,2,5,3,2,3,3,76,73.0,neutral or dissatisfied +69345,48819,Female,Loyal Customer,55,Personal Travel,Business,421,2,4,5,2,4,4,3,5,5,5,5,2,5,5,0,0.0,neutral or dissatisfied +69346,72440,Male,Loyal Customer,39,Business travel,Business,1503,2,5,2,2,2,4,5,3,3,4,3,3,3,5,0,24.0,satisfied +69347,60023,Male,Loyal Customer,9,Personal Travel,Eco,937,3,3,3,4,1,3,1,1,1,1,4,2,3,1,0,1.0,neutral or dissatisfied +69348,7761,Female,Loyal Customer,54,Business travel,Business,3969,4,4,4,4,5,4,4,5,5,5,5,4,5,3,6,0.0,satisfied +69349,122126,Male,Loyal Customer,48,Personal Travel,Eco Plus,130,1,0,1,1,5,1,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +69350,29515,Female,Loyal Customer,19,Personal Travel,Eco Plus,1107,4,5,4,3,1,4,1,1,4,2,4,4,4,1,0,2.0,neutral or dissatisfied +69351,46489,Male,Loyal Customer,42,Business travel,Business,125,0,4,0,3,4,2,5,3,3,3,3,4,3,5,45,41.0,satisfied +69352,74072,Female,disloyal Customer,35,Business travel,Business,641,1,1,1,4,1,1,2,1,5,5,5,5,5,1,19,4.0,neutral or dissatisfied +69353,55108,Female,Loyal Customer,20,Personal Travel,Eco,1303,2,4,1,3,3,1,3,3,2,4,3,1,4,3,6,7.0,neutral or dissatisfied +69354,106449,Female,disloyal Customer,30,Business travel,Eco Plus,1062,2,2,2,3,2,2,2,2,1,4,3,3,3,2,0,4.0,neutral or dissatisfied +69355,128610,Female,Loyal Customer,39,Business travel,Business,679,5,5,5,5,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +69356,103546,Male,Loyal Customer,65,Personal Travel,Eco,967,3,5,3,3,3,3,3,3,4,2,5,4,5,3,9,0.0,neutral or dissatisfied +69357,108098,Male,Loyal Customer,43,Business travel,Business,3829,5,3,5,5,3,4,4,4,4,4,4,3,4,3,87,74.0,satisfied +69358,72697,Female,Loyal Customer,54,Personal Travel,Eco,985,3,5,2,4,4,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +69359,11045,Female,Loyal Customer,22,Personal Travel,Eco,191,3,4,3,1,5,3,1,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +69360,58131,Female,Loyal Customer,56,Business travel,Eco Plus,612,3,2,1,1,5,3,2,2,2,3,2,1,2,3,25,41.0,neutral or dissatisfied +69361,119140,Male,Loyal Customer,53,Personal Travel,Eco,119,3,1,3,2,5,3,2,5,4,5,2,3,3,5,18,57.0,neutral or dissatisfied +69362,87818,Female,disloyal Customer,27,Business travel,Business,143,3,3,3,4,1,3,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +69363,64664,Male,Loyal Customer,46,Business travel,Business,247,0,0,0,3,4,4,5,1,1,1,1,3,1,3,70,72.0,satisfied +69364,40324,Female,Loyal Customer,28,Business travel,Eco Plus,531,2,4,4,4,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +69365,58977,Female,disloyal Customer,34,Business travel,Business,1744,2,3,3,4,4,3,4,4,5,4,3,4,5,4,0,0.0,neutral or dissatisfied +69366,29750,Male,Loyal Customer,41,Business travel,Business,2197,2,2,3,2,5,4,5,5,5,5,5,3,5,5,16,5.0,satisfied +69367,61246,Female,disloyal Customer,22,Business travel,Business,567,2,2,1,4,5,1,5,5,3,2,3,1,4,5,45,68.0,neutral or dissatisfied +69368,126417,Male,Loyal Customer,41,Business travel,Business,2265,5,5,2,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +69369,7530,Male,Loyal Customer,65,Business travel,Business,2772,3,3,3,3,5,4,4,4,4,4,4,3,4,5,17,3.0,satisfied +69370,115184,Female,Loyal Customer,44,Business travel,Business,337,3,3,3,3,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +69371,76952,Female,Loyal Customer,47,Business travel,Business,1990,4,1,4,4,3,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +69372,64091,Female,Loyal Customer,45,Personal Travel,Eco,919,2,5,2,5,5,4,5,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +69373,79278,Male,Loyal Customer,50,Business travel,Business,2248,1,1,1,1,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +69374,3077,Male,Loyal Customer,41,Business travel,Business,1899,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +69375,121963,Female,Loyal Customer,54,Business travel,Business,3362,2,2,2,2,5,4,4,4,4,4,5,4,4,3,17,32.0,satisfied +69376,124719,Male,Loyal Customer,14,Personal Travel,Eco,399,2,5,2,3,5,2,5,5,3,4,4,5,5,5,6,0.0,neutral or dissatisfied +69377,124131,Female,Loyal Customer,60,Personal Travel,Eco,529,4,4,5,2,5,4,5,1,1,5,1,4,1,3,0,0.0,neutral or dissatisfied +69378,105025,Male,Loyal Customer,39,Business travel,Eco,255,1,3,3,3,1,1,1,1,4,3,3,2,4,1,0,0.0,neutral or dissatisfied +69379,128593,Female,Loyal Customer,26,Business travel,Business,2043,1,1,1,1,3,3,3,3,3,5,4,5,4,3,57,71.0,satisfied +69380,122089,Female,Loyal Customer,32,Personal Travel,Eco,130,2,0,2,1,4,2,4,4,4,4,5,4,4,4,39,34.0,neutral or dissatisfied +69381,119815,Female,Loyal Customer,46,Business travel,Business,912,3,3,3,3,2,4,5,5,5,5,5,3,5,4,29,13.0,satisfied +69382,12804,Male,disloyal Customer,23,Business travel,Eco,489,2,4,1,4,2,1,2,2,2,2,5,4,2,2,0,0.0,neutral or dissatisfied +69383,13811,Female,Loyal Customer,29,Business travel,Business,3951,3,3,3,3,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +69384,110254,Male,Loyal Customer,40,Business travel,Business,2810,2,2,2,2,5,5,4,5,5,5,5,4,5,4,24,46.0,satisfied +69385,23699,Female,Loyal Customer,58,Business travel,Eco,251,5,1,1,1,1,5,1,5,5,5,5,5,5,4,13,7.0,satisfied +69386,98350,Female,Loyal Customer,57,Business travel,Business,1189,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +69387,1299,Female,Loyal Customer,34,Personal Travel,Eco,354,4,5,4,3,1,4,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +69388,30277,Female,Loyal Customer,16,Personal Travel,Eco,1024,2,5,2,1,3,2,3,3,4,5,5,4,5,3,0,7.0,neutral or dissatisfied +69389,10224,Male,Loyal Customer,41,Business travel,Business,2115,2,2,3,3,3,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +69390,88312,Male,Loyal Customer,35,Business travel,Business,1591,3,3,3,3,2,4,5,4,4,4,4,4,4,4,35,31.0,satisfied +69391,64567,Female,Loyal Customer,36,Business travel,Business,3171,0,0,0,3,2,4,4,2,2,5,5,5,2,4,0,0.0,satisfied +69392,60033,Male,Loyal Customer,28,Personal Travel,Eco,1023,4,4,4,5,4,4,4,4,3,1,2,2,5,4,40,,neutral or dissatisfied +69393,6711,Male,Loyal Customer,50,Personal Travel,Eco,403,3,2,3,4,2,3,2,2,2,3,4,2,3,2,30,26.0,neutral or dissatisfied +69394,55004,Male,Loyal Customer,30,Business travel,Business,1608,5,5,5,5,5,5,5,5,3,4,5,3,4,5,3,9.0,satisfied +69395,53240,Female,Loyal Customer,22,Personal Travel,Eco,642,2,1,2,4,2,2,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +69396,106486,Female,Loyal Customer,42,Business travel,Business,3476,1,1,1,1,4,5,4,5,5,5,5,5,5,5,12,4.0,satisfied +69397,27767,Male,disloyal Customer,46,Business travel,Eco,1485,3,3,3,5,5,3,5,5,1,2,1,5,3,5,0,6.0,neutral or dissatisfied +69398,83582,Female,Loyal Customer,30,Personal Travel,Eco,936,5,5,5,3,3,5,3,3,3,3,4,5,5,3,0,0.0,satisfied +69399,129603,Male,Loyal Customer,49,Business travel,Business,2103,1,1,1,1,4,5,5,4,4,4,4,5,4,3,6,12.0,satisfied +69400,94903,Male,disloyal Customer,16,Business travel,Eco,458,3,0,3,3,1,3,1,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +69401,5543,Female,Loyal Customer,51,Personal Travel,Eco,404,2,4,2,5,5,5,5,4,4,2,2,4,4,3,0,0.0,neutral or dissatisfied +69402,65853,Female,Loyal Customer,45,Personal Travel,Eco,1389,3,5,3,4,2,4,4,1,1,3,1,3,1,3,0,10.0,neutral or dissatisfied +69403,80981,Male,disloyal Customer,39,Business travel,Business,297,2,2,2,4,4,2,4,4,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +69404,128181,Female,Loyal Customer,10,Personal Travel,Eco,1788,3,5,3,5,4,3,4,4,5,4,5,4,4,4,8,5.0,neutral or dissatisfied +69405,54646,Female,Loyal Customer,38,Business travel,Business,3607,1,1,1,1,3,2,4,4,4,4,4,2,4,3,0,0.0,satisfied +69406,77658,Female,Loyal Customer,20,Business travel,Business,731,4,4,4,4,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +69407,4510,Male,Loyal Customer,62,Personal Travel,Eco,435,3,5,3,3,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +69408,100636,Male,Loyal Customer,35,Business travel,Business,349,2,2,2,2,4,5,4,5,5,5,5,3,5,5,0,7.0,satisfied +69409,18086,Female,Loyal Customer,24,Personal Travel,Eco,488,4,2,4,3,5,4,5,5,1,5,2,2,4,5,0,0.0,neutral or dissatisfied +69410,82065,Female,Loyal Customer,39,Business travel,Business,2829,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +69411,16541,Male,disloyal Customer,22,Business travel,Eco,1134,4,4,4,5,4,1,1,2,4,4,2,1,4,1,185,190.0,satisfied +69412,97462,Female,disloyal Customer,24,Business travel,Eco,756,2,2,2,5,3,2,3,3,5,5,5,5,4,3,6,21.0,neutral or dissatisfied +69413,34909,Female,Loyal Customer,34,Business travel,Eco,187,5,3,3,3,5,5,5,5,3,4,3,1,3,5,3,0.0,satisfied +69414,58814,Female,Loyal Customer,57,Personal Travel,Eco,1050,2,5,2,4,2,5,3,5,5,2,5,1,5,5,9,37.0,neutral or dissatisfied +69415,35939,Male,Loyal Customer,18,Personal Travel,Eco Plus,2381,3,5,3,1,3,2,2,3,5,5,4,2,3,2,153,140.0,neutral or dissatisfied +69416,63043,Male,Loyal Customer,62,Personal Travel,Eco,846,3,5,3,3,5,3,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +69417,8291,Male,Loyal Customer,52,Personal Travel,Eco,530,2,4,2,3,1,2,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +69418,51180,Female,Loyal Customer,41,Business travel,Eco Plus,109,5,3,3,3,5,1,3,5,5,5,5,3,5,4,0,0.0,satisfied +69419,76503,Female,Loyal Customer,53,Business travel,Business,2733,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +69420,61535,Male,Loyal Customer,58,Personal Travel,Eco,2419,2,2,3,3,2,3,1,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +69421,71853,Male,Loyal Customer,48,Business travel,Business,1918,4,4,4,4,4,4,1,5,5,5,5,2,5,2,0,0.0,satisfied +69422,59691,Male,Loyal Customer,23,Personal Travel,Eco,854,1,4,1,1,4,1,4,4,5,3,4,3,5,4,23,14.0,neutral or dissatisfied +69423,93777,Female,disloyal Customer,26,Business travel,Business,1865,1,0,0,4,2,0,2,2,5,5,3,4,4,2,2,6.0,neutral or dissatisfied +69424,47351,Female,Loyal Customer,49,Business travel,Eco,590,2,5,5,5,5,3,4,2,2,2,2,4,2,5,68,66.0,satisfied +69425,83312,Female,Loyal Customer,48,Business travel,Business,1671,1,1,1,1,4,5,4,4,4,4,4,4,4,4,41,74.0,satisfied +69426,71066,Female,Loyal Customer,17,Personal Travel,Eco,802,1,5,1,4,3,1,3,3,2,2,3,1,1,3,10,0.0,neutral or dissatisfied +69427,83261,Male,Loyal Customer,52,Business travel,Eco,1956,2,2,2,2,2,2,2,2,1,4,4,3,3,2,48,48.0,neutral or dissatisfied +69428,71094,Male,Loyal Customer,49,Business travel,Business,2002,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +69429,116496,Female,Loyal Customer,30,Personal Travel,Eco,373,1,4,1,4,2,1,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +69430,129722,Female,Loyal Customer,48,Business travel,Eco,337,2,4,4,4,5,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +69431,104425,Male,Loyal Customer,14,Business travel,Business,2433,3,1,1,1,3,3,3,3,1,5,3,2,4,3,0,16.0,neutral or dissatisfied +69432,19666,Male,Loyal Customer,59,Business travel,Business,475,4,4,4,4,5,4,4,4,4,5,4,3,4,5,63,61.0,satisfied +69433,60082,Female,Loyal Customer,22,Business travel,Business,1005,2,2,2,2,4,4,4,4,3,3,5,3,5,4,13,0.0,satisfied +69434,60782,Male,Loyal Customer,55,Personal Travel,Eco,628,1,4,1,2,1,1,1,1,3,4,5,5,4,1,16,4.0,neutral or dissatisfied +69435,22913,Male,Loyal Customer,56,Business travel,Eco,630,5,2,2,2,5,5,5,5,4,3,2,2,3,5,76,63.0,satisfied +69436,37490,Female,Loyal Customer,70,Business travel,Eco,828,1,1,1,1,3,4,3,1,1,1,1,2,1,3,21,7.0,neutral or dissatisfied +69437,80099,Female,disloyal Customer,22,Business travel,Business,1470,0,0,0,1,3,0,3,3,4,5,3,3,5,3,0,0.0,satisfied +69438,30631,Female,Loyal Customer,22,Business travel,Eco,770,5,2,3,2,5,5,4,5,3,2,1,2,5,5,2,9.0,satisfied +69439,114063,Female,Loyal Customer,46,Business travel,Business,2139,5,5,5,5,4,5,4,4,4,5,4,4,4,3,118,127.0,satisfied +69440,88340,Female,Loyal Customer,45,Business travel,Business,2722,3,3,2,3,5,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +69441,19918,Female,Loyal Customer,48,Business travel,Business,296,4,2,4,4,5,4,4,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +69442,107149,Female,Loyal Customer,52,Business travel,Business,2270,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +69443,9189,Male,Loyal Customer,12,Personal Travel,Eco,363,1,5,1,4,4,1,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +69444,34616,Male,Loyal Customer,31,Business travel,Eco Plus,1598,5,4,4,4,5,5,5,5,5,4,4,5,2,5,0,0.0,satisfied +69445,52723,Male,Loyal Customer,25,Business travel,Business,406,3,5,2,5,3,3,3,3,3,5,3,2,2,3,0,18.0,neutral or dissatisfied +69446,124423,Female,disloyal Customer,26,Business travel,Eco,1044,3,3,3,1,2,3,2,2,4,4,5,2,3,2,3,0.0,neutral or dissatisfied +69447,75142,Female,Loyal Customer,58,Business travel,Business,1652,1,1,1,1,5,3,5,5,5,5,5,5,5,3,0,0.0,satisfied +69448,108097,Male,Loyal Customer,62,Business travel,Eco,849,2,1,1,1,2,2,2,2,2,4,3,1,3,2,31,46.0,neutral or dissatisfied +69449,43226,Male,Loyal Customer,26,Business travel,Eco Plus,472,4,2,2,2,4,4,3,4,4,3,1,3,1,4,2,1.0,satisfied +69450,61359,Male,Loyal Customer,51,Personal Travel,Eco Plus,602,2,2,2,3,5,2,5,5,2,3,3,4,4,5,8,0.0,neutral or dissatisfied +69451,34819,Female,Loyal Customer,10,Personal Travel,Eco,301,2,4,4,3,4,4,4,4,1,5,1,2,3,4,0,0.0,neutral or dissatisfied +69452,54113,Male,Loyal Customer,59,Business travel,Business,2377,1,4,4,4,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +69453,19671,Male,Loyal Customer,25,Personal Travel,Business,475,3,4,3,1,3,3,3,3,2,5,5,3,1,3,0,0.0,neutral or dissatisfied +69454,15221,Female,disloyal Customer,45,Business travel,Eco,416,3,0,3,2,2,3,2,2,5,1,3,4,4,2,18,1.0,neutral or dissatisfied +69455,76824,Female,Loyal Customer,52,Business travel,Business,1851,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +69456,18334,Female,Loyal Customer,48,Business travel,Business,554,1,1,1,1,2,3,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +69457,27837,Female,Loyal Customer,59,Personal Travel,Eco,680,2,5,2,1,1,4,3,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +69458,77527,Male,Loyal Customer,26,Business travel,Business,2320,3,3,3,3,2,2,2,2,4,2,4,5,4,2,0,0.0,satisfied +69459,20780,Female,Loyal Customer,48,Business travel,Business,2834,4,4,4,4,1,4,3,4,4,4,4,4,4,5,60,52.0,satisfied +69460,71729,Female,disloyal Customer,37,Business travel,Eco Plus,607,2,3,3,4,3,3,1,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +69461,92120,Female,Loyal Customer,49,Personal Travel,Eco,1535,3,3,3,4,3,3,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +69462,120135,Female,Loyal Customer,41,Personal Travel,Business,1475,4,4,5,2,4,5,4,5,5,5,5,3,5,5,21,5.0,satisfied +69463,36469,Female,Loyal Customer,37,Business travel,Business,3816,4,4,4,4,4,4,3,4,4,4,4,3,4,1,0,0.0,satisfied +69464,88066,Male,Loyal Customer,37,Business travel,Business,3667,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,9.0,satisfied +69465,116369,Male,Loyal Customer,38,Personal Travel,Eco,342,4,3,4,2,2,4,2,2,2,1,3,3,3,2,0,0.0,neutral or dissatisfied +69466,128761,Female,Loyal Customer,53,Business travel,Business,550,4,4,1,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +69467,49008,Male,Loyal Customer,29,Business travel,Business,1697,4,5,4,4,5,5,5,5,3,2,1,2,1,5,19,12.0,satisfied +69468,119747,Male,Loyal Customer,64,Personal Travel,Eco,1303,1,5,1,4,5,1,4,5,5,5,3,3,5,5,0,0.0,neutral or dissatisfied +69469,69581,Male,Loyal Customer,22,Personal Travel,Eco,2446,2,4,2,3,3,2,3,3,3,5,4,4,4,3,78,79.0,neutral or dissatisfied +69470,5896,Female,Loyal Customer,37,Business travel,Eco,108,3,4,4,4,3,3,3,3,3,1,3,3,4,3,19,8.0,neutral or dissatisfied +69471,127423,Male,Loyal Customer,58,Personal Travel,Eco,1009,2,5,2,4,4,2,2,4,5,5,2,1,1,4,0,0.0,neutral or dissatisfied +69472,23960,Male,Loyal Customer,25,Business travel,Business,2814,3,3,3,3,4,4,4,4,2,1,2,2,3,4,0,0.0,satisfied +69473,104913,Male,Loyal Customer,60,Personal Travel,Business,210,2,2,2,3,5,4,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +69474,44627,Female,Loyal Customer,52,Business travel,Business,2898,4,4,4,4,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +69475,34771,Female,disloyal Customer,23,Business travel,Eco,264,0,0,0,4,4,0,4,4,4,2,4,1,2,4,0,0.0,satisfied +69476,48046,Male,Loyal Customer,22,Business travel,Business,677,4,4,4,4,4,4,4,4,4,3,4,4,4,4,120,122.0,neutral or dissatisfied +69477,18434,Male,Loyal Customer,56,Business travel,Business,2757,3,3,3,3,3,5,4,4,4,4,5,4,4,5,28,11.0,satisfied +69478,118904,Male,Loyal Customer,59,Business travel,Business,3499,3,3,3,3,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +69479,73818,Male,disloyal Customer,26,Business travel,Business,794,3,4,4,3,5,4,3,5,2,2,3,3,3,5,14,71.0,neutral or dissatisfied +69480,106980,Female,Loyal Customer,45,Business travel,Eco,972,5,2,2,2,4,5,5,5,5,5,5,2,5,5,0,0.0,satisfied +69481,87682,Male,disloyal Customer,24,Business travel,Eco,206,5,4,5,1,2,5,4,2,2,3,1,4,2,2,6,3.0,satisfied +69482,30509,Male,Loyal Customer,50,Business travel,Eco,1620,3,4,4,4,3,3,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +69483,43644,Female,Loyal Customer,12,Personal Travel,Eco,1034,2,2,2,3,2,2,2,2,4,2,2,2,2,2,16,0.0,neutral or dissatisfied +69484,87666,Female,disloyal Customer,37,Business travel,Business,591,1,1,1,4,3,1,3,3,3,4,4,5,5,3,3,0.0,neutral or dissatisfied +69485,46667,Male,Loyal Customer,31,Business travel,Business,2363,2,5,5,5,2,2,2,2,3,5,4,2,4,2,14,11.0,neutral or dissatisfied +69486,67830,Female,disloyal Customer,19,Business travel,Eco,1235,4,4,4,4,3,4,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +69487,36607,Male,Loyal Customer,59,Business travel,Eco,1121,4,4,4,4,4,4,4,4,1,5,1,3,4,4,0,0.0,satisfied +69488,99145,Female,Loyal Customer,19,Business travel,Business,1617,2,2,2,2,5,5,4,5,4,3,5,5,4,5,0,0.0,satisfied +69489,116425,Female,Loyal Customer,37,Personal Travel,Eco,373,4,4,4,3,1,4,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +69490,58649,Female,disloyal Customer,35,Business travel,Eco,867,2,2,2,4,4,2,4,4,2,3,5,5,5,4,4,0.0,neutral or dissatisfied +69491,19069,Male,disloyal Customer,29,Business travel,Eco,569,4,3,4,3,2,4,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +69492,14639,Female,Loyal Customer,24,Business travel,Business,3453,4,4,4,4,5,5,5,5,1,3,5,2,5,5,0,0.0,satisfied +69493,51806,Male,Loyal Customer,46,Personal Travel,Eco,493,5,4,5,3,2,5,1,2,4,2,4,3,5,2,0,0.0,satisfied +69494,9415,Male,Loyal Customer,54,Business travel,Business,3648,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,5.0,satisfied +69495,88906,Male,Loyal Customer,40,Personal Travel,Eco,859,2,0,2,4,4,2,4,4,5,3,5,5,5,4,7,0.0,neutral or dissatisfied +69496,67648,Male,Loyal Customer,55,Business travel,Business,1188,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +69497,5366,Male,Loyal Customer,54,Business travel,Eco,812,3,1,1,1,3,3,3,3,4,5,3,4,3,3,3,0.0,neutral or dissatisfied +69498,108212,Male,Loyal Customer,25,Business travel,Business,777,2,2,2,2,2,2,2,2,1,2,3,3,3,2,0,0.0,neutral or dissatisfied +69499,45049,Male,Loyal Customer,39,Business travel,Business,2045,2,2,2,2,3,4,2,4,4,4,4,1,4,3,0,19.0,satisfied +69500,3222,Female,Loyal Customer,53,Business travel,Business,2739,5,1,1,1,5,2,3,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +69501,49374,Male,Loyal Customer,42,Business travel,Business,304,5,5,5,5,4,5,3,5,5,5,5,2,5,5,0,0.0,satisfied +69502,91606,Male,Loyal Customer,60,Business travel,Business,1340,1,1,3,1,5,4,5,4,4,4,4,5,4,3,8,2.0,satisfied +69503,6006,Male,Loyal Customer,23,Business travel,Business,3337,5,5,5,5,4,4,4,4,3,5,4,4,5,4,29,22.0,satisfied +69504,1663,Female,Loyal Customer,21,Personal Travel,Eco,435,3,5,4,3,3,4,4,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +69505,16084,Female,Loyal Customer,43,Business travel,Eco,303,4,2,2,2,5,5,3,3,3,4,3,4,3,3,0,11.0,satisfied +69506,6090,Male,Loyal Customer,15,Business travel,Eco Plus,691,3,5,5,5,3,3,2,3,3,3,4,1,4,3,8,0.0,neutral or dissatisfied +69507,17542,Female,disloyal Customer,22,Business travel,Eco,970,1,1,1,3,3,1,3,3,3,4,5,1,4,3,77,71.0,neutral or dissatisfied +69508,80674,Female,Loyal Customer,62,Personal Travel,Eco,821,3,1,3,4,1,3,4,3,3,3,3,4,3,4,0,2.0,neutral or dissatisfied +69509,112629,Male,Loyal Customer,30,Business travel,Business,1973,1,1,1,1,3,3,3,3,4,4,4,5,4,3,9,0.0,satisfied +69510,25125,Female,disloyal Customer,39,Business travel,Business,946,3,3,3,3,2,3,2,2,4,1,3,1,4,2,23,19.0,neutral or dissatisfied +69511,124143,Female,Loyal Customer,50,Business travel,Business,2194,3,2,3,3,5,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +69512,125507,Male,Loyal Customer,57,Personal Travel,Eco,666,4,2,4,3,2,4,1,2,4,1,3,2,4,2,6,2.0,neutral or dissatisfied +69513,107379,Female,Loyal Customer,66,Personal Travel,Business,468,2,5,5,2,4,5,5,3,3,5,3,4,3,3,65,70.0,neutral or dissatisfied +69514,2199,Female,Loyal Customer,31,Personal Travel,Eco,685,2,4,2,4,1,2,1,1,4,5,4,4,5,1,24,28.0,neutral or dissatisfied +69515,64866,Male,Loyal Customer,47,Business travel,Business,247,2,4,4,4,1,2,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +69516,16892,Female,Loyal Customer,52,Business travel,Business,3427,2,3,3,3,5,3,3,2,2,1,2,3,2,1,6,0.0,neutral or dissatisfied +69517,55770,Male,disloyal Customer,37,Business travel,Business,599,2,2,2,1,4,2,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +69518,22776,Male,Loyal Customer,35,Business travel,Eco,302,3,4,4,4,3,3,3,3,1,1,3,2,4,3,26,7.0,neutral or dissatisfied +69519,129079,Female,disloyal Customer,30,Business travel,Business,2342,2,2,2,4,2,4,4,3,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +69520,77445,Male,Loyal Customer,60,Business travel,Business,3652,3,3,3,3,3,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +69521,82442,Male,disloyal Customer,14,Business travel,Eco,502,2,1,2,4,1,2,1,1,1,5,4,1,3,1,0,16.0,neutral or dissatisfied +69522,20841,Female,disloyal Customer,16,Business travel,Eco,357,1,2,0,3,3,0,3,3,1,4,3,4,4,3,0,0.0,neutral or dissatisfied +69523,108479,Male,Loyal Customer,23,Business travel,Business,570,1,1,1,1,3,4,3,3,4,2,5,4,5,3,14,0.0,satisfied +69524,127698,Female,disloyal Customer,23,Business travel,Eco,1178,1,1,1,3,3,1,3,3,1,3,2,3,4,3,0,0.0,neutral or dissatisfied +69525,110280,Male,Loyal Customer,66,Personal Travel,Business,919,4,4,4,1,3,5,4,1,1,4,1,4,1,3,74,61.0,neutral or dissatisfied +69526,91561,Female,Loyal Customer,41,Personal Travel,Eco,680,2,4,2,2,4,2,4,4,3,3,4,3,4,4,43,21.0,neutral or dissatisfied +69527,3405,Male,disloyal Customer,30,Business travel,Business,213,2,2,2,4,1,2,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +69528,9395,Male,Loyal Customer,53,Personal Travel,Eco,372,3,3,3,3,5,3,1,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +69529,93860,Male,Loyal Customer,39,Business travel,Business,588,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +69530,15854,Male,Loyal Customer,59,Business travel,Eco,332,5,5,5,5,5,5,5,5,2,4,2,1,4,5,0,0.0,satisfied +69531,162,Male,Loyal Customer,14,Personal Travel,Eco,227,3,5,0,1,5,0,5,5,1,2,5,3,4,5,0,0.0,neutral or dissatisfied +69532,73349,Female,Loyal Customer,31,Business travel,Business,1005,1,3,3,3,1,1,1,1,4,4,3,3,3,1,0,0.0,neutral or dissatisfied +69533,69671,Male,Loyal Customer,31,Personal Travel,Eco,569,4,5,4,5,4,4,4,4,4,2,5,4,4,4,26,13.0,neutral or dissatisfied +69534,92514,Male,Loyal Customer,55,Personal Travel,Eco,1919,2,3,2,3,4,2,4,4,1,5,3,2,3,4,0,0.0,neutral or dissatisfied +69535,85259,Male,Loyal Customer,26,Personal Travel,Eco,874,3,3,3,3,4,3,1,4,1,1,2,3,3,4,2,2.0,neutral or dissatisfied +69536,33307,Female,Loyal Customer,54,Business travel,Eco Plus,101,5,4,4,4,2,4,5,5,5,5,5,2,5,4,0,3.0,satisfied +69537,122931,Female,disloyal Customer,33,Business travel,Business,631,3,3,3,1,3,3,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +69538,117484,Male,Loyal Customer,48,Business travel,Business,2400,4,4,4,4,4,4,5,4,4,4,4,4,4,4,10,0.0,satisfied +69539,9219,Female,Loyal Customer,46,Business travel,Business,157,5,5,5,5,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +69540,105431,Male,Loyal Customer,37,Personal Travel,Eco,452,2,5,2,2,2,2,2,2,3,3,4,5,5,2,18,4.0,neutral or dissatisfied +69541,4710,Female,disloyal Customer,33,Business travel,Business,327,2,2,2,3,4,2,4,4,5,5,4,5,4,4,79,99.0,neutral or dissatisfied +69542,110614,Male,Loyal Customer,8,Personal Travel,Eco Plus,488,1,4,1,2,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +69543,74804,Female,Loyal Customer,45,Business travel,Business,1431,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +69544,98172,Male,Loyal Customer,58,Business travel,Business,2214,4,4,4,4,2,4,5,5,5,5,5,3,5,3,86,81.0,satisfied +69545,47669,Female,disloyal Customer,36,Business travel,Eco,1104,4,4,4,3,1,4,1,1,4,3,1,4,2,1,4,0.0,neutral or dissatisfied +69546,37900,Female,disloyal Customer,36,Business travel,Eco,597,3,0,2,3,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +69547,65778,Male,Loyal Customer,56,Business travel,Business,1389,2,3,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +69548,129231,Male,Loyal Customer,38,Business travel,Business,1504,1,4,4,4,4,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +69549,440,Female,Loyal Customer,66,Personal Travel,Business,396,1,5,4,4,4,5,5,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +69550,1352,Female,Loyal Customer,60,Business travel,Business,2186,4,3,3,3,5,4,3,2,2,2,4,2,2,3,0,0.0,neutral or dissatisfied +69551,37247,Male,Loyal Customer,59,Personal Travel,Business,1069,2,5,2,3,3,5,4,1,1,2,1,4,1,3,11,10.0,neutral or dissatisfied +69552,75049,Female,Loyal Customer,21,Business travel,Business,1592,4,4,4,4,5,5,5,5,4,4,3,3,5,5,0,0.0,satisfied +69553,108798,Male,Loyal Customer,31,Personal Travel,Eco,581,3,5,3,5,3,3,3,3,3,5,5,4,5,3,3,13.0,neutral or dissatisfied +69554,95606,Female,Loyal Customer,44,Business travel,Eco,756,4,5,5,5,3,3,4,4,4,4,4,2,4,3,7,6.0,neutral or dissatisfied +69555,52975,Male,Loyal Customer,27,Personal Travel,Eco,2306,3,4,3,5,5,3,3,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +69556,75793,Male,Loyal Customer,38,Personal Travel,Eco,868,3,3,3,3,1,3,1,1,1,4,3,2,2,1,0,0.0,neutral or dissatisfied +69557,21627,Female,disloyal Customer,17,Business travel,Eco,780,2,2,2,4,2,2,2,2,2,2,3,4,4,2,16,12.0,neutral or dissatisfied +69558,1288,Female,Loyal Customer,7,Personal Travel,Eco,309,1,3,5,3,4,5,4,4,1,5,4,1,2,4,29,21.0,neutral or dissatisfied +69559,88156,Male,Loyal Customer,50,Business travel,Eco,515,3,4,4,4,3,3,3,3,1,1,3,3,4,3,0,0.0,neutral or dissatisfied +69560,17346,Female,Loyal Customer,38,Business travel,Business,2235,1,1,1,1,2,4,4,5,5,5,5,1,5,3,41,51.0,satisfied +69561,87941,Female,Loyal Customer,21,Personal Travel,Business,444,2,2,4,3,2,4,3,2,2,2,3,3,3,2,0,0.0,neutral or dissatisfied +69562,116510,Female,disloyal Customer,63,Personal Travel,Eco,446,3,5,3,3,5,3,1,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +69563,8432,Female,Loyal Customer,29,Personal Travel,Eco,862,2,1,2,3,5,2,5,5,2,5,3,2,3,5,42,43.0,neutral or dissatisfied +69564,65145,Male,Loyal Customer,56,Personal Travel,Eco,190,2,5,0,4,3,0,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +69565,83045,Male,Loyal Customer,39,Business travel,Business,3633,4,4,3,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +69566,109508,Male,Loyal Customer,25,Business travel,Business,992,1,1,5,1,1,1,1,1,1,3,3,4,3,1,11,7.0,neutral or dissatisfied +69567,30037,Male,Loyal Customer,65,Business travel,Business,2610,3,5,5,5,3,3,3,2,3,4,3,3,3,3,259,256.0,neutral or dissatisfied +69568,70611,Male,disloyal Customer,39,Business travel,Business,817,3,3,3,3,4,3,4,4,4,3,4,3,3,4,0,0.0,neutral or dissatisfied +69569,129745,Male,Loyal Customer,63,Business travel,Eco,337,4,1,1,1,4,4,4,4,2,5,5,3,5,4,0,0.0,satisfied +69570,124830,Male,Loyal Customer,17,Personal Travel,Eco,280,1,5,1,3,1,1,1,1,2,3,3,4,1,1,0,0.0,neutral or dissatisfied +69571,64075,Male,Loyal Customer,66,Personal Travel,Eco,919,5,4,5,4,2,5,2,2,4,4,1,1,4,2,8,0.0,satisfied +69572,105141,Male,disloyal Customer,37,Business travel,Business,220,1,1,1,3,4,1,5,4,2,4,3,3,4,4,45,43.0,neutral or dissatisfied +69573,105403,Male,Loyal Customer,38,Personal Travel,Eco,369,3,3,3,3,4,3,5,4,5,3,1,4,3,4,26,42.0,neutral or dissatisfied +69574,76061,Female,Loyal Customer,50,Business travel,Business,2005,3,3,3,3,5,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +69575,30679,Male,Loyal Customer,32,Business travel,Business,680,3,1,1,1,3,3,3,3,2,5,3,4,3,3,0,6.0,neutral or dissatisfied +69576,12828,Male,Loyal Customer,19,Business travel,Business,489,3,3,3,3,3,3,3,3,3,1,2,3,3,3,36,31.0,neutral or dissatisfied +69577,78231,Male,Loyal Customer,18,Personal Travel,Eco,259,3,5,3,4,2,3,3,2,4,1,1,2,4,2,1,0.0,neutral or dissatisfied +69578,87648,Male,Loyal Customer,44,Business travel,Business,591,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +69579,9983,Male,Loyal Customer,29,Personal Travel,Eco,457,2,4,2,3,1,2,1,1,3,3,4,4,4,1,61,61.0,neutral or dissatisfied +69580,116618,Female,disloyal Customer,38,Business travel,Business,362,1,1,1,1,3,1,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +69581,115654,Female,disloyal Customer,39,Business travel,Business,296,3,3,3,4,3,3,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +69582,53595,Male,Loyal Customer,40,Business travel,Business,3801,3,3,3,3,5,5,5,1,3,5,4,5,4,5,0,0.0,satisfied +69583,113496,Male,Loyal Customer,59,Business travel,Business,2011,2,5,5,5,2,2,2,2,2,2,2,3,2,1,26,13.0,neutral or dissatisfied +69584,7648,Female,Loyal Customer,51,Business travel,Business,604,1,1,1,1,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +69585,74343,Female,Loyal Customer,31,Personal Travel,Business,1126,2,2,2,3,3,2,3,3,2,3,4,3,3,3,5,1.0,neutral or dissatisfied +69586,1614,Male,disloyal Customer,41,Business travel,Eco,568,4,0,4,5,5,4,5,5,4,3,4,1,3,5,0,8.0,satisfied +69587,31140,Female,Loyal Customer,70,Personal Travel,Eco,991,1,4,1,1,3,4,4,5,5,1,5,3,5,3,27,41.0,neutral or dissatisfied +69588,86459,Male,Loyal Customer,32,Business travel,Business,3851,1,5,5,5,1,1,1,1,3,2,3,4,3,1,37,50.0,neutral or dissatisfied +69589,112735,Male,Loyal Customer,60,Business travel,Business,723,5,5,5,5,5,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +69590,33806,Female,Loyal Customer,36,Business travel,Eco,1521,5,1,2,1,5,5,5,5,5,5,1,5,4,5,30,30.0,satisfied +69591,12896,Female,Loyal Customer,49,Business travel,Business,3517,1,1,1,1,5,5,2,4,4,4,4,1,4,5,27,28.0,satisfied +69592,14632,Male,Loyal Customer,38,Business travel,Eco,363,5,3,1,1,5,4,5,5,1,5,5,4,1,5,0,0.0,satisfied +69593,103200,Male,Loyal Customer,56,Business travel,Business,814,4,4,4,4,2,4,5,4,4,4,4,5,4,4,37,21.0,satisfied +69594,120563,Female,Loyal Customer,24,Personal Travel,Eco,2176,2,2,2,3,1,2,5,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +69595,105657,Female,Loyal Customer,33,Business travel,Business,2235,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +69596,48362,Female,Loyal Customer,37,Business travel,Business,522,4,1,1,1,2,2,2,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +69597,109211,Female,Loyal Customer,31,Business travel,Business,616,1,4,4,4,1,2,1,1,4,3,3,3,3,1,51,41.0,neutral or dissatisfied +69598,8217,Female,Loyal Customer,38,Business travel,Business,294,3,3,2,3,1,3,1,4,4,4,4,5,4,2,2,0.0,satisfied +69599,112727,Male,Loyal Customer,21,Personal Travel,Eco,672,1,1,0,3,2,0,2,2,4,1,3,1,4,2,54,48.0,neutral or dissatisfied +69600,68411,Male,disloyal Customer,25,Business travel,Eco,645,3,0,3,5,3,3,3,3,4,2,4,5,3,3,0,0.0,neutral or dissatisfied +69601,31715,Male,Loyal Customer,15,Personal Travel,Eco,862,3,3,3,4,4,3,4,4,3,3,3,4,3,4,10,1.0,neutral or dissatisfied +69602,67004,Male,Loyal Customer,24,Business travel,Eco,985,2,1,1,1,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +69603,88065,Male,Loyal Customer,46,Business travel,Business,515,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +69604,118500,Male,Loyal Customer,57,Business travel,Business,3852,3,3,3,3,5,4,5,4,4,4,4,4,4,3,89,75.0,satisfied +69605,94665,Female,Loyal Customer,44,Business travel,Business,2422,2,5,5,5,4,4,3,2,2,2,2,3,2,2,2,0.0,neutral or dissatisfied +69606,57810,Male,disloyal Customer,31,Business travel,Eco Plus,1235,2,2,2,3,5,2,5,5,1,4,3,4,3,5,55,21.0,neutral or dissatisfied +69607,22007,Male,Loyal Customer,36,Personal Travel,Eco,503,2,5,4,4,5,4,5,5,4,3,4,3,5,5,0,,neutral or dissatisfied +69608,87438,Male,Loyal Customer,40,Business travel,Business,3712,5,5,5,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +69609,83614,Male,Loyal Customer,63,Business travel,Business,409,1,3,3,3,4,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +69610,91494,Female,Loyal Customer,54,Business travel,Business,3910,4,4,1,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +69611,76337,Female,Loyal Customer,69,Personal Travel,Business,954,1,5,1,2,4,3,1,2,2,1,5,1,2,3,18,17.0,neutral or dissatisfied +69612,23898,Male,Loyal Customer,48,Business travel,Eco,589,3,1,1,1,4,3,4,4,5,4,3,5,4,4,0,0.0,satisfied +69613,118005,Female,Loyal Customer,40,Business travel,Business,1037,2,2,2,2,3,5,4,5,5,5,5,3,5,3,48,35.0,satisfied +69614,110181,Female,Loyal Customer,19,Personal Travel,Eco,1056,2,4,2,4,5,2,5,5,1,1,3,5,3,5,22,32.0,neutral or dissatisfied +69615,38050,Male,Loyal Customer,48,Business travel,Eco,1121,5,1,1,1,5,5,5,5,1,5,2,4,1,5,25,27.0,satisfied +69616,102947,Female,Loyal Customer,54,Business travel,Business,719,1,1,1,1,2,5,4,5,5,5,5,3,5,3,3,0.0,satisfied +69617,46660,Female,Loyal Customer,65,Business travel,Business,2650,2,2,2,2,4,4,4,3,3,3,2,3,3,3,9,19.0,neutral or dissatisfied +69618,49782,Female,Loyal Customer,51,Business travel,Business,3479,5,5,5,5,2,3,3,4,4,4,5,3,4,3,0,0.0,satisfied +69619,1226,Female,Loyal Customer,67,Personal Travel,Eco,164,2,5,2,4,4,4,5,2,2,2,1,4,2,3,17,27.0,neutral or dissatisfied +69620,125263,Female,Loyal Customer,43,Business travel,Business,1488,5,2,5,5,2,4,5,4,4,4,4,4,4,5,3,11.0,satisfied +69621,118163,Female,disloyal Customer,27,Business travel,Business,1444,5,5,5,1,5,5,5,5,3,2,5,5,4,5,71,47.0,satisfied +69622,14458,Female,disloyal Customer,15,Business travel,Eco,674,3,3,3,3,3,4,3,1,4,3,3,3,1,3,187,160.0,neutral or dissatisfied +69623,59095,Male,Loyal Customer,37,Personal Travel,Eco,1846,3,1,3,4,5,3,5,5,2,4,3,2,3,5,1,0.0,neutral or dissatisfied +69624,67613,Male,Loyal Customer,25,Business travel,Business,1235,1,1,1,1,2,2,2,2,4,3,4,5,4,2,12,1.0,satisfied +69625,128086,Female,Loyal Customer,9,Business travel,Business,2917,3,3,3,3,4,4,4,4,4,4,5,4,3,4,0,0.0,satisfied +69626,54002,Female,Loyal Customer,8,Personal Travel,Eco Plus,1825,3,1,3,3,4,3,2,4,4,3,3,4,3,4,0,0.0,neutral or dissatisfied +69627,97475,Male,Loyal Customer,54,Business travel,Business,484,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,1.0,satisfied +69628,48129,Female,disloyal Customer,25,Business travel,Eco,259,3,2,3,4,4,3,4,4,2,2,3,2,3,4,70,66.0,neutral or dissatisfied +69629,5725,Female,Loyal Customer,31,Business travel,Eco Plus,234,2,1,1,1,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +69630,19911,Male,Loyal Customer,59,Business travel,Eco,315,3,4,4,4,3,3,3,3,4,5,3,4,3,3,118,113.0,neutral or dissatisfied +69631,47758,Female,Loyal Customer,38,Business travel,Business,451,3,3,3,3,2,4,5,5,5,5,5,5,5,3,21,11.0,satisfied +69632,106011,Male,Loyal Customer,50,Personal Travel,Eco,1999,3,1,4,4,2,4,2,2,1,2,2,1,3,2,12,22.0,neutral or dissatisfied +69633,25895,Female,Loyal Customer,62,Personal Travel,Eco,907,2,3,2,3,2,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +69634,115612,Male,Loyal Customer,53,Business travel,Eco,337,3,5,5,5,3,3,3,3,1,4,2,4,3,3,1,0.0,neutral or dissatisfied +69635,14221,Female,Loyal Customer,16,Personal Travel,Eco,620,2,3,2,2,4,2,4,4,2,2,3,2,3,4,0,10.0,neutral or dissatisfied +69636,53402,Male,disloyal Customer,24,Business travel,Eco,1247,3,3,3,2,4,3,1,4,5,5,3,4,4,4,0,0.0,neutral or dissatisfied +69637,127234,Female,Loyal Customer,68,Personal Travel,Eco,1460,4,5,4,1,3,4,4,5,5,4,3,4,5,3,52,36.0,neutral or dissatisfied +69638,70708,Female,Loyal Customer,39,Business travel,Business,3406,2,2,5,2,4,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +69639,91293,Male,Loyal Customer,28,Business travel,Business,1790,0,0,0,2,5,3,3,5,5,4,5,5,4,5,0,0.0,satisfied +69640,7831,Male,Loyal Customer,22,Personal Travel,Eco,710,4,4,4,2,2,4,2,2,1,3,5,4,3,2,0,0.0,satisfied +69641,692,Male,disloyal Customer,26,Business travel,Business,164,2,5,3,4,5,3,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +69642,58893,Male,Loyal Customer,48,Business travel,Business,888,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +69643,73892,Female,Loyal Customer,29,Business travel,Business,2585,2,2,2,2,4,4,4,5,3,4,4,4,4,4,0,0.0,satisfied +69644,72086,Male,Loyal Customer,69,Personal Travel,Eco,2556,5,4,5,1,4,5,3,4,1,3,5,3,1,4,0,0.0,satisfied +69645,126485,Female,Loyal Customer,48,Business travel,Eco,1788,3,3,3,3,5,3,3,4,4,3,4,4,4,4,0,16.0,neutral or dissatisfied +69646,99398,Male,Loyal Customer,68,Business travel,Business,3190,1,1,5,1,3,4,4,3,3,4,3,4,3,5,7,2.0,satisfied +69647,51239,Female,Loyal Customer,59,Business travel,Eco Plus,308,5,4,4,4,4,3,5,5,5,5,5,4,5,1,117,110.0,satisfied +69648,11289,Female,Loyal Customer,16,Personal Travel,Eco,224,3,5,3,2,1,3,2,1,4,5,4,5,5,1,0,3.0,neutral or dissatisfied +69649,61717,Male,disloyal Customer,25,Business travel,Business,1379,5,0,5,3,3,5,1,3,4,4,4,3,4,3,16,0.0,satisfied +69650,71598,Male,Loyal Customer,25,Business travel,Business,2791,3,2,2,2,3,3,3,3,1,4,2,4,3,3,0,0.0,neutral or dissatisfied +69651,93424,Female,Loyal Customer,22,Business travel,Eco,605,2,1,1,1,2,2,2,2,4,2,4,2,3,2,8,0.0,neutral or dissatisfied +69652,6285,Male,Loyal Customer,45,Personal Travel,Eco,693,2,4,2,2,5,2,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +69653,129727,Female,Loyal Customer,43,Business travel,Business,2279,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +69654,71906,Female,Loyal Customer,51,Personal Travel,Eco,1744,3,4,3,1,5,5,4,5,5,3,5,4,5,5,8,10.0,neutral or dissatisfied +69655,7480,Female,Loyal Customer,52,Personal Travel,Business,925,2,4,3,5,2,1,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +69656,2310,Male,Loyal Customer,17,Business travel,Business,2233,4,4,4,4,4,4,4,4,5,5,1,3,3,4,0,0.0,satisfied +69657,9098,Male,Loyal Customer,31,Personal Travel,Eco Plus,212,1,0,1,3,4,1,4,4,5,3,5,4,4,4,101,97.0,neutral or dissatisfied +69658,99353,Female,Loyal Customer,59,Personal Travel,Eco,1771,4,2,4,3,2,3,3,3,3,4,3,1,3,2,0,1.0,neutral or dissatisfied +69659,61648,Female,Loyal Customer,46,Business travel,Business,1609,2,3,2,2,5,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +69660,69595,Female,Loyal Customer,37,Personal Travel,Eco,2475,3,4,3,2,3,5,5,4,4,3,4,5,3,5,0,5.0,neutral or dissatisfied +69661,45564,Female,Loyal Customer,66,Business travel,Business,799,3,5,2,5,1,3,4,3,3,3,3,1,3,3,53,48.0,neutral or dissatisfied +69662,110913,Female,disloyal Customer,29,Business travel,Eco,406,4,1,4,4,1,4,1,1,2,1,3,4,4,1,47,39.0,neutral or dissatisfied +69663,112386,Female,Loyal Customer,24,Business travel,Business,819,3,3,3,3,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +69664,84293,Female,Loyal Customer,55,Business travel,Business,3874,4,5,5,5,2,3,4,4,4,4,4,3,4,1,4,0.0,neutral or dissatisfied +69665,103822,Male,disloyal Customer,26,Business travel,Business,1072,0,0,0,5,2,0,1,2,4,4,4,4,5,2,3,0.0,satisfied +69666,125983,Female,disloyal Customer,20,Business travel,Business,468,1,4,1,4,2,1,2,2,4,1,4,3,3,2,0,1.0,neutral or dissatisfied +69667,92335,Male,Loyal Customer,31,Business travel,Business,2399,3,3,3,3,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +69668,10675,Male,Loyal Customer,40,Business travel,Business,2860,2,2,2,2,2,4,4,5,5,5,4,4,5,3,17,28.0,satisfied +69669,117702,Female,disloyal Customer,23,Business travel,Eco,2075,2,2,2,3,4,2,4,4,4,3,3,1,4,4,0,0.0,neutral or dissatisfied +69670,86440,Male,Loyal Customer,45,Business travel,Eco,712,2,2,2,2,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +69671,111820,Female,Loyal Customer,22,Personal Travel,Business,1605,4,4,4,4,4,4,4,4,4,4,3,5,4,4,53,38.0,neutral or dissatisfied +69672,13079,Female,disloyal Customer,25,Business travel,Business,562,2,0,2,1,4,2,4,4,5,5,4,5,5,4,6,0.0,neutral or dissatisfied +69673,115474,Male,disloyal Customer,25,Business travel,Business,446,1,4,1,1,1,1,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +69674,88329,Female,Loyal Customer,71,Business travel,Business,545,3,3,3,3,5,2,3,3,3,3,3,4,3,3,1,21.0,neutral or dissatisfied +69675,16185,Female,Loyal Customer,62,Business travel,Business,2208,1,1,1,1,5,4,5,4,4,4,4,5,4,2,0,0.0,satisfied +69676,105341,Male,disloyal Customer,23,Business travel,Eco,409,1,2,1,3,3,1,3,3,1,4,4,2,3,3,15,15.0,neutral or dissatisfied +69677,63560,Male,Loyal Customer,58,Personal Travel,Eco Plus,1009,3,4,3,4,1,3,1,1,4,2,5,2,1,1,0,0.0,neutral or dissatisfied +69678,53642,Female,Loyal Customer,21,Personal Travel,Eco,1874,4,1,4,2,3,4,3,3,4,4,3,3,3,3,0,19.0,neutral or dissatisfied +69679,43597,Female,Loyal Customer,68,Business travel,Business,3302,3,5,5,5,5,3,4,4,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +69680,27607,Female,Loyal Customer,51,Personal Travel,Eco,978,4,4,4,1,2,5,5,3,3,4,1,5,3,5,0,0.0,neutral or dissatisfied +69681,80584,Female,Loyal Customer,28,Personal Travel,Eco,1747,2,5,2,1,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +69682,103376,Female,Loyal Customer,42,Business travel,Business,3927,3,1,3,1,2,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +69683,55321,Male,Loyal Customer,49,Business travel,Business,1325,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +69684,6608,Female,Loyal Customer,45,Personal Travel,Eco,473,3,1,3,4,4,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +69685,49090,Male,Loyal Customer,42,Business travel,Business,3762,2,2,2,2,5,5,1,5,5,5,4,1,5,2,0,0.0,satisfied +69686,69384,Male,disloyal Customer,24,Business travel,Eco,1096,3,3,3,4,1,3,1,1,2,5,4,2,3,1,0,0.0,neutral or dissatisfied +69687,6803,Male,Loyal Customer,16,Business travel,Business,223,1,1,1,1,4,4,4,4,5,3,3,4,5,4,2,0.0,satisfied +69688,87558,Female,Loyal Customer,57,Business travel,Business,432,5,5,4,5,5,4,4,5,5,5,5,5,5,5,11,1.0,satisfied +69689,37326,Female,disloyal Customer,45,Business travel,Eco,1165,3,3,3,2,3,3,1,3,2,5,3,3,3,3,25,7.0,neutral or dissatisfied +69690,104426,Female,Loyal Customer,57,Business travel,Business,1956,4,4,4,4,2,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +69691,12268,Female,disloyal Customer,34,Business travel,Eco,253,1,0,1,2,2,1,4,2,4,3,4,2,2,2,0,0.0,neutral or dissatisfied +69692,30275,Female,Loyal Customer,35,Personal Travel,Eco,1024,3,5,3,2,2,3,2,2,4,4,4,4,5,2,20,15.0,neutral or dissatisfied +69693,125234,Female,Loyal Customer,55,Business travel,Eco,1149,1,4,4,4,3,3,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +69694,90000,Male,Loyal Customer,33,Business travel,Business,2456,4,4,4,4,4,4,4,4,3,5,5,4,4,4,33,24.0,satisfied +69695,7920,Male,Loyal Customer,55,Personal Travel,Eco,1020,3,0,2,4,4,2,4,4,3,4,4,3,4,4,8,16.0,neutral or dissatisfied +69696,9571,Female,Loyal Customer,35,Business travel,Eco,288,1,5,5,5,1,1,1,1,3,2,2,2,2,1,66,61.0,neutral or dissatisfied +69697,108761,Male,Loyal Customer,57,Business travel,Business,2659,5,5,5,5,5,5,5,4,4,4,4,5,4,4,52,36.0,satisfied +69698,10449,Female,Loyal Customer,35,Business travel,Business,3562,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +69699,9259,Male,Loyal Customer,54,Business travel,Business,157,3,3,3,3,2,4,4,5,5,5,4,4,5,4,0,2.0,satisfied +69700,19801,Male,Loyal Customer,39,Personal Travel,Eco Plus,760,3,5,3,4,4,3,2,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +69701,88791,Male,Loyal Customer,56,Business travel,Business,1946,5,1,5,5,3,5,4,2,2,2,2,4,2,5,5,2.0,satisfied +69702,109137,Male,Loyal Customer,58,Business travel,Business,2203,1,3,3,3,3,2,3,1,1,1,1,2,1,2,30,36.0,neutral or dissatisfied +69703,122371,Female,disloyal Customer,18,Business travel,Eco,529,3,3,3,4,5,3,1,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +69704,48494,Male,Loyal Customer,21,Business travel,Eco,948,5,1,1,1,5,5,5,5,4,2,1,5,1,5,0,0.0,satisfied +69705,48996,Female,Loyal Customer,37,Business travel,Eco,373,3,2,3,2,3,3,3,3,1,4,2,2,1,3,0,0.0,satisfied +69706,49948,Male,Loyal Customer,52,Business travel,Business,110,0,3,0,3,5,4,3,1,1,1,1,3,1,4,0,6.0,satisfied +69707,124887,Female,Loyal Customer,34,Business travel,Business,728,1,1,1,1,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +69708,113365,Female,Loyal Customer,57,Business travel,Business,1771,1,1,1,1,3,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +69709,43787,Female,disloyal Customer,22,Business travel,Eco,223,1,4,1,3,5,1,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +69710,125614,Female,Loyal Customer,45,Business travel,Business,899,3,5,5,5,2,3,3,3,3,3,3,3,3,4,19,43.0,neutral or dissatisfied +69711,104353,Male,Loyal Customer,53,Business travel,Business,409,4,4,4,4,5,4,5,3,3,3,3,4,3,3,64,45.0,satisfied +69712,6957,Female,disloyal Customer,30,Business travel,Eco Plus,588,4,4,4,4,4,4,5,4,2,1,3,1,4,4,24,19.0,neutral or dissatisfied +69713,117418,Female,Loyal Customer,58,Business travel,Business,1460,5,5,5,5,5,5,4,5,5,5,5,4,5,3,4,5.0,satisfied +69714,42930,Female,Loyal Customer,41,Business travel,Business,192,4,3,5,3,4,4,4,2,2,2,4,1,2,3,0,0.0,neutral or dissatisfied +69715,83724,Male,Loyal Customer,55,Business travel,Business,1520,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +69716,42466,Male,Loyal Customer,52,Business travel,Business,429,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +69717,5534,Female,disloyal Customer,17,Business travel,Eco,404,3,0,3,2,1,3,1,1,3,3,5,1,1,1,0,0.0,neutral or dissatisfied +69718,39757,Female,disloyal Customer,51,Business travel,Eco,546,1,4,1,3,4,1,4,4,4,2,2,5,3,4,0,0.0,neutral or dissatisfied +69719,87998,Male,Loyal Customer,56,Business travel,Business,1621,4,4,4,4,4,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +69720,6310,Male,Loyal Customer,41,Business travel,Business,1926,3,3,3,3,5,4,4,4,4,4,4,3,4,5,2,18.0,satisfied +69721,31343,Female,Loyal Customer,30,Business travel,Business,1069,4,4,4,4,5,5,5,5,5,2,4,2,4,5,8,7.0,satisfied +69722,70032,Female,Loyal Customer,42,Business travel,Business,3299,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +69723,80719,Male,Loyal Customer,18,Personal Travel,Eco,920,1,5,1,3,4,1,2,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +69724,47765,Male,Loyal Customer,42,Business travel,Eco,834,3,2,2,2,3,3,3,3,2,1,4,3,3,3,0,11.0,neutral or dissatisfied +69725,88028,Female,Loyal Customer,45,Business travel,Business,2948,1,1,1,1,2,5,5,4,4,4,4,3,4,5,97,100.0,satisfied +69726,33446,Female,Loyal Customer,40,Personal Travel,Eco,2556,2,3,2,3,2,1,1,2,1,3,2,1,4,1,0,25.0,neutral or dissatisfied +69727,104650,Female,Loyal Customer,40,Personal Travel,Eco,1754,3,1,3,3,5,3,5,5,2,5,3,2,3,5,27,34.0,neutral or dissatisfied +69728,44519,Female,Loyal Customer,60,Business travel,Business,3495,0,4,0,3,5,3,5,1,1,1,1,1,1,1,0,0.0,satisfied +69729,57562,Male,Loyal Customer,52,Business travel,Business,1597,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +69730,73002,Female,Loyal Customer,12,Personal Travel,Eco,1096,1,4,1,3,1,1,1,1,4,4,3,3,4,1,0,0.0,neutral or dissatisfied +69731,15984,Male,Loyal Customer,35,Business travel,Eco,780,5,2,2,2,5,5,5,5,4,4,2,4,1,5,30,39.0,satisfied +69732,37102,Male,Loyal Customer,39,Business travel,Business,1046,4,4,4,4,1,1,5,4,4,5,4,4,4,5,23,42.0,satisfied +69733,92109,Female,Loyal Customer,21,Personal Travel,Eco,1517,3,5,3,2,4,3,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +69734,95672,Male,Loyal Customer,61,Personal Travel,Eco,1131,3,4,3,2,4,3,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +69735,108621,Male,Loyal Customer,57,Personal Travel,Eco,813,1,0,1,3,1,1,1,1,1,1,5,2,5,1,44,34.0,neutral or dissatisfied +69736,105814,Female,Loyal Customer,50,Personal Travel,Eco,919,3,4,4,4,2,4,3,2,2,4,2,4,2,4,24,32.0,neutral or dissatisfied +69737,61412,Female,Loyal Customer,12,Personal Travel,Eco,679,3,4,3,4,3,3,3,3,4,4,4,3,5,3,80,70.0,neutral or dissatisfied +69738,113493,Female,disloyal Customer,38,Business travel,Business,223,4,5,5,2,4,5,4,4,4,3,4,3,5,4,0,0.0,satisfied +69739,57198,Male,Loyal Customer,48,Business travel,Business,1514,1,1,1,1,2,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +69740,44917,Female,Loyal Customer,16,Business travel,Business,1626,3,3,3,3,4,4,4,4,5,3,5,3,2,4,0,0.0,satisfied +69741,118595,Male,Loyal Customer,40,Business travel,Business,3938,4,4,4,4,2,5,5,4,4,4,4,3,4,5,13,0.0,satisfied +69742,122307,Female,Loyal Customer,47,Personal Travel,Eco,544,3,3,3,4,3,3,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +69743,126994,Female,disloyal Customer,27,Business travel,Eco,647,4,0,4,4,1,4,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +69744,14462,Male,Loyal Customer,32,Personal Travel,Eco,674,3,5,3,3,5,3,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +69745,6425,Female,Loyal Customer,60,Personal Travel,Eco,296,4,1,4,1,2,1,2,2,2,4,2,4,2,3,62,59.0,neutral or dissatisfied +69746,107157,Female,Loyal Customer,43,Business travel,Business,1707,3,4,4,4,1,4,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +69747,85958,Male,disloyal Customer,27,Business travel,Business,528,3,3,3,1,4,3,4,4,5,5,5,4,5,4,46,20.0,neutral or dissatisfied +69748,23169,Female,Loyal Customer,56,Personal Travel,Eco,223,1,1,1,3,1,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +69749,3505,Female,Loyal Customer,7,Personal Travel,Business,968,4,4,4,3,1,4,1,1,5,4,4,3,4,1,24,10.0,neutral or dissatisfied +69750,96463,Female,Loyal Customer,60,Business travel,Business,2773,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +69751,46323,Male,Loyal Customer,58,Business travel,Business,1546,3,3,3,3,1,5,2,3,3,3,3,1,3,4,0,0.0,satisfied +69752,43906,Female,Loyal Customer,13,Personal Travel,Eco,114,1,1,0,2,4,0,4,4,2,1,2,4,2,4,0,6.0,neutral or dissatisfied +69753,51663,Female,Loyal Customer,23,Business travel,Business,3480,4,3,3,3,4,4,4,4,3,5,4,2,4,4,10,8.0,neutral or dissatisfied +69754,76575,Male,Loyal Customer,52,Business travel,Business,2645,5,5,5,5,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +69755,13187,Female,Loyal Customer,34,Business travel,Business,419,4,4,4,4,4,4,2,4,4,4,4,5,4,3,0,0.0,satisfied +69756,82509,Female,disloyal Customer,48,Business travel,Business,1345,5,4,4,3,2,5,2,2,5,5,4,3,5,2,0,6.0,satisfied +69757,60128,Female,Loyal Customer,53,Business travel,Business,3594,4,4,2,4,3,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +69758,5206,Male,Loyal Customer,45,Business travel,Business,1809,2,2,2,2,5,5,4,1,1,2,1,5,1,5,0,0.0,satisfied +69759,60897,Male,Loyal Customer,22,Personal Travel,Eco,420,3,4,3,1,3,3,3,3,5,2,2,2,3,3,0,0.0,neutral or dissatisfied +69760,64560,Female,disloyal Customer,39,Business travel,Business,224,3,3,3,4,2,3,2,2,4,5,5,3,5,2,0,1.0,neutral or dissatisfied +69761,75120,Female,Loyal Customer,48,Business travel,Business,1744,2,3,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +69762,22197,Female,Loyal Customer,39,Personal Travel,Eco,565,0,4,1,3,3,1,1,3,4,2,5,4,5,3,0,0.0,satisfied +69763,87609,Male,Loyal Customer,26,Business travel,Business,2651,3,3,3,3,3,3,3,3,4,2,5,5,5,3,0,3.0,satisfied +69764,58691,Female,Loyal Customer,29,Personal Travel,Eco,299,4,5,4,2,1,4,5,1,3,3,4,3,4,1,2,4.0,satisfied +69765,92982,Female,disloyal Customer,24,Business travel,Eco,738,1,1,1,1,3,1,3,3,5,3,5,4,5,3,31,18.0,neutral or dissatisfied +69766,110764,Male,Loyal Customer,40,Business travel,Business,2723,2,2,2,2,4,5,4,4,4,4,4,4,4,5,7,0.0,satisfied +69767,11124,Male,Loyal Customer,12,Personal Travel,Eco,312,2,4,2,2,2,2,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +69768,64508,Male,Loyal Customer,50,Business travel,Business,247,5,5,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +69769,41522,Female,disloyal Customer,55,Business travel,Eco,889,3,3,3,3,3,3,3,3,4,5,3,4,4,3,8,10.0,neutral or dissatisfied +69770,104712,Male,Loyal Customer,46,Business travel,Business,1829,5,5,5,5,2,5,4,5,5,5,5,4,5,5,50,26.0,satisfied +69771,12237,Female,Loyal Customer,49,Business travel,Eco,201,4,2,2,2,2,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +69772,11818,Female,disloyal Customer,20,Business travel,Eco,986,1,1,1,2,4,1,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +69773,121202,Female,disloyal Customer,26,Business travel,Eco Plus,2402,2,2,2,4,2,2,2,3,2,4,3,2,2,2,0,19.0,neutral or dissatisfied +69774,14574,Male,Loyal Customer,34,Business travel,Business,2207,5,2,5,5,3,2,3,5,5,5,5,3,5,2,0,0.0,satisfied +69775,100892,Male,Loyal Customer,46,Business travel,Business,2976,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +69776,96669,Male,Loyal Customer,53,Personal Travel,Eco,972,2,4,2,1,2,2,3,2,4,5,5,5,5,2,11,3.0,neutral or dissatisfied +69777,101567,Female,Loyal Customer,64,Personal Travel,Eco Plus,345,4,5,4,2,4,4,4,2,2,4,2,5,2,5,0,0.0,neutral or dissatisfied +69778,115116,Female,Loyal Customer,49,Business travel,Business,325,3,3,3,3,3,5,5,4,4,4,4,3,4,5,1,8.0,satisfied +69779,123861,Male,Loyal Customer,55,Business travel,Business,544,5,1,5,5,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +69780,105903,Female,Loyal Customer,39,Business travel,Business,3480,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +69781,127181,Male,Loyal Customer,45,Business travel,Business,3430,2,2,2,2,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +69782,77520,Female,Loyal Customer,9,Personal Travel,Eco,1587,3,4,3,2,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +69783,111594,Female,disloyal Customer,15,Business travel,Business,883,0,5,0,4,1,5,1,1,3,2,4,5,5,1,0,0.0,satisfied +69784,126913,Male,Loyal Customer,52,Business travel,Business,2538,5,2,5,5,2,4,5,5,5,5,5,3,5,4,4,0.0,satisfied +69785,46499,Female,Loyal Customer,37,Business travel,Eco,125,5,2,2,2,5,5,5,5,3,3,2,2,3,5,0,25.0,satisfied +69786,121101,Male,Loyal Customer,58,Business travel,Business,2370,2,2,2,2,4,3,4,3,3,3,3,4,3,3,1,0.0,satisfied +69787,127407,Male,Loyal Customer,46,Business travel,Eco,609,5,1,1,1,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +69788,4577,Male,Loyal Customer,47,Business travel,Business,1514,5,5,5,5,5,4,4,5,5,5,5,5,5,5,0,24.0,satisfied +69789,110438,Female,Loyal Customer,15,Personal Travel,Eco,787,3,5,3,3,3,3,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +69790,119499,Male,Loyal Customer,23,Business travel,Business,1685,4,4,4,4,4,5,4,4,4,3,5,5,4,4,0,0.0,satisfied +69791,121418,Male,Loyal Customer,37,Business travel,Business,2023,1,1,2,1,4,5,4,5,5,5,5,3,5,4,0,1.0,satisfied +69792,119866,Female,Loyal Customer,68,Personal Travel,Eco,936,4,5,4,2,3,4,4,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +69793,76038,Male,Loyal Customer,60,Personal Travel,Eco Plus,311,4,4,2,4,4,2,4,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +69794,50030,Female,Loyal Customer,65,Business travel,Business,2256,2,4,4,4,5,4,4,2,2,2,2,4,2,1,0,1.0,neutral or dissatisfied +69795,6510,Male,Loyal Customer,28,Business travel,Eco,599,2,2,2,2,2,2,2,2,2,4,4,1,3,2,0,0.0,neutral or dissatisfied +69796,31578,Female,Loyal Customer,32,Business travel,Business,3043,4,4,4,4,4,4,4,4,3,4,2,4,5,4,0,0.0,satisfied +69797,65165,Female,Loyal Customer,43,Personal Travel,Eco,247,3,2,3,2,4,2,3,5,5,3,5,3,5,1,0,7.0,neutral or dissatisfied +69798,98407,Male,Loyal Customer,12,Personal Travel,Eco,675,1,5,1,3,4,1,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +69799,55531,Male,Loyal Customer,24,Business travel,Business,1502,4,4,3,4,4,4,4,4,3,3,5,3,5,4,5,12.0,satisfied +69800,105823,Male,Loyal Customer,22,Personal Travel,Eco,842,2,2,2,3,3,2,3,3,4,5,2,2,3,3,0,0.0,neutral or dissatisfied +69801,5408,Male,Loyal Customer,33,Personal Travel,Eco,812,1,4,1,5,1,1,1,1,4,1,2,4,3,1,0,0.0,neutral or dissatisfied +69802,21626,Male,Loyal Customer,56,Business travel,Business,3764,1,1,1,1,4,4,4,1,1,1,1,3,1,2,15,19.0,neutral or dissatisfied +69803,94209,Female,Loyal Customer,40,Business travel,Business,1977,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +69804,41710,Male,Loyal Customer,52,Business travel,Business,2540,2,3,3,3,3,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +69805,77410,Female,Loyal Customer,12,Personal Travel,Eco,590,5,4,5,4,2,5,3,2,5,5,5,4,4,2,29,14.0,satisfied +69806,97156,Male,Loyal Customer,58,Business travel,Business,2021,2,5,5,5,2,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +69807,53270,Female,Loyal Customer,57,Business travel,Eco,758,5,4,4,4,2,1,2,5,5,5,5,2,5,1,0,0.0,satisfied +69808,123677,Female,disloyal Customer,26,Business travel,Business,214,4,4,4,3,3,4,3,3,3,3,5,5,5,3,0,3.0,satisfied +69809,109953,Male,Loyal Customer,7,Personal Travel,Eco,971,3,5,3,3,2,3,2,2,3,4,5,5,5,2,3,4.0,neutral or dissatisfied +69810,48363,Female,Loyal Customer,59,Business travel,Eco,522,2,4,4,4,1,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +69811,98397,Female,Loyal Customer,56,Business travel,Eco,462,1,3,3,3,4,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +69812,77824,Female,Loyal Customer,40,Personal Travel,Eco,1282,4,4,4,3,1,4,4,1,5,3,3,3,5,1,0,0.0,neutral or dissatisfied +69813,54419,Male,Loyal Customer,53,Personal Travel,Eco,305,2,3,3,3,1,3,1,1,4,5,3,1,2,1,0,0.0,neutral or dissatisfied +69814,108457,Female,Loyal Customer,36,Business travel,Eco,1044,3,4,4,4,3,3,3,3,1,4,3,2,3,3,18,8.0,neutral or dissatisfied +69815,123016,Male,Loyal Customer,42,Business travel,Business,650,4,4,4,4,4,5,5,4,4,4,4,3,4,4,3,26.0,satisfied +69816,85873,Male,disloyal Customer,23,Business travel,Eco,2172,3,3,3,3,4,3,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +69817,49119,Male,Loyal Customer,54,Business travel,Business,110,4,4,4,4,4,4,1,4,4,4,4,4,4,5,0,0.0,satisfied +69818,101002,Male,Loyal Customer,32,Business travel,Business,564,1,1,3,1,4,4,4,4,4,5,4,5,5,4,6,0.0,satisfied +69819,54995,Female,Loyal Customer,32,Business travel,Business,1635,2,2,2,2,5,5,5,4,5,4,5,5,5,5,200,203.0,satisfied +69820,110107,Male,disloyal Customer,27,Business travel,Business,979,1,1,1,3,1,1,1,1,4,3,4,3,4,1,3,0.0,neutral or dissatisfied +69821,103394,Female,Loyal Customer,52,Business travel,Business,237,1,1,1,1,4,5,4,5,5,5,5,3,5,4,14,15.0,satisfied +69822,55596,Male,Loyal Customer,56,Business travel,Business,404,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +69823,102742,Male,Loyal Customer,45,Personal Travel,Eco,255,2,4,2,4,4,2,2,4,3,1,2,1,2,4,0,0.0,neutral or dissatisfied +69824,111298,Female,Loyal Customer,39,Business travel,Business,283,1,5,5,5,2,3,4,1,1,1,1,2,1,1,5,10.0,neutral or dissatisfied +69825,74049,Female,Loyal Customer,27,Personal Travel,Eco,1194,2,4,2,4,3,2,1,3,4,3,4,4,5,3,14,24.0,neutral or dissatisfied +69826,99499,Male,Loyal Customer,52,Personal Travel,Eco,307,3,5,3,4,1,3,1,1,5,3,5,4,4,1,42,59.0,neutral or dissatisfied +69827,56117,Female,Loyal Customer,51,Business travel,Business,1400,4,4,5,4,3,4,5,5,5,5,5,5,5,5,7,7.0,satisfied +69828,3928,Male,Loyal Customer,55,Personal Travel,Eco Plus,213,1,2,1,4,4,1,4,4,2,3,4,4,3,4,64,64.0,neutral or dissatisfied +69829,111176,Female,Loyal Customer,56,Business travel,Business,1506,4,4,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +69830,92644,Male,Loyal Customer,20,Personal Travel,Eco,453,3,2,3,3,3,3,3,3,3,1,3,3,4,3,0,5.0,neutral or dissatisfied +69831,21801,Female,Loyal Customer,57,Business travel,Eco,352,1,2,2,2,1,3,3,1,1,1,1,1,1,4,1,0.0,neutral or dissatisfied +69832,33256,Female,Loyal Customer,29,Personal Travel,Eco Plus,102,3,4,3,4,2,3,2,2,4,3,4,1,3,2,0,3.0,neutral or dissatisfied +69833,12078,Male,Loyal Customer,48,Business travel,Eco Plus,376,4,5,5,5,4,4,4,4,3,5,1,3,5,4,0,2.0,satisfied +69834,7469,Female,disloyal Customer,34,Business travel,Eco,510,2,3,2,4,1,2,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +69835,11096,Female,Loyal Customer,54,Personal Travel,Eco,316,2,3,2,2,3,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +69836,78793,Female,disloyal Customer,34,Business travel,Eco,447,2,0,2,4,4,2,4,4,2,3,4,4,2,4,0,0.0,neutral or dissatisfied +69837,44371,Male,Loyal Customer,50,Personal Travel,Eco,596,4,1,5,3,4,5,4,4,1,5,3,1,4,4,3,0.0,neutral or dissatisfied +69838,40801,Male,Loyal Customer,19,Business travel,Business,2247,4,4,4,4,4,4,4,4,5,2,3,1,4,4,0,0.0,satisfied +69839,88167,Male,Loyal Customer,49,Business travel,Business,3559,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +69840,9479,Female,Loyal Customer,46,Business travel,Business,2426,1,1,1,1,3,5,5,4,4,4,4,5,4,5,11,17.0,satisfied +69841,113363,Female,Loyal Customer,39,Business travel,Business,223,1,1,1,1,3,4,4,4,4,4,4,4,4,5,4,1.0,satisfied +69842,84589,Female,Loyal Customer,53,Business travel,Business,669,5,5,1,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +69843,11085,Female,Loyal Customer,15,Personal Travel,Eco,216,1,1,1,2,1,1,1,1,1,4,2,3,2,1,0,0.0,neutral or dissatisfied +69844,123036,Female,disloyal Customer,20,Business travel,Eco,468,5,5,5,2,2,5,2,2,4,3,4,5,5,2,0,13.0,satisfied +69845,17718,Male,Loyal Customer,56,Business travel,Eco,383,5,5,5,5,5,5,5,5,5,3,3,3,3,5,13,0.0,satisfied +69846,26434,Male,Loyal Customer,42,Business travel,Business,3207,3,3,5,3,3,5,3,4,4,4,4,2,4,3,0,0.0,satisfied +69847,116255,Male,Loyal Customer,18,Personal Travel,Eco,373,2,4,2,3,4,2,1,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +69848,108258,Male,Loyal Customer,51,Business travel,Eco,895,2,3,3,3,2,2,2,2,2,2,4,3,4,2,14,3.0,neutral or dissatisfied +69849,17874,Male,disloyal Customer,34,Business travel,Eco,371,2,0,2,2,3,2,2,3,5,2,1,2,3,3,56,40.0,neutral or dissatisfied +69850,65119,Male,Loyal Customer,10,Personal Travel,Eco,247,3,4,3,2,4,3,4,4,3,3,5,5,4,4,27,19.0,neutral or dissatisfied +69851,95399,Female,Loyal Customer,48,Personal Travel,Eco,677,1,5,1,3,3,4,5,2,2,1,2,1,2,1,30,16.0,neutral or dissatisfied +69852,11723,Male,Loyal Customer,60,Business travel,Business,2747,4,4,4,4,4,4,5,5,5,5,5,3,5,4,4,1.0,satisfied +69853,24742,Female,Loyal Customer,56,Business travel,Business,3952,5,5,5,5,3,3,5,5,5,4,5,3,5,1,0,0.0,satisfied +69854,76976,Female,Loyal Customer,39,Business travel,Business,1969,4,4,4,4,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +69855,103613,Male,Loyal Customer,37,Business travel,Business,405,3,3,4,3,4,4,5,5,5,4,5,3,5,4,85,83.0,satisfied +69856,96779,Female,Loyal Customer,43,Business travel,Business,928,4,4,3,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +69857,88416,Female,Loyal Customer,40,Business travel,Business,404,3,1,3,3,3,5,5,1,1,2,1,5,1,3,0,0.0,satisfied +69858,19959,Female,Loyal Customer,44,Personal Travel,Eco Plus,315,5,5,5,4,2,2,4,5,5,5,5,5,5,2,0,0.0,satisfied +69859,21885,Female,Loyal Customer,42,Business travel,Eco,551,2,3,2,2,5,4,2,2,2,2,2,4,2,2,0,0.0,satisfied +69860,62421,Female,Loyal Customer,38,Personal Travel,Eco,2457,3,4,3,3,4,3,5,4,4,2,5,5,5,4,34,29.0,neutral or dissatisfied +69861,111196,Female,Loyal Customer,43,Business travel,Business,1506,2,2,2,2,4,4,4,4,4,4,4,4,4,3,13,0.0,satisfied +69862,86057,Male,Loyal Customer,49,Personal Travel,Eco,432,3,4,3,4,5,3,1,5,4,2,4,5,5,5,23,6.0,neutral or dissatisfied +69863,37134,Female,Loyal Customer,56,Business travel,Eco,1237,2,4,4,4,3,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +69864,94311,Male,Loyal Customer,48,Business travel,Eco,248,3,4,4,4,3,3,3,3,1,5,3,2,4,3,3,0.0,neutral or dissatisfied +69865,2175,Female,Loyal Customer,58,Business travel,Business,2702,3,3,3,3,2,4,4,4,4,5,4,3,4,4,0,46.0,satisfied +69866,96908,Female,Loyal Customer,16,Personal Travel,Eco,571,1,4,1,4,5,1,5,5,4,5,4,4,4,5,2,0.0,neutral or dissatisfied +69867,89564,Female,Loyal Customer,50,Business travel,Business,1866,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +69868,68964,Female,Loyal Customer,60,Business travel,Business,3407,5,3,5,5,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +69869,37825,Male,Loyal Customer,39,Business travel,Business,937,2,5,5,5,2,3,4,2,2,2,2,3,2,4,129,117.0,neutral or dissatisfied +69870,58920,Female,Loyal Customer,11,Personal Travel,Eco,888,2,4,2,2,5,2,5,5,5,4,3,5,4,5,7,5.0,neutral or dissatisfied +69871,74560,Female,Loyal Customer,23,Business travel,Business,2334,1,1,1,1,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +69872,129588,Male,Loyal Customer,58,Business travel,Business,3784,3,5,5,5,3,4,3,3,3,2,3,1,3,1,8,2.0,neutral or dissatisfied +69873,95579,Male,Loyal Customer,51,Business travel,Business,670,3,4,4,4,3,3,4,3,3,4,3,3,3,4,32,43.0,neutral or dissatisfied +69874,27881,Female,Loyal Customer,54,Personal Travel,Eco Plus,1448,2,3,3,4,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +69875,36784,Female,disloyal Customer,36,Business travel,Eco,1111,4,4,4,1,4,5,5,1,2,5,1,5,2,5,275,319.0,neutral or dissatisfied +69876,106471,Female,Loyal Customer,32,Personal Travel,Eco,1300,5,4,5,2,3,5,3,3,4,5,3,3,5,3,3,0.0,satisfied +69877,30306,Female,Loyal Customer,65,Personal Travel,Eco,1476,2,4,2,2,2,5,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +69878,23663,Male,Loyal Customer,45,Business travel,Eco,212,5,3,3,3,5,5,5,5,4,1,2,1,3,5,63,51.0,satisfied +69879,24447,Female,Loyal Customer,53,Business travel,Eco,481,5,4,4,4,3,1,3,5,5,5,5,5,5,1,1,1.0,satisfied +69880,86411,Female,Loyal Customer,39,Business travel,Business,3483,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +69881,124977,Male,Loyal Customer,42,Business travel,Business,3636,0,5,0,4,2,5,4,1,1,1,1,3,1,3,0,0.0,satisfied +69882,12060,Female,Loyal Customer,64,Personal Travel,Eco,376,1,5,1,1,2,4,5,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +69883,12481,Female,Loyal Customer,57,Personal Travel,Eco,192,5,5,5,1,2,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +69884,125475,Male,Loyal Customer,69,Personal Travel,Eco,2917,3,3,3,3,3,3,3,4,1,3,4,3,2,3,181,179.0,neutral or dissatisfied +69885,11848,Male,Loyal Customer,60,Business travel,Business,912,2,2,2,2,4,3,2,2,2,2,2,3,2,2,39,23.0,neutral or dissatisfied +69886,22235,Male,disloyal Customer,38,Business travel,Business,208,3,3,3,4,5,3,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +69887,76517,Male,Loyal Customer,31,Business travel,Business,3147,1,1,1,1,5,5,5,5,4,3,5,5,5,5,2,0.0,satisfied +69888,22601,Male,Loyal Customer,53,Business travel,Business,2327,3,2,2,2,3,3,3,3,5,3,4,3,1,3,186,182.0,neutral or dissatisfied +69889,123238,Male,Loyal Customer,30,Personal Travel,Eco,650,3,4,3,4,3,3,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +69890,2520,Female,Loyal Customer,57,Business travel,Business,3621,5,5,5,5,4,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +69891,31473,Male,disloyal Customer,30,Business travel,Eco,853,2,2,2,3,4,2,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +69892,57509,Male,disloyal Customer,22,Business travel,Eco,235,3,0,3,3,2,3,2,2,4,3,4,4,4,2,22,105.0,neutral or dissatisfied +69893,59925,Female,Loyal Customer,37,Business travel,Business,3977,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +69894,98390,Female,disloyal Customer,23,Business travel,Eco,1131,2,2,2,4,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +69895,103710,Male,Loyal Customer,60,Personal Travel,Eco,405,3,4,3,3,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +69896,30675,Female,Loyal Customer,25,Business travel,Business,1775,3,3,5,3,5,5,5,5,5,4,2,2,4,5,0,10.0,satisfied +69897,83729,Male,Loyal Customer,49,Business travel,Eco,1027,3,4,4,4,2,3,2,2,2,1,3,1,3,2,0,4.0,neutral or dissatisfied +69898,47216,Female,Loyal Customer,40,Personal Travel,Eco,954,1,5,1,1,2,1,2,2,2,2,5,2,3,2,0,0.0,neutral or dissatisfied +69899,60574,Female,disloyal Customer,37,Business travel,Business,1290,3,3,3,3,4,3,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +69900,19369,Male,disloyal Customer,34,Business travel,Eco,476,4,5,4,2,3,4,3,3,5,1,4,1,4,3,0,0.0,neutral or dissatisfied +69901,67709,Male,Loyal Customer,43,Business travel,Business,1920,2,2,2,2,4,4,5,4,4,4,4,3,4,4,31,28.0,satisfied +69902,125792,Male,Loyal Customer,42,Business travel,Business,920,5,5,2,5,2,5,5,4,4,4,4,5,4,4,3,0.0,satisfied +69903,64053,Female,Loyal Customer,39,Business travel,Business,919,2,2,2,2,4,4,5,3,3,3,3,4,3,4,0,36.0,satisfied +69904,110492,Male,Loyal Customer,33,Personal Travel,Eco,842,2,1,2,4,1,2,1,1,3,3,3,3,4,1,78,72.0,neutral or dissatisfied +69905,48229,Female,Loyal Customer,27,Personal Travel,Eco,192,3,5,3,2,2,3,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +69906,103138,Female,Loyal Customer,53,Business travel,Eco Plus,460,5,5,5,5,5,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +69907,9457,Male,Loyal Customer,28,Personal Travel,Eco,288,3,4,3,2,4,3,4,4,1,4,2,3,5,4,0,0.0,neutral or dissatisfied +69908,51053,Female,Loyal Customer,47,Personal Travel,Eco,109,1,4,1,2,5,4,5,3,3,1,5,3,3,5,0,0.0,neutral or dissatisfied +69909,56371,Male,Loyal Customer,68,Personal Travel,Eco,200,2,3,2,1,4,2,4,4,4,4,4,5,1,4,0,0.0,neutral or dissatisfied +69910,28800,Male,Loyal Customer,40,Business travel,Business,2585,4,4,4,4,1,1,5,3,3,3,3,4,3,1,0,0.0,satisfied +69911,121144,Male,Loyal Customer,57,Business travel,Business,2521,3,4,4,4,5,3,3,3,3,2,3,3,3,3,5,0.0,neutral or dissatisfied +69912,121288,Female,Loyal Customer,19,Personal Travel,Eco,2282,2,2,2,3,5,2,5,5,3,3,3,4,2,5,0,0.0,neutral or dissatisfied +69913,102928,Female,Loyal Customer,16,Personal Travel,Eco,436,1,5,1,4,5,1,5,5,5,4,5,4,5,5,5,7.0,neutral or dissatisfied +69914,93747,Male,Loyal Customer,41,Business travel,Business,2369,3,3,3,3,2,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +69915,98388,Female,Loyal Customer,30,Business travel,Business,2295,4,4,4,4,4,4,4,4,3,2,5,3,4,4,0,0.0,satisfied +69916,8565,Female,Loyal Customer,53,Business travel,Business,1732,4,3,3,3,3,4,3,3,3,3,4,4,3,4,30,43.0,neutral or dissatisfied +69917,48893,Male,Loyal Customer,33,Business travel,Business,2035,5,5,5,5,4,4,5,4,3,4,5,2,3,4,0,0.0,satisfied +69918,44326,Male,Loyal Customer,48,Business travel,Business,3249,1,1,1,1,1,2,1,4,4,4,4,4,4,3,51,23.0,satisfied +69919,129541,Female,disloyal Customer,30,Business travel,Business,2342,4,4,4,4,5,4,5,5,4,2,3,5,4,5,0,0.0,satisfied +69920,61096,Female,Loyal Customer,26,Personal Travel,Eco,1703,3,4,3,3,4,3,4,4,3,2,3,1,3,4,5,5.0,neutral or dissatisfied +69921,65896,Female,Loyal Customer,52,Business travel,Business,2312,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +69922,48086,Male,Loyal Customer,42,Business travel,Business,192,4,4,4,4,4,4,2,5,5,5,5,4,5,2,38,25.0,satisfied +69923,36328,Female,Loyal Customer,44,Business travel,Eco,395,5,4,4,4,4,4,1,5,5,5,5,1,5,2,0,0.0,satisfied +69924,105879,Male,disloyal Customer,22,Business travel,Business,283,5,5,5,2,5,5,5,5,5,4,5,5,4,5,6,4.0,satisfied +69925,87349,Female,Loyal Customer,59,Business travel,Business,1990,2,2,2,2,2,4,4,5,5,4,5,3,5,5,7,0.0,satisfied +69926,5615,Female,Loyal Customer,51,Business travel,Business,3346,3,3,3,3,4,5,2,5,5,5,5,3,5,3,6,2.0,satisfied +69927,6170,Male,Loyal Customer,69,Personal Travel,Eco,491,4,5,4,3,5,4,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +69928,33071,Male,Loyal Customer,14,Personal Travel,Eco,163,3,5,3,1,3,3,3,3,3,5,2,4,5,3,0,0.0,neutral or dissatisfied +69929,90069,Male,Loyal Customer,41,Business travel,Business,1127,2,2,2,2,2,5,5,4,4,4,4,4,4,5,47,30.0,satisfied +69930,41097,Female,disloyal Customer,26,Business travel,Eco,295,3,4,3,2,1,3,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +69931,113050,Male,Loyal Customer,57,Business travel,Business,1718,1,1,1,1,3,5,4,5,5,5,5,3,5,5,11,3.0,satisfied +69932,24577,Female,Loyal Customer,46,Personal Travel,Eco Plus,813,4,0,4,3,2,3,5,4,4,4,4,5,4,4,4,0.0,neutral or dissatisfied +69933,111528,Male,Loyal Customer,39,Business travel,Business,2910,4,4,4,4,4,4,4,4,4,4,4,5,4,4,51,49.0,satisfied +69934,36374,Female,Loyal Customer,38,Business travel,Business,3087,4,4,4,4,3,4,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +69935,32438,Female,disloyal Customer,57,Business travel,Eco,102,5,0,5,4,2,5,2,2,4,3,1,1,4,2,0,0.0,satisfied +69936,21342,Male,Loyal Customer,25,Business travel,Business,2902,5,5,3,5,5,5,5,5,5,2,4,1,5,5,0,0.0,satisfied +69937,19690,Female,Loyal Customer,23,Business travel,Business,3748,1,1,1,1,4,4,4,4,4,2,3,5,5,4,10,4.0,satisfied +69938,71743,Female,Loyal Customer,48,Personal Travel,Business,1744,2,5,2,4,4,4,5,5,5,2,5,4,5,3,6,0.0,neutral or dissatisfied +69939,70296,Female,Loyal Customer,33,Personal Travel,Eco,852,2,4,2,3,5,2,5,5,3,4,5,3,4,5,16,17.0,neutral or dissatisfied +69940,94106,Male,Loyal Customer,10,Personal Travel,Business,192,3,5,3,5,5,3,5,5,4,1,5,5,1,5,38,23.0,neutral or dissatisfied +69941,9922,Male,Loyal Customer,48,Business travel,Business,508,2,2,2,2,5,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +69942,120113,Female,Loyal Customer,25,Business travel,Business,1576,1,5,2,2,1,2,1,1,2,1,4,4,3,1,0,0.0,neutral or dissatisfied +69943,128449,Female,Loyal Customer,24,Personal Travel,Eco,325,5,3,5,3,4,5,4,4,2,3,3,2,1,4,0,0.0,satisfied +69944,127471,Female,disloyal Customer,28,Business travel,Eco,763,3,3,3,4,5,3,4,5,3,3,3,3,4,5,29,61.0,neutral or dissatisfied +69945,87513,Female,Loyal Customer,26,Personal Travel,Eco,373,2,5,2,5,1,2,1,1,2,4,4,2,1,1,0,0.0,neutral or dissatisfied +69946,88876,Female,Loyal Customer,29,Business travel,Business,859,2,2,2,2,5,5,5,5,5,3,4,5,5,5,121,103.0,satisfied +69947,20784,Male,Loyal Customer,62,Business travel,Business,3892,2,2,2,2,4,2,3,5,5,5,5,2,5,5,108,96.0,satisfied +69948,110297,Female,disloyal Customer,28,Business travel,Business,842,4,5,5,1,5,5,5,5,3,2,4,4,4,5,0,6.0,satisfied +69949,115465,Male,Loyal Customer,59,Business travel,Business,362,4,4,4,4,4,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +69950,65737,Male,Loyal Customer,59,Business travel,Eco,936,2,4,4,4,2,2,2,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +69951,18743,Female,Loyal Customer,43,Business travel,Business,1167,3,3,3,3,1,2,3,5,5,5,5,1,5,4,0,0.0,satisfied +69952,71032,Female,Loyal Customer,64,Business travel,Business,2630,1,3,3,3,4,4,4,1,1,1,1,1,1,1,20,41.0,neutral or dissatisfied +69953,37484,Female,disloyal Customer,36,Business travel,Eco,944,3,3,3,2,1,3,1,1,3,5,2,1,3,1,0,0.0,neutral or dissatisfied +69954,95611,Male,Loyal Customer,40,Business travel,Eco,670,2,2,2,2,2,2,2,2,1,2,4,2,4,2,0,2.0,neutral or dissatisfied +69955,88754,Female,Loyal Customer,10,Personal Travel,Eco,406,2,5,2,2,1,2,1,1,4,4,2,3,4,1,16,16.0,neutral or dissatisfied +69956,56495,Male,Loyal Customer,46,Business travel,Business,937,4,4,4,4,3,5,4,3,3,4,3,3,3,5,0,7.0,satisfied +69957,34971,Male,Loyal Customer,39,Business travel,Business,2197,3,2,2,2,3,3,3,1,4,3,4,3,2,3,129,144.0,neutral or dissatisfied +69958,98818,Female,disloyal Customer,19,Business travel,Eco,763,2,2,2,3,3,2,2,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +69959,17063,Male,Loyal Customer,50,Business travel,Eco Plus,1134,4,1,1,1,4,4,4,4,4,1,1,3,1,4,0,0.0,satisfied +69960,69650,Male,Loyal Customer,44,Business travel,Business,2859,2,3,3,3,3,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +69961,90173,Male,Loyal Customer,21,Personal Travel,Eco,1127,3,5,3,4,5,3,5,5,5,3,3,5,4,5,0,2.0,neutral or dissatisfied +69962,58461,Male,Loyal Customer,30,Business travel,Eco Plus,733,2,1,3,1,2,2,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +69963,51044,Male,Loyal Customer,70,Personal Travel,Eco,109,3,5,3,2,3,2,2,3,4,5,5,2,3,2,141,150.0,neutral or dissatisfied +69964,9634,Male,disloyal Customer,23,Business travel,Business,199,4,0,4,4,2,4,2,2,4,4,5,4,4,2,0,0.0,satisfied +69965,69150,Female,Loyal Customer,45,Personal Travel,Eco,2248,3,4,3,4,5,4,4,4,4,3,4,1,4,4,8,0.0,neutral or dissatisfied +69966,127118,Female,Loyal Customer,11,Personal Travel,Eco,338,2,5,5,2,3,5,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +69967,80111,Male,Loyal Customer,8,Personal Travel,Eco,1620,5,4,5,4,2,5,2,2,3,3,4,5,4,2,0,0.0,satisfied +69968,55744,Female,Loyal Customer,61,Personal Travel,Eco Plus,2161,4,5,4,5,4,2,2,5,2,5,4,2,5,2,180,145.0,neutral or dissatisfied +69969,92403,Male,Loyal Customer,42,Business travel,Business,1892,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +69970,48516,Male,Loyal Customer,45,Business travel,Business,1944,3,1,5,1,4,2,3,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +69971,93465,Female,Loyal Customer,27,Business travel,Business,2110,1,1,1,1,5,5,5,5,5,3,5,4,4,5,50,35.0,satisfied +69972,82949,Male,Loyal Customer,54,Business travel,Business,1539,1,5,5,5,4,3,3,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +69973,24993,Female,Loyal Customer,49,Business travel,Eco,484,4,5,4,5,3,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +69974,102417,Female,Loyal Customer,33,Personal Travel,Eco,258,2,4,2,3,4,2,3,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +69975,108607,Female,Loyal Customer,42,Business travel,Business,2407,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +69976,108936,Male,Loyal Customer,41,Personal Travel,Eco,1183,1,5,1,2,1,1,1,1,5,4,4,4,5,1,30,19.0,neutral or dissatisfied +69977,6096,Male,Loyal Customer,30,Personal Travel,Eco Plus,693,1,4,1,3,5,1,4,5,4,2,5,4,5,5,8,38.0,neutral or dissatisfied +69978,72424,Male,Loyal Customer,43,Business travel,Eco,929,4,2,5,5,3,4,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +69979,27279,Male,Loyal Customer,59,Personal Travel,Business,679,2,5,2,3,2,5,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +69980,129323,Male,Loyal Customer,52,Business travel,Business,2475,2,3,3,3,4,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +69981,7843,Male,disloyal Customer,23,Business travel,Business,1005,0,0,0,4,1,0,1,1,5,2,4,4,5,1,0,0.0,satisfied +69982,18643,Male,Loyal Customer,51,Personal Travel,Eco,305,1,4,1,1,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +69983,56112,Male,Loyal Customer,46,Business travel,Business,1400,2,2,5,2,2,5,5,4,4,4,4,5,4,3,0,4.0,satisfied +69984,71471,Female,Loyal Customer,48,Personal Travel,Eco Plus,867,2,2,2,3,4,3,2,3,3,2,1,4,3,4,5,1.0,neutral or dissatisfied +69985,48702,Male,Loyal Customer,55,Business travel,Business,1642,3,3,3,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +69986,73644,Female,Loyal Customer,57,Business travel,Business,192,3,3,4,3,2,5,4,3,3,4,5,4,3,5,37,36.0,satisfied +69987,61297,Male,Loyal Customer,9,Personal Travel,Eco,967,2,3,1,3,4,1,4,4,1,5,4,4,4,4,10,27.0,neutral or dissatisfied +69988,101232,Female,Loyal Customer,57,Personal Travel,Eco Plus,795,3,5,3,2,2,4,5,5,5,3,5,5,5,5,4,0.0,neutral or dissatisfied +69989,67641,Female,Loyal Customer,52,Business travel,Business,1438,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +69990,105191,Male,Loyal Customer,57,Personal Travel,Eco,220,5,5,5,3,5,5,5,5,2,1,1,4,5,5,0,0.0,satisfied +69991,72544,Female,Loyal Customer,46,Business travel,Business,2890,3,2,2,2,1,2,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +69992,29413,Male,Loyal Customer,46,Personal Travel,Eco,2614,1,4,1,3,1,4,4,1,4,4,3,4,3,4,8,18.0,neutral or dissatisfied +69993,65063,Female,Loyal Customer,64,Personal Travel,Eco,190,3,5,0,4,3,4,4,1,1,0,1,5,1,4,0,0.0,neutral or dissatisfied +69994,39555,Male,Loyal Customer,60,Business travel,Eco,965,4,2,2,2,4,4,4,4,1,1,5,4,5,4,0,19.0,satisfied +69995,54852,Female,Loyal Customer,33,Business travel,Business,3456,1,2,2,2,5,3,3,1,1,1,1,2,1,4,14,14.0,neutral or dissatisfied +69996,92862,Female,Loyal Customer,42,Business travel,Business,2519,1,1,1,1,5,5,5,5,5,4,5,3,5,3,107,106.0,satisfied +69997,12543,Male,disloyal Customer,38,Business travel,Eco,388,2,0,2,4,3,2,3,3,5,5,5,1,2,3,0,0.0,neutral or dissatisfied +69998,4051,Female,Loyal Customer,33,Personal Travel,Eco,479,1,3,1,2,5,1,5,5,1,2,3,1,1,5,54,46.0,neutral or dissatisfied +69999,59157,Male,Loyal Customer,55,Business travel,Business,1846,3,3,3,3,5,3,5,5,5,5,5,5,5,3,4,0.0,satisfied +70000,89365,Female,Loyal Customer,38,Personal Travel,Eco,1587,3,5,3,2,5,3,3,5,4,2,5,5,4,5,38,34.0,neutral or dissatisfied +70001,26978,Male,Loyal Customer,9,Business travel,Business,1722,2,2,2,2,2,2,2,2,2,3,4,1,4,2,8,2.0,neutral or dissatisfied +70002,77760,Male,Loyal Customer,19,Business travel,Business,3279,4,4,4,4,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +70003,32065,Female,Loyal Customer,32,Business travel,Business,216,1,3,1,1,5,5,5,5,2,3,5,5,5,5,0,0.0,satisfied +70004,101454,Male,disloyal Customer,22,Business travel,Business,345,4,0,4,3,3,4,2,3,3,2,5,5,4,3,116,113.0,satisfied +70005,44417,Female,Loyal Customer,37,Business travel,Eco Plus,265,2,5,5,5,2,2,2,2,2,4,3,1,2,2,0,21.0,neutral or dissatisfied +70006,84396,Female,Loyal Customer,54,Business travel,Business,2460,1,5,4,5,3,3,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +70007,5315,Male,Loyal Customer,55,Business travel,Eco Plus,190,2,1,1,1,2,2,2,2,4,4,3,2,3,2,18,19.0,neutral or dissatisfied +70008,105099,Female,disloyal Customer,42,Business travel,Business,289,4,4,4,3,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +70009,14988,Male,Loyal Customer,32,Personal Travel,Eco Plus,1080,2,5,2,1,1,2,1,1,5,5,4,5,5,1,6,14.0,neutral or dissatisfied +70010,114546,Female,Loyal Customer,22,Personal Travel,Business,372,1,4,1,3,5,1,5,5,4,5,3,3,3,5,98,84.0,neutral or dissatisfied +70011,98567,Male,Loyal Customer,47,Business travel,Business,834,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +70012,45859,Female,Loyal Customer,49,Personal Travel,Eco Plus,411,4,5,4,1,3,5,5,4,4,4,4,5,4,3,56,41.0,neutral or dissatisfied +70013,9492,Male,Loyal Customer,43,Business travel,Business,3616,3,3,3,3,5,5,4,5,5,5,5,3,5,3,67,61.0,satisfied +70014,51178,Female,Loyal Customer,51,Business travel,Eco Plus,209,5,5,5,5,1,5,1,5,5,5,5,5,5,5,0,0.0,satisfied +70015,123624,Female,Loyal Customer,8,Personal Travel,Business,214,1,0,1,4,5,1,5,5,1,5,3,4,1,5,0,10.0,neutral or dissatisfied +70016,121667,Female,Loyal Customer,49,Business travel,Eco,511,2,3,3,3,3,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +70017,41716,Female,Loyal Customer,23,Personal Travel,Eco,1404,1,4,1,1,5,1,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +70018,18912,Female,Loyal Customer,58,Personal Travel,Eco,551,2,5,2,4,5,5,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +70019,89869,Female,Loyal Customer,41,Business travel,Business,3916,3,3,3,3,4,5,4,5,5,5,5,5,5,4,21,38.0,satisfied +70020,3280,Female,Loyal Customer,54,Personal Travel,Eco,479,3,3,3,5,2,1,3,3,3,3,3,1,3,2,48,37.0,neutral or dissatisfied +70021,97336,Male,disloyal Customer,44,Business travel,Business,347,2,2,2,4,1,2,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +70022,104816,Male,Loyal Customer,25,Business travel,Eco Plus,587,3,1,1,1,3,3,2,3,3,4,4,3,3,3,17,24.0,neutral or dissatisfied +70023,31885,Male,Loyal Customer,32,Business travel,Business,2762,3,2,3,3,4,4,4,4,4,5,4,2,2,4,19,2.0,satisfied +70024,119173,Female,Loyal Customer,48,Business travel,Business,2943,0,0,0,1,4,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +70025,76458,Male,Loyal Customer,59,Business travel,Business,2749,0,4,0,2,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +70026,30056,Female,Loyal Customer,24,Business travel,Business,3459,3,3,3,3,4,4,5,4,5,3,1,3,1,4,0,0.0,satisfied +70027,114438,Male,Loyal Customer,42,Business travel,Business,446,1,1,1,1,5,5,5,4,4,4,4,5,4,5,8,15.0,satisfied +70028,41742,Male,Loyal Customer,64,Personal Travel,Eco,695,1,1,1,4,4,1,4,4,1,2,4,4,4,4,0,0.0,neutral or dissatisfied +70029,113338,Male,Loyal Customer,59,Business travel,Business,1943,4,4,4,4,3,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +70030,85475,Male,disloyal Customer,18,Business travel,Eco,332,1,1,1,4,4,1,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +70031,36580,Male,Loyal Customer,67,Business travel,Business,1121,1,5,3,5,1,3,4,1,1,1,1,3,1,4,5,14.0,neutral or dissatisfied +70032,117215,Male,Loyal Customer,46,Personal Travel,Eco,304,1,4,1,5,2,1,2,2,4,4,5,5,4,2,15,18.0,neutral or dissatisfied +70033,42890,Male,Loyal Customer,41,Business travel,Eco,200,4,5,5,5,3,4,3,3,5,4,4,2,5,3,0,0.0,satisfied +70034,12516,Male,disloyal Customer,39,Business travel,Eco,788,4,4,4,1,2,4,3,2,1,5,3,5,4,2,16,4.0,neutral or dissatisfied +70035,49945,Female,disloyal Customer,33,Business travel,Eco,86,1,0,1,3,5,1,5,5,3,2,4,2,3,5,17,11.0,neutral or dissatisfied +70036,65745,Male,Loyal Customer,13,Personal Travel,Eco,936,1,3,1,5,5,1,5,5,5,2,1,3,2,5,8,5.0,neutral or dissatisfied +70037,92751,Female,Loyal Customer,17,Personal Travel,Eco,1276,3,4,4,4,2,4,1,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +70038,38253,Female,Loyal Customer,47,Business travel,Business,3766,1,1,1,1,5,4,4,3,3,4,3,4,3,4,1,11.0,satisfied +70039,106755,Female,Loyal Customer,33,Business travel,Business,945,4,1,1,1,4,3,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +70040,48771,Female,disloyal Customer,37,Business travel,Business,326,2,2,2,3,1,2,1,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +70041,15131,Female,disloyal Customer,27,Business travel,Eco,912,2,2,2,3,5,2,4,5,4,1,5,5,5,5,0,4.0,neutral or dissatisfied +70042,94096,Female,Loyal Customer,62,Personal Travel,Business,562,1,5,1,2,2,4,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +70043,18031,Female,disloyal Customer,20,Business travel,Eco,488,4,5,4,4,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +70044,21548,Male,Loyal Customer,21,Personal Travel,Eco,331,2,4,5,4,3,5,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +70045,34889,Female,disloyal Customer,37,Business travel,Business,187,3,3,3,2,5,3,5,5,1,1,3,2,3,5,14,7.0,neutral or dissatisfied +70046,115850,Female,disloyal Customer,23,Business travel,Eco,373,1,2,1,4,4,1,4,4,2,2,3,1,3,4,0,0.0,neutral or dissatisfied +70047,100233,Female,disloyal Customer,15,Business travel,Eco,1053,1,0,0,4,3,0,3,3,4,5,4,1,3,3,11,6.0,neutral or dissatisfied +70048,109224,Male,Loyal Customer,37,Personal Travel,Eco,483,1,4,3,3,3,3,3,3,2,1,3,3,4,3,0,7.0,neutral or dissatisfied +70049,12974,Female,disloyal Customer,23,Business travel,Eco,374,3,5,3,4,1,3,1,1,4,3,4,4,5,1,22,22.0,neutral or dissatisfied +70050,106820,Female,Loyal Customer,35,Business travel,Business,1488,3,3,3,3,4,5,5,4,4,4,4,3,4,5,44,38.0,satisfied +70051,105683,Male,Loyal Customer,34,Business travel,Business,787,4,4,4,4,3,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +70052,39669,Male,Loyal Customer,32,Personal Travel,Eco,476,5,4,5,4,3,5,3,3,1,1,3,4,3,3,0,0.0,satisfied +70053,8890,Male,Loyal Customer,15,Personal Travel,Eco,539,1,5,1,2,2,1,5,2,4,5,4,4,4,2,21,14.0,neutral or dissatisfied +70054,126531,Male,Loyal Customer,46,Business travel,Business,644,4,4,3,4,2,5,4,5,5,5,5,3,5,4,15,0.0,satisfied +70055,58046,Female,Loyal Customer,39,Business travel,Business,1827,5,5,2,5,5,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +70056,62714,Female,Loyal Customer,56,Business travel,Business,2486,2,2,5,2,5,5,5,3,4,4,5,5,4,5,1,45.0,satisfied +70057,25315,Male,Loyal Customer,42,Personal Travel,Eco,432,3,3,3,1,3,3,3,3,2,2,5,4,3,3,17,19.0,neutral or dissatisfied +70058,16032,Female,Loyal Customer,51,Personal Travel,Eco,780,3,3,3,3,1,1,5,3,3,3,1,4,3,5,0,0.0,neutral or dissatisfied +70059,18377,Male,Loyal Customer,69,Personal Travel,Eco Plus,169,3,5,3,3,4,3,5,4,3,4,4,5,5,4,43,31.0,neutral or dissatisfied +70060,28439,Male,Loyal Customer,28,Business travel,Business,2496,2,4,2,2,4,3,3,2,4,5,5,3,1,3,0,0.0,satisfied +70061,92282,Male,Loyal Customer,32,Personal Travel,Eco,1900,3,2,3,4,5,3,3,5,4,2,3,1,3,5,1,23.0,neutral or dissatisfied +70062,2459,Female,Loyal Customer,29,Business travel,Business,3573,1,1,1,1,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +70063,120651,Female,Loyal Customer,36,Business travel,Business,3583,2,2,2,2,3,5,5,4,4,4,4,5,4,5,14,4.0,satisfied +70064,14103,Female,Loyal Customer,30,Personal Travel,Eco,201,3,5,0,2,2,0,2,2,1,1,5,3,2,2,2,0.0,neutral or dissatisfied +70065,116676,Female,disloyal Customer,39,Business travel,Business,447,3,3,3,3,2,3,4,2,3,2,5,4,4,2,1,0.0,neutral or dissatisfied +70066,48172,Female,Loyal Customer,39,Business travel,Business,259,2,2,2,2,2,2,3,4,4,4,4,3,4,1,0,0.0,satisfied +70067,30526,Male,Loyal Customer,37,Personal Travel,Eco,464,4,4,4,4,3,4,3,3,3,4,4,5,4,3,35,41.0,neutral or dissatisfied +70068,35494,Male,Loyal Customer,24,Personal Travel,Eco,1074,1,5,1,1,5,1,5,5,3,2,5,3,4,5,51,39.0,neutral or dissatisfied +70069,23981,Female,disloyal Customer,18,Business travel,Eco,562,0,0,0,3,5,0,5,5,5,3,4,4,5,5,0,0.0,satisfied +70070,16225,Male,Loyal Customer,52,Business travel,Eco,266,4,4,4,4,4,4,4,4,2,2,3,1,5,4,0,0.0,satisfied +70071,39391,Female,Loyal Customer,22,Business travel,Business,521,3,3,3,3,5,5,5,5,3,4,2,3,1,5,0,0.0,satisfied +70072,61310,Female,Loyal Customer,55,Business travel,Business,3379,4,4,4,4,3,4,4,4,4,4,4,4,4,3,60,45.0,satisfied +70073,66919,Male,Loyal Customer,47,Business travel,Business,3530,4,4,4,4,4,5,4,4,4,5,4,3,4,4,0,4.0,satisfied +70074,74310,Female,disloyal Customer,54,Business travel,Business,1171,3,2,2,3,5,3,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +70075,52848,Male,Loyal Customer,34,Personal Travel,Eco,1721,3,4,3,3,4,3,4,4,3,4,3,3,4,4,12,0.0,neutral or dissatisfied +70076,101353,Male,disloyal Customer,48,Business travel,Business,1986,3,4,4,2,3,3,3,3,4,4,4,3,5,3,0,17.0,neutral or dissatisfied +70077,107077,Female,Loyal Customer,22,Personal Travel,Eco,395,2,5,2,5,4,2,4,4,3,4,5,4,5,4,9,12.0,neutral or dissatisfied +70078,36966,Male,Loyal Customer,40,Business travel,Business,2976,1,1,1,1,2,1,4,5,5,5,5,1,5,4,0,0.0,satisfied +70079,113325,Male,disloyal Customer,21,Business travel,Eco,258,4,2,4,2,1,4,1,1,3,3,3,1,2,1,20,20.0,neutral or dissatisfied +70080,26072,Female,disloyal Customer,25,Business travel,Eco,591,4,0,3,5,3,3,3,3,2,3,4,2,5,3,0,0.0,satisfied +70081,61663,Male,Loyal Customer,47,Business travel,Business,1464,2,2,2,2,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +70082,40909,Male,Loyal Customer,35,Personal Travel,Eco,532,4,4,4,2,2,4,2,2,3,3,5,4,4,2,0,0.0,satisfied +70083,68480,Female,Loyal Customer,56,Business travel,Business,1506,3,3,3,3,5,5,4,4,4,5,4,5,4,5,0,0.0,satisfied +70084,14906,Male,Loyal Customer,19,Personal Travel,Eco,343,3,4,3,3,1,3,1,1,4,2,5,3,5,1,12,31.0,neutral or dissatisfied +70085,75670,Female,Loyal Customer,55,Business travel,Business,1758,5,5,5,5,4,4,4,3,3,5,5,4,3,4,169,160.0,satisfied +70086,67580,Male,Loyal Customer,40,Business travel,Business,1464,4,4,4,4,4,5,4,4,4,4,4,5,4,4,100,91.0,satisfied +70087,29299,Male,Loyal Customer,68,Business travel,Business,2785,3,3,3,3,5,2,5,4,4,4,4,1,4,2,0,0.0,satisfied +70088,39115,Male,disloyal Customer,23,Business travel,Eco,190,2,2,2,4,1,2,1,1,2,1,4,4,3,1,0,0.0,neutral or dissatisfied +70089,31436,Female,Loyal Customer,14,Business travel,Eco Plus,1546,1,3,3,3,1,2,1,1,2,1,3,2,3,1,68,89.0,neutral or dissatisfied +70090,95150,Male,Loyal Customer,22,Personal Travel,Eco,248,1,5,1,4,5,1,5,5,5,5,4,4,5,5,20,31.0,neutral or dissatisfied +70091,47247,Female,disloyal Customer,22,Business travel,Eco,599,2,4,2,5,3,2,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +70092,121544,Female,disloyal Customer,39,Business travel,Business,936,3,3,3,3,1,3,1,1,1,4,4,1,3,1,0,0.0,neutral or dissatisfied +70093,33823,Female,Loyal Customer,23,Business travel,Eco Plus,1521,0,3,0,2,2,0,5,2,1,1,1,3,2,2,0,0.0,satisfied +70094,80476,Male,Loyal Customer,54,Personal Travel,Eco,1299,5,4,5,1,5,4,5,5,3,4,4,3,5,5,0,0.0,satisfied +70095,111344,Male,Loyal Customer,28,Personal Travel,Eco Plus,283,3,5,3,3,5,3,5,5,3,2,5,4,5,5,32,52.0,neutral or dissatisfied +70096,54999,Male,Loyal Customer,14,Business travel,Eco,1303,3,2,2,2,3,3,4,3,2,4,3,3,4,3,2,0.0,neutral or dissatisfied +70097,16954,Female,Loyal Customer,64,Personal Travel,Eco,116,2,3,2,1,1,3,3,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +70098,19595,Male,Loyal Customer,40,Personal Travel,Eco,212,4,5,4,2,5,4,5,5,2,2,5,3,4,5,60,63.0,neutral or dissatisfied +70099,25034,Male,Loyal Customer,50,Personal Travel,Eco,907,1,4,1,4,1,1,1,1,4,2,5,5,5,1,10,0.0,neutral or dissatisfied +70100,88469,Male,Loyal Customer,49,Business travel,Eco,194,4,1,1,1,4,4,4,4,4,5,2,3,4,4,8,3.0,satisfied +70101,117507,Male,Loyal Customer,57,Personal Travel,Eco,507,2,5,3,2,5,3,5,5,4,4,4,5,4,5,7,0.0,neutral or dissatisfied +70102,89011,Male,disloyal Customer,55,Business travel,Business,1892,5,5,5,4,5,5,5,5,4,2,5,5,5,5,0,5.0,satisfied +70103,22809,Male,Loyal Customer,27,Business travel,Business,1970,3,3,3,3,2,2,3,2,4,4,3,4,4,2,0,19.0,neutral or dissatisfied +70104,24069,Female,Loyal Customer,37,Personal Travel,Eco Plus,595,2,2,2,3,4,2,4,4,2,1,3,4,3,4,0,20.0,neutral or dissatisfied +70105,76921,Male,Loyal Customer,56,Business travel,Business,1727,4,1,4,4,3,4,5,5,5,5,5,3,5,3,10,0.0,satisfied +70106,126103,Male,Loyal Customer,49,Business travel,Business,2211,1,1,1,1,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +70107,37862,Female,Loyal Customer,39,Business travel,Business,1768,1,0,0,4,4,3,3,4,4,0,2,1,4,4,0,0.0,neutral or dissatisfied +70108,124909,Female,Loyal Customer,31,Business travel,Business,3061,2,4,4,4,2,2,2,2,3,4,4,4,4,2,0,3.0,neutral or dissatisfied +70109,77989,Male,Loyal Customer,44,Business travel,Business,214,4,3,4,4,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +70110,123732,Male,Loyal Customer,52,Personal Travel,Eco Plus,214,3,5,3,4,3,3,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +70111,47941,Male,Loyal Customer,59,Personal Travel,Eco,451,2,3,2,1,3,2,2,3,2,3,3,1,2,3,82,72.0,neutral or dissatisfied +70112,6098,Male,Loyal Customer,20,Personal Travel,Eco Plus,672,2,4,2,1,1,2,1,1,5,1,3,5,5,1,0,0.0,neutral or dissatisfied +70113,80585,Female,Loyal Customer,61,Personal Travel,Eco,1747,2,5,2,3,5,5,5,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +70114,32352,Male,Loyal Customer,39,Business travel,Business,1754,2,2,2,2,5,5,5,4,4,4,5,4,4,3,0,1.0,satisfied +70115,10551,Male,disloyal Customer,27,Business travel,Business,316,4,4,4,1,1,4,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +70116,35462,Female,Loyal Customer,24,Personal Travel,Eco,989,2,4,2,3,1,2,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +70117,43110,Female,Loyal Customer,8,Personal Travel,Eco,236,2,4,2,1,3,2,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +70118,100016,Female,disloyal Customer,32,Business travel,Business,289,1,1,1,2,3,1,3,3,4,5,5,3,4,3,37,41.0,neutral or dissatisfied +70119,44620,Male,Loyal Customer,26,Business travel,Business,2363,3,3,3,3,5,5,5,5,5,3,2,3,3,5,0,0.0,satisfied +70120,105190,Female,Loyal Customer,22,Personal Travel,Eco,281,3,5,3,1,5,3,5,5,5,2,2,4,1,5,33,25.0,neutral or dissatisfied +70121,28982,Female,disloyal Customer,20,Business travel,Eco,1050,1,0,0,3,1,0,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +70122,48540,Female,Loyal Customer,49,Business travel,Business,337,2,2,2,2,5,1,3,4,4,4,4,4,4,3,15,14.0,satisfied +70123,34865,Female,Loyal Customer,54,Business travel,Business,2248,2,2,2,2,4,4,4,5,3,5,1,4,3,4,0,90.0,satisfied +70124,14,Male,Loyal Customer,9,Personal Travel,Business,853,1,5,1,2,5,1,5,5,4,3,4,5,5,5,68,76.0,neutral or dissatisfied +70125,24516,Male,disloyal Customer,22,Business travel,Eco,547,4,3,4,1,2,4,2,2,4,5,2,5,2,2,3,13.0,satisfied +70126,45429,Female,Loyal Customer,53,Business travel,Business,649,4,4,4,4,5,5,3,4,4,4,4,3,4,2,0,3.0,satisfied +70127,12697,Female,Loyal Customer,50,Business travel,Eco,689,4,2,2,2,2,1,4,4,4,4,4,3,4,2,0,0.0,satisfied +70128,97128,Male,Loyal Customer,41,Business travel,Eco,715,4,5,5,5,5,4,5,5,3,3,3,2,2,5,15,15.0,neutral or dissatisfied +70129,67504,Female,disloyal Customer,29,Business travel,Business,1205,2,2,2,4,2,2,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +70130,94743,Female,Loyal Customer,55,Business travel,Business,341,2,1,1,1,3,4,3,2,2,2,2,2,2,3,8,10.0,neutral or dissatisfied +70131,42191,Male,Loyal Customer,45,Business travel,Business,2737,1,1,1,1,2,5,4,5,5,5,5,4,5,2,16,4.0,satisfied +70132,14833,Male,Loyal Customer,40,Business travel,Eco,261,5,2,2,2,5,5,5,5,3,5,2,5,3,5,0,0.0,satisfied +70133,47829,Female,disloyal Customer,25,Business travel,Eco,817,2,2,2,4,5,2,3,5,2,4,4,3,4,5,0,0.0,neutral or dissatisfied +70134,103838,Male,Loyal Customer,50,Business travel,Eco,979,3,5,5,5,3,3,3,3,2,1,4,4,3,3,1,16.0,neutral or dissatisfied +70135,62025,Female,Loyal Customer,43,Business travel,Business,2475,5,5,5,5,4,5,5,4,4,3,4,3,4,3,0,0.0,satisfied +70136,15550,Female,Loyal Customer,42,Business travel,Business,1595,4,4,4,4,5,5,5,4,4,4,4,3,4,5,30,0.0,satisfied +70137,23008,Female,Loyal Customer,68,Personal Travel,Eco,528,3,3,3,4,1,1,2,5,5,3,5,5,5,5,4,0.0,neutral or dissatisfied +70138,105411,Female,Loyal Customer,23,Personal Travel,Eco Plus,369,4,1,4,3,4,4,4,4,2,4,4,3,4,4,33,33.0,neutral or dissatisfied +70139,107673,Male,disloyal Customer,26,Business travel,Business,251,4,0,4,2,3,4,3,3,4,3,5,4,4,3,9,6.0,neutral or dissatisfied +70140,91350,Male,Loyal Customer,28,Personal Travel,Eco Plus,406,2,5,2,3,3,2,1,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +70141,76408,Male,Loyal Customer,52,Personal Travel,Business,405,2,5,2,4,3,4,4,3,3,2,3,4,3,4,6,0.0,neutral or dissatisfied +70142,87928,Male,Loyal Customer,58,Business travel,Business,594,1,4,4,4,3,2,2,1,1,2,1,4,1,4,59,52.0,neutral or dissatisfied +70143,55955,Male,Loyal Customer,43,Business travel,Business,1620,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +70144,13499,Female,Loyal Customer,31,Business travel,Eco,227,5,3,5,3,5,5,5,5,2,1,3,5,2,5,0,4.0,satisfied +70145,54192,Female,disloyal Customer,59,Personal Travel,Eco,1400,2,5,2,3,5,2,1,5,5,2,4,4,4,5,31,2.0,neutral or dissatisfied +70146,84723,Female,Loyal Customer,22,Business travel,Business,2612,3,3,3,3,5,5,5,5,5,5,5,3,4,5,12,8.0,satisfied +70147,94963,Male,Loyal Customer,36,Business travel,Eco,248,5,4,4,4,5,5,5,5,5,3,1,3,4,5,1,0.0,satisfied +70148,28619,Female,disloyal Customer,22,Business travel,Business,1486,0,5,0,3,1,5,3,1,1,2,3,4,4,1,0,0.0,satisfied +70149,10134,Female,Loyal Customer,63,Personal Travel,Eco,946,4,5,4,1,1,4,1,2,2,4,2,3,2,1,0,0.0,satisfied +70150,117461,Male,Loyal Customer,37,Business travel,Eco Plus,1020,4,4,4,4,4,3,4,4,1,1,3,4,3,4,94,95.0,neutral or dissatisfied +70151,74753,Male,Loyal Customer,15,Personal Travel,Eco,1464,1,4,1,5,3,1,3,3,5,4,4,4,5,3,45,74.0,neutral or dissatisfied +70152,10257,Female,Loyal Customer,46,Personal Travel,Business,247,3,5,0,4,4,5,4,5,5,0,5,5,5,5,0,0.0,neutral or dissatisfied +70153,93016,Female,Loyal Customer,40,Business travel,Eco,1124,5,3,3,3,5,5,5,5,2,1,1,4,4,5,86,114.0,satisfied +70154,41633,Male,Loyal Customer,33,Personal Travel,Eco,374,3,0,3,4,3,3,1,3,5,3,5,3,5,3,9,13.0,neutral or dissatisfied +70155,18518,Male,disloyal Customer,25,Business travel,Eco,262,5,4,5,5,4,5,4,4,2,5,5,4,4,4,0,0.0,satisfied +70156,74826,Male,Loyal Customer,45,Personal Travel,Eco Plus,1464,5,4,5,3,3,5,3,3,5,4,5,3,4,3,8,31.0,satisfied +70157,101712,Male,Loyal Customer,14,Personal Travel,Eco,1624,4,2,4,3,5,4,3,5,2,1,3,2,3,5,15,0.0,neutral or dissatisfied +70158,37595,Female,Loyal Customer,65,Business travel,Business,2227,4,3,3,3,4,3,4,4,4,4,4,3,4,3,64,65.0,neutral or dissatisfied +70159,75124,Female,Loyal Customer,60,Business travel,Business,1726,4,4,4,4,3,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +70160,52573,Male,Loyal Customer,32,Business travel,Eco,160,4,1,1,1,4,4,4,4,5,5,3,4,4,4,0,0.0,satisfied +70161,126613,Male,Loyal Customer,28,Personal Travel,Eco,1337,3,4,3,3,3,3,3,3,4,3,5,3,5,3,108,130.0,neutral or dissatisfied +70162,108141,Male,Loyal Customer,46,Business travel,Business,766,3,1,1,1,1,3,3,3,3,3,3,4,3,4,2,0.0,neutral or dissatisfied +70163,97569,Male,Loyal Customer,51,Business travel,Business,2563,5,5,5,5,4,5,4,4,4,5,4,3,4,5,14,3.0,satisfied +70164,19254,Male,Loyal Customer,34,Business travel,Eco Plus,420,3,3,3,3,4,3,3,5,5,2,3,3,2,3,177,167.0,satisfied +70165,86361,Female,Loyal Customer,59,Business travel,Business,762,1,1,1,1,5,4,4,5,5,4,5,3,5,3,16,51.0,satisfied +70166,68359,Female,Loyal Customer,40,Business travel,Business,2072,5,5,4,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +70167,121201,Female,Loyal Customer,63,Business travel,Eco Plus,2521,3,4,4,4,3,2,2,3,3,3,3,4,3,4,107,,neutral or dissatisfied +70168,103872,Female,Loyal Customer,13,Personal Travel,Eco,1056,2,4,2,3,4,2,4,4,5,1,5,2,5,4,2,0.0,neutral or dissatisfied +70169,96845,Male,Loyal Customer,36,Business travel,Business,2539,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +70170,62657,Male,Loyal Customer,31,Personal Travel,Eco,1723,3,5,3,1,1,3,5,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +70171,55940,Female,Loyal Customer,13,Personal Travel,Eco Plus,733,1,2,1,4,3,1,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +70172,99800,Female,Loyal Customer,38,Business travel,Business,584,1,4,4,4,1,4,4,1,1,1,1,4,1,1,54,49.0,neutral or dissatisfied +70173,70040,Female,Loyal Customer,59,Business travel,Eco,583,4,1,1,1,3,5,3,4,4,4,4,3,4,3,0,0.0,satisfied +70174,35073,Female,Loyal Customer,48,Personal Travel,Business,1005,2,5,2,4,2,5,4,5,5,2,1,5,5,4,13,13.0,neutral or dissatisfied +70175,125647,Female,Loyal Customer,41,Business travel,Business,1642,4,4,4,4,3,5,5,2,2,2,2,3,2,4,43,39.0,satisfied +70176,118431,Female,disloyal Customer,20,Business travel,Business,304,5,0,5,2,2,5,4,2,3,5,4,5,5,2,21,18.0,satisfied +70177,122388,Male,Loyal Customer,7,Personal Travel,Eco,529,1,5,1,1,2,1,2,2,5,5,5,5,4,2,125,91.0,neutral or dissatisfied +70178,124019,Female,Loyal Customer,56,Personal Travel,Eco,184,2,3,2,3,2,4,3,4,4,2,1,3,4,1,0,0.0,neutral or dissatisfied +70179,19178,Male,disloyal Customer,28,Business travel,Eco,1024,2,2,2,4,5,2,5,5,2,2,4,4,4,5,9,0.0,neutral or dissatisfied +70180,4702,Male,Loyal Customer,42,Personal Travel,Eco,364,1,5,1,3,4,1,4,4,4,3,4,4,5,4,0,2.0,neutral or dissatisfied +70181,114192,Female,Loyal Customer,72,Business travel,Eco,957,3,5,2,2,5,4,4,3,3,3,3,1,3,1,9,1.0,neutral or dissatisfied +70182,42885,Female,Loyal Customer,52,Business travel,Business,200,5,5,5,5,3,5,4,4,4,4,5,5,4,3,0,6.0,satisfied +70183,14782,Female,Loyal Customer,41,Personal Travel,Eco,487,4,2,4,3,5,4,5,5,1,5,4,2,3,5,115,121.0,neutral or dissatisfied +70184,44305,Female,Loyal Customer,51,Business travel,Eco,1428,4,4,3,4,3,1,4,4,4,4,4,4,4,5,0,0.0,satisfied +70185,27095,Male,Loyal Customer,26,Business travel,Business,1721,4,4,4,4,4,4,4,4,5,2,3,3,2,4,0,0.0,satisfied +70186,15805,Female,Loyal Customer,57,Personal Travel,Eco,143,3,2,3,3,2,3,3,1,1,3,1,1,1,1,11,0.0,neutral or dissatisfied +70187,74532,Male,disloyal Customer,44,Business travel,Eco,810,1,1,1,3,5,1,5,5,3,2,4,4,3,5,12,0.0,neutral or dissatisfied +70188,45474,Male,disloyal Customer,25,Business travel,Eco,522,2,2,2,2,3,2,3,3,3,1,2,1,2,3,63,68.0,neutral or dissatisfied +70189,52027,Male,Loyal Customer,42,Personal Travel,Eco,328,4,4,4,4,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +70190,27566,Female,Loyal Customer,66,Personal Travel,Eco,954,3,5,3,1,3,5,5,1,1,3,1,5,1,5,49,18.0,neutral or dissatisfied +70191,89507,Male,Loyal Customer,47,Business travel,Business,950,1,1,1,1,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +70192,35004,Male,Loyal Customer,14,Personal Travel,Eco,1182,3,5,3,4,3,3,2,3,3,4,4,5,4,3,1,13.0,neutral or dissatisfied +70193,102174,Female,Loyal Customer,47,Business travel,Business,3234,3,3,3,3,3,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +70194,126255,Female,disloyal Customer,23,Business travel,Eco,328,4,0,4,1,4,4,1,4,4,1,4,2,3,4,0,0.0,neutral or dissatisfied +70195,48329,Female,Loyal Customer,45,Business travel,Eco,674,5,1,1,1,4,3,1,5,5,5,5,4,5,2,82,74.0,satisfied +70196,893,Female,disloyal Customer,33,Business travel,Business,102,1,1,1,4,2,1,2,2,1,3,4,1,4,2,8,43.0,neutral or dissatisfied +70197,31575,Male,Loyal Customer,39,Business travel,Business,602,5,5,4,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +70198,125950,Male,Loyal Customer,18,Personal Travel,Eco,861,3,4,3,3,3,3,2,3,4,5,5,5,5,3,0,42.0,neutral or dissatisfied +70199,76713,Male,Loyal Customer,25,Business travel,Business,534,2,2,2,2,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +70200,56807,Male,disloyal Customer,41,Business travel,Business,1605,4,4,4,5,2,4,2,2,5,3,4,3,5,2,47,50.0,neutral or dissatisfied +70201,58703,Male,disloyal Customer,8,Business travel,Eco,4243,2,2,2,3,2,4,4,3,4,3,4,4,2,4,57,36.0,neutral or dissatisfied +70202,119477,Female,Loyal Customer,52,Business travel,Business,759,2,2,2,2,3,5,4,5,5,5,5,5,5,4,4,0.0,satisfied +70203,93491,Female,Loyal Customer,42,Business travel,Business,2546,2,2,2,2,3,4,5,5,5,4,5,5,5,5,27,18.0,satisfied +70204,16275,Female,Loyal Customer,8,Personal Travel,Eco,748,5,4,5,5,3,5,3,3,3,2,5,3,5,3,95,90.0,satisfied +70205,97031,Male,Loyal Customer,64,Personal Travel,Eco Plus,883,3,3,3,4,3,1,1,2,3,4,5,1,1,1,151,160.0,neutral or dissatisfied +70206,91374,Female,Loyal Customer,28,Business travel,Business,2430,1,1,1,1,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +70207,62405,Female,Loyal Customer,9,Personal Travel,Eco,2704,2,5,2,3,1,2,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +70208,5003,Male,Loyal Customer,36,Business travel,Business,3215,1,1,4,1,1,3,2,5,5,5,4,1,5,2,68,66.0,satisfied +70209,38668,Female,Loyal Customer,48,Personal Travel,Eco,2611,3,1,3,3,5,3,3,5,5,3,5,2,5,3,112,115.0,neutral or dissatisfied +70210,79240,Female,Loyal Customer,35,Business travel,Business,1598,3,3,3,3,3,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +70211,70567,Male,disloyal Customer,36,Business travel,Eco,858,3,3,3,4,1,3,1,1,3,4,5,1,1,1,6,0.0,neutral or dissatisfied +70212,51227,Male,disloyal Customer,23,Business travel,Eco,373,2,4,2,3,2,2,2,2,3,4,5,3,2,2,58,58.0,neutral or dissatisfied +70213,85672,Female,Loyal Customer,23,Personal Travel,Eco,903,3,4,3,3,1,3,1,1,5,5,3,1,5,1,2,0.0,neutral or dissatisfied +70214,6834,Female,Loyal Customer,61,Personal Travel,Eco,223,3,4,3,1,5,5,4,4,4,3,2,5,4,4,0,0.0,neutral or dissatisfied +70215,40320,Female,Loyal Customer,31,Business travel,Eco Plus,402,4,3,2,3,4,4,4,4,2,5,4,5,1,4,0,0.0,satisfied +70216,61753,Female,Loyal Customer,18,Personal Travel,Eco,1635,2,4,2,2,2,4,3,3,3,5,4,3,3,3,150,168.0,neutral or dissatisfied +70217,91317,Male,Loyal Customer,30,Business travel,Business,1609,4,4,4,4,5,5,5,5,5,5,5,4,4,5,0,0.0,satisfied +70218,39006,Male,Loyal Customer,42,Business travel,Eco,391,1,4,4,4,1,1,1,1,2,1,3,2,3,1,19,8.0,neutral or dissatisfied +70219,125359,Male,Loyal Customer,41,Personal Travel,Eco,599,2,0,3,2,3,3,3,3,2,1,3,1,2,3,0,10.0,neutral or dissatisfied +70220,68697,Male,Loyal Customer,16,Personal Travel,Eco,237,3,3,0,3,1,0,1,1,4,3,4,3,4,1,0,2.0,neutral or dissatisfied +70221,126922,Female,Loyal Customer,66,Personal Travel,Business,370,2,1,2,3,3,3,4,2,2,2,5,4,2,3,0,0.0,neutral or dissatisfied +70222,117249,Male,Loyal Customer,56,Personal Travel,Eco,338,2,4,2,2,2,2,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +70223,121731,Female,disloyal Customer,20,Business travel,Eco,1459,2,2,2,3,3,2,3,3,2,1,2,2,2,3,0,8.0,neutral or dissatisfied +70224,99544,Female,Loyal Customer,47,Business travel,Business,829,4,4,4,4,3,4,4,4,4,4,4,4,4,5,5,3.0,satisfied +70225,104262,Male,Loyal Customer,36,Business travel,Business,1667,2,3,3,3,5,4,3,2,2,2,2,3,2,3,20,12.0,neutral or dissatisfied +70226,9522,Female,Loyal Customer,53,Business travel,Business,229,5,3,4,3,3,3,3,5,5,4,5,1,5,1,6,0.0,neutral or dissatisfied +70227,33218,Female,Loyal Customer,65,Business travel,Eco Plus,216,4,2,5,2,5,5,5,4,4,4,4,4,4,2,0,0.0,satisfied +70228,81365,Female,disloyal Customer,58,Business travel,Business,282,4,4,4,3,3,4,4,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +70229,112811,Female,Loyal Customer,39,Business travel,Eco,1211,3,2,2,2,3,3,3,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +70230,16086,Female,Loyal Customer,53,Business travel,Business,303,0,0,0,3,3,5,2,1,1,1,1,1,1,3,4,0.0,satisfied +70231,8624,Female,disloyal Customer,39,Business travel,Business,280,3,3,3,4,3,3,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +70232,34551,Male,disloyal Customer,24,Business travel,Eco,798,1,1,1,5,5,1,4,5,5,3,4,4,3,5,13,0.0,neutral or dissatisfied +70233,36446,Male,disloyal Customer,50,Business travel,Eco,1368,5,5,5,1,5,5,3,5,3,3,3,1,2,5,0,0.0,satisfied +70234,65736,Male,Loyal Customer,59,Business travel,Eco,1061,1,0,0,4,5,1,5,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +70235,14642,Male,disloyal Customer,37,Business travel,Eco,548,1,2,2,3,5,2,5,5,1,4,3,1,4,5,0,0.0,neutral or dissatisfied +70236,112153,Male,Loyal Customer,39,Business travel,Business,1564,3,2,2,2,4,3,3,3,3,3,3,1,3,2,53,47.0,neutral or dissatisfied +70237,95525,Male,Loyal Customer,44,Personal Travel,Eco Plus,189,4,4,4,3,5,4,1,5,3,3,4,3,4,5,2,8.0,satisfied +70238,58798,Male,Loyal Customer,53,Business travel,Business,797,3,3,3,3,1,4,5,3,3,3,3,1,3,4,5,3.0,satisfied +70239,61266,Male,Loyal Customer,40,Personal Travel,Eco,862,5,5,5,3,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +70240,99083,Male,Loyal Customer,54,Business travel,Business,3531,4,4,4,4,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +70241,96997,Male,Loyal Customer,40,Personal Travel,Eco,883,3,4,3,4,3,3,3,3,2,2,4,2,4,3,34,15.0,neutral or dissatisfied +70242,53046,Male,Loyal Customer,7,Personal Travel,Eco,1190,4,4,4,1,1,4,1,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +70243,48276,Male,disloyal Customer,69,Business travel,Business,236,4,4,4,4,4,4,4,4,4,4,4,1,3,4,9,0.0,neutral or dissatisfied +70244,8327,Male,Loyal Customer,32,Business travel,Business,661,2,2,2,2,4,4,4,4,3,3,4,4,4,4,101,108.0,satisfied +70245,105054,Female,Loyal Customer,68,Personal Travel,Eco,255,3,4,3,4,2,5,2,2,2,3,2,1,2,3,5,8.0,neutral or dissatisfied +70246,108336,Male,disloyal Customer,44,Business travel,Business,1750,4,4,4,4,1,4,1,1,3,2,4,5,4,1,20,0.0,satisfied +70247,87342,Male,Loyal Customer,45,Business travel,Business,425,2,2,2,2,3,5,5,5,5,5,5,4,5,5,43,23.0,satisfied +70248,86600,Male,Loyal Customer,50,Business travel,Business,3363,4,4,4,4,5,4,5,4,4,4,4,3,4,3,28,27.0,satisfied +70249,79432,Male,Loyal Customer,57,Business travel,Business,3264,2,2,5,2,5,5,4,5,5,5,5,5,5,4,23,47.0,satisfied +70250,65356,Male,Loyal Customer,50,Business travel,Business,631,1,1,1,1,3,5,5,4,4,4,4,5,4,3,3,3.0,satisfied +70251,129332,Female,Loyal Customer,33,Business travel,Business,2586,2,2,2,2,4,4,4,5,5,5,5,3,5,3,0,13.0,satisfied +70252,30615,Male,Loyal Customer,11,Personal Travel,Eco Plus,472,2,5,2,5,5,2,4,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +70253,78674,Male,disloyal Customer,22,Business travel,Business,674,5,0,5,2,2,5,2,2,5,5,4,3,5,2,0,0.0,satisfied +70254,52884,Male,Loyal Customer,38,Business travel,Eco,624,4,1,4,4,4,4,4,4,5,4,4,4,3,4,2,0.0,satisfied +70255,123140,Male,Loyal Customer,29,Business travel,Business,631,5,1,5,5,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +70256,115669,Female,disloyal Customer,25,Business travel,Business,325,4,4,4,4,3,4,3,3,3,2,4,3,4,3,0,0.0,satisfied +70257,4138,Male,Loyal Customer,31,Business travel,Eco,431,2,3,3,3,2,2,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +70258,22708,Female,Loyal Customer,63,Personal Travel,Eco,589,2,4,2,3,3,5,4,5,5,2,5,5,5,3,0,,neutral or dissatisfied +70259,57235,Female,Loyal Customer,64,Personal Travel,Eco Plus,1514,3,4,3,3,3,3,2,3,3,3,1,5,3,4,0,0.0,neutral or dissatisfied +70260,35006,Male,Loyal Customer,56,Personal Travel,Eco,1182,2,5,2,3,3,2,3,3,5,2,4,5,5,3,0,9.0,neutral or dissatisfied +70261,76820,Female,Loyal Customer,32,Business travel,Business,1851,5,5,5,5,4,4,4,4,4,5,3,4,5,4,0,0.0,satisfied +70262,5081,Male,disloyal Customer,37,Business travel,Business,224,1,1,1,2,3,1,3,3,2,2,2,2,3,3,0,14.0,neutral or dissatisfied +70263,79610,Male,Loyal Customer,71,Business travel,Business,2802,2,3,3,3,2,4,4,2,2,2,2,4,2,4,0,24.0,neutral or dissatisfied +70264,70266,Male,disloyal Customer,28,Business travel,Business,852,4,4,4,5,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +70265,116638,Female,Loyal Customer,57,Business travel,Business,2975,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +70266,34731,Female,Loyal Customer,36,Business travel,Business,3587,3,3,4,3,1,1,5,4,4,4,3,1,4,1,0,0.0,satisfied +70267,35742,Female,disloyal Customer,21,Business travel,Eco,2153,3,3,3,3,1,3,1,1,1,3,3,1,4,1,20,25.0,neutral or dissatisfied +70268,117482,Female,disloyal Customer,45,Business travel,Business,507,4,3,3,2,1,4,1,1,3,4,5,5,4,1,25,9.0,satisfied +70269,5164,Female,Loyal Customer,47,Business travel,Business,1523,0,0,0,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +70270,52820,Male,Loyal Customer,50,Personal Travel,Eco,2402,3,2,3,3,5,3,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +70271,17618,Female,Loyal Customer,24,Business travel,Eco,622,4,4,4,4,4,5,4,4,2,3,1,5,3,4,56,53.0,satisfied +70272,65989,Female,Loyal Customer,51,Business travel,Eco Plus,1372,2,5,5,5,4,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +70273,93861,Male,Loyal Customer,22,Business travel,Business,588,3,4,4,4,3,3,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +70274,74808,Male,Loyal Customer,52,Business travel,Eco Plus,1188,3,4,1,4,4,3,4,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +70275,54863,Male,Loyal Customer,33,Business travel,Business,641,3,3,3,3,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +70276,104975,Male,Loyal Customer,48,Business travel,Eco,337,4,1,3,1,5,4,5,5,4,3,2,1,3,5,0,40.0,neutral or dissatisfied +70277,58650,Male,disloyal Customer,27,Business travel,Eco,867,2,2,2,3,5,2,5,5,1,3,4,1,3,5,10,0.0,neutral or dissatisfied +70278,6283,Male,Loyal Customer,42,Personal Travel,Eco,585,0,4,0,4,3,0,3,3,3,4,5,4,4,3,1,0.0,satisfied +70279,123543,Male,disloyal Customer,36,Business travel,Business,1773,2,2,2,1,3,2,3,3,5,2,5,4,5,3,0,6.0,neutral or dissatisfied +70280,64857,Male,Loyal Customer,57,Business travel,Business,3524,4,4,4,4,5,4,5,4,4,4,4,4,4,3,43,31.0,satisfied +70281,117780,Female,Loyal Customer,51,Business travel,Business,1912,5,5,5,5,3,4,5,3,3,4,3,3,3,4,31,11.0,satisfied +70282,58542,Male,Loyal Customer,44,Business travel,Business,1514,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +70283,35527,Female,Loyal Customer,14,Personal Travel,Eco,1076,1,5,1,1,3,1,3,3,4,5,4,3,5,3,0,1.0,neutral or dissatisfied +70284,12451,Male,Loyal Customer,8,Personal Travel,Eco,201,2,5,2,1,3,2,3,3,5,3,4,4,3,3,0,12.0,neutral or dissatisfied +70285,106957,Male,disloyal Customer,23,Business travel,Business,937,0,0,0,3,5,0,5,5,4,2,5,3,4,5,25,2.0,satisfied +70286,96569,Male,Loyal Customer,57,Business travel,Business,3702,0,0,0,1,2,4,4,1,1,1,1,5,1,5,6,24.0,satisfied +70287,83875,Male,Loyal Customer,59,Business travel,Business,1670,2,2,2,2,4,3,4,5,5,5,5,5,5,4,0,17.0,satisfied +70288,86592,Male,Loyal Customer,49,Business travel,Business,746,3,3,3,3,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +70289,118852,Female,Loyal Customer,19,Personal Travel,Eco Plus,325,2,3,2,1,3,2,3,3,1,5,5,2,5,3,0,0.0,neutral or dissatisfied +70290,51225,Female,Loyal Customer,42,Business travel,Eco Plus,421,5,4,5,4,1,2,5,5,5,5,5,3,5,4,31,32.0,satisfied +70291,27328,Male,Loyal Customer,23,Business travel,Business,954,1,1,1,1,4,4,4,4,3,2,3,2,4,4,0,0.0,satisfied +70292,116757,Female,Loyal Customer,26,Personal Travel,Eco Plus,358,2,4,2,3,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +70293,117649,Female,disloyal Customer,23,Business travel,Eco,1020,2,2,2,1,2,2,2,2,2,3,1,2,2,2,98,89.0,neutral or dissatisfied +70294,67562,Female,Loyal Customer,46,Business travel,Business,2860,3,3,3,3,3,4,5,5,5,5,5,4,5,5,2,,satisfied +70295,62531,Male,Loyal Customer,47,Business travel,Eco,1726,1,2,2,2,1,1,1,1,2,2,3,4,4,1,0,28.0,neutral or dissatisfied +70296,54489,Male,Loyal Customer,50,Business travel,Eco,925,2,1,1,1,2,2,2,2,2,4,1,1,5,2,2,0.0,satisfied +70297,93404,Female,Loyal Customer,60,Business travel,Business,3131,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +70298,23764,Male,Loyal Customer,11,Personal Travel,Eco Plus,1083,3,1,3,3,3,3,3,3,2,2,3,3,3,3,0,36.0,neutral or dissatisfied +70299,120605,Male,Loyal Customer,35,Business travel,Business,2772,5,4,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +70300,11986,Female,Loyal Customer,34,Personal Travel,Eco,643,4,5,4,2,1,4,1,1,4,5,4,3,5,1,18,25.0,neutral or dissatisfied +70301,91816,Female,Loyal Customer,10,Personal Travel,Eco,599,2,2,2,4,1,2,1,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +70302,94147,Female,disloyal Customer,20,Business travel,Business,562,4,1,5,2,4,5,2,4,5,5,5,5,4,4,0,0.0,satisfied +70303,60025,Female,Loyal Customer,52,Personal Travel,Eco,937,1,1,1,3,5,4,4,1,1,1,1,2,1,3,10,3.0,neutral or dissatisfied +70304,26349,Female,Loyal Customer,24,Personal Travel,Eco Plus,834,2,2,2,3,3,2,1,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +70305,12720,Female,Loyal Customer,24,Business travel,Business,2919,5,5,5,5,5,4,5,5,2,3,3,4,3,5,33,39.0,neutral or dissatisfied +70306,84246,Male,Loyal Customer,34,Personal Travel,Eco Plus,432,3,4,1,3,4,1,5,4,5,5,3,1,1,4,25,29.0,neutral or dissatisfied +70307,127430,Female,Loyal Customer,48,Personal Travel,Eco,868,2,4,2,4,1,3,1,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +70308,24313,Female,Loyal Customer,50,Personal Travel,Eco Plus,147,2,4,2,4,2,5,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +70309,49397,Male,Loyal Customer,62,Business travel,Business,421,3,3,3,3,2,1,2,4,4,4,4,3,4,3,1,0.0,satisfied +70310,90992,Male,Loyal Customer,51,Business travel,Eco,545,1,3,3,3,1,1,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +70311,115523,Female,disloyal Customer,25,Business travel,Business,333,1,0,2,3,2,2,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +70312,60828,Female,Loyal Customer,19,Personal Travel,Eco Plus,455,2,4,2,1,3,2,3,3,3,3,4,3,4,3,10,38.0,neutral or dissatisfied +70313,99821,Male,disloyal Customer,37,Business travel,Business,534,4,4,4,3,2,4,2,2,4,4,4,5,4,2,12,1.0,satisfied +70314,46755,Male,Loyal Customer,46,Business travel,Eco Plus,73,5,2,2,2,5,5,5,5,4,3,3,4,3,5,0,0.0,satisfied +70315,52301,Female,Loyal Customer,30,Business travel,Business,451,4,5,5,5,4,4,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +70316,82658,Male,Loyal Customer,47,Business travel,Eco,120,2,4,3,4,2,2,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +70317,85003,Female,Loyal Customer,59,Business travel,Business,1590,2,2,2,2,2,4,4,5,5,5,5,4,5,3,2,5.0,satisfied +70318,54916,Male,Loyal Customer,27,Business travel,Eco Plus,862,3,4,4,4,3,3,3,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +70319,8041,Female,disloyal Customer,38,Business travel,Business,530,5,5,5,3,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +70320,84944,Male,Loyal Customer,43,Business travel,Business,2646,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +70321,67604,Female,disloyal Customer,29,Business travel,Business,1188,5,5,5,4,5,5,3,5,4,2,5,4,5,5,0,0.0,satisfied +70322,2016,Female,Loyal Customer,41,Business travel,Business,1779,5,5,5,5,2,4,4,3,3,4,3,5,3,4,0,7.0,satisfied +70323,22505,Male,Loyal Customer,41,Business travel,Eco Plus,143,4,2,2,2,4,4,4,4,5,2,1,5,2,4,1,0.0,satisfied +70324,29755,Female,Loyal Customer,50,Business travel,Business,3623,4,4,4,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +70325,15089,Female,disloyal Customer,36,Business travel,Eco,239,2,3,2,5,4,2,4,4,5,1,1,3,2,4,0,0.0,neutral or dissatisfied +70326,92102,Male,Loyal Customer,31,Business travel,Eco,1535,5,2,2,2,5,5,5,5,2,3,1,1,3,5,0,0.0,satisfied +70327,39445,Female,Loyal Customer,17,Personal Travel,Eco,129,5,0,5,1,4,5,4,4,3,2,5,5,4,4,0,0.0,satisfied +70328,2804,Male,Loyal Customer,50,Personal Travel,Eco,764,3,5,3,1,4,3,4,4,5,4,5,5,4,4,19,28.0,neutral or dissatisfied +70329,28624,Female,disloyal Customer,46,Business travel,Eco,2457,4,4,4,3,2,4,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +70330,67253,Male,Loyal Customer,43,Personal Travel,Eco,964,2,5,2,5,3,2,5,3,4,3,5,5,4,3,1,0.0,neutral or dissatisfied +70331,90949,Female,Loyal Customer,39,Business travel,Eco,246,3,4,3,4,3,3,3,3,1,4,3,4,4,3,0,0.0,neutral or dissatisfied +70332,44638,Male,Loyal Customer,35,Business travel,Eco,268,5,4,4,4,5,5,5,5,5,3,3,2,2,5,0,0.0,satisfied +70333,92119,Female,Loyal Customer,67,Personal Travel,Eco,1589,2,2,2,4,2,2,3,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +70334,13242,Male,Loyal Customer,47,Business travel,Business,657,5,5,5,5,3,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +70335,9939,Female,Loyal Customer,43,Business travel,Business,3487,5,5,5,5,5,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +70336,123614,Female,Loyal Customer,22,Personal Travel,Eco Plus,1773,3,4,3,5,1,3,1,1,3,4,4,1,1,1,114,108.0,neutral or dissatisfied +70337,88622,Male,Loyal Customer,53,Personal Travel,Eco,442,3,3,3,2,4,3,5,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +70338,86140,Male,Loyal Customer,56,Business travel,Business,356,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +70339,21166,Male,Loyal Customer,45,Business travel,Business,2358,0,4,0,3,2,4,5,4,4,1,1,5,4,3,0,0.0,satisfied +70340,110134,Male,Loyal Customer,40,Business travel,Business,869,1,1,1,1,1,4,3,1,1,1,1,3,1,3,1,0.0,neutral or dissatisfied +70341,82147,Female,Loyal Customer,44,Business travel,Business,3664,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,1.0,satisfied +70342,27854,Female,Loyal Customer,57,Personal Travel,Eco,1448,3,3,3,3,5,3,4,5,5,3,5,2,5,4,5,0.0,neutral or dissatisfied +70343,118947,Male,Loyal Customer,44,Business travel,Business,682,3,3,3,3,3,4,4,4,4,4,4,3,4,5,30,23.0,satisfied +70344,41638,Male,Loyal Customer,53,Business travel,Business,2878,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +70345,121883,Male,Loyal Customer,32,Personal Travel,Eco,366,5,5,5,4,3,5,2,3,5,2,4,5,4,3,4,0.0,satisfied +70346,63527,Female,Loyal Customer,48,Business travel,Business,1009,4,4,3,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +70347,23729,Female,Loyal Customer,24,Personal Travel,Eco Plus,196,2,2,2,3,2,2,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +70348,34177,Male,Loyal Customer,34,Business travel,Business,3131,3,4,4,4,5,4,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +70349,30889,Male,Loyal Customer,54,Business travel,Business,841,5,1,5,5,2,4,4,4,4,4,4,4,4,3,0,14.0,satisfied +70350,96833,Female,disloyal Customer,42,Business travel,Business,849,2,2,2,3,5,2,5,5,5,5,5,5,4,5,19,0.0,neutral or dissatisfied +70351,117778,Female,Loyal Customer,33,Business travel,Business,1912,2,5,2,2,4,4,5,5,5,5,5,3,5,3,29,23.0,satisfied +70352,129024,Female,Loyal Customer,44,Personal Travel,Eco,2611,4,3,4,3,4,5,5,4,5,3,3,5,2,5,0,10.0,neutral or dissatisfied +70353,80872,Male,Loyal Customer,8,Personal Travel,Eco,484,1,3,5,4,1,5,1,1,2,2,4,2,4,1,0,13.0,neutral or dissatisfied +70354,21483,Male,Loyal Customer,61,Business travel,Eco,331,4,5,5,5,4,4,4,4,1,2,1,5,3,4,0,0.0,satisfied +70355,100007,Female,Loyal Customer,59,Business travel,Business,281,2,2,2,2,3,5,4,5,5,5,5,5,5,5,77,75.0,satisfied +70356,89889,Female,disloyal Customer,26,Business travel,Business,1306,4,4,4,4,5,4,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +70357,90612,Female,Loyal Customer,48,Business travel,Eco,581,3,3,3,3,4,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +70358,65359,Male,Loyal Customer,60,Business travel,Business,2919,2,1,2,2,5,5,5,4,4,4,4,4,4,3,5,9.0,satisfied +70359,27719,Male,Loyal Customer,42,Business travel,Business,1448,5,5,5,5,3,1,3,5,5,5,5,5,5,2,0,0.0,satisfied +70360,92040,Male,Loyal Customer,40,Business travel,Business,1535,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +70361,8038,Female,Loyal Customer,41,Business travel,Business,294,5,4,5,5,2,4,4,4,4,4,4,4,4,3,24,23.0,satisfied +70362,68768,Male,Loyal Customer,43,Business travel,Business,3252,2,2,2,2,3,2,2,2,4,3,4,2,2,2,308,297.0,neutral or dissatisfied +70363,85330,Male,Loyal Customer,25,Business travel,Business,1899,2,2,2,2,3,4,3,3,3,4,5,3,5,3,35,13.0,satisfied +70364,94318,Male,disloyal Customer,22,Business travel,Eco,239,3,2,3,4,2,3,2,2,3,5,3,4,3,2,3,5.0,neutral or dissatisfied +70365,85510,Male,Loyal Customer,38,Personal Travel,Eco,152,3,5,3,3,5,3,5,5,3,5,4,4,4,5,0,2.0,neutral or dissatisfied +70366,111482,Male,Loyal Customer,28,Business travel,Business,1452,2,2,3,2,5,4,5,5,3,2,4,4,5,5,12,0.0,satisfied +70367,84447,Female,Loyal Customer,47,Business travel,Business,2660,3,1,1,1,1,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +70368,19230,Female,Loyal Customer,35,Personal Travel,Eco Plus,459,3,4,4,4,3,4,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +70369,5027,Female,Loyal Customer,29,Business travel,Business,235,4,4,4,4,5,4,5,5,4,5,5,4,5,5,3,32.0,satisfied +70370,71430,Female,Loyal Customer,39,Business travel,Business,3032,2,2,2,2,5,4,4,4,4,4,4,3,4,5,53,42.0,satisfied +70371,68402,Male,Loyal Customer,23,Business travel,Business,1045,4,4,4,4,5,5,5,5,4,3,4,5,5,5,0,0.0,satisfied +70372,35417,Female,Loyal Customer,53,Business travel,Eco,1076,1,4,4,4,4,3,4,1,1,1,1,3,1,3,45,49.0,neutral or dissatisfied +70373,111824,Male,Loyal Customer,23,Business travel,Business,1605,1,1,1,1,5,5,5,5,3,2,4,3,4,5,36,20.0,satisfied +70374,42752,Female,Loyal Customer,68,Personal Travel,Eco,607,1,4,1,3,2,5,4,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +70375,44529,Male,Loyal Customer,47,Business travel,Business,157,3,4,3,3,4,2,2,2,2,3,3,2,2,2,0,0.0,neutral or dissatisfied +70376,27832,Female,Loyal Customer,44,Personal Travel,Eco,1448,4,1,4,2,4,1,1,5,5,4,5,4,5,2,0,12.0,neutral or dissatisfied +70377,93129,Female,disloyal Customer,39,Business travel,Business,1183,3,3,3,3,4,3,4,4,5,5,4,5,4,4,0,26.0,neutral or dissatisfied +70378,128010,Male,Loyal Customer,37,Personal Travel,Eco,1488,4,5,4,3,2,4,2,2,3,2,4,3,1,2,0,0.0,neutral or dissatisfied +70379,126309,Female,disloyal Customer,26,Personal Travel,Eco,650,1,1,1,3,2,1,2,2,2,5,2,1,3,2,0,0.0,neutral or dissatisfied +70380,86117,Male,Loyal Customer,48,Business travel,Business,356,4,4,4,4,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +70381,49726,Male,Loyal Customer,33,Business travel,Eco,89,3,4,4,4,3,3,3,3,1,3,3,3,3,3,0,0.0,neutral or dissatisfied +70382,28437,Female,Loyal Customer,41,Business travel,Business,2496,2,4,4,4,2,2,2,2,4,2,4,2,3,2,0,39.0,neutral or dissatisfied +70383,81241,Female,disloyal Customer,24,Business travel,Eco,930,3,3,3,3,3,3,3,3,5,2,4,5,5,3,1,7.0,neutral or dissatisfied +70384,28435,Male,Loyal Customer,27,Business travel,Eco,2496,4,4,4,4,4,4,4,5,3,3,1,4,5,4,9,0.0,satisfied +70385,94984,Female,Loyal Customer,67,Personal Travel,Eco,239,4,1,0,4,1,4,3,4,4,0,2,2,4,1,8,3.0,neutral or dissatisfied +70386,102410,Female,Loyal Customer,30,Personal Travel,Eco,226,3,4,3,1,4,3,4,4,4,5,5,5,5,4,4,0.0,neutral or dissatisfied +70387,121335,Female,disloyal Customer,39,Business travel,Business,430,3,3,3,3,2,3,2,2,3,2,5,4,4,2,9,2.0,neutral or dissatisfied +70388,98045,Male,Loyal Customer,48,Business travel,Business,1751,4,4,3,4,5,4,5,4,4,4,4,5,4,3,34,14.0,satisfied +70389,99961,Female,Loyal Customer,62,Personal Travel,Business,888,3,5,3,5,5,4,4,3,3,3,3,5,3,4,3,0.0,neutral or dissatisfied +70390,101934,Female,Loyal Customer,42,Business travel,Business,1912,2,2,2,2,3,5,5,3,3,4,3,4,3,4,34,20.0,satisfied +70391,17692,Male,Loyal Customer,57,Personal Travel,Eco,1050,2,5,2,3,4,2,1,4,3,5,4,3,4,4,55,47.0,neutral or dissatisfied +70392,84199,Female,Loyal Customer,45,Business travel,Business,3832,3,3,3,3,4,4,4,5,5,5,5,4,5,4,56,40.0,satisfied +70393,93097,Male,Loyal Customer,49,Business travel,Business,1562,1,5,5,5,4,3,4,1,1,1,1,3,1,3,59,42.0,neutral or dissatisfied +70394,57634,Male,Loyal Customer,51,Business travel,Eco,200,2,3,3,3,2,2,2,2,1,3,3,2,3,2,8,10.0,neutral or dissatisfied +70395,18296,Female,Loyal Customer,43,Personal Travel,Eco,640,1,5,1,3,5,4,5,1,1,1,1,5,1,3,17,6.0,neutral or dissatisfied +70396,42144,Male,disloyal Customer,36,Business travel,Business,329,1,1,1,4,5,1,5,5,3,4,5,4,5,5,77,77.0,neutral or dissatisfied +70397,21531,Female,Loyal Customer,29,Personal Travel,Eco,399,2,5,5,1,4,5,4,4,3,4,4,4,5,4,47,41.0,neutral or dissatisfied +70398,123452,Female,Loyal Customer,24,Business travel,Business,2125,1,3,3,3,1,1,1,1,2,5,2,3,4,1,1,24.0,neutral or dissatisfied +70399,111064,Female,Loyal Customer,35,Personal Travel,Eco,319,3,3,3,4,3,3,3,3,4,1,4,4,5,3,55,45.0,neutral or dissatisfied +70400,101351,Female,disloyal Customer,11,Business travel,Eco,986,3,3,3,2,4,3,5,4,4,3,5,3,5,4,0,3.0,neutral or dissatisfied +70401,19056,Male,Loyal Customer,9,Personal Travel,Business,569,0,4,0,3,1,0,1,1,1,5,3,4,4,1,0,0.0,satisfied +70402,37036,Female,disloyal Customer,22,Business travel,Eco,994,3,3,3,4,5,3,3,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +70403,113636,Female,Loyal Customer,42,Personal Travel,Eco,258,4,4,4,1,3,3,2,4,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +70404,100141,Male,Loyal Customer,49,Business travel,Eco,523,1,4,4,4,2,1,2,2,2,1,3,1,2,2,0,34.0,neutral or dissatisfied +70405,47178,Male,disloyal Customer,22,Business travel,Eco,954,2,1,1,3,3,1,3,3,1,3,3,2,4,3,4,6.0,neutral or dissatisfied +70406,6943,Female,disloyal Customer,22,Business travel,Eco,501,1,0,1,4,3,1,3,3,4,5,5,4,5,3,0,1.0,neutral or dissatisfied +70407,32596,Female,Loyal Customer,53,Business travel,Eco,216,4,1,1,1,1,4,3,4,4,4,4,2,4,4,0,0.0,satisfied +70408,87540,Female,Loyal Customer,25,Business travel,Business,1742,5,5,5,5,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +70409,115558,Female,Loyal Customer,33,Business travel,Business,3135,1,4,1,4,5,3,3,1,1,1,1,2,1,4,7,0.0,neutral or dissatisfied +70410,82019,Female,Loyal Customer,63,Personal Travel,Eco,1517,1,5,0,1,5,4,4,3,3,0,3,3,3,5,20,17.0,neutral or dissatisfied +70411,15765,Female,Loyal Customer,41,Business travel,Business,2849,0,1,1,2,2,4,3,3,3,3,4,5,3,2,0,0.0,satisfied +70412,101310,Female,Loyal Customer,22,Personal Travel,Business,1076,3,5,3,1,5,3,4,5,3,5,4,5,5,5,9,0.0,neutral or dissatisfied +70413,116168,Male,Loyal Customer,38,Personal Travel,Eco,390,1,1,1,2,4,1,4,4,1,3,2,2,2,4,0,0.0,neutral or dissatisfied +70414,121909,Female,Loyal Customer,39,Personal Travel,Eco,366,3,1,3,3,2,3,2,2,4,4,2,4,2,2,2,0.0,neutral or dissatisfied +70415,14291,Female,Loyal Customer,19,Business travel,Business,1941,5,5,5,5,5,5,5,5,3,1,1,5,3,5,0,0.0,satisfied +70416,14189,Female,Loyal Customer,42,Business travel,Eco,620,4,5,5,5,2,5,5,4,4,4,4,1,4,2,0,0.0,satisfied +70417,122651,Female,disloyal Customer,25,Business travel,Business,361,3,5,3,2,5,3,3,5,5,3,5,5,4,5,19,18.0,neutral or dissatisfied +70418,36764,Male,Loyal Customer,38,Business travel,Business,2588,1,1,1,1,2,1,1,5,4,5,1,1,1,1,0,0.0,satisfied +70419,798,Female,disloyal Customer,48,Business travel,Business,309,2,2,2,3,5,2,5,5,1,3,4,4,4,5,0,5.0,neutral or dissatisfied +70420,83486,Female,Loyal Customer,46,Business travel,Business,2235,3,5,5,5,4,3,3,3,3,3,3,1,3,4,8,14.0,neutral or dissatisfied +70421,96941,Male,Loyal Customer,53,Business travel,Business,2044,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,7.0,satisfied +70422,13982,Male,disloyal Customer,24,Business travel,Eco,372,3,3,3,2,3,3,3,3,1,4,5,4,3,3,0,0.0,neutral or dissatisfied +70423,113663,Male,Loyal Customer,12,Personal Travel,Eco,226,3,5,0,2,3,0,3,3,5,3,4,4,4,3,10,2.0,neutral or dissatisfied +70424,62580,Female,Loyal Customer,26,Business travel,Eco,1846,1,4,4,4,1,1,2,1,3,1,2,2,4,1,10,6.0,neutral or dissatisfied +70425,31019,Male,Loyal Customer,35,Personal Travel,Eco,391,2,4,2,4,1,2,1,1,4,3,2,5,3,1,0,0.0,neutral or dissatisfied +70426,9184,Male,Loyal Customer,32,Business travel,Business,363,5,3,5,5,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +70427,118669,Female,Loyal Customer,39,Business travel,Eco,325,2,3,3,3,2,2,2,2,2,2,1,5,4,2,117,107.0,satisfied +70428,76096,Female,Loyal Customer,36,Personal Travel,Eco,669,2,5,2,4,5,2,2,5,1,5,3,4,1,5,8,0.0,neutral or dissatisfied +70429,92015,Female,Loyal Customer,33,Business travel,Business,1535,2,2,2,2,4,5,5,4,4,4,4,4,4,4,5,10.0,satisfied +70430,119190,Female,disloyal Customer,48,Business travel,Business,290,5,5,5,5,4,5,3,4,5,5,5,5,5,4,123,105.0,satisfied +70431,22143,Female,disloyal Customer,21,Business travel,Eco Plus,350,3,4,3,2,1,3,1,1,4,3,4,1,1,1,0,0.0,neutral or dissatisfied +70432,116476,Male,Loyal Customer,26,Personal Travel,Eco,337,4,3,1,2,1,1,1,1,3,3,3,5,4,1,0,0.0,neutral or dissatisfied +70433,87359,Male,Loyal Customer,39,Business travel,Business,425,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,13.0,satisfied +70434,116033,Female,Loyal Customer,11,Personal Travel,Eco,296,2,3,2,4,2,2,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +70435,103981,Male,Loyal Customer,35,Personal Travel,Business,1334,2,5,2,3,4,5,4,5,5,2,5,3,5,5,2,9.0,neutral or dissatisfied +70436,14633,Female,disloyal Customer,40,Business travel,Business,363,4,4,4,4,4,4,4,4,2,1,3,3,3,4,115,109.0,satisfied +70437,87374,Female,Loyal Customer,37,Business travel,Business,3070,1,1,5,1,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +70438,95595,Male,Loyal Customer,31,Business travel,Business,484,4,4,4,4,4,4,4,4,5,4,4,3,4,4,33,24.0,satisfied +70439,105201,Male,Loyal Customer,63,Personal Travel,Eco Plus,281,4,4,4,3,5,4,4,5,3,3,3,3,4,5,1,0.0,neutral or dissatisfied +70440,15865,Female,Loyal Customer,28,Business travel,Business,618,1,1,1,1,4,4,4,4,3,1,5,1,2,4,107,97.0,satisfied +70441,21965,Male,Loyal Customer,58,Business travel,Eco,503,5,3,3,3,5,5,5,5,1,1,2,3,4,5,2,0.0,satisfied +70442,124046,Male,Loyal Customer,30,Business travel,Eco Plus,184,1,2,2,2,1,1,1,1,1,1,4,2,3,1,0,11.0,neutral or dissatisfied +70443,93476,Female,disloyal Customer,22,Business travel,Eco Plus,697,2,1,1,3,2,1,2,2,3,1,4,4,4,2,32,22.0,neutral or dissatisfied +70444,24642,Female,Loyal Customer,39,Business travel,Eco Plus,126,2,1,1,1,2,2,2,2,2,1,1,4,2,2,0,0.0,neutral or dissatisfied +70445,117283,Male,disloyal Customer,45,Business travel,Business,370,4,4,4,3,5,4,5,5,5,3,4,5,4,5,0,0.0,satisfied +70446,85156,Female,disloyal Customer,37,Business travel,Business,731,4,4,4,3,3,4,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +70447,71507,Female,Loyal Customer,22,Business travel,Business,2151,1,1,1,1,4,4,4,4,4,4,5,3,4,4,0,17.0,satisfied +70448,40985,Male,Loyal Customer,26,Business travel,Eco,984,3,1,3,1,3,4,5,3,2,4,4,5,4,3,9,0.0,satisfied +70449,85840,Female,Loyal Customer,8,Personal Travel,Eco,666,2,1,2,3,2,2,2,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +70450,94996,Female,Loyal Customer,67,Personal Travel,Eco,239,3,4,0,5,4,5,5,2,2,0,2,3,2,4,7,7.0,neutral or dissatisfied +70451,128313,Male,Loyal Customer,40,Business travel,Business,2386,5,5,2,5,4,4,5,5,5,5,5,3,5,5,18,36.0,satisfied +70452,128354,Male,Loyal Customer,16,Business travel,Business,370,5,5,5,5,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +70453,71971,Male,Loyal Customer,40,Business travel,Eco,1440,2,1,1,1,2,2,2,2,2,1,4,3,4,2,24,23.0,neutral or dissatisfied +70454,82629,Female,Loyal Customer,7,Personal Travel,Eco,408,2,3,2,1,4,2,1,4,4,1,2,2,4,4,0,0.0,neutral or dissatisfied +70455,32708,Male,Loyal Customer,73,Business travel,Business,2408,2,2,4,2,3,3,3,4,4,4,5,2,4,1,0,0.0,satisfied +70456,3190,Male,Loyal Customer,40,Business travel,Eco,185,5,5,5,5,5,5,5,5,2,4,4,4,4,5,22,23.0,satisfied +70457,5903,Male,Loyal Customer,38,Business travel,Eco,108,2,5,5,5,2,1,2,2,3,3,4,2,3,2,0,7.0,neutral or dissatisfied +70458,29149,Female,Loyal Customer,53,Personal Travel,Eco,954,3,3,3,3,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +70459,69903,Female,Loyal Customer,37,Business travel,Business,1514,2,2,2,2,3,4,5,4,4,4,4,4,4,5,43,39.0,satisfied +70460,22445,Female,Loyal Customer,29,Personal Travel,Eco,238,1,2,1,4,2,1,5,2,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +70461,107949,Male,Loyal Customer,60,Business travel,Business,611,4,4,4,4,4,4,4,5,5,5,4,4,3,4,122,154.0,satisfied +70462,120828,Female,Loyal Customer,53,Business travel,Business,3739,3,3,3,3,5,4,4,4,4,4,4,5,4,4,23,9.0,satisfied +70463,22399,Male,disloyal Customer,15,Business travel,Eco,208,3,3,3,4,2,3,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +70464,44912,Female,Loyal Customer,46,Business travel,Business,2163,2,2,2,2,4,5,1,5,5,5,5,5,5,3,0,0.0,satisfied +70465,81470,Male,Loyal Customer,47,Business travel,Eco,528,3,3,3,3,3,3,3,3,1,1,4,2,4,3,0,7.0,neutral or dissatisfied +70466,48710,Female,Loyal Customer,41,Business travel,Business,1791,0,4,0,1,2,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +70467,7409,Female,Loyal Customer,41,Business travel,Business,1940,1,1,1,1,4,4,5,4,4,4,4,4,4,4,9,2.0,satisfied +70468,64271,Female,Loyal Customer,56,Business travel,Business,2078,2,2,2,2,4,5,5,4,4,4,4,4,4,5,106,87.0,satisfied +70469,41072,Male,disloyal Customer,24,Business travel,Eco,224,3,5,3,2,5,3,4,5,2,4,4,4,1,5,9,6.0,neutral or dissatisfied +70470,79848,Female,disloyal Customer,40,Business travel,Business,944,2,2,2,4,4,2,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +70471,103928,Male,disloyal Customer,20,Business travel,Eco,770,3,3,3,3,1,3,3,1,3,4,5,3,4,1,0,3.0,neutral or dissatisfied +70472,128273,Female,Loyal Customer,15,Personal Travel,Business,647,3,3,3,3,5,3,5,5,4,3,3,4,4,5,3,5.0,neutral or dissatisfied +70473,114916,Male,Loyal Customer,44,Business travel,Business,404,4,4,4,4,3,5,4,4,4,4,4,3,4,5,55,55.0,satisfied +70474,50730,Male,Loyal Customer,43,Personal Travel,Eco,308,3,5,3,1,1,3,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +70475,110612,Female,Loyal Customer,69,Personal Travel,Eco Plus,551,0,4,0,4,5,3,4,5,5,0,5,4,5,1,4,0.0,satisfied +70476,81904,Male,Loyal Customer,17,Personal Travel,Eco,680,2,5,2,3,4,2,4,4,3,4,4,4,5,4,11,0.0,neutral or dissatisfied +70477,128808,Female,disloyal Customer,35,Business travel,Business,2586,2,2,2,4,2,2,4,3,3,5,5,4,3,4,72,94.0,neutral or dissatisfied +70478,75005,Female,Loyal Customer,42,Business travel,Business,236,5,5,5,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +70479,120417,Female,Loyal Customer,72,Business travel,Business,366,5,5,3,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +70480,23205,Male,Loyal Customer,61,Business travel,Eco Plus,223,3,2,2,2,3,3,3,3,4,1,4,3,3,3,23,18.0,neutral or dissatisfied +70481,70643,Female,Loyal Customer,25,Business travel,Business,946,2,2,2,2,2,3,2,2,4,5,4,3,4,2,0,0.0,satisfied +70482,120112,Female,Loyal Customer,42,Business travel,Business,1576,2,2,2,2,5,5,4,3,3,3,3,4,3,4,0,1.0,satisfied +70483,22698,Male,Loyal Customer,62,Business travel,Eco,189,3,4,4,4,3,3,3,3,1,3,3,1,3,3,0,0.0,neutral or dissatisfied +70484,107045,Female,Loyal Customer,44,Business travel,Eco,480,3,2,2,2,5,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +70485,109397,Male,Loyal Customer,11,Personal Travel,Eco,1046,2,4,2,5,5,2,1,5,2,4,2,2,4,5,22,5.0,neutral or dissatisfied +70486,121262,Female,Loyal Customer,48,Personal Travel,Eco,1814,3,1,3,3,5,3,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +70487,122415,Male,disloyal Customer,27,Business travel,Business,762,5,5,5,4,1,5,1,1,5,3,5,5,5,1,24,30.0,satisfied +70488,123026,Female,Loyal Customer,46,Business travel,Business,1584,3,3,3,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +70489,80997,Male,Loyal Customer,23,Personal Travel,Eco,297,2,5,2,4,5,2,5,5,5,5,5,4,5,5,31,19.0,neutral or dissatisfied +70490,41548,Male,Loyal Customer,56,Business travel,Business,1701,4,4,4,4,1,3,3,2,2,2,2,2,2,4,0,0.0,satisfied +70491,27061,Female,Loyal Customer,26,Business travel,Eco,1399,5,3,3,3,5,4,4,5,1,2,3,3,4,5,0,0.0,satisfied +70492,75163,Male,Loyal Customer,49,Business travel,Business,1846,5,5,5,5,2,4,4,3,3,4,3,4,3,3,24,10.0,satisfied +70493,35380,Male,Loyal Customer,38,Business travel,Business,628,4,4,4,4,4,3,3,1,4,4,3,3,1,3,210,209.0,satisfied +70494,81280,Male,disloyal Customer,26,Business travel,Eco,1020,1,1,1,3,1,4,4,4,3,4,4,4,4,4,258,247.0,neutral or dissatisfied +70495,72670,Male,Loyal Customer,50,Personal Travel,Eco,964,1,4,1,1,2,1,2,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +70496,93583,Male,Loyal Customer,55,Personal Travel,Eco,159,5,5,5,1,3,5,3,3,5,3,5,3,5,3,0,6.0,satisfied +70497,113180,Female,Loyal Customer,24,Personal Travel,Eco,677,2,4,2,1,1,2,1,1,3,3,5,4,4,1,68,72.0,neutral or dissatisfied +70498,88557,Female,Loyal Customer,30,Personal Travel,Eco,406,2,1,2,4,1,2,1,1,3,3,4,4,3,1,0,1.0,neutral or dissatisfied +70499,73236,Female,disloyal Customer,42,Business travel,Business,946,1,1,1,5,1,1,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +70500,113260,Female,disloyal Customer,49,Business travel,Business,226,4,4,4,3,3,4,3,3,5,2,5,4,4,3,4,0.0,satisfied +70501,125956,Female,Loyal Customer,48,Business travel,Eco Plus,992,4,2,2,2,4,2,3,4,4,4,4,3,4,1,6,8.0,neutral or dissatisfied +70502,51425,Female,Loyal Customer,21,Personal Travel,Eco Plus,134,4,4,0,1,1,0,1,1,4,1,3,5,4,1,0,0.0,satisfied +70503,96532,Male,Loyal Customer,15,Personal Travel,Eco,302,2,4,3,2,3,3,3,3,5,4,4,3,4,3,16,8.0,neutral or dissatisfied +70504,72190,Female,Loyal Customer,47,Business travel,Business,3577,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +70505,84910,Female,Loyal Customer,17,Personal Travel,Eco,481,2,4,2,5,2,2,2,2,2,5,5,5,3,2,0,7.0,neutral or dissatisfied +70506,114854,Female,Loyal Customer,43,Business travel,Business,373,3,3,3,3,3,4,4,4,4,4,4,4,4,3,31,30.0,satisfied +70507,84565,Male,Loyal Customer,17,Personal Travel,Eco,2486,4,4,3,2,1,3,1,1,5,4,4,4,4,1,15,0.0,neutral or dissatisfied +70508,101406,Male,Loyal Customer,42,Personal Travel,Eco,486,3,1,3,3,5,3,5,5,1,3,2,4,2,5,83,75.0,neutral or dissatisfied +70509,11943,Male,disloyal Customer,30,Business travel,Business,781,0,0,0,1,5,0,5,5,3,4,5,5,4,5,0,0.0,satisfied +70510,125839,Male,Loyal Customer,47,Business travel,Business,1728,1,3,3,3,1,3,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +70511,21002,Male,Loyal Customer,23,Business travel,Eco Plus,689,3,3,3,3,3,3,2,3,3,4,2,3,2,3,0,0.0,neutral or dissatisfied +70512,124855,Male,Loyal Customer,64,Personal Travel,Eco,280,2,4,4,3,3,4,3,3,4,5,5,3,3,3,0,0.0,neutral or dissatisfied +70513,6303,Female,Loyal Customer,46,Business travel,Business,296,2,5,5,5,4,4,4,2,2,2,2,1,2,2,95,82.0,neutral or dissatisfied +70514,44010,Female,Loyal Customer,46,Personal Travel,Eco,397,2,4,2,3,3,5,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +70515,94674,Male,disloyal Customer,26,Business travel,Eco,562,3,1,3,2,2,3,2,2,2,5,2,3,3,2,0,1.0,neutral or dissatisfied +70516,117918,Male,Loyal Customer,53,Business travel,Business,255,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +70517,118714,Female,Loyal Customer,52,Personal Travel,Eco,369,3,1,3,3,2,3,3,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +70518,13841,Female,Loyal Customer,24,Personal Travel,Eco,628,4,4,4,4,2,4,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +70519,17350,Female,Loyal Customer,27,Business travel,Business,2717,5,5,4,5,4,5,4,4,2,2,5,4,4,4,0,0.0,satisfied +70520,5500,Male,disloyal Customer,25,Business travel,Eco,948,4,5,5,4,4,5,4,4,1,4,3,2,3,4,0,1.0,neutral or dissatisfied +70521,65038,Male,Loyal Customer,57,Personal Travel,Eco,551,1,5,1,3,5,1,4,5,4,2,2,3,5,5,0,0.0,neutral or dissatisfied +70522,67927,Female,disloyal Customer,15,Personal Travel,Eco,1235,3,3,3,4,5,3,5,5,1,4,3,1,3,5,0,0.0,neutral or dissatisfied +70523,15345,Male,Loyal Customer,48,Business travel,Business,306,2,2,2,2,4,4,4,5,4,4,5,4,5,4,187,186.0,satisfied +70524,112015,Male,Loyal Customer,53,Business travel,Business,2304,3,3,3,3,2,5,4,4,4,4,4,3,4,4,13,9.0,satisfied +70525,21289,Female,disloyal Customer,20,Business travel,Eco,526,2,2,3,3,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +70526,69885,Male,disloyal Customer,19,Business travel,Eco,2248,3,3,3,3,1,3,1,1,3,3,3,4,4,1,0,11.0,neutral or dissatisfied +70527,64869,Female,Loyal Customer,36,Business travel,Business,282,4,2,2,2,3,4,3,4,4,4,4,2,4,1,9,27.0,neutral or dissatisfied +70528,77811,Female,Loyal Customer,36,Personal Travel,Eco,874,2,2,2,3,5,2,5,5,1,4,2,4,4,5,47,76.0,neutral or dissatisfied +70529,84766,Male,Loyal Customer,42,Business travel,Business,3148,3,4,3,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +70530,12262,Female,Loyal Customer,56,Business travel,Eco,201,5,5,5,5,5,2,2,5,5,5,5,4,5,1,2,0.0,satisfied +70531,770,Male,Loyal Customer,60,Business travel,Business,2883,1,3,3,3,2,2,3,2,2,2,1,1,2,1,0,0.0,neutral or dissatisfied +70532,90180,Male,Loyal Customer,61,Personal Travel,Eco,957,3,5,3,3,3,3,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +70533,121692,Female,Loyal Customer,59,Business travel,Business,3691,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +70534,114523,Female,Loyal Customer,51,Personal Travel,Business,308,2,1,2,3,5,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +70535,79883,Female,Loyal Customer,56,Business travel,Business,1507,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +70536,25597,Male,Loyal Customer,55,Personal Travel,Eco,696,1,5,1,2,1,1,1,1,4,4,4,4,4,1,10,1.0,neutral or dissatisfied +70537,101967,Male,Loyal Customer,51,Business travel,Eco,228,4,2,2,2,3,4,3,3,3,4,4,2,4,3,9,1.0,satisfied +70538,12844,Male,Loyal Customer,43,Personal Travel,Eco,489,2,4,2,3,1,2,1,1,4,5,4,3,4,1,6,0.0,neutral or dissatisfied +70539,28274,Male,Loyal Customer,43,Business travel,Business,2402,5,5,2,5,5,4,4,1,1,5,2,4,1,4,0,0.0,satisfied +70540,18332,Female,Loyal Customer,36,Business travel,Business,554,1,1,5,1,3,4,5,5,5,5,5,3,5,4,0,3.0,satisfied +70541,9518,Male,Loyal Customer,49,Business travel,Business,3697,3,3,3,3,2,4,5,4,4,4,4,3,4,4,51,14.0,satisfied +70542,97566,Male,Loyal Customer,54,Business travel,Business,448,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +70543,58062,Male,Loyal Customer,27,Business travel,Business,2434,5,5,2,5,5,5,5,5,4,5,5,3,5,5,3,0.0,satisfied +70544,3376,Female,disloyal Customer,22,Business travel,Eco,213,2,2,2,2,2,2,2,2,2,2,3,3,3,2,8,20.0,neutral or dissatisfied +70545,98203,Male,Loyal Customer,18,Personal Travel,Eco,327,4,0,4,1,1,4,4,1,4,2,5,5,5,1,0,7.0,neutral or dissatisfied +70546,104876,Male,Loyal Customer,35,Business travel,Business,3546,2,5,5,5,5,3,4,2,2,2,2,3,2,3,37,38.0,neutral or dissatisfied +70547,128684,Female,Loyal Customer,53,Personal Travel,Eco,2419,3,3,3,3,3,5,4,1,2,3,3,4,2,4,0,0.0,neutral or dissatisfied +70548,85750,Male,Loyal Customer,42,Business travel,Business,666,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +70549,6361,Female,Loyal Customer,56,Business travel,Business,3843,1,1,1,1,5,4,4,5,5,5,5,3,5,3,8,2.0,satisfied +70550,103665,Male,Loyal Customer,49,Business travel,Business,3032,5,2,5,5,5,5,5,5,5,4,5,5,3,5,95,132.0,satisfied +70551,78044,Male,Loyal Customer,63,Personal Travel,Eco,332,2,4,2,2,4,2,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +70552,103945,Male,Loyal Customer,44,Business travel,Eco,770,3,5,5,5,3,3,3,3,3,3,3,3,4,3,0,6.0,neutral or dissatisfied +70553,88069,Female,Loyal Customer,47,Business travel,Business,3728,0,5,0,4,3,5,4,3,3,3,3,4,3,4,6,5.0,satisfied +70554,44328,Female,Loyal Customer,33,Business travel,Business,812,3,3,3,3,5,3,3,5,5,5,5,4,5,4,0,0.0,satisfied +70555,108276,Female,Loyal Customer,39,Personal Travel,Eco,895,3,4,3,3,3,3,3,3,4,3,4,4,4,3,93,126.0,neutral or dissatisfied +70556,75773,Male,Loyal Customer,60,Personal Travel,Eco,868,3,5,3,2,4,3,1,4,5,5,3,4,2,4,0,0.0,neutral or dissatisfied +70557,1889,Female,disloyal Customer,32,Business travel,Business,285,2,2,2,2,4,2,4,4,3,4,5,3,4,4,59,65.0,neutral or dissatisfied +70558,55369,Male,Loyal Customer,48,Business travel,Business,2930,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,3.0,satisfied +70559,13382,Male,Loyal Customer,38,Personal Travel,Eco Plus,946,3,4,4,4,1,4,5,1,4,2,4,1,4,1,105,103.0,neutral or dissatisfied +70560,63004,Male,disloyal Customer,11,Business travel,Business,967,4,4,4,4,3,4,3,3,5,4,4,4,4,3,0,0.0,satisfied +70561,35502,Female,Loyal Customer,30,Personal Travel,Eco,1056,3,4,3,2,5,3,5,5,2,4,2,2,4,5,0,9.0,neutral or dissatisfied +70562,83230,Female,disloyal Customer,22,Business travel,Eco,1979,2,2,2,4,5,2,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +70563,11364,Male,Loyal Customer,30,Personal Travel,Eco,191,3,5,3,2,3,3,2,3,3,4,4,3,4,3,42,40.0,neutral or dissatisfied +70564,65595,Female,Loyal Customer,65,Business travel,Business,1580,1,3,4,3,5,4,3,1,1,2,1,1,1,3,14,5.0,neutral or dissatisfied +70565,58436,Male,Loyal Customer,34,Personal Travel,Eco,723,4,1,4,3,3,4,3,3,1,4,4,1,4,3,24,12.0,neutral or dissatisfied +70566,95131,Male,Loyal Customer,42,Personal Travel,Eco,441,2,5,2,2,3,2,3,3,3,3,5,4,4,3,6,2.0,neutral or dissatisfied +70567,8292,Female,Loyal Customer,9,Personal Travel,Eco,125,5,5,5,4,5,5,5,5,4,2,5,2,3,5,0,0.0,satisfied +70568,117790,Female,Loyal Customer,56,Business travel,Business,1679,2,2,2,2,5,5,4,5,5,5,5,5,5,4,4,2.0,satisfied +70569,45260,Female,Loyal Customer,31,Personal Travel,Eco,584,3,5,3,1,3,2,2,5,2,4,5,2,5,2,226,233.0,neutral or dissatisfied +70570,15309,Female,disloyal Customer,51,Business travel,Eco,589,3,0,3,3,3,3,3,3,5,1,1,3,4,3,45,44.0,neutral or dissatisfied +70571,129634,Male,disloyal Customer,26,Business travel,Eco,337,2,2,2,3,4,2,4,4,4,3,4,1,3,4,0,0.0,neutral or dissatisfied +70572,27429,Female,Loyal Customer,43,Business travel,Business,3010,4,4,4,4,5,1,3,4,4,4,4,5,4,5,0,0.0,satisfied +70573,115361,Male,Loyal Customer,55,Business travel,Business,2480,1,1,5,1,5,5,4,3,3,3,3,4,3,5,110,101.0,satisfied +70574,81929,Male,Loyal Customer,31,Personal Travel,Business,1532,3,4,3,4,5,3,5,5,1,1,4,4,4,5,8,0.0,neutral or dissatisfied +70575,107898,Female,disloyal Customer,9,Business travel,Eco,861,4,4,4,1,5,4,1,5,5,5,5,4,4,5,6,0.0,satisfied +70576,110854,Male,Loyal Customer,47,Business travel,Business,3027,4,3,4,4,2,5,4,4,4,4,4,3,4,3,14,2.0,satisfied +70577,70455,Female,Loyal Customer,22,Business travel,Business,2301,1,1,1,1,5,5,4,5,3,5,5,3,4,5,4,0.0,satisfied +70578,122553,Male,disloyal Customer,40,Business travel,Eco,100,3,1,4,3,4,4,4,4,2,2,3,4,3,4,0,0.0,neutral or dissatisfied +70579,58348,Male,Loyal Customer,8,Personal Travel,Eco,315,3,3,3,4,5,3,5,5,4,2,2,3,1,5,91,97.0,neutral or dissatisfied +70580,4300,Female,Loyal Customer,67,Personal Travel,Eco,502,0,5,0,4,3,4,4,3,3,0,3,4,3,4,0,0.0,satisfied +70581,10067,Male,Loyal Customer,69,Personal Travel,Eco,596,3,2,3,4,5,3,5,5,1,5,2,2,3,5,0,0.0,neutral or dissatisfied +70582,119061,Female,Loyal Customer,30,Personal Travel,Eco,2279,1,4,1,4,4,1,4,4,5,3,4,5,4,4,54,32.0,neutral or dissatisfied +70583,122203,Female,Loyal Customer,47,Business travel,Business,3856,3,3,2,3,3,5,4,4,4,4,4,5,4,4,11,5.0,satisfied +70584,14646,Male,Loyal Customer,37,Business travel,Eco Plus,948,4,3,3,3,4,4,4,4,2,2,4,3,5,4,0,9.0,satisfied +70585,13376,Male,Loyal Customer,54,Personal Travel,Eco,748,1,3,1,2,2,1,2,2,4,3,3,5,5,2,0,0.0,neutral or dissatisfied +70586,77211,Female,Loyal Customer,10,Personal Travel,Eco,2994,1,2,1,3,1,3,3,3,2,4,3,3,1,3,0,7.0,neutral or dissatisfied +70587,45813,Male,disloyal Customer,20,Business travel,Eco,391,4,1,4,4,4,4,4,4,3,1,4,3,3,4,29,48.0,neutral or dissatisfied +70588,86275,Male,Loyal Customer,29,Personal Travel,Eco,356,4,5,4,3,3,4,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +70589,20636,Female,Loyal Customer,18,Business travel,Business,911,3,3,5,3,2,2,2,2,4,3,3,4,2,2,10,19.0,satisfied +70590,105588,Male,Loyal Customer,13,Personal Travel,Eco,577,3,5,2,3,2,2,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +70591,59364,Female,disloyal Customer,16,Business travel,Eco,2449,3,3,3,3,4,3,2,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +70592,27545,Male,Loyal Customer,24,Personal Travel,Eco,679,0,4,1,5,1,1,1,1,5,4,5,4,4,1,0,0.0,satisfied +70593,94008,Female,disloyal Customer,21,Business travel,Business,248,5,0,5,3,4,5,4,4,3,5,5,3,4,4,53,58.0,satisfied +70594,125275,Male,Loyal Customer,49,Business travel,Business,2758,2,2,2,2,5,4,4,5,5,5,5,4,5,5,2,13.0,satisfied +70595,55809,Female,Loyal Customer,24,Business travel,Business,1416,5,5,5,5,2,2,2,2,5,2,4,4,4,2,21,24.0,satisfied +70596,69940,Male,Loyal Customer,58,Business travel,Eco,2174,2,5,2,5,2,2,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +70597,18766,Male,disloyal Customer,23,Business travel,Eco,503,2,5,2,4,2,1,1,3,4,5,5,1,5,1,139,127.0,neutral or dissatisfied +70598,13964,Male,Loyal Customer,34,Personal Travel,Eco,153,3,5,3,1,3,3,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +70599,16372,Male,Loyal Customer,40,Business travel,Eco,1325,3,2,2,2,3,4,3,3,1,5,5,4,2,3,30,23.0,satisfied +70600,90394,Male,Loyal Customer,47,Personal Travel,Business,444,2,5,2,2,3,4,4,4,4,2,2,3,4,5,0,19.0,neutral or dissatisfied +70601,125261,Female,Loyal Customer,67,Business travel,Business,1488,3,3,3,3,5,5,4,2,2,2,2,3,2,4,21,25.0,satisfied +70602,120451,Female,Loyal Customer,33,Personal Travel,Eco,449,4,4,4,2,5,4,5,5,5,2,4,4,4,5,0,0.0,satisfied +70603,28844,Female,Loyal Customer,49,Business travel,Business,679,5,5,5,5,2,5,5,3,3,4,3,4,3,4,2,3.0,satisfied +70604,11171,Female,Loyal Customer,9,Personal Travel,Eco,316,3,3,3,1,4,3,4,4,1,4,2,2,5,4,0,0.0,neutral or dissatisfied +70605,88147,Male,Loyal Customer,57,Business travel,Business,442,1,1,1,1,2,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +70606,30618,Female,disloyal Customer,26,Business travel,Eco,524,4,3,4,4,2,4,4,2,2,3,4,3,1,2,0,4.0,neutral or dissatisfied +70607,25464,Male,Loyal Customer,46,Business travel,Business,2792,3,3,5,3,4,4,4,4,4,4,4,5,4,3,13,4.0,satisfied +70608,23329,Male,Loyal Customer,53,Business travel,Business,3206,4,5,5,5,2,3,3,4,4,4,4,3,4,3,14,39.0,neutral or dissatisfied +70609,116748,Female,Loyal Customer,22,Personal Travel,Eco Plus,358,3,2,2,3,1,2,1,1,2,2,3,3,4,1,0,0.0,neutral or dissatisfied +70610,65555,Male,Loyal Customer,40,Business travel,Business,175,0,4,0,2,3,4,5,1,1,1,1,3,1,5,9,23.0,satisfied +70611,126144,Male,Loyal Customer,47,Business travel,Business,631,5,5,5,5,2,5,5,4,4,4,4,5,4,3,30,17.0,satisfied +70612,90481,Female,Loyal Customer,41,Business travel,Business,442,4,4,4,4,5,4,4,5,5,5,5,3,5,3,3,0.0,satisfied +70613,108786,Female,Loyal Customer,56,Business travel,Business,406,3,1,1,1,1,3,2,3,3,3,3,1,3,1,12,1.0,neutral or dissatisfied +70614,2344,Female,disloyal Customer,52,Business travel,Business,690,1,1,1,2,4,1,4,4,1,4,3,1,2,4,0,0.0,neutral or dissatisfied +70615,112087,Female,Loyal Customer,30,Personal Travel,Eco,1491,1,1,1,3,1,1,1,1,4,3,4,4,3,1,0,0.0,neutral or dissatisfied +70616,110070,Female,Loyal Customer,47,Business travel,Business,869,4,1,3,1,4,2,3,4,4,4,4,2,4,4,0,2.0,neutral or dissatisfied +70617,20409,Female,Loyal Customer,27,Business travel,Business,1811,3,3,3,3,4,4,5,4,3,2,5,4,3,4,39,25.0,satisfied +70618,52625,Male,Loyal Customer,41,Business travel,Business,119,3,3,3,3,1,2,4,4,4,4,3,1,4,2,0,0.0,satisfied +70619,34206,Female,Loyal Customer,65,Personal Travel,Eco,1237,1,5,1,3,2,4,5,5,5,1,3,3,5,5,0,0.0,neutral or dissatisfied +70620,72487,Male,Loyal Customer,52,Business travel,Business,1017,3,3,1,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +70621,127351,Male,Loyal Customer,80,Business travel,Business,2410,4,3,5,3,4,4,4,2,2,1,4,1,2,2,0,15.0,neutral or dissatisfied +70622,114223,Male,Loyal Customer,33,Business travel,Business,819,2,2,2,2,2,1,2,2,1,4,3,1,3,2,18,6.0,neutral or dissatisfied +70623,29853,Male,Loyal Customer,30,Business travel,Business,123,1,1,1,1,5,5,5,5,1,3,1,2,1,5,0,0.0,satisfied +70624,38107,Female,disloyal Customer,21,Business travel,Business,1237,3,1,3,3,1,3,1,1,1,3,3,1,3,1,49,31.0,neutral or dissatisfied +70625,79981,Male,Loyal Customer,35,Personal Travel,Eco,1010,2,5,2,3,2,2,2,2,5,4,1,3,4,2,0,30.0,neutral or dissatisfied +70626,83413,Male,Loyal Customer,34,Business travel,Business,632,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +70627,86302,Female,Loyal Customer,42,Business travel,Business,2303,1,1,1,1,3,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +70628,31617,Female,Loyal Customer,10,Business travel,Business,3963,3,1,1,1,3,3,3,3,2,2,3,3,3,3,0,7.0,neutral or dissatisfied +70629,25645,Male,Loyal Customer,16,Personal Travel,Eco,666,3,3,3,3,1,3,1,1,2,5,3,4,1,1,8,0.0,neutral or dissatisfied +70630,76501,Female,Loyal Customer,44,Business travel,Business,481,4,4,4,4,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +70631,95971,Female,Loyal Customer,57,Business travel,Business,583,3,3,3,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +70632,113406,Female,Loyal Customer,42,Business travel,Business,258,4,4,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +70633,92993,Male,Loyal Customer,48,Personal Travel,Eco,738,1,5,0,2,4,0,4,4,5,2,4,3,5,4,64,49.0,neutral or dissatisfied +70634,49404,Female,disloyal Customer,43,Business travel,Eco,86,3,0,3,4,2,3,2,2,4,3,4,3,2,2,37,36.0,neutral or dissatisfied +70635,29443,Female,Loyal Customer,51,Business travel,Eco,421,5,2,2,2,1,2,2,5,5,5,5,5,5,2,0,0.0,satisfied +70636,56847,Female,disloyal Customer,34,Business travel,Business,2454,3,3,3,3,3,2,2,3,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +70637,58858,Male,disloyal Customer,23,Business travel,Eco,888,5,5,5,1,5,5,5,5,3,5,5,4,4,5,0,13.0,satisfied +70638,33058,Female,Loyal Customer,63,Personal Travel,Eco,216,4,2,0,4,3,3,4,4,4,0,1,4,4,1,0,0.0,neutral or dissatisfied +70639,39632,Female,disloyal Customer,32,Business travel,Eco Plus,908,3,3,3,3,3,3,3,3,4,1,5,5,3,3,0,0.0,neutral or dissatisfied +70640,85357,Male,Loyal Customer,38,Personal Travel,Eco Plus,689,3,4,3,2,2,3,4,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +70641,24218,Male,Loyal Customer,41,Business travel,Eco,302,5,3,3,3,5,5,5,5,1,1,1,3,2,5,9,0.0,satisfied +70642,6234,Female,disloyal Customer,22,Business travel,Eco,413,0,0,0,5,3,0,1,3,5,4,4,3,5,3,22,14.0,satisfied +70643,15609,Female,Loyal Customer,58,Business travel,Business,292,5,5,5,5,1,3,3,5,5,5,5,4,5,5,0,0.0,satisfied +70644,77010,Female,Loyal Customer,39,Business travel,Business,2542,5,3,5,5,5,4,5,4,4,4,4,5,4,4,113,99.0,satisfied +70645,52509,Male,Loyal Customer,53,Personal Travel,Business,119,2,3,2,3,4,5,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +70646,31412,Male,Loyal Customer,26,Business travel,Business,1703,1,1,1,1,4,4,4,4,1,5,3,1,2,4,4,2.0,satisfied +70647,117392,Female,disloyal Customer,30,Business travel,Eco Plus,912,4,4,4,3,4,4,4,4,1,5,4,2,3,4,0,0.0,neutral or dissatisfied +70648,64671,Male,Loyal Customer,40,Business travel,Business,190,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,,satisfied +70649,45788,Female,disloyal Customer,38,Business travel,Eco,216,4,0,4,1,2,4,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +70650,93444,Female,Loyal Customer,19,Personal Travel,Eco,697,3,1,4,4,3,4,3,3,1,2,3,2,4,3,8,0.0,neutral or dissatisfied +70651,96871,Female,Loyal Customer,48,Personal Travel,Eco,571,3,5,3,2,2,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +70652,103224,Female,disloyal Customer,25,Business travel,Eco,351,3,1,4,3,3,4,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +70653,42632,Male,Loyal Customer,40,Business travel,Eco,146,3,4,4,4,3,3,3,3,4,2,1,1,2,3,0,0.0,satisfied +70654,71134,Female,Loyal Customer,58,Personal Travel,Eco,1739,1,4,1,2,4,4,5,3,3,1,3,5,3,4,48,46.0,neutral or dissatisfied +70655,105115,Male,Loyal Customer,39,Business travel,Business,3598,3,3,4,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +70656,118716,Male,Loyal Customer,49,Personal Travel,Eco,651,5,1,5,3,3,5,3,3,1,5,3,1,3,3,0,0.0,satisfied +70657,75104,Male,Loyal Customer,40,Personal Travel,Business,1726,2,5,2,2,5,3,5,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +70658,106484,Male,Loyal Customer,43,Personal Travel,Eco,1624,4,4,3,4,5,3,4,5,1,5,3,2,3,5,3,30.0,neutral or dissatisfied +70659,43831,Male,Loyal Customer,49,Business travel,Eco,255,4,2,2,2,4,4,4,4,1,4,2,2,3,4,0,0.0,satisfied +70660,39767,Female,Loyal Customer,53,Business travel,Business,546,2,1,1,1,5,3,4,2,2,2,2,1,2,3,24,19.0,neutral or dissatisfied +70661,68197,Female,Loyal Customer,25,Business travel,Business,2650,5,5,5,5,5,4,5,5,3,5,5,4,4,5,0,0.0,satisfied +70662,70730,Male,disloyal Customer,25,Business travel,Business,275,4,0,4,3,2,4,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +70663,70884,Male,Loyal Customer,55,Business travel,Business,1814,1,1,1,1,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +70664,11720,Female,Loyal Customer,44,Business travel,Business,1654,3,3,3,3,5,5,5,4,4,4,4,3,4,5,8,0.0,satisfied +70665,31326,Female,Loyal Customer,23,Business travel,Business,3012,1,4,4,4,1,1,1,1,1,4,2,3,2,1,24,15.0,neutral or dissatisfied +70666,2664,Male,Loyal Customer,9,Business travel,Business,2595,4,4,4,4,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +70667,91627,Male,Loyal Customer,36,Business travel,Business,2452,3,3,3,3,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +70668,116666,Female,Loyal Customer,52,Business travel,Business,2163,5,5,5,5,4,5,5,3,3,3,3,4,3,4,24,16.0,satisfied +70669,53895,Female,Loyal Customer,14,Personal Travel,Eco,140,1,3,1,3,2,1,2,2,4,2,1,5,4,2,39,32.0,neutral or dissatisfied +70670,21898,Female,disloyal Customer,38,Business travel,Eco,503,2,0,2,1,4,2,4,4,5,2,4,2,3,4,0,0.0,neutral or dissatisfied +70671,68483,Male,Loyal Customer,50,Business travel,Business,2854,2,3,3,3,4,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +70672,33227,Female,disloyal Customer,50,Business travel,Eco Plus,101,3,3,3,4,2,3,2,2,2,3,2,5,5,2,0,0.0,neutral or dissatisfied +70673,128596,Male,Loyal Customer,43,Business travel,Business,1911,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +70674,128037,Female,Loyal Customer,39,Business travel,Business,3964,5,5,5,5,5,5,1,5,5,5,5,2,5,4,0,0.0,satisfied +70675,8621,Male,disloyal Customer,23,Business travel,Eco,181,4,0,4,2,4,4,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +70676,62340,Female,Loyal Customer,48,Business travel,Business,3087,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +70677,16325,Female,Loyal Customer,26,Business travel,Eco,602,2,1,3,1,2,2,1,2,1,3,3,4,4,2,26,35.0,neutral or dissatisfied +70678,100271,Male,disloyal Customer,27,Business travel,Business,1073,1,1,1,3,4,1,4,4,1,5,4,1,4,4,0,0.0,neutral or dissatisfied +70679,115792,Male,Loyal Customer,22,Business travel,Business,1658,3,2,2,2,3,3,3,3,1,5,3,4,3,3,10,0.0,neutral or dissatisfied +70680,50274,Male,Loyal Customer,39,Business travel,Business,3692,2,2,4,2,3,5,1,5,5,5,4,5,5,5,0,0.0,satisfied +70681,61122,Male,Loyal Customer,40,Business travel,Business,3500,4,4,4,4,2,5,4,4,4,3,4,3,4,3,0,0.0,satisfied +70682,111807,Male,Loyal Customer,21,Personal Travel,Eco,349,2,4,2,4,4,2,4,4,3,3,5,5,5,4,46,46.0,neutral or dissatisfied +70683,87838,Female,Loyal Customer,45,Personal Travel,Eco,214,2,0,0,4,3,4,4,4,4,0,5,3,4,3,0,0.0,neutral or dissatisfied +70684,89899,Male,disloyal Customer,41,Business travel,Eco,1416,1,1,1,3,4,1,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +70685,41738,Male,Loyal Customer,36,Business travel,Business,295,4,4,5,4,2,1,5,4,4,4,4,5,4,1,0,0.0,satisfied +70686,112775,Male,Loyal Customer,49,Personal Travel,Eco,590,1,5,1,3,3,1,3,3,4,2,4,4,4,3,0,8.0,neutral or dissatisfied +70687,94115,Female,Loyal Customer,24,Personal Travel,Business,319,2,5,3,5,2,3,4,2,1,5,2,1,2,2,0,0.0,neutral or dissatisfied +70688,80173,Female,Loyal Customer,53,Business travel,Business,2586,5,5,5,5,5,5,5,5,1,4,2,5,5,5,16,15.0,satisfied +70689,113930,Male,Loyal Customer,39,Business travel,Business,1750,4,4,4,4,5,3,4,4,4,4,4,3,4,4,53,42.0,satisfied +70690,94960,Male,Loyal Customer,70,Business travel,Business,3033,5,3,3,3,5,4,4,5,5,4,5,1,5,4,12,20.0,neutral or dissatisfied +70691,49657,Female,Loyal Customer,38,Business travel,Business,1625,0,5,0,1,3,3,4,4,4,4,4,2,4,3,0,0.0,satisfied +70692,49803,Male,Loyal Customer,65,Business travel,Eco,262,4,4,4,4,4,4,4,4,1,5,3,1,4,4,48,55.0,neutral or dissatisfied +70693,3552,Female,Loyal Customer,58,Business travel,Business,227,5,5,5,5,2,5,4,4,4,4,4,5,4,5,7,0.0,satisfied +70694,93134,Male,Loyal Customer,48,Business travel,Eco,1183,2,2,2,2,2,2,2,2,2,5,2,3,3,2,42,22.0,neutral or dissatisfied +70695,59176,Male,Loyal Customer,14,Personal Travel,Eco Plus,1744,3,4,3,2,2,3,2,2,3,5,4,3,5,2,72,80.0,neutral or dissatisfied +70696,63093,Male,Loyal Customer,41,Business travel,Business,2309,5,5,5,5,2,4,5,5,5,5,5,3,5,4,16,15.0,satisfied +70697,45016,Male,Loyal Customer,32,Personal Travel,Eco,222,1,4,0,4,2,0,2,2,5,1,4,2,4,2,9,5.0,neutral or dissatisfied +70698,92049,Female,disloyal Customer,38,Business travel,Business,1589,2,3,3,2,2,3,2,2,4,3,3,3,4,2,16,0.0,neutral or dissatisfied +70699,7625,Female,Loyal Customer,59,Business travel,Business,604,1,5,5,5,1,3,3,1,1,1,1,1,1,3,18,23.0,neutral or dissatisfied +70700,107599,Female,Loyal Customer,45,Business travel,Business,423,5,5,1,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +70701,49778,Female,Loyal Customer,36,Business travel,Business,3500,5,5,1,5,5,3,4,4,4,4,4,5,4,2,0,0.0,satisfied +70702,6394,Female,Loyal Customer,48,Business travel,Eco,296,3,3,3,3,5,4,4,3,3,3,3,4,3,1,1,1.0,neutral or dissatisfied +70703,74605,Female,disloyal Customer,27,Business travel,Eco,1103,3,2,2,4,5,3,5,5,3,4,4,1,4,5,0,7.0,neutral or dissatisfied +70704,48404,Male,Loyal Customer,14,Personal Travel,Eco Plus,522,1,5,1,4,5,1,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +70705,63666,Female,Loyal Customer,32,Personal Travel,Eco,2405,3,2,3,3,3,3,3,3,4,3,2,4,3,3,0,0.0,neutral or dissatisfied +70706,121186,Female,Loyal Customer,53,Personal Travel,Eco,2370,1,4,1,3,1,5,5,2,4,2,4,5,1,5,69,65.0,neutral or dissatisfied +70707,30417,Female,Loyal Customer,55,Personal Travel,Eco Plus,775,0,5,0,1,3,5,4,3,3,0,3,4,3,3,0,5.0,satisfied +70708,12358,Female,Loyal Customer,41,Business travel,Business,3500,2,2,2,2,3,2,2,5,5,5,3,2,5,2,2,0.0,satisfied +70709,63170,Male,Loyal Customer,49,Business travel,Business,1869,2,2,4,2,4,4,4,5,5,5,5,3,5,4,0,8.0,satisfied +70710,98308,Male,Loyal Customer,51,Business travel,Business,1565,3,3,3,3,4,5,5,4,4,5,4,4,4,4,32,55.0,satisfied +70711,122190,Female,Loyal Customer,40,Business travel,Business,1690,3,3,3,3,2,4,3,3,3,3,3,4,3,3,0,19.0,neutral or dissatisfied +70712,126261,Male,Loyal Customer,53,Business travel,Business,1648,1,1,1,1,3,5,3,5,5,5,5,3,5,3,4,0.0,satisfied +70713,629,Male,disloyal Customer,35,Business travel,Business,89,3,3,3,3,3,3,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +70714,103333,Female,Loyal Customer,70,Personal Travel,Eco,1371,3,5,3,2,4,4,5,1,1,3,1,3,1,4,3,0.0,neutral or dissatisfied +70715,123997,Male,Loyal Customer,50,Business travel,Business,3660,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +70716,34195,Male,Loyal Customer,55,Personal Travel,Eco,1189,1,5,1,1,2,1,2,2,4,5,4,5,4,2,37,22.0,neutral or dissatisfied +70717,26320,Female,disloyal Customer,34,Business travel,Eco,892,3,3,3,3,5,3,5,5,3,2,3,1,3,5,0,0.0,neutral or dissatisfied +70718,26875,Female,disloyal Customer,38,Business travel,Eco,829,2,2,2,2,4,2,4,4,5,1,1,4,5,4,0,0.0,neutral or dissatisfied +70719,450,Female,Loyal Customer,32,Business travel,Business,1804,2,2,2,2,5,5,4,5,5,2,4,3,4,5,0,0.0,satisfied +70720,19149,Female,disloyal Customer,21,Business travel,Eco,321,3,4,3,4,2,3,2,2,5,5,5,2,2,2,0,3.0,neutral or dissatisfied +70721,72965,Female,Loyal Customer,69,Business travel,Business,2410,3,4,4,4,1,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +70722,126335,Female,Loyal Customer,32,Personal Travel,Eco,650,1,4,1,4,5,1,5,5,1,5,4,4,4,5,1,0.0,neutral or dissatisfied +70723,39212,Male,Loyal Customer,49,Business travel,Business,173,5,5,5,5,5,5,5,5,5,5,4,5,5,3,50,73.0,satisfied +70724,6356,Male,Loyal Customer,66,Business travel,Business,1946,0,0,0,3,3,5,5,5,5,5,5,3,5,3,57,46.0,satisfied +70725,80509,Male,Loyal Customer,19,Business travel,Business,1749,2,2,2,2,2,2,2,2,1,5,4,1,4,2,0,0.0,neutral or dissatisfied +70726,64083,Female,Loyal Customer,65,Personal Travel,Eco,919,1,1,1,3,3,3,3,3,3,1,1,3,3,1,0,0.0,neutral or dissatisfied +70727,128312,Male,Loyal Customer,42,Business travel,Business,2154,1,3,1,1,5,5,4,5,5,5,5,5,5,4,2,0.0,satisfied +70728,15871,Male,disloyal Customer,37,Business travel,Eco,618,3,3,4,4,3,4,3,3,3,3,3,4,3,3,43,50.0,neutral or dissatisfied +70729,83086,Male,disloyal Customer,35,Business travel,Business,1084,4,4,4,4,5,4,5,5,1,1,3,3,4,5,17,2.0,neutral or dissatisfied +70730,84712,Male,disloyal Customer,27,Business travel,Business,547,2,2,2,3,3,2,3,3,4,4,3,2,3,3,28,21.0,neutral or dissatisfied +70731,84084,Male,Loyal Customer,8,Personal Travel,Eco,773,5,4,5,1,3,5,2,3,3,4,4,3,5,3,0,0.0,satisfied +70732,22794,Male,disloyal Customer,23,Business travel,Eco,302,2,5,2,3,3,2,5,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +70733,24002,Male,Loyal Customer,36,Business travel,Eco,427,5,3,3,3,5,5,5,5,2,5,1,4,5,5,9,13.0,satisfied +70734,125293,Female,Loyal Customer,50,Business travel,Business,678,3,2,2,2,3,3,2,3,3,3,3,4,3,1,31,25.0,neutral or dissatisfied +70735,20054,Male,disloyal Customer,25,Business travel,Eco,338,5,5,5,3,4,5,1,4,3,5,2,2,4,4,0,0.0,satisfied +70736,81788,Female,Loyal Customer,23,Business travel,Eco,1416,2,2,2,2,2,2,1,2,3,2,4,2,4,2,14,4.0,neutral or dissatisfied +70737,25705,Female,Loyal Customer,38,Business travel,Business,2650,5,5,5,5,1,5,2,4,4,4,4,4,4,2,21,11.0,satisfied +70738,9946,Female,Loyal Customer,35,Business travel,Eco,508,2,2,2,2,2,2,2,2,3,3,3,2,3,2,165,156.0,neutral or dissatisfied +70739,105678,Female,Loyal Customer,20,Business travel,Business,1782,2,5,5,5,2,2,2,2,2,1,3,4,4,2,2,23.0,neutral or dissatisfied +70740,81305,Female,Loyal Customer,59,Business travel,Business,3877,1,5,3,5,2,3,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +70741,81349,Male,Loyal Customer,20,Personal Travel,Eco,1299,2,4,2,2,3,2,3,3,3,5,4,4,5,3,0,1.0,neutral or dissatisfied +70742,13717,Female,disloyal Customer,29,Business travel,Eco,441,2,3,2,3,5,2,2,5,5,5,2,5,4,5,1,0.0,neutral or dissatisfied +70743,99179,Female,Loyal Customer,71,Business travel,Business,3344,2,2,2,2,4,5,5,4,4,4,4,4,4,4,4,0.0,satisfied +70744,56466,Male,Loyal Customer,59,Business travel,Business,2620,3,3,3,3,4,4,5,4,4,4,4,4,4,3,7,0.0,satisfied +70745,41184,Male,Loyal Customer,35,Business travel,Eco,429,5,1,1,1,5,5,5,5,3,4,3,2,4,5,0,3.0,satisfied +70746,71109,Female,Loyal Customer,41,Business travel,Business,2072,3,3,2,3,2,4,4,4,4,4,4,4,4,4,26,32.0,satisfied +70747,82707,Male,Loyal Customer,15,Personal Travel,Eco,632,2,4,2,1,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +70748,124013,Male,disloyal Customer,22,Business travel,Eco,184,1,0,1,3,2,1,2,2,1,5,3,3,1,2,0,0.0,neutral or dissatisfied +70749,6684,Male,Loyal Customer,44,Business travel,Eco,403,4,2,2,2,4,4,4,4,3,2,3,3,4,4,15,27.0,neutral or dissatisfied +70750,106892,Male,Loyal Customer,13,Personal Travel,Eco,577,1,4,0,4,4,0,4,4,4,2,4,3,4,4,17,8.0,neutral or dissatisfied +70751,70472,Male,Loyal Customer,33,Business travel,Business,867,5,5,5,5,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +70752,38272,Female,Loyal Customer,56,Personal Travel,Eco,1173,3,4,3,2,4,3,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +70753,79752,Female,Loyal Customer,31,Business travel,Business,760,2,2,2,2,3,3,3,3,4,4,5,4,4,3,0,0.0,satisfied +70754,18558,Female,Loyal Customer,31,Business travel,Eco,383,4,4,4,4,4,4,4,4,5,5,4,2,5,4,99,99.0,satisfied +70755,55423,Male,disloyal Customer,30,Business travel,Business,2254,4,4,4,2,3,4,3,3,3,2,4,5,5,3,16,0.0,neutral or dissatisfied +70756,19349,Female,Loyal Customer,56,Business travel,Business,692,1,1,1,1,2,2,2,1,4,5,1,2,5,2,136,135.0,satisfied +70757,90162,Female,Loyal Customer,67,Personal Travel,Eco,983,2,4,2,3,2,5,5,3,3,2,3,3,3,4,30,65.0,neutral or dissatisfied +70758,3922,Female,Loyal Customer,29,Personal Travel,Eco,213,4,1,0,4,2,0,2,2,3,1,3,4,4,2,0,0.0,satisfied +70759,79583,Female,Loyal Customer,49,Business travel,Business,760,1,2,1,1,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +70760,105136,Male,disloyal Customer,22,Business travel,Eco,277,2,4,2,3,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +70761,75338,Female,Loyal Customer,58,Personal Travel,Eco,2615,3,5,3,4,3,3,2,4,3,3,4,2,5,2,0,0.0,neutral or dissatisfied +70762,122206,Female,Loyal Customer,31,Business travel,Business,1564,2,4,4,4,2,2,2,2,2,3,4,4,3,2,14,5.0,neutral or dissatisfied +70763,26429,Male,Loyal Customer,50,Business travel,Business,925,1,1,1,1,2,4,2,4,4,4,4,5,4,1,116,102.0,satisfied +70764,38250,Male,Loyal Customer,44,Business travel,Business,1050,5,5,5,5,1,4,1,4,4,4,4,3,4,1,0,0.0,satisfied +70765,11795,Female,Loyal Customer,64,Business travel,Business,2765,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +70766,65470,Male,Loyal Customer,49,Business travel,Business,1067,3,3,3,3,3,4,5,5,5,5,5,4,5,5,25,22.0,satisfied +70767,90348,Female,Loyal Customer,24,Business travel,Business,1719,4,4,4,4,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +70768,84889,Female,Loyal Customer,33,Personal Travel,Eco,547,3,4,3,3,4,3,4,4,4,2,3,3,4,4,8,7.0,neutral or dissatisfied +70769,59929,Female,Loyal Customer,35,Business travel,Business,937,5,5,5,5,3,4,4,5,5,5,5,4,5,4,10,11.0,satisfied +70770,70574,Male,Loyal Customer,7,Personal Travel,Eco,1258,3,4,3,3,4,3,4,4,4,4,3,5,5,4,0,0.0,neutral or dissatisfied +70771,44692,Female,disloyal Customer,26,Business travel,Eco,67,4,5,4,2,5,4,5,5,1,5,1,5,5,5,11,10.0,neutral or dissatisfied +70772,1040,Male,Loyal Customer,47,Business travel,Eco,102,3,2,2,2,2,3,2,2,1,2,4,3,3,2,0,6.0,neutral or dissatisfied +70773,93105,Male,Loyal Customer,7,Personal Travel,Eco,641,2,5,2,3,1,2,1,1,4,2,4,5,4,1,0,4.0,neutral or dissatisfied +70774,44054,Female,Loyal Customer,36,Business travel,Eco Plus,287,5,5,5,5,5,5,5,5,4,3,4,3,3,5,0,0.0,satisfied +70775,59679,Male,Loyal Customer,18,Personal Travel,Eco,956,2,5,2,2,1,2,1,1,5,5,5,3,4,1,1,0.0,neutral or dissatisfied +70776,7583,Male,Loyal Customer,46,Business travel,Eco,194,4,4,4,4,4,4,4,4,5,2,3,2,3,4,42,25.0,satisfied +70777,129571,Female,Loyal Customer,54,Business travel,Eco Plus,2218,1,3,3,3,3,3,4,1,1,1,1,4,1,2,1,8.0,neutral or dissatisfied +70778,106418,Male,Loyal Customer,63,Personal Travel,Eco,674,3,5,3,1,1,3,1,1,5,3,4,3,5,1,9,6.0,neutral or dissatisfied +70779,73702,Female,Loyal Customer,33,Business travel,Business,2676,4,4,4,4,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +70780,1345,Female,Loyal Customer,52,Business travel,Business,1528,1,1,4,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +70781,76672,Male,Loyal Customer,55,Personal Travel,Eco,547,4,1,4,3,4,4,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +70782,59849,Male,Loyal Customer,40,Business travel,Business,3851,1,1,1,1,3,4,4,5,5,5,5,5,5,5,8,0.0,satisfied +70783,14718,Female,Loyal Customer,50,Personal Travel,Eco,419,2,2,4,3,3,3,3,1,1,4,1,1,1,1,0,0.0,neutral or dissatisfied +70784,40202,Female,Loyal Customer,40,Business travel,Business,2806,1,1,1,1,2,1,1,5,5,5,5,4,5,4,0,0.0,satisfied +70785,8140,Male,Loyal Customer,38,Business travel,Business,335,2,1,1,1,4,3,3,2,2,2,2,4,2,4,53,49.0,neutral or dissatisfied +70786,56877,Male,Loyal Customer,51,Business travel,Business,2565,4,4,4,4,4,4,4,5,3,4,5,4,5,4,93,93.0,satisfied +70787,68122,Female,Loyal Customer,31,Personal Travel,Eco,868,3,5,2,4,3,2,3,3,3,4,1,5,1,3,0,0.0,neutral or dissatisfied +70788,126947,Male,Loyal Customer,33,Business travel,Business,3411,1,1,1,1,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +70789,110412,Female,Loyal Customer,41,Business travel,Business,2842,1,4,4,4,1,3,4,1,1,1,1,4,1,3,1,2.0,neutral or dissatisfied +70790,100915,Male,Loyal Customer,57,Business travel,Business,377,2,2,2,2,3,5,5,4,4,4,4,4,4,3,5,6.0,satisfied +70791,85886,Male,Loyal Customer,28,Personal Travel,Eco,2172,4,4,4,5,2,4,2,2,4,4,4,4,5,2,0,3.0,neutral or dissatisfied +70792,20586,Female,Loyal Customer,27,Personal Travel,Eco,633,1,5,1,4,4,1,4,4,3,4,5,3,4,4,34,21.0,neutral or dissatisfied +70793,74657,Female,Loyal Customer,59,Personal Travel,Eco,1171,4,4,4,1,2,4,5,2,2,4,2,3,2,4,0,0.0,satisfied +70794,111588,Female,Loyal Customer,45,Personal Travel,Eco,359,4,4,4,3,4,5,2,5,5,4,5,2,5,4,52,46.0,neutral or dissatisfied +70795,92103,Female,Loyal Customer,55,Personal Travel,Eco,1535,5,4,5,4,4,3,4,4,4,5,4,1,4,4,29,5.0,satisfied +70796,109105,Male,Loyal Customer,16,Personal Travel,Eco,488,2,2,2,3,1,2,1,1,2,5,2,3,3,1,0,0.0,neutral or dissatisfied +70797,8073,Male,disloyal Customer,41,Business travel,Business,335,3,3,3,1,5,3,5,5,4,2,4,3,5,5,3,11.0,neutral or dissatisfied +70798,4456,Male,Loyal Customer,44,Personal Travel,Eco Plus,762,3,5,3,1,1,3,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +70799,82634,Male,Loyal Customer,69,Personal Travel,Eco,528,4,5,4,4,5,4,1,5,5,4,5,3,4,5,0,0.0,neutral or dissatisfied +70800,87079,Male,Loyal Customer,41,Business travel,Business,2124,1,1,1,1,3,4,4,5,5,5,5,4,5,4,5,4.0,satisfied +70801,120582,Male,disloyal Customer,26,Business travel,Business,980,4,4,4,3,5,4,4,5,5,2,4,4,4,5,0,0.0,satisfied +70802,68539,Female,Loyal Customer,46,Business travel,Eco,1013,4,2,2,2,5,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +70803,33820,Male,Loyal Customer,70,Personal Travel,Eco,1521,3,5,3,2,5,3,5,5,5,5,5,4,5,5,59,36.0,neutral or dissatisfied +70804,88265,Female,Loyal Customer,30,Business travel,Business,594,2,1,1,1,2,2,2,2,1,4,3,4,4,2,30,21.0,neutral or dissatisfied +70805,71034,Male,Loyal Customer,64,Business travel,Eco,802,4,2,2,2,4,4,4,4,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +70806,109521,Female,disloyal Customer,21,Business travel,Eco,861,2,2,2,3,2,2,2,2,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +70807,41331,Female,disloyal Customer,22,Business travel,Business,689,3,3,3,2,5,3,5,5,4,1,2,1,3,5,0,0.0,neutral or dissatisfied +70808,15716,Female,Loyal Customer,57,Business travel,Business,1777,3,5,5,5,2,3,3,3,3,3,3,4,3,3,45,28.0,neutral or dissatisfied +70809,115048,Female,Loyal Customer,44,Business travel,Business,1860,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,4.0,satisfied +70810,70045,Female,Loyal Customer,53,Personal Travel,Eco,583,2,4,2,3,5,4,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +70811,61047,Male,Loyal Customer,48,Business travel,Business,1506,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +70812,103028,Female,Loyal Customer,48,Business travel,Business,2339,2,5,5,5,1,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +70813,129134,Male,Loyal Customer,25,Business travel,Business,2728,5,5,1,5,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +70814,88210,Female,Loyal Customer,51,Business travel,Business,2046,4,4,4,4,4,5,4,4,4,4,4,3,4,3,6,6.0,satisfied +70815,24460,Female,Loyal Customer,21,Business travel,Business,1677,5,5,5,5,5,5,5,5,5,3,2,5,2,5,0,0.0,satisfied +70816,107310,Female,Loyal Customer,48,Personal Travel,Eco,283,1,2,4,3,2,4,3,4,4,4,4,2,4,1,9,1.0,neutral or dissatisfied +70817,82546,Female,Loyal Customer,44,Personal Travel,Eco,629,4,1,4,3,5,4,4,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +70818,95695,Female,Loyal Customer,61,Business travel,Business,3850,5,5,3,5,3,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +70819,43794,Female,Loyal Customer,52,Business travel,Eco,282,4,5,4,5,2,4,2,4,4,4,4,1,4,4,0,6.0,satisfied +70820,18443,Male,Loyal Customer,50,Business travel,Business,383,1,4,4,4,3,2,2,1,1,1,1,4,1,1,2,0.0,neutral or dissatisfied +70821,72537,Female,Loyal Customer,47,Business travel,Eco,1017,1,3,2,2,3,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +70822,18502,Female,Loyal Customer,39,Business travel,Eco,262,4,2,2,2,4,4,4,4,2,2,1,4,5,4,0,0.0,satisfied +70823,68935,Male,Loyal Customer,45,Business travel,Eco,646,4,2,2,2,4,4,4,4,2,1,3,1,4,4,0,0.0,neutral or dissatisfied +70824,88320,Female,disloyal Customer,25,Business travel,Business,240,5,0,5,4,3,5,3,3,4,2,5,4,5,3,17,15.0,satisfied +70825,114477,Female,Loyal Customer,45,Business travel,Business,337,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +70826,113869,Male,Loyal Customer,65,Personal Travel,Eco,1363,1,5,1,3,3,1,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +70827,59094,Female,Loyal Customer,59,Personal Travel,Eco,1726,4,3,5,3,3,2,3,1,1,5,1,3,1,1,0,0.0,neutral or dissatisfied +70828,79852,Female,Loyal Customer,51,Business travel,Eco,1089,2,5,5,5,2,4,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +70829,1283,Male,Loyal Customer,44,Personal Travel,Eco,229,2,5,2,3,3,2,3,3,5,3,4,5,5,3,1,0.0,neutral or dissatisfied +70830,73599,Female,disloyal Customer,26,Business travel,Business,204,5,4,5,2,3,5,3,3,5,3,5,4,5,3,58,54.0,satisfied +70831,114463,Male,Loyal Customer,49,Business travel,Business,373,2,3,3,3,5,4,4,2,2,2,2,3,2,2,87,77.0,neutral or dissatisfied +70832,70069,Female,Loyal Customer,27,Personal Travel,Business,460,2,3,2,1,2,2,2,2,2,4,2,3,4,2,0,0.0,neutral or dissatisfied +70833,53327,Female,Loyal Customer,23,Business travel,Eco Plus,901,0,5,0,5,3,0,1,3,4,3,4,5,1,3,9,3.0,satisfied +70834,28886,Male,Loyal Customer,36,Business travel,Business,671,1,1,1,1,2,3,5,4,4,4,4,1,4,3,0,7.0,satisfied +70835,71428,Male,Loyal Customer,39,Business travel,Business,3763,2,2,2,2,5,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +70836,8255,Female,Loyal Customer,51,Personal Travel,Eco,125,3,4,0,4,4,4,4,3,3,0,3,2,3,3,0,0.0,neutral or dissatisfied +70837,16867,Male,Loyal Customer,22,Business travel,Business,2426,2,3,4,3,2,2,2,2,1,4,1,1,1,2,53,73.0,neutral or dissatisfied +70838,50026,Female,disloyal Customer,38,Business travel,Eco,89,4,4,4,4,3,4,3,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +70839,115245,Male,Loyal Customer,35,Business travel,Eco,342,3,1,2,1,3,3,3,3,1,4,4,2,4,3,0,0.0,neutral or dissatisfied +70840,112963,Female,Loyal Customer,55,Personal Travel,Eco,1164,2,5,2,2,5,4,4,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +70841,114850,Female,Loyal Customer,42,Business travel,Business,2677,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +70842,75400,Male,Loyal Customer,53,Business travel,Business,2342,1,1,1,1,2,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +70843,65373,Male,Loyal Customer,49,Business travel,Business,2407,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +70844,67039,Female,disloyal Customer,22,Business travel,Eco,964,4,4,4,4,5,4,5,5,2,5,4,4,3,5,11,10.0,neutral or dissatisfied +70845,89949,Female,Loyal Customer,61,Personal Travel,Eco,1310,2,5,2,3,2,5,4,5,5,2,5,5,5,3,1,0.0,neutral or dissatisfied +70846,79366,Female,disloyal Customer,24,Business travel,Business,502,4,2,4,4,3,4,3,3,5,4,4,3,5,3,0,4.0,satisfied +70847,3293,Male,disloyal Customer,30,Personal Travel,Eco,479,3,5,3,1,4,3,1,4,5,2,4,5,2,4,41,24.0,neutral or dissatisfied +70848,119704,Male,Loyal Customer,48,Business travel,Business,2928,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,1.0,satisfied +70849,53701,Male,disloyal Customer,48,Business travel,Eco,1208,3,4,4,3,2,4,2,2,4,2,4,2,3,2,108,88.0,neutral or dissatisfied +70850,29344,Male,Loyal Customer,50,Business travel,Eco Plus,873,4,5,5,5,4,4,4,4,2,1,1,5,1,4,0,0.0,satisfied +70851,108980,Male,Loyal Customer,51,Business travel,Business,781,1,3,3,3,3,4,3,1,1,1,1,3,1,4,13,2.0,neutral or dissatisfied +70852,83121,Male,Loyal Customer,56,Personal Travel,Eco,1127,2,5,2,5,5,2,5,5,3,4,4,3,5,5,0,3.0,neutral or dissatisfied +70853,23560,Male,Loyal Customer,57,Personal Travel,Eco,770,4,5,4,1,4,4,2,4,5,2,4,5,5,4,17,37.0,satisfied +70854,35447,Female,Loyal Customer,45,Personal Travel,Eco,1074,2,4,2,2,4,5,5,4,4,2,4,5,4,4,40,38.0,neutral or dissatisfied +70855,39167,Female,Loyal Customer,78,Business travel,Eco,287,3,1,1,1,5,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +70856,65377,Female,disloyal Customer,45,Business travel,Eco,231,3,4,3,3,5,3,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +70857,39081,Male,disloyal Customer,27,Business travel,Eco,984,3,2,2,1,4,2,4,4,3,4,1,1,3,4,0,0.0,neutral or dissatisfied +70858,66309,Female,Loyal Customer,30,Business travel,Business,2896,3,4,4,4,3,3,3,3,3,4,4,1,3,3,0,9.0,neutral or dissatisfied +70859,126066,Male,Loyal Customer,53,Business travel,Business,1659,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +70860,6028,Female,Loyal Customer,54,Business travel,Business,1751,3,3,4,3,4,3,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +70861,46970,Male,Loyal Customer,20,Personal Travel,Eco,846,3,1,2,4,3,2,3,3,2,2,4,1,3,3,8,4.0,neutral or dissatisfied +70862,107265,Female,disloyal Customer,26,Business travel,Business,283,4,5,3,4,4,3,4,4,3,5,4,4,4,4,21,21.0,neutral or dissatisfied +70863,38508,Male,Loyal Customer,35,Business travel,Business,2521,5,5,5,5,2,5,1,4,4,4,4,5,4,2,5,9.0,satisfied +70864,50061,Female,disloyal Customer,41,Business travel,Business,304,2,2,2,4,1,2,1,1,5,5,4,2,4,1,0,0.0,neutral or dissatisfied +70865,122292,Female,Loyal Customer,20,Personal Travel,Eco,544,1,5,1,2,3,1,1,3,2,1,4,4,4,3,11,2.0,neutral or dissatisfied +70866,30186,Male,Loyal Customer,50,Business travel,Eco Plus,548,2,5,2,5,3,2,3,3,3,5,4,2,2,3,0,0.0,satisfied +70867,40755,Female,Loyal Customer,52,Business travel,Business,2103,5,5,3,5,5,2,5,4,4,4,4,1,4,4,0,0.0,satisfied +70868,40198,Female,Loyal Customer,39,Business travel,Business,358,2,2,2,2,2,3,2,5,5,5,5,2,5,5,0,0.0,satisfied +70869,76139,Female,disloyal Customer,32,Business travel,Business,689,4,4,4,5,2,4,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +70870,67088,Female,Loyal Customer,51,Business travel,Business,1818,1,1,2,1,3,5,5,4,4,4,4,5,4,5,0,1.0,satisfied +70871,49671,Male,Loyal Customer,39,Business travel,Business,308,0,0,0,1,3,1,2,2,2,2,2,3,2,3,0,0.0,satisfied +70872,27311,Female,Loyal Customer,40,Business travel,Eco,978,5,3,3,3,5,5,5,5,4,2,4,4,4,5,0,3.0,satisfied +70873,35197,Female,disloyal Customer,23,Business travel,Eco,1005,2,2,2,3,4,2,4,4,1,1,4,4,4,4,0,16.0,neutral or dissatisfied +70874,116085,Male,Loyal Customer,14,Personal Travel,Eco,446,2,4,2,4,4,2,4,4,4,4,2,5,2,4,0,0.0,neutral or dissatisfied +70875,121718,Female,Loyal Customer,51,Personal Travel,Eco,683,1,5,1,5,3,5,5,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +70876,93310,Male,Loyal Customer,15,Personal Travel,Eco,1733,2,5,2,3,2,5,5,1,1,4,3,5,4,5,206,215.0,neutral or dissatisfied +70877,9160,Male,Loyal Customer,27,Business travel,Eco,946,2,1,1,1,2,2,2,2,3,2,3,4,3,2,67,33.0,neutral or dissatisfied +70878,57712,Male,Loyal Customer,42,Personal Travel,Eco,867,0,1,0,3,1,0,1,1,1,4,3,2,3,1,0,0.0,satisfied +70879,94189,Female,Loyal Customer,51,Business travel,Business,1632,5,5,2,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +70880,77135,Male,disloyal Customer,20,Business travel,Eco,1185,4,4,4,3,2,4,2,2,4,2,3,3,4,2,3,0.0,neutral or dissatisfied +70881,4877,Female,Loyal Customer,38,Personal Travel,Eco,408,3,4,3,5,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +70882,27672,Female,disloyal Customer,37,Business travel,Eco,1216,4,4,4,3,4,4,4,4,2,4,5,4,3,4,0,0.0,neutral or dissatisfied +70883,87171,Female,Loyal Customer,37,Business travel,Business,946,1,1,1,1,4,5,4,5,5,5,5,5,5,4,12,13.0,satisfied +70884,84208,Male,Loyal Customer,39,Business travel,Business,432,4,4,4,4,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +70885,49581,Female,Loyal Customer,51,Business travel,Eco,308,5,4,4,4,4,5,2,5,5,5,5,3,5,4,9,57.0,satisfied +70886,57272,Male,Loyal Customer,44,Personal Travel,Eco,804,2,4,2,3,2,2,2,2,2,4,3,2,3,2,0,8.0,neutral or dissatisfied +70887,15052,Female,Loyal Customer,53,Business travel,Eco,176,4,2,2,2,5,5,1,4,4,4,4,4,4,3,0,0.0,satisfied +70888,32229,Male,disloyal Customer,59,Business travel,Eco,101,3,0,3,2,4,3,4,4,4,1,2,2,5,4,0,0.0,neutral or dissatisfied +70889,89863,Female,Loyal Customer,54,Business travel,Business,1416,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,2.0,satisfied +70890,103618,Female,Loyal Customer,53,Business travel,Business,405,4,4,4,4,3,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +70891,12212,Female,disloyal Customer,45,Business travel,Business,285,3,2,2,3,3,3,4,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +70892,45086,Male,Loyal Customer,55,Business travel,Business,2379,2,2,2,2,4,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +70893,120227,Male,Loyal Customer,35,Business travel,Business,2628,2,2,1,2,1,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +70894,99121,Female,Loyal Customer,62,Personal Travel,Eco,453,4,5,4,3,4,2,2,5,3,5,5,2,3,2,140,132.0,neutral or dissatisfied +70895,12104,Female,disloyal Customer,29,Business travel,Eco,1034,2,2,2,2,2,2,3,2,4,5,5,1,5,2,0,4.0,neutral or dissatisfied +70896,48847,Male,Loyal Customer,41,Personal Travel,Business,250,2,4,2,1,4,4,5,3,3,2,1,5,3,5,0,0.0,neutral or dissatisfied +70897,66815,Female,Loyal Customer,51,Business travel,Business,731,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +70898,33863,Female,Loyal Customer,10,Personal Travel,Eco,1562,2,4,2,4,3,2,3,3,1,3,3,3,3,3,10,0.0,neutral or dissatisfied +70899,61895,Male,disloyal Customer,30,Business travel,Eco Plus,2521,2,2,2,5,5,2,5,5,3,2,2,5,5,5,0,0.0,neutral or dissatisfied +70900,34601,Male,Loyal Customer,62,Personal Travel,Eco,1598,3,3,3,4,4,3,4,4,3,2,4,2,4,4,27,19.0,neutral or dissatisfied +70901,123052,Male,Loyal Customer,58,Business travel,Business,328,1,1,1,1,4,4,5,5,5,4,5,5,5,5,0,7.0,satisfied +70902,35894,Male,Loyal Customer,69,Personal Travel,Eco,1065,2,4,2,2,3,2,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +70903,57260,Male,Loyal Customer,51,Business travel,Business,3964,1,1,1,1,4,4,5,4,4,4,4,4,4,4,72,64.0,satisfied +70904,93822,Female,Loyal Customer,42,Business travel,Business,1536,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,6.0,satisfied +70905,36145,Female,disloyal Customer,12,Business travel,Eco Plus,1609,3,2,3,4,2,3,3,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +70906,35612,Male,Loyal Customer,61,Personal Travel,Eco Plus,972,4,5,4,2,1,4,1,1,3,4,5,3,4,1,0,3.0,neutral or dissatisfied +70907,98422,Female,Loyal Customer,54,Business travel,Business,2176,3,3,3,3,3,5,4,4,4,4,4,4,4,3,13,4.0,satisfied +70908,113981,Male,disloyal Customer,13,Business travel,Eco,1790,2,2,2,4,4,2,4,4,1,1,4,4,3,4,17,24.0,neutral or dissatisfied +70909,43599,Female,disloyal Customer,49,Business travel,Eco,252,3,5,3,1,5,3,5,5,4,4,2,3,4,5,0,0.0,neutral or dissatisfied +70910,73706,Male,disloyal Customer,25,Business travel,Eco,192,2,1,2,3,3,2,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +70911,4247,Male,Loyal Customer,22,Personal Travel,Eco,1020,1,2,1,4,2,1,2,2,1,4,3,1,4,2,0,0.0,neutral or dissatisfied +70912,22491,Male,Loyal Customer,37,Personal Travel,Eco,238,1,5,1,2,5,1,5,5,3,4,5,3,4,5,0,60.0,neutral or dissatisfied +70913,61531,Male,Loyal Customer,24,Personal Travel,Eco,2442,2,5,2,1,2,2,2,2,3,3,5,4,4,2,9,0.0,neutral or dissatisfied +70914,19660,Male,Loyal Customer,39,Business travel,Business,3021,3,5,5,5,4,2,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +70915,46420,Male,Loyal Customer,66,Business travel,Business,458,1,1,1,1,3,3,3,1,1,1,1,4,1,2,32,60.0,neutral or dissatisfied +70916,109596,Female,Loyal Customer,34,Business travel,Eco Plus,920,3,4,4,4,3,3,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +70917,98670,Male,Loyal Customer,35,Personal Travel,Eco,993,3,5,3,5,1,3,1,1,4,3,5,4,4,1,19,10.0,neutral or dissatisfied +70918,39484,Male,disloyal Customer,27,Business travel,Eco,867,4,4,4,4,1,4,1,1,1,1,5,5,1,1,0,0.0,neutral or dissatisfied +70919,57417,Male,Loyal Customer,17,Personal Travel,Eco,524,2,4,2,2,3,2,4,3,4,4,5,5,5,3,1,0.0,neutral or dissatisfied +70920,120264,Female,Loyal Customer,36,Personal Travel,Eco,237,3,2,0,3,3,0,3,3,2,2,3,3,3,3,34,44.0,neutral or dissatisfied +70921,43379,Female,Loyal Customer,7,Personal Travel,Eco,463,3,5,3,2,5,3,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +70922,11355,Male,Loyal Customer,7,Personal Travel,Eco,308,2,3,2,4,5,2,4,5,1,3,4,3,3,5,0,0.0,neutral or dissatisfied +70923,73255,Male,Loyal Customer,70,Business travel,Business,2594,1,2,2,2,3,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +70924,113465,Male,Loyal Customer,34,Business travel,Business,1741,5,5,4,5,2,4,5,4,4,4,5,3,4,5,0,4.0,satisfied +70925,128226,Female,Loyal Customer,65,Business travel,Business,2311,3,1,1,1,3,2,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +70926,124993,Female,disloyal Customer,23,Business travel,Business,184,5,0,5,1,5,5,5,5,3,2,5,3,4,5,12,0.0,satisfied +70927,73480,Male,Loyal Customer,28,Personal Travel,Eco,1012,3,2,4,1,1,4,1,1,2,5,1,3,2,1,0,0.0,neutral or dissatisfied +70928,8787,Male,Loyal Customer,48,Business travel,Business,3541,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +70929,68085,Female,disloyal Customer,36,Business travel,Eco,813,3,4,4,3,1,4,1,1,2,3,4,3,3,1,14,6.0,neutral or dissatisfied +70930,54188,Female,Loyal Customer,34,Personal Travel,Eco,1400,3,1,3,4,5,3,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +70931,37990,Male,Loyal Customer,27,Business travel,Business,1957,5,5,5,5,4,4,4,4,3,1,4,4,2,4,0,0.0,satisfied +70932,212,Female,Loyal Customer,30,Business travel,Business,213,2,5,5,5,5,4,2,5,1,2,3,1,4,5,25,13.0,neutral or dissatisfied +70933,39174,Male,disloyal Customer,18,Business travel,Business,237,5,0,5,3,3,5,3,3,2,5,5,2,2,3,0,0.0,satisfied +70934,125606,Male,Loyal Customer,58,Business travel,Business,1587,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +70935,125502,Female,Loyal Customer,38,Business travel,Business,666,3,4,3,4,3,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +70936,115302,Female,disloyal Customer,26,Business travel,Eco,390,3,0,3,4,3,3,3,3,3,3,3,1,4,3,99,87.0,neutral or dissatisfied +70937,81790,Male,Loyal Customer,40,Business travel,Business,1416,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +70938,104135,Male,Loyal Customer,37,Business travel,Eco,448,4,3,3,3,4,4,4,2,2,2,3,4,4,4,151,,satisfied +70939,80447,Male,Loyal Customer,50,Business travel,Business,1812,3,4,3,3,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +70940,99889,Female,Loyal Customer,41,Business travel,Business,2854,1,1,4,1,3,4,4,3,3,3,3,5,3,5,1,,satisfied +70941,112917,Male,disloyal Customer,17,Business travel,Business,1164,5,0,5,1,5,5,4,5,5,4,3,1,4,5,0,4.0,satisfied +70942,64449,Female,Loyal Customer,42,Business travel,Eco,589,1,3,3,3,5,3,4,1,1,1,1,2,1,1,0,18.0,neutral or dissatisfied +70943,26780,Female,Loyal Customer,23,Business travel,Business,1199,3,3,3,3,3,2,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +70944,10491,Male,Loyal Customer,55,Business travel,Business,2929,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,3.0,satisfied +70945,88197,Female,disloyal Customer,23,Business travel,Eco,515,2,0,2,3,4,2,4,4,3,3,4,5,5,4,58,44.0,neutral or dissatisfied +70946,116079,Female,Loyal Customer,63,Personal Travel,Eco,480,4,3,4,2,4,1,3,2,2,4,4,2,2,4,11,11.0,neutral or dissatisfied +70947,119131,Female,Loyal Customer,43,Business travel,Business,1698,3,3,3,3,2,4,4,5,5,5,5,5,5,3,1,8.0,satisfied +70948,103364,Female,Loyal Customer,63,Business travel,Eco,342,1,1,1,1,5,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +70949,60455,Female,Loyal Customer,49,Business travel,Business,886,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +70950,106194,Female,Loyal Customer,28,Personal Travel,Eco,436,2,5,2,2,3,2,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +70951,39126,Male,Loyal Customer,39,Business travel,Business,252,0,0,0,5,3,3,4,3,3,3,3,4,3,1,0,0.0,satisfied +70952,5249,Female,Loyal Customer,31,Business travel,Business,351,2,1,1,1,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +70953,71660,Male,Loyal Customer,67,Personal Travel,Eco,1197,4,4,4,1,1,4,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +70954,40266,Male,Loyal Customer,26,Personal Travel,Eco,358,3,5,3,2,3,3,3,3,3,5,5,5,4,3,0,10.0,neutral or dissatisfied +70955,51345,Male,Loyal Customer,55,Business travel,Eco Plus,266,3,3,3,3,3,3,3,3,1,2,4,3,3,3,0,0.0,neutral or dissatisfied +70956,15564,Male,Loyal Customer,49,Business travel,Business,3503,3,2,3,3,3,1,1,5,5,5,5,5,5,1,8,0.0,satisfied +70957,72600,Female,Loyal Customer,16,Personal Travel,Eco,1121,3,4,3,3,4,3,3,4,5,3,3,5,4,4,0,0.0,neutral or dissatisfied +70958,23124,Male,Loyal Customer,15,Business travel,Business,2292,4,1,1,1,2,2,4,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +70959,81842,Male,Loyal Customer,48,Personal Travel,Eco,1487,2,1,2,4,2,2,2,2,1,2,4,2,3,2,16,41.0,neutral or dissatisfied +70960,80675,Male,Loyal Customer,49,Personal Travel,Eco,821,0,1,0,4,2,0,1,2,1,1,3,1,4,2,0,0.0,satisfied +70961,21778,Female,Loyal Customer,46,Business travel,Business,352,3,3,2,3,3,5,3,4,4,4,4,1,4,5,0,0.0,satisfied +70962,84530,Male,Loyal Customer,39,Business travel,Business,2399,5,5,5,5,5,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +70963,24859,Male,Loyal Customer,43,Business travel,Business,3699,5,5,2,5,3,1,5,5,5,5,5,5,5,3,10,21.0,satisfied +70964,125001,Male,Loyal Customer,31,Business travel,Business,3318,2,2,2,2,3,4,4,3,5,3,5,4,4,3,0,0.0,satisfied +70965,71869,Female,Loyal Customer,40,Personal Travel,Eco,1744,4,5,4,2,4,4,1,4,5,2,5,4,5,4,1,0.0,satisfied +70966,16637,Female,Loyal Customer,33,Business travel,Business,488,3,3,3,3,3,4,4,5,5,5,5,2,5,1,0,0.0,satisfied +70967,54548,Female,Loyal Customer,8,Personal Travel,Eco,925,2,5,2,4,4,2,4,4,3,3,5,3,5,4,29,1.0,neutral or dissatisfied +70968,67003,Female,disloyal Customer,28,Business travel,Business,1119,5,5,5,3,4,0,4,4,4,2,5,3,4,4,0,0.0,satisfied +70969,7887,Male,Loyal Customer,61,Personal Travel,Eco,948,2,0,2,4,4,2,4,4,3,2,5,3,5,4,0,10.0,neutral or dissatisfied +70970,1897,Female,Loyal Customer,50,Business travel,Business,295,5,4,5,5,4,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +70971,98301,Male,Loyal Customer,58,Personal Travel,Eco,1136,1,5,1,4,3,1,4,3,3,3,5,5,4,3,9,5.0,neutral or dissatisfied +70972,33779,Male,Loyal Customer,42,Business travel,Business,2235,1,1,1,1,4,1,3,3,3,3,3,2,3,5,0,0.0,satisfied +70973,42708,Male,Loyal Customer,43,Personal Travel,Eco,516,4,5,4,5,4,4,4,4,1,5,3,3,1,4,0,0.0,satisfied +70974,14406,Male,Loyal Customer,54,Business travel,Eco Plus,900,3,4,4,4,2,3,2,2,3,4,2,4,2,2,28,25.0,neutral or dissatisfied +70975,29560,Male,disloyal Customer,29,Business travel,Eco,754,1,1,1,2,5,1,5,5,1,5,1,2,1,5,0,0.0,neutral or dissatisfied +70976,3232,Male,Loyal Customer,39,Business travel,Business,3735,2,2,2,2,2,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +70977,85652,Male,Loyal Customer,31,Personal Travel,Eco Plus,153,3,1,3,3,4,3,4,4,4,5,3,3,4,4,27,19.0,neutral or dissatisfied +70978,56498,Female,Loyal Customer,49,Business travel,Business,1068,1,1,1,1,5,5,5,4,4,4,4,3,4,3,23,9.0,satisfied +70979,83015,Female,disloyal Customer,27,Business travel,Business,1127,5,5,5,2,2,5,2,2,4,5,4,4,4,2,2,0.0,satisfied +70980,76254,Male,Loyal Customer,52,Personal Travel,Eco,1399,4,4,4,1,5,4,5,5,4,4,4,5,5,5,0,0.0,neutral or dissatisfied +70981,60485,Male,disloyal Customer,9,Business travel,Business,794,0,0,0,1,2,0,2,2,4,3,4,3,4,2,0,0.0,satisfied +70982,51959,Male,Loyal Customer,41,Business travel,Eco,347,4,2,2,2,4,4,4,4,1,4,3,3,5,4,0,0.0,satisfied +70983,44165,Female,Loyal Customer,36,Personal Travel,Eco,229,4,2,4,3,5,4,5,5,2,4,2,4,3,5,0,0.0,neutral or dissatisfied +70984,31367,Female,Loyal Customer,38,Business travel,Business,977,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +70985,54764,Male,Loyal Customer,34,Business travel,Eco Plus,965,3,1,4,1,3,3,3,3,2,1,4,1,3,3,30,13.0,neutral or dissatisfied +70986,105790,Female,Loyal Customer,49,Personal Travel,Eco,883,3,3,3,4,1,3,3,1,1,3,1,1,1,4,25,6.0,neutral or dissatisfied +70987,117048,Male,Loyal Customer,23,Business travel,Business,621,5,1,2,2,5,4,5,5,2,3,3,2,3,5,0,0.0,neutral or dissatisfied +70988,24935,Female,Loyal Customer,50,Business travel,Eco,606,3,4,4,4,2,3,3,3,3,3,3,4,3,1,4,0.0,neutral or dissatisfied +70989,100547,Female,Loyal Customer,57,Business travel,Eco Plus,580,3,3,3,3,2,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +70990,86468,Female,Loyal Customer,60,Business travel,Business,1554,1,1,1,1,4,3,3,5,5,5,5,2,5,5,0,2.0,satisfied +70991,102173,Male,Loyal Customer,34,Business travel,Business,236,4,4,4,4,5,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +70992,18880,Male,Loyal Customer,61,Business travel,Business,2270,1,2,2,2,4,2,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +70993,124775,Male,Loyal Customer,47,Business travel,Business,1679,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,10.0,satisfied +70994,93631,Female,Loyal Customer,39,Personal Travel,Eco,577,3,4,3,4,2,3,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +70995,8311,Male,Loyal Customer,64,Business travel,Eco Plus,125,3,2,4,4,3,3,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +70996,52227,Male,disloyal Customer,26,Business travel,Eco,751,2,2,2,4,5,2,1,5,3,2,5,1,2,5,0,0.0,neutral or dissatisfied +70997,18379,Male,Loyal Customer,45,Business travel,Eco,936,4,5,5,5,4,4,4,4,5,3,2,1,3,4,1,0.0,satisfied +70998,34226,Female,Loyal Customer,45,Business travel,Eco Plus,1046,5,4,5,4,1,5,5,5,5,5,5,4,5,3,36,34.0,satisfied +70999,64860,Male,Loyal Customer,13,Business travel,Business,3341,1,3,3,3,1,1,1,1,4,3,4,2,3,1,64,60.0,neutral or dissatisfied +71000,10855,Female,Loyal Customer,45,Business travel,Business,216,0,5,0,4,5,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +71001,108403,Male,Loyal Customer,41,Business travel,Business,1750,5,5,5,5,3,3,4,2,2,2,2,4,2,5,22,21.0,satisfied +71002,16315,Male,Loyal Customer,38,Business travel,Business,1886,2,3,3,3,5,1,2,2,2,3,2,3,2,3,67,90.0,neutral or dissatisfied +71003,59805,Female,Loyal Customer,42,Business travel,Business,2790,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +71004,86630,Female,disloyal Customer,23,Business travel,Business,746,0,0,0,3,4,0,4,4,5,3,5,4,4,4,4,0.0,satisfied +71005,67608,Female,Loyal Customer,40,Business travel,Business,1242,5,5,5,5,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +71006,28515,Male,Loyal Customer,36,Business travel,Business,2681,5,5,5,5,1,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +71007,49594,Female,Loyal Customer,37,Business travel,Business,3489,3,3,3,3,2,4,5,5,5,5,5,5,5,1,35,34.0,satisfied +71008,86560,Male,Loyal Customer,33,Business travel,Eco Plus,762,4,5,5,5,4,4,4,4,4,4,4,2,4,4,57,44.0,neutral or dissatisfied +71009,54326,Female,Loyal Customer,38,Business travel,Business,2970,4,4,4,4,3,3,2,4,4,4,4,1,4,4,0,0.0,satisfied +71010,98212,Male,disloyal Customer,26,Business travel,Business,842,2,2,2,5,4,2,4,4,5,3,4,5,4,4,0,9.0,neutral or dissatisfied +71011,65576,Female,Loyal Customer,54,Business travel,Business,2094,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,10.0,satisfied +71012,84515,Female,Loyal Customer,54,Business travel,Business,2504,1,1,1,1,4,4,4,3,4,4,4,4,5,4,159,140.0,satisfied +71013,24453,Female,Loyal Customer,50,Business travel,Eco,547,4,2,4,4,5,4,4,4,4,4,4,1,4,1,0,0.0,satisfied +71014,12428,Male,Loyal Customer,56,Personal Travel,Eco,253,3,5,3,4,1,3,1,1,4,4,2,3,3,1,0,0.0,neutral or dissatisfied +71015,117159,Female,Loyal Customer,21,Personal Travel,Eco,338,3,2,3,4,3,3,3,3,1,5,3,4,4,3,23,12.0,neutral or dissatisfied +71016,122881,Female,Loyal Customer,64,Personal Travel,Eco,226,2,4,2,1,4,4,4,4,4,2,4,4,4,4,52,39.0,neutral or dissatisfied +71017,2772,Male,Loyal Customer,39,Business travel,Business,764,2,2,2,2,4,5,4,4,4,3,4,3,4,4,0,0.0,satisfied +71018,12647,Male,Loyal Customer,61,Personal Travel,Eco,844,2,1,2,4,5,2,5,5,1,2,4,2,3,5,0,0.0,neutral or dissatisfied +71019,77190,Male,Loyal Customer,25,Personal Travel,Eco,290,2,4,2,4,1,2,3,1,4,2,5,4,5,1,28,16.0,neutral or dissatisfied +71020,43792,Male,Loyal Customer,48,Business travel,Business,2925,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +71021,28401,Male,Loyal Customer,53,Business travel,Eco,1709,2,4,4,4,2,2,2,2,3,2,1,2,1,2,0,0.0,neutral or dissatisfied +71022,37529,Female,Loyal Customer,28,Business travel,Business,2164,2,2,2,2,5,5,5,5,1,1,5,2,4,5,0,0.0,satisfied +71023,29556,Male,Loyal Customer,31,Business travel,Business,1448,4,4,4,4,5,5,5,5,4,3,3,5,1,5,5,8.0,satisfied +71024,60502,Male,Loyal Customer,54,Business travel,Business,1667,2,1,1,1,2,3,4,2,2,2,2,2,2,2,3,0.0,neutral or dissatisfied +71025,59073,Male,Loyal Customer,43,Business travel,Business,1662,2,2,3,2,4,2,5,5,5,5,5,5,5,5,0,0.0,satisfied +71026,100132,Male,Loyal Customer,51,Business travel,Business,2309,2,2,2,2,3,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +71027,66568,Male,Loyal Customer,42,Business travel,Business,624,5,5,5,5,2,4,4,4,4,4,4,3,4,5,14,41.0,satisfied +71028,95707,Male,Loyal Customer,60,Business travel,Business,3349,0,0,0,2,4,5,5,4,4,4,2,5,4,5,4,4.0,satisfied +71029,78037,Male,Loyal Customer,29,Personal Travel,Eco,332,2,3,2,3,1,2,1,1,3,2,1,3,4,1,0,0.0,neutral or dissatisfied +71030,101110,Female,Loyal Customer,48,Business travel,Business,2723,1,1,1,1,4,5,4,4,4,4,4,4,4,5,23,18.0,satisfied +71031,29964,Female,disloyal Customer,25,Business travel,Eco,183,2,0,2,2,2,2,5,2,2,5,3,2,2,2,0,0.0,neutral or dissatisfied +71032,36578,Female,Loyal Customer,26,Business travel,Business,1211,5,1,5,5,2,2,2,2,5,1,3,5,1,2,0,0.0,satisfied +71033,80745,Male,Loyal Customer,9,Personal Travel,Eco,393,2,2,2,2,2,2,2,2,4,3,2,3,3,2,0,0.0,neutral or dissatisfied +71034,40427,Male,Loyal Customer,27,Business travel,Business,175,0,4,0,4,2,2,3,2,2,2,5,1,1,2,0,0.0,satisfied +71035,32689,Female,Loyal Customer,37,Business travel,Eco,102,3,4,3,4,3,3,3,3,3,2,2,3,2,3,0,6.0,neutral or dissatisfied +71036,21155,Male,disloyal Customer,31,Business travel,Eco,954,3,3,3,3,4,3,4,4,1,4,2,5,1,4,41,11.0,neutral or dissatisfied +71037,90747,Female,Loyal Customer,25,Business travel,Business,3315,1,1,1,1,1,1,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +71038,22315,Female,disloyal Customer,56,Business travel,Eco,238,2,4,2,1,2,2,2,2,5,4,4,4,3,2,0,2.0,neutral or dissatisfied +71039,112245,Male,Loyal Customer,45,Business travel,Business,1703,5,5,5,5,5,4,4,5,5,4,5,4,5,4,46,55.0,satisfied +71040,108901,Female,disloyal Customer,36,Business travel,Eco,1075,1,1,1,4,3,1,3,3,4,4,4,2,3,3,0,6.0,neutral or dissatisfied +71041,628,Male,Loyal Customer,42,Business travel,Business,3903,5,5,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +71042,104332,Male,Loyal Customer,39,Business travel,Business,528,2,2,3,2,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +71043,62752,Female,Loyal Customer,27,Business travel,Business,2486,2,3,3,3,2,2,2,2,2,2,2,4,2,2,16,10.0,neutral or dissatisfied +71044,5053,Female,Loyal Customer,51,Business travel,Business,2733,2,1,1,1,1,4,3,2,2,1,2,2,2,1,18,13.0,neutral or dissatisfied +71045,74342,Female,Loyal Customer,45,Personal Travel,Business,1171,4,5,4,2,5,3,5,5,5,4,5,4,5,3,0,0.0,satisfied +71046,57587,Female,Loyal Customer,65,Personal Travel,Eco,1597,3,3,3,2,4,1,2,4,4,3,4,4,4,2,9,0.0,neutral or dissatisfied +71047,34500,Male,Loyal Customer,51,Business travel,Business,1428,5,5,5,5,3,3,4,4,4,4,4,5,4,1,2,0.0,satisfied +71048,20891,Female,Loyal Customer,39,Business travel,Eco Plus,457,5,5,5,5,5,5,5,5,2,2,2,3,2,5,0,0.0,satisfied +71049,48199,Female,disloyal Customer,17,Business travel,Eco,236,1,3,1,3,3,1,3,3,5,3,3,5,3,3,10,4.0,neutral or dissatisfied +71050,16410,Male,Loyal Customer,51,Business travel,Eco Plus,404,4,4,4,4,4,4,4,4,1,1,5,5,3,4,38,,satisfied +71051,114897,Male,Loyal Customer,53,Business travel,Business,446,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +71052,55355,Male,disloyal Customer,45,Business travel,Business,594,5,5,5,4,5,5,5,5,5,3,4,4,4,5,0,7.0,satisfied +71053,56537,Male,Loyal Customer,47,Business travel,Business,3511,3,3,3,3,4,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +71054,13950,Female,Loyal Customer,44,Personal Travel,Eco,192,1,5,0,3,0,3,4,5,5,4,4,4,5,4,151,136.0,neutral or dissatisfied +71055,28542,Female,Loyal Customer,67,Personal Travel,Eco,2688,4,5,4,3,2,5,5,4,4,4,1,5,4,5,0,18.0,neutral or dissatisfied +71056,901,Female,disloyal Customer,18,Business travel,Eco,309,3,3,3,3,2,3,2,2,2,1,4,4,3,2,48,63.0,neutral or dissatisfied +71057,110447,Male,Loyal Customer,38,Personal Travel,Eco,787,3,2,3,3,5,3,4,5,4,1,4,4,3,5,33,22.0,neutral or dissatisfied +71058,20112,Female,Loyal Customer,35,Business travel,Business,416,3,2,2,2,3,4,3,3,3,3,3,2,3,4,0,13.0,neutral or dissatisfied +71059,57999,Male,Loyal Customer,43,Business travel,Eco,1943,4,2,2,2,4,4,4,4,3,2,2,3,1,4,4,20.0,neutral or dissatisfied +71060,100451,Male,Loyal Customer,49,Personal Travel,Eco Plus,1180,1,5,0,1,5,0,2,5,4,5,4,5,4,5,1,0.0,neutral or dissatisfied +71061,81736,Male,disloyal Customer,48,Business travel,Business,1487,4,4,4,5,3,4,3,3,4,5,4,3,4,3,0,0.0,satisfied +71062,24354,Male,Loyal Customer,43,Business travel,Eco Plus,634,4,2,2,2,4,4,4,4,4,5,3,4,2,4,5,43.0,satisfied +71063,24249,Female,Loyal Customer,33,Personal Travel,Eco,302,4,5,4,4,1,4,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +71064,20282,Male,Loyal Customer,47,Personal Travel,Eco,224,3,1,0,2,3,0,3,3,4,1,2,2,2,3,0,0.0,neutral or dissatisfied +71065,92567,Female,Loyal Customer,54,Business travel,Business,2139,3,3,3,3,3,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +71066,41020,Female,disloyal Customer,29,Business travel,Eco,1195,3,4,4,1,2,4,2,2,5,5,3,4,4,2,0,2.0,neutral or dissatisfied +71067,19588,Male,Loyal Customer,12,Personal Travel,Eco,160,3,4,3,3,4,3,4,4,3,3,4,2,4,4,6,17.0,neutral or dissatisfied +71068,23813,Female,Loyal Customer,26,Personal Travel,Eco,304,5,4,5,3,5,5,2,5,4,2,4,3,4,5,0,0.0,satisfied +71069,88678,Female,Loyal Customer,50,Personal Travel,Eco,515,2,5,2,3,4,4,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +71070,100951,Female,Loyal Customer,40,Business travel,Business,1142,3,5,5,5,4,4,4,3,3,3,3,2,3,1,0,2.0,neutral or dissatisfied +71071,54909,Female,Loyal Customer,39,Business travel,Business,2175,1,1,1,1,4,4,5,4,4,4,4,5,4,4,0,2.0,satisfied +71072,79862,Male,disloyal Customer,23,Business travel,Eco,1010,4,4,4,3,3,4,3,3,5,2,4,4,4,3,0,0.0,satisfied +71073,91379,Male,Loyal Customer,42,Business travel,Business,2218,4,4,4,4,3,4,4,4,4,4,4,5,4,4,7,0.0,satisfied +71074,80471,Female,disloyal Customer,34,Business travel,Eco,1299,2,2,2,2,5,2,5,5,4,2,2,3,1,5,0,0.0,neutral or dissatisfied +71075,29387,Female,disloyal Customer,26,Business travel,Eco,2541,2,2,2,3,2,1,1,1,3,2,3,1,1,1,0,0.0,neutral or dissatisfied +71076,30945,Male,Loyal Customer,49,Business travel,Eco,1024,4,2,2,2,4,4,4,4,2,2,1,5,2,4,5,17.0,satisfied +71077,46958,Female,Loyal Customer,40,Personal Travel,Eco,776,3,4,3,3,1,3,1,1,4,4,4,3,4,1,8,12.0,neutral or dissatisfied +71078,116058,Female,Loyal Customer,14,Personal Travel,Eco,404,2,2,1,4,4,1,4,4,3,5,3,1,3,4,1,2.0,neutral or dissatisfied +71079,41516,Female,Loyal Customer,30,Business travel,Business,1235,2,4,2,2,5,5,5,5,5,5,1,4,3,5,8,0.0,satisfied +71080,121328,Male,Loyal Customer,51,Personal Travel,Eco,1009,3,3,3,2,3,2,2,3,3,2,3,2,4,2,167,150.0,neutral or dissatisfied +71081,119123,Female,Loyal Customer,12,Personal Travel,Eco,1020,3,4,3,2,1,3,1,1,1,4,2,5,2,1,0,0.0,neutral or dissatisfied +71082,15435,Male,Loyal Customer,66,Business travel,Business,3685,2,2,4,2,3,2,1,5,5,5,5,3,5,4,0,0.0,satisfied +71083,36016,Male,Loyal Customer,25,Business travel,Business,399,2,2,4,2,4,4,4,4,2,1,4,4,5,4,0,0.0,satisfied +71084,118704,Female,Loyal Customer,55,Personal Travel,Eco,369,2,3,1,3,2,2,2,1,1,1,1,4,1,1,1,0.0,neutral or dissatisfied +71085,11072,Female,Loyal Customer,18,Personal Travel,Eco,295,4,5,4,2,5,4,3,5,4,4,4,5,5,5,0,0.0,satisfied +71086,108236,Female,Loyal Customer,53,Business travel,Business,895,2,2,2,2,4,5,5,4,4,4,4,4,4,3,19,19.0,satisfied +71087,99743,Male,Loyal Customer,38,Business travel,Eco,255,3,2,4,4,3,3,3,3,1,5,4,1,3,3,22,24.0,neutral or dissatisfied +71088,47017,Male,disloyal Customer,33,Business travel,Business,602,3,3,3,3,2,3,2,2,3,4,4,5,5,2,5,15.0,neutral or dissatisfied +71089,298,Male,disloyal Customer,52,Business travel,Business,590,3,3,3,5,5,3,5,5,4,3,4,3,4,5,5,0.0,neutral or dissatisfied +71090,24501,Female,Loyal Customer,10,Personal Travel,Eco,481,2,1,2,4,3,2,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +71091,27318,Male,Loyal Customer,41,Business travel,Eco,679,4,1,1,1,4,4,4,4,5,5,3,1,5,4,0,12.0,satisfied +71092,90478,Female,disloyal Customer,27,Business travel,Business,545,4,4,4,3,4,4,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +71093,58367,Male,Loyal Customer,20,Personal Travel,Eco Plus,599,5,4,5,4,5,5,5,5,2,5,3,1,3,5,17,18.0,satisfied +71094,33724,Female,Loyal Customer,52,Personal Travel,Eco,759,5,5,5,3,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +71095,26519,Male,Loyal Customer,38,Business travel,Business,990,2,2,2,2,1,3,4,4,4,4,4,1,4,5,3,17.0,satisfied +71096,114386,Female,Loyal Customer,39,Business travel,Business,3291,2,2,5,2,4,5,4,4,4,4,4,4,4,3,20,1.0,satisfied +71097,72625,Male,Loyal Customer,48,Personal Travel,Eco,1119,3,5,3,3,3,3,3,3,5,4,4,5,5,3,0,2.0,neutral or dissatisfied +71098,6061,Female,Loyal Customer,20,Personal Travel,Eco,690,3,5,2,2,1,2,1,1,4,5,5,4,5,1,8,9.0,neutral or dissatisfied +71099,114694,Female,Loyal Customer,39,Business travel,Business,3606,3,3,5,3,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +71100,55085,Female,Loyal Customer,77,Business travel,Business,1379,4,5,5,5,4,3,2,4,4,4,4,2,4,4,32,24.0,neutral or dissatisfied +71101,19872,Female,Loyal Customer,41,Business travel,Business,296,1,5,5,5,1,1,1,2,1,3,3,1,2,1,143,141.0,neutral or dissatisfied +71102,12395,Female,disloyal Customer,27,Business travel,Eco,201,1,3,0,3,5,0,5,5,2,3,4,3,3,5,5,0.0,neutral or dissatisfied +71103,46921,Male,Loyal Customer,30,Business travel,Business,850,3,5,5,5,3,3,3,4,5,2,3,3,1,3,267,284.0,neutral or dissatisfied +71104,73268,Male,Loyal Customer,38,Business travel,Business,1654,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +71105,72286,Male,Loyal Customer,25,Personal Travel,Eco,919,4,2,4,4,5,4,5,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +71106,53198,Male,Loyal Customer,44,Business travel,Business,3334,2,2,5,2,3,2,3,4,4,4,4,4,4,3,50,43.0,satisfied +71107,13386,Male,Loyal Customer,14,Personal Travel,Business,456,3,5,3,3,3,3,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +71108,40322,Male,Loyal Customer,36,Business travel,Eco Plus,402,5,2,2,2,5,5,5,5,1,4,3,2,4,5,3,5.0,satisfied +71109,22033,Female,Loyal Customer,17,Personal Travel,Eco Plus,448,2,4,2,3,3,2,3,3,1,5,3,5,4,3,0,0.0,neutral or dissatisfied +71110,83457,Male,Loyal Customer,28,Business travel,Business,2151,5,5,5,5,4,4,4,4,3,4,5,5,4,4,11,22.0,satisfied +71111,57502,Female,Loyal Customer,51,Personal Travel,Eco,1075,4,4,4,3,2,4,3,2,2,4,2,2,2,4,0,0.0,satisfied +71112,37785,Male,Loyal Customer,30,Business travel,Eco Plus,1080,4,3,3,3,4,3,4,4,3,2,3,2,4,4,18,8.0,neutral or dissatisfied +71113,70646,Female,disloyal Customer,38,Business travel,Business,946,4,4,4,3,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +71114,68815,Male,Loyal Customer,16,Personal Travel,Eco,926,1,4,1,3,4,1,4,4,3,3,5,3,4,4,0,1.0,neutral or dissatisfied +71115,108962,Male,disloyal Customer,28,Business travel,Business,667,5,5,5,4,2,5,2,2,5,3,4,5,5,2,3,3.0,satisfied +71116,9126,Female,Loyal Customer,39,Personal Travel,Eco,765,3,2,3,3,3,5,5,4,3,4,3,5,2,5,433,455.0,neutral or dissatisfied +71117,59333,Female,Loyal Customer,30,Business travel,Business,2486,4,4,4,4,2,2,2,2,4,3,4,3,5,2,25,0.0,satisfied +71118,90704,Female,Loyal Customer,50,Business travel,Business,404,1,1,1,1,3,5,5,5,5,5,5,4,5,5,4,0.0,satisfied +71119,123258,Male,Loyal Customer,58,Personal Travel,Eco,631,2,5,2,5,3,2,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +71120,42901,Male,Loyal Customer,67,Business travel,Business,2318,1,1,1,1,2,2,1,4,4,4,4,2,4,2,0,0.0,satisfied +71121,43936,Female,disloyal Customer,20,Business travel,Eco,144,0,3,0,2,2,0,2,2,1,3,3,3,5,2,0,9.0,satisfied +71122,50866,Female,Loyal Customer,14,Personal Travel,Eco,109,3,2,3,2,2,3,2,2,3,1,2,4,2,2,0,0.0,neutral or dissatisfied +71123,52074,Male,Loyal Customer,27,Business travel,Business,3030,4,4,4,4,4,5,4,4,4,3,1,5,2,4,0,0.0,satisfied +71124,32020,Female,Loyal Customer,52,Business travel,Business,1572,2,2,2,2,4,4,3,4,4,4,5,1,4,5,2,6.0,satisfied +71125,53324,Male,Loyal Customer,11,Personal Travel,Eco,811,4,4,4,1,1,4,1,1,4,3,1,5,1,1,32,64.0,neutral or dissatisfied +71126,123417,Male,Loyal Customer,53,Business travel,Eco,937,5,2,3,2,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +71127,39544,Female,Loyal Customer,23,Business travel,Business,954,3,3,4,3,2,2,2,2,4,2,4,5,5,2,0,0.0,satisfied +71128,20079,Male,Loyal Customer,29,Business travel,Eco Plus,528,4,1,1,1,4,4,4,4,2,2,3,2,3,4,0,0.0,satisfied +71129,55141,Female,Loyal Customer,70,Personal Travel,Eco,1303,2,5,2,3,4,4,4,1,1,2,1,4,1,4,7,5.0,neutral or dissatisfied +71130,90816,Male,Loyal Customer,56,Business travel,Business,2987,4,4,4,4,5,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +71131,68,Male,Loyal Customer,43,Business travel,Business,173,4,5,5,5,4,3,3,2,2,2,4,2,2,4,0,0.0,neutral or dissatisfied +71132,74227,Female,Loyal Customer,47,Business travel,Business,1007,5,5,5,5,2,5,4,5,5,5,5,3,5,3,72,49.0,satisfied +71133,106912,Female,Loyal Customer,40,Business travel,Business,1591,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,2.0,satisfied +71134,14631,Female,disloyal Customer,8,Business travel,Eco,541,1,0,1,3,1,1,3,1,5,3,4,5,1,1,0,0.0,neutral or dissatisfied +71135,116998,Female,Loyal Customer,45,Business travel,Business,451,5,5,5,5,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +71136,119491,Male,disloyal Customer,21,Business travel,Business,857,5,0,5,2,5,5,1,5,3,4,4,3,4,5,0,0.0,satisfied +71137,55843,Female,Loyal Customer,27,Personal Travel,Eco,1416,0,2,0,3,1,0,1,1,1,1,2,3,3,1,0,0.0,satisfied +71138,22203,Male,Loyal Customer,44,Personal Travel,Eco,633,3,5,3,4,3,3,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +71139,48503,Male,disloyal Customer,22,Business travel,Eco,909,4,4,4,2,2,4,2,2,2,5,2,4,5,2,0,1.0,satisfied +71140,18990,Female,Loyal Customer,50,Business travel,Business,3391,1,3,1,1,1,2,4,5,5,5,5,3,5,4,0,0.0,satisfied +71141,22847,Female,Loyal Customer,43,Personal Travel,Eco,302,5,5,3,3,3,5,4,1,1,3,1,3,1,3,0,0.0,satisfied +71142,35570,Female,Loyal Customer,45,Business travel,Eco Plus,828,5,3,5,3,2,5,4,5,5,5,5,3,5,2,0,13.0,satisfied +71143,108835,Female,Loyal Customer,16,Business travel,Eco,1199,5,2,2,2,5,5,5,5,4,4,1,1,5,5,0,0.0,satisfied +71144,37450,Female,Loyal Customer,31,Business travel,Business,944,5,5,5,5,3,4,3,3,3,1,1,4,4,3,4,0.0,satisfied +71145,20098,Female,Loyal Customer,61,Business travel,Business,1730,3,3,4,3,3,5,2,4,4,4,4,4,4,5,1,5.0,satisfied +71146,128558,Female,Loyal Customer,48,Business travel,Eco Plus,221,2,4,4,4,5,3,3,2,2,2,2,4,2,2,0,4.0,neutral or dissatisfied +71147,109904,Female,disloyal Customer,38,Business travel,Eco,701,1,1,1,3,3,1,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +71148,63865,Male,Loyal Customer,60,Business travel,Business,1688,1,1,4,1,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +71149,6702,Female,Loyal Customer,21,Personal Travel,Eco,438,4,4,4,1,5,4,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +71150,53177,Male,Loyal Customer,50,Business travel,Eco,612,4,2,2,2,4,4,4,4,2,5,1,3,1,4,0,0.0,satisfied +71151,71752,Male,Loyal Customer,43,Business travel,Business,1744,4,4,5,4,3,4,5,4,4,4,4,4,4,3,5,10.0,satisfied +71152,9271,Female,Loyal Customer,21,Personal Travel,Eco,441,2,5,2,3,5,2,1,5,4,5,4,4,5,5,42,24.0,neutral or dissatisfied +71153,29694,Male,disloyal Customer,44,Business travel,Eco,1475,1,1,1,2,4,1,4,4,3,1,2,5,1,4,0,0.0,neutral or dissatisfied +71154,5518,Female,disloyal Customer,24,Business travel,Business,404,5,2,5,1,2,5,2,2,4,3,4,4,4,2,0,0.0,satisfied +71155,10455,Female,Loyal Customer,40,Business travel,Business,429,2,2,2,2,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +71156,86742,Male,Loyal Customer,42,Business travel,Business,2641,5,5,3,5,3,4,5,3,3,3,3,4,3,5,20,0.0,satisfied +71157,33370,Female,Loyal Customer,55,Personal Travel,Eco,2556,3,3,3,4,4,2,3,4,4,3,4,5,4,2,9,0.0,neutral or dissatisfied +71158,70127,Female,Loyal Customer,27,Business travel,Eco,550,1,1,1,1,1,1,1,1,3,5,4,1,4,1,36,47.0,neutral or dissatisfied +71159,85617,Female,Loyal Customer,68,Personal Travel,Eco,259,4,4,0,4,3,5,5,2,2,0,2,5,2,1,0,0.0,neutral or dissatisfied +71160,20769,Male,Loyal Customer,41,Business travel,Business,515,3,3,3,3,1,1,5,4,4,4,4,4,4,1,0,44.0,satisfied +71161,9043,Male,Loyal Customer,37,Business travel,Business,108,2,2,4,2,3,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +71162,19560,Male,Loyal Customer,17,Business travel,Business,3826,3,3,3,3,4,4,4,4,2,5,2,3,2,4,0,0.0,satisfied +71163,102786,Female,Loyal Customer,61,Personal Travel,Eco,1099,2,4,2,4,2,3,4,3,3,2,1,4,3,1,0,0.0,neutral or dissatisfied +71164,24113,Male,Loyal Customer,30,Business travel,Business,3899,3,3,3,3,4,4,4,4,1,3,1,3,2,4,0,0.0,satisfied +71165,10875,Female,Loyal Customer,34,Business travel,Business,429,1,2,2,2,1,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +71166,26347,Female,Loyal Customer,9,Business travel,Eco Plus,873,3,1,4,1,3,3,4,3,2,5,4,1,4,3,60,53.0,neutral or dissatisfied +71167,88593,Female,disloyal Customer,65,Personal Travel,Eco,545,2,1,2,3,4,2,4,4,4,5,3,1,4,4,3,0.0,neutral or dissatisfied +71168,63460,Male,Loyal Customer,49,Business travel,Business,1727,0,0,0,3,2,4,4,2,2,2,2,5,2,5,0,5.0,satisfied +71169,1569,Female,Loyal Customer,45,Business travel,Business,1998,2,2,2,2,2,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +71170,27241,Male,Loyal Customer,20,Personal Travel,Eco,1024,3,5,3,1,3,3,1,3,1,5,3,3,4,3,11,2.0,neutral or dissatisfied +71171,127472,Female,disloyal Customer,30,Business travel,Business,1274,4,4,4,3,4,4,4,4,5,5,5,3,5,4,9,8.0,satisfied +71172,57523,Male,Loyal Customer,56,Business travel,Business,3514,3,3,3,3,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +71173,47222,Female,Loyal Customer,38,Personal Travel,Eco,620,2,3,2,1,1,2,1,1,5,2,3,5,5,1,0,0.0,neutral or dissatisfied +71174,7029,Male,Loyal Customer,64,Personal Travel,Eco,147,4,5,4,2,5,4,5,5,4,2,4,4,5,5,0,0.0,satisfied +71175,101479,Female,disloyal Customer,45,Business travel,Business,345,3,3,3,4,5,3,1,5,4,3,5,4,4,5,2,0.0,neutral or dissatisfied +71176,99443,Male,Loyal Customer,39,Personal Travel,Eco Plus,337,3,4,3,3,4,3,4,4,2,2,4,2,3,4,0,0.0,neutral or dissatisfied +71177,47278,Male,Loyal Customer,25,Business travel,Eco,588,0,4,0,3,5,0,5,5,4,2,2,2,3,5,0,0.0,satisfied +71178,34541,Female,Loyal Customer,32,Business travel,Business,1598,5,5,5,5,4,5,4,4,5,3,3,5,4,4,0,0.0,satisfied +71179,101297,Male,Loyal Customer,68,Personal Travel,Eco,763,2,4,2,3,3,2,3,3,3,2,1,5,4,3,13,18.0,neutral or dissatisfied +71180,13547,Female,disloyal Customer,80,Business travel,Business,152,3,4,4,3,3,3,3,4,5,4,3,3,3,3,249,248.0,neutral or dissatisfied +71181,53280,Female,Loyal Customer,35,Business travel,Eco,758,5,4,4,4,5,5,5,5,4,5,3,5,2,5,1,22.0,satisfied +71182,105450,Female,disloyal Customer,24,Business travel,Eco,998,1,1,1,3,5,1,5,5,2,5,4,3,3,5,47,45.0,neutral or dissatisfied +71183,55730,Female,disloyal Customer,23,Business travel,Business,1378,0,0,0,4,5,0,2,5,4,4,5,3,5,5,4,0.0,satisfied +71184,9342,Female,Loyal Customer,38,Business travel,Business,3173,4,4,4,4,4,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +71185,70726,Female,Loyal Customer,31,Business travel,Business,675,4,1,1,1,4,3,4,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +71186,13321,Female,Loyal Customer,12,Business travel,Business,3531,2,2,2,2,5,5,5,5,3,5,2,2,5,5,0,0.0,satisfied +71187,104737,Male,Loyal Customer,33,Business travel,Business,2448,3,3,3,3,4,4,4,4,4,4,4,3,4,4,12,9.0,satisfied +71188,90475,Female,Loyal Customer,44,Business travel,Business,250,0,0,0,2,5,5,4,1,1,3,3,3,1,4,0,2.0,satisfied +71189,18697,Male,Loyal Customer,49,Business travel,Eco Plus,190,4,2,2,2,4,4,4,4,3,4,4,4,2,4,0,0.0,satisfied +71190,103272,Male,Loyal Customer,24,Personal Travel,Eco,888,4,4,4,2,2,4,2,2,4,2,5,4,4,2,0,0.0,satisfied +71191,123492,Female,Loyal Customer,9,Business travel,Eco,2125,2,3,3,3,2,2,3,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +71192,1682,Female,Loyal Customer,27,Personal Travel,Eco,561,2,1,2,1,2,2,2,2,2,1,1,4,2,2,0,2.0,neutral or dissatisfied +71193,127196,Male,Loyal Customer,36,Business travel,Eco Plus,651,2,3,3,3,2,2,2,2,4,5,3,2,3,2,0,0.0,neutral or dissatisfied +71194,94587,Male,Loyal Customer,52,Business travel,Business,562,5,5,5,5,5,5,4,5,5,5,5,3,5,4,10,3.0,satisfied +71195,60433,Female,Loyal Customer,39,Business travel,Business,862,3,3,3,3,5,4,5,3,3,3,3,5,3,4,10,0.0,satisfied +71196,27004,Male,Loyal Customer,9,Business travel,Eco,867,5,2,4,2,5,4,4,5,3,5,1,1,2,5,0,0.0,satisfied +71197,6375,Female,Loyal Customer,46,Business travel,Business,2134,1,3,3,3,3,2,2,1,1,2,1,2,1,2,0,13.0,neutral or dissatisfied +71198,236,Male,Loyal Customer,35,Business travel,Business,3242,2,4,4,4,1,2,2,2,2,2,2,1,2,4,0,4.0,neutral or dissatisfied +71199,59269,Male,Loyal Customer,27,Personal Travel,Eco,4963,2,1,2,4,2,3,3,2,5,4,3,3,4,3,0,2.0,neutral or dissatisfied +71200,51694,Male,disloyal Customer,55,Business travel,Eco,451,5,0,5,5,1,5,1,1,5,5,4,4,2,1,0,0.0,satisfied +71201,95000,Male,Loyal Customer,54,Personal Travel,Eco,248,1,5,0,1,3,0,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +71202,102042,Female,Loyal Customer,67,Business travel,Business,407,1,3,3,3,2,4,4,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +71203,2515,Female,Loyal Customer,42,Business travel,Business,2401,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +71204,35262,Female,Loyal Customer,14,Business travel,Business,1028,2,2,2,2,3,3,3,3,1,1,3,4,3,3,7,1.0,satisfied +71205,8367,Female,disloyal Customer,20,Business travel,Eco,674,3,2,2,3,5,2,5,5,3,3,4,1,3,5,40,29.0,neutral or dissatisfied +71206,77092,Female,Loyal Customer,53,Business travel,Business,1481,5,5,5,5,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +71207,49503,Male,Loyal Customer,47,Business travel,Business,421,1,1,1,1,5,1,1,4,4,4,4,5,4,3,50,64.0,satisfied +71208,72409,Female,disloyal Customer,29,Business travel,Business,964,0,0,0,2,3,0,3,3,5,2,5,5,4,3,0,0.0,satisfied +71209,86599,Male,Loyal Customer,30,Business travel,Business,3493,5,5,5,5,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +71210,59209,Female,Loyal Customer,44,Personal Travel,Eco,1440,4,4,4,5,3,5,5,5,5,4,5,3,5,3,5,9.0,neutral or dissatisfied +71211,89061,Female,Loyal Customer,57,Business travel,Business,1947,5,5,5,5,4,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +71212,76701,Female,Loyal Customer,26,Personal Travel,Eco,534,3,1,3,4,3,3,3,3,1,2,3,2,4,3,0,0.0,neutral or dissatisfied +71213,17989,Female,Loyal Customer,48,Business travel,Business,1644,4,4,4,4,4,4,4,1,3,1,3,4,5,4,120,165.0,satisfied +71214,102851,Male,Loyal Customer,42,Personal Travel,Eco,423,2,4,2,3,1,2,1,1,3,4,4,5,4,1,1,0.0,neutral or dissatisfied +71215,17924,Male,Loyal Customer,69,Personal Travel,Eco,789,4,4,3,4,2,3,4,2,5,2,5,5,4,2,0,19.0,neutral or dissatisfied +71216,4216,Male,Loyal Customer,30,Personal Travel,Eco,888,3,5,3,3,1,3,1,1,4,3,4,3,5,1,0,48.0,neutral or dissatisfied +71217,73260,Female,Loyal Customer,22,Personal Travel,Eco,675,1,5,1,1,5,1,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +71218,52018,Male,Loyal Customer,33,Business travel,Business,2464,3,3,3,3,4,4,4,4,3,1,2,2,5,4,0,3.0,satisfied +71219,42143,Male,Loyal Customer,33,Business travel,Business,2138,2,2,2,2,3,4,3,3,3,4,5,3,4,3,0,0.0,satisfied +71220,63808,Female,Loyal Customer,42,Personal Travel,Eco,2724,0,3,0,3,5,5,5,5,5,0,5,3,5,3,0,0.0,satisfied +71221,62134,Male,Loyal Customer,47,Business travel,Business,2565,1,1,3,1,4,5,5,4,4,4,4,3,4,3,7,7.0,satisfied +71222,329,Male,Loyal Customer,47,Business travel,Business,3954,1,3,3,3,1,3,3,1,1,1,1,2,1,3,9,0.0,neutral or dissatisfied +71223,19459,Female,Loyal Customer,42,Business travel,Eco,177,4,1,1,1,4,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +71224,29490,Female,Loyal Customer,53,Business travel,Business,1861,5,5,5,5,2,3,5,5,5,5,5,4,5,1,0,0.0,satisfied +71225,5303,Female,Loyal Customer,53,Personal Travel,Eco,383,4,5,4,4,4,4,5,3,3,4,3,5,3,3,0,0.0,neutral or dissatisfied +71226,117984,Female,Loyal Customer,34,Personal Travel,Eco,255,1,3,1,2,5,1,5,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +71227,29,Male,Loyal Customer,40,Business travel,Business,3734,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,52.0,satisfied +71228,51813,Male,Loyal Customer,11,Personal Travel,Eco,370,4,4,4,3,4,5,5,2,4,3,4,5,2,5,202,214.0,neutral or dissatisfied +71229,16068,Female,Loyal Customer,33,Business travel,Business,744,2,2,2,2,1,5,2,5,5,4,5,4,5,1,0,0.0,satisfied +71230,43573,Male,disloyal Customer,26,Business travel,Eco,1499,2,2,2,4,5,2,5,5,2,2,3,2,4,5,37,,neutral or dissatisfied +71231,34507,Female,Loyal Customer,39,Business travel,Eco,1428,3,4,4,4,3,3,3,3,4,2,1,3,1,3,4,0.0,neutral or dissatisfied +71232,124871,Male,Loyal Customer,17,Personal Travel,Eco Plus,280,2,5,2,1,5,2,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +71233,122675,Female,Loyal Customer,63,Business travel,Business,2638,3,1,3,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +71234,19819,Female,Loyal Customer,43,Business travel,Eco,528,4,4,1,4,2,4,4,4,4,4,4,2,4,5,0,0.0,satisfied +71235,44909,Male,Loyal Customer,52,Business travel,Business,718,3,5,5,5,3,3,3,3,5,4,4,3,2,3,132,117.0,neutral or dissatisfied +71236,21319,Female,Loyal Customer,64,Personal Travel,Eco Plus,692,3,4,3,2,4,4,4,5,5,3,2,3,5,5,0,0.0,neutral or dissatisfied +71237,42834,Female,Loyal Customer,53,Business travel,Business,2965,5,5,5,5,2,1,1,4,4,4,4,1,4,4,0,0.0,satisfied +71238,73833,Male,Loyal Customer,25,Business travel,Business,1709,2,2,1,2,4,4,4,4,4,4,3,4,4,4,21,11.0,satisfied +71239,113209,Female,disloyal Customer,42,Business travel,Business,414,5,5,5,2,4,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +71240,54195,Female,Loyal Customer,47,Personal Travel,Eco,1400,4,3,5,4,1,3,4,1,1,5,1,3,1,3,0,0.0,satisfied +71241,19229,Male,Loyal Customer,26,Personal Travel,Eco Plus,459,2,5,2,3,5,2,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +71242,90852,Female,Loyal Customer,39,Business travel,Business,250,2,5,3,3,5,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +71243,4751,Female,Loyal Customer,38,Business travel,Business,2834,4,4,4,4,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +71244,100402,Female,Loyal Customer,46,Business travel,Eco Plus,971,2,3,3,3,3,3,4,2,2,2,2,3,2,1,1,0.0,neutral or dissatisfied +71245,16350,Male,Loyal Customer,22,Personal Travel,Eco,160,5,4,0,3,4,0,4,4,5,3,4,5,5,4,14,11.0,satisfied +71246,87769,Male,Loyal Customer,57,Business travel,Business,3632,1,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +71247,51821,Female,Loyal Customer,25,Business travel,Eco Plus,370,5,5,5,5,5,5,5,5,1,3,1,3,2,5,0,0.0,satisfied +71248,85928,Female,Loyal Customer,29,Business travel,Business,2970,2,2,2,2,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +71249,127832,Female,Loyal Customer,70,Personal Travel,Eco,1262,3,2,3,1,5,2,2,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +71250,9147,Male,Loyal Customer,48,Business travel,Business,227,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +71251,124958,Female,Loyal Customer,48,Business travel,Business,1732,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +71252,78936,Male,disloyal Customer,26,Business travel,Eco,101,3,1,3,4,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +71253,97256,Female,disloyal Customer,39,Business travel,Eco,296,3,0,4,3,4,4,4,4,2,1,2,4,2,4,2,0.0,neutral or dissatisfied +71254,102451,Female,Loyal Customer,11,Personal Travel,Eco,223,4,5,4,1,1,4,1,1,4,5,4,4,4,1,0,0.0,satisfied +71255,88201,Male,Loyal Customer,45,Business travel,Business,3096,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +71256,14756,Female,disloyal Customer,18,Business travel,Eco,463,3,2,3,2,2,3,2,2,1,4,3,4,3,2,0,11.0,neutral or dissatisfied +71257,20335,Male,disloyal Customer,20,Business travel,Eco,323,5,2,5,4,2,5,2,2,1,4,5,1,3,2,0,0.0,satisfied +71258,14241,Female,Loyal Customer,67,Business travel,Business,3387,1,1,1,1,2,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +71259,39969,Male,Loyal Customer,51,Business travel,Eco,1404,3,1,1,1,3,3,3,3,4,3,4,5,2,3,0,0.0,satisfied +71260,68778,Female,Loyal Customer,47,Business travel,Business,926,3,3,4,3,5,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +71261,77409,Female,Loyal Customer,27,Personal Travel,Eco,532,1,5,1,2,5,1,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +71262,69638,Male,disloyal Customer,25,Business travel,Business,569,5,2,5,5,2,5,2,2,3,4,4,3,5,2,0,0.0,satisfied +71263,60464,Female,disloyal Customer,34,Business travel,Eco,862,4,4,4,3,2,4,3,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +71264,69887,Female,Loyal Customer,50,Personal Travel,Eco,2248,2,4,2,2,5,4,5,2,2,2,1,4,2,5,0,0.0,neutral or dissatisfied +71265,81754,Male,disloyal Customer,26,Business travel,Business,1416,4,4,4,1,2,4,4,2,3,5,4,3,4,2,0,0.0,satisfied +71266,92193,Male,Loyal Customer,58,Business travel,Business,1979,1,1,3,1,5,4,4,5,5,5,5,4,5,4,12,26.0,satisfied +71267,92841,Male,Loyal Customer,56,Personal Travel,Eco,1587,2,4,2,5,2,2,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +71268,84542,Female,disloyal Customer,16,Business travel,Eco,1125,4,4,4,3,2,4,2,2,5,2,4,1,3,2,0,0.0,satisfied +71269,60164,Male,Loyal Customer,27,Personal Travel,Eco,1182,2,4,2,3,4,2,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +71270,31163,Female,Loyal Customer,35,Business travel,Eco,1201,2,2,2,2,2,2,2,2,3,2,4,4,3,2,24,32.0,neutral or dissatisfied +71271,52880,Male,disloyal Customer,10,Business travel,Eco,1024,4,5,5,5,5,5,5,5,3,2,3,1,4,5,0,0.0,neutral or dissatisfied +71272,91152,Male,Loyal Customer,65,Personal Travel,Eco,581,1,5,1,2,5,1,5,5,4,4,2,1,5,5,0,0.0,neutral or dissatisfied +71273,116356,Male,Loyal Customer,30,Personal Travel,Eco,417,3,4,3,4,2,3,2,2,1,3,5,1,4,2,49,46.0,neutral or dissatisfied +71274,129636,Male,Loyal Customer,41,Business travel,Business,2683,0,0,0,1,5,4,4,5,5,5,5,4,5,4,48,36.0,satisfied +71275,34331,Female,Loyal Customer,28,Business travel,Eco,846,4,3,3,3,4,4,4,3,1,1,4,4,5,4,182,174.0,satisfied +71276,113062,Male,Loyal Customer,40,Business travel,Business,2834,1,3,3,3,1,1,1,3,4,3,2,1,4,1,334,318.0,neutral or dissatisfied +71277,11796,Male,disloyal Customer,35,Business travel,Eco Plus,429,4,4,4,4,2,4,2,2,4,4,3,1,3,2,21,17.0,neutral or dissatisfied +71278,73893,Male,Loyal Customer,39,Business travel,Business,2342,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +71279,82402,Female,Loyal Customer,20,Personal Travel,Eco,501,4,4,4,3,5,4,5,5,3,4,4,4,5,5,0,0.0,satisfied +71280,31766,Female,disloyal Customer,23,Business travel,Eco,602,4,0,4,4,5,4,5,5,5,4,2,3,1,5,0,0.0,satisfied +71281,124345,Male,Loyal Customer,25,Personal Travel,Eco,1037,2,5,2,3,1,2,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +71282,67179,Female,Loyal Customer,32,Personal Travel,Eco,1119,2,5,2,2,4,2,4,4,5,3,5,3,4,4,9,9.0,neutral or dissatisfied +71283,118765,Male,Loyal Customer,14,Personal Travel,Eco,647,3,2,3,2,2,3,2,2,1,4,3,3,2,2,0,0.0,neutral or dissatisfied +71284,59167,Female,Loyal Customer,22,Personal Travel,Eco Plus,1781,1,5,1,5,4,1,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +71285,94968,Male,disloyal Customer,20,Business travel,Eco,189,2,3,2,2,1,2,1,1,2,3,3,5,3,1,3,4.0,neutral or dissatisfied +71286,32942,Male,Loyal Customer,24,Personal Travel,Eco,163,4,4,4,1,3,4,2,3,4,5,4,4,5,3,0,0.0,satisfied +71287,53962,Male,disloyal Customer,35,Business travel,Business,1117,2,2,2,1,2,2,5,2,2,2,3,2,2,2,0,0.0,neutral or dissatisfied +71288,93664,Female,Loyal Customer,49,Business travel,Eco,667,2,4,4,4,5,3,2,2,2,2,2,1,2,2,2,11.0,neutral or dissatisfied +71289,89761,Female,Loyal Customer,13,Personal Travel,Eco,950,4,3,3,3,3,3,3,3,2,1,2,4,4,3,0,0.0,neutral or dissatisfied +71290,110979,Male,Loyal Customer,39,Business travel,Business,2785,0,4,0,4,5,4,5,4,4,4,4,3,4,4,27,19.0,satisfied +71291,52706,Female,Loyal Customer,51,Personal Travel,Eco,584,1,5,1,1,5,4,5,2,2,1,2,4,2,3,9,6.0,neutral or dissatisfied +71292,108173,Male,Loyal Customer,67,Personal Travel,Eco,997,5,4,5,2,2,5,2,2,3,4,5,5,5,2,0,0.0,satisfied +71293,99591,Female,Loyal Customer,36,Personal Travel,Eco,930,2,4,2,2,5,2,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +71294,511,Female,Loyal Customer,40,Business travel,Business,134,3,3,3,3,3,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +71295,28833,Female,disloyal Customer,19,Business travel,Eco,1050,4,3,3,3,5,3,3,5,2,3,3,2,5,5,0,0.0,neutral or dissatisfied +71296,7059,Male,disloyal Customer,26,Business travel,Business,273,4,4,5,3,2,5,2,2,5,4,5,5,5,2,0,0.0,satisfied +71297,59422,Female,Loyal Customer,39,Business travel,Business,2367,4,4,4,4,3,4,4,4,4,4,4,5,4,3,8,0.0,satisfied +71298,122266,Male,Loyal Customer,9,Personal Travel,Eco,546,1,2,1,3,4,1,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +71299,53255,Female,Loyal Customer,44,Personal Travel,Eco Plus,612,1,4,1,3,2,2,4,1,1,1,2,3,1,1,17,0.0,neutral or dissatisfied +71300,14369,Male,disloyal Customer,31,Business travel,Eco,1215,1,1,1,3,4,1,2,4,1,5,4,1,3,4,12,6.0,neutral or dissatisfied +71301,10364,Female,Loyal Customer,44,Business travel,Business,295,5,5,4,5,2,4,5,4,4,4,4,5,4,5,38,28.0,satisfied +71302,120148,Male,Loyal Customer,59,Personal Travel,Eco,1475,3,4,3,4,5,3,5,5,1,1,2,2,3,5,0,0.0,neutral or dissatisfied +71303,126237,Female,disloyal Customer,30,Business travel,Eco,107,3,2,3,4,4,3,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +71304,83840,Female,disloyal Customer,39,Business travel,Eco,448,2,4,2,3,5,2,5,5,4,3,3,3,4,5,29,27.0,neutral or dissatisfied +71305,32095,Female,Loyal Customer,38,Business travel,Eco,163,5,5,5,5,5,5,5,5,3,5,2,4,2,5,0,0.0,satisfied +71306,99348,Male,Loyal Customer,44,Business travel,Business,1771,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +71307,31130,Male,Loyal Customer,38,Business travel,Eco,991,5,3,3,3,5,5,5,5,4,5,2,4,2,5,0,2.0,satisfied +71308,29767,Male,disloyal Customer,22,Business travel,Business,95,5,0,5,3,1,5,1,1,3,4,4,5,5,1,0,0.0,satisfied +71309,49496,Female,Loyal Customer,72,Business travel,Eco,134,4,4,4,4,1,4,5,4,4,4,4,1,4,1,0,0.0,satisfied +71310,5680,Male,disloyal Customer,56,Business travel,Business,147,3,3,3,2,4,3,4,4,4,3,4,3,5,4,94,93.0,neutral or dissatisfied +71311,50508,Male,Loyal Customer,27,Personal Travel,Eco,250,2,4,2,1,2,5,5,4,2,5,4,5,3,5,131,129.0,neutral or dissatisfied +71312,68533,Female,Loyal Customer,49,Business travel,Eco,1013,3,3,3,3,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +71313,104198,Female,Loyal Customer,25,Business travel,Eco,1310,1,3,5,3,1,1,1,1,3,1,4,3,3,1,0,0.0,neutral or dissatisfied +71314,54808,Female,Loyal Customer,30,Business travel,Business,3837,1,1,1,1,4,4,4,4,5,1,2,4,5,4,0,0.0,satisfied +71315,111230,Female,Loyal Customer,59,Personal Travel,Eco,1546,4,5,4,1,3,5,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +71316,117294,Male,Loyal Customer,38,Business travel,Eco Plus,304,2,3,3,3,2,2,2,2,4,4,3,2,3,2,56,53.0,neutral or dissatisfied +71317,47745,Male,Loyal Customer,52,Business travel,Business,329,0,0,0,2,5,3,3,2,2,2,2,5,2,5,10,18.0,satisfied +71318,54783,Female,Loyal Customer,55,Business travel,Business,2136,4,4,4,4,5,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +71319,65185,Male,Loyal Customer,22,Personal Travel,Eco,247,1,4,1,3,3,1,3,3,4,1,4,1,4,3,0,9.0,neutral or dissatisfied +71320,105674,Female,Loyal Customer,48,Business travel,Business,883,3,3,3,3,3,5,4,5,5,5,5,4,5,3,19,13.0,satisfied +71321,21978,Male,Loyal Customer,30,Personal Travel,Eco,500,3,2,3,4,5,3,5,5,2,3,3,4,3,5,0,13.0,neutral or dissatisfied +71322,39832,Male,Loyal Customer,34,Business travel,Business,272,1,1,1,1,4,3,5,4,4,5,4,1,4,2,0,8.0,satisfied +71323,15286,Female,Loyal Customer,40,Personal Travel,Eco,501,2,4,2,2,2,2,2,2,3,4,4,3,4,2,27,14.0,neutral or dissatisfied +71324,39958,Male,Loyal Customer,11,Personal Travel,Eco,1086,2,4,2,2,2,2,2,2,5,2,5,5,5,2,14,0.0,neutral or dissatisfied +71325,76589,Female,Loyal Customer,57,Business travel,Business,481,2,2,2,2,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +71326,95321,Male,Loyal Customer,55,Personal Travel,Eco,323,2,5,3,5,3,3,3,3,4,3,3,4,1,3,0,0.0,neutral or dissatisfied +71327,37452,Female,disloyal Customer,14,Business travel,Eco,1056,2,2,2,4,2,4,2,2,4,4,3,2,2,2,175,165.0,neutral or dissatisfied +71328,39518,Male,Loyal Customer,58,Business travel,Eco,624,3,3,3,3,3,3,3,3,1,5,3,3,3,3,103,84.0,neutral or dissatisfied +71329,65133,Male,Loyal Customer,42,Personal Travel,Eco,190,2,3,0,3,2,0,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +71330,78789,Female,Loyal Customer,36,Business travel,Business,528,1,1,1,1,5,4,4,1,1,1,1,4,1,3,36,10.0,neutral or dissatisfied +71331,57250,Female,Loyal Customer,40,Business travel,Business,804,5,5,1,5,3,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +71332,9971,Male,Loyal Customer,33,Personal Travel,Eco,357,3,4,3,1,3,3,3,3,2,5,1,3,5,3,0,0.0,neutral or dissatisfied +71333,2447,Female,disloyal Customer,25,Business travel,Business,767,4,4,5,1,3,5,3,3,4,4,4,3,4,3,0,1.0,satisfied +71334,44858,Female,Loyal Customer,25,Business travel,Eco,693,4,2,2,2,4,4,4,4,3,4,1,2,4,4,0,9.0,satisfied +71335,9568,Female,Loyal Customer,66,Business travel,Business,288,2,2,2,2,5,3,3,2,2,2,2,2,2,4,0,22.0,neutral or dissatisfied +71336,92402,Female,Loyal Customer,56,Business travel,Business,1947,1,1,1,1,4,3,5,5,5,5,5,4,5,5,3,4.0,satisfied +71337,36615,Female,Loyal Customer,29,Business travel,Business,2948,5,5,5,5,2,2,2,2,2,2,3,4,2,2,0,3.0,satisfied +71338,80918,Female,Loyal Customer,54,Business travel,Eco,341,1,2,4,4,3,4,4,1,1,1,1,1,1,4,5,0.0,neutral or dissatisfied +71339,48254,Female,Loyal Customer,43,Personal Travel,Eco,414,3,5,4,4,4,1,2,3,3,4,3,5,3,1,2,0.0,neutral or dissatisfied +71340,124845,Female,Loyal Customer,24,Personal Travel,Eco,280,1,4,1,3,2,1,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +71341,108485,Female,Loyal Customer,8,Business travel,Eco,570,1,3,3,3,1,1,1,1,1,4,4,4,4,1,0,2.0,neutral or dissatisfied +71342,26936,Male,Loyal Customer,28,Business travel,Business,2378,4,4,4,4,5,5,5,5,2,5,5,4,3,5,0,0.0,satisfied +71343,83108,Male,Loyal Customer,15,Personal Travel,Eco,1127,3,5,3,3,2,3,2,2,4,4,4,5,4,2,14,75.0,neutral or dissatisfied +71344,102171,Male,Loyal Customer,35,Business travel,Business,2489,2,4,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +71345,46255,Male,Loyal Customer,20,Personal Travel,Eco,752,1,2,1,4,4,1,4,4,4,4,3,4,4,4,23,35.0,neutral or dissatisfied +71346,42805,Female,disloyal Customer,35,Business travel,Eco,677,3,3,3,4,3,3,4,3,4,1,1,5,4,3,0,0.0,neutral or dissatisfied +71347,4047,Male,Loyal Customer,39,Personal Travel,Eco,479,4,4,4,4,5,4,5,5,1,2,4,2,4,5,40,59.0,satisfied +71348,104280,Female,Loyal Customer,58,Personal Travel,Eco,1733,4,3,3,4,3,1,1,4,1,4,4,1,4,1,168,155.0,neutral or dissatisfied +71349,15262,Male,Loyal Customer,45,Business travel,Eco Plus,445,2,2,2,2,2,2,2,1,2,4,4,2,3,2,161,158.0,neutral or dissatisfied +71350,48857,Female,disloyal Customer,34,Business travel,Eco,308,3,4,3,2,5,3,5,5,1,3,5,3,2,5,0,0.0,neutral or dissatisfied +71351,20604,Male,Loyal Customer,37,Business travel,Business,794,2,2,2,2,2,5,2,4,4,4,4,2,4,5,0,11.0,satisfied +71352,70345,Female,Loyal Customer,41,Personal Travel,Eco,986,4,5,5,5,4,5,4,4,4,2,5,4,5,4,6,0.0,neutral or dissatisfied +71353,119437,Male,Loyal Customer,61,Personal Travel,Eco,399,2,4,2,4,3,2,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +71354,26150,Female,Loyal Customer,42,Business travel,Eco,270,4,3,2,3,4,5,1,4,4,4,4,4,4,2,0,0.0,satisfied +71355,106120,Female,Loyal Customer,60,Business travel,Business,2266,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +71356,69470,Female,Loyal Customer,24,Personal Travel,Eco,1096,4,2,4,4,5,4,5,5,4,3,3,1,4,5,0,0.0,satisfied +71357,101741,Female,Loyal Customer,46,Business travel,Business,1590,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +71358,84798,Female,Loyal Customer,49,Business travel,Business,516,2,4,2,2,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +71359,79691,Male,Loyal Customer,64,Personal Travel,Eco,712,2,5,2,4,2,2,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +71360,55774,Female,Loyal Customer,22,Business travel,Business,599,1,2,2,2,1,1,1,1,3,1,2,4,2,1,0,0.0,neutral or dissatisfied +71361,68100,Male,Loyal Customer,55,Business travel,Eco,413,4,4,4,4,4,4,4,4,2,5,2,5,3,4,0,0.0,satisfied +71362,14428,Male,Loyal Customer,18,Business travel,Eco Plus,585,4,1,1,1,4,4,3,4,4,2,3,5,4,4,0,0.0,satisfied +71363,10666,Male,disloyal Customer,27,Business travel,Eco,309,3,2,3,3,4,3,2,4,3,2,3,1,2,4,0,0.0,neutral or dissatisfied +71364,105886,Male,Loyal Customer,28,Business travel,Business,3151,3,1,2,1,3,3,3,3,3,5,3,1,3,3,9,0.0,neutral or dissatisfied +71365,127918,Female,Loyal Customer,56,Business travel,Business,2300,5,5,5,5,4,3,5,3,3,4,3,5,3,5,23,15.0,satisfied +71366,57322,Male,Loyal Customer,42,Business travel,Business,3490,1,1,3,1,5,4,4,2,2,2,2,4,2,5,9,0.0,satisfied +71367,119850,Female,Loyal Customer,39,Business travel,Business,2892,4,4,4,4,2,5,1,4,4,4,4,5,4,5,27,13.0,satisfied +71368,73377,Female,Loyal Customer,50,Business travel,Business,1779,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +71369,43643,Male,Loyal Customer,56,Personal Travel,Eco,1042,1,5,1,1,1,4,4,5,5,4,4,4,3,4,279,252.0,neutral or dissatisfied +71370,66662,Male,disloyal Customer,16,Business travel,Eco,978,3,3,3,4,4,3,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +71371,26749,Male,Loyal Customer,45,Business travel,Eco,859,5,3,3,3,3,5,3,3,5,1,1,5,5,3,0,0.0,satisfied +71372,35259,Male,Loyal Customer,39,Business travel,Business,1725,1,1,4,1,4,2,4,4,4,4,4,4,4,3,0,0.0,satisfied +71373,112894,Male,disloyal Customer,22,Business travel,Business,1129,3,3,3,3,5,3,5,5,3,4,4,3,4,5,8,0.0,neutral or dissatisfied +71374,8680,Female,Loyal Customer,24,Business travel,Business,1699,1,4,4,4,1,1,1,1,3,2,1,3,1,1,10,6.0,neutral or dissatisfied +71375,108330,Male,disloyal Customer,25,Business travel,Eco,1728,2,2,2,4,3,2,3,3,2,2,2,1,4,3,57,73.0,neutral or dissatisfied +71376,119134,Female,Loyal Customer,42,Personal Travel,Eco,356,1,4,5,5,3,5,4,1,1,5,1,4,1,4,0,3.0,neutral or dissatisfied +71377,49434,Male,disloyal Customer,21,Business travel,Eco,266,3,2,4,3,4,4,4,2,3,4,3,4,2,4,183,194.0,neutral or dissatisfied +71378,85265,Male,Loyal Customer,26,Personal Travel,Eco,689,3,5,3,2,5,3,5,5,3,3,4,3,4,5,21,27.0,neutral or dissatisfied +71379,18027,Male,disloyal Customer,23,Business travel,Eco,488,4,5,4,4,5,4,5,5,2,5,1,4,3,5,15,10.0,satisfied +71380,33313,Female,disloyal Customer,33,Business travel,Business,2556,3,3,3,2,5,3,1,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +71381,102920,Male,Loyal Customer,58,Business travel,Business,317,5,5,3,5,2,5,5,5,5,5,5,5,5,5,13,12.0,satisfied +71382,74331,Female,Loyal Customer,41,Business travel,Business,1438,3,4,3,3,3,4,5,5,5,5,5,3,5,4,12,13.0,satisfied +71383,75915,Female,Loyal Customer,70,Personal Travel,Eco,603,2,5,2,3,2,5,4,1,1,2,1,3,1,4,6,4.0,neutral or dissatisfied +71384,92405,Male,Loyal Customer,36,Business travel,Business,1947,4,4,3,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +71385,93662,Female,Loyal Customer,68,Business travel,Business,667,3,2,2,2,4,3,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +71386,101083,Male,Loyal Customer,69,Personal Travel,Business,1069,4,4,4,4,1,3,3,4,4,4,4,3,4,2,40,26.0,neutral or dissatisfied +71387,39032,Male,Loyal Customer,62,Personal Travel,Eco,313,2,4,2,5,1,2,5,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +71388,63193,Female,Loyal Customer,51,Business travel,Business,337,2,2,2,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +71389,77574,Male,disloyal Customer,26,Business travel,Business,689,2,2,2,3,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +71390,94143,Female,Loyal Customer,54,Business travel,Business,3613,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +71391,23327,Male,disloyal Customer,59,Business travel,Business,274,4,4,4,5,2,4,2,2,5,5,1,2,1,2,0,0.0,satisfied +71392,17382,Male,Loyal Customer,7,Personal Travel,Eco,637,2,4,2,2,2,2,2,2,5,5,2,5,5,2,0,0.0,neutral or dissatisfied +71393,48089,Female,Loyal Customer,32,Business travel,Eco,259,5,5,5,5,5,5,5,5,1,4,1,5,5,5,0,4.0,satisfied +71394,80110,Male,Loyal Customer,56,Personal Travel,Eco,1620,3,5,2,4,2,2,2,2,3,3,5,5,1,2,0,0.0,neutral or dissatisfied +71395,54923,Male,Loyal Customer,68,Personal Travel,Eco Plus,862,4,4,4,5,5,4,5,5,3,4,5,3,4,5,1,16.0,neutral or dissatisfied +71396,32757,Male,Loyal Customer,54,Business travel,Business,1923,2,5,3,5,5,3,4,3,3,3,2,1,3,1,0,0.0,neutral or dissatisfied +71397,88798,Male,Loyal Customer,35,Business travel,Eco Plus,515,1,5,5,5,1,1,1,4,3,2,2,1,4,1,253,269.0,neutral or dissatisfied +71398,42919,Male,Loyal Customer,33,Business travel,Business,3891,1,1,1,1,5,5,5,5,4,1,1,2,2,5,0,3.0,satisfied +71399,29549,Male,Loyal Customer,28,Business travel,Business,2867,2,2,2,2,4,4,4,4,3,5,3,1,2,4,0,0.0,satisfied +71400,5517,Male,Loyal Customer,44,Business travel,Business,2975,1,1,1,1,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +71401,57369,Female,Loyal Customer,70,Personal Travel,Eco,414,1,2,1,3,2,3,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +71402,43414,Female,Loyal Customer,26,Business travel,Eco Plus,463,4,3,3,3,4,4,4,4,5,5,4,2,5,4,0,0.0,satisfied +71403,48655,Male,Loyal Customer,59,Business travel,Business,2539,1,1,1,1,4,5,4,5,5,5,4,3,5,3,118,128.0,satisfied +71404,17990,Female,Loyal Customer,58,Business travel,Eco,332,5,4,4,4,1,5,2,5,5,5,5,4,5,2,36,25.0,satisfied +71405,8398,Female,Loyal Customer,43,Personal Travel,Eco,888,4,1,4,4,3,3,3,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +71406,30391,Female,Loyal Customer,29,Personal Travel,Eco,641,2,5,2,5,2,2,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +71407,81789,Female,Loyal Customer,48,Business travel,Business,1487,1,1,1,1,5,4,5,3,3,4,3,5,3,4,1,41.0,satisfied +71408,71072,Female,Loyal Customer,26,Personal Travel,Eco,978,3,4,2,1,4,2,4,4,4,2,4,4,5,4,8,2.0,neutral or dissatisfied +71409,79713,Male,Loyal Customer,26,Personal Travel,Eco,762,3,4,4,2,1,4,1,1,3,2,4,3,5,1,0,25.0,neutral or dissatisfied +71410,70819,Male,Loyal Customer,16,Personal Travel,Eco,624,3,5,3,2,5,3,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +71411,54274,Female,Loyal Customer,19,Personal Travel,Eco,1222,4,0,4,4,5,4,5,5,5,3,5,3,4,5,0,0.0,satisfied +71412,118463,Male,Loyal Customer,50,Business travel,Business,646,1,1,1,1,5,4,4,4,4,4,4,4,4,3,47,47.0,satisfied +71413,96645,Male,Loyal Customer,51,Business travel,Business,2826,1,1,1,1,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +71414,26269,Female,Loyal Customer,31,Business travel,Business,1922,2,1,3,1,2,2,2,2,2,3,4,3,3,2,13,2.0,neutral or dissatisfied +71415,22326,Male,Loyal Customer,59,Business travel,Eco,208,4,5,5,5,4,4,4,4,2,5,4,3,1,4,0,0.0,satisfied +71416,78497,Female,disloyal Customer,45,Business travel,Eco,666,2,1,2,3,5,2,5,5,4,4,3,2,3,5,0,16.0,neutral or dissatisfied +71417,68337,Male,Loyal Customer,40,Business travel,Business,1598,2,4,2,2,4,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +71418,22271,Female,Loyal Customer,48,Business travel,Eco,238,4,2,2,2,1,3,1,4,4,4,4,2,4,5,0,30.0,satisfied +71419,65352,Male,disloyal Customer,38,Business travel,Eco,432,3,1,3,3,1,3,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +71420,105140,Male,Loyal Customer,25,Business travel,Business,1595,2,2,2,2,2,2,2,2,2,4,3,3,4,2,115,120.0,neutral or dissatisfied +71421,25997,Male,Loyal Customer,45,Personal Travel,Eco,577,2,5,2,3,5,2,5,5,4,5,4,3,4,5,29,20.0,neutral or dissatisfied +71422,100589,Female,Loyal Customer,53,Personal Travel,Eco,486,1,5,1,4,5,4,4,5,5,1,1,1,5,1,58,53.0,neutral or dissatisfied +71423,43431,Female,Loyal Customer,55,Personal Travel,Eco,913,2,4,2,1,2,4,4,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +71424,96561,Female,Loyal Customer,50,Business travel,Business,2696,4,4,4,4,2,4,5,5,5,5,5,3,5,3,5,21.0,satisfied +71425,25968,Female,Loyal Customer,36,Personal Travel,Eco,946,4,3,4,4,2,4,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +71426,23756,Female,Loyal Customer,9,Personal Travel,Eco,1048,5,1,5,4,2,5,2,2,4,5,3,2,3,2,0,0.0,satisfied +71427,68726,Female,disloyal Customer,16,Business travel,Eco,175,3,2,3,3,5,3,5,5,4,2,3,3,4,5,47,44.0,neutral or dissatisfied +71428,111651,Female,Loyal Customer,55,Business travel,Business,1558,3,3,3,3,3,4,5,4,4,4,4,5,4,4,14,28.0,satisfied +71429,77496,Female,Loyal Customer,49,Business travel,Eco,795,4,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +71430,36047,Male,Loyal Customer,38,Business travel,Business,399,3,3,3,3,3,1,5,4,4,4,4,2,4,2,0,0.0,satisfied +71431,76566,Female,disloyal Customer,26,Business travel,Eco,534,1,1,0,2,3,0,3,3,2,4,2,3,1,3,3,49.0,neutral or dissatisfied +71432,118949,Male,Loyal Customer,52,Business travel,Eco,682,2,2,2,2,1,2,1,1,1,3,2,4,3,1,9,0.0,neutral or dissatisfied +71433,66580,Male,Loyal Customer,60,Business travel,Business,1995,1,1,1,1,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +71434,51643,Male,Loyal Customer,28,Business travel,Business,261,2,3,3,3,2,2,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +71435,23615,Male,Loyal Customer,40,Business travel,Eco,977,4,5,5,5,4,4,4,4,1,2,3,2,3,4,0,16.0,satisfied +71436,110151,Male,Loyal Customer,41,Business travel,Business,2539,2,3,3,3,1,4,3,2,2,2,2,1,2,1,0,5.0,neutral or dissatisfied +71437,59387,Female,Loyal Customer,34,Personal Travel,Eco,2486,3,1,3,3,2,3,2,2,2,2,2,3,3,2,0,0.0,neutral or dissatisfied +71438,45633,Male,Loyal Customer,38,Business travel,Business,1893,2,2,1,2,4,4,4,4,4,5,4,1,4,1,0,0.0,satisfied +71439,31764,Female,Loyal Customer,36,Business travel,Business,2503,3,3,3,3,2,4,3,5,5,5,5,5,5,5,2,0.0,satisfied +71440,105241,Female,Loyal Customer,70,Personal Travel,Eco,377,1,5,1,1,5,5,4,2,2,1,3,4,2,3,16,6.0,neutral or dissatisfied +71441,60582,Female,Loyal Customer,32,Business travel,Business,1558,4,5,5,5,4,4,4,4,2,2,3,4,2,4,24,16.0,neutral or dissatisfied +71442,7533,Male,Loyal Customer,38,Business travel,Business,1638,3,1,3,3,4,4,3,3,3,3,3,2,3,1,20,13.0,neutral or dissatisfied +71443,60770,Male,Loyal Customer,45,Business travel,Business,2898,1,2,4,2,3,3,2,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +71444,38820,Female,Loyal Customer,47,Personal Travel,Eco,354,3,1,3,3,5,4,4,3,3,3,3,3,3,2,13,13.0,neutral or dissatisfied +71445,16777,Male,Loyal Customer,61,Personal Travel,Eco,569,3,5,3,2,4,3,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +71446,45811,Female,Loyal Customer,47,Business travel,Business,3203,3,2,2,2,1,3,4,3,3,2,3,1,3,2,0,39.0,neutral or dissatisfied +71447,88160,Male,Loyal Customer,47,Business travel,Business,3750,5,5,5,5,2,5,5,4,4,4,4,3,4,4,50,52.0,satisfied +71448,63509,Female,Loyal Customer,40,Business travel,Business,2694,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +71449,105506,Female,Loyal Customer,13,Personal Travel,Business,611,1,3,1,5,3,1,3,3,2,3,2,1,1,3,10,18.0,neutral or dissatisfied +71450,55456,Male,Loyal Customer,50,Business travel,Business,827,2,2,2,2,3,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +71451,79351,Female,Loyal Customer,11,Personal Travel,Eco,1029,4,4,4,3,3,4,5,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +71452,120570,Female,Loyal Customer,21,Personal Travel,Eco,2176,1,4,1,4,1,1,1,1,4,2,3,4,1,1,0,0.0,neutral or dissatisfied +71453,14696,Male,Loyal Customer,67,Business travel,Business,317,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +71454,79338,Male,Loyal Customer,25,Business travel,Business,2283,5,5,5,5,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +71455,72990,Male,Loyal Customer,60,Business travel,Business,2249,4,2,2,2,1,3,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +71456,43201,Female,Loyal Customer,36,Business travel,Eco,466,3,1,5,1,3,3,3,3,2,1,4,3,3,3,24,13.0,neutral or dissatisfied +71457,53538,Female,disloyal Customer,16,Business travel,Eco,1062,4,4,4,4,1,4,5,1,4,5,3,1,5,1,0,0.0,satisfied +71458,40125,Male,Loyal Customer,48,Personal Travel,Eco,200,3,4,3,5,5,3,2,5,5,4,4,3,2,5,0,0.0,neutral or dissatisfied +71459,33753,Male,Loyal Customer,36,Business travel,Business,3233,0,0,0,3,5,5,1,3,3,3,3,4,3,3,0,9.0,satisfied +71460,74535,Male,Loyal Customer,50,Business travel,Eco,1171,4,1,1,1,4,4,4,4,4,4,3,1,4,4,0,0.0,neutral or dissatisfied +71461,6278,Male,Loyal Customer,36,Business travel,Eco,185,4,2,2,2,4,4,4,4,4,3,2,3,4,4,0,0.0,satisfied +71462,86087,Male,Loyal Customer,32,Business travel,Business,3736,0,1,1,4,3,3,3,3,5,2,5,5,5,3,0,0.0,satisfied +71463,23476,Male,Loyal Customer,33,Personal Travel,Eco,576,3,4,3,2,2,3,2,2,3,4,4,5,5,2,5,0.0,neutral or dissatisfied +71464,22881,Female,Loyal Customer,48,Personal Travel,Eco,147,3,1,3,4,3,4,4,1,1,3,1,1,1,2,0,0.0,neutral or dissatisfied +71465,79915,Female,Loyal Customer,54,Business travel,Business,3867,5,2,2,2,3,4,3,5,5,4,5,1,5,1,0,0.0,neutral or dissatisfied +71466,114083,Female,Loyal Customer,34,Business travel,Business,1892,1,1,1,1,1,3,5,4,4,4,4,2,4,1,0,0.0,satisfied +71467,91421,Female,Loyal Customer,21,Business travel,Business,549,4,1,1,1,4,4,4,4,1,1,4,2,3,4,74,60.0,neutral or dissatisfied +71468,107342,Female,Loyal Customer,36,Business travel,Business,3311,3,3,3,3,2,4,5,3,3,3,3,4,3,3,59,40.0,satisfied +71469,22085,Female,disloyal Customer,22,Business travel,Eco,782,5,5,5,3,2,5,2,2,5,5,5,5,5,2,9,0.0,satisfied +71470,115615,Female,Loyal Customer,39,Business travel,Business,325,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +71471,99187,Female,Loyal Customer,51,Personal Travel,Eco,351,4,4,4,3,5,5,5,1,1,4,1,3,1,5,23,17.0,neutral or dissatisfied +71472,66152,Male,disloyal Customer,22,Business travel,Business,550,4,0,4,4,2,4,2,2,3,4,5,5,5,2,0,0.0,satisfied +71473,49160,Female,Loyal Customer,30,Business travel,Business,3302,2,2,2,2,5,5,4,5,1,3,2,5,3,5,25,21.0,satisfied +71474,83169,Male,Loyal Customer,69,Personal Travel,Eco Plus,983,1,5,1,2,3,1,3,3,4,5,5,4,4,3,9,18.0,neutral or dissatisfied +71475,115942,Female,Loyal Customer,42,Personal Travel,Eco,308,2,5,2,4,4,5,5,2,2,2,2,4,2,4,4,0.0,neutral or dissatisfied +71476,89354,Male,Loyal Customer,58,Business travel,Eco,1141,3,4,4,4,3,3,3,3,4,2,4,1,4,3,17,0.0,neutral or dissatisfied +71477,87917,Female,Loyal Customer,39,Business travel,Business,2230,2,4,4,4,2,2,2,2,2,2,2,1,2,1,22,38.0,neutral or dissatisfied +71478,85877,Female,disloyal Customer,27,Business travel,Business,2172,4,5,5,1,5,2,2,4,3,5,4,2,5,2,11,50.0,satisfied +71479,21565,Female,disloyal Customer,27,Business travel,Eco Plus,164,1,1,1,2,1,1,1,1,1,2,2,3,3,1,0,0.0,neutral or dissatisfied +71480,107228,Male,Loyal Customer,36,Business travel,Business,583,1,1,2,1,3,4,4,4,4,4,4,5,4,3,50,43.0,satisfied +71481,16194,Female,Loyal Customer,44,Personal Travel,Eco,212,4,2,0,3,2,4,3,1,1,0,1,4,1,2,0,0.0,satisfied +71482,59718,Male,Loyal Customer,56,Business travel,Business,2469,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +71483,114569,Male,Loyal Customer,69,Personal Travel,Business,417,3,3,3,1,2,4,2,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +71484,128452,Male,Loyal Customer,60,Personal Travel,Eco,646,5,2,5,3,2,5,2,2,3,5,3,3,4,2,0,0.0,satisfied +71485,54634,Female,Loyal Customer,47,Business travel,Business,854,1,1,2,1,4,2,1,5,5,5,5,1,5,2,1,0.0,satisfied +71486,45597,Female,Loyal Customer,60,Business travel,Business,3515,1,1,1,1,4,5,2,5,5,5,5,5,5,4,0,3.0,satisfied +71487,29637,Male,disloyal Customer,36,Business travel,Eco,1048,1,1,1,3,4,1,4,4,3,4,3,3,4,4,0,7.0,neutral or dissatisfied +71488,35950,Female,disloyal Customer,24,Business travel,Eco,231,2,5,2,2,4,2,4,4,1,4,5,4,4,4,0,0.0,neutral or dissatisfied +71489,100310,Female,Loyal Customer,51,Business travel,Business,1871,2,1,1,1,3,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +71490,78886,Female,Loyal Customer,52,Business travel,Business,1727,3,3,3,3,4,4,4,4,4,4,4,4,4,3,1,1.0,satisfied +71491,124765,Female,Loyal Customer,45,Business travel,Business,280,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +71492,62003,Female,disloyal Customer,23,Business travel,Business,2475,4,0,4,3,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +71493,46666,Male,Loyal Customer,30,Business travel,Business,73,4,1,1,1,2,2,4,2,2,1,4,1,3,2,0,0.0,neutral or dissatisfied +71494,33586,Female,Loyal Customer,40,Business travel,Eco,399,5,4,4,4,5,5,5,5,2,2,5,1,5,5,0,0.0,satisfied +71495,109991,Male,Loyal Customer,56,Personal Travel,Eco Plus,1130,2,5,2,3,3,2,3,3,5,3,4,3,4,3,6,0.0,neutral or dissatisfied +71496,61596,Male,Loyal Customer,39,Business travel,Business,1346,1,1,1,1,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +71497,123618,Male,Loyal Customer,60,Business travel,Business,1989,0,4,0,4,3,5,4,1,1,1,1,5,1,4,0,0.0,satisfied +71498,26559,Male,disloyal Customer,62,Business travel,Business,404,3,3,3,3,3,3,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +71499,73120,Female,Loyal Customer,54,Personal Travel,Eco,2174,3,3,3,3,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +71500,111742,Male,Loyal Customer,52,Business travel,Business,3965,3,4,2,4,5,2,3,3,3,3,3,3,3,4,2,3.0,neutral or dissatisfied +71501,74471,Male,Loyal Customer,31,Business travel,Business,1235,4,4,4,4,5,5,5,5,3,5,5,4,4,5,0,0.0,satisfied +71502,23716,Male,Loyal Customer,15,Personal Travel,Eco,251,1,5,1,3,1,1,1,1,2,1,5,4,5,1,7,0.0,neutral or dissatisfied +71503,7526,Female,Loyal Customer,34,Business travel,Business,2408,3,2,2,2,1,2,1,3,3,3,3,2,3,2,68,54.0,neutral or dissatisfied +71504,9383,Male,Loyal Customer,24,Personal Travel,Eco,401,4,4,4,2,5,4,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +71505,92687,Female,Loyal Customer,65,Personal Travel,Eco,507,2,4,3,4,4,4,4,4,4,3,4,4,4,3,7,1.0,neutral or dissatisfied +71506,2184,Male,Loyal Customer,42,Business travel,Business,624,4,4,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +71507,92152,Female,Loyal Customer,25,Business travel,Business,1532,1,1,2,1,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +71508,23093,Female,Loyal Customer,44,Personal Travel,Eco Plus,794,4,1,4,4,5,4,4,1,1,4,1,4,1,3,0,0.0,satisfied +71509,84517,Male,Loyal Customer,44,Business travel,Business,2486,3,3,3,3,5,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +71510,1757,Male,Loyal Customer,55,Business travel,Business,3819,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +71511,79621,Male,Loyal Customer,31,Business travel,Business,2419,2,5,5,5,2,2,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +71512,107563,Female,Loyal Customer,44,Personal Travel,Eco,1521,2,5,2,1,2,5,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +71513,125289,Female,Loyal Customer,57,Business travel,Business,678,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +71514,110274,Female,disloyal Customer,27,Business travel,Business,519,2,2,2,4,1,2,1,1,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +71515,26777,Male,Loyal Customer,26,Business travel,Business,3232,1,1,1,1,3,4,3,3,3,5,1,2,5,3,5,0.0,satisfied +71516,16356,Female,disloyal Customer,43,Business travel,Business,319,3,3,3,4,5,3,3,5,2,1,4,2,3,5,31,43.0,neutral or dissatisfied +71517,40803,Male,disloyal Customer,22,Business travel,Eco,558,2,0,2,2,2,2,5,2,3,2,3,4,5,2,7,0.0,neutral or dissatisfied +71518,32297,Female,Loyal Customer,55,Business travel,Eco,101,3,2,3,2,5,5,2,2,2,3,2,3,2,1,24,26.0,satisfied +71519,45182,Female,Loyal Customer,74,Business travel,Eco Plus,174,5,1,1,1,1,3,2,5,5,5,5,5,5,2,0,0.0,satisfied +71520,100855,Female,Loyal Customer,65,Personal Travel,Eco,711,3,2,2,4,1,4,4,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +71521,109745,Female,Loyal Customer,55,Personal Travel,Eco,468,2,3,2,2,5,3,4,4,4,2,4,1,4,4,29,21.0,neutral or dissatisfied +71522,100890,Male,disloyal Customer,46,Business travel,Business,377,3,3,3,2,1,3,1,1,3,4,4,5,4,1,3,3.0,neutral or dissatisfied +71523,1921,Male,disloyal Customer,24,Business travel,Eco,351,5,0,5,2,2,5,2,2,5,5,4,5,5,2,43,54.0,satisfied +71524,31512,Male,disloyal Customer,22,Business travel,Eco,846,3,3,3,2,1,3,1,1,4,3,2,4,3,1,0,11.0,neutral or dissatisfied +71525,85415,Female,disloyal Customer,22,Business travel,Eco,214,3,2,3,3,5,3,5,5,3,5,4,3,3,5,2,0.0,neutral or dissatisfied +71526,18237,Male,disloyal Customer,47,Business travel,Business,228,2,2,2,1,3,2,3,3,3,3,3,3,5,3,0,0.0,neutral or dissatisfied +71527,108144,Female,disloyal Customer,30,Business travel,Eco,1105,3,3,3,3,2,3,2,2,4,3,4,1,3,2,29,2.0,neutral or dissatisfied +71528,42187,Male,Loyal Customer,27,Business travel,Eco,462,4,3,3,3,4,4,4,4,4,1,2,3,4,4,0,0.0,satisfied +71529,99493,Female,Loyal Customer,63,Personal Travel,Eco,283,4,3,4,4,2,3,4,4,4,4,4,3,4,1,0,1.0,neutral or dissatisfied +71530,976,Female,Loyal Customer,54,Business travel,Business,309,1,0,0,3,3,3,2,4,4,0,4,1,4,4,0,0.0,neutral or dissatisfied +71531,22339,Female,Loyal Customer,61,Business travel,Business,2864,4,4,4,4,5,3,5,5,5,5,5,2,5,2,0,0.0,satisfied +71532,4896,Male,disloyal Customer,26,Business travel,Business,620,4,4,4,4,5,4,5,5,5,4,5,4,5,5,5,0.0,neutral or dissatisfied +71533,89977,Female,Loyal Customer,43,Business travel,Business,1416,4,4,4,4,4,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +71534,1953,Female,Loyal Customer,27,Business travel,Business,1756,3,4,4,4,3,3,3,3,3,5,3,4,2,3,0,0.0,neutral or dissatisfied +71535,112346,Male,Loyal Customer,27,Business travel,Business,2866,4,1,4,4,4,4,4,4,4,3,5,5,4,4,9,0.0,satisfied +71536,94386,Female,Loyal Customer,69,Business travel,Business,239,3,3,3,3,5,4,5,5,5,5,5,3,5,5,27,27.0,satisfied +71537,124347,Female,Loyal Customer,52,Business travel,Business,2114,1,1,1,1,3,4,4,4,4,4,4,5,4,5,30,29.0,satisfied +71538,16613,Female,Loyal Customer,40,Business travel,Business,2938,3,2,2,2,4,2,3,3,3,3,3,1,3,2,24,12.0,neutral or dissatisfied +71539,86547,Female,disloyal Customer,27,Business travel,Eco Plus,762,2,2,2,3,5,2,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +71540,90744,Male,Loyal Customer,30,Business travel,Business,2090,3,3,3,3,2,2,2,2,3,4,5,3,4,2,0,2.0,satisfied +71541,108970,Female,disloyal Customer,27,Business travel,Eco Plus,655,4,4,4,3,3,4,3,3,1,5,3,2,4,3,33,18.0,neutral or dissatisfied +71542,102452,Female,Loyal Customer,32,Personal Travel,Eco,226,3,5,3,2,2,3,2,2,3,3,4,5,4,2,40,45.0,neutral or dissatisfied +71543,67255,Female,Loyal Customer,34,Personal Travel,Eco,1119,2,5,3,3,5,3,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +71544,70989,Male,Loyal Customer,45,Business travel,Business,3824,5,5,2,5,3,5,5,4,4,4,4,4,4,3,32,30.0,satisfied +71545,122454,Male,Loyal Customer,45,Business travel,Business,2162,2,2,2,2,4,5,5,4,4,4,4,4,4,4,4,7.0,satisfied +71546,83391,Female,Loyal Customer,43,Business travel,Business,632,1,1,1,1,4,5,5,2,2,2,2,3,2,3,0,19.0,satisfied +71547,42344,Female,Loyal Customer,24,Personal Travel,Eco,834,5,5,5,4,4,5,4,4,5,3,5,4,4,4,0,0.0,satisfied +71548,63781,Female,Loyal Customer,44,Business travel,Eco,1721,3,2,5,2,3,1,2,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +71549,95989,Male,disloyal Customer,37,Business travel,Business,583,3,3,3,1,3,3,3,3,3,2,5,4,4,3,6,2.0,neutral or dissatisfied +71550,38208,Female,disloyal Customer,46,Business travel,Eco Plus,1220,4,4,4,4,3,4,3,3,3,1,4,5,2,3,0,0.0,neutral or dissatisfied +71551,54551,Female,Loyal Customer,18,Personal Travel,Eco,925,4,4,4,4,3,4,3,3,4,2,5,4,5,3,9,0.0,satisfied +71552,64263,Male,Loyal Customer,48,Business travel,Business,1212,3,3,3,3,4,4,4,4,4,4,4,3,4,3,9,0.0,satisfied +71553,38544,Male,Loyal Customer,52,Business travel,Business,2465,2,2,2,2,5,3,4,4,4,5,4,4,4,1,0,0.0,satisfied +71554,28008,Male,Loyal Customer,39,Business travel,Business,763,4,4,4,4,2,2,3,5,5,5,5,1,5,5,0,3.0,satisfied +71555,79282,Female,Loyal Customer,67,Personal Travel,Business,2248,2,4,2,2,2,1,1,5,5,5,4,1,3,1,0,13.0,neutral or dissatisfied +71556,55512,Male,Loyal Customer,35,Business travel,Business,991,1,1,5,1,3,5,4,4,4,4,4,4,4,5,44,28.0,satisfied +71557,29974,Male,Loyal Customer,50,Business travel,Business,95,1,3,3,3,4,1,3,4,3,4,4,3,2,3,455,,neutral or dissatisfied +71558,85706,Female,Loyal Customer,51,Personal Travel,Eco,1547,3,3,3,3,2,2,2,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +71559,110792,Female,Loyal Customer,62,Business travel,Business,597,2,2,2,2,2,3,4,4,4,4,4,5,4,1,0,1.0,satisfied +71560,71557,Male,Loyal Customer,52,Business travel,Business,1012,1,1,1,1,4,4,5,5,5,5,5,5,5,5,87,100.0,satisfied +71561,71890,Male,Loyal Customer,49,Personal Travel,Eco,1744,1,5,1,1,2,1,2,2,5,3,3,3,4,2,0,4.0,neutral or dissatisfied +71562,47973,Male,Loyal Customer,63,Personal Travel,Eco,817,1,1,1,3,4,1,3,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +71563,45851,Female,disloyal Customer,23,Business travel,Eco,517,3,5,3,3,5,3,5,5,4,3,3,1,3,5,18,29.0,neutral or dissatisfied +71564,97436,Male,Loyal Customer,62,Personal Travel,Eco Plus,587,3,4,3,4,5,3,5,5,1,4,3,2,4,5,60,52.0,neutral or dissatisfied +71565,126697,Female,Loyal Customer,33,Business travel,Business,2370,3,3,3,3,5,4,4,4,4,4,4,4,4,4,12,8.0,satisfied +71566,129070,Female,Loyal Customer,39,Business travel,Business,2218,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +71567,67593,Female,Loyal Customer,51,Business travel,Business,1464,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +71568,7439,Female,Loyal Customer,19,Personal Travel,Eco,522,2,3,2,1,4,2,4,4,2,2,5,5,5,4,37,41.0,neutral or dissatisfied +71569,121225,Female,Loyal Customer,55,Business travel,Business,2075,5,1,5,5,3,5,5,4,4,4,4,4,4,3,39,26.0,satisfied +71570,52001,Male,Loyal Customer,70,Personal Travel,Eco,1119,1,4,1,4,4,1,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +71571,5979,Male,Loyal Customer,29,Business travel,Business,3818,5,3,5,5,5,5,5,5,4,2,5,5,5,5,0,3.0,satisfied +71572,40957,Male,Loyal Customer,21,Business travel,Eco,601,0,4,0,4,3,0,3,3,2,3,1,4,3,3,0,0.0,satisfied +71573,98612,Male,Loyal Customer,47,Business travel,Business,2092,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +71574,77284,Female,Loyal Customer,51,Business travel,Business,2505,4,4,3,4,5,1,1,5,5,5,5,4,5,1,0,0.0,satisfied +71575,45509,Female,Loyal Customer,23,Business travel,Business,2980,4,4,4,4,4,4,4,4,4,4,3,1,3,4,5,21.0,neutral or dissatisfied +71576,24245,Male,Loyal Customer,69,Personal Travel,Eco,147,0,1,0,4,4,0,4,4,4,4,3,2,3,4,0,0.0,satisfied +71577,40990,Female,Loyal Customer,8,Personal Travel,Eco,984,2,2,2,3,1,2,1,1,1,1,2,2,3,1,42,53.0,neutral or dissatisfied +71578,16278,Female,Loyal Customer,18,Personal Travel,Eco,946,3,2,3,3,5,3,5,5,3,2,3,2,3,5,0,17.0,neutral or dissatisfied +71579,49088,Female,Loyal Customer,27,Business travel,Business,2714,3,2,2,2,3,3,3,3,3,4,4,2,4,3,64,76.0,neutral or dissatisfied +71580,31867,Female,Loyal Customer,57,Business travel,Business,2603,4,2,2,2,1,2,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +71581,55331,Male,Loyal Customer,56,Personal Travel,Eco,1325,3,4,4,3,5,4,5,5,3,4,5,4,5,5,2,0.0,neutral or dissatisfied +71582,67899,Male,Loyal Customer,26,Personal Travel,Eco,1464,1,4,1,1,1,1,5,5,5,3,5,5,3,5,238,255.0,neutral or dissatisfied +71583,9881,Male,Loyal Customer,45,Business travel,Business,1551,3,5,5,5,5,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +71584,57719,Female,disloyal Customer,22,Business travel,Eco,770,2,2,2,3,2,5,5,3,5,5,4,5,5,5,162,160.0,neutral or dissatisfied +71585,47559,Male,Loyal Customer,27,Business travel,Eco Plus,599,1,4,4,4,1,1,1,1,1,1,3,2,3,1,0,1.0,neutral or dissatisfied +71586,61579,Female,Loyal Customer,60,Business travel,Business,2107,4,4,4,4,4,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +71587,9089,Female,Loyal Customer,33,Personal Travel,Eco,212,2,1,2,3,5,2,5,5,1,5,4,1,3,5,0,0.0,neutral or dissatisfied +71588,82790,Male,Loyal Customer,12,Personal Travel,Eco,231,1,4,1,3,5,1,5,5,4,3,4,4,4,5,12,19.0,neutral or dissatisfied +71589,78199,Female,Loyal Customer,42,Business travel,Business,1754,4,5,5,5,5,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +71590,1537,Female,Loyal Customer,30,Business travel,Business,922,3,4,4,4,3,3,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +71591,127764,Female,Loyal Customer,19,Personal Travel,Eco,255,3,3,3,2,3,3,3,3,1,4,5,2,1,3,0,1.0,neutral or dissatisfied +71592,83110,Male,Loyal Customer,60,Personal Travel,Eco,1127,2,5,2,1,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +71593,57524,Female,disloyal Customer,35,Business travel,Business,413,4,4,4,5,3,4,3,3,4,2,5,4,4,3,114,124.0,neutral or dissatisfied +71594,90010,Male,Loyal Customer,49,Personal Travel,Business,1086,3,4,3,3,2,4,4,1,1,3,1,5,1,4,7,0.0,neutral or dissatisfied +71595,96577,Female,Loyal Customer,54,Personal Travel,Eco,333,4,2,1,1,3,1,2,4,4,1,5,1,4,3,0,0.0,satisfied +71596,93101,Male,disloyal Customer,35,Business travel,Eco,641,3,0,2,1,2,2,2,2,1,1,3,1,4,2,6,0.0,neutral or dissatisfied +71597,103368,Female,Loyal Customer,66,Personal Travel,Eco,342,1,5,1,3,2,4,5,5,5,1,5,4,5,3,35,33.0,neutral or dissatisfied +71598,27535,Female,Loyal Customer,58,Personal Travel,Eco,978,2,5,2,5,5,5,5,1,1,2,1,4,1,3,0,1.0,neutral or dissatisfied +71599,32614,Male,disloyal Customer,18,Business travel,Business,216,3,4,3,4,4,3,4,4,2,1,4,2,3,4,2,7.0,neutral or dissatisfied +71600,50354,Male,Loyal Customer,58,Business travel,Business,3525,1,1,1,1,4,4,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +71601,45624,Male,Loyal Customer,32,Business travel,Business,3884,1,2,2,2,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +71602,102527,Female,Loyal Customer,37,Personal Travel,Eco,236,3,4,0,4,2,0,2,2,1,4,1,4,5,2,69,81.0,neutral or dissatisfied +71603,11250,Male,Loyal Customer,43,Personal Travel,Eco,295,2,5,2,2,2,2,2,2,1,5,2,1,5,2,0,0.0,neutral or dissatisfied +71604,25493,Female,disloyal Customer,25,Business travel,Eco,516,2,5,2,4,3,2,3,3,2,5,1,2,5,3,0,0.0,neutral or dissatisfied +71605,6596,Female,Loyal Customer,44,Personal Travel,Eco,473,2,5,2,3,1,4,5,5,5,2,5,4,5,1,42,34.0,neutral or dissatisfied +71606,47213,Male,Loyal Customer,18,Personal Travel,Eco,679,4,5,4,4,1,4,1,1,5,3,4,3,4,1,13,0.0,satisfied +71607,92310,Female,Loyal Customer,39,Business travel,Business,2486,1,1,1,1,3,3,3,3,3,4,4,3,4,3,0,40.0,satisfied +71608,109261,Female,Loyal Customer,40,Business travel,Business,1566,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,3.0,satisfied +71609,64309,Male,Loyal Customer,54,Business travel,Business,3293,2,2,2,2,5,4,5,4,4,4,4,5,4,4,36,9.0,satisfied +71610,123241,Female,Loyal Customer,48,Personal Travel,Eco,650,1,5,1,1,2,3,5,1,1,1,2,1,1,1,0,0.0,neutral or dissatisfied +71611,121988,Male,Loyal Customer,51,Business travel,Business,130,5,4,5,5,5,4,4,5,5,4,4,3,5,4,0,0.0,satisfied +71612,74172,Female,Loyal Customer,57,Personal Travel,Eco,678,4,4,3,4,3,5,4,3,3,3,3,3,3,3,1,1.0,neutral or dissatisfied +71613,69129,Male,Loyal Customer,56,Personal Travel,Eco,1598,3,4,3,3,2,3,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +71614,42197,Male,disloyal Customer,50,Business travel,Eco,462,4,4,4,3,5,4,5,5,4,3,3,5,5,5,0,0.0,neutral or dissatisfied +71615,112420,Female,disloyal Customer,23,Business travel,Eco,948,1,1,1,3,3,1,3,3,4,1,3,2,3,3,5,7.0,neutral or dissatisfied +71616,92363,Female,Loyal Customer,29,Business travel,Business,1947,2,2,2,2,5,5,5,5,3,3,5,4,5,5,0,0.0,satisfied +71617,76173,Male,Loyal Customer,37,Personal Travel,Eco,689,3,3,3,3,2,3,2,2,4,1,5,1,5,2,0,0.0,neutral or dissatisfied +71618,41779,Male,Loyal Customer,23,Business travel,Business,2086,4,4,4,4,4,5,4,4,4,3,4,5,2,4,0,0.0,satisfied +71619,3102,Male,Loyal Customer,39,Personal Travel,Eco,413,2,4,2,1,3,2,3,3,4,5,4,5,4,3,37,79.0,neutral or dissatisfied +71620,58607,Male,Loyal Customer,51,Personal Travel,Eco,334,2,4,2,4,2,3,3,3,3,4,5,3,4,3,238,212.0,neutral or dissatisfied +71621,68737,Male,Loyal Customer,20,Business travel,Business,585,4,4,4,4,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +71622,30552,Female,Loyal Customer,32,Personal Travel,Eco,955,1,5,1,3,2,1,4,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +71623,98132,Female,Loyal Customer,33,Personal Travel,Eco,472,1,4,1,4,5,1,3,5,1,1,5,1,4,5,0,0.0,neutral or dissatisfied +71624,122724,Male,disloyal Customer,24,Business travel,Eco,651,1,5,2,4,4,2,4,4,4,5,5,3,5,4,27,46.0,neutral or dissatisfied +71625,94275,Male,Loyal Customer,55,Business travel,Business,1748,3,3,3,3,2,4,4,4,4,4,4,4,4,3,5,5.0,satisfied +71626,36708,Female,Loyal Customer,54,Personal Travel,Eco,1197,2,5,2,2,3,3,5,5,5,2,5,5,5,5,0,7.0,neutral or dissatisfied +71627,122330,Male,Loyal Customer,35,Business travel,Eco Plus,544,4,2,2,2,4,4,4,4,5,5,1,2,3,4,0,0.0,satisfied +71628,74175,Female,Loyal Customer,39,Personal Travel,Eco,641,4,5,4,1,4,4,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +71629,83248,Male,disloyal Customer,21,Business travel,Eco,2079,3,3,3,3,5,3,5,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +71630,79491,Female,Loyal Customer,18,Personal Travel,Business,749,3,4,3,3,4,3,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +71631,80840,Female,disloyal Customer,34,Business travel,Eco,484,4,2,4,4,1,4,1,1,4,5,4,1,4,1,0,0.0,neutral or dissatisfied +71632,11454,Female,Loyal Customer,49,Business travel,Eco Plus,166,3,4,4,4,4,4,4,2,2,3,2,4,2,2,25,12.0,neutral or dissatisfied +71633,107067,Female,Loyal Customer,32,Personal Travel,Eco,395,2,4,2,5,5,2,5,5,3,1,1,3,2,5,8,6.0,neutral or dissatisfied +71634,118481,Female,disloyal Customer,28,Business travel,Business,325,1,1,1,3,5,1,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +71635,53166,Male,Loyal Customer,18,Business travel,Business,1801,2,2,2,2,4,4,4,4,5,3,2,1,5,4,0,0.0,satisfied +71636,24570,Male,Loyal Customer,15,Personal Travel,Eco,696,4,5,4,2,4,4,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +71637,69053,Female,Loyal Customer,24,Business travel,Business,1389,2,4,4,4,2,2,2,2,4,2,3,3,3,2,18,0.0,neutral or dissatisfied +71638,108278,Male,Loyal Customer,26,Personal Travel,Eco,895,1,4,1,3,1,1,1,1,3,4,4,4,4,1,36,33.0,neutral or dissatisfied +71639,96500,Male,disloyal Customer,27,Business travel,Eco,436,2,1,2,4,4,2,4,4,3,3,4,2,3,4,49,44.0,neutral or dissatisfied +71640,34043,Male,disloyal Customer,24,Business travel,Eco,1006,5,5,5,3,5,5,5,5,2,5,1,4,5,5,28,21.0,satisfied +71641,36991,Female,disloyal Customer,27,Business travel,Eco,814,2,2,2,3,4,2,4,4,1,3,3,1,4,4,22,16.0,neutral or dissatisfied +71642,69422,Female,disloyal Customer,20,Business travel,Eco,1096,1,1,1,3,4,1,4,4,2,2,4,5,1,4,0,0.0,neutral or dissatisfied +71643,122140,Male,Loyal Customer,44,Business travel,Business,546,1,1,1,1,3,5,5,2,2,2,2,5,2,4,0,4.0,satisfied +71644,116933,Male,Loyal Customer,50,Business travel,Business,2297,5,5,5,5,2,4,5,4,4,5,4,3,4,3,2,4.0,satisfied +71645,62848,Female,Loyal Customer,19,Business travel,Eco Plus,2447,5,4,4,4,5,3,5,5,2,1,4,5,3,5,6,32.0,satisfied +71646,84485,Male,Loyal Customer,16,Personal Travel,Eco Plus,2677,1,4,1,3,5,1,5,5,2,5,3,1,3,5,0,0.0,neutral or dissatisfied +71647,83642,Male,disloyal Customer,22,Business travel,Business,577,5,0,5,3,5,5,5,5,5,3,5,3,4,5,9,0.0,satisfied +71648,28508,Female,Loyal Customer,59,Business travel,Business,2715,3,3,3,3,4,4,4,2,5,4,4,4,3,4,0,0.0,satisfied +71649,6220,Female,disloyal Customer,24,Business travel,Eco,678,4,4,4,1,5,4,1,5,5,3,5,4,5,5,125,129.0,neutral or dissatisfied +71650,86265,Male,Loyal Customer,56,Personal Travel,Eco,356,1,4,2,4,2,2,4,2,2,1,4,3,5,2,0,21.0,neutral or dissatisfied +71651,38520,Female,Loyal Customer,44,Business travel,Business,2521,3,3,4,3,2,4,5,4,4,4,4,1,4,5,15,10.0,satisfied +71652,66027,Male,disloyal Customer,21,Business travel,Eco,1055,4,4,4,3,5,4,5,5,4,3,4,5,5,5,0,0.0,satisfied +71653,29118,Male,Loyal Customer,61,Personal Travel,Eco,978,3,4,3,2,4,3,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +71654,8571,Male,Loyal Customer,50,Business travel,Business,1985,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +71655,8722,Male,Loyal Customer,50,Personal Travel,Eco,280,2,3,2,3,2,2,2,2,1,5,3,2,4,2,0,3.0,neutral or dissatisfied +71656,73775,Male,Loyal Customer,44,Personal Travel,Eco,192,0,4,0,3,5,0,5,5,3,2,4,3,4,5,0,0.0,satisfied +71657,89037,Female,Loyal Customer,37,Business travel,Business,1947,1,1,3,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +71658,16584,Female,Loyal Customer,46,Personal Travel,Eco,1092,3,1,3,4,2,3,4,2,2,3,2,2,2,4,21,19.0,neutral or dissatisfied +71659,60749,Male,disloyal Customer,26,Business travel,Business,628,5,4,4,3,2,4,1,2,3,5,4,4,5,2,102,102.0,satisfied +71660,103051,Female,Loyal Customer,35,Business travel,Business,2400,3,3,3,3,2,4,4,3,3,3,3,2,3,3,25,15.0,neutral or dissatisfied +71661,56639,Male,Loyal Customer,40,Business travel,Eco,1085,1,1,1,1,1,1,1,1,2,2,3,4,4,1,0,0.0,neutral or dissatisfied +71662,30517,Male,Loyal Customer,46,Business travel,Business,484,3,3,3,3,1,1,1,5,5,5,5,1,5,3,25,23.0,satisfied +71663,39380,Female,Loyal Customer,50,Business travel,Business,521,1,1,1,1,3,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +71664,93838,Female,Loyal Customer,27,Business travel,Business,2708,5,5,1,5,3,4,3,3,5,4,5,3,1,3,19,8.0,satisfied +71665,35689,Female,Loyal Customer,20,Business travel,Business,2475,4,1,1,1,3,4,4,3,2,3,3,4,2,4,0,10.0,neutral or dissatisfied +71666,36130,Male,Loyal Customer,21,Business travel,Business,1562,4,2,2,2,4,4,4,4,1,1,4,1,3,4,30,86.0,neutral or dissatisfied +71667,97182,Female,Loyal Customer,10,Personal Travel,Eco,1164,4,1,4,3,2,4,2,2,3,5,2,2,4,2,34,11.0,neutral or dissatisfied +71668,2046,Male,Loyal Customer,37,Business travel,Business,3225,2,2,1,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +71669,37745,Male,Loyal Customer,30,Business travel,Eco Plus,1005,5,5,5,5,5,5,5,5,2,4,4,5,3,5,0,0.0,satisfied +71670,64200,Female,Loyal Customer,33,Business travel,Business,853,1,2,2,2,3,2,2,1,1,1,1,4,1,3,55,51.0,neutral or dissatisfied +71671,9477,Male,Loyal Customer,30,Business travel,Business,2629,0,0,0,3,1,1,1,1,5,4,4,4,4,1,0,0.0,satisfied +71672,41265,Male,Loyal Customer,46,Business travel,Business,1075,4,4,3,4,3,3,3,4,4,4,4,2,4,3,0,13.0,satisfied +71673,27781,Male,Loyal Customer,48,Business travel,Business,1448,5,5,5,5,3,5,2,4,4,4,4,2,4,5,0,14.0,satisfied +71674,32672,Female,Loyal Customer,52,Business travel,Eco,163,1,3,3,3,4,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +71675,29226,Male,Loyal Customer,12,Personal Travel,Business,873,3,0,3,1,1,3,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +71676,91280,Male,Loyal Customer,57,Business travel,Business,1600,3,3,3,3,2,4,5,5,5,5,5,4,5,4,40,30.0,satisfied +71677,37500,Female,Loyal Customer,40,Business travel,Business,2868,2,2,2,2,5,4,4,2,2,2,2,4,2,2,4,4.0,neutral or dissatisfied +71678,61217,Female,disloyal Customer,39,Business travel,Business,967,3,3,3,4,5,3,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +71679,52179,Female,Loyal Customer,39,Business travel,Eco,451,2,5,5,5,2,2,2,2,4,2,2,5,4,2,5,1.0,satisfied +71680,75775,Female,Loyal Customer,31,Personal Travel,Eco,868,2,4,2,3,1,2,1,1,2,5,3,4,4,1,0,4.0,neutral or dissatisfied +71681,97900,Female,Loyal Customer,41,Business travel,Business,616,3,3,3,3,3,5,4,4,4,4,4,4,4,5,115,113.0,satisfied +71682,83318,Male,Loyal Customer,60,Business travel,Business,2741,2,2,2,2,2,4,5,5,5,5,3,1,5,3,0,0.0,satisfied +71683,14594,Female,Loyal Customer,41,Personal Travel,Eco,986,2,4,2,2,4,2,4,4,3,5,5,5,5,4,7,4.0,neutral or dissatisfied +71684,97542,Male,disloyal Customer,27,Business travel,Eco,675,3,3,3,3,3,3,3,4,5,4,4,3,2,3,157,147.0,neutral or dissatisfied +71685,43137,Female,disloyal Customer,24,Business travel,Eco,391,3,3,3,2,4,3,1,4,2,5,5,1,4,4,0,0.0,neutral or dissatisfied +71686,1020,Female,disloyal Customer,39,Business travel,Eco,164,1,0,1,2,3,1,3,3,1,1,2,1,3,3,0,11.0,neutral or dissatisfied +71687,9720,Female,Loyal Customer,24,Personal Travel,Eco,199,2,4,2,3,5,2,5,5,4,4,4,3,4,5,11,1.0,neutral or dissatisfied +71688,23842,Female,Loyal Customer,25,Business travel,Eco Plus,705,3,4,4,4,3,2,1,3,4,1,3,1,3,3,0,12.0,neutral or dissatisfied +71689,85693,Female,Loyal Customer,46,Business travel,Business,1547,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +71690,44425,Female,Loyal Customer,49,Business travel,Business,542,5,5,5,5,2,5,2,5,5,5,5,4,5,5,6,34.0,satisfied +71691,36540,Male,Loyal Customer,33,Business travel,Business,1237,2,2,4,2,4,4,4,4,5,2,4,2,3,4,1,0.0,satisfied +71692,11494,Female,Loyal Customer,38,Personal Travel,Eco Plus,201,3,3,0,5,1,0,1,1,4,1,1,5,5,1,24,18.0,neutral or dissatisfied +71693,35752,Female,disloyal Customer,26,Business travel,Eco,1608,2,3,3,3,2,2,2,2,2,4,3,2,4,2,30,22.0,neutral or dissatisfied +71694,34169,Female,disloyal Customer,9,Business travel,Eco,1046,2,2,2,2,2,2,3,2,5,5,4,1,3,2,0,0.0,neutral or dissatisfied +71695,103056,Male,Loyal Customer,27,Business travel,Eco,687,1,3,3,3,1,1,1,1,2,3,4,1,3,1,69,65.0,neutral or dissatisfied +71696,5897,Female,disloyal Customer,21,Business travel,Eco,173,3,0,3,1,2,3,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +71697,1155,Male,Loyal Customer,53,Personal Travel,Eco,270,2,5,2,4,2,2,2,2,5,2,4,4,5,2,58,53.0,neutral or dissatisfied +71698,66337,Male,Loyal Customer,13,Personal Travel,Business,986,2,4,3,3,2,3,2,2,3,4,4,4,5,2,17,13.0,neutral or dissatisfied +71699,127470,Male,Loyal Customer,45,Business travel,Eco,1814,3,1,1,1,3,3,3,3,1,4,2,1,4,3,0,0.0,neutral or dissatisfied +71700,88748,Male,Loyal Customer,17,Personal Travel,Eco,240,3,5,3,1,1,3,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +71701,98038,Male,Loyal Customer,55,Business travel,Business,1797,4,4,4,4,5,4,4,3,3,4,3,5,3,5,87,60.0,satisfied +71702,30320,Male,Loyal Customer,32,Business travel,Business,391,5,5,5,5,2,2,2,2,3,3,4,1,1,2,44,30.0,satisfied +71703,29761,Female,Loyal Customer,56,Business travel,Business,3240,2,2,2,2,5,4,5,4,4,4,5,4,4,4,100,119.0,satisfied +71704,31393,Female,Loyal Customer,25,Business travel,Business,2518,1,1,1,1,4,5,4,4,3,3,5,5,4,4,0,0.0,satisfied +71705,61605,Male,Loyal Customer,41,Business travel,Business,1635,1,1,1,1,3,3,4,4,4,4,4,5,4,5,1,0.0,satisfied +71706,76868,Male,Loyal Customer,44,Business travel,Business,1927,2,2,2,2,2,3,4,2,2,2,2,5,2,4,4,0.0,satisfied +71707,36086,Male,Loyal Customer,28,Personal Travel,Eco,399,4,2,4,4,1,4,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +71708,109495,Male,Loyal Customer,49,Business travel,Business,2754,3,3,5,3,3,4,4,5,5,5,5,5,5,3,11,0.0,satisfied +71709,15010,Female,disloyal Customer,15,Business travel,Eco,557,3,5,3,2,1,3,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +71710,15341,Female,Loyal Customer,54,Business travel,Business,3087,3,3,3,3,3,4,5,4,4,4,5,5,4,4,0,0.0,satisfied +71711,47872,Female,Loyal Customer,48,Business travel,Eco,329,2,5,3,5,4,3,3,2,2,2,2,4,2,3,84,71.0,neutral or dissatisfied +71712,32833,Female,Loyal Customer,34,Personal Travel,Eco,101,4,5,4,3,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +71713,19744,Female,Loyal Customer,34,Personal Travel,Eco Plus,475,2,5,2,4,5,2,5,5,5,1,2,1,5,5,7,6.0,neutral or dissatisfied +71714,44876,Male,Loyal Customer,41,Personal Travel,Eco,315,4,4,4,3,4,5,5,2,5,4,4,5,2,5,135,136.0,satisfied +71715,53310,Male,Loyal Customer,47,Personal Travel,Eco,758,3,3,3,4,4,3,4,4,4,5,4,2,1,4,0,0.0,neutral or dissatisfied +71716,3351,Male,Loyal Customer,36,Business travel,Business,315,3,3,3,3,5,5,4,5,5,5,5,3,5,4,3,13.0,satisfied +71717,98328,Female,Loyal Customer,70,Personal Travel,Business,1189,3,4,3,3,4,5,4,3,3,3,5,4,3,3,4,3.0,neutral or dissatisfied +71718,57008,Female,Loyal Customer,9,Personal Travel,Eco,2565,3,4,3,3,3,3,5,4,5,4,1,5,5,5,0,0.0,neutral or dissatisfied +71719,79429,Male,Loyal Customer,39,Personal Travel,Eco,502,3,1,3,4,4,3,4,4,3,1,4,1,3,4,1,46.0,neutral or dissatisfied +71720,42229,Female,Loyal Customer,46,Business travel,Business,329,3,1,1,1,3,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +71721,95881,Male,disloyal Customer,19,Business travel,Eco,759,4,4,4,3,2,4,2,2,4,2,4,1,3,2,54,43.0,neutral or dissatisfied +71722,71185,Male,Loyal Customer,59,Business travel,Business,1531,3,3,3,3,3,5,4,5,5,5,5,4,5,4,22,17.0,satisfied +71723,86465,Female,Loyal Customer,46,Business travel,Eco,362,5,3,5,5,4,1,3,5,5,5,5,2,5,2,0,0.0,satisfied +71724,107394,Male,Loyal Customer,37,Business travel,Business,468,1,1,1,1,4,4,5,4,4,4,4,5,4,5,7,0.0,satisfied +71725,98588,Female,disloyal Customer,20,Business travel,Business,834,4,0,3,4,5,3,4,5,3,4,5,5,4,5,98,100.0,satisfied +71726,22245,Female,Loyal Customer,36,Business travel,Business,208,4,4,4,4,4,1,5,5,5,4,4,4,5,3,0,13.0,satisfied +71727,43736,Male,Loyal Customer,34,Business travel,Business,622,2,2,5,2,3,4,5,5,5,5,5,5,5,4,36,41.0,satisfied +71728,17584,Female,Loyal Customer,29,Personal Travel,Eco,1034,3,5,3,1,2,3,2,2,4,3,4,3,5,2,23,7.0,neutral or dissatisfied +71729,71721,Male,Loyal Customer,25,Business travel,Business,2577,2,3,3,3,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +71730,105772,Female,disloyal Customer,36,Business travel,Eco,525,4,0,4,3,1,4,1,1,4,4,1,1,2,1,16,0.0,neutral or dissatisfied +71731,122389,Female,Loyal Customer,38,Personal Travel,Eco,529,3,4,3,4,5,3,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +71732,90557,Female,disloyal Customer,38,Business travel,Business,240,4,4,4,3,4,4,4,4,3,2,4,3,5,4,0,0.0,satisfied +71733,51323,Female,disloyal Customer,36,Business travel,Eco Plus,308,2,1,1,4,1,1,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +71734,70403,Male,Loyal Customer,70,Personal Travel,Eco,1562,1,1,1,3,3,1,3,3,1,2,2,4,4,3,0,0.0,neutral or dissatisfied +71735,87546,Female,Loyal Customer,26,Personal Travel,Eco,782,5,5,4,3,2,4,2,2,3,5,5,3,4,2,1,0.0,satisfied +71736,105085,Female,Loyal Customer,43,Business travel,Business,220,1,1,1,1,2,4,4,5,5,5,4,5,5,5,10,0.0,satisfied +71737,54514,Female,disloyal Customer,24,Business travel,Eco,925,2,2,2,1,5,2,3,5,2,5,5,4,2,5,15,10.0,neutral or dissatisfied +71738,97991,Female,Loyal Customer,55,Business travel,Business,612,1,1,1,1,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +71739,44772,Male,Loyal Customer,29,Business travel,Eco,1250,5,1,1,1,5,5,5,5,5,1,4,1,2,5,72,89.0,satisfied +71740,62933,Female,Loyal Customer,49,Business travel,Business,853,4,4,4,4,5,4,5,5,5,5,5,4,5,5,11,2.0,satisfied +71741,97212,Male,Loyal Customer,43,Business travel,Business,1390,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,6.0,satisfied +71742,49280,Male,disloyal Customer,23,Business travel,Eco,89,5,0,5,4,3,5,4,3,1,2,5,5,5,3,77,64.0,satisfied +71743,108539,Male,Loyal Customer,33,Business travel,Business,1831,2,2,2,2,4,4,4,4,3,3,5,3,5,4,0,1.0,satisfied +71744,104127,Female,Loyal Customer,53,Business travel,Business,2561,5,5,5,5,4,5,5,5,5,5,5,5,5,4,4,3.0,satisfied +71745,6358,Female,Loyal Customer,46,Business travel,Business,315,0,0,0,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +71746,60784,Male,Loyal Customer,29,Business travel,Business,1794,4,4,2,4,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +71747,46683,Male,Loyal Customer,33,Personal Travel,Eco,125,2,1,2,2,2,2,2,2,4,3,2,2,2,2,6,0.0,neutral or dissatisfied +71748,101793,Female,disloyal Customer,27,Business travel,Business,1521,3,3,3,1,3,3,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +71749,91376,Female,Loyal Customer,52,Business travel,Business,3977,4,4,4,4,5,4,4,5,5,5,5,3,5,5,9,14.0,satisfied +71750,84318,Male,Loyal Customer,53,Business travel,Business,3868,2,2,2,2,4,5,5,3,3,4,3,4,3,3,15,6.0,satisfied +71751,42331,Male,Loyal Customer,66,Personal Travel,Eco,451,2,4,5,4,1,5,1,1,3,3,4,4,4,1,3,0.0,neutral or dissatisfied +71752,58176,Male,Loyal Customer,36,Business travel,Business,3930,1,5,5,5,4,3,4,1,1,1,1,1,1,1,93,72.0,neutral or dissatisfied +71753,49802,Male,disloyal Customer,30,Business travel,Eco,158,3,1,3,4,1,3,1,1,3,2,4,1,4,1,0,9.0,neutral or dissatisfied +71754,83453,Male,disloyal Customer,52,Business travel,Business,946,2,2,2,4,2,2,2,2,4,5,4,3,4,2,5,0.0,neutral or dissatisfied +71755,96345,Female,disloyal Customer,31,Business travel,Business,1609,1,1,1,5,5,1,5,5,3,4,3,3,5,5,21,0.0,neutral or dissatisfied +71756,87642,Male,Loyal Customer,56,Business travel,Business,2404,4,4,4,4,3,5,5,5,5,5,5,5,5,5,18,4.0,satisfied +71757,123259,Male,Loyal Customer,51,Personal Travel,Eco,468,3,3,5,4,2,5,2,2,5,2,4,4,1,2,0,0.0,neutral or dissatisfied +71758,57479,Male,Loyal Customer,7,Personal Travel,Eco,680,3,5,4,1,4,4,4,4,1,5,4,4,4,4,135,114.0,neutral or dissatisfied +71759,88309,Male,disloyal Customer,28,Business travel,Eco,594,2,4,2,4,1,2,1,1,4,1,4,3,3,1,9,9.0,neutral or dissatisfied +71760,70807,Female,Loyal Customer,44,Business travel,Business,2454,4,4,4,4,2,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +71761,14601,Male,Loyal Customer,70,Personal Travel,Eco,1021,1,3,1,4,2,1,2,2,1,5,4,3,4,2,1,32.0,neutral or dissatisfied +71762,37935,Male,Loyal Customer,13,Personal Travel,Eco,1065,4,1,4,4,5,4,5,5,4,5,4,3,4,5,0,3.0,satisfied +71763,102036,Female,Loyal Customer,57,Business travel,Business,226,1,1,2,1,5,5,4,5,5,4,5,5,5,5,45,40.0,satisfied +71764,80442,Male,Loyal Customer,30,Personal Travel,Eco,2248,2,5,3,2,3,3,5,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +71765,52962,Female,disloyal Customer,66,Business travel,Eco,1351,3,3,3,3,4,3,4,4,2,4,1,3,3,4,0,0.0,neutral or dissatisfied +71766,5659,Female,Loyal Customer,50,Business travel,Business,2215,2,2,2,2,3,4,4,5,5,5,5,3,5,3,25,12.0,satisfied +71767,2442,Female,Loyal Customer,42,Personal Travel,Eco,604,1,5,1,2,5,4,4,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +71768,16002,Male,Loyal Customer,41,Business travel,Eco,853,4,1,1,1,4,4,4,4,3,4,4,2,4,4,0,3.0,neutral or dissatisfied +71769,82285,Male,Loyal Customer,39,Personal Travel,Eco,1481,3,5,3,3,3,3,3,3,5,3,4,1,3,3,1,0.0,neutral or dissatisfied +71770,82761,Female,Loyal Customer,58,Personal Travel,Eco,409,3,2,2,3,3,4,4,2,2,2,2,1,2,3,0,2.0,neutral or dissatisfied +71771,103134,Female,Loyal Customer,51,Business travel,Business,666,2,2,2,2,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +71772,37179,Female,Loyal Customer,46,Personal Travel,Eco,1189,4,5,4,3,4,4,4,1,1,4,1,5,1,3,6,15.0,neutral or dissatisfied +71773,120997,Female,Loyal Customer,37,Business travel,Business,1563,1,1,1,1,1,3,4,5,5,5,5,1,5,2,0,35.0,satisfied +71774,71039,Male,disloyal Customer,26,Business travel,Eco,802,2,2,2,3,1,2,1,1,4,4,3,4,3,1,18,16.0,neutral or dissatisfied +71775,10936,Female,Loyal Customer,35,Business travel,Eco,482,1,3,3,3,1,1,1,1,3,5,3,3,3,1,0,0.0,neutral or dissatisfied +71776,118214,Male,Loyal Customer,54,Business travel,Business,1444,1,1,1,1,2,5,5,5,5,5,5,5,5,5,11,21.0,satisfied +71777,19163,Male,Loyal Customer,34,Business travel,Business,1703,2,2,2,2,3,3,3,2,2,2,2,2,2,2,0,2.0,neutral or dissatisfied +71778,28669,Male,disloyal Customer,36,Business travel,Eco Plus,2417,3,3,3,4,2,3,2,2,3,1,3,1,1,2,0,4.0,neutral or dissatisfied +71779,45875,Male,disloyal Customer,25,Business travel,Eco,563,2,3,3,5,3,3,3,3,4,1,5,2,1,3,55,52.0,neutral or dissatisfied +71780,105172,Male,Loyal Customer,23,Personal Travel,Eco,289,1,2,1,4,2,1,2,2,3,4,4,2,4,2,45,43.0,neutral or dissatisfied +71781,77073,Male,Loyal Customer,41,Business travel,Eco,991,3,1,1,1,4,3,4,4,4,5,4,3,4,4,11,8.0,neutral or dissatisfied +71782,51282,Male,disloyal Customer,22,Business travel,Eco,250,4,4,4,5,2,4,2,2,4,2,4,4,2,2,0,0.0,neutral or dissatisfied +71783,31770,Female,disloyal Customer,55,Business travel,Eco,202,2,1,1,1,1,1,3,1,2,2,1,3,2,1,0,3.0,neutral or dissatisfied +71784,11268,Female,Loyal Customer,13,Personal Travel,Eco,312,2,5,2,5,5,2,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +71785,29027,Female,Loyal Customer,59,Business travel,Business,279,3,1,1,1,3,2,2,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +71786,67130,Female,Loyal Customer,31,Business travel,Business,3950,3,3,4,4,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +71787,91411,Male,disloyal Customer,49,Business travel,Business,1050,3,2,2,3,4,3,4,4,5,4,4,5,5,4,9,11.0,neutral or dissatisfied +71788,53685,Male,Loyal Customer,25,Business travel,Eco,1190,4,4,4,4,4,4,4,4,5,1,1,3,2,4,0,0.0,satisfied +71789,96045,Female,disloyal Customer,12,Business travel,Business,1069,4,0,4,3,1,4,1,1,5,3,4,4,5,1,0,0.0,satisfied +71790,32612,Female,Loyal Customer,64,Business travel,Business,1932,2,3,3,3,1,3,2,3,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +71791,10927,Female,disloyal Customer,20,Business travel,Eco,191,3,2,3,3,1,3,1,1,3,3,3,1,4,1,3,0.0,neutral or dissatisfied +71792,88283,Female,disloyal Customer,62,Business travel,Business,271,3,3,3,3,2,3,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +71793,55571,Male,disloyal Customer,14,Business travel,Eco,1091,3,3,3,3,2,3,2,2,1,1,4,1,4,2,3,6.0,neutral or dissatisfied +71794,58817,Female,Loyal Customer,70,Personal Travel,Eco,1005,1,4,0,4,2,5,4,3,3,0,3,5,3,3,0,0.0,neutral or dissatisfied +71795,10092,Female,Loyal Customer,24,Business travel,Business,1759,1,1,1,1,4,4,4,4,4,3,4,4,5,4,16,24.0,satisfied +71796,52162,Female,disloyal Customer,42,Business travel,Eco,370,3,3,3,2,2,3,2,2,2,3,3,3,3,2,17,13.0,neutral or dissatisfied +71797,34415,Female,Loyal Customer,55,Personal Travel,Eco,612,2,3,2,3,2,2,2,3,1,2,2,2,3,2,235,230.0,neutral or dissatisfied +71798,95602,Female,Loyal Customer,57,Business travel,Eco,822,3,4,1,4,5,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +71799,125477,Male,Loyal Customer,63,Personal Travel,Eco,2860,3,4,3,2,3,3,3,3,4,3,5,1,4,3,0,0.0,neutral or dissatisfied +71800,2246,Female,disloyal Customer,29,Business travel,Business,672,2,2,2,1,4,2,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +71801,5947,Male,Loyal Customer,31,Business travel,Business,3636,1,4,4,4,1,2,1,1,4,1,3,1,4,1,6,7.0,neutral or dissatisfied +71802,123994,Male,Loyal Customer,48,Business travel,Business,3760,5,5,5,5,5,5,5,5,5,5,4,3,5,4,0,4.0,satisfied +71803,96579,Male,Loyal Customer,35,Personal Travel,Eco,333,1,4,1,4,2,1,2,2,3,4,4,3,4,2,9,0.0,neutral or dissatisfied +71804,59551,Female,Loyal Customer,44,Business travel,Business,3571,4,4,4,4,3,5,4,5,5,5,5,5,5,5,10,0.0,satisfied +71805,189,Female,Loyal Customer,42,Business travel,Business,2888,0,0,0,2,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +71806,19417,Male,disloyal Customer,24,Business travel,Eco,645,2,0,2,4,5,2,5,5,1,5,4,4,2,5,99,110.0,neutral or dissatisfied +71807,55858,Male,Loyal Customer,29,Personal Travel,Eco Plus,1416,4,5,4,3,1,4,1,1,5,3,3,3,5,1,0,0.0,neutral or dissatisfied +71808,38764,Male,Loyal Customer,36,Business travel,Business,3236,4,4,4,4,2,2,2,4,4,4,4,2,4,2,23,21.0,satisfied +71809,109162,Female,Loyal Customer,42,Business travel,Business,722,2,2,2,2,2,5,5,4,4,4,4,4,4,4,0,10.0,satisfied +71810,40193,Male,Loyal Customer,41,Business travel,Business,1786,4,1,4,4,5,2,2,4,4,4,4,2,4,4,0,0.0,satisfied +71811,119026,Female,disloyal Customer,20,Business travel,Eco,1060,2,2,2,4,5,2,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +71812,46556,Female,disloyal Customer,40,Business travel,Business,125,2,2,2,4,1,2,1,1,2,2,3,1,4,1,17,16.0,neutral or dissatisfied +71813,96415,Female,Loyal Customer,16,Personal Travel,Eco,1407,4,2,4,3,3,4,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +71814,115553,Female,disloyal Customer,37,Business travel,Eco,325,2,3,2,2,2,2,2,2,3,3,2,2,2,2,17,12.0,neutral or dissatisfied +71815,50251,Male,disloyal Customer,30,Business travel,Eco,89,3,4,3,3,2,3,2,2,1,3,3,1,4,2,0,0.0,neutral or dissatisfied +71816,82522,Female,Loyal Customer,53,Business travel,Business,1948,1,5,5,5,3,3,4,1,1,1,1,1,1,2,27,21.0,neutral or dissatisfied +71817,123498,Female,disloyal Customer,26,Business travel,Eco,2125,2,2,2,3,3,2,4,3,2,5,3,2,3,3,125,125.0,neutral or dissatisfied +71818,44744,Female,disloyal Customer,51,Business travel,Eco,589,2,0,2,1,5,2,5,5,3,5,2,5,5,5,13,9.0,neutral or dissatisfied +71819,68534,Male,disloyal Customer,25,Business travel,Eco,1013,2,2,2,4,4,2,4,4,1,2,4,3,4,4,35,5.0,neutral or dissatisfied +71820,40960,Male,Loyal Customer,51,Business travel,Business,3314,3,3,3,3,2,2,3,5,5,5,5,2,5,5,0,0.0,satisfied +71821,88169,Male,Loyal Customer,42,Business travel,Business,545,4,3,4,4,2,4,4,4,4,4,4,3,4,3,27,37.0,satisfied +71822,94502,Male,disloyal Customer,40,Business travel,Business,189,4,4,4,1,5,4,5,5,3,5,4,5,5,5,4,13.0,neutral or dissatisfied +71823,99312,Male,Loyal Customer,35,Business travel,Business,3659,1,4,3,4,4,3,3,1,1,1,1,3,1,4,46,32.0,neutral or dissatisfied +71824,13930,Female,Loyal Customer,54,Business travel,Eco,192,5,4,4,4,2,5,2,5,5,5,5,3,5,2,0,0.0,satisfied +71825,53325,Female,Loyal Customer,19,Personal Travel,Eco,758,3,4,3,3,1,3,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +71826,105534,Male,Loyal Customer,52,Business travel,Eco,611,1,5,5,5,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +71827,126108,Male,Loyal Customer,34,Business travel,Business,507,1,1,1,1,5,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +71828,63172,Male,Loyal Customer,61,Business travel,Business,3882,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +71829,113706,Male,Loyal Customer,69,Personal Travel,Eco,236,4,1,4,4,5,4,5,5,3,1,4,4,4,5,63,63.0,neutral or dissatisfied +71830,38530,Male,Loyal Customer,26,Business travel,Business,2465,4,4,4,4,4,4,4,4,1,5,3,2,2,4,0,0.0,satisfied +71831,59451,Male,Loyal Customer,58,Business travel,Business,2553,2,2,2,2,2,4,4,5,5,5,5,3,5,4,9,3.0,satisfied +71832,16519,Female,disloyal Customer,26,Business travel,Eco Plus,143,3,5,3,4,4,3,4,4,3,4,5,1,4,4,0,0.0,neutral or dissatisfied +71833,67932,Female,Loyal Customer,19,Personal Travel,Eco,1171,3,5,3,3,4,3,4,4,4,1,4,5,1,4,0,0.0,neutral or dissatisfied +71834,20244,Female,disloyal Customer,50,Business travel,Eco,179,2,1,2,4,5,2,5,5,1,1,4,4,3,5,24,17.0,neutral or dissatisfied +71835,50874,Male,Loyal Customer,14,Personal Travel,Eco,109,2,4,2,4,2,2,2,2,5,2,3,5,4,2,0,0.0,neutral or dissatisfied +71836,41029,Male,Loyal Customer,59,Business travel,Eco,1195,4,3,3,3,4,4,4,4,1,2,2,1,1,4,61,47.0,satisfied +71837,87493,Female,Loyal Customer,37,Business travel,Eco,373,1,5,3,5,1,1,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +71838,121414,Male,Loyal Customer,44,Business travel,Business,1621,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +71839,9008,Female,Loyal Customer,58,Business travel,Business,3715,3,3,3,3,3,5,4,5,5,5,5,4,5,4,24,26.0,satisfied +71840,17150,Male,Loyal Customer,68,Personal Travel,Eco,926,3,5,3,1,1,3,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +71841,84058,Male,disloyal Customer,26,Business travel,Business,757,3,3,3,1,1,3,1,1,4,5,5,3,4,1,8,0.0,neutral or dissatisfied +71842,125753,Male,Loyal Customer,32,Business travel,Business,920,4,4,4,4,2,2,2,2,3,4,5,3,4,2,0,0.0,satisfied +71843,114054,Male,disloyal Customer,28,Business travel,Business,1486,4,4,4,4,4,4,4,4,4,3,4,5,5,4,2,0.0,satisfied +71844,81438,Male,Loyal Customer,57,Business travel,Business,2238,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +71845,36420,Female,Loyal Customer,37,Business travel,Business,3443,2,4,4,4,2,2,2,3,2,4,3,2,4,2,136,144.0,neutral or dissatisfied +71846,88636,Female,Loyal Customer,33,Personal Travel,Eco,406,2,4,2,4,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +71847,113189,Male,disloyal Customer,44,Business travel,Business,391,2,1,1,5,4,2,4,4,4,3,5,5,4,4,1,0.0,neutral or dissatisfied +71848,27900,Female,Loyal Customer,32,Business travel,Business,2350,1,1,1,1,4,4,4,1,4,4,1,4,3,4,0,5.0,satisfied +71849,109158,Male,disloyal Customer,37,Business travel,Business,391,3,3,3,2,3,3,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +71850,45296,Male,Loyal Customer,38,Business travel,Business,1620,3,3,3,3,1,1,5,4,4,4,4,3,4,3,0,0.0,satisfied +71851,114976,Female,Loyal Customer,52,Business travel,Business,446,3,3,3,3,3,5,4,4,4,4,4,3,4,4,29,16.0,satisfied +71852,40238,Male,Loyal Customer,33,Business travel,Business,358,2,2,2,2,3,3,3,3,1,5,5,3,5,3,0,1.0,satisfied +71853,21116,Female,Loyal Customer,7,Personal Travel,Eco,106,2,4,2,3,3,2,3,3,1,3,1,4,1,3,25,35.0,neutral or dissatisfied +71854,82840,Female,Loyal Customer,34,Business travel,Business,594,1,1,1,1,2,5,4,5,5,5,5,4,5,4,3,0.0,satisfied +71855,64215,Female,Loyal Customer,50,Business travel,Business,1660,4,2,1,2,2,3,4,4,4,4,4,3,4,1,0,13.0,neutral or dissatisfied +71856,19015,Female,Loyal Customer,24,Business travel,Eco,871,4,4,4,4,4,4,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +71857,63963,Male,Loyal Customer,53,Personal Travel,Eco,1158,1,1,2,2,4,2,4,4,1,5,1,2,1,4,0,0.0,neutral or dissatisfied +71858,78303,Female,Loyal Customer,30,Personal Travel,Eco,1598,0,5,0,3,3,0,3,3,4,3,4,3,5,3,16,0.0,satisfied +71859,14148,Female,Loyal Customer,14,Personal Travel,Eco,528,2,4,2,1,2,2,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +71860,116646,Female,disloyal Customer,37,Business travel,Eco Plus,372,2,2,2,4,5,2,5,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +71861,80596,Male,Loyal Customer,46,Business travel,Business,1747,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +71862,28218,Female,Loyal Customer,28,Business travel,Eco Plus,933,0,0,0,2,4,0,1,4,4,3,3,2,1,4,0,0.0,satisfied +71863,60865,Female,Loyal Customer,58,Business travel,Business,1491,3,2,2,2,3,3,4,3,3,3,3,3,3,3,0,3.0,neutral or dissatisfied +71864,126827,Male,Loyal Customer,31,Business travel,Business,2296,5,5,5,5,5,5,5,5,4,4,4,3,5,5,30,23.0,satisfied +71865,54178,Male,Loyal Customer,58,Business travel,Business,2678,4,3,3,3,4,1,1,4,4,4,4,4,4,3,50,20.0,neutral or dissatisfied +71866,2349,Female,Loyal Customer,50,Personal Travel,Eco Plus,672,1,5,1,1,4,4,4,4,4,1,5,3,4,5,0,0.0,neutral or dissatisfied +71867,41314,Female,disloyal Customer,26,Business travel,Eco,802,3,3,3,4,4,3,2,4,4,1,4,4,4,4,0,25.0,neutral or dissatisfied +71868,60057,Female,Loyal Customer,60,Personal Travel,Eco Plus,997,3,5,3,4,4,5,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +71869,88663,Male,Loyal Customer,39,Personal Travel,Eco,270,1,0,1,1,1,1,4,1,4,3,4,5,5,1,12,0.0,neutral or dissatisfied +71870,87266,Female,disloyal Customer,26,Business travel,Business,577,2,2,2,4,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +71871,126789,Male,Loyal Customer,53,Business travel,Business,2125,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +71872,27427,Female,disloyal Customer,39,Business travel,Business,937,2,2,2,4,4,2,4,4,3,5,3,2,4,4,0,0.0,neutral or dissatisfied +71873,126792,Female,Loyal Customer,45,Business travel,Business,2296,4,4,4,4,2,5,4,3,3,4,3,5,3,5,74,74.0,satisfied +71874,120254,Male,Loyal Customer,18,Personal Travel,Eco Plus,1303,4,2,4,3,3,4,3,3,1,3,3,3,3,3,0,0.0,satisfied +71875,11323,Female,Loyal Customer,13,Personal Travel,Eco,247,4,4,4,1,5,4,5,5,3,3,5,4,5,5,0,0.0,neutral or dissatisfied +71876,16667,Female,Loyal Customer,64,Personal Travel,Eco,605,3,3,3,4,1,4,3,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +71877,117195,Male,Loyal Customer,9,Personal Travel,Eco,651,1,1,1,3,1,1,1,1,4,5,2,4,2,1,80,78.0,neutral or dissatisfied +71878,67073,Male,disloyal Customer,24,Business travel,Eco,985,2,2,2,4,3,2,3,3,5,3,4,3,4,3,7,1.0,satisfied +71879,110652,Female,disloyal Customer,26,Business travel,Eco,945,2,2,2,3,5,2,5,5,1,2,3,2,3,5,29,24.0,neutral or dissatisfied +71880,90322,Female,Loyal Customer,46,Business travel,Business,545,2,2,2,2,4,4,4,5,3,4,4,4,3,4,347,359.0,satisfied +71881,56181,Female,Loyal Customer,62,Personal Travel,Eco,1400,3,4,4,2,5,5,4,1,1,4,1,3,1,4,5,2.0,neutral or dissatisfied +71882,110423,Female,disloyal Customer,22,Business travel,Eco,442,3,4,2,1,4,2,5,4,4,2,5,1,4,4,27,6.0,neutral or dissatisfied +71883,50649,Female,Loyal Customer,21,Personal Travel,Eco,153,4,5,4,2,2,4,4,2,3,1,2,1,3,2,4,5.0,neutral or dissatisfied +71884,72110,Male,Loyal Customer,58,Business travel,Business,2772,4,4,4,4,2,4,4,4,4,4,4,1,4,2,0,4.0,neutral or dissatisfied +71885,68353,Female,disloyal Customer,25,Business travel,Business,1598,1,4,1,3,4,1,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +71886,67926,Female,Loyal Customer,43,Personal Travel,Eco,1431,3,5,3,1,2,5,4,2,2,3,2,4,2,5,20,17.0,neutral or dissatisfied +71887,34995,Male,Loyal Customer,36,Business travel,Business,2253,3,3,1,3,2,4,2,5,5,5,5,3,5,2,0,0.0,satisfied +71888,108809,Male,Loyal Customer,36,Business travel,Business,545,2,2,2,2,4,4,4,5,5,5,5,4,5,3,17,6.0,satisfied +71889,25435,Male,disloyal Customer,32,Business travel,Eco,669,3,3,3,3,5,3,5,5,3,3,5,5,1,5,0,0.0,neutral or dissatisfied +71890,97699,Male,Loyal Customer,34,Business travel,Business,2667,2,2,3,3,2,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +71891,64350,Female,Loyal Customer,31,Business travel,Eco,1212,3,3,3,3,3,3,3,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +71892,111674,Female,Loyal Customer,41,Personal Travel,Eco,991,3,4,3,4,2,3,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +71893,129117,Female,Loyal Customer,61,Personal Travel,Eco Plus,2583,1,1,1,3,1,4,4,3,1,4,3,4,1,4,0,0.0,neutral or dissatisfied +71894,80744,Female,Loyal Customer,10,Personal Travel,Eco,448,2,2,2,3,3,2,1,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +71895,51717,Female,Loyal Customer,34,Personal Travel,Eco,237,4,5,4,2,1,4,1,1,3,4,4,5,4,1,0,0.0,satisfied +71896,91807,Male,Loyal Customer,41,Personal Travel,Eco,626,2,4,2,3,5,2,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +71897,109269,Female,Loyal Customer,43,Personal Travel,Eco Plus,616,2,5,2,2,1,3,2,5,5,2,5,2,5,3,12,10.0,neutral or dissatisfied +71898,57154,Female,Loyal Customer,49,Business travel,Business,1824,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +71899,67020,Female,disloyal Customer,24,Business travel,Eco,985,3,3,3,2,4,3,4,4,1,5,2,4,2,4,0,0.0,neutral or dissatisfied +71900,95945,Female,Loyal Customer,41,Business travel,Business,3709,4,4,4,4,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +71901,19612,Female,disloyal Customer,23,Business travel,Eco,416,3,0,3,2,1,3,1,1,3,3,3,4,1,1,0,0.0,neutral or dissatisfied +71902,100234,Male,Loyal Customer,53,Business travel,Business,971,2,2,2,2,2,2,2,2,2,2,2,2,2,3,0,17.0,neutral or dissatisfied +71903,58755,Female,Loyal Customer,28,Business travel,Business,2472,3,5,5,5,3,3,3,4,5,3,3,3,4,3,444,434.0,neutral or dissatisfied +71904,124434,Female,Loyal Customer,69,Personal Travel,Eco,1044,2,3,2,2,1,2,5,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +71905,115849,Female,disloyal Customer,20,Business travel,Eco,337,0,0,0,2,2,0,2,2,4,4,4,2,4,2,0,0.0,satisfied +71906,31339,Male,Loyal Customer,47,Personal Travel,Eco,1062,3,1,3,3,4,3,4,4,4,5,3,1,3,4,7,0.0,neutral or dissatisfied +71907,32026,Female,disloyal Customer,56,Business travel,Eco,163,1,4,1,2,5,1,5,5,1,4,1,2,2,5,0,0.0,neutral or dissatisfied +71908,71891,Male,Loyal Customer,22,Personal Travel,Eco,1723,4,4,4,4,4,4,4,4,4,5,3,3,5,4,13,16.0,neutral or dissatisfied +71909,33386,Male,Loyal Customer,54,Business travel,Eco Plus,2556,1,1,1,1,1,1,1,2,1,4,3,1,4,1,146,116.0,neutral or dissatisfied +71910,116952,Male,disloyal Customer,62,Business travel,Business,338,1,1,1,2,2,1,5,2,3,2,5,4,5,2,8,0.0,neutral or dissatisfied +71911,108490,Female,disloyal Customer,37,Business travel,Eco,170,2,5,2,3,4,2,4,4,4,1,1,4,1,4,1,0.0,neutral or dissatisfied +71912,83991,Male,Loyal Customer,32,Business travel,Business,321,3,5,5,5,3,3,3,3,1,2,4,2,4,3,0,12.0,neutral or dissatisfied +71913,64312,Male,Loyal Customer,42,Business travel,Business,2064,4,4,4,4,5,5,5,4,4,4,4,3,4,5,33,19.0,satisfied +71914,40250,Male,Loyal Customer,37,Business travel,Eco,387,2,1,1,1,2,2,2,2,1,4,2,2,3,2,0,0.0,neutral or dissatisfied +71915,97854,Male,Loyal Customer,39,Business travel,Business,616,1,0,0,1,4,1,2,2,2,0,2,2,2,2,0,0.0,neutral or dissatisfied +71916,243,Male,disloyal Customer,22,Business travel,Eco,719,1,1,1,3,1,1,1,1,4,3,3,1,4,1,14,25.0,neutral or dissatisfied +71917,101446,Male,Loyal Customer,42,Business travel,Business,3287,1,1,1,1,3,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +71918,121930,Female,disloyal Customer,20,Business travel,Business,366,5,4,5,1,2,5,2,2,5,3,4,5,5,2,0,0.0,satisfied +71919,93537,Male,Loyal Customer,46,Personal Travel,Eco,1315,2,5,2,4,2,2,2,2,4,4,5,5,4,2,15,0.0,neutral or dissatisfied +71920,123257,Female,Loyal Customer,32,Personal Travel,Eco,590,3,5,3,2,2,3,4,2,5,4,5,3,5,2,4,0.0,neutral or dissatisfied +71921,19141,Female,Loyal Customer,63,Personal Travel,Eco Plus,265,2,5,2,3,5,4,4,4,4,2,4,3,4,3,0,1.0,neutral or dissatisfied +71922,75511,Male,Loyal Customer,60,Personal Travel,Eco,2527,1,4,1,3,2,1,2,2,5,2,3,5,5,2,0,0.0,neutral or dissatisfied +71923,109464,Female,Loyal Customer,41,Business travel,Business,873,2,2,1,2,2,5,5,4,4,5,4,3,4,5,53,39.0,satisfied +71924,20896,Male,Loyal Customer,51,Personal Travel,Eco,961,1,5,1,5,5,1,3,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +71925,83163,Male,Loyal Customer,46,Business travel,Business,3787,2,2,3,2,4,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +71926,102775,Male,disloyal Customer,36,Business travel,Business,1099,3,3,3,2,2,3,2,2,4,3,4,4,4,2,3,9.0,neutral or dissatisfied +71927,22309,Male,Loyal Customer,34,Business travel,Eco,145,0,0,0,2,5,0,5,5,5,5,1,1,3,5,0,0.0,satisfied +71928,7826,Male,Loyal Customer,41,Personal Travel,Eco,650,2,3,2,3,4,2,4,4,2,3,5,5,5,4,0,0.0,neutral or dissatisfied +71929,113061,Male,Loyal Customer,39,Business travel,Business,1961,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +71930,12289,Female,Loyal Customer,39,Business travel,Business,1967,3,3,3,3,4,5,4,2,1,1,2,4,1,4,137,154.0,satisfied +71931,129710,Female,Loyal Customer,32,Business travel,Eco,308,4,4,4,4,4,4,4,4,4,4,4,2,3,4,18,14.0,neutral or dissatisfied +71932,45170,Male,Loyal Customer,69,Personal Travel,Eco,130,3,1,0,4,2,0,2,2,3,1,3,3,4,2,0,4.0,neutral or dissatisfied +71933,27787,Male,Loyal Customer,37,Business travel,Business,1448,3,2,2,2,5,3,4,3,3,3,3,1,3,1,26,0.0,neutral or dissatisfied +71934,1787,Male,disloyal Customer,22,Business travel,Eco,500,3,0,3,2,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +71935,98856,Male,Loyal Customer,50,Business travel,Business,1751,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +71936,13663,Female,Loyal Customer,28,Business travel,Business,3559,1,1,3,1,4,4,4,4,1,1,1,5,5,4,0,0.0,satisfied +71937,82190,Male,Loyal Customer,50,Business travel,Business,1927,3,5,2,5,1,3,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +71938,24865,Male,disloyal Customer,37,Business travel,Business,356,1,1,1,1,2,1,2,2,2,1,4,5,1,2,0,0.0,neutral or dissatisfied +71939,17081,Female,disloyal Customer,32,Business travel,Eco,416,2,0,2,3,2,2,3,2,5,1,1,1,3,2,0,0.0,neutral or dissatisfied +71940,87355,Female,Loyal Customer,47,Business travel,Business,3401,4,2,2,2,3,3,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +71941,22947,Male,Loyal Customer,26,Business travel,Business,817,5,5,5,5,3,3,3,3,4,3,2,3,5,3,2,3.0,satisfied +71942,14953,Male,Loyal Customer,9,Personal Travel,Eco,528,4,5,4,5,1,4,1,1,3,2,4,4,4,1,35,22.0,neutral or dissatisfied +71943,21336,Male,Loyal Customer,34,Business travel,Business,674,1,1,4,1,2,1,5,5,5,5,5,3,5,2,19,21.0,satisfied +71944,109339,Female,disloyal Customer,17,Business travel,Eco,1072,5,5,5,4,4,5,4,4,3,4,5,3,4,4,0,0.0,satisfied +71945,96880,Male,Loyal Customer,20,Personal Travel,Eco,994,1,5,1,5,1,1,1,1,4,4,5,4,5,1,11,3.0,neutral or dissatisfied +71946,79572,Female,Loyal Customer,9,Business travel,Eco,762,1,4,4,4,1,1,2,1,1,2,4,4,3,1,0,20.0,neutral or dissatisfied +71947,67976,Male,Loyal Customer,33,Business travel,Eco Plus,1464,4,1,1,1,4,4,4,4,3,2,4,1,4,4,27,31.0,neutral or dissatisfied +71948,4257,Male,Loyal Customer,14,Personal Travel,Business,502,2,5,2,3,4,2,2,4,4,3,5,3,5,4,17,21.0,neutral or dissatisfied +71949,11152,Male,Loyal Customer,36,Personal Travel,Eco,482,2,2,2,4,2,2,2,2,3,1,4,2,3,2,58,47.0,neutral or dissatisfied +71950,72333,Male,Loyal Customer,44,Business travel,Business,2795,3,3,3,3,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +71951,34583,Male,Loyal Customer,38,Business travel,Business,1617,2,2,2,2,5,4,4,2,2,2,2,1,2,1,0,0.0,satisfied +71952,119898,Male,disloyal Customer,12,Business travel,Business,912,4,0,4,5,3,4,3,3,4,4,4,3,4,3,0,0.0,satisfied +71953,36386,Female,Loyal Customer,51,Personal Travel,Eco,200,3,1,3,1,4,1,1,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +71954,32611,Male,disloyal Customer,23,Business travel,Eco,101,4,4,4,4,5,4,2,5,2,2,3,1,4,5,0,0.0,neutral or dissatisfied +71955,102904,Female,disloyal Customer,24,Business travel,Eco Plus,1037,3,1,3,2,1,3,1,1,3,1,1,3,1,1,0,7.0,neutral or dissatisfied +71956,89397,Female,Loyal Customer,47,Business travel,Business,151,0,4,0,2,4,4,5,2,2,2,2,5,2,5,1,0.0,satisfied +71957,82035,Female,Loyal Customer,33,Personal Travel,Eco,1576,1,5,1,4,2,1,2,2,5,2,5,4,5,2,112,97.0,neutral or dissatisfied +71958,68684,Female,disloyal Customer,25,Business travel,Eco,237,3,2,3,4,5,3,5,5,4,1,3,1,4,5,0,0.0,neutral or dissatisfied +71959,123152,Female,disloyal Customer,21,Business travel,Business,468,2,3,2,4,2,2,1,2,1,1,4,3,4,2,79,71.0,neutral or dissatisfied +71960,86121,Female,Loyal Customer,60,Business travel,Business,1672,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +71961,68523,Female,Loyal Customer,53,Business travel,Business,1013,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +71962,53641,Female,Loyal Customer,17,Personal Travel,Eco,1874,1,2,2,3,2,4,4,1,1,4,3,4,2,4,164,162.0,neutral or dissatisfied +71963,7673,Male,Loyal Customer,47,Business travel,Eco,604,3,5,5,5,3,3,3,3,4,4,4,4,3,3,0,19.0,neutral or dissatisfied +71964,36444,Male,Loyal Customer,64,Personal Travel,Eco,369,2,3,0,3,2,0,2,2,3,5,4,1,4,2,15,11.0,neutral or dissatisfied +71965,113268,Female,Loyal Customer,43,Business travel,Business,397,3,3,3,3,5,4,4,4,4,4,4,4,4,5,20,17.0,satisfied +71966,72049,Female,Loyal Customer,57,Business travel,Business,2556,1,1,5,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +71967,37417,Female,Loyal Customer,37,Business travel,Business,3876,1,1,1,1,2,3,3,1,1,1,1,1,1,1,33,30.0,neutral or dissatisfied +71968,90829,Male,disloyal Customer,30,Business travel,Business,223,3,4,4,4,3,4,3,3,3,5,4,4,3,3,7,23.0,neutral or dissatisfied +71969,3041,Male,Loyal Customer,52,Business travel,Business,2564,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +71970,108719,Male,Loyal Customer,59,Personal Travel,Business,591,2,4,2,1,4,5,5,3,3,2,3,3,3,4,0,4.0,neutral or dissatisfied +71971,42941,Male,disloyal Customer,42,Business travel,Business,236,3,3,3,4,4,3,5,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +71972,75272,Male,Loyal Customer,38,Personal Travel,Eco,1744,3,4,3,4,4,3,4,4,4,5,3,3,4,4,3,0.0,neutral or dissatisfied +71973,127724,Male,disloyal Customer,32,Business travel,Business,255,2,2,2,2,1,2,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +71974,108643,Male,Loyal Customer,27,Personal Travel,Eco,528,2,5,2,1,2,2,4,2,3,3,4,4,5,2,47,22.0,neutral or dissatisfied +71975,99111,Female,disloyal Customer,36,Business travel,Eco,237,2,0,2,2,4,2,4,4,3,1,2,4,3,4,13,1.0,neutral or dissatisfied +71976,78062,Female,Loyal Customer,58,Personal Travel,Eco,332,2,4,2,1,3,4,4,3,3,2,2,4,3,4,14,41.0,neutral or dissatisfied +71977,20541,Male,Loyal Customer,47,Business travel,Eco,533,5,3,3,3,5,5,5,5,1,3,1,4,4,5,0,0.0,satisfied +71978,53507,Male,Loyal Customer,51,Personal Travel,Eco,2253,2,5,2,3,5,2,2,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +71979,35437,Female,Loyal Customer,65,Personal Travel,Eco,1010,1,4,1,1,5,4,5,3,3,1,3,1,3,5,0,0.0,neutral or dissatisfied +71980,12168,Male,Loyal Customer,25,Business travel,Business,1214,4,4,4,4,4,4,4,4,5,1,2,1,1,4,0,0.0,satisfied +71981,53252,Female,Loyal Customer,10,Personal Travel,Eco Plus,612,3,5,3,3,3,3,3,3,1,2,5,3,5,3,89,80.0,neutral or dissatisfied +71982,112714,Female,Loyal Customer,22,Business travel,Business,1731,1,1,1,1,3,3,3,3,2,5,3,2,5,3,1,0.0,satisfied +71983,113640,Female,Loyal Customer,50,Personal Travel,Eco,386,3,5,3,2,3,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +71984,37835,Male,Loyal Customer,52,Business travel,Business,1734,3,3,3,3,3,1,1,4,4,4,4,2,4,4,2,0.0,satisfied +71985,31523,Male,Loyal Customer,62,Business travel,Business,1595,3,4,4,4,1,4,4,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +71986,27919,Female,Loyal Customer,36,Business travel,Business,289,1,1,1,1,3,5,4,5,5,5,5,2,5,2,0,10.0,satisfied +71987,80194,Male,Loyal Customer,60,Personal Travel,Eco,2586,4,2,4,4,4,2,2,2,3,4,4,2,1,2,0,0.0,satisfied +71988,100735,Female,Loyal Customer,37,Business travel,Business,328,5,5,5,5,5,2,1,5,5,5,5,2,5,5,1,0.0,satisfied +71989,60108,Male,Loyal Customer,39,Business travel,Business,1182,1,1,1,1,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +71990,56812,Female,Loyal Customer,45,Business travel,Business,1605,3,5,3,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +71991,15746,Female,Loyal Customer,38,Business travel,Eco,544,3,3,3,3,3,3,3,3,4,5,3,1,3,3,67,55.0,neutral or dissatisfied +71992,99979,Female,Loyal Customer,41,Business travel,Business,289,1,1,2,1,5,5,5,5,4,5,4,5,5,5,282,305.0,satisfied +71993,41676,Male,Loyal Customer,63,Business travel,Business,347,4,4,4,4,1,3,2,5,5,5,5,4,5,1,0,0.0,satisfied +71994,56445,Male,Loyal Customer,21,Personal Travel,Eco,719,0,4,0,4,2,0,2,2,4,5,3,4,4,2,14,29.0,satisfied +71995,34549,Female,Loyal Customer,23,Business travel,Business,1576,3,3,3,3,4,4,4,4,5,1,4,3,1,4,0,0.0,satisfied +71996,114913,Female,Loyal Customer,58,Business travel,Business,1834,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +71997,73321,Male,Loyal Customer,40,Business travel,Business,1197,3,3,3,3,5,5,5,4,4,4,4,5,4,4,105,99.0,satisfied +71998,17462,Female,Loyal Customer,59,Personal Travel,Eco,677,1,4,1,3,1,4,3,4,4,1,4,3,4,3,76,83.0,neutral or dissatisfied +71999,50346,Male,Loyal Customer,26,Business travel,Business,3116,5,5,5,5,5,5,5,5,5,2,1,4,3,5,35,44.0,satisfied +72000,65711,Male,Loyal Customer,47,Business travel,Eco,1061,2,1,1,1,2,2,2,2,2,1,3,3,3,2,18,5.0,neutral or dissatisfied +72001,85664,Male,Loyal Customer,27,Business travel,Business,903,5,2,5,5,5,5,5,5,3,4,5,3,4,5,0,1.0,satisfied +72002,23951,Female,Loyal Customer,40,Business travel,Business,2425,4,4,2,4,2,2,5,5,5,5,5,2,5,3,0,0.0,satisfied +72003,55008,Female,Loyal Customer,56,Business travel,Business,1608,1,1,1,1,2,4,4,5,5,4,5,3,5,5,39,43.0,satisfied +72004,28972,Male,Loyal Customer,21,Business travel,Business,2098,2,5,5,5,2,2,2,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +72005,129594,Male,Loyal Customer,45,Personal Travel,Business,308,3,5,3,3,5,5,4,1,1,3,5,4,1,4,0,0.0,neutral or dissatisfied +72006,5597,Female,Loyal Customer,28,Business travel,Business,2499,5,5,5,5,4,4,4,4,5,4,5,3,5,4,87,89.0,satisfied +72007,26040,Female,disloyal Customer,45,Business travel,Eco,432,3,0,3,4,2,3,2,2,1,1,5,3,1,2,95,82.0,neutral or dissatisfied +72008,57740,Female,disloyal Customer,16,Business travel,Eco,1481,2,2,2,5,2,4,4,5,4,5,5,4,3,4,0,0.0,neutral or dissatisfied +72009,56240,Female,Loyal Customer,56,Business travel,Business,2434,3,3,3,3,4,4,4,4,4,5,5,4,4,4,3,4.0,satisfied +72010,66939,Female,Loyal Customer,48,Business travel,Business,1986,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +72011,16127,Male,Loyal Customer,18,Personal Travel,Eco,725,1,3,1,3,5,1,1,5,4,2,3,1,2,5,17,5.0,neutral or dissatisfied +72012,124057,Female,Loyal Customer,45,Business travel,Business,2153,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +72013,64349,Male,disloyal Customer,71,Business travel,Business,1212,1,0,0,3,4,1,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +72014,58198,Female,Loyal Customer,52,Business travel,Business,925,2,2,2,2,1,3,4,2,2,2,2,3,2,1,68,58.0,neutral or dissatisfied +72015,27060,Male,Loyal Customer,57,Business travel,Business,1399,2,2,1,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +72016,36140,Male,Loyal Customer,19,Personal Travel,Eco,1562,2,3,2,4,5,2,5,5,4,5,2,3,1,5,58,61.0,neutral or dissatisfied +72017,96523,Female,Loyal Customer,44,Personal Travel,Eco,302,2,5,2,2,3,4,4,1,1,2,1,4,1,4,15,2.0,neutral or dissatisfied +72018,104014,Female,Loyal Customer,17,Personal Travel,Eco,1592,1,5,1,3,2,1,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +72019,116118,Male,Loyal Customer,62,Personal Travel,Eco,371,2,1,4,3,5,4,5,5,1,1,2,2,4,5,1,4.0,neutral or dissatisfied +72020,66072,Female,Loyal Customer,56,Personal Travel,Eco,1055,2,4,2,2,4,3,1,3,3,2,3,3,3,4,1,0.0,neutral or dissatisfied +72021,71031,Female,Loyal Customer,11,Business travel,Eco,978,2,3,5,5,2,2,1,2,3,1,2,1,2,2,26,15.0,neutral or dissatisfied +72022,72494,Female,Loyal Customer,41,Business travel,Eco,1017,3,4,4,4,3,3,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +72023,94296,Male,disloyal Customer,37,Business travel,Business,187,2,2,2,1,5,2,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +72024,31863,Male,Loyal Customer,26,Business travel,Eco Plus,2599,1,3,3,3,1,1,2,1,3,3,3,2,4,1,15,6.0,neutral or dissatisfied +72025,78369,Female,disloyal Customer,21,Business travel,Eco,980,1,1,1,5,2,1,3,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +72026,40759,Male,Loyal Customer,33,Business travel,Business,558,2,2,2,2,1,2,1,1,2,5,1,5,3,1,0,0.0,satisfied +72027,61517,Male,Loyal Customer,7,Personal Travel,Eco,2419,2,4,2,4,3,2,3,3,1,3,4,4,4,3,0,0.0,neutral or dissatisfied +72028,15024,Male,disloyal Customer,19,Business travel,Eco,516,2,4,2,3,2,2,5,2,4,4,4,5,5,2,2,0.0,neutral or dissatisfied +72029,540,Male,Loyal Customer,57,Business travel,Business,2298,5,5,5,5,5,4,5,5,5,5,5,3,5,5,9,10.0,satisfied +72030,17881,Male,Loyal Customer,25,Personal Travel,Eco,371,0,4,0,3,4,0,1,4,1,3,4,2,3,4,6,0.0,satisfied +72031,127157,Male,Loyal Customer,40,Personal Travel,Eco,651,2,1,1,2,1,1,1,1,3,3,2,1,2,1,0,0.0,neutral or dissatisfied +72032,185,Male,Loyal Customer,49,Business travel,Business,213,2,1,1,1,4,3,3,3,3,2,2,1,3,1,19,29.0,neutral or dissatisfied +72033,122354,Female,Loyal Customer,58,Business travel,Business,3134,1,1,1,1,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +72034,35987,Female,disloyal Customer,15,Business travel,Eco,726,4,4,4,2,4,2,2,3,5,1,1,2,2,2,114,99.0,neutral or dissatisfied +72035,127964,Male,Loyal Customer,54,Personal Travel,Eco,1999,3,4,3,5,2,3,2,2,3,5,4,3,4,2,0,3.0,neutral or dissatisfied +72036,63340,Male,Loyal Customer,16,Business travel,Business,2567,3,1,5,1,3,3,3,3,3,1,4,3,4,3,2,17.0,neutral or dissatisfied +72037,41334,Male,Loyal Customer,66,Personal Travel,Eco,689,1,3,1,2,1,1,1,1,3,5,3,3,3,1,0,6.0,neutral or dissatisfied +72038,18995,Female,Loyal Customer,23,Personal Travel,Eco,388,3,4,2,4,1,2,1,1,5,2,5,4,5,1,25,11.0,neutral or dissatisfied +72039,49316,Male,disloyal Customer,37,Business travel,Eco,86,1,5,2,1,3,2,3,3,1,1,3,5,3,3,0,1.0,neutral or dissatisfied +72040,114109,Female,Loyal Customer,27,Business travel,Business,850,4,4,4,4,5,5,5,5,4,3,4,4,4,5,6,0.0,satisfied +72041,41997,Female,Loyal Customer,50,Business travel,Business,2528,5,5,5,5,5,4,2,4,4,5,4,4,4,2,101,104.0,satisfied +72042,110034,Female,disloyal Customer,29,Business travel,Business,1422,0,0,0,1,1,0,3,1,3,5,5,4,4,1,46,54.0,satisfied +72043,44012,Female,Loyal Customer,64,Personal Travel,Eco,397,2,5,2,3,4,5,4,5,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +72044,128213,Female,Loyal Customer,39,Business travel,Business,2083,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +72045,8131,Male,Loyal Customer,33,Business travel,Business,1840,5,5,5,5,4,4,5,4,3,5,4,5,4,4,0,0.0,satisfied +72046,121913,Female,Loyal Customer,19,Personal Travel,Eco,449,1,3,1,4,3,1,3,3,5,4,3,2,4,3,31,23.0,neutral or dissatisfied +72047,3241,Male,Loyal Customer,43,Business travel,Business,425,1,1,1,1,4,5,5,4,4,4,4,5,4,5,73,96.0,satisfied +72048,63112,Female,Loyal Customer,14,Personal Travel,Eco Plus,862,2,1,2,3,3,2,3,3,4,1,2,3,2,3,8,9.0,neutral or dissatisfied +72049,89736,Male,Loyal Customer,49,Personal Travel,Eco,1076,3,4,4,2,1,4,1,1,5,2,4,5,5,1,0,0.0,neutral or dissatisfied +72050,99303,Male,Loyal Customer,44,Business travel,Business,2203,2,2,2,2,2,5,4,4,4,4,4,3,4,4,28,22.0,satisfied +72051,100238,Female,Loyal Customer,10,Personal Travel,Business,1011,4,5,4,1,4,5,5,3,3,3,3,5,5,5,340,338.0,neutral or dissatisfied +72052,111564,Male,disloyal Customer,26,Business travel,Business,775,4,5,5,4,3,5,3,3,4,3,5,3,5,3,11,4.0,neutral or dissatisfied +72053,92708,Female,Loyal Customer,50,Business travel,Business,2153,1,1,1,1,4,4,4,4,4,5,4,4,4,5,6,0.0,satisfied +72054,61375,Male,disloyal Customer,25,Business travel,Business,679,4,5,4,3,5,4,5,5,3,5,5,3,5,5,0,0.0,satisfied +72055,118906,Female,disloyal Customer,27,Business travel,Eco,187,2,0,2,3,2,2,2,2,2,4,5,1,3,2,0,0.0,neutral or dissatisfied +72056,115376,Female,disloyal Customer,66,Business travel,Eco,342,1,1,1,3,3,1,1,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +72057,50106,Male,Loyal Customer,69,Business travel,Business,3175,2,4,4,4,3,3,4,4,4,3,2,2,4,3,0,8.0,neutral or dissatisfied +72058,65830,Female,Loyal Customer,15,Business travel,Business,1389,4,4,3,4,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +72059,37447,Female,Loyal Customer,53,Business travel,Business,3078,1,3,3,3,5,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +72060,13764,Male,Loyal Customer,19,Business travel,Eco Plus,401,4,3,3,3,4,4,5,4,1,2,2,5,2,4,0,0.0,satisfied +72061,53454,Female,Loyal Customer,53,Business travel,Business,2288,5,5,5,5,3,3,2,5,5,5,5,1,5,5,2,0.0,satisfied +72062,28449,Male,Loyal Customer,24,Business travel,Business,2537,2,5,5,5,2,2,2,2,3,1,3,2,4,2,0,0.0,neutral or dissatisfied +72063,40205,Female,Loyal Customer,45,Business travel,Business,2078,4,4,3,4,4,1,2,4,4,4,4,3,4,3,19,56.0,satisfied +72064,96913,Male,Loyal Customer,32,Personal Travel,Eco,488,2,1,2,1,4,2,4,4,1,4,2,2,1,4,1,0.0,neutral or dissatisfied +72065,3415,Female,Loyal Customer,55,Personal Travel,Eco,315,2,4,2,3,5,4,4,5,5,2,5,1,5,1,0,0.0,neutral or dissatisfied +72066,118274,Male,Loyal Customer,40,Personal Travel,Business,639,3,4,3,4,4,3,3,4,4,3,4,1,4,4,10,0.0,neutral or dissatisfied +72067,73170,Female,Loyal Customer,62,Personal Travel,Business,1258,4,2,3,1,2,2,2,4,4,3,4,2,4,4,0,0.0,satisfied +72068,109763,Male,Loyal Customer,31,Business travel,Business,1204,2,2,2,2,5,5,5,5,5,5,5,5,5,5,39,28.0,satisfied +72069,24363,Male,Loyal Customer,18,Personal Travel,Business,669,2,4,2,2,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +72070,118758,Male,Loyal Customer,33,Personal Travel,Eco,451,3,3,3,1,2,3,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +72071,62534,Male,Loyal Customer,52,Business travel,Business,1846,4,4,4,4,5,5,5,3,3,3,3,4,3,4,55,39.0,satisfied +72072,44780,Male,Loyal Customer,8,Business travel,Business,3157,3,2,2,2,3,3,3,3,1,4,4,1,4,3,36,30.0,neutral or dissatisfied +72073,104440,Male,Loyal Customer,38,Personal Travel,Eco,1041,3,4,3,3,2,3,3,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +72074,28607,Male,Loyal Customer,47,Business travel,Eco,2349,4,3,3,3,5,4,5,5,5,1,3,5,4,5,0,0.0,satisfied +72075,47045,Male,disloyal Customer,26,Business travel,Eco,639,3,3,3,4,5,3,5,5,1,3,2,2,1,5,70,53.0,neutral or dissatisfied +72076,105831,Female,Loyal Customer,51,Personal Travel,Eco,883,3,3,3,4,1,4,4,5,5,3,5,1,5,1,33,48.0,neutral or dissatisfied +72077,73096,Male,Loyal Customer,40,Personal Travel,Eco Plus,1085,3,4,3,1,5,3,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +72078,17483,Male,Loyal Customer,38,Business travel,Business,3018,2,2,2,2,1,1,2,4,4,4,4,4,4,2,0,0.0,satisfied +72079,72394,Female,Loyal Customer,59,Business travel,Business,2478,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +72080,5217,Male,disloyal Customer,25,Business travel,Business,383,5,0,5,3,4,5,3,4,3,5,5,5,4,4,0,0.0,satisfied +72081,52284,Female,disloyal Customer,38,Business travel,Eco,261,4,0,4,4,4,4,3,4,4,4,3,3,3,4,20,17.0,neutral or dissatisfied +72082,57212,Male,disloyal Customer,30,Business travel,Eco,1039,1,1,1,3,5,1,5,5,3,1,3,4,3,5,23,28.0,neutral or dissatisfied +72083,79720,Female,Loyal Customer,66,Personal Travel,Eco,762,3,3,3,3,2,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +72084,86920,Female,Loyal Customer,15,Personal Travel,Eco,341,3,2,3,2,5,3,4,5,4,1,2,1,2,5,98,96.0,neutral or dissatisfied +72085,91485,Female,Loyal Customer,34,Personal Travel,Eco,859,3,4,3,2,4,3,4,4,3,5,4,4,4,4,6,0.0,neutral or dissatisfied +72086,113622,Female,Loyal Customer,29,Personal Travel,Eco,226,2,5,2,3,3,2,3,3,5,4,4,5,4,3,38,34.0,neutral or dissatisfied +72087,128763,Male,Loyal Customer,52,Business travel,Business,550,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +72088,106338,Female,Loyal Customer,48,Business travel,Business,425,2,2,2,2,2,2,3,2,2,2,2,1,2,1,2,9.0,neutral or dissatisfied +72089,76705,Male,Loyal Customer,37,Personal Travel,Eco,547,3,5,3,3,3,4,1,5,4,4,4,1,4,1,289,279.0,neutral or dissatisfied +72090,20736,Female,Loyal Customer,24,Business travel,Eco,363,4,4,4,4,4,4,5,4,2,3,2,4,4,4,0,0.0,satisfied +72091,110564,Male,disloyal Customer,33,Business travel,Business,551,2,2,2,4,2,3,3,5,3,4,4,3,5,3,124,133.0,neutral or dissatisfied +72092,123678,Male,Loyal Customer,39,Business travel,Business,3337,3,3,3,3,2,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +72093,15634,Male,Loyal Customer,53,Business travel,Eco Plus,228,2,1,1,1,3,2,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +72094,45767,Female,Loyal Customer,19,Business travel,Business,1832,5,5,5,5,4,4,4,4,4,3,1,1,2,4,0,0.0,satisfied +72095,12725,Female,disloyal Customer,37,Business travel,Eco,403,3,0,2,3,1,2,1,1,4,5,4,4,2,1,0,0.0,neutral or dissatisfied +72096,40732,Female,disloyal Customer,39,Business travel,Business,532,3,3,3,4,3,3,3,3,2,3,1,5,2,3,9,6.0,neutral or dissatisfied +72097,1392,Male,Loyal Customer,46,Personal Travel,Eco Plus,354,3,5,5,2,4,5,2,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +72098,70482,Female,Loyal Customer,25,Business travel,Business,1714,4,1,1,1,4,4,4,4,2,3,4,2,4,4,0,106.0,neutral or dissatisfied +72099,33240,Female,Loyal Customer,58,Business travel,Eco Plus,163,1,1,5,1,1,4,4,1,1,1,1,4,1,2,4,4.0,neutral or dissatisfied +72100,53297,Female,disloyal Customer,28,Business travel,Eco,758,3,3,3,3,3,3,3,3,3,5,4,4,3,3,12,7.0,neutral or dissatisfied +72101,81049,Male,Loyal Customer,15,Business travel,Business,1399,1,1,1,1,5,5,5,5,1,3,2,5,5,5,6,0.0,satisfied +72102,108405,Female,disloyal Customer,22,Business travel,Business,544,5,4,4,3,4,4,4,4,4,4,5,5,5,4,20,18.0,satisfied +72103,112978,Female,Loyal Customer,49,Personal Travel,Eco Plus,1129,3,5,3,3,3,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +72104,118960,Female,Loyal Customer,33,Personal Travel,Eco,682,2,4,2,2,3,2,3,3,4,5,4,5,4,3,35,34.0,neutral or dissatisfied +72105,21137,Female,Loyal Customer,25,Personal Travel,Eco,152,1,5,0,1,4,0,4,4,3,4,4,4,5,4,8,21.0,neutral or dissatisfied +72106,59513,Male,Loyal Customer,40,Business travel,Business,956,1,1,1,1,5,5,4,5,5,5,5,3,5,5,27,15.0,satisfied +72107,7516,Male,disloyal Customer,25,Business travel,Business,762,1,0,2,3,3,2,3,3,3,5,5,3,5,3,26,7.0,neutral or dissatisfied +72108,2041,Female,Loyal Customer,48,Business travel,Business,3175,2,5,2,2,4,5,4,4,4,5,4,4,4,3,0,5.0,satisfied +72109,2414,Female,Loyal Customer,50,Personal Travel,Eco,641,2,3,2,3,3,2,3,3,3,2,3,3,3,3,1,0.0,neutral or dissatisfied +72110,60338,Male,Loyal Customer,25,Business travel,Business,2994,4,4,4,4,5,5,5,5,3,2,5,3,4,5,12,0.0,satisfied +72111,61671,Male,Loyal Customer,41,Business travel,Business,2296,5,5,5,5,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +72112,115544,Female,disloyal Customer,43,Business travel,Business,372,4,4,4,1,2,4,2,2,3,4,4,5,4,2,3,0.0,satisfied +72113,1005,Female,Loyal Customer,62,Business travel,Eco,396,1,3,3,3,2,4,3,1,1,1,1,1,1,1,81,89.0,neutral or dissatisfied +72114,19501,Male,Loyal Customer,31,Business travel,Eco,350,5,5,5,5,5,5,5,5,3,1,1,3,4,5,0,0.0,satisfied +72115,11092,Female,Loyal Customer,52,Personal Travel,Eco,166,2,4,2,2,2,5,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +72116,68506,Male,Loyal Customer,43,Personal Travel,Eco,1303,3,5,3,3,5,3,5,5,3,5,3,3,5,5,37,37.0,neutral or dissatisfied +72117,106897,Male,Loyal Customer,37,Personal Travel,Eco,577,4,2,4,3,2,4,4,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +72118,91730,Female,Loyal Customer,39,Business travel,Eco,588,2,1,1,1,2,2,2,2,1,2,4,2,3,2,0,0.0,neutral or dissatisfied +72119,90562,Male,disloyal Customer,23,Business travel,Eco,270,3,0,3,3,4,3,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +72120,46474,Female,Loyal Customer,53,Business travel,Business,2921,3,1,2,1,1,4,4,3,3,3,3,1,3,3,13,30.0,neutral or dissatisfied +72121,26792,Male,Loyal Customer,59,Business travel,Eco,226,5,4,4,4,5,5,5,5,5,1,1,5,4,5,0,0.0,satisfied +72122,74667,Female,Loyal Customer,11,Personal Travel,Eco,1438,2,4,2,3,1,2,1,1,4,4,3,3,5,1,0,0.0,neutral or dissatisfied +72123,20850,Female,Loyal Customer,21,Personal Travel,Eco,508,3,4,3,4,2,3,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +72124,81705,Female,Loyal Customer,32,Personal Travel,Eco,907,3,4,4,5,5,4,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +72125,26840,Male,disloyal Customer,40,Business travel,Business,224,1,1,1,3,2,1,2,2,2,1,3,3,2,2,1,0.0,neutral or dissatisfied +72126,12231,Female,Loyal Customer,45,Business travel,Business,1732,4,4,4,4,4,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +72127,27993,Male,Loyal Customer,67,Personal Travel,Eco,1616,1,2,1,3,4,1,4,4,2,2,4,3,3,4,0,0.0,neutral or dissatisfied +72128,128457,Male,Loyal Customer,53,Personal Travel,Eco,647,3,1,3,4,2,3,2,2,3,3,3,1,3,2,10,27.0,neutral or dissatisfied +72129,55192,Male,Loyal Customer,42,Business travel,Eco Plus,1064,1,3,3,3,1,1,1,1,1,4,4,2,4,1,76,68.0,neutral or dissatisfied +72130,22566,Male,Loyal Customer,58,Business travel,Business,300,0,0,0,2,5,3,1,3,3,3,3,2,3,4,0,0.0,satisfied +72131,33908,Male,Loyal Customer,33,Personal Travel,Eco Plus,1226,1,4,1,1,2,1,2,2,5,4,1,3,2,2,29,24.0,neutral or dissatisfied +72132,81443,Female,Loyal Customer,48,Business travel,Business,2497,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +72133,17004,Female,Loyal Customer,68,Business travel,Eco Plus,552,5,3,3,3,4,2,3,5,5,5,5,3,5,2,5,0.0,satisfied +72134,123869,Male,Loyal Customer,23,Business travel,Business,3426,2,5,5,5,2,2,2,2,2,1,4,4,3,2,8,13.0,neutral or dissatisfied +72135,98296,Female,Loyal Customer,32,Personal Travel,Eco,1072,3,5,3,4,3,3,2,3,4,4,4,3,4,3,11,25.0,neutral or dissatisfied +72136,118098,Male,Loyal Customer,36,Personal Travel,Eco,1671,2,5,2,4,5,2,5,5,1,2,5,2,4,5,35,24.0,neutral or dissatisfied +72137,3806,Female,Loyal Customer,57,Business travel,Business,650,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +72138,70201,Male,Loyal Customer,31,Personal Travel,Eco,258,5,3,5,3,2,5,2,2,2,5,4,2,3,2,0,4.0,satisfied +72139,88096,Male,Loyal Customer,32,Business travel,Business,3309,4,4,4,4,5,5,5,5,5,2,4,4,4,5,25,21.0,satisfied +72140,11790,Female,Loyal Customer,54,Personal Travel,Eco,429,4,5,4,3,4,2,5,3,3,4,3,2,3,2,17,5.0,neutral or dissatisfied +72141,9370,Female,disloyal Customer,38,Business travel,Eco,441,2,0,2,5,5,2,4,5,4,1,1,5,3,5,0,0.0,neutral or dissatisfied +72142,65718,Female,Loyal Customer,31,Business travel,Business,3392,3,3,3,3,4,4,4,4,5,2,4,3,5,4,0,1.0,satisfied +72143,36909,Female,Loyal Customer,15,Personal Travel,Eco,2072,4,5,4,3,4,4,4,4,3,4,3,4,4,4,4,14.0,neutral or dissatisfied +72144,13699,Female,Loyal Customer,12,Personal Travel,Eco,483,3,4,3,4,5,3,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +72145,34224,Male,Loyal Customer,63,Personal Travel,Eco,1189,1,4,1,3,3,1,4,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +72146,110784,Female,disloyal Customer,21,Business travel,Business,1128,2,0,2,4,4,2,4,4,1,2,4,4,3,4,0,9.0,neutral or dissatisfied +72147,23148,Male,Loyal Customer,37,Business travel,Business,3339,3,2,2,2,3,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +72148,48632,Male,disloyal Customer,38,Business travel,Business,308,3,2,2,4,1,2,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +72149,128050,Female,Loyal Customer,22,Personal Travel,Eco,735,2,4,2,2,2,2,2,2,4,5,4,3,4,2,9,13.0,neutral or dissatisfied +72150,69876,Male,Loyal Customer,42,Business travel,Business,2248,5,5,5,5,4,5,5,4,4,4,4,3,4,5,11,0.0,satisfied +72151,82479,Female,Loyal Customer,48,Personal Travel,Eco,502,1,5,1,2,2,4,5,2,2,1,5,5,2,5,0,0.0,neutral or dissatisfied +72152,50415,Female,Loyal Customer,49,Business travel,Eco,77,4,2,2,2,2,4,3,4,4,4,4,3,4,4,0,0.0,satisfied +72153,73214,Female,Loyal Customer,41,Business travel,Business,1258,2,2,2,2,5,5,4,4,4,4,4,5,4,5,6,0.0,satisfied +72154,93391,Female,Loyal Customer,32,Business travel,Business,3627,4,4,4,4,3,3,3,3,4,2,4,4,4,3,32,25.0,satisfied +72155,86909,Male,Loyal Customer,51,Business travel,Business,1726,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +72156,76160,Female,Loyal Customer,48,Personal Travel,Eco,689,3,5,3,1,2,5,5,4,4,3,1,3,4,3,0,0.0,neutral or dissatisfied +72157,86876,Male,Loyal Customer,21,Business travel,Eco Plus,484,1,2,2,2,1,1,1,1,2,4,2,1,2,1,71,59.0,neutral or dissatisfied +72158,93410,Female,Loyal Customer,23,Business travel,Business,671,4,4,4,4,4,4,4,4,4,2,4,5,5,4,6,0.0,satisfied +72159,31961,Female,Loyal Customer,56,Business travel,Business,2656,1,1,5,1,1,2,3,3,3,4,1,1,3,4,0,0.0,neutral or dissatisfied +72160,112698,Male,Loyal Customer,49,Business travel,Business,3642,4,3,4,3,4,3,2,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +72161,71987,Female,Loyal Customer,25,Personal Travel,Eco,1440,3,5,3,3,5,3,5,5,3,4,4,3,5,5,0,5.0,neutral or dissatisfied +72162,9148,Male,Loyal Customer,74,Business travel,Business,2192,1,0,0,2,2,2,2,5,5,0,5,1,5,2,16,19.0,neutral or dissatisfied +72163,55167,Male,Loyal Customer,20,Personal Travel,Eco,1608,4,5,4,3,3,4,2,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +72164,44896,Female,disloyal Customer,34,Business travel,Eco,536,1,2,1,4,2,1,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +72165,120842,Male,Loyal Customer,34,Business travel,Business,3440,1,1,2,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +72166,33869,Female,Loyal Customer,37,Personal Travel,Eco Plus,1609,2,3,2,3,2,2,2,2,2,5,2,2,4,2,0,0.0,neutral or dissatisfied +72167,66893,Male,disloyal Customer,25,Business travel,Eco,1119,3,3,3,4,2,3,5,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +72168,14615,Female,Loyal Customer,52,Personal Travel,Eco,448,3,5,3,1,2,4,4,3,3,3,2,3,3,3,0,6.0,neutral or dissatisfied +72169,50023,Female,Loyal Customer,36,Business travel,Business,1899,1,1,1,1,2,2,3,4,4,4,4,2,4,2,0,0.0,satisfied +72170,88933,Male,Loyal Customer,51,Business travel,Business,1184,2,2,2,2,4,4,4,4,2,4,5,4,3,4,258,250.0,satisfied +72171,56938,Male,Loyal Customer,43,Business travel,Eco,2454,3,1,1,1,3,3,3,4,5,2,4,3,1,3,11,10.0,neutral or dissatisfied +72172,95862,Male,Loyal Customer,41,Business travel,Business,2456,2,2,2,2,2,2,2,5,3,5,4,2,3,2,193,193.0,satisfied +72173,73500,Female,Loyal Customer,51,Business travel,Business,1120,3,3,3,3,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +72174,12356,Male,Loyal Customer,41,Business travel,Business,285,4,4,4,4,4,5,2,5,5,5,5,4,5,1,0,0.0,satisfied +72175,104618,Male,disloyal Customer,23,Business travel,Eco,861,4,4,4,2,4,4,4,4,5,5,4,3,4,4,23,23.0,satisfied +72176,100278,Male,Loyal Customer,44,Business travel,Business,2243,1,1,4,1,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +72177,122714,Female,Loyal Customer,37,Business travel,Business,2253,4,1,1,1,4,4,4,4,4,4,4,3,4,4,23,20.0,neutral or dissatisfied +72178,8111,Female,disloyal Customer,25,Business travel,Business,125,2,0,2,2,5,2,3,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +72179,35103,Male,disloyal Customer,22,Business travel,Business,1076,5,0,5,2,1,5,1,1,3,2,2,1,4,1,42,30.0,satisfied +72180,71839,Female,Loyal Customer,42,Business travel,Eco,1744,3,1,3,1,5,2,4,2,2,3,2,3,2,1,25,32.0,neutral or dissatisfied +72181,119381,Female,disloyal Customer,32,Business travel,Business,399,2,2,2,1,5,2,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +72182,80124,Male,Loyal Customer,26,Personal Travel,Business,2475,3,4,3,3,3,1,1,2,3,4,1,1,3,1,2,0.0,neutral or dissatisfied +72183,76759,Female,Loyal Customer,42,Business travel,Business,2896,2,2,2,2,5,4,4,4,4,4,4,4,4,3,6,0.0,satisfied +72184,8097,Female,disloyal Customer,20,Business travel,Eco,335,4,0,5,4,5,5,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +72185,93601,Male,Loyal Customer,54,Business travel,Business,577,3,3,3,3,2,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +72186,126735,Female,disloyal Customer,17,Business travel,Eco,1025,4,4,4,3,2,4,2,2,2,3,2,2,3,2,41,36.0,neutral or dissatisfied +72187,42627,Female,disloyal Customer,11,Business travel,Eco,546,1,0,1,2,3,1,3,3,1,4,5,5,2,3,0,0.0,neutral or dissatisfied +72188,13238,Female,Loyal Customer,77,Business travel,Eco,468,2,4,5,5,5,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +72189,26566,Female,Loyal Customer,34,Business travel,Business,1709,2,1,1,1,2,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +72190,108615,Male,Loyal Customer,32,Personal Travel,Eco,813,2,2,2,3,2,2,5,2,2,1,3,1,3,2,2,0.0,neutral or dissatisfied +72191,34626,Female,disloyal Customer,37,Business travel,Business,427,3,3,3,2,5,3,4,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +72192,113031,Female,Loyal Customer,44,Business travel,Business,3571,1,1,1,1,4,4,5,5,5,4,5,5,5,3,51,56.0,satisfied +72193,109385,Male,Loyal Customer,15,Personal Travel,Eco,1189,3,5,3,2,1,3,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +72194,53478,Female,Loyal Customer,26,Business travel,Business,2253,3,5,4,5,3,3,3,3,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +72195,107484,Female,Loyal Customer,24,Business travel,Business,1655,2,3,3,3,2,2,2,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +72196,23561,Female,Loyal Customer,35,Personal Travel,Eco,637,1,3,1,4,4,1,4,4,2,1,3,3,4,4,23,13.0,neutral or dissatisfied +72197,99435,Female,Loyal Customer,58,Personal Travel,Eco,337,1,3,1,4,5,1,3,3,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +72198,31150,Male,disloyal Customer,27,Business travel,Eco,495,2,3,2,2,3,2,3,3,4,4,3,4,2,3,0,0.0,neutral or dissatisfied +72199,102092,Male,Loyal Customer,53,Business travel,Business,3358,2,2,4,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +72200,24356,Male,disloyal Customer,35,Business travel,Eco Plus,634,2,2,2,2,1,2,1,1,2,5,5,2,1,1,0,0.0,neutral or dissatisfied +72201,94664,Male,disloyal Customer,35,Business travel,Eco,323,3,1,3,2,5,3,5,5,4,5,3,3,2,5,3,12.0,neutral or dissatisfied +72202,111748,Male,Loyal Customer,70,Personal Travel,Eco,1224,2,5,2,5,5,2,2,5,3,2,3,4,1,5,0,0.0,neutral or dissatisfied +72203,122006,Female,Loyal Customer,60,Business travel,Business,3805,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,1.0,satisfied +72204,31433,Female,Loyal Customer,44,Personal Travel,Eco,1703,1,4,1,5,1,1,4,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +72205,97009,Female,Loyal Customer,24,Personal Travel,Eco,794,4,5,4,4,2,4,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +72206,78300,Male,Loyal Customer,30,Personal Travel,Eco,1598,1,4,1,2,1,1,1,5,3,4,4,1,4,1,978,970.0,neutral or dissatisfied +72207,99957,Female,Loyal Customer,25,Business travel,Eco Plus,2237,2,2,3,2,2,2,4,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +72208,734,Female,disloyal Customer,39,Business travel,Business,89,2,2,2,1,4,2,4,4,5,3,4,4,4,4,0,44.0,satisfied +72209,71942,Female,Loyal Customer,22,Business travel,Eco Plus,1744,2,2,2,2,2,2,1,2,4,4,2,3,2,2,5,0.0,neutral or dissatisfied +72210,93913,Male,disloyal Customer,22,Business travel,Business,507,4,0,4,4,5,4,5,5,4,3,5,5,4,5,25,12.0,satisfied +72211,54894,Female,Loyal Customer,58,Personal Travel,Eco,862,4,4,4,4,2,4,5,4,4,4,1,4,4,3,3,5.0,satisfied +72212,20716,Female,disloyal Customer,12,Business travel,Eco,707,2,2,2,1,4,2,4,4,4,1,5,3,1,4,0,0.0,neutral or dissatisfied +72213,76259,Female,disloyal Customer,23,Business travel,Eco Plus,1399,1,4,1,4,5,1,5,5,5,5,1,1,5,5,0,0.0,neutral or dissatisfied +72214,56335,Male,Loyal Customer,63,Business travel,Business,3129,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +72215,23335,Male,Loyal Customer,20,Personal Travel,Eco,809,2,4,2,4,4,2,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +72216,98716,Male,Loyal Customer,49,Business travel,Business,3354,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +72217,13328,Male,Loyal Customer,45,Business travel,Eco,748,5,4,4,4,5,5,5,5,1,4,3,2,1,5,0,0.0,satisfied +72218,71499,Female,Loyal Customer,11,Personal Travel,Business,1005,1,4,1,3,5,1,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +72219,39600,Male,Loyal Customer,40,Personal Travel,Eco,748,2,2,2,4,1,2,1,1,2,2,4,3,4,1,0,6.0,neutral or dissatisfied +72220,39828,Female,Loyal Customer,47,Business travel,Eco,132,4,2,2,2,5,4,3,4,4,4,4,4,4,3,0,0.0,satisfied +72221,36808,Male,Loyal Customer,30,Business travel,Eco,2300,4,4,4,4,4,4,4,4,1,2,5,2,5,4,83,58.0,satisfied +72222,58913,Female,Loyal Customer,30,Personal Travel,Eco,888,4,3,4,3,1,4,1,1,5,4,2,5,1,1,49,24.0,neutral or dissatisfied +72223,73325,Male,Loyal Customer,39,Business travel,Business,2855,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,20.0,satisfied +72224,102322,Female,Loyal Customer,47,Business travel,Business,3450,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +72225,118036,Female,disloyal Customer,11,Business travel,Eco,1262,4,4,4,3,2,4,2,2,4,5,4,5,4,2,4,0.0,satisfied +72226,111095,Female,Loyal Customer,50,Business travel,Business,2808,0,1,1,1,3,4,4,3,3,3,3,5,3,4,9,23.0,satisfied +72227,85608,Female,Loyal Customer,36,Personal Travel,Eco,259,1,4,1,3,2,1,2,2,4,5,3,3,3,2,14,2.0,neutral or dissatisfied +72228,21179,Female,Loyal Customer,41,Business travel,Business,153,5,5,5,5,5,2,3,4,4,4,5,3,4,5,24,20.0,satisfied +72229,37664,Male,Loyal Customer,50,Personal Travel,Eco,1056,3,4,3,2,4,3,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +72230,23685,Female,Loyal Customer,69,Business travel,Eco,73,1,3,3,3,1,4,4,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +72231,77481,Male,Loyal Customer,32,Business travel,Business,2230,3,3,5,3,4,5,4,4,5,4,5,4,5,4,0,0.0,satisfied +72232,88747,Male,Loyal Customer,51,Personal Travel,Eco,515,3,5,4,4,3,4,3,3,4,5,4,3,5,3,1,8.0,neutral or dissatisfied +72233,39374,Male,Loyal Customer,47,Personal Travel,Business,521,0,5,0,3,3,4,4,1,1,0,3,3,1,4,0,0.0,satisfied +72234,41162,Male,Loyal Customer,25,Personal Travel,Eco,191,2,5,2,1,4,2,4,4,3,4,4,5,5,4,2,5.0,neutral or dissatisfied +72235,61487,Female,Loyal Customer,15,Business travel,Business,2419,2,1,1,1,2,2,2,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +72236,102533,Female,Loyal Customer,30,Personal Travel,Eco,386,4,4,4,3,4,4,4,4,3,4,5,3,4,4,11,5.0,neutral or dissatisfied +72237,25210,Male,disloyal Customer,27,Business travel,Eco,787,3,3,3,3,4,3,4,4,5,5,2,5,2,4,1,8.0,neutral or dissatisfied +72238,66196,Male,Loyal Customer,27,Business travel,Business,2010,3,3,3,3,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +72239,77202,Male,disloyal Customer,28,Business travel,Business,1423,5,4,4,4,4,1,1,5,5,4,4,1,4,1,8,0.0,satisfied +72240,64364,Female,Loyal Customer,41,Personal Travel,Eco,1158,0,4,0,2,4,0,4,4,4,2,5,5,5,4,4,7.0,satisfied +72241,124294,Male,Loyal Customer,42,Business travel,Business,601,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +72242,43961,Male,Loyal Customer,45,Business travel,Business,3640,3,3,3,3,5,1,2,5,5,5,5,3,5,4,77,64.0,satisfied +72243,56413,Female,Loyal Customer,48,Business travel,Business,1587,3,3,3,3,2,5,4,4,4,4,4,5,4,5,64,54.0,satisfied +72244,72925,Female,Loyal Customer,56,Business travel,Business,3666,1,1,1,1,2,5,5,5,5,5,5,5,5,4,4,0.0,satisfied +72245,128793,Male,Loyal Customer,20,Personal Travel,Business,2475,3,2,3,4,3,5,5,3,5,4,4,5,2,5,19,16.0,neutral or dissatisfied +72246,107878,Male,Loyal Customer,35,Personal Travel,Eco,228,4,4,4,2,1,4,1,1,3,3,5,3,5,1,8,3.0,neutral or dissatisfied +72247,36919,Female,Loyal Customer,69,Business travel,Eco,340,1,2,2,2,2,3,4,1,1,1,1,1,1,4,18,31.0,neutral or dissatisfied +72248,97045,Female,Loyal Customer,13,Personal Travel,Business,1242,4,5,4,3,1,4,1,1,4,3,5,4,5,1,0,5.0,neutral or dissatisfied +72249,1718,Female,Loyal Customer,54,Business travel,Business,1967,3,4,3,4,5,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +72250,119046,Male,Loyal Customer,49,Business travel,Business,2279,4,4,4,4,5,5,5,4,4,4,4,3,4,5,37,33.0,satisfied +72251,1192,Female,Loyal Customer,27,Personal Travel,Eco,309,1,4,5,2,4,5,4,4,2,5,2,1,5,4,0,0.0,neutral or dissatisfied +72252,96547,Female,Loyal Customer,40,Business travel,Business,1927,0,1,1,3,4,5,4,5,5,5,5,4,5,3,28,24.0,satisfied +72253,106132,Female,Loyal Customer,49,Business travel,Business,302,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +72254,120270,Male,Loyal Customer,51,Business travel,Eco,1576,3,4,4,4,3,3,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +72255,21162,Male,Loyal Customer,9,Personal Travel,Eco,954,2,4,2,4,2,2,2,2,4,1,3,2,3,2,0,4.0,neutral or dissatisfied +72256,32794,Male,Loyal Customer,45,Business travel,Eco,102,4,3,4,3,4,4,4,4,1,2,5,4,1,4,1,4.0,satisfied +72257,70442,Female,disloyal Customer,23,Business travel,Eco,187,3,1,3,4,5,3,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +72258,54508,Male,Loyal Customer,37,Business travel,Eco,525,2,2,2,2,2,2,2,2,1,2,1,4,2,2,57,46.0,neutral or dissatisfied +72259,81085,Male,disloyal Customer,39,Business travel,Eco,531,1,2,1,4,5,1,5,5,4,5,3,1,4,5,0,0.0,neutral or dissatisfied +72260,71779,Male,Loyal Customer,38,Business travel,Business,1744,3,3,3,3,4,3,4,4,4,4,4,4,4,5,23,30.0,satisfied +72261,58555,Female,Loyal Customer,54,Personal Travel,Eco,1514,3,5,3,1,3,5,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +72262,92946,Male,Loyal Customer,46,Personal Travel,Eco,134,4,0,0,4,2,0,2,2,4,5,3,3,5,2,0,0.0,neutral or dissatisfied +72263,119517,Male,disloyal Customer,27,Business travel,Eco,899,2,2,2,4,1,2,1,1,1,4,4,3,3,1,0,0.0,neutral or dissatisfied +72264,44496,Female,Loyal Customer,45,Business travel,Business,3158,4,4,4,4,5,3,2,2,2,2,2,5,2,4,0,0.0,satisfied +72265,97641,Male,Loyal Customer,50,Business travel,Business,1587,2,2,2,2,4,4,4,5,5,5,5,3,5,3,0,14.0,satisfied +72266,109698,Female,disloyal Customer,15,Business travel,Eco,930,4,4,4,4,2,4,2,2,2,2,4,4,1,2,0,0.0,satisfied +72267,62576,Male,Loyal Customer,24,Business travel,Business,1846,3,5,5,5,3,3,3,3,3,4,4,2,3,3,0,8.0,neutral or dissatisfied +72268,108288,Male,Loyal Customer,54,Business travel,Business,1706,4,4,4,4,3,4,4,4,4,4,4,5,4,4,36,53.0,satisfied +72269,25361,Male,Loyal Customer,22,Business travel,Eco,591,5,1,5,5,5,4,5,5,5,5,1,1,1,5,0,0.0,satisfied +72270,49815,Female,disloyal Customer,58,Business travel,Eco,266,4,0,4,1,5,4,5,5,2,5,3,2,3,5,0,0.0,satisfied +72271,37860,Female,Loyal Customer,43,Business travel,Business,3656,5,5,5,5,4,2,4,2,2,2,2,2,2,3,1,0.0,satisfied +72272,7567,Female,Loyal Customer,17,Personal Travel,Business,594,3,3,3,5,2,3,2,2,3,2,3,4,1,2,0,0.0,neutral or dissatisfied +72273,99325,Male,Loyal Customer,19,Personal Travel,Eco,337,3,5,3,1,5,3,5,5,4,4,4,5,4,5,11,5.0,neutral or dissatisfied +72274,191,Male,disloyal Customer,35,Business travel,Business,213,2,2,2,4,2,2,2,2,4,4,3,4,4,2,41,29.0,neutral or dissatisfied +72275,123819,Male,Loyal Customer,37,Business travel,Business,541,3,3,3,3,5,5,5,2,2,2,2,5,2,5,0,8.0,satisfied +72276,78823,Male,Loyal Customer,20,Personal Travel,Eco,432,3,5,3,3,3,3,3,3,3,2,5,5,5,3,17,18.0,neutral or dissatisfied +72277,68791,Female,Loyal Customer,27,Business travel,Business,3921,3,1,2,1,3,3,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +72278,109884,Female,Loyal Customer,37,Business travel,Business,3951,1,4,4,4,4,4,4,1,1,1,1,1,1,1,45,41.0,neutral or dissatisfied +72279,45459,Male,Loyal Customer,25,Business travel,Business,522,2,2,3,2,5,5,5,5,3,4,2,4,2,5,0,0.0,satisfied +72280,118371,Male,Loyal Customer,40,Personal Travel,Eco Plus,602,3,3,3,3,3,2,2,3,5,2,4,2,1,2,158,147.0,neutral or dissatisfied +72281,108344,Female,disloyal Customer,23,Business travel,Eco,1750,3,3,3,4,1,3,1,1,1,1,4,3,3,1,14,0.0,neutral or dissatisfied +72282,128341,Male,Loyal Customer,25,Business travel,Business,3612,1,1,1,1,5,5,5,5,3,4,4,3,5,5,0,3.0,satisfied +72283,7076,Male,Loyal Customer,55,Business travel,Business,2426,4,4,2,4,5,5,4,4,4,4,4,4,4,3,3,0.0,satisfied +72284,114830,Female,Loyal Customer,46,Business travel,Business,337,2,2,5,2,5,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +72285,102622,Female,Loyal Customer,45,Business travel,Business,365,3,3,3,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +72286,12335,Female,Loyal Customer,51,Business travel,Business,3027,0,4,0,1,1,1,2,4,4,4,2,3,4,4,57,59.0,satisfied +72287,97624,Female,disloyal Customer,29,Business travel,Business,764,4,4,4,5,4,4,2,4,4,3,5,3,5,4,31,18.0,neutral or dissatisfied +72288,21321,Female,disloyal Customer,42,Business travel,Business,674,3,3,3,2,3,3,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +72289,54613,Male,Loyal Customer,19,Business travel,Eco,787,4,4,4,4,4,4,3,4,4,1,3,2,5,4,3,0.0,satisfied +72290,108175,Female,Loyal Customer,10,Personal Travel,Eco,990,2,5,2,4,4,2,4,4,5,3,4,4,4,4,2,0.0,neutral or dissatisfied +72291,89672,Female,Loyal Customer,34,Business travel,Business,1607,3,3,4,3,4,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +72292,79503,Female,Loyal Customer,39,Business travel,Business,712,1,1,3,1,3,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +72293,56530,Female,Loyal Customer,52,Business travel,Business,1065,5,5,5,5,2,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +72294,13514,Male,disloyal Customer,44,Business travel,Eco,106,3,5,3,2,4,3,3,4,3,1,2,4,4,4,0,0.0,neutral or dissatisfied +72295,105131,Female,disloyal Customer,25,Business travel,Eco,220,4,1,4,3,2,4,2,2,1,5,4,4,3,2,69,73.0,neutral or dissatisfied +72296,3483,Male,Loyal Customer,38,Business travel,Business,2632,3,3,3,3,5,4,4,5,5,5,5,5,5,3,116,87.0,satisfied +72297,51958,Male,disloyal Customer,38,Business travel,Business,347,3,3,3,5,4,3,4,4,1,5,4,5,4,4,0,6.0,neutral or dissatisfied +72298,59955,Female,disloyal Customer,24,Business travel,Eco,1068,3,3,3,4,2,3,2,2,2,5,3,4,4,2,0,7.0,neutral or dissatisfied +72299,19374,Female,Loyal Customer,30,Personal Travel,Eco,476,3,2,3,2,1,3,1,1,4,3,2,1,3,1,0,0.0,neutral or dissatisfied +72300,8738,Female,Loyal Customer,56,Business travel,Business,304,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +72301,30887,Female,Loyal Customer,7,Personal Travel,Eco,653,3,0,3,3,2,3,2,2,5,4,5,5,4,2,49,44.0,neutral or dissatisfied +72302,32200,Male,Loyal Customer,37,Business travel,Business,163,2,2,2,2,2,2,2,5,5,5,5,3,5,1,0,0.0,satisfied +72303,45341,Male,Loyal Customer,34,Personal Travel,Eco,188,0,4,0,2,4,0,4,4,1,3,5,3,3,4,0,0.0,satisfied +72304,40621,Male,Loyal Customer,35,Personal Travel,Eco,391,4,1,4,3,4,4,4,4,2,4,4,4,3,4,186,194.0,neutral or dissatisfied +72305,105624,Female,Loyal Customer,27,Business travel,Business,787,4,4,4,4,5,5,5,5,4,3,4,4,5,5,1,0.0,satisfied +72306,67797,Male,disloyal Customer,57,Business travel,Eco,1464,4,4,4,4,3,4,3,3,4,4,3,4,4,3,2,14.0,neutral or dissatisfied +72307,25851,Female,Loyal Customer,50,Personal Travel,Eco,692,4,1,4,3,1,2,3,3,3,4,3,1,3,1,15,5.0,satisfied +72308,30755,Female,Loyal Customer,11,Personal Travel,Eco,977,1,4,1,4,3,1,3,3,3,5,5,3,4,3,0,13.0,neutral or dissatisfied +72309,46785,Male,Loyal Customer,40,Business travel,Business,3348,2,2,2,2,5,5,5,5,2,5,4,5,4,5,184,226.0,satisfied +72310,65502,Female,disloyal Customer,26,Business travel,Business,1303,4,4,4,5,5,4,5,5,5,4,4,3,5,5,88,97.0,satisfied +72311,66462,Male,Loyal Customer,15,Personal Travel,Eco,1217,2,3,2,5,5,2,4,5,2,3,4,3,4,5,15,4.0,neutral or dissatisfied +72312,83525,Female,Loyal Customer,7,Personal Travel,Eco,946,3,1,3,3,3,3,3,3,2,1,2,4,3,3,0,0.0,neutral or dissatisfied +72313,2234,Female,Loyal Customer,36,Personal Travel,Eco,859,4,4,5,2,4,5,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +72314,69751,Female,Loyal Customer,25,Business travel,Business,3324,3,3,3,3,5,5,5,5,2,1,1,5,5,5,0,15.0,satisfied +72315,113112,Female,Loyal Customer,35,Personal Travel,Eco,569,3,1,3,4,1,3,1,1,2,4,3,3,4,1,0,0.0,neutral or dissatisfied +72316,80395,Male,Loyal Customer,14,Personal Travel,Eco,422,3,0,4,5,5,4,5,5,3,3,5,4,5,5,0,12.0,neutral or dissatisfied +72317,30436,Female,Loyal Customer,8,Personal Travel,Eco,483,4,5,4,2,3,4,5,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +72318,81561,Female,disloyal Customer,23,Business travel,Eco,936,1,1,1,4,4,1,4,4,4,5,3,3,4,4,0,0.0,neutral or dissatisfied +72319,86936,Female,Loyal Customer,41,Business travel,Business,907,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +72320,1394,Male,Loyal Customer,54,Personal Travel,Eco Plus,134,3,2,3,4,4,3,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +72321,2494,Male,Loyal Customer,13,Personal Travel,Eco,1379,1,5,1,4,5,1,5,5,4,2,4,3,4,5,0,5.0,neutral or dissatisfied +72322,94087,Female,Loyal Customer,41,Business travel,Business,293,1,1,4,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +72323,32143,Female,Loyal Customer,47,Business travel,Eco,102,5,5,3,3,1,4,1,5,5,5,5,1,5,1,0,0.0,satisfied +72324,59735,Female,Loyal Customer,8,Personal Travel,Eco Plus,965,2,5,2,1,4,2,2,4,5,5,5,3,4,4,34,35.0,neutral or dissatisfied +72325,109033,Female,Loyal Customer,72,Business travel,Business,957,4,1,1,1,1,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +72326,106360,Male,Loyal Customer,34,Business travel,Business,3847,4,4,4,4,4,4,4,3,2,5,4,4,4,4,180,178.0,satisfied +72327,90784,Male,Loyal Customer,21,Business travel,Business,2099,2,5,5,5,2,2,2,2,1,3,3,1,4,2,0,6.0,neutral or dissatisfied +72328,49693,Male,Loyal Customer,43,Business travel,Eco,158,3,2,2,2,3,3,3,3,3,1,3,3,3,3,0,3.0,neutral or dissatisfied +72329,24963,Female,Loyal Customer,37,Business travel,Business,3387,2,3,5,5,4,3,4,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +72330,116364,Male,Loyal Customer,43,Personal Travel,Eco,390,4,4,4,3,3,4,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +72331,65180,Female,Loyal Customer,56,Personal Travel,Eco,551,3,4,2,3,2,3,3,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +72332,2811,Male,disloyal Customer,17,Business travel,Business,409,0,2,0,5,1,0,1,1,3,2,5,5,4,1,0,0.0,satisfied +72333,106345,Female,Loyal Customer,27,Business travel,Business,488,1,1,4,1,2,2,2,2,3,5,4,4,4,2,9,3.0,satisfied +72334,66141,Male,Loyal Customer,17,Personal Travel,Eco,583,1,1,1,3,4,1,4,4,1,1,3,3,2,4,0,9.0,neutral or dissatisfied +72335,58154,Male,Loyal Customer,49,Business travel,Eco,925,2,2,2,2,2,2,2,2,2,1,3,3,3,2,3,3.0,neutral or dissatisfied +72336,25372,Female,Loyal Customer,43,Business travel,Eco,591,2,4,2,4,1,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +72337,20044,Male,Loyal Customer,55,Business travel,Eco,738,5,5,5,5,5,5,5,5,4,5,2,5,2,5,0,0.0,satisfied +72338,48939,Female,Loyal Customer,37,Business travel,Business,2408,3,3,3,3,3,3,2,5,5,5,5,5,5,1,0,0.0,satisfied +72339,7381,Female,Loyal Customer,28,Business travel,Business,3032,5,5,5,5,3,4,3,3,3,4,5,3,5,3,69,70.0,satisfied +72340,100595,Male,Loyal Customer,33,Personal Travel,Eco Plus,486,2,3,2,4,4,2,4,4,3,1,3,2,4,4,36,41.0,neutral or dissatisfied +72341,105603,Male,disloyal Customer,29,Business travel,Business,919,4,4,4,3,5,4,5,5,3,2,4,3,4,5,4,0.0,satisfied +72342,109030,Male,Loyal Customer,46,Business travel,Business,1105,3,3,3,3,2,4,5,3,3,4,3,3,3,5,8,15.0,satisfied +72343,105100,Female,Loyal Customer,49,Business travel,Business,3332,5,5,5,5,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +72344,28137,Female,Loyal Customer,24,Business travel,Eco,873,1,1,1,1,1,1,2,1,1,2,3,3,4,1,51,54.0,neutral or dissatisfied +72345,47896,Female,disloyal Customer,24,Business travel,Business,348,3,1,3,3,2,3,2,2,4,4,4,1,4,2,77,91.0,neutral or dissatisfied +72346,78281,Male,Loyal Customer,52,Business travel,Business,1598,3,3,3,3,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +72347,7499,Female,Loyal Customer,68,Personal Travel,Eco,925,2,5,2,2,5,2,5,1,1,2,3,3,1,2,0,6.0,neutral or dissatisfied +72348,52874,Male,Loyal Customer,40,Business travel,Eco,1024,3,3,3,3,3,3,3,3,2,5,2,3,2,3,2,6.0,neutral or dissatisfied +72349,86735,Female,Loyal Customer,66,Personal Travel,Eco Plus,1747,1,1,1,3,5,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +72350,32163,Male,Loyal Customer,55,Business travel,Eco,84,5,2,2,2,5,5,5,5,1,5,2,3,3,5,0,0.0,satisfied +72351,56508,Male,disloyal Customer,36,Business travel,Business,1085,1,1,1,3,5,1,5,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +72352,101944,Female,Loyal Customer,39,Business travel,Business,3226,3,3,3,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +72353,45716,Female,disloyal Customer,26,Business travel,Eco,1068,3,3,3,3,2,3,4,2,2,2,4,2,3,2,0,23.0,neutral or dissatisfied +72354,14398,Male,Loyal Customer,29,Personal Travel,Eco,789,2,4,2,3,3,2,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +72355,47439,Female,Loyal Customer,46,Business travel,Eco,188,4,4,4,4,5,5,2,4,4,4,4,3,4,1,0,0.0,satisfied +72356,3657,Male,Loyal Customer,42,Business travel,Business,1633,4,4,4,4,5,5,5,4,4,4,4,3,4,5,7,0.0,satisfied +72357,115660,Male,Loyal Customer,38,Business travel,Business,2700,2,4,4,4,5,2,3,2,2,2,2,4,2,2,75,78.0,neutral or dissatisfied +72358,124081,Male,Loyal Customer,53,Business travel,Business,1779,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,44.0,satisfied +72359,60533,Male,Loyal Customer,19,Personal Travel,Eco,862,2,5,2,2,1,2,1,1,5,2,4,3,4,1,19,4.0,neutral or dissatisfied +72360,36289,Male,Loyal Customer,26,Personal Travel,Business,187,2,4,2,4,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +72361,127122,Female,Loyal Customer,11,Personal Travel,Eco,646,3,2,3,2,2,3,2,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +72362,122805,Female,disloyal Customer,25,Business travel,Eco,199,2,1,2,1,3,2,3,3,2,2,1,3,2,3,0,0.0,neutral or dissatisfied +72363,124682,Male,Loyal Customer,42,Business travel,Eco,399,2,3,3,3,2,2,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +72364,80440,Male,Loyal Customer,11,Personal Travel,Eco,2248,3,4,3,1,2,3,2,2,3,4,5,4,4,2,15,14.0,neutral or dissatisfied +72365,25397,Male,Loyal Customer,60,Business travel,Business,3052,1,4,4,4,3,3,3,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +72366,55354,Male,Loyal Customer,54,Business travel,Business,678,4,4,4,4,5,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +72367,100812,Male,Loyal Customer,47,Business travel,Eco,1167,2,2,2,2,1,2,1,1,4,5,2,4,2,1,51,52.0,neutral or dissatisfied +72368,21895,Female,Loyal Customer,43,Business travel,Eco,448,2,1,1,1,3,3,2,2,2,2,2,3,2,2,18,6.0,neutral or dissatisfied +72369,61689,Female,Loyal Customer,47,Business travel,Business,3087,3,4,4,4,3,2,3,3,3,3,3,2,3,3,12,1.0,neutral or dissatisfied +72370,67472,Male,Loyal Customer,16,Personal Travel,Eco,769,4,4,5,4,4,5,4,4,3,1,5,1,1,4,0,0.0,satisfied +72371,92801,Male,Loyal Customer,49,Business travel,Business,1587,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +72372,103094,Female,Loyal Customer,7,Personal Travel,Eco,687,4,5,4,1,5,4,5,5,3,5,4,5,5,5,0,0.0,satisfied +72373,125508,Male,Loyal Customer,53,Personal Travel,Eco,666,1,2,1,3,4,1,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +72374,71551,Male,Loyal Customer,51,Business travel,Business,3382,3,3,5,3,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +72375,66304,Female,Loyal Customer,54,Business travel,Eco,852,3,5,5,5,4,4,3,3,3,3,3,2,3,2,0,7.0,neutral or dissatisfied +72376,104689,Male,disloyal Customer,27,Business travel,Eco,159,2,1,2,2,2,2,2,2,4,3,2,1,2,2,19,11.0,neutral or dissatisfied +72377,25679,Male,Loyal Customer,38,Personal Travel,Eco,761,2,5,2,4,3,2,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +72378,108055,Female,Loyal Customer,12,Personal Travel,Eco,591,2,5,2,2,2,2,2,2,3,3,4,3,4,2,3,0.0,neutral or dissatisfied +72379,72287,Male,Loyal Customer,25,Personal Travel,Eco,919,2,5,1,3,5,1,4,5,1,2,5,5,3,5,0,0.0,neutral or dissatisfied +72380,85619,Male,Loyal Customer,49,Personal Travel,Eco,153,1,4,0,3,2,0,4,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +72381,43676,Female,Loyal Customer,62,Personal Travel,Eco,695,2,4,2,2,3,5,4,2,2,2,2,5,2,4,100,91.0,neutral or dissatisfied +72382,102790,Male,Loyal Customer,64,Personal Travel,Eco,1099,3,2,3,3,1,3,1,1,4,5,3,4,4,1,0,3.0,neutral or dissatisfied +72383,97805,Female,Loyal Customer,54,Business travel,Business,395,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +72384,106094,Female,Loyal Customer,41,Business travel,Business,436,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,3.0,satisfied +72385,15284,Female,Loyal Customer,13,Personal Travel,Eco,460,1,5,2,1,3,2,3,3,4,4,1,4,2,3,6,23.0,neutral or dissatisfied +72386,113741,Female,Loyal Customer,26,Personal Travel,Eco,391,5,5,5,2,3,5,3,3,4,4,5,3,5,3,0,0.0,satisfied +72387,54994,Male,Loyal Customer,53,Business travel,Business,1346,2,2,2,2,4,5,4,4,4,4,4,3,4,5,24,28.0,satisfied +72388,69532,Female,disloyal Customer,37,Business travel,Business,2475,1,1,1,3,1,3,3,3,3,4,4,3,3,3,11,16.0,neutral or dissatisfied +72389,22111,Female,disloyal Customer,16,Business travel,Eco,694,3,3,3,4,3,3,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +72390,20344,Male,Loyal Customer,44,Business travel,Business,1902,5,5,5,5,1,4,4,5,5,5,5,2,5,4,38,30.0,satisfied +72391,86504,Male,Loyal Customer,15,Personal Travel,Eco,853,2,4,2,3,4,2,4,4,3,4,5,5,5,4,84,71.0,neutral or dissatisfied +72392,94744,Female,Loyal Customer,53,Business travel,Eco,323,1,0,0,4,1,3,3,5,5,1,5,1,5,2,2,7.0,neutral or dissatisfied +72393,76232,Female,Loyal Customer,52,Business travel,Business,1175,3,5,5,5,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +72394,27976,Male,Loyal Customer,46,Business travel,Business,2378,3,3,3,3,4,4,4,5,2,5,2,4,3,4,0,1.0,satisfied +72395,117269,Female,Loyal Customer,42,Personal Travel,Eco,338,4,5,4,3,3,4,4,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +72396,123603,Male,Loyal Customer,65,Personal Travel,Eco,1773,2,3,2,3,1,2,1,1,2,1,3,1,5,1,4,3.0,neutral or dissatisfied +72397,105932,Male,Loyal Customer,51,Business travel,Business,1491,3,3,3,3,3,4,4,4,4,4,4,3,4,4,21,4.0,satisfied +72398,43849,Male,Loyal Customer,71,Business travel,Eco,255,3,5,2,5,3,3,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +72399,61259,Female,Loyal Customer,69,Personal Travel,Eco,862,2,4,2,1,2,4,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +72400,52552,Male,Loyal Customer,57,Business travel,Business,3560,0,5,0,2,5,5,1,2,2,2,2,5,2,4,0,5.0,satisfied +72401,117091,Male,Loyal Customer,41,Business travel,Business,3477,4,4,4,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +72402,125066,Female,Loyal Customer,55,Personal Travel,Eco Plus,90,4,1,4,3,2,3,3,5,5,4,3,4,5,4,0,2.0,neutral or dissatisfied +72403,106512,Female,Loyal Customer,52,Business travel,Business,1703,0,1,1,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +72404,123541,Female,Loyal Customer,43,Business travel,Business,1773,2,4,2,2,3,3,4,4,4,4,4,4,4,4,4,1.0,satisfied +72405,34168,Female,Loyal Customer,25,Business travel,Business,2606,2,2,2,2,2,1,2,2,2,4,3,1,3,2,0,5.0,neutral or dissatisfied +72406,31187,Female,disloyal Customer,44,Business travel,Business,628,4,4,4,3,4,4,5,4,5,2,5,3,5,4,15,19.0,neutral or dissatisfied +72407,78881,Female,Loyal Customer,45,Personal Travel,Eco,223,4,2,4,3,3,3,4,1,1,4,1,3,1,2,5,4.0,satisfied +72408,5814,Female,Loyal Customer,11,Personal Travel,Eco,273,4,2,5,3,4,5,4,4,4,3,3,2,3,4,0,0.0,satisfied +72409,118734,Female,Loyal Customer,24,Personal Travel,Eco,621,1,5,1,2,4,1,4,4,5,2,5,5,4,4,40,33.0,neutral or dissatisfied +72410,108041,Male,Loyal Customer,44,Business travel,Business,306,0,0,0,3,5,4,4,3,3,3,5,5,3,4,4,0.0,satisfied +72411,60443,Male,Loyal Customer,47,Business travel,Business,2433,3,3,4,3,3,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +72412,39099,Male,Loyal Customer,46,Business travel,Eco,328,5,1,1,1,5,5,5,5,5,5,4,4,4,5,1,4.0,satisfied +72413,86274,Male,Loyal Customer,70,Personal Travel,Eco,356,2,5,2,1,4,2,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +72414,38436,Female,Loyal Customer,26,Business travel,Eco,2277,5,2,2,2,5,5,5,5,3,3,4,2,5,5,0,0.0,satisfied +72415,56661,Female,Loyal Customer,34,Business travel,Business,3272,2,3,3,3,4,4,4,2,2,2,2,3,2,1,3,18.0,neutral or dissatisfied +72416,81273,Female,Loyal Customer,35,Business travel,Business,2895,2,2,2,2,3,2,2,1,1,3,3,2,2,2,109,175.0,neutral or dissatisfied +72417,2054,Male,Loyal Customer,36,Business travel,Business,812,3,3,3,3,5,5,4,1,1,2,1,3,1,3,0,0.0,satisfied +72418,53129,Female,disloyal Customer,21,Business travel,Eco Plus,2065,0,4,0,2,4,0,4,4,4,2,5,3,4,4,1,0.0,satisfied +72419,106795,Female,Loyal Customer,37,Business travel,Business,3207,4,4,4,4,4,4,3,4,4,3,4,3,4,2,1,2.0,neutral or dissatisfied +72420,106798,Female,Loyal Customer,40,Business travel,Business,3066,1,0,0,2,0,3,3,4,4,3,3,3,3,3,330,327.0,neutral or dissatisfied +72421,63986,Female,Loyal Customer,45,Business travel,Business,3147,4,4,5,4,2,5,5,4,4,3,4,5,4,5,0,0.0,satisfied +72422,82241,Male,Loyal Customer,34,Personal Travel,Eco,405,2,5,2,3,4,2,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +72423,35989,Female,Loyal Customer,31,Business travel,Business,2496,3,3,3,3,3,3,3,3,3,3,3,3,4,3,16,18.0,neutral or dissatisfied +72424,90675,Female,disloyal Customer,37,Business travel,Business,404,5,5,5,5,3,5,3,3,4,3,4,5,5,3,0,2.0,satisfied +72425,93408,Male,disloyal Customer,24,Business travel,Business,697,4,5,4,1,1,4,1,1,4,2,4,3,5,1,0,6.0,satisfied +72426,100660,Female,Loyal Customer,37,Business travel,Business,628,3,3,3,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +72427,73655,Female,Loyal Customer,46,Business travel,Business,3770,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +72428,92820,Female,Loyal Customer,63,Business travel,Business,1587,1,1,1,1,3,2,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +72429,38866,Male,Loyal Customer,77,Business travel,Eco,2300,2,2,2,2,2,2,2,1,4,4,3,2,1,2,162,149.0,neutral or dissatisfied +72430,18587,Male,Loyal Customer,38,Business travel,Business,127,3,1,4,1,3,3,2,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +72431,854,Female,disloyal Customer,18,Business travel,Eco,158,5,0,5,4,3,5,5,3,5,2,4,4,5,3,0,0.0,satisfied +72432,125709,Female,Loyal Customer,55,Personal Travel,Eco,759,2,5,2,1,4,5,5,3,3,2,1,4,3,3,0,0.0,neutral or dissatisfied +72433,102493,Male,Loyal Customer,15,Personal Travel,Eco,391,1,5,1,3,3,1,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +72434,21754,Female,Loyal Customer,48,Business travel,Eco Plus,563,4,2,2,2,4,4,4,3,2,5,1,4,2,4,172,167.0,satisfied +72435,25902,Female,Loyal Customer,46,Business travel,Eco Plus,907,4,3,2,3,1,1,1,5,5,4,5,1,5,2,0,0.0,satisfied +72436,24879,Female,Loyal Customer,41,Business travel,Business,3905,5,5,5,5,5,2,5,4,4,5,4,2,4,3,27,29.0,satisfied +72437,14600,Male,Loyal Customer,47,Personal Travel,Eco,1021,4,1,4,4,1,4,1,1,2,3,3,4,3,1,0,0.0,neutral or dissatisfied +72438,53257,Female,Loyal Customer,32,Business travel,Eco Plus,589,4,1,1,1,5,5,5,5,5,1,2,1,2,5,6,7.0,satisfied +72439,78113,Female,Loyal Customer,35,Business travel,Business,1619,3,3,3,3,3,3,4,3,3,3,3,1,3,4,15,0.0,neutral or dissatisfied +72440,63889,Female,Loyal Customer,49,Business travel,Business,1192,1,3,3,3,3,2,3,1,1,2,1,1,1,3,9,21.0,neutral or dissatisfied +72441,119071,Male,disloyal Customer,23,Business travel,Eco,1107,1,1,1,3,4,1,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +72442,122155,Female,Loyal Customer,48,Business travel,Business,2398,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +72443,33063,Female,Loyal Customer,55,Personal Travel,Eco,201,1,2,1,4,3,3,3,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +72444,92964,Female,disloyal Customer,24,Business travel,Business,194,4,3,4,1,5,4,5,5,1,2,1,4,3,5,2,0.0,satisfied +72445,47717,Male,Loyal Customer,39,Personal Travel,Eco Plus,1504,3,4,3,2,1,3,5,1,5,3,5,5,4,1,16,0.0,neutral or dissatisfied +72446,113300,Male,Loyal Customer,44,Business travel,Business,2040,1,1,3,1,4,4,4,4,4,4,4,5,4,4,0,5.0,satisfied +72447,62823,Male,Loyal Customer,10,Personal Travel,Eco,2556,1,5,2,1,2,2,2,2,3,3,3,4,5,2,12,0.0,neutral or dissatisfied +72448,93699,Male,Loyal Customer,41,Personal Travel,Eco,1452,1,1,1,2,5,1,5,5,4,2,3,3,2,5,18,8.0,neutral or dissatisfied +72449,57327,Female,Loyal Customer,38,Business travel,Business,1937,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +72450,38490,Female,Loyal Customer,37,Personal Travel,Business,2475,3,2,3,3,1,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +72451,106941,Female,Loyal Customer,41,Business travel,Business,3215,1,1,1,1,5,4,5,4,4,4,4,3,4,4,8,8.0,satisfied +72452,61288,Male,Loyal Customer,48,Personal Travel,Eco,862,3,5,3,4,5,3,5,5,5,4,3,4,5,5,0,0.0,neutral or dissatisfied +72453,39950,Female,Loyal Customer,46,Personal Travel,Eco,989,3,3,3,3,5,3,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +72454,25026,Female,Loyal Customer,59,Business travel,Eco,907,5,3,3,3,1,1,1,4,4,5,4,1,4,5,0,0.0,satisfied +72455,103050,Female,Loyal Customer,23,Business travel,Business,2309,2,3,3,3,2,3,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +72456,64792,Female,disloyal Customer,23,Business travel,Eco,224,1,4,1,3,1,1,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +72457,32036,Female,Loyal Customer,45,Business travel,Eco,102,4,1,1,1,4,1,2,4,4,4,4,1,4,3,0,0.0,satisfied +72458,36891,Male,Loyal Customer,63,Personal Travel,Eco Plus,1182,5,5,5,3,5,1,1,5,3,3,4,1,5,1,61,138.0,satisfied +72459,61008,Female,Loyal Customer,49,Personal Travel,Business,3302,3,2,3,4,3,2,2,4,4,3,4,2,1,2,0,4.0,neutral or dissatisfied +72460,69579,Male,Loyal Customer,65,Personal Travel,Eco,2586,2,3,2,3,2,2,2,3,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +72461,64609,Male,disloyal Customer,20,Business travel,Business,224,5,3,5,2,4,5,3,4,3,5,5,3,4,4,0,0.0,satisfied +72462,101857,Male,disloyal Customer,56,Business travel,Eco,119,3,0,3,3,1,3,1,1,5,3,1,1,3,1,0,0.0,neutral or dissatisfied +72463,13690,Male,Loyal Customer,45,Business travel,Business,483,5,5,3,5,3,2,5,3,3,3,3,1,3,2,0,0.0,satisfied +72464,13979,Female,Loyal Customer,69,Business travel,Eco Plus,317,5,3,4,4,1,2,1,4,4,5,4,3,4,4,0,0.0,satisfied +72465,52313,Female,Loyal Customer,52,Business travel,Business,370,4,2,2,2,2,4,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +72466,103652,Male,Loyal Customer,24,Business travel,Business,251,1,4,4,4,1,1,1,1,3,1,3,2,4,1,9,13.0,neutral or dissatisfied +72467,28213,Female,disloyal Customer,27,Business travel,Eco Plus,859,4,4,4,3,1,4,1,1,1,1,2,1,2,1,0,0.0,neutral or dissatisfied +72468,7333,Male,Loyal Customer,57,Business travel,Business,606,2,2,4,2,3,4,5,3,3,4,3,4,3,4,0,19.0,satisfied +72469,35777,Female,disloyal Customer,22,Business travel,Eco,200,2,4,2,4,3,2,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +72470,49021,Female,Loyal Customer,30,Business travel,Business,3341,5,5,5,5,4,4,5,4,1,2,3,2,1,4,43,31.0,satisfied +72471,105984,Female,Loyal Customer,15,Business travel,Eco Plus,2329,3,3,4,3,3,3,3,3,3,2,4,2,4,3,90,91.0,neutral or dissatisfied +72472,119062,Female,Loyal Customer,50,Business travel,Business,2279,5,5,5,5,5,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +72473,128546,Male,Loyal Customer,28,Business travel,Eco Plus,621,3,5,5,5,3,3,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +72474,63910,Female,Loyal Customer,32,Business travel,Business,1559,3,3,3,3,3,3,3,3,1,4,4,3,4,3,124,136.0,neutral or dissatisfied +72475,116922,Male,Loyal Customer,43,Business travel,Business,2481,3,3,3,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +72476,72739,Male,Loyal Customer,36,Personal Travel,Eco Plus,1121,3,5,3,1,4,3,4,4,4,5,4,4,5,4,1,0.0,neutral or dissatisfied +72477,127362,Male,disloyal Customer,26,Business travel,Business,1009,4,3,3,3,2,3,2,2,5,3,4,4,4,2,0,7.0,neutral or dissatisfied +72478,5683,Female,Loyal Customer,18,Business travel,Business,1905,3,4,4,4,3,3,3,3,2,3,4,3,2,3,315,347.0,neutral or dissatisfied +72479,90838,Female,Loyal Customer,56,Business travel,Business,545,1,1,1,1,1,4,3,1,1,1,1,3,1,4,9,7.0,neutral or dissatisfied +72480,73417,Male,Loyal Customer,35,Business travel,Business,2342,5,5,5,5,4,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +72481,112134,Male,Loyal Customer,60,Personal Travel,Business,895,4,1,4,4,5,4,4,2,2,4,1,1,2,2,0,0.0,neutral or dissatisfied +72482,60809,Female,Loyal Customer,48,Business travel,Business,455,3,1,1,1,1,4,3,3,3,3,3,2,3,3,25,31.0,neutral or dissatisfied +72483,41990,Female,Loyal Customer,58,Business travel,Business,116,3,3,3,3,5,2,3,4,4,4,5,4,4,4,0,0.0,satisfied +72484,16405,Female,Loyal Customer,7,Personal Travel,Eco,463,2,5,2,3,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +72485,128918,Female,disloyal Customer,15,Business travel,Business,236,4,2,4,3,5,4,5,5,1,1,3,2,4,5,0,0.0,neutral or dissatisfied +72486,118822,Male,Loyal Customer,59,Business travel,Business,325,0,0,0,3,2,5,4,1,1,1,1,3,1,3,15,14.0,satisfied +72487,105845,Female,Loyal Customer,20,Business travel,Business,883,3,3,3,3,4,4,4,4,5,5,4,3,5,4,14,0.0,satisfied +72488,40287,Female,Loyal Customer,47,Personal Travel,Eco,463,1,5,1,3,3,5,4,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +72489,63797,Female,Loyal Customer,22,Personal Travel,Eco,1721,4,4,4,2,4,4,4,4,4,5,5,5,4,4,31,0.0,neutral or dissatisfied +72490,48935,Female,Loyal Customer,37,Business travel,Eco,373,4,1,4,1,4,4,4,4,5,5,4,2,4,4,11,0.0,satisfied +72491,33131,Female,Loyal Customer,38,Personal Travel,Eco,216,3,4,3,2,2,3,2,2,4,2,3,3,5,2,0,0.0,neutral or dissatisfied +72492,126685,Female,disloyal Customer,23,Business travel,Eco,851,2,3,3,3,2,3,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +72493,95575,Female,Loyal Customer,48,Business travel,Eco Plus,192,2,3,3,3,5,4,3,3,3,2,3,3,3,2,84,72.0,neutral or dissatisfied +72494,51680,Female,disloyal Customer,22,Business travel,Eco,370,3,3,4,4,1,4,1,1,3,3,3,3,4,1,26,21.0,neutral or dissatisfied +72495,103764,Male,disloyal Customer,45,Business travel,Business,882,2,2,2,5,2,2,2,2,4,5,4,3,5,2,16,17.0,neutral or dissatisfied +72496,64226,Female,Loyal Customer,50,Business travel,Eco,1660,3,2,2,2,5,4,3,3,3,3,3,4,3,4,0,12.0,neutral or dissatisfied +72497,96179,Female,Loyal Customer,59,Business travel,Business,3832,3,4,2,2,5,3,4,3,3,3,3,3,3,1,13,19.0,neutral or dissatisfied +72498,22067,Female,Loyal Customer,51,Personal Travel,Eco,304,3,5,3,5,2,5,4,5,5,3,5,4,5,3,9,3.0,neutral or dissatisfied +72499,63281,Female,Loyal Customer,60,Business travel,Business,3481,5,5,5,5,5,4,4,5,2,5,4,4,5,4,136,119.0,satisfied +72500,71166,Male,Loyal Customer,60,Personal Travel,Eco,646,2,5,2,3,3,2,3,3,2,3,2,4,1,3,0,0.0,neutral or dissatisfied +72501,1215,Female,Loyal Customer,31,Personal Travel,Eco,309,1,5,1,1,5,1,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +72502,112692,Female,Loyal Customer,44,Business travel,Eco,605,2,2,2,2,4,3,2,2,2,2,2,2,2,1,16,12.0,neutral or dissatisfied +72503,27037,Female,Loyal Customer,9,Personal Travel,Eco Plus,867,1,5,1,2,1,1,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +72504,30341,Female,disloyal Customer,20,Personal Travel,Eco,391,2,5,2,4,3,2,3,3,5,3,5,4,5,3,0,1.0,neutral or dissatisfied +72505,83808,Female,Loyal Customer,31,Business travel,Eco,425,3,3,3,3,3,3,3,3,1,2,3,1,4,3,30,38.0,neutral or dissatisfied +72506,72986,Male,Loyal Customer,35,Business travel,Eco,1096,4,5,5,5,4,4,4,4,4,2,3,1,4,4,0,0.0,satisfied +72507,78980,Male,Loyal Customer,58,Business travel,Business,226,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +72508,73457,Male,Loyal Customer,26,Personal Travel,Eco,1197,4,4,4,3,3,4,1,3,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +72509,102112,Female,disloyal Customer,22,Business travel,Eco,397,5,0,5,3,4,5,4,4,3,3,4,3,4,4,0,0.0,satisfied +72510,60744,Male,disloyal Customer,56,Business travel,Business,228,3,3,3,3,4,3,4,4,5,4,5,4,4,4,14,0.0,neutral or dissatisfied +72511,70082,Female,Loyal Customer,62,Business travel,Eco,460,2,1,1,1,1,4,4,2,2,2,2,3,2,2,73,63.0,neutral or dissatisfied +72512,121649,Male,Loyal Customer,45,Business travel,Business,1636,5,5,4,5,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +72513,29250,Male,Loyal Customer,40,Business travel,Eco,834,4,1,1,1,4,4,4,4,1,4,3,5,1,4,0,0.0,satisfied +72514,73109,Female,Loyal Customer,60,Business travel,Business,2174,1,5,5,5,1,3,2,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +72515,75700,Male,Loyal Customer,53,Business travel,Business,868,1,1,2,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +72516,48448,Male,disloyal Customer,30,Business travel,Eco,948,3,3,3,3,5,3,5,5,4,1,1,2,4,5,95,93.0,neutral or dissatisfied +72517,110426,Male,disloyal Customer,15,Business travel,Eco,842,4,5,5,4,3,5,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +72518,29688,Male,Loyal Customer,48,Personal Travel,Eco Plus,1448,4,3,4,4,2,4,1,2,3,4,4,2,3,2,5,1.0,neutral or dissatisfied +72519,117367,Male,Loyal Customer,51,Personal Travel,Eco,296,2,4,1,1,4,1,4,4,3,5,5,2,3,4,0,0.0,neutral or dissatisfied +72520,53116,Female,Loyal Customer,49,Business travel,Business,2065,1,0,0,3,1,2,2,5,5,0,5,4,5,3,0,0.0,neutral or dissatisfied +72521,41137,Male,Loyal Customer,27,Personal Travel,Eco,295,5,5,5,3,4,5,5,4,4,3,5,3,4,4,0,0.0,satisfied +72522,86882,Male,Loyal Customer,50,Personal Travel,Eco Plus,692,2,5,2,1,5,2,5,5,5,3,5,5,5,5,3,0.0,neutral or dissatisfied +72523,52025,Male,disloyal Customer,39,Business travel,Eco,328,3,0,2,2,4,2,4,4,2,3,2,1,4,4,0,0.0,neutral or dissatisfied +72524,5,Female,Loyal Customer,49,Business travel,Business,3470,3,3,3,3,4,5,4,3,3,4,3,3,3,5,0,1.0,satisfied +72525,26179,Female,disloyal Customer,24,Business travel,Business,404,2,2,2,3,3,2,4,3,3,2,3,3,3,3,2,0.0,neutral or dissatisfied +72526,93146,Male,Loyal Customer,51,Business travel,Business,3936,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +72527,128025,Male,Loyal Customer,50,Business travel,Business,1440,5,5,5,5,3,4,4,4,4,4,4,5,4,4,28,19.0,satisfied +72528,53027,Male,Loyal Customer,51,Business travel,Business,1190,3,5,5,5,1,3,3,3,3,3,3,1,3,3,10,0.0,neutral or dissatisfied +72529,97824,Female,disloyal Customer,36,Business travel,Business,395,2,2,2,1,1,2,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +72530,8063,Male,Loyal Customer,39,Business travel,Business,3061,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +72531,125183,Female,Loyal Customer,41,Business travel,Business,3365,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +72532,24,Male,Loyal Customer,77,Business travel,Eco Plus,821,4,5,5,5,4,4,4,4,4,5,3,1,2,4,0,0.0,neutral or dissatisfied +72533,657,Female,Loyal Customer,58,Business travel,Business,3824,2,2,2,2,5,4,4,2,2,1,2,3,2,1,0,5.0,neutral or dissatisfied +72534,43973,Female,Loyal Customer,36,Business travel,Eco,411,3,5,1,1,3,4,3,3,4,2,4,3,5,3,0,0.0,satisfied +72535,96942,Female,Loyal Customer,35,Business travel,Business,2895,5,5,5,5,2,4,5,5,5,5,5,3,5,5,68,71.0,satisfied +72536,54550,Male,Loyal Customer,62,Personal Travel,Eco,925,4,2,3,2,2,3,2,2,1,3,3,2,2,2,1,0.0,neutral or dissatisfied +72537,83299,Male,Loyal Customer,45,Business travel,Business,1979,1,1,1,1,3,4,5,4,4,4,4,5,4,3,5,10.0,satisfied +72538,90341,Male,Loyal Customer,53,Business travel,Business,2437,5,5,5,5,3,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +72539,105782,Male,Loyal Customer,52,Personal Travel,Eco,925,1,5,1,5,5,1,2,5,2,5,3,3,3,5,65,66.0,neutral or dissatisfied +72540,27599,Female,Loyal Customer,67,Personal Travel,Eco,679,1,5,1,1,5,4,5,5,5,1,5,3,5,3,2,0.0,neutral or dissatisfied +72541,67946,Female,Loyal Customer,57,Personal Travel,Eco,1171,2,5,2,3,3,3,5,4,4,2,4,4,4,5,4,0.0,neutral or dissatisfied +72542,128210,Female,Loyal Customer,59,Business travel,Business,2563,5,5,5,5,4,4,5,5,5,5,5,4,5,3,0,4.0,satisfied +72543,96984,Female,Loyal Customer,35,Business travel,Business,883,3,3,3,3,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +72544,46305,Male,Loyal Customer,53,Personal Travel,Eco,680,2,4,3,3,4,3,5,4,2,2,1,3,1,4,73,94.0,neutral or dissatisfied +72545,122918,Male,Loyal Customer,32,Personal Travel,Business,600,3,2,3,3,1,3,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +72546,92587,Female,Loyal Customer,24,Business travel,Business,2158,1,1,1,1,5,5,5,5,4,4,4,3,4,5,0,0.0,satisfied +72547,13611,Female,disloyal Customer,23,Business travel,Eco Plus,152,2,3,2,3,3,2,3,3,1,1,4,4,4,3,0,20.0,neutral or dissatisfied +72548,73371,Male,disloyal Customer,44,Business travel,Business,1120,5,5,5,3,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +72549,123361,Female,disloyal Customer,33,Business travel,Business,644,2,2,2,2,5,2,5,5,3,3,4,3,4,5,10,8.0,neutral or dissatisfied +72550,35111,Female,Loyal Customer,39,Business travel,Business,3114,1,1,1,1,5,4,1,4,4,4,4,1,4,4,12,0.0,satisfied +72551,80618,Female,Loyal Customer,15,Personal Travel,Eco,236,4,5,4,2,2,4,2,2,3,4,4,4,5,2,4,1.0,neutral or dissatisfied +72552,98470,Female,Loyal Customer,43,Personal Travel,Eco,210,0,4,0,1,4,3,5,1,1,0,1,1,1,5,0,0.0,satisfied +72553,98915,Female,Loyal Customer,56,Business travel,Business,543,5,5,5,5,5,4,5,3,3,3,3,4,3,3,105,105.0,satisfied +72554,109722,Male,Loyal Customer,24,Business travel,Business,680,4,5,5,5,4,4,4,4,4,3,3,2,3,4,10,50.0,neutral or dissatisfied +72555,18150,Male,Loyal Customer,11,Personal Travel,Eco,296,5,1,5,3,4,5,4,4,1,2,2,3,3,4,3,3.0,satisfied +72556,84041,Female,Loyal Customer,48,Business travel,Business,1947,3,3,2,3,5,5,5,4,4,4,4,4,4,4,11,2.0,satisfied +72557,59164,Male,Loyal Customer,21,Business travel,Eco Plus,1744,4,1,1,1,4,4,4,4,1,2,3,4,4,4,1,0.0,neutral or dissatisfied +72558,127460,Male,Loyal Customer,46,Business travel,Business,2075,3,3,3,3,5,4,5,3,3,3,3,4,3,4,2,0.0,satisfied +72559,101068,Female,Loyal Customer,10,Personal Travel,Eco,368,1,2,1,3,4,1,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +72560,7535,Male,Loyal Customer,54,Personal Travel,Eco,762,3,1,3,4,1,3,1,1,4,5,3,1,4,1,14,21.0,neutral or dissatisfied +72561,57262,Male,Loyal Customer,50,Business travel,Business,3735,3,3,3,3,3,4,5,5,5,5,5,5,5,5,27,11.0,satisfied +72562,90967,Male,Loyal Customer,34,Business travel,Business,404,1,3,3,3,5,3,3,1,1,2,1,2,1,3,14,12.0,neutral or dissatisfied +72563,122831,Female,Loyal Customer,50,Business travel,Business,599,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +72564,83896,Female,Loyal Customer,52,Business travel,Business,1450,3,3,3,3,2,4,4,2,2,2,2,5,2,5,0,1.0,satisfied +72565,26012,Male,Loyal Customer,43,Business travel,Business,3785,2,1,1,1,1,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +72566,126702,Male,Loyal Customer,43,Business travel,Business,2370,5,5,4,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +72567,6059,Female,Loyal Customer,58,Personal Travel,Eco,925,3,2,3,3,3,3,3,1,1,3,2,2,1,4,1,0.0,neutral or dissatisfied +72568,126512,Male,Loyal Customer,67,Business travel,Business,313,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +72569,28998,Male,Loyal Customer,40,Business travel,Business,1050,4,4,1,4,5,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +72570,53738,Female,Loyal Customer,39,Personal Travel,Eco,1190,4,4,4,1,5,4,5,5,4,3,3,3,5,5,0,0.0,neutral or dissatisfied +72571,24826,Male,Loyal Customer,54,Business travel,Business,2746,1,1,1,1,2,1,3,2,2,2,2,4,2,3,0,17.0,satisfied +72572,114794,Male,Loyal Customer,49,Business travel,Business,3895,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +72573,126570,Male,Loyal Customer,32,Business travel,Eco,1558,1,5,5,5,1,1,1,1,2,1,3,1,3,1,0,0.0,neutral or dissatisfied +72574,101132,Female,disloyal Customer,17,Business travel,Business,1090,4,1,4,3,2,4,2,2,5,2,4,5,4,2,17,4.0,satisfied +72575,4810,Female,disloyal Customer,38,Business travel,Business,403,3,2,2,4,5,2,5,5,3,5,5,4,5,5,5,0.0,satisfied +72576,87172,Female,disloyal Customer,24,Business travel,Eco,946,2,1,1,1,1,1,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +72577,89649,Male,Loyal Customer,59,Business travel,Business,1010,2,2,2,2,4,5,4,4,4,4,4,5,4,5,10,0.0,satisfied +72578,112310,Female,disloyal Customer,45,Business travel,Business,967,4,4,4,3,5,4,5,5,5,5,4,5,5,5,78,116.0,satisfied +72579,88589,Male,Loyal Customer,32,Personal Travel,Eco,594,1,5,1,2,5,1,4,5,1,3,3,2,5,5,0,0.0,neutral or dissatisfied +72580,90684,Male,Loyal Customer,60,Business travel,Business,646,2,5,2,2,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +72581,60205,Male,Loyal Customer,60,Business travel,Business,1506,5,5,5,5,5,5,5,5,5,5,5,5,5,5,7,0.0,satisfied +72582,49085,Male,Loyal Customer,40,Business travel,Eco,421,4,1,1,1,4,4,4,4,5,1,1,2,1,4,19,29.0,satisfied +72583,22498,Female,Loyal Customer,35,Personal Travel,Eco,83,4,4,4,4,3,4,3,3,5,5,4,3,4,3,11,6.0,neutral or dissatisfied +72584,69342,Female,disloyal Customer,25,Business travel,Business,1096,2,4,2,2,3,2,3,3,3,2,5,3,4,3,0,5.0,neutral or dissatisfied +72585,54479,Male,Loyal Customer,59,Business travel,Eco,802,4,3,3,3,4,4,4,4,1,4,4,2,4,4,6,9.0,satisfied +72586,122147,Male,Loyal Customer,57,Business travel,Business,3542,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +72587,127309,Male,Loyal Customer,34,Business travel,Eco,1979,4,3,3,3,4,4,4,4,4,5,5,1,2,4,0,2.0,satisfied +72588,15237,Female,Loyal Customer,32,Business travel,Business,416,4,4,5,4,5,5,5,5,3,1,2,5,5,5,0,0.0,satisfied +72589,65974,Female,disloyal Customer,54,Business travel,Eco,1372,3,3,3,4,4,3,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +72590,68598,Male,Loyal Customer,42,Business travel,Business,1739,4,4,4,4,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +72591,48204,Female,disloyal Customer,20,Business travel,Eco,391,2,3,2,3,4,2,1,4,4,1,3,2,4,4,10,10.0,neutral or dissatisfied +72592,98718,Male,disloyal Customer,26,Business travel,Business,473,3,3,3,1,2,3,2,2,4,2,3,1,3,2,7,0.0,neutral or dissatisfied +72593,93889,Male,Loyal Customer,37,Business travel,Business,3266,3,4,3,4,3,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +72594,128407,Male,Loyal Customer,61,Business travel,Business,338,2,3,2,3,5,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +72595,24696,Male,Loyal Customer,22,Business travel,Business,397,1,1,1,1,3,4,3,3,5,1,5,3,3,3,50,53.0,satisfied +72596,38408,Male,Loyal Customer,56,Business travel,Business,2544,4,4,4,4,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +72597,88154,Female,disloyal Customer,27,Business travel,Eco,594,1,1,1,4,2,1,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +72598,52894,Male,Loyal Customer,33,Personal Travel,Eco,836,1,5,1,3,4,1,4,4,4,2,4,5,4,4,27,11.0,neutral or dissatisfied +72599,21267,Male,disloyal Customer,27,Business travel,Business,692,2,3,3,4,5,3,5,5,3,2,3,2,4,5,0,106.0,neutral or dissatisfied +72600,56320,Female,disloyal Customer,35,Business travel,Business,200,2,2,2,3,5,2,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +72601,39854,Male,disloyal Customer,37,Business travel,Business,272,2,2,2,4,3,2,3,3,2,4,4,3,4,3,0,1.0,neutral or dissatisfied +72602,115237,Female,disloyal Customer,32,Business travel,Business,417,4,4,4,4,1,4,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +72603,111236,Female,disloyal Customer,25,Business travel,Eco Plus,1506,3,2,3,3,4,3,4,4,1,5,4,2,3,4,104,101.0,neutral or dissatisfied +72604,102496,Female,Loyal Customer,23,Personal Travel,Eco,386,2,5,2,4,4,2,4,4,3,2,4,3,4,4,44,36.0,neutral or dissatisfied +72605,108548,Female,Loyal Customer,43,Personal Travel,Eco,511,4,4,4,2,5,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +72606,119018,Male,Loyal Customer,67,Personal Travel,Business,1460,4,4,4,1,3,3,4,2,2,4,2,3,2,3,0,25.0,neutral or dissatisfied +72607,57295,Male,Loyal Customer,60,Business travel,Business,414,1,1,1,1,2,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +72608,12980,Male,Loyal Customer,49,Business travel,Business,2844,3,3,3,3,4,3,3,5,5,4,5,4,5,2,10,3.0,satisfied +72609,99887,Male,Loyal Customer,32,Business travel,Business,738,3,3,3,3,4,4,4,4,3,4,5,3,5,4,20,0.0,satisfied +72610,56343,Female,disloyal Customer,59,Business travel,Eco,200,2,1,2,4,4,2,4,4,1,2,3,1,4,4,11,0.0,neutral or dissatisfied +72611,58992,Female,Loyal Customer,28,Business travel,Business,1846,3,3,3,3,3,4,3,3,5,2,5,4,5,3,22,24.0,satisfied +72612,99209,Female,Loyal Customer,59,Business travel,Business,495,1,1,2,1,2,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +72613,71646,Female,Loyal Customer,49,Personal Travel,Eco,1182,3,5,3,1,3,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +72614,28002,Female,disloyal Customer,22,Business travel,Eco,763,2,1,1,4,4,1,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +72615,102224,Female,Loyal Customer,43,Business travel,Eco,258,1,4,4,4,4,4,3,1,1,1,1,1,1,1,8,0.0,neutral or dissatisfied +72616,94633,Male,Loyal Customer,53,Business travel,Business,2339,0,4,0,1,5,4,5,3,3,3,3,5,3,4,1,0.0,satisfied +72617,108811,Male,Loyal Customer,48,Business travel,Business,404,2,2,2,2,4,5,5,5,5,5,4,5,4,5,144,135.0,satisfied +72618,44004,Female,Loyal Customer,20,Business travel,Business,3119,2,2,2,2,5,5,5,5,3,3,5,3,2,5,0,0.0,satisfied +72619,54474,Female,disloyal Customer,18,Business travel,Eco,925,2,2,2,2,1,2,5,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +72620,12840,Female,Loyal Customer,35,Personal Travel,Eco,489,2,3,2,3,5,2,3,5,5,5,1,4,1,5,6,12.0,neutral or dissatisfied +72621,68609,Female,Loyal Customer,58,Business travel,Business,3807,1,1,1,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +72622,73054,Female,Loyal Customer,47,Business travel,Business,1096,3,5,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +72623,58213,Female,Loyal Customer,48,Personal Travel,Eco,925,2,4,2,1,4,4,4,3,3,2,3,4,3,3,1,0.0,neutral or dissatisfied +72624,3948,Male,Loyal Customer,57,Business travel,Business,765,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +72625,119438,Male,Loyal Customer,15,Personal Travel,Eco,399,2,4,2,3,1,2,1,1,1,1,4,1,4,1,8,0.0,neutral or dissatisfied +72626,97695,Male,disloyal Customer,34,Business travel,Business,456,3,3,3,3,5,3,5,5,5,2,4,3,5,5,27,31.0,neutral or dissatisfied +72627,72547,Female,Loyal Customer,28,Business travel,Business,1017,2,1,5,5,2,2,2,2,2,2,2,3,3,2,0,7.0,neutral or dissatisfied +72628,126934,Male,Loyal Customer,47,Business travel,Business,1574,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,16.0,satisfied +72629,69841,Male,Loyal Customer,43,Personal Travel,Eco,1055,5,4,5,3,2,5,2,2,4,2,4,3,5,2,35,45.0,satisfied +72630,86067,Female,Loyal Customer,40,Business travel,Business,3084,3,3,4,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +72631,39929,Male,Loyal Customer,41,Business travel,Business,2003,5,5,5,5,3,5,2,5,5,5,5,3,5,1,18,13.0,satisfied +72632,60125,Male,Loyal Customer,35,Business travel,Eco,1050,2,3,3,3,2,2,2,2,1,3,4,4,4,2,0,11.0,neutral or dissatisfied +72633,55656,Female,Loyal Customer,17,Business travel,Eco,315,4,2,2,2,4,4,4,4,1,3,4,2,1,4,0,0.0,satisfied +72634,113519,Male,disloyal Customer,59,Business travel,Business,223,4,4,4,3,2,4,2,2,1,1,4,1,4,2,73,66.0,neutral or dissatisfied +72635,59367,Female,disloyal Customer,21,Business travel,Eco,2399,4,4,4,2,4,4,4,4,5,2,5,4,5,4,13,0.0,satisfied +72636,8224,Female,Loyal Customer,19,Personal Travel,Eco,335,2,3,2,4,5,2,5,5,3,1,3,4,4,5,0,14.0,neutral or dissatisfied +72637,17006,Male,Loyal Customer,40,Business travel,Business,2928,3,3,3,3,2,4,4,4,4,4,4,5,4,3,1,0.0,satisfied +72638,58153,Female,Loyal Customer,53,Business travel,Business,2776,4,4,4,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +72639,45150,Male,disloyal Customer,37,Business travel,Eco,174,1,2,1,3,4,1,4,4,1,1,3,1,3,4,0,10.0,neutral or dissatisfied +72640,96126,Male,Loyal Customer,29,Business travel,Business,1549,5,5,5,5,5,4,5,5,4,5,5,5,4,5,0,4.0,satisfied +72641,106416,Male,Loyal Customer,47,Personal Travel,Eco,674,3,4,3,4,4,3,4,4,5,4,5,5,5,4,0,1.0,neutral or dissatisfied +72642,39031,Female,Loyal Customer,67,Personal Travel,Eco,230,1,4,1,4,2,4,3,4,4,1,4,4,4,1,122,114.0,neutral or dissatisfied +72643,40349,Female,Loyal Customer,40,Business travel,Business,1428,5,5,5,5,3,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +72644,24189,Male,Loyal Customer,23,Business travel,Eco,147,2,5,5,5,2,2,2,2,1,5,2,2,3,2,0,0.0,neutral or dissatisfied +72645,102195,Female,Loyal Customer,50,Business travel,Business,3849,3,3,5,3,5,5,5,4,4,4,4,5,4,3,62,52.0,satisfied +72646,65019,Male,Loyal Customer,36,Business travel,Business,1546,3,2,2,2,1,2,1,3,3,3,3,2,3,3,8,12.0,neutral or dissatisfied +72647,15349,Female,Loyal Customer,46,Business travel,Business,306,4,5,5,5,3,3,3,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +72648,77118,Male,Loyal Customer,59,Personal Travel,Eco,1481,4,4,4,4,1,4,1,1,3,5,4,3,4,1,0,0.0,satisfied +72649,98070,Male,Loyal Customer,29,Business travel,Business,1449,2,4,4,4,2,3,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +72650,116478,Female,Loyal Customer,36,Personal Travel,Eco,337,4,3,4,3,2,4,2,2,2,4,2,1,2,2,0,0.0,neutral or dissatisfied +72651,45581,Male,Loyal Customer,62,Business travel,Eco,230,4,1,1,1,3,4,3,3,4,4,4,1,2,3,12,18.0,satisfied +72652,62798,Male,Loyal Customer,33,Personal Travel,Eco,2556,3,3,3,4,3,4,1,3,3,5,2,1,3,1,0,0.0,neutral or dissatisfied +72653,61308,Female,Loyal Customer,44,Business travel,Business,2298,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +72654,83860,Male,Loyal Customer,22,Personal Travel,Eco,425,1,0,3,2,3,3,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +72655,117743,Female,Loyal Customer,47,Personal Travel,Eco,833,4,4,4,4,3,4,5,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +72656,99293,Female,Loyal Customer,56,Business travel,Business,2088,5,5,5,5,4,5,4,4,4,4,4,3,4,4,0,5.0,satisfied +72657,48602,Female,Loyal Customer,48,Personal Travel,Eco,844,3,4,3,5,2,5,5,2,2,3,2,5,2,5,0,4.0,neutral or dissatisfied +72658,83928,Male,disloyal Customer,36,Business travel,Business,321,2,2,2,4,4,2,1,4,4,4,4,3,5,4,5,3.0,neutral or dissatisfied +72659,87646,Male,Loyal Customer,57,Business travel,Business,606,1,5,5,5,3,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +72660,19486,Male,Loyal Customer,33,Personal Travel,Eco,84,4,2,4,3,5,4,5,5,2,3,3,2,3,5,0,0.0,neutral or dissatisfied +72661,65198,Female,Loyal Customer,19,Personal Travel,Eco,282,1,4,3,4,4,3,1,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +72662,52329,Female,Loyal Customer,57,Business travel,Eco,751,2,3,3,3,4,3,4,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +72663,90280,Female,Loyal Customer,48,Business travel,Business,879,2,2,2,2,5,4,5,4,4,4,4,3,4,3,9,3.0,satisfied +72664,115462,Female,Loyal Customer,61,Business travel,Eco,390,4,4,4,4,4,3,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +72665,28904,Female,Loyal Customer,29,Business travel,Business,697,4,2,2,2,4,4,4,4,3,1,3,2,2,4,15,12.0,neutral or dissatisfied +72666,32357,Male,Loyal Customer,58,Business travel,Business,101,5,5,5,5,4,5,1,4,4,5,4,2,4,5,0,5.0,satisfied +72667,114275,Male,disloyal Customer,21,Business travel,Eco,453,1,1,1,2,3,1,3,3,3,3,1,1,1,3,0,25.0,neutral or dissatisfied +72668,29518,Male,Loyal Customer,47,Business travel,Eco,1009,5,5,2,5,5,5,5,5,4,5,3,3,2,5,11,0.0,satisfied +72669,51446,Male,Loyal Customer,23,Personal Travel,Eco Plus,266,3,0,3,2,2,3,2,2,3,2,5,3,4,2,0,15.0,neutral or dissatisfied +72670,87873,Female,disloyal Customer,26,Business travel,Business,214,5,5,5,3,4,5,4,4,4,4,4,4,5,4,0,1.0,satisfied +72671,18786,Female,Loyal Customer,46,Business travel,Business,3061,1,1,1,1,5,4,4,3,3,3,3,3,3,3,21,8.0,satisfied +72672,100611,Male,Loyal Customer,42,Business travel,Business,1670,3,3,3,3,3,4,4,5,5,5,5,4,5,4,54,33.0,satisfied +72673,8656,Female,Loyal Customer,40,Business travel,Business,280,4,4,4,4,2,5,4,4,4,4,4,4,4,4,16,31.0,satisfied +72674,86399,Female,Loyal Customer,45,Business travel,Business,853,5,5,5,5,3,5,4,3,3,3,3,3,3,5,4,0.0,satisfied +72675,115195,Female,disloyal Customer,44,Business travel,Eco,417,3,3,3,3,3,3,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +72676,5158,Female,Loyal Customer,68,Personal Travel,Eco,622,1,4,1,4,5,5,5,1,1,1,1,4,1,5,15,6.0,neutral or dissatisfied +72677,49724,Female,Loyal Customer,26,Business travel,Eco,373,5,2,3,2,5,5,4,5,4,1,2,4,2,5,0,0.0,satisfied +72678,8821,Female,Loyal Customer,22,Personal Travel,Eco,522,3,3,3,2,5,3,5,5,2,1,3,3,2,5,68,94.0,neutral or dissatisfied +72679,24175,Male,Loyal Customer,43,Business travel,Eco,170,3,2,3,3,3,3,3,3,2,2,2,1,3,3,0,0.0,neutral or dissatisfied +72680,60592,Male,Loyal Customer,35,Personal Travel,Eco,1558,1,1,2,3,1,2,1,1,4,5,2,3,3,1,1,5.0,neutral or dissatisfied +72681,87589,Female,Loyal Customer,57,Personal Travel,Eco,432,2,4,5,3,5,4,5,1,1,5,1,5,1,4,0,0.0,neutral or dissatisfied +72682,108973,Male,Loyal Customer,39,Business travel,Business,994,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +72683,73076,Male,Loyal Customer,37,Business travel,Business,3767,4,4,4,4,4,5,4,4,4,4,4,5,4,4,1,9.0,satisfied +72684,42720,Female,Loyal Customer,58,Business travel,Eco,912,3,3,3,3,4,4,3,3,3,3,3,3,3,4,3,6.0,neutral or dissatisfied +72685,66284,Female,disloyal Customer,20,Business travel,Eco Plus,460,1,2,2,3,3,2,1,3,4,2,4,2,3,3,88,89.0,neutral or dissatisfied +72686,87833,Female,Loyal Customer,69,Personal Travel,Eco,214,1,0,1,1,3,5,4,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +72687,9552,Male,disloyal Customer,22,Business travel,Eco,229,2,5,3,1,3,3,3,4,5,4,4,3,3,3,152,133.0,neutral or dissatisfied +72688,103647,Female,Loyal Customer,29,Business travel,Business,2372,0,0,0,4,3,3,3,3,4,2,5,5,5,3,0,0.0,satisfied +72689,59228,Male,Loyal Customer,48,Business travel,Business,649,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +72690,5125,Female,disloyal Customer,24,Business travel,Eco,235,4,4,4,4,3,4,3,3,3,2,4,4,5,3,0,0.0,satisfied +72691,31746,Male,Loyal Customer,48,Personal Travel,Eco Plus,846,1,2,1,4,2,1,2,2,4,4,3,3,4,2,0,0.0,neutral or dissatisfied +72692,16698,Female,Loyal Customer,30,Business travel,Business,3480,2,2,4,2,4,4,4,4,5,1,4,4,4,4,0,0.0,satisfied +72693,87176,Female,disloyal Customer,30,Business travel,Business,946,3,3,3,3,2,3,1,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +72694,73701,Female,Loyal Customer,42,Business travel,Business,204,5,5,5,5,4,5,4,5,5,4,4,4,5,3,0,0.0,satisfied +72695,73803,Male,Loyal Customer,66,Business travel,Eco Plus,204,4,2,2,2,3,4,3,3,2,2,3,1,3,3,2,0.0,neutral or dissatisfied +72696,109241,Female,Loyal Customer,64,Personal Travel,Eco,612,2,2,2,3,5,3,4,2,2,2,3,2,2,2,48,47.0,neutral or dissatisfied +72697,62426,Female,Loyal Customer,38,Business travel,Business,1911,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +72698,49850,Male,disloyal Customer,20,Business travel,Eco,262,2,3,2,2,3,2,3,3,1,4,2,1,2,3,63,52.0,neutral or dissatisfied +72699,70375,Female,Loyal Customer,54,Business travel,Business,1145,5,5,5,5,2,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +72700,127624,Female,Loyal Customer,22,Business travel,Eco,1773,3,1,1,1,3,3,2,3,4,3,2,3,3,3,13,16.0,neutral or dissatisfied +72701,98156,Male,Loyal Customer,54,Business travel,Business,562,1,1,3,1,4,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +72702,90120,Female,Loyal Customer,41,Business travel,Business,1084,5,5,2,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +72703,7617,Male,Loyal Customer,39,Business travel,Business,3256,5,5,5,5,5,4,4,5,5,5,5,4,5,3,14,15.0,satisfied +72704,12813,Female,Loyal Customer,29,Business travel,Business,817,3,4,4,4,3,3,3,3,1,4,2,4,3,3,0,0.0,neutral or dissatisfied +72705,77376,Male,disloyal Customer,37,Business travel,Eco,590,4,2,4,2,4,4,4,4,3,4,3,4,2,4,0,0.0,neutral or dissatisfied +72706,52759,Male,Loyal Customer,45,Business travel,Business,1874,2,2,2,2,1,5,3,4,4,4,4,3,4,4,0,0.0,satisfied +72707,27403,Male,Loyal Customer,52,Business travel,Business,2266,3,3,3,3,3,1,1,5,5,5,5,1,5,3,0,0.0,satisfied +72708,64758,Female,Loyal Customer,50,Business travel,Business,1834,0,0,0,2,2,5,5,1,1,1,1,3,1,3,0,0.0,satisfied +72709,81356,Female,Loyal Customer,31,Personal Travel,Eco,1299,3,5,3,3,1,3,1,1,4,2,4,3,4,1,3,0.0,neutral or dissatisfied +72710,81966,Female,Loyal Customer,45,Business travel,Business,1522,2,2,2,2,2,4,4,4,4,4,4,5,4,5,14,0.0,satisfied +72711,89243,Male,Loyal Customer,64,Personal Travel,Eco Plus,1892,3,3,3,3,4,3,4,4,4,3,2,4,2,4,21,0.0,neutral or dissatisfied +72712,37425,Male,disloyal Customer,24,Business travel,Eco,1028,1,1,1,3,4,1,4,4,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +72713,35288,Male,Loyal Customer,33,Business travel,Business,972,2,2,2,2,5,5,5,5,1,5,4,4,3,5,0,0.0,satisfied +72714,120682,Female,Loyal Customer,22,Business travel,Eco,280,0,4,0,1,5,0,5,5,4,2,3,4,4,5,63,116.0,satisfied +72715,72264,Male,disloyal Customer,30,Business travel,Eco,919,4,5,5,4,4,5,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +72716,35276,Male,Loyal Customer,55,Business travel,Business,1642,1,1,1,1,5,5,5,1,2,4,3,5,3,5,173,224.0,satisfied +72717,30828,Female,disloyal Customer,26,Business travel,Eco,896,2,2,2,1,5,2,4,5,4,1,1,4,3,5,0,0.0,neutral or dissatisfied +72718,48677,Male,disloyal Customer,59,Business travel,Business,250,1,1,1,1,2,1,4,2,4,2,5,5,4,2,22,17.0,neutral or dissatisfied +72719,3924,Female,Loyal Customer,67,Personal Travel,Eco,290,3,4,3,3,3,4,4,2,2,3,1,3,2,4,0,0.0,neutral or dissatisfied +72720,91937,Male,Loyal Customer,42,Business travel,Business,975,4,4,4,4,5,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +72721,122499,Male,disloyal Customer,35,Business travel,Business,930,1,1,1,3,4,1,4,4,4,4,5,4,4,4,10,13.0,neutral or dissatisfied +72722,30512,Female,Loyal Customer,41,Personal Travel,Eco,349,2,4,2,3,4,2,4,4,4,3,4,3,4,4,7,9.0,neutral or dissatisfied +72723,4078,Male,Loyal Customer,58,Business travel,Business,431,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +72724,114091,Male,Loyal Customer,36,Personal Travel,Eco,1947,4,4,4,3,4,4,4,4,3,2,5,3,5,4,20,0.0,satisfied +72725,77720,Male,Loyal Customer,51,Business travel,Business,689,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +72726,12238,Male,Loyal Customer,31,Business travel,Eco,253,5,3,3,3,5,5,5,5,2,1,2,1,3,5,0,0.0,satisfied +72727,46435,Male,Loyal Customer,45,Personal Travel,Eco Plus,458,4,4,4,2,3,4,3,3,3,5,5,4,5,3,0,13.0,neutral or dissatisfied +72728,44630,Male,Loyal Customer,63,Personal Travel,Business,67,2,5,2,3,2,5,4,3,3,2,3,3,3,5,61,65.0,neutral or dissatisfied +72729,96914,Male,Loyal Customer,47,Personal Travel,Eco,781,3,5,3,2,5,3,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +72730,68145,Male,Loyal Customer,41,Business travel,Business,2142,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +72731,2495,Female,Loyal Customer,62,Personal Travel,Eco,1379,2,4,2,2,2,3,5,2,2,2,2,3,2,4,56,58.0,neutral or dissatisfied +72732,53432,Female,disloyal Customer,36,Business travel,Eco,767,2,2,2,3,4,2,4,4,5,1,5,3,2,4,24,19.0,neutral or dissatisfied +72733,68193,Female,disloyal Customer,50,Business travel,Eco Plus,203,4,5,5,5,5,4,5,5,5,3,1,2,2,5,0,0.0,satisfied +72734,102860,Female,disloyal Customer,26,Business travel,Business,423,2,0,2,1,3,2,3,3,5,2,4,4,4,3,0,5.0,neutral or dissatisfied +72735,109273,Female,Loyal Customer,54,Personal Travel,Eco Plus,684,1,1,1,4,5,3,3,4,4,1,4,1,4,3,26,29.0,neutral or dissatisfied +72736,105738,Male,Loyal Customer,26,Business travel,Business,925,2,2,2,2,2,2,2,2,2,5,1,4,1,2,3,0.0,neutral or dissatisfied +72737,42974,Female,Loyal Customer,26,Business travel,Eco,192,5,4,4,4,5,4,3,5,5,4,4,4,3,5,0,8.0,satisfied +72738,18773,Male,Loyal Customer,54,Business travel,Business,2896,2,3,3,3,2,3,4,2,2,2,2,2,2,4,5,3.0,neutral or dissatisfied +72739,38709,Female,Loyal Customer,60,Business travel,Business,2583,2,3,3,3,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +72740,79786,Female,Loyal Customer,43,Business travel,Business,944,5,5,5,5,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +72741,121352,Female,Loyal Customer,53,Personal Travel,Eco,430,1,5,1,3,2,5,4,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +72742,81413,Female,Loyal Customer,40,Business travel,Business,448,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +72743,46338,Female,disloyal Customer,36,Business travel,Eco,589,3,0,3,4,5,3,5,5,2,3,2,1,1,5,57,75.0,neutral or dissatisfied +72744,10132,Female,Loyal Customer,50,Personal Travel,Eco,946,3,4,3,4,2,3,4,1,1,3,1,2,1,3,19,24.0,neutral or dissatisfied +72745,115645,Male,Loyal Customer,63,Business travel,Eco,358,1,4,4,4,1,1,1,1,4,1,3,4,4,1,0,0.0,neutral or dissatisfied +72746,80351,Female,Loyal Customer,19,Personal Travel,Business,422,2,0,2,2,3,2,3,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +72747,79795,Male,Loyal Customer,59,Business travel,Business,944,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +72748,27264,Female,Loyal Customer,57,Business travel,Business,679,5,5,5,5,5,5,4,5,5,5,5,3,5,3,2,0.0,satisfied +72749,76385,Male,Loyal Customer,39,Business travel,Business,2436,1,2,2,2,4,4,3,1,1,1,1,4,1,2,0,13.0,neutral or dissatisfied +72750,13931,Male,disloyal Customer,20,Business travel,Eco,192,4,5,4,1,4,4,5,4,1,3,4,3,5,4,0,0.0,satisfied +72751,54140,Male,Loyal Customer,40,Business travel,Business,1400,3,2,2,2,3,3,3,3,4,4,3,3,3,3,276,255.0,neutral or dissatisfied +72752,60467,Male,Loyal Customer,55,Business travel,Business,934,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +72753,41302,Male,disloyal Customer,15,Business travel,Eco,802,5,5,5,1,5,5,5,5,4,3,4,3,4,5,55,31.0,satisfied +72754,79468,Male,Loyal Customer,56,Personal Travel,Eco,1183,2,2,2,4,5,2,5,5,1,4,2,1,4,5,23,0.0,neutral or dissatisfied +72755,6087,Male,Loyal Customer,44,Business travel,Business,3037,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +72756,73508,Male,Loyal Customer,46,Business travel,Eco Plus,1005,3,1,3,1,3,3,3,3,4,2,2,1,3,3,96,83.0,neutral or dissatisfied +72757,99939,Female,Loyal Customer,36,Personal Travel,Eco Plus,764,2,4,2,1,5,2,5,5,4,3,3,4,3,5,0,14.0,neutral or dissatisfied +72758,110268,Female,Loyal Customer,29,Business travel,Business,919,3,2,3,3,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +72759,68530,Female,disloyal Customer,35,Business travel,Business,1013,2,2,2,4,4,2,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +72760,11267,Male,Loyal Customer,16,Personal Travel,Eco,308,3,5,3,2,5,3,5,5,5,2,4,1,5,5,12,21.0,neutral or dissatisfied +72761,71294,Male,Loyal Customer,40,Personal Travel,Eco Plus,733,4,2,5,2,2,5,1,2,4,5,1,3,1,2,0,0.0,neutral or dissatisfied +72762,12385,Male,Loyal Customer,48,Business travel,Business,253,4,4,4,4,4,3,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +72763,30457,Male,Loyal Customer,25,Personal Travel,Eco,991,2,1,2,4,4,2,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +72764,36351,Male,disloyal Customer,27,Business travel,Eco Plus,187,2,2,2,3,3,2,3,3,2,5,4,5,1,3,3,2.0,neutral or dissatisfied +72765,66682,Male,Loyal Customer,57,Business travel,Business,802,1,1,1,1,2,4,5,4,4,4,4,4,4,3,18,19.0,satisfied +72766,12939,Female,Loyal Customer,50,Personal Travel,Eco,563,3,5,3,3,3,3,2,5,5,3,3,4,5,4,0,0.0,neutral or dissatisfied +72767,9597,Male,Loyal Customer,18,Personal Travel,Eco,228,3,2,3,2,5,3,5,5,3,1,2,4,3,5,86,60.0,neutral or dissatisfied +72768,116349,Female,Loyal Customer,69,Personal Travel,Eco,404,4,2,1,3,3,4,3,2,2,1,2,4,2,3,2,0.0,neutral or dissatisfied +72769,61680,Male,Loyal Customer,48,Business travel,Business,1346,3,5,5,5,5,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +72770,73432,Male,Loyal Customer,45,Personal Travel,Eco,1120,4,1,5,3,5,5,5,5,2,1,4,4,3,5,0,0.0,neutral or dissatisfied +72771,4107,Female,Loyal Customer,48,Business travel,Business,2269,3,3,1,3,3,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +72772,56462,Male,Loyal Customer,59,Personal Travel,Eco,719,3,4,3,4,1,3,4,1,5,2,4,5,4,1,21,20.0,neutral or dissatisfied +72773,65149,Female,Loyal Customer,63,Personal Travel,Eco,551,4,3,4,3,2,3,3,3,3,4,5,3,3,4,0,0.0,neutral or dissatisfied +72774,120413,Male,disloyal Customer,22,Business travel,Business,366,2,1,2,2,5,2,5,5,2,1,2,3,2,5,26,22.0,neutral or dissatisfied +72775,71552,Male,Loyal Customer,30,Business travel,Business,1197,4,4,4,4,5,5,5,5,4,2,5,3,5,5,0,0.0,satisfied +72776,53870,Female,Loyal Customer,44,Business travel,Eco,191,2,4,4,4,3,1,3,2,2,2,2,3,2,1,1,0.0,satisfied +72777,59740,Female,Loyal Customer,29,Business travel,Business,1025,4,4,5,4,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +72778,16470,Male,Loyal Customer,58,Personal Travel,Eco,529,4,5,4,3,5,4,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +72779,4574,Male,disloyal Customer,42,Business travel,Business,416,3,3,3,4,4,3,4,4,2,3,4,3,3,4,0,13.0,neutral or dissatisfied +72780,119603,Female,Loyal Customer,37,Business travel,Business,2617,3,5,1,5,5,2,1,3,3,4,3,3,3,2,33,29.0,neutral or dissatisfied +72781,6685,Female,disloyal Customer,58,Business travel,Business,438,1,1,1,2,5,1,4,5,3,5,5,4,5,5,27,22.0,neutral or dissatisfied +72782,79818,Male,Loyal Customer,47,Business travel,Business,3094,1,1,1,1,5,4,4,2,2,3,2,4,2,4,0,3.0,satisfied +72783,45351,Female,Loyal Customer,20,Personal Travel,Eco,222,2,5,0,1,2,0,2,2,4,2,2,2,3,2,44,33.0,neutral or dissatisfied +72784,35505,Male,Loyal Customer,41,Personal Travel,Eco,1144,2,2,2,4,5,2,5,5,2,4,4,4,4,5,0,0.0,neutral or dissatisfied +72785,8161,Male,Loyal Customer,48,Business travel,Business,1981,5,5,5,5,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +72786,122713,Male,Loyal Customer,28,Personal Travel,Eco Plus,813,3,2,3,4,3,3,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +72787,46483,Female,Loyal Customer,50,Business travel,Business,3966,2,2,2,2,3,2,2,4,4,4,5,3,4,5,0,0.0,satisfied +72788,98947,Female,disloyal Customer,17,Business travel,Eco,569,3,0,3,1,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +72789,64897,Male,disloyal Customer,9,Business travel,Eco,551,5,0,5,3,1,5,1,1,4,2,4,5,4,1,0,0.0,satisfied +72790,126743,Female,Loyal Customer,23,Personal Travel,Eco,2402,0,5,1,4,1,1,1,1,5,5,4,3,5,1,0,0.0,satisfied +72791,76223,Female,Loyal Customer,29,Business travel,Business,1399,4,4,4,4,4,4,4,4,4,5,4,5,4,4,0,3.0,satisfied +72792,936,Male,Loyal Customer,44,Business travel,Business,2867,4,4,4,4,4,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +72793,113639,Male,Loyal Customer,27,Personal Travel,Eco,407,3,4,3,4,1,3,1,1,4,3,3,2,2,1,1,12.0,neutral or dissatisfied +72794,123414,Female,Loyal Customer,43,Business travel,Business,3000,2,2,2,2,1,3,1,5,5,5,5,2,5,2,27,0.0,satisfied +72795,17264,Male,Loyal Customer,34,Personal Travel,Eco,1092,2,3,2,2,3,2,3,3,3,4,1,5,2,3,0,0.0,neutral or dissatisfied +72796,111260,Female,Loyal Customer,41,Personal Travel,Eco Plus,1788,3,5,3,5,5,4,4,3,3,3,3,4,3,4,25,12.0,neutral or dissatisfied +72797,78473,Female,Loyal Customer,29,Business travel,Business,1800,2,2,2,2,4,4,4,4,5,5,4,4,4,4,19,11.0,satisfied +72798,105277,Female,Loyal Customer,45,Business travel,Business,1895,5,5,5,5,4,4,5,5,5,5,5,4,5,5,69,89.0,satisfied +72799,126058,Female,disloyal Customer,40,Business travel,Business,328,2,3,3,1,3,3,3,3,4,2,4,4,5,3,0,3.0,neutral or dissatisfied +72800,107248,Female,Loyal Customer,33,Business travel,Business,283,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +72801,62811,Female,Loyal Customer,47,Personal Travel,Eco,2399,1,4,1,1,4,4,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +72802,38768,Male,disloyal Customer,38,Business travel,Business,354,1,2,2,4,1,2,1,1,2,4,4,2,3,1,0,0.0,neutral or dissatisfied +72803,5208,Male,Loyal Customer,49,Business travel,Business,3068,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,20.0,satisfied +72804,65253,Female,disloyal Customer,43,Business travel,Eco Plus,354,2,2,2,3,3,2,1,3,3,3,4,4,3,3,0,3.0,neutral or dissatisfied +72805,105862,Male,Loyal Customer,46,Business travel,Eco Plus,525,3,1,1,1,3,3,3,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +72806,31531,Female,Loyal Customer,60,Personal Travel,Eco,853,3,3,2,4,4,4,4,2,2,2,2,1,2,3,106,115.0,neutral or dissatisfied +72807,11315,Male,Loyal Customer,11,Personal Travel,Eco,316,1,2,3,3,2,3,2,2,3,1,3,1,4,2,14,10.0,neutral or dissatisfied +72808,100343,Male,disloyal Customer,44,Business travel,Eco,692,4,3,3,2,3,3,1,3,4,1,2,4,3,3,90,76.0,neutral or dissatisfied +72809,2200,Female,Loyal Customer,61,Personal Travel,Eco,685,4,4,4,2,2,5,4,2,2,4,2,4,2,3,38,33.0,neutral or dissatisfied +72810,79054,Male,Loyal Customer,51,Business travel,Business,2607,3,4,4,4,3,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +72811,78397,Female,disloyal Customer,29,Business travel,Business,726,3,3,3,3,2,3,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +72812,91362,Male,Loyal Customer,50,Personal Travel,Eco Plus,581,3,4,3,4,4,3,4,4,4,3,2,2,3,4,0,0.0,neutral or dissatisfied +72813,121446,Female,Loyal Customer,34,Business travel,Business,331,4,4,3,4,4,3,3,4,4,4,4,2,4,4,9,10.0,neutral or dissatisfied +72814,1210,Female,Loyal Customer,53,Personal Travel,Eco,158,0,5,0,4,3,4,5,2,2,0,2,3,2,5,0,0.0,satisfied +72815,106900,Male,Loyal Customer,56,Personal Travel,Eco,577,0,4,0,2,2,0,1,2,5,3,4,3,5,2,1,0.0,satisfied +72816,43585,Female,Loyal Customer,62,Business travel,Business,2306,1,1,5,1,3,5,4,4,4,4,5,5,4,5,2,0.0,satisfied +72817,89128,Female,Loyal Customer,39,Business travel,Business,1892,5,5,5,5,3,3,4,5,5,5,5,3,5,4,1,0.0,satisfied +72818,29453,Female,Loyal Customer,37,Personal Travel,Eco,421,4,4,4,3,1,4,1,1,2,3,4,2,4,1,3,0.0,neutral or dissatisfied +72819,105663,Female,Loyal Customer,10,Business travel,Business,1586,2,5,5,5,2,2,2,2,3,2,3,2,3,2,0,24.0,neutral or dissatisfied +72820,120912,Female,disloyal Customer,25,Business travel,Business,992,1,5,1,3,3,1,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +72821,88217,Male,Loyal Customer,36,Business travel,Business,1646,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,5.0,satisfied +72822,24783,Female,Loyal Customer,43,Personal Travel,Eco,432,2,5,2,4,4,5,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +72823,77444,Male,Loyal Customer,47,Personal Travel,Eco Plus,626,2,2,2,3,2,2,4,2,2,2,4,4,3,2,8,4.0,neutral or dissatisfied +72824,103305,Female,Loyal Customer,26,Business travel,Business,1371,4,4,4,4,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +72825,95144,Male,Loyal Customer,8,Personal Travel,Eco,528,1,4,1,3,3,1,3,3,4,2,4,4,5,3,68,53.0,neutral or dissatisfied +72826,36013,Female,Loyal Customer,48,Business travel,Business,1925,2,2,2,2,3,1,1,5,5,5,5,2,5,4,0,0.0,satisfied +72827,7081,Female,Loyal Customer,23,Business travel,Business,2123,1,4,2,4,1,1,1,1,1,1,4,4,3,1,4,0.0,neutral or dissatisfied +72828,58196,Male,Loyal Customer,49,Business travel,Business,2928,1,3,3,3,3,3,4,1,1,1,1,3,1,3,1,25.0,neutral or dissatisfied +72829,78747,Female,Loyal Customer,56,Business travel,Business,432,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +72830,70738,Female,Loyal Customer,20,Personal Travel,Eco,675,3,4,3,2,3,3,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +72831,3807,Male,Loyal Customer,29,Business travel,Business,1727,2,2,2,2,5,5,5,5,3,2,5,3,5,5,8,0.0,satisfied +72832,68681,Male,disloyal Customer,36,Business travel,Eco,175,2,3,2,2,4,2,4,4,4,4,2,3,2,4,0,0.0,neutral or dissatisfied +72833,47032,Male,Loyal Customer,43,Business travel,Eco,639,5,5,5,5,5,5,5,5,5,5,5,1,3,5,2,0.0,satisfied +72834,49534,Male,Loyal Customer,38,Business travel,Business,190,0,5,0,4,5,3,3,3,3,3,3,2,3,5,0,0.0,satisfied +72835,59723,Female,disloyal Customer,17,Business travel,Eco Plus,964,2,2,2,4,2,2,2,2,2,4,3,4,3,2,50,49.0,neutral or dissatisfied +72836,129805,Female,Loyal Customer,7,Personal Travel,Eco,447,5,4,5,2,1,5,1,1,3,4,5,4,4,1,0,0.0,satisfied +72837,10660,Female,Loyal Customer,45,Business travel,Business,2394,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +72838,82952,Female,Loyal Customer,54,Business travel,Business,1885,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +72839,129344,Male,Loyal Customer,64,Personal Travel,Eco,2586,2,4,3,4,1,3,1,1,1,1,3,4,4,1,8,1.0,neutral or dissatisfied +72840,109842,Male,Loyal Customer,49,Business travel,Business,1053,3,3,1,3,3,2,2,4,4,5,4,2,5,2,209,199.0,satisfied +72841,86835,Male,Loyal Customer,33,Business travel,Business,1905,4,1,1,1,4,4,4,4,2,3,3,3,4,4,18,13.0,neutral or dissatisfied +72842,78843,Male,Loyal Customer,22,Personal Travel,Eco,554,1,5,1,2,5,1,5,5,3,1,1,1,3,5,6,0.0,neutral or dissatisfied +72843,30797,Female,Loyal Customer,38,Business travel,Business,301,3,5,5,5,3,1,1,3,3,3,3,3,3,1,127,116.0,neutral or dissatisfied +72844,118341,Female,Loyal Customer,47,Business travel,Business,202,0,5,0,3,4,3,1,4,4,4,4,3,4,2,23,26.0,satisfied +72845,3646,Male,Loyal Customer,38,Business travel,Business,3150,5,5,5,5,3,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +72846,82800,Male,Loyal Customer,56,Business travel,Business,2960,0,1,1,3,5,5,4,5,5,5,5,4,5,5,0,10.0,satisfied +72847,30701,Female,Loyal Customer,12,Personal Travel,Eco,680,1,4,1,2,4,1,4,4,4,5,5,5,5,4,75,76.0,neutral or dissatisfied +72848,123564,Male,disloyal Customer,20,Business travel,Eco,829,4,4,4,4,1,4,3,1,5,5,5,3,5,1,2,0.0,satisfied +72849,39702,Female,disloyal Customer,24,Business travel,Eco,162,0,0,0,1,4,0,4,4,3,2,3,1,2,4,0,0.0,satisfied +72850,76808,Female,Loyal Customer,43,Personal Travel,Eco,689,4,5,4,3,3,4,4,2,2,4,2,4,2,5,0,6.0,neutral or dissatisfied +72851,30276,Female,Loyal Customer,14,Personal Travel,Eco,1024,2,5,2,2,3,2,3,3,5,4,4,2,5,3,0,0.0,neutral or dissatisfied +72852,87444,Male,Loyal Customer,61,Business travel,Eco,321,3,4,4,4,3,3,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +72853,2203,Female,Loyal Customer,67,Personal Travel,Eco,685,3,5,3,3,5,4,4,4,4,3,4,5,4,4,0,7.0,neutral or dissatisfied +72854,120168,Male,Loyal Customer,29,Business travel,Business,335,2,2,2,2,5,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +72855,26857,Male,Loyal Customer,17,Personal Travel,Eco,224,2,4,2,1,2,2,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +72856,93829,Female,Loyal Customer,54,Business travel,Business,3149,3,3,3,3,4,5,4,4,4,4,4,5,4,5,23,7.0,satisfied +72857,19830,Male,Loyal Customer,50,Personal Travel,Eco,413,3,1,3,2,2,3,2,2,2,3,1,1,1,2,42,55.0,neutral or dissatisfied +72858,126520,Female,disloyal Customer,26,Business travel,Eco,196,2,3,2,3,2,2,2,2,1,1,3,4,4,2,0,17.0,neutral or dissatisfied +72859,117685,Male,disloyal Customer,25,Business travel,Eco,2075,3,3,3,4,5,3,5,5,5,4,4,5,4,5,76,99.0,neutral or dissatisfied +72860,51943,Male,disloyal Customer,37,Business travel,Business,347,2,2,2,3,1,2,1,1,1,5,4,5,3,1,0,0.0,neutral or dissatisfied +72861,75376,Female,Loyal Customer,45,Business travel,Business,2342,5,5,5,5,3,3,4,5,5,5,5,4,5,3,111,95.0,satisfied +72862,123383,Male,Loyal Customer,70,Personal Travel,Eco Plus,644,1,5,1,4,2,1,2,2,3,5,4,5,4,2,0,2.0,neutral or dissatisfied +72863,61055,Male,disloyal Customer,26,Business travel,Business,1607,2,2,2,1,1,2,4,1,3,4,4,3,4,1,13,28.0,neutral or dissatisfied +72864,78345,Female,Loyal Customer,16,Personal Travel,Eco,1547,5,1,5,2,1,5,4,1,3,1,1,1,2,1,0,0.0,satisfied +72865,98614,Male,Loyal Customer,49,Business travel,Business,3231,3,3,3,3,5,5,5,5,5,5,5,3,5,5,12,0.0,satisfied +72866,26122,Female,Loyal Customer,64,Personal Travel,Business,581,4,4,3,4,5,4,4,2,2,3,2,4,2,5,0,0.0,satisfied +72867,94656,Male,disloyal Customer,44,Business travel,Eco,248,1,4,0,3,3,0,3,3,3,1,4,4,4,3,0,17.0,neutral or dissatisfied +72868,82677,Female,Loyal Customer,41,Business travel,Business,3780,4,4,4,4,4,5,5,4,4,4,4,5,4,3,2,0.0,satisfied +72869,61020,Female,Loyal Customer,35,Business travel,Eco,3365,3,5,5,5,2,3,3,2,3,3,4,3,3,3,0,3.0,neutral or dissatisfied +72870,24975,Female,Loyal Customer,51,Business travel,Business,2338,4,4,2,4,2,4,2,4,4,4,4,1,4,4,0,0.0,satisfied +72871,43968,Female,Loyal Customer,9,Personal Travel,Eco,596,4,4,4,4,4,4,4,4,2,2,4,1,4,4,0,0.0,satisfied +72872,80715,Female,Loyal Customer,22,Business travel,Business,3001,1,4,4,4,1,2,1,1,4,2,3,3,4,1,7,14.0,neutral or dissatisfied +72873,102267,Male,Loyal Customer,57,Business travel,Business,3259,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +72874,98380,Male,Loyal Customer,21,Personal Travel,Eco Plus,1189,2,4,2,2,5,2,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +72875,93792,Male,Loyal Customer,44,Business travel,Business,2189,1,1,1,1,5,4,5,4,4,4,4,5,4,4,2,0.0,satisfied +72876,108034,Male,Loyal Customer,61,Business travel,Business,306,2,5,5,5,5,3,3,2,2,2,2,2,2,2,7,8.0,neutral or dissatisfied +72877,28249,Male,Loyal Customer,9,Personal Travel,Business,1542,4,5,4,3,5,4,5,5,3,4,3,4,5,5,0,0.0,neutral or dissatisfied +72878,9183,Female,Loyal Customer,49,Business travel,Business,2510,4,4,4,4,2,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +72879,71900,Male,Loyal Customer,40,Personal Travel,Eco,1726,4,4,4,1,4,4,4,4,3,4,4,4,5,4,0,4.0,satisfied +72880,99477,Female,Loyal Customer,44,Business travel,Eco,307,1,3,3,3,2,3,4,1,1,1,1,3,1,3,61,55.0,neutral or dissatisfied +72881,67649,Male,Loyal Customer,49,Business travel,Business,1313,3,3,3,3,3,5,4,4,4,4,4,5,4,4,15,4.0,satisfied +72882,65266,Male,Loyal Customer,47,Business travel,Eco Plus,190,4,4,4,4,4,4,4,4,3,3,1,4,2,4,0,0.0,satisfied +72883,37101,Female,Loyal Customer,52,Business travel,Eco,1046,5,1,1,1,5,4,4,1,4,3,2,4,3,4,138,130.0,satisfied +72884,16678,Female,Loyal Customer,56,Personal Travel,Eco,488,1,2,2,2,3,2,3,2,2,2,2,4,2,4,2,1.0,neutral or dissatisfied +72885,83866,Female,disloyal Customer,42,Business travel,Business,425,4,4,4,2,2,4,4,2,4,4,4,3,5,2,7,1.0,satisfied +72886,27322,Female,Loyal Customer,40,Business travel,Eco,679,5,3,3,3,5,5,5,5,1,3,5,3,2,5,0,0.0,satisfied +72887,115628,Male,Loyal Customer,47,Business travel,Business,337,2,5,5,5,1,1,2,2,2,2,2,1,2,3,29,21.0,neutral or dissatisfied +72888,4556,Female,Loyal Customer,44,Business travel,Eco,561,2,2,4,2,5,1,1,2,2,2,2,1,2,3,15,29.0,neutral or dissatisfied +72889,74138,Female,Loyal Customer,47,Business travel,Business,2647,1,1,1,1,3,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +72890,19286,Male,Loyal Customer,38,Business travel,Eco,299,3,4,2,2,3,4,3,3,5,2,3,3,1,3,49,61.0,satisfied +72891,103263,Male,Loyal Customer,30,Business travel,Business,1916,3,3,3,3,4,4,4,4,3,5,4,4,5,4,12,55.0,satisfied +72892,4869,Male,Loyal Customer,54,Personal Travel,Eco,408,3,5,2,3,3,2,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +72893,71369,Male,Loyal Customer,59,Business travel,Business,2530,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +72894,33381,Female,Loyal Customer,28,Personal Travel,Eco,2355,3,1,3,2,3,3,3,3,1,1,1,4,3,3,0,0.0,neutral or dissatisfied +72895,60069,Male,Loyal Customer,29,Personal Travel,Business,1144,1,4,1,3,3,1,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +72896,39776,Female,Loyal Customer,35,Personal Travel,Eco,521,2,5,4,4,5,4,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +72897,78218,Male,Loyal Customer,49,Personal Travel,Eco,153,1,5,1,3,3,1,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +72898,95306,Male,Loyal Customer,21,Personal Travel,Eco,293,1,5,1,2,4,1,4,4,4,2,4,4,5,4,38,27.0,neutral or dissatisfied +72899,101961,Female,Loyal Customer,63,Business travel,Business,628,3,5,5,5,2,3,4,3,3,3,3,3,3,3,11,0.0,neutral or dissatisfied +72900,23292,Male,disloyal Customer,42,Business travel,Business,359,2,2,2,2,5,2,5,5,3,1,5,5,3,5,0,0.0,satisfied +72901,20892,Female,disloyal Customer,22,Business travel,Eco,961,0,0,0,3,4,0,4,4,2,5,1,5,4,4,102,82.0,satisfied +72902,105635,Female,Loyal Customer,23,Business travel,Business,2531,2,2,1,2,4,4,4,4,4,4,4,5,5,4,0,1.0,satisfied +72903,5242,Female,Loyal Customer,48,Business travel,Business,383,1,1,1,1,2,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +72904,45522,Male,Loyal Customer,38,Personal Travel,Eco,689,3,4,3,2,3,3,3,3,4,4,4,3,5,3,0,4.0,neutral or dissatisfied +72905,96953,Female,Loyal Customer,54,Business travel,Business,359,3,3,3,3,3,5,4,5,5,5,5,4,5,3,9,10.0,satisfied +72906,59300,Female,Loyal Customer,58,Business travel,Business,2556,2,2,4,2,4,3,4,5,5,5,5,4,5,3,38,0.0,satisfied +72907,79740,Male,Loyal Customer,32,Business travel,Eco Plus,762,1,2,2,2,1,1,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +72908,101123,Female,Loyal Customer,50,Business travel,Business,3872,3,3,3,3,4,5,5,5,5,5,5,5,5,5,10,13.0,satisfied +72909,58579,Female,Loyal Customer,53,Personal Travel,Eco,403,2,4,2,1,4,5,5,5,5,2,5,3,5,5,67,78.0,neutral or dissatisfied +72910,77416,Female,Loyal Customer,38,Personal Travel,Eco,590,5,5,5,3,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +72911,107023,Male,Loyal Customer,41,Business travel,Business,395,4,4,4,4,3,4,4,5,5,5,5,3,5,5,8,8.0,satisfied +72912,117221,Female,Loyal Customer,20,Personal Travel,Eco,368,2,3,5,3,2,5,2,2,3,3,4,4,3,2,14,5.0,neutral or dissatisfied +72913,95693,Female,Loyal Customer,60,Business travel,Business,1827,1,1,1,1,3,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +72914,112996,Female,disloyal Customer,28,Business travel,Business,1797,4,4,4,3,3,4,3,3,4,4,3,3,5,3,0,0.0,neutral or dissatisfied +72915,10747,Female,Loyal Customer,56,Business travel,Business,201,1,1,1,1,4,4,5,5,5,5,5,5,5,5,63,60.0,satisfied +72916,21169,Male,Loyal Customer,62,Business travel,Business,2165,0,5,1,1,2,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +72917,120422,Male,Loyal Customer,51,Business travel,Eco,449,1,3,3,3,1,2,2,2,1,3,3,2,2,2,145,166.0,neutral or dissatisfied +72918,114923,Female,Loyal Customer,60,Business travel,Business,2290,3,3,3,3,2,5,4,5,5,5,5,5,5,3,22,19.0,satisfied +72919,13290,Female,disloyal Customer,30,Business travel,Eco Plus,468,2,2,2,1,5,2,3,5,3,2,1,1,1,5,30,16.0,neutral or dissatisfied +72920,117734,Male,Loyal Customer,33,Business travel,Business,2334,4,4,4,4,5,4,5,5,5,4,4,3,4,5,11,9.0,satisfied +72921,126418,Male,Loyal Customer,62,Business travel,Business,2792,3,3,3,3,5,4,4,4,4,4,4,5,4,5,8,0.0,satisfied +72922,93366,Male,Loyal Customer,51,Personal Travel,Eco,1024,1,3,1,4,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +72923,91686,Female,Loyal Customer,41,Business travel,Business,2806,2,5,5,5,5,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +72924,128139,Female,Loyal Customer,37,Business travel,Business,288,3,4,4,4,3,3,3,3,3,3,3,1,3,4,10,0.0,neutral or dissatisfied +72925,122250,Female,disloyal Customer,23,Business travel,Eco,144,4,0,4,3,3,4,4,3,4,4,5,3,3,3,0,0.0,neutral or dissatisfied +72926,123645,Female,Loyal Customer,40,Business travel,Business,3752,0,5,0,2,2,5,4,1,1,1,1,4,1,3,11,0.0,satisfied +72927,43278,Male,Loyal Customer,51,Business travel,Business,1554,4,4,4,4,4,4,4,4,4,4,4,4,4,2,0,0.0,satisfied +72928,39011,Female,disloyal Customer,29,Business travel,Eco,230,1,0,1,5,2,1,2,2,3,1,3,1,1,2,0,0.0,neutral or dissatisfied +72929,67905,Female,Loyal Customer,70,Personal Travel,Eco,1235,3,5,2,4,4,2,2,5,5,2,5,1,5,5,84,70.0,neutral or dissatisfied +72930,22956,Male,Loyal Customer,49,Business travel,Business,2092,5,5,3,5,3,1,5,4,4,4,4,4,4,5,0,0.0,satisfied +72931,65949,Male,Loyal Customer,30,Business travel,Business,1372,5,5,5,5,4,4,4,4,3,2,4,4,5,4,0,0.0,satisfied +72932,36814,Female,Loyal Customer,31,Personal Travel,Eco,2300,1,5,1,3,1,1,1,4,2,5,4,1,4,1,0,0.0,neutral or dissatisfied +72933,103366,Male,Loyal Customer,33,Business travel,Business,1870,4,4,4,4,5,5,5,5,4,4,3,1,1,5,11,4.0,satisfied +72934,57614,Male,Loyal Customer,53,Business travel,Business,2623,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +72935,10064,Male,Loyal Customer,22,Business travel,Business,2943,3,1,1,1,3,3,3,3,2,2,4,1,4,3,0,2.0,neutral or dissatisfied +72936,108710,Female,Loyal Customer,27,Personal Travel,Eco,425,2,0,4,1,1,4,1,1,4,4,5,5,5,1,10,6.0,neutral or dissatisfied +72937,9242,Female,Loyal Customer,35,Business travel,Business,1629,3,5,5,5,4,4,4,2,2,2,3,2,2,1,28,22.0,neutral or dissatisfied +72938,101438,Male,Loyal Customer,39,Business travel,Business,345,2,2,2,2,5,5,4,5,5,4,5,3,5,5,11,1.0,satisfied +72939,84176,Female,Loyal Customer,51,Personal Travel,Eco,231,2,5,2,2,4,5,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +72940,71480,Male,Loyal Customer,45,Business travel,Eco,4243,3,1,1,1,3,3,3,1,2,1,2,3,1,3,4,19.0,neutral or dissatisfied +72941,5617,Male,Loyal Customer,36,Business travel,Business,3595,3,4,4,4,1,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +72942,57362,Female,Loyal Customer,69,Personal Travel,Eco,236,3,4,3,2,4,4,4,2,2,3,5,5,2,4,3,0.0,neutral or dissatisfied +72943,105874,Female,Loyal Customer,46,Business travel,Business,3833,2,2,5,2,2,4,5,3,3,4,3,3,3,4,34,67.0,satisfied +72944,103975,Female,Loyal Customer,17,Personal Travel,Eco Plus,533,1,3,3,4,4,3,4,4,1,1,3,2,3,4,55,49.0,neutral or dissatisfied +72945,79766,Male,disloyal Customer,27,Business travel,Business,1035,1,1,1,3,1,1,1,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +72946,107803,Male,Loyal Customer,39,Business travel,Business,2633,4,4,4,4,5,5,5,4,4,4,4,5,4,5,4,8.0,satisfied +72947,35511,Male,Loyal Customer,49,Personal Travel,Eco,1069,3,4,3,1,4,3,4,4,5,2,5,3,3,4,0,0.0,neutral or dissatisfied +72948,118018,Male,Loyal Customer,68,Personal Travel,Eco,1037,4,5,4,5,1,4,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +72949,18672,Female,Loyal Customer,41,Personal Travel,Eco,190,5,2,5,3,5,5,2,5,1,2,4,4,4,5,0,0.0,satisfied +72950,21046,Female,Loyal Customer,56,Business travel,Business,2154,4,4,4,4,2,1,4,5,5,4,5,2,5,1,0,0.0,satisfied +72951,7307,Male,Loyal Customer,36,Business travel,Eco Plus,139,1,1,5,1,1,1,1,3,4,3,4,1,2,1,165,194.0,neutral or dissatisfied +72952,110788,Male,disloyal Customer,72,Business travel,Business,1166,3,3,3,4,2,3,4,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +72953,40616,Female,Loyal Customer,54,Personal Travel,Eco,411,2,5,2,5,2,5,5,4,4,2,4,5,4,3,26,13.0,neutral or dissatisfied +72954,84200,Male,Loyal Customer,43,Business travel,Business,1856,5,5,5,5,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +72955,128075,Female,Loyal Customer,39,Business travel,Business,2917,1,1,2,1,4,4,4,4,3,4,5,4,5,4,45,28.0,satisfied +72956,7245,Female,Loyal Customer,27,Personal Travel,Eco,135,4,0,4,3,3,4,3,3,1,4,5,3,4,3,0,0.0,satisfied +72957,127536,Male,Loyal Customer,25,Business travel,Business,3897,1,1,1,1,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +72958,112077,Female,Loyal Customer,54,Business travel,Eco,1491,3,1,4,1,2,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +72959,74623,Female,Loyal Customer,41,Business travel,Eco,835,4,5,5,5,4,4,4,4,1,5,1,5,1,4,78,69.0,satisfied +72960,89667,Male,Loyal Customer,46,Business travel,Eco,1096,2,4,3,4,2,2,2,2,3,5,2,1,2,2,67,113.0,neutral or dissatisfied +72961,127938,Female,Loyal Customer,17,Personal Travel,Eco,2300,1,4,1,4,2,1,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +72962,35851,Female,Loyal Customer,25,Business travel,Eco,1068,2,4,1,4,2,2,2,2,4,2,4,4,4,2,0,19.0,neutral or dissatisfied +72963,112038,Male,Loyal Customer,51,Business travel,Business,1689,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +72964,40966,Female,Loyal Customer,48,Business travel,Business,3256,5,5,5,5,2,1,3,2,2,2,2,5,2,3,0,0.0,satisfied +72965,87507,Female,Loyal Customer,15,Personal Travel,Eco,373,2,1,1,2,5,1,5,5,3,2,2,2,1,5,0,0.0,neutral or dissatisfied +72966,32289,Female,Loyal Customer,31,Business travel,Business,102,0,3,0,4,5,5,5,5,5,1,2,3,5,5,0,0.0,satisfied +72967,63048,Male,Loyal Customer,65,Personal Travel,Eco,948,3,1,4,3,2,4,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +72968,129264,Male,Loyal Customer,43,Business travel,Business,2402,2,2,2,2,4,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +72969,25177,Male,Loyal Customer,30,Business travel,Business,2845,5,5,5,5,1,2,1,1,3,4,3,5,1,1,0,0.0,satisfied +72970,24686,Male,Loyal Customer,44,Business travel,Business,2339,3,3,3,3,5,4,1,4,4,4,4,4,4,4,0,0.0,satisfied +72971,14695,Female,Loyal Customer,35,Business travel,Eco,419,4,1,1,1,4,4,4,4,3,4,5,2,5,4,77,82.0,satisfied +72972,86020,Female,Loyal Customer,22,Business travel,Eco,154,5,5,5,5,5,5,3,5,4,2,2,3,5,5,0,0.0,satisfied +72973,39134,Female,Loyal Customer,40,Personal Travel,Eco,190,1,5,1,2,2,1,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +72974,94622,Female,Loyal Customer,56,Business travel,Business,248,3,3,3,3,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +72975,128635,Female,Loyal Customer,65,Personal Travel,Eco,679,4,4,4,3,3,4,5,2,2,4,1,5,2,4,0,0.0,neutral or dissatisfied +72976,128259,Male,Loyal Customer,50,Business travel,Business,3776,2,3,3,3,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +72977,89389,Male,Loyal Customer,33,Business travel,Business,151,3,3,3,3,5,5,5,5,5,4,5,5,5,5,0,2.0,satisfied +72978,115491,Male,Loyal Customer,47,Business travel,Business,417,2,3,3,3,3,4,3,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +72979,122079,Male,Loyal Customer,42,Personal Travel,Eco,130,3,1,3,3,4,3,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +72980,36600,Female,Loyal Customer,38,Business travel,Business,1237,4,4,4,4,2,3,3,4,4,4,4,3,4,1,0,0.0,satisfied +72981,40371,Male,Loyal Customer,44,Business travel,Business,2354,5,4,4,4,4,3,4,5,5,4,5,2,5,4,11,16.0,neutral or dissatisfied +72982,98129,Male,Loyal Customer,57,Personal Travel,Eco,472,5,3,5,1,2,5,2,2,2,2,1,3,2,2,0,0.0,satisfied +72983,83072,Male,disloyal Customer,14,Business travel,Eco,1084,1,1,1,4,5,1,1,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +72984,107318,Female,Loyal Customer,50,Business travel,Business,1955,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +72985,102635,Male,Loyal Customer,40,Business travel,Business,2169,4,4,4,4,4,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +72986,92971,Male,Loyal Customer,25,Personal Travel,Business,738,4,5,3,2,1,3,1,1,4,3,5,3,4,1,10,10.0,satisfied +72987,39949,Male,Loyal Customer,26,Personal Travel,Eco,1195,2,5,3,3,2,3,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +72988,75060,Female,Loyal Customer,60,Business travel,Business,2611,4,4,4,4,3,5,4,4,4,5,4,5,4,3,64,46.0,satisfied +72989,13232,Female,Loyal Customer,29,Business travel,Business,3268,3,3,3,3,4,4,4,4,4,4,4,4,1,4,9,0.0,satisfied +72990,127119,Female,Loyal Customer,42,Personal Travel,Eco,370,3,1,3,3,3,2,2,4,4,3,4,3,4,1,28,27.0,neutral or dissatisfied +72991,114343,Male,Loyal Customer,61,Personal Travel,Eco,850,3,4,3,4,4,3,4,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +72992,8269,Female,Loyal Customer,64,Personal Travel,Eco,125,1,4,1,5,2,3,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +72993,110436,Female,Loyal Customer,11,Personal Travel,Eco,663,3,1,3,3,2,3,2,2,2,3,2,2,4,2,0,0.0,neutral or dissatisfied +72994,88080,Male,Loyal Customer,34,Business travel,Business,3080,5,5,4,5,3,4,5,5,5,5,5,5,5,4,8,0.0,satisfied +72995,78522,Female,Loyal Customer,20,Personal Travel,Eco,526,2,4,2,2,4,2,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +72996,6563,Female,Loyal Customer,51,Business travel,Business,3906,2,2,2,2,2,5,4,3,3,3,3,5,3,5,2,2.0,satisfied +72997,6668,Male,Loyal Customer,39,Business travel,Business,3313,1,5,1,1,3,4,5,1,1,2,1,3,1,3,0,0.0,satisfied +72998,36560,Female,Loyal Customer,50,Business travel,Business,1609,3,1,3,3,2,2,1,5,5,5,5,5,5,1,0,0.0,satisfied +72999,29943,Female,Loyal Customer,44,Business travel,Business,3989,1,1,1,1,2,3,4,4,4,4,4,2,4,1,0,0.0,satisfied +73000,22621,Male,Loyal Customer,55,Personal Travel,Eco,300,3,4,3,1,5,3,5,5,5,4,5,4,5,5,5,0.0,neutral or dissatisfied +73001,77036,Female,Loyal Customer,36,Personal Travel,Eco,368,4,4,4,3,1,4,1,1,5,4,2,2,2,1,8,0.0,neutral or dissatisfied +73002,76064,Female,disloyal Customer,21,Business travel,Eco,669,2,3,2,4,1,2,1,1,4,3,4,3,4,1,6,6.0,neutral or dissatisfied +73003,6249,Female,Loyal Customer,45,Personal Travel,Eco,413,3,4,5,3,2,5,5,5,5,5,5,4,5,3,82,85.0,neutral or dissatisfied +73004,69588,Male,Loyal Customer,18,Personal Travel,Eco,2475,2,4,2,2,2,1,1,5,2,5,5,1,4,1,0,0.0,neutral or dissatisfied +73005,122333,Male,Loyal Customer,24,Personal Travel,Eco Plus,546,2,3,2,3,2,2,2,2,5,4,4,2,1,2,59,37.0,neutral or dissatisfied +73006,45920,Male,Loyal Customer,66,Business travel,Business,513,4,4,4,4,1,2,5,4,4,4,4,4,4,2,13,0.0,satisfied +73007,44261,Female,Loyal Customer,32,Personal Travel,Eco,118,1,5,1,3,4,1,4,4,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +73008,59261,Female,disloyal Customer,27,Business travel,Business,4963,0,0,0,3,0,5,2,5,2,4,5,2,3,2,0,0.0,satisfied +73009,59843,Male,Loyal Customer,54,Business travel,Business,3000,2,2,2,2,2,4,4,5,5,5,5,3,5,3,16,4.0,satisfied +73010,6060,Male,Loyal Customer,18,Personal Travel,Eco,691,3,4,3,2,4,3,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +73011,112249,Male,Loyal Customer,31,Business travel,Business,1506,3,3,3,3,3,3,3,3,4,4,5,4,4,3,6,0.0,satisfied +73012,98100,Male,Loyal Customer,44,Personal Travel,Eco,439,4,4,3,2,3,3,3,3,3,4,4,5,5,3,0,0.0,satisfied +73013,124697,Female,disloyal Customer,46,Business travel,Eco,399,2,4,2,4,2,2,2,2,3,3,3,2,4,2,41,64.0,neutral or dissatisfied +73014,106947,Female,Loyal Customer,40,Business travel,Business,2023,5,5,5,5,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +73015,90911,Female,disloyal Customer,23,Business travel,Eco,366,2,3,2,4,5,2,5,5,3,5,3,2,3,5,0,0.0,neutral or dissatisfied +73016,87559,Female,Loyal Customer,46,Business travel,Business,432,5,5,5,5,5,5,5,2,2,2,2,5,2,4,55,48.0,satisfied +73017,717,Female,Loyal Customer,44,Business travel,Business,1915,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +73018,95504,Male,disloyal Customer,47,Business travel,Eco Plus,441,3,4,4,3,5,3,1,5,1,1,3,3,3,5,0,0.0,neutral or dissatisfied +73019,19335,Male,Loyal Customer,18,Personal Travel,Eco,694,3,5,3,3,4,3,4,4,5,2,4,5,5,4,0,9.0,neutral or dissatisfied +73020,99826,Male,Loyal Customer,46,Business travel,Business,2086,1,1,1,1,2,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +73021,25285,Male,Loyal Customer,44,Business travel,Business,321,2,2,2,2,4,3,3,5,5,5,5,4,5,1,7,1.0,satisfied +73022,78661,Female,Loyal Customer,44,Personal Travel,Eco Plus,2172,4,4,3,3,3,4,5,2,2,3,2,3,2,3,0,0.0,satisfied +73023,109252,Female,Loyal Customer,16,Personal Travel,Eco,616,2,4,2,4,2,2,1,2,5,4,2,3,4,2,25,20.0,neutral or dissatisfied +73024,108948,Male,Loyal Customer,64,Personal Travel,Eco Plus,1066,2,4,2,2,4,2,4,4,5,3,4,3,4,4,15,3.0,neutral or dissatisfied +73025,20544,Female,Loyal Customer,32,Business travel,Business,3821,3,3,4,3,3,3,3,3,2,1,4,2,3,3,0,23.0,neutral or dissatisfied +73026,62142,Male,Loyal Customer,31,Business travel,Business,2454,3,3,3,3,4,3,4,4,5,5,4,4,4,4,12,18.0,satisfied +73027,86347,Female,Loyal Customer,57,Business travel,Business,1665,2,2,4,2,4,4,4,5,5,5,5,5,5,5,22,14.0,satisfied +73028,123156,Male,disloyal Customer,7,Business travel,Eco,631,0,0,0,2,3,0,3,3,5,4,4,5,4,3,0,0.0,satisfied +73029,104770,Female,Loyal Customer,67,Business travel,Eco Plus,846,2,5,5,5,5,4,3,2,2,2,2,3,2,1,64,67.0,neutral or dissatisfied +73030,81978,Male,Loyal Customer,28,Business travel,Business,1532,4,4,4,4,3,4,3,3,5,2,5,4,5,3,0,0.0,satisfied +73031,88280,Female,Loyal Customer,46,Business travel,Business,1686,2,5,5,5,1,3,3,2,2,2,2,4,2,4,5,1.0,neutral or dissatisfied +73032,76535,Female,Loyal Customer,50,Business travel,Business,3804,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +73033,46846,Male,Loyal Customer,57,Business travel,Eco,845,5,2,2,2,5,5,5,5,2,3,5,4,5,5,0,0.0,satisfied +73034,30050,Female,Loyal Customer,59,Business travel,Eco,139,3,2,3,3,3,4,3,3,3,3,3,1,3,4,0,8.0,neutral or dissatisfied +73035,123770,Female,Loyal Customer,58,Business travel,Business,1797,1,1,1,1,5,4,3,1,1,1,1,1,1,1,0,1.0,neutral or dissatisfied +73036,112398,Male,Loyal Customer,55,Business travel,Business,2730,5,5,1,5,4,5,4,5,5,4,5,5,5,4,22,15.0,satisfied +73037,44339,Male,Loyal Customer,50,Personal Travel,Eco,230,1,4,1,5,2,1,2,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +73038,67733,Female,Loyal Customer,24,Business travel,Business,3712,2,5,5,5,2,2,2,2,3,5,4,2,3,2,1,0.0,neutral or dissatisfied +73039,17750,Male,Loyal Customer,39,Personal Travel,Eco,383,2,2,5,3,5,3,3,3,4,4,3,3,1,3,110,157.0,neutral or dissatisfied +73040,87551,Female,Loyal Customer,50,Business travel,Business,432,4,4,4,4,3,5,5,3,3,3,3,4,3,4,4,10.0,satisfied +73041,15287,Male,Loyal Customer,60,Personal Travel,Eco,500,4,5,3,3,5,3,5,5,5,3,5,5,5,5,0,8.0,neutral or dissatisfied +73042,111714,Female,Loyal Customer,52,Personal Travel,Eco,495,2,3,2,3,1,4,4,1,1,2,1,1,1,3,14,0.0,neutral or dissatisfied +73043,74250,Male,disloyal Customer,54,Business travel,Eco,1357,1,1,1,3,1,1,1,1,2,3,2,1,2,1,0,31.0,neutral or dissatisfied +73044,15744,Female,Loyal Customer,41,Business travel,Business,461,3,3,3,3,4,1,1,5,5,5,5,3,5,3,33,27.0,satisfied +73045,87014,Female,disloyal Customer,39,Business travel,Business,907,5,5,5,2,4,5,4,4,3,3,5,5,5,4,0,0.0,satisfied +73046,126266,Male,Loyal Customer,36,Business travel,Eco,468,4,3,3,3,4,4,4,4,1,5,3,2,3,4,0,80.0,neutral or dissatisfied +73047,848,Male,Loyal Customer,63,Business travel,Business,134,3,5,5,5,5,3,4,2,2,3,3,1,2,1,0,0.0,neutral or dissatisfied +73048,68641,Female,Loyal Customer,48,Business travel,Business,2716,1,4,4,4,2,4,4,1,1,1,1,4,1,1,28,27.0,neutral or dissatisfied +73049,16455,Male,Loyal Customer,7,Personal Travel,Eco,416,2,3,3,3,4,3,4,4,2,2,4,1,3,4,26,16.0,neutral or dissatisfied +73050,84697,Male,Loyal Customer,24,Business travel,Business,2182,3,3,3,3,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +73051,12571,Male,Loyal Customer,13,Personal Travel,Eco Plus,871,3,3,2,4,1,2,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +73052,2502,Female,disloyal Customer,64,Business travel,Business,280,5,5,5,5,4,5,3,4,3,5,5,4,4,4,0,0.0,satisfied +73053,95386,Female,Loyal Customer,33,Personal Travel,Eco,273,2,4,5,4,2,5,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +73054,12241,Male,Loyal Customer,38,Business travel,Business,2948,0,4,0,5,2,4,2,5,5,5,5,3,5,1,0,0.0,satisfied +73055,70565,Female,disloyal Customer,23,Business travel,Eco,1258,1,1,1,3,1,1,1,1,5,4,1,1,5,1,0,0.0,neutral or dissatisfied +73056,4946,Female,Loyal Customer,42,Personal Travel,Eco,268,3,2,3,3,5,4,3,2,2,3,2,1,2,4,13,10.0,neutral or dissatisfied +73057,82878,Female,disloyal Customer,21,Business travel,Eco,594,4,2,4,3,2,4,2,2,2,5,3,2,4,2,24,18.0,neutral or dissatisfied +73058,122622,Male,Loyal Customer,40,Personal Travel,Eco,728,4,3,3,4,1,3,4,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +73059,32964,Male,Loyal Customer,48,Personal Travel,Eco,163,2,5,0,3,1,0,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +73060,54397,Male,Loyal Customer,52,Business travel,Eco,305,3,5,5,5,4,3,4,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +73061,67584,Female,Loyal Customer,36,Business travel,Business,1235,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,1.0,satisfied +73062,107234,Female,Loyal Customer,68,Business travel,Business,583,5,2,4,2,3,4,4,5,5,4,5,3,5,2,11,0.0,neutral or dissatisfied +73063,76098,Male,Loyal Customer,66,Personal Travel,Eco,669,2,4,2,2,1,2,1,1,3,2,4,4,4,1,26,19.0,neutral or dissatisfied +73064,124407,Male,Loyal Customer,47,Business travel,Business,2624,3,3,3,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +73065,110846,Female,Loyal Customer,40,Business travel,Business,2807,4,4,4,4,3,4,5,4,4,4,4,4,4,5,28,50.0,satisfied +73066,119003,Female,Loyal Customer,22,Business travel,Business,2453,1,1,4,1,3,3,3,3,3,4,1,1,2,3,0,0.0,satisfied +73067,126445,Male,Loyal Customer,44,Business travel,Business,1972,4,4,1,4,4,4,4,5,3,4,5,4,3,4,122,219.0,satisfied +73068,57345,Female,disloyal Customer,27,Business travel,Eco,414,3,4,3,4,5,3,3,5,3,4,3,3,4,5,1,6.0,neutral or dissatisfied +73069,71371,Male,Loyal Customer,64,Business travel,Eco,258,4,1,1,1,4,4,4,4,1,3,3,1,4,4,7,1.0,neutral or dissatisfied +73070,67,Male,Loyal Customer,50,Business travel,Business,67,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +73071,71680,Female,Loyal Customer,49,Personal Travel,Eco,1005,2,5,2,4,5,4,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +73072,103221,Male,Loyal Customer,53,Business travel,Business,462,1,3,3,3,5,2,3,1,1,1,1,3,1,2,13,8.0,neutral or dissatisfied +73073,43445,Male,Loyal Customer,30,Business travel,Business,3982,1,1,1,1,5,5,5,5,1,1,2,2,3,5,0,0.0,satisfied +73074,100003,Female,Loyal Customer,56,Business travel,Business,3386,0,5,0,2,3,5,5,1,1,1,1,4,1,5,0,2.0,satisfied +73075,121233,Female,Loyal Customer,35,Business travel,Business,2075,4,4,4,4,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +73076,3063,Male,Loyal Customer,16,Personal Travel,Eco,340,1,5,1,2,5,1,5,5,3,5,4,3,4,5,0,0.0,neutral or dissatisfied +73077,78210,Female,Loyal Customer,11,Personal Travel,Eco,259,1,4,0,2,5,0,5,5,4,4,3,3,2,5,0,32.0,neutral or dissatisfied +73078,14884,Female,Loyal Customer,43,Business travel,Business,2471,3,4,1,4,3,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +73079,113096,Male,Loyal Customer,22,Personal Travel,Eco,479,2,2,2,4,4,2,4,4,1,4,3,3,3,4,92,79.0,neutral or dissatisfied +73080,56235,Female,Loyal Customer,52,Business travel,Business,1585,2,2,2,2,4,4,5,5,5,5,5,5,5,5,105,97.0,satisfied +73081,84073,Male,disloyal Customer,30,Business travel,Eco,757,2,1,1,4,3,1,3,3,2,4,4,4,3,3,13,22.0,neutral or dissatisfied +73082,123132,Female,Loyal Customer,52,Business travel,Eco,590,4,3,2,3,1,3,3,3,3,4,3,1,3,2,24,29.0,neutral or dissatisfied +73083,33896,Female,Loyal Customer,64,Personal Travel,Eco,1504,4,5,4,3,2,4,4,5,5,4,5,4,5,3,0,0.0,satisfied +73084,118991,Female,Loyal Customer,52,Business travel,Business,479,2,2,2,2,5,4,4,4,4,4,4,3,4,5,36,28.0,satisfied +73085,56726,Male,Loyal Customer,64,Personal Travel,Eco,1023,1,3,1,5,1,1,3,1,5,3,2,4,3,1,4,0.0,neutral or dissatisfied +73086,65776,Female,disloyal Customer,23,Business travel,Business,1389,5,5,4,4,3,4,3,3,3,3,4,5,4,3,3,0.0,satisfied +73087,52310,Male,Loyal Customer,9,Business travel,Business,1852,2,1,1,1,2,3,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +73088,19768,Male,disloyal Customer,44,Business travel,Business,667,3,3,3,2,4,3,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +73089,41317,Female,disloyal Customer,35,Business travel,Eco,1041,3,3,3,4,2,3,2,2,1,2,3,2,3,2,0,16.0,neutral or dissatisfied +73090,101718,Male,Loyal Customer,34,Personal Travel,Eco,986,1,1,1,4,3,1,3,3,2,3,3,1,3,3,16,10.0,neutral or dissatisfied +73091,44546,Male,Loyal Customer,41,Personal Travel,Eco,157,4,4,4,2,4,4,3,4,4,2,4,4,4,4,0,0.0,satisfied +73092,104751,Female,Loyal Customer,61,Business travel,Eco,942,4,5,5,5,2,4,3,4,4,4,4,1,4,2,0,1.0,satisfied +73093,33192,Female,disloyal Customer,50,Business travel,Eco Plus,102,3,3,3,1,4,3,4,4,5,3,1,1,1,4,0,0.0,neutral or dissatisfied +73094,19809,Female,Loyal Customer,26,Business travel,Business,1976,1,1,3,1,2,2,2,5,1,5,2,2,5,2,134,119.0,satisfied +73095,39179,Male,Loyal Customer,39,Personal Travel,Eco,237,2,5,2,2,3,2,3,3,3,5,4,5,5,3,0,13.0,neutral or dissatisfied +73096,64659,Male,disloyal Customer,49,Business travel,Business,247,3,3,3,4,5,3,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +73097,73162,Female,Loyal Customer,42,Business travel,Business,3543,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,5.0,satisfied +73098,45293,Male,disloyal Customer,20,Business travel,Eco,461,2,0,2,3,4,2,4,4,3,5,1,4,5,4,95,93.0,neutral or dissatisfied +73099,42306,Female,Loyal Customer,28,Personal Travel,Eco,451,5,4,5,5,5,5,5,5,5,4,5,5,4,5,0,0.0,satisfied +73100,47179,Male,Loyal Customer,30,Business travel,Business,679,4,2,2,2,4,4,4,4,1,3,2,1,3,4,0,0.0,neutral or dissatisfied +73101,84466,Female,Loyal Customer,12,Personal Travel,Eco Plus,290,5,5,5,3,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +73102,34095,Female,disloyal Customer,29,Business travel,Business,1046,3,3,3,3,2,3,2,2,2,4,4,3,3,2,0,0.0,neutral or dissatisfied +73103,15566,Female,Loyal Customer,53,Business travel,Eco,229,4,1,2,2,4,3,1,4,4,4,4,4,4,3,2,0.0,satisfied +73104,41808,Female,Loyal Customer,38,Business travel,Eco,489,5,4,1,1,5,5,5,5,5,2,1,2,1,5,0,23.0,satisfied +73105,84700,Female,Loyal Customer,45,Business travel,Business,2465,3,3,3,3,4,4,4,5,5,5,5,3,5,3,8,0.0,satisfied +73106,928,Male,disloyal Customer,62,Business travel,Business,89,3,3,3,3,4,3,4,4,1,2,3,1,3,4,13,9.0,neutral or dissatisfied +73107,107193,Male,disloyal Customer,19,Business travel,Eco,402,1,1,1,3,4,1,4,4,3,1,4,4,4,4,20,16.0,neutral or dissatisfied +73108,90205,Male,Loyal Customer,24,Personal Travel,Eco,1127,1,4,1,2,4,1,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +73109,102773,Male,Loyal Customer,28,Business travel,Business,3675,4,4,4,4,5,5,5,5,4,4,4,4,4,5,0,0.0,satisfied +73110,17780,Female,disloyal Customer,24,Business travel,Business,1042,0,0,0,2,1,0,1,1,1,4,4,1,5,1,0,0.0,satisfied +73111,55340,Female,Loyal Customer,24,Personal Travel,Eco,1117,3,5,4,2,4,4,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +73112,53204,Male,Loyal Customer,50,Business travel,Business,612,3,2,2,2,5,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +73113,4627,Male,Loyal Customer,48,Business travel,Business,3417,2,5,4,5,2,3,4,2,2,2,2,2,2,4,1,8.0,neutral or dissatisfied +73114,45718,Female,Loyal Customer,80,Business travel,Business,3826,4,3,3,3,2,4,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +73115,18109,Female,Loyal Customer,49,Business travel,Eco,629,5,3,2,3,1,4,2,5,5,5,5,5,5,2,0,0.0,satisfied +73116,88106,Male,Loyal Customer,52,Business travel,Business,1521,1,1,1,1,2,4,4,5,5,5,5,4,5,3,21,15.0,satisfied +73117,113,Male,Loyal Customer,54,Business travel,Business,3389,4,2,5,2,2,4,4,4,4,4,4,3,4,3,32,40.0,neutral or dissatisfied +73118,62697,Male,disloyal Customer,23,Business travel,Business,1344,5,0,5,3,5,5,5,5,3,5,5,4,4,5,14,1.0,satisfied +73119,127436,Male,Loyal Customer,52,Personal Travel,Eco,868,4,1,4,4,5,4,1,5,4,2,4,1,3,5,0,0.0,neutral or dissatisfied +73120,99347,Male,Loyal Customer,33,Business travel,Business,1771,1,1,1,1,1,1,1,1,4,2,3,3,4,1,0,11.0,neutral or dissatisfied +73121,48783,Female,Loyal Customer,46,Business travel,Business,2915,0,5,0,5,3,4,5,1,1,1,1,4,1,3,0,0.0,satisfied +73122,16384,Male,disloyal Customer,22,Business travel,Eco,404,4,1,3,5,2,3,3,2,2,4,3,5,5,2,108,111.0,satisfied +73123,3420,Female,Loyal Customer,47,Personal Travel,Eco,296,3,3,3,5,2,5,2,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +73124,85906,Female,Loyal Customer,39,Business travel,Business,674,3,3,3,3,2,5,5,4,4,4,4,4,4,3,30,19.0,satisfied +73125,101450,Female,Loyal Customer,39,Business travel,Business,3307,1,1,3,1,5,4,5,5,5,5,5,4,5,5,16,21.0,satisfied +73126,68214,Male,Loyal Customer,31,Business travel,Business,3044,2,2,2,2,5,5,5,5,3,5,5,5,4,5,9,8.0,satisfied +73127,96017,Male,disloyal Customer,23,Business travel,Business,1090,5,1,5,3,1,5,1,1,5,4,4,4,4,1,19,6.0,satisfied +73128,61080,Female,disloyal Customer,59,Business travel,Eco,1106,4,4,4,4,5,4,5,5,1,2,4,3,3,5,89,95.0,neutral or dissatisfied +73129,119011,Female,Loyal Customer,39,Personal Travel,Eco,479,1,5,1,3,2,1,1,2,3,4,2,5,5,2,20,24.0,neutral or dissatisfied +73130,75098,Male,Loyal Customer,60,Business travel,Business,1846,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +73131,31500,Male,Loyal Customer,23,Business travel,Business,2401,2,2,2,2,4,4,4,4,5,4,4,5,5,4,14,27.0,satisfied +73132,112795,Female,disloyal Customer,20,Business travel,Business,1208,5,0,5,3,5,4,4,5,3,5,4,4,3,4,322,299.0,satisfied +73133,84595,Female,disloyal Customer,13,Business travel,Eco,669,4,2,4,4,2,4,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +73134,102643,Female,disloyal Customer,25,Business travel,Business,365,1,5,1,4,1,1,1,1,4,3,5,3,4,1,1,0.0,neutral or dissatisfied +73135,119536,Female,Loyal Customer,56,Personal Travel,Eco,899,1,5,1,5,2,5,5,2,2,1,2,4,2,5,0,8.0,neutral or dissatisfied +73136,86632,Male,Loyal Customer,25,Business travel,Business,1818,5,5,5,5,4,4,4,4,4,3,5,3,4,4,5,0.0,satisfied +73137,811,Female,Loyal Customer,42,Business travel,Business,1532,1,1,1,1,2,4,5,5,5,5,5,5,5,3,6,1.0,satisfied +73138,52220,Male,Loyal Customer,36,Business travel,Eco,370,3,2,2,2,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +73139,8442,Male,Loyal Customer,63,Business travel,Business,2288,3,2,2,2,1,3,2,3,3,3,3,2,3,2,15,7.0,neutral or dissatisfied +73140,78228,Female,Loyal Customer,60,Personal Travel,Eco,192,3,4,0,3,3,4,4,2,2,0,2,3,2,5,0,2.0,neutral or dissatisfied +73141,97143,Male,disloyal Customer,34,Business travel,Eco,986,3,3,3,3,3,3,3,3,4,4,3,1,3,3,36,32.0,neutral or dissatisfied +73142,39732,Female,Loyal Customer,33,Personal Travel,Eco,320,4,5,4,1,2,4,2,2,1,3,1,1,3,2,0,0.0,satisfied +73143,56979,Female,Loyal Customer,44,Personal Travel,Eco,2454,4,5,4,4,5,3,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +73144,98535,Male,Loyal Customer,35,Personal Travel,Eco,402,3,5,3,3,4,3,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +73145,60927,Male,Loyal Customer,25,Business travel,Business,3933,1,1,1,1,5,5,5,5,5,5,5,3,5,5,7,4.0,satisfied +73146,33190,Male,Loyal Customer,38,Business travel,Eco Plus,216,5,5,5,5,5,5,5,5,2,4,3,1,4,5,0,0.0,satisfied +73147,115101,Female,Loyal Customer,46,Business travel,Business,3109,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +73148,17669,Female,Loyal Customer,44,Business travel,Eco,282,5,3,2,3,1,4,1,5,5,5,5,4,5,2,0,0.0,satisfied +73149,105401,Male,Loyal Customer,25,Personal Travel,Eco,369,1,4,1,2,3,1,5,3,4,2,1,3,2,3,0,0.0,neutral or dissatisfied +73150,126441,Female,Loyal Customer,22,Personal Travel,Eco Plus,328,2,5,2,2,3,2,2,3,2,3,4,2,1,3,6,20.0,neutral or dissatisfied +73151,17755,Female,Loyal Customer,51,Personal Travel,Eco,383,3,4,3,1,3,5,4,4,4,3,4,5,4,3,71,50.0,neutral or dissatisfied +73152,117950,Female,Loyal Customer,48,Business travel,Business,3321,4,4,4,4,1,2,3,4,4,4,4,4,4,3,0,0.0,satisfied +73153,81122,Female,Loyal Customer,52,Personal Travel,Eco,991,2,3,2,4,5,5,3,4,4,2,4,2,4,3,11,1.0,neutral or dissatisfied +73154,69915,Female,Loyal Customer,57,Personal Travel,Eco,1514,1,2,1,2,4,3,3,5,5,1,5,3,5,2,0,4.0,neutral or dissatisfied +73155,108475,Female,Loyal Customer,26,Personal Travel,Eco Plus,1444,1,5,1,5,3,1,1,3,3,2,3,5,5,3,0,0.0,neutral or dissatisfied +73156,37243,Female,Loyal Customer,47,Personal Travel,Business,1076,1,5,2,2,4,5,5,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +73157,78941,Female,Loyal Customer,19,Personal Travel,Eco,500,3,4,3,2,4,3,4,4,4,4,4,5,1,4,0,0.0,neutral or dissatisfied +73158,91473,Female,Loyal Customer,32,Personal Travel,Eco,859,3,4,3,1,3,3,3,3,5,5,5,4,5,3,76,70.0,neutral or dissatisfied +73159,54753,Female,Loyal Customer,22,Personal Travel,Eco,964,1,5,1,4,2,1,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +73160,19095,Female,Loyal Customer,45,Personal Travel,Business,287,1,1,1,1,4,2,1,3,3,1,3,2,3,2,31,45.0,neutral or dissatisfied +73161,56774,Female,Loyal Customer,18,Personal Travel,Eco Plus,1065,3,5,3,1,3,3,3,3,3,4,5,5,5,3,0,2.0,neutral or dissatisfied +73162,87568,Male,Loyal Customer,49,Business travel,Business,432,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,4.0,satisfied +73163,13978,Female,Loyal Customer,18,Personal Travel,Eco Plus,317,4,2,4,3,3,4,3,3,2,2,3,1,3,3,68,85.0,neutral or dissatisfied +73164,61343,Male,Loyal Customer,58,Business travel,Business,2210,2,2,4,2,2,4,4,5,5,5,5,4,5,4,6,0.0,satisfied +73165,50258,Male,disloyal Customer,23,Business travel,Eco,372,4,0,4,5,1,4,1,1,5,1,2,5,4,1,0,0.0,satisfied +73166,40025,Female,Loyal Customer,32,Business travel,Eco,525,0,0,0,1,5,0,2,5,2,5,2,2,5,5,0,0.0,satisfied +73167,93687,Male,Loyal Customer,52,Business travel,Business,1452,3,3,3,3,3,4,5,2,2,2,2,5,2,3,14,33.0,satisfied +73168,26468,Female,Loyal Customer,16,Personal Travel,Eco,919,2,5,1,1,2,1,2,2,4,2,5,4,5,2,62,66.0,neutral or dissatisfied +73169,27112,Female,Loyal Customer,57,Business travel,Business,2688,4,4,4,4,3,1,2,4,4,4,4,2,4,4,1,,neutral or dissatisfied +73170,79244,Female,Loyal Customer,53,Business travel,Business,1598,3,4,4,4,2,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +73171,7270,Male,Loyal Customer,7,Personal Travel,Eco,116,4,2,4,4,1,4,1,1,4,4,4,4,3,1,0,8.0,neutral or dissatisfied +73172,112937,Female,Loyal Customer,70,Personal Travel,Eco,1164,3,5,3,1,4,3,5,4,4,3,2,4,4,3,1,0.0,neutral or dissatisfied +73173,8859,Male,Loyal Customer,54,Business travel,Business,597,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +73174,73801,Male,Loyal Customer,39,Business travel,Business,3815,1,1,1,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +73175,48734,Male,Loyal Customer,40,Business travel,Business,3572,1,1,1,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +73176,107842,Male,Loyal Customer,11,Personal Travel,Eco,349,3,3,3,3,5,3,5,5,3,2,3,4,2,5,69,114.0,neutral or dissatisfied +73177,103166,Male,Loyal Customer,20,Business travel,Business,491,3,4,4,4,3,3,3,3,3,5,4,1,4,3,40,23.0,neutral or dissatisfied +73178,9790,Female,Loyal Customer,20,Personal Travel,Eco,382,5,5,5,3,4,5,4,4,3,3,4,4,4,4,0,0.0,satisfied +73179,17246,Male,Loyal Customer,28,Business travel,Eco,872,5,1,1,1,5,5,5,5,4,5,3,3,4,5,0,0.0,satisfied +73180,53553,Female,Loyal Customer,11,Personal Travel,Eco,1956,4,3,4,4,2,4,2,2,4,3,4,1,3,2,11,0.0,satisfied +73181,116319,Female,Loyal Customer,20,Personal Travel,Eco,337,1,4,1,3,2,1,3,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +73182,111610,Female,disloyal Customer,25,Business travel,Eco,1014,1,1,1,2,3,1,3,3,5,3,5,4,5,3,0,2.0,neutral or dissatisfied +73183,94393,Male,Loyal Customer,48,Business travel,Business,1967,3,3,3,3,3,4,4,5,5,5,5,3,5,4,2,7.0,satisfied +73184,47262,Female,Loyal Customer,21,Personal Travel,Business,590,2,4,2,4,4,2,4,4,4,2,3,3,3,4,0,13.0,neutral or dissatisfied +73185,97429,Male,Loyal Customer,53,Business travel,Business,570,1,1,5,1,2,4,5,4,4,4,4,5,4,4,5,4.0,satisfied +73186,45165,Female,Loyal Customer,33,Business travel,Eco,174,4,3,3,3,4,4,4,4,4,5,2,5,1,4,4,5.0,satisfied +73187,119956,Female,Loyal Customer,65,Business travel,Eco,868,3,4,4,4,4,2,2,3,3,3,3,1,3,1,16,6.0,neutral or dissatisfied +73188,67657,Female,disloyal Customer,41,Business travel,Eco,1205,1,1,1,3,1,1,5,1,2,3,3,3,4,1,0,1.0,neutral or dissatisfied +73189,95105,Male,Loyal Customer,66,Personal Travel,Eco,239,2,5,2,4,2,2,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +73190,119629,Male,Loyal Customer,25,Personal Travel,Eco Plus,1927,2,4,2,4,4,2,4,4,5,4,3,5,5,4,0,0.0,neutral or dissatisfied +73191,61230,Female,Loyal Customer,39,Business travel,Business,3883,4,4,4,4,2,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +73192,17265,Male,Loyal Customer,65,Personal Travel,Eco,1092,2,5,2,1,5,2,5,5,5,3,2,3,5,5,0,0.0,neutral or dissatisfied +73193,98902,Male,Loyal Customer,56,Personal Travel,Business,543,1,4,1,3,2,4,5,3,3,1,3,3,3,5,114,105.0,neutral or dissatisfied +73194,24394,Female,disloyal Customer,45,Business travel,Eco Plus,669,3,3,3,4,3,3,3,3,2,4,1,2,1,3,16,11.0,neutral or dissatisfied +73195,12671,Male,disloyal Customer,29,Business travel,Eco,721,2,2,2,1,5,2,5,5,5,4,1,5,3,5,0,0.0,neutral or dissatisfied +73196,2215,Male,Loyal Customer,57,Business travel,Business,859,5,5,4,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +73197,36200,Male,Loyal Customer,55,Business travel,Business,1675,5,5,5,5,5,5,2,4,4,4,4,1,4,2,73,77.0,satisfied +73198,51461,Female,Loyal Customer,30,Personal Travel,Eco Plus,77,3,4,0,2,4,0,1,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +73199,103040,Male,disloyal Customer,32,Business travel,Eco,786,2,3,3,3,2,3,4,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +73200,16510,Female,Loyal Customer,43,Personal Travel,Eco,143,3,2,3,3,5,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +73201,46508,Female,Loyal Customer,32,Business travel,Business,1899,4,4,4,4,5,5,4,5,1,4,2,5,5,5,0,0.0,satisfied +73202,102621,Male,Loyal Customer,23,Personal Travel,Eco Plus,1294,2,5,2,3,2,2,2,2,3,3,4,3,4,2,48,34.0,neutral or dissatisfied +73203,10065,Male,Loyal Customer,45,Business travel,Business,3115,2,4,5,4,5,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +73204,66135,Female,Loyal Customer,58,Personal Travel,Eco,583,3,4,3,4,4,3,4,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +73205,59107,Male,Loyal Customer,13,Personal Travel,Eco,1846,2,5,2,3,2,2,1,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +73206,107817,Female,disloyal Customer,32,Business travel,Eco,349,2,4,2,4,3,2,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +73207,33721,Female,Loyal Customer,42,Personal Travel,Eco,667,3,4,3,1,4,4,4,4,4,3,4,4,4,5,0,3.0,neutral or dissatisfied +73208,8065,Female,disloyal Customer,20,Business travel,Business,335,5,4,4,2,3,4,3,3,3,5,4,4,4,3,0,0.0,satisfied +73209,97149,Male,disloyal Customer,54,Business travel,Eco,990,3,3,3,3,1,3,1,1,4,2,4,2,4,1,14,16.0,neutral or dissatisfied +73210,48597,Male,Loyal Customer,21,Personal Travel,Eco,845,2,4,2,3,2,2,1,2,2,1,3,4,3,2,0,3.0,neutral or dissatisfied +73211,26870,Female,Loyal Customer,29,Business travel,Business,2329,4,4,4,4,4,4,4,4,2,3,4,4,4,4,6,6.0,satisfied +73212,17199,Female,Loyal Customer,38,Business travel,Business,3829,3,3,3,3,5,1,4,4,4,4,4,5,4,3,92,83.0,satisfied +73213,62035,Female,Loyal Customer,42,Business travel,Business,2475,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +73214,51268,Female,disloyal Customer,23,Business travel,Eco Plus,156,0,2,0,4,4,0,4,4,5,4,4,2,2,4,0,1.0,satisfied +73215,92957,Female,Loyal Customer,66,Personal Travel,Eco Plus,151,2,5,2,3,2,4,5,2,2,2,4,5,2,3,0,0.0,neutral or dissatisfied +73216,7940,Female,Loyal Customer,30,Business travel,Business,3759,2,2,2,2,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +73217,83748,Female,Loyal Customer,78,Business travel,Business,2200,1,5,5,5,1,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +73218,15558,Female,Loyal Customer,37,Business travel,Eco,229,4,1,1,1,4,4,4,4,4,4,1,3,3,4,10,14.0,satisfied +73219,98661,Female,Loyal Customer,39,Personal Travel,Eco,994,4,4,4,3,5,4,5,5,4,2,4,3,4,5,0,0.0,satisfied +73220,44650,Male,Loyal Customer,31,Business travel,Eco,67,0,0,0,3,4,0,1,4,3,3,5,5,2,4,45,42.0,satisfied +73221,54439,Female,Loyal Customer,32,Business travel,Eco Plus,305,5,3,3,3,5,5,5,5,3,4,5,1,1,5,0,0.0,satisfied +73222,107400,Female,Loyal Customer,57,Business travel,Business,725,1,1,1,1,4,4,4,2,2,2,2,3,2,3,17,9.0,satisfied +73223,45152,Female,Loyal Customer,44,Business travel,Eco,174,2,5,4,5,5,3,3,2,2,2,2,2,2,5,83,69.0,satisfied +73224,124781,Male,Loyal Customer,18,Business travel,Business,2861,3,3,3,3,3,3,3,3,2,4,3,1,2,3,36,51.0,neutral or dissatisfied +73225,59601,Female,Loyal Customer,52,Business travel,Business,965,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +73226,41013,Male,Loyal Customer,43,Business travel,Business,1774,2,2,5,2,3,4,4,3,3,3,3,4,3,3,0,8.0,satisfied +73227,62826,Female,Loyal Customer,39,Personal Travel,Eco,2486,2,4,2,3,2,1,1,3,3,3,3,1,2,1,22,31.0,neutral or dissatisfied +73228,48067,Female,Loyal Customer,59,Business travel,Business,173,4,4,5,4,4,4,5,5,5,5,5,3,5,5,0,7.0,satisfied +73229,46698,Female,Loyal Customer,19,Personal Travel,Eco,125,4,5,4,4,3,4,2,3,3,4,4,3,3,3,39,46.0,neutral or dissatisfied +73230,24437,Female,Loyal Customer,8,Personal Travel,Eco Plus,634,2,5,2,3,3,2,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +73231,37337,Female,Loyal Customer,40,Business travel,Eco,1076,4,1,2,2,4,4,4,4,5,3,5,1,2,4,0,4.0,satisfied +73232,13159,Male,Loyal Customer,34,Personal Travel,Eco,562,3,4,3,4,4,3,4,4,3,5,4,5,5,4,13,11.0,neutral or dissatisfied +73233,101135,Female,Loyal Customer,33,Business travel,Business,2484,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +73234,57184,Female,Loyal Customer,32,Personal Travel,Eco,2227,2,2,2,4,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +73235,86589,Female,Loyal Customer,33,Personal Travel,Eco,1269,3,4,4,3,1,4,2,1,4,5,4,5,5,1,1,0.0,neutral or dissatisfied +73236,33571,Female,Loyal Customer,45,Business travel,Business,1562,4,4,4,4,5,3,4,4,4,4,4,3,4,3,5,27.0,satisfied +73237,41989,Female,Loyal Customer,38,Business travel,Business,2150,1,1,1,1,1,2,5,5,5,5,3,5,5,1,50,56.0,satisfied +73238,22125,Male,Loyal Customer,28,Personal Travel,Eco,694,1,5,1,3,4,1,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +73239,109320,Male,Loyal Customer,19,Personal Travel,Eco,1072,3,4,3,2,2,3,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +73240,44991,Male,Loyal Customer,65,Business travel,Eco,118,4,2,2,2,4,4,4,4,4,3,5,4,1,4,3,0.0,satisfied +73241,60617,Male,Loyal Customer,57,Business travel,Business,3380,4,4,4,4,3,5,4,5,5,5,5,3,5,4,8,4.0,satisfied +73242,6389,Female,disloyal Customer,26,Business travel,Eco,296,1,2,1,3,3,1,3,3,2,4,3,3,4,3,0,0.0,neutral or dissatisfied +73243,100995,Female,Loyal Customer,18,Business travel,Business,867,4,4,4,4,5,5,5,5,3,2,5,5,4,5,63,47.0,satisfied +73244,7367,Male,disloyal Customer,29,Business travel,Business,783,2,2,2,3,5,2,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +73245,123159,Male,disloyal Customer,34,Business travel,Eco,468,1,0,1,4,4,1,4,4,3,3,5,2,5,4,0,5.0,neutral or dissatisfied +73246,95780,Male,Loyal Customer,43,Personal Travel,Eco,181,1,2,0,3,2,0,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +73247,59320,Female,Loyal Customer,26,Business travel,Business,2556,1,1,1,1,5,5,5,5,4,4,4,5,5,5,20,10.0,satisfied +73248,91356,Male,Loyal Customer,55,Personal Travel,Eco Plus,223,4,5,4,1,5,4,1,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +73249,254,Male,Loyal Customer,18,Personal Travel,Eco Plus,719,1,4,1,2,2,1,1,2,5,5,5,3,4,2,80,76.0,neutral or dissatisfied +73250,13948,Female,Loyal Customer,71,Business travel,Eco,153,5,1,1,1,5,5,4,5,5,5,5,4,5,2,0,0.0,satisfied +73251,75652,Female,Loyal Customer,36,Business travel,Business,1964,2,5,5,5,3,3,4,2,2,1,2,3,2,4,14,45.0,neutral or dissatisfied +73252,40581,Female,Loyal Customer,48,Business travel,Eco,517,3,4,4,4,3,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +73253,122965,Male,Loyal Customer,39,Business travel,Business,2991,1,1,1,1,4,4,4,5,5,4,5,4,5,4,135,138.0,satisfied +73254,84303,Male,Loyal Customer,48,Business travel,Business,3481,5,5,5,5,5,4,4,3,3,4,3,5,3,3,5,0.0,satisfied +73255,84640,Male,Loyal Customer,60,Business travel,Business,669,2,2,1,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +73256,97466,Male,Loyal Customer,48,Business travel,Business,3124,5,5,5,5,3,5,4,4,4,5,4,3,4,5,2,0.0,satisfied +73257,50632,Female,Loyal Customer,28,Personal Travel,Eco,308,1,5,1,4,1,1,1,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +73258,46759,Female,Loyal Customer,45,Business travel,Eco Plus,125,4,2,2,2,5,1,3,4,4,4,4,2,4,4,0,0.0,satisfied +73259,24542,Female,Loyal Customer,40,Business travel,Eco,813,5,4,4,4,5,5,5,5,2,4,1,1,5,5,0,0.0,satisfied +73260,22164,Male,disloyal Customer,39,Business travel,Eco,633,1,5,1,1,2,1,2,2,5,3,5,3,3,2,38,26.0,neutral or dissatisfied +73261,108864,Male,Loyal Customer,9,Personal Travel,Eco,1892,2,2,2,3,4,2,4,4,4,2,2,1,3,4,1,0.0,neutral or dissatisfied +73262,4671,Male,Loyal Customer,66,Business travel,Business,2777,2,1,1,1,5,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +73263,118404,Female,Loyal Customer,42,Personal Travel,Business,304,3,5,2,5,5,5,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +73264,91060,Male,Loyal Customer,37,Personal Travel,Eco,270,1,1,1,4,5,1,5,5,3,1,4,4,3,5,1,0.0,neutral or dissatisfied +73265,48936,Male,disloyal Customer,43,Business travel,Eco,109,2,0,2,4,3,2,3,3,3,5,4,5,4,3,0,6.0,neutral or dissatisfied +73266,91228,Male,Loyal Customer,10,Personal Travel,Eco,515,3,1,3,2,3,2,2,1,1,2,2,2,3,2,156,185.0,neutral or dissatisfied +73267,67002,Female,Loyal Customer,55,Business travel,Business,3379,5,5,5,5,3,5,5,5,5,5,5,4,5,4,66,64.0,satisfied +73268,93859,Female,Loyal Customer,14,Personal Travel,Business,590,4,2,4,3,1,4,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +73269,115014,Female,disloyal Customer,22,Business travel,Business,417,1,4,1,4,1,1,1,1,3,3,4,4,4,1,0,8.0,neutral or dissatisfied +73270,117934,Male,Loyal Customer,58,Business travel,Business,2644,5,5,5,5,3,4,4,4,4,4,4,5,4,4,1,2.0,satisfied +73271,7711,Male,Loyal Customer,50,Business travel,Business,1700,1,1,1,1,4,5,4,4,4,5,4,4,4,5,0,3.0,satisfied +73272,37251,Male,Loyal Customer,9,Personal Travel,Business,1028,3,1,3,4,2,3,2,2,2,2,4,4,3,2,27,25.0,neutral or dissatisfied +73273,76147,Female,disloyal Customer,12,Business travel,Eco,689,3,3,3,4,2,3,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +73274,93166,Female,Loyal Customer,48,Personal Travel,Eco,1066,1,4,1,4,4,5,5,4,4,1,2,4,4,4,18,26.0,neutral or dissatisfied +73275,25043,Male,Loyal Customer,51,Personal Travel,Eco Plus,907,3,4,3,1,2,3,2,2,4,3,4,5,4,2,2,46.0,neutral or dissatisfied +73276,48018,Female,Loyal Customer,43,Personal Travel,Eco Plus,817,3,2,3,3,4,4,3,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +73277,80858,Female,Loyal Customer,30,Personal Travel,Eco,692,4,5,4,2,2,4,1,2,3,4,1,3,5,2,0,0.0,neutral or dissatisfied +73278,6645,Male,Loyal Customer,44,Business travel,Business,2589,5,5,5,5,5,4,4,4,4,4,4,3,4,5,6,3.0,satisfied +73279,72325,Female,Loyal Customer,33,Business travel,Business,964,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +73280,13147,Male,Loyal Customer,28,Personal Travel,Eco,427,2,2,2,4,1,2,1,1,3,4,3,4,4,1,105,97.0,neutral or dissatisfied +73281,116596,Female,Loyal Customer,28,Business travel,Business,3228,5,5,3,5,4,4,4,4,3,4,5,4,3,4,165,152.0,satisfied +73282,83803,Male,Loyal Customer,58,Business travel,Business,425,5,5,5,5,4,4,5,5,5,5,5,5,5,4,0,2.0,satisfied +73283,80428,Male,Loyal Customer,48,Business travel,Business,748,5,5,5,5,1,1,4,5,5,4,5,4,5,5,0,0.0,satisfied +73284,90025,Male,Loyal Customer,45,Business travel,Business,957,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +73285,44206,Female,Loyal Customer,55,Personal Travel,Eco,157,2,5,0,2,4,5,5,2,2,0,2,5,2,5,0,0.0,neutral or dissatisfied +73286,52912,Female,disloyal Customer,27,Business travel,Eco,679,2,2,2,4,2,2,2,2,3,2,3,3,4,2,13,0.0,neutral or dissatisfied +73287,36280,Female,Loyal Customer,32,Business travel,Eco Plus,612,4,2,2,2,4,4,4,4,2,1,3,1,2,4,0,0.0,satisfied +73288,11311,Female,Loyal Customer,9,Personal Travel,Eco,429,4,4,4,4,2,4,2,2,2,4,2,3,4,2,0,3.0,satisfied +73289,65146,Female,Loyal Customer,34,Personal Travel,Eco,551,3,2,3,4,5,3,2,5,2,5,4,2,4,5,0,1.0,neutral or dissatisfied +73290,19055,Female,Loyal Customer,38,Business travel,Business,169,4,4,4,4,5,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +73291,54568,Female,disloyal Customer,45,Business travel,Eco Plus,925,3,3,3,3,4,3,4,4,3,1,4,1,4,4,95,113.0,neutral or dissatisfied +73292,60593,Male,Loyal Customer,38,Personal Travel,Eco,1290,2,5,2,3,3,2,3,3,5,4,4,5,5,3,21,54.0,neutral or dissatisfied +73293,71353,Female,disloyal Customer,21,Business travel,Eco,258,0,0,0,4,3,0,3,3,3,2,5,4,4,3,0,0.0,satisfied +73294,15288,Female,Loyal Customer,36,Personal Travel,Eco,501,3,5,3,1,1,3,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +73295,45286,Male,disloyal Customer,22,Business travel,Eco,175,1,4,1,3,4,1,5,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +73296,19857,Female,Loyal Customer,26,Business travel,Business,585,1,5,5,5,1,1,1,1,4,4,3,3,3,1,18,7.0,neutral or dissatisfied +73297,33891,Female,Loyal Customer,45,Business travel,Eco,1504,5,4,4,4,5,2,2,5,5,5,5,4,5,3,0,0.0,satisfied +73298,45524,Male,Loyal Customer,36,Personal Travel,Eco,689,3,5,2,2,2,2,2,2,5,3,5,5,4,2,1,14.0,neutral or dissatisfied +73299,65876,Male,Loyal Customer,42,Business travel,Business,1391,5,5,5,5,5,5,4,2,2,2,2,4,2,4,0,20.0,satisfied +73300,92941,Female,Loyal Customer,69,Personal Travel,Eco,134,2,3,2,3,5,4,4,5,5,2,2,4,5,1,0,0.0,neutral or dissatisfied +73301,5698,Female,Loyal Customer,45,Business travel,Business,3178,3,3,3,3,5,3,4,3,3,4,3,1,3,5,0,0.0,satisfied +73302,101826,Female,Loyal Customer,68,Personal Travel,Eco,1521,3,5,2,3,3,5,5,2,2,2,2,4,2,3,7,0.0,neutral or dissatisfied +73303,32966,Female,Loyal Customer,51,Personal Travel,Eco,102,1,4,1,3,5,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +73304,114064,Female,disloyal Customer,22,Business travel,Eco,2139,2,2,2,4,4,2,5,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +73305,59227,Female,disloyal Customer,19,Business travel,Eco,649,2,0,1,3,3,1,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +73306,24139,Female,Loyal Customer,53,Personal Travel,Business,147,2,5,0,3,5,4,4,5,5,0,5,4,5,4,0,0.0,neutral or dissatisfied +73307,14450,Male,Loyal Customer,28,Business travel,Business,3852,2,4,4,4,2,2,2,2,4,4,3,3,3,2,70,65.0,neutral or dissatisfied +73308,103261,Male,Loyal Customer,61,Business travel,Business,888,2,2,2,2,3,4,4,2,2,2,2,4,2,2,85,69.0,neutral or dissatisfied +73309,842,Male,Loyal Customer,52,Business travel,Business,134,0,5,0,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +73310,67219,Female,Loyal Customer,61,Personal Travel,Eco,985,1,4,1,5,3,5,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +73311,102650,Male,Loyal Customer,44,Business travel,Business,1631,3,3,4,3,5,5,4,5,5,5,5,4,5,5,72,57.0,satisfied +73312,120548,Male,disloyal Customer,22,Business travel,Eco,2176,3,3,3,4,3,3,2,3,3,4,2,4,3,3,9,8.0,neutral or dissatisfied +73313,77682,Female,disloyal Customer,23,Business travel,Eco,813,1,1,1,4,3,1,3,3,3,5,4,3,4,3,95,78.0,neutral or dissatisfied +73314,70902,Male,disloyal Customer,28,Business travel,Eco,1721,1,1,1,3,3,1,5,3,2,3,3,1,3,3,0,0.0,neutral or dissatisfied +73315,123427,Female,disloyal Customer,26,Business travel,Business,1184,4,4,4,2,5,4,2,5,5,3,4,5,4,5,78,74.0,satisfied +73316,101097,Male,Loyal Customer,44,Business travel,Business,583,2,2,2,2,2,5,5,4,4,4,4,4,4,5,26,34.0,satisfied +73317,28903,Male,Loyal Customer,29,Business travel,Business,978,4,4,5,4,5,5,5,5,2,3,4,2,5,5,0,0.0,satisfied +73318,51802,Female,Loyal Customer,31,Personal Travel,Eco,493,4,5,4,4,4,4,4,4,3,5,5,5,5,4,0,1.0,neutral or dissatisfied +73319,61668,Male,Loyal Customer,43,Business travel,Business,1346,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +73320,50146,Female,disloyal Customer,26,Business travel,Eco,89,2,3,2,4,5,2,5,5,1,3,3,1,4,5,0,0.0,neutral or dissatisfied +73321,40958,Female,Loyal Customer,42,Business travel,Business,507,3,3,3,3,4,4,2,4,4,4,4,4,4,3,0,0.0,satisfied +73322,40511,Male,Loyal Customer,54,Personal Travel,Eco,222,4,1,4,4,1,4,5,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +73323,40,Male,Loyal Customer,51,Business travel,Business,212,2,2,2,2,2,4,4,5,5,4,4,3,5,5,0,0.0,satisfied +73324,123142,Female,Loyal Customer,40,Business travel,Business,507,1,1,2,1,4,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +73325,68665,Male,Loyal Customer,35,Business travel,Business,1653,3,2,2,2,4,2,2,3,3,3,3,3,3,1,0,2.0,neutral or dissatisfied +73326,78074,Male,disloyal Customer,63,Business travel,Business,106,3,4,4,5,3,3,5,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +73327,26904,Male,Loyal Customer,32,Business travel,Eco,1774,4,3,3,3,4,4,4,4,4,3,4,4,3,4,4,0.0,satisfied +73328,45994,Male,Loyal Customer,45,Business travel,Business,483,3,3,3,3,2,2,3,4,4,4,4,2,4,3,0,0.0,satisfied +73329,20384,Male,Loyal Customer,15,Personal Travel,Eco Plus,287,2,5,2,1,3,2,3,3,3,4,4,3,5,3,42,25.0,neutral or dissatisfied +73330,107989,Male,Loyal Customer,57,Business travel,Business,1949,1,1,1,1,5,5,4,5,5,5,5,5,5,3,9,4.0,satisfied +73331,104349,Female,Loyal Customer,31,Personal Travel,Eco,528,3,5,3,3,4,3,3,4,5,4,3,2,4,4,0,0.0,neutral or dissatisfied +73332,27204,Female,Loyal Customer,34,Business travel,Business,2554,5,5,5,5,3,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +73333,94682,Female,Loyal Customer,48,Business travel,Business,189,2,2,2,2,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +73334,59522,Male,Loyal Customer,58,Business travel,Business,956,2,2,2,2,4,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +73335,44777,Male,Loyal Customer,26,Business travel,Business,3982,3,2,2,2,3,3,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +73336,119558,Female,Loyal Customer,63,Personal Travel,Eco,759,2,1,3,2,2,2,3,4,4,3,4,3,4,4,66,131.0,neutral or dissatisfied +73337,101493,Female,Loyal Customer,65,Business travel,Eco,345,2,5,5,5,1,3,4,1,1,2,1,1,1,3,54,46.0,neutral or dissatisfied +73338,9164,Female,Loyal Customer,50,Personal Travel,Eco,975,4,3,4,2,4,4,5,3,3,4,3,1,3,1,45,54.0,neutral or dissatisfied +73339,119494,Female,Loyal Customer,31,Business travel,Business,2227,4,4,4,4,4,4,4,4,5,3,5,5,4,4,0,6.0,satisfied +73340,56969,Female,Loyal Customer,45,Business travel,Eco,954,4,2,2,2,4,4,4,3,5,2,2,4,1,4,0,0.0,neutral or dissatisfied +73341,53653,Male,Loyal Customer,59,Business travel,Business,2133,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +73342,92537,Female,Loyal Customer,68,Personal Travel,Eco,1947,3,4,2,2,3,5,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +73343,123864,Male,Loyal Customer,53,Business travel,Business,541,2,2,2,2,1,3,4,2,2,2,2,1,2,3,18,11.0,neutral or dissatisfied +73344,56519,Male,Loyal Customer,18,Business travel,Business,1068,1,1,1,1,4,4,4,4,4,2,5,5,5,4,65,40.0,satisfied +73345,104128,Female,disloyal Customer,28,Business travel,Business,393,3,4,4,2,3,4,3,3,5,2,5,5,4,3,17,0.0,neutral or dissatisfied +73346,46211,Male,Loyal Customer,31,Personal Travel,Business,624,3,4,3,4,1,3,1,1,3,4,5,3,5,1,0,12.0,neutral or dissatisfied +73347,79417,Female,Loyal Customer,67,Personal Travel,Eco,502,3,3,3,2,4,2,2,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +73348,126686,Male,Loyal Customer,44,Business travel,Business,2521,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +73349,117115,Female,Loyal Customer,44,Business travel,Eco,251,1,2,2,2,2,4,3,1,1,1,1,1,1,1,23,21.0,neutral or dissatisfied +73350,119347,Male,Loyal Customer,57,Business travel,Business,2889,0,5,0,4,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +73351,105121,Male,Loyal Customer,56,Business travel,Business,220,3,2,2,2,5,3,3,3,3,3,3,2,3,3,43,38.0,neutral or dissatisfied +73352,114339,Male,Loyal Customer,46,Personal Travel,Eco,862,4,5,4,2,3,4,3,3,4,3,4,5,5,3,0,2.0,neutral or dissatisfied +73353,27284,Male,Loyal Customer,36,Personal Travel,Business,987,3,2,3,3,1,3,3,2,2,3,2,2,2,2,5,2.0,neutral or dissatisfied +73354,106115,Female,Loyal Customer,60,Business travel,Business,3336,4,4,4,4,4,5,4,2,2,2,2,5,2,3,0,3.0,satisfied +73355,47009,Female,Loyal Customer,28,Business travel,Business,3528,2,2,2,2,5,5,5,5,5,5,2,4,1,5,5,13.0,satisfied +73356,35426,Female,Loyal Customer,26,Personal Travel,Eco,1069,2,2,3,3,3,3,3,3,2,4,3,1,3,3,34,67.0,neutral or dissatisfied +73357,115667,Male,disloyal Customer,24,Business travel,Business,342,4,5,5,4,3,5,3,3,5,2,4,4,5,3,7,1.0,satisfied +73358,43816,Male,Loyal Customer,25,Business travel,Business,199,3,2,2,2,1,3,1,3,3,4,3,1,3,1,147,141.0,neutral or dissatisfied +73359,125019,Female,Loyal Customer,67,Personal Travel,Eco,184,1,4,1,2,3,5,5,3,3,1,3,3,3,3,0,41.0,neutral or dissatisfied +73360,63117,Male,Loyal Customer,41,Business travel,Business,337,1,1,1,1,3,5,5,5,5,4,5,5,5,3,10,7.0,satisfied +73361,104034,Male,Loyal Customer,56,Business travel,Business,1044,3,3,3,3,5,4,5,4,4,4,4,4,4,4,12,8.0,satisfied +73362,30078,Female,Loyal Customer,22,Personal Travel,Eco,31,2,5,2,3,5,2,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +73363,58917,Male,Loyal Customer,10,Personal Travel,Eco,888,2,4,2,1,3,2,3,3,4,2,4,3,4,3,29,41.0,neutral or dissatisfied +73364,129328,Male,disloyal Customer,25,Business travel,Eco,2586,1,1,1,2,4,1,4,4,1,1,2,2,3,4,10,8.0,neutral or dissatisfied +73365,66365,Male,Loyal Customer,38,Personal Travel,Eco,986,1,2,1,3,2,1,2,2,1,1,4,3,3,2,0,0.0,neutral or dissatisfied +73366,101214,Female,Loyal Customer,34,Personal Travel,Eco,1090,3,2,3,3,3,3,3,3,1,1,4,4,3,3,69,58.0,neutral or dissatisfied +73367,3175,Male,disloyal Customer,44,Business travel,Eco,693,1,1,1,3,5,1,5,5,1,1,3,3,4,5,2,0.0,neutral or dissatisfied +73368,28406,Female,Loyal Customer,64,Personal Travel,Eco,1709,2,3,2,3,2,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +73369,75893,Female,Loyal Customer,40,Business travel,Business,1537,3,3,3,3,4,5,5,5,5,5,5,5,5,4,1,8.0,satisfied +73370,116423,Male,Loyal Customer,66,Personal Travel,Eco,337,2,4,2,5,4,2,5,4,5,5,4,5,4,4,9,3.0,neutral or dissatisfied +73371,110266,Male,Loyal Customer,37,Business travel,Business,3420,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +73372,106183,Female,Loyal Customer,69,Personal Travel,Eco,444,4,2,4,2,1,2,1,1,1,4,4,3,1,2,0,0.0,neutral or dissatisfied +73373,41783,Male,Loyal Customer,65,Personal Travel,Eco,508,4,5,4,5,2,4,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +73374,6546,Female,Loyal Customer,54,Business travel,Business,2093,5,5,4,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +73375,37184,Female,Loyal Customer,46,Personal Travel,Eco,1189,3,2,3,3,5,3,3,3,3,3,3,4,3,3,0,7.0,neutral or dissatisfied +73376,95330,Female,Loyal Customer,35,Personal Travel,Eco,239,1,5,0,3,3,0,3,3,4,5,4,5,4,3,14,8.0,neutral or dissatisfied +73377,63898,Female,disloyal Customer,18,Business travel,Eco,1192,2,2,2,4,3,2,3,3,1,1,3,3,4,3,0,1.0,neutral or dissatisfied +73378,17800,Female,disloyal Customer,36,Business travel,Eco,1075,1,1,1,4,1,1,1,1,2,4,4,1,3,1,30,78.0,neutral or dissatisfied +73379,13131,Female,Loyal Customer,57,Business travel,Eco,162,4,3,1,3,2,1,5,5,5,4,5,2,5,5,6,3.0,satisfied +73380,56247,Female,disloyal Customer,42,Business travel,Business,1111,5,5,5,2,5,2,2,3,3,3,5,2,4,2,0,0.0,satisfied +73381,28376,Female,disloyal Customer,25,Business travel,Eco,763,2,2,2,3,1,2,3,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +73382,61175,Male,Loyal Customer,54,Business travel,Business,2584,3,3,4,3,4,5,4,5,5,4,5,4,5,4,0,32.0,satisfied +73383,32075,Female,Loyal Customer,45,Business travel,Business,101,3,3,3,3,5,2,1,5,5,5,5,4,5,4,0,0.0,satisfied +73384,54310,Male,disloyal Customer,30,Business travel,Eco,899,5,5,5,3,3,5,3,3,1,2,5,2,5,3,12,0.0,satisfied +73385,7878,Female,disloyal Customer,28,Business travel,Eco,948,2,2,2,2,3,2,3,3,3,1,2,2,3,3,10,8.0,neutral or dissatisfied +73386,116371,Male,Loyal Customer,32,Personal Travel,Eco,446,2,4,2,3,2,2,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +73387,120994,Male,Loyal Customer,49,Business travel,Eco,920,1,2,2,2,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +73388,82292,Male,Loyal Customer,17,Personal Travel,Eco Plus,1481,1,3,1,4,5,1,5,5,5,3,5,4,5,5,5,5.0,neutral or dissatisfied +73389,78012,Female,Loyal Customer,32,Business travel,Eco,214,2,1,1,1,2,2,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +73390,119700,Male,Loyal Customer,56,Business travel,Business,1303,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +73391,83848,Male,Loyal Customer,46,Personal Travel,Eco,425,2,5,2,4,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +73392,116897,Female,Loyal Customer,33,Business travel,Business,338,0,0,0,1,5,5,4,2,2,2,2,3,2,3,41,55.0,satisfied +73393,2492,Female,Loyal Customer,60,Business travel,Eco,1379,3,1,1,1,3,4,4,3,3,3,3,4,3,2,110,109.0,neutral or dissatisfied +73394,105232,Female,disloyal Customer,24,Business travel,Eco,377,2,0,2,1,3,2,3,3,5,5,2,1,2,3,32,11.0,neutral or dissatisfied +73395,78195,Female,Loyal Customer,58,Business travel,Eco,259,3,3,3,3,3,3,4,4,4,3,4,4,4,3,46,37.0,neutral or dissatisfied +73396,46377,Male,disloyal Customer,20,Business travel,Eco,1013,3,3,3,3,1,3,1,1,4,4,3,4,5,1,13,3.0,neutral or dissatisfied +73397,104086,Male,Loyal Customer,22,Personal Travel,Eco,666,3,3,3,2,2,3,2,2,4,4,4,4,3,2,8,6.0,neutral or dissatisfied +73398,107619,Male,Loyal Customer,25,Business travel,Business,3410,1,1,1,1,4,4,4,4,4,1,1,3,1,4,15,9.0,satisfied +73399,105088,Male,Loyal Customer,32,Business travel,Business,281,3,5,5,5,3,2,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +73400,105691,Male,Loyal Customer,35,Business travel,Business,1786,3,2,2,2,4,2,2,3,3,3,3,3,3,3,126,92.0,neutral or dissatisfied +73401,128001,Female,Loyal Customer,33,Personal Travel,Eco,1488,5,5,5,2,1,5,1,1,5,2,3,4,4,1,0,4.0,satisfied +73402,60176,Female,Loyal Customer,26,Personal Travel,Eco,1120,2,5,2,1,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +73403,119023,Female,disloyal Customer,54,Business travel,Eco,1460,2,1,1,3,5,2,5,5,3,1,3,3,2,5,2,1.0,neutral or dissatisfied +73404,97974,Male,Loyal Customer,8,Personal Travel,Eco,483,3,3,3,2,5,3,5,5,4,2,3,4,2,5,7,0.0,neutral or dissatisfied +73405,98711,Male,Loyal Customer,56,Business travel,Business,3226,1,1,1,1,5,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +73406,41985,Female,Loyal Customer,56,Business travel,Business,3088,5,5,2,5,5,5,4,5,5,5,5,5,5,5,14,25.0,satisfied +73407,41236,Female,disloyal Customer,26,Business travel,Eco Plus,744,5,5,5,1,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +73408,7907,Female,Loyal Customer,19,Business travel,Business,2816,2,2,2,2,2,2,2,2,4,4,4,3,4,2,0,0.0,satisfied +73409,93004,Female,Loyal Customer,45,Business travel,Business,1524,3,3,2,3,3,5,5,5,5,5,5,5,5,4,84,114.0,satisfied +73410,8802,Female,Loyal Customer,29,Business travel,Business,552,1,1,5,1,1,1,1,1,1,1,3,1,3,1,60,67.0,neutral or dissatisfied +73411,115258,Female,Loyal Customer,31,Business travel,Eco,480,4,3,2,3,4,4,4,4,4,5,3,1,4,4,27,21.0,neutral or dissatisfied +73412,117018,Female,Loyal Customer,51,Business travel,Business,338,0,0,0,4,3,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +73413,10069,Male,Loyal Customer,23,Personal Travel,Eco,596,2,3,2,3,5,2,5,5,4,4,2,1,3,5,0,0.0,neutral or dissatisfied +73414,122029,Female,Loyal Customer,39,Business travel,Business,130,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +73415,72468,Female,Loyal Customer,39,Business travel,Business,2504,2,2,4,2,4,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +73416,4538,Male,Loyal Customer,48,Business travel,Business,319,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +73417,128896,Female,Loyal Customer,47,Business travel,Business,954,2,2,2,2,4,4,4,5,5,2,1,4,1,4,167,151.0,satisfied +73418,77215,Male,Loyal Customer,46,Business travel,Business,1590,5,5,5,5,5,4,4,4,4,4,4,3,4,3,8,4.0,satisfied +73419,85078,Male,Loyal Customer,55,Business travel,Business,2503,4,4,2,4,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +73420,85344,Male,Loyal Customer,9,Business travel,Eco Plus,731,3,1,1,1,3,3,2,3,3,3,4,2,3,3,27,30.0,neutral or dissatisfied +73421,70997,Male,disloyal Customer,39,Business travel,Business,802,4,4,4,4,1,4,1,1,4,4,4,3,4,1,30,8.0,satisfied +73422,462,Female,Loyal Customer,53,Business travel,Business,102,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,1.0,satisfied +73423,86608,Female,Loyal Customer,29,Business travel,Business,2329,5,5,5,5,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +73424,117025,Female,Loyal Customer,33,Business travel,Business,304,3,1,1,1,4,4,4,3,3,3,3,3,3,2,4,8.0,neutral or dissatisfied +73425,89353,Female,disloyal Customer,24,Business travel,Eco,1108,5,3,3,4,2,5,2,2,1,4,5,3,1,2,0,0.0,satisfied +73426,16857,Female,Loyal Customer,27,Business travel,Business,3665,4,4,4,4,4,4,4,4,2,1,5,5,4,4,13,23.0,satisfied +73427,68178,Male,Loyal Customer,14,Personal Travel,Eco,603,2,5,2,3,5,2,5,5,5,2,4,4,5,5,5,7.0,neutral or dissatisfied +73428,38953,Female,Loyal Customer,17,Personal Travel,Eco Plus,205,1,4,1,3,2,1,4,2,4,3,3,2,4,2,0,1.0,neutral or dissatisfied +73429,54543,Female,Loyal Customer,56,Personal Travel,Eco,925,2,5,2,5,5,4,5,3,3,2,3,4,3,3,13,0.0,neutral or dissatisfied +73430,72695,Female,Loyal Customer,13,Personal Travel,Eco,918,2,4,2,3,5,2,5,5,3,2,5,2,2,5,19,19.0,neutral or dissatisfied +73431,108558,Female,Loyal Customer,29,Business travel,Business,735,3,4,3,3,4,4,4,4,3,5,4,5,5,4,18,10.0,satisfied +73432,52855,Male,Loyal Customer,22,Personal Travel,Eco,1721,3,5,3,1,4,3,4,4,4,5,3,3,4,4,0,0.0,neutral or dissatisfied +73433,84034,Female,disloyal Customer,24,Business travel,Eco,773,3,3,3,2,1,3,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +73434,69449,Female,Loyal Customer,45,Personal Travel,Eco,1089,4,3,4,3,2,2,5,3,3,4,3,3,3,5,5,0.0,neutral or dissatisfied +73435,106881,Female,disloyal Customer,37,Business travel,Eco,704,2,2,2,3,4,2,4,4,2,2,3,3,3,4,27,12.0,neutral or dissatisfied +73436,58699,Female,Loyal Customer,43,Business travel,Business,4243,3,3,3,3,2,2,2,5,2,4,5,2,4,2,21,28.0,satisfied +73437,91211,Female,Loyal Customer,27,Personal Travel,Eco,545,1,4,2,3,3,2,3,3,3,3,3,3,4,3,12,12.0,neutral or dissatisfied +73438,49859,Male,disloyal Customer,27,Business travel,Eco,89,3,3,3,3,4,3,4,4,2,5,1,4,1,4,81,84.0,neutral or dissatisfied +73439,98048,Female,disloyal Customer,43,Business travel,Eco,875,3,3,3,4,5,3,5,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +73440,127566,Female,Loyal Customer,44,Business travel,Business,1670,2,3,2,2,5,3,4,5,5,5,5,5,5,3,11,1.0,satisfied +73441,61883,Female,Loyal Customer,27,Business travel,Business,2521,4,3,4,4,5,5,5,5,3,4,3,5,4,5,67,47.0,satisfied +73442,33976,Male,Loyal Customer,38,Business travel,Eco,1598,3,1,1,1,3,3,3,3,4,4,1,2,2,3,19,5.0,neutral or dissatisfied +73443,24527,Female,Loyal Customer,50,Business travel,Business,892,4,1,1,1,3,3,2,4,4,3,4,4,4,4,0,14.0,neutral or dissatisfied +73444,32735,Female,disloyal Customer,28,Business travel,Eco,201,1,3,1,4,2,1,2,2,3,5,4,1,3,2,0,0.0,neutral or dissatisfied +73445,81304,Female,Loyal Customer,43,Business travel,Business,2820,3,3,3,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +73446,4221,Male,disloyal Customer,15,Personal Travel,Eco,888,2,4,2,4,5,2,5,5,3,2,2,4,2,5,0,0.0,neutral or dissatisfied +73447,44455,Male,Loyal Customer,38,Business travel,Eco,402,5,3,3,3,5,5,5,5,1,1,2,4,2,5,4,10.0,satisfied +73448,6499,Female,Loyal Customer,52,Business travel,Business,3306,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,4.0,satisfied +73449,1004,Female,Loyal Customer,32,Business travel,Business,309,2,2,2,2,4,4,4,4,1,1,2,5,4,4,0,0.0,satisfied +73450,116487,Male,Loyal Customer,19,Personal Travel,Eco,337,2,5,2,3,5,2,5,5,4,5,3,5,4,5,0,0.0,neutral or dissatisfied +73451,54686,Female,Loyal Customer,41,Business travel,Business,854,3,5,5,5,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +73452,81940,Female,Loyal Customer,31,Business travel,Business,1517,4,4,4,4,5,5,5,5,3,2,5,4,5,5,23,8.0,satisfied +73453,120037,Female,Loyal Customer,39,Personal Travel,Business,168,2,5,2,3,3,5,4,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +73454,72975,Female,Loyal Customer,25,Business travel,Business,944,2,1,1,1,2,2,2,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +73455,50876,Female,Loyal Customer,66,Personal Travel,Eco,373,2,1,2,3,1,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +73456,70670,Male,Loyal Customer,42,Business travel,Business,1896,5,5,5,5,2,4,5,4,4,4,4,5,4,4,11,0.0,satisfied +73457,16477,Female,Loyal Customer,26,Personal Travel,Eco Plus,529,2,4,2,2,4,2,4,4,3,5,4,4,4,4,14,0.0,neutral or dissatisfied +73458,82604,Male,Loyal Customer,43,Business travel,Business,408,5,5,5,5,2,5,4,3,3,4,3,3,3,4,4,3.0,satisfied +73459,64157,Male,Loyal Customer,35,Business travel,Business,2106,4,2,2,2,1,4,3,4,4,4,4,3,4,1,1,0.0,neutral or dissatisfied +73460,49262,Male,Loyal Customer,42,Business travel,Business,2405,0,0,0,2,4,1,2,4,4,4,4,5,4,5,5,7.0,satisfied +73461,46058,Male,Loyal Customer,12,Personal Travel,Eco,898,3,3,3,1,1,3,1,1,2,4,3,4,3,1,5,13.0,neutral or dissatisfied +73462,35592,Female,Loyal Customer,29,Business travel,Eco Plus,1005,2,2,2,2,2,2,2,2,2,4,4,1,3,2,31,26.0,neutral or dissatisfied +73463,128136,Female,Loyal Customer,55,Business travel,Business,1849,4,5,4,5,3,1,3,4,4,4,4,1,4,4,6,0.0,neutral or dissatisfied +73464,77415,Male,Loyal Customer,57,Personal Travel,Eco,588,4,4,4,2,3,4,3,3,5,4,4,3,4,3,28,17.0,neutral or dissatisfied +73465,110868,Female,Loyal Customer,56,Business travel,Business,545,1,1,1,1,4,4,5,4,4,4,4,5,4,4,38,38.0,satisfied +73466,19077,Male,Loyal Customer,31,Personal Travel,Eco,642,2,4,2,2,2,2,2,2,5,4,5,5,5,2,62,39.0,neutral or dissatisfied +73467,46513,Female,Loyal Customer,20,Business travel,Eco,73,5,5,5,5,5,5,5,5,3,3,5,1,4,5,15,25.0,satisfied +73468,123845,Female,disloyal Customer,23,Business travel,Business,603,0,2,0,2,4,0,4,4,3,2,4,4,4,4,0,0.0,satisfied +73469,79623,Female,Loyal Customer,32,Business travel,Business,762,1,1,1,1,5,4,5,5,5,2,4,4,4,5,0,0.0,satisfied +73470,109627,Male,Loyal Customer,26,Business travel,Business,3443,4,4,4,4,5,5,5,5,4,3,4,3,5,5,30,9.0,satisfied +73471,30930,Male,Loyal Customer,47,Business travel,Business,1024,4,4,4,4,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +73472,420,Male,Loyal Customer,36,Business travel,Business,140,3,2,2,2,2,3,4,1,1,1,3,1,1,2,88,85.0,neutral or dissatisfied +73473,60257,Female,Loyal Customer,69,Personal Travel,Eco,1703,1,1,1,4,3,3,4,2,2,1,4,3,2,1,0,0.0,neutral or dissatisfied +73474,75669,Male,disloyal Customer,25,Business travel,Business,813,3,0,3,3,1,3,1,1,4,5,4,3,5,1,4,0.0,neutral or dissatisfied +73475,20271,Female,Loyal Customer,55,Personal Travel,Eco,235,4,5,4,3,4,5,5,2,2,4,2,3,2,4,15,5.0,satisfied +73476,104904,Female,Loyal Customer,67,Business travel,Business,3929,5,5,4,5,1,3,4,4,4,4,4,4,4,1,1,0.0,satisfied +73477,92020,Male,Loyal Customer,44,Business travel,Business,1535,3,3,3,3,4,4,5,5,5,5,5,3,5,3,6,1.0,satisfied +73478,75394,Male,Loyal Customer,54,Business travel,Business,2218,1,1,1,1,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +73479,102475,Male,Loyal Customer,41,Personal Travel,Eco,223,1,5,1,2,2,1,1,2,3,2,4,4,5,2,44,43.0,neutral or dissatisfied +73480,52907,Male,disloyal Customer,25,Business travel,Eco,679,3,4,4,4,2,4,2,2,4,2,4,5,3,2,29,6.0,neutral or dissatisfied +73481,93532,Male,Loyal Customer,64,Personal Travel,Eco,1218,1,2,1,3,2,1,2,2,3,2,2,2,3,2,0,1.0,neutral or dissatisfied +73482,48801,Male,disloyal Customer,22,Business travel,Eco,266,2,4,2,2,2,2,5,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +73483,71878,Female,Loyal Customer,57,Personal Travel,Eco,1744,2,1,2,3,2,2,3,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +73484,25509,Male,Loyal Customer,26,Business travel,Business,2565,5,5,5,5,4,4,4,4,2,1,1,1,5,4,0,0.0,satisfied +73485,59916,Male,Loyal Customer,34,Business travel,Business,1023,1,3,3,3,4,4,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +73486,99810,Male,Loyal Customer,54,Personal Travel,Eco,632,2,5,2,3,4,2,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +73487,119574,Female,Loyal Customer,55,Business travel,Business,1663,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +73488,123506,Male,Loyal Customer,61,Business travel,Business,3646,4,4,4,4,5,5,5,3,4,5,4,5,3,5,0,4.0,satisfied +73489,71282,Male,Loyal Customer,8,Personal Travel,Eco,733,4,4,4,4,2,4,2,2,2,5,2,1,4,2,15,5.0,satisfied +73490,104533,Female,disloyal Customer,21,Business travel,Eco,1047,4,3,3,3,2,3,4,2,4,5,3,2,3,2,19,14.0,neutral or dissatisfied +73491,90042,Male,Loyal Customer,24,Business travel,Business,3080,1,1,1,1,5,5,5,5,5,5,5,5,5,5,2,15.0,satisfied +73492,119202,Female,disloyal Customer,39,Business travel,Business,331,4,4,4,3,2,4,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +73493,59391,Female,Loyal Customer,13,Personal Travel,Eco,2338,1,4,1,2,1,1,1,1,5,5,3,5,4,1,8,0.0,neutral or dissatisfied +73494,50019,Male,Loyal Customer,66,Business travel,Business,1860,2,2,2,2,4,1,2,2,2,2,2,1,2,3,0,20.0,neutral or dissatisfied +73495,108593,Male,disloyal Customer,29,Business travel,Business,813,2,2,2,3,1,2,1,1,4,4,5,5,4,1,0,2.0,neutral or dissatisfied +73496,93746,Male,Loyal Customer,43,Business travel,Business,1741,5,5,5,5,3,4,4,4,4,3,4,3,4,3,20,12.0,satisfied +73497,100994,Female,Loyal Customer,47,Business travel,Business,1809,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +73498,124120,Female,Loyal Customer,39,Business travel,Business,1798,2,2,2,2,2,2,2,4,1,4,3,2,2,2,189,174.0,neutral or dissatisfied +73499,83941,Female,Loyal Customer,43,Business travel,Business,321,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +73500,128618,Female,disloyal Customer,30,Business travel,Business,679,4,4,4,1,3,4,3,3,5,2,5,5,5,3,11,0.0,satisfied +73501,50327,Female,disloyal Customer,38,Business travel,Eco,199,2,0,2,1,4,2,4,4,4,2,1,5,4,4,0,0.0,neutral or dissatisfied +73502,118992,Male,Loyal Customer,27,Business travel,Business,3195,2,2,2,2,5,5,5,5,3,4,5,3,5,5,0,0.0,satisfied +73503,83563,Male,Loyal Customer,45,Business travel,Business,936,2,4,4,4,5,1,2,2,2,2,2,4,2,4,80,98.0,neutral or dissatisfied +73504,11204,Male,Loyal Customer,15,Personal Travel,Eco,429,3,5,3,4,5,3,5,5,3,2,4,3,3,5,56,56.0,neutral or dissatisfied +73505,60181,Female,Loyal Customer,30,Personal Travel,Eco,1050,4,2,5,3,4,5,5,4,2,5,4,4,3,4,0,14.0,neutral or dissatisfied +73506,39551,Male,Loyal Customer,56,Business travel,Eco,954,5,5,5,5,5,5,5,5,1,4,2,5,3,5,0,0.0,satisfied +73507,100606,Female,Loyal Customer,57,Business travel,Business,1670,3,1,1,1,5,2,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +73508,80349,Male,Loyal Customer,36,Personal Travel,Business,422,5,2,5,3,4,2,2,4,4,5,4,4,4,4,0,8.0,satisfied +73509,67383,Male,Loyal Customer,41,Business travel,Business,2375,4,4,4,4,2,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +73510,121136,Female,Loyal Customer,50,Business travel,Business,2370,3,3,3,3,3,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +73511,113417,Female,Loyal Customer,50,Business travel,Business,3359,0,4,0,3,2,4,5,4,4,4,4,3,4,4,5,1.0,satisfied +73512,89202,Female,Loyal Customer,63,Personal Travel,Eco,1919,3,5,3,1,5,4,5,1,1,3,1,4,1,4,0,6.0,neutral or dissatisfied +73513,34326,Female,Loyal Customer,31,Personal Travel,Business,846,3,1,3,3,4,3,4,4,4,3,4,1,4,4,12,7.0,neutral or dissatisfied +73514,126761,Female,Loyal Customer,18,Personal Travel,Eco,2521,4,1,4,3,4,4,4,4,3,4,3,2,2,4,0,0.0,neutral or dissatisfied +73515,13229,Male,disloyal Customer,49,Business travel,Eco,771,5,5,5,3,3,5,1,3,5,2,5,1,4,3,54,34.0,satisfied +73516,9316,Female,disloyal Customer,21,Business travel,Eco,542,3,4,4,4,4,4,4,4,1,4,3,2,4,4,117,114.0,neutral or dissatisfied +73517,59814,Female,Loyal Customer,55,Business travel,Business,3639,4,1,4,4,5,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +73518,6416,Female,Loyal Customer,17,Personal Travel,Eco,315,2,5,2,5,5,2,5,5,3,2,5,4,4,5,0,8.0,neutral or dissatisfied +73519,64099,Female,Loyal Customer,24,Personal Travel,Eco,919,1,2,1,4,2,1,2,2,4,5,3,1,4,2,0,6.0,neutral or dissatisfied +73520,71812,Male,Loyal Customer,41,Business travel,Business,1723,2,2,2,2,4,5,4,4,4,4,4,5,4,5,16,7.0,satisfied +73521,66357,Female,Loyal Customer,47,Business travel,Business,1775,4,4,4,4,1,3,2,4,4,4,4,3,4,4,1,0.0,neutral or dissatisfied +73522,42175,Male,disloyal Customer,22,Business travel,Eco,726,4,4,4,2,2,4,2,2,3,5,4,3,1,2,0,0.0,neutral or dissatisfied +73523,11159,Male,Loyal Customer,50,Personal Travel,Eco,429,3,1,3,2,2,3,2,2,2,5,2,3,3,2,0,0.0,neutral or dissatisfied +73524,58202,Male,Loyal Customer,10,Business travel,Business,925,2,1,4,1,2,3,2,2,4,5,4,4,4,2,10,3.0,neutral or dissatisfied +73525,49750,Female,Loyal Customer,39,Business travel,Business,326,4,4,4,4,1,2,4,4,4,5,4,1,4,5,0,0.0,satisfied +73526,114053,Female,Loyal Customer,21,Business travel,Business,1947,5,2,5,5,5,5,5,5,5,3,3,3,5,5,79,67.0,satisfied +73527,109281,Female,disloyal Customer,20,Business travel,Eco,1072,3,3,3,4,1,3,1,1,4,2,4,4,3,1,57,32.0,neutral or dissatisfied +73528,59570,Male,Loyal Customer,47,Business travel,Business,3196,2,2,5,2,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +73529,90570,Male,Loyal Customer,52,Business travel,Business,3997,5,5,5,5,5,5,4,5,5,5,4,5,5,3,12,8.0,satisfied +73530,74409,Male,Loyal Customer,41,Business travel,Business,1188,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,3.0,satisfied +73531,98999,Male,Loyal Customer,47,Personal Travel,Eco,569,2,4,2,2,4,2,4,4,5,2,5,5,5,4,12,8.0,neutral or dissatisfied +73532,124369,Male,Loyal Customer,9,Business travel,Business,2550,1,1,1,1,1,1,1,1,3,2,3,3,4,1,22,27.0,neutral or dissatisfied +73533,26508,Female,Loyal Customer,47,Personal Travel,Eco,829,2,5,2,2,5,5,4,4,4,2,4,5,4,5,0,2.0,neutral or dissatisfied +73534,72361,Female,Loyal Customer,34,Business travel,Business,1980,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +73535,95114,Female,Loyal Customer,17,Personal Travel,Eco,239,2,5,0,2,0,1,1,4,4,4,5,1,3,1,167,161.0,neutral or dissatisfied +73536,44319,Male,Loyal Customer,8,Personal Travel,Eco,837,3,4,3,2,1,3,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +73537,84674,Male,Loyal Customer,27,Business travel,Business,2182,3,3,3,3,4,4,4,4,3,3,4,5,4,4,9,4.0,satisfied +73538,38001,Male,Loyal Customer,46,Business travel,Business,2014,5,5,1,5,3,1,5,4,4,4,4,3,4,3,0,0.0,satisfied +73539,75779,Male,Loyal Customer,24,Personal Travel,Eco,813,2,5,2,4,4,2,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +73540,45063,Female,disloyal Customer,41,Business travel,Business,342,3,4,4,2,3,3,3,3,2,5,3,3,4,3,7,0.0,neutral or dissatisfied +73541,5109,Male,Loyal Customer,14,Personal Travel,Eco,235,1,4,1,1,5,1,5,5,4,3,5,4,5,5,92,78.0,neutral or dissatisfied +73542,63029,Male,Loyal Customer,25,Business travel,Business,376,3,3,3,3,4,4,4,4,4,1,5,3,4,4,2,4.0,satisfied +73543,108606,Male,Loyal Customer,31,Business travel,Business,2735,1,5,5,5,1,1,1,1,4,3,3,3,3,1,59,45.0,neutral or dissatisfied +73544,59280,Male,Loyal Customer,24,Business travel,Business,3302,5,5,5,5,5,5,5,5,3,4,5,5,3,5,0,0.0,satisfied +73545,45853,Male,Loyal Customer,32,Business travel,Eco Plus,391,5,4,4,4,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +73546,33714,Female,Loyal Customer,21,Personal Travel,Eco,814,4,1,4,2,1,4,1,1,3,3,1,4,1,1,0,0.0,neutral or dissatisfied +73547,11891,Male,Loyal Customer,41,Business travel,Business,501,3,3,3,3,2,4,4,2,2,3,2,3,2,4,0,0.0,satisfied +73548,36931,Male,Loyal Customer,48,Business travel,Eco,867,4,5,5,5,4,4,4,4,4,3,5,2,2,4,9,0.0,satisfied +73549,65852,Female,Loyal Customer,11,Personal Travel,Eco,1389,5,5,5,3,1,5,1,1,5,2,3,4,5,1,0,0.0,satisfied +73550,100225,Male,Loyal Customer,58,Business travel,Business,1073,4,4,4,4,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +73551,67006,Male,Loyal Customer,36,Business travel,Business,3937,1,1,1,1,4,4,4,3,3,3,3,5,3,3,19,14.0,satisfied +73552,58743,Female,Loyal Customer,47,Business travel,Business,3541,3,3,3,3,5,4,4,4,4,4,4,5,4,3,12,13.0,satisfied +73553,81489,Male,Loyal Customer,28,Personal Travel,Eco,528,2,5,2,4,4,2,4,4,5,2,5,3,4,4,27,21.0,neutral or dissatisfied +73554,51867,Female,Loyal Customer,52,Business travel,Eco Plus,552,5,4,4,4,2,1,1,5,5,5,5,3,5,3,38,34.0,satisfied +73555,81042,Female,Loyal Customer,37,Business travel,Eco,1399,3,4,4,4,3,3,3,3,3,3,3,2,4,3,6,0.0,neutral or dissatisfied +73556,77309,Male,disloyal Customer,25,Business travel,Business,626,4,3,4,1,4,4,1,4,5,2,5,5,5,4,0,0.0,satisfied +73557,83753,Female,Loyal Customer,51,Personal Travel,Eco,1183,4,4,3,3,4,5,5,1,1,3,1,5,1,5,0,0.0,satisfied +73558,16872,Female,Loyal Customer,28,Business travel,Business,2875,2,2,2,2,4,4,4,4,4,4,2,4,2,4,19,4.0,satisfied +73559,14625,Male,Loyal Customer,24,Personal Travel,Eco Plus,450,3,4,3,2,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +73560,33261,Male,Loyal Customer,36,Personal Travel,Eco Plus,216,5,3,5,4,3,5,3,3,4,4,3,4,4,3,0,0.0,satisfied +73561,30846,Male,Loyal Customer,31,Business travel,Business,899,1,2,2,2,1,1,1,3,1,4,4,1,3,1,239,236.0,neutral or dissatisfied +73562,4401,Female,Loyal Customer,17,Personal Travel,Eco,607,1,4,1,3,4,1,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +73563,121423,Female,Loyal Customer,48,Business travel,Business,3782,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +73564,39362,Male,Loyal Customer,43,Business travel,Business,896,3,4,4,4,3,3,3,4,2,2,2,3,1,3,208,208.0,neutral or dissatisfied +73565,91435,Male,Loyal Customer,57,Business travel,Business,859,4,4,4,4,5,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +73566,24082,Male,Loyal Customer,68,Personal Travel,Eco Plus,866,4,5,4,1,4,4,4,4,3,3,4,3,1,4,0,0.0,neutral or dissatisfied +73567,22817,Male,Loyal Customer,65,Business travel,Business,147,1,1,1,1,4,1,3,5,5,5,4,5,5,5,0,0.0,satisfied +73568,4438,Female,Loyal Customer,21,Personal Travel,Eco,762,3,3,3,4,5,3,3,5,1,5,3,2,4,5,48,72.0,neutral or dissatisfied +73569,3252,Male,disloyal Customer,32,Business travel,Business,479,4,4,4,5,2,4,2,2,5,5,4,4,5,2,14,18.0,neutral or dissatisfied +73570,121049,Female,Loyal Customer,16,Personal Travel,Eco,992,3,5,3,4,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +73571,29414,Male,Loyal Customer,48,Personal Travel,Eco,2676,3,4,2,4,2,2,4,4,5,4,4,4,3,4,76,86.0,neutral or dissatisfied +73572,43874,Female,Loyal Customer,45,Business travel,Eco,174,2,4,4,4,4,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +73573,18969,Male,Loyal Customer,12,Personal Travel,Eco Plus,551,3,2,3,1,3,3,4,3,2,3,1,2,2,3,0,0.0,neutral or dissatisfied +73574,26847,Male,Loyal Customer,18,Business travel,Business,224,4,2,2,2,1,1,4,1,4,1,4,4,3,1,0,0.0,neutral or dissatisfied +73575,101095,Female,Loyal Customer,44,Business travel,Business,583,4,4,4,4,2,5,4,5,5,5,5,5,5,5,5,0.0,satisfied +73576,70705,Female,disloyal Customer,24,Business travel,Business,675,0,0,0,3,2,0,2,2,3,4,5,5,4,2,7,10.0,satisfied +73577,6690,Male,disloyal Customer,22,Business travel,Business,258,4,0,4,3,4,3,3,3,3,5,4,3,5,3,170,210.0,satisfied +73578,74280,Male,Loyal Customer,31,Business travel,Business,2311,2,3,3,3,2,2,2,2,3,1,1,2,1,2,0,0.0,neutral or dissatisfied +73579,89089,Male,Loyal Customer,55,Business travel,Business,2139,5,5,5,5,5,4,4,5,5,5,5,5,5,3,11,12.0,satisfied +73580,24500,Female,Loyal Customer,35,Personal Travel,Eco,547,5,4,5,3,2,5,2,2,3,3,4,2,3,2,0,0.0,satisfied +73581,42444,Male,Loyal Customer,52,Business travel,Business,866,1,1,1,1,4,4,5,5,5,5,5,3,5,4,10,0.0,satisfied +73582,113944,Female,Loyal Customer,41,Business travel,Business,1838,4,2,3,3,3,2,3,4,4,4,4,1,4,3,0,23.0,neutral or dissatisfied +73583,41204,Female,Loyal Customer,55,Business travel,Business,1091,5,5,5,5,2,1,2,4,4,4,4,1,4,4,0,0.0,satisfied +73584,50786,Male,Loyal Customer,35,Personal Travel,Eco,190,3,3,3,4,4,3,4,4,3,5,3,4,3,4,20,15.0,neutral or dissatisfied +73585,92833,Male,Loyal Customer,40,Personal Travel,Eco,1587,2,3,2,2,1,2,1,1,2,1,3,2,2,1,0,0.0,neutral or dissatisfied +73586,12249,Male,Loyal Customer,53,Business travel,Business,2763,4,4,4,4,2,5,2,5,5,4,5,3,5,3,0,0.0,satisfied +73587,46094,Male,Loyal Customer,27,Business travel,Eco Plus,495,5,5,5,5,5,5,5,5,3,4,2,1,4,5,5,17.0,satisfied +73588,121691,Female,Loyal Customer,48,Personal Travel,Eco,328,3,3,3,4,3,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +73589,127415,Male,Loyal Customer,46,Personal Travel,Eco,868,4,5,4,3,2,4,2,2,3,4,3,3,3,2,1,0.0,satisfied +73590,22564,Male,Loyal Customer,33,Business travel,Business,300,1,1,1,1,4,4,4,4,2,1,1,2,4,4,0,0.0,satisfied +73591,26993,Female,Loyal Customer,23,Business travel,Business,2081,2,2,2,2,3,3,3,3,1,2,4,2,1,3,47,39.0,satisfied +73592,56615,Female,Loyal Customer,26,Business travel,Business,3163,4,4,4,4,5,4,5,5,4,5,5,4,4,5,0,0.0,satisfied +73593,110044,Male,Loyal Customer,24,Business travel,Business,2173,1,1,1,1,5,5,5,5,5,2,3,5,5,5,19,5.0,satisfied +73594,113250,Female,Loyal Customer,32,Personal Travel,Business,407,1,4,1,1,3,1,3,3,3,1,5,4,5,3,24,12.0,neutral or dissatisfied +73595,50699,Male,Loyal Customer,67,Personal Travel,Eco,308,2,5,2,4,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +73596,19864,Male,Loyal Customer,30,Personal Travel,Eco,585,3,5,3,5,2,3,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +73597,7271,Male,Loyal Customer,26,Personal Travel,Eco,139,3,4,3,3,2,3,1,2,4,4,4,4,4,2,73,65.0,neutral or dissatisfied +73598,73401,Female,Loyal Customer,51,Business travel,Business,1197,1,1,1,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +73599,74366,Male,Loyal Customer,35,Business travel,Business,1235,1,1,1,1,2,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +73600,65258,Male,Loyal Customer,58,Business travel,Eco Plus,190,4,2,2,2,4,4,4,4,1,3,3,1,3,4,28,16.0,neutral or dissatisfied +73601,71989,Male,Loyal Customer,48,Personal Travel,Eco,1437,4,5,4,3,2,4,2,2,4,4,4,4,5,2,51,38.0,neutral or dissatisfied +73602,50344,Male,disloyal Customer,25,Business travel,Eco,337,2,0,2,1,3,2,3,3,1,3,2,1,4,3,0,0.0,neutral or dissatisfied +73603,83118,Male,Loyal Customer,10,Personal Travel,Eco,1145,4,5,4,2,1,4,1,1,5,2,3,4,4,1,58,50.0,neutral or dissatisfied +73604,128296,Male,Loyal Customer,44,Business travel,Business,370,1,1,1,1,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +73605,58894,Female,Loyal Customer,51,Business travel,Business,3049,1,3,3,3,4,2,2,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +73606,103185,Female,Loyal Customer,79,Business travel,Eco Plus,272,3,4,4,4,4,3,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +73607,37311,Female,Loyal Customer,29,Business travel,Business,1076,2,2,2,2,4,4,4,4,3,5,1,2,4,4,0,0.0,satisfied +73608,54181,Female,Loyal Customer,46,Business travel,Business,1000,2,4,4,4,1,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +73609,50365,Female,Loyal Customer,50,Business travel,Business,2166,3,3,3,3,4,1,2,4,4,4,4,2,4,5,0,0.0,satisfied +73610,100810,Male,disloyal Customer,31,Business travel,Business,1167,2,3,3,4,3,3,5,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +73611,104714,Female,Loyal Customer,45,Business travel,Business,1342,3,4,4,4,3,3,3,2,1,2,2,3,3,3,186,181.0,neutral or dissatisfied +73612,16875,Male,Loyal Customer,48,Business travel,Business,708,3,4,4,4,5,3,3,3,3,3,3,3,3,3,35,43.0,neutral or dissatisfied +73613,10373,Female,Loyal Customer,52,Business travel,Business,224,1,1,1,1,2,4,5,5,5,5,5,3,5,3,1,14.0,satisfied +73614,22239,Male,Loyal Customer,47,Business travel,Business,238,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +73615,28949,Male,Loyal Customer,24,Business travel,Business,3481,1,1,2,1,4,4,4,4,3,4,3,3,4,4,7,0.0,satisfied +73616,27128,Male,disloyal Customer,22,Business travel,Eco,790,3,3,3,3,3,1,1,5,4,3,1,1,2,1,0,0.0,neutral or dissatisfied +73617,13786,Female,Loyal Customer,63,Personal Travel,Eco,878,1,0,1,3,2,3,4,2,2,1,5,3,2,5,0,3.0,neutral or dissatisfied +73618,26227,Male,Loyal Customer,55,Personal Travel,Eco,581,2,4,2,3,2,2,2,2,5,5,4,4,4,2,12,11.0,neutral or dissatisfied +73619,46161,Male,Loyal Customer,65,Personal Travel,Eco,516,3,1,3,3,3,3,3,3,4,3,4,4,3,3,15,15.0,neutral or dissatisfied +73620,85614,Male,Loyal Customer,32,Personal Travel,Eco,259,3,0,3,4,4,3,4,4,3,3,4,5,4,4,7,0.0,neutral or dissatisfied +73621,62602,Male,Loyal Customer,11,Personal Travel,Eco,1744,4,3,4,3,2,4,2,2,4,5,2,2,3,2,33,27.0,satisfied +73622,22824,Male,Loyal Customer,40,Business travel,Business,3983,4,1,1,1,2,3,3,3,3,3,4,1,3,2,39,24.0,neutral or dissatisfied +73623,104738,Female,Loyal Customer,50,Business travel,Eco,1246,3,1,1,1,1,3,3,4,4,3,4,4,4,3,102,117.0,neutral or dissatisfied +73624,126866,Male,Loyal Customer,63,Personal Travel,Eco,2125,2,4,2,4,3,2,3,3,4,1,4,4,4,3,8,1.0,neutral or dissatisfied +73625,44775,Female,disloyal Customer,24,Business travel,Business,1250,3,1,3,4,1,3,1,1,3,3,3,1,4,1,12,0.0,neutral or dissatisfied +73626,121088,Male,Loyal Customer,47,Personal Travel,Eco,196,3,4,3,2,1,3,1,1,5,2,5,3,5,1,0,18.0,neutral or dissatisfied +73627,15396,Female,Loyal Customer,59,Business travel,Business,1833,2,4,4,4,4,4,4,1,1,2,2,1,1,1,0,14.0,neutral or dissatisfied +73628,117693,Female,Loyal Customer,19,Personal Travel,Eco,2075,3,1,3,3,3,3,1,3,2,2,4,2,4,3,49,50.0,neutral or dissatisfied +73629,67703,Male,Loyal Customer,47,Business travel,Eco,1438,3,2,2,2,3,3,3,3,2,4,4,4,4,3,3,3.0,neutral or dissatisfied +73630,72922,Female,Loyal Customer,60,Business travel,Business,1089,3,3,3,3,3,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +73631,32723,Female,Loyal Customer,35,Business travel,Business,102,1,1,1,1,5,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +73632,115607,Male,disloyal Customer,61,Business travel,Business,337,2,2,2,2,5,2,5,5,4,2,4,3,4,5,119,109.0,satisfied +73633,95318,Male,Loyal Customer,39,Personal Travel,Eco,148,2,5,0,3,5,0,5,5,3,4,3,5,1,5,13,18.0,neutral or dissatisfied +73634,113478,Female,Loyal Customer,46,Business travel,Business,386,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +73635,64216,Female,Loyal Customer,48,Business travel,Business,1660,3,1,2,1,1,2,3,3,3,3,3,3,3,1,5,8.0,neutral or dissatisfied +73636,40774,Female,Loyal Customer,20,Business travel,Eco,588,4,1,1,1,4,4,4,4,2,4,3,3,1,4,19,17.0,satisfied +73637,89614,Female,Loyal Customer,28,Business travel,Business,2623,1,1,1,1,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +73638,89191,Female,Loyal Customer,22,Personal Travel,Eco,2139,2,4,2,3,2,2,1,2,3,2,4,5,4,2,2,0.0,neutral or dissatisfied +73639,74842,Female,Loyal Customer,17,Personal Travel,Eco,1797,2,5,2,3,5,2,5,5,4,4,3,5,4,5,0,0.0,neutral or dissatisfied +73640,2796,Female,Loyal Customer,70,Personal Travel,Eco,764,2,4,3,3,4,4,5,4,4,3,5,5,4,5,1,0.0,neutral or dissatisfied +73641,105684,Female,Loyal Customer,51,Business travel,Business,842,1,1,2,1,4,4,4,5,4,5,5,4,5,4,132,143.0,satisfied +73642,97435,Female,disloyal Customer,34,Business travel,Eco Plus,587,2,1,1,2,3,1,3,3,1,4,2,4,2,3,1,0.0,neutral or dissatisfied +73643,26816,Male,Loyal Customer,47,Business travel,Eco,224,4,1,1,1,4,4,4,4,5,2,3,1,2,4,0,0.0,satisfied +73644,106463,Female,Loyal Customer,47,Business travel,Business,1300,1,5,1,1,4,4,5,5,5,5,5,4,5,4,5,0.0,satisfied +73645,28810,Male,disloyal Customer,43,Business travel,Eco,697,2,2,2,2,3,2,3,3,1,1,5,4,2,3,40,24.0,neutral or dissatisfied +73646,31865,Female,disloyal Customer,25,Business travel,Eco,1369,5,5,5,2,1,5,1,1,3,2,5,5,2,1,0,0.0,satisfied +73647,68689,Male,Loyal Customer,35,Personal Travel,Eco,237,1,5,1,4,5,1,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +73648,40768,Male,Loyal Customer,43,Business travel,Business,2863,4,4,2,4,4,5,3,5,5,5,5,3,5,3,0,0.0,satisfied +73649,106699,Male,Loyal Customer,30,Business travel,Business,3048,1,3,3,3,1,1,1,1,2,5,3,1,4,1,22,12.0,neutral or dissatisfied +73650,43347,Male,Loyal Customer,55,Business travel,Eco,358,5,5,4,5,5,5,5,5,2,1,4,5,1,5,0,0.0,satisfied +73651,105893,Male,disloyal Customer,37,Business travel,Business,283,1,1,1,3,3,1,1,3,3,2,4,4,4,3,0,6.0,neutral or dissatisfied +73652,58587,Female,Loyal Customer,51,Business travel,Business,2326,2,2,2,2,5,5,4,4,4,4,4,3,4,4,19,12.0,satisfied +73653,57428,Male,Loyal Customer,41,Business travel,Business,3137,1,1,1,1,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +73654,104122,Male,Loyal Customer,50,Business travel,Business,448,2,2,2,2,5,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +73655,74515,Male,Loyal Customer,59,Business travel,Business,1464,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +73656,13450,Female,Loyal Customer,32,Personal Travel,Eco,409,1,2,1,3,5,1,5,5,3,1,3,1,4,5,0,1.0,neutral or dissatisfied +73657,90315,Female,Loyal Customer,42,Personal Travel,Eco Plus,757,2,5,1,2,5,4,4,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +73658,221,Female,Loyal Customer,36,Personal Travel,Eco,213,2,0,2,2,3,2,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +73659,101541,Female,Loyal Customer,69,Personal Travel,Eco,345,1,3,1,4,5,4,4,4,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +73660,1196,Female,Loyal Customer,9,Personal Travel,Eco,354,3,5,3,1,4,3,4,4,1,1,5,4,4,4,2,9.0,neutral or dissatisfied +73661,57434,Male,Loyal Customer,46,Business travel,Business,1735,1,1,1,1,4,3,5,5,5,4,5,4,5,5,8,0.0,satisfied +73662,82612,Male,disloyal Customer,24,Business travel,Eco,128,4,0,4,1,2,4,5,2,5,5,3,5,3,2,0,0.0,satisfied +73663,81803,Female,disloyal Customer,22,Business travel,Business,1310,4,0,4,5,4,4,2,4,4,3,5,5,5,4,0,0.0,satisfied +73664,37568,Male,Loyal Customer,22,Business travel,Business,944,2,2,3,2,2,2,2,2,2,3,3,3,4,2,29,35.0,neutral or dissatisfied +73665,84072,Male,disloyal Customer,21,Business travel,Eco,773,3,3,3,2,4,3,4,4,4,4,4,4,5,4,0,3.0,neutral or dissatisfied +73666,28583,Male,Loyal Customer,42,Personal Travel,Eco,2607,5,3,5,3,4,5,2,4,5,1,5,1,2,4,1,0.0,satisfied +73667,97141,Male,disloyal Customer,31,Business travel,Business,1164,1,1,1,3,1,1,1,1,3,2,3,1,2,1,4,0.0,neutral or dissatisfied +73668,34115,Male,disloyal Customer,24,Business travel,Eco,1046,5,5,5,3,1,5,1,1,3,2,1,3,1,1,112,108.0,satisfied +73669,124705,Male,Loyal Customer,37,Personal Travel,Eco,399,2,4,2,3,3,2,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +73670,10731,Female,Loyal Customer,51,Business travel,Business,458,1,4,2,4,4,3,3,1,1,1,1,1,1,3,1,4.0,neutral or dissatisfied +73671,75308,Male,Loyal Customer,53,Business travel,Business,2556,3,3,3,3,5,5,5,3,3,3,4,5,5,5,0,0.0,satisfied +73672,88542,Female,Loyal Customer,41,Personal Travel,Eco,270,3,3,3,3,2,3,1,2,3,5,3,4,2,2,0,0.0,neutral or dissatisfied +73673,52165,Male,Loyal Customer,37,Business travel,Eco,509,4,2,2,2,4,4,4,4,4,2,4,5,1,4,0,3.0,satisfied +73674,46488,Female,disloyal Customer,22,Business travel,Eco,125,3,0,3,2,5,3,4,5,4,4,3,2,2,5,88,91.0,neutral or dissatisfied +73675,13145,Male,Loyal Customer,65,Personal Travel,Eco,562,4,4,5,4,2,5,2,2,1,3,4,3,3,2,0,5.0,satisfied +73676,90009,Male,Loyal Customer,29,Personal Travel,Business,1084,2,5,2,3,3,2,3,3,4,4,5,5,4,3,1,0.0,neutral or dissatisfied +73677,7676,Male,Loyal Customer,49,Business travel,Business,3887,2,5,5,5,2,2,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +73678,113434,Male,disloyal Customer,25,Business travel,Business,226,2,0,2,3,4,2,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +73679,59713,Female,disloyal Customer,29,Business travel,Business,965,0,0,0,1,1,5,4,1,3,5,4,4,4,1,0,6.0,satisfied +73680,12668,Female,Loyal Customer,55,Business travel,Business,3501,1,1,2,1,5,2,1,4,4,4,4,4,4,4,30,29.0,satisfied +73681,4324,Male,Loyal Customer,58,Personal Travel,Eco,589,3,4,3,4,4,3,4,4,4,5,5,5,4,4,8,20.0,neutral or dissatisfied +73682,69474,Female,Loyal Customer,51,Personal Travel,Eco,1096,1,5,1,5,4,3,5,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +73683,89503,Female,Loyal Customer,41,Personal Travel,Eco,655,2,5,2,3,4,2,1,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +73684,17337,Male,Loyal Customer,29,Business travel,Business,563,4,4,4,4,5,5,5,5,4,2,2,2,3,5,0,0.0,satisfied +73685,115557,Female,Loyal Customer,27,Business travel,Business,2676,4,3,3,3,4,4,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +73686,117178,Female,Loyal Customer,44,Personal Travel,Eco,325,3,3,3,3,5,2,1,3,3,3,2,1,3,3,0,0.0,neutral or dissatisfied +73687,78616,Female,Loyal Customer,70,Business travel,Business,1426,3,4,4,4,1,4,3,3,3,3,3,1,3,3,0,2.0,neutral or dissatisfied +73688,126927,Female,disloyal Customer,34,Business travel,Business,370,4,4,4,2,5,4,5,5,4,2,5,4,4,5,129,123.0,neutral or dissatisfied +73689,63530,Female,disloyal Customer,19,Business travel,Eco,1009,2,2,2,3,5,2,5,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +73690,55195,Female,Loyal Customer,67,Personal Travel,Eco Plus,1504,4,5,4,2,5,3,3,5,5,4,5,1,5,5,6,0.0,neutral or dissatisfied +73691,33467,Male,Loyal Customer,14,Personal Travel,Eco Plus,2556,3,3,3,3,2,3,2,2,1,2,4,4,3,2,22,25.0,neutral or dissatisfied +73692,125245,Female,Loyal Customer,52,Business travel,Business,427,2,3,3,3,4,4,4,2,2,2,2,1,2,4,4,7.0,neutral or dissatisfied +73693,8905,Female,disloyal Customer,22,Business travel,Business,510,4,0,4,4,2,4,2,2,5,3,4,3,4,2,34,50.0,satisfied +73694,36078,Female,Loyal Customer,58,Personal Travel,Eco,399,4,3,4,4,4,1,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +73695,7160,Female,disloyal Customer,26,Business travel,Business,139,2,4,2,3,4,2,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +73696,46994,Female,Loyal Customer,29,Business travel,Eco Plus,845,0,0,0,4,5,0,3,5,4,3,4,2,5,5,99,100.0,satisfied +73697,107312,Female,Loyal Customer,42,Personal Travel,Eco,283,1,4,1,1,4,4,4,4,4,1,4,3,4,4,1,0.0,neutral or dissatisfied +73698,79006,Male,Loyal Customer,19,Business travel,Business,226,1,3,3,3,1,1,1,1,3,3,3,3,3,1,29,26.0,neutral or dissatisfied +73699,105355,Male,Loyal Customer,44,Personal Travel,Eco,528,2,4,2,2,5,2,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +73700,63634,Female,Loyal Customer,23,Business travel,Eco,602,4,4,4,4,4,4,2,4,2,2,3,2,4,4,18,14.0,neutral or dissatisfied +73701,99595,Male,Loyal Customer,37,Personal Travel,Eco,802,0,4,0,5,4,0,4,4,4,3,4,3,5,4,0,0.0,satisfied +73702,28281,Male,Loyal Customer,33,Personal Travel,Eco,2402,2,1,2,3,2,1,1,3,2,3,3,1,2,1,0,0.0,neutral or dissatisfied +73703,99941,Female,disloyal Customer,23,Business travel,Business,2237,0,0,0,2,2,0,2,2,3,2,5,5,4,2,0,0.0,satisfied +73704,94927,Male,Loyal Customer,42,Business travel,Eco,277,4,4,2,4,4,4,4,4,2,3,3,3,3,4,87,64.0,neutral or dissatisfied +73705,53066,Male,Loyal Customer,11,Personal Travel,Eco,1208,3,3,3,2,4,3,2,4,3,1,2,3,2,4,0,17.0,neutral or dissatisfied +73706,44933,Male,disloyal Customer,43,Business travel,Eco,397,1,0,1,5,1,1,1,1,5,4,5,3,2,1,2,13.0,neutral or dissatisfied +73707,9222,Male,Loyal Customer,43,Business travel,Business,3894,2,2,2,2,2,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +73708,3051,Female,Loyal Customer,30,Business travel,Business,489,2,2,2,2,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +73709,18946,Female,Loyal Customer,59,Personal Travel,Eco,551,4,3,4,4,1,4,4,2,2,4,2,1,2,3,52,120.0,neutral or dissatisfied +73710,46523,Female,Loyal Customer,50,Business travel,Business,1515,2,2,2,2,2,3,5,4,4,4,4,5,4,1,0,0.0,satisfied +73711,69045,Male,Loyal Customer,55,Business travel,Business,1389,2,2,2,2,5,3,4,2,2,2,2,4,2,3,4,1.0,neutral or dissatisfied +73712,72633,Female,Loyal Customer,28,Personal Travel,Eco,929,4,5,4,3,2,4,2,2,5,5,4,3,4,2,20,17.0,neutral or dissatisfied +73713,125636,Male,Loyal Customer,46,Business travel,Business,759,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +73714,61756,Female,Loyal Customer,50,Personal Travel,Eco,1608,1,2,1,3,1,2,4,3,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +73715,58799,Female,Loyal Customer,38,Business travel,Business,3293,5,5,5,5,5,1,2,5,5,5,5,2,5,5,0,0.0,satisfied +73716,61254,Male,Loyal Customer,63,Personal Travel,Eco,967,4,4,4,3,3,4,3,3,2,3,4,2,4,3,9,36.0,neutral or dissatisfied +73717,83305,Male,Loyal Customer,50,Personal Travel,Eco Plus,1979,3,3,3,2,5,3,5,5,5,1,5,4,1,5,4,2.0,neutral or dissatisfied +73718,10507,Male,Loyal Customer,39,Business travel,Business,2178,4,4,4,4,2,5,4,5,5,5,5,4,5,5,36,39.0,satisfied +73719,32142,Male,Loyal Customer,46,Business travel,Eco,102,4,5,5,5,4,4,4,4,5,2,2,5,2,4,4,8.0,satisfied +73720,232,Female,Loyal Customer,57,Business travel,Business,213,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +73721,40286,Female,Loyal Customer,63,Personal Travel,Eco,463,4,5,4,4,1,5,4,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +73722,49523,Female,disloyal Customer,39,Business travel,Eco,110,3,3,3,3,5,3,5,5,3,5,4,3,4,5,30,19.0,neutral or dissatisfied +73723,60379,Female,disloyal Customer,50,Business travel,Business,1452,1,1,1,4,1,1,1,1,4,2,5,4,4,1,1,4.0,neutral or dissatisfied +73724,90050,Male,Loyal Customer,42,Business travel,Business,1548,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +73725,106796,Female,Loyal Customer,26,Business travel,Business,977,3,4,5,5,3,3,3,3,2,3,3,1,3,3,8,15.0,neutral or dissatisfied +73726,12082,Female,Loyal Customer,9,Personal Travel,Eco Plus,351,3,3,3,2,2,3,3,2,1,1,2,4,3,2,20,28.0,neutral or dissatisfied +73727,6007,Female,disloyal Customer,38,Business travel,Business,691,3,3,3,2,4,3,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +73728,103761,Female,Loyal Customer,32,Business travel,Business,3144,1,1,1,1,3,4,3,3,3,3,5,5,4,3,80,83.0,satisfied +73729,77564,Male,disloyal Customer,24,Business travel,Eco Plus,986,3,3,3,3,5,3,5,5,4,4,3,2,4,5,18,3.0,neutral or dissatisfied +73730,61422,Male,Loyal Customer,41,Business travel,Business,2419,5,5,4,5,5,5,4,5,5,5,5,4,5,4,0,5.0,satisfied +73731,75109,Female,Loyal Customer,26,Business travel,Business,1846,3,3,1,3,5,5,5,5,4,5,5,4,4,5,11,1.0,satisfied +73732,46949,Male,Loyal Customer,42,Personal Travel,Eco,848,5,4,5,1,4,5,4,4,3,5,4,5,5,4,23,18.0,satisfied +73733,52875,Male,disloyal Customer,25,Business travel,Eco,1024,2,2,2,3,2,5,5,1,2,3,4,5,2,5,174,166.0,neutral or dissatisfied +73734,30461,Female,disloyal Customer,22,Business travel,Eco,991,3,3,3,1,3,3,2,3,4,1,1,4,4,3,0,0.0,neutral or dissatisfied +73735,101291,Male,disloyal Customer,63,Business travel,Business,363,3,3,3,3,2,3,2,2,3,2,3,3,4,2,53,35.0,neutral or dissatisfied +73736,8244,Male,Loyal Customer,10,Personal Travel,Eco,125,2,5,2,1,5,2,5,5,5,1,1,4,5,5,6,9.0,neutral or dissatisfied +73737,18356,Male,Loyal Customer,36,Personal Travel,Eco,314,2,4,2,1,4,2,4,4,3,5,4,4,5,4,6,1.0,neutral or dissatisfied +73738,84354,Female,Loyal Customer,38,Business travel,Eco,606,3,5,5,5,3,3,3,3,1,5,4,3,4,3,0,12.0,neutral or dissatisfied +73739,31432,Female,Loyal Customer,32,Personal Travel,Eco,1607,3,4,3,1,3,3,3,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +73740,57902,Male,disloyal Customer,18,Business travel,Business,305,5,5,5,2,5,5,1,5,4,5,5,3,4,5,3,0.0,satisfied +73741,89847,Female,Loyal Customer,19,Personal Travel,Business,1416,4,2,4,3,1,4,1,1,2,2,3,3,4,1,0,0.0,satisfied +73742,76877,Female,Loyal Customer,51,Business travel,Business,1584,1,1,1,1,3,5,5,5,5,5,5,3,5,3,0,6.0,satisfied +73743,12714,Male,Loyal Customer,11,Business travel,Eco,689,3,2,2,2,3,3,1,3,3,1,2,2,2,3,53,39.0,neutral or dissatisfied +73744,3880,Male,disloyal Customer,21,Business travel,Eco,213,5,0,5,4,5,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +73745,127290,Male,Loyal Customer,52,Business travel,Business,1107,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,2.0,satisfied +73746,120678,Male,disloyal Customer,25,Business travel,Business,280,1,5,1,2,4,1,4,4,1,1,5,1,3,4,0,2.0,neutral or dissatisfied +73747,10043,Female,disloyal Customer,37,Business travel,Business,326,4,4,4,2,4,4,4,4,4,5,5,4,5,4,276,293.0,satisfied +73748,30342,Male,Loyal Customer,56,Personal Travel,Eco,391,0,4,0,5,3,0,1,3,3,3,3,1,4,3,0,0.0,satisfied +73749,9210,Male,Loyal Customer,53,Business travel,Business,2699,4,4,4,4,2,4,5,3,3,4,4,5,3,4,77,79.0,satisfied +73750,45146,Male,disloyal Customer,21,Business travel,Eco,174,4,0,4,4,3,4,3,3,2,1,1,1,3,3,6,3.0,neutral or dissatisfied +73751,97936,Female,disloyal Customer,30,Business travel,Eco,612,3,4,3,4,2,3,5,2,2,5,4,2,4,2,67,64.0,neutral or dissatisfied +73752,40432,Male,Loyal Customer,38,Business travel,Business,222,2,2,2,2,3,4,3,5,5,5,5,5,5,5,0,0.0,satisfied +73753,64080,Male,Loyal Customer,37,Personal Travel,Eco,919,1,5,1,2,1,3,2,5,3,4,5,2,4,2,188,184.0,neutral or dissatisfied +73754,112884,Female,disloyal Customer,39,Business travel,Business,1390,2,2,2,4,3,2,3,3,4,1,4,3,4,3,28,22.0,neutral or dissatisfied +73755,88333,Male,disloyal Customer,33,Business travel,Business,581,3,3,3,5,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +73756,42592,Female,Loyal Customer,36,Business travel,Eco,801,4,1,1,1,4,4,4,4,3,2,1,5,3,4,9,25.0,satisfied +73757,86896,Female,Loyal Customer,41,Business travel,Business,3638,2,2,2,2,4,4,5,4,4,4,4,4,4,5,9,3.0,satisfied +73758,86201,Male,Loyal Customer,41,Business travel,Business,3265,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +73759,14120,Female,Loyal Customer,18,Personal Travel,Business,413,5,4,5,4,5,5,2,5,3,4,5,3,4,5,7,0.0,satisfied +73760,78168,Female,Loyal Customer,32,Business travel,Business,2129,3,3,3,3,4,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +73761,28826,Female,disloyal Customer,22,Business travel,Eco,954,2,3,3,3,3,3,1,3,3,4,4,3,3,3,0,14.0,neutral or dissatisfied +73762,27069,Male,Loyal Customer,30,Personal Travel,Eco,1399,2,4,2,3,2,2,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +73763,65967,Male,disloyal Customer,27,Business travel,Business,1372,4,4,4,3,2,4,2,2,4,5,5,3,5,2,60,22.0,neutral or dissatisfied +73764,66127,Male,Loyal Customer,25,Personal Travel,Eco,583,1,4,1,4,3,1,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +73765,59846,Female,Loyal Customer,40,Business travel,Business,1698,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +73766,41656,Female,Loyal Customer,31,Business travel,Eco,347,1,1,1,1,1,2,1,1,2,2,3,4,3,1,0,11.0,neutral or dissatisfied +73767,24473,Female,Loyal Customer,43,Business travel,Business,481,3,1,1,1,2,2,2,3,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +73768,122789,Male,Loyal Customer,50,Business travel,Eco,599,2,2,2,2,2,2,2,2,2,1,3,1,4,2,0,0.0,neutral or dissatisfied +73769,44558,Male,Loyal Customer,30,Business travel,Eco Plus,231,3,3,3,3,3,3,3,3,4,1,3,2,3,3,37,22.0,neutral or dissatisfied +73770,89997,Female,disloyal Customer,15,Business travel,Eco,1084,1,1,1,5,1,5,2,3,5,5,4,2,3,2,152,153.0,neutral or dissatisfied +73771,126072,Female,Loyal Customer,57,Business travel,Business,1672,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +73772,50950,Male,Loyal Customer,26,Personal Travel,Eco,209,3,3,3,2,4,3,4,4,3,3,3,5,4,4,0,0.0,neutral or dissatisfied +73773,23651,Male,Loyal Customer,17,Personal Travel,Business,212,5,4,5,5,2,5,2,2,3,3,5,4,4,2,0,0.0,satisfied +73774,98897,Male,Loyal Customer,56,Business travel,Business,543,5,5,5,5,4,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +73775,890,Female,Loyal Customer,55,Business travel,Business,2431,1,2,2,2,3,3,4,2,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +73776,63278,Male,Loyal Customer,36,Business travel,Business,337,0,0,0,2,5,4,5,5,5,5,5,3,5,3,13,0.0,satisfied +73777,112532,Female,Loyal Customer,15,Personal Travel,Eco,862,1,4,1,1,1,1,2,1,4,5,5,5,4,1,5,0.0,neutral or dissatisfied +73778,23976,Male,Loyal Customer,32,Personal Travel,Eco,596,4,4,4,4,2,4,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +73779,77629,Female,Loyal Customer,54,Business travel,Business,3936,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +73780,5393,Male,Loyal Customer,17,Personal Travel,Eco,733,2,3,2,2,1,2,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +73781,3731,Female,Loyal Customer,32,Personal Travel,Eco,431,3,5,3,2,2,3,4,2,1,3,4,4,1,2,71,95.0,neutral or dissatisfied +73782,109258,Female,Loyal Customer,30,Business travel,Eco Plus,793,3,1,4,1,3,3,3,3,2,2,3,3,4,3,90,76.0,neutral or dissatisfied +73783,28423,Female,disloyal Customer,25,Business travel,Eco,999,1,1,1,2,1,1,1,1,5,1,1,3,3,1,0,0.0,neutral or dissatisfied +73784,96166,Female,Loyal Customer,45,Business travel,Business,687,1,1,1,1,5,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +73785,96187,Male,Loyal Customer,46,Business travel,Business,546,1,1,1,1,3,5,5,5,5,5,5,5,5,4,6,0.0,satisfied +73786,25356,Female,disloyal Customer,37,Business travel,Eco,591,1,0,1,2,4,1,3,4,4,1,5,2,1,4,0,0.0,neutral or dissatisfied +73787,40894,Male,Loyal Customer,12,Personal Travel,Eco,590,2,5,3,4,5,3,5,5,5,1,1,3,4,5,0,0.0,neutral or dissatisfied +73788,125861,Female,disloyal Customer,38,Business travel,Business,992,2,2,2,1,1,2,1,1,5,4,4,5,4,1,0,1.0,neutral or dissatisfied +73789,36604,Male,disloyal Customer,25,Business travel,Eco,1237,4,4,4,5,2,4,2,2,4,1,4,2,2,2,1,0.0,neutral or dissatisfied +73790,16628,Female,Loyal Customer,37,Business travel,Business,605,5,5,2,5,2,4,5,5,5,5,5,4,5,3,13,4.0,satisfied +73791,96552,Female,disloyal Customer,38,Business travel,Business,302,5,5,5,5,4,5,4,4,5,3,4,3,4,4,0,0.0,satisfied +73792,115449,Female,disloyal Customer,23,Business travel,Eco,417,4,0,5,4,3,5,3,3,3,1,3,1,4,3,25,12.0,neutral or dissatisfied +73793,79138,Male,Loyal Customer,65,Business travel,Eco Plus,226,4,2,2,2,4,4,4,4,4,1,3,4,4,4,0,0.0,neutral or dissatisfied +73794,102202,Male,Loyal Customer,51,Business travel,Business,3235,5,5,5,5,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +73795,122902,Female,disloyal Customer,28,Business travel,Business,600,3,3,3,2,5,3,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +73796,72894,Female,Loyal Customer,44,Personal Travel,Business,1089,5,3,5,3,5,3,3,1,1,5,1,2,1,1,11,0.0,satisfied +73797,15377,Female,Loyal Customer,40,Business travel,Business,3632,4,1,1,1,5,3,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +73798,28080,Male,Loyal Customer,39,Business travel,Business,2172,5,5,5,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +73799,100520,Female,Loyal Customer,63,Personal Travel,Eco,580,3,5,3,2,5,4,4,2,2,3,3,4,2,4,0,0.0,neutral or dissatisfied +73800,82645,Female,Loyal Customer,46,Business travel,Business,120,2,2,3,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +73801,38300,Female,Loyal Customer,40,Business travel,Eco,2583,4,5,3,5,4,4,4,1,4,4,4,4,1,4,23,19.0,neutral or dissatisfied +73802,4557,Female,Loyal Customer,59,Business travel,Business,3724,3,3,5,3,5,5,5,4,4,4,4,4,4,5,0,6.0,satisfied +73803,76279,Female,Loyal Customer,41,Business travel,Business,2850,4,4,4,4,5,1,5,5,5,5,5,4,5,2,2,0.0,satisfied +73804,128990,Male,Loyal Customer,33,Business travel,Business,2621,5,5,5,5,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +73805,76286,Female,Loyal Customer,25,Business travel,Business,1927,2,2,2,2,4,4,4,4,5,5,3,4,4,4,0,0.0,satisfied +73806,58299,Female,disloyal Customer,30,Business travel,Eco Plus,678,2,2,2,3,4,2,4,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +73807,58609,Female,disloyal Customer,23,Business travel,Eco,334,1,4,0,4,1,0,1,1,1,2,4,2,4,1,17,9.0,neutral or dissatisfied +73808,56248,Female,Loyal Customer,47,Business travel,Business,1702,5,5,5,5,4,5,4,3,3,4,3,3,3,5,5,18.0,satisfied +73809,126317,Male,Loyal Customer,47,Personal Travel,Eco,468,3,4,3,1,2,3,2,2,4,4,5,3,4,2,20,14.0,neutral or dissatisfied +73810,77596,Male,Loyal Customer,43,Business travel,Business,3059,4,4,4,4,3,4,5,4,4,4,4,5,4,4,56,65.0,satisfied +73811,45485,Female,Loyal Customer,24,Business travel,Business,274,5,1,5,5,4,4,4,4,2,2,1,2,5,4,0,3.0,satisfied +73812,116474,Female,Loyal Customer,54,Personal Travel,Eco,342,1,3,1,4,3,5,4,3,3,1,3,3,3,5,31,9.0,neutral or dissatisfied +73813,85169,Female,disloyal Customer,36,Business travel,Eco,689,3,3,3,4,3,2,2,1,4,3,4,2,4,2,143,126.0,neutral or dissatisfied +73814,60812,Male,disloyal Customer,38,Business travel,Eco,524,3,2,3,4,4,3,5,4,2,2,4,1,3,4,12,17.0,neutral or dissatisfied +73815,51318,Male,Loyal Customer,46,Business travel,Eco Plus,337,4,5,5,5,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +73816,33412,Male,Loyal Customer,23,Business travel,Business,2614,1,1,1,1,4,4,4,1,1,5,2,4,2,4,0,60.0,satisfied +73817,123979,Male,Loyal Customer,47,Business travel,Business,3253,2,4,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +73818,95291,Male,Loyal Customer,37,Personal Travel,Eco,239,1,3,0,4,1,0,1,1,3,2,3,3,3,1,0,8.0,neutral or dissatisfied +73819,95461,Male,Loyal Customer,58,Business travel,Business,3879,0,4,0,2,3,4,5,3,3,3,3,4,3,5,7,15.0,satisfied +73820,123058,Male,disloyal Customer,44,Business travel,Business,590,3,3,3,1,1,3,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +73821,91242,Female,Loyal Customer,20,Personal Travel,Eco,404,2,4,2,3,3,2,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +73822,4034,Female,Loyal Customer,37,Business travel,Business,419,4,4,4,4,2,3,1,5,5,5,5,4,5,1,0,0.0,satisfied +73823,107367,Male,Loyal Customer,37,Business travel,Business,3768,4,4,4,4,5,5,5,5,5,4,5,4,5,4,11,17.0,satisfied +73824,110867,Male,disloyal Customer,43,Business travel,Business,406,4,4,4,3,3,4,3,3,5,4,4,4,5,3,20,21.0,satisfied +73825,53808,Male,Loyal Customer,30,Business travel,Business,3377,4,4,4,4,5,5,5,5,3,3,5,2,2,5,5,0.0,satisfied +73826,45992,Female,disloyal Customer,12,Business travel,Eco,483,1,1,1,4,2,1,2,2,3,5,4,1,3,2,0,0.0,neutral or dissatisfied +73827,78647,Male,Loyal Customer,19,Business travel,Business,2172,2,1,2,1,2,2,2,2,3,4,1,4,2,2,0,0.0,neutral or dissatisfied +73828,44399,Male,Loyal Customer,59,Business travel,Business,342,4,1,1,1,1,3,3,4,4,3,4,1,4,4,0,16.0,neutral or dissatisfied +73829,23151,Female,Loyal Customer,74,Business travel,Business,3287,2,2,2,2,2,1,4,4,4,4,4,3,4,5,0,0.0,satisfied +73830,125149,Female,disloyal Customer,30,Business travel,Eco,764,2,2,2,4,3,2,3,3,1,1,4,4,3,3,26,4.0,neutral or dissatisfied +73831,40451,Female,Loyal Customer,44,Business travel,Eco,461,4,4,4,4,2,3,1,4,4,4,4,1,4,1,0,0.0,satisfied +73832,113577,Male,Loyal Customer,52,Business travel,Business,386,2,2,2,2,2,2,5,5,5,5,5,4,5,4,24,16.0,satisfied +73833,9813,Male,disloyal Customer,52,Business travel,Business,493,3,3,3,2,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +73834,68033,Male,disloyal Customer,27,Business travel,Business,868,0,0,0,4,5,0,5,5,3,3,4,5,4,5,3,0.0,satisfied +73835,29838,Male,Loyal Customer,60,Business travel,Business,399,3,3,3,3,4,2,3,4,4,4,4,3,4,2,55,50.0,satisfied +73836,69306,Male,Loyal Customer,48,Business travel,Business,1547,3,3,3,3,2,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +73837,50931,Female,Loyal Customer,67,Personal Travel,Eco,110,2,4,2,4,3,3,3,2,2,2,4,2,2,3,2,3.0,neutral or dissatisfied +73838,107545,Male,Loyal Customer,68,Business travel,Business,1521,1,0,0,3,4,3,3,1,1,0,1,2,1,3,14,11.0,neutral or dissatisfied +73839,6461,Female,disloyal Customer,40,Business travel,Business,315,3,3,3,1,3,3,3,3,5,4,4,5,4,3,2,0.0,neutral or dissatisfied +73840,53232,Male,Loyal Customer,40,Personal Travel,Eco,642,1,4,1,5,3,1,3,3,3,4,2,2,3,3,0,0.0,neutral or dissatisfied +73841,125228,Female,Loyal Customer,56,Business travel,Business,2040,4,4,4,4,5,5,4,4,4,4,4,4,4,4,2,4.0,satisfied +73842,60679,Female,Loyal Customer,34,Business travel,Business,1725,4,3,4,4,2,4,4,5,5,5,5,3,5,3,112,80.0,satisfied +73843,42098,Male,disloyal Customer,36,Business travel,Eco,964,2,2,2,3,2,2,3,2,4,5,1,1,2,2,0,0.0,neutral or dissatisfied +73844,107030,Female,disloyal Customer,20,Business travel,Eco,395,3,1,4,4,4,4,3,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +73845,60359,Male,Loyal Customer,41,Business travel,Business,1076,3,3,3,3,5,3,4,3,3,3,3,3,3,4,8,30.0,neutral or dissatisfied +73846,125168,Female,Loyal Customer,45,Business travel,Business,3409,2,2,2,2,5,4,5,1,1,2,1,4,1,5,0,0.0,satisfied +73847,47515,Female,Loyal Customer,18,Personal Travel,Eco,599,1,4,1,4,3,1,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +73848,8721,Female,Loyal Customer,59,Personal Travel,Eco,280,3,5,5,5,3,4,4,1,1,5,1,5,1,4,3,1.0,neutral or dissatisfied +73849,46492,Female,Loyal Customer,60,Business travel,Eco,141,4,1,1,1,5,5,3,4,4,4,4,5,4,5,2,0.0,satisfied +73850,1673,Female,Loyal Customer,54,Business travel,Business,3195,2,1,2,2,2,4,5,2,2,2,2,4,2,4,29,22.0,satisfied +73851,99213,Female,Loyal Customer,57,Business travel,Business,541,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +73852,103441,Female,Loyal Customer,53,Personal Travel,Business,393,4,5,3,2,2,4,5,4,4,3,4,3,4,4,0,0.0,satisfied +73853,38048,Male,Loyal Customer,27,Business travel,Business,3538,2,2,2,2,4,4,4,4,3,5,2,3,1,4,21,107.0,satisfied +73854,28503,Female,Loyal Customer,48,Business travel,Business,2701,4,4,4,4,5,4,5,5,5,5,5,1,5,1,5,0.0,satisfied +73855,16054,Female,Loyal Customer,54,Business travel,Eco,501,5,3,3,3,4,5,4,5,5,5,5,3,5,1,0,0.0,satisfied +73856,26720,Female,Loyal Customer,40,Business travel,Eco Plus,406,2,1,1,1,2,2,2,2,5,5,3,2,2,2,0,5.0,satisfied +73857,45140,Female,disloyal Customer,36,Business travel,Eco,174,1,4,1,2,2,1,2,2,3,3,1,3,1,2,0,0.0,neutral or dissatisfied +73858,83858,Male,Loyal Customer,57,Personal Travel,Eco,425,3,1,3,3,5,3,5,5,2,4,3,3,2,5,127,118.0,neutral or dissatisfied +73859,115839,Female,disloyal Customer,23,Business travel,Eco,404,5,0,5,3,3,5,4,3,4,1,3,2,2,3,0,3.0,satisfied +73860,109950,Female,Loyal Customer,18,Personal Travel,Eco,1079,2,1,2,2,2,4,4,2,2,2,3,4,1,4,184,179.0,neutral or dissatisfied +73861,74561,Female,disloyal Customer,42,Business travel,Business,1464,2,2,2,3,2,2,1,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +73862,57721,Male,Loyal Customer,44,Business travel,Business,1754,5,5,5,5,5,4,5,5,5,5,5,3,5,3,8,13.0,satisfied +73863,105769,Male,disloyal Customer,25,Business travel,Eco,663,2,4,2,4,4,2,4,4,3,1,1,1,3,4,0,0.0,neutral or dissatisfied +73864,42133,Male,Loyal Customer,54,Personal Travel,Eco Plus,991,4,4,4,5,2,4,2,2,3,2,5,4,4,2,0,0.0,satisfied +73865,6213,Male,disloyal Customer,22,Business travel,Eco,462,1,3,1,1,1,1,1,1,3,4,4,3,2,1,0,0.0,neutral or dissatisfied +73866,35976,Male,Loyal Customer,54,Business travel,Eco Plus,231,2,3,3,3,1,2,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +73867,125912,Female,Loyal Customer,56,Personal Travel,Eco,861,3,4,3,3,2,4,4,3,3,3,3,5,3,4,13,27.0,neutral or dissatisfied +73868,36960,Female,Loyal Customer,44,Business travel,Eco,899,2,2,2,2,4,5,5,2,2,2,2,1,2,5,41,24.0,satisfied +73869,123547,Male,disloyal Customer,55,Business travel,Business,1773,2,2,2,1,4,2,5,4,5,2,4,5,4,4,1,0.0,neutral or dissatisfied +73870,102129,Female,disloyal Customer,23,Business travel,Eco,223,2,5,2,3,4,2,4,4,3,5,4,3,5,4,37,30.0,neutral or dissatisfied +73871,25484,Male,Loyal Customer,41,Business travel,Business,481,2,2,2,2,1,4,4,5,5,5,5,4,5,3,3,0.0,satisfied +73872,10809,Female,Loyal Customer,43,Business travel,Business,2470,3,3,5,3,2,4,4,2,2,2,3,3,2,2,14,3.0,neutral or dissatisfied +73873,102707,Female,disloyal Customer,35,Business travel,Eco,601,2,0,2,3,2,2,2,2,4,2,3,5,1,2,0,0.0,neutral or dissatisfied +73874,122847,Male,disloyal Customer,38,Business travel,Business,226,4,4,4,3,1,4,1,1,5,4,4,4,5,1,3,2.0,satisfied +73875,77226,Male,Loyal Customer,50,Business travel,Business,1590,4,4,4,4,3,4,4,4,4,4,4,4,4,3,0,11.0,satisfied +73876,79811,Male,Loyal Customer,56,Business travel,Business,1096,3,3,5,3,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +73877,110751,Male,Loyal Customer,42,Business travel,Business,2023,2,2,4,2,4,5,4,4,4,4,4,4,4,4,31,20.0,satisfied +73878,119204,Male,Loyal Customer,54,Business travel,Business,1662,1,1,1,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +73879,55536,Male,disloyal Customer,29,Business travel,Eco,550,4,2,4,2,3,4,3,3,4,4,2,2,3,3,49,34.0,neutral or dissatisfied +73880,48482,Female,Loyal Customer,32,Business travel,Eco,846,5,4,4,4,5,5,5,5,3,1,1,3,3,5,0,0.0,satisfied +73881,16515,Male,Loyal Customer,42,Business travel,Eco Plus,143,1,3,3,3,1,1,1,1,4,5,3,4,4,1,41,37.0,neutral or dissatisfied +73882,40284,Female,Loyal Customer,62,Personal Travel,Eco,347,3,3,3,4,3,4,4,5,5,3,5,1,5,3,1,8.0,neutral or dissatisfied +73883,9949,Female,Loyal Customer,43,Business travel,Business,357,2,2,2,2,2,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +73884,23120,Male,Loyal Customer,22,Business travel,Eco,300,5,2,2,2,5,5,3,5,4,3,2,5,5,5,16,28.0,satisfied +73885,111728,Female,Loyal Customer,22,Business travel,Eco Plus,541,3,5,5,5,3,3,1,3,2,5,4,2,4,3,0,0.0,neutral or dissatisfied +73886,73667,Female,Loyal Customer,31,Business travel,Business,3846,3,2,2,2,2,2,3,2,3,3,4,1,4,2,16,18.0,neutral or dissatisfied +73887,2750,Female,Loyal Customer,38,Business travel,Business,2597,3,4,4,4,4,3,3,3,3,3,3,1,3,4,0,11.0,neutral or dissatisfied +73888,123192,Male,Loyal Customer,37,Personal Travel,Eco,650,2,3,3,4,5,3,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +73889,44972,Male,Loyal Customer,55,Business travel,Business,222,3,3,3,3,1,2,5,5,5,5,5,3,5,3,0,0.0,satisfied +73890,23052,Male,Loyal Customer,31,Business travel,Business,2123,4,4,4,4,5,4,5,5,4,1,4,1,4,5,3,0.0,satisfied +73891,40728,Male,disloyal Customer,26,Business travel,Eco,599,2,4,2,3,5,2,5,5,1,1,5,4,1,5,0,0.0,neutral or dissatisfied +73892,123691,Male,Loyal Customer,22,Personal Travel,Eco,214,0,3,0,4,4,0,4,4,1,2,5,5,1,4,0,0.0,satisfied +73893,98764,Female,disloyal Customer,21,Business travel,Eco,1292,5,5,5,1,3,5,3,3,5,2,2,5,2,3,16,0.0,satisfied +73894,76881,Male,Loyal Customer,46,Business travel,Business,630,5,5,5,5,5,5,4,5,5,5,5,5,5,3,9,7.0,satisfied +73895,101645,Female,Loyal Customer,24,Business travel,Eco,1749,2,2,2,2,2,2,2,2,1,4,2,1,3,2,12,4.0,neutral or dissatisfied +73896,76265,Female,Loyal Customer,46,Business travel,Business,1927,3,3,5,3,3,5,5,4,4,4,4,4,4,5,0,27.0,satisfied +73897,75880,Female,Loyal Customer,38,Personal Travel,Eco,1972,1,2,1,2,1,1,1,1,4,1,2,4,3,1,0,9.0,neutral or dissatisfied +73898,2404,Female,disloyal Customer,29,Business travel,Eco,641,4,1,5,3,5,5,1,5,1,5,4,1,4,5,0,0.0,neutral or dissatisfied +73899,65639,Female,Loyal Customer,52,Business travel,Business,237,0,0,0,4,4,5,4,5,5,1,1,3,5,5,0,0.0,satisfied +73900,54962,Female,Loyal Customer,41,Business travel,Business,1379,4,4,4,4,4,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +73901,66669,Male,Loyal Customer,53,Business travel,Business,1908,4,4,4,4,5,4,5,4,4,4,4,3,4,5,4,32.0,satisfied +73902,57091,Male,disloyal Customer,24,Business travel,Eco,1222,3,3,3,3,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +73903,34011,Female,Loyal Customer,23,Personal Travel,Eco,1598,2,4,2,1,2,2,2,2,3,2,4,3,4,2,31,30.0,neutral or dissatisfied +73904,47378,Female,Loyal Customer,31,Business travel,Business,588,3,2,3,2,3,3,3,3,3,1,1,4,1,3,0,0.0,neutral or dissatisfied +73905,57638,Male,Loyal Customer,59,Business travel,Business,3890,4,4,4,4,3,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +73906,57567,Male,disloyal Customer,28,Business travel,Eco,1271,2,2,2,4,3,2,3,3,2,1,2,3,4,3,53,52.0,neutral or dissatisfied +73907,6652,Female,Loyal Customer,21,Business travel,Eco Plus,416,3,1,1,1,3,3,2,3,2,2,3,4,3,3,38,45.0,neutral or dissatisfied +73908,47002,Female,Loyal Customer,51,Personal Travel,Eco Plus,848,3,4,3,4,4,5,5,1,1,3,5,5,1,3,0,2.0,neutral or dissatisfied +73909,95484,Male,Loyal Customer,60,Business travel,Business,677,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +73910,67367,Male,Loyal Customer,41,Business travel,Business,2593,2,2,2,2,3,5,5,5,5,5,5,4,5,4,5,8.0,satisfied +73911,51990,Female,Loyal Customer,59,Personal Travel,Eco Plus,936,4,4,4,3,5,4,4,1,1,4,1,4,1,2,0,0.0,neutral or dissatisfied +73912,33451,Male,Loyal Customer,53,Personal Travel,Eco,2556,3,1,3,4,2,3,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +73913,108260,Female,Loyal Customer,47,Business travel,Eco,495,5,2,2,2,5,1,1,5,5,5,5,1,5,4,0,3.0,satisfied +73914,56461,Male,Loyal Customer,8,Personal Travel,Eco,719,2,4,2,3,3,2,3,3,3,3,5,3,5,3,0,28.0,neutral or dissatisfied +73915,62625,Female,Loyal Customer,14,Personal Travel,Eco,1846,2,1,1,4,5,1,5,5,1,4,3,3,4,5,0,0.0,neutral or dissatisfied +73916,70590,Male,Loyal Customer,70,Personal Travel,Eco Plus,1258,3,5,3,2,3,3,3,3,4,5,3,5,5,3,0,0.0,neutral or dissatisfied +73917,118024,Male,Loyal Customer,10,Personal Travel,Business,1044,2,5,2,5,3,2,3,3,2,3,2,1,1,3,32,24.0,neutral or dissatisfied +73918,15597,Female,Loyal Customer,54,Business travel,Business,3475,2,4,4,4,3,2,2,2,2,2,2,4,2,1,0,3.0,neutral or dissatisfied +73919,107690,Male,disloyal Customer,36,Business travel,Business,251,1,1,1,2,2,1,5,2,3,2,4,3,4,2,6,0.0,neutral or dissatisfied +73920,68338,Female,disloyal Customer,49,Business travel,Business,1598,3,3,3,1,2,3,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +73921,119362,Female,Loyal Customer,33,Business travel,Business,399,2,2,5,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +73922,10446,Female,Loyal Customer,47,Business travel,Business,3788,0,5,0,1,5,5,5,4,4,4,4,3,4,4,33,35.0,satisfied +73923,86062,Male,disloyal Customer,58,Business travel,Eco Plus,447,1,0,0,4,5,1,5,5,1,4,3,1,3,5,1,0.0,neutral or dissatisfied +73924,48567,Male,Loyal Customer,55,Personal Travel,Eco,844,2,5,2,3,4,2,1,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +73925,103438,Female,Loyal Customer,31,Personal Travel,Eco Plus,237,4,5,4,1,5,4,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +73926,119926,Male,Loyal Customer,24,Business travel,Business,1531,1,1,1,1,4,4,4,4,5,2,5,5,4,4,0,0.0,satisfied +73927,58877,Male,Loyal Customer,39,Business travel,Eco,888,2,4,4,4,2,2,2,2,3,1,4,4,3,2,58,62.0,neutral or dissatisfied +73928,59655,Female,Loyal Customer,30,Personal Travel,Eco,787,4,1,5,4,1,5,1,1,1,5,4,1,4,1,7,3.0,neutral or dissatisfied +73929,71376,Female,Loyal Customer,48,Business travel,Eco,258,2,5,5,5,2,2,2,3,1,3,2,2,1,2,133,142.0,neutral or dissatisfied +73930,33449,Male,Loyal Customer,68,Personal Travel,Eco,2614,2,3,2,2,2,3,3,1,2,3,4,3,5,3,0,22.0,neutral or dissatisfied +73931,101472,Female,Loyal Customer,39,Business travel,Business,2783,1,1,1,1,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +73932,73118,Male,Loyal Customer,49,Personal Travel,Eco,2174,1,2,1,3,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +73933,121432,Male,Loyal Customer,45,Business travel,Eco,331,2,4,4,4,2,2,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +73934,19267,Male,Loyal Customer,22,Business travel,Business,3078,2,2,2,2,3,3,3,3,4,3,2,4,5,3,0,0.0,satisfied +73935,94012,Male,Loyal Customer,58,Business travel,Business,293,3,3,4,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +73936,66598,Female,Loyal Customer,55,Business travel,Business,761,3,2,2,2,4,4,3,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +73937,109920,Male,Loyal Customer,31,Personal Travel,Eco,1165,4,4,4,1,2,4,2,2,5,5,5,5,4,2,44,4.0,satisfied +73938,119790,Female,disloyal Customer,22,Business travel,Eco,1032,1,1,1,1,2,1,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +73939,105404,Male,Loyal Customer,64,Personal Travel,Eco,369,3,4,3,2,5,3,5,5,1,3,4,1,2,5,0,0.0,neutral or dissatisfied +73940,102400,Male,Loyal Customer,51,Business travel,Business,3679,1,1,1,1,4,4,5,5,5,5,5,5,5,2,0,0.0,satisfied +73941,110880,Male,disloyal Customer,36,Business travel,Eco,406,1,1,1,4,1,1,1,1,4,4,4,3,3,1,1,12.0,neutral or dissatisfied +73942,59177,Male,Loyal Customer,18,Personal Travel,Eco Plus,1846,3,5,3,1,2,3,2,2,1,4,5,1,5,2,46,22.0,neutral or dissatisfied +73943,86268,Female,Loyal Customer,51,Personal Travel,Eco,356,4,1,4,4,5,3,4,1,1,4,1,2,1,2,0,0.0,satisfied +73944,117795,Male,disloyal Customer,37,Business travel,Business,328,2,2,2,4,1,2,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +73945,1715,Female,Loyal Customer,54,Business travel,Business,327,0,0,0,3,3,5,5,1,1,1,1,5,1,5,0,0.0,satisfied +73946,60264,Female,Loyal Customer,72,Business travel,Eco Plus,1146,1,1,1,1,1,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +73947,55401,Male,Loyal Customer,43,Business travel,Business,1290,1,1,1,1,5,5,5,4,4,4,4,5,4,5,20,5.0,satisfied +73948,124344,Male,disloyal Customer,16,Business travel,Eco,1037,5,5,5,1,2,5,2,2,3,5,5,3,3,2,0,2.0,satisfied +73949,31495,Male,Loyal Customer,54,Business travel,Eco,853,1,1,1,1,1,1,1,1,1,3,3,1,2,1,0,0.0,neutral or dissatisfied +73950,66035,Female,Loyal Customer,40,Business travel,Business,3774,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,3.0,satisfied +73951,4258,Male,Loyal Customer,65,Personal Travel,Business,502,4,4,4,3,4,4,5,3,3,4,2,5,3,5,0,1.0,neutral or dissatisfied +73952,64940,Male,Loyal Customer,46,Business travel,Business,224,4,4,4,4,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +73953,23102,Female,Loyal Customer,42,Business travel,Business,223,0,5,0,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +73954,65495,Male,Loyal Customer,61,Personal Travel,Eco,1303,2,4,2,4,1,2,3,1,4,4,3,3,4,1,0,0.0,neutral or dissatisfied +73955,67715,Female,Loyal Customer,40,Business travel,Business,3568,3,3,3,3,4,5,4,4,4,4,4,4,4,5,5,0.0,satisfied +73956,66464,Male,Loyal Customer,52,Business travel,Business,1217,4,4,4,4,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +73957,67981,Female,disloyal Customer,44,Business travel,Eco Plus,1171,1,1,1,4,3,1,3,3,3,2,3,1,4,3,21,11.0,neutral or dissatisfied +73958,35405,Female,Loyal Customer,77,Business travel,Eco,669,4,3,3,3,5,3,3,3,3,4,3,1,3,2,7,16.0,neutral or dissatisfied +73959,72502,Female,Loyal Customer,25,Business travel,Business,3208,2,5,3,5,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +73960,109296,Female,Loyal Customer,34,Business travel,Business,1136,3,3,3,3,2,4,5,2,2,2,2,3,2,4,104,92.0,satisfied +73961,23201,Male,Loyal Customer,9,Personal Travel,Eco Plus,300,3,3,3,2,3,3,3,3,1,2,2,4,3,3,40,36.0,neutral or dissatisfied +73962,15526,Female,Loyal Customer,24,Personal Travel,Eco Plus,331,1,3,1,5,3,1,3,3,2,3,3,4,4,3,0,0.0,neutral or dissatisfied +73963,86587,Female,Loyal Customer,69,Personal Travel,Eco,1269,2,4,2,3,2,4,5,3,3,2,3,5,3,3,4,0.0,neutral or dissatisfied +73964,31253,Female,Loyal Customer,21,Personal Travel,Eco,524,2,4,2,5,4,2,5,4,3,4,4,3,5,4,9,11.0,neutral or dissatisfied +73965,108377,Female,Loyal Customer,29,Personal Travel,Eco,1790,2,5,2,3,5,2,5,5,5,2,4,3,5,5,1,0.0,neutral or dissatisfied +73966,103361,Male,Loyal Customer,39,Business travel,Business,342,1,1,1,1,2,5,4,4,4,4,4,4,4,5,34,35.0,satisfied +73967,65234,Male,Loyal Customer,59,Business travel,Business,247,0,1,1,4,2,5,5,5,5,5,5,5,5,3,17,9.0,satisfied +73968,1160,Female,Loyal Customer,22,Personal Travel,Eco,134,2,0,2,4,3,2,3,3,2,4,2,1,5,3,16,5.0,neutral or dissatisfied +73969,100612,Female,disloyal Customer,28,Business travel,Eco,905,1,0,0,4,3,1,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +73970,126061,Female,Loyal Customer,43,Business travel,Business,2783,1,1,1,1,4,5,5,4,4,4,4,4,4,3,13,14.0,satisfied +73971,34230,Male,Loyal Customer,34,Business travel,Eco Plus,1189,4,1,1,1,5,5,5,5,5,1,1,5,5,5,40,36.0,satisfied +73972,125506,Male,Loyal Customer,17,Personal Travel,Eco,666,3,5,3,5,2,3,4,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +73973,112478,Female,Loyal Customer,53,Personal Travel,Eco,862,2,4,2,3,5,4,4,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +73974,66755,Male,Loyal Customer,17,Personal Travel,Eco,802,2,4,2,3,3,2,5,3,3,4,5,5,5,3,0,17.0,neutral or dissatisfied +73975,99785,Female,Loyal Customer,60,Business travel,Business,2137,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,1.0,satisfied +73976,120769,Female,Loyal Customer,45,Business travel,Business,678,2,2,1,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +73977,25500,Female,Loyal Customer,18,Business travel,Business,2121,3,1,1,1,3,3,3,3,4,2,3,2,3,3,0,15.0,neutral or dissatisfied +73978,55837,Male,Loyal Customer,44,Business travel,Business,1416,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,39.0,satisfied +73979,27906,Female,Loyal Customer,61,Business travel,Business,2311,2,2,2,2,4,4,4,3,5,5,1,4,3,4,0,0.0,satisfied +73980,73834,Male,Loyal Customer,27,Business travel,Business,1709,2,2,2,2,4,4,4,4,5,5,3,3,5,4,0,0.0,satisfied +73981,33349,Male,disloyal Customer,26,Business travel,Eco,1269,5,4,4,1,3,5,3,3,5,1,5,3,4,3,0,0.0,satisfied +73982,72619,Female,Loyal Customer,61,Personal Travel,Eco,964,3,5,3,4,2,5,4,2,2,3,2,4,2,4,5,5.0,neutral or dissatisfied +73983,61077,Male,Loyal Customer,77,Business travel,Business,1506,4,3,2,3,5,4,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +73984,85661,Female,Loyal Customer,60,Business travel,Business,903,1,1,1,1,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +73985,13533,Male,Loyal Customer,41,Business travel,Business,214,1,1,1,1,2,1,5,5,5,4,5,2,5,3,114,125.0,satisfied +73986,70626,Male,Loyal Customer,50,Personal Travel,Eco,1217,3,5,3,1,4,3,1,4,5,3,3,2,2,4,0,1.0,neutral or dissatisfied +73987,90733,Male,disloyal Customer,25,Business travel,Business,515,2,5,2,2,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +73988,5040,Male,Loyal Customer,40,Business travel,Business,235,2,2,2,2,4,5,4,4,4,4,4,4,4,5,33,17.0,satisfied +73989,6843,Female,Loyal Customer,41,Business travel,Business,224,5,5,5,5,4,4,4,5,5,5,5,5,5,3,104,112.0,satisfied +73990,28981,Male,disloyal Customer,28,Business travel,Eco,978,3,3,3,2,4,3,4,4,1,1,2,4,3,4,0,2.0,neutral or dissatisfied +73991,67299,Female,disloyal Customer,19,Business travel,Eco,1102,3,3,3,5,3,3,3,3,4,5,4,4,5,3,0,8.0,neutral or dissatisfied +73992,76903,Female,Loyal Customer,13,Personal Travel,Eco,630,3,4,3,1,4,3,4,4,5,5,2,2,3,4,0,3.0,neutral or dissatisfied +73993,32093,Female,Loyal Customer,33,Business travel,Business,3550,1,1,1,1,3,3,4,5,5,5,4,2,5,5,0,0.0,satisfied +73994,92735,Female,disloyal Customer,27,Business travel,Eco,1276,3,3,3,4,3,3,3,3,2,5,3,4,3,3,38,36.0,neutral or dissatisfied +73995,377,Female,Loyal Customer,54,Business travel,Business,3628,4,4,4,4,3,5,5,4,4,4,4,3,4,3,14,6.0,satisfied +73996,101198,Male,Loyal Customer,48,Personal Travel,Eco,1235,2,5,2,1,2,2,1,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +73997,32507,Male,Loyal Customer,50,Business travel,Eco,84,5,3,3,3,5,5,5,5,1,3,5,5,1,5,5,5.0,satisfied +73998,22985,Male,Loyal Customer,25,Personal Travel,Eco,641,4,1,4,3,5,4,5,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +73999,124617,Female,Loyal Customer,40,Business travel,Business,1671,1,1,1,1,3,3,4,5,5,5,5,5,5,3,1,0.0,satisfied +74000,76732,Female,Loyal Customer,62,Personal Travel,Eco Plus,547,2,1,2,3,3,3,2,3,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +74001,35168,Male,Loyal Customer,46,Business travel,Business,1681,5,5,5,5,4,5,5,4,4,4,4,4,4,5,35,25.0,satisfied +74002,66117,Male,Loyal Customer,47,Business travel,Business,2411,4,4,4,4,4,5,5,4,4,4,4,4,4,4,13,4.0,satisfied +74003,118398,Male,Loyal Customer,57,Business travel,Business,3334,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +74004,35771,Female,Loyal Customer,34,Business travel,Business,200,1,1,1,1,4,4,5,5,5,5,5,4,5,1,0,0.0,satisfied +74005,126698,Female,disloyal Customer,39,Business travel,Business,2521,3,3,3,2,3,3,1,3,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +74006,118877,Male,Loyal Customer,46,Business travel,Business,3444,3,3,3,3,4,5,5,3,3,3,3,1,3,1,0,0.0,satisfied +74007,30581,Female,disloyal Customer,36,Business travel,Eco,228,4,5,4,3,3,4,3,3,3,5,5,4,1,3,0,0.0,neutral or dissatisfied +74008,70540,Male,Loyal Customer,34,Business travel,Business,1258,3,3,3,3,5,5,4,3,3,3,3,4,3,4,0,18.0,satisfied +74009,46014,Female,Loyal Customer,55,Business travel,Business,3122,2,4,4,4,5,3,3,2,2,2,2,4,2,4,15,8.0,neutral or dissatisfied +74010,77264,Female,disloyal Customer,57,Business travel,Business,1590,2,2,2,3,4,2,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +74011,123426,Male,Loyal Customer,52,Business travel,Business,1337,3,3,2,3,2,4,5,5,5,5,5,5,5,4,48,41.0,satisfied +74012,111693,Female,disloyal Customer,50,Business travel,Business,541,2,2,2,2,2,2,2,2,4,3,4,5,4,2,113,107.0,neutral or dissatisfied +74013,74549,Female,disloyal Customer,25,Business travel,Eco,1235,3,3,3,3,4,3,3,4,3,3,3,1,4,4,10,13.0,neutral or dissatisfied +74014,105899,Male,Loyal Customer,30,Business travel,Business,3778,5,5,5,5,4,4,4,4,4,2,5,5,4,4,52,66.0,satisfied +74015,117289,Female,disloyal Customer,21,Business travel,Eco,370,3,0,3,3,2,3,2,2,2,1,4,4,3,2,2,2.0,neutral or dissatisfied +74016,93954,Male,Loyal Customer,10,Personal Travel,Eco,507,4,5,4,2,2,4,2,2,1,5,4,4,3,2,23,14.0,neutral or dissatisfied +74017,111816,Male,Loyal Customer,53,Personal Travel,Eco,349,2,2,3,4,5,3,5,5,1,4,4,1,4,5,32,31.0,neutral or dissatisfied +74018,122253,Male,Loyal Customer,29,Business travel,Business,1979,2,2,2,2,4,4,4,4,1,2,2,5,1,4,0,0.0,satisfied +74019,13620,Female,Loyal Customer,32,Business travel,Business,3709,5,5,3,5,4,4,4,4,4,1,2,5,4,4,0,0.0,satisfied +74020,3964,Male,Loyal Customer,34,Personal Travel,Eco,764,3,5,3,3,5,3,5,5,4,2,4,3,5,5,6,0.0,neutral or dissatisfied +74021,97692,Male,Loyal Customer,56,Personal Travel,Eco Plus,491,3,3,3,1,2,3,5,2,5,5,4,4,3,2,94,89.0,neutral or dissatisfied +74022,120667,Female,Loyal Customer,40,Business travel,Business,280,1,1,1,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +74023,105615,Male,Loyal Customer,37,Business travel,Business,3903,4,4,4,4,3,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +74024,55856,Female,disloyal Customer,57,Business travel,Eco Plus,1416,3,3,3,4,3,3,4,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +74025,26259,Female,Loyal Customer,34,Personal Travel,Eco Plus,404,2,2,2,3,2,2,2,2,1,2,2,4,3,2,7,11.0,neutral or dissatisfied +74026,85089,Male,Loyal Customer,47,Business travel,Business,696,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,2.0,satisfied +74027,86455,Male,disloyal Customer,26,Business travel,Eco,712,3,3,3,4,2,3,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +74028,47562,Female,Loyal Customer,65,Personal Travel,Eco Plus,558,3,4,3,3,1,3,3,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +74029,67777,Male,Loyal Customer,25,Business travel,Business,1464,3,4,5,5,3,4,3,3,4,4,3,2,2,3,6,0.0,neutral or dissatisfied +74030,28272,Male,disloyal Customer,14,Business travel,Eco,1204,2,2,2,4,2,3,3,5,4,4,1,3,4,3,0,3.0,neutral or dissatisfied +74031,112197,Female,disloyal Customer,18,Business travel,Business,649,5,4,5,3,3,5,3,3,3,2,5,5,4,3,0,0.0,satisfied +74032,42754,Female,disloyal Customer,20,Business travel,Business,493,4,5,4,5,2,4,2,2,4,2,4,4,4,2,0,0.0,satisfied +74033,78028,Male,disloyal Customer,37,Business travel,Eco,332,1,3,0,2,2,0,2,2,1,4,1,4,4,2,0,0.0,neutral or dissatisfied +74034,117580,Female,disloyal Customer,45,Business travel,Business,347,4,4,4,3,3,4,4,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +74035,34271,Male,Loyal Customer,45,Business travel,Eco,496,5,5,5,5,5,5,5,5,4,3,5,3,3,5,0,0.0,satisfied +74036,106145,Female,disloyal Customer,33,Business travel,Eco,436,4,1,3,4,5,3,5,5,2,4,4,1,4,5,61,60.0,neutral or dissatisfied +74037,90831,Male,Loyal Customer,48,Business travel,Business,2657,2,3,3,3,4,4,4,2,2,2,2,3,2,1,48,30.0,neutral or dissatisfied +74038,25029,Female,Loyal Customer,47,Business travel,Eco,907,3,5,5,5,3,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +74039,6465,Female,disloyal Customer,23,Business travel,Business,296,4,0,4,3,2,4,1,2,3,3,4,5,5,2,0,0.0,satisfied +74040,76100,Male,Loyal Customer,35,Personal Travel,Eco,669,2,5,2,2,2,2,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +74041,38865,Female,disloyal Customer,10,Business travel,Eco,1082,1,1,1,4,5,1,5,5,1,2,4,2,3,5,0,0.0,neutral or dissatisfied +74042,79246,Female,Loyal Customer,62,Business travel,Business,1598,5,5,1,5,3,4,4,5,5,5,5,4,5,3,0,8.0,satisfied +74043,86667,Male,Loyal Customer,15,Personal Travel,Eco,746,1,5,1,4,4,1,4,4,4,5,4,4,5,4,1,0.0,neutral or dissatisfied +74044,65179,Female,Loyal Customer,32,Personal Travel,Eco,224,3,4,3,3,5,3,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +74045,5783,Male,Loyal Customer,51,Business travel,Business,3790,4,4,4,4,5,4,4,4,4,4,4,5,4,3,9,11.0,satisfied +74046,75993,Female,Loyal Customer,37,Business travel,Business,2633,2,2,3,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +74047,37965,Male,Loyal Customer,41,Business travel,Business,1121,5,5,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +74048,52540,Female,disloyal Customer,21,Business travel,Eco,160,3,4,3,3,2,3,2,2,2,3,4,2,1,2,0,0.0,neutral or dissatisfied +74049,54095,Female,Loyal Customer,49,Personal Travel,Eco,1416,3,5,3,3,3,4,5,3,5,5,4,5,5,5,210,204.0,neutral or dissatisfied +74050,72391,Female,Loyal Customer,38,Business travel,Business,3257,3,3,1,3,2,5,4,5,5,5,5,4,5,5,4,0.0,satisfied +74051,124695,Female,Loyal Customer,41,Business travel,Business,2377,2,5,3,5,3,4,4,2,2,2,2,1,2,3,56,50.0,neutral or dissatisfied +74052,27634,Male,Loyal Customer,31,Business travel,Eco Plus,697,4,1,1,1,4,5,4,4,4,2,3,5,4,4,0,0.0,satisfied +74053,92070,Female,Loyal Customer,23,Business travel,Business,1589,3,2,2,2,3,3,3,3,3,3,3,2,4,3,53,43.0,neutral or dissatisfied +74054,73744,Male,Loyal Customer,23,Personal Travel,Eco,192,2,4,2,3,1,2,1,1,4,3,4,4,4,1,9,0.0,neutral or dissatisfied +74055,2946,Female,Loyal Customer,49,Business travel,Business,2583,1,1,1,1,3,4,4,5,5,5,5,3,5,4,0,42.0,satisfied +74056,26615,Female,Loyal Customer,43,Business travel,Business,581,1,1,1,1,3,1,1,5,5,5,5,5,5,1,0,0.0,satisfied +74057,5009,Male,Loyal Customer,9,Personal Travel,Eco,502,2,3,2,3,1,2,1,1,4,3,1,4,1,1,21,43.0,neutral or dissatisfied +74058,18366,Female,disloyal Customer,18,Business travel,Eco,169,3,4,3,3,4,3,4,4,1,4,3,1,3,4,4,34.0,neutral or dissatisfied +74059,24709,Male,Loyal Customer,49,Personal Travel,Eco,397,4,4,4,3,1,4,1,1,4,3,5,1,3,1,17,8.0,satisfied +74060,119006,Male,Loyal Customer,34,Personal Travel,Eco,479,3,5,2,3,5,2,5,5,5,1,3,5,5,5,19,27.0,neutral or dissatisfied +74061,50316,Male,Loyal Customer,46,Business travel,Business,86,1,1,1,1,5,5,5,5,1,3,1,5,2,2,0,0.0,satisfied +74062,109846,Male,Loyal Customer,37,Business travel,Eco,1052,1,3,3,3,1,1,1,1,4,3,4,4,3,1,0,0.0,neutral or dissatisfied +74063,29395,Female,disloyal Customer,30,Business travel,Eco,2378,4,4,4,3,2,4,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +74064,119098,Female,disloyal Customer,28,Business travel,Eco,1107,3,3,3,4,2,3,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +74065,88206,Male,Loyal Customer,35,Business travel,Business,404,3,3,3,3,2,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +74066,94561,Female,Loyal Customer,48,Business travel,Business,2458,3,3,3,3,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +74067,57057,Female,Loyal Customer,29,Personal Travel,Eco,2133,2,2,1,3,1,4,4,2,2,4,3,4,1,4,365,383.0,neutral or dissatisfied +74068,33373,Female,Loyal Customer,7,Personal Travel,Eco,2556,3,5,3,1,3,3,3,3,5,5,3,3,4,3,0,0.0,neutral or dissatisfied +74069,105077,Male,disloyal Customer,39,Business travel,Business,277,3,3,3,3,1,3,1,1,3,4,4,3,5,1,68,60.0,neutral or dissatisfied +74070,108397,Female,Loyal Customer,24,Personal Travel,Eco Plus,1728,1,1,1,2,1,3,3,2,1,1,1,3,3,3,201,208.0,neutral or dissatisfied +74071,116600,Male,Loyal Customer,30,Business travel,Eco Plus,308,1,4,3,3,1,1,1,1,2,3,4,1,3,1,12,7.0,neutral or dissatisfied +74072,72442,Male,disloyal Customer,32,Business travel,Business,964,3,3,3,4,5,3,2,5,3,2,4,4,5,5,9,7.0,neutral or dissatisfied +74073,91727,Male,disloyal Customer,62,Business travel,Business,588,2,2,2,4,1,2,5,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +74074,87150,Female,Loyal Customer,10,Personal Travel,Eco Plus,594,1,4,1,4,3,1,3,3,3,3,4,4,4,3,27,18.0,neutral or dissatisfied +74075,115001,Male,Loyal Customer,56,Business travel,Business,1599,1,1,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +74076,39899,Female,Loyal Customer,64,Business travel,Eco Plus,221,4,3,3,3,3,1,4,3,3,4,3,5,3,2,0,0.0,satisfied +74077,2115,Male,disloyal Customer,55,Business travel,Business,404,1,1,1,2,1,5,5,4,5,5,4,5,4,5,137,140.0,neutral or dissatisfied +74078,68175,Female,disloyal Customer,27,Business travel,Eco,197,3,1,3,1,3,3,3,3,3,4,2,2,1,3,4,36.0,neutral or dissatisfied +74079,27733,Female,disloyal Customer,44,Business travel,Eco,1435,3,3,3,4,4,3,4,4,3,2,1,2,1,4,1,0.0,neutral or dissatisfied +74080,128992,Male,Loyal Customer,57,Business travel,Business,2134,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +74081,8975,Female,Loyal Customer,61,Business travel,Business,3625,2,2,2,2,4,4,4,1,2,3,5,4,2,4,212,214.0,satisfied +74082,53337,Female,disloyal Customer,18,Business travel,Eco,1452,2,2,2,3,1,2,1,1,3,4,5,4,4,1,7,0.0,neutral or dissatisfied +74083,37118,Male,Loyal Customer,36,Business travel,Business,1046,2,2,2,2,5,3,5,4,4,4,4,1,4,4,31,25.0,satisfied +74084,55440,Female,Loyal Customer,12,Personal Travel,Eco,2136,1,4,1,2,3,1,3,3,3,5,3,5,4,3,11,0.0,neutral or dissatisfied +74085,6293,Male,Loyal Customer,44,Personal Travel,Eco,585,0,4,0,1,5,0,5,5,4,3,5,4,5,5,0,0.0,satisfied +74086,20689,Female,Loyal Customer,45,Business travel,Business,779,2,2,2,2,4,3,4,2,2,2,2,2,2,3,4,0.0,satisfied +74087,90791,Female,Loyal Customer,28,Business travel,Eco,444,5,3,3,3,5,4,5,5,2,2,3,2,3,5,2,1.0,neutral or dissatisfied +74088,35704,Male,Loyal Customer,24,Personal Travel,Eco,2475,1,3,1,3,1,5,5,1,5,3,4,5,2,5,0,0.0,neutral or dissatisfied +74089,43272,Female,Loyal Customer,49,Business travel,Eco,436,4,4,4,4,1,1,1,4,4,4,4,3,4,3,0,0.0,satisfied +74090,46529,Female,Loyal Customer,44,Business travel,Business,251,1,3,3,3,1,3,3,1,1,1,1,1,1,3,42,22.0,neutral or dissatisfied +74091,91918,Male,disloyal Customer,42,Business travel,Eco,2475,2,2,2,4,1,2,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +74092,73721,Male,disloyal Customer,26,Business travel,Eco,192,3,2,3,4,5,3,5,5,1,4,3,2,3,5,64,58.0,neutral or dissatisfied +74093,74589,Female,Loyal Customer,51,Business travel,Eco,1242,4,5,5,5,5,3,3,5,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +74094,128265,Male,Loyal Customer,41,Business travel,Business,2573,2,4,4,4,3,3,4,2,2,2,2,1,2,2,6,8.0,neutral or dissatisfied +74095,2359,Male,Loyal Customer,43,Business travel,Business,2015,3,3,4,3,2,5,5,4,4,4,4,4,4,3,1,1.0,satisfied +74096,123956,Female,Loyal Customer,11,Personal Travel,Eco Plus,573,2,2,2,3,4,2,4,4,1,2,3,3,4,4,0,0.0,neutral or dissatisfied +74097,74248,Male,disloyal Customer,27,Business travel,Business,1709,2,2,2,3,3,2,3,3,5,2,3,5,4,3,9,0.0,neutral or dissatisfied +74098,121778,Female,disloyal Customer,42,Business travel,Business,449,3,3,3,1,1,3,1,1,5,2,5,5,4,1,2,5.0,neutral or dissatisfied +74099,94288,Female,Loyal Customer,60,Business travel,Business,248,5,5,5,5,5,5,4,4,4,4,4,4,4,4,47,53.0,satisfied +74100,115276,Female,disloyal Customer,28,Business travel,Eco,362,2,2,2,3,2,2,2,2,2,1,3,4,3,2,11,1.0,neutral or dissatisfied +74101,124714,Male,Loyal Customer,61,Personal Travel,Eco,399,1,4,1,3,3,1,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +74102,62240,Female,Loyal Customer,17,Personal Travel,Eco,2565,4,4,4,1,3,4,2,3,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +74103,115080,Female,Loyal Customer,54,Business travel,Business,358,2,2,2,2,2,5,5,3,3,3,3,4,3,5,15,13.0,satisfied +74104,53612,Female,Loyal Customer,47,Business travel,Eco,1874,2,5,4,5,4,4,3,2,2,2,2,2,2,5,15,0.0,satisfied +74105,109354,Female,Loyal Customer,37,Business travel,Business,3941,5,2,5,5,5,5,5,4,4,4,4,3,4,5,28,24.0,satisfied +74106,118229,Female,Loyal Customer,49,Business travel,Business,1587,2,2,2,2,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +74107,25428,Male,Loyal Customer,7,Personal Travel,Business,669,2,2,2,4,4,2,4,4,2,5,3,2,4,4,0,0.0,neutral or dissatisfied +74108,120161,Female,Loyal Customer,53,Business travel,Business,119,5,5,5,5,5,4,4,4,4,4,5,5,4,3,13,9.0,satisfied +74109,114680,Female,Loyal Customer,38,Business travel,Business,417,5,5,5,5,3,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +74110,127049,Male,Loyal Customer,37,Business travel,Eco,304,4,1,1,1,4,4,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +74111,69287,Female,Loyal Customer,7,Personal Travel,Eco,733,2,5,2,4,2,2,2,2,4,4,5,2,5,2,0,0.0,neutral or dissatisfied +74112,93458,Male,Loyal Customer,41,Personal Travel,Eco,723,1,4,1,2,5,1,5,5,2,1,1,3,4,5,0,0.0,neutral or dissatisfied +74113,73590,Male,Loyal Customer,54,Business travel,Business,192,5,5,5,5,3,5,5,5,5,4,4,5,5,4,0,0.0,satisfied +74114,122405,Female,Loyal Customer,48,Personal Travel,Eco Plus,529,2,4,2,1,5,4,5,3,3,2,2,3,3,3,0,0.0,neutral or dissatisfied +74115,76691,Male,Loyal Customer,31,Personal Travel,Eco,516,4,4,4,4,3,4,5,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +74116,19324,Male,disloyal Customer,28,Business travel,Eco,694,4,4,4,4,5,4,5,5,1,1,3,1,3,5,8,11.0,neutral or dissatisfied +74117,21507,Male,Loyal Customer,17,Personal Travel,Eco,306,3,4,3,5,5,3,5,5,4,4,5,3,4,5,7,3.0,neutral or dissatisfied +74118,59715,Male,Loyal Customer,54,Business travel,Business,3950,4,4,4,4,3,4,5,4,4,4,4,4,4,5,20,28.0,satisfied +74119,119607,Male,Loyal Customer,55,Personal Travel,Eco,1979,1,1,1,4,2,1,2,2,4,4,4,3,4,2,2,15.0,neutral or dissatisfied +74120,43513,Male,Loyal Customer,63,Personal Travel,Eco,624,4,4,4,5,5,4,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +74121,108744,Male,Loyal Customer,64,Personal Travel,Business,404,1,4,1,3,4,4,5,3,3,1,3,4,3,4,2,0.0,neutral or dissatisfied +74122,44201,Female,Loyal Customer,40,Personal Travel,Eco,157,2,4,0,4,2,0,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +74123,61162,Male,Loyal Customer,43,Business travel,Business,1504,2,2,4,2,3,4,5,5,5,4,5,3,5,3,6,9.0,satisfied +74124,104197,Male,disloyal Customer,39,Business travel,Eco,1310,1,1,1,2,5,1,5,5,2,4,3,3,3,5,17,0.0,neutral or dissatisfied +74125,83271,Female,Loyal Customer,52,Business travel,Eco,479,3,4,4,4,2,4,4,3,3,3,3,1,3,1,53,20.0,neutral or dissatisfied +74126,93526,Male,Loyal Customer,44,Business travel,Business,1218,4,4,4,4,3,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +74127,38200,Female,disloyal Customer,27,Business travel,Eco Plus,1237,3,3,3,5,4,3,4,4,2,4,5,5,4,4,0,0.0,neutral or dissatisfied +74128,37481,Female,Loyal Customer,25,Business travel,Business,972,4,1,3,3,4,4,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +74129,126819,Male,Loyal Customer,54,Business travel,Business,2296,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +74130,71613,Male,disloyal Customer,28,Business travel,Eco,1005,4,3,3,3,2,3,3,2,3,2,2,1,3,2,20,23.0,neutral or dissatisfied +74131,75582,Female,disloyal Customer,35,Business travel,Business,337,3,4,4,3,1,4,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +74132,91739,Male,Loyal Customer,44,Business travel,Business,2421,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +74133,61522,Male,Loyal Customer,48,Personal Travel,Eco,2442,1,5,1,2,4,1,4,4,5,5,5,4,4,4,73,48.0,neutral or dissatisfied +74134,95554,Female,Loyal Customer,22,Personal Travel,Eco Plus,239,3,5,0,2,5,0,5,5,2,1,3,1,3,5,0,0.0,neutral or dissatisfied +74135,49801,Female,Loyal Customer,42,Business travel,Business,3821,1,1,1,1,5,4,5,5,5,5,3,5,5,2,0,0.0,satisfied +74136,46974,Female,Loyal Customer,7,Personal Travel,Eco,833,3,2,3,4,4,3,2,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +74137,21647,Male,Loyal Customer,23,Business travel,Eco Plus,722,4,5,5,5,4,4,3,4,2,3,5,4,4,4,6,0.0,satisfied +74138,120363,Female,Loyal Customer,48,Business travel,Business,2132,4,4,3,4,3,5,5,5,5,5,5,4,5,4,0,4.0,satisfied +74139,96122,Female,Loyal Customer,57,Personal Travel,Eco Plus,1069,3,5,3,2,3,5,4,2,2,3,2,5,2,5,20,8.0,neutral or dissatisfied +74140,2996,Female,disloyal Customer,20,Business travel,Business,862,4,0,5,3,2,5,2,2,4,3,5,3,4,2,10,22.0,satisfied +74141,45473,Female,Loyal Customer,48,Business travel,Eco,522,3,3,3,3,2,4,4,3,3,3,3,3,3,1,68,55.0,neutral or dissatisfied +74142,32058,Female,Loyal Customer,30,Business travel,Eco,121,5,2,2,2,5,5,5,5,1,1,4,2,3,5,3,2.0,satisfied +74143,50262,Female,Loyal Customer,45,Business travel,Business,3745,3,1,1,1,5,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +74144,76603,Male,Loyal Customer,51,Business travel,Business,2976,1,5,5,5,4,4,3,1,1,1,1,1,1,4,7,8.0,neutral or dissatisfied +74145,66183,Female,disloyal Customer,25,Business travel,Business,550,3,5,3,5,1,3,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +74146,15322,Female,disloyal Customer,25,Business travel,Eco,589,2,3,2,3,2,2,2,2,4,3,4,2,3,2,0,0.0,neutral or dissatisfied +74147,91691,Male,Loyal Customer,41,Personal Travel,Business,626,2,5,1,3,1,4,2,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +74148,96692,Female,Loyal Customer,53,Business travel,Business,2388,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,16.0,satisfied +74149,96072,Female,Loyal Customer,30,Personal Travel,Eco,583,2,4,2,1,2,2,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +74150,15053,Male,disloyal Customer,41,Business travel,Eco,116,2,0,2,3,5,2,5,5,5,5,2,1,5,5,0,0.0,neutral or dissatisfied +74151,75381,Male,Loyal Customer,31,Business travel,Business,2585,5,1,5,5,3,3,3,3,5,2,4,5,5,3,10,0.0,satisfied +74152,27939,Male,Loyal Customer,22,Business travel,Business,1874,1,1,1,1,4,4,4,4,2,4,5,4,1,4,0,0.0,satisfied +74153,56975,Female,Loyal Customer,54,Personal Travel,Eco,2454,1,3,1,4,1,5,5,5,1,5,4,5,4,5,31,34.0,neutral or dissatisfied +74154,21492,Male,Loyal Customer,63,Personal Travel,Eco,377,5,5,5,5,5,5,3,5,3,3,4,5,5,5,93,102.0,satisfied +74155,45297,Female,Loyal Customer,67,Business travel,Business,2984,4,4,4,4,5,3,4,5,5,5,5,2,5,4,5,4.0,satisfied +74156,41329,Male,disloyal Customer,27,Business travel,Eco,689,1,1,1,4,3,1,3,3,1,3,3,2,4,3,16,16.0,neutral or dissatisfied +74157,128224,Female,disloyal Customer,28,Business travel,Business,602,3,3,3,3,5,3,2,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +74158,84337,Female,Loyal Customer,42,Business travel,Business,3523,3,3,3,3,5,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +74159,68045,Male,Loyal Customer,45,Business travel,Business,868,4,4,4,4,3,5,4,2,2,2,2,5,2,4,17,20.0,satisfied +74160,52360,Female,Loyal Customer,41,Personal Travel,Eco,598,3,2,3,3,4,3,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +74161,93316,Male,Loyal Customer,48,Business travel,Business,287,4,4,3,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +74162,38816,Male,Loyal Customer,66,Personal Travel,Eco,353,3,2,3,4,2,3,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +74163,53236,Female,Loyal Customer,14,Personal Travel,Eco,589,4,5,3,1,3,1,5,5,4,5,5,5,3,5,152,151.0,neutral or dissatisfied +74164,123835,Male,Loyal Customer,34,Business travel,Business,541,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,13.0,satisfied +74165,114673,Female,Loyal Customer,49,Business travel,Business,337,4,1,4,4,3,4,5,5,5,5,5,3,5,4,10,2.0,satisfied +74166,79392,Female,Loyal Customer,48,Business travel,Business,2194,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +74167,118923,Female,Loyal Customer,44,Personal Travel,Eco,570,2,5,2,3,5,4,5,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +74168,60516,Male,Loyal Customer,44,Personal Travel,Eco,934,1,4,1,2,4,1,4,4,5,4,5,3,4,4,19,19.0,neutral or dissatisfied +74169,55035,Female,Loyal Customer,36,Business travel,Eco,1379,2,4,4,4,2,2,2,2,4,2,3,3,3,2,4,0.0,neutral or dissatisfied +74170,4838,Female,Loyal Customer,56,Business travel,Business,1599,4,4,4,4,4,4,4,5,5,4,5,5,5,5,0,5.0,satisfied +74171,54366,Female,disloyal Customer,23,Business travel,Eco Plus,1235,3,0,3,1,3,3,3,3,4,3,5,3,5,3,1,0.0,neutral or dissatisfied +74172,116875,Female,Loyal Customer,40,Business travel,Business,3590,5,5,5,5,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +74173,111555,Female,disloyal Customer,42,Business travel,Business,883,5,5,5,3,2,5,2,2,3,4,4,3,5,2,0,0.0,satisfied +74174,44607,Female,Loyal Customer,25,Business travel,Business,1553,4,4,4,4,4,4,4,4,5,4,1,1,1,4,0,0.0,satisfied +74175,29036,Female,Loyal Customer,60,Personal Travel,Eco,1050,4,5,4,3,2,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +74176,51848,Male,Loyal Customer,57,Personal Travel,Eco Plus,751,3,5,3,1,2,3,2,2,4,5,4,5,5,2,64,52.0,neutral or dissatisfied +74177,12763,Male,Loyal Customer,53,Personal Travel,Eco,721,2,5,2,1,5,2,5,5,4,3,3,1,1,5,0,0.0,neutral or dissatisfied +74178,49645,Male,disloyal Customer,21,Business travel,Eco,86,5,0,5,2,2,5,2,2,5,5,3,5,2,2,0,11.0,satisfied +74179,20383,Female,Loyal Customer,20,Business travel,Eco Plus,265,2,2,2,2,2,1,2,2,5,3,4,2,1,2,275,276.0,neutral or dissatisfied +74180,59189,Male,Loyal Customer,46,Business travel,Business,1440,3,3,3,3,4,5,5,2,2,2,2,5,2,4,13,28.0,satisfied +74181,35633,Female,Loyal Customer,43,Business travel,Eco,1626,4,3,4,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +74182,97326,Male,disloyal Customer,20,Business travel,Eco,347,4,2,4,4,1,4,1,1,3,5,3,4,3,1,29,41.0,neutral or dissatisfied +74183,122052,Female,Loyal Customer,25,Business travel,Business,130,2,5,5,5,3,3,2,3,4,4,2,1,3,3,0,0.0,neutral or dissatisfied +74184,102995,Male,Loyal Customer,50,Business travel,Business,2999,3,3,3,3,5,4,4,4,4,4,4,5,4,4,76,79.0,satisfied +74185,30340,Female,Loyal Customer,17,Personal Travel,Eco,391,5,4,5,3,5,5,5,5,4,2,5,5,5,5,13,6.0,satisfied +74186,17617,Female,Loyal Customer,18,Business travel,Business,2458,4,4,4,4,2,2,2,2,2,1,3,2,1,2,2,0.0,satisfied +74187,111932,Male,Loyal Customer,58,Business travel,Business,2001,3,1,1,1,5,2,2,3,3,2,3,1,3,4,8,0.0,neutral or dissatisfied +74188,90191,Female,Loyal Customer,43,Personal Travel,Eco,1084,3,5,3,3,2,4,5,1,1,3,1,5,1,3,4,7.0,neutral or dissatisfied +74189,123530,Female,Loyal Customer,55,Business travel,Business,2125,2,2,4,2,5,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +74190,68645,Male,Loyal Customer,32,Business travel,Business,1641,1,1,1,1,4,4,5,4,3,2,4,4,5,4,0,0.0,satisfied +74191,97032,Male,Loyal Customer,29,Personal Travel,Eco Plus,775,1,5,1,3,1,1,1,1,1,4,4,3,3,1,52,54.0,neutral or dissatisfied +74192,1276,Male,Loyal Customer,68,Personal Travel,Eco,89,2,4,2,1,2,2,4,2,2,5,4,3,5,2,0,0.0,neutral or dissatisfied +74193,50105,Female,Loyal Customer,66,Business travel,Eco,134,2,4,4,4,3,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +74194,46754,Female,disloyal Customer,17,Business travel,Eco,125,4,0,4,1,4,4,4,4,1,4,4,2,2,4,0,0.0,neutral or dissatisfied +74195,52298,Female,disloyal Customer,36,Business travel,Eco,261,3,1,4,3,1,4,1,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +74196,11710,Female,Loyal Customer,38,Business travel,Business,2861,5,5,5,5,3,5,5,5,5,5,5,5,5,5,19,12.0,satisfied +74197,87716,Female,disloyal Customer,23,Business travel,Eco,591,0,1,0,1,1,0,1,1,5,4,5,4,5,1,0,0.0,satisfied +74198,49863,Male,disloyal Customer,27,Business travel,Eco,209,1,5,1,1,4,1,4,4,5,3,3,3,2,4,0,0.0,neutral or dissatisfied +74199,2590,Male,Loyal Customer,23,Personal Travel,Eco,280,1,4,1,4,4,1,4,4,1,2,4,1,3,4,39,30.0,neutral or dissatisfied +74200,60837,Male,disloyal Customer,34,Business travel,Business,1754,3,3,3,2,1,3,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +74201,127719,Female,Loyal Customer,54,Business travel,Business,255,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,8.0,satisfied +74202,47738,Female,Loyal Customer,13,Personal Travel,Business,834,3,1,3,3,1,3,3,1,2,5,2,2,3,1,25,13.0,neutral or dissatisfied +74203,94965,Female,Loyal Customer,47,Business travel,Business,2746,3,1,3,3,2,2,4,4,4,4,4,4,4,3,0,0.0,satisfied +74204,68470,Female,Loyal Customer,59,Business travel,Business,1303,1,5,1,1,2,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +74205,80621,Male,Loyal Customer,23,Personal Travel,Eco,236,1,5,0,4,2,0,5,2,3,2,5,3,5,2,27,24.0,neutral or dissatisfied +74206,97423,Male,Loyal Customer,16,Personal Travel,Eco,570,1,5,1,2,2,1,2,2,3,4,5,5,4,2,3,0.0,neutral or dissatisfied +74207,126566,Male,Loyal Customer,31,Business travel,Business,1558,3,2,2,2,3,3,3,3,1,4,4,2,4,3,0,4.0,neutral or dissatisfied +74208,11261,Female,Loyal Customer,39,Personal Travel,Eco,308,3,4,3,3,1,3,1,1,4,5,3,4,3,1,72,60.0,neutral or dissatisfied +74209,24334,Male,Loyal Customer,30,Business travel,Business,3276,3,3,3,3,4,4,4,4,3,3,1,2,2,4,0,0.0,satisfied +74210,75208,Male,Loyal Customer,54,Business travel,Business,1829,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +74211,67188,Female,Loyal Customer,37,Personal Travel,Eco,929,3,5,3,5,4,3,4,4,4,4,2,4,1,4,0,6.0,neutral or dissatisfied +74212,78902,Female,disloyal Customer,62,Business travel,Business,930,3,3,3,3,2,3,2,2,1,1,3,3,4,2,0,0.0,neutral or dissatisfied +74213,127496,Male,Loyal Customer,27,Personal Travel,Eco,1814,2,4,2,4,2,2,2,2,1,2,2,1,4,2,3,0.0,neutral or dissatisfied +74214,51467,Male,Loyal Customer,52,Business travel,Eco Plus,134,5,3,4,3,5,5,5,5,1,2,1,3,5,5,0,1.0,satisfied +74215,35529,Female,Loyal Customer,57,Personal Travel,Eco,1097,3,4,4,1,5,4,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +74216,128545,Male,Loyal Customer,47,Business travel,Business,647,1,1,1,1,3,4,5,5,5,5,5,5,5,5,17,7.0,satisfied +74217,21508,Male,Loyal Customer,63,Personal Travel,Eco,399,2,3,2,4,1,2,1,1,5,3,2,1,4,1,0,0.0,neutral or dissatisfied +74218,55742,Male,Loyal Customer,58,Business travel,Business,2052,4,4,4,4,2,4,4,4,4,4,4,4,4,3,3,15.0,satisfied +74219,40628,Female,Loyal Customer,18,Personal Travel,Eco,411,2,5,2,3,2,2,2,2,5,3,4,5,4,2,2,0.0,neutral or dissatisfied +74220,124858,Female,Loyal Customer,66,Business travel,Business,1677,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,12.0,satisfied +74221,37764,Female,Loyal Customer,55,Business travel,Eco Plus,944,5,3,5,5,2,5,5,5,5,5,5,1,5,2,105,104.0,satisfied +74222,16261,Female,disloyal Customer,23,Business travel,Eco,748,3,3,3,4,3,3,3,3,2,2,4,5,4,3,0,0.0,neutral or dissatisfied +74223,26522,Female,disloyal Customer,29,Business travel,Eco,990,4,4,4,1,5,4,5,5,4,2,2,1,3,5,27,17.0,satisfied +74224,108197,Female,Loyal Customer,67,Business travel,Eco Plus,590,2,4,3,3,5,4,4,2,2,2,2,4,2,3,21,11.0,neutral or dissatisfied +74225,205,Male,Loyal Customer,59,Business travel,Business,1828,4,5,5,5,5,3,3,4,4,3,4,3,4,2,21,19.0,neutral or dissatisfied +74226,79916,Female,disloyal Customer,25,Business travel,Eco,1010,4,4,4,4,2,4,2,2,2,3,4,1,4,2,0,7.0,neutral or dissatisfied +74227,115016,Male,disloyal Customer,26,Business travel,Business,337,2,0,2,4,3,2,3,3,3,2,4,5,4,3,29,23.0,neutral or dissatisfied +74228,15720,Female,Loyal Customer,61,Business travel,Eco,424,2,1,1,1,2,4,3,2,2,2,2,2,2,2,0,21.0,neutral or dissatisfied +74229,5688,Female,Loyal Customer,41,Business travel,Business,299,1,2,2,2,2,2,2,1,1,1,1,3,1,1,23,9.0,neutral or dissatisfied +74230,115394,Female,disloyal Customer,38,Business travel,Business,417,4,5,5,4,3,5,3,3,3,2,4,3,5,3,2,0.0,satisfied +74231,56734,Male,Loyal Customer,29,Personal Travel,Eco,937,2,3,2,4,5,2,5,5,1,5,3,4,3,5,5,0.0,neutral or dissatisfied +74232,92718,Male,Loyal Customer,45,Business travel,Business,2934,2,3,3,3,2,4,4,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +74233,68753,Male,Loyal Customer,58,Business travel,Business,861,1,1,1,1,3,5,4,4,4,4,4,3,4,4,14,14.0,satisfied +74234,55421,Male,Loyal Customer,51,Business travel,Business,2521,5,5,5,5,4,4,4,5,3,3,5,4,4,4,14,116.0,satisfied +74235,99171,Male,Loyal Customer,40,Personal Travel,Eco,1076,2,4,2,3,2,2,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +74236,126196,Female,Loyal Customer,42,Business travel,Business,631,2,2,2,2,2,5,5,2,2,2,2,3,2,4,4,5.0,satisfied +74237,73504,Male,Loyal Customer,46,Business travel,Business,1197,2,2,2,2,4,5,5,3,3,3,3,5,3,4,26,9.0,satisfied +74238,73837,Female,Loyal Customer,33,Business travel,Business,1709,2,2,2,2,4,3,4,2,2,2,2,3,2,5,0,0.0,satisfied +74239,21503,Female,Loyal Customer,41,Personal Travel,Eco,164,3,1,0,2,1,0,1,1,2,3,3,1,2,1,84,73.0,neutral or dissatisfied +74240,45488,Female,Loyal Customer,13,Personal Travel,Eco,522,3,5,3,3,3,3,5,3,5,4,5,3,5,3,3,0.0,neutral or dissatisfied +74241,43872,Female,Loyal Customer,42,Business travel,Eco,114,5,3,3,3,3,2,3,5,5,5,5,3,5,5,0,0.0,satisfied +74242,30902,Male,Loyal Customer,38,Business travel,Eco,826,5,1,1,1,5,5,5,5,1,4,4,5,4,5,2,5.0,satisfied +74243,126183,Female,Loyal Customer,44,Business travel,Eco,507,2,5,5,5,2,4,4,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +74244,107652,Female,Loyal Customer,31,Personal Travel,Business,251,1,5,1,3,4,1,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +74245,95062,Female,Loyal Customer,35,Personal Travel,Eco,239,5,4,5,5,3,5,3,3,5,3,4,5,4,3,0,2.0,satisfied +74246,72228,Female,Loyal Customer,56,Business travel,Business,2982,4,4,4,4,2,4,5,5,5,4,5,3,5,5,10,0.0,satisfied +74247,118697,Male,Loyal Customer,63,Personal Travel,Eco,304,2,5,2,4,4,2,5,4,5,3,4,3,4,4,9,14.0,neutral or dissatisfied +74248,107346,Male,Loyal Customer,51,Business travel,Business,3733,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +74249,41175,Male,Loyal Customer,8,Personal Travel,Eco Plus,140,2,5,2,3,5,2,5,5,5,5,5,1,3,5,0,0.0,neutral or dissatisfied +74250,88811,Female,disloyal Customer,54,Business travel,Eco Plus,250,4,4,4,2,1,4,1,1,3,3,1,4,1,1,0,3.0,neutral or dissatisfied +74251,95609,Male,Loyal Customer,44,Business travel,Business,670,1,3,3,3,5,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +74252,70513,Female,Loyal Customer,54,Personal Travel,Eco,867,5,4,5,2,3,5,4,4,4,5,1,5,4,3,0,0.0,satisfied +74253,31734,Male,Loyal Customer,24,Personal Travel,Eco,862,1,4,1,1,4,1,5,4,4,5,5,3,4,4,0,4.0,neutral or dissatisfied +74254,37273,Male,Loyal Customer,62,Business travel,Eco,944,5,4,2,4,5,5,5,5,1,5,2,3,1,5,0,0.0,satisfied +74255,66143,Female,Loyal Customer,49,Personal Travel,Eco,583,1,4,1,3,2,5,5,2,2,1,2,3,2,5,0,1.0,neutral or dissatisfied +74256,91966,Female,Loyal Customer,64,Personal Travel,Eco,2586,3,2,3,3,4,4,4,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +74257,22769,Female,Loyal Customer,39,Business travel,Eco,147,5,3,3,3,5,5,5,5,4,1,1,5,4,5,0,0.0,satisfied +74258,102419,Female,Loyal Customer,52,Personal Travel,Eco,236,2,5,2,1,4,5,1,2,2,2,2,4,2,2,11,10.0,neutral or dissatisfied +74259,38665,Female,Loyal Customer,13,Personal Travel,Eco,2611,3,3,2,3,4,2,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +74260,82396,Female,Loyal Customer,56,Business travel,Business,2120,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +74261,118332,Female,Loyal Customer,52,Business travel,Eco,602,2,1,1,1,4,2,2,2,2,2,2,1,2,1,86,108.0,neutral or dissatisfied +74262,80287,Male,Loyal Customer,57,Business travel,Business,2452,1,4,1,1,5,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +74263,50907,Male,Loyal Customer,39,Personal Travel,Eco,337,3,3,3,3,5,3,5,5,4,3,3,4,4,5,10,9.0,neutral or dissatisfied +74264,66009,Male,disloyal Customer,42,Business travel,Business,1055,4,4,4,3,2,4,2,2,4,5,4,4,5,2,8,0.0,satisfied +74265,1057,Female,Loyal Customer,67,Personal Travel,Eco,270,5,1,5,4,4,3,4,1,1,5,1,2,1,4,0,0.0,satisfied +74266,45925,Female,Loyal Customer,17,Business travel,Business,563,5,5,5,5,5,5,5,5,4,1,2,2,5,5,4,32.0,satisfied +74267,71360,Male,Loyal Customer,63,Business travel,Business,3697,5,5,5,5,3,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +74268,122463,Female,disloyal Customer,22,Business travel,Business,575,5,0,5,5,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +74269,82218,Female,disloyal Customer,21,Business travel,Eco,405,4,5,4,5,2,4,2,2,4,5,5,4,5,2,0,0.0,satisfied +74270,54267,Male,Loyal Customer,57,Personal Travel,Eco,1222,3,4,3,1,4,3,5,4,1,5,1,5,1,4,30,4.0,neutral or dissatisfied +74271,112843,Female,Loyal Customer,43,Business travel,Business,3746,3,3,3,3,2,4,5,3,3,3,3,4,3,5,82,73.0,satisfied +74272,15056,Male,Loyal Customer,61,Personal Travel,Eco,488,3,0,3,2,5,3,3,5,5,4,4,5,5,5,52,98.0,neutral or dissatisfied +74273,11344,Male,Loyal Customer,65,Personal Travel,Eco,517,2,5,2,3,1,2,1,1,4,5,1,2,2,1,0,0.0,neutral or dissatisfied +74274,118611,Female,Loyal Customer,51,Business travel,Business,647,4,4,4,4,2,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +74275,127720,Female,disloyal Customer,25,Business travel,Business,255,2,0,2,1,3,2,3,3,4,5,4,3,4,3,0,1.0,neutral or dissatisfied +74276,98202,Male,Loyal Customer,44,Personal Travel,Eco,327,3,3,3,4,4,3,4,4,3,3,4,3,4,4,15,6.0,neutral or dissatisfied +74277,110535,Female,Loyal Customer,50,Business travel,Business,3669,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +74278,90055,Female,Loyal Customer,32,Business travel,Eco,1145,4,1,1,1,4,4,4,4,4,2,2,4,2,4,17,17.0,neutral or dissatisfied +74279,66647,Female,Loyal Customer,47,Business travel,Business,1677,1,1,1,1,4,4,4,4,4,4,4,3,4,4,74,59.0,satisfied +74280,27697,Male,Loyal Customer,8,Personal Travel,Eco,1107,2,4,2,4,1,2,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +74281,31850,Female,Loyal Customer,25,Business travel,Eco,2677,5,5,4,5,5,5,3,5,3,1,3,3,5,5,9,0.0,satisfied +74282,24970,Male,Loyal Customer,49,Personal Travel,Business,692,5,1,5,4,4,4,4,1,1,5,1,1,1,4,0,0.0,satisfied +74283,46503,Male,disloyal Customer,39,Business travel,Eco,196,4,0,4,3,2,4,2,2,3,5,2,2,1,2,16,32.0,neutral or dissatisfied +74284,41226,Male,Loyal Customer,15,Personal Travel,Eco,1042,2,3,2,4,2,2,3,2,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +74285,76578,Male,Loyal Customer,72,Business travel,Business,516,3,4,4,4,1,3,3,3,3,3,3,3,3,1,0,8.0,neutral or dissatisfied +74286,119524,Male,disloyal Customer,34,Business travel,Eco,759,2,2,2,3,2,2,2,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +74287,29628,Male,disloyal Customer,37,Business travel,Eco,509,3,1,3,3,1,3,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +74288,28926,Male,Loyal Customer,60,Business travel,Eco,672,1,0,0,3,5,1,5,5,4,5,4,3,4,5,11,19.0,neutral or dissatisfied +74289,19213,Male,disloyal Customer,62,Business travel,Eco,459,3,1,3,2,3,3,3,3,1,5,3,1,3,3,48,61.0,neutral or dissatisfied +74290,106069,Female,Loyal Customer,36,Personal Travel,Business,302,4,4,4,3,2,5,4,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +74291,127819,Male,Loyal Customer,42,Business travel,Eco,862,4,5,5,5,4,4,4,4,4,3,4,1,3,4,0,0.0,satisfied +74292,35515,Female,Loyal Customer,51,Personal Travel,Eco,972,3,5,4,1,4,4,5,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +74293,118236,Male,Loyal Customer,27,Business travel,Eco,1587,1,1,1,1,1,2,1,1,4,5,1,2,3,1,40,39.0,neutral or dissatisfied +74294,24323,Female,Loyal Customer,20,Business travel,Eco,1048,2,2,2,2,2,2,3,2,3,1,2,2,1,2,90,87.0,neutral or dissatisfied +74295,78868,Male,Loyal Customer,30,Business travel,Business,1995,1,1,1,1,4,4,4,4,5,1,4,2,2,4,0,0.0,satisfied +74296,11246,Female,Loyal Customer,62,Personal Travel,Eco,429,4,2,4,3,5,4,3,5,5,4,5,4,5,2,0,0.0,satisfied +74297,92400,Female,Loyal Customer,43,Business travel,Business,1892,5,5,1,5,2,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +74298,95667,Male,Loyal Customer,31,Business travel,Business,3782,3,3,3,3,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +74299,51172,Female,Loyal Customer,48,Personal Travel,Eco,421,2,3,2,2,2,1,1,2,2,2,5,5,2,1,4,3.0,neutral or dissatisfied +74300,15051,Male,Loyal Customer,50,Business travel,Business,3158,2,4,4,4,1,4,4,2,2,2,2,1,2,3,27,23.0,neutral or dissatisfied +74301,114243,Male,disloyal Customer,54,Business travel,Eco,909,1,0,0,3,5,0,5,5,3,3,2,3,2,5,33,39.0,neutral or dissatisfied +74302,79106,Female,Loyal Customer,24,Personal Travel,Eco,226,1,5,1,4,5,1,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +74303,92561,Male,Loyal Customer,35,Personal Travel,Eco,2139,3,5,3,3,2,3,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +74304,84036,Male,Loyal Customer,41,Business travel,Business,879,2,2,2,2,5,5,5,4,5,4,5,5,3,5,279,309.0,satisfied +74305,58901,Female,Loyal Customer,55,Business travel,Eco,488,4,2,2,2,1,3,4,4,4,4,4,3,4,1,20,41.0,neutral or dissatisfied +74306,32307,Female,Loyal Customer,28,Business travel,Business,102,5,5,5,5,4,4,5,4,4,5,3,5,2,4,0,0.0,satisfied +74307,70586,Female,disloyal Customer,37,Business travel,Business,1258,1,1,1,1,1,1,1,1,5,3,5,4,4,1,2,0.0,neutral or dissatisfied +74308,63116,Female,disloyal Customer,20,Business travel,Eco,967,2,2,2,2,3,2,3,3,1,3,3,1,1,3,0,1.0,neutral or dissatisfied +74309,16746,Female,disloyal Customer,38,Business travel,Eco,569,2,0,2,1,3,2,4,3,4,2,1,1,5,3,0,57.0,neutral or dissatisfied +74310,35579,Male,Loyal Customer,33,Business travel,Eco Plus,1005,5,5,5,5,5,5,5,5,2,2,4,4,1,5,10,0.0,satisfied +74311,127789,Male,Loyal Customer,39,Personal Travel,Eco Plus,1037,2,3,2,3,3,2,3,3,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +74312,51398,Male,Loyal Customer,13,Personal Travel,Eco Plus,110,3,1,3,4,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +74313,30011,Male,disloyal Customer,21,Business travel,Eco,160,2,1,2,4,2,2,2,2,2,4,3,2,3,2,0,15.0,neutral or dissatisfied +74314,123717,Female,Loyal Customer,49,Personal Travel,Eco,214,2,4,2,1,3,5,5,3,3,2,2,4,3,4,0,0.0,neutral or dissatisfied +74315,17570,Female,Loyal Customer,58,Business travel,Eco,1034,5,3,1,1,3,1,1,5,5,5,5,3,5,2,41,30.0,satisfied +74316,88908,Male,Loyal Customer,52,Personal Travel,Eco,859,2,5,2,3,5,2,5,5,5,3,4,4,5,5,16,15.0,neutral or dissatisfied +74317,107701,Female,Loyal Customer,56,Business travel,Business,1699,3,4,4,4,2,1,2,3,3,3,3,3,3,2,3,0.0,neutral or dissatisfied +74318,23616,Male,disloyal Customer,43,Business travel,Eco,977,3,3,3,3,3,3,3,3,1,3,4,2,2,3,0,0.0,neutral or dissatisfied +74319,44653,Female,Loyal Customer,26,Business travel,Business,1543,3,3,3,3,2,2,3,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +74320,126167,Female,Loyal Customer,44,Business travel,Business,2183,2,2,3,2,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +74321,40663,Male,Loyal Customer,52,Business travel,Business,3439,4,4,4,4,2,4,4,4,4,5,4,5,4,5,4,0.0,satisfied +74322,73194,Male,Loyal Customer,37,Business travel,Business,1675,1,1,1,1,2,4,4,4,4,5,4,4,4,3,0,2.0,satisfied +74323,74449,Male,Loyal Customer,40,Business travel,Business,1431,3,3,3,3,3,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +74324,95187,Female,Loyal Customer,28,Personal Travel,Eco,239,3,1,3,4,2,3,5,2,2,4,4,2,3,2,4,0.0,neutral or dissatisfied +74325,84415,Male,Loyal Customer,56,Personal Travel,Eco,606,1,4,1,3,5,1,3,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +74326,104810,Female,Loyal Customer,11,Personal Travel,Eco,587,1,4,1,1,5,1,5,5,4,2,4,5,5,5,0,4.0,neutral or dissatisfied +74327,111843,Male,Loyal Customer,59,Business travel,Business,2856,5,5,5,5,5,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +74328,57522,Female,Loyal Customer,46,Business travel,Business,2372,4,4,3,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +74329,76129,Male,Loyal Customer,48,Business travel,Business,3700,3,3,5,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +74330,18891,Female,Loyal Customer,80,Business travel,Eco,103,3,1,1,1,1,4,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +74331,100802,Female,Loyal Customer,53,Personal Travel,Eco,748,2,4,2,2,1,4,1,5,5,2,5,4,5,1,12,0.0,neutral or dissatisfied +74332,80078,Male,Loyal Customer,39,Business travel,Eco Plus,1010,2,1,1,1,2,2,2,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +74333,68708,Male,Loyal Customer,7,Personal Travel,Eco,237,2,5,0,1,3,0,3,3,3,2,4,3,5,3,20,11.0,neutral or dissatisfied +74334,60260,Male,Loyal Customer,67,Personal Travel,Eco,1607,2,4,2,1,4,2,3,4,4,2,3,5,5,4,0,0.0,neutral or dissatisfied +74335,27764,Female,Loyal Customer,45,Business travel,Eco,1448,5,2,2,2,3,1,2,5,5,5,5,3,5,4,12,4.0,satisfied +74336,109255,Female,Loyal Customer,48,Business travel,Business,401,1,1,1,1,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +74337,118238,Female,Loyal Customer,36,Business travel,Business,1587,3,5,5,5,2,2,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +74338,26968,Male,disloyal Customer,20,Business travel,Eco,867,4,4,4,3,3,4,3,3,3,5,1,5,3,3,0,7.0,satisfied +74339,54697,Female,Loyal Customer,41,Business travel,Eco,787,4,1,1,1,4,4,4,4,2,1,4,4,5,4,0,0.0,satisfied +74340,52262,Male,disloyal Customer,25,Business travel,Eco,451,2,5,2,2,2,2,2,2,4,2,2,2,1,2,0,0.0,neutral or dissatisfied +74341,66638,Female,Loyal Customer,60,Business travel,Business,3522,2,2,2,2,3,5,5,4,4,4,4,5,4,5,16,4.0,satisfied +74342,77049,Male,Loyal Customer,61,Business travel,Business,3204,5,5,5,5,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +74343,77647,Male,Loyal Customer,56,Business travel,Business,1670,3,3,3,3,5,4,4,5,5,5,5,5,5,4,14,2.0,satisfied +74344,57835,Male,Loyal Customer,32,Business travel,Business,1491,2,2,2,2,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +74345,62123,Female,Loyal Customer,55,Business travel,Business,2425,1,1,1,1,3,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +74346,99652,Male,disloyal Customer,22,Business travel,Business,1050,4,0,4,4,5,4,3,5,3,2,5,4,4,5,0,8.0,satisfied +74347,105741,Male,Loyal Customer,55,Business travel,Eco,663,1,0,0,4,3,1,4,3,2,1,3,3,3,3,62,71.0,neutral or dissatisfied +74348,22456,Male,Loyal Customer,30,Personal Travel,Eco,208,4,2,4,4,3,4,4,3,3,5,3,4,3,3,38,38.0,neutral or dissatisfied +74349,19567,Male,Loyal Customer,54,Business travel,Eco,160,1,1,1,1,1,1,1,1,4,4,3,4,2,1,32,47.0,neutral or dissatisfied +74350,96302,Female,Loyal Customer,32,Business travel,Business,546,1,1,1,1,4,4,4,4,3,4,4,4,5,4,1,0.0,satisfied +74351,15501,Female,Loyal Customer,59,Personal Travel,Eco,377,1,5,1,3,4,4,5,5,5,1,5,4,5,3,69,61.0,neutral or dissatisfied +74352,51286,Male,Loyal Customer,19,Business travel,Eco Plus,421,3,4,4,4,3,3,2,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +74353,7629,Female,Loyal Customer,47,Business travel,Business,767,3,3,3,3,5,5,5,4,2,4,4,5,5,5,167,184.0,satisfied +74354,107562,Male,Loyal Customer,55,Business travel,Eco,1121,2,2,2,2,2,2,2,2,2,2,3,2,3,2,1,0.0,neutral or dissatisfied +74355,27677,Male,Loyal Customer,42,Business travel,Business,1883,2,1,1,1,5,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +74356,29331,Female,Loyal Customer,62,Personal Travel,Eco,834,3,4,3,4,3,5,4,5,5,3,5,4,5,4,0,12.0,neutral or dissatisfied +74357,82768,Male,Loyal Customer,43,Business travel,Business,409,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +74358,77600,Male,Loyal Customer,60,Business travel,Business,2476,4,4,4,4,5,4,4,4,4,3,4,4,4,4,1,0.0,satisfied +74359,78765,Female,Loyal Customer,49,Business travel,Business,2691,3,3,3,3,2,4,5,5,5,5,5,3,5,3,1,4.0,satisfied +74360,52941,Male,Loyal Customer,56,Business travel,Eco Plus,279,4,5,5,5,3,4,3,3,2,3,4,1,2,3,0,0.0,satisfied +74361,61427,Male,Loyal Customer,46,Business travel,Business,2419,3,3,3,3,5,3,4,4,4,4,4,5,4,3,87,78.0,satisfied +74362,92247,Male,Loyal Customer,54,Business travel,Eco,1670,3,4,4,4,3,3,3,3,3,5,2,2,3,3,0,0.0,neutral or dissatisfied +74363,58712,Male,Loyal Customer,58,Business travel,Business,1640,3,3,3,3,5,5,5,3,5,5,4,5,5,5,152,150.0,satisfied +74364,498,Female,Loyal Customer,49,Business travel,Business,3603,5,5,5,5,3,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +74365,15016,Female,Loyal Customer,24,Business travel,Business,3856,3,3,3,3,4,4,4,4,4,5,5,2,3,4,5,2.0,satisfied +74366,115815,Male,disloyal Customer,27,Business travel,Eco,337,3,4,3,3,5,3,5,5,2,4,4,2,4,5,10,5.0,neutral or dissatisfied +74367,85477,Female,disloyal Customer,40,Business travel,Business,214,1,1,1,3,1,1,4,1,2,1,3,4,4,1,0,4.0,neutral or dissatisfied +74368,5113,Female,Loyal Customer,52,Personal Travel,Eco,235,2,3,2,4,2,4,4,1,1,2,1,5,1,2,0,0.0,neutral or dissatisfied +74369,33314,Female,Loyal Customer,47,Business travel,Business,2355,4,3,3,3,3,2,2,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +74370,4148,Male,Loyal Customer,62,Business travel,Business,2381,3,5,5,5,1,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +74371,35852,Female,Loyal Customer,25,Business travel,Eco,665,5,1,1,1,5,5,5,5,4,1,2,2,4,5,0,0.0,satisfied +74372,124100,Male,Loyal Customer,47,Business travel,Business,529,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +74373,35124,Male,Loyal Customer,23,Business travel,Business,3176,1,1,1,1,5,5,5,5,2,5,2,5,2,5,22,21.0,satisfied +74374,82937,Female,disloyal Customer,42,Business travel,Eco Plus,194,5,5,5,1,4,5,4,4,2,5,5,3,4,4,0,12.0,satisfied +74375,105735,Female,Loyal Customer,30,Business travel,Business,3170,4,3,3,3,4,4,4,4,3,3,3,3,4,4,51,62.0,neutral or dissatisfied +74376,4129,Female,Loyal Customer,40,Business travel,Business,431,1,1,1,1,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +74377,110609,Male,Loyal Customer,32,Business travel,Eco Plus,488,2,2,2,2,2,2,2,2,3,3,3,4,3,2,12,4.0,neutral or dissatisfied +74378,67697,Male,disloyal Customer,22,Business travel,Business,1242,4,4,4,3,3,4,3,3,3,2,5,3,4,3,0,0.0,satisfied +74379,70272,Female,Loyal Customer,26,Business travel,Business,852,2,2,2,2,4,4,4,4,5,2,5,4,5,4,8,2.0,satisfied +74380,4446,Male,Loyal Customer,61,Personal Travel,Eco,762,2,5,1,4,2,1,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +74381,41118,Female,disloyal Customer,27,Business travel,Eco,295,3,5,3,5,3,3,1,3,1,1,3,3,1,3,0,0.0,neutral or dissatisfied +74382,111071,Male,Loyal Customer,20,Personal Travel,Eco,197,4,4,4,3,1,4,1,1,5,5,5,3,5,1,6,0.0,satisfied +74383,75633,Male,Loyal Customer,26,Personal Travel,Eco Plus,337,1,1,1,3,2,1,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +74384,126740,Male,disloyal Customer,23,Business travel,Eco,1339,2,2,2,4,5,2,5,5,3,3,4,1,4,5,29,36.0,neutral or dissatisfied +74385,85275,Male,Loyal Customer,54,Personal Travel,Eco,696,2,4,2,1,5,2,5,5,4,4,4,5,5,5,0,0.0,neutral or dissatisfied +74386,21881,Female,Loyal Customer,39,Business travel,Eco,500,5,3,3,3,5,5,5,5,2,1,2,3,2,5,0,0.0,satisfied +74387,7877,Female,Loyal Customer,36,Business travel,Business,948,5,5,5,5,4,4,4,4,4,4,4,3,4,5,0,4.0,satisfied +74388,18699,Male,Loyal Customer,56,Business travel,Eco Plus,190,5,5,5,5,5,5,5,5,1,4,1,3,2,5,0,10.0,satisfied +74389,62185,Female,disloyal Customer,22,Business travel,Eco,1425,1,1,1,3,5,1,5,5,1,3,2,3,3,5,87,81.0,neutral or dissatisfied +74390,23572,Male,Loyal Customer,37,Personal Travel,Eco,1015,1,2,1,3,2,1,2,2,1,1,3,3,3,2,30,16.0,neutral or dissatisfied +74391,68857,Female,Loyal Customer,52,Business travel,Business,2972,4,4,5,4,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +74392,91265,Female,Loyal Customer,66,Personal Travel,Eco,271,4,2,4,2,3,2,2,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +74393,83025,Female,Loyal Customer,42,Business travel,Business,3532,2,2,2,2,4,4,5,5,5,5,5,5,5,3,109,100.0,satisfied +74394,87360,Female,Loyal Customer,50,Business travel,Business,3748,5,5,5,5,3,4,5,4,4,4,4,5,4,3,8,11.0,satisfied +74395,58620,Female,Loyal Customer,42,Personal Travel,Eco,137,3,0,0,4,3,5,4,4,4,0,4,5,4,5,3,9.0,neutral or dissatisfied +74396,75256,Female,Loyal Customer,68,Personal Travel,Eco,1744,2,3,2,3,3,3,3,5,5,2,5,1,5,3,9,0.0,neutral or dissatisfied +74397,63996,Male,Loyal Customer,46,Business travel,Business,612,1,1,1,1,2,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +74398,85262,Female,Loyal Customer,28,Personal Travel,Eco,689,1,4,1,2,1,1,1,1,5,5,4,5,4,1,1,0.0,neutral or dissatisfied +74399,100617,Male,disloyal Customer,21,Business travel,Business,1121,4,5,4,2,1,4,5,1,5,2,5,3,4,1,0,0.0,satisfied +74400,83849,Male,Loyal Customer,62,Personal Travel,Eco,425,3,0,3,2,2,3,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +74401,124257,Male,Loyal Customer,67,Business travel,Eco Plus,1916,3,2,2,2,3,3,3,3,1,4,1,4,3,3,0,7.0,neutral or dissatisfied +74402,108458,Female,Loyal Customer,37,Personal Travel,Eco,1444,3,2,3,3,5,3,5,5,4,2,3,1,3,5,22,8.0,neutral or dissatisfied +74403,80393,Female,Loyal Customer,32,Personal Travel,Eco,368,4,5,4,1,1,4,1,1,5,4,3,1,4,1,0,0.0,neutral or dissatisfied +74404,88452,Female,Loyal Customer,38,Business travel,Business,115,1,1,1,1,3,5,1,4,4,4,4,1,4,1,0,0.0,satisfied +74405,69365,Female,disloyal Customer,25,Business travel,Business,1096,4,0,4,2,2,4,2,2,5,4,4,4,4,2,0,14.0,neutral or dissatisfied +74406,74773,Female,Loyal Customer,64,Personal Travel,Eco,1242,2,5,2,3,4,3,5,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +74407,2595,Male,Loyal Customer,50,Personal Travel,Eco,227,3,5,3,3,5,3,3,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +74408,27454,Female,disloyal Customer,25,Business travel,Eco,954,1,1,1,3,4,1,4,4,3,5,4,2,1,4,0,0.0,neutral or dissatisfied +74409,78568,Female,disloyal Customer,50,Business travel,Business,630,4,4,4,5,1,4,1,1,3,4,5,3,5,1,0,13.0,neutral or dissatisfied +74410,90450,Female,Loyal Customer,60,Business travel,Business,2274,1,1,1,1,4,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +74411,59608,Female,Loyal Customer,30,Business travel,Eco,964,1,2,2,2,1,1,1,1,3,1,4,4,3,1,3,0.0,neutral or dissatisfied +74412,19397,Male,Loyal Customer,49,Business travel,Eco,261,4,4,4,4,4,4,4,4,3,4,5,1,1,4,41,43.0,satisfied +74413,9386,Male,Loyal Customer,68,Personal Travel,Eco,401,4,4,3,3,5,3,5,5,5,2,5,4,5,5,0,2.0,neutral or dissatisfied +74414,8119,Female,disloyal Customer,44,Business travel,Business,402,4,4,4,1,1,4,1,1,5,2,5,4,4,1,0,0.0,satisfied +74415,40417,Female,Loyal Customer,43,Business travel,Business,2076,4,4,4,4,4,3,3,4,4,4,5,3,4,4,0,5.0,satisfied +74416,41354,Female,Loyal Customer,53,Business travel,Business,563,5,5,5,5,4,5,4,4,4,4,4,5,4,5,42,45.0,satisfied +74417,30583,Female,Loyal Customer,21,Personal Travel,Eco,628,3,3,3,3,5,3,2,5,4,2,4,1,3,5,0,0.0,neutral or dissatisfied +74418,64116,Female,disloyal Customer,10,Business travel,Eco,1049,3,3,3,3,1,3,1,1,2,4,2,1,3,1,0,8.0,neutral or dissatisfied +74419,71006,Female,Loyal Customer,10,Business travel,Business,802,2,2,2,2,4,4,4,4,5,4,5,5,5,4,5,0.0,satisfied +74420,77873,Female,Loyal Customer,33,Business travel,Business,1416,4,4,4,4,2,4,5,3,3,4,3,5,3,3,0,2.0,satisfied +74421,55874,Female,Loyal Customer,57,Business travel,Business,733,1,1,1,1,5,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +74422,97496,Male,Loyal Customer,54,Personal Travel,Eco,670,2,5,2,3,2,3,3,3,4,5,5,3,5,3,225,223.0,neutral or dissatisfied +74423,51940,Female,disloyal Customer,24,Business travel,Eco,843,0,0,0,2,5,0,5,5,4,1,2,4,2,5,0,0.0,satisfied +74424,117951,Female,Loyal Customer,48,Business travel,Business,255,1,1,1,1,5,4,1,5,5,5,5,4,5,1,13,4.0,satisfied +74425,102796,Female,disloyal Customer,20,Business travel,Eco,342,0,5,0,3,4,5,4,4,5,5,5,5,5,4,0,0.0,satisfied +74426,620,Male,Loyal Customer,58,Business travel,Business,1936,3,3,3,3,5,4,5,5,5,5,4,4,5,3,24,21.0,satisfied +74427,76889,Male,disloyal Customer,25,Business travel,Business,630,0,2,0,3,5,0,5,5,5,4,4,3,4,5,0,8.0,satisfied +74428,96576,Male,Loyal Customer,9,Personal Travel,Eco,333,3,3,3,3,3,3,4,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +74429,13282,Female,Loyal Customer,51,Personal Travel,Eco,771,2,5,2,3,2,1,1,1,4,3,4,1,1,1,197,205.0,neutral or dissatisfied +74430,43173,Female,disloyal Customer,23,Business travel,Eco,781,1,1,1,2,2,1,2,2,3,3,1,2,5,2,0,0.0,neutral or dissatisfied +74431,60696,Female,Loyal Customer,43,Business travel,Business,1605,5,5,5,5,3,3,3,4,3,4,4,3,4,3,171,137.0,satisfied +74432,73104,Male,Loyal Customer,45,Business travel,Business,2174,1,1,1,1,5,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +74433,14451,Male,Loyal Customer,8,Business travel,Business,2859,2,1,1,1,2,2,2,2,2,2,4,3,3,2,4,12.0,neutral or dissatisfied +74434,101942,Male,Loyal Customer,43,Business travel,Business,628,4,4,4,4,3,4,4,5,5,5,5,3,5,3,4,5.0,satisfied +74435,11838,Male,Loyal Customer,10,Personal Travel,Eco,1021,3,3,3,4,3,3,3,3,2,4,2,5,3,3,2,0.0,neutral or dissatisfied +74436,54622,Male,disloyal Customer,42,Business travel,Eco,861,3,3,3,3,3,3,5,3,2,1,2,2,2,3,72,74.0,neutral or dissatisfied +74437,89961,Female,Loyal Customer,66,Personal Travel,Eco,1416,3,2,3,3,2,4,3,5,5,3,3,2,5,4,6,12.0,neutral or dissatisfied +74438,6212,Male,disloyal Customer,27,Business travel,Business,462,2,2,2,2,5,2,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +74439,24285,Male,Loyal Customer,15,Personal Travel,Eco,134,1,0,1,3,5,1,2,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +74440,71590,Male,Loyal Customer,13,Business travel,Business,1182,3,2,2,2,3,3,3,4,3,4,4,3,3,3,133,111.0,neutral or dissatisfied +74441,123163,Female,Loyal Customer,60,Business travel,Business,507,3,3,5,5,1,3,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +74442,93333,Male,Loyal Customer,29,Business travel,Business,3494,1,2,2,2,1,1,1,1,2,1,3,2,4,1,3,0.0,neutral or dissatisfied +74443,44823,Male,Loyal Customer,47,Business travel,Business,2773,1,1,1,1,3,2,1,4,4,4,4,2,4,5,12,20.0,satisfied +74444,72320,Male,Loyal Customer,42,Business travel,Business,3347,3,3,2,3,2,5,5,4,4,4,4,4,4,4,11,19.0,satisfied +74445,74979,Male,Loyal Customer,50,Personal Travel,Eco,2475,3,1,4,4,5,4,5,5,1,1,4,3,4,5,0,29.0,neutral or dissatisfied +74446,94121,Male,disloyal Customer,62,Business travel,Business,277,3,3,3,2,1,3,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +74447,40479,Male,Loyal Customer,24,Business travel,Business,222,4,4,4,4,5,5,4,5,4,4,5,4,3,5,0,0.0,satisfied +74448,89400,Male,Loyal Customer,41,Business travel,Business,151,3,3,2,3,4,5,4,4,4,4,4,3,4,5,24,50.0,satisfied +74449,22336,Male,Loyal Customer,42,Business travel,Business,3093,2,2,2,2,4,2,1,4,4,4,4,1,4,1,0,0.0,satisfied +74450,111340,Female,Loyal Customer,11,Personal Travel,Eco,283,1,5,1,4,3,1,3,3,3,3,5,5,5,3,1,2.0,neutral or dissatisfied +74451,41526,Male,disloyal Customer,55,Business travel,Eco,1334,3,3,3,3,1,3,1,1,5,4,4,5,5,1,39,37.0,neutral or dissatisfied +74452,105699,Female,disloyal Customer,13,Business travel,Eco,842,1,1,1,4,3,1,1,3,1,4,3,4,3,3,5,13.0,neutral or dissatisfied +74453,106664,Male,Loyal Customer,40,Personal Travel,Eco,1590,3,4,3,5,3,3,3,3,3,3,4,3,5,3,18,7.0,neutral or dissatisfied +74454,44409,Male,Loyal Customer,45,Personal Travel,Eco,323,2,4,2,5,1,2,1,1,4,5,1,3,3,1,0,0.0,neutral or dissatisfied +74455,102276,Female,Loyal Customer,51,Business travel,Eco,386,2,2,4,2,2,2,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +74456,4100,Female,Loyal Customer,48,Business travel,Business,431,1,1,1,1,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +74457,127508,Male,Loyal Customer,70,Personal Travel,Eco,2075,3,4,3,4,4,3,2,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +74458,13101,Female,Loyal Customer,56,Business travel,Eco,562,4,4,4,4,1,5,5,4,4,4,4,2,4,3,0,0.0,satisfied +74459,70019,Male,Loyal Customer,52,Business travel,Business,583,3,3,4,3,2,4,4,5,5,5,5,4,5,5,0,7.0,satisfied +74460,47572,Female,Loyal Customer,66,Personal Travel,Eco Plus,590,1,4,1,1,2,4,5,5,5,1,5,4,5,3,0,2.0,neutral or dissatisfied +74461,94397,Female,disloyal Customer,18,Business travel,Eco,277,1,4,2,5,2,2,5,2,4,3,5,3,4,2,2,0.0,neutral or dissatisfied +74462,119456,Male,Loyal Customer,17,Personal Travel,Business,899,2,5,2,5,2,2,2,2,4,2,5,5,5,2,12,34.0,neutral or dissatisfied +74463,118838,Male,Loyal Customer,30,Business travel,Business,2783,2,2,4,2,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +74464,20998,Male,disloyal Customer,37,Business travel,Eco Plus,851,3,3,3,1,4,3,2,4,4,1,1,2,2,4,8,11.0,neutral or dissatisfied +74465,82965,Male,Loyal Customer,51,Business travel,Business,3131,4,4,4,4,5,5,5,5,5,5,5,3,5,5,53,66.0,satisfied +74466,103602,Female,disloyal Customer,22,Business travel,Eco,251,4,2,5,2,4,5,4,4,1,5,2,4,3,4,38,33.0,neutral or dissatisfied +74467,16531,Male,Loyal Customer,45,Business travel,Eco,209,2,1,1,1,2,2,2,2,2,4,3,1,3,2,59,62.0,neutral or dissatisfied +74468,73916,Female,Loyal Customer,54,Business travel,Business,2342,1,2,2,2,1,1,1,2,1,2,4,1,4,1,10,14.0,neutral or dissatisfied +74469,97942,Male,Loyal Customer,57,Business travel,Eco,616,4,1,1,1,4,4,4,4,4,2,3,2,2,4,84,79.0,neutral or dissatisfied +74470,90358,Female,Loyal Customer,42,Business travel,Business,270,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,1.0,satisfied +74471,74666,Female,Loyal Customer,37,Personal Travel,Eco,1235,3,2,3,4,5,3,5,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +74472,41189,Male,Loyal Customer,44,Business travel,Business,2564,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +74473,59598,Female,Loyal Customer,48,Business travel,Business,3253,4,4,4,4,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +74474,67427,Male,Loyal Customer,53,Business travel,Business,641,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +74475,26112,Female,Loyal Customer,47,Business travel,Business,2141,4,4,4,4,2,4,4,4,4,4,4,4,4,5,5,0.0,satisfied +74476,69222,Male,Loyal Customer,50,Business travel,Business,2623,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +74477,19602,Male,Loyal Customer,12,Personal Travel,Eco Plus,160,2,4,0,2,2,0,5,2,5,4,4,5,5,2,2,3.0,neutral or dissatisfied +74478,71394,Female,Loyal Customer,60,Personal Travel,Eco Plus,258,4,3,4,3,2,3,4,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +74479,53813,Female,Loyal Customer,48,Business travel,Business,140,2,2,2,2,1,1,3,5,5,5,5,1,5,4,26,19.0,satisfied +74480,85055,Male,Loyal Customer,55,Business travel,Business,731,2,4,2,2,5,5,5,5,5,5,5,4,5,5,15,2.0,satisfied +74481,72198,Female,Loyal Customer,58,Personal Travel,Eco,594,2,4,2,4,4,4,3,2,2,2,1,3,2,4,0,2.0,neutral or dissatisfied +74482,58416,Male,Loyal Customer,30,Business travel,Business,2415,3,2,2,2,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +74483,89083,Male,Loyal Customer,41,Business travel,Business,1947,4,4,4,4,3,4,5,2,2,2,2,3,2,4,6,0.0,satisfied +74484,93826,Male,Loyal Customer,46,Business travel,Business,391,3,3,3,3,2,4,5,5,5,5,5,4,5,3,2,0.0,satisfied +74485,57539,Female,Loyal Customer,14,Personal Travel,Eco,413,2,1,2,3,5,2,5,5,4,1,3,3,3,5,0,0.0,neutral or dissatisfied +74486,59100,Male,Loyal Customer,38,Personal Travel,Eco,1726,3,5,3,2,5,3,3,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +74487,13754,Male,Loyal Customer,13,Personal Travel,Eco,401,2,5,2,1,2,2,1,2,3,4,5,4,5,2,116,100.0,neutral or dissatisfied +74488,56006,Male,Loyal Customer,44,Business travel,Business,2475,1,1,1,1,4,4,4,4,2,5,5,4,5,4,0,9.0,satisfied +74489,118620,Male,disloyal Customer,18,Business travel,Eco,338,1,3,0,3,5,0,5,5,3,3,4,2,4,5,62,58.0,neutral or dissatisfied +74490,106894,Female,Loyal Customer,45,Personal Travel,Eco,577,2,4,2,1,4,5,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +74491,115655,Male,Loyal Customer,22,Business travel,Business,1958,3,5,5,5,3,3,3,3,2,3,3,4,3,3,31,24.0,neutral or dissatisfied +74492,22976,Female,Loyal Customer,70,Business travel,Eco,641,2,2,2,2,5,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +74493,102478,Male,Loyal Customer,24,Personal Travel,Eco,258,1,4,1,5,3,1,4,3,5,5,4,4,2,3,1,0.0,neutral or dissatisfied +74494,29445,Female,disloyal Customer,32,Business travel,Eco,421,3,0,3,4,3,3,3,3,1,5,5,4,4,3,2,3.0,neutral or dissatisfied +74495,111655,Male,Loyal Customer,40,Personal Travel,Eco Plus,1290,2,4,2,1,4,2,4,4,5,3,4,3,5,4,8,0.0,neutral or dissatisfied +74496,54465,Male,Loyal Customer,40,Business travel,Business,2033,2,3,3,3,3,3,4,2,2,1,2,3,2,2,0,18.0,neutral or dissatisfied +74497,117826,Male,Loyal Customer,34,Personal Travel,Eco,328,2,2,3,2,5,3,5,5,1,4,3,2,3,5,16,7.0,neutral or dissatisfied +74498,11747,Female,disloyal Customer,27,Business travel,Eco,429,3,0,3,4,4,3,4,4,1,2,4,4,3,4,6,6.0,neutral or dissatisfied +74499,129686,Male,Loyal Customer,34,Business travel,Business,2954,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +74500,13513,Male,disloyal Customer,38,Business travel,Eco,152,3,0,3,2,5,3,5,5,1,1,3,5,5,5,14,14.0,neutral or dissatisfied +74501,41958,Male,Loyal Customer,40,Business travel,Business,3578,5,5,5,5,5,3,1,4,4,4,4,3,4,5,0,0.0,satisfied +74502,39948,Female,Loyal Customer,20,Personal Travel,Eco,1195,2,4,2,3,3,2,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +74503,72356,Female,Loyal Customer,13,Personal Travel,Business,964,0,5,0,3,1,0,1,1,3,2,4,4,5,1,0,0.0,satisfied +74504,18137,Male,Loyal Customer,19,Personal Travel,Eco,632,3,1,3,3,2,3,3,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +74505,48438,Female,disloyal Customer,20,Business travel,Eco,844,0,0,0,1,4,0,4,4,3,1,3,4,1,4,0,0.0,satisfied +74506,20131,Female,Loyal Customer,63,Personal Travel,Eco,416,3,3,3,1,5,3,1,3,3,3,3,1,3,5,0,0.0,neutral or dissatisfied +74507,114982,Male,disloyal Customer,41,Business travel,Business,308,5,5,5,2,1,5,1,1,5,3,5,5,5,1,0,0.0,satisfied +74508,55400,Female,Loyal Customer,51,Business travel,Business,1573,5,5,5,5,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +74509,63673,Female,Loyal Customer,11,Personal Travel,Business,1047,3,4,3,4,3,2,2,4,5,5,5,2,5,2,162,129.0,neutral or dissatisfied +74510,87286,Male,disloyal Customer,23,Business travel,Eco,577,1,5,1,4,3,1,1,3,3,1,2,5,5,3,0,0.0,neutral or dissatisfied +74511,83446,Female,Loyal Customer,51,Business travel,Business,946,3,3,1,3,3,5,5,4,4,4,4,5,4,4,8,18.0,satisfied +74512,88532,Male,Loyal Customer,34,Personal Travel,Eco,250,2,4,2,2,4,2,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +74513,50065,Female,Loyal Customer,31,Business travel,Business,1773,1,5,5,5,1,1,1,1,4,2,3,1,3,1,15,15.0,neutral or dissatisfied +74514,88887,Male,Loyal Customer,16,Business travel,Eco,859,1,5,5,5,1,1,2,1,1,1,3,2,3,1,5,11.0,neutral or dissatisfied +74515,98194,Female,disloyal Customer,33,Business travel,Business,327,3,3,3,3,2,3,2,2,4,4,4,5,5,2,0,1.0,neutral or dissatisfied +74516,51849,Female,Loyal Customer,32,Business travel,Eco Plus,493,2,2,2,2,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +74517,111841,Female,Loyal Customer,27,Business travel,Business,1865,2,3,2,2,5,4,5,5,4,2,4,3,5,5,0,0.0,satisfied +74518,13593,Female,Loyal Customer,57,Personal Travel,Eco,106,5,4,5,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +74519,79242,Male,Loyal Customer,52,Business travel,Eco,1598,3,4,4,4,3,3,3,4,1,3,3,3,2,3,134,125.0,neutral or dissatisfied +74520,39721,Male,Loyal Customer,42,Business travel,Business,2387,2,2,3,2,2,5,3,5,5,5,4,1,5,1,0,0.0,satisfied +74521,3461,Female,Loyal Customer,57,Business travel,Eco Plus,213,3,2,2,2,1,4,4,3,3,3,3,1,3,3,36,78.0,neutral or dissatisfied +74522,16934,Male,disloyal Customer,20,Business travel,Eco,820,4,4,4,5,5,4,3,5,4,2,2,2,3,5,0,0.0,neutral or dissatisfied +74523,60988,Female,Loyal Customer,14,Personal Travel,Eco Plus,888,3,3,3,4,3,3,3,3,2,2,3,2,4,3,33,38.0,neutral or dissatisfied +74524,35840,Male,Loyal Customer,26,Business travel,Business,1621,1,1,1,1,1,1,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +74525,97697,Female,Loyal Customer,32,Business travel,Business,2104,2,2,2,2,5,4,5,5,3,5,4,5,5,5,6,2.0,satisfied +74526,43901,Male,Loyal Customer,29,Personal Travel,Eco,199,2,4,0,2,1,0,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +74527,88408,Female,Loyal Customer,27,Business travel,Business,2999,3,2,2,2,3,3,3,3,2,4,4,4,4,3,0,7.0,neutral or dissatisfied +74528,89902,Female,disloyal Customer,26,Business travel,Business,1310,4,3,3,1,2,3,2,2,4,5,5,4,5,2,0,6.0,satisfied +74529,89714,Female,Loyal Customer,9,Personal Travel,Eco,1035,3,4,3,2,5,3,5,5,3,3,5,4,4,5,47,103.0,neutral or dissatisfied +74530,73446,Female,Loyal Customer,18,Personal Travel,Eco,1182,2,4,1,5,2,1,2,2,5,5,4,4,5,2,32,43.0,neutral or dissatisfied +74531,26386,Female,Loyal Customer,51,Personal Travel,Eco Plus,991,4,4,4,3,3,5,5,4,4,4,3,5,4,3,0,0.0,neutral or dissatisfied +74532,95686,Female,disloyal Customer,38,Business travel,Business,453,2,3,3,4,2,3,2,2,3,4,4,5,5,2,7,0.0,neutral or dissatisfied +74533,124881,Female,disloyal Customer,30,Business travel,Business,728,4,4,4,3,4,4,4,4,4,3,4,3,4,4,10,25.0,neutral or dissatisfied +74534,75317,Female,Loyal Customer,48,Business travel,Business,2486,1,4,1,4,2,4,3,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +74535,122032,Male,Loyal Customer,64,Business travel,Eco,130,3,2,2,2,3,3,3,3,4,4,4,3,4,3,2,3.0,neutral or dissatisfied +74536,14610,Female,Loyal Customer,51,Business travel,Business,3634,2,2,2,2,5,1,2,5,5,5,5,4,5,1,0,0.0,satisfied +74537,79012,Male,Loyal Customer,52,Business travel,Business,3898,2,2,2,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +74538,28066,Female,Loyal Customer,44,Business travel,Business,2607,5,5,5,5,1,5,3,4,4,4,4,2,4,3,0,0.0,satisfied +74539,25783,Male,disloyal Customer,25,Business travel,Eco,762,4,4,4,2,3,4,3,3,2,4,4,1,1,3,0,24.0,satisfied +74540,27047,Female,disloyal Customer,41,Business travel,Eco,1154,2,2,2,3,4,2,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +74541,115058,Male,Loyal Customer,41,Business travel,Business,3907,4,5,4,4,5,5,5,5,5,5,5,4,5,3,53,51.0,satisfied +74542,11517,Male,Loyal Customer,10,Personal Travel,Eco Plus,201,2,4,2,4,5,2,5,5,2,4,3,4,4,5,0,0.0,neutral or dissatisfied +74543,15975,Male,Loyal Customer,46,Business travel,Business,3536,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +74544,20427,Female,Loyal Customer,41,Personal Travel,Eco,299,2,5,2,3,5,2,5,5,5,5,5,4,5,5,0,16.0,neutral or dissatisfied +74545,92571,Male,disloyal Customer,22,Business travel,Eco,1324,2,1,1,3,2,2,1,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +74546,122627,Female,Loyal Customer,55,Personal Travel,Eco,728,2,3,2,2,3,3,3,2,2,2,2,4,2,4,12,13.0,neutral or dissatisfied +74547,65843,Male,Loyal Customer,15,Business travel,Business,1389,4,2,2,2,4,3,4,4,1,3,4,2,3,4,0,0.0,neutral or dissatisfied +74548,102201,Male,Loyal Customer,47,Business travel,Business,223,4,4,4,4,5,5,4,3,3,4,5,3,3,3,40,30.0,satisfied +74549,46722,Male,Loyal Customer,42,Personal Travel,Eco,251,2,5,2,2,2,2,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +74550,25989,Female,Loyal Customer,45,Business travel,Eco,577,4,2,2,2,4,4,3,4,4,4,4,3,4,3,7,6.0,satisfied +74551,90289,Female,Loyal Customer,23,Business travel,Business,2589,2,4,4,4,2,2,2,2,3,1,3,4,2,2,0,0.0,neutral or dissatisfied +74552,123387,Female,Loyal Customer,33,Business travel,Business,1337,2,2,2,2,5,4,4,5,5,5,5,5,5,5,0,1.0,satisfied +74553,91016,Male,Loyal Customer,39,Personal Travel,Eco,404,4,2,4,3,5,4,5,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +74554,126041,Male,Loyal Customer,31,Business travel,Business,507,3,3,1,3,3,3,3,3,4,4,4,3,4,3,1,0.0,satisfied +74555,86146,Female,Loyal Customer,50,Business travel,Business,1636,1,4,4,4,1,3,3,2,2,2,1,1,2,4,0,0.0,neutral or dissatisfied +74556,35972,Male,Loyal Customer,34,Personal Travel,Eco,231,3,4,3,4,1,3,5,1,4,5,4,4,4,1,4,0.0,neutral or dissatisfied +74557,113883,Male,Loyal Customer,15,Personal Travel,Eco Plus,1334,4,5,4,3,5,4,5,5,5,4,3,4,5,5,0,0.0,neutral or dissatisfied +74558,4643,Male,disloyal Customer,43,Business travel,Business,364,5,5,5,4,5,2,5,4,4,4,5,5,4,5,167,188.0,satisfied +74559,92176,Male,Loyal Customer,59,Business travel,Business,1979,5,5,5,5,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +74560,71690,Female,Loyal Customer,47,Personal Travel,Eco,1005,3,2,3,3,5,4,4,5,5,3,3,3,5,3,14,6.0,neutral or dissatisfied +74561,15266,Male,Loyal Customer,10,Personal Travel,Eco,930,1,4,1,2,3,1,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +74562,6856,Male,Loyal Customer,60,Business travel,Business,1888,1,1,1,1,2,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +74563,52650,Female,Loyal Customer,21,Personal Travel,Eco,160,2,4,2,4,3,2,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +74564,70716,Female,Loyal Customer,36,Business travel,Business,2788,5,5,5,5,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +74565,44851,Female,disloyal Customer,17,Business travel,Eco,413,3,2,3,3,3,3,3,3,4,4,4,3,4,3,17,14.0,neutral or dissatisfied +74566,74240,Male,Loyal Customer,35,Business travel,Business,1709,1,1,5,1,2,3,4,5,5,5,5,4,5,4,0,7.0,satisfied +74567,112632,Female,Loyal Customer,72,Business travel,Eco Plus,602,3,4,4,4,4,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +74568,129813,Male,Loyal Customer,67,Personal Travel,Eco,337,2,4,2,2,2,2,2,2,4,3,4,4,4,2,9,0.0,neutral or dissatisfied +74569,4026,Female,disloyal Customer,22,Business travel,Eco,479,3,4,3,3,3,3,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +74570,128414,Female,disloyal Customer,27,Business travel,Eco,647,2,2,2,4,5,2,2,5,1,2,3,4,3,5,2,0.0,neutral or dissatisfied +74571,86322,Male,disloyal Customer,42,Business travel,Business,712,4,4,4,4,4,4,4,4,3,3,4,3,4,4,2,0.0,satisfied +74572,107710,Female,disloyal Customer,27,Business travel,Eco,251,1,2,1,4,3,1,5,3,4,4,3,3,4,3,26,45.0,neutral or dissatisfied +74573,62872,Male,Loyal Customer,19,Personal Travel,Eco,2583,3,4,3,3,2,3,2,2,2,2,2,4,4,2,0,0.0,neutral or dissatisfied +74574,27551,Male,Loyal Customer,47,Personal Travel,Eco,1050,2,1,2,4,3,2,3,3,2,2,4,2,4,3,1,0.0,neutral or dissatisfied +74575,59203,Female,Loyal Customer,39,Business travel,Business,1440,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +74576,8271,Male,Loyal Customer,11,Personal Travel,Eco,294,1,4,1,3,3,1,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +74577,15163,Male,Loyal Customer,41,Business travel,Eco Plus,1042,4,4,4,4,4,4,4,4,2,4,3,1,3,4,0,26.0,neutral or dissatisfied +74578,61932,Female,Loyal Customer,50,Personal Travel,Eco,550,4,3,4,3,3,3,3,3,3,4,3,4,3,1,0,7.0,neutral or dissatisfied +74579,9417,Male,disloyal Customer,37,Business travel,Business,362,3,3,3,4,4,3,4,4,3,2,3,4,4,4,0,21.0,neutral or dissatisfied +74580,37776,Male,disloyal Customer,54,Business travel,Eco Plus,972,2,2,2,2,1,2,1,1,3,5,1,4,2,1,27,32.0,neutral or dissatisfied +74581,88409,Female,Loyal Customer,66,Business travel,Eco,404,2,4,4,4,5,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +74582,39775,Female,Loyal Customer,50,Business travel,Business,121,0,4,0,1,5,4,5,1,1,1,1,2,1,2,0,1.0,satisfied +74583,58399,Female,Loyal Customer,50,Business travel,Business,733,3,3,4,3,5,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +74584,64766,Female,Loyal Customer,39,Business travel,Business,3742,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +74585,54118,Female,Loyal Customer,38,Business travel,Business,1400,2,2,2,2,3,1,2,4,4,4,4,4,4,5,8,15.0,satisfied +74586,25996,Female,Loyal Customer,58,Personal Travel,Eco,577,2,4,2,2,4,4,4,5,5,2,2,5,5,4,1,0.0,neutral or dissatisfied +74587,35170,Male,Loyal Customer,32,Business travel,Business,1076,2,2,3,2,5,5,5,5,5,2,3,5,5,5,0,13.0,satisfied +74588,115564,Male,Loyal Customer,42,Business travel,Business,417,3,3,3,3,3,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +74589,63276,Male,disloyal Customer,34,Business travel,Eco,447,4,1,4,4,1,4,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +74590,4902,Female,Loyal Customer,52,Business travel,Business,3515,3,3,3,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +74591,49467,Male,disloyal Customer,20,Business travel,Eco,109,4,4,4,2,5,4,2,5,1,1,1,4,5,5,0,0.0,satisfied +74592,6091,Female,disloyal Customer,25,Business travel,Eco Plus,672,1,4,1,4,4,1,4,4,2,3,3,4,4,4,0,11.0,neutral or dissatisfied +74593,36050,Female,disloyal Customer,20,Business travel,Eco,399,2,3,2,2,4,2,4,4,4,1,3,4,2,4,17,20.0,neutral or dissatisfied +74594,45358,Female,Loyal Customer,48,Personal Travel,Eco,461,1,3,1,3,2,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +74595,23099,Male,Loyal Customer,58,Business travel,Business,2777,2,2,2,2,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +74596,29151,Male,Loyal Customer,31,Business travel,Eco Plus,937,0,0,0,1,5,0,5,5,2,2,3,1,5,5,0,0.0,satisfied +74597,125733,Male,Loyal Customer,33,Business travel,Eco Plus,759,2,3,3,3,2,2,2,2,3,4,4,4,4,2,19,11.0,neutral or dissatisfied +74598,26048,Female,disloyal Customer,37,Business travel,Eco,432,2,3,2,3,3,2,3,3,3,4,4,4,3,3,31,17.0,neutral or dissatisfied +74599,5044,Male,disloyal Customer,29,Business travel,Eco,122,2,2,2,3,2,2,2,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +74600,46331,Male,disloyal Customer,17,Business travel,Eco,692,5,5,5,3,1,5,1,1,2,1,2,4,3,1,0,0.0,satisfied +74601,41778,Male,Loyal Customer,45,Business travel,Eco,508,4,1,1,1,4,4,4,4,1,3,1,2,2,4,0,0.0,satisfied +74602,49074,Male,Loyal Customer,53,Business travel,Eco,190,5,4,4,4,5,5,5,5,2,2,5,2,4,5,0,0.0,satisfied +74603,38527,Female,Loyal Customer,38,Business travel,Eco,2475,3,2,2,2,3,5,3,3,2,4,3,4,3,3,0,0.0,satisfied +74604,77500,Female,Loyal Customer,36,Personal Travel,Eco,1087,4,4,4,3,4,4,1,4,3,3,3,3,4,4,0,0.0,neutral or dissatisfied +74605,37709,Male,Loyal Customer,17,Personal Travel,Eco,1035,3,4,3,1,5,3,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +74606,68450,Male,Loyal Customer,39,Business travel,Business,1303,3,3,2,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +74607,26651,Female,Loyal Customer,40,Business travel,Business,2409,3,4,4,4,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +74608,69833,Male,disloyal Customer,27,Business travel,Eco,1055,1,1,1,4,4,1,4,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +74609,52338,Male,Loyal Customer,26,Business travel,Business,1977,3,5,5,5,3,3,3,3,4,2,4,1,3,3,66,63.0,neutral or dissatisfied +74610,39040,Male,Loyal Customer,35,Personal Travel,Eco,260,2,3,2,2,4,2,4,4,5,5,2,2,1,4,0,0.0,neutral or dissatisfied +74611,3431,Female,Loyal Customer,57,Personal Travel,Eco,296,3,2,3,1,1,1,2,5,5,3,5,4,5,4,41,34.0,neutral or dissatisfied +74612,21946,Female,disloyal Customer,28,Business travel,Eco,500,3,3,4,4,4,4,3,4,3,1,3,5,1,4,0,0.0,neutral or dissatisfied +74613,56616,Male,disloyal Customer,29,Business travel,Business,1023,3,3,3,2,5,3,3,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +74614,92550,Male,Loyal Customer,46,Personal Travel,Eco,1947,3,4,3,4,3,3,4,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +74615,127996,Female,Loyal Customer,9,Business travel,Business,1488,2,2,2,2,2,2,2,2,2,2,3,4,4,2,8,15.0,neutral or dissatisfied +74616,106479,Female,Loyal Customer,56,Business travel,Business,1624,3,3,3,3,2,4,5,5,5,5,5,5,5,5,15,29.0,satisfied +74617,61388,Female,disloyal Customer,70,Business travel,Eco,679,2,2,2,2,1,2,1,1,4,3,2,2,3,1,0,0.0,neutral or dissatisfied +74618,35488,Female,Loyal Customer,35,Personal Travel,Eco,950,3,0,3,4,1,3,4,1,5,5,4,5,4,1,21,25.0,neutral or dissatisfied +74619,17060,Female,Loyal Customer,21,Personal Travel,Eco,1134,3,4,3,3,3,1,3,3,2,5,5,3,3,3,152,219.0,neutral or dissatisfied +74620,81272,Male,disloyal Customer,16,Business travel,Eco,1020,4,4,4,3,5,4,5,5,4,4,5,5,5,5,10,34.0,satisfied +74621,109902,Female,Loyal Customer,49,Business travel,Business,634,2,2,2,2,2,4,4,4,4,4,4,1,4,4,14,0.0,satisfied +74622,30024,Male,disloyal Customer,40,Business travel,Eco,204,2,0,2,3,5,2,5,5,3,2,5,3,1,5,0,0.0,neutral or dissatisfied +74623,15594,Male,Loyal Customer,22,Business travel,Business,1756,4,4,4,4,4,4,4,4,1,4,2,2,2,4,0,0.0,neutral or dissatisfied +74624,385,Female,Loyal Customer,45,Business travel,Business,229,0,0,0,4,4,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +74625,48564,Male,Loyal Customer,19,Personal Travel,Eco,776,4,5,5,4,1,5,1,1,5,4,1,3,3,1,0,0.0,neutral or dissatisfied +74626,40851,Female,Loyal Customer,60,Personal Travel,Eco,599,2,2,2,3,1,3,3,4,4,2,4,1,4,2,30,19.0,neutral or dissatisfied +74627,109187,Female,Loyal Customer,56,Business travel,Eco,612,1,1,1,1,1,3,3,1,1,1,1,1,1,3,109,115.0,neutral or dissatisfied +74628,31310,Male,Loyal Customer,29,Business travel,Business,680,5,5,5,5,4,4,4,4,5,3,2,5,1,4,5,0.0,satisfied +74629,81447,Male,Loyal Customer,32,Business travel,Business,3716,5,5,5,5,5,5,5,5,5,2,5,5,5,5,0,2.0,satisfied +74630,46062,Female,disloyal Customer,28,Business travel,Eco Plus,991,3,3,3,3,3,3,3,3,4,2,3,2,4,3,15,42.0,neutral or dissatisfied +74631,27056,Female,Loyal Customer,45,Personal Travel,Eco,1709,3,4,3,3,4,2,1,5,5,3,5,5,5,3,0,13.0,neutral or dissatisfied +74632,28029,Male,Loyal Customer,44,Personal Travel,Eco,763,1,5,0,4,5,0,2,5,4,5,5,5,4,5,13,21.0,neutral or dissatisfied +74633,90215,Female,Loyal Customer,42,Personal Travel,Eco,983,4,5,3,4,3,1,2,5,5,3,5,3,5,2,0,0.0,satisfied +74634,112377,Female,Loyal Customer,46,Business travel,Business,967,3,1,3,3,4,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +74635,119110,Female,Loyal Customer,17,Personal Travel,Eco,1107,2,5,2,4,3,2,3,3,1,1,2,3,4,3,0,0.0,neutral or dissatisfied +74636,48913,Male,Loyal Customer,31,Business travel,Business,3252,3,3,3,3,5,5,5,5,5,2,5,5,1,5,3,0.0,satisfied +74637,94908,Female,Loyal Customer,33,Business travel,Business,2637,4,4,4,4,3,1,2,4,4,5,4,2,4,2,61,68.0,satisfied +74638,108195,Female,Loyal Customer,41,Business travel,Eco Plus,990,3,3,3,3,2,3,3,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +74639,111917,Female,Loyal Customer,48,Business travel,Business,3277,3,3,4,3,2,5,5,5,5,5,5,3,5,4,11,1.0,satisfied +74640,16480,Female,Loyal Customer,53,Business travel,Business,2531,0,0,0,5,2,2,2,4,5,5,5,2,3,2,202,186.0,satisfied +74641,31619,Male,Loyal Customer,48,Personal Travel,Business,846,3,5,3,4,3,5,5,1,1,3,2,5,1,3,41,41.0,neutral or dissatisfied +74642,64447,Male,disloyal Customer,29,Business travel,Eco,989,1,1,1,4,1,1,1,1,4,5,4,2,4,1,6,9.0,neutral or dissatisfied +74643,53207,Male,Loyal Customer,41,Business travel,Business,612,3,3,5,3,5,2,2,4,4,5,4,1,4,1,0,0.0,satisfied +74644,78340,Male,Loyal Customer,39,Business travel,Business,1547,5,5,4,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +74645,65232,Male,Loyal Customer,69,Business travel,Eco Plus,469,2,3,5,3,1,2,1,1,2,3,3,3,4,1,1,0.0,neutral or dissatisfied +74646,122706,Female,disloyal Customer,30,Business travel,Business,813,5,5,5,4,3,5,3,3,4,4,4,4,5,3,0,0.0,satisfied +74647,7503,Female,Loyal Customer,22,Personal Travel,Eco Plus,925,3,3,2,3,5,2,5,5,3,5,1,2,1,5,45,37.0,neutral or dissatisfied +74648,122773,Male,Loyal Customer,57,Business travel,Business,599,4,4,4,4,5,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +74649,23507,Male,Loyal Customer,37,Business travel,Eco,303,4,2,2,2,4,4,4,4,5,5,5,5,2,4,0,0.0,satisfied +74650,92478,Male,Loyal Customer,48,Business travel,Eco,1919,3,4,4,4,3,3,3,3,1,3,2,4,3,3,0,5.0,neutral or dissatisfied +74651,69994,Male,Loyal Customer,37,Personal Travel,Eco,236,2,4,2,4,3,2,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +74652,78513,Male,Loyal Customer,7,Personal Travel,Eco,526,3,4,3,1,2,3,4,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +74653,38120,Male,Loyal Customer,34,Business travel,Business,1010,1,1,1,1,2,5,1,3,3,3,3,1,3,4,0,0.0,satisfied +74654,26942,Male,Loyal Customer,52,Business travel,Business,2402,5,5,5,5,5,4,1,4,4,4,4,5,4,3,0,9.0,satisfied +74655,20755,Female,Loyal Customer,56,Business travel,Eco Plus,363,2,4,5,5,4,4,3,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +74656,44758,Female,Loyal Customer,55,Business travel,Business,2883,2,2,2,2,3,5,5,4,4,4,4,5,4,3,4,1.0,satisfied +74657,91763,Female,disloyal Customer,26,Business travel,Eco,588,3,1,3,4,1,3,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +74658,50751,Male,Loyal Customer,17,Personal Travel,Eco,337,3,5,3,5,2,3,2,2,4,4,4,4,4,2,0,2.0,neutral or dissatisfied +74659,12424,Female,Loyal Customer,22,Personal Travel,Eco,127,2,4,2,3,2,2,2,2,4,3,2,1,5,2,0,0.0,neutral or dissatisfied +74660,76673,Female,Loyal Customer,60,Personal Travel,Eco,481,1,2,1,3,4,3,3,3,3,1,3,4,3,3,0,2.0,neutral or dissatisfied +74661,117088,Male,Loyal Customer,33,Business travel,Business,1976,4,4,3,4,5,5,5,5,3,3,5,4,4,5,10,0.0,satisfied +74662,127140,Male,Loyal Customer,13,Personal Travel,Eco,647,2,1,2,3,1,2,1,1,4,3,2,3,2,1,16,5.0,neutral or dissatisfied +74663,73073,Male,Loyal Customer,44,Business travel,Business,1085,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +74664,26889,Male,Loyal Customer,31,Personal Travel,Eco,689,1,5,2,1,1,2,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +74665,31369,Male,Loyal Customer,46,Business travel,Business,2542,1,1,5,1,1,2,1,4,4,4,4,1,4,3,0,0.0,satisfied +74666,73092,Female,Loyal Customer,56,Personal Travel,Eco,1085,3,5,3,2,5,4,4,3,3,3,3,4,3,3,84,77.0,neutral or dissatisfied +74667,90526,Male,disloyal Customer,38,Business travel,Business,240,2,2,2,2,5,2,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +74668,33940,Male,disloyal Customer,22,Business travel,Eco,1188,3,2,2,3,5,2,1,5,1,5,1,2,4,5,0,0.0,neutral or dissatisfied +74669,5468,Male,Loyal Customer,13,Personal Travel,Eco,265,3,2,3,4,3,3,2,3,4,3,4,2,3,3,59,61.0,neutral or dissatisfied +74670,125891,Female,Loyal Customer,46,Personal Travel,Eco,861,1,5,1,3,4,5,5,3,3,1,5,4,3,4,0,0.0,neutral or dissatisfied +74671,58832,Female,Loyal Customer,52,Business travel,Eco Plus,1197,3,5,5,5,2,3,3,4,4,3,4,4,4,1,6,12.0,neutral or dissatisfied +74672,64585,Male,Loyal Customer,37,Business travel,Business,1743,3,3,3,3,4,5,5,4,4,4,5,4,4,5,0,12.0,satisfied +74673,81765,Male,Loyal Customer,19,Business travel,Business,1416,3,3,3,3,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +74674,12431,Male,Loyal Customer,7,Personal Travel,Eco,383,3,5,3,4,5,3,5,5,4,3,4,5,5,5,30,84.0,neutral or dissatisfied +74675,71481,Male,Loyal Customer,48,Business travel,Business,1012,5,5,5,5,5,5,5,5,5,5,5,4,5,3,29,23.0,satisfied +74676,124742,Female,Loyal Customer,53,Personal Travel,Eco Plus,399,2,5,2,3,2,5,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +74677,81579,Female,Loyal Customer,54,Business travel,Eco Plus,1039,3,5,5,5,1,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +74678,98014,Male,Loyal Customer,53,Business travel,Business,1014,2,2,2,2,3,4,4,4,4,4,4,4,4,5,4,13.0,satisfied +74679,100430,Female,Loyal Customer,20,Business travel,Business,1620,2,2,2,2,2,2,2,2,3,2,3,4,4,2,64,58.0,neutral or dissatisfied +74680,85965,Male,Loyal Customer,48,Business travel,Business,1777,1,1,1,1,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +74681,59631,Male,Loyal Customer,50,Business travel,Eco,854,4,3,3,3,4,4,4,4,4,5,2,3,3,4,0,0.0,neutral or dissatisfied +74682,14751,Female,disloyal Customer,70,Business travel,Eco,463,1,5,1,2,2,1,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +74683,103554,Female,Loyal Customer,11,Personal Travel,Eco,738,2,4,2,2,4,2,4,4,3,4,5,4,5,4,8,1.0,neutral or dissatisfied +74684,15658,Female,Loyal Customer,35,Business travel,Business,3291,2,2,2,2,3,4,4,5,5,5,5,4,5,3,44,30.0,satisfied +74685,71657,Female,Loyal Customer,59,Personal Travel,Eco,1197,1,5,1,1,4,3,5,2,2,1,5,4,2,3,0,0.0,neutral or dissatisfied +74686,3228,Female,Loyal Customer,60,Business travel,Business,3135,4,4,4,4,4,4,4,4,4,4,4,4,4,4,75,88.0,satisfied +74687,126125,Male,Loyal Customer,57,Business travel,Business,631,1,1,5,1,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +74688,40075,Female,disloyal Customer,34,Business travel,Eco,493,3,3,3,2,1,3,1,1,3,4,1,5,2,1,0,0.0,neutral or dissatisfied +74689,67632,Female,Loyal Customer,25,Business travel,Business,1723,2,2,2,2,4,4,4,4,5,4,4,4,5,4,2,,satisfied +74690,108370,Female,Loyal Customer,55,Personal Travel,Eco,1728,1,4,1,4,2,3,5,1,1,1,1,3,1,5,10,0.0,neutral or dissatisfied +74691,41687,Male,Loyal Customer,18,Personal Travel,Eco,347,5,4,5,2,2,5,2,2,5,4,4,5,5,2,0,0.0,satisfied +74692,121928,Male,Loyal Customer,55,Business travel,Business,366,3,3,3,3,4,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +74693,20298,Male,Loyal Customer,45,Personal Travel,Eco,235,1,4,1,4,1,1,2,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +74694,100919,Female,Loyal Customer,11,Personal Travel,Eco Plus,377,2,2,2,3,1,2,1,1,4,1,3,4,4,1,4,2.0,neutral or dissatisfied +74695,55318,Male,Loyal Customer,47,Business travel,Business,1117,5,5,5,5,3,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +74696,98987,Female,Loyal Customer,54,Personal Travel,Eco,479,2,5,2,1,1,3,2,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +74697,1916,Male,Loyal Customer,34,Business travel,Business,351,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +74698,71127,Female,Loyal Customer,56,Business travel,Business,1739,4,4,4,4,4,4,5,3,3,2,3,4,3,3,0,0.0,satisfied +74699,113659,Female,Loyal Customer,12,Personal Travel,Eco,223,3,3,3,4,4,3,4,4,3,4,3,3,4,4,13,6.0,neutral or dissatisfied +74700,18424,Male,Loyal Customer,52,Business travel,Business,1578,2,2,5,2,2,3,4,2,2,2,2,1,2,1,34,28.0,neutral or dissatisfied +74701,35830,Female,disloyal Customer,38,Business travel,Eco,937,3,3,3,3,4,3,4,4,1,4,3,3,4,4,107,102.0,neutral or dissatisfied +74702,50195,Female,Loyal Customer,37,Business travel,Eco,266,4,2,2,2,4,4,4,4,2,4,2,2,1,4,0,0.0,satisfied +74703,32690,Female,Loyal Customer,39,Business travel,Eco,201,4,3,4,3,4,4,4,4,2,3,3,5,5,4,0,0.0,satisfied +74704,42108,Female,Loyal Customer,54,Business travel,Business,996,1,2,5,2,1,3,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +74705,76583,Male,Loyal Customer,38,Business travel,Business,481,1,3,3,3,5,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +74706,28226,Male,Loyal Customer,28,Personal Travel,Eco Plus,569,1,5,0,3,3,0,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +74707,100894,Male,Loyal Customer,63,Business travel,Business,2501,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +74708,119569,Male,Loyal Customer,60,Business travel,Business,759,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +74709,24765,Female,Loyal Customer,48,Business travel,Business,2828,5,5,5,5,1,2,4,3,3,3,3,4,3,4,0,15.0,satisfied +74710,15584,Male,disloyal Customer,30,Business travel,Eco,296,2,3,1,4,4,1,4,4,2,3,2,1,4,4,3,4.0,neutral or dissatisfied +74711,42860,Female,Loyal Customer,62,Personal Travel,Eco,328,2,2,2,5,3,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +74712,117254,Female,Loyal Customer,39,Personal Travel,Eco,651,1,2,0,3,1,0,4,1,1,4,3,3,4,1,0,0.0,neutral or dissatisfied +74713,110010,Female,Loyal Customer,53,Business travel,Business,3823,1,1,2,1,2,5,4,4,4,5,4,3,4,5,5,2.0,satisfied +74714,22961,Female,Loyal Customer,40,Business travel,Business,3961,4,4,4,4,2,5,1,5,5,5,5,4,5,2,0,0.0,satisfied +74715,56674,Female,Loyal Customer,32,Personal Travel,Eco,1085,2,2,2,3,1,2,1,1,1,1,3,2,3,1,31,27.0,neutral or dissatisfied +74716,120408,Female,Loyal Customer,52,Business travel,Eco,337,4,2,2,2,5,2,2,4,4,4,4,3,4,3,8,45.0,neutral or dissatisfied +74717,49478,Male,Loyal Customer,59,Business travel,Business,3715,4,4,4,4,2,5,4,4,4,4,4,2,4,1,0,0.0,satisfied +74718,123517,Male,Loyal Customer,41,Personal Travel,Eco,2296,3,5,3,4,3,2,2,3,2,4,5,2,3,2,5,10.0,neutral or dissatisfied +74719,50055,Male,disloyal Customer,54,Business travel,Eco,158,1,4,1,4,5,1,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +74720,93551,Female,Loyal Customer,40,Business travel,Business,949,1,1,1,1,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +74721,27225,Female,disloyal Customer,22,Business travel,Eco,1024,2,2,2,2,2,2,2,2,1,1,3,1,2,2,0,0.0,neutral or dissatisfied +74722,32356,Male,Loyal Customer,60,Business travel,Eco,102,3,2,2,2,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +74723,69138,Male,Loyal Customer,39,Business travel,Business,2248,1,1,1,1,3,3,3,5,3,3,5,3,4,3,0,30.0,satisfied +74724,123724,Male,Loyal Customer,33,Business travel,Eco Plus,214,4,2,4,2,4,4,4,4,2,1,3,3,2,4,3,21.0,neutral or dissatisfied +74725,71399,Female,disloyal Customer,37,Business travel,Business,334,2,2,2,2,2,2,2,2,3,5,5,3,4,2,28,21.0,neutral or dissatisfied +74726,66947,Male,Loyal Customer,48,Business travel,Business,1894,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,3.0,satisfied +74727,5457,Female,Loyal Customer,35,Business travel,Business,1958,0,0,0,5,3,4,4,1,1,1,1,4,1,1,62,71.0,satisfied +74728,15532,Male,Loyal Customer,47,Business travel,Business,1937,4,2,2,2,2,3,3,4,4,4,4,4,4,3,1,12.0,neutral or dissatisfied +74729,82680,Female,Loyal Customer,46,Business travel,Business,3948,3,3,3,3,5,5,5,5,5,5,5,5,5,5,9,0.0,satisfied +74730,125045,Female,Loyal Customer,51,Personal Travel,Eco,2300,2,4,2,2,2,5,4,1,1,2,1,3,1,5,8,1.0,neutral or dissatisfied +74731,31395,Female,Loyal Customer,55,Business travel,Eco,1199,4,2,2,2,2,1,5,4,4,4,4,1,4,3,0,0.0,satisfied +74732,93142,Female,Loyal Customer,42,Business travel,Business,2176,1,4,4,4,1,4,3,1,1,1,1,2,1,3,0,7.0,neutral or dissatisfied +74733,46168,Female,Loyal Customer,36,Personal Travel,Eco,627,1,5,1,2,3,1,3,3,3,4,4,3,4,3,4,3.0,neutral or dissatisfied +74734,59382,Female,disloyal Customer,24,Business travel,Eco,1056,3,4,4,1,2,4,2,2,2,2,4,4,5,2,0,0.0,neutral or dissatisfied +74735,67334,Female,Loyal Customer,20,Business travel,Business,1471,2,2,4,2,4,4,4,4,5,3,4,3,5,4,10,0.0,satisfied +74736,33444,Male,Loyal Customer,46,Personal Travel,Eco,2614,3,4,3,4,3,4,4,4,4,3,4,4,4,4,0,19.0,neutral or dissatisfied +74737,85331,Female,disloyal Customer,28,Business travel,Business,731,4,4,4,3,3,4,3,3,4,5,5,5,5,3,0,4.0,satisfied +74738,123917,Male,Loyal Customer,14,Personal Travel,Eco,546,1,5,2,3,2,2,5,2,4,2,1,4,1,2,18,23.0,neutral or dissatisfied +74739,84044,Female,Loyal Customer,58,Business travel,Business,2129,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +74740,48399,Female,disloyal Customer,43,Business travel,Eco Plus,674,4,4,4,3,3,4,2,3,1,2,2,4,2,3,0,0.0,neutral or dissatisfied +74741,42686,Male,Loyal Customer,51,Business travel,Business,516,1,5,5,5,3,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +74742,50899,Female,Loyal Customer,62,Personal Travel,Eco,266,4,5,4,3,4,4,5,3,3,4,3,5,3,5,0,4.0,neutral or dissatisfied +74743,75037,Female,Loyal Customer,49,Personal Travel,Eco,236,2,4,2,3,4,4,5,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +74744,14653,Male,Loyal Customer,50,Business travel,Business,112,2,2,2,2,3,3,3,4,4,4,3,1,4,2,0,8.0,satisfied +74745,119501,Male,Loyal Customer,60,Business travel,Business,759,2,2,2,2,3,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +74746,25927,Female,Loyal Customer,24,Business travel,Business,194,3,1,1,1,2,2,3,2,4,5,3,3,4,2,27,15.0,neutral or dissatisfied +74747,121503,Female,Loyal Customer,62,Personal Travel,Eco Plus,331,2,1,4,4,3,4,4,3,3,4,3,4,3,3,0,23.0,neutral or dissatisfied +74748,110271,Male,disloyal Customer,16,Business travel,Eco,798,5,5,5,1,2,5,2,2,5,3,4,5,5,2,9,3.0,satisfied +74749,40353,Female,Loyal Customer,24,Personal Travel,Eco,1428,4,4,4,4,2,4,2,2,1,5,4,1,3,2,0,0.0,satisfied +74750,113587,Female,Loyal Customer,53,Business travel,Eco,258,4,3,3,3,2,5,2,4,4,4,4,1,4,4,12,3.0,satisfied +74751,111926,Male,Loyal Customer,70,Personal Travel,Eco,472,2,5,2,1,2,2,3,2,4,4,4,3,5,2,3,10.0,neutral or dissatisfied +74752,37078,Female,Loyal Customer,46,Business travel,Business,3255,4,4,2,4,4,5,5,4,4,4,4,5,4,4,23,32.0,satisfied +74753,52978,Female,Loyal Customer,53,Business travel,Business,3719,5,5,5,5,3,4,4,1,1,2,1,5,1,5,3,0.0,satisfied +74754,18054,Male,Loyal Customer,33,Business travel,Business,3507,1,3,3,3,1,1,1,1,2,3,4,1,3,1,5,0.0,neutral or dissatisfied +74755,14644,Male,Loyal Customer,53,Personal Travel,Eco,948,5,1,5,2,2,5,2,2,2,1,1,3,1,2,0,0.0,satisfied +74756,31145,Male,Loyal Customer,40,Business travel,Business,1502,5,5,5,5,1,4,3,4,4,4,4,2,4,4,0,0.0,satisfied +74757,17302,Male,Loyal Customer,48,Business travel,Business,403,3,3,3,3,2,5,2,4,4,4,4,2,4,4,0,0.0,satisfied +74758,1880,Female,Loyal Customer,21,Personal Travel,Eco,931,4,4,3,1,5,3,5,5,5,2,5,3,4,5,24,22.0,neutral or dissatisfied +74759,119050,Male,Loyal Customer,35,Business travel,Business,2279,1,1,1,1,2,5,4,5,5,5,5,3,5,4,14,16.0,satisfied +74760,75526,Male,Loyal Customer,42,Business travel,Business,337,0,0,0,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +74761,40350,Female,Loyal Customer,10,Business travel,Eco,1428,3,2,2,2,3,3,4,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +74762,32217,Male,Loyal Customer,60,Business travel,Business,216,1,2,2,2,1,4,3,2,2,2,1,4,2,3,0,0.0,neutral or dissatisfied +74763,36813,Female,Loyal Customer,31,Business travel,Business,2300,3,3,3,3,5,5,5,5,2,5,2,4,5,5,22,0.0,satisfied +74764,91251,Female,Loyal Customer,66,Personal Travel,Eco,270,3,5,4,3,3,4,4,3,3,4,1,3,3,4,15,22.0,neutral or dissatisfied +74765,66875,Male,Loyal Customer,49,Business travel,Business,2727,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +74766,47184,Female,Loyal Customer,8,Business travel,Business,2497,2,2,2,2,2,2,2,2,1,2,3,3,4,2,0,17.0,neutral or dissatisfied +74767,51167,Female,Loyal Customer,37,Personal Travel,Eco,250,4,1,4,3,3,4,3,3,1,1,3,1,2,3,68,55.0,neutral or dissatisfied +74768,126122,Female,Loyal Customer,43,Business travel,Business,468,2,4,4,4,3,3,2,2,2,2,2,1,2,4,0,10.0,neutral or dissatisfied +74769,45064,Male,Loyal Customer,38,Business travel,Business,2653,0,0,0,3,4,1,2,1,1,1,1,2,1,5,0,0.0,satisfied +74770,114947,Male,disloyal Customer,23,Business travel,Eco,373,2,0,2,1,3,2,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +74771,67590,Female,disloyal Customer,22,Business travel,Eco,1171,4,4,4,1,5,4,5,5,5,3,4,4,4,5,0,0.0,satisfied +74772,31127,Female,disloyal Customer,21,Business travel,Eco,991,3,3,3,4,4,3,5,4,4,4,4,2,3,4,4,0.0,neutral or dissatisfied +74773,109576,Male,Loyal Customer,25,Personal Travel,Eco,992,1,1,1,3,1,1,1,1,1,5,3,3,3,1,24,15.0,neutral or dissatisfied +74774,18710,Female,Loyal Customer,16,Business travel,Eco Plus,253,2,2,5,5,2,2,2,2,2,4,3,4,3,2,6,9.0,neutral or dissatisfied +74775,92628,Female,disloyal Customer,37,Business travel,Eco,453,2,4,2,3,3,2,3,3,4,4,4,2,3,3,0,0.0,neutral or dissatisfied +74776,22194,Male,Loyal Customer,31,Business travel,Business,2607,4,4,4,4,4,4,4,4,3,4,1,5,1,4,76,60.0,satisfied +74777,48965,Female,disloyal Customer,25,Business travel,Eco,158,1,0,1,4,3,1,1,3,2,3,2,5,1,3,0,0.0,neutral or dissatisfied +74778,88043,Female,Loyal Customer,36,Business travel,Business,1930,2,2,2,2,2,4,4,2,2,2,2,3,2,3,45,33.0,satisfied +74779,9081,Female,Loyal Customer,24,Personal Travel,Eco,160,1,3,1,2,3,1,5,3,3,5,5,1,1,3,0,0.0,neutral or dissatisfied +74780,50525,Female,Loyal Customer,7,Personal Travel,Eco,373,3,2,3,3,1,3,1,1,2,1,3,3,3,1,6,1.0,neutral or dissatisfied +74781,30437,Male,Loyal Customer,17,Business travel,Eco,851,5,2,2,2,5,5,4,5,5,5,3,2,5,5,0,0.0,satisfied +74782,76636,Female,disloyal Customer,25,Business travel,Eco,357,2,0,2,2,2,2,2,2,4,5,2,3,1,2,0,0.0,neutral or dissatisfied +74783,112222,Male,Loyal Customer,54,Business travel,Eco,799,3,5,2,5,3,3,3,3,2,1,4,4,4,3,18,0.0,neutral or dissatisfied +74784,45106,Female,Loyal Customer,38,Business travel,Business,157,4,4,4,4,3,5,1,5,5,5,5,5,5,3,0,0.0,satisfied +74785,65431,Female,Loyal Customer,44,Personal Travel,Eco,2165,3,5,3,1,5,4,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +74786,64278,Female,Loyal Customer,24,Business travel,Business,1172,3,3,3,3,5,4,5,5,4,2,5,4,4,5,0,0.0,satisfied +74787,41683,Male,Loyal Customer,46,Personal Travel,Eco,843,1,5,1,3,3,1,3,3,1,2,2,3,3,3,0,0.0,neutral or dissatisfied +74788,98519,Male,Loyal Customer,44,Business travel,Eco,402,4,1,1,1,4,4,4,4,4,2,3,1,4,4,0,0.0,satisfied +74789,112480,Female,Loyal Customer,69,Personal Travel,Eco,846,1,4,2,2,3,4,4,3,3,2,3,3,3,5,30,23.0,neutral or dissatisfied +74790,57462,Male,Loyal Customer,49,Personal Travel,Eco,334,2,5,4,3,2,4,2,2,4,3,4,5,4,2,29,31.0,neutral or dissatisfied +74791,72236,Female,Loyal Customer,48,Business travel,Business,2916,1,1,4,1,5,4,5,5,5,5,5,3,5,4,4,0.0,satisfied +74792,23965,Male,Loyal Customer,48,Business travel,Business,1742,5,5,5,5,4,4,5,4,4,4,4,1,4,5,27,32.0,satisfied +74793,27731,Male,Loyal Customer,59,Business travel,Eco,680,5,3,3,3,5,5,5,5,2,2,2,4,3,5,1,5.0,satisfied +74794,100175,Male,Loyal Customer,58,Personal Travel,Eco,523,3,4,3,4,5,3,5,5,5,4,5,5,5,5,1,0.0,neutral or dissatisfied +74795,89574,Male,Loyal Customer,26,Business travel,Business,2128,1,1,1,1,3,4,3,3,4,4,4,5,4,3,16,0.0,satisfied +74796,79494,Male,disloyal Customer,32,Business travel,Business,760,3,3,3,2,2,3,2,2,4,3,4,5,5,2,0,17.0,neutral or dissatisfied +74797,18490,Male,Loyal Customer,33,Business travel,Business,2884,4,4,4,4,5,5,5,5,1,1,1,5,4,5,9,0.0,satisfied +74798,22118,Female,Loyal Customer,30,Personal Travel,Eco,694,1,4,1,3,5,1,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +74799,114056,Male,Loyal Customer,39,Business travel,Business,1947,2,2,2,2,5,4,4,5,5,5,5,4,5,3,19,0.0,satisfied +74800,74750,Male,Loyal Customer,54,Personal Travel,Eco,1464,2,3,2,3,5,2,5,5,2,3,4,2,4,5,13,1.0,neutral or dissatisfied +74801,113000,Female,Loyal Customer,54,Business travel,Business,1797,1,1,1,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +74802,21843,Female,Loyal Customer,34,Business travel,Business,2346,2,2,2,2,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +74803,65057,Female,Loyal Customer,61,Personal Travel,Eco,190,3,4,0,4,1,5,5,2,2,0,2,2,2,3,60,58.0,neutral or dissatisfied +74804,93576,Female,disloyal Customer,22,Business travel,Eco,159,1,0,1,3,4,1,1,4,3,2,4,5,4,4,9,28.0,neutral or dissatisfied +74805,68994,Female,Loyal Customer,35,Business travel,Business,2422,2,2,2,2,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +74806,121706,Female,disloyal Customer,23,Business travel,Business,683,4,0,5,5,4,5,4,4,3,3,4,4,4,4,0,0.0,satisfied +74807,33904,Female,Loyal Customer,8,Personal Travel,Eco,1226,2,3,2,2,1,2,1,1,4,3,2,4,3,1,70,64.0,neutral or dissatisfied +74808,50014,Female,Loyal Customer,38,Business travel,Business,2787,1,2,2,2,3,4,3,1,1,1,1,1,1,4,4,11.0,neutral or dissatisfied +74809,99936,Female,Loyal Customer,40,Business travel,Business,2664,5,5,5,5,5,4,4,4,4,3,4,4,4,5,64,53.0,satisfied +74810,87936,Female,Loyal Customer,45,Business travel,Business,115,5,5,5,5,5,4,4,5,5,4,4,4,5,5,16,28.0,satisfied +74811,73890,Male,disloyal Customer,24,Business travel,Eco,998,3,3,3,1,4,3,3,4,5,5,3,4,4,4,0,0.0,neutral or dissatisfied +74812,118781,Female,Loyal Customer,66,Personal Travel,Eco,325,2,2,2,3,5,3,4,1,1,2,3,3,1,4,47,37.0,neutral or dissatisfied +74813,59344,Male,disloyal Customer,42,Business travel,Business,2338,3,3,3,3,1,3,1,1,5,3,3,5,5,1,26,0.0,neutral or dissatisfied +74814,38694,Female,Loyal Customer,31,Business travel,Eco,2342,5,4,4,4,5,5,5,5,1,2,4,3,5,5,0,18.0,satisfied +74815,54770,Male,disloyal Customer,25,Business travel,Eco Plus,787,2,5,2,4,4,2,4,4,2,2,4,5,1,4,0,0.0,neutral or dissatisfied +74816,47202,Female,Loyal Customer,48,Personal Travel,Eco,679,2,4,2,2,3,4,5,1,1,2,1,5,1,4,24,16.0,neutral or dissatisfied +74817,46630,Female,disloyal Customer,39,Business travel,Business,251,1,1,1,3,2,1,2,2,3,4,3,4,4,2,25,15.0,neutral or dissatisfied +74818,80657,Male,Loyal Customer,52,Business travel,Business,821,1,1,1,1,4,4,5,5,5,5,5,5,5,4,10,0.0,satisfied +74819,76187,Male,disloyal Customer,46,Business travel,Business,2422,1,1,1,3,1,1,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +74820,86409,Female,Loyal Customer,29,Business travel,Business,853,3,3,3,3,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +74821,104402,Female,Loyal Customer,31,Business travel,Business,2904,2,2,2,2,5,5,5,5,5,5,5,3,5,5,31,56.0,satisfied +74822,63237,Male,Loyal Customer,40,Business travel,Business,372,4,1,1,1,3,4,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +74823,67113,Male,Loyal Customer,51,Business travel,Eco,929,3,2,3,2,3,3,3,3,3,4,4,4,3,3,0,0.0,neutral or dissatisfied +74824,39227,Male,Loyal Customer,34,Business travel,Business,3698,1,1,1,1,5,5,4,4,4,5,5,4,4,3,0,3.0,satisfied +74825,79061,Male,disloyal Customer,44,Business travel,Eco,306,1,3,2,3,2,1,3,2,1,4,3,3,2,3,141,142.0,neutral or dissatisfied +74826,93554,Male,Loyal Customer,48,Business travel,Business,2718,3,4,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +74827,107176,Male,Loyal Customer,70,Business travel,Eco,402,3,2,2,2,3,3,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +74828,46837,Female,Loyal Customer,58,Business travel,Eco,845,5,3,3,3,3,1,1,5,5,5,5,3,5,2,9,1.0,satisfied +74829,1850,Male,Loyal Customer,60,Business travel,Eco Plus,500,2,5,5,5,1,2,1,1,2,5,3,2,3,1,36,22.0,neutral or dissatisfied +74830,27555,Male,Loyal Customer,56,Personal Travel,Eco,671,0,4,0,1,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +74831,101349,Female,Loyal Customer,23,Personal Travel,Eco,2026,1,4,2,1,4,2,3,4,3,5,3,4,5,4,0,0.0,neutral or dissatisfied +74832,63270,Male,disloyal Customer,25,Business travel,Eco,337,1,1,1,2,5,1,5,5,2,5,2,1,2,5,15,26.0,neutral or dissatisfied +74833,30816,Male,Loyal Customer,26,Business travel,Business,2659,3,3,5,3,2,2,2,2,1,5,5,4,3,2,0,0.0,satisfied +74834,65425,Male,disloyal Customer,49,Business travel,Business,2165,2,2,2,2,3,2,1,3,3,5,5,3,5,3,56,25.0,neutral or dissatisfied +74835,111982,Female,Loyal Customer,65,Personal Travel,Eco,533,1,4,1,3,4,4,4,4,4,1,1,3,4,4,4,0.0,neutral or dissatisfied +74836,29266,Male,Loyal Customer,29,Business travel,Business,3931,2,2,2,2,2,2,2,2,3,5,3,1,4,2,0,1.0,neutral or dissatisfied +74837,31813,Female,Loyal Customer,37,Business travel,Business,4983,2,3,2,2,4,4,4,3,1,5,1,4,3,4,0,2.0,satisfied +74838,38547,Male,disloyal Customer,37,Business travel,Business,1086,2,2,2,3,1,2,1,1,2,3,3,1,4,1,94,75.0,neutral or dissatisfied +74839,47420,Female,Loyal Customer,43,Business travel,Business,3052,3,4,4,4,3,3,3,3,3,3,3,2,3,1,3,0.0,neutral or dissatisfied +74840,58398,Female,disloyal Customer,15,Business travel,Business,733,4,4,4,2,3,4,3,3,4,5,4,4,5,3,0,0.0,satisfied +74841,75130,Male,disloyal Customer,35,Business travel,Business,1744,1,1,1,4,4,1,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +74842,31769,Male,Loyal Customer,39,Business travel,Business,3395,1,3,4,3,2,3,4,3,3,3,1,1,3,3,65,60.0,neutral or dissatisfied +74843,115336,Male,disloyal Customer,39,Business travel,Eco,308,4,1,4,4,2,4,2,2,2,4,3,4,4,2,40,38.0,neutral or dissatisfied +74844,61670,Male,Loyal Customer,58,Business travel,Eco,1504,2,3,1,1,2,2,2,2,1,2,3,3,2,2,46,26.0,neutral or dissatisfied +74845,62201,Male,Loyal Customer,59,Personal Travel,Eco,2565,3,2,3,3,4,3,4,4,2,1,4,4,3,4,15,0.0,neutral or dissatisfied +74846,84207,Female,Loyal Customer,26,Business travel,Business,432,2,2,2,2,4,4,4,4,4,2,5,3,5,4,0,3.0,satisfied +74847,64167,Male,Loyal Customer,7,Personal Travel,Eco,989,1,4,1,4,5,1,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +74848,17788,Female,Loyal Customer,41,Business travel,Business,1075,5,5,5,5,1,4,5,5,5,4,5,2,5,4,0,21.0,satisfied +74849,6067,Male,Loyal Customer,45,Personal Travel,Eco,630,2,4,1,4,2,1,2,2,3,4,4,4,5,2,0,1.0,neutral or dissatisfied +74850,85723,Male,Loyal Customer,56,Business travel,Business,3540,3,3,2,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +74851,105338,Male,Loyal Customer,37,Business travel,Eco,409,3,1,1,1,3,3,3,3,3,2,3,1,4,3,14,5.0,neutral or dissatisfied +74852,17864,Female,Loyal Customer,45,Business travel,Business,201,1,1,5,1,1,3,1,5,5,5,4,5,5,1,109,91.0,satisfied +74853,127284,Male,Loyal Customer,9,Personal Travel,Eco,1107,1,3,1,1,4,1,4,4,2,4,1,3,3,4,16,17.0,neutral or dissatisfied +74854,79169,Female,Loyal Customer,24,Business travel,Business,2422,1,1,1,1,4,4,4,3,3,3,4,4,5,4,0,0.0,satisfied +74855,127677,Female,Loyal Customer,46,Personal Travel,Eco,2153,0,4,0,1,3,5,4,1,1,0,1,5,1,3,0,0.0,satisfied +74856,64563,Female,Loyal Customer,48,Business travel,Business,2505,3,2,2,2,1,2,3,3,3,4,3,4,3,2,86,79.0,neutral or dissatisfied +74857,79718,Female,Loyal Customer,44,Personal Travel,Eco,712,1,2,1,3,5,4,3,5,5,1,5,4,5,3,37,56.0,neutral or dissatisfied +74858,22460,Female,Loyal Customer,36,Personal Travel,Eco,143,1,3,1,1,4,1,4,4,4,5,3,1,3,4,15,30.0,neutral or dissatisfied +74859,63571,Male,Loyal Customer,56,Personal Travel,Eco,1737,4,5,4,5,1,4,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +74860,82988,Male,Loyal Customer,59,Business travel,Business,1084,5,5,5,5,5,4,4,4,4,4,4,5,4,5,0,16.0,satisfied +74861,24303,Female,disloyal Customer,33,Business travel,Eco Plus,134,2,2,2,4,2,2,2,2,4,5,2,1,2,2,0,0.0,neutral or dissatisfied +74862,67782,Female,Loyal Customer,43,Business travel,Business,2249,3,3,5,3,3,3,3,3,3,3,3,1,3,4,13,9.0,neutral or dissatisfied +74863,15519,Male,Loyal Customer,33,Business travel,Eco Plus,399,0,0,0,3,3,0,3,3,2,3,3,4,4,3,11,0.0,satisfied +74864,75974,Male,Loyal Customer,47,Business travel,Business,228,3,3,3,3,2,2,3,5,5,5,5,3,5,2,0,0.0,satisfied +74865,108685,Female,Loyal Customer,26,Business travel,Business,1780,3,3,3,3,5,5,5,5,5,5,4,5,4,5,26,8.0,satisfied +74866,25118,Male,Loyal Customer,40,Personal Travel,Eco,946,1,1,0,2,3,0,3,3,2,2,2,1,2,3,62,63.0,neutral or dissatisfied +74867,48987,Male,Loyal Customer,37,Business travel,Business,1992,1,1,1,1,2,4,3,5,5,5,4,1,5,2,0,0.0,satisfied +74868,113987,Male,Loyal Customer,39,Business travel,Eco,1728,1,1,1,1,1,1,1,1,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +74869,60147,Male,disloyal Customer,17,Business travel,Eco,1012,1,2,2,4,1,2,1,1,2,5,4,3,3,1,0,3.0,neutral or dissatisfied +74870,11453,Male,Loyal Customer,56,Business travel,Business,2072,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,2.0,satisfied +74871,80299,Female,Loyal Customer,33,Business travel,Business,2674,5,5,5,5,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +74872,39820,Male,Loyal Customer,42,Business travel,Business,1859,1,1,1,1,3,3,1,5,5,5,5,1,5,2,0,5.0,satisfied +74873,29510,Male,Loyal Customer,50,Business travel,Eco Plus,1216,4,4,4,4,4,4,4,4,1,1,2,2,5,4,10,0.0,satisfied +74874,118244,Female,Loyal Customer,43,Personal Travel,Business,1788,1,5,1,1,3,3,5,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +74875,23270,Female,Loyal Customer,54,Business travel,Business,2253,2,2,2,2,5,4,5,4,4,4,4,4,4,4,13,0.0,satisfied +74876,80926,Female,Loyal Customer,51,Business travel,Business,3749,3,1,1,1,2,2,3,3,3,3,3,1,3,3,24,6.0,neutral or dissatisfied +74877,104210,Female,Loyal Customer,48,Business travel,Business,2640,4,4,4,4,5,4,5,4,4,4,4,3,4,4,15,4.0,satisfied +74878,40260,Female,disloyal Customer,17,Business travel,Eco,402,4,4,4,3,1,4,2,1,4,2,4,4,4,1,49,40.0,neutral or dissatisfied +74879,29567,Female,disloyal Customer,28,Business travel,Eco,1312,4,5,5,3,4,4,4,4,5,1,4,2,2,4,0,0.0,neutral or dissatisfied +74880,113623,Female,Loyal Customer,62,Personal Travel,Eco,407,2,4,5,3,4,4,3,3,3,5,2,1,3,1,16,29.0,neutral or dissatisfied +74881,91169,Male,Loyal Customer,10,Personal Travel,Eco,406,2,4,2,3,5,2,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +74882,118198,Female,Loyal Customer,43,Personal Travel,Eco,1444,2,1,2,4,1,2,3,2,2,2,2,1,2,2,11,2.0,neutral or dissatisfied +74883,91838,Male,Loyal Customer,69,Personal Travel,Eco Plus,590,1,3,1,4,1,1,1,1,4,5,4,2,4,1,2,1.0,neutral or dissatisfied +74884,118625,Female,disloyal Customer,40,Business travel,Business,621,4,4,4,3,3,4,3,3,4,5,5,5,4,3,0,0.0,satisfied +74885,7983,Male,Loyal Customer,60,Business travel,Business,2294,0,4,0,2,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +74886,68458,Male,disloyal Customer,22,Business travel,Eco,1303,1,1,1,3,2,1,2,2,3,3,4,4,5,2,0,3.0,neutral or dissatisfied +74887,81507,Male,disloyal Customer,20,Business travel,Eco,408,3,0,3,4,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +74888,78187,Male,Loyal Customer,36,Business travel,Eco,259,1,4,3,4,1,1,1,1,1,2,3,2,3,1,0,0.0,neutral or dissatisfied +74889,6785,Male,Loyal Customer,38,Business travel,Business,224,1,1,1,1,1,4,3,1,1,1,1,1,1,1,9,5.0,neutral or dissatisfied +74890,62669,Male,Loyal Customer,53,Business travel,Eco Plus,1744,2,3,3,3,2,2,2,2,3,3,4,3,4,2,1,12.0,neutral or dissatisfied +74891,54980,Female,disloyal Customer,38,Business travel,Business,1379,4,4,4,3,3,4,1,3,3,5,4,4,4,3,4,0.0,satisfied +74892,52473,Female,Loyal Customer,17,Personal Travel,Eco Plus,451,2,3,2,1,2,2,2,2,1,3,3,1,4,2,0,0.0,neutral or dissatisfied +74893,125740,Female,Loyal Customer,41,Business travel,Business,951,4,4,4,4,4,4,4,2,2,2,2,4,2,5,1,18.0,satisfied +74894,54542,Female,Loyal Customer,64,Personal Travel,Eco,925,3,4,3,2,3,2,5,1,1,3,1,4,1,1,28,19.0,neutral or dissatisfied +74895,107440,Male,Loyal Customer,9,Personal Travel,Eco,523,4,5,4,2,4,4,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +74896,64419,Female,Loyal Customer,36,Personal Travel,Business,989,2,5,2,3,2,4,4,3,3,2,3,3,3,5,26,23.0,neutral or dissatisfied +74897,72291,Male,Loyal Customer,42,Personal Travel,Eco,919,4,4,3,1,1,3,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +74898,47095,Male,Loyal Customer,63,Personal Travel,Eco,639,3,5,3,3,3,3,4,3,5,3,5,3,4,3,41,59.0,neutral or dissatisfied +74899,17161,Male,disloyal Customer,25,Business travel,Eco,643,3,0,2,4,2,2,2,2,5,1,1,1,4,2,0,20.0,neutral or dissatisfied +74900,126565,Female,Loyal Customer,40,Business travel,Business,1558,2,5,5,5,1,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +74901,34389,Female,disloyal Customer,33,Business travel,Eco,612,1,0,1,3,2,1,2,2,1,2,1,1,4,2,0,0.0,neutral or dissatisfied +74902,104023,Female,disloyal Customer,15,Business travel,Eco,1044,5,5,5,3,4,5,4,4,5,5,5,3,5,4,0,0.0,satisfied +74903,119490,Male,Loyal Customer,38,Business travel,Business,857,5,5,5,5,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +74904,88208,Female,Loyal Customer,35,Business travel,Eco,250,3,2,3,3,3,4,3,3,1,5,4,4,4,3,23,8.0,neutral or dissatisfied +74905,87502,Male,Loyal Customer,37,Business travel,Eco,321,5,1,1,1,5,5,5,5,1,2,2,5,2,5,1,0.0,satisfied +74906,16391,Male,Loyal Customer,59,Business travel,Business,533,5,5,5,5,4,5,1,5,5,5,5,3,5,4,0,2.0,satisfied +74907,85905,Male,Loyal Customer,59,Business travel,Business,761,4,4,4,4,4,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +74908,66277,Female,Loyal Customer,37,Business travel,Eco Plus,550,3,1,1,1,3,3,3,3,4,5,3,3,4,3,52,52.0,neutral or dissatisfied +74909,51994,Female,Loyal Customer,28,Business travel,Business,3117,3,4,4,4,3,2,3,3,1,5,4,3,4,3,0,0.0,neutral or dissatisfied +74910,76960,Female,disloyal Customer,26,Business travel,Eco,490,3,2,3,4,5,3,1,5,3,1,3,4,4,5,21,22.0,neutral or dissatisfied +74911,15993,Male,Loyal Customer,42,Business travel,Business,1636,2,2,2,2,3,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +74912,73218,Female,disloyal Customer,19,Business travel,Eco,946,4,4,4,1,1,4,1,1,3,2,4,3,4,1,4,5.0,satisfied +74913,100054,Male,Loyal Customer,14,Personal Travel,Eco,289,2,4,2,4,2,2,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +74914,51909,Female,Loyal Customer,44,Personal Travel,Eco,507,4,4,4,2,5,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +74915,89809,Female,disloyal Customer,24,Business travel,Business,1096,0,4,0,2,4,0,4,4,3,2,5,4,4,4,0,0.0,satisfied +74916,33390,Male,Loyal Customer,36,Personal Travel,Eco Plus,2614,1,3,1,4,2,1,2,2,2,4,2,1,3,2,0,0.0,neutral or dissatisfied +74917,126807,Female,Loyal Customer,42,Business travel,Business,2125,4,4,1,4,2,4,5,5,5,5,5,4,5,5,0,1.0,satisfied +74918,11083,Male,Loyal Customer,34,Personal Travel,Eco,224,2,4,2,1,3,2,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +74919,126634,Male,disloyal Customer,28,Business travel,Business,602,3,3,3,4,5,3,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +74920,65242,Female,Loyal Customer,47,Business travel,Business,2962,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +74921,115324,Male,disloyal Customer,27,Business travel,Eco,404,3,2,3,4,4,3,4,4,4,2,3,1,4,4,0,0.0,neutral or dissatisfied +74922,41974,Male,Loyal Customer,24,Personal Travel,Eco,525,2,2,2,4,2,2,2,2,2,5,3,2,4,2,54,45.0,neutral or dissatisfied +74923,81026,Female,Loyal Customer,52,Business travel,Business,1399,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,26.0,satisfied +74924,119915,Male,Loyal Customer,23,Business travel,Business,3117,5,5,5,5,4,4,4,4,5,4,5,4,4,4,1,0.0,satisfied +74925,27871,Female,Loyal Customer,51,Business travel,Eco Plus,1448,2,5,5,5,4,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +74926,101642,Male,Loyal Customer,52,Business travel,Business,1733,4,4,4,4,4,4,5,4,4,4,4,3,4,3,9,0.0,satisfied +74927,96158,Female,Loyal Customer,49,Business travel,Business,2720,3,1,3,3,4,4,5,2,2,2,2,4,2,3,11,13.0,satisfied +74928,34959,Male,Loyal Customer,27,Business travel,Eco Plus,187,0,0,0,4,2,0,3,2,2,4,5,4,2,2,0,0.0,satisfied +74929,109891,Female,Loyal Customer,36,Business travel,Business,692,2,2,2,2,2,4,4,4,4,4,4,2,4,5,4,0.0,satisfied +74930,92173,Male,Loyal Customer,53,Business travel,Business,2079,5,5,1,5,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +74931,97206,Female,Loyal Customer,50,Personal Travel,Eco,1390,3,3,3,3,1,2,3,2,2,3,2,3,2,4,20,17.0,neutral or dissatisfied +74932,100764,Male,disloyal Customer,20,Business travel,Eco,1411,4,4,4,4,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +74933,82232,Male,Loyal Customer,44,Business travel,Eco,405,2,5,5,5,2,2,2,2,1,1,4,3,1,2,0,0.0,satisfied +74934,15333,Male,Loyal Customer,11,Personal Travel,Eco,589,2,5,2,3,2,2,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +74935,93356,Female,Loyal Customer,38,Business travel,Business,436,2,2,2,2,3,1,4,5,5,5,5,4,5,5,0,0.0,satisfied +74936,67488,Male,disloyal Customer,25,Business travel,Business,592,1,0,1,2,2,1,2,2,4,4,4,3,4,2,0,7.0,neutral or dissatisfied +74937,83925,Female,Loyal Customer,20,Personal Travel,Business,373,2,4,2,3,2,2,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +74938,110611,Male,Loyal Customer,22,Business travel,Eco Plus,551,2,1,1,1,2,2,1,2,2,2,4,2,4,2,17,8.0,neutral or dissatisfied +74939,123558,Male,Loyal Customer,52,Business travel,Business,1773,1,3,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +74940,79179,Female,Loyal Customer,26,Business travel,Business,2422,3,4,4,4,3,3,3,4,2,4,3,3,4,3,117,104.0,neutral or dissatisfied +74941,77918,Female,disloyal Customer,24,Business travel,Eco,214,4,4,5,2,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +74942,114669,Female,Loyal Customer,33,Business travel,Business,1683,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +74943,9570,Male,Loyal Customer,53,Business travel,Business,3642,2,2,4,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +74944,60947,Female,disloyal Customer,26,Business travel,Business,888,1,1,1,4,4,1,1,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +74945,87951,Male,Loyal Customer,43,Personal Travel,Business,404,1,4,1,4,3,4,5,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +74946,11752,Male,Loyal Customer,47,Business travel,Business,429,3,2,2,2,2,3,2,3,3,3,3,1,3,3,86,84.0,neutral or dissatisfied +74947,83494,Female,Loyal Customer,46,Business travel,Eco,946,2,4,5,5,3,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +74948,36369,Male,Loyal Customer,38,Business travel,Eco,200,5,4,4,4,5,5,5,5,2,3,5,1,1,5,0,0.0,satisfied +74949,92112,Male,Loyal Customer,54,Personal Travel,Eco,1535,2,2,2,3,5,2,5,5,4,1,2,3,2,5,0,0.0,neutral or dissatisfied +74950,5105,Male,Loyal Customer,59,Personal Travel,Eco,235,3,4,3,3,5,3,5,5,3,1,5,4,5,5,0,0.0,neutral or dissatisfied +74951,36282,Female,Loyal Customer,7,Personal Travel,Eco Plus,728,4,3,4,5,3,4,3,3,4,4,3,5,3,3,0,0.0,neutral or dissatisfied +74952,41702,Female,Loyal Customer,40,Personal Travel,Eco Plus,347,3,4,5,5,2,5,2,2,5,5,5,4,5,2,2,0.0,neutral or dissatisfied +74953,96905,Male,Loyal Customer,49,Personal Travel,Eco,972,2,5,2,5,5,2,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +74954,88727,Female,Loyal Customer,26,Personal Travel,Eco,240,2,4,2,2,4,2,4,4,3,5,2,4,3,4,14,27.0,neutral or dissatisfied +74955,25794,Female,Loyal Customer,41,Business travel,Business,762,4,5,5,5,1,3,3,4,4,4,4,2,4,1,0,3.0,neutral or dissatisfied +74956,90283,Female,Loyal Customer,23,Business travel,Business,879,4,3,3,3,4,4,4,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +74957,105070,Female,Loyal Customer,17,Personal Travel,Business,289,4,5,3,1,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +74958,30754,Female,Loyal Customer,58,Personal Travel,Eco,977,3,4,3,3,3,5,5,2,2,3,3,3,2,4,4,13.0,neutral or dissatisfied +74959,69373,Male,Loyal Customer,46,Business travel,Business,1035,1,1,1,1,4,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +74960,58518,Female,Loyal Customer,25,Personal Travel,Eco,719,3,4,3,4,2,3,1,2,3,4,4,5,4,2,59,55.0,neutral or dissatisfied +74961,13102,Male,disloyal Customer,39,Business travel,Eco,427,4,1,4,4,5,4,5,5,1,5,4,2,3,5,0,8.0,neutral or dissatisfied +74962,44285,Male,disloyal Customer,21,Business travel,Eco,1123,4,5,5,3,5,5,4,5,3,4,5,5,4,5,0,0.0,satisfied +74963,50527,Male,Loyal Customer,34,Personal Travel,Eco,363,4,4,2,1,4,2,4,4,4,5,4,5,5,4,0,0.0,satisfied +74964,1563,Male,Loyal Customer,67,Personal Travel,Business,237,4,4,4,2,1,4,4,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +74965,8965,Male,Loyal Customer,59,Business travel,Business,2950,1,1,1,1,5,5,5,4,4,4,4,3,4,4,33,44.0,satisfied +74966,23426,Female,disloyal Customer,24,Business travel,Eco,1201,4,3,3,5,5,3,5,5,3,1,5,1,2,5,0,0.0,satisfied +74967,33203,Male,Loyal Customer,35,Business travel,Eco Plus,102,5,1,1,1,5,5,5,5,1,1,5,1,5,5,0,0.0,satisfied +74968,89155,Female,Loyal Customer,62,Personal Travel,Eco,1919,5,4,5,4,3,4,4,1,1,5,4,4,1,5,0,0.0,satisfied +74969,107550,Female,Loyal Customer,47,Business travel,Business,1521,5,5,5,5,5,4,4,2,2,2,2,4,2,3,7,0.0,satisfied +74970,94919,Female,disloyal Customer,38,Business travel,Eco,189,3,2,3,4,1,3,1,1,2,4,4,1,3,1,0,0.0,neutral or dissatisfied +74971,91434,Female,Loyal Customer,60,Business travel,Business,2624,5,5,5,5,4,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +74972,52961,Female,disloyal Customer,22,Business travel,Business,2306,5,0,5,3,5,1,2,2,1,4,5,2,5,2,9,25.0,satisfied +74973,123267,Female,Loyal Customer,33,Personal Travel,Eco,547,1,3,1,4,1,1,2,1,1,5,2,4,3,1,7,12.0,neutral or dissatisfied +74974,53691,Female,Loyal Customer,28,Business travel,Business,2254,1,1,1,1,4,4,4,4,2,2,1,4,1,4,0,0.0,satisfied +74975,7353,Male,disloyal Customer,38,Business travel,Business,864,3,3,3,2,5,3,5,5,3,4,4,4,5,5,3,0.0,satisfied +74976,5229,Male,Loyal Customer,41,Business travel,Business,285,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,9.0,satisfied +74977,96081,Female,Loyal Customer,68,Personal Travel,Eco,1069,4,4,3,4,1,4,3,3,3,3,3,2,3,4,11,0.0,neutral or dissatisfied +74978,18901,Female,Loyal Customer,48,Personal Travel,Eco,503,0,3,0,2,3,2,2,5,5,0,5,1,5,3,66,57.0,satisfied +74979,23592,Female,Loyal Customer,51,Personal Travel,Eco,1069,2,5,2,1,2,2,2,3,2,4,5,2,5,2,496,470.0,neutral or dissatisfied +74980,31026,Male,disloyal Customer,38,Business travel,Eco Plus,391,1,1,1,4,2,1,2,2,2,4,2,5,1,2,0,0.0,neutral or dissatisfied +74981,30062,Male,Loyal Customer,33,Business travel,Business,399,3,3,3,3,1,2,1,1,5,4,1,4,5,1,0,0.0,satisfied +74982,5695,Male,Loyal Customer,37,Business travel,Business,3863,4,3,3,3,3,3,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +74983,96678,Female,Loyal Customer,20,Personal Travel,Eco Plus,972,0,4,0,2,1,0,1,1,3,5,4,5,5,1,17,17.0,satisfied +74984,85481,Male,Loyal Customer,51,Personal Travel,Eco,214,5,0,5,4,3,5,3,3,4,4,4,4,4,3,2,0.0,satisfied +74985,22545,Male,Loyal Customer,44,Business travel,Eco Plus,143,5,1,1,1,5,5,5,5,1,1,2,5,3,5,0,15.0,satisfied +74986,32640,Female,disloyal Customer,33,Business travel,Eco,101,2,3,2,2,3,2,3,3,3,2,1,5,4,3,0,0.0,neutral or dissatisfied +74987,83153,Male,disloyal Customer,47,Business travel,Business,1086,5,5,5,1,2,5,2,2,5,5,4,4,5,2,0,37.0,satisfied +74988,118399,Female,Loyal Customer,47,Business travel,Business,369,1,3,3,3,4,3,3,1,1,1,1,3,1,1,57,52.0,neutral or dissatisfied +74989,52309,Male,Loyal Customer,31,Business travel,Business,3744,2,3,3,3,2,2,2,2,3,3,4,3,3,2,0,10.0,neutral or dissatisfied +74990,109167,Female,Loyal Customer,48,Business travel,Business,793,2,2,2,2,4,5,4,3,3,4,3,4,3,5,14,0.0,satisfied +74991,50443,Male,disloyal Customer,23,Business travel,Eco,89,4,0,4,1,4,4,4,4,1,3,4,1,5,4,13,4.0,satisfied +74992,124589,Male,disloyal Customer,29,Business travel,Eco,500,2,3,2,4,1,2,1,1,2,3,4,4,4,1,10,0.0,neutral or dissatisfied +74993,30287,Female,Loyal Customer,39,Business travel,Business,1476,4,4,4,4,4,4,4,4,1,3,1,4,4,4,149,148.0,satisfied +74994,45934,Female,Loyal Customer,16,Personal Travel,Eco,563,2,3,2,3,3,2,3,3,2,4,3,1,4,3,86,103.0,neutral or dissatisfied +74995,19265,Female,Loyal Customer,49,Personal Travel,Eco,802,3,3,3,3,3,5,4,3,3,3,4,4,3,3,0,0.0,neutral or dissatisfied +74996,124053,Male,Loyal Customer,29,Business travel,Business,2153,2,2,2,2,5,5,5,5,5,5,4,5,4,5,10,0.0,satisfied +74997,62149,Female,Loyal Customer,37,Business travel,Eco,2565,3,3,3,3,3,3,3,3,3,4,1,1,3,3,52,52.0,neutral or dissatisfied +74998,58969,Male,Loyal Customer,46,Personal Travel,Business,1846,2,2,2,4,5,2,4,3,3,2,3,4,3,3,79,70.0,neutral or dissatisfied +74999,119030,Male,Loyal Customer,26,Personal Travel,Eco,1460,2,4,2,2,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +75000,82220,Female,Loyal Customer,56,Business travel,Business,3143,1,1,1,1,2,5,5,4,4,4,4,3,4,5,19,20.0,satisfied +75001,19652,Female,Loyal Customer,56,Business travel,Eco,763,1,3,3,3,2,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +75002,95973,Male,Loyal Customer,44,Business travel,Business,583,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +75003,49869,Male,Loyal Customer,36,Business travel,Eco,421,3,3,3,3,3,3,3,3,3,1,3,3,3,3,11,23.0,neutral or dissatisfied +75004,86044,Female,Loyal Customer,34,Personal Travel,Eco,432,4,4,4,5,5,4,4,5,3,1,2,2,4,5,0,0.0,neutral or dissatisfied +75005,3294,Female,Loyal Customer,42,Personal Travel,Eco,479,2,3,2,3,1,1,3,1,1,2,1,3,1,1,89,98.0,neutral or dissatisfied +75006,62841,Female,disloyal Customer,9,Business travel,Business,2556,4,0,4,4,4,3,3,4,4,5,4,3,5,3,0,4.0,satisfied +75007,124602,Male,Loyal Customer,38,Personal Travel,Eco,500,1,4,1,3,2,1,2,2,4,1,3,4,3,2,20,11.0,neutral or dissatisfied +75008,81061,Female,disloyal Customer,39,Business travel,Business,1399,2,2,2,3,1,2,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +75009,129462,Male,Loyal Customer,66,Personal Travel,Eco Plus,414,1,4,1,4,2,1,5,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +75010,14208,Female,disloyal Customer,29,Business travel,Eco,620,1,2,1,3,1,1,1,1,4,3,3,1,4,1,143,133.0,neutral or dissatisfied +75011,101024,Female,Loyal Customer,35,Personal Travel,Eco,564,3,4,3,3,5,3,5,5,2,4,4,3,4,5,16,24.0,neutral or dissatisfied +75012,53971,Female,Loyal Customer,24,Personal Travel,Eco,1325,1,5,1,3,3,1,3,3,5,5,4,4,4,3,10,8.0,neutral or dissatisfied +75013,103549,Female,Loyal Customer,58,Personal Travel,Eco,967,2,5,2,5,3,5,4,1,1,2,1,5,1,4,8,26.0,neutral or dissatisfied +75014,10008,Female,Loyal Customer,37,Personal Travel,Eco,508,5,5,1,4,3,1,3,3,1,4,2,5,3,3,0,0.0,satisfied +75015,68552,Male,Loyal Customer,25,Personal Travel,Eco Plus,1013,1,1,1,4,2,1,2,2,4,5,3,4,3,2,45,16.0,neutral or dissatisfied +75016,6676,Female,Loyal Customer,46,Business travel,Business,258,5,5,3,5,4,4,5,4,4,4,4,3,4,5,13,59.0,satisfied +75017,66297,Female,Loyal Customer,38,Business travel,Business,2334,4,4,4,4,3,5,4,5,5,5,5,4,5,5,39,38.0,satisfied +75018,45752,Male,Loyal Customer,37,Business travel,Business,391,3,3,3,3,1,4,2,4,4,5,4,5,4,2,0,0.0,satisfied +75019,101321,Female,Loyal Customer,16,Personal Travel,Eco,1076,4,1,4,1,5,4,5,5,3,5,2,1,1,5,9,0.0,satisfied +75020,30800,Female,Loyal Customer,70,Personal Travel,Eco,701,3,5,2,1,3,5,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +75021,89240,Female,Loyal Customer,48,Business travel,Eco Plus,2139,1,0,0,3,1,2,4,3,3,1,3,1,3,3,64,71.0,neutral or dissatisfied +75022,3211,Female,Loyal Customer,46,Business travel,Business,585,5,5,5,5,3,4,4,2,2,2,2,4,2,4,11,6.0,satisfied +75023,106020,Male,Loyal Customer,45,Business travel,Business,1864,4,4,4,4,5,4,5,4,4,5,4,5,4,5,24,28.0,satisfied +75024,78829,Female,Loyal Customer,37,Personal Travel,Eco,554,2,5,2,5,2,2,1,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +75025,95357,Female,Loyal Customer,66,Personal Travel,Eco,239,3,4,3,1,1,2,3,5,5,3,5,3,5,3,36,25.0,neutral or dissatisfied +75026,78326,Male,disloyal Customer,46,Business travel,Business,1547,4,4,4,2,4,4,2,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +75027,64969,Male,Loyal Customer,77,Business travel,Business,3768,3,4,4,4,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +75028,107115,Female,Loyal Customer,57,Business travel,Business,842,2,2,1,2,3,5,4,5,5,5,5,3,5,5,11,16.0,satisfied +75029,79232,Male,Loyal Customer,25,Business travel,Business,1521,3,4,2,4,3,3,3,3,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +75030,57701,Male,Loyal Customer,39,Personal Travel,Eco,867,1,1,1,3,1,1,1,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +75031,104025,Male,disloyal Customer,26,Business travel,Business,1044,3,3,3,4,4,3,4,4,5,5,5,3,5,4,23,50.0,neutral or dissatisfied +75032,62092,Female,Loyal Customer,60,Business travel,Business,2454,4,3,4,4,5,4,5,3,3,3,3,3,3,5,1,18.0,satisfied +75033,59473,Female,Loyal Customer,23,Business travel,Eco,758,3,2,2,2,3,3,4,3,4,4,3,2,4,3,0,3.0,neutral or dissatisfied +75034,106573,Female,disloyal Customer,14,Business travel,Business,1506,5,0,5,1,5,5,5,5,4,2,4,5,5,5,6,0.0,satisfied +75035,13197,Male,Loyal Customer,30,Personal Travel,Eco,542,2,4,2,3,2,2,1,2,5,4,4,5,1,2,69,51.0,neutral or dissatisfied +75036,33003,Female,Loyal Customer,15,Personal Travel,Eco,102,2,5,2,5,2,2,2,2,5,2,5,4,5,2,1,5.0,neutral or dissatisfied +75037,52404,Male,Loyal Customer,32,Personal Travel,Eco,451,2,5,2,2,3,2,3,3,1,4,3,2,2,3,9,9.0,neutral or dissatisfied +75038,87995,Female,Loyal Customer,53,Business travel,Business,404,2,2,2,2,3,5,5,2,2,2,2,5,2,3,25,20.0,satisfied +75039,85528,Female,disloyal Customer,37,Business travel,Business,259,2,2,2,3,5,2,5,5,3,3,4,3,3,5,128,125.0,neutral or dissatisfied +75040,104219,Male,Loyal Customer,17,Business travel,Business,1961,1,3,5,3,1,1,1,1,4,3,4,3,4,1,14,3.0,neutral or dissatisfied +75041,93802,Male,Loyal Customer,36,Personal Travel,Eco,1259,2,4,2,4,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +75042,106521,Male,Loyal Customer,37,Business travel,Business,271,3,3,2,3,4,1,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +75043,122118,Female,Loyal Customer,59,Business travel,Business,130,0,4,0,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +75044,3298,Male,Loyal Customer,25,Personal Travel,Eco,419,2,1,0,3,2,0,2,2,1,3,3,3,3,2,49,59.0,neutral or dissatisfied +75045,101049,Male,Loyal Customer,54,Business travel,Business,368,4,4,4,4,3,4,5,4,4,5,4,4,4,3,0,,satisfied +75046,23542,Male,Loyal Customer,60,Personal Travel,Eco,423,1,2,1,4,2,1,2,2,3,3,4,1,3,2,44,44.0,neutral or dissatisfied +75047,117147,Male,Loyal Customer,30,Personal Travel,Eco,647,2,4,2,1,2,2,2,2,4,1,2,5,3,2,15,0.0,neutral or dissatisfied +75048,72898,Female,Loyal Customer,56,Business travel,Business,1096,1,1,1,1,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +75049,71120,Female,Loyal Customer,52,Business travel,Business,1739,4,4,4,4,5,5,4,5,5,4,5,3,5,4,35,39.0,satisfied +75050,16582,Female,Loyal Customer,30,Personal Travel,Eco,1092,2,4,2,1,3,2,3,3,5,4,5,1,3,3,66,61.0,neutral or dissatisfied +75051,5471,Female,Loyal Customer,33,Personal Travel,Eco,265,2,5,0,4,0,1,1,3,4,5,4,1,5,1,389,378.0,neutral or dissatisfied +75052,56745,Female,Loyal Customer,44,Personal Travel,Eco,997,2,4,2,1,3,2,3,5,5,2,5,2,5,5,25,62.0,neutral or dissatisfied +75053,71716,Male,Loyal Customer,17,Business travel,Business,1642,2,2,2,2,2,3,2,2,3,5,5,4,5,2,33,29.0,satisfied +75054,64579,Female,Loyal Customer,55,Business travel,Business,1687,4,4,4,4,5,5,5,5,5,5,5,5,5,5,21,10.0,satisfied +75055,24422,Male,Loyal Customer,26,Business travel,Eco,634,4,3,3,3,4,4,1,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +75056,48230,Female,Loyal Customer,13,Personal Travel,Eco,236,2,4,2,4,5,2,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +75057,114183,Male,disloyal Customer,25,Business travel,Business,853,5,5,5,4,5,5,5,5,3,3,4,3,4,5,12,1.0,satisfied +75058,50504,Female,Loyal Customer,33,Personal Travel,Eco,262,4,5,4,2,2,4,2,2,1,3,2,2,3,2,0,0.0,satisfied +75059,79557,Male,Loyal Customer,53,Business travel,Business,1855,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +75060,70833,Male,Loyal Customer,60,Business travel,Business,761,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +75061,39298,Female,Loyal Customer,49,Personal Travel,Eco,268,1,2,0,4,3,3,3,2,2,0,2,3,2,2,0,0.0,neutral or dissatisfied +75062,32226,Male,Loyal Customer,50,Business travel,Eco,102,4,3,3,3,4,4,4,4,5,2,3,2,2,4,0,0.0,satisfied +75063,58980,Female,disloyal Customer,35,Business travel,Business,1846,1,1,1,5,4,1,4,4,3,3,4,3,5,4,63,49.0,neutral or dissatisfied +75064,101773,Female,Loyal Customer,48,Business travel,Business,1521,1,1,1,1,3,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +75065,121211,Male,Loyal Customer,56,Business travel,Business,2075,2,4,1,4,1,1,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +75066,109998,Female,Loyal Customer,44,Personal Travel,Business,1142,3,5,3,3,4,4,3,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +75067,23816,Female,Loyal Customer,28,Personal Travel,Eco,374,1,1,2,4,5,2,5,5,2,3,4,4,3,5,48,35.0,neutral or dissatisfied +75068,111015,Male,Loyal Customer,49,Business travel,Business,2645,4,4,4,4,3,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +75069,71325,Female,disloyal Customer,22,Business travel,Eco,1514,3,2,2,4,2,3,3,2,3,5,5,4,4,2,7,1.0,satisfied +75070,47560,Female,Loyal Customer,47,Personal Travel,Eco Plus,584,0,4,0,3,5,4,5,2,2,4,3,4,2,3,0,0.0,satisfied +75071,82485,Female,Loyal Customer,25,Personal Travel,Eco Plus,509,3,4,3,3,1,3,1,1,1,4,5,4,1,1,0,0.0,neutral or dissatisfied +75072,12496,Male,Loyal Customer,65,Business travel,Eco Plus,253,1,1,1,1,1,1,1,1,4,3,1,3,2,1,43,39.0,neutral or dissatisfied +75073,82214,Female,Loyal Customer,55,Business travel,Business,3335,4,4,4,4,2,5,4,4,4,4,4,4,4,3,18,44.0,satisfied +75074,44611,Female,Loyal Customer,53,Business travel,Eco,508,3,3,3,3,3,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +75075,107347,Female,Loyal Customer,51,Business travel,Business,2985,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +75076,32178,Female,Loyal Customer,53,Business travel,Business,216,5,5,4,5,3,3,3,4,4,4,4,1,4,2,13,24.0,satisfied +75077,50559,Female,Loyal Customer,40,Personal Travel,Eco,89,4,4,4,4,2,4,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +75078,16045,Male,Loyal Customer,45,Business travel,Eco,972,4,1,1,1,4,4,4,4,2,3,2,5,1,4,9,7.0,satisfied +75079,92271,Female,Loyal Customer,43,Business travel,Business,1900,1,1,2,1,4,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +75080,46947,Female,Loyal Customer,11,Personal Travel,Eco,833,3,1,3,3,1,3,1,1,1,1,3,3,2,1,0,0.0,neutral or dissatisfied +75081,18095,Female,Loyal Customer,35,Business travel,Eco Plus,605,5,4,4,4,5,5,5,5,2,4,1,3,5,5,0,0.0,satisfied +75082,26379,Male,Loyal Customer,52,Personal Travel,Eco,828,3,3,2,2,5,2,2,5,4,3,2,4,3,5,0,0.0,neutral or dissatisfied +75083,62807,Female,Loyal Customer,33,Personal Travel,Eco,2338,0,1,1,2,2,1,2,2,3,5,3,4,2,2,0,0.0,satisfied +75084,99968,Female,Loyal Customer,18,Business travel,Business,888,2,2,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +75085,85892,Male,Loyal Customer,41,Business travel,Business,3040,2,2,2,2,3,5,5,4,4,4,4,3,4,5,20,15.0,satisfied +75086,36330,Male,Loyal Customer,30,Business travel,Business,395,1,2,2,2,1,1,1,1,4,5,4,1,4,1,0,0.0,neutral or dissatisfied +75087,28246,Female,Loyal Customer,19,Personal Travel,Eco,1009,3,5,3,1,1,3,2,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +75088,24397,Male,Loyal Customer,20,Personal Travel,Eco Plus,669,3,4,3,3,4,3,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +75089,32980,Female,Loyal Customer,47,Personal Travel,Eco,102,4,5,4,3,5,4,4,1,1,4,1,4,1,5,0,2.0,neutral or dissatisfied +75090,7150,Male,Loyal Customer,35,Business travel,Business,116,3,3,3,3,2,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +75091,116354,Male,Loyal Customer,18,Personal Travel,Eco,446,3,5,3,3,3,3,2,3,4,5,5,3,4,3,29,24.0,neutral or dissatisfied +75092,78097,Female,Loyal Customer,59,Business travel,Eco,684,2,4,4,4,3,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +75093,11446,Male,Loyal Customer,27,Business travel,Eco Plus,316,3,5,5,5,3,3,3,3,1,5,4,3,3,3,0,5.0,neutral or dissatisfied +75094,100144,Male,Loyal Customer,44,Business travel,Business,3719,3,3,2,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +75095,7665,Female,Loyal Customer,43,Business travel,Business,3952,4,4,4,4,4,4,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +75096,65863,Female,Loyal Customer,41,Personal Travel,Eco,1389,3,5,3,2,3,3,3,3,3,1,5,3,4,3,12,0.0,neutral or dissatisfied +75097,21176,Male,Loyal Customer,25,Personal Travel,Business,192,1,5,0,4,3,0,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +75098,125460,Female,Loyal Customer,51,Business travel,Business,2917,3,5,1,1,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +75099,44857,Male,Loyal Customer,33,Business travel,Business,693,5,5,5,5,4,4,4,4,4,2,5,2,3,4,11,15.0,satisfied +75100,121677,Female,Loyal Customer,67,Personal Travel,Eco,328,1,1,1,3,4,3,3,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +75101,93409,Male,Loyal Customer,21,Business travel,Business,697,4,4,4,4,4,4,4,4,3,4,4,5,4,4,0,0.0,satisfied +75102,53225,Male,Loyal Customer,62,Personal Travel,Eco,589,4,4,4,2,2,4,2,2,5,5,4,3,4,2,16,0.0,satisfied +75103,109127,Male,Loyal Customer,32,Business travel,Business,3183,4,4,4,4,3,4,3,3,4,5,5,5,5,3,0,0.0,satisfied +75104,116601,Female,Loyal Customer,52,Business travel,Business,2831,2,2,2,2,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +75105,38640,Female,Loyal Customer,37,Business travel,Eco,2611,5,3,3,3,5,5,5,5,4,1,5,4,3,5,0,0.0,satisfied +75106,121313,Male,disloyal Customer,21,Business travel,Eco,1009,4,4,4,3,1,4,3,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +75107,70685,Male,Loyal Customer,11,Personal Travel,Eco,447,2,5,2,1,2,2,2,2,4,5,4,5,5,2,0,4.0,neutral or dissatisfied +75108,5064,Male,Loyal Customer,33,Business travel,Business,3364,4,3,3,3,1,1,4,1,3,4,3,2,3,1,43,38.0,neutral or dissatisfied +75109,59969,Male,Loyal Customer,45,Business travel,Eco,537,5,5,4,4,5,5,5,5,1,4,2,1,5,5,0,0.0,satisfied +75110,100792,Male,disloyal Customer,15,Business travel,Eco,748,3,3,3,4,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +75111,22774,Male,Loyal Customer,53,Business travel,Business,147,1,1,1,1,1,5,3,5,5,5,5,2,5,1,21,23.0,satisfied +75112,24624,Female,Loyal Customer,77,Business travel,Business,3259,4,2,2,2,3,4,4,3,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +75113,126582,Male,Loyal Customer,47,Business travel,Business,1337,4,4,4,4,4,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +75114,74081,Female,Loyal Customer,39,Business travel,Business,2562,3,3,3,3,2,4,5,5,5,5,5,4,5,3,13,24.0,satisfied +75115,86267,Male,Loyal Customer,51,Personal Travel,Eco,356,3,4,3,2,2,3,4,2,4,5,4,3,4,2,0,2.0,neutral or dissatisfied +75116,118610,Male,disloyal Customer,23,Business travel,Eco,304,4,3,3,3,5,3,2,5,1,2,4,1,3,5,2,2.0,neutral or dissatisfied +75117,103233,Female,Loyal Customer,42,Business travel,Business,1935,3,3,3,3,4,4,4,4,4,5,4,5,4,5,6,0.0,satisfied +75118,60741,Female,Loyal Customer,44,Business travel,Business,3268,1,1,1,1,5,4,4,4,4,4,4,3,4,5,2,0.0,satisfied +75119,72705,Female,Loyal Customer,49,Business travel,Business,2432,4,4,4,4,4,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +75120,85130,Female,Loyal Customer,53,Business travel,Business,731,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +75121,89425,Female,Loyal Customer,71,Business travel,Business,3067,2,2,2,2,5,2,2,1,1,1,2,3,1,3,0,0.0,neutral or dissatisfied +75122,89755,Female,Loyal Customer,20,Personal Travel,Eco,1035,2,5,2,4,2,2,2,2,3,4,4,5,5,2,82,62.0,neutral or dissatisfied +75123,741,Male,disloyal Customer,39,Business travel,Business,158,1,1,1,4,4,1,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +75124,10377,Male,disloyal Customer,24,Business travel,Business,429,4,0,4,2,5,4,5,5,3,5,4,5,5,5,0,0.0,satisfied +75125,55202,Female,Loyal Customer,22,Personal Travel,Eco Plus,1635,1,1,1,4,2,1,2,2,4,1,2,2,3,2,0,0.0,neutral or dissatisfied +75126,109903,Female,Loyal Customer,60,Business travel,Eco,1073,1,4,4,4,4,3,4,1,1,1,1,3,1,2,3,0.0,neutral or dissatisfied +75127,94483,Male,Loyal Customer,18,Business travel,Business,2634,5,5,2,5,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +75128,16587,Female,Loyal Customer,49,Personal Travel,Eco,1092,3,3,3,2,3,3,3,5,3,5,4,3,2,3,116,135.0,neutral or dissatisfied +75129,97334,Female,Loyal Customer,20,Business travel,Eco,872,2,1,3,1,2,2,3,2,4,4,4,2,3,2,0,0.0,neutral or dissatisfied +75130,4582,Male,disloyal Customer,40,Business travel,Business,416,2,2,2,2,1,2,1,1,5,2,4,5,4,1,5,0.0,neutral or dissatisfied +75131,92682,Male,Loyal Customer,49,Business travel,Business,2992,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +75132,35768,Male,Loyal Customer,51,Business travel,Business,2178,5,5,5,5,3,1,4,4,4,4,5,2,4,1,33,13.0,satisfied +75133,64219,Female,Loyal Customer,47,Personal Travel,Business,1660,1,0,1,3,3,5,4,2,2,1,2,5,2,4,16,0.0,neutral or dissatisfied +75134,79626,Female,Loyal Customer,59,Business travel,Business,712,5,5,5,5,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +75135,106408,Female,Loyal Customer,12,Personal Travel,Eco,551,3,2,3,4,2,3,4,2,4,1,4,3,3,2,77,75.0,neutral or dissatisfied +75136,42119,Female,Loyal Customer,56,Business travel,Business,3153,3,4,4,4,1,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +75137,6559,Male,Loyal Customer,31,Business travel,Eco,528,3,5,5,5,3,3,3,3,3,1,3,1,3,3,32,18.0,neutral or dissatisfied +75138,45551,Female,Loyal Customer,24,Business travel,Eco Plus,508,5,3,2,2,5,5,3,5,1,2,4,2,1,5,0,3.0,satisfied +75139,37886,Female,Loyal Customer,58,Business travel,Eco,1065,2,3,3,3,4,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +75140,109231,Male,Loyal Customer,31,Personal Travel,Eco,612,5,4,5,3,1,5,1,1,1,2,3,2,2,1,14,0.0,satisfied +75141,64342,Male,Loyal Customer,34,Business travel,Business,1192,1,1,1,1,2,5,5,4,4,5,4,4,4,5,109,101.0,satisfied +75142,41244,Female,Loyal Customer,18,Business travel,Business,643,5,5,5,5,4,4,4,4,1,2,3,1,3,4,0,8.0,satisfied +75143,110479,Male,Loyal Customer,49,Personal Travel,Eco,842,4,1,4,3,5,4,5,5,3,2,4,4,3,5,0,0.0,satisfied +75144,68087,Male,Loyal Customer,51,Business travel,Business,3542,5,5,5,5,5,5,5,4,4,4,4,5,4,5,49,54.0,satisfied +75145,113286,Female,Loyal Customer,60,Business travel,Business,2236,5,5,5,5,3,4,4,5,5,5,5,4,5,5,1,6.0,satisfied +75146,23315,Female,Loyal Customer,43,Business travel,Business,456,4,3,3,3,4,3,3,4,4,4,4,4,4,3,19,15.0,neutral or dissatisfied +75147,1656,Female,Loyal Customer,42,Business travel,Business,551,2,2,2,2,3,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +75148,85390,Female,Loyal Customer,34,Business travel,Business,2237,1,1,1,1,3,5,4,4,4,4,5,3,4,5,1,4.0,satisfied +75149,35525,Female,Loyal Customer,65,Personal Travel,Eco,1028,4,4,4,3,5,4,5,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +75150,75573,Male,Loyal Customer,48,Business travel,Business,1522,3,3,3,3,5,4,5,4,4,4,4,4,4,4,49,43.0,satisfied +75151,89094,Male,disloyal Customer,28,Business travel,Eco,1947,3,4,4,3,2,3,2,2,2,1,3,2,4,2,4,0.0,neutral or dissatisfied +75152,43596,Female,Loyal Customer,40,Business travel,Business,252,4,4,4,4,1,5,2,3,3,4,3,4,3,4,0,0.0,satisfied +75153,108657,Female,disloyal Customer,24,Business travel,Eco,1123,3,3,3,4,5,3,5,5,1,2,3,3,3,5,14,17.0,neutral or dissatisfied +75154,38582,Female,Loyal Customer,52,Business travel,Eco Plus,2586,2,4,4,4,2,1,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +75155,34908,Female,Loyal Customer,33,Business travel,Business,1769,3,3,3,3,5,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +75156,4641,Male,Loyal Customer,52,Business travel,Business,3458,1,1,1,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +75157,31690,Male,Loyal Customer,38,Business travel,Business,446,5,5,5,5,2,1,2,4,4,4,4,1,4,4,0,0.0,satisfied +75158,123747,Female,Loyal Customer,8,Personal Travel,Eco,96,1,5,1,4,5,1,2,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +75159,82265,Female,disloyal Customer,26,Business travel,Business,1481,4,5,5,4,2,5,2,2,3,5,5,4,4,2,3,0.0,neutral or dissatisfied +75160,96102,Female,Loyal Customer,61,Personal Travel,Eco,795,2,5,1,2,4,5,4,3,3,1,3,3,3,4,30,11.0,neutral or dissatisfied +75161,110497,Female,Loyal Customer,55,Business travel,Business,1966,1,1,1,1,3,4,5,2,2,2,2,5,2,3,4,0.0,satisfied +75162,81322,Female,Loyal Customer,29,Business travel,Business,2232,2,2,2,2,5,5,5,5,3,2,5,4,4,5,5,14.0,satisfied +75163,40772,Male,disloyal Customer,11,Business travel,Eco,501,4,1,4,3,5,4,2,5,3,3,4,3,4,5,6,7.0,neutral or dissatisfied +75164,11719,Female,Loyal Customer,37,Business travel,Business,395,3,2,2,2,5,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +75165,5822,Female,Loyal Customer,34,Personal Travel,Eco,273,4,1,4,3,3,4,2,3,4,2,3,2,3,3,35,47.0,neutral or dissatisfied +75166,40525,Female,Loyal Customer,27,Personal Travel,Eco Plus,175,4,5,4,5,4,4,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +75167,679,Male,Loyal Customer,42,Business travel,Business,3640,1,1,4,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +75168,112353,Male,Loyal Customer,46,Business travel,Business,3301,3,3,3,3,2,4,4,5,5,5,5,4,5,3,8,1.0,satisfied +75169,102459,Male,Loyal Customer,45,Personal Travel,Eco,258,2,3,2,2,4,2,4,4,4,1,3,1,3,4,17,10.0,neutral or dissatisfied +75170,43693,Female,disloyal Customer,29,Business travel,Eco,196,3,5,3,3,5,3,5,5,1,3,4,4,2,5,0,0.0,neutral or dissatisfied +75171,57501,Female,Loyal Customer,36,Business travel,Business,675,3,2,2,2,5,3,3,3,3,2,3,1,3,1,0,7.0,neutral or dissatisfied +75172,110111,Female,Loyal Customer,40,Business travel,Business,869,5,5,5,5,4,4,5,4,4,4,4,5,4,3,19,13.0,satisfied +75173,26716,Female,Loyal Customer,46,Personal Travel,Eco,515,3,5,3,2,2,4,5,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +75174,104814,Female,Loyal Customer,63,Personal Travel,Eco,587,1,5,1,3,4,4,4,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +75175,43773,Female,disloyal Customer,36,Business travel,Eco,146,4,2,4,4,5,4,5,5,2,4,3,4,4,5,52,51.0,neutral or dissatisfied +75176,39035,Female,Loyal Customer,63,Personal Travel,Eco,113,4,4,4,3,1,2,3,3,3,4,5,3,3,4,0,0.0,satisfied +75177,66308,Female,disloyal Customer,24,Business travel,Eco,852,1,1,1,2,2,1,2,2,3,5,2,4,3,2,29,20.0,neutral or dissatisfied +75178,3988,Female,Loyal Customer,50,Business travel,Business,3511,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +75179,73055,Male,Loyal Customer,30,Business travel,Eco Plus,1089,3,1,1,1,3,3,3,3,3,3,3,3,3,3,14,21.0,neutral or dissatisfied +75180,121623,Female,Loyal Customer,37,Personal Travel,Eco,936,2,3,2,3,5,2,5,5,2,1,4,4,4,5,1,0.0,neutral or dissatisfied +75181,6176,Male,Loyal Customer,33,Personal Travel,Eco,409,3,5,3,5,2,3,2,2,5,2,4,5,5,2,18,12.0,neutral or dissatisfied +75182,52515,Female,Loyal Customer,53,Business travel,Eco,119,5,5,5,5,2,4,2,5,5,5,5,1,5,4,0,0.0,satisfied +75183,82154,Female,Loyal Customer,50,Business travel,Business,311,1,1,1,1,2,4,5,4,4,4,4,4,4,3,31,29.0,satisfied +75184,40024,Male,Loyal Customer,52,Business travel,Business,125,4,3,3,3,4,3,4,2,2,2,4,2,2,4,0,96.0,neutral or dissatisfied +75185,68082,Female,disloyal Customer,10,Business travel,Eco,868,1,0,0,4,5,0,5,5,4,3,4,3,4,5,24,16.0,neutral or dissatisfied +75186,18304,Female,Loyal Customer,42,Business travel,Business,813,2,2,2,2,4,3,2,5,5,5,5,3,5,5,0,0.0,satisfied +75187,113392,Female,disloyal Customer,20,Business travel,Eco,488,2,5,2,1,3,2,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +75188,55901,Male,disloyal Customer,25,Business travel,Eco,733,3,3,3,3,4,3,4,4,4,5,4,4,4,4,10,17.0,neutral or dissatisfied +75189,47389,Female,Loyal Customer,59,Business travel,Business,1898,4,1,1,1,5,4,4,4,4,4,4,4,4,2,37,28.0,neutral or dissatisfied +75190,52140,Male,Loyal Customer,28,Business travel,Business,1784,4,4,4,4,4,4,4,4,4,4,4,4,5,4,18,14.0,satisfied +75191,75584,Female,Loyal Customer,40,Business travel,Business,2970,0,0,0,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +75192,115659,Male,disloyal Customer,17,Business travel,Eco,362,3,4,3,3,5,3,5,5,2,5,4,2,3,5,14,20.0,neutral or dissatisfied +75193,66433,Female,Loyal Customer,56,Business travel,Business,1217,2,2,4,2,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +75194,84731,Female,Loyal Customer,54,Business travel,Business,516,4,4,1,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +75195,51997,Male,disloyal Customer,23,Business travel,Business,1119,3,4,3,3,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +75196,47936,Male,Loyal Customer,35,Personal Travel,Eco,550,3,3,3,3,5,3,5,5,3,4,4,3,4,5,9,0.0,neutral or dissatisfied +75197,89861,Male,disloyal Customer,28,Business travel,Business,1174,5,5,5,4,3,5,3,3,4,3,5,3,4,3,15,0.0,satisfied +75198,19350,Female,Loyal Customer,42,Business travel,Business,1882,5,5,5,5,4,1,3,4,4,4,4,3,4,1,76,66.0,satisfied +75199,25946,Female,Loyal Customer,46,Business travel,Business,1583,1,1,1,1,3,4,4,4,4,4,4,5,4,5,12,0.0,satisfied +75200,80342,Female,Loyal Customer,37,Personal Travel,Eco,952,2,3,2,4,3,2,4,3,2,4,3,5,4,3,1,0.0,neutral or dissatisfied +75201,69630,Female,Loyal Customer,42,Business travel,Business,569,2,2,2,2,2,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +75202,78157,Male,disloyal Customer,40,Business travel,Business,192,3,2,2,1,3,2,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +75203,25007,Female,disloyal Customer,51,Business travel,Eco Plus,484,5,5,5,3,1,5,1,1,3,4,5,3,3,1,0,0.0,satisfied +75204,4943,Female,Loyal Customer,48,Personal Travel,Eco,268,2,2,2,3,4,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +75205,15910,Male,Loyal Customer,52,Business travel,Eco,607,5,2,2,2,5,5,5,5,4,5,4,1,3,5,25,43.0,satisfied +75206,70908,Female,Loyal Customer,44,Personal Travel,Eco,1721,2,4,1,5,5,5,5,2,2,1,2,5,2,5,39,22.0,neutral or dissatisfied +75207,14346,Male,Loyal Customer,9,Personal Travel,Eco,429,2,3,5,4,5,5,5,5,2,3,3,1,2,5,0,0.0,neutral or dissatisfied +75208,105276,Male,Loyal Customer,28,Business travel,Business,738,4,4,4,4,5,5,5,5,5,5,5,5,4,5,11,17.0,satisfied +75209,4717,Male,Loyal Customer,44,Business travel,Business,1646,3,3,3,3,4,4,5,4,4,4,4,5,4,5,68,80.0,satisfied +75210,53912,Female,Loyal Customer,23,Personal Travel,Eco,140,1,1,1,3,1,3,3,2,5,4,4,3,1,3,236,239.0,neutral or dissatisfied +75211,118375,Female,Loyal Customer,39,Business travel,Business,1987,5,5,5,5,4,5,5,5,5,5,5,3,5,4,45,43.0,satisfied +75212,117237,Female,Loyal Customer,8,Personal Travel,Eco,304,1,4,1,5,1,1,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +75213,26367,Female,Loyal Customer,37,Business travel,Business,3603,2,2,2,2,2,3,4,5,5,5,5,1,5,1,4,12.0,satisfied +75214,70917,Male,Loyal Customer,40,Business travel,Business,612,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +75215,69251,Male,Loyal Customer,28,Business travel,Business,2479,2,3,3,3,2,2,2,2,2,1,4,3,4,2,0,0.0,neutral or dissatisfied +75216,64038,Female,disloyal Customer,28,Business travel,Business,919,2,2,2,2,4,2,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +75217,8640,Male,Loyal Customer,35,Business travel,Business,2108,0,4,0,3,3,4,5,5,5,5,2,5,5,3,2,0.0,satisfied +75218,87060,Male,Loyal Customer,44,Business travel,Business,594,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,3.0,satisfied +75219,42670,Female,Loyal Customer,38,Business travel,Eco,604,4,2,2,2,4,4,4,4,3,3,2,2,1,4,0,0.0,satisfied +75220,64690,Male,Loyal Customer,46,Business travel,Business,469,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +75221,72843,Male,Loyal Customer,54,Business travel,Business,1013,1,1,1,1,3,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +75222,29359,Female,Loyal Customer,44,Business travel,Eco,2409,4,3,3,3,5,3,2,3,3,4,3,5,3,5,5,1.0,satisfied +75223,110275,Female,Loyal Customer,31,Personal Travel,Business,787,0,1,0,3,2,0,2,2,4,2,3,3,3,2,10,0.0,satisfied +75224,59815,Male,Loyal Customer,64,Personal Travel,Business,997,3,3,4,4,4,3,3,4,4,4,4,1,4,4,60,47.0,neutral or dissatisfied +75225,4071,Male,Loyal Customer,34,Business travel,Eco Plus,483,3,3,3,3,3,2,3,3,4,4,4,3,4,3,56,41.0,neutral or dissatisfied +75226,91451,Male,disloyal Customer,24,Business travel,Eco,859,3,3,3,3,1,3,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +75227,52199,Female,Loyal Customer,37,Business travel,Business,1583,2,2,2,2,2,2,5,4,4,4,4,2,4,3,0,0.0,satisfied +75228,39852,Female,disloyal Customer,30,Business travel,Eco,272,3,0,3,4,3,3,4,3,3,5,3,4,4,3,0,10.0,neutral or dissatisfied +75229,124754,Female,Loyal Customer,60,Personal Travel,Business,280,4,4,4,1,1,2,3,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +75230,9527,Female,Loyal Customer,48,Business travel,Business,2738,0,0,0,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +75231,39765,Male,Loyal Customer,53,Business travel,Business,3602,4,4,4,4,5,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +75232,25773,Female,Loyal Customer,26,Business travel,Business,3607,5,5,5,5,2,2,2,2,3,5,3,4,1,2,4,0.0,satisfied +75233,1826,Female,Loyal Customer,43,Business travel,Eco,408,5,4,4,4,1,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +75234,25316,Male,Loyal Customer,65,Personal Travel,Eco,432,2,4,2,3,2,2,2,2,4,5,4,3,2,2,2,0.0,neutral or dissatisfied +75235,48409,Male,Loyal Customer,46,Business travel,Business,2920,1,1,1,1,5,3,3,1,1,1,1,3,1,1,0,8.0,neutral or dissatisfied +75236,22070,Male,Loyal Customer,45,Personal Travel,Eco,304,2,5,2,4,3,2,2,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +75237,103048,Male,disloyal Customer,8,Business travel,Eco,490,4,4,4,3,5,4,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +75238,114328,Male,Loyal Customer,37,Personal Travel,Eco,862,3,5,3,1,5,3,5,5,5,2,4,3,4,5,21,24.0,neutral or dissatisfied +75239,4274,Male,Loyal Customer,43,Business travel,Business,502,1,1,1,1,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +75240,114301,Male,Loyal Customer,27,Personal Travel,Eco,862,2,3,1,1,2,1,2,2,2,5,5,3,1,2,46,38.0,neutral or dissatisfied +75241,44596,Male,Loyal Customer,36,Personal Travel,Eco Plus,177,2,5,0,2,4,0,4,4,3,5,4,5,4,4,17,20.0,neutral or dissatisfied +75242,112078,Female,Loyal Customer,24,Business travel,Business,1491,2,2,4,2,2,2,2,2,3,1,4,1,4,2,15,13.0,neutral or dissatisfied +75243,102161,Female,disloyal Customer,42,Business travel,Business,258,3,3,3,4,5,3,5,5,4,4,5,3,5,5,12,9.0,neutral or dissatisfied +75244,61025,Male,Loyal Customer,55,Personal Travel,Eco,3302,2,3,3,3,3,5,3,4,5,5,2,3,1,3,0,0.0,neutral or dissatisfied +75245,89607,Male,disloyal Customer,44,Business travel,Business,1096,4,5,5,4,4,3,3,4,4,5,5,3,4,3,173,160.0,satisfied +75246,18492,Male,disloyal Customer,20,Business travel,Eco,190,3,4,3,3,5,3,5,5,4,2,4,3,2,5,0,0.0,neutral or dissatisfied +75247,15469,Male,Loyal Customer,21,Personal Travel,Eco,331,2,5,2,2,2,2,2,2,2,4,5,2,5,2,34,29.0,neutral or dissatisfied +75248,30991,Female,Loyal Customer,34,Business travel,Business,391,2,2,2,2,5,1,5,4,4,3,4,3,4,4,30,38.0,satisfied +75249,89749,Male,Loyal Customer,59,Personal Travel,Eco,944,2,4,2,4,3,2,3,3,2,1,3,3,4,3,0,0.0,neutral or dissatisfied +75250,105996,Female,Loyal Customer,22,Business travel,Business,1999,3,3,3,3,4,4,4,4,4,5,4,4,4,4,63,43.0,satisfied +75251,71585,Female,Loyal Customer,24,Business travel,Business,1197,1,0,0,2,3,0,4,3,4,5,2,1,2,3,0,0.0,neutral or dissatisfied +75252,59604,Female,Loyal Customer,20,Business travel,Eco,965,2,4,4,4,2,2,2,2,4,1,3,2,4,2,0,0.0,neutral or dissatisfied +75253,70404,Female,Loyal Customer,9,Personal Travel,Eco,1562,3,4,3,3,3,3,3,3,3,4,5,4,4,3,1,26.0,neutral or dissatisfied +75254,42342,Female,Loyal Customer,57,Personal Travel,Eco,817,1,4,2,4,5,4,4,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +75255,98266,Male,Loyal Customer,25,Business travel,Business,3969,5,5,5,5,3,4,3,3,4,2,5,5,4,3,4,0.0,satisfied +75256,122738,Male,disloyal Customer,30,Business travel,Business,651,2,2,2,1,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +75257,99764,Female,Loyal Customer,45,Personal Travel,Eco,255,4,4,4,1,4,3,5,3,3,4,3,3,3,5,0,0.0,satisfied +75258,9682,Female,disloyal Customer,29,Business travel,Business,212,1,1,1,3,1,1,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +75259,52647,Male,Loyal Customer,38,Personal Travel,Eco,119,2,1,2,3,1,2,1,1,3,4,4,1,4,1,0,0.0,neutral or dissatisfied +75260,83929,Female,Loyal Customer,41,Business travel,Business,321,3,5,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +75261,30410,Female,Loyal Customer,29,Business travel,Eco Plus,862,4,3,3,3,4,5,4,4,2,4,1,3,5,4,0,13.0,satisfied +75262,68191,Female,disloyal Customer,22,Business travel,Eco Plus,597,2,4,2,3,3,2,3,3,4,2,3,3,3,3,12,8.0,neutral or dissatisfied +75263,105854,Female,Loyal Customer,60,Business travel,Business,2481,4,4,4,4,3,5,4,4,4,4,4,4,4,3,25,17.0,satisfied +75264,115966,Male,Loyal Customer,22,Personal Travel,Eco,296,5,2,5,3,1,5,1,1,3,2,4,4,4,1,11,11.0,satisfied +75265,94406,Female,Loyal Customer,58,Business travel,Business,3040,1,1,1,1,4,4,5,4,4,5,5,4,4,4,38,22.0,satisfied +75266,42285,Male,Loyal Customer,23,Business travel,Business,550,1,1,1,1,5,5,5,5,5,3,3,1,1,5,98,92.0,satisfied +75267,91349,Female,Loyal Customer,37,Personal Travel,Eco Plus,594,1,5,1,1,1,1,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +75268,33336,Female,disloyal Customer,26,Business travel,Eco,2409,3,3,3,4,2,3,4,2,4,3,4,1,5,2,0,0.0,neutral or dissatisfied +75269,121870,Female,Loyal Customer,57,Business travel,Eco,449,1,5,4,4,3,4,4,1,1,1,1,2,1,2,9,10.0,neutral or dissatisfied +75270,45304,Female,disloyal Customer,21,Business travel,Eco,188,0,0,0,2,3,0,3,3,1,2,5,5,5,3,0,0.0,satisfied +75271,92498,Female,Loyal Customer,34,Business travel,Business,2116,5,5,5,5,5,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +75272,112358,Male,Loyal Customer,45,Business travel,Business,2301,5,3,5,5,3,5,5,5,5,5,5,4,5,3,22,3.0,satisfied +75273,1322,Male,Loyal Customer,33,Business travel,Business,2713,3,3,3,3,4,4,5,4,3,3,5,3,5,4,0,8.0,satisfied +75274,129573,Female,disloyal Customer,26,Business travel,Eco Plus,2583,2,2,2,4,2,2,5,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +75275,7089,Female,Loyal Customer,40,Business travel,Business,3293,4,4,4,4,4,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +75276,30911,Female,Loyal Customer,18,Business travel,Business,3417,4,4,4,4,4,5,4,4,2,3,2,4,1,4,21,15.0,satisfied +75277,60610,Female,disloyal Customer,27,Business travel,Business,991,2,2,2,3,3,2,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +75278,59818,Male,Loyal Customer,17,Personal Travel,Business,1085,1,5,2,3,4,2,4,4,3,1,5,5,1,4,5,0.0,neutral or dissatisfied +75279,55116,Female,Loyal Customer,56,Personal Travel,Eco,1303,3,4,3,2,5,4,4,2,2,3,2,5,2,5,2,0.0,neutral or dissatisfied +75280,49301,Female,Loyal Customer,43,Business travel,Eco,262,4,3,3,3,5,4,1,4,4,4,4,5,4,5,0,0.0,satisfied +75281,75296,Male,Loyal Customer,52,Personal Travel,Eco Plus,1744,2,4,2,4,3,2,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +75282,49247,Male,disloyal Customer,40,Business travel,Eco,77,2,0,2,5,3,2,4,3,3,5,2,5,5,3,52,77.0,neutral or dissatisfied +75283,104308,Female,Loyal Customer,57,Business travel,Business,2152,2,3,3,3,3,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +75284,104253,Female,Loyal Customer,38,Personal Travel,Eco,1276,3,5,3,2,2,3,2,2,4,1,5,3,1,2,0,0.0,neutral or dissatisfied +75285,79051,Female,Loyal Customer,28,Business travel,Business,164,5,5,5,5,5,4,5,5,5,4,4,5,4,5,10,7.0,satisfied +75286,17650,Male,disloyal Customer,27,Business travel,Eco,1008,4,4,4,3,2,4,5,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +75287,20133,Male,Loyal Customer,14,Personal Travel,Eco,416,3,3,3,1,2,3,2,2,4,5,1,3,4,2,23,23.0,neutral or dissatisfied +75288,53429,Female,Loyal Customer,53,Business travel,Eco,2358,4,4,4,4,1,3,1,4,4,4,4,3,4,5,1,0.0,satisfied +75289,60937,Male,Loyal Customer,40,Business travel,Business,888,1,1,2,1,2,4,4,4,4,4,4,5,4,5,13,0.0,satisfied +75290,15841,Female,Loyal Customer,51,Business travel,Business,888,2,2,2,2,2,1,2,5,5,5,5,3,5,1,0,0.0,satisfied +75291,27788,Male,Loyal Customer,62,Business travel,Business,1448,2,1,1,1,4,2,3,2,2,2,2,2,2,2,10,6.0,neutral or dissatisfied +75292,103415,Male,disloyal Customer,47,Business travel,Eco,237,1,0,1,3,3,1,3,3,4,1,2,2,3,3,0,0.0,neutral or dissatisfied +75293,6810,Male,Loyal Customer,57,Personal Travel,Eco,137,3,5,3,1,4,3,4,4,2,1,2,4,4,4,0,0.0,neutral or dissatisfied +75294,73544,Male,Loyal Customer,47,Personal Travel,Eco,594,2,1,2,3,5,2,5,5,3,5,3,4,2,5,0,0.0,neutral or dissatisfied +75295,30018,Female,Loyal Customer,62,Business travel,Business,3937,2,3,3,3,2,2,2,2,2,2,2,3,2,1,92,75.0,neutral or dissatisfied +75296,63798,Female,Loyal Customer,29,Personal Travel,Eco,1721,2,4,1,4,2,1,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +75297,55419,Female,Loyal Customer,51,Business travel,Business,2521,1,1,1,1,5,5,5,3,4,3,4,5,5,5,19,59.0,satisfied +75298,37948,Female,Loyal Customer,41,Personal Travel,Eco Plus,997,3,1,4,2,2,2,2,5,5,4,4,3,5,1,9,0.0,neutral or dissatisfied +75299,47705,Female,Loyal Customer,9,Personal Travel,Eco,1464,2,5,2,1,4,2,4,4,3,4,4,5,4,4,18,0.0,neutral or dissatisfied +75300,126499,Female,Loyal Customer,13,Personal Travel,Eco,1849,5,4,5,2,1,5,1,1,1,4,4,4,2,1,0,0.0,satisfied +75301,105416,Female,Loyal Customer,44,Business travel,Business,452,3,3,3,3,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +75302,39905,Male,disloyal Customer,22,Business travel,Business,272,5,3,5,5,4,5,4,4,3,2,4,4,3,4,0,2.0,satisfied +75303,14460,Female,Loyal Customer,66,Business travel,Business,1713,5,5,5,5,4,2,1,5,5,5,5,2,5,1,78,87.0,satisfied +75304,47493,Male,Loyal Customer,13,Personal Travel,Eco,590,2,5,2,3,1,2,1,1,4,3,5,3,4,1,104,85.0,neutral or dissatisfied +75305,83522,Male,Loyal Customer,32,Personal Travel,Eco,946,5,5,5,3,2,5,2,2,5,3,4,2,4,2,0,3.0,satisfied +75306,83324,Male,Loyal Customer,64,Personal Travel,Eco,1671,2,4,2,3,3,2,3,3,1,4,2,5,1,3,0,0.0,neutral or dissatisfied +75307,99607,Male,Loyal Customer,60,Business travel,Business,802,5,5,5,5,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +75308,85655,Female,Loyal Customer,32,Personal Travel,Eco Plus,259,2,5,2,5,3,2,1,3,5,5,1,5,1,3,0,0.0,neutral or dissatisfied +75309,21094,Male,Loyal Customer,51,Business travel,Business,3807,3,5,5,5,5,1,1,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +75310,95207,Male,Loyal Customer,65,Personal Travel,Eco,239,2,5,2,1,1,2,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +75311,119939,Male,Loyal Customer,54,Business travel,Business,3485,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +75312,43649,Male,disloyal Customer,20,Business travel,Eco,695,2,2,2,1,3,2,3,3,5,2,2,1,3,3,0,0.0,neutral or dissatisfied +75313,99635,Male,Loyal Customer,58,Business travel,Business,1085,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +75314,33155,Male,Loyal Customer,40,Personal Travel,Eco,101,1,2,1,3,4,1,4,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +75315,41367,Female,Loyal Customer,48,Business travel,Business,3583,4,4,2,4,4,1,2,2,2,2,2,5,2,2,0,27.0,satisfied +75316,4525,Male,Loyal Customer,55,Business travel,Business,677,4,4,4,4,2,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +75317,42598,Female,Loyal Customer,55,Business travel,Eco,866,4,5,3,5,4,4,1,3,3,4,3,2,3,1,0,3.0,satisfied +75318,3967,Male,Loyal Customer,12,Personal Travel,Eco,764,4,5,3,1,1,3,1,1,3,1,5,2,1,1,4,27.0,neutral or dissatisfied +75319,70926,Male,Loyal Customer,58,Business travel,Business,2279,2,2,2,2,3,5,4,4,4,4,4,3,4,4,36,16.0,satisfied +75320,54115,Male,Loyal Customer,10,Personal Travel,Business,1400,2,1,2,4,4,2,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +75321,28020,Male,Loyal Customer,29,Business travel,Business,3476,3,5,5,5,3,3,3,3,4,4,4,2,4,3,10,0.0,neutral or dissatisfied +75322,48617,Male,Loyal Customer,38,Business travel,Eco Plus,445,3,1,1,1,3,3,3,3,5,5,3,1,5,3,3,0.0,satisfied +75323,33185,Female,disloyal Customer,39,Business travel,Business,216,2,2,2,4,4,2,4,4,2,4,2,1,3,4,10,13.0,neutral or dissatisfied +75324,90296,Female,Loyal Customer,34,Personal Travel,Eco,757,2,5,2,3,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +75325,48748,Male,Loyal Customer,52,Business travel,Business,3176,0,4,0,5,4,4,4,3,3,3,1,4,3,4,13,8.0,satisfied +75326,82763,Male,Loyal Customer,43,Personal Travel,Eco,409,3,4,3,3,5,3,5,5,3,4,5,3,4,5,3,1.0,neutral or dissatisfied +75327,38263,Male,Loyal Customer,25,Business travel,Business,1111,4,5,5,5,4,4,4,4,3,2,4,4,3,4,20,17.0,neutral or dissatisfied +75328,127170,Male,Loyal Customer,56,Personal Travel,Eco,304,3,3,3,1,3,3,1,3,2,3,5,5,5,3,7,0.0,neutral or dissatisfied +75329,60722,Male,Loyal Customer,39,Personal Travel,Eco,1605,1,4,1,1,4,1,2,4,3,5,3,4,5,4,74,60.0,neutral or dissatisfied +75330,104021,Female,Loyal Customer,25,Business travel,Business,3439,3,3,3,3,4,4,4,4,3,2,4,3,4,4,2,0.0,satisfied +75331,111672,Male,Loyal Customer,54,Business travel,Eco,591,5,3,3,3,5,5,5,5,1,1,3,4,1,5,28,26.0,satisfied +75332,90754,Male,disloyal Customer,39,Business travel,Business,270,3,3,3,4,1,3,1,1,3,1,4,1,4,1,0,0.0,neutral or dissatisfied +75333,66029,Male,Loyal Customer,38,Business travel,Business,3394,5,5,5,5,5,4,5,5,5,5,5,3,5,4,0,4.0,satisfied +75334,20497,Male,disloyal Customer,26,Business travel,Eco,130,1,3,1,1,2,1,2,2,4,5,4,1,2,2,121,,neutral or dissatisfied +75335,79034,Female,Loyal Customer,37,Business travel,Business,3354,2,2,4,2,3,5,5,5,5,5,5,5,5,4,53,56.0,satisfied +75336,35409,Male,disloyal Customer,41,Business travel,Eco,628,2,4,2,3,5,2,5,5,2,3,3,2,4,5,0,11.0,neutral or dissatisfied +75337,114664,Male,Loyal Customer,44,Business travel,Business,2592,1,1,5,1,2,5,4,4,4,4,4,3,4,5,13,24.0,satisfied +75338,65169,Female,Loyal Customer,18,Personal Travel,Eco,190,4,4,0,4,5,0,5,5,2,3,3,1,4,5,0,0.0,satisfied +75339,41453,Female,Loyal Customer,54,Business travel,Business,1334,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +75340,57293,Male,Loyal Customer,8,Personal Travel,Eco Plus,804,4,2,4,3,5,4,5,5,3,2,3,2,4,5,0,0.0,satisfied +75341,102699,Female,Loyal Customer,44,Business travel,Business,2184,4,5,5,5,4,4,4,3,1,3,3,4,1,4,171,175.0,neutral or dissatisfied +75342,66307,Female,Loyal Customer,48,Business travel,Eco,852,1,4,4,4,2,3,3,1,1,1,1,2,1,2,5,12.0,neutral or dissatisfied +75343,117495,Male,disloyal Customer,22,Business travel,Eco,507,3,0,3,3,5,3,5,5,3,1,3,2,3,5,13,7.0,neutral or dissatisfied +75344,128192,Male,Loyal Customer,53,Personal Travel,Eco Plus,1972,5,1,5,3,1,1,1,1,2,1,1,1,3,1,3,0.0,satisfied +75345,31311,Female,Loyal Customer,43,Business travel,Eco,680,2,5,5,5,5,3,4,2,2,2,2,1,2,3,0,2.0,neutral or dissatisfied +75346,9398,Male,Loyal Customer,41,Personal Travel,Eco Plus,372,3,0,3,5,2,3,2,2,3,3,5,2,1,2,13,15.0,neutral or dissatisfied +75347,93768,Female,disloyal Customer,20,Business travel,Eco,368,0,0,0,1,3,0,3,3,4,2,5,3,4,3,20,15.0,satisfied +75348,35287,Female,Loyal Customer,25,Business travel,Business,1005,2,5,5,5,2,2,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +75349,120156,Male,disloyal Customer,26,Business travel,Eco,878,2,2,2,4,2,2,2,2,1,4,3,2,1,2,6,14.0,neutral or dissatisfied +75350,63529,Male,Loyal Customer,49,Business travel,Business,2046,4,4,3,4,4,4,5,4,4,4,4,4,4,3,11,0.0,satisfied +75351,71050,Female,Loyal Customer,38,Business travel,Eco,402,3,1,2,2,3,3,3,3,5,2,1,2,1,3,0,0.0,satisfied +75352,98493,Male,Loyal Customer,28,Business travel,Business,668,2,1,4,1,2,2,2,1,1,4,4,2,3,2,249,232.0,neutral or dissatisfied +75353,5358,Male,Loyal Customer,51,Business travel,Business,812,1,1,1,1,2,4,5,2,2,2,2,3,2,4,0,12.0,satisfied +75354,47026,Male,Loyal Customer,43,Business travel,Business,2997,5,5,5,5,4,3,4,5,5,5,5,3,5,2,0,0.0,satisfied +75355,50660,Male,Loyal Customer,69,Personal Travel,Eco,209,3,4,3,3,3,3,2,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +75356,94793,Male,Loyal Customer,57,Business travel,Business,192,3,2,2,2,4,4,4,4,4,4,3,2,4,2,0,0.0,neutral or dissatisfied +75357,38056,Female,Loyal Customer,31,Business travel,Business,3749,1,1,1,1,4,4,4,4,3,1,5,4,4,4,8,0.0,satisfied +75358,127216,Female,Loyal Customer,53,Personal Travel,Eco Plus,325,1,3,1,2,3,1,4,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +75359,89028,Male,Loyal Customer,27,Business travel,Business,2139,2,2,2,2,3,3,3,3,3,2,4,4,4,3,0,0.0,satisfied +75360,40537,Female,disloyal Customer,23,Business travel,Eco,391,5,3,5,1,5,3,2,5,5,3,5,5,4,5,0,0.0,satisfied +75361,63391,Female,Loyal Customer,10,Personal Travel,Eco,372,4,2,4,3,2,4,2,2,2,4,2,3,4,2,0,0.0,neutral or dissatisfied +75362,65227,Male,Loyal Customer,40,Business travel,Business,224,0,0,0,2,4,5,4,4,4,4,4,3,4,4,20,18.0,satisfied +75363,46167,Male,Loyal Customer,17,Personal Travel,Eco,604,0,5,0,2,3,0,3,3,4,5,4,3,4,3,0,0.0,satisfied +75364,41294,Female,Loyal Customer,15,Business travel,Business,2888,4,4,4,4,3,3,3,3,2,1,3,3,3,3,41,33.0,satisfied +75365,101361,Male,disloyal Customer,25,Business travel,Business,1148,0,0,0,2,4,0,4,4,5,5,5,4,4,4,6,0.0,satisfied +75366,48706,Male,disloyal Customer,36,Business travel,Business,308,2,2,2,5,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +75367,15487,Male,Loyal Customer,47,Personal Travel,Eco,164,2,4,2,2,4,2,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +75368,61747,Male,Loyal Customer,64,Business travel,Business,3667,1,4,4,4,4,4,4,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +75369,42308,Female,Loyal Customer,67,Personal Travel,Eco,315,4,5,4,2,4,5,4,2,2,4,2,2,2,1,0,0.0,neutral or dissatisfied +75370,117465,Male,Loyal Customer,42,Business travel,Business,507,2,2,2,2,5,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +75371,12803,Female,Loyal Customer,25,Business travel,Business,3709,4,4,4,4,4,4,4,4,2,3,5,1,5,4,8,11.0,satisfied +75372,115436,Female,Loyal Customer,21,Business travel,Business,1804,3,4,5,4,3,3,3,3,1,3,4,2,4,3,52,50.0,neutral or dissatisfied +75373,85329,Female,Loyal Customer,49,Business travel,Business,3876,4,4,4,4,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +75374,91533,Male,Loyal Customer,31,Business travel,Business,680,2,2,2,2,4,4,4,4,3,4,4,3,5,4,29,31.0,satisfied +75375,106410,Male,Loyal Customer,20,Personal Travel,Eco,551,2,3,2,3,2,2,2,2,4,4,3,1,2,2,9,3.0,neutral or dissatisfied +75376,112542,Female,Loyal Customer,59,Business travel,Business,2740,1,1,1,1,3,4,5,5,5,5,5,5,5,5,37,26.0,satisfied +75377,44944,Female,Loyal Customer,78,Business travel,Business,334,3,1,2,1,1,1,1,3,3,3,3,2,3,4,33,46.0,neutral or dissatisfied +75378,88485,Female,disloyal Customer,80,Business travel,Business,271,3,3,3,1,1,2,2,3,3,3,3,3,3,2,13,14.0,neutral or dissatisfied +75379,47210,Male,Loyal Customer,34,Personal Travel,Eco,954,4,3,4,5,1,4,1,1,4,2,1,4,1,1,0,0.0,neutral or dissatisfied +75380,84809,Female,Loyal Customer,13,Business travel,Eco,516,3,1,4,1,3,3,3,3,4,5,3,1,3,3,0,0.0,neutral or dissatisfied +75381,56635,Male,Loyal Customer,48,Business travel,Eco,1085,3,4,4,4,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +75382,38840,Male,Loyal Customer,44,Business travel,Eco Plus,387,2,4,4,4,2,2,2,2,5,3,3,5,2,2,0,0.0,satisfied +75383,107445,Female,Loyal Customer,40,Personal Travel,Eco,725,3,5,4,3,4,4,4,4,2,2,3,1,5,4,4,0.0,neutral or dissatisfied +75384,125211,Female,Loyal Customer,53,Business travel,Business,251,3,1,1,1,4,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +75385,44222,Male,Loyal Customer,33,Business travel,Business,3871,0,5,0,1,2,2,2,2,3,1,3,5,2,2,26,25.0,satisfied +75386,31001,Male,Loyal Customer,28,Business travel,Business,3581,5,5,5,5,5,5,5,5,5,4,3,2,1,5,6,1.0,satisfied +75387,70665,Male,Loyal Customer,43,Business travel,Business,3925,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +75388,275,Female,Loyal Customer,29,Business travel,Business,3044,3,5,3,3,4,5,4,4,3,4,5,3,4,4,0,0.0,satisfied +75389,3721,Male,Loyal Customer,16,Personal Travel,Eco,544,1,2,1,4,5,1,5,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +75390,68047,Male,Loyal Customer,40,Business travel,Business,868,5,5,5,5,4,4,5,2,2,2,2,5,2,4,32,105.0,satisfied +75391,101697,Female,Loyal Customer,32,Personal Travel,Eco,1500,4,2,4,2,1,4,1,1,2,5,3,1,2,1,0,0.0,neutral or dissatisfied +75392,26892,Male,Loyal Customer,48,Personal Travel,Eco,689,1,5,1,1,5,1,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +75393,124930,Male,Loyal Customer,41,Personal Travel,Eco,728,4,2,4,3,2,4,2,2,3,3,2,4,3,2,0,0.0,neutral or dissatisfied +75394,99151,Female,disloyal Customer,16,Business travel,Eco,986,3,3,3,5,5,3,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +75395,48640,Female,Loyal Customer,44,Business travel,Business,1760,1,1,1,1,4,4,4,5,3,5,4,4,3,4,121,135.0,satisfied +75396,13188,Male,Loyal Customer,28,Business travel,Business,1758,1,0,0,4,4,0,1,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +75397,112972,Male,Loyal Customer,32,Business travel,Business,1497,3,3,3,3,5,5,5,5,5,4,5,3,5,5,33,19.0,satisfied +75398,128359,Female,disloyal Customer,23,Business travel,Eco,325,4,5,4,3,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +75399,103534,Female,Loyal Customer,54,Business travel,Business,3838,4,4,3,4,2,4,4,4,4,4,4,3,4,3,0,29.0,satisfied +75400,89129,Male,disloyal Customer,20,Business travel,Eco,1238,4,4,4,4,4,4,4,4,4,2,3,3,4,4,0,0.0,satisfied +75401,99168,Male,Loyal Customer,19,Personal Travel,Eco,1076,2,5,3,5,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +75402,49755,Female,Loyal Customer,45,Business travel,Eco,86,1,2,2,2,1,3,4,2,2,1,2,3,2,1,104,96.0,neutral or dissatisfied +75403,8700,Male,Loyal Customer,61,Business travel,Business,3883,2,4,4,4,5,4,3,2,2,2,2,2,2,2,0,13.0,neutral or dissatisfied +75404,88326,Female,Loyal Customer,39,Business travel,Eco,404,2,3,3,3,2,1,2,2,4,2,4,3,4,2,28,51.0,neutral or dissatisfied +75405,76757,Female,Loyal Customer,44,Business travel,Business,146,2,1,3,1,5,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +75406,68201,Female,Loyal Customer,53,Personal Travel,Business,631,2,4,2,1,5,5,4,5,5,2,5,4,5,5,34,8.0,neutral or dissatisfied +75407,53096,Male,Loyal Customer,9,Personal Travel,Eco,224,3,3,3,4,3,3,3,3,2,5,4,3,4,3,1,22.0,neutral or dissatisfied +75408,45902,Male,disloyal Customer,17,Business travel,Eco,809,4,4,4,1,5,4,5,5,2,4,1,4,1,5,6,12.0,neutral or dissatisfied +75409,116918,Male,Loyal Customer,58,Business travel,Business,325,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +75410,38992,Male,Loyal Customer,42,Business travel,Eco,406,2,2,2,2,2,2,2,2,3,1,2,1,3,2,97,80.0,neutral or dissatisfied +75411,90392,Female,Loyal Customer,35,Personal Travel,Business,646,2,1,2,2,5,2,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +75412,11895,Male,Loyal Customer,58,Business travel,Business,744,3,3,3,3,3,4,5,4,4,4,4,4,4,4,5,12.0,satisfied +75413,88805,Female,Loyal Customer,60,Business travel,Business,3641,1,1,3,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +75414,11645,Male,disloyal Customer,26,Business travel,Eco,925,1,1,1,4,5,1,5,5,2,4,3,3,4,5,0,0.0,neutral or dissatisfied +75415,9187,Male,Loyal Customer,46,Business travel,Business,2852,3,3,4,3,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +75416,107863,Female,disloyal Customer,20,Business travel,Eco,228,3,0,3,2,2,3,2,2,3,4,4,3,4,2,12,0.0,neutral or dissatisfied +75417,110039,Female,Loyal Customer,44,Business travel,Business,2039,5,5,5,5,5,3,4,5,5,5,5,3,5,5,0,4.0,satisfied +75418,81722,Female,disloyal Customer,17,Business travel,Eco,1416,1,2,2,4,5,1,1,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +75419,36324,Male,Loyal Customer,63,Business travel,Business,3828,1,5,5,5,1,4,3,4,4,4,1,2,4,1,33,43.0,neutral or dissatisfied +75420,75030,Female,disloyal Customer,7,Personal Travel,Eco,236,3,4,0,4,4,0,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +75421,54302,Male,Loyal Customer,45,Personal Travel,Eco,1075,2,5,2,4,2,2,2,5,4,5,5,2,5,2,157,151.0,neutral or dissatisfied +75422,127247,Male,disloyal Customer,37,Business travel,Business,1107,3,3,3,4,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +75423,53985,Male,Loyal Customer,27,Business travel,Eco,1825,4,4,4,4,4,4,4,4,2,2,3,4,4,4,13,9.0,satisfied +75424,86661,Female,Loyal Customer,60,Personal Travel,Eco,746,2,5,2,1,2,4,4,3,3,2,3,5,3,5,1,0.0,neutral or dissatisfied +75425,44946,Male,Loyal Customer,57,Business travel,Business,1549,2,4,4,4,2,2,2,2,4,3,2,2,3,2,158,159.0,neutral or dissatisfied +75426,85190,Male,disloyal Customer,39,Business travel,Eco,813,3,3,3,4,4,3,2,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +75427,120481,Female,Loyal Customer,51,Personal Travel,Eco,366,3,1,3,3,3,3,2,5,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +75428,79135,Female,Loyal Customer,29,Business travel,Eco Plus,356,2,5,3,5,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +75429,26492,Male,Loyal Customer,25,Business travel,Business,2523,1,1,1,1,5,5,5,5,4,1,5,5,3,5,1,0.0,satisfied +75430,64150,Male,Loyal Customer,47,Business travel,Business,989,2,2,2,2,5,4,4,5,5,5,5,3,5,4,24,0.0,satisfied +75431,76924,Female,Loyal Customer,53,Business travel,Business,1727,3,3,5,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +75432,74625,Male,Loyal Customer,56,Business travel,Eco,771,4,4,4,4,4,4,4,4,5,4,1,4,2,4,0,0.0,satisfied +75433,46887,Female,Loyal Customer,27,Business travel,Business,2900,1,1,1,1,5,5,5,5,4,2,4,1,4,5,0,0.0,satisfied +75434,83986,Female,Loyal Customer,45,Business travel,Eco,304,2,1,1,1,3,3,4,2,2,2,2,3,2,3,4,46.0,neutral or dissatisfied +75435,96471,Male,Loyal Customer,60,Business travel,Business,3239,2,2,2,2,2,5,5,4,4,4,4,3,4,3,37,34.0,satisfied +75436,54469,Female,Loyal Customer,34,Business travel,Business,925,2,2,2,2,4,3,3,4,4,4,4,4,4,3,0,0.0,satisfied +75437,44099,Male,disloyal Customer,62,Business travel,Business,473,3,3,3,2,1,3,1,1,3,5,2,4,2,1,0,6.0,neutral or dissatisfied +75438,68429,Male,Loyal Customer,10,Personal Travel,Eco,1045,1,4,1,3,4,1,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +75439,48197,Male,disloyal Customer,24,Business travel,Eco,192,4,2,4,3,4,4,4,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +75440,18567,Male,Loyal Customer,64,Business travel,Business,2270,2,4,4,4,2,2,2,4,4,4,2,3,4,1,0,1.0,neutral or dissatisfied +75441,120183,Female,Loyal Customer,55,Business travel,Business,1325,1,1,1,1,5,5,4,3,3,3,3,5,3,5,45,29.0,satisfied +75442,126701,Female,disloyal Customer,37,Business travel,Business,2370,2,2,2,3,2,2,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +75443,125237,Male,Loyal Customer,29,Business travel,Eco,1149,2,1,1,1,2,2,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +75444,11270,Male,Loyal Customer,70,Personal Travel,Eco,316,4,0,5,4,2,5,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +75445,90536,Female,disloyal Customer,34,Business travel,Business,404,2,2,2,1,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +75446,54402,Female,disloyal Customer,61,Business travel,Eco,305,3,4,3,3,3,3,3,3,1,2,3,1,4,3,77,62.0,neutral or dissatisfied +75447,10742,Male,Loyal Customer,15,Business travel,Eco,224,2,3,5,5,2,1,2,2,3,4,2,3,3,2,5,0.0,neutral or dissatisfied +75448,117674,Female,Loyal Customer,48,Business travel,Eco Plus,1049,4,2,2,2,1,1,1,4,4,4,4,4,4,3,27,15.0,satisfied +75449,43548,Male,disloyal Customer,34,Business travel,Eco,308,2,0,2,3,4,2,4,4,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +75450,83182,Female,disloyal Customer,30,Business travel,Eco,549,4,2,4,3,3,4,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +75451,119646,Female,Loyal Customer,48,Business travel,Business,507,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +75452,120133,Female,disloyal Customer,48,Business travel,Business,1475,1,1,1,1,5,1,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +75453,19792,Female,Loyal Customer,10,Personal Travel,Eco,667,2,4,2,3,1,2,1,1,1,3,3,4,3,1,99,114.0,neutral or dissatisfied +75454,124647,Male,Loyal Customer,55,Business travel,Business,399,3,3,3,3,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +75455,107917,Male,disloyal Customer,45,Business travel,Business,611,3,3,3,3,4,3,4,4,3,4,4,3,4,4,20,18.0,satisfied +75456,8253,Female,Loyal Customer,11,Personal Travel,Eco,335,3,5,3,3,1,3,1,1,5,4,5,4,4,1,18,22.0,neutral or dissatisfied +75457,77992,Female,Loyal Customer,48,Business travel,Eco,214,2,2,5,2,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +75458,40046,Female,Loyal Customer,27,Business travel,Business,2098,2,2,2,2,5,5,5,5,3,2,4,2,5,5,0,0.0,satisfied +75459,114224,Male,Loyal Customer,32,Business travel,Business,1757,1,5,2,5,1,1,1,1,2,2,3,1,4,1,0,4.0,neutral or dissatisfied +75460,82130,Female,disloyal Customer,24,Business travel,Eco,802,3,3,3,3,4,3,4,4,2,2,2,2,4,4,0,34.0,neutral or dissatisfied +75461,38628,Male,Loyal Customer,39,Business travel,Business,2704,3,3,3,3,3,3,2,3,3,2,3,5,3,3,0,10.0,satisfied +75462,113796,Female,disloyal Customer,22,Business travel,Business,236,4,0,4,3,5,4,2,5,4,5,4,5,4,5,2,2.0,satisfied +75463,21109,Male,Loyal Customer,31,Personal Travel,Eco,227,2,3,2,3,1,2,1,1,4,1,3,1,4,1,3,2.0,neutral or dissatisfied +75464,81496,Female,Loyal Customer,20,Personal Travel,Eco,528,2,5,2,2,3,2,1,3,1,5,4,5,5,3,0,0.0,neutral or dissatisfied +75465,119825,Female,disloyal Customer,22,Business travel,Eco,912,3,3,3,4,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +75466,21377,Female,disloyal Customer,39,Business travel,Business,554,4,4,4,4,4,4,2,4,2,5,3,4,2,4,0,0.0,satisfied +75467,30670,Female,Loyal Customer,23,Personal Travel,Eco Plus,533,3,4,4,4,2,4,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +75468,111367,Female,Loyal Customer,41,Business travel,Business,1173,2,2,2,2,5,5,5,4,4,4,4,4,4,3,4,6.0,satisfied +75469,82552,Female,disloyal Customer,20,Business travel,Eco,528,1,0,1,4,5,1,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +75470,55702,Female,disloyal Customer,59,Business travel,Eco,662,1,0,1,3,5,1,1,5,4,1,2,2,5,5,9,0.0,neutral or dissatisfied +75471,82328,Female,disloyal Customer,27,Business travel,Eco,456,2,2,2,2,5,2,5,5,4,2,1,1,2,5,0,0.0,neutral or dissatisfied +75472,66625,Male,Loyal Customer,10,Business travel,Business,2535,3,2,3,2,3,3,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +75473,112126,Female,Loyal Customer,38,Personal Travel,Eco,977,4,2,5,4,4,5,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +75474,123488,Male,disloyal Customer,40,Business travel,Eco,1282,4,4,4,3,4,1,2,4,1,3,4,2,3,2,1,56.0,neutral or dissatisfied +75475,69434,Female,Loyal Customer,63,Personal Travel,Eco,1096,0,2,0,3,3,3,3,4,4,0,4,1,4,1,0,0.0,satisfied +75476,117029,Female,disloyal Customer,25,Business travel,Eco,338,3,1,3,3,5,3,5,5,3,5,3,3,4,5,14,2.0,neutral or dissatisfied +75477,123051,Male,disloyal Customer,38,Business travel,Business,507,5,5,5,4,1,5,1,1,5,5,4,3,4,1,0,0.0,satisfied +75478,55557,Female,Loyal Customer,47,Business travel,Business,2112,2,2,2,2,4,4,4,4,4,4,4,3,4,4,63,57.0,satisfied +75479,127236,Male,Loyal Customer,49,Personal Travel,Eco,1460,2,4,2,3,2,2,2,2,5,2,3,4,4,2,6,1.0,neutral or dissatisfied +75480,35681,Female,disloyal Customer,48,Business travel,Eco,854,1,1,1,3,1,5,5,2,2,4,4,5,4,5,0,4.0,neutral or dissatisfied +75481,100781,Female,Loyal Customer,44,Personal Travel,Eco,1411,0,5,0,2,3,5,5,2,2,0,2,2,2,5,0,0.0,satisfied +75482,50045,Male,Loyal Customer,33,Business travel,Business,89,2,3,3,3,2,2,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +75483,96682,Female,Loyal Customer,27,Personal Travel,Eco Plus,937,4,3,4,4,1,4,1,1,2,3,3,1,3,1,0,0.0,satisfied +75484,15574,Male,disloyal Customer,37,Business travel,Business,228,4,4,4,3,4,4,5,4,2,5,5,1,1,4,1,0.0,neutral or dissatisfied +75485,112857,Male,Loyal Customer,52,Business travel,Business,2934,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +75486,104151,Male,Loyal Customer,57,Business travel,Business,2662,3,3,3,3,2,5,4,5,5,5,5,3,5,3,24,19.0,satisfied +75487,124615,Male,Loyal Customer,51,Business travel,Business,1671,2,2,2,2,4,4,4,2,2,3,2,5,2,4,0,0.0,satisfied +75488,28128,Female,Loyal Customer,35,Business travel,Business,2952,3,3,3,3,3,1,1,4,4,4,4,1,4,4,40,36.0,satisfied +75489,820,Male,disloyal Customer,41,Business travel,Business,309,2,2,2,4,2,2,2,2,3,4,4,3,4,2,18,18.0,neutral or dissatisfied +75490,58641,Male,Loyal Customer,56,Business travel,Business,867,4,4,4,4,2,5,4,5,5,4,5,3,5,4,12,0.0,satisfied +75491,39267,Male,Loyal Customer,47,Business travel,Business,1667,4,2,2,2,2,4,3,1,1,1,4,1,1,4,0,11.0,neutral or dissatisfied +75492,43373,Female,Loyal Customer,16,Personal Travel,Eco,387,2,4,2,3,3,2,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +75493,110821,Female,Loyal Customer,50,Personal Travel,Eco,990,2,2,1,3,5,3,3,5,5,1,5,3,5,1,74,68.0,neutral or dissatisfied +75494,111749,Male,Loyal Customer,19,Personal Travel,Eco,1085,4,4,4,1,4,4,4,4,4,4,5,3,5,4,1,12.0,neutral or dissatisfied +75495,18872,Male,Loyal Customer,53,Business travel,Eco,503,3,3,5,5,3,3,3,3,1,5,3,2,3,3,30,22.0,neutral or dissatisfied +75496,75671,Male,Loyal Customer,55,Business travel,Business,868,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,11.0,satisfied +75497,100604,Female,disloyal Customer,59,Business travel,Eco,318,1,3,1,2,4,1,4,4,2,5,3,1,2,4,0,0.0,neutral or dissatisfied +75498,75702,Female,Loyal Customer,54,Business travel,Business,868,4,4,4,4,3,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +75499,34630,Female,Loyal Customer,43,Business travel,Eco,427,5,3,3,3,1,1,3,5,5,5,5,1,5,3,0,18.0,satisfied +75500,91440,Female,Loyal Customer,16,Business travel,Business,3863,2,2,3,2,4,4,4,4,5,2,4,5,5,4,11,0.0,satisfied +75501,5739,Male,disloyal Customer,45,Business travel,Business,642,1,1,1,1,5,1,5,5,3,4,5,3,5,5,5,15.0,neutral or dissatisfied +75502,71291,Male,Loyal Customer,42,Personal Travel,Eco Plus,733,4,3,4,3,1,4,1,1,1,1,2,5,3,1,0,0.0,satisfied +75503,61862,Female,Loyal Customer,18,Personal Travel,Eco Plus,1303,3,2,3,3,5,3,3,5,1,3,3,3,3,5,0,0.0,neutral or dissatisfied +75504,3980,Female,Loyal Customer,42,Business travel,Business,3292,1,2,2,2,5,3,3,1,1,2,1,2,1,3,0,8.0,neutral or dissatisfied +75505,19997,Female,Loyal Customer,37,Business travel,Eco,589,5,2,2,2,5,5,5,5,3,3,3,3,1,5,29,30.0,satisfied +75506,113517,Male,Loyal Customer,45,Business travel,Business,236,2,5,4,5,4,3,3,2,2,2,2,1,2,4,22,26.0,neutral or dissatisfied +75507,11138,Female,Loyal Customer,50,Personal Travel,Eco,667,2,4,2,4,4,5,5,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +75508,98393,Female,Loyal Customer,43,Business travel,Business,675,4,4,4,4,5,4,5,5,5,5,5,3,5,4,15,10.0,satisfied +75509,13206,Female,Loyal Customer,37,Personal Travel,Eco Plus,419,3,1,3,3,1,3,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +75510,61882,Male,Loyal Customer,41,Business travel,Eco,2521,3,5,5,5,3,3,3,3,2,1,2,3,3,3,67,48.0,neutral or dissatisfied +75511,124530,Male,Loyal Customer,51,Business travel,Business,1276,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +75512,53645,Female,Loyal Customer,25,Personal Travel,Eco,1874,0,5,0,4,2,0,2,2,2,4,5,3,1,2,0,0.0,satisfied +75513,11561,Male,disloyal Customer,20,Business travel,Eco,657,2,0,2,3,2,2,2,2,3,2,5,3,4,2,9,1.0,neutral or dissatisfied +75514,24325,Female,Loyal Customer,51,Business travel,Business,3388,4,4,4,4,2,2,5,5,5,5,5,1,5,4,0,0.0,satisfied +75515,68765,Female,Loyal Customer,46,Business travel,Business,2730,1,1,3,1,1,3,4,1,1,1,1,4,1,3,0,12.0,neutral or dissatisfied +75516,85586,Female,Loyal Customer,58,Business travel,Business,153,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +75517,18897,Female,Loyal Customer,54,Business travel,Business,2467,4,3,3,3,1,1,2,1,1,1,4,2,1,4,2,0.0,neutral or dissatisfied +75518,122447,Male,Loyal Customer,30,Business travel,Business,575,5,5,5,5,4,4,4,4,3,4,4,5,5,4,0,5.0,satisfied +75519,121563,Male,Loyal Customer,58,Business travel,Business,936,2,4,4,4,2,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +75520,62095,Male,Loyal Customer,50,Business travel,Business,2565,3,3,5,3,5,4,4,5,5,5,5,3,5,3,9,0.0,satisfied +75521,38884,Female,Loyal Customer,61,Personal Travel,Eco,261,3,4,3,4,5,3,4,1,1,3,1,1,1,2,0,0.0,neutral or dissatisfied +75522,113043,Male,Loyal Customer,59,Business travel,Business,2536,3,5,1,5,3,3,4,3,3,3,3,2,3,4,13,0.0,neutral or dissatisfied +75523,29112,Male,Loyal Customer,61,Personal Travel,Eco,697,4,5,4,2,2,4,2,2,3,4,5,4,5,2,48,63.0,neutral or dissatisfied +75524,98169,Female,Loyal Customer,26,Business travel,Business,562,3,3,3,3,4,4,4,4,5,4,4,5,4,4,13,7.0,satisfied +75525,9279,Male,Loyal Customer,25,Business travel,Business,1764,3,3,3,3,4,4,4,4,4,5,4,4,4,4,121,128.0,satisfied +75526,120375,Female,Loyal Customer,56,Business travel,Business,449,3,3,3,3,3,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +75527,25083,Female,Loyal Customer,52,Business travel,Eco,549,4,4,4,4,2,3,3,4,4,4,4,5,4,3,9,11.0,satisfied +75528,64472,Male,Loyal Customer,36,Business travel,Business,551,4,4,4,4,4,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +75529,7253,Male,Loyal Customer,20,Personal Travel,Eco,135,2,3,2,4,4,2,4,4,1,1,4,1,4,4,0,0.0,neutral or dissatisfied +75530,23094,Male,Loyal Customer,14,Personal Travel,Eco Plus,864,2,1,2,1,2,2,4,2,2,2,1,1,2,2,18,56.0,neutral or dissatisfied +75531,108320,Male,Loyal Customer,49,Business travel,Business,1750,2,2,2,2,4,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +75532,23627,Male,Loyal Customer,35,Business travel,Business,2758,4,4,5,4,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +75533,116002,Female,Loyal Customer,58,Personal Travel,Eco,446,3,5,3,1,4,4,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +75534,82176,Female,Loyal Customer,44,Business travel,Eco Plus,237,3,3,3,3,2,4,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +75535,17344,Female,Loyal Customer,22,Business travel,Eco,563,4,3,2,2,4,4,5,4,3,4,3,5,4,4,1,9.0,satisfied +75536,38716,Male,Loyal Customer,69,Personal Travel,Eco,2583,4,5,4,4,4,4,2,4,5,5,4,2,5,4,12,6.0,neutral or dissatisfied +75537,121439,Male,disloyal Customer,25,Business travel,Eco,331,2,3,2,3,3,2,1,3,1,2,3,1,3,3,0,4.0,neutral or dissatisfied +75538,56324,Male,disloyal Customer,30,Business travel,Business,200,3,3,3,4,2,3,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +75539,34928,Male,Loyal Customer,38,Business travel,Business,187,1,1,1,1,4,3,1,4,4,4,5,2,4,1,0,0.0,satisfied +75540,42675,Female,Loyal Customer,38,Business travel,Business,1710,4,4,5,4,3,1,1,3,3,3,3,2,3,3,0,0.0,satisfied +75541,87106,Female,Loyal Customer,61,Personal Travel,Eco,594,4,5,4,1,2,4,4,3,3,4,2,1,3,1,0,3.0,neutral or dissatisfied +75542,127239,Female,Loyal Customer,20,Business travel,Eco Plus,1460,2,4,4,4,2,2,3,2,1,5,4,2,3,2,15,9.0,neutral or dissatisfied +75543,109770,Female,Loyal Customer,17,Business travel,Business,3607,4,4,4,4,4,4,4,4,3,2,4,5,5,4,21,15.0,satisfied +75544,58311,Male,Loyal Customer,44,Business travel,Business,1739,4,4,4,4,5,4,5,2,2,2,2,4,2,4,1,6.0,satisfied +75545,79602,Female,Loyal Customer,60,Business travel,Business,853,3,5,5,5,4,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +75546,115510,Female,Loyal Customer,60,Business travel,Business,2500,5,1,1,1,4,4,3,5,5,4,5,3,5,1,6,5.0,neutral or dissatisfied +75547,116294,Male,Loyal Customer,42,Personal Travel,Eco,362,2,5,2,4,3,2,3,3,5,4,5,5,4,3,6,0.0,neutral or dissatisfied +75548,53463,Male,Loyal Customer,42,Business travel,Business,2288,5,5,4,5,4,4,4,4,4,4,4,1,4,5,1,4.0,satisfied +75549,42966,Male,Loyal Customer,40,Business travel,Eco,192,3,3,3,3,3,3,3,3,2,3,5,5,3,3,47,36.0,satisfied +75550,126872,Male,Loyal Customer,24,Personal Travel,Eco,2296,2,5,1,4,1,1,1,1,5,2,3,4,4,1,20,0.0,neutral or dissatisfied +75551,49108,Male,Loyal Customer,65,Business travel,Eco,109,5,3,3,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +75552,71392,Female,Loyal Customer,51,Business travel,Eco Plus,258,4,5,5,5,4,3,4,4,4,4,4,4,4,3,1,4.0,neutral or dissatisfied +75553,39313,Male,Loyal Customer,25,Personal Travel,Eco,67,2,5,2,2,5,2,1,5,4,5,5,5,5,5,9,8.0,neutral or dissatisfied +75554,60816,Male,disloyal Customer,21,Business travel,Eco,524,1,1,1,3,3,1,3,3,4,4,4,1,4,3,41,41.0,neutral or dissatisfied +75555,57282,Male,Loyal Customer,69,Personal Travel,Eco,804,3,3,3,2,3,3,3,3,3,3,2,3,1,3,136,136.0,neutral or dissatisfied +75556,34044,Male,Loyal Customer,64,Personal Travel,Eco,1608,1,5,1,3,2,1,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +75557,11767,Female,Loyal Customer,32,Personal Travel,Eco,429,3,4,3,1,2,3,2,2,5,5,3,5,2,2,0,5.0,neutral or dissatisfied +75558,97700,Male,Loyal Customer,41,Business travel,Business,456,1,1,2,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +75559,90517,Female,Loyal Customer,35,Business travel,Business,3810,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +75560,109583,Male,Loyal Customer,29,Personal Travel,Eco,834,3,4,3,3,1,3,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +75561,61845,Female,Loyal Customer,57,Business travel,Business,1635,1,1,1,1,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +75562,22897,Female,Loyal Customer,47,Business travel,Eco Plus,170,3,2,2,2,3,4,3,4,4,3,4,4,4,2,53,62.0,neutral or dissatisfied +75563,128607,Male,Loyal Customer,27,Business travel,Business,954,2,2,2,2,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +75564,47590,Male,Loyal Customer,70,Business travel,Business,1242,3,3,3,3,3,2,2,4,4,4,4,3,4,2,9,0.0,satisfied +75565,44891,Female,Loyal Customer,22,Business travel,Business,3632,3,3,3,3,3,4,3,3,1,3,5,5,2,3,0,1.0,satisfied +75566,60608,Male,Loyal Customer,11,Business travel,Business,1678,2,2,3,2,5,5,5,5,5,2,5,3,4,5,3,1.0,satisfied +75567,82239,Female,Loyal Customer,8,Personal Travel,Eco,405,2,3,1,4,4,1,4,4,1,2,1,3,1,4,11,30.0,neutral or dissatisfied +75568,31213,Male,Loyal Customer,21,Personal Travel,Eco,628,3,4,3,2,2,3,2,2,3,4,4,4,5,2,42,42.0,neutral or dissatisfied +75569,11518,Female,Loyal Customer,67,Personal Travel,Eco Plus,429,2,3,2,3,3,3,3,3,3,2,3,4,3,1,120,113.0,neutral or dissatisfied +75570,19665,Female,disloyal Customer,23,Business travel,Business,475,0,0,0,3,3,0,3,3,5,3,4,3,5,3,21,20.0,satisfied +75571,128482,Female,Loyal Customer,8,Personal Travel,Eco,325,3,4,3,3,2,3,2,2,5,1,1,5,3,2,0,0.0,neutral or dissatisfied +75572,103703,Female,Loyal Customer,21,Personal Travel,Eco,405,4,4,4,5,3,4,1,3,4,3,4,4,4,3,7,0.0,neutral or dissatisfied +75573,28684,Male,Loyal Customer,51,Personal Travel,Eco,2797,3,0,3,3,2,3,2,2,1,4,2,3,3,2,0,0.0,neutral or dissatisfied +75574,69433,Male,Loyal Customer,61,Personal Travel,Eco,1035,3,5,3,2,3,3,3,3,5,3,5,3,4,3,7,0.0,neutral or dissatisfied +75575,106226,Female,Loyal Customer,42,Personal Travel,Eco,471,4,4,4,1,3,4,4,4,4,4,4,5,4,5,14,15.0,neutral or dissatisfied +75576,66151,Female,Loyal Customer,39,Business travel,Business,550,3,3,3,3,1,4,4,3,3,3,3,2,3,3,7,0.0,neutral or dissatisfied +75577,92442,Male,Loyal Customer,53,Business travel,Business,2139,2,3,3,3,4,4,3,2,2,2,2,4,2,4,0,1.0,neutral or dissatisfied +75578,64121,Female,Loyal Customer,14,Personal Travel,Eco,2288,4,2,5,4,5,2,2,1,1,4,4,2,2,2,0,5.0,satisfied +75579,41318,Female,Loyal Customer,13,Personal Travel,Eco,802,5,5,5,3,1,5,1,1,3,2,4,3,4,1,88,86.0,satisfied +75580,47694,Male,Loyal Customer,56,Personal Travel,Eco,1242,3,5,3,3,4,3,4,4,3,2,4,5,4,4,0,3.0,neutral or dissatisfied +75581,110500,Male,Loyal Customer,40,Business travel,Business,2085,3,3,5,3,5,4,4,5,5,5,5,5,5,5,12,0.0,satisfied +75582,26728,Female,disloyal Customer,39,Business travel,Business,404,5,5,5,1,1,5,4,1,4,3,5,3,2,1,0,1.0,satisfied +75583,38030,Male,Loyal Customer,43,Business travel,Business,1121,4,4,4,4,5,1,2,4,4,4,4,2,4,5,0,0.0,satisfied +75584,27485,Female,Loyal Customer,33,Business travel,Business,2367,3,3,3,3,3,2,2,3,3,3,3,4,3,3,0,15.0,neutral or dissatisfied +75585,34008,Male,disloyal Customer,38,Business travel,Eco,998,2,2,2,4,3,2,3,3,3,5,4,1,4,3,8,20.0,neutral or dissatisfied +75586,116616,Male,Loyal Customer,53,Business travel,Business,1737,5,5,5,5,3,4,4,5,5,5,5,4,5,5,18,15.0,satisfied +75587,28593,Female,Loyal Customer,46,Business travel,Eco Plus,2562,5,1,3,1,5,5,2,5,5,5,5,2,5,4,0,0.0,satisfied +75588,8497,Female,Loyal Customer,55,Personal Travel,Business,737,1,5,1,5,2,5,5,1,1,1,3,5,1,4,0,0.0,neutral or dissatisfied +75589,63670,Male,Loyal Customer,17,Personal Travel,Eco Plus,2405,3,4,3,4,2,3,2,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +75590,79522,Female,Loyal Customer,50,Business travel,Business,762,1,1,1,1,2,4,4,4,4,4,4,4,4,3,0,20.0,satisfied +75591,51934,Male,Loyal Customer,34,Business travel,Eco,347,0,0,0,4,3,0,3,3,2,5,4,5,3,3,0,0.0,satisfied +75592,109897,Female,disloyal Customer,38,Business travel,Eco,765,2,2,2,3,5,2,4,5,1,5,4,1,4,5,23,6.0,neutral or dissatisfied +75593,74964,Male,Loyal Customer,23,Personal Travel,Eco,2586,2,2,2,4,5,2,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +75594,38049,Female,Loyal Customer,29,Business travel,Business,3933,4,4,4,4,3,3,3,3,1,3,1,3,3,3,26,0.0,satisfied +75595,107420,Male,disloyal Customer,24,Business travel,Eco,317,1,4,1,4,3,1,3,3,2,5,3,1,5,3,12,0.0,neutral or dissatisfied +75596,124267,Male,Loyal Customer,26,Personal Travel,Business,255,2,4,2,4,3,2,3,3,5,3,1,1,5,3,1,0.0,neutral or dissatisfied +75597,80470,Male,disloyal Customer,47,Business travel,Eco,899,3,3,3,1,3,3,3,3,4,5,2,4,1,3,0,0.0,neutral or dissatisfied +75598,6110,Male,Loyal Customer,40,Personal Travel,Business,409,3,4,3,3,5,5,5,1,1,3,1,5,1,3,0,63.0,neutral or dissatisfied +75599,122854,Male,Loyal Customer,59,Business travel,Business,3010,0,0,0,3,2,4,5,2,2,2,2,4,2,3,0,2.0,satisfied +75600,39936,Male,Loyal Customer,45,Business travel,Business,2451,1,1,1,1,5,1,3,2,2,2,2,5,2,3,3,0.0,satisfied +75601,106702,Male,Loyal Customer,47,Business travel,Eco,116,2,3,5,3,1,2,1,1,1,3,3,2,5,1,0,0.0,satisfied +75602,83014,Male,disloyal Customer,27,Business travel,Business,1127,5,5,5,2,4,5,3,4,3,2,5,4,4,4,61,51.0,satisfied +75603,108149,Female,Loyal Customer,8,Personal Travel,Eco,997,4,3,4,3,1,4,1,1,4,1,5,2,1,1,10,0.0,neutral or dissatisfied +75604,70012,Female,Loyal Customer,27,Personal Travel,Eco Plus,236,4,5,4,3,5,4,3,5,5,3,1,1,4,5,3,0.0,neutral or dissatisfied +75605,20348,Female,Loyal Customer,38,Business travel,Eco,323,2,2,2,2,2,2,2,3,2,3,3,2,2,2,136,133.0,neutral or dissatisfied +75606,124375,Female,Loyal Customer,43,Business travel,Business,575,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +75607,85366,Male,Loyal Customer,35,Personal Travel,Eco Plus,731,3,4,3,4,5,3,1,5,1,1,3,1,3,5,62,66.0,neutral or dissatisfied +75608,16485,Male,disloyal Customer,25,Business travel,Eco,143,0,3,0,4,2,0,5,2,4,1,4,5,3,2,0,0.0,satisfied +75609,66639,Female,Loyal Customer,47,Business travel,Business,2272,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,1.0,satisfied +75610,73475,Male,Loyal Customer,7,Personal Travel,Eco,1120,1,4,1,3,3,1,3,3,5,1,4,3,1,3,130,119.0,neutral or dissatisfied +75611,105638,Male,Loyal Customer,41,Business travel,Business,1616,5,5,5,5,5,4,4,5,5,5,5,3,5,5,23,28.0,satisfied +75612,117781,Male,Loyal Customer,42,Business travel,Eco,412,5,4,4,4,4,5,4,4,5,5,1,5,5,4,35,45.0,satisfied +75613,68056,Female,Loyal Customer,43,Business travel,Business,3965,1,1,1,1,5,5,4,5,5,5,5,5,5,4,14,2.0,satisfied +75614,116129,Female,Loyal Customer,55,Personal Travel,Eco,446,2,5,2,1,5,4,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +75615,76927,Female,Loyal Customer,57,Business travel,Business,1727,3,3,3,3,3,4,5,4,4,4,4,5,4,5,0,13.0,satisfied +75616,58415,Male,Loyal Customer,24,Business travel,Business,723,3,1,1,1,3,3,3,3,1,5,3,2,3,3,1,0.0,neutral or dissatisfied +75617,120806,Female,disloyal Customer,44,Business travel,Business,666,3,3,3,5,5,3,5,5,3,2,5,3,4,5,67,68.0,neutral or dissatisfied +75618,85596,Female,disloyal Customer,25,Business travel,Eco,317,3,5,3,5,3,3,3,3,1,5,5,2,3,3,12,0.0,neutral or dissatisfied +75619,119291,Male,disloyal Customer,37,Business travel,Business,214,2,2,2,4,2,2,2,2,1,3,4,3,3,2,0,8.0,neutral or dissatisfied +75620,12977,Male,Loyal Customer,46,Personal Travel,Business,374,4,2,4,3,1,4,3,4,4,4,4,4,4,2,32,21.0,neutral or dissatisfied +75621,65052,Male,Loyal Customer,54,Personal Travel,Eco,247,3,5,3,3,1,3,1,1,4,3,4,4,4,1,6,3.0,neutral or dissatisfied +75622,3035,Female,Loyal Customer,42,Business travel,Eco Plus,922,1,5,5,5,5,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +75623,56528,Male,Loyal Customer,53,Business travel,Eco,1065,2,5,1,5,2,2,2,2,2,3,4,3,4,2,10,47.0,neutral or dissatisfied +75624,32995,Male,Loyal Customer,10,Personal Travel,Eco,216,1,2,1,4,1,1,1,1,2,4,3,1,3,1,0,2.0,neutral or dissatisfied +75625,111968,Female,Loyal Customer,26,Business travel,Business,533,4,4,4,4,4,4,4,4,1,4,3,2,3,4,0,0.0,neutral or dissatisfied +75626,126099,Male,Loyal Customer,43,Business travel,Business,3574,5,5,5,5,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +75627,16557,Male,Loyal Customer,41,Business travel,Business,872,3,3,5,3,3,4,3,4,4,4,4,4,4,2,0,4.0,satisfied +75628,30598,Male,Loyal Customer,49,Business travel,Business,472,3,3,3,3,4,2,2,4,4,4,4,5,4,2,98,102.0,satisfied +75629,92806,Female,Loyal Customer,42,Business travel,Business,1587,2,4,4,4,5,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +75630,48704,Male,Loyal Customer,43,Business travel,Business,308,2,2,2,2,1,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +75631,93370,Male,Loyal Customer,67,Personal Travel,Eco,836,4,4,4,3,3,4,5,3,4,2,3,2,4,3,10,7.0,neutral or dissatisfied +75632,99587,Male,Loyal Customer,65,Personal Travel,Eco,930,4,4,4,4,1,4,1,1,3,4,4,5,5,1,0,0.0,satisfied +75633,28173,Female,Loyal Customer,13,Personal Travel,Eco,569,5,3,5,1,2,5,1,2,5,4,4,1,1,2,0,0.0,satisfied +75634,751,Female,disloyal Customer,21,Business travel,Eco,354,0,4,0,4,3,0,3,3,4,3,4,3,5,3,2,8.0,satisfied +75635,52097,Female,Loyal Customer,68,Personal Travel,Eco,639,3,5,3,4,5,5,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +75636,416,Female,Loyal Customer,44,Business travel,Business,3915,1,2,2,2,5,3,2,4,4,3,1,3,4,4,0,0.0,neutral or dissatisfied +75637,87285,Female,Loyal Customer,39,Business travel,Business,2004,2,3,3,3,5,3,4,2,2,2,2,3,2,3,9,11.0,neutral or dissatisfied +75638,56678,Male,Loyal Customer,63,Personal Travel,Eco,1065,3,5,4,5,3,4,3,3,5,4,5,4,4,3,1,0.0,neutral or dissatisfied +75639,40516,Female,Loyal Customer,61,Business travel,Eco Plus,150,4,4,4,4,4,2,3,4,4,4,4,3,4,3,0,0.0,satisfied +75640,21150,Female,Loyal Customer,55,Personal Travel,Eco Plus,227,2,4,2,4,5,5,5,4,4,2,4,4,4,3,4,0.0,neutral or dissatisfied +75641,18670,Female,Loyal Customer,29,Personal Travel,Eco,192,4,5,4,4,2,4,5,2,3,3,4,5,4,2,0,2.0,neutral or dissatisfied +75642,1802,Male,Loyal Customer,49,Business travel,Business,2799,4,4,5,4,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +75643,97167,Female,Loyal Customer,36,Personal Travel,Eco,1164,5,4,4,3,1,4,1,1,4,2,3,3,4,1,1,0.0,satisfied +75644,48087,Male,Loyal Customer,39,Business travel,Eco,236,3,2,2,2,3,3,3,3,1,4,4,4,5,3,0,4.0,satisfied +75645,124178,Female,Loyal Customer,37,Personal Travel,Business,2089,1,3,0,4,1,4,3,1,1,0,1,2,1,2,0,0.0,neutral or dissatisfied +75646,27745,Female,Loyal Customer,37,Business travel,Eco,1448,5,3,3,3,5,5,5,5,5,4,3,2,4,5,0,0.0,satisfied +75647,110046,Male,Loyal Customer,53,Business travel,Eco,1984,1,1,1,1,2,1,2,2,2,3,1,3,3,2,4,18.0,neutral or dissatisfied +75648,32788,Male,Loyal Customer,34,Business travel,Eco,201,5,5,5,5,5,5,5,5,3,1,5,4,3,5,0,0.0,satisfied +75649,47787,Male,Loyal Customer,59,Business travel,Eco,834,4,5,2,5,4,4,4,4,3,1,1,3,4,4,0,0.0,satisfied +75650,87625,Female,Loyal Customer,50,Business travel,Business,2323,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,14.0,satisfied +75651,104838,Male,Loyal Customer,42,Personal Travel,Eco,472,3,4,3,3,5,3,4,5,1,1,1,3,1,5,13,44.0,neutral or dissatisfied +75652,9867,Female,Loyal Customer,49,Business travel,Business,642,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +75653,29134,Male,Loyal Customer,55,Personal Travel,Eco,605,3,4,3,1,3,3,4,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +75654,98291,Male,Loyal Customer,47,Personal Travel,Eco,1136,2,1,2,2,4,2,4,4,1,5,1,3,2,4,0,4.0,neutral or dissatisfied +75655,17869,Male,disloyal Customer,33,Business travel,Eco,399,4,3,4,2,1,4,1,1,1,4,3,3,3,1,28,16.0,neutral or dissatisfied +75656,79015,Male,Loyal Customer,39,Business travel,Business,306,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,8.0,satisfied +75657,84770,Female,Loyal Customer,42,Business travel,Business,3431,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,11.0,satisfied +75658,108094,Female,Loyal Customer,20,Business travel,Eco,990,2,5,5,5,2,3,2,2,2,4,3,4,4,2,8,2.0,neutral or dissatisfied +75659,35781,Female,Loyal Customer,38,Business travel,Business,200,2,4,4,4,4,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +75660,3004,Male,Loyal Customer,43,Business travel,Business,922,4,4,4,4,2,4,4,3,3,3,3,5,3,5,28,27.0,satisfied +75661,63958,Female,Loyal Customer,41,Personal Travel,Eco,1192,2,4,2,3,3,2,3,3,4,1,3,4,4,3,2,0.0,neutral or dissatisfied +75662,6030,Male,Loyal Customer,16,Business travel,Business,2435,1,3,3,3,1,1,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +75663,43138,Female,Loyal Customer,73,Business travel,Eco Plus,236,5,1,1,1,3,2,2,5,5,5,5,2,5,3,4,4.0,satisfied +75664,104399,Male,Loyal Customer,57,Business travel,Business,2940,1,1,4,1,4,5,4,4,4,4,4,3,4,3,2,17.0,satisfied +75665,109875,Male,Loyal Customer,43,Business travel,Business,1130,2,2,2,2,4,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +75666,56272,Female,Loyal Customer,59,Personal Travel,Eco Plus,404,3,1,3,3,2,3,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +75667,1538,Male,disloyal Customer,30,Business travel,Business,922,2,2,2,3,1,2,1,1,2,4,4,4,4,1,75,74.0,neutral or dissatisfied +75668,64488,Male,Loyal Customer,42,Business travel,Business,3766,0,0,0,2,5,5,5,1,1,1,1,4,1,5,0,0.0,satisfied +75669,80569,Male,disloyal Customer,17,Business travel,Business,1747,5,5,5,4,4,5,4,4,4,5,4,5,5,4,1,0.0,satisfied +75670,84988,Male,Loyal Customer,52,Business travel,Business,1590,2,2,2,2,3,4,5,4,4,4,4,4,4,3,30,19.0,satisfied +75671,78770,Male,disloyal Customer,26,Business travel,Business,554,3,3,3,2,4,3,4,4,5,5,5,4,5,4,10,4.0,neutral or dissatisfied +75672,62413,Male,Loyal Customer,13,Personal Travel,Eco Plus,2704,3,5,3,1,5,3,5,5,3,3,1,2,1,5,27,0.0,neutral or dissatisfied +75673,56317,Male,Loyal Customer,41,Business travel,Business,2719,4,2,4,2,3,4,4,2,2,2,4,4,2,2,0,0.0,neutral or dissatisfied +75674,20429,Male,Loyal Customer,51,Personal Travel,Eco,299,2,5,2,2,5,2,5,5,4,4,5,5,4,5,7,8.0,neutral or dissatisfied +75675,127901,Female,disloyal Customer,34,Business travel,Eco,840,3,3,3,4,2,3,2,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +75676,105884,Male,Loyal Customer,55,Business travel,Business,2934,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +75677,35651,Male,Loyal Customer,28,Business travel,Business,2465,5,5,5,5,5,5,5,1,2,4,4,5,4,5,0,18.0,satisfied +75678,64918,Male,Loyal Customer,68,Business travel,Business,247,0,0,0,3,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +75679,50242,Male,disloyal Customer,23,Business travel,Eco,109,1,0,1,1,3,1,1,3,2,5,5,3,1,3,0,0.0,neutral or dissatisfied +75680,30430,Female,disloyal Customer,8,Business travel,Eco Plus,1014,3,2,3,4,1,3,1,1,3,5,4,4,3,1,0,11.0,neutral or dissatisfied +75681,51122,Female,Loyal Customer,68,Personal Travel,Eco,110,1,3,1,1,3,2,4,3,3,1,4,5,3,4,0,0.0,neutral or dissatisfied +75682,95502,Male,Loyal Customer,52,Business travel,Business,323,5,5,5,5,5,5,5,5,5,5,5,5,5,4,0,3.0,satisfied +75683,29185,Male,Loyal Customer,49,Personal Travel,Eco Plus,679,4,2,4,3,2,4,2,2,1,4,2,2,3,2,0,0.0,satisfied +75684,56266,Female,disloyal Customer,21,Business travel,Eco,404,3,1,3,2,5,3,1,5,3,3,1,3,2,5,0,0.0,neutral or dissatisfied +75685,92529,Female,Loyal Customer,21,Personal Travel,Eco,1947,2,1,2,3,5,2,2,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +75686,67881,Female,Loyal Customer,35,Personal Travel,Eco,1205,1,2,1,4,5,1,5,5,4,3,3,2,4,5,0,0.0,neutral or dissatisfied +75687,113186,Male,Loyal Customer,45,Business travel,Business,414,4,4,4,4,2,4,4,4,4,4,4,5,4,3,13,6.0,satisfied +75688,52009,Male,disloyal Customer,36,Business travel,Eco,328,4,4,4,4,2,4,5,2,1,5,5,1,5,2,0,0.0,neutral or dissatisfied +75689,31744,Female,Loyal Customer,54,Business travel,Eco Plus,862,4,2,2,2,1,4,2,4,4,4,4,1,4,2,0,0.0,satisfied +75690,88498,Female,Loyal Customer,43,Business travel,Eco,515,4,3,3,3,4,2,4,3,3,4,3,3,3,5,0,0.0,satisfied +75691,117492,Male,Loyal Customer,60,Business travel,Business,507,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +75692,88433,Female,disloyal Customer,17,Business travel,Business,270,4,4,4,3,3,4,3,3,3,5,4,3,4,3,0,0.0,satisfied +75693,19944,Female,Loyal Customer,30,Personal Travel,Eco,315,2,5,1,1,4,1,4,4,5,5,1,5,3,4,80,74.0,neutral or dissatisfied +75694,88455,Male,Loyal Customer,62,Business travel,Eco,115,5,4,4,4,4,5,4,4,3,5,2,2,2,4,0,0.0,satisfied +75695,11526,Female,Loyal Customer,51,Personal Travel,Eco Plus,216,2,0,2,3,2,4,4,1,1,2,1,5,1,5,69,68.0,neutral or dissatisfied +75696,20587,Male,Loyal Customer,64,Personal Travel,Eco,773,1,4,1,3,1,1,4,1,2,5,3,3,5,1,108,107.0,neutral or dissatisfied +75697,11639,Female,Loyal Customer,8,Personal Travel,Eco,835,1,5,1,1,2,1,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +75698,74263,Female,disloyal Customer,24,Business travel,Eco,748,4,4,4,3,1,4,1,1,4,5,5,3,5,1,0,0.0,satisfied +75699,113974,Female,Loyal Customer,40,Business travel,Business,1750,4,3,5,3,4,4,4,4,4,4,4,2,4,2,8,0.0,neutral or dissatisfied +75700,53766,Female,Loyal Customer,38,Business travel,Eco,1195,4,2,2,2,4,4,4,4,2,2,5,3,2,4,15,5.0,satisfied +75701,35384,Male,Loyal Customer,35,Business travel,Eco,1076,4,1,2,1,4,4,4,4,2,5,1,2,1,4,0,0.0,satisfied +75702,99838,Male,disloyal Customer,40,Business travel,Business,587,4,4,4,3,1,4,1,1,4,3,4,5,4,1,0,0.0,satisfied +75703,109144,Female,disloyal Customer,41,Business travel,Business,612,3,3,3,3,1,3,1,1,5,3,4,4,4,1,35,37.0,satisfied +75704,60970,Female,Loyal Customer,20,Personal Travel,Eco,888,3,5,3,2,2,3,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +75705,125547,Male,Loyal Customer,51,Business travel,Business,226,1,1,1,1,5,4,5,5,5,5,5,3,5,3,0,3.0,satisfied +75706,40724,Male,Loyal Customer,25,Business travel,Business,3722,4,4,4,4,4,4,4,4,2,4,4,3,1,4,29,29.0,satisfied +75707,62780,Male,disloyal Customer,38,Business travel,Eco,986,1,1,1,1,3,1,3,3,3,2,1,4,3,3,0,0.0,neutral or dissatisfied +75708,52127,Male,disloyal Customer,38,Business travel,Business,370,2,3,3,1,2,3,2,2,4,2,4,3,4,2,17,35.0,satisfied +75709,22754,Female,Loyal Customer,61,Business travel,Eco,302,4,3,3,3,4,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +75710,114646,Male,disloyal Customer,20,Business travel,Business,333,0,0,0,4,4,0,4,4,3,4,4,4,4,4,40,28.0,satisfied +75711,71250,Male,Loyal Customer,43,Business travel,Business,2971,3,2,2,2,4,2,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +75712,99119,Female,Loyal Customer,10,Personal Travel,Eco,181,4,2,4,3,5,4,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +75713,30324,Male,Loyal Customer,34,Business travel,Business,3356,2,2,2,2,3,4,4,4,4,4,4,2,4,4,5,4.0,satisfied +75714,16532,Female,Loyal Customer,38,Business travel,Business,209,1,1,1,1,5,5,2,4,4,4,5,4,4,3,0,0.0,satisfied +75715,121090,Male,Loyal Customer,42,Business travel,Business,1558,4,4,4,4,3,5,5,5,5,5,5,4,5,4,2,0.0,satisfied +75716,103400,Male,disloyal Customer,25,Business travel,Business,237,1,5,1,2,5,1,5,5,5,3,5,4,5,5,1,0.0,neutral or dissatisfied +75717,66730,Male,Loyal Customer,47,Personal Travel,Eco,802,1,4,0,4,0,3,3,3,3,4,5,3,4,3,139,149.0,neutral or dissatisfied +75718,69523,Female,Loyal Customer,44,Business travel,Business,2586,3,3,3,3,4,4,4,5,2,5,4,4,3,4,47,47.0,satisfied +75719,57067,Male,Loyal Customer,26,Business travel,Business,2065,1,1,1,1,3,3,3,3,4,2,5,4,5,3,10,1.0,satisfied +75720,57147,Male,disloyal Customer,35,Business travel,Business,1824,2,2,2,3,3,2,3,3,4,4,3,4,5,3,3,0.0,neutral or dissatisfied +75721,22977,Male,Loyal Customer,36,Business travel,Business,3931,3,3,4,3,1,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +75722,6342,Male,Loyal Customer,39,Business travel,Business,3528,2,2,3,2,3,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +75723,63799,Female,Loyal Customer,56,Personal Travel,Eco,1721,4,5,5,4,5,5,4,2,2,5,2,3,2,4,0,0.0,neutral or dissatisfied +75724,53541,Female,Loyal Customer,49,Personal Travel,Eco Plus,2419,1,1,0,2,0,4,4,1,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +75725,90163,Female,Loyal Customer,68,Personal Travel,Eco,1084,4,5,3,1,5,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +75726,48639,Female,Loyal Customer,49,Business travel,Business,373,2,3,2,2,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +75727,112506,Female,Loyal Customer,51,Personal Travel,Eco,862,2,4,2,3,5,3,2,1,1,2,1,4,1,2,35,27.0,neutral or dissatisfied +75728,43556,Female,Loyal Customer,58,Business travel,Eco Plus,438,4,3,3,3,1,1,2,4,4,4,4,4,4,4,0,0.0,satisfied +75729,74935,Female,Loyal Customer,45,Business travel,Business,2475,1,1,1,1,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +75730,107851,Male,disloyal Customer,20,Business travel,Eco,228,2,3,2,4,1,2,1,1,3,3,4,3,3,1,12,9.0,neutral or dissatisfied +75731,57453,Female,Loyal Customer,36,Business travel,Business,334,4,4,4,4,4,5,5,4,4,4,4,3,4,4,11,2.0,satisfied +75732,36619,Female,Loyal Customer,48,Business travel,Eco,721,3,4,4,4,1,5,1,3,3,3,3,1,3,4,0,0.0,satisfied +75733,24591,Female,disloyal Customer,21,Business travel,Eco,526,4,0,3,5,4,3,4,4,4,3,5,5,2,4,0,0.0,satisfied +75734,73219,Female,disloyal Customer,17,Business travel,Eco,946,3,3,3,4,3,3,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +75735,119573,Male,Loyal Customer,36,Business travel,Eco Plus,857,2,4,4,4,2,2,2,2,1,1,4,1,4,2,0,0.0,neutral or dissatisfied +75736,98234,Female,Loyal Customer,37,Business travel,Business,1148,5,5,5,5,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +75737,101020,Female,Loyal Customer,47,Personal Travel,Eco,867,2,1,2,4,5,3,3,2,2,2,2,1,2,4,1,7.0,neutral or dissatisfied +75738,73070,Male,Loyal Customer,56,Business travel,Business,1503,4,4,5,4,2,4,4,5,5,5,5,4,5,3,0,5.0,satisfied +75739,113740,Male,Loyal Customer,8,Personal Travel,Eco,236,3,5,3,4,3,3,3,3,3,5,4,4,5,3,5,0.0,neutral or dissatisfied +75740,32880,Female,Loyal Customer,54,Personal Travel,Eco,101,2,3,2,5,1,5,3,4,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +75741,107709,Female,Loyal Customer,47,Business travel,Business,2661,3,4,4,4,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +75742,118044,Male,Loyal Customer,59,Business travel,Business,2104,4,4,4,4,3,4,5,4,4,4,4,3,4,5,4,0.0,satisfied +75743,27538,Male,Loyal Customer,57,Personal Travel,Eco,978,2,4,2,4,5,2,3,5,3,5,5,3,4,5,0,9.0,neutral or dissatisfied +75744,74403,Male,disloyal Customer,23,Business travel,Eco,1205,2,2,2,1,3,2,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +75745,72685,Male,Loyal Customer,60,Personal Travel,Eco,1121,1,4,1,2,4,1,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +75746,31156,Female,Loyal Customer,58,Personal Travel,Eco,495,3,1,3,2,2,2,2,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +75747,121612,Male,Loyal Customer,57,Personal Travel,Eco,936,2,5,2,1,5,2,5,5,3,5,4,4,5,5,0,3.0,neutral or dissatisfied +75748,41441,Female,Loyal Customer,24,Business travel,Eco Plus,913,5,1,1,1,5,5,3,5,3,5,1,5,1,5,0,0.0,satisfied +75749,77153,Male,Loyal Customer,44,Personal Travel,Eco,1865,3,3,3,3,5,3,5,5,3,5,4,1,4,5,0,0.0,neutral or dissatisfied +75750,4287,Male,Loyal Customer,19,Personal Travel,Eco,502,4,4,4,5,2,4,1,2,5,2,4,5,4,2,4,0.0,neutral or dissatisfied +75751,21442,Male,Loyal Customer,30,Business travel,Eco,164,3,3,3,3,3,4,3,3,1,5,3,3,1,3,0,0.0,satisfied +75752,70869,Female,Loyal Customer,51,Personal Travel,Eco,761,2,4,2,2,4,4,5,3,3,2,3,4,3,5,1,0.0,neutral or dissatisfied +75753,30143,Female,Loyal Customer,46,Personal Travel,Eco,571,4,4,4,1,4,5,5,5,5,4,5,3,5,4,23,28.0,neutral or dissatisfied +75754,84309,Male,Loyal Customer,9,Personal Travel,Eco,235,3,4,3,5,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +75755,89489,Male,Loyal Customer,46,Personal Travel,Eco,1931,3,4,3,1,2,3,2,2,3,5,3,5,4,2,0,0.0,neutral or dissatisfied +75756,68952,Male,Loyal Customer,26,Personal Travel,Eco Plus,646,2,5,2,4,5,2,3,5,1,1,5,3,5,5,0,0.0,neutral or dissatisfied +75757,49520,Female,disloyal Customer,20,Business travel,Eco,109,3,3,3,4,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +75758,68463,Male,Loyal Customer,59,Business travel,Business,1303,1,3,1,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +75759,58949,Female,Loyal Customer,67,Personal Travel,Eco Plus,888,3,4,3,3,5,5,4,5,5,3,5,4,5,5,8,2.0,neutral or dissatisfied +75760,68159,Male,Loyal Customer,36,Business travel,Business,603,1,1,1,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +75761,122919,Female,Loyal Customer,52,Personal Travel,Business,631,2,3,2,3,3,3,4,5,5,2,5,5,5,4,0,1.0,neutral or dissatisfied +75762,32887,Male,Loyal Customer,18,Personal Travel,Eco,163,4,5,4,3,3,4,3,3,3,3,4,4,5,3,19,16.0,neutral or dissatisfied +75763,208,Female,disloyal Customer,49,Business travel,Business,213,2,2,2,4,5,2,5,5,4,4,4,3,4,5,20,21.0,neutral or dissatisfied +75764,49564,Female,Loyal Customer,48,Business travel,Business,3689,0,5,0,2,2,4,1,5,5,5,5,5,5,1,0,0.0,satisfied +75765,37125,Male,Loyal Customer,19,Business travel,Business,1046,4,5,5,5,4,3,4,4,1,2,3,1,4,4,31,25.0,neutral or dissatisfied +75766,5271,Male,Loyal Customer,52,Personal Travel,Eco,351,1,3,1,4,2,1,2,2,3,2,3,3,4,2,0,11.0,neutral or dissatisfied +75767,107437,Female,Loyal Customer,63,Personal Travel,Eco,725,4,4,5,5,2,1,4,3,3,5,5,4,3,5,3,0.0,neutral or dissatisfied +75768,35369,Male,disloyal Customer,24,Business travel,Eco,1076,2,2,2,4,3,2,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +75769,84528,Male,disloyal Customer,37,Business travel,Business,2504,4,4,4,3,5,4,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +75770,91147,Male,Loyal Customer,13,Personal Travel,Eco,444,2,5,2,1,3,2,3,3,3,5,5,4,5,3,0,1.0,neutral or dissatisfied +75771,127626,Male,Loyal Customer,52,Business travel,Business,1773,2,5,5,5,4,2,2,2,2,2,2,1,2,3,3,0.0,neutral or dissatisfied +75772,115182,Male,Loyal Customer,50,Business travel,Business,1656,0,0,0,5,4,4,5,2,2,2,2,4,2,5,15,15.0,satisfied +75773,9251,Male,Loyal Customer,12,Personal Travel,Eco,177,4,5,4,1,3,4,3,3,4,4,5,3,4,3,0,6.0,neutral or dissatisfied +75774,86591,Female,Loyal Customer,42,Business travel,Business,2380,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +75775,92810,Female,disloyal Customer,21,Business travel,Business,1587,4,1,4,4,3,4,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +75776,72658,Male,Loyal Customer,27,Personal Travel,Eco,918,4,4,4,2,2,4,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +75777,53934,Male,Loyal Customer,37,Personal Travel,Eco Plus,191,1,4,1,5,2,1,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +75778,47647,Female,Loyal Customer,24,Business travel,Business,1464,2,2,2,2,4,4,4,4,1,4,5,1,3,4,0,0.0,satisfied +75779,26648,Male,Loyal Customer,72,Business travel,Business,3583,1,4,4,4,1,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +75780,7460,Male,Loyal Customer,43,Personal Travel,Eco Plus,522,2,4,2,3,5,2,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +75781,56115,Male,disloyal Customer,44,Business travel,Business,1400,4,4,4,1,2,4,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +75782,99562,Female,Loyal Customer,50,Business travel,Business,1647,4,4,4,4,2,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +75783,64253,Male,Loyal Customer,64,Personal Travel,Eco,1660,2,5,2,3,5,2,5,5,3,2,5,3,5,5,0,44.0,neutral or dissatisfied +75784,95774,Male,Loyal Customer,41,Personal Travel,Eco,419,4,2,4,3,4,4,3,4,1,2,3,1,4,4,20,18.0,neutral or dissatisfied +75785,66558,Female,Loyal Customer,34,Personal Travel,Eco,328,2,0,2,2,4,2,4,4,5,4,4,3,5,4,0,5.0,neutral or dissatisfied +75786,114240,Male,Loyal Customer,48,Business travel,Eco,862,3,1,1,1,3,3,3,3,1,4,4,1,4,3,2,0.0,neutral or dissatisfied +75787,41582,Male,Loyal Customer,39,Personal Travel,Eco,1235,3,2,3,4,5,3,5,5,3,4,4,1,4,5,1,18.0,neutral or dissatisfied +75788,69126,Male,Loyal Customer,9,Personal Travel,Eco,1598,1,4,1,3,4,1,2,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +75789,14693,Female,Loyal Customer,52,Business travel,Eco,419,5,3,2,2,3,5,5,5,5,5,5,3,5,2,0,1.0,satisfied +75790,118480,Male,disloyal Customer,34,Business travel,Business,647,4,4,4,1,2,4,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +75791,3379,Female,disloyal Customer,24,Business travel,Eco,315,3,1,3,3,5,3,5,5,3,3,3,3,3,5,73,109.0,neutral or dissatisfied +75792,44203,Male,Loyal Customer,40,Personal Travel,Eco,157,3,5,3,2,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +75793,35481,Male,Loyal Customer,51,Personal Travel,Eco,972,1,4,1,2,1,1,1,1,4,4,5,3,5,1,5,0.0,neutral or dissatisfied +75794,125302,Male,Loyal Customer,58,Business travel,Eco,278,2,5,5,5,2,2,2,2,2,3,1,2,1,2,9,9.0,neutral or dissatisfied +75795,17082,Male,Loyal Customer,39,Business travel,Eco,416,5,2,2,2,5,5,5,5,4,5,2,1,3,5,0,0.0,satisfied +75796,17719,Male,disloyal Customer,32,Business travel,Eco,382,4,0,4,4,1,4,1,1,3,1,2,3,4,1,81,58.0,neutral or dissatisfied +75797,72813,Male,Loyal Customer,71,Business travel,Eco Plus,645,1,1,1,1,1,1,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +75798,127792,Female,Loyal Customer,62,Business travel,Business,1747,2,2,2,2,2,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +75799,104966,Female,Loyal Customer,38,Business travel,Business,1516,1,1,1,1,3,4,5,4,4,4,4,4,4,4,3,2.0,satisfied +75800,87999,Male,Loyal Customer,44,Business travel,Business,270,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +75801,3678,Male,Loyal Customer,36,Business travel,Eco,431,1,3,3,3,1,1,1,1,4,4,3,2,4,1,7,0.0,neutral or dissatisfied +75802,3042,Male,disloyal Customer,24,Business travel,Eco,489,3,4,3,4,4,3,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +75803,5161,Female,Loyal Customer,53,Business travel,Business,2959,3,3,3,3,5,5,4,5,5,5,5,5,5,3,7,12.0,satisfied +75804,32602,Female,Loyal Customer,40,Business travel,Eco,102,5,1,1,1,5,5,5,5,1,4,4,3,1,5,4,5.0,satisfied +75805,710,Female,Loyal Customer,40,Business travel,Business,158,4,4,4,4,4,5,4,5,4,4,5,4,4,4,116,135.0,satisfied +75806,33275,Female,Loyal Customer,58,Personal Travel,Eco Plus,102,4,4,4,4,4,1,5,1,1,4,1,3,1,2,0,0.0,neutral or dissatisfied +75807,38367,Male,Loyal Customer,17,Personal Travel,Eco,1173,3,4,3,3,4,3,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +75808,85558,Female,Loyal Customer,44,Business travel,Business,3908,4,4,4,4,4,4,5,4,4,4,4,4,4,3,19,10.0,satisfied +75809,9654,Female,Loyal Customer,55,Business travel,Business,2121,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,32.0,satisfied +75810,19761,Female,Loyal Customer,15,Personal Travel,Eco,462,3,5,4,3,2,4,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +75811,52015,Female,Loyal Customer,51,Business travel,Eco,328,3,2,4,4,1,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +75812,15631,Male,Loyal Customer,33,Personal Travel,Eco,296,2,5,3,3,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +75813,79625,Female,Loyal Customer,46,Business travel,Business,712,2,3,3,3,5,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +75814,3640,Male,Loyal Customer,56,Business travel,Business,2289,4,1,4,4,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +75815,93399,Male,Loyal Customer,40,Business travel,Business,672,3,3,5,3,2,5,5,5,5,4,5,4,5,3,27,25.0,satisfied +75816,115034,Male,Loyal Customer,48,Business travel,Business,337,3,3,3,3,2,5,5,3,3,4,3,4,3,4,23,18.0,satisfied +75817,46196,Female,Loyal Customer,36,Personal Travel,Eco,423,3,4,3,4,3,3,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +75818,68361,Male,Loyal Customer,47,Business travel,Business,2072,4,4,4,4,3,5,5,5,5,4,5,4,5,3,0,1.0,satisfied +75819,33567,Male,Loyal Customer,35,Business travel,Business,1864,3,3,3,3,4,5,4,2,2,2,2,2,2,4,0,0.0,satisfied +75820,13322,Female,disloyal Customer,40,Business travel,Business,748,5,5,5,3,4,5,4,4,3,5,4,5,4,4,0,0.0,satisfied +75821,51841,Female,Loyal Customer,21,Personal Travel,Eco Plus,425,2,4,2,3,3,2,5,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +75822,43044,Male,Loyal Customer,32,Business travel,Business,3685,4,4,4,4,4,4,5,4,1,3,4,5,2,4,0,0.0,satisfied +75823,102463,Female,Loyal Customer,21,Personal Travel,Eco,391,2,5,2,1,3,2,1,3,5,5,4,5,5,3,2,0.0,neutral or dissatisfied +75824,47919,Male,Loyal Customer,54,Personal Travel,Eco,817,2,2,2,4,2,2,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +75825,121994,Male,disloyal Customer,25,Business travel,Business,130,1,0,1,4,1,1,1,1,3,4,4,3,4,1,12,21.0,neutral or dissatisfied +75826,92366,Female,disloyal Customer,34,Business travel,Business,1892,3,3,3,3,3,3,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +75827,122977,Male,Loyal Customer,50,Business travel,Business,328,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +75828,8728,Male,Loyal Customer,64,Personal Travel,Eco,304,4,5,4,4,2,4,2,2,2,1,3,3,2,2,0,0.0,satisfied +75829,108918,Male,disloyal Customer,47,Business travel,Eco,675,2,2,2,3,5,2,5,5,1,4,4,3,3,5,13,14.0,neutral or dissatisfied +75830,29306,Female,Loyal Customer,44,Personal Travel,Eco,933,2,4,1,1,3,4,4,5,5,1,5,4,5,5,1,0.0,neutral or dissatisfied +75831,90167,Female,Loyal Customer,48,Personal Travel,Eco,1145,2,1,2,3,2,4,4,4,4,2,4,3,4,1,0,5.0,neutral or dissatisfied +75832,115887,Female,disloyal Customer,37,Business travel,Eco,480,2,4,2,4,3,2,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +75833,124433,Male,Loyal Customer,63,Personal Travel,Eco,1262,2,1,2,1,2,2,1,2,4,5,2,1,1,2,0,0.0,neutral or dissatisfied +75834,109318,Female,Loyal Customer,9,Personal Travel,Eco,1072,4,5,4,4,3,4,3,3,4,2,4,5,4,3,37,33.0,neutral or dissatisfied +75835,91544,Female,disloyal Customer,36,Business travel,Eco,680,1,2,2,3,5,2,5,5,3,4,3,2,4,5,0,13.0,neutral or dissatisfied +75836,54277,Male,Loyal Customer,53,Personal Travel,Eco,1222,5,3,5,3,2,5,4,2,1,2,4,1,4,2,0,0.0,satisfied +75837,101919,Female,Loyal Customer,15,Business travel,Eco Plus,2173,3,5,5,5,3,3,1,3,2,4,2,4,4,3,0,0.0,neutral or dissatisfied +75838,89688,Female,Loyal Customer,42,Business travel,Business,689,1,1,1,1,2,2,3,4,4,4,4,1,4,2,113,120.0,satisfied +75839,18752,Female,Loyal Customer,27,Personal Travel,Eco,1167,1,5,1,1,3,1,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +75840,43488,Male,Loyal Customer,41,Business travel,Business,3718,0,1,1,3,1,2,2,5,5,5,5,1,5,3,2,0.0,satisfied +75841,48346,Female,Loyal Customer,22,Business travel,Eco,522,5,2,2,2,5,5,5,5,2,2,2,2,2,5,0,21.0,satisfied +75842,111941,Female,disloyal Customer,37,Business travel,Business,533,2,2,2,1,5,2,5,5,4,3,5,4,4,5,1,0.0,neutral or dissatisfied +75843,102412,Female,Loyal Customer,7,Personal Travel,Eco,236,1,5,1,4,3,1,3,3,2,2,1,3,4,3,0,0.0,neutral or dissatisfied +75844,105914,Male,Loyal Customer,19,Personal Travel,Eco,283,2,4,2,1,1,2,2,1,1,4,5,2,5,1,0,0.0,neutral or dissatisfied +75845,29100,Female,Loyal Customer,36,Personal Travel,Eco,987,3,4,2,2,2,2,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +75846,42653,Female,disloyal Customer,36,Business travel,Eco Plus,223,2,3,3,4,3,3,3,3,4,1,3,2,4,3,11,1.0,neutral or dissatisfied +75847,10196,Male,disloyal Customer,23,Business travel,Business,166,0,2,0,3,2,2,2,2,4,3,4,3,4,2,0,0.0,satisfied +75848,127208,Female,disloyal Customer,37,Business travel,Eco Plus,251,1,1,1,3,1,1,1,1,3,4,3,4,3,1,13,11.0,neutral or dissatisfied +75849,24933,Male,Loyal Customer,34,Business travel,Business,2106,1,2,1,1,4,5,4,4,4,4,4,1,4,3,6,0.0,satisfied +75850,18803,Male,disloyal Customer,24,Business travel,Eco,448,4,3,4,3,5,4,5,5,3,2,3,1,5,5,0,0.0,neutral or dissatisfied +75851,21613,Female,Loyal Customer,46,Business travel,Eco,780,5,3,1,3,1,5,2,4,4,5,4,1,4,4,4,13.0,satisfied +75852,89239,Male,Loyal Customer,9,Business travel,Eco Plus,1892,1,2,2,2,1,1,2,1,4,4,4,4,3,1,5,12.0,neutral or dissatisfied +75853,52146,Female,Loyal Customer,39,Business travel,Business,3759,3,2,2,2,5,2,2,3,3,3,3,2,3,3,78,72.0,neutral or dissatisfied +75854,104095,Female,Loyal Customer,52,Business travel,Eco Plus,188,5,5,5,5,1,1,4,5,5,5,5,2,5,3,0,0.0,satisfied +75855,20015,Female,Loyal Customer,59,Personal Travel,Eco,589,3,5,3,4,2,5,4,1,1,3,1,3,1,5,46,42.0,neutral or dissatisfied +75856,28458,Male,Loyal Customer,40,Personal Travel,Eco,2588,4,5,4,4,4,5,5,3,4,5,5,5,4,5,0,0.0,satisfied +75857,69645,Male,Loyal Customer,59,Business travel,Business,569,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +75858,100578,Female,disloyal Customer,22,Business travel,Business,486,5,0,4,3,1,4,1,1,5,3,5,5,4,1,24,14.0,satisfied +75859,67794,Male,Loyal Customer,48,Business travel,Business,1698,4,1,2,1,4,2,2,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +75860,78432,Female,Loyal Customer,52,Personal Travel,Business,666,4,4,4,4,2,3,3,4,4,4,4,5,4,3,0,10.0,neutral or dissatisfied +75861,81262,Female,Loyal Customer,58,Business travel,Business,2299,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +75862,46747,Male,Loyal Customer,14,Personal Travel,Eco,125,3,4,0,3,1,0,1,1,2,5,4,2,3,1,0,0.0,neutral or dissatisfied +75863,98085,Female,disloyal Customer,23,Business travel,Eco,928,3,3,3,3,2,3,4,2,2,2,4,2,4,2,11,17.0,neutral or dissatisfied +75864,58568,Female,Loyal Customer,42,Business travel,Business,3608,4,2,4,4,2,4,5,5,5,5,5,4,5,4,19,58.0,satisfied +75865,107075,Female,Loyal Customer,60,Personal Travel,Eco,480,2,5,3,4,4,1,3,5,5,3,5,1,5,1,37,29.0,neutral or dissatisfied +75866,69558,Female,Loyal Customer,23,Business travel,Business,2475,2,5,4,5,2,2,2,3,5,1,2,2,1,2,0,5.0,neutral or dissatisfied +75867,47353,Male,Loyal Customer,49,Business travel,Business,2328,2,3,5,5,4,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +75868,122085,Female,Loyal Customer,36,Personal Travel,Eco,130,4,4,4,3,4,4,4,4,3,3,3,4,4,4,2,0.0,satisfied +75869,72096,Female,Loyal Customer,64,Personal Travel,Eco,2504,3,4,3,3,3,2,4,2,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +75870,12934,Male,Loyal Customer,59,Personal Travel,Eco,563,5,4,5,5,3,5,2,3,3,4,4,5,5,3,2,3.0,satisfied +75871,114038,Female,disloyal Customer,22,Business travel,Eco,511,2,0,2,4,1,2,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +75872,54155,Female,Loyal Customer,37,Business travel,Eco,1400,2,5,4,5,2,2,2,2,2,3,4,1,4,2,17,36.0,neutral or dissatisfied +75873,24607,Male,Loyal Customer,29,Business travel,Business,2601,3,2,2,2,3,3,3,3,4,2,4,2,4,3,0,13.0,neutral or dissatisfied +75874,77393,Male,Loyal Customer,25,Personal Travel,Eco,599,3,5,4,3,5,4,5,5,2,5,1,5,4,5,0,0.0,neutral or dissatisfied +75875,57565,Male,Loyal Customer,40,Business travel,Business,1597,4,4,4,4,5,5,5,3,3,3,3,5,3,5,15,21.0,satisfied +75876,80810,Female,Loyal Customer,22,Business travel,Business,484,3,2,2,2,3,3,3,3,4,5,3,1,4,3,2,0.0,neutral or dissatisfied +75877,2052,Male,Loyal Customer,27,Business travel,Business,2341,3,3,3,3,4,4,4,4,5,4,5,3,5,4,0,0.0,satisfied +75878,14784,Female,Loyal Customer,27,Business travel,Eco Plus,694,4,1,1,1,4,4,4,4,3,2,5,2,5,4,0,0.0,satisfied +75879,117901,Male,disloyal Customer,36,Business travel,Business,255,2,3,3,4,4,3,4,4,5,3,5,5,5,4,7,7.0,neutral or dissatisfied +75880,33243,Female,disloyal Customer,24,Business travel,Business,201,3,1,3,4,3,3,3,3,2,4,4,3,4,3,28,30.0,neutral or dissatisfied +75881,35154,Female,Loyal Customer,29,Business travel,Business,944,4,4,4,4,4,4,4,4,3,2,1,1,1,4,3,0.0,satisfied +75882,23444,Female,Loyal Customer,49,Business travel,Eco,488,4,1,4,1,5,3,3,4,4,4,4,4,4,2,0,6.0,satisfied +75883,124476,Female,Loyal Customer,50,Business travel,Business,1555,3,5,3,3,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +75884,7050,Female,Loyal Customer,42,Business travel,Business,3525,2,2,2,2,3,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +75885,118286,Female,Loyal Customer,54,Business travel,Business,3389,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +75886,61474,Female,Loyal Customer,51,Business travel,Business,2358,3,5,5,5,3,3,3,3,1,2,3,3,2,3,282,255.0,neutral or dissatisfied +75887,29172,Male,Loyal Customer,16,Business travel,Eco Plus,671,4,2,2,2,4,4,5,4,5,4,5,2,3,4,0,1.0,satisfied +75888,62332,Male,Loyal Customer,26,Personal Travel,Eco,414,1,5,1,1,1,1,1,1,4,3,1,3,3,1,7,3.0,neutral or dissatisfied +75889,118622,Female,disloyal Customer,32,Business travel,Eco,451,4,1,5,3,3,5,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +75890,70689,Female,Loyal Customer,46,Personal Travel,Eco,447,2,4,2,2,3,3,1,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +75891,88834,Male,Loyal Customer,13,Personal Travel,Eco Plus,406,2,4,2,2,2,2,2,2,5,5,4,5,4,2,1,0.0,neutral or dissatisfied +75892,49182,Male,disloyal Customer,63,Business travel,Eco,89,3,0,2,1,1,2,1,1,1,5,5,4,4,1,0,0.0,neutral or dissatisfied +75893,46076,Female,Loyal Customer,23,Business travel,Business,1939,5,5,2,5,4,4,4,4,5,5,5,5,1,4,31,63.0,satisfied +75894,110118,Female,Loyal Customer,60,Business travel,Eco,869,3,5,5,5,4,3,3,3,3,3,3,3,3,3,24,35.0,neutral or dissatisfied +75895,68170,Male,Loyal Customer,52,Business travel,Business,2238,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +75896,46649,Female,Loyal Customer,41,Business travel,Business,1582,4,4,4,4,2,1,3,4,4,4,3,3,4,5,0,0.0,satisfied +75897,103213,Male,Loyal Customer,52,Business travel,Business,3999,2,2,5,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +75898,78715,Male,Loyal Customer,44,Business travel,Business,3630,2,2,2,2,2,4,5,4,4,4,4,4,4,4,60,57.0,satisfied +75899,73113,Male,Loyal Customer,41,Business travel,Eco,2174,2,2,4,2,2,2,2,2,1,5,1,1,2,2,0,3.0,neutral or dissatisfied +75900,47817,Female,Loyal Customer,47,Business travel,Eco,784,5,3,3,3,2,3,4,5,5,5,5,3,5,2,33,26.0,satisfied +75901,16466,Male,Loyal Customer,24,Personal Travel,Eco,529,2,4,2,2,4,2,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +75902,20066,Female,Loyal Customer,8,Personal Travel,Eco,528,3,4,3,3,3,3,3,3,4,3,5,5,4,3,0,11.0,neutral or dissatisfied +75903,127587,Male,Loyal Customer,51,Business travel,Business,1773,2,2,2,2,3,4,5,5,5,5,5,3,5,3,7,8.0,satisfied +75904,82098,Female,Loyal Customer,33,Business travel,Business,1592,2,5,3,5,1,3,3,2,2,2,2,4,2,3,0,13.0,neutral or dissatisfied +75905,38267,Female,Loyal Customer,16,Business travel,Business,2714,1,3,3,3,1,1,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +75906,43904,Female,Loyal Customer,25,Personal Travel,Eco,114,2,3,2,1,3,2,1,3,4,4,4,1,2,3,3,23.0,neutral or dissatisfied +75907,82117,Male,Loyal Customer,66,Personal Travel,Eco,1276,3,5,3,1,5,3,5,5,4,2,3,5,4,5,0,0.0,neutral or dissatisfied +75908,76571,Female,Loyal Customer,14,Business travel,Business,3421,2,1,1,1,2,2,2,2,3,2,3,2,4,2,1,0.0,neutral or dissatisfied +75909,16046,Male,Loyal Customer,44,Business travel,Eco,833,4,2,2,2,4,4,4,4,4,3,3,4,2,4,246,247.0,neutral or dissatisfied +75910,36288,Female,Loyal Customer,15,Personal Travel,Business,395,3,4,3,2,5,3,4,5,5,2,1,2,3,5,0,0.0,neutral or dissatisfied +75911,121748,Female,Loyal Customer,60,Personal Travel,Eco Plus,1475,1,5,1,3,2,5,4,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +75912,104211,Female,Loyal Customer,50,Business travel,Business,2035,1,1,1,1,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +75913,49484,Male,Loyal Customer,43,Business travel,Business,1516,5,5,3,5,3,5,2,4,4,5,3,2,4,4,0,0.0,satisfied +75914,84922,Male,Loyal Customer,17,Personal Travel,Eco,516,3,5,3,1,1,3,1,1,3,4,4,3,5,1,86,73.0,neutral or dissatisfied +75915,93498,Male,disloyal Customer,36,Business travel,Eco,1020,2,2,2,2,3,2,3,3,3,2,2,4,2,3,20,17.0,neutral or dissatisfied +75916,21758,Male,Loyal Customer,41,Personal Travel,Eco Plus,563,2,4,2,4,2,2,2,2,5,5,5,3,4,2,23,24.0,neutral or dissatisfied +75917,113092,Male,disloyal Customer,17,Business travel,Eco,543,2,1,3,4,5,3,5,5,2,3,4,4,3,5,0,0.0,neutral or dissatisfied +75918,55693,Male,Loyal Customer,56,Business travel,Business,895,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,5.0,satisfied +75919,48580,Female,Loyal Customer,70,Personal Travel,Eco,850,2,5,2,4,2,4,2,4,3,4,4,2,4,2,135,150.0,neutral or dissatisfied +75920,58787,Female,Loyal Customer,36,Business travel,Eco,1012,1,3,4,3,1,1,1,1,4,4,3,1,3,1,3,0.0,neutral or dissatisfied +75921,36196,Female,disloyal Customer,24,Business travel,Eco,280,4,0,4,4,3,4,3,3,5,2,4,5,4,3,0,26.0,satisfied +75922,119015,Female,Loyal Customer,35,Personal Travel,Eco Plus,459,4,4,2,5,3,2,3,3,3,4,5,5,5,3,0,17.0,neutral or dissatisfied +75923,107510,Male,Loyal Customer,60,Business travel,Business,838,1,4,4,4,1,2,2,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +75924,126596,Female,disloyal Customer,22,Business travel,Eco,1337,1,1,1,3,5,1,5,5,2,3,3,4,3,5,23,17.0,neutral or dissatisfied +75925,46495,Male,Loyal Customer,61,Business travel,Eco,125,4,1,1,1,4,4,4,4,3,4,3,2,5,4,16,14.0,satisfied +75926,100009,Female,disloyal Customer,39,Business travel,Business,281,4,4,4,3,3,4,3,3,4,3,4,5,4,3,24,20.0,neutral or dissatisfied +75927,114993,Female,Loyal Customer,25,Business travel,Eco,308,1,4,4,4,1,1,3,1,1,3,3,3,4,1,0,13.0,neutral or dissatisfied +75928,59774,Male,Loyal Customer,38,Business travel,Business,3463,5,5,5,5,1,4,5,5,5,5,5,2,5,2,0,0.0,satisfied +75929,30726,Male,Loyal Customer,52,Business travel,Business,1727,4,4,3,4,3,1,5,4,4,4,4,5,4,3,0,5.0,satisfied +75930,30355,Male,disloyal Customer,29,Business travel,Eco,641,2,5,2,2,5,2,5,5,3,4,1,4,2,5,57,58.0,neutral or dissatisfied +75931,27668,Male,Loyal Customer,42,Business travel,Eco,1216,2,3,2,3,3,2,3,3,5,2,2,4,2,3,0,0.0,satisfied +75932,88396,Female,disloyal Customer,32,Business travel,Business,404,2,3,3,5,5,3,1,5,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +75933,23612,Male,Loyal Customer,57,Personal Travel,Eco Plus,589,2,4,2,3,5,2,5,5,2,2,1,2,3,5,65,60.0,neutral or dissatisfied +75934,107889,Male,Loyal Customer,26,Business travel,Business,1621,5,5,5,5,2,2,2,2,3,2,5,5,5,2,0,0.0,satisfied +75935,69190,Female,Loyal Customer,42,Personal Travel,Eco,187,3,1,0,2,1,2,2,4,4,0,4,1,4,1,0,0.0,neutral or dissatisfied +75936,114304,Male,Loyal Customer,16,Personal Travel,Eco,957,5,5,4,1,5,4,5,5,5,5,5,5,4,5,0,0.0,satisfied +75937,25607,Male,disloyal Customer,25,Business travel,Eco,666,1,0,1,1,2,1,5,2,4,1,3,1,1,2,18,18.0,neutral or dissatisfied +75938,12831,Male,disloyal Customer,17,Business travel,Eco,817,0,0,0,2,5,0,5,5,4,3,5,4,4,5,1,0.0,satisfied +75939,126991,Male,Loyal Customer,42,Business travel,Eco,304,3,2,5,5,3,3,3,3,2,4,3,4,4,3,0,0.0,neutral or dissatisfied +75940,90717,Male,Loyal Customer,44,Business travel,Business,515,2,2,2,2,2,4,4,4,4,4,4,5,4,4,1,1.0,satisfied +75941,87290,Male,disloyal Customer,37,Personal Travel,Eco,577,5,4,5,1,1,5,1,1,5,2,5,5,4,1,20,24.0,satisfied +75942,116688,Male,Loyal Customer,36,Business travel,Eco Plus,337,3,1,3,3,3,3,3,3,1,1,2,2,3,3,9,10.0,neutral or dissatisfied +75943,31830,Female,disloyal Customer,42,Business travel,Eco,908,1,1,1,4,1,1,1,3,5,2,4,1,4,1,0,61.0,neutral or dissatisfied +75944,50978,Male,Loyal Customer,40,Personal Travel,Eco,158,3,5,3,2,5,3,1,5,5,3,1,1,1,5,96,81.0,neutral or dissatisfied +75945,17904,Female,Loyal Customer,25,Business travel,Business,900,4,4,4,4,5,5,5,5,3,1,3,2,5,5,33,16.0,satisfied +75946,108507,Male,Loyal Customer,49,Business travel,Business,519,5,5,5,5,5,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +75947,21249,Female,disloyal Customer,23,Business travel,Eco,317,3,0,3,4,1,3,1,1,1,3,3,3,4,1,67,57.0,neutral or dissatisfied +75948,120178,Female,Loyal Customer,41,Business travel,Business,1927,1,1,1,1,2,3,5,2,2,2,2,3,2,5,0,0.0,satisfied +75949,62404,Female,Loyal Customer,10,Personal Travel,Eco,2704,2,3,2,4,3,2,3,3,1,5,4,3,3,3,1,0.0,neutral or dissatisfied +75950,24423,Female,disloyal Customer,30,Business travel,Eco,634,3,2,3,3,3,4,4,4,5,3,4,4,2,4,141,150.0,neutral or dissatisfied +75951,129731,Female,Loyal Customer,51,Business travel,Business,337,1,1,1,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +75952,21227,Male,Loyal Customer,58,Personal Travel,Eco,192,2,5,2,1,1,2,3,1,4,3,4,4,4,1,26,23.0,neutral or dissatisfied +75953,12051,Male,disloyal Customer,27,Business travel,Eco,376,2,1,2,4,4,2,2,4,2,2,4,2,3,4,82,84.0,neutral or dissatisfied +75954,82893,Female,Loyal Customer,39,Personal Travel,Eco,645,3,4,3,2,4,3,3,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +75955,11960,Male,Loyal Customer,57,Business travel,Business,643,2,2,3,2,2,4,4,4,4,4,4,3,4,3,33,24.0,satisfied +75956,28892,Female,Loyal Customer,22,Business travel,Business,937,3,1,1,1,3,3,3,3,2,5,3,1,3,3,25,10.0,neutral or dissatisfied +75957,83964,Female,Loyal Customer,43,Business travel,Business,2572,3,2,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +75958,88848,Male,Loyal Customer,46,Personal Travel,Eco Plus,594,4,5,3,4,5,3,5,5,2,3,5,4,4,5,0,0.0,neutral or dissatisfied +75959,2099,Male,Loyal Customer,11,Personal Travel,Eco,812,3,1,3,4,2,3,2,2,1,5,3,1,4,2,45,42.0,neutral or dissatisfied +75960,6800,Male,Loyal Customer,66,Business travel,Business,3031,2,4,4,4,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +75961,46685,Male,Loyal Customer,61,Personal Travel,Eco,125,3,4,3,4,3,3,3,3,1,3,3,1,3,3,67,71.0,neutral or dissatisfied +75962,71449,Female,Loyal Customer,46,Business travel,Business,867,2,2,2,2,4,3,4,2,2,2,2,4,2,3,0,13.0,neutral or dissatisfied +75963,61135,Male,Loyal Customer,40,Business travel,Business,967,5,5,5,5,3,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +75964,98249,Male,Loyal Customer,32,Business travel,Business,2171,3,3,3,3,4,4,4,4,5,2,5,4,4,4,0,12.0,satisfied +75965,3360,Male,Loyal Customer,44,Business travel,Business,213,0,4,0,5,5,4,4,5,5,5,5,5,5,3,0,5.0,satisfied +75966,39429,Female,Loyal Customer,40,Business travel,Eco,129,4,1,1,1,4,4,4,4,2,3,3,2,3,4,19,25.0,neutral or dissatisfied +75967,78875,Female,disloyal Customer,37,Business travel,Eco,223,2,1,2,4,4,2,3,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +75968,15673,Female,Loyal Customer,27,Business travel,Business,1740,3,3,3,3,2,3,2,2,5,4,4,2,1,2,4,0.0,satisfied +75969,89825,Female,Loyal Customer,48,Personal Travel,Eco Plus,1076,3,2,3,3,3,4,3,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +75970,61016,Male,Loyal Customer,31,Business travel,Business,3365,2,2,2,2,4,4,4,3,3,3,5,4,3,4,61,78.0,satisfied +75971,92762,Female,Loyal Customer,67,Business travel,Eco Plus,1276,1,2,4,2,5,4,3,1,1,1,1,2,1,2,33,33.0,neutral or dissatisfied +75972,70316,Female,Loyal Customer,40,Business travel,Business,1501,4,4,5,4,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +75973,23848,Male,Loyal Customer,35,Business travel,Business,3175,3,4,4,4,1,4,3,3,3,3,3,2,3,1,0,11.0,neutral or dissatisfied +75974,67216,Male,Loyal Customer,47,Personal Travel,Eco,1119,2,4,2,4,4,2,4,4,1,5,3,4,4,4,56,60.0,neutral or dissatisfied +75975,80071,Male,Loyal Customer,40,Business travel,Business,4000,3,3,3,3,4,5,4,4,4,4,4,3,4,5,2,3.0,satisfied +75976,43290,Female,Loyal Customer,56,Business travel,Eco,436,5,3,3,3,5,4,3,4,4,5,4,3,4,1,0,0.0,satisfied +75977,50762,Female,Loyal Customer,28,Personal Travel,Eco,110,2,1,2,3,4,2,4,4,4,1,4,2,3,4,0,0.0,neutral or dissatisfied +75978,4908,Male,Loyal Customer,46,Business travel,Business,2859,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +75979,70484,Male,Loyal Customer,12,Business travel,Business,867,5,5,5,5,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +75980,32214,Male,Loyal Customer,49,Business travel,Business,2342,0,4,0,3,3,3,1,1,1,1,1,4,1,5,0,3.0,satisfied +75981,64043,Male,Loyal Customer,26,Business travel,Business,919,2,2,1,2,5,5,5,5,3,4,5,3,5,5,0,6.0,satisfied +75982,58860,Male,disloyal Customer,11,Business travel,Eco,888,3,3,3,4,1,3,1,1,1,4,3,1,4,1,31,64.0,neutral or dissatisfied +75983,59411,Female,Loyal Customer,55,Personal Travel,Eco,2367,2,5,1,4,3,4,5,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +75984,48382,Male,Loyal Customer,53,Personal Travel,Eco,674,1,5,1,2,4,1,4,4,3,4,4,5,5,4,45,41.0,neutral or dissatisfied +75985,34664,Male,Loyal Customer,41,Business travel,Business,301,2,1,1,1,3,4,4,2,2,2,2,1,2,2,6,21.0,neutral or dissatisfied +75986,12715,Female,Loyal Customer,25,Business travel,Eco,689,3,1,1,1,3,3,3,3,3,4,4,1,4,3,27,18.0,neutral or dissatisfied +75987,27540,Female,Loyal Customer,50,Personal Travel,Eco,954,0,4,0,1,2,5,5,2,2,0,2,5,2,3,0,1.0,satisfied +75988,61285,Female,Loyal Customer,15,Personal Travel,Eco,967,3,4,3,2,3,3,3,3,3,3,4,3,4,3,0,52.0,neutral or dissatisfied +75989,16008,Male,disloyal Customer,25,Business travel,Eco,780,3,3,3,3,1,3,1,1,2,3,3,3,3,1,3,7.0,neutral or dissatisfied +75990,90841,Female,disloyal Customer,21,Business travel,Eco,545,1,0,1,4,4,1,4,4,3,4,4,4,5,4,0,4.0,neutral or dissatisfied +75991,85456,Male,Loyal Customer,44,Business travel,Business,3416,2,2,2,2,1,3,3,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +75992,45758,Female,disloyal Customer,28,Business travel,Eco,391,2,3,2,1,1,2,1,1,2,2,5,2,5,1,18,42.0,neutral or dissatisfied +75993,103488,Female,Loyal Customer,56,Personal Travel,Eco,440,2,5,2,2,3,4,5,2,2,2,2,3,2,5,10,1.0,neutral or dissatisfied +75994,104182,Female,Loyal Customer,60,Personal Travel,Eco,349,2,5,2,2,4,5,2,1,1,2,1,5,1,2,13,19.0,neutral or dissatisfied +75995,74058,Male,Loyal Customer,33,Business travel,Business,2527,1,1,5,1,5,5,5,3,5,3,4,5,3,5,0,0.0,satisfied +75996,45574,Female,disloyal Customer,38,Business travel,Business,406,2,2,2,1,4,2,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +75997,128503,Female,Loyal Customer,60,Personal Travel,Eco,621,4,4,4,2,2,5,4,4,4,4,4,3,4,4,10,5.0,neutral or dissatisfied +75998,80445,Female,Loyal Customer,16,Personal Travel,Eco Plus,2248,3,3,3,4,2,3,4,2,1,4,5,2,5,2,0,0.0,neutral or dissatisfied +75999,71459,Male,Loyal Customer,46,Personal Travel,Eco,867,4,3,4,4,4,4,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +76000,112336,Male,Loyal Customer,52,Business travel,Business,3743,1,1,5,1,4,5,4,3,3,4,3,3,3,5,1,0.0,satisfied +76001,50329,Male,Loyal Customer,51,Business travel,Business,3455,0,1,1,3,2,2,3,3,3,3,3,2,3,4,10,2.0,satisfied +76002,61140,Female,Loyal Customer,60,Business travel,Business,862,1,1,1,1,3,5,4,5,5,5,5,3,5,4,5,0.0,satisfied +76003,68015,Male,Loyal Customer,32,Business travel,Eco,304,1,5,5,5,1,1,1,1,1,3,3,1,4,1,16,20.0,neutral or dissatisfied +76004,59308,Female,Loyal Customer,44,Business travel,Business,2504,4,4,4,4,4,5,5,5,5,5,5,4,5,3,14,0.0,satisfied +76005,75754,Male,Loyal Customer,37,Business travel,Business,3162,2,2,3,2,4,3,1,5,5,5,5,2,5,3,0,0.0,satisfied +76006,47188,Male,Loyal Customer,14,Business travel,Eco,679,2,2,4,4,2,2,2,2,2,1,3,1,3,2,50,37.0,neutral or dissatisfied +76007,117850,Female,Loyal Customer,64,Personal Travel,Eco,2133,5,2,5,4,2,4,4,1,1,5,1,1,1,4,8,0.0,satisfied +76008,24714,Male,Loyal Customer,38,Business travel,Business,549,3,5,5,5,4,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +76009,16173,Male,Loyal Customer,53,Business travel,Eco,212,3,2,2,2,3,3,3,3,2,3,4,4,3,3,0,8.0,neutral or dissatisfied +76010,23220,Female,Loyal Customer,8,Personal Travel,Eco,326,3,1,3,3,1,3,1,1,1,4,2,1,4,1,0,0.0,neutral or dissatisfied +76011,45942,Female,Loyal Customer,23,Personal Travel,Eco,809,2,5,2,5,1,2,1,1,1,5,4,1,5,1,0,0.0,neutral or dissatisfied +76012,37656,Female,Loyal Customer,68,Personal Travel,Eco,1076,2,4,2,3,5,5,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +76013,38284,Male,Loyal Customer,53,Personal Travel,Eco,1133,2,4,2,1,5,2,5,5,4,5,3,4,5,5,0,0.0,neutral or dissatisfied +76014,63602,Female,Loyal Customer,31,Personal Travel,Business,1440,4,4,3,1,3,3,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +76015,103277,Male,Loyal Customer,57,Personal Travel,Eco Plus,888,4,4,4,4,2,4,4,2,4,3,5,4,5,2,2,8.0,neutral or dissatisfied +76016,108035,Male,Loyal Customer,50,Personal Travel,Eco,306,3,2,3,4,5,3,3,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +76017,23802,Male,Loyal Customer,46,Business travel,Business,2341,2,2,2,2,5,3,4,5,5,5,5,2,5,1,0,0.0,satisfied +76018,65921,Male,Loyal Customer,33,Business travel,Business,3547,2,1,1,1,2,2,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +76019,22993,Female,Loyal Customer,36,Personal Travel,Eco,489,2,4,2,1,5,2,5,5,4,4,4,4,4,5,4,9.0,neutral or dissatisfied +76020,13810,Male,Loyal Customer,41,Business travel,Business,617,5,5,5,5,4,4,1,4,4,4,4,5,4,2,0,0.0,satisfied +76021,5840,Female,Loyal Customer,68,Personal Travel,Eco Plus,157,5,4,5,2,4,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +76022,4884,Female,Loyal Customer,37,Personal Travel,Eco,408,4,1,3,4,2,3,2,2,3,4,3,1,3,2,0,16.0,neutral or dissatisfied +76023,17925,Male,Loyal Customer,46,Personal Travel,Eco,789,3,5,3,3,1,3,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +76024,21253,Male,Loyal Customer,37,Personal Travel,Eco Plus,192,4,4,0,1,4,0,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +76025,100332,Female,disloyal Customer,38,Business travel,Eco,1073,2,2,2,3,1,2,3,1,2,5,3,4,2,1,0,0.0,neutral or dissatisfied +76026,52194,Female,Loyal Customer,58,Business travel,Business,2960,4,4,4,4,2,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +76027,55862,Female,Loyal Customer,50,Personal Travel,Eco,419,3,2,3,2,4,3,3,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +76028,25901,Male,Loyal Customer,39,Personal Travel,Eco,907,3,4,3,4,2,3,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +76029,8850,Male,Loyal Customer,46,Business travel,Eco,451,3,5,5,5,3,3,3,3,1,3,1,4,1,3,10,21.0,neutral or dissatisfied +76030,86559,Male,disloyal Customer,37,Business travel,Eco Plus,453,2,2,2,4,5,2,2,5,2,2,3,4,4,5,31,37.0,neutral or dissatisfied +76031,72636,Male,Loyal Customer,55,Personal Travel,Eco,1121,1,4,0,4,5,0,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +76032,30419,Female,Loyal Customer,60,Business travel,Business,1014,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,11.0,satisfied +76033,39107,Female,Loyal Customer,39,Business travel,Business,190,0,3,0,5,2,3,3,2,2,2,2,3,2,5,0,5.0,satisfied +76034,94872,Female,Loyal Customer,25,Business travel,Business,293,3,1,1,1,3,3,3,3,3,5,4,2,3,3,1,2.0,neutral or dissatisfied +76035,6101,Male,Loyal Customer,28,Business travel,Business,3086,1,1,1,1,5,5,5,5,3,5,4,5,4,5,4,0.0,satisfied +76036,126758,Male,Loyal Customer,60,Personal Travel,Eco,2402,1,0,1,1,2,1,2,2,3,3,4,3,4,2,14,11.0,neutral or dissatisfied +76037,33136,Female,Loyal Customer,12,Personal Travel,Eco,163,3,3,3,3,4,3,4,4,3,4,5,3,3,4,0,0.0,neutral or dissatisfied +76038,29406,Female,Loyal Customer,65,Personal Travel,Eco,2466,3,4,3,2,3,1,1,3,4,3,4,1,5,1,0,46.0,neutral or dissatisfied +76039,109075,Male,Loyal Customer,44,Personal Travel,Eco,957,2,5,2,2,4,2,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +76040,109227,Male,Loyal Customer,26,Personal Travel,Eco,612,3,5,3,4,4,3,4,4,3,4,3,2,4,4,5,0.0,neutral or dissatisfied +76041,101521,Female,Loyal Customer,66,Personal Travel,Eco,345,1,4,1,3,4,5,4,2,2,1,2,3,2,3,18,19.0,neutral or dissatisfied +76042,87864,Female,Loyal Customer,47,Personal Travel,Eco,214,3,3,0,4,2,4,3,2,2,0,2,2,2,1,0,0.0,neutral or dissatisfied +76043,93301,Female,Loyal Customer,34,Business travel,Business,1733,4,4,4,4,5,4,5,4,4,4,4,5,4,4,7,0.0,satisfied +76044,52799,Male,Loyal Customer,66,Personal Travel,Eco,1874,3,3,3,4,3,3,2,3,2,4,4,2,4,3,8,0.0,neutral or dissatisfied +76045,122057,Female,Loyal Customer,40,Business travel,Eco,130,2,4,4,4,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +76046,41253,Male,Loyal Customer,25,Business travel,Eco,852,0,5,0,4,3,0,3,3,1,2,1,4,3,3,0,0.0,satisfied +76047,110359,Female,disloyal Customer,54,Business travel,Eco,919,2,2,2,1,1,2,1,1,2,3,1,3,1,1,22,7.0,neutral or dissatisfied +76048,84493,Female,Loyal Customer,17,Personal Travel,Eco,2994,1,4,1,3,4,1,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +76049,87035,Male,disloyal Customer,40,Business travel,Business,594,1,0,0,1,1,0,1,1,3,5,5,4,5,1,25,9.0,neutral or dissatisfied +76050,66101,Female,Loyal Customer,23,Personal Travel,Business,583,1,4,2,1,3,2,3,3,5,2,5,4,5,3,17,19.0,neutral or dissatisfied +76051,2881,Female,Loyal Customer,14,Personal Travel,Eco,491,1,2,2,3,1,2,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +76052,12979,Male,Loyal Customer,45,Business travel,Business,3392,3,3,3,3,2,4,2,4,4,4,4,2,4,5,0,0.0,satisfied +76053,25761,Female,Loyal Customer,42,Personal Travel,Eco,356,4,3,4,3,1,3,3,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +76054,16072,Male,disloyal Customer,21,Business travel,Eco,501,1,5,1,4,4,1,4,4,5,2,3,5,1,4,0,0.0,neutral or dissatisfied +76055,108050,Male,Loyal Customer,14,Personal Travel,Eco,591,3,4,3,3,4,3,1,4,1,5,2,3,3,4,20,8.0,neutral or dissatisfied +76056,106001,Male,Loyal Customer,39,Business travel,Eco,1999,3,4,4,4,3,3,3,3,4,4,3,1,3,3,13,8.0,neutral or dissatisfied +76057,82749,Female,disloyal Customer,20,Business travel,Eco,409,3,1,3,4,1,3,1,1,3,4,3,3,4,1,7,0.0,neutral or dissatisfied +76058,20189,Male,Loyal Customer,57,Personal Travel,Eco Plus,403,3,5,3,3,5,3,2,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +76059,29145,Male,Loyal Customer,24,Personal Travel,Eco,679,3,5,3,3,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +76060,7691,Male,Loyal Customer,31,Personal Travel,Eco,604,3,4,3,3,2,3,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +76061,27314,Female,Loyal Customer,34,Business travel,Business,3978,4,4,4,4,2,4,1,5,5,5,5,4,5,3,0,0.0,satisfied +76062,6719,Male,Loyal Customer,25,Personal Travel,Eco,438,1,4,3,4,5,3,4,5,5,2,2,5,2,5,0,0.0,neutral or dissatisfied +76063,105838,Male,Loyal Customer,54,Personal Travel,Eco,787,5,4,5,4,4,5,1,4,4,5,4,3,4,4,4,2.0,satisfied +76064,49774,Female,Loyal Customer,66,Business travel,Eco,209,5,4,4,4,4,4,2,4,4,5,4,3,4,4,0,0.0,satisfied +76065,26931,Male,Loyal Customer,41,Business travel,Eco Plus,1660,4,3,3,3,4,4,4,4,1,4,3,4,3,4,8,7.0,satisfied +76066,2183,Male,Loyal Customer,24,Business travel,Business,685,3,3,3,3,3,3,3,3,3,1,3,3,3,3,18,19.0,neutral or dissatisfied +76067,92892,Male,Loyal Customer,58,Business travel,Business,2384,0,4,0,3,3,5,5,5,5,5,4,5,5,5,0,13.0,satisfied +76068,127704,Female,Loyal Customer,44,Personal Travel,Eco,2133,3,3,3,3,1,4,3,2,2,3,2,3,2,1,4,0.0,neutral or dissatisfied +76069,127042,Female,Loyal Customer,61,Business travel,Eco,647,2,3,3,3,1,2,3,2,2,2,2,4,2,2,17,15.0,neutral or dissatisfied +76070,47881,Female,Loyal Customer,36,Business travel,Business,1840,3,3,3,3,5,2,3,4,4,4,4,5,4,4,0,5.0,satisfied +76071,98795,Male,Loyal Customer,70,Personal Travel,Eco,630,4,1,4,4,4,4,4,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +76072,94005,Male,Loyal Customer,45,Business travel,Business,2963,1,1,1,1,3,5,5,5,5,5,4,5,5,4,0,0.0,satisfied +76073,47311,Male,disloyal Customer,30,Business travel,Eco,588,1,0,1,4,1,5,5,2,5,3,2,5,2,5,141,131.0,neutral or dissatisfied +76074,76668,Female,Loyal Customer,51,Personal Travel,Eco,481,3,3,3,4,1,1,1,2,2,3,2,4,2,3,33,64.0,neutral or dissatisfied +76075,93956,Male,Loyal Customer,54,Business travel,Business,2252,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +76076,29131,Male,Loyal Customer,19,Personal Travel,Eco,978,3,4,3,3,4,3,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +76077,113242,Female,Loyal Customer,34,Personal Travel,Business,258,3,3,3,1,1,1,3,5,5,3,5,3,5,1,21,22.0,neutral or dissatisfied +76078,16330,Male,Loyal Customer,34,Personal Travel,Eco,628,3,5,3,2,2,3,2,2,5,3,4,5,4,2,0,8.0,neutral or dissatisfied +76079,16175,Female,disloyal Customer,23,Business travel,Business,277,4,3,4,3,5,4,5,5,4,1,2,2,1,5,0,0.0,satisfied +76080,35540,Male,Loyal Customer,67,Personal Travel,Eco,972,4,5,4,4,3,4,3,3,5,5,4,3,5,3,0,30.0,neutral or dissatisfied +76081,63977,Female,Loyal Customer,48,Personal Travel,Eco Plus,1192,2,1,2,1,1,1,2,5,5,2,3,1,5,3,0,0.0,neutral or dissatisfied +76082,107706,Male,Loyal Customer,37,Business travel,Eco,405,4,1,1,1,4,4,4,2,5,3,4,4,4,4,177,196.0,neutral or dissatisfied +76083,113880,Male,Loyal Customer,67,Personal Travel,Eco Plus,1592,2,4,2,4,1,2,1,1,4,5,5,4,5,1,4,0.0,neutral or dissatisfied +76084,29536,Female,Loyal Customer,25,Business travel,Business,1448,2,2,2,2,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +76085,21105,Male,Loyal Customer,19,Personal Travel,Eco,152,5,4,0,2,2,0,2,2,4,5,5,4,5,2,68,59.0,satisfied +76086,126137,Male,Loyal Customer,42,Business travel,Eco,468,4,2,2,2,5,4,5,5,1,2,3,4,3,5,112,102.0,neutral or dissatisfied +76087,56323,Male,Loyal Customer,34,Business travel,Business,3203,3,3,3,3,2,4,5,4,4,4,4,5,4,3,8,10.0,satisfied +76088,102670,Female,Loyal Customer,24,Business travel,Business,2981,0,0,0,3,3,3,3,3,3,3,5,3,4,3,9,4.0,satisfied +76089,55087,Female,disloyal Customer,17,Business travel,Eco,1243,1,0,0,4,1,1,1,1,3,4,3,2,4,1,122,110.0,neutral or dissatisfied +76090,20843,Male,Loyal Customer,12,Personal Travel,Eco,508,1,4,1,2,4,1,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +76091,63714,Male,disloyal Customer,21,Business travel,Eco,1208,3,3,3,5,2,3,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +76092,112652,Male,Loyal Customer,40,Business travel,Business,2087,4,4,2,4,2,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +76093,81700,Male,Loyal Customer,36,Personal Travel,Eco,907,2,4,1,1,2,1,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +76094,89,Female,Loyal Customer,53,Personal Travel,Eco,108,2,2,0,4,3,4,3,1,1,0,1,1,1,3,0,0.0,neutral or dissatisfied +76095,120416,Female,Loyal Customer,48,Business travel,Business,1812,0,0,0,3,3,4,5,1,1,1,1,3,1,3,0,0.0,satisfied +76096,40045,Female,disloyal Customer,24,Business travel,Eco,866,0,0,0,2,3,0,3,3,1,2,3,2,1,3,0,0.0,satisfied +76097,43476,Female,Loyal Customer,19,Business travel,Business,624,4,5,5,5,4,4,4,4,4,5,3,3,3,4,25,49.0,neutral or dissatisfied +76098,36533,Female,Loyal Customer,59,Business travel,Eco,1249,2,1,5,1,3,4,3,2,2,2,2,2,2,1,5,0.0,satisfied +76099,49648,Male,Loyal Customer,41,Business travel,Business,3583,3,3,3,3,3,2,4,4,4,4,4,4,4,5,29,16.0,satisfied +76100,38802,Female,Loyal Customer,67,Personal Travel,Eco,353,3,3,3,1,1,4,3,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +76101,25803,Female,Loyal Customer,37,Personal Travel,Eco,762,4,5,4,2,2,4,2,2,5,2,4,4,4,2,0,0.0,satisfied +76102,7767,Female,Loyal Customer,41,Business travel,Business,1611,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,4.0,satisfied +76103,71747,Male,disloyal Customer,54,Business travel,Business,1744,3,3,3,2,5,3,5,5,4,3,5,4,4,5,2,0.0,neutral or dissatisfied +76104,38009,Male,Loyal Customer,48,Business travel,Business,2853,2,2,2,2,2,5,4,4,4,4,4,4,4,2,19,0.0,satisfied +76105,77,Female,disloyal Customer,72,Business travel,Eco,67,3,3,3,4,3,2,2,3,4,4,3,2,2,2,324,296.0,neutral or dissatisfied +76106,37699,Male,Loyal Customer,28,Personal Travel,Eco,1028,3,4,3,1,5,3,3,5,2,1,4,2,1,5,4,0.0,neutral or dissatisfied +76107,7795,Female,Loyal Customer,53,Business travel,Business,650,4,4,4,4,4,4,4,5,5,4,5,5,5,4,0,13.0,satisfied +76108,120696,Female,Loyal Customer,10,Personal Travel,Eco,280,3,4,3,3,1,3,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +76109,95820,Female,Loyal Customer,50,Business travel,Business,1428,3,4,2,2,5,4,3,3,3,3,3,2,3,2,45,54.0,neutral or dissatisfied +76110,99582,Female,Loyal Customer,37,Personal Travel,Eco,930,5,3,5,3,2,5,2,2,1,3,3,4,2,2,0,0.0,satisfied +76111,105461,Male,Loyal Customer,45,Personal Travel,Eco Plus,998,1,5,1,3,4,1,4,4,5,2,4,3,5,4,13,7.0,neutral or dissatisfied +76112,86716,Female,Loyal Customer,31,Business travel,Business,1747,3,3,3,3,3,3,3,3,4,2,3,2,4,3,0,0.0,neutral or dissatisfied +76113,70187,Female,Loyal Customer,22,Business travel,Business,3139,3,3,3,3,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +76114,73836,Male,Loyal Customer,39,Business travel,Business,1709,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +76115,77027,Female,Loyal Customer,37,Business travel,Business,2661,2,2,1,2,2,4,2,2,2,2,2,5,2,1,39,28.0,satisfied +76116,32327,Female,Loyal Customer,33,Business travel,Eco,101,4,2,2,2,4,4,4,4,1,4,1,5,4,4,0,0.0,satisfied +76117,32843,Female,Loyal Customer,59,Personal Travel,Eco,102,4,4,4,4,5,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +76118,54924,Male,Loyal Customer,69,Personal Travel,Eco Plus,862,4,5,4,2,4,4,1,4,1,5,1,2,1,4,0,0.0,neutral or dissatisfied +76119,57423,Male,Loyal Customer,34,Personal Travel,Eco,403,2,1,2,4,4,2,4,4,1,5,4,4,3,4,0,0.0,neutral or dissatisfied +76120,94922,Female,Loyal Customer,49,Business travel,Eco,192,4,5,5,5,3,2,2,4,4,4,4,4,4,1,0,0.0,satisfied +76121,65664,Female,Loyal Customer,51,Business travel,Business,2613,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +76122,5141,Female,Loyal Customer,21,Business travel,Business,2739,5,4,5,5,4,4,4,4,5,2,4,4,4,4,4,12.0,satisfied +76123,99357,Female,disloyal Customer,21,Business travel,Business,1771,3,2,3,3,4,3,4,4,3,2,2,2,3,4,0,0.0,neutral or dissatisfied +76124,79359,Male,Loyal Customer,43,Business travel,Business,2483,5,5,5,5,5,5,4,5,5,5,5,4,5,5,84,69.0,satisfied +76125,123625,Male,Loyal Customer,21,Personal Travel,Business,214,2,5,2,1,1,2,1,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +76126,103187,Male,Loyal Customer,69,Personal Travel,Business,814,3,0,3,4,3,5,4,1,1,3,4,3,1,4,8,3.0,neutral or dissatisfied +76127,109457,Male,Loyal Customer,58,Business travel,Business,861,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +76128,106845,Male,Loyal Customer,47,Personal Travel,Eco,1733,2,4,2,5,4,2,4,4,5,4,5,4,5,4,11,5.0,neutral or dissatisfied +76129,115132,Female,Loyal Customer,54,Business travel,Business,1854,1,1,1,1,2,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +76130,86886,Female,Loyal Customer,10,Personal Travel,Eco Plus,692,3,5,3,5,5,3,5,5,5,3,4,3,4,5,30,44.0,neutral or dissatisfied +76131,22935,Female,Loyal Customer,48,Business travel,Business,3172,1,1,1,1,5,5,1,5,5,5,5,2,5,4,13,5.0,satisfied +76132,94916,Female,Loyal Customer,50,Business travel,Eco,162,5,4,5,4,1,1,1,5,5,5,5,5,5,5,0,0.0,satisfied +76133,49957,Male,Loyal Customer,59,Business travel,Eco,308,1,3,3,3,1,1,1,1,2,2,4,3,4,1,0,0.0,neutral or dissatisfied +76134,35907,Female,disloyal Customer,24,Business travel,Eco,1300,4,3,3,2,3,4,3,3,5,4,4,1,1,3,0,0.0,satisfied +76135,111740,Female,disloyal Customer,24,Business travel,Eco,1224,4,4,4,4,2,4,2,2,5,2,5,4,4,2,31,18.0,satisfied +76136,128101,Male,Loyal Customer,54,Personal Travel,Eco,2860,1,2,1,3,1,4,4,3,2,3,3,4,3,4,0,3.0,neutral or dissatisfied +76137,64158,Female,Loyal Customer,36,Business travel,Business,589,5,5,5,5,1,3,2,3,3,3,3,2,3,3,15,26.0,satisfied +76138,116111,Female,Loyal Customer,32,Personal Travel,Eco,362,2,5,2,3,5,2,5,5,4,3,4,3,5,5,14,15.0,neutral or dissatisfied +76139,53761,Female,Loyal Customer,29,Business travel,Business,1195,4,4,4,4,4,4,4,4,4,2,2,2,2,4,3,0.0,satisfied +76140,112008,Male,Loyal Customer,22,Business travel,Eco Plus,370,2,4,4,4,2,2,1,2,1,1,3,1,3,2,16,4.0,neutral or dissatisfied +76141,90445,Female,Loyal Customer,60,Business travel,Business,3455,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,6.0,satisfied +76142,49781,Male,disloyal Customer,33,Business travel,Eco,209,2,0,1,2,4,1,4,4,2,4,5,4,5,4,18,17.0,neutral or dissatisfied +76143,83024,Male,Loyal Customer,43,Business travel,Eco,983,2,4,3,3,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +76144,1045,Male,Loyal Customer,69,Business travel,Business,396,4,4,4,4,4,3,3,3,3,4,3,5,3,2,0,0.0,satisfied +76145,115088,Male,Loyal Customer,56,Business travel,Business,2846,4,4,2,4,5,4,4,2,2,2,2,5,2,4,2,2.0,satisfied +76146,88769,Male,Loyal Customer,25,Business travel,Eco Plus,581,1,4,4,4,1,1,4,1,3,5,3,3,3,1,0,0.0,neutral or dissatisfied +76147,29846,Female,Loyal Customer,55,Business travel,Eco,82,5,1,1,1,2,5,4,5,5,5,5,3,5,2,1,0.0,satisfied +76148,97122,Female,Loyal Customer,26,Business travel,Business,1313,3,3,3,3,3,3,3,3,5,3,4,3,4,3,2,0.0,satisfied +76149,105690,Male,Loyal Customer,44,Business travel,Business,3771,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +76150,103971,Male,Loyal Customer,42,Business travel,Business,3166,5,5,5,5,4,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +76151,51566,Female,Loyal Customer,49,Business travel,Business,2529,3,3,3,3,1,3,5,4,4,4,4,3,4,2,0,0.0,satisfied +76152,29874,Female,disloyal Customer,23,Business travel,Eco,261,3,0,3,3,3,3,4,3,1,5,5,2,1,3,2,7.0,neutral or dissatisfied +76153,67395,Male,Loyal Customer,35,Business travel,Eco,592,2,2,2,2,2,2,2,2,2,5,4,4,3,2,0,45.0,neutral or dissatisfied +76154,37215,Male,Loyal Customer,48,Business travel,Business,1895,1,1,4,1,2,5,5,4,4,4,4,3,4,3,17,6.0,satisfied +76155,91805,Female,Loyal Customer,64,Personal Travel,Eco,588,1,5,1,3,5,4,4,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +76156,120202,Male,Loyal Customer,22,Business travel,Business,1496,1,1,1,1,4,4,4,4,5,4,5,3,4,4,12,21.0,satisfied +76157,102113,Female,Loyal Customer,42,Business travel,Business,258,0,1,1,3,4,4,5,3,3,3,3,5,3,3,45,32.0,satisfied +76158,33859,Female,Loyal Customer,65,Personal Travel,Eco,1562,1,2,1,3,5,2,4,3,3,1,3,2,3,3,122,99.0,neutral or dissatisfied +76159,80091,Female,Loyal Customer,13,Personal Travel,Eco Plus,944,2,1,2,4,1,2,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +76160,106247,Female,disloyal Customer,21,Business travel,Eco,1167,4,3,3,4,3,3,3,3,3,4,4,3,4,3,27,7.0,neutral or dissatisfied +76161,69909,Male,Loyal Customer,18,Business travel,Business,1671,2,3,3,3,2,2,2,3,5,3,3,2,4,2,175,171.0,neutral or dissatisfied +76162,62781,Male,Loyal Customer,39,Business travel,Business,1004,2,5,5,5,2,2,2,2,4,3,4,2,4,2,2,10.0,neutral or dissatisfied +76163,99215,Female,Loyal Customer,59,Business travel,Business,3560,5,5,5,5,4,4,4,3,3,3,3,4,3,5,6,0.0,satisfied +76164,2073,Male,Loyal Customer,40,Business travel,Eco,733,2,3,3,3,2,2,2,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +76165,77126,Female,Loyal Customer,39,Business travel,Business,1481,4,1,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +76166,83973,Male,Loyal Customer,59,Business travel,Business,2527,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +76167,88052,Male,Loyal Customer,39,Business travel,Business,1672,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,3.0,satisfied +76168,103776,Male,disloyal Customer,25,Business travel,Business,979,3,0,2,2,1,2,3,1,3,3,5,3,5,1,0,0.0,neutral or dissatisfied +76169,85733,Female,disloyal Customer,24,Business travel,Eco,666,1,0,1,3,5,1,5,5,3,4,5,4,5,5,4,0.0,neutral or dissatisfied +76170,104664,Female,disloyal Customer,21,Business travel,Business,641,2,3,2,3,2,2,2,2,4,3,3,2,2,2,146,138.0,neutral or dissatisfied +76171,108322,Male,Loyal Customer,56,Business travel,Business,1844,2,2,2,2,3,4,5,3,3,3,3,5,3,3,42,29.0,satisfied +76172,34899,Male,Loyal Customer,33,Business travel,Business,187,5,5,5,5,5,5,4,5,4,4,5,1,2,5,0,0.0,satisfied +76173,19701,Male,Loyal Customer,16,Business travel,Business,491,1,1,1,1,4,4,4,4,3,5,3,1,4,4,13,6.0,satisfied +76174,100635,Female,Loyal Customer,58,Business travel,Business,349,5,5,5,5,2,5,5,4,4,4,4,4,4,3,15,3.0,satisfied +76175,33388,Female,Loyal Customer,14,Business travel,Eco Plus,2614,4,2,5,5,4,4,2,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +76176,116756,Female,Loyal Customer,37,Personal Travel,Eco Plus,446,4,4,4,2,3,4,3,3,3,3,5,5,4,3,7,2.0,neutral or dissatisfied +76177,55561,Male,Loyal Customer,57,Business travel,Business,1967,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +76178,37839,Female,disloyal Customer,23,Business travel,Eco,937,0,0,0,1,4,0,4,4,5,4,2,2,3,4,0,0.0,satisfied +76179,54392,Female,disloyal Customer,37,Business travel,Eco,305,2,3,1,2,4,1,4,4,5,4,5,1,4,4,4,0.0,neutral or dissatisfied +76180,4487,Female,Loyal Customer,40,Business travel,Business,3000,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,31.0,satisfied +76181,111363,Female,Loyal Customer,46,Business travel,Business,3748,1,1,1,1,5,5,5,4,4,4,4,4,4,5,26,23.0,satisfied +76182,98848,Male,disloyal Customer,30,Business travel,Business,1482,0,0,0,1,5,0,4,5,4,4,4,5,4,5,38,35.0,satisfied +76183,71199,Male,Loyal Customer,58,Business travel,Business,3313,3,3,3,3,3,5,5,4,4,4,4,5,4,4,46,35.0,satisfied +76184,64935,Male,Loyal Customer,35,Business travel,Business,3805,1,2,3,2,3,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +76185,113841,Female,Loyal Customer,59,Personal Travel,Business,1334,3,5,3,3,3,4,5,3,3,3,3,3,3,4,0,19.0,neutral or dissatisfied +76186,129200,Female,Loyal Customer,59,Business travel,Business,2442,5,5,5,5,3,3,4,5,5,5,5,4,5,5,0,1.0,satisfied +76187,48525,Female,Loyal Customer,46,Business travel,Business,2546,2,1,1,1,4,4,3,2,2,2,2,3,2,4,0,1.0,neutral or dissatisfied +76188,46794,Male,Loyal Customer,13,Business travel,Business,3532,2,5,5,5,2,1,2,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +76189,101374,Male,Loyal Customer,33,Business travel,Business,1986,2,2,1,2,4,4,4,4,4,2,3,5,5,4,7,0.0,satisfied +76190,110622,Male,Loyal Customer,40,Business travel,Business,719,3,3,3,3,3,3,2,3,3,3,3,3,3,1,67,62.0,neutral or dissatisfied +76191,81060,Male,Loyal Customer,53,Personal Travel,Eco,1399,3,5,3,1,5,3,5,5,2,4,2,1,4,5,0,0.0,neutral or dissatisfied +76192,45466,Female,Loyal Customer,44,Business travel,Business,3757,4,4,2,4,5,2,4,4,4,4,4,3,4,4,9,10.0,satisfied +76193,96305,Male,Loyal Customer,21,Business travel,Business,1523,5,5,5,5,4,5,4,4,3,4,5,3,4,4,109,91.0,satisfied +76194,64424,Female,Loyal Customer,39,Business travel,Business,2465,5,5,5,5,2,5,4,5,5,5,5,4,5,5,5,0.0,satisfied +76195,78386,Female,disloyal Customer,10,Business travel,Eco,980,3,4,4,4,5,4,5,5,2,4,4,2,4,5,0,0.0,neutral or dissatisfied +76196,110342,Male,Loyal Customer,22,Business travel,Business,3664,1,4,4,4,1,1,1,1,2,5,2,3,2,1,0,0.0,neutral or dissatisfied +76197,114985,Male,disloyal Customer,61,Business travel,Eco,296,2,1,2,3,1,2,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +76198,71056,Female,disloyal Customer,27,Business travel,Eco,802,2,2,2,2,3,2,3,3,3,5,2,5,3,3,0,0.0,neutral or dissatisfied +76199,73295,Male,Loyal Customer,55,Business travel,Business,1555,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +76200,786,Male,disloyal Customer,22,Business travel,Eco,134,1,4,1,4,4,1,4,4,2,2,3,3,4,4,27,18.0,neutral or dissatisfied +76201,65999,Male,disloyal Customer,35,Business travel,Business,1055,2,2,2,4,4,2,4,4,4,4,5,5,5,4,0,1.0,neutral or dissatisfied +76202,14234,Male,disloyal Customer,21,Business travel,Eco,1290,3,3,3,3,3,3,1,3,5,3,4,5,4,3,0,4.0,neutral or dissatisfied +76203,121705,Female,Loyal Customer,38,Business travel,Eco,683,1,0,0,4,5,0,5,5,3,4,3,1,4,5,0,0.0,neutral or dissatisfied +76204,40779,Male,disloyal Customer,21,Business travel,Eco,574,2,3,1,4,5,1,5,5,2,5,4,3,3,5,0,1.0,neutral or dissatisfied +76205,120850,Female,Loyal Customer,13,Personal Travel,Business,861,4,3,4,4,5,4,1,5,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +76206,123705,Male,Loyal Customer,64,Personal Travel,Eco,214,2,0,2,4,2,2,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +76207,114282,Female,Loyal Customer,41,Personal Travel,Eco,957,3,5,3,4,3,3,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +76208,102902,Male,Loyal Customer,32,Personal Travel,Eco,1037,2,4,2,4,2,2,2,2,5,2,5,4,5,2,13,14.0,neutral or dissatisfied +76209,19977,Female,Loyal Customer,38,Personal Travel,Eco,557,4,2,4,4,3,4,1,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +76210,83346,Female,Loyal Customer,48,Personal Travel,Eco,187,4,2,4,4,2,4,3,4,4,4,4,1,4,3,0,0.0,satisfied +76211,53522,Female,Loyal Customer,8,Personal Travel,Eco,2419,3,5,3,3,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +76212,29677,Male,Loyal Customer,38,Business travel,Eco Plus,1448,3,4,4,4,3,3,3,3,1,2,3,2,4,3,85,75.0,neutral or dissatisfied +76213,27091,Male,Loyal Customer,31,Personal Travel,Business,1721,3,3,3,2,5,3,3,5,3,5,2,1,2,5,66,54.0,neutral or dissatisfied +76214,92277,Female,Loyal Customer,10,Personal Travel,Eco,1900,5,4,5,2,2,4,4,2,5,4,5,3,5,2,0,0.0,satisfied +76215,62435,Male,Loyal Customer,59,Business travel,Business,1943,3,3,3,3,4,5,4,4,4,4,4,5,4,3,84,52.0,satisfied +76216,81387,Female,Loyal Customer,44,Business travel,Business,748,4,4,4,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +76217,40639,Female,Loyal Customer,70,Business travel,Eco Plus,411,4,1,1,1,5,2,1,4,4,4,4,4,4,3,0,0.0,satisfied +76218,98701,Female,Loyal Customer,40,Personal Travel,Eco,861,2,4,2,1,4,2,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +76219,57396,Male,Loyal Customer,41,Business travel,Business,1783,4,4,4,4,5,4,5,4,4,4,4,4,4,5,1,0.0,satisfied +76220,129325,Female,disloyal Customer,37,Business travel,Eco,2475,2,2,2,4,3,2,3,3,1,2,4,4,3,3,7,10.0,neutral or dissatisfied +76221,58539,Male,Loyal Customer,51,Business travel,Business,1514,2,2,2,2,3,5,5,3,3,4,3,5,3,5,119,118.0,satisfied +76222,57786,Male,Loyal Customer,46,Personal Travel,Eco,2611,2,5,3,2,3,4,4,1,4,5,1,4,5,4,1,0.0,neutral or dissatisfied +76223,92665,Male,Loyal Customer,46,Business travel,Business,1996,1,1,2,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +76224,1925,Female,Loyal Customer,36,Business travel,Business,383,1,1,3,1,5,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +76225,30656,Female,Loyal Customer,45,Personal Travel,Eco,533,4,4,4,3,3,3,4,2,2,4,2,1,2,1,0,0.0,neutral or dissatisfied +76226,84473,Male,Loyal Customer,29,Personal Travel,Eco,1142,4,3,4,4,3,4,1,3,1,4,2,1,3,3,0,0.0,satisfied +76227,52871,Female,Loyal Customer,42,Business travel,Business,836,2,3,3,3,2,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +76228,2860,Male,Loyal Customer,48,Business travel,Eco,491,2,4,4,4,2,2,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +76229,126494,Male,Loyal Customer,66,Personal Travel,Eco,1788,2,4,1,1,4,1,4,4,3,5,3,3,5,4,0,0.0,neutral or dissatisfied +76230,111650,Male,Loyal Customer,13,Personal Travel,Eco,1558,2,3,2,2,3,2,3,3,3,4,3,4,2,3,52,31.0,neutral or dissatisfied +76231,106388,Male,disloyal Customer,13,Business travel,Eco,674,3,3,3,4,2,3,2,2,4,3,3,1,4,2,19,0.0,neutral or dissatisfied +76232,113616,Female,Loyal Customer,31,Personal Travel,Eco,386,2,4,2,3,5,2,5,5,5,4,5,4,5,5,2,2.0,neutral or dissatisfied +76233,127760,Female,Loyal Customer,51,Personal Travel,Eco,255,3,4,3,4,4,4,4,5,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +76234,124325,Female,Loyal Customer,31,Personal Travel,Eco,255,3,3,3,2,3,3,3,3,1,3,1,3,3,3,0,0.0,neutral or dissatisfied +76235,74161,Male,Loyal Customer,69,Personal Travel,Eco,592,1,5,1,4,1,1,1,1,3,4,5,2,1,1,34,41.0,neutral or dissatisfied +76236,111220,Female,disloyal Customer,57,Business travel,Eco,1146,3,3,3,2,5,3,1,5,2,2,1,4,3,5,0,0.0,neutral or dissatisfied +76237,60198,Male,Loyal Customer,54,Business travel,Business,1607,2,4,4,4,3,1,2,2,2,3,2,4,2,1,34,18.0,neutral or dissatisfied +76238,116554,Female,Loyal Customer,70,Personal Travel,Eco,337,3,5,3,2,4,5,5,2,2,3,2,3,2,3,18,15.0,neutral or dissatisfied +76239,12660,Male,Loyal Customer,56,Business travel,Business,689,3,3,3,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +76240,54200,Female,Loyal Customer,42,Personal Travel,Eco,1400,3,4,3,5,3,5,4,5,5,3,5,5,5,3,1,0.0,neutral or dissatisfied +76241,13871,Female,Loyal Customer,54,Business travel,Eco,667,2,5,5,5,3,4,4,3,3,2,3,3,3,3,0,6.0,neutral or dissatisfied +76242,81483,Female,disloyal Customer,27,Business travel,Eco,528,4,0,4,4,1,4,1,1,5,5,1,4,4,1,0,0.0,satisfied +76243,69157,Male,Loyal Customer,36,Business travel,Business,187,5,5,5,5,3,4,5,5,5,5,4,4,5,3,8,0.0,satisfied +76244,72471,Male,Loyal Customer,47,Business travel,Business,2373,5,3,5,5,4,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +76245,113468,Male,Loyal Customer,60,Business travel,Business,1574,1,1,1,1,5,4,4,4,4,4,4,4,4,4,15,8.0,satisfied +76246,27604,Male,Loyal Customer,23,Personal Travel,Eco,954,4,4,5,1,2,5,2,2,1,3,5,2,3,2,1,3.0,neutral or dissatisfied +76247,128277,Male,Loyal Customer,30,Personal Travel,Business,651,2,5,3,4,2,3,5,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +76248,42877,Male,Loyal Customer,8,Personal Travel,Eco,867,2,5,2,4,1,2,1,1,4,5,1,5,1,1,0,8.0,neutral or dissatisfied +76249,22082,Male,Loyal Customer,35,Business travel,Eco,782,4,2,2,2,4,4,4,4,5,3,3,4,1,4,0,0.0,satisfied +76250,54191,Female,Loyal Customer,22,Personal Travel,Eco,1400,3,2,3,3,4,3,4,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +76251,20355,Male,Loyal Customer,37,Business travel,Eco,323,1,5,5,5,1,1,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +76252,84355,Female,Loyal Customer,48,Business travel,Business,591,1,1,1,1,3,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +76253,24376,Female,Loyal Customer,49,Business travel,Business,669,2,2,2,2,2,2,2,2,5,4,3,2,2,2,156,167.0,neutral or dissatisfied +76254,52495,Male,disloyal Customer,23,Business travel,Eco,160,1,0,2,4,4,2,3,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +76255,86151,Female,Loyal Customer,16,Business travel,Business,356,1,1,1,1,1,1,1,1,4,1,3,2,4,1,0,0.0,neutral or dissatisfied +76256,121814,Male,Loyal Customer,56,Business travel,Eco,449,4,2,2,2,4,4,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +76257,125764,Female,disloyal Customer,24,Business travel,Eco,993,1,1,1,1,2,1,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +76258,105894,Female,Loyal Customer,57,Business travel,Business,2016,5,5,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +76259,84093,Female,Loyal Customer,57,Personal Travel,Eco,879,2,5,2,1,3,3,4,3,3,2,3,3,3,4,0,1.0,neutral or dissatisfied +76260,21320,Female,Loyal Customer,22,Personal Travel,Eco Plus,692,1,4,0,3,4,0,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +76261,12308,Female,disloyal Customer,39,Business travel,Business,305,3,3,3,4,4,3,4,4,3,1,2,2,1,4,54,49.0,satisfied +76262,75617,Male,Loyal Customer,70,Personal Travel,Eco,337,2,5,2,3,2,2,2,2,4,2,4,3,4,2,8,5.0,neutral or dissatisfied +76263,68037,Male,Loyal Customer,26,Personal Travel,Business,868,3,3,3,3,3,3,3,3,4,2,2,5,5,3,0,6.0,neutral or dissatisfied +76264,68135,Male,Loyal Customer,56,Business travel,Business,1802,5,3,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +76265,49644,Female,Loyal Customer,25,Business travel,Eco,109,5,3,3,3,5,5,3,5,2,3,1,5,2,5,0,0.0,satisfied +76266,91062,Male,Loyal Customer,24,Personal Travel,Eco,404,0,1,0,3,5,0,5,5,1,1,4,4,3,5,11,1.0,satisfied +76267,112250,Female,Loyal Customer,25,Business travel,Business,1506,4,4,4,4,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +76268,65207,Female,disloyal Customer,34,Business travel,Business,247,3,3,3,3,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +76269,39741,Male,Loyal Customer,7,Personal Travel,Eco,162,3,5,3,3,4,3,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +76270,5642,Female,disloyal Customer,23,Business travel,Business,436,2,1,2,4,5,2,5,5,1,3,3,1,4,5,71,52.0,neutral or dissatisfied +76271,91261,Male,Loyal Customer,66,Personal Travel,Eco,250,1,5,1,1,2,1,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +76272,9503,Male,Loyal Customer,32,Personal Travel,Eco,322,3,4,3,1,4,3,4,4,1,1,5,1,3,4,50,37.0,neutral or dissatisfied +76273,18450,Male,Loyal Customer,66,Personal Travel,Business,201,2,2,2,2,5,2,2,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +76274,105110,Male,Loyal Customer,37,Business travel,Business,3972,0,4,0,5,4,4,5,5,5,5,5,4,5,3,0,12.0,satisfied +76275,19088,Male,Loyal Customer,62,Business travel,Business,2894,1,1,2,1,2,5,2,4,4,4,4,4,4,2,0,0.0,satisfied +76276,40088,Female,Loyal Customer,53,Business travel,Business,1579,2,2,2,2,2,5,5,4,4,4,5,4,4,3,2,0.0,satisfied +76277,10655,Female,Loyal Customer,39,Business travel,Business,3172,3,3,3,3,4,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +76278,24929,Female,Loyal Customer,26,Personal Travel,Eco,762,3,4,3,3,2,3,1,2,5,5,5,5,4,2,20,60.0,neutral or dissatisfied +76279,18247,Male,Loyal Customer,25,Personal Travel,Eco,224,4,5,4,4,2,4,2,2,4,3,2,4,1,2,0,3.0,satisfied +76280,68124,Female,Loyal Customer,22,Personal Travel,Eco,813,4,4,4,4,4,4,4,4,5,3,2,5,1,4,15,12.0,neutral or dissatisfied +76281,9104,Male,disloyal Customer,34,Business travel,Business,707,3,3,3,3,5,3,5,5,3,4,5,5,4,5,21,13.0,neutral or dissatisfied +76282,19377,Male,Loyal Customer,18,Business travel,Business,2720,1,1,1,1,4,4,4,5,1,5,3,4,2,4,133,122.0,satisfied +76283,98934,Male,Loyal Customer,45,Business travel,Business,543,3,3,3,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +76284,73995,Male,Loyal Customer,53,Business travel,Business,1972,3,3,3,3,4,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +76285,98047,Female,Loyal Customer,40,Business travel,Business,1751,3,3,3,3,4,2,2,3,3,3,3,1,3,4,8,3.0,neutral or dissatisfied +76286,50153,Female,disloyal Customer,42,Business travel,Eco,372,4,1,4,3,4,4,4,4,4,3,3,2,4,4,0,10.0,neutral or dissatisfied +76287,128758,Female,disloyal Customer,23,Business travel,Business,550,5,0,5,1,2,5,2,2,3,4,4,5,5,2,0,0.0,satisfied +76288,94255,Female,Loyal Customer,59,Business travel,Business,3781,0,0,0,4,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +76289,109288,Female,disloyal Customer,39,Business travel,Business,1072,3,3,3,3,3,3,5,5,3,5,4,5,4,5,170,164.0,neutral or dissatisfied +76290,93919,Male,Loyal Customer,39,Business travel,Business,507,5,5,5,5,5,5,4,5,5,5,5,3,5,3,11,1.0,satisfied +76291,72353,Female,Loyal Customer,60,Personal Travel,Business,1119,2,2,2,3,2,4,3,3,3,2,3,3,3,3,19,,neutral or dissatisfied +76292,18152,Female,Loyal Customer,52,Personal Travel,Eco,296,4,4,4,4,2,4,4,1,1,4,1,3,1,5,0,0.0,neutral or dissatisfied +76293,76024,Female,Loyal Customer,51,Business travel,Business,2262,2,2,2,2,2,5,1,4,4,4,4,1,4,3,6,10.0,satisfied +76294,70987,Male,Loyal Customer,35,Business travel,Business,3258,1,2,1,1,4,4,4,4,4,4,4,5,4,4,6,9.0,satisfied +76295,123389,Female,Loyal Customer,33,Business travel,Business,1337,2,5,5,5,2,3,4,2,2,2,2,2,2,1,25,11.0,neutral or dissatisfied +76296,8234,Male,Loyal Customer,22,Personal Travel,Eco,530,1,4,5,1,3,5,5,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +76297,4584,Female,Loyal Customer,58,Business travel,Business,416,1,1,1,1,4,5,4,4,4,4,4,3,4,3,8,5.0,satisfied +76298,90414,Female,disloyal Customer,39,Business travel,Business,515,3,3,3,3,2,3,1,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +76299,67771,Female,Loyal Customer,42,Business travel,Business,1431,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +76300,76679,Female,Loyal Customer,55,Personal Travel,Eco,547,2,1,2,2,2,1,1,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +76301,17968,Female,Loyal Customer,16,Personal Travel,Eco,500,1,5,1,3,3,1,3,3,3,3,4,5,4,3,0,8.0,neutral or dissatisfied +76302,77011,Male,disloyal Customer,59,Business travel,Business,422,2,2,2,4,2,2,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +76303,109947,Female,Loyal Customer,68,Personal Travel,Eco,1165,3,3,4,2,1,3,4,5,5,4,5,4,5,4,42,55.0,neutral or dissatisfied +76304,22247,Male,Loyal Customer,63,Business travel,Business,143,1,1,1,1,4,3,2,5,5,5,4,5,5,3,0,27.0,satisfied +76305,100543,Female,Loyal Customer,30,Personal Travel,Eco,580,3,3,3,4,2,3,2,2,1,3,4,1,3,2,1,0.0,neutral or dissatisfied +76306,46289,Female,Loyal Customer,35,Personal Travel,Eco Plus,594,1,3,1,2,2,1,2,2,1,2,2,3,2,2,68,68.0,neutral or dissatisfied +76307,117878,Female,Loyal Customer,60,Business travel,Business,2363,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +76308,27416,Male,Loyal Customer,22,Business travel,Business,3076,2,2,2,2,4,5,4,4,5,5,2,3,4,4,43,38.0,satisfied +76309,99205,Male,Loyal Customer,56,Personal Travel,Eco,691,2,5,2,2,3,2,3,3,5,4,5,4,5,3,5,0.0,neutral or dissatisfied +76310,122426,Female,disloyal Customer,12,Business travel,Eco,1234,3,3,3,1,2,3,2,2,3,2,3,5,4,2,0,0.0,neutral or dissatisfied +76311,84468,Female,Loyal Customer,41,Personal Travel,Business,1142,3,1,3,3,5,4,3,2,2,3,4,2,2,4,0,0.0,neutral or dissatisfied +76312,74895,Male,Loyal Customer,41,Business travel,Business,2586,1,1,1,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +76313,23812,Female,Loyal Customer,27,Personal Travel,Eco,438,3,2,3,2,3,3,3,3,4,3,2,4,2,3,2,0.0,neutral or dissatisfied +76314,104760,Male,Loyal Customer,15,Personal Travel,Eco,1342,2,3,2,1,3,2,3,3,4,3,4,4,5,3,38,28.0,neutral or dissatisfied +76315,30972,Female,Loyal Customer,32,Business travel,Eco,1476,0,0,0,2,1,0,1,1,1,3,4,2,3,1,0,0.0,satisfied +76316,72299,Male,Loyal Customer,35,Personal Travel,Eco,919,3,4,3,1,2,3,2,2,4,5,4,5,5,2,1,0.0,neutral or dissatisfied +76317,107331,Female,Loyal Customer,43,Business travel,Business,2266,3,3,3,3,5,5,5,4,4,5,4,4,4,5,25,27.0,satisfied +76318,74930,Male,Loyal Customer,37,Business travel,Business,2475,3,3,3,3,3,3,5,5,5,5,5,3,5,5,9,0.0,satisfied +76319,51009,Male,Loyal Customer,33,Personal Travel,Eco,363,3,3,3,2,2,3,2,2,3,1,4,1,1,2,2,3.0,neutral or dissatisfied +76320,35885,Male,Loyal Customer,13,Personal Travel,Eco,1065,3,2,3,3,3,4,4,4,2,3,2,4,1,4,202,198.0,neutral or dissatisfied +76321,90492,Male,Loyal Customer,60,Business travel,Business,404,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +76322,64939,Male,Loyal Customer,46,Business travel,Business,2323,1,3,3,3,5,3,3,1,1,1,1,2,1,3,6,9.0,neutral or dissatisfied +76323,80586,Male,Loyal Customer,32,Personal Travel,Eco,1747,2,1,2,4,1,2,1,1,1,3,3,3,3,1,48,47.0,neutral or dissatisfied +76324,1019,Male,Loyal Customer,37,Business travel,Business,2458,4,3,4,3,2,4,4,3,3,3,4,2,3,1,0,0.0,neutral or dissatisfied +76325,101916,Female,Loyal Customer,48,Business travel,Business,1984,2,2,2,2,2,5,4,5,5,5,5,5,5,5,12,22.0,satisfied +76326,31113,Female,disloyal Customer,20,Personal Travel,Business,991,3,5,3,2,3,3,3,3,3,3,5,3,5,3,8,37.0,neutral or dissatisfied +76327,35418,Male,Loyal Customer,25,Business travel,Business,2501,3,3,3,3,4,4,4,4,4,3,1,5,2,4,0,0.0,satisfied +76328,87932,Male,Loyal Customer,26,Business travel,Business,581,3,3,3,3,3,3,3,3,2,5,3,3,3,3,22,28.0,neutral or dissatisfied +76329,71436,Male,Loyal Customer,23,Business travel,Business,2867,2,2,2,2,5,5,5,5,4,2,5,5,5,5,0,0.0,satisfied +76330,109091,Female,Loyal Customer,68,Personal Travel,Eco,1041,2,4,2,1,2,5,5,1,1,2,1,4,1,3,33,33.0,neutral or dissatisfied +76331,105116,Male,Loyal Customer,58,Business travel,Business,2475,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +76332,30016,Male,Loyal Customer,51,Business travel,Eco,82,3,3,3,3,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +76333,102828,Male,Loyal Customer,51,Business travel,Business,3288,2,2,2,2,5,5,5,3,3,5,4,5,5,5,152,156.0,satisfied +76334,21455,Male,Loyal Customer,34,Business travel,Business,399,3,3,3,3,5,3,2,3,3,3,3,4,3,3,33,33.0,satisfied +76335,78414,Male,Loyal Customer,47,Business travel,Business,3922,5,5,5,5,3,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +76336,44155,Female,Loyal Customer,8,Personal Travel,Business,229,2,4,2,2,4,2,4,4,5,3,4,5,5,4,14,5.0,neutral or dissatisfied +76337,34111,Male,Loyal Customer,27,Business travel,Business,1046,5,5,4,5,5,5,5,5,1,2,3,1,2,5,0,5.0,satisfied +76338,78186,Female,Loyal Customer,33,Business travel,Eco,259,3,2,2,2,3,3,3,3,1,2,3,2,3,3,6,2.0,neutral or dissatisfied +76339,76955,Female,Loyal Customer,33,Business travel,Business,1990,1,4,4,4,2,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +76340,61164,Male,Loyal Customer,55,Business travel,Business,3766,4,2,4,4,3,3,3,5,4,5,4,3,5,3,185,158.0,satisfied +76341,80482,Male,Loyal Customer,46,Personal Travel,Eco,1299,1,4,1,5,2,1,2,2,3,4,5,3,4,2,85,86.0,neutral or dissatisfied +76342,100574,Female,Loyal Customer,50,Business travel,Business,486,3,3,3,3,5,5,4,5,5,5,5,5,5,5,25,30.0,satisfied +76343,104073,Female,Loyal Customer,60,Business travel,Business,3914,3,3,3,3,4,5,5,5,5,5,5,3,5,5,0,4.0,satisfied +76344,50120,Female,Loyal Customer,73,Business travel,Eco,373,2,5,5,5,4,2,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +76345,117561,Female,Loyal Customer,43,Business travel,Business,843,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +76346,124374,Female,Loyal Customer,66,Business travel,Eco,575,2,1,1,1,3,3,4,2,2,2,2,3,2,4,2,3.0,neutral or dissatisfied +76347,4016,Male,Loyal Customer,44,Business travel,Business,425,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +76348,41896,Female,Loyal Customer,58,Business travel,Business,2816,0,3,1,4,3,1,3,5,5,1,1,1,5,2,0,4.0,satisfied +76349,9256,Male,Loyal Customer,21,Personal Travel,Eco,100,3,5,3,3,1,3,1,1,3,2,5,3,4,1,0,5.0,neutral or dissatisfied +76350,94806,Female,Loyal Customer,22,Business travel,Business,2074,3,3,3,3,3,3,3,3,2,1,2,2,3,3,0,0.0,neutral or dissatisfied +76351,95706,Female,Loyal Customer,42,Business travel,Business,237,4,4,3,4,2,4,5,4,4,4,4,4,4,4,11,2.0,satisfied +76352,55538,Female,Loyal Customer,42,Business travel,Business,550,2,2,2,2,1,3,3,2,2,2,2,2,2,2,58,64.0,neutral or dissatisfied +76353,88101,Male,Loyal Customer,33,Business travel,Business,3204,3,3,3,3,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +76354,57865,Male,Loyal Customer,26,Personal Travel,Eco,955,4,4,4,5,5,4,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +76355,57092,Male,Loyal Customer,46,Business travel,Business,3660,4,4,4,4,2,4,4,5,5,4,5,4,5,5,3,0.0,satisfied +76356,74848,Male,Loyal Customer,10,Personal Travel,Business,2136,0,2,0,3,4,0,4,4,1,4,3,1,4,4,1,0.0,satisfied +76357,103864,Female,Loyal Customer,28,Personal Travel,Eco,882,1,1,1,2,1,1,1,1,1,5,2,4,1,1,0,0.0,neutral or dissatisfied +76358,128571,Female,Loyal Customer,47,Business travel,Business,2200,2,2,2,2,5,5,4,4,4,4,5,5,4,5,0,0.0,satisfied +76359,116022,Female,Loyal Customer,10,Personal Travel,Eco,480,1,2,1,2,1,1,1,1,1,5,1,2,1,1,0,0.0,neutral or dissatisfied +76360,88070,Female,Loyal Customer,40,Business travel,Business,3906,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +76361,78725,Male,Loyal Customer,50,Business travel,Business,447,2,5,2,2,4,5,4,4,4,4,4,3,4,3,2,0.0,satisfied +76362,8937,Female,Loyal Customer,43,Business travel,Business,328,4,4,4,4,2,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +76363,91819,Female,Loyal Customer,48,Personal Travel,Eco,626,5,5,5,1,2,5,4,1,1,5,1,5,1,4,0,0.0,satisfied +76364,95976,Female,disloyal Customer,25,Business travel,Eco,1069,1,1,1,4,2,1,2,2,1,5,4,2,3,2,41,47.0,neutral or dissatisfied +76365,55896,Female,disloyal Customer,48,Business travel,Business,733,4,4,4,3,3,4,3,3,5,5,4,5,4,3,2,7.0,neutral or dissatisfied +76366,129734,Female,Loyal Customer,36,Business travel,Eco,337,2,1,1,1,2,2,2,2,4,4,3,2,2,2,152,159.0,neutral or dissatisfied +76367,44033,Male,Loyal Customer,51,Business travel,Business,311,4,4,4,4,3,3,1,4,4,4,4,1,4,4,0,0.0,satisfied +76368,60504,Female,Loyal Customer,9,Personal Travel,Eco,862,0,4,0,4,3,4,3,3,3,3,5,4,2,3,1,5.0,satisfied +76369,105752,Male,Loyal Customer,41,Business travel,Eco,387,5,3,3,3,5,5,5,5,2,1,2,2,2,5,23,25.0,satisfied +76370,55417,Male,Loyal Customer,44,Business travel,Business,2136,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +76371,26322,Female,Loyal Customer,55,Personal Travel,Eco,892,1,4,0,4,5,5,5,3,3,0,3,4,3,5,16,,neutral or dissatisfied +76372,33041,Female,Loyal Customer,33,Personal Travel,Eco,216,3,0,3,1,1,3,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +76373,80337,Female,Loyal Customer,43,Business travel,Eco Plus,746,3,5,5,5,3,3,3,3,5,3,4,3,2,3,191,239.0,neutral or dissatisfied +76374,92581,Male,Loyal Customer,44,Business travel,Eco Plus,2139,2,1,1,1,2,2,2,2,3,2,3,4,3,2,1,0.0,neutral or dissatisfied +76375,89768,Female,Loyal Customer,10,Personal Travel,Eco,1010,4,4,4,4,3,4,3,3,2,2,4,4,3,3,66,66.0,neutral or dissatisfied +76376,64639,Male,Loyal Customer,39,Business travel,Business,190,4,4,4,4,4,5,5,5,5,4,4,3,5,5,0,4.0,satisfied +76377,60772,Female,Loyal Customer,57,Business travel,Business,3989,3,3,3,3,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +76378,87358,Male,Loyal Customer,53,Business travel,Business,1596,4,1,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +76379,85542,Female,Loyal Customer,40,Business travel,Business,3194,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +76380,6933,Male,Loyal Customer,41,Business travel,Business,3036,3,3,3,3,4,4,5,5,5,5,5,3,5,5,40,41.0,satisfied +76381,100560,Female,Loyal Customer,40,Business travel,Business,1542,1,1,1,1,5,5,5,5,3,5,4,5,3,5,138,131.0,satisfied +76382,114792,Female,Loyal Customer,42,Business travel,Business,417,2,2,2,2,3,4,4,3,3,4,3,5,3,4,7,3.0,satisfied +76383,67144,Male,Loyal Customer,44,Business travel,Eco,564,5,5,5,5,5,5,5,5,3,3,1,5,1,5,79,53.0,satisfied +76384,11685,Male,Loyal Customer,16,Personal Travel,Business,395,4,4,4,1,5,4,5,5,3,2,4,3,5,5,81,90.0,neutral or dissatisfied +76385,118361,Male,Loyal Customer,41,Business travel,Business,3103,5,5,3,5,5,5,4,4,4,4,4,5,4,5,5,3.0,satisfied +76386,28468,Female,Loyal Customer,46,Business travel,Business,1721,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +76387,10792,Female,Loyal Customer,32,Business travel,Business,2900,2,4,4,4,2,2,2,2,1,1,4,4,3,2,0,0.0,neutral or dissatisfied +76388,92951,Female,Loyal Customer,36,Business travel,Business,134,4,4,4,4,4,5,4,4,4,4,5,3,4,3,23,22.0,satisfied +76389,77203,Female,Loyal Customer,40,Business travel,Business,2994,3,3,3,3,4,4,4,5,4,4,5,4,4,4,0,6.0,satisfied +76390,18194,Male,Loyal Customer,43,Business travel,Business,137,5,5,5,5,3,3,2,4,4,4,3,2,4,2,43,53.0,satisfied +76391,18245,Female,Loyal Customer,37,Business travel,Business,1752,0,0,0,4,1,5,5,1,1,1,1,5,1,1,0,3.0,satisfied +76392,123220,Male,Loyal Customer,47,Personal Travel,Eco,631,3,4,3,1,5,3,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +76393,64828,Male,disloyal Customer,27,Business travel,Business,551,0,0,0,2,2,0,2,2,5,2,5,3,4,2,0,0.0,satisfied +76394,15616,Male,Loyal Customer,28,Personal Travel,Eco,292,2,5,2,3,2,2,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +76395,51463,Female,Loyal Customer,10,Personal Travel,Eco Plus,153,3,4,3,1,5,3,5,5,3,2,5,5,5,5,115,120.0,neutral or dissatisfied +76396,91081,Female,Loyal Customer,26,Personal Travel,Eco,581,2,5,2,5,3,2,3,3,2,2,3,2,1,3,2,3.0,neutral or dissatisfied +76397,62747,Female,disloyal Customer,28,Business travel,Business,2486,2,2,2,1,3,2,3,3,5,2,5,4,5,3,3,0.0,neutral or dissatisfied +76398,2731,Male,Loyal Customer,54,Business travel,Business,695,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +76399,124196,Male,Loyal Customer,46,Business travel,Business,2176,2,2,2,2,2,5,5,2,2,2,2,4,2,4,84,63.0,satisfied +76400,30966,Male,Loyal Customer,19,Business travel,Eco Plus,1024,4,5,5,5,4,4,5,4,1,4,2,4,3,4,0,0.0,satisfied +76401,106160,Male,Loyal Customer,64,Personal Travel,Eco,302,2,4,2,4,2,2,2,2,4,4,4,5,4,2,4,12.0,neutral or dissatisfied +76402,45414,Female,disloyal Customer,22,Business travel,Eco,458,0,0,0,5,3,0,3,3,5,5,2,2,2,3,35,63.0,satisfied +76403,43946,Male,disloyal Customer,30,Business travel,Eco,408,1,5,1,1,3,1,3,3,2,1,3,5,1,3,24,15.0,neutral or dissatisfied +76404,100706,Female,disloyal Customer,22,Business travel,Eco,677,4,4,4,5,4,4,4,4,3,2,4,4,5,4,4,0.0,satisfied +76405,19189,Female,disloyal Customer,21,Business travel,Eco,542,5,0,5,4,5,0,5,5,3,3,2,3,3,5,0,0.0,satisfied +76406,35198,Male,Loyal Customer,45,Business travel,Business,3709,4,4,4,4,3,5,1,4,4,4,4,4,4,3,0,2.0,satisfied +76407,91145,Male,Loyal Customer,53,Personal Travel,Eco,223,4,4,4,3,5,4,5,5,1,2,4,2,4,5,0,3.0,neutral or dissatisfied +76408,62609,Male,Loyal Customer,54,Personal Travel,Eco,1846,1,3,2,4,3,2,3,3,4,5,4,2,4,3,27,4.0,neutral or dissatisfied +76409,111382,Female,Loyal Customer,59,Business travel,Business,2513,3,2,2,2,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +76410,84178,Female,Loyal Customer,18,Personal Travel,Eco,231,3,5,3,3,4,3,4,4,5,5,5,3,3,4,32,53.0,neutral or dissatisfied +76411,59796,Male,Loyal Customer,16,Personal Travel,Eco Plus,895,1,3,1,1,3,1,3,3,4,5,1,1,5,3,17,0.0,neutral or dissatisfied +76412,4691,Male,Loyal Customer,8,Personal Travel,Eco,364,3,4,3,4,5,3,2,5,2,1,3,4,4,5,0,0.0,neutral or dissatisfied +76413,102394,Male,Loyal Customer,27,Business travel,Eco,223,5,3,3,3,5,5,5,5,3,1,5,2,5,5,0,0.0,satisfied +76414,117157,Male,Loyal Customer,37,Personal Travel,Eco,304,3,4,3,4,2,3,2,2,5,4,4,3,5,2,72,61.0,neutral or dissatisfied +76415,122492,Male,Loyal Customer,50,Business travel,Eco Plus,808,2,4,4,4,2,2,2,2,2,2,3,4,3,2,7,14.0,neutral or dissatisfied +76416,80318,Female,Loyal Customer,40,Personal Travel,Eco,746,1,3,1,4,4,1,4,4,2,2,3,2,4,4,0,14.0,neutral or dissatisfied +76417,69583,Female,Loyal Customer,62,Personal Travel,Eco,2586,1,2,1,2,1,4,5,1,4,3,2,5,4,5,0,37.0,neutral or dissatisfied +76418,70157,Female,Loyal Customer,67,Personal Travel,Eco,460,2,5,2,2,3,4,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +76419,8600,Female,Loyal Customer,44,Business travel,Business,3918,0,4,0,4,4,4,4,1,1,1,1,3,1,5,0,0.0,satisfied +76420,8506,Male,disloyal Customer,34,Business travel,Business,862,3,3,3,1,2,3,2,2,3,5,5,3,4,2,63,53.0,neutral or dissatisfied +76421,85234,Male,Loyal Customer,32,Business travel,Business,2845,1,1,1,1,4,4,4,4,4,1,4,1,5,4,12,4.0,satisfied +76422,44962,Male,Loyal Customer,50,Personal Travel,Eco Plus,397,5,4,5,4,3,5,3,3,3,5,5,5,4,3,0,0.0,satisfied +76423,107438,Male,Loyal Customer,31,Personal Travel,Eco,468,4,4,1,4,3,1,3,3,5,5,5,2,2,3,0,11.0,neutral or dissatisfied +76424,83592,Male,disloyal Customer,44,Business travel,Business,409,3,3,3,1,3,3,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +76425,26900,Male,Loyal Customer,31,Business travel,Business,1774,2,2,2,2,4,4,4,4,3,4,3,1,2,4,0,0.0,satisfied +76426,110936,Male,Loyal Customer,58,Personal Travel,Eco,545,1,4,1,3,2,1,2,2,2,5,4,1,5,2,0,0.0,neutral or dissatisfied +76427,28495,Male,disloyal Customer,33,Business travel,Business,2640,2,2,2,3,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +76428,14184,Male,Loyal Customer,35,Business travel,Business,2846,3,3,3,3,2,4,4,4,4,4,4,5,4,3,18,8.0,satisfied +76429,68147,Female,Loyal Customer,54,Personal Travel,Business,597,3,0,4,3,5,5,5,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +76430,80895,Female,Loyal Customer,45,Personal Travel,Eco Plus,484,3,5,3,4,3,5,5,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +76431,30261,Female,Loyal Customer,29,Business travel,Eco,836,0,0,0,4,5,0,3,5,3,2,5,1,2,5,0,0.0,satisfied +76432,27509,Female,Loyal Customer,59,Business travel,Eco,650,5,1,5,1,3,4,2,5,5,5,5,1,5,1,0,0.0,satisfied +76433,58359,Male,disloyal Customer,37,Business travel,Eco,199,4,5,4,2,4,4,5,4,2,1,4,5,1,4,25,20.0,neutral or dissatisfied +76434,70280,Female,disloyal Customer,20,Business travel,Eco,852,4,4,4,4,5,4,5,5,4,5,3,4,3,5,20,0.0,neutral or dissatisfied +76435,97893,Male,Loyal Customer,25,Business travel,Business,616,3,3,3,3,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +76436,68841,Male,Loyal Customer,52,Business travel,Business,936,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +76437,12096,Female,Loyal Customer,37,Business travel,Business,3117,4,4,3,4,1,4,3,5,5,5,5,3,5,2,0,0.0,satisfied +76438,129596,Female,Loyal Customer,56,Business travel,Business,2053,5,5,5,5,2,5,4,4,4,4,4,5,4,3,1,5.0,satisfied +76439,106685,Female,Loyal Customer,31,Personal Travel,Eco,451,1,2,1,4,1,1,1,1,2,1,4,4,4,1,0,5.0,neutral or dissatisfied +76440,65996,Male,Loyal Customer,58,Business travel,Business,1345,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +76441,126773,Female,Loyal Customer,45,Business travel,Business,2402,4,4,4,4,4,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +76442,25073,Female,Loyal Customer,27,Business travel,Eco,1084,4,1,1,1,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +76443,58244,Male,disloyal Customer,14,Business travel,Eco Plus,925,1,3,0,3,1,0,1,1,4,4,4,1,3,1,32,19.0,neutral or dissatisfied +76444,122060,Female,disloyal Customer,25,Business travel,Eco,83,1,1,1,3,1,1,1,1,4,4,4,1,3,1,0,11.0,neutral or dissatisfied +76445,9484,Male,Loyal Customer,40,Business travel,Business,3360,5,5,5,5,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +76446,28293,Male,Loyal Customer,48,Business travel,Business,3497,1,1,1,1,5,5,3,4,4,4,4,5,4,4,0,7.0,satisfied +76447,128805,Male,Loyal Customer,59,Business travel,Business,2586,2,2,2,2,4,4,4,5,3,3,5,4,5,4,20,11.0,satisfied +76448,111197,Male,Loyal Customer,58,Business travel,Business,1447,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +76449,15416,Female,Loyal Customer,46,Business travel,Business,3986,5,5,5,5,2,4,1,5,5,5,5,2,5,5,0,0.0,satisfied +76450,112413,Male,Loyal Customer,46,Business travel,Business,948,2,2,2,2,1,3,3,2,2,2,2,3,2,1,1,16.0,neutral or dissatisfied +76451,45784,Female,Loyal Customer,22,Business travel,Business,391,3,2,2,2,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +76452,30576,Male,disloyal Customer,10,Business travel,Eco,628,4,0,4,3,3,4,1,3,2,1,5,4,5,3,1,0.0,satisfied +76453,82923,Female,Loyal Customer,29,Business travel,Eco Plus,594,4,2,2,2,4,4,4,4,2,5,3,4,4,4,18,0.0,neutral or dissatisfied +76454,12557,Male,Loyal Customer,17,Personal Travel,Eco,788,1,4,0,3,3,0,3,3,4,3,3,3,3,3,52,48.0,neutral or dissatisfied +76455,126951,Female,Loyal Customer,47,Business travel,Business,2049,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +76456,58136,Female,Loyal Customer,48,Personal Travel,Eco Plus,589,4,4,4,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +76457,48303,Male,Loyal Customer,35,Business travel,Eco,1499,3,3,3,3,3,3,3,3,1,5,2,2,1,3,23,33.0,neutral or dissatisfied +76458,21140,Male,Loyal Customer,27,Business travel,Eco Plus,227,3,5,3,5,3,4,3,3,4,1,2,1,1,3,0,0.0,satisfied +76459,98431,Female,Loyal Customer,44,Personal Travel,Eco,1910,2,5,2,2,2,5,4,5,5,2,5,4,5,4,8,23.0,neutral or dissatisfied +76460,9643,Male,Loyal Customer,41,Business travel,Business,277,1,1,1,1,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +76461,120727,Male,Loyal Customer,26,Business travel,Eco Plus,90,2,5,5,5,2,2,4,2,4,2,4,1,3,2,15,11.0,neutral or dissatisfied +76462,16497,Female,Loyal Customer,55,Business travel,Business,1800,5,5,3,5,3,5,4,5,5,5,5,1,5,2,0,0.0,satisfied +76463,64855,Female,Loyal Customer,33,Business travel,Business,3643,1,2,2,2,4,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +76464,37274,Female,Loyal Customer,24,Business travel,Business,1005,2,2,2,2,4,4,4,4,1,3,4,1,5,4,11,0.0,satisfied +76465,115225,Male,disloyal Customer,24,Business travel,Eco,446,2,1,2,3,2,2,1,2,1,5,3,1,2,2,51,66.0,neutral or dissatisfied +76466,18457,Female,Loyal Customer,41,Business travel,Business,305,0,0,0,3,2,3,1,2,2,2,2,4,2,1,0,0.0,satisfied +76467,15044,Male,Loyal Customer,49,Business travel,Eco,516,4,4,4,4,4,4,4,4,5,2,2,4,4,4,0,0.0,satisfied +76468,92034,Male,Loyal Customer,31,Business travel,Business,1535,3,3,3,3,3,4,3,3,5,4,5,5,5,3,3,0.0,satisfied +76469,82177,Female,Loyal Customer,66,Personal Travel,Eco Plus,237,1,4,0,5,5,5,4,3,3,0,3,5,3,3,18,19.0,neutral or dissatisfied +76470,35793,Male,Loyal Customer,26,Personal Travel,Eco,200,2,2,2,3,2,2,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +76471,7125,Male,Loyal Customer,48,Business travel,Business,3800,1,3,1,1,5,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +76472,126337,Male,Loyal Customer,48,Personal Travel,Eco,631,4,5,4,4,5,4,5,5,3,4,4,4,4,5,12,7.0,neutral or dissatisfied +76473,109815,Male,disloyal Customer,37,Business travel,Business,1052,3,3,3,2,3,3,4,3,3,2,5,5,5,3,8,0.0,neutral or dissatisfied +76474,5456,Female,Loyal Customer,18,Business travel,Business,265,3,3,3,3,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +76475,52108,Female,Loyal Customer,67,Personal Travel,Eco,438,3,4,3,3,2,5,5,3,3,3,4,4,3,4,104,101.0,neutral or dissatisfied +76476,99057,Female,Loyal Customer,58,Business travel,Business,3490,3,3,3,3,3,4,5,4,4,4,4,3,4,3,12,6.0,satisfied +76477,35324,Male,Loyal Customer,26,Business travel,Business,3106,1,0,0,3,3,0,2,3,4,2,2,2,3,3,0,9.0,neutral or dissatisfied +76478,120949,Male,Loyal Customer,36,Business travel,Business,1783,5,5,5,5,5,4,5,3,3,4,3,3,3,3,2,0.0,satisfied +76479,9057,Female,Loyal Customer,60,Business travel,Business,2207,1,1,1,1,5,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +76480,100956,Female,Loyal Customer,34,Business travel,Business,1204,3,4,4,4,1,3,3,3,3,3,3,2,3,3,36,28.0,neutral or dissatisfied +76481,99777,Male,disloyal Customer,24,Business travel,Business,584,5,0,5,1,3,5,4,3,5,4,4,3,4,3,13,11.0,satisfied +76482,48106,Male,Loyal Customer,66,Business travel,Business,259,5,5,4,5,3,2,2,4,4,4,4,4,4,2,0,0.0,satisfied +76483,46522,Male,Loyal Customer,64,Business travel,Business,141,1,1,3,1,1,3,2,5,5,5,4,2,5,5,0,0.0,satisfied +76484,14029,Female,Loyal Customer,42,Business travel,Business,1117,1,1,1,1,1,1,5,4,4,4,4,2,4,3,0,0.0,satisfied +76485,65637,Female,Loyal Customer,42,Business travel,Business,2365,0,0,0,3,3,4,4,4,4,5,5,5,4,5,0,0.0,satisfied +76486,49546,Male,Loyal Customer,39,Business travel,Business,153,3,3,3,3,4,5,1,3,3,4,4,4,3,3,0,1.0,satisfied +76487,27539,Male,Loyal Customer,18,Personal Travel,Eco,671,3,2,3,2,3,3,3,3,3,1,1,3,2,3,0,0.0,neutral or dissatisfied +76488,64021,Male,Loyal Customer,60,Business travel,Business,3916,1,1,1,1,5,4,4,4,4,5,4,3,4,5,1,8.0,satisfied +76489,91230,Male,Loyal Customer,67,Personal Travel,Eco,581,3,5,3,1,2,3,2,2,5,4,4,4,4,2,72,69.0,neutral or dissatisfied +76490,71061,Male,Loyal Customer,53,Personal Travel,Eco,802,1,5,1,3,2,1,2,2,3,5,4,5,4,2,31,39.0,neutral or dissatisfied +76491,68627,Female,Loyal Customer,48,Business travel,Business,1700,0,4,0,4,3,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +76492,57206,Male,Loyal Customer,23,Business travel,Business,1514,1,1,1,1,5,5,5,5,4,2,4,5,5,5,1,0.0,satisfied +76493,26470,Male,Loyal Customer,35,Personal Travel,Eco,925,3,4,3,2,3,3,3,3,3,4,4,3,4,3,2,0.0,neutral or dissatisfied +76494,51065,Female,Loyal Customer,21,Personal Travel,Eco,373,3,4,3,2,4,3,4,4,2,3,4,5,2,4,31,22.0,neutral or dissatisfied +76495,114327,Male,Loyal Customer,23,Personal Travel,Eco,909,4,5,4,2,4,4,4,4,5,4,3,2,4,4,1,0.0,neutral or dissatisfied +76496,13106,Male,Loyal Customer,33,Business travel,Business,1990,5,5,5,5,4,4,4,4,4,1,5,5,1,4,0,0.0,satisfied +76497,94270,Male,disloyal Customer,42,Business travel,Business,293,4,3,3,4,5,4,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +76498,66086,Male,Loyal Customer,24,Personal Travel,Eco,1345,4,4,4,3,5,4,2,5,5,1,5,5,4,5,26,33.0,neutral or dissatisfied +76499,39190,Female,Loyal Customer,11,Personal Travel,Eco Plus,311,3,4,5,1,5,5,1,5,5,2,4,4,4,5,32,75.0,neutral or dissatisfied +76500,8228,Male,Loyal Customer,21,Personal Travel,Eco,294,2,5,2,3,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +76501,244,Male,disloyal Customer,30,Business travel,Business,719,2,2,2,3,3,2,3,3,2,2,2,1,2,3,45,41.0,neutral or dissatisfied +76502,69329,Female,Loyal Customer,47,Business travel,Business,1967,3,3,5,3,3,5,5,5,5,5,5,4,5,4,81,89.0,satisfied +76503,31185,Male,Loyal Customer,48,Personal Travel,Eco,349,3,4,3,2,2,3,3,2,5,3,4,4,4,2,28,29.0,neutral or dissatisfied +76504,83927,Male,Loyal Customer,64,Business travel,Business,304,5,3,5,5,5,4,4,4,4,4,4,3,4,5,0,8.0,satisfied +76505,112060,Male,Loyal Customer,44,Business travel,Eco,1754,2,1,2,2,2,2,2,2,1,2,1,1,2,2,0,0.0,neutral or dissatisfied +76506,40816,Male,Loyal Customer,25,Business travel,Business,2739,3,4,1,4,3,3,3,3,3,5,4,3,4,3,16,8.0,neutral or dissatisfied +76507,113780,Female,Loyal Customer,41,Business travel,Business,3170,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +76508,93259,Male,Loyal Customer,54,Business travel,Business,1524,1,1,1,1,3,4,4,5,5,5,5,4,5,3,17,15.0,satisfied +76509,52698,Male,Loyal Customer,30,Personal Travel,Eco Plus,160,2,4,2,1,4,2,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +76510,80550,Male,disloyal Customer,15,Business travel,Eco,870,1,0,0,5,5,0,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +76511,96632,Male,disloyal Customer,11,Business travel,Eco,1036,3,3,3,5,3,3,3,3,4,3,5,4,4,3,4,2.0,neutral or dissatisfied +76512,41580,Female,Loyal Customer,51,Personal Travel,Eco,1504,2,4,2,2,4,3,4,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +76513,128666,Female,disloyal Customer,46,Business travel,Business,2288,2,3,3,3,2,5,5,5,5,5,4,5,3,5,0,10.0,neutral or dissatisfied +76514,94497,Female,Loyal Customer,32,Business travel,Business,3200,1,2,2,2,1,1,1,1,4,4,3,2,3,1,38,21.0,neutral or dissatisfied +76515,103444,Female,disloyal Customer,33,Business travel,Business,393,3,3,3,4,3,3,3,3,4,3,4,3,5,3,10,8.0,neutral or dissatisfied +76516,40748,Female,Loyal Customer,30,Business travel,Business,2303,3,5,3,3,2,2,2,2,4,4,2,3,1,2,0,0.0,satisfied +76517,71653,Male,Loyal Customer,21,Personal Travel,Eco,1120,2,4,2,4,1,2,1,1,5,5,4,5,5,1,38,50.0,neutral or dissatisfied +76518,113017,Female,Loyal Customer,31,Personal Travel,Eco Plus,1751,2,1,2,3,2,2,2,2,3,3,4,1,3,2,9,7.0,neutral or dissatisfied +76519,81236,Male,Loyal Customer,10,Personal Travel,Eco,223,2,5,2,4,3,2,3,3,3,5,4,4,4,3,52,47.0,neutral or dissatisfied +76520,122657,Male,Loyal Customer,44,Business travel,Business,361,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +76521,85583,Female,disloyal Customer,27,Business travel,Eco,259,3,4,3,4,2,3,2,2,2,5,4,1,4,2,25,23.0,neutral or dissatisfied +76522,11714,Male,Loyal Customer,56,Business travel,Business,3805,3,3,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +76523,14780,Female,Loyal Customer,51,Business travel,Business,2065,3,4,4,4,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +76524,9007,Female,Loyal Customer,32,Business travel,Business,2423,1,1,1,1,4,4,5,4,5,2,5,5,5,4,0,0.0,satisfied +76525,99297,Female,disloyal Customer,25,Business travel,Business,448,2,5,2,1,1,2,1,1,3,3,5,3,4,1,13,2.0,neutral or dissatisfied +76526,80301,Male,Loyal Customer,41,Business travel,Business,746,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,17.0,satisfied +76527,71316,Male,Loyal Customer,41,Business travel,Business,1514,5,5,5,5,2,5,4,4,4,4,4,3,4,3,0,3.0,satisfied +76528,69355,Male,Loyal Customer,23,Business travel,Business,3991,1,1,1,1,3,4,3,3,5,3,5,5,4,3,0,0.0,satisfied +76529,27875,Male,Loyal Customer,24,Business travel,Eco Plus,680,1,1,1,1,1,1,3,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +76530,72059,Male,Loyal Customer,38,Business travel,Business,2486,5,5,5,5,2,3,5,5,5,5,5,3,5,3,57,55.0,satisfied +76531,26279,Male,Loyal Customer,69,Personal Travel,Eco,859,2,3,2,3,1,2,1,1,3,4,1,2,4,1,5,6.0,neutral or dissatisfied +76532,96791,Male,disloyal Customer,24,Business travel,Business,1105,5,1,5,1,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +76533,26736,Female,disloyal Customer,25,Business travel,Eco Plus,406,2,1,2,4,4,2,2,4,4,5,4,4,4,4,9,5.0,neutral or dissatisfied +76534,51981,Male,Loyal Customer,63,Personal Travel,Eco,936,2,3,2,3,2,3,3,3,3,4,3,3,1,3,166,151.0,neutral or dissatisfied +76535,124702,Female,disloyal Customer,26,Business travel,Eco,399,2,4,2,4,2,2,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +76536,16620,Male,Loyal Customer,38,Personal Travel,Eco,1008,3,2,3,3,5,3,5,5,3,3,3,3,2,5,0,0.0,neutral or dissatisfied +76537,106884,Female,Loyal Customer,62,Business travel,Eco,577,2,2,2,2,2,3,3,2,2,2,2,2,2,2,7,12.0,neutral or dissatisfied +76538,81412,Male,disloyal Customer,21,Business travel,Eco,393,3,0,4,4,2,4,2,2,3,4,4,3,4,2,1,0.0,neutral or dissatisfied +76539,1379,Male,disloyal Customer,36,Business travel,Eco Plus,134,2,2,2,4,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +76540,27556,Male,Loyal Customer,56,Personal Travel,Eco,937,1,5,1,2,3,1,3,3,5,5,5,4,5,3,7,6.0,neutral or dissatisfied +76541,79542,Male,Loyal Customer,42,Business travel,Eco,762,3,5,5,5,3,3,3,3,3,1,4,3,3,3,9,0.0,neutral or dissatisfied +76542,80807,Male,Loyal Customer,28,Business travel,Business,484,2,2,2,2,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +76543,127533,Female,Loyal Customer,25,Business travel,Business,1009,2,2,2,2,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +76544,116539,Male,Loyal Customer,44,Personal Travel,Eco,371,2,2,2,3,4,2,1,4,2,1,4,1,3,4,1,0.0,neutral or dissatisfied +76545,71668,Female,Loyal Customer,35,Personal Travel,Eco,1197,3,4,3,2,4,3,4,4,5,3,2,3,5,4,0,0.0,neutral or dissatisfied +76546,11892,Female,Loyal Customer,29,Business travel,Business,1647,1,1,1,1,4,4,4,4,3,5,4,3,4,4,0,1.0,satisfied +76547,84599,Female,disloyal Customer,24,Business travel,Business,669,4,0,3,3,3,3,4,3,4,2,4,4,5,3,0,1.0,satisfied +76548,82715,Male,Loyal Customer,27,Personal Travel,Eco,632,2,1,2,3,1,2,1,1,2,5,2,3,3,1,0,0.0,neutral or dissatisfied +76549,34231,Female,disloyal Customer,26,Business travel,Eco Plus,1237,1,1,1,2,5,1,5,5,4,5,4,2,1,5,0,0.0,neutral or dissatisfied +76550,44535,Female,disloyal Customer,25,Business travel,Eco,157,3,3,3,3,2,3,2,2,1,5,4,1,3,2,0,0.0,neutral or dissatisfied +76551,86643,Male,Loyal Customer,43,Business travel,Business,2985,5,5,5,5,2,1,3,4,4,4,4,4,4,1,0,0.0,satisfied +76552,121648,Female,Loyal Customer,56,Business travel,Business,2009,3,3,3,3,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +76553,48858,Male,Loyal Customer,46,Business travel,Business,2189,0,5,0,1,4,4,3,1,1,1,1,3,1,3,0,16.0,satisfied +76554,85177,Female,disloyal Customer,40,Business travel,Business,689,1,1,1,4,5,1,5,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +76555,2482,Female,disloyal Customer,25,Business travel,Business,1379,4,5,4,5,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +76556,53837,Female,Loyal Customer,66,Business travel,Eco,224,2,2,2,2,5,3,4,2,2,2,2,3,2,1,7,19.0,neutral or dissatisfied +76557,14364,Female,Loyal Customer,40,Business travel,Eco,948,4,2,2,2,4,4,4,4,3,5,3,1,3,4,0,0.0,satisfied +76558,9240,Male,Loyal Customer,51,Business travel,Business,177,1,4,4,4,3,1,1,3,3,3,1,1,3,2,87,81.0,neutral or dissatisfied +76559,69199,Male,disloyal Customer,36,Business travel,Business,733,2,2,2,3,1,2,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +76560,58932,Female,Loyal Customer,30,Personal Travel,Eco,888,3,4,4,3,5,4,5,5,4,5,5,3,5,5,109,112.0,neutral or dissatisfied +76561,17173,Female,disloyal Customer,26,Business travel,Eco,643,3,4,3,4,5,3,5,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +76562,81704,Female,Loyal Customer,27,Personal Travel,Eco,907,2,3,3,1,3,3,3,3,3,2,4,1,1,3,0,9.0,neutral or dissatisfied +76563,75856,Female,Loyal Customer,29,Personal Travel,Eco,1440,3,5,3,3,5,3,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +76564,58561,Female,Loyal Customer,39,Business travel,Eco Plus,1114,2,2,2,2,2,2,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +76565,424,Female,Loyal Customer,51,Business travel,Business,3873,4,1,4,4,4,5,4,4,4,4,4,4,4,3,2,0.0,satisfied +76566,100103,Female,Loyal Customer,39,Business travel,Business,725,1,1,1,1,2,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +76567,107806,Female,disloyal Customer,17,Business travel,Eco,349,3,3,3,3,2,3,2,2,2,1,3,3,4,2,0,0.0,neutral or dissatisfied +76568,21447,Female,disloyal Customer,23,Business travel,Eco,377,4,1,4,4,2,4,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +76569,95366,Female,Loyal Customer,13,Personal Travel,Eco,277,3,3,3,3,5,3,5,5,2,3,4,2,1,5,9,9.0,neutral or dissatisfied +76570,58970,Female,Loyal Customer,42,Personal Travel,Business,1744,0,3,0,3,5,3,4,4,4,0,4,3,4,3,10,0.0,satisfied +76571,100645,Male,Loyal Customer,61,Personal Travel,Eco,349,2,2,1,3,1,1,1,1,4,2,3,3,3,1,0,0.0,neutral or dissatisfied +76572,55789,Female,Loyal Customer,41,Business travel,Business,2400,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +76573,122268,Female,Loyal Customer,67,Personal Travel,Eco,573,3,5,3,2,5,5,4,3,3,3,3,3,3,3,7,3.0,neutral or dissatisfied +76574,45728,Female,Loyal Customer,41,Personal Travel,Eco,1068,1,5,1,1,2,1,2,2,4,3,5,4,4,2,0,17.0,neutral or dissatisfied +76575,96967,Female,Loyal Customer,59,Business travel,Business,2205,3,3,3,3,2,4,5,5,5,4,5,4,5,4,5,0.0,satisfied +76576,26186,Female,Loyal Customer,33,Business travel,Eco,270,3,5,5,5,3,3,3,3,3,2,3,4,3,3,39,30.0,neutral or dissatisfied +76577,118915,Female,Loyal Customer,44,Personal Travel,Eco,587,4,4,4,4,4,5,5,3,3,4,3,4,3,5,1,0.0,satisfied +76578,8421,Female,Loyal Customer,48,Business travel,Eco,862,2,2,2,2,1,4,4,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +76579,103868,Male,Loyal Customer,14,Personal Travel,Eco,869,2,5,2,2,1,2,1,1,5,2,1,1,1,1,12,0.0,neutral or dissatisfied +76580,29693,Male,disloyal Customer,24,Business travel,Eco,1542,2,2,2,2,2,2,2,2,4,5,3,1,4,2,0,0.0,neutral or dissatisfied +76581,86132,Male,Loyal Customer,56,Business travel,Business,226,0,0,0,2,4,4,4,4,4,4,4,4,4,5,0,3.0,satisfied +76582,114226,Male,Loyal Customer,36,Business travel,Business,862,2,2,2,2,3,5,5,5,5,5,5,4,5,3,21,1.0,satisfied +76583,63210,Female,Loyal Customer,43,Business travel,Business,3657,0,0,0,4,2,4,5,2,2,2,2,5,2,5,0,1.0,satisfied +76584,106846,Male,Loyal Customer,22,Personal Travel,Eco,1733,1,4,1,2,2,1,2,2,4,4,5,4,2,2,28,14.0,neutral or dissatisfied +76585,125217,Male,Loyal Customer,65,Personal Travel,Eco,651,4,3,4,3,1,4,1,1,1,1,3,4,4,1,0,0.0,satisfied +76586,90767,Female,disloyal Customer,22,Business travel,Eco,223,3,2,3,2,3,3,3,3,3,5,2,4,2,3,11,38.0,neutral or dissatisfied +76587,22304,Female,Loyal Customer,56,Business travel,Business,143,3,3,3,3,3,4,1,4,4,5,3,2,4,2,0,0.0,satisfied +76588,39263,Female,Loyal Customer,39,Business travel,Business,2176,4,5,5,5,2,3,3,3,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +76589,88552,Male,Loyal Customer,16,Personal Travel,Eco,515,3,4,3,4,4,3,1,4,3,5,4,5,5,4,15,12.0,neutral or dissatisfied +76590,110957,Male,Loyal Customer,39,Business travel,Business,319,0,0,0,2,4,5,5,4,4,4,4,5,4,3,31,39.0,satisfied +76591,47832,Male,Loyal Customer,60,Business travel,Business,1705,5,5,5,5,1,2,2,5,5,5,5,4,5,1,0,0.0,satisfied +76592,124625,Male,disloyal Customer,20,Business travel,Eco,1273,2,2,2,4,3,2,3,3,3,1,4,4,4,3,0,1.0,neutral or dissatisfied +76593,13149,Male,Loyal Customer,32,Personal Travel,Eco,562,1,2,1,4,4,1,4,4,2,5,3,2,3,4,87,88.0,neutral or dissatisfied +76594,51104,Female,Loyal Customer,39,Personal Travel,Eco,373,2,3,2,4,3,2,3,3,1,4,2,4,5,3,8,15.0,neutral or dissatisfied +76595,48284,Male,Loyal Customer,12,Personal Travel,Eco Plus,236,2,3,2,1,1,2,5,1,1,4,1,4,3,1,32,25.0,neutral or dissatisfied +76596,4285,Male,Loyal Customer,67,Personal Travel,Eco,502,4,4,4,3,5,4,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +76597,12924,Female,disloyal Customer,35,Business travel,Eco,809,2,2,2,4,3,2,3,3,1,3,3,2,4,3,7,13.0,neutral or dissatisfied +76598,85214,Female,Loyal Customer,29,Business travel,Business,1618,1,1,1,1,4,4,4,4,4,3,5,3,4,4,4,0.0,satisfied +76599,57267,Female,disloyal Customer,13,Business travel,Business,804,5,4,5,3,4,5,4,4,3,4,4,4,5,4,0,0.0,satisfied +76600,115900,Male,disloyal Customer,19,Business travel,Eco,342,2,0,2,3,4,2,4,4,5,1,2,3,1,4,0,0.0,neutral or dissatisfied +76601,120462,Female,Loyal Customer,37,Personal Travel,Eco,366,2,1,2,2,1,2,1,1,4,5,3,2,2,1,0,0.0,neutral or dissatisfied +76602,35728,Female,Loyal Customer,9,Personal Travel,Eco Plus,2475,3,2,4,4,4,4,2,4,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +76603,25427,Male,disloyal Customer,27,Business travel,Business,269,1,1,1,4,4,1,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +76604,69112,Male,Loyal Customer,60,Business travel,Eco Plus,989,5,2,2,2,5,5,5,5,2,3,5,1,2,5,0,0.0,satisfied +76605,94976,Female,disloyal Customer,20,Business travel,Eco,187,4,4,4,4,5,4,5,5,1,1,3,3,3,5,0,0.0,neutral or dissatisfied +76606,125222,Male,Loyal Customer,33,Personal Travel,Eco,651,3,4,3,4,4,3,4,4,4,2,4,5,4,4,0,4.0,neutral or dissatisfied +76607,6353,Male,disloyal Customer,25,Business travel,Business,296,2,4,1,3,5,1,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +76608,39613,Female,Loyal Customer,58,Personal Travel,Eco,908,2,5,2,2,1,1,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +76609,80691,Male,Loyal Customer,51,Business travel,Business,2173,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +76610,82202,Female,Loyal Customer,59,Business travel,Business,2096,3,3,3,3,5,4,4,5,5,5,5,4,5,4,2,0.0,satisfied +76611,89938,Male,Loyal Customer,13,Personal Travel,Eco,1416,3,1,3,2,5,3,5,5,4,3,3,4,3,5,10,18.0,neutral or dissatisfied +76612,38580,Female,Loyal Customer,43,Personal Travel,Eco,2586,4,4,4,4,5,2,4,1,1,4,1,2,1,3,0,0.0,neutral or dissatisfied +76613,1393,Male,Loyal Customer,10,Personal Travel,Eco Plus,102,3,4,3,3,3,3,3,3,3,1,3,2,3,3,33,23.0,neutral or dissatisfied +76614,43654,Female,Loyal Customer,48,Business travel,Eco,695,5,5,5,5,3,2,1,5,5,5,5,3,5,3,0,0.0,satisfied +76615,114840,Female,disloyal Customer,38,Business travel,Business,333,5,4,4,5,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +76616,101620,Male,Loyal Customer,40,Personal Travel,Eco,1371,3,4,3,3,1,3,1,1,5,3,5,4,4,1,12,0.0,neutral or dissatisfied +76617,50651,Female,Loyal Customer,50,Personal Travel,Eco,190,1,4,0,3,3,3,4,3,3,0,3,1,3,4,0,0.0,neutral or dissatisfied +76618,71644,Female,Loyal Customer,41,Personal Travel,Eco,1120,2,4,2,3,2,2,4,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +76619,19648,Female,Loyal Customer,52,Business travel,Business,763,1,1,1,1,4,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +76620,96492,Female,Loyal Customer,17,Business travel,Business,2963,2,5,5,5,2,2,2,2,2,2,4,2,4,2,69,64.0,neutral or dissatisfied +76621,50981,Female,Loyal Customer,51,Personal Travel,Eco,308,2,2,2,3,4,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +76622,33198,Female,Loyal Customer,51,Business travel,Eco Plus,216,4,4,4,4,5,4,2,3,3,4,3,1,3,4,2,3.0,satisfied +76623,66533,Male,Loyal Customer,27,Business travel,Eco,733,2,2,2,2,2,2,2,2,3,4,4,4,3,2,23,19.0,neutral or dissatisfied +76624,122643,Male,Loyal Customer,50,Business travel,Business,2043,4,4,4,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +76625,96253,Female,Loyal Customer,24,Personal Travel,Eco,460,1,4,1,1,5,1,5,5,2,3,4,1,2,5,0,0.0,neutral or dissatisfied +76626,19104,Male,disloyal Customer,44,Business travel,Eco,287,2,0,1,3,4,1,5,4,2,3,5,1,4,4,0,9.0,neutral or dissatisfied +76627,53009,Female,Loyal Customer,33,Business travel,Business,1190,4,2,4,4,1,2,5,5,5,5,5,1,5,1,5,0.0,satisfied +76628,45283,Male,Loyal Customer,47,Business travel,Business,3444,3,1,1,1,5,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +76629,25114,Male,Loyal Customer,29,Business travel,Business,946,2,3,3,3,2,2,2,2,2,3,4,4,3,2,0,0.0,neutral or dissatisfied +76630,110169,Female,Loyal Customer,44,Personal Travel,Eco,1048,4,5,4,2,3,4,5,3,3,4,1,5,3,4,40,31.0,neutral or dissatisfied +76631,64094,Female,Loyal Customer,8,Personal Travel,Eco,919,1,5,1,3,2,1,2,2,4,4,4,3,4,2,5,28.0,neutral or dissatisfied +76632,45438,Male,Loyal Customer,62,Personal Travel,Eco,458,2,4,2,2,2,2,3,2,3,4,4,1,2,2,0,3.0,neutral or dissatisfied +76633,14014,Female,Loyal Customer,56,Business travel,Business,182,1,1,1,1,5,2,3,3,3,4,1,2,3,1,0,6.0,neutral or dissatisfied +76634,8573,Male,disloyal Customer,43,Business travel,Eco,109,2,1,2,2,3,2,3,3,1,4,2,1,2,3,0,0.0,neutral or dissatisfied +76635,83722,Female,Loyal Customer,8,Personal Travel,Eco Plus,577,3,5,3,1,1,3,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +76636,58188,Male,Loyal Customer,43,Business travel,Business,3672,5,5,5,5,2,4,5,5,5,5,5,4,5,5,10,4.0,satisfied +76637,79055,Male,Loyal Customer,36,Business travel,Business,2166,2,4,4,4,5,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +76638,23597,Male,Loyal Customer,40,Business travel,Business,589,5,5,5,5,3,5,1,4,4,4,4,4,4,3,43,30.0,satisfied +76639,108625,Female,Loyal Customer,66,Personal Travel,Eco Plus,696,4,2,4,2,3,2,2,2,2,4,2,3,2,3,31,62.0,satisfied +76640,127422,Female,Loyal Customer,40,Personal Travel,Eco,1009,2,5,2,2,4,2,4,4,2,4,3,2,1,4,0,0.0,neutral or dissatisfied +76641,39649,Female,Loyal Customer,52,Business travel,Eco,1136,5,5,5,5,1,4,4,5,5,5,5,5,5,1,1,38.0,satisfied +76642,100446,Male,Loyal Customer,47,Business travel,Business,1793,4,4,5,4,2,4,5,4,4,5,4,5,4,4,0,12.0,satisfied +76643,26667,Male,Loyal Customer,55,Business travel,Eco,515,1,3,3,3,1,1,1,1,4,4,3,1,4,1,92,81.0,neutral or dissatisfied +76644,32492,Male,Loyal Customer,39,Business travel,Business,102,2,2,2,2,4,4,2,5,5,5,5,4,5,2,9,5.0,satisfied +76645,81767,Female,Loyal Customer,54,Business travel,Business,1487,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +76646,80746,Female,Loyal Customer,8,Personal Travel,Eco,393,1,3,1,3,4,1,4,4,3,5,2,4,4,4,0,0.0,neutral or dissatisfied +76647,51982,Male,Loyal Customer,38,Personal Travel,Eco,347,1,5,1,1,4,1,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +76648,74178,Male,Loyal Customer,21,Personal Travel,Eco,641,2,3,2,2,2,2,5,2,1,3,5,1,2,2,73,77.0,neutral or dissatisfied +76649,11139,Male,Loyal Customer,15,Personal Travel,Eco,74,3,4,3,3,4,3,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +76650,112489,Female,Loyal Customer,20,Personal Travel,Eco,846,2,4,2,2,1,2,1,1,4,5,5,5,5,1,4,0.0,neutral or dissatisfied +76651,87854,Male,disloyal Customer,60,Personal Travel,Eco,214,2,4,0,4,1,0,1,1,3,5,3,4,3,1,0,0.0,neutral or dissatisfied +76652,18591,Male,Loyal Customer,47,Business travel,Business,2446,4,5,5,5,1,3,3,4,4,4,4,1,4,4,26,22.0,neutral or dissatisfied +76653,24797,Female,disloyal Customer,40,Business travel,Business,432,3,3,3,3,1,3,3,1,4,3,4,2,4,1,0,20.0,neutral or dissatisfied +76654,11996,Male,Loyal Customer,52,Personal Travel,Eco,643,0,5,0,2,2,0,1,2,5,5,5,4,4,2,0,0.0,satisfied +76655,7760,Male,Loyal Customer,42,Business travel,Business,3251,2,2,2,2,2,4,4,5,5,5,5,4,5,3,51,75.0,satisfied +76656,21426,Male,disloyal Customer,32,Business travel,Eco,331,1,0,1,1,3,1,3,3,5,4,2,3,1,3,0,0.0,neutral or dissatisfied +76657,30735,Male,Loyal Customer,20,Personal Travel,Eco,1069,2,3,2,2,1,2,1,1,3,1,2,4,2,1,0,2.0,neutral or dissatisfied +76658,92875,Female,Loyal Customer,51,Business travel,Business,151,2,2,2,2,3,5,5,3,3,4,5,4,3,4,0,0.0,satisfied +76659,5950,Female,Loyal Customer,20,Personal Travel,Eco,642,4,5,4,4,5,4,5,5,5,2,5,5,5,5,0,50.0,neutral or dissatisfied +76660,43858,Male,Loyal Customer,52,Business travel,Business,114,4,4,4,4,2,2,1,4,4,4,5,4,4,2,0,0.0,satisfied +76661,41347,Female,Loyal Customer,20,Business travel,Eco,956,4,4,4,4,4,4,5,4,4,2,3,5,1,4,34,21.0,satisfied +76662,87627,Male,Loyal Customer,41,Business travel,Business,3864,4,4,4,4,4,5,5,4,4,4,4,4,4,3,11,9.0,satisfied +76663,79487,Male,Loyal Customer,52,Personal Travel,Business,762,4,4,4,3,2,4,4,1,1,4,1,4,1,4,0,10.0,satisfied +76664,30597,Female,disloyal Customer,27,Business travel,Eco,472,4,0,4,4,3,4,3,3,5,1,4,1,2,3,0,0.0,satisfied +76665,112756,Female,Loyal Customer,34,Business travel,Business,2728,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +76666,3519,Female,Loyal Customer,42,Business travel,Business,2401,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +76667,13829,Male,Loyal Customer,39,Business travel,Business,594,5,5,5,5,1,4,3,4,4,5,4,1,4,5,0,0.0,satisfied +76668,49131,Male,Loyal Customer,57,Business travel,Eco,86,1,2,2,2,1,1,1,1,1,2,3,2,3,1,0,0.0,neutral or dissatisfied +76669,107496,Female,disloyal Customer,30,Business travel,Eco,711,3,4,4,3,2,4,5,2,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +76670,37631,Male,Loyal Customer,38,Personal Travel,Eco,944,3,4,2,2,5,2,5,5,2,2,1,1,4,5,0,0.0,neutral or dissatisfied +76671,75909,Female,Loyal Customer,34,Personal Travel,Eco,597,3,0,3,3,2,3,2,2,4,4,4,2,4,2,0,2.0,neutral or dissatisfied +76672,7731,Male,Loyal Customer,46,Business travel,Business,2803,5,5,5,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +76673,85774,Male,Loyal Customer,48,Business travel,Business,3896,2,2,2,2,4,5,4,5,5,5,5,4,5,5,37,26.0,satisfied +76674,25032,Female,disloyal Customer,44,Business travel,Eco,507,4,4,4,5,2,4,4,2,1,5,2,4,5,2,0,8.0,satisfied +76675,91830,Male,Loyal Customer,25,Business travel,Eco Plus,590,4,3,4,4,4,4,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +76676,108823,Male,Loyal Customer,65,Personal Travel,Business,1199,3,5,3,4,2,2,2,4,4,3,4,3,4,1,29,32.0,neutral or dissatisfied +76677,7035,Female,disloyal Customer,17,Business travel,Eco,147,3,1,3,3,5,3,5,5,3,2,3,1,4,5,65,80.0,neutral or dissatisfied +76678,605,Female,Loyal Customer,39,Business travel,Business,270,1,1,1,1,3,5,5,5,5,5,5,4,5,5,20,26.0,satisfied +76679,28191,Male,Loyal Customer,59,Personal Travel,Eco,834,2,3,2,3,5,2,5,5,5,1,1,3,3,5,0,0.0,neutral or dissatisfied +76680,11584,Female,Loyal Customer,40,Business travel,Eco,657,4,5,5,5,4,4,4,4,3,4,4,1,4,4,4,5.0,neutral or dissatisfied +76681,71916,Male,Loyal Customer,56,Personal Travel,Eco,1723,1,4,1,2,2,1,2,2,5,3,5,5,5,2,15,23.0,neutral or dissatisfied +76682,449,Male,disloyal Customer,42,Business travel,Business,282,4,4,4,3,3,4,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +76683,36888,Female,Loyal Customer,64,Personal Travel,Eco,1182,1,4,1,2,4,3,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +76684,51687,Male,Loyal Customer,51,Business travel,Eco,351,5,1,5,1,5,5,5,5,4,3,4,5,3,5,72,72.0,satisfied +76685,6866,Female,disloyal Customer,39,Business travel,Business,622,2,2,2,2,4,2,4,4,4,3,3,2,2,4,47,29.0,neutral or dissatisfied +76686,21045,Male,disloyal Customer,25,Business travel,Business,227,4,4,4,4,3,4,3,3,3,2,4,2,1,3,0,38.0,satisfied +76687,99784,Female,Loyal Customer,42,Business travel,Business,2428,3,3,3,3,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +76688,80352,Female,Loyal Customer,37,Business travel,Business,368,5,5,5,5,4,5,5,5,5,5,5,3,5,4,2,1.0,satisfied +76689,114104,Male,Loyal Customer,51,Business travel,Business,948,5,5,5,5,2,4,5,4,4,4,4,4,4,4,3,3.0,satisfied +76690,13215,Male,Loyal Customer,42,Business travel,Business,3228,4,4,4,4,3,5,2,4,4,4,4,5,4,3,0,0.0,satisfied +76691,66646,Male,disloyal Customer,22,Business travel,Eco,978,4,4,4,2,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +76692,92114,Female,Loyal Customer,19,Personal Travel,Eco,1532,3,5,3,4,4,3,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +76693,2654,Female,Loyal Customer,51,Business travel,Business,622,1,1,1,1,5,5,5,5,5,5,5,5,5,3,22,27.0,satisfied +76694,103817,Male,disloyal Customer,45,Business travel,Business,869,2,2,2,1,1,2,1,1,3,2,5,5,4,1,7,20.0,neutral or dissatisfied +76695,2027,Female,disloyal Customer,20,Business travel,Eco,812,0,0,0,3,3,0,2,3,4,3,5,5,4,3,0,0.0,satisfied +76696,33963,Female,Loyal Customer,52,Business travel,Business,1598,3,3,3,3,5,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +76697,115570,Male,Loyal Customer,43,Business travel,Business,3144,2,3,3,3,3,4,3,2,2,2,2,3,2,2,5,4.0,neutral or dissatisfied +76698,80723,Male,Loyal Customer,43,Business travel,Business,448,3,3,3,3,2,4,4,5,5,4,5,3,5,5,31,11.0,satisfied +76699,73418,Male,Loyal Customer,16,Business travel,Eco,1005,1,1,1,1,1,1,1,1,4,1,4,2,3,1,0,10.0,neutral or dissatisfied +76700,83257,Male,Loyal Customer,44,Business travel,Eco,1979,1,4,3,4,2,1,2,2,1,3,3,3,4,2,0,0.0,neutral or dissatisfied +76701,15135,Female,Loyal Customer,29,Business travel,Business,1949,3,1,1,1,3,3,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +76702,83597,Female,Loyal Customer,53,Business travel,Business,409,5,5,5,5,4,4,4,4,4,4,4,4,4,4,29,20.0,satisfied +76703,102369,Male,disloyal Customer,41,Business travel,Business,226,3,3,3,3,4,3,2,4,4,1,1,4,4,4,0,0.0,neutral or dissatisfied +76704,75503,Male,Loyal Customer,38,Personal Travel,Eco Plus,2342,5,3,5,3,1,5,2,1,1,5,3,2,2,1,0,0.0,satisfied +76705,67762,Male,Loyal Customer,54,Business travel,Business,3444,2,1,1,1,1,4,4,2,2,2,2,1,2,2,104,106.0,neutral or dissatisfied +76706,14456,Male,Loyal Customer,46,Business travel,Business,3848,2,2,1,2,3,5,5,5,5,5,5,1,5,4,30,26.0,satisfied +76707,89925,Female,Loyal Customer,39,Business travel,Eco,910,4,4,4,4,4,4,4,4,2,1,1,4,5,4,0,0.0,satisfied +76708,4474,Male,Loyal Customer,38,Personal Travel,Eco,1005,1,5,1,3,5,1,5,5,5,5,5,4,4,5,0,24.0,neutral or dissatisfied +76709,122173,Female,disloyal Customer,20,Business travel,Eco,544,2,0,2,5,3,2,3,3,3,3,4,4,5,3,24,15.0,neutral or dissatisfied +76710,72848,Female,Loyal Customer,15,Personal Travel,Eco Plus,1013,4,2,4,3,1,4,1,1,1,5,3,2,4,1,11,4.0,satisfied +76711,62192,Male,disloyal Customer,33,Business travel,Eco,982,4,4,4,1,2,4,2,2,2,2,3,2,3,2,31,0.0,neutral or dissatisfied +76712,33653,Female,Loyal Customer,57,Personal Travel,Eco,474,2,3,2,4,4,1,1,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +76713,9499,Male,disloyal Customer,37,Business travel,Business,239,1,1,1,4,5,1,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +76714,104835,Female,Loyal Customer,37,Business travel,Business,472,5,5,5,5,1,3,5,3,3,3,3,5,3,2,32,19.0,satisfied +76715,9400,Male,Loyal Customer,42,Business travel,Business,182,0,5,0,4,2,4,4,5,5,2,2,4,5,5,15,48.0,satisfied +76716,18774,Female,Loyal Customer,36,Personal Travel,Business,551,2,4,2,3,5,5,1,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +76717,13456,Male,Loyal Customer,31,Personal Travel,Eco,475,3,4,3,3,4,3,4,4,2,3,4,4,4,4,0,0.0,neutral or dissatisfied +76718,37546,Male,disloyal Customer,31,Business travel,Business,1069,4,4,4,4,5,4,2,5,4,5,4,1,3,5,72,114.0,neutral or dissatisfied +76719,37374,Male,disloyal Customer,39,Business travel,Eco,944,2,2,2,4,2,2,2,2,4,1,2,4,5,2,0,0.0,neutral or dissatisfied +76720,26388,Female,disloyal Customer,52,Business travel,Eco,534,3,0,3,2,1,3,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +76721,85535,Female,Loyal Customer,47,Business travel,Business,1848,5,5,5,5,4,5,4,5,5,5,5,4,5,4,6,5.0,satisfied +76722,111280,Male,Loyal Customer,10,Personal Travel,Eco,479,3,5,3,3,3,3,3,3,1,4,4,5,3,3,3,0.0,neutral or dissatisfied +76723,123758,Male,Loyal Customer,32,Business travel,Business,541,5,3,5,5,4,4,4,4,5,5,5,5,5,4,85,70.0,satisfied +76724,50211,Female,Loyal Customer,59,Business travel,Eco,77,2,5,5,5,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +76725,46041,Female,Loyal Customer,17,Business travel,Eco,964,1,1,1,1,1,1,1,4,3,3,3,1,2,1,140,156.0,neutral or dissatisfied +76726,56792,Male,Loyal Customer,61,Personal Travel,Business,1728,2,5,2,1,2,5,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +76727,11332,Male,Loyal Customer,38,Personal Travel,Eco,166,2,4,2,5,3,2,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +76728,91113,Male,Loyal Customer,37,Personal Travel,Eco,594,4,1,4,2,5,4,5,5,1,1,3,3,2,5,0,0.0,neutral or dissatisfied +76729,4028,Female,Loyal Customer,51,Business travel,Business,483,3,3,3,3,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +76730,97879,Male,Loyal Customer,39,Business travel,Business,722,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +76731,7481,Female,Loyal Customer,46,Business travel,Business,925,3,3,3,3,3,5,4,5,5,5,5,5,5,3,17,9.0,satisfied +76732,27588,Female,Loyal Customer,18,Personal Travel,Eco,954,2,4,2,5,3,2,4,3,3,4,4,5,5,3,12,1.0,neutral or dissatisfied +76733,82794,Female,Loyal Customer,58,Business travel,Business,3556,3,3,3,3,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +76734,7819,Female,Loyal Customer,36,Business travel,Business,1738,1,5,1,1,5,3,2,5,5,5,5,1,5,2,0,0.0,satisfied +76735,53531,Female,Loyal Customer,10,Business travel,Eco Plus,2419,2,4,4,4,2,4,2,2,5,3,3,2,4,2,0,0.0,neutral or dissatisfied +76736,41569,Male,Loyal Customer,59,Personal Travel,Eco,1464,3,5,3,2,3,3,3,3,4,5,4,4,5,3,64,90.0,neutral or dissatisfied +76737,107691,Female,Loyal Customer,34,Business travel,Business,251,3,3,2,3,2,5,4,5,5,5,5,5,5,3,37,24.0,satisfied +76738,63813,Male,Loyal Customer,41,Business travel,Business,3063,4,1,4,4,4,5,5,3,3,4,3,5,3,5,3,14.0,satisfied +76739,11019,Female,disloyal Customer,39,Business travel,Eco,312,1,0,1,1,2,1,2,2,3,1,1,1,4,2,0,0.0,neutral or dissatisfied +76740,82779,Male,Loyal Customer,19,Personal Travel,Eco,926,5,5,5,4,2,5,2,2,4,3,5,5,4,2,0,0.0,satisfied +76741,21609,Male,disloyal Customer,21,Business travel,Eco,853,4,4,4,3,1,4,1,1,5,5,2,5,5,1,3,0.0,satisfied +76742,114414,Female,Loyal Customer,31,Business travel,Business,447,1,1,1,1,5,5,5,5,3,4,4,4,4,5,5,0.0,satisfied +76743,58330,Male,Loyal Customer,53,Personal Travel,Eco,1739,2,4,2,4,2,2,2,2,3,5,4,3,5,2,5,6.0,neutral or dissatisfied +76744,74870,Male,Loyal Customer,28,Business travel,Business,2239,1,1,5,1,5,5,5,5,3,2,4,4,5,5,0,6.0,satisfied +76745,4960,Male,Loyal Customer,57,Personal Travel,Eco,931,3,4,3,3,4,3,4,4,4,5,4,3,5,4,0,13.0,neutral or dissatisfied +76746,84187,Male,Loyal Customer,68,Personal Travel,Business,432,1,4,1,4,4,4,4,5,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +76747,94124,Male,Loyal Customer,50,Business travel,Business,293,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +76748,37742,Female,Loyal Customer,37,Personal Travel,Eco,1056,3,5,3,1,4,3,4,4,5,2,1,4,3,4,0,0.0,neutral or dissatisfied +76749,49537,Female,Loyal Customer,51,Business travel,Business,1618,1,1,1,1,2,3,5,5,5,5,5,2,5,3,0,0.0,satisfied +76750,25749,Male,disloyal Customer,38,Business travel,Business,356,4,4,4,2,2,4,2,2,4,2,2,1,4,2,0,0.0,satisfied +76751,3057,Female,disloyal Customer,37,Business travel,Eco,340,4,4,4,3,2,4,2,2,3,5,3,2,4,2,0,6.0,neutral or dissatisfied +76752,67500,Male,Loyal Customer,36,Personal Travel,Eco Plus,641,2,5,2,4,3,2,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +76753,56089,Female,Loyal Customer,65,Business travel,Eco Plus,1086,5,1,1,1,5,5,5,4,4,2,1,5,2,5,0,0.0,satisfied +76754,123104,Male,Loyal Customer,57,Business travel,Business,3923,3,3,3,3,5,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +76755,76169,Female,Loyal Customer,18,Personal Travel,Eco,546,2,3,2,3,5,2,5,5,4,2,3,1,2,5,0,0.0,neutral or dissatisfied +76756,119649,Female,Loyal Customer,29,Business travel,Business,507,5,5,5,5,5,5,5,5,3,2,5,5,5,5,19,6.0,satisfied +76757,126749,Male,Loyal Customer,9,Personal Travel,Eco,2370,3,5,3,1,4,3,4,4,4,3,4,5,3,4,0,0.0,neutral or dissatisfied +76758,66037,Female,disloyal Customer,26,Business travel,Business,1055,3,2,2,2,2,2,2,2,5,3,5,3,5,2,5,5.0,neutral or dissatisfied +76759,90960,Male,Loyal Customer,63,Business travel,Business,3699,4,4,4,4,5,3,1,5,5,5,5,1,5,3,0,0.0,satisfied +76760,122136,Male,Loyal Customer,21,Personal Travel,Business,646,0,4,0,3,3,0,4,3,1,2,3,3,4,3,0,5.0,satisfied +76761,42072,Female,Loyal Customer,9,Personal Travel,Eco,116,1,4,0,4,4,0,4,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +76762,96515,Male,Loyal Customer,68,Personal Travel,Eco,436,2,5,2,5,5,2,5,5,4,5,5,5,5,5,110,92.0,neutral or dissatisfied +76763,104576,Male,Loyal Customer,38,Business travel,Business,3945,1,1,1,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +76764,17163,Male,disloyal Customer,29,Business travel,Eco,643,2,4,2,3,3,2,3,3,2,2,1,5,3,3,4,4.0,neutral or dissatisfied +76765,125981,Female,disloyal Customer,8,Business travel,Eco,590,3,4,3,1,1,3,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +76766,74462,Male,disloyal Customer,36,Business travel,Business,1438,2,3,3,4,1,3,1,1,5,3,4,4,5,1,12,10.0,neutral or dissatisfied +76767,77796,Male,Loyal Customer,33,Personal Travel,Eco,874,1,1,1,3,1,1,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +76768,94068,Male,Loyal Customer,41,Business travel,Business,441,4,4,3,4,5,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +76769,55183,Female,Loyal Customer,31,Business travel,Eco Plus,1635,2,2,3,2,2,2,2,2,2,4,4,3,3,2,21,17.0,neutral or dissatisfied +76770,45062,Female,Loyal Customer,48,Business travel,Eco,342,2,3,3,3,3,3,3,2,2,2,2,1,2,4,2,8.0,neutral or dissatisfied +76771,81279,Male,disloyal Customer,17,Business travel,Eco,1020,4,4,4,4,5,4,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +76772,41848,Male,Loyal Customer,30,Business travel,Business,483,3,3,3,3,3,5,3,3,1,5,5,4,4,3,0,0.0,satisfied +76773,74329,Male,Loyal Customer,19,Business travel,Business,1464,2,5,5,5,2,2,2,2,4,4,3,1,3,2,1,0.0,neutral or dissatisfied +76774,71472,Male,Loyal Customer,39,Business travel,Business,2443,1,3,1,1,4,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +76775,118644,Male,Loyal Customer,35,Business travel,Eco,370,1,3,3,3,1,1,1,1,3,5,3,3,4,1,7,2.0,neutral or dissatisfied +76776,43459,Female,disloyal Customer,25,Business travel,Eco,524,2,2,2,4,5,2,5,5,3,2,3,3,4,5,0,45.0,neutral or dissatisfied +76777,95224,Male,Loyal Customer,63,Personal Travel,Eco,496,1,4,5,3,1,5,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +76778,71636,Female,Loyal Customer,46,Personal Travel,Eco,1144,4,4,4,3,4,4,4,4,4,4,3,5,4,3,2,0.0,satisfied +76779,19484,Male,Loyal Customer,69,Personal Travel,Eco,177,3,4,3,3,2,3,3,2,4,4,5,4,5,2,0,16.0,neutral or dissatisfied +76780,94750,Female,Loyal Customer,60,Business travel,Business,192,0,4,0,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +76781,47159,Female,Loyal Customer,41,Business travel,Eco,748,4,3,3,3,4,5,4,4,1,2,5,5,5,4,0,0.0,satisfied +76782,72816,Female,Loyal Customer,31,Personal Travel,Eco Plus,1045,5,3,5,1,5,5,5,5,5,3,1,2,3,5,10,2.0,satisfied +76783,54823,Female,disloyal Customer,21,Business travel,Eco,641,2,1,2,4,2,2,2,2,1,2,4,3,3,2,0,0.0,neutral or dissatisfied +76784,115393,Female,Loyal Customer,41,Business travel,Business,2465,1,0,0,3,2,4,3,5,5,0,1,1,5,4,0,0.0,neutral or dissatisfied +76785,58425,Female,Loyal Customer,43,Business travel,Business,3047,2,2,2,2,1,1,1,3,3,3,3,3,3,3,39,20.0,satisfied +76786,111545,Female,Loyal Customer,43,Business travel,Business,1659,2,2,2,2,5,4,4,4,4,4,4,3,4,4,60,52.0,satisfied +76787,20526,Male,disloyal Customer,25,Business travel,Eco,606,1,0,1,1,3,1,5,3,4,2,1,5,4,3,0,0.0,neutral or dissatisfied +76788,16258,Male,Loyal Customer,32,Business travel,Business,946,5,5,4,5,4,4,4,4,1,1,4,2,3,4,0,22.0,satisfied +76789,32512,Female,Loyal Customer,42,Business travel,Business,3496,3,3,3,3,1,1,5,4,4,4,4,2,4,1,4,6.0,satisfied +76790,65055,Female,Loyal Customer,26,Personal Travel,Eco,190,3,3,3,3,5,3,5,5,1,1,4,4,3,5,34,102.0,neutral or dissatisfied +76791,96675,Male,Loyal Customer,58,Business travel,Business,3974,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +76792,30649,Male,Loyal Customer,55,Business travel,Eco,133,5,1,2,1,5,5,5,5,4,1,1,2,4,5,0,5.0,satisfied +76793,121684,Female,Loyal Customer,51,Personal Travel,Eco,328,3,5,3,2,4,3,4,1,1,3,1,4,1,5,0,3.0,neutral or dissatisfied +76794,67509,Male,Loyal Customer,35,Business travel,Business,1683,3,3,1,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +76795,36783,Female,disloyal Customer,15,Business travel,Eco,2602,3,3,3,4,3,4,4,4,5,4,4,4,4,4,26,17.0,neutral or dissatisfied +76796,31749,Male,Loyal Customer,22,Personal Travel,Eco Plus,853,1,4,0,3,5,0,1,5,4,2,5,5,5,5,6,0.0,neutral or dissatisfied +76797,37175,Female,Loyal Customer,23,Personal Travel,Eco,1189,2,4,2,4,5,2,5,5,5,5,4,4,4,5,77,83.0,neutral or dissatisfied +76798,7155,Male,Loyal Customer,50,Business travel,Business,135,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +76799,111778,Female,disloyal Customer,15,Business travel,Eco,1146,2,2,2,3,1,2,3,1,1,4,2,1,4,1,50,51.0,neutral or dissatisfied +76800,27016,Male,Loyal Customer,51,Personal Travel,Eco,954,2,4,2,3,4,2,4,4,1,4,4,2,4,4,17,19.0,neutral or dissatisfied +76801,79248,Male,Loyal Customer,44,Business travel,Business,1598,1,5,5,5,4,4,4,1,1,1,1,2,1,4,13,4.0,neutral or dissatisfied +76802,46342,Male,Loyal Customer,51,Business travel,Business,692,2,1,1,1,2,4,2,2,2,2,2,2,2,1,0,5.0,neutral or dissatisfied +76803,98076,Female,Loyal Customer,26,Personal Travel,Eco,1449,2,5,2,4,1,2,1,1,5,5,2,1,1,1,0,2.0,neutral or dissatisfied +76804,90964,Female,Loyal Customer,50,Business travel,Business,3520,2,5,5,5,2,2,2,4,1,4,4,2,3,2,338,322.0,neutral or dissatisfied +76805,92033,Female,Loyal Customer,40,Business travel,Business,1589,4,4,4,4,2,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +76806,92776,Female,Loyal Customer,35,Business travel,Eco,1671,3,1,1,1,3,3,3,3,3,3,2,1,4,3,0,20.0,neutral or dissatisfied +76807,11417,Male,disloyal Customer,37,Business travel,Business,301,5,5,5,3,4,5,4,4,5,2,5,4,4,4,0,0.0,satisfied +76808,13297,Female,disloyal Customer,16,Business travel,Eco,468,4,0,4,5,4,4,4,4,3,5,2,1,4,4,0,0.0,neutral or dissatisfied +76809,14182,Female,Loyal Customer,40,Business travel,Business,620,2,2,5,2,4,5,1,2,2,2,2,4,2,2,67,56.0,satisfied +76810,111792,Female,Loyal Customer,42,Business travel,Business,3348,2,2,2,2,2,5,5,5,5,5,5,3,5,4,10,8.0,satisfied +76811,53755,Male,disloyal Customer,39,Business travel,Eco,1195,3,3,3,3,3,1,1,2,4,3,2,1,5,1,170,222.0,neutral or dissatisfied +76812,71679,Female,Loyal Customer,21,Personal Travel,Eco,1182,3,3,3,1,2,3,2,2,5,1,4,3,1,2,0,0.0,neutral or dissatisfied +76813,86187,Female,Loyal Customer,55,Business travel,Eco,356,3,3,1,3,1,3,3,3,3,3,3,2,3,2,7,0.0,neutral or dissatisfied +76814,84970,Female,Loyal Customer,44,Personal Travel,Eco Plus,516,3,2,3,3,4,3,4,3,3,3,5,4,3,4,0,0.0,neutral or dissatisfied +76815,24348,Male,Loyal Customer,38,Personal Travel,Eco,634,2,5,2,2,4,2,3,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +76816,94677,Female,Loyal Customer,69,Business travel,Business,2038,1,5,5,5,2,2,2,2,2,2,1,2,2,2,21,17.0,neutral or dissatisfied +76817,124207,Male,Loyal Customer,43,Business travel,Eco,2176,3,2,2,2,4,3,4,4,4,2,2,3,4,4,0,0.0,satisfied +76818,113700,Male,Loyal Customer,57,Personal Travel,Eco,386,1,4,1,2,3,1,3,3,3,3,5,5,5,3,31,14.0,neutral or dissatisfied +76819,26541,Female,Loyal Customer,42,Personal Travel,Eco,990,1,4,1,4,2,4,4,1,1,1,1,4,1,5,0,0.0,neutral or dissatisfied +76820,88599,Male,Loyal Customer,17,Personal Travel,Eco,646,3,4,3,1,3,3,2,3,5,1,2,4,4,3,0,2.0,neutral or dissatisfied +76821,91887,Male,disloyal Customer,44,Business travel,Business,2586,4,4,4,2,2,4,2,2,4,3,5,4,4,2,0,0.0,satisfied +76822,109644,Female,Loyal Customer,39,Business travel,Business,3516,2,2,2,2,4,5,4,5,5,5,5,5,5,4,5,0.0,satisfied +76823,13010,Female,Loyal Customer,46,Business travel,Eco,438,5,2,2,2,3,1,4,5,5,5,5,1,5,5,0,0.0,satisfied +76824,53411,Female,disloyal Customer,22,Business travel,Eco,2442,2,2,2,3,2,5,5,2,3,3,4,5,3,5,2,14.0,neutral or dissatisfied +76825,110775,Male,Loyal Customer,20,Business travel,Eco,1166,3,2,2,2,3,3,2,3,1,2,3,2,3,3,0,8.0,neutral or dissatisfied +76826,2751,Female,disloyal Customer,23,Business travel,Eco,772,0,1,1,3,5,1,5,5,1,4,3,3,2,5,0,0.0,satisfied +76827,102350,Female,Loyal Customer,45,Business travel,Eco,407,3,1,1,1,5,3,3,3,3,3,3,3,3,1,50,40.0,neutral or dissatisfied +76828,59358,Male,disloyal Customer,39,Business travel,Business,2367,1,2,2,3,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +76829,40036,Female,Loyal Customer,10,Personal Travel,Eco,575,2,4,2,3,2,2,2,2,3,4,4,5,5,2,0,14.0,neutral or dissatisfied +76830,87536,Male,Loyal Customer,20,Personal Travel,Eco Plus,321,3,4,3,1,5,3,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +76831,45599,Female,Loyal Customer,44,Business travel,Eco,230,4,2,2,2,3,5,3,4,4,4,4,1,4,3,0,0.0,satisfied +76832,89343,Male,disloyal Customer,24,Business travel,Eco,948,1,1,1,3,2,1,4,2,5,3,4,4,5,2,20,0.0,neutral or dissatisfied +76833,78478,Female,Loyal Customer,39,Business travel,Eco,526,2,3,3,3,2,2,2,2,4,4,2,4,2,2,0,9.0,neutral or dissatisfied +76834,116731,Female,Loyal Customer,23,Personal Travel,Eco Plus,358,5,4,2,2,2,2,2,2,3,4,4,5,4,2,1,0.0,satisfied +76835,70291,Female,Loyal Customer,37,Business travel,Business,452,4,4,2,4,1,3,3,4,4,4,4,1,4,4,19,35.0,neutral or dissatisfied +76836,23586,Female,Loyal Customer,51,Business travel,Eco,1024,2,1,1,1,2,5,2,2,2,2,2,2,2,2,15,15.0,neutral or dissatisfied +76837,71350,Male,Loyal Customer,44,Business travel,Eco Plus,1114,5,4,4,4,5,5,5,5,4,3,2,2,4,5,45,44.0,satisfied +76838,13880,Female,disloyal Customer,24,Business travel,Eco,578,2,0,2,3,2,2,2,2,4,4,2,2,2,2,0,0.0,neutral or dissatisfied +76839,41163,Female,Loyal Customer,38,Personal Travel,Eco,224,3,1,3,3,4,3,3,4,2,3,3,1,2,4,0,0.0,neutral or dissatisfied +76840,129103,Male,Loyal Customer,60,Personal Travel,Eco,2342,1,4,1,4,1,1,1,1,1,1,5,1,2,1,7,0.0,neutral or dissatisfied +76841,119770,Female,disloyal Customer,30,Business travel,Business,912,3,3,3,2,4,3,4,4,3,3,4,3,4,4,61,46.0,neutral or dissatisfied +76842,57855,Female,disloyal Customer,23,Business travel,Business,2329,4,4,4,3,4,4,4,4,2,3,4,3,4,4,6,0.0,neutral or dissatisfied +76843,30933,Female,disloyal Customer,39,Business travel,Business,1024,3,2,2,3,4,2,4,4,5,5,3,4,4,4,0,25.0,neutral or dissatisfied +76844,1084,Female,Loyal Customer,59,Personal Travel,Eco,158,3,4,3,2,5,4,4,3,3,3,3,3,3,4,8,10.0,neutral or dissatisfied +76845,39004,Female,disloyal Customer,24,Business travel,Eco,260,1,2,1,3,3,1,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +76846,54522,Male,Loyal Customer,22,Personal Travel,Eco,925,1,1,1,3,5,1,5,5,4,2,2,4,3,5,0,0.0,neutral or dissatisfied +76847,44384,Male,Loyal Customer,49,Business travel,Business,265,0,0,0,5,2,5,4,5,5,1,1,5,5,3,0,0.0,satisfied +76848,128747,Female,Loyal Customer,31,Business travel,Business,2402,2,1,4,1,2,2,2,4,5,2,3,2,2,2,0,10.0,neutral or dissatisfied +76849,13490,Male,Loyal Customer,54,Business travel,Business,2994,2,2,2,2,3,4,1,5,5,5,4,1,5,3,0,0.0,satisfied +76850,89440,Female,Loyal Customer,54,Personal Travel,Eco,134,2,5,2,5,5,4,2,5,5,2,5,4,5,3,2,0.0,neutral or dissatisfied +76851,110081,Male,disloyal Customer,37,Business travel,Business,882,3,3,3,2,2,3,2,2,4,5,5,5,4,2,14,24.0,neutral or dissatisfied +76852,101342,Male,Loyal Customer,39,Business travel,Business,2026,3,5,5,5,1,4,4,3,3,2,3,1,3,4,62,61.0,neutral or dissatisfied +76853,46372,Female,Loyal Customer,43,Business travel,Eco,1081,2,4,5,4,2,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +76854,118191,Female,disloyal Customer,18,Business travel,Eco,1444,3,3,3,3,1,3,1,1,4,4,3,2,4,1,47,35.0,neutral or dissatisfied +76855,77612,Female,Loyal Customer,43,Business travel,Business,731,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +76856,98355,Male,Loyal Customer,31,Business travel,Business,1699,1,3,3,3,1,1,1,1,3,3,3,1,4,1,0,2.0,neutral or dissatisfied +76857,24184,Male,Loyal Customer,58,Business travel,Eco,134,4,3,3,3,4,4,4,4,4,3,4,1,5,4,0,3.0,satisfied +76858,39667,Female,Loyal Customer,39,Business travel,Business,1586,3,3,3,3,5,3,3,3,3,3,3,1,3,1,0,5.0,neutral or dissatisfied +76859,52829,Male,Loyal Customer,53,Business travel,Eco,1721,4,3,3,3,4,4,4,4,2,4,4,5,3,4,0,0.0,satisfied +76860,99955,Female,Loyal Customer,17,Personal Travel,Eco,1986,3,5,3,5,3,3,3,3,1,2,1,4,4,3,0,0.0,neutral or dissatisfied +76861,18945,Male,Loyal Customer,62,Personal Travel,Eco,503,2,5,2,2,3,2,1,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +76862,92977,Female,Loyal Customer,57,Business travel,Business,738,2,2,2,2,2,5,5,4,4,4,4,3,4,4,8,1.0,satisfied +76863,119091,Male,disloyal Customer,45,Business travel,Business,1020,3,2,2,4,5,3,5,5,4,4,5,3,5,5,0,0.0,satisfied +76864,5669,Female,Loyal Customer,55,Business travel,Business,2053,4,4,4,4,5,4,5,4,4,4,5,3,4,3,0,0.0,satisfied +76865,51082,Female,Loyal Customer,20,Personal Travel,Eco,109,3,4,3,1,1,3,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +76866,12625,Male,Loyal Customer,51,Business travel,Business,2748,2,5,3,5,4,4,3,2,2,2,2,2,2,2,0,,neutral or dissatisfied +76867,90885,Female,Loyal Customer,47,Business travel,Eco,406,3,5,5,5,3,4,3,3,3,3,3,2,3,4,0,13.0,neutral or dissatisfied +76868,46267,Female,Loyal Customer,49,Personal Travel,Eco,624,2,3,2,3,4,4,4,2,2,2,2,2,2,2,113,119.0,neutral or dissatisfied +76869,111996,Male,disloyal Customer,13,Business travel,Business,770,4,0,4,3,1,4,1,1,5,5,5,3,4,1,63,56.0,satisfied +76870,83388,Male,Loyal Customer,58,Personal Travel,Business,632,4,5,4,4,2,4,4,5,5,4,5,3,5,3,63,45.0,neutral or dissatisfied +76871,46881,Male,Loyal Customer,45,Business travel,Business,737,4,4,4,4,2,3,2,4,4,4,4,2,4,2,0,0.0,satisfied +76872,97802,Male,Loyal Customer,44,Business travel,Business,395,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +76873,12290,Female,disloyal Customer,23,Business travel,Eco,190,0,2,0,3,3,0,4,3,3,5,1,5,4,3,81,76.0,satisfied +76874,20311,Male,Loyal Customer,27,Business travel,Business,2358,3,3,3,3,3,3,3,3,3,4,3,1,4,3,0,0.0,satisfied +76875,42003,Female,Loyal Customer,56,Business travel,Eco,106,5,2,2,2,4,2,1,5,5,5,5,1,5,1,0,0.0,satisfied +76876,31948,Male,Loyal Customer,29,Business travel,Business,2118,5,5,5,5,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +76877,54712,Male,Loyal Customer,41,Business travel,Eco,461,4,2,2,2,4,4,4,4,2,5,3,4,3,4,20,12.0,satisfied +76878,79058,Male,Loyal Customer,38,Business travel,Eco,356,2,5,4,5,2,2,2,2,4,1,3,4,3,2,41,39.0,neutral or dissatisfied +76879,65200,Female,disloyal Customer,26,Business travel,Business,190,1,4,2,4,5,2,5,5,5,3,5,3,4,5,27,12.0,neutral or dissatisfied +76880,87222,Male,Loyal Customer,16,Personal Travel,Eco,946,1,2,1,3,1,5,5,3,3,4,3,5,2,5,177,178.0,neutral or dissatisfied +76881,10737,Female,Loyal Customer,39,Business travel,Business,2882,1,1,1,1,5,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +76882,35837,Female,disloyal Customer,27,Business travel,Eco,1068,3,3,3,3,2,3,2,2,2,4,4,1,4,2,0,9.0,neutral or dissatisfied +76883,47060,Female,Loyal Customer,24,Business travel,Business,639,3,4,4,4,3,3,3,3,4,5,4,3,4,3,44,30.0,neutral or dissatisfied +76884,51326,Male,Loyal Customer,49,Business travel,Eco Plus,86,2,3,3,3,1,2,1,1,2,2,4,2,3,1,0,0.0,neutral or dissatisfied +76885,17590,Male,Loyal Customer,35,Business travel,Eco Plus,1042,1,1,1,1,1,1,1,1,1,2,2,3,3,1,67,47.0,neutral or dissatisfied +76886,118432,Female,Loyal Customer,25,Business travel,Business,621,4,4,4,4,4,4,4,4,5,5,5,5,4,4,0,2.0,satisfied +76887,3775,Female,Loyal Customer,48,Business travel,Business,2857,4,4,4,4,3,4,4,4,4,4,4,5,4,5,30,28.0,satisfied +76888,6809,Male,Loyal Customer,35,Personal Travel,Eco,137,3,0,3,4,5,3,5,5,4,5,5,3,4,5,0,20.0,neutral or dissatisfied +76889,93757,Female,disloyal Customer,17,Business travel,Eco,368,3,2,3,4,5,3,5,5,2,2,3,4,4,5,16,11.0,neutral or dissatisfied +76890,49982,Male,disloyal Customer,48,Business travel,Eco,250,3,3,3,2,3,3,3,3,1,4,2,2,2,3,88,98.0,neutral or dissatisfied +76891,43285,Male,disloyal Customer,45,Business travel,Business,347,1,1,1,3,2,1,2,2,2,4,5,4,1,2,0,0.0,neutral or dissatisfied +76892,48809,Female,Loyal Customer,16,Personal Travel,Business,78,1,5,1,3,3,1,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +76893,26118,Male,Loyal Customer,56,Business travel,Business,1823,4,4,4,4,5,5,4,5,5,5,5,3,5,3,69,51.0,satisfied +76894,90178,Male,Loyal Customer,48,Personal Travel,Eco,1127,1,5,1,4,5,1,5,5,5,5,3,5,4,5,0,0.0,neutral or dissatisfied +76895,112850,Female,Loyal Customer,48,Business travel,Business,1390,2,5,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +76896,75725,Female,Loyal Customer,42,Business travel,Eco,868,3,1,1,1,2,2,1,3,3,3,3,1,3,3,0,3.0,neutral or dissatisfied +76897,67785,Male,Loyal Customer,54,Business travel,Business,1205,5,5,5,5,5,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +76898,87425,Male,Loyal Customer,37,Business travel,Eco Plus,425,1,1,1,1,1,1,1,1,3,2,4,4,4,1,53,45.0,neutral or dissatisfied +76899,103181,Female,Loyal Customer,32,Business travel,Business,2040,1,1,1,1,3,4,3,3,3,2,5,5,4,3,5,0.0,satisfied +76900,49256,Male,Loyal Customer,42,Business travel,Business,373,2,2,2,2,5,3,3,4,4,5,4,3,4,5,0,0.0,satisfied +76901,103728,Female,Loyal Customer,30,Personal Travel,Eco,405,2,3,4,3,2,4,2,2,2,2,4,3,3,2,35,49.0,neutral or dissatisfied +76902,112039,Male,Loyal Customer,44,Business travel,Business,1123,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +76903,71038,Female,Loyal Customer,52,Business travel,Business,3125,1,5,5,5,2,3,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +76904,57864,Female,Loyal Customer,59,Business travel,Business,955,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +76905,101022,Female,Loyal Customer,38,Personal Travel,Eco,806,2,3,1,1,2,1,5,2,5,1,2,1,3,2,69,48.0,neutral or dissatisfied +76906,86679,Male,Loyal Customer,49,Business travel,Business,1747,5,5,5,5,2,4,5,3,3,3,3,4,3,5,23,23.0,satisfied +76907,103173,Male,Loyal Customer,26,Personal Travel,Eco,272,1,0,1,2,4,1,5,4,5,4,5,4,4,4,17,10.0,neutral or dissatisfied +76908,96613,Male,disloyal Customer,24,Business travel,Eco,937,2,2,2,1,5,2,5,5,1,3,2,1,1,5,119,99.0,neutral or dissatisfied +76909,74235,Male,Loyal Customer,32,Personal Travel,Eco,1007,3,4,3,3,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +76910,127786,Female,Loyal Customer,48,Personal Travel,Eco,1037,2,4,2,3,4,5,4,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +76911,68602,Male,Loyal Customer,52,Business travel,Eco,1739,3,4,4,4,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +76912,46320,Female,Loyal Customer,36,Business travel,Business,420,4,4,4,4,1,5,4,4,4,4,4,1,4,2,2,4.0,satisfied +76913,72268,Female,Loyal Customer,20,Business travel,Business,2754,2,3,2,2,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +76914,59669,Female,Loyal Customer,29,Personal Travel,Eco,787,3,5,3,4,1,3,2,1,5,5,4,3,5,1,3,0.0,neutral or dissatisfied +76915,117333,Male,Loyal Customer,37,Business travel,Business,1684,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +76916,14093,Male,Loyal Customer,30,Business travel,Business,371,4,4,3,4,5,5,5,5,5,5,4,2,5,5,6,0.0,satisfied +76917,95705,Female,Loyal Customer,41,Business travel,Business,237,0,0,0,3,3,5,5,4,4,4,4,5,4,3,6,1.0,satisfied +76918,20537,Female,Loyal Customer,51,Business travel,Business,2368,3,5,3,3,4,5,3,5,5,5,5,2,5,1,0,0.0,satisfied +76919,103985,Female,Loyal Customer,60,Business travel,Business,1334,5,5,5,5,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +76920,109726,Female,disloyal Customer,30,Business travel,Eco,587,2,4,2,4,2,2,2,2,3,1,1,2,3,2,0,0.0,neutral or dissatisfied +76921,34753,Male,Loyal Customer,34,Business travel,Business,264,1,2,2,2,3,2,1,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +76922,46988,Male,Loyal Customer,37,Personal Travel,Eco,833,2,4,2,1,1,2,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +76923,35480,Male,Loyal Customer,46,Personal Travel,Eco,1076,3,2,3,3,3,5,5,4,4,4,3,5,2,5,168,157.0,neutral or dissatisfied +76924,63299,Male,Loyal Customer,67,Business travel,Business,2631,2,2,2,2,2,3,3,2,2,2,2,2,2,2,6,3.0,neutral or dissatisfied +76925,125345,Female,disloyal Customer,22,Business travel,Eco,599,5,2,5,4,1,5,1,1,3,3,4,3,5,1,0,0.0,satisfied +76926,124624,Female,Loyal Customer,66,Business travel,Eco,171,1,0,0,3,4,4,4,3,3,1,3,2,3,4,37,10.0,neutral or dissatisfied +76927,86487,Male,Loyal Customer,65,Personal Travel,Eco,712,3,5,2,4,3,2,3,3,4,2,2,5,4,3,52,49.0,neutral or dissatisfied +76928,100593,Female,Loyal Customer,27,Personal Travel,Eco,486,2,2,1,4,1,1,5,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +76929,8491,Male,disloyal Customer,28,Business travel,Eco,677,2,2,2,3,2,2,2,2,4,1,4,1,3,2,43,36.0,neutral or dissatisfied +76930,77687,Female,Loyal Customer,60,Business travel,Business,3019,4,4,4,4,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +76931,78305,Female,Loyal Customer,14,Personal Travel,Eco,1598,4,5,4,3,5,4,5,5,4,2,5,4,5,5,0,5.0,neutral or dissatisfied +76932,106174,Female,Loyal Customer,61,Personal Travel,Eco,302,1,5,1,3,2,5,5,4,4,1,4,4,4,3,3,3.0,neutral or dissatisfied +76933,17985,Male,Loyal Customer,25,Business travel,Business,3595,2,2,5,2,4,4,4,4,4,2,3,3,2,4,0,0.0,satisfied +76934,73688,Male,disloyal Customer,27,Business travel,Business,204,2,2,2,4,3,2,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +76935,115567,Female,Loyal Customer,56,Business travel,Business,337,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +76936,125830,Female,disloyal Customer,40,Business travel,Business,861,2,2,2,5,5,2,5,5,4,3,5,5,5,5,0,2.0,neutral or dissatisfied +76937,54471,Male,Loyal Customer,47,Business travel,Business,1808,4,4,4,4,3,2,3,4,4,4,4,4,4,2,0,0.0,satisfied +76938,10568,Male,Loyal Customer,41,Business travel,Business,312,0,0,0,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +76939,58866,Female,Loyal Customer,29,Business travel,Business,3316,4,4,4,4,5,5,5,5,5,3,5,4,5,5,9,3.0,satisfied +76940,60107,Male,Loyal Customer,66,Business travel,Eco,1120,2,2,2,2,2,2,2,2,2,4,4,1,4,2,0,4.0,neutral or dissatisfied +76941,47998,Female,disloyal Customer,28,Business travel,Eco Plus,550,4,4,4,4,5,4,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +76942,64538,Female,Loyal Customer,53,Business travel,Business,3922,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +76943,14053,Female,Loyal Customer,69,Personal Travel,Eco,335,4,5,2,4,5,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +76944,65386,Male,Loyal Customer,31,Personal Travel,Eco,432,2,3,2,3,2,2,2,2,2,2,4,4,4,2,0,9.0,neutral or dissatisfied +76945,59950,Female,disloyal Customer,30,Business travel,Business,937,5,5,5,2,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +76946,85123,Male,Loyal Customer,29,Business travel,Business,3740,1,3,3,3,1,1,1,1,4,1,4,2,4,1,34,24.0,neutral or dissatisfied +76947,88441,Male,Loyal Customer,58,Business travel,Business,1724,1,3,3,3,2,3,4,1,1,1,1,1,1,1,13,8.0,neutral or dissatisfied +76948,95378,Male,Loyal Customer,26,Personal Travel,Eco,293,1,4,1,3,3,1,3,3,5,5,5,4,4,3,32,17.0,neutral or dissatisfied +76949,316,Female,Loyal Customer,44,Business travel,Business,821,1,1,1,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +76950,37,Female,Loyal Customer,54,Business travel,Business,212,4,4,4,4,5,5,4,4,4,4,5,5,4,4,12,26.0,satisfied +76951,121810,Female,Loyal Customer,45,Business travel,Business,3485,2,2,2,2,5,4,4,4,4,4,4,3,4,4,35,17.0,satisfied +76952,76884,Male,Loyal Customer,54,Business travel,Business,630,4,4,4,4,3,5,5,2,2,2,2,5,2,5,4,6.0,satisfied +76953,99920,Male,Loyal Customer,48,Business travel,Business,1731,2,2,2,2,3,5,4,4,4,4,4,5,4,4,5,0.0,satisfied +76954,111854,Female,Loyal Customer,25,Business travel,Business,628,1,1,1,1,4,4,4,4,3,4,4,4,5,4,19,9.0,satisfied +76955,4900,Male,Loyal Customer,52,Business travel,Business,1020,5,5,5,5,3,5,5,3,3,3,3,5,3,3,118,,satisfied +76956,61204,Male,Loyal Customer,51,Business travel,Business,862,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,3.0,satisfied +76957,126658,Female,Loyal Customer,15,Personal Travel,Eco,602,2,5,2,4,4,2,4,4,4,5,5,4,5,4,4,15.0,neutral or dissatisfied +76958,28561,Female,Loyal Customer,47,Business travel,Eco Plus,2677,5,3,3,3,1,4,2,5,5,5,5,2,5,2,41,0.0,satisfied +76959,40503,Male,Loyal Customer,58,Personal Travel,Eco,461,2,4,2,1,5,2,5,5,5,5,2,4,2,5,0,0.0,neutral or dissatisfied +76960,71402,Male,Loyal Customer,30,Business travel,Business,1677,1,1,1,1,5,5,5,5,5,3,5,3,4,5,18,10.0,satisfied +76961,30230,Male,Loyal Customer,49,Business travel,Eco,896,4,5,5,5,4,4,4,4,4,5,1,3,5,4,0,0.0,satisfied +76962,21407,Male,Loyal Customer,55,Business travel,Eco,433,5,2,2,2,5,5,5,5,3,2,3,2,2,5,0,0.0,satisfied +76963,32016,Male,Loyal Customer,46,Business travel,Business,2285,0,4,0,4,2,2,2,3,3,3,3,2,3,5,0,0.0,satisfied +76964,22083,Male,Loyal Customer,25,Business travel,Business,782,3,3,3,3,4,4,4,4,4,4,3,4,4,4,116,110.0,satisfied +76965,38815,Male,Loyal Customer,27,Personal Travel,Eco,354,4,1,4,1,3,4,1,3,1,4,1,2,2,3,0,0.0,neutral or dissatisfied +76966,42059,Male,Loyal Customer,19,Personal Travel,Eco,116,5,4,0,3,2,0,2,2,3,2,3,1,3,2,0,0.0,satisfied +76967,125725,Female,Loyal Customer,57,Personal Travel,Eco,899,0,5,0,5,3,4,5,3,3,0,3,3,3,4,0,0.0,satisfied +76968,36223,Female,Loyal Customer,49,Business travel,Business,3013,4,1,1,1,2,3,3,4,4,4,4,2,4,2,50,44.0,neutral or dissatisfied +76969,94329,Female,Loyal Customer,47,Business travel,Business,3114,2,2,2,2,5,5,4,5,5,5,5,4,5,3,16,17.0,satisfied +76970,106398,Male,Loyal Customer,45,Business travel,Eco,488,2,2,2,2,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +76971,123160,Male,Loyal Customer,48,Business travel,Business,107,4,4,4,4,2,2,1,3,3,4,5,3,3,1,38,29.0,satisfied +76972,71395,Male,disloyal Customer,22,Business travel,Business,334,5,0,5,3,3,5,3,3,3,2,4,5,5,3,105,127.0,satisfied +76973,95967,Female,Loyal Customer,56,Business travel,Business,1090,3,3,3,3,4,5,5,5,5,5,5,5,5,4,14,0.0,satisfied +76974,90053,Male,disloyal Customer,25,Business travel,Business,957,3,5,3,1,1,3,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +76975,110933,Female,Loyal Customer,56,Personal Travel,Eco,545,3,4,3,1,1,1,1,4,4,3,4,3,4,3,4,0.0,neutral or dissatisfied +76976,10958,Female,Loyal Customer,41,Business travel,Eco,163,3,2,3,3,3,3,3,3,1,1,1,1,4,3,0,0.0,satisfied +76977,19313,Female,Loyal Customer,34,Business travel,Business,3400,2,2,2,2,1,3,3,4,4,4,4,4,4,1,61,57.0,satisfied +76978,105597,Female,Loyal Customer,51,Business travel,Business,925,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +76979,5584,Female,Loyal Customer,28,Business travel,Business,685,4,4,2,4,4,4,4,4,3,2,5,5,5,4,4,15.0,satisfied +76980,32265,Female,Loyal Customer,42,Business travel,Business,3837,1,1,1,1,1,5,3,5,5,5,5,5,5,4,1,1.0,satisfied +76981,119677,Female,Loyal Customer,59,Business travel,Business,1496,5,5,2,5,5,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +76982,80105,Female,disloyal Customer,50,Business travel,Business,1198,2,2,2,2,1,2,1,1,3,4,4,4,5,1,5,0.0,satisfied +76983,115596,Female,Loyal Customer,35,Business travel,Business,3125,1,2,2,2,1,3,4,1,1,2,1,4,1,4,27,20.0,neutral or dissatisfied +76984,12052,Male,Loyal Customer,39,Business travel,Eco,351,4,3,3,3,4,4,4,4,1,3,4,3,1,4,12,1.0,satisfied +76985,74014,Female,Loyal Customer,29,Business travel,Business,1471,4,4,4,4,4,4,4,4,3,2,4,5,5,4,96,88.0,satisfied +76986,60072,Female,disloyal Customer,43,Business travel,Business,1005,2,2,2,1,3,2,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +76987,119276,Male,disloyal Customer,42,Business travel,Business,214,5,5,5,4,5,5,5,5,5,3,5,3,5,5,0,2.0,satisfied +76988,107778,Female,Loyal Customer,9,Personal Travel,Eco Plus,405,3,4,3,4,2,3,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +76989,80000,Female,Loyal Customer,23,Personal Travel,Eco,1010,0,5,0,3,1,0,1,1,3,4,5,4,4,1,21,0.0,satisfied +76990,125108,Female,Loyal Customer,30,Business travel,Eco,361,1,1,1,1,1,1,1,1,3,5,4,2,4,1,0,0.0,neutral or dissatisfied +76991,41039,Male,Loyal Customer,55,Business travel,Business,2506,4,4,4,4,4,2,3,4,4,4,4,2,4,1,0,0.0,satisfied +76992,113518,Female,Loyal Customer,37,Business travel,Business,3127,5,5,5,5,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +76993,68302,Female,disloyal Customer,31,Business travel,Business,1797,4,4,4,1,3,4,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +76994,97919,Male,Loyal Customer,57,Business travel,Business,2512,1,1,3,1,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +76995,102710,Female,disloyal Customer,34,Business travel,Eco,255,4,0,4,2,4,4,4,4,3,1,4,5,4,4,0,0.0,neutral or dissatisfied +76996,83447,Female,Loyal Customer,50,Business travel,Business,946,2,2,3,2,3,4,4,5,5,5,5,3,5,3,0,6.0,satisfied +76997,123795,Male,Loyal Customer,57,Business travel,Business,3259,3,3,3,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +76998,109479,Male,Loyal Customer,29,Business travel,Business,1513,3,3,3,3,4,4,4,4,3,2,5,3,5,4,56,59.0,satisfied +76999,30655,Male,Loyal Customer,50,Personal Travel,Eco,533,1,4,3,5,5,3,5,5,3,4,4,4,5,5,12,11.0,neutral or dissatisfied +77000,106281,Male,Loyal Customer,50,Business travel,Business,689,3,3,3,3,5,2,2,3,3,3,3,3,3,4,25,39.0,neutral or dissatisfied +77001,77419,Male,Loyal Customer,53,Personal Travel,Eco,590,2,1,2,3,4,2,4,4,4,4,4,1,4,4,52,43.0,neutral or dissatisfied +77002,59802,Female,Loyal Customer,48,Business travel,Business,2949,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +77003,1009,Female,Loyal Customer,29,Business travel,Business,2012,3,3,3,3,4,4,4,4,5,2,5,5,3,4,0,2.0,satisfied +77004,128143,Female,Loyal Customer,55,Business travel,Business,1849,2,2,2,2,2,4,5,4,4,4,4,3,4,4,16,23.0,satisfied +77005,46154,Male,Loyal Customer,30,Business travel,Business,2075,2,2,2,2,4,4,4,4,5,5,1,3,1,4,119,104.0,satisfied +77006,26814,Female,Loyal Customer,47,Business travel,Business,2668,4,4,4,4,3,4,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +77007,112642,Female,Loyal Customer,15,Personal Travel,Eco Plus,639,3,5,3,2,3,3,1,3,3,3,5,5,5,3,52,66.0,neutral or dissatisfied +77008,81314,Male,Loyal Customer,27,Business travel,Business,1611,3,3,3,3,5,5,5,5,3,5,5,3,5,5,0,0.0,satisfied +77009,75486,Female,Loyal Customer,47,Business travel,Business,2342,5,5,5,5,4,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +77010,13697,Male,Loyal Customer,68,Personal Travel,Eco,300,1,2,1,3,3,1,3,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +77011,111146,Male,Loyal Customer,22,Business travel,Eco,650,4,4,4,4,4,4,4,4,1,2,1,3,3,4,5,2.0,satisfied +77012,51922,Female,disloyal Customer,36,Business travel,Eco Plus,601,2,2,2,5,3,2,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +77013,40786,Male,Loyal Customer,23,Business travel,Business,1605,5,5,5,5,5,4,5,5,2,4,2,2,1,5,1,0.0,satisfied +77014,7922,Male,Loyal Customer,41,Personal Travel,Eco,1020,2,4,2,3,2,2,2,2,4,2,3,2,4,2,5,6.0,neutral or dissatisfied +77015,43316,Male,Loyal Customer,55,Business travel,Business,463,1,2,2,2,1,1,1,2,3,4,4,1,3,1,182,166.0,neutral or dissatisfied +77016,3749,Female,Loyal Customer,23,Business travel,Eco Plus,431,4,5,5,5,4,4,3,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +77017,110328,Female,Loyal Customer,41,Business travel,Business,1697,2,4,2,2,5,4,5,5,5,5,5,3,5,4,54,51.0,satisfied +77018,75787,Male,Loyal Customer,63,Personal Travel,Eco,813,0,5,0,5,5,0,2,5,3,2,5,3,1,5,0,0.0,satisfied +77019,71740,Male,Loyal Customer,33,Personal Travel,Business,1652,5,5,5,3,4,5,5,4,3,3,5,4,5,4,0,0.0,satisfied +77020,1704,Female,Loyal Customer,46,Business travel,Business,364,1,1,1,1,5,5,5,5,5,4,5,3,5,5,36,41.0,satisfied +77021,90886,Female,Loyal Customer,44,Business travel,Business,3234,3,4,4,4,1,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +77022,15911,Male,Loyal Customer,44,Business travel,Business,2091,3,3,3,3,5,2,2,5,5,5,5,4,5,2,0,0.0,satisfied +77023,85218,Male,Loyal Customer,55,Business travel,Business,1670,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +77024,63248,Female,Loyal Customer,34,Business travel,Business,1924,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +77025,65970,Male,Loyal Customer,57,Business travel,Business,1372,5,3,5,5,2,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +77026,4473,Female,Loyal Customer,23,Personal Travel,Eco,1005,5,5,5,5,4,5,4,4,3,4,4,5,4,4,0,0.0,satisfied +77027,39663,Male,disloyal Customer,22,Business travel,Eco,476,3,0,3,4,2,3,2,2,3,1,3,2,5,2,0,0.0,neutral or dissatisfied +77028,77680,Female,disloyal Customer,28,Business travel,Business,689,2,2,2,2,1,2,1,1,5,3,5,4,4,1,1,0.0,neutral or dissatisfied +77029,55801,Female,disloyal Customer,23,Business travel,Business,1416,2,2,2,3,2,2,2,2,4,2,3,1,2,2,0,0.0,neutral or dissatisfied +77030,54127,Male,Loyal Customer,27,Business travel,Business,1400,4,4,4,4,4,4,4,4,5,5,1,3,1,4,3,13.0,satisfied +77031,105258,Male,Loyal Customer,30,Business travel,Business,2106,2,2,2,2,2,3,2,2,2,1,3,2,4,2,0,8.0,neutral or dissatisfied +77032,116685,Male,Loyal Customer,41,Business travel,Eco Plus,446,2,3,3,3,2,2,2,2,4,5,4,3,4,2,6,11.0,neutral or dissatisfied +77033,5385,Female,Loyal Customer,64,Personal Travel,Eco,812,1,4,1,3,5,3,4,3,3,1,3,3,3,4,47,59.0,neutral or dissatisfied +77034,91138,Female,Loyal Customer,70,Personal Travel,Eco,271,1,0,1,4,4,1,1,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +77035,77703,Female,Loyal Customer,27,Business travel,Business,3953,4,4,4,4,4,4,4,4,1,1,3,1,4,4,36,43.0,neutral or dissatisfied +77036,64850,Male,Loyal Customer,43,Business travel,Business,3346,1,1,1,1,4,5,5,5,5,5,5,5,5,5,30,33.0,satisfied +77037,108070,Male,Loyal Customer,44,Business travel,Business,2141,4,4,4,4,4,5,4,5,5,5,5,3,5,3,59,88.0,satisfied +77038,45478,Male,disloyal Customer,21,Business travel,Eco,674,2,2,2,3,5,2,4,5,1,3,3,2,3,5,1,0.0,neutral or dissatisfied +77039,71841,Female,Loyal Customer,43,Business travel,Eco,1652,3,3,4,4,1,2,2,3,3,3,3,4,3,2,30,12.0,neutral or dissatisfied +77040,33490,Female,Loyal Customer,11,Personal Travel,Eco,2496,2,3,3,3,3,3,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +77041,37966,Male,disloyal Customer,25,Business travel,Eco,1121,1,1,1,3,2,1,1,2,3,3,3,2,3,2,61,48.0,neutral or dissatisfied +77042,59302,Male,Loyal Customer,49,Business travel,Business,2556,5,5,5,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +77043,50434,Female,Loyal Customer,40,Business travel,Business,156,4,4,4,4,2,4,5,4,4,4,3,2,4,1,0,0.0,satisfied +77044,69726,Male,Loyal Customer,45,Personal Travel,Eco,1372,2,5,2,4,1,2,1,1,5,5,5,3,5,1,0,13.0,neutral or dissatisfied +77045,1239,Female,Loyal Customer,22,Personal Travel,Eco,164,3,1,3,1,5,3,5,5,3,2,1,1,1,5,0,0.0,neutral or dissatisfied +77046,30802,Male,Loyal Customer,26,Business travel,Business,3753,5,5,5,5,5,5,5,5,3,2,1,2,4,5,4,0.0,satisfied +77047,1721,Female,disloyal Customer,27,Business travel,Eco,364,2,4,2,4,2,2,2,2,4,4,3,2,3,2,31,52.0,neutral or dissatisfied +77048,110076,Female,disloyal Customer,34,Business travel,Business,1072,2,2,2,1,2,2,2,2,5,2,4,3,4,2,29,25.0,neutral or dissatisfied +77049,80793,Male,Loyal Customer,54,Business travel,Business,484,5,5,5,5,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +77050,95855,Male,Loyal Customer,51,Business travel,Business,759,5,5,2,5,2,4,4,5,5,5,5,4,5,3,28,32.0,satisfied +77051,9481,Female,Loyal Customer,44,Business travel,Business,2284,4,4,4,4,4,5,5,5,5,5,5,5,5,3,31,31.0,satisfied +77052,36185,Female,Loyal Customer,51,Business travel,Business,280,2,1,1,1,3,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +77053,20093,Male,Loyal Customer,42,Business travel,Business,416,1,1,2,1,3,3,1,4,4,4,4,5,4,5,88,69.0,satisfied +77054,81399,Male,Loyal Customer,58,Personal Travel,Eco,874,2,4,3,1,5,3,5,5,5,5,3,5,4,5,0,0.0,neutral or dissatisfied +77055,115876,Female,Loyal Customer,38,Business travel,Business,1525,5,5,5,5,1,3,5,5,5,5,5,3,5,1,78,73.0,satisfied +77056,82444,Male,Loyal Customer,36,Business travel,Business,502,3,5,5,5,2,4,3,3,3,3,3,1,3,4,5,23.0,neutral or dissatisfied +77057,126809,Female,Loyal Customer,62,Business travel,Business,2077,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +77058,611,Male,Loyal Customer,56,Business travel,Business,158,5,5,5,5,3,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +77059,88857,Female,disloyal Customer,49,Business travel,Business,646,2,3,3,1,4,2,4,4,5,4,4,3,5,4,9,2.0,neutral or dissatisfied +77060,97889,Female,Loyal Customer,25,Business travel,Business,612,1,1,1,1,5,5,5,5,5,4,4,5,4,5,27,19.0,satisfied +77061,34951,Male,Loyal Customer,26,Personal Travel,Eco,187,2,4,2,3,1,2,1,1,5,3,3,4,4,1,0,0.0,neutral or dissatisfied +77062,7895,Female,Loyal Customer,39,Personal Travel,Eco Plus,910,2,5,2,4,4,2,4,4,4,2,5,3,5,4,0,6.0,neutral or dissatisfied +77063,8706,Female,Loyal Customer,55,Personal Travel,Eco,280,3,5,3,2,3,5,4,1,1,3,1,4,1,4,0,6.0,neutral or dissatisfied +77064,43250,Male,Loyal Customer,35,Business travel,Eco,463,3,5,5,5,3,3,3,3,1,1,3,2,1,3,0,0.0,satisfied +77065,50123,Female,Loyal Customer,41,Business travel,Eco,308,1,4,4,4,1,1,1,1,2,4,1,3,2,1,0,13.0,neutral or dissatisfied +77066,41457,Female,Loyal Customer,25,Personal Travel,Business,1428,1,4,1,3,4,1,4,4,5,3,4,3,5,4,8,8.0,neutral or dissatisfied +77067,99867,Female,Loyal Customer,41,Business travel,Business,534,1,1,1,1,4,4,4,4,4,4,4,5,4,5,20,23.0,satisfied +77068,69312,Male,Loyal Customer,53,Personal Travel,Business,1096,2,4,2,1,4,5,4,2,2,2,4,2,2,5,0,0.0,neutral or dissatisfied +77069,103008,Male,disloyal Customer,20,Business travel,Eco,546,2,0,3,2,3,3,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +77070,77661,Male,disloyal Customer,38,Business travel,Business,696,3,3,3,2,1,3,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +77071,31006,Female,disloyal Customer,26,Business travel,Eco,391,2,0,2,4,3,2,1,3,5,4,3,5,3,3,1,0.0,neutral or dissatisfied +77072,44030,Male,Loyal Customer,33,Business travel,Business,3332,5,5,5,5,4,4,4,4,1,2,4,5,5,4,0,0.0,satisfied +77073,71733,Female,Loyal Customer,43,Business travel,Business,1744,2,2,2,2,2,3,4,3,3,4,3,3,3,4,0,0.0,satisfied +77074,110309,Female,Loyal Customer,53,Business travel,Business,2678,2,2,2,2,5,4,5,4,4,4,4,3,4,5,1,17.0,satisfied +77075,91745,Male,Loyal Customer,52,Business travel,Business,626,3,3,3,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +77076,91218,Male,Loyal Customer,28,Personal Travel,Eco,442,2,4,3,1,1,3,1,1,5,3,5,4,5,1,0,1.0,neutral or dissatisfied +77077,30619,Female,Loyal Customer,33,Business travel,Business,3487,3,3,2,2,5,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +77078,52701,Female,Loyal Customer,55,Personal Travel,Eco Plus,160,5,4,5,2,3,4,5,3,3,5,3,5,3,5,0,0.0,satisfied +77079,68236,Female,disloyal Customer,20,Business travel,Eco,631,4,0,4,3,4,4,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +77080,20828,Male,Loyal Customer,54,Business travel,Eco,357,3,4,4,4,3,3,3,3,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +77081,83971,Male,disloyal Customer,25,Business travel,Eco,373,3,4,3,3,1,3,1,1,1,5,3,4,3,1,86,127.0,neutral or dissatisfied +77082,127648,Male,Loyal Customer,17,Personal Travel,Eco,1773,4,3,4,4,3,4,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +77083,35351,Female,Loyal Customer,16,Business travel,Business,1890,2,3,3,3,2,1,2,2,2,5,4,1,3,2,36,45.0,neutral or dissatisfied +77084,38136,Female,Loyal Customer,30,Business travel,Eco,1237,4,3,3,3,4,4,4,4,2,3,2,1,3,4,0,0.0,satisfied +77085,66282,Female,disloyal Customer,13,Business travel,Eco,550,2,3,2,3,4,2,4,4,2,3,3,3,4,4,4,0.0,neutral or dissatisfied +77086,84592,Male,Loyal Customer,43,Business travel,Business,2501,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,18.0,satisfied +77087,89762,Female,Loyal Customer,38,Personal Travel,Eco,1035,3,5,3,4,5,3,5,5,4,2,5,5,4,5,12,0.0,neutral or dissatisfied +77088,72987,Male,disloyal Customer,47,Business travel,Eco,696,4,4,4,3,5,4,5,5,4,1,1,2,4,5,0,3.0,neutral or dissatisfied +77089,81184,Female,disloyal Customer,22,Business travel,Eco,980,3,3,3,3,4,3,4,4,2,2,3,1,3,4,76,80.0,neutral or dissatisfied +77090,87051,Female,Loyal Customer,41,Business travel,Business,594,1,1,5,1,5,5,4,5,5,5,5,5,5,5,3,0.0,satisfied +77091,49361,Female,Loyal Customer,58,Business travel,Eco,337,2,3,2,3,1,3,3,2,2,2,2,4,2,3,0,7.0,satisfied +77092,120376,Male,Loyal Customer,48,Business travel,Business,3555,5,1,5,5,4,5,5,5,5,5,5,4,5,3,0,1.0,satisfied +77093,73875,Male,disloyal Customer,29,Business travel,Business,2342,2,2,2,4,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +77094,19249,Male,Loyal Customer,45,Business travel,Eco Plus,782,4,1,1,1,4,4,4,4,2,4,1,5,3,4,41,36.0,satisfied +77095,41653,Male,Loyal Customer,25,Business travel,Business,3275,0,0,0,4,3,3,3,3,3,2,1,4,2,3,0,0.0,satisfied +77096,67824,Male,Loyal Customer,38,Business travel,Business,1560,3,2,2,2,3,2,1,3,3,3,3,4,3,2,28,19.0,neutral or dissatisfied +77097,20826,Female,Loyal Customer,49,Business travel,Eco,534,2,4,4,4,1,4,4,2,2,2,2,3,2,3,36,39.0,neutral or dissatisfied +77098,4978,Female,Loyal Customer,47,Business travel,Business,3498,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +77099,56373,Male,Loyal Customer,29,Personal Travel,Eco,200,3,5,0,2,2,0,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +77100,65708,Male,disloyal Customer,34,Business travel,Business,936,1,1,1,1,2,1,2,2,5,5,5,5,5,2,39,22.0,neutral or dissatisfied +77101,19429,Female,Loyal Customer,36,Business travel,Eco,245,4,4,4,4,4,4,4,4,2,5,4,1,4,4,33,28.0,satisfied +77102,31209,Female,Loyal Customer,31,Business travel,Business,3114,2,2,2,2,5,5,5,5,3,4,1,5,5,5,14,4.0,satisfied +77103,22518,Female,disloyal Customer,36,Business travel,Eco Plus,238,1,1,1,3,3,1,3,3,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +77104,124683,Male,Loyal Customer,67,Business travel,Business,399,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +77105,115824,Female,Loyal Customer,39,Business travel,Business,3657,2,5,5,5,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +77106,85814,Female,Loyal Customer,61,Personal Travel,Eco,666,1,5,1,3,5,5,4,5,5,1,5,5,5,5,19,4.0,neutral or dissatisfied +77107,75562,Male,disloyal Customer,23,Business travel,Business,337,5,0,5,1,3,5,5,3,5,5,5,5,5,3,84,76.0,satisfied +77108,76320,Female,Loyal Customer,48,Personal Travel,Eco,2182,3,2,3,4,2,4,4,2,2,3,3,2,2,3,3,0.0,neutral or dissatisfied +77109,65040,Male,Loyal Customer,9,Personal Travel,Eco,469,2,4,5,1,4,5,4,4,5,5,4,4,4,4,115,116.0,neutral or dissatisfied +77110,111670,Female,Loyal Customer,22,Business travel,Business,2123,1,1,1,1,1,1,1,1,2,5,3,1,3,1,46,51.0,neutral or dissatisfied +77111,26160,Female,disloyal Customer,22,Business travel,Eco,404,1,0,0,3,4,0,4,4,5,5,1,4,5,4,0,0.0,neutral or dissatisfied +77112,102455,Male,Loyal Customer,12,Personal Travel,Eco,223,3,4,0,4,2,0,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +77113,4486,Female,disloyal Customer,27,Business travel,Business,551,2,2,2,3,1,2,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +77114,53290,Male,Loyal Customer,25,Business travel,Business,758,3,3,3,3,5,5,5,5,1,2,4,1,5,5,3,4.0,satisfied +77115,35063,Male,disloyal Customer,22,Business travel,Eco,1011,2,2,2,4,3,2,5,3,1,1,3,3,4,3,0,7.0,neutral or dissatisfied +77116,49508,Female,disloyal Customer,25,Business travel,Eco,110,2,5,2,3,2,2,2,2,5,1,2,4,2,2,17,15.0,neutral or dissatisfied +77117,10146,Female,Loyal Customer,63,Business travel,Business,1201,2,4,4,4,3,3,3,2,2,2,2,4,2,2,1,0.0,neutral or dissatisfied +77118,106326,Female,disloyal Customer,23,Business travel,Business,825,5,5,5,3,3,5,2,3,3,2,5,5,4,3,40,56.0,satisfied +77119,63721,Male,Loyal Customer,53,Business travel,Business,1660,2,3,2,2,2,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +77120,18835,Male,disloyal Customer,25,Business travel,Eco,551,2,4,2,3,4,2,1,4,5,5,4,1,4,4,0,0.0,neutral or dissatisfied +77121,81145,Female,disloyal Customer,24,Business travel,Business,1310,5,4,5,4,4,5,4,4,4,3,5,5,4,4,125,,satisfied +77122,87301,Female,Loyal Customer,39,Personal Travel,Eco,577,3,5,3,3,4,3,5,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +77123,129431,Male,Loyal Customer,43,Business travel,Business,1873,3,5,4,5,1,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +77124,61483,Male,Loyal Customer,44,Business travel,Business,2288,2,2,2,2,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +77125,21760,Female,Loyal Customer,49,Business travel,Business,352,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +77126,36315,Male,Loyal Customer,51,Business travel,Eco,187,4,2,2,2,4,4,4,4,1,5,2,1,3,4,0,0.0,neutral or dissatisfied +77127,111756,Female,Loyal Customer,30,Business travel,Business,1436,1,4,2,2,1,1,1,1,5,3,3,1,3,1,167,152.0,neutral or dissatisfied +77128,10910,Male,Loyal Customer,58,Business travel,Eco,429,2,4,4,4,2,2,2,2,1,3,3,3,4,2,10,4.0,neutral or dissatisfied +77129,68604,Female,Loyal Customer,28,Business travel,Business,1739,3,3,3,3,3,4,3,3,5,3,4,4,5,3,0,0.0,satisfied +77130,126521,Female,disloyal Customer,17,Business travel,Eco,196,2,0,2,2,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +77131,10741,Male,Loyal Customer,18,Business travel,Business,2935,2,4,4,4,1,1,2,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +77132,43967,Female,Loyal Customer,61,Business travel,Business,2553,2,3,3,3,1,1,2,2,2,2,2,4,2,1,0,29.0,neutral or dissatisfied +77133,2739,Female,Loyal Customer,36,Business travel,Eco,772,4,4,4,4,4,4,4,4,1,3,3,4,3,4,0,1.0,neutral or dissatisfied +77134,43253,Female,Loyal Customer,42,Business travel,Business,1748,1,1,1,1,1,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +77135,97625,Male,Loyal Customer,54,Personal Travel,Eco,764,2,4,2,4,3,2,3,3,5,2,4,4,5,3,77,63.0,neutral or dissatisfied +77136,38677,Male,Loyal Customer,44,Personal Travel,Eco,2588,1,4,1,5,3,1,3,3,5,3,5,4,4,3,28,5.0,neutral or dissatisfied +77137,78684,Male,disloyal Customer,39,Business travel,Eco,761,1,1,1,4,4,1,1,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +77138,55603,Female,disloyal Customer,27,Business travel,Eco,404,4,4,3,3,4,3,3,4,4,3,3,3,4,4,103,103.0,neutral or dissatisfied +77139,76127,Female,Loyal Customer,49,Business travel,Business,1862,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +77140,108985,Female,disloyal Customer,14,Business travel,Eco,994,2,3,3,4,5,3,5,5,4,4,4,5,4,5,14,14.0,neutral or dissatisfied +77141,2900,Male,Loyal Customer,51,Personal Travel,Eco,409,1,5,1,3,3,1,3,3,4,5,5,5,5,3,0,30.0,neutral or dissatisfied +77142,23474,Male,Loyal Customer,20,Personal Travel,Eco,488,2,5,2,2,2,2,2,2,5,3,4,5,4,2,3,4.0,neutral or dissatisfied +77143,37817,Male,Loyal Customer,63,Personal Travel,Eco Plus,1056,1,5,1,4,5,1,5,5,5,5,5,3,5,5,18,11.0,neutral or dissatisfied +77144,24108,Male,Loyal Customer,53,Business travel,Eco,584,4,4,4,4,5,4,5,5,3,1,3,3,3,5,0,0.0,satisfied +77145,25570,Female,Loyal Customer,26,Business travel,Eco,874,3,1,1,1,3,3,1,3,3,5,2,1,2,3,12,12.0,neutral or dissatisfied +77146,97830,Male,Loyal Customer,22,Business travel,Eco,395,4,5,5,5,4,4,2,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +77147,107106,Female,Loyal Customer,47,Personal Travel,Eco Plus,745,4,2,4,3,1,3,3,5,5,4,5,1,5,2,0,0.0,satisfied +77148,43891,Female,Loyal Customer,61,Business travel,Eco,144,5,5,5,5,2,5,4,5,5,5,5,5,5,1,62,64.0,satisfied +77149,33323,Female,Loyal Customer,27,Business travel,Business,2556,3,3,2,3,3,2,3,3,1,4,3,2,5,3,0,0.0,satisfied +77150,67401,Female,Loyal Customer,59,Business travel,Business,641,3,3,3,3,5,5,5,2,2,2,2,4,2,3,3,0.0,satisfied +77151,107864,Male,Loyal Customer,69,Business travel,Business,2262,3,5,5,5,2,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +77152,75492,Male,Loyal Customer,44,Business travel,Business,2342,2,2,3,2,3,3,4,1,1,2,1,5,1,3,0,0.0,satisfied +77153,120087,Female,disloyal Customer,23,Business travel,Eco,683,2,2,2,3,3,2,2,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +77154,97443,Female,Loyal Customer,54,Business travel,Business,585,4,4,4,4,2,5,4,4,4,4,4,4,4,4,40,12.0,satisfied +77155,116876,Male,Loyal Customer,58,Business travel,Business,651,4,4,4,4,2,5,5,4,4,4,4,3,4,3,21,23.0,satisfied +77156,21993,Female,Loyal Customer,55,Personal Travel,Eco,448,3,5,3,3,3,5,5,2,2,3,2,3,2,5,58,49.0,neutral or dissatisfied +77157,103527,Male,Loyal Customer,15,Personal Travel,Business,967,2,4,2,3,3,2,3,3,4,3,2,3,4,3,35,32.0,neutral or dissatisfied +77158,76986,Female,Loyal Customer,51,Business travel,Business,422,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,12.0,satisfied +77159,35909,Male,disloyal Customer,25,Business travel,Eco,817,4,4,4,4,5,4,5,5,3,5,3,3,4,5,0,0.0,satisfied +77160,104519,Male,Loyal Customer,50,Business travel,Business,3503,4,4,4,4,5,4,4,4,4,4,4,4,4,3,4,10.0,satisfied +77161,47492,Female,Loyal Customer,67,Personal Travel,Eco,532,3,4,3,3,4,5,5,4,4,3,4,5,4,5,0,2.0,neutral or dissatisfied +77162,30257,Female,Loyal Customer,46,Business travel,Business,1024,5,5,5,5,2,3,5,4,4,5,4,5,4,1,0,0.0,satisfied +77163,33880,Female,disloyal Customer,25,Business travel,Eco,1105,1,1,1,4,3,1,3,3,4,2,3,3,4,3,17,23.0,neutral or dissatisfied +77164,123734,Female,Loyal Customer,37,Business travel,Business,3474,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +77165,121294,Male,disloyal Customer,38,Business travel,Business,609,1,1,1,2,2,1,3,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +77166,15023,Male,Loyal Customer,63,Personal Travel,Eco Plus,557,3,5,3,2,3,3,3,3,2,4,2,1,4,3,81,62.0,neutral or dissatisfied +77167,105939,Male,disloyal Customer,19,Personal Travel,Eco,1491,3,5,3,1,1,3,2,1,3,4,5,4,5,1,27,0.0,neutral or dissatisfied +77168,86648,Male,Loyal Customer,68,Personal Travel,Eco,746,4,5,4,3,5,4,5,5,3,5,5,5,5,5,0,1.0,neutral or dissatisfied +77169,17342,Male,Loyal Customer,31,Business travel,Business,3997,4,4,4,4,3,4,3,3,4,2,1,3,1,3,0,0.0,satisfied +77170,83856,Female,Loyal Customer,24,Personal Travel,Eco,425,4,2,4,4,4,4,4,4,2,2,3,2,3,4,7,8.0,neutral or dissatisfied +77171,45365,Female,Loyal Customer,34,Personal Travel,Eco,222,3,1,3,4,4,3,4,4,4,2,3,3,4,4,0,0.0,neutral or dissatisfied +77172,83913,Female,Loyal Customer,35,Business travel,Business,3405,2,2,2,2,5,4,4,2,2,2,2,4,2,3,1,11.0,neutral or dissatisfied +77173,58072,Female,Loyal Customer,46,Business travel,Business,2256,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +77174,3978,Male,Loyal Customer,30,Business travel,Business,340,4,4,4,4,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +77175,119199,Female,disloyal Customer,22,Business travel,Eco,331,2,4,2,4,4,2,4,4,2,1,3,3,3,4,23,18.0,neutral or dissatisfied +77176,32486,Female,Loyal Customer,34,Business travel,Business,101,3,4,4,4,4,2,3,3,3,3,3,2,3,4,35,42.0,neutral or dissatisfied +77177,99257,Male,Loyal Customer,26,Personal Travel,Business,833,2,4,2,4,3,2,2,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +77178,68851,Male,Loyal Customer,39,Business travel,Business,1061,3,4,4,4,4,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +77179,55094,Male,disloyal Customer,26,Business travel,Eco,135,5,5,5,4,5,5,5,5,2,3,3,4,4,5,0,0.0,satisfied +77180,25136,Female,Loyal Customer,63,Personal Travel,Eco,1249,4,5,4,1,5,5,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +77181,78667,Female,Loyal Customer,33,Business travel,Business,761,4,4,4,4,4,5,5,5,5,5,5,5,5,5,13,5.0,satisfied +77182,71560,Female,Loyal Customer,58,Business travel,Business,1593,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +77183,57657,Female,Loyal Customer,63,Personal Travel,Eco,200,3,3,3,1,4,4,1,2,2,3,2,4,2,2,33,17.0,neutral or dissatisfied +77184,67865,Male,Loyal Customer,8,Personal Travel,Eco,1235,2,5,1,3,1,1,1,1,4,3,4,5,4,1,3,0.0,neutral or dissatisfied +77185,125720,Male,Loyal Customer,64,Personal Travel,Eco,899,2,4,2,1,5,2,5,5,4,5,4,3,5,5,2,0.0,neutral or dissatisfied +77186,18718,Male,Loyal Customer,53,Personal Travel,Eco Plus,127,2,4,2,4,3,2,3,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +77187,125495,Male,Loyal Customer,55,Business travel,Business,3694,3,1,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +77188,42514,Male,disloyal Customer,36,Business travel,Business,1187,2,2,2,5,2,2,3,2,4,5,4,4,3,2,59,36.0,neutral or dissatisfied +77189,114769,Male,Loyal Customer,58,Business travel,Business,417,2,2,2,2,4,4,4,2,2,2,2,5,2,4,30,30.0,satisfied +77190,46092,Male,Loyal Customer,9,Personal Travel,Eco,541,2,5,4,5,2,4,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +77191,89911,Male,Loyal Customer,29,Business travel,Eco,1487,4,2,2,2,4,4,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +77192,126619,Male,Loyal Customer,31,Personal Travel,Business,602,3,4,3,1,3,3,3,3,5,5,5,3,5,3,11,13.0,neutral or dissatisfied +77193,18386,Male,Loyal Customer,20,Personal Travel,Eco,493,0,5,0,4,5,0,5,5,4,3,5,4,4,5,3,0.0,satisfied +77194,103456,Female,Loyal Customer,44,Business travel,Business,393,1,5,5,5,2,3,3,1,1,1,1,3,1,1,75,71.0,neutral or dissatisfied +77195,58640,Female,Loyal Customer,34,Business travel,Business,3518,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +77196,106091,Female,disloyal Customer,35,Business travel,Business,302,4,4,4,3,5,4,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +77197,70073,Male,disloyal Customer,52,Business travel,Eco,550,4,3,4,3,3,4,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +77198,20607,Female,Loyal Customer,41,Business travel,Business,2216,1,1,1,1,4,5,1,4,4,4,4,4,4,5,0,0.0,satisfied +77199,1278,Male,Loyal Customer,14,Personal Travel,Eco,229,2,4,2,4,3,2,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +77200,7190,Male,Loyal Customer,47,Business travel,Business,2722,1,1,5,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +77201,42840,Female,Loyal Customer,23,Business travel,Business,1503,4,4,4,4,4,4,4,4,1,2,3,2,4,4,0,4.0,satisfied +77202,19585,Male,Loyal Customer,10,Personal Travel,Eco,173,3,5,3,1,2,3,2,2,5,2,4,4,5,2,66,68.0,neutral or dissatisfied +77203,86461,Female,Loyal Customer,37,Business travel,Business,1907,5,5,5,5,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +77204,36326,Male,Loyal Customer,66,Business travel,Business,1870,2,1,1,1,3,2,2,2,2,2,2,3,2,1,13,9.0,neutral or dissatisfied +77205,110515,Male,Loyal Customer,70,Personal Travel,Eco Plus,925,3,4,3,2,2,3,2,2,4,5,5,4,4,2,1,0.0,neutral or dissatisfied +77206,9121,Male,Loyal Customer,21,Personal Travel,Eco,765,0,1,0,4,4,0,4,4,1,4,3,4,4,4,0,0.0,satisfied +77207,52539,Female,Loyal Customer,51,Business travel,Eco,160,2,5,5,5,3,2,2,2,2,2,2,1,2,3,0,0.0,satisfied +77208,33652,Female,Loyal Customer,20,Personal Travel,Eco,399,1,4,1,5,3,1,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +77209,118730,Female,Loyal Customer,53,Personal Travel,Eco,369,1,4,1,1,1,1,3,2,2,1,2,5,2,2,0,0.0,neutral or dissatisfied +77210,16800,Female,Loyal Customer,54,Personal Travel,Eco Plus,1017,4,3,4,4,2,3,3,5,5,4,5,3,5,2,0,0.0,satisfied +77211,85170,Female,disloyal Customer,10,Business travel,Eco,731,4,4,4,4,5,4,5,5,5,2,4,3,4,5,18,0.0,neutral or dissatisfied +77212,92041,Male,Loyal Customer,40,Business travel,Business,1535,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +77213,36553,Female,Loyal Customer,48,Business travel,Business,1237,5,5,5,5,2,1,2,5,5,5,5,5,5,3,0,0.0,satisfied +77214,55344,Female,Loyal Customer,40,Business travel,Business,1956,3,3,2,3,5,5,4,3,3,4,3,3,3,4,0,17.0,satisfied +77215,59907,Male,Loyal Customer,37,Business travel,Business,937,5,5,5,5,2,5,5,4,4,4,4,3,4,5,42,8.0,satisfied +77216,32839,Male,Loyal Customer,42,Personal Travel,Eco,163,4,4,4,1,5,4,5,5,4,2,4,5,5,5,0,3.0,satisfied +77217,38692,Male,Loyal Customer,55,Business travel,Business,2342,2,4,3,4,2,3,4,2,2,2,2,3,2,1,36,19.0,neutral or dissatisfied +77218,10842,Female,Loyal Customer,60,Business travel,Business,316,4,4,4,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +77219,4679,Male,Loyal Customer,31,Business travel,Business,364,3,4,3,3,5,5,5,5,5,2,1,3,4,5,0,0.0,satisfied +77220,26907,Male,Loyal Customer,23,Business travel,Business,1660,2,2,2,2,5,5,5,5,1,3,3,2,4,5,1,5.0,satisfied +77221,55760,Female,Loyal Customer,49,Business travel,Business,224,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +77222,123291,Female,Loyal Customer,29,Personal Travel,Eco,468,2,5,2,4,5,2,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +77223,83467,Male,disloyal Customer,26,Business travel,Business,946,4,4,4,4,2,4,1,2,3,2,4,4,4,2,0,0.0,satisfied +77224,8916,Female,Loyal Customer,49,Business travel,Business,2314,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +77225,75082,Male,Loyal Customer,12,Personal Travel,Business,1814,4,4,4,5,3,4,3,3,3,2,3,4,5,3,0,0.0,neutral or dissatisfied +77226,99141,Female,Loyal Customer,39,Business travel,Business,453,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +77227,73957,Female,Loyal Customer,28,Personal Travel,Eco,2267,4,4,4,2,4,4,2,4,4,3,4,2,4,2,0,0.0,satisfied +77228,98265,Male,Loyal Customer,39,Business travel,Business,2135,2,2,2,2,2,5,4,4,4,3,4,5,4,3,0,0.0,satisfied +77229,24332,Female,Loyal Customer,52,Business travel,Business,2671,3,3,2,3,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +77230,121413,Female,disloyal Customer,38,Business travel,Business,290,4,4,4,1,2,4,3,2,5,2,4,4,4,2,0,0.0,satisfied +77231,109606,Female,disloyal Customer,25,Business travel,Business,829,5,2,5,2,5,5,5,5,3,2,5,4,5,5,1,0.0,satisfied +77232,11786,Female,Loyal Customer,28,Personal Travel,Eco,429,4,1,4,3,3,4,3,3,4,2,2,1,2,3,3,11.0,neutral or dissatisfied +77233,76935,Female,Loyal Customer,10,Personal Travel,Eco,1727,3,5,3,1,5,3,3,5,3,2,5,3,5,5,108,89.0,neutral or dissatisfied +77234,42196,Male,Loyal Customer,42,Business travel,Business,2597,1,1,1,1,4,4,1,4,4,4,4,5,4,3,0,0.0,satisfied +77235,83588,Female,Loyal Customer,30,Business travel,Business,2755,3,3,3,3,5,5,5,5,5,3,5,5,4,5,6,12.0,satisfied +77236,57962,Female,Loyal Customer,29,Business travel,Business,1670,1,2,4,2,1,1,1,1,4,3,1,3,2,1,0,7.0,neutral or dissatisfied +77237,2660,Female,Loyal Customer,22,Business travel,Business,3600,3,3,3,3,3,4,3,3,3,4,4,2,3,3,0,6.0,neutral or dissatisfied +77238,48071,Male,Loyal Customer,59,Business travel,Business,236,2,3,3,3,1,2,2,2,2,2,2,3,2,4,27,32.0,neutral or dissatisfied +77239,35005,Female,Loyal Customer,38,Personal Travel,Eco,1182,2,5,2,3,5,2,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +77240,105843,Male,Loyal Customer,28,Business travel,Business,2900,2,2,2,2,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +77241,18193,Female,Loyal Customer,39,Business travel,Eco,346,5,1,1,1,5,5,5,5,5,5,1,5,4,5,0,0.0,satisfied +77242,34194,Male,Loyal Customer,8,Personal Travel,Eco,1063,4,4,4,2,4,3,3,3,4,4,5,3,4,3,221,219.0,neutral or dissatisfied +77243,26268,Male,disloyal Customer,20,Business travel,Eco,859,2,2,2,4,5,2,5,5,1,3,3,4,3,5,0,10.0,neutral or dissatisfied +77244,17764,Male,Loyal Customer,53,Personal Travel,Business,1075,0,1,0,2,1,3,3,1,1,0,1,3,1,1,0,0.0,satisfied +77245,97874,Male,disloyal Customer,45,Business travel,Business,612,4,4,4,4,4,4,4,4,3,2,5,3,4,4,1,0.0,neutral or dissatisfied +77246,46592,Male,Loyal Customer,57,Business travel,Business,141,0,5,0,1,3,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +77247,48882,Female,Loyal Customer,63,Business travel,Business,3795,1,1,1,1,1,5,4,4,4,4,4,1,4,5,93,95.0,satisfied +77248,24167,Female,disloyal Customer,22,Business travel,Eco,134,2,0,2,1,2,2,1,2,3,4,1,3,2,2,0,0.0,neutral or dissatisfied +77249,11623,Female,Loyal Customer,13,Personal Travel,Eco,657,3,4,3,4,3,3,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +77250,19816,Female,Loyal Customer,53,Business travel,Eco,528,5,2,3,2,5,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +77251,64535,Male,Loyal Customer,41,Business travel,Business,1591,3,3,4,3,2,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +77252,117390,Female,Loyal Customer,37,Personal Travel,Eco,912,3,4,4,3,4,4,4,4,4,2,5,4,5,4,0,7.0,neutral or dissatisfied +77253,61229,Female,Loyal Customer,15,Business travel,Eco,909,3,1,1,1,3,3,3,3,1,5,4,3,4,3,66,75.0,neutral or dissatisfied +77254,37824,Male,Loyal Customer,40,Business travel,Business,2850,2,3,3,3,4,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +77255,69654,Female,Loyal Customer,13,Business travel,Business,2219,3,1,3,1,3,3,3,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +77256,7799,Female,Loyal Customer,51,Business travel,Business,650,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +77257,127645,Female,Loyal Customer,61,Personal Travel,Eco,1773,3,4,3,4,4,3,4,1,1,3,1,3,1,5,68,78.0,neutral or dissatisfied +77258,104681,Female,disloyal Customer,25,Business travel,Eco Plus,641,3,2,3,3,4,3,3,4,2,4,2,2,3,4,0,0.0,neutral or dissatisfied +77259,117962,Female,disloyal Customer,34,Business travel,Eco,255,3,2,3,4,5,3,5,5,4,4,3,4,3,5,5,14.0,neutral or dissatisfied +77260,32064,Male,Loyal Customer,36,Business travel,Eco,101,4,1,1,1,4,4,4,4,3,1,4,2,1,4,0,0.0,satisfied +77261,31271,Female,Loyal Customer,28,Business travel,Business,3513,3,3,4,3,4,5,4,4,2,1,3,2,5,4,28,41.0,satisfied +77262,57586,Male,Loyal Customer,17,Personal Travel,Eco,1597,3,3,4,2,5,4,5,5,3,3,1,2,3,5,0,37.0,neutral or dissatisfied +77263,77717,Female,disloyal Customer,20,Business travel,Eco,813,2,2,2,4,1,2,1,1,4,1,4,3,4,1,0,7.0,neutral or dissatisfied +77264,101905,Female,Loyal Customer,46,Personal Travel,Eco,1984,3,5,3,4,4,4,2,5,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +77265,1793,Male,Loyal Customer,53,Business travel,Business,2961,1,1,2,1,2,4,5,2,2,2,2,3,2,3,0,4.0,satisfied +77266,112940,Female,Loyal Customer,40,Personal Travel,Eco,1313,2,5,2,2,2,2,2,2,5,5,4,4,5,2,10,0.0,neutral or dissatisfied +77267,104784,Female,Loyal Customer,13,Business travel,Business,3734,4,4,4,4,5,5,5,5,5,3,5,5,5,5,57,59.0,satisfied +77268,25156,Female,Loyal Customer,50,Business travel,Business,2106,4,3,3,3,4,3,4,4,4,4,4,4,4,2,44,40.0,neutral or dissatisfied +77269,99273,Female,Loyal Customer,41,Business travel,Business,833,5,5,5,5,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +77270,92151,Female,Loyal Customer,23,Business travel,Eco Plus,1535,3,2,2,2,3,2,2,3,4,1,4,3,3,3,25,0.0,neutral or dissatisfied +77271,8381,Male,Loyal Customer,32,Personal Travel,Eco,773,0,5,0,4,4,0,4,4,2,3,3,3,3,4,0,8.0,satisfied +77272,32059,Female,Loyal Customer,61,Business travel,Business,163,5,1,5,5,1,2,3,4,4,4,4,1,4,3,0,0.0,satisfied +77273,61333,Male,Loyal Customer,52,Business travel,Business,1667,3,4,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +77274,36437,Male,Loyal Customer,18,Personal Travel,Eco,369,1,4,1,5,5,1,5,5,4,4,2,4,2,5,0,0.0,neutral or dissatisfied +77275,37813,Female,Loyal Customer,32,Personal Travel,Eco Plus,1069,4,3,3,5,2,3,2,2,4,5,4,1,4,2,101,81.0,neutral or dissatisfied +77276,43703,Female,Loyal Customer,35,Business travel,Business,3886,1,5,4,5,3,3,3,1,1,1,1,1,1,3,14,10.0,neutral or dissatisfied +77277,85381,Male,Loyal Customer,57,Business travel,Business,332,2,2,2,2,4,4,5,5,5,5,5,4,5,5,129,118.0,satisfied +77278,104203,Male,Loyal Customer,46,Business travel,Business,280,4,4,4,4,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +77279,90720,Male,Loyal Customer,53,Business travel,Business,3038,0,0,0,3,2,5,5,3,3,4,4,3,3,5,3,0.0,satisfied +77280,24523,Male,Loyal Customer,32,Business travel,Business,892,1,1,1,1,5,5,5,5,5,2,2,1,5,5,11,23.0,satisfied +77281,859,Female,Loyal Customer,50,Business travel,Business,309,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +77282,81261,Female,Loyal Customer,39,Business travel,Business,1578,1,1,1,1,5,4,5,4,4,4,4,5,4,3,86,,satisfied +77283,95028,Male,Loyal Customer,14,Personal Travel,Eco,239,4,5,4,4,4,4,4,4,5,2,4,3,4,4,4,5.0,neutral or dissatisfied +77284,27172,Female,Loyal Customer,50,Personal Travel,Eco,2701,3,5,3,4,3,1,5,3,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +77285,38930,Male,Loyal Customer,58,Personal Travel,Eco,410,2,4,2,2,3,2,3,3,4,3,5,4,5,3,0,16.0,neutral or dissatisfied +77286,30661,Female,Loyal Customer,15,Personal Travel,Eco,533,1,4,1,5,2,1,5,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +77287,27377,Female,Loyal Customer,49,Business travel,Business,2510,3,3,3,3,5,1,1,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +77288,52684,Female,Loyal Customer,54,Personal Travel,Eco,119,2,4,2,4,3,3,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +77289,90643,Female,Loyal Customer,48,Business travel,Business,406,2,2,2,2,5,4,4,2,2,2,2,4,2,4,10,4.0,satisfied +77290,62923,Female,Loyal Customer,48,Business travel,Business,1746,2,2,2,2,3,4,4,4,4,4,4,5,4,5,0,4.0,satisfied +77291,21489,Male,disloyal Customer,20,Business travel,Eco,164,3,2,3,4,4,3,4,4,1,5,4,1,4,4,11,18.0,neutral or dissatisfied +77292,80513,Male,Loyal Customer,40,Personal Travel,Eco,1749,4,3,4,3,5,4,2,5,3,1,1,3,3,5,0,0.0,neutral or dissatisfied +77293,86400,Female,disloyal Customer,28,Business travel,Business,762,4,4,4,2,3,4,3,3,3,2,4,5,5,3,120,99.0,satisfied +77294,2081,Female,Loyal Customer,55,Personal Travel,Eco,812,5,2,5,2,5,3,3,5,5,5,5,1,5,2,0,4.0,satisfied +77295,80409,Male,Loyal Customer,54,Business travel,Business,1416,5,5,5,5,2,4,5,4,4,4,4,5,4,4,2,0.0,satisfied +77296,42289,Female,Loyal Customer,51,Business travel,Business,2400,3,2,2,2,2,2,1,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +77297,44511,Male,Loyal Customer,34,Business travel,Business,3143,4,4,4,4,2,5,4,5,5,4,4,5,5,5,21,17.0,satisfied +77298,27477,Female,Loyal Customer,55,Business travel,Eco,954,1,0,0,3,4,3,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +77299,127465,Male,Loyal Customer,12,Business travel,Business,2075,2,2,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +77300,123889,Male,Loyal Customer,54,Personal Travel,Eco,573,3,4,3,2,3,3,3,3,3,3,4,5,4,3,0,13.0,neutral or dissatisfied +77301,12757,Male,Loyal Customer,58,Personal Travel,Eco,689,2,2,2,3,5,2,3,5,3,5,4,1,3,5,22,19.0,neutral or dissatisfied +77302,104463,Male,disloyal Customer,38,Business travel,Eco,615,1,4,1,3,2,1,2,2,3,5,3,2,4,2,24,24.0,neutral or dissatisfied +77303,53743,Male,Loyal Customer,22,Business travel,Eco Plus,1208,4,2,2,2,4,4,5,4,4,1,2,3,5,4,2,0.0,satisfied +77304,112447,Male,disloyal Customer,18,Business travel,Eco,967,2,2,2,4,3,2,3,3,3,5,3,3,4,3,19,9.0,neutral or dissatisfied +77305,72683,Female,Loyal Customer,55,Personal Travel,Eco,985,3,4,3,3,5,4,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +77306,9382,Male,Loyal Customer,64,Personal Travel,Eco,441,2,1,2,3,3,2,3,3,1,5,2,3,2,3,0,0.0,neutral or dissatisfied +77307,21809,Male,Loyal Customer,49,Personal Travel,Eco,241,5,5,5,4,3,5,3,3,4,5,5,5,4,3,0,5.0,satisfied +77308,42120,Male,Loyal Customer,43,Business travel,Eco,498,4,3,3,3,4,4,4,4,4,2,5,5,3,4,0,0.0,satisfied +77309,122106,Female,Loyal Customer,38,Personal Travel,Eco,130,1,2,1,3,3,1,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +77310,28586,Female,Loyal Customer,15,Personal Travel,Eco,2603,2,1,2,2,4,2,4,4,1,3,2,1,2,4,0,0.0,neutral or dissatisfied +77311,47660,Male,Loyal Customer,9,Business travel,Eco,1211,3,5,5,5,3,4,1,3,2,5,2,4,3,3,46,52.0,neutral or dissatisfied +77312,116376,Female,Loyal Customer,8,Personal Travel,Eco,373,2,4,2,2,1,2,3,1,2,5,4,1,2,1,11,19.0,neutral or dissatisfied +77313,118039,Male,disloyal Customer,27,Business travel,Business,1044,2,2,2,1,1,2,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +77314,46552,Male,Loyal Customer,61,Business travel,Business,125,3,3,3,3,4,4,3,5,5,5,5,3,5,2,60,60.0,satisfied +77315,45708,Female,Loyal Customer,46,Business travel,Eco,1024,5,2,2,2,5,3,1,5,5,5,5,4,5,5,17,0.0,satisfied +77316,81157,Male,Loyal Customer,22,Business travel,Business,3858,4,4,4,4,2,3,2,2,3,2,5,4,4,2,0,0.0,satisfied +77317,3020,Female,disloyal Customer,18,Business travel,Eco,862,2,2,2,3,4,2,4,4,1,4,3,4,4,4,29,15.0,neutral or dissatisfied +77318,66451,Female,Loyal Customer,55,Business travel,Business,2242,4,4,4,4,4,5,4,5,5,5,5,1,5,3,35,32.0,satisfied +77319,91921,Female,Loyal Customer,46,Business travel,Business,2475,1,2,2,2,1,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +77320,119869,Male,Loyal Customer,34,Personal Travel,Eco,936,3,4,3,4,4,3,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +77321,100287,Female,disloyal Customer,12,Business travel,Business,1130,5,5,4,3,4,4,2,4,5,3,5,4,4,4,0,0.0,satisfied +77322,115810,Female,Loyal Customer,42,Business travel,Business,1522,2,2,2,2,2,5,1,5,5,5,5,1,5,3,26,13.0,satisfied +77323,5051,Female,disloyal Customer,42,Business travel,Business,224,2,2,2,3,3,2,3,3,4,4,4,3,5,3,9,37.0,neutral or dissatisfied +77324,129056,Male,Loyal Customer,63,Personal Travel,Eco,1846,1,3,2,3,4,2,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +77325,44044,Male,Loyal Customer,26,Personal Travel,Eco,237,4,5,4,1,3,4,3,3,3,2,5,4,4,3,0,0.0,satisfied +77326,55395,Female,Loyal Customer,53,Business travel,Business,3038,5,5,4,5,2,4,4,4,4,4,4,4,4,5,7,0.0,satisfied +77327,78546,Female,Loyal Customer,54,Personal Travel,Eco,526,2,5,2,3,5,4,5,5,5,2,5,3,5,4,0,1.0,neutral or dissatisfied +77328,71336,Male,Loyal Customer,69,Personal Travel,Eco,1514,4,5,4,2,1,4,1,1,3,2,3,3,4,1,60,66.0,neutral or dissatisfied +77329,115789,Female,disloyal Customer,24,Business travel,Eco,447,4,3,4,4,2,4,2,2,1,2,3,4,3,2,13,7.0,neutral or dissatisfied +77330,76929,Female,Loyal Customer,50,Business travel,Business,1823,2,4,4,4,1,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +77331,87814,Female,disloyal Customer,26,Business travel,Business,214,3,0,3,4,2,3,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +77332,127778,Female,Loyal Customer,42,Business travel,Business,2658,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +77333,83721,Male,Loyal Customer,42,Personal Travel,Eco Plus,577,2,4,2,1,2,2,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +77334,100222,Female,disloyal Customer,42,Business travel,Business,1011,3,3,3,1,1,3,1,1,5,4,4,4,4,1,0,2.0,neutral or dissatisfied +77335,100841,Female,Loyal Customer,52,Business travel,Business,2161,2,2,3,2,1,3,1,5,5,5,5,4,5,4,0,0.0,satisfied +77336,98938,Female,disloyal Customer,22,Business travel,Eco,543,3,5,3,5,1,3,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +77337,78516,Female,Loyal Customer,45,Personal Travel,Eco,666,0,2,0,3,1,2,3,3,3,0,3,1,3,2,3,1.0,satisfied +77338,124305,Female,Loyal Customer,39,Business travel,Business,2184,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +77339,11309,Female,Loyal Customer,46,Personal Travel,Eco,247,2,3,2,4,4,1,5,2,2,2,1,4,2,3,0,5.0,neutral or dissatisfied +77340,95923,Male,Loyal Customer,47,Business travel,Business,1411,4,4,4,4,4,5,4,5,5,5,5,4,5,4,11,5.0,satisfied +77341,48878,Female,Loyal Customer,53,Business travel,Eco,326,5,2,2,2,2,2,2,5,5,5,5,5,5,3,0,0.0,satisfied +77342,119579,Male,Loyal Customer,30,Business travel,Business,1682,4,4,4,4,4,3,4,4,3,2,4,4,3,4,0,6.0,neutral or dissatisfied +77343,50969,Male,Loyal Customer,62,Personal Travel,Eco,421,3,5,3,4,5,3,5,5,3,1,3,3,1,5,68,83.0,neutral or dissatisfied +77344,36968,Female,Loyal Customer,26,Business travel,Business,899,2,2,2,2,5,5,5,5,2,2,2,1,4,5,25,24.0,satisfied +77345,3590,Male,Loyal Customer,28,Business travel,Business,3418,4,3,3,3,4,4,4,4,2,3,3,2,3,4,0,8.0,neutral or dissatisfied +77346,119920,Female,Loyal Customer,31,Business travel,Business,2236,5,5,5,5,4,4,4,4,3,4,4,3,5,4,0,10.0,satisfied +77347,103338,Female,Loyal Customer,37,Personal Travel,Eco,1139,2,4,3,3,2,3,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +77348,79480,Male,Loyal Customer,52,Business travel,Business,762,3,4,4,4,5,4,3,3,3,3,3,1,3,4,1,0.0,neutral or dissatisfied +77349,61706,Male,Loyal Customer,61,Business travel,Business,1334,2,5,3,5,5,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +77350,53435,Male,Loyal Customer,51,Business travel,Eco,2419,5,1,1,1,5,5,5,3,1,5,3,5,4,5,0,0.0,satisfied +77351,63741,Male,Loyal Customer,35,Personal Travel,Eco,1660,3,5,4,5,5,4,5,5,5,5,4,5,4,5,33,18.0,neutral or dissatisfied +77352,107993,Male,Loyal Customer,79,Business travel,Business,2847,3,3,3,3,2,3,2,3,3,3,3,2,3,2,4,7.0,neutral or dissatisfied +77353,23342,Female,Loyal Customer,27,Personal Travel,Eco,641,2,2,2,4,2,2,2,2,4,3,4,4,3,2,0,0.0,neutral or dissatisfied +77354,17822,Female,Loyal Customer,26,Personal Travel,Eco,1075,3,4,3,3,4,3,4,4,4,5,3,2,4,4,0,0.0,neutral or dissatisfied +77355,117007,Male,Loyal Customer,49,Business travel,Business,1931,0,0,0,2,3,3,3,3,5,4,4,3,4,3,264,270.0,satisfied +77356,76497,Male,disloyal Customer,27,Business travel,Business,516,5,5,5,1,4,5,1,4,4,3,4,3,5,4,7,0.0,satisfied +77357,92215,Female,Loyal Customer,7,Personal Travel,Eco,2079,1,3,0,1,5,0,5,5,4,2,2,5,5,5,0,13.0,neutral or dissatisfied +77358,57532,Female,disloyal Customer,46,Business travel,Eco,413,4,3,4,3,2,4,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +77359,31629,Male,Loyal Customer,26,Business travel,Business,3180,1,1,1,1,4,4,4,4,1,5,3,4,4,4,0,0.0,satisfied +77360,102627,Male,Loyal Customer,67,Personal Travel,Business,365,2,1,2,3,1,2,3,2,2,2,5,4,2,3,85,71.0,neutral or dissatisfied +77361,92734,Female,Loyal Customer,49,Business travel,Business,1276,2,5,5,5,1,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +77362,67884,Female,Loyal Customer,56,Personal Travel,Eco,1464,3,4,3,4,2,5,5,2,2,3,2,5,2,4,19,18.0,neutral or dissatisfied +77363,90547,Female,disloyal Customer,24,Business travel,Business,406,4,2,4,3,2,4,2,2,3,5,3,4,3,2,28,19.0,neutral or dissatisfied +77364,74860,Male,disloyal Customer,22,Business travel,Eco,495,0,0,0,3,2,0,2,2,1,3,1,3,4,2,0,0.0,satisfied +77365,37206,Female,disloyal Customer,50,Business travel,Business,680,4,4,4,2,1,4,1,1,4,2,5,4,5,1,0,0.0,satisfied +77366,28389,Female,Loyal Customer,8,Personal Travel,Eco,763,4,2,4,3,2,4,2,2,4,5,4,2,4,2,0,5.0,neutral or dissatisfied +77367,79209,Male,Loyal Customer,46,Business travel,Business,1990,5,5,5,5,5,4,5,4,4,4,4,5,4,3,26,0.0,satisfied +77368,107767,Male,Loyal Customer,21,Personal Travel,Eco,405,3,5,3,2,5,3,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +77369,44281,Female,Loyal Customer,10,Personal Travel,Eco Plus,359,3,5,3,2,3,3,3,3,5,4,4,3,5,3,0,9.0,neutral or dissatisfied +77370,111911,Female,Loyal Customer,23,Personal Travel,Eco Plus,628,3,5,3,3,5,3,5,5,3,3,5,3,4,5,35,40.0,neutral or dissatisfied +77371,22955,Female,Loyal Customer,56,Business travel,Eco,817,4,4,3,3,2,4,1,4,4,4,4,5,4,5,43,41.0,satisfied +77372,109955,Male,Loyal Customer,48,Personal Travel,Eco,1204,2,3,2,3,5,2,5,5,3,1,3,1,5,5,18,0.0,neutral or dissatisfied +77373,72860,Male,disloyal Customer,13,Business travel,Eco,700,5,5,5,3,2,5,1,2,3,5,5,4,5,2,0,0.0,satisfied +77374,94422,Female,Loyal Customer,49,Business travel,Business,293,4,4,5,4,4,4,5,5,5,5,5,5,5,5,2,0.0,satisfied +77375,53693,Female,Loyal Customer,40,Business travel,Business,1190,5,5,5,5,3,1,3,5,5,5,5,4,5,4,0,0.0,satisfied +77376,36740,Male,Loyal Customer,68,Business travel,Business,2148,2,4,4,4,5,4,3,2,2,2,2,3,2,1,0,21.0,neutral or dissatisfied +77377,36622,Female,disloyal Customer,25,Business travel,Eco,797,4,4,4,5,1,4,2,1,5,5,3,2,3,1,32,26.0,neutral or dissatisfied +77378,98113,Female,disloyal Customer,34,Business travel,Business,472,1,1,1,1,5,1,5,5,3,5,5,3,5,5,18,2.0,neutral or dissatisfied +77379,17733,Female,Loyal Customer,42,Business travel,Business,3910,3,5,5,5,3,4,4,3,3,3,3,3,3,2,81,68.0,neutral or dissatisfied +77380,85101,Female,disloyal Customer,26,Business travel,Business,689,2,4,2,2,2,2,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +77381,117821,Female,Loyal Customer,45,Personal Travel,Eco,328,3,3,3,3,3,5,3,1,3,4,4,3,3,3,132,135.0,neutral or dissatisfied +77382,46766,Male,Loyal Customer,44,Business travel,Eco Plus,125,5,4,4,4,5,5,5,5,1,1,1,4,1,5,0,5.0,satisfied +77383,26062,Male,Loyal Customer,31,Business travel,Eco Plus,432,2,1,1,1,2,2,2,2,3,3,4,3,4,2,18,22.0,neutral or dissatisfied +77384,13143,Male,Loyal Customer,70,Personal Travel,Eco,427,1,5,4,2,5,4,5,5,4,5,5,3,4,5,3,2.0,neutral or dissatisfied +77385,88537,Female,Loyal Customer,69,Personal Travel,Eco,404,3,5,3,2,4,4,4,4,4,3,4,4,4,4,0,4.0,neutral or dissatisfied +77386,96342,Female,Loyal Customer,32,Business travel,Business,1609,5,5,5,5,5,5,5,5,4,2,3,3,5,5,0,0.0,satisfied +77387,21973,Female,Loyal Customer,34,Business travel,Eco,551,3,4,4,4,3,3,3,3,3,4,3,2,4,3,11,3.0,neutral or dissatisfied +77388,55088,Female,Loyal Customer,55,Business travel,Eco,1346,3,3,3,3,2,3,2,4,4,3,4,2,4,3,10,2.0,neutral or dissatisfied +77389,80444,Female,Loyal Customer,23,Personal Travel,Eco,2248,1,4,0,3,2,0,2,2,4,3,4,4,4,2,1,15.0,neutral or dissatisfied +77390,24008,Male,Loyal Customer,23,Business travel,Business,3479,1,1,2,1,3,3,3,3,1,4,4,1,2,3,0,0.0,satisfied +77391,22499,Female,Loyal Customer,52,Personal Travel,Eco,238,4,4,4,3,5,3,3,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +77392,40910,Female,Loyal Customer,56,Personal Travel,Eco,599,1,3,1,4,1,2,3,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +77393,33914,Male,Loyal Customer,36,Business travel,Eco,636,4,1,1,1,4,4,4,4,4,1,2,3,4,4,0,0.0,satisfied +77394,40791,Female,Loyal Customer,27,Business travel,Eco,532,1,3,3,3,1,2,1,1,1,4,3,3,2,1,0,3.0,neutral or dissatisfied +77395,90865,Female,Loyal Customer,58,Business travel,Business,545,5,5,2,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +77396,31576,Female,Loyal Customer,24,Business travel,Business,2941,4,4,4,4,5,5,5,5,1,5,1,2,3,5,45,49.0,satisfied +77397,113907,Female,Loyal Customer,57,Personal Travel,Eco,2329,2,5,2,1,4,4,4,5,5,2,5,2,5,5,2,0.0,neutral or dissatisfied +77398,86069,Female,Loyal Customer,49,Business travel,Business,3056,5,2,5,5,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +77399,60982,Male,Loyal Customer,63,Personal Travel,Eco,888,3,4,2,1,1,2,1,1,3,5,5,5,4,1,21,37.0,neutral or dissatisfied +77400,30429,Female,Loyal Customer,68,Business travel,Eco Plus,1014,4,2,2,2,1,4,5,4,4,4,4,3,4,4,0,4.0,satisfied +77401,80887,Male,Loyal Customer,37,Business travel,Eco Plus,292,5,3,3,3,5,5,5,5,3,2,5,5,1,5,1,0.0,satisfied +77402,122392,Female,Loyal Customer,28,Personal Travel,Eco,529,3,4,3,4,1,3,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +77403,35065,Male,Loyal Customer,43,Business travel,Business,2173,1,0,0,4,4,3,3,4,4,0,4,4,4,1,0,0.0,neutral or dissatisfied +77404,65815,Female,disloyal Customer,24,Business travel,Eco,1389,1,1,1,1,5,1,1,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +77405,99925,Female,Loyal Customer,39,Business travel,Business,2465,3,3,3,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +77406,107627,Female,Loyal Customer,38,Personal Travel,Eco,423,1,0,1,3,1,4,4,3,2,5,5,4,5,4,184,195.0,neutral or dissatisfied +77407,60422,Female,Loyal Customer,47,Business travel,Business,1558,3,5,3,3,3,4,4,2,2,2,2,3,2,4,3,0.0,satisfied +77408,20898,Female,disloyal Customer,30,Business travel,Business,689,3,3,3,2,3,3,3,3,4,2,4,4,4,3,24,19.0,neutral or dissatisfied +77409,60757,Female,Loyal Customer,29,Business travel,Business,804,2,2,2,2,4,4,4,4,5,3,4,5,4,4,97,84.0,satisfied +77410,104875,Male,Loyal Customer,36,Business travel,Eco,327,1,5,4,5,1,1,1,1,3,4,4,1,3,1,37,29.0,neutral or dissatisfied +77411,88221,Female,Loyal Customer,51,Business travel,Eco,366,3,4,4,4,3,2,3,3,3,3,3,4,3,2,7,4.0,neutral or dissatisfied +77412,59131,Male,Loyal Customer,44,Personal Travel,Eco,1723,3,4,3,3,5,3,5,5,4,4,4,2,4,5,27,26.0,neutral or dissatisfied +77413,24802,Male,Loyal Customer,51,Business travel,Business,894,4,4,4,4,3,3,3,4,3,4,5,3,4,3,135,123.0,satisfied +77414,40731,Male,Loyal Customer,49,Business travel,Business,3338,5,5,4,5,2,1,1,4,4,4,4,2,4,1,0,0.0,satisfied +77415,1624,Female,Loyal Customer,57,Business travel,Business,3765,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +77416,56207,Male,Loyal Customer,30,Business travel,Eco Plus,1400,1,5,5,5,1,2,1,1,3,5,3,3,3,1,0,0.0,neutral or dissatisfied +77417,128756,Female,disloyal Customer,36,Business travel,Business,550,2,2,2,3,3,2,3,3,5,3,4,4,4,3,5,1.0,neutral or dissatisfied +77418,107534,Female,Loyal Customer,56,Business travel,Business,1521,1,1,1,1,2,4,4,4,4,4,4,3,4,4,0,4.0,satisfied +77419,81728,Male,Loyal Customer,31,Business travel,Business,1416,2,5,5,5,2,2,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +77420,92362,Male,Loyal Customer,22,Business travel,Business,1947,5,5,5,5,5,5,5,5,5,3,5,5,4,5,57,70.0,satisfied +77421,76211,Male,Loyal Customer,37,Personal Travel,Eco Plus,2422,3,5,3,3,3,3,3,3,3,2,4,3,4,3,0,17.0,neutral or dissatisfied +77422,99794,Male,Loyal Customer,41,Business travel,Business,1504,5,5,5,5,4,4,4,4,4,4,4,3,4,3,6,0.0,satisfied +77423,31400,Male,Loyal Customer,16,Personal Travel,Eco,1199,2,2,2,3,4,2,4,4,2,5,3,4,2,4,6,0.0,neutral or dissatisfied +77424,24004,Male,Loyal Customer,48,Business travel,Business,562,2,2,4,2,1,3,4,4,4,4,4,3,4,4,4,0.0,satisfied +77425,126111,Male,disloyal Customer,25,Business travel,Business,631,5,0,4,4,2,4,4,2,4,4,5,5,4,2,0,0.0,satisfied +77426,109164,Female,disloyal Customer,40,Business travel,Business,391,1,1,1,2,5,1,5,5,4,5,4,3,5,5,3,0.0,neutral or dissatisfied +77427,109248,Female,Loyal Customer,10,Personal Travel,Eco,483,3,4,3,4,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +77428,31564,Female,Loyal Customer,15,Business travel,Eco Plus,846,2,3,3,3,2,3,3,2,2,4,3,1,3,2,8,18.0,neutral or dissatisfied +77429,70415,Male,Loyal Customer,53,Business travel,Business,1562,3,3,3,3,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +77430,45615,Male,Loyal Customer,42,Business travel,Eco,313,4,5,5,5,4,4,4,4,1,3,4,1,3,4,3,7.0,neutral or dissatisfied +77431,58639,Male,Loyal Customer,50,Business travel,Business,3878,1,1,1,1,2,5,4,5,5,5,5,5,5,4,4,0.0,satisfied +77432,15803,Male,Loyal Customer,22,Personal Travel,Eco,246,3,4,3,1,1,3,1,1,4,2,5,1,5,1,110,95.0,neutral or dissatisfied +77433,101855,Female,Loyal Customer,12,Business travel,Eco,519,5,2,2,2,5,4,1,5,4,1,3,3,3,5,72,60.0,neutral or dissatisfied +77434,4707,Male,Loyal Customer,59,Business travel,Business,1886,5,5,3,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +77435,17804,Female,Loyal Customer,35,Business travel,Business,2846,2,3,3,3,4,3,3,2,2,2,2,1,2,2,31,59.0,neutral or dissatisfied +77436,52906,Female,Loyal Customer,44,Business travel,Eco,679,4,1,1,1,1,4,1,3,3,4,3,4,3,1,7,10.0,satisfied +77437,8559,Male,Loyal Customer,58,Business travel,Business,1824,3,3,3,3,2,4,3,1,1,1,3,2,1,4,0,0.0,neutral or dissatisfied +77438,78192,Female,disloyal Customer,21,Business travel,Eco,259,5,4,5,2,2,5,2,2,5,3,5,3,5,2,0,0.0,satisfied +77439,19445,Female,Loyal Customer,23,Personal Travel,Eco,503,3,1,3,3,2,3,2,2,4,2,3,3,3,2,13,16.0,neutral or dissatisfied +77440,67258,Male,Loyal Customer,44,Personal Travel,Eco,1121,3,3,3,1,4,3,4,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +77441,5587,Male,Loyal Customer,60,Business travel,Business,624,1,3,3,3,4,4,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +77442,80017,Male,Loyal Customer,16,Personal Travel,Eco,1005,3,3,3,4,5,3,2,5,2,3,3,1,3,5,0,2.0,neutral or dissatisfied +77443,38305,Male,Loyal Customer,64,Personal Travel,Eco,2342,1,3,1,3,2,1,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +77444,51148,Female,Loyal Customer,62,Personal Travel,Eco,207,1,2,0,4,4,4,3,5,5,0,5,3,5,3,0,0.0,neutral or dissatisfied +77445,10391,Male,Loyal Customer,42,Business travel,Business,3457,1,5,5,5,5,3,3,1,1,1,1,4,1,2,5,0.0,neutral or dissatisfied +77446,90670,Male,Loyal Customer,36,Business travel,Business,3468,5,5,5,5,4,5,5,5,5,5,5,4,5,3,8,2.0,satisfied +77447,115748,Male,Loyal Customer,69,Business travel,Eco,373,3,1,5,1,3,3,3,3,3,3,2,3,3,3,48,60.0,neutral or dissatisfied +77448,15064,Male,Loyal Customer,51,Personal Travel,Eco,488,2,1,2,3,2,2,2,1,3,2,2,2,1,2,318,317.0,neutral or dissatisfied +77449,94881,Female,Loyal Customer,39,Business travel,Eco,239,4,1,3,1,4,3,4,4,2,1,2,4,3,4,0,1.0,neutral or dissatisfied +77450,85074,Male,disloyal Customer,24,Business travel,Eco,874,5,5,5,4,2,5,2,2,4,2,5,4,5,2,5,0.0,satisfied +77451,96488,Male,Loyal Customer,50,Business travel,Business,3867,2,2,2,2,4,4,5,2,2,2,2,5,2,4,0,4.0,satisfied +77452,103001,Male,Loyal Customer,49,Business travel,Business,546,1,1,1,1,5,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +77453,86715,Female,disloyal Customer,22,Business travel,Eco,1110,3,3,3,4,4,3,4,4,2,4,3,3,3,4,0,0.0,neutral or dissatisfied +77454,69808,Female,Loyal Customer,58,Business travel,Business,2354,4,4,5,4,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +77455,20215,Male,Loyal Customer,73,Business travel,Eco,179,4,1,1,1,4,4,4,4,5,1,3,4,4,4,0,0.0,satisfied +77456,82621,Female,Loyal Customer,32,Personal Travel,Eco,408,1,2,4,4,3,4,3,3,2,2,3,2,4,3,0,0.0,neutral or dissatisfied +77457,38151,Female,Loyal Customer,46,Personal Travel,Eco,1185,2,5,2,2,3,5,1,4,4,2,4,1,4,4,0,3.0,neutral or dissatisfied +77458,37193,Male,Loyal Customer,33,Business travel,Eco Plus,1046,2,2,2,2,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +77459,109527,Male,disloyal Customer,35,Business travel,Eco,834,1,2,2,3,1,2,1,1,1,3,3,1,3,1,40,42.0,neutral or dissatisfied +77460,115943,Female,Loyal Customer,55,Personal Travel,Eco,337,5,5,3,3,4,4,4,3,3,3,3,5,3,4,9,0.0,satisfied +77461,70493,Female,Loyal Customer,17,Business travel,Business,867,2,1,1,1,2,2,2,2,4,2,3,2,3,2,0,42.0,neutral or dissatisfied +77462,33068,Female,Loyal Customer,59,Personal Travel,Eco,121,3,5,3,3,5,2,5,4,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +77463,52414,Male,Loyal Customer,64,Personal Travel,Eco,261,1,4,1,3,5,1,4,5,4,3,2,2,1,5,9,7.0,neutral or dissatisfied +77464,120639,Male,Loyal Customer,47,Business travel,Business,3200,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +77465,76804,Male,Loyal Customer,22,Personal Travel,Eco,689,2,4,2,2,2,2,2,2,5,2,5,3,4,2,0,10.0,neutral or dissatisfied +77466,39361,Male,Loyal Customer,39,Business travel,Business,826,3,5,5,5,5,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +77467,84868,Male,Loyal Customer,63,Personal Travel,Eco,534,2,4,2,4,1,2,1,1,5,3,4,3,5,1,42,34.0,neutral or dissatisfied +77468,71975,Male,Loyal Customer,23,Business travel,Business,1440,1,1,1,1,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +77469,25910,Female,Loyal Customer,39,Business travel,Business,594,3,3,3,3,4,5,5,4,4,4,4,4,4,4,14,16.0,satisfied +77470,69831,Female,Loyal Customer,55,Business travel,Eco,1055,3,2,2,2,1,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +77471,121110,Female,Loyal Customer,60,Business travel,Business,2370,5,5,3,5,4,4,4,5,4,3,4,4,4,4,0,39.0,satisfied +77472,103533,Female,Loyal Customer,53,Business travel,Business,3590,3,3,3,3,4,5,4,4,4,4,4,5,4,4,19,3.0,satisfied +77473,87173,Female,Loyal Customer,54,Business travel,Business,946,3,3,3,3,4,5,5,4,4,4,4,3,4,5,97,70.0,satisfied +77474,40695,Male,Loyal Customer,51,Business travel,Eco,558,5,2,2,2,5,5,5,5,2,1,5,2,4,5,0,0.0,satisfied +77475,127376,Male,Loyal Customer,56,Business travel,Business,3714,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +77476,76404,Female,Loyal Customer,65,Personal Travel,Eco Plus,931,3,5,3,1,5,4,5,5,5,3,5,5,5,3,11,39.0,neutral or dissatisfied +77477,114366,Female,disloyal Customer,27,Business travel,Business,909,4,4,4,5,3,4,3,3,3,2,4,5,5,3,1,7.0,neutral or dissatisfied +77478,6516,Female,Loyal Customer,30,Business travel,Business,2875,2,1,1,1,3,2,2,4,1,4,3,2,2,2,78,171.0,neutral or dissatisfied +77479,65418,Female,Loyal Customer,42,Personal Travel,Eco Plus,432,2,4,2,2,3,1,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +77480,97248,Male,Loyal Customer,49,Business travel,Business,2450,2,1,1,1,4,4,4,2,2,2,2,4,2,1,1,0.0,neutral or dissatisfied +77481,71470,Male,Loyal Customer,56,Personal Travel,Eco Plus,867,1,5,1,5,5,1,5,5,5,3,3,4,5,5,3,0.0,neutral or dissatisfied +77482,9231,Female,Loyal Customer,38,Business travel,Eco,177,1,4,3,4,1,1,1,1,1,4,4,4,4,1,13,44.0,neutral or dissatisfied +77483,40905,Male,Loyal Customer,32,Personal Travel,Eco,590,1,5,1,2,2,1,2,2,4,3,4,5,5,2,0,14.0,neutral or dissatisfied +77484,53745,Male,Loyal Customer,46,Business travel,Eco Plus,1208,3,3,3,3,3,3,3,3,4,5,4,4,3,3,13,25.0,neutral or dissatisfied +77485,626,Male,Loyal Customer,51,Business travel,Business,2073,0,0,0,4,5,5,4,2,2,2,2,4,2,4,22,17.0,satisfied +77486,33016,Female,Loyal Customer,9,Personal Travel,Eco,216,1,0,1,1,5,1,5,5,3,5,5,3,4,5,0,11.0,neutral or dissatisfied +77487,64599,Female,Loyal Customer,31,Business travel,Business,2135,2,3,3,3,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +77488,31527,Female,Loyal Customer,40,Personal Travel,Eco,967,1,4,1,3,3,1,2,3,4,4,4,4,5,3,7,4.0,neutral or dissatisfied +77489,117287,Female,Loyal Customer,39,Business travel,Business,304,1,1,1,1,3,4,4,4,4,4,4,5,4,5,62,58.0,satisfied +77490,113846,Male,Loyal Customer,60,Business travel,Business,1592,5,5,4,5,3,5,4,4,4,5,4,5,4,5,0,0.0,satisfied +77491,50606,Female,Loyal Customer,57,Personal Travel,Eco,207,1,5,0,2,5,3,2,2,2,0,2,4,2,4,9,20.0,neutral or dissatisfied +77492,129687,Female,disloyal Customer,36,Business travel,Eco,337,1,0,1,4,1,2,2,1,3,3,3,2,1,2,227,246.0,neutral or dissatisfied +77493,69110,Female,Loyal Customer,14,Personal Travel,Eco Plus,1391,4,2,4,3,4,4,4,4,4,2,3,3,3,4,2,19.0,neutral or dissatisfied +77494,57476,Female,Loyal Customer,27,Business travel,Business,2635,2,5,5,5,2,2,2,2,2,2,2,3,3,2,0,0.0,neutral or dissatisfied +77495,465,Female,Loyal Customer,30,Business travel,Business,396,1,1,1,1,5,4,5,5,4,3,4,4,5,5,0,0.0,satisfied +77496,77764,Female,Loyal Customer,11,Personal Travel,Eco,1282,2,5,3,1,2,3,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +77497,19608,Female,disloyal Customer,36,Business travel,Eco,416,3,3,3,4,2,3,2,2,2,4,4,1,3,2,113,115.0,neutral or dissatisfied +77498,62337,Female,Loyal Customer,21,Personal Travel,Eco,414,2,4,2,3,1,2,1,1,3,4,1,4,5,1,0,0.0,neutral or dissatisfied +77499,39119,Female,disloyal Customer,24,Business travel,Eco,190,2,0,2,4,5,2,1,5,2,5,1,5,5,5,0,3.0,neutral or dissatisfied +77500,61827,Male,Loyal Customer,54,Personal Travel,Eco,1504,4,1,4,3,4,4,4,4,1,2,4,2,3,4,0,6.0,neutral or dissatisfied +77501,120890,Male,Loyal Customer,56,Business travel,Business,951,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +77502,72565,Male,disloyal Customer,38,Business travel,Eco,985,2,2,2,3,4,2,4,4,1,5,2,1,3,4,1,4.0,neutral or dissatisfied +77503,117808,Female,disloyal Customer,45,Business travel,Eco,328,1,1,0,4,5,0,5,5,2,2,4,1,3,5,48,51.0,neutral or dissatisfied +77504,7055,Female,Loyal Customer,40,Business travel,Business,2106,1,1,1,1,2,5,5,4,4,4,4,4,4,4,7,20.0,satisfied +77505,79697,Female,Loyal Customer,35,Personal Travel,Eco,762,2,4,2,3,2,2,2,2,4,3,4,4,5,2,43,24.0,neutral or dissatisfied +77506,80104,Female,Loyal Customer,45,Business travel,Business,1620,2,2,2,2,5,5,5,4,4,4,4,3,4,5,58,43.0,satisfied +77507,53329,Female,Loyal Customer,30,Business travel,Eco Plus,811,4,1,1,1,4,4,4,4,3,1,4,1,2,4,0,0.0,satisfied +77508,6613,Female,disloyal Customer,18,Business travel,Eco,473,2,2,2,3,3,2,3,3,2,4,3,4,4,3,35,26.0,neutral or dissatisfied +77509,116148,Female,Loyal Customer,70,Personal Travel,Eco,417,5,5,5,3,5,4,2,5,5,5,5,5,5,4,14,11.0,satisfied +77510,110762,Female,Loyal Customer,59,Business travel,Business,1950,5,5,5,5,3,5,4,5,5,5,5,5,5,3,10,19.0,satisfied +77511,73423,Male,Loyal Customer,41,Business travel,Business,2365,2,2,2,2,2,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +77512,114789,Female,Loyal Customer,43,Business travel,Business,3135,0,1,1,3,5,5,4,1,1,1,1,5,1,4,0,6.0,satisfied +77513,91232,Female,Loyal Customer,34,Personal Travel,Eco,594,4,4,4,3,5,4,5,5,1,5,2,1,1,5,0,0.0,neutral or dissatisfied +77514,80288,Male,disloyal Customer,37,Business travel,Business,746,1,1,1,5,4,1,2,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +77515,69551,Female,disloyal Customer,25,Business travel,Eco,1043,2,2,2,3,2,2,2,1,2,4,4,2,4,2,0,11.0,neutral or dissatisfied +77516,26067,Female,Loyal Customer,39,Personal Travel,Business,591,5,5,5,4,4,4,5,4,4,5,5,3,4,5,4,0.0,satisfied +77517,114470,Female,Loyal Customer,52,Business travel,Business,446,4,4,4,4,3,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +77518,104382,Male,Loyal Customer,39,Personal Travel,Eco,228,4,2,4,2,1,4,1,1,4,2,2,2,1,1,4,12.0,neutral or dissatisfied +77519,11963,Female,Loyal Customer,33,Business travel,Business,3057,4,4,3,4,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +77520,112138,Male,disloyal Customer,24,Business travel,Business,895,4,0,4,3,3,4,5,3,4,4,4,4,5,3,0,0.0,satisfied +77521,68292,Female,Loyal Customer,40,Business travel,Business,1797,2,2,2,2,5,4,5,4,4,4,4,5,4,4,5,6.0,satisfied +77522,32591,Male,Loyal Customer,35,Business travel,Business,216,3,3,3,3,2,5,1,5,5,5,3,5,5,3,2,1.0,satisfied +77523,52335,Female,disloyal Customer,37,Business travel,Eco,251,3,2,3,3,1,3,1,1,3,1,4,4,4,1,0,0.0,neutral or dissatisfied +77524,114989,Female,Loyal Customer,48,Business travel,Business,2581,2,4,5,4,2,4,3,2,2,2,2,1,2,4,18,12.0,neutral or dissatisfied +77525,18241,Female,Loyal Customer,40,Business travel,Business,235,0,0,0,3,2,2,4,4,4,4,4,5,4,5,87,92.0,satisfied +77526,104409,Male,disloyal Customer,12,Business travel,Eco,1011,3,3,3,5,5,3,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +77527,67063,Male,Loyal Customer,55,Business travel,Business,2938,5,5,1,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +77528,120480,Male,Loyal Customer,40,Personal Travel,Eco,449,2,3,2,3,5,2,5,5,5,5,2,2,2,5,1,0.0,neutral or dissatisfied +77529,38289,Male,Loyal Customer,31,Personal Travel,Eco Plus,1050,4,4,4,4,4,3,3,3,4,4,5,3,3,3,135,127.0,neutral or dissatisfied +77530,120210,Male,Loyal Customer,38,Business travel,Business,1430,3,5,5,5,1,2,2,3,3,3,3,3,3,4,17,39.0,neutral or dissatisfied +77531,317,Female,disloyal Customer,25,Business travel,Business,821,5,5,5,3,5,5,5,5,3,3,5,4,5,5,0,0.0,satisfied +77532,98293,Male,Loyal Customer,63,Personal Travel,Eco,1072,3,5,2,1,1,2,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +77533,107332,Male,Loyal Customer,41,Business travel,Business,1504,1,1,1,1,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +77534,27229,Male,Loyal Customer,39,Business travel,Business,1024,2,2,2,2,1,3,1,2,2,2,2,4,2,1,0,0.0,satisfied +77535,31427,Female,Loyal Customer,32,Personal Travel,Eco,1703,5,2,5,2,4,5,4,4,4,3,2,2,2,4,0,0.0,satisfied +77536,9644,Female,Loyal Customer,52,Business travel,Business,3137,3,3,3,3,5,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +77537,127315,Male,Loyal Customer,20,Personal Travel,Eco,1979,3,0,3,3,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +77538,92121,Male,Loyal Customer,18,Personal Travel,Eco,1522,2,5,2,3,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +77539,45610,Male,Loyal Customer,42,Business travel,Business,1643,5,2,5,5,3,2,5,5,5,5,3,5,5,3,38,56.0,satisfied +77540,125696,Female,Loyal Customer,51,Personal Travel,Eco,814,4,4,4,3,3,4,4,1,1,4,1,5,1,4,14,12.0,satisfied +77541,104557,Female,disloyal Customer,33,Business travel,Business,369,3,3,3,2,3,3,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +77542,18281,Female,disloyal Customer,69,Business travel,Eco Plus,228,2,2,2,1,2,2,2,2,2,2,3,4,5,2,0,0.0,neutral or dissatisfied +77543,47825,Male,Loyal Customer,38,Business travel,Business,3159,1,1,1,1,4,2,1,2,2,2,2,5,2,5,0,14.0,satisfied +77544,114898,Female,Loyal Customer,50,Business travel,Business,358,2,2,2,2,4,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +77545,16188,Female,disloyal Customer,33,Business travel,Eco,212,3,4,3,3,3,3,3,3,2,2,3,4,4,3,40,51.0,neutral or dissatisfied +77546,55580,Female,disloyal Customer,38,Business travel,Eco,1091,4,4,4,3,3,4,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +77547,114377,Female,Loyal Customer,52,Personal Travel,Eco Plus,862,2,4,2,4,3,5,5,1,1,2,1,3,1,3,58,50.0,neutral or dissatisfied +77548,106510,Male,disloyal Customer,63,Business travel,Business,271,5,5,5,2,3,5,3,3,5,3,4,5,4,3,17,29.0,satisfied +77549,27342,Female,Loyal Customer,46,Business travel,Business,954,4,4,3,4,4,3,4,5,5,5,5,3,5,2,0,0.0,satisfied +77550,40127,Female,Loyal Customer,24,Personal Travel,Eco,368,1,5,1,2,4,1,4,4,2,5,4,5,1,4,0,0.0,neutral or dissatisfied +77551,46855,Female,Loyal Customer,34,Business travel,Business,3207,2,2,2,2,4,1,5,4,4,4,4,1,4,1,12,37.0,satisfied +77552,57348,Female,Loyal Customer,22,Business travel,Eco,414,1,4,4,4,1,1,2,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +77553,109622,Female,Loyal Customer,52,Business travel,Business,930,1,1,1,1,2,5,4,2,2,2,2,3,2,4,42,38.0,satisfied +77554,100412,Male,Loyal Customer,63,Business travel,Eco Plus,1165,3,3,3,3,3,3,3,3,2,5,3,2,4,3,3,45.0,neutral or dissatisfied +77555,34235,Male,Loyal Customer,31,Business travel,Eco Plus,1189,4,5,5,5,4,4,4,4,5,5,3,4,1,4,8,0.0,satisfied +77556,26530,Male,Loyal Customer,46,Business travel,Business,3269,3,4,4,4,2,4,4,3,3,3,3,3,3,4,32,28.0,neutral or dissatisfied +77557,85223,Male,disloyal Customer,63,Business travel,Eco,296,5,0,5,3,4,5,4,4,5,5,2,5,4,4,12,18.0,satisfied +77558,45498,Female,Loyal Customer,68,Personal Travel,Eco,522,1,4,1,2,3,2,4,4,4,1,4,1,4,5,0,0.0,neutral or dissatisfied +77559,61035,Male,Loyal Customer,52,Personal Travel,Business,1506,4,5,4,3,4,5,5,3,3,4,4,3,3,3,0,5.0,satisfied +77560,124184,Female,Loyal Customer,57,Business travel,Business,2089,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +77561,72864,Female,Loyal Customer,62,Personal Travel,Eco,700,3,5,3,2,1,5,2,4,4,3,4,4,4,4,12,0.0,neutral or dissatisfied +77562,123887,Female,Loyal Customer,24,Personal Travel,Eco,544,5,3,5,4,4,5,4,4,1,4,3,2,4,4,0,62.0,satisfied +77563,7112,Male,Loyal Customer,12,Personal Travel,Eco,273,1,1,1,2,4,1,4,4,4,5,2,1,3,4,0,0.0,neutral or dissatisfied +77564,11811,Male,Loyal Customer,42,Business travel,Business,2072,5,1,5,5,2,4,4,4,4,4,4,3,4,5,121,106.0,satisfied +77565,13055,Male,Loyal Customer,37,Personal Travel,Eco Plus,374,3,4,3,3,5,3,5,5,5,3,4,3,4,5,6,6.0,neutral or dissatisfied +77566,5952,Female,Loyal Customer,39,Business travel,Business,3368,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +77567,15025,Male,Loyal Customer,44,Business travel,Business,576,2,1,1,1,1,4,4,2,2,2,2,3,2,3,30,25.0,neutral or dissatisfied +77568,9729,Female,disloyal Customer,29,Business travel,Business,696,3,3,3,1,1,3,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +77569,60786,Female,Loyal Customer,41,Personal Travel,Eco Plus,628,2,5,3,1,3,1,5,2,2,3,1,5,2,2,7,33.0,neutral or dissatisfied +77570,99933,Male,Loyal Customer,24,Personal Travel,Eco,764,4,5,4,1,5,4,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +77571,10978,Male,Loyal Customer,39,Business travel,Eco,396,3,5,5,5,3,2,3,3,4,5,3,1,3,3,48,34.0,neutral or dissatisfied +77572,67506,Female,Loyal Customer,43,Business travel,Business,2006,3,3,3,3,3,5,4,5,5,5,5,4,5,4,2,1.0,satisfied +77573,65147,Female,Loyal Customer,24,Personal Travel,Eco,190,5,5,5,2,5,5,1,5,3,4,4,3,5,5,0,0.0,satisfied +77574,8437,Male,Loyal Customer,47,Business travel,Eco Plus,737,4,5,5,5,4,4,4,4,3,4,3,3,4,4,37,20.0,neutral or dissatisfied +77575,21464,Female,Loyal Customer,47,Business travel,Eco,399,3,4,4,4,3,3,3,4,5,3,4,3,1,3,158,147.0,neutral or dissatisfied +77576,63072,Female,Loyal Customer,47,Personal Travel,Eco,967,1,5,1,1,4,5,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +77577,54517,Female,disloyal Customer,24,Business travel,Eco,925,5,4,4,3,5,4,5,5,4,5,3,5,1,5,13,0.0,satisfied +77578,40738,Female,Loyal Customer,35,Business travel,Business,599,3,3,1,3,2,2,3,4,4,4,4,1,4,5,0,0.0,satisfied +77579,23067,Male,Loyal Customer,15,Personal Travel,Eco,820,2,5,2,3,3,2,3,3,1,5,1,3,1,3,0,0.0,neutral or dissatisfied +77580,73133,Male,Loyal Customer,47,Business travel,Business,2810,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +77581,125334,Female,disloyal Customer,45,Business travel,Business,599,3,3,3,4,4,3,4,4,5,3,4,3,4,4,1,0.0,neutral or dissatisfied +77582,118519,Female,Loyal Customer,56,Business travel,Business,1531,3,3,3,3,4,5,4,4,4,4,4,5,4,4,36,29.0,satisfied +77583,32552,Male,Loyal Customer,38,Business travel,Business,101,5,5,5,5,4,5,5,5,5,5,4,4,5,2,0,0.0,satisfied +77584,111251,Female,Loyal Customer,46,Business travel,Business,1972,1,1,1,1,3,5,4,4,4,4,4,4,4,3,14,0.0,satisfied +77585,47703,Male,Loyal Customer,7,Personal Travel,Eco,1504,3,5,3,3,1,3,1,1,3,2,1,1,4,1,18,16.0,neutral or dissatisfied +77586,46268,Female,Loyal Customer,15,Personal Travel,Eco,679,3,4,3,1,1,3,1,1,4,4,5,3,5,1,17,12.0,neutral or dissatisfied +77587,11902,Male,Loyal Customer,40,Business travel,Business,3595,4,4,4,4,4,5,5,4,4,4,4,5,4,5,0,2.0,satisfied +77588,43029,Female,Loyal Customer,62,Business travel,Business,192,2,3,3,3,3,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +77589,36303,Male,Loyal Customer,16,Business travel,Business,187,1,4,4,4,3,3,1,3,2,2,3,2,2,3,4,0.0,neutral or dissatisfied +77590,73571,Male,Loyal Customer,54,Business travel,Business,3154,2,5,2,2,2,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +77591,55290,Male,Loyal Customer,55,Business travel,Business,1185,3,3,1,3,5,1,5,5,5,5,5,4,5,1,42,40.0,satisfied +77592,47742,Female,Loyal Customer,38,Personal Travel,Business,550,5,2,4,3,2,3,4,2,2,4,4,3,2,2,0,1.0,satisfied +77593,113230,Female,Loyal Customer,47,Business travel,Business,197,2,2,2,2,1,3,4,1,1,1,2,2,1,3,9,0.0,neutral or dissatisfied +77594,22469,Male,Loyal Customer,27,Personal Travel,Eco,208,1,5,1,2,1,1,1,1,5,1,4,3,3,1,0,0.0,neutral or dissatisfied +77595,34455,Male,Loyal Customer,60,Personal Travel,Eco,228,2,4,2,4,4,2,5,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +77596,18475,Male,Loyal Customer,41,Business travel,Eco,201,4,5,5,5,4,4,4,4,4,5,4,2,4,4,9,2.0,satisfied +77597,85688,Female,disloyal Customer,54,Business travel,Business,1547,1,2,2,1,5,1,3,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +77598,53520,Male,Loyal Customer,37,Personal Travel,Eco,2288,3,2,3,3,5,3,5,5,3,1,2,4,3,5,0,0.0,neutral or dissatisfied +77599,70502,Female,Loyal Customer,64,Personal Travel,Eco,867,4,1,4,4,4,4,4,2,2,4,2,1,2,3,49,31.0,neutral or dissatisfied +77600,58520,Female,Loyal Customer,63,Personal Travel,Eco,719,3,4,2,4,5,5,5,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +77601,64327,Female,disloyal Customer,21,Business travel,Eco,1212,4,4,4,4,1,4,1,1,2,5,4,2,4,1,18,21.0,neutral or dissatisfied +77602,87525,Female,Loyal Customer,47,Personal Travel,Eco,321,3,3,4,3,2,4,3,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +77603,113643,Male,Loyal Customer,45,Personal Travel,Eco,397,3,3,3,4,4,3,1,4,3,5,4,4,3,4,42,40.0,neutral or dissatisfied +77604,69077,Male,disloyal Customer,44,Business travel,Eco,989,4,4,4,1,5,4,5,5,1,1,5,4,3,5,0,0.0,satisfied +77605,68488,Male,disloyal Customer,8,Business travel,Eco,1067,4,3,3,3,1,3,1,1,4,5,2,3,3,1,0,4.0,neutral or dissatisfied +77606,58342,Female,disloyal Customer,22,Business travel,Business,296,2,1,1,2,2,1,2,2,1,5,3,4,3,2,81,82.0,neutral or dissatisfied +77607,29849,Female,Loyal Customer,54,Business travel,Business,1606,2,2,2,2,2,2,1,5,5,5,5,5,5,5,0,0.0,satisfied +77608,13769,Female,Loyal Customer,28,Personal Travel,Business,925,3,5,3,4,4,3,4,4,4,2,4,3,4,4,0,1.0,neutral or dissatisfied +77609,31247,Male,Loyal Customer,48,Personal Travel,Eco,472,2,5,1,2,4,1,4,4,5,5,3,3,1,4,0,8.0,neutral or dissatisfied +77610,83231,Female,disloyal Customer,28,Business travel,Business,1979,3,2,2,3,4,2,4,4,5,5,3,3,5,4,67,38.0,neutral or dissatisfied +77611,94425,Male,Loyal Customer,60,Business travel,Business,2419,5,5,5,5,4,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +77612,92213,Male,Loyal Customer,15,Personal Travel,Eco,1956,1,5,1,5,1,1,1,1,5,3,5,4,5,1,5,0.0,neutral or dissatisfied +77613,106568,Male,Loyal Customer,57,Personal Travel,Eco Plus,1024,3,4,3,3,1,3,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +77614,2276,Male,disloyal Customer,39,Business travel,Business,691,4,4,4,3,1,4,1,1,3,4,4,4,4,1,67,65.0,neutral or dissatisfied +77615,94278,Male,Loyal Customer,56,Business travel,Business,3762,5,5,5,5,3,4,4,5,5,5,5,4,5,5,10,5.0,satisfied +77616,5497,Male,Loyal Customer,51,Business travel,Business,910,3,3,4,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +77617,64502,Male,disloyal Customer,27,Business travel,Business,469,1,1,1,2,4,1,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +77618,55136,Female,Loyal Customer,70,Personal Travel,Eco,1379,3,3,3,3,2,4,3,2,2,3,2,1,2,1,49,38.0,neutral or dissatisfied +77619,123893,Male,Loyal Customer,23,Personal Travel,Eco,546,4,3,4,1,3,4,3,3,1,1,3,2,4,3,0,0.0,neutral or dissatisfied +77620,63446,Female,Loyal Customer,28,Personal Travel,Eco,337,3,4,3,1,3,3,3,3,4,4,5,5,4,3,31,29.0,neutral or dissatisfied +77621,102460,Male,Loyal Customer,49,Personal Travel,Eco,397,0,5,0,3,3,0,1,3,4,5,5,4,5,3,6,0.0,satisfied +77622,56644,Male,Loyal Customer,45,Business travel,Business,597,5,5,5,5,4,3,3,5,5,5,5,5,5,2,2,16.0,satisfied +77623,48203,Male,Loyal Customer,45,Business travel,Business,3032,5,5,5,5,1,4,3,5,5,5,5,5,5,4,40,36.0,satisfied +77624,38923,Female,Loyal Customer,43,Business travel,Eco,162,4,4,4,4,4,4,1,4,4,4,4,4,4,5,0,0.0,satisfied +77625,5020,Male,disloyal Customer,38,Business travel,Business,235,4,4,4,2,4,4,5,4,3,2,5,4,5,4,0,0.0,satisfied +77626,72561,Female,disloyal Customer,30,Business travel,Eco,985,1,1,1,3,1,1,3,4,3,4,3,3,1,3,154,157.0,neutral or dissatisfied +77627,16070,Female,disloyal Customer,23,Business travel,Eco,744,2,1,1,4,4,1,4,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +77628,88509,Male,Loyal Customer,56,Business travel,Eco,442,4,5,5,5,4,4,4,4,1,1,1,1,4,4,0,0.0,satisfied +77629,23983,Female,Loyal Customer,9,Personal Travel,Business,427,3,3,3,3,1,3,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +77630,27760,Female,Loyal Customer,51,Business travel,Business,680,4,4,4,4,1,1,2,5,5,5,5,2,5,3,0,0.0,satisfied +77631,43820,Female,Loyal Customer,39,Business travel,Business,2542,0,5,1,2,1,2,4,5,5,5,5,1,5,4,0,0.0,satisfied +77632,57012,Female,Loyal Customer,30,Personal Travel,Eco,2425,3,2,3,3,3,5,5,4,4,4,4,5,3,5,19,22.0,neutral or dissatisfied +77633,98261,Male,disloyal Customer,24,Business travel,Eco,1072,3,3,3,5,4,3,4,4,3,3,5,4,4,4,0,22.0,neutral or dissatisfied +77634,104922,Female,disloyal Customer,18,Business travel,Business,210,5,5,5,1,1,5,1,1,5,2,5,3,4,1,0,0.0,satisfied +77635,69058,Male,Loyal Customer,40,Business travel,Business,1521,2,5,5,5,5,3,3,2,2,2,2,3,2,3,0,15.0,neutral or dissatisfied +77636,10940,Female,disloyal Customer,25,Business travel,Business,224,5,4,5,3,3,5,3,3,3,2,4,3,5,3,0,0.0,satisfied +77637,18341,Male,Loyal Customer,35,Business travel,Eco,818,4,1,3,1,4,4,4,4,3,1,2,4,1,4,0,0.0,satisfied +77638,15394,Male,Loyal Customer,51,Business travel,Business,2609,2,1,1,1,2,3,3,2,2,2,2,2,2,3,3,12.0,neutral or dissatisfied +77639,96681,Male,Loyal Customer,66,Personal Travel,Eco Plus,937,1,5,0,3,2,0,2,2,4,3,4,5,3,2,1,0.0,neutral or dissatisfied +77640,105074,Male,Loyal Customer,41,Business travel,Business,2396,2,2,2,2,5,4,4,4,4,4,4,3,4,3,19,16.0,satisfied +77641,77744,Male,disloyal Customer,23,Business travel,Eco,413,2,4,2,3,3,2,3,3,4,4,3,4,1,3,0,0.0,neutral or dissatisfied +77642,90107,Male,Loyal Customer,28,Business travel,Business,2992,3,2,2,2,3,3,3,3,3,3,2,4,2,3,39,40.0,neutral or dissatisfied +77643,92727,Male,Loyal Customer,22,Business travel,Business,3920,3,3,3,3,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +77644,95819,Male,Loyal Customer,33,Business travel,Business,1428,2,2,2,2,4,4,4,4,3,4,4,5,4,4,0,0.0,satisfied +77645,61232,Male,disloyal Customer,24,Business travel,Eco,909,1,1,1,3,3,1,3,3,3,4,4,1,4,3,10,7.0,neutral or dissatisfied +77646,19074,Female,Loyal Customer,68,Business travel,Business,569,1,2,2,2,5,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +77647,31300,Male,Loyal Customer,51,Business travel,Business,680,2,2,2,2,1,1,3,4,4,4,4,3,4,2,0,0.0,satisfied +77648,30248,Female,Loyal Customer,39,Personal Travel,Eco Plus,896,3,4,3,2,2,3,2,2,4,3,5,5,4,2,1,7.0,neutral or dissatisfied +77649,124807,Female,disloyal Customer,49,Business travel,Eco,280,3,1,3,4,1,3,3,1,3,3,4,2,3,1,78,63.0,neutral or dissatisfied +77650,104818,Male,Loyal Customer,59,Business travel,Business,472,3,3,3,3,3,2,2,3,3,3,3,4,3,1,16,23.0,neutral or dissatisfied +77651,8964,Male,Loyal Customer,11,Personal Travel,Eco,812,3,1,3,3,3,1,1,1,4,3,3,1,3,1,49,162.0,neutral or dissatisfied +77652,64835,Female,Loyal Customer,57,Business travel,Business,354,3,3,3,3,2,5,5,3,3,4,3,5,3,4,4,4.0,satisfied +77653,72573,Female,Loyal Customer,32,Business travel,Eco,1121,1,5,5,5,1,1,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +77654,53349,Female,Loyal Customer,23,Business travel,Eco,1452,0,4,0,1,5,0,5,5,2,3,2,5,2,5,2,0.0,satisfied +77655,14967,Male,Loyal Customer,39,Business travel,Eco,1020,5,5,5,5,5,5,5,5,5,2,2,1,4,5,0,0.0,satisfied +77656,10279,Male,Loyal Customer,41,Business travel,Business,3126,2,2,2,2,4,4,5,5,5,5,5,4,5,5,7,9.0,satisfied +77657,114773,Female,Loyal Customer,46,Business travel,Business,2071,4,4,4,4,4,4,4,2,2,2,2,3,2,4,39,38.0,satisfied +77658,124565,Female,Loyal Customer,29,Personal Travel,Eco,453,2,1,2,4,5,2,5,5,2,5,4,4,3,5,29,13.0,neutral or dissatisfied +77659,44443,Male,Loyal Customer,62,Personal Travel,Eco,420,0,3,0,1,1,0,1,1,1,3,5,5,2,1,0,0.0,satisfied +77660,75329,Male,Loyal Customer,37,Business travel,Business,2504,3,2,2,2,3,3,3,2,2,3,4,3,2,3,5,28.0,neutral or dissatisfied +77661,3221,Female,Loyal Customer,48,Business travel,Business,2903,4,4,4,4,4,5,4,4,4,5,4,5,4,5,43,43.0,satisfied +77662,110644,Female,Loyal Customer,50,Business travel,Business,2260,1,1,1,1,5,5,5,5,5,5,5,4,5,5,21,16.0,satisfied +77663,13571,Male,Loyal Customer,61,Personal Travel,Eco,106,2,4,2,2,1,2,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +77664,95335,Male,Loyal Customer,50,Personal Travel,Eco,441,3,4,3,3,1,3,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +77665,103643,Male,Loyal Customer,45,Business travel,Business,3657,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +77666,51481,Male,disloyal Customer,34,Business travel,Business,369,2,2,2,1,1,2,1,1,4,3,5,3,4,1,0,1.0,neutral or dissatisfied +77667,127186,Male,Loyal Customer,44,Business travel,Business,1996,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +77668,75439,Male,Loyal Customer,50,Business travel,Eco,2342,2,1,1,1,1,2,1,1,4,3,2,4,3,1,0,14.0,neutral or dissatisfied +77669,46768,Female,Loyal Customer,53,Personal Travel,Eco Plus,73,2,5,2,4,2,4,5,1,1,2,1,5,1,3,54,54.0,neutral or dissatisfied +77670,15883,Female,Loyal Customer,70,Personal Travel,Eco,241,3,5,3,3,5,4,5,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +77671,81948,Female,Loyal Customer,53,Business travel,Business,1522,3,3,5,3,5,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +77672,55840,Male,Loyal Customer,71,Business travel,Eco,1016,1,2,2,2,1,1,1,1,3,1,3,2,4,1,0,6.0,neutral or dissatisfied +77673,73978,Male,Loyal Customer,48,Personal Travel,Eco,2330,4,4,4,2,4,5,5,4,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +77674,124517,Male,disloyal Customer,27,Business travel,Business,1276,3,4,4,4,5,4,5,5,5,3,5,4,5,5,0,27.0,neutral or dissatisfied +77675,9193,Female,Loyal Customer,32,Business travel,Business,363,3,3,3,3,2,2,2,2,5,2,4,3,5,2,0,0.0,satisfied +77676,91159,Female,Loyal Customer,60,Personal Travel,Eco,366,1,4,1,2,5,4,3,4,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +77677,82045,Female,Loyal Customer,12,Personal Travel,Eco,1589,3,4,3,3,1,3,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +77678,50139,Male,Loyal Customer,42,Business travel,Eco,373,3,3,3,3,3,3,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +77679,28639,Female,disloyal Customer,42,Business travel,Eco,1169,2,2,2,3,1,2,1,1,3,1,4,4,2,1,0,0.0,neutral or dissatisfied +77680,17577,Male,Loyal Customer,30,Business travel,Business,2343,3,2,2,2,3,3,3,2,4,4,3,3,1,3,149,108.0,neutral or dissatisfied +77681,80867,Female,Loyal Customer,64,Personal Travel,Eco,484,4,4,4,2,3,2,1,1,1,4,1,3,1,2,40,41.0,neutral or dissatisfied +77682,68156,Male,Loyal Customer,59,Business travel,Business,3310,4,4,4,4,4,4,5,4,4,5,4,5,4,4,4,6.0,satisfied +77683,66232,Male,Loyal Customer,60,Business travel,Eco,550,2,4,4,4,2,2,2,2,2,3,3,4,3,2,15,30.0,neutral or dissatisfied +77684,20401,Female,Loyal Customer,60,Personal Travel,Eco,588,3,4,3,3,5,5,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +77685,86084,Male,disloyal Customer,23,Business travel,Eco,331,2,5,2,1,4,2,4,4,4,3,4,5,5,4,4,0.0,neutral or dissatisfied +77686,91757,Female,Loyal Customer,31,Business travel,Business,2013,5,5,5,5,4,4,4,4,4,5,5,4,5,4,78,82.0,satisfied +77687,111909,Male,Loyal Customer,24,Business travel,Eco Plus,804,2,1,1,1,2,2,1,2,2,3,3,4,3,2,8,16.0,neutral or dissatisfied +77688,24863,Female,Loyal Customer,45,Business travel,Business,356,5,5,5,5,2,3,1,2,2,2,2,2,2,1,0,0.0,satisfied +77689,56416,Male,disloyal Customer,39,Business travel,Eco,719,2,2,2,2,5,2,5,5,4,3,2,2,3,5,0,9.0,neutral or dissatisfied +77690,82901,Female,Loyal Customer,54,Personal Travel,Eco,594,4,3,4,4,3,2,3,4,4,4,4,2,4,2,28,18.0,neutral or dissatisfied +77691,116398,Female,Loyal Customer,21,Personal Travel,Eco,358,1,4,1,2,4,1,4,4,4,2,4,5,5,4,39,40.0,neutral or dissatisfied +77692,4458,Male,Loyal Customer,25,Personal Travel,Eco Plus,762,1,1,1,2,3,1,3,3,3,4,3,1,2,3,0,0.0,neutral or dissatisfied +77693,30030,Female,disloyal Customer,37,Business travel,Eco,261,1,1,1,4,3,1,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +77694,101269,Male,Loyal Customer,42,Personal Travel,Eco,2176,1,3,1,1,1,1,1,1,4,4,3,2,5,1,70,42.0,neutral or dissatisfied +77695,40095,Female,Loyal Customer,42,Business travel,Eco,368,5,3,3,3,3,3,4,5,5,5,5,2,5,1,13,0.0,satisfied +77696,7634,Male,disloyal Customer,26,Business travel,Business,641,2,2,2,1,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +77697,8691,Male,Loyal Customer,26,Business travel,Business,3666,2,5,5,5,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +77698,119436,Female,Loyal Customer,24,Personal Travel,Eco,399,3,5,3,2,4,3,3,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +77699,18082,Female,Loyal Customer,30,Personal Travel,Eco,605,4,4,4,3,5,4,5,5,5,5,4,5,4,5,0,16.0,neutral or dissatisfied +77700,93763,Female,Loyal Customer,27,Personal Travel,Eco,368,2,5,2,1,2,2,5,2,3,3,5,1,3,2,1,0.0,neutral or dissatisfied +77701,76175,Male,Loyal Customer,58,Personal Travel,Eco,546,2,4,2,3,4,2,4,4,3,2,4,2,4,4,7,0.0,neutral or dissatisfied +77702,93719,Male,Loyal Customer,23,Business travel,Business,630,5,5,5,5,4,4,4,4,3,3,5,4,5,4,0,17.0,satisfied +77703,8133,Female,Loyal Customer,60,Business travel,Business,125,1,1,1,1,5,3,4,2,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +77704,8492,Female,Loyal Customer,68,Personal Travel,Eco,677,2,3,2,1,1,4,5,5,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +77705,51197,Male,Loyal Customer,24,Business travel,Eco Plus,373,4,5,5,5,4,4,4,4,3,3,2,3,5,4,0,0.0,satisfied +77706,22705,Female,Loyal Customer,42,Personal Travel,Eco,589,4,4,4,2,3,4,5,2,2,4,2,3,2,4,17,15.0,neutral or dissatisfied +77707,65212,Male,Loyal Customer,57,Business travel,Business,1951,1,1,1,1,3,5,4,5,5,4,5,5,5,4,59,52.0,satisfied +77708,86180,Female,disloyal Customer,37,Business travel,Business,377,4,4,4,4,2,4,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +77709,128243,Female,Loyal Customer,54,Business travel,Business,2927,3,3,3,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +77710,7457,Female,Loyal Customer,38,Business travel,Eco Plus,122,4,2,2,2,4,4,4,4,4,2,5,4,1,4,0,0.0,satisfied +77711,103165,Male,Loyal Customer,53,Business travel,Business,2213,4,4,2,4,3,5,4,4,4,4,4,3,4,5,0,3.0,satisfied +77712,87488,Female,Loyal Customer,41,Business travel,Business,321,0,0,0,1,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +77713,3840,Male,Loyal Customer,31,Personal Travel,Eco,710,2,4,2,1,3,2,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +77714,10836,Male,Loyal Customer,52,Business travel,Eco,140,2,1,1,1,2,2,2,2,2,2,4,4,4,2,20,19.0,neutral or dissatisfied +77715,61192,Male,Loyal Customer,50,Business travel,Business,1826,1,1,1,1,4,4,5,5,5,5,5,5,5,3,1,19.0,satisfied +77716,129414,Male,disloyal Customer,24,Business travel,Business,414,5,0,5,5,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +77717,38053,Male,Loyal Customer,58,Business travel,Business,2945,1,1,1,1,4,4,2,4,4,4,4,3,4,3,37,39.0,satisfied +77718,76484,Female,Loyal Customer,26,Business travel,Business,1601,3,1,3,3,3,3,3,3,3,5,4,5,4,3,5,0.0,satisfied +77719,76103,Female,Loyal Customer,27,Personal Travel,Eco,669,4,5,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +77720,65649,Male,Loyal Customer,49,Business travel,Business,2271,2,2,2,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +77721,49473,Female,disloyal Customer,47,Business travel,Eco,447,4,5,5,3,5,5,3,5,5,1,1,2,4,5,0,0.0,neutral or dissatisfied +77722,97049,Female,Loyal Customer,48,Business travel,Business,1211,2,2,2,2,5,4,5,4,4,4,4,3,4,3,18,6.0,satisfied +77723,19600,Female,disloyal Customer,22,Business travel,Eco Plus,173,3,3,3,4,5,3,5,5,4,1,3,1,3,5,20,31.0,neutral or dissatisfied +77724,42431,Female,Loyal Customer,61,Business travel,Eco,1119,4,1,1,1,3,5,1,4,4,4,4,2,4,3,0,0.0,satisfied +77725,94148,Male,Loyal Customer,39,Business travel,Business,3226,5,5,5,5,3,4,5,4,4,4,5,3,4,4,12,7.0,satisfied +77726,23296,Male,disloyal Customer,25,Business travel,Eco,674,3,3,3,1,1,3,2,1,2,5,5,2,2,1,11,16.0,neutral or dissatisfied +77727,56427,Female,disloyal Customer,45,Business travel,Business,719,1,1,1,3,1,2,3,4,5,4,5,3,3,3,132,115.0,neutral or dissatisfied +77728,77559,Female,Loyal Customer,17,Business travel,Business,986,3,3,3,3,5,5,5,5,5,2,5,4,4,5,2,0.0,satisfied +77729,98231,Female,disloyal Customer,27,Business travel,Business,1072,1,1,1,3,1,1,1,1,1,1,3,4,4,1,20,10.0,neutral or dissatisfied +77730,32692,Female,Loyal Customer,39,Business travel,Eco,163,3,5,5,5,3,3,3,3,1,4,1,1,2,3,0,0.0,neutral or dissatisfied +77731,32101,Female,Loyal Customer,35,Business travel,Business,1539,5,5,5,5,4,1,4,5,5,5,5,4,5,1,0,0.0,satisfied +77732,108589,Male,disloyal Customer,37,Business travel,Business,696,1,1,1,3,1,1,1,1,5,3,5,3,4,1,0,4.0,neutral or dissatisfied +77733,26250,Female,disloyal Customer,21,Business travel,Eco,270,3,0,3,1,4,3,4,4,4,2,3,1,3,4,0,0.0,neutral or dissatisfied +77734,82423,Female,Loyal Customer,49,Business travel,Business,2039,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +77735,113148,Male,Loyal Customer,36,Business travel,Eco,628,1,3,4,4,1,2,1,1,3,2,3,1,4,1,18,11.0,neutral or dissatisfied +77736,8490,Female,Loyal Customer,38,Business travel,Eco,677,3,1,1,1,3,3,3,3,3,5,4,1,3,3,19,10.0,neutral or dissatisfied +77737,63500,Female,Loyal Customer,53,Business travel,Business,1956,3,3,3,3,3,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +77738,25697,Male,Loyal Customer,46,Business travel,Business,1733,2,2,2,2,4,4,3,2,2,2,2,2,2,3,17,8.0,neutral or dissatisfied +77739,98832,Female,Loyal Customer,40,Personal Travel,Eco,763,4,4,4,3,3,4,3,3,1,4,3,4,3,3,34,39.0,neutral or dissatisfied +77740,65199,Female,Loyal Customer,54,Personal Travel,Eco,247,3,4,3,4,5,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +77741,87154,Female,Loyal Customer,34,Business travel,Business,946,3,3,5,3,3,5,5,4,4,4,4,4,4,4,36,62.0,satisfied +77742,36049,Male,Loyal Customer,44,Business travel,Eco,399,2,3,3,3,2,2,2,2,2,3,4,3,4,2,30,29.0,neutral or dissatisfied +77743,34581,Female,Loyal Customer,58,Business travel,Business,1576,3,2,2,2,2,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +77744,60523,Female,Loyal Customer,12,Personal Travel,Eco,985,3,4,3,5,2,3,2,2,5,4,5,3,5,2,29,25.0,neutral or dissatisfied +77745,99190,Female,Loyal Customer,37,Personal Travel,Eco,462,3,5,2,4,4,2,4,4,3,3,4,3,4,4,22,16.0,neutral or dissatisfied +77746,84018,Male,Loyal Customer,8,Personal Travel,Eco,373,3,0,3,5,5,3,5,5,5,2,4,3,5,5,3,0.0,neutral or dissatisfied +77747,68054,Male,disloyal Customer,29,Business travel,Business,868,0,0,0,3,3,0,3,3,3,2,4,5,5,3,0,4.0,satisfied +77748,100352,Female,Loyal Customer,35,Personal Travel,Eco,1033,1,3,1,2,5,1,5,5,3,5,3,1,3,5,8,22.0,neutral or dissatisfied +77749,20507,Female,Loyal Customer,7,Personal Travel,Eco,130,2,0,2,4,3,2,3,3,5,3,5,3,4,3,23,20.0,neutral or dissatisfied +77750,93604,Female,Loyal Customer,55,Business travel,Business,1964,4,1,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +77751,15710,Female,disloyal Customer,25,Business travel,Eco,419,2,2,2,2,4,2,4,4,4,1,1,3,1,4,63,57.0,neutral or dissatisfied +77752,26246,Female,Loyal Customer,24,Personal Travel,Eco,270,2,0,2,3,1,2,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +77753,50937,Female,Loyal Customer,50,Personal Travel,Eco,262,4,3,4,3,2,2,5,1,1,4,1,1,1,3,60,79.0,neutral or dissatisfied +77754,95356,Female,Loyal Customer,28,Personal Travel,Eco,248,3,4,3,4,1,3,1,1,5,2,5,4,4,1,31,34.0,neutral or dissatisfied +77755,53268,Female,disloyal Customer,42,Business travel,Eco,811,2,1,1,1,1,1,1,1,3,2,1,2,5,1,3,0.0,neutral or dissatisfied +77756,114379,Male,Loyal Customer,49,Personal Travel,Eco Plus,957,3,5,3,2,4,3,4,4,4,5,5,4,5,4,2,8.0,neutral or dissatisfied +77757,8064,Male,Loyal Customer,61,Business travel,Business,2895,0,0,0,3,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +77758,118464,Male,disloyal Customer,26,Business travel,Business,621,5,5,5,4,3,4,3,3,3,2,4,3,5,3,3,0.0,satisfied +77759,25468,Male,disloyal Customer,29,Business travel,Business,481,2,2,2,3,4,2,1,4,2,1,3,4,4,4,7,0.0,neutral or dissatisfied +77760,46812,Female,Loyal Customer,50,Business travel,Eco,850,2,2,2,2,4,1,2,2,2,2,2,1,2,4,29,18.0,satisfied +77761,105742,Female,Loyal Customer,50,Business travel,Business,925,2,2,2,2,4,5,4,4,4,4,4,4,4,4,15,3.0,satisfied +77762,2044,Female,disloyal Customer,48,Business travel,Business,812,1,1,1,4,5,1,5,5,3,5,5,3,4,5,0,29.0,neutral or dissatisfied +77763,98910,Male,Loyal Customer,52,Business travel,Business,3097,5,5,5,5,3,5,4,4,4,5,4,3,4,5,3,0.0,satisfied +77764,126693,Male,disloyal Customer,39,Business travel,Business,2521,4,4,4,1,1,4,1,1,4,4,4,3,4,1,0,45.0,neutral or dissatisfied +77765,77282,Female,Loyal Customer,55,Business travel,Eco,1931,3,4,4,4,2,4,4,2,2,3,2,1,2,2,112,101.0,neutral or dissatisfied +77766,104931,Male,Loyal Customer,16,Personal Travel,Eco,210,1,3,1,3,1,1,1,1,3,2,3,2,3,1,35,26.0,neutral or dissatisfied +77767,110022,Male,Loyal Customer,48,Personal Travel,Eco,1204,2,2,2,3,4,2,4,4,2,4,3,1,3,4,14,12.0,neutral or dissatisfied +77768,66229,Male,Loyal Customer,25,Business travel,Eco,550,3,2,2,2,3,2,1,3,2,5,3,2,2,3,20,26.0,neutral or dissatisfied +77769,16368,Male,disloyal Customer,23,Business travel,Eco,319,1,0,1,4,2,1,2,2,5,2,4,5,3,2,0,0.0,neutral or dissatisfied +77770,122240,Male,Loyal Customer,29,Business travel,Business,1687,3,3,3,3,3,3,3,3,1,2,2,1,3,3,0,0.0,neutral or dissatisfied +77771,93595,Female,disloyal Customer,43,Business travel,Business,577,2,2,2,5,3,2,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +77772,33612,Male,Loyal Customer,38,Business travel,Eco,399,3,5,5,5,3,5,3,3,5,2,1,2,4,3,0,0.0,satisfied +77773,37141,Female,Loyal Customer,64,Business travel,Eco,1189,5,4,5,4,1,3,4,5,5,5,5,3,5,5,0,5.0,satisfied +77774,4131,Male,Loyal Customer,43,Business travel,Eco,544,1,3,5,3,1,1,1,1,4,2,2,3,2,1,0,0.0,neutral or dissatisfied +77775,117439,Male,Loyal Customer,60,Business travel,Business,1020,5,5,5,5,5,4,5,5,5,4,5,3,5,4,15,9.0,satisfied +77776,93958,Female,disloyal Customer,50,Business travel,Eco Plus,107,2,2,2,4,3,2,4,3,4,2,1,5,1,3,0,0.0,neutral or dissatisfied +77777,19338,Male,Loyal Customer,36,Personal Travel,Eco,694,3,5,2,3,4,2,1,4,3,2,5,3,4,4,53,63.0,neutral or dissatisfied +77778,49630,Male,disloyal Customer,23,Business travel,Eco,337,3,2,3,4,1,3,1,1,4,4,4,3,4,1,0,21.0,neutral or dissatisfied +77779,128287,Male,Loyal Customer,28,Business travel,Business,2013,1,1,1,1,4,4,4,4,4,5,4,5,4,4,14,7.0,satisfied +77780,13902,Female,disloyal Customer,57,Business travel,Eco,192,4,3,4,1,1,4,1,1,2,1,4,5,2,1,0,0.0,neutral or dissatisfied +77781,55646,Male,Loyal Customer,52,Business travel,Business,315,2,2,2,2,5,5,4,5,5,5,5,3,5,5,57,65.0,satisfied +77782,96001,Male,Loyal Customer,52,Business travel,Business,3771,3,4,3,3,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +77783,77298,Male,Loyal Customer,43,Business travel,Business,3554,1,1,1,1,5,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +77784,94844,Male,disloyal Customer,44,Business travel,Business,239,2,2,2,4,3,2,3,3,5,5,4,3,4,3,1,0.0,neutral or dissatisfied +77785,38140,Male,Loyal Customer,16,Personal Travel,Eco,1121,1,5,1,1,1,1,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +77786,15741,Female,Loyal Customer,24,Business travel,Eco Plus,419,0,3,0,3,3,0,3,3,1,3,4,4,1,3,0,0.0,satisfied +77787,4647,Female,Loyal Customer,60,Business travel,Business,327,1,1,1,1,4,4,4,5,4,4,5,4,3,4,118,137.0,satisfied +77788,15328,Female,disloyal Customer,25,Business travel,Eco,199,1,2,1,4,1,3,3,1,5,4,4,3,2,3,184,170.0,neutral or dissatisfied +77789,91087,Male,Loyal Customer,13,Personal Travel,Eco,444,4,5,4,5,4,4,4,4,3,4,5,3,5,4,21,15.0,neutral or dissatisfied +77790,36024,Female,disloyal Customer,25,Business travel,Eco,399,3,0,2,4,1,2,1,1,3,4,3,4,5,1,0,0.0,neutral or dissatisfied +77791,46437,Female,Loyal Customer,24,Business travel,Business,1304,1,1,1,1,5,5,5,5,2,4,2,4,4,5,6,0.0,satisfied +77792,75794,Female,Loyal Customer,35,Personal Travel,Eco,868,2,2,3,3,3,3,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +77793,103997,Male,disloyal Customer,27,Business travel,Eco,1592,3,2,2,4,1,3,1,1,1,5,2,1,3,1,0,0.0,neutral or dissatisfied +77794,7892,Female,Loyal Customer,41,Personal Travel,Eco,910,3,4,3,5,3,3,3,3,3,2,5,2,2,3,0,32.0,neutral or dissatisfied +77795,124393,Male,Loyal Customer,23,Personal Travel,Eco,808,2,2,2,4,1,2,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +77796,16271,Female,Loyal Customer,38,Business travel,Eco,546,2,1,1,1,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +77797,98258,Female,Loyal Customer,39,Business travel,Business,2191,1,1,3,1,4,4,5,4,4,4,4,4,4,5,0,3.0,satisfied +77798,32324,Male,Loyal Customer,61,Business travel,Business,2748,5,5,5,5,3,2,4,4,4,4,5,2,4,1,0,0.0,satisfied +77799,36653,Female,Loyal Customer,55,Personal Travel,Eco,1010,2,3,2,3,5,4,3,3,3,2,3,4,3,3,0,13.0,neutral or dissatisfied +77800,54167,Female,disloyal Customer,22,Business travel,Eco,1400,2,3,3,2,3,2,3,3,5,1,5,4,1,3,1,0.0,neutral or dissatisfied +77801,57697,Male,Loyal Customer,53,Business travel,Eco,467,5,5,5,5,5,5,5,5,5,1,2,1,3,5,0,46.0,satisfied +77802,124636,Male,Loyal Customer,44,Personal Travel,Eco,1671,1,4,1,4,5,1,2,5,2,2,4,2,4,5,4,0.0,neutral or dissatisfied +77803,585,Male,Loyal Customer,46,Business travel,Business,164,1,1,4,1,2,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +77804,107156,Male,Loyal Customer,49,Business travel,Business,1877,5,5,5,5,4,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +77805,122909,Male,Loyal Customer,41,Business travel,Business,507,3,1,1,1,3,3,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +77806,54900,Female,Loyal Customer,24,Personal Travel,Eco,641,2,4,2,2,2,2,4,2,4,5,5,4,4,2,11,12.0,neutral or dissatisfied +77807,61365,Male,Loyal Customer,19,Business travel,Business,2057,4,4,2,4,4,4,4,4,4,3,4,3,4,4,12,0.0,satisfied +77808,87740,Male,Loyal Customer,43,Business travel,Business,214,5,5,5,5,2,5,5,5,5,5,5,4,5,3,33,23.0,satisfied +77809,71882,Female,Loyal Customer,13,Personal Travel,Eco,1723,3,4,2,3,5,2,5,5,3,4,4,4,4,5,2,0.0,neutral or dissatisfied +77810,96418,Male,Loyal Customer,69,Personal Travel,Eco,1407,3,4,3,4,5,3,5,5,4,3,5,2,2,5,49,22.0,neutral or dissatisfied +77811,20450,Male,Loyal Customer,40,Business travel,Eco,177,3,5,5,5,3,2,3,3,3,4,3,5,4,3,0,5.0,satisfied +77812,103210,Female,Loyal Customer,42,Business travel,Business,1869,1,1,1,1,5,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +77813,58513,Female,Loyal Customer,49,Personal Travel,Eco,719,3,4,3,3,3,5,4,2,2,3,2,5,2,4,7,0.0,neutral or dissatisfied +77814,62158,Female,Loyal Customer,45,Business travel,Business,2454,1,1,1,1,3,4,4,4,4,4,4,5,4,3,10,3.0,satisfied +77815,115190,Female,Loyal Customer,48,Business travel,Business,3183,2,2,3,2,3,5,4,5,5,5,5,3,5,4,8,0.0,satisfied +77816,43148,Female,Loyal Customer,69,Personal Travel,Eco Plus,192,1,5,1,1,4,1,2,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +77817,70712,Female,Loyal Customer,28,Business travel,Business,1527,1,1,1,1,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +77818,18057,Male,Loyal Customer,29,Business travel,Business,488,2,4,3,3,2,2,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +77819,107668,Male,Loyal Customer,49,Business travel,Business,405,4,4,4,4,3,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +77820,78696,Male,Loyal Customer,52,Personal Travel,Eco Plus,674,0,4,0,2,1,0,1,1,5,4,5,5,4,1,2,0.0,satisfied +77821,30863,Male,Loyal Customer,23,Business travel,Business,1506,4,4,4,4,5,5,5,5,5,2,5,3,3,5,0,0.0,satisfied +77822,4222,Male,Loyal Customer,31,Personal Travel,Eco,888,3,3,3,4,1,3,1,1,5,5,3,1,5,1,0,0.0,neutral or dissatisfied +77823,30657,Male,Loyal Customer,63,Personal Travel,Eco,533,1,5,1,1,2,1,2,2,4,3,5,4,5,2,0,3.0,neutral or dissatisfied +77824,116800,Male,Loyal Customer,9,Personal Travel,Eco Plus,342,3,4,4,5,5,4,2,5,4,4,5,4,5,5,29,26.0,neutral or dissatisfied +77825,76797,Male,Loyal Customer,57,Business travel,Eco,289,1,4,4,4,1,1,1,1,4,2,3,4,4,1,0,10.0,neutral or dissatisfied +77826,31897,Female,disloyal Customer,30,Business travel,Eco Plus,2762,2,2,2,3,5,2,5,5,2,4,4,3,1,5,1,0.0,neutral or dissatisfied +77827,21797,Male,disloyal Customer,24,Business travel,Eco,241,4,0,5,3,4,5,4,4,1,2,4,5,3,4,0,0.0,neutral or dissatisfied +77828,22472,Male,Loyal Customer,47,Personal Travel,Eco,83,1,3,1,3,5,1,5,5,4,5,2,2,3,5,0,0.0,neutral or dissatisfied +77829,8626,Female,Loyal Customer,64,Business travel,Business,1652,3,2,2,2,4,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +77830,83574,Male,Loyal Customer,30,Business travel,Business,2613,2,3,3,3,2,2,2,2,3,3,4,3,3,2,2,10.0,neutral or dissatisfied +77831,103943,Male,disloyal Customer,25,Business travel,Eco,533,4,3,4,4,5,4,3,5,4,1,3,2,3,5,69,58.0,neutral or dissatisfied +77832,128384,Female,Loyal Customer,55,Business travel,Business,2086,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +77833,123512,Male,Loyal Customer,58,Personal Travel,Eco,2296,3,4,3,3,3,5,5,4,2,4,4,5,5,5,0,9.0,neutral or dissatisfied +77834,114780,Female,Loyal Customer,57,Business travel,Business,2275,2,2,4,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +77835,66279,Female,disloyal Customer,36,Business travel,Business,460,3,3,3,2,3,3,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +77836,44497,Female,Loyal Customer,51,Business travel,Eco,411,2,1,1,1,3,2,3,2,2,2,2,3,2,2,0,0.0,satisfied +77837,8335,Male,Loyal Customer,45,Business travel,Business,661,2,2,2,2,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +77838,49499,Male,disloyal Customer,22,Business travel,Eco,109,3,1,3,3,4,3,4,4,3,3,2,3,2,4,50,52.0,neutral or dissatisfied +77839,74990,Female,Loyal Customer,45,Personal Travel,Eco Plus,2475,3,2,3,4,4,4,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +77840,61202,Female,Loyal Customer,29,Business travel,Business,2365,5,5,4,5,4,4,4,4,3,3,4,4,4,4,41,26.0,satisfied +77841,39703,Male,Loyal Customer,37,Business travel,Business,2843,4,4,4,4,5,2,3,4,4,4,4,3,4,1,0,15.0,satisfied +77842,71373,Male,Loyal Customer,44,Business travel,Business,258,4,2,2,2,1,3,3,4,4,4,4,4,4,2,9,17.0,neutral or dissatisfied +77843,23761,Male,Loyal Customer,30,Business travel,Eco Plus,1048,5,5,5,5,5,5,5,5,4,1,2,1,3,5,0,0.0,satisfied +77844,125025,Male,Loyal Customer,24,Business travel,Business,2167,4,4,4,4,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +77845,115752,Male,disloyal Customer,20,Business travel,Eco,446,1,5,1,1,5,1,2,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +77846,55452,Female,Loyal Customer,63,Personal Travel,Eco Plus,2521,2,3,2,3,2,3,3,4,2,4,4,3,2,3,0,13.0,neutral or dissatisfied +77847,69756,Male,Loyal Customer,50,Personal Travel,Eco,1085,2,5,2,2,2,2,3,2,5,4,5,2,3,2,0,0.0,neutral or dissatisfied +77848,121896,Female,Loyal Customer,25,Personal Travel,Eco,366,0,5,0,3,1,0,1,1,3,3,4,4,5,1,1,0.0,satisfied +77849,19333,Female,Loyal Customer,22,Personal Travel,Eco,694,3,4,3,3,2,3,1,2,3,3,5,5,4,2,8,3.0,neutral or dissatisfied +77850,17994,Female,Loyal Customer,28,Business travel,Eco,489,3,4,4,4,3,3,3,3,2,4,2,1,1,3,0,0.0,neutral or dissatisfied +77851,114956,Female,Loyal Customer,46,Business travel,Business,337,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,2.0,satisfied +77852,70477,Male,Loyal Customer,54,Business travel,Business,867,2,2,1,2,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +77853,106213,Female,Loyal Customer,27,Business travel,Business,471,3,3,3,3,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +77854,51373,Male,Loyal Customer,60,Personal Travel,Eco Plus,209,1,1,1,4,1,1,1,1,1,5,4,2,3,1,64,45.0,neutral or dissatisfied +77855,48475,Male,Loyal Customer,54,Business travel,Eco,776,4,1,1,1,4,4,4,4,3,1,3,3,4,4,1,11.0,neutral or dissatisfied +77856,68427,Male,Loyal Customer,11,Personal Travel,Eco,1045,5,4,5,3,4,5,4,4,3,4,5,4,5,4,0,0.0,satisfied +77857,51037,Male,Loyal Customer,22,Personal Travel,Eco,326,2,1,2,2,1,2,1,1,4,1,1,4,3,1,0,0.0,neutral or dissatisfied +77858,37143,Female,Loyal Customer,41,Business travel,Eco,1046,4,3,2,3,4,4,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +77859,74097,Female,Loyal Customer,44,Business travel,Business,3159,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +77860,106365,Female,Loyal Customer,47,Business travel,Business,674,2,2,2,2,4,5,4,5,5,5,5,3,5,4,37,41.0,satisfied +77861,63968,Female,Loyal Customer,34,Business travel,Business,3907,3,3,3,3,5,5,4,4,4,4,4,4,4,5,7,4.0,satisfied +77862,50776,Female,Loyal Customer,57,Personal Travel,Eco,308,4,1,4,3,2,4,3,5,5,4,1,2,5,3,0,6.0,neutral or dissatisfied +77863,90663,Male,Loyal Customer,41,Business travel,Business,240,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +77864,65339,Female,Loyal Customer,57,Business travel,Business,2875,3,3,3,3,4,5,4,5,5,5,5,3,5,4,26,25.0,satisfied +77865,60999,Female,disloyal Customer,25,Business travel,Business,649,3,4,3,3,2,3,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +77866,5594,Male,Loyal Customer,60,Business travel,Business,685,4,4,4,4,2,5,4,4,4,4,4,3,4,4,75,68.0,satisfied +77867,74467,Female,Loyal Customer,50,Business travel,Eco,1126,3,4,5,4,4,3,4,2,2,3,2,4,2,1,0,20.0,neutral or dissatisfied +77868,108559,Male,Loyal Customer,41,Personal Travel,Eco,735,4,4,4,4,4,4,4,4,5,2,4,5,5,4,4,0.0,neutral or dissatisfied +77869,109928,Female,Loyal Customer,35,Personal Travel,Eco,1079,3,3,3,3,3,3,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +77870,76274,Male,disloyal Customer,27,Business travel,Eco,774,3,4,4,3,2,3,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +77871,2191,Female,Loyal Customer,58,Personal Travel,Eco,685,1,4,1,3,2,4,5,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +77872,61027,Female,Loyal Customer,48,Business travel,Eco Plus,3302,1,1,1,1,1,2,2,2,5,4,4,2,2,2,0,0.0,neutral or dissatisfied +77873,114374,Female,disloyal Customer,17,Business travel,Eco Plus,967,1,2,1,4,1,1,1,1,4,1,4,2,3,1,0,44.0,neutral or dissatisfied +77874,107977,Female,Loyal Customer,9,Personal Travel,Eco,825,2,4,2,3,3,2,4,3,3,4,5,3,4,3,16,0.0,neutral or dissatisfied +77875,109344,Female,disloyal Customer,39,Business travel,Business,1136,4,4,4,2,1,4,1,1,5,5,4,4,4,1,0,0.0,satisfied +77876,79210,Female,Loyal Customer,7,Business travel,Business,1990,2,5,5,5,2,2,2,2,1,1,3,2,4,2,0,7.0,neutral or dissatisfied +77877,79194,Female,Loyal Customer,27,Business travel,Business,1990,1,1,1,1,4,4,4,4,4,2,5,3,4,4,2,13.0,satisfied +77878,13585,Male,Loyal Customer,46,Personal Travel,Eco,227,3,4,3,3,1,3,1,1,4,4,3,3,4,1,0,0.0,neutral or dissatisfied +77879,3770,Male,disloyal Customer,45,Business travel,Business,599,5,4,4,4,4,5,4,4,5,5,4,3,4,4,0,13.0,satisfied +77880,55328,Female,Loyal Customer,64,Business travel,Business,717,4,1,1,1,3,3,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +77881,8320,Female,Loyal Customer,25,Personal Travel,Eco Plus,125,1,3,0,2,2,0,2,2,5,1,2,2,3,2,0,0.0,neutral or dissatisfied +77882,96235,Male,Loyal Customer,37,Business travel,Business,460,2,2,2,2,3,3,3,5,5,5,5,5,5,4,3,2.0,satisfied +77883,21119,Male,Loyal Customer,15,Personal Travel,Eco,152,5,4,5,2,1,5,1,1,3,4,5,3,5,1,0,0.0,satisfied +77884,126454,Male,Loyal Customer,47,Business travel,Business,1788,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +77885,65202,Male,Loyal Customer,54,Business travel,Business,224,5,5,3,5,3,5,5,4,4,4,4,4,4,3,16,14.0,satisfied +77886,98153,Male,Loyal Customer,31,Business travel,Business,1588,5,5,3,5,4,4,4,4,4,5,5,4,4,4,3,0.0,satisfied +77887,46528,Female,Loyal Customer,57,Business travel,Eco,125,3,3,4,3,3,2,2,3,3,3,3,3,3,1,88,93.0,satisfied +77888,41903,Male,Loyal Customer,37,Business travel,Eco,129,5,1,1,1,5,4,5,5,4,3,5,3,4,5,0,0.0,satisfied +77889,51624,Male,Loyal Customer,41,Business travel,Business,261,2,2,2,2,3,3,4,5,5,5,5,2,5,2,0,0.0,satisfied +77890,98371,Male,Loyal Customer,66,Personal Travel,Eco,1189,1,5,1,2,2,1,2,2,5,3,5,3,5,2,53,41.0,neutral or dissatisfied +77891,2198,Female,Loyal Customer,69,Personal Travel,Eco,624,1,5,0,3,4,2,2,3,3,0,3,1,3,3,0,0.0,neutral or dissatisfied +77892,54996,Male,disloyal Customer,38,Business travel,Business,1346,3,3,3,1,2,3,2,2,3,2,5,4,4,2,0,19.0,neutral or dissatisfied +77893,39855,Female,disloyal Customer,20,Business travel,Eco,272,1,4,1,3,4,1,3,4,1,2,4,1,3,4,0,3.0,neutral or dissatisfied +77894,50307,Female,Loyal Customer,35,Business travel,Business,3897,1,4,4,4,2,4,3,2,2,3,1,1,2,1,0,0.0,neutral or dissatisfied +77895,4432,Female,disloyal Customer,24,Business travel,Eco,762,1,1,1,3,3,1,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +77896,118839,Female,disloyal Customer,40,Business travel,Business,369,2,2,2,3,1,2,1,1,4,3,5,3,4,1,6,4.0,neutral or dissatisfied +77897,122935,Male,Loyal Customer,45,Business travel,Business,2520,3,3,3,3,2,5,5,4,4,4,4,3,4,3,17,15.0,satisfied +77898,2243,Female,disloyal Customer,43,Business travel,Business,690,3,3,3,4,5,3,5,5,5,3,4,3,4,5,49,45.0,neutral or dissatisfied +77899,119295,Female,disloyal Customer,61,Business travel,Business,214,2,2,2,3,5,2,5,5,3,2,5,3,5,5,93,130.0,neutral or dissatisfied +77900,26302,Male,Loyal Customer,15,Personal Travel,Eco,1199,2,2,2,4,4,2,4,4,4,2,3,2,4,4,13,19.0,neutral or dissatisfied +77901,11119,Male,Loyal Customer,24,Personal Travel,Eco,224,1,3,1,4,3,1,3,3,1,4,4,1,4,3,82,72.0,neutral or dissatisfied +77902,11898,Male,Loyal Customer,35,Business travel,Business,744,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +77903,57833,Male,disloyal Customer,24,Business travel,Eco,1006,4,4,4,3,5,4,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +77904,39289,Male,Loyal Customer,61,Personal Travel,Eco,67,2,5,2,3,5,2,5,5,3,2,4,5,5,5,71,64.0,neutral or dissatisfied +77905,19371,Male,Loyal Customer,68,Personal Travel,Eco,476,2,3,2,2,5,2,5,5,1,5,2,5,2,5,53,35.0,neutral or dissatisfied +77906,97743,Female,disloyal Customer,26,Business travel,Eco,587,2,2,2,3,4,2,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +77907,1539,Female,disloyal Customer,31,Business travel,Business,922,3,3,3,3,3,3,5,3,1,1,3,1,4,3,21,30.0,neutral or dissatisfied +77908,1444,Female,Loyal Customer,54,Business travel,Business,3525,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +77909,29463,Female,disloyal Customer,26,Business travel,Business,421,3,3,3,4,5,3,3,5,2,2,4,1,3,5,0,0.0,neutral or dissatisfied +77910,35400,Female,disloyal Customer,19,Business travel,Eco,1028,4,4,4,4,1,4,1,1,2,3,3,4,4,1,19,4.0,neutral or dissatisfied +77911,59928,Male,Loyal Customer,41,Business travel,Business,2138,5,3,5,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +77912,106731,Female,disloyal Customer,25,Business travel,Business,945,1,5,1,2,4,1,4,4,5,3,4,3,5,4,0,3.0,neutral or dissatisfied +77913,41106,Female,disloyal Customer,36,Business travel,Eco,216,4,4,4,4,2,4,5,2,2,3,4,1,4,2,52,85.0,neutral or dissatisfied +77914,122283,Male,Loyal Customer,34,Personal Travel,Eco,546,1,2,1,4,2,1,2,2,2,3,4,4,4,2,0,5.0,neutral or dissatisfied +77915,50970,Female,Loyal Customer,26,Personal Travel,Eco,250,3,4,3,3,3,3,3,3,2,4,3,5,3,3,128,126.0,neutral or dissatisfied +77916,37538,Female,Loyal Customer,20,Business travel,Business,1757,4,5,2,2,4,4,4,4,1,2,4,4,4,4,0,0.0,neutral or dissatisfied +77917,93865,Male,Loyal Customer,43,Business travel,Business,2408,1,1,1,1,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +77918,126675,Male,Loyal Customer,35,Personal Travel,Eco,2276,5,5,5,2,1,5,1,1,3,4,3,4,5,1,0,0.0,satisfied +77919,97963,Male,Loyal Customer,38,Personal Travel,Eco,655,3,0,3,1,4,3,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +77920,95359,Male,Loyal Customer,25,Personal Travel,Eco,273,3,3,3,1,5,3,5,5,5,2,4,1,5,5,0,0.0,neutral or dissatisfied +77921,120535,Female,Loyal Customer,35,Business travel,Business,2176,3,3,4,3,2,5,5,4,4,4,4,5,4,3,0,16.0,satisfied +77922,83352,Male,Loyal Customer,54,Personal Travel,Business,1124,3,5,3,3,3,4,4,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +77923,92792,Female,disloyal Customer,26,Business travel,Eco,1109,1,1,1,4,2,1,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +77924,69693,Male,disloyal Customer,24,Business travel,Eco,1372,4,3,3,2,5,4,5,5,4,5,5,5,4,5,0,0.0,satisfied +77925,114150,Female,Loyal Customer,47,Business travel,Business,967,1,1,1,1,3,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +77926,17941,Male,Loyal Customer,16,Personal Travel,Eco,214,2,2,2,3,4,2,4,4,1,3,4,2,4,4,15,3.0,neutral or dissatisfied +77927,110378,Male,disloyal Customer,35,Business travel,Eco,787,1,1,1,4,1,1,3,1,4,1,4,1,4,1,9,5.0,neutral or dissatisfied +77928,43754,Male,Loyal Customer,45,Business travel,Eco,386,5,1,1,1,5,5,5,5,5,2,5,4,5,5,45,46.0,satisfied +77929,92544,Male,Loyal Customer,32,Personal Travel,Eco,2092,3,4,3,5,4,3,5,4,3,4,4,5,4,4,8,0.0,neutral or dissatisfied +77930,95256,Female,Loyal Customer,30,Personal Travel,Eco,293,1,5,1,4,5,1,1,5,3,5,4,5,5,5,28,9.0,neutral or dissatisfied +77931,45275,Female,Loyal Customer,47,Business travel,Business,188,1,1,1,1,5,1,3,4,4,4,5,1,4,1,0,0.0,satisfied +77932,71982,Female,Loyal Customer,44,Business travel,Eco,1037,4,1,1,1,1,1,4,4,4,4,4,5,4,3,94,76.0,satisfied +77933,65720,Male,Loyal Customer,36,Business travel,Business,3645,1,0,0,2,1,2,2,5,5,0,5,2,5,4,0,0.0,neutral or dissatisfied +77934,26556,Female,disloyal Customer,27,Business travel,Business,515,3,3,3,2,2,3,2,2,5,3,4,3,5,2,68,61.0,neutral or dissatisfied +77935,16670,Female,Loyal Customer,25,Personal Travel,Eco,488,3,2,3,4,5,3,5,5,3,5,4,2,3,5,5,0.0,neutral or dissatisfied +77936,9039,Male,disloyal Customer,47,Business travel,Business,108,2,2,2,4,3,2,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +77937,2564,Male,Loyal Customer,55,Business travel,Business,3789,3,2,2,2,4,4,4,3,3,3,3,3,3,2,6,9.0,neutral or dissatisfied +77938,20208,Female,Loyal Customer,19,Personal Travel,Business,179,3,3,3,5,3,3,3,3,3,4,2,2,3,3,0,0.0,neutral or dissatisfied +77939,25678,Female,Loyal Customer,67,Personal Travel,Eco,761,1,5,2,1,2,4,4,1,1,2,2,3,1,3,8,7.0,neutral or dissatisfied +77940,118107,Male,Loyal Customer,14,Personal Travel,Eco,1999,5,4,5,2,2,4,2,2,1,2,5,4,2,2,0,0.0,satisfied +77941,7847,Female,Loyal Customer,52,Business travel,Business,3617,4,4,4,4,5,5,5,5,5,5,5,4,5,3,39,38.0,satisfied +77942,126659,Male,Loyal Customer,33,Personal Travel,Eco,602,4,3,4,3,4,4,4,4,3,5,4,2,4,4,2,0.0,neutral or dissatisfied +77943,107192,Male,Loyal Customer,47,Business travel,Eco,402,2,4,4,4,1,2,1,1,2,1,4,4,4,1,5,10.0,neutral or dissatisfied +77944,82990,Female,Loyal Customer,64,Business travel,Business,1650,4,4,4,4,4,5,4,3,3,3,3,3,3,4,24,2.0,satisfied +77945,32865,Female,Loyal Customer,30,Personal Travel,Eco,216,4,2,4,4,4,4,4,4,1,3,4,1,4,4,0,0.0,satisfied +77946,114445,Male,Loyal Customer,51,Business travel,Business,3275,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +77947,70761,Male,Loyal Customer,51,Business travel,Business,328,3,5,3,3,5,5,5,5,5,5,5,4,5,4,21,16.0,satisfied +77948,126580,Male,Loyal Customer,55,Business travel,Business,1558,2,2,2,2,4,5,4,4,4,4,4,4,4,4,11,6.0,satisfied +77949,107128,Male,Loyal Customer,26,Personal Travel,Eco,842,4,3,5,4,3,5,3,3,1,2,4,1,4,3,3,0.0,neutral or dissatisfied +77950,54947,Female,Loyal Customer,53,Personal Travel,Business,1504,3,4,3,3,1,5,1,1,1,3,1,5,1,3,22,60.0,neutral or dissatisfied +77951,57090,Female,Loyal Customer,45,Business travel,Business,1222,1,1,1,1,3,5,4,5,5,5,5,4,5,4,50,29.0,satisfied +77952,12324,Female,Loyal Customer,48,Business travel,Business,1771,3,3,3,3,4,4,1,4,4,4,4,5,4,5,0,0.0,satisfied +77953,127944,Female,Loyal Customer,28,Personal Travel,Eco Plus,2300,1,3,1,4,5,1,5,5,3,1,3,2,4,5,22,2.0,neutral or dissatisfied +77954,53439,Female,Loyal Customer,27,Business travel,Business,2419,2,3,2,2,5,5,5,3,5,3,3,5,1,5,0,0.0,satisfied +77955,85629,Female,Loyal Customer,11,Personal Travel,Eco,259,3,1,3,3,1,3,1,1,2,5,2,4,3,1,22,20.0,neutral or dissatisfied +77956,8138,Male,disloyal Customer,36,Business travel,Business,335,3,3,3,2,2,3,2,2,5,5,5,3,5,2,0,1.0,neutral or dissatisfied +77957,58007,Female,Loyal Customer,50,Business travel,Business,2661,4,4,4,4,5,4,5,3,3,3,3,3,3,5,14,10.0,satisfied +77958,93545,Male,disloyal Customer,24,Business travel,Business,585,0,4,0,3,2,0,2,2,3,3,5,5,4,2,0,0.0,satisfied +77959,98228,Female,Loyal Customer,43,Business travel,Business,3777,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,14.0,satisfied +77960,110100,Male,Loyal Customer,32,Business travel,Business,3422,3,3,3,3,4,4,4,4,4,5,5,4,5,4,14,5.0,satisfied +77961,71384,Female,Loyal Customer,10,Personal Travel,Eco,258,1,4,1,5,4,1,4,4,4,5,1,3,2,4,0,0.0,neutral or dissatisfied +77962,119171,Male,Loyal Customer,34,Business travel,Business,3139,4,4,4,4,5,4,5,5,5,5,5,5,5,3,72,82.0,satisfied +77963,47878,Male,Loyal Customer,24,Business travel,Eco,329,1,2,2,2,1,1,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +77964,53021,Male,Loyal Customer,66,Business travel,Business,3088,3,1,3,1,3,3,4,3,3,3,3,3,3,2,42,33.0,neutral or dissatisfied +77965,103334,Female,Loyal Customer,30,Personal Travel,Eco,1139,4,5,4,1,5,4,5,5,3,4,4,3,4,5,12,14.0,neutral or dissatisfied +77966,10012,Male,Loyal Customer,63,Business travel,Eco Plus,457,2,3,3,3,2,2,2,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +77967,19150,Male,Loyal Customer,70,Business travel,Business,3687,0,0,0,4,5,1,2,4,4,4,4,1,4,5,26,16.0,satisfied +77968,111953,Male,Loyal Customer,50,Business travel,Business,770,5,5,5,5,4,4,5,2,2,2,2,3,2,4,16,3.0,satisfied +77969,62974,Female,Loyal Customer,56,Business travel,Eco,909,3,5,5,5,1,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +77970,122572,Male,Loyal Customer,53,Business travel,Business,728,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +77971,108450,Female,Loyal Customer,49,Business travel,Business,1444,3,3,3,3,5,5,4,4,4,4,4,4,4,3,11,0.0,satisfied +77972,42408,Male,Loyal Customer,29,Business travel,Eco Plus,550,3,4,5,4,3,3,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +77973,117466,Female,Loyal Customer,47,Business travel,Business,2717,2,2,2,2,5,4,4,4,4,4,4,4,4,3,16,18.0,satisfied +77974,67333,Male,Loyal Customer,39,Business travel,Business,1471,4,2,4,4,5,4,5,4,4,4,4,3,4,4,22,36.0,satisfied +77975,104251,Female,Loyal Customer,30,Personal Travel,Eco,1276,3,4,2,4,5,2,5,5,2,1,3,2,4,5,2,0.0,neutral or dissatisfied +77976,71822,Male,Loyal Customer,51,Business travel,Business,1744,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +77977,13177,Male,disloyal Customer,26,Business travel,Eco,542,1,3,1,3,2,1,2,2,3,3,3,3,5,2,0,0.0,neutral or dissatisfied +77978,115145,Male,Loyal Customer,53,Business travel,Business,3274,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +77979,9575,Male,Loyal Customer,58,Business travel,Business,228,2,1,4,1,2,2,2,2,2,4,4,2,4,2,167,194.0,neutral or dissatisfied +77980,86457,Female,disloyal Customer,18,Business travel,Eco,762,5,5,5,1,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +77981,5987,Female,Loyal Customer,51,Business travel,Business,3902,3,3,3,3,2,5,4,5,5,5,5,4,5,4,13,0.0,satisfied +77982,106296,Male,Loyal Customer,39,Business travel,Business,998,5,5,5,5,2,5,5,4,4,5,4,4,4,5,0,14.0,satisfied +77983,959,Female,Loyal Customer,74,Business travel,Business,102,4,4,4,4,5,4,4,4,4,4,4,2,4,2,31,34.0,neutral or dissatisfied +77984,69280,Female,Loyal Customer,64,Personal Travel,Eco,733,2,1,2,3,2,1,1,3,3,1,3,1,2,1,132,137.0,neutral or dissatisfied +77985,79020,Female,Loyal Customer,51,Business travel,Business,356,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +77986,61203,Female,Loyal Customer,28,Business travel,Business,3665,1,1,1,1,4,4,4,4,3,4,4,4,4,4,44,77.0,satisfied +77987,118700,Female,Loyal Customer,43,Personal Travel,Eco,451,5,4,5,2,2,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +77988,15788,Female,disloyal Customer,33,Business travel,Eco Plus,198,4,4,4,4,4,1,4,4,4,4,3,4,3,4,165,165.0,neutral or dissatisfied +77989,30356,Male,Loyal Customer,48,Business travel,Eco,641,4,1,2,1,4,4,4,4,2,5,2,5,4,4,0,0.0,satisfied +77990,68252,Female,Loyal Customer,16,Personal Travel,Eco,432,2,1,2,4,1,2,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +77991,74306,Male,disloyal Customer,15,Business travel,Eco,1205,4,3,3,4,5,3,5,5,4,5,4,4,5,5,0,2.0,satisfied +77992,7427,Male,Loyal Customer,9,Business travel,Business,3418,2,2,2,2,2,2,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +77993,109275,Male,Loyal Customer,47,Business travel,Business,3962,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +77994,73576,Male,Loyal Customer,52,Business travel,Business,3134,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +77995,95445,Male,disloyal Customer,27,Business travel,Business,148,5,5,5,1,3,5,3,3,5,3,5,3,4,3,0,0.0,satisfied +77996,123974,Male,Loyal Customer,60,Business travel,Business,3799,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +77997,128496,Male,Loyal Customer,50,Personal Travel,Eco,304,2,3,2,3,2,2,2,2,2,4,3,3,3,2,14,7.0,neutral or dissatisfied +77998,128398,Male,disloyal Customer,26,Business travel,Eco,651,3,3,3,3,2,3,2,2,4,1,2,4,3,2,54,43.0,neutral or dissatisfied +77999,75515,Female,Loyal Customer,37,Business travel,Business,748,5,5,5,5,4,5,5,5,5,5,5,3,5,4,9,3.0,satisfied +78000,85221,Female,Loyal Customer,55,Business travel,Business,3553,2,4,4,4,5,2,3,2,2,2,2,2,2,4,13,0.0,neutral or dissatisfied +78001,98063,Female,Loyal Customer,22,Business travel,Business,1449,5,5,5,5,5,5,5,5,3,4,5,3,5,5,6,0.0,satisfied +78002,37195,Female,disloyal Customer,50,Business travel,Eco Plus,1046,1,1,1,4,2,1,2,2,4,1,3,1,4,2,10,8.0,neutral or dissatisfied +78003,114919,Female,Loyal Customer,43,Business travel,Business,2303,4,4,4,4,5,5,5,2,2,2,2,3,2,3,4,4.0,satisfied +78004,55489,Female,disloyal Customer,25,Business travel,Business,1739,3,0,3,4,5,3,1,5,5,5,3,5,5,5,57,54.0,neutral or dissatisfied +78005,111313,Male,disloyal Customer,21,Business travel,Eco,283,3,0,3,1,3,3,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +78006,50849,Female,Loyal Customer,8,Personal Travel,Eco,337,3,4,3,3,4,3,2,4,5,5,5,3,5,4,19,32.0,neutral or dissatisfied +78007,111087,Male,Loyal Customer,64,Personal Travel,Eco,268,1,3,1,3,4,1,4,4,1,1,4,1,4,4,0,22.0,neutral or dissatisfied +78008,62233,Female,Loyal Customer,39,Personal Travel,Eco,2454,2,4,2,3,1,2,1,1,4,3,3,3,4,1,0,0.0,neutral or dissatisfied +78009,29220,Female,disloyal Customer,37,Business travel,Business,569,2,2,2,1,2,2,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +78010,109840,Female,Loyal Customer,47,Business travel,Business,3270,3,3,3,3,5,5,5,3,5,5,5,5,3,5,188,180.0,satisfied +78011,29718,Female,Loyal Customer,32,Business travel,Business,2777,1,1,1,1,5,5,5,4,3,5,5,5,3,5,0,0.0,satisfied +78012,69949,Female,Loyal Customer,75,Business travel,Business,674,3,3,3,3,3,5,3,5,5,5,5,5,5,3,0,0.0,satisfied +78013,125118,Male,Loyal Customer,22,Personal Travel,Eco,361,1,2,5,2,3,5,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +78014,52828,Female,disloyal Customer,55,Business travel,Eco,1115,4,4,4,5,2,4,2,2,5,1,5,4,1,2,0,0.0,neutral or dissatisfied +78015,59698,Female,Loyal Customer,26,Personal Travel,Eco,854,3,4,3,4,2,3,2,2,4,2,5,5,5,2,11,19.0,neutral or dissatisfied +78016,118516,Female,Loyal Customer,42,Business travel,Business,338,5,5,5,5,4,5,5,4,4,4,4,5,4,4,4,0.0,satisfied +78017,110968,Female,Loyal Customer,35,Personal Travel,Business,197,2,1,2,2,5,2,2,5,5,2,5,2,5,3,25,39.0,neutral or dissatisfied +78018,112553,Male,disloyal Customer,29,Business travel,Eco Plus,853,2,2,2,3,5,2,5,5,4,4,3,2,3,5,36,40.0,neutral or dissatisfied +78019,112882,Female,Loyal Customer,54,Business travel,Business,1476,1,5,1,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +78020,42155,Female,Loyal Customer,26,Personal Travel,Business,838,1,4,1,3,2,1,5,2,4,2,3,1,5,2,0,0.0,neutral or dissatisfied +78021,128438,Female,disloyal Customer,26,Business travel,Eco,221,3,0,3,2,5,3,5,5,2,4,3,2,1,5,0,0.0,neutral or dissatisfied +78022,29478,Male,Loyal Customer,45,Business travel,Business,1107,1,1,3,1,4,4,1,2,2,2,2,4,2,5,0,0.0,satisfied +78023,52151,Male,Loyal Customer,61,Business travel,Business,451,4,4,4,4,2,4,4,5,5,5,5,5,5,4,0,3.0,satisfied +78024,46015,Female,Loyal Customer,57,Business travel,Business,2237,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +78025,104213,Female,Loyal Customer,22,Business travel,Business,680,3,3,3,3,5,5,5,5,5,4,4,3,4,5,4,70.0,satisfied +78026,87277,Male,disloyal Customer,33,Business travel,Eco,577,3,2,3,4,2,3,1,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +78027,34397,Female,Loyal Customer,52,Business travel,Eco,612,3,3,3,3,5,3,3,3,3,3,3,1,3,1,29,43.0,neutral or dissatisfied +78028,8120,Male,Loyal Customer,29,Business travel,Business,530,1,1,1,1,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +78029,36474,Male,disloyal Customer,25,Business travel,Eco,1211,3,3,3,1,2,3,4,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +78030,52804,Male,disloyal Customer,31,Business travel,Eco,2021,3,3,3,4,4,3,4,4,3,5,4,5,4,4,27,31.0,neutral or dissatisfied +78031,100703,Male,Loyal Customer,58,Personal Travel,Eco,628,3,5,3,3,3,3,4,3,4,3,5,5,4,3,41,36.0,neutral or dissatisfied +78032,6887,Male,Loyal Customer,45,Business travel,Business,265,5,5,5,5,5,5,5,5,4,4,5,5,4,5,252,275.0,satisfied +78033,35038,Male,Loyal Customer,43,Business travel,Business,2397,4,4,4,4,4,5,4,4,4,4,4,3,4,3,59,49.0,satisfied +78034,235,Female,Loyal Customer,16,Personal Travel,Eco Plus,213,5,2,5,3,2,5,2,2,5,4,4,4,5,2,0,0.0,satisfied +78035,109160,Female,Loyal Customer,36,Business travel,Business,2041,4,4,4,4,2,4,4,4,4,4,4,5,4,4,6,6.0,satisfied +78036,90242,Male,Loyal Customer,44,Business travel,Business,3431,2,3,2,2,4,4,5,3,3,3,3,3,3,4,15,0.0,satisfied +78037,50232,Female,Loyal Customer,45,Business travel,Eco,89,4,1,5,1,2,4,4,4,4,4,4,2,4,2,0,0.0,satisfied +78038,87028,Male,Loyal Customer,31,Personal Travel,Business,594,2,3,2,2,2,2,2,2,2,1,4,2,3,2,185,186.0,neutral or dissatisfied +78039,64878,Male,Loyal Customer,49,Business travel,Business,190,5,5,5,5,4,5,5,4,4,4,5,5,4,4,0,0.0,satisfied +78040,16160,Male,Loyal Customer,49,Business travel,Business,277,3,3,3,3,2,3,2,5,5,5,5,3,5,2,108,107.0,satisfied +78041,33761,Female,Loyal Customer,34,Personal Travel,Eco,266,1,0,1,1,5,1,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +78042,26487,Female,Loyal Customer,64,Business travel,Business,3732,3,1,1,1,3,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +78043,20683,Male,Loyal Customer,62,Personal Travel,Eco,522,3,5,3,4,2,3,2,2,3,4,2,2,1,2,16,18.0,neutral or dissatisfied +78044,13089,Male,Loyal Customer,49,Business travel,Business,2100,1,1,1,1,3,2,1,4,4,4,4,3,4,2,4,0.0,satisfied +78045,1473,Female,Loyal Customer,54,Personal Travel,Eco,772,1,5,1,4,4,1,1,1,1,1,1,4,1,5,24,19.0,neutral or dissatisfied +78046,99540,Female,Loyal Customer,36,Business travel,Business,829,3,5,5,5,2,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +78047,68858,Male,Loyal Customer,36,Business travel,Business,936,1,1,3,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +78048,90839,Male,Loyal Customer,66,Business travel,Business,3871,4,2,2,2,5,3,2,4,4,4,4,3,4,2,2,0.0,neutral or dissatisfied +78049,69500,Female,Loyal Customer,50,Personal Travel,Eco Plus,1096,3,4,3,3,5,3,4,4,4,3,4,4,4,3,0,12.0,neutral or dissatisfied +78050,29098,Male,Loyal Customer,35,Personal Travel,Eco,672,2,3,2,2,5,2,5,5,1,1,4,4,1,5,0,0.0,neutral or dissatisfied +78051,91106,Female,Loyal Customer,16,Personal Travel,Eco,545,3,5,3,1,5,3,5,5,3,4,1,3,1,5,0,0.0,neutral or dissatisfied +78052,120046,Male,Loyal Customer,47,Personal Travel,Eco,168,4,4,0,3,2,0,2,2,4,3,4,4,5,2,0,8.0,neutral or dissatisfied +78053,75320,Female,disloyal Customer,41,Business travel,Eco,1497,3,3,3,3,3,5,5,3,2,3,3,5,1,5,0,6.0,neutral or dissatisfied +78054,5741,Female,disloyal Customer,27,Business travel,Business,859,4,4,4,2,4,4,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +78055,62019,Male,Loyal Customer,38,Business travel,Business,2586,4,4,4,4,4,3,4,4,4,4,4,5,4,4,5,9.0,satisfied +78056,12829,Female,Loyal Customer,50,Business travel,Eco,528,4,4,4,4,3,3,5,4,4,4,4,1,4,2,0,0.0,satisfied +78057,33018,Male,Loyal Customer,38,Personal Travel,Eco,163,2,3,2,3,1,2,1,1,2,4,4,4,3,1,0,1.0,neutral or dissatisfied +78058,126320,Male,Loyal Customer,22,Personal Travel,Eco,507,3,3,2,3,2,2,2,2,2,5,3,4,3,2,0,4.0,neutral or dissatisfied +78059,45234,Female,disloyal Customer,47,Business travel,Eco,613,4,0,4,3,1,4,5,1,3,5,2,2,4,1,0,0.0,neutral or dissatisfied +78060,7227,Male,Loyal Customer,40,Business travel,Business,139,0,5,0,2,2,5,4,2,2,2,2,2,2,2,0,0.0,satisfied +78061,54374,Male,Loyal Customer,55,Personal Travel,Business,305,4,5,4,3,4,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +78062,72212,Male,disloyal Customer,16,Business travel,Business,919,5,0,5,5,5,5,5,5,4,3,4,3,4,5,7,7.0,satisfied +78063,117027,Male,Loyal Customer,33,Business travel,Business,1716,4,5,2,5,4,4,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +78064,42426,Male,Loyal Customer,47,Personal Travel,Eco Plus,412,2,4,2,3,1,2,1,1,3,2,4,5,5,1,68,48.0,neutral or dissatisfied +78065,101957,Female,Loyal Customer,77,Business travel,Eco,628,3,5,5,5,4,4,3,3,3,3,3,3,3,3,24,43.0,neutral or dissatisfied +78066,93015,Male,disloyal Customer,36,Business travel,Eco,707,3,3,3,4,3,3,3,3,4,4,4,3,3,3,43,34.0,neutral or dissatisfied +78067,109440,Female,Loyal Customer,34,Business travel,Business,2820,4,4,4,4,2,4,5,5,5,5,5,4,5,5,65,105.0,satisfied +78068,21397,Male,Loyal Customer,33,Business travel,Eco,433,5,4,4,4,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +78069,44855,Male,Loyal Customer,22,Business travel,Eco,585,0,3,0,2,5,0,5,5,3,2,2,3,3,5,107,103.0,satisfied +78070,114309,Female,Loyal Customer,10,Personal Travel,Eco,957,3,5,3,3,3,3,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +78071,45201,Female,disloyal Customer,42,Business travel,Business,911,1,1,1,2,3,1,1,3,3,2,2,1,3,3,0,14.0,neutral or dissatisfied +78072,83350,Male,Loyal Customer,52,Business travel,Business,3850,5,5,5,5,2,5,5,2,2,2,2,4,2,3,7,0.0,satisfied +78073,25217,Male,Loyal Customer,56,Business travel,Eco,925,5,4,4,4,5,5,5,5,1,1,4,1,2,5,18,11.0,satisfied +78074,71630,Female,Loyal Customer,33,Business travel,Business,3254,1,5,5,5,3,1,2,1,1,1,1,3,1,1,36,35.0,neutral or dissatisfied +78075,14949,Male,Loyal Customer,38,Business travel,Eco,554,2,5,5,5,2,2,2,2,3,5,3,4,4,2,0,1.0,neutral or dissatisfied +78076,56404,Female,disloyal Customer,35,Business travel,Business,719,2,2,2,4,1,2,1,1,3,2,4,3,5,1,1,7.0,neutral or dissatisfied +78077,102682,Female,disloyal Customer,27,Business travel,Eco,365,1,0,1,4,5,1,5,5,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +78078,30077,Male,Loyal Customer,41,Personal Travel,Eco,253,2,3,2,4,1,2,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +78079,50873,Female,Loyal Customer,63,Personal Travel,Eco,109,2,5,0,3,3,4,3,5,5,0,5,3,5,5,0,0.0,neutral or dissatisfied +78080,14763,Male,Loyal Customer,24,Personal Travel,Eco,533,2,5,2,2,2,5,4,5,4,5,5,4,4,4,189,183.0,neutral or dissatisfied +78081,9508,Male,Loyal Customer,15,Personal Travel,Eco,322,2,4,2,1,3,2,3,3,5,2,3,5,1,3,3,0.0,neutral or dissatisfied +78082,85850,Female,Loyal Customer,44,Business travel,Business,3452,4,4,4,4,3,5,5,4,4,5,4,3,4,3,12,0.0,satisfied +78083,111005,Female,Loyal Customer,43,Business travel,Business,197,0,5,1,4,2,4,5,2,2,2,2,3,2,3,1,0.0,satisfied +78084,117753,Female,Loyal Customer,59,Personal Travel,Business,1670,4,5,4,1,3,1,3,1,1,4,1,1,1,4,3,0.0,neutral or dissatisfied +78085,121404,Female,Loyal Customer,34,Business travel,Business,2190,0,0,0,1,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +78086,84218,Female,disloyal Customer,37,Business travel,Business,432,3,3,3,5,4,3,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +78087,93596,Male,disloyal Customer,38,Business travel,Business,577,4,4,4,2,1,4,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +78088,65353,Female,disloyal Customer,50,Business travel,Eco,631,3,4,4,3,5,4,1,5,3,4,4,4,3,5,10,0.0,neutral or dissatisfied +78089,18312,Male,Loyal Customer,34,Business travel,Business,1519,2,2,2,2,3,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +78090,9339,Male,Loyal Customer,47,Business travel,Business,1894,5,3,5,5,5,4,4,5,5,5,5,5,5,3,24,12.0,satisfied +78091,65191,Male,Loyal Customer,13,Personal Travel,Eco,551,2,4,2,3,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +78092,73728,Male,Loyal Customer,49,Personal Travel,Eco,192,3,4,3,2,2,3,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +78093,106807,Female,Loyal Customer,68,Personal Travel,Eco,977,3,5,3,3,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +78094,100108,Female,Loyal Customer,57,Business travel,Business,2092,2,2,2,2,4,5,4,4,4,4,4,3,4,5,13,8.0,satisfied +78095,123629,Male,Loyal Customer,46,Business travel,Business,214,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +78096,15148,Male,Loyal Customer,67,Personal Travel,Eco,912,4,2,4,4,4,2,2,1,1,3,4,2,4,2,152,175.0,satisfied +78097,27425,Female,disloyal Customer,24,Business travel,Eco,1050,1,1,1,3,5,1,5,5,1,2,1,2,2,5,13,3.0,neutral or dissatisfied +78098,37553,Male,Loyal Customer,39,Business travel,Business,2180,2,2,2,2,2,5,4,5,5,5,5,2,5,1,0,0.0,satisfied +78099,98559,Female,disloyal Customer,45,Business travel,Business,993,5,5,5,1,4,5,4,4,4,2,5,5,5,4,0,0.0,satisfied +78100,16115,Female,Loyal Customer,45,Business travel,Business,1522,4,4,4,4,3,2,3,5,5,5,5,1,5,3,110,121.0,satisfied +78101,82582,Female,Loyal Customer,44,Business travel,Business,408,3,1,3,3,4,4,5,4,4,4,4,4,4,4,0,3.0,satisfied +78102,54786,Male,Loyal Customer,27,Business travel,Business,862,3,4,3,3,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +78103,117066,Female,disloyal Customer,21,Business travel,Business,647,5,5,5,3,2,5,2,2,4,4,5,4,5,2,3,2.0,satisfied +78104,46800,Male,Loyal Customer,34,Personal Travel,Business,916,1,4,1,3,4,5,4,3,3,1,3,4,3,5,22,0.0,neutral or dissatisfied +78105,29526,Male,disloyal Customer,22,Business travel,Eco,609,3,4,3,4,4,3,4,4,1,1,3,2,4,4,0,9.0,neutral or dissatisfied +78106,15124,Male,Loyal Customer,46,Business travel,Eco,912,3,2,2,2,4,3,4,4,2,3,4,4,3,4,46,56.0,neutral or dissatisfied +78107,71767,Female,Loyal Customer,37,Business travel,Business,1846,5,5,5,5,2,5,5,4,4,4,4,4,4,4,43,36.0,satisfied +78108,123102,Male,Loyal Customer,44,Business travel,Business,1750,1,1,4,1,3,5,5,5,5,5,5,4,5,3,9,3.0,satisfied +78109,22840,Male,Loyal Customer,61,Business travel,Eco,134,5,2,2,2,5,5,5,5,1,3,2,2,4,5,0,0.0,satisfied +78110,101075,Male,Loyal Customer,50,Business travel,Business,1069,3,3,3,3,3,5,4,5,5,4,5,3,5,4,111,107.0,satisfied +78111,1432,Female,Loyal Customer,37,Business travel,Business,772,2,3,3,3,4,3,3,2,2,1,2,4,2,2,0,0.0,neutral or dissatisfied +78112,58135,Male,Loyal Customer,56,Personal Travel,Eco Plus,612,2,5,2,1,1,2,1,1,4,5,4,2,5,1,35,29.0,neutral or dissatisfied +78113,101489,Female,Loyal Customer,53,Business travel,Business,2204,1,4,4,4,2,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +78114,115306,Male,disloyal Customer,34,Business travel,Business,342,3,3,3,2,5,3,5,5,5,3,4,5,5,5,2,0.0,neutral or dissatisfied +78115,67164,Male,Loyal Customer,8,Personal Travel,Eco,1102,4,4,5,2,5,5,5,5,2,1,2,5,3,5,0,3.0,satisfied +78116,108151,Female,Loyal Customer,38,Personal Travel,Eco,1105,2,0,2,3,2,1,2,4,4,4,4,2,3,2,140,,neutral or dissatisfied +78117,67507,Male,disloyal Customer,39,Business travel,Business,1235,5,5,5,4,5,5,5,5,5,5,5,5,5,5,0,20.0,satisfied +78118,76791,Male,disloyal Customer,27,Business travel,Eco,689,3,2,2,3,2,2,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +78119,109951,Female,Loyal Customer,35,Personal Travel,Eco,1011,3,4,3,4,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +78120,89181,Male,Loyal Customer,55,Personal Travel,Eco,2139,1,3,1,3,1,1,1,1,2,5,3,4,4,1,11,0.0,neutral or dissatisfied +78121,99613,Female,Loyal Customer,56,Personal Travel,Eco Plus,930,2,4,2,3,2,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +78122,16138,Male,Loyal Customer,32,Personal Travel,Eco Plus,799,2,5,2,1,2,2,2,2,2,1,1,1,5,2,27,16.0,neutral or dissatisfied +78123,123175,Male,Loyal Customer,57,Business travel,Business,328,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +78124,58016,Male,Loyal Customer,46,Business travel,Business,1721,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +78125,44849,Female,Loyal Customer,56,Business travel,Business,413,3,3,3,3,1,4,3,3,3,3,3,2,3,1,0,1.0,neutral or dissatisfied +78126,77662,Female,Loyal Customer,23,Business travel,Eco,689,3,1,1,1,3,3,2,3,1,3,4,1,3,3,62,100.0,neutral or dissatisfied +78127,119056,Female,Loyal Customer,10,Personal Travel,Eco,2279,2,3,2,4,4,2,4,4,2,1,2,3,4,4,4,1.0,neutral or dissatisfied +78128,116726,Male,Loyal Customer,37,Business travel,Eco Plus,296,4,4,3,4,4,4,4,4,3,3,3,4,2,4,0,0.0,satisfied +78129,35296,Male,disloyal Customer,23,Business travel,Eco,1056,2,2,2,3,5,2,5,5,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +78130,126285,Female,Loyal Customer,65,Personal Travel,Eco,468,1,2,1,3,1,4,3,2,2,1,2,1,2,2,38,35.0,neutral or dissatisfied +78131,104520,Male,Loyal Customer,45,Business travel,Business,1256,4,4,3,4,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +78132,82325,Female,Loyal Customer,20,Business travel,Business,2759,5,5,1,5,4,4,4,4,5,2,4,3,4,4,0,0.0,satisfied +78133,65878,Female,Loyal Customer,45,Business travel,Business,1389,3,3,3,3,5,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +78134,43206,Female,Loyal Customer,60,Personal Travel,Eco,466,4,5,4,4,3,5,5,4,4,4,4,5,4,5,9,0.0,satisfied +78135,5396,Male,Loyal Customer,45,Personal Travel,Eco,733,4,3,4,3,2,4,2,2,4,4,2,2,2,2,25,40.0,neutral or dissatisfied +78136,76531,Male,Loyal Customer,51,Business travel,Business,3135,1,1,1,1,4,4,5,4,4,4,4,4,4,3,28,65.0,satisfied +78137,41172,Male,disloyal Customer,39,Business travel,Business,216,3,3,3,5,1,3,1,1,4,5,2,5,2,1,0,0.0,neutral or dissatisfied +78138,34736,Male,Loyal Customer,35,Business travel,Business,209,3,3,3,3,5,3,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +78139,84486,Male,disloyal Customer,21,Business travel,Eco,988,4,4,4,4,4,1,1,3,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +78140,33850,Male,Loyal Customer,72,Business travel,Eco,1562,4,3,2,3,4,4,4,4,3,2,4,1,4,4,0,0.0,neutral or dissatisfied +78141,83984,Female,Loyal Customer,48,Business travel,Business,373,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +78142,106732,Female,Loyal Customer,49,Business travel,Business,829,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +78143,28465,Female,Loyal Customer,11,Business travel,Eco Plus,2588,2,1,1,1,2,2,2,1,1,3,3,2,4,2,0,0.0,neutral or dissatisfied +78144,40532,Male,Loyal Customer,70,Personal Travel,Business,216,4,4,4,3,4,5,5,4,4,4,4,3,4,5,7,1.0,neutral or dissatisfied +78145,108217,Female,disloyal Customer,36,Business travel,Eco,377,3,3,3,3,3,3,3,3,4,2,3,1,3,3,28,7.0,neutral or dissatisfied +78146,14526,Male,Loyal Customer,30,Business travel,Business,310,3,3,3,3,3,3,3,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +78147,58451,Male,Loyal Customer,24,Personal Travel,Eco,723,4,3,4,4,2,4,2,2,1,5,3,4,3,2,1,2.0,neutral or dissatisfied +78148,13391,Female,Loyal Customer,11,Business travel,Eco,505,4,1,5,5,4,4,3,4,5,5,3,4,1,4,0,0.0,satisfied +78149,23144,Male,Loyal Customer,60,Business travel,Business,3838,4,4,4,4,1,1,4,4,4,4,4,3,4,5,0,5.0,satisfied +78150,22879,Male,Loyal Customer,67,Personal Travel,Eco,134,2,2,2,3,5,2,5,5,1,5,4,3,3,5,38,26.0,neutral or dissatisfied +78151,67864,Male,Loyal Customer,8,Personal Travel,Eco,1438,3,5,3,3,5,3,5,5,5,5,5,5,5,5,5,0.0,neutral or dissatisfied +78152,101375,Male,Loyal Customer,22,Personal Travel,Eco Plus,2237,3,5,3,1,2,3,2,2,4,4,4,3,4,2,28,9.0,neutral or dissatisfied +78153,111503,Male,Loyal Customer,35,Business travel,Eco,391,4,4,2,4,4,3,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +78154,1998,Female,Loyal Customer,53,Personal Travel,Eco,293,4,5,4,3,3,5,4,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +78155,22104,Female,disloyal Customer,28,Business travel,Eco,743,4,4,4,3,4,4,4,4,4,1,3,2,4,4,70,60.0,satisfied +78156,101581,Male,disloyal Customer,20,Business travel,Business,1099,4,5,4,3,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +78157,77167,Female,Loyal Customer,36,Personal Travel,Eco,1450,4,2,4,3,5,4,5,5,2,1,4,4,3,5,101,76.0,neutral or dissatisfied +78158,18543,Female,disloyal Customer,25,Business travel,Eco,190,4,2,4,4,4,5,4,3,3,4,4,4,3,4,230,232.0,neutral or dissatisfied +78159,68274,Female,Loyal Customer,55,Business travel,Business,631,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +78160,111722,Female,Loyal Customer,45,Personal Travel,Eco,495,2,4,2,3,3,4,4,1,1,2,1,3,1,5,8,5.0,neutral or dissatisfied +78161,92262,Male,Loyal Customer,47,Business travel,Business,1900,2,2,2,2,4,5,4,2,2,2,2,3,2,5,14,4.0,satisfied +78162,115514,Male,disloyal Customer,27,Business travel,Eco,372,3,3,3,3,5,3,4,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +78163,117059,Male,Loyal Customer,48,Business travel,Business,1874,2,2,2,2,2,4,5,5,5,5,5,5,5,3,4,2.0,satisfied +78164,46651,Female,Loyal Customer,43,Business travel,Business,3640,4,4,4,4,4,3,2,5,5,5,3,3,5,2,0,0.0,satisfied +78165,27523,Male,Loyal Customer,23,Personal Travel,Eco,987,1,5,1,5,2,1,2,2,3,5,4,4,4,2,2,0.0,neutral or dissatisfied +78166,51443,Male,Loyal Customer,69,Personal Travel,Eco Plus,190,3,3,3,2,1,3,1,1,1,1,3,2,4,1,6,18.0,neutral or dissatisfied +78167,117846,Female,Loyal Customer,33,Business travel,Business,2133,4,3,3,3,4,4,4,1,4,2,3,4,4,4,146,129.0,neutral or dissatisfied +78168,103090,Female,Loyal Customer,68,Personal Travel,Eco,460,2,3,5,3,4,5,1,1,1,5,1,4,1,2,0,0.0,neutral or dissatisfied +78169,124068,Male,Loyal Customer,12,Personal Travel,Eco,2153,3,4,3,3,4,3,4,4,1,4,4,5,3,4,0,8.0,neutral or dissatisfied +78170,102534,Female,Loyal Customer,16,Personal Travel,Eco,236,2,5,2,2,5,2,5,5,4,5,1,4,1,5,0,0.0,neutral or dissatisfied +78171,15409,Male,disloyal Customer,33,Business travel,Eco,433,1,4,1,1,1,1,1,1,5,5,5,3,5,1,0,2.0,neutral or dissatisfied +78172,41384,Male,Loyal Customer,34,Business travel,Business,809,5,5,5,5,5,3,3,5,5,5,5,5,5,4,13,7.0,satisfied +78173,100474,Male,disloyal Customer,43,Business travel,Business,580,2,1,1,1,5,2,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +78174,32860,Male,Loyal Customer,51,Personal Travel,Eco,102,3,4,0,2,3,0,3,3,5,5,5,4,4,3,0,1.0,neutral or dissatisfied +78175,63395,Female,Loyal Customer,11,Personal Travel,Eco,447,4,5,4,2,1,4,1,1,3,3,5,4,4,1,41,47.0,neutral or dissatisfied +78176,113708,Male,Loyal Customer,14,Personal Travel,Eco,397,4,4,4,1,4,4,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +78177,59712,Female,Loyal Customer,56,Business travel,Business,787,4,1,4,4,4,5,4,4,4,4,4,4,4,5,0,6.0,satisfied +78178,36599,Female,Loyal Customer,70,Business travel,Business,2922,3,5,1,5,1,4,4,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +78179,5521,Male,Loyal Customer,49,Business travel,Business,3095,3,1,1,1,5,3,3,3,3,2,3,1,3,2,0,1.0,neutral or dissatisfied +78180,20778,Female,Loyal Customer,46,Business travel,Business,508,2,2,2,2,1,1,2,4,4,5,4,4,4,3,12,9.0,satisfied +78181,53782,Male,disloyal Customer,24,Business travel,Eco,140,5,0,5,4,5,5,5,5,4,2,4,5,4,5,6,0.0,satisfied +78182,76966,Male,Loyal Customer,61,Personal Travel,Eco,1990,3,2,3,3,2,3,2,2,1,3,2,1,3,2,0,0.0,neutral or dissatisfied +78183,85004,Male,disloyal Customer,44,Business travel,Business,1590,3,3,3,3,5,3,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +78184,129165,Male,Loyal Customer,24,Business travel,Business,679,3,5,5,5,3,3,3,3,1,5,4,1,4,3,0,1.0,neutral or dissatisfied +78185,126106,Male,Loyal Customer,53,Business travel,Business,650,3,3,3,3,5,4,5,4,4,4,4,3,4,4,18,5.0,satisfied +78186,50574,Male,Loyal Customer,33,Personal Travel,Eco,337,5,4,5,3,1,5,1,1,1,5,3,3,3,1,22,56.0,satisfied +78187,9651,Male,Loyal Customer,60,Business travel,Business,1564,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +78188,123402,Female,Loyal Customer,47,Business travel,Business,1337,2,2,5,2,3,5,4,5,5,5,5,5,5,3,24,10.0,satisfied +78189,89375,Male,Loyal Customer,46,Business travel,Business,2684,0,0,0,2,5,4,4,3,3,5,5,4,3,5,0,0.0,satisfied +78190,82586,Female,Loyal Customer,41,Business travel,Business,1712,3,3,3,3,2,4,4,4,4,4,4,4,4,3,0,7.0,satisfied +78191,16035,Male,Loyal Customer,59,Personal Travel,Eco,780,4,2,3,4,1,3,1,1,3,5,4,2,3,1,0,10.0,neutral or dissatisfied +78192,53566,Female,Loyal Customer,46,Business travel,Eco,1195,1,3,3,3,4,2,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +78193,39432,Female,disloyal Customer,38,Business travel,Eco,129,4,3,4,1,2,4,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +78194,117997,Female,Loyal Customer,45,Personal Travel,Eco Plus,365,3,2,3,3,5,3,2,2,2,3,2,1,2,3,9,4.0,neutral or dissatisfied +78195,86490,Male,disloyal Customer,54,Personal Travel,Eco,762,2,4,2,3,5,2,5,5,3,4,5,4,5,5,29,0.0,neutral or dissatisfied +78196,67825,Male,disloyal Customer,25,Business travel,Eco,835,2,2,2,4,5,2,5,5,5,4,5,1,3,5,1,0.0,neutral or dissatisfied +78197,46545,Female,Loyal Customer,58,Business travel,Business,125,4,4,4,4,5,2,5,4,4,4,5,3,4,2,0,0.0,satisfied +78198,46081,Male,disloyal Customer,25,Business travel,Eco,541,2,0,2,5,3,2,3,3,5,3,4,4,1,3,0,0.0,neutral or dissatisfied +78199,70817,Male,Loyal Customer,29,Personal Travel,Eco,624,1,5,1,4,2,1,3,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +78200,103902,Male,disloyal Customer,9,Business travel,Eco,1072,4,4,4,3,2,4,2,2,3,4,3,3,4,2,9,0.0,neutral or dissatisfied +78201,11825,Male,Loyal Customer,47,Business travel,Business,1021,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,1.0,satisfied +78202,38982,Female,Loyal Customer,37,Business travel,Eco,230,4,3,3,3,4,4,4,4,4,3,3,4,4,4,0,0.0,satisfied +78203,18780,Female,disloyal Customer,37,Business travel,Eco,448,1,5,1,3,5,1,1,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +78204,12930,Female,Loyal Customer,56,Personal Travel,Eco,359,4,4,4,3,4,3,3,3,3,4,3,3,3,1,0,0.0,neutral or dissatisfied +78205,101649,Female,Loyal Customer,16,Personal Travel,Eco,1749,3,1,3,3,2,3,2,2,3,2,2,1,3,2,0,0.0,neutral or dissatisfied +78206,43499,Female,Loyal Customer,51,Personal Travel,Eco,594,2,4,1,3,1,3,4,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +78207,110998,Female,disloyal Customer,24,Business travel,Eco,319,2,3,2,2,2,2,2,2,2,4,2,3,2,2,28,103.0,neutral or dissatisfied +78208,22419,Female,Loyal Customer,17,Business travel,Eco,143,5,3,3,3,5,5,5,5,1,1,1,5,5,5,0,0.0,satisfied +78209,98786,Male,Loyal Customer,52,Business travel,Business,2228,2,2,2,2,5,4,4,5,5,5,5,5,5,5,14,9.0,satisfied +78210,45243,Female,Loyal Customer,55,Personal Travel,Eco,1013,2,1,2,4,5,4,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +78211,76348,Male,disloyal Customer,24,Business travel,Eco,1250,3,3,3,3,1,3,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +78212,93764,Male,Loyal Customer,7,Personal Travel,Eco,368,3,2,1,3,3,1,5,3,2,2,2,4,3,3,93,110.0,neutral or dissatisfied +78213,5614,Female,Loyal Customer,28,Business travel,Eco,685,2,2,2,2,2,2,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +78214,69455,Female,Loyal Customer,15,Personal Travel,Eco,1089,3,5,3,5,4,3,2,4,3,5,2,2,1,4,1,0.0,neutral or dissatisfied +78215,89799,Female,Loyal Customer,17,Personal Travel,Eco,1080,1,1,1,3,2,1,2,2,2,3,4,2,3,2,0,0.0,neutral or dissatisfied +78216,121560,Male,disloyal Customer,24,Business travel,Eco,936,4,4,4,4,2,4,2,2,4,5,5,4,4,2,9,0.0,neutral or dissatisfied +78217,83229,Male,disloyal Customer,39,Business travel,Business,1076,4,4,4,2,2,4,2,2,3,3,5,5,4,2,0,0.0,satisfied +78218,35786,Male,Loyal Customer,56,Personal Travel,Eco,200,2,3,0,4,5,0,5,5,1,5,2,4,5,5,0,0.0,neutral or dissatisfied +78219,17674,Female,Loyal Customer,79,Business travel,Business,1643,3,1,1,1,4,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +78220,128576,Female,disloyal Customer,25,Business travel,Business,1161,4,3,5,4,5,4,2,5,5,5,4,2,4,2,14,0.0,satisfied +78221,117435,Male,Loyal Customer,58,Business travel,Business,1020,1,1,1,1,2,5,5,4,4,4,4,4,4,3,9,0.0,satisfied +78222,110375,Female,Loyal Customer,40,Business travel,Business,787,4,3,3,3,4,1,2,4,4,4,4,1,4,4,19,18.0,neutral or dissatisfied +78223,8552,Male,Loyal Customer,53,Business travel,Business,2269,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +78224,30492,Male,Loyal Customer,22,Business travel,Eco,604,1,1,1,1,1,1,2,1,2,4,3,4,3,1,0,12.0,neutral or dissatisfied +78225,41308,Male,disloyal Customer,21,Business travel,Eco,802,3,2,2,2,3,2,3,3,2,1,1,2,1,3,33,32.0,neutral or dissatisfied +78226,55471,Male,Loyal Customer,66,Business travel,Eco,325,3,4,5,4,3,3,3,3,3,1,1,4,4,3,0,0.0,satisfied +78227,129387,Female,Loyal Customer,47,Business travel,Business,2454,3,3,3,3,4,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +78228,55291,Female,Loyal Customer,43,Business travel,Business,1185,1,1,1,1,2,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +78229,13175,Male,Loyal Customer,44,Business travel,Business,3276,2,3,3,3,2,3,3,2,2,2,2,4,2,4,92,79.0,neutral or dissatisfied +78230,126898,Female,Loyal Customer,42,Business travel,Business,2125,3,3,3,3,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +78231,52380,Male,Loyal Customer,56,Personal Travel,Eco,493,4,4,4,2,5,4,5,5,4,1,1,3,4,5,0,0.0,neutral or dissatisfied +78232,118334,Female,Loyal Customer,26,Business travel,Business,2791,3,4,3,3,5,4,5,5,5,3,5,5,4,5,0,0.0,satisfied +78233,21246,Female,disloyal Customer,20,Business travel,Eco,192,5,4,5,1,4,5,1,4,3,5,2,3,5,4,0,0.0,satisfied +78234,94413,Male,Loyal Customer,59,Business travel,Business,3851,3,3,2,3,3,5,4,5,5,5,5,5,5,3,12,0.0,satisfied +78235,107107,Female,Loyal Customer,8,Personal Travel,Business,842,3,5,3,5,3,3,2,3,2,5,4,5,1,3,5,,neutral or dissatisfied +78236,24505,Female,Loyal Customer,53,Personal Travel,Eco,547,4,4,4,3,4,4,4,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +78237,41427,Male,Loyal Customer,19,Personal Travel,Eco,913,2,4,3,1,5,3,5,5,3,4,5,3,5,5,42,,neutral or dissatisfied +78238,109395,Male,Loyal Customer,19,Personal Travel,Eco,1046,4,2,5,4,5,5,5,5,3,5,3,1,4,5,31,24.0,neutral or dissatisfied +78239,121841,Female,Loyal Customer,49,Business travel,Business,449,2,4,4,4,1,2,3,2,2,2,2,3,2,2,39,38.0,neutral or dissatisfied +78240,38395,Female,disloyal Customer,8,Business travel,Eco,811,3,3,3,3,1,3,1,1,1,2,4,1,4,1,0,20.0,neutral or dissatisfied +78241,119705,Female,disloyal Customer,24,Business travel,Eco,1303,5,5,5,4,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +78242,5082,Female,Loyal Customer,66,Business travel,Eco,235,1,2,2,2,1,1,1,4,2,3,3,1,3,1,116,216.0,neutral or dissatisfied +78243,98379,Male,Loyal Customer,32,Business travel,Eco Plus,1046,3,3,5,3,3,2,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +78244,46771,Male,Loyal Customer,33,Personal Travel,Eco Plus,125,1,1,1,1,4,1,4,4,1,1,1,3,1,4,23,42.0,neutral or dissatisfied +78245,109965,Male,Loyal Customer,7,Personal Travel,Eco,1073,2,4,1,3,4,1,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +78246,104734,Female,disloyal Customer,22,Business travel,Eco,1407,4,4,4,2,1,4,1,1,4,2,5,4,5,1,0,11.0,satisfied +78247,43853,Male,Loyal Customer,59,Business travel,Business,2234,0,5,0,4,5,5,5,3,3,3,3,1,3,3,0,0.0,satisfied +78248,103509,Male,disloyal Customer,25,Business travel,Eco,1256,2,2,2,3,3,2,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +78249,34257,Male,Loyal Customer,59,Business travel,Business,280,1,2,2,2,1,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +78250,39523,Female,Loyal Customer,60,Personal Travel,Eco,852,2,4,2,1,3,5,4,3,3,2,3,4,3,4,124,111.0,neutral or dissatisfied +78251,105904,Male,Loyal Customer,18,Business travel,Business,2120,3,5,5,5,3,3,3,3,3,5,3,3,4,3,19,12.0,neutral or dissatisfied +78252,26476,Male,Loyal Customer,33,Business travel,Eco Plus,925,5,5,5,5,5,5,5,5,4,1,1,2,4,5,0,0.0,satisfied +78253,25256,Female,disloyal Customer,34,Business travel,Eco,425,3,3,3,5,4,3,4,4,5,2,2,5,5,4,80,69.0,neutral or dissatisfied +78254,94133,Female,Loyal Customer,42,Business travel,Business,2685,3,3,3,3,4,5,4,5,5,5,5,4,5,5,6,2.0,satisfied +78255,124127,Female,Loyal Customer,49,Business travel,Eco,129,1,5,2,5,5,3,4,1,1,1,1,2,1,2,45,30.0,neutral or dissatisfied +78256,30830,Female,Loyal Customer,39,Business travel,Eco,955,1,0,0,3,5,0,5,5,4,1,3,4,2,5,18,26.0,neutral or dissatisfied +78257,125095,Female,Loyal Customer,39,Business travel,Business,361,5,5,5,5,5,4,4,3,3,2,3,3,3,4,0,0.0,satisfied +78258,88547,Female,Loyal Customer,52,Personal Travel,Eco,406,3,4,3,3,2,4,4,2,2,3,2,4,2,5,0,2.0,neutral or dissatisfied +78259,10058,Female,Loyal Customer,40,Personal Travel,Business,596,5,3,5,4,2,4,3,3,3,5,3,1,3,1,0,0.0,satisfied +78260,43209,Female,Loyal Customer,54,Business travel,Business,3342,1,1,1,1,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +78261,11696,Male,disloyal Customer,20,Business travel,Business,395,4,5,5,1,2,5,2,2,5,2,4,5,5,2,5,4.0,satisfied +78262,88442,Male,Loyal Customer,42,Business travel,Eco,270,1,5,5,5,1,1,1,1,1,1,3,3,3,1,1,0.0,neutral or dissatisfied +78263,73270,Female,Loyal Customer,44,Business travel,Business,3975,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +78264,71656,Male,Loyal Customer,9,Personal Travel,Eco,1012,1,1,0,4,4,0,4,4,4,4,4,1,3,4,15,8.0,neutral or dissatisfied +78265,121354,Female,disloyal Customer,22,Business travel,Business,430,4,0,4,5,4,3,3,4,4,5,4,3,3,3,359,379.0,satisfied +78266,83834,Male,Loyal Customer,46,Business travel,Eco,425,4,4,4,4,4,4,4,4,4,2,4,1,5,4,0,0.0,satisfied +78267,55338,Male,Loyal Customer,56,Personal Travel,Eco,1325,3,5,3,2,1,3,1,1,3,2,3,4,4,1,1,0.0,neutral or dissatisfied +78268,97266,Male,Loyal Customer,38,Personal Travel,Eco,296,3,2,3,4,2,3,2,2,4,2,3,3,4,2,14,14.0,neutral or dissatisfied +78269,94401,Female,Loyal Customer,29,Business travel,Business,677,4,4,4,4,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +78270,51293,Female,Loyal Customer,37,Business travel,Eco Plus,262,4,5,5,5,4,4,4,4,2,2,1,5,1,4,0,0.0,satisfied +78271,22409,Female,disloyal Customer,42,Business travel,Eco,208,4,3,4,3,2,4,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +78272,26360,Female,Loyal Customer,13,Business travel,Business,1525,4,4,3,4,4,4,4,4,3,3,3,5,5,4,16,13.0,satisfied +78273,105094,Female,Loyal Customer,51,Business travel,Business,281,2,2,2,2,4,5,4,4,4,4,4,3,4,4,36,28.0,satisfied +78274,64928,Male,Loyal Customer,22,Business travel,Business,247,3,3,3,3,4,4,4,4,5,3,5,4,5,4,10,0.0,satisfied +78275,33262,Male,Loyal Customer,60,Personal Travel,Eco Plus,101,3,3,3,4,2,3,3,2,3,5,1,2,2,2,0,0.0,neutral or dissatisfied +78276,100712,Male,Loyal Customer,36,Business travel,Business,2338,2,2,5,2,4,4,4,5,5,5,5,3,5,4,0,2.0,satisfied +78277,103673,Female,Loyal Customer,55,Business travel,Business,3021,5,5,3,5,3,5,4,5,5,5,5,5,5,3,7,6.0,satisfied +78278,64217,Female,Loyal Customer,55,Personal Travel,Business,1660,1,0,1,3,2,4,5,3,3,1,5,3,3,4,3,2.0,neutral or dissatisfied +78279,1175,Female,Loyal Customer,55,Personal Travel,Eco,312,2,5,2,1,2,4,4,1,1,2,4,3,1,5,0,0.0,neutral or dissatisfied +78280,59083,Female,disloyal Customer,26,Business travel,Eco,281,0,0,0,1,1,0,1,1,2,5,4,5,5,1,0,0.0,satisfied +78281,77212,Female,disloyal Customer,30,Business travel,Business,1590,3,3,3,4,5,3,5,5,4,3,3,1,4,5,3,23.0,neutral or dissatisfied +78282,31013,Female,disloyal Customer,22,Business travel,Eco,391,0,0,0,3,3,0,3,3,1,4,2,2,2,3,0,0.0,satisfied +78283,58358,Male,disloyal Customer,37,Business travel,Eco,246,2,1,2,4,3,2,4,3,4,5,3,3,4,3,23,36.0,neutral or dissatisfied +78284,100828,Male,Loyal Customer,45,Business travel,Business,1504,3,3,3,3,4,5,4,5,5,5,5,4,5,4,41,14.0,satisfied +78285,104094,Male,Loyal Customer,54,Personal Travel,Eco,588,2,5,2,3,5,2,5,5,4,5,5,5,5,5,0,12.0,neutral or dissatisfied +78286,87921,Male,Loyal Customer,44,Business travel,Business,3227,2,3,3,3,5,3,3,2,2,2,2,1,2,2,22,11.0,neutral or dissatisfied +78287,103177,Male,Loyal Customer,57,Personal Travel,Eco,272,3,0,3,1,4,3,4,4,1,3,3,4,1,4,0,0.0,neutral or dissatisfied +78288,108323,Male,disloyal Customer,25,Business travel,Eco,1125,1,1,1,2,1,1,1,1,3,3,4,3,4,1,45,40.0,neutral or dissatisfied +78289,68486,Female,disloyal Customer,29,Business travel,Eco,1303,1,1,1,3,4,1,4,4,1,3,3,4,2,4,0,0.0,neutral or dissatisfied +78290,87381,Female,disloyal Customer,59,Business travel,Eco,448,4,1,4,2,3,4,3,3,2,3,1,1,2,3,79,69.0,neutral or dissatisfied +78291,101137,Female,Loyal Customer,57,Business travel,Business,3189,5,5,2,5,3,4,4,5,5,5,5,3,5,4,0,6.0,satisfied +78292,90902,Female,Loyal Customer,25,Business travel,Business,3367,2,1,1,1,2,2,2,2,3,1,3,4,3,2,6,7.0,neutral or dissatisfied +78293,59325,Female,disloyal Customer,37,Business travel,Business,2447,2,2,2,4,3,2,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +78294,51433,Female,Loyal Customer,7,Personal Travel,Eco Plus,373,3,4,5,2,5,5,5,5,2,2,4,1,1,5,64,57.0,neutral or dissatisfied +78295,29193,Female,Loyal Customer,47,Personal Travel,Eco Plus,978,3,5,4,3,5,5,5,5,5,4,5,5,5,4,33,38.0,neutral or dissatisfied +78296,13133,Female,disloyal Customer,25,Business travel,Eco,562,2,2,2,4,4,2,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +78297,111587,Female,Loyal Customer,48,Personal Travel,Eco,883,4,3,4,3,3,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +78298,59318,Female,Loyal Customer,52,Business travel,Business,2399,4,4,5,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +78299,120242,Female,Loyal Customer,30,Personal Travel,Eco,1303,2,4,2,3,1,2,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +78300,60510,Female,Loyal Customer,58,Personal Travel,Eco,862,3,1,3,4,3,3,4,4,4,3,3,2,4,2,13,0.0,neutral or dissatisfied +78301,4963,Male,Loyal Customer,56,Personal Travel,Eco,931,4,1,4,2,1,4,1,1,3,2,2,2,1,1,0,17.0,neutral or dissatisfied +78302,41596,Female,Loyal Customer,40,Personal Travel,Eco,1482,2,1,2,2,3,2,3,3,2,5,2,1,2,3,0,0.0,neutral or dissatisfied +78303,4626,Female,Loyal Customer,58,Business travel,Business,489,1,1,1,1,4,4,3,1,1,1,1,2,1,1,0,30.0,neutral or dissatisfied +78304,85896,Female,Loyal Customer,50,Business travel,Business,2435,3,3,3,3,4,4,5,5,5,5,5,5,5,3,0,4.0,satisfied +78305,83441,Female,Loyal Customer,11,Personal Travel,Eco Plus,632,3,1,3,2,4,3,4,4,1,2,2,3,1,4,0,0.0,neutral or dissatisfied +78306,70088,Male,Loyal Customer,40,Business travel,Business,3013,3,3,3,3,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +78307,60662,Female,Loyal Customer,28,Personal Travel,Eco,1620,3,4,3,3,4,3,4,4,3,2,3,4,5,4,0,0.0,neutral or dissatisfied +78308,108955,Female,Loyal Customer,26,Business travel,Business,655,1,1,1,1,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +78309,17888,Male,Loyal Customer,45,Personal Travel,Eco,399,2,5,4,2,4,4,4,4,1,2,3,2,2,4,0,0.0,neutral or dissatisfied +78310,121635,Female,Loyal Customer,26,Business travel,Business,3408,2,2,2,2,3,4,3,3,3,4,4,5,4,3,0,0.0,satisfied +78311,1058,Male,Loyal Customer,62,Personal Travel,Eco,396,4,5,4,1,1,4,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +78312,95229,Male,Loyal Customer,27,Personal Travel,Eco,323,2,3,2,1,5,2,5,5,5,4,3,2,3,5,49,32.0,neutral or dissatisfied +78313,82774,Male,disloyal Customer,36,Business travel,Business,926,4,4,4,3,2,4,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +78314,126822,Female,Loyal Customer,54,Business travel,Business,2296,1,1,1,1,3,4,4,2,2,2,2,3,2,3,13,0.0,satisfied +78315,36124,Female,Loyal Customer,24,Business travel,Eco,1609,4,5,5,5,4,4,3,4,5,5,3,3,1,4,0,0.0,satisfied +78316,75179,Male,disloyal Customer,34,Business travel,Eco,964,3,3,3,3,3,3,3,3,1,2,2,4,4,3,0,0.0,neutral or dissatisfied +78317,34457,Male,Loyal Customer,14,Personal Travel,Eco,228,2,5,2,3,3,2,1,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +78318,51655,Female,Loyal Customer,63,Business travel,Business,325,1,1,1,1,2,3,1,4,4,4,4,2,4,5,0,0.0,satisfied +78319,84225,Male,Loyal Customer,57,Personal Travel,Eco,432,3,5,3,4,3,3,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +78320,99603,Male,Loyal Customer,29,Business travel,Business,2818,3,3,3,3,5,5,5,5,5,2,4,3,4,5,4,8.0,satisfied +78321,14503,Male,disloyal Customer,27,Business travel,Eco,328,1,5,1,3,2,1,2,2,4,1,4,4,5,2,0,56.0,neutral or dissatisfied +78322,30686,Female,Loyal Customer,42,Business travel,Eco,680,4,1,1,1,4,3,2,5,5,4,5,1,5,1,0,0.0,satisfied +78323,41439,Male,disloyal Customer,25,Business travel,Eco Plus,563,2,2,2,2,2,5,5,1,2,2,3,5,1,5,181,187.0,neutral or dissatisfied +78324,104118,Male,Loyal Customer,42,Business travel,Business,1655,1,1,1,1,3,5,4,3,3,3,3,5,3,5,33,34.0,satisfied +78325,81389,Male,Loyal Customer,37,Business travel,Eco,874,3,3,3,3,3,3,3,3,1,1,3,3,3,3,0,7.0,neutral or dissatisfied +78326,24581,Female,Loyal Customer,47,Business travel,Business,666,5,5,1,5,4,3,2,5,5,5,5,4,5,2,4,3.0,satisfied +78327,116242,Female,Loyal Customer,7,Personal Travel,Eco,325,2,3,1,3,3,1,3,3,4,1,4,5,1,3,35,32.0,neutral or dissatisfied +78328,125146,Male,Loyal Customer,30,Business travel,Eco,1999,2,1,1,1,2,3,2,2,4,4,1,1,2,2,0,2.0,neutral or dissatisfied +78329,123346,Female,Loyal Customer,23,Personal Travel,Eco Plus,328,2,3,2,2,2,2,2,2,5,5,3,2,1,2,7,7.0,neutral or dissatisfied +78330,127794,Male,Loyal Customer,46,Personal Travel,Business,1262,3,4,3,5,4,5,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +78331,85134,Male,Loyal Customer,57,Business travel,Business,3826,1,1,1,1,3,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +78332,80094,Female,Loyal Customer,41,Business travel,Business,2722,1,1,1,1,2,4,4,5,5,5,5,3,5,3,10,0.0,satisfied +78333,1695,Female,Loyal Customer,42,Business travel,Business,489,5,5,5,5,2,5,5,3,3,3,3,5,3,3,0,2.0,satisfied +78334,75024,Male,Loyal Customer,55,Business travel,Eco,236,3,4,4,4,4,3,4,4,4,4,4,1,3,4,2,0.0,neutral or dissatisfied +78335,19924,Female,Loyal Customer,54,Business travel,Business,2635,5,5,5,5,3,1,1,4,4,4,4,4,4,1,0,0.0,satisfied +78336,55990,Female,disloyal Customer,19,Business travel,Eco,834,1,1,1,3,1,3,3,1,2,2,2,3,1,3,0,13.0,neutral or dissatisfied +78337,68556,Female,Loyal Customer,46,Business travel,Business,2136,2,2,2,2,4,5,5,5,5,5,5,3,5,5,36,6.0,satisfied +78338,117970,Female,Loyal Customer,40,Personal Travel,Eco,255,3,0,0,1,1,0,1,1,5,2,5,4,4,1,13,6.0,neutral or dissatisfied +78339,18981,Male,disloyal Customer,23,Business travel,Eco,451,3,0,3,4,2,3,2,2,2,3,1,2,3,2,15,10.0,neutral or dissatisfied +78340,113606,Female,Loyal Customer,31,Personal Travel,Eco,407,3,3,3,4,3,3,3,3,5,4,2,2,1,3,0,0.0,neutral or dissatisfied +78341,33347,Male,disloyal Customer,34,Business travel,Eco,835,3,3,3,1,3,3,3,3,4,1,4,3,2,3,0,0.0,neutral or dissatisfied +78342,63451,Female,Loyal Customer,53,Personal Travel,Eco,447,3,1,3,2,2,2,1,5,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +78343,87714,Male,Loyal Customer,67,Personal Travel,Eco,606,2,5,2,2,5,2,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +78344,117591,Female,Loyal Customer,26,Business travel,Business,3382,4,1,1,1,4,4,4,4,2,2,4,1,3,4,24,5.0,neutral or dissatisfied +78345,3334,Male,Loyal Customer,49,Business travel,Business,2037,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +78346,107009,Female,Loyal Customer,36,Business travel,Business,1036,4,4,4,4,3,4,5,3,3,3,3,3,3,3,20,21.0,satisfied +78347,80728,Female,Loyal Customer,49,Business travel,Business,2936,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,38.0,satisfied +78348,41007,Male,Loyal Customer,13,Personal Travel,Eco,1362,1,5,1,3,3,1,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +78349,42491,Male,Loyal Customer,61,Personal Travel,Eco,585,3,4,3,4,4,3,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +78350,32859,Female,Loyal Customer,7,Personal Travel,Eco,102,2,4,2,3,1,2,1,1,1,3,4,2,3,1,1,0.0,neutral or dissatisfied +78351,42,Female,Loyal Customer,45,Business travel,Business,108,4,4,4,4,3,5,4,4,4,4,5,5,4,3,0,0.0,satisfied +78352,22219,Female,disloyal Customer,72,Business travel,Eco Plus,533,4,4,4,4,3,4,3,3,3,1,5,1,5,3,0,0.0,neutral or dissatisfied +78353,107662,Female,Loyal Customer,57,Business travel,Business,466,3,3,3,3,3,3,3,3,3,4,4,3,5,3,184,172.0,satisfied +78354,43069,Female,Loyal Customer,12,Personal Travel,Eco,259,3,4,3,1,5,3,5,5,1,3,1,2,2,5,60,54.0,neutral or dissatisfied +78355,72541,Male,Loyal Customer,13,Business travel,Business,1121,1,3,3,3,1,1,1,1,4,5,4,3,4,1,1,26.0,neutral or dissatisfied +78356,57460,Female,Loyal Customer,25,Personal Travel,Eco,334,2,4,2,4,4,2,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +78357,35019,Male,Loyal Customer,37,Business travel,Business,3391,3,2,2,2,1,4,4,3,3,3,3,1,3,4,0,3.0,neutral or dissatisfied +78358,28994,Male,Loyal Customer,25,Business travel,Business,1819,5,2,5,5,4,4,4,4,3,5,1,3,2,4,0,0.0,satisfied +78359,65105,Male,Loyal Customer,60,Personal Travel,Eco,551,1,1,1,3,3,1,3,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +78360,76596,Male,Loyal Customer,51,Business travel,Business,534,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +78361,65665,Male,Loyal Customer,42,Business travel,Business,3860,5,5,5,5,2,4,5,3,3,4,3,5,3,4,42,46.0,satisfied +78362,99498,Female,Loyal Customer,30,Personal Travel,Eco,307,3,4,3,4,4,3,4,4,3,4,4,5,5,4,3,6.0,neutral or dissatisfied +78363,97114,Male,Loyal Customer,35,Business travel,Business,2446,1,1,1,1,2,4,4,4,4,4,4,3,4,3,5,0.0,satisfied +78364,115529,Female,Loyal Customer,33,Business travel,Eco,333,3,5,5,5,3,3,3,3,2,4,3,4,2,3,13,17.0,neutral or dissatisfied +78365,95670,Male,disloyal Customer,24,Business travel,Eco,1131,2,3,3,3,3,3,5,3,2,2,2,4,2,3,53,35.0,neutral or dissatisfied +78366,75339,Female,Loyal Customer,48,Personal Travel,Eco,2486,3,2,3,3,3,4,3,3,4,4,4,3,2,3,0,6.0,neutral or dissatisfied +78367,32040,Female,Loyal Customer,42,Business travel,Business,201,3,3,3,3,1,3,1,5,5,5,3,4,5,3,0,0.0,satisfied +78368,22812,Male,Loyal Customer,20,Business travel,Eco,170,5,2,2,2,5,5,3,5,4,3,4,3,1,5,0,0.0,satisfied +78369,82624,Female,Loyal Customer,48,Personal Travel,Eco,528,1,4,1,3,3,1,2,3,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +78370,105095,Female,Loyal Customer,56,Business travel,Business,2788,3,3,3,3,5,5,5,4,4,4,4,5,3,5,415,410.0,satisfied +78371,44249,Female,disloyal Customer,24,Business travel,Eco,118,3,1,3,2,4,3,4,4,3,5,1,1,1,4,18,32.0,neutral or dissatisfied +78372,100459,Male,Loyal Customer,34,Business travel,Business,2711,2,2,2,2,4,5,5,4,4,4,4,3,4,5,7,0.0,satisfied +78373,23316,Male,Loyal Customer,22,Business travel,Eco,674,3,4,4,4,3,3,2,3,2,3,3,1,3,3,18,6.0,neutral or dissatisfied +78374,80516,Male,Loyal Customer,63,Personal Travel,Eco,1749,2,1,2,2,3,2,3,3,4,3,2,1,1,3,0,0.0,neutral or dissatisfied +78375,51242,Male,Loyal Customer,59,Business travel,Eco Plus,373,5,4,4,4,5,5,5,5,1,4,5,3,4,5,0,0.0,satisfied +78376,29025,Female,Loyal Customer,76,Business travel,Eco,650,3,2,2,2,4,4,4,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +78377,38089,Male,disloyal Customer,55,Business travel,Eco,1249,3,3,3,3,2,3,2,2,4,5,2,3,2,2,2,0.0,neutral or dissatisfied +78378,28857,Male,Loyal Customer,22,Business travel,Business,954,2,2,2,2,2,2,2,2,5,3,2,5,3,2,0,0.0,satisfied +78379,96891,Male,Loyal Customer,48,Personal Travel,Eco,1105,2,2,2,2,3,2,3,3,4,2,3,1,2,3,0,0.0,neutral or dissatisfied +78380,103795,Female,Loyal Customer,45,Business travel,Business,2064,5,5,5,5,2,4,5,5,5,5,5,3,5,3,5,0.0,satisfied +78381,77855,Female,Loyal Customer,33,Personal Travel,Eco Plus,874,1,3,1,3,1,1,1,1,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +78382,122642,Male,Loyal Customer,37,Personal Travel,Eco Plus,728,3,4,3,1,4,3,4,4,5,2,3,3,1,4,2,0.0,neutral or dissatisfied +78383,79009,Female,Loyal Customer,61,Business travel,Business,356,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,11.0,satisfied +78384,56236,Female,Loyal Customer,46,Business travel,Business,1608,5,5,5,5,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +78385,95316,Male,Loyal Customer,30,Personal Travel,Eco,323,3,3,3,3,1,3,1,1,5,1,1,4,3,1,0,0.0,neutral or dissatisfied +78386,21913,Female,Loyal Customer,51,Business travel,Business,2981,2,2,2,2,2,2,5,4,4,4,4,3,4,4,0,5.0,satisfied +78387,64297,Male,Loyal Customer,52,Business travel,Business,2167,2,2,2,2,2,5,4,3,3,4,3,5,3,5,20,20.0,satisfied +78388,73123,Male,Loyal Customer,36,Personal Travel,Eco,2174,2,4,2,4,4,2,4,4,2,3,3,1,4,4,4,19.0,neutral or dissatisfied +78389,108211,Female,disloyal Customer,26,Business travel,Business,777,5,5,5,4,1,5,3,1,4,4,5,4,5,1,0,0.0,satisfied +78390,124235,Male,Loyal Customer,60,Business travel,Business,1916,5,3,5,5,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +78391,73135,Female,Loyal Customer,18,Personal Travel,Eco,1068,3,5,3,3,3,3,3,3,5,5,4,3,4,3,0,8.0,neutral or dissatisfied +78392,47793,Male,disloyal Customer,25,Business travel,Eco,329,2,0,3,4,2,3,2,2,5,2,1,3,1,2,78,73.0,neutral or dissatisfied +78393,51017,Male,Loyal Customer,62,Personal Travel,Eco,308,1,5,1,3,2,1,2,2,4,5,5,3,5,2,3,0.0,neutral or dissatisfied +78394,110724,Male,Loyal Customer,40,Business travel,Business,2231,1,1,1,1,3,4,4,4,4,4,4,4,4,5,52,31.0,satisfied +78395,63600,Female,Loyal Customer,56,Business travel,Business,1440,3,3,3,3,4,5,5,4,3,4,4,5,3,5,248,262.0,satisfied +78396,6419,Male,Loyal Customer,55,Personal Travel,Eco,315,4,5,4,5,3,4,3,3,3,1,1,4,2,3,3,0.0,satisfied +78397,49465,Female,Loyal Customer,55,Business travel,Business,262,3,3,3,3,2,5,1,4,4,4,4,1,4,4,0,0.0,satisfied +78398,37903,Female,disloyal Customer,22,Business travel,Business,937,0,5,0,1,5,0,5,5,1,4,3,5,2,5,5,12.0,satisfied +78399,106129,Male,Loyal Customer,59,Business travel,Business,1768,5,5,5,5,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +78400,46189,Male,disloyal Customer,25,Business travel,Business,472,2,0,2,4,4,2,4,4,5,1,3,2,1,4,50,62.0,neutral or dissatisfied +78401,67475,Female,Loyal Customer,68,Personal Travel,Eco,769,2,4,2,3,4,4,5,3,3,2,1,3,3,5,0,0.0,neutral or dissatisfied +78402,25425,Male,Loyal Customer,59,Business travel,Business,669,3,3,3,3,5,5,5,4,4,4,4,5,4,3,79,60.0,satisfied +78403,110098,Male,Loyal Customer,25,Business travel,Business,1072,2,2,2,2,3,2,3,3,5,4,5,4,5,3,6,0.0,satisfied +78404,108635,Female,Loyal Customer,20,Personal Travel,Eco,1547,3,5,4,3,3,4,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +78405,56172,Female,disloyal Customer,26,Business travel,Eco,1000,3,3,3,3,5,3,5,5,4,3,3,1,4,5,25,23.0,neutral or dissatisfied +78406,110718,Female,Loyal Customer,42,Business travel,Business,1105,1,1,1,1,2,5,4,3,3,3,3,4,3,5,20,7.0,satisfied +78407,35458,Female,Loyal Customer,37,Personal Travel,Eco,1074,2,5,2,5,3,2,1,3,3,2,5,4,5,3,0,3.0,neutral or dissatisfied +78408,40370,Male,Loyal Customer,25,Business travel,Business,1250,4,2,4,2,4,3,4,4,3,1,4,1,3,4,0,0.0,neutral or dissatisfied +78409,118685,Female,Loyal Customer,12,Personal Travel,Eco,369,3,5,3,2,1,3,5,1,2,1,1,5,2,1,47,46.0,neutral or dissatisfied +78410,7395,Male,Loyal Customer,19,Business travel,Business,3492,4,4,4,4,3,3,3,3,4,4,4,3,4,3,0,3.0,satisfied +78411,68671,Female,Loyal Customer,31,Business travel,Business,3804,2,4,4,4,2,2,2,2,2,4,4,4,4,2,0,0.0,neutral or dissatisfied +78412,73027,Female,Loyal Customer,57,Personal Travel,Eco,1096,3,0,3,4,2,3,2,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +78413,45605,Male,Loyal Customer,59,Business travel,Business,1608,3,3,3,3,3,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +78414,65743,Male,Loyal Customer,36,Business travel,Business,2222,4,4,4,4,1,4,4,2,2,2,2,4,2,1,0,0.0,satisfied +78415,14943,Female,disloyal Customer,22,Business travel,Business,554,5,0,5,5,3,5,3,3,5,2,4,1,4,3,0,0.0,satisfied +78416,25215,Male,Loyal Customer,34,Business travel,Business,3767,2,2,2,2,5,5,3,4,4,4,4,5,4,4,7,9.0,satisfied +78417,64370,Male,Loyal Customer,59,Personal Travel,Eco,1158,1,5,1,3,3,1,1,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +78418,63539,Male,Loyal Customer,25,Personal Travel,Eco,1009,5,4,5,4,1,5,1,1,5,3,5,3,5,1,14,7.0,satisfied +78419,20083,Female,Loyal Customer,48,Personal Travel,Business,843,2,2,2,4,2,3,3,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +78420,88146,Female,Loyal Customer,46,Business travel,Business,3499,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +78421,59845,Male,Loyal Customer,44,Business travel,Business,937,4,4,4,4,4,5,4,5,5,5,5,3,5,4,35,15.0,satisfied +78422,45307,Male,Loyal Customer,42,Business travel,Business,188,1,1,1,1,2,5,3,4,4,4,3,3,4,3,20,22.0,satisfied +78423,72979,Male,Loyal Customer,40,Business travel,Business,2175,4,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +78424,97758,Male,Loyal Customer,36,Personal Travel,Eco,587,2,4,2,2,3,2,3,3,5,5,5,5,5,3,31,29.0,neutral or dissatisfied +78425,124044,Female,disloyal Customer,22,Business travel,Eco,184,2,2,2,4,4,2,2,4,2,2,4,3,3,4,0,0.0,neutral or dissatisfied +78426,38187,Female,Loyal Customer,8,Personal Travel,Eco,1185,3,3,3,4,1,3,1,1,1,3,3,3,3,1,3,0.0,neutral or dissatisfied +78427,84543,Female,Loyal Customer,13,Personal Travel,Eco,2486,1,5,1,4,3,1,3,3,2,4,3,4,1,3,45,36.0,neutral or dissatisfied +78428,122288,Male,Loyal Customer,24,Personal Travel,Eco,544,2,2,2,3,4,2,4,4,1,4,4,2,4,4,3,0.0,neutral or dissatisfied +78429,31124,Female,Loyal Customer,33,Business travel,Business,991,3,4,4,4,3,2,2,3,3,3,3,3,3,1,19,17.0,neutral or dissatisfied +78430,16291,Female,Loyal Customer,52,Personal Travel,Eco,748,0,5,0,1,3,5,4,4,4,0,4,5,4,5,0,0.0,satisfied +78431,112987,Female,Loyal Customer,22,Business travel,Business,1751,4,4,4,4,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +78432,30059,Male,Loyal Customer,58,Business travel,Eco,199,3,1,1,1,3,3,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +78433,76116,Female,Loyal Customer,26,Personal Travel,Business,546,5,5,5,1,4,5,4,4,2,1,3,4,3,4,0,0.0,satisfied +78434,122442,Female,Loyal Customer,50,Business travel,Business,2693,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,15.0,satisfied +78435,33774,Male,Loyal Customer,42,Personal Travel,Eco,1990,3,1,2,3,1,2,5,1,4,2,4,2,4,1,96,74.0,neutral or dissatisfied +78436,34544,Male,disloyal Customer,22,Business travel,Business,1598,2,1,2,4,2,2,2,2,1,4,4,4,4,2,87,86.0,neutral or dissatisfied +78437,81637,Male,disloyal Customer,28,Business travel,Business,907,2,2,2,4,2,2,4,2,4,5,4,2,4,2,41,40.0,neutral or dissatisfied +78438,18561,Male,Loyal Customer,17,Business travel,Eco,127,2,1,1,1,2,2,2,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +78439,17014,Female,Loyal Customer,36,Business travel,Business,781,3,3,3,3,5,3,3,4,4,4,4,5,4,1,54,33.0,satisfied +78440,26726,Female,Loyal Customer,31,Business travel,Eco Plus,515,5,4,4,4,5,5,5,5,5,1,2,2,4,5,0,0.0,satisfied +78441,38016,Male,Loyal Customer,41,Business travel,Business,3840,4,4,4,4,5,3,1,4,4,4,4,3,4,2,55,45.0,satisfied +78442,31394,Male,disloyal Customer,27,Business travel,Business,1199,2,2,2,5,4,2,4,4,5,2,5,5,5,4,20,4.0,neutral or dissatisfied +78443,47733,Female,Loyal Customer,37,Business travel,Business,3567,3,3,3,3,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +78444,114156,Female,Loyal Customer,51,Business travel,Business,846,2,2,2,2,4,5,5,1,1,2,1,4,1,4,7,0.0,satisfied +78445,24551,Female,Loyal Customer,40,Business travel,Business,2249,1,1,1,1,3,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +78446,24012,Female,Loyal Customer,42,Business travel,Eco,562,1,2,5,2,3,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +78447,52928,Male,Loyal Customer,64,Personal Travel,Eco,679,1,4,1,3,2,1,2,2,1,3,1,5,3,2,1,0.0,neutral or dissatisfied +78448,85736,Male,disloyal Customer,43,Business travel,Business,666,4,4,4,4,3,4,3,3,5,4,5,4,5,3,88,72.0,satisfied +78449,126886,Female,Loyal Customer,58,Personal Travel,Eco,2296,3,5,3,3,5,4,5,2,2,3,2,3,2,3,0,11.0,neutral or dissatisfied +78450,125192,Male,disloyal Customer,40,Business travel,Business,651,5,5,5,4,3,5,3,3,5,5,4,3,4,3,0,0.0,satisfied +78451,87030,Male,Loyal Customer,52,Business travel,Business,645,1,1,1,1,4,4,5,4,4,4,4,5,4,4,43,33.0,satisfied +78452,90769,Female,Loyal Customer,41,Business travel,Business,594,3,3,3,3,3,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +78453,63428,Female,Loyal Customer,60,Personal Travel,Eco,447,3,5,2,1,3,4,4,4,4,2,5,4,4,3,28,24.0,neutral or dissatisfied +78454,81536,Male,Loyal Customer,60,Business travel,Eco,724,3,5,5,5,3,3,3,3,4,5,3,4,3,3,2,8.0,neutral or dissatisfied +78455,7960,Male,Loyal Customer,34,Business travel,Business,2982,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,4.0,satisfied +78456,90739,Female,disloyal Customer,20,Business travel,Eco,250,2,4,2,3,2,2,2,2,3,2,4,3,4,2,0,0.0,neutral or dissatisfied +78457,92990,Female,Loyal Customer,62,Business travel,Business,2487,3,3,3,3,4,2,4,4,4,4,4,1,4,1,0,0.0,satisfied +78458,94735,Female,Loyal Customer,49,Business travel,Business,192,5,5,4,5,5,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +78459,49140,Male,Loyal Customer,40,Business travel,Business,109,2,2,2,2,3,4,3,4,4,4,5,2,4,5,0,0.0,satisfied +78460,100215,Female,Loyal Customer,32,Personal Travel,Eco,762,5,2,5,3,3,5,3,3,3,4,4,1,4,3,0,0.0,satisfied +78461,65473,Female,Loyal Customer,39,Business travel,Business,2113,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +78462,74423,Female,Loyal Customer,41,Business travel,Business,2572,5,5,5,5,5,4,5,3,3,3,3,5,3,3,11,26.0,satisfied +78463,123739,Male,disloyal Customer,33,Business travel,Business,96,3,3,3,2,1,3,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +78464,66180,Female,Loyal Customer,41,Business travel,Business,1796,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +78465,108267,Male,Loyal Customer,67,Personal Travel,Eco,895,2,4,2,1,3,2,3,3,4,4,1,3,2,3,0,5.0,neutral or dissatisfied +78466,65323,Male,disloyal Customer,24,Business travel,Business,432,5,5,5,3,3,5,3,3,3,2,5,4,4,3,0,0.0,satisfied +78467,111456,Female,Loyal Customer,31,Personal Travel,Eco,1024,3,4,3,4,4,3,4,4,4,4,2,1,3,4,67,57.0,neutral or dissatisfied +78468,71556,Female,disloyal Customer,25,Business travel,Business,1197,2,5,1,2,2,1,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +78469,36841,Male,Loyal Customer,67,Business travel,Business,369,2,3,3,3,4,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +78470,50924,Female,Loyal Customer,68,Personal Travel,Eco,109,3,4,0,4,2,4,5,4,4,0,4,3,4,3,25,19.0,neutral or dissatisfied +78471,69778,Female,disloyal Customer,36,Business travel,Eco,954,1,1,1,3,1,2,2,2,1,1,1,2,3,2,0,0.0,neutral or dissatisfied +78472,86133,Female,Loyal Customer,37,Business travel,Business,356,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +78473,98968,Female,Loyal Customer,66,Business travel,Business,2286,2,4,4,4,3,4,4,2,2,2,2,2,2,3,53,37.0,neutral or dissatisfied +78474,40638,Female,disloyal Customer,23,Business travel,Eco,411,2,3,2,3,2,2,2,2,3,1,2,4,1,2,0,0.0,neutral or dissatisfied +78475,80843,Male,Loyal Customer,42,Business travel,Business,3821,1,5,5,5,4,3,4,1,1,1,1,2,1,1,0,12.0,neutral or dissatisfied +78476,11383,Female,Loyal Customer,54,Business travel,Business,2923,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +78477,126015,Female,disloyal Customer,27,Business travel,Business,468,4,4,4,1,5,4,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +78478,108087,Male,Loyal Customer,43,Business travel,Business,997,1,1,4,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +78479,38420,Female,Loyal Customer,22,Business travel,Business,965,1,1,3,1,5,5,5,5,5,2,1,5,4,5,60,61.0,satisfied +78480,96372,Male,Loyal Customer,30,Business travel,Business,3791,5,5,4,5,2,2,2,2,4,5,5,5,4,2,0,3.0,satisfied +78481,128150,Female,Loyal Customer,43,Business travel,Business,1788,3,3,3,3,3,4,5,5,5,5,5,4,5,3,12,11.0,satisfied +78482,80300,Female,Loyal Customer,22,Business travel,Business,746,3,5,5,5,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +78483,108535,Female,Loyal Customer,37,Personal Travel,Eco,649,3,1,3,4,5,3,5,5,1,3,4,2,3,5,0,2.0,neutral or dissatisfied +78484,66911,Male,Loyal Customer,39,Business travel,Business,3267,3,3,3,3,2,5,5,5,5,5,5,5,5,5,15,7.0,satisfied +78485,19232,Male,disloyal Customer,20,Business travel,Business,782,5,0,5,2,2,5,2,2,3,3,5,5,5,2,100,92.0,satisfied +78486,16481,Female,Loyal Customer,60,Business travel,Business,3814,1,1,1,1,4,5,4,5,5,5,4,4,5,4,1,0.0,satisfied +78487,39960,Male,Loyal Customer,63,Personal Travel,Eco,1086,1,2,1,2,2,1,2,2,3,3,2,4,3,2,90,78.0,neutral or dissatisfied +78488,12524,Female,Loyal Customer,38,Business travel,Business,2977,2,3,1,3,4,4,4,2,2,2,2,4,2,4,12,7.0,neutral or dissatisfied +78489,47874,Male,Loyal Customer,9,Business travel,Business,2776,3,3,3,3,3,3,3,3,2,2,3,2,4,3,0,9.0,neutral or dissatisfied +78490,21776,Male,Loyal Customer,56,Business travel,Eco,352,5,4,4,4,5,5,5,5,2,3,3,1,1,5,0,2.0,satisfied +78491,49521,Male,Loyal Customer,42,Business travel,Eco,109,4,2,2,2,4,4,4,4,5,2,3,5,4,4,0,0.0,satisfied +78492,21142,Male,disloyal Customer,20,Business travel,Eco Plus,106,2,1,2,1,5,2,5,5,1,2,1,2,1,5,10,10.0,neutral or dissatisfied +78493,108931,Female,Loyal Customer,43,Personal Travel,Eco,1183,3,4,3,4,3,3,4,1,1,3,1,4,1,5,5,2.0,neutral or dissatisfied +78494,86853,Female,Loyal Customer,64,Personal Travel,Eco,484,3,3,3,4,5,4,3,4,4,3,4,1,4,3,4,4.0,neutral or dissatisfied +78495,100856,Male,Loyal Customer,44,Business travel,Business,3107,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +78496,20804,Female,Loyal Customer,46,Business travel,Business,457,5,5,5,5,1,3,4,4,4,5,4,3,4,4,14,15.0,satisfied +78497,118736,Male,Loyal Customer,51,Personal Travel,Eco,325,3,4,3,4,2,3,2,2,1,1,4,3,4,2,0,0.0,neutral or dissatisfied +78498,40875,Female,Loyal Customer,59,Personal Travel,Eco,501,3,4,4,3,2,5,5,1,1,4,1,3,1,5,0,9.0,neutral or dissatisfied +78499,44423,Male,Loyal Customer,25,Business travel,Business,542,4,4,4,4,3,3,3,3,3,5,4,3,5,3,0,0.0,satisfied +78500,103421,Male,Loyal Customer,40,Personal Travel,Eco,237,4,4,4,1,4,4,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +78501,18173,Female,Loyal Customer,33,Personal Travel,Eco,128,1,5,1,2,5,1,5,5,4,3,5,3,3,5,77,79.0,neutral or dissatisfied +78502,61105,Male,Loyal Customer,36,Personal Travel,Eco,1709,2,5,2,5,3,2,3,3,5,3,3,5,3,3,1,0.0,neutral or dissatisfied +78503,47236,Male,Loyal Customer,57,Personal Travel,Eco Plus,954,3,3,3,4,2,3,2,2,3,3,3,1,3,2,0,11.0,neutral or dissatisfied +78504,12131,Male,Loyal Customer,30,Personal Travel,Eco Plus,1034,2,4,2,2,5,2,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +78505,11779,Male,Loyal Customer,47,Personal Travel,Eco,429,2,5,2,2,4,2,4,4,4,3,1,5,4,4,5,6.0,neutral or dissatisfied +78506,10383,Female,disloyal Customer,56,Business travel,Business,158,1,1,1,2,3,1,3,3,3,4,5,5,4,3,47,49.0,neutral or dissatisfied +78507,128026,Male,disloyal Customer,21,Business travel,Eco,1440,1,2,2,1,1,1,1,1,5,2,2,1,3,1,139,139.0,neutral or dissatisfied +78508,78682,Male,disloyal Customer,29,Business travel,Business,761,3,3,3,1,2,3,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +78509,109106,Female,Loyal Customer,51,Personal Travel,Eco,849,4,4,4,5,4,4,5,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +78510,14049,Male,Loyal Customer,35,Business travel,Business,2321,1,1,1,1,4,1,3,4,4,4,4,2,4,4,0,6.0,satisfied +78511,15247,Female,Loyal Customer,21,Personal Travel,Eco,529,5,5,5,1,4,5,3,4,5,5,4,4,4,4,0,0.0,satisfied +78512,13063,Female,Loyal Customer,29,Business travel,Eco,936,4,1,1,1,4,4,4,1,3,3,5,4,4,4,195,184.0,satisfied +78513,25489,Female,Loyal Customer,40,Business travel,Business,2652,1,1,1,1,2,1,1,4,4,4,4,3,4,5,0,0.0,satisfied +78514,50469,Male,Loyal Customer,39,Business travel,Business,1819,1,5,5,5,3,1,2,1,1,1,1,4,1,4,105,127.0,neutral or dissatisfied +78515,95929,Female,Loyal Customer,71,Business travel,Eco,1011,2,2,2,2,4,5,4,2,2,2,2,5,2,2,0,0.0,satisfied +78516,57175,Male,disloyal Customer,20,Business travel,Eco,1383,3,3,3,3,5,3,5,5,4,5,4,4,3,5,0,0.0,neutral or dissatisfied +78517,56569,Female,Loyal Customer,43,Business travel,Business,1023,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,4.0,satisfied +78518,60206,Female,Loyal Customer,60,Business travel,Business,1546,5,5,5,5,3,4,5,5,5,5,5,5,5,3,4,0.0,satisfied +78519,76391,Male,Loyal Customer,7,Personal Travel,Eco,931,1,4,1,2,1,1,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +78520,122138,Male,Loyal Customer,59,Personal Travel,Business,544,5,5,5,1,4,5,5,3,3,5,3,2,3,3,0,4.0,satisfied +78521,94757,Female,disloyal Customer,38,Business travel,Business,248,2,2,2,4,4,2,4,4,5,4,4,5,5,4,0,0.0,satisfied +78522,109140,Male,disloyal Customer,18,Business travel,Eco,655,3,2,3,3,4,3,4,4,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +78523,108863,Male,Loyal Customer,22,Personal Travel,Eco,1947,3,4,3,5,1,3,1,1,4,5,5,3,4,1,6,0.0,neutral or dissatisfied +78524,119120,Male,Loyal Customer,21,Personal Travel,Eco,1107,2,4,2,5,5,2,1,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +78525,44107,Male,Loyal Customer,39,Personal Travel,Eco,473,3,3,3,3,2,3,5,2,1,1,3,3,3,2,0,4.0,neutral or dissatisfied +78526,92365,Female,Loyal Customer,59,Business travel,Business,1947,4,4,4,4,3,4,5,3,3,4,3,3,3,5,5,0.0,satisfied +78527,72348,Male,Loyal Customer,50,Business travel,Business,3447,3,3,3,3,4,5,5,4,4,4,4,3,4,4,8,0.0,satisfied +78528,121440,Male,Loyal Customer,50,Business travel,Business,331,0,1,1,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +78529,22902,Male,Loyal Customer,50,Personal Travel,Eco Plus,147,2,4,2,3,3,2,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +78530,30394,Male,Loyal Customer,42,Personal Travel,Eco,775,5,5,5,2,2,5,2,2,5,3,3,2,2,2,0,0.0,satisfied +78531,41058,Female,disloyal Customer,39,Business travel,Eco Plus,686,3,3,3,1,1,3,1,1,2,2,2,4,1,1,0,0.0,neutral or dissatisfied +78532,63413,Male,Loyal Customer,34,Personal Travel,Eco,337,4,4,4,3,2,4,2,2,1,4,1,1,5,2,29,31.0,neutral or dissatisfied +78533,128514,Male,Loyal Customer,35,Personal Travel,Eco,646,3,1,3,3,3,3,3,3,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +78534,80932,Female,Loyal Customer,67,Personal Travel,Eco,341,3,5,3,3,2,5,5,2,2,3,2,3,2,5,0,27.0,neutral or dissatisfied +78535,106880,Male,Loyal Customer,66,Business travel,Business,577,4,3,3,3,3,4,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +78536,102563,Female,Loyal Customer,41,Business travel,Business,2874,0,0,0,4,2,5,5,1,1,1,1,4,1,3,57,42.0,satisfied +78537,110238,Female,Loyal Customer,56,Business travel,Eco,1147,4,1,3,3,5,3,3,4,4,4,4,3,4,2,44,36.0,neutral or dissatisfied +78538,128900,Male,Loyal Customer,19,Personal Travel,Eco,2454,4,2,4,4,4,5,5,3,2,3,4,5,2,5,0,0.0,neutral or dissatisfied +78539,16906,Male,Loyal Customer,69,Personal Travel,Eco,746,3,4,3,5,5,3,5,5,4,4,5,5,5,5,13,4.0,neutral or dissatisfied +78540,42320,Male,Loyal Customer,24,Personal Travel,Eco,329,2,4,2,3,2,2,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +78541,82439,Female,Loyal Customer,33,Business travel,Business,502,1,1,1,1,5,3,3,1,1,1,1,3,1,2,9,7.0,neutral or dissatisfied +78542,16689,Female,Loyal Customer,58,Business travel,Business,2563,5,5,5,5,4,5,4,4,4,4,5,5,4,5,0,0.0,satisfied +78543,38907,Female,Loyal Customer,30,Business travel,Business,205,0,5,0,4,2,2,2,2,3,5,3,3,4,2,0,0.0,satisfied +78544,74173,Male,Loyal Customer,7,Personal Travel,Eco,592,3,5,4,1,4,4,4,4,3,4,2,5,1,4,0,0.0,neutral or dissatisfied +78545,16428,Female,Loyal Customer,51,Business travel,Eco,529,4,5,5,5,4,4,4,2,1,2,3,4,4,4,329,395.0,satisfied +78546,7386,Female,disloyal Customer,28,Business travel,Business,522,3,3,3,4,5,3,5,5,5,2,4,3,4,5,77,82.0,neutral or dissatisfied +78547,55492,Male,Loyal Customer,41,Business travel,Eco,1739,1,1,1,1,1,1,1,1,3,5,2,2,3,1,37,54.0,neutral or dissatisfied +78548,33794,Male,Loyal Customer,45,Business travel,Business,1428,4,4,4,4,2,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +78549,88922,Female,disloyal Customer,25,Business travel,Business,1199,5,5,5,3,1,5,1,1,5,4,4,3,4,1,11,0.0,satisfied +78550,107625,Female,Loyal Customer,35,Personal Travel,Eco,423,2,3,2,2,4,2,4,4,5,1,4,2,3,4,8,1.0,neutral or dissatisfied +78551,62330,Female,Loyal Customer,11,Personal Travel,Eco,414,1,3,1,1,5,1,5,5,3,2,1,2,2,5,40,29.0,neutral or dissatisfied +78552,64182,Female,Loyal Customer,60,Business travel,Business,1047,1,1,5,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +78553,101072,Male,Loyal Customer,50,Personal Travel,Eco Plus,368,3,2,3,3,4,3,4,4,2,3,4,2,4,4,106,99.0,neutral or dissatisfied +78554,91439,Female,disloyal Customer,37,Business travel,Eco,859,3,3,3,4,5,3,5,5,1,5,3,4,3,5,17,22.0,neutral or dissatisfied +78555,27040,Female,Loyal Customer,60,Personal Travel,Eco Plus,867,2,2,2,3,3,4,3,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +78556,101199,Male,Loyal Customer,34,Personal Travel,Eco,775,2,4,2,4,5,2,5,5,1,2,4,4,4,5,112,118.0,neutral or dissatisfied +78557,8637,Female,Loyal Customer,51,Business travel,Business,304,4,4,4,4,4,5,5,5,5,5,5,3,5,3,3,2.0,satisfied +78558,114434,Male,Loyal Customer,41,Business travel,Business,362,2,2,2,2,5,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +78559,78235,Female,Loyal Customer,44,Business travel,Business,3060,3,3,4,3,2,4,5,5,5,5,5,5,5,4,23,15.0,satisfied +78560,54701,Female,disloyal Customer,25,Business travel,Eco,454,2,3,2,4,1,2,1,1,5,2,3,5,5,1,15,9.0,neutral or dissatisfied +78561,28655,Male,Loyal Customer,64,Personal Travel,Eco,2409,4,3,5,4,5,5,5,5,1,3,1,5,4,5,0,0.0,neutral or dissatisfied +78562,6489,Male,disloyal Customer,40,Business travel,Business,557,1,0,0,3,4,0,4,4,4,5,5,3,4,4,1,5.0,neutral or dissatisfied +78563,54020,Female,Loyal Customer,27,Personal Travel,Eco,1091,4,5,4,3,4,4,1,4,1,4,3,2,4,4,7,0.0,neutral or dissatisfied +78564,77158,Male,Loyal Customer,29,Business travel,Business,1450,4,4,4,4,5,5,5,5,4,5,5,4,5,5,2,0.0,satisfied +78565,77560,Female,Loyal Customer,29,Business travel,Business,3895,5,5,5,5,4,4,4,4,5,5,5,4,5,4,77,58.0,satisfied +78566,21577,Male,Loyal Customer,68,Personal Travel,Eco Plus,399,4,4,4,5,4,4,1,4,4,4,5,5,4,4,4,4.0,neutral or dissatisfied +78567,47824,Female,disloyal Customer,26,Business travel,Eco,834,4,4,4,3,3,4,3,3,1,3,2,3,3,3,1,18.0,neutral or dissatisfied +78568,7486,Female,Loyal Customer,36,Business travel,Business,925,3,3,3,3,5,5,4,3,3,4,3,4,3,3,34,56.0,satisfied +78569,113963,Male,Loyal Customer,47,Business travel,Business,1706,1,1,1,1,4,5,5,5,5,5,5,3,5,3,0,14.0,satisfied +78570,83507,Female,Loyal Customer,67,Personal Travel,Eco,946,2,2,2,3,2,4,3,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +78571,54407,Female,Loyal Customer,46,Business travel,Business,3538,1,1,1,1,5,1,1,5,5,5,5,1,5,1,0,0.0,satisfied +78572,80158,Male,Loyal Customer,47,Business travel,Business,2586,3,4,4,4,3,3,3,2,5,2,2,3,3,3,30,4.0,neutral or dissatisfied +78573,735,Female,Loyal Customer,59,Business travel,Business,3085,2,2,2,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +78574,65138,Female,Loyal Customer,52,Personal Travel,Eco,551,3,2,2,3,1,3,3,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +78575,30182,Female,disloyal Customer,35,Business travel,Eco Plus,213,1,1,1,4,3,1,3,3,1,4,3,1,1,3,0,5.0,neutral or dissatisfied +78576,1638,Female,Loyal Customer,8,Personal Travel,Eco Plus,999,3,1,3,2,5,3,2,5,3,5,2,1,1,5,0,0.0,neutral or dissatisfied +78577,57946,Male,Loyal Customer,66,Personal Travel,Business,1062,3,3,3,2,5,5,2,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +78578,76963,Male,Loyal Customer,69,Personal Travel,Eco,1990,4,2,3,4,1,3,4,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +78579,23381,Male,Loyal Customer,28,Business travel,Eco Plus,1162,4,3,3,3,4,4,4,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +78580,12422,Female,disloyal Customer,68,Personal Travel,Eco,192,3,5,0,3,1,0,4,1,4,3,5,3,4,1,84,73.0,neutral or dissatisfied +78581,38057,Male,Loyal Customer,31,Business travel,Business,3737,5,5,5,5,4,4,4,4,2,2,3,4,3,4,70,59.0,satisfied +78582,43397,Male,Loyal Customer,49,Personal Travel,Eco,387,4,4,4,5,3,4,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +78583,3451,Female,Loyal Customer,27,Personal Travel,Eco,213,2,0,0,4,3,0,2,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +78584,11750,Male,disloyal Customer,39,Business travel,Eco,395,2,2,2,3,3,2,3,3,4,5,3,1,4,3,59,57.0,neutral or dissatisfied +78585,14759,Female,Loyal Customer,42,Business travel,Business,533,3,4,4,4,2,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +78586,45584,Male,Loyal Customer,42,Business travel,Eco,230,4,1,1,1,4,4,4,4,5,4,4,4,5,4,53,47.0,satisfied +78587,121940,Female,Loyal Customer,50,Business travel,Business,2360,0,0,0,1,2,5,5,4,4,4,4,5,4,3,13,17.0,satisfied +78588,80806,Female,Loyal Customer,43,Business travel,Business,2279,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +78589,113006,Female,Loyal Customer,31,Personal Travel,Eco,1797,2,3,2,1,2,2,2,2,4,1,3,2,5,2,90,73.0,neutral or dissatisfied +78590,127519,Male,disloyal Customer,42,Business travel,Business,1009,2,2,2,3,2,2,2,2,5,2,5,5,4,2,10,0.0,neutral or dissatisfied +78591,69401,Female,Loyal Customer,56,Business travel,Eco,1096,2,2,2,2,5,3,3,2,2,2,2,4,2,4,8,0.0,neutral or dissatisfied +78592,6625,Male,Loyal Customer,57,Business travel,Business,719,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +78593,12190,Male,Loyal Customer,16,Personal Travel,Eco,1075,5,2,5,3,4,5,4,4,3,5,3,2,4,4,0,0.0,satisfied +78594,9030,Male,Loyal Customer,49,Business travel,Business,2383,5,5,5,5,2,5,5,5,5,5,5,4,5,4,29,43.0,satisfied +78595,31235,Female,Loyal Customer,35,Business travel,Eco,472,5,2,2,2,5,5,5,5,2,2,5,5,4,5,0,1.0,satisfied +78596,11129,Female,Loyal Customer,29,Personal Travel,Eco,270,1,1,1,3,5,1,2,5,1,3,4,2,4,5,46,46.0,neutral or dissatisfied +78597,19869,Male,disloyal Customer,37,Business travel,Business,296,4,4,4,1,1,4,1,1,5,4,5,5,5,1,36,36.0,satisfied +78598,16297,Female,Loyal Customer,52,Personal Travel,Eco Plus,748,3,5,3,1,3,4,5,3,3,3,3,5,3,3,115,124.0,neutral or dissatisfied +78599,8304,Male,Loyal Customer,42,Business travel,Business,3592,3,3,3,3,5,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +78600,17899,Female,Loyal Customer,42,Business travel,Business,789,4,4,4,4,2,2,2,4,5,5,4,2,4,2,137,125.0,satisfied +78601,20220,Male,disloyal Customer,23,Business travel,Eco,179,4,0,4,1,1,4,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +78602,117360,Male,Loyal Customer,35,Business travel,Business,296,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +78603,121802,Female,Loyal Customer,43,Business travel,Business,2075,1,1,1,1,2,4,4,5,5,5,5,3,5,4,50,31.0,satisfied +78604,125955,Male,Loyal Customer,58,Business travel,Business,992,1,1,1,1,3,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +78605,10760,Male,disloyal Customer,23,Business travel,Business,216,0,0,0,4,1,0,1,1,3,5,5,3,4,1,0,0.0,satisfied +78606,78882,Female,disloyal Customer,20,Business travel,Eco,223,3,0,3,1,5,3,5,5,3,4,4,4,5,5,3,0.0,neutral or dissatisfied +78607,62790,Male,Loyal Customer,31,Personal Travel,Eco,2447,1,0,1,4,2,1,2,2,4,1,4,5,5,2,2,0.0,neutral or dissatisfied +78608,111895,Female,Loyal Customer,27,Personal Travel,Eco,628,1,4,1,2,3,1,3,3,3,3,4,5,5,3,60,53.0,neutral or dissatisfied +78609,120762,Male,disloyal Customer,27,Business travel,Business,678,1,1,1,4,3,1,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +78610,46562,Female,Loyal Customer,34,Business travel,Eco,125,4,2,2,2,4,4,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +78611,78996,Female,Loyal Customer,55,Business travel,Business,356,1,1,1,1,3,4,5,5,5,4,5,5,5,4,4,0.0,satisfied +78612,54039,Female,disloyal Customer,21,Business travel,Eco,1416,1,1,1,3,2,1,2,2,2,4,5,3,4,2,16,5.0,neutral or dissatisfied +78613,107324,Female,disloyal Customer,66,Business travel,Business,584,3,3,3,3,3,3,3,3,2,1,4,3,3,3,0,0.0,neutral or dissatisfied +78614,125965,Male,Loyal Customer,63,Business travel,Business,468,3,3,3,3,5,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +78615,117843,Female,Loyal Customer,29,Business travel,Business,2133,4,4,4,4,2,2,2,2,3,5,4,4,4,2,5,0.0,satisfied +78616,20179,Male,Loyal Customer,50,Personal Travel,Eco,403,3,2,3,4,4,3,4,4,3,2,4,2,3,4,11,26.0,neutral or dissatisfied +78617,10766,Female,Loyal Customer,43,Business travel,Business,2430,5,5,5,5,5,4,4,5,5,5,4,3,5,3,3,6.0,satisfied +78618,110331,Female,Loyal Customer,51,Business travel,Business,3958,2,2,3,2,2,4,4,4,4,4,4,5,4,4,47,53.0,satisfied +78619,12853,Male,Loyal Customer,36,Personal Travel,Eco,641,3,4,3,3,3,3,2,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +78620,3328,Female,Loyal Customer,33,Business travel,Business,3227,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,7.0,satisfied +78621,66466,Male,Loyal Customer,23,Business travel,Eco Plus,1217,4,2,4,4,4,4,5,4,5,4,1,4,3,4,29,19.0,satisfied +78622,50877,Male,Loyal Customer,48,Personal Travel,Eco,308,3,3,3,3,1,3,4,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +78623,127998,Female,disloyal Customer,29,Business travel,Business,1488,2,2,2,5,2,2,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +78624,34426,Female,Loyal Customer,45,Personal Travel,Eco Plus,612,1,4,1,5,5,4,4,3,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +78625,61796,Male,Loyal Customer,22,Personal Travel,Eco,1635,3,2,3,4,4,3,4,4,3,3,4,4,3,4,30,7.0,neutral or dissatisfied +78626,63447,Male,Loyal Customer,45,Personal Travel,Eco,337,3,4,3,4,4,3,4,4,3,4,4,1,4,4,41,29.0,neutral or dissatisfied +78627,78578,Female,Loyal Customer,54,Business travel,Business,2663,2,4,3,4,2,3,4,2,2,2,2,4,2,4,34,41.0,neutral or dissatisfied +78628,34891,Female,Loyal Customer,39,Business travel,Business,2755,2,3,3,3,4,3,4,2,2,2,2,3,2,1,28,30.0,neutral or dissatisfied +78629,86569,Female,Loyal Customer,41,Business travel,Business,1729,1,1,5,1,3,4,4,3,3,4,3,4,3,3,100,87.0,satisfied +78630,121470,Female,Loyal Customer,29,Personal Travel,Eco,331,3,5,3,4,4,3,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +78631,116416,Male,Loyal Customer,63,Personal Travel,Eco,358,3,2,3,3,2,3,2,2,4,1,3,1,2,2,1,0.0,neutral or dissatisfied +78632,43847,Male,Loyal Customer,53,Business travel,Business,199,1,1,1,1,5,1,3,5,5,5,5,2,5,2,21,14.0,satisfied +78633,53194,Female,disloyal Customer,30,Business travel,Eco,612,3,1,3,4,3,3,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +78634,108680,Male,disloyal Customer,25,Business travel,Eco,577,3,3,3,4,2,3,2,2,3,4,4,3,4,2,6,0.0,neutral or dissatisfied +78635,10814,Female,Loyal Customer,31,Business travel,Business,216,1,3,4,4,4,4,1,4,1,1,3,4,3,4,81,71.0,neutral or dissatisfied +78636,104468,Male,Loyal Customer,29,Personal Travel,Eco,1123,1,3,1,3,1,1,1,1,2,4,1,1,2,1,13,21.0,neutral or dissatisfied +78637,102233,Female,Loyal Customer,37,Business travel,Business,1910,5,5,5,5,5,4,4,3,3,4,3,4,3,5,6,0.0,satisfied +78638,125407,Male,Loyal Customer,41,Business travel,Business,1440,1,1,1,1,2,4,4,2,2,2,2,4,2,3,5,0.0,satisfied +78639,51636,Female,disloyal Customer,27,Business travel,Eco,355,3,3,3,2,2,3,2,2,5,4,1,5,1,2,0,0.0,neutral or dissatisfied +78640,6898,Female,disloyal Customer,39,Business travel,Business,265,3,3,3,4,3,3,1,3,4,1,4,1,4,3,23,25.0,neutral or dissatisfied +78641,24821,Male,Loyal Customer,41,Business travel,Business,861,5,5,5,5,3,3,2,4,4,4,4,4,4,4,29,30.0,satisfied +78642,31612,Male,Loyal Customer,41,Business travel,Business,2504,1,1,5,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +78643,1806,Female,Loyal Customer,50,Business travel,Business,3782,4,4,4,4,5,4,3,4,4,4,4,1,4,1,3,4.0,neutral or dissatisfied +78644,1151,Male,Loyal Customer,40,Personal Travel,Eco,309,1,5,1,3,3,1,3,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +78645,119653,Female,disloyal Customer,34,Business travel,Eco,507,1,1,1,4,3,1,3,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +78646,96411,Male,Loyal Customer,38,Personal Travel,Eco,1246,5,5,5,5,4,5,4,4,4,4,5,3,5,4,0,0.0,satisfied +78647,61727,Female,Loyal Customer,36,Business travel,Business,1518,2,2,2,2,3,4,5,3,3,3,3,1,3,2,0,0.0,satisfied +78648,83397,Male,disloyal Customer,26,Business travel,Business,632,3,4,4,1,1,4,1,1,4,3,5,4,4,1,3,0.0,neutral or dissatisfied +78649,30695,Female,disloyal Customer,41,Business travel,Business,280,3,3,3,4,4,3,4,4,1,3,4,1,3,4,9,17.0,neutral or dissatisfied +78650,71910,Female,Loyal Customer,32,Personal Travel,Eco,1744,3,0,3,2,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +78651,54855,Male,disloyal Customer,26,Business travel,Eco,862,4,4,4,4,2,4,4,2,3,1,4,2,3,2,23,12.0,neutral or dissatisfied +78652,76280,Male,Loyal Customer,16,Personal Travel,Eco,1927,4,4,4,3,1,4,1,1,5,5,3,3,4,1,0,0.0,satisfied +78653,35060,Female,Loyal Customer,48,Business travel,Business,2812,1,4,4,4,5,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +78654,54358,Female,Loyal Customer,35,Business travel,Eco,1235,4,4,5,4,4,4,4,4,4,4,2,5,4,4,0,0.0,satisfied +78655,66047,Female,Loyal Customer,41,Business travel,Business,1345,2,2,2,2,1,4,3,2,2,1,2,1,2,3,7,5.0,neutral or dissatisfied +78656,94726,Male,Loyal Customer,43,Business travel,Business,2232,2,4,4,4,4,4,3,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +78657,94355,Female,Loyal Customer,42,Business travel,Business,3224,5,5,5,5,5,4,4,5,5,5,5,4,5,4,75,75.0,satisfied +78658,121831,Male,Loyal Customer,30,Business travel,Business,449,4,1,3,3,4,3,4,4,2,4,3,1,4,4,102,95.0,neutral or dissatisfied +78659,20239,Female,disloyal Customer,26,Business travel,Business,228,2,2,2,2,2,1,1,3,4,2,3,1,3,1,157,153.0,neutral or dissatisfied +78660,12002,Male,Loyal Customer,60,Business travel,Eco Plus,667,4,2,3,3,4,4,4,4,5,1,1,3,1,4,1,0.0,satisfied +78661,22347,Female,Loyal Customer,35,Business travel,Eco,143,3,2,1,2,3,4,3,3,3,1,2,5,4,3,3,0.0,satisfied +78662,113635,Female,Loyal Customer,46,Personal Travel,Eco,226,3,4,3,3,5,5,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +78663,120660,Female,Loyal Customer,17,Business travel,Eco,280,2,3,3,3,2,2,3,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +78664,91591,Male,Loyal Customer,58,Business travel,Business,1199,2,3,3,3,1,4,3,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +78665,35217,Male,disloyal Customer,49,Business travel,Eco,1047,3,3,3,1,3,2,2,4,2,3,5,2,3,2,229,240.0,satisfied +78666,95943,Female,Loyal Customer,54,Business travel,Business,795,1,1,1,1,2,5,4,4,4,4,4,5,4,4,37,32.0,satisfied +78667,2714,Male,Loyal Customer,65,Personal Travel,Eco,562,3,4,3,4,2,3,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +78668,106753,Male,disloyal Customer,62,Business travel,Eco,545,4,4,4,3,1,4,1,1,1,1,3,4,4,1,0,6.0,neutral or dissatisfied +78669,119318,Female,Loyal Customer,45,Personal Travel,Eco,214,3,2,3,4,5,3,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +78670,59223,Male,Loyal Customer,61,Business travel,Eco Plus,1040,4,5,5,5,4,4,4,4,4,3,2,5,4,4,26,17.0,satisfied +78671,68425,Male,Loyal Customer,14,Personal Travel,Eco,1045,4,1,4,3,1,4,1,1,2,4,2,2,3,1,0,0.0,neutral or dissatisfied +78672,63053,Female,Loyal Customer,11,Personal Travel,Eco,862,2,3,2,3,1,2,1,1,1,1,4,4,3,1,7,0.0,neutral or dissatisfied +78673,28887,Female,Loyal Customer,23,Business travel,Business,2291,5,5,5,5,5,5,5,5,3,3,4,5,5,5,98,98.0,satisfied +78674,54637,Male,disloyal Customer,25,Business travel,Eco,965,3,3,3,5,1,3,1,1,1,2,5,3,1,1,0,0.0,neutral or dissatisfied +78675,64180,Female,Loyal Customer,60,Business travel,Business,3607,3,3,3,3,4,5,5,5,5,5,5,3,5,3,92,94.0,satisfied +78676,41489,Male,Loyal Customer,44,Business travel,Business,1428,3,3,2,3,4,4,5,4,4,4,4,5,4,2,88,69.0,satisfied +78677,87371,Male,Loyal Customer,59,Business travel,Business,3933,3,3,3,3,5,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +78678,115753,Female,Loyal Customer,52,Business travel,Business,480,2,3,3,3,4,3,4,2,2,2,2,3,2,3,22,15.0,neutral or dissatisfied +78679,121033,Female,Loyal Customer,56,Personal Travel,Eco,993,3,5,3,3,4,4,5,5,5,3,5,4,5,4,27,64.0,neutral or dissatisfied +78680,72170,Male,Loyal Customer,45,Business travel,Business,594,1,4,4,4,4,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +78681,6708,Male,Loyal Customer,12,Personal Travel,Eco,438,1,5,1,4,2,1,2,2,5,3,4,4,3,2,0,1.0,neutral or dissatisfied +78682,16458,Female,Loyal Customer,37,Personal Travel,Eco,529,3,4,3,1,4,3,4,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +78683,124272,Female,disloyal Customer,22,Business travel,Business,601,5,4,5,3,1,5,1,1,4,3,4,3,4,1,0,0.0,satisfied +78684,51085,Male,Loyal Customer,60,Personal Travel,Eco,238,1,4,1,2,2,1,2,2,4,2,4,5,4,2,2,0.0,neutral or dissatisfied +78685,88032,Female,Loyal Customer,52,Business travel,Business,545,5,5,5,5,5,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +78686,39350,Male,Loyal Customer,63,Business travel,Business,3729,1,1,5,1,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +78687,33333,Female,disloyal Customer,25,Business travel,Eco,1358,2,2,2,3,1,2,1,1,1,2,3,5,2,1,3,15.0,neutral or dissatisfied +78688,65820,Female,Loyal Customer,41,Business travel,Business,1389,5,5,5,5,5,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +78689,48257,Female,Loyal Customer,46,Personal Travel,Eco,236,2,5,2,4,4,2,4,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +78690,30197,Male,Loyal Customer,37,Business travel,Eco Plus,123,5,1,1,1,5,5,5,5,4,4,5,1,3,5,0,0.0,satisfied +78691,89660,Male,Loyal Customer,56,Business travel,Business,1765,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +78692,116285,Female,Loyal Customer,44,Personal Travel,Eco,308,4,4,2,1,2,2,2,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +78693,2107,Male,Loyal Customer,35,Personal Travel,Eco,812,2,5,2,4,5,2,5,5,3,1,3,5,3,5,47,33.0,neutral or dissatisfied +78694,70797,Male,Loyal Customer,30,Personal Travel,Eco,328,3,0,3,2,4,3,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +78695,8081,Female,Loyal Customer,47,Business travel,Business,294,2,2,2,2,4,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +78696,110908,Male,disloyal Customer,37,Business travel,Eco,404,3,4,3,4,4,3,4,4,1,4,3,3,3,4,10,6.0,neutral or dissatisfied +78697,99971,Female,Loyal Customer,18,Personal Travel,Eco,888,2,5,2,4,4,2,4,4,3,2,4,3,4,4,14,0.0,neutral or dissatisfied +78698,74710,Female,Loyal Customer,66,Personal Travel,Eco,1171,2,5,2,4,5,5,4,3,3,2,3,3,3,5,7,0.0,neutral or dissatisfied +78699,89751,Female,Loyal Customer,37,Personal Travel,Eco,1035,3,5,3,3,1,3,1,1,4,2,4,4,5,1,0,,neutral or dissatisfied +78700,129440,Female,Loyal Customer,65,Personal Travel,Eco,414,0,3,0,4,3,3,3,3,3,0,3,4,3,2,0,0.0,satisfied +78701,110150,Male,disloyal Customer,29,Business travel,Eco,979,3,2,2,3,3,2,3,3,4,5,3,1,3,3,0,4.0,neutral or dissatisfied +78702,54289,Female,Loyal Customer,55,Business travel,Eco,1075,4,3,3,3,1,3,4,4,4,4,4,5,4,4,2,1.0,satisfied +78703,21771,Female,Loyal Customer,42,Business travel,Business,3558,0,0,0,3,2,3,1,3,3,3,3,5,3,2,0,0.0,satisfied +78704,5880,Male,Loyal Customer,27,Business travel,Business,1917,4,4,4,4,4,5,4,4,3,4,5,5,5,4,87,99.0,satisfied +78705,39500,Female,disloyal Customer,23,Business travel,Eco,1068,1,1,1,3,5,1,5,5,2,3,4,3,2,5,0,0.0,neutral or dissatisfied +78706,109776,Female,Loyal Customer,55,Business travel,Business,971,1,3,3,3,4,1,1,1,1,1,1,3,1,2,15,0.0,neutral or dissatisfied +78707,53733,Female,Loyal Customer,9,Personal Travel,Eco,1208,4,1,4,4,1,4,1,1,1,5,3,2,3,1,0,0.0,neutral or dissatisfied +78708,95456,Male,Loyal Customer,47,Business travel,Business,3689,5,5,5,5,4,4,4,4,5,4,4,4,5,4,150,141.0,satisfied +78709,21798,Female,disloyal Customer,49,Business travel,Eco,241,1,0,0,4,2,0,2,2,1,2,2,1,5,2,0,0.0,neutral or dissatisfied +78710,99384,Female,disloyal Customer,22,Business travel,Eco,337,3,0,3,5,1,3,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +78711,13354,Female,Loyal Customer,39,Business travel,Business,748,2,4,4,4,4,4,3,2,2,2,2,4,2,4,21,9.0,neutral or dissatisfied +78712,73658,Male,Loyal Customer,47,Business travel,Business,2233,4,4,4,4,5,5,5,5,5,5,4,4,5,4,0,3.0,satisfied +78713,25202,Female,Loyal Customer,22,Business travel,Eco,842,0,5,0,1,3,0,3,3,4,1,5,1,4,3,37,56.0,satisfied +78714,56405,Female,Loyal Customer,47,Business travel,Business,3919,3,4,3,3,5,5,4,5,5,5,5,3,5,4,0,9.0,satisfied +78715,124603,Female,Loyal Customer,27,Business travel,Eco Plus,500,1,4,4,4,1,1,1,1,2,5,2,3,2,1,79,71.0,neutral or dissatisfied +78716,88057,Female,Loyal Customer,15,Business travel,Business,2117,1,1,1,1,3,4,3,3,3,4,5,5,5,3,0,0.0,satisfied +78717,2600,Male,Loyal Customer,65,Personal Travel,Eco,227,4,5,4,4,4,4,4,4,4,4,4,4,4,4,9,20.0,neutral or dissatisfied +78718,81004,Male,Loyal Customer,27,Personal Travel,Eco,228,2,5,2,4,2,2,2,2,5,4,5,4,4,2,125,122.0,neutral or dissatisfied +78719,29626,Male,disloyal Customer,57,Business travel,Business,1133,3,4,4,3,4,3,3,4,4,1,3,3,5,4,0,0.0,neutral or dissatisfied +78720,118688,Male,Loyal Customer,41,Personal Travel,Eco,304,4,4,4,3,5,4,5,5,5,4,5,4,4,5,2,6.0,satisfied +78721,43532,Male,Loyal Customer,42,Business travel,Business,920,2,4,4,4,5,2,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +78722,69957,Female,Loyal Customer,10,Personal Travel,Eco,2174,2,3,2,3,4,2,4,4,4,3,3,2,4,4,0,4.0,neutral or dissatisfied +78723,77548,Female,Loyal Customer,37,Business travel,Eco,586,3,1,1,1,3,2,3,3,3,3,3,1,3,3,128,126.0,neutral or dissatisfied +78724,84838,Female,Loyal Customer,31,Business travel,Business,2684,3,3,3,3,4,4,4,4,3,4,4,4,5,4,0,5.0,satisfied +78725,20515,Male,disloyal Customer,48,Business travel,Business,773,5,5,5,2,1,5,1,1,5,2,5,5,4,1,3,15.0,satisfied +78726,120461,Male,Loyal Customer,56,Personal Travel,Eco,449,1,5,1,1,4,1,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +78727,25590,Male,Loyal Customer,35,Personal Travel,Eco,696,3,4,3,4,5,3,4,5,5,2,5,5,4,5,6,0.0,neutral or dissatisfied +78728,16774,Male,disloyal Customer,25,Business travel,Eco,169,3,0,3,4,3,3,3,3,1,3,5,2,2,3,15,,neutral or dissatisfied +78729,28702,Male,Loyal Customer,53,Personal Travel,Eco,2172,3,4,3,3,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +78730,80113,Male,Loyal Customer,60,Personal Travel,Eco,1626,2,3,2,1,2,2,2,2,2,3,5,4,5,2,0,0.0,neutral or dissatisfied +78731,62844,Female,Loyal Customer,54,Personal Travel,Eco Plus,2504,4,1,3,3,3,5,5,4,4,3,4,5,2,5,0,0.0,neutral or dissatisfied +78732,32182,Male,disloyal Customer,27,Business travel,Business,216,4,4,4,5,4,4,4,4,2,1,4,4,1,4,0,0.0,satisfied +78733,13267,Female,Loyal Customer,51,Personal Travel,Eco,468,1,3,1,4,4,5,4,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +78734,1592,Female,Loyal Customer,20,Personal Travel,Eco,237,2,5,2,4,2,2,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +78735,94165,Male,Loyal Customer,52,Business travel,Business,239,4,4,4,4,5,4,5,5,5,5,5,5,5,3,28,30.0,satisfied +78736,27266,Male,Loyal Customer,23,Business travel,Business,956,2,2,2,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +78737,14338,Female,Loyal Customer,26,Personal Travel,Eco,429,3,3,5,3,2,5,2,2,3,5,2,4,3,2,0,1.0,neutral or dissatisfied +78738,60478,Male,Loyal Customer,51,Business travel,Business,862,5,5,4,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +78739,11741,Male,disloyal Customer,42,Business travel,Eco,395,2,1,2,1,2,2,2,2,1,4,2,3,2,2,0,0.0,neutral or dissatisfied +78740,20065,Female,Loyal Customer,38,Personal Travel,Eco,738,3,5,3,1,2,3,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +78741,75714,Female,Loyal Customer,41,Business travel,Business,2413,1,1,1,1,5,5,4,3,3,2,3,4,3,5,0,0.0,satisfied +78742,127289,Female,Loyal Customer,53,Business travel,Business,2911,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +78743,106506,Female,disloyal Customer,15,Business travel,Eco Plus,495,3,2,3,3,5,3,5,5,1,5,4,1,3,5,25,20.0,neutral or dissatisfied +78744,12654,Male,Loyal Customer,29,Business travel,Eco Plus,844,0,0,0,1,1,0,1,1,1,2,4,5,5,1,0,0.0,satisfied +78745,88513,Male,Loyal Customer,41,Business travel,Eco,145,5,2,2,2,5,5,5,5,1,3,3,2,4,5,0,0.0,satisfied +78746,4059,Female,Loyal Customer,18,Personal Travel,Eco,479,1,5,1,2,2,1,4,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +78747,96461,Male,disloyal Customer,18,Business travel,Eco,444,2,2,3,4,3,3,3,3,2,2,3,4,4,3,14,7.0,neutral or dissatisfied +78748,16978,Male,Loyal Customer,51,Business travel,Eco Plus,209,2,5,3,5,1,2,1,1,3,1,2,3,1,1,0,0.0,satisfied +78749,78754,Female,Loyal Customer,33,Business travel,Business,2257,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +78750,57130,Male,Loyal Customer,53,Personal Travel,Eco,1222,4,1,4,2,5,4,5,5,1,3,1,3,3,5,0,13.0,satisfied +78751,116345,Female,Loyal Customer,10,Personal Travel,Eco,337,2,5,2,3,4,2,4,4,3,1,3,5,3,4,51,38.0,neutral or dissatisfied +78752,99324,Female,Loyal Customer,47,Personal Travel,Eco,448,4,5,5,3,2,4,5,3,3,5,3,3,3,4,0,0.0,neutral or dissatisfied +78753,125145,Male,disloyal Customer,30,Business travel,Eco,1999,3,2,2,2,3,3,3,3,3,5,1,3,2,3,4,0.0,neutral or dissatisfied +78754,124495,Female,disloyal Customer,38,Business travel,Business,930,3,3,3,3,1,3,1,1,5,4,4,5,4,1,1,0.0,neutral or dissatisfied +78755,47812,Female,Loyal Customer,39,Business travel,Business,3833,4,4,4,4,3,4,5,4,4,5,4,4,4,3,0,3.0,satisfied +78756,79931,Male,disloyal Customer,23,Business travel,Eco,944,1,1,1,4,3,1,3,3,1,5,4,3,4,3,0,8.0,neutral or dissatisfied +78757,17598,Female,Loyal Customer,7,Personal Travel,Eco,700,3,5,3,5,3,3,3,3,1,1,4,4,2,3,79,71.0,neutral or dissatisfied +78758,73666,Female,Loyal Customer,57,Business travel,Business,2550,5,5,5,5,5,5,4,5,5,5,5,4,5,4,86,87.0,satisfied +78759,99093,Female,Loyal Customer,50,Business travel,Business,2582,5,5,5,5,2,4,4,4,4,4,4,3,4,3,6,2.0,satisfied +78760,31638,Female,Loyal Customer,63,Business travel,Eco,862,4,5,5,5,1,2,1,4,4,4,4,3,4,3,0,0.0,satisfied +78761,67260,Female,Loyal Customer,27,Personal Travel,Eco,964,1,4,1,4,2,1,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +78762,87876,Female,Loyal Customer,56,Business travel,Business,214,3,3,3,3,5,5,4,4,4,4,5,3,4,3,4,5.0,satisfied +78763,91859,Male,Loyal Customer,61,Personal Travel,Eco Plus,1619,3,5,3,2,1,3,1,1,4,5,5,5,5,1,4,0.0,neutral or dissatisfied +78764,53393,Male,Loyal Customer,13,Personal Travel,Eco Plus,1452,1,4,1,3,2,1,2,2,1,2,4,1,1,2,0,0.0,neutral or dissatisfied +78765,5498,Male,disloyal Customer,15,Business travel,Eco,910,2,2,2,4,5,2,1,5,4,3,4,2,3,5,9,15.0,neutral or dissatisfied +78766,93011,Male,disloyal Customer,23,Business travel,Business,1524,5,5,5,2,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +78767,55855,Female,Loyal Customer,45,Business travel,Eco Plus,1416,2,4,4,4,5,4,3,2,2,2,2,2,2,3,4,0.0,neutral or dissatisfied +78768,82876,Male,Loyal Customer,54,Business travel,Business,645,4,4,4,4,3,4,5,2,2,2,2,4,2,4,0,3.0,satisfied +78769,119985,Male,Loyal Customer,22,Business travel,Business,1591,4,4,4,4,2,2,2,2,3,3,5,3,5,2,0,0.0,satisfied +78770,128020,Female,Loyal Customer,36,Business travel,Business,1440,2,2,4,2,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +78771,24424,Female,Loyal Customer,31,Business travel,Business,634,1,2,2,2,1,1,1,1,3,3,3,3,4,1,45,53.0,neutral or dissatisfied +78772,106087,Male,disloyal Customer,40,Business travel,Business,302,4,4,4,5,5,4,5,5,3,5,4,3,5,5,17,10.0,satisfied +78773,64497,Male,Loyal Customer,49,Business travel,Business,551,2,4,4,4,5,4,3,2,2,2,2,4,2,1,52,32.0,neutral or dissatisfied +78774,126123,Male,disloyal Customer,22,Business travel,Business,507,0,0,0,1,3,0,3,3,4,2,5,4,4,3,9,3.0,satisfied +78775,51071,Male,Loyal Customer,13,Personal Travel,Eco,156,1,3,0,3,4,0,4,4,4,4,3,2,4,4,2,16.0,neutral or dissatisfied +78776,68335,Male,Loyal Customer,28,Business travel,Business,1598,5,5,5,5,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +78777,50396,Male,Loyal Customer,42,Business travel,Business,2465,1,1,1,1,3,3,5,4,4,4,3,4,4,5,0,3.0,satisfied +78778,66033,Female,disloyal Customer,36,Business travel,Business,1055,4,4,4,4,1,4,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +78779,3818,Female,disloyal Customer,36,Business travel,Business,650,3,3,3,3,4,3,2,4,5,4,5,3,5,4,15,13.0,neutral or dissatisfied +78780,127401,Male,Loyal Customer,58,Business travel,Business,2043,4,4,4,4,3,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +78781,89510,Female,Loyal Customer,60,Business travel,Business,1089,2,4,3,4,5,4,4,2,2,2,2,1,2,4,65,47.0,neutral or dissatisfied +78782,4124,Female,Loyal Customer,62,Business travel,Eco,431,3,4,4,4,4,4,4,3,3,3,3,2,3,4,0,14.0,neutral or dissatisfied +78783,77198,Female,Loyal Customer,59,Business travel,Eco Plus,290,1,0,0,3,3,4,4,2,2,1,2,3,2,3,12,11.0,neutral or dissatisfied +78784,55535,Female,Loyal Customer,58,Business travel,Business,550,3,3,3,3,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +78785,17902,Male,Loyal Customer,25,Business travel,Business,2944,4,4,4,4,4,4,4,4,3,5,2,3,3,4,0,0.0,satisfied +78786,22476,Male,Loyal Customer,69,Personal Travel,Eco,143,1,5,1,1,3,1,3,3,5,5,3,5,5,3,0,0.0,neutral or dissatisfied +78787,65928,Male,Loyal Customer,41,Personal Travel,Eco,569,4,4,4,3,4,4,3,4,5,2,4,4,3,4,14,24.0,neutral or dissatisfied +78788,19670,Female,disloyal Customer,22,Business travel,Business,409,2,1,2,2,1,2,1,1,3,5,2,1,1,1,5,6.0,neutral or dissatisfied +78789,50385,Female,Loyal Customer,21,Business travel,Business,372,2,5,5,5,2,2,2,2,1,2,4,2,3,2,0,13.0,neutral or dissatisfied +78790,62374,Male,Loyal Customer,57,Business travel,Business,2704,3,3,3,3,3,5,4,2,2,2,2,5,2,4,6,0.0,satisfied +78791,73313,Male,Loyal Customer,56,Business travel,Business,2099,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,1.0,satisfied +78792,45763,Male,Loyal Customer,45,Business travel,Eco,391,1,4,4,4,1,1,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +78793,89455,Female,Loyal Customer,37,Personal Travel,Eco,151,3,4,0,5,5,0,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +78794,2131,Female,Loyal Customer,49,Business travel,Eco,431,2,3,3,3,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +78795,87407,Female,Loyal Customer,41,Personal Travel,Eco,425,4,0,2,5,3,2,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +78796,62624,Male,Loyal Customer,14,Personal Travel,Eco,1781,3,4,3,2,3,3,3,3,3,3,3,3,5,3,18,2.0,neutral or dissatisfied +78797,114557,Male,Loyal Customer,56,Personal Travel,Business,373,1,5,1,1,2,4,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +78798,55134,Female,Loyal Customer,27,Personal Travel,Eco,1379,3,5,3,5,2,3,2,2,5,2,4,5,5,2,22,0.0,neutral or dissatisfied +78799,67397,Female,Loyal Customer,46,Business travel,Eco,592,4,1,1,1,2,2,2,4,4,4,4,2,4,3,1,0.0,neutral or dissatisfied +78800,54507,Female,disloyal Customer,38,Business travel,Eco,525,1,0,1,5,5,1,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +78801,68310,Female,Loyal Customer,40,Business travel,Business,2165,3,3,3,3,4,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +78802,87380,Male,Loyal Customer,39,Business travel,Eco,425,3,4,4,4,3,3,3,3,2,4,3,3,2,3,0,0.0,neutral or dissatisfied +78803,74696,Male,Loyal Customer,44,Personal Travel,Eco,1188,3,4,4,3,1,4,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +78804,107756,Male,Loyal Customer,24,Personal Travel,Eco,405,3,1,3,3,3,3,3,3,3,2,4,1,3,3,11,1.0,neutral or dissatisfied +78805,91615,Female,Loyal Customer,58,Business travel,Business,1736,4,4,5,4,5,4,4,5,5,5,5,4,5,3,7,5.0,satisfied +78806,118502,Male,Loyal Customer,55,Business travel,Business,3528,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +78807,105132,Male,Loyal Customer,28,Business travel,Business,281,1,5,5,5,1,1,1,1,1,4,4,4,3,1,9,13.0,neutral or dissatisfied +78808,39181,Male,Loyal Customer,9,Personal Travel,Eco,237,1,4,0,3,4,0,4,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +78809,71309,Male,Loyal Customer,45,Business travel,Business,1514,3,3,2,3,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +78810,125476,Female,Loyal Customer,14,Personal Travel,Eco,2917,3,2,3,2,3,3,3,3,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +78811,36319,Female,disloyal Customer,49,Business travel,Eco,187,1,4,1,4,4,1,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +78812,51088,Male,Loyal Customer,57,Personal Travel,Eco,77,2,5,2,3,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +78813,9665,Male,disloyal Customer,39,Business travel,Business,277,4,4,4,1,3,4,3,3,4,4,4,3,4,3,0,0.0,satisfied +78814,47449,Female,disloyal Customer,19,Business travel,Eco,584,2,4,2,3,1,2,1,1,2,4,4,1,4,1,0,0.0,neutral or dissatisfied +78815,83804,Female,Loyal Customer,33,Business travel,Business,2763,3,3,3,3,5,4,5,5,5,5,5,4,5,4,12,10.0,satisfied +78816,43728,Male,Loyal Customer,52,Business travel,Eco Plus,257,3,1,5,1,3,3,3,3,2,1,3,4,3,3,83,79.0,neutral or dissatisfied +78817,123590,Male,Loyal Customer,42,Personal Travel,Eco,1773,3,3,3,3,5,3,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +78818,107359,Female,Loyal Customer,18,Personal Travel,Eco,584,3,4,3,2,3,3,3,3,3,4,5,4,5,3,43,47.0,neutral or dissatisfied +78819,44923,Female,Loyal Customer,45,Business travel,Eco Plus,466,4,5,5,5,3,5,4,4,4,4,4,5,4,5,40,76.0,satisfied +78820,50850,Female,Loyal Customer,38,Personal Travel,Eco,86,1,5,1,3,3,1,3,3,1,2,2,3,2,3,6,0.0,neutral or dissatisfied +78821,70410,Female,Loyal Customer,53,Personal Travel,Eco,1562,1,1,1,1,3,1,1,1,1,1,1,4,1,2,0,24.0,neutral or dissatisfied +78822,95918,Female,Loyal Customer,46,Business travel,Business,1411,1,1,1,1,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +78823,97270,Female,Loyal Customer,46,Business travel,Business,296,1,1,1,1,3,4,5,4,4,4,4,4,4,5,50,60.0,satisfied +78824,8861,Male,Loyal Customer,47,Business travel,Business,539,5,5,5,5,2,4,4,3,3,3,3,4,3,5,8,2.0,satisfied +78825,4181,Female,Loyal Customer,18,Personal Travel,Eco,431,1,5,3,2,4,3,4,4,4,3,4,3,4,4,0,11.0,neutral or dissatisfied +78826,79531,Female,Loyal Customer,18,Business travel,Business,2134,4,4,4,4,5,5,5,5,3,2,4,4,5,5,0,11.0,satisfied +78827,75755,Female,Loyal Customer,53,Business travel,Eco,468,4,1,4,1,5,2,5,4,4,4,4,5,4,5,0,0.0,satisfied +78828,128401,Female,Loyal Customer,62,Business travel,Business,2679,3,4,2,4,4,2,3,3,3,3,3,3,3,1,11,7.0,neutral or dissatisfied +78829,96563,Male,disloyal Customer,23,Business travel,Eco,333,4,0,5,3,4,5,4,4,4,3,4,4,4,4,2,0.0,satisfied +78830,90725,Male,Loyal Customer,55,Business travel,Business,240,2,5,5,5,2,2,2,1,1,2,3,2,3,2,163,153.0,neutral or dissatisfied +78831,108838,Female,Loyal Customer,46,Personal Travel,Eco Plus,1199,2,3,2,1,1,1,2,3,3,2,3,3,3,4,0,4.0,neutral or dissatisfied +78832,4587,Male,Loyal Customer,63,Business travel,Business,416,3,1,1,1,3,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +78833,44139,Male,disloyal Customer,47,Business travel,Eco,74,3,1,3,4,3,3,3,3,3,3,3,1,4,3,54,44.0,neutral or dissatisfied +78834,101936,Male,Loyal Customer,52,Business travel,Business,628,1,1,5,1,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +78835,29609,Male,disloyal Customer,32,Business travel,Eco,680,2,2,2,4,4,2,2,4,1,2,4,1,4,4,0,0.0,neutral or dissatisfied +78836,99542,Female,disloyal Customer,26,Business travel,Business,802,0,0,0,1,2,0,2,2,4,4,5,5,4,2,0,0.0,satisfied +78837,92694,Female,Loyal Customer,69,Personal Travel,Eco,507,2,4,2,4,4,4,3,2,2,2,2,2,2,4,24,27.0,neutral or dissatisfied +78838,10967,Male,Loyal Customer,59,Business travel,Business,429,1,1,1,1,5,1,5,4,4,4,4,2,4,3,48,49.0,satisfied +78839,102989,Female,Loyal Customer,19,Business travel,Business,3000,4,4,4,4,5,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +78840,55813,Female,disloyal Customer,24,Business travel,Eco,1416,2,3,3,1,1,2,1,1,3,4,5,3,5,1,12,0.0,satisfied +78841,6876,Male,Loyal Customer,54,Business travel,Business,3399,5,5,5,5,5,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +78842,54077,Male,Loyal Customer,56,Business travel,Business,1416,1,0,0,2,2,2,2,1,1,0,1,4,1,2,42,23.0,neutral or dissatisfied +78843,120627,Female,Loyal Customer,44,Business travel,Business,280,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +78844,120819,Male,Loyal Customer,70,Personal Travel,Eco,666,4,3,4,4,1,4,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +78845,64092,Male,Loyal Customer,30,Personal Travel,Eco,921,3,2,3,3,1,3,1,1,2,4,2,4,3,1,0,0.0,neutral or dissatisfied +78846,62846,Male,Loyal Customer,42,Business travel,Business,2399,1,1,1,1,3,5,4,4,4,4,4,3,4,5,6,0.0,satisfied +78847,129101,Female,Loyal Customer,40,Personal Travel,Eco,2218,3,5,3,1,2,3,3,2,1,4,2,4,5,2,1,0.0,neutral or dissatisfied +78848,97789,Male,disloyal Customer,38,Business travel,Eco,471,3,4,3,4,3,3,3,3,4,2,4,4,4,3,6,15.0,neutral or dissatisfied +78849,86884,Male,Loyal Customer,32,Personal Travel,Eco Plus,484,2,0,3,3,5,3,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +78850,124037,Female,Loyal Customer,14,Personal Travel,Eco,184,1,4,0,3,5,0,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +78851,41301,Female,Loyal Customer,13,Business travel,Business,2018,5,5,5,5,3,3,3,3,1,1,5,2,2,3,0,5.0,satisfied +78852,110634,Male,Loyal Customer,40,Business travel,Business,719,5,5,5,5,4,5,4,2,2,2,2,4,2,3,37,36.0,satisfied +78853,89212,Male,Loyal Customer,41,Personal Travel,Eco,2116,4,5,4,3,1,4,1,1,2,1,4,2,5,1,1,0.0,neutral or dissatisfied +78854,69065,Male,Loyal Customer,53,Business travel,Business,1389,1,2,2,2,4,4,3,1,1,1,1,4,1,3,0,9.0,neutral or dissatisfied +78855,76148,Male,Loyal Customer,42,Business travel,Business,546,2,2,2,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +78856,99469,Female,Loyal Customer,39,Business travel,Business,3572,3,3,3,3,4,5,4,5,5,5,5,3,5,5,62,57.0,satisfied +78857,33075,Male,Loyal Customer,13,Personal Travel,Eco,163,3,5,3,1,4,3,4,4,4,2,3,4,1,4,0,0.0,neutral or dissatisfied +78858,21747,Male,disloyal Customer,43,Business travel,Eco,163,1,3,1,2,4,1,2,4,3,4,3,4,5,4,43,33.0,neutral or dissatisfied +78859,7848,Female,Loyal Customer,51,Business travel,Business,1005,3,3,2,3,3,5,4,4,4,4,4,4,4,4,8,5.0,satisfied +78860,107740,Male,Loyal Customer,14,Personal Travel,Eco,405,4,5,4,3,3,4,3,3,2,4,3,1,4,3,30,37.0,neutral or dissatisfied +78861,128804,Female,Loyal Customer,43,Business travel,Business,2586,1,1,3,1,4,4,4,4,5,5,5,4,5,4,49,45.0,satisfied +78862,97169,Male,Loyal Customer,43,Personal Travel,Eco,1357,3,2,3,3,5,3,5,5,3,4,4,2,3,5,6,7.0,neutral or dissatisfied +78863,22145,Male,Loyal Customer,50,Business travel,Business,2391,1,2,2,2,1,1,1,2,2,3,3,1,2,1,120,144.0,neutral or dissatisfied +78864,115525,Male,Loyal Customer,41,Business travel,Business,3728,0,0,0,3,2,5,4,2,2,2,2,5,2,5,3,0.0,satisfied +78865,113221,Female,Loyal Customer,22,Business travel,Business,3278,5,5,5,5,5,5,5,5,3,2,4,4,4,5,15,5.0,satisfied +78866,122274,Female,Loyal Customer,24,Personal Travel,Eco,546,2,5,2,1,2,2,2,2,2,1,3,5,5,2,0,0.0,neutral or dissatisfied +78867,110655,Male,Loyal Customer,26,Business travel,Business,837,3,2,5,2,3,3,3,3,2,1,4,1,4,3,18,18.0,neutral or dissatisfied +78868,65906,Female,Loyal Customer,39,Business travel,Business,2117,2,2,2,2,5,4,4,3,3,3,3,5,3,3,0,15.0,satisfied +78869,81897,Male,Loyal Customer,38,Business travel,Business,1721,2,5,5,5,3,4,4,2,2,2,2,1,2,1,91,77.0,neutral or dissatisfied +78870,41218,Female,Loyal Customer,19,Personal Travel,Eco,1174,3,5,3,4,2,3,2,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +78871,91156,Female,Loyal Customer,42,Personal Travel,Eco,270,3,4,3,4,1,4,4,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +78872,18584,Female,Loyal Customer,33,Business travel,Eco,262,4,1,1,1,4,4,4,3,2,4,4,4,1,4,299,284.0,neutral or dissatisfied +78873,117928,Female,Loyal Customer,26,Business travel,Business,2274,3,5,5,5,3,3,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +78874,80114,Male,Loyal Customer,45,Personal Travel,Eco,1626,4,3,4,3,1,4,1,1,4,2,3,3,4,1,0,0.0,neutral or dissatisfied +78875,38967,Male,Loyal Customer,35,Business travel,Eco,230,5,2,2,2,5,5,5,5,3,1,3,5,1,5,0,0.0,satisfied +78876,122960,Male,Loyal Customer,45,Business travel,Business,1621,5,5,5,5,2,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +78877,29980,Male,Loyal Customer,43,Business travel,Business,1832,2,1,4,4,3,3,3,2,2,2,2,3,2,3,0,1.0,neutral or dissatisfied +78878,111581,Female,Loyal Customer,40,Personal Travel,Eco,775,3,3,3,3,3,3,3,3,1,4,4,4,4,3,5,6.0,neutral or dissatisfied +78879,74996,Male,disloyal Customer,33,Business travel,Business,2454,4,4,4,1,1,4,1,1,4,5,4,3,4,1,0,19.0,neutral or dissatisfied +78880,128725,Male,Loyal Customer,38,Personal Travel,Eco,1464,4,4,4,3,2,4,4,2,3,3,4,1,4,2,0,0.0,satisfied +78881,31936,Male,disloyal Customer,37,Business travel,Business,163,3,3,3,4,3,3,3,4,2,4,4,3,4,3,136,146.0,neutral or dissatisfied +78882,26178,Female,Loyal Customer,36,Business travel,Business,581,4,1,2,1,2,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +78883,21557,Female,Loyal Customer,36,Business travel,Eco Plus,399,5,1,1,1,5,5,5,5,2,2,1,5,3,5,14,3.0,satisfied +78884,44390,Male,disloyal Customer,44,Business travel,Business,265,4,4,4,4,4,4,4,4,1,2,5,5,1,4,24,59.0,neutral or dissatisfied +78885,29267,Female,Loyal Customer,37,Business travel,Business,933,3,3,3,3,5,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +78886,127883,Male,Loyal Customer,51,Business travel,Business,3920,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,25.0,satisfied +78887,113161,Female,Loyal Customer,49,Business travel,Business,628,1,1,3,1,3,4,5,5,5,5,5,3,5,5,7,2.0,satisfied +78888,1982,Male,Loyal Customer,30,Personal Travel,Eco,351,2,4,2,3,4,2,4,4,3,2,4,3,5,4,0,11.0,neutral or dissatisfied +78889,116164,Male,Loyal Customer,41,Personal Travel,Eco,447,3,2,3,3,4,3,1,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +78890,100018,Female,disloyal Customer,57,Business travel,Business,277,2,2,2,5,1,2,1,1,4,4,5,4,4,1,79,71.0,neutral or dissatisfied +78891,83990,Male,Loyal Customer,54,Business travel,Business,2488,3,3,3,3,3,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +78892,51340,Male,Loyal Customer,27,Business travel,Eco Plus,156,3,1,1,1,3,3,3,3,2,4,4,4,3,3,0,9.0,neutral or dissatisfied +78893,126887,Male,Loyal Customer,31,Personal Travel,Eco,2125,1,3,0,4,1,0,1,1,3,3,4,3,4,1,29,28.0,neutral or dissatisfied +78894,91401,Female,Loyal Customer,63,Personal Travel,Eco,2218,3,4,3,2,3,4,4,3,3,3,5,5,3,5,0,0.0,neutral or dissatisfied +78895,72621,Male,Loyal Customer,9,Personal Travel,Eco,985,5,4,5,3,1,5,1,1,4,2,4,3,5,1,0,0.0,satisfied +78896,42557,Male,Loyal Customer,9,Business travel,Eco,694,1,1,1,1,1,1,2,1,3,4,4,1,3,1,0,16.0,neutral or dissatisfied +78897,113296,Male,Loyal Customer,35,Business travel,Business,2396,5,5,3,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +78898,97112,Male,Loyal Customer,38,Business travel,Business,1164,2,2,2,2,3,5,5,4,4,4,4,4,4,3,15,3.0,satisfied +78899,4843,Male,Loyal Customer,31,Business travel,Business,500,3,3,3,3,3,4,3,3,4,4,4,5,5,3,0,1.0,satisfied +78900,125381,Female,disloyal Customer,24,Business travel,Business,1440,4,0,4,1,2,4,3,2,4,2,5,4,4,2,0,0.0,satisfied +78901,95036,Female,Loyal Customer,41,Personal Travel,Eco,677,3,4,3,4,1,3,1,1,3,1,4,1,3,1,0,0.0,neutral or dissatisfied +78902,75749,Female,Loyal Customer,35,Business travel,Business,2002,3,3,3,3,4,4,2,5,5,5,5,3,5,3,46,46.0,satisfied +78903,114720,Female,Loyal Customer,59,Business travel,Business,2806,5,5,5,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +78904,56155,Male,Loyal Customer,51,Business travel,Business,1400,3,3,3,3,3,5,4,4,4,4,4,5,4,4,8,0.0,satisfied +78905,102945,Male,Loyal Customer,37,Personal Travel,Business,719,3,4,3,2,4,4,5,4,4,3,4,3,4,3,34,20.0,neutral or dissatisfied +78906,66133,Female,Loyal Customer,33,Personal Travel,Eco,583,1,4,1,4,5,1,5,5,4,1,4,4,3,5,0,0.0,neutral or dissatisfied +78907,70498,Male,Loyal Customer,28,Personal Travel,Eco,867,5,5,5,4,1,5,1,1,3,2,4,3,4,1,52,38.0,satisfied +78908,118954,Female,Loyal Customer,70,Business travel,Business,282,4,5,4,5,3,4,3,4,4,4,4,4,4,4,80,72.0,neutral or dissatisfied +78909,6792,Male,Loyal Customer,52,Business travel,Business,1965,4,4,4,4,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +78910,98381,Female,Loyal Customer,16,Business travel,Eco Plus,1189,5,2,2,2,5,4,2,5,2,3,3,2,4,5,0,0.0,neutral or dissatisfied +78911,66973,Female,Loyal Customer,55,Business travel,Business,1794,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +78912,2426,Male,Loyal Customer,26,Personal Travel,Eco,641,3,5,3,1,3,3,3,3,3,3,5,3,5,3,0,0.0,neutral or dissatisfied +78913,96674,Female,Loyal Customer,26,Personal Travel,Eco,937,2,3,2,3,2,2,2,2,1,1,4,1,4,2,13,0.0,neutral or dissatisfied +78914,9144,Female,Loyal Customer,57,Business travel,Business,227,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +78915,21088,Female,disloyal Customer,21,Business travel,Eco,152,1,1,1,3,2,1,2,2,2,2,4,3,4,2,0,0.0,neutral or dissatisfied +78916,21380,Male,disloyal Customer,43,Business travel,Eco,154,1,5,1,1,5,1,5,5,4,2,5,1,4,5,106,103.0,neutral or dissatisfied +78917,67013,Male,Loyal Customer,42,Business travel,Business,1995,1,1,2,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +78918,70579,Male,Loyal Customer,42,Personal Travel,Eco,1258,3,4,3,2,1,3,1,1,5,4,4,4,4,1,28,36.0,neutral or dissatisfied +78919,87929,Male,Loyal Customer,45,Business travel,Business,2936,3,2,2,2,3,3,3,3,3,3,3,4,3,2,3,0.0,neutral or dissatisfied +78920,102515,Female,Loyal Customer,56,Personal Travel,Eco,414,4,3,4,3,4,2,3,3,3,4,3,3,3,2,82,63.0,neutral or dissatisfied +78921,55767,Male,Loyal Customer,21,Personal Travel,Business,646,4,5,4,1,5,4,5,5,5,1,5,5,1,5,66,78.0,satisfied +78922,39075,Female,Loyal Customer,35,Business travel,Business,1174,1,2,2,2,1,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +78923,55515,Male,disloyal Customer,28,Business travel,Eco,991,1,1,1,4,1,1,1,1,2,4,4,4,4,1,113,114.0,neutral or dissatisfied +78924,107699,Male,Loyal Customer,48,Business travel,Business,1724,1,4,4,4,4,3,4,1,1,1,1,3,1,1,15,9.0,neutral or dissatisfied +78925,35326,Male,Loyal Customer,38,Business travel,Eco,1069,4,1,5,1,4,4,4,4,3,1,1,4,5,4,64,65.0,satisfied +78926,84107,Female,Loyal Customer,40,Business travel,Business,1900,4,4,4,4,2,5,4,4,4,4,4,5,4,5,0,13.0,satisfied +78927,78840,Male,Loyal Customer,18,Personal Travel,Eco,432,4,5,4,2,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +78928,65300,Female,Loyal Customer,39,Personal Travel,Eco Plus,247,3,4,3,3,3,3,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +78929,106599,Female,Loyal Customer,60,Business travel,Business,2446,3,3,5,3,3,5,5,4,4,4,4,3,4,3,0,,satisfied +78930,52104,Male,Loyal Customer,47,Personal Travel,Eco,639,3,4,3,4,3,3,5,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +78931,94935,Female,Loyal Customer,36,Business travel,Business,2202,3,3,3,3,3,4,3,2,2,2,3,1,2,2,0,0.0,neutral or dissatisfied +78932,112828,Female,Loyal Customer,54,Business travel,Business,3970,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +78933,120982,Male,Loyal Customer,32,Business travel,Business,920,1,1,3,3,1,2,1,1,4,1,3,1,3,1,14,80.0,neutral or dissatisfied +78934,46927,Male,Loyal Customer,55,Business travel,Eco,509,3,4,4,4,3,3,3,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +78935,71996,Male,Loyal Customer,40,Personal Travel,Eco,1440,1,5,1,3,5,1,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +78936,27574,Male,Loyal Customer,16,Personal Travel,Eco,1050,2,4,2,5,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +78937,15794,Female,Loyal Customer,42,Business travel,Eco,143,4,4,4,4,3,5,1,4,4,4,4,1,4,2,39,57.0,satisfied +78938,83623,Male,Loyal Customer,39,Personal Travel,Eco,409,2,4,2,1,2,2,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +78939,69925,Female,Loyal Customer,57,Business travel,Business,1514,2,2,2,2,4,5,5,5,5,4,5,3,5,3,22,21.0,satisfied +78940,114590,Female,Loyal Customer,40,Business travel,Business,446,3,4,3,3,5,5,5,5,5,5,5,3,5,4,55,52.0,satisfied +78941,17139,Male,Loyal Customer,56,Business travel,Business,3018,3,2,2,2,3,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +78942,46821,Male,Loyal Customer,36,Business travel,Eco,737,4,2,2,2,4,4,4,4,4,2,3,5,1,4,21,29.0,satisfied +78943,100240,Female,Loyal Customer,30,Business travel,Business,1205,2,2,2,2,5,5,5,5,5,5,5,4,5,5,1,4.0,satisfied +78944,58683,Male,Loyal Customer,54,Personal Travel,Eco,837,2,4,2,1,2,2,2,2,4,5,4,4,4,2,11,0.0,neutral or dissatisfied +78945,68476,Male,Loyal Customer,39,Business travel,Business,1303,3,1,1,1,2,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +78946,85773,Female,Loyal Customer,44,Business travel,Business,2178,4,4,4,4,3,5,5,5,5,5,5,3,5,4,46,54.0,satisfied +78947,8669,Male,Loyal Customer,46,Business travel,Business,3752,5,5,5,5,5,4,5,4,4,4,4,5,4,4,10,16.0,satisfied +78948,579,Male,Loyal Customer,56,Business travel,Business,2414,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +78949,45629,Male,disloyal Customer,26,Business travel,Business,230,3,5,3,3,1,3,1,1,2,5,3,5,5,1,30,40.0,neutral or dissatisfied +78950,100500,Female,disloyal Customer,25,Business travel,Business,580,2,0,3,3,5,3,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +78951,72809,Male,Loyal Customer,47,Personal Travel,Eco,1045,1,2,1,3,3,1,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +78952,124884,Male,Loyal Customer,52,Business travel,Business,3984,3,3,3,3,5,5,4,3,3,4,3,3,3,5,1,6.0,satisfied +78953,94374,Female,disloyal Customer,59,Business travel,Business,239,3,4,4,3,2,3,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +78954,126823,Male,Loyal Customer,44,Business travel,Business,2296,1,1,2,1,2,5,4,4,4,4,4,4,4,5,6,0.0,satisfied +78955,52292,Female,Loyal Customer,40,Business travel,Business,451,2,2,2,2,5,5,5,4,2,2,3,5,3,5,326,366.0,satisfied +78956,3681,Female,Loyal Customer,37,Business travel,Business,3603,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +78957,41438,Female,Loyal Customer,25,Business travel,Eco Plus,563,5,2,2,2,5,5,5,5,1,3,4,4,2,5,6,6.0,satisfied +78958,90906,Male,Loyal Customer,23,Business travel,Business,406,3,2,2,2,3,3,3,3,3,2,4,3,3,3,1,0.0,neutral or dissatisfied +78959,68513,Male,Loyal Customer,37,Personal Travel,Eco Plus,1303,3,4,3,3,4,3,4,4,4,3,3,3,4,4,0,0.0,neutral or dissatisfied +78960,46165,Male,Loyal Customer,46,Personal Travel,Eco,604,2,2,2,4,2,2,2,2,2,3,4,4,3,2,46,36.0,neutral or dissatisfied +78961,103240,Female,disloyal Customer,35,Business travel,Eco,409,2,2,2,2,5,2,5,5,4,4,2,3,2,5,12,9.0,neutral or dissatisfied +78962,80792,Male,Loyal Customer,59,Business travel,Business,2358,5,5,5,5,2,4,5,4,4,4,4,4,4,5,21,19.0,satisfied +78963,6556,Female,disloyal Customer,36,Business travel,Business,473,3,3,3,4,4,3,4,4,5,5,5,4,4,4,14,5.0,neutral or dissatisfied +78964,8009,Male,Loyal Customer,61,Business travel,Business,335,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,,satisfied +78965,14193,Male,disloyal Customer,28,Business travel,Eco,620,3,1,2,3,2,4,4,1,2,3,4,4,4,4,170,166.0,neutral or dissatisfied +78966,32241,Female,Loyal Customer,38,Business travel,Eco,163,4,4,4,4,4,4,4,4,4,5,4,2,3,4,0,8.0,satisfied +78967,128394,Female,Loyal Customer,10,Business travel,Business,2155,1,4,4,4,1,1,1,1,2,2,3,1,4,1,2,0.0,neutral or dissatisfied +78968,118250,Male,Loyal Customer,32,Business travel,Business,1788,4,4,4,4,4,4,4,4,5,3,4,3,5,4,2,0.0,satisfied +78969,97769,Male,Loyal Customer,59,Business travel,Business,1894,2,2,2,2,3,5,5,3,3,4,3,3,3,4,0,26.0,satisfied +78970,89876,Female,Loyal Customer,24,Business travel,Business,1487,1,1,1,1,4,4,4,4,4,5,4,3,4,4,10,0.0,satisfied +78971,104068,Female,Loyal Customer,14,Personal Travel,Eco Plus,1044,3,3,3,4,4,3,4,4,4,5,1,1,3,4,3,0.0,neutral or dissatisfied +78972,9174,Female,Loyal Customer,33,Business travel,Business,416,1,0,0,3,3,3,3,4,4,0,4,3,4,3,0,0.0,neutral or dissatisfied +78973,24967,Male,Loyal Customer,44,Business travel,Eco Plus,949,4,2,2,2,4,4,4,4,2,4,5,2,3,4,0,0.0,satisfied +78974,30386,Female,disloyal Customer,36,Business travel,Eco,462,1,4,1,3,4,1,4,4,2,5,4,1,3,4,82,76.0,neutral or dissatisfied +78975,104748,Male,Loyal Customer,62,Business travel,Business,3802,2,3,3,3,2,4,4,2,2,2,2,2,2,2,25,25.0,neutral or dissatisfied +78976,88563,Female,Loyal Customer,16,Personal Travel,Eco,545,3,2,3,2,1,3,1,1,1,3,3,1,2,1,3,0.0,neutral or dissatisfied +78977,1755,Male,Loyal Customer,58,Business travel,Business,3770,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,6.0,satisfied +78978,32193,Female,Loyal Customer,55,Business travel,Business,3158,4,4,4,4,3,3,2,5,5,5,3,3,5,1,0,0.0,satisfied +78979,72462,Male,disloyal Customer,23,Business travel,Business,1102,5,3,5,4,3,5,3,3,4,3,5,4,4,3,26,7.0,satisfied +78980,55520,Female,Loyal Customer,43,Personal Travel,Eco,991,4,1,4,3,1,2,3,4,4,4,1,2,4,3,14,0.0,neutral or dissatisfied +78981,101533,Female,Loyal Customer,53,Personal Travel,Eco,345,3,5,3,2,5,5,5,3,3,3,3,3,3,5,25,24.0,neutral or dissatisfied +78982,106342,Female,Loyal Customer,44,Business travel,Business,1775,3,3,3,3,5,5,5,4,4,5,4,4,4,3,21,11.0,satisfied +78983,62345,Male,Loyal Customer,11,Personal Travel,Eco Plus,414,3,5,3,3,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +78984,121665,Female,Loyal Customer,49,Business travel,Eco,328,2,4,4,4,1,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +78985,66715,Female,Loyal Customer,49,Personal Travel,Eco,802,2,4,2,4,2,3,4,5,5,2,5,3,5,1,9,12.0,neutral or dissatisfied +78986,119834,Female,Loyal Customer,56,Business travel,Business,912,2,2,2,2,3,5,4,4,4,4,4,4,4,5,0,1.0,satisfied +78987,110818,Female,Loyal Customer,59,Personal Travel,Eco,997,2,5,2,2,2,1,3,4,4,2,3,5,4,1,0,0.0,neutral or dissatisfied +78988,97236,Female,disloyal Customer,23,Business travel,Eco,296,3,1,3,3,4,3,4,4,4,3,2,1,2,4,0,0.0,neutral or dissatisfied +78989,88819,Female,disloyal Customer,23,Business travel,Eco,581,1,5,0,4,2,0,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +78990,70250,Male,disloyal Customer,23,Business travel,Business,1592,5,4,5,4,5,5,5,5,5,3,4,5,5,5,17,0.0,satisfied +78991,4901,Female,Loyal Customer,57,Business travel,Business,2688,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +78992,39057,Female,Loyal Customer,35,Business travel,Eco Plus,230,3,5,2,5,3,3,3,3,4,5,3,3,3,3,31,46.0,neutral or dissatisfied +78993,99677,Female,disloyal Customer,26,Business travel,Business,442,1,5,1,3,1,1,1,1,5,2,5,4,4,1,3,0.0,neutral or dissatisfied +78994,10646,Female,Loyal Customer,52,Business travel,Business,308,0,0,0,4,5,4,5,4,4,4,4,3,4,4,21,9.0,satisfied +78995,116427,Male,Loyal Customer,15,Personal Travel,Eco,446,3,2,3,3,1,3,1,1,1,4,4,4,4,1,9,1.0,neutral or dissatisfied +78996,128862,Female,disloyal Customer,25,Business travel,Business,2475,1,5,1,5,1,1,1,3,3,3,4,1,5,1,0,0.0,neutral or dissatisfied +78997,106953,Male,disloyal Customer,35,Business travel,Business,937,3,3,3,2,2,3,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +78998,103946,Male,Loyal Customer,51,Business travel,Business,2308,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +78999,49419,Female,Loyal Customer,32,Business travel,Business,110,2,1,1,1,1,1,2,1,2,4,4,3,3,1,4,9.0,neutral or dissatisfied +79000,47435,Male,Loyal Customer,20,Business travel,Business,2517,2,2,2,2,5,5,5,5,1,4,5,1,3,5,13,0.0,satisfied +79001,7554,Female,Loyal Customer,46,Business travel,Business,606,4,4,1,4,5,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +79002,30967,Male,Loyal Customer,41,Business travel,Eco Plus,1024,3,4,3,4,3,3,3,3,3,2,4,2,3,3,34,29.0,neutral or dissatisfied +79003,112028,Female,Loyal Customer,57,Personal Travel,Eco,680,2,5,2,2,2,4,4,5,5,2,2,4,5,5,0,0.0,neutral or dissatisfied +79004,125852,Male,Loyal Customer,43,Business travel,Business,1013,1,1,4,1,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +79005,116305,Female,Loyal Customer,26,Personal Travel,Eco,373,4,1,4,2,2,4,2,2,1,3,3,1,3,2,6,13.0,neutral or dissatisfied +79006,8566,Female,disloyal Customer,25,Business travel,Eco,109,2,2,2,4,1,2,1,1,4,4,4,1,3,1,3,8.0,neutral or dissatisfied +79007,40526,Male,Loyal Customer,58,Business travel,Business,391,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +79008,25183,Female,Loyal Customer,10,Business travel,Eco,577,3,2,2,2,3,4,4,3,2,3,3,2,3,3,0,6.0,neutral or dissatisfied +79009,24875,Female,Loyal Customer,43,Personal Travel,Eco,356,2,4,3,3,3,5,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +79010,104350,Male,Loyal Customer,10,Personal Travel,Eco,409,2,5,2,4,4,2,4,4,5,4,5,5,5,4,33,18.0,neutral or dissatisfied +79011,28090,Female,Loyal Customer,31,Business travel,Business,550,2,2,2,2,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +79012,7275,Male,Loyal Customer,15,Personal Travel,Eco,139,1,4,1,3,5,1,5,5,3,1,4,2,4,5,63,57.0,neutral or dissatisfied +79013,11036,Female,Loyal Customer,17,Personal Travel,Eco,224,4,5,4,2,2,4,1,2,4,3,5,4,5,2,11,,neutral or dissatisfied +79014,19998,Male,disloyal Customer,25,Business travel,Eco,589,3,3,3,2,2,3,2,2,3,2,2,5,2,2,2,13.0,neutral or dissatisfied +79015,68801,Female,Loyal Customer,56,Personal Travel,Eco,861,2,5,2,4,3,4,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +79016,101470,Male,disloyal Customer,20,Business travel,Eco,345,4,1,4,3,3,4,3,3,4,2,4,3,5,3,42,34.0,satisfied +79017,58152,Female,disloyal Customer,23,Business travel,Eco,925,3,3,3,3,4,3,4,4,3,4,4,5,5,4,8,2.0,neutral or dissatisfied +79018,65823,Female,disloyal Customer,25,Business travel,Eco,1389,3,3,3,3,3,3,3,3,4,5,3,2,3,3,12,5.0,neutral or dissatisfied +79019,87069,Male,Loyal Customer,42,Business travel,Business,3383,5,5,2,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +79020,22084,Female,Loyal Customer,32,Business travel,Eco,782,4,2,2,2,4,4,4,4,3,1,1,2,3,4,50,44.0,satisfied +79021,81118,Female,Loyal Customer,50,Business travel,Business,991,3,2,2,2,2,3,3,3,3,3,3,1,3,2,6,7.0,neutral or dissatisfied +79022,56394,Female,Loyal Customer,42,Business travel,Business,719,2,4,4,4,4,4,4,2,2,2,2,2,2,1,31,48.0,neutral or dissatisfied +79023,54907,Female,disloyal Customer,29,Business travel,Business,862,0,0,0,4,3,0,3,3,3,2,5,4,5,3,0,0.0,satisfied +79024,69591,Female,Loyal Customer,35,Personal Travel,Eco,2475,3,0,3,4,3,3,3,1,1,5,5,3,3,3,0,3.0,neutral or dissatisfied +79025,59515,Female,Loyal Customer,43,Business travel,Business,956,2,2,2,2,5,4,5,4,4,4,4,5,4,3,99,90.0,satisfied +79026,108282,Female,Loyal Customer,55,Business travel,Business,2127,4,4,4,4,4,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +79027,102106,Female,Loyal Customer,41,Business travel,Business,2783,0,0,0,1,5,4,4,3,3,3,3,5,3,5,0,4.0,satisfied +79028,91940,Female,disloyal Customer,25,Business travel,Eco,1086,2,2,2,2,1,2,1,1,2,3,4,4,1,1,0,0.0,neutral or dissatisfied +79029,121916,Male,Loyal Customer,23,Personal Travel,Eco,449,4,3,4,3,2,4,5,2,2,2,3,3,1,2,0,0.0,neutral or dissatisfied +79030,53416,Female,Loyal Customer,28,Business travel,Eco,2419,5,2,2,2,5,5,5,5,1,4,5,2,4,5,0,0.0,satisfied +79031,127442,Female,disloyal Customer,26,Business travel,Eco Plus,1009,3,3,3,3,4,3,4,4,4,4,3,3,3,4,124,117.0,neutral or dissatisfied +79032,88015,Male,Loyal Customer,47,Business travel,Business,2991,4,4,4,4,4,4,4,4,4,4,4,3,4,5,86,80.0,satisfied +79033,61401,Female,Loyal Customer,19,Personal Travel,Eco,679,1,4,1,5,3,1,2,3,4,5,5,4,5,3,0,9.0,neutral or dissatisfied +79034,111987,Female,Loyal Customer,67,Personal Travel,Eco,770,2,4,2,3,5,3,3,5,5,2,5,1,5,2,8,26.0,neutral or dissatisfied +79035,2704,Female,Loyal Customer,49,Business travel,Eco,562,2,4,2,4,2,4,4,2,2,2,2,3,2,2,39,30.0,neutral or dissatisfied +79036,73561,Male,disloyal Customer,21,Business travel,Eco,204,2,4,2,4,3,2,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +79037,51081,Female,Loyal Customer,17,Personal Travel,Eco,153,1,5,1,2,5,1,5,5,4,2,2,5,2,5,0,0.0,neutral or dissatisfied +79038,128706,Male,Loyal Customer,60,Business travel,Business,1504,1,1,2,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +79039,47679,Male,Loyal Customer,53,Personal Travel,Eco,1428,1,1,1,4,2,1,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +79040,128217,Male,disloyal Customer,36,Business travel,Business,602,3,3,3,1,2,3,5,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +79041,44485,Male,disloyal Customer,44,Business travel,Eco,476,2,0,2,3,2,2,2,2,1,2,1,4,2,2,0,0.0,neutral or dissatisfied +79042,48608,Female,disloyal Customer,20,Business travel,Eco,819,5,5,5,2,3,5,3,3,3,1,3,2,4,3,74,64.0,satisfied +79043,1762,Female,Loyal Customer,22,Personal Travel,Eco Plus,327,2,4,2,2,4,2,5,4,5,3,4,5,5,4,84,78.0,neutral or dissatisfied +79044,117760,Male,Loyal Customer,31,Business travel,Business,1670,2,2,2,2,4,4,4,4,4,3,3,5,5,4,1,0.0,satisfied +79045,124474,Male,Loyal Customer,31,Personal Travel,Eco,980,2,5,2,4,4,2,4,4,5,2,5,5,4,4,3,0.0,neutral or dissatisfied +79046,39488,Male,Loyal Customer,43,Personal Travel,Eco,867,4,3,5,4,2,5,2,2,1,1,3,4,3,2,11,4.0,neutral or dissatisfied +79047,63220,Male,Loyal Customer,58,Business travel,Business,2475,0,0,0,2,5,4,4,3,3,3,3,3,3,5,0,11.0,satisfied +79048,81022,Male,Loyal Customer,43,Business travel,Business,1399,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +79049,119142,Female,Loyal Customer,29,Personal Travel,Eco,119,1,2,1,1,3,1,4,3,2,3,2,3,1,3,2,0.0,neutral or dissatisfied +79050,59446,Female,Loyal Customer,54,Business travel,Business,3098,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +79051,52105,Female,Loyal Customer,20,Personal Travel,Eco,639,2,5,2,4,5,2,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +79052,96487,Male,Loyal Customer,44,Business travel,Business,444,3,3,3,3,4,5,4,5,5,4,5,5,5,5,5,0.0,satisfied +79053,71328,Male,Loyal Customer,54,Business travel,Business,1514,3,3,3,3,2,3,3,3,3,3,3,1,3,4,12,10.0,neutral or dissatisfied +79054,37584,Female,Loyal Customer,80,Business travel,Business,611,2,3,3,3,4,1,1,2,2,2,2,3,2,3,0,2.0,neutral or dissatisfied +79055,23797,Female,Loyal Customer,42,Business travel,Eco,374,1,3,3,3,5,3,4,1,1,1,1,2,1,3,17,25.0,neutral or dissatisfied +79056,71875,Male,Loyal Customer,11,Personal Travel,Eco,1726,4,5,4,1,1,4,1,1,5,4,5,4,5,1,1,3.0,satisfied +79057,109715,Female,Loyal Customer,25,Business travel,Business,2008,3,3,3,3,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +79058,88002,Female,Loyal Customer,52,Business travel,Business,545,5,5,5,5,3,5,5,5,5,5,5,4,5,3,9,6.0,satisfied +79059,3736,Male,Loyal Customer,10,Personal Travel,Eco,427,1,2,1,2,5,1,5,5,4,1,3,1,2,5,78,46.0,neutral or dissatisfied +79060,19140,Male,Loyal Customer,7,Personal Travel,Eco Plus,265,2,5,2,5,2,2,2,2,2,5,4,1,2,2,0,0.0,neutral or dissatisfied +79061,49760,Female,Loyal Customer,55,Business travel,Business,1640,1,1,1,1,1,2,5,5,5,5,5,4,5,5,0,0.0,satisfied +79062,116546,Male,Loyal Customer,52,Personal Travel,Eco,446,3,4,3,3,5,3,5,5,3,3,4,3,5,5,15,12.0,neutral or dissatisfied +79063,122507,Female,Loyal Customer,41,Business travel,Business,3870,2,3,2,2,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +79064,111407,Female,Loyal Customer,23,Business travel,Eco Plus,1111,1,2,2,2,1,1,1,1,3,2,4,4,4,1,8,16.0,neutral or dissatisfied +79065,14335,Female,Loyal Customer,44,Personal Travel,Eco,175,4,5,0,4,2,4,4,2,2,0,2,3,2,4,129,122.0,neutral or dissatisfied +79066,63609,Male,Loyal Customer,36,Business travel,Business,1440,3,3,5,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +79067,74027,Female,disloyal Customer,21,Business travel,Eco,1071,4,4,4,1,5,4,5,5,4,5,1,2,1,5,0,0.0,satisfied +79068,96900,Male,Loyal Customer,13,Personal Travel,Eco,571,2,2,2,3,2,2,2,2,3,4,2,3,2,2,0,0.0,neutral or dissatisfied +79069,58405,Male,Loyal Customer,48,Business travel,Business,733,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +79070,86521,Female,Loyal Customer,65,Personal Travel,Eco,762,3,5,3,2,5,4,5,3,3,3,1,4,3,5,39,20.0,neutral or dissatisfied +79071,29059,Male,Loyal Customer,19,Personal Travel,Eco,978,4,4,4,3,5,4,5,5,3,2,4,5,4,5,0,0.0,satisfied +79072,28829,Male,Loyal Customer,37,Business travel,Business,1548,2,2,1,2,3,3,2,5,5,5,5,4,5,4,0,6.0,satisfied +79073,1504,Male,Loyal Customer,45,Personal Travel,Eco,737,4,5,4,1,5,4,5,5,5,2,5,5,4,5,2,10.0,neutral or dissatisfied +79074,123628,Male,Loyal Customer,60,Business travel,Business,214,4,3,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +79075,77708,Female,Loyal Customer,52,Business travel,Eco,696,3,3,4,3,4,4,4,3,3,3,3,4,3,4,4,0.0,neutral or dissatisfied +79076,45878,Male,Loyal Customer,34,Business travel,Business,2799,3,3,3,3,4,4,1,4,4,5,4,1,4,2,18,17.0,satisfied +79077,106767,Male,Loyal Customer,23,Personal Travel,Eco,945,4,2,4,3,2,4,5,2,3,4,3,1,4,2,0,0.0,satisfied +79078,121794,Male,Loyal Customer,46,Business travel,Business,3894,3,1,1,1,2,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +79079,115117,Female,Loyal Customer,49,Business travel,Business,3995,5,5,5,5,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +79080,23553,Female,Loyal Customer,36,Business travel,Eco,637,3,4,4,4,3,4,3,3,4,4,1,4,5,3,114,127.0,satisfied +79081,96116,Female,Loyal Customer,40,Business travel,Business,583,3,3,3,3,3,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +79082,84219,Female,Loyal Customer,78,Business travel,Eco,432,2,3,4,4,2,2,2,4,1,3,3,2,1,2,362,371.0,neutral or dissatisfied +79083,112975,Female,Loyal Customer,46,Business travel,Business,1715,1,1,1,1,4,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +79084,92599,Male,Loyal Customer,45,Business travel,Business,2158,2,2,2,2,4,4,3,2,2,2,2,4,2,3,5,0.0,neutral or dissatisfied +79085,63354,Female,Loyal Customer,20,Personal Travel,Eco,447,4,1,0,4,2,0,2,2,1,5,4,4,4,2,87,80.0,satisfied +79086,41026,Female,disloyal Customer,60,Business travel,Eco,1087,1,0,0,3,5,0,5,5,1,4,2,1,2,5,0,0.0,neutral or dissatisfied +79087,123699,Male,Loyal Customer,31,Personal Travel,Eco,214,3,5,0,4,4,0,4,4,5,4,4,3,4,4,18,6.0,neutral or dissatisfied +79088,61800,Male,Loyal Customer,15,Personal Travel,Eco,1346,2,4,2,4,4,2,5,4,2,3,4,2,4,4,0,21.0,neutral or dissatisfied +79089,106148,Male,Loyal Customer,33,Business travel,Eco,302,0,0,0,4,2,5,2,2,2,5,5,5,2,2,0,0.0,satisfied +79090,42180,Female,Loyal Customer,44,Business travel,Business,2229,2,2,2,2,2,5,5,5,5,5,5,5,5,3,4,3.0,satisfied +79091,129007,Male,Loyal Customer,27,Business travel,Business,2611,4,4,4,4,5,5,5,4,5,5,4,5,5,5,0,5.0,satisfied +79092,102088,Female,disloyal Customer,48,Business travel,Business,223,3,3,3,3,3,3,3,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +79093,100808,Male,Loyal Customer,70,Personal Travel,Eco,872,5,5,5,1,3,5,3,3,1,2,4,3,4,3,0,3.0,satisfied +79094,29405,Male,Loyal Customer,12,Personal Travel,Eco,2404,3,1,3,3,3,1,5,3,3,2,3,5,3,5,0,4.0,neutral or dissatisfied +79095,71999,Female,Loyal Customer,60,Personal Travel,Eco,1440,1,4,1,3,2,3,4,4,4,1,4,3,4,4,0,4.0,neutral or dissatisfied +79096,3847,Female,Loyal Customer,17,Personal Travel,Eco,710,3,4,2,3,3,2,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +79097,120389,Male,Loyal Customer,45,Business travel,Business,2904,1,1,1,1,3,4,4,2,2,2,2,5,2,4,3,0.0,satisfied +79098,11831,Female,Loyal Customer,23,Personal Travel,Eco,1021,1,5,1,5,5,1,3,5,2,5,1,4,5,5,0,0.0,neutral or dissatisfied +79099,51407,Female,Loyal Customer,50,Personal Travel,Eco Plus,250,2,5,2,5,3,5,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +79100,114153,Female,Loyal Customer,47,Business travel,Business,967,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +79101,37352,Male,disloyal Customer,30,Business travel,Eco,828,3,2,2,3,4,2,4,4,1,2,5,2,2,4,0,0.0,neutral or dissatisfied +79102,88412,Male,Loyal Customer,31,Business travel,Eco,270,2,4,4,4,2,2,2,2,4,4,4,2,2,2,166,147.0,neutral or dissatisfied +79103,17049,Female,Loyal Customer,45,Business travel,Eco,1134,5,4,4,4,2,3,3,5,5,5,5,1,5,4,0,0.0,satisfied +79104,59020,Female,Loyal Customer,43,Business travel,Business,1744,1,1,1,1,4,4,4,4,4,5,4,5,4,4,15,1.0,satisfied +79105,83884,Female,Loyal Customer,33,Personal Travel,Eco,1670,2,4,2,2,4,2,1,4,3,1,2,4,1,4,0,0.0,neutral or dissatisfied +79106,51375,Male,Loyal Customer,34,Personal Travel,Eco Plus,86,3,2,3,3,3,3,1,3,4,1,4,1,3,3,28,17.0,neutral or dissatisfied +79107,51036,Female,Loyal Customer,32,Personal Travel,Eco,86,4,4,4,4,5,4,5,5,1,1,1,4,3,5,9,5.0,neutral or dissatisfied +79108,111239,Male,Loyal Customer,62,Personal Travel,Eco Plus,1506,1,4,0,4,2,0,2,2,5,2,5,5,4,2,0,1.0,neutral or dissatisfied +79109,24952,Male,Loyal Customer,70,Personal Travel,Eco,1747,4,1,4,3,4,4,4,4,2,1,3,3,4,4,0,0.0,neutral or dissatisfied +79110,62444,Male,Loyal Customer,29,Business travel,Business,1846,5,5,5,5,3,4,3,3,4,4,3,5,5,3,0,0.0,satisfied +79111,48952,Male,disloyal Customer,26,Business travel,Eco,156,3,0,3,3,2,3,2,2,3,4,2,5,2,2,0,0.0,neutral or dissatisfied +79112,105455,Female,Loyal Customer,24,Personal Travel,Eco,998,2,4,2,1,3,2,3,3,5,5,4,2,4,3,14,7.0,neutral or dissatisfied +79113,26260,Female,Loyal Customer,60,Personal Travel,Eco Plus,515,4,2,4,2,3,2,2,4,4,4,4,2,4,2,0,0.0,satisfied +79114,93312,Male,Loyal Customer,37,Personal Travel,Eco,1733,2,4,2,5,1,2,1,1,4,4,4,5,5,1,0,1.0,neutral or dissatisfied +79115,42162,Male,Loyal Customer,29,Business travel,Business,748,5,5,5,5,4,4,4,4,4,1,1,2,4,4,10,17.0,satisfied +79116,70221,Female,disloyal Customer,23,Business travel,Business,1068,5,0,5,5,4,5,4,4,4,2,5,3,4,4,9,17.0,satisfied +79117,103027,Female,Loyal Customer,49,Business travel,Business,460,2,2,4,2,5,5,4,2,2,2,2,4,2,4,11,0.0,satisfied +79118,80551,Male,Loyal Customer,49,Business travel,Business,1747,3,4,4,4,1,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +79119,29868,Male,Loyal Customer,41,Business travel,Eco,539,5,5,5,5,5,5,5,5,1,3,4,2,1,5,0,0.0,satisfied +79120,98104,Female,Loyal Customer,74,Business travel,Eco Plus,265,2,4,4,4,1,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +79121,80490,Female,Loyal Customer,52,Business travel,Business,1749,3,3,3,3,4,4,5,5,5,5,5,5,5,3,0,6.0,satisfied +79122,119527,Female,Loyal Customer,11,Personal Travel,Eco,814,1,3,1,3,2,1,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +79123,96351,Male,Loyal Customer,9,Personal Travel,Eco,1609,3,2,3,3,5,3,5,5,2,5,2,4,3,5,5,0.0,neutral or dissatisfied +79124,108109,Male,Loyal Customer,44,Business travel,Business,1166,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,31.0,satisfied +79125,123254,Male,Loyal Customer,30,Personal Travel,Eco,600,2,5,2,3,1,2,1,1,2,2,4,1,3,1,12,0.0,neutral or dissatisfied +79126,69418,Female,disloyal Customer,38,Business travel,Eco,696,5,5,5,2,2,5,2,2,2,2,4,5,1,2,0,0.0,satisfied +79127,101306,Female,Loyal Customer,29,Business travel,Business,2461,3,3,3,3,5,5,5,5,5,4,4,3,5,5,1,0.0,satisfied +79128,105776,Male,Loyal Customer,38,Business travel,Eco,519,1,3,3,3,1,1,1,1,3,2,3,4,4,1,33,17.0,neutral or dissatisfied +79129,126738,Male,disloyal Customer,15,Business travel,Eco,1407,3,3,3,3,2,3,2,2,1,4,3,3,4,2,0,0.0,neutral or dissatisfied +79130,48901,Female,Loyal Customer,38,Business travel,Business,2506,5,5,5,5,5,1,4,5,5,5,5,3,5,2,3,0.0,satisfied +79131,18087,Female,Loyal Customer,65,Personal Travel,Eco,488,4,0,4,3,3,5,4,3,3,4,3,4,3,3,57,47.0,neutral or dissatisfied +79132,119399,Female,Loyal Customer,60,Business travel,Business,399,2,2,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +79133,34595,Female,disloyal Customer,23,Business travel,Eco,998,4,5,5,3,2,5,2,2,2,4,4,1,4,2,0,15.0,neutral or dissatisfied +79134,87771,Female,Loyal Customer,50,Business travel,Business,214,5,4,5,5,4,4,4,5,5,5,5,5,5,3,17,29.0,satisfied +79135,83399,Male,Loyal Customer,59,Business travel,Business,632,2,2,5,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +79136,47981,Female,Loyal Customer,34,Personal Travel,Eco,784,2,5,2,5,5,2,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +79137,121085,Male,Loyal Customer,60,Business travel,Business,196,4,5,4,4,5,4,5,5,5,5,5,3,5,4,18,22.0,satisfied +79138,10474,Female,disloyal Customer,23,Business travel,Business,163,4,3,4,3,4,4,1,4,4,4,4,3,4,4,44,24.0,satisfied +79139,892,Female,disloyal Customer,24,Business travel,Eco,113,2,2,2,4,3,2,3,3,4,5,4,2,4,3,20,6.0,neutral or dissatisfied +79140,63319,Female,Loyal Customer,22,Business travel,Business,447,2,5,5,5,2,2,2,2,2,3,4,4,4,2,4,0.0,neutral or dissatisfied +79141,121229,Male,Loyal Customer,51,Business travel,Business,2075,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +79142,11428,Female,Loyal Customer,17,Business travel,Business,1709,5,5,1,5,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +79143,39063,Male,disloyal Customer,24,Business travel,Eco,784,4,4,4,4,1,4,1,1,4,1,3,4,3,1,26,15.0,neutral or dissatisfied +79144,83976,Male,Loyal Customer,54,Business travel,Business,2295,3,3,3,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +79145,14050,Female,disloyal Customer,21,Business travel,Eco,335,4,0,3,2,4,3,4,4,4,2,2,1,5,4,0,0.0,satisfied +79146,86880,Female,Loyal Customer,23,Personal Travel,Eco Plus,484,2,4,2,2,4,2,4,4,5,4,4,4,5,4,1,0.0,neutral or dissatisfied +79147,120905,Female,Loyal Customer,30,Business travel,Business,2833,5,5,5,5,4,4,4,4,3,2,5,4,5,4,0,0.0,satisfied +79148,85140,Female,Loyal Customer,42,Business travel,Business,1567,1,4,4,4,3,3,4,1,1,2,1,4,1,4,6,6.0,neutral or dissatisfied +79149,70219,Female,disloyal Customer,36,Business travel,Eco Plus,258,3,2,2,3,2,2,2,2,2,3,3,4,3,2,64,51.0,neutral or dissatisfied +79150,87576,Female,Loyal Customer,13,Personal Travel,Eco,432,1,1,1,3,5,1,5,5,4,1,3,1,3,5,22,17.0,neutral or dissatisfied +79151,56658,Female,disloyal Customer,41,Business travel,Business,537,3,3,3,2,2,4,2,2,4,2,4,1,1,2,0,0.0,neutral or dissatisfied +79152,23260,Male,Loyal Customer,39,Business travel,Eco Plus,783,2,5,2,5,2,2,2,2,3,2,2,2,1,2,0,0.0,satisfied +79153,35501,Female,Loyal Customer,47,Personal Travel,Eco,1056,3,5,3,5,5,4,5,1,1,3,1,4,1,5,11,11.0,neutral or dissatisfied +79154,40669,Male,Loyal Customer,31,Personal Travel,Business,590,1,2,1,4,4,1,4,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +79155,36493,Female,disloyal Customer,31,Business travel,Eco,1185,1,1,1,3,5,1,5,5,2,2,3,4,5,5,0,0.0,neutral or dissatisfied +79156,105084,Female,Loyal Customer,45,Business travel,Business,3738,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +79157,123358,Female,Loyal Customer,27,Business travel,Business,644,3,4,4,4,3,2,3,3,3,2,3,1,4,3,16,9.0,neutral or dissatisfied +79158,85470,Female,Loyal Customer,64,Business travel,Business,2337,4,4,4,4,2,1,3,5,5,5,5,1,5,5,0,0.0,satisfied +79159,31989,Female,Loyal Customer,11,Personal Travel,Business,101,1,5,1,1,2,1,1,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +79160,103258,Male,Loyal Customer,59,Business travel,Business,888,4,4,4,4,2,4,4,4,4,4,4,4,4,5,28,16.0,satisfied +79161,99951,Female,Loyal Customer,34,Personal Travel,Eco,1986,3,4,3,3,5,3,3,5,4,3,4,2,3,5,0,15.0,neutral or dissatisfied +79162,115072,Female,Loyal Customer,57,Business travel,Business,446,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +79163,82382,Female,Loyal Customer,46,Business travel,Business,1811,4,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +79164,48298,Female,Loyal Customer,31,Business travel,Business,1499,4,4,4,4,3,3,3,3,2,3,1,1,2,3,0,0.0,satisfied +79165,10496,Male,disloyal Customer,38,Business travel,Business,201,5,5,5,4,4,5,4,4,5,4,5,3,4,4,22,25.0,satisfied +79166,112761,Female,Loyal Customer,24,Business travel,Business,1517,5,5,5,5,5,5,5,5,5,2,4,3,5,5,13,8.0,satisfied +79167,69492,Female,Loyal Customer,64,Business travel,Eco Plus,696,3,4,4,4,5,3,3,3,3,3,3,2,3,1,0,14.0,neutral or dissatisfied +79168,124417,Female,disloyal Customer,29,Business travel,Eco,1262,3,3,3,2,1,3,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +79169,7696,Female,Loyal Customer,68,Personal Travel,Eco,604,1,3,1,4,3,4,5,2,2,1,2,4,2,2,6,0.0,neutral or dissatisfied +79170,69267,Male,Loyal Customer,36,Personal Travel,Eco,733,4,5,4,4,1,4,1,1,5,5,1,5,3,1,0,5.0,neutral or dissatisfied +79171,99565,Female,Loyal Customer,18,Business travel,Business,802,4,4,4,4,4,4,4,4,5,2,5,5,4,4,8,4.0,satisfied +79172,22109,Male,disloyal Customer,42,Business travel,Eco,694,3,3,3,4,5,3,5,5,2,3,1,4,3,5,4,0.0,neutral or dissatisfied +79173,80054,Female,Loyal Customer,60,Personal Travel,Eco,950,4,4,4,4,4,5,4,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +79174,20907,Male,disloyal Customer,33,Business travel,Eco,721,3,3,3,2,2,3,2,2,4,5,1,3,5,2,0,0.0,neutral or dissatisfied +79175,124422,Male,Loyal Customer,32,Business travel,Business,1262,3,1,1,1,3,3,3,3,3,2,3,4,3,3,7,0.0,neutral or dissatisfied +79176,51444,Female,Loyal Customer,25,Personal Travel,Eco Plus,326,4,2,4,2,1,4,3,1,3,1,2,3,3,1,0,0.0,neutral or dissatisfied +79177,42178,Female,Loyal Customer,37,Business travel,Business,3256,4,4,4,4,4,4,4,1,4,1,1,4,4,4,353,370.0,satisfied +79178,48148,Male,disloyal Customer,21,Business travel,Eco,192,4,1,4,4,4,4,4,4,2,3,3,2,4,4,0,2.0,neutral or dissatisfied +79179,65326,Female,Loyal Customer,35,Business travel,Business,1930,3,3,3,3,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +79180,18717,Female,Loyal Customer,41,Personal Travel,Eco Plus,253,1,2,1,3,5,4,4,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +79181,121857,Female,disloyal Customer,22,Business travel,Eco,366,2,2,2,3,3,2,3,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +79182,17292,Female,Loyal Customer,40,Business travel,Business,1810,3,3,3,3,2,1,4,4,4,4,4,3,4,4,0,0.0,satisfied +79183,107250,Male,disloyal Customer,21,Business travel,Business,307,0,0,0,2,3,0,3,3,4,2,5,5,5,3,0,2.0,satisfied +79184,88357,Male,Loyal Customer,63,Business travel,Business,1599,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +79185,11814,Male,Loyal Customer,44,Business travel,Eco,1021,3,1,2,1,3,3,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +79186,38700,Male,Loyal Customer,30,Business travel,Business,2583,3,3,3,3,3,3,3,3,5,3,4,1,3,3,11,22.0,satisfied +79187,4418,Male,Loyal Customer,44,Business travel,Business,762,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +79188,122915,Female,disloyal Customer,24,Business travel,Eco,547,5,2,5,2,1,5,1,1,5,3,5,4,4,1,0,0.0,satisfied +79189,27605,Female,Loyal Customer,45,Personal Travel,Eco,605,2,4,2,4,5,4,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +79190,66441,Male,disloyal Customer,45,Business travel,Business,1217,3,3,3,3,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +79191,112505,Female,Loyal Customer,15,Personal Travel,Eco,967,3,5,3,4,2,3,2,2,4,5,5,5,4,2,19,3.0,neutral or dissatisfied +79192,14219,Female,Loyal Customer,25,Personal Travel,Eco,620,1,5,1,2,5,1,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +79193,83206,Male,Loyal Customer,55,Personal Travel,Eco,1123,3,1,4,3,4,4,4,4,3,4,3,3,3,4,0,2.0,neutral or dissatisfied +79194,70447,Female,Loyal Customer,50,Personal Travel,Eco,187,2,4,2,3,2,2,2,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +79195,272,Male,Loyal Customer,43,Business travel,Business,802,3,1,1,1,2,2,2,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +79196,21370,Male,disloyal Customer,45,Business travel,Eco,554,3,0,3,3,2,3,2,2,3,2,5,1,2,2,0,0.0,neutral or dissatisfied +79197,77436,Male,Loyal Customer,18,Business travel,Eco Plus,588,2,2,2,2,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +79198,127,Female,Loyal Customer,68,Personal Travel,Eco,562,2,1,2,3,4,3,3,3,3,2,3,1,3,4,42,37.0,neutral or dissatisfied +79199,103617,Male,Loyal Customer,34,Business travel,Business,1996,2,2,2,2,2,5,4,4,4,4,4,4,4,4,62,60.0,satisfied +79200,90386,Female,Loyal Customer,49,Business travel,Business,1782,3,1,1,1,3,1,1,3,3,3,3,3,3,1,26,19.0,neutral or dissatisfied +79201,12781,Male,Loyal Customer,53,Business travel,Business,2323,3,3,3,3,2,4,4,5,5,5,5,5,5,4,3,2.0,satisfied +79202,63599,Female,Loyal Customer,69,Personal Travel,Eco Plus,2133,3,4,3,1,2,3,5,1,1,3,1,3,1,3,8,8.0,neutral or dissatisfied +79203,38851,Male,Loyal Customer,49,Business travel,Eco Plus,354,5,3,5,3,5,5,5,5,2,3,5,2,5,5,0,4.0,satisfied +79204,29023,Male,Loyal Customer,54,Business travel,Business,3671,5,5,5,5,2,3,4,5,5,5,5,5,5,5,52,50.0,satisfied +79205,49260,Male,disloyal Customer,50,Business travel,Eco,109,2,3,2,2,1,2,1,1,3,3,4,3,3,1,14,24.0,neutral or dissatisfied +79206,113917,Male,Loyal Customer,30,Business travel,Business,2329,2,2,2,2,4,4,4,4,4,2,3,5,4,4,6,0.0,satisfied +79207,97990,Female,Loyal Customer,48,Business travel,Business,2787,5,5,4,5,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +79208,51386,Female,Loyal Customer,59,Personal Travel,Eco Plus,156,1,5,1,3,4,4,5,3,3,1,3,4,3,5,26,19.0,neutral or dissatisfied +79209,123897,Female,Loyal Customer,31,Personal Travel,Eco,544,5,4,5,3,5,5,5,5,1,3,5,3,4,5,0,0.0,satisfied +79210,34801,Male,Loyal Customer,37,Personal Travel,Eco,264,1,1,1,3,2,1,2,2,2,4,2,2,3,2,0,0.0,neutral or dissatisfied +79211,76975,Male,Loyal Customer,27,Business travel,Business,1969,4,1,5,1,4,4,4,4,2,3,2,2,4,4,0,0.0,neutral or dissatisfied +79212,99055,Male,Loyal Customer,34,Business travel,Business,3765,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +79213,15614,Female,Loyal Customer,49,Personal Travel,Eco,229,1,4,1,2,4,4,5,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +79214,30097,Male,Loyal Customer,38,Personal Travel,Eco,213,2,5,2,5,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +79215,120203,Female,Loyal Customer,36,Business travel,Eco,1325,1,2,2,2,1,1,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +79216,76226,Male,Loyal Customer,37,Business travel,Business,2279,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +79217,99341,Female,Loyal Customer,42,Business travel,Business,1771,4,4,4,4,4,4,5,3,3,3,3,3,3,5,0,16.0,satisfied +79218,37151,Male,Loyal Customer,70,Business travel,Business,3695,1,3,3,3,5,4,3,1,1,2,1,2,1,1,2,32.0,neutral or dissatisfied +79219,121115,Male,disloyal Customer,28,Business travel,Business,2521,0,0,0,1,0,2,5,4,5,4,4,5,3,5,0,0.0,satisfied +79220,121707,Male,Loyal Customer,37,Business travel,Business,2651,5,5,3,5,2,4,5,1,1,2,1,3,1,3,10,16.0,satisfied +79221,99513,Female,Loyal Customer,61,Personal Travel,Eco,307,3,3,3,1,5,1,2,2,2,3,2,3,2,3,14,13.0,neutral or dissatisfied +79222,107697,Female,Loyal Customer,57,Business travel,Business,2834,3,3,1,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +79223,93386,Female,Loyal Customer,49,Business travel,Business,605,3,3,3,3,5,5,4,4,4,4,4,5,4,5,50,47.0,satisfied +79224,20536,Male,Loyal Customer,38,Business travel,Business,533,3,3,3,3,1,1,4,4,4,4,4,1,4,4,0,0.0,satisfied +79225,20475,Female,Loyal Customer,10,Personal Travel,Eco Plus,84,2,4,2,4,2,2,2,2,5,3,4,5,4,2,12,1.0,neutral or dissatisfied +79226,16750,Male,Loyal Customer,27,Business travel,Eco,642,4,5,5,5,4,4,4,3,5,2,4,4,5,4,150,132.0,satisfied +79227,55588,Male,Loyal Customer,7,Personal Travel,Eco Plus,1091,1,4,1,3,4,1,4,4,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +79228,66631,Female,Loyal Customer,22,Personal Travel,Business,802,2,2,2,3,4,2,4,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +79229,19667,Male,Loyal Customer,33,Business travel,Business,491,2,2,2,2,4,4,4,4,4,3,5,5,4,4,92,83.0,satisfied +79230,80517,Female,Loyal Customer,48,Personal Travel,Eco,1749,3,3,2,5,3,1,5,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +79231,74267,Male,Loyal Customer,47,Personal Travel,Eco Plus,748,4,5,4,3,5,4,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +79232,80163,Male,disloyal Customer,30,Business travel,Business,710,5,5,5,3,5,5,4,3,3,4,5,4,3,4,24,0.0,satisfied +79233,28122,Female,Loyal Customer,40,Business travel,Eco,569,4,3,3,3,4,4,4,4,2,1,5,1,3,4,0,0.0,satisfied +79234,117991,Male,Loyal Customer,48,Business travel,Business,3234,1,1,1,1,5,5,4,4,4,4,4,3,4,5,15,7.0,satisfied +79235,16475,Male,Loyal Customer,32,Business travel,Eco Plus,529,2,4,4,4,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +79236,64753,Male,Loyal Customer,70,Business travel,Eco,247,2,5,5,5,2,2,2,2,4,5,2,1,2,2,0,0.0,neutral or dissatisfied +79237,69657,Male,Loyal Customer,55,Business travel,Business,569,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +79238,57323,Male,disloyal Customer,36,Business travel,Business,414,1,1,1,4,1,1,1,1,5,3,4,3,5,1,0,11.0,neutral or dissatisfied +79239,110583,Male,Loyal Customer,29,Business travel,Business,3825,4,1,1,1,4,3,4,4,3,4,4,2,3,4,0,11.0,neutral or dissatisfied +79240,57895,Male,Loyal Customer,35,Business travel,Business,2746,4,2,2,2,4,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +79241,106622,Male,Loyal Customer,32,Business travel,Business,2560,0,0,0,4,3,3,5,3,5,2,5,4,4,3,65,60.0,satisfied +79242,82410,Female,Loyal Customer,45,Business travel,Business,3375,2,2,2,2,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +79243,48656,Male,disloyal Customer,27,Business travel,Business,266,3,3,3,5,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +79244,23346,Female,Loyal Customer,63,Personal Travel,Eco,456,3,5,4,1,4,5,2,3,3,4,3,3,3,2,0,34.0,neutral or dissatisfied +79245,29467,Female,Loyal Customer,49,Business travel,Business,2668,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +79246,12410,Male,Loyal Customer,46,Business travel,Eco,383,4,4,4,4,5,4,5,5,2,1,4,5,4,5,0,0.0,satisfied +79247,124752,Male,Loyal Customer,18,Personal Travel,Business,280,2,4,3,5,5,3,5,5,3,5,4,4,4,5,15,3.0,neutral or dissatisfied +79248,106058,Female,disloyal Customer,39,Business travel,Business,903,2,2,2,2,5,2,4,5,4,1,2,3,1,5,74,75.0,neutral or dissatisfied +79249,8687,Male,Loyal Customer,29,Business travel,Business,181,0,5,0,5,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +79250,20226,Male,Loyal Customer,33,Business travel,Business,235,1,1,1,1,4,4,4,4,1,3,1,4,3,4,18,8.0,satisfied +79251,104241,Male,Loyal Customer,36,Business travel,Business,1276,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +79252,93594,Female,Loyal Customer,19,Personal Travel,Eco Plus,159,2,5,2,4,3,2,3,3,1,5,4,2,5,3,0,10.0,neutral or dissatisfied +79253,86575,Female,disloyal Customer,17,Business travel,Business,1269,0,0,0,3,3,0,3,3,3,2,5,5,5,3,107,126.0,satisfied +79254,128656,Male,disloyal Customer,55,Business travel,Business,2419,2,1,1,1,2,2,2,5,5,5,5,2,5,2,1,4.0,neutral or dissatisfied +79255,74689,Female,Loyal Customer,10,Personal Travel,Eco,1171,2,3,2,2,1,2,1,1,3,3,2,2,2,1,6,0.0,neutral or dissatisfied +79256,87527,Female,Loyal Customer,26,Personal Travel,Eco,373,2,4,2,3,4,2,4,4,5,3,5,2,5,4,61,69.0,neutral or dissatisfied +79257,33819,Female,Loyal Customer,8,Personal Travel,Eco,1428,4,4,5,3,4,5,4,4,1,3,4,4,4,4,0,0.0,neutral or dissatisfied +79258,94854,Female,Loyal Customer,38,Business travel,Business,2304,4,2,2,2,5,2,2,4,4,3,4,2,4,1,39,36.0,neutral or dissatisfied +79259,50615,Female,Loyal Customer,14,Personal Travel,Eco,373,2,0,2,4,2,2,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +79260,128065,Female,Loyal Customer,8,Personal Travel,Business,2845,3,0,3,3,3,2,2,5,3,5,3,2,3,2,1,49.0,neutral or dissatisfied +79261,82519,Male,Loyal Customer,53,Business travel,Business,1749,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +79262,105891,Male,Loyal Customer,48,Business travel,Business,283,0,0,0,3,4,4,5,5,5,2,2,3,5,5,12,9.0,satisfied +79263,96228,Female,Loyal Customer,25,Business travel,Business,1530,3,3,3,3,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +79264,10692,Male,Loyal Customer,64,Business travel,Business,1646,2,2,2,2,4,4,5,5,5,5,5,4,5,4,37,41.0,satisfied +79265,91802,Female,Loyal Customer,42,Personal Travel,Eco,588,3,1,3,4,5,3,4,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +79266,82570,Female,Loyal Customer,59,Business travel,Business,2044,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,7.0,satisfied +79267,85124,Female,Loyal Customer,54,Business travel,Business,731,3,3,3,3,5,4,5,3,3,4,3,3,3,3,3,16.0,satisfied +79268,101052,Male,Loyal Customer,23,Business travel,Business,368,2,2,5,2,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +79269,113951,Female,Loyal Customer,27,Business travel,Business,1728,5,5,5,5,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +79270,44728,Female,Loyal Customer,65,Personal Travel,Eco,67,3,1,0,1,1,2,2,5,5,0,5,1,5,4,0,12.0,neutral or dissatisfied +79271,96684,Male,Loyal Customer,24,Personal Travel,Eco Plus,1036,1,4,1,3,4,1,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +79272,23735,Male,Loyal Customer,63,Personal Travel,Eco,771,2,5,2,2,3,2,3,3,3,3,5,4,1,3,54,51.0,neutral or dissatisfied +79273,99127,Male,Loyal Customer,17,Personal Travel,Eco,237,3,4,0,4,2,0,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +79274,42387,Female,Loyal Customer,67,Personal Travel,Eco,817,3,1,3,4,2,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +79275,9825,Male,Loyal Customer,39,Personal Travel,Eco,388,4,3,4,3,1,4,1,1,3,4,4,2,1,1,0,20.0,neutral or dissatisfied +79276,16632,Female,Loyal Customer,70,Personal Travel,Business,605,3,5,3,3,4,2,5,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +79277,14383,Female,Loyal Customer,51,Business travel,Business,3319,2,1,1,1,4,3,3,2,2,3,2,4,2,4,57,69.0,neutral or dissatisfied +79278,99109,Female,Loyal Customer,22,Business travel,Business,3917,3,4,3,4,3,3,3,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +79279,13638,Male,Loyal Customer,38,Business travel,Business,3079,4,4,4,4,4,2,3,3,3,3,3,5,3,1,8,11.0,satisfied +79280,109485,Female,Loyal Customer,27,Business travel,Business,834,3,3,3,3,4,4,4,4,4,5,5,3,5,4,1,0.0,satisfied +79281,70703,Female,Loyal Customer,27,Personal Travel,Eco,837,0,3,0,2,2,0,2,2,3,3,3,2,3,2,0,0.0,satisfied +79282,30903,Female,Loyal Customer,49,Business travel,Eco,896,5,1,1,1,4,1,1,5,5,5,5,2,5,5,0,6.0,satisfied +79283,74679,Male,Loyal Customer,39,Personal Travel,Eco,1313,3,4,3,3,3,3,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +79284,92970,Male,Loyal Customer,27,Business travel,Business,738,2,2,2,2,3,3,3,3,3,2,4,4,5,3,12,0.0,satisfied +79285,83843,Male,Loyal Customer,49,Personal Travel,Eco,425,1,0,1,5,1,1,1,1,3,2,5,3,5,1,0,2.0,neutral or dissatisfied +79286,102215,Female,Loyal Customer,59,Business travel,Business,1635,1,1,1,1,3,5,5,4,4,4,5,5,4,4,8,3.0,satisfied +79287,28282,Male,Loyal Customer,55,Personal Travel,Eco,2402,1,2,1,4,1,2,2,3,2,3,4,2,3,2,0,3.0,neutral or dissatisfied +79288,54738,Female,Loyal Customer,15,Personal Travel,Eco,861,3,5,3,2,2,3,4,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +79289,75053,Male,Loyal Customer,70,Personal Travel,Eco,1592,3,4,3,2,2,3,3,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +79290,125874,Female,disloyal Customer,36,Business travel,Eco,520,3,0,3,5,5,3,5,5,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +79291,11738,Male,Loyal Customer,22,Business travel,Business,1811,2,1,1,1,2,2,2,2,4,3,4,2,3,2,34,32.0,neutral or dissatisfied +79292,98137,Male,Loyal Customer,47,Business travel,Business,2221,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +79293,14643,Female,disloyal Customer,26,Business travel,Eco,948,2,2,2,4,5,2,5,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +79294,25,Male,Loyal Customer,51,Business travel,Business,3460,3,3,3,3,2,4,5,5,5,4,5,5,5,4,0,2.0,satisfied +79295,45765,Male,disloyal Customer,20,Business travel,Eco,391,3,0,3,2,3,3,3,3,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +79296,11349,Female,Loyal Customer,42,Personal Travel,Eco,316,1,4,5,2,4,5,3,5,5,5,5,2,5,2,0,0.0,neutral or dissatisfied +79297,5328,Female,disloyal Customer,15,Business travel,Eco,733,4,4,4,2,4,4,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +79298,24016,Male,Loyal Customer,44,Business travel,Business,2627,1,1,1,1,2,5,1,4,4,5,4,2,4,2,3,0.0,satisfied +79299,38369,Female,Loyal Customer,18,Personal Travel,Eco,1050,3,5,4,1,3,4,3,3,5,3,4,4,5,3,0,36.0,neutral or dissatisfied +79300,94321,Male,Loyal Customer,49,Business travel,Business,2725,1,1,3,1,2,5,5,4,4,4,4,5,4,3,68,61.0,satisfied +79301,123172,Female,Loyal Customer,41,Business travel,Eco,507,1,3,3,3,1,1,1,1,2,2,4,4,3,1,38,21.0,neutral or dissatisfied +79302,112621,Male,Loyal Customer,10,Personal Travel,Eco,639,2,5,2,3,2,2,2,5,2,2,2,2,5,2,136,135.0,neutral or dissatisfied +79303,47855,Male,Loyal Customer,32,Business travel,Business,1729,1,2,2,2,1,1,1,1,3,3,4,3,4,1,81,74.0,neutral or dissatisfied +79304,73193,Female,Loyal Customer,58,Business travel,Eco,1258,4,1,1,1,2,4,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +79305,90751,Female,Loyal Customer,39,Business travel,Business,3554,1,3,2,3,3,4,3,1,1,1,1,4,1,1,0,7.0,neutral or dissatisfied +79306,64941,Male,Loyal Customer,37,Business travel,Business,247,4,2,2,2,5,4,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +79307,103507,Male,Loyal Customer,26,Business travel,Business,3441,5,5,5,5,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +79308,116629,Female,Loyal Customer,33,Business travel,Eco Plus,325,2,4,4,4,2,2,2,2,1,2,3,1,3,2,18,24.0,neutral or dissatisfied +79309,22785,Female,Loyal Customer,36,Business travel,Eco,302,4,3,3,3,4,4,4,4,1,2,4,5,3,4,0,0.0,satisfied +79310,114797,Male,Loyal Customer,56,Business travel,Business,2817,2,4,2,2,3,5,4,5,5,5,5,5,5,5,14,1.0,satisfied +79311,26387,Male,Loyal Customer,54,Business travel,Business,534,1,2,2,2,5,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +79312,292,Female,disloyal Customer,21,Business travel,Eco,1250,4,3,3,3,1,3,1,1,5,2,4,3,5,1,14,0.0,satisfied +79313,35188,Female,disloyal Customer,17,Business travel,Eco,950,4,4,4,3,2,4,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +79314,74507,Female,Loyal Customer,35,Business travel,Business,1188,2,4,3,4,1,2,1,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +79315,51667,Male,Loyal Customer,46,Business travel,Business,2195,1,5,5,5,3,2,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +79316,27737,Male,Loyal Customer,39,Business travel,Eco,1448,4,3,5,3,4,4,4,4,5,3,1,2,4,4,0,0.0,satisfied +79317,87887,Male,Loyal Customer,33,Business travel,Eco Plus,214,0,0,0,4,2,0,2,2,1,1,3,2,4,2,0,0.0,satisfied +79318,52447,Female,Loyal Customer,66,Personal Travel,Eco,355,3,4,3,1,5,5,5,2,2,3,3,4,2,3,0,0.0,neutral or dissatisfied +79319,43131,Female,Loyal Customer,54,Business travel,Eco Plus,236,3,4,3,3,5,2,4,2,2,3,2,4,2,3,0,6.0,satisfied +79320,22091,Female,Loyal Customer,50,Business travel,Eco,782,2,1,1,1,3,4,3,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +79321,57631,Female,disloyal Customer,48,Business travel,Business,200,4,4,4,2,4,4,3,4,3,3,4,5,4,4,3,2.0,satisfied +79322,86847,Male,Loyal Customer,19,Personal Travel,Eco,484,4,4,4,4,4,4,3,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +79323,94780,Male,Loyal Customer,42,Business travel,Business,3745,1,4,4,4,3,3,3,1,1,1,1,3,1,2,26,32.0,neutral or dissatisfied +79324,16598,Male,Loyal Customer,59,Business travel,Eco,1008,4,2,2,2,4,4,4,4,5,4,1,3,2,4,0,0.0,satisfied +79325,64830,Female,Loyal Customer,56,Business travel,Business,247,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +79326,30630,Female,Loyal Customer,36,Business travel,Eco,770,5,4,4,4,5,5,5,5,5,2,2,1,2,5,0,0.0,satisfied +79327,23,Female,Loyal Customer,56,Personal Travel,Eco,821,4,4,3,3,3,4,3,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +79328,126173,Male,Loyal Customer,44,Business travel,Business,590,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +79329,74024,Female,disloyal Customer,8,Business travel,Business,1471,2,4,2,2,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +79330,117240,Female,Loyal Customer,51,Personal Travel,Eco,304,4,3,5,3,3,1,2,3,3,5,3,3,3,1,1,0.0,neutral or dissatisfied +79331,117080,Female,disloyal Customer,15,Business travel,Eco,646,4,0,4,3,3,4,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +79332,54739,Male,Loyal Customer,67,Personal Travel,Eco,861,3,4,3,4,1,3,1,1,4,3,4,4,4,1,10,0.0,neutral or dissatisfied +79333,66018,Female,Loyal Customer,60,Business travel,Business,1055,5,5,5,5,5,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +79334,71763,Male,Loyal Customer,34,Business travel,Business,1846,1,1,1,1,4,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +79335,76626,Female,disloyal Customer,25,Business travel,Eco,147,4,0,4,3,4,4,4,4,2,2,4,4,3,4,0,0.0,satisfied +79336,40725,Male,Loyal Customer,25,Business travel,Business,2942,3,3,5,3,4,5,4,4,1,3,1,2,2,4,5,14.0,satisfied +79337,56843,Male,Loyal Customer,29,Business travel,Eco Plus,1605,3,4,4,4,3,3,3,3,4,2,3,3,4,3,0,14.0,neutral or dissatisfied +79338,47547,Male,Loyal Customer,34,Business travel,Eco Plus,584,5,1,1,1,5,5,5,5,1,2,1,1,4,5,0,24.0,satisfied +79339,15867,Male,Loyal Customer,39,Business travel,Business,332,3,2,3,3,5,4,3,5,5,5,5,2,5,4,108,91.0,satisfied +79340,27724,Female,Loyal Customer,59,Business travel,Eco,680,5,5,5,5,5,1,1,5,5,5,5,1,5,5,8,24.0,satisfied +79341,49321,Female,disloyal Customer,43,Business travel,Eco,190,5,4,5,5,2,5,2,2,4,3,2,3,5,2,0,0.0,satisfied +79342,106339,Female,Loyal Customer,26,Business travel,Business,2229,1,1,1,1,2,3,2,2,4,5,3,5,4,2,4,1.0,satisfied +79343,45107,Female,Loyal Customer,51,Business travel,Eco,177,4,3,3,3,1,5,5,4,4,4,4,1,4,3,1,0.0,satisfied +79344,53394,Male,Loyal Customer,43,Personal Travel,Eco Plus,1476,5,4,5,2,2,5,2,2,3,3,3,5,5,2,0,0.0,satisfied +79345,59829,Female,Loyal Customer,47,Business travel,Business,3849,4,4,4,4,3,4,4,4,4,4,4,3,4,4,10,0.0,satisfied +79346,99256,Male,Loyal Customer,14,Personal Travel,Eco Plus,495,3,4,5,3,2,5,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +79347,49135,Male,Loyal Customer,42,Business travel,Business,363,1,1,4,1,1,5,3,4,4,5,4,3,4,1,0,0.0,satisfied +79348,22293,Female,Loyal Customer,50,Business travel,Business,3142,5,3,5,5,2,1,1,5,5,5,4,2,5,2,0,0.0,satisfied +79349,100145,Female,Loyal Customer,60,Business travel,Eco,725,3,1,1,1,2,4,3,3,3,3,3,1,3,4,35,66.0,neutral or dissatisfied +79350,109942,Female,Loyal Customer,23,Personal Travel,Eco,1073,3,5,3,1,1,3,1,1,3,2,4,4,5,1,13,0.0,neutral or dissatisfied +79351,38467,Male,disloyal Customer,13,Business travel,Eco,846,2,2,2,3,5,2,2,5,1,2,3,4,4,5,6,21.0,neutral or dissatisfied +79352,98339,Male,Loyal Customer,18,Business travel,Business,1189,3,1,1,1,3,3,3,3,3,4,3,2,4,3,0,6.0,neutral or dissatisfied +79353,65166,Female,Loyal Customer,28,Personal Travel,Eco,469,1,5,1,1,4,1,1,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +79354,60641,Female,Loyal Customer,40,Business travel,Business,1620,3,3,3,3,2,4,4,4,4,4,4,5,4,4,6,0.0,satisfied +79355,34102,Female,Loyal Customer,49,Personal Travel,Business,1237,3,5,3,3,4,5,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +79356,72412,Male,Loyal Customer,45,Business travel,Business,2638,2,2,2,2,2,5,5,3,3,4,3,5,3,5,2,0.0,satisfied +79357,109854,Female,Loyal Customer,25,Business travel,Business,3803,3,2,2,2,3,3,3,3,3,3,3,1,2,3,0,0.0,neutral or dissatisfied +79358,49276,Female,Loyal Customer,50,Business travel,Business,3785,3,3,3,3,3,1,4,5,5,5,5,2,5,2,0,0.0,satisfied +79359,47360,Male,disloyal Customer,45,Business travel,Eco,558,2,3,2,1,1,2,1,1,1,4,3,2,5,1,0,0.0,neutral or dissatisfied +79360,110446,Female,Loyal Customer,24,Personal Travel,Eco,787,2,5,2,3,4,2,5,4,4,4,5,4,5,4,9,12.0,neutral or dissatisfied +79361,3355,Male,disloyal Customer,27,Business travel,Eco,296,2,0,2,3,4,2,4,4,4,5,3,1,3,4,16,23.0,neutral or dissatisfied +79362,101717,Male,Loyal Customer,47,Personal Travel,Eco,986,2,4,2,1,2,2,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +79363,111712,Female,Loyal Customer,25,Business travel,Business,2628,3,4,4,4,3,3,3,3,4,5,3,4,3,3,79,83.0,neutral or dissatisfied +79364,23803,Male,Loyal Customer,57,Business travel,Eco,374,2,2,2,2,2,2,2,2,3,1,2,1,2,2,6,14.0,neutral or dissatisfied +79365,46404,Female,Loyal Customer,36,Business travel,Business,1757,2,2,2,2,3,3,4,2,2,2,2,4,2,2,59,52.0,neutral or dissatisfied +79366,93338,Male,disloyal Customer,20,Business travel,Business,1024,4,4,4,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +79367,39635,Male,Loyal Customer,27,Personal Travel,Eco Plus,945,3,3,3,4,2,3,2,2,1,1,4,2,3,2,0,4.0,neutral or dissatisfied +79368,124953,Male,Loyal Customer,7,Personal Travel,Eco Plus,728,3,4,3,3,5,3,5,5,1,4,3,3,1,5,0,29.0,neutral or dissatisfied +79369,65121,Female,Loyal Customer,44,Personal Travel,Eco,190,1,4,1,3,4,5,4,5,5,1,5,3,5,4,1,0.0,neutral or dissatisfied +79370,83779,Male,disloyal Customer,26,Business travel,Business,425,1,0,1,5,2,1,2,2,4,4,4,3,5,2,0,2.0,neutral or dissatisfied +79371,42492,Female,Loyal Customer,43,Personal Travel,Eco,585,1,4,1,4,1,2,2,5,2,4,5,2,4,2,236,230.0,neutral or dissatisfied +79372,80212,Female,Loyal Customer,45,Business travel,Business,2153,2,2,4,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +79373,57831,Female,Loyal Customer,64,Personal Travel,Eco Plus,622,4,5,3,2,2,4,4,5,5,3,5,3,5,3,9,11.0,neutral or dissatisfied +79374,25115,Male,Loyal Customer,41,Business travel,Eco,946,5,4,4,4,5,5,5,5,2,2,4,4,1,5,79,61.0,satisfied +79375,26552,Female,Loyal Customer,51,Business travel,Eco Plus,990,5,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +79376,16561,Male,disloyal Customer,54,Business travel,Business,1092,1,2,2,3,1,1,5,1,1,5,1,5,1,1,113,101.0,neutral or dissatisfied +79377,19495,Male,Loyal Customer,32,Business travel,Business,3921,0,0,0,4,5,5,5,5,1,3,5,5,4,5,3,0.0,satisfied +79378,55371,Male,Loyal Customer,61,Business travel,Business,413,5,5,5,5,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +79379,16586,Female,Loyal Customer,7,Personal Travel,Eco,1092,2,1,2,2,2,2,2,2,3,1,2,1,2,2,97,120.0,neutral or dissatisfied +79380,41482,Male,Loyal Customer,35,Business travel,Eco,1242,5,2,2,2,5,5,5,5,2,3,5,1,2,5,0,13.0,satisfied +79381,32410,Male,Loyal Customer,29,Business travel,Business,2816,5,5,5,5,4,4,4,4,1,3,2,5,3,4,0,0.0,satisfied +79382,13482,Female,disloyal Customer,39,Business travel,Business,227,3,3,3,3,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +79383,88251,Female,Loyal Customer,49,Business travel,Eco,545,1,5,5,5,2,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +79384,129205,Female,disloyal Customer,34,Business travel,Eco,2288,4,4,4,2,2,4,2,2,2,1,1,3,1,2,0,0.0,neutral or dissatisfied +79385,63119,Male,Loyal Customer,41,Business travel,Business,2790,3,3,3,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +79386,68036,Male,Loyal Customer,50,Personal Travel,Business,868,3,5,3,3,5,1,5,3,3,3,3,1,3,3,0,7.0,neutral or dissatisfied +79387,20154,Female,Loyal Customer,53,Business travel,Eco,403,2,1,5,5,1,2,3,2,2,2,2,1,2,5,3,11.0,satisfied +79388,96275,Female,Loyal Customer,64,Personal Travel,Eco,546,1,1,4,3,3,4,4,4,4,4,4,1,4,4,33,18.0,neutral or dissatisfied +79389,57418,Female,Loyal Customer,15,Personal Travel,Eco,524,4,4,4,2,3,4,3,3,4,5,4,3,4,3,0,0.0,satisfied +79390,27330,Female,Loyal Customer,22,Business travel,Business,3999,2,2,2,2,3,3,3,3,4,4,3,1,5,3,0,0.0,satisfied +79391,57838,Male,Loyal Customer,56,Business travel,Business,1491,1,5,5,5,5,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +79392,15723,Female,Loyal Customer,24,Business travel,Business,2233,1,1,1,1,4,4,4,4,1,4,1,4,1,4,0,5.0,satisfied +79393,83529,Female,Loyal Customer,60,Business travel,Eco Plus,946,2,1,1,1,5,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +79394,33979,Male,disloyal Customer,27,Business travel,Eco,1598,5,5,5,3,3,5,1,3,1,4,4,3,3,3,48,76.0,satisfied +79395,89750,Female,Loyal Customer,29,Personal Travel,Eco,1035,3,3,3,4,3,5,5,1,5,4,4,5,3,5,179,158.0,neutral or dissatisfied +79396,37024,Female,Loyal Customer,46,Personal Travel,Eco Plus,899,4,5,4,4,3,3,3,5,5,4,5,1,5,3,3,10.0,neutral or dissatisfied +79397,50839,Male,Loyal Customer,9,Personal Travel,Eco,86,4,4,4,4,1,4,1,1,1,1,3,1,3,1,47,52.0,neutral or dissatisfied +79398,79588,Female,Loyal Customer,47,Business travel,Business,1781,5,5,5,5,2,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +79399,96315,Female,Loyal Customer,9,Personal Travel,Eco Plus,546,3,4,3,3,2,3,2,2,3,4,1,3,1,2,33,23.0,neutral or dissatisfied +79400,30300,Male,Loyal Customer,27,Business travel,Business,1533,3,3,3,3,4,4,4,4,1,4,4,4,1,4,0,0.0,satisfied +79401,74279,Female,Loyal Customer,50,Business travel,Business,2311,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +79402,40948,Male,Loyal Customer,68,Personal Travel,Eco Plus,588,2,5,3,2,2,3,2,2,4,4,5,4,4,2,0,0.0,neutral or dissatisfied +79403,105787,Female,Loyal Customer,70,Personal Travel,Eco,842,1,3,1,3,1,1,5,1,1,1,1,2,1,3,2,14.0,neutral or dissatisfied +79404,98155,Female,Loyal Customer,33,Business travel,Business,745,2,2,2,2,3,4,4,5,5,5,5,5,5,5,39,45.0,satisfied +79405,27305,Male,Loyal Customer,44,Business travel,Business,3165,3,3,3,3,5,5,2,4,4,4,4,2,4,5,0,0.0,satisfied +79406,122350,Female,Loyal Customer,40,Business travel,Business,529,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +79407,87874,Female,Loyal Customer,63,Business travel,Eco Plus,214,2,2,2,2,3,2,2,2,2,2,2,3,2,4,12,1.0,neutral or dissatisfied +79408,113236,Female,Loyal Customer,29,Personal Travel,Business,236,3,5,3,4,4,3,4,4,2,4,1,2,5,4,18,16.0,neutral or dissatisfied +79409,20213,Female,disloyal Customer,39,Business travel,Eco,137,3,3,3,2,1,3,5,1,4,3,2,4,1,1,58,56.0,neutral or dissatisfied +79410,122299,Male,Loyal Customer,32,Personal Travel,Eco,544,4,2,2,3,1,2,1,1,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +79411,52204,Female,Loyal Customer,57,Business travel,Eco,261,5,4,4,4,1,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +79412,47847,Female,Loyal Customer,27,Business travel,Eco,550,1,3,3,3,1,2,1,1,1,4,3,3,4,1,16,16.0,neutral or dissatisfied +79413,65342,Female,Loyal Customer,42,Business travel,Business,2718,4,4,4,4,3,4,4,5,5,5,5,3,5,5,7,2.0,satisfied +79414,48566,Male,Loyal Customer,15,Personal Travel,Eco,844,5,4,5,3,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +79415,14889,Female,disloyal Customer,26,Business travel,Eco,296,3,3,3,3,1,3,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +79416,79048,Female,Loyal Customer,53,Business travel,Business,2546,3,2,2,2,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +79417,32292,Female,Loyal Customer,41,Business travel,Business,1620,4,4,4,4,3,2,5,3,3,4,3,3,3,4,6,5.0,satisfied +79418,59883,Female,Loyal Customer,32,Business travel,Business,3278,2,2,2,2,2,2,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +79419,16617,Male,Loyal Customer,32,Personal Travel,Eco,1008,2,5,2,5,3,2,3,3,5,5,5,5,4,3,40,16.0,neutral or dissatisfied +79420,7924,Male,Loyal Customer,14,Personal Travel,Eco,1020,1,1,1,3,4,1,4,4,3,1,3,3,2,4,0,0.0,neutral or dissatisfied +79421,69385,Male,disloyal Customer,29,Business travel,Business,1096,3,3,3,4,4,3,4,4,1,2,3,3,4,4,0,9.0,neutral or dissatisfied +79422,99719,Male,Loyal Customer,50,Business travel,Business,1564,4,2,2,2,2,3,3,4,4,4,4,3,4,4,13,15.0,neutral or dissatisfied +79423,72773,Female,Loyal Customer,46,Business travel,Business,2340,5,5,3,5,3,4,5,3,3,3,3,5,3,5,15,21.0,satisfied +79424,23922,Female,Loyal Customer,20,Personal Travel,Eco,589,3,5,3,5,2,3,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +79425,123494,Female,Loyal Customer,36,Business travel,Business,2125,3,2,2,2,5,4,3,3,3,3,3,3,3,3,3,10.0,neutral or dissatisfied +79426,117913,Male,Loyal Customer,45,Business travel,Business,255,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,7.0,satisfied +79427,58304,Male,Loyal Customer,45,Business travel,Business,1739,5,5,5,5,2,5,5,5,5,5,5,4,5,5,8,2.0,satisfied +79428,18179,Male,disloyal Customer,68,Business travel,Business,224,4,4,4,3,3,4,3,3,2,3,3,2,3,3,26,17.0,neutral or dissatisfied +79429,51098,Male,Loyal Customer,27,Personal Travel,Eco,109,3,2,3,2,2,3,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +79430,82105,Female,Loyal Customer,25,Personal Travel,Eco,1298,2,4,1,3,3,1,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +79431,52089,Male,disloyal Customer,30,Business travel,Eco,639,2,0,1,5,2,1,2,2,2,5,1,2,5,2,9,0.0,neutral or dissatisfied +79432,108780,Female,Loyal Customer,53,Business travel,Business,406,2,2,2,2,3,5,4,4,4,4,4,3,4,4,1,0.0,satisfied +79433,91165,Male,Loyal Customer,29,Personal Travel,Eco,404,3,3,3,3,1,3,1,1,4,1,3,4,3,1,31,24.0,neutral or dissatisfied +79434,68878,Male,Loyal Customer,30,Business travel,Eco,936,3,5,5,5,3,2,3,3,2,4,3,4,2,3,9,19.0,neutral or dissatisfied +79435,7765,Female,Loyal Customer,58,Business travel,Business,2023,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +79436,29348,Female,Loyal Customer,30,Business travel,Business,2588,4,2,2,2,4,3,4,4,4,4,2,2,4,4,0,0.0,neutral or dissatisfied +79437,121509,Female,Loyal Customer,42,Business travel,Business,1727,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +79438,67425,Female,Loyal Customer,40,Business travel,Business,678,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +79439,73806,Male,Loyal Customer,46,Business travel,Eco Plus,204,4,4,4,4,4,4,4,4,5,1,1,4,1,4,3,0.0,satisfied +79440,113899,Female,Loyal Customer,29,Business travel,Eco,2295,3,4,4,4,3,3,3,3,1,5,3,3,3,3,6,2.0,neutral or dissatisfied +79441,19430,Male,Loyal Customer,17,Personal Travel,Eco,645,4,5,4,4,4,4,4,4,4,2,5,4,5,4,0,0.0,satisfied +79442,100717,Female,Loyal Customer,54,Business travel,Business,3892,5,5,4,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +79443,28759,Male,disloyal Customer,20,Business travel,Eco,624,3,0,3,3,5,3,5,5,3,1,1,5,1,5,0,0.0,neutral or dissatisfied +79444,22345,Male,disloyal Customer,25,Business travel,Eco,143,2,0,2,1,2,2,2,2,3,4,3,3,1,2,0,0.0,neutral or dissatisfied +79445,17607,Female,Loyal Customer,47,Personal Travel,Eco,196,3,2,3,3,4,3,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +79446,109348,Male,disloyal Customer,24,Business travel,Business,1046,4,5,4,1,4,4,3,4,3,4,4,5,5,4,13,0.0,satisfied +79447,125505,Male,Loyal Customer,16,Personal Travel,Eco,666,2,4,2,3,3,2,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +79448,60775,Female,Loyal Customer,51,Personal Travel,Eco,628,2,1,2,4,1,3,3,2,2,2,2,2,2,1,14,0.0,neutral or dissatisfied +79449,83254,Male,disloyal Customer,24,Business travel,Eco,1979,3,4,4,2,3,3,3,3,1,5,1,3,2,3,59,89.0,neutral or dissatisfied +79450,110035,Male,Loyal Customer,63,Business travel,Business,1984,2,1,5,1,2,4,4,2,2,2,2,1,2,2,0,5.0,neutral or dissatisfied +79451,93605,Female,disloyal Customer,44,Business travel,Eco,704,1,1,1,3,1,1,1,1,1,2,4,1,4,1,8,5.0,neutral or dissatisfied +79452,91183,Female,Loyal Customer,24,Personal Travel,Eco,444,3,5,3,4,3,3,4,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +79453,1620,Male,disloyal Customer,30,Business travel,Business,999,0,0,0,2,5,0,5,5,5,3,4,4,4,5,0,0.0,satisfied +79454,17404,Female,Loyal Customer,57,Business travel,Eco,351,4,5,5,5,2,5,4,4,4,4,4,2,4,4,0,0.0,satisfied +79455,63970,Male,Loyal Customer,27,Business travel,Eco Plus,1172,5,5,5,5,5,4,5,5,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +79456,95165,Female,Loyal Customer,52,Personal Travel,Eco,248,4,5,0,3,2,4,5,4,4,0,4,4,4,4,1,2.0,neutral or dissatisfied +79457,124061,Male,Loyal Customer,64,Business travel,Business,2153,2,5,5,5,3,1,3,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +79458,64985,Male,disloyal Customer,27,Business travel,Eco,247,4,0,4,1,2,4,2,2,3,1,3,5,1,2,1,2.0,neutral or dissatisfied +79459,51169,Female,Loyal Customer,57,Personal Travel,Eco,134,1,0,1,1,4,5,4,5,5,1,5,4,5,5,17,13.0,neutral or dissatisfied +79460,12484,Female,Loyal Customer,37,Business travel,Eco Plus,253,4,5,5,5,4,5,4,4,3,4,1,4,1,4,0,0.0,satisfied +79461,105153,Female,Loyal Customer,60,Business travel,Business,1968,1,1,1,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +79462,72701,Female,Loyal Customer,46,Personal Travel,Eco,1121,3,4,3,2,3,5,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +79463,123113,Female,Loyal Customer,45,Business travel,Business,2283,1,3,3,3,3,3,3,1,1,1,1,4,1,2,32,43.0,neutral or dissatisfied +79464,82858,Female,Loyal Customer,53,Business travel,Business,2359,1,1,1,1,5,5,4,4,4,4,4,3,4,4,5,0.0,satisfied +79465,81131,Male,Loyal Customer,48,Personal Travel,Eco,991,2,4,2,2,4,2,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +79466,32148,Female,disloyal Customer,37,Business travel,Eco,201,2,0,2,3,4,2,4,4,4,1,3,3,2,4,0,0.0,neutral or dissatisfied +79467,102648,Female,Loyal Customer,57,Business travel,Business,3448,4,4,4,4,4,4,5,4,4,4,4,3,4,3,4,0.0,satisfied +79468,87980,Male,Loyal Customer,48,Business travel,Business,2761,4,4,4,4,2,4,5,4,4,5,4,3,4,4,24,26.0,satisfied +79469,23630,Male,Loyal Customer,58,Business travel,Eco,911,4,3,3,3,4,4,4,4,5,5,5,5,1,4,2,0.0,satisfied +79470,84583,Male,Loyal Customer,47,Business travel,Business,2751,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +79471,19040,Female,Loyal Customer,26,Personal Travel,Eco Plus,788,2,5,2,3,4,2,3,4,3,4,4,3,5,4,59,38.0,neutral or dissatisfied +79472,86514,Female,Loyal Customer,44,Personal Travel,Eco,762,3,5,3,2,5,5,5,5,5,3,5,5,5,3,21,25.0,neutral or dissatisfied +79473,92786,Male,Loyal Customer,16,Personal Travel,Eco,1671,5,3,5,3,4,5,4,4,4,1,4,3,4,4,0,0.0,satisfied +79474,41519,Male,Loyal Customer,49,Business travel,Eco,1482,5,3,5,3,5,5,5,5,5,5,1,4,1,5,0,0.0,satisfied +79475,110319,Female,disloyal Customer,24,Business travel,Eco,787,2,2,2,1,4,2,4,4,5,5,5,3,5,4,6,0.0,neutral or dissatisfied +79476,128160,Male,Loyal Customer,39,Business travel,Business,1849,4,4,4,4,4,5,4,4,4,4,4,4,4,3,26,48.0,satisfied +79477,62740,Female,disloyal Customer,41,Business travel,Business,2399,3,2,2,5,5,3,5,5,3,5,3,3,5,5,2,0.0,neutral or dissatisfied +79478,31184,Male,Loyal Customer,43,Business travel,Eco,349,5,4,4,4,5,5,5,5,2,4,4,4,5,5,0,4.0,satisfied +79479,111306,Female,Loyal Customer,34,Business travel,Business,2248,5,5,5,5,4,4,4,5,5,5,5,4,5,5,16,7.0,satisfied +79480,91093,Female,Loyal Customer,52,Personal Travel,Eco,366,3,5,3,2,5,5,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +79481,123237,Female,Loyal Customer,55,Personal Travel,Eco,468,3,4,3,5,4,4,5,4,4,3,4,5,4,3,3,27.0,neutral or dissatisfied +79482,12376,Male,Loyal Customer,21,Business travel,Business,262,3,2,3,3,5,5,5,5,4,5,4,2,4,5,0,0.0,satisfied +79483,29855,Male,Loyal Customer,56,Business travel,Eco,261,2,1,1,1,2,2,2,2,1,5,5,1,2,2,0,0.0,satisfied +79484,129824,Female,Loyal Customer,29,Personal Travel,Eco,337,4,4,3,1,3,3,3,3,4,4,5,4,4,3,0,0.0,satisfied +79485,66541,Male,Loyal Customer,52,Business travel,Business,3457,5,5,5,5,3,5,5,4,4,5,4,3,4,4,5,6.0,satisfied +79486,78536,Female,Loyal Customer,26,Personal Travel,Eco,666,2,4,2,4,4,2,4,4,3,3,4,3,4,4,0,45.0,neutral or dissatisfied +79487,9401,Male,Loyal Customer,51,Personal Travel,Eco,182,3,4,3,3,2,3,2,2,3,4,4,3,5,2,46,35.0,neutral or dissatisfied +79488,40986,Female,Loyal Customer,60,Business travel,Business,3902,2,4,4,4,2,4,4,2,2,2,2,3,2,3,104,98.0,neutral or dissatisfied +79489,111566,Female,Loyal Customer,30,Business travel,Business,1626,2,4,4,4,2,2,2,2,4,3,4,2,4,2,15,0.0,neutral or dissatisfied +79490,57289,Male,disloyal Customer,25,Business travel,Eco Plus,628,4,1,4,4,3,4,3,3,2,4,4,3,3,3,0,0.0,neutral or dissatisfied +79491,118821,Male,Loyal Customer,40,Business travel,Business,1892,3,2,3,3,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +79492,126907,Female,Loyal Customer,58,Business travel,Business,304,0,0,0,2,4,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +79493,100542,Female,Loyal Customer,45,Personal Travel,Eco,580,2,4,2,1,5,5,4,5,5,2,1,3,5,3,28,24.0,neutral or dissatisfied +79494,4279,Male,disloyal Customer,29,Business travel,Eco,502,4,2,4,3,2,4,2,2,4,3,3,4,4,2,8,68.0,neutral or dissatisfied +79495,69597,Male,Loyal Customer,40,Personal Travel,Eco,2475,3,2,3,3,3,4,4,2,2,2,3,4,1,4,0,3.0,neutral or dissatisfied +79496,61156,Female,disloyal Customer,30,Business travel,Business,846,5,5,5,4,3,5,3,3,3,3,4,5,4,3,0,37.0,satisfied +79497,109046,Male,Loyal Customer,32,Business travel,Eco,994,2,4,4,4,2,2,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +79498,109240,Male,Loyal Customer,8,Personal Travel,Eco,612,2,1,2,4,1,2,1,1,1,5,4,4,3,1,0,4.0,neutral or dissatisfied +79499,41248,Female,Loyal Customer,9,Personal Travel,Eco,643,2,2,2,4,1,2,4,1,2,5,3,3,4,1,0,5.0,neutral or dissatisfied +79500,94678,Female,disloyal Customer,59,Business travel,Eco,248,4,2,4,4,3,4,3,3,1,2,4,3,4,3,10,9.0,neutral or dissatisfied +79501,87151,Male,Loyal Customer,41,Personal Travel,Eco Plus,594,3,1,3,2,2,3,2,2,4,2,2,4,2,2,0,0.0,neutral or dissatisfied +79502,59140,Male,Loyal Customer,26,Personal Travel,Eco,1744,2,4,2,2,2,2,2,2,4,5,3,5,5,2,2,0.0,neutral or dissatisfied +79503,110857,Female,Loyal Customer,46,Business travel,Business,2149,5,5,5,5,3,4,5,4,4,4,4,4,4,4,82,57.0,satisfied +79504,26303,Male,Loyal Customer,50,Business travel,Eco Plus,799,2,3,5,3,2,2,2,2,2,2,3,5,4,2,0,0.0,satisfied +79505,92117,Female,Loyal Customer,68,Personal Travel,Eco,1535,3,1,3,3,1,2,3,2,2,3,2,1,2,1,0,13.0,neutral or dissatisfied +79506,29839,Male,disloyal Customer,36,Business travel,Eco,399,4,3,4,3,4,4,4,4,1,2,4,4,1,4,0,0.0,neutral or dissatisfied +79507,7967,Female,Loyal Customer,51,Personal Travel,Eco,594,1,4,1,4,1,1,2,1,1,1,1,4,1,4,5,20.0,neutral or dissatisfied +79508,71960,Male,Loyal Customer,53,Business travel,Business,1440,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +79509,86428,Male,Loyal Customer,38,Business travel,Eco,794,1,3,4,3,1,1,1,1,2,2,3,3,2,1,93,82.0,neutral or dissatisfied +79510,80193,Male,Loyal Customer,9,Personal Travel,Eco,2586,3,3,3,4,3,1,1,2,2,3,4,1,2,1,44,39.0,neutral or dissatisfied +79511,120457,Male,Loyal Customer,32,Personal Travel,Eco,337,4,5,4,2,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +79512,274,Female,disloyal Customer,27,Business travel,Business,802,4,3,3,4,1,3,1,1,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +79513,106609,Male,Loyal Customer,19,Personal Travel,Eco,589,2,4,2,1,2,2,2,2,1,5,3,5,2,2,0,0.0,neutral or dissatisfied +79514,129251,Female,Loyal Customer,11,Personal Travel,Eco,1464,3,3,3,3,1,3,1,1,1,3,1,4,2,1,0,1.0,neutral or dissatisfied +79515,3039,Male,Loyal Customer,34,Business travel,Business,1616,2,2,4,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +79516,31155,Male,Loyal Customer,7,Personal Travel,Eco,495,3,3,3,3,2,3,2,2,4,1,1,3,3,2,0,0.0,neutral or dissatisfied +79517,78464,Male,Loyal Customer,29,Business travel,Business,526,2,2,2,2,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +79518,81380,Male,Loyal Customer,48,Business travel,Business,2224,1,1,1,1,4,5,4,4,4,4,4,5,4,3,3,0.0,satisfied +79519,54665,Female,Loyal Customer,40,Business travel,Business,854,4,4,4,4,4,1,5,4,4,4,4,5,4,1,0,0.0,satisfied +79520,2137,Male,Loyal Customer,52,Personal Travel,Eco,404,4,3,4,4,5,4,5,5,2,2,3,4,4,5,0,0.0,neutral or dissatisfied +79521,94510,Female,Loyal Customer,53,Business travel,Business,2942,3,3,3,3,4,4,4,5,5,5,5,5,5,3,23,15.0,satisfied +79522,7786,Male,Loyal Customer,20,Personal Travel,Business,650,4,5,4,5,2,4,2,2,4,1,5,3,4,2,0,7.0,neutral or dissatisfied +79523,38908,Female,Loyal Customer,45,Business travel,Eco,320,5,4,4,4,1,5,4,5,5,5,5,1,5,5,0,7.0,satisfied +79524,82691,Male,Loyal Customer,52,Business travel,Business,3622,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +79525,123283,Male,Loyal Customer,15,Personal Travel,Eco,650,1,3,1,3,3,1,1,3,2,5,3,3,3,3,128,127.0,neutral or dissatisfied +79526,25538,Female,Loyal Customer,19,Personal Travel,Eco,547,4,5,4,1,4,4,4,4,5,5,3,3,1,4,104,95.0,neutral or dissatisfied +79527,97944,Male,Loyal Customer,69,Business travel,Business,684,1,5,5,5,2,3,4,1,1,2,1,2,1,2,7,12.0,neutral or dissatisfied +79528,115043,Male,Loyal Customer,47,Business travel,Business,2123,1,1,1,1,3,4,4,5,5,5,5,5,5,5,5,0.0,satisfied +79529,124551,Female,Loyal Customer,50,Business travel,Business,2798,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +79530,20961,Male,Loyal Customer,19,Business travel,Business,2388,3,3,3,3,5,5,5,5,5,4,5,1,2,5,0,0.0,satisfied +79531,112333,Female,Loyal Customer,43,Business travel,Business,846,3,3,3,3,2,5,5,3,3,4,3,4,3,5,0,0.0,satisfied +79532,15622,Female,Loyal Customer,59,Personal Travel,Eco,228,2,4,2,4,5,3,3,5,5,2,2,4,5,4,64,48.0,neutral or dissatisfied +79533,118726,Female,Loyal Customer,38,Personal Travel,Eco,451,1,3,1,3,5,1,5,5,1,5,4,1,4,5,73,72.0,neutral or dissatisfied +79534,116260,Female,Loyal Customer,52,Personal Travel,Eco,308,5,1,2,3,3,3,3,5,5,2,2,4,5,1,0,0.0,satisfied +79535,81335,Male,disloyal Customer,25,Business travel,Business,1299,4,4,4,2,3,4,3,3,5,4,5,4,4,3,12,0.0,satisfied +79536,17785,Male,Loyal Customer,64,Business travel,Business,1214,2,5,5,5,3,3,2,2,2,2,2,2,2,2,28,11.0,neutral or dissatisfied +79537,96165,Male,disloyal Customer,27,Business travel,Business,687,4,4,4,5,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +79538,115433,Female,disloyal Customer,59,Business travel,Eco,308,2,3,2,3,1,2,1,1,3,5,3,4,3,1,92,93.0,neutral or dissatisfied +79539,127715,Male,Loyal Customer,44,Business travel,Business,3750,3,3,3,3,2,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +79540,44804,Male,Loyal Customer,32,Business travel,Business,2130,4,5,5,5,4,4,4,4,4,5,3,4,3,4,7,18.0,neutral or dissatisfied +79541,104406,Male,disloyal Customer,25,Business travel,Eco,1147,5,5,5,3,5,5,5,5,5,2,5,4,4,5,11,4.0,satisfied +79542,96084,Male,Loyal Customer,47,Personal Travel,Eco,1069,4,4,4,4,1,4,1,1,2,4,1,2,5,1,4,6.0,neutral or dissatisfied +79543,66810,Female,Loyal Customer,68,Business travel,Business,2524,4,4,4,4,4,4,4,4,4,4,4,5,4,5,3,1.0,satisfied +79544,79834,Male,Loyal Customer,38,Business travel,Business,2029,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +79545,99751,Male,Loyal Customer,35,Business travel,Business,255,5,5,5,5,2,5,3,5,5,5,5,2,5,5,0,0.0,satisfied +79546,77048,Male,Loyal Customer,48,Business travel,Business,1553,4,4,4,4,3,5,5,5,5,5,5,4,5,5,2,0.0,satisfied +79547,44366,Female,Loyal Customer,30,Personal Travel,Eco,596,1,1,1,4,3,1,3,3,3,2,3,1,3,3,2,11.0,neutral or dissatisfied +79548,39823,Female,disloyal Customer,37,Business travel,Eco,272,2,0,2,3,4,2,4,4,5,2,4,4,4,4,3,1.0,neutral or dissatisfied +79549,97512,Male,Loyal Customer,61,Personal Travel,Eco Plus,670,2,5,2,4,2,2,2,2,4,5,4,5,4,2,0,11.0,neutral or dissatisfied +79550,47310,Female,Loyal Customer,37,Business travel,Business,599,3,3,3,3,5,1,1,4,4,4,4,1,4,5,0,0.0,satisfied +79551,58926,Female,Loyal Customer,60,Personal Travel,Eco,888,4,3,4,1,3,5,1,1,1,4,1,5,1,2,76,80.0,neutral or dissatisfied +79552,42795,Male,Loyal Customer,47,Business travel,Business,3352,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,5.0,satisfied +79553,118571,Male,Loyal Customer,48,Business travel,Business,369,5,5,5,5,4,4,5,5,5,4,5,4,5,5,14,20.0,satisfied +79554,54724,Male,Loyal Customer,43,Personal Travel,Eco,965,1,5,1,3,1,1,1,1,5,2,4,5,4,1,39,31.0,neutral or dissatisfied +79555,47821,Male,Loyal Customer,61,Business travel,Eco,329,5,5,5,5,5,5,5,5,5,1,4,5,2,5,165,162.0,satisfied +79556,69977,Female,disloyal Customer,16,Business travel,Eco,236,3,2,3,4,2,3,4,2,4,1,4,2,4,2,4,13.0,neutral or dissatisfied +79557,18042,Female,Loyal Customer,44,Business travel,Eco,488,2,2,2,2,1,1,2,2,2,2,2,5,2,2,0,48.0,satisfied +79558,34166,Female,Loyal Customer,60,Business travel,Eco,1189,3,4,5,4,1,3,2,3,3,3,3,2,3,1,0,11.0,neutral or dissatisfied +79559,14893,Male,disloyal Customer,22,Business travel,Eco,315,0,0,0,4,5,0,5,5,5,2,4,1,4,5,58,80.0,satisfied +79560,87376,Female,Loyal Customer,50,Business travel,Business,425,2,2,2,2,3,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +79561,93378,Female,Loyal Customer,49,Business travel,Business,271,1,1,1,1,2,4,4,5,5,5,5,5,5,3,10,4.0,satisfied +79562,62540,Male,disloyal Customer,27,Business travel,Business,1744,1,1,1,1,2,1,3,2,4,4,4,5,5,2,35,6.0,neutral or dissatisfied +79563,5740,Male,Loyal Customer,26,Business travel,Business,2283,3,3,3,3,5,4,5,5,5,4,4,3,5,5,0,0.0,satisfied +79564,104582,Male,Loyal Customer,53,Business travel,Business,2263,3,1,1,1,4,2,2,3,3,3,3,2,3,3,25,33.0,neutral or dissatisfied +79565,34703,Male,Loyal Customer,59,Business travel,Eco,301,4,1,1,1,4,4,4,4,4,2,1,3,5,4,12,11.0,satisfied +79566,129560,Male,Loyal Customer,37,Personal Travel,Eco,2218,2,4,3,3,4,3,3,4,2,5,4,3,3,4,2,0.0,neutral or dissatisfied +79567,63018,Female,disloyal Customer,30,Business travel,Eco,862,1,1,1,4,2,1,2,2,3,5,3,1,4,2,39,25.0,neutral or dissatisfied +79568,12390,Female,Loyal Customer,15,Business travel,Business,201,1,5,5,5,2,1,1,2,1,1,2,2,2,2,36,29.0,neutral or dissatisfied +79569,56984,Female,Loyal Customer,21,Personal Travel,Eco,2425,1,3,1,3,1,2,2,2,5,2,3,2,3,2,8,0.0,neutral or dissatisfied +79570,32499,Male,Loyal Customer,34,Business travel,Business,101,0,5,0,3,1,2,3,4,4,4,4,4,4,1,0,0.0,satisfied +79571,103895,Male,disloyal Customer,27,Business travel,Eco Plus,1056,2,2,2,4,5,2,5,5,3,1,3,1,3,5,16,1.0,neutral or dissatisfied +79572,25198,Female,disloyal Customer,25,Business travel,Business,919,0,0,0,2,3,0,3,3,5,5,4,5,5,3,8,1.0,satisfied +79573,39274,Female,Loyal Customer,26,Business travel,Business,212,1,5,5,5,1,1,1,1,2,4,3,2,3,1,6,8.0,neutral or dissatisfied +79574,31817,Male,Loyal Customer,38,Business travel,Eco Plus,4983,4,4,4,4,4,4,4,3,4,3,5,4,5,4,2,0.0,satisfied +79575,45857,Female,Loyal Customer,15,Personal Travel,Eco Plus,517,2,5,2,1,2,2,2,2,1,4,5,5,2,2,0,2.0,neutral or dissatisfied +79576,52401,Female,Loyal Customer,10,Personal Travel,Eco,751,2,5,2,2,1,2,1,1,5,5,5,3,5,1,57,75.0,neutral or dissatisfied +79577,28276,Male,Loyal Customer,29,Business travel,Eco,2402,2,2,2,2,2,2,2,3,2,3,3,2,4,2,17,59.0,neutral or dissatisfied +79578,53814,Female,disloyal Customer,20,Business travel,Eco,140,4,0,4,4,5,4,5,5,3,2,3,5,4,5,0,1.0,satisfied +79579,101633,Female,disloyal Customer,23,Business travel,Eco,1371,5,5,5,3,3,5,3,3,5,5,5,3,5,3,0,0.0,satisfied +79580,85279,Male,Loyal Customer,62,Personal Travel,Eco,731,2,1,2,3,5,2,5,5,3,1,3,3,2,5,1,0.0,neutral or dissatisfied +79581,118290,Male,Loyal Customer,44,Business travel,Business,3980,1,1,1,1,4,4,4,4,4,4,4,5,4,4,1,0.0,satisfied +79582,114957,Male,disloyal Customer,33,Business travel,Business,372,2,2,2,3,3,2,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +79583,40327,Female,Loyal Customer,57,Business travel,Eco Plus,347,4,1,1,1,2,3,3,4,4,4,4,4,4,4,9,17.0,neutral or dissatisfied +79584,50348,Male,Loyal Customer,60,Business travel,Business,1950,5,5,5,5,5,4,2,4,4,4,4,2,4,1,0,0.0,satisfied +79585,94251,Male,Loyal Customer,53,Business travel,Business,2295,2,2,2,2,3,5,5,5,5,5,5,3,5,3,5,0.0,satisfied +79586,28723,Female,Loyal Customer,40,Personal Travel,Eco,2717,1,4,1,2,1,3,5,3,2,5,5,5,3,5,0,18.0,neutral or dissatisfied +79587,92622,Male,Loyal Customer,44,Business travel,Business,2011,1,1,1,1,4,4,5,4,4,4,4,5,4,4,55,60.0,satisfied +79588,53558,Male,Loyal Customer,17,Personal Travel,Business,1195,2,1,2,4,4,2,4,4,2,4,3,1,4,4,31,22.0,neutral or dissatisfied +79589,121285,Male,Loyal Customer,52,Personal Travel,Eco Plus,1814,2,5,1,5,4,1,4,4,4,5,4,3,5,4,0,9.0,neutral or dissatisfied +79590,103402,Female,Loyal Customer,35,Business travel,Business,237,3,2,2,2,1,4,3,3,3,3,3,3,3,4,2,2.0,neutral or dissatisfied +79591,57589,Male,Loyal Customer,63,Personal Travel,Eco,1597,1,4,2,3,2,2,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +79592,25839,Female,Loyal Customer,60,Business travel,Eco,484,5,3,3,3,2,5,3,4,4,5,4,4,4,3,2,3.0,satisfied +79593,94177,Female,Loyal Customer,51,Business travel,Business,1974,4,4,4,4,2,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +79594,56015,Female,Loyal Customer,39,Business travel,Business,2586,4,4,4,4,3,3,3,5,4,4,4,3,5,3,0,0.0,satisfied +79595,33716,Male,Loyal Customer,59,Personal Travel,Eco,814,1,1,1,4,1,1,1,1,4,5,2,4,3,1,5,0.0,neutral or dissatisfied +79596,99555,Female,Loyal Customer,27,Business travel,Business,3693,3,3,3,3,3,3,3,3,1,2,4,2,4,3,0,14.0,neutral or dissatisfied +79597,15904,Female,Loyal Customer,59,Personal Travel,Eco,660,4,2,4,3,4,4,3,2,2,4,2,3,2,2,4,0.0,neutral or dissatisfied +79598,53457,Male,Loyal Customer,50,Business travel,Eco,2288,3,1,1,1,3,3,3,3,2,2,3,1,2,3,0,0.0,neutral or dissatisfied +79599,102439,Female,Loyal Customer,58,Personal Travel,Eco,407,3,3,3,3,3,5,5,5,5,3,5,2,5,2,38,19.0,neutral or dissatisfied +79600,57189,Male,Loyal Customer,66,Personal Travel,Eco Plus,2227,3,4,3,2,5,3,5,5,3,3,5,3,5,5,62,53.0,neutral or dissatisfied +79601,73191,Female,Loyal Customer,30,Business travel,Business,1258,4,4,4,4,4,4,4,4,3,2,3,1,4,4,9,17.0,neutral or dissatisfied +79602,68824,Male,Loyal Customer,35,Business travel,Business,1995,5,5,5,5,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +79603,91358,Male,Loyal Customer,25,Personal Travel,Eco Plus,250,3,5,3,5,3,3,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +79604,74333,Female,Loyal Customer,57,Business travel,Business,1843,4,4,4,4,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +79605,4306,Male,Loyal Customer,42,Business travel,Eco Plus,102,4,5,2,5,5,4,5,5,4,2,1,2,5,5,21,22.0,satisfied +79606,64118,Male,Loyal Customer,60,Business travel,Business,2288,2,2,2,2,2,2,2,5,4,5,5,2,5,2,0,0.0,satisfied +79607,16312,Female,disloyal Customer,52,Business travel,Eco,628,2,0,2,3,5,2,4,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +79608,45272,Male,Loyal Customer,26,Personal Travel,Business,150,2,4,2,4,2,2,2,2,2,5,2,5,3,2,0,0.0,neutral or dissatisfied +79609,32666,Female,Loyal Customer,39,Business travel,Eco,216,4,5,5,5,4,4,4,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +79610,67583,Male,disloyal Customer,28,Business travel,Business,1205,1,1,1,4,4,1,4,4,4,3,5,4,5,4,14,14.0,neutral or dissatisfied +79611,40041,Female,Loyal Customer,24,Business travel,Business,2647,2,2,2,2,5,5,5,5,4,4,4,1,1,5,15,3.0,satisfied +79612,44258,Female,Loyal Customer,11,Personal Travel,Eco,222,4,0,4,3,5,4,5,5,4,5,4,4,5,5,0,0.0,satisfied +79613,83847,Male,Loyal Customer,7,Personal Travel,Eco,425,2,2,2,4,5,2,1,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +79614,34035,Female,Loyal Customer,46,Personal Travel,Eco Plus,1598,3,3,3,3,3,4,3,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +79615,22932,Female,Loyal Customer,53,Business travel,Business,2489,2,2,5,2,1,5,1,5,5,4,5,3,5,5,0,0.0,satisfied +79616,63016,Male,disloyal Customer,29,Business travel,Business,967,4,4,4,2,4,4,4,4,5,5,4,5,4,4,0,4.0,neutral or dissatisfied +79617,23456,Female,Loyal Customer,7,Business travel,Business,516,3,2,2,2,3,3,3,3,1,1,4,3,4,3,0,10.0,neutral or dissatisfied +79618,129762,Male,Loyal Customer,48,Business travel,Eco,337,2,5,5,5,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +79619,6715,Male,Loyal Customer,41,Personal Travel,Eco,438,1,2,4,3,2,4,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +79620,120597,Female,Loyal Customer,29,Personal Travel,Eco,980,2,4,2,3,5,2,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +79621,62592,Male,Loyal Customer,65,Business travel,Business,2567,1,1,1,1,5,5,3,4,4,4,4,4,4,5,0,0.0,satisfied +79622,89833,Female,Loyal Customer,33,Personal Travel,Eco Plus,1035,3,5,3,3,4,3,4,4,5,3,4,4,4,4,1,0.0,neutral or dissatisfied +79623,27252,Female,disloyal Customer,22,Business travel,Eco,1050,2,2,2,4,4,2,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +79624,77774,Female,Loyal Customer,48,Personal Travel,Eco,731,1,1,1,3,3,3,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +79625,56704,Female,disloyal Customer,61,Personal Travel,Eco,1065,3,4,3,5,2,3,2,2,5,3,4,3,4,2,35,12.0,neutral or dissatisfied +79626,59896,Female,disloyal Customer,39,Business travel,Business,1068,3,3,3,2,3,3,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +79627,40987,Male,Loyal Customer,43,Business travel,Business,984,4,2,4,4,3,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +79628,108354,Male,disloyal Customer,25,Business travel,Eco,941,2,2,2,3,1,2,1,1,4,4,4,5,3,1,65,67.0,neutral or dissatisfied +79629,105089,Female,Loyal Customer,57,Business travel,Business,220,5,5,5,5,4,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +79630,120271,Female,Loyal Customer,18,Business travel,Business,1576,3,3,3,3,5,5,5,5,5,3,5,4,5,5,17,46.0,satisfied +79631,7740,Male,Loyal Customer,24,Business travel,Business,3489,2,4,4,4,2,2,2,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +79632,2315,Male,Loyal Customer,32,Personal Travel,Eco,1041,2,4,3,3,2,3,2,2,4,3,5,5,5,2,0,33.0,neutral or dissatisfied +79633,107598,Male,Loyal Customer,59,Business travel,Business,1581,1,1,1,1,4,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +79634,111223,Male,disloyal Customer,22,Business travel,Eco,203,0,5,0,4,1,0,2,1,1,5,3,4,3,1,1,0.0,satisfied +79635,128179,Male,Loyal Customer,64,Personal Travel,Eco,1849,2,2,3,3,2,3,2,2,1,4,3,4,3,2,4,0.0,neutral or dissatisfied +79636,113168,Male,Loyal Customer,38,Business travel,Business,1731,0,0,0,2,1,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +79637,34574,Female,Loyal Customer,43,Business travel,Business,1598,3,3,3,3,1,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +79638,114689,Female,Loyal Customer,61,Business travel,Business,362,1,1,5,1,3,4,4,5,5,5,5,5,5,5,15,12.0,satisfied +79639,76102,Male,Loyal Customer,14,Personal Travel,Eco,707,1,5,1,2,2,1,2,2,1,1,5,4,4,2,0,12.0,neutral or dissatisfied +79640,1662,Male,Loyal Customer,33,Personal Travel,Eco,551,2,0,1,5,3,1,3,3,5,4,4,3,4,3,0,3.0,neutral or dissatisfied +79641,82935,Male,Loyal Customer,9,Business travel,Business,594,4,4,4,4,2,2,2,2,3,2,4,5,5,2,0,0.0,satisfied +79642,49672,Male,Loyal Customer,57,Business travel,Business,308,5,5,5,5,5,2,3,4,4,4,4,1,4,4,0,0.0,satisfied +79643,57695,Female,disloyal Customer,20,Business travel,Business,867,5,5,5,4,3,5,4,3,4,4,4,3,5,3,0,0.0,satisfied +79644,3620,Female,Loyal Customer,59,Business travel,Business,144,3,3,3,3,5,5,5,4,4,4,5,3,4,5,0,9.0,satisfied +79645,24256,Female,Loyal Customer,37,Personal Travel,Eco,147,4,3,0,1,3,0,3,3,4,4,1,2,1,3,49,40.0,neutral or dissatisfied +79646,27709,Female,disloyal Customer,46,Business travel,Business,1448,1,1,1,4,1,1,1,1,3,2,4,3,4,1,1,0.0,neutral or dissatisfied +79647,92565,Male,Loyal Customer,29,Business travel,Eco Plus,1892,1,4,4,4,1,1,1,1,1,2,2,3,4,1,0,1.0,neutral or dissatisfied +79648,4639,Female,Loyal Customer,56,Business travel,Business,3562,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,6.0,satisfied +79649,60657,Female,Loyal Customer,35,Business travel,Business,1620,3,2,3,2,4,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +79650,104364,Female,Loyal Customer,37,Personal Travel,Business,228,5,4,5,2,4,5,4,2,2,5,2,3,2,3,3,1.0,satisfied +79651,35469,Male,Loyal Customer,47,Personal Travel,Eco,1074,2,4,2,2,3,2,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +79652,91269,Female,Loyal Customer,16,Personal Travel,Eco,404,4,2,4,4,1,4,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +79653,68289,Female,Loyal Customer,17,Business travel,Business,806,3,3,3,3,5,5,5,5,1,3,2,4,4,5,0,0.0,satisfied +79654,88064,Female,disloyal Customer,24,Business travel,Business,404,5,5,5,3,2,5,2,2,5,4,4,3,4,2,0,0.0,satisfied +79655,67716,Female,Loyal Customer,47,Business travel,Business,2152,2,1,1,1,3,3,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +79656,46451,Male,Loyal Customer,57,Business travel,Business,125,4,4,4,4,5,5,4,4,4,4,5,3,4,5,0,0.0,satisfied +79657,69514,Male,Loyal Customer,58,Business travel,Business,2586,2,2,2,2,2,2,2,3,5,4,4,2,3,2,0,0.0,satisfied +79658,64450,Male,Loyal Customer,15,Personal Travel,Eco,989,0,4,0,1,1,0,1,1,5,5,4,5,5,1,0,16.0,satisfied +79659,63002,Female,Loyal Customer,13,Business travel,Business,853,2,5,2,5,2,2,2,2,3,1,3,3,4,2,4,2.0,neutral or dissatisfied +79660,16938,Female,Loyal Customer,24,Business travel,Business,820,1,5,4,4,1,1,1,1,4,2,2,1,1,1,0,21.0,neutral or dissatisfied +79661,46883,Male,Loyal Customer,38,Business travel,Business,909,5,5,5,5,4,2,4,5,5,5,5,4,5,5,0,0.0,satisfied +79662,85816,Male,Loyal Customer,49,Personal Travel,Eco,666,1,5,1,2,4,1,1,4,4,5,4,1,1,4,0,0.0,neutral or dissatisfied +79663,90777,Female,Loyal Customer,47,Business travel,Business,2714,5,5,5,5,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +79664,52838,Female,Loyal Customer,24,Business travel,Business,1721,2,2,1,2,5,5,5,5,1,1,3,2,2,5,0,0.0,satisfied +79665,18950,Male,Loyal Customer,27,Personal Travel,Eco,500,1,5,1,1,5,1,3,5,3,2,4,5,4,5,17,9.0,neutral or dissatisfied +79666,2799,Male,Loyal Customer,55,Personal Travel,Eco,764,4,3,4,2,2,4,2,2,2,4,5,2,2,2,19,7.0,neutral or dissatisfied +79667,42768,Male,disloyal Customer,29,Business travel,Eco,493,3,1,3,3,1,3,1,1,4,5,2,4,2,1,26,27.0,neutral or dissatisfied +79668,81038,Female,Loyal Customer,35,Business travel,Business,1175,2,2,2,2,2,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +79669,53964,Female,Loyal Customer,36,Business travel,Eco,925,2,3,3,3,2,2,2,2,1,3,4,5,3,2,0,0.0,satisfied +79670,48988,Male,Loyal Customer,50,Business travel,Eco,421,4,5,5,5,4,4,4,4,1,4,3,5,5,4,0,13.0,satisfied +79671,111940,Female,Loyal Customer,60,Business travel,Business,2710,4,4,2,4,4,4,4,3,3,3,3,5,3,5,15,0.0,satisfied +79672,78450,Female,Loyal Customer,59,Business travel,Business,2301,4,4,4,4,3,5,4,4,4,4,4,3,4,5,4,0.0,satisfied +79673,126177,Male,Loyal Customer,52,Business travel,Eco,468,2,4,4,4,2,2,2,2,1,2,2,4,3,2,26,19.0,neutral or dissatisfied +79674,44419,Female,Loyal Customer,34,Business travel,Eco Plus,342,0,0,0,4,2,0,2,2,5,4,1,2,5,2,0,0.0,satisfied +79675,113447,Male,Loyal Customer,53,Business travel,Business,223,2,5,5,5,3,4,4,2,2,3,2,4,2,3,24,23.0,neutral or dissatisfied +79676,93222,Female,Loyal Customer,62,Business travel,Business,1460,2,3,3,3,4,3,4,2,2,2,2,2,2,4,111,110.0,neutral or dissatisfied +79677,5976,Female,Loyal Customer,22,Personal Travel,Business,925,3,5,3,2,1,3,1,1,3,3,5,3,5,1,76,101.0,neutral or dissatisfied +79678,23450,Male,Loyal Customer,38,Business travel,Business,488,3,3,3,3,4,5,1,5,5,5,5,2,5,5,21,31.0,satisfied +79679,62883,Female,Loyal Customer,16,Business travel,Eco Plus,2446,4,2,2,2,4,3,3,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +79680,13648,Female,Loyal Customer,43,Business travel,Eco,196,5,3,3,3,2,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +79681,45330,Male,Loyal Customer,39,Business travel,Eco,175,1,3,3,3,1,1,1,1,3,1,2,1,2,1,0,0.0,neutral or dissatisfied +79682,83122,Female,Loyal Customer,59,Personal Travel,Eco,1127,3,5,3,5,3,4,4,2,2,3,2,4,2,4,13,35.0,neutral or dissatisfied +79683,57811,Female,disloyal Customer,35,Business travel,Eco Plus,1235,2,2,2,3,1,2,1,1,2,1,4,1,4,1,33,17.0,neutral or dissatisfied +79684,28013,Female,Loyal Customer,28,Business travel,Business,763,5,5,5,5,4,4,4,4,3,2,2,5,3,4,0,0.0,satisfied +79685,37518,Female,Loyal Customer,51,Business travel,Eco,1010,5,3,3,3,1,3,2,5,5,5,5,5,5,3,0,10.0,satisfied +79686,102705,Male,Loyal Customer,46,Business travel,Eco,255,5,3,3,3,5,5,5,5,2,5,2,5,4,5,0,0.0,satisfied +79687,30823,Male,Loyal Customer,44,Business travel,Business,2922,1,1,1,1,3,2,3,5,5,5,5,1,5,3,68,51.0,satisfied +79688,78773,Male,Loyal Customer,45,Business travel,Eco,447,3,4,4,4,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +79689,93817,Male,disloyal Customer,58,Business travel,Business,391,5,4,4,2,4,5,4,4,4,5,5,4,4,4,5,13.0,satisfied +79690,52825,Female,Loyal Customer,69,Personal Travel,Eco Plus,2402,2,0,2,1,2,3,5,2,2,2,2,2,2,4,1,4.0,neutral or dissatisfied +79691,47653,Female,Loyal Customer,22,Business travel,Business,1235,3,5,3,3,4,4,4,4,5,5,5,2,5,4,0,0.0,satisfied +79692,69161,Male,disloyal Customer,23,Business travel,Eco,187,1,0,1,4,2,1,2,2,3,5,5,5,4,2,17,69.0,neutral or dissatisfied +79693,44179,Female,Loyal Customer,39,Business travel,Eco,157,5,4,3,4,5,5,5,5,3,1,1,1,4,5,0,1.0,satisfied +79694,42207,Female,Loyal Customer,41,Business travel,Business,3500,2,1,2,2,2,4,1,4,4,4,4,4,4,2,0,0.0,satisfied +79695,113370,Male,disloyal Customer,48,Business travel,Business,236,5,5,5,5,4,5,1,4,4,3,5,4,4,4,62,58.0,satisfied +79696,46315,Male,Loyal Customer,19,Personal Travel,Business,420,3,1,3,4,5,3,5,5,1,5,3,4,3,5,39,39.0,neutral or dissatisfied +79697,116776,Male,Loyal Customer,19,Personal Travel,Eco Plus,446,2,5,2,5,2,2,2,2,3,2,4,3,5,2,21,15.0,neutral or dissatisfied +79698,42973,Male,Loyal Customer,56,Business travel,Eco,259,4,5,5,5,3,4,3,3,2,3,2,1,1,3,73,61.0,satisfied +79699,68553,Female,disloyal Customer,24,Business travel,Eco,2136,4,4,4,3,1,4,1,1,5,4,5,3,5,1,0,0.0,satisfied +79700,29575,Female,disloyal Customer,23,Business travel,Eco,680,3,2,2,3,5,2,5,5,5,1,2,5,3,5,0,0.0,neutral or dissatisfied +79701,14023,Female,Loyal Customer,27,Business travel,Business,3050,2,2,2,2,4,4,4,4,4,1,2,3,2,4,0,4.0,satisfied +79702,105760,Female,disloyal Customer,39,Business travel,Eco,483,3,4,3,3,4,3,4,4,2,5,4,1,4,4,29,7.0,neutral or dissatisfied +79703,38280,Female,Loyal Customer,55,Personal Travel,Eco,1050,2,5,2,2,2,4,4,3,3,2,3,3,3,3,6,0.0,neutral or dissatisfied +79704,77747,Male,disloyal Customer,23,Business travel,Eco,296,2,0,2,5,5,2,5,5,1,5,4,4,5,5,5,0.0,neutral or dissatisfied +79705,69718,Female,Loyal Customer,35,Business travel,Eco,1372,5,4,4,4,5,5,5,5,3,4,3,3,2,5,0,16.0,satisfied +79706,27359,Female,disloyal Customer,49,Business travel,Eco,956,1,1,1,2,4,1,4,4,1,5,1,1,1,4,7,13.0,neutral or dissatisfied +79707,124825,Male,Loyal Customer,44,Business travel,Eco,280,5,2,2,2,5,5,5,5,2,5,3,2,3,5,50,55.0,satisfied +79708,12114,Male,Loyal Customer,22,Business travel,Business,1097,3,3,3,3,3,3,3,3,2,5,2,2,3,3,0,0.0,neutral or dissatisfied +79709,82929,Female,disloyal Customer,23,Business travel,Eco,594,2,5,2,3,4,2,4,4,5,2,4,5,5,4,33,14.0,neutral or dissatisfied +79710,11215,Male,Loyal Customer,8,Personal Travel,Eco,309,3,5,3,3,4,3,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +79711,52421,Male,Loyal Customer,25,Personal Travel,Eco,425,5,4,5,4,5,5,5,5,3,5,5,3,4,5,0,0.0,satisfied +79712,8461,Male,Loyal Customer,60,Personal Travel,Eco,1379,1,4,1,4,3,1,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +79713,22036,Male,Loyal Customer,9,Personal Travel,Eco Plus,551,4,4,4,4,4,4,4,4,2,3,5,3,4,4,0,0.0,neutral or dissatisfied +79714,99698,Female,Loyal Customer,20,Personal Travel,Eco,442,3,5,3,3,1,3,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +79715,50953,Male,Loyal Customer,23,Personal Travel,Eco,373,3,0,3,2,1,3,1,1,3,5,3,5,5,1,1,0.0,neutral or dissatisfied +79716,12361,Female,Loyal Customer,37,Business travel,Eco,383,1,1,1,1,1,1,1,1,2,5,3,1,4,1,2,0.0,neutral or dissatisfied +79717,44521,Male,Loyal Customer,32,Business travel,Eco,157,5,2,2,2,5,5,5,5,5,4,5,1,3,5,56,48.0,satisfied +79718,91281,Female,Loyal Customer,48,Business travel,Business,3838,1,1,1,1,5,4,5,4,4,5,4,4,4,3,6,4.0,satisfied +79719,91557,Female,Loyal Customer,28,Personal Travel,Eco,680,4,5,4,1,4,4,2,4,3,2,4,5,4,4,3,1.0,neutral or dissatisfied +79720,113334,Male,disloyal Customer,41,Business travel,Business,397,2,2,2,3,5,2,5,5,3,3,4,5,4,5,0,0.0,satisfied +79721,126899,Male,Loyal Customer,55,Business travel,Business,2125,2,2,2,2,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +79722,115351,Female,Loyal Customer,34,Business travel,Business,404,5,5,5,5,2,4,5,5,5,5,5,3,5,3,47,41.0,satisfied +79723,57860,Male,Loyal Customer,23,Personal Travel,Eco,2329,2,5,3,4,3,2,2,3,3,4,5,2,3,2,8,12.0,neutral or dissatisfied +79724,97296,Male,Loyal Customer,48,Business travel,Business,1020,2,5,5,5,1,4,4,2,2,2,2,3,2,4,1,0.0,neutral or dissatisfied +79725,70755,Male,disloyal Customer,23,Business travel,Eco,733,4,4,4,1,4,4,4,4,5,5,4,4,4,4,0,2.0,satisfied +79726,18439,Female,Loyal Customer,25,Business travel,Business,3498,1,1,3,1,5,5,5,5,3,2,5,3,4,5,30,22.0,satisfied +79727,22232,Male,Loyal Customer,44,Business travel,Business,1569,2,2,2,2,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +79728,114225,Male,Loyal Customer,24,Business travel,Eco,853,2,1,1,1,2,2,4,2,1,5,4,2,4,2,10,4.0,neutral or dissatisfied +79729,123808,Male,Loyal Customer,45,Business travel,Business,541,5,5,5,5,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +79730,105017,Female,Loyal Customer,47,Business travel,Business,2817,1,1,1,1,4,4,4,4,4,4,4,5,4,4,21,11.0,satisfied +79731,89183,Male,Loyal Customer,8,Personal Travel,Eco,1919,2,5,2,2,4,2,4,4,5,4,4,5,5,4,27,12.0,neutral or dissatisfied +79732,60395,Male,Loyal Customer,13,Personal Travel,Eco,1452,2,4,2,2,2,2,4,2,3,5,4,2,3,2,130,118.0,neutral or dissatisfied +79733,89739,Male,Loyal Customer,69,Personal Travel,Eco,1010,2,4,2,4,3,2,3,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +79734,118358,Female,Loyal Customer,48,Personal Travel,Eco,639,3,3,3,3,4,4,3,3,3,3,3,4,3,1,3,0.0,neutral or dissatisfied +79735,93121,Female,Loyal Customer,43,Business travel,Business,1243,4,4,4,4,3,4,4,5,5,5,5,3,5,3,6,4.0,satisfied +79736,24126,Male,Loyal Customer,26,Personal Travel,Eco,584,3,5,3,2,1,3,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +79737,51735,Female,Loyal Customer,15,Personal Travel,Eco,451,2,4,2,4,3,2,3,3,1,3,3,1,4,3,36,28.0,neutral or dissatisfied +79738,85386,Male,Loyal Customer,8,Personal Travel,Business,214,2,0,2,4,5,2,5,5,4,4,5,3,4,5,45,36.0,neutral or dissatisfied +79739,34930,Female,Loyal Customer,53,Personal Travel,Eco,395,2,5,2,2,5,5,4,3,3,2,3,4,3,4,19,15.0,neutral or dissatisfied +79740,34003,Female,disloyal Customer,55,Business travel,Eco,1576,2,2,2,4,2,1,1,3,1,4,3,1,3,1,186,187.0,neutral or dissatisfied +79741,82167,Female,Loyal Customer,66,Personal Travel,Eco,311,0,5,0,5,5,4,4,4,4,0,4,4,4,4,0,0.0,satisfied +79742,58757,Male,Loyal Customer,25,Business travel,Business,1005,1,1,4,1,4,4,4,4,4,2,4,5,4,4,13,8.0,satisfied +79743,71227,Female,Loyal Customer,25,Business travel,Business,3133,3,1,1,1,3,3,3,1,1,4,4,3,1,3,152,134.0,neutral or dissatisfied +79744,50794,Male,Loyal Customer,60,Personal Travel,Eco,110,3,4,0,3,1,0,1,1,1,3,3,2,3,1,31,28.0,neutral or dissatisfied +79745,10112,Female,Loyal Customer,42,Business travel,Business,984,4,4,1,4,2,4,5,4,4,4,4,3,4,4,26,22.0,satisfied +79746,31946,Male,disloyal Customer,57,Business travel,Business,101,2,2,2,3,3,2,4,3,4,5,5,4,4,3,13,21.0,neutral or dissatisfied +79747,18522,Male,disloyal Customer,50,Business travel,Eco,127,3,0,3,3,5,3,5,5,4,5,4,4,5,5,17,24.0,neutral or dissatisfied +79748,24980,Female,disloyal Customer,24,Business travel,Eco,692,3,3,3,4,5,3,3,5,4,1,3,1,2,5,31,31.0,neutral or dissatisfied +79749,8673,Male,Loyal Customer,38,Business travel,Business,280,1,1,1,1,4,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +79750,28801,Female,Loyal Customer,27,Business travel,Business,605,3,3,3,3,4,4,4,4,2,3,5,4,5,4,0,0.0,satisfied +79751,5435,Female,Loyal Customer,47,Business travel,Business,287,0,0,0,2,4,5,5,5,5,5,5,3,5,4,11,1.0,satisfied +79752,121679,Female,Loyal Customer,64,Personal Travel,Eco,328,3,0,3,2,4,4,4,1,1,3,1,3,1,5,0,1.0,neutral or dissatisfied +79753,82126,Male,Loyal Customer,17,Business travel,Business,2519,4,4,4,4,4,4,4,4,4,2,4,4,1,4,3,0.0,neutral or dissatisfied +79754,74877,Male,Loyal Customer,30,Personal Travel,Eco,2239,2,4,2,2,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +79755,51537,Male,Loyal Customer,54,Business travel,Eco,370,4,5,5,5,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +79756,69378,Female,Loyal Customer,41,Business travel,Business,1585,1,4,4,4,4,2,1,1,1,1,1,2,1,1,49,51.0,neutral or dissatisfied +79757,122429,Female,Loyal Customer,39,Business travel,Eco,416,2,5,5,5,2,2,2,2,1,3,4,1,3,2,30,33.0,neutral or dissatisfied +79758,52683,Female,Loyal Customer,27,Personal Travel,Eco,119,2,4,2,3,1,2,3,1,3,4,1,2,5,1,0,0.0,neutral or dissatisfied +79759,33544,Male,Loyal Customer,65,Personal Travel,Business,399,3,4,3,5,4,2,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +79760,3018,Female,Loyal Customer,45,Business travel,Eco,922,1,5,3,5,2,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +79761,42487,Female,Loyal Customer,58,Business travel,Eco,585,4,2,2,2,4,4,4,2,2,1,2,4,5,4,454,448.0,satisfied +79762,114014,Male,Loyal Customer,56,Personal Travel,Eco,1838,3,4,3,5,5,3,5,5,5,5,4,4,2,5,0,0.0,neutral or dissatisfied +79763,44408,Male,Loyal Customer,34,Personal Travel,Eco,342,2,5,4,4,1,4,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +79764,71000,Male,Loyal Customer,42,Business travel,Business,802,3,3,2,3,5,5,5,5,5,5,5,4,5,5,4,0.0,satisfied +79765,22549,Female,Loyal Customer,44,Business travel,Business,223,1,1,2,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +79766,16837,Female,Loyal Customer,48,Personal Travel,Eco,645,3,5,3,3,2,5,4,1,1,3,1,4,1,4,51,40.0,neutral or dissatisfied +79767,23670,Female,disloyal Customer,25,Business travel,Eco,251,3,0,3,3,1,3,1,1,1,1,3,5,3,1,0,0.0,neutral or dissatisfied +79768,112050,Male,Loyal Customer,24,Personal Travel,Eco,1123,3,4,3,2,3,3,3,3,4,2,4,5,4,3,8,0.0,neutral or dissatisfied +79769,83193,Female,Loyal Customer,42,Business travel,Business,2600,1,1,1,1,2,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +79770,97949,Female,Loyal Customer,46,Business travel,Business,3771,5,5,4,5,3,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +79771,54656,Female,disloyal Customer,10,Business travel,Eco,787,4,4,4,4,2,4,2,2,4,2,3,4,3,2,21,12.0,neutral or dissatisfied +79772,50159,Female,disloyal Customer,20,Business travel,Eco,109,5,0,5,2,5,0,1,5,1,5,2,5,3,5,0,0.0,satisfied +79773,59503,Female,Loyal Customer,72,Business travel,Eco Plus,811,2,3,4,4,4,4,4,2,2,2,2,4,2,3,5,0.0,neutral or dissatisfied +79774,37059,Female,Loyal Customer,36,Business travel,Eco,1188,2,3,3,3,2,2,2,2,3,3,3,1,5,2,47,57.0,satisfied +79775,59471,Male,Loyal Customer,22,Business travel,Business,758,3,3,3,3,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +79776,56582,Male,Loyal Customer,52,Business travel,Business,937,5,5,5,5,5,4,5,4,4,4,4,5,4,3,6,0.0,satisfied +79777,116277,Female,Loyal Customer,60,Personal Travel,Eco,325,1,3,1,4,3,1,5,3,3,1,3,2,3,4,8,4.0,neutral or dissatisfied +79778,39778,Male,Loyal Customer,39,Personal Travel,Eco,546,1,5,1,2,2,1,2,2,1,5,2,4,4,2,0,0.0,neutral or dissatisfied +79779,108255,Female,disloyal Customer,11,Business travel,Eco,895,1,1,1,4,3,1,3,3,4,2,3,2,3,3,102,113.0,neutral or dissatisfied +79780,69990,Female,Loyal Customer,36,Business travel,Business,2237,3,3,3,3,3,5,1,5,5,5,5,4,5,3,0,0.0,satisfied +79781,7885,Female,Loyal Customer,36,Personal Travel,Eco,948,3,2,3,3,4,3,4,4,1,2,3,3,4,4,11,12.0,neutral or dissatisfied +79782,119875,Male,Loyal Customer,27,Personal Travel,Eco,912,1,5,1,4,3,1,3,3,5,5,5,4,5,3,7,0.0,neutral or dissatisfied +79783,122193,Male,Loyal Customer,55,Business travel,Business,3028,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +79784,96137,Male,Loyal Customer,49,Business travel,Business,1810,5,5,5,5,3,4,5,4,4,4,4,5,4,3,19,12.0,satisfied +79785,72232,Male,Loyal Customer,64,Business travel,Eco,919,1,3,3,3,1,1,1,1,1,2,3,3,3,1,11,3.0,neutral or dissatisfied +79786,68038,Male,Loyal Customer,8,Personal Travel,Business,868,4,1,4,3,1,4,1,1,3,5,3,4,4,1,6,0.0,satisfied +79787,33664,Female,Loyal Customer,31,Business travel,Eco Plus,399,0,0,0,4,4,0,4,4,3,2,2,1,4,4,11,4.0,satisfied +79788,18007,Male,disloyal Customer,35,Business travel,Eco,241,2,0,2,4,1,2,1,1,2,3,3,2,2,1,30,44.0,neutral or dissatisfied +79789,34223,Female,Loyal Customer,69,Personal Travel,Eco,1189,2,2,2,4,5,2,3,2,2,2,1,4,2,3,9,16.0,neutral or dissatisfied +79790,28278,Male,Loyal Customer,20,Personal Travel,Eco,2402,0,2,0,3,0,5,5,2,5,3,3,5,2,5,0,0.0,satisfied +79791,108845,Female,Loyal Customer,23,Business travel,Business,1892,3,1,3,3,3,3,3,3,5,5,3,4,4,3,24,16.0,satisfied +79792,62778,Female,disloyal Customer,55,Business travel,Eco,1056,4,4,4,3,4,3,3,1,1,4,4,3,2,3,1,14.0,neutral or dissatisfied +79793,106056,Female,Loyal Customer,24,Business travel,Business,2190,4,4,4,4,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +79794,22552,Female,Loyal Customer,39,Business travel,Business,2930,4,2,2,2,2,3,4,2,2,2,4,2,2,1,7,6.0,neutral or dissatisfied +79795,24919,Male,Loyal Customer,56,Business travel,Eco,762,2,4,4,4,2,2,2,2,3,1,4,1,4,2,0,0.0,neutral or dissatisfied +79796,108842,Female,Loyal Customer,60,Business travel,Business,1947,3,3,3,3,5,4,5,4,4,4,4,3,4,4,107,118.0,satisfied +79797,15160,Male,Loyal Customer,43,Personal Travel,Eco,912,4,4,4,3,2,4,2,2,5,2,4,4,4,2,0,10.0,neutral or dissatisfied +79798,75432,Male,disloyal Customer,22,Business travel,Eco,1259,1,1,1,3,1,3,3,5,2,5,4,3,5,3,186,165.0,neutral or dissatisfied +79799,39327,Male,Loyal Customer,24,Business travel,Eco Plus,160,5,5,5,5,5,4,2,5,2,2,4,4,3,5,0,19.0,neutral or dissatisfied +79800,104606,Male,Loyal Customer,44,Personal Travel,Eco,369,4,3,4,3,1,4,4,1,1,4,4,1,3,1,0,0.0,satisfied +79801,12380,Male,Loyal Customer,30,Business travel,Eco,253,1,5,2,5,1,1,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +79802,105255,Female,Loyal Customer,43,Business travel,Business,2106,2,2,2,2,2,5,4,5,5,4,5,4,5,3,12,0.0,satisfied +79803,42772,Male,Loyal Customer,49,Personal Travel,Eco,493,5,2,5,3,1,5,5,1,2,3,2,3,3,1,0,0.0,satisfied +79804,127225,Female,Loyal Customer,53,Business travel,Business,1460,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +79805,86903,Male,disloyal Customer,26,Business travel,Business,352,5,0,5,4,1,5,1,1,5,3,5,3,5,1,0,0.0,satisfied +79806,24357,Male,Loyal Customer,18,Personal Travel,Eco Plus,634,4,4,4,3,2,4,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +79807,49566,Male,Loyal Customer,62,Business travel,Eco,337,3,2,4,2,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +79808,105052,Female,Loyal Customer,8,Personal Travel,Eco,255,2,0,2,1,5,2,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +79809,100073,Female,Loyal Customer,44,Business travel,Business,1585,0,4,0,1,2,4,5,4,4,4,4,3,4,4,35,31.0,satisfied +79810,111881,Male,Loyal Customer,52,Business travel,Eco,628,1,2,2,2,2,1,2,2,3,1,4,2,4,2,20,27.0,neutral or dissatisfied +79811,83058,Male,disloyal Customer,47,Business travel,Business,957,5,5,5,1,2,5,2,2,5,5,5,4,4,2,0,3.0,satisfied +79812,112897,Male,Loyal Customer,16,Business travel,Business,3922,1,1,5,1,1,1,1,1,4,2,3,1,4,1,52,49.0,neutral or dissatisfied +79813,98742,Male,Loyal Customer,19,Personal Travel,Eco,1558,3,4,4,1,1,4,3,1,5,5,5,3,4,1,6,0.0,neutral or dissatisfied +79814,110745,Female,Loyal Customer,56,Business travel,Business,1701,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +79815,75512,Female,Loyal Customer,16,Personal Travel,Eco,2527,4,3,4,3,2,4,1,2,5,3,5,5,1,2,4,25.0,neutral or dissatisfied +79816,77396,Male,Loyal Customer,45,Personal Travel,Eco,626,1,5,1,1,2,1,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +79817,118626,Female,disloyal Customer,21,Business travel,Business,370,5,0,5,1,2,5,2,2,3,4,5,4,4,2,7,9.0,satisfied +79818,8740,Male,Loyal Customer,41,Business travel,Business,280,0,0,0,2,3,4,5,4,4,5,5,4,4,3,0,0.0,satisfied +79819,104301,Male,Loyal Customer,70,Personal Travel,Eco,382,3,5,4,3,3,4,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +79820,87963,Male,Loyal Customer,44,Business travel,Business,2147,2,2,2,2,4,5,4,5,5,5,5,3,5,5,2,0.0,satisfied +79821,119722,Male,disloyal Customer,21,Business travel,Eco,1303,2,2,2,4,4,2,4,4,2,1,3,4,3,4,0,1.0,neutral or dissatisfied +79822,39079,Male,disloyal Customer,36,Business travel,Business,984,3,3,3,3,3,3,3,3,3,2,4,3,4,3,0,9.0,neutral or dissatisfied +79823,60562,Female,Loyal Customer,24,Business travel,Eco Plus,462,5,1,1,1,5,4,1,5,3,2,2,2,1,5,0,0.0,neutral or dissatisfied +79824,44369,Female,Loyal Customer,19,Personal Travel,Eco,596,1,3,1,3,3,1,3,3,1,2,4,3,4,3,0,6.0,neutral or dissatisfied +79825,21906,Male,Loyal Customer,44,Business travel,Eco,448,4,4,4,4,4,4,4,4,2,2,1,1,5,4,0,0.0,satisfied +79826,60175,Female,Loyal Customer,49,Personal Travel,Eco,1144,0,2,0,4,1,2,4,3,3,2,3,2,3,2,12,0.0,satisfied +79827,66366,Male,Loyal Customer,42,Personal Travel,Eco,986,1,5,1,5,1,1,1,1,4,3,5,5,4,1,10,10.0,neutral or dissatisfied +79828,61276,Female,Loyal Customer,59,Personal Travel,Eco,967,2,4,2,4,5,5,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +79829,41882,Male,Loyal Customer,37,Business travel,Business,2904,3,3,3,3,2,2,3,5,5,5,5,5,5,2,29,35.0,satisfied +79830,46613,Female,disloyal Customer,33,Business travel,Eco,125,1,0,1,4,3,1,3,3,5,5,1,2,4,3,2,0.0,neutral or dissatisfied +79831,27522,Male,Loyal Customer,35,Personal Travel,Eco,954,3,4,3,3,1,3,1,1,1,3,4,3,4,1,0,0.0,neutral or dissatisfied +79832,17367,Female,Loyal Customer,56,Personal Travel,Eco,563,3,4,4,3,3,4,4,2,2,4,4,4,2,3,0,0.0,neutral or dissatisfied +79833,76453,Male,disloyal Customer,43,Business travel,Business,547,3,2,2,4,4,3,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +79834,16392,Male,disloyal Customer,18,Business travel,Eco,463,2,0,2,4,1,2,1,1,3,4,3,3,4,1,0,0.0,neutral or dissatisfied +79835,71504,Female,Loyal Customer,47,Business travel,Business,1012,4,4,4,4,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +79836,98931,Male,Loyal Customer,28,Business travel,Business,3083,5,5,3,5,5,5,5,5,5,4,4,3,4,5,9,16.0,satisfied +79837,56803,Female,Loyal Customer,37,Business travel,Business,1605,1,3,1,1,3,3,4,3,3,4,3,4,3,4,15,23.0,satisfied +79838,53734,Female,Loyal Customer,30,Personal Travel,Eco,1208,3,2,3,4,3,3,3,3,3,2,4,3,4,3,1,0.0,neutral or dissatisfied +79839,10157,Male,Loyal Customer,61,Business travel,Business,2234,2,2,2,2,4,3,3,2,2,2,2,4,2,1,0,13.0,neutral or dissatisfied +79840,31354,Female,Loyal Customer,45,Business travel,Business,2457,3,3,4,3,1,5,2,2,2,2,2,4,2,1,0,2.0,satisfied +79841,64047,Female,Loyal Customer,26,Business travel,Business,3442,4,5,5,5,4,4,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +79842,21231,Female,Loyal Customer,26,Personal Travel,Eco,153,3,5,3,4,5,3,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +79843,72711,Male,Loyal Customer,59,Business travel,Business,2236,5,1,5,5,4,5,5,4,4,4,4,4,4,5,0,2.0,satisfied +79844,73348,Female,Loyal Customer,43,Business travel,Business,1120,4,4,4,4,4,4,5,3,3,3,3,4,3,5,0,3.0,satisfied +79845,49468,Male,Loyal Customer,56,Business travel,Eco,109,4,5,5,5,3,4,3,3,5,1,1,3,5,3,44,43.0,satisfied +79846,111362,Female,Loyal Customer,54,Business travel,Business,1741,1,1,1,1,4,5,5,4,4,4,4,4,4,4,10,0.0,satisfied +79847,27927,Female,disloyal Customer,24,Business travel,Eco Plus,689,4,0,3,2,2,3,2,2,4,2,2,1,2,2,0,0.0,neutral or dissatisfied +79848,80222,Female,Loyal Customer,28,Business travel,Business,2153,4,2,5,5,4,4,4,4,1,3,1,4,2,4,0,0.0,neutral or dissatisfied +79849,71626,Male,Loyal Customer,48,Business travel,Business,2818,5,5,2,5,1,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +79850,84311,Female,Loyal Customer,15,Personal Travel,Eco Plus,235,2,1,2,4,4,2,2,4,2,1,4,1,3,4,0,13.0,neutral or dissatisfied +79851,23031,Female,Loyal Customer,48,Business travel,Eco,1080,5,4,2,4,1,5,1,5,5,5,5,2,5,1,7,0.0,satisfied +79852,127332,Female,Loyal Customer,45,Business travel,Business,1897,1,1,1,1,4,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +79853,94150,Male,Loyal Customer,48,Business travel,Business,441,1,1,1,1,2,4,5,2,2,2,2,3,2,5,41,33.0,satisfied +79854,27929,Male,Loyal Customer,54,Business travel,Business,1774,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +79855,66925,Female,Loyal Customer,54,Business travel,Business,1583,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +79856,122699,Male,Loyal Customer,22,Personal Travel,Eco,361,3,5,3,3,5,3,5,5,4,3,4,3,4,5,10,17.0,neutral or dissatisfied +79857,54196,Male,Loyal Customer,33,Personal Travel,Eco,1372,2,4,2,3,5,2,5,5,2,2,2,2,4,5,0,0.0,neutral or dissatisfied +79858,61836,Female,Loyal Customer,49,Business travel,Business,1635,3,3,3,3,5,4,4,3,3,3,3,5,3,4,24,15.0,satisfied +79859,126364,Female,Loyal Customer,19,Personal Travel,Eco,507,5,5,5,2,3,5,3,3,3,2,4,3,4,3,0,0.0,satisfied +79860,114801,Female,Loyal Customer,36,Business travel,Business,1826,5,5,5,5,3,4,5,5,5,5,5,5,5,4,9,6.0,satisfied +79861,87844,Female,Loyal Customer,47,Personal Travel,Eco,214,3,0,3,3,5,2,2,5,5,3,2,2,5,3,0,0.0,neutral or dissatisfied +79862,30470,Female,Loyal Customer,35,Personal Travel,Eco Plus,495,2,5,2,1,5,2,4,5,3,4,4,3,4,5,81,98.0,neutral or dissatisfied +79863,38880,Female,disloyal Customer,68,Business travel,Eco,261,4,3,4,3,4,4,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +79864,116128,Male,Loyal Customer,20,Personal Travel,Eco,362,2,5,2,5,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +79865,40172,Female,disloyal Customer,29,Business travel,Eco,387,3,5,3,3,3,3,3,3,2,2,2,2,4,3,0,0.0,neutral or dissatisfied +79866,65513,Male,disloyal Customer,20,Business travel,Eco,1616,1,1,1,4,3,1,3,3,3,1,4,1,4,3,64,68.0,neutral or dissatisfied +79867,14420,Female,Loyal Customer,23,Personal Travel,Eco,585,2,3,2,2,2,2,2,2,4,4,2,1,2,2,50,44.0,neutral or dissatisfied +79868,50124,Female,Loyal Customer,32,Business travel,Eco,109,3,3,3,3,3,3,3,3,1,2,4,2,4,3,25,32.0,neutral or dissatisfied +79869,24891,Male,disloyal Customer,25,Business travel,Eco,397,2,0,3,4,1,3,1,1,3,1,2,3,4,1,0,4.0,neutral or dissatisfied +79870,125076,Female,Loyal Customer,26,Business travel,Business,361,2,4,4,4,2,3,2,2,3,1,3,1,4,2,0,0.0,neutral or dissatisfied +79871,111923,Female,Loyal Customer,49,Business travel,Business,3798,1,1,1,1,2,3,4,4,4,4,4,5,4,2,0,0.0,satisfied +79872,127820,Female,disloyal Customer,85,Business travel,Business,862,1,1,1,2,1,5,5,4,2,1,1,5,1,5,57,51.0,neutral or dissatisfied +79873,63878,Male,Loyal Customer,45,Business travel,Business,1700,3,3,3,3,4,5,5,5,5,5,5,3,5,4,2,0.0,satisfied +79874,10346,Male,Loyal Customer,57,Business travel,Business,316,0,0,0,4,3,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +79875,94640,Female,Loyal Customer,49,Business travel,Eco,273,1,2,2,2,4,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +79876,10295,Male,Loyal Customer,24,Business travel,Business,2502,1,1,1,1,4,5,4,4,2,5,4,4,4,4,141,141.0,satisfied +79877,7144,Female,Loyal Customer,57,Business travel,Business,3801,0,5,0,3,2,4,4,2,2,2,2,4,2,3,0,7.0,satisfied +79878,32929,Female,Loyal Customer,68,Personal Travel,Eco,163,2,5,2,1,5,5,4,3,3,2,3,4,3,3,1,0.0,neutral or dissatisfied +79879,112487,Male,Loyal Customer,61,Personal Travel,Eco,948,0,0,0,1,2,0,2,2,4,4,5,4,5,2,1,0.0,satisfied +79880,77823,Female,Loyal Customer,24,Personal Travel,Eco,731,1,4,1,4,5,1,5,5,5,1,4,1,4,5,57,48.0,neutral or dissatisfied +79881,96006,Female,Loyal Customer,45,Business travel,Business,2937,3,2,3,3,5,5,4,5,5,5,5,5,5,3,12,0.0,satisfied +79882,31095,Female,Loyal Customer,29,Business travel,Business,1014,1,0,0,3,3,0,3,3,3,5,4,1,3,3,23,39.0,neutral or dissatisfied +79883,110820,Male,Loyal Customer,57,Personal Travel,Eco,990,3,1,3,2,1,3,1,1,3,1,3,3,3,1,24,20.0,neutral or dissatisfied +79884,13888,Female,Loyal Customer,62,Personal Travel,Eco,667,2,2,2,3,1,3,3,4,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +79885,78477,Male,Loyal Customer,33,Business travel,Business,526,5,5,5,5,5,5,5,5,5,5,4,3,4,5,3,0.0,satisfied +79886,86985,Female,Loyal Customer,40,Personal Travel,Eco,907,2,4,2,2,2,2,2,2,4,4,5,5,5,2,0,6.0,neutral or dissatisfied +79887,71264,Female,Loyal Customer,39,Personal Travel,Eco,733,4,5,4,2,1,4,3,1,1,5,4,4,1,1,4,6.0,neutral or dissatisfied +79888,2116,Female,Loyal Customer,39,Business travel,Business,3974,2,2,2,2,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +79889,14564,Female,Loyal Customer,48,Business travel,Business,1091,3,5,5,5,1,2,1,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +79890,54241,Male,Loyal Customer,41,Business travel,Business,1222,1,3,3,3,1,4,3,1,1,2,1,2,1,1,98,85.0,neutral or dissatisfied +79891,67029,Female,Loyal Customer,55,Business travel,Business,964,2,2,2,2,3,4,3,2,2,2,2,3,2,4,2,0.0,neutral or dissatisfied +79892,118195,Female,Loyal Customer,66,Personal Travel,Eco,1444,5,4,5,1,2,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +79893,6277,Male,disloyal Customer,40,Business travel,Eco,693,1,1,1,4,5,1,3,5,4,4,3,2,4,5,0,7.0,neutral or dissatisfied +79894,8839,Male,Loyal Customer,30,Personal Travel,Eco Plus,522,1,4,1,2,4,1,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +79895,99904,Female,Loyal Customer,35,Personal Travel,Eco,738,3,4,3,3,5,3,2,5,5,5,4,3,4,5,55,68.0,neutral or dissatisfied +79896,29240,Female,Loyal Customer,21,Business travel,Business,834,4,4,3,4,4,4,4,4,1,3,4,1,2,4,0,3.0,satisfied +79897,44518,Female,disloyal Customer,22,Business travel,Eco,157,4,2,4,3,4,4,4,4,2,3,3,2,4,4,20,0.0,neutral or dissatisfied +79898,86694,Female,disloyal Customer,39,Business travel,Business,1747,3,3,3,4,1,3,1,1,4,2,3,4,5,1,0,0.0,neutral or dissatisfied +79899,61022,Male,Loyal Customer,62,Personal Travel,Eco,3365,1,4,1,4,1,5,5,5,2,4,5,5,4,5,19,31.0,neutral or dissatisfied +79900,44125,Female,Loyal Customer,34,Business travel,Business,2058,1,5,5,5,3,3,2,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +79901,20516,Female,disloyal Customer,33,Business travel,Business,565,3,3,3,4,1,3,1,1,2,4,4,2,4,1,12,5.0,neutral or dissatisfied +79902,109676,Male,Loyal Customer,20,Personal Travel,Eco,802,1,2,1,3,1,1,1,1,4,4,4,1,4,1,30,22.0,neutral or dissatisfied +79903,67759,Female,Loyal Customer,29,Business travel,Business,2705,1,1,2,1,4,4,4,4,5,3,4,5,4,4,5,33.0,satisfied +79904,11088,Female,Loyal Customer,23,Personal Travel,Eco,316,1,3,1,4,4,1,4,4,2,3,2,3,3,4,0,0.0,neutral or dissatisfied +79905,90535,Female,disloyal Customer,24,Business travel,Business,594,0,3,0,1,4,0,4,4,4,4,4,5,5,4,0,0.0,satisfied +79906,47595,Male,Loyal Customer,55,Business travel,Business,1464,3,3,3,3,4,3,1,4,4,4,4,3,4,4,4,0.0,satisfied +79907,1389,Female,Loyal Customer,45,Personal Travel,Eco Plus,158,3,5,3,3,3,4,5,1,1,3,1,5,1,3,0,13.0,neutral or dissatisfied +79908,77641,Female,Loyal Customer,38,Business travel,Business,2677,5,5,5,5,3,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +79909,102449,Male,Loyal Customer,11,Personal Travel,Eco,386,3,5,4,2,4,4,4,4,5,3,5,5,5,4,15,5.0,neutral or dissatisfied +79910,7450,Male,Loyal Customer,49,Personal Travel,Eco,522,2,5,2,1,2,2,2,2,3,2,4,3,4,2,20,15.0,neutral or dissatisfied +79911,119033,Female,Loyal Customer,59,Business travel,Business,1460,2,2,2,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +79912,25828,Female,Loyal Customer,41,Business travel,Business,692,3,3,3,3,1,2,1,4,4,4,4,3,4,4,0,0.0,satisfied +79913,28748,Female,Loyal Customer,30,Business travel,Business,2901,1,5,5,5,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +79914,83789,Female,Loyal Customer,41,Business travel,Business,2225,2,2,2,2,3,4,5,4,4,4,4,4,4,4,20,6.0,satisfied +79915,80993,Female,Loyal Customer,43,Business travel,Business,2067,3,3,3,3,2,3,3,3,3,3,3,1,3,1,51,40.0,neutral or dissatisfied +79916,110974,Male,Loyal Customer,58,Business travel,Business,319,2,2,2,2,5,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +79917,51872,Female,Loyal Customer,22,Business travel,Business,2742,4,4,4,4,4,4,4,4,1,2,1,3,1,4,0,3.0,satisfied +79918,4775,Female,Loyal Customer,53,Business travel,Business,403,4,4,4,4,5,5,5,3,2,5,4,5,3,5,20,148.0,satisfied +79919,62040,Male,Loyal Customer,37,Business travel,Eco,2586,2,1,1,1,2,1,2,2,3,2,1,1,2,2,75,34.0,neutral or dissatisfied +79920,30587,Male,Loyal Customer,36,Personal Travel,Eco,628,2,4,2,3,5,2,2,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +79921,49195,Male,Loyal Customer,44,Business travel,Eco,109,5,4,4,4,5,5,5,5,3,3,3,2,4,5,26,21.0,satisfied +79922,70737,Female,Loyal Customer,42,Personal Travel,Eco,675,3,4,3,3,3,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +79923,93304,Male,disloyal Customer,37,Business travel,Business,1733,3,3,3,3,4,3,3,4,3,4,3,5,4,4,4,2.0,neutral or dissatisfied +79924,125924,Male,Loyal Customer,41,Personal Travel,Eco,861,3,5,3,5,2,3,2,2,3,5,4,4,5,2,19,25.0,neutral or dissatisfied +79925,105413,Female,Loyal Customer,59,Personal Travel,Eco Plus,369,3,3,3,4,3,4,4,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +79926,48840,Male,Loyal Customer,67,Personal Travel,Business,86,4,4,4,2,5,4,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +79927,100945,Male,Loyal Customer,55,Business travel,Business,3497,5,4,5,5,3,4,4,5,5,5,5,4,5,3,7,0.0,satisfied +79928,35705,Male,Loyal Customer,40,Personal Travel,Eco,2586,3,3,3,4,3,1,1,3,2,4,5,1,5,1,0,34.0,neutral or dissatisfied +79929,102464,Male,Loyal Customer,7,Personal Travel,Eco,397,4,4,5,3,2,5,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +79930,91780,Female,Loyal Customer,69,Personal Travel,Eco,590,3,1,3,3,1,4,4,1,1,3,1,1,1,1,0,0.0,neutral or dissatisfied +79931,77617,Male,Loyal Customer,51,Business travel,Business,731,5,5,5,5,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +79932,71768,Male,Loyal Customer,54,Business travel,Business,1744,3,3,3,3,2,3,4,5,5,5,5,4,5,3,31,36.0,satisfied +79933,77595,Male,Loyal Customer,48,Business travel,Business,3527,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +79934,36072,Male,disloyal Customer,16,Business travel,Eco,399,4,0,4,5,5,4,5,5,3,1,4,5,1,5,1,0.0,satisfied +79935,6270,Female,disloyal Customer,45,Business travel,Eco,585,2,4,2,4,1,2,1,1,4,5,4,3,4,1,11,18.0,neutral or dissatisfied +79936,31739,Female,disloyal Customer,46,Business travel,Eco Plus,853,4,4,4,3,1,4,1,1,4,3,2,5,4,1,2,0.0,neutral or dissatisfied +79937,76558,Male,Loyal Customer,43,Business travel,Eco,534,1,2,5,5,1,1,1,1,4,5,4,1,4,1,0,0.0,neutral or dissatisfied +79938,63310,Male,Loyal Customer,44,Business travel,Business,3519,4,4,3,4,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +79939,58722,Female,disloyal Customer,35,Business travel,Business,1120,2,2,2,3,5,2,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +79940,114563,Male,Loyal Customer,28,Personal Travel,Business,337,0,4,0,2,5,0,5,5,3,4,4,4,4,5,0,0.0,satisfied +79941,63185,Male,Loyal Customer,39,Business travel,Business,3383,3,3,5,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +79942,43230,Male,disloyal Customer,24,Business travel,Eco,1037,3,3,3,4,3,3,5,3,5,1,4,4,4,3,0,10.0,neutral or dissatisfied +79943,120004,Female,Loyal Customer,40,Business travel,Business,3129,4,4,4,4,3,4,4,5,5,5,5,3,5,3,3,0.0,satisfied +79944,62402,Female,Loyal Customer,10,Personal Travel,Eco,2704,2,5,2,1,4,2,4,4,1,5,2,1,3,4,96,73.0,neutral or dissatisfied +79945,108696,Female,Loyal Customer,14,Personal Travel,Eco,577,3,2,3,3,3,4,4,3,1,3,3,4,1,4,177,163.0,neutral or dissatisfied +79946,54729,Male,Loyal Customer,20,Personal Travel,Eco,787,2,4,2,1,2,2,2,2,3,5,4,3,4,2,6,0.0,neutral or dissatisfied +79947,6907,Female,Loyal Customer,9,Personal Travel,Eco,265,1,3,1,3,1,1,1,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +79948,114027,Female,disloyal Customer,16,Business travel,Eco,1186,5,5,5,5,4,5,4,4,4,1,3,1,5,4,0,0.0,satisfied +79949,91457,Female,Loyal Customer,40,Business travel,Business,859,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +79950,19877,Female,Loyal Customer,13,Personal Travel,Business,315,3,5,3,4,3,3,3,3,5,2,5,4,5,3,14,7.0,neutral or dissatisfied +79951,63475,Male,Loyal Customer,56,Personal Travel,Eco Plus,337,2,5,2,3,3,2,3,3,5,5,1,3,4,3,0,7.0,neutral or dissatisfied +79952,26074,Female,Loyal Customer,38,Business travel,Eco,591,3,4,4,4,3,3,3,3,4,4,5,3,5,3,0,0.0,satisfied +79953,54571,Male,Loyal Customer,10,Business travel,Eco Plus,925,2,4,4,4,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +79954,113258,Female,Loyal Customer,41,Business travel,Business,3657,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,3.0,satisfied +79955,107901,Female,disloyal Customer,18,Business travel,Eco,861,4,4,4,1,5,4,5,5,5,2,5,4,5,5,27,5.0,neutral or dissatisfied +79956,59560,Female,Loyal Customer,39,Business travel,Business,3703,1,1,1,1,5,5,5,4,4,5,4,3,4,3,8,19.0,satisfied +79957,81988,Male,Loyal Customer,8,Business travel,Business,1522,1,5,5,5,1,1,1,1,3,3,4,3,3,1,3,4.0,neutral or dissatisfied +79958,45041,Male,Loyal Customer,48,Business travel,Business,2347,0,0,0,1,2,2,1,5,5,5,5,4,5,4,0,0.0,satisfied +79959,69271,Female,Loyal Customer,51,Personal Travel,Eco,733,2,3,2,3,1,3,4,5,5,2,5,3,5,4,0,12.0,neutral or dissatisfied +79960,85113,Male,Loyal Customer,32,Business travel,Business,1904,3,3,3,3,3,3,3,3,3,5,4,5,5,3,16,36.0,satisfied +79961,46743,Female,Loyal Customer,53,Personal Travel,Eco,125,2,5,2,2,2,2,5,1,1,2,1,2,1,3,58,48.0,neutral or dissatisfied +79962,14076,Female,disloyal Customer,20,Business travel,Eco,425,0,0,0,2,0,4,4,4,4,2,2,4,1,4,197,198.0,satisfied +79963,69541,Female,Loyal Customer,26,Business travel,Business,2475,3,3,3,3,3,3,3,1,2,2,3,3,1,3,8,14.0,neutral or dissatisfied +79964,14350,Male,Loyal Customer,53,Personal Travel,Eco,395,4,3,4,3,3,4,3,3,3,3,2,4,1,3,0,7.0,neutral or dissatisfied +79965,85973,Female,Loyal Customer,41,Business travel,Business,3818,3,3,3,3,5,5,5,4,4,4,4,4,4,4,90,74.0,satisfied +79966,109872,Female,Loyal Customer,39,Business travel,Business,2867,5,5,5,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +79967,21628,Male,disloyal Customer,34,Personal Travel,Eco,853,1,5,1,1,5,1,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +79968,21035,Female,Loyal Customer,36,Business travel,Eco,227,4,4,2,4,4,5,4,4,4,1,4,3,4,4,0,0.0,satisfied +79969,124555,Female,disloyal Customer,25,Business travel,Business,453,0,5,0,4,3,0,3,3,3,5,5,5,5,3,44,66.0,satisfied +79970,119564,Female,disloyal Customer,17,Business travel,Business,814,5,0,5,2,3,5,3,3,3,5,5,4,4,3,0,15.0,satisfied +79971,109555,Male,Loyal Customer,62,Personal Travel,Eco,920,4,5,4,2,3,4,1,3,4,3,4,3,5,3,0,1.0,neutral or dissatisfied +79972,4218,Male,Loyal Customer,52,Personal Travel,Eco,888,2,4,2,3,2,2,2,2,1,2,2,1,3,2,0,0.0,neutral or dissatisfied +79973,37475,Male,disloyal Customer,23,Business travel,Eco,1053,1,1,1,4,5,1,5,5,1,2,3,1,3,5,0,6.0,neutral or dissatisfied +79974,93215,Male,disloyal Customer,38,Business travel,Business,1460,5,5,5,4,4,5,4,4,4,5,4,5,5,4,0,0.0,satisfied +79975,44942,Female,Loyal Customer,25,Business travel,Business,334,3,4,5,5,3,3,3,3,2,1,4,2,3,3,16,3.0,neutral or dissatisfied +79976,82787,Female,disloyal Customer,18,Business travel,Eco,231,3,3,3,3,5,3,5,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +79977,56063,Male,Loyal Customer,22,Personal Travel,Eco,2475,1,5,1,3,1,2,3,3,4,4,5,3,2,3,26,17.0,neutral or dissatisfied +79978,111256,Female,Loyal Customer,24,Personal Travel,Eco,1972,3,0,3,3,3,3,2,3,5,5,5,3,5,3,40,57.0,neutral or dissatisfied +79979,123882,Male,Loyal Customer,49,Business travel,Business,1750,2,2,2,2,5,3,4,3,3,3,2,3,3,3,0,2.0,neutral or dissatisfied +79980,2678,Female,Loyal Customer,25,Personal Travel,Eco,622,4,4,4,2,2,4,2,2,3,4,2,1,3,2,26,21.0,satisfied +79981,68092,Female,Loyal Customer,34,Business travel,Eco,813,2,4,4,4,2,2,2,2,4,1,4,2,4,2,1,0.0,neutral or dissatisfied +79982,2230,Male,Loyal Customer,44,Personal Travel,Eco,642,1,4,1,4,1,1,1,1,3,3,5,5,4,1,0,11.0,neutral or dissatisfied +79983,35330,Male,disloyal Customer,45,Business travel,Eco,1041,4,4,4,4,5,4,5,5,3,1,3,4,4,5,2,0.0,neutral or dissatisfied +79984,87800,Female,disloyal Customer,54,Business travel,Eco,214,1,3,1,4,5,1,1,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +79985,117303,Male,Loyal Customer,49,Business travel,Eco Plus,369,2,1,1,1,2,2,2,2,1,4,3,3,2,2,0,0.0,neutral or dissatisfied +79986,106589,Female,Loyal Customer,57,Business travel,Business,333,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +79987,78416,Male,Loyal Customer,36,Business travel,Eco,453,2,4,4,4,2,1,2,2,4,5,4,3,3,2,96,86.0,neutral or dissatisfied +79988,124310,Female,Loyal Customer,44,Business travel,Eco,255,2,1,1,1,2,3,3,2,2,2,2,1,2,1,0,9.0,neutral or dissatisfied +79989,121853,Male,Loyal Customer,44,Business travel,Business,366,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +79990,59575,Male,Loyal Customer,49,Business travel,Business,1620,2,2,2,2,2,4,5,4,4,4,4,5,4,5,8,0.0,satisfied +79991,111420,Male,Loyal Customer,50,Business travel,Business,2278,1,1,1,1,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +79992,62018,Male,disloyal Customer,27,Business travel,Business,2475,5,5,5,3,5,5,5,5,4,5,3,3,4,5,0,39.0,satisfied +79993,78933,Male,Loyal Customer,25,Business travel,Eco,500,3,5,5,5,3,3,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +79994,47416,Female,disloyal Customer,43,Business travel,Eco,588,3,3,3,5,5,3,1,5,4,1,5,2,4,5,0,3.0,neutral or dissatisfied +79995,48,Female,disloyal Customer,40,Business travel,Business,212,3,3,3,3,5,3,4,5,1,2,3,2,2,5,29,41.0,neutral or dissatisfied +79996,2158,Female,Loyal Customer,47,Business travel,Business,3286,5,5,5,5,5,4,5,4,4,4,4,3,4,5,61,74.0,satisfied +79997,4224,Female,Loyal Customer,25,Business travel,Eco Plus,888,1,1,1,1,1,1,3,1,3,1,4,1,4,1,5,14.0,neutral or dissatisfied +79998,26058,Female,Loyal Customer,15,Personal Travel,Eco,432,1,4,1,1,3,1,3,3,4,2,5,5,5,3,6,0.0,neutral or dissatisfied +79999,7461,Female,Loyal Customer,44,Business travel,Business,510,2,2,2,2,4,4,4,5,2,5,5,4,4,4,180,183.0,satisfied +80000,42802,Female,Loyal Customer,45,Business travel,Eco,710,4,2,2,2,1,1,2,4,4,4,4,1,4,5,0,0.0,satisfied +80001,100069,Male,Loyal Customer,18,Personal Travel,Eco,220,4,2,4,4,4,4,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +80002,116163,Male,Loyal Customer,43,Personal Travel,Eco,333,2,5,2,1,4,2,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +80003,69699,Male,Loyal Customer,39,Business travel,Business,1372,5,5,5,5,4,4,4,4,3,4,4,4,3,4,338,334.0,satisfied +80004,28018,Female,Loyal Customer,42,Business travel,Business,763,1,1,1,1,4,4,1,5,5,5,5,4,5,4,0,0.0,satisfied +80005,96055,Female,Loyal Customer,46,Business travel,Business,395,2,2,2,2,2,1,4,5,5,5,5,3,5,4,0,0.0,satisfied +80006,29697,Female,disloyal Customer,29,Business travel,Eco,1052,3,3,3,1,4,3,4,4,1,3,3,4,1,4,3,7.0,neutral or dissatisfied +80007,11065,Female,Loyal Customer,68,Personal Travel,Eco,429,4,5,4,2,2,5,5,5,5,4,5,2,5,5,0,0.0,neutral or dissatisfied +80008,53160,Female,disloyal Customer,51,Business travel,Business,589,4,4,4,3,5,4,2,5,4,3,5,4,4,5,0,0.0,satisfied +80009,69331,Male,disloyal Customer,24,Business travel,Business,1096,4,0,3,2,5,3,5,5,3,2,4,4,5,5,0,0.0,satisfied +80010,7995,Male,Loyal Customer,46,Business travel,Business,3550,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +80011,129804,Male,Loyal Customer,54,Personal Travel,Eco,447,1,5,1,2,2,1,2,2,5,2,5,3,4,2,17,5.0,neutral or dissatisfied +80012,51484,Male,Loyal Customer,54,Business travel,Business,451,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +80013,25729,Male,Loyal Customer,70,Personal Travel,Eco,432,2,4,5,2,4,5,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +80014,62542,Female,disloyal Customer,50,Business travel,Eco,993,4,4,4,4,4,4,4,4,3,4,3,2,3,4,0,21.0,neutral or dissatisfied +80015,109463,Male,Loyal Customer,55,Business travel,Business,2819,2,2,2,2,2,4,5,5,5,5,5,3,5,4,4,0.0,satisfied +80016,102940,Female,Loyal Customer,58,Personal Travel,Eco Plus,436,1,3,4,4,4,3,3,3,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +80017,126667,Female,Loyal Customer,60,Business travel,Business,2014,1,5,1,1,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +80018,82010,Male,Loyal Customer,50,Business travel,Eco,1135,1,5,5,5,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +80019,112463,Male,Loyal Customer,46,Business travel,Eco,462,3,3,3,3,3,3,3,3,5,3,4,3,1,3,168,162.0,neutral or dissatisfied +80020,57662,Female,Loyal Customer,64,Personal Travel,Eco,200,2,2,2,4,1,4,3,5,5,2,2,2,5,2,2,0.0,neutral or dissatisfied +80021,17249,Female,Loyal Customer,64,Business travel,Business,2569,3,3,3,3,3,1,2,5,5,5,5,4,5,2,0,0.0,satisfied +80022,123521,Male,Loyal Customer,20,Personal Travel,Eco,2077,4,4,4,4,1,4,5,1,1,5,5,4,2,1,0,0.0,neutral or dissatisfied +80023,20289,Female,Loyal Customer,50,Personal Travel,Eco,235,2,4,2,3,2,5,4,5,5,2,5,5,5,4,0,16.0,neutral or dissatisfied +80024,100373,Female,Loyal Customer,54,Personal Travel,Eco,1053,2,4,2,2,5,5,4,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +80025,28154,Female,Loyal Customer,57,Business travel,Eco,859,3,3,3,3,2,1,1,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +80026,83811,Male,Loyal Customer,49,Business travel,Business,1816,2,2,4,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +80027,21041,Female,Loyal Customer,63,Business travel,Business,2051,0,5,0,2,3,2,3,1,1,1,1,4,1,1,0,0.0,satisfied +80028,34314,Male,Loyal Customer,33,Business travel,Eco Plus,280,2,1,1,1,2,2,2,2,4,5,3,1,4,2,100,82.0,neutral or dissatisfied +80029,129856,Female,Loyal Customer,41,Business travel,Business,3926,0,0,0,1,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +80030,58658,Male,Loyal Customer,32,Personal Travel,Eco,867,2,4,2,4,5,2,5,5,4,3,2,3,3,5,0,0.0,neutral or dissatisfied +80031,34895,Female,Loyal Customer,25,Business travel,Business,187,2,2,2,2,5,5,5,5,2,3,2,4,4,5,0,0.0,satisfied +80032,35694,Male,Loyal Customer,76,Business travel,Business,3680,4,4,4,4,5,5,5,5,5,4,5,5,2,5,23,28.0,satisfied +80033,30396,Male,Loyal Customer,67,Personal Travel,Eco,862,2,5,2,1,3,2,5,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +80034,93724,Female,Loyal Customer,21,Personal Travel,Eco,630,4,4,3,3,3,4,4,5,4,4,5,4,3,4,143,133.0,neutral or dissatisfied +80035,73473,Female,Loyal Customer,49,Personal Travel,Eco,1144,1,4,1,3,2,4,4,5,5,1,5,4,5,4,67,58.0,neutral or dissatisfied +80036,115627,Female,Loyal Customer,51,Business travel,Eco,390,4,2,2,2,4,3,4,3,3,4,3,3,3,4,7,0.0,neutral or dissatisfied +80037,94438,Male,Loyal Customer,47,Business travel,Business,3178,2,2,2,2,5,5,4,4,4,4,4,3,4,3,2,0.0,satisfied +80038,100487,Female,Loyal Customer,40,Business travel,Business,1834,5,4,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +80039,73108,Female,Loyal Customer,55,Business travel,Business,2174,2,2,4,2,2,4,5,4,4,5,4,4,4,5,64,75.0,satisfied +80040,93857,Male,Loyal Customer,56,Business travel,Business,588,3,2,2,2,5,4,3,3,3,3,3,3,3,2,6,1.0,neutral or dissatisfied +80041,39910,Female,Loyal Customer,46,Personal Travel,Eco Plus,221,3,0,3,5,3,4,5,2,2,3,2,1,2,5,0,11.0,neutral or dissatisfied +80042,27897,Male,Loyal Customer,42,Personal Travel,Eco Plus,2329,1,5,2,4,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +80043,73422,Male,Loyal Customer,57,Business travel,Eco,720,5,4,4,4,5,5,5,5,5,1,2,2,1,5,0,0.0,satisfied +80044,27124,Female,disloyal Customer,21,Business travel,Eco,824,5,5,5,3,5,3,3,4,1,5,5,3,5,3,0,0.0,satisfied +80045,45318,Female,Loyal Customer,46,Business travel,Business,3529,2,2,2,2,5,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +80046,1250,Female,Loyal Customer,40,Personal Travel,Eco,134,2,4,0,4,5,0,5,5,4,2,4,2,3,5,19,13.0,neutral or dissatisfied +80047,4827,Male,Loyal Customer,59,Business travel,Business,2851,5,5,5,5,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +80048,105111,Male,disloyal Customer,42,Business travel,Business,281,3,3,3,3,2,3,2,2,3,5,4,3,3,2,1,0.0,neutral or dissatisfied +80049,128290,Male,Loyal Customer,44,Business travel,Business,2767,5,5,5,5,5,4,5,5,5,5,5,3,5,3,0,6.0,satisfied +80050,86585,Female,disloyal Customer,80,Business travel,Business,869,1,1,1,4,3,4,4,3,3,1,5,4,3,2,19,0.0,neutral or dissatisfied +80051,53618,Male,Loyal Customer,31,Business travel,Business,1874,3,5,5,5,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +80052,14238,Male,disloyal Customer,19,Business travel,Eco,1290,5,5,5,4,5,5,5,5,5,4,2,1,3,5,0,0.0,satisfied +80053,66602,Female,disloyal Customer,22,Business travel,Eco,761,3,3,3,4,3,3,3,3,4,5,3,2,4,3,25,12.0,neutral or dissatisfied +80054,31628,Male,disloyal Customer,32,Business travel,Eco,967,3,3,3,3,2,3,2,2,1,4,5,5,4,2,0,0.0,neutral or dissatisfied +80055,119339,Male,Loyal Customer,48,Personal Travel,Eco,214,3,0,3,2,5,3,5,5,3,2,4,3,4,5,106,96.0,neutral or dissatisfied +80056,94193,Female,Loyal Customer,46,Business travel,Business,189,3,3,4,3,5,4,5,4,4,4,4,3,4,3,19,19.0,satisfied +80057,22420,Female,Loyal Customer,37,Business travel,Business,3403,1,1,1,1,5,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +80058,89554,Female,Loyal Customer,12,Business travel,Business,2930,4,4,4,4,4,4,4,4,4,2,5,5,5,4,0,28.0,satisfied +80059,58847,Female,Loyal Customer,42,Business travel,Eco,783,3,3,3,3,2,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +80060,68242,Female,Loyal Customer,44,Business travel,Eco,432,2,3,3,3,2,3,3,2,2,2,2,1,2,3,0,6.0,neutral or dissatisfied +80061,120714,Female,disloyal Customer,47,Business travel,Business,90,1,2,2,3,1,1,4,1,4,1,3,4,4,1,3,19.0,neutral or dissatisfied +80062,19193,Female,disloyal Customer,20,Business travel,Eco,542,2,0,2,3,4,2,2,4,5,1,1,1,1,4,40,33.0,neutral or dissatisfied +80063,68787,Female,Loyal Customer,59,Business travel,Eco,926,4,2,2,2,2,3,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +80064,98624,Female,Loyal Customer,49,Business travel,Business,951,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +80065,85084,Female,Loyal Customer,42,Business travel,Business,696,4,4,4,4,4,4,4,5,3,5,5,4,4,4,274,259.0,satisfied +80066,70379,Female,Loyal Customer,54,Business travel,Business,1562,3,4,3,3,3,3,3,4,5,3,4,3,1,3,78,132.0,neutral or dissatisfied +80067,110531,Female,Loyal Customer,55,Business travel,Business,3074,4,4,4,4,2,4,5,5,5,5,5,3,5,3,29,28.0,satisfied +80068,114579,Female,Loyal Customer,59,Business travel,Business,390,2,2,2,2,5,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +80069,75561,Female,Loyal Customer,46,Business travel,Business,337,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +80070,32954,Male,Loyal Customer,42,Personal Travel,Eco,101,2,1,2,3,4,2,5,4,4,3,3,3,4,4,26,28.0,neutral or dissatisfied +80071,27657,Male,disloyal Customer,31,Business travel,Business,1107,4,4,4,4,4,4,4,4,5,5,1,1,2,4,0,0.0,neutral or dissatisfied +80072,58840,Male,Loyal Customer,25,Personal Travel,Eco Plus,1182,3,4,3,4,3,3,3,3,3,4,5,3,5,3,1,0.0,neutral or dissatisfied +80073,61095,Male,Loyal Customer,48,Personal Travel,Eco,1546,1,5,1,4,4,1,5,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +80074,88817,Male,Loyal Customer,46,Business travel,Eco Plus,545,3,1,1,1,3,3,3,3,3,2,3,3,3,3,74,86.0,neutral or dissatisfied +80075,117525,Male,Loyal Customer,40,Business travel,Business,1020,3,5,5,5,4,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +80076,63094,Female,Loyal Customer,52,Business travel,Business,967,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,5.0,satisfied +80077,66655,Female,Loyal Customer,32,Business travel,Business,1610,4,4,4,4,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +80078,107083,Female,Loyal Customer,32,Business travel,Eco Plus,395,0,0,0,4,1,0,1,1,5,2,2,3,1,1,1,0.0,satisfied +80079,119106,Male,Loyal Customer,35,Business travel,Business,1761,2,4,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +80080,40723,Female,disloyal Customer,34,Business travel,Eco,558,4,0,4,1,1,4,1,1,2,2,5,4,1,1,0,0.0,neutral or dissatisfied +80081,44960,Male,Loyal Customer,78,Business travel,Eco Plus,334,1,4,4,4,1,1,1,1,1,2,3,1,4,1,12,10.0,neutral or dissatisfied +80082,24920,Female,disloyal Customer,39,Business travel,Business,762,1,1,1,3,5,1,3,5,2,1,2,4,2,5,50,54.0,neutral or dissatisfied +80083,2416,Female,Loyal Customer,26,Personal Travel,Eco,641,3,1,3,4,5,3,5,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +80084,126753,Male,Loyal Customer,13,Personal Travel,Eco,2402,2,4,2,2,1,2,1,1,4,4,4,1,2,1,0,0.0,neutral or dissatisfied +80085,41400,Female,Loyal Customer,51,Business travel,Eco,563,1,5,5,5,1,3,3,1,1,1,1,3,1,4,20,25.0,neutral or dissatisfied +80086,57265,Female,Loyal Customer,54,Business travel,Business,3314,1,1,1,1,3,3,4,1,1,1,1,2,1,4,87,92.0,neutral or dissatisfied +80087,86448,Male,Loyal Customer,39,Business travel,Business,760,4,5,4,5,3,2,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +80088,54758,Male,Loyal Customer,22,Business travel,Eco Plus,787,2,2,5,5,2,2,3,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +80089,68936,Male,Loyal Customer,40,Business travel,Business,2388,2,1,1,1,2,3,4,2,2,2,2,2,2,2,0,7.0,neutral or dissatisfied +80090,119060,Female,Loyal Customer,67,Personal Travel,Eco,2279,1,4,1,2,3,4,5,5,5,1,2,5,5,3,7,0.0,neutral or dissatisfied +80091,47148,Female,disloyal Customer,39,Business travel,Business,679,2,2,2,3,5,2,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +80092,118784,Female,Loyal Customer,48,Personal Travel,Eco,369,2,1,3,4,5,4,4,5,5,3,5,3,5,1,2,0.0,neutral or dissatisfied +80093,51764,Male,Loyal Customer,25,Personal Travel,Eco,237,0,5,0,3,4,0,4,4,5,2,5,4,4,4,0,0.0,satisfied +80094,3032,Male,Loyal Customer,76,Business travel,Eco Plus,587,2,1,1,1,2,2,2,2,1,1,3,4,4,2,16,37.0,neutral or dissatisfied +80095,56740,Male,Loyal Customer,57,Personal Travel,Eco,997,3,5,3,2,4,3,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +80096,9792,Male,Loyal Customer,53,Business travel,Business,2794,5,5,5,5,3,5,4,5,5,5,5,3,5,3,2,0.0,satisfied +80097,54304,Female,Loyal Customer,38,Business travel,Business,1909,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +80098,50822,Female,Loyal Customer,12,Personal Travel,Eco,89,4,4,4,3,4,4,4,4,3,3,3,2,4,4,0,0.0,neutral or dissatisfied +80099,117578,Male,Loyal Customer,44,Business travel,Business,872,5,5,3,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +80100,40854,Female,Loyal Customer,28,Personal Travel,Eco,588,4,5,4,2,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +80101,120105,Female,Loyal Customer,59,Business travel,Business,1576,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +80102,65192,Male,Loyal Customer,17,Personal Travel,Eco,247,2,4,2,4,2,2,2,2,5,2,4,3,4,2,1,0.0,neutral or dissatisfied +80103,78082,Female,disloyal Customer,42,Business travel,Business,214,4,4,4,5,2,4,2,2,4,2,5,3,5,2,4,5.0,satisfied +80104,77644,Female,disloyal Customer,33,Business travel,Business,696,1,1,1,4,5,1,4,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +80105,44654,Male,Loyal Customer,50,Business travel,Eco,67,4,1,1,1,4,4,4,4,1,5,2,3,3,4,0,21.0,satisfied +80106,54761,Female,Loyal Customer,56,Business travel,Eco Plus,787,4,4,2,4,2,3,5,4,4,4,4,2,4,2,11,0.0,satisfied +80107,57249,Male,Loyal Customer,28,Business travel,Business,2789,3,3,3,3,3,3,3,3,5,2,5,3,5,3,0,0.0,satisfied +80108,127276,Male,Loyal Customer,54,Personal Travel,Eco,1107,4,5,4,2,4,4,3,4,3,3,1,2,1,4,0,0.0,satisfied +80109,48459,Male,Loyal Customer,19,Business travel,Business,776,5,5,5,5,5,5,5,5,4,3,4,5,4,5,4,0.0,satisfied +80110,119228,Female,Loyal Customer,66,Personal Travel,Eco,331,2,3,2,1,3,2,4,5,5,2,5,2,5,3,9,0.0,neutral or dissatisfied +80111,99323,Female,Loyal Customer,43,Personal Travel,Eco,448,2,4,0,4,4,3,4,3,3,0,3,4,3,1,56,57.0,neutral or dissatisfied +80112,70967,Male,Loyal Customer,37,Personal Travel,Business,802,3,4,3,5,1,2,3,1,1,3,1,5,1,4,27,46.0,neutral or dissatisfied +80113,110174,Female,Loyal Customer,67,Personal Travel,Eco,869,4,3,4,5,3,5,2,2,2,4,2,2,2,5,2,2.0,neutral or dissatisfied +80114,7732,Female,Loyal Customer,51,Business travel,Business,859,3,3,3,3,4,4,5,3,3,3,3,3,3,3,11,17.0,satisfied +80115,32170,Female,Loyal Customer,40,Business travel,Business,163,1,1,1,1,4,4,4,4,4,5,4,5,4,4,0,2.0,satisfied +80116,71062,Female,Loyal Customer,30,Personal Travel,Eco,802,5,3,5,1,1,5,1,1,2,4,3,5,4,1,14,0.0,satisfied +80117,46856,Male,Loyal Customer,50,Business travel,Business,2326,2,2,2,2,3,1,5,4,4,4,4,2,4,5,21,12.0,satisfied +80118,111938,Female,Loyal Customer,40,Business travel,Business,533,3,1,3,3,3,4,5,5,5,5,5,4,5,3,7,6.0,satisfied +80119,76089,Female,Loyal Customer,65,Personal Travel,Eco,707,1,4,1,3,3,4,5,4,4,1,4,4,4,3,0,4.0,neutral or dissatisfied +80120,106013,Female,Loyal Customer,56,Business travel,Business,1999,4,4,4,4,3,4,5,4,4,4,4,4,4,3,31,12.0,satisfied +80121,46645,Female,Loyal Customer,33,Business travel,Business,3773,2,1,1,1,2,3,3,3,3,3,2,2,3,2,24,19.0,neutral or dissatisfied +80122,23182,Female,Loyal Customer,29,Personal Travel,Eco,223,5,5,5,2,3,5,3,3,5,2,5,3,5,3,0,0.0,satisfied +80123,122012,Male,Loyal Customer,53,Business travel,Business,130,2,2,2,2,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +80124,13551,Male,disloyal Customer,23,Business travel,Eco,152,4,4,4,3,2,4,2,2,1,4,5,4,2,2,0,0.0,satisfied +80125,107712,Male,Loyal Customer,56,Business travel,Business,405,3,1,1,1,1,3,4,3,3,3,3,4,3,1,27,18.0,neutral or dissatisfied +80126,48035,Male,Loyal Customer,46,Business travel,Business,710,4,4,1,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +80127,74156,Male,Loyal Customer,48,Personal Travel,Eco,641,1,4,1,3,4,1,4,4,5,4,4,4,4,4,1,0.0,neutral or dissatisfied +80128,81454,Female,disloyal Customer,33,Business travel,Business,408,3,3,3,2,3,3,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +80129,49944,Female,Loyal Customer,29,Business travel,Eco,304,4,4,4,4,4,4,4,1,2,3,1,4,3,4,193,184.0,satisfied +80130,92122,Female,Loyal Customer,15,Personal Travel,Eco,1454,3,5,4,1,5,4,5,5,3,5,5,3,5,5,48,8.0,neutral or dissatisfied +80131,60420,Female,Loyal Customer,31,Business travel,Business,1860,4,4,5,4,3,3,3,3,4,2,4,4,5,3,0,7.0,satisfied +80132,40984,Male,disloyal Customer,30,Business travel,Eco,984,1,1,1,3,3,1,1,3,3,2,1,2,3,3,25,6.0,neutral or dissatisfied +80133,84906,Female,Loyal Customer,42,Personal Travel,Eco,357,4,5,4,5,3,5,4,2,2,4,2,5,2,3,1,0.0,neutral or dissatisfied +80134,37213,Male,Loyal Customer,23,Business travel,Business,989,1,1,1,1,4,4,4,4,4,3,4,3,5,4,37,28.0,satisfied +80135,32497,Female,Loyal Customer,48,Business travel,Eco,163,2,2,2,2,1,3,3,2,2,2,2,1,2,1,19,18.0,neutral or dissatisfied +80136,67471,Male,Loyal Customer,13,Personal Travel,Eco,641,4,4,4,4,3,4,3,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +80137,15452,Female,Loyal Customer,44,Business travel,Business,433,3,3,1,3,3,1,3,4,4,4,4,3,4,1,0,0.0,satisfied +80138,30566,Female,Loyal Customer,31,Business travel,Eco,628,5,4,4,4,5,5,5,5,4,4,4,4,3,5,0,0.0,satisfied +80139,118426,Male,disloyal Customer,34,Business travel,Business,369,1,1,1,4,1,1,1,1,3,4,4,5,4,1,6,1.0,neutral or dissatisfied +80140,55986,Male,Loyal Customer,45,Personal Travel,Eco Plus,1620,4,5,4,3,2,4,4,2,3,5,4,3,5,2,0,5.0,neutral or dissatisfied +80141,53677,Male,Loyal Customer,24,Business travel,Business,1190,1,1,1,1,4,4,4,4,1,2,2,4,3,4,0,0.0,satisfied +80142,40698,Female,Loyal Customer,40,Business travel,Business,532,2,2,2,2,1,2,1,4,4,5,4,5,4,2,0,0.0,satisfied +80143,74594,Female,Loyal Customer,25,Business travel,Eco,1126,2,2,2,2,2,2,3,2,1,4,4,4,3,2,0,10.0,neutral or dissatisfied +80144,100971,Female,Loyal Customer,22,Personal Travel,Business,1524,3,5,3,1,3,3,3,3,4,3,4,4,5,3,31,17.0,neutral or dissatisfied +80145,36727,Male,Loyal Customer,13,Personal Travel,Eco Plus,1197,4,5,4,3,1,4,1,1,3,2,4,2,5,1,0,0.0,satisfied +80146,92606,Female,Loyal Customer,29,Personal Travel,Eco,2158,1,4,1,4,4,1,4,4,5,5,5,4,4,4,57,41.0,neutral or dissatisfied +80147,8744,Female,Loyal Customer,69,Personal Travel,Eco Plus,280,3,4,4,2,5,4,4,5,5,4,5,4,5,5,12,14.0,neutral or dissatisfied +80148,84856,Male,disloyal Customer,38,Business travel,Eco,116,5,5,5,2,1,5,1,1,2,1,3,4,1,1,0,0.0,satisfied +80149,10643,Female,Loyal Customer,39,Business travel,Business,429,5,5,5,5,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +80150,73679,Male,Loyal Customer,25,Business travel,Business,2839,4,4,5,4,3,4,5,3,5,2,4,4,4,3,0,0.0,satisfied +80151,118820,Female,Loyal Customer,59,Business travel,Business,3075,5,5,5,5,3,4,4,4,4,4,4,4,4,5,39,24.0,satisfied +80152,15813,Male,Loyal Customer,62,Personal Travel,Eco,143,4,5,0,4,2,0,2,2,4,2,2,3,4,2,0,0.0,neutral or dissatisfied +80153,73835,Male,Loyal Customer,69,Personal Travel,Business,1709,2,2,2,4,3,3,3,4,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +80154,60290,Male,disloyal Customer,26,Business travel,Eco,783,1,1,1,4,2,1,2,2,1,4,3,2,3,2,79,89.0,neutral or dissatisfied +80155,87526,Female,Loyal Customer,64,Personal Travel,Eco,373,3,4,3,3,5,3,4,2,2,3,2,2,2,3,6,0.0,neutral or dissatisfied +80156,113453,Female,Loyal Customer,60,Business travel,Business,414,3,1,3,3,2,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +80157,22257,Male,Loyal Customer,51,Business travel,Business,83,0,4,0,2,1,3,5,5,5,5,5,3,5,1,0,0.0,satisfied +80158,80102,Female,disloyal Customer,26,Business travel,Business,1620,1,1,1,5,1,1,1,1,4,4,5,5,5,1,0,32.0,neutral or dissatisfied +80159,14009,Female,Loyal Customer,65,Personal Travel,Eco,615,4,3,4,5,1,5,2,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +80160,35621,Female,Loyal Customer,57,Personal Travel,Eco Plus,1028,4,5,4,1,5,5,4,5,5,4,2,5,5,5,9,0.0,satisfied +80161,44619,Female,Loyal Customer,42,Business travel,Eco Plus,566,4,3,3,3,5,4,5,5,5,4,5,5,5,1,0,0.0,satisfied +80162,28641,Male,disloyal Customer,30,Business travel,Business,2614,4,4,4,4,2,4,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +80163,6611,Male,disloyal Customer,27,Business travel,Business,473,4,4,4,2,5,4,5,5,4,2,4,5,5,5,74,71.0,satisfied +80164,114971,Male,Loyal Customer,53,Business travel,Business,3094,1,1,1,1,5,5,5,4,4,4,4,5,4,4,72,66.0,satisfied +80165,61586,Male,Loyal Customer,51,Personal Travel,Business,1635,5,5,5,2,2,4,4,5,5,5,4,5,5,3,9,7.0,satisfied +80166,14157,Female,Loyal Customer,57,Business travel,Business,2886,4,4,4,4,3,5,4,3,3,3,3,5,3,5,0,8.0,satisfied +80167,53086,Female,Loyal Customer,69,Personal Travel,Eco,2327,0,5,0,3,5,4,4,5,5,0,5,2,5,3,9,0.0,satisfied +80168,77667,Male,Loyal Customer,38,Business travel,Business,813,4,2,2,2,5,3,3,4,4,4,4,1,4,1,21,9.0,neutral or dissatisfied +80169,51241,Male,Loyal Customer,48,Business travel,Eco Plus,153,4,5,5,5,4,4,4,4,5,4,4,4,5,4,11,31.0,satisfied +80170,113854,Female,Loyal Customer,24,Business travel,Business,1363,5,5,5,5,4,5,4,4,5,3,4,4,5,4,0,0.0,satisfied +80171,115422,Female,Loyal Customer,57,Business travel,Business,3011,3,1,1,1,2,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +80172,80889,Female,disloyal Customer,39,Business travel,Eco Plus,292,3,3,3,3,4,3,4,4,2,5,1,5,5,4,0,4.0,satisfied +80173,56340,Female,Loyal Customer,64,Business travel,Business,3513,1,3,3,3,1,4,3,3,3,3,1,2,3,3,10,4.0,neutral or dissatisfied +80174,8885,Female,Loyal Customer,56,Personal Travel,Eco,539,2,4,2,4,5,4,5,5,5,2,1,3,5,3,80,60.0,neutral or dissatisfied +80175,25405,Female,Loyal Customer,58,Business travel,Eco,990,2,1,1,1,5,3,4,2,2,2,2,4,2,4,12,0.0,neutral or dissatisfied +80176,114581,Female,Loyal Customer,44,Business travel,Business,2969,2,2,2,2,5,4,4,5,5,5,5,5,5,5,47,25.0,satisfied +80177,23696,Female,Loyal Customer,31,Business travel,Business,1753,1,5,5,5,1,1,1,1,3,4,4,2,3,1,0,6.0,neutral or dissatisfied +80178,14395,Female,disloyal Customer,18,Business travel,Eco,789,2,2,2,3,3,2,3,3,2,1,3,1,3,3,21,10.0,neutral or dissatisfied +80179,85848,Male,Loyal Customer,46,Business travel,Business,666,3,3,3,3,3,5,5,5,5,5,5,5,5,3,16,5.0,satisfied +80180,17604,Male,disloyal Customer,33,Business travel,Eco,196,4,3,4,3,4,4,4,4,4,4,2,3,2,4,0,0.0,neutral or dissatisfied +80181,83252,Female,Loyal Customer,28,Business travel,Business,1979,2,2,1,2,4,5,4,4,3,4,5,4,5,4,0,17.0,satisfied +80182,8345,Male,Loyal Customer,47,Business travel,Business,2187,4,5,4,4,4,4,4,5,4,5,5,4,4,4,933,920.0,satisfied +80183,13190,Female,disloyal Customer,20,Business travel,Eco,542,3,3,3,4,5,3,5,5,3,2,1,5,5,5,0,0.0,neutral or dissatisfied +80184,86760,Male,Loyal Customer,56,Personal Travel,Eco,821,3,3,3,4,1,3,1,1,4,4,3,1,4,1,4,0.0,neutral or dissatisfied +80185,39493,Male,Loyal Customer,23,Business travel,Business,1368,4,1,4,4,4,4,4,4,5,1,2,2,3,4,0,0.0,satisfied +80186,84454,Female,Loyal Customer,44,Business travel,Eco,290,3,2,2,2,2,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +80187,33734,Female,Loyal Customer,42,Personal Travel,Eco,759,2,3,2,2,4,4,1,1,1,2,1,2,1,2,10,21.0,neutral or dissatisfied +80188,119450,Male,Loyal Customer,51,Business travel,Business,759,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +80189,41415,Female,Loyal Customer,53,Personal Travel,Eco,563,0,4,0,2,5,4,5,2,2,0,2,4,2,5,0,0.0,satisfied +80190,112776,Male,Loyal Customer,61,Personal Travel,Eco,588,3,5,3,3,3,3,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +80191,85095,Male,Loyal Customer,57,Business travel,Business,3737,1,1,1,1,5,5,5,5,5,5,5,5,5,3,14,7.0,satisfied +80192,71289,Male,Loyal Customer,54,Business travel,Eco Plus,733,3,3,2,3,3,3,3,3,4,3,4,2,4,3,39,32.0,neutral or dissatisfied +80193,114508,Male,disloyal Customer,23,Business travel,Eco,342,1,2,1,3,3,1,3,3,3,1,4,4,4,3,60,54.0,neutral or dissatisfied +80194,54872,Male,disloyal Customer,19,Business travel,Eco,934,5,5,5,5,5,5,5,5,3,3,5,1,1,5,4,4.0,satisfied +80195,39753,Male,Loyal Customer,30,Business travel,Business,1658,3,3,3,3,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +80196,35463,Male,Loyal Customer,60,Personal Travel,Eco,1056,1,4,1,3,4,1,4,4,2,3,4,4,5,4,77,104.0,neutral or dissatisfied +80197,94831,Female,Loyal Customer,26,Business travel,Business,2062,2,3,3,3,2,2,2,2,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +80198,1013,Female,disloyal Customer,16,Business travel,Eco,229,3,1,3,3,2,3,2,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +80199,104085,Male,Loyal Customer,24,Personal Travel,Eco,666,3,1,3,2,3,3,3,3,2,5,2,2,2,3,0,0.0,neutral or dissatisfied +80200,4764,Male,Loyal Customer,51,Business travel,Business,1520,2,2,1,2,2,2,2,4,2,4,4,2,4,2,127,162.0,satisfied +80201,96568,Female,Loyal Customer,34,Business travel,Business,333,4,4,4,4,2,5,4,4,4,4,4,3,4,5,41,31.0,satisfied +80202,6424,Female,Loyal Customer,42,Personal Travel,Eco,213,2,4,0,4,4,3,2,1,1,0,4,3,1,2,0,0.0,neutral or dissatisfied +80203,1435,Female,Loyal Customer,52,Business travel,Business,3909,3,3,3,3,3,4,4,5,5,5,5,4,5,4,31,33.0,satisfied +80204,62441,Female,Loyal Customer,24,Personal Travel,Eco,1943,3,5,3,2,5,3,5,5,4,3,3,5,4,5,28,4.0,neutral or dissatisfied +80205,63121,Male,Loyal Customer,42,Business travel,Business,447,4,4,4,4,2,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +80206,99410,Male,disloyal Customer,44,Business travel,Business,314,2,2,2,2,2,2,1,2,3,2,5,3,5,2,6,3.0,neutral or dissatisfied +80207,116621,Female,Loyal Customer,26,Business travel,Business,3169,5,5,4,5,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +80208,37470,Male,Loyal Customer,22,Business travel,Business,1005,2,1,1,1,2,2,2,2,1,1,5,1,2,2,0,0.0,neutral or dissatisfied +80209,105453,Male,Loyal Customer,28,Personal Travel,Eco,998,1,4,1,4,3,1,3,3,3,2,4,3,5,3,10,22.0,neutral or dissatisfied +80210,102296,Female,Loyal Customer,42,Business travel,Business,2969,1,4,4,4,1,4,4,1,1,1,1,4,1,3,0,3.0,neutral or dissatisfied +80211,48894,Male,disloyal Customer,63,Business travel,Eco,89,1,0,1,5,5,1,5,5,5,1,4,4,3,5,0,9.0,neutral or dissatisfied +80212,20343,Male,disloyal Customer,37,Business travel,Business,287,3,3,3,4,4,3,4,4,2,2,3,2,4,4,0,0.0,neutral or dissatisfied +80213,29449,Male,Loyal Customer,71,Business travel,Business,2598,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +80214,88516,Male,Loyal Customer,61,Personal Travel,Eco,404,4,5,4,3,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +80215,18199,Male,Loyal Customer,54,Business travel,Eco,235,4,4,4,4,4,4,4,4,3,4,5,5,3,4,18,6.0,satisfied +80216,33188,Female,disloyal Customer,33,Business travel,Eco Plus,101,2,1,1,1,4,1,4,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +80217,48072,Female,Loyal Customer,52,Business travel,Business,3424,1,1,1,1,5,5,4,4,4,4,5,4,4,3,21,45.0,satisfied +80218,75294,Male,Loyal Customer,11,Personal Travel,Eco Plus,1744,4,5,4,1,5,4,5,5,4,5,3,3,4,5,0,0.0,satisfied +80219,118472,Female,Loyal Customer,43,Business travel,Business,369,3,3,3,3,3,4,5,2,2,2,2,3,2,3,19,12.0,satisfied +80220,109094,Female,Loyal Customer,38,Personal Travel,Eco,781,2,5,2,1,4,2,4,4,1,2,2,4,5,4,0,0.0,neutral or dissatisfied +80221,55552,Female,Loyal Customer,66,Personal Travel,Eco,550,4,0,4,1,1,3,4,3,3,4,3,2,3,3,0,0.0,satisfied +80222,35892,Female,Loyal Customer,36,Personal Travel,Eco,1023,4,3,4,3,4,4,4,4,4,1,4,4,3,4,0,0.0,neutral or dissatisfied +80223,102886,Female,Loyal Customer,44,Business travel,Business,3071,4,4,4,4,5,5,5,5,5,5,5,3,5,4,0,5.0,satisfied +80224,22466,Male,Loyal Customer,68,Personal Travel,Eco,143,3,2,3,4,2,3,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +80225,24161,Male,Loyal Customer,39,Business travel,Eco,147,4,3,3,3,4,4,4,4,4,3,5,1,5,4,0,0.0,satisfied +80226,1676,Female,Loyal Customer,44,Business travel,Business,561,1,1,1,1,2,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +80227,99905,Male,Loyal Customer,29,Personal Travel,Eco,738,3,5,3,1,2,3,2,2,3,3,5,3,5,2,0,9.0,neutral or dissatisfied +80228,44472,Female,Loyal Customer,11,Personal Travel,Eco,196,1,3,1,1,5,1,5,5,3,4,2,1,2,5,0,0.0,neutral or dissatisfied +80229,74585,Male,disloyal Customer,26,Business travel,Eco,1235,3,4,4,3,4,4,4,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +80230,32962,Male,Loyal Customer,60,Personal Travel,Eco,163,3,5,3,1,3,3,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +80231,13725,Male,disloyal Customer,42,Business travel,Eco,401,4,4,4,3,5,4,5,5,4,5,3,3,2,5,30,21.0,neutral or dissatisfied +80232,77861,Female,Loyal Customer,14,Personal Travel,Eco Plus,874,4,1,4,4,3,4,2,3,3,4,2,4,3,3,0,0.0,satisfied +80233,105030,Female,Loyal Customer,56,Business travel,Business,3476,4,4,3,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +80234,118793,Female,Loyal Customer,42,Personal Travel,Eco,325,1,3,1,3,3,1,4,1,1,1,1,2,1,1,10,9.0,neutral or dissatisfied +80235,14755,Male,disloyal Customer,37,Business travel,Eco,463,1,2,1,3,3,1,3,3,2,5,4,4,3,3,49,45.0,neutral or dissatisfied +80236,108566,Male,disloyal Customer,25,Business travel,Business,547,5,0,5,4,4,5,1,4,3,3,4,5,4,4,49,36.0,satisfied +80237,126191,Female,Loyal Customer,33,Business travel,Business,2760,2,4,4,4,2,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +80238,7095,Male,Loyal Customer,47,Business travel,Eco,273,3,5,5,5,3,3,3,3,3,2,3,3,4,3,55,55.0,neutral or dissatisfied +80239,92295,Female,Loyal Customer,60,Personal Travel,Eco,1814,1,3,1,1,4,5,1,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +80240,93179,Female,Loyal Customer,64,Personal Travel,Eco,1183,1,3,1,4,1,3,3,5,5,1,5,2,5,1,8,0.0,neutral or dissatisfied +80241,105492,Female,Loyal Customer,45,Business travel,Eco,516,2,3,3,3,1,4,4,2,2,2,2,1,2,4,21,15.0,neutral or dissatisfied +80242,31451,Male,Loyal Customer,55,Personal Travel,Business,853,4,4,4,4,2,4,5,4,4,4,4,5,4,3,9,32.0,satisfied +80243,129330,Male,Loyal Customer,30,Business travel,Business,2586,3,3,3,3,3,3,3,3,4,4,2,2,4,3,5,9.0,neutral or dissatisfied +80244,73340,Male,Loyal Customer,60,Business travel,Business,2432,3,3,2,3,3,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +80245,36654,Female,Loyal Customer,53,Personal Travel,Eco,1010,2,3,2,4,2,3,3,2,2,2,2,5,2,2,0,0.0,neutral or dissatisfied +80246,117988,Female,Loyal Customer,30,Business travel,Business,1967,2,2,5,2,3,4,3,3,3,2,5,3,5,3,0,0.0,satisfied +80247,66942,Male,Loyal Customer,49,Business travel,Business,1121,3,3,3,3,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +80248,94969,Female,Loyal Customer,45,Business travel,Eco,277,3,2,2,2,4,4,3,3,3,3,3,3,3,1,15,18.0,neutral or dissatisfied +80249,85171,Female,Loyal Customer,44,Business travel,Business,813,3,3,3,3,2,2,3,3,3,2,3,4,3,2,59,34.0,neutral or dissatisfied +80250,49640,Female,Loyal Customer,63,Business travel,Business,337,0,0,0,3,3,3,4,2,2,2,2,2,2,2,11,3.0,satisfied +80251,76052,Female,Loyal Customer,41,Business travel,Business,669,2,2,2,2,5,5,5,5,5,5,5,5,5,4,4,0.0,satisfied +80252,86219,Female,Loyal Customer,33,Business travel,Eco,306,3,4,4,4,3,3,3,3,3,4,3,4,3,3,1,8.0,neutral or dissatisfied +80253,38246,Female,disloyal Customer,38,Business travel,Eco,1180,2,2,2,3,2,2,2,2,1,3,3,1,3,2,18,4.0,neutral or dissatisfied +80254,50015,Female,disloyal Customer,34,Business travel,Eco,373,2,0,2,3,4,2,4,4,5,2,5,5,3,4,0,0.0,neutral or dissatisfied +80255,88417,Male,Loyal Customer,58,Business travel,Business,442,2,2,2,2,3,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +80256,60499,Female,disloyal Customer,25,Business travel,Eco,862,4,4,4,4,3,4,3,3,5,4,3,2,1,3,8,0.0,neutral or dissatisfied +80257,93707,Female,disloyal Customer,25,Business travel,Eco,689,3,2,2,3,5,2,5,5,2,5,3,2,3,5,30,14.0,neutral or dissatisfied +80258,40119,Female,Loyal Customer,43,Business travel,Business,368,3,5,5,5,1,4,4,3,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +80259,82977,Female,disloyal Customer,50,Business travel,Business,1127,4,4,4,1,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +80260,112094,Male,Loyal Customer,44,Business travel,Business,1062,1,1,5,1,5,5,5,2,2,2,2,3,2,3,47,41.0,satisfied +80261,482,Female,Loyal Customer,30,Business travel,Business,482,1,1,1,1,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +80262,68570,Female,Loyal Customer,53,Business travel,Business,1616,5,5,5,5,3,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +80263,104010,Male,Loyal Customer,17,Personal Travel,Eco,1363,1,5,1,2,4,1,4,4,3,2,5,5,5,4,6,0.0,neutral or dissatisfied +80264,76106,Female,Loyal Customer,41,Business travel,Eco Plus,669,4,3,3,3,5,3,3,4,4,4,4,3,4,1,40,49.0,neutral or dissatisfied +80265,76249,Male,Loyal Customer,25,Personal Travel,Eco,1175,1,5,1,4,4,1,4,4,4,4,4,5,4,4,1,0.0,neutral or dissatisfied +80266,87485,Female,Loyal Customer,42,Business travel,Business,373,4,4,4,4,2,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +80267,68640,Male,Loyal Customer,48,Business travel,Business,237,4,4,5,4,5,5,5,5,5,4,5,3,5,4,3,0.0,satisfied +80268,31474,Female,disloyal Customer,43,Business travel,Eco,967,3,3,3,3,3,3,4,3,3,1,5,5,5,3,15,39.0,neutral or dissatisfied +80269,36693,Male,Loyal Customer,65,Personal Travel,Eco,1249,2,5,1,3,4,1,4,4,5,5,5,3,4,4,46,79.0,neutral or dissatisfied +80270,84313,Male,Loyal Customer,32,Business travel,Business,2730,5,5,5,5,4,4,4,4,4,2,4,4,5,4,1,0.0,satisfied +80271,66483,Female,Loyal Customer,39,Business travel,Business,3650,1,1,4,1,5,5,5,5,5,5,5,5,4,5,244,250.0,satisfied +80272,81949,Female,Loyal Customer,41,Business travel,Business,1532,2,2,4,2,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +80273,103163,Male,Loyal Customer,43,Business travel,Business,272,5,3,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +80274,34264,Female,disloyal Customer,27,Business travel,Eco,280,2,0,2,4,3,2,3,3,5,3,3,3,4,3,0,0.0,neutral or dissatisfied +80275,69158,Female,Loyal Customer,40,Business travel,Business,2553,2,2,2,2,2,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +80276,62881,Female,disloyal Customer,17,Business travel,Eco,830,3,3,3,3,2,3,2,2,3,3,4,5,4,2,1,0.0,neutral or dissatisfied +80277,91100,Female,Loyal Customer,23,Personal Travel,Eco,271,2,0,5,2,1,5,1,1,3,1,4,2,5,1,8,0.0,neutral or dissatisfied +80278,112295,Male,Loyal Customer,29,Personal Travel,Eco Plus,1546,3,4,3,1,4,3,4,4,3,4,4,5,4,4,8,0.0,neutral or dissatisfied +80279,118889,Female,Loyal Customer,56,Business travel,Business,587,1,1,1,1,3,5,5,2,2,2,2,3,2,5,61,70.0,satisfied +80280,92917,Male,Loyal Customer,49,Business travel,Business,134,2,2,2,2,2,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +80281,27155,Male,Loyal Customer,69,Business travel,Business,2688,3,5,2,5,3,3,3,3,3,2,4,3,2,3,0,8.0,neutral or dissatisfied +80282,54845,Female,Loyal Customer,25,Business travel,Business,2201,1,2,2,2,1,1,1,1,2,4,4,4,3,1,17,2.0,neutral or dissatisfied +80283,76863,Male,Loyal Customer,53,Business travel,Business,1927,2,2,2,2,3,3,4,4,4,4,4,3,4,3,5,0.0,satisfied +80284,121971,Female,disloyal Customer,70,Personal Travel,Business,130,3,5,0,5,1,0,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +80285,126274,Female,Loyal Customer,42,Personal Travel,Eco,468,1,4,1,3,2,4,3,3,3,1,1,1,3,1,0,0.0,neutral or dissatisfied +80286,28842,Male,Loyal Customer,38,Business travel,Eco,679,4,3,5,5,4,4,4,4,1,1,1,2,4,4,0,0.0,satisfied +80287,81666,Male,disloyal Customer,39,Business travel,Eco,907,2,2,2,3,5,2,5,5,3,1,2,1,3,5,0,0.0,neutral or dissatisfied +80288,64983,Female,Loyal Customer,35,Business travel,Eco,469,3,2,2,2,3,3,3,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +80289,105579,Male,Loyal Customer,49,Business travel,Business,2289,2,4,4,4,5,3,3,4,4,4,2,3,4,4,35,41.0,neutral or dissatisfied +80290,91799,Male,Loyal Customer,57,Personal Travel,Eco,588,3,4,3,4,4,3,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +80291,58586,Female,Loyal Customer,35,Business travel,Business,334,2,3,3,3,1,3,3,2,2,2,2,2,2,4,6,0.0,neutral or dissatisfied +80292,57921,Male,Loyal Customer,35,Personal Travel,Eco,305,3,2,3,3,4,3,4,4,4,1,4,2,4,4,0,12.0,neutral or dissatisfied +80293,43500,Male,Loyal Customer,31,Personal Travel,Eco,624,2,4,2,3,2,2,2,2,1,4,5,1,5,2,0,0.0,neutral or dissatisfied +80294,61960,Male,Loyal Customer,40,Personal Travel,Eco,2052,2,5,2,1,4,2,4,4,4,4,4,4,4,4,1,0.0,neutral or dissatisfied +80295,101546,Female,Loyal Customer,32,Personal Travel,Eco,345,4,5,4,5,4,4,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +80296,53859,Male,Loyal Customer,58,Business travel,Business,1810,4,4,4,4,1,2,2,5,5,5,3,2,5,2,0,0.0,satisfied +80297,42751,Male,Loyal Customer,30,Business travel,Eco,607,4,1,1,1,4,4,4,4,4,1,1,5,5,4,0,0.0,satisfied +80298,128562,Female,Loyal Customer,52,Personal Travel,Eco Plus,304,4,4,4,3,3,4,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +80299,104508,Male,disloyal Customer,36,Business travel,Eco,1009,1,1,1,2,4,1,4,4,5,3,3,4,2,4,0,0.0,neutral or dissatisfied +80300,84250,Female,Loyal Customer,69,Personal Travel,Business,1814,4,5,4,3,4,3,4,2,2,4,2,3,2,4,0,13.0,neutral or dissatisfied +80301,90833,Male,Loyal Customer,52,Business travel,Business,406,5,5,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +80302,56368,Male,Loyal Customer,43,Personal Travel,Eco,200,2,5,2,4,3,2,3,3,5,3,4,3,4,3,2,0.0,neutral or dissatisfied +80303,53877,Female,Loyal Customer,63,Business travel,Business,224,3,2,2,2,2,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +80304,40478,Male,Loyal Customer,24,Business travel,Eco,175,5,5,4,5,5,5,3,5,1,1,1,2,4,5,0,0.0,satisfied +80305,25824,Female,Loyal Customer,26,Personal Travel,Eco Plus,1747,3,5,3,4,4,3,4,4,5,1,3,3,1,4,15,38.0,neutral or dissatisfied +80306,89516,Male,Loyal Customer,58,Business travel,Business,3631,2,3,3,3,1,4,4,2,2,2,2,2,2,4,13,18.0,neutral or dissatisfied +80307,96790,Male,Loyal Customer,49,Business travel,Business,1575,3,3,3,3,2,4,5,5,5,5,5,5,5,3,5,18.0,satisfied +80308,71228,Female,Loyal Customer,43,Business travel,Business,2261,3,2,2,2,3,3,3,3,3,3,3,2,3,2,27,23.0,neutral or dissatisfied +80309,35675,Female,Loyal Customer,49,Business travel,Eco,2475,4,2,2,2,4,4,4,5,3,3,2,4,4,4,34,40.0,satisfied +80310,98772,Male,Loyal Customer,8,Personal Travel,Eco,2075,3,5,3,4,2,3,5,2,4,4,5,3,4,2,21,28.0,neutral or dissatisfied +80311,8797,Female,Loyal Customer,42,Business travel,Business,2268,3,5,5,5,3,4,3,3,3,3,3,2,3,1,45,57.0,neutral or dissatisfied +80312,9779,Female,Loyal Customer,11,Personal Travel,Eco,383,2,5,2,3,3,2,4,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +80313,129239,Female,disloyal Customer,38,Business travel,Eco,809,1,1,1,4,4,1,4,4,1,3,4,1,4,4,0,0.0,neutral or dissatisfied +80314,79952,Female,Loyal Customer,23,Business travel,Eco,1076,4,4,4,4,4,4,1,4,4,2,4,4,3,4,59,57.0,neutral or dissatisfied +80315,93419,Male,Loyal Customer,56,Business travel,Business,3515,2,1,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +80316,35104,Male,disloyal Customer,42,Business travel,Eco,950,3,3,3,3,1,3,1,1,1,4,4,5,2,1,0,27.0,neutral or dissatisfied +80317,28728,Female,Loyal Customer,32,Business travel,Eco Plus,2717,4,5,5,5,4,4,4,1,5,4,1,4,2,4,0,0.0,satisfied +80318,23131,Female,disloyal Customer,52,Business travel,Eco,646,2,0,2,3,1,2,2,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +80319,96420,Male,Loyal Customer,42,Business travel,Eco Plus,1342,3,3,3,3,3,3,3,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +80320,122771,Female,Loyal Customer,23,Personal Travel,Eco,427,3,2,3,4,3,3,3,3,2,5,4,4,4,3,0,8.0,neutral or dissatisfied +80321,77994,Female,Loyal Customer,56,Business travel,Business,332,4,4,4,4,4,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +80322,15512,Female,Loyal Customer,48,Personal Travel,Eco,377,3,5,3,4,4,4,5,4,4,3,4,5,4,3,0,3.0,neutral or dissatisfied +80323,114677,Male,disloyal Customer,37,Business travel,Business,333,3,3,3,1,5,3,5,5,4,2,4,4,5,5,1,0.0,neutral or dissatisfied +80324,20152,Female,Loyal Customer,45,Business travel,Business,2710,3,3,3,3,4,5,1,4,4,4,4,2,4,3,9,0.0,satisfied +80325,91618,Male,Loyal Customer,31,Business travel,Business,1744,3,3,3,3,3,3,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +80326,44195,Female,Loyal Customer,62,Business travel,Business,157,5,5,5,5,1,4,5,4,4,4,4,5,4,1,0,0.0,satisfied +80327,35625,Male,Loyal Customer,10,Personal Travel,Eco Plus,1056,1,5,1,1,5,1,5,5,4,4,4,3,5,5,72,78.0,neutral or dissatisfied +80328,109253,Female,Loyal Customer,31,Business travel,Business,2907,4,4,4,4,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +80329,22393,Male,Loyal Customer,49,Business travel,Eco,145,4,1,5,1,4,4,4,4,4,5,1,3,5,4,0,0.0,satisfied +80330,31939,Female,Loyal Customer,45,Business travel,Business,201,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,3.0,satisfied +80331,84916,Male,Loyal Customer,32,Personal Travel,Eco,547,3,2,3,3,3,3,4,3,4,1,3,2,4,3,19,15.0,neutral or dissatisfied +80332,50275,Female,Loyal Customer,72,Business travel,Eco,308,3,1,1,1,3,3,3,3,3,3,3,2,3,3,53,50.0,neutral or dissatisfied +80333,12258,Male,Loyal Customer,47,Business travel,Business,201,3,3,4,3,5,3,1,4,4,4,5,4,4,2,0,0.0,satisfied +80334,46201,Female,Loyal Customer,37,Business travel,Business,624,2,2,2,2,2,4,4,4,4,4,4,4,4,5,0,1.0,satisfied +80335,128406,Male,Loyal Customer,40,Business travel,Business,646,5,5,5,5,5,5,5,5,5,5,5,3,5,3,0,5.0,satisfied +80336,59863,Male,Loyal Customer,30,Business travel,Business,1065,1,1,5,1,5,5,5,5,5,3,4,4,5,5,6,0.0,satisfied +80337,94279,Female,Loyal Customer,53,Business travel,Business,248,2,2,2,2,4,5,5,4,4,4,4,4,4,4,84,81.0,satisfied +80338,71825,Male,disloyal Customer,27,Business travel,Business,1359,4,4,4,3,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +80339,75119,Female,disloyal Customer,25,Business travel,Business,1846,2,5,2,1,1,2,1,1,4,3,4,5,4,1,1,0.0,neutral or dissatisfied +80340,13891,Male,Loyal Customer,32,Business travel,Eco Plus,578,3,5,5,5,3,3,3,3,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +80341,88195,Female,Loyal Customer,59,Business travel,Business,594,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,9.0,satisfied +80342,116863,Male,disloyal Customer,23,Business travel,Eco,451,3,2,3,4,1,3,1,1,2,4,4,2,4,1,52,55.0,neutral or dissatisfied +80343,70406,Male,Loyal Customer,36,Personal Travel,Eco,1562,1,2,1,3,5,1,4,5,4,4,2,4,4,5,0,3.0,neutral or dissatisfied +80344,27358,Female,disloyal Customer,25,Business travel,Eco,679,3,3,3,3,5,3,5,5,3,2,4,1,4,5,0,0.0,neutral or dissatisfied +80345,3862,Male,Loyal Customer,21,Business travel,Business,213,2,2,2,2,2,2,2,2,1,2,3,2,4,2,124,129.0,neutral or dissatisfied +80346,103650,Male,Loyal Customer,58,Business travel,Business,1978,1,1,5,1,4,5,4,4,4,4,4,5,4,3,57,58.0,satisfied +80347,26518,Female,Loyal Customer,36,Business travel,Business,990,2,2,2,2,3,3,3,5,5,5,5,5,5,3,0,0.0,satisfied +80348,57636,Male,Loyal Customer,46,Business travel,Business,3183,2,5,5,5,2,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +80349,104195,Male,disloyal Customer,27,Business travel,Business,1310,5,5,5,3,1,5,1,1,4,3,4,4,4,1,0,0.0,satisfied +80350,49908,Male,Loyal Customer,35,Business travel,Business,1776,2,3,4,3,5,4,3,2,2,2,2,2,2,4,0,2.0,neutral or dissatisfied +80351,106231,Male,Loyal Customer,48,Personal Travel,Eco,471,2,4,2,2,1,2,1,1,4,2,5,5,5,1,14,5.0,neutral or dissatisfied +80352,90935,Female,Loyal Customer,54,Business travel,Business,250,3,3,4,3,4,5,3,5,5,5,5,2,5,5,0,3.0,satisfied +80353,21271,Male,Loyal Customer,41,Business travel,Eco,620,4,1,1,1,4,4,4,4,5,4,3,2,3,4,0,0.0,satisfied +80354,42961,Female,Loyal Customer,36,Business travel,Business,1977,0,0,0,4,1,4,3,1,1,1,1,5,1,3,0,0.0,satisfied +80355,1126,Female,Loyal Customer,32,Personal Travel,Eco,134,1,2,0,4,2,0,1,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +80356,46379,Female,Loyal Customer,38,Business travel,Business,1013,1,3,3,3,1,2,2,1,1,1,1,4,1,2,18,29.0,neutral or dissatisfied +80357,50576,Female,Loyal Customer,10,Personal Travel,Eco,326,2,1,2,2,2,2,2,2,2,3,1,2,3,2,0,0.0,neutral or dissatisfied +80358,97210,Female,disloyal Customer,36,Business travel,Business,1390,2,2,2,2,3,2,3,3,5,5,4,4,4,3,1,0.0,neutral or dissatisfied +80359,67283,Female,Loyal Customer,13,Personal Travel,Eco,1121,3,4,3,1,1,3,1,1,5,5,4,4,4,1,20,14.0,neutral or dissatisfied +80360,52810,Male,disloyal Customer,25,Business travel,Eco,836,2,2,2,3,5,2,5,5,3,2,5,4,1,5,2,0.0,neutral or dissatisfied +80361,11937,Female,Loyal Customer,33,Business travel,Business,781,2,2,2,2,5,5,5,5,5,5,5,5,5,5,32,34.0,satisfied +80362,62690,Male,Loyal Customer,59,Business travel,Business,2338,4,4,4,4,2,4,4,4,4,4,4,3,4,3,4,0.0,satisfied +80363,53159,Female,Loyal Customer,59,Business travel,Business,2597,3,2,2,2,3,3,3,2,1,4,3,3,2,3,140,144.0,neutral or dissatisfied +80364,83975,Male,Loyal Customer,51,Business travel,Business,1780,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +80365,21264,Male,Loyal Customer,59,Business travel,Business,620,2,2,5,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +80366,32652,Male,disloyal Customer,36,Business travel,Eco,101,3,0,3,4,2,3,2,2,2,3,1,5,4,2,0,0.0,neutral or dissatisfied +80367,98761,Female,Loyal Customer,39,Business travel,Business,575,1,1,1,1,5,5,3,5,5,5,5,3,5,4,21,9.0,satisfied +80368,67285,Male,Loyal Customer,21,Personal Travel,Eco,1121,1,5,2,4,1,2,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +80369,117973,Male,Loyal Customer,14,Personal Travel,Eco,255,2,5,2,2,2,2,3,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +80370,15685,Male,Loyal Customer,22,Business travel,Eco Plus,617,2,4,4,4,2,2,3,2,1,4,3,2,4,2,86,93.0,neutral or dissatisfied +80371,126877,Female,Loyal Customer,13,Personal Travel,Eco,2125,1,4,1,4,2,1,2,2,4,2,3,3,4,2,81,64.0,neutral or dissatisfied +80372,10246,Male,Loyal Customer,48,Personal Travel,Business,229,3,5,3,2,2,5,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +80373,39865,Female,disloyal Customer,79,Business travel,Eco,272,3,0,3,2,3,3,3,3,2,4,5,1,1,3,0,0.0,neutral or dissatisfied +80374,13359,Female,disloyal Customer,38,Business travel,Eco,348,2,3,2,3,4,2,4,4,2,3,3,3,4,4,127,108.0,neutral or dissatisfied +80375,63010,Male,Loyal Customer,60,Business travel,Business,3879,2,2,2,2,4,4,4,4,4,4,4,4,4,5,6,0.0,satisfied +80376,127446,Male,Loyal Customer,43,Personal Travel,Eco Plus,868,2,2,2,4,2,2,2,2,1,1,3,3,4,2,4,13.0,neutral or dissatisfied +80377,120155,Female,Loyal Customer,34,Business travel,Business,2378,4,5,5,5,4,4,4,2,4,4,4,4,2,4,0,36.0,neutral or dissatisfied +80378,3666,Female,Loyal Customer,45,Business travel,Business,431,2,2,2,2,2,5,4,4,4,4,4,4,4,3,49,64.0,satisfied +80379,118532,Female,Loyal Customer,32,Business travel,Business,621,3,1,3,3,3,3,3,3,3,5,2,1,2,3,40,30.0,neutral or dissatisfied +80380,57105,Female,Loyal Customer,41,Business travel,Business,1222,4,4,4,4,3,5,5,3,3,2,3,3,3,5,11,0.0,satisfied +80381,34720,Female,disloyal Customer,20,Business travel,Eco,264,3,0,3,3,5,3,5,5,5,1,5,3,1,5,0,0.0,neutral or dissatisfied +80382,100672,Female,Loyal Customer,63,Business travel,Eco,628,2,2,4,2,4,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +80383,113064,Female,Loyal Customer,39,Business travel,Business,2083,2,2,2,2,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +80384,126820,Male,Loyal Customer,61,Business travel,Business,2077,1,5,5,5,2,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +80385,61479,Male,Loyal Customer,37,Business travel,Business,2288,2,2,3,2,5,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +80386,26712,Female,Loyal Customer,8,Personal Travel,Eco,581,2,5,3,4,4,3,4,4,5,5,5,5,5,4,0,10.0,neutral or dissatisfied +80387,68947,Male,Loyal Customer,36,Personal Travel,Eco,646,3,3,3,2,4,3,3,4,5,3,3,3,5,4,0,0.0,neutral or dissatisfied +80388,121676,Female,Loyal Customer,44,Personal Travel,Eco,328,2,0,2,3,2,4,5,2,2,2,2,4,2,4,3,0.0,neutral or dissatisfied +80389,12783,Female,Loyal Customer,68,Personal Travel,Business,641,2,4,2,4,3,4,4,3,3,2,3,3,3,4,24,25.0,neutral or dissatisfied +80390,158,Male,disloyal Customer,22,Business travel,Eco,227,1,4,1,3,2,1,2,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +80391,3325,Female,Loyal Customer,55,Business travel,Business,240,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,18.0,satisfied +80392,19408,Female,Loyal Customer,60,Personal Travel,Business,645,2,5,2,4,3,5,5,4,4,2,5,5,4,4,100,87.0,neutral or dissatisfied +80393,18852,Male,disloyal Customer,21,Business travel,Eco,448,1,4,1,3,2,1,2,2,3,2,4,3,3,2,0,2.0,neutral or dissatisfied +80394,6154,Male,Loyal Customer,68,Business travel,Business,475,3,2,2,2,5,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +80395,94343,Male,disloyal Customer,20,Business travel,Business,277,5,0,5,1,1,5,1,1,3,5,5,3,5,1,7,1.0,satisfied +80396,16087,Male,Loyal Customer,35,Business travel,Eco,349,5,1,1,1,5,5,5,5,4,2,2,3,1,5,0,0.0,satisfied +80397,71591,Male,disloyal Customer,27,Business travel,Eco,1197,1,1,1,3,2,1,2,2,4,5,2,3,3,2,73,62.0,neutral or dissatisfied +80398,105468,Male,disloyal Customer,34,Business travel,Business,495,3,3,3,1,1,3,1,1,3,2,4,5,5,1,20,15.0,neutral or dissatisfied +80399,1594,Female,Loyal Customer,49,Personal Travel,Eco,237,4,3,4,3,3,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +80400,45255,Male,Loyal Customer,57,Business travel,Business,2764,5,5,5,5,5,4,5,4,4,4,4,5,4,5,20,27.0,satisfied +80401,62731,Male,Loyal Customer,51,Business travel,Business,2486,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +80402,9445,Female,Loyal Customer,33,Business travel,Business,288,1,5,5,5,1,4,3,1,1,1,1,4,1,4,6,20.0,neutral or dissatisfied +80403,25994,Male,Loyal Customer,58,Personal Travel,Eco,577,3,5,3,5,1,3,5,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +80404,128974,Male,Loyal Customer,13,Personal Travel,Eco,414,3,3,3,4,5,3,3,5,1,1,4,2,4,5,11,7.0,neutral or dissatisfied +80405,97831,Male,Loyal Customer,16,Business travel,Business,2572,2,2,3,2,2,2,2,2,1,2,4,1,4,2,2,8.0,neutral or dissatisfied +80406,562,Female,disloyal Customer,59,Business travel,Business,247,4,4,4,2,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +80407,40950,Male,Loyal Customer,66,Personal Travel,Eco Plus,574,4,1,4,3,3,4,3,3,3,1,4,3,3,3,0,8.0,neutral or dissatisfied +80408,14257,Male,disloyal Customer,33,Business travel,Business,429,2,2,2,4,5,2,5,5,5,3,4,4,5,5,0,6.0,neutral or dissatisfied +80409,14192,Male,Loyal Customer,55,Business travel,Eco,526,2,1,1,1,2,2,2,2,5,3,2,3,4,2,0,4.0,satisfied +80410,87893,Female,disloyal Customer,54,Business travel,Business,250,5,5,5,4,4,5,4,4,4,2,5,4,5,4,0,4.0,satisfied +80411,9490,Male,Loyal Customer,39,Business travel,Business,3977,2,2,2,2,2,5,4,5,5,5,5,3,5,4,25,23.0,satisfied +80412,55641,Male,Loyal Customer,42,Personal Travel,Eco,563,2,5,3,3,4,3,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +80413,87040,Female,Loyal Customer,45,Business travel,Business,594,4,4,4,4,4,5,5,4,4,4,4,5,4,5,4,0.0,satisfied +80414,21001,Female,Loyal Customer,66,Business travel,Eco Plus,689,3,5,5,5,4,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +80415,85851,Male,Loyal Customer,52,Business travel,Eco Plus,666,2,3,3,3,2,2,2,2,1,1,3,1,3,2,13,0.0,neutral or dissatisfied +80416,91881,Female,Loyal Customer,36,Business travel,Business,2586,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +80417,124130,Female,Loyal Customer,55,Personal Travel,Eco,529,3,1,3,2,1,2,2,2,2,3,5,2,2,4,0,10.0,neutral or dissatisfied +80418,129035,Male,Loyal Customer,34,Business travel,Business,1846,3,2,2,2,1,3,4,3,3,3,3,1,3,1,49,31.0,neutral or dissatisfied +80419,105600,Female,Loyal Customer,53,Business travel,Business,919,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +80420,108148,Female,disloyal Customer,24,Business travel,Business,449,0,0,0,1,2,0,2,2,2,2,5,2,2,2,11,0.0,satisfied +80421,79656,Male,Loyal Customer,16,Business travel,Business,762,1,1,1,1,1,1,1,1,3,5,4,3,3,1,0,11.0,neutral or dissatisfied +80422,21603,Female,Loyal Customer,22,Business travel,Business,2451,5,5,5,5,4,4,4,4,3,2,5,5,1,4,0,0.0,satisfied +80423,78979,Male,Loyal Customer,42,Business travel,Business,356,4,3,4,4,3,5,4,4,4,4,4,4,4,5,0,5.0,satisfied +80424,61618,Female,Loyal Customer,39,Business travel,Business,1346,2,2,2,2,4,4,5,2,2,2,2,3,2,4,68,56.0,satisfied +80425,5216,Male,Loyal Customer,50,Business travel,Business,383,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +80426,34286,Female,Loyal Customer,33,Business travel,Business,3273,0,0,0,1,2,4,2,3,3,3,3,1,3,4,0,0.0,satisfied +80427,57048,Female,Loyal Customer,29,Business travel,Business,2133,2,2,2,2,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +80428,103604,Female,Loyal Customer,39,Business travel,Business,2753,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +80429,56891,Male,Loyal Customer,41,Business travel,Business,2565,3,3,1,3,4,4,4,5,3,5,4,4,3,4,0,0.0,satisfied +80430,65474,Male,Loyal Customer,59,Business travel,Business,2818,1,5,5,5,1,4,4,1,1,2,1,4,1,4,104,106.0,neutral or dissatisfied +80431,40583,Female,disloyal Customer,40,Business travel,Business,391,3,2,2,3,2,2,2,2,3,4,4,2,3,2,5,0.0,neutral or dissatisfied +80432,24358,Male,Loyal Customer,69,Personal Travel,Eco Plus,634,3,2,3,3,2,3,2,2,3,3,2,1,2,2,0,2.0,neutral or dissatisfied +80433,46370,Female,Loyal Customer,44,Business travel,Business,2164,2,2,2,2,1,3,1,4,4,4,4,2,4,1,14,0.0,satisfied +80434,60815,Female,Loyal Customer,37,Business travel,Eco,455,1,4,4,4,1,1,1,1,1,4,3,4,4,1,4,12.0,neutral or dissatisfied +80435,52671,Female,Loyal Customer,54,Personal Travel,Eco,160,4,2,0,3,5,3,3,2,2,0,1,2,2,4,0,0.0,satisfied +80436,61445,Male,Loyal Customer,39,Business travel,Business,2288,5,5,5,5,5,5,5,5,5,5,5,5,5,5,124,120.0,satisfied +80437,115378,Female,disloyal Customer,26,Business travel,Business,372,0,0,0,4,5,0,2,5,5,5,5,4,4,5,7,0.0,satisfied +80438,76195,Female,Loyal Customer,36,Business travel,Business,2422,2,1,1,1,2,2,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +80439,118873,Female,Loyal Customer,51,Business travel,Business,1136,2,2,2,2,3,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +80440,19980,Male,Loyal Customer,56,Personal Travel,Business,589,1,1,0,2,5,1,2,4,4,0,4,4,4,4,17,4.0,neutral or dissatisfied +80441,77672,Male,Loyal Customer,55,Business travel,Eco,696,3,1,4,4,3,3,3,3,1,1,3,4,3,3,22,5.0,neutral or dissatisfied +80442,90919,Female,disloyal Customer,26,Business travel,Eco,404,1,5,2,4,3,2,3,3,4,2,2,1,2,3,0,0.0,neutral or dissatisfied +80443,87238,Male,disloyal Customer,26,Business travel,Business,577,4,4,4,3,3,4,3,3,5,4,4,3,4,3,4,0.0,satisfied +80444,90061,Female,Loyal Customer,72,Business travel,Business,1084,4,3,3,3,2,2,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +80445,64269,Male,disloyal Customer,29,Business travel,Business,1212,2,2,2,4,5,2,5,5,3,4,3,1,4,5,4,8.0,neutral or dissatisfied +80446,28179,Female,Loyal Customer,44,Personal Travel,Eco,834,1,4,1,3,5,5,4,4,4,1,4,3,4,3,0,17.0,neutral or dissatisfied +80447,3855,Female,Loyal Customer,18,Personal Travel,Eco,650,3,3,3,2,5,3,5,5,5,5,3,4,1,5,0,0.0,neutral or dissatisfied +80448,96455,Female,Loyal Customer,47,Business travel,Business,436,2,2,2,2,2,4,4,3,3,3,3,3,3,3,0,5.0,satisfied +80449,86492,Male,Loyal Customer,53,Personal Travel,Eco,712,3,3,3,4,5,3,5,5,5,1,5,2,4,5,0,0.0,neutral or dissatisfied +80450,4635,Female,Loyal Customer,52,Business travel,Business,3759,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +80451,40934,Female,Loyal Customer,36,Business travel,Eco Plus,599,4,1,1,1,4,4,4,4,3,3,5,1,4,4,16,3.0,satisfied +80452,70011,Female,Loyal Customer,31,Personal Travel,Eco Plus,236,2,5,2,2,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +80453,56971,Male,Loyal Customer,19,Personal Travel,Eco,2454,3,4,3,1,3,4,4,3,2,5,5,4,3,4,0,0.0,neutral or dissatisfied +80454,103804,Male,Loyal Customer,31,Business travel,Eco,1048,4,1,1,1,4,4,4,2,5,4,4,4,4,4,151,152.0,neutral or dissatisfied +80455,128379,Male,disloyal Customer,9,Business travel,Eco,621,1,3,1,2,3,1,3,3,3,2,2,2,2,3,0,2.0,neutral or dissatisfied +80456,120809,Female,Loyal Customer,53,Business travel,Business,666,1,1,1,1,4,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +80457,31832,Female,disloyal Customer,26,Business travel,Eco,2762,4,4,4,1,4,3,3,2,3,3,5,3,4,3,0,3.0,neutral or dissatisfied +80458,63709,Male,Loyal Customer,47,Business travel,Business,1660,1,1,2,1,5,3,4,4,4,5,4,4,4,3,9,0.0,satisfied +80459,22571,Female,Loyal Customer,59,Business travel,Eco,223,4,5,5,5,2,3,4,4,4,4,4,2,4,2,10,10.0,satisfied +80460,108268,Female,Loyal Customer,12,Personal Travel,Eco,895,3,5,3,3,2,3,2,2,3,2,4,5,4,2,2,0.0,neutral or dissatisfied +80461,60887,Female,Loyal Customer,8,Personal Travel,Eco,1062,4,5,4,4,5,4,5,5,4,5,5,3,5,5,4,0.0,satisfied +80462,17724,Male,disloyal Customer,34,Business travel,Eco,501,1,4,1,4,1,5,5,3,5,2,1,5,1,5,159,164.0,neutral or dissatisfied +80463,55146,Female,Loyal Customer,55,Personal Travel,Eco,1379,3,5,3,4,4,3,1,3,3,3,3,3,3,4,12,4.0,neutral or dissatisfied +80464,68567,Female,disloyal Customer,39,Business travel,Business,1616,2,2,2,3,4,2,4,4,4,4,4,5,4,4,11,0.0,neutral or dissatisfied +80465,75047,Female,Loyal Customer,57,Business travel,Business,1592,3,3,3,3,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +80466,117564,Female,disloyal Customer,20,Business travel,Business,872,5,5,5,4,3,5,2,3,5,3,4,3,4,3,0,0.0,satisfied +80467,23015,Male,Loyal Customer,32,Business travel,Eco Plus,817,5,4,3,4,5,4,5,5,2,5,4,1,4,5,16,4.0,neutral or dissatisfied +80468,71235,Female,Loyal Customer,38,Business travel,Business,2072,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +80469,4142,Female,disloyal Customer,27,Business travel,Business,544,5,5,5,3,3,5,3,3,4,3,4,5,4,3,0,0.0,satisfied +80470,69624,Male,Loyal Customer,36,Personal Travel,Eco Plus,2586,2,4,2,5,2,3,3,3,4,4,1,3,3,3,0,0.0,neutral or dissatisfied +80471,12744,Male,Loyal Customer,37,Personal Travel,Eco,689,2,5,3,2,2,3,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +80472,103288,Male,Loyal Customer,48,Business travel,Business,872,5,5,5,5,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +80473,76101,Female,Loyal Customer,9,Personal Travel,Eco,669,2,2,2,3,2,2,2,2,1,4,3,3,4,2,5,0.0,neutral or dissatisfied +80474,89683,Female,Loyal Customer,48,Business travel,Eco,669,4,3,3,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +80475,127159,Female,Loyal Customer,63,Personal Travel,Eco,325,3,4,3,3,1,5,2,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +80476,15383,Female,Loyal Customer,41,Business travel,Business,3787,4,4,2,4,2,1,5,5,5,5,5,1,5,4,0,0.0,satisfied +80477,127985,Female,disloyal Customer,27,Business travel,Eco,749,0,0,0,1,5,0,5,5,2,1,4,1,1,5,0,0.0,satisfied +80478,105195,Female,disloyal Customer,21,Business travel,Eco,281,1,2,1,4,5,1,5,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +80479,52620,Female,Loyal Customer,41,Business travel,Eco,119,5,1,1,1,4,5,4,4,4,3,2,4,1,4,0,0.0,satisfied +80480,59970,Male,disloyal Customer,23,Business travel,Eco,623,1,4,0,3,2,0,2,2,4,2,4,2,4,2,37,24.0,neutral or dissatisfied +80481,65659,Male,Loyal Customer,47,Business travel,Business,861,5,5,5,5,4,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +80482,60255,Male,Loyal Customer,27,Personal Travel,Eco,1546,3,3,3,3,2,3,2,2,3,4,2,1,4,2,0,7.0,neutral or dissatisfied +80483,106974,Female,Loyal Customer,41,Business travel,Business,937,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +80484,62438,Female,Loyal Customer,37,Business travel,Business,1943,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,7.0,satisfied +80485,127676,Female,Loyal Customer,34,Personal Travel,Eco,2153,2,4,2,2,3,2,5,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +80486,34436,Female,Loyal Customer,38,Business travel,Business,2987,2,5,5,5,2,2,2,1,4,3,4,2,4,2,220,211.0,neutral or dissatisfied +80487,15946,Female,Loyal Customer,13,Personal Travel,Eco,566,3,5,3,1,2,3,2,2,4,4,5,4,5,2,4,8.0,neutral or dissatisfied +80488,51685,Male,Loyal Customer,52,Business travel,Business,2374,3,3,3,3,5,1,5,4,4,4,4,1,4,1,0,0.0,satisfied +80489,4663,Female,Loyal Customer,29,Business travel,Business,2299,3,3,5,3,4,4,4,4,4,4,4,3,5,4,0,3.0,satisfied +80490,14433,Female,Loyal Customer,41,Business travel,Eco,674,5,4,4,4,5,5,5,5,3,4,1,1,5,5,0,0.0,satisfied +80491,82116,Male,Loyal Customer,66,Personal Travel,Eco,1276,1,4,1,1,1,1,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +80492,104302,Male,Loyal Customer,9,Personal Travel,Eco,382,3,5,3,1,3,3,3,3,3,2,4,5,4,3,18,40.0,neutral or dissatisfied +80493,1810,Female,disloyal Customer,22,Business travel,Eco,500,3,2,3,4,3,3,3,3,1,5,3,4,3,3,14,0.0,neutral or dissatisfied +80494,8501,Male,Loyal Customer,42,Business travel,Business,2643,2,3,2,2,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +80495,38410,Male,Loyal Customer,14,Personal Travel,Business,965,3,2,3,3,3,3,3,3,4,5,3,3,4,3,0,0.0,neutral or dissatisfied +80496,2242,Male,Loyal Customer,41,Business travel,Business,925,1,1,1,1,4,5,5,4,4,4,4,5,4,5,25,21.0,satisfied +80497,319,Female,Loyal Customer,60,Business travel,Business,821,2,1,3,1,1,3,4,2,2,2,2,1,2,3,2,0.0,neutral or dissatisfied +80498,42352,Female,Loyal Customer,66,Personal Travel,Eco,550,2,4,2,2,5,4,5,4,4,2,4,3,4,5,78,82.0,neutral or dissatisfied +80499,7842,Female,Loyal Customer,48,Business travel,Business,1005,1,1,1,1,5,5,4,4,4,4,4,3,4,3,21,14.0,satisfied +80500,104257,Female,Loyal Customer,60,Business travel,Business,1584,2,4,4,4,4,3,3,2,2,2,2,2,2,1,2,0.0,neutral or dissatisfied +80501,102485,Female,Loyal Customer,65,Personal Travel,Eco,397,2,4,2,1,5,4,4,2,2,2,2,5,2,2,3,0.0,neutral or dissatisfied +80502,113407,Female,Loyal Customer,49,Business travel,Business,258,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +80503,124678,Male,Loyal Customer,47,Business travel,Business,399,5,5,5,5,4,5,5,3,3,3,3,3,3,3,130,129.0,satisfied +80504,24032,Female,Loyal Customer,40,Business travel,Business,2624,4,4,4,4,5,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +80505,36595,Female,Loyal Customer,33,Business travel,Eco,1237,2,1,1,1,2,2,2,2,3,2,3,2,3,2,0,1.0,neutral or dissatisfied +80506,80140,Male,Loyal Customer,41,Business travel,Business,2586,1,1,1,1,5,5,5,3,3,3,4,5,4,5,0,0.0,satisfied +80507,108446,Female,Loyal Customer,21,Business travel,Business,1444,1,4,4,4,1,1,1,1,4,4,4,2,4,1,16,22.0,neutral or dissatisfied +80508,26537,Male,Loyal Customer,31,Personal Travel,Eco,990,3,4,3,1,3,3,3,3,3,3,4,3,5,3,27,16.0,neutral or dissatisfied +80509,81362,Male,Loyal Customer,41,Business travel,Eco Plus,899,5,4,4,4,5,5,5,5,5,1,3,3,3,5,0,0.0,satisfied +80510,32601,Female,disloyal Customer,39,Business travel,Business,216,4,4,4,3,2,4,2,2,5,2,2,1,2,2,0,0.0,neutral or dissatisfied +80511,19661,Male,Loyal Customer,36,Personal Travel,Eco,1236,2,5,2,3,3,2,1,3,5,3,3,3,5,3,0,22.0,neutral or dissatisfied +80512,115840,Male,Loyal Customer,72,Business travel,Business,2741,3,3,3,3,1,3,3,5,5,5,5,5,5,3,0,0.0,satisfied +80513,123210,Female,Loyal Customer,37,Personal Travel,Eco,631,2,4,2,1,5,2,5,5,3,4,5,5,4,5,2,0.0,neutral or dissatisfied +80514,126585,Female,Loyal Customer,26,Business travel,Business,1337,4,4,4,4,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +80515,96887,Male,Loyal Customer,25,Personal Travel,Eco,957,4,5,4,3,3,4,3,3,5,3,5,5,4,3,18,1.0,neutral or dissatisfied +80516,37463,Female,disloyal Customer,26,Business travel,Eco,944,2,1,1,3,5,1,5,5,3,1,4,1,3,5,81,64.0,neutral or dissatisfied +80517,43821,Male,disloyal Customer,37,Business travel,Eco,114,2,5,2,3,4,2,4,4,2,4,2,3,5,4,0,0.0,neutral or dissatisfied +80518,53622,Male,Loyal Customer,14,Business travel,Business,1874,1,1,1,1,5,5,5,5,3,4,5,3,5,5,0,3.0,satisfied +80519,75215,Male,Loyal Customer,31,Business travel,Eco,1652,4,5,5,5,4,4,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +80520,121734,Male,disloyal Customer,27,Business travel,Business,1075,4,4,4,5,4,4,4,4,5,4,3,5,2,4,28,28.0,satisfied +80521,7066,Female,Loyal Customer,39,Business travel,Business,2156,4,4,4,4,3,4,4,4,4,4,4,5,4,5,4,5.0,satisfied +80522,81913,Female,Loyal Customer,24,Personal Travel,Eco Plus,680,3,4,3,3,1,3,1,1,3,4,5,5,4,1,37,9.0,neutral or dissatisfied +80523,26127,Male,Loyal Customer,26,Business travel,Eco,515,4,1,1,1,4,4,5,4,1,3,4,4,4,4,22,24.0,satisfied +80524,24177,Male,Loyal Customer,44,Business travel,Business,2761,0,0,0,1,5,5,2,3,3,3,3,1,3,5,6,0.0,satisfied +80525,81589,Male,Loyal Customer,16,Personal Travel,Business,334,2,5,2,1,2,2,2,2,3,5,5,5,5,2,21,26.0,neutral or dissatisfied +80526,63318,Male,Loyal Customer,18,Business travel,Business,1875,1,1,1,1,4,5,4,4,5,5,4,5,4,4,0,0.0,satisfied +80527,93809,Male,Loyal Customer,40,Business travel,Business,391,3,3,3,3,5,4,4,4,4,5,4,3,4,4,9,2.0,satisfied +80528,60663,Female,Loyal Customer,17,Personal Travel,Eco,1620,4,5,4,2,3,4,3,3,5,2,5,3,5,3,25,23.0,neutral or dissatisfied +80529,49721,Male,Loyal Customer,34,Business travel,Business,89,5,5,4,5,5,3,2,4,4,4,3,3,4,1,0,0.0,satisfied +80530,42763,Male,disloyal Customer,28,Business travel,Eco,493,1,0,1,4,2,1,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +80531,66846,Male,Loyal Customer,64,Personal Travel,Eco,731,2,3,2,2,1,2,1,1,3,1,1,5,5,1,0,0.0,neutral or dissatisfied +80532,11218,Male,Loyal Customer,14,Personal Travel,Eco,247,2,5,2,3,3,2,5,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +80533,114040,Male,disloyal Customer,39,Business travel,Business,511,2,2,2,4,2,2,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +80534,80912,Female,disloyal Customer,27,Business travel,Business,341,4,4,4,2,2,4,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +80535,84751,Female,Loyal Customer,33,Business travel,Eco,516,1,3,3,3,1,1,1,1,4,4,3,4,3,1,0,0.0,neutral or dissatisfied +80536,32845,Male,Loyal Customer,57,Personal Travel,Eco,102,4,4,4,3,1,4,1,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +80537,128696,Female,Loyal Customer,57,Business travel,Business,1464,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +80538,6826,Male,Loyal Customer,60,Personal Travel,Eco,235,2,4,2,3,1,2,3,1,1,3,3,4,4,1,0,0.0,neutral or dissatisfied +80539,71914,Male,Loyal Customer,55,Personal Travel,Eco,1726,2,4,2,1,5,2,5,5,4,5,3,3,2,5,31,51.0,neutral or dissatisfied +80540,79456,Male,Loyal Customer,26,Business travel,Business,1717,5,5,5,5,5,5,5,5,3,3,4,5,5,5,0,0.0,satisfied +80541,123350,Female,Loyal Customer,57,Personal Travel,Business,644,4,4,4,4,4,5,5,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +80542,89523,Female,Loyal Customer,24,Personal Travel,Business,1005,1,5,1,3,1,1,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +80543,15985,Female,disloyal Customer,27,Business travel,Eco,853,2,2,2,4,2,2,2,2,5,1,2,4,3,2,54,39.0,neutral or dissatisfied +80544,116470,Female,Loyal Customer,14,Personal Travel,Eco,447,3,5,3,2,4,3,4,4,5,4,3,1,5,4,118,109.0,neutral or dissatisfied +80545,7958,Female,disloyal Customer,41,Business travel,Eco,594,2,3,2,3,3,2,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +80546,20351,Male,Loyal Customer,33,Business travel,Business,287,2,2,4,2,2,2,2,2,1,3,3,2,3,2,27,20.0,neutral or dissatisfied +80547,31524,Female,Loyal Customer,49,Business travel,Eco,453,2,4,4,4,3,4,4,2,2,2,2,4,2,4,30,30.0,neutral or dissatisfied +80548,112690,Male,Loyal Customer,55,Business travel,Business,1557,1,1,1,1,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +80549,39684,Female,Loyal Customer,38,Business travel,Eco,534,3,1,1,1,3,3,3,3,2,4,3,2,3,3,71,72.0,neutral or dissatisfied +80550,55484,Female,Loyal Customer,45,Business travel,Business,2434,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +80551,57773,Female,disloyal Customer,40,Business travel,Business,2704,2,2,2,4,2,4,4,1,3,2,3,4,1,4,0,50.0,neutral or dissatisfied +80552,107147,Male,Loyal Customer,50,Business travel,Business,3144,2,2,2,2,3,5,4,4,4,4,4,5,4,4,31,18.0,satisfied +80553,81838,Male,Loyal Customer,26,Personal Travel,Eco,1501,3,2,4,3,5,4,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +80554,29385,Male,Loyal Customer,27,Business travel,Eco,2384,3,3,3,3,3,3,3,4,5,2,2,3,1,3,0,2.0,neutral or dissatisfied +80555,19268,Female,Loyal Customer,55,Business travel,Business,1017,1,4,4,4,3,3,3,1,1,1,1,3,1,1,1,0.0,neutral or dissatisfied +80556,108807,Female,Loyal Customer,49,Personal Travel,Eco,581,2,4,2,4,4,5,5,4,4,2,4,5,4,5,68,56.0,neutral or dissatisfied +80557,63177,Female,Loyal Customer,58,Business travel,Business,3788,3,4,3,3,3,5,4,3,3,3,3,3,3,3,11,10.0,satisfied +80558,85181,Female,Loyal Customer,35,Business travel,Eco,813,2,5,5,5,2,3,2,2,3,3,3,1,3,2,19,31.0,neutral or dissatisfied +80559,117793,Male,Loyal Customer,38,Business travel,Business,328,0,0,0,3,4,5,5,2,2,2,2,5,2,4,6,0.0,satisfied +80560,78269,Male,Loyal Customer,64,Personal Travel,Eco,903,4,4,4,3,2,4,2,2,4,5,2,5,5,2,0,0.0,neutral or dissatisfied +80561,47183,Female,Loyal Customer,77,Business travel,Business,965,2,3,3,3,2,3,2,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +80562,51702,Male,Loyal Customer,56,Business travel,Eco,370,5,2,4,2,5,5,5,5,1,5,4,5,5,5,0,0.0,satisfied +80563,61184,Female,Loyal Customer,38,Business travel,Business,3302,2,1,1,1,1,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +80564,111434,Female,Loyal Customer,47,Business travel,Business,836,3,3,1,3,2,4,5,4,4,4,4,5,4,4,0,2.0,satisfied +80565,33637,Female,Loyal Customer,16,Personal Travel,Eco,399,2,4,2,5,2,2,2,2,3,4,4,3,5,2,26,43.0,neutral or dissatisfied +80566,6449,Female,disloyal Customer,22,Business travel,Eco,296,1,0,1,4,1,2,2,3,4,5,5,2,5,2,116,150.0,neutral or dissatisfied +80567,94200,Male,Loyal Customer,36,Business travel,Business,1516,5,5,5,5,3,4,4,5,5,5,5,3,5,5,38,15.0,satisfied +80568,67763,Female,Loyal Customer,50,Business travel,Eco,1126,2,2,2,2,1,3,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +80569,22820,Male,Loyal Customer,38,Business travel,Business,2782,1,4,4,4,5,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +80570,59314,Female,Loyal Customer,43,Business travel,Business,2504,3,3,3,3,2,5,4,5,5,5,5,5,5,5,4,0.0,satisfied +80571,8868,Female,disloyal Customer,23,Business travel,Eco,622,1,3,1,4,4,1,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +80572,32982,Female,Loyal Customer,68,Personal Travel,Eco,216,3,4,0,2,4,4,5,4,4,0,4,4,4,4,0,0.0,neutral or dissatisfied +80573,103010,Female,Loyal Customer,56,Business travel,Eco,546,2,2,2,2,4,4,3,2,2,2,2,2,2,2,12,11.0,neutral or dissatisfied +80574,124543,Female,Loyal Customer,15,Personal Travel,Eco,1276,2,5,2,1,5,2,5,5,4,2,4,5,5,5,104,96.0,neutral or dissatisfied +80575,2758,Female,Loyal Customer,30,Business travel,Eco Plus,772,2,1,1,1,2,2,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +80576,30025,Male,Loyal Customer,33,Business travel,Business,539,4,4,4,4,5,5,5,5,2,3,1,4,4,5,0,0.0,satisfied +80577,21459,Male,disloyal Customer,22,Business travel,Eco,331,2,4,2,3,2,2,3,2,1,1,3,3,3,2,10,0.0,neutral or dissatisfied +80578,59445,Male,Loyal Customer,53,Business travel,Business,3765,2,2,1,1,3,3,4,2,2,2,2,3,2,2,41,10.0,neutral or dissatisfied +80579,111102,Male,Loyal Customer,40,Business travel,Business,319,1,1,2,1,4,5,4,5,5,5,5,5,5,3,26,24.0,satisfied +80580,49697,Male,Loyal Customer,36,Business travel,Eco,373,5,2,2,2,5,5,5,5,4,2,1,5,2,5,0,0.0,satisfied +80581,62988,Female,Loyal Customer,34,Business travel,Business,2988,5,5,5,5,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +80582,64533,Male,Loyal Customer,55,Business travel,Business,247,0,0,0,2,4,5,4,4,4,2,2,4,4,5,0,0.0,satisfied +80583,18287,Female,disloyal Customer,48,Business travel,Eco,705,3,3,3,1,2,3,1,2,3,1,4,3,2,2,0,0.0,neutral or dissatisfied +80584,98608,Male,Loyal Customer,46,Business travel,Business,1867,2,2,2,2,5,5,4,5,5,5,5,4,5,4,1,11.0,satisfied +80585,99317,Male,Loyal Customer,33,Business travel,Business,337,1,1,1,1,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +80586,18783,Male,Loyal Customer,46,Business travel,Business,551,4,4,5,4,1,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +80587,75742,Male,Loyal Customer,57,Business travel,Business,868,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +80588,56672,Male,Loyal Customer,36,Personal Travel,Eco,1023,2,3,2,2,2,2,2,2,3,2,2,3,3,2,0,0.0,neutral or dissatisfied +80589,15971,Male,Loyal Customer,48,Personal Travel,Eco Plus,607,3,5,3,1,1,3,1,1,3,2,4,3,5,1,9,0.0,neutral or dissatisfied +80590,87472,Female,disloyal Customer,23,Business travel,Business,373,5,0,5,4,4,5,4,4,5,3,5,5,5,4,0,0.0,satisfied +80591,49956,Male,Loyal Customer,35,Business travel,Business,3835,4,3,4,4,2,2,5,4,4,4,4,5,4,1,39,46.0,satisfied +80592,60371,Male,Loyal Customer,39,Business travel,Business,1452,1,1,3,1,5,5,5,3,3,3,3,3,3,5,1,0.0,satisfied +80593,91452,Female,Loyal Customer,38,Business travel,Eco,859,1,1,1,1,1,1,1,1,3,1,4,2,4,1,0,0.0,neutral or dissatisfied +80594,11940,Female,disloyal Customer,34,Business travel,Eco,781,3,3,3,2,1,3,1,1,2,1,3,4,3,1,1,21.0,neutral or dissatisfied +80595,126710,Male,Loyal Customer,58,Business travel,Business,2521,3,3,3,3,5,4,4,5,5,5,5,4,5,3,6,23.0,satisfied +80596,46122,Male,Loyal Customer,30,Business travel,Eco,627,5,5,3,5,5,5,5,5,5,2,3,5,2,5,3,0.0,satisfied +80597,5382,Male,Loyal Customer,17,Personal Travel,Eco,733,5,4,5,4,4,5,4,4,4,2,1,1,2,4,0,0.0,satisfied +80598,9687,Male,Loyal Customer,36,Business travel,Business,2925,2,3,3,3,1,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +80599,78586,Female,Loyal Customer,54,Personal Travel,Eco,630,2,5,2,5,5,3,4,1,1,2,1,3,1,2,42,48.0,neutral or dissatisfied +80600,48691,Female,Loyal Customer,50,Business travel,Business,421,3,1,1,1,4,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +80601,43314,Male,Loyal Customer,40,Business travel,Business,387,1,2,3,3,5,4,3,1,1,2,1,4,1,4,0,3.0,neutral or dissatisfied +80602,106508,Male,disloyal Customer,40,Business travel,Business,271,3,3,3,1,1,3,1,1,4,3,5,3,5,1,3,9.0,neutral or dissatisfied +80603,119183,Male,Loyal Customer,53,Business travel,Business,3464,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +80604,106835,Male,disloyal Customer,20,Business travel,Eco,1297,4,4,4,3,5,4,5,5,4,4,5,4,4,5,42,53.0,satisfied +80605,82159,Male,Loyal Customer,19,Business travel,Business,1819,1,2,2,2,1,1,1,1,1,1,2,1,3,1,3,2.0,neutral or dissatisfied +80606,44915,Female,Loyal Customer,41,Business travel,Eco,466,4,4,4,4,4,4,4,4,5,2,5,1,2,4,0,15.0,satisfied +80607,77575,Female,Loyal Customer,47,Business travel,Business,874,1,2,2,2,5,4,3,1,1,1,1,4,1,2,0,11.0,neutral or dissatisfied +80608,68275,Female,Loyal Customer,80,Business travel,Eco Plus,432,2,1,1,1,5,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +80609,89359,Female,Loyal Customer,69,Personal Travel,Eco,1587,3,5,3,2,4,4,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +80610,41449,Female,Loyal Customer,45,Business travel,Business,1464,2,2,2,2,5,5,4,5,5,5,5,3,5,4,49,29.0,satisfied +80611,50345,Female,Loyal Customer,37,Business travel,Business,1683,2,2,2,2,4,4,3,2,2,3,2,3,2,1,24,10.0,neutral or dissatisfied +80612,60967,Female,disloyal Customer,38,Business travel,Eco,488,4,0,4,2,4,4,2,4,4,4,2,2,3,2,169,219.0,neutral or dissatisfied +80613,120428,Male,Loyal Customer,49,Business travel,Eco,366,3,4,2,4,3,3,3,3,4,4,4,4,4,3,0,28.0,neutral or dissatisfied +80614,75401,Female,Loyal Customer,28,Business travel,Business,2585,5,5,5,5,5,5,5,5,3,5,3,4,4,5,0,0.0,satisfied +80615,8049,Male,Loyal Customer,49,Business travel,Business,1990,5,1,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +80616,102895,Female,Loyal Customer,59,Business travel,Business,1037,3,3,3,3,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +80617,102261,Female,Loyal Customer,32,Business travel,Business,3875,1,3,3,3,2,1,1,4,4,3,2,1,2,1,171,176.0,neutral or dissatisfied +80618,95004,Male,Loyal Customer,49,Personal Travel,Eco,192,2,5,2,3,2,1,2,3,4,5,4,2,3,2,210,204.0,neutral or dissatisfied +80619,52692,Male,Loyal Customer,58,Business travel,Eco Plus,160,5,1,1,1,5,5,5,5,5,3,3,4,3,5,0,0.0,satisfied +80620,86357,Female,Loyal Customer,26,Business travel,Business,3071,3,3,3,3,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +80621,104033,Male,Loyal Customer,42,Business travel,Business,3685,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +80622,15158,Female,Loyal Customer,13,Personal Travel,Eco,912,3,5,3,1,5,3,2,5,4,3,5,3,5,5,9,9.0,neutral or dissatisfied +80623,52670,Male,Loyal Customer,48,Personal Travel,Eco,119,1,5,1,4,5,1,5,5,2,4,3,4,5,5,0,0.0,neutral or dissatisfied +80624,79744,Male,Loyal Customer,55,Business travel,Business,712,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +80625,97332,Female,Loyal Customer,42,Business travel,Business,843,3,3,3,3,3,4,4,5,5,5,5,4,5,3,30,22.0,satisfied +80626,114865,Female,Loyal Customer,32,Business travel,Business,3205,4,4,3,4,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +80627,38391,Female,Loyal Customer,38,Business travel,Business,1626,5,5,5,5,5,4,1,3,3,3,3,2,3,5,15,4.0,satisfied +80628,77766,Male,Loyal Customer,21,Personal Travel,Eco,731,4,1,3,4,3,3,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +80629,30760,Female,disloyal Customer,36,Business travel,Eco,683,1,1,1,3,4,1,5,4,5,3,1,5,3,4,8,1.0,neutral or dissatisfied +80630,45893,Male,disloyal Customer,37,Business travel,Eco,809,1,1,1,1,1,1,1,1,2,4,5,5,2,1,0,4.0,neutral or dissatisfied +80631,53608,Male,disloyal Customer,50,Business travel,Eco,769,1,1,1,1,5,1,5,5,5,4,3,3,3,5,43,44.0,neutral or dissatisfied +80632,3541,Male,Loyal Customer,52,Business travel,Business,3282,0,0,0,3,5,4,4,2,2,2,2,5,2,4,0,9.0,satisfied +80633,127840,Female,Loyal Customer,59,Business travel,Business,1262,5,5,5,5,3,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +80634,76715,Male,Loyal Customer,51,Business travel,Business,3182,5,1,5,5,3,5,5,5,5,4,5,3,5,4,5,22.0,satisfied +80635,58909,Male,disloyal Customer,41,Business travel,Eco,488,3,0,3,3,1,3,1,1,4,4,5,3,5,1,3,0.0,neutral or dissatisfied +80636,29819,Female,Loyal Customer,47,Business travel,Business,234,0,0,0,3,3,1,3,2,2,2,2,3,2,1,0,0.0,satisfied +80637,493,Male,Loyal Customer,59,Business travel,Business,134,0,4,0,3,2,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +80638,98687,Female,Loyal Customer,26,Personal Travel,Eco,861,2,4,2,5,5,2,5,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +80639,103932,Female,disloyal Customer,25,Business travel,Eco,533,4,3,4,3,4,4,4,4,3,5,3,3,3,4,43,88.0,neutral or dissatisfied +80640,81859,Female,disloyal Customer,54,Business travel,Business,1416,3,3,3,2,1,3,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +80641,5736,Female,Loyal Customer,42,Personal Travel,Eco Plus,234,1,1,1,3,2,4,4,3,3,1,3,1,3,2,0,12.0,neutral or dissatisfied +80642,110931,Female,Loyal Customer,61,Personal Travel,Eco,581,4,5,4,3,3,4,5,1,1,4,1,4,1,3,12,14.0,neutral or dissatisfied +80643,67526,Male,disloyal Customer,22,Business travel,Eco,1235,1,1,1,3,5,1,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +80644,80246,Male,Loyal Customer,59,Personal Travel,Eco,1269,1,4,1,3,5,1,1,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +80645,43877,Male,Loyal Customer,50,Business travel,Business,2993,0,3,0,4,1,2,3,4,4,4,4,1,4,3,0,0.0,satisfied +80646,56529,Male,Loyal Customer,39,Business travel,Business,937,4,4,4,4,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +80647,46258,Male,Loyal Customer,55,Personal Travel,Eco,679,2,4,1,1,5,1,5,5,5,5,5,3,5,5,6,11.0,neutral or dissatisfied +80648,34990,Male,Loyal Customer,57,Business travel,Business,3722,3,3,1,3,4,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +80649,119622,Male,Loyal Customer,71,Business travel,Eco,335,1,0,0,3,4,1,2,4,1,3,3,4,3,4,6,8.0,neutral or dissatisfied +80650,56642,Male,Loyal Customer,67,Business travel,Business,2191,5,1,3,1,2,3,3,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +80651,112499,Male,Loyal Customer,31,Personal Travel,Eco,862,3,4,3,2,2,3,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +80652,17365,Male,Loyal Customer,58,Personal Travel,Eco,563,4,5,4,1,1,4,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +80653,75657,Female,Loyal Customer,63,Personal Travel,Eco,304,3,4,3,3,2,5,5,4,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +80654,19606,Male,Loyal Customer,54,Business travel,Business,416,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +80655,23689,Female,Loyal Customer,51,Business travel,Eco,73,3,3,2,3,3,3,3,4,3,3,3,3,4,3,152,160.0,neutral or dissatisfied +80656,84206,Male,Loyal Customer,39,Business travel,Business,432,5,5,5,5,3,4,4,3,3,3,3,4,3,4,0,9.0,satisfied +80657,83250,Male,Loyal Customer,62,Business travel,Business,2079,4,4,4,4,3,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +80658,8058,Male,Loyal Customer,45,Business travel,Business,125,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,3.0,satisfied +80659,77459,Male,Loyal Customer,52,Business travel,Business,1897,3,1,3,1,2,3,3,3,3,3,3,1,3,4,21,11.0,neutral or dissatisfied +80660,63969,Male,Loyal Customer,52,Business travel,Business,1212,3,3,3,3,2,5,4,4,4,5,4,3,4,5,0,25.0,satisfied +80661,67753,Male,Loyal Customer,52,Business travel,Business,3845,2,2,2,2,4,3,3,2,2,3,2,2,2,3,0,5.0,neutral or dissatisfied +80662,95448,Male,Loyal Customer,43,Business travel,Eco Plus,239,1,2,5,2,1,1,1,1,3,4,4,3,3,1,0,0.0,neutral or dissatisfied +80663,101721,Male,Loyal Customer,9,Personal Travel,Eco,986,3,4,3,4,3,3,3,3,5,4,4,3,5,3,14,2.0,neutral or dissatisfied +80664,109667,Female,disloyal Customer,39,Business travel,Eco,429,2,3,2,3,2,2,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +80665,109214,Male,Loyal Customer,27,Business travel,Business,3396,4,3,3,3,4,4,4,4,3,3,4,4,4,4,43,33.0,neutral or dissatisfied +80666,87674,Male,Loyal Customer,38,Business travel,Business,606,3,5,5,5,4,2,3,3,3,3,3,2,3,4,14,26.0,neutral or dissatisfied +80667,40213,Male,Loyal Customer,25,Business travel,Eco,387,5,3,3,3,5,5,5,5,2,3,1,1,3,5,0,15.0,satisfied +80668,33627,Male,Loyal Customer,63,Personal Travel,Eco,399,2,4,2,2,5,2,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +80669,10177,Female,disloyal Customer,23,Business travel,Eco,309,2,4,2,3,3,2,5,3,5,5,5,3,4,3,63,75.0,neutral or dissatisfied +80670,36212,Male,disloyal Customer,38,Business travel,Eco,496,3,4,3,1,1,3,1,1,4,3,2,4,2,1,0,12.0,neutral or dissatisfied +80671,44495,Male,Loyal Customer,34,Business travel,Business,2817,5,5,5,5,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +80672,114458,Female,Loyal Customer,70,Business travel,Business,2792,3,5,5,5,2,4,3,3,3,3,3,3,3,2,6,0.0,neutral or dissatisfied +80673,60646,Female,Loyal Customer,32,Business travel,Eco,1620,3,5,5,5,3,3,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +80674,15779,Female,Loyal Customer,67,Business travel,Business,3319,2,4,4,4,2,2,2,1,3,3,4,2,3,2,186,199.0,neutral or dissatisfied +80675,94786,Male,Loyal Customer,22,Business travel,Eco,189,2,3,3,3,2,2,4,2,2,1,4,3,3,2,54,49.0,neutral or dissatisfied +80676,16765,Female,Loyal Customer,60,Business travel,Eco,569,5,1,4,4,2,4,1,5,5,5,5,4,5,5,21,23.0,satisfied +80677,56194,Male,Loyal Customer,58,Personal Travel,Eco,1400,3,1,3,4,2,3,2,2,4,2,4,1,3,2,0,9.0,neutral or dissatisfied +80678,48701,Female,Loyal Customer,33,Business travel,Business,2591,0,0,0,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +80679,35757,Female,Loyal Customer,47,Business travel,Business,1608,2,1,1,1,2,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +80680,219,Male,Loyal Customer,31,Personal Travel,Eco,290,4,5,5,3,2,5,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +80681,12848,Female,Loyal Customer,53,Personal Travel,Eco,817,4,3,3,2,1,5,4,4,4,3,5,1,4,1,2,0.0,neutral or dissatisfied +80682,105970,Female,Loyal Customer,48,Business travel,Eco,2329,1,4,4,4,1,1,1,4,4,3,4,1,1,1,9,7.0,neutral or dissatisfied +80683,76121,Female,Loyal Customer,47,Business travel,Business,3567,2,1,4,4,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +80684,3546,Female,Loyal Customer,55,Business travel,Business,3172,2,2,2,2,5,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +80685,39127,Male,disloyal Customer,27,Business travel,Business,228,5,5,5,4,4,5,5,4,5,2,5,5,2,4,0,2.0,satisfied +80686,53002,Male,disloyal Customer,22,Business travel,Eco,1172,3,3,3,2,4,3,4,4,3,4,5,4,5,4,122,98.0,neutral or dissatisfied +80687,76004,Male,Loyal Customer,48,Business travel,Business,237,2,2,2,2,4,5,4,4,4,4,4,4,4,3,2,0.0,satisfied +80688,4351,Female,Loyal Customer,36,Business travel,Business,3389,2,2,2,2,5,5,5,4,4,5,4,4,4,4,0,5.0,satisfied +80689,49678,Male,Loyal Customer,35,Business travel,Eco,86,4,2,4,2,4,4,4,4,4,3,1,4,4,4,0,0.0,satisfied +80690,19782,Male,Loyal Customer,26,Business travel,Business,760,4,4,4,4,5,5,5,5,4,4,1,1,2,5,8,29.0,satisfied +80691,28473,Female,disloyal Customer,28,Business travel,Eco,1160,3,3,3,3,3,3,3,3,1,2,2,2,4,3,0,0.0,neutral or dissatisfied +80692,44264,Female,Loyal Customer,42,Personal Travel,Eco,118,3,5,3,5,1,1,1,1,1,3,1,3,1,5,33,22.0,neutral or dissatisfied +80693,127916,Female,Loyal Customer,51,Personal Travel,Eco Plus,1671,4,1,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +80694,118517,Female,Loyal Customer,40,Business travel,Business,2946,2,2,2,2,4,5,4,4,4,4,4,5,4,4,9,3.0,satisfied +80695,101608,Female,Loyal Customer,51,Business travel,Business,1371,4,4,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +80696,15234,Female,disloyal Customer,39,Business travel,Business,416,2,2,2,2,2,2,5,2,5,2,2,2,4,2,0,0.0,satisfied +80697,23199,Female,Loyal Customer,11,Personal Travel,Eco Plus,223,2,0,2,2,2,2,3,2,3,2,5,3,4,2,45,36.0,neutral or dissatisfied +80698,41544,Female,disloyal Customer,25,Business travel,Eco,1428,1,1,1,3,4,1,4,4,4,5,3,4,4,4,0,25.0,neutral or dissatisfied +80699,3991,Male,Loyal Customer,33,Personal Travel,Business,479,2,2,2,3,1,2,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +80700,98235,Male,disloyal Customer,22,Business travel,Eco,1136,3,3,3,4,4,3,4,4,4,5,4,3,5,4,2,0.0,neutral or dissatisfied +80701,919,Male,disloyal Customer,25,Business travel,Business,89,1,3,1,3,2,1,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +80702,125513,Male,Loyal Customer,30,Business travel,Eco Plus,666,3,1,1,1,3,4,3,3,2,3,4,3,4,3,0,27.0,neutral or dissatisfied +80703,18674,Male,Loyal Customer,30,Personal Travel,Eco,201,3,1,3,4,2,3,2,2,3,1,4,1,3,2,27,25.0,neutral or dissatisfied +80704,65173,Female,Loyal Customer,65,Personal Travel,Eco,469,1,5,1,1,4,4,4,4,4,1,3,4,4,5,0,0.0,neutral or dissatisfied +80705,1211,Female,Loyal Customer,35,Personal Travel,Eco,134,4,0,0,3,2,0,2,2,3,2,3,5,5,2,0,0.0,neutral or dissatisfied +80706,69979,Male,Loyal Customer,48,Business travel,Business,236,0,0,0,5,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +80707,56741,Male,Loyal Customer,35,Personal Travel,Eco,937,2,5,2,4,2,2,2,2,3,5,5,1,2,2,7,18.0,neutral or dissatisfied +80708,78174,Male,disloyal Customer,48,Business travel,Business,259,3,3,3,3,2,3,2,2,3,2,5,3,4,2,57,49.0,neutral or dissatisfied +80709,28584,Male,Loyal Customer,43,Personal Travel,Eco,2603,3,2,3,3,2,3,2,2,2,4,4,2,4,2,11,0.0,neutral or dissatisfied +80710,26397,Female,Loyal Customer,17,Business travel,Business,3746,3,4,1,1,3,3,3,3,4,5,3,4,3,3,0,7.0,neutral or dissatisfied +80711,361,Male,Loyal Customer,40,Business travel,Business,229,5,5,5,5,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +80712,83795,Female,Loyal Customer,40,Business travel,Business,425,4,4,4,4,3,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +80713,96306,Male,Loyal Customer,35,Business travel,Business,2069,2,2,2,2,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +80714,44230,Female,Loyal Customer,27,Business travel,Business,359,5,5,5,5,4,5,4,4,1,1,2,5,4,4,0,1.0,satisfied +80715,3982,Female,Loyal Customer,23,Personal Travel,Eco,340,3,4,3,3,3,3,3,3,5,5,4,3,5,3,36,22.0,neutral or dissatisfied +80716,16648,Male,Loyal Customer,43,Business travel,Business,2962,2,3,3,3,2,2,2,2,2,2,2,1,2,1,96,121.0,neutral or dissatisfied +80717,120668,Female,Loyal Customer,65,Business travel,Eco,280,1,4,4,4,1,2,2,4,5,3,3,2,2,2,200,183.0,neutral or dissatisfied +80718,102095,Male,disloyal Customer,24,Business travel,Eco,236,2,0,2,1,4,2,4,4,3,4,4,3,5,4,10,46.0,neutral or dissatisfied +80719,84134,Female,Loyal Customer,33,Business travel,Business,3959,1,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +80720,96391,Male,disloyal Customer,25,Business travel,Eco,1246,2,2,2,4,2,2,2,2,1,1,4,2,4,2,16,0.0,neutral or dissatisfied +80721,48304,Male,Loyal Customer,12,Business travel,Eco,1499,2,1,1,1,2,2,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +80722,41803,Male,Loyal Customer,8,Business travel,Business,1816,2,2,2,2,2,2,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +80723,112927,Female,Loyal Customer,67,Personal Travel,Eco,1164,2,4,2,3,4,4,5,4,4,2,3,2,4,5,0,0.0,neutral or dissatisfied +80724,31884,Male,Loyal Customer,47,Business travel,Business,2762,5,5,5,5,2,4,5,4,4,4,4,5,4,1,0,0.0,satisfied +80725,94880,Male,disloyal Customer,26,Business travel,Eco,239,2,0,2,3,4,2,4,4,2,1,3,4,3,4,1,0.0,neutral or dissatisfied +80726,84855,Female,Loyal Customer,37,Business travel,Business,134,3,3,3,3,5,2,1,5,5,5,5,5,5,1,20,27.0,satisfied +80727,126794,Male,Loyal Customer,42,Business travel,Business,2125,2,2,5,2,2,3,5,4,4,4,4,5,4,5,7,0.0,satisfied +80728,112785,Female,Loyal Customer,38,Business travel,Business,590,5,5,5,5,2,5,5,5,5,5,5,3,5,5,31,31.0,satisfied +80729,68347,Male,Loyal Customer,58,Business travel,Eco,1598,3,1,2,2,3,3,3,3,2,1,3,2,4,3,1,16.0,neutral or dissatisfied +80730,13883,Male,Loyal Customer,37,Business travel,Business,2522,0,4,0,1,2,3,1,1,1,1,1,4,1,2,43,33.0,satisfied +80731,78001,Female,disloyal Customer,25,Business travel,Business,332,2,0,2,3,2,2,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +80732,31899,Female,Loyal Customer,17,Personal Travel,Eco Plus,2762,1,4,1,4,2,1,2,2,2,5,3,1,5,2,0,0.0,neutral or dissatisfied +80733,36360,Female,Loyal Customer,33,Business travel,Business,200,2,2,2,2,5,3,1,5,5,5,4,3,5,2,0,0.0,satisfied +80734,54833,Male,Loyal Customer,49,Business travel,Business,2669,4,4,1,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +80735,69102,Male,Loyal Customer,8,Business travel,Eco Plus,1391,3,2,2,2,3,3,2,3,4,3,4,1,3,3,10,8.0,neutral or dissatisfied +80736,119636,Male,Loyal Customer,67,Personal Travel,Eco,1727,4,5,3,3,4,3,4,4,1,5,4,3,5,4,0,0.0,satisfied +80737,87819,Male,Loyal Customer,45,Business travel,Business,2811,4,2,4,4,3,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +80738,65269,Female,disloyal Customer,24,Business travel,Eco Plus,247,5,0,5,3,2,5,2,2,4,5,1,5,3,2,0,0.0,satisfied +80739,52054,Female,Loyal Customer,23,Business travel,Business,2008,1,1,1,1,5,5,5,5,3,2,3,1,5,5,0,5.0,satisfied +80740,8121,Female,disloyal Customer,24,Business travel,Eco,402,0,3,0,3,1,3,1,1,3,4,5,4,4,1,0,0.0,satisfied +80741,85974,Female,Loyal Customer,54,Business travel,Business,1856,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +80742,129711,Female,Loyal Customer,18,Business travel,Business,3432,2,2,2,2,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +80743,43518,Male,disloyal Customer,44,Business travel,Eco Plus,752,1,1,1,2,3,1,3,3,2,2,1,2,3,3,0,0.0,neutral or dissatisfied +80744,110442,Female,Loyal Customer,41,Personal Travel,Eco,798,3,5,3,1,5,3,5,5,5,2,5,3,4,5,1,7.0,neutral or dissatisfied +80745,97523,Female,Loyal Customer,45,Business travel,Eco,265,3,4,4,4,4,2,2,2,2,3,2,1,2,3,0,3.0,neutral or dissatisfied +80746,31879,Female,Loyal Customer,47,Personal Travel,Eco,4983,1,3,1,4,1,3,3,3,3,3,5,3,2,3,0,0.0,neutral or dissatisfied +80747,72259,Male,disloyal Customer,32,Business travel,Eco,921,2,2,2,4,1,2,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +80748,88216,Female,Loyal Customer,18,Business travel,Business,2583,1,4,2,4,1,1,1,1,1,4,3,3,3,1,0,0.0,neutral or dissatisfied +80749,71874,Female,Loyal Customer,42,Personal Travel,Eco,1846,2,4,2,5,3,4,5,4,4,2,4,5,4,4,50,50.0,neutral or dissatisfied +80750,51303,Female,Loyal Customer,54,Business travel,Eco Plus,109,5,2,2,2,4,4,1,5,5,5,5,4,5,1,0,0.0,satisfied +80751,44145,Female,Loyal Customer,59,Personal Travel,Eco,74,3,4,3,1,5,3,1,3,3,3,4,5,3,4,0,0.0,neutral or dissatisfied +80752,98017,Female,Loyal Customer,54,Business travel,Business,2782,5,5,5,5,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +80753,98256,Female,Loyal Customer,17,Business travel,Business,2615,1,1,3,1,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +80754,8425,Male,Loyal Customer,60,Business travel,Business,737,1,1,1,1,4,4,5,4,4,4,4,5,4,3,5,0.0,satisfied +80755,72068,Male,Loyal Customer,53,Business travel,Business,2556,4,5,5,5,4,2,4,4,4,4,4,1,4,2,5,0.0,neutral or dissatisfied +80756,40077,Female,Loyal Customer,37,Business travel,Business,493,4,4,4,4,2,2,3,4,4,4,4,4,4,5,0,0.0,satisfied +80757,41908,Male,disloyal Customer,77,Business travel,Eco,129,1,0,1,5,1,1,1,1,4,3,5,1,3,1,21,15.0,neutral or dissatisfied +80758,76714,Male,disloyal Customer,39,Business travel,Business,547,2,2,2,4,4,2,4,4,5,5,5,3,5,4,0,14.0,neutral or dissatisfied +80759,11974,Male,Loyal Customer,57,Business travel,Business,643,4,4,4,4,2,5,5,5,5,5,5,5,5,4,59,43.0,satisfied +80760,119739,Female,Loyal Customer,25,Personal Travel,Eco,1303,3,5,3,1,2,3,2,2,3,2,3,5,5,2,0,0.0,neutral or dissatisfied +80761,73718,Male,disloyal Customer,36,Business travel,Eco,204,3,0,3,4,2,3,2,2,1,3,3,3,1,2,0,0.0,neutral or dissatisfied +80762,116301,Male,Loyal Customer,56,Personal Travel,Eco,404,2,2,2,4,1,2,3,1,1,5,3,4,3,1,6,5.0,neutral or dissatisfied +80763,74601,Male,disloyal Customer,29,Business travel,Eco,1313,2,2,2,4,3,2,3,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +80764,38845,Female,disloyal Customer,23,Business travel,Eco,387,3,2,3,3,5,3,5,5,1,5,3,4,4,5,0,0.0,neutral or dissatisfied +80765,54582,Female,Loyal Customer,56,Business travel,Business,3904,3,2,2,2,3,3,3,3,3,3,3,3,3,3,30,29.0,neutral or dissatisfied +80766,119218,Female,Loyal Customer,28,Personal Travel,Eco,331,4,2,1,2,2,1,2,2,3,3,3,2,3,2,15,38.0,neutral or dissatisfied +80767,95628,Male,Loyal Customer,48,Personal Travel,Eco,756,4,5,4,3,2,4,2,2,5,4,4,4,4,2,16,23.0,neutral or dissatisfied +80768,27459,Female,disloyal Customer,44,Business travel,Eco,679,2,2,2,4,3,2,4,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +80769,9397,Female,Loyal Customer,7,Personal Travel,Eco,372,0,1,0,3,3,0,3,3,2,2,4,3,4,3,0,0.0,satisfied +80770,10476,Male,Loyal Customer,43,Business travel,Business,3092,0,4,0,4,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +80771,55109,Female,Loyal Customer,19,Personal Travel,Eco,1303,3,2,3,4,4,3,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +80772,120695,Male,Loyal Customer,31,Personal Travel,Eco,280,2,4,3,4,1,3,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +80773,68250,Female,Loyal Customer,61,Personal Travel,Eco,631,4,5,4,5,3,3,3,4,4,4,4,3,4,4,0,9.0,satisfied +80774,2250,Female,Loyal Customer,19,Business travel,Business,925,2,2,2,2,4,4,4,4,3,2,4,3,5,4,0,17.0,satisfied +80775,5800,Female,Loyal Customer,47,Business travel,Business,1528,0,0,0,3,2,5,4,4,4,1,1,3,4,5,0,0.0,satisfied +80776,97082,Male,disloyal Customer,22,Business travel,Business,715,5,0,5,4,5,5,5,5,3,2,4,5,5,5,12,12.0,satisfied +80777,23776,Male,Loyal Customer,25,Business travel,Business,374,3,3,3,3,3,3,3,3,3,2,4,2,4,3,25,18.0,satisfied +80778,28733,Male,Loyal Customer,29,Business travel,Eco,2149,1,1,1,1,1,1,1,1,3,1,2,2,3,1,0,0.0,neutral or dissatisfied +80779,3709,Male,Loyal Customer,13,Personal Travel,Eco,431,2,5,2,5,1,2,1,1,5,2,5,4,4,1,2,1.0,neutral or dissatisfied +80780,90074,Male,Loyal Customer,58,Business travel,Business,2792,2,2,2,2,4,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +80781,48753,Male,disloyal Customer,49,Business travel,Business,266,3,2,2,4,2,3,2,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +80782,79383,Male,Loyal Customer,29,Business travel,Business,3273,1,1,1,1,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +80783,3663,Male,Loyal Customer,53,Business travel,Business,1600,4,4,4,4,2,5,5,4,4,4,4,3,4,4,96,79.0,satisfied +80784,99009,Female,Loyal Customer,8,Business travel,Eco Plus,569,3,5,5,5,3,3,2,3,4,5,4,2,3,3,52,48.0,neutral or dissatisfied +80785,28834,Female,disloyal Customer,24,Business travel,Business,679,4,4,4,3,1,4,1,1,4,3,4,4,5,1,0,0.0,satisfied +80786,36277,Male,Loyal Customer,45,Personal Travel,Eco,612,3,5,3,5,2,3,1,2,2,1,3,2,1,2,0,0.0,neutral or dissatisfied +80787,36703,Male,Loyal Customer,51,Personal Travel,Eco,1010,3,1,4,3,1,4,3,1,2,5,3,1,4,1,0,16.0,neutral or dissatisfied +80788,76768,Female,Loyal Customer,58,Business travel,Business,2999,3,3,3,3,5,5,4,5,5,5,5,5,5,5,30,18.0,satisfied +80789,77283,Male,Loyal Customer,53,Business travel,Business,1931,2,3,3,3,5,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +80790,90320,Female,Loyal Customer,40,Business travel,Business,3693,3,4,4,4,2,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +80791,97604,Female,Loyal Customer,63,Business travel,Eco,442,1,3,3,3,4,2,1,1,1,1,1,1,1,1,6,3.0,neutral or dissatisfied +80792,29402,Male,Loyal Customer,33,Personal Travel,Eco,2409,2,3,2,3,2,2,2,5,5,4,3,2,4,2,0,15.0,neutral or dissatisfied +80793,61780,Female,Loyal Customer,9,Personal Travel,Eco,1464,4,5,4,3,4,4,4,4,3,3,4,4,5,4,19,15.0,neutral or dissatisfied +80794,76220,Male,disloyal Customer,19,Business travel,Eco,1175,2,2,2,3,4,2,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +80795,120590,Female,Loyal Customer,57,Business travel,Business,1788,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +80796,109090,Male,Loyal Customer,26,Personal Travel,Eco,972,4,5,4,4,3,4,1,3,4,4,5,5,5,3,12,3.0,satisfied +80797,118064,Male,Loyal Customer,35,Personal Travel,Eco,1044,2,1,1,1,5,1,5,5,4,2,2,4,2,5,5,0.0,neutral or dissatisfied +80798,119998,Female,Loyal Customer,39,Business travel,Business,328,0,0,0,1,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +80799,74374,Male,Loyal Customer,38,Business travel,Business,3290,1,1,3,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +80800,98429,Male,Loyal Customer,42,Personal Travel,Eco,1910,2,4,2,3,5,2,1,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +80801,25310,Female,disloyal Customer,38,Business travel,Eco,432,1,2,1,3,2,1,2,2,3,3,3,3,4,2,1,16.0,neutral or dissatisfied +80802,103202,Male,Loyal Customer,49,Business travel,Business,1482,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +80803,3748,Female,Loyal Customer,57,Business travel,Business,431,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +80804,45400,Female,Loyal Customer,25,Personal Travel,Business,458,2,5,2,1,1,2,3,1,2,1,1,2,5,1,0,0.0,neutral or dissatisfied +80805,105511,Female,disloyal Customer,23,Business travel,Eco,611,4,5,4,1,3,4,3,3,4,2,4,5,5,3,31,30.0,satisfied +80806,125713,Male,Loyal Customer,26,Personal Travel,Eco,759,2,5,1,2,1,1,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +80807,10003,Male,Loyal Customer,26,Personal Travel,Eco,457,3,1,3,3,4,3,4,4,3,1,2,4,2,4,0,0.0,neutral or dissatisfied +80808,13552,Male,Loyal Customer,33,Business travel,Business,214,3,1,3,3,5,5,5,5,3,1,4,2,3,5,0,0.0,satisfied +80809,323,Male,Loyal Customer,59,Business travel,Business,3674,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +80810,124076,Female,Loyal Customer,16,Personal Travel,Eco,328,2,4,2,3,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +80811,31081,Female,Loyal Customer,74,Business travel,Eco Plus,241,4,3,3,3,1,2,4,4,4,4,4,5,4,3,23,20.0,satisfied +80812,68356,Male,Loyal Customer,27,Personal Travel,Eco,1598,2,4,3,1,2,3,4,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +80813,2727,Female,Loyal Customer,60,Business travel,Business,372,5,5,5,5,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +80814,56780,Female,Loyal Customer,41,Personal Travel,Eco Plus,937,2,5,2,5,2,5,5,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +80815,22900,Female,disloyal Customer,38,Business travel,Eco Plus,151,4,4,4,4,2,4,2,2,3,1,4,2,2,2,0,0.0,satisfied +80816,119168,Male,Loyal Customer,46,Business travel,Business,2306,0,0,0,3,3,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +80817,96241,Female,Loyal Customer,22,Personal Travel,Eco,546,2,1,2,4,4,2,5,4,1,3,4,1,3,4,2,1.0,neutral or dissatisfied +80818,72469,Male,Loyal Customer,60,Business travel,Eco,985,4,5,3,5,4,4,4,4,3,5,3,3,4,4,0,0.0,neutral or dissatisfied +80819,30478,Female,disloyal Customer,26,Business travel,Eco,1201,4,4,4,2,1,4,1,1,1,3,3,5,4,1,5,12.0,neutral or dissatisfied +80820,70083,Male,Loyal Customer,57,Business travel,Business,460,4,4,5,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +80821,61990,Female,Loyal Customer,39,Business travel,Business,2586,1,1,1,1,5,5,5,4,5,3,4,5,3,5,0,26.0,satisfied +80822,123850,Female,Loyal Customer,56,Business travel,Business,3687,2,2,1,2,2,5,4,4,4,5,4,5,4,5,1,2.0,satisfied +80823,110476,Male,Loyal Customer,33,Personal Travel,Eco,925,3,4,3,4,3,3,3,3,5,2,4,5,5,3,21,8.0,neutral or dissatisfied +80824,126969,Male,Loyal Customer,54,Business travel,Business,3730,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,4.0,satisfied +80825,55187,Male,Loyal Customer,54,Business travel,Eco Plus,1609,4,5,4,5,4,4,4,4,3,4,3,1,2,4,0,4.0,neutral or dissatisfied +80826,58124,Female,Loyal Customer,29,Personal Travel,Eco,612,3,5,3,1,1,3,1,1,4,4,5,5,5,1,7,13.0,neutral or dissatisfied +80827,92467,Male,Loyal Customer,47,Business travel,Eco,2139,2,2,2,2,2,2,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +80828,17355,Male,disloyal Customer,34,Business travel,Eco,563,1,4,1,3,1,1,1,1,3,4,4,2,3,1,108,98.0,neutral or dissatisfied +80829,28071,Female,Loyal Customer,36,Personal Travel,Eco,2603,2,5,2,3,2,1,1,2,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +80830,118466,Male,Loyal Customer,52,Business travel,Business,304,0,0,0,1,4,4,5,4,4,4,4,3,4,4,0,2.0,satisfied +80831,100266,Female,Loyal Customer,59,Business travel,Business,1073,2,2,3,2,2,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +80832,91789,Male,Loyal Customer,67,Personal Travel,Eco,626,3,5,3,2,3,3,4,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +80833,31183,Male,Loyal Customer,61,Personal Travel,Eco,1620,2,4,2,2,3,2,5,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +80834,57346,Female,Loyal Customer,40,Business travel,Eco,414,3,1,1,1,3,3,3,1,2,3,3,3,3,3,169,162.0,neutral or dissatisfied +80835,88387,Female,Loyal Customer,45,Business travel,Eco,442,3,4,4,4,2,2,2,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +80836,68233,Female,disloyal Customer,25,Business travel,Eco,631,4,2,4,4,2,4,2,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +80837,70199,Male,disloyal Customer,22,Business travel,Eco,403,3,5,3,1,2,3,3,2,1,1,5,1,1,2,0,0.0,neutral or dissatisfied +80838,37460,Female,Loyal Customer,21,Business travel,Eco,1032,4,5,5,5,4,4,5,4,2,2,1,1,1,4,93,100.0,satisfied +80839,65948,Female,Loyal Customer,27,Personal Travel,Business,1372,3,4,3,1,3,3,3,3,4,4,3,3,4,3,39,37.0,neutral or dissatisfied +80840,14136,Female,Loyal Customer,31,Business travel,Business,2664,1,2,2,2,1,1,1,1,1,4,3,1,3,1,12,4.0,neutral or dissatisfied +80841,98467,Male,Loyal Customer,38,Business travel,Business,3016,1,1,1,1,4,5,3,4,4,4,3,3,4,3,46,49.0,satisfied +80842,83757,Female,disloyal Customer,29,Business travel,Business,1183,4,4,4,3,1,4,1,1,4,5,4,5,4,1,0,0.0,satisfied +80843,23573,Female,Loyal Customer,48,Personal Travel,Eco,1015,3,4,3,1,3,4,5,3,3,3,3,5,3,4,1,0.0,neutral or dissatisfied +80844,98437,Female,Loyal Customer,20,Business travel,Business,2118,1,1,1,1,5,5,5,5,3,3,5,4,4,5,78,80.0,satisfied +80845,111522,Male,Loyal Customer,48,Business travel,Business,391,4,4,5,4,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +80846,81755,Male,Loyal Customer,45,Business travel,Business,1174,4,4,4,4,4,5,4,4,4,4,4,4,4,3,12,3.0,satisfied +80847,64859,Male,Loyal Customer,26,Business travel,Business,2794,5,5,5,5,4,4,5,4,5,2,5,5,4,4,0,0.0,satisfied +80848,57677,Male,Loyal Customer,52,Business travel,Business,1695,2,2,2,2,3,4,4,5,5,5,5,4,5,5,9,11.0,satisfied +80849,60737,Male,Loyal Customer,60,Business travel,Business,1725,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +80850,115996,Male,Loyal Customer,10,Personal Travel,Eco,373,2,5,2,4,4,2,4,4,5,5,3,2,3,4,76,82.0,neutral or dissatisfied +80851,67799,Male,Loyal Customer,49,Business travel,Business,1652,1,3,3,3,4,3,3,1,1,2,1,1,1,4,21,5.0,neutral or dissatisfied +80852,72375,Female,Loyal Customer,57,Business travel,Business,1017,3,3,3,3,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +80853,35442,Female,Loyal Customer,43,Personal Travel,Eco,1005,3,4,3,2,5,1,3,2,2,3,2,3,2,2,0,10.0,neutral or dissatisfied +80854,50900,Male,Loyal Customer,18,Personal Travel,Eco,308,5,5,5,2,1,5,1,1,4,4,4,4,5,1,0,0.0,satisfied +80855,26316,Male,Loyal Customer,55,Business travel,Eco Plus,1947,1,0,0,4,4,1,4,4,2,1,4,2,4,4,3,0.0,neutral or dissatisfied +80856,73646,Male,Loyal Customer,44,Business travel,Business,3957,0,5,0,4,2,4,4,4,4,4,2,4,4,4,0,0.0,satisfied +80857,44284,Male,disloyal Customer,23,Business travel,Eco,137,2,0,3,3,2,3,2,2,5,3,2,3,1,2,0,0.0,neutral or dissatisfied +80858,74160,Female,Loyal Customer,37,Personal Travel,Eco,641,4,5,4,3,4,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +80859,60942,Female,Loyal Customer,45,Business travel,Business,2803,2,2,2,2,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +80860,23977,Female,Loyal Customer,57,Personal Travel,Eco,596,1,2,1,3,5,4,4,5,5,1,5,2,5,2,0,0.0,neutral or dissatisfied +80861,17421,Female,disloyal Customer,27,Business travel,Eco,351,1,0,1,4,2,1,5,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +80862,46826,Male,Loyal Customer,28,Business travel,Business,844,5,5,5,5,5,4,5,5,1,2,4,3,2,5,14,23.0,satisfied +80863,42050,Male,Loyal Customer,51,Business travel,Business,106,1,1,1,1,2,3,2,5,5,5,4,2,5,4,0,1.0,satisfied +80864,2926,Male,Loyal Customer,39,Business travel,Business,2620,5,5,5,5,5,4,4,4,4,4,4,3,4,3,2,4.0,satisfied +80865,126425,Female,disloyal Customer,33,Business travel,Business,600,2,2,2,1,2,2,2,2,5,3,4,4,4,2,3,0.0,neutral or dissatisfied +80866,85428,Male,Loyal Customer,43,Business travel,Business,214,1,1,3,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +80867,92435,Male,Loyal Customer,49,Business travel,Business,1919,4,4,4,4,5,3,4,4,4,4,4,5,4,5,6,0.0,satisfied +80868,59042,Male,Loyal Customer,54,Business travel,Business,1744,5,5,3,5,4,3,5,4,4,4,4,5,4,5,1,3.0,satisfied +80869,52987,Male,Loyal Customer,27,Business travel,Eco,1208,4,4,3,4,4,5,4,4,5,2,4,2,3,4,18,0.0,satisfied +80870,28701,Female,Loyal Customer,54,Business travel,Eco,2172,4,4,4,4,1,4,2,4,4,4,4,4,4,3,0,0.0,satisfied +80871,10542,Male,disloyal Customer,58,Business travel,Business,429,2,2,2,1,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +80872,19863,Male,Loyal Customer,58,Personal Travel,Eco,585,1,4,1,3,2,1,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +80873,92438,Female,Loyal Customer,49,Business travel,Business,2139,4,4,4,4,5,3,4,5,5,5,5,4,5,4,4,4.0,satisfied +80874,41878,Female,Loyal Customer,22,Business travel,Business,760,2,2,2,2,2,2,2,2,4,4,5,3,2,2,0,6.0,satisfied +80875,25031,Male,Loyal Customer,26,Business travel,Business,2394,3,4,4,4,3,2,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +80876,9141,Male,Loyal Customer,28,Business travel,Business,3817,1,1,1,1,5,5,5,5,4,2,5,4,5,5,123,122.0,satisfied +80877,84487,Female,Loyal Customer,40,Business travel,Business,2994,2,3,3,3,3,4,3,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +80878,117253,Male,Loyal Customer,45,Personal Travel,Eco,621,3,3,3,1,3,3,3,3,1,4,3,1,5,3,27,23.0,neutral or dissatisfied +80879,120312,Female,Loyal Customer,38,Business travel,Business,268,3,4,4,4,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +80880,73153,Male,disloyal Customer,28,Business travel,Business,1501,4,4,4,4,2,4,2,2,4,3,5,5,4,2,4,0.0,neutral or dissatisfied +80881,77501,Female,Loyal Customer,24,Personal Travel,Eco,989,4,3,4,3,5,4,5,5,3,1,4,4,4,5,0,0.0,satisfied +80882,75816,Female,Loyal Customer,40,Personal Travel,Eco Plus,813,2,0,2,1,1,2,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +80883,125382,Male,Loyal Customer,59,Business travel,Business,1440,4,4,4,4,2,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +80884,96316,Male,Loyal Customer,7,Personal Travel,Eco Plus,687,0,5,0,2,1,0,1,1,4,5,5,5,4,1,0,0.0,satisfied +80885,32395,Female,Loyal Customer,32,Business travel,Eco,101,4,4,4,4,4,4,4,4,5,1,2,4,2,4,0,33.0,satisfied +80886,101130,Female,Loyal Customer,54,Business travel,Business,2897,2,2,2,2,3,4,4,4,4,4,4,3,4,4,36,12.0,satisfied +80887,112598,Male,Loyal Customer,27,Business travel,Business,639,3,5,5,5,3,3,3,3,4,5,4,2,3,3,74,81.0,neutral or dissatisfied +80888,110755,Male,Loyal Customer,51,Business travel,Business,1166,2,2,2,2,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +80889,40421,Female,Loyal Customer,34,Business travel,Business,188,3,3,3,3,2,5,1,5,5,5,4,3,5,3,0,0.0,satisfied +80890,61772,Female,Loyal Customer,32,Personal Travel,Eco,1303,3,4,3,1,4,3,4,4,4,4,3,4,5,4,21,10.0,neutral or dissatisfied +80891,45514,Female,Loyal Customer,47,Business travel,Business,689,4,4,4,4,2,3,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +80892,116679,Female,Loyal Customer,63,Business travel,Eco Plus,337,3,3,5,3,4,3,3,4,4,3,4,3,4,2,23,15.0,neutral or dissatisfied +80893,16403,Female,Loyal Customer,37,Personal Travel,Eco,463,2,5,2,1,5,2,5,5,4,4,4,4,5,5,107,124.0,neutral or dissatisfied +80894,90762,Male,Loyal Customer,76,Business travel,Eco,271,2,5,5,5,2,2,2,2,3,3,2,1,2,2,0,0.0,neutral or dissatisfied +80895,99299,Male,disloyal Customer,26,Business travel,Business,448,3,0,3,3,3,3,2,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +80896,92245,Male,disloyal Customer,25,Business travel,Eco,1052,3,3,3,3,1,3,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +80897,83593,Female,Loyal Customer,50,Business travel,Business,1629,1,1,1,1,4,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +80898,36342,Female,Loyal Customer,68,Personal Travel,Eco,395,4,5,4,1,3,4,4,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +80899,101437,Male,disloyal Customer,41,Business travel,Business,345,4,4,4,3,5,4,5,5,3,5,4,4,5,5,60,59.0,satisfied +80900,128251,Male,Loyal Customer,59,Business travel,Business,2092,2,2,4,2,5,5,4,5,5,5,5,5,5,5,16,19.0,satisfied +80901,82964,Male,disloyal Customer,27,Business travel,Business,1127,3,4,4,2,1,4,1,1,5,4,4,3,5,1,0,27.0,neutral or dissatisfied +80902,68583,Male,Loyal Customer,68,Personal Travel,Eco,1616,3,4,3,1,5,3,5,5,3,3,4,5,5,5,6,3.0,neutral or dissatisfied +80903,92738,Female,disloyal Customer,48,Business travel,Eco,1276,3,3,3,4,4,3,4,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +80904,30937,Female,Loyal Customer,51,Business travel,Business,2642,1,1,1,1,5,1,3,4,4,4,4,5,4,5,5,0.0,satisfied +80905,90071,Female,Loyal Customer,40,Business travel,Business,1145,4,4,4,4,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +80906,64598,Male,Loyal Customer,44,Business travel,Business,2682,5,5,5,5,5,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +80907,108773,Male,disloyal Customer,26,Business travel,Eco,581,4,4,4,3,3,4,3,3,1,1,3,4,4,3,83,71.0,neutral or dissatisfied +80908,53485,Female,disloyal Customer,23,Business travel,Business,2419,1,4,1,3,3,1,2,3,1,4,3,1,4,3,8,0.0,neutral or dissatisfied +80909,45373,Female,Loyal Customer,54,Personal Travel,Eco,222,1,1,1,2,2,1,2,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +80910,22710,Female,Loyal Customer,51,Business travel,Eco Plus,579,2,1,1,1,3,3,2,3,3,2,3,2,3,1,29,38.0,satisfied +80911,111136,Male,Loyal Customer,59,Business travel,Business,3363,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +80912,36472,Female,Loyal Customer,38,Business travel,Business,2656,2,2,2,2,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +80913,49184,Male,Loyal Customer,36,Business travel,Business,2658,1,1,1,1,2,3,4,4,4,4,4,3,4,4,7,23.0,satisfied +80914,37940,Male,Loyal Customer,20,Personal Travel,Eco,1065,3,4,3,1,3,3,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +80915,113713,Male,Loyal Customer,50,Personal Travel,Eco,397,2,5,4,2,2,4,2,2,3,5,4,3,4,2,2,0.0,neutral or dissatisfied +80916,100780,Male,Loyal Customer,44,Personal Travel,Eco,1411,3,1,3,3,4,3,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +80917,32469,Male,Loyal Customer,41,Business travel,Business,163,3,3,3,3,1,5,1,5,5,5,5,3,5,1,0,0.0,satisfied +80918,52930,Female,Loyal Customer,60,Personal Travel,Eco,679,4,5,4,1,5,4,4,1,1,4,2,4,1,5,20,81.0,neutral or dissatisfied +80919,106710,Female,Loyal Customer,54,Business travel,Eco Plus,516,3,1,1,1,4,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +80920,110676,Male,Loyal Customer,50,Business travel,Business,3073,4,4,4,4,5,4,3,5,5,5,5,1,5,2,23,14.0,satisfied +80921,97691,Female,Loyal Customer,55,Personal Travel,Eco Plus,491,4,4,4,1,4,4,2,4,4,4,4,4,4,5,0,0.0,satisfied +80922,26205,Female,disloyal Customer,36,Business travel,Eco,581,1,1,0,3,3,0,3,3,3,3,3,4,2,3,18,8.0,neutral or dissatisfied +80923,75281,Male,Loyal Customer,56,Personal Travel,Eco,1744,4,4,4,4,1,4,1,1,3,2,3,3,5,1,0,0.0,satisfied +80924,26328,Male,disloyal Customer,39,Business travel,Business,834,3,3,3,3,2,3,2,2,4,2,2,2,2,2,8,15.0,neutral or dissatisfied +80925,42373,Male,Loyal Customer,55,Personal Travel,Eco,834,2,5,2,4,5,2,5,5,4,4,4,5,4,5,30,15.0,neutral or dissatisfied +80926,93880,Female,Loyal Customer,52,Business travel,Business,588,3,4,4,4,3,4,3,3,3,3,3,4,3,1,58,54.0,neutral or dissatisfied +80927,101434,Female,Loyal Customer,59,Business travel,Business,2518,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +80928,95632,Male,Loyal Customer,67,Personal Travel,Eco,756,3,5,3,2,3,3,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +80929,12321,Female,Loyal Customer,54,Business travel,Eco,190,4,1,1,1,3,5,2,4,4,4,4,1,4,3,82,78.0,satisfied +80930,61942,Female,Loyal Customer,58,Business travel,Business,2052,2,4,4,4,4,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +80931,122503,Male,Loyal Customer,47,Business travel,Business,930,1,1,2,1,3,5,5,5,5,5,5,4,5,5,0,5.0,satisfied +80932,83410,Female,Loyal Customer,39,Business travel,Business,632,1,1,1,1,4,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +80933,51450,Female,Loyal Customer,52,Personal Travel,Eco Plus,373,4,1,4,3,4,3,4,2,2,4,2,2,2,2,0,0.0,neutral or dissatisfied +80934,126647,Female,Loyal Customer,29,Business travel,Business,3851,1,2,2,2,1,1,1,1,1,3,4,3,3,1,6,18.0,neutral or dissatisfied +80935,55443,Male,Loyal Customer,48,Personal Travel,Eco,2521,1,1,1,1,1,1,1,1,4,1,1,4,2,1,16,0.0,neutral or dissatisfied +80936,59144,Male,Loyal Customer,49,Personal Travel,Eco,1726,2,4,2,2,1,2,1,1,2,3,4,3,4,1,0,14.0,neutral or dissatisfied +80937,77535,Male,Loyal Customer,39,Business travel,Business,986,2,2,2,2,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +80938,14439,Female,Loyal Customer,57,Business travel,Eco,674,2,2,2,2,1,1,5,2,2,2,2,3,2,3,4,0.0,satisfied +80939,96785,Male,Loyal Customer,53,Business travel,Business,2204,3,2,3,3,2,5,5,5,5,5,5,3,5,3,18,14.0,satisfied +80940,107951,Male,Loyal Customer,68,Business travel,Eco Plus,611,2,2,5,5,2,2,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +80941,111859,Male,disloyal Customer,38,Business travel,Eco,628,3,2,3,4,2,3,2,2,2,4,3,2,4,2,13,26.0,neutral or dissatisfied +80942,47772,Male,Loyal Customer,39,Business travel,Business,315,5,5,5,5,4,4,5,4,4,4,4,3,4,3,9,15.0,satisfied +80943,33622,Female,disloyal Customer,26,Business travel,Eco,399,2,4,2,1,4,2,4,4,1,1,5,1,4,4,45,72.0,neutral or dissatisfied +80944,31318,Male,Loyal Customer,34,Personal Travel,Eco,680,4,5,4,1,4,4,4,4,4,4,4,4,5,4,33,34.0,neutral or dissatisfied +80945,75411,Male,disloyal Customer,22,Business travel,Eco,2342,3,3,3,3,3,3,3,3,3,2,2,4,3,3,17,6.0,neutral or dissatisfied +80946,125972,Female,Loyal Customer,40,Business travel,Business,2810,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,8.0,satisfied +80947,69625,Female,Loyal Customer,42,Personal Travel,Eco Plus,2475,4,1,4,3,4,2,2,1,2,3,2,2,4,2,0,0.0,neutral or dissatisfied +80948,22080,Female,Loyal Customer,36,Business travel,Business,782,4,4,4,4,2,4,5,4,4,5,4,1,4,4,0,0.0,satisfied +80949,8268,Female,Loyal Customer,37,Personal Travel,Eco,402,5,5,5,3,1,5,1,1,3,2,5,5,5,1,0,0.0,satisfied +80950,57495,Female,Loyal Customer,42,Business travel,Business,1525,4,4,4,4,4,5,5,4,4,4,4,5,4,5,3,0.0,satisfied +80951,92459,Male,Loyal Customer,41,Business travel,Business,2139,3,3,1,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +80952,99669,Female,Loyal Customer,45,Personal Travel,Eco,1050,2,5,2,5,2,4,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +80953,43764,Female,disloyal Customer,25,Business travel,Eco,481,2,4,3,3,5,3,3,5,1,4,3,1,3,5,0,1.0,neutral or dissatisfied +80954,30326,Male,Loyal Customer,57,Business travel,Business,391,2,5,3,5,2,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +80955,97804,Male,Loyal Customer,49,Business travel,Business,2398,3,3,3,3,2,4,4,5,5,5,5,5,5,4,21,17.0,satisfied +80956,92778,Male,disloyal Customer,30,Business travel,Eco,1671,2,2,2,4,3,2,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +80957,56765,Female,Loyal Customer,30,Business travel,Eco Plus,997,3,2,2,2,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +80958,71814,Female,Loyal Customer,30,Business travel,Eco,1829,3,3,3,3,3,3,3,3,1,2,4,3,4,3,16,11.0,neutral or dissatisfied +80959,9192,Female,disloyal Customer,26,Business travel,Business,363,4,0,4,1,4,4,4,4,3,5,5,5,4,4,22,72.0,satisfied +80960,128751,Female,Loyal Customer,70,Personal Travel,Eco Plus,2521,1,4,1,4,1,3,3,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +80961,35392,Female,disloyal Customer,20,Business travel,Eco,972,2,2,2,3,3,2,5,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +80962,11858,Male,Loyal Customer,40,Business travel,Business,2680,4,5,5,5,5,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +80963,86945,Female,Loyal Customer,26,Business travel,Business,907,1,1,2,1,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +80964,42084,Female,Loyal Customer,44,Personal Travel,Eco Plus,106,4,5,4,3,3,2,2,2,2,4,2,4,2,3,40,45.0,neutral or dissatisfied +80965,15643,Female,disloyal Customer,18,Business travel,Eco,228,4,4,4,4,1,4,1,1,1,1,3,3,3,1,0,0.0,neutral or dissatisfied +80966,61842,Male,Loyal Customer,27,Business travel,Business,1609,3,3,3,3,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +80967,26055,Male,Loyal Customer,11,Personal Travel,Eco,432,2,4,2,5,1,2,1,1,4,2,5,3,4,1,98,,neutral or dissatisfied +80968,37399,Male,Loyal Customer,40,Business travel,Eco,1056,5,1,1,1,5,5,5,5,1,5,2,3,2,5,0,0.0,satisfied +80969,73661,Male,disloyal Customer,44,Business travel,Business,204,5,5,5,1,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +80970,74451,Female,Loyal Customer,50,Business travel,Business,1464,3,3,4,3,3,4,5,5,5,4,5,3,5,4,10,6.0,satisfied +80971,10461,Male,Loyal Customer,55,Business travel,Business,308,4,4,4,4,5,5,5,4,4,4,4,3,4,4,14,4.0,satisfied +80972,110461,Male,Loyal Customer,57,Personal Travel,Eco,919,2,4,2,3,4,2,4,4,3,5,3,2,4,4,8,9.0,neutral or dissatisfied +80973,14956,Male,Loyal Customer,35,Personal Travel,Eco,554,1,5,1,5,1,1,1,1,5,2,4,3,4,1,1,25.0,neutral or dissatisfied +80974,39023,Female,Loyal Customer,34,Personal Travel,Eco,313,0,4,0,3,5,0,5,5,4,2,4,5,4,5,127,131.0,satisfied +80975,59114,Female,Loyal Customer,20,Personal Travel,Eco,1846,3,5,3,3,5,3,2,5,4,5,5,1,5,5,31,71.0,neutral or dissatisfied +80976,121362,Male,disloyal Customer,24,Business travel,Eco,1670,2,2,2,2,2,2,2,2,3,2,2,1,3,2,2,15.0,neutral or dissatisfied +80977,4341,Female,Loyal Customer,70,Personal Travel,Business,618,2,5,2,3,5,5,4,5,5,2,5,4,5,3,66,38.0,neutral or dissatisfied +80978,4265,Female,Loyal Customer,29,Business travel,Business,3802,2,2,2,2,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +80979,22528,Female,disloyal Customer,34,Business travel,Eco Plus,143,1,1,1,3,3,1,3,3,3,3,4,2,3,3,0,0.0,neutral or dissatisfied +80980,124078,Female,Loyal Customer,38,Business travel,Business,80,0,5,0,3,5,5,5,3,3,3,3,4,3,5,0,14.0,satisfied +80981,7273,Female,Loyal Customer,35,Personal Travel,Eco,139,3,3,0,3,1,0,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +80982,107090,Female,Loyal Customer,21,Business travel,Business,745,3,3,3,3,5,5,5,5,5,3,5,5,4,5,0,0.0,satisfied +80983,82148,Male,Loyal Customer,26,Business travel,Business,3125,1,1,1,1,5,5,5,5,5,5,5,3,4,5,1,0.0,satisfied +80984,20668,Female,Loyal Customer,16,Business travel,Business,3973,4,4,4,4,3,3,3,3,4,5,2,2,3,3,2,14.0,satisfied +80985,69154,Male,disloyal Customer,36,Business travel,Business,187,3,3,3,3,3,3,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +80986,78867,Male,disloyal Customer,39,Business travel,Eco,495,3,3,3,4,5,3,5,5,4,5,3,2,5,5,0,0.0,neutral or dissatisfied +80987,94758,Female,disloyal Customer,65,Business travel,Eco,239,2,1,2,3,1,2,1,1,2,4,3,3,2,1,0,0.0,neutral or dissatisfied +80988,65082,Female,Loyal Customer,53,Personal Travel,Eco,190,3,4,3,4,2,5,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +80989,36498,Female,Loyal Customer,47,Business travel,Eco,1185,4,3,3,3,1,2,4,4,4,4,4,5,4,5,0,19.0,satisfied +80990,20872,Male,Loyal Customer,46,Business travel,Eco Plus,534,4,3,3,3,4,4,4,4,1,4,3,5,4,4,9,5.0,satisfied +80991,1366,Male,Loyal Customer,56,Business travel,Business,309,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +80992,101637,Female,Loyal Customer,29,Personal Travel,Business,1749,3,5,3,2,3,3,3,3,5,4,1,4,2,3,0,0.0,neutral or dissatisfied +80993,124281,Male,Loyal Customer,43,Business travel,Business,1892,0,0,0,1,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +80994,14073,Male,Loyal Customer,34,Business travel,Business,1700,3,5,3,3,2,5,4,5,5,5,5,2,5,4,0,0.0,satisfied +80995,71260,Male,Loyal Customer,24,Personal Travel,Eco,733,0,4,0,2,2,0,2,2,4,5,5,5,2,2,0,0.0,satisfied +80996,19887,Male,disloyal Customer,39,Business travel,Eco,296,4,3,4,3,5,4,5,5,2,5,3,2,2,5,0,0.0,neutral or dissatisfied +80997,17166,Female,Loyal Customer,27,Business travel,Eco,643,4,5,4,5,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +80998,90115,Male,Loyal Customer,45,Business travel,Business,957,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +80999,65690,Female,disloyal Customer,49,Business travel,Business,926,5,5,5,1,2,5,2,2,5,2,5,4,5,2,0,0.0,satisfied +81000,129188,Female,disloyal Customer,25,Business travel,Business,863,4,0,4,4,2,4,2,2,4,2,3,3,5,2,0,0.0,satisfied +81001,18915,Female,Loyal Customer,10,Personal Travel,Eco,551,1,4,1,2,5,1,5,5,1,2,1,3,3,5,25,10.0,neutral or dissatisfied +81002,111844,Female,Loyal Customer,32,Business travel,Business,2196,3,3,3,3,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +81003,125866,Female,Loyal Customer,45,Business travel,Business,3324,5,1,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +81004,120782,Male,Loyal Customer,49,Personal Travel,Eco,678,4,5,4,4,3,4,3,3,5,5,4,4,4,3,0,0.0,satisfied +81005,4504,Female,disloyal Customer,37,Business travel,Eco,435,4,4,4,3,4,4,4,4,5,5,3,5,4,4,0,0.0,neutral or dissatisfied +81006,74130,Male,disloyal Customer,28,Business travel,Business,641,2,1,1,4,1,1,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +81007,90214,Female,Loyal Customer,35,Personal Travel,Eco,957,2,4,2,1,4,2,1,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +81008,85804,Male,Loyal Customer,43,Business travel,Eco,266,4,5,5,5,4,4,4,4,5,2,1,3,1,4,0,0.0,satisfied +81009,67276,Female,Loyal Customer,34,Personal Travel,Eco,929,1,1,1,4,5,1,3,5,2,1,4,3,3,5,0,0.0,neutral or dissatisfied +81010,60685,Female,Loyal Customer,37,Personal Travel,Business,1605,1,5,1,1,4,3,5,1,1,1,1,3,1,3,55,27.0,neutral or dissatisfied +81011,86438,Male,Loyal Customer,39,Business travel,Business,760,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +81012,63394,Male,Loyal Customer,15,Personal Travel,Eco,337,3,3,3,4,5,3,2,5,4,1,1,2,5,5,2,14.0,neutral or dissatisfied +81013,89021,Male,Loyal Customer,59,Business travel,Business,3711,4,4,4,4,3,4,4,5,5,5,5,3,5,4,86,79.0,satisfied +81014,30412,Female,Loyal Customer,46,Business travel,Eco Plus,641,5,5,5,5,3,1,3,5,5,5,5,5,5,4,1,0.0,satisfied +81015,50695,Male,Loyal Customer,64,Personal Travel,Eco,89,2,4,0,2,4,0,2,4,5,3,5,3,2,4,59,59.0,neutral or dissatisfied +81016,46539,Male,disloyal Customer,55,Business travel,Eco,125,1,0,1,1,4,1,1,4,2,3,1,1,3,4,0,5.0,neutral or dissatisfied +81017,96324,Male,disloyal Customer,24,Business travel,Eco,359,4,5,3,2,2,3,4,2,4,2,5,5,5,2,9,0.0,satisfied +81018,33927,Female,Loyal Customer,54,Personal Travel,Eco,818,5,3,5,2,1,5,1,3,3,3,3,2,3,5,0,0.0,satisfied +81019,42665,Male,disloyal Customer,23,Business travel,Eco,627,3,3,3,5,1,3,1,1,2,2,4,4,3,1,58,57.0,neutral or dissatisfied +81020,55222,Male,Loyal Customer,39,Business travel,Business,3473,5,5,4,5,3,4,5,5,5,5,5,5,5,4,3,5.0,satisfied +81021,108659,Male,Loyal Customer,27,Personal Travel,Eco,1747,3,0,3,5,2,3,2,2,4,3,4,3,4,2,21,0.0,neutral or dissatisfied +81022,110922,Male,Loyal Customer,29,Personal Travel,Eco,406,2,3,2,2,5,2,5,5,1,3,3,1,5,5,15,22.0,neutral or dissatisfied +81023,45349,Female,Loyal Customer,55,Personal Travel,Eco,188,3,5,3,2,3,5,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +81024,123335,Female,Loyal Customer,40,Personal Travel,Eco Plus,468,1,5,1,5,2,1,2,2,4,2,5,3,4,2,38,29.0,neutral or dissatisfied +81025,7193,Female,Loyal Customer,48,Business travel,Business,139,2,4,5,4,3,3,3,3,3,3,2,4,3,3,0,24.0,neutral or dissatisfied +81026,128205,Female,Loyal Customer,41,Business travel,Business,2436,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +81027,51137,Female,Loyal Customer,35,Personal Travel,Eco,363,4,5,4,5,1,4,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +81028,86019,Male,disloyal Customer,42,Business travel,Eco,447,2,4,2,3,2,2,2,4,3,3,3,2,1,2,145,129.0,neutral or dissatisfied +81029,25253,Male,Loyal Customer,45,Business travel,Business,1529,1,1,1,1,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +81030,43632,Male,Loyal Customer,16,Personal Travel,Eco,119,4,2,4,3,2,4,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +81031,14936,Female,disloyal Customer,23,Business travel,Eco,528,3,0,3,4,4,3,4,4,4,1,4,5,1,4,22,32.0,neutral or dissatisfied +81032,17426,Male,disloyal Customer,36,Business travel,Business,351,4,4,4,3,5,4,5,5,4,2,4,1,4,5,0,0.0,neutral or dissatisfied +81033,17714,Male,Loyal Customer,57,Business travel,Business,2497,1,1,1,1,5,5,4,5,5,5,5,3,5,5,6,0.0,satisfied +81034,1627,Female,Loyal Customer,57,Business travel,Business,999,3,2,4,2,5,3,3,3,3,3,3,4,3,1,0,9.0,neutral or dissatisfied +81035,99690,Male,disloyal Customer,27,Business travel,Eco,442,1,1,1,1,1,1,1,1,4,4,2,3,2,1,18,22.0,neutral or dissatisfied +81036,34041,Female,Loyal Customer,49,Business travel,Business,1608,3,3,4,3,4,4,5,4,4,3,4,2,4,5,0,0.0,satisfied +81037,74975,Female,Loyal Customer,31,Personal Travel,Eco,2475,1,2,1,4,2,1,2,2,3,2,3,2,4,2,6,90.0,neutral or dissatisfied +81038,29044,Female,Loyal Customer,30,Personal Travel,Eco,978,4,2,4,3,4,4,2,4,3,4,4,1,3,4,0,0.0,neutral or dissatisfied +81039,20441,Male,disloyal Customer,21,Business travel,Eco,84,5,0,5,2,5,5,5,1,5,4,1,5,5,5,294,320.0,satisfied +81040,98768,Male,Loyal Customer,52,Personal Travel,Eco,1814,2,5,2,3,2,2,2,2,5,5,5,4,5,2,5,7.0,neutral or dissatisfied +81041,38556,Male,Loyal Customer,14,Personal Travel,Eco,2475,4,2,4,4,5,4,5,5,2,2,4,3,4,5,0,0.0,neutral or dissatisfied +81042,6316,Male,disloyal Customer,24,Business travel,Eco,296,3,0,4,3,5,4,5,5,3,3,5,4,4,5,56,45.0,neutral or dissatisfied +81043,41413,Male,Loyal Customer,19,Personal Travel,Eco,794,4,5,4,2,4,4,4,4,3,4,4,4,5,4,0,20.0,neutral or dissatisfied +81044,36877,Female,Loyal Customer,48,Business travel,Business,3013,5,5,3,5,2,1,4,5,5,5,5,1,5,3,0,0.0,satisfied +81045,21877,Male,Loyal Customer,58,Business travel,Eco,448,3,4,4,4,3,3,3,3,4,4,3,3,2,3,0,0.0,satisfied +81046,89834,Female,Loyal Customer,68,Personal Travel,Eco Plus,950,4,1,4,1,1,1,2,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +81047,53019,Female,Loyal Customer,45,Business travel,Business,1835,2,4,4,4,4,4,3,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +81048,80907,Male,Loyal Customer,42,Business travel,Business,341,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +81049,2554,Female,disloyal Customer,57,Business travel,Business,280,2,2,2,2,1,2,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +81050,79675,Male,Loyal Customer,50,Personal Travel,Eco,712,0,5,0,3,1,0,1,1,5,4,4,3,5,1,0,0.0,satisfied +81051,106590,Female,disloyal Customer,33,Business travel,Business,333,3,3,3,4,5,3,4,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +81052,56586,Female,disloyal Customer,28,Business travel,Business,1068,4,4,4,2,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +81053,19455,Female,Loyal Customer,69,Personal Travel,Eco,363,2,5,2,2,3,4,5,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +81054,91002,Male,Loyal Customer,9,Personal Travel,Eco,646,3,5,3,2,1,3,1,1,5,3,2,1,3,1,0,0.0,neutral or dissatisfied +81055,34101,Female,Loyal Customer,15,Personal Travel,Business,1046,2,4,2,1,4,2,4,4,5,2,4,4,4,4,0,8.0,neutral or dissatisfied +81056,114093,Male,Loyal Customer,55,Personal Travel,Eco,1947,3,3,3,4,3,3,3,3,2,3,2,3,3,3,18,5.0,neutral or dissatisfied +81057,94849,Male,Loyal Customer,28,Business travel,Business,3498,4,1,1,1,4,4,4,4,3,2,3,2,3,4,3,0.0,neutral or dissatisfied +81058,53213,Male,Loyal Customer,56,Business travel,Eco,589,3,1,1,1,3,3,3,3,1,5,2,2,2,3,0,0.0,neutral or dissatisfied +81059,44967,Male,Loyal Customer,61,Business travel,Business,118,3,3,3,3,2,4,5,5,5,5,4,3,5,5,4,0.0,satisfied +81060,9003,Male,Loyal Customer,48,Business travel,Business,2431,3,3,3,3,2,4,4,4,4,5,4,3,4,4,48,34.0,satisfied +81061,56772,Female,disloyal Customer,21,Business travel,Eco,685,1,2,2,3,3,2,3,3,1,4,4,2,3,3,8,10.0,neutral or dissatisfied +81062,7048,Male,Loyal Customer,24,Personal Travel,Eco Plus,234,3,5,0,4,1,0,1,1,4,4,4,5,5,1,96,,neutral or dissatisfied +81063,88749,Female,Loyal Customer,20,Personal Travel,Eco,404,2,5,2,1,3,2,3,3,3,4,5,5,4,3,2,5.0,neutral or dissatisfied +81064,27207,Male,Loyal Customer,44,Business travel,Business,2554,3,5,5,5,2,2,4,3,3,3,3,2,3,1,5,9.0,neutral or dissatisfied +81065,82155,Male,Loyal Customer,31,Business travel,Business,2366,2,1,1,1,2,2,2,2,1,3,4,4,4,2,24,54.0,neutral or dissatisfied +81066,55542,Male,Loyal Customer,46,Business travel,Eco,550,4,4,4,4,5,4,5,5,2,5,3,1,2,5,3,5.0,neutral or dissatisfied +81067,73315,Male,Loyal Customer,49,Business travel,Business,2107,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +81068,129220,Male,disloyal Customer,27,Business travel,Business,1235,2,3,3,3,5,3,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +81069,125816,Male,Loyal Customer,33,Business travel,Business,3264,2,2,2,2,5,5,5,5,3,5,4,5,5,5,0,0.0,satisfied +81070,8763,Female,Loyal Customer,29,Business travel,Business,1833,1,1,1,1,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +81071,107459,Male,Loyal Customer,23,Personal Travel,Eco Plus,468,4,3,4,3,1,4,4,1,3,4,4,1,3,1,0,11.0,neutral or dissatisfied +81072,46676,Male,Loyal Customer,18,Personal Travel,Eco,73,3,4,0,1,4,0,4,4,5,4,5,5,4,4,110,120.0,neutral or dissatisfied +81073,95162,Male,Loyal Customer,68,Personal Travel,Eco,528,3,4,3,1,2,3,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +81074,113948,Female,Loyal Customer,52,Business travel,Business,1706,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,11.0,satisfied +81075,78260,Female,disloyal Customer,35,Business travel,Business,903,1,1,1,3,2,1,2,2,4,4,5,3,4,2,0,,neutral or dissatisfied +81076,124448,Female,Loyal Customer,39,Business travel,Business,2534,4,5,4,4,2,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +81077,37122,Female,Loyal Customer,38,Business travel,Eco,1046,5,3,3,3,5,5,5,5,2,3,4,3,5,5,0,0.0,satisfied +81078,55080,Male,Loyal Customer,27,Business travel,Eco,1635,3,2,2,2,3,3,3,3,3,3,3,1,3,3,13,43.0,neutral or dissatisfied +81079,116636,Female,Loyal Customer,50,Business travel,Business,1505,1,1,1,1,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +81080,125509,Female,Loyal Customer,52,Personal Travel,Eco,666,3,1,3,2,3,2,2,4,4,3,4,3,4,1,14,2.0,neutral or dissatisfied +81081,36992,Male,disloyal Customer,39,Business travel,Eco,759,3,3,3,2,1,3,2,1,4,1,2,2,3,1,0,0.0,neutral or dissatisfied +81082,27611,Male,Loyal Customer,14,Personal Travel,Eco,978,3,4,2,4,1,2,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +81083,73819,Male,Loyal Customer,44,Business travel,Business,3623,5,5,5,5,5,5,5,4,4,4,4,3,4,5,9,21.0,satisfied +81084,57288,Male,Loyal Customer,31,Business travel,Business,628,1,1,1,1,2,2,2,2,3,3,5,5,4,2,0,0.0,satisfied +81085,81837,Female,Loyal Customer,32,Personal Travel,Eco,1306,4,2,4,3,5,4,5,5,1,4,2,3,2,5,2,0.0,satisfied +81086,71527,Male,Loyal Customer,55,Business travel,Business,3086,1,1,1,1,5,5,5,2,2,2,2,4,2,3,0,5.0,satisfied +81087,70949,Male,Loyal Customer,41,Personal Travel,Eco,612,3,4,3,3,2,3,2,2,3,5,4,3,4,2,64,45.0,neutral or dissatisfied +81088,48390,Female,Loyal Customer,34,Personal Travel,Eco,522,3,4,3,4,2,3,2,2,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +81089,72598,Female,Loyal Customer,38,Personal Travel,Eco,985,1,5,1,2,2,1,2,2,5,5,4,5,4,2,126,112.0,neutral or dissatisfied +81090,64703,Female,Loyal Customer,47,Business travel,Business,2389,5,5,5,5,3,4,4,5,5,5,4,5,5,5,72,60.0,satisfied +81091,108125,Female,Loyal Customer,60,Business travel,Business,1166,2,5,4,5,4,3,4,2,2,2,2,2,2,4,14,19.0,neutral or dissatisfied +81092,114182,Female,Loyal Customer,56,Business travel,Business,2554,4,4,3,4,3,5,4,5,5,5,5,4,5,5,12,4.0,satisfied +81093,96121,Female,Loyal Customer,45,Business travel,Eco Plus,1090,3,2,2,2,2,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +81094,115805,Male,Loyal Customer,45,Business travel,Business,1643,4,4,4,4,5,1,2,4,4,4,4,1,4,4,0,0.0,satisfied +81095,28709,Female,Loyal Customer,32,Business travel,Eco,2554,4,2,2,2,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +81096,79813,Female,Loyal Customer,52,Business travel,Business,1887,3,3,3,3,5,5,4,4,4,5,4,4,4,3,21,14.0,satisfied +81097,99132,Female,Loyal Customer,58,Personal Travel,Eco,237,2,4,2,1,2,4,4,2,2,2,1,5,2,5,33,27.0,neutral or dissatisfied +81098,71838,Female,disloyal Customer,46,Business travel,Business,1348,3,3,3,5,4,3,4,4,4,4,3,3,4,4,0,0.0,satisfied +81099,67269,Male,Loyal Customer,44,Personal Travel,Eco,1121,4,1,4,3,3,4,3,3,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +81100,110502,Female,Loyal Customer,21,Business travel,Eco Plus,925,2,2,2,2,2,2,4,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +81101,108610,Female,Loyal Customer,49,Business travel,Business,296,3,4,4,4,1,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +81102,122111,Male,Loyal Customer,22,Personal Travel,Eco,130,4,5,0,3,1,0,1,1,3,3,3,5,4,1,0,4.0,satisfied +81103,32090,Male,disloyal Customer,40,Business travel,Eco,101,1,5,0,1,4,0,4,4,1,1,3,5,5,4,3,1.0,neutral or dissatisfied +81104,91167,Male,Loyal Customer,14,Personal Travel,Eco,545,1,4,1,2,2,1,2,2,1,2,1,3,5,2,0,3.0,neutral or dissatisfied +81105,100966,Female,Loyal Customer,27,Personal Travel,Eco,1204,3,5,2,5,2,2,2,2,3,2,2,1,2,2,0,0.0,neutral or dissatisfied +81106,103524,Male,disloyal Customer,23,Business travel,Eco,738,5,5,5,2,3,5,3,3,5,3,5,3,4,3,0,6.0,satisfied +81107,109916,Male,Loyal Customer,70,Personal Travel,Eco,1092,3,5,3,2,2,3,1,2,4,4,2,1,1,2,21,3.0,neutral or dissatisfied +81108,39712,Male,Loyal Customer,55,Business travel,Business,2734,2,2,2,2,3,3,5,4,4,4,4,5,4,5,0,,satisfied +81109,19663,Female,Loyal Customer,12,Business travel,Eco Plus,1236,2,3,3,3,2,2,3,2,1,1,4,2,3,2,40,42.0,neutral or dissatisfied +81110,35486,Female,Loyal Customer,39,Personal Travel,Eco,1056,3,1,3,3,2,3,2,2,4,2,4,4,3,2,12,3.0,neutral or dissatisfied +81111,91954,Female,Loyal Customer,30,Personal Travel,Eco,2475,3,4,3,4,2,3,2,2,4,2,3,3,3,2,0,4.0,neutral or dissatisfied +81112,128639,Male,Loyal Customer,53,Personal Travel,Eco,954,3,4,3,4,4,3,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +81113,144,Female,Loyal Customer,41,Business travel,Business,3002,0,0,0,2,5,4,5,1,1,1,1,4,1,5,0,0.0,satisfied +81114,120630,Female,Loyal Customer,51,Business travel,Business,280,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +81115,102938,Male,Loyal Customer,40,Business travel,Business,436,1,1,1,1,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +81116,58955,Male,Loyal Customer,53,Business travel,Business,1723,3,3,3,3,4,4,5,5,5,4,5,4,5,3,15,7.0,satisfied +81117,57168,Female,Loyal Customer,59,Business travel,Business,2227,5,5,5,5,5,4,4,4,4,4,4,3,4,5,79,43.0,satisfied +81118,16874,Female,Loyal Customer,35,Business travel,Eco,746,3,1,5,5,3,3,3,3,1,3,4,4,3,3,0,6.0,neutral or dissatisfied +81119,23617,Male,Loyal Customer,55,Business travel,Eco,977,5,1,1,1,5,5,5,5,4,1,2,5,3,5,7,9.0,satisfied +81120,90766,Female,Loyal Customer,29,Business travel,Business,2436,4,4,4,4,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +81121,118000,Male,Loyal Customer,24,Personal Travel,Eco Plus,255,1,5,0,3,4,0,4,4,3,3,1,1,3,4,9,13.0,neutral or dissatisfied +81122,85522,Male,Loyal Customer,54,Personal Travel,Eco Plus,152,2,5,2,2,5,2,5,5,4,2,5,4,4,5,21,15.0,neutral or dissatisfied +81123,49064,Female,Loyal Customer,33,Business travel,Eco,86,4,3,3,3,4,4,4,4,5,1,2,3,2,4,0,0.0,satisfied +81124,50389,Male,Loyal Customer,23,Business travel,Business,3025,3,1,1,1,3,3,3,3,4,1,3,1,4,3,59,52.0,neutral or dissatisfied +81125,9545,Male,Loyal Customer,38,Business travel,Business,288,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +81126,70640,Male,disloyal Customer,24,Business travel,Eco,946,1,1,1,1,2,1,2,2,4,3,5,5,4,2,0,6.0,neutral or dissatisfied +81127,34800,Male,Loyal Customer,61,Personal Travel,Eco,301,2,4,2,2,1,2,1,1,5,4,4,2,4,1,0,0.0,neutral or dissatisfied +81128,93656,Male,Loyal Customer,39,Business travel,Business,655,5,5,1,5,4,4,5,3,3,3,3,5,3,5,0,2.0,satisfied +81129,12225,Male,Loyal Customer,60,Personal Travel,Business,127,3,5,3,1,5,2,4,3,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +81130,37872,Male,Loyal Customer,18,Business travel,Business,3456,2,2,2,2,4,4,4,4,4,2,1,3,3,4,0,0.0,satisfied +81131,73322,Male,Loyal Customer,56,Business travel,Business,3497,3,3,1,3,2,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +81132,80739,Female,Loyal Customer,35,Business travel,Business,3300,1,4,4,4,1,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +81133,99829,Male,Loyal Customer,54,Business travel,Business,3250,4,4,2,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +81134,80676,Male,Loyal Customer,45,Personal Travel,Eco,821,5,2,4,3,1,4,1,1,2,4,3,1,4,1,2,5.0,satisfied +81135,16247,Male,Loyal Customer,44,Business travel,Business,946,2,2,2,2,2,5,1,4,4,4,4,2,4,3,0,0.0,satisfied +81136,10918,Male,disloyal Customer,37,Business travel,Business,166,4,4,4,1,5,4,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +81137,97189,Male,Loyal Customer,65,Personal Travel,Eco,1129,1,4,2,4,5,2,4,5,5,3,5,3,4,5,28,44.0,neutral or dissatisfied +81138,49836,Female,Loyal Customer,47,Business travel,Eco,156,5,5,5,5,3,4,4,4,4,5,4,4,4,2,0,0.0,satisfied +81139,14798,Male,Loyal Customer,36,Business travel,Eco,214,4,5,5,5,4,4,4,1,2,2,5,4,4,4,133,143.0,satisfied +81140,75656,Female,Loyal Customer,68,Personal Travel,Eco,304,2,3,2,2,3,3,2,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +81141,32423,Female,Loyal Customer,33,Business travel,Business,3452,2,2,2,2,4,3,2,5,5,5,4,2,5,5,0,0.0,satisfied +81142,101650,Female,Loyal Customer,53,Personal Travel,Eco,1733,2,5,2,4,3,4,5,4,4,2,4,5,4,3,47,34.0,neutral or dissatisfied +81143,118638,Female,disloyal Customer,26,Business travel,Eco,621,3,1,3,4,1,3,1,1,1,5,4,4,3,1,0,0.0,neutral or dissatisfied +81144,96028,Female,Loyal Customer,22,Business travel,Business,758,2,5,5,5,2,2,2,2,2,1,3,3,3,2,7,13.0,neutral or dissatisfied +81145,74907,Female,Loyal Customer,39,Business travel,Business,2446,4,4,4,4,2,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +81146,73735,Female,Loyal Customer,57,Personal Travel,Eco,192,3,5,0,2,3,5,5,2,2,0,2,5,2,3,8,14.0,neutral or dissatisfied +81147,119854,Female,Loyal Customer,63,Business travel,Business,3669,3,3,3,3,3,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +81148,42484,Male,Loyal Customer,25,Business travel,Business,693,3,3,3,3,5,5,5,5,1,5,1,4,4,5,0,0.0,satisfied +81149,59077,Female,Loyal Customer,62,Business travel,Business,244,3,3,3,3,5,4,4,3,3,3,3,2,3,1,12,9.0,neutral or dissatisfied +81150,11395,Male,Loyal Customer,42,Business travel,Business,316,0,1,1,1,2,5,5,3,3,3,3,4,3,3,18,8.0,satisfied +81151,21092,Male,disloyal Customer,26,Business travel,Business,227,3,3,3,4,3,3,3,3,2,4,4,1,4,3,0,0.0,neutral or dissatisfied +81152,33556,Male,disloyal Customer,33,Business travel,Eco,399,3,0,3,4,3,3,3,3,5,2,4,5,2,3,0,0.0,neutral or dissatisfied +81153,51703,Female,disloyal Customer,40,Business travel,Business,261,1,1,1,3,1,3,3,3,4,3,3,3,4,3,402,389.0,neutral or dissatisfied +81154,55194,Female,Loyal Customer,65,Personal Travel,Eco Plus,1504,5,5,5,4,5,4,5,5,5,5,3,4,5,3,0,0.0,satisfied +81155,4242,Female,disloyal Customer,23,Business travel,Eco,620,3,0,3,4,1,3,1,1,2,5,1,1,5,1,105,118.0,neutral or dissatisfied +81156,59760,Female,Loyal Customer,40,Business travel,Business,895,1,1,1,1,3,5,5,5,5,4,5,4,5,5,0,2.0,satisfied +81157,6919,Male,Loyal Customer,63,Personal Travel,Eco,265,3,1,3,2,1,3,1,1,1,4,1,4,2,1,0,2.0,neutral or dissatisfied +81158,90383,Female,Loyal Customer,26,Business travel,Business,404,3,1,1,1,3,3,3,3,3,4,3,2,4,3,3,9.0,neutral or dissatisfied +81159,8961,Female,Loyal Customer,37,Business travel,Business,2456,1,4,1,1,1,2,5,5,5,5,5,5,5,3,0,0.0,satisfied +81160,31903,Female,Loyal Customer,50,Business travel,Business,2761,0,5,0,2,5,4,4,3,3,3,3,5,3,5,21,19.0,satisfied +81161,82699,Male,Loyal Customer,23,Business travel,Business,2643,2,3,1,3,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +81162,56387,Male,Loyal Customer,59,Business travel,Business,1167,1,1,1,1,3,4,5,2,2,3,2,5,2,5,7,0.0,satisfied +81163,58286,Male,Loyal Customer,24,Personal Travel,Eco,594,2,4,2,3,4,2,1,4,4,5,3,2,1,4,45,28.0,neutral or dissatisfied +81164,45475,Female,Loyal Customer,43,Business travel,Eco,522,5,5,5,5,4,5,1,5,5,5,5,2,5,4,0,0.0,satisfied +81165,122450,Female,Loyal Customer,44,Business travel,Business,575,1,1,1,1,3,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +81166,119546,Male,Loyal Customer,17,Personal Travel,Eco,899,4,4,5,4,4,5,4,4,4,5,5,5,5,4,60,41.0,neutral or dissatisfied +81167,68162,Male,Loyal Customer,47,Business travel,Eco,603,2,2,2,2,2,2,2,2,2,4,4,4,4,2,10,6.0,neutral or dissatisfied +81168,55885,Male,Loyal Customer,15,Business travel,Business,3586,5,5,5,5,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +81169,100772,Male,disloyal Customer,25,Business travel,Eco,982,5,5,5,5,5,5,5,5,4,3,5,3,5,5,3,0.0,satisfied +81170,44190,Male,disloyal Customer,24,Business travel,Eco,231,4,1,4,2,3,4,3,3,2,4,3,3,2,3,0,5.0,neutral or dissatisfied +81171,116520,Male,Loyal Customer,62,Personal Travel,Eco,325,2,2,2,4,1,2,1,1,3,4,3,2,4,1,56,56.0,neutral or dissatisfied +81172,35926,Female,Loyal Customer,25,Business travel,Business,2381,2,2,2,2,4,4,4,4,4,3,4,2,5,4,0,0.0,satisfied +81173,112627,Male,Loyal Customer,49,Personal Travel,Eco,639,4,5,4,2,4,3,3,4,4,4,4,3,5,3,152,153.0,neutral or dissatisfied +81174,90977,Female,disloyal Customer,26,Business travel,Eco,366,4,0,4,1,5,4,5,5,2,2,3,3,3,5,0,0.0,satisfied +81175,125915,Male,Loyal Customer,58,Personal Travel,Eco,993,1,4,1,5,4,1,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +81176,113819,Female,Loyal Customer,63,Personal Travel,Eco Plus,197,3,5,3,4,2,4,4,3,3,3,3,4,3,4,36,32.0,neutral or dissatisfied +81177,61001,Female,disloyal Customer,45,Business travel,Eco,649,2,1,2,3,5,2,5,5,1,2,2,1,2,5,0,0.0,neutral or dissatisfied +81178,104923,Male,Loyal Customer,42,Business travel,Business,1994,5,5,5,5,5,5,5,4,4,4,4,3,4,5,7,0.0,satisfied +81179,8055,Male,Loyal Customer,37,Business travel,Business,2039,3,3,3,3,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +81180,125515,Female,Loyal Customer,12,Personal Travel,Eco Plus,666,3,4,3,3,2,3,2,2,3,5,3,3,1,2,8,0.0,neutral or dissatisfied +81181,45804,Male,Loyal Customer,57,Business travel,Eco,216,5,2,2,2,5,5,5,5,2,2,2,2,1,5,0,0.0,satisfied +81182,98575,Male,Loyal Customer,51,Business travel,Eco,834,3,2,2,2,2,3,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +81183,108028,Female,Loyal Customer,44,Business travel,Business,1508,2,3,3,3,1,4,4,2,2,2,2,1,2,2,1,0.0,neutral or dissatisfied +81184,94602,Female,Loyal Customer,53,Business travel,Business,2151,0,0,0,5,5,4,5,2,2,2,2,3,2,5,22,18.0,satisfied +81185,61484,Male,Loyal Customer,32,Business travel,Business,2419,5,5,5,5,4,4,4,4,4,4,3,5,4,4,0,0.0,satisfied +81186,42114,Male,Loyal Customer,42,Business travel,Business,1590,1,2,2,2,3,4,4,1,1,1,1,1,1,4,8,0.0,neutral or dissatisfied +81187,24072,Male,Loyal Customer,46,Business travel,Business,3224,2,2,2,2,1,5,3,5,5,5,5,1,5,3,12,11.0,satisfied +81188,129236,Female,Loyal Customer,29,Business travel,Business,1464,2,2,2,2,2,2,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +81189,58503,Male,Loyal Customer,64,Business travel,Business,3624,4,4,4,4,5,5,4,4,4,5,4,5,4,4,20,4.0,satisfied +81190,94639,Female,Loyal Customer,60,Business travel,Business,189,3,3,3,3,3,5,4,5,5,5,4,5,5,4,1,2.0,satisfied +81191,110864,Female,disloyal Customer,24,Business travel,Eco,404,4,4,4,1,2,4,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +81192,57888,Female,Loyal Customer,49,Business travel,Business,305,1,1,1,1,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +81193,43346,Female,Loyal Customer,37,Business travel,Business,3996,2,4,4,4,1,4,4,2,2,2,2,3,2,2,0,26.0,neutral or dissatisfied +81194,121157,Female,disloyal Customer,29,Business travel,Eco,1410,3,4,4,2,3,2,2,2,5,1,2,2,1,2,86,237.0,neutral or dissatisfied +81195,68039,Female,Loyal Customer,57,Personal Travel,Business,868,2,2,2,3,1,3,4,4,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +81196,76238,Male,Loyal Customer,31,Business travel,Business,1175,2,4,4,4,2,3,2,2,1,4,4,3,3,2,0,0.0,neutral or dissatisfied +81197,7659,Male,Loyal Customer,72,Business travel,Eco,767,1,3,3,3,1,1,1,1,1,2,3,2,3,1,0,0.0,neutral or dissatisfied +81198,64290,Male,disloyal Customer,57,Business travel,Business,1212,2,2,2,4,1,2,1,1,5,5,5,4,4,1,4,2.0,neutral or dissatisfied +81199,2398,Female,disloyal Customer,17,Business travel,Eco,604,0,4,0,4,3,0,3,3,3,5,4,5,5,3,0,0.0,satisfied +81200,113806,Male,Loyal Customer,25,Business travel,Business,3072,2,2,2,2,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +81201,26435,Female,Loyal Customer,40,Business travel,Business,842,5,5,5,5,2,4,5,3,3,4,3,2,3,5,0,0.0,satisfied +81202,37197,Female,disloyal Customer,21,Business travel,Eco,1189,2,2,2,3,2,2,2,2,3,2,2,2,3,2,2,0.0,neutral or dissatisfied +81203,65911,Female,Loyal Customer,54,Business travel,Business,3741,5,5,2,5,4,5,4,5,5,5,5,5,5,3,29,34.0,satisfied +81204,70573,Male,Loyal Customer,26,Personal Travel,Eco,1258,1,4,1,4,1,5,5,5,4,4,5,5,4,5,111,158.0,neutral or dissatisfied +81205,86305,Male,Loyal Customer,58,Business travel,Business,356,5,5,5,5,3,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +81206,72525,Male,disloyal Customer,29,Business travel,Business,929,2,2,2,1,3,2,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +81207,96592,Male,Loyal Customer,58,Business travel,Business,461,5,5,5,5,5,1,3,4,4,4,4,1,4,5,12,16.0,satisfied +81208,31995,Male,Loyal Customer,60,Personal Travel,Business,216,1,5,1,5,5,5,4,4,4,1,5,4,4,3,2,14.0,neutral or dissatisfied +81209,63616,Male,Loyal Customer,52,Business travel,Eco,1440,1,1,1,1,1,1,1,1,4,3,4,3,4,1,0,5.0,neutral or dissatisfied +81210,15071,Male,Loyal Customer,15,Personal Travel,Eco Plus,627,1,4,0,3,3,0,3,3,4,3,3,4,4,3,42,35.0,neutral or dissatisfied +81211,121790,Male,disloyal Customer,24,Business travel,Business,449,5,0,5,1,1,5,1,1,5,4,5,3,5,1,0,0.0,satisfied +81212,99733,Male,Loyal Customer,37,Business travel,Business,3191,5,5,2,5,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +81213,10395,Female,disloyal Customer,34,Business travel,Business,301,2,2,2,4,4,2,4,4,3,2,5,3,5,4,2,0.0,neutral or dissatisfied +81214,95319,Male,Loyal Customer,46,Personal Travel,Eco,239,3,4,0,2,4,0,4,4,3,3,4,3,4,4,3,6.0,neutral or dissatisfied +81215,62705,Male,disloyal Customer,23,Business travel,Business,855,5,0,5,3,5,5,2,5,4,4,5,3,5,5,6,18.0,satisfied +81216,83713,Male,Loyal Customer,49,Business travel,Business,577,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +81217,9812,Female,Loyal Customer,25,Business travel,Business,2961,3,3,3,3,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +81218,62049,Female,Loyal Customer,16,Business travel,Business,2475,3,3,4,3,4,4,4,4,1,4,4,4,4,4,6,0.0,satisfied +81219,33116,Female,Loyal Customer,60,Personal Travel,Eco,121,4,3,4,2,3,3,3,1,1,4,1,3,1,1,0,0.0,neutral or dissatisfied +81220,75637,Male,disloyal Customer,44,Business travel,Business,304,3,3,3,4,2,3,2,2,4,3,5,3,5,2,0,0.0,satisfied +81221,125721,Male,Loyal Customer,25,Personal Travel,Eco,899,3,4,3,3,1,3,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +81222,19799,Male,Loyal Customer,56,Personal Travel,Eco Plus,667,2,5,2,1,5,2,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +81223,55889,Male,Loyal Customer,58,Business travel,Business,1816,3,3,3,3,5,5,5,5,5,5,5,5,5,3,49,33.0,satisfied +81224,103052,Male,Loyal Customer,34,Business travel,Business,3458,3,1,1,1,1,4,4,3,3,3,3,3,3,4,27,23.0,neutral or dissatisfied +81225,17672,Male,Loyal Customer,60,Business travel,Eco,282,4,2,2,2,4,4,4,4,4,2,2,2,3,4,0,0.0,satisfied +81226,81687,Female,disloyal Customer,11,Business travel,Eco,907,2,2,2,4,5,2,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +81227,1561,Male,Loyal Customer,53,Business travel,Business,3373,3,3,5,3,3,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +81228,74185,Female,Loyal Customer,24,Personal Travel,Eco,592,3,4,3,4,4,3,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +81229,92278,Female,Loyal Customer,68,Personal Travel,Eco,1900,5,3,5,3,2,3,3,5,5,5,5,3,5,2,0,1.0,satisfied +81230,31694,Male,Loyal Customer,68,Business travel,Business,3849,1,2,2,2,1,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +81231,46245,Male,Loyal Customer,57,Business travel,Business,3162,1,3,3,3,1,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +81232,87691,Female,Loyal Customer,39,Personal Travel,Eco,606,3,5,3,3,5,3,5,5,5,5,3,5,1,5,107,90.0,neutral or dissatisfied +81233,52234,Male,Loyal Customer,41,Business travel,Business,2054,3,3,3,3,3,2,3,5,5,5,5,5,5,3,0,0.0,satisfied +81234,64104,Male,Loyal Customer,39,Business travel,Eco Plus,919,1,3,3,3,1,1,1,1,3,5,2,3,3,1,0,0.0,neutral or dissatisfied +81235,100782,Male,Loyal Customer,19,Personal Travel,Eco,1411,3,2,3,4,2,3,2,2,1,2,2,1,4,2,0,0.0,neutral or dissatisfied +81236,25261,Male,Loyal Customer,49,Business travel,Eco,425,5,1,2,1,5,5,5,5,3,1,5,5,5,5,0,0.0,satisfied +81237,61707,Female,Loyal Customer,48,Business travel,Business,1464,5,5,5,5,2,4,5,4,4,4,4,3,4,3,17,1.0,satisfied +81238,37404,Female,disloyal Customer,35,Business travel,Eco,944,2,2,2,3,1,2,1,1,3,2,4,3,5,1,8,0.0,neutral or dissatisfied +81239,63723,Female,Loyal Customer,40,Business travel,Business,1660,1,2,2,2,1,2,2,1,1,1,1,4,1,3,22,0.0,neutral or dissatisfied +81240,31399,Female,Loyal Customer,11,Personal Travel,Eco,1199,5,5,5,2,4,5,4,4,3,5,1,1,5,4,0,0.0,satisfied +81241,109294,Male,Loyal Customer,50,Business travel,Business,3895,3,3,1,3,5,5,5,5,4,4,4,5,4,5,182,158.0,satisfied +81242,13093,Male,Loyal Customer,53,Business travel,Business,595,5,5,4,5,5,3,4,5,5,4,5,4,5,4,18,13.0,satisfied +81243,60460,Male,Loyal Customer,59,Business travel,Business,927,2,2,2,2,4,4,4,5,5,5,5,3,5,5,17,0.0,satisfied +81244,85473,Female,Loyal Customer,29,Business travel,Business,3086,1,4,4,4,1,1,1,1,1,1,1,1,2,1,9,2.0,neutral or dissatisfied +81245,103252,Male,Loyal Customer,69,Personal Travel,Eco,667,2,4,2,2,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +81246,58612,Female,Loyal Customer,22,Personal Travel,Business,235,2,4,2,1,2,2,2,2,4,3,5,3,4,2,52,41.0,neutral or dissatisfied +81247,73003,Female,Loyal Customer,68,Personal Travel,Eco,1096,2,2,2,4,4,4,4,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +81248,64540,Female,disloyal Customer,27,Business travel,Eco,282,2,3,2,4,2,2,2,2,1,5,3,4,4,2,92,100.0,neutral or dissatisfied +81249,110234,Male,disloyal Customer,20,Business travel,Eco,1041,1,1,1,3,4,1,5,4,5,5,5,5,4,4,41,30.0,neutral or dissatisfied +81250,100378,Female,Loyal Customer,53,Personal Travel,Eco,1053,1,4,1,3,2,4,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +81251,10506,Female,disloyal Customer,48,Business travel,Business,309,1,1,1,2,3,1,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +81252,91518,Male,Loyal Customer,15,Personal Travel,Eco,1620,3,4,3,3,3,5,5,3,3,4,4,5,4,5,194,289.0,neutral or dissatisfied +81253,32856,Male,Loyal Customer,11,Personal Travel,Eco,101,5,2,5,2,2,5,2,2,3,2,2,3,2,2,3,7.0,satisfied +81254,45830,Male,Loyal Customer,59,Personal Travel,Eco,216,2,5,2,2,4,2,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +81255,51817,Male,Loyal Customer,27,Business travel,Eco Plus,493,4,4,4,4,4,4,4,4,1,5,5,3,3,4,0,0.0,satisfied +81256,118535,Female,Loyal Customer,52,Business travel,Business,338,0,0,0,4,2,5,5,5,5,5,5,5,5,3,12,23.0,satisfied +81257,18545,Male,disloyal Customer,77,Business travel,Eco,190,4,3,4,4,5,4,5,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +81258,119785,Female,Loyal Customer,23,Business travel,Business,3238,4,4,4,4,4,4,4,4,3,3,4,5,5,4,14,0.0,satisfied +81259,76778,Female,Loyal Customer,44,Business travel,Business,689,4,4,1,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +81260,102911,Male,disloyal Customer,50,Business travel,Business,436,2,2,2,5,4,2,4,4,3,4,4,4,5,4,14,14.0,neutral or dissatisfied +81261,48678,Female,Loyal Customer,52,Business travel,Business,209,2,4,4,4,1,4,3,3,3,2,2,4,3,2,0,12.0,neutral or dissatisfied +81262,30164,Male,Loyal Customer,17,Personal Travel,Eco,399,3,5,4,4,5,4,1,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +81263,110407,Female,Loyal Customer,52,Business travel,Business,787,4,4,4,4,2,5,4,4,4,4,4,3,4,3,5,0.0,satisfied +81264,69205,Female,disloyal Customer,37,Business travel,Business,740,3,3,3,4,3,2,2,1,5,4,4,2,4,2,221,198.0,neutral or dissatisfied +81265,62575,Male,disloyal Customer,27,Business travel,Business,850,5,5,5,3,1,5,1,1,4,5,5,4,4,1,1,0.0,satisfied +81266,72637,Female,Loyal Customer,33,Personal Travel,Eco,1119,2,5,2,3,3,2,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +81267,121674,Male,Loyal Customer,69,Personal Travel,Eco,328,2,5,2,2,1,2,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +81268,74669,Male,Loyal Customer,38,Personal Travel,Eco,1188,2,2,2,4,4,2,4,4,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +81269,64273,Female,disloyal Customer,19,Business travel,Eco,1212,4,4,4,3,4,4,4,4,5,4,5,3,4,4,6,0.0,satisfied +81270,127103,Female,Loyal Customer,41,Personal Travel,Eco,621,4,4,4,1,2,4,2,2,4,4,5,5,4,2,3,7.0,satisfied +81271,51442,Male,Loyal Customer,42,Personal Travel,Eco Plus,109,4,5,4,2,3,4,3,3,3,4,1,4,4,3,10,2.0,neutral or dissatisfied +81272,25296,Female,Loyal Customer,72,Business travel,Business,3604,5,5,5,5,4,4,5,4,4,4,4,3,4,3,6,36.0,satisfied +81273,66965,Female,Loyal Customer,57,Business travel,Business,2384,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +81274,56106,Female,Loyal Customer,51,Personal Travel,Eco,2402,3,3,3,2,3,3,4,5,1,1,2,4,3,4,0,16.0,neutral or dissatisfied +81275,17303,Male,Loyal Customer,61,Business travel,Business,3502,3,3,3,3,2,3,3,5,5,5,5,2,5,1,0,0.0,satisfied +81276,72517,Female,Loyal Customer,45,Business travel,Business,2647,3,3,3,3,5,5,5,4,4,4,4,3,4,3,12,0.0,satisfied +81277,10544,Male,Loyal Customer,47,Business travel,Business,1734,0,4,0,3,2,5,4,5,5,5,5,3,5,4,0,1.0,satisfied +81278,42470,Male,disloyal Customer,40,Business travel,Eco,429,4,4,4,3,1,4,1,1,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +81279,98991,Male,Loyal Customer,29,Personal Travel,Eco,543,3,4,3,2,1,3,1,1,4,3,4,5,4,1,8,0.0,neutral or dissatisfied +81280,90658,Female,Loyal Customer,16,Business travel,Eco,545,4,3,3,3,4,4,3,4,2,1,3,1,3,4,104,114.0,neutral or dissatisfied +81281,19599,Female,Loyal Customer,43,Business travel,Eco Plus,108,2,4,4,4,2,2,2,2,2,2,2,3,2,3,0,0.0,satisfied +81282,66881,Male,Loyal Customer,53,Business travel,Business,3423,3,5,5,5,1,3,3,3,3,3,3,4,3,4,64,51.0,neutral or dissatisfied +81283,24578,Female,Loyal Customer,30,Personal Travel,Eco Plus,696,4,5,4,2,2,4,5,2,4,2,5,3,5,2,76,70.0,satisfied +81284,55797,Male,Loyal Customer,31,Business travel,Eco Plus,2400,4,3,3,3,4,4,4,3,2,4,3,4,1,4,0,30.0,neutral or dissatisfied +81285,121846,Female,Loyal Customer,39,Business travel,Business,3851,3,1,3,3,1,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +81286,86787,Male,Loyal Customer,29,Business travel,Business,692,3,3,3,3,5,5,5,5,3,2,4,3,4,5,12,0.0,satisfied +81287,57777,Female,disloyal Customer,37,Business travel,Eco,1204,2,2,2,4,2,3,3,3,2,4,5,3,4,3,15,0.0,neutral or dissatisfied +81288,8099,Female,Loyal Customer,48,Business travel,Business,125,4,4,4,4,3,5,5,4,4,4,5,5,4,3,0,0.0,satisfied +81289,76335,Female,Loyal Customer,11,Personal Travel,Eco Plus,2182,4,4,4,4,4,4,4,4,3,1,1,4,4,4,11,5.0,satisfied +81290,88196,Female,Loyal Customer,38,Business travel,Business,3961,4,4,4,4,4,5,4,5,5,5,5,4,5,3,33,38.0,satisfied +81291,86724,Male,Loyal Customer,48,Personal Travel,Eco,1747,1,0,1,3,5,1,5,5,5,5,4,4,4,5,4,0.0,neutral or dissatisfied +81292,101146,Female,Loyal Customer,29,Business travel,Business,3627,2,4,4,4,2,2,2,2,2,1,3,4,3,2,0,5.0,neutral or dissatisfied +81293,51288,Male,Loyal Customer,56,Business travel,Eco Plus,373,4,4,4,4,4,4,4,4,1,3,4,1,4,4,0,0.0,satisfied +81294,101457,Female,Loyal Customer,53,Business travel,Business,3541,4,4,4,4,2,4,5,5,5,5,5,4,5,5,7,0.0,satisfied +81295,123246,Female,Loyal Customer,32,Personal Travel,Eco,590,2,5,2,3,2,2,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +81296,129768,Male,Loyal Customer,59,Personal Travel,Eco,337,5,3,4,2,3,4,3,3,3,4,3,4,2,3,0,0.0,satisfied +81297,41665,Female,disloyal Customer,11,Business travel,Eco,936,3,3,3,4,1,3,1,1,5,5,4,5,2,1,24,4.0,neutral or dissatisfied +81298,79668,Male,Loyal Customer,21,Personal Travel,Eco,760,1,3,1,3,2,1,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +81299,6433,Female,Loyal Customer,48,Personal Travel,Eco,296,4,4,4,5,4,4,5,5,5,4,5,3,5,3,45,69.0,neutral or dissatisfied +81300,22713,Female,Loyal Customer,9,Personal Travel,Eco Plus,579,2,3,2,3,1,2,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +81301,62830,Female,Loyal Customer,23,Personal Travel,Eco,2556,3,5,4,4,4,2,2,4,5,3,5,2,3,2,0,0.0,neutral or dissatisfied +81302,73832,Male,Loyal Customer,52,Personal Travel,Eco,1194,5,5,5,5,2,5,2,2,4,3,3,3,5,2,0,0.0,satisfied +81303,91965,Female,Loyal Customer,67,Personal Travel,Eco,2475,2,4,3,3,2,3,3,5,5,3,5,1,5,3,9,0.0,neutral or dissatisfied +81304,57667,Female,Loyal Customer,46,Business travel,Business,1718,4,4,4,4,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +81305,49935,Female,Loyal Customer,23,Business travel,Eco,109,0,3,0,2,3,0,3,3,3,2,1,4,4,3,0,0.0,satisfied +81306,43673,Male,Loyal Customer,10,Personal Travel,Eco,695,4,5,4,2,4,4,4,4,5,3,4,3,5,4,6,0.0,satisfied +81307,44280,Female,Loyal Customer,38,Personal Travel,Eco Plus,222,5,5,5,4,4,5,4,4,2,5,3,3,4,4,0,0.0,satisfied +81308,55382,Female,Loyal Customer,58,Personal Travel,Eco,413,2,5,2,1,4,5,5,4,4,2,4,5,4,4,7,0.0,neutral or dissatisfied +81309,55976,Male,Loyal Customer,68,Personal Travel,Eco,1620,0,5,0,1,5,0,5,5,5,5,5,4,4,5,0,0.0,satisfied +81310,35596,Female,Loyal Customer,30,Business travel,Eco Plus,1005,3,1,1,1,3,3,3,3,1,2,4,1,4,3,0,0.0,neutral or dissatisfied +81311,17353,Male,Loyal Customer,16,Business travel,Business,2031,2,2,2,2,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +81312,57887,Male,disloyal Customer,23,Business travel,Business,305,4,0,4,4,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +81313,9362,Male,Loyal Customer,38,Business travel,Business,2650,3,1,1,1,5,2,2,3,3,2,3,2,3,1,26,31.0,neutral or dissatisfied +81314,15081,Female,Loyal Customer,48,Business travel,Eco,239,4,1,1,1,3,4,4,4,4,4,4,4,4,3,81,75.0,neutral or dissatisfied +81315,55949,Female,Loyal Customer,49,Business travel,Business,1620,2,2,2,2,2,5,4,4,4,4,4,4,4,3,7,9.0,satisfied +81316,103235,Female,Loyal Customer,51,Business travel,Business,409,2,2,4,2,2,5,5,5,5,4,5,4,5,5,14,0.0,satisfied +81317,53967,Male,Loyal Customer,69,Personal Travel,Eco,1325,4,4,4,1,1,4,1,1,3,2,3,4,5,1,2,1.0,neutral or dissatisfied +81318,50046,Male,disloyal Customer,44,Business travel,Eco,109,3,1,3,3,3,3,3,3,3,4,4,4,3,3,0,0.0,neutral or dissatisfied +81319,43740,Male,Loyal Customer,62,Business travel,Eco,622,3,1,3,3,3,3,3,3,3,4,3,4,3,3,0,9.0,neutral or dissatisfied +81320,23521,Female,Loyal Customer,47,Personal Travel,Eco,349,4,1,4,3,1,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +81321,34919,Female,disloyal Customer,39,Business travel,Business,187,4,4,4,4,1,4,1,1,2,2,3,3,3,1,22,32.0,neutral or dissatisfied +81322,56901,Female,Loyal Customer,39,Business travel,Business,2565,3,3,3,3,2,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +81323,96818,Male,disloyal Customer,14,Business travel,Eco,972,4,4,4,1,3,4,3,3,5,2,4,4,5,3,5,0.0,satisfied +81324,5088,Male,Loyal Customer,43,Business travel,Eco,235,3,4,4,4,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +81325,106647,Female,disloyal Customer,24,Business travel,Eco,861,1,1,1,3,3,1,5,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +81326,75103,Male,Loyal Customer,52,Business travel,Business,1846,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +81327,31751,Male,Loyal Customer,64,Personal Travel,Eco Plus,862,2,5,2,5,4,2,4,4,5,5,5,5,5,4,20,14.0,neutral or dissatisfied +81328,54454,Female,Loyal Customer,34,Business travel,Business,925,2,2,2,2,4,4,5,5,5,5,5,5,5,5,58,51.0,satisfied +81329,90764,Male,Loyal Customer,51,Business travel,Eco,581,2,5,5,5,2,2,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +81330,126869,Male,Loyal Customer,59,Personal Travel,Eco,2296,2,4,2,1,4,2,3,4,3,2,4,4,4,4,0,5.0,neutral or dissatisfied +81331,120175,Female,Loyal Customer,42,Business travel,Business,335,3,3,3,3,4,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +81332,67295,Female,disloyal Customer,11,Business travel,Eco,1121,3,3,3,3,3,3,3,3,4,5,4,4,4,3,3,0.0,neutral or dissatisfied +81333,4056,Male,Loyal Customer,50,Personal Travel,Eco,425,2,3,2,3,5,2,5,5,4,4,3,5,5,5,0,0.0,neutral or dissatisfied +81334,18355,Male,Loyal Customer,25,Business travel,Business,2302,1,5,5,5,1,1,1,1,4,4,4,4,3,1,16,8.0,neutral or dissatisfied +81335,56165,Female,disloyal Customer,10,Business travel,Eco,1400,3,3,3,3,3,3,3,3,3,5,2,2,2,3,7,16.0,neutral or dissatisfied +81336,44388,Female,disloyal Customer,44,Business travel,Eco,342,1,0,1,1,5,1,5,5,1,4,4,3,3,5,0,0.0,neutral or dissatisfied +81337,81288,Female,Loyal Customer,43,Personal Travel,Eco,1020,4,0,3,3,4,4,3,2,2,3,3,2,2,4,0,0.0,neutral or dissatisfied +81338,76322,Female,Loyal Customer,9,Personal Travel,Eco,2182,3,4,3,3,5,3,5,5,3,4,4,2,4,5,0,0.0,neutral or dissatisfied +81339,22516,Male,Loyal Customer,26,Business travel,Eco Plus,143,4,4,4,4,4,4,5,4,3,1,3,4,2,4,2,7.0,satisfied +81340,91381,Female,disloyal Customer,21,Business travel,Eco,710,4,4,4,4,5,4,5,5,4,5,5,4,5,5,9,2.0,satisfied +81341,38975,Female,Loyal Customer,63,Business travel,Business,230,0,0,0,5,2,1,1,3,3,3,1,1,3,1,0,3.0,satisfied +81342,9348,Male,disloyal Customer,20,Business travel,Business,401,0,0,0,5,2,0,2,2,5,3,4,3,4,2,90,83.0,satisfied +81343,53728,Male,Loyal Customer,49,Personal Travel,Eco,1208,2,3,2,3,1,2,2,1,2,2,4,3,4,1,78,61.0,neutral or dissatisfied +81344,50060,Female,disloyal Customer,21,Business travel,Eco,373,4,3,4,2,3,4,1,3,4,2,5,4,3,3,0,0.0,satisfied +81345,18608,Male,Loyal Customer,19,Business travel,Eco,190,4,4,3,4,4,4,4,4,1,1,4,1,2,4,0,0.0,satisfied +81346,101828,Female,Loyal Customer,45,Personal Travel,Eco,1521,1,4,1,2,5,4,5,2,2,1,2,4,2,3,69,,neutral or dissatisfied +81347,36525,Female,disloyal Customer,26,Business travel,Eco,1237,2,2,2,3,2,2,2,2,1,1,3,3,3,2,8,16.0,neutral or dissatisfied +81348,90955,Male,Loyal Customer,64,Business travel,Business,1589,4,4,2,4,1,4,4,1,1,1,4,4,1,4,0,0.0,neutral or dissatisfied +81349,94252,Male,Loyal Customer,37,Business travel,Business,248,0,0,0,2,2,4,4,2,2,2,2,3,2,5,7,1.0,satisfied +81350,10308,Male,Loyal Customer,48,Business travel,Business,308,0,0,0,5,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +81351,98094,Female,disloyal Customer,27,Business travel,Business,845,0,0,0,2,1,0,1,1,4,4,4,5,5,1,5,0.0,satisfied +81352,12333,Male,Loyal Customer,48,Business travel,Eco,383,2,4,2,4,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +81353,89575,Male,disloyal Customer,29,Business travel,Business,1096,1,1,1,3,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +81354,81944,Male,disloyal Customer,28,Business travel,Business,1532,3,3,3,4,3,3,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +81355,55815,Female,disloyal Customer,37,Business travel,Business,1416,2,2,2,4,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +81356,5813,Male,Loyal Customer,12,Personal Travel,Eco,273,2,3,4,3,4,4,4,4,4,5,3,2,3,4,0,57.0,neutral or dissatisfied +81357,63489,Female,Loyal Customer,46,Business travel,Business,1766,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +81358,22480,Female,Loyal Customer,32,Personal Travel,Eco,208,3,1,3,1,4,3,4,4,4,4,1,4,1,4,0,0.0,neutral or dissatisfied +81359,15425,Female,Loyal Customer,41,Business travel,Eco,331,5,5,5,5,4,5,4,4,3,2,2,3,5,4,0,0.0,satisfied +81360,121056,Male,Loyal Customer,62,Personal Travel,Eco,1013,2,4,2,3,4,2,4,4,2,1,3,4,4,4,0,8.0,neutral or dissatisfied +81361,27880,Female,Loyal Customer,67,Personal Travel,Eco Plus,1448,3,1,3,3,5,3,2,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +81362,117363,Male,Loyal Customer,62,Personal Travel,Eco,296,5,5,5,1,3,5,3,3,3,5,4,4,5,3,0,0.0,satisfied +81363,125873,Male,Loyal Customer,49,Business travel,Business,461,3,3,3,3,3,3,3,3,3,4,3,2,3,2,6,13.0,neutral or dissatisfied +81364,26204,Male,Loyal Customer,61,Business travel,Business,270,3,3,5,5,1,3,3,3,3,3,3,2,3,2,116,104.0,neutral or dissatisfied +81365,91657,Male,Loyal Customer,23,Personal Travel,Eco,1340,2,1,2,3,3,2,3,3,4,2,3,4,4,3,4,2.0,neutral or dissatisfied +81366,74813,Female,Loyal Customer,24,Personal Travel,Eco Plus,1205,1,3,1,3,3,1,3,3,3,5,3,4,4,3,23,5.0,neutral or dissatisfied +81367,109317,Male,Loyal Customer,44,Business travel,Business,2620,3,3,3,3,2,4,4,5,5,5,5,3,5,5,8,0.0,satisfied +81368,107855,Female,Loyal Customer,65,Business travel,Business,2282,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,14.0,satisfied +81369,108189,Male,disloyal Customer,24,Business travel,Business,1166,5,5,5,5,5,5,5,5,4,2,5,4,5,5,50,58.0,satisfied +81370,39813,Male,disloyal Customer,20,Business travel,Eco,221,5,4,5,4,1,5,1,1,2,1,2,1,3,1,0,0.0,satisfied +81371,106242,Female,disloyal Customer,28,Business travel,Eco,1167,1,1,1,3,5,1,5,5,4,4,4,2,4,5,63,60.0,neutral or dissatisfied +81372,22612,Female,Loyal Customer,42,Business travel,Business,3211,0,3,0,1,2,5,3,1,1,1,1,4,1,2,0,0.0,satisfied +81373,58464,Female,Loyal Customer,63,Personal Travel,Eco Plus,723,3,3,3,3,1,3,4,4,4,3,5,1,4,2,1,1.0,neutral or dissatisfied +81374,36534,Male,disloyal Customer,25,Business travel,Business,1121,4,0,5,2,3,5,3,3,4,3,3,1,5,3,13,0.0,satisfied +81375,75605,Female,Loyal Customer,70,Personal Travel,Eco,337,1,4,1,3,3,2,4,3,3,1,3,3,3,4,20,38.0,neutral or dissatisfied +81376,108426,Male,Loyal Customer,44,Business travel,Business,1444,3,3,4,3,4,5,4,4,4,4,4,3,4,4,0,3.0,satisfied +81377,48660,Male,Loyal Customer,42,Business travel,Business,77,5,5,5,5,5,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +81378,73410,Male,disloyal Customer,27,Business travel,Business,1144,5,5,5,1,3,5,3,3,4,1,4,1,3,3,0,0.0,satisfied +81379,47345,Female,Loyal Customer,22,Business travel,Business,2168,4,4,4,4,4,4,4,4,4,3,2,4,3,4,0,0.0,satisfied +81380,127643,Female,Loyal Customer,60,Personal Travel,Eco,1773,3,5,3,2,1,4,3,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +81381,92057,Female,Loyal Customer,48,Business travel,Business,1522,5,5,5,5,2,5,4,5,5,4,5,4,5,3,3,0.0,satisfied +81382,23588,Female,Loyal Customer,45,Business travel,Eco,1024,3,4,4,4,1,4,5,3,3,3,3,5,3,3,0,15.0,satisfied +81383,17837,Male,Loyal Customer,42,Personal Travel,Eco Plus,1075,5,5,5,5,5,5,5,5,4,2,4,5,5,5,15,33.0,satisfied +81384,43040,Female,Loyal Customer,63,Business travel,Business,391,2,3,3,3,1,3,3,2,2,2,2,3,2,1,9,4.0,neutral or dissatisfied +81385,49611,Female,disloyal Customer,40,Business travel,Business,238,2,2,2,3,2,2,2,2,2,5,4,2,3,2,0,0.0,neutral or dissatisfied +81386,105607,Female,Loyal Customer,52,Business travel,Business,2459,2,2,2,2,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +81387,31973,Male,Loyal Customer,46,Business travel,Business,101,0,4,0,1,3,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +81388,117941,Female,disloyal Customer,18,Business travel,Eco,601,2,4,2,3,3,2,3,3,3,5,4,2,3,3,2,0.0,neutral or dissatisfied +81389,65739,Female,Loyal Customer,50,Business travel,Business,936,2,2,2,2,5,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +81390,34070,Male,Loyal Customer,9,Personal Travel,Eco,1674,3,2,3,3,2,3,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +81391,52693,Female,Loyal Customer,59,Business travel,Eco Plus,119,3,2,2,2,2,4,3,2,2,3,2,1,2,1,0,9.0,neutral or dissatisfied +81392,129171,Female,Loyal Customer,49,Personal Travel,Eco,954,3,1,3,4,1,4,4,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +81393,92726,Male,Loyal Customer,48,Business travel,Business,1827,3,3,2,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +81394,89432,Male,Loyal Customer,11,Personal Travel,Eco,134,4,1,0,4,3,0,2,3,1,3,3,2,4,3,0,0.0,neutral or dissatisfied +81395,18260,Male,Loyal Customer,14,Personal Travel,Eco,179,3,4,3,3,2,3,2,2,5,5,4,5,3,2,16,21.0,neutral or dissatisfied +81396,34462,Female,Loyal Customer,41,Business travel,Eco Plus,228,5,3,3,3,1,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +81397,51226,Male,Loyal Customer,48,Business travel,Eco Plus,86,3,4,5,4,3,3,3,3,1,1,1,3,1,3,0,0.0,satisfied +81398,114188,Female,Loyal Customer,57,Business travel,Business,3611,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +81399,44440,Female,Loyal Customer,27,Business travel,Business,420,3,3,2,3,5,5,5,5,3,2,4,4,5,5,67,64.0,satisfied +81400,119188,Male,Loyal Customer,47,Business travel,Business,257,2,2,2,2,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +81401,24434,Female,Loyal Customer,45,Personal Travel,Eco,634,3,5,3,2,5,5,4,5,5,3,3,3,5,3,71,69.0,neutral or dissatisfied +81402,72197,Female,Loyal Customer,13,Personal Travel,Eco,594,1,3,1,2,4,1,4,4,2,1,5,4,3,4,0,0.0,neutral or dissatisfied +81403,72261,Male,Loyal Customer,50,Business travel,Business,3106,1,1,4,1,3,5,4,5,5,5,5,3,5,5,7,1.0,satisfied +81404,109718,Female,disloyal Customer,25,Business travel,Business,587,1,0,1,3,3,1,3,3,5,2,5,5,5,3,29,10.0,neutral or dissatisfied +81405,32074,Male,Loyal Customer,39,Business travel,Business,3038,5,4,5,5,1,1,2,5,5,5,5,2,5,5,0,3.0,satisfied +81406,62384,Female,disloyal Customer,11,Business travel,Business,2704,4,4,4,4,1,4,1,1,4,3,4,3,5,1,8,0.0,satisfied +81407,14959,Male,Loyal Customer,10,Personal Travel,Eco,554,3,5,3,3,4,3,4,4,3,5,4,4,4,4,0,1.0,neutral or dissatisfied +81408,99949,Female,Loyal Customer,10,Personal Travel,Eco,2237,3,4,2,2,2,1,2,3,4,3,5,2,5,2,42,75.0,neutral or dissatisfied +81409,46393,Female,Loyal Customer,54,Personal Travel,Eco,911,4,4,4,4,4,5,5,4,4,4,1,3,4,4,0,0.0,neutral or dissatisfied +81410,60227,Female,Loyal Customer,42,Business travel,Eco,1546,1,1,5,5,5,3,3,1,1,1,1,2,1,3,4,9.0,neutral or dissatisfied +81411,18707,Female,disloyal Customer,26,Business travel,Eco Plus,383,3,0,3,3,3,3,3,3,1,3,4,2,5,3,0,0.0,neutral or dissatisfied +81412,64506,Male,Loyal Customer,47,Business travel,Business,247,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +81413,95927,Female,disloyal Customer,23,Business travel,Eco,1104,2,2,2,4,3,2,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +81414,36269,Female,Loyal Customer,13,Personal Travel,Eco,728,1,2,0,3,3,0,3,3,4,3,2,1,2,3,0,8.0,neutral or dissatisfied +81415,28663,Male,Loyal Customer,17,Personal Travel,Eco,2466,5,4,5,5,4,5,4,4,4,3,5,5,4,4,0,0.0,satisfied +81416,126297,Male,Loyal Customer,37,Personal Travel,Eco,468,4,5,4,4,4,4,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +81417,6179,Male,Loyal Customer,70,Personal Travel,Eco,491,2,4,2,3,4,2,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +81418,69250,Female,disloyal Customer,35,Business travel,Business,733,1,1,1,4,5,1,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +81419,56516,Male,disloyal Customer,26,Business travel,Business,937,4,4,4,1,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +81420,68022,Female,Loyal Customer,63,Personal Travel,Eco,304,4,5,4,3,4,4,4,2,2,4,2,4,2,5,36,41.0,neutral or dissatisfied +81421,37025,Female,Loyal Customer,65,Personal Travel,Eco Plus,759,1,5,1,3,5,4,4,5,5,1,5,4,5,4,10,2.0,neutral or dissatisfied +81422,114148,Male,Loyal Customer,34,Business travel,Business,2453,3,5,5,5,4,4,3,3,3,3,3,2,3,4,2,0.0,neutral or dissatisfied +81423,32501,Female,disloyal Customer,18,Business travel,Eco,163,3,1,3,4,4,3,3,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +81424,43852,Male,disloyal Customer,20,Business travel,Eco,144,1,5,1,2,3,1,3,3,1,3,4,4,1,3,0,3.0,neutral or dissatisfied +81425,14652,Female,Loyal Customer,40,Business travel,Eco,112,4,4,4,4,4,4,4,4,3,3,1,5,4,4,0,1.0,satisfied +81426,28779,Female,disloyal Customer,37,Business travel,Business,672,1,1,1,4,4,1,3,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +81427,45568,Male,Loyal Customer,56,Business travel,Eco,956,2,4,4,4,2,2,2,2,3,3,3,3,3,2,32,18.0,neutral or dissatisfied +81428,60616,Male,disloyal Customer,25,Business travel,Eco,1201,4,4,4,4,3,4,3,3,3,2,4,4,5,3,18,0.0,satisfied +81429,36509,Female,Loyal Customer,46,Business travel,Business,3358,3,3,3,3,1,5,2,5,5,5,5,4,5,4,6,0.0,satisfied +81430,69095,Male,Loyal Customer,31,Personal Travel,Eco,1389,1,5,1,4,1,1,1,1,5,4,5,3,5,1,0,40.0,neutral or dissatisfied +81431,67118,Male,disloyal Customer,20,Business travel,Business,1121,2,1,2,4,4,2,4,4,4,5,3,2,3,4,0,7.0,neutral or dissatisfied +81432,103152,Male,disloyal Customer,25,Business travel,Business,491,2,0,2,4,5,2,5,5,4,2,5,5,5,5,47,43.0,neutral or dissatisfied +81433,119696,Female,Loyal Customer,34,Business travel,Business,1325,2,2,2,2,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +81434,17323,Female,Loyal Customer,43,Personal Travel,Eco,403,2,5,2,5,4,4,4,5,5,2,2,5,5,5,0,0.0,neutral or dissatisfied +81435,77546,Female,disloyal Customer,49,Business travel,Business,986,4,4,4,2,4,4,2,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +81436,39042,Male,Loyal Customer,7,Personal Travel,Eco,391,4,4,4,3,2,4,1,2,5,4,5,4,5,2,1,0.0,satisfied +81437,42637,Female,Loyal Customer,21,Personal Travel,Eco,386,2,1,2,3,5,2,5,5,2,3,2,3,2,5,0,12.0,neutral or dissatisfied +81438,115142,Female,Loyal Customer,55,Business travel,Business,446,4,4,4,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +81439,121812,Male,Loyal Customer,60,Business travel,Business,2160,1,1,4,1,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +81440,71885,Female,Loyal Customer,54,Personal Travel,Eco,1744,3,0,3,4,5,5,5,3,3,3,3,3,3,4,9,13.0,neutral or dissatisfied +81441,25244,Female,Loyal Customer,27,Personal Travel,Eco,925,3,3,3,4,2,3,2,2,2,5,3,1,4,2,28,10.0,neutral or dissatisfied +81442,121259,Male,disloyal Customer,38,Business travel,Eco,575,1,2,1,3,5,1,5,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +81443,79114,Male,Loyal Customer,51,Personal Travel,Eco,356,3,2,3,3,2,3,2,2,4,4,2,2,3,2,3,0.0,neutral or dissatisfied +81444,23394,Male,Loyal Customer,34,Business travel,Business,300,0,0,0,1,5,5,5,1,1,4,3,5,2,5,159,148.0,satisfied +81445,56736,Male,Loyal Customer,66,Personal Travel,Eco,997,3,2,3,3,1,3,1,1,1,2,4,1,4,1,41,71.0,neutral or dissatisfied +81446,26331,Male,Loyal Customer,29,Business travel,Business,873,3,3,3,3,4,4,4,4,2,2,3,4,2,4,30,27.0,satisfied +81447,19272,Male,Loyal Customer,27,Business travel,Business,430,2,2,2,2,4,4,4,4,2,3,1,5,2,4,1,10.0,satisfied +81448,125371,Female,disloyal Customer,29,Business travel,Eco Plus,599,2,2,2,4,2,2,1,2,3,5,4,1,3,2,30,22.0,neutral or dissatisfied +81449,7728,Female,Loyal Customer,64,Personal Travel,Eco,859,3,5,3,3,2,4,5,3,3,3,3,4,3,5,0,5.0,neutral or dissatisfied +81450,79783,Male,Loyal Customer,55,Personal Travel,Business,1005,2,5,2,1,2,5,5,4,4,2,4,1,4,2,19,24.0,neutral or dissatisfied +81451,49943,Female,Loyal Customer,54,Business travel,Eco,421,4,3,3,3,1,5,4,4,4,4,4,1,4,2,15,4.0,satisfied +81452,35541,Female,Loyal Customer,25,Personal Travel,Eco,1074,4,5,4,5,2,4,2,2,4,3,4,4,4,2,0,2.0,satisfied +81453,111830,Female,Loyal Customer,53,Business travel,Business,1605,1,1,1,1,5,4,4,5,5,5,5,3,5,3,10,0.0,satisfied +81454,74247,Female,Loyal Customer,25,Business travel,Business,1810,1,2,5,2,1,1,1,1,4,2,4,1,4,1,0,,neutral or dissatisfied +81455,119590,Female,Loyal Customer,27,Business travel,Business,1979,5,5,5,5,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +81456,57469,Female,Loyal Customer,8,Personal Travel,Eco Plus,334,2,5,2,4,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +81457,121770,Male,Loyal Customer,35,Business travel,Business,1855,1,1,2,1,3,4,4,4,4,4,4,4,4,4,0,2.0,satisfied +81458,95887,Male,Loyal Customer,26,Personal Travel,Eco,580,3,4,3,1,5,3,1,5,5,5,2,2,2,5,0,0.0,neutral or dissatisfied +81459,77352,Female,disloyal Customer,25,Business travel,Business,588,4,0,4,3,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +81460,895,Male,Loyal Customer,53,Business travel,Business,2319,4,2,4,2,5,4,4,4,4,4,4,4,4,2,13,6.0,neutral or dissatisfied +81461,7198,Female,disloyal Customer,25,Business travel,Business,135,1,5,1,3,1,1,1,1,5,2,5,3,5,1,0,5.0,neutral or dissatisfied +81462,123201,Male,Loyal Customer,51,Personal Travel,Eco,600,3,5,3,2,4,3,4,4,3,4,1,3,3,4,13,15.0,neutral or dissatisfied +81463,53723,Female,Loyal Customer,62,Personal Travel,Eco,1208,3,2,3,4,3,3,4,4,4,3,3,3,4,4,16,0.0,neutral or dissatisfied +81464,118589,Female,Loyal Customer,37,Business travel,Business,1730,4,3,3,3,1,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +81465,71346,Male,Loyal Customer,7,Personal Travel,Eco,1514,2,1,2,3,1,2,1,1,1,5,2,1,2,1,58,57.0,neutral or dissatisfied +81466,20339,Female,Loyal Customer,37,Business travel,Eco,287,5,4,4,4,5,5,5,2,1,4,2,5,1,5,237,213.0,satisfied +81467,78487,Male,Loyal Customer,28,Business travel,Eco,666,2,4,4,4,2,1,2,2,4,3,4,4,4,2,32,27.0,neutral or dissatisfied +81468,94175,Male,Loyal Customer,41,Business travel,Business,3167,0,0,0,1,2,5,4,1,1,1,1,5,1,4,28,23.0,satisfied +81469,97751,Male,Loyal Customer,72,Business travel,Eco,587,2,5,5,5,2,2,2,2,2,1,2,2,2,2,29,13.0,neutral or dissatisfied +81470,106498,Female,Loyal Customer,35,Business travel,Eco,495,4,1,1,1,4,4,4,4,2,5,5,5,4,4,2,0.0,satisfied +81471,89163,Male,Loyal Customer,41,Personal Travel,Eco,2139,4,4,3,3,3,3,1,3,4,4,5,3,5,3,6,5.0,satisfied +81472,66975,Female,disloyal Customer,26,Business travel,Business,985,2,2,2,4,2,2,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +81473,128880,Female,Loyal Customer,46,Business travel,Business,2565,5,5,5,5,4,4,4,3,2,5,5,4,3,4,0,0.0,satisfied +81474,49964,Female,Loyal Customer,17,Business travel,Business,1538,1,5,3,5,1,1,1,1,1,3,3,1,4,1,0,10.0,neutral or dissatisfied +81475,63538,Female,disloyal Customer,43,Business travel,Eco,609,3,3,3,1,1,3,1,1,1,3,4,4,5,1,0,0.0,neutral or dissatisfied +81476,95492,Male,Loyal Customer,44,Business travel,Eco Plus,239,2,3,3,3,2,2,2,2,1,3,3,2,3,2,5,0.0,neutral or dissatisfied +81477,63180,Male,Loyal Customer,43,Business travel,Business,3166,0,0,0,3,2,4,4,3,3,3,3,5,3,3,10,4.0,satisfied +81478,99238,Male,Loyal Customer,68,Personal Travel,Eco,495,4,4,4,4,3,4,1,3,1,1,3,2,4,3,27,28.0,satisfied +81479,117189,Female,Loyal Customer,65,Personal Travel,Eco,304,2,5,3,4,2,4,4,4,4,3,4,3,4,3,28,21.0,neutral or dissatisfied +81480,95412,Male,disloyal Customer,7,Personal Travel,Eco,528,2,5,2,2,2,2,2,2,5,2,4,5,5,2,16,5.0,neutral or dissatisfied +81481,87746,Female,Loyal Customer,15,Personal Travel,Business,214,3,4,3,4,5,3,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +81482,46580,Male,disloyal Customer,24,Business travel,Eco,125,0,4,0,5,0,5,5,2,5,3,5,5,3,5,185,197.0,satisfied +81483,8238,Male,Loyal Customer,64,Personal Travel,Eco,125,2,4,2,3,5,2,5,5,4,3,4,1,3,5,0,0.0,neutral or dissatisfied +81484,12130,Female,Loyal Customer,32,Personal Travel,Eco Plus,1034,3,4,3,2,1,3,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +81485,115575,Male,Loyal Customer,51,Business travel,Business,1657,2,3,2,2,4,4,5,5,5,5,5,5,5,3,0,13.0,satisfied +81486,10848,Female,Loyal Customer,9,Business travel,Business,2013,2,5,5,5,2,3,2,2,1,2,4,2,4,2,57,57.0,neutral or dissatisfied +81487,60027,Female,Loyal Customer,29,Personal Travel,Eco,937,2,4,2,4,3,2,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +81488,56955,Male,Loyal Customer,33,Business travel,Business,2565,1,2,2,2,1,1,1,1,2,5,1,3,2,1,0,0.0,neutral or dissatisfied +81489,116907,Male,disloyal Customer,26,Business travel,Business,646,4,4,4,3,1,4,1,1,3,5,4,5,5,1,0,0.0,satisfied +81490,14868,Female,Loyal Customer,32,Business travel,Business,315,4,4,4,4,4,4,4,4,1,5,3,1,2,4,0,0.0,satisfied +81491,23013,Female,Loyal Customer,49,Business travel,Eco Plus,641,4,3,3,3,5,3,2,4,4,4,4,5,4,1,0,0.0,satisfied +81492,59412,Female,Loyal Customer,19,Personal Travel,Eco,2399,3,1,3,1,3,2,3,3,5,1,2,3,2,3,204,177.0,neutral or dissatisfied +81493,108400,Female,Loyal Customer,41,Personal Travel,Eco Plus,1750,1,2,1,4,5,3,4,1,1,1,1,1,1,3,0,11.0,neutral or dissatisfied +81494,98075,Female,disloyal Customer,23,Business travel,Eco,1449,5,0,0,2,4,5,4,4,5,4,5,5,3,4,15,0.0,satisfied +81495,109328,Female,Loyal Customer,15,Personal Travel,Eco,1136,2,5,2,4,3,2,3,3,3,2,5,5,4,3,4,0.0,neutral or dissatisfied +81496,53839,Female,Loyal Customer,39,Business travel,Eco,191,1,3,3,3,1,2,1,1,2,5,4,2,4,1,0,0.0,neutral or dissatisfied +81497,10030,Female,disloyal Customer,25,Business travel,Business,630,1,5,1,1,5,1,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +81498,94812,Male,Loyal Customer,33,Business travel,Business,2722,2,4,4,4,2,2,2,2,1,3,3,1,3,2,13,12.0,neutral or dissatisfied +81499,95218,Female,Loyal Customer,38,Personal Travel,Eco,248,1,4,0,2,4,0,4,4,3,4,4,5,4,4,70,75.0,neutral or dissatisfied +81500,5110,Male,Loyal Customer,57,Personal Travel,Eco,235,4,3,4,3,4,4,4,4,2,5,3,1,3,4,7,4.0,neutral or dissatisfied +81501,92889,Female,disloyal Customer,33,Business travel,Eco,151,1,3,1,3,4,1,4,4,3,5,4,4,3,4,0,16.0,neutral or dissatisfied +81502,122629,Female,Loyal Customer,39,Personal Travel,Eco,728,3,2,3,3,4,3,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +81503,61331,Male,Loyal Customer,45,Business travel,Business,3908,1,4,1,1,2,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +81504,16951,Female,Loyal Customer,63,Personal Travel,Business,116,1,5,1,5,1,2,5,4,4,1,4,3,4,4,46,40.0,neutral or dissatisfied +81505,45093,Female,Loyal Customer,63,Personal Travel,Eco,196,1,5,1,3,2,4,4,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +81506,27650,Male,Loyal Customer,17,Business travel,Eco Plus,671,0,4,0,3,3,0,3,3,1,4,1,5,1,3,0,0.0,satisfied +81507,43398,Female,Loyal Customer,48,Personal Travel,Eco,531,1,4,3,1,4,4,5,4,4,3,4,5,4,5,0,10.0,neutral or dissatisfied +81508,117836,Male,Loyal Customer,40,Business travel,Business,2878,5,5,4,5,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +81509,2698,Male,Loyal Customer,33,Business travel,Business,2855,5,3,5,5,5,5,5,5,3,4,4,5,3,5,146,141.0,satisfied +81510,50480,Male,Loyal Customer,85,Business travel,Eco,86,2,5,5,5,2,2,2,4,1,3,3,2,2,2,65,73.0,neutral or dissatisfied +81511,122742,Male,disloyal Customer,36,Business travel,Eco,651,3,2,3,4,5,3,5,5,4,1,3,2,3,5,0,0.0,neutral or dissatisfied +81512,76522,Male,Loyal Customer,33,Business travel,Business,3407,4,4,4,4,4,4,4,4,4,5,4,5,5,4,0,14.0,satisfied +81513,12612,Male,Loyal Customer,32,Business travel,Business,802,1,1,1,1,5,5,5,5,3,1,3,4,1,5,0,0.0,satisfied +81514,29948,Male,Loyal Customer,46,Business travel,Eco,253,3,5,5,5,3,3,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +81515,75801,Male,Loyal Customer,23,Personal Travel,Eco,868,3,2,4,3,4,4,4,4,2,2,4,4,3,4,2,0.0,neutral or dissatisfied +81516,4298,Male,Loyal Customer,37,Personal Travel,Eco,502,2,4,2,3,5,2,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +81517,70793,Male,disloyal Customer,25,Business travel,Eco,328,1,4,2,3,5,2,5,5,5,4,3,2,5,5,0,4.0,neutral or dissatisfied +81518,17734,Female,disloyal Customer,37,Business travel,Eco,382,3,1,3,4,5,3,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +81519,8500,Male,Loyal Customer,48,Business travel,Business,3522,2,2,2,2,2,4,5,5,5,5,5,5,5,4,34,9.0,satisfied +81520,33110,Female,Loyal Customer,33,Personal Travel,Eco,101,1,2,0,1,4,0,4,4,4,1,2,4,1,4,0,0.0,neutral or dissatisfied +81521,104307,Male,Loyal Customer,49,Business travel,Business,3297,4,5,4,4,2,5,4,4,4,4,4,4,4,3,30,28.0,satisfied +81522,69788,Male,disloyal Customer,39,Business travel,Business,1055,3,3,3,3,2,3,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +81523,22846,Female,Loyal Customer,30,Personal Travel,Eco,170,3,1,3,1,3,3,3,3,4,3,2,1,2,3,2,1.0,neutral or dissatisfied +81524,57311,Female,Loyal Customer,41,Business travel,Business,2043,2,2,2,2,4,5,4,4,4,4,4,3,4,4,0,11.0,satisfied +81525,105666,Female,Loyal Customer,48,Business travel,Business,787,5,5,5,5,2,4,5,4,4,5,4,5,4,4,1,11.0,satisfied +81526,96379,Male,disloyal Customer,23,Business travel,Business,1407,5,5,5,4,5,5,2,5,3,2,5,4,5,5,32,24.0,satisfied +81527,106505,Male,Loyal Customer,55,Business travel,Eco Plus,495,3,2,5,2,2,3,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +81528,75057,Male,Loyal Customer,27,Personal Travel,Eco,1592,2,1,2,3,2,2,5,2,3,2,3,2,4,2,0,22.0,neutral or dissatisfied +81529,114855,Male,Loyal Customer,58,Business travel,Business,362,3,3,3,3,4,4,4,5,5,5,5,3,5,5,53,51.0,satisfied +81530,127509,Male,Loyal Customer,63,Personal Travel,Eco,2075,3,5,3,1,1,3,1,1,3,2,5,2,4,1,0,0.0,neutral or dissatisfied +81531,121862,Male,Loyal Customer,57,Business travel,Business,366,4,3,3,3,1,4,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +81532,22550,Female,Loyal Customer,45,Business travel,Business,3376,1,1,4,1,3,4,5,4,4,4,4,3,4,3,2,6.0,satisfied +81533,31053,Female,Loyal Customer,53,Business travel,Business,862,4,5,4,5,4,3,3,4,4,3,4,2,4,4,0,6.0,neutral or dissatisfied +81534,82914,Male,Loyal Customer,25,Personal Travel,Eco,594,2,1,3,3,4,3,3,4,2,5,4,3,4,4,0,0.0,neutral or dissatisfied +81535,105924,Male,Loyal Customer,47,Business travel,Business,1491,3,3,3,3,2,4,4,5,5,5,5,5,5,5,3,9.0,satisfied +81536,28467,Female,disloyal Customer,24,Business travel,Eco,2588,2,1,1,3,2,2,2,3,3,4,4,2,4,2,0,23.0,neutral or dissatisfied +81537,55068,Male,Loyal Customer,23,Business travel,Business,1635,3,3,3,3,3,3,3,3,1,3,4,3,3,3,86,72.0,neutral or dissatisfied +81538,44381,Male,Loyal Customer,33,Personal Travel,Eco,229,3,5,3,3,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +81539,17061,Male,Loyal Customer,31,Personal Travel,Eco,1134,2,5,2,3,3,2,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +81540,98281,Female,Loyal Customer,20,Business travel,Business,1136,3,3,5,3,3,3,3,3,2,1,3,1,4,3,3,15.0,neutral or dissatisfied +81541,21864,Female,Loyal Customer,41,Business travel,Business,3677,2,2,2,2,1,2,5,5,5,5,5,2,5,2,30,32.0,satisfied +81542,26684,Male,Loyal Customer,31,Personal Travel,Eco,515,5,4,5,5,3,5,3,3,5,5,4,5,4,3,0,0.0,satisfied +81543,118448,Male,Loyal Customer,60,Business travel,Business,2765,5,5,5,5,3,5,4,5,5,5,5,4,5,3,39,23.0,satisfied +81544,85183,Female,Loyal Customer,25,Business travel,Eco,731,3,4,4,4,3,2,2,3,4,5,4,3,3,3,110,115.0,neutral or dissatisfied +81545,21857,Male,Loyal Customer,46,Business travel,Business,503,2,2,2,2,3,2,2,4,4,4,4,2,4,1,0,0.0,satisfied +81546,62090,Female,Loyal Customer,51,Business travel,Business,2565,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +81547,103399,Male,Loyal Customer,74,Business travel,Business,237,2,2,2,2,2,4,4,2,2,2,2,4,2,1,2,11.0,neutral or dissatisfied +81548,3101,Female,Loyal Customer,13,Personal Travel,Eco,594,3,5,3,4,5,3,5,5,5,5,4,4,2,5,0,0.0,neutral or dissatisfied +81549,73754,Female,Loyal Customer,44,Personal Travel,Eco,204,4,1,4,2,2,2,2,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +81550,116300,Female,Loyal Customer,10,Personal Travel,Eco,446,1,4,1,3,2,1,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +81551,10094,Male,Loyal Customer,48,Personal Travel,Eco,763,2,5,2,1,2,2,2,2,3,2,4,3,4,2,63,59.0,neutral or dissatisfied +81552,12858,Female,Loyal Customer,41,Personal Travel,Eco,528,2,5,2,3,3,2,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +81553,19719,Male,Loyal Customer,30,Business travel,Business,491,4,4,5,4,3,3,3,3,1,3,5,2,2,3,0,0.0,satisfied +81554,60486,Female,Loyal Customer,44,Business travel,Business,934,2,1,1,1,2,4,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +81555,40483,Female,Loyal Customer,58,Personal Travel,Eco,175,3,4,3,2,5,4,4,4,4,3,4,3,4,5,0,1.0,neutral or dissatisfied +81556,104055,Female,Loyal Customer,41,Personal Travel,Eco,1262,2,5,2,3,4,2,4,4,4,3,3,4,4,4,8,4.0,neutral or dissatisfied +81557,11343,Male,Loyal Customer,15,Personal Travel,Eco,309,3,4,4,3,2,4,4,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +81558,70992,Male,Loyal Customer,53,Business travel,Business,802,2,2,2,2,4,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +81559,65799,Male,disloyal Customer,22,Business travel,Business,1389,4,0,4,3,2,4,2,2,4,5,4,3,4,2,85,69.0,satisfied +81560,52276,Female,disloyal Customer,34,Business travel,Eco,455,2,3,2,3,5,2,5,5,4,1,3,3,4,5,0,8.0,neutral or dissatisfied +81561,36952,Female,Loyal Customer,44,Business travel,Business,3486,1,1,5,1,2,4,4,4,4,4,4,5,4,4,1,0.0,satisfied +81562,42759,Male,Loyal Customer,42,Business travel,Business,493,4,4,4,4,1,4,2,5,5,4,5,4,5,5,0,0.0,satisfied +81563,55845,Male,disloyal Customer,20,Personal Travel,Eco,1416,4,2,4,4,3,4,3,3,1,2,3,3,4,3,0,0.0,satisfied +81564,42589,Female,Loyal Customer,56,Business travel,Business,1201,3,2,2,2,4,3,2,3,3,3,3,4,3,1,30,54.0,neutral or dissatisfied +81565,60062,Male,Loyal Customer,42,Business travel,Business,1758,5,5,5,5,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +81566,129073,Male,Loyal Customer,55,Personal Travel,Business,2218,3,3,3,3,2,5,4,2,2,3,2,5,2,1,20,11.0,neutral or dissatisfied +81567,3767,Male,Loyal Customer,47,Business travel,Business,3791,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +81568,89244,Female,Loyal Customer,69,Personal Travel,Eco Plus,1947,2,4,3,3,3,4,4,5,5,4,5,4,3,4,232,220.0,neutral or dissatisfied +81569,57086,Female,Loyal Customer,43,Personal Travel,Business,1222,2,4,2,2,2,2,3,4,4,2,4,4,4,3,7,0.0,neutral or dissatisfied +81570,111793,Female,disloyal Customer,33,Business travel,Business,349,2,1,1,2,3,1,3,3,5,5,5,3,5,3,14,15.0,neutral or dissatisfied +81571,106097,Male,Loyal Customer,44,Business travel,Business,302,5,5,5,5,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +81572,117713,Female,disloyal Customer,26,Business travel,Eco,1009,2,2,2,3,4,2,5,4,2,4,3,1,3,4,0,6.0,neutral or dissatisfied +81573,42539,Female,Loyal Customer,45,Business travel,Business,2334,3,5,3,3,3,3,4,3,3,4,3,5,3,4,18,0.0,satisfied +81574,16091,Female,Loyal Customer,25,Business travel,Eco,303,4,2,2,2,4,4,4,5,2,5,3,4,5,4,194,186.0,satisfied +81575,92767,Male,Loyal Customer,48,Business travel,Business,1671,3,3,3,3,2,3,4,5,5,5,5,3,5,4,0,20.0,satisfied +81576,2640,Female,Loyal Customer,58,Business travel,Business,3632,2,2,2,2,4,4,4,3,3,3,3,4,3,4,16,27.0,satisfied +81577,57177,Male,Loyal Customer,41,Business travel,Business,2909,3,3,3,3,5,1,5,4,4,4,4,2,4,3,0,0.0,satisfied +81578,29861,Female,disloyal Customer,22,Business travel,Business,213,0,0,1,1,2,1,2,2,1,2,5,5,2,2,0,0.0,satisfied +81579,84448,Female,Loyal Customer,45,Business travel,Business,2904,2,5,4,5,5,2,1,2,2,2,2,1,2,2,0,16.0,neutral or dissatisfied +81580,27592,Female,Loyal Customer,27,Personal Travel,Eco,956,3,4,3,3,1,3,1,1,1,4,3,3,4,1,0,0.0,neutral or dissatisfied +81581,52795,Female,Loyal Customer,38,Personal Travel,Eco,1874,2,5,2,5,3,2,3,3,4,5,2,5,1,3,0,3.0,neutral or dissatisfied +81582,37049,Male,Loyal Customer,11,Personal Travel,Eco,1105,1,4,1,4,3,1,3,3,3,3,1,2,1,3,13,5.0,neutral or dissatisfied +81583,38463,Male,Loyal Customer,41,Personal Travel,Eco Plus,1226,4,4,4,4,4,4,4,4,3,2,3,2,4,4,0,16.0,neutral or dissatisfied +81584,28235,Male,disloyal Customer,10,Business travel,Eco,1009,2,3,3,3,3,3,3,3,4,2,2,1,3,3,0,0.0,neutral or dissatisfied +81585,31485,Female,disloyal Customer,40,Business travel,Business,967,1,1,1,3,2,1,2,2,3,4,5,1,3,2,0,0.0,neutral or dissatisfied +81586,33791,Male,Loyal Customer,32,Business travel,Eco Plus,588,4,1,1,1,4,4,4,4,1,3,3,4,4,4,0,8.0,neutral or dissatisfied +81587,84457,Male,Loyal Customer,44,Business travel,Eco,290,4,5,5,5,4,4,4,4,3,3,1,3,3,4,0,0.0,satisfied +81588,89726,Male,Loyal Customer,70,Personal Travel,Eco,1035,1,5,1,3,3,1,2,3,3,5,5,3,4,3,0,27.0,neutral or dissatisfied +81589,107416,Male,Loyal Customer,60,Business travel,Business,3689,2,2,2,2,4,3,3,2,2,2,2,3,2,2,21,9.0,neutral or dissatisfied +81590,55286,Female,Loyal Customer,40,Business travel,Business,1608,2,5,5,5,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +81591,30010,Female,Loyal Customer,23,Business travel,Business,3152,2,2,2,2,2,1,2,2,2,4,2,4,3,2,29,42.0,neutral or dissatisfied +81592,79629,Male,Loyal Customer,57,Business travel,Business,3617,1,1,1,1,3,5,4,5,5,5,5,4,5,5,19,4.0,satisfied +81593,21904,Male,Loyal Customer,50,Business travel,Eco,503,2,4,4,4,2,2,2,2,4,2,2,3,5,2,67,72.0,satisfied +81594,18459,Male,Loyal Customer,41,Business travel,Business,3110,5,5,4,5,1,2,2,4,4,4,4,3,4,5,0,0.0,satisfied +81595,94442,Female,Loyal Customer,55,Business travel,Business,3244,2,4,2,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +81596,106448,Male,Loyal Customer,42,Personal Travel,Eco,1062,0,5,0,3,3,0,3,3,4,2,5,3,5,3,3,0.0,satisfied +81597,75920,Male,Loyal Customer,47,Personal Travel,Eco Plus,603,2,3,2,3,3,2,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +81598,19677,Female,disloyal Customer,38,Business travel,Eco,475,2,0,1,1,2,1,2,2,2,5,5,3,5,2,65,59.0,neutral or dissatisfied +81599,17280,Female,Loyal Customer,66,Personal Travel,Eco Plus,872,3,4,3,3,4,1,2,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +81600,3374,Male,Loyal Customer,36,Business travel,Business,3965,2,4,2,4,5,3,3,2,2,2,2,2,2,2,0,17.0,neutral or dissatisfied +81601,94170,Female,Loyal Customer,59,Business travel,Business,3187,2,1,2,2,3,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +81602,93133,Male,Loyal Customer,34,Business travel,Business,1066,1,1,1,1,2,5,5,4,4,4,4,5,4,4,27,31.0,satisfied +81603,18370,Female,Loyal Customer,27,Personal Travel,Eco,169,1,4,1,3,3,1,3,3,5,3,5,5,4,3,40,33.0,neutral or dissatisfied +81604,1355,Female,Loyal Customer,39,Business travel,Business,2805,4,4,4,4,2,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +81605,75879,Male,Loyal Customer,26,Personal Travel,Eco,1972,3,1,3,3,2,3,3,2,2,2,3,1,3,2,8,0.0,neutral or dissatisfied +81606,28858,Male,Loyal Customer,51,Business travel,Business,3433,5,5,5,5,4,5,4,5,5,5,5,4,5,2,0,0.0,satisfied +81607,23141,Male,disloyal Customer,37,Business travel,Eco,646,4,3,4,3,5,4,5,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +81608,88496,Male,Loyal Customer,46,Business travel,Eco,145,4,1,1,1,4,4,4,4,5,1,1,3,4,4,0,0.0,satisfied +81609,94259,Male,disloyal Customer,49,Business travel,Business,248,3,2,2,4,5,3,5,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +81610,44920,Female,Loyal Customer,15,Personal Travel,Eco,416,1,4,1,4,4,1,4,4,2,3,3,2,4,4,56,125.0,neutral or dissatisfied +81611,48670,Female,Loyal Customer,53,Business travel,Business,78,3,3,3,3,5,5,4,5,5,5,5,5,5,3,32,24.0,satisfied +81612,33580,Female,Loyal Customer,62,Business travel,Eco,399,3,1,1,1,5,1,1,3,3,3,3,2,3,4,63,51.0,neutral or dissatisfied +81613,56727,Male,Loyal Customer,50,Personal Travel,Eco,1023,1,2,2,1,3,2,3,3,3,2,1,4,1,3,0,0.0,neutral or dissatisfied +81614,47581,Male,Loyal Customer,10,Personal Travel,Business,1428,2,2,2,4,2,2,2,2,2,2,4,2,3,2,0,7.0,neutral or dissatisfied +81615,23554,Female,Loyal Customer,25,Business travel,Eco,533,5,2,2,2,5,5,5,5,1,2,4,5,1,5,51,36.0,satisfied +81616,116888,Male,Loyal Customer,55,Business travel,Business,304,0,0,0,2,2,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +81617,22628,Male,Loyal Customer,53,Personal Travel,Eco,223,3,4,3,3,5,3,5,5,3,5,4,2,3,5,57,87.0,neutral or dissatisfied +81618,52023,Female,Loyal Customer,25,Business travel,Eco,328,4,2,2,2,4,4,4,4,1,4,3,4,5,4,0,0.0,satisfied +81619,46808,Male,disloyal Customer,32,Business travel,Eco,853,2,2,2,4,2,2,2,2,5,2,3,5,4,2,1,0.0,neutral or dissatisfied +81620,77871,Male,disloyal Customer,9,Business travel,Eco,1262,4,4,4,3,4,4,4,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +81621,77207,Male,Loyal Customer,33,Personal Travel,Eco,2994,3,4,3,4,3,4,4,5,2,5,5,4,5,4,0,0.0,neutral or dissatisfied +81622,35226,Male,Loyal Customer,36,Business travel,Business,1080,3,3,3,3,1,1,5,2,2,2,2,5,2,1,16,31.0,satisfied +81623,98960,Male,Loyal Customer,35,Business travel,Business,3529,2,1,1,1,3,3,3,2,2,2,2,2,2,4,4,0.0,neutral or dissatisfied +81624,1532,Female,Loyal Customer,43,Business travel,Business,3836,2,5,5,5,4,4,4,2,2,2,2,3,2,1,4,0.0,neutral or dissatisfied +81625,96664,Male,disloyal Customer,25,Personal Travel,Eco,937,3,5,3,3,5,3,5,5,3,5,4,3,4,5,0,0.0,neutral or dissatisfied +81626,23998,Male,Loyal Customer,47,Business travel,Eco,427,4,3,4,4,4,4,4,4,4,5,1,1,5,4,0,0.0,satisfied +81627,75463,Female,Loyal Customer,34,Personal Travel,Eco,2585,1,5,1,1,4,1,4,4,1,5,4,1,5,4,0,0.0,neutral or dissatisfied +81628,5115,Male,Loyal Customer,7,Personal Travel,Eco,137,2,1,0,4,5,0,5,5,1,2,3,4,4,5,19,43.0,neutral or dissatisfied +81629,28220,Female,disloyal Customer,20,Business travel,Eco Plus,473,2,4,2,1,2,2,2,2,3,4,1,1,1,2,0,0.0,neutral or dissatisfied +81630,45862,Male,Loyal Customer,57,Business travel,Business,563,1,1,1,1,4,4,5,5,5,5,5,3,5,4,19,20.0,satisfied +81631,128657,Male,Loyal Customer,29,Business travel,Business,2288,2,2,2,2,4,4,4,3,2,5,4,4,5,4,5,56.0,satisfied +81632,100292,Female,disloyal Customer,27,Business travel,Business,1073,2,2,2,2,5,2,5,5,4,3,4,4,5,5,0,3.0,neutral or dissatisfied +81633,62672,Male,Loyal Customer,59,Business travel,Business,1744,2,2,2,2,5,4,5,5,5,5,5,4,5,5,15,25.0,satisfied +81634,77821,Female,Loyal Customer,42,Personal Travel,Eco,696,3,5,3,4,5,4,5,5,5,3,2,5,5,5,0,0.0,neutral or dissatisfied +81635,7900,Male,Loyal Customer,24,Business travel,Business,3116,3,3,3,3,5,5,5,5,5,4,5,4,4,5,0,33.0,satisfied +81636,69363,Female,Loyal Customer,40,Business travel,Business,2896,1,1,1,1,5,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +81637,122074,Female,Loyal Customer,25,Personal Travel,Eco,130,4,3,4,3,1,4,1,1,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +81638,36122,Female,Loyal Customer,36,Business travel,Business,1562,1,1,1,1,3,3,2,4,4,4,4,3,4,3,0,0.0,satisfied +81639,118899,Female,Loyal Customer,22,Business travel,Business,587,2,4,4,4,2,2,2,2,1,3,4,3,4,2,6,15.0,neutral or dissatisfied +81640,17019,Male,Loyal Customer,31,Business travel,Business,3680,2,1,1,1,2,2,2,2,1,3,3,1,4,2,0,1.0,neutral or dissatisfied +81641,96194,Male,Loyal Customer,55,Business travel,Business,328,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +81642,106628,Male,Loyal Customer,47,Business travel,Eco,306,4,3,3,3,4,4,4,4,1,2,3,2,3,4,60,89.0,neutral or dissatisfied +81643,93949,Male,Loyal Customer,23,Personal Travel,Eco,507,2,2,2,3,5,2,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +81644,29366,Female,disloyal Customer,27,Business travel,Eco,838,3,3,3,2,3,3,3,3,2,5,3,2,5,3,0,0.0,neutral or dissatisfied +81645,123665,Female,Loyal Customer,52,Business travel,Eco,214,2,5,5,5,5,4,4,2,2,2,2,3,2,2,0,30.0,neutral or dissatisfied +81646,54043,Male,Loyal Customer,26,Business travel,Business,1416,5,5,5,5,4,4,4,4,3,4,1,1,1,4,93,70.0,satisfied +81647,10206,Female,disloyal Customer,44,Business travel,Business,166,5,5,5,1,4,5,4,4,3,5,5,3,5,4,44,48.0,satisfied +81648,111057,Female,Loyal Customer,39,Personal Travel,Eco,197,4,2,4,3,4,4,4,4,3,3,4,3,3,4,0,0.0,satisfied +81649,25978,Male,Loyal Customer,41,Business travel,Business,2714,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +81650,100453,Male,Loyal Customer,42,Business travel,Business,580,2,2,2,2,3,5,4,3,3,3,3,3,3,5,16,8.0,satisfied +81651,46686,Male,Loyal Customer,20,Personal Travel,Eco,125,4,2,4,3,1,4,1,1,1,2,4,4,4,1,53,55.0,satisfied +81652,113837,Female,Loyal Customer,14,Personal Travel,Eco Plus,397,1,5,1,2,2,1,2,2,3,5,5,5,4,2,88,86.0,neutral or dissatisfied +81653,89940,Male,Loyal Customer,17,Personal Travel,Eco,1306,1,5,1,2,4,1,4,4,5,3,4,4,4,4,1,0.0,neutral or dissatisfied +81654,17977,Male,Loyal Customer,42,Business travel,Business,332,1,1,1,1,2,4,4,5,5,5,5,4,5,3,0,29.0,satisfied +81655,15257,Male,Loyal Customer,15,Personal Travel,Eco,416,4,1,4,3,5,4,1,5,4,4,3,3,2,5,0,0.0,satisfied +81656,39622,Female,Loyal Customer,28,Personal Travel,Eco,748,1,3,2,3,5,2,5,5,5,4,1,3,3,5,0,0.0,neutral or dissatisfied +81657,67241,Female,Loyal Customer,57,Personal Travel,Eco,918,4,5,4,3,2,4,4,1,1,4,1,5,1,3,1,0.0,neutral or dissatisfied +81658,2602,Female,Loyal Customer,43,Personal Travel,Eco,280,2,0,2,4,4,5,5,1,1,2,1,4,1,3,4,2.0,neutral or dissatisfied +81659,12433,Male,Loyal Customer,40,Personal Travel,Eco,190,1,5,1,2,3,1,3,3,3,2,5,3,5,3,0,3.0,neutral or dissatisfied +81660,12969,Female,Loyal Customer,21,Personal Travel,Eco Plus,979,0,5,0,4,4,0,4,4,4,5,4,5,5,4,0,0.0,satisfied +81661,54961,Male,Loyal Customer,41,Business travel,Business,1635,2,2,5,2,4,3,4,4,4,5,4,5,4,3,5,0.0,satisfied +81662,59911,Female,disloyal Customer,35,Business travel,Business,1065,2,2,2,5,5,2,3,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +81663,61918,Male,Loyal Customer,19,Business travel,Business,2630,1,4,4,4,1,1,1,1,2,5,4,3,4,1,1,4.0,neutral or dissatisfied +81664,61212,Female,Loyal Customer,42,Business travel,Business,3973,1,1,1,1,4,5,5,2,2,2,2,3,2,5,1,0.0,satisfied +81665,11047,Male,Loyal Customer,35,Personal Travel,Eco,308,4,5,3,3,5,3,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +81666,93718,Male,Loyal Customer,30,Business travel,Business,630,5,5,4,5,4,4,4,4,3,3,5,3,4,4,0,0.0,satisfied +81667,85990,Female,disloyal Customer,18,Business travel,Business,447,4,2,4,4,2,4,2,2,4,3,4,4,5,2,0,0.0,satisfied +81668,50857,Male,Loyal Customer,55,Personal Travel,Eco,209,3,3,0,3,4,0,4,4,4,1,4,3,3,4,75,73.0,neutral or dissatisfied +81669,121361,Female,Loyal Customer,57,Business travel,Business,1670,5,5,5,5,3,3,4,3,3,3,3,4,3,3,10,17.0,satisfied +81670,121528,Female,Loyal Customer,40,Business travel,Business,912,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +81671,100758,Female,disloyal Customer,38,Business travel,Business,1411,4,4,4,1,5,4,5,5,5,4,4,4,4,5,0,0.0,satisfied +81672,21091,Male,Loyal Customer,50,Business travel,Business,152,4,4,4,4,1,1,1,4,4,4,3,4,4,3,0,0.0,satisfied +81673,121350,Male,Loyal Customer,22,Personal Travel,Eco,430,5,5,5,3,2,5,2,2,4,4,5,5,4,2,0,0.0,satisfied +81674,43124,Female,disloyal Customer,23,Business travel,Eco Plus,391,4,1,4,3,2,4,2,2,5,1,3,3,4,2,0,0.0,satisfied +81675,6905,Male,Loyal Customer,44,Personal Travel,Eco,287,2,2,2,2,4,2,4,4,4,2,3,3,3,4,43,39.0,neutral or dissatisfied +81676,98480,Male,Loyal Customer,55,Business travel,Business,1888,2,2,1,1,5,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +81677,129136,Male,disloyal Customer,29,Business travel,Business,679,2,2,2,2,1,2,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +81678,69435,Male,Loyal Customer,29,Personal Travel,Eco,1096,4,5,4,1,1,4,2,1,4,1,5,3,3,1,0,0.0,neutral or dissatisfied +81679,90448,Male,Loyal Customer,41,Business travel,Business,3381,3,3,3,3,5,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +81680,25347,Male,Loyal Customer,38,Business travel,Business,2775,2,2,2,2,5,5,5,5,5,5,5,4,5,2,0,0.0,satisfied +81681,18097,Male,Loyal Customer,54,Personal Travel,Eco Plus,488,3,0,3,2,3,3,4,3,5,3,5,3,4,3,28,16.0,neutral or dissatisfied +81682,112753,Male,Loyal Customer,42,Business travel,Business,3446,4,4,4,4,2,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +81683,19673,Male,disloyal Customer,29,Business travel,Eco,409,3,0,3,4,1,3,1,1,1,4,4,5,3,1,40,34.0,neutral or dissatisfied +81684,19412,Female,Loyal Customer,33,Business travel,Business,645,2,2,4,2,3,1,4,5,5,5,5,1,5,2,0,0.0,satisfied +81685,33707,Male,disloyal Customer,28,Business travel,Business,359,3,2,2,4,1,2,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +81686,7508,Male,Loyal Customer,46,Personal Travel,Business,762,3,4,3,4,3,5,4,1,1,3,1,4,1,3,40,66.0,neutral or dissatisfied +81687,90574,Male,Loyal Customer,60,Business travel,Business,581,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +81688,38389,Female,Loyal Customer,56,Personal Travel,Eco Plus,1111,3,4,3,3,5,5,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +81689,37316,Male,Loyal Customer,45,Business travel,Eco,1069,5,2,2,2,5,5,5,5,2,4,5,5,1,5,19,25.0,satisfied +81690,33997,Female,disloyal Customer,35,Business travel,Eco,1617,1,1,1,2,4,1,4,4,3,2,3,3,2,4,14,1.0,neutral or dissatisfied +81691,23403,Male,Loyal Customer,27,Personal Travel,Eco,300,1,2,1,4,5,1,5,5,2,1,3,1,3,5,10,13.0,neutral or dissatisfied +81692,33566,Female,Loyal Customer,59,Business travel,Business,413,1,1,1,1,4,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +81693,12946,Male,Loyal Customer,26,Personal Travel,Eco,775,1,4,1,5,5,1,5,5,2,2,5,5,4,5,54,44.0,neutral or dissatisfied +81694,123601,Female,Loyal Customer,63,Personal Travel,Eco,1773,3,5,3,2,2,4,1,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +81695,97119,Female,Loyal Customer,40,Business travel,Eco,1357,4,5,5,5,4,4,4,4,4,5,4,1,3,4,2,0.0,neutral or dissatisfied +81696,41886,Female,Loyal Customer,45,Business travel,Business,129,4,4,3,4,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +81697,79326,Male,disloyal Customer,29,Business travel,Business,1020,2,2,2,3,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +81698,110204,Female,disloyal Customer,40,Business travel,Business,588,3,3,3,1,1,3,1,1,3,2,4,5,5,1,11,9.0,neutral or dissatisfied +81699,5998,Female,Loyal Customer,50,Business travel,Business,691,2,2,2,2,3,4,4,4,4,4,4,4,4,3,5,20.0,satisfied +81700,36532,Male,Loyal Customer,41,Business travel,Eco,1249,4,1,4,1,4,4,4,4,1,1,3,3,1,4,0,0.0,satisfied +81701,60196,Male,Loyal Customer,23,Business travel,Business,1709,2,2,2,2,5,5,5,5,4,4,5,4,5,5,27,22.0,satisfied +81702,119073,Female,Loyal Customer,49,Business travel,Business,3720,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +81703,32577,Male,disloyal Customer,17,Business travel,Eco,101,1,0,1,2,1,1,1,1,2,1,1,1,4,1,0,0.0,neutral or dissatisfied +81704,74567,Male,Loyal Customer,48,Business travel,Business,1205,4,3,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +81705,81836,Male,Loyal Customer,48,Personal Travel,Eco,1306,1,4,1,2,2,1,2,2,3,3,4,3,5,2,37,41.0,neutral or dissatisfied +81706,120081,Male,Loyal Customer,50,Personal Travel,Eco,683,2,5,2,2,1,2,1,1,4,4,5,4,4,1,0,20.0,neutral or dissatisfied +81707,76548,Female,Loyal Customer,50,Business travel,Business,547,3,3,3,3,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +81708,38407,Male,Loyal Customer,36,Business travel,Eco Plus,254,5,4,4,4,5,4,5,5,2,2,3,1,3,5,15,0.0,satisfied +81709,15840,Male,disloyal Customer,26,Business travel,Business,1107,0,0,0,2,3,0,3,3,2,4,4,5,2,3,12,0.0,satisfied +81710,33309,Male,Loyal Customer,60,Business travel,Eco Plus,102,3,2,2,2,3,3,3,3,1,2,4,4,3,3,0,5.0,neutral or dissatisfied +81711,87308,Male,Loyal Customer,26,Personal Travel,Eco,577,1,5,1,3,3,1,2,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +81712,91743,Male,Loyal Customer,45,Business travel,Business,1908,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +81713,85527,Female,disloyal Customer,40,Business travel,Business,259,4,4,4,3,5,4,5,5,3,3,4,5,5,5,0,0.0,satisfied +81714,10247,Female,Loyal Customer,47,Personal Travel,Business,201,4,5,4,5,2,4,1,1,1,4,1,2,1,5,0,0.0,neutral or dissatisfied +81715,65573,Female,Loyal Customer,57,Business travel,Business,237,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +81716,17489,Male,Loyal Customer,36,Business travel,Business,3297,2,2,2,2,1,3,2,4,4,4,4,2,4,2,34,17.0,satisfied +81717,23624,Female,Loyal Customer,33,Business travel,Business,2140,2,3,2,2,5,5,5,3,3,4,3,5,3,3,0,17.0,satisfied +81718,30737,Female,Loyal Customer,60,Business travel,Business,2109,2,2,3,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +81719,33231,Male,Loyal Customer,64,Business travel,Eco Plus,101,2,1,4,1,2,2,2,2,2,4,4,2,3,2,0,4.0,neutral or dissatisfied +81720,24670,Female,Loyal Customer,11,Personal Travel,Eco Plus,834,3,4,3,5,1,3,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +81721,106077,Female,Loyal Customer,52,Business travel,Business,3458,1,1,1,1,4,5,4,4,4,4,4,4,4,5,22,18.0,satisfied +81722,74595,Male,Loyal Customer,50,Business travel,Business,1438,5,5,5,5,2,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +81723,120794,Male,Loyal Customer,53,Business travel,Eco Plus,278,4,4,3,4,4,4,4,4,4,3,5,3,4,4,74,83.0,satisfied +81724,60184,Male,Loyal Customer,39,Business travel,Business,1197,2,2,2,2,4,5,4,4,4,4,4,5,4,3,39,1.0,satisfied +81725,26447,Male,Loyal Customer,47,Business travel,Eco,842,5,1,1,1,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +81726,59852,Female,Loyal Customer,23,Business travel,Business,1068,1,3,3,3,1,1,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +81727,42294,Male,Loyal Customer,37,Business travel,Eco,150,4,3,3,3,4,4,4,4,2,3,4,5,2,4,0,5.0,satisfied +81728,10063,Female,Loyal Customer,50,Business travel,Business,2154,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +81729,44652,Male,Loyal Customer,34,Business travel,Business,3066,4,4,4,4,3,1,4,3,3,4,3,1,3,2,0,4.0,satisfied +81730,943,Male,Loyal Customer,57,Business travel,Business,2491,3,3,3,3,5,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +81731,4198,Male,Loyal Customer,8,Personal Travel,Eco Plus,427,3,4,3,4,2,3,2,2,5,3,4,1,1,2,0,14.0,neutral or dissatisfied +81732,88764,Female,disloyal Customer,40,Business travel,Business,240,3,3,3,4,3,3,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +81733,69733,Female,Loyal Customer,10,Personal Travel,Eco,1372,4,4,4,1,3,4,2,3,4,3,3,3,5,3,0,2.0,neutral or dissatisfied +81734,21315,Male,Loyal Customer,29,Business travel,Eco Plus,692,4,3,3,3,4,4,4,4,1,4,3,1,4,4,0,0.0,satisfied +81735,18849,Female,Loyal Customer,56,Business travel,Business,3675,1,1,1,1,1,2,1,5,5,5,5,5,5,1,0,0.0,satisfied +81736,120159,Male,Loyal Customer,61,Personal Travel,Eco,2378,3,5,3,3,1,3,1,1,3,2,5,4,5,1,1,0.0,neutral or dissatisfied +81737,107109,Male,Loyal Customer,55,Business travel,Business,842,5,5,5,5,3,5,5,4,4,4,4,3,4,3,2,0.0,satisfied +81738,25566,Female,disloyal Customer,32,Business travel,Eco,874,2,2,2,1,4,2,4,4,4,5,3,3,3,4,24,22.0,neutral or dissatisfied +81739,39655,Male,Loyal Customer,36,Personal Travel,Eco,1136,2,4,2,3,1,2,1,1,2,3,2,4,3,1,0,9.0,neutral or dissatisfied +81740,98705,Male,Loyal Customer,57,Business travel,Business,3387,5,5,5,5,4,4,5,4,4,4,4,3,4,5,14,21.0,satisfied +81741,75169,Female,Loyal Customer,50,Business travel,Business,1744,1,1,2,1,5,2,1,1,1,1,1,4,1,1,0,28.0,neutral or dissatisfied +81742,93616,Male,disloyal Customer,30,Business travel,Eco,577,2,3,2,3,5,2,5,5,3,5,3,3,4,5,10,17.0,neutral or dissatisfied +81743,70756,Female,disloyal Customer,25,Business travel,Business,733,1,5,2,1,4,2,4,4,4,2,5,3,5,4,0,0.0,neutral or dissatisfied +81744,86070,Male,Loyal Customer,20,Business travel,Eco Plus,432,1,4,4,4,1,1,1,1,4,3,4,1,3,1,31,30.0,neutral or dissatisfied +81745,85230,Male,disloyal Customer,38,Business travel,Eco,331,4,4,4,4,3,4,1,3,4,4,4,2,2,3,0,0.0,neutral or dissatisfied +81746,73309,Male,Loyal Customer,14,Business travel,Business,3796,2,2,3,3,2,2,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +81747,14010,Female,Loyal Customer,48,Personal Travel,Eco,615,2,2,2,3,2,3,4,5,5,2,5,2,5,3,11,15.0,neutral or dissatisfied +81748,36704,Male,Loyal Customer,60,Personal Travel,Eco,1197,4,5,4,1,2,4,4,2,4,5,4,3,5,2,0,7.0,neutral or dissatisfied +81749,62468,Female,Loyal Customer,38,Business travel,Business,1744,5,5,5,5,2,3,5,5,5,5,5,4,5,3,28,16.0,satisfied +81750,109470,Male,Loyal Customer,48,Business travel,Business,861,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +81751,27418,Male,disloyal Customer,49,Business travel,Eco,1050,1,1,1,2,3,1,2,3,4,4,3,3,3,3,5,0.0,neutral or dissatisfied +81752,62527,Female,disloyal Customer,26,Business travel,Business,1744,0,0,0,4,2,0,2,2,5,4,3,4,4,2,18,0.0,satisfied +81753,60335,Male,disloyal Customer,24,Business travel,Business,1024,0,3,0,3,2,0,2,2,3,5,4,4,5,2,0,0.0,satisfied +81754,87578,Female,Loyal Customer,46,Personal Travel,Eco,432,1,4,1,1,4,4,4,2,2,1,3,4,2,4,0,0.0,neutral or dissatisfied +81755,59347,Male,Loyal Customer,55,Business travel,Eco,2399,3,4,4,4,3,3,3,3,3,4,1,3,3,3,22,2.0,neutral or dissatisfied +81756,120565,Female,Loyal Customer,35,Personal Travel,Eco,2176,2,3,2,4,2,2,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +81757,63785,Female,Loyal Customer,33,Business travel,Business,1721,1,1,1,1,3,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +81758,114827,Female,Loyal Customer,45,Business travel,Business,2627,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,3.0,satisfied +81759,77061,Female,Loyal Customer,53,Business travel,Business,991,5,5,5,5,3,4,5,5,5,5,5,5,5,5,13,0.0,satisfied +81760,70320,Male,Loyal Customer,26,Business travel,Eco,1501,3,4,4,4,3,3,2,3,3,5,2,1,3,3,0,0.0,neutral or dissatisfied +81761,76706,Male,Loyal Customer,50,Personal Travel,Eco,547,5,2,5,4,5,5,5,5,3,2,2,1,3,5,0,0.0,satisfied +81762,123719,Female,Loyal Customer,21,Personal Travel,Eco,214,1,3,1,3,2,1,3,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +81763,27365,Female,disloyal Customer,23,Business travel,Eco,671,3,4,4,4,3,4,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +81764,120362,Female,disloyal Customer,62,Business travel,Business,366,1,1,1,1,1,1,4,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +81765,77175,Female,Loyal Customer,51,Personal Travel,Eco,1355,1,4,0,4,5,4,3,5,5,0,5,2,5,4,0,0.0,neutral or dissatisfied +81766,102325,Female,disloyal Customer,65,Business travel,Eco,258,1,2,1,4,4,1,4,4,1,4,3,1,3,4,1,0.0,neutral or dissatisfied +81767,114474,Female,disloyal Customer,35,Business travel,Business,417,2,2,2,4,4,2,2,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +81768,38822,Male,Loyal Customer,39,Personal Travel,Eco,353,4,4,4,5,5,4,5,5,2,5,1,5,2,5,0,0.0,neutral or dissatisfied +81769,46077,Male,Loyal Customer,44,Business travel,Eco,541,4,2,2,2,5,4,5,5,4,1,1,5,4,5,6,10.0,satisfied +81770,19031,Male,Loyal Customer,9,Personal Travel,Eco,871,3,3,3,4,5,3,5,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +81771,113408,Female,Loyal Customer,51,Business travel,Business,2397,0,0,0,5,5,5,4,3,3,3,3,3,3,3,3,4.0,satisfied +81772,12593,Female,Loyal Customer,46,Business travel,Eco,542,3,2,2,2,2,3,2,3,3,3,3,1,3,3,105,111.0,neutral or dissatisfied +81773,109536,Male,Loyal Customer,64,Personal Travel,Eco,951,5,2,5,3,3,5,1,3,1,1,3,3,3,3,85,83.0,satisfied +81774,117864,Male,Loyal Customer,68,Personal Travel,Business,255,2,5,2,5,4,3,4,5,5,2,5,3,5,2,5,1.0,neutral or dissatisfied +81775,73175,Male,disloyal Customer,28,Business travel,Business,1258,4,5,5,3,2,5,2,2,3,5,5,3,4,2,0,0.0,satisfied +81776,54941,Female,Loyal Customer,48,Business travel,Business,1635,1,1,1,1,4,3,5,2,2,2,2,3,2,4,0,0.0,satisfied +81777,37821,Female,disloyal Customer,42,Business travel,Business,937,3,2,2,5,5,3,3,5,4,2,4,4,4,5,5,0.0,neutral or dissatisfied +81778,75277,Male,Loyal Customer,60,Personal Travel,Eco,1652,1,1,1,3,3,1,3,3,3,5,2,4,3,3,58,37.0,neutral or dissatisfied +81779,78108,Female,Loyal Customer,53,Business travel,Business,2853,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +81780,45010,Female,Loyal Customer,31,Personal Travel,Eco,222,3,1,3,3,2,3,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +81781,93540,Male,Loyal Customer,11,Personal Travel,Eco Plus,1315,3,5,3,3,1,3,1,1,3,4,3,5,4,1,0,0.0,neutral or dissatisfied +81782,69097,Female,Loyal Customer,21,Personal Travel,Eco,1521,2,3,2,3,2,5,5,2,5,1,3,5,2,5,139,151.0,neutral or dissatisfied +81783,69111,Female,disloyal Customer,23,Business travel,Eco,1389,2,2,2,4,5,2,5,5,4,3,4,3,3,5,0,18.0,neutral or dissatisfied +81784,21817,Male,Loyal Customer,59,Personal Travel,Eco,341,5,2,4,3,4,4,1,4,4,3,3,4,3,4,0,0.0,satisfied +81785,100061,Male,Loyal Customer,22,Personal Travel,Eco,289,3,4,3,2,5,3,2,5,4,3,5,4,4,5,3,5.0,neutral or dissatisfied +81786,110503,Female,Loyal Customer,54,Business travel,Business,919,2,4,2,2,2,4,5,4,4,5,4,5,4,4,16,3.0,satisfied +81787,17388,Female,Loyal Customer,52,Business travel,Business,2953,2,2,2,2,3,4,5,5,5,5,5,4,5,5,10,2.0,satisfied +81788,62925,Male,Loyal Customer,40,Business travel,Business,2285,1,1,1,1,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +81789,4962,Male,Loyal Customer,18,Personal Travel,Eco,931,3,3,3,2,1,3,1,1,3,4,2,3,2,1,0,0.0,neutral or dissatisfied +81790,65987,Male,Loyal Customer,57,Business travel,Business,1372,3,3,3,3,4,4,5,4,4,4,4,5,4,3,31,0.0,satisfied +81791,122396,Female,Loyal Customer,20,Personal Travel,Eco,529,2,4,1,3,3,1,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +81792,54596,Female,Loyal Customer,55,Business travel,Business,2051,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,10.0,satisfied +81793,83334,Female,Loyal Customer,17,Personal Travel,Eco,2105,1,0,1,3,2,1,2,2,4,2,5,3,5,2,0,13.0,neutral or dissatisfied +81794,69033,Female,Loyal Customer,54,Business travel,Business,1389,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +81795,121289,Male,Loyal Customer,55,Personal Travel,Eco,2282,2,3,2,5,5,2,5,5,5,2,5,2,1,5,0,15.0,neutral or dissatisfied +81796,92769,Male,Loyal Customer,46,Business travel,Business,1671,3,3,3,3,5,4,5,4,4,4,4,5,4,4,2,0.0,satisfied +81797,57828,Female,Loyal Customer,14,Personal Travel,Eco,622,2,4,1,1,4,1,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +81798,10645,Male,Loyal Customer,50,Business travel,Business,2347,4,4,4,4,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +81799,25948,Male,Loyal Customer,39,Business travel,Business,1699,2,2,2,2,2,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +81800,45295,Female,Loyal Customer,26,Business travel,Business,222,2,2,2,2,5,5,5,5,4,4,5,3,2,5,0,0.0,satisfied +81801,122855,Male,Loyal Customer,40,Business travel,Business,226,4,4,4,4,5,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +81802,42404,Male,Loyal Customer,43,Business travel,Eco Plus,817,5,3,5,5,5,5,5,5,2,3,5,2,4,5,0,0.0,satisfied +81803,36744,Male,Loyal Customer,30,Business travel,Business,2611,2,2,4,2,5,4,4,3,3,3,5,4,3,4,0,2.0,satisfied +81804,74408,Male,Loyal Customer,31,Business travel,Eco,1464,3,5,5,5,3,3,3,3,1,2,3,3,4,3,0,0.0,neutral or dissatisfied +81805,12613,Female,disloyal Customer,14,Business travel,Eco,802,4,4,4,3,4,4,2,4,3,1,3,4,2,4,30,24.0,neutral or dissatisfied +81806,27824,Male,Loyal Customer,43,Business travel,Business,1048,3,4,4,4,1,1,1,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +81807,46386,Male,Loyal Customer,40,Business travel,Business,1013,4,3,3,3,2,4,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +81808,95422,Male,Loyal Customer,65,Business travel,Business,187,2,2,2,2,3,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +81809,98016,Female,Loyal Customer,39,Business travel,Business,1014,2,2,2,2,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +81810,117374,Female,Loyal Customer,20,Personal Travel,Eco Plus,296,2,4,2,1,3,2,3,3,3,4,4,5,4,3,0,5.0,neutral or dissatisfied +81811,20630,Male,Loyal Customer,39,Business travel,Business,1797,2,2,2,2,4,5,5,4,4,4,4,4,4,1,0,0.0,satisfied +81812,22833,Female,Loyal Customer,30,Business travel,Eco,170,2,5,5,5,2,2,2,2,3,1,4,2,4,2,41,30.0,neutral or dissatisfied +81813,6470,Male,Loyal Customer,58,Personal Travel,Eco Plus,296,0,4,0,3,3,0,3,3,3,2,4,3,4,3,0,0.0,satisfied +81814,15762,Female,disloyal Customer,24,Business travel,Eco,254,0,0,0,4,4,0,4,4,4,2,4,3,5,4,0,0.0,satisfied +81815,11906,Male,Loyal Customer,31,Business travel,Business,1516,3,2,4,4,3,2,3,3,2,1,3,2,4,3,36,35.0,neutral or dissatisfied +81816,28195,Female,Loyal Customer,35,Personal Travel,Eco,834,1,5,1,4,4,1,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +81817,63717,Female,Loyal Customer,58,Business travel,Business,1660,4,4,4,4,2,4,4,4,4,4,4,4,4,4,44,16.0,satisfied +81818,1212,Male,Loyal Customer,51,Personal Travel,Eco,164,2,5,2,3,3,2,3,3,3,5,5,5,5,3,4,0.0,neutral or dissatisfied +81819,125103,Female,Loyal Customer,35,Business travel,Eco,361,1,5,5,5,1,1,1,1,2,2,3,2,3,1,5,24.0,neutral or dissatisfied +81820,74210,Female,Loyal Customer,25,Personal Travel,Eco Plus,641,2,5,3,1,1,3,1,1,4,3,5,4,5,1,1,0.0,neutral or dissatisfied +81821,83731,Female,Loyal Customer,14,Personal Travel,Eco,1027,4,1,4,3,2,4,4,2,3,5,3,1,3,2,0,3.0,satisfied +81822,95947,Male,Loyal Customer,31,Business travel,Business,2402,3,3,3,3,2,2,2,2,3,3,4,5,5,2,15,14.0,satisfied +81823,116035,Female,Loyal Customer,32,Personal Travel,Eco,480,2,5,2,4,2,2,2,2,5,5,3,3,2,2,130,131.0,neutral or dissatisfied +81824,114614,Male,Loyal Customer,40,Business travel,Business,404,3,3,4,3,5,5,4,3,3,3,3,5,3,3,40,37.0,satisfied +81825,47544,Male,Loyal Customer,14,Business travel,Eco Plus,590,4,5,5,5,4,4,3,4,3,3,1,5,2,4,0,0.0,satisfied +81826,29374,Female,disloyal Customer,10,Business travel,Eco,885,3,2,2,3,3,2,2,4,3,3,4,2,3,2,0,49.0,neutral or dissatisfied +81827,66509,Female,Loyal Customer,49,Personal Travel,Eco,447,0,5,0,2,3,5,5,2,2,0,5,5,2,5,0,0.0,satisfied +81828,122176,Male,Loyal Customer,46,Business travel,Business,3486,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +81829,41572,Male,Loyal Customer,46,Personal Travel,Eco,1242,2,4,2,4,2,2,2,2,4,3,5,4,4,2,6,0.0,neutral or dissatisfied +81830,10753,Male,disloyal Customer,37,Business travel,Business,224,3,3,3,2,3,3,1,3,1,3,3,1,2,3,0,0.0,neutral or dissatisfied +81831,6,Male,Loyal Customer,43,Business travel,Business,3788,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +81832,28119,Male,Loyal Customer,37,Business travel,Business,2012,2,3,3,3,2,2,3,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +81833,102144,Female,Loyal Customer,42,Business travel,Business,2151,3,3,3,3,4,4,4,5,5,5,5,3,5,3,17,13.0,satisfied +81834,77364,Female,disloyal Customer,30,Business travel,Eco,590,2,1,3,3,2,3,2,2,4,4,3,3,3,2,0,0.0,neutral or dissatisfied +81835,2764,Male,disloyal Customer,39,Business travel,Business,764,4,3,3,2,4,3,1,4,5,3,4,4,4,4,10,0.0,satisfied +81836,55909,Male,Loyal Customer,20,Personal Travel,Eco,733,4,2,4,4,2,4,2,2,1,4,4,3,3,2,0,23.0,neutral or dissatisfied +81837,61314,Male,Loyal Customer,41,Business travel,Business,909,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +81838,112341,Male,Loyal Customer,43,Business travel,Business,846,1,1,1,1,2,4,4,2,2,2,2,3,2,4,25,20.0,satisfied +81839,40240,Female,disloyal Customer,22,Business travel,Eco,358,0,5,1,5,1,1,5,1,3,4,2,3,1,1,3,0.0,satisfied +81840,1768,Male,Loyal Customer,45,Business travel,Business,408,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +81841,89364,Female,Loyal Customer,51,Personal Travel,Eco,1587,1,2,1,4,4,3,3,3,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +81842,28405,Male,Loyal Customer,47,Personal Travel,Eco,1489,3,3,2,3,2,2,2,2,2,3,4,2,2,2,0,0.0,neutral or dissatisfied +81843,13622,Male,Loyal Customer,32,Business travel,Business,1014,2,2,2,2,3,3,3,3,4,1,5,1,5,3,4,6.0,satisfied +81844,22925,Male,Loyal Customer,64,Personal Travel,Business,528,4,3,4,4,4,4,4,5,5,4,4,3,5,2,114,109.0,neutral or dissatisfied +81845,62075,Male,Loyal Customer,55,Business travel,Business,2586,5,5,5,5,4,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +81846,96867,Female,disloyal Customer,24,Business travel,Business,994,5,0,5,4,2,5,2,2,5,3,4,4,1,2,0,1.0,satisfied +81847,57400,Male,Loyal Customer,19,Personal Travel,Business,1186,1,4,1,2,2,1,2,2,3,2,4,3,4,2,28,26.0,neutral or dissatisfied +81848,124964,Male,Loyal Customer,54,Business travel,Business,1501,1,1,1,1,5,5,4,4,4,4,4,5,4,3,27,45.0,satisfied +81849,96531,Female,Loyal Customer,64,Personal Travel,Eco,302,3,5,3,3,4,4,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +81850,57611,Male,Loyal Customer,48,Business travel,Business,2627,2,2,2,2,5,4,4,4,4,4,5,4,4,5,64,77.0,satisfied +81851,88272,Female,Loyal Customer,48,Business travel,Business,2058,5,2,2,2,5,3,4,5,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +81852,116410,Male,Loyal Customer,67,Personal Travel,Eco,372,3,2,3,4,4,3,4,4,3,4,4,5,4,4,15,2.0,neutral or dissatisfied +81853,96368,Male,Loyal Customer,39,Business travel,Business,1407,4,4,2,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +81854,95101,Female,Loyal Customer,69,Personal Travel,Eco,293,1,4,1,1,2,5,5,5,5,1,5,4,5,4,3,5.0,neutral or dissatisfied +81855,93450,Male,Loyal Customer,51,Personal Travel,Eco,671,3,2,3,3,1,3,1,1,2,3,3,4,4,1,0,1.0,neutral or dissatisfied +81856,41198,Male,Loyal Customer,49,Business travel,Business,2041,3,2,2,2,1,3,4,3,3,3,3,2,3,4,0,8.0,neutral or dissatisfied +81857,64347,Male,Loyal Customer,53,Business travel,Business,2719,2,1,1,1,2,2,3,2,2,1,2,1,2,4,22,7.0,neutral or dissatisfied +81858,36838,Male,Loyal Customer,54,Business travel,Business,3734,2,1,1,1,5,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +81859,61662,Female,disloyal Customer,25,Business travel,Business,702,5,0,5,3,3,5,3,3,3,5,4,3,4,3,8,0.0,satisfied +81860,4344,Female,Loyal Customer,40,Business travel,Business,473,3,3,3,3,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +81861,69321,Female,disloyal Customer,28,Business travel,Business,1096,5,5,5,3,3,5,3,3,4,2,5,5,4,3,0,0.0,satisfied +81862,27380,Male,disloyal Customer,24,Business travel,Eco,679,1,1,1,1,4,1,4,4,4,5,3,5,1,4,0,0.0,neutral or dissatisfied +81863,8393,Male,disloyal Customer,25,Business travel,Business,888,5,0,5,2,4,5,4,4,5,3,5,3,4,4,1,0.0,satisfied +81864,28910,Female,Loyal Customer,29,Business travel,Eco,679,4,3,3,3,4,4,4,4,1,3,4,5,2,4,0,0.0,satisfied +81865,115783,Female,disloyal Customer,33,Business travel,Eco,372,3,4,3,3,3,3,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +81866,1453,Male,Loyal Customer,32,Business travel,Business,772,1,1,1,1,4,4,4,4,4,3,4,5,4,4,100,88.0,satisfied +81867,103096,Female,Loyal Customer,7,Personal Travel,Eco,460,2,4,2,3,5,2,1,5,3,5,3,4,1,5,80,71.0,neutral or dissatisfied +81868,67499,Female,Loyal Customer,18,Personal Travel,Eco Plus,641,3,4,3,4,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +81869,8134,Male,Loyal Customer,49,Business travel,Business,125,4,4,4,4,5,4,4,5,5,5,4,3,5,5,0,0.0,satisfied +81870,82017,Female,Loyal Customer,25,Personal Travel,Eco,1522,3,5,3,2,4,3,4,4,5,3,4,3,4,4,0,11.0,neutral or dissatisfied +81871,77940,Female,Loyal Customer,41,Business travel,Business,3761,5,5,5,5,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +81872,45116,Male,disloyal Customer,26,Business travel,Eco,157,3,5,3,1,2,3,2,2,5,5,4,3,5,2,14,9.0,neutral or dissatisfied +81873,126928,Female,Loyal Customer,38,Business travel,Business,2194,2,2,2,2,5,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +81874,43767,Male,Loyal Customer,37,Business travel,Eco,146,1,3,3,3,1,1,1,1,4,2,4,4,3,1,0,0.0,neutral or dissatisfied +81875,21060,Female,Loyal Customer,49,Business travel,Business,227,3,2,3,2,3,1,3,3,3,3,3,2,3,1,43,36.0,neutral or dissatisfied +81876,103876,Female,Loyal Customer,9,Personal Travel,Eco,1056,2,4,2,3,5,2,5,5,4,4,5,3,4,5,22,37.0,neutral or dissatisfied +81877,70259,Male,Loyal Customer,45,Personal Travel,Eco Plus,1592,2,5,2,1,3,2,3,3,3,4,4,3,5,3,6,0.0,neutral or dissatisfied +81878,18046,Female,Loyal Customer,52,Business travel,Eco,488,4,2,2,2,3,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +81879,86774,Female,Loyal Customer,29,Business travel,Business,2675,1,3,3,3,1,1,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +81880,117677,Male,Loyal Customer,60,Business travel,Business,1814,1,1,1,1,3,5,4,5,5,5,5,3,5,4,17,4.0,satisfied +81881,127013,Female,disloyal Customer,21,Business travel,Business,621,5,2,5,2,2,5,2,2,3,5,5,5,5,2,0,0.0,satisfied +81882,107725,Male,Loyal Customer,64,Personal Travel,Eco,405,5,4,5,2,4,5,4,4,5,4,5,4,5,4,33,33.0,satisfied +81883,77129,Male,Loyal Customer,32,Personal Travel,Eco Plus,1481,2,5,2,4,2,2,2,2,4,2,3,3,5,2,10,0.0,neutral or dissatisfied +81884,17181,Male,Loyal Customer,36,Business travel,Business,267,3,3,3,3,4,5,3,5,5,4,5,1,5,1,3,0.0,satisfied +81885,16329,Male,Loyal Customer,15,Personal Travel,Eco,628,1,5,1,3,1,1,4,1,5,5,4,4,4,1,7,11.0,neutral or dissatisfied +81886,2608,Female,Loyal Customer,62,Personal Travel,Eco,280,2,5,2,5,4,4,5,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +81887,20879,Female,disloyal Customer,32,Business travel,Eco Plus,357,2,2,2,2,5,2,5,5,5,5,3,1,4,5,0,9.0,neutral or dissatisfied +81888,108388,Male,Loyal Customer,9,Personal Travel,Eco,1750,2,3,2,4,5,2,5,5,4,1,3,2,3,5,0,0.0,neutral or dissatisfied +81889,40261,Male,Loyal Customer,57,Business travel,Business,2099,0,4,1,4,5,3,1,1,1,1,1,3,1,5,0,0.0,satisfied +81890,102992,Female,Loyal Customer,51,Business travel,Business,3613,4,4,3,4,5,4,4,4,4,4,4,3,4,5,70,67.0,satisfied +81891,96181,Male,Loyal Customer,35,Business travel,Eco,328,2,1,1,1,2,2,2,2,3,3,4,2,3,2,82,74.0,neutral or dissatisfied +81892,26444,Male,Loyal Customer,25,Business travel,Business,2515,3,2,2,2,3,3,3,3,4,2,4,2,4,3,48,46.0,neutral or dissatisfied +81893,102678,Male,disloyal Customer,23,Business travel,Eco,255,2,2,2,4,4,2,4,4,1,5,3,4,4,4,26,17.0,neutral or dissatisfied +81894,18266,Female,Loyal Customer,45,Personal Travel,Eco,179,1,4,0,3,0,4,5,4,5,4,4,5,4,5,139,146.0,neutral or dissatisfied +81895,111480,Female,Loyal Customer,18,Business travel,Eco,1452,4,5,3,3,4,3,2,4,1,1,4,2,4,4,5,0.0,neutral or dissatisfied +81896,96939,Female,Loyal Customer,50,Business travel,Business,1648,3,2,3,2,5,1,1,3,3,3,3,2,3,2,0,8.0,neutral or dissatisfied +81897,95051,Male,Loyal Customer,57,Personal Travel,Eco,189,5,1,0,3,5,0,5,5,2,5,4,3,4,5,1,0.0,satisfied +81898,63300,Female,disloyal Customer,26,Business travel,Business,447,3,0,3,4,1,3,1,1,3,3,5,4,4,1,2,0.0,neutral or dissatisfied +81899,35274,Male,Loyal Customer,22,Business travel,Business,2730,1,4,4,4,1,1,1,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +81900,1430,Female,Loyal Customer,53,Business travel,Business,772,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +81901,81793,Male,disloyal Customer,22,Business travel,Eco,1310,3,3,3,5,3,3,1,3,3,5,5,4,4,3,5,0.0,neutral or dissatisfied +81902,24162,Male,Loyal Customer,34,Business travel,Business,170,2,2,2,2,4,4,4,5,5,4,4,1,5,1,0,0.0,satisfied +81903,82184,Male,Loyal Customer,39,Business travel,Business,1927,4,4,4,4,3,5,4,4,4,4,4,5,4,5,15,9.0,satisfied +81904,68126,Male,Loyal Customer,64,Personal Travel,Eco,868,4,2,4,1,4,4,4,4,1,1,1,4,1,4,1,0.0,satisfied +81905,35173,Male,Loyal Customer,29,Business travel,Business,1648,1,1,1,1,4,3,4,4,4,3,5,3,2,4,0,0.0,satisfied +81906,89774,Female,Loyal Customer,32,Personal Travel,Eco,1069,4,5,4,4,4,4,4,4,4,5,4,4,5,4,1,0.0,neutral or dissatisfied +81907,63469,Female,disloyal Customer,18,Business travel,Eco,447,2,4,2,3,2,4,4,3,3,4,3,4,1,4,241,251.0,neutral or dissatisfied +81908,99097,Male,Loyal Customer,60,Business travel,Business,3301,2,2,4,2,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +81909,61540,Male,Loyal Customer,31,Personal Travel,Eco,2253,4,5,4,3,1,4,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +81910,87091,Female,disloyal Customer,36,Business travel,Eco,245,4,0,4,2,1,4,1,1,5,2,1,1,3,1,10,2.0,neutral or dissatisfied +81911,12058,Female,Loyal Customer,21,Personal Travel,Eco,351,4,5,4,1,3,4,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +81912,42520,Female,Loyal Customer,38,Personal Travel,Eco,1384,4,4,3,1,5,3,5,5,5,3,3,4,5,5,0,0.0,neutral or dissatisfied +81913,118616,Female,Loyal Customer,24,Business travel,Eco,646,1,2,3,3,1,1,3,1,1,5,3,3,3,1,21,18.0,neutral or dissatisfied +81914,122857,Male,Loyal Customer,68,Business travel,Eco,226,2,3,3,3,3,2,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +81915,15819,Male,Loyal Customer,49,Business travel,Eco Plus,195,4,3,3,3,4,4,4,4,1,1,3,1,1,4,0,0.0,satisfied +81916,39526,Female,Loyal Customer,11,Personal Travel,Eco,852,2,4,2,3,3,2,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +81917,40651,Female,Loyal Customer,45,Business travel,Business,590,4,4,4,4,3,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +81918,47164,Female,Loyal Customer,29,Business travel,Eco,620,5,2,3,2,5,4,5,5,3,5,3,2,3,5,0,0.0,satisfied +81919,32965,Male,Loyal Customer,10,Personal Travel,Eco,101,1,3,1,4,5,1,3,5,4,5,3,2,4,5,0,2.0,neutral or dissatisfied +81920,62621,Male,Loyal Customer,67,Personal Travel,Eco,1723,3,4,3,3,1,3,1,1,3,3,4,3,4,1,7,0.0,neutral or dissatisfied +81921,96640,Female,Loyal Customer,23,Business travel,Business,972,2,4,4,4,2,2,2,2,3,3,2,1,2,2,0,0.0,neutral or dissatisfied +81922,119651,Male,Loyal Customer,27,Business travel,Business,507,3,3,3,3,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +81923,89099,Male,disloyal Customer,23,Business travel,Eco,726,5,5,5,2,2,5,2,2,3,4,5,5,5,2,0,0.0,satisfied +81924,33516,Male,Loyal Customer,25,Business travel,Eco,1554,4,3,1,3,4,4,3,4,4,1,1,1,3,4,13,0.0,satisfied +81925,92025,Female,Loyal Customer,43,Business travel,Business,1589,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +81926,53269,Male,Loyal Customer,44,Business travel,Business,901,1,1,1,1,3,4,5,4,4,4,4,4,4,1,39,53.0,satisfied +81927,57156,Male,Loyal Customer,22,Business travel,Business,3435,3,3,3,3,4,4,4,4,5,3,4,4,1,4,33,22.0,satisfied +81928,110246,Female,Loyal Customer,22,Personal Travel,Eco,1147,0,1,0,3,3,0,3,3,2,1,2,2,3,3,0,0.0,satisfied +81929,107517,Female,Loyal Customer,39,Business travel,Eco,838,2,5,5,5,2,2,2,2,3,1,3,3,3,2,23,4.0,neutral or dissatisfied +81930,114102,Male,Loyal Customer,29,Personal Travel,Eco Plus,1947,1,5,1,2,1,1,1,1,3,4,5,4,2,1,7,0.0,neutral or dissatisfied +81931,42356,Female,Loyal Customer,59,Personal Travel,Eco,834,1,4,1,2,2,3,3,4,4,1,4,1,4,5,0,0.0,neutral or dissatisfied +81932,117190,Female,Loyal Customer,10,Personal Travel,Eco,651,2,0,1,4,2,1,2,2,4,4,4,4,5,2,72,68.0,neutral or dissatisfied +81933,44639,Female,Loyal Customer,37,Business travel,Business,2307,5,5,5,5,4,5,2,4,4,4,3,5,4,3,38,46.0,satisfied +81934,103384,Female,Loyal Customer,45,Business travel,Business,1842,3,3,3,3,2,5,4,4,4,4,4,5,4,4,27,27.0,satisfied +81935,82211,Male,Loyal Customer,40,Business travel,Business,3240,2,2,5,2,5,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +81936,41381,Female,Loyal Customer,62,Business travel,Business,1914,3,5,5,5,5,3,3,3,3,3,3,3,3,3,64,48.0,neutral or dissatisfied +81937,31782,Male,Loyal Customer,37,Personal Travel,Eco,602,1,4,1,1,1,1,1,1,5,2,4,4,4,1,6,0.0,neutral or dissatisfied +81938,33143,Male,Loyal Customer,11,Personal Travel,Eco,102,1,2,1,2,3,1,3,3,3,2,3,1,2,3,0,0.0,neutral or dissatisfied +81939,5737,Female,Loyal Customer,58,Personal Travel,Eco Plus,436,1,4,1,4,4,5,4,2,2,1,2,5,2,5,0,5.0,neutral or dissatisfied +81940,98152,Female,Loyal Customer,59,Business travel,Business,3493,5,5,4,5,2,4,5,5,5,5,5,3,5,4,12,0.0,satisfied +81941,77713,Female,Loyal Customer,37,Business travel,Business,3631,3,2,2,2,1,2,2,3,3,3,3,1,3,1,25,10.0,neutral or dissatisfied +81942,80002,Female,Loyal Customer,36,Personal Travel,Eco,1096,4,3,4,2,1,4,1,1,1,4,3,5,5,1,0,5.0,neutral or dissatisfied +81943,38047,Female,Loyal Customer,52,Business travel,Business,2021,2,2,2,2,1,3,4,2,2,2,2,2,2,5,60,58.0,satisfied +81944,34276,Male,disloyal Customer,27,Business travel,Eco,496,4,0,4,4,3,4,3,3,3,1,3,2,3,3,52,60.0,neutral or dissatisfied +81945,58065,Male,Loyal Customer,59,Business travel,Business,612,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +81946,106946,Female,Loyal Customer,48,Business travel,Business,937,1,1,1,1,3,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +81947,82295,Male,Loyal Customer,60,Business travel,Business,1635,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,3.0,satisfied +81948,21942,Male,Loyal Customer,31,Business travel,Business,2604,3,4,3,3,5,5,5,5,1,1,3,5,1,5,0,0.0,satisfied +81949,122049,Male,Loyal Customer,42,Business travel,Business,3280,2,2,2,2,4,3,3,4,4,4,2,1,4,1,0,0.0,neutral or dissatisfied +81950,25095,Male,Loyal Customer,56,Business travel,Eco,369,4,2,4,4,4,4,4,4,2,2,5,2,3,4,2,6.0,satisfied +81951,23748,Female,disloyal Customer,42,Business travel,Eco,1083,2,2,2,1,1,2,1,1,3,2,4,5,5,1,0,2.0,neutral or dissatisfied +81952,90672,Female,disloyal Customer,24,Business travel,Eco,406,3,4,3,3,2,3,2,2,2,1,4,4,3,2,9,25.0,neutral or dissatisfied +81953,123904,Female,Loyal Customer,14,Personal Travel,Eco,603,3,2,3,3,2,3,2,2,1,3,3,1,2,2,24,20.0,neutral or dissatisfied +81954,96593,Male,Loyal Customer,47,Personal Travel,Eco,861,3,4,3,1,1,3,1,1,5,4,5,3,4,1,29,15.0,neutral or dissatisfied +81955,96201,Male,Loyal Customer,52,Business travel,Business,3907,2,2,2,2,5,4,5,3,3,3,3,4,3,4,11,9.0,satisfied +81956,42684,Female,Loyal Customer,47,Business travel,Eco,627,1,1,1,1,2,4,3,1,1,1,1,3,1,1,2,20.0,neutral or dissatisfied +81957,24266,Male,Loyal Customer,27,Personal Travel,Eco,134,2,0,0,1,5,0,2,5,5,5,4,4,5,5,0,4.0,neutral or dissatisfied +81958,25520,Male,Loyal Customer,46,Business travel,Eco,147,4,4,3,4,4,4,4,4,1,4,2,5,5,4,0,0.0,satisfied +81959,15389,Male,Loyal Customer,61,Business travel,Business,1660,0,0,0,5,4,2,4,4,4,1,1,5,4,3,14,6.0,satisfied +81960,5162,Male,disloyal Customer,69,Business travel,Business,222,1,1,1,3,1,1,1,1,2,2,3,3,3,1,0,1.0,neutral or dissatisfied +81961,69631,Female,Loyal Customer,32,Business travel,Business,2170,3,3,5,3,4,4,4,4,5,3,4,3,5,4,0,0.0,satisfied +81962,121879,Male,Loyal Customer,40,Personal Travel,Eco,337,5,5,5,2,1,5,3,1,5,4,4,5,4,1,0,0.0,satisfied +81963,70865,Male,disloyal Customer,15,Business travel,Eco,761,1,1,1,5,5,1,5,5,2,4,4,2,2,5,0,0.0,neutral or dissatisfied +81964,118719,Female,Loyal Customer,23,Personal Travel,Eco,370,2,0,2,2,4,2,4,4,4,4,5,3,5,4,14,3.0,neutral or dissatisfied +81965,52730,Male,Loyal Customer,26,Personal Travel,Eco,406,1,2,1,4,4,1,4,4,2,3,4,4,4,4,1,0.0,neutral or dissatisfied +81966,5935,Male,Loyal Customer,59,Personal Travel,Eco,212,3,3,3,3,4,3,4,4,2,1,2,3,4,4,2,0.0,neutral or dissatisfied +81967,30491,Female,disloyal Customer,10,Business travel,Eco,516,3,1,3,2,2,3,3,2,2,2,3,2,2,2,11,18.0,neutral or dissatisfied +81968,41205,Male,Loyal Customer,54,Business travel,Eco,1091,4,5,5,5,4,4,4,4,1,1,5,1,4,4,88,79.0,satisfied +81969,19115,Female,disloyal Customer,37,Business travel,Eco,323,1,3,1,3,5,1,5,5,1,3,3,4,3,5,0,8.0,neutral or dissatisfied +81970,24552,Female,Loyal Customer,24,Business travel,Business,1721,3,2,3,3,5,5,5,5,3,2,5,3,3,5,0,0.0,satisfied +81971,16722,Male,disloyal Customer,24,Business travel,Business,1167,5,0,5,3,3,5,3,3,5,1,3,5,5,3,56,42.0,satisfied +81972,33531,Male,Loyal Customer,39,Personal Travel,Eco,228,3,5,0,5,2,0,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +81973,108327,Female,Loyal Customer,44,Business travel,Business,1706,2,2,2,2,2,4,4,4,4,5,4,5,4,5,6,0.0,satisfied +81974,34092,Male,Loyal Customer,49,Business travel,Business,3789,4,4,4,4,5,5,5,3,2,5,5,5,3,5,331,322.0,satisfied +81975,103385,Female,Loyal Customer,56,Business travel,Business,1905,4,4,4,4,3,5,5,5,5,5,5,5,5,3,30,31.0,satisfied +81976,42982,Female,Loyal Customer,47,Business travel,Business,3509,2,2,2,2,3,5,4,5,5,5,5,2,5,1,47,41.0,satisfied +81977,82975,Female,disloyal Customer,49,Business travel,Eco,1127,4,4,4,4,1,4,1,1,4,2,4,1,4,1,0,27.0,neutral or dissatisfied +81978,17033,Female,Loyal Customer,17,Business travel,Eco Plus,781,5,2,2,2,5,5,5,5,1,4,2,2,3,5,0,0.0,satisfied +81979,9317,Female,Loyal Customer,45,Business travel,Business,3058,1,0,0,4,2,4,3,5,5,0,5,2,5,3,42,25.0,neutral or dissatisfied +81980,100530,Female,Loyal Customer,17,Personal Travel,Eco,580,1,4,1,3,4,1,4,4,2,3,3,4,4,4,0,0.0,neutral or dissatisfied +81981,45261,Male,disloyal Customer,48,Business travel,Business,290,4,4,4,4,2,4,2,2,5,3,4,3,4,2,0,1.0,neutral or dissatisfied +81982,48609,Female,Loyal Customer,31,Business travel,Eco Plus,819,5,3,3,3,5,5,5,5,2,3,5,4,3,5,0,0.0,satisfied +81983,15029,Male,Loyal Customer,46,Business travel,Business,627,4,4,4,4,5,4,1,4,4,4,4,4,4,3,62,57.0,satisfied +81984,77554,Male,Loyal Customer,61,Personal Travel,Eco,986,4,5,4,4,5,4,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +81985,44934,Male,Loyal Customer,39,Business travel,Business,3696,5,4,5,5,2,5,4,2,2,2,2,5,2,1,0,0.0,satisfied +81986,127215,Female,Loyal Customer,50,Personal Travel,Eco Plus,370,2,1,2,2,1,2,2,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +81987,78131,Male,Loyal Customer,46,Business travel,Business,2645,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +81988,19354,Female,Loyal Customer,47,Business travel,Eco,692,5,5,5,5,1,1,4,5,5,5,5,2,5,1,22,19.0,satisfied +81989,36666,Male,Loyal Customer,68,Personal Travel,Eco,1121,2,5,2,4,2,5,5,4,2,5,4,5,3,5,142,146.0,neutral or dissatisfied +81990,124147,Female,disloyal Customer,20,Business travel,Business,2133,1,4,1,4,4,1,4,4,2,5,3,1,4,4,54,35.0,neutral or dissatisfied +81991,100513,Female,disloyal Customer,37,Business travel,Eco,359,4,2,4,4,2,4,2,2,1,3,4,3,3,2,27,19.0,neutral or dissatisfied +81992,118440,Female,Loyal Customer,52,Business travel,Business,304,2,2,3,2,1,3,4,2,2,2,2,2,2,1,2,0.0,neutral or dissatisfied +81993,128280,Female,disloyal Customer,26,Business travel,Business,325,2,0,2,4,5,2,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +81994,85708,Female,Loyal Customer,48,Personal Travel,Eco,1547,1,2,1,4,3,4,4,4,4,1,3,4,4,1,0,0.0,neutral or dissatisfied +81995,55300,Female,Loyal Customer,51,Business travel,Business,2072,3,3,3,3,5,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +81996,33749,Male,Loyal Customer,56,Business travel,Business,2410,1,1,1,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +81997,96127,Female,Loyal Customer,54,Business travel,Business,546,4,2,3,2,3,4,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +81998,71863,Male,Loyal Customer,25,Business travel,Eco,1723,0,5,0,2,5,0,5,5,2,1,3,4,4,5,7,0.0,satisfied +81999,17770,Male,disloyal Customer,23,Business travel,Eco,1075,4,4,4,5,5,4,5,5,2,1,3,3,4,5,0,0.0,satisfied +82000,112596,Female,Loyal Customer,27,Business travel,Business,3225,1,0,0,3,4,0,3,4,2,3,3,1,2,4,21,10.0,neutral or dissatisfied +82001,52135,Male,Loyal Customer,25,Business travel,Business,2501,2,2,2,2,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +82002,736,Male,disloyal Customer,56,Business travel,Business,229,2,2,2,3,3,2,3,3,4,3,3,3,4,3,0,0.0,neutral or dissatisfied +82003,62646,Female,Loyal Customer,69,Personal Travel,Eco,1726,4,4,4,3,5,4,5,3,3,4,5,4,3,4,8,0.0,neutral or dissatisfied +82004,125299,Female,Loyal Customer,12,Business travel,Business,678,1,2,2,2,1,1,1,1,1,3,3,3,4,1,0,10.0,neutral or dissatisfied +82005,79367,Male,Loyal Customer,10,Personal Travel,Business,502,3,5,3,3,2,3,1,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +82006,14373,Male,Loyal Customer,23,Personal Travel,Eco,1215,2,2,2,4,2,3,3,3,5,3,4,3,4,3,175,180.0,neutral or dissatisfied +82007,79341,Female,Loyal Customer,52,Business travel,Eco,1020,3,4,4,4,2,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +82008,106278,Female,Loyal Customer,58,Business travel,Business,689,2,4,5,4,2,3,2,2,2,2,2,3,2,3,13,5.0,neutral or dissatisfied +82009,59288,Male,Loyal Customer,41,Business travel,Business,3414,5,5,5,5,4,4,4,5,3,3,4,4,4,4,0,0.0,satisfied +82010,70067,Female,Loyal Customer,45,Business travel,Business,550,2,2,2,2,5,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +82011,79655,Female,Loyal Customer,33,Business travel,Business,712,1,3,1,1,3,2,5,4,4,4,4,3,4,1,0,3.0,satisfied +82012,56470,Female,Loyal Customer,26,Personal Travel,Eco Plus,719,2,5,2,4,5,2,5,5,3,2,4,3,5,5,15,0.0,neutral or dissatisfied +82013,35696,Female,Loyal Customer,35,Personal Travel,Eco,2475,0,1,0,3,0,4,4,2,2,3,4,4,3,4,0,0.0,satisfied +82014,87486,Female,Loyal Customer,61,Business travel,Eco,321,1,1,1,1,3,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +82015,49568,Female,Loyal Customer,38,Business travel,Business,1964,0,0,0,4,3,3,1,2,2,2,2,1,2,3,25,31.0,satisfied +82016,107279,Female,Loyal Customer,55,Business travel,Business,2979,3,1,3,1,1,3,3,3,3,3,3,1,3,2,3,1.0,neutral or dissatisfied +82017,52967,Female,Loyal Customer,16,Personal Travel,Eco,2306,2,3,1,3,1,3,3,4,4,5,1,3,2,3,280,355.0,neutral or dissatisfied +82018,49722,Male,Loyal Customer,61,Business travel,Business,262,3,3,3,3,3,1,1,5,5,5,5,5,5,2,30,37.0,satisfied +82019,30683,Female,Loyal Customer,32,Business travel,Business,3665,5,5,5,5,4,4,4,4,2,2,3,3,4,4,1,8.0,satisfied +82020,47049,Female,Loyal Customer,22,Business travel,Eco,351,1,5,5,5,1,1,2,1,2,5,2,2,2,1,0,0.0,neutral or dissatisfied +82021,98655,Male,Loyal Customer,53,Business travel,Business,3815,4,2,3,2,2,4,4,4,4,3,4,1,4,3,0,5.0,neutral or dissatisfied +82022,91196,Male,Loyal Customer,44,Personal Travel,Eco,444,4,4,4,3,5,4,1,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +82023,1681,Female,Loyal Customer,59,Personal Travel,Eco,561,5,3,5,5,1,1,2,2,2,5,2,5,2,3,0,0.0,satisfied +82024,106582,Female,Loyal Customer,39,Business travel,Business,2055,0,0,0,4,4,5,4,5,5,5,5,3,5,3,55,52.0,satisfied +82025,111390,Male,Loyal Customer,70,Personal Travel,Eco,1050,1,5,1,1,4,1,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +82026,80067,Male,Loyal Customer,23,Personal Travel,Eco,1076,1,5,1,2,3,1,3,3,5,5,5,4,5,3,24,42.0,neutral or dissatisfied +82027,89926,Female,Loyal Customer,63,Business travel,Business,3609,5,5,5,5,1,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +82028,18619,Female,Loyal Customer,68,Personal Travel,Eco,201,4,4,4,3,2,2,4,5,5,4,5,1,5,2,0,0.0,satisfied +82029,25718,Male,Loyal Customer,38,Business travel,Eco,447,2,2,2,2,2,2,2,2,1,2,3,2,3,2,6,0.0,neutral or dissatisfied +82030,44036,Female,Loyal Customer,42,Business travel,Business,2698,5,3,5,5,5,1,4,4,4,4,4,4,4,3,0,0.0,satisfied +82031,11546,Male,Loyal Customer,45,Personal Travel,Business,771,3,4,4,3,3,5,5,3,3,4,4,5,3,5,0,0.0,neutral or dissatisfied +82032,116481,Male,Loyal Customer,33,Personal Travel,Eco,337,2,2,2,3,5,2,1,5,4,1,3,3,3,5,0,0.0,neutral or dissatisfied +82033,42190,Female,Loyal Customer,39,Business travel,Business,550,4,4,4,4,2,1,2,3,3,4,3,4,3,3,0,12.0,satisfied +82034,122979,Female,disloyal Customer,23,Business travel,Eco,468,2,5,2,3,4,2,4,4,4,4,4,4,5,4,7,15.0,neutral or dissatisfied +82035,84361,Male,disloyal Customer,29,Business travel,Eco,591,3,3,3,4,3,2,2,1,4,3,4,2,3,2,331,341.0,neutral or dissatisfied +82036,110760,Male,Loyal Customer,59,Business travel,Business,1166,4,4,4,4,5,5,5,2,2,2,2,5,2,3,34,16.0,satisfied +82037,26703,Female,Loyal Customer,54,Personal Travel,Eco,581,2,4,2,4,3,5,5,2,2,2,4,4,2,3,0,0.0,neutral or dissatisfied +82038,94944,Male,Loyal Customer,18,Business travel,Business,2018,3,3,3,3,3,3,3,3,2,3,4,2,4,3,25,10.0,neutral or dissatisfied +82039,18499,Male,Loyal Customer,53,Business travel,Business,201,0,4,0,2,5,1,5,5,5,5,5,5,5,2,0,0.0,satisfied +82040,113777,Male,Loyal Customer,56,Personal Travel,Eco,414,2,3,2,4,5,2,5,5,2,4,4,4,3,5,0,0.0,neutral or dissatisfied +82041,73828,Female,Loyal Customer,68,Personal Travel,Eco,1194,1,5,1,3,2,5,5,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +82042,65094,Male,Loyal Customer,66,Personal Travel,Eco,247,4,5,4,4,1,4,1,1,5,2,4,3,4,1,0,4.0,satisfied +82043,51119,Female,Loyal Customer,62,Personal Travel,Eco,373,4,4,4,4,5,5,5,1,1,4,1,4,1,4,0,11.0,neutral or dissatisfied +82044,91540,Male,Loyal Customer,59,Business travel,Business,680,3,3,3,3,2,5,5,5,5,5,5,3,5,3,75,79.0,satisfied +82045,21210,Male,Loyal Customer,32,Business travel,Business,192,1,4,4,4,2,2,1,2,4,2,3,1,3,2,16,12.0,neutral or dissatisfied +82046,24603,Female,Loyal Customer,42,Business travel,Eco,526,5,5,5,5,4,2,1,5,5,5,5,5,5,2,5,0.0,satisfied +82047,47785,Female,Loyal Customer,39,Business travel,Business,2696,3,3,3,3,2,4,3,4,4,4,4,1,4,1,11,28.0,satisfied +82048,73510,Male,Loyal Customer,33,Business travel,Eco Plus,1144,2,5,5,5,2,2,2,2,2,1,3,4,4,2,3,3.0,neutral or dissatisfied +82049,68051,Female,Loyal Customer,44,Business travel,Business,868,5,5,5,5,3,4,5,5,5,4,5,3,5,4,17,33.0,satisfied +82050,38441,Male,Loyal Customer,53,Business travel,Business,588,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +82051,38401,Male,Loyal Customer,43,Business travel,Business,1754,4,3,3,3,3,3,3,4,4,4,4,1,4,3,0,2.0,neutral or dissatisfied +82052,129879,Male,Loyal Customer,50,Personal Travel,Eco Plus,337,5,4,4,1,3,4,4,3,4,5,5,3,4,3,31,22.0,satisfied +82053,43330,Male,Loyal Customer,45,Business travel,Business,387,1,0,0,3,3,4,4,2,2,0,2,3,2,4,0,21.0,neutral or dissatisfied +82054,106996,Male,Loyal Customer,60,Personal Travel,Eco,1036,3,5,3,2,2,3,2,2,3,5,4,3,5,2,4,7.0,neutral or dissatisfied +82055,65682,Male,Loyal Customer,32,Personal Travel,Eco,1021,3,5,3,2,3,3,3,3,2,5,2,1,5,3,0,0.0,neutral or dissatisfied +82056,29938,Female,Loyal Customer,75,Business travel,Business,373,2,2,2,2,2,2,3,3,3,5,3,2,3,3,0,0.0,satisfied +82057,91102,Male,Loyal Customer,21,Personal Travel,Eco,270,3,0,3,3,3,3,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +82058,119085,Male,Loyal Customer,18,Business travel,Business,2835,4,4,4,4,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +82059,6029,Male,Loyal Customer,39,Business travel,Business,630,1,3,3,3,3,4,4,1,1,1,1,2,1,4,0,1.0,neutral or dissatisfied +82060,57210,Female,Loyal Customer,50,Business travel,Business,1514,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +82061,80463,Female,disloyal Customer,12,Business travel,Eco,1299,3,3,3,3,3,3,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +82062,5018,Male,disloyal Customer,39,Business travel,Business,224,2,2,2,3,2,2,2,2,4,4,4,5,4,2,9,29.0,neutral or dissatisfied +82063,110484,Female,Loyal Customer,8,Personal Travel,Eco,842,3,5,3,3,2,3,2,2,5,5,3,2,2,2,0,0.0,neutral or dissatisfied +82064,48723,Female,disloyal Customer,24,Business travel,Eco,262,3,4,3,4,3,3,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +82065,110843,Male,disloyal Customer,24,Business travel,Business,406,4,0,4,4,1,4,1,1,4,2,5,3,5,1,0,0.0,satisfied +82066,42416,Male,Loyal Customer,49,Business travel,Eco Plus,150,2,4,4,4,2,2,2,2,1,4,4,2,4,2,123,108.0,neutral or dissatisfied +82067,41608,Female,Loyal Customer,45,Personal Travel,Eco,1242,4,5,3,2,5,4,5,1,1,3,1,5,1,5,0,1.0,satisfied +82068,10601,Male,Loyal Customer,62,Business travel,Business,3283,1,5,5,5,4,4,4,1,1,1,1,3,1,2,50,40.0,neutral or dissatisfied +82069,116902,Female,Loyal Customer,39,Business travel,Business,2684,5,5,2,5,4,4,5,4,4,4,4,4,4,4,73,65.0,satisfied +82070,35790,Male,Loyal Customer,51,Personal Travel,Eco,200,4,5,0,1,2,0,2,2,4,3,1,4,2,2,13,0.0,satisfied +82071,23083,Female,Loyal Customer,46,Business travel,Eco,794,3,3,3,3,3,2,3,3,3,3,3,1,3,3,46,25.0,neutral or dissatisfied +82072,120364,Female,Loyal Customer,53,Business travel,Business,366,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +82073,50724,Female,Loyal Customer,53,Personal Travel,Eco,110,4,4,4,2,4,5,5,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +82074,23459,Male,disloyal Customer,45,Business travel,Eco,516,3,3,3,3,4,3,2,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +82075,48529,Female,Loyal Customer,47,Business travel,Business,3318,3,3,3,3,5,5,1,4,4,4,4,2,4,5,0,7.0,satisfied +82076,55637,Male,Loyal Customer,58,Business travel,Business,563,1,1,1,1,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +82077,46737,Female,Loyal Customer,29,Personal Travel,Eco,73,2,1,2,1,2,3,3,4,5,2,2,3,2,3,141,184.0,neutral or dissatisfied +82078,28959,Male,Loyal Customer,31,Business travel,Business,697,4,2,2,2,4,3,4,4,2,3,2,3,3,4,0,0.0,neutral or dissatisfied +82079,82207,Male,Loyal Customer,49,Business travel,Business,3196,3,3,3,3,4,4,5,4,4,4,4,5,4,3,6,8.0,satisfied +82080,85080,Female,Loyal Customer,54,Business travel,Business,731,1,1,1,1,2,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +82081,38159,Female,Loyal Customer,8,Personal Travel,Eco,1185,4,5,4,2,2,4,2,2,4,4,4,3,4,2,25,16.0,neutral or dissatisfied +82082,102554,Female,Loyal Customer,37,Personal Travel,Eco,386,2,5,2,2,3,2,3,3,4,2,5,3,5,3,9,12.0,neutral or dissatisfied +82083,58127,Male,Loyal Customer,32,Personal Travel,Eco,589,1,1,1,3,4,1,4,4,4,5,2,3,3,4,25,18.0,neutral or dissatisfied +82084,109124,Male,Loyal Customer,39,Business travel,Eco Plus,528,5,1,1,1,5,5,5,5,5,5,4,2,2,5,0,0.0,satisfied +82085,53404,Female,disloyal Customer,35,Business travel,Business,2288,2,3,3,2,4,3,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +82086,57559,Male,Loyal Customer,55,Business travel,Business,1597,5,5,5,5,2,5,4,5,5,5,5,3,5,3,4,9.0,satisfied +82087,97440,Female,disloyal Customer,80,Business travel,Eco,185,1,1,1,3,2,1,2,2,3,5,3,4,3,2,16,12.0,neutral or dissatisfied +82088,90965,Male,Loyal Customer,25,Business travel,Business,3584,2,3,3,3,2,2,2,2,1,4,4,1,4,2,14,5.0,neutral or dissatisfied +82089,27625,Female,Loyal Customer,26,Business travel,Eco Plus,954,2,4,4,4,2,2,1,2,1,1,4,3,4,2,0,13.0,neutral or dissatisfied +82090,75358,Female,disloyal Customer,30,Business travel,Business,2556,4,4,4,5,4,4,4,5,3,5,5,4,3,4,0,1.0,neutral or dissatisfied +82091,63688,Male,Loyal Customer,54,Business travel,Business,853,1,1,1,1,3,4,4,5,5,5,5,3,5,5,2,9.0,satisfied +82092,86169,Male,Loyal Customer,44,Business travel,Business,2436,3,3,3,3,4,5,5,5,5,5,5,3,5,4,10,0.0,satisfied +82093,19974,Female,Loyal Customer,8,Personal Travel,Eco,557,2,3,2,5,3,2,3,3,3,4,3,1,4,3,0,0.0,neutral or dissatisfied +82094,64161,Male,disloyal Customer,63,Business travel,Eco,589,4,1,4,3,3,4,1,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +82095,96767,Male,Loyal Customer,50,Business travel,Business,849,2,2,2,2,2,5,5,5,5,5,5,4,5,5,30,16.0,satisfied +82096,115906,Male,Loyal Customer,43,Business travel,Eco,362,3,5,5,5,3,3,3,3,1,5,2,4,1,3,2,0.0,neutral or dissatisfied +82097,96923,Female,Loyal Customer,57,Business travel,Business,1649,4,4,4,4,4,4,5,5,5,5,5,3,5,4,31,25.0,satisfied +82098,26864,Female,Loyal Customer,14,Personal Travel,Eco Plus,224,1,3,1,4,2,1,2,2,3,2,3,2,4,2,26,22.0,neutral or dissatisfied +82099,51845,Male,Loyal Customer,69,Personal Travel,Eco Plus,651,2,3,2,2,5,2,2,5,3,3,3,4,5,5,0,0.0,neutral or dissatisfied +82100,72691,Female,Loyal Customer,9,Personal Travel,Eco,1121,1,1,1,2,3,1,3,3,1,2,2,1,2,3,0,4.0,neutral or dissatisfied +82101,103919,Female,Loyal Customer,21,Business travel,Business,3732,2,2,2,2,3,4,3,3,4,2,5,4,4,3,0,0.0,satisfied +82102,94118,Female,Loyal Customer,10,Personal Travel,Business,323,3,2,3,4,5,3,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +82103,83664,Female,Loyal Customer,31,Business travel,Business,3644,3,3,3,3,4,5,4,4,4,5,4,4,5,4,0,0.0,satisfied +82104,32144,Male,disloyal Customer,27,Business travel,Eco,102,3,5,3,5,1,3,1,1,3,1,4,1,5,1,4,6.0,neutral or dissatisfied +82105,4391,Female,Loyal Customer,64,Personal Travel,Eco,607,0,4,0,3,4,4,4,1,1,0,3,4,1,5,0,0.0,satisfied +82106,73972,Female,Loyal Customer,44,Personal Travel,Eco,2342,1,0,1,3,1,1,1,4,4,4,5,1,4,1,0,9.0,neutral or dissatisfied +82107,17976,Female,Loyal Customer,39,Business travel,Business,3322,5,5,5,5,5,4,4,5,5,5,5,5,5,4,0,13.0,satisfied +82108,107031,Male,Loyal Customer,52,Business travel,Business,395,3,3,3,3,2,4,5,3,3,3,3,4,3,4,10,18.0,satisfied +82109,40605,Male,Loyal Customer,15,Personal Travel,Eco,391,0,4,0,3,2,0,4,2,1,4,1,2,2,2,5,0.0,satisfied +82110,50582,Male,Loyal Customer,24,Personal Travel,Eco,262,1,3,0,4,4,0,4,4,2,4,1,4,1,4,99,110.0,neutral or dissatisfied +82111,93112,Female,Loyal Customer,27,Personal Travel,Eco,903,2,3,1,3,5,1,3,5,3,1,4,2,3,5,0,0.0,neutral or dissatisfied +82112,6813,Male,Loyal Customer,35,Personal Travel,Eco,235,1,5,0,2,4,0,1,4,3,1,5,3,3,4,0,0.0,neutral or dissatisfied +82113,115690,Male,Loyal Customer,59,Business travel,Eco,337,2,4,4,4,2,2,2,2,1,3,3,1,4,2,9,0.0,neutral or dissatisfied +82114,81506,Female,disloyal Customer,22,Business travel,Eco,528,3,0,4,1,1,4,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +82115,63522,Female,disloyal Customer,22,Business travel,Business,1009,4,3,4,2,2,4,2,2,4,5,4,3,4,2,17,10.0,satisfied +82116,52569,Female,Loyal Customer,68,Business travel,Business,119,4,4,4,4,5,5,5,4,4,4,5,1,4,4,0,0.0,satisfied +82117,8863,Male,disloyal Customer,26,Business travel,Eco,539,2,1,2,2,4,2,4,4,2,3,2,1,2,4,11,7.0,neutral or dissatisfied +82118,19726,Male,Loyal Customer,31,Personal Travel,Eco,409,2,1,2,4,1,2,1,1,1,4,4,4,3,1,31,51.0,neutral or dissatisfied +82119,97126,Female,Loyal Customer,30,Business travel,Business,2849,2,4,3,4,2,2,2,2,3,5,3,4,3,2,20,22.0,neutral or dissatisfied +82120,2500,Female,disloyal Customer,21,Business travel,Business,280,0,4,1,3,3,1,3,3,5,3,4,3,5,3,9,28.0,satisfied +82121,11091,Male,Loyal Customer,23,Personal Travel,Eco,224,3,4,0,4,0,1,1,5,5,5,4,1,3,1,351,342.0,neutral or dissatisfied +82122,41947,Male,Loyal Customer,32,Personal Travel,Business,575,1,4,1,2,5,1,5,5,5,2,5,3,4,5,1,0.0,neutral or dissatisfied +82123,129093,Female,Loyal Customer,30,Business travel,Eco,2446,4,1,1,1,4,4,4,2,2,4,4,4,4,4,0,3.0,neutral or dissatisfied +82124,116122,Female,Loyal Customer,66,Personal Travel,Eco,358,2,5,2,5,4,4,4,3,3,2,1,3,3,4,18,11.0,neutral or dissatisfied +82125,96991,Female,Loyal Customer,47,Business travel,Business,375,4,4,4,4,4,3,3,2,2,2,2,2,2,1,8,0.0,satisfied +82126,88851,Male,Loyal Customer,46,Personal Travel,Eco Plus,270,2,1,2,4,2,2,2,2,4,1,3,3,4,2,112,115.0,neutral or dissatisfied +82127,70848,Male,Loyal Customer,57,Business travel,Business,761,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +82128,86370,Female,Loyal Customer,25,Business travel,Business,762,1,1,1,1,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +82129,61136,Male,Loyal Customer,43,Business travel,Business,2850,5,5,5,5,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +82130,118584,Male,Loyal Customer,44,Business travel,Business,1873,4,4,4,4,4,5,5,5,5,5,5,5,5,4,17,10.0,satisfied +82131,12809,Male,Loyal Customer,42,Business travel,Eco,817,1,4,1,1,1,1,1,1,2,4,2,2,2,1,25,21.0,neutral or dissatisfied +82132,15674,Female,Loyal Customer,45,Business travel,Eco,641,4,3,3,3,4,5,5,4,4,4,4,4,4,1,0,0.0,satisfied +82133,124473,Male,Loyal Customer,36,Personal Travel,Eco,980,3,5,3,5,5,3,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +82134,17819,Male,Loyal Customer,15,Personal Travel,Eco,1214,4,3,4,4,4,4,4,4,2,2,4,2,4,4,0,0.0,satisfied +82135,32256,Female,disloyal Customer,29,Business travel,Eco,101,3,4,4,4,3,4,3,3,5,4,3,4,3,3,0,0.0,neutral or dissatisfied +82136,6116,Male,disloyal Customer,23,Business travel,Eco,409,4,4,4,4,5,4,5,5,2,5,3,4,4,5,0,7.0,neutral or dissatisfied +82137,3080,Male,Loyal Customer,46,Business travel,Business,594,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +82138,123054,Male,Loyal Customer,44,Business travel,Business,631,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +82139,40827,Female,Loyal Customer,63,Business travel,Business,532,2,5,3,5,1,2,3,2,2,2,2,1,2,3,0,11.0,neutral or dissatisfied +82140,22062,Male,Loyal Customer,36,Business travel,Eco,304,1,5,1,5,1,1,1,1,4,2,4,2,4,1,0,13.0,neutral or dissatisfied +82141,90227,Female,disloyal Customer,27,Business travel,Business,1145,5,5,5,3,4,5,3,4,5,5,5,3,5,4,3,5.0,satisfied +82142,126118,Male,Loyal Customer,49,Business travel,Business,1830,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +82143,63866,Male,Loyal Customer,30,Business travel,Business,1192,3,3,3,3,3,3,3,3,4,1,4,3,4,3,36,39.0,neutral or dissatisfied +82144,96132,Female,Loyal Customer,58,Business travel,Business,3600,3,3,3,3,3,5,4,5,5,5,5,4,5,4,21,23.0,satisfied +82145,122436,Male,Loyal Customer,59,Personal Travel,Eco,1916,2,4,2,1,2,2,2,2,4,3,3,5,4,2,0,0.0,neutral or dissatisfied +82146,105850,Female,Loyal Customer,60,Business travel,Business,3416,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +82147,18954,Female,Loyal Customer,13,Personal Travel,Eco,503,2,5,2,3,5,2,5,5,5,2,4,4,4,5,2,0.0,neutral or dissatisfied +82148,98487,Female,Loyal Customer,45,Business travel,Business,668,2,2,2,2,3,4,5,5,5,5,5,4,5,5,14,10.0,satisfied +82149,5488,Female,Loyal Customer,45,Business travel,Business,910,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,2.0,satisfied +82150,108251,Female,disloyal Customer,12,Business travel,Eco,895,2,2,2,4,2,2,2,2,4,2,3,2,3,2,4,6.0,neutral or dissatisfied +82151,74575,Female,Loyal Customer,57,Business travel,Business,2976,2,5,5,5,2,4,3,2,2,2,2,2,2,1,0,12.0,neutral or dissatisfied +82152,49664,Female,Loyal Customer,60,Business travel,Business,78,1,3,3,3,1,4,4,3,3,3,1,4,3,4,113,105.0,neutral or dissatisfied +82153,218,Male,Loyal Customer,17,Personal Travel,Eco,213,4,4,4,3,3,4,2,3,3,3,2,4,4,3,0,3.0,neutral or dissatisfied +82154,96884,Female,Loyal Customer,70,Personal Travel,Eco,781,1,5,1,4,2,5,5,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +82155,72138,Female,disloyal Customer,10,Business travel,Eco,731,1,1,1,3,4,1,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +82156,4771,Male,Loyal Customer,35,Business travel,Business,315,2,2,2,2,2,5,4,4,4,4,4,4,4,4,38,33.0,satisfied +82157,59119,Male,Loyal Customer,32,Personal Travel,Eco,1846,4,5,5,5,4,5,5,4,4,5,5,4,4,4,0,0.0,satisfied +82158,93390,Female,disloyal Customer,20,Business travel,Eco,672,1,1,1,2,4,1,2,4,4,5,4,5,4,4,3,0.0,neutral or dissatisfied +82159,79892,Female,Loyal Customer,63,Business travel,Business,944,3,4,4,4,4,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +82160,84052,Male,Loyal Customer,50,Business travel,Business,2784,5,5,5,5,4,5,5,4,4,4,4,5,4,4,0,5.0,satisfied +82161,86841,Female,Loyal Customer,44,Business travel,Business,484,5,5,4,5,3,5,1,2,2,2,2,4,2,4,0,0.0,satisfied +82162,3363,Female,disloyal Customer,33,Business travel,Eco,213,1,1,0,3,4,0,5,4,1,1,3,1,4,4,0,0.0,neutral or dissatisfied +82163,9178,Female,Loyal Customer,31,Personal Travel,Eco,416,1,2,1,4,4,1,4,4,2,1,4,2,3,4,0,15.0,neutral or dissatisfied +82164,82596,Male,Loyal Customer,44,Business travel,Eco,408,4,1,1,1,4,4,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +82165,100227,Female,Loyal Customer,38,Business travel,Business,1073,4,4,4,4,5,5,4,5,5,5,5,5,5,3,5,0.0,satisfied +82166,118081,Female,Loyal Customer,28,Business travel,Business,3956,2,2,2,2,5,5,5,5,5,5,5,4,5,5,19,6.0,satisfied +82167,74865,Female,Loyal Customer,16,Personal Travel,Eco,1995,1,5,2,3,1,2,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +82168,21912,Female,Loyal Customer,57,Business travel,Business,3433,2,2,2,2,1,2,3,5,5,5,5,2,5,4,0,0.0,satisfied +82169,75889,Female,Loyal Customer,25,Business travel,Business,2610,5,5,5,5,4,4,4,4,4,5,5,4,4,4,5,12.0,satisfied +82170,12600,Male,Loyal Customer,38,Personal Travel,Eco,542,2,4,2,4,2,2,2,2,5,5,4,5,4,2,2,1.0,neutral or dissatisfied +82171,27038,Female,Loyal Customer,45,Personal Travel,Eco Plus,867,2,3,2,4,2,4,4,1,1,2,1,2,1,4,1,6.0,neutral or dissatisfied +82172,118411,Male,disloyal Customer,26,Business travel,Business,304,2,4,2,3,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +82173,109249,Female,Loyal Customer,28,Personal Travel,Eco,616,2,5,2,2,2,2,2,2,1,5,1,4,1,2,0,0.0,neutral or dissatisfied +82174,29960,Male,Loyal Customer,62,Business travel,Business,2798,4,2,2,2,2,2,2,4,4,4,4,2,4,1,1,10.0,neutral or dissatisfied +82175,54138,Female,Loyal Customer,52,Business travel,Business,1400,4,4,4,4,5,4,3,3,3,4,3,1,3,1,27,0.0,satisfied +82176,97994,Female,Loyal Customer,51,Business travel,Business,722,3,3,3,3,2,5,5,4,4,4,4,5,4,4,120,126.0,satisfied +82177,94384,Male,Loyal Customer,42,Business travel,Business,2565,2,2,2,2,3,5,4,5,5,5,5,4,5,5,1,2.0,satisfied +82178,12981,Male,Loyal Customer,44,Business travel,Eco,374,4,3,3,3,4,4,4,4,2,4,2,4,5,4,19,9.0,satisfied +82179,36516,Male,disloyal Customer,37,Business travel,Eco,1211,3,2,2,1,4,2,4,4,4,4,3,2,5,4,0,4.0,neutral or dissatisfied +82180,45386,Female,Loyal Customer,34,Personal Travel,Eco Plus,222,4,2,0,3,2,0,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +82181,2345,Female,Loyal Customer,42,Business travel,Eco Plus,525,5,4,4,4,1,1,5,3,3,5,3,4,3,1,0,0.0,satisfied +82182,88650,Male,Loyal Customer,44,Personal Travel,Eco,545,3,3,3,5,4,3,4,4,2,2,5,1,3,4,0,9.0,neutral or dissatisfied +82183,67847,Male,Loyal Customer,44,Personal Travel,Eco,1188,5,5,4,4,2,4,3,2,4,5,4,1,3,2,0,0.0,satisfied +82184,88582,Male,Loyal Customer,52,Personal Travel,Eco,223,3,4,3,3,1,3,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +82185,36118,Male,Loyal Customer,27,Business travel,Business,1562,5,5,5,5,4,4,4,4,1,1,4,2,4,4,0,0.0,satisfied +82186,46825,Male,Loyal Customer,33,Business travel,Eco,819,4,2,4,4,4,4,4,4,2,4,2,3,3,4,0,15.0,satisfied +82187,21313,Male,Loyal Customer,19,Personal Travel,Eco,692,4,4,4,1,3,4,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +82188,3622,Male,Loyal Customer,46,Personal Travel,Business,427,4,0,4,2,3,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +82189,92248,Female,Loyal Customer,31,Business travel,Business,1670,2,4,4,4,2,2,2,2,2,1,2,1,4,2,11,2.0,neutral or dissatisfied +82190,129567,Female,Loyal Customer,68,Personal Travel,Eco,2218,3,1,3,3,2,4,3,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +82191,16398,Female,Loyal Customer,53,Personal Travel,Eco,463,5,5,5,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +82192,39954,Female,Loyal Customer,47,Personal Travel,Eco,1086,2,4,2,1,2,5,5,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +82193,16024,Female,Loyal Customer,49,Personal Travel,Eco,722,2,5,3,2,4,4,2,4,4,3,4,2,4,5,95,68.0,neutral or dissatisfied +82194,111123,Male,Loyal Customer,58,Business travel,Business,1111,5,5,5,5,5,5,5,4,4,4,4,3,4,5,27,13.0,satisfied +82195,120220,Male,Loyal Customer,23,Business travel,Business,1430,2,2,2,2,2,2,2,2,2,4,3,1,4,2,0,30.0,neutral or dissatisfied +82196,88854,Male,Loyal Customer,59,Personal Travel,Eco Plus,270,3,2,3,3,3,2,4,3,1,4,4,4,4,4,222,215.0,neutral or dissatisfied +82197,74150,Male,Loyal Customer,39,Business travel,Business,321,0,0,0,3,5,5,4,3,3,3,3,5,3,1,9,0.0,satisfied +82198,36638,Female,Loyal Customer,57,Personal Travel,Eco,1197,2,4,2,3,3,4,5,3,3,2,3,4,3,5,0,15.0,neutral or dissatisfied +82199,77775,Male,Loyal Customer,47,Personal Travel,Eco,696,4,5,4,2,2,4,2,2,5,1,1,3,2,2,10,6.0,neutral or dissatisfied +82200,23992,Female,Loyal Customer,27,Business travel,Business,595,2,2,2,2,5,5,5,5,3,1,2,4,1,5,0,0.0,satisfied +82201,124778,Female,disloyal Customer,22,Business travel,Business,280,2,1,2,3,5,2,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +82202,14604,Male,Loyal Customer,48,Personal Travel,Eco,986,3,5,4,1,2,4,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +82203,61732,Male,Loyal Customer,38,Business travel,Business,903,4,4,2,4,4,3,2,5,5,5,5,4,5,3,5,0.0,satisfied +82204,25016,Female,Loyal Customer,50,Business travel,Eco,907,5,1,1,1,2,2,4,5,5,5,5,5,5,1,0,18.0,satisfied +82205,403,Female,Loyal Customer,39,Business travel,Business,1661,3,3,5,3,5,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +82206,34567,Female,Loyal Customer,23,Business travel,Business,1598,1,1,1,1,5,5,5,5,1,4,4,1,3,5,2,0.0,satisfied +82207,64721,Female,Loyal Customer,53,Business travel,Business,247,3,3,3,3,3,5,5,4,4,4,4,5,4,3,4,1.0,satisfied +82208,129250,Male,Loyal Customer,25,Personal Travel,Eco,1464,3,4,4,3,4,4,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +82209,99315,Male,Loyal Customer,51,Business travel,Business,448,4,4,4,4,5,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +82210,109732,Male,disloyal Customer,47,Business travel,Eco,187,1,2,1,4,5,1,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +82211,15932,Female,Loyal Customer,48,Business travel,Business,566,1,1,1,1,5,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +82212,7712,Female,Loyal Customer,30,Business travel,Business,859,3,3,3,3,4,4,4,4,5,2,4,5,4,4,0,2.0,satisfied +82213,37997,Female,Loyal Customer,34,Business travel,Business,2574,5,5,5,5,4,5,3,4,4,4,4,4,4,5,0,0.0,satisfied +82214,5638,Female,disloyal Customer,26,Business travel,Business,196,4,0,3,3,5,3,5,5,3,3,5,5,4,5,17,4.0,satisfied +82215,50381,Female,Loyal Customer,42,Business travel,Business,308,2,2,2,2,1,2,1,5,5,5,5,1,5,3,0,0.0,satisfied +82216,119719,Female,disloyal Customer,44,Business travel,Business,1303,5,5,5,2,2,5,2,2,4,3,5,4,4,2,0,2.0,satisfied +82217,127933,Female,Loyal Customer,7,Personal Travel,Eco,2300,2,4,1,1,4,1,4,4,5,4,5,5,4,4,38,14.0,neutral or dissatisfied +82218,72849,Female,Loyal Customer,56,Personal Travel,Eco,1168,5,5,5,2,3,5,4,3,3,5,2,4,3,5,0,0.0,satisfied +82219,123923,Male,Loyal Customer,64,Personal Travel,Eco,646,3,4,3,2,3,3,3,3,3,5,1,1,2,3,0,0.0,neutral or dissatisfied +82220,60811,Male,Loyal Customer,47,Business travel,Business,3719,5,5,2,5,2,5,4,4,4,4,4,3,4,3,5,1.0,satisfied +82221,93069,Female,Loyal Customer,58,Personal Travel,Eco,297,3,3,3,3,5,5,2,4,4,3,4,1,4,1,34,23.0,neutral or dissatisfied +82222,14038,Male,Loyal Customer,8,Personal Travel,Eco,1117,1,4,0,4,1,0,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +82223,19565,Male,Loyal Customer,37,Business travel,Eco,108,4,2,2,2,4,4,4,4,5,1,1,1,2,4,0,0.0,satisfied +82224,97638,Male,Loyal Customer,31,Business travel,Business,1587,4,2,2,2,4,4,4,4,4,2,4,2,3,4,0,6.0,neutral or dissatisfied +82225,32322,Male,disloyal Customer,37,Business travel,Eco,102,2,0,2,3,4,2,4,4,3,4,5,2,2,4,0,0.0,neutral or dissatisfied +82226,104139,Male,Loyal Customer,60,Personal Travel,Eco,448,3,4,3,3,4,3,4,4,3,1,3,2,3,4,49,36.0,neutral or dissatisfied +82227,95827,Male,Loyal Customer,20,Personal Travel,Eco,1428,2,5,1,3,1,1,1,1,5,3,5,3,4,1,11,4.0,neutral or dissatisfied +82228,71138,Female,Loyal Customer,25,Business travel,Business,1502,2,5,5,5,2,2,2,2,1,3,4,1,4,2,70,80.0,neutral or dissatisfied +82229,56289,Male,Loyal Customer,63,Business travel,Business,2227,3,4,4,4,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +82230,123840,Female,Loyal Customer,49,Business travel,Business,1774,5,5,5,5,5,4,5,5,5,5,5,5,5,4,6,0.0,satisfied +82231,77947,Female,Loyal Customer,53,Business travel,Business,2345,0,5,0,4,2,5,5,4,4,4,4,4,4,4,54,77.0,satisfied +82232,64589,Male,Loyal Customer,57,Business travel,Business,2529,4,4,4,4,5,5,5,4,4,4,4,5,4,5,10,3.0,satisfied +82233,39879,Male,Loyal Customer,58,Personal Travel,Eco,272,3,0,3,4,2,3,2,2,1,2,3,1,2,2,0,3.0,neutral or dissatisfied +82234,8343,Male,Loyal Customer,72,Business travel,Business,661,4,4,4,4,4,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +82235,14773,Female,Loyal Customer,25,Business travel,Business,3535,5,5,5,5,5,5,5,5,4,3,1,5,5,5,92,105.0,satisfied +82236,116324,Female,Loyal Customer,53,Personal Travel,Eco,337,1,4,1,4,4,4,4,5,5,1,5,1,5,3,58,64.0,neutral or dissatisfied +82237,32382,Female,Loyal Customer,58,Business travel,Eco,102,4,4,4,4,3,2,5,4,4,4,4,5,4,3,0,0.0,satisfied +82238,103858,Male,Loyal Customer,15,Personal Travel,Eco,882,4,2,4,3,5,4,5,5,3,1,4,1,3,5,10,9.0,satisfied +82239,108386,Male,Loyal Customer,10,Personal Travel,Eco,1838,3,4,3,4,2,3,5,2,1,1,5,1,2,2,0,0.0,neutral or dissatisfied +82240,29831,Female,disloyal Customer,37,Business travel,Eco,261,5,2,5,1,5,5,5,5,5,4,2,2,3,5,0,0.0,satisfied +82241,2181,Female,Loyal Customer,26,Business travel,Business,3346,1,0,0,3,1,0,1,1,1,1,4,3,4,1,0,7.0,neutral or dissatisfied +82242,75826,Female,disloyal Customer,24,Business travel,Eco,1440,2,1,1,3,2,2,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +82243,73910,Female,Loyal Customer,56,Business travel,Business,2218,5,5,5,5,4,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +82244,102758,Male,disloyal Customer,26,Business travel,Business,1618,3,3,3,1,2,3,2,2,4,2,3,5,5,2,0,0.0,neutral or dissatisfied +82245,62077,Female,Loyal Customer,51,Business travel,Business,2586,1,1,1,1,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +82246,98694,Male,Loyal Customer,23,Personal Travel,Eco,966,0,5,0,2,1,0,1,1,3,4,5,5,5,1,13,0.0,satisfied +82247,77623,Male,Loyal Customer,35,Business travel,Business,3101,4,4,4,4,4,5,5,2,2,2,2,4,2,5,1,0.0,satisfied +82248,49189,Male,Loyal Customer,45,Business travel,Business,1818,4,4,4,4,4,3,2,4,4,4,4,4,4,3,0,0.0,satisfied +82249,88974,Male,Loyal Customer,66,Business travel,Business,940,5,1,5,5,2,4,3,5,5,5,5,2,5,1,2,0.0,satisfied +82250,70679,Male,Loyal Customer,48,Personal Travel,Eco,447,2,3,2,2,3,2,3,3,1,4,2,3,2,3,0,0.0,neutral or dissatisfied +82251,35090,Female,Loyal Customer,45,Business travel,Business,2501,1,1,1,1,5,3,3,4,4,4,4,1,4,3,5,0.0,satisfied +82252,105284,Female,Loyal Customer,45,Business travel,Business,3592,2,2,2,2,2,5,4,4,4,4,4,4,4,4,18,1.0,satisfied +82253,34488,Male,disloyal Customer,24,Business travel,Eco,1123,4,4,4,4,3,4,3,3,1,1,3,4,5,3,0,6.0,satisfied +82254,119077,Female,Loyal Customer,48,Business travel,Business,1020,1,1,1,1,5,5,5,5,5,5,4,5,5,5,126,136.0,satisfied +82255,127943,Male,Loyal Customer,8,Personal Travel,Eco Plus,2300,1,4,1,3,1,1,1,1,3,5,3,3,4,1,10,18.0,neutral or dissatisfied +82256,129499,Female,Loyal Customer,23,Business travel,Business,1846,3,5,5,5,3,3,3,3,2,5,4,4,3,3,0,0.0,neutral or dissatisfied +82257,25588,Male,disloyal Customer,40,Business travel,Eco,474,1,1,1,1,4,1,4,4,3,3,1,2,2,4,22,14.0,neutral or dissatisfied +82258,1306,Male,Loyal Customer,44,Business travel,Business,1948,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +82259,38796,Male,Loyal Customer,32,Business travel,Business,387,3,4,4,4,3,2,3,3,2,4,4,2,3,3,4,4.0,neutral or dissatisfied +82260,30843,Male,Loyal Customer,26,Business travel,Business,2178,5,5,5,5,3,3,3,3,2,2,1,2,3,3,9,0.0,satisfied +82261,76950,Male,Loyal Customer,37,Business travel,Business,1990,3,3,3,3,4,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +82262,128753,Male,Loyal Customer,27,Business travel,Business,3612,2,2,2,2,5,5,5,5,5,5,5,4,5,5,17,8.0,satisfied +82263,54184,Male,disloyal Customer,25,Business travel,Eco,1400,2,2,2,3,5,2,1,5,2,3,3,2,3,5,17,0.0,neutral or dissatisfied +82264,76078,Female,Loyal Customer,36,Business travel,Business,3871,3,3,3,3,2,5,5,4,4,4,4,5,4,5,0,4.0,satisfied +82265,48147,Female,Loyal Customer,57,Business travel,Eco,391,5,2,5,2,3,2,1,5,5,5,5,2,5,5,0,0.0,satisfied +82266,92045,Male,Loyal Customer,41,Business travel,Business,1589,3,3,3,3,3,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +82267,122779,Female,Loyal Customer,51,Business travel,Business,599,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +82268,67906,Female,Loyal Customer,49,Personal Travel,Eco,1242,3,5,3,3,4,4,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +82269,115008,Female,Loyal Customer,46,Business travel,Business,3452,2,2,2,2,4,4,5,3,3,3,3,5,3,4,1,0.0,satisfied +82270,101001,Male,Loyal Customer,60,Business travel,Business,1897,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +82271,107388,Female,Loyal Customer,48,Business travel,Business,3360,5,1,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +82272,43052,Female,disloyal Customer,22,Business travel,Eco,236,1,3,1,2,3,1,3,3,3,5,2,2,3,3,0,23.0,neutral or dissatisfied +82273,56191,Female,Loyal Customer,39,Personal Travel,Eco,1400,3,4,3,2,3,3,3,3,4,3,4,5,4,3,1,4.0,neutral or dissatisfied +82274,64110,Male,Loyal Customer,42,Business travel,Business,2311,1,1,1,1,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +82275,25665,Female,Loyal Customer,51,Business travel,Eco,761,4,2,2,2,1,1,4,4,4,4,4,4,4,1,36,13.0,satisfied +82276,95814,Female,Loyal Customer,43,Business travel,Business,1428,1,1,1,1,5,5,5,1,1,2,1,3,1,3,42,25.0,satisfied +82277,77411,Male,Loyal Customer,30,Personal Travel,Eco,588,3,5,3,1,4,3,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +82278,61231,Male,Loyal Customer,43,Business travel,Business,846,5,5,5,5,4,4,5,5,5,5,5,4,5,4,1,4.0,satisfied +82279,89533,Female,Loyal Customer,49,Business travel,Business,3857,4,4,4,4,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +82280,103616,Female,Loyal Customer,47,Business travel,Business,3190,1,1,3,1,5,4,4,5,5,5,5,4,5,5,17,16.0,satisfied +82281,99807,Male,Loyal Customer,34,Personal Travel,Eco,632,3,5,3,4,2,3,2,2,3,3,2,3,2,2,0,0.0,neutral or dissatisfied +82282,36989,Female,disloyal Customer,14,Business travel,Eco,759,2,2,2,1,5,2,4,5,1,4,3,4,2,5,4,0.0,neutral or dissatisfied +82283,7335,Female,disloyal Customer,23,Business travel,Business,606,5,0,5,3,3,5,3,3,4,5,4,4,4,3,80,70.0,satisfied +82284,6453,Male,disloyal Customer,65,Business travel,Business,296,2,2,2,3,4,2,5,4,3,2,5,5,5,4,20,20.0,satisfied +82285,52229,Male,Loyal Customer,42,Business travel,Business,2600,4,1,1,1,1,3,4,4,4,3,4,3,4,2,45,35.0,neutral or dissatisfied +82286,29836,Male,Loyal Customer,33,Business travel,Eco,261,5,2,2,2,5,5,5,5,2,3,2,4,1,5,61,61.0,satisfied +82287,91942,Male,disloyal Customer,26,Business travel,Eco,975,2,2,2,3,3,2,3,3,5,4,1,4,5,3,12,0.0,neutral or dissatisfied +82288,8202,Female,disloyal Customer,75,Business travel,Eco,294,2,0,2,4,2,2,1,2,5,3,3,1,3,2,1,0.0,neutral or dissatisfied +82289,36863,Male,Loyal Customer,36,Business travel,Business,3228,4,4,4,4,4,4,4,4,4,4,3,4,2,4,176,175.0,neutral or dissatisfied +82290,30525,Male,Loyal Customer,47,Personal Travel,Eco,464,3,5,5,2,4,5,3,4,4,3,4,4,5,4,28,41.0,neutral or dissatisfied +82291,27072,Female,Loyal Customer,23,Personal Travel,Eco,1399,3,4,3,2,1,3,1,1,5,3,3,3,5,1,1,0.0,neutral or dissatisfied +82292,46012,Male,disloyal Customer,20,Business travel,Eco,991,3,3,3,3,3,3,3,3,5,4,4,3,5,3,83,70.0,neutral or dissatisfied +82293,61953,Male,Loyal Customer,43,Business travel,Eco,552,4,4,4,4,4,4,4,4,4,1,3,1,1,4,0,0.0,satisfied +82294,30953,Female,Loyal Customer,43,Business travel,Business,624,1,1,1,1,1,4,3,5,5,5,5,3,5,1,11,11.0,satisfied +82295,70486,Male,disloyal Customer,18,Business travel,Eco,867,2,2,2,3,5,2,5,5,3,2,3,1,4,5,0,0.0,neutral or dissatisfied +82296,124357,Female,Loyal Customer,43,Business travel,Business,808,3,2,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +82297,104481,Male,Loyal Customer,21,Personal Travel,Eco Plus,1671,1,5,1,5,2,1,2,2,3,1,2,1,5,2,3,0.0,neutral or dissatisfied +82298,64230,Male,disloyal Customer,48,Business travel,Business,1660,4,4,4,2,4,4,4,4,4,2,3,3,5,4,11,0.0,satisfied +82299,68811,Male,Loyal Customer,42,Personal Travel,Eco,926,5,5,5,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +82300,48080,Male,Loyal Customer,39,Personal Travel,Business,192,2,4,2,3,2,5,5,4,4,2,1,4,4,3,0,0.0,neutral or dissatisfied +82301,78636,Male,Loyal Customer,68,Personal Travel,Eco Plus,1953,4,4,4,4,2,4,2,2,2,5,3,3,3,2,0,0.0,satisfied +82302,22018,Female,disloyal Customer,47,Business travel,Eco Plus,448,2,1,1,4,1,2,1,1,5,2,1,1,2,1,0,0.0,neutral or dissatisfied +82303,65871,Male,Loyal Customer,9,Personal Travel,Eco,1389,5,4,5,2,4,5,4,4,2,3,4,3,2,4,0,0.0,satisfied +82304,29430,Male,Loyal Customer,28,Business travel,Business,2149,3,3,3,3,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +82305,79540,Female,Loyal Customer,58,Business travel,Business,760,4,4,4,4,4,4,5,5,5,5,5,5,5,5,25,14.0,satisfied +82306,129858,Female,Loyal Customer,40,Business travel,Business,337,0,0,0,2,5,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +82307,27123,Male,Loyal Customer,25,Business travel,Business,2701,4,4,4,4,4,3,3,3,5,5,5,3,1,3,0,0.0,satisfied +82308,71542,Female,disloyal Customer,29,Business travel,Eco,1144,2,2,2,3,1,2,1,1,2,3,3,4,3,1,9,16.0,neutral or dissatisfied +82309,74614,Female,Loyal Customer,63,Business travel,Business,3859,3,3,3,3,4,3,4,4,4,4,4,2,4,1,21,0.0,satisfied +82310,7889,Female,Loyal Customer,48,Personal Travel,Eco,910,1,5,1,5,2,4,5,2,2,1,4,4,2,5,0,6.0,neutral or dissatisfied +82311,114015,Female,Loyal Customer,35,Personal Travel,Eco,1728,4,5,4,3,2,4,2,2,4,4,4,5,3,2,0,0.0,neutral or dissatisfied +82312,106128,Male,Loyal Customer,39,Business travel,Business,2882,2,3,3,3,3,3,2,2,2,2,2,3,2,2,74,80.0,neutral or dissatisfied +82313,123631,Female,Loyal Customer,46,Business travel,Business,2159,5,5,5,5,5,5,5,4,4,5,5,5,4,5,0,14.0,satisfied +82314,125254,Female,Loyal Customer,14,Personal Travel,Eco,427,2,0,2,3,5,2,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +82315,124566,Female,Loyal Customer,38,Personal Travel,Eco,453,4,4,4,1,5,4,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +82316,47206,Male,Loyal Customer,12,Personal Travel,Eco,679,4,5,5,3,4,5,4,4,3,5,1,2,4,4,0,0.0,neutral or dissatisfied +82317,3617,Female,Loyal Customer,28,Business travel,Business,3161,3,3,3,3,3,4,3,3,3,2,5,5,4,3,0,0.0,satisfied +82318,70837,Male,Loyal Customer,51,Business travel,Business,1523,5,5,5,5,5,5,5,2,2,2,2,3,2,4,43,54.0,satisfied +82319,118182,Female,disloyal Customer,50,Business travel,Eco,1142,3,3,3,2,4,3,5,4,4,3,3,2,3,4,15,37.0,neutral or dissatisfied +82320,36131,Female,disloyal Customer,48,Business travel,Eco,1562,2,2,2,3,2,2,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +82321,114017,Male,Loyal Customer,70,Personal Travel,Eco,1750,3,2,4,4,4,4,4,4,1,1,3,3,3,4,10,0.0,neutral or dissatisfied +82322,35700,Female,Loyal Customer,48,Personal Travel,Eco,2465,3,3,4,4,4,2,2,1,5,2,4,2,2,2,0,0.0,neutral or dissatisfied +82323,14607,Male,Loyal Customer,30,Business travel,Business,448,2,2,2,2,5,5,5,5,4,4,4,5,4,5,90,97.0,satisfied +82324,85487,Female,Loyal Customer,39,Personal Travel,Eco,332,3,3,3,4,3,3,3,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +82325,36614,Female,Loyal Customer,47,Business travel,Eco,1197,5,1,1,1,4,3,1,5,5,5,5,1,5,3,0,2.0,satisfied +82326,128118,Male,Loyal Customer,50,Business travel,Eco,1587,4,1,1,1,4,4,4,4,2,1,3,4,3,4,0,20.0,neutral or dissatisfied +82327,22189,Female,Loyal Customer,45,Business travel,Business,3128,3,3,3,3,3,3,2,4,4,4,4,3,4,3,36,35.0,satisfied +82328,112876,Female,Loyal Customer,45,Business travel,Business,1390,3,3,4,3,4,5,4,5,5,5,5,4,5,3,1,0.0,satisfied +82329,60769,Male,Loyal Customer,9,Business travel,Business,804,3,3,2,3,4,4,4,4,4,4,5,4,5,4,1,0.0,satisfied +82330,125748,Female,Loyal Customer,51,Personal Travel,Business,861,1,4,2,1,4,5,4,1,1,2,1,5,1,3,0,6.0,neutral or dissatisfied +82331,76340,Male,Loyal Customer,54,Business travel,Business,3106,2,1,1,1,1,3,2,2,2,2,2,4,2,1,17,8.0,neutral or dissatisfied +82332,108432,Male,Loyal Customer,41,Business travel,Business,1444,3,3,4,3,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +82333,55584,Male,Loyal Customer,54,Personal Travel,Eco,1091,2,2,2,4,1,2,1,1,4,4,3,4,3,1,0,0.0,neutral or dissatisfied +82334,100039,Female,disloyal Customer,36,Business travel,Eco,281,3,0,3,3,1,3,1,1,2,5,4,4,2,1,1,1.0,neutral or dissatisfied +82335,13548,Female,Loyal Customer,44,Business travel,Eco,106,2,5,5,5,5,3,3,2,2,2,2,2,2,4,0,0.0,satisfied +82336,58377,Female,Loyal Customer,55,Business travel,Business,2207,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +82337,33115,Female,Loyal Customer,43,Personal Travel,Eco,163,3,5,3,5,4,5,3,1,1,3,1,1,1,4,35,34.0,neutral or dissatisfied +82338,113315,Male,disloyal Customer,22,Business travel,Business,414,4,0,3,2,4,3,5,4,5,2,4,4,4,4,0,0.0,satisfied +82339,43448,Male,Loyal Customer,33,Business travel,Business,679,4,4,2,4,2,2,2,2,4,1,1,2,1,2,0,0.0,satisfied +82340,125876,Male,Loyal Customer,30,Business travel,Business,920,1,4,4,4,1,1,1,1,1,4,1,2,2,1,37,35.0,neutral or dissatisfied +82341,94208,Male,disloyal Customer,23,Business travel,Eco,189,0,4,0,2,3,0,3,3,5,4,5,4,4,3,0,0.0,satisfied +82342,128749,Male,Loyal Customer,8,Personal Travel,Eco,2402,1,4,1,2,1,1,1,1,5,4,3,3,5,1,18,0.0,neutral or dissatisfied +82343,105835,Male,Loyal Customer,59,Personal Travel,Eco,787,4,2,4,4,5,4,5,5,2,4,3,4,3,5,0,0.0,neutral or dissatisfied +82344,102831,Male,Loyal Customer,42,Business travel,Business,1660,5,5,5,5,5,4,4,5,5,5,5,3,5,3,9,0.0,satisfied +82345,24283,Male,Loyal Customer,18,Personal Travel,Eco,302,3,4,3,3,4,3,4,4,3,5,5,4,5,4,0,10.0,neutral or dissatisfied +82346,33251,Male,Loyal Customer,58,Business travel,Eco Plus,163,1,5,5,5,2,1,2,2,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +82347,91798,Female,Loyal Customer,53,Personal Travel,Eco,626,3,5,3,5,2,5,4,5,5,3,5,3,5,4,0,1.0,neutral or dissatisfied +82348,110558,Male,Loyal Customer,41,Business travel,Business,551,4,4,4,4,5,4,5,5,5,5,5,5,5,5,16,6.0,satisfied +82349,125392,Male,Loyal Customer,31,Business travel,Business,1440,5,4,5,5,4,4,4,4,3,2,5,3,4,4,0,12.0,satisfied +82350,43464,Male,disloyal Customer,16,Business travel,Eco,752,5,5,5,1,3,3,3,3,2,3,3,5,3,3,0,2.0,satisfied +82351,125555,Male,Loyal Customer,17,Business travel,Business,1714,3,5,5,5,3,3,3,3,1,4,3,4,3,3,0,16.0,neutral or dissatisfied +82352,75554,Female,disloyal Customer,42,Business travel,Business,337,5,5,5,3,5,5,5,5,3,2,5,3,4,5,0,12.0,satisfied +82353,97537,Male,Loyal Customer,50,Business travel,Business,3236,2,2,2,2,3,5,5,4,4,4,4,5,4,3,41,32.0,satisfied +82354,43605,Female,Loyal Customer,57,Business travel,Business,2470,0,0,0,2,4,3,3,4,4,4,4,4,4,2,0,0.0,satisfied +82355,37513,Male,disloyal Customer,43,Business travel,Eco,1041,4,4,4,4,2,4,2,2,3,5,3,4,4,2,0,1.0,neutral or dissatisfied +82356,62209,Female,Loyal Customer,32,Personal Travel,Eco,2565,2,4,2,4,5,2,5,5,2,4,3,3,4,5,1,0.0,neutral or dissatisfied +82357,125511,Female,Loyal Customer,36,Personal Travel,Eco,666,3,2,3,4,3,3,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +82358,89663,Male,disloyal Customer,25,Business travel,Eco,1035,2,2,2,4,2,2,2,2,3,3,3,4,4,2,17,4.0,neutral or dissatisfied +82359,104577,Male,Loyal Customer,40,Business travel,Business,369,5,5,4,5,3,4,4,2,2,2,2,3,2,5,2,0.0,satisfied +82360,101932,Female,Loyal Customer,54,Personal Travel,Business,804,1,4,1,3,1,3,4,2,2,1,2,3,2,3,48,54.0,neutral or dissatisfied +82361,13897,Female,Loyal Customer,51,Business travel,Business,317,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +82362,56298,Male,Loyal Customer,36,Personal Travel,Eco,2227,3,5,3,1,3,5,5,5,4,3,5,5,3,5,211,238.0,neutral or dissatisfied +82363,72151,Female,Loyal Customer,40,Personal Travel,Eco,731,4,4,4,5,2,4,2,2,4,4,2,1,5,2,0,21.0,neutral or dissatisfied +82364,2025,Female,disloyal Customer,34,Business travel,Business,785,2,2,2,1,1,2,1,1,4,4,4,3,5,1,0,1.0,neutral or dissatisfied +82365,78695,Male,Loyal Customer,58,Personal Travel,Eco Plus,761,3,5,3,2,3,3,3,3,4,5,4,5,5,3,12,4.0,neutral or dissatisfied +82366,123813,Male,Loyal Customer,42,Business travel,Business,2832,1,1,2,1,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +82367,21604,Male,Loyal Customer,32,Business travel,Business,1599,4,4,4,4,5,5,5,5,1,1,5,4,4,5,0,0.0,satisfied +82368,122421,Male,disloyal Customer,20,Business travel,Eco,1916,5,5,5,4,3,5,3,3,3,5,4,5,5,3,0,0.0,satisfied +82369,92922,Male,Loyal Customer,52,Business travel,Business,2397,0,5,0,3,4,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +82370,14273,Female,Loyal Customer,46,Business travel,Business,3570,4,4,5,4,5,1,4,3,3,4,3,5,3,5,0,0.0,satisfied +82371,79204,Female,Loyal Customer,45,Business travel,Business,1990,1,1,1,1,2,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +82372,39382,Female,Loyal Customer,27,Business travel,Business,546,5,5,5,5,5,5,5,5,3,5,2,1,4,5,40,27.0,satisfied +82373,23395,Female,Loyal Customer,45,Business travel,Business,483,4,4,4,4,4,5,2,5,5,5,5,3,5,2,0,0.0,satisfied +82374,94891,Male,Loyal Customer,40,Business travel,Eco,248,2,2,1,2,2,2,2,2,2,4,4,1,4,2,15,10.0,neutral or dissatisfied +82375,100403,Female,Loyal Customer,63,Business travel,Eco Plus,971,2,1,1,1,1,2,2,2,2,2,2,3,2,3,13,3.0,neutral or dissatisfied +82376,85531,Female,Loyal Customer,39,Business travel,Business,259,4,3,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +82377,115444,Female,Loyal Customer,45,Business travel,Eco,337,2,5,4,5,2,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +82378,87219,Female,Loyal Customer,55,Personal Travel,Eco,946,3,1,3,3,3,2,2,3,2,2,3,2,4,2,258,234.0,neutral or dissatisfied +82379,31159,Female,Loyal Customer,39,Business travel,Business,3112,4,4,4,4,4,5,5,5,5,4,5,4,5,4,15,4.0,satisfied +82380,86135,Male,disloyal Customer,28,Business travel,Business,356,2,2,2,1,3,2,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +82381,49133,Female,Loyal Customer,29,Business travel,Business,373,3,3,3,3,4,5,4,4,5,3,3,2,5,4,0,0.0,satisfied +82382,129725,Female,disloyal Customer,21,Business travel,Business,308,3,1,3,3,1,3,1,1,2,1,3,4,4,1,0,0.0,neutral or dissatisfied +82383,77702,Male,Loyal Customer,52,Business travel,Eco,696,4,3,3,3,3,4,3,3,4,3,4,4,4,3,12,7.0,neutral or dissatisfied +82384,73050,Male,Loyal Customer,40,Business travel,Business,1096,3,3,3,3,3,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +82385,24701,Male,Loyal Customer,39,Business travel,Business,2805,3,4,2,2,1,3,3,3,3,3,3,3,3,1,0,5.0,neutral or dissatisfied +82386,13873,Female,disloyal Customer,27,Business travel,Eco,578,3,0,3,5,1,3,1,1,5,1,5,2,5,1,0,20.0,neutral or dissatisfied +82387,66325,Female,Loyal Customer,27,Personal Travel,Eco,852,2,1,2,3,2,2,2,2,2,2,3,1,3,2,4,0.0,neutral or dissatisfied +82388,96395,Female,Loyal Customer,15,Business travel,Business,2427,2,5,5,5,2,2,2,2,2,4,3,3,4,2,10,0.0,neutral or dissatisfied +82389,47473,Male,Loyal Customer,13,Personal Travel,Eco,574,2,4,2,5,2,2,2,2,3,3,4,4,5,2,0,16.0,neutral or dissatisfied +82390,59491,Male,disloyal Customer,69,Personal Travel,Eco,901,2,4,2,3,2,2,2,2,1,1,2,1,5,2,32,8.0,neutral or dissatisfied +82391,37366,Male,Loyal Customer,32,Business travel,Business,2271,2,2,2,2,5,5,5,5,5,3,4,3,2,5,32,2.0,satisfied +82392,28346,Male,Loyal Customer,70,Personal Travel,Eco,867,5,4,5,2,4,4,4,4,3,2,5,2,2,4,1,0.0,satisfied +82393,107747,Male,Loyal Customer,21,Personal Travel,Eco,251,3,4,0,1,2,0,2,2,5,2,5,5,4,2,16,12.0,neutral or dissatisfied +82394,86852,Male,Loyal Customer,56,Personal Travel,Eco,692,4,5,4,1,2,4,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +82395,63217,Female,Loyal Customer,47,Business travel,Business,1532,1,2,2,2,2,4,4,1,1,1,1,2,1,1,5,0.0,neutral or dissatisfied +82396,122102,Female,Loyal Customer,9,Personal Travel,Eco,130,1,2,1,3,3,1,4,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +82397,102178,Male,Loyal Customer,51,Business travel,Business,1841,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +82398,27111,Female,Loyal Customer,45,Business travel,Business,2640,3,3,3,3,4,4,4,3,5,3,4,4,5,4,1,0.0,satisfied +82399,61991,Female,Loyal Customer,34,Business travel,Business,2475,1,1,1,1,3,5,5,4,4,4,4,3,4,5,0,8.0,satisfied +82400,97422,Male,Loyal Customer,28,Personal Travel,Eco,587,4,4,3,2,2,3,2,2,5,5,4,3,4,2,1,0.0,neutral or dissatisfied +82401,1923,Female,Loyal Customer,36,Business travel,Business,1765,2,2,2,2,3,4,5,5,5,5,4,5,5,5,9,7.0,satisfied +82402,22738,Male,disloyal Customer,25,Business travel,Eco,170,4,0,4,1,2,4,2,2,5,2,1,4,1,2,0,0.0,neutral or dissatisfied +82403,24983,Male,Loyal Customer,28,Business travel,Business,2195,5,5,5,5,4,4,4,4,3,5,4,2,1,4,0,0.0,satisfied +82404,10402,Female,Loyal Customer,47,Business travel,Business,3451,3,3,3,3,2,5,4,4,4,4,4,5,4,3,8,5.0,satisfied +82405,81391,Male,Loyal Customer,45,Business travel,Business,3594,2,2,4,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +82406,43543,Male,Loyal Customer,49,Business travel,Business,3303,2,2,2,2,2,4,2,4,4,4,4,1,4,4,2,5.0,satisfied +82407,93127,Male,Loyal Customer,53,Business travel,Business,1243,5,5,5,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +82408,65923,Female,Loyal Customer,56,Personal Travel,Eco,569,3,5,3,4,5,4,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +82409,93862,Female,Loyal Customer,45,Business travel,Business,588,5,5,5,5,2,5,4,5,5,5,5,3,5,4,11,0.0,satisfied +82410,106542,Female,Loyal Customer,34,Business travel,Business,2082,2,4,4,4,2,2,2,4,1,3,4,2,3,2,286,281.0,neutral or dissatisfied +82411,102603,Female,Loyal Customer,44,Personal Travel,Eco Plus,407,2,5,2,5,3,4,5,2,2,2,2,3,2,5,36,26.0,neutral or dissatisfied +82412,8901,Male,Loyal Customer,29,Personal Travel,Eco Plus,622,4,3,4,4,5,4,5,5,2,4,4,4,3,5,0,0.0,neutral or dissatisfied +82413,123385,Female,Loyal Customer,50,Business travel,Business,1337,2,2,2,2,3,4,5,5,5,5,5,4,5,5,6,14.0,satisfied +82414,123844,Male,disloyal Customer,25,Business travel,Business,544,5,1,5,4,5,5,5,5,3,5,5,5,4,5,0,37.0,satisfied +82415,128553,Female,Loyal Customer,60,Business travel,Eco Plus,338,2,4,4,4,5,3,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +82416,91028,Female,Loyal Customer,19,Personal Travel,Eco,581,3,5,3,1,2,3,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +82417,115398,Male,Loyal Customer,56,Business travel,Eco,337,1,4,4,4,1,1,1,1,4,2,4,1,3,1,1,0.0,neutral or dissatisfied +82418,13486,Female,Loyal Customer,40,Business travel,Business,2485,2,2,2,2,5,1,2,5,5,5,5,5,5,2,14,7.0,satisfied +82419,88024,Male,disloyal Customer,23,Business travel,Business,404,4,0,4,2,1,4,1,1,4,4,5,4,5,1,0,2.0,satisfied +82420,98193,Female,Loyal Customer,55,Business travel,Business,327,0,0,0,4,5,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +82421,61243,Male,Loyal Customer,36,Business travel,Business,1835,5,5,1,5,2,2,3,4,4,4,4,4,4,2,11,0.0,satisfied +82422,119500,Female,Loyal Customer,48,Business travel,Business,3175,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +82423,128907,Male,Loyal Customer,50,Business travel,Business,2248,3,3,3,3,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +82424,91289,Male,disloyal Customer,18,Business travel,Eco,581,3,0,3,3,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +82425,50208,Male,Loyal Customer,73,Business travel,Eco,373,2,5,5,5,2,2,2,2,1,3,3,2,3,2,98,132.0,neutral or dissatisfied +82426,16417,Male,Loyal Customer,41,Business travel,Business,2913,5,5,5,5,4,1,4,5,5,5,5,1,5,4,0,7.0,satisfied +82427,1906,Female,Loyal Customer,56,Business travel,Business,351,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +82428,91786,Male,Loyal Customer,30,Personal Travel,Eco,590,4,4,4,1,3,4,3,3,5,4,5,5,4,3,4,3.0,neutral or dissatisfied +82429,3116,Female,Loyal Customer,54,Business travel,Business,1880,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,4.0,satisfied +82430,67546,Male,Loyal Customer,19,Personal Travel,Business,1464,3,4,3,3,2,3,2,2,5,2,5,5,4,2,6,0.0,neutral or dissatisfied +82431,96099,Female,Loyal Customer,23,Personal Travel,Eco,583,2,1,3,4,3,3,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +82432,100314,Male,Loyal Customer,58,Business travel,Business,1611,1,1,1,1,4,4,4,1,1,1,1,4,1,3,5,4.0,neutral or dissatisfied +82433,72182,Female,Loyal Customer,49,Business travel,Eco,594,4,2,2,2,2,4,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +82434,104285,Female,Loyal Customer,54,Business travel,Business,3704,3,3,2,3,3,4,4,4,4,4,4,5,4,4,0,16.0,satisfied +82435,11981,Female,Loyal Customer,34,Business travel,Business,3813,2,4,4,4,1,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +82436,37671,Male,Loyal Customer,64,Personal Travel,Eco,1041,4,5,4,5,4,4,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +82437,76490,Female,Loyal Customer,51,Business travel,Business,481,4,4,4,4,4,5,4,5,5,5,5,3,5,5,33,35.0,satisfied +82438,52832,Male,Loyal Customer,48,Business travel,Eco,1721,4,5,5,5,4,4,4,4,2,2,5,5,1,4,5,0.0,satisfied +82439,106804,Female,Loyal Customer,50,Personal Travel,Eco,977,5,2,5,3,2,4,3,5,5,5,5,4,5,1,0,16.0,satisfied +82440,95709,Female,disloyal Customer,36,Business travel,Eco,181,1,3,1,4,2,1,2,2,4,1,4,2,3,2,112,120.0,neutral or dissatisfied +82441,56349,Male,disloyal Customer,16,Business travel,Eco,200,4,2,4,3,1,4,1,1,1,3,4,3,3,1,44,46.0,neutral or dissatisfied +82442,75074,Male,Loyal Customer,67,Personal Travel,Eco,2611,3,1,3,4,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +82443,124911,Female,disloyal Customer,44,Business travel,Eco,728,4,4,4,3,2,4,2,2,2,2,3,1,3,2,0,0.0,neutral or dissatisfied +82444,45463,Male,Loyal Customer,29,Business travel,Business,522,1,1,1,1,3,4,3,3,2,5,4,4,1,3,0,0.0,satisfied +82445,62273,Female,disloyal Customer,39,Business travel,Business,414,4,4,4,4,2,4,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +82446,11788,Male,Loyal Customer,18,Personal Travel,Eco,395,1,5,1,1,4,1,4,4,3,2,5,5,4,4,9,2.0,neutral or dissatisfied +82447,81792,Male,Loyal Customer,50,Business travel,Business,2679,2,1,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +82448,11341,Female,Loyal Customer,31,Personal Travel,Eco,247,1,4,1,2,4,1,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +82449,100246,Male,Loyal Customer,50,Business travel,Business,971,3,3,3,3,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +82450,50958,Female,Loyal Customer,67,Personal Travel,Eco,89,4,3,4,4,3,3,4,2,2,4,2,4,2,2,0,0.0,neutral or dissatisfied +82451,16118,Male,disloyal Customer,30,Business travel,Eco,725,3,3,3,3,4,3,4,4,1,4,5,1,2,4,5,3.0,neutral or dissatisfied +82452,126708,Female,Loyal Customer,48,Business travel,Business,2521,3,3,3,3,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +82453,4594,Female,disloyal Customer,18,Business travel,Eco,416,3,4,3,4,4,3,4,4,4,1,4,2,3,4,6,44.0,neutral or dissatisfied +82454,58329,Female,Loyal Customer,29,Personal Travel,Eco,1739,3,5,4,2,4,4,4,4,4,4,4,5,5,4,128,120.0,neutral or dissatisfied +82455,93323,Male,Loyal Customer,43,Business travel,Business,1639,0,0,0,2,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +82456,54511,Female,Loyal Customer,40,Business travel,Eco,525,4,3,2,3,4,4,4,4,5,3,2,4,4,4,0,0.0,satisfied +82457,53200,Female,disloyal Customer,10,Business travel,Eco,589,4,3,4,3,1,4,1,1,2,4,4,1,3,1,50,57.0,neutral or dissatisfied +82458,101700,Female,Loyal Customer,9,Personal Travel,Eco Plus,1500,5,4,5,3,4,5,1,4,4,2,4,3,3,4,0,0.0,satisfied +82459,26389,Female,Loyal Customer,27,Business travel,Business,534,3,3,4,3,3,4,3,3,4,1,2,2,5,3,0,0.0,satisfied +82460,83168,Female,Loyal Customer,59,Personal Travel,Eco Plus,957,2,2,2,3,4,3,2,2,2,2,1,4,2,3,8,0.0,neutral or dissatisfied +82461,29555,Male,Loyal Customer,34,Business travel,Business,1448,2,2,2,2,4,4,1,2,2,2,2,3,2,2,0,0.0,satisfied +82462,63342,Male,Loyal Customer,56,Business travel,Business,447,2,2,2,2,5,4,1,3,3,3,3,4,3,2,0,0.0,satisfied +82463,38041,Female,Loyal Customer,38,Business travel,Eco,1121,4,1,3,3,4,4,4,4,5,3,5,4,2,4,117,129.0,satisfied +82464,114210,Female,Loyal Customer,38,Business travel,Business,3270,3,3,3,3,5,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +82465,12019,Male,disloyal Customer,42,Business travel,Eco,376,3,0,3,5,5,3,5,5,4,4,4,3,2,5,0,0.0,neutral or dissatisfied +82466,14867,Female,Loyal Customer,37,Business travel,Business,2106,2,2,2,2,5,5,2,4,4,4,4,4,4,2,0,0.0,satisfied +82467,101698,Male,Loyal Customer,34,Personal Travel,Eco,1500,1,1,0,2,4,0,4,4,2,1,2,1,2,4,37,23.0,neutral or dissatisfied +82468,24948,Male,Loyal Customer,29,Business travel,Eco,1747,1,5,3,5,1,1,1,1,1,5,2,3,2,1,0,0.0,neutral or dissatisfied +82469,108367,Female,Loyal Customer,12,Personal Travel,Eco,1844,1,5,1,1,2,1,2,2,4,4,5,3,4,2,41,44.0,neutral or dissatisfied +82470,102259,Male,disloyal Customer,20,Business travel,Business,223,0,0,0,4,3,0,3,3,3,2,4,4,5,3,5,0.0,satisfied +82471,77265,Male,Loyal Customer,22,Business travel,Business,1590,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +82472,101373,Female,Loyal Customer,39,Personal Travel,Eco,2237,1,4,1,1,2,1,2,2,4,4,4,3,4,2,6,8.0,neutral or dissatisfied +82473,100499,Female,Loyal Customer,41,Business travel,Eco,759,3,3,1,3,3,3,3,2,1,4,4,3,2,3,307,295.0,neutral or dissatisfied +82474,50976,Male,Loyal Customer,43,Personal Travel,Eco,109,3,4,3,4,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +82475,59639,Female,disloyal Customer,48,Business travel,Eco,854,1,1,1,4,5,1,5,5,3,1,3,4,3,5,40,31.0,neutral or dissatisfied +82476,74070,Male,Loyal Customer,26,Business travel,Business,2329,4,4,4,4,4,4,4,4,4,2,5,5,4,4,22,5.0,satisfied +82477,80528,Female,Loyal Customer,49,Business travel,Business,1678,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,12.0,satisfied +82478,64010,Female,Loyal Customer,25,Business travel,Business,2629,3,3,3,3,5,5,5,5,4,5,4,5,4,5,53,37.0,satisfied +82479,51465,Female,Loyal Customer,34,Business travel,Eco Plus,373,4,1,1,1,4,4,4,4,4,2,2,1,5,4,0,0.0,satisfied +82480,65583,Male,Loyal Customer,46,Business travel,Business,237,0,0,0,3,2,5,4,5,5,5,5,5,5,3,3,3.0,satisfied +82481,78680,Female,Loyal Customer,48,Business travel,Business,2342,1,1,1,1,5,5,5,5,5,5,5,3,5,4,10,0.0,satisfied +82482,115483,Male,Loyal Customer,55,Business travel,Business,1685,2,5,5,5,3,3,4,2,2,2,2,2,2,3,58,31.0,neutral or dissatisfied +82483,108161,Female,Loyal Customer,63,Personal Travel,Eco,1166,2,4,2,2,3,5,4,1,1,2,1,4,1,5,107,87.0,neutral or dissatisfied +82484,104548,Male,Loyal Customer,23,Personal Travel,Eco,1047,4,3,4,4,3,4,4,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +82485,129680,Male,disloyal Customer,34,Business travel,Business,337,2,2,2,2,4,2,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +82486,97501,Male,Loyal Customer,39,Personal Travel,Eco,670,2,4,2,2,3,2,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +82487,60700,Female,Loyal Customer,54,Business travel,Business,1605,4,5,4,4,5,4,5,4,4,4,4,3,4,4,35,11.0,satisfied +82488,5772,Male,Loyal Customer,28,Personal Travel,Eco,665,4,5,4,3,5,4,5,5,2,2,2,1,3,5,17,0.0,neutral or dissatisfied +82489,91088,Male,Loyal Customer,40,Personal Travel,Eco,406,4,5,4,1,4,4,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +82490,112579,Female,Loyal Customer,47,Business travel,Business,2924,3,3,3,3,2,5,4,4,4,4,4,5,4,5,10,15.0,satisfied +82491,115286,Female,Loyal Customer,24,Business travel,Business,3302,3,5,5,5,3,3,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +82492,98309,Female,Loyal Customer,46,Business travel,Business,1565,5,5,1,5,5,5,5,2,2,2,2,4,2,5,8,0.0,satisfied +82493,107791,Female,Loyal Customer,53,Business travel,Business,3860,1,1,1,1,4,4,4,5,5,5,5,5,5,3,35,27.0,satisfied +82494,38020,Male,disloyal Customer,20,Business travel,Eco,1197,3,3,3,3,2,3,2,2,3,4,3,5,3,2,0,0.0,neutral or dissatisfied +82495,89718,Female,Loyal Customer,55,Personal Travel,Eco,944,2,3,2,5,4,5,3,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +82496,63592,Female,disloyal Customer,26,Business travel,Eco,2133,4,4,4,1,2,4,3,2,1,3,1,3,5,2,67,67.0,neutral or dissatisfied +82497,74612,Female,Loyal Customer,51,Business travel,Business,1438,3,3,3,3,3,3,3,3,1,3,2,3,1,3,174,159.0,neutral or dissatisfied +82498,13139,Female,Loyal Customer,35,Personal Travel,Eco,562,1,1,1,4,2,1,3,2,3,5,3,2,4,2,0,0.0,neutral or dissatisfied +82499,81125,Male,Loyal Customer,67,Personal Travel,Eco,991,3,4,4,1,1,4,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +82500,10627,Male,Loyal Customer,54,Business travel,Business,74,0,5,0,3,3,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +82501,125790,Female,Loyal Customer,56,Business travel,Business,3527,5,5,5,5,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +82502,128568,Female,disloyal Customer,22,Business travel,Business,110,4,5,4,4,3,4,3,3,4,4,5,3,5,3,3,18.0,satisfied +82503,8741,Male,disloyal Customer,25,Business travel,Eco Plus,304,3,2,3,3,4,3,4,4,3,4,4,1,3,4,37,74.0,neutral or dissatisfied +82504,97280,Female,Loyal Customer,27,Personal Travel,Business,347,5,5,5,3,2,5,5,2,3,3,5,4,5,2,0,0.0,satisfied +82505,23539,Male,Loyal Customer,38,Personal Travel,Eco,423,2,0,2,4,1,2,1,1,5,3,4,3,5,1,34,32.0,neutral or dissatisfied +82506,98182,Male,Loyal Customer,77,Business travel,Business,327,1,1,1,1,4,2,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +82507,28033,Male,disloyal Customer,41,Business travel,Business,1214,5,5,5,3,1,5,1,1,4,4,4,5,5,1,0,0.0,satisfied +82508,9561,Female,Loyal Customer,37,Business travel,Business,3572,2,2,2,2,3,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +82509,45786,Male,Loyal Customer,59,Business travel,Eco,391,3,2,2,2,3,3,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +82510,43683,Female,disloyal Customer,26,Business travel,Eco,489,3,4,3,2,1,3,1,1,3,3,2,4,1,1,0,0.0,neutral or dissatisfied +82511,114247,Male,disloyal Customer,23,Business travel,Business,967,0,0,0,4,5,0,5,5,4,5,5,4,5,5,0,0.0,satisfied +82512,8012,Male,Loyal Customer,43,Business travel,Business,2802,3,3,3,3,5,5,4,4,4,4,4,5,4,4,33,45.0,satisfied +82513,56767,Male,disloyal Customer,29,Business travel,Eco Plus,937,2,2,2,4,3,2,5,3,4,1,4,3,3,3,51,37.0,neutral or dissatisfied +82514,115330,Male,disloyal Customer,36,Business travel,Business,325,3,3,3,2,4,3,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +82515,59122,Male,Loyal Customer,30,Personal Travel,Eco,1744,1,2,1,3,2,1,3,2,3,1,3,3,2,2,75,71.0,neutral or dissatisfied +82516,129757,Male,Loyal Customer,55,Business travel,Business,3091,1,1,1,1,2,1,4,5,5,5,5,2,5,1,0,0.0,satisfied +82517,30984,Male,disloyal Customer,36,Business travel,Business,1076,1,0,0,4,5,0,5,5,3,5,3,1,3,5,28,48.0,neutral or dissatisfied +82518,72681,Male,Loyal Customer,68,Personal Travel,Eco,1121,3,4,3,3,4,3,4,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +82519,86266,Female,Loyal Customer,25,Personal Travel,Eco,356,2,4,2,3,3,2,3,3,4,3,5,5,4,3,11,15.0,neutral or dissatisfied +82520,125154,Male,Loyal Customer,39,Business travel,Business,1999,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +82521,28174,Female,Loyal Customer,61,Personal Travel,Eco,859,4,3,3,2,1,2,3,2,2,3,2,3,2,1,0,11.0,satisfied +82522,50161,Female,disloyal Customer,38,Business travel,Eco,109,3,1,2,3,5,2,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +82523,50000,Female,Loyal Customer,57,Business travel,Eco,156,2,4,4,4,2,4,2,2,2,2,2,5,2,2,0,0.0,satisfied +82524,9811,Male,Loyal Customer,41,Business travel,Business,1555,3,2,3,3,4,5,5,5,5,5,5,5,5,5,0,11.0,satisfied +82525,20119,Female,Loyal Customer,40,Business travel,Eco,416,1,5,5,5,1,1,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +82526,99468,Male,disloyal Customer,32,Business travel,Business,283,3,3,3,3,3,3,5,3,3,4,4,3,4,3,0,2.0,neutral or dissatisfied +82527,117142,Male,Loyal Customer,56,Personal Travel,Eco,370,3,5,3,5,5,3,5,5,5,5,1,2,3,5,7,5.0,neutral or dissatisfied +82528,105583,Female,Loyal Customer,34,Personal Travel,Eco,577,1,5,1,3,3,1,3,3,3,2,5,3,4,3,46,61.0,neutral or dissatisfied +82529,73434,Female,Loyal Customer,14,Personal Travel,Eco,1012,4,5,4,1,5,4,5,5,1,1,1,1,4,5,0,0.0,satisfied +82530,45946,Female,Loyal Customer,51,Personal Travel,Eco,809,3,1,4,3,3,4,4,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +82531,31515,Female,Loyal Customer,47,Business travel,Eco,967,1,3,3,3,4,3,3,1,1,1,1,1,1,4,0,13.0,neutral or dissatisfied +82532,100742,Male,Loyal Customer,55,Personal Travel,Eco,328,0,3,0,3,1,0,1,1,2,4,3,3,3,1,97,96.0,satisfied +82533,35036,Male,Loyal Customer,23,Business travel,Business,3937,3,3,2,3,4,5,4,4,3,4,4,5,4,4,79,70.0,satisfied +82534,52367,Female,Loyal Customer,49,Personal Travel,Eco,261,2,3,2,4,4,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +82535,62005,Male,Loyal Customer,58,Business travel,Business,2475,5,5,4,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +82536,62335,Male,Loyal Customer,29,Personal Travel,Eco,414,2,2,2,4,3,2,2,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +82537,96658,Female,Loyal Customer,53,Personal Travel,Eco,972,2,4,2,3,3,5,4,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +82538,74104,Female,Loyal Customer,59,Business travel,Eco,592,4,1,1,1,3,2,3,4,4,4,4,4,4,2,32,38.0,neutral or dissatisfied +82539,50077,Female,Loyal Customer,50,Business travel,Business,1937,1,3,4,3,5,3,4,2,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +82540,57107,Female,Loyal Customer,63,Business travel,Business,1882,1,4,4,4,5,4,3,1,1,1,1,4,1,4,1,0.0,neutral or dissatisfied +82541,20285,Male,Loyal Customer,41,Personal Travel,Eco,224,3,4,3,1,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +82542,81204,Female,Loyal Customer,30,Business travel,Business,1426,3,3,3,3,3,4,3,3,4,3,4,5,5,3,0,0.0,satisfied +82543,5510,Male,Loyal Customer,42,Business travel,Business,910,1,1,1,1,3,5,5,5,5,5,5,4,5,3,0,4.0,satisfied +82544,56680,Female,Loyal Customer,49,Personal Travel,Eco,937,3,5,3,1,1,1,3,3,3,3,3,1,3,5,22,31.0,neutral or dissatisfied +82545,2901,Male,Loyal Customer,35,Personal Travel,Eco,409,3,4,3,2,1,3,5,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +82546,122534,Male,disloyal Customer,19,Business travel,Business,500,5,0,5,4,4,0,4,4,5,2,4,5,4,4,0,0.0,satisfied +82547,23065,Female,Loyal Customer,45,Business travel,Business,420,2,2,2,2,2,3,1,4,4,4,4,2,4,1,91,87.0,satisfied +82548,99772,Male,Loyal Customer,10,Personal Travel,Eco Plus,361,3,4,3,3,5,3,5,5,4,2,4,3,5,5,70,85.0,neutral or dissatisfied +82549,62769,Male,Loyal Customer,53,Business travel,Business,2447,1,1,1,1,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +82550,65669,Female,disloyal Customer,46,Business travel,Business,1021,4,4,4,3,5,4,5,5,5,2,5,5,4,5,0,0.0,satisfied +82551,115775,Female,disloyal Customer,33,Business travel,Eco,337,2,4,1,3,4,1,4,4,4,3,3,2,3,4,65,66.0,neutral or dissatisfied +82552,11169,Female,Loyal Customer,16,Personal Travel,Eco,74,1,5,1,4,3,1,3,3,5,2,5,5,5,3,58,56.0,neutral or dissatisfied +82553,18577,Male,Loyal Customer,41,Business travel,Eco,201,3,1,1,1,3,3,3,3,1,2,4,4,4,3,9,8.0,neutral or dissatisfied +82554,18696,Male,Loyal Customer,39,Business travel,Eco Plus,201,5,3,3,3,5,5,5,5,5,4,3,2,4,5,0,13.0,satisfied +82555,6299,Male,Loyal Customer,68,Personal Travel,Eco Plus,693,4,4,4,4,3,4,1,3,4,4,4,4,5,3,24,41.0,neutral or dissatisfied +82556,60407,Male,Loyal Customer,52,Personal Travel,Eco,1476,4,5,4,3,2,4,2,2,3,3,5,3,5,2,1,0.0,neutral or dissatisfied +82557,116775,Female,Loyal Customer,28,Personal Travel,Eco Plus,372,4,3,2,4,3,2,3,3,2,1,2,3,4,3,66,49.0,neutral or dissatisfied +82558,4443,Female,Loyal Customer,48,Personal Travel,Eco,762,1,5,1,2,2,5,3,5,5,1,5,2,5,5,15,31.0,neutral or dissatisfied +82559,124253,Female,Loyal Customer,61,Personal Travel,Eco,1916,4,5,4,3,4,5,4,2,2,4,5,5,2,3,0,0.0,neutral or dissatisfied +82560,118352,Female,Loyal Customer,59,Personal Travel,Eco,602,5,5,5,1,5,5,4,3,3,5,3,3,3,3,0,0.0,satisfied +82561,106562,Male,Loyal Customer,31,Business travel,Business,2112,5,5,5,5,5,5,5,5,4,4,4,4,5,5,1,0.0,satisfied +82562,2825,Male,Loyal Customer,56,Business travel,Business,2117,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +82563,117919,Female,Loyal Customer,75,Business travel,Eco,255,3,5,5,5,3,3,4,3,3,3,3,2,3,2,8,5.0,neutral or dissatisfied +82564,84064,Female,disloyal Customer,36,Business travel,Eco,932,2,2,2,3,4,2,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +82565,113216,Male,Loyal Customer,40,Business travel,Business,236,0,0,0,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +82566,52255,Female,Loyal Customer,56,Business travel,Business,3320,2,2,2,2,2,5,3,4,4,5,4,1,4,3,32,29.0,satisfied +82567,11781,Male,Loyal Customer,61,Personal Travel,Eco,429,2,0,2,2,5,2,3,5,5,5,5,4,4,5,17,23.0,neutral or dissatisfied +82568,75686,Female,Loyal Customer,58,Business travel,Business,813,1,1,3,1,3,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +82569,127028,Female,disloyal Customer,30,Business travel,Business,647,3,3,3,2,3,3,3,3,4,5,5,3,5,3,9,1.0,neutral or dissatisfied +82570,21956,Female,Loyal Customer,63,Business travel,Eco,448,1,2,5,2,4,4,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +82571,11625,Male,Loyal Customer,32,Business travel,Business,771,5,5,4,5,5,5,5,5,4,5,4,5,5,5,26,19.0,satisfied +82572,78158,Female,disloyal Customer,20,Business travel,Business,317,5,0,4,3,2,4,2,2,4,5,5,4,4,2,0,0.0,satisfied +82573,34191,Male,Loyal Customer,68,Personal Travel,Eco,1046,3,5,2,3,1,2,1,1,4,2,4,5,4,1,8,0.0,neutral or dissatisfied +82574,15641,Male,Loyal Customer,38,Business travel,Eco Plus,229,3,3,3,3,3,2,3,3,4,1,5,3,4,3,0,0.0,satisfied +82575,102767,Male,Loyal Customer,26,Personal Travel,Eco,1618,2,2,2,4,4,2,4,4,3,5,2,3,4,4,58,54.0,neutral or dissatisfied +82576,65652,Male,Loyal Customer,59,Business travel,Business,3689,3,3,3,3,4,4,5,5,5,5,5,4,5,3,7,14.0,satisfied +82577,17245,Female,disloyal Customer,28,Business travel,Eco,872,1,2,2,1,2,2,3,2,3,3,2,2,2,2,0,0.0,neutral or dissatisfied +82578,21511,Female,Loyal Customer,55,Personal Travel,Eco,164,3,2,3,4,1,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +82579,501,Female,Loyal Customer,38,Business travel,Business,354,1,1,1,1,2,5,4,4,4,4,4,4,4,4,16,3.0,satisfied +82580,81694,Female,Loyal Customer,58,Personal Travel,Eco,907,1,4,1,1,5,4,4,2,2,1,2,5,2,3,7,19.0,neutral or dissatisfied +82581,124132,Female,Loyal Customer,64,Personal Travel,Eco,529,3,5,3,3,4,5,4,2,2,3,2,5,2,5,14,7.0,neutral or dissatisfied +82582,109324,Male,Loyal Customer,69,Personal Travel,Eco,1188,2,5,2,3,2,2,2,2,4,3,3,3,4,2,69,65.0,neutral or dissatisfied +82583,69366,Female,disloyal Customer,49,Business travel,Business,1096,1,0,0,3,4,1,4,4,3,4,4,5,5,4,0,2.0,neutral or dissatisfied +82584,32186,Male,Loyal Customer,48,Business travel,Eco,101,5,3,5,3,5,5,5,5,5,3,1,1,2,5,0,0.0,satisfied +82585,103566,Female,Loyal Customer,39,Business travel,Business,3889,3,3,2,3,3,5,4,3,3,3,3,4,3,5,9,0.0,satisfied +82586,84787,Male,disloyal Customer,36,Business travel,Business,516,1,1,1,2,4,1,2,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +82587,70039,Male,Loyal Customer,39,Business travel,Eco,183,4,3,3,3,4,4,4,4,1,2,1,4,4,4,0,0.0,satisfied +82588,86036,Female,Loyal Customer,31,Personal Travel,Eco,554,1,3,2,2,4,2,4,4,2,5,4,1,1,4,1,8.0,neutral or dissatisfied +82589,10903,Female,disloyal Customer,20,Business travel,Eco,163,4,2,4,3,5,4,5,5,1,4,3,3,3,5,73,87.0,neutral or dissatisfied +82590,63499,Male,Loyal Customer,48,Business travel,Business,1956,5,5,5,5,3,5,4,5,5,4,5,3,5,4,32,14.0,satisfied +82591,13732,Female,Loyal Customer,33,Business travel,Eco,384,4,5,5,5,4,4,4,4,3,1,1,1,4,4,0,6.0,satisfied +82592,64742,Male,Loyal Customer,30,Business travel,Eco,469,4,5,3,5,4,3,4,4,3,5,3,2,4,4,0,18.0,neutral or dissatisfied +82593,45329,Male,disloyal Customer,39,Business travel,Business,222,1,1,1,1,2,1,2,2,5,2,2,1,2,2,0,0.0,neutral or dissatisfied +82594,102135,Female,Loyal Customer,55,Business travel,Business,1552,2,2,2,2,3,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +82595,19956,Female,Loyal Customer,30,Business travel,Eco Plus,343,4,3,3,3,4,4,4,4,1,2,4,4,3,4,11,12.0,neutral or dissatisfied +82596,5502,Female,Loyal Customer,16,Business travel,Business,3895,3,2,2,2,3,3,3,3,1,2,3,4,3,3,0,4.0,neutral or dissatisfied +82597,68256,Male,Loyal Customer,67,Personal Travel,Eco,432,4,4,4,3,2,4,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +82598,64528,Male,disloyal Customer,39,Business travel,Business,247,1,1,1,3,3,1,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +82599,121922,Female,Loyal Customer,44,Business travel,Business,449,3,3,3,3,3,5,4,4,4,4,4,5,4,4,16,16.0,satisfied +82600,62325,Male,Loyal Customer,15,Personal Travel,Eco,414,3,3,3,3,3,4,4,4,3,3,3,4,1,4,161,155.0,neutral or dissatisfied +82601,103716,Female,Loyal Customer,65,Personal Travel,Eco,405,0,1,0,3,4,4,3,2,2,0,1,3,2,4,0,0.0,satisfied +82602,46150,Female,Loyal Customer,49,Business travel,Business,116,4,4,4,4,1,3,2,4,4,5,5,1,4,1,0,0.0,satisfied +82603,113533,Female,disloyal Customer,27,Business travel,Business,397,4,4,4,2,1,4,1,1,5,5,5,5,4,1,0,0.0,satisfied +82604,127573,Female,Loyal Customer,59,Personal Travel,Eco,1670,3,4,3,3,5,3,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +82605,92681,Female,Loyal Customer,40,Business travel,Business,507,1,4,4,4,2,4,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +82606,104004,Female,Loyal Customer,61,Business travel,Business,2793,3,1,1,1,5,3,3,3,3,3,3,4,3,2,24,17.0,neutral or dissatisfied +82607,120302,Female,Loyal Customer,60,Business travel,Business,268,2,2,2,2,2,5,5,4,4,4,4,4,4,3,2,8.0,satisfied +82608,128323,Male,disloyal Customer,23,Business travel,Eco,621,3,0,3,2,2,3,2,2,4,3,4,5,4,2,0,8.0,neutral or dissatisfied +82609,18642,Female,Loyal Customer,29,Personal Travel,Eco,127,4,4,4,3,1,4,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +82610,18676,Male,Loyal Customer,9,Personal Travel,Eco,383,2,3,2,3,4,2,4,4,2,2,3,2,2,4,65,100.0,neutral or dissatisfied +82611,113553,Female,Loyal Customer,52,Business travel,Eco,397,2,4,4,4,3,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +82612,6486,Female,disloyal Customer,40,Business travel,Business,557,1,1,1,4,5,1,1,5,3,3,3,2,4,5,45,39.0,neutral or dissatisfied +82613,47393,Female,disloyal Customer,22,Business travel,Eco,588,4,0,4,3,3,4,2,3,2,2,2,4,4,3,0,0.0,satisfied +82614,126754,Female,Loyal Customer,34,Personal Travel,Eco,2370,2,4,2,4,4,2,2,4,4,4,3,3,4,4,4,17.0,neutral or dissatisfied +82615,2944,Female,Loyal Customer,49,Business travel,Business,1813,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +82616,16435,Male,Loyal Customer,66,Business travel,Business,3919,2,5,5,5,1,3,3,2,2,2,2,2,2,3,19,16.0,neutral or dissatisfied +82617,103765,Female,disloyal Customer,37,Business travel,Business,1072,3,3,3,3,4,3,4,4,1,5,3,3,4,4,111,126.0,neutral or dissatisfied +82618,105707,Male,disloyal Customer,26,Business travel,Eco,842,2,2,2,2,5,2,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +82619,61629,Female,disloyal Customer,50,Business travel,Business,1333,4,4,4,3,4,4,4,4,3,5,4,3,4,4,14,4.0,satisfied +82620,117450,Female,disloyal Customer,38,Business travel,Business,1107,4,4,4,3,4,4,4,4,5,5,5,3,5,4,8,0.0,satisfied +82621,25076,Male,Loyal Customer,66,Business travel,Business,957,2,1,1,1,2,2,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +82622,76990,Male,Loyal Customer,46,Personal Travel,Business,422,4,1,2,3,1,2,3,5,5,2,5,4,5,4,0,0.0,satisfied +82623,42555,Male,Loyal Customer,54,Personal Travel,Eco Plus,1091,1,3,1,2,3,1,5,3,2,3,5,1,2,3,34,41.0,neutral or dissatisfied +82624,98681,Female,Loyal Customer,11,Personal Travel,Eco,994,4,5,4,2,5,4,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +82625,17633,Male,Loyal Customer,21,Personal Travel,Eco,980,3,4,3,4,3,2,2,2,3,3,3,2,2,2,190,,neutral or dissatisfied +82626,21675,Female,disloyal Customer,25,Business travel,Eco,746,4,4,4,5,2,4,2,2,3,4,3,5,4,2,4,5.0,neutral or dissatisfied +82627,56712,Female,Loyal Customer,31,Personal Travel,Eco,997,3,4,3,3,5,3,4,5,4,1,3,4,4,5,0,0.0,neutral or dissatisfied +82628,37706,Male,Loyal Customer,41,Personal Travel,Eco,1005,3,5,3,4,2,3,2,2,4,5,4,4,4,2,0,9.0,neutral or dissatisfied +82629,81974,Male,Loyal Customer,40,Business travel,Eco,1589,2,5,5,5,2,2,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +82630,94703,Female,disloyal Customer,15,Business travel,Eco,239,3,2,2,2,2,2,4,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +82631,5103,Male,Loyal Customer,28,Personal Travel,Eco,223,3,5,3,4,4,3,4,4,2,3,1,4,1,4,8,2.0,neutral or dissatisfied +82632,120866,Male,Loyal Customer,46,Business travel,Eco,861,4,5,5,5,5,4,5,5,2,4,3,2,4,5,11,16.0,neutral or dissatisfied +82633,120734,Female,disloyal Customer,22,Business travel,Eco,1089,2,2,2,4,2,5,5,2,5,4,4,5,3,5,41,150.0,neutral or dissatisfied +82634,43401,Female,Loyal Customer,44,Personal Travel,Eco,463,3,4,3,4,3,4,3,1,1,3,1,1,1,2,0,0.0,neutral or dissatisfied +82635,103347,Male,Loyal Customer,46,Business travel,Business,1371,3,3,3,3,2,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +82636,101677,Female,Loyal Customer,48,Business travel,Business,1500,4,4,4,4,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +82637,111067,Male,Loyal Customer,15,Personal Travel,Eco,197,4,4,0,2,2,0,1,2,3,5,1,1,5,2,0,2.0,satisfied +82638,6218,Male,Loyal Customer,45,Business travel,Business,413,3,3,3,3,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +82639,65388,Female,Loyal Customer,50,Personal Travel,Eco,432,2,2,2,4,1,4,3,3,3,2,2,2,3,4,9,5.0,neutral or dissatisfied +82640,61892,Male,Loyal Customer,34,Business travel,Business,2521,2,2,2,2,2,5,5,5,5,5,5,4,5,3,97,78.0,satisfied +82641,9995,Female,Loyal Customer,55,Personal Travel,Eco,508,1,4,1,3,5,5,4,4,4,1,5,5,4,5,0,3.0,neutral or dissatisfied +82642,97320,Female,Loyal Customer,40,Business travel,Business,3061,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +82643,17967,Female,Loyal Customer,28,Personal Travel,Eco,500,1,5,1,3,5,1,5,5,3,3,5,3,5,5,0,3.0,neutral or dissatisfied +82644,106230,Male,Loyal Customer,22,Personal Travel,Eco,471,3,3,3,5,2,3,2,2,5,3,5,1,4,2,18,15.0,neutral or dissatisfied +82645,96476,Male,Loyal Customer,57,Business travel,Eco,436,3,5,5,5,3,3,3,3,3,5,4,4,3,3,0,6.0,neutral or dissatisfied +82646,1187,Female,Loyal Customer,30,Personal Travel,Eco,134,4,5,0,1,1,0,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +82647,90056,Male,Loyal Customer,52,Business travel,Business,1588,3,3,3,3,4,5,5,5,5,5,5,5,5,5,8,0.0,satisfied +82648,111985,Male,Loyal Customer,60,Personal Travel,Eco,533,3,1,2,3,1,2,1,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +82649,21148,Male,Loyal Customer,21,Personal Travel,Eco Plus,152,2,5,2,3,1,2,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +82650,97086,Male,Loyal Customer,49,Business travel,Business,1476,2,2,2,2,5,4,4,5,5,4,5,4,5,4,21,18.0,satisfied +82651,87706,Female,Loyal Customer,45,Personal Travel,Eco,591,2,4,1,4,1,3,4,1,1,1,1,1,1,1,69,67.0,neutral or dissatisfied +82652,58462,Female,Loyal Customer,52,Business travel,Business,1882,2,2,3,2,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +82653,118161,Male,Loyal Customer,48,Business travel,Business,1444,1,1,1,1,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +82654,85082,Male,Loyal Customer,40,Business travel,Business,874,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +82655,92645,Male,Loyal Customer,20,Personal Travel,Eco,453,3,5,3,4,4,3,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +82656,46304,Female,Loyal Customer,10,Personal Travel,Eco,680,4,5,3,5,4,3,4,4,3,5,5,5,4,4,0,0.0,satisfied +82657,73514,Female,Loyal Customer,33,Personal Travel,Eco Plus,1144,2,4,3,3,4,3,4,4,3,4,4,4,5,4,16,39.0,neutral or dissatisfied +82658,32713,Female,Loyal Customer,54,Business travel,Eco,163,4,3,3,3,3,3,3,4,4,4,4,1,4,2,0,0.0,satisfied +82659,51814,Male,Loyal Customer,42,Personal Travel,Eco,370,4,4,4,3,5,4,3,5,1,1,3,2,1,5,20,10.0,neutral or dissatisfied +82660,6543,Female,Loyal Customer,7,Personal Travel,Business,607,3,4,2,1,2,2,2,2,5,5,5,5,5,2,6,10.0,neutral or dissatisfied +82661,83544,Female,Loyal Customer,63,Personal Travel,Eco,1121,2,4,2,4,2,5,4,3,3,2,3,4,3,4,0,11.0,neutral or dissatisfied +82662,122849,Female,Loyal Customer,32,Business travel,Business,2071,1,5,2,5,1,1,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +82663,81117,Male,disloyal Customer,23,Business travel,Business,991,0,5,0,1,1,0,1,1,3,3,4,4,5,1,0,0.0,satisfied +82664,42573,Female,disloyal Customer,27,Business travel,Eco,315,3,3,3,3,3,3,2,3,3,1,3,1,4,3,1,20.0,neutral or dissatisfied +82665,99820,Female,Loyal Customer,47,Business travel,Business,587,3,3,2,3,3,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +82666,100241,Male,Loyal Customer,60,Business travel,Business,1130,2,2,4,2,4,4,5,5,5,5,5,5,5,4,14,2.0,satisfied +82667,113361,Female,Loyal Customer,50,Business travel,Business,3291,5,1,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +82668,86824,Male,Loyal Customer,26,Business travel,Eco,484,2,1,1,1,2,2,2,2,4,5,2,2,2,2,9,0.0,neutral or dissatisfied +82669,49362,Female,Loyal Customer,40,Business travel,Business,1667,3,1,1,1,3,2,2,3,3,3,3,2,3,3,20,4.0,neutral or dissatisfied +82670,73941,Female,Loyal Customer,48,Business travel,Business,2342,3,4,4,4,3,3,3,4,5,3,3,3,3,3,4,0.0,neutral or dissatisfied +82671,123055,Female,Loyal Customer,45,Business travel,Business,507,4,4,4,4,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +82672,105980,Female,Loyal Customer,26,Personal Travel,Eco,2295,3,3,3,1,3,1,3,4,3,1,1,3,5,3,0,28.0,neutral or dissatisfied +82673,90600,Female,Loyal Customer,48,Business travel,Business,404,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,9.0,satisfied +82674,26946,Male,Loyal Customer,27,Business travel,Business,2402,1,5,5,5,1,1,1,1,4,3,2,4,4,1,25,2.0,neutral or dissatisfied +82675,69087,Female,Loyal Customer,42,Personal Travel,Eco,1389,4,4,4,3,2,4,5,3,3,4,3,5,3,4,0,56.0,neutral or dissatisfied +82676,122725,Male,Loyal Customer,54,Business travel,Business,2375,5,5,4,5,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +82677,118897,Male,disloyal Customer,34,Business travel,Business,570,1,1,1,3,2,1,4,2,4,4,4,4,5,2,0,4.0,neutral or dissatisfied +82678,127679,Male,Loyal Customer,20,Personal Travel,Eco,2153,1,5,1,2,3,1,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +82679,95184,Male,Loyal Customer,26,Personal Travel,Eco,677,3,5,3,4,5,3,5,5,1,1,4,4,2,5,15,8.0,neutral or dissatisfied +82680,118385,Female,disloyal Customer,22,Business travel,Business,370,5,3,5,1,2,5,2,2,3,5,4,4,5,2,59,41.0,satisfied +82681,58812,Male,Loyal Customer,36,Personal Travel,Eco,1012,4,3,3,2,4,3,1,4,5,1,5,1,3,4,6,0.0,neutral or dissatisfied +82682,65939,Male,Loyal Customer,39,Business travel,Business,3841,3,3,3,3,2,5,4,2,2,2,2,3,2,3,91,84.0,satisfied +82683,42403,Male,Loyal Customer,12,Business travel,Eco Plus,817,2,3,1,3,2,2,1,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +82684,67015,Female,Loyal Customer,53,Business travel,Business,3907,2,2,2,2,2,5,4,4,4,4,4,5,4,4,10,0.0,satisfied +82685,69954,Female,Loyal Customer,64,Personal Travel,Eco,2174,3,4,3,1,4,4,4,1,1,3,1,3,1,3,1,0.0,neutral or dissatisfied +82686,101886,Female,Loyal Customer,28,Business travel,Business,2039,2,2,2,2,3,4,3,3,4,3,3,4,4,3,19,0.0,satisfied +82687,97235,Female,Loyal Customer,45,Business travel,Business,2157,0,0,0,3,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +82688,112345,Male,Loyal Customer,24,Business travel,Business,909,1,1,2,1,5,4,5,5,3,4,4,3,5,5,0,0.0,satisfied +82689,101320,Male,Loyal Customer,48,Business travel,Business,2687,5,5,5,5,4,5,3,5,5,5,5,4,5,2,8,0.0,satisfied +82690,75004,Female,Loyal Customer,53,Business travel,Business,3382,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +82691,52361,Female,Loyal Customer,42,Personal Travel,Eco,651,3,2,3,3,2,2,3,1,1,3,1,2,1,1,0,0.0,neutral or dissatisfied +82692,19910,Male,Loyal Customer,39,Business travel,Business,2069,2,2,4,2,5,5,5,2,5,1,3,5,5,5,206,219.0,satisfied +82693,119978,Female,Loyal Customer,37,Personal Travel,Eco,868,1,3,1,2,1,1,1,1,1,2,2,3,3,1,0,0.0,neutral or dissatisfied +82694,576,Female,disloyal Customer,68,Business travel,Business,158,2,2,2,4,3,2,3,3,3,4,5,4,5,3,0,0.0,neutral or dissatisfied +82695,59072,Female,Loyal Customer,27,Business travel,Eco,1846,2,5,5,5,2,2,2,2,2,2,3,3,2,2,2,0.0,neutral or dissatisfied +82696,45492,Male,Loyal Customer,41,Personal Travel,Eco,587,2,4,2,4,2,2,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +82697,106044,Male,Loyal Customer,21,Business travel,Business,3479,2,3,3,3,2,1,2,2,3,3,4,4,3,2,4,0.0,neutral or dissatisfied +82698,17710,Male,Loyal Customer,15,Personal Travel,Eco,311,3,5,3,3,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +82699,22237,Female,Loyal Customer,57,Business travel,Business,3926,2,2,2,2,5,5,4,5,5,5,4,4,5,5,0,0.0,satisfied +82700,116451,Male,Loyal Customer,12,Personal Travel,Eco,446,1,4,1,3,1,1,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +82701,36397,Female,Loyal Customer,33,Personal Travel,Eco Plus,2381,0,4,0,3,1,0,1,1,3,5,4,5,4,1,0,0.0,satisfied +82702,102884,Female,Loyal Customer,36,Business travel,Business,472,1,1,1,1,5,5,5,4,4,3,4,5,4,3,0,2.0,satisfied +82703,55455,Male,Loyal Customer,37,Business travel,Business,2327,4,4,4,4,4,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +82704,101625,Male,Loyal Customer,20,Personal Travel,Eco,1139,4,1,4,3,5,4,5,5,3,5,2,1,4,5,0,0.0,satisfied +82705,82775,Male,Loyal Customer,42,Business travel,Business,3117,2,2,4,2,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +82706,122529,Female,Loyal Customer,55,Business travel,Business,500,4,4,4,4,3,5,4,3,3,3,3,3,3,4,2,0.0,satisfied +82707,40228,Female,Loyal Customer,73,Business travel,Eco,463,3,5,5,5,3,3,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +82708,3428,Female,Loyal Customer,70,Personal Travel,Eco,213,4,4,4,3,1,4,3,4,4,4,3,3,4,4,0,0.0,neutral or dissatisfied +82709,95773,Female,Loyal Customer,48,Personal Travel,Eco,419,4,1,4,3,4,3,4,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +82710,39332,Female,Loyal Customer,34,Personal Travel,Eco Plus,67,1,4,1,1,4,1,4,4,4,2,4,4,5,4,18,20.0,neutral or dissatisfied +82711,75220,Female,Loyal Customer,53,Business travel,Eco,346,4,5,5,5,1,1,4,3,3,4,3,3,3,2,12,26.0,satisfied +82712,35855,Female,Loyal Customer,42,Business travel,Business,2623,2,5,5,5,5,3,3,2,2,2,2,3,2,1,22,30.0,neutral or dissatisfied +82713,36940,Male,Loyal Customer,45,Business travel,Eco,718,4,5,5,5,4,4,4,4,1,1,5,1,2,4,0,0.0,satisfied +82714,123392,Male,Loyal Customer,28,Business travel,Business,1337,1,1,4,1,4,4,4,4,4,5,5,3,5,4,0,0.0,satisfied +82715,52250,Male,Loyal Customer,35,Business travel,Eco,261,3,4,4,4,3,3,3,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +82716,48810,Male,Loyal Customer,50,Personal Travel,Business,89,4,4,0,1,2,5,5,4,4,0,4,5,4,3,23,14.0,neutral or dissatisfied +82717,49896,Female,disloyal Customer,30,Business travel,Eco,109,3,2,3,4,5,3,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +82718,86248,Female,Loyal Customer,36,Personal Travel,Eco,164,3,3,3,3,3,3,3,3,4,3,4,4,3,3,17,21.0,neutral or dissatisfied +82719,12533,Female,Loyal Customer,30,Business travel,Business,2944,5,5,5,5,5,5,5,5,3,1,2,4,3,5,0,0.0,satisfied +82720,120165,Female,Loyal Customer,48,Business travel,Business,119,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +82721,62691,Male,Loyal Customer,37,Personal Travel,Business,2556,3,2,3,4,3,2,4,4,2,4,4,4,4,4,148,182.0,neutral or dissatisfied +82722,61524,Female,Loyal Customer,38,Personal Travel,Eco,2288,3,5,3,1,1,3,1,1,5,4,2,3,5,1,0,0.0,neutral or dissatisfied +82723,41182,Female,Loyal Customer,32,Business travel,Business,3405,2,2,2,2,4,4,4,4,3,4,2,4,1,4,14,23.0,satisfied +82724,80756,Female,Loyal Customer,54,Business travel,Business,2279,4,4,4,4,5,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +82725,57139,Female,Loyal Customer,44,Business travel,Business,1222,1,1,1,1,2,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +82726,7408,Male,Loyal Customer,42,Business travel,Business,2935,2,2,2,2,5,5,4,4,4,4,4,4,4,3,60,55.0,satisfied +82727,77936,Female,disloyal Customer,37,Business travel,Business,152,3,3,3,3,2,3,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +82728,91813,Female,Loyal Customer,54,Personal Travel,Eco,584,3,5,3,2,4,4,4,5,5,3,2,4,5,3,0,0.0,neutral or dissatisfied +82729,56121,Male,Loyal Customer,27,Business travel,Business,1400,5,1,5,5,2,2,2,2,5,4,5,5,5,2,0,0.0,satisfied +82730,79233,Female,Loyal Customer,42,Business travel,Eco,1521,5,4,4,4,3,3,3,5,5,5,5,5,5,5,31,22.0,satisfied +82731,105260,Female,disloyal Customer,24,Business travel,Eco,873,5,5,5,2,3,5,3,3,5,5,3,5,4,3,0,0.0,satisfied +82732,28055,Male,Loyal Customer,46,Business travel,Business,2607,1,1,5,1,2,2,2,2,5,3,3,2,2,2,0,15.0,satisfied +82733,64044,Male,Loyal Customer,50,Business travel,Business,3604,2,2,2,2,2,5,5,5,5,5,5,3,5,4,12,35.0,satisfied +82734,34961,Female,Loyal Customer,56,Personal Travel,Eco Plus,187,2,5,0,1,0,3,3,5,3,4,4,3,4,3,118,160.0,neutral or dissatisfied +82735,8940,Female,Loyal Customer,39,Business travel,Business,2258,0,0,0,4,4,4,4,5,5,5,5,4,5,3,82,102.0,satisfied +82736,57442,Male,Loyal Customer,46,Personal Travel,Eco,1735,2,4,2,3,4,2,5,4,2,3,4,5,3,4,28,1.0,neutral or dissatisfied +82737,34013,Female,Loyal Customer,55,Personal Travel,Eco,1598,1,5,1,2,3,5,5,2,2,1,2,4,2,4,18,4.0,neutral or dissatisfied +82738,38726,Male,disloyal Customer,55,Business travel,Business,354,2,2,2,1,2,2,5,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +82739,112179,Male,Loyal Customer,41,Personal Travel,Eco,895,2,4,1,2,3,1,3,3,3,3,5,3,5,3,10,0.0,neutral or dissatisfied +82740,45735,Male,Loyal Customer,42,Personal Travel,Eco,1463,3,4,3,1,1,3,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +82741,27222,Male,Loyal Customer,39,Business travel,Business,1024,1,1,1,1,4,4,5,2,2,2,2,2,2,5,0,0.0,satisfied +82742,70794,Male,Loyal Customer,48,Business travel,Eco,328,4,4,4,4,4,4,4,4,2,2,4,3,4,4,0,0.0,satisfied +82743,51054,Female,Loyal Customer,57,Personal Travel,Eco,266,4,0,4,1,2,4,4,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +82744,8416,Female,disloyal Customer,46,Business travel,Eco,862,1,1,1,2,3,1,3,3,2,3,3,2,2,3,29,44.0,neutral or dissatisfied +82745,4593,Female,Loyal Customer,36,Business travel,Eco,416,2,3,3,3,2,2,2,2,1,1,3,3,3,2,9,20.0,neutral or dissatisfied +82746,51309,Male,disloyal Customer,23,Business travel,Eco,89,3,3,3,3,1,3,1,1,1,2,3,1,3,1,62,61.0,neutral or dissatisfied +82747,16634,Female,disloyal Customer,22,Business travel,Eco,605,0,4,0,5,2,0,2,2,4,2,5,1,4,2,4,0.0,satisfied +82748,123169,Female,disloyal Customer,22,Business travel,Business,107,3,2,3,4,4,3,4,4,1,5,4,2,4,4,1,0.0,neutral or dissatisfied +82749,48073,Male,Loyal Customer,40,Business travel,Business,3004,5,5,5,5,5,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +82750,3627,Male,Loyal Customer,44,Business travel,Business,427,2,5,2,2,4,4,4,4,4,4,4,4,4,3,74,53.0,satisfied +82751,74076,Male,Loyal Customer,20,Business travel,Business,2703,5,5,4,5,3,3,3,3,4,4,5,4,4,3,0,0.0,satisfied +82752,3730,Female,Loyal Customer,10,Personal Travel,Eco,431,4,4,4,1,4,4,3,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +82753,14060,Male,Loyal Customer,42,Business travel,Eco,319,4,2,2,2,4,4,4,4,5,2,3,1,2,4,14,6.0,satisfied +82754,15399,Male,disloyal Customer,21,Business travel,Eco,433,3,0,3,1,2,3,2,2,5,3,4,2,3,2,0,0.0,neutral or dissatisfied +82755,118988,Male,Loyal Customer,46,Business travel,Business,479,2,2,2,2,2,5,4,5,5,5,5,3,5,3,10,13.0,satisfied +82756,66717,Male,Loyal Customer,23,Personal Travel,Eco,802,2,5,2,2,4,2,4,4,1,1,1,4,1,4,42,38.0,neutral or dissatisfied +82757,90422,Male,disloyal Customer,36,Business travel,Business,444,3,3,3,1,4,3,4,4,3,5,5,4,4,4,0,3.0,neutral or dissatisfied +82758,115646,Male,Loyal Customer,31,Business travel,Eco,480,3,2,2,2,3,3,3,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +82759,42232,Female,Loyal Customer,41,Business travel,Business,3904,3,3,3,3,1,3,3,4,4,4,4,4,4,1,0,0.0,satisfied +82760,116124,Female,Loyal Customer,31,Personal Travel,Eco,337,4,5,5,2,1,5,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +82761,84745,Female,disloyal Customer,34,Business travel,Business,534,2,2,2,1,5,2,4,5,5,2,4,4,5,5,9,0.0,neutral or dissatisfied +82762,7423,Female,Loyal Customer,26,Business travel,Eco,552,3,3,3,3,3,3,1,3,4,5,3,2,3,3,0,11.0,neutral or dissatisfied +82763,22838,Female,Loyal Customer,33,Business travel,Business,1553,5,5,5,5,4,1,5,5,5,5,5,4,5,1,0,4.0,satisfied +82764,97667,Female,Loyal Customer,9,Business travel,Business,491,1,1,1,1,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +82765,125976,Male,disloyal Customer,19,Business travel,Business,590,4,4,4,3,3,4,1,3,5,4,5,5,5,3,0,2.0,satisfied +82766,119404,Female,disloyal Customer,24,Business travel,Eco,399,1,2,1,3,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +82767,52931,Male,Loyal Customer,20,Personal Travel,Eco,679,4,4,4,3,1,4,1,1,3,5,4,4,5,1,8,0.0,neutral or dissatisfied +82768,37634,Male,Loyal Customer,34,Personal Travel,Eco,972,2,4,2,2,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +82769,55208,Male,Loyal Customer,49,Business travel,Business,2153,2,2,4,2,2,4,4,3,3,3,3,3,3,5,13,8.0,satisfied +82770,124439,Male,Loyal Customer,50,Business travel,Eco Plus,862,4,5,5,5,4,4,4,4,2,1,3,2,5,4,0,5.0,satisfied +82771,104178,Male,Loyal Customer,17,Personal Travel,Eco,349,3,4,3,4,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +82772,38960,Male,disloyal Customer,27,Business travel,Business,313,2,2,2,4,1,2,1,1,3,3,3,1,4,1,40,13.0,neutral or dissatisfied +82773,119335,Female,Loyal Customer,56,Personal Travel,Eco,214,4,1,4,4,5,3,3,4,4,4,1,2,4,1,0,0.0,neutral or dissatisfied +82774,73360,Female,Loyal Customer,72,Business travel,Eco,1144,2,1,1,1,3,3,3,2,2,2,2,4,2,4,0,17.0,neutral or dissatisfied +82775,81171,Male,disloyal Customer,34,Business travel,Business,2404,3,3,3,1,1,3,1,1,5,4,3,4,5,1,0,0.0,neutral or dissatisfied +82776,117377,Male,Loyal Customer,43,Business travel,Business,2688,2,2,3,2,2,4,4,5,5,5,5,4,5,3,22,0.0,satisfied +82777,38051,Male,Loyal Customer,52,Business travel,Business,1954,1,1,1,1,4,3,4,5,5,5,5,1,5,5,0,0.0,satisfied +82778,63461,Female,Loyal Customer,51,Business travel,Business,337,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +82779,52682,Female,Loyal Customer,46,Personal Travel,Eco,160,2,4,0,3,5,3,3,5,5,0,5,3,5,4,0,2.0,neutral or dissatisfied +82780,110839,Male,Loyal Customer,38,Personal Travel,Eco Plus,990,3,4,4,3,2,4,3,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +82781,97520,Male,Loyal Customer,25,Business travel,Eco,439,4,3,3,3,4,4,4,3,3,4,4,4,1,4,164,201.0,neutral or dissatisfied +82782,25422,Male,Loyal Customer,60,Personal Travel,Eco Plus,990,4,5,4,2,2,4,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +82783,109286,Female,Loyal Customer,55,Business travel,Business,3947,4,4,4,4,5,5,5,4,4,4,4,3,4,4,35,13.0,satisfied +82784,19791,Female,Loyal Customer,11,Personal Travel,Eco,667,3,1,3,2,3,3,2,1,2,2,2,2,2,2,280,252.0,neutral or dissatisfied +82785,53150,Male,Loyal Customer,39,Business travel,Business,2266,4,2,2,2,3,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +82786,62858,Male,Loyal Customer,49,Business travel,Business,2218,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +82787,72664,Male,Loyal Customer,44,Personal Travel,Eco,985,3,5,3,5,4,3,2,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +82788,108484,Female,disloyal Customer,20,Business travel,Eco,570,1,3,1,3,4,1,4,4,2,5,4,3,4,4,67,57.0,neutral or dissatisfied +82789,17693,Male,Loyal Customer,32,Business travel,Eco,680,0,0,0,1,3,0,3,3,3,1,1,3,4,3,0,0.0,satisfied +82790,46457,Female,disloyal Customer,33,Business travel,Business,73,4,4,4,5,4,4,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +82791,43413,Male,Loyal Customer,47,Business travel,Eco Plus,347,5,5,5,5,5,5,5,5,3,1,3,2,5,5,0,2.0,satisfied +82792,20664,Female,Loyal Customer,41,Business travel,Business,522,2,2,2,2,5,2,1,5,5,5,5,5,5,2,15,0.0,satisfied +82793,76608,Male,Loyal Customer,37,Business travel,Eco,547,4,1,1,1,4,4,4,4,1,5,4,2,3,4,42,38.0,neutral or dissatisfied +82794,2721,Female,Loyal Customer,63,Personal Travel,Eco Plus,562,2,3,2,2,4,2,3,1,1,2,1,2,1,1,17,19.0,neutral or dissatisfied +82795,101197,Female,Loyal Customer,17,Personal Travel,Eco,1090,1,5,1,4,4,1,4,4,2,5,2,2,2,4,31,44.0,neutral or dissatisfied +82796,88957,Female,Loyal Customer,30,Business travel,Business,1312,5,5,5,5,3,3,3,3,4,3,4,3,4,3,22,45.0,satisfied +82797,89139,Female,Loyal Customer,43,Business travel,Business,2139,1,1,1,1,3,4,4,5,5,4,5,4,5,5,12,0.0,satisfied +82798,73056,Male,Loyal Customer,40,Business travel,Eco Plus,1096,1,3,3,3,1,1,1,1,4,1,2,3,2,1,0,0.0,neutral or dissatisfied +82799,11514,Male,Loyal Customer,42,Personal Travel,Eco Plus,429,4,4,5,5,3,5,3,3,3,5,3,1,1,3,0,0.0,neutral or dissatisfied +82800,53287,Male,Loyal Customer,53,Business travel,Eco,811,5,1,5,1,5,5,5,5,4,4,3,4,4,5,118,103.0,satisfied +82801,20414,Female,Loyal Customer,45,Business travel,Eco,299,4,4,2,4,4,4,4,5,5,2,3,4,5,4,146,136.0,satisfied +82802,14769,Male,Loyal Customer,35,Business travel,Eco Plus,463,4,3,2,3,4,4,4,4,4,2,3,1,1,4,3,0.0,satisfied +82803,28375,Female,Loyal Customer,14,Business travel,Business,2559,2,2,2,2,4,4,4,4,1,3,1,2,2,4,0,0.0,satisfied +82804,123600,Male,Loyal Customer,58,Personal Travel,Eco,1773,2,2,2,4,5,2,5,5,1,3,4,3,3,5,13,0.0,neutral or dissatisfied +82805,47707,Male,Loyal Customer,49,Business travel,Eco Plus,1464,5,5,2,2,5,5,5,5,5,1,3,3,5,5,21,15.0,satisfied +82806,96581,Male,Loyal Customer,35,Personal Travel,Eco,333,3,4,3,3,3,3,3,3,3,2,5,3,5,3,4,1.0,neutral or dissatisfied +82807,16305,Male,Loyal Customer,27,Business travel,Eco,594,5,5,5,5,5,5,5,5,1,5,3,5,4,5,0,42.0,satisfied +82808,51422,Male,Loyal Customer,12,Personal Travel,Eco Plus,308,3,4,3,2,1,3,1,1,2,3,1,1,5,1,0,0.0,neutral or dissatisfied +82809,52927,Female,Loyal Customer,57,Personal Travel,Eco,679,5,4,5,4,2,4,5,3,3,5,3,4,3,5,14,19.0,satisfied +82810,29157,Female,Loyal Customer,23,Business travel,Eco Plus,954,3,2,5,2,3,3,4,3,1,2,4,3,3,3,0,9.0,neutral or dissatisfied +82811,43085,Female,Loyal Customer,12,Personal Travel,Eco,391,3,5,3,4,4,3,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +82812,79704,Male,Loyal Customer,67,Personal Travel,Eco,749,2,1,3,1,5,3,5,5,1,2,1,1,2,5,0,0.0,neutral or dissatisfied +82813,13847,Male,Loyal Customer,24,Personal Travel,Eco,594,2,1,3,4,1,3,1,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +82814,37240,Female,Loyal Customer,10,Personal Travel,Business,1041,3,5,3,4,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +82815,90485,Female,Loyal Customer,29,Business travel,Business,2600,4,4,4,4,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +82816,37623,Male,Loyal Customer,63,Personal Travel,Eco,989,2,4,2,4,2,2,1,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +82817,67105,Male,Loyal Customer,23,Business travel,Business,985,1,3,3,3,1,1,1,1,4,4,4,1,3,1,12,4.0,neutral or dissatisfied +82818,1027,Male,disloyal Customer,22,Business travel,Eco,309,4,1,4,3,3,4,3,3,1,4,1,3,4,3,0,0.0,satisfied +82819,72656,Female,Loyal Customer,67,Personal Travel,Eco,1119,3,5,3,5,1,4,4,5,5,3,5,1,5,2,82,76.0,neutral or dissatisfied +82820,10325,Female,Loyal Customer,33,Business travel,Business,1763,3,3,3,3,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +82821,82333,Female,Loyal Customer,64,Personal Travel,Eco Plus,456,1,4,1,3,1,3,5,4,4,1,4,5,4,2,23,55.0,neutral or dissatisfied +82822,38899,Male,Loyal Customer,55,Business travel,Business,320,0,0,0,3,4,5,3,2,2,1,1,2,2,1,0,0.0,satisfied +82823,89001,Male,Loyal Customer,41,Business travel,Business,1919,2,2,2,2,5,5,4,4,4,4,4,4,4,3,0,20.0,satisfied +82824,48092,Male,disloyal Customer,24,Business travel,Eco,391,4,0,4,5,3,4,3,3,3,2,4,2,3,3,0,2.0,satisfied +82825,64456,Male,Loyal Customer,55,Personal Travel,Eco,989,1,2,1,2,4,1,4,4,2,5,2,3,2,4,13,14.0,neutral or dissatisfied +82826,44531,Male,disloyal Customer,22,Business travel,Eco,157,3,1,3,2,2,3,2,2,2,1,2,2,2,2,28,55.0,neutral or dissatisfied +82827,52131,Male,disloyal Customer,34,Business travel,Business,261,2,2,2,1,5,2,5,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +82828,58837,Female,Loyal Customer,37,Personal Travel,Eco Plus,1005,1,4,1,1,3,1,3,3,5,4,2,5,3,3,116,112.0,neutral or dissatisfied +82829,97757,Female,Loyal Customer,16,Personal Travel,Eco,587,2,4,2,2,3,2,3,3,5,2,5,3,5,3,7,0.0,neutral or dissatisfied +82830,123854,Female,Loyal Customer,15,Business travel,Eco,544,4,3,3,3,4,4,4,4,3,2,4,3,4,4,15,40.0,neutral or dissatisfied +82831,82481,Female,Loyal Customer,63,Personal Travel,Eco,509,3,4,3,1,4,5,5,3,3,3,3,4,3,5,1,0.0,neutral or dissatisfied +82832,102293,Male,Loyal Customer,44,Business travel,Business,223,3,3,3,3,5,4,4,4,4,4,5,5,4,3,0,0.0,satisfied +82833,50017,Female,Loyal Customer,37,Business travel,Business,110,3,1,1,1,1,3,3,3,3,3,3,1,3,1,0,1.0,neutral or dissatisfied +82834,54135,Female,Loyal Customer,44,Business travel,Business,1400,1,1,5,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +82835,7282,Female,Loyal Customer,8,Personal Travel,Eco,135,2,0,2,5,3,2,3,3,4,4,4,3,4,3,8,0.0,neutral or dissatisfied +82836,52778,Female,Loyal Customer,30,Business travel,Business,1874,2,2,2,2,5,5,5,5,2,3,5,5,5,5,0,0.0,satisfied +82837,50027,Male,Loyal Customer,42,Business travel,Business,308,1,1,1,1,3,4,4,1,1,1,1,3,1,4,18,25.0,neutral or dissatisfied +82838,127768,Male,Loyal Customer,65,Personal Travel,Eco,601,2,2,1,4,3,1,3,3,1,4,4,2,4,3,0,0.0,neutral or dissatisfied +82839,53017,Male,disloyal Customer,25,Business travel,Business,1190,4,4,4,5,1,4,1,1,4,4,2,1,3,1,31,17.0,satisfied +82840,68875,Male,Loyal Customer,43,Business travel,Business,2987,2,2,3,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +82841,44516,Male,Loyal Customer,20,Business travel,Eco,157,4,4,4,4,4,4,4,4,5,4,3,2,4,4,0,0.0,satisfied +82842,60490,Male,Loyal Customer,32,Business travel,Eco,862,4,5,1,1,4,4,4,4,3,2,3,3,3,4,38,33.0,neutral or dissatisfied +82843,82920,Female,Loyal Customer,21,Personal Travel,Eco,594,2,3,2,3,3,2,3,3,2,1,4,3,2,3,6,27.0,neutral or dissatisfied +82844,28298,Female,Loyal Customer,41,Business travel,Business,3188,5,5,5,5,3,1,2,4,4,4,4,2,4,1,0,2.0,satisfied +82845,49713,Male,disloyal Customer,32,Business travel,Eco,209,2,5,2,4,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +82846,58989,Female,Loyal Customer,54,Business travel,Eco,1744,2,4,4,4,1,3,3,2,2,2,2,2,2,1,16,19.0,neutral or dissatisfied +82847,28159,Male,disloyal Customer,55,Business travel,Eco,150,4,0,3,1,2,3,2,2,2,3,3,2,4,2,9,10.0,neutral or dissatisfied +82848,60583,Female,disloyal Customer,54,Business travel,Eco,1369,4,4,4,4,3,4,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +82849,67024,Female,disloyal Customer,18,Business travel,Eco,1119,2,1,1,1,4,1,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +82850,2634,Male,Loyal Customer,16,Personal Travel,Eco Plus,280,4,4,3,4,1,3,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +82851,8405,Male,Loyal Customer,25,Business travel,Business,2829,1,3,1,1,4,4,4,4,5,4,4,5,5,4,23,24.0,satisfied +82852,23610,Male,Loyal Customer,32,Personal Travel,Eco,589,1,3,1,3,1,1,1,1,5,2,4,1,3,1,49,57.0,neutral or dissatisfied +82853,21471,Male,disloyal Customer,38,Business travel,Eco,164,5,3,5,4,2,3,2,2,2,1,2,4,1,2,0,0.0,satisfied +82854,7284,Female,Loyal Customer,53,Personal Travel,Eco,116,2,3,2,3,3,2,2,5,5,2,5,2,5,4,72,66.0,neutral or dissatisfied +82855,127005,Male,Loyal Customer,42,Business travel,Business,2305,4,2,2,2,3,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +82856,70385,Female,Loyal Customer,55,Business travel,Business,1562,1,1,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +82857,96631,Female,disloyal Customer,48,Business travel,Eco,1036,2,2,2,3,3,2,3,3,2,4,4,3,4,3,4,0.0,neutral or dissatisfied +82858,63485,Female,Loyal Customer,56,Business travel,Business,337,4,4,4,4,3,5,5,4,4,4,4,4,4,4,6,3.0,satisfied +82859,63738,Male,Loyal Customer,65,Personal Travel,Eco,1660,3,4,3,4,3,3,3,3,2,5,2,1,4,3,0,0.0,neutral or dissatisfied +82860,86890,Female,Loyal Customer,60,Business travel,Business,352,4,3,3,3,3,2,2,4,4,4,4,3,4,4,18,8.0,neutral or dissatisfied +82861,9691,Female,disloyal Customer,25,Business travel,Eco,212,4,2,5,4,4,5,1,4,1,1,3,3,3,4,105,100.0,neutral or dissatisfied +82862,64681,Male,Loyal Customer,41,Business travel,Business,247,0,0,0,3,4,5,4,5,5,1,1,4,5,4,3,5.0,satisfied +82863,12669,Male,Loyal Customer,22,Business travel,Eco,721,5,3,5,5,5,5,4,5,1,5,3,2,2,5,4,0.0,satisfied +82864,24666,Female,Loyal Customer,34,Personal Travel,Eco,834,3,2,3,4,1,3,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +82865,55898,Female,Loyal Customer,38,Business travel,Eco,473,1,4,4,4,1,1,1,1,1,2,3,3,4,1,0,5.0,neutral or dissatisfied +82866,94782,Female,Loyal Customer,15,Business travel,Eco,189,1,5,5,5,1,1,2,1,1,1,4,4,4,1,0,0.0,neutral or dissatisfied +82867,61574,Male,Loyal Customer,31,Business travel,Business,2711,1,3,3,3,1,1,1,1,2,2,4,4,3,1,12,0.0,neutral or dissatisfied +82868,117015,Female,disloyal Customer,42,Business travel,Eco,370,3,1,3,2,3,3,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +82869,16819,Female,Loyal Customer,9,Business travel,Eco,645,4,4,2,4,4,4,1,4,4,4,2,3,3,4,3,16.0,neutral or dissatisfied +82870,267,Female,Loyal Customer,40,Business travel,Business,2026,1,1,1,1,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +82871,116548,Male,Loyal Customer,50,Personal Travel,Eco,325,3,5,3,5,5,3,5,5,1,3,5,2,5,5,112,117.0,neutral or dissatisfied +82872,32682,Male,Loyal Customer,46,Business travel,Business,163,2,1,4,1,2,4,3,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +82873,46655,Male,Loyal Customer,43,Business travel,Business,2373,0,4,1,5,5,5,5,2,2,2,2,3,2,4,0,4.0,satisfied +82874,96709,Female,disloyal Customer,29,Business travel,Eco,696,4,5,5,3,1,5,1,1,4,3,3,1,2,1,0,0.0,neutral or dissatisfied +82875,39586,Male,disloyal Customer,36,Business travel,Eco,954,2,2,2,1,3,2,3,3,2,2,3,1,3,3,0,5.0,neutral or dissatisfied +82876,99548,Male,Loyal Customer,45,Business travel,Business,3927,1,1,1,1,2,4,4,4,4,4,4,5,4,4,17,7.0,satisfied +82877,32775,Male,Loyal Customer,57,Business travel,Business,3242,5,5,5,5,4,5,5,5,5,5,5,2,5,3,0,0.0,satisfied +82878,93629,Female,Loyal Customer,37,Personal Travel,Eco,704,2,5,1,5,1,2,2,3,2,5,4,2,4,2,236,226.0,neutral or dissatisfied +82879,15645,Male,Loyal Customer,37,Personal Travel,Eco Plus,228,2,2,2,4,4,2,4,4,3,2,4,2,3,4,9,1.0,neutral or dissatisfied +82880,99022,Male,Loyal Customer,27,Personal Travel,Business,1009,3,4,3,2,2,3,2,2,3,1,2,2,3,2,0,0.0,neutral or dissatisfied +82881,36408,Female,disloyal Customer,23,Business travel,Business,369,4,5,5,3,2,5,2,2,3,2,4,5,4,2,105,101.0,satisfied +82882,36107,Female,disloyal Customer,32,Business travel,Eco Plus,413,3,3,3,1,2,3,2,2,2,5,5,1,5,2,0,0.0,neutral or dissatisfied +82883,71129,Male,Loyal Customer,42,Business travel,Eco,1739,3,3,5,3,3,3,3,3,3,3,2,4,2,3,57,70.0,neutral or dissatisfied +82884,10678,Female,Loyal Customer,40,Business travel,Business,312,0,0,0,1,4,4,5,1,1,1,1,4,1,5,0,0.0,satisfied +82885,13172,Male,Loyal Customer,27,Business travel,Business,542,5,5,5,5,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +82886,128016,Female,Loyal Customer,51,Personal Travel,Business,1440,2,4,2,4,2,2,2,5,2,3,4,2,4,2,194,186.0,neutral or dissatisfied +82887,84596,Female,Loyal Customer,31,Business travel,Business,2254,1,3,3,3,1,1,1,1,1,1,3,4,3,1,0,0.0,neutral or dissatisfied +82888,4624,Male,Loyal Customer,60,Business travel,Business,364,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +82889,77370,Male,Loyal Customer,53,Business travel,Business,3849,5,5,5,5,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +82890,128077,Female,Loyal Customer,56,Business travel,Business,2917,3,3,3,3,4,3,3,4,2,5,5,3,4,3,0,0.0,satisfied +82891,86244,Male,Loyal Customer,45,Personal Travel,Eco,226,1,4,0,4,3,0,3,3,5,2,5,5,4,3,22,49.0,neutral or dissatisfied +82892,81569,Male,Loyal Customer,18,Personal Travel,Eco,936,2,5,2,1,4,2,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +82893,3778,Female,Loyal Customer,22,Business travel,Business,599,3,1,1,1,3,3,3,3,2,1,3,4,4,3,4,7.0,neutral or dissatisfied +82894,50377,Female,disloyal Customer,43,Business travel,Eco,266,3,3,3,4,3,3,4,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +82895,67227,Female,Loyal Customer,9,Personal Travel,Eco,918,1,4,1,1,5,1,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +82896,58498,Female,Loyal Customer,53,Business travel,Eco,719,3,3,3,3,5,3,3,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +82897,10181,Male,disloyal Customer,22,Business travel,Business,316,4,0,3,4,2,3,2,2,5,5,4,5,5,2,0,0.0,satisfied +82898,36625,Male,Loyal Customer,45,Business travel,Business,691,2,4,4,4,2,4,3,2,2,2,2,2,2,4,0,5.0,neutral or dissatisfied +82899,63099,Female,disloyal Customer,12,Business travel,Eco,846,2,2,2,4,3,2,3,3,3,5,4,2,3,3,15,22.0,neutral or dissatisfied +82900,67212,Female,Loyal Customer,52,Personal Travel,Eco,1121,3,5,3,3,5,4,5,1,1,3,1,4,1,3,14,14.0,neutral or dissatisfied +82901,40928,Female,Loyal Customer,20,Business travel,Eco Plus,590,0,5,1,3,4,1,4,4,2,5,4,1,2,4,32,13.0,satisfied +82902,7263,Female,Loyal Customer,16,Personal Travel,Eco,135,3,0,0,4,2,0,2,2,4,5,2,4,5,2,0,0.0,neutral or dissatisfied +82903,77223,Female,disloyal Customer,27,Business travel,Business,1590,4,4,4,5,2,4,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +82904,117300,Female,Loyal Customer,49,Business travel,Business,3871,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +82905,53965,Male,Loyal Customer,66,Personal Travel,Eco,1325,2,3,2,3,2,2,2,1,4,2,4,2,1,2,210,196.0,neutral or dissatisfied +82906,120675,Male,Loyal Customer,53,Business travel,Business,280,5,5,5,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +82907,61239,Female,disloyal Customer,23,Business travel,Eco,567,3,1,3,4,2,3,2,2,3,4,4,1,3,2,0,0.0,neutral or dissatisfied +82908,126429,Male,disloyal Customer,30,Business travel,Eco Plus,507,1,2,2,4,1,2,1,1,3,2,2,3,4,1,0,0.0,neutral or dissatisfied +82909,55058,Female,Loyal Customer,49,Business travel,Business,1609,4,4,4,4,2,4,5,2,2,2,2,5,2,5,7,0.0,satisfied +82910,24842,Female,Loyal Customer,42,Personal Travel,Eco,991,3,4,3,1,3,2,2,3,2,5,5,2,4,2,160,146.0,neutral or dissatisfied +82911,88284,Female,Loyal Customer,41,Business travel,Business,515,5,5,5,5,3,5,4,3,3,3,3,4,3,4,11,25.0,satisfied +82912,48377,Male,Loyal Customer,59,Personal Travel,Eco,522,3,5,3,3,3,3,3,3,4,4,4,3,5,3,5,0.0,neutral or dissatisfied +82913,101368,Female,Loyal Customer,47,Personal Travel,Eco,1986,2,4,2,4,2,4,4,5,5,2,1,3,5,2,30,15.0,neutral or dissatisfied +82914,17991,Female,Loyal Customer,45,Business travel,Business,2704,1,1,4,1,1,1,2,4,4,4,4,1,4,1,0,3.0,satisfied +82915,14074,Female,Loyal Customer,46,Business travel,Business,1618,3,3,4,3,3,3,2,2,2,2,2,1,2,3,0,21.0,satisfied +82916,10547,Female,Loyal Customer,38,Business travel,Business,224,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,8.0,satisfied +82917,121427,Male,disloyal Customer,24,Business travel,Eco,290,3,0,3,4,3,3,5,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +82918,32861,Female,Loyal Customer,17,Personal Travel,Eco,216,2,0,2,1,1,2,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +82919,118030,Female,Loyal Customer,59,Business travel,Business,2567,1,1,1,1,4,5,4,4,4,4,4,4,4,5,5,0.0,satisfied +82920,28872,Female,disloyal Customer,28,Business travel,Eco,954,4,4,4,3,2,4,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +82921,64527,Male,Loyal Customer,48,Business travel,Business,551,3,3,2,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +82922,75097,Female,Loyal Customer,61,Business travel,Business,1744,1,1,5,1,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +82923,102645,Female,Loyal Customer,54,Business travel,Business,2734,3,3,3,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +82924,101598,Female,Loyal Customer,58,Business travel,Business,1371,1,1,1,1,2,5,5,4,4,4,4,4,4,4,11,0.0,satisfied +82925,95951,Male,Loyal Customer,55,Business travel,Business,2626,5,5,5,5,4,4,5,5,5,4,5,4,5,5,6,0.0,satisfied +82926,32433,Female,Loyal Customer,55,Business travel,Business,102,3,3,5,3,4,1,5,3,3,4,4,3,3,1,0,0.0,satisfied +82927,54453,Female,Loyal Customer,40,Business travel,Business,802,5,5,5,5,5,4,4,4,4,4,4,3,4,5,2,0.0,satisfied +82928,101505,Female,disloyal Customer,45,Business travel,Eco,345,1,2,1,3,4,1,4,4,4,4,3,2,3,4,85,91.0,neutral or dissatisfied +82929,48915,Male,Loyal Customer,43,Business travel,Eco,86,4,1,1,1,4,4,4,4,3,1,1,3,3,4,0,0.0,satisfied +82930,75708,Female,Loyal Customer,39,Business travel,Business,868,3,3,3,3,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +82931,117499,Female,Loyal Customer,39,Business travel,Business,107,5,5,5,5,5,5,2,5,5,5,5,4,5,5,6,14.0,satisfied +82932,74367,Female,Loyal Customer,42,Business travel,Business,1998,3,5,3,3,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +82933,72055,Male,disloyal Customer,21,Business travel,Eco,1149,3,3,3,3,2,3,2,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +82934,23688,Female,Loyal Customer,24,Business travel,Business,73,2,4,4,4,3,3,2,3,2,2,4,1,3,3,26,20.0,neutral or dissatisfied +82935,65276,Female,Loyal Customer,69,Personal Travel,Eco Plus,190,3,5,3,3,3,4,4,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +82936,45277,Male,Loyal Customer,34,Business travel,Eco,222,4,2,2,2,4,4,4,4,4,1,4,3,2,4,0,0.0,satisfied +82937,64373,Female,Loyal Customer,43,Personal Travel,Eco,1158,3,4,3,2,3,3,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +82938,126461,Male,Loyal Customer,44,Business travel,Business,1849,3,3,3,3,3,4,5,3,3,3,3,3,3,5,21,33.0,satisfied +82939,3733,Male,Loyal Customer,70,Personal Travel,Eco,427,4,3,4,4,3,4,3,3,1,5,2,2,4,3,45,45.0,neutral or dissatisfied +82940,16192,Female,Loyal Customer,68,Business travel,Eco,277,4,4,4,4,3,2,1,4,4,4,4,4,4,4,0,0.0,satisfied +82941,122207,Female,Loyal Customer,55,Business travel,Business,544,4,4,4,4,2,5,4,5,5,4,5,3,5,4,71,84.0,satisfied +82942,25434,Male,Loyal Customer,41,Business travel,Business,2027,5,5,5,5,5,1,4,3,3,5,3,2,3,2,68,53.0,satisfied +82943,48523,Male,Loyal Customer,10,Business travel,Business,845,5,5,5,5,2,2,2,2,3,3,3,5,1,2,0,0.0,satisfied +82944,64135,Male,Loyal Customer,43,Business travel,Business,3528,3,4,4,4,2,3,3,3,5,3,4,3,2,3,138,129.0,neutral or dissatisfied +82945,6469,Male,Loyal Customer,33,Personal Travel,Eco Plus,213,1,3,1,4,3,1,3,3,2,1,3,3,3,3,72,62.0,neutral or dissatisfied +82946,13212,Male,Loyal Customer,44,Business travel,Business,3162,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +82947,6374,Male,Loyal Customer,24,Business travel,Eco,213,2,3,3,3,2,1,2,4,5,4,3,2,3,2,125,169.0,neutral or dissatisfied +82948,102242,Female,disloyal Customer,20,Business travel,Business,414,4,0,5,5,3,5,3,3,3,3,5,4,5,3,0,0.0,satisfied +82949,49831,Male,Loyal Customer,39,Business travel,Business,326,5,5,5,5,3,3,1,3,3,4,3,2,3,1,9,16.0,satisfied +82950,106046,Female,Loyal Customer,56,Business travel,Business,452,2,4,4,4,5,4,4,2,2,2,2,2,2,1,21,21.0,neutral or dissatisfied +82951,123681,Female,Loyal Customer,44,Business travel,Eco,214,4,2,2,2,5,3,3,4,4,4,4,1,4,2,0,6.0,neutral or dissatisfied +82952,79760,Female,Loyal Customer,48,Business travel,Business,2976,4,4,4,4,2,4,4,5,5,5,5,5,5,5,3,9.0,satisfied +82953,95045,Male,Loyal Customer,22,Personal Travel,Eco,562,3,3,3,3,4,3,4,4,4,4,4,1,4,4,64,57.0,neutral or dissatisfied +82954,75262,Female,Loyal Customer,12,Personal Travel,Eco,1846,1,5,1,3,1,1,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +82955,28930,Female,disloyal Customer,37,Business travel,Eco,1050,2,2,2,3,2,2,2,2,1,2,1,2,2,2,6,3.0,neutral or dissatisfied +82956,732,Female,Loyal Customer,55,Business travel,Business,3446,1,2,5,2,1,3,3,2,2,2,1,4,2,1,0,0.0,neutral or dissatisfied +82957,76115,Male,Loyal Customer,53,Personal Travel,Business,689,2,4,2,3,5,3,3,5,5,2,3,3,5,3,0,0.0,neutral or dissatisfied +82958,24774,Male,disloyal Customer,24,Business travel,Eco,528,2,0,2,2,5,2,5,5,1,3,1,5,5,5,0,22.0,neutral or dissatisfied +82959,2788,Female,Loyal Customer,42,Business travel,Business,3167,1,1,1,1,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +82960,102996,Female,Loyal Customer,27,Business travel,Business,666,4,4,4,4,4,4,4,4,4,2,4,4,5,4,30,6.0,satisfied +82961,91125,Female,Loyal Customer,70,Personal Travel,Eco,270,3,0,3,1,5,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +82962,97072,Male,Loyal Customer,28,Business travel,Business,1390,4,4,4,4,5,5,5,5,3,2,5,3,4,5,1,0.0,satisfied +82963,102905,Male,Loyal Customer,59,Business travel,Business,3059,2,2,4,2,3,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +82964,81610,Male,Loyal Customer,46,Personal Travel,Eco,334,2,5,2,2,5,2,5,5,3,2,4,5,5,5,11,25.0,neutral or dissatisfied +82965,42824,Female,Loyal Customer,41,Business travel,Business,3899,0,0,0,1,3,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +82966,32957,Female,Loyal Customer,26,Personal Travel,Eco,102,2,4,2,2,1,2,1,1,3,4,4,3,1,1,0,0.0,neutral or dissatisfied +82967,88410,Female,disloyal Customer,38,Business travel,Business,404,4,4,4,1,2,4,2,2,5,3,5,3,4,2,3,0.0,neutral or dissatisfied +82968,114334,Male,Loyal Customer,37,Personal Travel,Eco,819,1,3,1,4,4,1,4,4,1,5,5,2,4,4,0,0.0,neutral or dissatisfied +82969,34141,Male,Loyal Customer,40,Business travel,Business,1189,5,5,5,5,3,3,3,4,4,4,4,1,4,3,0,0.0,satisfied +82970,111413,Female,Loyal Customer,39,Business travel,Business,1671,5,5,5,5,3,3,5,4,4,4,4,4,4,3,37,44.0,satisfied +82971,54495,Male,Loyal Customer,50,Business travel,Business,1996,3,5,5,5,1,3,3,3,3,3,3,3,3,2,8,4.0,neutral or dissatisfied +82972,89885,Female,Loyal Customer,51,Business travel,Eco,1310,3,1,5,5,1,4,3,3,3,3,3,4,3,2,40,27.0,neutral or dissatisfied +82973,7734,Female,Loyal Customer,56,Business travel,Business,3562,1,2,2,2,5,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +82974,75066,Male,Loyal Customer,39,Business travel,Business,2611,4,4,4,4,4,5,4,2,2,3,2,3,2,4,0,0.0,satisfied +82975,72445,Female,Loyal Customer,53,Business travel,Business,2119,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +82976,128681,Male,Loyal Customer,26,Personal Travel,Eco,2419,4,4,4,4,4,4,4,2,3,3,4,4,4,4,0,10.0,neutral or dissatisfied +82977,124206,Male,Loyal Customer,10,Business travel,Business,2176,2,2,2,2,2,2,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +82978,51171,Female,Loyal Customer,27,Personal Travel,Eco,209,0,5,0,5,4,0,4,4,5,5,4,2,2,4,0,0.0,satisfied +82979,106961,Female,Loyal Customer,22,Business travel,Business,937,1,4,3,4,1,1,1,1,4,4,4,1,4,1,0,3.0,neutral or dissatisfied +82980,129520,Female,Loyal Customer,46,Business travel,Business,2342,2,2,4,2,4,5,5,5,5,5,5,3,5,4,17,13.0,satisfied +82981,8036,Male,disloyal Customer,25,Business travel,Business,125,3,4,3,4,2,3,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +82982,102342,Female,Loyal Customer,58,Business travel,Eco,223,3,2,2,2,4,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +82983,44322,Male,Loyal Customer,13,Personal Travel,Eco,318,2,1,2,3,2,2,1,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +82984,78905,Male,Loyal Customer,52,Business travel,Business,2542,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +82985,91221,Male,Loyal Customer,65,Personal Travel,Eco,581,1,4,1,4,2,1,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +82986,17113,Female,Loyal Customer,41,Personal Travel,Eco,416,3,5,4,1,2,4,2,2,1,1,1,5,5,2,8,21.0,neutral or dissatisfied +82987,98649,Female,Loyal Customer,37,Business travel,Eco,551,2,2,4,4,2,2,2,2,4,5,4,4,4,2,50,39.0,neutral or dissatisfied +82988,15203,Male,Loyal Customer,47,Business travel,Business,3407,4,4,4,4,5,4,4,5,5,5,5,3,5,3,4,18.0,satisfied +82989,88388,Male,Loyal Customer,37,Business travel,Business,2590,3,2,5,5,3,3,3,3,3,3,3,2,3,2,27,24.0,neutral or dissatisfied +82990,19405,Male,Loyal Customer,13,Personal Travel,Business,660,2,5,2,3,1,2,1,1,1,5,2,3,2,1,0,9.0,neutral or dissatisfied +82991,68735,Female,Loyal Customer,57,Business travel,Business,585,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +82992,5624,Male,Loyal Customer,17,Personal Travel,Eco,624,2,3,2,1,1,2,1,1,2,4,1,2,1,1,31,30.0,neutral or dissatisfied +82993,98375,Female,Loyal Customer,49,Business travel,Business,3563,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +82994,119635,Male,Loyal Customer,25,Business travel,Business,1727,2,2,2,2,5,5,5,5,3,4,1,1,5,5,0,5.0,satisfied +82995,32624,Female,Loyal Customer,70,Business travel,Eco,101,2,1,1,1,2,2,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +82996,93427,Female,disloyal Customer,25,Business travel,Business,672,2,0,2,3,2,2,4,2,4,4,5,3,5,2,9,0.0,neutral or dissatisfied +82997,57839,Female,Loyal Customer,28,Business travel,Business,1491,2,2,3,2,3,3,3,3,3,3,4,4,4,3,8,0.0,satisfied +82998,74055,Female,Loyal Customer,36,Personal Travel,Business,2527,3,1,3,2,3,4,3,4,5,1,1,3,1,3,0,0.0,neutral or dissatisfied +82999,37761,Female,disloyal Customer,18,Business travel,Eco Plus,1005,3,3,2,1,1,2,3,1,1,3,3,3,2,1,8,0.0,neutral or dissatisfied +83000,73640,Female,Loyal Customer,47,Business travel,Business,2651,1,1,1,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +83001,30977,Male,Loyal Customer,47,Business travel,Eco,1476,4,4,4,4,4,4,4,4,4,3,1,1,4,4,0,2.0,satisfied +83002,44734,Female,Loyal Customer,62,Business travel,Eco Plus,268,4,3,2,2,1,5,3,4,4,4,4,5,4,4,0,0.0,satisfied +83003,116992,Female,Loyal Customer,22,Business travel,Eco,370,2,5,5,5,2,2,1,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +83004,31293,Male,Loyal Customer,26,Business travel,Eco Plus,533,3,2,2,2,3,3,1,3,3,3,4,3,4,3,1,6.0,neutral or dissatisfied +83005,108024,Male,Loyal Customer,29,Business travel,Eco Plus,589,3,5,5,5,3,3,3,3,3,5,3,2,4,3,20,12.0,neutral or dissatisfied +83006,975,Female,disloyal Customer,21,Business travel,Eco,309,1,2,1,4,2,1,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +83007,71339,Male,Loyal Customer,37,Personal Travel,Eco,1514,3,1,3,3,5,3,5,5,4,5,4,3,4,5,11,0.0,neutral or dissatisfied +83008,65144,Female,Loyal Customer,36,Personal Travel,Eco,551,2,3,2,5,2,2,4,2,1,3,1,2,2,2,9,0.0,neutral or dissatisfied +83009,75212,Male,Loyal Customer,58,Business travel,Eco,1846,1,4,1,1,1,1,1,1,3,2,1,1,2,1,0,0.0,neutral or dissatisfied +83010,93541,Female,disloyal Customer,28,Business travel,Eco Plus,1218,1,1,1,3,1,1,1,1,2,2,3,2,4,1,78,107.0,neutral or dissatisfied +83011,101299,Female,Loyal Customer,24,Personal Travel,Eco,763,2,2,2,4,1,2,1,1,3,2,3,4,3,1,10,1.0,neutral or dissatisfied +83012,99005,Male,Loyal Customer,11,Business travel,Eco Plus,569,2,3,3,3,2,2,1,2,3,3,4,2,3,2,20,9.0,neutral or dissatisfied +83013,30081,Male,Loyal Customer,53,Personal Travel,Eco,253,3,5,3,2,4,3,4,4,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +83014,91982,Male,Loyal Customer,70,Personal Travel,Eco Plus,2475,2,5,2,4,5,2,5,5,3,5,3,4,5,5,0,0.0,neutral or dissatisfied +83015,129828,Male,Loyal Customer,70,Personal Travel,Eco,337,2,5,2,3,2,2,2,2,1,2,5,2,2,2,0,0.0,neutral or dissatisfied +83016,19231,Female,Loyal Customer,42,Business travel,Business,3689,1,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +83017,129735,Female,Loyal Customer,60,Business travel,Eco,337,1,4,4,4,5,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +83018,78526,Female,Loyal Customer,53,Personal Travel,Eco,666,4,4,4,1,5,4,5,3,3,4,5,3,3,5,0,2.0,neutral or dissatisfied +83019,24849,Male,Loyal Customer,40,Personal Travel,Eco,861,3,4,3,4,2,3,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +83020,100185,Female,Loyal Customer,44,Personal Travel,Eco,523,2,2,2,4,1,4,3,5,5,2,2,2,5,2,93,92.0,neutral or dissatisfied +83021,116766,Female,Loyal Customer,7,Personal Travel,Eco Plus,358,2,4,2,2,3,2,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +83022,75236,Male,Loyal Customer,50,Personal Travel,Eco,1846,1,0,1,5,3,1,3,3,4,3,3,1,3,3,1,4.0,neutral or dissatisfied +83023,24352,Female,Loyal Customer,44,Personal Travel,Eco,634,4,5,4,2,3,4,5,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +83024,88753,Male,Loyal Customer,40,Personal Travel,Eco,406,3,5,3,3,3,3,4,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +83025,115515,Female,disloyal Customer,28,Business travel,Eco,371,2,2,2,4,5,2,5,5,1,5,3,2,3,5,0,0.0,neutral or dissatisfied +83026,16521,Male,Loyal Customer,37,Business travel,Business,209,4,2,2,2,4,4,4,3,3,3,4,2,3,1,0,11.0,neutral or dissatisfied +83027,20375,Male,Loyal Customer,38,Personal Travel,Eco,323,1,2,1,3,4,1,1,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +83028,94072,Male,disloyal Customer,43,Business travel,Business,189,3,2,2,3,4,3,4,4,1,5,3,2,4,4,53,53.0,neutral or dissatisfied +83029,56714,Male,Loyal Customer,18,Personal Travel,Eco,1023,2,4,1,3,4,1,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +83030,29663,Male,disloyal Customer,55,Personal Travel,Eco,1448,0,3,0,4,3,0,3,3,3,5,3,2,3,3,0,0.0,satisfied +83031,21333,Male,Loyal Customer,36,Business travel,Business,3684,4,4,4,4,2,2,3,5,5,5,5,5,5,3,2,0.0,satisfied +83032,74993,Female,Loyal Customer,42,Personal Travel,Eco Plus,2475,2,0,2,1,1,3,5,5,5,2,3,3,5,5,24,0.0,neutral or dissatisfied +83033,38524,Female,Loyal Customer,39,Business travel,Business,2475,4,4,4,4,4,3,4,4,4,4,4,2,4,2,17,0.0,satisfied +83034,68869,Female,disloyal Customer,26,Business travel,Business,1061,3,3,3,2,1,3,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +83035,28083,Male,Loyal Customer,23,Business travel,Eco,2172,5,2,2,2,5,5,4,5,2,3,5,1,1,5,0,0.0,satisfied +83036,120006,Male,Loyal Customer,53,Business travel,Business,1614,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +83037,88302,Female,Loyal Customer,46,Business travel,Business,366,2,2,2,2,3,5,4,5,5,5,5,3,5,5,78,74.0,satisfied +83038,121807,Male,disloyal Customer,23,Business travel,Business,366,0,3,0,4,2,0,1,2,5,2,5,4,5,2,0,0.0,satisfied +83039,103373,Male,Loyal Customer,38,Business travel,Eco Plus,342,2,5,5,5,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +83040,47504,Male,Loyal Customer,10,Personal Travel,Eco,584,2,5,2,4,3,2,3,3,3,2,4,5,4,3,26,10.0,neutral or dissatisfied +83041,89123,Male,Loyal Customer,49,Business travel,Business,2139,5,5,5,5,4,5,4,5,5,5,5,5,5,3,4,25.0,satisfied +83042,82693,Female,disloyal Customer,8,Business travel,Eco,632,4,2,4,5,2,4,2,2,3,3,4,5,5,2,0,0.0,satisfied +83043,92967,Male,Loyal Customer,26,Personal Travel,Eco,1694,1,5,1,4,2,1,2,2,1,5,5,1,3,2,11,4.0,neutral or dissatisfied +83044,12252,Male,Loyal Customer,28,Business travel,Business,201,4,4,4,4,4,4,3,4,4,3,2,5,4,4,2,0.0,satisfied +83045,113130,Female,Loyal Customer,65,Personal Travel,Eco Plus,569,2,4,2,2,5,5,5,5,5,2,5,4,5,5,10,0.0,neutral or dissatisfied +83046,73513,Male,Loyal Customer,14,Personal Travel,Eco Plus,1197,2,4,2,1,2,2,2,2,3,4,4,3,5,2,1,4.0,neutral or dissatisfied +83047,108238,Male,Loyal Customer,57,Business travel,Business,2449,1,1,1,1,4,4,5,4,4,4,4,4,4,4,5,5.0,satisfied +83048,113870,Female,Loyal Customer,37,Personal Travel,Eco,1334,2,5,2,3,4,2,1,4,5,2,4,5,5,4,2,3.0,neutral or dissatisfied +83049,55337,Female,Loyal Customer,49,Personal Travel,Eco,1325,1,4,1,2,2,5,4,1,1,1,1,3,1,5,3,9.0,neutral or dissatisfied +83050,122940,Male,Loyal Customer,55,Business travel,Business,507,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +83051,59807,Male,Loyal Customer,51,Business travel,Business,2638,2,2,2,2,3,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +83052,34970,Male,Loyal Customer,43,Business travel,Business,273,0,0,0,4,2,1,4,5,5,5,5,4,5,3,0,0.0,satisfied +83053,83470,Female,Loyal Customer,26,Business travel,Business,946,3,3,2,3,4,4,4,4,3,5,5,4,5,4,0,1.0,satisfied +83054,118359,Male,Loyal Customer,8,Personal Travel,Eco,602,4,5,4,3,1,4,1,1,5,4,4,5,5,1,42,32.0,neutral or dissatisfied +83055,84927,Male,Loyal Customer,49,Personal Travel,Eco,481,4,1,4,3,4,4,4,4,3,4,4,4,4,4,111,110.0,neutral or dissatisfied +83056,49336,Male,disloyal Customer,27,Business travel,Eco,86,5,0,5,4,2,0,2,2,1,4,3,3,4,2,0,3.0,satisfied +83057,75496,Female,disloyal Customer,11,Business travel,Business,2330,0,0,0,3,5,0,3,5,5,2,3,5,5,5,0,0.0,satisfied +83058,96635,Female,Loyal Customer,59,Business travel,Eco,937,3,5,5,5,1,3,4,4,4,3,4,1,4,1,44,30.0,neutral or dissatisfied +83059,118418,Male,Loyal Customer,31,Business travel,Business,2406,3,3,3,3,4,4,4,4,4,3,4,3,4,4,6,0.0,satisfied +83060,97533,Male,Loyal Customer,33,Personal Travel,Eco Plus,265,3,4,3,1,3,3,3,3,5,4,4,5,2,3,55,50.0,neutral or dissatisfied +83061,92169,Male,Loyal Customer,44,Business travel,Business,2079,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +83062,64545,Male,disloyal Customer,48,Business travel,Business,247,1,1,1,3,2,1,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +83063,27941,Female,Loyal Customer,29,Business travel,Business,1660,4,4,4,4,5,5,5,5,3,4,4,2,2,5,0,5.0,satisfied +83064,17325,Female,Loyal Customer,26,Personal Travel,Eco,403,4,4,5,3,4,5,5,4,5,4,4,5,5,4,1,0.0,neutral or dissatisfied +83065,99176,Male,Loyal Customer,59,Business travel,Business,351,2,2,2,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +83066,33056,Female,Loyal Customer,64,Personal Travel,Eco,84,4,4,0,2,4,4,5,2,2,0,2,3,2,5,0,0.0,satisfied +83067,100269,Male,disloyal Customer,29,Business travel,Business,1033,5,5,5,3,5,5,5,5,4,4,4,4,5,5,2,7.0,satisfied +83068,52,Female,disloyal Customer,20,Business travel,Eco,67,4,0,4,1,5,4,5,5,4,5,5,3,4,5,2,10.0,neutral or dissatisfied +83069,62328,Female,Loyal Customer,38,Personal Travel,Eco,236,2,4,2,4,2,2,2,2,3,3,5,5,5,2,95,86.0,neutral or dissatisfied +83070,39060,Male,disloyal Customer,24,Business travel,Eco,737,4,4,4,1,5,4,5,5,2,2,1,4,5,5,0,12.0,neutral or dissatisfied +83071,79322,Male,disloyal Customer,45,Business travel,Business,1020,2,2,2,1,4,2,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +83072,129729,Female,Loyal Customer,20,Business travel,Business,3295,3,3,4,3,3,3,3,1,4,3,3,3,1,3,160,173.0,neutral or dissatisfied +83073,31388,Male,Loyal Customer,39,Personal Travel,Eco,895,1,5,1,2,3,1,4,3,5,4,4,3,5,3,18,11.0,neutral or dissatisfied +83074,17373,Female,Loyal Customer,20,Business travel,Business,770,2,2,2,2,5,5,5,5,1,5,1,5,5,5,9,0.0,satisfied +83075,120830,Female,Loyal Customer,27,Business travel,Business,742,3,3,3,3,4,4,4,4,5,2,4,3,4,4,0,0.0,satisfied +83076,96759,Male,Loyal Customer,53,Business travel,Business,957,1,3,3,3,5,4,3,1,1,1,1,1,1,2,76,70.0,neutral or dissatisfied +83077,94610,Male,disloyal Customer,39,Business travel,Eco,239,1,2,1,4,4,1,4,4,2,4,3,1,3,4,4,0.0,neutral or dissatisfied +83078,33856,Female,Loyal Customer,45,Personal Travel,Eco,1609,1,4,1,1,5,4,4,5,5,1,2,4,5,4,0,0.0,neutral or dissatisfied +83079,1612,Male,Loyal Customer,39,Business travel,Business,968,2,2,5,2,5,4,5,4,4,4,4,3,4,4,0,5.0,satisfied +83080,92097,Male,Loyal Customer,45,Business travel,Business,3992,4,4,4,4,2,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +83081,3177,Male,Loyal Customer,36,Business travel,Business,2354,5,5,5,5,4,4,4,5,2,4,4,4,5,4,407,409.0,satisfied +83082,96513,Male,Loyal Customer,54,Personal Travel,Eco,436,0,4,0,4,4,0,4,4,3,5,4,5,5,4,20,19.0,satisfied +83083,27166,Female,Loyal Customer,46,Business travel,Business,2119,1,1,1,1,4,4,4,3,3,4,1,4,5,4,0,0.0,satisfied +83084,107060,Male,Loyal Customer,61,Personal Travel,Eco,480,3,2,3,4,1,3,1,1,1,1,4,2,4,1,31,21.0,neutral or dissatisfied +83085,20745,Male,Loyal Customer,22,Business travel,Business,3012,1,1,1,1,4,5,4,4,4,1,4,2,4,4,0,0.0,satisfied +83086,125862,Male,Loyal Customer,50,Business travel,Eco,993,3,1,1,1,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +83087,44083,Female,Loyal Customer,58,Personal Travel,Eco Plus,651,3,0,3,2,3,4,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +83088,75377,Female,Loyal Customer,40,Business travel,Business,2342,2,2,4,2,2,3,5,3,3,3,3,4,3,4,0,0.0,satisfied +83089,11900,Female,Loyal Customer,55,Business travel,Business,2271,4,4,5,4,4,5,5,4,4,4,4,4,4,3,7,0.0,satisfied +83090,59060,Male,Loyal Customer,60,Business travel,Business,1726,2,2,2,2,2,3,3,2,2,2,2,4,2,1,29,9.0,neutral or dissatisfied +83091,38022,Male,Loyal Customer,30,Business travel,Business,2396,4,4,4,4,4,4,4,4,4,1,5,4,4,4,0,0.0,satisfied +83092,21214,Female,Loyal Customer,48,Business travel,Eco,192,4,3,3,3,2,3,2,4,4,4,4,3,4,5,0,0.0,satisfied +83093,77731,Female,disloyal Customer,36,Business travel,Eco,813,3,3,3,4,3,3,3,3,1,4,3,4,3,3,0,6.0,neutral or dissatisfied +83094,79827,Male,Loyal Customer,18,Business travel,Business,2187,1,3,3,3,1,1,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +83095,120567,Male,Loyal Customer,13,Personal Travel,Eco,2176,4,4,5,5,4,5,2,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +83096,106136,Male,Loyal Customer,55,Business travel,Business,302,2,5,5,5,2,2,2,2,2,2,2,1,2,3,5,5.0,neutral or dissatisfied +83097,94721,Male,disloyal Customer,25,Business travel,Eco,293,3,2,3,3,5,3,5,5,4,2,4,2,4,5,15,7.0,neutral or dissatisfied +83098,4928,Male,Loyal Customer,61,Business travel,Business,1549,2,2,2,2,2,5,4,5,5,5,5,4,5,3,0,12.0,satisfied +83099,50370,Female,disloyal Customer,25,Business travel,Eco,109,1,0,1,4,4,1,4,4,4,3,1,3,2,4,0,0.0,neutral or dissatisfied +83100,3528,Female,disloyal Customer,7,Business travel,Business,557,1,5,1,1,4,1,4,4,4,2,4,5,4,4,0,1.0,neutral or dissatisfied +83101,109156,Male,Loyal Customer,36,Business travel,Business,793,2,2,2,2,3,5,4,4,4,4,4,5,4,3,8,11.0,satisfied +83102,66290,Male,Loyal Customer,22,Personal Travel,Business,852,4,4,4,2,5,4,5,5,4,2,5,4,4,5,1,0.0,neutral or dissatisfied +83103,118869,Male,Loyal Customer,43,Business travel,Eco Plus,369,2,3,3,3,2,2,2,2,4,2,4,4,4,2,0,1.0,neutral or dissatisfied +83104,101894,Male,Loyal Customer,27,Business travel,Business,2039,1,1,1,1,3,4,3,3,4,4,5,5,5,3,5,3.0,satisfied +83105,77730,Female,disloyal Customer,28,Business travel,Eco,1282,2,2,2,4,2,2,2,2,2,5,4,4,4,2,83,72.0,neutral or dissatisfied +83106,124096,Female,Loyal Customer,49,Business travel,Business,1924,5,5,5,5,4,5,5,3,3,3,3,5,3,5,0,22.0,satisfied +83107,71022,Female,Loyal Customer,41,Business travel,Eco,802,4,4,4,4,4,4,4,4,4,1,3,1,3,4,16,6.0,neutral or dissatisfied +83108,32534,Male,Loyal Customer,53,Business travel,Eco,216,5,1,5,5,5,5,5,5,5,1,2,4,3,5,0,0.0,satisfied +83109,104825,Female,disloyal Customer,35,Business travel,Business,426,2,2,2,5,5,2,2,5,5,2,4,4,5,5,4,0.0,neutral or dissatisfied +83110,10220,Male,Loyal Customer,51,Business travel,Business,2377,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +83111,39532,Male,Loyal Customer,55,Business travel,Business,3268,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +83112,54594,Male,Loyal Customer,72,Business travel,Business,1766,2,3,3,3,1,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +83113,103447,Female,Loyal Customer,24,Business travel,Eco,393,4,4,4,4,4,4,2,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +83114,82788,Female,Loyal Customer,40,Personal Travel,Eco,231,2,3,2,4,1,2,1,1,5,4,3,2,1,1,1,0.0,neutral or dissatisfied +83115,105101,Female,Loyal Customer,45,Business travel,Business,2654,3,3,5,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +83116,82823,Female,disloyal Customer,28,Business travel,Business,594,4,4,4,4,5,4,5,5,3,3,4,3,5,5,1,0.0,neutral or dissatisfied +83117,42651,Female,Loyal Customer,18,Business travel,Eco Plus,546,3,2,2,2,3,3,3,3,1,5,2,4,3,3,14,48.0,neutral or dissatisfied +83118,100217,Female,Loyal Customer,12,Personal Travel,Eco,762,3,5,3,3,2,3,2,2,4,4,5,3,4,2,0,17.0,neutral or dissatisfied +83119,43092,Male,Loyal Customer,70,Personal Travel,Eco,391,4,4,4,3,5,4,5,5,4,4,4,5,4,5,0,0.0,satisfied +83120,110198,Female,Loyal Customer,8,Business travel,Eco Plus,1056,3,5,5,5,3,3,2,3,1,4,3,2,3,3,31,46.0,neutral or dissatisfied +83121,7747,Female,disloyal Customer,25,Business travel,Business,1013,2,4,2,3,3,2,1,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +83122,115704,Female,Loyal Customer,57,Business travel,Business,1526,3,3,3,3,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +83123,69899,Female,disloyal Customer,24,Business travel,Business,831,0,4,0,3,3,0,3,3,5,3,3,3,4,3,0,0.0,satisfied +83124,117106,Male,Loyal Customer,39,Business travel,Business,1500,2,4,4,4,5,3,4,2,2,2,2,1,2,4,44,26.0,neutral or dissatisfied +83125,58543,Male,Loyal Customer,58,Business travel,Business,1514,1,1,1,1,2,4,5,4,4,5,4,5,4,5,1,0.0,satisfied +83126,124118,Male,disloyal Customer,23,Business travel,Eco,529,2,5,2,4,3,2,2,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +83127,52736,Female,Loyal Customer,49,Business travel,Eco,2306,4,4,5,4,5,5,5,4,4,4,4,5,4,5,3,0.0,satisfied +83128,50989,Male,Loyal Customer,17,Personal Travel,Eco,373,1,1,1,4,2,1,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +83129,51525,Male,Loyal Customer,37,Business travel,Eco,261,3,2,2,2,3,3,3,3,5,1,1,5,2,3,0,0.0,satisfied +83130,56033,Female,disloyal Customer,41,Business travel,Eco,811,2,2,2,4,2,5,3,4,5,3,3,3,3,3,1,6.0,neutral or dissatisfied +83131,2507,Female,disloyal Customer,50,Business travel,Business,181,4,4,4,5,4,4,2,4,4,4,4,5,4,4,0,0.0,satisfied +83132,83665,Female,Loyal Customer,51,Business travel,Business,1778,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +83133,42547,Female,Loyal Customer,46,Personal Travel,Eco,1174,4,4,4,4,2,4,5,5,5,4,5,5,5,3,12,0.0,satisfied +83134,55873,Male,Loyal Customer,44,Business travel,Business,3986,3,3,3,3,3,5,4,4,4,4,4,4,4,5,40,43.0,satisfied +83135,102894,Female,Loyal Customer,44,Business travel,Business,2504,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +83136,39137,Male,Loyal Customer,20,Personal Travel,Eco,190,3,4,3,1,5,3,4,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +83137,112442,Male,Loyal Customer,60,Business travel,Business,1579,4,4,4,4,2,4,5,4,4,4,4,3,4,5,1,0.0,satisfied +83138,58275,Male,Loyal Customer,38,Business travel,Business,594,2,2,2,2,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +83139,52699,Female,Loyal Customer,25,Personal Travel,Eco Plus,160,3,4,3,1,3,3,3,3,4,4,5,4,4,3,0,4.0,neutral or dissatisfied +83140,100486,Female,Loyal Customer,41,Business travel,Business,580,2,2,2,2,4,5,5,5,5,5,5,5,5,5,8,14.0,satisfied +83141,74332,Female,Loyal Customer,32,Business travel,Business,3334,5,5,5,5,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +83142,62894,Female,Loyal Customer,40,Business travel,Business,1711,2,2,2,2,4,4,4,3,3,3,3,5,3,3,22,19.0,satisfied +83143,32981,Male,Loyal Customer,52,Personal Travel,Eco,101,1,4,1,1,5,1,2,5,3,3,4,3,5,5,5,17.0,neutral or dissatisfied +83144,93039,Female,disloyal Customer,34,Business travel,Business,317,1,0,0,4,2,0,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +83145,7592,Female,Loyal Customer,45,Business travel,Business,594,1,1,1,1,3,5,4,4,4,4,4,3,4,4,34,17.0,satisfied +83146,123989,Male,disloyal Customer,49,Business travel,Business,184,4,4,4,1,5,4,5,5,4,4,4,4,4,5,0,0.0,satisfied +83147,83777,Male,Loyal Customer,42,Business travel,Business,1912,3,3,3,3,3,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +83148,125478,Male,Loyal Customer,42,Personal Travel,Eco,2979,2,5,2,3,3,2,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +83149,51513,Male,Loyal Customer,42,Business travel,Business,2971,2,5,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +83150,64393,Female,Loyal Customer,59,Personal Travel,Eco,1172,2,5,2,5,4,5,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +83151,61253,Female,Loyal Customer,69,Personal Travel,Eco,948,3,0,3,4,4,5,4,2,2,3,3,5,2,5,20,0.0,neutral or dissatisfied +83152,41679,Female,Loyal Customer,7,Personal Travel,Eco,936,3,2,3,3,3,3,5,3,4,5,3,4,3,3,18,22.0,neutral or dissatisfied +83153,8778,Female,Loyal Customer,22,Business travel,Business,552,3,3,3,3,3,3,3,3,4,1,3,2,4,3,5,14.0,neutral or dissatisfied +83154,101802,Male,disloyal Customer,20,Business travel,Eco,1521,3,3,3,2,2,3,2,2,3,4,5,3,4,2,3,0.0,neutral or dissatisfied +83155,126438,Female,Loyal Customer,55,Personal Travel,Eco Plus,547,2,3,2,2,3,3,2,4,4,2,2,3,4,4,0,0.0,neutral or dissatisfied +83156,10382,Female,Loyal Customer,54,Business travel,Business,667,2,2,1,2,4,3,3,5,4,4,4,3,4,3,142,151.0,satisfied +83157,38932,Female,Loyal Customer,70,Personal Travel,Eco,162,2,5,2,5,2,5,4,4,4,2,4,5,4,5,27,36.0,neutral or dissatisfied +83158,85697,Female,Loyal Customer,31,Business travel,Business,1547,2,4,4,4,2,2,2,2,3,5,3,4,4,2,0,6.0,neutral or dissatisfied +83159,92048,Male,Loyal Customer,50,Business travel,Business,1532,4,4,4,4,5,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +83160,107755,Female,Loyal Customer,32,Personal Travel,Eco,251,2,2,2,3,5,2,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +83161,41901,Female,Loyal Customer,50,Business travel,Business,129,0,3,0,1,4,2,4,2,2,2,2,4,2,5,0,0.0,satisfied +83162,127313,Female,Loyal Customer,38,Personal Travel,Eco,1979,3,5,3,3,3,3,3,3,3,2,5,5,3,3,4,0.0,neutral or dissatisfied +83163,29774,Male,Loyal Customer,48,Personal Travel,Business,548,3,3,2,4,3,3,3,1,1,2,4,1,1,3,0,1.0,neutral or dissatisfied +83164,106968,Female,Loyal Customer,46,Business travel,Business,2446,5,5,4,5,5,5,5,4,4,4,4,5,4,4,0,5.0,satisfied +83165,119327,Female,Loyal Customer,11,Personal Travel,Eco,214,4,0,4,2,1,4,1,1,4,5,1,4,3,1,0,0.0,neutral or dissatisfied +83166,9455,Female,Loyal Customer,38,Personal Travel,Eco,288,3,2,3,4,1,3,1,1,2,2,3,2,4,1,7,0.0,neutral or dissatisfied +83167,20067,Male,Loyal Customer,29,Personal Travel,Eco,738,1,4,1,3,1,1,1,1,3,3,5,4,4,1,74,79.0,neutral or dissatisfied +83168,11068,Male,Loyal Customer,47,Personal Travel,Eco,166,3,4,0,4,3,0,5,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +83169,5292,Male,Loyal Customer,42,Personal Travel,Eco,383,1,4,1,2,3,1,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +83170,60968,Female,Loyal Customer,50,Personal Travel,Eco,888,4,4,3,2,1,3,4,3,3,3,3,5,3,4,3,5.0,satisfied +83171,2920,Female,Loyal Customer,58,Personal Travel,Business,859,5,5,5,2,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +83172,62959,Male,disloyal Customer,21,Business travel,Business,862,4,5,4,1,2,4,2,2,5,3,4,5,5,2,13,3.0,satisfied +83173,29877,Male,Loyal Customer,31,Business travel,Eco,123,4,2,3,2,4,4,4,4,1,3,2,1,4,4,12,1.0,satisfied +83174,28059,Female,Loyal Customer,51,Business travel,Business,2562,1,1,1,1,4,4,4,4,3,5,2,4,4,4,21,33.0,satisfied +83175,62622,Male,Loyal Customer,66,Personal Travel,Eco,1744,1,5,1,3,3,1,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +83176,51766,Female,Loyal Customer,36,Personal Travel,Eco,261,5,5,5,3,3,5,3,3,3,4,3,1,2,3,0,0.0,satisfied +83177,77450,Female,Loyal Customer,60,Business travel,Business,2605,5,5,5,5,5,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +83178,50923,Male,Loyal Customer,17,Personal Travel,Eco,109,2,3,2,3,3,2,3,3,3,4,2,1,3,3,18,13.0,neutral or dissatisfied +83179,50421,Male,disloyal Customer,15,Business travel,Eco,337,1,4,1,4,5,1,3,5,2,4,3,4,3,5,109,100.0,neutral or dissatisfied +83180,91904,Female,Loyal Customer,58,Business travel,Business,2475,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +83181,3412,Male,Loyal Customer,40,Personal Travel,Eco,315,2,3,2,4,4,2,4,4,1,5,4,5,4,4,0,0.0,neutral or dissatisfied +83182,96522,Male,Loyal Customer,31,Personal Travel,Eco,302,3,4,3,2,1,3,1,1,4,4,5,4,4,1,10,13.0,neutral or dissatisfied +83183,67249,Male,Loyal Customer,12,Personal Travel,Eco,964,4,5,4,5,2,4,2,2,3,4,5,3,5,2,18,0.0,neutral or dissatisfied +83184,8005,Female,Loyal Customer,36,Personal Travel,Business,294,2,1,5,4,4,4,3,5,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +83185,105319,Male,disloyal Customer,27,Business travel,Business,528,5,5,5,3,1,5,2,1,3,3,5,5,5,1,12,20.0,satisfied +83186,72666,Male,Loyal Customer,15,Personal Travel,Eco,1121,2,5,2,3,3,2,3,3,3,5,3,5,5,3,0,0.0,neutral or dissatisfied +83187,108071,Female,Loyal Customer,34,Business travel,Business,1929,5,5,5,5,3,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +83188,49584,Female,Loyal Customer,71,Business travel,Business,109,2,5,5,5,2,3,4,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +83189,101151,Female,Loyal Customer,55,Business travel,Business,3098,1,1,1,1,4,4,5,2,2,2,2,3,2,4,64,56.0,satisfied +83190,28770,Male,Loyal Customer,32,Business travel,Business,2458,3,3,3,3,4,4,4,4,4,5,4,3,5,4,3,20.0,satisfied +83191,3044,Male,Loyal Customer,23,Business travel,Business,489,4,4,4,4,4,4,4,4,4,5,3,2,3,4,0,0.0,satisfied +83192,14069,Male,disloyal Customer,35,Business travel,Business,201,1,1,1,5,3,1,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +83193,81321,Female,Loyal Customer,23,Business travel,Business,3034,4,4,3,4,4,4,4,4,3,3,4,4,5,4,3,13.0,satisfied +83194,128309,Female,Loyal Customer,56,Business travel,Business,646,4,4,4,4,2,5,5,5,5,5,5,5,5,4,16,4.0,satisfied +83195,34531,Female,Loyal Customer,24,Business travel,Eco,636,3,4,4,4,5,5,3,5,3,1,4,5,3,5,0,14.0,satisfied +83196,41816,Male,Loyal Customer,59,Personal Travel,Eco,489,4,5,4,3,4,4,4,4,5,5,5,5,5,4,0,1.0,neutral or dissatisfied +83197,118042,Female,disloyal Customer,45,Business travel,Eco,1262,1,1,1,4,4,1,4,4,3,5,4,1,3,4,28,7.0,neutral or dissatisfied +83198,56754,Female,disloyal Customer,22,Business travel,Eco,937,5,5,5,2,1,5,1,1,3,5,5,4,5,1,15,40.0,satisfied +83199,81138,Female,Loyal Customer,49,Business travel,Business,991,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +83200,124123,Male,Loyal Customer,53,Business travel,Eco,529,3,2,2,2,3,3,3,3,4,4,3,2,3,3,0,0.0,neutral or dissatisfied +83201,38479,Male,Loyal Customer,45,Personal Travel,Eco,846,1,4,1,1,5,1,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +83202,76198,Male,Loyal Customer,46,Business travel,Business,2422,2,4,2,4,5,3,3,2,2,2,2,1,2,2,29,40.0,neutral or dissatisfied +83203,11306,Male,Loyal Customer,51,Personal Travel,Eco,667,2,5,2,3,1,2,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +83204,84534,Female,disloyal Customer,30,Business travel,Eco,1239,3,3,3,2,2,3,2,2,1,4,1,2,1,2,0,21.0,neutral or dissatisfied +83205,109110,Male,Loyal Customer,51,Business travel,Business,2342,3,3,3,3,5,4,4,4,4,5,4,3,4,4,20,2.0,satisfied +83206,78170,Female,Loyal Customer,66,Business travel,Business,2660,3,3,3,3,3,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +83207,93753,Male,Loyal Customer,33,Business travel,Business,368,1,3,3,3,1,1,1,1,4,5,3,2,3,1,94,87.0,neutral or dissatisfied +83208,88852,Female,Loyal Customer,65,Personal Travel,Eco Plus,270,2,4,2,4,2,5,5,4,5,5,4,5,3,5,148,134.0,neutral or dissatisfied +83209,84471,Female,Loyal Customer,35,Business travel,Business,1718,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +83210,93903,Male,Loyal Customer,67,Personal Travel,Eco,588,1,5,1,4,1,1,1,1,3,3,5,4,4,1,11,0.0,neutral or dissatisfied +83211,70701,Female,Loyal Customer,35,Personal Travel,Eco,837,2,3,3,3,4,3,4,4,4,5,4,5,4,4,0,21.0,neutral or dissatisfied +83212,61575,Female,Loyal Customer,49,Business travel,Business,1635,3,4,2,2,1,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +83213,17886,Male,Loyal Customer,12,Personal Travel,Eco,453,2,4,2,3,4,2,3,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +83214,76019,Female,Loyal Customer,50,Business travel,Eco,237,2,5,5,5,5,3,4,2,2,2,2,4,2,4,0,5.0,neutral or dissatisfied +83215,90597,Female,Loyal Customer,30,Business travel,Business,581,1,1,2,1,5,5,5,5,5,2,4,3,4,5,9,2.0,satisfied +83216,80638,Male,Loyal Customer,57,Business travel,Eco,282,1,1,1,1,1,1,1,1,4,4,3,4,3,1,0,0.0,neutral or dissatisfied +83217,45419,Female,disloyal Customer,22,Business travel,Eco,649,3,0,3,2,5,3,1,5,5,3,2,2,3,5,17,16.0,neutral or dissatisfied +83218,1224,Female,Loyal Customer,51,Personal Travel,Eco,89,3,5,0,2,2,5,5,2,2,0,2,3,2,4,0,0.0,neutral or dissatisfied +83219,105775,Male,Loyal Customer,38,Business travel,Eco,263,2,3,3,3,2,2,2,2,5,1,3,5,2,2,15,22.0,satisfied +83220,88153,Female,Loyal Customer,49,Business travel,Business,2446,2,2,2,2,3,5,4,4,4,4,4,5,4,3,26,36.0,satisfied +83221,9744,Female,disloyal Customer,37,Business travel,Eco,570,4,1,4,3,5,4,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +83222,64576,Male,Loyal Customer,58,Business travel,Business,190,5,5,4,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +83223,114823,Female,Loyal Customer,46,Business travel,Business,1510,4,4,4,4,4,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +83224,41571,Female,Loyal Customer,62,Personal Travel,Eco,1428,1,5,1,1,5,5,2,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +83225,5067,Male,Loyal Customer,52,Business travel,Business,2474,4,5,4,4,4,5,5,5,5,5,5,4,5,4,101,68.0,satisfied +83226,73586,Female,Loyal Customer,47,Business travel,Business,2440,5,5,5,5,4,4,4,4,4,4,5,4,4,3,16,20.0,satisfied +83227,15223,Female,Loyal Customer,49,Business travel,Eco,416,5,5,5,5,2,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +83228,56568,Male,Loyal Customer,53,Business travel,Business,3257,4,4,3,4,2,5,4,4,4,4,4,4,4,4,9,0.0,satisfied +83229,118773,Male,Loyal Customer,36,Personal Travel,Eco,646,2,5,3,4,3,3,3,3,1,2,5,3,3,3,61,65.0,neutral or dissatisfied +83230,119658,Male,disloyal Customer,27,Business travel,Eco,507,3,3,3,4,1,3,1,1,4,4,3,4,3,1,0,0.0,neutral or dissatisfied +83231,68974,Female,Loyal Customer,49,Personal Travel,Eco,700,4,2,4,3,1,2,3,2,2,4,2,2,2,1,0,0.0,neutral or dissatisfied +83232,14672,Female,Loyal Customer,21,Business travel,Eco,430,2,3,3,3,2,2,4,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +83233,10805,Female,disloyal Customer,50,Business travel,Eco,74,3,1,3,2,1,3,1,1,3,5,2,1,3,1,4,22.0,neutral or dissatisfied +83234,44975,Male,Loyal Customer,57,Business travel,Eco,222,5,1,1,1,5,5,5,5,4,5,4,1,5,5,4,0.0,satisfied +83235,123973,Female,Loyal Customer,43,Business travel,Business,184,5,5,5,5,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +83236,75641,Female,Loyal Customer,42,Business travel,Business,1750,2,2,2,2,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +83237,120774,Female,Loyal Customer,22,Business travel,Eco,678,1,1,5,5,1,1,1,1,4,4,4,1,3,1,0,0.0,neutral or dissatisfied +83238,52371,Female,Loyal Customer,70,Personal Travel,Eco,451,3,1,3,3,5,4,3,3,3,3,4,3,3,4,0,10.0,neutral or dissatisfied +83239,120086,Female,Loyal Customer,52,Personal Travel,Eco,683,2,5,2,3,4,4,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +83240,105221,Female,Loyal Customer,45,Business travel,Business,3560,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +83241,77294,Male,Loyal Customer,33,Business travel,Business,391,5,5,5,5,4,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +83242,14739,Male,Loyal Customer,26,Business travel,Business,463,4,4,4,4,4,4,4,4,2,5,3,2,4,4,0,0.0,satisfied +83243,108459,Male,Loyal Customer,13,Personal Travel,Eco,1444,2,0,2,1,2,1,1,4,5,5,5,1,5,1,188,198.0,neutral or dissatisfied +83244,104144,Male,Loyal Customer,59,Business travel,Business,2000,4,4,4,4,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +83245,52503,Female,Loyal Customer,58,Business travel,Business,2182,1,5,4,4,5,4,4,3,3,3,1,2,3,1,25,22.0,neutral or dissatisfied +83246,85762,Female,Loyal Customer,56,Business travel,Business,3534,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,2.0,satisfied +83247,40495,Male,Loyal Customer,52,Personal Travel,Eco,188,5,4,5,5,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +83248,9005,Female,Loyal Customer,15,Business travel,Eco,287,4,5,5,5,4,4,2,4,2,5,3,2,4,4,0,0.0,neutral or dissatisfied +83249,116684,Male,Loyal Customer,57,Business travel,Business,308,0,0,0,2,3,4,4,5,5,5,5,3,5,5,25,5.0,satisfied +83250,26025,Male,disloyal Customer,44,Business travel,Eco,321,1,3,1,4,5,1,2,5,5,3,3,1,1,5,5,0.0,neutral or dissatisfied +83251,61120,Female,disloyal Customer,46,Business travel,Business,967,1,1,1,4,3,1,5,3,5,5,5,3,4,3,1,0.0,neutral or dissatisfied +83252,100424,Female,Loyal Customer,47,Business travel,Business,1130,5,5,5,5,3,4,4,5,5,5,5,3,5,3,1,0.0,satisfied +83253,129783,Male,Loyal Customer,55,Personal Travel,Eco,308,1,5,1,4,2,1,2,2,4,4,5,3,1,2,75,66.0,neutral or dissatisfied +83254,119064,Male,Loyal Customer,40,Business travel,Business,2043,4,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +83255,3786,Female,disloyal Customer,36,Business travel,Eco,599,1,4,1,4,2,1,2,2,1,5,4,4,3,2,0,35.0,neutral or dissatisfied +83256,73014,Male,Loyal Customer,67,Personal Travel,Eco,1096,1,0,1,3,4,1,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +83257,62060,Female,Loyal Customer,26,Personal Travel,Eco,2586,2,1,2,2,1,2,1,1,1,2,1,3,2,1,6,0.0,neutral or dissatisfied +83258,101226,Male,Loyal Customer,60,Business travel,Business,2648,2,2,2,2,5,5,5,4,4,4,4,4,4,4,35,31.0,satisfied +83259,65916,Male,Loyal Customer,34,Business travel,Business,2649,3,3,5,3,5,5,5,3,3,3,3,3,3,3,49,63.0,satisfied +83260,9855,Female,disloyal Customer,39,Business travel,Eco,242,3,0,3,2,3,3,3,3,2,3,1,4,3,3,0,0.0,neutral or dissatisfied +83261,39277,Female,Loyal Customer,40,Business travel,Business,3367,1,3,3,3,3,2,3,2,2,2,1,1,2,3,0,12.0,neutral or dissatisfied +83262,14359,Male,Loyal Customer,40,Personal Travel,Eco Plus,395,3,5,3,4,4,3,4,4,3,5,4,3,4,4,42,39.0,neutral or dissatisfied +83263,123921,Female,Loyal Customer,12,Personal Travel,Eco,573,3,1,3,2,3,3,3,3,4,3,2,1,3,3,0,8.0,neutral or dissatisfied +83264,125068,Male,Loyal Customer,39,Business travel,Business,1853,5,5,5,5,2,4,5,4,4,4,4,5,4,4,0,22.0,satisfied +83265,107888,Female,Loyal Customer,22,Business travel,Business,2429,2,2,2,2,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +83266,16393,Female,disloyal Customer,20,Business travel,Eco,404,3,2,3,3,3,3,3,3,1,1,3,1,3,3,57,42.0,neutral or dissatisfied +83267,41087,Male,Loyal Customer,32,Business travel,Business,3411,3,3,3,3,5,5,5,5,3,1,2,1,3,5,0,0.0,satisfied +83268,4934,Male,Loyal Customer,47,Business travel,Business,2399,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +83269,31767,Male,Loyal Customer,44,Business travel,Business,602,4,2,2,2,2,3,3,4,4,4,4,1,4,1,0,11.0,neutral or dissatisfied +83270,111054,Male,Loyal Customer,37,Business travel,Business,1807,4,3,3,3,1,4,3,3,3,3,4,2,3,1,2,1.0,neutral or dissatisfied +83271,115274,Female,Loyal Customer,59,Business travel,Eco,372,2,2,2,2,2,2,2,3,4,3,4,2,2,2,155,148.0,neutral or dissatisfied +83272,122364,Male,Loyal Customer,25,Business travel,Business,1711,2,4,4,4,2,2,2,2,2,3,3,4,2,2,0,0.0,neutral or dissatisfied +83273,69926,Male,Loyal Customer,33,Business travel,Business,1671,1,1,2,1,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +83274,52169,Male,Loyal Customer,37,Business travel,Business,370,5,5,5,5,3,1,5,3,3,4,3,1,3,5,0,0.0,satisfied +83275,30952,Female,Loyal Customer,24,Business travel,Eco,836,3,3,2,3,3,3,1,3,2,1,2,3,2,3,0,5.0,neutral or dissatisfied +83276,80069,Male,Loyal Customer,39,Business travel,Business,1089,2,2,5,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +83277,97972,Male,Loyal Customer,60,Personal Travel,Eco,612,3,2,4,3,5,4,5,5,3,1,4,3,3,5,6,2.0,neutral or dissatisfied +83278,20268,Female,disloyal Customer,55,Business travel,Eco,228,2,4,2,2,1,2,1,1,5,4,2,1,1,1,12,0.0,neutral or dissatisfied +83279,114097,Female,Loyal Customer,23,Personal Travel,Eco,1947,4,5,5,3,2,5,2,2,3,3,3,5,5,2,36,19.0,neutral or dissatisfied +83280,66351,Male,Loyal Customer,39,Business travel,Business,3349,4,4,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +83281,19358,Female,Loyal Customer,32,Business travel,Business,692,3,4,2,4,3,3,3,3,1,4,2,1,2,3,1,0.0,neutral or dissatisfied +83282,69824,Male,Loyal Customer,60,Business travel,Business,3266,3,3,3,3,3,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +83283,128895,Female,Loyal Customer,50,Business travel,Eco,2565,4,5,3,3,4,4,4,1,3,2,4,4,5,4,0,0.0,satisfied +83284,23420,Female,Loyal Customer,63,Personal Travel,Eco,495,4,2,4,2,5,2,3,1,1,4,4,2,1,3,34,28.0,neutral or dissatisfied +83285,51765,Male,Loyal Customer,29,Personal Travel,Eco,455,3,1,5,3,2,5,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +83286,120347,Female,Loyal Customer,27,Personal Travel,Business,337,3,5,2,5,3,2,3,3,2,5,4,4,3,3,0,0.0,neutral or dissatisfied +83287,111858,Male,Loyal Customer,53,Business travel,Business,1820,1,1,1,1,2,4,4,4,4,4,4,3,4,3,1,15.0,satisfied +83288,7803,Male,Loyal Customer,29,Business travel,Business,1606,3,3,5,3,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +83289,73,Male,Loyal Customer,70,Business travel,Eco,173,5,5,5,5,5,5,5,5,3,2,1,3,4,5,0,0.0,satisfied +83290,71809,Male,Loyal Customer,46,Business travel,Business,1744,4,4,4,4,2,5,5,4,4,4,4,3,4,5,29,25.0,satisfied +83291,67769,Male,disloyal Customer,27,Business travel,Eco,1235,4,4,4,2,5,4,5,5,1,3,3,3,3,5,13,6.0,neutral or dissatisfied +83292,82478,Male,Loyal Customer,70,Personal Travel,Eco,502,3,4,3,4,4,3,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +83293,76861,Female,Loyal Customer,48,Business travel,Business,3889,1,1,4,1,2,5,5,4,4,4,4,4,4,3,4,10.0,satisfied +83294,18438,Male,Loyal Customer,45,Business travel,Business,383,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +83295,51795,Female,Loyal Customer,53,Personal Travel,Eco,370,1,5,1,4,2,4,4,3,3,1,3,3,3,5,0,1.0,neutral or dissatisfied +83296,36812,Female,Loyal Customer,14,Business travel,Business,2300,4,5,5,5,4,4,4,3,3,3,3,4,4,4,0,12.0,neutral or dissatisfied +83297,112322,Male,disloyal Customer,11,Business travel,Business,853,1,2,1,4,3,1,1,3,3,1,3,3,3,3,27,27.0,neutral or dissatisfied +83298,80827,Female,Loyal Customer,23,Business travel,Business,2712,1,1,1,1,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +83299,32669,Male,Loyal Customer,41,Business travel,Business,2005,2,1,1,1,4,2,2,1,1,1,2,2,1,1,0,0.0,neutral or dissatisfied +83300,41197,Female,Loyal Customer,31,Business travel,Business,1091,2,2,2,2,2,2,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +83301,91978,Female,disloyal Customer,18,Business travel,Eco Plus,1225,5,0,5,5,2,5,2,2,1,1,2,2,5,2,0,5.0,satisfied +83302,545,Male,Loyal Customer,39,Business travel,Business,3498,0,5,0,4,3,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +83303,129380,Female,Loyal Customer,60,Business travel,Eco,2565,2,5,5,5,1,2,2,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +83304,5727,Female,Loyal Customer,36,Business travel,Eco Plus,299,1,3,3,3,1,1,1,1,3,1,3,1,3,1,0,13.0,neutral or dissatisfied +83305,124906,Male,disloyal Customer,26,Business travel,Business,728,4,4,4,1,3,4,3,3,3,4,4,3,4,3,15,12.0,neutral or dissatisfied +83306,93508,Female,Loyal Customer,30,Personal Travel,Eco,1107,3,2,3,3,4,3,4,4,3,4,2,3,2,4,5,0.0,neutral or dissatisfied +83307,60604,Male,Loyal Customer,50,Business travel,Business,991,5,5,5,5,3,5,4,4,4,4,4,4,4,4,1,20.0,satisfied +83308,49572,Male,Loyal Customer,48,Business travel,Eco,308,4,2,4,2,3,4,3,3,3,5,5,3,1,3,0,0.0,satisfied +83309,59179,Female,Loyal Customer,62,Business travel,Eco Plus,1846,3,5,4,5,3,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +83310,70683,Female,Loyal Customer,70,Personal Travel,Eco,447,2,4,2,4,3,4,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +83311,125317,Male,disloyal Customer,22,Business travel,Eco,599,2,0,3,4,4,3,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +83312,124550,Male,Loyal Customer,45,Personal Travel,Eco,1276,2,5,2,4,3,2,3,3,3,2,5,4,4,3,0,3.0,neutral or dissatisfied +83313,74634,Female,Loyal Customer,69,Business travel,Eco,842,2,3,3,3,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +83314,47980,Female,Loyal Customer,23,Personal Travel,Eco,451,4,3,4,3,4,4,4,4,4,2,3,4,3,4,0,0.0,satisfied +83315,81071,Male,Loyal Customer,47,Business travel,Business,931,2,4,5,4,2,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +83316,35565,Female,Loyal Customer,40,Business travel,Eco Plus,1005,5,1,1,1,5,5,5,5,1,5,2,2,3,5,0,0.0,satisfied +83317,83037,Male,disloyal Customer,24,Business travel,Eco,983,4,4,4,4,1,4,3,1,2,3,3,3,4,1,0,12.0,neutral or dissatisfied +83318,756,Female,Loyal Customer,44,Business travel,Business,3189,1,1,1,1,4,5,5,5,5,5,5,4,5,5,5,3.0,satisfied +83319,14039,Male,Loyal Customer,52,Personal Travel,Eco,1117,4,5,4,3,1,4,1,1,5,4,4,3,4,1,9,21.0,neutral or dissatisfied +83320,38396,Male,Loyal Customer,30,Business travel,Business,1754,1,1,2,1,5,5,5,5,1,4,3,5,4,5,231,240.0,satisfied +83321,75643,Female,Loyal Customer,37,Business travel,Business,304,0,0,0,5,2,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +83322,44228,Male,Loyal Customer,65,Business travel,Business,222,1,2,3,3,3,3,2,3,3,3,1,1,3,2,0,11.0,neutral or dissatisfied +83323,123109,Male,Loyal Customer,19,Business travel,Business,2537,2,5,2,2,2,2,2,2,2,5,3,4,3,2,46,45.0,neutral or dissatisfied +83324,54740,Female,Loyal Customer,64,Personal Travel,Eco,861,1,5,1,3,2,5,5,1,1,1,1,3,1,5,35,22.0,neutral or dissatisfied +83325,68391,Male,Loyal Customer,55,Business travel,Business,1045,1,1,1,1,2,4,5,4,4,4,4,4,4,5,9,1.0,satisfied +83326,108286,Male,Loyal Customer,58,Business travel,Business,1750,3,3,3,3,5,3,5,4,4,4,4,4,4,5,0,14.0,satisfied +83327,97603,Female,disloyal Customer,39,Business travel,Business,442,1,1,1,1,2,1,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +83328,32712,Female,Loyal Customer,46,Business travel,Business,1710,3,1,3,1,5,3,4,4,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +83329,50283,Male,Loyal Customer,39,Business travel,Eco,158,1,4,4,4,1,1,1,1,1,5,3,2,3,1,0,0.0,neutral or dissatisfied +83330,13413,Male,Loyal Customer,52,Business travel,Eco,409,2,2,2,2,2,2,2,2,4,2,4,2,5,2,0,0.0,satisfied +83331,114393,Female,Loyal Customer,44,Business travel,Business,3534,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +83332,70803,Female,Loyal Customer,31,Personal Travel,Eco Plus,328,3,0,3,3,3,3,5,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +83333,64073,Female,Loyal Customer,49,Business travel,Eco,519,2,1,1,1,1,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +83334,63554,Female,disloyal Customer,45,Business travel,Business,1009,4,4,4,3,5,4,5,5,3,4,5,5,5,5,0,0.0,satisfied +83335,88458,Female,Loyal Customer,41,Business travel,Business,181,0,5,0,1,1,4,5,1,1,1,1,4,1,5,1,2.0,satisfied +83336,127727,Female,Loyal Customer,58,Business travel,Business,3730,2,2,2,2,4,4,4,4,4,4,4,5,4,4,9,4.0,satisfied +83337,117008,Male,disloyal Customer,45,Business travel,Business,304,2,1,1,4,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +83338,91391,Male,Loyal Customer,40,Business travel,Business,2218,2,4,3,4,1,4,4,2,2,2,2,3,2,1,20,20.0,neutral or dissatisfied +83339,88821,Female,Loyal Customer,33,Business travel,Eco Plus,581,1,1,1,1,1,1,1,1,4,4,4,4,3,1,0,0.0,neutral or dissatisfied +83340,74737,Male,Loyal Customer,39,Personal Travel,Eco,1205,1,3,1,3,3,1,3,3,3,1,4,3,3,3,90,70.0,neutral or dissatisfied +83341,3366,Male,Loyal Customer,35,Business travel,Business,315,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +83342,22228,Female,Loyal Customer,27,Business travel,Eco Plus,591,3,1,5,1,3,3,3,3,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +83343,64082,Male,Loyal Customer,58,Personal Travel,Eco,919,1,4,1,1,3,1,3,3,3,3,4,3,5,3,0,0.0,neutral or dissatisfied +83344,48879,Male,Loyal Customer,47,Business travel,Business,156,2,2,2,2,1,5,1,4,4,4,3,1,4,1,0,0.0,satisfied +83345,53872,Male,Loyal Customer,17,Business travel,Business,3401,4,4,4,4,4,4,4,4,4,4,3,1,3,4,15,9.0,neutral or dissatisfied +83346,92997,Male,Loyal Customer,31,Business travel,Eco Plus,738,3,2,2,2,3,3,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +83347,70834,Female,Loyal Customer,39,Business travel,Business,761,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +83348,121632,Female,disloyal Customer,39,Business travel,Business,936,2,2,2,1,5,2,4,5,4,3,4,3,5,5,0,1.0,neutral or dissatisfied +83349,106529,Male,Loyal Customer,8,Personal Travel,Eco,271,3,3,3,2,5,3,5,5,1,5,1,2,1,5,10,5.0,neutral or dissatisfied +83350,32877,Female,Loyal Customer,23,Personal Travel,Eco,102,2,4,2,1,3,2,3,3,4,4,4,4,5,3,0,2.0,neutral or dissatisfied +83351,100002,Male,Loyal Customer,22,Business travel,Business,3871,4,1,1,1,4,4,4,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +83352,3060,Male,Loyal Customer,57,Personal Travel,Eco,340,4,5,4,2,3,4,2,3,5,3,4,4,4,3,0,1.0,neutral or dissatisfied +83353,68723,Female,disloyal Customer,22,Business travel,Business,237,0,5,0,2,3,0,1,3,5,3,4,3,5,3,0,0.0,satisfied +83354,103103,Male,Loyal Customer,27,Personal Travel,Eco,460,3,3,3,3,4,3,4,4,2,1,3,3,3,4,0,19.0,neutral or dissatisfied +83355,43203,Male,Loyal Customer,37,Business travel,Business,3668,1,3,3,3,1,3,3,1,1,1,1,4,1,3,11,19.0,neutral or dissatisfied +83356,115493,Female,Loyal Customer,38,Business travel,Business,3946,1,1,1,1,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +83357,6073,Male,Loyal Customer,60,Personal Travel,Eco,925,2,5,2,3,2,2,2,2,4,2,2,3,3,2,0,11.0,neutral or dissatisfied +83358,102899,Male,Loyal Customer,65,Personal Travel,Eco,1037,3,3,3,4,4,3,1,4,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +83359,14556,Male,Loyal Customer,52,Personal Travel,Eco,310,2,5,4,2,2,4,2,2,5,5,5,3,4,2,0,0.0,neutral or dissatisfied +83360,104187,Female,Loyal Customer,45,Personal Travel,Eco,349,1,3,1,3,1,3,3,2,2,1,2,2,2,1,0,17.0,neutral or dissatisfied +83361,109321,Female,Loyal Customer,64,Personal Travel,Eco,1136,1,4,1,1,3,5,4,5,5,1,5,5,5,4,28,14.0,neutral or dissatisfied +83362,129854,Female,Loyal Customer,69,Personal Travel,Eco,337,3,5,3,5,1,5,2,4,4,3,4,3,4,4,41,48.0,neutral or dissatisfied +83363,53681,Male,disloyal Customer,49,Business travel,Eco,1208,3,3,3,3,3,3,3,3,1,5,3,3,5,3,0,0.0,neutral or dissatisfied +83364,12869,Male,Loyal Customer,56,Business travel,Business,456,5,5,4,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +83365,33423,Male,Loyal Customer,38,Business travel,Business,2556,1,1,1,1,4,4,4,4,1,4,3,4,2,4,0,16.0,satisfied +83366,83831,Female,Loyal Customer,43,Business travel,Business,425,1,4,4,4,1,3,3,1,1,1,1,2,1,3,6,9.0,neutral or dissatisfied +83367,95846,Female,Loyal Customer,36,Business travel,Business,2573,2,2,2,2,5,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +83368,40914,Male,Loyal Customer,45,Personal Travel,Eco,574,3,5,2,4,2,2,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +83369,61787,Female,Loyal Customer,53,Personal Travel,Eco,1379,3,1,3,4,2,3,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +83370,82129,Female,Loyal Customer,66,Personal Travel,Eco,2519,2,3,2,2,2,5,1,1,4,3,2,1,2,1,4,2.0,neutral or dissatisfied +83371,53630,Male,Loyal Customer,46,Personal Travel,Eco,1874,4,4,4,4,2,4,2,2,2,4,3,1,4,2,3,0.0,neutral or dissatisfied +83372,77462,Female,Loyal Customer,21,Business travel,Business,1688,3,3,3,3,3,3,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +83373,75908,Male,Loyal Customer,46,Personal Travel,Eco,603,4,3,4,3,1,4,1,1,1,1,3,2,2,1,0,19.0,neutral or dissatisfied +83374,87339,Male,Loyal Customer,33,Business travel,Business,425,5,5,5,5,2,3,2,2,4,4,5,3,5,2,0,0.0,satisfied +83375,61368,Female,Loyal Customer,17,Personal Travel,Business,679,2,5,2,4,3,2,3,3,4,2,1,4,3,3,0,0.0,neutral or dissatisfied +83376,48618,Female,disloyal Customer,34,Business travel,Eco Plus,833,1,1,1,5,5,1,3,5,3,4,3,2,2,5,0,0.0,neutral or dissatisfied +83377,68581,Female,Loyal Customer,18,Personal Travel,Eco,1616,3,3,3,3,4,3,4,4,1,3,2,3,3,4,0,0.0,neutral or dissatisfied +83378,23388,Male,disloyal Customer,32,Business travel,Eco,300,3,5,3,3,1,3,1,1,2,4,1,2,1,1,69,61.0,neutral or dissatisfied +83379,381,Female,Loyal Customer,56,Business travel,Business,102,5,4,5,5,3,4,4,4,4,4,4,4,4,4,34,31.0,satisfied +83380,31762,Female,Loyal Customer,22,Business travel,Business,602,1,2,2,2,2,1,1,3,1,4,3,1,1,1,139,130.0,neutral or dissatisfied +83381,60307,Male,Loyal Customer,35,Business travel,Eco,406,2,3,1,1,2,2,2,2,2,4,1,1,2,2,0,0.0,neutral or dissatisfied +83382,73397,Male,disloyal Customer,24,Business travel,Eco,1005,3,4,4,3,3,4,5,3,3,3,3,3,3,3,54,35.0,neutral or dissatisfied +83383,111604,Male,Loyal Customer,34,Personal Travel,Eco Plus,794,4,5,4,2,5,4,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +83384,4176,Male,Loyal Customer,70,Personal Travel,Eco,431,3,4,4,3,5,4,5,5,3,4,4,1,3,5,66,76.0,neutral or dissatisfied +83385,33942,Male,disloyal Customer,20,Business travel,Business,1188,0,4,0,1,4,0,3,4,4,1,3,5,1,4,5,0.0,satisfied +83386,86690,Male,Loyal Customer,48,Business travel,Business,1747,3,3,3,3,2,3,5,4,4,5,4,4,4,5,0,1.0,satisfied +83387,6409,Female,Loyal Customer,24,Personal Travel,Eco,240,2,4,2,3,2,2,2,2,5,2,4,4,5,2,52,50.0,neutral or dissatisfied +83388,82594,Male,Loyal Customer,54,Business travel,Business,528,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +83389,42881,Female,Loyal Customer,54,Personal Travel,Eco,867,3,4,3,3,1,4,4,3,3,3,1,2,3,2,0,0.0,neutral or dissatisfied +83390,84472,Male,Loyal Customer,71,Business travel,Business,742,2,3,4,3,2,2,1,2,2,2,2,2,2,2,0,2.0,neutral or dissatisfied +83391,63880,Male,Loyal Customer,47,Business travel,Eco,1212,4,3,3,3,4,4,4,4,1,4,2,1,3,4,0,0.0,neutral or dissatisfied +83392,54892,Male,Loyal Customer,23,Personal Travel,Eco,862,1,5,1,3,5,1,5,5,3,4,4,5,4,5,8,19.0,neutral or dissatisfied +83393,27043,Male,Loyal Customer,21,Personal Travel,Business,1489,3,3,3,3,2,3,4,2,1,3,3,2,3,2,10,1.0,neutral or dissatisfied +83394,23691,Female,Loyal Customer,34,Business travel,Eco,212,1,4,4,4,1,1,1,1,3,5,3,1,2,1,0,0.0,neutral or dissatisfied +83395,33367,Male,Loyal Customer,48,Personal Travel,Eco,2355,3,4,3,3,3,2,2,5,3,4,4,2,3,2,414,,neutral or dissatisfied +83396,118215,Male,disloyal Customer,42,Business travel,Business,735,2,2,2,3,5,2,5,5,5,3,5,3,4,5,7,0.0,satisfied +83397,20622,Female,disloyal Customer,24,Business travel,Eco,783,2,2,2,2,3,2,3,3,1,2,5,1,2,3,0,0.0,neutral or dissatisfied +83398,117847,Female,Loyal Customer,29,Business travel,Business,2133,1,1,1,1,1,1,1,1,4,4,2,3,4,1,24,0.0,neutral or dissatisfied +83399,89237,Female,Loyal Customer,26,Business travel,Business,2139,3,3,3,3,4,4,4,4,4,2,5,5,4,4,4,27.0,satisfied +83400,96092,Male,Loyal Customer,69,Personal Travel,Eco,583,3,5,2,4,1,2,1,1,3,4,5,4,5,1,28,31.0,neutral or dissatisfied +83401,6835,Female,Loyal Customer,31,Personal Travel,Eco,223,3,4,3,3,1,3,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +83402,70830,Female,Loyal Customer,48,Business travel,Business,1998,1,1,1,1,4,5,5,5,5,5,5,3,5,4,0,2.0,satisfied +83403,29664,Female,Loyal Customer,54,Personal Travel,Eco,680,4,4,4,2,4,5,5,2,2,4,2,5,2,4,60,66.0,neutral or dissatisfied +83404,94716,Male,Loyal Customer,52,Business travel,Business,2310,4,4,4,4,2,5,4,4,4,4,4,3,4,5,11,2.0,satisfied +83405,22582,Female,Loyal Customer,64,Business travel,Business,2158,1,4,1,1,3,1,2,4,4,4,4,2,4,1,7,13.0,satisfied +83406,62642,Male,Loyal Customer,49,Personal Travel,Eco,1744,1,5,1,5,5,1,5,5,4,4,3,5,5,5,0,0.0,neutral or dissatisfied +83407,128861,Female,disloyal Customer,37,Business travel,Business,2586,3,3,3,2,3,4,4,5,5,5,5,4,5,4,10,0.0,neutral or dissatisfied +83408,31493,Female,Loyal Customer,41,Business travel,Eco,853,2,3,2,3,2,2,2,2,2,2,2,3,3,2,114,106.0,neutral or dissatisfied +83409,24262,Male,Loyal Customer,70,Personal Travel,Eco,302,5,4,2,3,5,2,5,5,1,4,3,3,4,5,0,0.0,satisfied +83410,167,Female,Loyal Customer,66,Personal Travel,Eco,227,3,5,0,3,5,5,5,5,5,0,1,3,5,4,0,0.0,neutral or dissatisfied +83411,65868,Male,Loyal Customer,69,Personal Travel,Eco,1389,4,4,4,3,1,4,1,1,1,5,4,2,4,1,0,0.0,neutral or dissatisfied +83412,57364,Female,Loyal Customer,21,Personal Travel,Eco,414,1,3,1,4,3,1,3,3,1,2,5,1,4,3,28,20.0,neutral or dissatisfied +83413,58521,Female,Loyal Customer,58,Personal Travel,Eco,719,2,5,2,2,5,4,4,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +83414,106930,Male,Loyal Customer,53,Personal Travel,Eco Plus,1259,4,4,3,2,3,3,3,3,5,3,5,5,5,3,18,0.0,satisfied +83415,80576,Male,disloyal Customer,38,Business travel,Eco,247,3,4,3,4,2,3,2,2,4,5,1,3,5,2,0,0.0,neutral or dissatisfied +83416,111178,Male,Loyal Customer,48,Business travel,Business,1703,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +83417,105167,Female,Loyal Customer,32,Personal Travel,Eco,220,5,2,0,3,5,0,5,5,3,5,3,4,4,5,0,0.0,satisfied +83418,31241,Female,disloyal Customer,26,Business travel,Eco,472,4,0,4,3,1,4,1,1,4,5,5,1,2,1,0,2.0,neutral or dissatisfied +83419,102328,Female,Loyal Customer,58,Business travel,Eco,226,3,1,1,1,4,3,3,3,3,3,3,2,3,4,11,5.0,neutral or dissatisfied +83420,6912,Male,Loyal Customer,56,Personal Travel,Eco,323,1,4,1,4,2,1,2,2,2,1,3,1,4,2,29,60.0,neutral or dissatisfied +83421,51232,Female,Loyal Customer,63,Business travel,Eco Plus,109,5,2,2,2,5,5,5,5,5,5,5,4,5,1,5,7.0,satisfied +83422,124800,Female,Loyal Customer,27,Business travel,Business,280,1,1,1,1,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +83423,7229,Male,Loyal Customer,43,Business travel,Business,2252,3,3,3,3,2,2,4,4,4,4,5,5,4,5,77,68.0,satisfied +83424,106199,Female,disloyal Customer,64,Business travel,Eco Plus,302,2,1,1,3,1,2,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +83425,36074,Male,Loyal Customer,35,Business travel,Eco,399,2,5,3,3,2,2,2,2,2,4,2,4,2,2,0,0.0,satisfied +83426,18799,Female,Loyal Customer,25,Business travel,Business,2486,5,5,5,5,4,4,4,4,2,1,4,1,3,4,0,0.0,satisfied +83427,10863,Female,Loyal Customer,65,Business travel,Business,429,3,3,3,3,1,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +83428,61270,Male,Loyal Customer,39,Personal Travel,Eco,862,4,5,3,1,1,3,1,1,5,4,4,4,5,1,22,27.0,neutral or dissatisfied +83429,1570,Male,Loyal Customer,31,Business travel,Business,140,4,4,4,4,3,4,4,3,5,4,5,5,5,3,31,34.0,satisfied +83430,109411,Male,Loyal Customer,39,Business travel,Business,834,4,4,4,4,2,4,5,5,5,5,5,4,5,4,15,1.0,satisfied +83431,15990,Female,Loyal Customer,49,Business travel,Eco,794,4,2,2,2,1,1,2,5,5,4,5,4,5,1,0,0.0,satisfied +83432,32031,Female,disloyal Customer,36,Business travel,Eco,101,3,0,3,4,2,3,2,2,4,2,5,4,4,2,1,0.0,neutral or dissatisfied +83433,67953,Female,Loyal Customer,22,Business travel,Business,1837,2,2,2,2,3,4,3,3,5,5,4,3,4,3,0,13.0,satisfied +83434,85891,Male,Loyal Customer,30,Personal Travel,Eco Plus,2172,4,5,4,3,2,4,2,2,3,3,3,5,4,2,0,0.0,neutral or dissatisfied +83435,128575,Male,disloyal Customer,37,Business travel,Business,2552,2,2,2,4,2,4,4,5,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +83436,17929,Female,disloyal Customer,57,Business travel,Eco Plus,789,1,1,1,2,1,3,3,4,2,5,1,3,1,3,154,144.0,neutral or dissatisfied +83437,118309,Male,Loyal Customer,44,Business travel,Eco,602,3,3,3,3,3,3,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +83438,78430,Female,Loyal Customer,53,Business travel,Business,526,4,4,4,4,3,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +83439,30610,Male,Loyal Customer,44,Personal Travel,Eco,472,4,4,4,4,1,4,1,1,4,5,4,4,5,1,62,81.0,neutral or dissatisfied +83440,118848,Male,Loyal Customer,14,Personal Travel,Eco Plus,451,5,4,5,4,2,5,2,2,3,3,5,4,4,2,0,0.0,satisfied +83441,119808,Female,Loyal Customer,54,Business travel,Business,3069,4,4,4,4,2,5,5,4,4,4,4,3,4,5,80,93.0,satisfied +83442,48610,Female,Loyal Customer,52,Business travel,Eco Plus,844,4,5,5,5,4,4,3,4,4,4,4,4,4,4,9,0.0,satisfied +83443,94884,Male,Loyal Customer,37,Business travel,Business,323,3,5,5,5,4,4,3,3,3,3,3,4,3,2,8,10.0,neutral or dissatisfied +83444,5830,Male,Loyal Customer,60,Personal Travel,Eco,273,1,2,2,4,5,2,5,5,4,3,4,2,3,5,1,5.0,neutral or dissatisfied +83445,18616,Male,Loyal Customer,45,Personal Travel,Eco,383,3,4,2,3,2,2,3,2,1,4,5,1,5,2,0,0.0,neutral or dissatisfied +83446,44447,Female,Loyal Customer,43,Business travel,Business,2441,3,4,4,4,3,4,3,3,3,3,3,2,3,3,0,6.0,neutral or dissatisfied +83447,107576,Male,Loyal Customer,21,Personal Travel,Eco,1521,3,2,3,3,4,3,4,4,2,1,3,1,2,4,3,0.0,neutral or dissatisfied +83448,129484,Female,Loyal Customer,21,Business travel,Business,2611,3,3,3,3,3,3,3,3,1,4,4,3,4,3,1,0.0,neutral or dissatisfied +83449,97550,Female,Loyal Customer,14,Personal Travel,Eco,462,1,2,1,2,2,1,5,2,4,2,2,2,3,2,0,0.0,neutral or dissatisfied +83450,57594,Female,Loyal Customer,54,Business travel,Business,1597,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,7.0,satisfied +83451,523,Female,Loyal Customer,48,Business travel,Business,3418,3,3,3,3,4,4,5,3,3,4,4,5,3,3,0,1.0,satisfied +83452,67952,Female,Loyal Customer,33,Personal Travel,Eco,1235,2,4,2,3,5,2,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +83453,43386,Female,Loyal Customer,38,Personal Travel,Eco,358,4,5,4,2,1,4,1,1,4,2,4,4,5,1,18,9.0,neutral or dissatisfied +83454,90943,Female,Loyal Customer,44,Business travel,Eco,404,4,5,5,5,2,3,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +83455,29722,Female,Loyal Customer,30,Business travel,Business,2777,1,1,1,1,4,5,5,3,3,5,2,5,5,5,0,0.0,satisfied +83456,35634,Male,Loyal Customer,49,Business travel,Business,1626,3,3,3,3,1,3,3,3,3,4,3,3,3,1,28,36.0,satisfied +83457,60551,Female,Loyal Customer,39,Business travel,Business,3537,3,3,3,3,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +83458,45750,Female,disloyal Customer,62,Business travel,Eco,391,2,3,2,2,5,2,5,5,2,4,5,2,2,5,10,19.0,neutral or dissatisfied +83459,22349,Male,disloyal Customer,16,Business travel,Eco,238,2,4,2,4,4,2,4,4,1,3,4,2,3,4,16,26.0,neutral or dissatisfied +83460,127134,Male,Loyal Customer,26,Personal Travel,Eco,647,3,4,3,3,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +83461,86683,Male,disloyal Customer,35,Business travel,Business,1747,2,2,2,5,2,2,2,2,3,4,4,4,4,2,0,1.0,neutral or dissatisfied +83462,79418,Male,Loyal Customer,33,Personal Travel,Eco,502,3,5,3,3,1,3,5,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +83463,83767,Male,Loyal Customer,35,Business travel,Business,926,4,2,2,2,4,2,2,4,4,4,4,4,4,3,15,7.0,neutral or dissatisfied +83464,85184,Male,disloyal Customer,29,Business travel,Business,874,5,5,5,1,2,5,2,2,5,3,5,5,5,2,9,8.0,satisfied +83465,17399,Male,disloyal Customer,21,Business travel,Eco,351,0,0,0,1,3,0,3,3,5,1,5,4,5,3,1,0.0,satisfied +83466,57852,Female,Loyal Customer,33,Business travel,Business,2329,1,1,1,1,2,2,2,5,4,4,5,2,4,2,10,68.0,satisfied +83467,105918,Male,Loyal Customer,7,Personal Travel,Eco,283,4,2,4,4,5,4,5,5,2,2,4,4,4,5,0,0.0,neutral or dissatisfied +83468,118767,Male,Loyal Customer,69,Personal Travel,Eco,369,3,5,3,3,1,3,1,1,4,3,4,4,4,1,20,18.0,neutral or dissatisfied +83469,47457,Female,Loyal Customer,41,Personal Travel,Eco,588,3,3,3,3,4,3,4,4,4,4,3,2,2,4,0,0.0,neutral or dissatisfied +83470,11167,Female,Loyal Customer,19,Personal Travel,Eco,429,3,3,3,1,4,3,4,4,4,2,4,1,4,4,42,33.0,neutral or dissatisfied +83471,41906,Female,Loyal Customer,57,Business travel,Business,2671,1,1,1,1,5,3,3,5,5,5,4,4,5,2,0,3.0,satisfied +83472,96323,Female,Loyal Customer,55,Business travel,Business,359,3,3,3,3,2,5,5,5,5,5,5,4,5,4,44,28.0,satisfied +83473,39388,Male,Loyal Customer,42,Business travel,Business,521,2,2,2,2,3,4,2,5,5,4,5,5,5,1,0,0.0,satisfied +83474,78512,Female,Loyal Customer,34,Business travel,Business,2353,4,4,4,4,3,4,4,2,5,4,2,4,2,4,410,435.0,satisfied +83475,36650,Female,Loyal Customer,28,Personal Travel,Eco,1185,4,4,4,2,2,4,2,2,1,3,3,2,4,2,1,7.0,neutral or dissatisfied +83476,18089,Female,Loyal Customer,40,Personal Travel,Eco,488,2,5,2,5,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +83477,61801,Male,Loyal Customer,24,Personal Travel,Eco,1346,4,5,4,2,1,4,1,1,4,3,5,3,5,1,3,0.0,neutral or dissatisfied +83478,123338,Male,Loyal Customer,27,Personal Travel,Eco Plus,650,2,4,2,4,4,2,4,4,4,1,4,4,4,4,5,8.0,neutral or dissatisfied +83479,50653,Male,Loyal Customer,26,Personal Travel,Eco,86,2,4,2,3,2,2,2,2,3,5,4,5,5,2,0,9.0,neutral or dissatisfied +83480,51487,Female,Loyal Customer,35,Business travel,Business,425,1,2,2,2,4,4,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +83481,36716,Male,disloyal Customer,28,Business travel,Business,1121,1,1,1,4,2,1,2,2,3,3,3,3,3,2,0,11.0,neutral or dissatisfied +83482,37794,Female,Loyal Customer,30,Business travel,Eco Plus,1069,4,5,5,5,4,4,4,4,1,5,5,3,1,4,3,8.0,satisfied +83483,9906,Male,Loyal Customer,55,Business travel,Business,357,5,5,5,5,2,5,4,4,4,4,4,3,4,5,12,2.0,satisfied +83484,107105,Female,Loyal Customer,45,Business travel,Eco Plus,562,2,5,5,5,3,4,3,2,2,2,2,4,2,3,2,0.0,neutral or dissatisfied +83485,24053,Male,Loyal Customer,8,Personal Travel,Eco,562,2,4,2,3,3,2,3,3,4,4,5,3,4,3,0,9.0,neutral or dissatisfied +83486,62627,Male,Loyal Customer,43,Personal Travel,Eco,1744,2,4,2,3,3,2,3,3,4,5,5,5,4,3,0,6.0,neutral or dissatisfied +83487,93564,Female,Loyal Customer,17,Personal Travel,Eco Plus,719,3,4,3,3,2,3,2,2,3,3,4,5,5,2,0,2.0,neutral or dissatisfied +83488,121763,Female,Loyal Customer,51,Personal Travel,Business,366,2,1,2,3,3,3,3,4,4,2,1,4,4,4,0,0.0,neutral or dissatisfied +83489,101390,Male,Loyal Customer,43,Business travel,Business,486,3,4,4,4,3,3,4,3,3,3,3,2,3,2,60,57.0,neutral or dissatisfied +83490,128367,Female,Loyal Customer,57,Business travel,Business,621,3,3,3,3,3,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +83491,47894,Female,Loyal Customer,33,Business travel,Business,329,3,5,3,3,1,3,2,5,5,5,5,4,5,4,29,23.0,satisfied +83492,105573,Female,Loyal Customer,51,Business travel,Business,1873,3,3,3,3,4,4,4,3,3,4,3,3,3,3,23,11.0,satisfied +83493,96047,Male,Loyal Customer,22,Business travel,Eco,1235,3,3,3,3,3,3,3,3,4,2,4,3,3,3,35,35.0,neutral or dissatisfied +83494,63123,Male,Loyal Customer,55,Business travel,Business,447,4,2,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +83495,107736,Female,Loyal Customer,36,Personal Travel,Eco,251,2,4,2,4,4,2,2,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +83496,30865,Female,Loyal Customer,32,Business travel,Eco,1546,4,5,5,5,4,4,4,4,1,3,3,3,4,4,5,1.0,neutral or dissatisfied +83497,31570,Male,Loyal Customer,65,Personal Travel,Eco Plus,846,4,4,4,3,5,4,4,5,4,4,4,5,4,5,3,0.0,neutral or dissatisfied +83498,48621,Female,Loyal Customer,29,Personal Travel,Eco Plus,959,2,5,2,3,3,2,3,3,3,2,4,5,5,3,19,21.0,neutral or dissatisfied +83499,82862,Female,Loyal Customer,63,Business travel,Eco,645,3,4,4,4,1,4,3,3,3,3,3,2,3,1,24,4.0,neutral or dissatisfied +83500,9352,Female,disloyal Customer,50,Business travel,Business,441,2,2,2,1,2,2,2,2,5,2,4,3,5,2,0,5.0,neutral or dissatisfied +83501,36181,Female,Loyal Customer,41,Business travel,Eco Plus,1674,5,5,3,5,5,5,1,5,5,5,5,4,5,4,0,0.0,satisfied +83502,109002,Female,Loyal Customer,49,Business travel,Business,3864,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +83503,26844,Female,Loyal Customer,49,Business travel,Eco,224,5,4,4,4,5,5,4,5,5,5,5,2,5,1,0,0.0,satisfied +83504,61475,Male,disloyal Customer,28,Business travel,Eco,2288,3,3,3,3,4,3,4,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +83505,94471,Female,Loyal Customer,30,Business travel,Business,3665,1,1,1,1,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +83506,123572,Female,disloyal Customer,31,Business travel,Business,1773,1,1,1,1,1,1,1,1,5,3,3,3,5,1,0,0.0,neutral or dissatisfied +83507,35115,Male,disloyal Customer,27,Business travel,Eco,1028,2,3,3,4,3,3,3,3,3,4,2,5,3,3,0,0.0,neutral or dissatisfied +83508,106325,Female,Loyal Customer,54,Business travel,Business,825,5,5,5,5,3,4,5,4,4,3,4,5,4,3,0,9.0,satisfied +83509,67254,Female,Loyal Customer,49,Personal Travel,Eco,929,2,4,2,1,3,5,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +83510,35337,Female,Loyal Customer,72,Business travel,Business,3553,3,1,1,1,3,2,2,3,3,3,3,1,3,1,1,83.0,neutral or dissatisfied +83511,126353,Female,Loyal Customer,10,Personal Travel,Eco,590,3,4,3,3,3,3,1,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +83512,5523,Male,Loyal Customer,50,Business travel,Business,2593,1,1,1,1,4,5,4,5,5,5,5,4,5,3,33,32.0,satisfied +83513,83663,Male,Loyal Customer,54,Business travel,Business,3144,1,1,2,1,3,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +83514,111974,Male,Loyal Customer,71,Business travel,Business,370,5,5,5,5,5,2,1,4,4,4,4,1,4,4,4,0.0,satisfied +83515,92765,Female,Loyal Customer,55,Personal Travel,Eco Plus,1276,2,5,2,1,3,4,4,5,5,2,2,5,5,4,0,0.0,neutral or dissatisfied +83516,25951,Female,Loyal Customer,49,Business travel,Business,1805,3,3,3,3,3,5,4,3,3,3,3,2,3,3,19,0.0,satisfied +83517,99862,Female,Loyal Customer,55,Personal Travel,Eco,534,3,3,3,3,4,4,3,1,1,3,1,4,1,3,39,33.0,neutral or dissatisfied +83518,90465,Male,Loyal Customer,34,Business travel,Business,1542,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +83519,60893,Female,disloyal Customer,47,Business travel,Eco,420,2,1,2,3,2,2,2,2,1,4,3,3,4,2,6,4.0,neutral or dissatisfied +83520,104324,Male,Loyal Customer,39,Business travel,Business,452,3,2,2,2,5,3,2,3,3,3,3,4,3,4,52,73.0,neutral or dissatisfied +83521,69861,Male,Loyal Customer,28,Personal Travel,Eco,1055,4,5,4,2,1,4,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +83522,103005,Female,Loyal Customer,59,Business travel,Business,2368,5,5,5,5,5,4,4,5,5,5,5,3,5,5,8,0.0,satisfied +83523,7578,Male,disloyal Customer,23,Business travel,Business,594,4,3,4,3,3,4,3,3,4,2,4,5,5,3,0,0.0,satisfied +83524,85369,Male,Loyal Customer,60,Business travel,Business,2400,3,3,4,3,2,5,4,5,5,4,5,3,5,5,0,1.0,satisfied +83525,71823,Female,disloyal Customer,28,Business travel,Business,1007,5,5,5,1,5,5,5,5,4,2,3,5,4,5,0,0.0,satisfied +83526,86561,Male,Loyal Customer,11,Personal Travel,Eco Plus,749,3,4,3,3,3,3,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +83527,110216,Female,Loyal Customer,29,Personal Travel,Eco,1310,1,5,1,1,4,1,4,4,5,5,5,5,5,4,15,3.0,neutral or dissatisfied +83528,522,Female,Loyal Customer,39,Business travel,Business,158,1,1,1,1,4,4,5,4,4,4,5,4,4,5,0,18.0,satisfied +83529,54142,Male,Loyal Customer,22,Business travel,Business,1400,3,3,3,3,5,5,5,5,5,2,1,1,3,5,0,0.0,satisfied +83530,113952,Female,Loyal Customer,43,Business travel,Business,1728,4,4,4,4,2,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +83531,116372,Male,Loyal Customer,49,Personal Travel,Eco,325,3,3,3,3,2,3,3,2,4,5,2,3,3,2,35,24.0,neutral or dissatisfied +83532,88886,Female,Loyal Customer,37,Business travel,Business,3270,5,5,4,5,3,5,5,5,5,4,5,5,5,5,9,23.0,satisfied +83533,16762,Male,disloyal Customer,33,Business travel,Eco,642,3,4,3,3,5,3,5,5,5,2,3,5,1,5,0,0.0,neutral or dissatisfied +83534,71242,Female,Loyal Customer,25,Business travel,Business,733,2,4,4,4,2,2,2,2,3,5,4,4,3,2,104,88.0,neutral or dissatisfied +83535,24449,Male,disloyal Customer,23,Business travel,Eco,547,4,4,5,3,4,5,4,4,2,3,4,3,1,4,2,0.0,neutral or dissatisfied +83536,38886,Male,Loyal Customer,35,Personal Travel,Eco Plus,261,3,5,3,3,4,3,4,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +83537,99123,Male,Loyal Customer,46,Personal Travel,Eco,181,4,3,4,2,2,4,5,2,2,1,3,3,2,2,11,9.0,satisfied +83538,77059,Female,Loyal Customer,25,Personal Travel,Business,991,3,5,3,4,4,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +83539,111311,Male,Loyal Customer,57,Business travel,Business,3015,4,4,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +83540,69076,Male,Loyal Customer,65,Business travel,Eco,989,5,1,1,1,5,5,5,5,4,3,5,3,3,5,3,22.0,satisfied +83541,104644,Female,disloyal Customer,15,Business travel,Business,1754,0,0,0,4,4,0,4,4,4,5,4,4,5,4,1,0.0,satisfied +83542,21439,Female,Loyal Customer,22,Business travel,Business,399,4,4,4,4,4,4,4,4,2,1,3,2,4,4,0,0.0,satisfied +83543,100594,Male,Loyal Customer,46,Business travel,Business,486,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +83544,29000,Female,disloyal Customer,29,Business travel,Eco,937,2,1,1,4,2,1,3,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +83545,22700,Male,Loyal Customer,26,Personal Travel,Eco,589,3,5,3,4,3,3,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +83546,64384,Male,Loyal Customer,37,Personal Travel,Eco,1192,4,3,4,4,2,4,2,2,4,2,4,2,2,2,0,0.0,neutral or dissatisfied +83547,36974,Male,Loyal Customer,26,Business travel,Business,2040,4,4,5,4,4,4,4,4,5,5,5,4,2,4,37,94.0,satisfied +83548,17815,Female,Loyal Customer,30,Personal Travel,Eco,986,3,3,3,2,3,3,3,3,4,3,2,3,3,3,80,69.0,neutral or dissatisfied +83549,85499,Female,Loyal Customer,7,Personal Travel,Eco,214,4,0,4,3,3,4,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +83550,17378,Male,Loyal Customer,22,Business travel,Business,637,4,2,2,2,4,3,4,4,3,1,4,2,3,4,23,6.0,neutral or dissatisfied +83551,69870,Male,Loyal Customer,40,Personal Travel,Eco Plus,1055,3,4,3,3,2,3,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +83552,111104,Male,Loyal Customer,54,Business travel,Business,2927,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +83553,16630,Male,disloyal Customer,29,Business travel,Business,488,2,2,2,3,1,2,1,1,3,3,3,3,4,1,100,100.0,neutral or dissatisfied +83554,124736,Female,disloyal Customer,36,Business travel,Business,399,2,2,2,4,4,2,4,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +83555,89427,Male,Loyal Customer,33,Business travel,Eco,134,1,2,2,2,1,1,1,1,1,4,4,3,3,1,0,0.0,neutral or dissatisfied +83556,32783,Female,disloyal Customer,35,Business travel,Eco,102,4,3,4,1,1,4,1,1,1,4,2,4,4,1,6,9.0,neutral or dissatisfied +83557,94634,Male,Loyal Customer,53,Business travel,Business,323,1,1,1,1,3,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +83558,102273,Female,disloyal Customer,42,Business travel,Business,391,2,2,2,2,2,2,2,2,5,4,5,3,4,2,9,0.0,neutral or dissatisfied +83559,99556,Female,disloyal Customer,22,Business travel,Eco,802,2,2,2,3,3,2,3,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +83560,79131,Female,Loyal Customer,42,Business travel,Business,377,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +83561,45120,Male,Loyal Customer,59,Personal Travel,Eco,157,4,2,4,3,2,4,5,2,1,1,3,1,4,2,0,0.0,satisfied +83562,11154,Female,Loyal Customer,41,Personal Travel,Eco,270,2,2,2,4,2,5,5,1,4,3,3,5,1,5,147,139.0,neutral or dissatisfied +83563,38825,Male,Loyal Customer,44,Personal Travel,Eco,353,2,4,3,2,4,3,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +83564,118994,Male,Loyal Customer,52,Business travel,Business,2004,1,1,1,1,2,4,5,5,5,5,5,4,5,4,10,0.0,satisfied +83565,50555,Male,Loyal Customer,44,Personal Travel,Eco,250,2,5,2,3,3,2,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +83566,42869,Female,disloyal Customer,23,Business travel,Eco,867,1,2,2,3,1,2,1,1,3,4,1,4,4,1,0,4.0,neutral or dissatisfied +83567,82545,Female,Loyal Customer,63,Personal Travel,Eco,440,5,5,5,1,4,5,4,3,3,5,3,5,3,4,0,0.0,satisfied +83568,38795,Male,Loyal Customer,33,Business travel,Business,354,3,3,3,3,5,4,5,5,2,5,2,5,5,5,0,0.0,satisfied +83569,115782,Male,Loyal Customer,37,Business travel,Business,390,5,5,5,5,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +83570,105368,Male,Loyal Customer,51,Business travel,Business,3923,2,2,5,2,3,5,5,5,5,5,5,4,5,5,8,0.0,satisfied +83571,52128,Male,Loyal Customer,56,Business travel,Business,3998,3,3,3,3,4,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +83572,120196,Female,Loyal Customer,38,Business travel,Business,1303,3,3,3,3,3,3,3,3,3,3,3,4,3,1,24,54.0,neutral or dissatisfied +83573,121843,Female,Loyal Customer,51,Business travel,Business,449,1,4,2,2,3,3,4,1,1,1,1,4,1,4,18,61.0,neutral or dissatisfied +83574,35425,Female,Loyal Customer,17,Personal Travel,Eco,972,1,4,1,3,3,1,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +83575,80689,Female,Loyal Customer,46,Business travel,Business,2903,1,1,1,1,5,4,4,5,5,5,5,5,5,5,0,13.0,satisfied +83576,107412,Male,Loyal Customer,58,Business travel,Business,725,2,2,2,2,4,5,5,4,4,5,4,3,4,4,39,32.0,satisfied +83577,78899,Male,Loyal Customer,38,Personal Travel,Eco,1823,3,3,4,4,2,4,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +83578,6172,Male,Loyal Customer,33,Personal Travel,Eco,491,0,4,0,2,3,0,3,3,2,2,1,5,5,3,3,10.0,satisfied +83579,34940,Male,Loyal Customer,34,Personal Travel,Eco,187,1,5,1,3,4,1,2,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +83580,63653,Female,Loyal Customer,67,Personal Travel,Eco,1448,3,4,3,4,5,3,3,1,1,3,5,2,1,1,4,0.0,neutral or dissatisfied +83581,13581,Female,Loyal Customer,12,Personal Travel,Eco,214,2,4,2,3,2,3,3,2,3,3,3,3,2,3,135,119.0,neutral or dissatisfied +83582,71102,Female,Loyal Customer,14,Personal Travel,Eco Plus,802,1,4,1,1,3,1,3,3,5,3,5,4,4,3,2,22.0,neutral or dissatisfied +83583,14018,Male,Loyal Customer,52,Personal Travel,Eco,182,2,5,0,3,2,0,1,2,5,2,5,3,5,2,67,76.0,neutral or dissatisfied +83584,44632,Female,Loyal Customer,28,Business travel,Eco,160,0,0,0,5,2,0,2,2,4,5,2,5,2,2,11,12.0,satisfied +83585,46082,Female,disloyal Customer,22,Business travel,Eco,541,1,3,1,3,2,1,2,2,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +83586,40578,Male,disloyal Customer,24,Business travel,Eco,216,2,2,2,4,3,2,3,3,1,1,4,3,4,3,2,1.0,neutral or dissatisfied +83587,3822,Female,Loyal Customer,41,Business travel,Business,2795,2,2,2,2,2,4,3,2,2,2,2,1,2,4,50,44.0,neutral or dissatisfied +83588,4246,Female,Loyal Customer,28,Personal Travel,Eco,1020,1,2,1,4,5,1,4,5,3,2,3,4,3,5,39,64.0,neutral or dissatisfied +83589,110890,Male,Loyal Customer,51,Business travel,Business,2766,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +83590,111446,Male,Loyal Customer,36,Business travel,Business,1024,2,2,2,2,4,4,5,4,4,4,4,3,4,3,7,0.0,satisfied +83591,69177,Female,Loyal Customer,64,Personal Travel,Eco,187,0,4,0,1,2,5,5,1,1,0,1,3,1,4,0,0.0,satisfied +83592,68138,Female,Loyal Customer,50,Business travel,Business,2220,5,5,5,5,4,5,5,4,4,4,4,4,4,5,39,23.0,satisfied +83593,82798,Male,Loyal Customer,40,Business travel,Business,235,3,3,3,3,5,4,5,4,4,4,4,5,4,4,4,1.0,satisfied +83594,70113,Female,Loyal Customer,26,Business travel,Business,550,3,3,3,3,5,5,5,5,5,4,4,4,4,5,66,60.0,satisfied +83595,122859,Female,disloyal Customer,21,Business travel,Eco,226,3,2,3,3,1,3,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +83596,99802,Male,disloyal Customer,37,Business travel,Eco,184,1,2,0,4,2,0,5,2,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +83597,122901,Male,Loyal Customer,47,Business travel,Business,468,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,7.0,satisfied +83598,34086,Male,Loyal Customer,54,Business travel,Eco,2072,2,2,2,2,2,2,2,2,3,3,4,1,4,2,6,12.0,neutral or dissatisfied +83599,62379,Male,disloyal Customer,23,Business travel,Eco,766,5,5,5,3,2,5,2,2,3,3,3,5,5,2,0,0.0,satisfied +83600,39453,Female,Loyal Customer,26,Personal Travel,Eco,129,2,3,2,3,2,2,3,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +83601,27750,Male,Loyal Customer,40,Business travel,Eco,909,5,4,4,4,5,5,5,5,1,5,2,3,4,5,0,0.0,satisfied +83602,66860,Female,Loyal Customer,17,Personal Travel,Eco,731,5,3,5,4,1,5,4,1,1,4,3,2,3,1,3,0.0,satisfied +83603,26069,Female,Loyal Customer,27,Business travel,Eco,591,5,3,3,3,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +83604,59287,Male,Loyal Customer,23,Personal Travel,Eco,3302,2,1,2,3,2,1,1,2,3,3,4,1,1,1,0,0.0,neutral or dissatisfied +83605,128395,Female,Loyal Customer,37,Business travel,Eco,304,2,1,1,1,2,2,2,2,2,2,3,4,2,2,0,9.0,neutral or dissatisfied +83606,72354,Female,Loyal Customer,51,Personal Travel,Business,929,1,4,1,4,5,4,5,2,2,1,1,4,2,3,38,36.0,neutral or dissatisfied +83607,116741,Male,Loyal Customer,55,Personal Travel,Eco Plus,390,1,3,1,3,5,1,3,5,3,2,3,1,4,5,3,0.0,neutral or dissatisfied +83608,44581,Female,Loyal Customer,34,Business travel,Business,157,4,5,4,4,1,3,4,4,4,4,5,1,4,1,59,58.0,satisfied +83609,113689,Male,Loyal Customer,19,Personal Travel,Eco,226,4,4,4,5,4,4,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +83610,18553,Male,Loyal Customer,44,Business travel,Eco,192,4,3,2,3,4,4,4,4,5,2,5,4,5,4,19,19.0,satisfied +83611,12820,Female,Loyal Customer,47,Business travel,Eco,528,5,1,1,1,4,5,2,5,5,5,5,2,5,1,0,0.0,satisfied +83612,59340,Female,Loyal Customer,44,Business travel,Business,2399,1,1,1,1,2,5,4,4,4,4,4,5,4,3,19,3.0,satisfied +83613,57966,Male,Loyal Customer,8,Personal Travel,Eco,1911,3,5,3,4,3,3,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +83614,29937,Male,Loyal Customer,49,Business travel,Business,261,2,2,2,2,4,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +83615,9767,Male,Loyal Customer,43,Business travel,Business,383,2,2,2,2,3,4,4,4,4,4,4,3,4,5,36,40.0,satisfied +83616,127603,Male,disloyal Customer,29,Business travel,Eco,1411,1,1,1,3,2,1,4,2,3,2,3,2,4,2,11,13.0,neutral or dissatisfied +83617,46915,Female,disloyal Customer,44,Business travel,Eco,737,2,1,1,4,4,1,4,4,2,5,4,1,3,4,94,91.0,neutral or dissatisfied +83618,125643,Female,Loyal Customer,59,Business travel,Business,2645,3,3,3,3,5,5,4,3,3,4,3,5,3,4,28,16.0,satisfied +83619,24253,Female,Loyal Customer,14,Personal Travel,Eco,147,2,3,2,4,1,2,1,1,3,1,4,3,4,1,68,53.0,neutral or dissatisfied +83620,32629,Male,disloyal Customer,20,Business travel,Eco,201,2,4,2,4,5,2,1,5,3,1,3,1,4,5,0,4.0,neutral or dissatisfied +83621,123555,Female,Loyal Customer,59,Business travel,Business,1773,3,3,3,3,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +83622,88900,Female,disloyal Customer,34,Business travel,Eco,859,2,3,3,4,4,3,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +83623,22687,Male,Loyal Customer,61,Business travel,Business,2528,1,4,4,4,2,3,2,1,1,2,1,3,1,2,3,1.0,neutral or dissatisfied +83624,29319,Male,Loyal Customer,48,Personal Travel,Eco,834,4,2,4,3,3,4,3,3,3,4,2,1,2,3,0,0.0,neutral or dissatisfied +83625,89082,Male,Loyal Customer,44,Business travel,Business,1892,4,4,4,4,2,5,4,5,5,5,5,3,5,5,9,0.0,satisfied +83626,39161,Female,Loyal Customer,60,Business travel,Eco,237,4,5,3,3,3,4,1,4,4,4,4,2,4,4,0,0.0,satisfied +83627,33628,Male,Loyal Customer,53,Personal Travel,Eco,399,1,4,1,3,2,1,2,2,4,3,4,3,4,2,89,99.0,neutral or dissatisfied +83628,92815,Male,Loyal Customer,34,Business travel,Business,1587,1,4,4,4,1,2,2,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +83629,108296,Male,Loyal Customer,30,Business travel,Business,1838,1,4,1,1,5,5,5,5,5,5,4,4,4,5,15,23.0,satisfied +83630,8759,Female,Loyal Customer,46,Personal Travel,Eco,1147,3,3,3,3,1,2,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +83631,11304,Male,Loyal Customer,23,Personal Travel,Eco,140,3,3,0,3,2,0,2,2,5,2,1,2,3,2,13,0.0,neutral or dissatisfied +83632,36531,Female,Loyal Customer,29,Business travel,Business,2706,5,5,2,5,4,4,4,4,5,4,3,1,1,4,0,17.0,satisfied +83633,2209,Female,disloyal Customer,20,Business travel,Eco,224,3,1,3,3,5,3,5,5,4,3,4,1,4,5,0,2.0,neutral or dissatisfied +83634,100964,Female,Loyal Customer,34,Personal Travel,Eco,1142,1,4,2,4,3,2,5,3,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +83635,22441,Male,Loyal Customer,62,Personal Travel,Eco,145,1,1,1,3,4,1,4,4,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +83636,30343,Female,Loyal Customer,24,Personal Travel,Eco,391,3,5,3,3,4,3,4,4,1,4,4,2,2,4,5,8.0,neutral or dissatisfied +83637,36618,Female,Loyal Customer,36,Business travel,Business,785,1,1,1,1,4,2,4,2,2,2,2,2,2,4,0,1.0,satisfied +83638,108263,Male,disloyal Customer,57,Business travel,Eco,495,2,2,2,3,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +83639,74261,Male,Loyal Customer,60,Business travel,Business,2148,5,5,5,5,3,5,5,5,5,5,5,3,5,5,28,28.0,satisfied +83640,12759,Female,Loyal Customer,48,Personal Travel,Eco,721,4,4,4,1,3,2,2,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +83641,32448,Male,disloyal Customer,38,Business travel,Eco,102,3,0,3,3,4,3,4,4,3,1,4,3,2,4,2,1.0,neutral or dissatisfied +83642,114490,Female,disloyal Customer,8,Business travel,Eco,480,1,1,1,4,4,1,4,4,1,5,3,2,3,4,101,107.0,neutral or dissatisfied +83643,17087,Male,Loyal Customer,44,Business travel,Eco,466,5,2,2,2,5,5,5,5,1,5,4,2,1,5,0,0.0,satisfied +83644,65163,Male,Loyal Customer,70,Personal Travel,Eco,247,2,4,2,2,4,2,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +83645,12068,Female,Loyal Customer,61,Personal Travel,Eco,376,3,5,3,3,4,5,5,3,3,3,1,3,3,3,0,13.0,neutral or dissatisfied +83646,75873,Female,Loyal Customer,69,Business travel,Eco,1972,4,4,4,4,1,3,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +83647,120314,Female,Loyal Customer,31,Business travel,Business,2747,2,4,4,4,2,1,2,2,2,5,3,2,2,2,0,0.0,neutral or dissatisfied +83648,72438,Female,Loyal Customer,43,Business travel,Business,2014,5,5,5,5,3,5,4,5,5,5,5,5,5,5,10,23.0,satisfied +83649,59050,Male,Loyal Customer,51,Business travel,Business,1744,2,4,4,4,5,2,2,2,2,2,2,4,2,1,4,25.0,neutral or dissatisfied +83650,23398,Male,Loyal Customer,70,Personal Travel,Eco,483,2,5,2,4,1,2,1,1,1,1,3,2,2,1,0,0.0,neutral or dissatisfied +83651,84779,Female,Loyal Customer,16,Business travel,Business,547,5,5,5,5,4,4,4,4,4,4,5,3,5,4,2,0.0,satisfied +83652,111392,Male,Loyal Customer,54,Personal Travel,Eco,1111,1,5,1,3,4,1,4,4,4,4,5,4,5,4,12,14.0,neutral or dissatisfied +83653,103420,Male,Loyal Customer,41,Personal Travel,Eco,237,4,4,0,2,2,0,1,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +83654,117695,Female,Loyal Customer,44,Personal Travel,Eco,2075,2,3,2,4,3,5,2,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +83655,99401,Female,Loyal Customer,48,Business travel,Business,2625,1,1,1,1,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +83656,91094,Female,Loyal Customer,41,Personal Travel,Eco,444,4,5,3,2,4,3,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +83657,7821,Female,disloyal Customer,30,Business travel,Eco,710,3,3,3,1,3,3,4,3,1,3,2,1,2,3,56,58.0,neutral or dissatisfied +83658,119934,Female,Loyal Customer,40,Business travel,Business,2782,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +83659,37590,Male,disloyal Customer,37,Business travel,Eco,718,3,3,3,3,1,3,1,1,4,5,3,1,4,1,11,8.0,neutral or dissatisfied +83660,64603,Female,disloyal Customer,26,Business travel,Business,551,4,4,4,2,3,4,3,3,3,4,4,3,4,3,13,2.0,satisfied +83661,74604,Male,Loyal Customer,59,Business travel,Business,1464,1,1,1,1,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +83662,16884,Female,Loyal Customer,27,Business travel,Business,3896,1,1,1,1,4,4,4,4,5,1,4,1,5,4,0,0.0,satisfied +83663,34265,Male,disloyal Customer,24,Business travel,Eco,280,3,4,3,3,4,3,1,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +83664,10309,Male,Loyal Customer,49,Business travel,Business,308,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +83665,30975,Female,Loyal Customer,24,Business travel,Business,1476,5,5,5,5,5,5,5,5,1,1,3,5,3,5,3,2.0,satisfied +83666,39886,Male,Loyal Customer,68,Personal Travel,Eco,272,1,3,1,3,4,1,4,4,3,5,2,2,3,4,0,0.0,neutral or dissatisfied +83667,46997,Male,Loyal Customer,31,Business travel,Eco Plus,846,3,4,4,4,3,3,3,3,4,2,3,4,4,3,16,32.0,neutral or dissatisfied +83668,22079,Male,Loyal Customer,56,Business travel,Business,3472,1,1,5,1,2,5,4,5,5,5,5,3,5,4,94,95.0,satisfied +83669,10780,Male,disloyal Customer,34,Business travel,Eco,316,3,2,3,3,4,3,4,4,4,4,3,2,3,4,46,41.0,neutral or dissatisfied +83670,98458,Male,Loyal Customer,29,Business travel,Business,210,4,1,1,1,2,2,4,2,2,3,3,3,4,2,0,0.0,neutral or dissatisfied +83671,23855,Male,Loyal Customer,31,Business travel,Business,522,3,1,1,1,3,3,3,3,3,5,3,2,3,3,7,36.0,neutral or dissatisfied +83672,36067,Female,Loyal Customer,38,Business travel,Eco,399,5,3,3,3,5,5,5,5,4,3,3,5,1,5,0,0.0,satisfied +83673,62409,Male,Loyal Customer,53,Business travel,Business,2704,5,5,5,5,2,3,4,4,4,4,4,5,4,4,0,0.0,satisfied +83674,68021,Male,Loyal Customer,32,Personal Travel,Eco,304,3,5,3,3,3,3,2,3,5,5,4,3,5,3,0,4.0,neutral or dissatisfied +83675,25660,Male,Loyal Customer,30,Business travel,Business,1741,5,5,5,5,4,4,4,4,5,5,2,2,3,4,0,0.0,satisfied +83676,36945,Male,Loyal Customer,22,Business travel,Business,2168,1,3,3,3,1,1,1,1,3,3,3,1,4,1,26,36.0,neutral or dissatisfied +83677,2428,Male,Loyal Customer,17,Personal Travel,Eco,604,5,4,5,2,5,5,2,5,5,3,5,4,4,5,0,0.0,satisfied +83678,101874,Female,Loyal Customer,61,Personal Travel,Eco,1747,3,4,3,4,5,4,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +83679,107351,Male,disloyal Customer,24,Business travel,Eco,632,3,0,3,3,2,3,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +83680,91672,Male,Loyal Customer,47,Business travel,Business,1796,1,1,1,1,4,5,5,2,2,2,2,4,2,5,0,2.0,satisfied +83681,116110,Female,Loyal Customer,36,Personal Travel,Eco,446,4,4,4,1,2,4,2,2,3,5,4,3,5,2,47,42.0,neutral or dissatisfied +83682,26584,Male,Loyal Customer,30,Business travel,Business,2957,1,1,1,1,5,4,5,5,5,1,4,1,5,5,0,0.0,satisfied +83683,71543,Female,disloyal Customer,25,Business travel,Business,1197,3,0,3,2,5,3,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +83684,121860,Female,Loyal Customer,50,Business travel,Business,366,3,3,3,3,5,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +83685,77338,Female,Loyal Customer,23,Business travel,Business,626,2,2,3,2,2,2,2,2,4,2,3,3,3,2,2,0.0,neutral or dissatisfied +83686,118033,Female,Loyal Customer,42,Business travel,Business,1792,1,1,1,1,3,5,5,4,4,4,4,5,4,3,5,0.0,satisfied +83687,60888,Male,Loyal Customer,7,Personal Travel,Eco,1062,2,5,2,2,4,2,4,4,5,3,4,3,5,4,51,36.0,neutral or dissatisfied +83688,2291,Female,disloyal Customer,25,Business travel,Eco,691,4,4,4,4,5,4,5,5,4,4,3,4,3,5,14,13.0,neutral or dissatisfied +83689,29531,Male,Loyal Customer,46,Personal Travel,Business,2552,3,3,3,3,3,5,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +83690,108757,Female,Loyal Customer,45,Business travel,Business,2452,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,5.0,satisfied +83691,54509,Male,disloyal Customer,15,Business travel,Eco,925,2,2,2,3,2,2,1,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +83692,26477,Male,Loyal Customer,33,Business travel,Eco Plus,919,4,3,3,3,4,4,4,4,1,5,4,5,4,4,39,22.0,satisfied +83693,80050,Male,Loyal Customer,48,Personal Travel,Eco,1069,4,5,4,3,4,4,2,4,2,3,1,4,4,4,17,0.0,satisfied +83694,23187,Male,Loyal Customer,20,Personal Travel,Eco,646,3,4,3,4,4,3,5,4,2,2,4,2,3,4,72,76.0,neutral or dissatisfied +83695,106631,Female,Loyal Customer,39,Business travel,Eco,306,1,4,4,4,1,1,1,1,3,5,3,1,3,1,0,7.0,neutral or dissatisfied +83696,58265,Male,disloyal Customer,37,Business travel,Business,413,2,2,2,4,4,2,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +83697,55459,Female,disloyal Customer,23,Business travel,Eco,1266,2,1,1,2,2,1,2,2,3,4,4,5,5,2,0,2.0,neutral or dissatisfied +83698,88652,Female,Loyal Customer,52,Personal Travel,Eco,545,4,5,4,3,2,2,5,3,3,4,3,3,3,2,0,0.0,satisfied +83699,113618,Male,Loyal Customer,18,Personal Travel,Eco,223,2,5,2,2,5,2,4,5,3,3,5,4,5,5,0,7.0,neutral or dissatisfied +83700,93119,Male,Loyal Customer,40,Personal Travel,Business,1066,3,5,3,1,3,4,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +83701,51105,Female,Loyal Customer,30,Personal Travel,Eco,86,3,4,3,3,1,3,1,1,3,4,4,4,4,1,10,3.0,neutral or dissatisfied +83702,50488,Male,disloyal Customer,18,Business travel,Eco,262,5,4,5,4,4,5,4,4,3,5,3,5,1,4,0,0.0,satisfied +83703,98858,Male,Loyal Customer,39,Business travel,Business,1751,5,5,4,5,4,4,5,5,5,5,5,3,5,3,2,0.0,satisfied +83704,80418,Female,Loyal Customer,49,Business travel,Business,2248,5,5,5,5,5,3,5,4,4,4,4,3,4,5,56,61.0,satisfied +83705,92184,Female,Loyal Customer,38,Business travel,Eco,1979,1,0,0,3,4,0,4,4,3,1,3,4,3,4,13,6.0,neutral or dissatisfied +83706,17982,Male,disloyal Customer,39,Business travel,Business,332,2,2,2,4,5,2,3,5,1,4,3,3,3,5,4,0.0,neutral or dissatisfied +83707,83268,Female,Loyal Customer,25,Business travel,Business,2079,2,3,3,3,2,2,2,2,1,2,2,1,3,2,0,6.0,neutral or dissatisfied +83708,86898,Male,disloyal Customer,22,Business travel,Eco,352,3,5,3,3,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +83709,64740,Female,Loyal Customer,35,Business travel,Business,224,3,4,4,4,4,3,4,3,3,3,3,2,3,3,0,5.0,neutral or dissatisfied +83710,83194,Female,Loyal Customer,37,Business travel,Business,2664,3,3,4,3,3,4,4,4,4,5,4,4,4,3,0,8.0,satisfied +83711,102437,Male,Loyal Customer,57,Personal Travel,Eco,258,3,4,3,3,5,3,5,5,3,3,1,3,3,5,15,3.0,neutral or dissatisfied +83712,32002,Female,Loyal Customer,67,Personal Travel,Business,101,3,4,3,2,4,5,4,2,2,3,2,3,2,4,0,4.0,neutral or dissatisfied +83713,5186,Female,Loyal Customer,53,Business travel,Business,295,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +83714,63697,Male,disloyal Customer,63,Business travel,Eco,453,0,0,0,4,4,0,4,4,1,2,4,5,2,4,21,0.0,satisfied +83715,60030,Female,Loyal Customer,31,Personal Travel,Eco,1085,2,4,2,1,1,2,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +83716,53077,Female,Loyal Customer,32,Business travel,Eco Plus,1190,3,3,3,3,3,2,3,3,1,4,4,1,4,3,1,0.0,neutral or dissatisfied +83717,126421,Male,Loyal Customer,51,Business travel,Business,3983,5,5,4,5,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +83718,35568,Male,Loyal Customer,60,Business travel,Eco Plus,1076,5,3,2,2,5,5,5,5,4,3,2,4,3,5,0,0.0,satisfied +83719,74388,Female,Loyal Customer,59,Business travel,Business,1464,2,2,2,2,4,4,4,4,3,4,5,4,5,4,151,145.0,satisfied +83720,40130,Male,Loyal Customer,29,Personal Travel,Eco,422,2,1,2,3,3,2,5,3,3,2,2,2,4,3,0,3.0,neutral or dissatisfied +83721,15276,Female,Loyal Customer,60,Business travel,Eco,501,5,4,4,4,5,4,5,5,5,5,5,2,5,1,0,0.0,satisfied +83722,92846,Female,disloyal Customer,42,Business travel,Eco Plus,1587,3,3,3,3,5,3,5,5,2,1,3,3,4,5,0,0.0,neutral or dissatisfied +83723,7790,Male,disloyal Customer,35,Business travel,Business,710,4,4,4,4,2,4,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +83724,110049,Female,Loyal Customer,55,Business travel,Business,3636,2,2,2,2,3,3,5,5,5,5,5,1,5,4,0,0.0,satisfied +83725,91360,Female,Loyal Customer,45,Personal Travel,Eco Plus,223,2,1,2,3,4,2,3,2,2,2,2,2,2,2,0,5.0,neutral or dissatisfied +83726,127960,Male,disloyal Customer,72,Business travel,Eco,1332,1,1,1,4,2,1,2,2,4,2,3,2,4,2,21,13.0,neutral or dissatisfied +83727,99371,Male,Loyal Customer,36,Business travel,Eco Plus,409,2,3,4,3,2,2,2,2,1,5,3,1,4,2,36,26.0,neutral or dissatisfied +83728,36312,Male,Loyal Customer,24,Business travel,Business,3319,2,2,2,2,1,1,2,1,4,5,4,3,4,1,7,4.0,neutral or dissatisfied +83729,101293,Male,Loyal Customer,63,Personal Travel,Eco,763,1,3,1,5,5,1,4,5,5,2,4,2,4,5,0,0.0,neutral or dissatisfied +83730,26209,Male,disloyal Customer,16,Business travel,Eco,404,2,3,2,3,3,2,3,3,4,2,5,5,3,3,2,5.0,neutral or dissatisfied +83731,36641,Male,Loyal Customer,27,Personal Travel,Eco,1237,5,5,5,2,4,5,3,4,5,4,4,3,4,4,24,10.0,satisfied +83732,58113,Male,Loyal Customer,43,Personal Travel,Eco,612,2,3,3,5,1,3,1,1,1,1,3,4,5,1,0,0.0,neutral or dissatisfied +83733,77233,Male,disloyal Customer,48,Business travel,Business,1590,4,4,4,3,3,4,3,3,5,2,4,3,4,3,10,0.0,satisfied +83734,91103,Female,Loyal Customer,55,Personal Travel,Eco,594,4,2,5,4,2,4,4,1,1,5,1,1,1,4,0,3.0,neutral or dissatisfied +83735,49754,Male,Loyal Customer,40,Business travel,Business,266,3,3,3,3,2,5,3,4,4,4,4,4,4,5,19,0.0,satisfied +83736,66559,Female,Loyal Customer,22,Personal Travel,Eco,328,1,1,1,3,1,1,1,1,4,3,3,4,4,1,5,14.0,neutral or dissatisfied +83737,15996,Male,Loyal Customer,28,Business travel,Business,3630,4,1,1,1,4,4,4,4,4,1,4,3,3,4,0,6.0,neutral or dissatisfied +83738,126838,Male,disloyal Customer,46,Business travel,Business,2125,4,4,4,5,5,4,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +83739,47889,Female,disloyal Customer,25,Business travel,Eco,451,1,2,1,4,3,1,3,3,4,5,4,3,3,3,0,4.0,neutral or dissatisfied +83740,52235,Female,Loyal Customer,49,Business travel,Business,2957,2,2,2,2,4,2,5,2,2,2,2,1,2,4,0,0.0,satisfied +83741,73471,Female,Loyal Customer,47,Personal Travel,Eco,1120,2,2,2,3,2,4,2,2,4,4,4,2,3,2,1592,1584.0,neutral or dissatisfied +83742,115355,Female,Loyal Customer,41,Business travel,Business,2046,5,5,5,5,5,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +83743,112035,Male,Loyal Customer,54,Business travel,Business,1123,5,5,5,5,2,5,5,5,5,5,5,3,5,4,7,9.0,satisfied +83744,75744,Male,Loyal Customer,45,Business travel,Business,2455,2,1,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +83745,8427,Male,disloyal Customer,36,Business travel,Eco,462,2,3,2,2,2,2,2,2,1,1,3,3,2,2,0,1.0,neutral or dissatisfied +83746,66637,Male,disloyal Customer,36,Business travel,Business,802,3,3,3,1,3,3,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +83747,122873,Male,Loyal Customer,9,Personal Travel,Eco,226,4,2,4,3,4,4,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +83748,123033,Female,disloyal Customer,38,Business travel,Business,328,4,4,4,2,2,4,2,2,4,2,4,4,5,2,0,0.0,satisfied +83749,68219,Male,Loyal Customer,27,Business travel,Business,631,2,3,2,2,5,4,5,5,5,3,5,4,4,5,0,0.0,satisfied +83750,18677,Male,Loyal Customer,34,Personal Travel,Eco,190,1,2,1,2,3,1,3,3,2,3,2,3,1,3,38,37.0,neutral or dissatisfied +83751,95322,Female,Loyal Customer,69,Personal Travel,Eco,239,4,4,4,4,2,5,5,1,1,4,1,5,1,4,3,3.0,neutral or dissatisfied +83752,36247,Female,Loyal Customer,41,Business travel,Business,2205,1,1,1,1,2,4,5,4,4,5,4,1,4,5,43,50.0,satisfied +83753,50303,Male,Loyal Customer,59,Business travel,Business,89,2,3,3,3,4,4,4,4,4,4,2,4,4,4,0,0.0,neutral or dissatisfied +83754,25010,Female,Loyal Customer,48,Business travel,Business,907,4,4,4,4,3,2,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +83755,61770,Female,Loyal Customer,9,Personal Travel,Eco,1379,3,3,3,4,3,3,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +83756,121534,Male,Loyal Customer,40,Business travel,Business,3246,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +83757,51338,Male,Loyal Customer,33,Business travel,Eco Plus,262,3,4,4,4,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +83758,18201,Female,Loyal Customer,52,Business travel,Eco,179,4,4,4,4,1,5,2,4,4,4,4,1,4,4,35,,satisfied +83759,123937,Female,Loyal Customer,22,Personal Travel,Eco,544,2,1,2,1,2,2,2,2,4,2,2,4,1,2,0,0.0,neutral or dissatisfied +83760,1884,Female,Loyal Customer,23,Business travel,Eco Plus,931,2,1,2,1,2,2,3,2,1,1,4,2,4,2,20,21.0,neutral or dissatisfied +83761,97407,Female,disloyal Customer,28,Business travel,Business,587,3,3,3,3,5,3,5,5,4,5,4,3,4,5,16,20.0,neutral or dissatisfied +83762,124469,Female,Loyal Customer,27,Personal Travel,Eco,980,2,4,2,4,1,2,1,1,1,1,3,4,3,1,0,9.0,neutral or dissatisfied +83763,74418,Male,Loyal Customer,50,Business travel,Business,1431,5,5,5,5,5,5,5,4,4,4,4,5,4,5,33,36.0,satisfied +83764,106065,Female,Loyal Customer,56,Business travel,Business,302,3,3,4,3,2,4,5,5,5,4,5,4,5,5,4,0.0,satisfied +83765,87421,Female,Loyal Customer,59,Personal Travel,Eco,425,3,4,3,4,3,5,4,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +83766,109266,Female,Loyal Customer,19,Personal Travel,Eco Plus,793,2,4,2,3,1,2,1,1,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +83767,113996,Male,Loyal Customer,59,Business travel,Business,2427,4,5,5,5,3,4,4,4,4,4,4,3,4,1,15,15.0,neutral or dissatisfied +83768,61634,Male,Loyal Customer,32,Business travel,Business,1464,2,2,2,2,4,4,4,4,5,4,4,5,4,4,8,6.0,satisfied +83769,51568,Female,Loyal Customer,41,Business travel,Eco,261,4,4,4,4,4,4,4,4,3,1,2,5,1,4,0,0.0,satisfied +83770,69873,Male,Loyal Customer,31,Business travel,Business,1055,5,5,5,5,5,5,5,5,5,5,4,4,5,5,96,81.0,satisfied +83771,123403,Female,Loyal Customer,40,Business travel,Business,1337,5,5,2,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +83772,21438,Female,disloyal Customer,34,Business travel,Eco,306,1,4,2,3,2,2,2,2,2,3,4,1,4,2,37,39.0,neutral or dissatisfied +83773,20221,Female,Loyal Customer,37,Business travel,Business,228,2,2,2,2,1,3,2,5,5,5,5,4,5,4,0,0.0,satisfied +83774,80936,Female,Loyal Customer,18,Personal Travel,Eco,341,2,5,2,4,4,2,4,4,4,3,5,3,4,4,1,0.0,neutral or dissatisfied +83775,102874,Female,Loyal Customer,54,Business travel,Business,2705,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +83776,44943,Female,Loyal Customer,43,Business travel,Business,397,1,1,1,1,3,4,5,4,4,4,4,5,4,1,0,0.0,satisfied +83777,5490,Male,Loyal Customer,32,Business travel,Eco,910,1,1,1,1,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +83778,93242,Male,Loyal Customer,40,Business travel,Business,2330,3,3,3,3,5,5,4,4,4,4,4,4,4,3,11,7.0,satisfied +83779,1888,Male,Loyal Customer,54,Business travel,Business,285,5,5,5,5,4,5,4,4,4,4,4,4,4,5,5,2.0,satisfied +83780,8126,Male,Loyal Customer,34,Business travel,Business,1796,3,4,4,4,4,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +83781,40144,Male,Loyal Customer,32,Business travel,Business,2432,4,4,4,4,3,3,3,3,3,2,1,4,1,3,0,0.0,satisfied +83782,65965,Female,Loyal Customer,32,Business travel,Business,1372,4,2,2,2,4,4,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +83783,129861,Female,Loyal Customer,30,Business travel,Business,337,2,2,2,2,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +83784,100675,Female,disloyal Customer,18,Business travel,Eco,889,3,3,3,2,5,3,4,5,3,2,3,3,2,5,98,98.0,neutral or dissatisfied +83785,23629,Female,Loyal Customer,51,Business travel,Eco,793,5,5,5,5,4,3,3,5,5,5,5,5,5,4,8,3.0,satisfied +83786,105743,Female,disloyal Customer,9,Business travel,Eco,842,1,1,1,4,3,1,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +83787,128044,Female,Loyal Customer,48,Personal Travel,Eco Plus,1440,3,1,3,2,2,3,2,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +83788,119324,Female,Loyal Customer,59,Personal Travel,Eco,214,3,2,3,2,3,3,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +83789,93962,Female,Loyal Customer,41,Business travel,Business,1218,3,3,3,3,4,4,4,4,4,4,4,4,4,3,5,0.0,satisfied +83790,99416,Male,Loyal Customer,51,Business travel,Eco,337,1,5,5,5,1,1,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +83791,35047,Male,Loyal Customer,41,Business travel,Business,3494,1,1,1,1,5,5,5,4,2,4,5,5,4,5,501,500.0,satisfied +83792,15598,Female,Loyal Customer,54,Business travel,Business,2386,3,5,5,5,1,2,2,3,3,3,3,4,3,1,20,8.0,neutral or dissatisfied +83793,87229,Female,Loyal Customer,47,Business travel,Business,2134,1,1,1,1,5,5,5,5,5,5,5,3,5,5,4,0.0,satisfied +83794,117741,Female,Loyal Customer,11,Personal Travel,Eco,935,5,5,5,3,4,5,4,4,3,4,1,4,1,4,0,0.0,satisfied +83795,54246,Male,disloyal Customer,21,Business travel,Eco,1222,4,4,4,3,3,4,3,3,5,2,1,2,2,3,19,24.0,satisfied +83796,103622,Female,Loyal Customer,44,Business travel,Business,405,5,5,5,5,2,5,4,3,3,3,3,4,3,3,32,32.0,satisfied +83797,30474,Male,disloyal Customer,22,Business travel,Eco,377,4,0,4,3,2,4,2,2,4,1,3,5,2,2,0,0.0,neutral or dissatisfied +83798,28261,Male,Loyal Customer,40,Personal Travel,Eco,1542,4,4,3,4,3,3,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +83799,47029,Male,Loyal Customer,44,Business travel,Business,2835,1,1,1,1,2,3,3,5,5,5,5,3,5,2,0,0.0,satisfied +83800,111519,Male,Loyal Customer,44,Personal Travel,Eco,391,4,2,4,3,5,4,5,5,1,3,3,2,4,5,24,7.0,neutral or dissatisfied +83801,79379,Male,disloyal Customer,23,Business travel,Business,502,0,0,0,4,5,0,5,5,5,5,4,3,5,5,44,26.0,satisfied +83802,65954,Female,Loyal Customer,29,Business travel,Business,1372,3,3,3,3,5,5,5,5,4,5,4,4,4,5,0,0.0,satisfied +83803,66160,Male,Loyal Customer,57,Business travel,Business,1999,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +83804,44593,Male,Loyal Customer,13,Personal Travel,Eco,157,3,5,3,1,4,3,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +83805,85318,Female,Loyal Customer,48,Personal Travel,Eco,696,2,4,2,3,2,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +83806,19962,Female,Loyal Customer,55,Personal Travel,Eco Plus,315,1,5,1,2,5,5,5,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +83807,105261,Female,Loyal Customer,47,Business travel,Business,2106,5,5,5,5,1,2,2,5,5,4,5,1,5,4,1,0.0,neutral or dissatisfied +83808,26771,Female,Loyal Customer,31,Business travel,Eco Plus,859,4,3,3,3,4,4,4,4,4,2,1,3,3,4,0,6.0,satisfied +83809,108442,Female,Loyal Customer,42,Business travel,Business,1444,2,1,1,1,5,2,3,2,2,2,2,2,2,1,12,11.0,neutral or dissatisfied +83810,60640,Female,Loyal Customer,40,Business travel,Business,1620,3,3,3,3,4,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +83811,23341,Female,Loyal Customer,15,Personal Travel,Eco,456,3,1,3,4,1,3,1,1,1,3,4,3,3,1,67,62.0,neutral or dissatisfied +83812,94102,Male,Loyal Customer,70,Personal Travel,Business,239,3,4,3,4,3,5,4,4,4,3,4,5,4,4,17,14.0,neutral or dissatisfied +83813,62979,Male,Loyal Customer,50,Business travel,Business,853,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +83814,10422,Male,Loyal Customer,58,Business travel,Business,2479,1,1,2,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +83815,127585,Male,Loyal Customer,32,Business travel,Business,1773,2,2,2,2,5,5,5,5,4,4,3,4,5,5,0,0.0,satisfied +83816,79801,Female,Loyal Customer,45,Business travel,Business,950,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +83817,19639,Male,Loyal Customer,37,Personal Travel,Eco,642,1,4,1,4,2,1,2,2,3,2,4,4,3,2,69,52.0,neutral or dissatisfied +83818,84765,Female,Loyal Customer,56,Business travel,Business,3026,3,3,3,3,3,4,4,5,5,5,5,5,5,4,11,0.0,satisfied +83819,41552,Male,Loyal Customer,24,Business travel,Business,1504,1,1,1,1,1,1,1,1,4,1,3,2,3,1,0,0.0,neutral or dissatisfied +83820,117145,Male,Loyal Customer,37,Personal Travel,Eco,646,4,1,4,3,2,4,2,2,3,2,4,3,4,2,38,29.0,satisfied +83821,125374,Female,Loyal Customer,43,Personal Travel,Business,1440,1,4,1,5,2,5,4,2,2,1,4,3,2,3,0,27.0,neutral or dissatisfied +83822,90788,Male,disloyal Customer,37,Business travel,Eco,404,1,3,1,4,3,1,3,3,3,3,3,2,3,3,20,16.0,neutral or dissatisfied +83823,68754,Male,disloyal Customer,28,Business travel,Business,861,3,3,3,1,2,3,2,2,5,5,5,4,5,2,0,2.0,neutral or dissatisfied +83824,13941,Male,Loyal Customer,32,Business travel,Eco,192,4,3,3,3,4,3,4,4,1,2,3,3,3,4,7,0.0,neutral or dissatisfied +83825,76412,Male,disloyal Customer,34,Business travel,Eco,405,3,2,2,4,4,2,4,4,2,3,4,3,3,4,5,0.0,neutral or dissatisfied +83826,19106,Male,Loyal Customer,37,Business travel,Eco,323,3,5,5,5,3,4,3,3,5,2,3,3,5,3,0,23.0,satisfied +83827,112637,Female,disloyal Customer,24,Business travel,Eco,602,3,4,4,4,4,4,4,4,4,3,4,2,4,4,9,1.0,neutral or dissatisfied +83828,78294,Female,Loyal Customer,16,Business travel,Business,1598,2,2,2,2,5,5,5,5,4,3,5,2,2,5,0,3.0,satisfied +83829,91752,Male,Loyal Customer,51,Business travel,Business,588,2,1,1,1,2,4,3,2,2,2,2,4,2,1,3,0.0,neutral or dissatisfied +83830,34835,Female,Loyal Customer,36,Business travel,Eco Plus,209,3,5,5,5,3,3,3,3,2,1,3,2,3,3,0,19.0,neutral or dissatisfied +83831,87009,Male,Loyal Customer,42,Personal Travel,Eco,907,2,4,2,1,4,2,4,4,4,3,4,4,5,4,0,7.0,neutral or dissatisfied +83832,111288,Male,Loyal Customer,29,Personal Travel,Eco,459,3,5,3,3,3,3,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +83833,59729,Female,Loyal Customer,22,Personal Travel,Eco Plus,854,0,4,0,4,5,0,5,5,3,5,4,3,5,5,0,1.0,satisfied +83834,70829,Male,Loyal Customer,49,Business travel,Business,1511,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +83835,121628,Male,Loyal Customer,11,Personal Travel,Eco,912,1,5,1,3,5,1,5,5,4,3,4,4,5,5,1,5.0,neutral or dissatisfied +83836,11966,Male,Loyal Customer,50,Business travel,Business,643,4,4,4,4,4,4,4,4,4,4,4,5,4,4,11,2.0,satisfied +83837,128864,Male,disloyal Customer,28,Business travel,Business,2454,3,3,3,4,3,4,4,2,2,2,3,4,2,4,10,34.0,neutral or dissatisfied +83838,103722,Female,Loyal Customer,33,Personal Travel,Eco,251,2,4,2,4,4,2,4,4,3,4,5,3,5,4,14,22.0,neutral or dissatisfied +83839,113998,Female,disloyal Customer,37,Business travel,Eco,228,1,3,1,4,2,1,2,2,2,3,4,2,3,2,0,0.0,neutral or dissatisfied +83840,53011,Female,Loyal Customer,27,Business travel,Eco,1190,5,1,1,1,5,5,5,5,1,1,5,5,5,5,203,171.0,satisfied +83841,47151,Female,Loyal Customer,23,Business travel,Eco,954,5,3,3,3,5,4,3,5,1,3,1,2,2,5,19,18.0,satisfied +83842,89149,Male,disloyal Customer,50,Business travel,Eco,419,4,3,4,3,3,4,3,3,3,2,4,1,4,3,0,2.0,neutral or dissatisfied +83843,78339,Female,Loyal Customer,54,Business travel,Business,1547,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +83844,68019,Male,Loyal Customer,71,Business travel,Eco,280,4,2,2,2,3,4,3,3,4,3,4,1,2,3,0,0.0,satisfied +83845,123219,Female,Loyal Customer,42,Personal Travel,Eco,650,3,3,3,3,5,3,3,5,5,3,4,2,5,4,7,5.0,neutral or dissatisfied +83846,7570,Female,Loyal Customer,39,Business travel,Business,2369,3,3,3,3,4,5,4,4,4,4,4,4,4,5,24,22.0,satisfied +83847,83997,Male,Loyal Customer,37,Personal Travel,Eco,373,4,2,1,2,2,1,1,2,3,4,3,1,2,2,0,0.0,neutral or dissatisfied +83848,60904,Male,disloyal Customer,22,Business travel,Eco,589,3,4,2,4,4,2,4,4,3,4,4,3,5,4,68,61.0,neutral or dissatisfied +83849,128975,Male,Loyal Customer,39,Personal Travel,Eco,414,5,4,5,5,5,5,4,5,1,4,5,4,3,5,0,0.0,satisfied +83850,7435,Male,Loyal Customer,46,Personal Travel,Eco,522,2,5,2,5,3,2,3,3,4,4,4,5,4,3,2,0.0,neutral or dissatisfied +83851,950,Male,disloyal Customer,36,Business travel,Business,354,2,2,2,1,1,2,1,1,3,1,2,1,1,1,0,0.0,neutral or dissatisfied +83852,121894,Male,Loyal Customer,64,Personal Travel,Eco,366,3,5,3,2,1,3,1,1,5,1,1,3,4,1,2,0.0,neutral or dissatisfied +83853,38414,Female,Loyal Customer,35,Business travel,Business,965,5,5,5,5,4,4,1,4,4,4,4,5,4,1,0,0.0,satisfied +83854,113118,Female,Loyal Customer,67,Personal Travel,Eco,479,3,1,3,2,3,1,1,1,1,3,1,1,1,1,7,0.0,neutral or dissatisfied +83855,26611,Male,Loyal Customer,36,Business travel,Business,404,2,3,3,3,4,2,3,2,2,2,2,1,2,3,12,6.0,neutral or dissatisfied +83856,3764,Female,Loyal Customer,55,Business travel,Business,1999,4,4,4,4,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +83857,57392,Male,disloyal Customer,20,Business travel,Eco,472,4,2,4,3,1,4,1,1,1,2,4,2,4,1,0,5.0,neutral or dissatisfied +83858,69359,Female,Loyal Customer,53,Business travel,Business,3632,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +83859,92318,Female,disloyal Customer,48,Business travel,Business,1222,4,4,4,4,4,4,4,5,4,5,4,4,4,4,10,20.0,satisfied +83860,78439,Male,Loyal Customer,66,Business travel,Eco,666,4,1,1,1,4,4,4,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +83861,78064,Female,Loyal Customer,49,Personal Travel,Eco,332,4,1,4,2,3,2,2,5,5,4,5,3,5,1,0,6.0,neutral or dissatisfied +83862,95652,Male,Loyal Customer,49,Business travel,Business,928,2,2,2,2,5,4,5,5,5,5,5,3,5,5,78,67.0,satisfied +83863,118553,Male,disloyal Customer,37,Business travel,Business,621,1,1,1,1,5,1,5,5,4,4,5,4,4,5,0,10.0,neutral or dissatisfied +83864,109204,Female,disloyal Customer,30,Business travel,Eco,793,2,2,2,3,5,2,5,5,4,1,4,1,4,5,0,7.0,neutral or dissatisfied +83865,94347,Female,disloyal Customer,39,Business travel,Business,148,5,5,5,3,4,5,4,4,4,3,5,4,5,4,0,0.0,satisfied +83866,11456,Female,Loyal Customer,44,Business travel,Eco Plus,216,1,2,2,2,5,3,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +83867,89930,Female,disloyal Customer,21,Business travel,Eco,1279,3,3,3,1,4,3,4,4,3,4,3,3,1,4,36,21.0,neutral or dissatisfied +83868,125997,Female,Loyal Customer,21,Personal Travel,Business,328,2,4,2,4,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +83869,117092,Male,Loyal Customer,59,Business travel,Business,338,4,4,4,4,5,5,4,5,5,5,5,1,5,4,4,0.0,satisfied +83870,51614,Male,Loyal Customer,44,Business travel,Business,2155,4,5,4,4,1,1,2,5,5,5,5,2,5,4,0,0.0,satisfied +83871,57957,Male,Loyal Customer,47,Business travel,Business,1911,2,2,2,2,3,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +83872,81908,Male,Loyal Customer,41,Personal Travel,Eco,680,2,5,2,5,4,2,4,4,5,1,1,1,4,4,0,0.0,neutral or dissatisfied +83873,43776,Female,Loyal Customer,47,Personal Travel,Eco,386,3,5,3,4,4,4,5,4,4,3,4,5,4,4,0,6.0,neutral or dissatisfied +83874,98298,Male,Loyal Customer,14,Personal Travel,Eco,1136,2,3,2,4,3,2,5,3,4,5,3,2,4,3,21,0.0,neutral or dissatisfied +83875,14337,Female,Loyal Customer,50,Personal Travel,Eco,395,2,2,2,2,4,2,3,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +83876,16429,Male,Loyal Customer,51,Business travel,Eco,529,2,4,4,4,2,2,2,4,1,5,4,2,5,2,139,146.0,satisfied +83877,103927,Male,Loyal Customer,48,Business travel,Business,3673,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +83878,5567,Female,Loyal Customer,12,Personal Travel,Eco,588,5,5,5,3,1,5,1,1,3,3,5,4,5,1,85,93.0,satisfied +83879,45122,Female,Loyal Customer,10,Personal Travel,Eco,177,3,4,3,1,3,3,3,3,4,5,4,3,5,3,6,4.0,neutral or dissatisfied +83880,9177,Female,Loyal Customer,52,Personal Travel,Eco,416,2,3,2,2,2,1,1,4,5,2,3,1,5,1,266,,neutral or dissatisfied +83881,47254,Male,Loyal Customer,39,Business travel,Business,590,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +83882,57700,Male,Loyal Customer,16,Personal Travel,Eco,867,5,4,5,1,5,3,3,5,4,5,5,3,3,3,266,324.0,satisfied +83883,5353,Female,Loyal Customer,21,Business travel,Business,733,1,1,1,1,4,4,4,4,5,3,5,5,5,4,24,71.0,satisfied +83884,92595,Female,Loyal Customer,34,Business travel,Business,2158,1,1,1,1,3,5,4,4,4,4,4,5,4,3,50,30.0,satisfied +83885,102997,Female,disloyal Customer,40,Business travel,Business,666,2,2,2,1,3,2,3,3,3,2,5,4,4,3,20,6.0,neutral or dissatisfied +83886,56021,Female,disloyal Customer,22,Business travel,Eco,1277,5,5,5,3,5,1,1,5,3,3,5,1,4,1,0,0.0,satisfied +83887,99139,Female,Loyal Customer,53,Personal Travel,Eco,181,2,4,2,1,1,3,1,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +83888,48827,Female,Loyal Customer,34,Personal Travel,Business,372,2,0,2,2,3,5,5,4,4,2,4,5,4,5,44,42.0,neutral or dissatisfied +83889,6922,Male,Loyal Customer,68,Personal Travel,Eco,265,4,2,4,4,5,4,5,5,4,5,2,2,3,5,0,1.0,neutral or dissatisfied +83890,42766,Female,disloyal Customer,22,Business travel,Eco,493,3,0,3,4,2,3,2,2,4,5,2,5,4,2,0,2.0,neutral or dissatisfied +83891,116360,Male,Loyal Customer,42,Personal Travel,Eco,480,2,5,2,4,2,2,2,2,4,2,3,1,5,2,0,0.0,neutral or dissatisfied +83892,23239,Female,Loyal Customer,62,Personal Travel,Eco,549,3,4,4,2,5,4,5,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +83893,129664,Male,Loyal Customer,40,Business travel,Business,2208,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,2.0,satisfied +83894,31741,Male,Loyal Customer,39,Business travel,Eco Plus,846,4,4,2,4,4,4,4,4,3,2,4,5,1,4,22,12.0,satisfied +83895,43406,Male,Loyal Customer,45,Business travel,Eco Plus,347,5,4,4,4,5,5,5,5,5,5,4,5,2,5,0,0.0,satisfied +83896,38655,Female,Loyal Customer,54,Business travel,Eco,2588,5,3,3,3,3,4,3,5,5,5,5,2,5,1,0,14.0,satisfied +83897,43496,Female,Loyal Customer,33,Personal Travel,Eco,679,2,4,2,1,1,2,1,1,5,2,5,3,5,1,22,15.0,neutral or dissatisfied +83898,19080,Female,Loyal Customer,42,Personal Travel,Eco,642,2,4,2,2,4,4,5,1,1,2,1,5,1,3,38,38.0,neutral or dissatisfied +83899,721,Female,disloyal Customer,44,Business travel,Business,354,2,3,3,3,5,2,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +83900,40247,Male,Loyal Customer,41,Business travel,Business,531,1,5,5,5,4,3,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +83901,84762,Male,Loyal Customer,42,Business travel,Business,547,4,4,4,4,4,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +83902,7012,Male,Loyal Customer,17,Personal Travel,Eco,299,3,5,3,3,1,3,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +83903,3529,Female,Loyal Customer,58,Business travel,Business,1951,3,2,2,2,3,3,3,3,3,3,3,2,3,3,0,3.0,neutral or dissatisfied +83904,29954,Male,disloyal Customer,36,Business travel,Business,213,3,3,3,2,4,3,4,4,3,3,4,4,2,4,0,0.0,neutral or dissatisfied +83905,36712,Male,Loyal Customer,59,Business travel,Eco Plus,1121,3,1,4,4,3,3,3,3,4,5,2,4,3,3,0,0.0,neutral or dissatisfied +83906,74404,Female,Loyal Customer,18,Business travel,Business,1464,3,3,3,3,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +83907,66470,Male,Loyal Customer,40,Business travel,Business,1699,4,1,1,1,2,4,4,4,4,4,4,2,4,2,65,60.0,neutral or dissatisfied +83908,42221,Female,Loyal Customer,42,Business travel,Business,817,3,4,4,4,3,4,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +83909,74005,Female,Loyal Customer,52,Personal Travel,Eco,1972,1,4,0,4,1,3,4,4,4,0,3,1,4,1,14,8.0,neutral or dissatisfied +83910,125552,Male,disloyal Customer,49,Business travel,Business,226,1,1,1,2,1,1,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +83911,110582,Male,Loyal Customer,47,Business travel,Eco,151,4,1,5,1,4,4,4,4,3,2,3,5,1,4,22,19.0,satisfied +83912,41636,Female,Loyal Customer,40,Business travel,Business,1734,5,5,5,5,3,5,4,3,3,2,3,4,3,5,78,77.0,satisfied +83913,68441,Female,Loyal Customer,60,Personal Travel,Eco Plus,1045,2,4,2,3,5,3,3,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +83914,129865,Male,Loyal Customer,38,Business travel,Business,2740,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +83915,75003,Female,disloyal Customer,26,Business travel,Business,236,2,3,2,3,1,2,1,1,3,5,4,1,4,1,1,0.0,neutral or dissatisfied +83916,63513,Female,Loyal Customer,25,Business travel,Business,1009,2,2,4,2,5,5,5,5,5,2,5,4,4,5,1,4.0,satisfied +83917,91620,Male,Loyal Customer,44,Business travel,Business,1340,3,3,3,3,4,4,4,4,4,4,4,3,4,3,5,14.0,satisfied +83918,92340,Male,Loyal Customer,43,Business travel,Business,2556,3,3,5,5,1,1,3,3,3,3,3,1,3,4,33,7.0,neutral or dissatisfied +83919,9254,Female,Loyal Customer,58,Personal Travel,Eco,100,2,5,2,5,2,4,5,5,5,2,5,5,5,5,15,17.0,neutral or dissatisfied +83920,19007,Female,Loyal Customer,40,Business travel,Business,2029,2,2,2,2,5,4,2,4,4,4,4,4,4,2,16,65.0,satisfied +83921,16200,Male,Loyal Customer,48,Personal Travel,Eco,284,4,5,4,1,1,4,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +83922,9108,Male,Loyal Customer,52,Business travel,Business,3132,5,5,5,5,3,4,5,4,4,4,4,5,4,5,0,2.0,satisfied +83923,27039,Female,Loyal Customer,46,Personal Travel,Eco Plus,867,4,3,4,2,4,2,2,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +83924,490,Female,Loyal Customer,51,Business travel,Business,2752,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,2.0,satisfied +83925,33011,Male,Loyal Customer,13,Personal Travel,Eco,163,3,3,0,2,1,0,1,1,1,2,3,1,3,1,0,9.0,neutral or dissatisfied +83926,56631,Female,disloyal Customer,21,Business travel,Eco,1023,1,2,2,4,2,3,3,1,1,3,3,3,2,3,384,402.0,neutral or dissatisfied +83927,116428,Male,Loyal Customer,45,Personal Travel,Eco,447,1,5,1,2,2,1,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +83928,110834,Female,Loyal Customer,36,Business travel,Eco Plus,590,3,1,1,1,3,3,3,3,2,4,4,1,4,3,30,63.0,neutral or dissatisfied +83929,117280,Female,disloyal Customer,23,Business travel,Eco,621,1,0,2,3,2,2,2,2,4,2,4,5,5,2,25,20.0,neutral or dissatisfied +83930,57365,Female,Loyal Customer,51,Personal Travel,Eco,414,4,1,4,2,3,3,3,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +83931,44306,Female,Loyal Customer,38,Business travel,Business,1428,3,1,3,3,3,2,2,4,4,5,4,3,4,4,0,5.0,satisfied +83932,48531,Female,Loyal Customer,68,Business travel,Eco,376,2,4,4,4,4,3,4,2,2,2,2,3,2,2,0,12.0,neutral or dissatisfied +83933,65343,Male,Loyal Customer,39,Business travel,Business,432,2,2,2,2,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +83934,96321,Female,Loyal Customer,36,Business travel,Business,359,2,2,2,2,2,4,5,5,5,5,5,5,5,5,19,14.0,satisfied +83935,38707,Male,Loyal Customer,20,Business travel,Business,2342,3,3,3,3,3,3,3,3,2,2,4,2,2,3,0,0.0,satisfied +83936,48642,Male,disloyal Customer,55,Business travel,Business,89,2,2,2,4,3,2,3,3,3,2,4,3,4,3,0,0.0,satisfied +83937,63085,Male,Loyal Customer,19,Personal Travel,Eco,948,3,1,3,1,5,3,4,5,3,5,3,5,5,5,0,0.0,neutral or dissatisfied +83938,98229,Female,Loyal Customer,58,Business travel,Business,1136,1,1,5,1,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +83939,128173,Male,disloyal Customer,17,Business travel,Eco,1788,4,3,3,2,5,4,5,5,2,4,2,3,1,5,0,2.0,satisfied +83940,50841,Male,Loyal Customer,61,Personal Travel,Eco,109,1,5,1,1,4,1,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +83941,90837,Female,Loyal Customer,43,Business travel,Business,2641,5,5,4,5,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +83942,80891,Female,Loyal Customer,54,Personal Travel,Eco Plus,484,1,2,1,4,5,2,3,2,2,1,2,1,2,3,6,0.0,neutral or dissatisfied +83943,90618,Male,Loyal Customer,60,Business travel,Business,442,2,2,2,2,4,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +83944,102811,Female,Loyal Customer,49,Business travel,Business,342,0,0,0,4,4,5,4,4,4,4,4,5,4,5,22,17.0,satisfied +83945,66046,Female,disloyal Customer,26,Business travel,Business,1055,3,3,3,2,2,3,3,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +83946,94595,Male,disloyal Customer,39,Business travel,Business,189,1,1,1,1,2,1,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +83947,39955,Female,Loyal Customer,60,Personal Travel,Eco,1087,3,0,2,2,3,5,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +83948,3375,Female,Loyal Customer,44,Business travel,Business,1695,2,2,2,2,5,2,3,2,2,3,2,1,2,3,1,16.0,neutral or dissatisfied +83949,49541,Male,disloyal Customer,36,Business travel,Eco,110,1,0,2,2,3,2,3,3,5,2,5,4,5,3,0,5.0,neutral or dissatisfied +83950,108246,Male,Loyal Customer,49,Business travel,Eco,895,3,2,2,2,3,3,3,3,2,3,1,2,1,3,4,16.0,neutral or dissatisfied +83951,60126,Male,Loyal Customer,44,Business travel,Business,3350,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,14.0,satisfied +83952,17805,Female,disloyal Customer,39,Business travel,Business,1042,2,2,2,2,2,4,4,5,5,2,1,4,1,4,194,219.0,neutral or dissatisfied +83953,104469,Female,Loyal Customer,57,Personal Travel,Eco,1123,4,4,4,2,5,5,5,1,1,4,1,3,1,3,6,0.0,neutral or dissatisfied +83954,59932,Male,Loyal Customer,51,Business travel,Business,1542,4,4,4,4,3,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +83955,13134,Female,Loyal Customer,72,Business travel,Business,2083,4,5,5,5,5,4,3,1,1,2,4,1,1,2,0,0.0,neutral or dissatisfied +83956,53784,Female,Loyal Customer,57,Business travel,Business,3363,2,1,1,1,5,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +83957,58281,Male,disloyal Customer,18,Business travel,Eco,678,4,4,4,4,2,4,2,2,2,1,4,2,5,2,0,0.0,neutral or dissatisfied +83958,54615,Female,Loyal Customer,24,Business travel,Business,3377,1,1,1,1,4,4,4,4,2,4,1,2,1,4,7,0.0,satisfied +83959,97491,Male,Loyal Customer,27,Personal Travel,Eco,756,3,5,3,1,5,3,5,5,3,5,4,5,4,5,20,6.0,neutral or dissatisfied +83960,42689,Female,Loyal Customer,42,Business travel,Eco,627,2,2,2,2,5,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +83961,62228,Male,Loyal Customer,61,Personal Travel,Eco,2425,3,5,3,4,2,3,2,2,5,2,4,4,5,2,9,0.0,neutral or dissatisfied +83962,40158,Male,Loyal Customer,66,Personal Travel,Business,531,4,4,4,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +83963,60310,Female,Loyal Customer,33,Personal Travel,Eco,406,4,5,4,2,1,4,1,1,2,1,3,1,4,1,14,37.0,neutral or dissatisfied +83964,36176,Male,Loyal Customer,26,Personal Travel,Eco,1674,3,5,2,3,5,2,5,5,5,4,2,3,1,5,20,17.0,neutral or dissatisfied +83965,107833,Female,Loyal Customer,27,Personal Travel,Eco,349,1,5,4,3,4,4,4,4,3,3,5,3,5,4,26,16.0,neutral or dissatisfied +83966,10856,Male,Loyal Customer,77,Business travel,Business,3379,4,3,3,3,3,4,4,2,2,2,4,3,2,2,8,15.0,neutral or dissatisfied +83967,125654,Female,Loyal Customer,46,Business travel,Business,2230,2,2,2,2,4,4,4,2,2,2,2,5,2,4,0,13.0,satisfied +83968,93104,Male,Loyal Customer,55,Personal Travel,Eco,641,2,5,2,3,1,2,1,1,5,4,4,4,5,1,127,109.0,neutral or dissatisfied +83969,50985,Female,Loyal Customer,32,Personal Travel,Eco,373,2,3,1,1,2,1,5,2,2,2,5,4,5,2,4,0.0,neutral or dissatisfied +83970,53061,Male,Loyal Customer,31,Personal Travel,Eco,1208,3,2,3,3,4,3,1,4,3,4,2,1,3,4,35,8.0,neutral or dissatisfied +83971,32014,Female,disloyal Customer,22,Business travel,Business,101,4,4,4,1,5,4,5,5,3,5,5,2,3,5,0,0.0,satisfied +83972,124446,Female,Loyal Customer,47,Personal Travel,Business,980,3,5,2,1,4,5,5,5,5,2,5,3,5,4,52,39.0,neutral or dissatisfied +83973,56385,Male,Loyal Customer,50,Business travel,Business,1555,0,4,0,2,3,4,5,5,5,5,5,4,5,3,2,0.0,satisfied +83974,90331,Male,disloyal Customer,47,Business travel,Business,406,2,2,2,5,5,2,5,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +83975,127174,Female,Loyal Customer,7,Personal Travel,Eco,338,4,5,4,1,4,4,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +83976,94567,Male,Loyal Customer,29,Business travel,Business,2036,1,1,1,1,5,5,5,5,4,5,5,4,4,5,22,21.0,satisfied +83977,48341,Male,Loyal Customer,37,Business travel,Eco,522,5,1,3,1,5,5,5,5,3,1,3,4,1,5,27,28.0,satisfied +83978,125141,Male,Loyal Customer,34,Personal Travel,Business,1999,3,4,3,4,3,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +83979,103890,Female,Loyal Customer,8,Personal Travel,Eco,979,2,4,2,1,3,2,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +83980,44289,Female,Loyal Customer,28,Business travel,Business,1123,5,5,5,5,4,4,4,4,5,4,4,1,4,4,0,0.0,satisfied +83981,121569,Female,Loyal Customer,29,Business travel,Business,936,3,5,4,4,3,3,3,3,3,3,4,4,4,3,6,12.0,neutral or dissatisfied +83982,47813,Male,Loyal Customer,36,Business travel,Business,462,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,24.0,satisfied +83983,92398,Male,Loyal Customer,48,Business travel,Business,1892,1,1,1,1,2,4,4,3,3,4,3,5,3,4,0,3.0,satisfied +83984,106992,Female,Loyal Customer,49,Personal Travel,Eco,937,2,4,2,4,4,4,3,3,3,2,3,5,3,4,7,0.0,neutral or dissatisfied +83985,18572,Female,Loyal Customer,44,Business travel,Business,1607,1,2,2,2,5,4,4,3,3,3,1,1,3,4,4,0.0,neutral or dissatisfied +83986,125454,Female,disloyal Customer,25,Business travel,Business,2845,4,0,4,3,1,4,1,1,4,3,4,5,5,1,0,0.0,satisfied +83987,92313,Male,Loyal Customer,49,Business travel,Business,2556,1,1,1,1,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +83988,2770,Male,Loyal Customer,40,Personal Travel,Business,765,2,4,2,3,5,5,4,5,5,2,5,4,5,4,64,64.0,neutral or dissatisfied +83989,26699,Female,Loyal Customer,24,Personal Travel,Eco,406,2,5,2,3,4,2,1,4,3,2,4,4,5,4,8,9.0,neutral or dissatisfied +83990,110340,Male,Loyal Customer,49,Business travel,Business,787,4,4,4,4,4,4,4,4,4,4,4,4,4,4,35,34.0,satisfied +83991,61405,Female,Loyal Customer,7,Personal Travel,Eco,679,1,3,1,4,2,1,2,2,2,2,3,4,4,2,43,36.0,neutral or dissatisfied +83992,129390,Female,Loyal Customer,15,Personal Travel,Eco Plus,2454,1,5,1,2,3,1,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +83993,98867,Female,Loyal Customer,60,Personal Travel,Business,991,2,4,2,3,2,5,4,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +83994,5045,Male,Loyal Customer,41,Business travel,Business,2387,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,36.0,satisfied +83995,14687,Female,Loyal Customer,52,Business travel,Eco,192,5,1,1,1,4,1,2,5,5,5,5,1,5,1,0,0.0,satisfied +83996,79831,Female,Loyal Customer,56,Business travel,Business,1035,2,2,2,2,5,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +83997,91371,Female,Loyal Customer,51,Personal Travel,Eco Plus,270,3,0,3,3,3,1,5,1,1,3,4,4,1,1,0,0.0,neutral or dissatisfied +83998,9528,Female,Loyal Customer,64,Business travel,Business,1591,5,5,5,5,3,4,4,5,5,5,5,3,5,4,3,0.0,satisfied +83999,101150,Male,Loyal Customer,26,Business travel,Business,3797,2,2,2,2,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +84000,99616,Female,Loyal Customer,47,Business travel,Business,1622,3,3,3,3,3,4,4,2,2,2,2,4,2,3,2,2.0,satisfied +84001,80960,Male,Loyal Customer,55,Business travel,Business,3784,3,3,3,3,4,5,5,4,4,4,4,3,4,3,47,38.0,satisfied +84002,19018,Male,Loyal Customer,26,Business travel,Eco,871,5,5,5,5,5,5,3,5,3,1,3,1,1,5,21,26.0,satisfied +84003,58069,Female,disloyal Customer,35,Business travel,Business,589,2,2,2,3,1,2,1,1,3,2,4,4,5,1,19,7.0,neutral or dissatisfied +84004,14344,Female,Loyal Customer,11,Personal Travel,Eco,429,2,3,2,4,1,2,1,1,1,5,3,1,4,1,29,28.0,neutral or dissatisfied +84005,86741,Male,disloyal Customer,22,Business travel,Eco,821,4,3,3,3,5,3,5,5,4,1,4,2,3,5,3,0.0,neutral or dissatisfied +84006,72586,Female,disloyal Customer,43,Business travel,Eco,719,3,4,4,4,4,4,4,4,1,1,4,3,3,4,0,25.0,neutral or dissatisfied +84007,6225,Male,Loyal Customer,48,Business travel,Business,1763,3,3,3,3,4,5,4,4,4,4,4,5,4,5,11,3.0,satisfied +84008,67674,Female,Loyal Customer,45,Business travel,Business,1464,1,1,1,1,2,4,5,5,5,5,5,3,5,3,44,61.0,satisfied +84009,7053,Male,Loyal Customer,41,Business travel,Business,157,5,5,5,5,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +84010,35315,Male,Loyal Customer,45,Business travel,Eco,1028,2,2,2,2,2,2,2,2,1,4,3,3,4,2,0,0.0,neutral or dissatisfied +84011,70290,Male,Loyal Customer,17,Business travel,Business,2706,1,2,2,2,1,1,1,1,2,1,3,1,3,1,2,0.0,neutral or dissatisfied +84012,33255,Male,Loyal Customer,21,Business travel,Eco Plus,101,2,4,2,4,2,2,3,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +84013,79052,Male,Loyal Customer,61,Business travel,Eco,377,2,3,3,3,2,2,2,2,3,3,4,4,3,2,28,53.0,neutral or dissatisfied +84014,89710,Female,Loyal Customer,35,Personal Travel,Eco,1076,2,4,1,4,5,1,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +84015,86652,Female,Loyal Customer,10,Personal Travel,Eco,746,2,5,2,2,1,2,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +84016,121766,Female,Loyal Customer,59,Business travel,Business,2649,5,5,5,5,4,4,4,5,5,5,5,4,5,3,14,13.0,satisfied +84017,69181,Male,Loyal Customer,26,Personal Travel,Eco,187,2,5,2,2,1,2,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +84018,86711,Male,Loyal Customer,50,Business travel,Business,1747,1,2,2,2,3,3,2,1,1,1,1,3,1,2,40,33.0,neutral or dissatisfied +84019,52973,Female,Loyal Customer,30,Personal Travel,Eco,2306,3,4,3,2,2,3,1,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +84020,114260,Female,disloyal Customer,23,Business travel,Business,967,2,4,2,3,4,2,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +84021,39467,Female,Loyal Customer,45,Personal Travel,Eco Plus,129,2,4,2,1,2,5,5,3,3,2,3,5,3,4,0,9.0,neutral or dissatisfied +84022,53848,Female,Loyal Customer,49,Business travel,Business,224,4,4,2,4,4,4,2,5,5,5,5,5,5,4,2,4.0,satisfied +84023,10349,Male,Loyal Customer,58,Business travel,Business,316,1,1,1,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +84024,100887,Male,Loyal Customer,44,Business travel,Eco,377,3,4,4,4,3,3,3,3,1,2,3,2,4,3,0,0.0,neutral or dissatisfied +84025,106967,Female,Loyal Customer,54,Business travel,Business,2837,4,4,4,4,3,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +84026,96261,Male,Loyal Customer,51,Personal Travel,Eco,666,4,5,4,3,5,4,3,5,1,4,4,1,5,5,17,3.0,satisfied +84027,80565,Male,Loyal Customer,30,Business travel,Business,1747,1,3,3,3,1,2,1,1,2,5,2,2,3,1,0,0.0,neutral or dissatisfied +84028,39842,Female,Loyal Customer,43,Business travel,Eco,272,4,3,3,3,2,1,4,4,4,4,4,3,4,2,0,0.0,satisfied +84029,16560,Female,Loyal Customer,28,Business travel,Eco,872,3,3,3,3,3,3,3,3,2,4,4,2,3,3,0,16.0,neutral or dissatisfied +84030,91273,Male,Loyal Customer,53,Business travel,Business,2317,1,1,1,1,2,5,4,5,5,4,5,3,5,3,0,1.0,satisfied +84031,55981,Male,Loyal Customer,20,Personal Travel,Eco,1620,2,3,1,3,5,1,5,5,1,3,3,1,3,5,0,0.0,neutral or dissatisfied +84032,3724,Male,Loyal Customer,29,Personal Travel,Eco,431,3,1,3,2,1,3,1,1,4,4,2,2,1,1,0,0.0,neutral or dissatisfied +84033,64507,Female,Loyal Customer,43,Business travel,Business,3172,3,3,3,3,4,5,5,4,4,4,5,4,4,5,7,3.0,satisfied +84034,2726,Male,disloyal Customer,22,Business travel,Business,695,4,0,4,4,3,4,1,3,4,4,5,5,5,3,0,0.0,satisfied +84035,66269,Male,Loyal Customer,40,Personal Travel,Eco,460,3,4,3,4,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +84036,119895,Male,Loyal Customer,39,Business travel,Business,936,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +84037,101178,Male,Loyal Customer,50,Business travel,Eco,690,2,1,1,1,3,2,3,3,1,1,2,5,4,3,36,31.0,satisfied +84038,5152,Male,Loyal Customer,62,Personal Travel,Eco,622,1,5,1,1,5,1,5,5,2,4,4,4,1,5,0,0.0,neutral or dissatisfied +84039,23762,Female,Loyal Customer,38,Business travel,Eco Plus,1048,3,5,5,5,3,5,3,3,2,5,4,1,5,3,44,,satisfied +84040,70224,Male,Loyal Customer,44,Business travel,Eco,1068,2,5,2,5,2,2,2,2,3,5,3,4,4,2,0,7.0,neutral or dissatisfied +84041,128305,Female,Loyal Customer,52,Business travel,Business,1750,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,4.0,satisfied +84042,25320,Female,disloyal Customer,30,Business travel,Eco Plus,432,2,2,2,3,3,2,3,3,4,4,5,4,4,3,2,0.0,neutral or dissatisfied +84043,47094,Male,Loyal Customer,33,Personal Travel,Eco,639,3,5,3,5,4,3,4,4,5,5,4,3,5,4,83,121.0,neutral or dissatisfied +84044,110102,Male,Loyal Customer,45,Business travel,Business,3346,4,4,4,4,2,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +84045,53807,Male,disloyal Customer,27,Business travel,Eco,140,2,4,2,4,5,2,3,5,1,3,2,4,1,5,0,0.0,neutral or dissatisfied +84046,14822,Female,Loyal Customer,28,Personal Travel,Eco,563,4,4,4,3,3,4,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +84047,101821,Female,Loyal Customer,37,Personal Travel,Eco,1521,5,5,5,3,4,5,4,4,3,1,4,5,2,4,0,0.0,satisfied +84048,39242,Female,Loyal Customer,41,Business travel,Business,2948,2,2,2,2,2,2,4,4,4,5,3,4,4,3,67,72.0,satisfied +84049,66267,Male,Loyal Customer,12,Personal Travel,Eco,550,2,4,2,4,2,2,2,2,4,1,3,1,4,2,0,1.0,neutral or dissatisfied +84050,30048,Male,Loyal Customer,39,Business travel,Business,2063,0,3,0,4,5,4,5,3,3,3,3,3,3,5,14,18.0,satisfied +84051,121786,Female,disloyal Customer,34,Business travel,Business,366,1,2,2,1,5,2,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +84052,34977,Female,Loyal Customer,47,Business travel,Eco,273,4,5,5,5,4,1,3,4,4,4,4,4,4,5,10,1.0,satisfied +84053,68997,Male,Loyal Customer,20,Personal Travel,Eco,2422,2,3,2,5,5,2,5,5,4,2,4,3,4,5,1,0.0,neutral or dissatisfied +84054,117006,Female,Loyal Customer,37,Business travel,Business,651,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +84055,98389,Female,Loyal Customer,9,Business travel,Business,2764,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +84056,70116,Male,Loyal Customer,39,Business travel,Business,3081,4,2,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +84057,37285,Female,Loyal Customer,23,Business travel,Eco,1076,5,2,2,2,5,5,4,5,3,2,5,1,4,5,3,4.0,satisfied +84058,73114,Female,disloyal Customer,22,Business travel,Eco,1407,3,3,3,3,5,3,4,5,5,5,3,4,4,5,0,5.0,neutral or dissatisfied +84059,7814,Female,Loyal Customer,58,Business travel,Eco,650,3,3,3,3,2,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +84060,41591,Female,Loyal Customer,29,Personal Travel,Eco,1211,1,3,1,3,2,1,2,2,1,1,4,1,4,2,44,39.0,neutral or dissatisfied +84061,79139,Female,Loyal Customer,17,Business travel,Eco Plus,226,3,4,4,4,3,3,3,3,2,3,3,2,3,3,1,0.0,neutral or dissatisfied +84062,99189,Female,Loyal Customer,9,Personal Travel,Eco,351,3,5,2,4,4,2,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +84063,28654,Male,Loyal Customer,7,Personal Travel,Eco,2614,2,5,2,5,1,2,1,1,5,2,5,4,4,1,5,0.0,neutral or dissatisfied +84064,66448,Female,Loyal Customer,31,Business travel,Business,2254,4,4,5,4,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +84065,37464,Female,Loyal Customer,42,Business travel,Eco,1074,4,5,5,5,1,1,5,4,4,4,4,5,4,4,0,0.0,satisfied +84066,54458,Male,Loyal Customer,43,Personal Travel,Business,925,2,4,2,3,1,2,5,2,2,2,2,1,2,4,63,58.0,neutral or dissatisfied +84067,116207,Female,Loyal Customer,20,Personal Travel,Eco,447,4,5,4,1,1,4,1,1,5,4,4,4,4,1,30,21.0,neutral or dissatisfied +84068,37526,Male,Loyal Customer,39,Business travel,Eco,1076,3,3,3,3,3,3,3,3,2,1,3,2,3,3,30,14.0,neutral or dissatisfied +84069,6157,Female,Loyal Customer,54,Business travel,Business,475,1,1,1,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +84070,22671,Male,disloyal Customer,25,Business travel,Eco,589,3,0,3,1,2,3,2,2,3,3,5,5,5,2,33,39.0,neutral or dissatisfied +84071,117684,Female,Loyal Customer,44,Business travel,Business,1814,3,3,3,3,3,4,5,5,5,5,5,3,5,4,27,11.0,satisfied +84072,68276,Male,Loyal Customer,57,Business travel,Eco Plus,631,2,2,5,2,2,2,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +84073,100586,Male,Loyal Customer,54,Personal Travel,Eco,486,3,0,3,3,2,3,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +84074,38892,Female,Loyal Customer,55,Personal Travel,Business,410,3,5,3,4,5,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +84075,103678,Male,disloyal Customer,27,Business travel,Business,251,0,0,0,2,2,0,2,2,3,4,5,5,4,2,52,62.0,satisfied +84076,92348,Male,disloyal Customer,18,Business travel,Eco,1365,1,1,1,4,2,1,3,2,1,5,4,1,1,2,1,0.0,neutral or dissatisfied +84077,21935,Male,Loyal Customer,38,Business travel,Eco,500,2,2,2,2,2,2,2,2,4,2,3,1,4,2,29,38.0,neutral or dissatisfied +84078,66538,Male,Loyal Customer,57,Business travel,Business,2657,5,5,5,5,4,4,5,5,5,5,5,4,5,3,1,0.0,satisfied +84079,25191,Male,Loyal Customer,51,Personal Travel,Eco,577,3,5,3,2,5,3,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +84080,51919,Female,disloyal Customer,38,Business travel,Eco Plus,507,4,4,4,4,1,4,1,1,2,5,4,5,5,1,0,11.0,neutral or dissatisfied +84081,3819,Female,disloyal Customer,50,Business travel,Business,650,4,4,4,5,4,4,4,4,3,5,4,4,5,4,0,2.0,satisfied +84082,69143,Female,Loyal Customer,44,Business travel,Eco,2248,3,4,4,4,5,3,3,3,3,3,3,2,3,3,3,1.0,neutral or dissatisfied +84083,24217,Female,Loyal Customer,48,Business travel,Eco,170,4,1,1,1,5,4,3,4,4,4,4,2,4,3,0,17.0,neutral or dissatisfied +84084,102360,Female,Loyal Customer,46,Business travel,Eco,258,4,4,4,4,3,4,4,4,4,4,4,2,4,2,17,12.0,neutral or dissatisfied +84085,18396,Female,Loyal Customer,38,Personal Travel,Eco,378,5,4,5,3,2,5,2,2,1,1,4,3,3,2,6,0.0,satisfied +84086,77247,Female,Loyal Customer,59,Business travel,Business,1590,2,2,2,2,2,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +84087,87700,Male,Loyal Customer,34,Personal Travel,Eco,606,1,4,1,4,5,1,5,5,4,5,5,3,5,5,7,14.0,neutral or dissatisfied +84088,40644,Male,Loyal Customer,60,Personal Travel,Eco Plus,391,1,5,1,3,3,1,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +84089,87916,Male,Loyal Customer,60,Business travel,Business,2934,2,2,2,2,3,5,5,4,4,4,4,4,4,4,16,15.0,satisfied +84090,87314,Female,Loyal Customer,52,Business travel,Business,577,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +84091,87968,Male,Loyal Customer,47,Business travel,Business,1798,2,2,2,2,3,4,5,5,5,5,5,3,5,3,2,13.0,satisfied +84092,16811,Male,disloyal Customer,28,Business travel,Eco,645,1,0,1,3,4,1,4,4,2,2,1,5,4,4,22,0.0,neutral or dissatisfied +84093,94116,Female,Loyal Customer,42,Personal Travel,Business,248,3,5,3,1,2,5,5,3,3,3,2,5,3,5,5,1.0,neutral or dissatisfied +84094,107932,Female,Loyal Customer,55,Business travel,Eco,611,4,1,4,4,3,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +84095,12408,Male,Loyal Customer,39,Business travel,Eco,201,3,1,1,1,3,3,3,3,3,5,3,2,4,3,20,24.0,neutral or dissatisfied +84096,7472,Female,Loyal Customer,68,Personal Travel,Eco,510,3,3,3,4,5,4,3,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +84097,113082,Female,disloyal Customer,24,Business travel,Eco,543,2,2,2,3,5,2,2,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +84098,63368,Female,Loyal Customer,14,Personal Travel,Eco,337,4,5,5,2,2,5,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +84099,29232,Male,Loyal Customer,42,Business travel,Business,569,5,5,5,5,2,1,1,5,5,5,5,1,5,1,0,0.0,satisfied +84100,86351,Female,Loyal Customer,28,Business travel,Business,3238,2,2,5,2,4,4,4,4,4,5,5,4,4,4,11,1.0,satisfied +84101,106704,Female,Loyal Customer,8,Personal Travel,Eco,516,2,4,2,2,4,2,4,4,5,3,4,4,4,4,42,44.0,neutral or dissatisfied +84102,102896,Female,Loyal Customer,51,Business travel,Business,1037,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +84103,68559,Female,Loyal Customer,36,Personal Travel,Eco,2136,2,4,2,1,5,2,5,5,5,5,4,5,4,5,1,0.0,neutral or dissatisfied +84104,75410,Female,disloyal Customer,27,Business travel,Eco,2342,1,1,1,3,2,1,2,2,4,3,2,4,3,2,0,2.0,neutral or dissatisfied +84105,75099,Female,Loyal Customer,48,Business travel,Business,1744,2,2,2,2,3,5,4,4,4,4,4,5,4,5,50,63.0,satisfied +84106,42979,Female,Loyal Customer,36,Business travel,Business,3903,1,1,1,1,2,2,3,5,5,5,5,5,5,1,34,26.0,satisfied +84107,125082,Male,Loyal Customer,39,Business travel,Business,2716,5,5,1,5,5,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +84108,55810,Female,Loyal Customer,36,Business travel,Business,1416,1,1,1,1,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +84109,41722,Male,Loyal Customer,24,Business travel,Business,695,2,2,3,2,4,4,4,4,2,2,1,3,5,4,0,6.0,satisfied +84110,111349,Male,Loyal Customer,55,Business travel,Eco,777,1,1,1,1,1,1,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +84111,27529,Male,Loyal Customer,64,Personal Travel,Eco,937,2,3,2,2,1,2,1,1,1,5,3,2,5,1,0,0.0,neutral or dissatisfied +84112,62113,Female,disloyal Customer,37,Business travel,Business,2434,3,3,3,4,3,3,3,3,5,5,5,3,5,3,9,0.0,neutral or dissatisfied +84113,47636,Female,Loyal Customer,42,Business travel,Business,1334,4,4,4,4,5,4,4,4,4,4,4,3,4,1,30,41.0,neutral or dissatisfied +84114,53055,Female,Loyal Customer,21,Personal Travel,Eco,1208,3,2,4,4,4,4,4,4,4,2,4,1,3,4,10,6.0,neutral or dissatisfied +84115,24349,Female,Loyal Customer,38,Personal Travel,Eco,634,3,4,3,4,2,3,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +84116,19727,Male,Loyal Customer,11,Personal Travel,Eco,409,2,5,5,2,2,5,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +84117,99921,Female,Loyal Customer,27,Business travel,Business,764,1,1,1,1,2,2,2,2,5,2,5,5,4,2,22,15.0,satisfied +84118,127653,Female,Loyal Customer,24,Business travel,Eco Plus,1773,1,2,2,2,1,1,2,1,1,3,2,4,4,1,11,7.0,neutral or dissatisfied +84119,99720,Female,disloyal Customer,64,Business travel,Business,255,1,1,1,2,4,1,4,4,1,3,2,2,3,4,1,22.0,neutral or dissatisfied +84120,68070,Male,Loyal Customer,53,Business travel,Business,868,4,4,4,4,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +84121,105143,Female,disloyal Customer,39,Business travel,Business,277,2,2,2,2,2,2,2,2,1,4,2,1,3,2,0,0.0,neutral or dissatisfied +84122,29647,Female,Loyal Customer,40,Personal Travel,Eco,680,1,5,0,1,5,0,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +84123,9759,Female,Loyal Customer,59,Business travel,Business,3385,3,3,3,3,5,4,5,4,4,4,4,4,4,5,21,15.0,satisfied +84124,675,Female,Loyal Customer,46,Business travel,Business,113,3,3,3,3,4,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +84125,76631,Female,disloyal Customer,24,Business travel,Eco,481,3,5,3,2,3,3,3,3,5,2,5,5,2,3,1,0.0,neutral or dissatisfied +84126,98534,Female,Loyal Customer,24,Personal Travel,Eco,402,3,4,3,1,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +84127,87387,Female,Loyal Customer,36,Business travel,Eco,425,3,4,4,4,3,3,3,3,4,2,3,2,2,3,0,0.0,neutral or dissatisfied +84128,12442,Male,Loyal Customer,17,Personal Travel,Eco,383,3,3,3,3,2,3,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +84129,109141,Male,Loyal Customer,12,Personal Travel,Business,616,2,5,2,3,4,2,4,4,3,5,3,3,1,4,56,60.0,neutral or dissatisfied +84130,116102,Male,Loyal Customer,61,Personal Travel,Eco,337,2,2,3,3,3,3,3,2,4,3,4,3,3,3,142,151.0,neutral or dissatisfied +84131,70585,Female,disloyal Customer,12,Business travel,Eco,1258,3,3,3,4,3,3,3,3,2,1,3,2,4,3,27,9.0,neutral or dissatisfied +84132,34151,Male,Loyal Customer,45,Business travel,Eco,1189,4,1,4,4,4,4,4,4,3,2,3,1,5,4,0,0.0,satisfied +84133,15312,Male,Loyal Customer,46,Business travel,Eco,599,4,5,5,5,4,4,4,4,5,5,3,1,1,4,0,0.0,satisfied +84134,14147,Female,Loyal Customer,40,Personal Travel,Eco,528,2,4,3,4,1,3,1,1,2,1,5,5,5,1,0,0.0,neutral or dissatisfied +84135,68960,Female,Loyal Customer,24,Business travel,Business,700,1,1,1,1,3,3,3,3,3,3,4,3,4,3,0,0.0,satisfied +84136,79501,Female,disloyal Customer,24,Business travel,Business,762,0,0,0,1,4,0,4,4,3,3,4,3,5,4,0,0.0,satisfied +84137,2635,Female,Loyal Customer,42,Personal Travel,Eco Plus,181,2,2,2,4,3,3,4,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +84138,66507,Female,Loyal Customer,36,Business travel,Eco,447,2,2,2,2,2,2,2,2,4,4,4,4,3,2,0,0.0,neutral or dissatisfied +84139,18541,Male,Loyal Customer,54,Business travel,Business,1964,4,4,4,4,5,4,3,5,5,5,3,4,5,5,0,0.0,satisfied +84140,115521,Male,Loyal Customer,44,Business travel,Business,371,1,1,1,1,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +84141,92155,Male,Loyal Customer,33,Business travel,Eco Plus,1522,2,4,4,4,2,2,2,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +84142,39761,Female,disloyal Customer,39,Business travel,Business,521,1,1,1,4,1,1,1,1,1,2,5,3,5,1,0,0.0,neutral or dissatisfied +84143,123713,Male,Loyal Customer,28,Personal Travel,Eco,214,3,3,3,3,5,3,5,5,1,4,4,2,4,5,0,0.0,neutral or dissatisfied +84144,102583,Male,Loyal Customer,38,Business travel,Business,1814,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +84145,9990,Male,Loyal Customer,18,Personal Travel,Eco,508,1,4,4,1,2,4,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +84146,97249,Female,Loyal Customer,19,Business travel,Business,393,1,2,2,2,1,1,1,1,3,5,3,4,4,1,96,96.0,neutral or dissatisfied +84147,118652,Male,Loyal Customer,33,Business travel,Business,338,1,2,3,2,1,1,1,1,4,3,3,2,3,1,20,12.0,neutral or dissatisfied +84148,32283,Male,Loyal Customer,44,Business travel,Business,2236,3,3,3,3,2,3,3,5,5,5,5,2,5,4,0,0.0,satisfied +84149,1683,Male,Loyal Customer,41,Business travel,Business,2248,1,1,1,1,5,4,5,4,4,4,4,3,4,5,0,3.0,satisfied +84150,102101,Female,Loyal Customer,39,Business travel,Business,3558,0,0,0,4,2,5,4,3,3,3,5,5,3,5,0,0.0,satisfied +84151,57726,Female,Loyal Customer,40,Business travel,Business,1754,3,1,3,3,4,5,5,5,5,5,5,4,5,4,8,0.0,satisfied +84152,66051,Female,disloyal Customer,26,Business travel,Eco,655,2,1,1,4,5,1,5,5,4,3,4,3,4,5,0,28.0,neutral or dissatisfied +84153,27146,Female,disloyal Customer,25,Business travel,Eco,714,5,4,4,3,4,2,5,3,4,5,5,5,3,5,0,0.0,satisfied +84154,2471,Male,Loyal Customer,63,Personal Travel,Eco,701,3,4,3,3,2,3,2,2,4,2,4,3,4,2,60,57.0,neutral or dissatisfied +84155,22607,Male,Loyal Customer,30,Business travel,Eco,300,2,1,1,1,2,2,2,2,4,4,2,1,2,2,0,4.0,neutral or dissatisfied +84156,55691,Female,Loyal Customer,65,Business travel,Business,927,4,3,3,3,3,2,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +84157,42971,Male,disloyal Customer,27,Business travel,Business,236,2,2,2,3,1,2,1,1,4,4,1,1,3,1,89,78.0,neutral or dissatisfied +84158,123970,Female,Loyal Customer,46,Business travel,Business,3584,3,3,3,3,2,5,4,4,4,4,5,3,4,4,3,0.0,satisfied +84159,45217,Male,Loyal Customer,55,Business travel,Eco,1013,4,5,5,5,4,4,4,4,3,5,1,5,1,4,19,0.0,satisfied +84160,33164,Male,Loyal Customer,24,Personal Travel,Eco,163,2,4,2,2,3,2,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +84161,85387,Male,Loyal Customer,45,Business travel,Business,332,0,0,0,4,4,4,5,3,3,3,3,3,3,4,0,1.0,satisfied +84162,38848,Male,Loyal Customer,26,Personal Travel,Eco Plus,353,2,1,3,3,2,3,2,2,1,5,3,2,4,2,31,32.0,neutral or dissatisfied +84163,29255,Male,Loyal Customer,34,Business travel,Business,1907,1,1,5,1,4,4,1,4,4,4,4,3,4,3,10,0.0,satisfied +84164,69665,Female,Loyal Customer,30,Personal Travel,Eco,569,4,4,4,4,2,4,2,2,5,4,4,4,4,2,74,73.0,satisfied +84165,116852,Male,Loyal Customer,34,Business travel,Business,369,4,4,5,4,3,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +84166,76617,Male,Loyal Customer,60,Business travel,Eco,534,4,1,5,1,4,4,4,4,5,5,2,1,1,4,0,0.0,satisfied +84167,42582,Male,Loyal Customer,70,Personal Travel,Eco,315,1,5,5,5,5,5,5,5,3,4,5,3,5,5,0,6.0,neutral or dissatisfied +84168,124868,Female,Loyal Customer,33,Personal Travel,Eco Plus,280,2,5,2,4,5,2,1,5,2,5,2,4,1,5,0,0.0,neutral or dissatisfied +84169,108073,Male,Loyal Customer,48,Business travel,Business,1105,2,2,2,2,5,5,5,4,4,4,4,4,4,4,18,5.0,satisfied +84170,9017,Male,Loyal Customer,23,Business travel,Business,1809,0,4,0,2,4,4,4,4,5,5,5,4,5,4,2,0.0,satisfied +84171,102,Female,Loyal Customer,51,Business travel,Business,1970,3,3,3,3,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +84172,34391,Female,Loyal Customer,37,Business travel,Business,2899,2,2,2,2,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +84173,127654,Male,Loyal Customer,62,Personal Travel,Eco Plus,1773,0,1,0,3,5,0,5,5,4,1,2,2,2,5,34,19.0,satisfied +84174,78476,Male,disloyal Customer,23,Business travel,Business,526,5,5,5,2,2,5,2,2,4,3,4,3,4,2,0,3.0,satisfied +84175,91818,Male,Loyal Customer,60,Personal Travel,Eco,599,3,3,3,2,2,3,3,2,2,4,5,1,3,2,0,0.0,neutral or dissatisfied +84176,23293,Male,disloyal Customer,23,Business travel,Eco,456,3,5,3,4,4,3,4,4,2,5,4,2,2,4,0,13.0,neutral or dissatisfied +84177,7319,Female,Loyal Customer,59,Personal Travel,Eco Plus,135,3,5,3,4,5,5,4,1,1,3,1,5,1,3,118,113.0,neutral or dissatisfied +84178,31067,Male,Loyal Customer,21,Personal Travel,Eco,775,4,5,4,5,1,4,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +84179,56057,Male,Loyal Customer,66,Personal Travel,Eco,2586,4,4,4,1,4,4,4,5,3,5,5,4,5,4,9,0.0,neutral or dissatisfied +84180,18023,Female,Loyal Customer,64,Business travel,Eco Plus,218,4,3,3,3,2,4,1,4,4,4,4,3,4,3,0,0.0,satisfied +84181,122356,Male,Loyal Customer,58,Business travel,Business,529,3,3,3,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +84182,26270,Female,Loyal Customer,62,Business travel,Eco,859,3,2,2,2,2,3,4,3,3,3,3,2,3,1,28,2.0,neutral or dissatisfied +84183,52546,Male,Loyal Customer,41,Business travel,Business,2336,2,2,2,2,1,2,1,5,5,4,5,5,5,4,0,0.0,satisfied +84184,73805,Male,Loyal Customer,52,Business travel,Eco Plus,192,1,3,3,3,1,1,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +84185,120944,Female,disloyal Customer,11,Business travel,Eco,861,1,1,1,4,5,1,5,5,4,3,3,2,3,5,5,8.0,neutral or dissatisfied +84186,93253,Male,disloyal Customer,18,Business travel,Eco,1180,5,5,5,3,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +84187,79129,Male,Loyal Customer,39,Personal Travel,Eco,356,1,5,1,4,2,1,2,2,1,4,3,1,3,2,6,17.0,neutral or dissatisfied +84188,68989,Female,Loyal Customer,58,Business travel,Business,2422,4,4,4,4,5,5,5,5,4,3,5,5,5,5,7,0.0,satisfied +84189,82255,Male,Loyal Customer,42,Business travel,Business,1481,1,1,1,1,2,5,4,5,5,5,5,5,5,5,3,0.0,satisfied +84190,108865,Female,Loyal Customer,16,Personal Travel,Eco,1947,3,5,3,4,1,3,1,1,5,2,3,4,5,1,6,0.0,neutral or dissatisfied +84191,96223,Male,Loyal Customer,31,Business travel,Business,2603,4,4,4,4,4,4,4,4,1,5,4,3,3,4,2,6.0,neutral or dissatisfied +84192,64954,Female,Loyal Customer,64,Business travel,Business,224,5,5,5,5,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +84193,48763,Male,disloyal Customer,27,Business travel,Business,134,0,0,0,3,3,0,3,3,3,4,4,5,4,3,0,0.0,satisfied +84194,128736,Male,Loyal Customer,29,Business travel,Business,2402,1,1,5,1,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +84195,7589,Female,Loyal Customer,49,Personal Travel,Eco,594,2,3,2,3,3,4,3,2,2,2,2,3,2,1,0,3.0,neutral or dissatisfied +84196,78066,Female,Loyal Customer,68,Personal Travel,Eco,106,2,4,0,3,5,4,4,2,2,0,2,5,2,3,0,0.0,neutral or dissatisfied +84197,116964,Female,disloyal Customer,37,Business travel,Eco,451,1,4,1,4,5,1,5,5,4,4,3,4,4,5,16,6.0,neutral or dissatisfied +84198,6451,Male,Loyal Customer,42,Business travel,Business,3375,2,2,2,2,3,4,5,4,4,4,4,3,4,5,50,40.0,satisfied +84199,67392,Male,Loyal Customer,45,Business travel,Business,3910,1,1,5,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +84200,9915,Male,disloyal Customer,17,Business travel,Business,357,3,2,3,4,5,3,5,5,2,4,4,4,4,5,0,0.0,neutral or dissatisfied +84201,26475,Female,disloyal Customer,35,Business travel,Eco Plus,925,2,2,2,5,5,2,5,5,3,3,1,3,2,5,22,0.0,neutral or dissatisfied +84202,87104,Female,Loyal Customer,69,Personal Travel,Eco,645,2,4,2,2,3,4,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +84203,62733,Female,disloyal Customer,25,Business travel,Business,2615,2,0,3,3,3,1,2,5,3,5,5,2,3,2,2,11.0,neutral or dissatisfied +84204,103143,Male,Loyal Customer,57,Personal Travel,Eco Plus,546,3,2,3,1,1,3,1,1,3,5,2,3,2,1,0,0.0,neutral or dissatisfied +84205,101256,Male,Loyal Customer,33,Business travel,Business,1910,1,1,1,1,4,4,4,4,5,3,5,4,4,4,13,0.0,satisfied +84206,92339,Male,Loyal Customer,56,Business travel,Business,2556,4,4,4,4,4,4,4,3,3,5,4,4,3,4,19,18.0,satisfied +84207,10457,Female,disloyal Customer,61,Business travel,Business,224,3,3,3,1,5,3,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +84208,93539,Male,Loyal Customer,50,Business travel,Eco Plus,1315,3,4,4,4,3,3,3,3,2,4,3,4,4,3,2,0.0,neutral or dissatisfied +84209,77779,Female,Loyal Customer,29,Personal Travel,Eco,874,4,4,4,2,2,4,2,2,4,5,4,5,4,2,0,0.0,satisfied +84210,94618,Female,Loyal Customer,52,Business travel,Business,2609,2,3,2,2,4,4,5,4,4,4,4,3,4,5,2,7.0,satisfied +84211,102290,Male,Loyal Customer,43,Business travel,Business,1542,4,4,4,4,4,4,5,5,5,5,5,4,5,5,0,3.0,satisfied +84212,16457,Female,Loyal Customer,65,Personal Travel,Eco,445,2,1,2,2,1,2,2,2,2,2,2,1,2,1,3,0.0,neutral or dissatisfied +84213,21867,Female,Loyal Customer,22,Business travel,Business,500,1,1,1,1,5,5,5,5,5,4,2,4,5,5,0,0.0,satisfied +84214,66904,Male,Loyal Customer,20,Personal Travel,Business,1102,4,4,3,3,5,3,5,5,1,1,4,3,4,5,0,0.0,satisfied +84215,26529,Female,Loyal Customer,27,Business travel,Eco,1105,4,3,3,3,4,5,4,4,5,4,5,3,3,4,0,0.0,satisfied +84216,29896,Female,Loyal Customer,43,Business travel,Business,3487,4,4,4,4,1,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +84217,124050,Male,Loyal Customer,40,Business travel,Business,1905,1,2,2,2,5,2,2,1,1,1,1,4,1,2,10,14.0,neutral or dissatisfied +84218,22793,Female,disloyal Customer,29,Business travel,Eco,170,2,3,2,3,4,2,1,4,2,3,3,1,3,4,0,12.0,neutral or dissatisfied +84219,58625,Male,Loyal Customer,55,Business travel,Business,3086,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +84220,38541,Male,Loyal Customer,36,Business travel,Eco,2586,4,5,5,5,4,4,4,4,2,3,3,5,1,4,6,0.0,satisfied +84221,112323,Male,Loyal Customer,37,Business travel,Business,3987,4,4,4,4,4,4,5,2,2,2,2,5,2,5,20,0.0,satisfied +84222,121740,Female,Loyal Customer,58,Personal Travel,Eco,1475,4,5,4,1,4,3,5,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +84223,28330,Male,Loyal Customer,41,Business travel,Business,3392,3,3,3,3,3,3,4,3,3,3,3,2,3,3,2,17.0,neutral or dissatisfied +84224,125927,Female,Loyal Customer,11,Personal Travel,Eco,993,3,5,3,2,3,3,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +84225,105014,Male,Loyal Customer,48,Business travel,Business,1502,3,5,5,5,5,3,4,3,3,3,3,3,3,1,6,2.0,neutral or dissatisfied +84226,4507,Male,Loyal Customer,11,Personal Travel,Eco,435,2,3,2,4,1,2,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +84227,6569,Female,Loyal Customer,29,Business travel,Eco,607,3,2,2,2,3,3,3,3,3,4,4,3,3,3,0,0.0,neutral or dissatisfied +84228,126609,Male,Loyal Customer,46,Personal Travel,Eco,1337,2,5,2,2,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +84229,72033,Female,Loyal Customer,27,Personal Travel,Eco,3784,2,4,2,4,2,2,2,4,5,5,4,2,3,2,0,0.0,neutral or dissatisfied +84230,43960,Female,Loyal Customer,14,Personal Travel,Eco Plus,473,1,4,1,4,5,1,5,5,2,1,4,4,3,5,1,0.0,neutral or dissatisfied +84231,57331,Female,disloyal Customer,26,Business travel,Eco,414,3,4,3,3,1,3,1,1,2,1,3,4,4,1,43,57.0,neutral or dissatisfied +84232,54483,Female,Loyal Customer,26,Business travel,Business,802,4,4,4,4,5,5,5,5,3,2,1,5,5,5,3,0.0,satisfied +84233,45943,Female,Loyal Customer,14,Personal Travel,Eco,809,4,2,4,4,3,4,3,3,1,5,3,3,3,3,13,32.0,neutral or dissatisfied +84234,30489,Male,Loyal Customer,33,Business travel,Business,604,5,5,5,5,5,5,5,5,3,2,4,3,1,5,1,37.0,satisfied +84235,2231,Male,Loyal Customer,66,Personal Travel,Eco,642,4,4,3,1,4,3,4,4,5,2,4,4,4,4,59,59.0,neutral or dissatisfied +84236,113316,Female,Loyal Customer,41,Business travel,Business,3277,3,5,3,3,5,4,4,3,3,3,3,3,3,5,87,84.0,satisfied +84237,127352,Male,Loyal Customer,26,Personal Travel,Eco,507,3,3,3,3,5,3,5,5,3,3,3,1,4,5,4,4.0,neutral or dissatisfied +84238,75153,Female,Loyal Customer,30,Business travel,Business,1846,4,4,4,4,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +84239,18212,Female,Loyal Customer,30,Business travel,Eco,179,0,0,0,1,5,0,5,5,1,1,1,5,5,5,5,15.0,satisfied +84240,67734,Male,disloyal Customer,29,Business travel,Business,1235,4,4,4,4,4,4,2,4,3,5,4,3,4,4,0,5.0,satisfied +84241,123536,Female,Loyal Customer,52,Personal Travel,Eco Plus,2077,2,5,2,5,4,5,5,4,4,2,4,5,4,5,1,0.0,neutral or dissatisfied +84242,44803,Female,disloyal Customer,52,Business travel,Eco,802,3,3,3,2,2,3,2,2,1,1,3,4,3,2,18,21.0,neutral or dissatisfied +84243,73864,Female,Loyal Customer,45,Business travel,Business,2342,2,2,2,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +84244,68715,Male,Loyal Customer,57,Personal Travel,Eco,237,3,4,3,3,1,3,1,1,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +84245,112465,Female,disloyal Customer,22,Business travel,Business,462,5,0,5,2,1,5,1,1,1,2,1,3,5,1,0,0.0,satisfied +84246,51891,Male,Loyal Customer,31,Business travel,Business,3964,1,1,1,1,4,4,4,4,3,1,5,5,4,4,0,0.0,satisfied +84247,79202,Female,disloyal Customer,43,Business travel,Eco,1013,3,2,2,3,5,3,5,5,4,4,3,4,4,5,26,13.0,neutral or dissatisfied +84248,70706,Female,Loyal Customer,41,Business travel,Business,675,3,1,3,3,4,4,4,4,4,4,4,3,4,4,0,3.0,satisfied +84249,123287,Female,Loyal Customer,65,Personal Travel,Eco,507,1,5,1,3,3,4,4,5,5,1,5,3,5,3,0,18.0,neutral or dissatisfied +84250,4730,Male,disloyal Customer,40,Business travel,Business,888,2,2,2,1,1,2,1,1,4,5,4,3,4,1,16,4.0,neutral or dissatisfied +84251,33526,Female,Loyal Customer,19,Business travel,Business,228,4,4,4,4,3,4,3,3,1,3,5,5,3,3,51,42.0,satisfied +84252,27973,Male,Loyal Customer,47,Personal Travel,Eco Plus,1616,2,5,2,1,3,2,3,3,3,5,5,5,4,3,0,20.0,neutral or dissatisfied +84253,109220,Female,Loyal Customer,42,Business travel,Business,1910,3,5,5,5,2,2,1,3,3,4,3,1,3,4,22,13.0,neutral or dissatisfied +84254,72624,Female,Loyal Customer,40,Personal Travel,Eco,1121,3,1,3,3,2,3,5,2,1,5,2,3,2,2,27,24.0,neutral or dissatisfied +84255,49729,Male,Loyal Customer,36,Business travel,Business,1703,1,5,5,5,3,3,3,3,3,3,1,2,3,4,12,6.0,neutral or dissatisfied +84256,24847,Female,Loyal Customer,63,Personal Travel,Eco,991,5,4,5,1,4,4,5,4,4,5,4,5,4,5,0,2.0,satisfied +84257,53937,Male,disloyal Customer,39,Business travel,Eco,507,2,0,2,2,4,2,4,4,4,4,1,2,1,4,2,0.0,neutral or dissatisfied +84258,6841,Female,Loyal Customer,19,Personal Travel,Eco,223,1,2,0,3,5,0,5,5,2,3,2,3,2,5,0,2.0,neutral or dissatisfied +84259,55014,Male,Loyal Customer,53,Business travel,Business,1379,3,3,3,3,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +84260,18932,Male,Loyal Customer,64,Personal Travel,Eco,448,1,5,1,5,5,1,5,5,3,3,4,3,4,5,0,3.0,neutral or dissatisfied +84261,1720,Female,Loyal Customer,48,Business travel,Eco,364,2,1,2,2,4,3,4,2,2,2,2,4,2,3,0,3.0,neutral or dissatisfied +84262,25141,Female,Loyal Customer,68,Personal Travel,Eco,1249,3,5,3,1,5,5,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +84263,97723,Male,disloyal Customer,21,Business travel,Business,587,5,0,5,4,3,5,3,3,5,3,4,3,5,3,0,0.0,satisfied +84264,74204,Female,Loyal Customer,38,Business travel,Eco Plus,641,3,2,2,2,3,3,3,3,3,5,3,4,3,3,45,33.0,neutral or dissatisfied +84265,35843,Female,Loyal Customer,29,Business travel,Eco,1068,4,2,2,2,4,4,4,4,4,3,3,3,2,4,0,0.0,satisfied +84266,32934,Female,Loyal Customer,33,Personal Travel,Eco,102,3,4,0,4,4,0,4,4,5,1,2,1,2,4,0,0.0,neutral or dissatisfied +84267,49056,Male,Loyal Customer,29,Business travel,Business,2290,5,5,5,5,4,4,4,4,4,2,5,3,3,4,40,37.0,satisfied +84268,111648,Male,Loyal Customer,16,Personal Travel,Eco,1290,2,5,2,3,1,2,1,1,4,5,3,3,5,1,22,0.0,neutral or dissatisfied +84269,65629,Male,Loyal Customer,60,Personal Travel,Eco,175,3,5,3,4,2,3,1,2,4,4,2,1,4,2,2,6.0,neutral or dissatisfied +84270,125435,Male,Loyal Customer,54,Personal Travel,Eco,735,2,4,2,4,5,2,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +84271,29631,Female,Loyal Customer,62,Business travel,Eco,1048,5,4,4,4,3,3,2,4,4,5,4,2,4,1,0,0.0,satisfied +84272,34974,Female,Loyal Customer,46,Business travel,Eco,273,4,5,5,5,2,2,1,4,4,4,4,1,4,2,0,0.0,satisfied +84273,59406,Female,Loyal Customer,10,Personal Travel,Eco,2367,4,5,4,3,3,4,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +84274,43965,Female,Loyal Customer,50,Business travel,Business,3926,5,5,5,5,4,2,2,4,4,5,4,3,4,1,0,0.0,satisfied +84275,25819,Male,Loyal Customer,56,Personal Travel,Eco,1747,3,1,3,4,4,3,4,4,3,5,3,1,3,4,20,3.0,neutral or dissatisfied +84276,81992,Male,Loyal Customer,31,Business travel,Business,1535,2,1,1,1,2,2,2,2,1,1,4,4,3,2,24,6.0,neutral or dissatisfied +84277,64936,Male,disloyal Customer,27,Business travel,Eco,190,3,1,3,3,4,3,5,4,3,3,2,3,2,4,47,44.0,neutral or dissatisfied +84278,123300,Male,Loyal Customer,48,Business travel,Business,1710,3,3,3,3,4,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +84279,53284,Male,Loyal Customer,36,Business travel,Business,758,1,1,1,1,3,3,3,5,5,5,5,5,5,3,55,67.0,satisfied +84280,100086,Female,Loyal Customer,60,Business travel,Business,3135,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +84281,15271,Male,Loyal Customer,31,Business travel,Eco,500,0,0,0,5,1,0,1,1,3,4,2,4,1,1,0,0.0,satisfied +84282,96280,Female,Loyal Customer,40,Personal Travel,Eco,546,2,4,3,2,5,3,5,5,2,4,1,2,3,5,33,30.0,neutral or dissatisfied +84283,31061,Male,disloyal Customer,20,Business travel,Eco,862,2,2,2,4,5,2,5,5,1,2,4,4,4,5,33,27.0,neutral or dissatisfied +84284,19172,Female,Loyal Customer,25,Personal Travel,Eco Plus,304,5,4,4,4,5,4,5,5,3,4,4,5,4,5,14,4.0,satisfied +84285,19128,Male,Loyal Customer,21,Personal Travel,Eco,323,3,4,2,3,1,2,4,1,2,3,4,1,4,1,0,28.0,neutral or dissatisfied +84286,75453,Female,Loyal Customer,35,Business travel,Business,2267,3,2,2,2,5,4,4,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +84287,67567,Male,disloyal Customer,36,Business travel,Business,1438,4,3,3,2,1,3,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +84288,57016,Male,Loyal Customer,68,Personal Travel,Eco,2565,1,4,1,3,1,1,1,2,1,3,2,1,5,1,8,0.0,neutral or dissatisfied +84289,68230,Female,Loyal Customer,54,Business travel,Business,631,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +84290,52579,Female,Loyal Customer,43,Business travel,Business,3005,3,3,3,3,1,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +84291,43074,Female,Loyal Customer,37,Personal Travel,Eco,259,4,3,4,2,2,4,2,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +84292,75944,Male,Loyal Customer,56,Business travel,Business,297,0,0,0,1,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +84293,70481,Male,Loyal Customer,60,Business travel,Business,2902,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +84294,75323,Female,Loyal Customer,77,Business travel,Business,2556,2,1,5,5,2,2,2,4,5,2,3,2,1,2,0,2.0,neutral or dissatisfied +84295,59592,Male,Loyal Customer,59,Business travel,Business,2671,2,2,2,2,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +84296,24202,Female,Loyal Customer,55,Business travel,Eco,170,2,2,3,2,5,4,4,1,1,2,1,3,1,1,1,20.0,neutral or dissatisfied +84297,89487,Male,Loyal Customer,15,Business travel,Business,1931,2,2,2,2,2,2,2,2,3,1,2,3,3,2,0,6.0,neutral or dissatisfied +84298,123750,Female,Loyal Customer,69,Personal Travel,Eco Plus,96,4,4,4,3,1,3,4,3,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +84299,6552,Female,Loyal Customer,41,Business travel,Business,607,5,5,1,5,5,4,5,4,4,4,4,4,4,4,51,41.0,satisfied +84300,4699,Male,Loyal Customer,69,Personal Travel,Eco,327,3,0,5,3,2,5,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +84301,98462,Male,Loyal Customer,23,Business travel,Business,2761,3,4,4,4,3,3,3,2,3,3,3,3,1,3,200,204.0,neutral or dissatisfied +84302,42324,Female,Loyal Customer,34,Personal Travel,Eco,784,2,4,2,4,3,2,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +84303,103572,Female,Loyal Customer,49,Business travel,Eco,604,3,4,4,4,3,3,2,4,4,3,4,2,4,1,44,16.0,neutral or dissatisfied +84304,60635,Female,Loyal Customer,45,Business travel,Business,1620,1,1,2,1,3,5,5,5,5,5,5,3,5,5,52,41.0,satisfied +84305,32989,Male,Loyal Customer,7,Personal Travel,Eco,201,2,4,0,1,3,0,3,3,1,2,1,1,5,3,13,10.0,neutral or dissatisfied +84306,119260,Female,Loyal Customer,34,Personal Travel,Business,214,3,5,3,5,4,4,5,3,3,3,3,5,3,3,0,21.0,neutral or dissatisfied +84307,13205,Male,Loyal Customer,17,Personal Travel,Eco Plus,542,0,2,0,3,5,0,5,5,2,5,2,1,2,5,0,0.0,satisfied +84308,126552,Female,Loyal Customer,41,Personal Travel,Eco,644,2,4,2,3,5,2,5,5,2,3,1,1,2,5,0,16.0,neutral or dissatisfied +84309,8254,Male,Loyal Customer,52,Personal Travel,Eco,530,2,5,3,5,1,3,1,1,3,3,1,1,3,1,0,0.0,neutral or dissatisfied +84310,10082,Female,Loyal Customer,49,Business travel,Business,266,4,4,4,4,3,5,4,4,4,4,4,3,4,3,7,0.0,satisfied +84311,110221,Female,Loyal Customer,33,Business travel,Business,2577,2,3,3,3,4,2,2,2,2,2,2,1,2,2,10,20.0,neutral or dissatisfied +84312,42852,Male,Loyal Customer,18,Personal Travel,Eco,328,2,0,2,4,2,2,2,2,3,3,3,4,5,2,0,20.0,neutral or dissatisfied +84313,31603,Male,Loyal Customer,70,Personal Travel,Eco,602,3,4,3,2,4,3,4,4,4,5,4,4,4,4,22,14.0,neutral or dissatisfied +84314,43995,Female,Loyal Customer,40,Business travel,Eco,334,5,5,5,5,5,4,5,5,4,4,3,3,4,5,0,7.0,neutral or dissatisfied +84315,55051,Female,Loyal Customer,43,Business travel,Business,1608,4,4,4,4,3,4,5,4,4,4,4,3,4,5,0,2.0,satisfied +84316,124275,Female,Loyal Customer,61,Business travel,Business,3519,5,5,5,5,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +84317,85257,Female,Loyal Customer,61,Personal Travel,Eco,813,3,2,3,4,1,3,3,5,5,3,5,2,5,4,9,23.0,neutral or dissatisfied +84318,67384,Female,Loyal Customer,56,Business travel,Business,641,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +84319,15123,Female,Loyal Customer,48,Business travel,Business,2734,2,2,2,2,5,3,1,4,4,5,4,1,4,3,0,0.0,satisfied +84320,46983,Male,Loyal Customer,15,Personal Travel,Eco,763,4,4,4,3,5,4,5,5,4,5,5,3,5,5,36,61.0,neutral or dissatisfied +84321,76144,Male,Loyal Customer,21,Business travel,Eco,689,0,1,1,1,0,1,2,0,2,5,3,2,3,0,0,0.0,neutral or dissatisfied +84322,102898,Male,Loyal Customer,7,Personal Travel,Eco,1037,5,5,5,5,2,5,2,2,5,5,4,5,4,2,0,0.0,satisfied +84323,60561,Female,Loyal Customer,54,Business travel,Eco Plus,534,5,3,3,3,2,4,1,5,5,5,5,5,5,2,0,0.0,satisfied +84324,20274,Female,Loyal Customer,16,Personal Travel,Eco,137,3,2,3,3,4,3,4,4,3,4,3,3,3,4,128,131.0,neutral or dissatisfied +84325,13858,Male,disloyal Customer,40,Business travel,Business,578,1,1,1,5,2,1,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +84326,5807,Female,disloyal Customer,26,Business travel,Eco,157,3,3,3,4,3,4,4,3,3,3,4,4,3,4,165,184.0,neutral or dissatisfied +84327,1425,Female,Loyal Customer,33,Business travel,Business,2743,5,5,5,5,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +84328,56626,Male,Loyal Customer,29,Business travel,Business,2540,1,5,5,5,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +84329,87310,Male,Loyal Customer,40,Business travel,Eco Plus,577,2,5,5,5,2,2,2,2,1,2,4,1,4,2,5,9.0,neutral or dissatisfied +84330,65837,Male,Loyal Customer,52,Business travel,Business,1389,4,2,2,2,1,2,2,4,4,4,4,2,4,1,48,19.0,neutral or dissatisfied +84331,79840,Female,Loyal Customer,49,Business travel,Business,3904,1,1,1,1,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +84332,13670,Male,disloyal Customer,21,Business travel,Eco,462,1,0,1,2,2,1,2,2,2,3,4,3,2,2,1,0.0,neutral or dissatisfied +84333,119370,Male,Loyal Customer,44,Business travel,Business,3723,1,1,1,1,3,5,4,4,4,4,4,4,4,4,20,10.0,satisfied +84334,54210,Male,Loyal Customer,43,Business travel,Eco Plus,1400,4,1,1,1,4,4,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +84335,16298,Male,Loyal Customer,19,Personal Travel,Eco Plus,748,2,4,2,3,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +84336,12604,Male,Loyal Customer,31,Personal Travel,Eco,542,3,4,3,5,2,3,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +84337,33787,Male,disloyal Customer,22,Business travel,Eco,588,1,3,1,3,5,1,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +84338,57255,Female,Loyal Customer,39,Business travel,Business,628,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +84339,19764,Male,disloyal Customer,23,Business travel,Eco,462,1,0,2,3,2,5,5,3,4,4,5,5,4,5,131,138.0,neutral or dissatisfied +84340,109591,Female,disloyal Customer,25,Business travel,Eco Plus,920,4,4,4,3,2,4,4,2,4,4,4,2,3,2,56,65.0,neutral or dissatisfied +84341,54638,Female,Loyal Customer,49,Business travel,Business,2302,2,1,1,1,4,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +84342,124918,Female,disloyal Customer,23,Business travel,Eco,728,1,1,1,3,2,1,4,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +84343,82121,Male,Loyal Customer,34,Business travel,Eco Plus,1276,3,1,1,1,3,3,3,3,4,4,4,3,3,3,1,3.0,neutral or dissatisfied +84344,19382,Female,Loyal Customer,26,Business travel,Business,2504,4,4,2,4,5,5,5,5,3,3,4,1,2,5,0,0.0,satisfied +84345,102282,Female,Loyal Customer,25,Business travel,Business,2290,3,2,4,2,3,3,3,3,1,5,4,3,4,3,0,2.0,neutral or dissatisfied +84346,6347,Male,disloyal Customer,41,Business travel,Business,315,5,5,5,5,1,5,2,1,4,4,5,5,4,1,0,6.0,satisfied +84347,71355,Male,disloyal Customer,37,Business travel,Business,258,5,5,5,4,3,5,3,3,3,5,4,4,5,3,1,0.0,satisfied +84348,17706,Male,disloyal Customer,20,Business travel,Eco,311,4,3,4,4,2,4,5,2,3,4,4,1,3,2,6,9.0,neutral or dissatisfied +84349,49927,Female,Loyal Customer,53,Business travel,Business,2257,3,5,5,5,2,3,4,3,3,3,3,2,3,2,30,19.0,neutral or dissatisfied +84350,81247,Female,Loyal Customer,54,Personal Travel,Eco,980,2,4,2,4,3,5,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +84351,15210,Male,Loyal Customer,42,Business travel,Eco,416,5,1,1,1,5,5,5,5,4,4,4,1,2,5,25,33.0,satisfied +84352,60977,Male,Loyal Customer,53,Personal Travel,Eco,888,5,5,5,1,5,5,2,5,5,4,4,3,5,5,3,1.0,satisfied +84353,5444,Female,Loyal Customer,37,Business travel,Business,2428,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +84354,117386,Male,Loyal Customer,52,Business travel,Business,912,1,1,1,1,5,4,5,5,5,5,5,3,5,5,12,10.0,satisfied +84355,39458,Female,Loyal Customer,18,Personal Travel,Eco,129,4,2,4,2,3,4,2,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +84356,11726,Male,disloyal Customer,27,Business travel,Business,395,1,2,2,2,3,2,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +84357,31590,Male,Loyal Customer,41,Business travel,Business,602,2,3,3,3,4,3,4,2,2,2,2,3,2,2,12,7.0,neutral or dissatisfied +84358,44184,Male,Loyal Customer,37,Business travel,Business,157,3,3,3,3,1,2,5,5,5,5,4,3,5,2,0,0.0,satisfied +84359,89563,Female,disloyal Customer,45,Business travel,Business,944,1,1,1,4,2,1,2,2,3,5,5,4,5,2,3,6.0,neutral or dissatisfied +84360,93225,Female,disloyal Customer,24,Business travel,Eco,1460,3,3,3,2,5,3,4,5,4,4,2,4,2,5,6,6.0,neutral or dissatisfied +84361,92211,Male,Loyal Customer,19,Personal Travel,Eco,2079,3,4,3,2,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +84362,91414,Female,Loyal Customer,39,Business travel,Business,1050,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,2.0,satisfied +84363,73737,Female,Loyal Customer,10,Personal Travel,Eco,192,3,5,3,2,2,3,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +84364,60578,Female,Loyal Customer,24,Business travel,Business,1290,2,1,1,1,2,2,2,2,3,3,3,2,3,2,2,0.0,neutral or dissatisfied +84365,19800,Male,Loyal Customer,49,Personal Travel,Eco Plus,667,2,5,2,1,1,2,1,1,4,5,4,4,4,1,68,65.0,neutral or dissatisfied +84366,6828,Male,Loyal Customer,59,Personal Travel,Eco,137,2,4,2,1,5,2,5,5,5,3,4,3,4,5,97,97.0,neutral or dissatisfied +84367,86859,Male,Loyal Customer,56,Personal Travel,Eco,692,3,5,3,3,4,3,5,4,4,5,5,5,4,4,0,2.0,neutral or dissatisfied +84368,79413,Female,Loyal Customer,42,Personal Travel,Eco,502,1,4,1,5,3,5,5,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +84369,129533,Female,Loyal Customer,39,Business travel,Eco,2342,2,4,4,4,2,2,2,2,2,2,2,1,4,2,19,12.0,neutral or dissatisfied +84370,64435,Male,Loyal Customer,60,Business travel,Business,1562,4,4,4,4,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +84371,66222,Female,Loyal Customer,45,Business travel,Business,550,5,5,4,5,2,5,4,4,4,4,4,5,4,3,30,20.0,satisfied +84372,12818,Female,disloyal Customer,25,Business travel,Eco,817,2,2,2,4,4,2,4,4,2,5,4,1,3,4,0,0.0,neutral or dissatisfied +84373,16358,Male,Loyal Customer,56,Business travel,Business,319,4,4,4,4,4,4,2,5,5,5,5,3,5,1,0,0.0,satisfied +84374,33149,Male,Loyal Customer,31,Personal Travel,Eco,163,2,4,2,3,1,2,1,1,3,2,1,2,2,1,0,2.0,neutral or dissatisfied +84375,16512,Male,Loyal Customer,43,Personal Travel,Eco,246,4,1,4,3,3,4,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +84376,54896,Male,Loyal Customer,55,Personal Travel,Eco,862,1,4,1,5,1,1,1,1,5,2,4,2,3,1,4,7.0,neutral or dissatisfied +84377,77565,Female,Loyal Customer,34,Business travel,Business,2961,4,4,4,4,4,4,4,2,2,2,2,5,2,3,23,17.0,satisfied +84378,10619,Female,disloyal Customer,13,Business travel,Eco,517,1,4,1,3,4,1,4,4,5,3,4,3,4,4,14,25.0,neutral or dissatisfied +84379,75544,Male,Loyal Customer,60,Business travel,Business,337,2,2,2,2,2,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +84380,106380,Male,Loyal Customer,39,Business travel,Eco,551,4,4,4,4,4,4,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +84381,91187,Male,Loyal Customer,70,Personal Travel,Eco,250,1,4,1,3,2,1,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +84382,38483,Female,Loyal Customer,26,Business travel,Eco Plus,846,0,3,0,2,1,0,1,1,5,4,2,3,3,1,0,0.0,satisfied +84383,56269,Male,Loyal Customer,33,Personal Travel,Eco,404,2,5,2,1,3,2,3,3,4,5,4,5,5,3,11,4.0,neutral or dissatisfied +84384,103243,Female,Loyal Customer,55,Personal Travel,Eco,409,4,5,4,1,2,4,5,4,4,4,4,1,4,4,48,45.0,neutral or dissatisfied +84385,54208,Male,Loyal Customer,46,Business travel,Eco Plus,1400,5,2,2,2,5,5,5,5,1,3,2,2,4,5,0,0.0,satisfied +84386,116644,Male,Loyal Customer,55,Business travel,Eco Plus,337,3,2,3,3,3,3,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +84387,19831,Female,Loyal Customer,56,Personal Travel,Eco,528,3,5,3,4,5,5,2,5,5,3,3,3,5,2,0,0.0,neutral or dissatisfied +84388,84986,Female,Loyal Customer,41,Business travel,Business,1590,2,2,2,2,4,4,4,1,1,2,1,4,1,5,16,9.0,satisfied +84389,108929,Male,Loyal Customer,26,Personal Travel,Eco,1183,2,4,2,1,4,2,2,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +84390,101200,Female,Loyal Customer,40,Personal Travel,Eco,1090,4,1,4,2,4,4,5,4,4,3,2,2,3,4,48,59.0,neutral or dissatisfied +84391,73663,Female,disloyal Customer,19,Business travel,Eco,204,4,4,4,3,3,4,3,3,4,2,4,2,3,3,0,1.0,neutral or dissatisfied +84392,127869,Male,Loyal Customer,35,Business travel,Business,2141,3,4,4,4,5,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +84393,63777,Female,Loyal Customer,28,Business travel,Business,1721,2,2,2,2,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +84394,108668,Female,Loyal Customer,34,Business travel,Business,2935,3,1,1,1,4,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +84395,72518,Male,Loyal Customer,32,Business travel,Eco,1119,3,1,1,1,3,3,3,3,3,2,3,4,3,3,0,7.0,neutral or dissatisfied +84396,20818,Female,Loyal Customer,30,Business travel,Business,1647,5,5,3,5,5,5,5,5,4,5,1,2,5,5,97,91.0,satisfied +84397,63725,Male,Loyal Customer,19,Business travel,Business,1660,3,2,2,2,3,3,3,3,1,1,3,3,4,3,0,0.0,neutral or dissatisfied +84398,79109,Female,Loyal Customer,29,Personal Travel,Eco,226,4,1,0,2,4,0,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +84399,38293,Female,Loyal Customer,61,Business travel,Eco Plus,650,3,1,1,1,4,3,1,3,3,3,3,5,3,1,0,0.0,satisfied +84400,73862,Male,Loyal Customer,45,Business travel,Eco Plus,1709,3,4,4,4,2,3,2,2,1,1,4,2,3,2,3,5.0,neutral or dissatisfied +84401,109578,Female,Loyal Customer,20,Personal Travel,Eco,861,2,5,2,2,2,2,2,2,5,5,5,4,4,2,27,13.0,neutral or dissatisfied +84402,24620,Female,Loyal Customer,60,Business travel,Business,3335,1,5,5,5,3,3,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +84403,23423,Male,Loyal Customer,55,Business travel,Business,1201,4,4,4,4,4,4,4,1,2,3,3,4,4,4,186,180.0,satisfied +84404,88350,Male,Loyal Customer,31,Business travel,Business,3418,3,2,2,2,3,3,3,3,3,2,2,4,3,3,14,2.0,neutral or dissatisfied +84405,67143,Female,Loyal Customer,37,Business travel,Business,564,1,1,1,1,1,4,4,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +84406,8902,Female,Loyal Customer,54,Business travel,Business,510,3,2,2,2,1,3,2,3,3,3,3,4,3,4,4,0.0,neutral or dissatisfied +84407,124039,Female,Loyal Customer,30,Business travel,Business,2473,0,5,0,3,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +84408,19938,Female,Loyal Customer,65,Personal Travel,Eco,296,4,5,4,5,2,4,5,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +84409,81873,Female,Loyal Customer,18,Personal Travel,Eco,1050,2,4,2,5,5,2,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +84410,30297,Male,Loyal Customer,22,Business travel,Business,1533,3,3,3,3,3,3,3,3,4,2,3,2,4,3,0,7.0,neutral or dissatisfied +84411,59978,Female,Loyal Customer,65,Personal Travel,Eco,997,4,5,4,3,5,5,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +84412,86196,Male,Loyal Customer,39,Business travel,Business,3605,1,1,1,1,4,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +84413,15398,Male,Loyal Customer,41,Business travel,Business,164,5,5,5,5,3,2,4,5,5,5,3,2,5,2,0,0.0,satisfied +84414,38496,Female,Loyal Customer,50,Business travel,Business,2586,5,5,5,5,4,5,1,5,5,5,5,2,5,4,0,0.0,satisfied +84415,51516,Female,Loyal Customer,55,Business travel,Eco,355,4,5,5,5,2,2,5,4,4,4,4,1,4,1,0,0.0,satisfied +84416,33834,Female,Loyal Customer,44,Personal Travel,Business,1698,2,3,3,4,1,1,5,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +84417,35882,Female,Loyal Customer,58,Personal Travel,Eco,937,3,3,4,3,1,3,3,3,3,4,3,4,3,3,106,102.0,neutral or dissatisfied +84418,82011,Female,Loyal Customer,46,Business travel,Eco,1135,3,5,2,5,2,3,3,3,3,3,3,2,3,4,0,7.0,neutral or dissatisfied +84419,16686,Female,disloyal Customer,27,Business travel,Eco Plus,488,2,2,2,4,5,2,5,5,5,4,3,1,2,5,0,0.0,neutral or dissatisfied +84420,38994,Female,disloyal Customer,24,Business travel,Eco,260,2,2,2,4,2,2,2,2,4,3,4,3,4,2,0,6.0,neutral or dissatisfied +84421,11399,Female,disloyal Customer,48,Business travel,Business,295,4,4,4,3,1,4,1,1,5,3,4,4,4,1,24,26.0,satisfied +84422,118188,Male,Loyal Customer,70,Business travel,Business,1444,1,3,5,5,2,3,3,1,1,1,1,1,1,4,79,65.0,neutral or dissatisfied +84423,26841,Male,Loyal Customer,57,Business travel,Business,3490,4,4,4,4,4,1,1,4,4,4,4,3,4,2,0,0.0,satisfied +84424,75181,Male,Loyal Customer,49,Business travel,Business,1726,5,5,5,5,4,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +84425,92337,Female,disloyal Customer,23,Business travel,Eco,1297,1,1,1,3,4,1,4,4,2,1,3,3,4,4,0,0.0,neutral or dissatisfied +84426,13061,Male,Loyal Customer,39,Business travel,Business,1641,1,1,1,1,4,1,1,5,5,5,5,1,5,4,0,0.0,satisfied +84427,87703,Female,Loyal Customer,52,Personal Travel,Eco,606,3,1,3,3,3,3,4,2,2,3,2,3,2,1,69,57.0,neutral or dissatisfied +84428,32714,Female,Loyal Customer,43,Business travel,Business,102,2,3,3,3,2,1,1,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +84429,56647,Male,disloyal Customer,40,Business travel,Eco,665,2,0,2,5,5,2,5,5,4,1,4,3,2,5,8,0.0,neutral or dissatisfied +84430,13687,Female,Loyal Customer,62,Business travel,Business,300,2,2,2,2,2,1,3,4,4,4,4,1,4,4,0,0.0,satisfied +84431,3702,Male,Loyal Customer,44,Personal Travel,Eco,427,2,1,2,3,1,2,1,1,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +84432,42018,Female,disloyal Customer,35,Business travel,Eco,116,2,5,2,3,3,2,3,3,1,4,2,1,3,3,0,1.0,neutral or dissatisfied +84433,36403,Female,Loyal Customer,43,Business travel,Eco,232,4,2,2,2,3,1,2,4,4,4,4,4,4,1,0,0.0,satisfied +84434,10039,Female,Loyal Customer,15,Personal Travel,Eco,630,2,5,2,3,1,2,1,1,5,5,4,5,3,1,0,0.0,neutral or dissatisfied +84435,33897,Female,Loyal Customer,14,Personal Travel,Eco,1504,2,4,2,3,5,2,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +84436,114548,Male,Loyal Customer,18,Personal Travel,Business,372,1,3,1,1,3,1,3,3,1,4,4,3,4,3,8,1.0,neutral or dissatisfied +84437,27174,Male,Loyal Customer,25,Personal Travel,Eco,2677,2,3,3,4,3,4,3,1,2,3,4,3,1,3,0,0.0,neutral or dissatisfied +84438,48760,Male,disloyal Customer,40,Business travel,Business,158,4,4,4,3,2,4,2,2,4,4,4,4,5,2,0,0.0,satisfied +84439,91614,Male,Loyal Customer,50,Business travel,Business,2563,5,5,5,5,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +84440,114802,Female,Loyal Customer,54,Business travel,Business,2159,4,4,4,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +84441,176,Female,Loyal Customer,56,Personal Travel,Eco Plus,227,2,3,2,1,4,3,5,4,4,2,4,1,4,4,0,17.0,neutral or dissatisfied +84442,124769,Female,disloyal Customer,37,Business travel,Business,280,2,2,2,2,3,2,5,3,3,4,5,4,5,3,67,113.0,neutral or dissatisfied +84443,50089,Male,Loyal Customer,53,Business travel,Business,3917,3,3,3,3,5,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +84444,112680,Female,Loyal Customer,43,Business travel,Business,672,4,5,5,5,3,4,4,4,4,4,4,2,4,4,43,29.0,neutral or dissatisfied +84445,100085,Female,Loyal Customer,23,Personal Travel,Eco Plus,220,0,2,0,1,5,0,5,5,3,3,5,5,5,5,0,2.0,satisfied +84446,34892,Female,Loyal Customer,39,Personal Travel,Business,395,3,1,3,4,2,4,3,1,1,3,1,2,1,3,0,0.0,neutral or dissatisfied +84447,121609,Male,Loyal Customer,44,Personal Travel,Eco,936,3,4,2,3,5,2,2,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +84448,42977,Female,Loyal Customer,48,Business travel,Business,236,1,1,1,1,3,3,2,5,5,5,5,5,5,4,0,0.0,satisfied +84449,75848,Male,disloyal Customer,25,Business travel,Eco,803,4,4,4,4,4,4,4,4,2,3,4,4,3,4,0,39.0,neutral or dissatisfied +84450,111088,Female,Loyal Customer,52,Personal Travel,Eco,319,4,1,4,2,5,3,3,4,4,4,4,4,4,1,17,19.0,neutral or dissatisfied +84451,119488,Male,Loyal Customer,51,Business travel,Business,899,4,4,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +84452,58771,Female,Loyal Customer,39,Business travel,Business,2684,4,4,4,4,4,5,5,3,3,3,3,5,3,5,12,0.0,satisfied +84453,77890,Male,Loyal Customer,39,Business travel,Business,3245,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +84454,117412,Male,Loyal Customer,53,Business travel,Business,1136,4,4,4,4,5,4,4,5,5,5,5,3,5,4,0,2.0,satisfied +84455,18376,Female,Loyal Customer,20,Personal Travel,Eco Plus,169,2,5,2,3,1,2,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +84456,72747,Male,Loyal Customer,28,Business travel,Business,806,2,1,2,2,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +84457,29648,Male,Loyal Customer,46,Personal Travel,Eco,909,2,5,2,1,2,2,1,2,5,5,1,3,3,2,0,0.0,neutral or dissatisfied +84458,90782,Female,Loyal Customer,37,Business travel,Business,545,3,2,2,2,5,3,3,3,3,3,3,3,3,2,7,16.0,neutral or dissatisfied +84459,55508,Female,Loyal Customer,56,Business travel,Business,991,1,1,1,1,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +84460,128588,Female,Loyal Customer,38,Business travel,Business,2552,5,5,5,5,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +84461,7792,Female,Loyal Customer,24,Business travel,Business,650,5,5,5,5,4,3,4,4,5,4,5,4,5,4,0,0.0,satisfied +84462,92924,Male,disloyal Customer,54,Business travel,Eco,151,3,2,3,2,3,3,4,3,1,4,2,1,3,3,1,6.0,neutral or dissatisfied +84463,88763,Male,disloyal Customer,42,Business travel,Business,442,4,4,4,1,4,4,4,4,3,5,5,3,4,4,1,10.0,satisfied +84464,99458,Female,Loyal Customer,56,Business travel,Business,283,4,4,4,4,3,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +84465,81984,Female,Loyal Customer,41,Business travel,Eco,1532,1,3,3,3,1,1,1,1,4,4,3,2,4,1,64,129.0,neutral or dissatisfied +84466,28752,Male,Loyal Customer,48,Business travel,Eco,1024,4,3,3,3,4,4,4,4,3,2,1,4,5,4,21,17.0,satisfied +84467,110323,Female,disloyal Customer,25,Business travel,Business,925,5,0,5,3,2,5,2,2,5,3,5,4,5,2,44,39.0,satisfied +84468,125779,Female,Loyal Customer,31,Business travel,Business,3265,5,3,5,5,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +84469,54965,Female,Loyal Customer,39,Business travel,Business,3921,1,2,1,1,4,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +84470,91952,Female,Loyal Customer,41,Personal Travel,Eco,2475,4,3,4,3,1,4,1,1,2,1,4,1,3,1,0,0.0,satisfied +84471,120109,Female,Loyal Customer,25,Business travel,Eco,1576,4,3,3,3,4,1,4,1,4,2,2,4,1,4,200,188.0,neutral or dissatisfied +84472,13980,Male,Loyal Customer,33,Business travel,Eco Plus,153,4,2,1,2,4,4,4,4,2,3,4,3,4,4,0,9.0,neutral or dissatisfied +84473,101726,Male,Loyal Customer,46,Business travel,Business,1216,4,4,4,4,2,5,5,4,4,4,4,4,4,4,20,18.0,satisfied +84474,73965,Female,Loyal Customer,43,Personal Travel,Eco,2342,3,5,3,2,3,4,4,3,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +84475,59984,Female,Loyal Customer,50,Personal Travel,Eco,1023,4,0,5,5,5,4,3,4,4,4,5,3,4,3,368,350.0,neutral or dissatisfied +84476,89560,Male,Loyal Customer,56,Business travel,Business,3352,5,3,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +84477,10014,Male,disloyal Customer,38,Business travel,Business,457,5,5,5,1,1,5,1,1,5,3,5,5,4,1,31,15.0,satisfied +84478,64621,Female,Loyal Customer,54,Business travel,Business,2813,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,4.0,satisfied +84479,4926,Female,Loyal Customer,60,Personal Travel,Eco,1020,4,4,4,4,1,3,4,5,5,4,2,2,5,2,0,0.0,neutral or dissatisfied +84480,57385,Male,Loyal Customer,47,Business travel,Business,3219,1,1,1,1,4,5,4,5,5,5,5,4,5,5,3,38.0,satisfied +84481,106474,Male,Loyal Customer,24,Personal Travel,Eco,1300,3,5,3,5,1,3,1,1,4,5,4,5,5,1,79,59.0,neutral or dissatisfied +84482,25939,Female,disloyal Customer,23,Business travel,Eco Plus,594,2,0,2,2,1,2,4,1,1,1,4,2,2,1,3,0.0,neutral or dissatisfied +84483,114755,Male,disloyal Customer,58,Business travel,Business,337,5,4,4,4,5,5,5,5,4,5,5,5,4,5,0,1.0,satisfied +84484,68829,Female,Loyal Customer,68,Personal Travel,Eco,1995,2,3,2,4,4,3,3,2,2,2,2,2,2,3,16,20.0,neutral or dissatisfied +84485,3852,Male,Loyal Customer,32,Personal Travel,Eco,650,1,1,1,3,4,1,1,4,4,1,2,4,3,4,22,,neutral or dissatisfied +84486,21423,Male,Loyal Customer,49,Business travel,Eco,433,2,2,2,2,2,2,2,2,5,1,1,5,4,2,0,0.0,satisfied +84487,19361,Female,Loyal Customer,46,Personal Travel,Eco,692,3,5,3,4,4,4,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +84488,41044,Female,Loyal Customer,22,Business travel,Business,3659,4,4,4,4,4,4,4,4,3,4,2,3,5,4,0,0.0,satisfied +84489,90551,Male,Loyal Customer,41,Business travel,Business,3199,1,1,1,1,4,5,4,5,5,5,5,5,5,5,8,6.0,satisfied +84490,99030,Female,Loyal Customer,45,Business travel,Business,2033,2,2,2,2,4,4,5,4,4,4,4,3,4,4,44,29.0,satisfied +84491,26044,Female,Loyal Customer,47,Business travel,Eco,432,5,5,5,5,5,2,4,5,5,5,5,1,5,5,1,0.0,satisfied +84492,128014,Female,Loyal Customer,45,Business travel,Business,1440,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +84493,124975,Female,Loyal Customer,44,Business travel,Business,2390,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +84494,110538,Male,Loyal Customer,13,Business travel,Business,3350,3,3,3,3,5,5,5,5,3,5,4,3,4,5,13,0.0,satisfied +84495,97,Female,disloyal Customer,18,Business travel,Eco Plus,215,3,5,3,3,1,3,1,1,1,4,1,2,5,1,0,0.0,neutral or dissatisfied +84496,127575,Male,Loyal Customer,11,Personal Travel,Eco,1670,1,0,1,5,4,1,3,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +84497,109931,Female,Loyal Customer,51,Personal Travel,Eco,1165,1,5,2,4,2,3,5,5,5,2,5,4,5,3,37,13.0,neutral or dissatisfied +84498,105444,Female,Loyal Customer,60,Business travel,Business,3873,5,5,5,5,5,5,5,4,4,4,4,5,4,3,61,47.0,satisfied +84499,47260,Female,Loyal Customer,69,Personal Travel,Business,558,3,4,2,4,3,1,5,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +84500,42504,Male,Loyal Customer,9,Personal Travel,Eco,541,1,3,1,1,4,1,4,4,2,4,5,5,4,4,0,0.0,neutral or dissatisfied +84501,94470,Female,disloyal Customer,30,Business travel,Eco,239,3,2,3,3,1,3,1,1,4,5,3,2,2,1,0,0.0,neutral or dissatisfied +84502,79396,Male,Loyal Customer,34,Business travel,Eco,502,3,2,2,2,3,3,3,3,2,3,3,3,3,3,12,0.0,neutral or dissatisfied +84503,117370,Female,Loyal Customer,51,Personal Travel,Eco,393,5,4,5,1,3,5,5,1,1,5,1,4,1,4,0,0.0,satisfied +84504,43969,Male,Loyal Customer,31,Personal Travel,Eco,596,0,2,0,4,4,0,4,4,1,1,2,4,3,4,0,0.0,satisfied +84505,39656,Female,Loyal Customer,43,Business travel,Eco,310,5,5,5,5,5,4,5,5,5,5,5,5,5,1,7,7.0,satisfied +84506,115135,Male,Loyal Customer,43,Business travel,Business,2836,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +84507,87555,Male,Loyal Customer,70,Personal Travel,Business,432,1,4,1,2,5,2,5,3,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +84508,40056,Male,Loyal Customer,34,Business travel,Eco Plus,866,4,5,5,5,4,4,4,4,1,2,4,2,4,4,0,0.0,satisfied +84509,50949,Male,Loyal Customer,7,Personal Travel,Eco,373,3,5,4,2,5,4,5,5,3,2,1,3,2,5,10,13.0,neutral or dissatisfied +84510,62366,Male,Loyal Customer,34,Personal Travel,Business,2704,3,4,3,4,2,3,4,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +84511,52966,Female,Loyal Customer,12,Personal Travel,Eco,2306,1,5,1,3,1,4,4,3,3,5,4,4,4,4,194,205.0,neutral or dissatisfied +84512,100143,Male,Loyal Customer,22,Business travel,Business,2635,1,5,5,5,1,1,1,1,1,4,4,1,4,1,8,9.0,neutral or dissatisfied +84513,100097,Male,Loyal Customer,54,Business travel,Business,3125,4,4,4,4,5,5,4,4,4,4,4,3,4,4,65,44.0,satisfied +84514,38901,Male,Loyal Customer,36,Business travel,Eco,410,4,1,5,1,4,5,4,4,5,5,4,3,5,4,0,0.0,satisfied +84515,108861,Male,Loyal Customer,61,Personal Travel,Eco,2139,2,4,2,5,3,2,2,3,3,3,5,3,4,3,11,0.0,neutral or dissatisfied +84516,32333,Female,disloyal Customer,22,Business travel,Eco,163,3,5,3,4,4,3,4,4,4,2,5,2,1,4,0,7.0,neutral or dissatisfied +84517,12832,Male,Loyal Customer,66,Business travel,Eco,241,4,1,1,1,4,4,4,4,4,2,3,4,1,4,10,0.0,satisfied +84518,37619,Male,Loyal Customer,51,Personal Travel,Eco,1005,4,4,4,3,5,4,5,5,3,4,1,1,1,5,0,0.0,neutral or dissatisfied +84519,55391,Female,Loyal Customer,63,Personal Travel,Eco,413,4,5,3,3,3,2,2,4,4,5,5,2,4,2,123,150.0,neutral or dissatisfied +84520,115071,Female,Loyal Customer,51,Business travel,Business,2067,3,5,3,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +84521,79844,Male,disloyal Customer,23,Business travel,Eco,1010,2,3,3,4,2,3,2,2,4,5,5,4,4,2,117,94.0,neutral or dissatisfied +84522,2206,Female,Loyal Customer,12,Personal Travel,Eco,685,3,3,3,4,5,3,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +84523,124795,Female,Loyal Customer,61,Business travel,Business,280,1,3,3,3,2,4,3,1,1,1,1,4,1,2,9,45.0,neutral or dissatisfied +84524,116712,Female,disloyal Customer,21,Business travel,Business,371,2,2,2,3,1,2,1,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +84525,54076,Male,Loyal Customer,51,Business travel,Eco,1416,5,4,3,4,5,5,5,5,5,5,4,2,1,5,0,0.0,satisfied +84526,118709,Female,Loyal Customer,43,Personal Travel,Eco,621,2,4,2,2,4,3,4,3,3,2,5,4,3,2,1,0.0,neutral or dissatisfied +84527,24099,Female,Loyal Customer,60,Business travel,Business,2847,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +84528,6847,Female,Loyal Customer,15,Business travel,Eco Plus,122,3,1,1,1,3,3,2,3,3,4,2,1,3,3,0,0.0,neutral or dissatisfied +84529,46202,Male,Loyal Customer,39,Business travel,Business,2901,2,2,2,2,5,5,4,4,4,4,4,4,4,3,2,5.0,satisfied +84530,126149,Female,disloyal Customer,36,Business travel,Eco,650,2,4,3,4,5,3,5,5,4,2,3,1,4,5,0,0.0,neutral or dissatisfied +84531,96291,Male,Loyal Customer,14,Personal Travel,Eco,460,2,5,2,2,2,2,2,2,3,3,5,5,4,2,13,26.0,neutral or dissatisfied +84532,29959,Male,Loyal Customer,28,Business travel,Eco,627,3,1,1,1,3,3,3,3,3,4,2,3,1,3,0,6.0,neutral or dissatisfied +84533,78732,Male,Loyal Customer,43,Business travel,Business,3351,5,5,3,5,5,4,5,4,4,4,4,5,4,5,14,24.0,satisfied +84534,34670,Male,Loyal Customer,59,Personal Travel,Business,264,3,5,3,4,5,5,1,1,1,3,1,1,1,2,0,0.0,neutral or dissatisfied +84535,84132,Female,Loyal Customer,56,Business travel,Business,2606,4,4,4,4,4,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +84536,8865,Female,Loyal Customer,57,Business travel,Business,3521,3,1,3,3,2,4,5,5,5,5,5,3,5,5,1,1.0,satisfied +84537,125663,Male,Loyal Customer,56,Business travel,Business,3574,4,4,3,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +84538,91477,Female,Loyal Customer,28,Personal Travel,Eco,859,2,4,2,1,2,2,3,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +84539,117069,Female,Loyal Customer,36,Business travel,Business,304,4,2,2,2,5,3,4,4,4,4,4,3,4,4,15,7.0,neutral or dissatisfied +84540,11259,Female,Loyal Customer,29,Personal Travel,Eco,247,2,3,2,3,1,2,1,1,2,4,4,2,4,1,10,20.0,neutral or dissatisfied +84541,19441,Female,Loyal Customer,35,Personal Travel,Eco Plus,645,1,5,1,2,5,1,5,5,5,2,5,2,3,5,0,0.0,neutral or dissatisfied +84542,26767,Female,Loyal Customer,42,Business travel,Eco Plus,859,5,3,3,3,4,2,3,4,4,5,4,3,4,2,16,55.0,satisfied +84543,29540,Female,Loyal Customer,48,Business travel,Business,1448,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,7.0,satisfied +84544,24480,Female,Loyal Customer,9,Business travel,Eco,547,2,4,4,4,2,2,3,2,1,5,3,3,4,2,13,11.0,neutral or dissatisfied +84545,44697,Female,disloyal Customer,22,Business travel,Eco,268,4,0,4,2,4,4,2,4,4,1,4,1,3,4,0,0.0,neutral or dissatisfied +84546,103004,Male,Loyal Customer,43,Business travel,Eco,687,4,5,5,5,4,4,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +84547,95615,Female,disloyal Customer,24,Business travel,Eco,822,4,4,4,5,1,4,1,1,3,4,5,5,5,1,0,0.0,satisfied +84548,91240,Male,Loyal Customer,53,Personal Travel,Eco,404,1,2,1,4,4,1,4,4,4,2,3,4,3,4,0,0.0,neutral or dissatisfied +84549,112166,Male,Loyal Customer,50,Business travel,Business,2272,3,3,2,3,3,4,4,5,5,5,5,5,5,1,1,0.0,satisfied +84550,97920,Female,Loyal Customer,38,Business travel,Business,3885,4,4,4,4,3,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +84551,103242,Female,Loyal Customer,60,Personal Travel,Eco,409,2,5,4,4,4,4,4,5,5,4,5,5,5,5,96,87.0,neutral or dissatisfied +84552,113331,Female,Loyal Customer,44,Business travel,Business,414,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +84553,63603,Male,Loyal Customer,46,Business travel,Business,1440,5,5,5,5,2,5,4,4,4,4,4,4,4,5,4,0.0,satisfied +84554,71440,Male,disloyal Customer,39,Business travel,Business,867,2,2,2,2,5,2,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +84555,103426,Male,Loyal Customer,37,Personal Travel,Eco,237,2,5,2,5,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +84556,37411,Female,Loyal Customer,48,Business travel,Eco,1047,5,2,2,2,3,1,5,5,5,5,5,2,5,2,19,5.0,satisfied +84557,129222,Male,Loyal Customer,8,Business travel,Business,1464,5,5,5,5,4,4,4,4,4,3,4,4,4,4,0,0.0,satisfied +84558,34509,Female,disloyal Customer,24,Business travel,Eco,1255,2,2,2,3,5,2,5,5,3,1,4,4,3,5,0,38.0,neutral or dissatisfied +84559,21082,Female,disloyal Customer,37,Business travel,Eco,152,4,4,4,5,4,4,4,4,4,3,5,5,1,4,0,0.0,neutral or dissatisfied +84560,125239,Male,disloyal Customer,21,Business travel,Eco,1149,3,4,4,3,1,4,1,1,2,4,4,2,3,1,15,31.0,neutral or dissatisfied +84561,96053,Male,disloyal Customer,26,Business travel,Eco,1235,1,1,1,2,2,1,2,2,2,1,2,4,3,2,26,24.0,neutral or dissatisfied +84562,93442,Male,Loyal Customer,51,Personal Travel,Eco,605,4,5,4,1,2,4,5,2,4,4,5,3,5,2,38,31.0,satisfied +84563,68694,Female,Loyal Customer,25,Personal Travel,Eco,175,1,4,1,4,1,1,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +84564,18305,Female,Loyal Customer,13,Personal Travel,Eco,813,3,0,4,2,5,4,5,5,3,1,4,1,3,5,0,0.0,neutral or dissatisfied +84565,70232,Male,Loyal Customer,49,Personal Travel,Eco,1068,4,4,4,4,4,4,4,4,1,5,4,4,4,4,24,11.0,neutral or dissatisfied +84566,125365,Female,Loyal Customer,21,Personal Travel,Eco,599,2,4,2,1,1,2,1,1,4,1,1,3,1,1,0,0.0,neutral or dissatisfied +84567,69928,Female,Loyal Customer,27,Business travel,Eco Plus,1514,1,1,1,1,1,1,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +84568,13052,Female,Loyal Customer,9,Personal Travel,Eco Plus,374,4,3,4,4,2,4,2,2,2,4,3,1,3,2,0,51.0,neutral or dissatisfied +84569,119784,Female,Loyal Customer,21,Business travel,Business,3714,2,2,2,2,5,5,5,5,5,2,4,3,5,5,0,0.0,satisfied +84570,94380,Male,Loyal Customer,59,Business travel,Business,189,2,2,2,2,4,5,4,5,5,4,4,4,5,5,3,6.0,satisfied +84571,83180,Male,Loyal Customer,29,Business travel,Business,549,5,5,5,5,5,5,5,5,4,4,4,4,4,5,0,0.0,satisfied +84572,4412,Male,Loyal Customer,45,Personal Travel,Business,762,4,3,4,3,2,4,3,3,3,4,1,1,3,1,0,3.0,neutral or dissatisfied +84573,26206,Male,disloyal Customer,38,Business travel,Eco,404,4,0,5,4,3,5,2,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +84574,106684,Male,Loyal Customer,13,Personal Travel,Eco,451,3,4,4,3,5,4,5,5,3,5,4,4,4,5,60,50.0,neutral or dissatisfied +84575,14096,Female,Loyal Customer,24,Business travel,Business,399,1,1,1,1,5,5,5,5,2,1,3,2,1,5,0,0.0,satisfied +84576,8672,Female,Loyal Customer,42,Business travel,Business,2860,3,3,4,3,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +84577,101688,Female,Loyal Customer,35,Business travel,Eco,1500,3,1,5,1,3,3,3,3,4,5,3,1,3,3,0,0.0,neutral or dissatisfied +84578,32846,Male,Loyal Customer,21,Personal Travel,Eco,163,2,5,2,5,3,2,3,3,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +84579,26275,Male,Loyal Customer,41,Business travel,Eco,459,3,3,3,3,3,3,3,3,1,5,4,1,4,3,7,0.0,satisfied +84580,91804,Male,Loyal Customer,45,Personal Travel,Eco,626,3,3,3,2,2,3,2,2,5,3,4,2,2,2,0,0.0,neutral or dissatisfied +84581,16663,Male,Loyal Customer,54,Business travel,Eco,488,4,4,4,4,4,4,4,4,1,1,1,4,1,4,72,67.0,neutral or dissatisfied +84582,63511,Male,disloyal Customer,22,Business travel,Business,1009,4,0,4,3,2,4,2,2,4,3,5,4,4,2,50,34.0,satisfied +84583,15450,Male,Loyal Customer,58,Business travel,Eco,377,3,1,1,1,3,3,3,3,3,1,3,1,4,3,67,96.0,neutral or dissatisfied +84584,62948,Male,Loyal Customer,52,Business travel,Business,2646,2,2,2,2,5,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +84585,109643,Female,Loyal Customer,23,Business travel,Business,829,2,2,2,2,4,4,4,4,4,3,4,5,4,4,4,1.0,satisfied +84586,23789,Male,Loyal Customer,48,Business travel,Eco,374,4,3,3,3,4,4,4,4,3,1,3,2,2,4,0,0.0,satisfied +84587,123575,Female,Loyal Customer,35,Business travel,Business,1773,2,2,2,2,5,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +84588,97483,Female,Loyal Customer,54,Business travel,Eco,670,2,5,5,5,1,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +84589,843,Female,Loyal Customer,23,Business travel,Business,89,3,2,3,2,3,3,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +84590,99670,Male,Loyal Customer,30,Personal Travel,Eco,1050,1,4,1,2,1,1,1,1,4,4,5,4,5,1,22,0.0,neutral or dissatisfied +84591,51593,Female,disloyal Customer,40,Business travel,Business,261,3,2,2,1,2,2,2,2,3,3,4,1,4,2,0,11.0,neutral or dissatisfied +84592,32870,Male,Loyal Customer,58,Personal Travel,Eco,102,3,3,3,4,1,3,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +84593,80449,Female,disloyal Customer,49,Business travel,Business,1299,4,4,4,4,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +84594,50945,Female,Loyal Customer,55,Personal Travel,Eco,153,4,2,4,3,1,4,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +84595,120717,Female,Loyal Customer,40,Business travel,Business,2875,3,3,3,3,5,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +84596,95042,Female,Loyal Customer,15,Personal Travel,Eco,562,3,4,3,3,5,3,5,5,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +84597,76723,Female,Loyal Customer,49,Business travel,Eco Plus,481,4,5,5,5,4,3,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +84598,122181,Male,Loyal Customer,54,Business travel,Business,1615,2,2,2,2,5,5,5,4,4,5,4,4,4,4,0,4.0,satisfied +84599,91,Female,disloyal Customer,32,Business travel,Business,173,4,4,4,3,4,4,5,4,4,1,4,4,4,4,0,5.0,neutral or dissatisfied +84600,29991,Male,Loyal Customer,51,Business travel,Eco,95,3,1,1,1,3,3,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +84601,106257,Female,Loyal Customer,46,Business travel,Business,1500,3,3,3,3,3,4,4,5,5,5,5,3,5,3,4,0.0,satisfied +84602,49416,Male,Loyal Customer,51,Business travel,Business,2064,3,3,3,3,3,3,1,5,5,5,5,5,5,4,0,10.0,satisfied +84603,35735,Male,Loyal Customer,29,Business travel,Eco Plus,2446,4,4,4,4,4,4,4,1,4,3,3,4,4,4,0,4.0,satisfied +84604,72293,Female,Loyal Customer,26,Personal Travel,Eco,919,1,4,1,4,5,1,5,5,4,4,5,3,5,5,3,13.0,neutral or dissatisfied +84605,120624,Male,Loyal Customer,30,Business travel,Business,280,3,3,3,3,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +84606,1361,Male,Loyal Customer,34,Business travel,Business,134,4,1,1,1,5,3,3,5,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +84607,69740,Female,Loyal Customer,30,Business travel,Business,3711,5,5,5,5,4,3,4,4,5,2,4,3,4,4,0,0.0,satisfied +84608,85133,Male,Loyal Customer,55,Business travel,Business,3005,2,2,2,2,2,5,5,4,4,5,4,3,4,5,0,10.0,satisfied +84609,54593,Male,Loyal Customer,29,Business travel,Business,965,4,4,4,4,5,5,5,5,5,3,4,5,4,5,3,0.0,satisfied +84610,125197,Female,Loyal Customer,52,Business travel,Business,651,2,2,2,2,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +84611,128413,Male,Loyal Customer,39,Business travel,Business,621,4,4,4,4,4,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +84612,94188,Male,Loyal Customer,48,Business travel,Business,3203,2,2,2,2,3,5,5,5,5,5,5,4,5,3,9,0.0,satisfied +84613,18476,Female,Loyal Customer,58,Business travel,Eco,201,5,5,5,5,2,4,1,5,5,5,5,2,5,4,0,0.0,satisfied +84614,84222,Male,disloyal Customer,37,Business travel,Eco,432,2,5,2,1,1,2,1,1,1,1,1,2,5,1,10,0.0,neutral or dissatisfied +84615,32643,Female,Loyal Customer,51,Business travel,Business,2481,2,2,2,2,5,5,1,4,4,4,4,5,4,1,1,3.0,satisfied +84616,91549,Female,disloyal Customer,39,Business travel,Eco,280,2,4,2,2,2,2,2,2,1,3,3,1,5,2,9,0.0,neutral or dissatisfied +84617,97269,Male,Loyal Customer,23,Personal Travel,Eco,296,2,5,2,4,1,2,1,1,3,3,5,3,5,1,18,5.0,neutral or dissatisfied +84618,106985,Female,Loyal Customer,60,Personal Travel,Eco,1036,3,5,3,1,2,4,4,4,4,3,4,4,4,5,7,0.0,neutral or dissatisfied +84619,115827,Male,disloyal Customer,39,Business travel,Eco,337,2,0,2,3,4,2,4,4,1,4,5,3,3,4,0,0.0,neutral or dissatisfied +84620,94650,Male,Loyal Customer,38,Business travel,Business,189,3,2,2,2,2,4,3,1,1,2,3,3,1,1,4,8.0,neutral or dissatisfied +84621,26065,Male,Loyal Customer,28,Business travel,Business,591,4,4,4,4,4,4,4,4,4,5,5,4,4,4,12,6.0,satisfied +84622,112453,Female,Loyal Customer,41,Business travel,Business,3046,3,3,3,3,2,3,5,4,4,4,4,1,4,1,20,20.0,satisfied +84623,57480,Male,Loyal Customer,46,Business travel,Business,680,4,4,4,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +84624,107969,Female,Loyal Customer,59,Business travel,Eco,825,1,4,4,4,3,2,2,1,1,1,1,2,1,2,27,4.0,neutral or dissatisfied +84625,91098,Female,Loyal Customer,18,Personal Travel,Eco,271,3,4,3,2,2,3,3,2,3,4,5,5,4,2,0,2.0,neutral or dissatisfied +84626,79008,Female,Loyal Customer,71,Business travel,Eco,226,1,1,1,1,3,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +84627,13706,Male,Loyal Customer,40,Business travel,Eco Plus,483,3,3,3,3,3,3,3,3,1,4,3,2,3,3,0,0.0,neutral or dissatisfied +84628,40207,Male,Loyal Customer,38,Business travel,Business,347,3,3,3,3,3,1,5,5,5,5,5,5,5,5,0,0.0,satisfied +84629,29054,Male,Loyal Customer,55,Personal Travel,Eco,1050,5,5,5,4,4,5,4,4,3,5,5,4,5,4,0,0.0,satisfied +84630,36499,Female,Loyal Customer,27,Business travel,Eco,1197,5,4,4,4,5,5,5,5,2,4,5,2,3,5,1,0.0,satisfied +84631,52034,Female,Loyal Customer,8,Personal Travel,Eco,328,2,2,2,3,3,2,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +84632,47425,Female,disloyal Customer,23,Business travel,Eco,184,2,2,2,3,4,2,4,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +84633,55819,Female,disloyal Customer,24,Business travel,Eco,1416,2,2,2,3,1,2,1,1,4,5,5,4,5,1,1,18.0,neutral or dissatisfied +84634,106260,Female,Loyal Customer,43,Business travel,Business,1500,5,5,5,5,4,4,5,5,5,5,5,5,5,4,10,0.0,satisfied +84635,128700,Male,Loyal Customer,28,Business travel,Business,1504,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +84636,95614,Male,disloyal Customer,22,Business travel,Eco,670,3,3,3,4,1,3,1,1,2,5,3,1,4,1,15,0.0,neutral or dissatisfied +84637,129489,Male,Loyal Customer,23,Personal Travel,Eco,2704,1,1,1,3,2,1,2,2,1,3,4,4,4,2,0,,neutral or dissatisfied +84638,37020,Female,Loyal Customer,47,Business travel,Eco Plus,814,4,3,5,5,3,4,1,4,4,4,4,4,4,2,0,0.0,satisfied +84639,118427,Female,Loyal Customer,28,Business travel,Business,2129,2,2,2,2,4,3,3,5,5,4,5,3,3,3,139,123.0,satisfied +84640,100685,Male,Loyal Customer,22,Business travel,Business,677,4,4,4,4,5,5,5,5,1,2,2,5,1,5,0,0.0,satisfied +84641,117498,Female,disloyal Customer,26,Business travel,Eco,107,1,2,1,4,3,1,3,3,4,5,3,2,4,3,82,69.0,neutral or dissatisfied +84642,93963,Male,Loyal Customer,37,Business travel,Business,1734,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +84643,30259,Male,Loyal Customer,41,Business travel,Eco,836,5,1,1,1,5,5,5,5,5,1,2,5,5,5,0,0.0,satisfied +84644,26737,Male,Loyal Customer,48,Personal Travel,Eco Plus,581,2,4,2,2,1,2,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +84645,3404,Female,Loyal Customer,55,Business travel,Business,3360,2,2,2,2,2,4,1,5,5,5,5,5,5,3,8,0.0,satisfied +84646,114284,Female,Loyal Customer,69,Personal Travel,Eco,948,2,0,3,1,2,3,4,5,5,3,5,2,5,4,31,8.0,neutral or dissatisfied +84647,45480,Male,Loyal Customer,26,Business travel,Eco,522,0,5,0,4,2,0,3,2,4,3,2,1,3,2,0,0.0,satisfied +84648,2723,Male,Loyal Customer,60,Business travel,Business,2844,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +84649,17573,Female,Loyal Customer,44,Business travel,Business,1034,1,1,1,1,3,3,1,4,4,4,4,4,4,2,0,0.0,satisfied +84650,90896,Female,Loyal Customer,57,Business travel,Business,1956,1,3,3,3,1,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +84651,58343,Male,disloyal Customer,38,Business travel,Eco,296,3,0,3,4,2,3,3,2,5,1,3,5,4,2,0,0.0,neutral or dissatisfied +84652,49022,Female,Loyal Customer,56,Business travel,Eco,199,5,2,2,2,1,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +84653,103325,Male,Loyal Customer,56,Personal Travel,Eco,1371,2,5,2,4,1,2,5,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +84654,103719,Female,Loyal Customer,17,Personal Travel,Eco,251,2,5,2,5,3,2,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +84655,118436,Female,Loyal Customer,43,Business travel,Business,1528,2,2,5,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +84656,117304,Female,disloyal Customer,22,Business travel,Business,304,5,4,4,1,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +84657,39333,Female,Loyal Customer,48,Personal Travel,Eco Plus,67,1,5,1,2,4,5,5,3,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +84658,118812,Female,Loyal Customer,41,Business travel,Business,3457,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +84659,11602,Male,Loyal Customer,39,Personal Travel,Eco,657,4,4,3,2,3,3,3,3,3,5,5,3,5,3,0,0.0,satisfied +84660,129512,Male,Loyal Customer,19,Personal Travel,Eco,1744,1,0,1,3,1,1,1,1,2,3,4,2,4,1,1,0.0,neutral or dissatisfied +84661,80022,Male,Loyal Customer,46,Personal Travel,Eco,1076,1,5,1,3,5,1,5,5,4,5,4,3,4,5,20,18.0,neutral or dissatisfied +84662,71588,Male,Loyal Customer,33,Business travel,Business,2361,4,4,5,4,4,4,4,4,2,3,2,2,3,4,8,10.0,neutral or dissatisfied +84663,114933,Female,Loyal Customer,54,Business travel,Business,373,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +84664,92063,Male,Loyal Customer,27,Business travel,Eco,1589,2,5,5,5,2,2,2,2,3,1,4,4,3,2,29,7.0,neutral or dissatisfied +84665,122676,Male,disloyal Customer,26,Business travel,Business,361,5,1,5,4,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +84666,41707,Male,Loyal Customer,36,Business travel,Business,1404,2,2,5,2,5,1,3,2,2,2,2,3,2,2,0,12.0,satisfied +84667,22253,Female,Loyal Customer,42,Business travel,Business,238,0,0,0,5,4,3,5,1,1,1,1,5,1,4,22,18.0,satisfied +84668,65408,Male,Loyal Customer,40,Personal Travel,Eco,631,4,5,4,3,2,4,2,2,5,3,5,3,4,2,0,0.0,satisfied +84669,77187,Male,Loyal Customer,57,Business travel,Eco,290,4,5,5,5,4,4,4,4,3,5,4,3,4,4,2,0.0,satisfied +84670,36761,Female,Loyal Customer,37,Business travel,Eco,2611,3,4,4,4,4,3,3,3,3,5,5,3,5,3,1,0.0,satisfied +84671,85009,Female,disloyal Customer,23,Business travel,Eco,759,2,2,2,3,3,2,3,3,1,3,2,4,3,3,26,22.0,neutral or dissatisfied +84672,104643,Female,disloyal Customer,35,Business travel,Business,1754,2,2,2,1,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +84673,90746,Female,disloyal Customer,38,Business travel,Business,250,5,5,5,3,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +84674,74687,Male,Loyal Customer,56,Personal Travel,Eco,1171,2,4,2,3,4,2,4,4,5,3,3,4,5,4,1,0.0,neutral or dissatisfied +84675,35895,Male,Loyal Customer,34,Business travel,Eco Plus,1023,3,3,3,3,4,3,3,4,1,1,2,3,3,3,150,190.0,satisfied +84676,42370,Female,Loyal Customer,48,Personal Travel,Eco,834,2,5,2,5,5,4,4,3,3,2,1,4,3,4,21,5.0,neutral or dissatisfied +84677,27023,Female,Loyal Customer,48,Personal Travel,Eco,867,3,3,3,3,1,3,3,3,3,3,3,1,3,4,0,2.0,neutral or dissatisfied +84678,25150,Male,Loyal Customer,54,Personal Travel,Eco,406,1,5,1,4,5,1,5,5,5,3,4,2,5,5,0,0.0,neutral or dissatisfied +84679,78542,Female,Loyal Customer,27,Personal Travel,Eco,666,2,5,2,4,1,2,1,1,1,1,3,4,5,1,0,0.0,neutral or dissatisfied +84680,124072,Male,Loyal Customer,39,Business travel,Business,2153,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +84681,7152,Male,Loyal Customer,57,Business travel,Business,135,3,3,3,3,4,4,4,5,5,5,4,4,5,3,33,30.0,satisfied +84682,78835,Female,Loyal Customer,60,Personal Travel,Eco,447,4,4,4,3,5,5,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +84683,110577,Male,Loyal Customer,63,Business travel,Business,2751,3,3,3,3,4,5,4,4,4,3,4,3,4,5,13,5.0,satisfied +84684,99195,Male,Loyal Customer,47,Business travel,Business,2194,2,2,2,2,3,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +84685,126764,Male,Loyal Customer,39,Personal Travel,Eco,2521,3,4,3,2,1,3,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +84686,55985,Female,Loyal Customer,35,Business travel,Eco Plus,1620,4,5,1,1,4,3,4,4,3,1,3,2,3,4,0,0.0,neutral or dissatisfied +84687,51196,Male,Loyal Customer,38,Business travel,Eco Plus,86,4,3,3,3,4,4,4,4,5,2,5,3,1,4,69,87.0,satisfied +84688,8977,Female,Loyal Customer,52,Business travel,Eco,325,4,1,1,1,4,4,4,3,2,4,4,4,2,4,152,181.0,neutral or dissatisfied +84689,50529,Male,Loyal Customer,40,Personal Travel,Eco,86,2,4,0,3,3,0,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +84690,121796,Female,disloyal Customer,27,Business travel,Business,366,4,4,4,2,1,4,1,1,4,4,4,5,5,1,0,2.0,satisfied +84691,25332,Male,disloyal Customer,19,Business travel,Eco,829,3,3,3,3,4,3,5,4,2,5,5,3,3,4,7,0.0,neutral or dissatisfied +84692,51716,Female,Loyal Customer,10,Personal Travel,Eco,261,2,4,2,1,2,2,2,2,1,4,3,5,1,2,0,0.0,neutral or dissatisfied +84693,127947,Male,disloyal Customer,18,Business travel,Business,2300,5,0,5,4,5,5,5,5,3,4,4,5,4,5,1,0.0,satisfied +84694,118348,Female,Loyal Customer,70,Personal Travel,Eco,602,2,5,2,2,5,5,4,1,1,2,1,5,1,5,0,2.0,neutral or dissatisfied +84695,29437,Male,Loyal Customer,34,Business travel,Business,421,5,5,5,5,2,4,3,5,5,4,5,2,5,4,63,59.0,satisfied +84696,71216,Female,Loyal Customer,41,Business travel,Business,733,1,1,4,1,2,4,4,5,5,5,5,5,5,5,85,90.0,satisfied +84697,124429,Female,Loyal Customer,49,Personal Travel,Eco,1262,2,4,3,2,5,4,5,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +84698,16604,Male,Loyal Customer,40,Business travel,Eco,1008,5,3,3,3,5,5,5,5,3,2,5,3,1,5,28,38.0,satisfied +84699,128080,Male,Loyal Customer,55,Business travel,Business,2845,5,5,5,5,2,2,2,3,3,4,5,2,3,2,0,0.0,satisfied +84700,76020,Female,Loyal Customer,35,Business travel,Eco,311,2,3,3,3,2,2,2,2,1,5,1,3,1,2,93,93.0,neutral or dissatisfied +84701,43971,Male,Loyal Customer,20,Personal Travel,Eco,232,1,4,1,1,4,1,1,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +84702,12199,Female,Loyal Customer,58,Business travel,Business,2336,5,5,5,5,3,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +84703,115939,Male,Loyal Customer,57,Business travel,Business,2604,3,2,2,2,2,4,3,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +84704,13364,Female,Loyal Customer,65,Personal Travel,Eco,946,1,5,1,3,3,4,5,5,5,1,1,3,5,2,68,64.0,neutral or dissatisfied +84705,25402,Male,Loyal Customer,49,Business travel,Eco,1105,5,4,4,4,5,5,5,5,2,1,3,4,5,5,0,0.0,satisfied +84706,65856,Female,Loyal Customer,59,Personal Travel,Eco,1389,2,4,2,3,5,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +84707,80874,Female,Loyal Customer,57,Personal Travel,Eco,692,3,2,3,3,2,4,3,3,3,3,1,2,3,1,0,0.0,neutral or dissatisfied +84708,84426,Male,Loyal Customer,28,Personal Travel,Eco,591,3,5,3,2,4,3,3,4,4,2,5,4,5,4,0,16.0,neutral or dissatisfied +84709,39265,Female,disloyal Customer,34,Business travel,Eco,268,4,5,4,3,4,4,4,4,4,1,5,3,2,4,0,0.0,neutral or dissatisfied +84710,110823,Male,Loyal Customer,13,Personal Travel,Eco,997,2,1,2,2,1,2,1,1,3,3,2,2,2,1,96,,neutral or dissatisfied +84711,118097,Male,disloyal Customer,9,Business travel,Eco,1671,1,1,1,3,4,1,4,4,1,1,1,4,2,4,39,27.0,neutral or dissatisfied +84712,22987,Male,Loyal Customer,10,Personal Travel,Eco,489,2,5,2,4,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +84713,17587,Female,Loyal Customer,69,Personal Travel,Eco,1034,3,4,2,3,4,5,5,4,4,2,4,3,4,3,65,33.0,neutral or dissatisfied +84714,11532,Female,Loyal Customer,55,Business travel,Business,2291,4,4,4,4,4,4,4,4,4,5,5,4,4,3,0,0.0,satisfied +84715,15250,Male,Loyal Customer,10,Personal Travel,Eco,529,4,3,4,4,3,4,3,3,3,3,3,2,3,3,34,27.0,neutral or dissatisfied +84716,115665,Male,disloyal Customer,18,Business travel,Eco,373,4,2,4,4,2,4,2,2,1,5,3,3,4,2,0,0.0,neutral or dissatisfied +84717,74238,Male,Loyal Customer,19,Personal Travel,Eco Plus,888,3,4,4,3,3,4,1,3,5,3,4,5,5,3,0,5.0,neutral or dissatisfied +84718,119717,Male,disloyal Customer,21,Business travel,Eco,1303,3,3,3,3,5,3,5,5,1,5,3,4,4,5,63,70.0,neutral or dissatisfied +84719,105352,Female,Loyal Customer,51,Personal Travel,Eco,409,2,3,3,4,4,2,2,1,1,3,1,5,1,1,2,3.0,neutral or dissatisfied +84720,102246,Male,Loyal Customer,46,Business travel,Business,2975,2,3,3,3,5,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +84721,33568,Female,Loyal Customer,44,Business travel,Eco,399,4,3,3,3,4,4,5,4,4,4,4,1,4,3,6,15.0,satisfied +84722,61274,Male,Loyal Customer,18,Personal Travel,Eco,862,2,5,2,4,3,2,3,3,3,3,5,4,4,3,2,0.0,neutral or dissatisfied +84723,86061,Female,Loyal Customer,58,Business travel,Business,432,4,4,4,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +84724,13434,Female,Loyal Customer,57,Business travel,Business,3755,2,3,3,3,4,2,2,2,2,2,2,4,2,3,0,21.0,neutral or dissatisfied +84725,4119,Female,disloyal Customer,26,Business travel,Business,431,3,0,3,1,3,3,1,3,3,5,4,5,5,3,17,12.0,neutral or dissatisfied +84726,50498,Male,Loyal Customer,66,Personal Travel,Eco,266,2,5,2,4,2,2,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +84727,101843,Female,Loyal Customer,20,Personal Travel,Eco Plus,1521,2,4,3,3,1,3,3,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +84728,10524,Male,Loyal Customer,59,Business travel,Business,517,5,4,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +84729,44211,Female,Loyal Customer,56,Business travel,Business,224,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +84730,15860,Male,disloyal Customer,24,Business travel,Eco,332,0,0,0,1,3,0,3,3,3,4,2,2,3,3,0,0.0,satisfied +84731,129492,Female,Loyal Customer,47,Business travel,Business,2704,4,4,4,4,3,3,4,4,4,4,4,5,4,5,11,3.0,satisfied +84732,61227,Male,Loyal Customer,43,Business travel,Business,3879,2,5,2,5,5,3,4,2,2,2,2,1,2,1,7,0.0,neutral or dissatisfied +84733,3454,Female,disloyal Customer,26,Business travel,Business,296,3,0,3,3,3,3,3,3,5,3,4,3,4,3,0,14.0,neutral or dissatisfied +84734,37690,Male,Loyal Customer,44,Personal Travel,Eco,1097,3,4,3,4,4,3,5,4,1,3,3,4,3,4,74,81.0,neutral or dissatisfied +84735,27693,Male,Loyal Customer,8,Personal Travel,Eco,1107,3,3,3,1,5,3,4,5,2,1,5,4,2,5,0,0.0,neutral or dissatisfied +84736,33687,Female,disloyal Customer,26,Business travel,Eco,759,5,4,4,1,2,4,2,2,4,3,4,4,1,2,0,0.0,satisfied +84737,17726,Male,disloyal Customer,30,Business travel,Eco,383,2,0,2,3,5,2,5,5,3,2,1,1,1,5,0,0.0,neutral or dissatisfied +84738,18664,Female,Loyal Customer,12,Personal Travel,Eco,192,2,4,0,1,0,2,3,4,5,5,4,3,4,3,197,197.0,neutral or dissatisfied +84739,36837,Male,disloyal Customer,23,Business travel,Eco,369,2,2,2,3,2,2,2,2,4,4,4,4,3,2,11,1.0,neutral or dissatisfied +84740,37063,Male,disloyal Customer,18,Business travel,Business,1188,4,5,4,3,1,4,1,1,5,5,2,1,2,1,5,9.0,satisfied +84741,95960,Female,Loyal Customer,45,Business travel,Business,1090,2,2,2,2,5,5,5,5,5,5,5,5,5,5,10,4.0,satisfied +84742,122721,Male,Loyal Customer,50,Business travel,Business,651,2,2,2,2,5,4,4,4,4,4,4,3,4,5,33,19.0,satisfied +84743,65936,Male,Loyal Customer,39,Personal Travel,Eco,569,1,5,1,1,1,1,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +84744,61647,Female,Loyal Customer,58,Business travel,Business,3391,1,1,1,1,4,4,4,4,4,4,4,5,4,4,1,0.0,satisfied +84745,28897,Female,disloyal Customer,30,Business travel,Eco,954,2,2,2,3,4,2,4,4,1,5,4,4,2,4,0,0.0,neutral or dissatisfied +84746,129268,Male,Loyal Customer,56,Business travel,Business,2402,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,31.0,satisfied +84747,2372,Male,Loyal Customer,15,Personal Travel,Eco Plus,925,4,4,5,4,1,5,1,1,3,5,5,3,5,1,111,109.0,neutral or dissatisfied +84748,53765,Male,Loyal Customer,40,Business travel,Business,1195,3,3,3,3,2,3,4,3,3,2,3,4,3,3,64,50.0,neutral or dissatisfied +84749,14910,Male,Loyal Customer,7,Personal Travel,Eco,240,4,5,4,4,5,4,5,5,3,4,5,4,4,5,0,9.0,neutral or dissatisfied +84750,37908,Male,disloyal Customer,29,Business travel,Eco,937,2,2,2,3,3,2,3,3,4,3,3,3,3,3,70,48.0,neutral or dissatisfied +84751,99730,Female,disloyal Customer,39,Business travel,Business,255,2,2,2,4,2,2,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +84752,115662,Female,disloyal Customer,27,Business travel,Eco,333,3,4,3,4,4,3,4,4,2,2,3,1,3,4,7,9.0,neutral or dissatisfied +84753,11469,Male,Loyal Customer,60,Business travel,Business,216,0,4,0,4,4,4,4,5,5,1,1,5,5,3,4,1.0,satisfied +84754,14707,Male,Loyal Customer,52,Business travel,Business,419,3,3,3,3,3,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +84755,1139,Male,Loyal Customer,61,Personal Travel,Eco,134,4,0,4,3,5,4,5,5,2,4,4,3,4,5,0,1.0,neutral or dissatisfied +84756,57081,Male,Loyal Customer,50,Business travel,Business,1222,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +84757,83980,Female,Loyal Customer,35,Business travel,Business,2076,2,4,4,4,4,3,4,2,2,2,2,3,2,3,1,2.0,neutral or dissatisfied +84758,14416,Male,Loyal Customer,36,Business travel,Eco,693,1,3,3,3,1,1,1,1,3,3,2,4,2,1,5,10.0,neutral or dissatisfied +84759,61453,Male,Loyal Customer,57,Business travel,Business,2288,5,5,5,5,3,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +84760,82984,Male,disloyal Customer,26,Business travel,Business,1127,5,5,5,4,1,5,1,1,5,5,5,3,5,1,11,0.0,satisfied +84761,108965,Female,disloyal Customer,40,Business travel,Business,142,4,4,4,3,2,4,2,2,2,3,2,3,1,2,0,0.0,neutral or dissatisfied +84762,114391,Female,disloyal Customer,38,Business travel,Business,417,5,5,5,5,2,5,2,2,4,5,4,4,5,2,0,0.0,satisfied +84763,27227,Female,disloyal Customer,28,Business travel,Eco,1024,3,3,3,3,1,3,1,1,1,3,3,4,4,1,0,0.0,neutral or dissatisfied +84764,10997,Female,disloyal Customer,37,Business travel,Eco,191,5,5,5,2,4,5,4,4,4,4,4,2,1,4,0,0.0,satisfied +84765,118217,Male,Loyal Customer,58,Business travel,Business,735,1,1,1,1,3,5,4,2,2,3,2,5,2,3,0,0.0,satisfied +84766,42512,Male,disloyal Customer,28,Business travel,Business,1187,3,3,3,4,3,3,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +84767,127892,Male,Loyal Customer,53,Business travel,Business,1671,3,3,4,3,3,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +84768,110453,Female,Loyal Customer,33,Personal Travel,Eco,883,3,4,3,4,3,3,1,3,1,3,5,1,1,3,32,26.0,neutral or dissatisfied +84769,49153,Female,Loyal Customer,45,Business travel,Business,109,0,4,0,1,5,5,5,4,4,4,4,2,4,2,20,39.0,satisfied +84770,4965,Male,Loyal Customer,65,Personal Travel,Eco,931,2,1,2,4,1,2,1,1,1,3,4,2,4,1,0,27.0,neutral or dissatisfied +84771,32106,Female,Loyal Customer,51,Business travel,Business,3331,4,4,4,4,4,2,5,4,4,4,4,4,4,2,33,34.0,satisfied +84772,90237,Female,Loyal Customer,37,Personal Travel,Eco Plus,1127,2,4,2,3,3,2,5,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +84773,481,Male,Loyal Customer,55,Business travel,Business,134,1,1,1,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +84774,43713,Female,Loyal Customer,27,Personal Travel,Eco,257,1,1,1,2,1,1,1,1,2,3,2,4,3,1,0,0.0,neutral or dissatisfied +84775,32914,Male,Loyal Customer,45,Personal Travel,Eco,101,3,4,0,4,1,0,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +84776,49717,Female,Loyal Customer,56,Business travel,Business,3293,5,5,5,5,3,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +84777,82721,Male,Loyal Customer,52,Personal Travel,Eco,632,3,4,3,2,1,3,1,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +84778,57244,Female,Loyal Customer,29,Business travel,Business,2966,5,5,3,5,5,5,5,5,4,5,4,4,5,5,0,0.0,satisfied +84779,111198,Male,Loyal Customer,56,Business travel,Business,1546,1,1,1,1,2,4,5,4,4,4,4,3,4,5,75,79.0,satisfied +84780,10289,Female,disloyal Customer,22,Business travel,Business,201,4,0,4,1,2,4,2,2,5,5,5,3,5,2,21,24.0,satisfied +84781,58793,Male,Loyal Customer,26,Business travel,Eco,1012,3,3,3,3,3,3,3,3,1,2,3,4,2,3,1,0.0,neutral or dissatisfied +84782,115508,Male,Loyal Customer,38,Business travel,Eco,372,3,5,5,5,3,3,3,3,4,3,3,2,3,3,4,7.0,neutral or dissatisfied +84783,108907,Male,Loyal Customer,51,Business travel,Business,1729,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +84784,76180,Male,Loyal Customer,58,Business travel,Business,2422,1,1,1,1,5,3,4,3,3,3,3,5,3,3,0,0.0,satisfied +84785,102924,Female,Loyal Customer,30,Business travel,Business,1991,4,4,4,4,5,5,5,5,4,5,4,4,5,5,4,2.0,satisfied +84786,86422,Male,Loyal Customer,36,Business travel,Business,762,2,2,2,2,4,4,5,4,4,4,4,4,4,3,0,4.0,satisfied +84787,113257,Female,disloyal Customer,38,Business travel,Business,236,3,3,3,5,3,3,5,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +84788,123224,Male,Loyal Customer,40,Personal Travel,Eco,631,1,5,2,4,5,2,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +84789,109203,Male,Loyal Customer,46,Business travel,Eco,483,2,4,1,1,2,2,2,2,4,3,3,4,2,2,52,45.0,neutral or dissatisfied +84790,58635,Male,Loyal Customer,24,Business travel,Business,867,3,5,3,3,5,5,5,5,3,2,4,5,5,5,0,0.0,satisfied +84791,6214,Female,Loyal Customer,18,Business travel,Business,2057,2,2,3,2,4,4,4,4,2,5,1,4,3,4,0,0.0,satisfied +84792,39147,Female,Loyal Customer,45,Personal Travel,Eco,190,3,4,3,4,2,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +84793,39221,Female,Loyal Customer,31,Business travel,Business,67,4,4,4,4,3,4,5,3,1,2,5,2,5,3,20,10.0,satisfied +84794,102867,Female,Loyal Customer,48,Business travel,Business,3687,3,3,3,3,4,5,5,4,4,4,4,4,4,4,65,69.0,satisfied +84795,98284,Male,disloyal Customer,57,Business travel,Eco,672,4,4,4,1,5,4,5,5,2,4,4,1,3,5,3,1.0,neutral or dissatisfied +84796,65072,Male,Loyal Customer,8,Personal Travel,Eco,190,4,5,0,4,5,0,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +84797,67929,Female,Loyal Customer,31,Personal Travel,Eco,1464,3,2,3,4,2,3,5,2,4,4,4,1,4,2,8,9.0,neutral or dissatisfied +84798,6272,Female,Loyal Customer,34,Business travel,Business,2521,1,3,3,3,1,4,4,1,1,1,1,4,1,3,46,46.0,neutral or dissatisfied +84799,112432,Female,disloyal Customer,24,Business travel,Business,909,3,3,3,4,2,3,2,2,4,1,3,2,3,2,10,11.0,neutral or dissatisfied +84800,86961,Female,Loyal Customer,52,Business travel,Eco,907,1,4,4,4,2,2,2,1,1,1,1,2,1,3,24,32.0,neutral or dissatisfied +84801,121162,Male,Loyal Customer,40,Business travel,Eco,902,2,3,3,3,2,2,2,3,2,3,5,2,1,2,11,3.0,satisfied +84802,85303,Female,Loyal Customer,13,Personal Travel,Eco,813,3,0,3,5,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +84803,61793,Female,Loyal Customer,70,Personal Travel,Eco,1379,2,5,2,1,3,2,3,1,1,2,1,4,1,5,6,0.0,neutral or dissatisfied +84804,41845,Male,Loyal Customer,40,Personal Travel,Eco Plus,462,3,4,3,3,3,3,3,3,5,2,4,5,5,3,16,12.0,neutral or dissatisfied +84805,124335,Male,Loyal Customer,38,Business travel,Eco,1037,2,1,4,1,2,2,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +84806,107601,Male,Loyal Customer,58,Business travel,Business,423,4,4,4,4,2,4,5,4,4,4,4,4,4,4,2,0.0,satisfied +84807,51150,Male,Loyal Customer,70,Personal Travel,Eco,77,2,4,2,5,5,2,5,5,4,4,5,4,4,5,99,105.0,neutral or dissatisfied +84808,115484,Female,Loyal Customer,56,Business travel,Business,404,1,2,2,2,2,4,3,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +84809,79966,Male,Loyal Customer,44,Business travel,Business,1979,2,3,3,3,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +84810,50691,Male,Loyal Customer,18,Personal Travel,Eco,373,3,0,3,3,1,3,1,1,3,5,3,4,4,1,29,21.0,neutral or dissatisfied +84811,14750,Male,Loyal Customer,22,Business travel,Eco,533,1,1,3,1,1,1,1,1,4,3,3,3,3,1,0,0.0,neutral or dissatisfied +84812,117815,Female,Loyal Customer,22,Personal Travel,Eco,328,2,4,2,3,2,2,2,2,1,3,4,4,3,2,1,0.0,neutral or dissatisfied +84813,106588,Male,Loyal Customer,43,Personal Travel,Eco,333,1,4,1,1,4,1,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +84814,57527,Male,disloyal Customer,25,Business travel,Eco,413,3,2,3,2,4,3,3,4,4,3,2,1,3,4,67,60.0,neutral or dissatisfied +84815,25102,Female,Loyal Customer,10,Personal Travel,Eco,369,3,3,3,4,4,3,2,4,3,5,1,4,1,4,0,0.0,neutral or dissatisfied +84816,13225,Female,Loyal Customer,50,Business travel,Business,2131,1,1,1,1,4,4,4,5,5,5,5,5,5,2,0,0.0,satisfied +84817,82827,Female,Loyal Customer,43,Business travel,Business,594,4,4,4,4,4,4,5,2,2,2,2,3,2,3,6,11.0,satisfied +84818,108537,Male,Loyal Customer,17,Personal Travel,Eco Plus,649,1,2,1,3,4,1,3,4,2,1,4,1,4,4,9,1.0,neutral or dissatisfied +84819,43061,Female,Loyal Customer,16,Business travel,Eco,259,1,3,3,3,1,2,2,1,1,5,4,3,3,1,5,,neutral or dissatisfied +84820,54574,Female,Loyal Customer,18,Personal Travel,Eco Plus,802,2,5,2,3,5,2,3,5,1,5,2,3,2,5,10,9.0,neutral or dissatisfied +84821,33486,Female,Loyal Customer,22,Business travel,Business,2496,4,4,4,4,2,2,2,2,1,5,4,3,4,2,45,34.0,satisfied +84822,41713,Male,Loyal Customer,65,Personal Travel,Eco,1404,4,4,4,3,5,4,4,5,5,2,3,4,4,5,5,0.0,neutral or dissatisfied +84823,83329,Female,Loyal Customer,44,Business travel,Business,2105,4,4,4,4,2,3,5,2,2,2,2,5,2,4,0,0.0,satisfied +84824,7176,Male,disloyal Customer,79,Business travel,Business,139,4,4,4,4,5,4,4,3,3,4,3,4,3,5,4,4.0,satisfied +84825,22490,Female,Loyal Customer,17,Personal Travel,Eco,238,1,2,0,3,1,0,1,1,1,3,3,3,4,1,0,0.0,neutral or dissatisfied +84826,41498,Female,Loyal Customer,29,Business travel,Business,1235,4,4,4,4,5,5,5,5,4,4,2,4,1,5,10,16.0,satisfied +84827,84580,Male,Loyal Customer,37,Personal Travel,Eco,1572,2,4,1,2,2,1,2,2,5,2,3,5,5,2,0,8.0,neutral or dissatisfied +84828,125697,Female,Loyal Customer,64,Personal Travel,Eco,814,3,2,3,3,4,4,4,2,2,3,2,1,2,4,0,6.0,neutral or dissatisfied +84829,58887,Male,Loyal Customer,46,Business travel,Business,888,4,1,4,4,2,5,5,4,4,4,4,3,4,5,3,0.0,satisfied +84830,1134,Female,Loyal Customer,23,Personal Travel,Eco,158,4,5,4,1,1,4,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +84831,24192,Male,disloyal Customer,44,Business travel,Eco,170,3,2,4,3,1,4,1,1,4,3,4,4,3,1,8,0.0,neutral or dissatisfied +84832,44947,Female,Loyal Customer,37,Business travel,Eco,397,4,5,5,5,4,4,4,4,1,2,5,3,2,4,0,0.0,satisfied +84833,18035,Female,Loyal Customer,52,Business travel,Eco,605,4,1,1,1,5,4,4,4,4,4,4,5,4,5,21,16.0,satisfied +84834,74087,Female,disloyal Customer,33,Business travel,Business,641,3,3,3,3,1,3,1,1,5,4,5,5,5,1,73,60.0,neutral or dissatisfied +84835,118831,Male,Loyal Customer,52,Business travel,Business,2893,4,4,3,4,4,4,4,4,4,4,4,4,4,5,5,0.0,satisfied +84836,38638,Male,Loyal Customer,36,Business travel,Business,2611,5,5,5,5,2,5,1,4,4,4,4,3,4,4,0,0.0,satisfied +84837,27782,Male,Loyal Customer,52,Business travel,Eco,1448,2,2,2,2,2,2,2,2,4,2,1,1,1,2,0,23.0,neutral or dissatisfied +84838,41937,Female,Loyal Customer,35,Personal Travel,Eco,129,2,4,0,1,4,0,5,4,4,2,4,4,4,4,0,3.0,neutral or dissatisfied +84839,108107,Male,Loyal Customer,42,Business travel,Business,2041,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,4.0,satisfied +84840,77360,Male,Loyal Customer,43,Business travel,Business,1710,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +84841,113292,Male,Loyal Customer,46,Business travel,Business,2147,0,0,0,1,2,4,4,1,1,1,1,3,1,5,0,1.0,satisfied +84842,25153,Female,Loyal Customer,57,Business travel,Eco,2106,4,4,4,4,4,4,5,4,4,4,4,2,4,2,2,0.0,satisfied +84843,60647,Female,Loyal Customer,48,Business travel,Eco,1620,3,1,1,1,2,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +84844,82186,Male,disloyal Customer,22,Business travel,Eco,1927,2,3,3,4,4,2,4,4,4,2,4,5,4,4,9,6.0,neutral or dissatisfied +84845,12488,Female,Loyal Customer,33,Business travel,Eco Plus,127,4,2,2,2,4,4,4,4,5,2,1,4,3,4,15,19.0,satisfied +84846,69122,Female,disloyal Customer,50,Business travel,Eco,998,3,3,3,3,3,3,3,3,2,4,3,4,4,3,6,62.0,neutral or dissatisfied +84847,4527,Female,Loyal Customer,59,Business travel,Business,2375,3,3,3,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +84848,21871,Male,Loyal Customer,39,Business travel,Eco,448,3,2,5,2,3,3,3,4,2,2,5,3,3,3,163,178.0,satisfied +84849,82095,Male,Loyal Customer,51,Business travel,Business,1786,3,3,3,3,1,4,5,4,4,4,4,1,4,3,0,0.0,satisfied +84850,120534,Female,Loyal Customer,12,Personal Travel,Eco Plus,289,2,5,2,4,4,2,1,4,3,5,4,4,5,4,68,63.0,neutral or dissatisfied +84851,61098,Female,Loyal Customer,36,Personal Travel,Eco,1709,2,4,2,3,3,2,3,3,1,4,3,1,3,3,24,0.0,neutral or dissatisfied +84852,38964,Female,Loyal Customer,40,Personal Travel,Business,230,3,5,0,1,5,5,4,1,1,0,1,3,1,4,0,1.0,neutral or dissatisfied +84853,43229,Female,Loyal Customer,54,Personal Travel,Eco Plus,423,3,3,3,3,1,1,2,2,2,3,2,2,2,1,9,33.0,neutral or dissatisfied +84854,44076,Female,Loyal Customer,38,Business travel,Eco,651,4,3,3,3,4,4,4,4,3,3,4,5,5,4,20,29.0,satisfied +84855,74079,Female,Loyal Customer,57,Business travel,Business,592,2,2,2,2,3,3,3,3,4,4,4,3,5,3,163,196.0,satisfied +84856,13021,Male,Loyal Customer,31,Business travel,Eco,438,0,0,0,1,5,0,3,5,1,2,2,5,4,5,0,0.0,satisfied +84857,120744,Male,disloyal Customer,50,Business travel,Eco,588,2,1,2,4,1,2,1,1,3,5,4,4,3,1,0,41.0,neutral or dissatisfied +84858,98529,Male,Loyal Customer,63,Personal Travel,Eco,668,2,4,2,5,5,2,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +84859,34430,Female,disloyal Customer,26,Business travel,Eco,680,3,3,3,4,5,3,1,5,1,3,4,1,3,5,54,43.0,neutral or dissatisfied +84860,2907,Female,Loyal Customer,17,Personal Travel,Eco,409,1,4,1,5,1,1,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +84861,3423,Male,Loyal Customer,27,Personal Travel,Eco,296,1,3,1,4,4,1,4,4,2,5,4,4,4,4,67,59.0,neutral or dissatisfied +84862,93123,Female,Loyal Customer,41,Business travel,Business,3230,4,4,4,4,4,4,4,5,5,4,5,3,5,3,25,20.0,satisfied +84863,122877,Male,Loyal Customer,47,Personal Travel,Eco,226,5,5,5,4,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +84864,51659,Female,disloyal Customer,34,Business travel,Eco,751,1,1,1,3,5,1,3,5,2,4,5,5,1,5,0,0.0,neutral or dissatisfied +84865,34877,Female,Loyal Customer,41,Personal Travel,Eco,2248,5,4,5,3,2,5,2,2,5,5,5,5,4,2,10,0.0,satisfied +84866,63708,Female,Loyal Customer,52,Business travel,Business,1660,2,2,4,4,5,2,1,2,2,2,2,2,2,1,9,0.0,neutral or dissatisfied +84867,66783,Female,Loyal Customer,30,Business travel,Business,3784,3,3,3,3,3,3,3,1,2,3,4,3,4,3,50,55.0,neutral or dissatisfied +84868,51215,Female,disloyal Customer,43,Business travel,Eco Plus,56,1,1,1,2,4,1,4,4,5,2,5,3,3,4,0,0.0,neutral or dissatisfied +84869,59483,Female,Loyal Customer,50,Business travel,Business,1993,1,5,5,5,4,3,3,1,1,2,1,2,1,2,5,0.0,neutral or dissatisfied +84870,51682,Female,disloyal Customer,13,Business travel,Eco,598,2,2,2,3,3,2,3,3,2,4,4,3,3,3,0,2.0,neutral or dissatisfied +84871,39317,Male,Loyal Customer,9,Personal Travel,Eco,67,3,5,3,3,4,3,4,4,4,2,4,4,5,4,46,66.0,neutral or dissatisfied +84872,380,Male,Loyal Customer,45,Business travel,Business,1507,0,0,0,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +84873,38014,Male,Loyal Customer,46,Business travel,Business,1622,1,1,1,1,5,5,5,4,4,1,3,5,3,5,276,270.0,satisfied +84874,18578,Female,Loyal Customer,37,Business travel,Business,2631,4,2,2,2,4,3,4,4,4,4,4,4,4,2,10,9.0,neutral or dissatisfied +84875,99112,Male,Loyal Customer,67,Personal Travel,Eco,181,3,2,0,3,2,0,2,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +84876,28761,Female,Loyal Customer,13,Personal Travel,Eco,1024,1,5,0,2,4,0,4,4,1,1,5,2,4,4,0,0.0,neutral or dissatisfied +84877,113890,Female,Loyal Customer,60,Business travel,Business,2329,2,2,2,2,3,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +84878,99198,Male,disloyal Customer,22,Business travel,Eco,1180,2,2,2,2,4,2,2,4,3,3,2,1,2,4,0,0.0,neutral or dissatisfied +84879,13127,Male,Loyal Customer,8,Business travel,Business,2786,3,3,3,3,4,4,4,4,4,2,5,4,2,4,0,0.0,satisfied +84880,10468,Male,Loyal Customer,53,Business travel,Business,312,1,1,1,1,4,5,4,4,4,4,4,3,4,4,5,8.0,satisfied +84881,12261,Male,disloyal Customer,32,Business travel,Eco,253,3,0,3,3,3,3,3,3,4,1,2,1,5,3,14,8.0,neutral or dissatisfied +84882,74157,Female,Loyal Customer,66,Personal Travel,Eco,592,4,3,4,3,1,3,1,2,2,4,1,4,2,1,110,103.0,satisfied +84883,51307,Female,Loyal Customer,38,Business travel,Eco Plus,421,4,2,4,2,4,4,4,4,1,5,4,2,3,4,0,0.0,neutral or dissatisfied +84884,20486,Male,disloyal Customer,33,Business travel,Eco,139,3,2,3,4,1,3,1,1,1,2,3,1,4,1,15,8.0,neutral or dissatisfied +84885,35172,Male,disloyal Customer,27,Business travel,Business,1069,1,1,1,4,5,1,5,5,1,3,1,4,4,5,0,0.0,neutral or dissatisfied +84886,113955,Female,Loyal Customer,34,Business travel,Business,1728,4,4,4,4,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +84887,79993,Male,Loyal Customer,7,Personal Travel,Eco,1096,3,2,3,3,2,3,2,2,2,1,3,4,3,2,48,77.0,neutral or dissatisfied +84888,33288,Male,Loyal Customer,21,Personal Travel,Eco Plus,101,2,4,2,4,5,2,5,5,5,4,4,3,4,5,0,1.0,neutral or dissatisfied +84889,40700,Female,Loyal Customer,52,Business travel,Business,2406,3,3,5,3,1,2,5,5,5,5,5,5,5,3,0,3.0,satisfied +84890,22173,Male,Loyal Customer,41,Business travel,Business,633,1,1,3,1,1,2,3,4,4,4,4,1,4,5,0,0.0,satisfied +84891,79290,Male,Loyal Customer,45,Business travel,Business,2248,2,2,2,2,4,5,4,5,5,5,5,4,5,4,39,33.0,satisfied +84892,98654,Male,disloyal Customer,37,Business travel,Eco,434,1,0,1,3,3,1,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +84893,40687,Female,Loyal Customer,38,Business travel,Business,590,1,1,3,1,3,3,4,4,4,4,4,5,4,4,4,0.0,satisfied +84894,13576,Male,Loyal Customer,20,Personal Travel,Eco,152,2,4,0,4,4,0,4,4,2,1,3,1,3,4,38,59.0,neutral or dissatisfied +84895,53880,Female,Loyal Customer,25,Personal Travel,Eco,224,3,4,3,3,5,3,5,5,2,2,4,2,4,5,0,0.0,neutral or dissatisfied +84896,18993,Female,Loyal Customer,18,Personal Travel,Eco,451,3,1,3,3,4,3,4,4,1,5,4,3,3,4,59,49.0,neutral or dissatisfied +84897,13,Male,disloyal Customer,24,Business travel,Eco,453,2,2,2,4,5,2,5,5,2,4,4,2,4,5,16,30.0,neutral or dissatisfied +84898,105758,Male,Loyal Customer,22,Business travel,Business,387,2,5,5,5,2,3,2,2,1,4,3,4,3,2,22,36.0,neutral or dissatisfied +84899,14479,Female,Loyal Customer,38,Business travel,Eco,541,5,4,4,4,5,5,5,5,3,5,3,3,3,5,3,32.0,satisfied +84900,123047,Male,Loyal Customer,33,Business travel,Business,590,2,4,4,4,2,2,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +84901,2786,Male,Loyal Customer,56,Business travel,Business,764,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +84902,62301,Female,disloyal Customer,27,Business travel,Eco,414,1,4,1,4,4,1,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +84903,46096,Female,Loyal Customer,33,Business travel,Eco Plus,541,3,1,1,1,3,3,3,3,3,5,3,4,4,3,0,36.0,neutral or dissatisfied +84904,21714,Male,Loyal Customer,36,Personal Travel,Eco Plus,746,3,5,3,2,2,3,4,2,2,5,5,1,1,2,25,12.0,neutral or dissatisfied +84905,66964,Female,Loyal Customer,35,Business travel,Business,3363,1,1,1,1,1,3,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +84906,70030,Female,Loyal Customer,27,Business travel,Eco,583,3,4,3,4,3,2,3,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +84907,36029,Female,Loyal Customer,39,Business travel,Business,413,5,3,3,3,4,4,3,5,5,4,5,2,5,2,0,0.0,neutral or dissatisfied +84908,10322,Female,Loyal Customer,46,Business travel,Business,316,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +84909,13239,Female,Loyal Customer,36,Business travel,Business,1536,2,2,4,2,1,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +84910,124850,Female,Loyal Customer,68,Personal Travel,Eco,280,3,5,3,2,3,5,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +84911,21984,Male,Loyal Customer,12,Personal Travel,Eco,448,2,4,2,4,2,2,2,4,4,4,5,2,3,2,136,147.0,neutral or dissatisfied +84912,62054,Female,Loyal Customer,11,Personal Travel,Eco,2586,3,4,3,3,2,3,2,2,5,3,4,5,5,2,32,34.0,neutral or dissatisfied +84913,776,Male,Loyal Customer,55,Business travel,Business,247,3,3,3,3,5,5,5,3,3,4,3,3,3,4,23,26.0,satisfied +84914,114044,Female,disloyal Customer,15,Business travel,Eco,512,3,1,3,4,4,3,4,4,2,4,3,1,4,4,62,61.0,neutral or dissatisfied +84915,86998,Female,Loyal Customer,66,Personal Travel,Eco,907,4,5,3,1,2,5,5,3,3,3,3,5,3,3,25,12.0,neutral or dissatisfied +84916,58078,Female,disloyal Customer,20,Business travel,Eco,589,2,2,2,3,3,2,3,3,3,2,3,2,3,3,9,3.0,neutral or dissatisfied +84917,97842,Female,Loyal Customer,29,Personal Travel,Eco,395,3,5,3,4,2,3,3,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +84918,4085,Female,disloyal Customer,40,Business travel,Business,431,4,3,3,2,3,3,3,3,3,3,4,3,4,3,0,0.0,satisfied +84919,77580,Female,Loyal Customer,45,Personal Travel,Business,1282,4,4,4,1,3,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +84920,49328,Female,Loyal Customer,28,Business travel,Business,158,1,1,1,1,4,4,4,4,4,5,1,1,3,4,5,4.0,satisfied +84921,2745,Male,Loyal Customer,18,Business travel,Business,3172,2,2,2,2,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +84922,18300,Female,Loyal Customer,50,Personal Travel,Eco Plus,640,3,2,3,3,1,4,4,1,1,3,5,1,1,3,0,0.0,neutral or dissatisfied +84923,20582,Male,Loyal Customer,18,Personal Travel,Eco,533,3,2,2,3,3,2,3,3,1,3,4,3,4,3,2,19.0,neutral or dissatisfied +84924,88594,Female,Loyal Customer,33,Personal Travel,Eco,545,3,4,3,4,2,3,2,2,1,3,3,3,4,2,9,15.0,neutral or dissatisfied +84925,76720,Male,Loyal Customer,31,Business travel,Eco Plus,547,3,4,4,4,3,3,3,3,2,2,4,3,3,3,0,3.0,neutral or dissatisfied +84926,20094,Female,disloyal Customer,22,Business travel,Eco,466,3,0,3,1,5,3,5,5,4,3,1,2,3,5,112,95.0,neutral or dissatisfied +84927,93670,Female,Loyal Customer,43,Business travel,Business,667,5,5,5,5,2,5,5,4,4,5,4,5,4,3,3,0.0,satisfied +84928,21180,Female,disloyal Customer,23,Business travel,Eco,317,2,0,2,1,4,2,1,4,4,5,2,5,4,4,0,0.0,neutral or dissatisfied +84929,119420,Female,Loyal Customer,9,Personal Travel,Eco,399,3,5,3,5,1,3,1,1,5,5,4,5,4,1,0,0.0,neutral or dissatisfied +84930,78003,Male,Loyal Customer,32,Business travel,Business,2060,2,5,4,5,2,2,2,2,4,1,4,1,3,2,28,19.0,neutral or dissatisfied +84931,80831,Male,disloyal Customer,13,Business travel,Eco,692,1,2,2,2,5,2,5,5,5,2,4,5,4,5,0,0.0,neutral or dissatisfied +84932,31556,Female,Loyal Customer,43,Personal Travel,Eco,853,3,4,3,2,5,4,5,2,2,3,2,3,2,3,30,50.0,neutral or dissatisfied +84933,19641,Female,Loyal Customer,70,Personal Travel,Eco,531,3,5,3,2,2,4,4,5,5,3,5,4,5,4,14,3.0,neutral or dissatisfied +84934,42991,Female,Loyal Customer,43,Business travel,Business,192,0,4,0,2,2,1,3,4,4,4,2,1,4,5,0,0.0,satisfied +84935,9633,Female,Loyal Customer,53,Business travel,Business,1895,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +84936,104594,Male,Loyal Customer,35,Personal Travel,Eco,369,3,2,3,4,3,3,3,3,3,3,3,2,4,3,0,0.0,neutral or dissatisfied +84937,116717,Female,disloyal Customer,16,Business travel,Eco Plus,342,3,0,3,3,4,3,4,4,5,1,2,2,4,4,0,0.0,neutral or dissatisfied +84938,73212,Male,Loyal Customer,39,Personal Travel,Eco,1258,3,4,3,3,3,3,3,3,4,4,3,5,4,3,26,28.0,neutral or dissatisfied +84939,96212,Male,disloyal Customer,25,Business travel,Eco,546,3,2,3,1,1,3,1,1,2,2,2,1,1,1,12,12.0,neutral or dissatisfied +84940,13107,Female,disloyal Customer,65,Business travel,Eco,427,4,3,4,5,5,4,5,5,5,2,4,5,5,5,17,11.0,neutral or dissatisfied +84941,126676,Male,Loyal Customer,57,Personal Travel,Eco,2276,3,5,3,2,4,3,4,4,4,4,3,5,5,4,0,0.0,neutral or dissatisfied +84942,40696,Male,Loyal Customer,35,Business travel,Business,2574,5,5,2,5,5,2,4,3,3,2,3,5,3,1,0,2.0,satisfied +84943,33439,Female,disloyal Customer,63,Business travel,Eco,1056,3,3,3,5,3,2,3,2,2,4,2,3,3,3,0,5.0,neutral or dissatisfied +84944,122301,Female,Loyal Customer,49,Personal Travel,Eco,573,1,5,2,4,1,4,3,3,3,2,3,1,3,1,16,5.0,neutral or dissatisfied +84945,20711,Female,Loyal Customer,7,Personal Travel,Business,765,1,5,1,3,5,1,4,5,5,4,5,3,4,5,11,6.0,neutral or dissatisfied +84946,70771,Female,Loyal Customer,55,Business travel,Business,328,0,0,0,3,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +84947,5458,Female,Loyal Customer,40,Business travel,Eco,265,5,5,5,5,5,5,5,5,4,2,4,2,1,5,0,0.0,satisfied +84948,73040,Male,Loyal Customer,59,Personal Travel,Eco,1096,2,1,2,3,2,2,2,2,1,4,2,3,2,2,67,53.0,neutral or dissatisfied +84949,87566,Female,disloyal Customer,22,Business travel,Business,432,5,4,5,3,2,5,2,2,3,2,5,4,4,2,19,8.0,satisfied +84950,72447,Female,Loyal Customer,29,Business travel,Business,2156,5,5,5,5,5,5,5,5,5,5,5,4,4,5,0,2.0,satisfied +84951,84850,Female,Loyal Customer,23,Business travel,Business,3917,3,3,3,3,5,5,5,5,5,1,4,2,1,5,0,0.0,satisfied +84952,2024,Female,Loyal Customer,35,Business travel,Eco,812,3,2,3,2,3,3,3,3,2,1,3,4,4,3,0,0.0,neutral or dissatisfied +84953,81089,Male,Loyal Customer,39,Personal Travel,Eco,931,4,5,5,4,4,5,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +84954,60623,Female,Loyal Customer,46,Personal Travel,Eco,1201,4,2,5,3,5,2,3,1,1,5,1,4,1,3,0,0.0,neutral or dissatisfied +84955,16029,Female,Loyal Customer,49,Personal Travel,Eco,780,2,5,2,4,4,5,4,2,2,2,2,4,2,5,0,4.0,neutral or dissatisfied +84956,56522,Male,Loyal Customer,57,Business travel,Business,1801,3,3,3,3,2,4,4,5,5,5,5,3,5,3,36,39.0,satisfied +84957,110747,Female,disloyal Customer,29,Business travel,Business,1166,2,2,2,2,3,2,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +84958,128638,Male,Loyal Customer,37,Personal Travel,Eco,679,1,2,1,3,5,1,5,5,2,2,3,1,4,5,5,0.0,neutral or dissatisfied +84959,26821,Male,Loyal Customer,48,Business travel,Business,1557,1,1,1,1,3,5,3,4,4,4,4,4,4,3,0,0.0,satisfied +84960,61351,Male,Loyal Customer,41,Business travel,Eco,602,2,1,1,1,2,2,2,2,1,1,3,4,3,2,118,121.0,neutral or dissatisfied +84961,93505,Female,Loyal Customer,62,Personal Travel,Eco,1107,2,5,2,5,5,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +84962,70435,Female,Loyal Customer,55,Business travel,Business,2542,4,2,4,4,2,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +84963,55420,Female,disloyal Customer,46,Business travel,Business,2521,1,1,1,4,1,2,2,4,3,4,4,2,4,2,0,0.0,neutral or dissatisfied +84964,116690,Female,disloyal Customer,22,Business travel,Eco,480,2,3,2,3,3,2,1,3,2,4,4,4,3,3,20,22.0,neutral or dissatisfied +84965,17926,Female,Loyal Customer,29,Business travel,Eco Plus,789,4,4,4,4,4,4,4,4,5,1,4,1,5,4,128,117.0,satisfied +84966,58904,Male,Loyal Customer,69,Business travel,Business,488,3,3,3,3,4,4,1,4,4,4,4,2,4,4,2,0.0,satisfied +84967,98754,Female,Loyal Customer,22,Business travel,Business,1814,2,2,1,2,2,2,2,2,5,4,4,4,4,2,0,0.0,satisfied +84968,85775,Male,disloyal Customer,14,Business travel,Eco,526,0,0,0,4,5,0,5,5,4,3,5,4,4,5,0,0.0,satisfied +84969,60540,Male,Loyal Customer,19,Personal Travel,Eco,862,2,4,3,2,4,3,4,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +84970,32068,Male,Loyal Customer,45,Business travel,Business,1750,5,5,5,5,4,1,3,4,4,5,3,4,4,1,0,0.0,satisfied +84971,68088,Male,Loyal Customer,12,Business travel,Business,3163,2,3,3,3,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +84972,79329,Female,Loyal Customer,46,Business travel,Business,1020,1,2,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +84973,65028,Male,Loyal Customer,41,Personal Travel,Eco,224,4,4,0,1,2,0,2,2,5,4,5,3,5,2,13,8.0,neutral or dissatisfied +84974,24076,Male,Loyal Customer,51,Business travel,Eco,866,2,2,2,2,2,2,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +84975,10586,Female,Loyal Customer,44,Business travel,Business,458,1,1,1,1,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +84976,91383,Female,disloyal Customer,29,Business travel,Eco,2342,4,4,4,4,4,4,4,2,5,2,4,4,3,4,0,23.0,neutral or dissatisfied +84977,3504,Male,Loyal Customer,64,Business travel,Eco Plus,1080,2,5,5,5,2,2,2,2,1,3,3,2,3,2,4,10.0,neutral or dissatisfied +84978,41140,Male,Loyal Customer,21,Personal Travel,Eco,140,3,3,3,2,3,3,3,2,2,3,3,3,3,3,144,133.0,neutral or dissatisfied +84979,91284,Female,Loyal Customer,50,Business travel,Business,3801,0,0,0,1,4,5,4,3,3,3,3,3,3,3,0,12.0,satisfied +84980,102908,Male,Loyal Customer,61,Personal Travel,Business,317,5,5,5,2,2,3,4,2,2,5,2,2,2,1,0,0.0,satisfied +84981,47285,Female,Loyal Customer,35,Business travel,Business,1750,4,4,4,4,2,2,2,3,3,3,3,4,3,3,0,11.0,satisfied +84982,20110,Male,Loyal Customer,55,Business travel,Business,466,2,5,5,5,4,3,3,2,2,2,2,2,2,1,0,3.0,neutral or dissatisfied +84983,31959,Female,Loyal Customer,45,Business travel,Business,2170,0,5,0,1,5,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +84984,115582,Female,Loyal Customer,51,Business travel,Business,1906,4,4,5,4,4,4,5,4,4,4,4,5,4,4,24,18.0,satisfied +84985,129068,Male,disloyal Customer,38,Business travel,Business,2218,2,2,2,3,3,2,3,3,4,5,4,4,4,3,19,27.0,neutral or dissatisfied +84986,111898,Male,Loyal Customer,54,Personal Travel,Eco,628,4,4,5,4,5,5,5,5,5,3,4,4,5,5,5,4.0,satisfied +84987,10230,Female,disloyal Customer,36,Business travel,Business,247,3,3,3,3,2,3,5,2,3,1,2,4,2,2,0,0.0,neutral or dissatisfied +84988,76772,Male,Loyal Customer,56,Business travel,Business,1778,4,4,4,4,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +84989,15705,Male,disloyal Customer,33,Business travel,Eco,419,1,0,1,4,5,1,5,5,3,3,3,4,2,5,0,0.0,neutral or dissatisfied +84990,19854,Male,Loyal Customer,43,Business travel,Eco,693,5,4,4,4,5,5,5,5,2,2,1,3,5,5,0,0.0,satisfied +84991,116639,Male,Loyal Customer,42,Business travel,Business,2395,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +84992,102338,Female,Loyal Customer,56,Business travel,Business,407,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +84993,122469,Male,Loyal Customer,43,Business travel,Business,575,5,5,5,5,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +84994,76634,Female,Loyal Customer,39,Business travel,Business,147,1,1,1,1,2,2,5,4,4,4,3,2,4,3,0,5.0,satisfied +84995,83228,Male,Loyal Customer,57,Business travel,Business,1979,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +84996,86954,Female,Loyal Customer,31,Business travel,Business,3890,3,3,3,3,4,4,4,4,5,2,4,3,4,4,9,0.0,satisfied +84997,38457,Male,Loyal Customer,49,Business travel,Eco,1504,3,2,2,2,3,3,3,3,3,3,4,2,3,3,74,65.0,neutral or dissatisfied +84998,77361,Female,disloyal Customer,23,Business travel,Eco,590,4,4,4,3,5,4,5,5,2,2,4,1,4,5,9,20.0,neutral or dissatisfied +84999,72785,Male,disloyal Customer,29,Business travel,Business,1045,4,4,4,3,2,4,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +85000,69684,Male,Loyal Customer,37,Business travel,Eco Plus,569,2,5,5,5,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +85001,20490,Male,Loyal Customer,57,Business travel,Business,1688,1,1,1,1,1,3,1,4,4,4,5,2,4,3,0,0.0,satisfied +85002,112979,Female,Loyal Customer,41,Personal Travel,Eco Plus,1242,3,5,2,2,2,3,4,5,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +85003,95660,Female,Loyal Customer,50,Personal Travel,Eco,928,2,5,2,2,2,4,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +85004,85302,Male,Loyal Customer,45,Personal Travel,Eco,813,3,2,3,3,4,3,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +85005,127959,Female,disloyal Customer,46,Business travel,Eco,1061,1,1,1,3,4,1,4,4,1,2,3,3,4,4,79,69.0,neutral or dissatisfied +85006,101968,Female,Loyal Customer,46,Business travel,Eco,804,4,5,4,4,4,1,2,4,4,4,4,2,4,3,79,70.0,neutral or dissatisfied +85007,67882,Female,Loyal Customer,46,Personal Travel,Eco,1205,1,3,0,3,1,2,2,5,5,0,3,3,5,4,0,0.0,neutral or dissatisfied +85008,14640,Male,Loyal Customer,48,Business travel,Eco,948,4,4,5,4,4,4,4,4,3,1,1,5,4,4,0,0.0,satisfied +85009,14146,Male,Loyal Customer,19,Personal Travel,Eco,594,1,4,1,4,5,1,5,5,3,4,4,3,4,5,0,2.0,neutral or dissatisfied +85010,103440,Male,Loyal Customer,33,Business travel,Business,2437,1,4,2,4,1,1,1,1,3,4,3,3,4,1,30,24.0,neutral or dissatisfied +85011,2684,Female,Loyal Customer,64,Business travel,Business,597,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +85012,59781,Female,Loyal Customer,10,Personal Travel,Eco,895,3,4,3,3,3,3,3,3,4,3,3,4,4,3,57,51.0,neutral or dissatisfied +85013,28902,Female,disloyal Customer,25,Business travel,Eco,956,3,3,3,4,3,3,3,3,1,3,3,3,4,3,0,0.0,neutral or dissatisfied +85014,86064,Female,Loyal Customer,48,Business travel,Business,4000,2,2,2,2,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +85015,71919,Male,Loyal Customer,47,Personal Travel,Eco,1846,4,4,4,3,4,1,1,2,4,4,4,1,3,1,148,210.0,neutral or dissatisfied +85016,17843,Female,Loyal Customer,7,Business travel,Business,505,2,3,3,3,2,2,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +85017,123736,Female,Loyal Customer,50,Personal Travel,Business,96,4,4,0,3,3,4,4,3,3,0,3,4,3,4,0,3.0,satisfied +85018,52315,Male,disloyal Customer,37,Business travel,Eco,261,4,0,4,3,2,4,2,2,4,1,5,5,1,2,0,3.0,neutral or dissatisfied +85019,70003,Female,Loyal Customer,62,Personal Travel,Eco,236,3,5,3,5,1,4,4,3,3,3,3,2,3,3,0,2.0,neutral or dissatisfied +85020,62174,Male,disloyal Customer,34,Business travel,Business,2425,4,4,4,3,5,4,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +85021,7151,Female,Loyal Customer,45,Business travel,Business,2664,5,5,5,5,4,5,5,4,4,4,5,4,4,3,9,0.0,satisfied +85022,19735,Female,Loyal Customer,30,Personal Travel,Eco,475,1,4,1,1,3,1,1,3,4,2,3,4,2,3,1,0.0,neutral or dissatisfied +85023,62203,Male,Loyal Customer,16,Personal Travel,Eco,2454,2,4,1,1,1,1,1,1,5,2,5,4,5,1,7,5.0,neutral or dissatisfied +85024,109729,Male,Loyal Customer,68,Business travel,Eco,187,2,5,5,5,2,2,2,2,1,3,3,1,4,2,33,25.0,neutral or dissatisfied +85025,107963,Female,Loyal Customer,56,Business travel,Eco,825,1,5,5,5,5,3,3,1,1,1,1,2,1,3,10,0.0,neutral or dissatisfied +85026,123584,Male,Loyal Customer,7,Personal Travel,Eco,1773,3,4,2,4,5,2,5,5,2,1,2,3,3,5,20,44.0,neutral or dissatisfied +85027,32891,Male,Loyal Customer,50,Personal Travel,Eco,121,1,3,1,3,3,1,3,3,2,3,3,4,2,3,0,0.0,neutral or dissatisfied +85028,55796,Female,Loyal Customer,62,Personal Travel,Eco,2400,2,4,2,2,2,1,1,5,3,4,4,1,5,1,0,23.0,neutral or dissatisfied +85029,102889,Male,Loyal Customer,24,Business travel,Business,2136,2,2,2,2,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +85030,4644,Female,Loyal Customer,51,Business travel,Business,2740,1,1,1,1,5,5,4,3,3,3,3,3,3,5,51,34.0,satisfied +85031,73039,Male,Loyal Customer,64,Personal Travel,Eco,1089,4,4,4,2,4,4,4,4,4,1,3,2,4,4,4,0.0,satisfied +85032,76737,Male,Loyal Customer,52,Business travel,Business,3037,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +85033,112302,Female,Loyal Customer,26,Personal Travel,Eco,1671,2,2,3,4,5,3,5,5,2,4,4,2,4,5,7,0.0,neutral or dissatisfied +85034,33658,Female,Loyal Customer,51,Business travel,Eco Plus,399,3,2,2,2,1,3,4,3,3,3,3,2,3,4,0,3.0,neutral or dissatisfied +85035,35241,Male,Loyal Customer,27,Business travel,Business,1080,5,5,5,5,5,4,5,5,4,3,2,3,1,5,20,17.0,satisfied +85036,59312,Male,Loyal Customer,43,Business travel,Business,2399,3,3,3,3,3,4,4,4,4,4,4,5,4,4,65,59.0,satisfied +85037,11455,Female,Loyal Customer,38,Business travel,Eco Plus,429,3,4,4,4,3,3,3,3,2,4,4,2,3,3,22,29.0,neutral or dissatisfied +85038,99928,Female,Loyal Customer,43,Business travel,Business,3524,2,2,2,2,3,4,3,2,2,2,2,4,2,3,9,0.0,neutral or dissatisfied +85039,92096,Female,Loyal Customer,55,Business travel,Business,1135,1,0,0,3,5,3,4,1,1,0,1,4,1,1,45,44.0,neutral or dissatisfied +85040,25327,Female,Loyal Customer,53,Business travel,Business,3533,4,4,4,4,4,3,4,2,2,2,2,2,2,4,0,0.0,satisfied +85041,31208,Male,Loyal Customer,27,Business travel,Business,628,1,3,3,3,1,1,1,1,4,1,3,3,4,1,33,48.0,neutral or dissatisfied +85042,11619,Female,Loyal Customer,70,Personal Travel,Eco,771,1,1,0,3,3,3,3,5,5,0,5,1,5,2,1,0.0,neutral or dissatisfied +85043,70767,Male,Loyal Customer,47,Personal Travel,Business,328,1,0,1,1,4,4,5,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +85044,85631,Female,Loyal Customer,44,Personal Travel,Eco,192,2,4,2,5,2,4,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +85045,41199,Female,Loyal Customer,36,Business travel,Eco,1091,4,4,4,4,4,4,4,4,2,2,2,4,4,4,0,0.0,satisfied +85046,122803,Female,disloyal Customer,25,Business travel,Business,599,2,0,2,2,3,2,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +85047,92142,Female,Loyal Customer,48,Business travel,Business,1535,5,5,5,5,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +85048,17550,Male,Loyal Customer,37,Business travel,Business,3651,2,2,2,2,4,1,2,5,5,4,5,2,5,1,94,80.0,satisfied +85049,5243,Male,Loyal Customer,52,Business travel,Business,3975,4,4,4,4,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +85050,12642,Male,Loyal Customer,75,Business travel,Eco,444,3,2,2,2,3,3,3,3,1,3,4,2,4,3,0,0.0,neutral or dissatisfied +85051,45982,Female,disloyal Customer,37,Business travel,Eco,483,3,2,3,4,4,3,4,4,1,2,3,2,4,4,0,8.0,neutral or dissatisfied +85052,72407,Female,Loyal Customer,31,Business travel,Business,1119,4,4,4,4,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +85053,57214,Female,disloyal Customer,20,Business travel,Eco,1087,1,1,1,3,1,1,1,1,3,3,2,3,3,1,26,21.0,neutral or dissatisfied +85054,79514,Female,disloyal Customer,30,Business travel,Business,762,0,0,0,4,1,0,1,1,3,2,4,4,5,1,0,1.0,satisfied +85055,16764,Female,Loyal Customer,34,Business travel,Eco,569,1,5,5,5,1,1,1,1,3,2,3,2,4,1,7,0.0,neutral or dissatisfied +85056,42870,Female,Loyal Customer,27,Business travel,Business,867,2,4,4,4,2,2,2,2,1,3,3,4,3,2,0,33.0,neutral or dissatisfied +85057,8599,Male,Loyal Customer,35,Business travel,Eco Plus,109,5,5,5,5,5,4,5,5,2,1,3,2,3,5,0,0.0,neutral or dissatisfied +85058,15060,Female,Loyal Customer,39,Personal Travel,Eco,576,2,5,2,3,3,2,3,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +85059,105402,Male,Loyal Customer,15,Personal Travel,Eco,369,5,5,5,4,3,5,5,3,1,3,3,2,4,3,0,0.0,satisfied +85060,85293,Male,Loyal Customer,44,Personal Travel,Eco,696,2,1,2,4,1,2,1,1,3,4,4,4,3,1,0,0.0,neutral or dissatisfied +85061,115275,Male,disloyal Customer,47,Business travel,Eco,390,2,3,2,3,1,2,1,1,2,1,3,3,3,1,0,0.0,neutral or dissatisfied +85062,34735,Male,disloyal Customer,37,Business travel,Eco,264,2,3,2,3,4,2,4,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +85063,110381,Male,disloyal Customer,25,Business travel,Eco,925,3,3,3,4,2,3,2,2,2,3,3,3,3,2,9,17.0,neutral or dissatisfied +85064,20168,Male,Loyal Customer,26,Business travel,Eco,403,0,5,0,5,4,0,4,4,4,4,2,3,2,4,88,69.0,satisfied +85065,92829,Male,Loyal Customer,23,Personal Travel,Eco,1541,1,5,1,2,4,1,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +85066,91071,Female,Loyal Customer,15,Personal Travel,Eco,404,2,2,2,4,5,2,1,5,3,5,4,4,4,5,0,23.0,neutral or dissatisfied +85067,117888,Female,Loyal Customer,56,Business travel,Business,2955,3,3,3,3,2,5,4,4,4,4,4,5,4,4,9,8.0,satisfied +85068,29269,Female,disloyal Customer,23,Business travel,Eco,859,5,5,5,1,5,5,5,5,3,2,4,4,5,5,0,4.0,satisfied +85069,68328,Male,Loyal Customer,52,Personal Travel,Eco,2165,4,5,3,2,1,3,1,1,3,4,5,4,5,1,0,0.0,satisfied +85070,64975,Female,disloyal Customer,42,Business travel,Eco,151,1,4,0,3,4,0,4,4,4,4,3,4,4,4,19,17.0,neutral or dissatisfied +85071,122129,Male,Loyal Customer,14,Business travel,Business,2977,1,4,4,4,1,1,1,1,3,1,4,2,4,1,39,61.0,neutral or dissatisfied +85072,73614,Female,Loyal Customer,46,Business travel,Business,1775,3,2,2,2,5,4,4,3,3,3,3,2,3,1,0,5.0,neutral or dissatisfied +85073,46356,Female,Loyal Customer,35,Business travel,Business,1885,2,1,4,1,1,3,3,2,2,3,2,2,2,4,41,40.0,neutral or dissatisfied +85074,120307,Male,Loyal Customer,51,Business travel,Eco,268,3,4,4,4,3,3,3,3,4,4,2,4,1,3,51,55.0,neutral or dissatisfied +85075,123424,Male,Loyal Customer,48,Business travel,Business,1337,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +85076,21579,Female,Loyal Customer,8,Personal Travel,Eco Plus,399,3,5,2,2,4,2,4,4,3,2,5,4,4,4,19,8.0,neutral or dissatisfied +85077,49225,Male,Loyal Customer,33,Business travel,Business,3090,2,2,5,2,4,4,4,4,4,4,5,4,1,4,88,83.0,satisfied +85078,75305,Male,Loyal Customer,33,Business travel,Business,2504,4,4,4,4,4,4,4,4,4,5,5,4,4,4,0,8.0,satisfied +85079,109280,Female,Loyal Customer,52,Business travel,Business,1747,2,2,2,2,2,4,5,5,5,5,5,5,5,5,28,13.0,satisfied +85080,81459,Male,Loyal Customer,44,Business travel,Business,3293,2,2,2,2,3,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +85081,52372,Male,Loyal Customer,45,Personal Travel,Eco,451,2,4,2,3,5,2,5,5,3,3,5,5,4,5,6,11.0,neutral or dissatisfied +85082,47411,Female,Loyal Customer,26,Business travel,Eco,532,0,5,0,5,5,0,5,5,5,3,5,2,4,5,0,0.0,satisfied +85083,127962,Female,Loyal Customer,47,Personal Travel,Eco,1999,3,4,3,4,5,3,4,1,1,3,1,5,1,3,0,15.0,neutral or dissatisfied +85084,1406,Male,Loyal Customer,37,Personal Travel,Eco Plus,158,2,4,0,4,5,0,1,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +85085,15777,Female,disloyal Customer,59,Business travel,Eco,198,3,0,3,5,5,3,4,5,4,1,5,5,4,5,0,0.0,neutral or dissatisfied +85086,98554,Male,disloyal Customer,38,Business travel,Business,861,1,1,1,5,3,1,5,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +85087,2009,Male,Loyal Customer,65,Personal Travel,Eco Plus,285,1,5,1,1,2,1,1,2,5,4,4,4,5,2,3,2.0,neutral or dissatisfied +85088,54132,Female,Loyal Customer,29,Business travel,Business,1400,2,2,2,2,5,5,5,5,3,5,2,2,5,5,0,0.0,satisfied +85089,32627,Male,Loyal Customer,60,Business travel,Business,216,0,5,0,2,1,4,4,2,2,2,2,2,2,5,0,0.0,satisfied +85090,83129,Male,Loyal Customer,31,Personal Travel,Eco,983,3,5,3,1,2,3,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +85091,85316,Male,Loyal Customer,8,Personal Travel,Eco,731,3,2,3,3,2,3,3,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +85092,79231,Female,Loyal Customer,58,Business travel,Business,1587,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +85093,89800,Female,disloyal Customer,24,Business travel,Eco,1010,2,2,2,4,2,2,4,2,3,4,4,3,5,2,40,42.0,neutral or dissatisfied +85094,50282,Female,disloyal Customer,36,Business travel,Eco,262,1,2,1,2,1,1,1,1,2,1,2,4,3,1,0,0.0,neutral or dissatisfied +85095,125629,Female,disloyal Customer,36,Business travel,Business,899,4,4,4,3,5,4,5,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +85096,117548,Male,Loyal Customer,57,Business travel,Business,2270,5,5,5,5,2,4,5,2,2,3,2,3,2,4,6,6.0,satisfied +85097,41156,Female,Loyal Customer,68,Personal Travel,Eco,140,2,4,0,3,5,3,4,1,1,0,1,2,1,3,5,0.0,neutral or dissatisfied +85098,60939,Male,disloyal Customer,29,Business travel,Eco,888,4,4,4,3,4,4,5,4,4,2,4,3,3,4,61,53.0,neutral or dissatisfied +85099,65214,Male,Loyal Customer,48,Business travel,Business,3375,2,2,2,2,2,5,5,5,5,5,5,3,5,4,5,0.0,satisfied +85100,78621,Female,disloyal Customer,29,Business travel,Eco,1426,2,2,2,3,4,2,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +85101,93574,Female,Loyal Customer,35,Business travel,Business,159,1,3,3,3,5,3,4,3,3,3,1,3,3,2,8,15.0,neutral or dissatisfied +85102,124282,Male,Loyal Customer,51,Business travel,Business,255,3,3,4,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +85103,122379,Female,Loyal Customer,63,Business travel,Eco,129,1,3,4,4,5,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +85104,51538,Female,Loyal Customer,51,Business travel,Eco,751,4,2,2,2,3,4,2,4,4,4,4,5,4,1,4,7.0,satisfied +85105,128720,Male,Loyal Customer,50,Business travel,Eco,1104,4,4,4,4,4,4,4,4,2,3,2,2,3,4,0,0.0,satisfied +85106,54977,Male,disloyal Customer,44,Business travel,Business,1635,3,3,3,3,4,3,1,4,4,4,4,3,4,4,21,11.0,neutral or dissatisfied +85107,102354,Female,disloyal Customer,24,Business travel,Eco,386,3,3,3,4,4,3,4,4,2,5,4,3,4,4,0,0.0,neutral or dissatisfied +85108,84680,Male,Loyal Customer,44,Business travel,Eco,2182,3,1,1,1,2,3,2,2,2,1,4,2,4,2,1,0.0,neutral or dissatisfied +85109,121847,Female,Loyal Customer,69,Business travel,Eco,449,3,2,2,2,2,3,4,3,3,3,3,3,3,1,2,0.0,neutral or dissatisfied +85110,67469,Male,Loyal Customer,33,Personal Travel,Eco,641,1,5,1,3,5,1,5,5,5,4,4,3,5,5,84,83.0,neutral or dissatisfied +85111,96944,Female,Loyal Customer,46,Business travel,Business,794,5,5,5,5,4,5,5,4,4,4,4,5,4,5,23,18.0,satisfied +85112,38924,Male,Loyal Customer,36,Business travel,Business,2579,3,3,4,3,3,4,2,5,5,5,5,4,5,5,0,0.0,satisfied +85113,31385,Male,Loyal Customer,36,Business travel,Business,895,5,5,5,5,2,4,5,4,4,4,4,1,4,3,58,56.0,satisfied +85114,70597,Male,disloyal Customer,29,Business travel,Business,2611,3,3,3,3,3,3,3,5,2,3,5,3,5,3,11,1.0,neutral or dissatisfied +85115,108670,Male,Loyal Customer,32,Personal Travel,Eco,484,2,3,2,4,4,2,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +85116,10376,Female,Loyal Customer,42,Business travel,Business,2902,3,3,3,3,5,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +85117,26505,Female,Loyal Customer,48,Business travel,Eco,829,2,2,2,2,4,4,3,2,2,2,2,1,2,4,74,68.0,neutral or dissatisfied +85118,67903,Male,Loyal Customer,26,Personal Travel,Eco,1171,2,5,1,4,5,1,5,5,5,2,5,4,5,5,2,0.0,neutral or dissatisfied +85119,102731,Male,Loyal Customer,63,Personal Travel,Eco,255,1,2,1,4,5,1,5,5,3,4,3,1,4,5,1,0.0,neutral or dissatisfied +85120,62660,Male,Loyal Customer,26,Business travel,Business,1846,5,5,2,5,5,5,5,5,4,4,5,4,5,5,0,0.0,satisfied +85121,105565,Male,Loyal Customer,44,Business travel,Business,3759,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +85122,53890,Male,Loyal Customer,69,Personal Travel,Eco,224,4,4,4,4,4,4,4,4,4,2,5,5,5,4,0,15.0,neutral or dissatisfied +85123,109272,Male,Loyal Customer,29,Personal Travel,Eco Plus,616,3,4,3,3,1,3,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +85124,20216,Male,Loyal Customer,53,Business travel,Eco,137,4,3,4,4,4,4,4,4,2,2,2,1,2,4,0,0.0,satisfied +85125,50206,Male,Loyal Customer,55,Business travel,Business,3130,2,3,3,3,1,2,1,3,1,4,3,1,4,1,204,208.0,neutral or dissatisfied +85126,17485,Male,disloyal Customer,25,Business travel,Business,352,0,0,0,2,5,0,1,5,5,5,4,2,5,5,0,5.0,satisfied +85127,94612,Female,Loyal Customer,48,Business travel,Business,3895,4,4,4,4,5,4,4,4,4,4,4,3,4,3,9,8.0,satisfied +85128,74951,Female,Loyal Customer,44,Business travel,Eco,2446,3,4,4,4,1,1,3,3,3,3,3,1,3,1,0,18.0,neutral or dissatisfied +85129,119259,Female,Loyal Customer,14,Personal Travel,Business,214,3,4,3,2,4,3,4,4,3,2,2,3,2,4,0,0.0,neutral or dissatisfied +85130,15033,Female,Loyal Customer,42,Business travel,Business,3848,3,3,3,3,3,1,2,5,5,5,5,3,5,5,0,0.0,satisfied +85131,4441,Male,Loyal Customer,66,Personal Travel,Eco,762,4,3,4,4,5,4,5,5,1,5,1,4,4,5,14,57.0,neutral or dissatisfied +85132,53759,Male,Loyal Customer,51,Business travel,Business,3780,3,3,3,3,5,3,5,5,5,4,5,1,5,1,16,21.0,satisfied +85133,67786,Female,Loyal Customer,25,Business travel,Business,1431,3,5,5,5,3,3,3,3,1,1,3,1,2,3,0,15.0,neutral or dissatisfied +85134,47557,Female,disloyal Customer,41,Business travel,Eco Plus,584,4,4,4,3,5,4,5,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +85135,96774,Male,Loyal Customer,27,Business travel,Business,2808,4,4,1,4,4,4,4,4,4,4,5,3,4,4,58,46.0,satisfied +85136,85702,Female,disloyal Customer,37,Business travel,Eco,1147,3,3,3,2,1,3,1,1,4,2,1,3,1,1,0,0.0,neutral or dissatisfied +85137,93808,Male,Loyal Customer,47,Business travel,Business,3557,3,3,5,3,2,5,5,5,5,5,5,3,5,5,28,23.0,satisfied +85138,124461,Female,Loyal Customer,28,Business travel,Business,3930,2,1,1,1,2,3,2,2,4,5,3,1,3,2,53,109.0,neutral or dissatisfied +85139,113823,Male,Loyal Customer,23,Personal Travel,Eco Plus,258,4,3,0,3,5,0,5,5,5,3,2,3,4,5,59,67.0,neutral or dissatisfied +85140,64980,Female,disloyal Customer,26,Business travel,Eco,247,4,0,4,4,5,4,5,5,5,3,5,1,2,5,0,0.0,neutral or dissatisfied +85141,53206,Male,Loyal Customer,32,Business travel,Business,2385,1,1,1,1,3,3,3,3,3,1,5,3,3,3,25,0.0,satisfied +85142,45054,Male,Loyal Customer,60,Business travel,Business,3899,4,4,4,4,1,2,5,4,4,4,4,1,4,2,0,0.0,satisfied +85143,28730,Female,Loyal Customer,40,Business travel,Business,2149,1,1,1,1,4,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +85144,89060,Male,Loyal Customer,46,Business travel,Business,1947,3,3,5,3,5,4,5,5,5,5,5,4,5,4,23,18.0,satisfied +85145,47231,Male,Loyal Customer,36,Business travel,Eco Plus,620,5,3,3,3,5,5,5,5,1,2,1,3,4,5,2,4.0,satisfied +85146,4614,Female,Loyal Customer,55,Business travel,Eco,719,5,3,2,3,3,3,1,5,5,5,5,1,5,2,0,0.0,satisfied +85147,122704,Female,Loyal Customer,18,Personal Travel,Eco Plus,361,3,5,3,3,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +85148,75757,Female,disloyal Customer,27,Business travel,Eco,868,2,2,2,3,4,2,2,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +85149,48332,Female,disloyal Customer,26,Business travel,Eco,522,1,0,1,1,2,1,2,2,5,5,1,1,1,2,62,57.0,neutral or dissatisfied +85150,11324,Male,Loyal Customer,61,Personal Travel,Eco,295,4,2,4,4,1,4,1,1,4,2,4,4,3,1,5,0.0,neutral or dissatisfied +85151,76902,Female,Loyal Customer,30,Personal Travel,Eco,630,1,4,1,3,3,1,1,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +85152,8987,Male,Loyal Customer,35,Personal Travel,Eco,799,4,3,4,1,2,4,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +85153,72002,Female,Loyal Customer,54,Personal Travel,Eco,1440,4,5,5,3,2,4,4,2,2,5,2,3,2,3,0,0.0,neutral or dissatisfied +85154,20212,Female,Loyal Customer,40,Business travel,Business,2343,1,1,1,1,3,3,4,5,5,5,5,4,5,1,89,87.0,satisfied +85155,30082,Female,Loyal Customer,56,Personal Travel,Eco,548,2,5,2,1,2,4,4,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +85156,99041,Male,Loyal Customer,49,Business travel,Business,181,5,5,5,5,4,4,4,5,5,5,4,3,5,5,50,49.0,satisfied +85157,12059,Male,Loyal Customer,52,Personal Travel,Eco,376,2,4,4,4,3,4,3,3,4,2,5,3,5,3,4,0.0,neutral or dissatisfied +85158,5293,Male,Loyal Customer,8,Personal Travel,Eco,285,3,1,3,3,5,3,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +85159,102148,Female,Loyal Customer,42,Business travel,Business,1603,4,4,4,4,4,4,5,5,5,5,5,5,5,4,25,18.0,satisfied +85160,45512,Male,Loyal Customer,28,Personal Travel,Eco,774,3,3,3,2,5,3,5,5,4,2,5,2,5,5,20,2.0,neutral or dissatisfied +85161,19184,Female,Loyal Customer,7,Personal Travel,Eco,1024,4,4,4,2,5,4,1,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +85162,100825,Male,Loyal Customer,48,Business travel,Business,711,2,2,2,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +85163,89144,Male,Loyal Customer,17,Business travel,Eco,1892,4,1,3,1,4,4,5,4,2,5,2,2,3,4,0,0.0,satisfied +85164,71169,Female,Loyal Customer,26,Personal Travel,Eco Plus,646,0,3,0,3,4,0,1,4,2,4,3,2,4,4,2,0.0,satisfied +85165,121559,Female,Loyal Customer,45,Business travel,Business,912,2,5,5,5,1,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +85166,2613,Male,Loyal Customer,55,Personal Travel,Eco,181,2,4,0,2,5,0,5,5,4,4,4,5,5,5,37,28.0,neutral or dissatisfied +85167,15028,Female,Loyal Customer,31,Business travel,Business,576,5,5,5,5,4,4,4,4,5,1,3,2,2,4,94,65.0,satisfied +85168,92893,Female,Loyal Customer,41,Business travel,Business,3039,0,4,0,5,4,5,5,1,1,1,1,5,1,3,45,40.0,satisfied +85169,124093,Female,Loyal Customer,54,Business travel,Business,2898,2,2,2,2,2,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +85170,44843,Female,Loyal Customer,41,Business travel,Business,2903,3,3,3,3,2,3,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +85171,126254,Female,disloyal Customer,21,Business travel,Eco,190,4,5,4,3,5,4,5,5,1,5,1,3,1,5,0,1.0,satisfied +85172,90496,Female,Loyal Customer,52,Business travel,Business,3398,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +85173,106357,Female,disloyal Customer,34,Business travel,Business,551,4,4,4,5,4,4,4,4,4,2,4,5,5,4,10,6.0,neutral or dissatisfied +85174,90528,Female,Loyal Customer,39,Business travel,Business,404,1,1,1,1,4,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +85175,9780,Male,Loyal Customer,29,Personal Travel,Eco,456,2,5,3,4,5,3,5,5,4,3,5,5,4,5,1,0.0,neutral or dissatisfied +85176,85115,Male,Loyal Customer,26,Business travel,Business,696,4,4,2,4,4,4,4,4,3,4,4,3,4,4,30,25.0,satisfied +85177,119906,Male,Loyal Customer,35,Personal Travel,Eco Plus,912,2,5,2,1,5,2,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +85178,9948,Female,Loyal Customer,49,Business travel,Business,3209,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +85179,10508,Female,Loyal Customer,38,Business travel,Eco,224,1,4,4,4,1,1,1,1,2,3,4,3,3,1,0,0.0,neutral or dissatisfied +85180,48954,Male,Loyal Customer,24,Business travel,Business,447,5,5,5,5,5,5,5,5,2,3,3,5,4,5,79,89.0,satisfied +85181,56549,Female,Loyal Customer,40,Business travel,Business,1065,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +85182,18888,Male,disloyal Customer,27,Business travel,Eco,500,2,1,1,3,3,1,5,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +85183,30375,Female,Loyal Customer,47,Business travel,Eco,641,1,4,3,4,4,3,3,1,1,1,1,4,1,2,0,2.0,neutral or dissatisfied +85184,26694,Female,Loyal Customer,42,Personal Travel,Eco,270,2,0,0,3,4,4,1,3,3,0,2,1,3,2,0,0.0,neutral or dissatisfied +85185,68468,Male,Loyal Customer,32,Business travel,Eco,1303,3,3,3,3,3,3,3,3,2,3,2,2,3,3,0,40.0,neutral or dissatisfied +85186,100536,Male,Loyal Customer,43,Personal Travel,Eco,759,3,5,3,2,1,3,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +85187,61677,Male,Loyal Customer,39,Business travel,Business,1346,3,3,3,3,5,5,4,1,1,2,1,5,1,5,0,0.0,satisfied +85188,54801,Male,Loyal Customer,32,Business travel,Business,862,4,4,4,4,5,4,5,5,4,1,4,4,3,5,0,0.0,satisfied +85189,125174,Female,Loyal Customer,33,Business travel,Eco Plus,1089,2,1,1,1,2,2,2,2,1,2,4,3,3,2,53,37.0,neutral or dissatisfied +85190,40361,Male,disloyal Customer,28,Business travel,Eco,1250,4,4,4,3,5,4,5,5,3,3,2,1,2,5,0,7.0,neutral or dissatisfied +85191,6724,Female,Loyal Customer,40,Business travel,Business,1574,2,2,2,2,2,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +85192,6859,Male,Loyal Customer,32,Business travel,Business,2607,1,1,1,1,1,1,1,1,3,2,3,4,3,1,5,13.0,neutral or dissatisfied +85193,104986,Male,Loyal Customer,36,Business travel,Business,337,0,1,1,2,2,4,4,2,2,2,2,5,2,3,0,3.0,satisfied +85194,110970,Male,Loyal Customer,47,Personal Travel,Business,319,1,3,1,3,2,3,3,1,1,1,1,1,1,4,56,59.0,neutral or dissatisfied +85195,86556,Female,disloyal Customer,44,Business travel,Business,762,4,4,4,1,3,4,3,3,4,3,5,5,5,3,0,0.0,satisfied +85196,46641,Female,Loyal Customer,50,Business travel,Business,1766,3,2,2,2,3,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +85197,41910,Male,disloyal Customer,40,Business travel,Eco,129,3,0,3,1,5,3,5,5,4,4,5,5,5,5,0,1.0,neutral or dissatisfied +85198,24399,Female,Loyal Customer,58,Personal Travel,Eco,1066,3,4,3,3,3,4,4,3,3,3,2,3,3,4,33,36.0,neutral or dissatisfied +85199,103802,Female,Loyal Customer,57,Business travel,Business,882,1,1,1,1,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +85200,26198,Female,Loyal Customer,42,Business travel,Eco,581,2,4,4,4,3,4,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +85201,99455,Male,Loyal Customer,48,Business travel,Business,307,4,2,4,4,4,4,4,4,4,5,4,4,5,4,132,180.0,satisfied +85202,72032,Female,Loyal Customer,51,Personal Travel,Eco,3711,2,5,2,5,2,1,1,5,5,4,2,1,4,1,0,0.0,neutral or dissatisfied +85203,100381,Male,Loyal Customer,47,Personal Travel,Eco,1165,3,3,2,3,3,2,3,3,4,2,3,3,2,3,33,29.0,neutral or dissatisfied +85204,85724,Male,disloyal Customer,49,Business travel,Business,666,1,1,1,4,3,1,2,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +85205,98617,Male,Loyal Customer,51,Business travel,Business,873,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +85206,74045,Male,Loyal Customer,8,Business travel,Eco,1194,2,3,3,3,2,2,1,2,1,5,2,2,3,2,0,0.0,neutral or dissatisfied +85207,41698,Male,Loyal Customer,46,Personal Travel,Eco,843,4,5,4,1,4,4,4,4,4,2,5,4,5,4,0,8.0,neutral or dissatisfied +85208,123908,Female,Loyal Customer,69,Personal Travel,Eco,546,2,5,2,4,3,4,5,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +85209,58718,Male,Loyal Customer,53,Business travel,Business,3646,1,1,5,1,2,5,5,4,4,4,4,3,4,4,11,15.0,satisfied +85210,96985,Female,Loyal Customer,50,Business travel,Eco,794,3,3,3,3,4,3,3,3,3,3,3,2,3,2,94,79.0,neutral or dissatisfied +85211,100189,Female,Loyal Customer,50,Personal Travel,Eco,523,3,5,3,4,5,5,1,1,1,3,1,4,1,4,47,67.0,neutral or dissatisfied +85212,123807,Male,Loyal Customer,39,Business travel,Business,3007,1,1,1,1,3,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +85213,7129,Male,Loyal Customer,38,Business travel,Business,2809,3,3,3,3,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +85214,51022,Female,Loyal Customer,30,Personal Travel,Eco,337,2,4,2,3,1,2,1,1,4,2,5,5,4,1,21,10.0,neutral or dissatisfied +85215,69068,Male,disloyal Customer,35,Business travel,Eco,1389,2,2,2,2,4,2,1,4,3,5,2,3,3,4,1,9.0,neutral or dissatisfied +85216,34832,Female,disloyal Customer,25,Business travel,Eco Plus,209,1,3,1,3,4,1,4,4,3,4,3,3,3,4,115,112.0,neutral or dissatisfied +85217,101602,Female,Loyal Customer,39,Business travel,Business,1371,4,4,4,4,2,5,5,2,2,2,2,3,2,3,23,3.0,satisfied +85218,86746,Male,Loyal Customer,39,Business travel,Business,2957,5,5,5,5,5,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +85219,10262,Female,Loyal Customer,63,Personal Travel,Business,216,3,1,3,4,2,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +85220,117362,Female,Loyal Customer,60,Personal Travel,Eco,296,1,5,3,1,3,4,4,3,3,5,5,4,3,4,254,265.0,neutral or dissatisfied +85221,125683,Female,Loyal Customer,52,Business travel,Business,3404,1,4,4,4,4,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +85222,122124,Female,Loyal Customer,44,Business travel,Business,2865,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +85223,38444,Female,Loyal Customer,36,Business travel,Business,188,1,1,1,1,4,4,4,3,3,4,4,1,3,3,6,0.0,satisfied +85224,120791,Male,Loyal Customer,18,Personal Travel,Eco,678,3,5,3,3,4,3,1,4,2,3,1,5,5,4,0,0.0,neutral or dissatisfied +85225,99003,Female,Loyal Customer,53,Business travel,Business,1914,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +85226,117103,Female,Loyal Customer,35,Business travel,Eco,370,1,5,5,5,1,1,1,1,3,4,4,2,4,1,17,14.0,neutral or dissatisfied +85227,119270,Male,disloyal Customer,42,Business travel,Business,214,3,3,3,4,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +85228,8857,Male,Loyal Customer,45,Business travel,Business,539,4,4,4,4,2,5,4,5,5,5,5,4,5,4,33,27.0,satisfied +85229,119221,Male,Loyal Customer,64,Personal Travel,Eco,290,3,5,3,4,4,3,4,4,4,2,5,3,5,4,0,0.0,neutral or dissatisfied +85230,54760,Female,Loyal Customer,70,Business travel,Eco Plus,787,4,2,2,2,4,3,3,4,4,4,4,2,4,1,22,16.0,neutral or dissatisfied +85231,128520,Female,Loyal Customer,11,Personal Travel,Eco,647,2,1,1,3,3,1,5,3,1,1,4,4,3,3,3,0.0,neutral or dissatisfied +85232,107575,Male,Loyal Customer,57,Personal Travel,Eco,1521,4,4,4,3,5,4,2,5,3,2,5,3,5,5,5,6.0,neutral or dissatisfied +85233,102687,Female,Loyal Customer,36,Business travel,Business,365,3,4,4,4,2,2,3,3,3,3,3,3,3,3,51,47.0,neutral or dissatisfied +85234,104462,Male,disloyal Customer,37,Business travel,Eco,615,1,1,1,4,1,1,1,1,4,4,4,3,4,1,14,28.0,neutral or dissatisfied +85235,45724,Female,Loyal Customer,24,Personal Travel,Eco,852,1,5,1,3,3,1,3,3,4,4,5,3,4,3,0,6.0,neutral or dissatisfied +85236,91628,Male,Loyal Customer,56,Business travel,Business,3301,3,2,2,2,3,3,3,3,3,3,3,3,3,3,1,7.0,neutral or dissatisfied +85237,106028,Female,Loyal Customer,66,Personal Travel,Eco,682,3,5,3,4,3,4,4,2,2,3,2,5,2,4,2,13.0,neutral or dissatisfied +85238,23089,Male,Loyal Customer,48,Personal Travel,Eco,864,1,4,1,5,4,1,4,4,3,5,5,4,5,4,6,0.0,neutral or dissatisfied +85239,20468,Female,Loyal Customer,61,Personal Travel,Eco,177,4,3,4,4,5,4,3,2,2,4,2,3,2,2,3,24.0,neutral or dissatisfied +85240,62514,Female,Loyal Customer,23,Business travel,Business,1846,5,5,5,5,3,3,3,3,5,4,4,4,4,3,1,0.0,satisfied +85241,50806,Male,Loyal Customer,17,Personal Travel,Eco,373,4,3,4,3,4,4,4,4,4,2,2,5,3,4,0,0.0,neutral or dissatisfied +85242,47497,Female,Loyal Customer,33,Personal Travel,Eco,590,3,1,3,2,5,3,5,5,1,2,3,2,2,5,35,23.0,neutral or dissatisfied +85243,67919,Female,Loyal Customer,44,Personal Travel,Eco,1235,2,5,2,4,1,5,4,2,2,2,2,1,2,5,47,34.0,neutral or dissatisfied +85244,62993,Male,Loyal Customer,45,Business travel,Eco,967,3,1,1,1,3,3,3,3,3,5,4,4,3,3,1,0.0,neutral or dissatisfied +85245,9444,Female,disloyal Customer,24,Business travel,Eco,310,1,3,1,3,5,1,5,5,4,5,4,3,3,5,0,10.0,neutral or dissatisfied +85246,113317,Female,disloyal Customer,54,Business travel,Business,226,4,4,4,2,3,4,3,3,3,4,5,4,5,3,11,7.0,neutral or dissatisfied +85247,22352,Female,disloyal Customer,33,Business travel,Eco,143,2,4,2,1,4,2,4,4,2,4,4,4,1,4,0,0.0,neutral or dissatisfied +85248,59838,Male,Loyal Customer,35,Business travel,Business,1023,1,1,1,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +85249,24560,Male,Loyal Customer,65,Business travel,Business,3989,1,3,3,3,4,3,4,1,1,1,1,2,1,3,24,13.0,neutral or dissatisfied +85250,120491,Female,Loyal Customer,41,Personal Travel,Eco,449,4,5,4,4,5,4,5,5,5,4,5,3,5,5,0,24.0,neutral or dissatisfied +85251,20528,Male,Loyal Customer,38,Business travel,Eco,633,4,3,3,3,4,4,4,4,2,2,1,4,4,4,0,0.0,satisfied +85252,99098,Male,Loyal Customer,57,Business travel,Eco,453,2,1,1,1,2,2,2,2,1,1,1,3,2,2,5,0.0,neutral or dissatisfied +85253,52214,Female,Loyal Customer,54,Business travel,Eco,370,3,1,1,1,4,3,4,3,3,3,3,2,3,3,1,21.0,neutral or dissatisfied +85254,888,Male,Loyal Customer,42,Business travel,Business,134,4,3,3,3,4,3,4,4,4,4,4,1,4,3,0,1.0,neutral or dissatisfied +85255,40090,Female,Loyal Customer,43,Business travel,Eco,422,4,1,1,1,2,4,1,4,4,4,4,2,4,5,0,0.0,satisfied +85256,121200,Male,Loyal Customer,41,Personal Travel,Eco,2521,2,3,2,4,2,1,3,3,2,3,3,3,1,3,0,16.0,neutral or dissatisfied +85257,99622,Female,Loyal Customer,40,Business travel,Business,1802,1,1,1,1,2,5,4,4,4,4,4,4,4,5,23,5.0,satisfied +85258,84876,Male,Loyal Customer,65,Personal Travel,Eco,547,2,1,2,4,1,2,1,1,4,5,4,3,3,1,0,0.0,neutral or dissatisfied +85259,98877,Female,disloyal Customer,28,Business travel,Eco,991,3,3,3,3,2,3,2,2,3,5,3,1,3,2,5,5.0,neutral or dissatisfied +85260,79984,Male,Loyal Customer,7,Personal Travel,Eco,1005,3,5,3,2,4,3,4,4,1,2,1,4,2,4,2,0.0,neutral or dissatisfied +85261,79615,Female,disloyal Customer,26,Business travel,Business,762,0,0,0,1,4,0,4,4,4,2,4,3,4,4,0,0.0,satisfied +85262,25056,Male,Loyal Customer,40,Business travel,Eco,594,3,5,5,5,3,3,3,3,4,2,4,4,3,3,0,20.0,neutral or dissatisfied +85263,104482,Female,Loyal Customer,60,Business travel,Business,3873,3,3,3,3,5,4,5,4,4,4,4,4,4,4,23,0.0,satisfied +85264,41964,Male,Loyal Customer,27,Business travel,Business,575,1,2,2,2,1,1,1,1,4,5,4,4,3,1,0,0.0,neutral or dissatisfied +85265,45133,Female,disloyal Customer,39,Business travel,Eco,139,4,2,4,4,4,4,4,4,2,1,3,3,3,4,0,11.0,satisfied +85266,19868,Female,Loyal Customer,48,Business travel,Business,2498,0,0,0,1,3,4,4,1,1,1,1,5,1,4,25,19.0,satisfied +85267,351,Male,Loyal Customer,57,Business travel,Business,821,2,2,2,2,3,4,3,2,2,2,2,1,2,2,31,30.0,neutral or dissatisfied +85268,78322,Female,disloyal Customer,50,Business travel,Business,1547,1,1,1,1,4,1,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +85269,60956,Female,Loyal Customer,40,Business travel,Business,2283,4,1,2,1,2,4,3,4,4,4,4,1,4,1,1,0.0,neutral or dissatisfied +85270,120721,Female,Loyal Customer,56,Business travel,Eco,90,4,2,2,2,5,4,3,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +85271,108497,Male,Loyal Customer,53,Business travel,Business,287,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +85272,74642,Male,Loyal Customer,51,Business travel,Business,1031,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +85273,23233,Male,Loyal Customer,37,Business travel,Eco,116,4,2,2,2,4,4,4,4,2,4,3,4,3,4,0,0.0,neutral or dissatisfied +85274,35608,Female,Loyal Customer,43,Personal Travel,Eco Plus,1102,1,1,0,3,1,3,4,1,1,0,1,3,1,1,0,0.0,neutral or dissatisfied +85275,107642,Female,disloyal Customer,40,Business travel,Business,405,3,3,3,3,3,3,3,4,2,4,4,3,3,3,132,164.0,neutral or dissatisfied +85276,78307,Female,disloyal Customer,23,Business travel,Business,1598,4,0,4,4,3,4,3,3,4,2,4,5,4,3,0,0.0,satisfied +85277,72410,Male,disloyal Customer,35,Business travel,Business,1121,2,2,2,4,4,2,4,4,5,5,5,5,4,4,34,37.0,neutral or dissatisfied +85278,12835,Female,Loyal Customer,54,Business travel,Eco,241,4,1,1,1,3,2,4,4,4,4,4,4,4,4,55,55.0,satisfied +85279,52735,Male,Loyal Customer,33,Business travel,Business,2306,4,4,4,4,5,4,5,5,1,5,4,3,5,5,3,5.0,satisfied +85280,70947,Male,Loyal Customer,37,Personal Travel,Eco,612,1,5,0,3,5,0,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +85281,95763,Male,Loyal Customer,7,Personal Travel,Eco,181,4,1,4,2,2,4,2,2,1,4,3,2,3,2,7,23.0,neutral or dissatisfied +85282,103313,Female,Loyal Customer,42,Business travel,Business,2750,4,3,4,3,3,3,3,4,4,4,4,4,4,1,4,0.0,neutral or dissatisfied +85283,57647,Female,Loyal Customer,19,Business travel,Business,200,4,1,1,1,1,1,4,1,1,1,3,1,3,1,55,36.0,neutral or dissatisfied +85284,21846,Male,Loyal Customer,51,Business travel,Business,1511,2,4,4,4,5,4,3,2,2,2,2,2,2,4,49,45.0,neutral or dissatisfied +85285,118488,Male,Loyal Customer,46,Business travel,Business,325,1,1,1,1,2,4,4,5,5,5,5,4,5,3,38,36.0,satisfied +85286,125126,Male,Loyal Customer,42,Personal Travel,Eco,361,1,3,1,3,3,1,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +85287,64333,Male,disloyal Customer,26,Business travel,Eco,1192,2,2,2,4,5,2,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +85288,38691,Male,Loyal Customer,42,Business travel,Business,2583,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +85289,75040,Male,Loyal Customer,27,Personal Travel,Eco,236,3,2,3,3,1,3,1,1,1,2,3,2,4,1,41,27.0,neutral or dissatisfied +85290,86651,Male,Loyal Customer,8,Personal Travel,Eco,746,2,4,2,4,5,2,5,5,4,5,4,4,5,5,10,0.0,neutral or dissatisfied +85291,92588,Male,Loyal Customer,53,Business travel,Business,2158,1,1,1,1,4,4,5,5,5,5,5,5,5,4,80,66.0,satisfied +85292,60519,Female,Loyal Customer,27,Personal Travel,Eco,862,4,4,4,2,2,4,2,2,4,3,5,5,5,2,6,0.0,neutral or dissatisfied +85293,85544,Male,Loyal Customer,31,Business travel,Business,259,3,3,3,3,5,5,5,5,5,3,5,3,4,5,10,11.0,satisfied +85294,44698,Male,Loyal Customer,58,Personal Travel,Eco,67,3,4,0,1,2,0,5,2,3,5,4,4,4,2,20,12.0,neutral or dissatisfied +85295,109136,Male,Loyal Customer,41,Business travel,Business,1636,2,2,2,2,3,5,5,4,4,4,4,5,4,4,2,0.0,satisfied +85296,357,Female,Loyal Customer,43,Business travel,Business,102,2,2,2,2,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +85297,92356,Male,Loyal Customer,66,Personal Travel,Eco,2504,1,3,1,3,1,3,3,3,4,4,4,3,4,3,9,42.0,neutral or dissatisfied +85298,120530,Male,Loyal Customer,12,Personal Travel,Eco,96,4,4,4,4,2,4,5,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +85299,70182,Male,Loyal Customer,59,Business travel,Business,258,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +85300,47828,Male,Loyal Customer,76,Business travel,Eco,451,1,0,0,3,4,1,4,4,2,2,2,3,3,4,1,0.0,neutral or dissatisfied +85301,124580,Male,disloyal Customer,20,Business travel,Eco,500,5,0,5,1,3,5,3,3,3,2,5,5,5,3,8,10.0,satisfied +85302,77164,Female,Loyal Customer,58,Personal Travel,Eco,1450,4,3,4,4,4,3,4,2,2,4,2,1,2,4,0,0.0,satisfied +85303,108702,Female,Loyal Customer,64,Personal Travel,Eco Plus,577,3,4,3,3,5,5,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +85304,69614,Female,disloyal Customer,39,Business travel,Business,2586,1,1,1,4,1,3,3,3,3,5,5,3,5,3,73,78.0,neutral or dissatisfied +85305,79544,Male,Loyal Customer,57,Business travel,Business,2756,1,1,1,1,4,4,5,4,4,4,4,4,4,3,8,9.0,satisfied +85306,43948,Female,Loyal Customer,35,Business travel,Eco,473,4,5,5,5,4,4,4,4,5,4,3,3,3,4,5,47.0,satisfied +85307,15960,Male,Loyal Customer,43,Personal Travel,Eco,607,2,5,2,3,1,2,1,1,5,5,4,3,5,1,16,53.0,neutral or dissatisfied +85308,66958,Male,Loyal Customer,42,Business travel,Business,1121,1,1,3,1,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +85309,47317,Female,Loyal Customer,41,Business travel,Eco,558,4,4,4,4,4,4,4,4,1,1,3,5,1,4,0,0.0,satisfied +85310,23343,Female,Loyal Customer,26,Personal Travel,Eco,563,2,1,2,2,4,2,4,4,3,4,2,4,3,4,22,5.0,neutral or dissatisfied +85311,11834,Female,Loyal Customer,62,Personal Travel,Eco,986,2,4,2,2,5,4,5,5,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +85312,53889,Male,Loyal Customer,49,Personal Travel,Eco,191,3,5,3,5,3,3,3,3,3,2,5,5,5,3,5,0.0,neutral or dissatisfied +85313,76640,Male,Loyal Customer,67,Personal Travel,Eco,481,3,4,3,4,5,3,5,5,4,3,5,2,2,5,15,8.0,neutral or dissatisfied +85314,55565,Female,Loyal Customer,49,Business travel,Business,2252,5,5,5,5,5,4,4,4,4,5,4,3,4,5,2,0.0,satisfied +85315,44722,Female,Loyal Customer,7,Personal Travel,Eco,67,4,5,4,5,4,4,4,4,3,5,4,3,4,4,0,5.0,neutral or dissatisfied +85316,91455,Male,Loyal Customer,45,Business travel,Eco,859,1,2,3,2,1,1,1,1,4,5,4,4,4,1,29,25.0,neutral or dissatisfied +85317,36194,Female,Loyal Customer,24,Business travel,Business,3591,3,3,3,3,5,5,5,5,4,1,2,5,4,5,0,0.0,satisfied +85318,7280,Female,Loyal Customer,19,Personal Travel,Eco,135,3,4,3,4,3,5,5,4,2,4,5,5,3,5,91,168.0,neutral or dissatisfied +85319,40248,Female,disloyal Customer,23,Business travel,Eco,347,2,3,2,3,2,2,2,2,2,4,3,1,4,2,0,9.0,neutral or dissatisfied +85320,74239,Female,Loyal Customer,14,Personal Travel,Eco Plus,888,3,4,3,4,2,3,1,2,2,1,4,2,4,2,0,7.0,neutral or dissatisfied +85321,43939,Female,Loyal Customer,51,Personal Travel,Eco Plus,199,3,5,0,1,5,4,5,3,3,0,3,3,3,4,0,0.0,neutral or dissatisfied +85322,103069,Male,Loyal Customer,43,Business travel,Eco,146,4,2,2,2,4,4,4,4,2,4,3,1,3,4,10,9.0,satisfied +85323,39802,Female,Loyal Customer,55,Business travel,Business,2820,0,0,0,3,1,3,4,1,1,1,1,2,1,4,0,0.0,satisfied +85324,39162,Female,Loyal Customer,36,Business travel,Eco,237,3,3,3,3,3,3,3,3,1,3,3,1,4,3,0,26.0,neutral or dissatisfied +85325,87754,Female,Loyal Customer,35,Business travel,Business,3127,2,2,2,2,3,5,5,4,4,4,4,4,4,4,4,0.0,satisfied +85326,67038,Male,disloyal Customer,23,Business travel,Business,1121,4,4,4,2,2,4,2,2,3,4,4,3,4,2,0,0.0,satisfied +85327,80919,Female,Loyal Customer,48,Business travel,Eco,341,3,3,3,3,4,4,4,3,3,3,3,3,3,3,6,0.0,neutral or dissatisfied +85328,15220,Male,Loyal Customer,33,Business travel,Business,3323,4,4,4,4,5,5,5,5,2,2,4,5,5,5,43,45.0,satisfied +85329,64904,Female,Loyal Customer,46,Business travel,Business,3822,1,4,4,4,5,4,4,1,1,1,1,4,1,3,18,8.0,neutral or dissatisfied +85330,121080,Male,Loyal Customer,15,Personal Travel,Eco Plus,861,1,3,1,3,1,1,3,1,3,4,3,2,3,1,2,10.0,neutral or dissatisfied +85331,87587,Male,Loyal Customer,64,Personal Travel,Eco,432,1,2,1,4,3,1,2,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +85332,90649,Male,Loyal Customer,49,Business travel,Business,594,2,2,3,2,5,5,4,5,5,5,5,4,5,4,0,1.0,satisfied +85333,22551,Female,Loyal Customer,45,Business travel,Business,3851,4,4,4,4,3,4,5,4,4,4,4,4,4,4,105,94.0,satisfied +85334,90373,Male,Loyal Customer,62,Business travel,Business,404,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,5.0,satisfied +85335,104160,Female,Loyal Customer,46,Business travel,Business,2740,0,0,0,2,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +85336,7244,Female,Loyal Customer,62,Personal Travel,Eco,135,2,5,2,4,5,5,4,2,2,2,1,5,2,4,0,0.0,neutral or dissatisfied +85337,24067,Female,Loyal Customer,40,Personal Travel,Eco Plus,562,5,3,5,3,4,5,1,4,3,3,4,1,3,4,41,36.0,satisfied +85338,113282,Female,Loyal Customer,40,Business travel,Business,3011,4,4,4,4,5,5,4,4,4,4,4,3,4,3,17,12.0,satisfied +85339,15233,Female,Loyal Customer,52,Business travel,Business,2537,3,5,5,5,2,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +85340,28328,Female,Loyal Customer,49,Business travel,Business,867,3,3,3,3,2,4,1,5,5,5,5,4,5,5,0,0.0,satisfied +85341,18392,Female,Loyal Customer,23,Business travel,Eco,378,5,4,4,4,5,5,4,5,4,2,4,3,5,5,0,0.0,satisfied +85342,18108,Male,Loyal Customer,46,Business travel,Eco,651,3,3,3,3,3,3,3,3,3,4,3,3,4,3,156,147.0,neutral or dissatisfied +85343,26142,Male,Loyal Customer,44,Business travel,Business,581,1,1,1,1,5,1,4,4,4,4,4,4,4,3,21,13.0,satisfied +85344,84636,Female,Loyal Customer,24,Business travel,Eco Plus,707,1,3,3,3,1,1,2,1,1,3,3,2,2,1,0,0.0,neutral or dissatisfied +85345,38597,Female,Loyal Customer,36,Business travel,Business,3871,1,1,1,1,2,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +85346,106176,Female,Loyal Customer,10,Personal Travel,Eco,436,2,2,2,3,4,2,4,4,1,4,3,3,2,4,1,5.0,neutral or dissatisfied +85347,67646,Female,Loyal Customer,59,Business travel,Business,3919,2,2,2,2,4,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +85348,14186,Female,Loyal Customer,33,Business travel,Eco,714,5,3,3,3,5,5,5,2,3,1,5,5,1,5,232,238.0,satisfied +85349,117543,Female,Loyal Customer,56,Business travel,Business,3644,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +85350,99598,Male,Loyal Customer,47,Personal Travel,Eco,829,4,4,5,3,4,5,4,4,4,3,4,5,4,4,36,22.0,neutral or dissatisfied +85351,88668,Male,Loyal Customer,12,Personal Travel,Eco,406,3,5,3,2,1,3,1,1,5,2,5,5,5,1,26,24.0,neutral or dissatisfied +85352,109531,Male,Loyal Customer,67,Business travel,Business,2965,2,2,2,2,4,4,5,4,4,5,4,3,4,1,0,0.0,satisfied +85353,24474,Male,Loyal Customer,42,Business travel,Business,547,2,3,2,3,2,3,3,2,2,2,2,2,2,2,4,9.0,neutral or dissatisfied +85354,53342,Male,Loyal Customer,32,Business travel,Eco,1452,4,1,1,1,4,5,4,4,1,1,4,4,2,4,30,32.0,satisfied +85355,109467,Male,Loyal Customer,46,Business travel,Business,2935,4,4,4,4,4,4,5,4,4,4,4,5,4,5,1,0.0,satisfied +85356,12297,Male,Loyal Customer,39,Business travel,Business,253,2,2,2,2,4,1,2,5,5,5,5,2,5,4,9,13.0,satisfied +85357,21804,Female,disloyal Customer,18,Business travel,Eco,352,3,4,3,3,2,3,2,2,3,3,3,1,3,2,1,24.0,neutral or dissatisfied +85358,114451,Female,Loyal Customer,32,Business travel,Business,308,5,5,5,5,3,4,3,3,4,3,4,4,5,3,2,0.0,satisfied +85359,121242,Female,Loyal Customer,30,Business travel,Eco,1814,1,5,5,5,1,1,1,1,2,1,2,1,4,1,60,55.0,neutral or dissatisfied +85360,100770,Male,Loyal Customer,53,Business travel,Business,1504,3,3,3,3,2,5,4,3,3,3,3,3,3,3,32,10.0,satisfied +85361,43043,Female,disloyal Customer,40,Business travel,Business,236,3,3,3,4,4,3,4,4,3,1,4,2,4,4,0,3.0,neutral or dissatisfied +85362,11009,Male,Loyal Customer,38,Business travel,Eco,224,4,3,3,3,4,4,4,4,4,5,2,2,1,4,0,0.0,satisfied +85363,115089,Male,disloyal Customer,20,Business travel,Business,296,5,4,5,4,4,5,4,4,4,5,5,4,5,4,0,0.0,satisfied +85364,25317,Female,Loyal Customer,41,Personal Travel,Eco,432,2,4,2,4,3,2,3,3,5,5,5,5,4,3,0,6.0,neutral or dissatisfied +85365,23801,Female,Loyal Customer,36,Business travel,Eco,374,3,3,4,3,3,4,3,3,2,3,1,5,5,3,0,0.0,satisfied +85366,89572,Male,disloyal Customer,27,Business travel,Business,1089,4,4,4,3,2,4,5,2,4,4,5,5,4,2,0,0.0,satisfied +85367,111044,Male,Loyal Customer,38,Business travel,Business,197,2,5,5,5,1,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +85368,43225,Male,Loyal Customer,30,Personal Travel,Eco,472,3,3,3,4,5,3,5,5,2,5,4,3,3,5,0,0.0,neutral or dissatisfied +85369,20005,Female,disloyal Customer,24,Business travel,Eco,589,3,0,3,2,4,3,5,4,1,2,5,5,4,4,0,0.0,neutral or dissatisfied +85370,91748,Female,Loyal Customer,24,Business travel,Business,1559,1,1,1,1,4,5,4,4,3,2,5,5,4,4,0,0.0,satisfied +85371,117361,Female,Loyal Customer,39,Business travel,Eco,296,3,3,3,3,3,3,3,3,2,4,3,2,3,3,17,7.0,neutral or dissatisfied +85372,60268,Female,Loyal Customer,40,Business travel,Business,2218,1,1,1,1,4,5,5,5,5,5,5,5,5,3,10,9.0,satisfied +85373,47886,Male,Loyal Customer,25,Business travel,Business,550,2,5,2,5,2,2,2,1,3,3,4,2,1,2,140,171.0,neutral or dissatisfied +85374,128560,Male,disloyal Customer,21,Business travel,Eco,355,1,2,1,4,1,1,1,1,1,2,3,1,3,1,0,13.0,neutral or dissatisfied +85375,111706,Male,disloyal Customer,34,Business travel,Business,495,1,1,1,2,1,4,4,4,4,5,4,4,3,4,150,141.0,neutral or dissatisfied +85376,124109,Male,Loyal Customer,35,Business travel,Business,3410,5,2,5,5,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +85377,69792,Male,Loyal Customer,26,Business travel,Business,1055,1,1,2,1,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +85378,47502,Female,Loyal Customer,19,Personal Travel,Eco,599,2,2,2,4,1,2,1,1,1,4,2,3,4,1,0,0.0,neutral or dissatisfied +85379,90012,Female,Loyal Customer,44,Business travel,Business,3541,1,1,1,1,4,5,5,5,5,5,5,5,5,4,9,9.0,satisfied +85380,83747,Female,Loyal Customer,27,Business travel,Eco,1183,3,3,3,3,3,2,3,3,1,1,3,1,4,3,81,62.0,neutral or dissatisfied +85381,119154,Female,Loyal Customer,40,Business travel,Business,331,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +85382,120328,Male,Loyal Customer,38,Personal Travel,Eco,268,3,1,3,4,3,3,3,3,1,4,3,2,3,3,0,0.0,neutral or dissatisfied +85383,19276,Female,Loyal Customer,59,Business travel,Business,430,1,1,4,4,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +85384,39895,Male,Loyal Customer,51,Personal Travel,Eco,221,3,4,0,3,2,0,3,2,5,5,3,5,2,2,0,7.0,neutral or dissatisfied +85385,108902,Female,Loyal Customer,51,Business travel,Eco,1066,2,4,4,4,3,3,4,2,2,2,2,3,2,3,50,41.0,neutral or dissatisfied +85386,23132,Female,disloyal Customer,25,Business travel,Eco,300,5,4,5,3,4,5,4,4,1,3,5,5,5,4,0,0.0,satisfied +85387,122215,Female,disloyal Customer,23,Business travel,Business,541,4,1,4,4,3,4,5,3,4,3,5,3,4,3,0,0.0,satisfied +85388,74862,Male,Loyal Customer,8,Personal Travel,Eco,1995,4,4,4,3,5,4,3,5,5,5,4,4,4,5,0,44.0,neutral or dissatisfied +85389,72184,Female,Loyal Customer,51,Business travel,Business,2263,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +85390,110142,Male,Loyal Customer,23,Business travel,Business,2824,2,4,4,4,2,2,2,2,1,1,4,3,4,2,25,21.0,neutral or dissatisfied +85391,115927,Male,disloyal Customer,54,Business travel,Eco,446,2,3,3,4,5,3,4,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +85392,53169,Female,Loyal Customer,25,Business travel,Business,642,5,5,5,5,5,5,5,5,5,2,2,4,1,5,0,23.0,satisfied +85393,47052,Male,Loyal Customer,22,Business travel,Business,2640,1,5,5,5,1,1,1,1,2,2,3,2,3,1,0,14.0,neutral or dissatisfied +85394,103319,Female,disloyal Customer,20,Business travel,Eco,1371,2,2,2,3,3,2,5,3,4,2,4,2,3,3,21,20.0,neutral or dissatisfied +85395,65729,Female,Loyal Customer,25,Business travel,Eco,936,3,1,1,1,3,3,2,3,2,1,3,3,4,3,0,0.0,neutral or dissatisfied +85396,29045,Female,Loyal Customer,30,Personal Travel,Eco,937,3,3,3,2,5,3,5,5,4,5,4,4,2,5,0,0.0,neutral or dissatisfied +85397,128132,Male,Loyal Customer,55,Personal Travel,Eco Plus,1587,2,4,2,1,1,2,1,1,3,5,3,3,5,1,0,0.0,neutral or dissatisfied +85398,66932,Female,disloyal Customer,57,Business travel,Eco,985,3,3,3,3,2,3,2,2,2,2,3,3,3,2,21,8.0,neutral or dissatisfied +85399,19855,Female,disloyal Customer,33,Business travel,Eco,585,1,0,1,1,5,1,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +85400,62222,Female,Loyal Customer,32,Personal Travel,Eco,2454,2,5,2,3,2,2,2,2,3,2,5,3,4,2,0,13.0,neutral or dissatisfied +85401,10821,Female,Loyal Customer,23,Business travel,Business,316,2,4,4,4,2,2,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +85402,119280,Female,Loyal Customer,53,Business travel,Business,214,0,4,0,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +85403,38348,Female,Loyal Customer,41,Business travel,Eco,1050,5,4,4,4,5,5,5,5,4,2,4,4,1,5,0,0.0,satisfied +85404,22696,Female,Loyal Customer,51,Business travel,Eco,589,5,4,4,4,1,2,1,5,5,5,5,1,5,1,0,0.0,satisfied +85405,107094,Male,disloyal Customer,30,Business travel,Business,745,5,5,5,3,3,5,5,3,5,4,4,5,4,3,0,0.0,satisfied +85406,52830,Female,Loyal Customer,38,Business travel,Business,1721,5,5,5,5,4,5,1,2,2,2,2,3,2,2,4,0.0,satisfied +85407,50237,Male,Loyal Customer,31,Business travel,Business,308,3,2,2,2,3,3,3,3,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +85408,119264,Male,Loyal Customer,38,Business travel,Eco,214,4,1,1,1,4,4,4,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +85409,35924,Female,Loyal Customer,22,Business travel,Business,2381,5,5,5,5,5,5,5,5,2,1,3,3,1,5,0,0.0,satisfied +85410,39915,Female,Loyal Customer,48,Business travel,Business,1086,2,2,2,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +85411,42831,Female,Loyal Customer,41,Business travel,Business,1980,2,2,4,2,5,2,3,4,4,4,4,1,4,3,0,19.0,satisfied +85412,87849,Male,Loyal Customer,23,Personal Travel,Eco,214,2,0,2,2,4,2,4,4,5,4,5,5,3,4,0,0.0,neutral or dissatisfied +85413,111063,Male,Loyal Customer,15,Personal Travel,Eco,197,2,2,2,3,2,2,2,2,1,2,3,2,4,2,29,27.0,neutral or dissatisfied +85414,111643,Male,Loyal Customer,23,Personal Travel,Eco,1558,1,4,1,1,5,1,1,5,5,4,3,5,4,5,5,16.0,neutral or dissatisfied +85415,30064,Male,disloyal Customer,50,Business travel,Business,234,1,1,1,3,3,1,3,3,3,1,3,1,4,3,4,9.0,neutral or dissatisfied +85416,92780,Female,Loyal Customer,85,Business travel,Business,171,2,2,4,2,4,3,4,5,5,3,4,4,4,4,0,0.0,satisfied +85417,10032,Male,Loyal Customer,42,Business travel,Business,2205,4,5,5,5,5,2,2,4,4,4,4,3,4,4,0,20.0,neutral or dissatisfied +85418,115221,Male,Loyal Customer,49,Business travel,Business,2746,3,3,3,3,4,5,5,5,5,4,5,5,5,3,49,43.0,satisfied +85419,90213,Female,Loyal Customer,35,Personal Travel,Eco,1084,4,4,4,1,2,4,2,2,4,2,4,3,4,2,0,0.0,satisfied +85420,18920,Male,Loyal Customer,18,Personal Travel,Eco,448,1,5,1,3,5,1,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +85421,65347,Male,Loyal Customer,51,Business travel,Business,2210,3,3,2,3,4,5,4,5,5,5,5,4,5,4,37,29.0,satisfied +85422,46428,Male,Loyal Customer,69,Personal Travel,Eco,458,2,5,2,3,3,2,4,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +85423,17257,Male,Loyal Customer,32,Business travel,Business,2485,2,1,1,1,2,2,2,2,4,4,4,4,3,2,102,85.0,neutral or dissatisfied +85424,99479,Female,disloyal Customer,21,Business travel,Eco,307,2,2,2,4,2,4,4,2,2,3,3,4,3,4,212,237.0,neutral or dissatisfied +85425,45104,Male,disloyal Customer,20,Business travel,Eco,177,2,0,2,2,2,2,2,2,2,5,3,4,5,2,11,24.0,neutral or dissatisfied +85426,10210,Male,Loyal Customer,34,Business travel,Business,3415,1,1,1,1,4,4,4,5,2,5,5,4,3,4,144,135.0,satisfied +85427,115065,Female,disloyal Customer,40,Business travel,Business,417,2,2,2,4,3,2,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +85428,83060,Female,disloyal Customer,45,Business travel,Eco,983,4,4,4,3,4,4,4,4,3,5,4,2,3,4,15,9.0,neutral or dissatisfied +85429,105007,Male,Loyal Customer,60,Business travel,Business,361,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +85430,102912,Male,Loyal Customer,48,Business travel,Business,317,3,3,3,3,5,4,5,5,5,5,5,3,5,3,19,12.0,satisfied +85431,8928,Female,disloyal Customer,24,Business travel,Eco,984,2,2,2,3,3,2,3,3,4,2,4,4,4,3,67,45.0,neutral or dissatisfied +85432,16057,Female,Loyal Customer,51,Business travel,Business,3008,3,3,3,3,4,5,3,4,4,4,4,2,4,4,0,0.0,satisfied +85433,69026,Male,disloyal Customer,46,Business travel,Business,1389,3,3,3,4,4,3,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +85434,69921,Male,Loyal Customer,8,Personal Travel,Eco,1671,3,3,4,4,1,4,1,1,2,5,4,4,4,1,0,0.0,neutral or dissatisfied +85435,119943,Male,disloyal Customer,43,Business travel,Business,1009,1,2,2,3,5,1,5,5,3,2,4,3,4,5,0,2.0,neutral or dissatisfied +85436,55406,Male,Loyal Customer,39,Business travel,Business,1558,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +85437,113959,Male,Loyal Customer,30,Business travel,Business,1706,2,2,2,2,4,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +85438,27506,Female,Loyal Customer,45,Business travel,Eco,271,4,1,1,1,1,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +85439,93013,Female,disloyal Customer,24,Business travel,Business,1524,0,3,0,4,3,0,3,3,5,5,5,4,4,3,10,0.0,satisfied +85440,61191,Female,Loyal Customer,41,Business travel,Business,846,5,5,5,5,2,5,4,5,5,5,5,5,5,4,2,4.0,satisfied +85441,654,Female,Loyal Customer,30,Business travel,Business,2369,1,1,1,1,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +85442,10169,Male,disloyal Customer,23,Business travel,Eco,247,1,0,1,3,1,1,1,1,4,5,5,3,4,1,5,12.0,neutral or dissatisfied +85443,47715,Male,Loyal Customer,22,Personal Travel,Eco Plus,1482,2,2,2,3,2,2,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +85444,119031,Female,Loyal Customer,51,Personal Travel,Eco,1460,2,2,2,3,1,3,2,2,2,2,5,2,2,1,0,42.0,neutral or dissatisfied +85445,50376,Female,Loyal Customer,64,Business travel,Business,86,1,2,2,2,1,1,2,2,2,2,1,2,2,3,0,1.0,neutral or dissatisfied +85446,38079,Male,Loyal Customer,42,Business travel,Business,1121,3,3,3,3,1,1,1,4,4,4,4,1,4,3,12,5.0,satisfied +85447,51069,Female,Loyal Customer,30,Personal Travel,Eco,308,3,5,3,3,2,3,2,2,5,2,5,3,4,2,0,8.0,neutral or dissatisfied +85448,108644,Male,Loyal Customer,49,Business travel,Business,762,1,1,3,1,4,4,5,4,4,4,4,3,4,3,11,0.0,satisfied +85449,119555,Male,Loyal Customer,29,Personal Travel,Eco,759,1,5,1,3,2,1,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +85450,16955,Female,Loyal Customer,15,Personal Travel,Eco,116,2,2,0,3,1,0,1,1,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +85451,105044,Male,disloyal Customer,39,Personal Travel,Eco,255,4,5,4,2,1,4,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +85452,93612,Male,disloyal Customer,27,Business travel,Eco,704,2,2,2,3,3,2,3,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +85453,932,Female,disloyal Customer,61,Business travel,Business,309,2,2,2,3,1,2,1,1,2,3,4,2,4,1,19,14.0,neutral or dissatisfied +85454,129373,Male,disloyal Customer,18,Business travel,Eco,1225,1,1,1,3,2,1,2,2,5,2,4,5,4,2,2,0.0,neutral or dissatisfied +85455,62834,Female,disloyal Customer,35,Business travel,Business,2338,2,2,2,4,3,2,3,3,5,5,5,5,5,3,8,3.0,neutral or dissatisfied +85456,23571,Male,Loyal Customer,47,Personal Travel,Eco,1015,2,1,2,4,4,2,4,4,3,5,4,1,4,4,11,9.0,neutral or dissatisfied +85457,57615,Male,Loyal Customer,36,Business travel,Eco,200,2,4,4,4,2,3,2,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +85458,53559,Female,Loyal Customer,49,Personal Travel,Business,1195,2,5,2,1,4,3,5,1,1,2,1,4,1,4,3,0.0,neutral or dissatisfied +85459,121465,Male,Loyal Customer,22,Personal Travel,Eco,331,3,3,3,4,3,3,3,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +85460,12553,Male,Loyal Customer,62,Personal Travel,Eco,788,1,5,1,3,3,1,3,3,5,2,4,4,5,3,20,33.0,neutral or dissatisfied +85461,71175,Male,disloyal Customer,36,Business travel,Business,733,2,2,2,3,2,2,1,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +85462,115814,Male,Loyal Customer,34,Business travel,Business,3453,4,4,3,4,5,1,1,4,4,4,4,4,4,2,0,0.0,satisfied +85463,103371,Female,Loyal Customer,61,Personal Travel,Eco,342,2,1,1,3,2,3,3,5,5,1,5,1,5,1,59,57.0,neutral or dissatisfied +85464,128584,Female,Loyal Customer,41,Business travel,Business,2552,1,1,1,1,2,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +85465,112520,Female,Loyal Customer,53,Personal Travel,Eco,862,2,5,2,3,2,5,5,4,4,2,3,4,4,5,6,0.0,neutral or dissatisfied +85466,95801,Female,Loyal Customer,32,Business travel,Business,2484,3,3,3,3,5,5,5,5,5,5,4,5,4,5,10,10.0,satisfied +85467,101930,Male,disloyal Customer,62,Business travel,Business,628,2,2,2,4,2,2,2,2,3,5,4,4,3,2,2,0.0,neutral or dissatisfied +85468,46227,Male,disloyal Customer,45,Business travel,Eco,679,2,3,3,4,4,3,3,4,1,2,4,3,3,4,0,0.0,neutral or dissatisfied +85469,71425,Male,Loyal Customer,31,Business travel,Business,3222,1,1,1,1,4,4,4,4,5,3,4,5,4,4,18,2.0,satisfied +85470,76334,Female,Loyal Customer,15,Personal Travel,Eco Plus,2182,2,4,2,4,5,2,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +85471,33851,Female,Loyal Customer,40,Business travel,Business,1698,1,5,5,5,4,3,2,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +85472,57960,Female,Loyal Customer,48,Business travel,Business,1911,3,3,5,3,5,4,5,5,5,4,5,4,5,4,30,2.0,satisfied +85473,30335,Male,Loyal Customer,37,Business travel,Business,1757,2,3,3,3,1,4,4,2,2,2,2,3,2,2,5,10.0,neutral or dissatisfied +85474,14367,Female,Loyal Customer,19,Personal Travel,Business,1215,3,2,3,1,2,3,5,2,1,3,1,4,2,2,0,0.0,neutral or dissatisfied +85475,50577,Male,Loyal Customer,67,Personal Travel,Eco,109,4,4,4,3,1,4,1,1,4,3,3,3,4,1,0,0.0,neutral or dissatisfied +85476,124451,Male,Loyal Customer,28,Business travel,Business,1632,3,3,3,3,2,2,2,2,5,5,5,5,4,2,0,0.0,satisfied +85477,97849,Female,Loyal Customer,43,Business travel,Business,395,4,4,3,4,3,5,4,5,5,5,5,3,5,3,45,24.0,satisfied +85478,118579,Male,Loyal Customer,57,Business travel,Business,370,3,3,3,3,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +85479,116469,Male,Loyal Customer,54,Personal Travel,Eco,296,1,3,1,3,4,1,4,4,1,1,4,3,3,4,2,2.0,neutral or dissatisfied +85480,51672,Male,Loyal Customer,36,Business travel,Eco,370,3,1,1,1,3,3,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +85481,28012,Male,Loyal Customer,42,Business travel,Business,1548,2,4,5,4,5,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +85482,85038,Male,Loyal Customer,16,Personal Travel,Eco Plus,1590,2,4,2,1,2,2,2,2,4,3,4,4,5,2,21,15.0,neutral or dissatisfied +85483,39226,Male,Loyal Customer,54,Business travel,Eco,173,5,3,3,3,5,5,5,5,3,4,3,1,2,5,0,0.0,satisfied +85484,112147,Male,Loyal Customer,44,Business travel,Business,3642,5,5,5,5,4,5,5,4,4,4,4,3,4,5,7,12.0,satisfied +85485,78488,Male,Loyal Customer,23,Business travel,Business,666,3,5,5,5,3,3,3,3,1,3,3,3,3,3,3,0.0,neutral or dissatisfied +85486,50513,Female,Loyal Customer,21,Personal Travel,Eco,326,5,5,5,3,4,5,4,4,4,5,2,3,2,4,0,0.0,satisfied +85487,119754,Female,Loyal Customer,33,Personal Travel,Eco,1325,1,5,1,4,4,1,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +85488,103020,Male,Loyal Customer,40,Business travel,Business,3970,2,2,2,2,5,4,5,4,4,4,4,3,4,5,46,23.0,satisfied +85489,115516,Female,Loyal Customer,38,Business travel,Business,2325,2,2,2,2,4,4,4,2,2,2,2,1,2,1,53,37.0,neutral or dissatisfied +85490,79132,Male,Loyal Customer,59,Business travel,Business,356,5,5,3,5,4,4,5,5,5,5,5,5,5,5,22,30.0,satisfied +85491,120600,Female,Loyal Customer,47,Personal Travel,Eco,980,2,4,1,3,3,4,4,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +85492,3319,Male,Loyal Customer,40,Business travel,Business,2260,3,3,4,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +85493,89734,Male,Loyal Customer,10,Personal Travel,Eco,1005,2,4,2,1,4,2,4,4,3,4,4,3,4,4,23,8.0,neutral or dissatisfied +85494,127735,Female,Loyal Customer,49,Business travel,Business,255,2,1,2,2,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +85495,39835,Female,Loyal Customer,48,Business travel,Eco,221,4,3,3,3,4,2,4,4,4,4,4,2,4,2,0,0.0,satisfied +85496,112823,Female,disloyal Customer,38,Business travel,Business,715,2,2,2,5,2,2,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +85497,47605,Female,Loyal Customer,45,Business travel,Business,1334,5,5,5,5,1,5,2,5,5,5,5,5,5,2,0,3.0,satisfied +85498,118105,Male,Loyal Customer,55,Business travel,Eco,499,2,5,5,5,2,2,2,2,2,5,3,2,4,2,0,0.0,neutral or dissatisfied +85499,10057,Male,Loyal Customer,49,Personal Travel,Business,596,0,5,0,1,2,3,5,4,4,0,4,4,4,4,0,0.0,satisfied +85500,87270,Female,Loyal Customer,46,Business travel,Business,3611,2,2,2,2,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +85501,34604,Female,Loyal Customer,47,Personal Travel,Eco,1617,2,4,2,3,5,2,3,4,4,2,4,4,4,1,0,6.0,neutral or dissatisfied +85502,53662,Female,Loyal Customer,11,Personal Travel,Business,1208,2,2,2,3,4,2,4,4,3,2,1,1,2,4,0,0.0,neutral or dissatisfied +85503,106649,Female,Loyal Customer,49,Personal Travel,Eco,861,2,1,2,3,3,3,3,5,5,2,5,1,5,1,7,0.0,neutral or dissatisfied +85504,67843,Male,Loyal Customer,40,Personal Travel,Eco,1235,3,2,3,3,5,3,2,5,3,5,3,4,3,5,22,7.0,neutral or dissatisfied +85505,2071,Female,Loyal Customer,60,Business travel,Business,1864,1,2,2,2,4,2,3,1,1,1,1,3,1,3,0,5.0,neutral or dissatisfied +85506,32632,Female,disloyal Customer,33,Business travel,Eco,101,2,0,3,4,2,3,2,2,2,5,5,4,1,2,0,0.0,neutral or dissatisfied +85507,36468,Female,Loyal Customer,36,Business travel,Business,2292,1,1,1,1,1,2,5,5,5,5,5,1,5,1,0,0.0,satisfied +85508,34589,Male,Loyal Customer,40,Business travel,Eco,1576,3,4,4,4,3,3,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +85509,15855,Female,Loyal Customer,35,Business travel,Business,332,4,4,4,4,1,5,4,4,4,4,4,4,4,2,0,3.0,satisfied +85510,79606,Male,Loyal Customer,37,Business travel,Eco,853,2,4,4,4,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +85511,43370,Male,Loyal Customer,7,Personal Travel,Eco,347,4,3,4,4,4,4,3,4,1,5,3,2,3,4,0,0.0,satisfied +85512,67840,Female,disloyal Customer,16,Personal Travel,Eco,1242,4,5,4,2,4,4,1,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +85513,71478,Female,Loyal Customer,36,Personal Travel,Eco Plus,837,2,3,2,1,4,2,4,4,3,3,4,2,4,4,0,4.0,neutral or dissatisfied +85514,78362,Female,Loyal Customer,53,Business travel,Business,2363,2,2,2,2,4,4,4,4,4,4,4,4,4,5,48,40.0,satisfied +85515,77239,Female,Loyal Customer,50,Business travel,Business,1590,1,5,5,5,1,1,1,4,1,4,3,1,3,1,134,113.0,neutral or dissatisfied +85516,59495,Male,Loyal Customer,21,Personal Travel,Eco,758,3,5,4,4,5,4,5,5,3,3,5,3,1,5,51,45.0,neutral or dissatisfied +85517,20573,Male,Loyal Customer,59,Business travel,Eco,133,3,4,4,4,3,3,3,3,1,5,5,5,3,3,0,0.0,satisfied +85518,2893,Female,Loyal Customer,31,Personal Travel,Eco,409,3,5,3,2,3,3,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +85519,101330,Male,Loyal Customer,31,Personal Travel,Eco Plus,986,4,4,4,4,5,4,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +85520,110343,Male,disloyal Customer,25,Business travel,Business,883,4,5,3,4,3,3,3,3,3,2,5,4,5,3,5,0.0,satisfied +85521,84455,Female,disloyal Customer,23,Business travel,Eco,290,3,4,3,3,5,3,5,5,4,5,3,3,4,5,0,0.0,neutral or dissatisfied +85522,93267,Female,Loyal Customer,53,Business travel,Business,867,4,4,4,4,4,4,5,5,5,5,5,5,5,5,9,5.0,satisfied +85523,74482,Female,Loyal Customer,60,Business travel,Business,3143,4,4,4,4,2,4,4,4,4,4,4,5,4,5,46,33.0,satisfied +85524,70531,Male,Loyal Customer,66,Personal Travel,Business,1258,1,4,1,2,4,3,4,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +85525,34986,Male,Loyal Customer,45,Personal Travel,Eco,273,1,4,1,4,3,1,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +85526,123809,Female,Loyal Customer,35,Business travel,Business,2078,1,1,1,1,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +85527,33163,Male,Loyal Customer,47,Personal Travel,Eco,102,1,1,0,3,1,0,1,1,2,3,4,4,3,1,0,3.0,neutral or dissatisfied +85528,113202,Male,Loyal Customer,55,Business travel,Business,1790,0,0,0,1,4,4,4,2,2,2,2,3,2,4,1,0.0,satisfied +85529,103788,Female,Loyal Customer,47,Business travel,Business,2187,5,5,5,5,3,5,5,4,4,4,4,5,4,5,34,38.0,satisfied +85530,129503,Male,disloyal Customer,38,Business travel,Business,1846,3,3,3,1,4,3,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +85531,124880,Male,Loyal Customer,31,Business travel,Business,3099,2,2,4,2,4,4,4,4,3,2,5,5,4,4,0,8.0,satisfied +85532,63543,Male,Loyal Customer,54,Personal Travel,Eco,1009,3,4,3,5,4,3,4,4,5,5,4,3,4,4,13,26.0,neutral or dissatisfied +85533,33338,Male,Loyal Customer,61,Business travel,Business,2349,5,5,4,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +85534,101644,Female,Loyal Customer,60,Business travel,Business,1733,1,0,0,3,5,1,2,4,4,0,4,2,4,3,3,0.0,neutral or dissatisfied +85535,61791,Female,Loyal Customer,63,Personal Travel,Eco,1464,3,4,3,2,5,5,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +85536,58473,Female,Loyal Customer,49,Business travel,Business,1582,4,4,3,4,4,4,4,5,5,5,5,5,5,3,0,27.0,satisfied +85537,120282,Female,Loyal Customer,49,Business travel,Eco,1176,4,4,4,4,2,4,5,5,5,4,5,2,5,5,5,46.0,satisfied +85538,60926,Female,Loyal Customer,55,Business travel,Business,1740,1,4,1,1,4,4,4,5,3,5,4,4,3,4,114,171.0,satisfied +85539,109959,Female,Loyal Customer,14,Personal Travel,Eco,1205,3,1,3,4,4,3,4,4,4,1,3,2,3,4,5,0.0,neutral or dissatisfied +85540,110599,Male,Loyal Customer,20,Personal Travel,Eco,551,4,2,4,4,5,4,5,5,4,2,4,4,3,5,13,14.0,neutral or dissatisfied +85541,72477,Male,disloyal Customer,44,Business travel,Business,1119,4,4,4,2,3,4,3,3,3,3,4,5,5,3,0,16.0,neutral or dissatisfied +85542,102543,Male,Loyal Customer,20,Personal Travel,Eco,407,4,2,4,4,1,4,1,1,4,1,4,3,3,1,9,0.0,satisfied +85543,87933,Female,Loyal Customer,42,Business travel,Business,2425,3,5,5,5,3,4,4,3,3,3,3,4,3,1,18,16.0,neutral or dissatisfied +85544,79222,Male,Loyal Customer,48,Business travel,Business,1990,3,5,3,3,5,3,5,2,2,2,2,3,2,3,26,12.0,satisfied +85545,22046,Female,Loyal Customer,47,Business travel,Business,2897,1,5,5,5,2,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +85546,102937,Male,Loyal Customer,7,Personal Travel,Eco,317,3,5,5,2,4,5,4,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +85547,62964,Male,Loyal Customer,29,Business travel,Eco,846,4,4,4,4,4,4,4,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +85548,114821,Male,disloyal Customer,46,Business travel,Business,371,1,1,1,4,5,1,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +85549,125595,Female,Loyal Customer,47,Business travel,Business,1587,4,4,4,4,5,5,4,4,4,4,4,4,4,5,0,6.0,satisfied +85550,6571,Male,Loyal Customer,55,Business travel,Business,473,1,3,3,3,5,4,3,1,1,1,1,4,1,4,27,15.0,neutral or dissatisfied +85551,94368,Male,disloyal Customer,39,Business travel,Business,148,2,2,2,4,3,2,3,3,3,4,4,5,5,3,30,22.0,neutral or dissatisfied +85552,81374,Female,disloyal Customer,24,Business travel,Business,874,5,4,5,4,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +85553,105001,Female,disloyal Customer,24,Business travel,Eco,337,4,0,4,4,3,4,3,3,3,4,5,4,4,3,0,0.0,satisfied +85554,33782,Male,Loyal Customer,34,Business travel,Business,588,4,4,4,4,5,3,4,4,4,5,4,3,4,3,0,0.0,satisfied +85555,6165,Male,disloyal Customer,21,Business travel,Eco,475,3,3,3,3,2,3,2,2,4,1,4,1,4,2,8,16.0,neutral or dissatisfied +85556,85925,Female,Loyal Customer,56,Business travel,Business,447,2,2,2,2,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +85557,111892,Male,Loyal Customer,16,Personal Travel,Eco,628,2,5,2,4,4,2,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +85558,114530,Male,Loyal Customer,29,Personal Travel,Business,373,2,4,2,3,3,2,3,3,4,1,4,1,2,3,0,0.0,neutral or dissatisfied +85559,56297,Female,Loyal Customer,22,Personal Travel,Eco,2227,1,3,1,3,1,1,1,1,2,2,2,1,4,1,0,0.0,neutral or dissatisfied +85560,38516,Female,disloyal Customer,20,Business travel,Eco,938,2,2,2,3,1,2,5,1,2,5,3,3,4,1,0,0.0,neutral or dissatisfied +85561,14676,Female,Loyal Customer,7,Personal Travel,Eco,416,1,3,1,4,1,2,3,3,2,4,4,3,4,3,157,158.0,neutral or dissatisfied +85562,112890,Female,Loyal Customer,50,Business travel,Eco,1129,3,2,3,2,3,3,3,3,2,4,4,3,1,3,148,135.0,neutral or dissatisfied +85563,10335,Female,disloyal Customer,36,Business travel,Business,458,2,2,2,1,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +85564,108264,Female,disloyal Customer,41,Business travel,Business,495,4,4,4,3,4,4,4,4,3,3,2,3,1,4,110,109.0,satisfied +85565,20690,Male,Loyal Customer,32,Business travel,Business,3488,2,2,2,2,5,5,5,5,4,3,4,2,5,5,0,0.0,satisfied +85566,76680,Female,Loyal Customer,32,Personal Travel,Eco,547,4,4,4,5,3,4,3,3,3,3,4,3,4,3,0,0.0,satisfied +85567,25277,Male,Loyal Customer,59,Personal Travel,Eco,425,3,0,3,3,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +85568,34741,Male,disloyal Customer,38,Business travel,Eco,301,4,3,4,2,3,4,1,3,4,3,2,2,3,3,20,33.0,neutral or dissatisfied +85569,89034,Female,Loyal Customer,32,Business travel,Eco,1947,3,4,4,4,3,3,3,3,3,5,4,4,3,3,10,0.0,neutral or dissatisfied +85570,20534,Female,Loyal Customer,30,Business travel,Business,533,5,5,5,5,5,5,5,5,1,2,3,5,5,5,0,0.0,satisfied +85571,58379,Female,Loyal Customer,54,Business travel,Business,733,1,1,1,1,3,4,4,4,4,5,4,5,4,3,33,23.0,satisfied +85572,63682,Male,Loyal Customer,35,Personal Travel,Eco,1047,3,4,4,3,1,4,1,1,1,1,4,1,3,1,8,0.0,neutral or dissatisfied +85573,126584,Female,Loyal Customer,38,Personal Travel,Business,1337,3,5,3,4,4,3,4,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +85574,46718,Male,Loyal Customer,51,Personal Travel,Eco,141,3,5,3,5,2,3,2,2,2,4,1,4,3,2,30,27.0,neutral or dissatisfied +85575,12664,Female,Loyal Customer,17,Business travel,Business,721,3,3,3,3,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +85576,36998,Male,Loyal Customer,11,Personal Travel,Eco,899,1,3,1,3,4,1,3,4,3,1,4,5,5,4,0,0.0,neutral or dissatisfied +85577,102069,Male,Loyal Customer,36,Business travel,Business,3285,0,0,0,1,3,4,4,1,1,1,1,4,1,4,17,17.0,satisfied +85578,42040,Male,Loyal Customer,34,Business travel,Business,3366,4,2,4,4,2,5,2,4,4,4,4,3,4,5,0,0.0,satisfied +85579,93840,Female,Loyal Customer,24,Personal Travel,Eco,391,2,5,4,1,4,4,4,4,2,1,5,5,4,4,71,75.0,neutral or dissatisfied +85580,121471,Female,Loyal Customer,20,Personal Travel,Eco,257,4,4,4,4,4,4,4,4,2,5,4,3,4,4,15,20.0,neutral or dissatisfied +85581,14301,Male,Loyal Customer,35,Business travel,Business,3192,3,3,3,3,3,2,1,5,5,5,5,4,5,3,0,0.0,satisfied +85582,107683,Female,Loyal Customer,44,Business travel,Business,3768,4,4,2,4,3,4,4,4,4,4,4,5,4,4,35,30.0,satisfied +85583,123085,Male,Loyal Customer,53,Business travel,Business,1695,3,3,3,3,2,4,5,4,4,4,4,3,4,3,29,26.0,satisfied +85584,10727,Male,Loyal Customer,53,Business travel,Business,458,2,3,3,3,5,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +85585,80358,Female,Loyal Customer,41,Business travel,Business,368,1,1,5,1,3,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +85586,95755,Male,Loyal Customer,49,Business travel,Business,2033,2,1,1,1,1,3,4,2,2,2,2,4,2,3,40,33.0,neutral or dissatisfied +85587,75732,Female,Loyal Customer,57,Business travel,Eco,868,1,3,3,3,2,3,4,1,1,1,1,2,1,1,54,45.0,neutral or dissatisfied +85588,58187,Female,disloyal Customer,23,Business travel,Eco,925,4,3,3,1,1,3,1,1,4,4,5,4,5,1,12,5.0,satisfied +85589,111560,Female,disloyal Customer,22,Business travel,Eco,775,3,4,4,3,3,4,4,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +85590,90624,Male,disloyal Customer,23,Business travel,Eco,444,4,3,4,4,3,4,3,3,4,3,3,2,3,3,8,1.0,neutral or dissatisfied +85591,112101,Female,disloyal Customer,24,Business travel,Eco,662,1,2,1,3,5,1,5,5,2,2,4,4,4,5,22,64.0,neutral or dissatisfied +85592,88923,Female,disloyal Customer,20,Business travel,Business,1199,0,0,0,4,5,0,5,5,4,3,5,4,5,5,0,0.0,satisfied +85593,110886,Male,Loyal Customer,47,Business travel,Business,2475,3,2,2,2,2,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +85594,9615,Male,Loyal Customer,32,Personal Travel,Eco,288,3,5,3,3,5,3,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +85595,68062,Female,disloyal Customer,42,Business travel,Business,868,5,5,5,1,2,5,2,2,5,4,5,3,4,2,2,8.0,satisfied +85596,41720,Male,Loyal Customer,58,Business travel,Business,3099,5,5,5,5,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +85597,119801,Male,Loyal Customer,39,Business travel,Business,2176,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +85598,128202,Female,Loyal Customer,47,Business travel,Business,3978,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,3.0,satisfied +85599,36506,Female,Loyal Customer,69,Business travel,Business,1608,4,4,5,4,4,4,1,5,5,5,5,4,5,4,0,0.0,satisfied +85600,31509,Female,disloyal Customer,47,Business travel,Eco,967,1,1,1,4,3,1,3,3,2,4,3,1,4,3,0,1.0,neutral or dissatisfied +85601,54371,Male,disloyal Customer,39,Business travel,Business,305,5,5,5,3,2,5,2,2,4,4,5,4,4,2,0,0.0,satisfied +85602,52223,Female,Loyal Customer,36,Business travel,Business,2601,1,1,1,1,2,3,2,5,5,5,5,5,5,5,0,3.0,satisfied +85603,16549,Female,Loyal Customer,60,Business travel,Business,3580,2,2,2,2,5,3,4,2,2,2,2,4,2,4,45,47.0,neutral or dissatisfied +85604,14447,Female,Loyal Customer,48,Business travel,Eco,761,3,2,2,2,4,2,3,3,3,3,3,2,3,3,11,6.0,neutral or dissatisfied +85605,65346,Male,Loyal Customer,40,Business travel,Business,2420,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +85606,111457,Female,Loyal Customer,41,Personal Travel,Eco,836,1,4,1,1,4,1,4,4,4,3,4,3,5,4,28,32.0,neutral or dissatisfied +85607,129688,Male,Loyal Customer,60,Business travel,Business,1674,4,4,4,4,4,4,4,5,3,4,4,4,3,4,144,139.0,satisfied +85608,61528,Female,Loyal Customer,19,Personal Travel,Eco,2419,2,5,2,3,3,2,3,3,3,3,3,5,4,3,0,0.0,neutral or dissatisfied +85609,86665,Male,Loyal Customer,14,Personal Travel,Eco,746,4,3,4,3,3,4,3,3,3,1,3,3,3,3,92,72.0,neutral or dissatisfied +85610,78468,Male,Loyal Customer,40,Business travel,Business,1973,4,4,4,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +85611,42118,Male,Loyal Customer,65,Business travel,Eco,498,3,2,2,2,2,3,2,2,2,5,1,4,1,2,19,17.0,neutral or dissatisfied +85612,3656,Male,disloyal Customer,39,Business travel,Business,427,3,3,3,4,4,3,2,4,5,3,5,4,5,4,3,0.0,satisfied +85613,46917,Male,disloyal Customer,25,Business travel,Eco,916,2,2,2,4,5,2,5,5,3,1,4,4,4,5,0,0.0,neutral or dissatisfied +85614,121457,Male,Loyal Customer,35,Business travel,Eco,331,5,3,3,3,5,5,5,5,1,4,5,5,3,5,0,0.0,satisfied +85615,17835,Male,Loyal Customer,80,Business travel,Eco Plus,675,5,1,1,1,3,5,3,3,5,2,2,2,2,3,0,0.0,satisfied +85616,32381,Female,Loyal Customer,60,Business travel,Eco,101,4,5,5,5,3,2,3,4,4,4,4,4,4,4,0,4.0,satisfied +85617,66105,Female,disloyal Customer,24,Business travel,Eco,583,0,4,0,4,2,0,2,2,4,4,4,5,5,2,4,2.0,satisfied +85618,16536,Male,Loyal Customer,15,Personal Travel,Eco,209,3,2,0,2,4,0,4,4,4,3,2,2,2,4,0,0.0,neutral or dissatisfied +85619,128643,Male,Loyal Customer,51,Personal Travel,Eco,679,1,5,1,3,2,1,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +85620,13520,Male,Loyal Customer,45,Business travel,Business,227,5,5,5,5,2,2,4,5,5,5,5,3,5,3,0,0.0,satisfied +85621,50714,Female,Loyal Customer,68,Personal Travel,Eco,109,2,4,0,4,2,4,5,3,3,0,3,5,3,4,8,3.0,neutral or dissatisfied +85622,36285,Male,Loyal Customer,33,Business travel,Business,187,1,1,3,1,5,5,5,5,5,2,5,3,5,5,0,0.0,satisfied +85623,63747,Female,Loyal Customer,9,Personal Travel,Eco,1660,2,3,2,5,1,2,2,1,1,5,4,2,3,1,0,0.0,neutral or dissatisfied +85624,55826,Female,disloyal Customer,48,Business travel,Business,1416,3,3,3,2,3,3,3,3,4,3,4,3,4,3,0,5.0,neutral or dissatisfied +85625,104759,Female,Loyal Customer,23,Personal Travel,Eco,1407,2,1,2,4,5,2,5,5,2,3,4,2,4,5,0,0.0,neutral or dissatisfied +85626,47059,Female,Loyal Customer,12,Business travel,Business,3760,2,3,3,3,2,2,2,2,3,4,3,4,3,2,0,18.0,neutral or dissatisfied +85627,39786,Male,Loyal Customer,49,Business travel,Business,221,3,3,3,3,4,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +85628,116944,Male,Loyal Customer,56,Business travel,Business,304,1,1,1,1,2,4,4,4,4,4,4,5,4,3,14,26.0,satisfied +85629,119959,Female,Loyal Customer,43,Business travel,Eco,468,4,2,2,2,2,3,4,4,4,4,4,2,4,4,34,30.0,neutral or dissatisfied +85630,56019,Male,Loyal Customer,51,Business travel,Business,2586,1,1,1,1,4,4,4,4,4,4,5,4,3,4,2,0.0,satisfied +85631,12047,Male,disloyal Customer,47,Business travel,Eco,376,4,5,3,3,3,3,5,3,1,4,1,5,5,3,0,0.0,neutral or dissatisfied +85632,105448,Female,disloyal Customer,25,Business travel,Eco,998,3,3,3,4,3,3,2,3,3,1,4,1,3,3,31,17.0,neutral or dissatisfied +85633,79660,Male,Loyal Customer,61,Personal Travel,Eco,760,5,3,5,3,5,5,5,5,2,1,3,3,4,5,8,4.0,satisfied +85634,102807,Female,Loyal Customer,37,Business travel,Business,2699,3,3,3,3,2,5,4,5,5,5,5,3,5,5,0,1.0,satisfied +85635,49326,Female,Loyal Customer,58,Business travel,Business,2121,0,4,0,4,1,2,3,1,1,1,1,5,1,2,12,8.0,satisfied +85636,92639,Male,disloyal Customer,25,Business travel,Eco,453,2,4,2,5,2,2,3,2,3,5,3,2,2,2,0,0.0,neutral or dissatisfied +85637,53778,Male,disloyal Customer,48,Business travel,Business,191,3,3,3,4,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +85638,1376,Female,Loyal Customer,38,Business travel,Eco Plus,354,4,2,1,2,4,4,4,4,2,1,1,5,2,4,0,3.0,satisfied +85639,91875,Male,Loyal Customer,53,Business travel,Business,2586,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +85640,100897,Female,disloyal Customer,37,Business travel,Eco,377,4,2,4,3,1,4,1,1,3,2,3,4,3,1,0,1.0,neutral or dissatisfied +85641,17727,Male,Loyal Customer,38,Business travel,Business,2491,2,2,2,2,1,4,4,4,4,4,4,1,4,3,18,0.0,satisfied +85642,33233,Female,Loyal Customer,48,Business travel,Eco Plus,216,2,3,3,3,5,4,2,2,2,2,2,5,2,3,0,0.0,satisfied +85643,122907,Female,Loyal Customer,47,Business travel,Business,3184,2,1,1,1,1,3,3,2,2,2,2,1,2,3,34,49.0,neutral or dissatisfied +85644,103555,Male,Loyal Customer,34,Personal Travel,Eco,738,2,3,2,3,3,2,2,3,3,3,4,1,4,3,60,53.0,neutral or dissatisfied +85645,89134,Male,Loyal Customer,64,Business travel,Business,1947,1,5,5,5,1,2,3,1,1,1,1,1,1,2,27,17.0,neutral or dissatisfied +85646,49903,Male,Loyal Customer,41,Business travel,Business,326,2,3,3,3,2,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +85647,21940,Female,Loyal Customer,48,Business travel,Business,448,3,1,1,1,3,3,3,1,2,4,4,3,2,3,147,150.0,neutral or dissatisfied +85648,21513,Female,Loyal Customer,70,Personal Travel,Eco,399,3,4,3,1,3,4,4,4,4,3,4,5,4,3,1,,neutral or dissatisfied +85649,24615,Female,Loyal Customer,28,Business travel,Business,526,2,2,2,2,2,2,2,2,2,5,3,5,1,2,0,0.0,satisfied +85650,84800,Male,Loyal Customer,52,Business travel,Business,547,2,4,2,2,4,4,4,2,2,2,2,3,2,4,4,0.0,satisfied +85651,8564,Female,Loyal Customer,41,Business travel,Business,109,3,3,4,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +85652,125693,Male,Loyal Customer,38,Business travel,Business,3790,3,3,5,3,5,4,4,3,3,3,3,2,3,1,25,19.0,neutral or dissatisfied +85653,113485,Female,Loyal Customer,42,Business travel,Business,2240,3,3,3,3,5,5,4,4,4,4,4,5,4,4,62,60.0,satisfied +85654,104057,Female,Loyal Customer,58,Personal Travel,Eco,1262,2,5,1,3,3,4,5,3,3,1,3,4,3,5,0,3.0,neutral or dissatisfied +85655,102170,Female,Loyal Customer,32,Business travel,Business,3282,5,5,4,5,5,5,5,5,5,5,5,3,4,5,11,5.0,satisfied +85656,87781,Female,Loyal Customer,47,Business travel,Business,3257,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +85657,99950,Male,Loyal Customer,17,Personal Travel,Eco,1986,4,4,4,4,2,4,2,2,3,2,4,1,3,2,3,0.0,neutral or dissatisfied +85658,93466,Male,Loyal Customer,39,Business travel,Business,3626,3,2,3,3,3,5,4,4,4,4,4,5,4,3,3,5.0,satisfied +85659,20303,Female,Loyal Customer,38,Business travel,Eco Plus,235,5,4,4,4,5,5,5,5,3,2,5,1,2,5,0,0.0,satisfied +85660,73130,Male,disloyal Customer,24,Business travel,Eco,1068,5,5,5,4,1,5,1,1,3,4,5,5,4,1,0,0.0,satisfied +85661,116462,Female,Loyal Customer,40,Personal Travel,Eco,342,2,5,2,3,3,2,3,3,3,2,5,4,4,3,4,1.0,neutral or dissatisfied +85662,118116,Male,Loyal Customer,69,Personal Travel,Eco,1300,2,4,2,2,1,2,1,1,5,3,3,3,4,1,0,0.0,neutral or dissatisfied +85663,44464,Female,disloyal Customer,22,Business travel,Eco,196,4,4,4,3,3,4,4,3,2,1,3,2,4,3,20,25.0,neutral or dissatisfied +85664,69603,Male,Loyal Customer,40,Personal Travel,Eco,2475,2,1,2,4,2,1,2,1,2,3,4,2,4,2,2,0.0,neutral or dissatisfied +85665,65872,Female,Loyal Customer,10,Personal Travel,Eco,1389,3,5,3,4,2,3,2,2,3,2,3,5,4,2,4,0.0,neutral or dissatisfied +85666,31761,Female,Loyal Customer,24,Business travel,Business,1859,5,5,3,5,2,2,2,2,1,3,4,5,3,2,0,0.0,satisfied +85667,36332,Female,Loyal Customer,43,Business travel,Eco,187,4,2,2,2,4,4,4,3,5,5,1,4,3,4,129,147.0,satisfied +85668,107998,Female,disloyal Customer,36,Business travel,Eco,271,3,3,3,4,5,3,5,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +85669,113394,Male,disloyal Customer,40,Business travel,Business,407,4,4,4,4,5,4,5,5,5,2,5,3,4,5,16,10.0,satisfied +85670,109760,Male,Loyal Customer,34,Personal Travel,Eco Plus,587,3,5,3,3,5,3,4,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +85671,36687,Female,Loyal Customer,32,Personal Travel,Eco,1249,2,4,2,3,1,2,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +85672,42262,Female,Loyal Customer,54,Business travel,Eco,834,1,5,3,5,5,3,2,1,1,1,1,4,1,4,0,1.0,neutral or dissatisfied +85673,71284,Male,Loyal Customer,52,Business travel,Business,1853,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,5.0,satisfied +85674,101844,Male,Loyal Customer,51,Personal Travel,Eco Plus,1521,3,3,3,3,2,3,2,2,2,3,3,3,4,2,5,0.0,neutral or dissatisfied +85675,201,Female,Loyal Customer,43,Business travel,Business,213,1,5,5,5,5,4,3,2,2,2,1,2,2,3,65,85.0,neutral or dissatisfied +85676,903,Female,disloyal Customer,24,Business travel,Business,89,3,3,3,2,5,3,2,5,3,4,2,4,3,5,0,0.0,neutral or dissatisfied +85677,42999,Male,disloyal Customer,40,Business travel,Eco,259,2,0,2,3,1,2,1,1,2,5,1,4,5,1,0,0.0,neutral or dissatisfied +85678,8399,Male,Loyal Customer,16,Personal Travel,Eco,888,1,1,1,3,4,1,4,4,4,1,4,2,3,4,0,43.0,neutral or dissatisfied +85679,89046,Female,Loyal Customer,49,Business travel,Business,1947,5,5,5,5,5,4,4,5,5,5,5,3,5,4,6,0.0,satisfied +85680,52061,Female,disloyal Customer,20,Business travel,Eco,438,0,4,0,3,3,4,3,3,4,4,2,2,3,3,0,0.0,satisfied +85681,112384,Female,Loyal Customer,46,Business travel,Business,1970,4,4,4,4,4,4,5,5,5,5,5,4,5,3,3,0.0,satisfied +85682,76431,Male,Loyal Customer,45,Business travel,Eco,405,1,2,2,2,1,1,1,1,1,4,3,2,3,1,0,0.0,neutral or dissatisfied +85683,33425,Male,disloyal Customer,26,Business travel,Eco,2556,1,1,1,3,1,1,1,2,5,3,4,1,1,1,0,45.0,neutral or dissatisfied +85684,123757,Male,disloyal Customer,32,Business travel,Business,546,1,1,1,4,4,1,4,4,5,5,4,4,5,4,8,9.0,neutral or dissatisfied +85685,38415,Female,Loyal Customer,23,Business travel,Business,965,1,1,1,1,4,4,4,4,4,5,2,4,3,4,0,0.0,satisfied +85686,105803,Male,Loyal Customer,44,Personal Travel,Eco,842,1,2,1,4,2,1,2,2,4,4,4,1,3,2,0,10.0,neutral or dissatisfied +85687,44910,Female,Loyal Customer,58,Personal Travel,Eco,1118,2,4,2,2,3,5,5,4,4,2,4,5,4,5,0,3.0,neutral or dissatisfied +85688,48578,Female,Loyal Customer,39,Personal Travel,Eco,846,1,4,1,5,3,1,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +85689,5411,Male,Loyal Customer,9,Personal Travel,Eco,785,0,5,0,4,3,0,3,3,5,3,4,4,4,3,0,,satisfied +85690,44131,Female,Loyal Customer,35,Business travel,Business,3083,1,5,5,5,1,3,3,5,5,4,1,2,5,2,38,16.0,neutral or dissatisfied +85691,38810,Female,Loyal Customer,14,Personal Travel,Eco,354,1,4,1,2,5,1,5,5,3,4,5,5,5,5,39,37.0,neutral or dissatisfied +85692,1596,Female,Loyal Customer,24,Personal Travel,Eco,237,2,5,0,1,5,0,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +85693,40034,Female,Loyal Customer,45,Personal Travel,Eco,618,3,5,2,4,3,5,5,1,1,2,5,3,1,5,67,45.0,neutral or dissatisfied +85694,47658,Male,disloyal Customer,13,Business travel,Eco,715,4,4,4,4,5,4,1,5,3,3,4,5,2,5,0,1.0,neutral or dissatisfied +85695,50260,Female,disloyal Customer,20,Business travel,Eco,89,2,4,2,4,4,2,4,4,4,4,4,4,4,4,0,13.0,neutral or dissatisfied +85696,10695,Male,disloyal Customer,23,Business travel,Eco,166,2,4,1,4,4,1,4,4,3,3,4,1,4,4,0,0.0,neutral or dissatisfied +85697,100614,Male,Loyal Customer,52,Business travel,Business,3788,1,1,1,1,3,5,4,5,5,5,5,5,5,3,0,3.0,satisfied +85698,58875,Female,Loyal Customer,39,Business travel,Business,2394,2,2,2,2,4,5,5,4,4,4,4,4,4,4,9,0.0,satisfied +85699,46700,Male,Loyal Customer,18,Personal Travel,Eco,251,1,5,1,1,2,1,5,2,3,1,3,4,1,2,4,2.0,neutral or dissatisfied +85700,84763,Female,disloyal Customer,26,Business travel,Business,534,3,5,3,5,1,3,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +85701,9558,Male,Loyal Customer,45,Business travel,Business,1758,3,4,4,4,2,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +85702,72852,Male,disloyal Customer,40,Business travel,Business,700,2,2,2,2,2,2,2,2,5,4,4,3,5,2,83,80.0,neutral or dissatisfied +85703,98955,Female,Loyal Customer,45,Business travel,Business,3398,3,3,3,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +85704,99152,Male,Loyal Customer,42,Business travel,Business,986,5,5,5,5,3,5,4,4,4,4,4,3,4,3,1,2.0,satisfied +85705,39198,Female,Loyal Customer,31,Personal Travel,Eco,318,4,5,4,2,5,4,5,5,4,1,1,5,5,5,0,0.0,neutral or dissatisfied +85706,94045,Female,Loyal Customer,47,Business travel,Business,3991,0,4,0,3,3,4,4,4,4,3,3,5,4,4,0,1.0,satisfied +85707,26368,Female,Loyal Customer,21,Business travel,Business,2088,5,5,5,5,4,4,4,4,4,5,4,4,2,4,0,0.0,satisfied +85708,7043,Male,Loyal Customer,16,Personal Travel,Eco Plus,299,4,4,4,4,5,4,5,5,4,3,5,5,4,5,0,0.0,satisfied +85709,33799,Female,Loyal Customer,44,Business travel,Business,1521,5,5,5,5,1,1,1,5,5,5,5,4,5,5,85,66.0,satisfied +85710,20990,Male,Loyal Customer,55,Personal Travel,Eco,689,4,5,4,5,3,4,1,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +85711,110339,Male,Loyal Customer,50,Business travel,Business,3004,1,1,1,1,3,4,5,4,4,4,4,4,4,3,90,70.0,satisfied +85712,102067,Female,Loyal Customer,50,Personal Travel,Business,258,2,1,2,4,1,3,3,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +85713,51421,Female,Loyal Customer,7,Personal Travel,Eco Plus,86,1,5,1,2,4,1,4,4,4,3,4,4,4,4,4,25.0,neutral or dissatisfied +85714,71638,Female,Loyal Customer,53,Personal Travel,Eco,1005,2,5,3,2,4,5,4,2,2,3,2,5,2,5,35,50.0,neutral or dissatisfied +85715,60653,Male,Loyal Customer,55,Business travel,Business,1620,1,1,1,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +85716,13378,Female,Loyal Customer,32,Business travel,Eco Plus,748,5,5,5,5,5,5,5,5,4,2,3,3,4,5,0,0.0,satisfied +85717,125352,Female,Loyal Customer,52,Business travel,Business,1689,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +85718,30919,Female,disloyal Customer,24,Business travel,Business,496,5,0,5,2,2,5,2,2,2,3,4,3,3,2,0,2.0,satisfied +85719,29803,Female,disloyal Customer,21,Business travel,Eco,261,4,3,4,3,4,4,4,4,4,1,5,2,3,4,0,0.0,satisfied +85720,62110,Male,Loyal Customer,27,Business travel,Business,2454,3,3,4,3,4,4,4,4,4,4,3,4,4,4,0,0.0,satisfied +85721,116263,Female,Loyal Customer,17,Personal Travel,Eco,308,2,5,2,4,4,2,4,4,3,2,4,4,5,4,0,4.0,neutral or dissatisfied +85722,103635,Female,Loyal Customer,48,Business travel,Business,405,2,2,2,2,3,4,5,5,5,5,5,4,5,5,22,125.0,satisfied +85723,116966,Female,Loyal Customer,42,Business travel,Business,1951,1,1,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +85724,52753,Female,Loyal Customer,58,Business travel,Business,1874,4,4,5,4,3,4,5,5,5,5,5,4,5,5,18,10.0,satisfied +85725,63516,Male,Loyal Customer,46,Business travel,Business,1513,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,13.0,satisfied +85726,90276,Female,Loyal Customer,26,Business travel,Business,879,2,5,5,5,2,2,2,2,4,2,3,1,3,2,26,16.0,neutral or dissatisfied +85727,99379,Male,Loyal Customer,59,Business travel,Business,2060,2,2,2,2,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +85728,11949,Female,Loyal Customer,44,Personal Travel,Eco,781,3,4,3,3,2,5,4,5,5,3,5,3,5,5,55,59.0,neutral or dissatisfied +85729,86221,Male,disloyal Customer,40,Business travel,Business,356,2,2,2,4,1,2,1,1,1,4,3,1,3,1,5,0.0,neutral or dissatisfied +85730,59268,Male,Loyal Customer,26,Personal Travel,Eco,4963,4,4,3,1,3,1,1,4,1,4,5,1,3,1,0,0.0,satisfied +85731,118368,Male,Loyal Customer,51,Personal Travel,Eco Plus,639,3,4,3,1,1,3,1,1,3,3,4,3,5,1,1,11.0,neutral or dissatisfied +85732,90241,Female,Loyal Customer,46,Business travel,Eco,1121,2,3,3,3,3,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +85733,129197,Female,Loyal Customer,49,Business travel,Business,2288,3,3,3,3,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +85734,12093,Male,Loyal Customer,61,Personal Travel,Business,1034,4,4,4,2,3,4,5,3,3,4,3,5,3,3,0,13.0,neutral or dissatisfied +85735,48286,Male,Loyal Customer,25,Personal Travel,Eco Plus,192,4,4,4,1,2,4,2,2,3,5,4,3,4,2,13,15.0,neutral or dissatisfied +85736,112913,Male,Loyal Customer,55,Business travel,Eco,729,4,3,3,3,4,4,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +85737,124523,Female,disloyal Customer,22,Business travel,Eco,1276,3,3,3,1,5,3,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +85738,98414,Male,Loyal Customer,56,Personal Travel,Eco Plus,462,4,5,4,3,3,4,3,3,4,2,4,5,4,3,11,,satisfied +85739,23783,Male,Loyal Customer,49,Business travel,Eco,438,4,4,3,3,4,4,4,4,2,2,5,1,3,4,9,0.0,satisfied +85740,128439,Female,Loyal Customer,61,Business travel,Business,3620,0,0,0,4,4,4,3,3,3,5,5,4,3,5,0,0.0,satisfied +85741,47172,Male,Loyal Customer,60,Business travel,Eco,945,2,1,2,2,2,2,2,2,3,1,3,3,3,2,2,5.0,neutral or dissatisfied +85742,37108,Male,Loyal Customer,39,Business travel,Eco,1179,4,3,3,3,4,4,4,4,2,1,5,3,2,4,6,0.0,satisfied +85743,105799,Male,Loyal Customer,51,Personal Travel,Eco,787,2,4,1,2,3,1,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +85744,52190,Female,disloyal Customer,36,Business travel,Eco,651,4,0,4,4,4,4,4,4,2,1,2,3,2,4,2,0.0,neutral or dissatisfied +85745,121075,Male,Loyal Customer,26,Business travel,Eco Plus,992,2,1,2,1,2,2,3,2,4,2,4,2,4,2,9,1.0,neutral or dissatisfied +85746,87565,Female,Loyal Customer,51,Business travel,Business,432,3,3,2,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +85747,106728,Female,disloyal Customer,30,Business travel,Business,945,2,2,2,1,2,2,2,2,3,2,5,5,5,2,9,0.0,neutral or dissatisfied +85748,31449,Female,Loyal Customer,42,Business travel,Business,3339,2,2,2,2,3,4,5,5,5,5,5,4,5,4,13,9.0,satisfied +85749,13392,Female,Loyal Customer,54,Business travel,Business,456,4,3,3,3,5,2,2,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +85750,109081,Female,Loyal Customer,17,Personal Travel,Eco,1041,3,4,3,3,5,3,5,5,3,5,4,3,3,5,9,5.0,neutral or dissatisfied +85751,25340,Male,Loyal Customer,20,Personal Travel,Eco,829,3,4,3,4,2,3,2,2,3,2,5,5,4,2,24,10.0,neutral or dissatisfied +85752,126791,Female,Loyal Customer,29,Business travel,Business,2077,2,5,5,5,2,2,2,2,2,2,3,1,3,2,4,17.0,neutral or dissatisfied +85753,120635,Male,Loyal Customer,49,Business travel,Business,1796,5,5,2,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +85754,87860,Female,Loyal Customer,41,Personal Travel,Eco,214,2,0,2,3,2,2,1,2,5,5,4,3,5,2,10,15.0,neutral or dissatisfied +85755,65796,Male,Loyal Customer,40,Business travel,Business,1389,5,5,5,5,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +85756,112040,Female,Loyal Customer,56,Business travel,Business,3093,1,1,1,1,4,4,4,5,5,5,5,3,5,5,34,12.0,satisfied +85757,17767,Female,Loyal Customer,40,Business travel,Eco,1214,4,3,3,3,4,4,4,4,2,2,4,3,1,4,110,,satisfied +85758,28095,Female,Loyal Customer,47,Personal Travel,Business,550,3,5,3,2,5,4,5,4,4,3,2,3,4,3,0,1.0,neutral or dissatisfied +85759,18678,Male,Loyal Customer,33,Personal Travel,Eco,201,3,4,3,3,4,3,4,4,4,2,3,2,4,4,0,0.0,neutral or dissatisfied +85760,96901,Female,Loyal Customer,31,Personal Travel,Eco,781,2,3,2,3,5,2,1,5,4,3,4,5,5,5,6,6.0,neutral or dissatisfied +85761,99045,Female,Loyal Customer,42,Business travel,Business,453,3,5,5,5,5,3,3,3,3,2,3,2,3,1,116,114.0,neutral or dissatisfied +85762,42321,Male,Loyal Customer,11,Personal Travel,Eco,834,5,4,5,3,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +85763,8544,Male,Loyal Customer,56,Business travel,Business,109,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +85764,51396,Female,Loyal Customer,46,Personal Travel,Eco Plus,209,1,3,1,3,5,1,4,3,3,1,5,1,3,2,2,0.0,neutral or dissatisfied +85765,767,Female,Loyal Customer,46,Business travel,Business,1942,3,3,3,3,5,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +85766,90449,Female,Loyal Customer,32,Business travel,Business,2861,5,5,5,5,4,4,4,4,3,3,4,3,4,4,16,25.0,satisfied +85767,61160,Male,Loyal Customer,46,Business travel,Business,846,1,1,1,1,4,4,4,5,5,5,5,5,5,4,9,13.0,satisfied +85768,31920,Female,Loyal Customer,37,Business travel,Business,3653,5,5,5,5,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +85769,29211,Male,Loyal Customer,24,Personal Travel,Eco,2311,2,4,2,2,4,2,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +85770,125437,Male,Loyal Customer,45,Business travel,Eco Plus,735,2,3,3,3,2,2,2,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +85771,69739,Male,Loyal Customer,56,Business travel,Eco Plus,1372,2,2,2,2,2,2,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +85772,14295,Female,Loyal Customer,56,Business travel,Eco,429,4,3,5,3,3,4,4,4,4,4,4,1,4,3,0,0.0,satisfied +85773,85744,Male,Loyal Customer,28,Business travel,Business,3010,2,2,2,2,2,2,2,2,5,5,4,5,4,2,0,0.0,satisfied +85774,54258,Male,Loyal Customer,27,Personal Travel,Eco,1222,2,4,2,4,2,2,4,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +85775,83545,Female,Loyal Customer,53,Personal Travel,Eco,1121,4,2,4,3,3,3,3,3,3,4,3,3,3,3,5,0.0,neutral or dissatisfied +85776,3752,Female,Loyal Customer,38,Business travel,Business,1733,4,2,4,4,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +85777,32588,Female,disloyal Customer,19,Business travel,Eco,101,2,2,2,4,3,2,3,3,3,5,3,1,4,3,9,8.0,neutral or dissatisfied +85778,35044,Male,Loyal Customer,50,Business travel,Business,2079,1,4,4,4,3,2,2,1,1,1,1,4,1,3,19,19.0,neutral or dissatisfied +85779,48555,Female,Loyal Customer,59,Personal Travel,Eco,737,5,2,5,4,4,4,4,2,2,5,2,1,2,2,9,6.0,satisfied +85780,58408,Male,Loyal Customer,52,Business travel,Business,1588,1,1,1,1,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +85781,50909,Female,Loyal Customer,11,Personal Travel,Eco,308,3,5,3,3,2,3,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +85782,12412,Male,Loyal Customer,69,Business travel,Eco,305,4,1,1,1,4,4,4,4,5,2,2,3,3,4,0,0.0,satisfied +85783,95659,Female,Loyal Customer,55,Personal Travel,Eco,928,2,3,2,5,5,5,5,3,3,2,5,5,3,2,15,9.0,neutral or dissatisfied +85784,116537,Male,Loyal Customer,40,Personal Travel,Eco,447,1,4,1,4,5,1,5,5,3,4,4,3,5,5,82,71.0,neutral or dissatisfied +85785,8884,Female,Loyal Customer,49,Personal Travel,Eco,622,3,4,3,1,5,5,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +85786,100042,Female,Loyal Customer,22,Business travel,Eco,220,5,3,2,2,5,5,4,5,3,4,3,4,3,5,28,41.0,satisfied +85787,95583,Female,Loyal Customer,46,Business travel,Business,756,5,5,5,5,4,5,4,5,5,5,5,3,5,3,10,18.0,satisfied +85788,31298,Female,disloyal Customer,27,Business travel,Eco,680,2,2,2,2,2,2,2,2,3,1,5,3,3,2,0,0.0,neutral or dissatisfied +85789,127044,Male,Loyal Customer,36,Business travel,Business,338,3,5,5,5,2,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +85790,110296,Female,Loyal Customer,58,Business travel,Business,925,5,5,5,5,5,5,4,3,3,3,3,5,3,4,24,29.0,satisfied +85791,104472,Female,disloyal Customer,22,Business travel,Eco,1015,1,1,1,5,4,1,2,4,5,3,4,4,5,4,7,1.0,neutral or dissatisfied +85792,98441,Male,Loyal Customer,51,Business travel,Business,814,1,1,1,1,3,5,5,4,4,4,4,4,4,5,37,13.0,satisfied +85793,79441,Female,Loyal Customer,54,Personal Travel,Eco,187,2,5,2,3,5,5,5,2,2,2,2,5,2,4,17,19.0,neutral or dissatisfied +85794,68542,Female,Loyal Customer,42,Business travel,Business,3874,4,4,4,4,3,2,2,5,5,5,5,1,5,2,0,0.0,satisfied +85795,10139,Male,Loyal Customer,45,Business travel,Business,1157,1,1,1,1,2,4,5,5,5,5,5,4,5,3,51,42.0,satisfied +85796,27758,Male,Loyal Customer,26,Business travel,Business,1533,2,2,3,2,4,4,4,4,3,3,4,3,2,4,0,0.0,satisfied +85797,114795,Female,Loyal Customer,56,Business travel,Business,446,4,5,4,4,5,4,5,4,4,4,4,3,4,3,3,0.0,satisfied +85798,6156,Female,Loyal Customer,41,Business travel,Eco,409,3,5,5,5,2,3,2,2,2,4,4,1,4,2,0,0.0,neutral or dissatisfied +85799,18073,Female,Loyal Customer,47,Personal Travel,Eco,605,3,4,3,1,5,4,4,5,5,3,5,5,5,4,28,38.0,neutral or dissatisfied +85800,87335,Male,Loyal Customer,43,Business travel,Business,2257,2,2,2,2,4,4,4,5,5,5,5,4,5,3,40,49.0,satisfied +85801,8380,Male,Loyal Customer,22,Business travel,Business,1522,3,2,2,2,3,3,3,3,4,4,2,1,2,3,0,0.0,neutral or dissatisfied +85802,38926,Female,Loyal Customer,75,Business travel,Eco,205,4,2,5,5,2,2,1,4,4,4,4,5,4,2,0,0.0,satisfied +85803,129091,Male,disloyal Customer,34,Business travel,Eco,1499,1,1,1,4,1,1,1,3,1,3,4,1,4,1,0,30.0,neutral or dissatisfied +85804,84441,Female,Loyal Customer,22,Business travel,Eco Plus,606,0,5,0,2,3,0,3,3,5,3,3,1,2,3,0,0.0,satisfied +85805,13990,Male,Loyal Customer,39,Personal Travel,Business,160,3,1,3,4,1,3,3,2,2,3,4,4,2,2,0,0.0,neutral or dissatisfied +85806,59747,Male,Loyal Customer,53,Business travel,Business,2687,5,5,5,5,2,4,4,5,5,5,5,5,5,5,20,7.0,satisfied +85807,37723,Female,Loyal Customer,31,Personal Travel,Eco,944,2,5,2,5,5,2,3,5,1,4,4,2,3,5,0,,neutral or dissatisfied +85808,124011,Female,Loyal Customer,53,Business travel,Business,184,1,1,1,1,3,3,3,5,5,5,5,2,5,2,0,0.0,satisfied +85809,92212,Female,Loyal Customer,68,Personal Travel,Eco,1979,5,3,5,3,4,4,1,5,5,5,4,5,5,2,0,0.0,satisfied +85810,96225,Male,Loyal Customer,59,Business travel,Business,687,1,5,4,5,2,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +85811,81591,Male,Loyal Customer,30,Business travel,Business,334,0,1,1,3,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +85812,96816,Female,disloyal Customer,32,Business travel,Business,781,3,3,3,3,2,3,5,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +85813,15200,Female,Loyal Customer,65,Personal Travel,Eco,544,3,2,3,3,1,3,3,4,4,3,4,4,4,2,9,0.0,neutral or dissatisfied +85814,68006,Female,disloyal Customer,22,Business travel,Business,304,5,2,5,2,3,2,3,3,5,5,5,4,5,3,0,0.0,satisfied +85815,109038,Male,Loyal Customer,45,Business travel,Eco,849,4,3,3,3,4,4,4,4,4,1,4,4,3,4,16,19.0,neutral or dissatisfied +85816,21126,Female,Loyal Customer,51,Personal Travel,Eco,106,3,5,3,2,3,4,5,3,3,3,3,5,3,5,10,6.0,neutral or dissatisfied +85817,13612,Male,Loyal Customer,53,Business travel,Eco Plus,152,5,5,5,5,5,5,5,5,1,5,2,3,2,5,0,4.0,satisfied +85818,54316,Male,Loyal Customer,26,Business travel,Eco,1597,3,3,3,3,3,3,2,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +85819,47495,Female,Loyal Customer,19,Personal Travel,Eco,558,1,4,1,1,5,1,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +85820,118462,Male,Loyal Customer,40,Business travel,Business,338,1,1,1,1,3,4,4,5,5,5,5,5,5,3,17,0.0,satisfied +85821,49068,Female,Loyal Customer,63,Business travel,Business,2944,2,2,2,2,3,1,3,3,3,4,4,3,3,3,0,0.0,satisfied +85822,22558,Male,Loyal Customer,60,Personal Travel,Business,300,1,1,1,1,4,1,2,4,4,1,4,3,4,2,2,0.0,neutral or dissatisfied +85823,121787,Female,Loyal Customer,44,Business travel,Business,449,5,5,5,5,4,4,5,4,4,4,4,4,4,3,5,0.0,satisfied +85824,74816,Male,Loyal Customer,19,Personal Travel,Eco Plus,1171,2,5,3,4,4,3,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +85825,102756,Female,Loyal Customer,48,Personal Travel,Eco Plus,255,1,5,1,3,3,1,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +85826,107160,Female,Loyal Customer,55,Business travel,Eco,668,1,5,5,5,2,4,4,1,1,1,1,4,1,1,20,13.0,neutral or dissatisfied +85827,61566,Female,Loyal Customer,66,Personal Travel,Eco Plus,2419,1,4,1,4,2,5,4,4,4,1,4,5,4,4,17,0.0,neutral or dissatisfied +85828,100904,Male,Loyal Customer,34,Personal Travel,Eco,377,5,2,5,4,5,5,5,5,1,3,4,1,3,5,15,11.0,satisfied +85829,60162,Female,Loyal Customer,69,Personal Travel,Eco,1005,2,5,2,1,3,4,4,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +85830,100630,Female,Loyal Customer,51,Business travel,Eco,349,4,3,3,3,4,4,3,4,4,4,4,2,4,1,26,21.0,neutral or dissatisfied +85831,11123,Female,Loyal Customer,35,Personal Travel,Eco,458,2,5,2,4,4,2,4,4,5,4,5,4,4,4,5,0.0,neutral or dissatisfied +85832,25514,Male,disloyal Customer,47,Business travel,Eco,116,1,0,2,2,5,2,5,5,3,2,3,4,5,5,0,0.0,neutral or dissatisfied +85833,10832,Male,Loyal Customer,22,Business travel,Business,517,1,1,1,1,4,4,4,4,3,3,4,4,4,4,2,0.0,satisfied +85834,11458,Male,Loyal Customer,41,Business travel,Eco Plus,429,3,4,4,4,3,3,3,3,1,3,3,1,3,3,0,1.0,neutral or dissatisfied +85835,121762,Male,Loyal Customer,45,Personal Travel,Business,449,3,4,3,3,3,4,4,3,3,3,1,4,3,5,0,0.0,neutral or dissatisfied +85836,4469,Male,Loyal Customer,12,Personal Travel,Eco,1005,4,4,4,4,4,2,2,3,5,5,4,2,3,2,160,153.0,neutral or dissatisfied +85837,48587,Male,Loyal Customer,30,Personal Travel,Eco,916,2,5,2,3,1,2,1,1,3,5,3,5,4,1,0,0.0,neutral or dissatisfied +85838,4427,Female,Loyal Customer,47,Business travel,Business,3435,2,2,2,2,4,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +85839,97674,Female,Loyal Customer,12,Personal Travel,Eco,491,5,2,5,3,5,4,4,3,1,4,4,4,3,4,138,158.0,satisfied +85840,34822,Male,Loyal Customer,27,Personal Travel,Eco,264,5,4,5,5,1,5,1,1,5,2,3,5,3,1,0,0.0,satisfied +85841,91122,Male,Loyal Customer,44,Personal Travel,Eco,406,2,4,2,3,1,2,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +85842,27979,Male,Loyal Customer,17,Business travel,Business,2378,3,2,2,2,2,3,3,1,2,2,3,3,3,3,12,26.0,neutral or dissatisfied +85843,5319,Female,Loyal Customer,56,Personal Travel,Eco Plus,295,2,5,2,2,3,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +85844,15970,Male,Loyal Customer,70,Business travel,Eco Plus,338,1,1,1,1,1,1,1,1,4,2,3,1,4,1,39,36.0,neutral or dissatisfied +85845,51601,Male,Loyal Customer,47,Business travel,Eco,370,5,3,5,5,5,5,5,5,4,1,4,5,3,5,8,15.0,satisfied +85846,70225,Male,Loyal Customer,46,Business travel,Eco,1068,3,2,2,2,3,3,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +85847,102986,Female,disloyal Customer,39,Business travel,Business,328,3,3,3,1,2,3,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +85848,78202,Female,Loyal Customer,50,Business travel,Business,1958,1,1,1,1,2,5,4,5,5,5,5,3,5,5,17,2.0,satisfied +85849,116095,Male,Loyal Customer,15,Personal Travel,Eco,337,2,4,5,4,3,5,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +85850,117559,Male,Loyal Customer,39,Business travel,Eco,347,3,1,1,1,3,3,3,3,3,3,4,2,3,3,13,8.0,neutral or dissatisfied +85851,15829,Female,Loyal Customer,45,Business travel,Business,3105,1,1,1,1,4,1,1,5,5,5,4,3,5,4,0,0.0,satisfied +85852,123061,Male,disloyal Customer,66,Business travel,Business,468,5,5,5,5,2,5,2,2,3,2,5,4,5,2,0,0.0,satisfied +85853,89969,Female,Loyal Customer,27,Personal Travel,Eco,1416,3,4,3,3,2,3,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +85854,14721,Male,Loyal Customer,29,Personal Travel,Eco,419,4,1,4,4,1,4,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +85855,49939,Male,Loyal Customer,56,Business travel,Business,3284,4,5,5,5,2,2,2,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +85856,118496,Male,Loyal Customer,45,Business travel,Business,3095,2,2,2,2,5,4,5,4,4,4,4,5,4,5,20,13.0,satisfied +85857,100280,Female,Loyal Customer,48,Business travel,Business,1052,1,1,1,1,4,5,5,4,4,4,4,4,4,4,32,28.0,satisfied +85858,12119,Male,Loyal Customer,41,Personal Travel,Eco,1034,2,5,2,4,2,2,1,2,3,5,4,5,4,2,52,75.0,neutral or dissatisfied +85859,119632,Male,disloyal Customer,24,Business travel,Business,1727,4,4,4,1,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +85860,110540,Male,Loyal Customer,40,Business travel,Business,488,5,5,3,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +85861,32628,Male,disloyal Customer,19,Business travel,Eco,101,1,0,1,5,4,1,4,4,5,5,2,1,1,4,0,0.0,neutral or dissatisfied +85862,31562,Male,Loyal Customer,31,Business travel,Eco Plus,967,4,3,3,3,4,4,4,4,2,3,1,1,2,4,0,0.0,satisfied +85863,81320,Male,disloyal Customer,20,Business travel,Business,1299,4,5,4,4,5,4,5,5,4,3,4,3,4,5,0,12.0,satisfied +85864,79323,Female,disloyal Customer,35,Business travel,Business,1020,4,4,4,4,4,4,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +85865,116473,Female,Loyal Customer,14,Personal Travel,Eco,371,2,1,2,2,4,2,4,4,3,2,1,3,2,4,50,44.0,neutral or dissatisfied +85866,115959,Male,Loyal Customer,16,Personal Travel,Eco,372,5,4,5,5,5,5,2,5,5,5,5,4,4,5,0,8.0,satisfied +85867,42497,Male,disloyal Customer,38,Business travel,Eco,495,1,3,1,1,3,1,3,3,3,5,1,2,4,3,0,0.0,neutral or dissatisfied +85868,74037,Male,Loyal Customer,57,Business travel,Business,2559,2,3,3,3,4,4,3,2,2,2,2,1,2,2,39,36.0,neutral or dissatisfied +85869,17132,Female,disloyal Customer,24,Business travel,Eco,472,1,2,1,2,4,1,4,4,3,5,1,3,2,4,47,60.0,neutral or dissatisfied +85870,5621,Female,Loyal Customer,10,Personal Travel,Eco,624,3,3,3,2,4,3,4,4,4,4,3,5,4,4,118,115.0,neutral or dissatisfied +85871,3209,Female,Loyal Customer,15,Personal Travel,Eco,693,3,4,3,5,3,5,3,3,3,5,5,3,5,3,218,279.0,neutral or dissatisfied +85872,93499,Male,Loyal Customer,30,Business travel,Eco,1020,2,5,5,5,2,2,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +85873,85857,Male,Loyal Customer,29,Personal Travel,Eco Plus,666,1,5,1,5,3,1,1,3,3,4,3,4,5,3,1,0.0,neutral or dissatisfied +85874,12045,Female,Loyal Customer,61,Business travel,Eco,351,4,3,5,5,2,4,3,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +85875,109564,Male,Loyal Customer,62,Personal Travel,Eco,994,2,4,2,4,3,2,3,3,4,4,5,3,4,3,6,0.0,neutral or dissatisfied +85876,64231,Male,disloyal Customer,48,Business travel,Business,1660,5,5,5,3,4,5,4,4,4,5,4,4,4,4,0,6.0,satisfied +85877,57834,Male,disloyal Customer,24,Business travel,Eco,1491,1,1,1,3,1,1,1,1,2,1,4,2,4,1,0,0.0,neutral or dissatisfied +85878,4568,Male,Loyal Customer,16,Personal Travel,Eco,561,4,3,4,2,1,4,1,1,5,4,4,3,1,1,0,6.0,neutral or dissatisfied +85879,127899,Male,Loyal Customer,41,Business travel,Business,1671,1,1,2,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +85880,23523,Male,Loyal Customer,42,Personal Travel,Eco,303,4,3,4,4,3,4,3,3,2,2,3,3,4,3,0,0.0,satisfied +85881,116005,Male,Loyal Customer,51,Personal Travel,Eco,333,3,4,3,5,2,3,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +85882,39859,Male,Loyal Customer,36,Business travel,Business,184,3,3,3,3,2,2,2,4,4,4,4,1,4,5,0,0.0,satisfied +85883,115041,Male,Loyal Customer,50,Business travel,Business,2235,3,3,3,3,4,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +85884,129261,Female,Loyal Customer,38,Business travel,Eco Plus,1064,3,3,3,3,3,3,3,3,4,1,3,1,3,3,7,1.0,neutral or dissatisfied +85885,118956,Female,disloyal Customer,24,Business travel,Eco,282,2,0,2,1,4,2,4,4,2,3,5,2,1,4,0,0.0,neutral or dissatisfied +85886,99165,Male,Loyal Customer,29,Business travel,Eco,1076,3,4,4,4,3,3,3,3,4,3,3,3,3,3,29,41.0,neutral or dissatisfied +85887,3639,Male,Loyal Customer,44,Business travel,Business,431,5,5,3,5,5,4,5,5,5,5,5,3,5,4,6,,satisfied +85888,97438,Female,disloyal Customer,38,Business travel,Eco,585,2,1,2,4,4,2,4,4,3,5,4,1,3,4,5,0.0,neutral or dissatisfied +85889,96781,Female,Loyal Customer,52,Business travel,Business,3897,5,5,5,5,5,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +85890,15698,Female,Loyal Customer,28,Personal Travel,Business,419,1,4,1,3,2,1,2,2,5,5,5,3,1,2,0,0.0,neutral or dissatisfied +85891,103522,Female,Loyal Customer,25,Business travel,Eco Plus,1256,0,4,0,2,4,0,1,4,5,1,4,4,2,4,0,0.0,satisfied +85892,95323,Male,Loyal Customer,69,Personal Travel,Eco,239,4,3,4,2,2,4,2,2,1,5,3,1,3,2,5,0.0,satisfied +85893,17496,Female,Loyal Customer,34,Business travel,Business,3828,3,3,3,3,2,1,1,5,5,5,5,3,5,2,0,0.0,satisfied +85894,5184,Female,Loyal Customer,39,Business travel,Business,295,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,4.0,satisfied +85895,121675,Female,Loyal Customer,18,Personal Travel,Eco,328,2,3,1,4,5,1,3,5,2,2,4,4,4,5,0,0.0,neutral or dissatisfied +85896,9322,Male,Loyal Customer,28,Business travel,Business,3776,3,3,3,3,3,3,3,3,2,3,4,3,4,3,85,104.0,neutral or dissatisfied +85897,44684,Female,disloyal Customer,33,Business travel,Eco,67,2,0,1,4,3,1,3,3,1,1,3,2,4,3,79,105.0,neutral or dissatisfied +85898,52153,Male,Loyal Customer,63,Personal Travel,Business,598,2,2,3,5,4,4,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +85899,100022,Male,Loyal Customer,39,Business travel,Business,2513,1,1,1,1,4,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +85900,36765,Male,Loyal Customer,34,Business travel,Business,2704,1,1,2,1,5,5,5,3,5,4,2,5,4,5,0,0.0,satisfied +85901,16935,Male,Loyal Customer,34,Business travel,Business,820,3,3,3,3,1,3,4,4,4,4,4,5,4,2,4,0.0,satisfied +85902,106526,Male,Loyal Customer,60,Personal Travel,Eco,271,2,1,2,3,5,2,5,5,1,3,4,4,4,5,17,13.0,neutral or dissatisfied +85903,58888,Female,Loyal Customer,43,Business travel,Business,2773,4,3,4,4,3,4,4,3,3,2,3,5,3,3,3,0.0,satisfied +85904,90332,Male,Loyal Customer,52,Business travel,Business,406,1,1,1,1,3,5,4,5,5,5,5,4,5,3,0,1.0,satisfied +85905,62638,Female,Loyal Customer,57,Personal Travel,Eco,1744,2,4,2,2,4,5,5,2,2,2,2,3,2,4,32,50.0,neutral or dissatisfied +85906,127168,Male,Loyal Customer,39,Personal Travel,Eco,338,2,5,2,2,4,2,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +85907,125539,Male,Loyal Customer,60,Business travel,Business,226,0,0,0,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +85908,78603,Male,Loyal Customer,41,Business travel,Business,1426,4,4,4,4,3,5,5,5,5,4,5,3,5,3,3,0.0,satisfied +85909,54794,Male,Loyal Customer,29,Personal Travel,Business,775,1,1,1,4,2,1,1,2,4,2,3,1,4,2,0,30.0,neutral or dissatisfied +85910,110005,Female,Loyal Customer,42,Business travel,Business,2070,1,1,1,1,3,5,4,4,4,4,4,4,4,3,13,0.0,satisfied +85911,81797,Male,Loyal Customer,55,Business travel,Business,3049,2,2,2,2,4,4,5,4,4,4,4,3,4,4,8,0.0,satisfied +85912,55329,Female,Loyal Customer,46,Personal Travel,Eco,1117,4,4,4,2,5,5,5,4,4,4,4,5,4,5,39,27.0,satisfied +85913,101448,Female,Loyal Customer,56,Business travel,Business,345,0,0,0,2,5,5,4,1,1,1,1,4,1,4,0,0.0,satisfied +85914,21038,Male,Loyal Customer,55,Business travel,Business,2374,0,0,0,2,4,4,3,5,5,5,5,1,5,2,49,43.0,satisfied +85915,66482,Female,Loyal Customer,34,Business travel,Eco,447,3,2,2,2,3,3,3,3,4,2,4,2,4,3,1,9.0,neutral or dissatisfied +85916,114184,Male,disloyal Customer,45,Business travel,Business,862,4,4,4,4,4,4,4,4,4,5,5,4,5,4,2,0.0,satisfied +85917,27785,Male,disloyal Customer,20,Business travel,Eco,1448,3,3,3,1,3,3,3,3,1,4,2,3,1,3,0,0.0,neutral or dissatisfied +85918,18279,Male,Loyal Customer,76,Business travel,Eco Plus,224,4,4,4,4,4,4,4,4,4,4,3,1,2,4,0,19.0,neutral or dissatisfied +85919,71708,Female,Loyal Customer,53,Personal Travel,Eco Plus,1012,2,2,2,3,2,3,4,5,5,2,1,4,5,2,0,0.0,neutral or dissatisfied +85920,89546,Female,Loyal Customer,44,Business travel,Business,3925,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +85921,9893,Male,Loyal Customer,35,Business travel,Business,508,2,3,3,3,3,3,3,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +85922,98757,Male,Loyal Customer,23,Business travel,Business,2075,2,2,2,2,2,2,2,2,2,5,2,1,4,2,26,26.0,neutral or dissatisfied +85923,431,Male,Loyal Customer,47,Personal Travel,Business,102,1,2,0,3,5,4,4,1,1,0,1,4,1,4,0,0.0,neutral or dissatisfied +85924,68348,Female,disloyal Customer,26,Business travel,Eco,906,2,2,2,4,1,2,1,1,3,1,4,3,3,1,0,0.0,neutral or dissatisfied +85925,4597,Female,Loyal Customer,40,Personal Travel,Eco,416,5,4,5,4,3,5,3,3,1,4,4,4,3,3,0,0.0,satisfied +85926,68048,Female,Loyal Customer,39,Business travel,Business,813,2,2,2,2,2,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +85927,15895,Female,Loyal Customer,36,Business travel,Eco,378,4,3,3,3,4,5,4,4,2,2,4,5,1,4,0,25.0,satisfied +85928,51275,Female,Loyal Customer,51,Business travel,Eco Plus,109,4,4,5,5,3,5,5,4,4,4,4,4,4,2,2,14.0,satisfied +85929,76783,Female,disloyal Customer,37,Business travel,Eco,546,1,4,1,4,1,1,1,1,2,5,4,3,3,1,0,16.0,neutral or dissatisfied +85930,88576,Male,Loyal Customer,50,Personal Travel,Eco,270,3,0,3,3,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +85931,121226,Female,Loyal Customer,31,Business travel,Business,2075,4,4,3,4,3,3,3,3,3,5,4,4,4,3,2,47.0,satisfied +85932,8550,Male,Loyal Customer,41,Business travel,Business,2665,2,2,2,2,2,5,4,4,4,4,4,5,4,5,7,8.0,satisfied +85933,76306,Male,Loyal Customer,48,Business travel,Business,2182,4,4,4,4,4,3,4,4,4,4,4,4,4,4,5,6.0,satisfied +85934,2261,Female,Loyal Customer,46,Business travel,Business,3612,3,3,5,3,5,5,5,5,5,5,5,4,5,4,94,99.0,satisfied +85935,30717,Female,Loyal Customer,58,Business travel,Eco,1123,3,4,4,4,2,3,3,3,3,3,3,4,3,2,0,35.0,neutral or dissatisfied +85936,83156,Female,disloyal Customer,27,Business travel,Business,957,3,3,3,1,1,3,1,1,5,2,4,4,4,1,0,2.0,neutral or dissatisfied +85937,56198,Male,Loyal Customer,60,Personal Travel,Eco,1400,2,5,2,3,2,4,4,4,5,3,4,4,3,4,188,160.0,neutral or dissatisfied +85938,103794,Male,Loyal Customer,56,Business travel,Business,1242,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +85939,120315,Female,disloyal Customer,25,Business travel,Business,268,4,0,4,3,5,4,5,5,4,5,4,5,5,5,0,0.0,satisfied +85940,20888,Female,Loyal Customer,59,Personal Travel,Eco Plus,515,3,4,3,3,5,4,4,5,5,3,5,5,5,4,13,17.0,neutral or dissatisfied +85941,28813,Female,disloyal Customer,17,Business travel,Eco,1050,1,1,1,2,5,1,5,5,2,2,3,3,4,5,0,0.0,neutral or dissatisfied +85942,41810,Male,Loyal Customer,34,Business travel,Eco,489,2,2,2,2,2,2,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +85943,69085,Female,Loyal Customer,69,Personal Travel,Eco,1389,4,4,4,1,3,4,5,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +85944,91711,Male,disloyal Customer,21,Business travel,Eco,584,2,4,2,4,3,2,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +85945,186,Male,Loyal Customer,42,Business travel,Business,3880,1,1,1,1,3,4,4,3,3,4,5,3,3,3,0,0.0,satisfied +85946,23534,Female,disloyal Customer,26,Business travel,Eco,472,5,0,4,4,1,4,3,1,4,5,3,4,4,1,0,0.0,satisfied +85947,48526,Male,disloyal Customer,11,Business travel,Eco,848,1,1,1,4,3,1,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +85948,100181,Female,Loyal Customer,21,Personal Travel,Eco,468,2,4,2,4,5,2,5,5,1,1,4,1,3,5,0,0.0,neutral or dissatisfied +85949,8523,Female,Loyal Customer,12,Personal Travel,Eco,737,3,5,3,1,3,3,3,3,3,4,5,3,4,3,0,,neutral or dissatisfied +85950,47087,Female,Loyal Customer,60,Personal Travel,Eco,351,1,5,1,1,4,5,5,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +85951,46210,Male,Loyal Customer,33,Personal Travel,Business,752,2,5,2,4,3,2,3,3,4,2,5,4,4,3,51,76.0,neutral or dissatisfied +85952,101388,Male,Loyal Customer,52,Business travel,Business,486,5,5,5,5,2,5,4,4,4,4,4,3,4,3,96,88.0,satisfied +85953,127105,Female,Loyal Customer,58,Personal Travel,Eco,651,2,3,2,4,4,2,2,5,5,2,5,2,5,2,0,0.0,neutral or dissatisfied +85954,13803,Male,Loyal Customer,38,Business travel,Eco Plus,450,4,5,5,5,4,4,4,4,4,5,4,4,4,4,11,15.0,neutral or dissatisfied +85955,127732,Male,Loyal Customer,51,Business travel,Business,255,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +85956,45408,Female,Loyal Customer,56,Business travel,Eco,458,2,1,1,1,1,4,5,2,2,2,2,1,2,3,0,0.0,satisfied +85957,25787,Male,Loyal Customer,54,Business travel,Business,762,1,1,1,1,2,1,5,4,4,4,4,5,4,2,2,0.0,satisfied +85958,31486,Male,Loyal Customer,51,Business travel,Eco,862,4,5,5,5,4,4,4,4,5,5,2,5,4,4,7,16.0,satisfied +85959,84978,Female,disloyal Customer,37,Business travel,Business,1590,3,3,3,4,2,3,2,2,5,2,5,5,4,2,2,0.0,neutral or dissatisfied +85960,114306,Male,Loyal Customer,40,Personal Travel,Eco,853,3,4,3,5,5,3,5,5,5,3,4,5,4,5,26,12.0,neutral or dissatisfied +85961,102544,Male,Loyal Customer,45,Personal Travel,Eco,397,1,4,1,4,5,1,5,5,1,2,3,1,4,5,13,21.0,neutral or dissatisfied +85962,59159,Female,Loyal Customer,39,Business travel,Business,1846,2,2,5,2,3,4,4,2,2,2,2,5,2,5,35,56.0,satisfied +85963,53917,Male,Loyal Customer,24,Business travel,Eco Plus,224,5,5,5,5,5,5,4,5,2,2,3,5,4,5,0,0.0,satisfied +85964,72814,Female,Loyal Customer,42,Business travel,Eco Plus,645,3,5,5,5,1,4,2,3,3,3,3,5,3,1,0,0.0,satisfied +85965,59388,Male,Loyal Customer,17,Personal Travel,Eco,2399,3,4,3,4,1,3,1,1,5,5,3,3,4,1,0,0.0,neutral or dissatisfied +85966,6651,Female,Loyal Customer,39,Business travel,Business,3985,2,2,3,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +85967,4207,Male,Loyal Customer,58,Business travel,Business,888,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +85968,47843,Female,Loyal Customer,46,Business travel,Eco,748,5,5,3,5,5,2,4,5,5,5,5,1,5,5,0,0.0,satisfied +85969,57287,Male,Loyal Customer,28,Business travel,Business,2250,1,1,1,1,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +85970,121187,Female,Loyal Customer,64,Personal Travel,Eco,2402,0,2,0,3,0,3,3,1,2,4,4,3,2,3,0,0.0,satisfied +85971,36696,Female,Loyal Customer,38,Personal Travel,Eco,1197,2,5,2,2,4,2,4,4,5,2,3,3,4,4,0,0.0,neutral or dissatisfied +85972,28093,Female,Loyal Customer,27,Personal Travel,Business,873,5,0,5,3,4,5,4,4,5,2,3,5,4,4,0,0.0,satisfied +85973,126695,Male,Loyal Customer,42,Business travel,Business,2402,5,5,5,5,3,3,5,4,4,4,4,3,4,5,0,2.0,satisfied +85974,27250,Male,Loyal Customer,30,Personal Travel,Eco Plus,1024,3,4,2,3,4,2,3,4,4,3,5,4,4,4,0,3.0,neutral or dissatisfied +85975,33837,Male,Loyal Customer,24,Business travel,Business,1609,3,3,3,3,5,5,5,5,4,2,3,3,2,5,0,0.0,satisfied +85976,34618,Male,Loyal Customer,17,Personal Travel,Eco Plus,1598,3,4,3,2,5,3,5,5,3,3,3,4,5,5,72,63.0,neutral or dissatisfied +85977,110004,Female,Loyal Customer,34,Business travel,Business,1142,4,4,4,4,4,5,4,4,4,4,4,5,4,4,3,0.0,satisfied +85978,63770,Female,Loyal Customer,29,Business travel,Business,1721,1,1,1,1,5,5,5,5,5,2,5,3,4,5,0,19.0,satisfied +85979,48613,Female,Loyal Customer,33,Business travel,Eco Plus,844,4,4,4,4,4,4,4,4,5,3,5,2,1,4,0,0.0,satisfied +85980,96726,Female,Loyal Customer,33,Personal Travel,Eco,696,1,5,1,4,4,1,4,4,5,5,4,5,5,4,2,2.0,neutral or dissatisfied +85981,73873,Female,Loyal Customer,55,Business travel,Business,2342,4,4,4,4,4,4,4,4,2,5,4,4,4,4,0,0.0,satisfied +85982,82506,Male,Loyal Customer,41,Business travel,Business,1749,4,4,4,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +85983,112581,Female,Loyal Customer,40,Business travel,Business,2546,2,2,2,2,3,5,5,4,4,4,4,3,4,5,34,32.0,satisfied +85984,6298,Female,Loyal Customer,36,Business travel,Eco Plus,293,4,4,4,4,4,4,4,4,2,4,4,2,4,4,8,3.0,neutral or dissatisfied +85985,47624,Female,Loyal Customer,45,Business travel,Business,1334,5,5,5,5,4,3,2,5,5,5,5,3,5,4,0,9.0,satisfied +85986,62319,Male,Loyal Customer,63,Personal Travel,Eco,414,4,5,4,4,5,4,5,5,5,2,4,5,3,5,5,0.0,satisfied +85987,89069,Female,Loyal Customer,53,Business travel,Business,1947,3,3,3,3,5,4,4,3,3,3,3,5,3,4,0,4.0,satisfied +85988,101031,Male,Loyal Customer,37,Business travel,Eco Plus,806,3,3,3,3,3,3,3,3,1,4,4,1,3,3,11,0.0,neutral or dissatisfied +85989,114389,Female,Loyal Customer,45,Business travel,Business,3398,5,5,5,5,5,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +85990,55312,Male,Loyal Customer,32,Business travel,Eco,1325,2,4,4,4,2,3,2,2,2,1,4,3,3,2,0,0.0,neutral or dissatisfied +85991,22568,Male,disloyal Customer,45,Business travel,Eco,300,3,5,3,5,3,3,3,3,1,4,1,1,1,3,0,0.0,neutral or dissatisfied +85992,105644,Female,Loyal Customer,58,Business travel,Business,883,5,5,5,5,5,5,5,5,5,5,5,4,5,5,22,23.0,satisfied +85993,106012,Male,Loyal Customer,59,Personal Travel,Eco,1999,1,5,1,5,5,1,5,5,5,5,4,3,4,5,11,12.0,neutral or dissatisfied +85994,100472,Female,Loyal Customer,28,Business travel,Business,2774,5,5,5,5,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +85995,48966,Female,disloyal Customer,55,Business travel,Eco,109,3,5,2,5,4,2,3,4,5,1,3,5,4,4,0,0.0,neutral or dissatisfied +85996,63330,Female,Loyal Customer,68,Business travel,Business,3263,5,5,5,5,4,3,1,4,4,4,4,5,4,4,0,0.0,satisfied +85997,63667,Male,Loyal Customer,24,Personal Travel,Eco,2405,1,5,1,2,3,1,5,3,3,2,5,2,4,3,44,35.0,neutral or dissatisfied +85998,34994,Male,Loyal Customer,45,Business travel,Business,1182,1,1,1,1,4,2,1,5,5,5,5,5,5,5,0,0.0,satisfied +85999,127711,Male,Loyal Customer,30,Personal Travel,Business,255,4,4,4,3,3,4,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +86000,100634,Male,Loyal Customer,58,Business travel,Business,349,2,2,2,2,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +86001,78557,Female,Loyal Customer,28,Personal Travel,Eco Plus,526,2,4,2,4,3,2,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +86002,47169,Female,Loyal Customer,40,Business travel,Business,1642,2,2,2,2,4,3,1,3,3,4,3,1,3,4,0,0.0,satisfied +86003,123187,Female,Loyal Customer,36,Personal Travel,Eco,600,2,0,2,4,4,2,4,4,3,2,4,4,5,4,0,1.0,neutral or dissatisfied +86004,73107,Female,Loyal Customer,39,Business travel,Business,2174,5,5,5,5,2,3,5,4,4,4,4,3,4,5,18,20.0,satisfied +86005,25127,Male,disloyal Customer,44,Business travel,Eco,1249,3,3,3,4,4,3,4,4,4,1,4,3,3,4,38,27.0,neutral or dissatisfied +86006,125881,Male,Loyal Customer,12,Personal Travel,Eco,861,1,5,1,2,4,1,2,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +86007,39296,Male,Loyal Customer,52,Personal Travel,Eco,67,3,5,3,4,5,3,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +86008,104604,Female,Loyal Customer,56,Personal Travel,Eco,369,1,3,1,5,3,4,3,4,4,1,4,1,4,4,0,14.0,neutral or dissatisfied +86009,5568,Male,Loyal Customer,69,Personal Travel,Eco,588,3,3,3,3,4,3,4,4,4,2,3,2,4,4,5,0.0,neutral or dissatisfied +86010,59379,Male,disloyal Customer,27,Business travel,Eco,1059,4,4,4,4,2,4,2,2,1,1,4,2,3,2,6,18.0,neutral or dissatisfied +86011,42272,Male,disloyal Customer,38,Business travel,Eco,451,1,2,1,4,5,1,4,5,4,3,3,3,3,5,55,44.0,neutral or dissatisfied +86012,94660,Male,Loyal Customer,54,Business travel,Business,1719,4,4,4,4,3,5,4,4,4,4,4,3,4,3,4,28.0,satisfied +86013,15543,Female,Loyal Customer,45,Personal Travel,Eco,812,2,1,2,2,2,4,4,3,1,2,3,4,3,4,336,406.0,neutral or dissatisfied +86014,91582,Male,Loyal Customer,40,Personal Travel,Eco,1123,2,5,2,2,2,2,2,3,3,4,4,2,4,2,115,137.0,neutral or dissatisfied +86015,112408,Male,Loyal Customer,46,Business travel,Business,2108,2,5,2,2,4,5,4,4,4,4,4,3,4,4,12,16.0,satisfied +86016,16284,Female,disloyal Customer,23,Personal Travel,Eco,748,3,4,3,2,2,3,2,2,5,1,5,2,2,2,21,0.0,neutral or dissatisfied +86017,125859,Male,disloyal Customer,38,Business travel,Eco,992,4,4,4,2,4,4,4,4,4,2,2,1,2,4,14,4.0,neutral or dissatisfied +86018,90824,Male,Loyal Customer,42,Business travel,Eco,444,2,4,4,4,2,2,2,2,2,3,2,3,1,2,0,0.0,neutral or dissatisfied +86019,67072,Female,disloyal Customer,23,Business travel,Eco,1102,2,2,2,3,3,2,3,3,3,2,3,1,3,3,0,2.0,neutral or dissatisfied +86020,102149,Female,Loyal Customer,58,Business travel,Business,3785,4,4,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +86021,8051,Male,Loyal Customer,46,Business travel,Business,2192,1,1,1,1,4,5,5,2,2,2,2,4,2,5,3,3.0,satisfied +86022,19413,Male,disloyal Customer,26,Business travel,Eco,645,4,4,4,3,3,4,3,3,4,1,4,5,1,3,68,54.0,neutral or dissatisfied +86023,38355,Female,disloyal Customer,49,Business travel,Eco,1173,1,1,1,3,4,1,4,4,1,2,1,1,1,4,1,0.0,neutral or dissatisfied +86024,22972,Female,Loyal Customer,58,Business travel,Eco,489,2,2,2,2,4,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +86025,65771,Male,Loyal Customer,32,Personal Travel,Eco Plus,936,3,4,3,4,2,3,2,2,3,2,2,5,3,2,0,0.0,neutral or dissatisfied +86026,108797,Female,Loyal Customer,26,Personal Travel,Eco,406,3,5,3,2,2,3,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +86027,6620,Female,Loyal Customer,58,Business travel,Business,1945,3,3,3,3,3,4,5,4,4,4,4,4,4,3,85,75.0,satisfied +86028,33766,Male,Loyal Customer,24,Business travel,Eco Plus,266,0,5,0,2,0,5,5,2,3,1,3,5,5,5,112,146.0,satisfied +86029,108452,Male,disloyal Customer,35,Business travel,Eco,889,1,1,1,4,3,1,3,3,3,5,3,1,4,3,14,0.0,neutral or dissatisfied +86030,77124,Female,Loyal Customer,66,Personal Travel,Eco,1481,1,4,1,4,1,4,3,5,5,1,5,4,5,2,12,8.0,neutral or dissatisfied +86031,20559,Female,Loyal Customer,44,Business travel,Business,633,5,5,5,5,2,3,4,5,5,5,5,5,5,1,42,39.0,satisfied +86032,102778,Male,Loyal Customer,49,Business travel,Business,3568,1,1,1,1,4,4,4,3,3,4,5,4,3,4,358,357.0,satisfied +86033,114429,Female,Loyal Customer,55,Business travel,Business,3289,2,2,2,2,3,5,5,5,5,5,5,5,5,4,17,8.0,satisfied +86034,38695,Female,Loyal Customer,52,Business travel,Business,2583,4,4,5,4,3,3,5,2,2,2,2,3,2,3,0,0.0,satisfied +86035,53074,Female,disloyal Customer,26,Business travel,Eco Plus,1208,2,2,2,4,5,2,5,5,3,2,5,1,5,5,17,10.0,neutral or dissatisfied +86036,72745,Male,Loyal Customer,61,Personal Travel,Business,806,2,5,2,1,3,3,4,2,2,2,2,3,2,3,24,23.0,neutral or dissatisfied +86037,40559,Female,Loyal Customer,24,Business travel,Business,391,1,1,1,1,5,5,5,5,5,2,3,2,3,5,9,7.0,satisfied +86038,39644,Female,Loyal Customer,30,Business travel,Business,3877,4,4,4,4,4,4,4,4,2,2,2,4,3,4,0,0.0,satisfied +86039,124982,Female,disloyal Customer,20,Business travel,Eco,184,2,2,2,3,3,2,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +86040,92269,Male,Loyal Customer,51,Business travel,Business,1900,4,4,4,4,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +86041,34537,Female,Loyal Customer,15,Business travel,Eco,636,1,4,3,4,1,2,1,3,2,4,3,1,2,1,245,254.0,neutral or dissatisfied +86042,51832,Male,Loyal Customer,55,Business travel,Eco Plus,370,4,5,3,3,4,4,4,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +86043,118066,Male,Loyal Customer,17,Personal Travel,Eco,1262,5,5,5,4,3,5,3,3,4,2,3,3,4,3,0,0.0,satisfied +86044,49835,Female,disloyal Customer,18,Business travel,Eco,308,3,1,3,3,5,3,5,5,3,1,3,1,4,5,0,2.0,neutral or dissatisfied +86045,76472,Female,Loyal Customer,25,Business travel,Business,547,5,5,5,5,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +86046,75081,Male,Loyal Customer,59,Personal Travel,Eco Plus,2611,2,2,2,2,2,2,2,2,3,3,2,4,2,2,0,8.0,neutral or dissatisfied +86047,81819,Female,Loyal Customer,60,Business travel,Eco,1016,4,5,4,4,5,1,3,4,4,4,4,2,4,2,0,0.0,satisfied +86048,104467,Male,Loyal Customer,69,Personal Travel,Eco,1123,3,5,3,3,1,3,4,1,3,3,3,5,4,1,1,6.0,neutral or dissatisfied +86049,27450,Female,Loyal Customer,24,Business travel,Business,679,2,5,5,5,2,2,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +86050,1452,Female,Loyal Customer,53,Business travel,Business,3616,1,2,2,2,2,3,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +86051,103922,Male,disloyal Customer,19,Business travel,Eco,533,3,0,3,1,2,3,2,2,3,3,5,3,4,2,32,63.0,neutral or dissatisfied +86052,24092,Female,Loyal Customer,40,Business travel,Business,554,3,3,3,3,2,2,5,5,5,5,5,5,5,5,9,0.0,satisfied +86053,4642,Female,Loyal Customer,52,Business travel,Business,2330,4,4,1,4,5,4,4,4,4,4,4,4,4,3,0,8.0,satisfied +86054,86947,Female,Loyal Customer,35,Business travel,Business,907,3,4,3,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +86055,128178,Male,Loyal Customer,20,Personal Travel,Eco,1972,2,4,2,1,3,2,2,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +86056,64966,Female,Loyal Customer,44,Business travel,Eco,190,3,1,3,1,4,2,4,3,3,3,3,2,3,2,0,0.0,satisfied +86057,99694,Male,Loyal Customer,34,Personal Travel,Eco,442,1,4,1,4,3,1,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +86058,53654,Female,Loyal Customer,42,Business travel,Business,2582,1,1,1,1,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +86059,71268,Female,Loyal Customer,16,Personal Travel,Eco,733,4,3,4,4,5,4,5,5,2,4,4,4,4,5,22,14.0,neutral or dissatisfied +86060,72120,Female,Loyal Customer,41,Business travel,Business,3703,2,2,5,2,5,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +86061,97650,Female,Loyal Customer,16,Personal Travel,Eco,1587,3,5,3,2,3,3,3,3,4,4,3,4,5,3,0,3.0,neutral or dissatisfied +86062,15786,Female,Loyal Customer,42,Personal Travel,Eco,198,1,4,1,4,4,4,5,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +86063,30293,Female,disloyal Customer,42,Business travel,Eco,1476,3,3,3,3,5,3,2,5,3,4,3,3,3,5,0,6.0,neutral or dissatisfied +86064,120528,Female,disloyal Customer,39,Business travel,Eco,96,1,1,1,4,3,1,5,3,1,1,3,2,3,3,0,24.0,neutral or dissatisfied +86065,43411,Male,Loyal Customer,34,Business travel,Eco Plus,531,4,5,5,5,4,4,4,4,1,3,2,5,3,4,0,0.0,satisfied +86066,54059,Female,disloyal Customer,18,Business travel,Eco,1416,2,2,2,1,3,2,3,3,2,2,1,2,2,3,0,7.0,satisfied +86067,26808,Male,Loyal Customer,67,Personal Travel,Eco,1947,2,4,2,1,2,2,2,2,3,5,5,2,2,2,27,21.0,neutral or dissatisfied +86068,25406,Female,disloyal Customer,64,Business travel,Eco,990,3,3,3,4,5,3,5,5,2,5,4,2,4,5,6,0.0,neutral or dissatisfied +86069,98121,Male,Loyal Customer,18,Personal Travel,Eco,472,1,4,1,3,1,1,1,1,4,4,3,1,4,1,31,7.0,neutral or dissatisfied +86070,57050,Male,disloyal Customer,38,Business travel,Business,2133,4,4,4,1,3,4,3,3,5,3,3,5,4,3,27,0.0,satisfied +86071,17297,Male,Loyal Customer,52,Business travel,Eco,403,5,2,2,2,5,5,5,5,3,1,4,2,3,5,0,0.0,satisfied +86072,115020,Male,Loyal Customer,52,Business travel,Business,2214,3,3,3,3,3,5,5,4,4,4,4,5,4,4,12,16.0,satisfied +86073,98531,Male,Loyal Customer,23,Personal Travel,Eco,668,2,5,2,3,2,2,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +86074,118315,Male,Loyal Customer,65,Business travel,Business,602,2,4,4,4,1,4,3,2,2,2,2,1,2,3,26,13.0,neutral or dissatisfied +86075,110842,Male,Loyal Customer,15,Business travel,Business,1105,1,1,1,1,5,5,5,5,4,3,4,3,4,5,9,0.0,satisfied +86076,77295,Male,Loyal Customer,55,Business travel,Business,2166,1,1,1,1,2,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +86077,90840,Female,Loyal Customer,43,Business travel,Business,3716,2,3,3,3,3,3,3,1,1,1,2,2,1,4,24,27.0,neutral or dissatisfied +86078,46707,Male,disloyal Customer,63,Personal Travel,Eco,125,2,4,0,2,2,0,2,2,5,5,2,5,1,2,0,0.0,neutral or dissatisfied +86079,5023,Female,Loyal Customer,45,Business travel,Business,1708,4,2,4,2,4,3,4,4,4,4,4,1,4,1,0,6.0,neutral or dissatisfied +86080,98693,Female,Loyal Customer,8,Personal Travel,Eco,993,3,4,3,1,4,3,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +86081,72405,Female,Loyal Customer,52,Business travel,Business,2565,2,2,2,2,3,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +86082,79445,Female,Loyal Customer,15,Personal Travel,Eco,187,3,5,3,2,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +86083,20074,Female,Loyal Customer,34,Personal Travel,Eco,528,4,4,4,3,3,4,3,3,5,5,5,5,1,3,40,36.0,neutral or dissatisfied +86084,110419,Male,Loyal Customer,41,Business travel,Business,483,1,1,1,1,3,2,1,3,3,3,3,1,3,5,0,0.0,satisfied +86085,121508,Male,disloyal Customer,36,Business travel,Business,1727,2,2,2,4,5,2,5,5,3,2,3,4,5,5,0,0.0,neutral or dissatisfied +86086,24398,Male,Loyal Customer,55,Personal Travel,Eco Plus,669,1,1,1,3,5,1,5,5,4,3,3,3,2,5,6,3.0,neutral or dissatisfied +86087,2032,Male,disloyal Customer,22,Business travel,Eco,812,5,5,5,2,4,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +86088,62442,Female,Loyal Customer,41,Personal Travel,Eco,1943,2,5,1,1,1,4,5,3,5,5,4,5,3,5,165,130.0,neutral or dissatisfied +86089,37674,Male,Loyal Customer,39,Personal Travel,Eco,972,4,4,4,3,4,4,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +86090,31274,Female,Loyal Customer,34,Business travel,Business,770,2,3,4,3,4,3,4,2,2,2,2,3,2,2,82,73.0,neutral or dissatisfied +86091,24010,Female,disloyal Customer,22,Business travel,Business,562,2,4,2,3,1,2,1,1,4,5,3,1,4,1,53,36.0,neutral or dissatisfied +86092,46891,Female,disloyal Customer,46,Business travel,Eco,848,1,1,1,1,2,1,2,2,2,2,2,4,1,2,69,62.0,neutral or dissatisfied +86093,125166,Male,Loyal Customer,32,Business travel,Business,1681,4,3,3,3,4,3,4,4,4,3,3,3,3,4,0,24.0,neutral or dissatisfied +86094,100491,Female,disloyal Customer,29,Business travel,Eco,580,3,4,2,3,1,2,1,1,4,5,3,2,4,1,23,23.0,neutral or dissatisfied +86095,126453,Male,Loyal Customer,50,Business travel,Business,1849,3,3,3,3,2,5,5,3,3,2,3,3,3,3,0,7.0,satisfied +86096,120562,Female,Loyal Customer,59,Personal Travel,Eco,2176,4,3,4,2,4,3,3,1,1,4,1,4,1,2,0,14.0,neutral or dissatisfied +86097,4063,Male,Loyal Customer,39,Personal Travel,Eco,479,3,5,1,2,5,1,5,5,3,5,1,3,5,5,0,0.0,neutral or dissatisfied +86098,73263,Male,Loyal Customer,12,Personal Travel,Eco,675,3,4,3,3,4,3,3,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +86099,90342,Female,disloyal Customer,24,Business travel,Eco,594,3,0,3,3,3,3,3,3,3,4,4,5,5,3,4,0.0,neutral or dissatisfied +86100,127232,Female,Loyal Customer,15,Personal Travel,Eco,1460,2,4,1,3,4,1,5,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +86101,72593,Male,Loyal Customer,31,Personal Travel,Eco,1017,4,5,4,3,2,4,2,2,2,4,4,2,5,2,3,0.0,satisfied +86102,62880,Female,disloyal Customer,29,Business travel,Business,2583,2,3,3,5,5,3,5,5,4,5,5,3,5,5,5,11.0,neutral or dissatisfied +86103,123374,Male,Loyal Customer,21,Personal Travel,Eco,644,1,4,1,2,2,1,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +86104,98994,Female,Loyal Customer,29,Personal Travel,Eco,479,4,2,4,3,5,4,5,5,3,1,3,3,4,5,0,0.0,satisfied +86105,102313,Male,Loyal Customer,54,Business travel,Business,3510,0,0,0,3,3,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +86106,128021,Male,disloyal Customer,23,Business travel,Business,1440,0,0,0,3,2,0,2,2,4,3,5,3,4,2,16,9.0,satisfied +86107,82254,Female,Loyal Customer,52,Business travel,Business,1481,2,2,2,2,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +86108,121585,Female,Loyal Customer,51,Business travel,Eco,536,3,5,5,5,1,1,2,3,3,3,3,3,3,2,0,0.0,satisfied +86109,98710,Male,Loyal Customer,29,Business travel,Eco Plus,992,2,2,3,3,2,2,2,2,2,3,4,2,3,2,52,58.0,neutral or dissatisfied +86110,45529,Male,Loyal Customer,53,Business travel,Business,554,3,4,4,4,3,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +86111,27238,Female,Loyal Customer,27,Personal Travel,Eco,1024,1,1,1,2,5,1,5,5,2,2,2,3,3,5,0,0.0,neutral or dissatisfied +86112,66266,Male,Loyal Customer,18,Personal Travel,Eco,460,4,5,4,2,3,4,3,3,2,4,5,2,5,3,0,0.0,neutral or dissatisfied +86113,14568,Male,disloyal Customer,24,Business travel,Eco,986,5,5,5,1,3,5,5,3,2,4,5,1,1,3,0,0.0,satisfied +86114,64746,Female,Loyal Customer,62,Business travel,Eco,190,3,3,3,3,1,3,3,3,3,3,3,4,3,1,14,12.0,neutral or dissatisfied +86115,65858,Male,Loyal Customer,13,Personal Travel,Eco,1391,3,2,2,1,3,2,3,3,2,4,1,3,1,3,0,0.0,neutral or dissatisfied +86116,11785,Male,Loyal Customer,63,Personal Travel,Eco,429,1,4,5,5,2,5,2,2,4,4,1,2,5,2,15,,neutral or dissatisfied +86117,14272,Male,Loyal Customer,28,Business travel,Business,3506,1,1,4,1,3,4,3,3,1,1,3,1,3,3,0,0.0,satisfied +86118,85946,Male,disloyal Customer,37,Business travel,Business,432,3,3,3,2,4,3,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +86119,47995,Female,disloyal Customer,23,Business travel,Eco,834,2,2,2,4,3,2,2,3,3,4,1,3,3,3,19,12.0,neutral or dissatisfied +86120,45958,Male,Loyal Customer,56,Business travel,Eco Plus,409,3,5,5,5,3,3,3,3,1,5,3,3,4,3,6,6.0,neutral or dissatisfied +86121,17781,Female,Loyal Customer,30,Business travel,Business,986,1,1,1,1,5,4,5,5,4,1,3,2,3,5,0,0.0,satisfied +86122,24718,Female,Loyal Customer,16,Personal Travel,Eco,549,3,0,3,5,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +86123,64422,Male,Loyal Customer,68,Personal Travel,Business,989,4,4,4,4,3,5,4,4,4,4,4,5,4,5,24,24.0,neutral or dissatisfied +86124,89062,Male,Loyal Customer,47,Business travel,Business,1892,2,2,2,2,2,5,4,2,2,2,2,4,2,5,7,0.0,satisfied +86125,29362,Male,Loyal Customer,35,Business travel,Eco,2404,5,2,2,2,5,5,5,5,4,5,4,5,4,5,0,0.0,satisfied +86126,69905,Male,Loyal Customer,55,Business travel,Business,1514,3,3,3,3,4,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +86127,42002,Female,disloyal Customer,56,Business travel,Eco,106,4,3,4,2,5,4,5,5,5,1,4,4,2,5,0,0.0,neutral or dissatisfied +86128,23530,Female,Loyal Customer,11,Personal Travel,Business,423,4,4,4,3,1,4,1,1,1,4,3,4,4,1,0,6.0,neutral or dissatisfied +86129,71727,Female,Loyal Customer,67,Personal Travel,Eco,1007,2,4,2,1,4,5,4,2,2,2,2,5,2,4,119,104.0,neutral or dissatisfied +86130,28579,Male,Loyal Customer,25,Business travel,Business,2562,4,4,4,4,4,4,4,4,5,4,5,5,3,4,0,0.0,satisfied +86131,128385,Male,disloyal Customer,23,Business travel,Eco,647,3,3,3,3,5,3,4,5,1,2,4,3,4,5,0,7.0,neutral or dissatisfied +86132,19716,Male,Loyal Customer,59,Business travel,Eco,409,2,4,4,4,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +86133,96605,Female,Loyal Customer,42,Business travel,Business,937,1,1,1,1,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +86134,44307,Female,Loyal Customer,30,Personal Travel,Eco,1428,2,1,2,3,1,2,1,1,1,3,3,4,4,1,5,0.0,neutral or dissatisfied +86135,4454,Male,Loyal Customer,10,Personal Travel,Eco Plus,762,3,1,3,3,4,3,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +86136,128800,Male,Loyal Customer,40,Business travel,Business,2475,1,1,1,1,4,4,4,3,4,5,5,4,4,4,0,4.0,satisfied +86137,125579,Male,Loyal Customer,69,Business travel,Business,3492,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +86138,2174,Female,disloyal Customer,49,Business travel,Business,685,2,2,2,2,5,2,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +86139,46394,Male,Loyal Customer,17,Personal Travel,Eco,911,2,4,2,4,2,2,2,2,5,5,5,1,4,2,56,56.0,neutral or dissatisfied +86140,4942,Male,Loyal Customer,36,Personal Travel,Eco,268,3,3,3,4,3,3,3,3,2,1,5,1,2,3,38,33.0,neutral or dissatisfied +86141,79122,Male,Loyal Customer,26,Personal Travel,Eco,356,2,5,2,3,1,2,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +86142,105634,Male,Loyal Customer,56,Business travel,Business,1892,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +86143,125556,Male,Loyal Customer,39,Business travel,Business,3586,0,0,0,3,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +86144,81114,Male,Loyal Customer,46,Business travel,Eco,991,2,1,1,1,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +86145,71030,Male,Loyal Customer,50,Business travel,Business,2551,2,1,1,1,5,3,3,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +86146,50147,Male,Loyal Customer,17,Business travel,Business,3875,4,4,4,4,1,2,4,1,4,1,3,2,4,1,0,0.0,neutral or dissatisfied +86147,85437,Male,Loyal Customer,47,Business travel,Eco,152,3,3,3,3,3,3,3,3,3,1,4,3,4,3,0,0.0,neutral or dissatisfied +86148,95208,Female,Loyal Customer,21,Personal Travel,Eco,148,2,4,2,3,3,2,3,3,4,5,4,4,5,3,45,50.0,neutral or dissatisfied +86149,17274,Female,Loyal Customer,31,Personal Travel,Eco,1092,2,1,1,3,5,1,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +86150,64929,Female,Loyal Customer,31,Business travel,Eco,190,2,2,2,2,2,2,2,2,1,1,3,1,4,2,2,0.0,neutral or dissatisfied +86151,31076,Male,Loyal Customer,44,Business travel,Eco Plus,641,4,2,2,2,4,4,4,4,5,2,2,4,4,4,5,49.0,satisfied +86152,88711,Male,Loyal Customer,66,Personal Travel,Eco,545,4,2,4,2,2,4,2,2,2,4,1,1,2,2,0,1.0,neutral or dissatisfied +86153,76565,Male,Loyal Customer,54,Business travel,Business,1897,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +86154,35091,Female,Loyal Customer,22,Business travel,Eco,1069,3,1,1,1,3,2,3,3,5,1,2,1,1,3,0,22.0,neutral or dissatisfied +86155,27156,Male,Loyal Customer,47,Business travel,Business,2640,3,3,3,3,5,3,3,4,2,4,1,3,4,3,6,4.0,satisfied +86156,114853,Female,Loyal Customer,59,Business travel,Business,2331,1,1,2,1,2,5,4,5,5,5,5,4,5,5,0,12.0,satisfied +86157,21248,Male,Loyal Customer,59,Business travel,Eco Plus,153,5,4,4,4,5,5,5,5,3,3,1,1,4,5,0,0.0,satisfied +86158,117359,Female,Loyal Customer,33,Business travel,Eco,296,1,3,3,3,1,1,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +86159,29923,Male,Loyal Customer,33,Business travel,Eco,123,3,1,1,1,5,5,5,5,2,2,3,5,5,5,0,0.0,satisfied +86160,85691,Male,Loyal Customer,34,Business travel,Business,1547,2,2,1,2,4,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +86161,102819,Female,Loyal Customer,50,Personal Travel,Eco,342,2,4,2,3,3,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +86162,54353,Male,Loyal Customer,14,Business travel,Business,3613,4,4,4,4,4,4,4,4,1,2,4,1,2,4,0,0.0,satisfied +86163,100200,Female,Loyal Customer,60,Business travel,Business,2777,5,3,5,5,4,4,5,4,4,4,4,3,4,3,57,58.0,satisfied +86164,105829,Male,Loyal Customer,54,Personal Travel,Eco,925,1,1,1,3,3,1,3,3,4,5,3,1,4,3,4,8.0,neutral or dissatisfied +86165,40435,Female,disloyal Customer,37,Business travel,Eco,188,2,2,2,4,4,2,4,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +86166,103792,Female,disloyal Customer,46,Business travel,Business,869,4,4,4,4,5,4,5,5,3,2,5,4,4,5,59,40.0,satisfied +86167,65143,Female,Loyal Customer,52,Personal Travel,Eco,247,4,1,4,2,4,2,2,3,3,4,3,1,3,3,40,30.0,neutral or dissatisfied +86168,27374,Male,Loyal Customer,54,Business travel,Business,2019,2,3,3,3,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +86169,33369,Male,Loyal Customer,46,Personal Travel,Eco,2556,2,1,2,3,5,2,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +86170,10,Female,Loyal Customer,38,Business travel,Business,2822,2,2,5,2,2,5,4,5,5,5,5,3,5,4,13,0.0,satisfied +86171,119759,Female,disloyal Customer,26,Business travel,Eco Plus,1303,4,4,4,4,4,4,4,4,1,3,4,2,3,4,24,47.0,neutral or dissatisfied +86172,67651,Male,Loyal Customer,30,Business travel,Business,4000,4,4,4,4,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +86173,94290,Male,Loyal Customer,43,Business travel,Business,2656,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,4.0,satisfied +86174,125029,Female,Loyal Customer,69,Personal Travel,Eco Plus,184,2,4,2,5,5,5,5,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +86175,22442,Female,Loyal Customer,55,Personal Travel,Eco,238,2,1,2,2,4,3,2,3,3,2,2,2,3,2,34,40.0,neutral or dissatisfied +86176,108179,Female,Loyal Customer,70,Personal Travel,Eco,997,3,3,3,3,5,1,3,2,2,3,5,3,2,1,31,16.0,neutral or dissatisfied +86177,23566,Female,Loyal Customer,47,Business travel,Business,1015,5,3,5,5,3,5,5,5,5,5,5,3,5,1,9,8.0,satisfied +86178,79651,Female,disloyal Customer,19,Business travel,Eco,712,4,4,4,4,3,4,3,3,3,5,3,3,4,3,33,30.0,neutral or dissatisfied +86179,3487,Male,disloyal Customer,30,Business travel,Eco,990,1,1,1,3,2,1,2,2,2,1,4,4,4,2,0,5.0,neutral or dissatisfied +86180,77815,Male,Loyal Customer,48,Personal Travel,Eco,689,2,5,2,1,2,2,2,2,5,2,5,4,5,2,89,86.0,neutral or dissatisfied +86181,58181,Male,Loyal Customer,30,Business travel,Business,3584,2,5,5,5,2,3,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +86182,127502,Female,Loyal Customer,10,Personal Travel,Eco,1814,3,4,3,3,1,3,1,1,3,5,5,4,2,1,0,0.0,neutral or dissatisfied +86183,113678,Male,Loyal Customer,37,Personal Travel,Eco,226,3,3,3,5,5,3,5,5,3,4,2,1,4,5,0,0.0,neutral or dissatisfied +86184,126280,Female,Loyal Customer,11,Personal Travel,Eco,507,4,4,5,1,3,5,3,3,4,5,4,5,4,3,1,0.0,satisfied +86185,80546,Male,Loyal Customer,44,Business travel,Business,1747,5,5,5,5,4,3,4,5,5,5,5,3,5,3,23,2.0,satisfied +86186,2724,Female,Loyal Customer,25,Business travel,Business,772,4,4,4,4,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +86187,65518,Female,Loyal Customer,45,Business travel,Business,1616,5,5,5,5,4,4,4,5,5,5,5,3,5,5,71,62.0,satisfied +86188,27334,Male,Loyal Customer,24,Business travel,Business,954,4,4,4,4,4,4,4,4,5,3,2,4,1,4,0,0.0,satisfied +86189,24743,Female,Loyal Customer,39,Business travel,Business,432,4,4,4,4,3,5,3,5,5,5,5,2,5,5,10,32.0,satisfied +86190,95736,Male,Loyal Customer,41,Business travel,Eco,419,3,3,3,3,3,3,3,3,3,2,4,2,3,3,0,4.0,neutral or dissatisfied +86191,25953,Male,Loyal Customer,18,Business travel,Eco,946,4,3,5,5,4,5,5,4,2,1,2,1,1,4,0,0.0,satisfied +86192,29643,Male,Loyal Customer,29,Personal Travel,Eco,909,1,4,1,4,4,1,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +86193,26973,Male,Loyal Customer,43,Business travel,Business,2126,4,4,4,4,4,5,3,4,4,4,4,4,4,5,0,0.0,satisfied +86194,12558,Female,Loyal Customer,66,Personal Travel,Eco,871,2,3,2,3,1,4,4,5,5,2,5,2,5,4,0,0.0,neutral or dissatisfied +86195,109052,Female,disloyal Customer,39,Business travel,Business,816,4,4,4,4,5,4,5,5,2,1,3,1,4,5,14,1.0,neutral or dissatisfied +86196,117731,Male,Loyal Customer,44,Business travel,Eco,833,4,2,2,2,4,4,4,4,1,4,2,1,2,4,30,14.0,neutral or dissatisfied +86197,70546,Male,Loyal Customer,37,Business travel,Business,1258,1,2,1,1,3,4,5,4,4,4,4,5,4,5,0,5.0,satisfied +86198,104945,Male,Loyal Customer,23,Personal Travel,Eco,1180,3,4,3,4,1,3,1,1,3,5,5,5,4,1,20,2.0,neutral or dissatisfied +86199,89703,Female,Loyal Customer,35,Personal Travel,Eco,1076,5,4,5,4,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +86200,67180,Female,Loyal Customer,27,Personal Travel,Eco,929,3,5,3,2,4,3,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +86201,122383,Male,Loyal Customer,62,Personal Travel,Eco,529,3,2,5,3,3,5,3,3,2,4,3,1,4,3,3,0.0,neutral or dissatisfied +86202,67192,Male,Loyal Customer,56,Personal Travel,Eco,1121,2,4,2,5,2,2,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +86203,66724,Female,Loyal Customer,8,Personal Travel,Eco,802,1,3,1,2,2,1,2,2,5,5,2,5,4,2,10,2.0,neutral or dissatisfied +86204,1287,Male,Loyal Customer,37,Personal Travel,Eco,134,2,2,2,4,1,2,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +86205,1952,Male,Loyal Customer,56,Business travel,Eco,383,2,4,4,4,1,2,1,1,4,2,3,2,4,1,0,0.0,neutral or dissatisfied +86206,120632,Female,Loyal Customer,51,Business travel,Business,3874,4,5,4,4,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +86207,58836,Female,Loyal Customer,46,Personal Travel,Eco Plus,1005,2,5,2,5,5,5,4,4,4,2,4,5,4,5,1,0.0,neutral or dissatisfied +86208,101236,Female,disloyal Customer,31,Business travel,Business,1587,2,2,2,1,5,2,5,5,5,3,3,4,5,5,4,0.0,neutral or dissatisfied +86209,54577,Female,Loyal Customer,60,Business travel,Business,3904,1,3,3,3,1,1,1,1,5,1,2,1,2,1,27,8.0,neutral or dissatisfied +86210,52489,Male,Loyal Customer,30,Personal Travel,Eco Plus,493,3,3,3,3,3,3,3,3,2,1,3,3,3,3,0,5.0,neutral or dissatisfied +86211,91695,Male,Loyal Customer,28,Business travel,Business,626,2,2,2,2,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +86212,99986,Female,disloyal Customer,36,Business travel,Business,289,4,4,4,3,5,4,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +86213,68195,Male,Loyal Customer,65,Personal Travel,Eco Plus,597,3,4,3,2,1,3,1,1,2,5,4,1,5,1,0,0.0,neutral or dissatisfied +86214,27844,Female,Loyal Customer,27,Personal Travel,Eco,680,2,5,2,3,3,2,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +86215,63471,Female,disloyal Customer,59,Business travel,Eco Plus,337,3,3,3,1,5,3,5,5,1,3,1,4,2,5,22,21.0,neutral or dissatisfied +86216,49449,Female,Loyal Customer,69,Business travel,Eco,209,5,2,2,2,4,5,4,5,5,5,5,1,5,3,0,0.0,satisfied +86217,88917,Male,Loyal Customer,12,Personal Travel,Eco,859,1,4,1,3,1,1,1,1,5,2,4,5,4,1,31,13.0,neutral or dissatisfied +86218,65263,Male,Loyal Customer,51,Business travel,Business,3945,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +86219,58101,Female,Loyal Customer,43,Personal Travel,Eco,612,5,5,4,5,4,5,4,3,3,4,3,3,3,3,17,0.0,satisfied +86220,129866,Male,Loyal Customer,64,Business travel,Eco Plus,337,2,3,3,3,2,2,2,2,1,2,3,2,3,2,27,18.0,neutral or dissatisfied +86221,25008,Female,Loyal Customer,32,Business travel,Eco Plus,692,4,4,4,4,4,4,4,4,1,1,2,4,3,4,0,0.0,satisfied +86222,107609,Male,disloyal Customer,25,Business travel,Eco,423,2,2,3,3,2,3,2,2,3,3,4,4,4,2,62,64.0,neutral or dissatisfied +86223,19392,Male,Loyal Customer,19,Personal Travel,Eco,844,4,4,4,4,2,4,2,2,4,4,4,3,5,2,0,0.0,satisfied +86224,52085,Male,Loyal Customer,47,Business travel,Eco,438,1,5,5,5,1,1,1,1,4,4,4,2,4,1,0,1.0,neutral or dissatisfied +86225,3660,Male,disloyal Customer,25,Business travel,Business,544,1,0,1,5,1,1,1,1,4,3,4,4,4,1,0,11.0,neutral or dissatisfied +86226,105800,Female,Loyal Customer,59,Personal Travel,Eco,925,3,1,3,3,5,3,3,5,5,3,5,4,5,3,34,25.0,neutral or dissatisfied +86227,7804,Female,Loyal Customer,60,Business travel,Business,3831,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +86228,97458,Male,Loyal Customer,51,Business travel,Business,3491,4,4,3,4,5,4,4,5,5,5,5,3,5,3,26,0.0,satisfied +86229,37969,Female,Loyal Customer,53,Business travel,Business,3318,2,2,2,2,2,4,5,2,2,2,2,4,2,3,0,11.0,satisfied +86230,47069,Male,Loyal Customer,52,Personal Travel,Eco,602,3,2,3,3,3,3,3,2,1,4,3,3,3,3,129,178.0,neutral or dissatisfied +86231,51166,Male,Loyal Customer,63,Personal Travel,Eco,109,1,3,0,4,2,0,2,2,3,5,1,1,1,2,114,105.0,neutral or dissatisfied +86232,37611,Female,Loyal Customer,24,Personal Travel,Eco,1069,3,5,3,1,4,3,4,4,5,2,2,3,2,4,0,0.0,neutral or dissatisfied +86233,1222,Female,Loyal Customer,45,Personal Travel,Eco,482,2,1,2,1,2,1,2,4,4,2,4,3,4,1,0,8.0,neutral or dissatisfied +86234,17957,Female,disloyal Customer,52,Business travel,Eco,500,3,1,3,3,5,3,5,5,2,5,4,4,3,5,49,53.0,neutral or dissatisfied +86235,44093,Male,Loyal Customer,46,Business travel,Business,2858,3,2,4,2,4,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +86236,93658,Female,Loyal Customer,57,Business travel,Business,667,4,1,1,1,5,3,4,4,4,4,4,4,4,2,8,0.0,neutral or dissatisfied +86237,88625,Male,Loyal Customer,42,Personal Travel,Eco,515,3,5,3,2,2,3,2,2,5,3,5,5,5,2,15,14.0,neutral or dissatisfied +86238,17766,Female,disloyal Customer,23,Business travel,Eco,1075,1,0,0,3,2,0,2,2,5,1,5,2,5,2,0,23.0,neutral or dissatisfied +86239,7626,Female,disloyal Customer,17,Business travel,Eco,767,1,1,1,3,5,1,5,5,4,5,4,1,4,5,0,0.0,neutral or dissatisfied +86240,114503,Male,Loyal Customer,34,Business travel,Business,446,3,2,2,2,3,4,3,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +86241,18363,Male,disloyal Customer,20,Business travel,Eco,169,4,3,4,5,5,4,5,5,1,4,5,1,4,5,0,1.0,neutral or dissatisfied +86242,127435,Male,Loyal Customer,36,Personal Travel,Eco,868,4,1,4,4,3,4,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +86243,5658,Male,Loyal Customer,25,Business travel,Business,299,4,3,3,3,4,4,4,4,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +86244,8144,Female,Loyal Customer,48,Business travel,Eco,294,2,5,3,3,1,3,3,2,2,2,2,3,2,4,0,2.0,neutral or dissatisfied +86245,32522,Female,Loyal Customer,76,Business travel,Business,3302,1,1,1,1,1,4,5,4,4,4,4,3,4,1,0,0.0,satisfied +86246,108789,Male,Loyal Customer,59,Business travel,Business,2620,1,1,1,1,5,5,5,5,5,5,5,3,5,5,23,2.0,satisfied +86247,58054,Male,Loyal Customer,55,Business travel,Business,589,2,2,2,2,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +86248,17194,Female,Loyal Customer,27,Personal Travel,Eco Plus,643,1,5,1,4,1,1,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +86249,17176,Male,Loyal Customer,29,Business travel,Business,2733,2,1,2,2,4,4,4,4,1,2,3,1,4,4,0,0.0,satisfied +86250,89839,Male,Loyal Customer,41,Business travel,Business,3468,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +86251,107654,Female,Loyal Customer,56,Business travel,Business,405,4,4,4,4,5,4,5,2,2,2,2,5,2,3,29,32.0,satisfied +86252,22170,Male,disloyal Customer,22,Business travel,Eco,773,4,4,4,4,3,4,3,3,1,3,3,2,3,3,14,23.0,neutral or dissatisfied +86253,18656,Male,Loyal Customer,57,Personal Travel,Eco,192,3,2,3,4,3,3,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +86254,7426,Female,Loyal Customer,24,Business travel,Business,552,1,3,2,2,1,1,1,1,1,2,4,3,4,1,49,106.0,neutral or dissatisfied +86255,67386,Female,Loyal Customer,36,Business travel,Business,2904,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +86256,88261,Female,Loyal Customer,35,Business travel,Eco,250,2,1,4,4,2,2,2,2,1,1,3,2,4,2,3,0.0,neutral or dissatisfied +86257,109956,Male,Loyal Customer,34,Personal Travel,Eco,1052,2,3,2,4,5,2,5,5,3,2,4,4,3,5,4,2.0,neutral or dissatisfied +86258,4120,Female,Loyal Customer,51,Business travel,Business,431,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +86259,41420,Male,Loyal Customer,40,Personal Travel,Eco,913,3,1,3,2,3,3,3,3,3,2,2,2,3,3,34,19.0,neutral or dissatisfied +86260,11689,Male,Loyal Customer,46,Business travel,Business,395,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +86261,128498,Female,Loyal Customer,65,Personal Travel,Eco,621,3,1,3,3,5,4,3,5,5,3,3,1,5,2,2,1.0,neutral or dissatisfied +86262,44570,Male,disloyal Customer,36,Business travel,Eco,84,2,0,2,4,3,2,5,3,5,4,5,1,1,3,6,0.0,neutral or dissatisfied +86263,116075,Male,Loyal Customer,31,Personal Travel,Eco,373,2,3,2,3,1,2,1,1,1,1,4,3,4,1,11,11.0,neutral or dissatisfied +86264,59061,Female,Loyal Customer,45,Business travel,Business,1846,3,2,2,2,3,2,3,3,3,3,3,2,3,2,108,104.0,neutral or dissatisfied +86265,29088,Male,Loyal Customer,25,Personal Travel,Eco,1050,2,5,2,5,3,2,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +86266,106623,Female,Loyal Customer,60,Business travel,Business,1885,2,2,2,2,2,4,5,4,4,5,4,3,4,4,0,3.0,satisfied +86267,45423,Female,Loyal Customer,42,Business travel,Business,2075,3,3,3,3,3,2,5,4,4,4,4,3,4,1,0,0.0,satisfied +86268,81423,Male,Loyal Customer,51,Business travel,Business,2359,3,3,3,3,4,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +86269,26888,Male,Loyal Customer,33,Business travel,Business,689,2,4,4,4,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +86270,49297,Male,Loyal Customer,52,Business travel,Business,3282,4,4,4,4,1,1,3,5,5,5,5,2,5,1,0,0.0,satisfied +86271,41053,Female,disloyal Customer,60,Personal Travel,Eco,1195,1,4,1,2,2,1,2,2,5,2,4,5,4,2,28,54.0,neutral or dissatisfied +86272,72108,Male,Loyal Customer,50,Business travel,Business,731,3,3,3,3,4,5,4,4,4,4,4,5,4,5,5,15.0,satisfied +86273,108359,Female,disloyal Customer,25,Business travel,Eco,344,2,5,2,2,2,2,2,2,2,1,2,2,3,2,1,10.0,neutral or dissatisfied +86274,74257,Male,Loyal Customer,54,Personal Travel,Eco,1810,0,2,0,3,4,0,4,4,1,5,3,4,4,4,0,0.0,satisfied +86275,88349,Female,Loyal Customer,42,Business travel,Business,515,2,2,2,2,3,4,5,5,5,5,5,5,5,5,16,13.0,satisfied +86276,33134,Female,Loyal Customer,27,Personal Travel,Eco,163,2,1,2,3,3,2,2,3,1,4,2,4,2,3,4,3.0,neutral or dissatisfied +86277,116020,Male,Loyal Customer,7,Personal Travel,Eco,446,4,5,4,5,2,4,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +86278,125888,Male,Loyal Customer,11,Personal Travel,Eco,993,2,2,2,4,1,2,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +86279,120726,Female,Loyal Customer,37,Personal Travel,Eco,90,3,3,3,3,1,3,1,1,3,4,3,4,3,1,28,29.0,neutral or dissatisfied +86280,32123,Male,disloyal Customer,24,Business travel,Eco,102,1,5,1,4,5,1,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +86281,20980,Female,Loyal Customer,22,Personal Travel,Eco,803,1,3,1,5,1,1,1,1,4,2,4,1,3,1,2,0.0,neutral or dissatisfied +86282,21127,Male,Loyal Customer,17,Personal Travel,Eco,152,4,4,4,1,5,4,5,5,3,4,5,5,4,5,11,11.0,neutral or dissatisfied +86283,49016,Male,Loyal Customer,51,Business travel,Business,1887,5,5,5,5,4,4,2,4,4,4,4,2,4,5,49,37.0,satisfied +86284,116200,Male,Loyal Customer,37,Personal Travel,Eco,390,2,4,2,3,4,2,5,4,3,2,4,4,5,4,19,16.0,neutral or dissatisfied +86285,13059,Female,disloyal Customer,32,Business travel,Eco,936,2,2,2,4,3,2,3,3,3,3,5,2,3,3,10,8.0,neutral or dissatisfied +86286,103448,Male,Loyal Customer,68,Business travel,Business,2255,5,3,5,5,5,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +86287,74,Female,disloyal Customer,25,Business travel,Eco,212,3,2,3,4,4,3,3,4,1,2,3,1,4,4,10,1.0,neutral or dissatisfied +86288,45461,Female,Loyal Customer,47,Business travel,Eco,522,5,5,5,5,2,1,1,5,5,5,5,2,5,2,0,1.0,satisfied +86289,5095,Female,Loyal Customer,10,Personal Travel,Eco,224,4,4,4,4,2,4,2,2,3,4,4,3,4,2,95,94.0,satisfied +86290,27390,Female,Loyal Customer,47,Business travel,Business,3583,4,2,2,2,2,1,2,4,4,4,4,1,4,4,0,2.0,neutral or dissatisfied +86291,26184,Male,disloyal Customer,16,Business travel,Eco,404,4,5,4,4,5,4,5,5,5,3,5,3,1,5,2,0.0,satisfied +86292,39670,Female,Loyal Customer,24,Personal Travel,Eco,476,4,3,4,3,2,4,2,2,1,5,2,2,3,2,76,72.0,neutral or dissatisfied +86293,98257,Male,Loyal Customer,58,Business travel,Business,1522,2,4,4,4,1,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +86294,43769,Male,Loyal Customer,59,Business travel,Eco,386,4,2,2,2,5,4,5,5,2,3,2,5,3,5,0,0.0,satisfied +86295,98353,Female,Loyal Customer,47,Business travel,Eco,1189,2,3,3,3,3,2,2,3,3,2,3,1,3,4,38,14.0,neutral or dissatisfied +86296,106978,Male,Loyal Customer,40,Business travel,Eco,537,5,3,3,3,5,4,5,5,3,4,1,1,1,5,0,0.0,satisfied +86297,89050,Male,disloyal Customer,42,Business travel,Business,942,5,5,5,3,4,5,4,4,4,4,4,5,4,4,11,0.0,satisfied +86298,2307,Female,Loyal Customer,62,Business travel,Business,2820,4,5,5,5,1,1,2,4,4,4,4,1,4,4,16,23.0,neutral or dissatisfied +86299,11443,Female,Loyal Customer,50,Business travel,Business,140,1,1,1,1,4,4,4,5,5,5,4,3,5,3,0,0.0,satisfied +86300,51635,Male,disloyal Customer,39,Business travel,Eco,370,3,4,3,3,3,3,3,3,2,1,4,4,4,3,7,1.0,neutral or dissatisfied +86301,105857,Female,disloyal Customer,12,Business travel,Eco,925,1,1,1,4,3,1,3,3,2,4,4,3,3,3,0,0.0,neutral or dissatisfied +86302,22452,Female,Loyal Customer,31,Personal Travel,Eco,143,1,3,1,3,5,1,5,5,2,2,1,1,1,5,0,0.0,neutral or dissatisfied +86303,37458,Male,Loyal Customer,35,Business travel,Business,944,2,2,4,2,4,5,4,4,4,4,4,2,4,2,0,0.0,satisfied +86304,13862,Female,disloyal Customer,39,Business travel,Business,578,5,5,5,4,5,5,5,5,1,2,4,1,1,5,0,0.0,satisfied +86305,21412,Male,Loyal Customer,36,Business travel,Business,3277,4,4,4,4,3,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +86306,58981,Female,Loyal Customer,27,Business travel,Business,1846,2,2,2,2,4,4,4,4,5,3,3,5,5,4,1,8.0,satisfied +86307,100738,Male,Loyal Customer,43,Business travel,Business,328,4,4,1,4,1,1,5,5,5,5,5,5,5,5,0,0.0,satisfied +86308,73372,Female,Loyal Customer,61,Business travel,Business,1712,2,2,5,2,1,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +86309,108326,Male,Loyal Customer,26,Business travel,Business,1750,1,1,1,1,3,4,3,3,5,3,4,3,5,3,38,23.0,satisfied +86310,124014,Female,disloyal Customer,42,Business travel,Eco,184,4,0,4,1,5,4,5,5,1,2,4,1,2,5,0,0.0,neutral or dissatisfied +86311,120309,Female,Loyal Customer,45,Business travel,Eco,268,4,5,5,5,5,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +86312,106340,Female,Loyal Customer,51,Business travel,Business,425,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +86313,48903,Female,disloyal Customer,22,Business travel,Eco,209,4,5,4,5,1,4,1,1,3,2,4,1,3,1,12,7.0,satisfied +86314,41327,Male,Loyal Customer,48,Business travel,Business,3000,1,1,1,1,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +86315,11386,Male,Loyal Customer,53,Business travel,Business,201,4,4,4,4,2,5,4,5,5,5,5,3,5,5,45,42.0,satisfied +86316,61812,Female,Loyal Customer,68,Personal Travel,Eco,1379,2,5,2,3,5,3,5,1,1,2,1,4,1,5,0,1.0,neutral or dissatisfied +86317,92888,Female,Loyal Customer,58,Business travel,Business,302,2,2,2,2,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +86318,64557,Female,Loyal Customer,25,Business travel,Business,247,1,1,1,1,4,4,4,4,4,5,5,3,4,4,44,38.0,satisfied +86319,114670,Male,Loyal Customer,42,Business travel,Business,417,3,3,3,3,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +86320,57472,Female,Loyal Customer,37,Business travel,Business,680,5,5,5,5,2,4,5,5,5,5,5,4,5,5,13,10.0,satisfied +86321,33931,Male,Loyal Customer,38,Personal Travel,Business,1072,2,5,2,3,4,4,5,3,3,2,1,4,3,3,0,0.0,neutral or dissatisfied +86322,18589,Female,Loyal Customer,55,Business travel,Business,3561,3,1,4,1,3,2,2,2,2,2,3,1,2,2,0,0.0,neutral or dissatisfied +86323,105748,Female,disloyal Customer,39,Business travel,Business,663,4,4,4,3,4,4,4,4,4,2,4,3,4,4,18,21.0,neutral or dissatisfied +86324,42843,Female,disloyal Customer,23,Business travel,Eco,328,1,0,1,3,2,1,2,2,3,5,4,3,4,2,0,3.0,neutral or dissatisfied +86325,90249,Female,Loyal Customer,22,Personal Travel,Eco,1121,2,5,2,2,4,2,4,4,5,3,4,5,5,4,12,2.0,neutral or dissatisfied +86326,32418,Female,Loyal Customer,23,Business travel,Business,3059,0,5,0,4,4,4,4,4,1,2,5,2,3,4,0,0.0,satisfied +86327,62221,Female,Loyal Customer,22,Personal Travel,Eco,2565,3,3,3,3,4,3,4,4,3,1,4,1,2,4,0,0.0,neutral or dissatisfied +86328,112711,Male,Loyal Customer,37,Business travel,Eco,205,3,2,2,2,3,3,3,3,2,5,2,5,2,3,0,0.0,satisfied +86329,112871,Female,Loyal Customer,24,Business travel,Business,1390,3,1,1,1,3,3,3,3,1,4,4,1,4,3,16,0.0,neutral or dissatisfied +86330,41504,Male,disloyal Customer,23,Business travel,Eco,1211,3,2,2,3,2,2,2,2,4,5,5,1,5,2,16,13.0,neutral or dissatisfied +86331,5630,Female,Loyal Customer,41,Business travel,Business,2108,4,4,4,4,3,5,4,4,4,4,4,4,4,3,94,92.0,satisfied +86332,58251,Male,Loyal Customer,33,Personal Travel,Eco Plus,925,1,5,1,3,2,1,2,2,3,5,2,3,1,2,0,0.0,neutral or dissatisfied +86333,61931,Male,Loyal Customer,31,Personal Travel,Eco,550,1,3,1,3,5,1,5,5,2,3,2,1,2,5,124,111.0,neutral or dissatisfied +86334,115466,Female,Loyal Customer,45,Business travel,Business,2832,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +86335,65210,Female,Loyal Customer,62,Business travel,Business,3895,3,3,3,3,5,4,5,5,5,5,5,5,5,5,7,0.0,satisfied +86336,45770,Male,disloyal Customer,34,Business travel,Eco,411,2,0,2,1,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +86337,106121,Male,Loyal Customer,48,Business travel,Eco,436,2,3,3,3,2,2,2,2,4,2,3,2,3,2,18,9.0,neutral or dissatisfied +86338,52818,Female,Loyal Customer,45,Business travel,Eco,902,2,1,1,1,2,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +86339,2997,Female,Loyal Customer,45,Business travel,Business,3173,5,5,5,5,2,4,4,4,4,4,4,3,4,4,10,15.0,satisfied +86340,85623,Female,Loyal Customer,54,Personal Travel,Eco,259,1,5,1,1,1,1,2,2,2,1,2,5,2,2,0,4.0,neutral or dissatisfied +86341,78570,Male,Loyal Customer,39,Business travel,Business,630,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +86342,110956,Female,disloyal Customer,23,Business travel,Eco Plus,404,4,2,4,3,4,4,4,2,5,3,4,4,3,4,253,229.0,neutral or dissatisfied +86343,76488,Female,Loyal Customer,40,Business travel,Business,3457,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,15.0,satisfied +86344,110137,Female,disloyal Customer,57,Business travel,Business,1056,4,4,4,2,3,4,3,3,4,4,4,4,5,3,0,0.0,satisfied +86345,11488,Male,Loyal Customer,40,Personal Travel,Eco Plus,308,4,4,4,3,5,4,5,5,3,2,5,3,4,5,0,4.0,neutral or dissatisfied +86346,40642,Male,Loyal Customer,37,Personal Travel,Eco Plus,391,0,1,0,3,1,0,1,1,2,5,3,1,3,1,0,0.0,satisfied +86347,77833,Female,Loyal Customer,16,Personal Travel,Eco,731,2,4,2,4,4,2,4,4,5,3,5,4,4,4,11,0.0,neutral or dissatisfied +86348,8827,Female,Loyal Customer,25,Personal Travel,Eco,522,3,4,3,1,4,3,3,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +86349,72550,Male,Loyal Customer,58,Business travel,Business,2196,3,3,3,3,2,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +86350,70142,Male,Loyal Customer,27,Personal Travel,Eco,460,0,4,0,1,5,0,5,5,3,5,4,3,5,5,0,4.0,satisfied +86351,126705,Female,disloyal Customer,23,Business travel,Business,2521,5,5,5,2,3,5,3,3,4,3,4,3,4,3,7,0.0,satisfied +86352,68809,Female,Loyal Customer,37,Personal Travel,Eco,926,2,4,2,4,1,2,1,1,3,4,5,5,4,1,0,2.0,neutral or dissatisfied +86353,87658,Female,Loyal Customer,28,Business travel,Business,606,3,3,3,3,4,4,4,4,5,5,5,4,4,4,0,0.0,satisfied +86354,121724,Male,disloyal Customer,34,Business travel,Business,1475,2,2,2,3,3,2,3,3,4,5,5,3,4,3,29,25.0,neutral or dissatisfied +86355,120793,Male,Loyal Customer,58,Business travel,Business,678,2,2,2,2,3,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +86356,86566,Female,Loyal Customer,33,Personal Travel,Eco Plus,762,3,1,3,3,3,3,2,3,3,5,2,2,2,3,0,0.0,neutral or dissatisfied +86357,66987,Male,Loyal Customer,51,Business travel,Business,2974,3,3,3,3,5,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +86358,92283,Female,Loyal Customer,55,Personal Travel,Eco,1900,4,4,4,2,2,3,5,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +86359,72315,Male,Loyal Customer,15,Personal Travel,Eco Plus,919,4,3,4,4,4,4,4,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +86360,41736,Male,Loyal Customer,11,Business travel,Eco,695,3,2,2,2,3,3,3,3,4,5,3,3,4,3,14,21.0,neutral or dissatisfied +86361,44318,Male,Loyal Customer,50,Personal Travel,Eco,837,3,4,3,3,3,3,4,3,4,5,4,4,5,3,23,26.0,neutral or dissatisfied +86362,67592,Male,Loyal Customer,53,Business travel,Business,2350,3,2,3,3,2,4,5,4,4,4,4,3,4,3,15,18.0,satisfied +86363,7937,Female,Loyal Customer,48,Business travel,Business,594,4,4,4,4,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +86364,12892,Female,Loyal Customer,38,Business travel,Business,2974,2,2,2,2,3,1,4,4,4,4,4,5,4,3,0,0.0,satisfied +86365,80992,Male,disloyal Customer,26,Business travel,Business,228,2,4,3,4,5,3,5,5,4,4,3,3,3,5,11,1.0,neutral or dissatisfied +86366,46642,Male,Loyal Customer,40,Business travel,Eco,125,1,1,1,1,1,1,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +86367,16043,Male,Loyal Customer,54,Personal Travel,Eco Plus,780,3,2,3,4,2,3,2,2,2,4,4,1,4,2,75,89.0,neutral or dissatisfied +86368,38092,Female,Loyal Customer,39,Business travel,Business,1237,3,4,4,4,1,3,3,3,3,3,3,1,3,4,0,14.0,neutral or dissatisfied +86369,127635,Female,Loyal Customer,47,Personal Travel,Eco,1773,1,3,1,4,5,2,1,2,2,1,4,1,2,3,0,3.0,neutral or dissatisfied +86370,66159,Female,Loyal Customer,37,Business travel,Business,1993,2,2,2,2,2,5,5,4,4,4,4,4,4,4,14,14.0,satisfied +86371,103889,Female,Loyal Customer,8,Personal Travel,Eco,1072,3,5,3,3,5,3,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +86372,118197,Female,Loyal Customer,26,Personal Travel,Eco,1444,3,5,3,2,2,3,2,2,3,4,4,5,4,2,34,0.0,neutral or dissatisfied +86373,113079,Female,Loyal Customer,21,Business travel,Business,543,1,1,1,1,1,1,1,1,3,1,4,3,4,1,13,0.0,neutral or dissatisfied +86374,22462,Male,Loyal Customer,35,Personal Travel,Eco,83,4,5,4,3,4,4,4,4,3,4,4,4,4,4,11,0.0,neutral or dissatisfied +86375,42468,Female,Loyal Customer,34,Personal Travel,Business,395,2,4,2,2,5,4,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +86376,24637,Female,Loyal Customer,15,Personal Travel,Eco,526,1,4,1,1,2,1,2,2,3,2,5,5,4,2,7,10.0,neutral or dissatisfied +86377,65406,Female,Loyal Customer,21,Personal Travel,Eco,631,3,5,3,2,4,3,3,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +86378,2687,Male,disloyal Customer,23,Business travel,Eco,562,3,4,3,2,5,3,1,5,3,4,4,4,4,5,93,93.0,neutral or dissatisfied +86379,101695,Male,Loyal Customer,40,Personal Travel,Eco,1500,2,4,2,5,3,2,3,3,3,4,5,3,5,3,4,0.0,neutral or dissatisfied +86380,117771,Male,disloyal Customer,29,Business travel,Eco,1133,2,2,2,4,1,2,1,1,3,4,3,1,3,1,97,57.0,neutral or dissatisfied +86381,124576,Female,Loyal Customer,55,Business travel,Business,2263,5,5,4,5,5,5,5,5,5,5,5,4,5,5,0,15.0,satisfied +86382,117948,Male,Loyal Customer,39,Business travel,Eco,255,3,4,4,4,3,3,3,3,2,3,3,4,4,3,7,1.0,neutral or dissatisfied +86383,55375,Female,Loyal Customer,32,Business travel,Business,2313,2,2,3,2,2,1,2,2,4,5,4,4,4,2,14,0.0,neutral or dissatisfied +86384,30313,Male,disloyal Customer,27,Business travel,Business,391,5,5,5,4,2,5,4,2,5,2,5,4,4,2,25,17.0,satisfied +86385,82910,Male,Loyal Customer,31,Personal Travel,Eco,645,1,5,1,1,5,1,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +86386,47674,Female,Loyal Customer,47,Personal Travel,Eco,1464,2,4,2,3,5,3,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +86387,37038,Female,Loyal Customer,25,Business travel,Business,1105,5,5,5,5,3,3,3,3,3,5,1,3,5,3,2,0.0,satisfied +86388,125044,Female,Loyal Customer,29,Personal Travel,Eco,2300,5,1,5,2,5,5,5,2,5,3,2,5,3,5,0,3.0,satisfied +86389,26238,Female,Loyal Customer,62,Personal Travel,Eco,581,4,5,4,4,2,4,5,5,5,4,5,4,5,5,8,3.0,neutral or dissatisfied +86390,89124,Female,Loyal Customer,31,Business travel,Business,1947,5,5,5,5,4,3,4,4,3,2,3,4,4,4,2,0.0,satisfied +86391,48779,Male,disloyal Customer,39,Business travel,Business,89,4,4,4,3,4,4,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +86392,78354,Female,Loyal Customer,11,Business travel,Eco Plus,1547,1,5,5,5,1,1,1,1,2,3,3,4,3,1,0,0.0,neutral or dissatisfied +86393,55044,Male,disloyal Customer,26,Business travel,Business,1303,2,2,2,4,4,2,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +86394,73271,Male,Loyal Customer,53,Business travel,Business,1197,5,5,5,5,4,4,4,4,4,4,4,5,4,4,22,21.0,satisfied +86395,61057,Female,Loyal Customer,55,Business travel,Business,1703,1,1,4,1,4,5,4,4,4,4,4,5,4,3,60,64.0,satisfied +86396,45372,Male,Loyal Customer,29,Personal Travel,Eco,188,3,5,3,1,3,3,1,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +86397,32844,Male,Loyal Customer,46,Personal Travel,Eco,121,4,4,4,1,3,4,3,3,3,4,1,3,4,3,0,0.0,satisfied +86398,81557,Male,Loyal Customer,44,Business travel,Business,936,2,2,2,2,5,5,5,3,3,3,3,5,3,4,1,0.0,satisfied +86399,58232,Female,Loyal Customer,59,Personal Travel,Eco,925,2,4,3,4,3,1,3,5,5,3,5,3,5,4,4,5.0,neutral or dissatisfied +86400,49346,Female,Loyal Customer,38,Business travel,Eco,308,3,4,4,4,3,4,3,3,3,4,5,5,5,3,0,3.0,satisfied +86401,80479,Female,Loyal Customer,30,Personal Travel,Eco,1299,3,5,3,2,5,3,5,5,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +86402,102461,Female,Loyal Customer,7,Personal Travel,Eco,414,0,4,0,3,3,0,3,3,4,2,5,3,5,3,0,0.0,satisfied +86403,91344,Male,Loyal Customer,8,Personal Travel,Eco Plus,404,3,3,3,3,3,3,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +86404,26775,Female,Loyal Customer,59,Business travel,Business,1199,2,2,2,2,4,1,4,4,4,4,4,4,4,1,16,0.0,satisfied +86405,102082,Male,disloyal Customer,32,Business travel,Business,223,4,3,3,5,5,3,5,5,3,4,5,3,5,5,26,21.0,neutral or dissatisfied +86406,43751,Female,Loyal Customer,63,Business travel,Business,3514,1,1,1,1,5,5,3,4,4,4,4,4,4,5,0,28.0,satisfied +86407,49540,Male,Loyal Customer,59,Business travel,Business,1780,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +86408,71009,Male,Loyal Customer,42,Business travel,Eco,802,2,3,3,3,2,2,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +86409,95468,Female,Loyal Customer,45,Business travel,Business,1670,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +86410,16888,Male,disloyal Customer,25,Business travel,Eco,746,1,1,1,4,2,1,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +86411,71831,Male,Loyal Customer,29,Business travel,Business,1846,4,4,4,4,4,4,4,4,4,3,3,4,3,4,0,0.0,neutral or dissatisfied +86412,37299,Female,Loyal Customer,53,Business travel,Eco,1056,3,4,4,4,1,5,4,3,3,3,3,1,3,1,19,7.0,satisfied +86413,101730,Male,Loyal Customer,32,Personal Travel,Eco,1216,2,0,2,2,2,2,5,2,2,5,4,5,2,2,2,0.0,neutral or dissatisfied +86414,57426,Male,Loyal Customer,24,Business travel,Business,3850,4,3,4,3,4,4,4,4,3,5,3,2,4,4,0,0.0,neutral or dissatisfied +86415,48496,Male,disloyal Customer,25,Business travel,Eco,848,3,3,3,4,2,3,2,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +86416,119279,Female,disloyal Customer,22,Business travel,Eco,214,4,5,4,4,4,4,2,4,3,2,5,5,4,4,0,23.0,neutral or dissatisfied +86417,85021,Female,Loyal Customer,22,Personal Travel,Eco,1590,5,4,5,4,5,5,5,5,5,5,4,3,4,5,2,0.0,satisfied +86418,22127,Female,Loyal Customer,36,Business travel,Eco Plus,694,2,1,1,1,2,2,2,2,5,3,4,1,2,2,0,0.0,satisfied +86419,88163,Female,Loyal Customer,51,Business travel,Business,2792,3,2,3,3,3,4,5,4,4,4,4,4,4,5,15,6.0,satisfied +86420,104036,Female,Loyal Customer,47,Business travel,Business,2093,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +86421,84805,Male,Loyal Customer,51,Business travel,Business,2987,2,2,2,2,5,4,5,3,3,3,3,4,3,5,0,3.0,satisfied +86422,111582,Female,Loyal Customer,38,Personal Travel,Eco,883,1,4,0,3,5,0,5,5,4,5,4,4,5,5,80,80.0,neutral or dissatisfied +86423,105704,Female,Loyal Customer,29,Business travel,Business,787,4,4,3,4,4,4,4,4,4,5,5,4,4,4,15,23.0,satisfied +86424,123366,Female,disloyal Customer,12,Business travel,Business,644,4,4,3,5,3,3,3,3,3,5,5,5,5,3,0,0.0,satisfied +86425,70068,Male,Loyal Customer,49,Personal Travel,Business,460,4,4,4,4,3,4,4,1,1,4,1,5,1,5,0,1.0,satisfied +86426,59533,Female,Loyal Customer,44,Business travel,Business,2667,2,2,2,2,3,4,4,4,4,5,4,5,4,5,1,0.0,satisfied +86427,126414,Female,Loyal Customer,47,Business travel,Business,2918,4,4,4,4,4,4,5,5,5,5,5,4,5,4,7,0.0,satisfied +86428,19752,Male,Loyal Customer,60,Business travel,Business,3990,4,4,4,4,3,2,5,5,5,5,5,1,5,3,1,6.0,satisfied +86429,50350,Male,Loyal Customer,35,Business travel,Eco,190,5,2,2,2,5,5,5,5,1,4,5,2,5,5,0,0.0,satisfied +86430,94893,Female,Loyal Customer,51,Business travel,Business,248,2,4,4,4,3,3,3,2,2,2,2,2,2,2,14,5.0,neutral or dissatisfied +86431,118757,Female,Loyal Customer,42,Personal Travel,Eco,370,3,0,3,4,2,5,4,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +86432,105712,Female,disloyal Customer,21,Business travel,Business,787,4,0,5,5,3,5,3,3,3,3,4,3,4,3,31,18.0,satisfied +86433,99597,Male,Loyal Customer,22,Personal Travel,Eco,930,3,1,4,3,4,4,3,4,3,4,3,3,3,4,1,23.0,neutral or dissatisfied +86434,6107,Female,Loyal Customer,62,Personal Travel,Business,409,2,5,5,3,5,5,5,3,3,5,3,3,3,4,71,103.0,neutral or dissatisfied +86435,52726,Male,Loyal Customer,19,Business travel,Eco,406,2,1,1,1,2,2,3,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +86436,115981,Male,Loyal Customer,30,Personal Travel,Eco,308,5,3,5,4,5,5,5,5,2,3,4,4,4,5,12,3.0,satisfied +86437,7479,Female,disloyal Customer,25,Business travel,Business,925,5,3,5,1,2,5,2,2,3,4,5,4,5,2,0,0.0,satisfied +86438,111877,Male,disloyal Customer,18,Business travel,Eco,628,3,0,3,2,1,3,4,1,5,2,4,5,4,1,4,0.0,neutral or dissatisfied +86439,107181,Male,Loyal Customer,29,Business travel,Business,3628,1,2,2,2,1,2,1,1,1,2,4,1,3,1,18,7.0,neutral or dissatisfied +86440,42099,Female,Loyal Customer,44,Business travel,Business,996,3,3,3,3,2,3,5,4,4,4,4,2,4,1,0,0.0,satisfied +86441,25649,Female,Loyal Customer,18,Personal Travel,Eco,526,3,4,3,3,5,3,5,5,4,4,5,5,5,5,4,0.0,neutral or dissatisfied +86442,84419,Male,Loyal Customer,65,Personal Travel,Eco,606,1,4,1,4,2,1,2,2,4,5,4,3,3,2,6,8.0,neutral or dissatisfied +86443,101377,Female,Loyal Customer,52,Business travel,Business,2686,1,1,5,1,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +86444,103497,Male,Loyal Customer,39,Personal Travel,Eco Plus,440,4,5,4,3,3,4,3,3,5,4,5,4,4,3,0,0.0,satisfied +86445,9573,Female,Loyal Customer,61,Business travel,Eco,288,1,1,1,1,1,1,1,1,5,4,3,1,2,1,191,210.0,neutral or dissatisfied +86446,91719,Male,disloyal Customer,28,Business travel,Business,588,0,0,0,2,1,0,1,1,4,2,4,5,5,1,0,0.0,satisfied +86447,42472,Female,disloyal Customer,23,Business travel,Eco,429,4,0,4,3,3,4,3,3,5,2,1,2,3,3,0,8.0,satisfied +86448,27215,Female,Loyal Customer,57,Business travel,Business,1024,2,2,2,2,3,5,5,3,3,4,3,4,3,3,1,10.0,satisfied +86449,27430,Male,Loyal Customer,48,Business travel,Eco,954,5,4,4,4,5,5,5,5,5,5,1,1,3,5,0,0.0,satisfied +86450,115143,Female,disloyal Customer,41,Business travel,Business,325,4,4,4,3,3,4,1,3,4,4,4,3,4,3,9,2.0,neutral or dissatisfied +86451,94491,Female,Loyal Customer,49,Business travel,Business,3133,4,1,4,4,3,5,4,4,4,5,4,5,4,5,2,1.0,satisfied +86452,106168,Male,Loyal Customer,34,Personal Travel,Eco,444,3,5,2,2,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +86453,30602,Female,Loyal Customer,52,Business travel,Eco,472,5,1,1,1,5,3,1,5,5,5,5,2,5,4,0,0.0,satisfied +86454,66442,Female,Loyal Customer,67,Business travel,Business,1217,3,4,4,4,2,3,2,3,3,3,3,2,3,1,0,8.0,neutral or dissatisfied +86455,19180,Male,Loyal Customer,12,Business travel,Business,1024,3,3,3,3,3,3,3,3,4,4,3,3,3,3,134,146.0,neutral or dissatisfied +86456,103727,Female,Loyal Customer,62,Personal Travel,Eco,251,4,5,4,2,4,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +86457,21297,Male,Loyal Customer,45,Business travel,Business,292,5,5,5,5,3,2,3,4,4,4,4,3,4,4,0,0.0,satisfied +86458,115568,Male,Loyal Customer,47,Business travel,Business,1729,5,5,5,5,2,5,4,5,5,5,5,5,5,5,7,0.0,satisfied +86459,92105,Male,Loyal Customer,23,Personal Travel,Eco,1535,1,4,2,1,3,2,3,3,3,3,3,3,5,3,0,0.0,neutral or dissatisfied +86460,30662,Male,Loyal Customer,45,Personal Travel,Eco,770,2,4,2,3,1,2,1,1,3,2,4,5,4,1,12,20.0,neutral or dissatisfied +86461,15453,Male,Loyal Customer,51,Business travel,Eco,331,5,3,3,3,5,5,5,5,4,1,3,2,5,5,48,53.0,satisfied +86462,16130,Female,Loyal Customer,41,Personal Travel,Eco,725,2,4,2,4,5,2,5,5,3,5,4,4,4,5,21,16.0,neutral or dissatisfied +86463,80549,Female,Loyal Customer,23,Business travel,Business,1747,1,1,1,1,1,1,1,1,4,3,3,2,4,1,0,0.0,neutral or dissatisfied +86464,92123,Male,Loyal Customer,46,Personal Travel,Eco,1589,4,5,3,2,5,3,5,5,4,5,4,3,5,5,0,0.0,satisfied +86465,120311,Male,Loyal Customer,38,Business travel,Business,3746,4,4,4,4,3,5,5,5,5,5,5,3,5,4,23,42.0,satisfied +86466,84851,Female,Loyal Customer,37,Business travel,Business,2948,3,3,3,3,4,4,4,5,5,5,4,2,5,4,0,0.0,satisfied +86467,116037,Male,Loyal Customer,24,Personal Travel,Eco,325,1,5,1,2,5,1,5,5,3,3,2,4,1,5,0,0.0,neutral or dissatisfied +86468,129015,Male,Loyal Customer,57,Business travel,Business,2704,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,,satisfied +86469,105348,Female,Loyal Customer,11,Personal Travel,Eco,452,4,5,5,3,5,5,1,5,3,4,4,3,5,5,0,0.0,satisfied +86470,52161,Male,disloyal Customer,58,Business travel,Eco,451,4,0,4,3,2,4,2,2,2,5,1,5,4,2,10,6.0,neutral or dissatisfied +86471,76841,Female,Loyal Customer,45,Business travel,Business,989,3,3,3,3,3,4,5,4,4,4,4,3,4,3,4,0.0,satisfied +86472,75207,Male,Loyal Customer,39,Business travel,Business,1726,2,2,2,2,5,3,2,2,2,2,2,2,2,4,2,0.0,neutral or dissatisfied +86473,129570,Female,Loyal Customer,8,Business travel,Eco Plus,2583,2,3,3,3,3,4,2,1,3,3,3,2,1,2,159,157.0,neutral or dissatisfied +86474,20322,Male,Loyal Customer,49,Business travel,Business,3885,5,5,5,5,3,5,4,4,4,4,4,4,4,3,40,36.0,satisfied +86475,19620,Male,disloyal Customer,24,Business travel,Eco,416,3,0,3,1,4,3,4,4,2,4,3,5,2,4,89,,neutral or dissatisfied +86476,108154,Female,Loyal Customer,23,Personal Travel,Eco,990,2,5,2,2,2,5,5,3,3,5,5,5,5,5,188,195.0,neutral or dissatisfied +86477,1323,Male,Loyal Customer,60,Business travel,Business,3795,2,2,2,2,4,5,4,5,5,5,4,3,5,4,39,52.0,satisfied +86478,26119,Female,Loyal Customer,24,Business travel,Business,2521,3,5,5,5,3,3,3,3,2,3,4,1,3,3,31,30.0,neutral or dissatisfied +86479,49389,Female,Loyal Customer,50,Business travel,Business,89,1,1,1,1,5,4,3,4,4,4,3,2,4,3,28,19.0,satisfied +86480,129000,Female,Loyal Customer,60,Personal Travel,Business,2611,2,4,2,1,2,1,3,2,1,4,4,3,2,3,0,0.0,neutral or dissatisfied +86481,99336,Female,Loyal Customer,47,Personal Travel,Eco Plus,448,2,3,2,3,3,1,2,2,2,2,2,4,2,3,2,0.0,neutral or dissatisfied +86482,88341,Male,Loyal Customer,31,Business travel,Business,3060,4,1,5,1,4,4,4,4,1,4,4,3,3,4,0,5.0,neutral or dissatisfied +86483,16982,Male,Loyal Customer,55,Business travel,Eco,610,2,2,2,2,2,2,2,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +86484,118417,Male,disloyal Customer,23,Business travel,Business,647,0,5,0,2,5,0,5,5,3,5,4,5,5,5,14,9.0,satisfied +86485,19110,Female,Loyal Customer,25,Business travel,Business,323,5,5,5,5,4,4,4,4,4,5,1,4,4,4,0,0.0,satisfied +86486,70427,Female,Loyal Customer,39,Business travel,Business,187,1,1,1,1,2,4,4,3,3,4,4,3,3,3,0,0.0,satisfied +86487,54981,Male,disloyal Customer,27,Business travel,Business,1303,3,4,4,3,5,4,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +86488,41113,Male,Loyal Customer,35,Business travel,Business,216,3,2,2,2,5,4,3,1,1,1,3,4,1,3,13,9.0,neutral or dissatisfied +86489,123086,Male,Loyal Customer,38,Business travel,Eco,507,2,4,4,4,2,3,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +86490,112899,Female,Loyal Customer,45,Business travel,Eco,715,3,3,3,3,5,2,3,3,3,3,3,4,3,3,33,28.0,neutral or dissatisfied +86491,51567,Male,Loyal Customer,51,Business travel,Eco,509,4,1,1,1,4,4,4,4,1,1,5,5,1,4,0,0.0,satisfied +86492,7033,Female,Loyal Customer,52,Business travel,Business,2358,5,5,5,5,5,5,5,4,4,4,4,4,4,3,6,0.0,satisfied +86493,103721,Male,Loyal Customer,15,Personal Travel,Eco,251,2,5,0,5,3,0,3,3,3,2,5,5,4,3,3,0.0,neutral or dissatisfied +86494,30577,Male,disloyal Customer,29,Business travel,Eco,628,1,0,1,4,5,1,5,5,2,1,4,5,3,5,0,0.0,neutral or dissatisfied +86495,309,Male,Loyal Customer,53,Business travel,Business,853,2,2,2,2,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +86496,43235,Male,Loyal Customer,57,Business travel,Business,347,3,2,4,2,1,4,4,3,3,3,3,2,3,3,0,32.0,neutral or dissatisfied +86497,5917,Male,Loyal Customer,18,Personal Travel,Eco,173,3,3,0,2,0,5,5,5,2,4,5,5,5,5,115,183.0,neutral or dissatisfied +86498,106682,Male,Loyal Customer,22,Personal Travel,Eco,451,3,4,3,3,4,3,4,4,1,5,3,2,4,4,17,11.0,neutral or dissatisfied +86499,85046,Male,Loyal Customer,43,Business travel,Business,2172,5,5,5,5,5,4,5,4,4,4,4,5,4,3,17,11.0,satisfied +86500,7262,Female,Loyal Customer,64,Personal Travel,Eco,135,3,3,3,3,3,3,3,5,5,3,5,4,5,2,0,26.0,neutral or dissatisfied +86501,83988,Male,Loyal Customer,44,Business travel,Business,1984,2,1,1,1,5,3,2,2,2,3,2,4,2,4,14,0.0,neutral or dissatisfied +86502,98140,Male,Loyal Customer,30,Personal Travel,Eco Plus,472,2,4,2,5,2,2,4,2,3,2,5,3,5,2,45,42.0,neutral or dissatisfied +86503,90593,Female,Loyal Customer,60,Business travel,Business,3661,5,5,5,5,5,5,5,3,3,4,3,5,3,5,0,9.0,satisfied +86504,108976,Male,Loyal Customer,19,Business travel,Business,2175,3,3,3,3,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +86505,67918,Male,Loyal Customer,21,Personal Travel,Eco,1235,4,5,4,4,4,4,2,4,4,5,4,5,5,4,0,0.0,satisfied +86506,86851,Male,Loyal Customer,18,Personal Travel,Eco,484,3,2,3,3,2,3,4,2,1,5,3,2,2,2,10,13.0,neutral or dissatisfied +86507,121234,Male,Loyal Customer,46,Business travel,Business,2075,1,1,1,1,5,5,5,2,2,2,2,4,2,4,0,31.0,satisfied +86508,68395,Female,Loyal Customer,40,Business travel,Business,2374,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +86509,81217,Female,Loyal Customer,75,Business travel,Business,1026,2,2,2,2,4,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +86510,116009,Female,Loyal Customer,47,Personal Travel,Eco,358,1,3,1,2,1,3,2,1,1,1,1,1,1,3,2,0.0,neutral or dissatisfied +86511,7441,Female,Loyal Customer,26,Personal Travel,Eco,522,2,4,2,1,1,2,1,1,5,5,5,4,3,1,0,15.0,neutral or dissatisfied +86512,27375,Female,disloyal Customer,27,Business travel,Eco,1050,3,3,3,1,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +86513,11188,Male,Loyal Customer,60,Personal Travel,Eco,270,4,0,4,3,3,4,3,3,3,4,4,3,4,3,47,36.0,neutral or dissatisfied +86514,5932,Female,Loyal Customer,52,Personal Travel,Eco,212,3,4,0,3,1,2,3,5,5,0,5,1,5,2,0,0.0,neutral or dissatisfied +86515,31673,Male,disloyal Customer,62,Business travel,Eco,967,3,3,3,2,1,3,1,1,3,1,5,2,5,1,0,0.0,neutral or dissatisfied +86516,117163,Female,Loyal Customer,57,Personal Travel,Eco,304,2,5,2,3,2,4,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +86517,9809,Female,Loyal Customer,46,Personal Travel,Eco,493,1,4,1,1,2,4,5,3,3,1,3,3,3,3,0,2.0,neutral or dissatisfied +86518,121887,Female,Loyal Customer,22,Personal Travel,Eco,337,4,5,5,1,4,5,1,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +86519,101076,Female,Loyal Customer,44,Business travel,Business,583,5,5,2,5,3,5,5,4,4,4,4,3,4,5,32,30.0,satisfied +86520,75430,Female,disloyal Customer,25,Business travel,Business,1384,5,5,5,2,3,5,3,3,5,2,5,5,5,3,1,0.0,satisfied +86521,32644,Male,disloyal Customer,23,Business travel,Eco,102,3,4,3,4,4,3,2,4,4,2,3,3,3,4,0,4.0,neutral or dissatisfied +86522,48491,Female,Loyal Customer,29,Business travel,Business,909,4,2,2,2,4,4,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +86523,24766,Male,disloyal Customer,37,Business travel,Eco,432,2,4,2,2,5,2,5,5,4,3,4,2,4,5,0,15.0,neutral or dissatisfied +86524,62852,Female,Loyal Customer,41,Business travel,Business,2583,5,5,5,5,2,5,4,4,4,4,4,4,4,3,21,34.0,satisfied +86525,63954,Male,Loyal Customer,13,Personal Travel,Eco,1192,3,2,3,4,4,3,4,4,1,5,3,2,4,4,0,9.0,neutral or dissatisfied +86526,34785,Female,Loyal Customer,28,Personal Travel,Eco,301,1,4,1,3,2,1,4,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +86527,86845,Female,Loyal Customer,41,Personal Travel,Eco,692,2,1,2,3,2,2,2,2,4,5,2,2,3,2,0,0.0,neutral or dissatisfied +86528,27515,Male,Loyal Customer,28,Personal Travel,Eco,1050,4,4,4,5,5,4,5,5,5,4,4,4,5,5,8,0.0,satisfied +86529,12172,Male,Loyal Customer,38,Business travel,Business,1702,2,2,2,2,1,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +86530,126677,Male,Loyal Customer,42,Business travel,Business,2276,2,2,2,2,4,5,4,5,5,5,5,4,5,3,10,0.0,satisfied +86531,75989,Male,Loyal Customer,30,Personal Travel,Eco,297,2,4,2,2,2,2,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +86532,38320,Male,Loyal Customer,28,Personal Travel,Eco Plus,1666,3,3,3,3,3,3,3,3,3,4,2,1,2,3,92,122.0,neutral or dissatisfied +86533,78004,Female,Loyal Customer,44,Business travel,Business,2335,3,3,5,3,4,3,4,2,2,2,3,4,2,4,0,0.0,neutral or dissatisfied +86534,86013,Female,Loyal Customer,18,Business travel,Business,432,1,1,1,1,4,4,4,4,3,2,4,4,4,4,13,4.0,satisfied +86535,27743,Female,Loyal Customer,56,Business travel,Business,2213,1,1,1,1,5,5,4,4,4,4,4,1,4,4,0,0.0,satisfied +86536,34407,Female,Loyal Customer,14,Personal Travel,Eco,612,3,4,3,2,4,3,4,4,2,1,1,1,2,4,0,0.0,neutral or dissatisfied +86537,125775,Female,Loyal Customer,32,Business travel,Business,1684,2,2,2,2,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +86538,121134,Female,Loyal Customer,39,Business travel,Business,2521,1,2,1,1,2,2,2,4,4,4,4,2,5,2,32,11.0,satisfied +86539,94104,Male,Loyal Customer,29,Personal Travel,Business,323,3,3,3,2,1,3,1,1,4,1,4,5,2,1,0,6.0,neutral or dissatisfied +86540,57115,Male,Loyal Customer,20,Business travel,Business,1222,3,2,2,2,3,4,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +86541,100104,Female,Loyal Customer,52,Business travel,Business,2411,4,4,4,4,3,5,4,3,3,3,3,5,3,5,5,6.0,satisfied +86542,42490,Female,Loyal Customer,9,Business travel,Business,693,2,2,2,2,2,2,2,2,3,2,3,2,4,2,5,8.0,neutral or dissatisfied +86543,27815,Male,Loyal Customer,51,Business travel,Eco,909,4,5,5,5,4,4,4,4,3,5,2,1,2,4,0,0.0,neutral or dissatisfied +86544,100046,Male,Loyal Customer,12,Personal Travel,Eco,281,1,5,1,3,2,1,2,2,3,3,5,3,5,2,74,91.0,neutral or dissatisfied +86545,5720,Female,Loyal Customer,42,Personal Travel,Eco,234,2,4,2,3,2,4,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +86546,88041,Male,Loyal Customer,49,Business travel,Business,545,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +86547,101011,Male,Loyal Customer,34,Business travel,Business,3264,3,4,4,4,5,4,3,3,3,3,3,1,3,3,57,52.0,neutral or dissatisfied +86548,12670,Female,Loyal Customer,40,Business travel,Eco,721,5,2,2,2,5,5,5,5,2,3,3,4,3,5,0,20.0,satisfied +86549,100737,Female,Loyal Customer,16,Business travel,Business,328,4,2,2,2,4,4,4,4,3,1,3,4,3,4,4,1.0,neutral or dissatisfied +86550,16979,Female,Loyal Customer,60,Personal Travel,Eco Plus,209,1,3,1,3,5,3,3,3,3,1,3,1,3,3,93,106.0,neutral or dissatisfied +86551,52003,Female,Loyal Customer,47,Business travel,Business,328,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +86552,121960,Female,Loyal Customer,23,Business travel,Eco Plus,430,1,2,2,2,1,1,2,1,3,5,3,3,4,1,0,39.0,neutral or dissatisfied +86553,31100,Male,Loyal Customer,52,Personal Travel,Eco,1014,3,3,3,5,3,3,2,3,4,1,3,3,2,3,34,35.0,neutral or dissatisfied +86554,78831,Male,Loyal Customer,54,Personal Travel,Eco,447,4,4,4,1,5,4,4,5,3,2,5,5,5,5,10,4.0,satisfied +86555,102870,Male,Loyal Customer,40,Business travel,Business,2642,5,5,5,5,4,5,5,1,1,2,1,3,1,5,58,58.0,satisfied +86556,41689,Male,Loyal Customer,66,Personal Travel,Eco,347,4,3,4,1,3,4,2,3,4,4,2,2,5,3,0,0.0,neutral or dissatisfied +86557,22941,Male,disloyal Customer,24,Business travel,Eco,817,5,5,5,3,5,0,5,5,4,2,3,2,5,5,0,0.0,satisfied +86558,75146,Female,Loyal Customer,44,Business travel,Business,1744,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +86559,127085,Male,disloyal Customer,20,Business travel,Eco,647,2,0,2,3,1,2,1,1,5,2,3,1,5,1,0,0.0,neutral or dissatisfied +86560,3894,Female,disloyal Customer,24,Business travel,Eco,213,3,2,2,3,5,2,2,5,4,3,3,3,4,5,0,7.0,neutral or dissatisfied +86561,62292,Male,Loyal Customer,37,Business travel,Business,414,2,2,2,2,2,5,4,5,5,5,5,3,5,4,17,12.0,satisfied +86562,109483,Male,disloyal Customer,38,Business travel,Eco,992,2,2,2,4,3,2,3,3,4,4,4,2,3,3,28,49.0,neutral or dissatisfied +86563,3575,Male,Loyal Customer,46,Personal Travel,Eco,227,2,4,2,2,1,2,5,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +86564,69238,Female,Loyal Customer,47,Business travel,Business,733,2,1,1,1,3,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +86565,49349,Female,Loyal Customer,41,Business travel,Eco,209,3,2,2,2,3,3,3,3,1,1,3,4,3,3,0,4.0,neutral or dissatisfied +86566,34116,Male,Loyal Customer,38,Business travel,Eco,1288,5,5,3,5,5,5,5,5,5,2,1,4,5,5,0,0.0,satisfied +86567,125282,Female,disloyal Customer,30,Business travel,Business,678,2,2,2,3,3,2,3,3,3,5,4,4,5,3,6,0.0,neutral or dissatisfied +86568,97048,Male,Loyal Customer,69,Personal Travel,Business,1313,2,4,2,4,2,4,4,4,4,2,5,3,4,2,12,0.0,neutral or dissatisfied +86569,126197,Male,Loyal Customer,59,Business travel,Business,328,4,4,4,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +86570,37485,Female,Loyal Customer,49,Business travel,Eco,1076,2,3,1,1,3,3,4,2,2,2,2,4,2,1,5,22.0,neutral or dissatisfied +86571,53295,Female,Loyal Customer,12,Business travel,Business,3103,1,1,1,1,4,4,4,4,3,4,1,1,3,4,0,0.0,satisfied +86572,64122,Female,Loyal Customer,10,Personal Travel,Eco,2311,1,4,1,1,1,3,3,5,5,4,5,3,4,3,0,5.0,neutral or dissatisfied +86573,117646,Male,Loyal Customer,47,Business travel,Business,2363,1,1,4,1,3,5,5,4,4,4,4,3,4,3,43,39.0,satisfied +86574,73488,Female,Loyal Customer,45,Personal Travel,Eco,1144,2,3,2,4,2,5,5,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +86575,48124,Male,disloyal Customer,24,Business travel,Eco,192,4,0,4,4,5,4,4,5,3,1,2,4,5,5,15,16.0,satisfied +86576,114221,Female,Loyal Customer,25,Business travel,Business,2680,3,3,3,3,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +86577,99157,Male,Loyal Customer,59,Business travel,Business,2031,4,5,4,4,5,5,4,2,2,2,2,4,2,5,47,50.0,satisfied +86578,43612,Female,Loyal Customer,50,Business travel,Business,1722,2,2,2,2,3,2,4,4,4,4,5,4,4,3,0,0.0,satisfied +86579,122278,Male,Loyal Customer,10,Personal Travel,Eco,544,4,3,4,3,4,4,4,4,5,5,4,1,1,4,0,0.0,neutral or dissatisfied +86580,59677,Female,Loyal Customer,41,Personal Travel,Eco,965,2,4,2,3,5,2,5,5,2,3,3,3,1,5,0,0.0,neutral or dissatisfied +86581,42007,Female,Loyal Customer,55,Business travel,Eco,106,5,3,3,3,2,3,4,5,5,5,5,5,5,3,0,4.0,satisfied +86582,105847,Female,Loyal Customer,42,Business travel,Business,3394,1,1,1,1,3,4,4,2,2,2,2,3,2,3,14,0.0,satisfied +86583,101483,Female,Loyal Customer,48,Business travel,Business,3589,1,5,5,5,5,3,2,1,1,1,1,1,1,2,2,7.0,neutral or dissatisfied +86584,103350,Male,Loyal Customer,10,Personal Travel,Eco Plus,1139,1,4,1,3,3,1,5,3,5,4,3,3,4,3,0,0.0,neutral or dissatisfied +86585,9770,Male,Loyal Customer,41,Business travel,Business,456,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +86586,125284,Male,Loyal Customer,51,Business travel,Business,2740,2,2,5,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +86587,127790,Male,Loyal Customer,46,Business travel,Business,1044,2,1,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +86588,54225,Male,Loyal Customer,21,Business travel,Business,1530,3,3,3,3,4,4,4,4,4,4,5,5,2,4,2,0.0,satisfied +86589,97504,Female,Loyal Customer,9,Personal Travel,Eco,756,1,5,1,1,4,1,3,4,4,3,5,3,4,4,7,0.0,neutral or dissatisfied +86590,48518,Female,Loyal Customer,14,Business travel,Business,2835,2,4,4,4,2,2,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +86591,105921,Male,Loyal Customer,44,Personal Travel,Eco Plus,283,3,5,5,3,2,5,2,2,1,3,1,2,4,2,0,0.0,neutral or dissatisfied +86592,55206,Female,Loyal Customer,67,Personal Travel,Eco Plus,1379,4,4,4,1,2,3,4,1,1,4,1,3,1,3,0,3.0,neutral or dissatisfied +86593,56307,Female,Loyal Customer,50,Business travel,Business,1882,2,5,5,5,4,2,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +86594,53818,Male,Loyal Customer,58,Business travel,Business,1521,2,2,4,2,2,5,1,5,5,4,5,1,5,2,0,2.0,satisfied +86595,127259,Male,disloyal Customer,30,Business travel,Business,1107,3,3,3,2,2,3,4,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +86596,29483,Male,Loyal Customer,50,Business travel,Eco,1107,2,5,2,5,1,2,1,1,2,3,3,3,3,1,0,1.0,neutral or dissatisfied +86597,80740,Male,Loyal Customer,39,Business travel,Business,2345,2,3,3,3,5,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +86598,58307,Female,disloyal Customer,28,Business travel,Business,1285,4,4,4,5,5,4,3,5,4,4,3,3,4,5,5,0.0,satisfied +86599,31266,Female,Loyal Customer,47,Business travel,Business,2839,3,4,4,4,3,3,3,3,3,2,3,4,3,1,37,52.0,neutral or dissatisfied +86600,82732,Male,Loyal Customer,29,Personal Travel,Business,409,2,4,2,3,3,2,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +86601,34876,Male,Loyal Customer,25,Personal Travel,Eco,2248,4,5,4,5,4,4,3,4,3,4,4,5,5,4,27,14.0,neutral or dissatisfied +86602,108897,Female,Loyal Customer,33,Business travel,Business,2362,3,3,3,3,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +86603,85710,Male,Loyal Customer,64,Personal Travel,Eco,1547,4,5,4,2,3,4,3,3,5,3,4,3,4,3,17,0.0,neutral or dissatisfied +86604,8667,Male,disloyal Customer,57,Business travel,Business,227,5,5,5,4,2,5,2,2,5,5,4,4,4,2,0,0.0,satisfied +86605,122149,Male,Loyal Customer,26,Business travel,Business,3922,5,5,5,5,4,4,4,4,3,2,4,4,4,4,0,0.0,satisfied +86606,60211,Female,disloyal Customer,34,Business travel,Business,1546,1,1,1,4,5,1,5,5,4,4,4,5,5,5,7,0.0,neutral or dissatisfied +86607,22912,Male,Loyal Customer,53,Personal Travel,Business,630,3,4,3,3,3,5,5,2,2,3,3,3,2,3,0,0.0,neutral or dissatisfied +86608,29737,Female,Loyal Customer,45,Business travel,Business,1570,2,2,2,2,2,5,4,2,2,2,2,3,2,4,6,0.0,satisfied +86609,11412,Female,Loyal Customer,54,Business travel,Business,216,3,3,3,3,4,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +86610,13995,Male,Loyal Customer,51,Business travel,Business,1676,5,5,5,5,1,2,2,5,5,5,3,2,5,4,0,0.0,satisfied +86611,57629,Male,Loyal Customer,50,Business travel,Business,1644,3,3,1,3,5,4,5,5,5,5,4,5,5,5,0,0.0,satisfied +86612,32174,Male,disloyal Customer,22,Business travel,Eco,102,3,0,3,4,5,3,5,5,5,2,3,4,1,5,0,1.0,neutral or dissatisfied +86613,20478,Male,Loyal Customer,56,Personal Travel,Business,139,1,0,1,3,4,4,5,3,3,1,3,3,3,4,5,2.0,neutral or dissatisfied +86614,47104,Female,Loyal Customer,33,Business travel,Eco Plus,438,2,2,2,2,2,1,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +86615,118147,Male,Loyal Customer,33,Business travel,Business,1440,4,4,2,4,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +86616,39944,Female,Loyal Customer,22,Personal Travel,Eco,1195,2,5,2,5,1,2,1,1,5,4,3,5,4,1,13,8.0,neutral or dissatisfied +86617,7994,Female,Loyal Customer,59,Business travel,Business,1658,2,4,4,4,2,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +86618,102949,Female,Loyal Customer,29,Business travel,Business,1902,2,2,2,2,5,5,5,5,3,5,5,4,4,5,0,0.0,satisfied +86619,17129,Female,disloyal Customer,59,Business travel,Eco,472,4,0,4,5,2,4,4,2,3,4,2,2,5,2,0,0.0,neutral or dissatisfied +86620,51970,Female,disloyal Customer,37,Business travel,Eco,347,4,0,4,2,2,4,1,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +86621,13118,Female,Loyal Customer,52,Business travel,Business,3379,2,3,3,3,4,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +86622,18838,Female,Loyal Customer,47,Business travel,Eco,500,4,5,5,5,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +86623,33182,Female,disloyal Customer,24,Business travel,Eco,101,3,0,3,1,4,3,4,4,5,4,3,5,1,4,0,0.0,neutral or dissatisfied +86624,16563,Female,disloyal Customer,27,Business travel,Eco,1092,3,3,3,4,3,3,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +86625,124173,Male,Loyal Customer,70,Personal Travel,Eco,2133,3,1,3,2,2,3,2,2,1,1,2,4,3,2,0,0.0,neutral or dissatisfied +86626,80455,Male,Loyal Customer,27,Business travel,Business,2772,5,5,5,5,4,4,4,4,5,5,4,4,5,4,5,0.0,satisfied +86627,56471,Male,Loyal Customer,54,Personal Travel,Eco Plus,719,3,4,3,1,3,3,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +86628,36771,Male,disloyal Customer,33,Business travel,Business,2704,2,2,2,3,2,5,5,1,2,4,3,5,1,5,0,0.0,neutral or dissatisfied +86629,57930,Female,Loyal Customer,45,Business travel,Business,3051,3,3,3,3,4,4,5,5,5,5,5,4,5,4,19,14.0,satisfied +86630,13411,Female,Loyal Customer,37,Business travel,Business,2237,4,4,4,4,4,4,4,4,2,5,5,4,3,4,158,144.0,satisfied +86631,122216,Male,Loyal Customer,30,Business travel,Business,546,1,3,3,3,1,2,1,1,3,3,1,2,2,1,11,8.0,neutral or dissatisfied +86632,9754,Male,Loyal Customer,53,Personal Travel,Eco Plus,908,0,5,0,2,2,0,2,2,1,3,5,3,5,2,2,0.0,satisfied +86633,119229,Female,Loyal Customer,54,Personal Travel,Eco,331,3,3,3,2,3,3,4,2,2,3,2,2,2,5,8,18.0,neutral or dissatisfied +86634,115154,Male,Loyal Customer,37,Business travel,Business,2974,0,0,0,1,2,4,5,4,4,1,1,3,4,4,0,0.0,satisfied +86635,61063,Female,Loyal Customer,20,Business travel,Business,1506,3,3,3,3,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +86636,33559,Male,Loyal Customer,54,Business travel,Eco,399,4,1,2,1,4,4,4,4,3,1,1,5,5,4,0,0.0,satisfied +86637,99969,Male,Loyal Customer,43,Personal Travel,Eco,888,4,5,4,2,5,4,5,5,1,3,1,2,3,5,76,76.0,neutral or dissatisfied +86638,113103,Female,Loyal Customer,11,Personal Travel,Eco,569,1,2,1,3,1,1,1,1,3,4,2,3,3,1,11,0.0,neutral or dissatisfied +86639,96020,Female,Loyal Customer,44,Business travel,Eco,1069,2,3,3,3,1,3,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +86640,38442,Male,Loyal Customer,25,Business travel,Business,2373,5,5,5,5,5,5,5,5,5,2,4,5,5,5,0,0.0,satisfied +86641,76389,Female,Loyal Customer,44,Business travel,Eco,531,4,5,5,5,1,3,5,4,4,4,4,1,4,2,71,55.0,satisfied +86642,14150,Male,Loyal Customer,7,Personal Travel,Eco,413,2,5,2,5,3,2,3,3,2,3,5,3,3,3,0,0.0,neutral or dissatisfied +86643,59652,Male,disloyal Customer,41,Business travel,Eco,454,2,4,2,3,2,2,2,2,1,2,5,5,4,2,0,0.0,neutral or dissatisfied +86644,86502,Male,Loyal Customer,37,Personal Travel,Eco,762,3,4,3,4,3,3,1,3,3,4,4,3,3,3,9,11.0,neutral or dissatisfied +86645,41068,Female,Loyal Customer,39,Business travel,Eco,140,4,1,4,1,4,4,4,4,1,5,2,3,5,4,10,8.0,satisfied +86646,31934,Male,disloyal Customer,22,Business travel,Business,121,0,0,0,3,5,0,5,5,5,5,5,5,5,5,0,0.0,satisfied +86647,57564,Male,Loyal Customer,31,Business travel,Business,1597,1,5,5,5,1,1,1,1,3,2,2,1,3,1,0,0.0,neutral or dissatisfied +86648,33105,Male,Loyal Customer,25,Personal Travel,Eco,101,3,5,3,4,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +86649,90310,Female,Loyal Customer,51,Business travel,Business,1750,5,5,5,5,2,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +86650,16462,Male,Loyal Customer,45,Personal Travel,Eco,529,2,5,2,4,5,2,5,5,4,5,4,5,4,5,71,69.0,neutral or dissatisfied +86651,31596,Female,disloyal Customer,30,Business travel,Eco,602,2,4,2,4,3,2,3,3,1,1,3,3,4,3,78,88.0,neutral or dissatisfied +86652,53540,Male,Loyal Customer,60,Personal Travel,Eco Plus,2288,3,3,3,1,1,3,4,1,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +86653,7698,Female,Loyal Customer,29,Personal Travel,Eco,641,3,5,3,1,1,3,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +86654,11702,Male,Loyal Customer,47,Business travel,Business,395,2,5,2,2,4,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +86655,54666,Male,Loyal Customer,45,Business travel,Business,854,3,3,3,3,3,3,3,5,5,5,5,2,5,3,7,0.0,satisfied +86656,107137,Male,Loyal Customer,60,Business travel,Business,402,3,3,3,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +86657,121948,Male,Loyal Customer,37,Business travel,Business,1642,3,5,5,5,5,3,2,3,3,3,3,2,3,4,3,12.0,neutral or dissatisfied +86658,48266,Male,disloyal Customer,38,Business travel,Eco Plus,259,3,3,3,2,5,3,5,5,1,3,4,2,5,5,13,1.0,neutral or dissatisfied +86659,11829,Male,disloyal Customer,24,Business travel,Eco,586,2,5,2,1,3,2,3,3,1,2,1,3,5,3,20,7.0,neutral or dissatisfied +86660,46726,Female,Loyal Customer,18,Personal Travel,Eco,125,3,4,3,2,3,3,3,3,2,3,5,2,4,3,0,0.0,neutral or dissatisfied +86661,28763,Female,Loyal Customer,24,Personal Travel,Eco,1024,2,5,2,1,2,2,2,2,4,5,4,3,4,2,0,42.0,neutral or dissatisfied +86662,110435,Male,Loyal Customer,48,Personal Travel,Eco,663,2,5,2,3,2,2,2,2,5,4,2,5,5,2,0,0.0,neutral or dissatisfied +86663,61943,Female,Loyal Customer,47,Business travel,Business,2052,1,1,1,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +86664,60945,Male,Loyal Customer,53,Business travel,Business,888,1,5,5,5,3,4,3,1,1,1,1,4,1,3,33,45.0,neutral or dissatisfied +86665,8783,Male,Loyal Customer,44,Business travel,Business,3605,2,2,2,2,5,4,4,4,4,4,4,4,4,4,50,51.0,satisfied +86666,52187,Female,Loyal Customer,39,Business travel,Business,598,4,4,4,4,3,4,1,4,4,4,4,3,4,1,0,2.0,neutral or dissatisfied +86667,8909,Female,Loyal Customer,55,Personal Travel,Eco,510,5,5,5,1,5,5,5,3,3,5,2,3,3,4,8,25.0,satisfied +86668,23200,Male,Loyal Customer,63,Personal Travel,Eco Plus,223,3,5,0,1,1,0,1,1,5,4,5,4,5,1,60,58.0,neutral or dissatisfied +86669,67364,Female,Loyal Customer,42,Personal Travel,Business,769,3,5,3,1,2,4,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +86670,11291,Female,Loyal Customer,30,Personal Travel,Eco,224,2,4,2,3,4,2,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +86671,90579,Female,Loyal Customer,34,Business travel,Business,3896,0,0,0,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +86672,40626,Female,Loyal Customer,51,Personal Travel,Eco,411,1,4,1,3,3,4,5,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +86673,30116,Male,Loyal Customer,36,Personal Travel,Eco,399,2,5,2,3,3,2,3,3,3,4,5,5,4,3,2,0.0,neutral or dissatisfied +86674,23277,Female,Loyal Customer,41,Business travel,Business,1652,2,2,2,2,3,2,5,2,2,2,2,3,2,2,15,6.0,satisfied +86675,53190,Female,Loyal Customer,42,Business travel,Business,2646,1,1,1,1,2,1,2,4,4,4,4,3,4,2,0,4.0,satisfied +86676,9460,Male,Loyal Customer,27,Personal Travel,Eco,299,2,5,5,4,4,5,4,4,5,3,5,4,5,4,15,6.0,neutral or dissatisfied +86677,41759,Female,Loyal Customer,52,Business travel,Eco,491,4,1,5,1,2,5,2,4,4,4,4,3,4,3,0,0.0,satisfied +86678,49413,Male,Loyal Customer,28,Business travel,Business,1809,2,2,2,2,2,2,2,2,3,2,4,3,4,2,57,54.0,neutral or dissatisfied +86679,97350,Female,disloyal Customer,54,Business travel,Eco,472,3,0,3,1,4,3,1,4,2,2,2,2,4,4,0,0.0,neutral or dissatisfied +86680,120216,Male,Loyal Customer,17,Business travel,Business,1496,2,2,2,2,2,3,2,2,3,5,3,4,3,2,2,10.0,neutral or dissatisfied +86681,110104,Male,disloyal Customer,34,Business travel,Business,882,3,3,3,5,2,3,2,2,4,4,5,4,4,2,0,1.0,neutral or dissatisfied +86682,19520,Male,Loyal Customer,54,Business travel,Business,2853,5,5,5,5,5,4,5,5,5,5,5,4,5,4,15,10.0,satisfied +86683,16114,Male,Loyal Customer,19,Business travel,Business,725,3,3,3,3,5,5,5,5,4,2,3,5,5,5,0,12.0,satisfied +86684,45476,Female,Loyal Customer,10,Business travel,Eco,522,4,5,5,5,4,4,4,4,3,5,4,4,5,4,0,2.0,satisfied +86685,109538,Female,Loyal Customer,65,Personal Travel,Eco,992,2,5,2,3,4,5,4,1,1,2,1,3,1,5,4,2.0,neutral or dissatisfied +86686,52385,Female,Loyal Customer,41,Personal Travel,Eco,261,3,4,0,4,3,0,5,3,3,1,1,5,4,3,4,13.0,neutral or dissatisfied +86687,77271,Male,disloyal Customer,35,Business travel,Business,1931,1,1,1,2,1,1,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +86688,30072,Female,Loyal Customer,48,Personal Travel,Eco,571,2,3,2,4,1,3,3,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +86689,112514,Male,Loyal Customer,8,Personal Travel,Eco,846,2,1,2,3,3,2,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +86690,13623,Female,Loyal Customer,22,Business travel,Business,1969,1,1,1,1,4,4,4,4,1,3,4,5,4,4,0,0.0,satisfied +86691,124737,Female,Loyal Customer,44,Business travel,Business,399,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,4.0,satisfied +86692,29128,Female,Loyal Customer,11,Personal Travel,Eco,987,3,2,3,2,2,3,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +86693,113436,Female,disloyal Customer,36,Business travel,Business,407,1,1,1,2,3,1,1,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +86694,101079,Male,Loyal Customer,56,Business travel,Business,690,4,4,4,4,5,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +86695,36892,Female,Loyal Customer,14,Personal Travel,Eco Plus,1182,1,2,1,3,5,1,5,5,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +86696,8162,Female,Loyal Customer,45,Business travel,Business,335,3,2,3,3,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +86697,80589,Female,Loyal Customer,42,Personal Travel,Eco,1747,2,0,3,1,4,5,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +86698,97259,Female,Loyal Customer,16,Personal Travel,Eco,296,5,5,5,2,5,5,5,5,5,3,4,5,5,5,0,2.0,satisfied +86699,80231,Male,Loyal Customer,57,Business travel,Business,1695,1,3,4,4,5,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +86700,48313,Male,Loyal Customer,35,Personal Travel,Eco,1499,4,3,4,3,4,4,4,4,3,4,3,1,4,4,11,0.0,neutral or dissatisfied +86701,86881,Male,Loyal Customer,61,Personal Travel,Eco Plus,484,4,5,4,3,2,4,2,2,4,4,5,5,5,2,2,0.0,neutral or dissatisfied +86702,78254,Male,Loyal Customer,41,Business travel,Business,2118,3,3,3,3,4,4,4,5,4,4,5,4,5,4,139,151.0,satisfied +86703,29534,Male,disloyal Customer,59,Business travel,Eco,1052,2,2,2,4,2,2,2,1,5,4,3,2,4,2,0,0.0,neutral or dissatisfied +86704,126799,Male,Loyal Customer,49,Business travel,Business,2125,2,2,2,2,4,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +86705,65472,Male,disloyal Customer,25,Business travel,Eco,1303,4,4,4,3,5,4,5,5,3,2,3,4,3,5,3,6.0,neutral or dissatisfied +86706,16319,Male,Loyal Customer,23,Business travel,Business,1787,4,4,4,4,5,5,5,5,4,5,2,5,3,5,8,5.0,satisfied +86707,95202,Female,Loyal Customer,30,Personal Travel,Eco,677,3,4,3,1,4,3,4,4,5,3,5,5,5,4,5,3.0,neutral or dissatisfied +86708,52305,Male,disloyal Customer,42,Business travel,Eco,261,3,3,3,1,2,3,2,2,1,2,4,3,5,2,0,0.0,neutral or dissatisfied +86709,54715,Male,Loyal Customer,28,Personal Travel,Eco,787,5,5,5,1,5,5,4,5,4,5,4,4,4,5,0,0.0,satisfied +86710,114227,Female,Loyal Customer,25,Business travel,Business,2558,2,1,1,1,2,2,2,2,4,3,3,2,3,2,29,28.0,neutral or dissatisfied +86711,12510,Female,Loyal Customer,51,Personal Travel,Eco Plus,201,5,3,5,4,4,2,4,1,1,5,1,1,1,3,0,0.0,satisfied +86712,31806,Male,Loyal Customer,26,Business travel,Business,2603,4,4,4,4,5,5,5,5,2,3,4,5,4,5,0,0.0,satisfied +86713,28697,Female,Loyal Customer,65,Personal Travel,Eco,2182,4,4,4,1,3,2,4,3,3,4,3,5,3,4,0,0.0,satisfied +86714,116181,Female,Loyal Customer,18,Personal Travel,Eco,373,3,1,3,3,5,3,5,5,1,1,3,4,4,5,0,6.0,neutral or dissatisfied +86715,111976,Male,Loyal Customer,18,Business travel,Business,2759,2,4,4,4,2,2,2,2,2,3,3,3,4,2,24,6.0,neutral or dissatisfied +86716,46003,Male,Loyal Customer,56,Personal Travel,Eco,300,2,2,2,2,3,2,3,3,4,5,2,2,2,3,48,72.0,neutral or dissatisfied +86717,15472,Female,Loyal Customer,64,Personal Travel,Eco,164,5,4,5,2,4,5,4,2,2,5,2,4,2,3,0,0.0,satisfied +86718,110249,Male,Loyal Customer,22,Personal Travel,Eco,1147,3,4,3,5,5,3,5,5,4,5,5,5,4,5,20,17.0,neutral or dissatisfied +86719,73745,Female,Loyal Customer,62,Personal Travel,Eco,204,1,2,0,4,3,4,4,2,2,0,2,3,2,3,3,1.0,neutral or dissatisfied +86720,43757,Female,Loyal Customer,35,Business travel,Business,2902,4,4,4,4,5,2,3,5,5,4,5,1,5,5,0,0.0,satisfied +86721,99241,Male,Loyal Customer,43,Personal Travel,Eco,495,4,3,2,3,5,2,5,5,4,1,3,3,4,5,0,0.0,satisfied +86722,109819,Female,Loyal Customer,32,Business travel,Business,3790,2,2,2,2,4,4,4,4,3,4,4,3,4,4,12,14.0,satisfied +86723,86182,Female,disloyal Customer,37,Business travel,Eco,226,3,2,3,2,4,3,3,4,2,2,2,1,3,4,1,0.0,neutral or dissatisfied +86724,119502,Female,disloyal Customer,22,Business travel,Business,814,0,0,0,3,2,0,3,2,4,5,5,3,4,2,1,7.0,satisfied +86725,22408,Female,disloyal Customer,23,Business travel,Eco,238,3,4,3,1,2,3,2,2,5,2,3,5,2,2,0,0.0,neutral or dissatisfied +86726,105885,Male,Loyal Customer,39,Business travel,Business,283,4,4,4,4,2,4,4,4,4,4,4,5,4,4,39,22.0,satisfied +86727,82270,Female,disloyal Customer,44,Business travel,Business,1481,3,3,3,5,2,3,1,2,3,3,5,3,5,2,26,40.0,neutral or dissatisfied +86728,63810,Female,Loyal Customer,54,Business travel,Business,2724,2,2,2,2,5,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +86729,47521,Female,Loyal Customer,56,Personal Travel,Eco,588,3,4,3,1,4,4,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +86730,32190,Male,Loyal Customer,39,Business travel,Eco,163,4,4,4,4,4,4,4,4,3,3,2,1,5,4,12,13.0,satisfied +86731,44695,Male,Loyal Customer,61,Business travel,Eco,160,3,1,1,1,3,3,3,3,2,1,3,4,3,3,85,81.0,neutral or dissatisfied +86732,88368,Female,disloyal Customer,27,Business travel,Eco,594,1,2,1,2,2,1,2,2,1,3,2,3,3,2,0,0.0,neutral or dissatisfied +86733,47858,Male,Loyal Customer,48,Business travel,Business,329,2,5,5,5,1,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +86734,92471,Female,Loyal Customer,60,Business travel,Business,1947,5,3,5,5,4,3,5,5,5,5,5,3,5,4,8,0.0,satisfied +86735,9032,Male,disloyal Customer,25,Business travel,Business,212,2,4,2,4,3,2,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +86736,117260,Female,Loyal Customer,47,Personal Travel,Eco,646,2,5,2,4,2,4,4,5,5,2,5,2,5,3,83,86.0,neutral or dissatisfied +86737,16256,Male,Loyal Customer,52,Business travel,Eco,946,3,4,4,4,3,3,3,5,3,4,3,3,2,3,95,158.0,satisfied +86738,96872,Female,Loyal Customer,21,Personal Travel,Eco,849,3,5,3,3,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +86739,119556,Male,Loyal Customer,52,Personal Travel,Eco,759,1,2,1,4,2,1,2,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +86740,68976,Female,Loyal Customer,69,Personal Travel,Eco,700,1,5,1,5,2,4,4,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +86741,42428,Female,Loyal Customer,43,Personal Travel,Eco Plus,834,4,4,4,1,2,5,5,1,1,4,1,4,1,3,0,5.0,neutral or dissatisfied +86742,57503,Male,Loyal Customer,19,Personal Travel,Eco,1075,4,5,4,3,4,3,3,4,2,1,2,3,1,3,377,350.0,neutral or dissatisfied +86743,63752,Female,Loyal Customer,44,Personal Travel,Eco,1660,2,3,3,1,3,5,2,3,3,3,3,3,3,4,14,13.0,neutral or dissatisfied +86744,77670,Female,disloyal Customer,22,Business travel,Eco,813,3,3,3,4,3,3,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +86745,32688,Male,Loyal Customer,41,Business travel,Eco,101,1,4,4,4,1,1,1,1,1,1,4,4,3,1,2,2.0,neutral or dissatisfied +86746,96539,Male,Loyal Customer,46,Personal Travel,Eco,302,2,5,2,3,3,2,3,3,5,3,4,4,5,3,64,69.0,neutral or dissatisfied +86747,81642,Female,Loyal Customer,50,Personal Travel,Business,907,1,4,1,3,5,5,4,5,5,1,3,5,5,3,0,0.0,neutral or dissatisfied +86748,78924,Male,disloyal Customer,20,Business travel,Eco,501,2,4,1,3,1,1,1,1,3,1,4,1,3,1,0,0.0,neutral or dissatisfied +86749,23946,Female,Loyal Customer,36,Business travel,Eco,936,1,2,5,5,1,1,1,1,2,2,3,3,4,1,0,0.0,neutral or dissatisfied +86750,57689,Male,Loyal Customer,53,Business travel,Business,867,4,5,5,5,1,3,2,4,4,4,4,2,4,3,17,10.0,neutral or dissatisfied +86751,106557,Male,Loyal Customer,14,Personal Travel,Business,1024,3,4,3,1,3,2,2,2,5,1,1,2,2,2,142,141.0,neutral or dissatisfied +86752,27369,Female,disloyal Customer,17,Business travel,Eco,671,0,0,0,3,1,0,1,1,1,5,3,4,5,1,0,0.0,satisfied +86753,92331,Female,disloyal Customer,37,Business travel,Business,2556,2,2,2,1,2,5,5,4,4,3,4,5,4,5,0,4.0,neutral or dissatisfied +86754,15410,Female,Loyal Customer,39,Business travel,Eco,433,4,1,1,1,4,4,4,4,1,2,5,5,4,4,0,0.0,satisfied +86755,108645,Female,Loyal Customer,45,Business travel,Business,1685,4,4,4,4,4,4,4,3,3,3,3,3,3,4,12,0.0,satisfied +86756,67696,Male,Loyal Customer,58,Business travel,Eco,1171,1,5,4,5,1,1,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +86757,89235,Male,Loyal Customer,39,Business travel,Business,1947,4,4,4,4,3,4,5,5,5,5,5,5,5,5,10,20.0,satisfied +86758,55083,Male,Loyal Customer,57,Business travel,Business,1379,3,3,3,3,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +86759,46963,Male,Loyal Customer,56,Personal Travel,Eco,845,3,2,3,3,4,3,4,4,2,3,2,2,3,4,0,0.0,neutral or dissatisfied +86760,129164,Male,disloyal Customer,20,Business travel,Eco,679,2,2,2,1,5,2,5,5,1,1,5,2,1,5,0,0.0,neutral or dissatisfied +86761,95759,Male,Loyal Customer,50,Personal Travel,Eco,181,3,4,0,4,2,0,2,2,3,5,5,5,5,2,21,20.0,neutral or dissatisfied +86762,16727,Female,Loyal Customer,21,Business travel,Business,2929,1,1,1,1,4,4,4,4,5,2,4,2,3,4,0,44.0,satisfied +86763,26089,Male,Loyal Customer,57,Business travel,Eco,591,4,4,4,4,4,4,4,4,5,5,4,1,5,4,1,0.0,satisfied +86764,119657,Male,Loyal Customer,47,Business travel,Business,507,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +86765,32686,Female,Loyal Customer,36,Business travel,Business,101,2,2,3,2,5,2,2,4,4,4,2,2,4,4,6,22.0,neutral or dissatisfied +86766,112113,Female,disloyal Customer,35,Business travel,Eco,1024,3,3,3,3,2,3,2,2,1,1,3,3,4,2,24,15.0,neutral or dissatisfied +86767,61889,Female,Loyal Customer,40,Personal Travel,Eco,2254,3,4,3,5,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +86768,92680,Male,disloyal Customer,37,Business travel,Business,507,1,1,1,4,2,1,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +86769,28580,Female,Loyal Customer,23,Business travel,Business,2603,2,1,1,1,2,2,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +86770,97797,Male,Loyal Customer,70,Personal Travel,Eco,471,2,4,4,5,3,4,3,3,3,5,4,3,5,3,43,66.0,neutral or dissatisfied +86771,98524,Female,Loyal Customer,55,Personal Travel,Eco,402,2,3,2,3,3,3,4,1,1,2,1,1,1,4,93,87.0,neutral or dissatisfied +86772,5685,Male,Loyal Customer,57,Business travel,Eco,196,3,2,2,2,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +86773,50063,Female,Loyal Customer,36,Business travel,Eco,373,2,2,2,2,2,2,2,2,4,5,3,2,4,2,25,27.0,neutral or dissatisfied +86774,82228,Female,disloyal Customer,58,Business travel,Eco,405,2,1,2,3,3,2,3,3,4,3,2,3,2,3,0,41.0,neutral or dissatisfied +86775,109430,Male,disloyal Customer,27,Business travel,Business,834,1,1,1,4,4,1,5,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +86776,35726,Male,Loyal Customer,61,Personal Travel,Eco Plus,2475,4,4,4,1,4,1,1,3,3,5,5,1,3,1,0,0.0,neutral or dissatisfied +86777,17203,Female,Loyal Customer,60,Business travel,Eco,694,4,5,5,5,2,3,4,4,4,4,4,2,4,3,129,129.0,neutral or dissatisfied +86778,36218,Female,Loyal Customer,39,Business travel,Eco,496,5,1,3,3,5,5,5,5,2,4,1,1,2,5,0,0.0,satisfied +86779,81688,Female,Loyal Customer,26,Business travel,Business,2419,1,1,3,1,4,4,4,4,5,4,4,3,1,4,0,0.0,satisfied +86780,33318,Male,Loyal Customer,46,Business travel,Eco,2556,5,1,1,1,5,5,5,5,4,2,5,2,4,5,0,0.0,satisfied +86781,121793,Male,Loyal Customer,56,Business travel,Business,337,2,2,2,2,3,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +86782,78378,Male,disloyal Customer,23,Business travel,Eco,980,1,1,1,1,2,1,2,2,3,5,5,4,5,2,18,13.0,neutral or dissatisfied +86783,118489,Male,Loyal Customer,43,Business travel,Business,646,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +86784,123098,Female,Loyal Customer,51,Business travel,Business,1743,3,3,3,3,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +86785,66889,Male,Loyal Customer,36,Business travel,Business,3909,4,4,4,4,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +86786,71639,Male,Loyal Customer,22,Personal Travel,Eco,1197,5,4,5,1,2,5,1,2,3,2,5,4,5,2,0,0.0,satisfied +86787,34209,Female,Loyal Customer,24,Personal Travel,Eco,1189,2,5,2,4,5,2,3,5,3,4,3,5,5,5,0,0.0,neutral or dissatisfied +86788,28227,Female,Loyal Customer,25,Personal Travel,Eco Plus,859,5,2,5,4,5,5,5,5,2,3,4,2,3,5,0,0.0,satisfied +86789,9769,Female,Loyal Customer,53,Business travel,Business,2449,4,4,4,4,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +86790,100458,Male,Loyal Customer,42,Business travel,Business,759,4,4,4,4,2,5,5,4,4,4,4,4,4,4,3,6.0,satisfied +86791,26501,Male,Loyal Customer,40,Business travel,Eco,829,4,1,1,1,4,3,4,4,4,5,1,1,1,4,0,0.0,neutral or dissatisfied +86792,65631,Male,Loyal Customer,42,Personal Travel,Eco,175,2,5,2,2,2,2,2,2,4,2,5,3,5,2,7,1.0,neutral or dissatisfied +86793,39548,Male,Loyal Customer,41,Business travel,Eco,954,5,4,2,4,5,5,5,5,2,4,1,2,4,5,100,94.0,satisfied +86794,23558,Male,Loyal Customer,51,Business travel,Eco,637,2,4,3,3,2,2,2,2,4,2,3,2,4,2,19,11.0,neutral or dissatisfied +86795,7098,Female,Loyal Customer,34,Personal Travel,Eco,273,2,3,2,3,5,2,5,5,1,4,5,2,1,5,0,0.0,neutral or dissatisfied +86796,81830,Male,Loyal Customer,43,Personal Travel,Eco,1501,3,5,2,2,4,2,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +86797,102426,Female,Loyal Customer,20,Personal Travel,Eco,223,2,2,0,4,4,0,2,4,4,3,5,3,5,4,20,12.0,neutral or dissatisfied +86798,49335,Female,Loyal Customer,34,Business travel,Business,266,0,0,0,3,5,3,4,3,3,3,3,5,3,5,0,0.0,satisfied +86799,57046,Male,Loyal Customer,48,Business travel,Business,2133,3,3,3,3,4,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +86800,117555,Female,Loyal Customer,41,Business travel,Business,3781,5,5,5,5,4,5,5,4,4,4,4,4,4,3,0,9.0,satisfied +86801,97355,Female,disloyal Customer,26,Business travel,Eco,443,1,0,1,5,5,1,5,5,5,2,5,2,4,5,33,44.0,neutral or dissatisfied +86802,73549,Male,Loyal Customer,10,Personal Travel,Eco,594,1,3,1,1,5,1,3,5,1,3,5,4,3,5,0,0.0,neutral or dissatisfied +86803,65738,Male,disloyal Customer,11,Business travel,Eco,936,3,3,3,4,1,3,1,1,3,5,3,1,4,1,46,30.0,neutral or dissatisfied +86804,125405,Female,Loyal Customer,36,Personal Travel,Eco,1440,2,4,2,1,3,2,3,3,5,2,4,5,5,3,1,16.0,neutral or dissatisfied +86805,26750,Male,disloyal Customer,25,Business travel,Eco,859,1,1,1,1,1,1,2,1,4,3,2,1,3,1,0,0.0,neutral or dissatisfied +86806,48305,Male,Loyal Customer,51,Business travel,Business,1499,1,1,1,1,4,3,3,1,1,1,1,4,1,3,13,2.0,neutral or dissatisfied +86807,25337,Female,Loyal Customer,68,Personal Travel,Eco,837,2,4,2,5,2,4,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +86808,37030,Female,Loyal Customer,48,Personal Travel,Business,1105,3,4,3,4,3,2,1,3,3,3,4,3,3,5,13,0.0,neutral or dissatisfied +86809,99689,Female,disloyal Customer,27,Business travel,Eco,442,3,3,3,3,3,3,5,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +86810,87835,Female,Loyal Customer,49,Personal Travel,Eco,214,2,4,0,3,3,1,5,5,5,0,3,2,5,3,0,0.0,neutral or dissatisfied +86811,107885,Female,Loyal Customer,45,Business travel,Business,2738,4,4,4,4,5,4,5,4,4,4,4,3,4,3,5,0.0,satisfied +86812,114000,Male,Loyal Customer,69,Business travel,Business,344,1,5,5,5,5,4,4,1,1,1,1,1,1,3,4,0.0,neutral or dissatisfied +86813,122198,Female,disloyal Customer,37,Business travel,Business,544,3,3,3,3,4,3,4,4,4,5,5,5,5,4,3,22.0,neutral or dissatisfied +86814,21998,Female,Loyal Customer,51,Personal Travel,Eco,448,3,4,3,4,2,5,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +86815,3637,Male,Loyal Customer,72,Business travel,Business,427,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,19.0,satisfied +86816,63389,Male,Loyal Customer,16,Personal Travel,Eco,447,2,3,2,4,4,2,4,4,4,3,4,2,3,4,12,0.0,neutral or dissatisfied +86817,81121,Female,disloyal Customer,27,Business travel,Eco,591,3,0,3,2,5,3,5,5,4,3,2,3,4,5,0,0.0,neutral or dissatisfied +86818,88222,Male,Loyal Customer,55,Business travel,Business,594,2,2,2,2,2,4,5,4,4,4,4,5,4,4,23,14.0,satisfied +86819,74208,Female,Loyal Customer,20,Personal Travel,Eco Plus,641,4,5,5,1,5,5,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +86820,39686,Male,disloyal Customer,23,Business travel,Business,1463,4,3,3,4,3,3,3,3,1,5,4,3,3,3,0,6.0,neutral or dissatisfied +86821,44508,Male,Loyal Customer,57,Personal Travel,Eco,411,2,4,2,4,4,2,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +86822,79902,Male,Loyal Customer,41,Business travel,Business,1904,1,1,5,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +86823,53368,Male,Loyal Customer,13,Business travel,Business,1452,3,1,1,1,3,2,3,3,3,5,4,4,4,3,28,59.0,neutral or dissatisfied +86824,39365,Male,disloyal Customer,38,Business travel,Eco,496,4,0,4,3,1,4,1,1,3,3,3,3,1,1,3,6.0,neutral or dissatisfied +86825,116516,Female,Loyal Customer,33,Personal Travel,Eco,308,4,4,4,3,5,4,3,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +86826,14525,Male,disloyal Customer,33,Business travel,Business,362,2,2,2,4,2,2,2,2,3,3,2,2,3,2,1,4.0,neutral or dissatisfied +86827,32529,Female,disloyal Customer,22,Business travel,Eco,121,4,5,4,3,2,4,2,2,5,3,5,5,5,2,0,0.0,satisfied +86828,64186,Male,Loyal Customer,13,Business travel,Business,1047,1,0,0,4,1,0,1,1,4,3,4,2,3,1,73,82.0,neutral or dissatisfied +86829,57349,Female,Loyal Customer,35,Business travel,Business,2708,2,2,2,2,3,5,3,5,5,5,5,3,5,1,75,73.0,satisfied +86830,705,Female,Loyal Customer,42,Business travel,Business,2950,3,1,1,1,2,2,3,5,5,4,3,1,5,2,0,0.0,neutral or dissatisfied +86831,66780,Male,disloyal Customer,22,Business travel,Business,783,5,0,4,3,4,2,2,3,2,4,5,2,4,2,8,0.0,satisfied +86832,56244,Male,Loyal Customer,53,Business travel,Business,2434,1,1,1,1,3,3,3,4,4,4,5,3,3,3,0,0.0,satisfied +86833,100878,Male,Loyal Customer,40,Business travel,Business,2133,3,3,3,3,2,5,5,4,4,4,4,4,4,4,14,0.0,satisfied +86834,103186,Female,Loyal Customer,39,Business travel,Eco Plus,272,5,2,2,2,5,5,5,5,1,4,1,2,3,5,0,0.0,satisfied +86835,21232,Female,Loyal Customer,20,Personal Travel,Eco,259,3,1,3,1,2,3,2,2,1,5,1,3,1,2,0,0.0,neutral or dissatisfied +86836,127312,Female,Loyal Customer,67,Personal Travel,Eco,1979,3,5,3,3,4,3,4,2,2,3,2,2,2,2,9,15.0,neutral or dissatisfied +86837,92655,Female,Loyal Customer,53,Personal Travel,Eco,453,1,1,1,4,2,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +86838,3509,Female,Loyal Customer,13,Personal Travel,Eco,968,1,5,1,4,3,1,3,3,3,2,4,3,5,3,37,24.0,neutral or dissatisfied +86839,102735,Female,Loyal Customer,35,Personal Travel,Eco,365,3,5,3,3,1,3,1,1,4,3,5,5,5,1,8,1.0,neutral or dissatisfied +86840,1843,Male,Loyal Customer,24,Personal Travel,Eco,408,2,4,2,3,2,2,2,2,5,3,5,4,5,2,0,26.0,neutral or dissatisfied +86841,27849,Male,Loyal Customer,24,Personal Travel,Eco,1448,2,1,2,4,2,2,1,2,3,1,3,3,3,2,51,31.0,neutral or dissatisfied +86842,9795,Female,Loyal Customer,39,Business travel,Eco Plus,501,5,5,3,5,5,4,5,5,2,2,3,4,4,5,0,0.0,neutral or dissatisfied +86843,7288,Male,Loyal Customer,26,Personal Travel,Eco,139,4,5,4,2,5,4,4,5,2,1,3,1,2,5,7,0.0,neutral or dissatisfied +86844,60024,Female,Loyal Customer,63,Personal Travel,Eco,937,2,4,2,3,4,4,4,4,4,2,3,4,4,3,13,13.0,neutral or dissatisfied +86845,77285,Male,Loyal Customer,43,Business travel,Business,3538,1,1,3,1,2,4,3,4,4,4,4,1,4,3,0,0.0,satisfied +86846,51219,Female,Loyal Customer,45,Business travel,Eco Plus,193,5,1,1,1,2,4,1,5,5,5,5,2,5,5,0,0.0,satisfied +86847,95708,Male,Loyal Customer,48,Business travel,Business,2426,3,3,3,3,5,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +86848,12219,Male,Loyal Customer,50,Personal Travel,Business,190,3,5,3,3,2,4,4,2,2,3,2,3,2,3,0,6.0,neutral or dissatisfied +86849,35385,Male,Loyal Customer,61,Business travel,Eco,605,4,1,1,1,4,4,4,5,4,5,2,4,4,4,168,192.0,satisfied +86850,19989,Male,Loyal Customer,46,Business travel,Eco,589,3,3,1,3,4,3,4,4,4,4,5,1,5,4,39,48.0,satisfied +86851,56637,Male,Loyal Customer,28,Business travel,Eco,937,4,2,2,2,4,4,4,4,2,2,1,3,2,4,58,130.0,neutral or dissatisfied +86852,74149,Female,Loyal Customer,41,Business travel,Eco,641,5,3,4,3,5,5,5,5,2,1,3,1,4,5,0,0.0,satisfied +86853,66734,Female,Loyal Customer,65,Personal Travel,Eco,978,0,4,0,3,5,5,4,1,1,0,1,3,1,3,0,0.0,satisfied +86854,59857,Female,Loyal Customer,28,Business travel,Business,997,1,1,1,1,1,1,1,1,3,2,4,1,4,1,0,1.0,neutral or dissatisfied +86855,68680,Female,Loyal Customer,49,Business travel,Eco,237,4,5,5,5,1,3,1,4,4,4,4,1,4,4,84,75.0,satisfied +86856,64943,Male,Loyal Customer,25,Business travel,Eco,551,3,5,5,5,3,2,4,3,2,1,4,3,3,3,3,12.0,neutral or dissatisfied +86857,10101,Female,Loyal Customer,9,Personal Travel,Eco,961,3,4,3,3,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +86858,63681,Female,Loyal Customer,41,Personal Travel,Eco,1047,2,5,2,4,2,2,5,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +86859,73577,Female,Loyal Customer,47,Business travel,Business,3900,0,5,0,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +86860,53273,Female,Loyal Customer,38,Business travel,Business,758,3,3,3,3,1,4,5,5,5,5,5,1,5,5,20,13.0,satisfied +86861,52664,Female,Loyal Customer,66,Personal Travel,Eco,110,0,5,0,1,4,3,4,2,2,0,2,1,2,2,0,0.0,satisfied +86862,118477,Male,Loyal Customer,43,Business travel,Business,3385,5,5,5,5,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +86863,34333,Female,Loyal Customer,34,Business travel,Business,2048,2,2,2,2,2,5,3,5,5,5,5,4,5,5,0,0.0,satisfied +86864,25432,Male,disloyal Customer,28,Business travel,Eco,669,2,2,2,3,4,2,4,4,1,3,2,1,4,4,0,0.0,neutral or dissatisfied +86865,35603,Female,disloyal Customer,25,Business travel,Eco Plus,610,1,4,1,1,5,1,5,5,5,4,1,1,1,5,7,15.0,neutral or dissatisfied +86866,2903,Male,Loyal Customer,39,Personal Travel,Eco,409,2,4,2,4,2,2,2,2,3,2,2,5,4,2,0,0.0,neutral or dissatisfied +86867,41365,Female,disloyal Customer,40,Business travel,Business,913,4,4,4,2,2,4,2,2,1,4,1,3,1,2,5,12.0,neutral or dissatisfied +86868,65458,Female,Loyal Customer,49,Business travel,Business,3382,1,1,1,1,4,5,5,5,5,5,5,4,5,3,19,17.0,satisfied +86869,53603,Male,Loyal Customer,37,Business travel,Business,1874,1,1,1,1,5,5,5,5,5,5,5,4,5,3,18,4.0,satisfied +86870,115005,Female,Loyal Customer,58,Business travel,Business,325,0,0,0,5,4,5,5,1,1,1,1,5,1,5,0,0.0,satisfied +86871,123539,Female,Loyal Customer,52,Business travel,Business,1773,5,5,5,5,3,4,5,5,5,4,5,3,5,3,0,6.0,satisfied +86872,12006,Female,Loyal Customer,39,Business travel,Business,1675,5,5,5,5,3,5,5,5,5,5,5,5,5,3,42,42.0,satisfied +86873,65032,Female,Loyal Customer,41,Personal Travel,Eco,224,5,4,0,4,2,0,1,2,1,5,5,3,1,2,0,0.0,satisfied +86874,89372,Female,Loyal Customer,59,Business travel,Business,134,1,1,5,1,3,5,4,5,5,5,4,3,5,3,0,1.0,satisfied +86875,36010,Female,Loyal Customer,37,Business travel,Business,1666,3,3,3,3,2,2,3,5,5,5,5,1,5,1,26,27.0,satisfied +86876,28753,Male,disloyal Customer,24,Business travel,Eco,1024,4,4,4,3,5,4,5,5,2,2,3,1,4,5,5,6.0,neutral or dissatisfied +86877,57004,Female,Loyal Customer,66,Personal Travel,Eco,2425,3,5,3,1,3,5,5,5,4,5,4,5,3,5,13,6.0,neutral or dissatisfied +86878,102959,Female,disloyal Customer,39,Business travel,Business,719,1,1,1,5,1,1,1,1,5,5,5,4,4,1,20,23.0,neutral or dissatisfied +86879,81752,Female,Loyal Customer,34,Business travel,Business,1416,3,2,2,2,3,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +86880,35876,Female,Loyal Customer,25,Personal Travel,Eco,1065,2,2,2,4,3,2,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +86881,119185,Female,Loyal Customer,52,Business travel,Business,331,4,2,4,4,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +86882,34860,Male,disloyal Customer,25,Business travel,Eco,1393,4,4,4,1,4,4,4,4,5,5,3,4,5,4,13,0.0,satisfied +86883,22340,Female,Loyal Customer,37,Business travel,Business,3053,4,4,4,4,3,3,5,4,4,5,3,5,4,2,0,1.0,satisfied +86884,117099,Female,disloyal Customer,75,Business travel,Eco,251,4,2,3,3,2,3,2,2,1,5,4,3,3,2,18,12.0,neutral or dissatisfied +86885,16856,Female,Loyal Customer,36,Business travel,Eco,708,3,4,2,4,3,4,3,3,2,4,3,4,2,3,0,0.0,satisfied +86886,98491,Female,Loyal Customer,53,Business travel,Business,2341,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +86887,20321,Male,Loyal Customer,59,Business travel,Business,2771,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +86888,48164,Male,Loyal Customer,55,Business travel,Eco,391,5,1,1,1,4,5,4,4,4,2,2,1,5,4,0,0.0,satisfied +86889,128976,Male,Loyal Customer,38,Personal Travel,Eco,236,4,3,4,3,4,3,2,5,1,5,3,2,2,2,206,220.0,neutral or dissatisfied +86890,70215,Female,Loyal Customer,57,Business travel,Business,258,4,4,4,4,4,4,4,5,4,5,4,4,5,4,148,146.0,satisfied +86891,126490,Male,Loyal Customer,22,Personal Travel,Eco,1972,4,4,4,1,3,4,3,3,3,3,3,4,4,3,0,2.0,satisfied +86892,108086,Male,disloyal Customer,22,Business travel,Eco,1166,4,4,4,3,4,4,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +86893,50763,Female,Loyal Customer,40,Personal Travel,Eco,421,2,1,2,4,3,2,3,3,2,2,3,2,3,3,0,7.0,neutral or dissatisfied +86894,70128,Male,Loyal Customer,39,Business travel,Business,460,4,2,2,2,2,3,3,4,4,4,4,3,4,1,0,25.0,neutral or dissatisfied +86895,109053,Male,Loyal Customer,42,Business travel,Eco,849,3,3,3,3,2,3,2,2,4,4,2,3,2,2,38,31.0,neutral or dissatisfied +86896,50424,Female,disloyal Customer,24,Business travel,Business,156,0,0,0,4,4,0,1,4,4,1,5,3,4,4,0,0.0,satisfied +86897,64318,Male,Loyal Customer,53,Business travel,Business,1192,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +86898,117184,Male,Loyal Customer,49,Personal Travel,Eco,651,3,2,3,4,1,3,1,1,1,5,4,3,3,1,41,31.0,neutral or dissatisfied +86899,11366,Female,Loyal Customer,59,Personal Travel,Eco,458,1,3,1,2,5,3,2,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +86900,92602,Male,Loyal Customer,56,Business travel,Business,2158,3,1,1,1,1,3,4,3,3,3,3,3,3,2,4,0.0,neutral or dissatisfied +86901,122545,Male,Loyal Customer,55,Business travel,Business,3068,5,5,5,5,4,4,5,5,5,5,5,4,5,5,1,0.0,satisfied +86902,15588,Male,disloyal Customer,22,Business travel,Eco,288,2,1,2,3,2,3,3,3,5,3,3,3,4,3,503,484.0,neutral or dissatisfied +86903,54388,Female,Loyal Customer,76,Business travel,Business,1713,5,5,5,5,2,2,5,5,5,5,5,4,5,4,8,2.0,satisfied +86904,44002,Female,Loyal Customer,33,Business travel,Business,334,4,4,4,4,4,5,2,4,4,4,4,3,4,5,0,0.0,satisfied +86905,111592,Male,Loyal Customer,35,Personal Travel,Eco,883,4,4,4,5,4,4,5,4,1,2,1,4,3,4,12,0.0,satisfied +86906,26517,Male,Loyal Customer,30,Business travel,Business,990,5,5,1,5,4,5,4,4,4,1,1,2,4,4,0,,satisfied +86907,9241,Male,disloyal Customer,37,Business travel,Eco,177,2,3,2,3,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +86908,23894,Male,Loyal Customer,54,Business travel,Business,589,1,1,1,1,4,1,1,4,4,4,4,5,4,5,0,0.0,satisfied +86909,20056,Female,disloyal Customer,40,Business travel,Business,338,1,1,1,1,5,1,5,5,3,2,2,1,5,5,0,0.0,neutral or dissatisfied +86910,12751,Female,Loyal Customer,30,Personal Travel,Eco,689,3,5,3,3,1,3,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +86911,65705,Female,Loyal Customer,39,Business travel,Business,1722,2,2,2,2,4,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +86912,66886,Male,Loyal Customer,22,Business travel,Business,3398,3,3,3,3,4,4,4,4,4,4,4,4,5,4,12,0.0,satisfied +86913,83554,Female,Loyal Customer,44,Business travel,Business,1865,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +86914,38126,Male,Loyal Customer,42,Business travel,Eco,721,5,3,3,3,5,5,5,5,3,4,1,3,4,5,22,27.0,satisfied +86915,96140,Male,Loyal Customer,45,Personal Travel,Business,546,2,1,2,3,1,3,2,4,4,2,4,2,4,1,12,10.0,neutral or dissatisfied +86916,46848,Female,disloyal Customer,29,Business travel,Eco,737,3,3,3,1,2,3,2,2,4,3,5,4,2,2,18,13.0,neutral or dissatisfied +86917,4012,Female,Loyal Customer,50,Business travel,Business,1670,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +86918,83610,Male,disloyal Customer,22,Business travel,Eco,409,5,0,5,4,4,5,4,4,5,2,4,4,5,4,0,0.0,satisfied +86919,44335,Male,disloyal Customer,21,Business travel,Eco,230,4,4,4,2,2,4,2,2,2,1,2,5,2,2,0,0.0,neutral or dissatisfied +86920,120218,Male,Loyal Customer,9,Business travel,Business,1430,2,1,1,1,2,2,2,2,3,5,3,4,4,2,0,8.0,neutral or dissatisfied +86921,37937,Female,Loyal Customer,47,Personal Travel,Eco,937,2,4,2,5,3,5,4,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +86922,38157,Female,Loyal Customer,33,Personal Travel,Eco,1220,3,0,3,2,5,3,1,5,2,2,1,3,1,5,0,0.0,neutral or dissatisfied +86923,1833,Female,Loyal Customer,37,Personal Travel,Eco,500,4,5,5,5,5,5,5,5,4,3,4,4,5,5,16,6.0,neutral or dissatisfied +86924,53124,Female,Loyal Customer,56,Personal Travel,Eco,2065,2,5,2,2,5,4,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +86925,123996,Male,Loyal Customer,33,Business travel,Eco,184,4,3,4,3,4,4,4,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +86926,82102,Male,Loyal Customer,51,Personal Travel,Eco,1276,2,4,2,4,3,2,3,3,4,2,5,4,5,3,6,19.0,neutral or dissatisfied +86927,68842,Male,Loyal Customer,40,Business travel,Business,1061,3,3,2,3,2,5,4,5,5,4,5,5,5,4,0,9.0,satisfied +86928,105993,Female,Loyal Customer,55,Business travel,Business,1999,2,2,2,2,3,4,4,4,4,4,4,5,4,5,33,21.0,satisfied +86929,63519,Female,Loyal Customer,48,Business travel,Business,2187,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +86930,28574,Female,Loyal Customer,47,Business travel,Eco,2562,5,3,3,3,4,4,1,4,4,5,4,3,4,1,0,0.0,satisfied +86931,105837,Male,Loyal Customer,60,Personal Travel,Eco,925,3,1,3,4,3,3,3,3,2,1,3,1,4,3,3,0.0,neutral or dissatisfied +86932,62594,Female,Loyal Customer,26,Business travel,Business,1744,3,3,3,3,5,5,5,5,3,1,1,4,5,5,5,0.0,satisfied +86933,5395,Female,Loyal Customer,10,Personal Travel,Eco,812,3,5,3,4,2,3,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +86934,88768,Male,Loyal Customer,63,Business travel,Business,404,4,4,2,4,2,4,4,4,4,4,4,4,4,5,13,24.0,satisfied +86935,49732,Male,disloyal Customer,24,Business travel,Eco,373,2,0,2,1,2,2,2,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +86936,90563,Female,Loyal Customer,46,Business travel,Business,406,5,5,5,5,2,4,5,2,2,2,2,3,2,3,13,2.0,satisfied +86937,126403,Female,Loyal Customer,25,Business travel,Eco Plus,600,3,5,5,5,3,3,1,3,4,2,3,3,4,3,30,18.0,neutral or dissatisfied +86938,68241,Female,Loyal Customer,49,Business travel,Business,3626,3,2,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +86939,61929,Male,Loyal Customer,11,Personal Travel,Eco,550,3,0,3,1,2,3,2,2,5,2,4,3,5,2,29,19.0,neutral or dissatisfied +86940,117985,Male,Loyal Customer,53,Personal Travel,Eco,255,4,4,4,4,2,4,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +86941,4498,Male,disloyal Customer,38,Business travel,Business,551,4,4,4,1,2,4,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +86942,34364,Male,Loyal Customer,20,Personal Travel,Eco,427,3,2,3,3,4,3,4,4,1,4,3,1,4,4,1,19.0,neutral or dissatisfied +86943,31467,Female,Loyal Customer,50,Business travel,Business,862,2,2,2,2,3,2,3,5,5,5,5,1,5,4,0,2.0,satisfied +86944,31601,Female,Loyal Customer,13,Personal Travel,Eco,602,2,4,2,3,5,2,2,5,4,3,5,4,4,5,19,8.0,neutral or dissatisfied +86945,98978,Male,Loyal Customer,42,Personal Travel,Eco,543,3,2,3,4,5,3,4,5,1,4,4,2,3,5,12,9.0,neutral or dissatisfied +86946,34319,Female,Loyal Customer,40,Personal Travel,Eco Plus,496,3,5,3,2,2,3,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +86947,65717,Male,Loyal Customer,45,Business travel,Business,2164,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +86948,94541,Male,Loyal Customer,47,Business travel,Business,1540,0,4,0,2,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +86949,65536,Male,Loyal Customer,31,Business travel,Eco Plus,1616,2,1,1,1,2,2,2,2,4,5,2,1,3,2,3,20.0,neutral or dissatisfied +86950,5788,Male,Loyal Customer,59,Business travel,Business,273,3,3,2,3,4,4,5,5,5,5,5,3,5,3,17,47.0,satisfied +86951,17148,Male,Loyal Customer,55,Business travel,Business,926,3,1,1,1,4,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +86952,46398,Female,Loyal Customer,59,Personal Travel,Eco,1013,3,4,3,1,1,2,3,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +86953,85822,Male,Loyal Customer,18,Personal Travel,Eco,666,2,4,2,4,1,2,1,1,3,4,3,1,2,1,2,0.0,neutral or dissatisfied +86954,30349,Male,Loyal Customer,53,Business travel,Business,3471,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +86955,10339,Female,Loyal Customer,37,Business travel,Business,1519,2,2,2,2,4,5,5,2,2,2,2,4,2,4,21,5.0,satisfied +86956,22666,Female,Loyal Customer,17,Personal Travel,Business,589,5,4,5,4,4,5,4,4,3,5,3,2,3,4,0,0.0,satisfied +86957,16966,Female,disloyal Customer,34,Business travel,Eco,195,2,2,2,3,3,2,3,3,4,5,4,3,4,3,0,36.0,neutral or dissatisfied +86958,33959,Female,disloyal Customer,15,Business travel,Business,1598,5,0,5,4,3,5,5,3,3,5,5,5,5,3,61,42.0,satisfied +86959,48830,Male,Loyal Customer,7,Personal Travel,Business,209,2,2,2,3,2,2,2,2,4,2,4,1,4,2,12,10.0,neutral or dissatisfied +86960,97696,Male,Loyal Customer,47,Business travel,Business,1873,2,2,2,2,3,4,4,4,4,4,4,4,4,3,28,28.0,satisfied +86961,85364,Male,Loyal Customer,7,Personal Travel,Eco Plus,813,2,3,2,3,5,2,5,5,4,4,3,4,4,5,0,0.0,neutral or dissatisfied +86962,47357,Female,Loyal Customer,35,Business travel,Eco,599,4,2,2,2,4,5,4,4,3,5,1,5,2,4,1,0.0,satisfied +86963,10765,Female,Loyal Customer,41,Business travel,Business,3555,2,2,2,2,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +86964,72305,Male,Loyal Customer,69,Personal Travel,Eco,919,4,5,4,3,4,4,4,4,5,3,5,5,4,4,5,0.0,neutral or dissatisfied +86965,113558,Male,disloyal Customer,38,Business travel,Business,236,3,3,3,4,2,3,2,2,3,2,3,2,3,2,73,66.0,neutral or dissatisfied +86966,87006,Male,Loyal Customer,26,Personal Travel,Eco,907,1,5,2,4,4,2,4,4,4,4,4,5,4,4,1,0.0,neutral or dissatisfied +86967,43724,Female,Loyal Customer,23,Personal Travel,Eco,489,1,2,1,2,1,1,1,1,3,2,2,1,3,1,1,8.0,neutral or dissatisfied +86968,36125,Male,disloyal Customer,60,Business travel,Eco,801,4,4,4,4,4,4,4,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +86969,48508,Female,disloyal Customer,27,Business travel,Eco,844,2,2,2,2,3,2,4,3,3,3,1,2,3,3,1,3.0,neutral or dissatisfied +86970,54281,Male,Loyal Customer,23,Personal Travel,Eco Plus,1222,3,4,4,4,1,4,1,1,3,3,5,3,3,1,0,0.0,neutral or dissatisfied +86971,109206,Male,Loyal Customer,30,Business travel,Eco,612,1,4,4,4,1,1,1,1,3,5,3,2,4,1,39,44.0,neutral or dissatisfied +86972,112393,Female,disloyal Customer,27,Business travel,Business,853,4,4,4,4,1,4,3,1,3,3,5,5,5,1,1,3.0,satisfied +86973,51556,Male,Loyal Customer,39,Business travel,Business,3917,0,0,0,3,1,5,4,3,3,3,3,2,3,1,0,0.0,satisfied +86974,58392,Male,Loyal Customer,52,Business travel,Business,3164,1,1,1,1,3,5,5,5,5,5,5,4,5,4,66,52.0,satisfied +86975,111577,Female,Loyal Customer,17,Business travel,Business,3357,3,4,2,4,3,3,3,3,1,5,3,2,4,3,14,9.0,neutral or dissatisfied +86976,87242,Female,Loyal Customer,51,Business travel,Business,2409,5,5,5,5,5,4,4,4,4,4,4,3,4,3,33,26.0,satisfied +86977,93960,Female,Loyal Customer,65,Personal Travel,Eco Plus,507,3,4,4,3,5,4,5,1,1,4,1,5,1,5,44,34.0,neutral or dissatisfied +86978,7220,Male,disloyal Customer,37,Business travel,Eco,139,2,2,3,3,3,3,3,3,1,1,4,1,4,3,0,15.0,neutral or dissatisfied +86979,5858,Male,Loyal Customer,18,Personal Travel,Eco,1020,1,2,1,4,5,1,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +86980,100154,Male,Loyal Customer,58,Business travel,Business,3107,2,2,2,2,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +86981,92083,Male,Loyal Customer,58,Business travel,Business,1589,3,3,2,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +86982,96601,Male,Loyal Customer,39,Personal Travel,Business,972,1,5,1,3,4,5,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +86983,70024,Male,Loyal Customer,41,Business travel,Business,2473,4,4,4,4,2,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +86984,120761,Female,Loyal Customer,43,Business travel,Business,1888,1,1,1,1,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +86985,103110,Female,Loyal Customer,26,Personal Travel,Eco,460,3,5,3,1,2,3,2,2,2,4,3,5,3,2,0,0.0,neutral or dissatisfied +86986,22283,Male,disloyal Customer,37,Business travel,Eco,238,3,3,3,3,3,1,4,4,5,4,3,4,3,4,163,198.0,neutral or dissatisfied +86987,24355,Male,disloyal Customer,23,Business travel,Eco Plus,634,5,4,5,1,4,5,4,4,4,4,5,4,2,4,0,0.0,satisfied +86988,55541,Male,Loyal Customer,37,Business travel,Eco,550,4,2,2,2,4,4,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +86989,67654,Female,Loyal Customer,25,Business travel,Business,1431,1,1,1,1,5,4,5,5,5,4,5,4,4,5,8,2.0,satisfied +86990,43261,Female,Loyal Customer,44,Business travel,Eco,436,1,1,1,1,4,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +86991,31978,Female,Loyal Customer,43,Business travel,Business,1508,2,2,2,2,4,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +86992,82264,Female,Loyal Customer,36,Business travel,Business,1481,5,5,3,5,5,4,5,5,5,5,5,5,5,5,36,31.0,satisfied +86993,17775,Male,disloyal Customer,37,Business travel,Eco,1214,1,1,1,2,1,1,3,1,3,1,5,4,4,1,0,22.0,neutral or dissatisfied +86994,122230,Female,disloyal Customer,52,Business travel,Business,546,2,2,2,4,2,2,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +86995,13050,Male,Loyal Customer,47,Business travel,Eco Plus,374,4,4,4,4,4,4,4,4,3,5,5,5,2,4,27,19.0,satisfied +86996,102675,Male,disloyal Customer,25,Business travel,Business,255,1,0,1,3,3,1,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +86997,84968,Female,Loyal Customer,32,Personal Travel,Eco Plus,547,2,1,2,3,5,2,5,5,3,4,4,2,3,5,0,0.0,neutral or dissatisfied +86998,43457,Female,Loyal Customer,28,Business travel,Business,1595,2,3,2,2,4,4,4,4,3,3,2,4,1,4,19,5.0,satisfied +86999,73790,Female,Loyal Customer,43,Business travel,Business,204,1,1,1,1,2,4,4,3,3,4,5,4,3,4,0,0.0,satisfied +87000,54932,Male,Loyal Customer,59,Business travel,Business,1635,4,4,4,4,4,5,5,5,5,4,5,3,5,3,95,122.0,satisfied +87001,82872,Female,Loyal Customer,36,Business travel,Business,2002,3,3,3,3,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +87002,5728,Female,Loyal Customer,24,Personal Travel,Eco Plus,196,4,2,4,4,1,4,1,1,1,5,4,1,4,1,46,44.0,neutral or dissatisfied +87003,45549,Female,Loyal Customer,27,Personal Travel,Eco,566,3,4,3,4,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +87004,117075,Male,disloyal Customer,20,Business travel,Eco,647,1,4,1,4,3,1,3,3,2,1,4,2,4,3,9,0.0,neutral or dissatisfied +87005,22279,Male,Loyal Customer,46,Business travel,Eco,143,3,3,3,3,3,3,3,3,1,1,3,1,4,3,0,0.0,satisfied +87006,71520,Female,Loyal Customer,37,Business travel,Business,3409,3,2,3,3,3,5,5,4,4,4,4,5,4,4,3,0.0,satisfied +87007,105563,Female,Loyal Customer,39,Business travel,Business,577,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +87008,77715,Female,Loyal Customer,55,Business travel,Business,3997,2,3,3,3,3,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +87009,104171,Male,Loyal Customer,69,Business travel,Business,1560,2,5,1,5,5,3,4,2,2,2,2,1,2,4,15,14.0,neutral or dissatisfied +87010,59861,Male,Loyal Customer,56,Business travel,Business,2117,5,5,5,5,4,4,5,2,2,2,2,5,2,4,45,23.0,satisfied +87011,67481,Male,Loyal Customer,37,Personal Travel,Eco,641,1,4,1,4,4,1,2,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +87012,50337,Male,Loyal Customer,50,Business travel,Eco,109,4,1,1,1,4,4,4,4,2,4,1,5,4,4,0,0.0,satisfied +87013,857,Male,Loyal Customer,49,Business travel,Business,2449,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +87014,35251,Male,Loyal Customer,40,Business travel,Eco,1076,5,3,3,3,5,5,5,5,5,3,2,5,4,5,0,0.0,satisfied +87015,14412,Male,disloyal Customer,17,Business travel,Eco,693,1,1,1,3,3,1,3,3,2,4,1,2,4,3,0,0.0,neutral or dissatisfied +87016,1966,Male,Loyal Customer,36,Business travel,Eco,383,2,4,4,4,2,2,2,2,5,2,3,4,2,2,2,,satisfied +87017,102839,Female,Loyal Customer,44,Business travel,Business,2240,4,5,4,4,4,5,4,5,5,5,5,5,5,3,0,2.0,satisfied +87018,18768,Female,Loyal Customer,48,Business travel,Business,2847,1,1,1,1,2,4,4,4,4,4,4,4,4,3,0,4.0,satisfied +87019,78364,Female,Loyal Customer,27,Business travel,Business,1878,1,5,5,5,1,1,1,1,2,2,4,4,4,1,0,8.0,neutral or dissatisfied +87020,20721,Male,Loyal Customer,62,Personal Travel,Eco,707,3,2,3,3,3,3,3,2,1,2,3,3,1,3,224,205.0,neutral or dissatisfied +87021,121182,Male,Loyal Customer,57,Personal Travel,Eco,2370,1,5,1,1,1,1,1,1,4,2,5,5,4,1,93,80.0,neutral or dissatisfied +87022,119137,Female,Loyal Customer,39,Business travel,Business,3321,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +87023,107502,Female,Loyal Customer,14,Personal Travel,Eco,711,4,3,5,3,1,5,1,1,1,2,3,1,3,1,15,0.0,neutral or dissatisfied +87024,10137,Female,Loyal Customer,55,Business travel,Business,2973,3,3,3,3,3,4,5,2,2,2,2,3,2,3,33,24.0,satisfied +87025,77041,Male,Loyal Customer,57,Business travel,Business,1706,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +87026,42266,Male,Loyal Customer,51,Business travel,Eco,451,2,4,4,4,2,2,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +87027,52896,Male,Loyal Customer,39,Personal Travel,Eco,836,3,4,3,3,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +87028,67743,Male,disloyal Customer,27,Business travel,Eco,1431,2,2,2,3,2,2,2,2,2,2,3,1,3,2,18,11.0,neutral or dissatisfied +87029,64100,Female,Loyal Customer,12,Personal Travel,Eco,919,4,5,4,3,3,4,3,3,4,5,4,4,4,3,0,10.0,neutral or dissatisfied +87030,45238,Female,Loyal Customer,34,Personal Travel,Eco,1013,3,3,3,2,1,3,1,1,2,3,3,2,3,1,71,,neutral or dissatisfied +87031,106207,Male,Loyal Customer,24,Personal Travel,Eco Plus,302,3,4,3,1,2,3,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +87032,116550,Female,Loyal Customer,32,Personal Travel,Eco,480,1,3,1,4,1,1,1,1,2,3,3,1,3,1,1,0.0,neutral or dissatisfied +87033,93741,Male,Loyal Customer,57,Business travel,Business,368,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +87034,120577,Female,Loyal Customer,43,Business travel,Business,2176,2,2,2,2,3,4,4,4,4,4,4,5,4,5,7,6.0,satisfied +87035,47268,Female,disloyal Customer,25,Business travel,Eco,588,3,0,3,3,2,3,3,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +87036,42268,Male,Loyal Customer,42,Business travel,Business,784,3,3,3,3,1,4,3,4,4,4,4,1,4,2,0,0.0,satisfied +87037,64817,Male,Loyal Customer,37,Business travel,Business,2547,3,3,3,3,2,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +87038,109481,Female,disloyal Customer,38,Business travel,Eco,920,2,2,2,4,3,2,2,3,4,2,4,1,3,3,0,2.0,neutral or dissatisfied +87039,83039,Male,Loyal Customer,52,Business travel,Eco,983,1,1,1,1,1,1,1,1,2,4,4,3,3,1,0,7.0,neutral or dissatisfied +87040,92703,Female,Loyal Customer,67,Personal Travel,Eco Plus,507,3,5,3,2,2,5,4,2,2,3,2,3,2,3,63,51.0,neutral or dissatisfied +87041,14266,Male,disloyal Customer,20,Business travel,Eco,429,5,4,5,2,1,5,1,1,2,1,3,5,3,1,0,0.0,satisfied +87042,63431,Male,Loyal Customer,19,Personal Travel,Eco,447,4,5,4,4,5,4,4,5,4,3,4,3,5,5,0,0.0,satisfied +87043,97930,Female,Loyal Customer,48,Business travel,Business,3605,5,5,5,5,3,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +87044,56518,Female,disloyal Customer,25,Business travel,Business,1023,1,4,1,2,1,1,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +87045,106441,Male,Loyal Customer,43,Business travel,Business,1840,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +87046,26540,Male,Loyal Customer,62,Personal Travel,Eco,990,2,5,1,3,3,1,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +87047,28301,Female,Loyal Customer,50,Business travel,Business,3832,2,2,2,2,2,2,4,5,5,5,5,3,5,1,4,0.0,satisfied +87048,83473,Female,Loyal Customer,53,Business travel,Business,1992,2,2,2,2,4,5,5,4,4,4,4,3,4,3,56,59.0,satisfied +87049,126256,Male,Loyal Customer,23,Business travel,Eco,468,0,5,0,3,5,0,5,5,5,5,4,1,1,5,0,0.0,satisfied +87050,112784,Female,Loyal Customer,72,Business travel,Eco Plus,588,2,1,1,1,1,3,4,2,2,2,2,2,2,2,49,47.0,neutral or dissatisfied +87051,114051,Male,Loyal Customer,11,Personal Travel,Business,2139,3,4,3,1,3,3,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +87052,4893,Male,Loyal Customer,19,Personal Travel,Eco Plus,500,3,4,5,3,3,5,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +87053,101148,Male,Loyal Customer,26,Business travel,Business,3194,3,4,4,4,3,3,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +87054,20795,Male,disloyal Customer,24,Business travel,Eco,508,3,0,3,5,5,3,4,5,4,5,1,3,4,5,0,0.0,neutral or dissatisfied +87055,77224,Male,disloyal Customer,30,Business travel,Business,1590,4,4,4,5,2,4,3,2,5,4,4,3,4,2,0,0.0,satisfied +87056,36279,Male,Loyal Customer,45,Business travel,Eco Plus,612,5,3,2,3,5,5,5,5,3,1,5,2,2,5,0,0.0,satisfied +87057,92239,Female,Loyal Customer,13,Personal Travel,Business,1670,4,5,4,4,2,4,2,2,5,3,4,5,4,2,33,25.0,neutral or dissatisfied +87058,89116,Female,Loyal Customer,50,Business travel,Business,2092,3,3,3,3,5,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +87059,124137,Female,Loyal Customer,29,Personal Travel,Eco,529,3,3,3,3,5,3,5,5,4,2,3,1,3,5,0,0.0,neutral or dissatisfied +87060,21545,Male,Loyal Customer,51,Personal Travel,Eco,331,3,4,3,4,2,3,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +87061,8634,Male,Loyal Customer,58,Business travel,Business,280,0,0,0,1,2,4,4,2,2,4,4,5,2,4,13,23.0,satisfied +87062,116495,Female,Loyal Customer,50,Personal Travel,Eco,371,1,4,1,3,1,3,3,3,2,4,4,3,3,3,218,217.0,neutral or dissatisfied +87063,81887,Female,Loyal Customer,46,Business travel,Business,3399,3,3,3,3,5,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +87064,13115,Female,Loyal Customer,31,Business travel,Eco,562,3,5,2,5,3,3,3,3,1,1,3,4,3,3,26,18.0,neutral or dissatisfied +87065,109125,Female,Loyal Customer,42,Business travel,Business,793,1,1,1,1,2,5,5,4,4,4,4,3,4,4,6,0.0,satisfied +87066,117669,Female,Loyal Customer,15,Personal Travel,Eco,1449,4,4,3,2,3,3,3,3,2,5,3,3,4,3,137,112.0,neutral or dissatisfied +87067,60500,Male,Loyal Customer,63,Business travel,Eco,241,1,5,5,5,1,1,1,1,1,2,4,3,3,1,0,0.0,neutral or dissatisfied +87068,21910,Male,disloyal Customer,26,Business travel,Eco,448,4,0,4,3,3,4,1,3,4,2,2,3,3,3,0,0.0,satisfied +87069,9926,Male,Loyal Customer,40,Business travel,Eco,508,2,5,5,5,2,2,2,2,1,5,3,2,2,2,18,11.0,neutral or dissatisfied +87070,93294,Male,Loyal Customer,25,Business travel,Eco Plus,806,2,2,2,2,2,1,2,4,5,3,3,2,2,2,135,145.0,neutral or dissatisfied +87071,75054,Female,Loyal Customer,58,Personal Travel,Eco,1592,1,4,1,5,3,5,5,2,2,1,2,3,2,4,66,74.0,neutral or dissatisfied +87072,123410,Male,Loyal Customer,29,Business travel,Eco,1337,2,1,1,1,2,2,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +87073,44217,Male,Loyal Customer,52,Business travel,Business,2708,2,2,2,2,1,3,1,4,4,3,4,3,4,2,4,14.0,satisfied +87074,105118,Female,Loyal Customer,35,Business travel,Eco,289,3,2,4,2,3,3,3,3,1,5,3,2,3,3,23,23.0,neutral or dissatisfied +87075,50029,Female,Loyal Customer,42,Business travel,Eco,308,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +87076,50587,Male,Loyal Customer,33,Personal Travel,Eco,109,2,3,2,4,1,2,1,1,1,5,4,1,3,1,0,0.0,neutral or dissatisfied +87077,2296,Female,Loyal Customer,59,Business travel,Eco,691,3,2,2,2,2,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +87078,34772,Male,disloyal Customer,23,Business travel,Eco,264,3,4,3,3,1,3,1,1,1,5,4,4,4,1,20,55.0,neutral or dissatisfied +87079,6643,Female,Loyal Customer,52,Business travel,Eco,416,4,2,2,2,3,2,3,4,4,4,4,3,4,4,0,13.0,neutral or dissatisfied +87080,86849,Male,Loyal Customer,12,Personal Travel,Eco,692,1,4,1,4,5,1,5,5,2,5,4,4,4,5,0,0.0,neutral or dissatisfied +87081,88091,Male,Loyal Customer,49,Business travel,Business,250,0,0,0,3,3,4,4,4,4,4,4,3,4,4,45,39.0,satisfied +87082,110409,Female,Loyal Customer,15,Business travel,Business,2871,2,2,2,2,5,5,5,5,5,3,5,3,4,5,0,0.0,satisfied +87083,8460,Female,Loyal Customer,41,Business travel,Eco,979,4,2,2,2,4,4,4,4,3,2,1,2,1,4,25,4.0,satisfied +87084,47270,Female,Loyal Customer,61,Business travel,Business,1686,3,3,3,3,4,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +87085,22730,Female,Loyal Customer,34,Business travel,Business,3657,1,1,5,1,5,2,1,5,5,5,5,1,5,2,110,111.0,satisfied +87086,29296,Female,disloyal Customer,24,Business travel,Eco,150,2,0,2,3,3,2,2,3,3,5,1,3,2,3,0,0.0,neutral or dissatisfied +87087,80055,Male,Loyal Customer,7,Personal Travel,Eco,1069,4,4,4,3,3,4,5,3,5,5,5,3,4,3,9,52.0,neutral or dissatisfied +87088,84579,Male,Loyal Customer,60,Personal Travel,Eco,1572,4,4,4,1,2,4,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +87089,36582,Male,Loyal Customer,66,Business travel,Eco,1121,2,2,2,2,2,2,2,2,1,5,4,4,3,2,41,38.0,neutral or dissatisfied +87090,90346,Female,Loyal Customer,41,Business travel,Business,594,4,4,4,4,5,5,5,4,5,5,5,5,3,5,166,165.0,satisfied +87091,41177,Male,Loyal Customer,69,Personal Travel,Eco,468,3,2,3,3,3,3,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +87092,117620,Female,Loyal Customer,18,Business travel,Business,3869,3,5,5,5,3,3,3,3,1,3,3,2,3,3,28,9.0,neutral or dissatisfied +87093,25087,Male,Loyal Customer,41,Business travel,Eco,549,1,5,5,5,1,1,1,1,2,4,2,4,2,1,0,13.0,neutral or dissatisfied +87094,96937,Male,Loyal Customer,50,Business travel,Business,794,1,1,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +87095,124653,Male,Loyal Customer,21,Personal Travel,Business,399,2,5,2,5,4,2,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +87096,104914,Female,disloyal Customer,29,Business travel,Business,210,3,2,2,4,5,2,5,5,5,3,5,4,4,5,21,25.0,neutral or dissatisfied +87097,86215,Male,Loyal Customer,54,Business travel,Business,2086,0,0,0,3,3,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +87098,11783,Female,Loyal Customer,61,Personal Travel,Eco,395,2,4,2,1,1,5,2,1,1,2,1,2,1,3,80,96.0,neutral or dissatisfied +87099,93937,Male,Loyal Customer,44,Business travel,Business,1998,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +87100,38212,Female,Loyal Customer,45,Business travel,Eco Plus,1237,3,4,4,4,5,5,4,4,4,3,4,1,4,3,49,43.0,satisfied +87101,11472,Female,Loyal Customer,39,Business travel,Eco Plus,316,2,1,1,1,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +87102,54956,Female,Loyal Customer,53,Business travel,Business,1379,3,2,3,3,5,5,5,4,4,4,4,5,4,3,0,8.0,satisfied +87103,91090,Female,Loyal Customer,62,Personal Travel,Eco,545,2,5,2,5,2,5,5,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +87104,13473,Female,Loyal Customer,60,Business travel,Eco Plus,409,4,2,2,2,4,5,5,4,4,4,4,1,4,5,0,0.0,satisfied +87105,21146,Male,Loyal Customer,29,Personal Travel,Eco Plus,106,2,4,2,2,4,2,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +87106,14339,Male,Loyal Customer,40,Personal Travel,Eco,429,3,4,3,3,3,3,3,3,3,3,1,1,3,3,29,22.0,neutral or dissatisfied +87107,81564,Female,Loyal Customer,36,Business travel,Business,2689,5,5,5,5,4,1,5,4,4,4,4,3,4,3,0,0.0,satisfied +87108,19365,Male,Loyal Customer,63,Business travel,Business,3954,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +87109,94086,Male,Loyal Customer,52,Business travel,Business,2535,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,4.0,satisfied +87110,26171,Male,Loyal Customer,58,Business travel,Eco,515,1,1,1,1,1,1,1,1,1,1,3,1,4,1,0,0.0,neutral or dissatisfied +87111,49186,Female,Loyal Customer,51,Business travel,Business,109,3,3,3,3,2,3,4,4,4,4,5,4,4,4,0,0.0,satisfied +87112,109314,Female,disloyal Customer,31,Business travel,Eco,1136,1,1,1,3,3,1,3,3,2,5,3,1,3,3,35,32.0,neutral or dissatisfied +87113,126325,Female,Loyal Customer,14,Personal Travel,Eco,650,1,4,1,4,2,1,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +87114,26531,Male,disloyal Customer,23,Business travel,Eco,990,3,3,3,3,2,3,1,2,2,2,4,1,3,2,32,28.0,neutral or dissatisfied +87115,61921,Female,disloyal Customer,26,Business travel,Eco,550,2,0,2,2,4,2,4,4,2,5,3,3,4,4,0,0.0,neutral or dissatisfied +87116,39440,Female,Loyal Customer,41,Business travel,Eco,129,4,4,5,5,4,4,4,4,4,5,3,5,1,4,0,5.0,satisfied +87117,69956,Female,Loyal Customer,8,Personal Travel,Eco,2174,4,5,4,4,2,4,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +87118,121516,Female,Loyal Customer,43,Business travel,Business,912,2,2,2,2,4,4,5,5,5,5,5,4,5,4,0,4.0,satisfied +87119,3601,Male,Loyal Customer,68,Business travel,Business,1976,4,1,4,4,5,1,3,4,4,4,4,5,4,1,0,0.0,satisfied +87120,11827,Female,disloyal Customer,18,Business travel,Eco,986,3,3,3,4,4,3,4,4,4,5,3,2,4,4,0,0.0,neutral or dissatisfied +87121,104475,Female,Loyal Customer,39,Business travel,Business,1671,1,1,1,1,3,5,4,4,4,4,4,5,4,3,63,112.0,satisfied +87122,111737,Female,disloyal Customer,48,Business travel,Business,1224,1,1,1,2,2,1,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +87123,58239,Female,Loyal Customer,52,Business travel,Business,3058,1,1,1,1,5,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +87124,122030,Male,disloyal Customer,29,Business travel,Business,130,0,0,0,1,1,0,1,1,3,2,5,4,5,1,0,0.0,satisfied +87125,15751,Female,Loyal Customer,37,Business travel,Eco,461,1,3,3,3,1,1,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +87126,52334,Female,Loyal Customer,31,Business travel,Business,451,5,5,5,5,3,3,3,3,3,2,4,3,1,3,0,0.0,satisfied +87127,90527,Female,Loyal Customer,60,Business travel,Business,3840,5,5,5,5,4,5,5,5,5,5,5,3,5,3,6,30.0,satisfied +87128,105959,Male,Loyal Customer,46,Business travel,Business,2295,5,5,5,5,5,5,5,3,3,4,4,5,4,5,29,24.0,satisfied +87129,8580,Female,Loyal Customer,37,Business travel,Eco,109,4,1,1,1,4,4,4,4,4,3,5,5,1,4,0,0.0,satisfied +87130,123693,Male,Loyal Customer,9,Personal Travel,Eco,214,3,0,0,3,1,0,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +87131,60527,Female,Loyal Customer,58,Personal Travel,Eco,775,1,3,1,3,3,3,1,5,5,1,5,5,5,3,56,43.0,neutral or dissatisfied +87132,32825,Female,Loyal Customer,34,Business travel,Business,2826,3,5,4,4,2,3,4,1,1,1,3,4,1,1,21,19.0,neutral or dissatisfied +87133,49821,Male,Loyal Customer,40,Business travel,Eco,421,4,4,4,4,4,4,4,4,4,1,3,4,3,4,0,6.0,satisfied +87134,92779,Female,Loyal Customer,43,Business travel,Business,1671,3,3,3,3,2,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +87135,21923,Female,disloyal Customer,22,Business travel,Eco,503,4,3,4,2,5,4,5,5,3,2,5,2,4,5,0,0.0,neutral or dissatisfied +87136,48351,Male,Loyal Customer,23,Business travel,Business,2550,2,2,2,2,4,4,4,4,4,3,4,4,4,4,0,0.0,satisfied +87137,37033,Female,Loyal Customer,55,Business travel,Business,2064,3,3,3,3,5,4,4,3,3,3,3,4,3,3,32,18.0,satisfied +87138,108986,Female,Loyal Customer,53,Business travel,Business,957,1,1,5,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +87139,17312,Female,Loyal Customer,57,Business travel,Business,2438,4,2,2,2,3,4,4,4,4,4,4,3,4,4,93,118.0,neutral or dissatisfied +87140,45397,Male,Loyal Customer,40,Business travel,Business,649,5,5,5,5,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +87141,114444,Female,Loyal Customer,40,Business travel,Business,1661,5,5,5,5,4,5,5,4,4,5,4,3,4,4,9,3.0,satisfied +87142,72273,Male,Loyal Customer,25,Business travel,Business,2551,2,5,5,5,2,2,2,2,1,5,3,4,4,2,12,6.0,neutral or dissatisfied +87143,94875,Female,disloyal Customer,22,Business travel,Eco,248,3,5,2,1,3,2,3,3,5,2,5,5,4,3,14,1.0,neutral or dissatisfied +87144,27343,Female,Loyal Customer,31,Business travel,Business,1050,3,3,3,3,4,4,4,4,4,4,1,4,1,4,0,0.0,satisfied +87145,66581,Male,disloyal Customer,36,Business travel,Business,761,2,1,1,4,4,1,4,4,4,4,5,5,5,4,0,1.0,neutral or dissatisfied +87146,5015,Female,Loyal Customer,49,Personal Travel,Eco Plus,502,4,2,4,4,3,3,3,4,4,4,4,3,4,4,0,15.0,neutral or dissatisfied +87147,90092,Female,Loyal Customer,33,Business travel,Business,1127,1,1,1,1,5,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +87148,8973,Female,disloyal Customer,25,Business travel,Business,799,4,0,4,3,2,4,4,2,3,3,5,3,5,2,3,2.0,satisfied +87149,3759,Female,Loyal Customer,57,Personal Travel,Eco Plus,431,3,4,3,2,2,2,5,2,2,3,2,2,2,1,3,0.0,neutral or dissatisfied +87150,2605,Female,Loyal Customer,28,Personal Travel,Eco,181,3,4,3,2,3,3,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +87151,40784,Male,Loyal Customer,36,Business travel,Eco,501,3,4,4,4,3,3,3,3,1,5,4,4,3,3,0,0.0,neutral or dissatisfied +87152,6428,Female,Loyal Customer,60,Personal Travel,Eco,296,3,5,3,4,3,4,4,3,3,3,3,4,3,3,5,34.0,neutral or dissatisfied +87153,74752,Male,Loyal Customer,43,Personal Travel,Eco,1235,1,4,1,4,1,3,3,3,2,4,4,3,3,3,186,172.0,neutral or dissatisfied +87154,10345,Male,Loyal Customer,47,Business travel,Business,1631,2,2,2,2,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +87155,92196,Female,Loyal Customer,67,Business travel,Business,1979,1,2,2,2,4,4,4,1,1,1,1,1,1,3,21,0.0,neutral or dissatisfied +87156,71396,Female,disloyal Customer,25,Business travel,Business,334,4,3,4,4,5,4,5,5,5,3,5,4,5,5,7,0.0,satisfied +87157,103529,Male,Loyal Customer,42,Business travel,Business,3576,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +87158,118811,Female,Loyal Customer,26,Personal Travel,Eco,646,1,3,1,2,5,1,5,5,1,4,1,3,4,5,1,0.0,neutral or dissatisfied +87159,50184,Male,Loyal Customer,55,Business travel,Business,109,0,4,0,4,5,1,3,3,3,3,3,2,3,1,0,0.0,satisfied +87160,97739,Female,disloyal Customer,29,Business travel,Eco,587,3,2,3,3,1,3,1,1,3,4,2,2,2,1,0,0.0,neutral or dissatisfied +87161,109548,Male,Loyal Customer,52,Personal Travel,Eco,993,1,4,2,4,5,2,4,5,4,2,4,3,5,5,62,83.0,neutral or dissatisfied +87162,1568,Female,Loyal Customer,46,Business travel,Business,2699,3,3,3,3,2,5,5,5,5,5,5,4,5,3,0,12.0,satisfied +87163,37851,Female,Loyal Customer,50,Business travel,Eco,1065,4,5,5,5,4,4,4,3,5,3,4,4,1,4,214,194.0,neutral or dissatisfied +87164,35373,Male,Loyal Customer,39,Business travel,Business,1028,2,5,1,1,5,2,3,2,2,2,2,4,2,4,2,6.0,neutral or dissatisfied +87165,108889,Female,Loyal Customer,58,Business travel,Business,2610,3,3,3,3,5,4,5,5,5,5,5,4,5,3,38,35.0,satisfied +87166,89146,Female,Loyal Customer,38,Business travel,Business,1983,1,5,5,5,1,4,3,1,1,1,1,4,1,3,5,13.0,neutral or dissatisfied +87167,1191,Male,Loyal Customer,14,Personal Travel,Eco,354,2,5,5,1,1,5,4,1,3,4,4,4,5,1,0,13.0,neutral or dissatisfied +87168,39487,Female,Loyal Customer,33,Personal Travel,Eco,867,1,4,1,4,1,1,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +87169,38939,Male,Loyal Customer,61,Personal Travel,Eco,205,4,1,4,2,3,4,3,3,2,1,2,3,3,3,3,11.0,neutral or dissatisfied +87170,91899,Male,Loyal Customer,52,Business travel,Business,2446,1,1,1,1,2,3,4,3,3,2,3,4,3,5,0,0.0,satisfied +87171,30038,Male,Loyal Customer,38,Business travel,Business,261,3,3,3,3,1,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +87172,64413,Male,Loyal Customer,32,Personal Travel,Eco Plus,1192,2,4,2,3,4,2,4,4,3,5,4,3,4,4,0,2.0,neutral or dissatisfied +87173,21056,Female,Loyal Customer,30,Business travel,Eco,227,0,0,0,4,2,0,3,2,3,2,2,1,3,2,0,0.0,satisfied +87174,99956,Female,Loyal Customer,50,Business travel,Eco Plus,2237,2,5,5,5,2,2,2,2,5,4,4,2,2,2,0,7.0,neutral or dissatisfied +87175,53519,Female,Loyal Customer,49,Personal Travel,Eco,2288,2,4,3,4,3,4,4,1,1,4,4,4,3,4,0,52.0,neutral or dissatisfied +87176,59518,Male,Loyal Customer,21,Personal Travel,Business,854,3,5,3,5,4,3,4,4,4,4,5,4,5,4,3,0.0,neutral or dissatisfied +87177,2762,Female,Loyal Customer,32,Personal Travel,Eco Plus,695,3,5,3,1,3,3,3,3,5,3,4,4,4,3,0,6.0,neutral or dissatisfied +87178,114778,Male,disloyal Customer,41,Business travel,Business,390,1,2,2,1,1,2,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +87179,28015,Female,Loyal Customer,66,Business travel,Business,2856,1,3,4,4,2,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +87180,23743,Male,Loyal Customer,41,Business travel,Business,683,2,2,2,2,5,5,5,4,4,4,4,3,4,5,15,0.0,satisfied +87181,121280,Male,Loyal Customer,16,Business travel,Eco Plus,2075,4,3,3,3,4,3,4,4,2,4,4,4,3,4,264,256.0,neutral or dissatisfied +87182,75322,Female,Loyal Customer,43,Business travel,Business,2615,2,2,3,2,4,4,4,5,3,3,4,4,4,4,0,0.0,satisfied +87183,34082,Female,Loyal Customer,62,Personal Travel,Eco Plus,1674,1,4,1,3,1,3,5,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +87184,127178,Male,Loyal Customer,42,Personal Travel,Eco,304,1,4,1,1,3,1,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +87185,104515,Male,disloyal Customer,28,Business travel,Eco,942,2,1,1,3,5,1,5,5,2,2,4,4,3,5,35,28.0,neutral or dissatisfied +87186,26660,Male,Loyal Customer,43,Business travel,Eco,115,4,5,2,5,4,4,4,4,2,3,3,4,3,4,0,0.0,satisfied +87187,114236,Female,disloyal Customer,26,Business travel,Eco,957,2,2,2,4,2,2,2,2,4,5,3,3,4,2,4,34.0,neutral or dissatisfied +87188,85406,Male,Loyal Customer,43,Business travel,Business,332,1,1,1,1,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +87189,118862,Female,Loyal Customer,51,Personal Travel,Eco Plus,338,1,4,1,5,4,3,2,1,1,1,4,3,1,1,5,0.0,neutral or dissatisfied +87190,10231,Male,Loyal Customer,30,Business travel,Business,429,2,1,1,1,2,2,2,2,2,1,3,4,3,2,24,20.0,neutral or dissatisfied +87191,110353,Male,Loyal Customer,35,Business travel,Business,3136,1,1,1,1,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +87192,29745,Male,Loyal Customer,26,Business travel,Business,1666,4,4,4,4,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +87193,93559,Female,Loyal Customer,52,Personal Travel,Eco,719,1,4,1,3,2,5,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +87194,33599,Male,Loyal Customer,23,Business travel,Business,413,3,5,4,4,3,3,3,3,3,5,4,1,3,3,7,23.0,neutral or dissatisfied +87195,46188,Male,disloyal Customer,23,Business travel,Eco,472,5,3,5,1,1,5,1,1,1,4,4,1,3,1,0,0.0,satisfied +87196,85370,Female,Loyal Customer,49,Business travel,Business,2219,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +87197,10338,Female,disloyal Customer,27,Business travel,Business,517,2,2,2,3,3,2,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +87198,41280,Female,disloyal Customer,26,Business travel,Eco,871,4,5,5,2,1,5,1,1,5,3,3,5,3,1,0,0.0,neutral or dissatisfied +87199,17076,Male,disloyal Customer,66,Business travel,Business,416,1,1,1,3,1,4,1,2,3,3,4,1,4,1,149,138.0,neutral or dissatisfied +87200,105168,Male,Loyal Customer,64,Personal Travel,Eco,289,3,3,3,4,1,3,1,1,1,2,3,1,3,1,0,10.0,neutral or dissatisfied +87201,126850,Male,Loyal Customer,63,Business travel,Eco,577,3,3,2,2,3,3,3,3,3,2,4,1,2,3,7,0.0,satisfied +87202,96115,Female,disloyal Customer,26,Business travel,Business,1090,5,5,5,2,5,5,5,5,4,4,5,4,5,5,8,3.0,satisfied +87203,81802,Male,Loyal Customer,42,Business travel,Business,1416,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +87204,66709,Male,Loyal Customer,40,Business travel,Business,2366,2,3,3,3,1,3,3,2,2,2,2,2,2,4,17,6.0,neutral or dissatisfied +87205,121343,Male,disloyal Customer,38,Business travel,Eco,430,1,2,1,4,1,1,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +87206,58856,Male,Loyal Customer,65,Personal Travel,Business,888,3,4,3,1,4,4,5,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +87207,27652,Male,Loyal Customer,68,Business travel,Eco Plus,279,5,2,2,2,4,5,4,4,5,4,3,5,2,4,24,28.0,satisfied +87208,39730,Female,disloyal Customer,36,Business travel,Eco,298,4,2,4,4,3,4,3,3,4,3,3,1,3,3,0,0.0,neutral or dissatisfied +87209,54456,Female,Loyal Customer,29,Business travel,Business,2663,1,0,0,4,0,3,3,1,2,3,3,3,2,3,162,162.0,neutral or dissatisfied +87210,45432,Female,disloyal Customer,29,Business travel,Eco,649,2,4,2,1,5,2,5,5,3,4,4,3,1,5,0,0.0,neutral or dissatisfied +87211,23822,Female,Loyal Customer,34,Personal Travel,Eco,304,3,5,3,2,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +87212,53326,Female,Loyal Customer,63,Personal Travel,Eco,811,1,2,1,3,1,4,3,5,5,1,5,2,5,1,12,1.0,neutral or dissatisfied +87213,107216,Female,Loyal Customer,17,Business travel,Eco Plus,402,3,5,5,5,3,3,3,3,2,3,3,2,3,3,17,13.0,neutral or dissatisfied +87214,73971,Female,Loyal Customer,29,Personal Travel,Eco,2218,5,2,5,3,1,5,1,1,1,4,3,4,3,1,21,0.0,satisfied +87215,90457,Male,Loyal Customer,28,Business travel,Business,515,1,1,1,1,3,4,3,3,5,4,4,3,5,3,0,5.0,satisfied +87216,71438,Female,Loyal Customer,24,Business travel,Business,867,5,5,3,5,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +87217,45536,Male,Loyal Customer,47,Business travel,Eco,508,3,4,3,3,3,3,3,3,3,3,3,1,3,3,0,2.0,satisfied +87218,103496,Male,Loyal Customer,26,Personal Travel,Eco Plus,382,3,5,3,3,2,3,2,2,5,4,5,4,4,2,1,0.0,neutral or dissatisfied +87219,85472,Female,Loyal Customer,24,Business travel,Eco,332,5,4,2,2,5,5,4,5,4,5,5,2,2,5,0,0.0,satisfied +87220,68520,Male,Loyal Customer,40,Business travel,Business,678,2,2,2,2,3,4,4,4,4,4,4,3,4,5,0,11.0,satisfied +87221,129852,Male,Loyal Customer,43,Personal Travel,Eco,337,3,5,3,4,2,3,2,2,4,2,2,5,3,2,0,0.0,neutral or dissatisfied +87222,54226,Male,Loyal Customer,38,Business travel,Business,3208,3,4,3,3,2,2,5,3,3,3,3,1,3,1,7,18.0,satisfied +87223,72596,Male,Loyal Customer,39,Personal Travel,Eco,985,4,4,4,3,3,4,3,3,4,3,5,3,5,3,0,18.0,satisfied +87224,28216,Male,Loyal Customer,57,Business travel,Eco Plus,933,5,5,5,5,5,5,5,5,3,5,4,5,1,5,5,0.0,satisfied +87225,110208,Male,Loyal Customer,40,Personal Travel,Eco,588,2,5,2,5,4,2,4,4,5,2,5,3,5,4,27,15.0,neutral or dissatisfied +87226,16034,Male,Loyal Customer,26,Personal Travel,Eco,780,3,5,3,4,5,3,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +87227,103147,Male,Loyal Customer,52,Business travel,Business,272,0,0,0,2,2,4,5,3,3,3,3,3,3,4,12,0.0,satisfied +87228,33094,Male,Loyal Customer,52,Personal Travel,Eco,102,1,4,1,2,2,1,2,2,2,1,2,4,5,2,0,0.0,neutral or dissatisfied +87229,80879,Female,Loyal Customer,55,Business travel,Business,3990,3,3,3,3,4,4,4,3,3,3,3,3,3,5,20,37.0,satisfied +87230,53899,Male,Loyal Customer,54,Personal Travel,Eco,140,2,5,2,2,1,2,1,1,4,3,2,2,5,1,0,1.0,neutral or dissatisfied +87231,124599,Female,Loyal Customer,54,Personal Travel,Eco,500,3,4,3,3,3,4,5,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +87232,108658,Male,Loyal Customer,45,Personal Travel,Eco,1747,4,4,4,3,5,4,5,5,3,2,4,2,3,5,127,123.0,satisfied +87233,13500,Female,Loyal Customer,62,Business travel,Eco,106,5,3,3,3,1,4,3,5,5,5,5,3,5,2,0,0.0,satisfied +87234,119471,Female,Loyal Customer,44,Business travel,Business,3618,2,2,2,2,2,5,5,4,4,4,4,5,4,3,0,7.0,satisfied +87235,94689,Female,Loyal Customer,65,Business travel,Business,293,2,1,1,1,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +87236,63888,Male,Loyal Customer,28,Business travel,Eco,1158,3,1,1,1,3,3,3,3,2,3,4,1,4,3,0,28.0,neutral or dissatisfied +87237,52872,Male,disloyal Customer,22,Business travel,Eco,1024,5,5,5,3,4,5,4,4,4,3,3,3,1,4,4,0.0,satisfied +87238,54309,Female,Loyal Customer,10,Business travel,Business,1597,1,1,1,1,4,4,4,4,5,4,5,5,4,4,0,0.0,satisfied +87239,106514,Male,Loyal Customer,53,Business travel,Business,271,0,1,1,2,3,5,5,4,4,4,5,3,4,4,12,5.0,satisfied +87240,41081,Female,Loyal Customer,57,Business travel,Eco,140,4,3,3,3,5,1,5,4,4,4,4,2,4,4,0,0.0,satisfied +87241,53238,Male,Loyal Customer,30,Personal Travel,Eco,612,3,1,3,2,5,3,5,5,3,1,2,1,3,5,0,9.0,neutral or dissatisfied +87242,115309,Male,disloyal Customer,33,Business travel,Business,325,3,3,3,5,5,3,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +87243,32639,Female,Loyal Customer,53,Business travel,Business,163,3,4,4,4,1,3,4,1,1,1,3,2,1,4,0,6.0,neutral or dissatisfied +87244,97887,Male,Loyal Customer,44,Business travel,Business,3201,1,1,1,1,2,5,4,3,3,4,3,5,3,3,39,31.0,satisfied +87245,23312,Male,Loyal Customer,35,Business travel,Business,2202,5,5,5,5,2,2,4,3,3,3,3,4,3,4,0,1.0,satisfied +87246,2314,Male,Loyal Customer,43,Personal Travel,Eco,690,1,4,2,5,4,2,4,4,4,2,5,4,4,4,46,32.0,neutral or dissatisfied +87247,64089,Male,Loyal Customer,54,Personal Travel,Eco,919,0,5,0,1,4,5,4,4,4,4,4,4,5,4,0,3.0,satisfied +87248,36226,Female,Loyal Customer,68,Personal Travel,Eco,280,4,5,4,4,5,5,5,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +87249,28784,Female,Loyal Customer,30,Business travel,Business,2612,1,5,5,5,1,1,1,1,2,5,4,2,4,1,0,6.0,neutral or dissatisfied +87250,62312,Male,Loyal Customer,31,Business travel,Business,414,2,4,4,4,2,2,2,2,3,2,2,1,3,2,37,24.0,neutral or dissatisfied +87251,11305,Male,Loyal Customer,9,Personal Travel,Eco,166,2,4,0,5,2,0,4,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +87252,121048,Male,Loyal Customer,8,Personal Travel,Eco,993,2,3,2,4,2,2,2,2,4,5,3,3,4,2,0,5.0,neutral or dissatisfied +87253,51431,Male,Loyal Customer,32,Personal Travel,Eco Plus,77,2,4,2,5,4,2,5,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +87254,110894,Male,Loyal Customer,48,Business travel,Eco,545,4,3,1,3,4,4,4,4,3,5,4,3,4,4,33,30.0,neutral or dissatisfied +87255,44983,Female,Loyal Customer,47,Business travel,Eco,222,5,1,1,1,5,1,2,5,5,5,5,5,5,4,0,0.0,satisfied +87256,33176,Female,Loyal Customer,41,Personal Travel,Eco,101,4,4,4,3,5,4,5,5,2,2,5,4,4,5,0,2.0,neutral or dissatisfied +87257,120431,Male,Loyal Customer,40,Business travel,Business,449,1,3,3,3,2,3,4,1,1,1,1,3,1,3,50,49.0,neutral or dissatisfied +87258,36209,Male,disloyal Customer,37,Business travel,Business,280,2,2,2,3,2,4,4,2,1,3,3,4,1,4,79,161.0,neutral or dissatisfied +87259,15520,Female,Loyal Customer,52,Business travel,Eco Plus,433,4,5,5,5,5,4,5,4,4,4,4,3,4,2,0,10.0,satisfied +87260,44749,Female,Loyal Customer,12,Business travel,Eco,612,3,3,3,3,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +87261,40035,Male,Loyal Customer,60,Personal Travel,Eco,618,3,4,3,2,4,3,1,4,4,3,5,3,5,4,5,,neutral or dissatisfied +87262,18756,Female,disloyal Customer,25,Business travel,Eco Plus,1167,0,3,0,5,5,0,5,5,2,2,1,2,3,5,0,0.0,satisfied +87263,9330,Female,disloyal Customer,20,Business travel,Eco Plus,542,3,2,3,4,3,3,2,3,3,5,4,2,3,3,69,61.0,neutral or dissatisfied +87264,90002,Female,disloyal Customer,23,Business travel,Eco,983,2,2,2,4,3,2,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +87265,55320,Male,disloyal Customer,23,Business travel,Eco,1325,3,3,3,3,3,3,3,3,4,5,4,4,3,3,6,31.0,neutral or dissatisfied +87266,24496,Male,Loyal Customer,16,Personal Travel,Eco,547,3,5,2,1,1,2,1,1,4,3,4,3,5,1,1,8.0,neutral or dissatisfied +87267,13240,Male,Loyal Customer,26,Business travel,Eco,657,3,3,5,5,3,3,3,3,3,1,1,2,1,3,0,6.0,neutral or dissatisfied +87268,2816,Female,Loyal Customer,43,Business travel,Business,409,4,4,4,4,4,5,5,2,2,3,2,3,2,3,1,32.0,satisfied +87269,85096,Male,Loyal Customer,28,Business travel,Business,731,4,4,2,4,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +87270,95990,Male,Loyal Customer,54,Business travel,Business,2500,3,3,3,3,2,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +87271,33514,Female,Loyal Customer,45,Personal Travel,Eco Plus,965,4,4,4,4,3,4,4,2,2,4,2,5,2,3,0,0.0,neutral or dissatisfied +87272,46633,Female,Loyal Customer,68,Business travel,Business,2078,1,2,4,4,2,3,3,3,3,3,1,3,3,3,0,0.0,neutral or dissatisfied +87273,90181,Male,Loyal Customer,23,Personal Travel,Eco,1145,3,5,3,1,3,3,3,3,3,4,3,5,4,3,3,4.0,neutral or dissatisfied +87274,81915,Female,disloyal Customer,43,Business travel,Business,1522,5,5,5,3,3,5,3,3,5,4,5,5,5,3,0,0.0,satisfied +87275,4234,Male,Loyal Customer,59,Business travel,Eco,1020,3,5,5,5,3,3,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +87276,76887,Male,Loyal Customer,45,Business travel,Eco,630,2,2,2,2,3,2,3,3,3,3,3,2,3,3,0,6.0,neutral or dissatisfied +87277,46360,Female,Loyal Customer,49,Business travel,Business,2645,2,2,2,2,4,2,2,4,4,4,4,5,4,5,0,0.0,satisfied +87278,8118,Male,Loyal Customer,49,Business travel,Business,335,2,5,5,5,3,3,4,2,2,2,2,2,2,3,54,51.0,neutral or dissatisfied +87279,21112,Male,Loyal Customer,61,Personal Travel,Eco,152,1,5,0,2,2,0,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +87280,89745,Male,Loyal Customer,36,Personal Travel,Eco,1035,3,4,3,2,2,3,1,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +87281,16612,Female,Loyal Customer,60,Business travel,Business,1584,2,1,1,1,2,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +87282,19948,Female,Loyal Customer,8,Personal Travel,Eco,240,3,5,3,1,2,3,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +87283,52786,Female,disloyal Customer,26,Business travel,Eco,960,1,1,1,3,1,3,5,4,5,3,3,5,3,5,173,154.0,neutral or dissatisfied +87284,83277,Female,Loyal Customer,45,Personal Travel,Eco,2079,2,0,1,3,3,4,4,3,3,1,3,3,3,3,1,0.0,neutral or dissatisfied +87285,100665,Female,disloyal Customer,35,Business travel,Eco,889,2,2,2,4,2,2,2,2,2,3,4,1,3,2,53,65.0,neutral or dissatisfied +87286,48768,Male,Loyal Customer,39,Business travel,Business,2795,4,5,5,5,2,3,4,1,1,1,4,4,1,4,0,20.0,neutral or dissatisfied +87287,125598,Female,Loyal Customer,60,Business travel,Business,1587,3,1,1,1,4,1,2,3,3,3,3,2,3,1,0,13.0,neutral or dissatisfied +87288,53469,Female,Loyal Customer,24,Business travel,Business,2253,4,4,4,4,4,4,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +87289,31278,Male,Loyal Customer,14,Business travel,Business,770,4,4,5,5,4,4,4,4,3,2,3,2,4,4,0,1.0,neutral or dissatisfied +87290,115921,Male,Loyal Customer,36,Business travel,Business,342,0,0,0,5,4,4,1,3,3,3,3,1,3,4,0,0.0,satisfied +87291,67915,Female,Loyal Customer,16,Personal Travel,Eco,1464,1,5,1,1,2,1,5,2,3,2,3,4,4,2,6,0.0,neutral or dissatisfied +87292,72297,Female,Loyal Customer,64,Personal Travel,Eco,919,2,1,2,3,3,3,3,2,2,2,2,3,2,3,44,47.0,neutral or dissatisfied +87293,47870,Male,Loyal Customer,52,Business travel,Eco,817,4,3,3,3,4,4,4,4,5,3,1,5,4,4,0,0.0,satisfied +87294,2589,Female,Loyal Customer,7,Personal Travel,Eco,181,3,2,3,3,5,3,5,5,1,1,3,2,3,5,5,3.0,neutral or dissatisfied +87295,128221,Female,disloyal Customer,29,Business travel,Eco,602,2,1,2,2,3,2,1,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +87296,88940,Female,disloyal Customer,25,Business travel,Business,1199,3,4,3,3,3,3,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +87297,124276,Female,Loyal Customer,36,Business travel,Business,2078,4,1,4,4,4,4,4,5,5,5,5,5,5,4,3,1.0,satisfied +87298,83282,Male,Loyal Customer,67,Personal Travel,Eco,1956,4,4,4,3,5,4,5,5,5,5,4,4,5,5,13,28.0,neutral or dissatisfied +87299,128172,Female,disloyal Customer,17,Business travel,Eco,1849,3,3,3,5,2,3,2,2,1,3,4,4,1,2,0,0.0,neutral or dissatisfied +87300,79375,Female,disloyal Customer,26,Business travel,Business,502,4,4,4,4,3,4,3,3,5,5,5,4,5,3,0,0.0,satisfied +87301,75415,Male,Loyal Customer,60,Business travel,Business,2342,1,1,1,1,4,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +87302,120618,Female,Loyal Customer,42,Business travel,Business,2773,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +87303,11149,Female,Loyal Customer,36,Personal Travel,Eco,429,3,4,3,3,3,3,3,3,5,1,4,2,5,3,12,20.0,neutral or dissatisfied +87304,109922,Female,Loyal Customer,40,Personal Travel,Eco,1034,2,5,2,3,2,2,5,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +87305,56927,Female,disloyal Customer,49,Business travel,Business,2454,2,2,2,2,2,1,1,4,5,3,4,1,4,1,0,0.0,neutral or dissatisfied +87306,6882,Female,disloyal Customer,22,Business travel,Eco,265,2,0,2,1,5,2,3,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +87307,118045,Female,disloyal Customer,29,Business travel,Business,1262,2,2,2,2,4,2,3,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +87308,25930,Female,Loyal Customer,22,Personal Travel,Eco,594,0,4,0,3,2,0,2,2,4,2,3,3,4,2,7,59.0,satisfied +87309,16357,Male,Loyal Customer,54,Business travel,Eco,319,5,1,1,1,5,5,5,5,4,1,5,3,1,5,7,0.0,satisfied +87310,64854,Male,Loyal Customer,26,Business travel,Business,247,0,0,0,1,3,3,3,3,4,4,4,3,4,3,0,0.0,satisfied +87311,6314,Male,Loyal Customer,57,Business travel,Business,2198,0,0,0,5,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +87312,4846,Male,disloyal Customer,23,Business travel,Eco,500,2,3,1,3,5,1,5,5,2,2,2,4,3,5,0,0.0,neutral or dissatisfied +87313,71939,Female,Loyal Customer,7,Personal Travel,Eco Plus,1744,1,4,1,3,3,1,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +87314,42583,Female,Loyal Customer,46,Personal Travel,Eco,315,2,5,2,2,3,5,5,4,4,2,4,3,4,5,28,26.0,neutral or dissatisfied +87315,93557,Male,Loyal Customer,70,Personal Travel,Eco,949,2,2,2,3,2,2,2,2,1,1,4,1,4,2,0,0.0,neutral or dissatisfied +87316,42236,Male,disloyal Customer,17,Business travel,Eco,451,2,4,2,3,3,2,3,3,3,1,4,4,3,3,0,0.0,neutral or dissatisfied +87317,129374,Male,Loyal Customer,35,Business travel,Business,2565,1,1,1,1,4,3,5,2,2,2,2,3,2,3,0,0.0,satisfied +87318,119592,Male,Loyal Customer,42,Business travel,Business,1979,1,1,1,1,3,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +87319,93330,Male,Loyal Customer,51,Business travel,Business,2029,4,4,4,4,5,5,5,3,3,3,3,3,3,3,19,6.0,satisfied +87320,31057,Male,disloyal Customer,17,Business travel,Eco,775,2,2,2,4,3,2,3,3,2,5,3,3,3,3,2,4.0,neutral or dissatisfied +87321,83900,Female,Loyal Customer,48,Personal Travel,Business,1678,3,4,3,5,5,5,3,5,5,3,5,4,5,3,52,36.0,neutral or dissatisfied +87322,75068,Female,disloyal Customer,23,Business travel,Eco,2611,2,2,2,3,5,2,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +87323,69689,Male,Loyal Customer,58,Personal Travel,Eco Plus,569,1,5,1,5,1,1,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +87324,71234,Male,Loyal Customer,44,Business travel,Business,733,5,5,5,5,3,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +87325,75990,Female,Loyal Customer,42,Personal Travel,Eco,297,3,4,3,4,1,4,3,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +87326,104189,Female,Loyal Customer,66,Personal Travel,Eco Plus,349,2,4,2,5,3,5,5,1,1,2,1,5,1,5,0,3.0,neutral or dissatisfied +87327,68785,Female,Loyal Customer,68,Business travel,Business,926,2,5,1,5,1,4,3,2,2,2,2,4,2,4,5,7.0,neutral or dissatisfied +87328,2984,Female,Loyal Customer,43,Personal Travel,Eco Plus,462,4,4,4,4,2,4,5,2,2,4,4,1,2,1,0,0.0,satisfied +87329,14162,Female,disloyal Customer,20,Business travel,Eco,526,2,2,2,3,1,2,1,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +87330,57845,Male,Loyal Customer,38,Business travel,Eco Plus,1491,3,2,2,2,3,3,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +87331,124291,Male,Loyal Customer,44,Business travel,Business,601,3,3,3,3,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +87332,5784,Female,Loyal Customer,47,Business travel,Business,3169,4,4,4,4,4,5,5,4,4,4,5,4,4,3,2,3.0,satisfied +87333,62816,Female,Loyal Customer,69,Personal Travel,Eco,2486,4,3,4,1,2,5,3,3,3,4,3,1,3,4,4,16.0,neutral or dissatisfied +87334,42546,Male,Loyal Customer,40,Business travel,Business,2493,2,3,3,3,5,3,3,2,2,2,2,4,2,4,1,0.0,neutral or dissatisfied +87335,121156,Female,Loyal Customer,15,Business travel,Business,2402,2,2,2,2,2,2,2,4,3,3,3,2,4,2,2,24.0,neutral or dissatisfied +87336,37691,Male,Loyal Customer,40,Personal Travel,Eco,1005,2,5,1,2,3,1,1,3,5,3,4,5,5,3,91,97.0,neutral or dissatisfied +87337,128711,Male,Loyal Customer,61,Business travel,Business,2242,2,2,2,2,4,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +87338,118554,Male,Loyal Customer,53,Business travel,Business,370,2,2,4,2,2,4,4,4,4,4,4,5,4,4,1,13.0,satisfied +87339,9969,Male,Loyal Customer,69,Personal Travel,Eco,357,3,5,3,3,4,3,5,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +87340,67261,Male,Loyal Customer,68,Personal Travel,Eco,985,2,5,2,3,5,2,4,5,4,3,5,5,5,5,1,0.0,neutral or dissatisfied +87341,58499,Male,Loyal Customer,34,Business travel,Business,719,2,3,3,3,1,2,3,2,2,2,2,1,2,4,1,0.0,neutral or dissatisfied +87342,29404,Female,Loyal Customer,64,Personal Travel,Eco,2404,3,3,3,2,3,2,2,4,2,2,2,2,4,2,0,21.0,neutral or dissatisfied +87343,129059,Female,Loyal Customer,28,Personal Travel,Eco,1744,1,5,1,2,2,1,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +87344,56035,Male,disloyal Customer,22,Business travel,Eco,1121,2,2,2,3,2,5,1,1,4,2,4,1,4,1,14,46.0,neutral or dissatisfied +87345,29084,Female,Loyal Customer,51,Personal Travel,Eco,956,3,4,3,2,4,4,5,3,3,3,3,4,3,3,9,12.0,neutral or dissatisfied +87346,36173,Female,Loyal Customer,39,Business travel,Business,2749,2,2,2,2,4,4,3,4,4,4,4,2,4,1,0,0.0,satisfied +87347,38929,Male,Loyal Customer,25,Personal Travel,Eco,298,2,5,2,3,1,2,5,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +87348,58257,Female,Loyal Customer,55,Business travel,Business,2072,1,1,1,1,5,5,4,5,5,5,5,3,5,3,60,44.0,satisfied +87349,9524,Female,Loyal Customer,26,Personal Travel,Business,296,1,3,5,4,5,5,5,5,1,3,4,4,4,5,24,0.0,neutral or dissatisfied +87350,58581,Female,disloyal Customer,32,Business travel,Business,403,4,4,4,2,2,4,2,2,3,4,4,4,5,2,16,12.0,neutral or dissatisfied +87351,18204,Male,Loyal Customer,54,Business travel,Eco,228,4,3,3,3,4,4,4,4,3,3,2,4,1,4,71,91.0,satisfied +87352,32301,Female,Loyal Customer,39,Business travel,Eco,101,2,5,5,5,2,2,2,2,1,1,1,1,4,2,0,0.0,neutral or dissatisfied +87353,41666,Female,Loyal Customer,25,Business travel,Eco,936,3,2,2,2,3,2,1,3,4,1,2,3,3,3,3,0.0,neutral or dissatisfied +87354,117598,Female,disloyal Customer,20,Business travel,Eco,347,2,2,2,2,1,2,1,1,1,4,3,3,3,1,52,51.0,neutral or dissatisfied +87355,16363,Male,Loyal Customer,46,Personal Travel,Eco,319,3,3,3,1,2,3,2,2,3,4,5,3,4,2,0,2.0,neutral or dissatisfied +87356,78573,Male,Loyal Customer,42,Business travel,Eco,630,3,2,1,1,3,3,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +87357,83368,Female,Loyal Customer,58,Business travel,Business,2616,2,2,4,2,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +87358,36466,Female,disloyal Customer,48,Business travel,Eco Plus,867,3,3,3,3,5,3,5,5,4,4,3,5,5,5,0,0.0,neutral or dissatisfied +87359,34287,Female,Loyal Customer,51,Business travel,Eco,96,4,2,2,2,2,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +87360,68501,Male,Loyal Customer,10,Personal Travel,Eco,1303,2,4,2,4,1,2,1,1,3,4,4,4,4,1,14,0.0,neutral or dissatisfied +87361,31530,Male,Loyal Customer,40,Personal Travel,Eco,967,2,5,2,1,5,2,3,5,3,4,4,4,4,5,92,108.0,neutral or dissatisfied +87362,123458,Male,Loyal Customer,27,Business travel,Business,2125,5,5,5,5,4,4,4,4,3,2,5,5,5,4,6,0.0,satisfied +87363,1971,Female,Loyal Customer,36,Personal Travel,Eco,351,1,4,2,3,3,2,4,3,3,2,4,5,4,3,6,9.0,neutral or dissatisfied +87364,98937,Female,Loyal Customer,34,Business travel,Business,3497,1,1,1,1,2,5,4,5,5,5,5,4,5,5,12,0.0,satisfied +87365,118165,Female,Loyal Customer,49,Business travel,Business,1444,1,1,1,1,2,5,5,4,4,4,4,4,4,3,14,5.0,satisfied +87366,103127,Male,Loyal Customer,15,Personal Travel,Eco,687,3,4,3,4,2,3,2,2,4,2,5,4,5,2,19,19.0,neutral or dissatisfied +87367,114032,Male,Loyal Customer,48,Business travel,Business,1750,5,5,5,5,4,4,5,4,4,4,4,5,4,4,13,14.0,satisfied +87368,124552,Female,disloyal Customer,27,Business travel,Business,1276,4,4,4,3,2,4,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +87369,104412,Male,Loyal Customer,59,Business travel,Business,2435,3,3,3,3,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +87370,806,Male,Loyal Customer,42,Business travel,Business,1538,3,3,3,3,1,3,3,3,3,3,3,1,3,4,0,1.0,neutral or dissatisfied +87371,117430,Male,Loyal Customer,33,Business travel,Eco Plus,1460,3,1,3,1,3,3,3,3,2,1,3,2,3,3,45,33.0,neutral or dissatisfied +87372,126890,Female,Loyal Customer,67,Personal Travel,Eco,2125,2,5,1,2,1,3,1,3,3,1,3,3,3,4,0,1.0,neutral or dissatisfied +87373,125934,Female,Loyal Customer,69,Personal Travel,Eco,992,2,5,2,2,2,4,5,5,5,2,5,5,5,3,31,14.0,neutral or dissatisfied +87374,59410,Male,Loyal Customer,37,Personal Travel,Eco,2447,4,3,4,2,1,4,1,1,4,1,2,2,3,1,0,0.0,neutral or dissatisfied +87375,27776,Male,Loyal Customer,22,Business travel,Business,909,4,4,4,4,3,4,3,3,3,5,1,1,5,3,1,0.0,satisfied +87376,21788,Male,Loyal Customer,70,Business travel,Business,1611,3,5,5,5,3,3,2,3,3,3,3,1,3,3,3,1.0,neutral or dissatisfied +87377,10175,Male,disloyal Customer,22,Business travel,Eco,166,4,0,4,1,2,4,2,2,4,3,4,4,5,2,0,0.0,satisfied +87378,26075,Female,Loyal Customer,49,Business travel,Business,591,2,2,2,2,4,4,5,5,5,5,5,3,5,2,11,5.0,satisfied +87379,9663,Female,Loyal Customer,56,Business travel,Business,3805,5,5,5,5,5,5,5,5,3,4,5,5,3,5,167,157.0,satisfied +87380,110796,Male,disloyal Customer,57,Business travel,Eco,590,3,4,3,4,2,3,2,2,2,1,4,3,3,2,20,9.0,neutral or dissatisfied +87381,113845,Female,Loyal Customer,41,Business travel,Business,1334,2,2,2,2,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +87382,18970,Female,Loyal Customer,65,Personal Travel,Eco Plus,448,3,4,3,1,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +87383,20827,Male,Loyal Customer,28,Business travel,Business,515,3,5,5,5,3,3,3,3,2,1,1,3,3,3,181,196.0,neutral or dissatisfied +87384,99519,Male,Loyal Customer,39,Business travel,Business,3576,0,1,1,4,5,4,5,2,2,2,2,4,2,3,19,30.0,satisfied +87385,107224,Male,Loyal Customer,31,Business travel,Eco,1751,3,4,1,4,3,3,3,3,2,2,2,2,4,3,14,19.0,neutral or dissatisfied +87386,15,Male,Loyal Customer,52,Personal Travel,Eco,853,2,4,2,4,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +87387,104660,Male,disloyal Customer,23,Business travel,Eco,641,4,3,4,3,4,4,4,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +87388,109290,Male,Loyal Customer,52,Business travel,Business,3017,4,4,4,4,3,5,4,4,4,4,4,5,4,5,46,28.0,satisfied +87389,43687,Female,Loyal Customer,30,Business travel,Eco,196,1,2,2,2,1,1,1,1,2,5,3,1,4,1,0,0.0,neutral or dissatisfied +87390,11203,Female,Loyal Customer,15,Personal Travel,Eco,429,2,2,2,4,5,2,5,5,2,2,3,2,4,5,0,0.0,neutral or dissatisfied +87391,90412,Female,Loyal Customer,42,Business travel,Business,3923,2,2,2,2,3,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +87392,119823,Male,disloyal Customer,20,Business travel,Eco,912,2,3,3,4,5,3,5,5,2,3,3,2,4,5,0,0.0,neutral or dissatisfied +87393,128018,Female,Loyal Customer,44,Business travel,Business,1440,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +87394,4783,Female,Loyal Customer,38,Business travel,Eco,403,1,3,3,3,1,1,1,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +87395,115946,Female,Loyal Customer,23,Personal Travel,Eco,362,3,4,4,4,4,4,4,4,3,4,5,3,4,4,18,13.0,neutral or dissatisfied +87396,27090,Male,disloyal Customer,33,Business travel,Business,1721,1,1,1,3,3,1,3,3,4,3,3,4,4,3,4,0.0,neutral or dissatisfied +87397,60689,Male,Loyal Customer,43,Business travel,Business,1605,3,3,3,3,5,4,5,2,2,2,2,4,2,4,11,20.0,satisfied +87398,110949,Female,Loyal Customer,25,Business travel,Business,3699,4,4,2,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +87399,57673,Female,Loyal Customer,18,Personal Travel,Eco Plus,200,4,5,0,4,1,0,1,1,1,4,5,3,3,1,0,0.0,neutral or dissatisfied +87400,39873,Female,Loyal Customer,44,Personal Travel,Eco,272,2,0,2,3,2,4,5,4,4,2,4,3,4,4,0,1.0,neutral or dissatisfied +87401,42896,Male,Loyal Customer,23,Business travel,Business,3183,3,3,3,3,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +87402,49538,Male,Loyal Customer,42,Business travel,Business,3326,3,3,3,3,5,4,2,5,5,5,5,3,5,3,0,0.0,satisfied +87403,65994,Female,Loyal Customer,7,Personal Travel,Eco Plus,1372,2,5,2,4,5,2,5,5,3,5,4,3,4,5,9,0.0,neutral or dissatisfied +87404,112720,Female,Loyal Customer,13,Personal Travel,Eco,672,2,5,2,3,2,2,4,2,3,4,4,3,4,2,55,51.0,neutral or dissatisfied +87405,2848,Female,disloyal Customer,23,Business travel,Business,491,0,5,0,5,2,0,2,2,4,4,4,3,4,2,8,4.0,satisfied +87406,75033,Male,Loyal Customer,45,Personal Travel,Eco,236,4,5,4,3,1,4,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +87407,122740,Female,disloyal Customer,28,Business travel,Business,651,2,1,1,4,4,1,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +87408,5722,Female,Loyal Customer,67,Personal Travel,Eco,299,3,5,3,3,4,5,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +87409,95620,Male,Loyal Customer,66,Personal Travel,Eco,756,1,4,1,2,2,1,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +87410,31549,Female,Loyal Customer,42,Personal Travel,Eco,967,3,5,3,2,5,4,4,5,5,3,5,4,5,4,64,73.0,neutral or dissatisfied +87411,65111,Male,Loyal Customer,38,Personal Travel,Eco,247,1,5,0,1,4,0,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +87412,72794,Female,Loyal Customer,51,Business travel,Business,2598,4,5,5,5,4,3,4,4,4,4,4,4,4,4,9,26.0,neutral or dissatisfied +87413,48689,Female,disloyal Customer,20,Business travel,Business,134,5,3,5,1,3,3,3,3,3,3,4,4,4,3,0,7.0,satisfied +87414,8536,Female,Loyal Customer,55,Business travel,Business,109,0,4,0,3,5,4,4,5,5,5,5,3,5,3,0,10.0,satisfied +87415,17794,Female,disloyal Customer,27,Business travel,Eco,1214,1,1,1,2,3,1,3,3,2,2,2,3,3,3,62,59.0,neutral or dissatisfied +87416,70520,Female,Loyal Customer,56,Business travel,Business,3758,4,4,4,4,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +87417,52586,Female,Loyal Customer,37,Business travel,Eco,160,5,5,5,5,5,5,5,5,5,1,1,1,1,5,0,0.0,satisfied +87418,64194,Male,Loyal Customer,58,Business travel,Business,853,5,5,1,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +87419,101231,Female,disloyal Customer,25,Business travel,Business,1069,5,4,5,3,5,5,3,5,5,5,5,5,4,5,0,0.0,satisfied +87420,21645,Male,Loyal Customer,30,Business travel,Eco Plus,780,0,0,0,2,3,0,4,3,3,3,4,5,3,3,117,102.0,satisfied +87421,53344,Female,disloyal Customer,37,Business travel,Eco,1452,4,4,4,2,5,4,5,5,2,2,3,2,3,5,3,0.0,neutral or dissatisfied +87422,59626,Male,Loyal Customer,58,Business travel,Business,2453,2,3,3,3,4,2,3,2,2,2,2,2,2,2,122,130.0,neutral or dissatisfied +87423,21493,Male,Loyal Customer,37,Personal Travel,Eco,399,0,5,0,1,5,0,5,5,4,3,5,4,5,5,0,0.0,satisfied +87424,57113,Male,Loyal Customer,26,Business travel,Business,3405,2,2,2,2,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +87425,90846,Male,Loyal Customer,51,Business travel,Business,1609,0,0,0,3,4,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +87426,24779,Female,disloyal Customer,22,Business travel,Eco,447,4,3,4,4,2,4,2,2,5,5,3,1,1,2,0,1.0,satisfied +87427,26437,Male,Loyal Customer,50,Business travel,Eco,787,4,4,4,4,4,4,4,4,2,1,5,4,3,4,0,2.0,satisfied +87428,118302,Male,Loyal Customer,28,Business travel,Business,602,1,1,1,1,3,3,3,3,5,3,5,4,4,3,21,28.0,satisfied +87429,38606,Female,Loyal Customer,33,Business travel,Eco,231,5,1,1,1,5,5,5,5,3,1,3,4,3,5,0,0.0,satisfied +87430,129645,Female,Loyal Customer,40,Business travel,Business,1757,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +87431,91872,Male,Loyal Customer,31,Personal Travel,Eco,2239,2,1,3,3,3,3,3,3,2,4,4,4,4,3,10,0.0,neutral or dissatisfied +87432,13838,Male,Loyal Customer,17,Personal Travel,Eco,628,1,4,1,5,1,1,1,1,4,3,4,4,5,1,62,49.0,neutral or dissatisfied +87433,34280,Female,Loyal Customer,38,Business travel,Eco,496,5,2,2,2,5,5,5,5,2,2,2,2,1,5,0,0.0,satisfied +87434,94964,Male,Loyal Customer,54,Business travel,Eco,148,4,2,2,2,4,4,4,4,2,5,2,2,4,4,50,39.0,satisfied +87435,70662,Female,Loyal Customer,41,Business travel,Business,447,3,5,2,5,3,4,3,3,3,3,3,2,3,3,10,1.0,neutral or dissatisfied +87436,128433,Female,Loyal Customer,34,Business travel,Business,370,4,4,4,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +87437,70729,Male,Loyal Customer,34,Business travel,Business,675,5,5,4,5,5,5,4,4,4,4,4,2,4,3,0,0.0,satisfied +87438,1876,Male,Loyal Customer,57,Business travel,Eco,931,4,3,2,2,4,4,4,4,1,5,4,1,3,4,47,66.0,neutral or dissatisfied +87439,780,Male,Loyal Customer,60,Business travel,Business,113,0,4,0,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +87440,121456,Female,Loyal Customer,55,Business travel,Eco,331,5,5,5,5,2,5,1,5,5,5,5,2,5,3,0,6.0,satisfied +87441,70276,Female,Loyal Customer,59,Business travel,Eco,852,3,3,3,3,1,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +87442,56326,Male,Loyal Customer,54,Business travel,Business,2541,1,2,2,2,5,4,3,3,3,3,1,1,3,1,14,6.0,neutral or dissatisfied +87443,18732,Female,Loyal Customer,46,Personal Travel,Business,1167,2,5,2,5,4,5,5,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +87444,106023,Female,Loyal Customer,45,Business travel,Business,3034,4,4,4,4,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +87445,53615,Female,Loyal Customer,39,Business travel,Business,1874,5,5,5,5,4,4,1,4,4,4,4,2,4,3,65,59.0,satisfied +87446,64229,Male,Loyal Customer,58,Business travel,Business,1660,1,1,1,1,2,4,4,5,5,5,5,4,5,5,1,6.0,satisfied +87447,128798,Male,Loyal Customer,51,Business travel,Business,2586,3,3,3,3,4,4,4,3,4,5,5,4,3,4,42,27.0,satisfied +87448,121441,Male,Loyal Customer,36,Business travel,Business,257,4,3,3,3,3,4,3,4,4,4,4,3,4,4,9,19.0,neutral or dissatisfied +87449,805,Male,Loyal Customer,42,Business travel,Business,1750,1,5,5,5,3,3,3,1,1,1,1,2,1,4,0,5.0,neutral or dissatisfied +87450,72899,Female,Loyal Customer,50,Business travel,Business,944,1,4,1,1,5,4,4,4,4,4,4,5,4,4,30,24.0,satisfied +87451,54264,Male,Loyal Customer,18,Personal Travel,Eco,1222,3,4,4,3,3,4,2,3,4,2,4,2,3,3,46,33.0,neutral or dissatisfied +87452,78454,Male,Loyal Customer,58,Business travel,Business,526,5,5,5,5,5,4,4,2,2,2,2,3,2,4,17,15.0,satisfied +87453,99480,Female,Loyal Customer,62,Business travel,Eco,283,3,5,5,5,2,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +87454,113311,Male,disloyal Customer,25,Business travel,Business,223,1,5,1,3,3,1,3,3,3,5,4,4,5,3,0,11.0,neutral or dissatisfied +87455,13758,Male,Loyal Customer,23,Personal Travel,Eco,384,2,4,2,3,5,2,5,5,1,3,3,4,3,5,37,37.0,neutral or dissatisfied +87456,96138,Male,Loyal Customer,39,Business travel,Business,3548,2,2,2,2,2,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +87457,87122,Female,Loyal Customer,52,Personal Travel,Eco,594,1,5,1,5,2,4,3,3,3,1,3,4,3,4,21,10.0,neutral or dissatisfied +87458,20985,Female,Loyal Customer,66,Personal Travel,Eco,721,1,0,1,3,3,5,4,2,2,1,2,1,2,2,0,20.0,neutral or dissatisfied +87459,42642,Male,Loyal Customer,67,Personal Travel,Eco,546,4,4,4,1,4,4,4,4,5,2,4,3,4,4,0,0.0,neutral or dissatisfied +87460,102755,Male,Loyal Customer,57,Personal Travel,Eco Plus,255,2,4,2,3,5,2,5,5,5,5,5,3,4,5,47,43.0,neutral or dissatisfied +87461,96846,Male,Loyal Customer,43,Business travel,Business,3103,3,1,4,1,3,2,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +87462,93403,Female,Loyal Customer,58,Business travel,Business,2131,4,4,4,4,2,5,4,5,5,5,5,3,5,3,18,0.0,satisfied +87463,94707,Male,Loyal Customer,58,Business travel,Business,2579,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +87464,80357,Male,Loyal Customer,37,Business travel,Business,3905,1,1,1,1,5,4,5,5,5,5,5,5,5,5,27,20.0,satisfied +87465,54719,Male,Loyal Customer,68,Personal Travel,Eco,787,5,5,5,4,5,5,5,5,5,2,4,2,4,5,0,0.0,satisfied +87466,59913,Male,Loyal Customer,55,Business travel,Business,3249,2,2,3,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +87467,129218,Male,Loyal Customer,40,Business travel,Business,1504,4,4,4,4,5,4,4,5,5,4,5,5,5,5,12,4.0,satisfied +87468,129822,Female,Loyal Customer,62,Personal Travel,Eco,337,3,3,3,3,2,3,4,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +87469,81363,Female,Loyal Customer,79,Business travel,Eco Plus,899,2,3,3,3,5,4,3,2,2,2,2,1,2,3,63,82.0,neutral or dissatisfied +87470,98332,Female,disloyal Customer,21,Business travel,Eco,1046,2,2,2,4,1,2,1,1,5,3,4,3,4,1,0,0.0,satisfied +87471,88474,Male,Loyal Customer,34,Business travel,Business,271,3,3,1,1,3,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +87472,62884,Female,disloyal Customer,19,Business travel,Eco,1244,1,1,1,4,5,1,3,5,2,1,3,3,3,5,0,17.0,neutral or dissatisfied +87473,65638,Male,disloyal Customer,21,Business travel,Business,237,4,0,4,3,2,4,2,2,3,5,4,5,4,2,0,0.0,satisfied +87474,91496,Female,disloyal Customer,32,Business travel,Business,391,2,2,2,2,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +87475,35988,Female,Loyal Customer,31,Business travel,Business,2496,5,5,5,5,4,4,4,5,3,4,4,4,1,4,10,0.0,satisfied +87476,30228,Male,Loyal Customer,21,Business travel,Business,3523,1,1,1,1,4,4,4,4,5,5,5,4,2,4,0,0.0,satisfied +87477,116627,Male,Loyal Customer,40,Business travel,Business,3212,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +87478,86026,Female,Loyal Customer,37,Business travel,Business,154,5,5,5,5,1,2,1,5,5,5,3,3,5,3,0,1.0,satisfied +87479,100309,Male,Loyal Customer,45,Business travel,Eco,1052,2,1,1,1,2,2,2,2,2,4,4,4,4,2,41,51.0,neutral or dissatisfied +87480,95777,Male,Loyal Customer,56,Personal Travel,Eco,237,3,4,3,3,5,3,5,5,3,5,4,3,4,5,10,9.0,neutral or dissatisfied +87481,32198,Female,Loyal Customer,67,Business travel,Eco,163,5,3,3,3,1,2,5,5,5,5,5,3,5,3,0,0.0,satisfied +87482,77362,Female,disloyal Customer,23,Business travel,Eco,588,2,0,2,1,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +87483,118317,Male,Loyal Customer,67,Business travel,Business,2116,2,2,2,2,2,4,4,2,2,2,2,4,2,2,0,5.0,neutral or dissatisfied +87484,125801,Male,Loyal Customer,50,Business travel,Business,2001,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +87485,75065,Male,Loyal Customer,58,Business travel,Business,2611,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +87486,87924,Male,disloyal Customer,20,Business travel,Eco,406,3,5,3,1,5,3,4,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +87487,36062,Female,Loyal Customer,19,Business travel,Business,399,3,5,5,5,3,3,3,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +87488,52103,Female,Loyal Customer,34,Personal Travel,Eco,351,2,5,2,3,4,2,5,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +87489,84061,Female,Loyal Customer,57,Business travel,Business,2907,5,5,4,5,3,5,4,4,4,4,4,4,4,3,22,21.0,satisfied +87490,97089,Male,disloyal Customer,24,Business travel,Eco,1211,5,5,5,2,5,5,5,5,5,4,4,4,4,5,79,81.0,satisfied +87491,72366,Female,Loyal Customer,57,Business travel,Business,929,1,1,1,1,3,4,4,5,5,4,5,4,5,5,0,2.0,satisfied +87492,60580,Male,Loyal Customer,45,Business travel,Business,1558,4,3,3,3,4,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +87493,35748,Male,Loyal Customer,9,Personal Travel,Eco,1826,4,5,4,4,5,4,5,5,4,4,4,2,1,5,63,41.0,satisfied +87494,88332,Male,Loyal Customer,34,Business travel,Business,1630,3,1,1,1,3,3,4,3,3,3,3,2,3,3,40,46.0,neutral or dissatisfied +87495,37651,Female,Loyal Customer,7,Personal Travel,Eco,989,4,2,4,3,5,4,5,5,3,2,4,1,4,5,0,0.0,satisfied +87496,78558,Female,Loyal Customer,61,Personal Travel,Eco Plus,526,2,5,2,5,2,4,5,1,1,2,1,5,1,3,93,88.0,neutral or dissatisfied +87497,33901,Female,Loyal Customer,41,Personal Travel,Eco,1504,3,3,3,3,4,3,4,4,4,1,4,1,3,4,0,15.0,neutral or dissatisfied +87498,83531,Female,disloyal Customer,36,Business travel,Business,946,2,2,2,4,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +87499,50947,Female,Loyal Customer,38,Personal Travel,Eco,156,1,3,1,4,4,1,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +87500,105577,Male,disloyal Customer,28,Business travel,Eco,577,1,2,1,4,1,1,1,1,4,1,4,2,4,1,14,60.0,neutral or dissatisfied +87501,53535,Female,Loyal Customer,25,Business travel,Eco Plus,2358,1,4,4,4,1,1,3,1,4,2,4,3,4,1,19,8.0,neutral or dissatisfied +87502,76008,Male,Loyal Customer,41,Business travel,Business,2115,3,3,3,3,2,5,5,5,5,5,5,4,5,5,43,48.0,satisfied +87503,82055,Female,Loyal Customer,52,Business travel,Eco Plus,1122,4,5,5,5,2,3,2,4,4,4,4,2,4,1,15,0.0,satisfied +87504,25038,Female,Loyal Customer,8,Personal Travel,Eco,907,2,1,2,2,3,2,5,3,4,4,2,2,3,3,22,20.0,neutral or dissatisfied +87505,114084,Female,Loyal Customer,36,Business travel,Eco,447,4,3,3,3,4,4,4,4,4,5,3,4,4,4,6,0.0,satisfied +87506,117784,Male,Loyal Customer,30,Business travel,Business,3370,2,2,2,2,4,4,4,4,3,5,4,5,4,4,33,24.0,satisfied +87507,39439,Male,Loyal Customer,68,Business travel,Business,1709,2,4,4,4,4,3,4,1,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +87508,120886,Female,Loyal Customer,41,Business travel,Business,920,1,4,4,4,2,4,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +87509,11479,Female,Loyal Customer,32,Business travel,Eco Plus,158,4,4,2,4,4,4,4,4,1,3,4,1,3,4,12,10.0,neutral or dissatisfied +87510,62725,Female,Loyal Customer,40,Business travel,Business,2399,4,4,4,4,5,5,4,5,5,5,5,5,5,3,73,49.0,satisfied +87511,60615,Female,Loyal Customer,52,Business travel,Eco Plus,991,3,2,2,2,4,4,4,3,3,3,3,4,3,1,33,19.0,neutral or dissatisfied +87512,114406,Female,Loyal Customer,33,Business travel,Business,2472,1,1,1,1,3,5,4,4,4,5,4,3,4,4,0,4.0,satisfied +87513,110037,Female,disloyal Customer,22,Business travel,Business,2039,5,2,5,1,4,5,5,4,3,4,4,5,4,4,0,0.0,satisfied +87514,125268,Male,Loyal Customer,24,Business travel,Business,1488,4,3,3,3,4,4,4,4,3,5,4,4,4,4,1,0.0,neutral or dissatisfied +87515,28789,Female,Loyal Customer,43,Personal Travel,Business,679,4,5,4,2,2,4,4,2,2,4,2,3,2,4,0,0.0,satisfied +87516,90869,Female,disloyal Customer,27,Business travel,Business,515,3,3,3,1,4,3,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +87517,85104,Male,Loyal Customer,22,Business travel,Business,3218,3,3,3,3,5,4,5,5,5,4,4,5,4,5,0,0.0,satisfied +87518,124846,Female,Loyal Customer,64,Personal Travel,Eco,280,2,5,2,3,5,4,4,2,2,2,1,3,2,3,20,28.0,neutral or dissatisfied +87519,96968,Female,Loyal Customer,43,Business travel,Business,2504,4,4,4,4,4,4,5,3,3,4,3,5,3,3,5,0.0,satisfied +87520,12856,Male,Loyal Customer,20,Personal Travel,Eco,528,2,3,2,1,3,2,3,3,5,5,3,2,5,3,0,0.0,neutral or dissatisfied +87521,9823,Male,Loyal Customer,32,Business travel,Business,451,1,3,3,3,1,1,1,1,3,1,3,3,3,1,3,0.0,neutral or dissatisfied +87522,19922,Male,disloyal Customer,15,Business travel,Eco,343,3,1,3,4,2,3,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +87523,44836,Female,Loyal Customer,20,Business travel,Eco Plus,462,1,4,4,4,1,2,4,1,1,2,4,1,3,1,80,104.0,neutral or dissatisfied +87524,34615,Female,Loyal Customer,21,Business travel,Eco Plus,1598,0,3,0,2,1,0,1,1,4,5,3,3,3,1,0,5.0,satisfied +87525,13943,Male,Loyal Customer,17,Business travel,Eco,153,4,3,3,3,4,4,3,4,4,5,4,2,5,4,0,0.0,satisfied +87526,79958,Female,Loyal Customer,20,Business travel,Eco,950,2,1,1,1,2,2,2,2,1,5,3,2,4,2,0,0.0,neutral or dissatisfied +87527,113900,Female,Loyal Customer,24,Business travel,Business,2295,4,2,2,2,4,4,4,4,2,2,2,1,3,4,0,0.0,neutral or dissatisfied +87528,86952,Male,Loyal Customer,41,Business travel,Business,2668,1,1,1,1,2,5,4,3,3,3,3,4,3,3,8,9.0,satisfied +87529,113146,Male,Loyal Customer,20,Business travel,Business,1552,4,4,4,4,4,4,4,4,3,3,5,4,5,4,36,26.0,satisfied +87530,106405,Female,Loyal Customer,16,Personal Travel,Eco,674,5,4,5,3,1,5,1,1,5,5,4,5,5,1,0,0.0,satisfied +87531,64724,Male,Loyal Customer,44,Business travel,Business,2252,4,4,4,4,2,5,4,4,4,4,5,3,4,3,0,0.0,satisfied +87532,8668,Male,disloyal Customer,22,Business travel,Eco,304,1,2,1,2,1,1,1,1,3,5,3,2,2,1,0,0.0,neutral or dissatisfied +87533,124097,Female,Loyal Customer,54,Business travel,Business,3902,3,5,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +87534,10312,Male,disloyal Customer,24,Business travel,Business,482,4,0,3,1,3,3,1,3,5,5,4,4,4,3,0,0.0,satisfied +87535,85653,Male,Loyal Customer,39,Personal Travel,Eco Plus,259,3,1,3,2,5,3,5,5,2,4,2,4,1,5,32,27.0,neutral or dissatisfied +87536,113523,Female,Loyal Customer,42,Business travel,Business,1665,4,4,4,4,2,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +87537,90734,Female,Loyal Customer,53,Business travel,Business,2432,2,2,2,2,5,5,4,2,2,2,2,5,2,5,4,8.0,satisfied +87538,109934,Male,Loyal Customer,8,Personal Travel,Eco,1073,4,4,4,1,3,4,3,3,5,5,4,4,5,3,13,1.0,neutral or dissatisfied +87539,5297,Female,Loyal Customer,64,Personal Travel,Eco,351,4,1,4,4,1,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +87540,98496,Male,Loyal Customer,48,Business travel,Business,1586,5,5,5,5,2,5,4,4,4,5,4,4,4,3,25,28.0,satisfied +87541,66456,Male,Loyal Customer,43,Personal Travel,Eco,1217,2,5,2,2,1,2,1,1,3,3,4,3,4,1,11,2.0,neutral or dissatisfied +87542,61024,Female,Loyal Customer,52,Personal Travel,Eco,3365,3,4,3,3,3,2,2,3,1,4,4,2,2,2,16,83.0,neutral or dissatisfied +87543,74772,Female,Loyal Customer,60,Personal Travel,Eco,1205,2,2,2,3,1,3,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +87544,14874,Female,disloyal Customer,23,Business travel,Eco,315,4,0,4,2,3,4,3,3,1,3,4,5,3,3,0,0.0,satisfied +87545,103091,Male,Loyal Customer,56,Personal Travel,Eco,666,3,4,3,4,3,3,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +87546,106052,Female,Loyal Customer,44,Personal Travel,Eco,452,2,5,2,2,1,5,2,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +87547,111753,Female,disloyal Customer,22,Business travel,Eco,1154,3,3,3,4,5,3,4,5,3,5,3,1,3,5,11,24.0,neutral or dissatisfied +87548,37081,Female,Loyal Customer,60,Business travel,Business,2826,5,5,5,5,3,4,4,4,4,4,4,3,4,3,20,23.0,satisfied +87549,78494,Male,Loyal Customer,56,Business travel,Eco,526,2,3,2,3,2,2,2,2,3,2,2,2,2,2,39,19.0,neutral or dissatisfied +87550,9547,Male,disloyal Customer,21,Business travel,Business,228,0,0,0,2,0,5,5,4,4,4,4,5,4,5,158,133.0,satisfied +87551,7202,Male,Loyal Customer,40,Business travel,Eco,135,3,2,2,2,3,3,3,3,2,1,3,1,4,3,0,54.0,neutral or dissatisfied +87552,64543,Male,disloyal Customer,23,Business travel,Eco,247,2,0,2,4,3,2,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +87553,105944,Male,Loyal Customer,69,Personal Travel,Eco Plus,1491,1,5,1,2,2,1,2,2,3,3,1,3,2,2,0,0.0,neutral or dissatisfied +87554,98574,Female,Loyal Customer,27,Business travel,Business,951,4,4,5,4,3,3,3,3,4,2,5,3,4,3,0,0.0,satisfied +87555,75152,Female,Loyal Customer,34,Business travel,Business,1744,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +87556,31083,Female,Loyal Customer,61,Personal Travel,Eco Plus,641,2,5,2,4,4,4,5,1,1,2,1,5,1,4,17,11.0,neutral or dissatisfied +87557,19562,Female,disloyal Customer,21,Business travel,Eco,173,3,2,3,3,5,3,5,5,2,5,4,2,4,5,8,17.0,neutral or dissatisfied +87558,119392,Female,Loyal Customer,41,Business travel,Business,3990,5,5,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +87559,80372,Female,Loyal Customer,55,Business travel,Eco,368,3,4,4,4,5,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +87560,1616,Female,Loyal Customer,17,Personal Travel,Eco,968,1,3,1,4,5,1,5,5,3,4,4,3,4,5,18,19.0,neutral or dissatisfied +87561,4166,Male,Loyal Customer,50,Personal Travel,Eco,431,2,4,5,5,4,5,4,4,3,3,4,3,4,4,0,9.0,neutral or dissatisfied +87562,111534,Female,Loyal Customer,60,Business travel,Business,775,1,4,4,4,3,4,4,1,1,1,1,2,1,4,20,14.0,neutral or dissatisfied +87563,83065,Male,disloyal Customer,23,Business travel,Business,1084,0,0,0,3,2,0,2,2,3,5,5,5,5,2,0,0.0,satisfied +87564,63470,Female,disloyal Customer,19,Business travel,Eco Plus,447,2,2,2,3,5,2,5,5,4,2,3,3,3,5,0,11.0,neutral or dissatisfied +87565,20732,Female,Loyal Customer,30,Personal Travel,Eco,707,3,1,3,4,2,3,2,2,1,5,3,2,4,2,0,28.0,neutral or dissatisfied +87566,20404,Male,Loyal Customer,38,Business travel,Eco Plus,459,5,2,5,5,5,5,5,5,4,5,5,1,5,5,0,0.0,satisfied +87567,56849,Male,Loyal Customer,45,Business travel,Business,2434,2,1,1,1,2,2,2,4,4,1,2,2,1,2,18,9.0,neutral or dissatisfied +87568,33892,Male,Loyal Customer,40,Business travel,Eco,1504,5,3,3,3,5,5,5,5,2,1,5,1,1,5,73,94.0,satisfied +87569,18535,Female,Loyal Customer,22,Business travel,Business,127,2,2,2,2,5,5,4,5,3,3,2,2,2,5,0,0.0,satisfied +87570,36322,Female,Loyal Customer,56,Business travel,Eco,187,2,1,1,1,3,3,3,2,2,2,2,3,2,1,41,53.0,neutral or dissatisfied +87571,7084,Female,disloyal Customer,38,Business travel,Eco,177,3,3,3,4,3,3,3,3,1,5,3,1,4,3,1,26.0,neutral or dissatisfied +87572,76711,Female,disloyal Customer,36,Business travel,Business,547,1,1,1,5,3,1,3,3,4,3,5,5,4,3,24,14.0,neutral or dissatisfied +87573,57914,Male,Loyal Customer,19,Personal Travel,Eco,305,3,5,4,5,1,4,1,1,5,2,5,2,4,1,0,0.0,neutral or dissatisfied +87574,49078,Female,Loyal Customer,52,Business travel,Business,89,2,2,2,2,2,5,4,4,4,4,5,2,4,1,0,0.0,satisfied +87575,54528,Male,Loyal Customer,47,Personal Travel,Eco,925,1,3,1,3,1,1,1,1,4,4,1,1,3,1,0,24.0,neutral or dissatisfied +87576,30162,Female,Loyal Customer,35,Personal Travel,Eco,95,5,4,5,1,3,5,3,3,4,4,5,3,4,3,2,0.0,satisfied +87577,12495,Male,Loyal Customer,49,Business travel,Eco Plus,253,1,1,1,1,1,1,1,1,4,1,3,1,3,1,106,112.0,neutral or dissatisfied +87578,23119,Male,Loyal Customer,41,Business travel,Business,300,1,1,5,1,3,1,4,5,5,5,5,2,5,2,0,0.0,satisfied +87579,14760,Male,Loyal Customer,66,Business travel,Eco,463,3,3,2,2,3,3,3,3,1,3,4,4,4,3,15,1.0,neutral or dissatisfied +87580,12860,Male,Loyal Customer,47,Business travel,Eco Plus,528,4,2,4,2,4,4,4,4,2,4,3,3,3,4,0,6.0,satisfied +87581,24937,Female,Loyal Customer,66,Personal Travel,Eco,2106,2,2,2,2,3,2,2,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +87582,104852,Male,Loyal Customer,36,Business travel,Business,3196,5,5,5,5,5,5,5,4,4,4,4,5,4,3,32,20.0,satisfied +87583,61121,Male,Loyal Customer,42,Business travel,Business,862,1,1,1,1,5,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +87584,32247,Male,Loyal Customer,45,Business travel,Eco,216,3,4,4,4,3,3,3,3,5,5,3,3,1,3,1,0.0,satisfied +87585,24212,Male,Loyal Customer,54,Business travel,Eco,147,4,2,2,2,4,4,4,4,1,4,4,3,4,4,0,0.0,neutral or dissatisfied +87586,81826,Male,Loyal Customer,36,Personal Travel,Eco,1416,2,2,2,4,5,2,5,5,2,1,4,2,4,5,0,3.0,neutral or dissatisfied +87587,85141,Male,disloyal Customer,23,Business travel,Eco,689,4,4,4,3,3,4,3,3,4,2,4,3,4,3,7,14.0,neutral or dissatisfied +87588,6806,Male,Loyal Customer,36,Personal Travel,Eco,235,1,4,1,4,3,1,3,3,5,3,2,3,5,3,35,28.0,neutral or dissatisfied +87589,40244,Female,Loyal Customer,45,Business travel,Eco,387,4,1,1,1,3,5,3,4,4,4,4,4,4,5,0,0.0,satisfied +87590,19221,Male,disloyal Customer,38,Business travel,Eco,459,1,0,1,1,5,1,5,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +87591,119925,Female,Loyal Customer,42,Business travel,Business,3509,5,5,5,5,4,5,4,4,4,4,4,5,4,4,6,7.0,satisfied +87592,100107,Male,Loyal Customer,57,Business travel,Eco,717,2,3,3,3,2,2,2,2,4,1,3,1,3,2,25,18.0,neutral or dissatisfied +87593,8444,Male,Loyal Customer,32,Personal Travel,Eco,590,3,4,3,1,2,3,4,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +87594,80870,Female,Loyal Customer,47,Personal Travel,Eco,484,3,5,3,3,5,4,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +87595,40837,Male,disloyal Customer,50,Business travel,Eco,190,5,4,5,3,3,5,3,3,5,3,2,5,3,3,0,0.0,satisfied +87596,120080,Female,Loyal Customer,41,Personal Travel,Eco,683,2,4,2,3,4,2,4,4,1,4,4,1,4,4,0,25.0,neutral or dissatisfied +87597,86647,Female,Loyal Customer,21,Personal Travel,Eco,746,2,5,2,5,5,2,5,5,2,3,5,4,3,5,32,21.0,neutral or dissatisfied +87598,44911,Female,Loyal Customer,39,Personal Travel,Eco,1118,2,4,2,3,1,2,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +87599,32784,Male,Loyal Customer,34,Business travel,Business,3608,3,3,3,3,4,2,3,4,4,4,5,5,4,4,0,0.0,satisfied +87600,109993,Male,Loyal Customer,21,Personal Travel,Eco Plus,1011,1,5,1,3,3,1,3,3,4,5,5,1,1,3,42,68.0,neutral or dissatisfied +87601,65805,Female,Loyal Customer,29,Business travel,Business,1389,4,4,4,4,3,3,3,3,3,3,5,4,5,3,17,0.0,satisfied +87602,1551,Male,Loyal Customer,28,Personal Travel,Eco,922,3,4,3,1,4,3,4,4,5,2,4,5,4,4,108,100.0,neutral or dissatisfied +87603,60003,Female,Loyal Customer,44,Personal Travel,Eco,937,3,4,3,2,3,3,3,5,5,3,5,1,5,3,0,0.0,neutral or dissatisfied +87604,12367,Male,Loyal Customer,32,Business travel,Eco,201,1,2,2,2,1,1,1,1,1,4,3,4,4,1,15,9.0,neutral or dissatisfied +87605,86336,Female,Loyal Customer,57,Personal Travel,Business,762,2,5,2,2,3,4,5,5,5,2,5,3,5,5,0,31.0,neutral or dissatisfied +87606,118381,Male,Loyal Customer,55,Business travel,Business,2425,3,3,3,3,4,3,4,3,3,3,3,2,3,1,23,15.0,neutral or dissatisfied +87607,82515,Female,Loyal Customer,21,Business travel,Business,1749,5,5,5,5,4,4,4,4,3,5,5,5,4,4,0,0.0,satisfied +87608,56102,Female,Loyal Customer,43,Business travel,Business,2402,5,5,5,5,4,4,4,4,2,5,5,4,3,4,25,49.0,satisfied +87609,31675,Male,Loyal Customer,42,Business travel,Eco,967,2,1,1,1,1,2,1,1,1,3,1,3,2,1,58,58.0,satisfied +87610,18985,Male,Loyal Customer,34,Business travel,Business,1544,1,5,5,5,2,3,3,1,1,1,1,4,1,2,14,27.0,neutral or dissatisfied +87611,37868,Female,Loyal Customer,41,Business travel,Eco,997,1,2,2,2,1,1,1,1,4,1,4,1,4,1,15,5.0,neutral or dissatisfied +87612,74415,Male,Loyal Customer,49,Business travel,Business,3328,4,4,2,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +87613,82469,Male,Loyal Customer,38,Personal Travel,Eco,502,3,5,3,5,3,3,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +87614,5714,Female,Loyal Customer,43,Personal Travel,Eco,196,3,4,3,1,3,5,5,4,3,5,5,5,5,5,253,245.0,neutral or dissatisfied +87615,15075,Male,disloyal Customer,27,Business travel,Eco,239,2,5,2,1,3,2,3,3,4,1,1,3,3,3,0,0.0,neutral or dissatisfied +87616,50541,Female,Loyal Customer,32,Personal Travel,Eco,373,3,5,3,3,4,3,4,4,3,3,4,5,5,4,8,0.0,neutral or dissatisfied +87617,47661,Female,disloyal Customer,23,Business travel,Eco,1211,3,3,3,4,1,3,1,1,2,4,3,4,3,1,7,9.0,neutral or dissatisfied +87618,37032,Male,Loyal Customer,41,Business travel,Eco,1105,5,3,3,3,5,5,5,5,1,5,5,5,2,5,0,0.0,satisfied +87619,122666,Female,Loyal Customer,38,Business travel,Business,3543,4,4,4,4,2,5,5,5,5,5,5,4,5,3,3,1.0,satisfied +87620,118558,Male,Loyal Customer,51,Business travel,Business,2513,5,5,5,5,5,4,4,4,4,4,4,3,4,4,24,2.0,satisfied +87621,32941,Female,Loyal Customer,27,Personal Travel,Eco,163,3,5,3,4,2,3,2,2,3,3,5,2,5,2,0,0.0,neutral or dissatisfied +87622,129802,Male,Loyal Customer,17,Personal Travel,Eco,447,1,4,1,5,5,1,3,5,3,3,1,3,1,5,6,0.0,neutral or dissatisfied +87623,60915,Male,Loyal Customer,20,Business travel,Business,3454,4,5,4,4,5,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +87624,122490,Female,Loyal Customer,60,Business travel,Business,575,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +87625,91574,Male,Loyal Customer,28,Business travel,Business,1123,1,4,4,4,1,1,1,1,4,5,3,3,3,1,22,59.0,neutral or dissatisfied +87626,31068,Female,Loyal Customer,44,Personal Travel,Eco,641,2,4,2,5,4,4,5,2,2,2,2,5,2,5,10,16.0,neutral or dissatisfied +87627,28933,Male,Loyal Customer,45,Business travel,Business,2610,1,1,4,1,3,4,3,5,5,5,5,2,5,3,0,0.0,satisfied +87628,66168,Male,Loyal Customer,74,Business travel,Business,460,2,2,2,2,2,2,2,2,2,1,1,2,2,2,162,163.0,neutral or dissatisfied +87629,65722,Female,Loyal Customer,52,Business travel,Business,1781,1,1,1,1,2,5,5,4,4,4,4,5,4,4,49,39.0,satisfied +87630,17453,Female,disloyal Customer,27,Business travel,Eco Plus,376,4,4,4,4,2,4,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +87631,100184,Female,Loyal Customer,25,Personal Travel,Eco,725,3,4,3,1,2,3,2,2,2,5,5,4,5,2,14,7.0,neutral or dissatisfied +87632,10127,Male,Loyal Customer,20,Business travel,Business,3163,2,2,2,2,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +87633,69339,Male,disloyal Customer,23,Business travel,Eco,1096,2,2,2,3,3,2,3,3,1,5,3,4,4,3,19,51.0,neutral or dissatisfied +87634,56892,Female,Loyal Customer,31,Business travel,Business,2565,1,1,1,1,4,4,4,3,5,4,4,4,5,4,25,22.0,satisfied +87635,12148,Male,disloyal Customer,37,Business travel,Eco,1214,4,4,4,3,2,4,2,2,3,3,3,5,3,2,0,0.0,neutral or dissatisfied +87636,69408,Male,Loyal Customer,64,Business travel,Business,3149,3,5,5,5,4,4,3,3,3,3,3,1,3,3,61,74.0,neutral or dissatisfied +87637,7512,Male,Loyal Customer,44,Business travel,Business,2520,4,4,4,4,2,4,5,4,4,5,4,3,4,3,75,60.0,satisfied +87638,56278,Female,Loyal Customer,57,Business travel,Business,2227,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +87639,27497,Male,Loyal Customer,50,Business travel,Business,2592,1,5,5,5,2,4,4,1,1,1,1,2,1,3,12,16.0,neutral or dissatisfied +87640,106839,Male,Loyal Customer,42,Business travel,Eco,1733,3,4,4,4,3,3,3,3,2,2,3,1,3,3,8,15.0,neutral or dissatisfied +87641,96077,Female,Loyal Customer,36,Personal Travel,Eco,583,4,4,4,4,1,4,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +87642,37806,Male,Loyal Customer,63,Personal Travel,Eco Plus,1076,3,4,3,3,3,3,3,3,3,2,4,5,4,3,18,20.0,neutral or dissatisfied +87643,64467,Female,disloyal Customer,20,Business travel,Business,469,5,0,5,4,4,5,4,4,4,3,4,3,5,4,0,0.0,satisfied +87644,33738,Male,Loyal Customer,25,Business travel,Eco Plus,759,0,5,0,1,5,0,4,5,2,3,2,4,5,5,0,1.0,satisfied +87645,57696,Female,Loyal Customer,58,Business travel,Eco,867,3,2,2,2,1,2,2,3,3,3,3,4,3,4,5,0.0,neutral or dissatisfied +87646,61954,Male,Loyal Customer,45,Business travel,Eco,2161,3,2,2,2,3,3,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +87647,52537,Male,Loyal Customer,40,Business travel,Business,3675,2,2,2,2,2,1,1,5,5,5,5,4,5,3,0,0.0,satisfied +87648,40855,Female,Loyal Customer,60,Personal Travel,Eco,501,1,4,1,3,3,5,4,4,4,1,2,4,4,3,74,60.0,neutral or dissatisfied +87649,104435,Female,Loyal Customer,11,Personal Travel,Eco,1147,4,1,4,3,3,4,3,3,3,1,1,3,2,3,0,0.0,neutral or dissatisfied +87650,56150,Male,Loyal Customer,45,Business travel,Business,1400,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,18.0,satisfied +87651,79364,Male,Loyal Customer,30,Personal Travel,Eco Plus,1020,3,4,3,3,4,3,4,4,4,1,3,2,3,4,18,1.0,neutral or dissatisfied +87652,33161,Male,disloyal Customer,14,Personal Travel,Eco,163,4,5,4,3,2,4,2,2,3,3,4,4,5,2,0,0.0,neutral or dissatisfied +87653,115721,Female,disloyal Customer,66,Business travel,Eco,372,2,1,2,2,5,2,5,5,1,3,2,2,3,5,17,9.0,neutral or dissatisfied +87654,50927,Male,Loyal Customer,23,Personal Travel,Eco,190,3,4,3,2,5,3,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +87655,108910,Female,Loyal Customer,46,Business travel,Business,1066,3,5,5,5,4,3,3,3,3,3,3,4,3,3,15,5.0,neutral or dissatisfied +87656,5074,Male,disloyal Customer,21,Business travel,Eco,223,4,5,4,4,5,4,5,5,5,3,5,4,5,5,0,4.0,neutral or dissatisfied +87657,99791,Female,Loyal Customer,54,Business travel,Business,584,5,5,3,5,5,4,5,5,5,5,5,5,5,3,26,53.0,satisfied +87658,15800,Male,Loyal Customer,13,Personal Travel,Eco,246,5,4,5,1,2,5,2,2,5,3,5,4,5,2,1,0.0,satisfied +87659,113526,Female,Loyal Customer,59,Business travel,Business,407,5,5,5,5,2,5,5,4,4,4,4,4,4,5,1,0.0,satisfied +87660,76439,Male,Loyal Customer,56,Personal Travel,Eco,405,4,3,4,1,1,4,1,1,5,4,1,1,4,1,0,0.0,satisfied +87661,123578,Male,Loyal Customer,37,Business travel,Business,3640,3,4,4,4,4,4,3,3,3,3,3,2,3,2,4,0.0,neutral or dissatisfied +87662,83751,Male,Loyal Customer,57,Business travel,Business,783,1,1,4,1,4,3,3,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +87663,11471,Male,Loyal Customer,36,Business travel,Eco Plus,458,3,1,1,1,3,3,3,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +87664,91852,Female,Loyal Customer,27,Personal Travel,Eco,1619,2,4,2,4,4,2,3,4,5,3,5,4,4,4,42,14.0,neutral or dissatisfied +87665,59927,Female,Loyal Customer,41,Business travel,Business,3571,2,2,3,2,2,5,5,4,4,4,4,4,4,5,13,52.0,satisfied +87666,80814,Female,Loyal Customer,56,Business travel,Business,1529,4,1,2,2,1,2,3,4,4,4,4,2,4,2,63,58.0,neutral or dissatisfied +87667,10517,Male,Loyal Customer,48,Business travel,Business,3198,3,3,5,3,4,4,5,5,5,5,4,5,5,3,1,2.0,satisfied +87668,6916,Male,Loyal Customer,65,Personal Travel,Eco,265,1,5,0,3,2,0,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +87669,90255,Male,disloyal Customer,29,Business travel,Business,773,5,5,5,1,2,5,2,2,4,4,4,3,4,2,0,0.0,satisfied +87670,112806,Male,Loyal Customer,15,Personal Travel,Business,1476,1,5,1,2,5,1,5,5,5,2,3,4,5,5,33,3.0,neutral or dissatisfied +87671,5682,Male,disloyal Customer,36,Business travel,Business,436,3,3,3,3,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +87672,53979,Male,Loyal Customer,66,Personal Travel,Eco,1325,2,4,2,2,1,2,1,1,4,2,4,5,5,1,78,68.0,neutral or dissatisfied +87673,54343,Female,Loyal Customer,36,Business travel,Eco Plus,1597,4,3,3,3,4,4,4,4,2,3,5,4,2,4,0,0.0,satisfied +87674,105670,Male,Loyal Customer,56,Business travel,Eco,919,3,5,5,5,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +87675,100809,Male,Loyal Customer,60,Personal Travel,Eco,872,4,0,4,4,3,4,3,3,5,5,4,5,5,3,77,89.0,neutral or dissatisfied +87676,93854,Male,Loyal Customer,33,Personal Travel,Eco Plus,391,3,4,3,3,5,3,5,5,3,3,4,3,5,5,2,5.0,neutral or dissatisfied +87677,79002,Female,Loyal Customer,32,Business travel,Business,331,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +87678,59376,Male,Loyal Customer,36,Business travel,Eco,838,4,3,3,3,4,4,4,4,2,5,5,5,2,4,0,0.0,satisfied +87679,95824,Male,Loyal Customer,58,Business travel,Business,1428,3,5,5,5,2,2,3,3,3,3,3,2,3,3,54,42.0,neutral or dissatisfied +87680,66699,Female,Loyal Customer,49,Business travel,Eco,802,3,4,4,4,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +87681,88140,Female,Loyal Customer,60,Business travel,Business,1605,1,1,1,1,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +87682,468,Female,Loyal Customer,51,Business travel,Business,1568,5,5,5,5,3,5,4,4,4,4,5,5,4,5,0,0.0,satisfied +87683,47134,Female,disloyal Customer,22,Business travel,Eco,965,4,4,4,3,2,4,2,2,3,2,4,4,1,2,0,0.0,satisfied +87684,113418,Male,Loyal Customer,43,Business travel,Business,3249,3,3,3,3,4,5,5,4,4,4,5,4,4,5,39,36.0,satisfied +87685,115988,Male,Loyal Customer,70,Personal Travel,Eco,342,2,4,2,3,2,2,2,2,1,1,3,2,4,2,3,0.0,neutral or dissatisfied +87686,84450,Male,disloyal Customer,62,Business travel,Business,290,2,2,2,3,2,2,2,2,3,3,3,2,2,2,0,0.0,neutral or dissatisfied +87687,47983,Female,Loyal Customer,53,Personal Travel,Eco,315,3,4,3,5,4,3,1,1,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +87688,86195,Female,Loyal Customer,46,Business travel,Business,2082,3,3,3,3,1,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +87689,12386,Female,Loyal Customer,51,Business travel,Business,190,3,2,2,2,5,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +87690,92026,Male,Loyal Customer,43,Business travel,Business,1576,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +87691,36089,Male,Loyal Customer,16,Personal Travel,Eco,413,3,4,3,1,5,3,2,5,4,2,4,3,5,5,12,20.0,neutral or dissatisfied +87692,42414,Male,Loyal Customer,60,Business travel,Eco Plus,329,1,1,1,1,1,1,1,1,3,5,4,1,4,1,0,0.0,neutral or dissatisfied +87693,28286,Female,Loyal Customer,55,Business travel,Business,867,2,2,3,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +87694,99539,Male,disloyal Customer,26,Business travel,Business,829,4,4,4,5,5,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +87695,74974,Female,Loyal Customer,20,Personal Travel,Eco,2475,2,3,3,1,2,3,2,2,5,4,3,2,2,2,0,0.0,neutral or dissatisfied +87696,60456,Female,Loyal Customer,51,Business travel,Business,775,2,2,2,2,5,5,5,5,5,5,5,5,5,3,12,17.0,satisfied +87697,6175,Female,Loyal Customer,15,Personal Travel,Eco,409,3,4,3,4,1,3,1,1,3,2,4,3,3,1,68,62.0,neutral or dissatisfied +87698,93291,Male,Loyal Customer,41,Personal Travel,Eco,867,2,4,2,3,5,2,5,5,3,5,1,2,2,5,13,0.0,neutral or dissatisfied +87699,80229,Male,Loyal Customer,34,Business travel,Business,2153,3,3,3,3,5,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +87700,56721,Male,Loyal Customer,24,Personal Travel,Eco,1085,2,4,2,3,1,2,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +87701,13273,Female,Loyal Customer,37,Personal Travel,Eco,771,2,4,2,4,3,2,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +87702,13936,Female,Loyal Customer,47,Business travel,Business,3031,2,5,4,4,5,3,3,2,2,2,2,2,2,2,9,8.0,neutral or dissatisfied +87703,117619,Female,Loyal Customer,62,Business travel,Business,472,4,4,4,4,1,4,3,4,4,4,4,2,4,1,9,1.0,neutral or dissatisfied +87704,45259,Male,Loyal Customer,24,Personal Travel,Eco,584,3,4,4,2,4,4,4,4,5,2,4,3,5,4,0,11.0,neutral or dissatisfied +87705,2969,Male,Loyal Customer,35,Business travel,Business,3373,1,1,1,1,4,5,5,2,2,2,2,4,2,5,1,0.0,satisfied +87706,63362,Male,Loyal Customer,17,Personal Travel,Eco,337,4,4,4,5,1,4,1,1,4,2,5,5,5,1,0,0.0,satisfied +87707,79548,Female,Loyal Customer,42,Business travel,Eco,762,3,4,4,4,3,4,4,3,3,3,3,4,3,1,21,38.0,neutral or dissatisfied +87708,114042,Male,Loyal Customer,60,Business travel,Business,2297,4,4,4,4,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +87709,22425,Male,Loyal Customer,38,Personal Travel,Eco,238,2,4,0,3,3,0,3,3,5,5,5,3,5,3,96,92.0,neutral or dissatisfied +87710,128909,Female,disloyal Customer,55,Business travel,Business,923,3,3,3,1,1,3,3,1,5,2,4,5,5,1,0,0.0,satisfied +87711,15606,Female,disloyal Customer,18,Business travel,Eco,229,4,4,4,4,4,4,4,4,1,4,4,1,4,4,0,0.0,neutral or dissatisfied +87712,83936,Female,Loyal Customer,57,Business travel,Business,373,1,1,1,1,4,5,5,5,5,5,5,5,5,3,0,11.0,satisfied +87713,56702,Male,Loyal Customer,36,Personal Travel,Eco,1068,4,5,4,2,3,4,3,3,5,4,5,3,5,3,14,1.0,satisfied +87714,32128,Female,Loyal Customer,50,Business travel,Eco,163,5,4,4,4,4,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +87715,58220,Male,Loyal Customer,19,Personal Travel,Eco,925,1,5,1,5,3,1,5,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +87716,116743,Female,Loyal Customer,67,Personal Travel,Eco Plus,342,2,4,2,4,2,4,4,1,1,2,1,4,1,3,40,35.0,neutral or dissatisfied +87717,20935,Female,Loyal Customer,51,Business travel,Eco,851,2,1,4,1,3,3,4,1,1,2,1,2,1,4,65,74.0,neutral or dissatisfied +87718,87116,Male,Loyal Customer,69,Personal Travel,Eco,645,1,2,1,3,2,1,3,2,4,3,3,4,3,2,50,36.0,neutral or dissatisfied +87719,45044,Female,Loyal Customer,25,Business travel,Eco,342,5,4,4,4,5,5,5,5,3,1,2,4,1,5,37,33.0,satisfied +87720,116759,Male,Loyal Customer,23,Personal Travel,Eco Plus,362,3,5,3,4,2,3,4,2,5,5,5,5,4,2,7,1.0,neutral or dissatisfied +87721,55019,Male,Loyal Customer,54,Business travel,Business,1897,5,5,5,5,4,5,5,3,4,4,5,5,3,5,205,191.0,satisfied +87722,123497,Female,Loyal Customer,60,Business travel,Eco,2296,4,2,5,5,3,2,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +87723,92912,Male,disloyal Customer,24,Business travel,Eco,134,3,4,3,2,3,3,3,3,3,5,5,4,5,3,16,5.0,neutral or dissatisfied +87724,92088,Female,disloyal Customer,28,Business travel,Eco,1266,2,2,2,3,4,2,4,4,2,2,3,2,2,4,0,0.0,neutral or dissatisfied +87725,116913,Female,Loyal Customer,43,Business travel,Business,370,4,4,4,4,5,5,5,4,4,4,4,3,4,5,41,37.0,satisfied +87726,101465,Male,Loyal Customer,50,Business travel,Business,2210,1,1,1,1,2,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +87727,117388,Male,Loyal Customer,46,Business travel,Business,3631,1,5,5,5,2,3,4,1,1,2,1,1,1,4,3,8.0,neutral or dissatisfied +87728,1121,Male,Loyal Customer,47,Personal Travel,Eco,282,0,2,0,3,2,0,2,2,2,2,2,4,2,2,0,0.0,satisfied +87729,25130,Female,Loyal Customer,37,Business travel,Eco,1249,5,2,2,2,5,5,5,5,2,2,4,3,4,5,0,10.0,satisfied +87730,57205,Female,disloyal Customer,38,Business travel,Business,1514,5,5,5,4,3,5,3,3,5,3,5,3,5,3,0,1.0,satisfied +87731,30226,Male,disloyal Customer,47,Business travel,Eco,896,1,1,1,5,1,4,4,1,3,1,3,4,2,4,196,189.0,neutral or dissatisfied +87732,100105,Male,Loyal Customer,45,Business travel,Business,3879,2,2,3,2,4,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +87733,60270,Male,Loyal Customer,41,Business travel,Business,2446,3,3,3,3,5,5,5,5,3,5,5,5,5,5,1,2.0,satisfied +87734,15270,Female,Loyal Customer,54,Business travel,Business,460,5,5,3,5,2,4,3,4,4,5,4,1,4,5,0,0.0,satisfied +87735,20084,Male,disloyal Customer,28,Business travel,Eco,843,1,1,1,1,4,1,4,4,5,3,3,3,2,4,0,0.0,neutral or dissatisfied +87736,66332,Female,disloyal Customer,36,Business travel,Eco Plus,452,2,2,2,3,3,2,3,3,3,5,3,2,3,3,14,34.0,neutral or dissatisfied +87737,819,Female,Loyal Customer,43,Business travel,Business,102,3,3,3,3,3,5,4,4,4,4,5,3,4,3,39,48.0,satisfied +87738,73538,Male,Loyal Customer,25,Business travel,Business,594,3,2,2,2,3,3,3,3,1,2,3,4,4,3,19,10.0,neutral or dissatisfied +87739,69316,Male,Loyal Customer,39,Business travel,Eco,1035,2,4,4,4,2,3,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +87740,44170,Male,Loyal Customer,54,Personal Travel,Business,157,2,4,0,3,3,5,4,1,1,0,1,3,1,4,76,69.0,neutral or dissatisfied +87741,14838,Male,Loyal Customer,31,Business travel,Business,3563,1,1,1,1,5,5,5,5,2,5,2,3,1,5,0,0.0,satisfied +87742,39542,Female,Loyal Customer,56,Business travel,Business,679,4,4,4,4,1,1,1,5,5,5,5,1,5,5,90,106.0,satisfied +87743,33365,Male,Loyal Customer,48,Business travel,Business,1972,1,1,1,1,1,1,1,4,4,4,4,5,4,2,0,0.0,satisfied +87744,69506,Male,disloyal Customer,17,Business travel,Eco,1746,1,1,1,4,5,1,5,5,3,5,4,2,3,5,15,23.0,neutral or dissatisfied +87745,58458,Female,disloyal Customer,20,Business travel,Eco,733,1,1,1,1,1,1,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +87746,69897,Female,Loyal Customer,46,Business travel,Business,1514,2,2,4,2,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +87747,4566,Male,Loyal Customer,20,Personal Travel,Eco,561,2,3,2,2,5,2,5,5,1,1,2,4,5,5,0,0.0,neutral or dissatisfied +87748,42827,Female,Loyal Customer,49,Business travel,Eco,328,4,1,1,1,4,5,2,3,3,4,3,1,3,4,0,0.0,satisfied +87749,108093,Female,disloyal Customer,36,Business travel,Business,997,3,3,3,5,2,3,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +87750,121309,Female,Loyal Customer,29,Business travel,Business,1009,3,3,3,3,3,3,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +87751,3257,Male,Loyal Customer,75,Business travel,Business,419,3,3,3,3,3,3,3,2,3,3,3,3,2,3,79,158.0,neutral or dissatisfied +87752,82771,Male,Loyal Customer,69,Business travel,Eco Plus,409,3,2,4,2,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +87753,81044,Female,Loyal Customer,20,Business travel,Business,2965,3,3,3,3,4,4,4,4,4,3,5,3,4,4,0,8.0,satisfied +87754,84406,Male,Loyal Customer,42,Personal Travel,Eco,591,3,4,3,3,2,3,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +87755,120272,Female,Loyal Customer,60,Business travel,Business,1576,2,2,1,2,5,5,4,5,5,5,5,3,5,4,77,74.0,satisfied +87756,46243,Male,disloyal Customer,30,Business travel,Eco,524,3,4,3,4,2,3,2,2,1,5,3,3,3,2,42,36.0,neutral or dissatisfied +87757,74662,Female,Loyal Customer,45,Personal Travel,Eco,1171,1,4,1,2,5,4,4,2,2,1,2,4,2,5,0,0.0,neutral or dissatisfied +87758,34337,Male,Loyal Customer,52,Business travel,Eco,846,2,2,4,2,2,2,2,2,3,3,2,4,3,2,13,6.0,neutral or dissatisfied +87759,26203,Female,Loyal Customer,47,Business travel,Eco,581,4,3,3,3,4,2,5,4,4,4,4,1,4,4,0,0.0,satisfied +87760,112352,Male,Loyal Customer,28,Business travel,Business,2787,2,4,2,2,5,5,5,5,2,4,5,5,4,5,130,145.0,satisfied +87761,126146,Male,disloyal Customer,9,Business travel,Eco,507,0,0,0,4,5,0,5,5,4,5,5,4,4,5,0,0.0,satisfied +87762,52687,Female,Loyal Customer,60,Personal Travel,Eco,160,2,5,0,2,3,5,4,3,3,0,3,5,3,5,0,0.0,neutral or dissatisfied +87763,73394,Male,Loyal Customer,25,Business travel,Business,1005,3,2,2,2,3,3,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +87764,41800,Female,Loyal Customer,26,Business travel,Business,3228,4,4,4,4,5,5,5,5,4,2,1,5,2,5,0,7.0,satisfied +87765,63834,Male,Loyal Customer,50,Business travel,Business,2146,2,2,1,2,4,4,5,5,5,5,5,4,5,4,0,19.0,satisfied +87766,7652,Female,Loyal Customer,23,Business travel,Business,2828,5,5,3,5,3,3,3,3,3,2,5,4,4,3,0,0.0,satisfied +87767,23066,Female,Loyal Customer,61,Personal Travel,Eco,820,3,4,3,3,2,3,3,5,5,3,5,2,5,4,15,6.0,neutral or dissatisfied +87768,65337,Female,disloyal Customer,27,Business travel,Eco,432,1,2,1,4,2,1,5,2,3,5,3,1,3,2,86,74.0,neutral or dissatisfied +87769,119681,Female,Loyal Customer,64,Personal Travel,Business,1325,4,4,4,4,3,4,4,1,1,4,1,4,1,3,0,0.0,satisfied +87770,83739,Female,Loyal Customer,40,Business travel,Business,2742,3,3,3,3,3,4,4,4,4,4,4,3,4,3,26,8.0,satisfied +87771,96465,Male,Loyal Customer,55,Business travel,Business,1759,1,1,3,1,4,4,5,4,4,4,4,4,4,3,39,36.0,satisfied +87772,50435,Male,disloyal Customer,21,Business travel,Eco,109,4,4,5,3,3,5,3,3,2,3,3,5,2,3,0,0.0,neutral or dissatisfied +87773,48946,Female,Loyal Customer,41,Business travel,Eco,156,5,1,1,1,5,5,5,5,5,1,4,5,3,5,0,0.0,satisfied +87774,78643,Male,Loyal Customer,45,Business travel,Business,2172,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +87775,41164,Female,Loyal Customer,12,Personal Travel,Eco,667,1,4,2,3,5,2,5,5,3,4,4,4,3,5,0,0.0,neutral or dissatisfied +87776,53644,Female,Loyal Customer,43,Personal Travel,Eco,1874,3,3,3,4,4,4,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +87777,57909,Female,Loyal Customer,49,Personal Travel,Eco,305,1,3,1,1,2,5,4,5,5,1,5,5,5,2,23,24.0,neutral or dissatisfied +87778,89477,Male,Loyal Customer,31,Personal Travel,Eco,1066,3,5,3,1,5,3,5,5,5,2,5,3,4,5,33,54.0,neutral or dissatisfied +87779,89634,Male,disloyal Customer,25,Business travel,Eco,1010,2,2,2,3,4,2,4,4,4,3,3,1,3,4,103,87.0,neutral or dissatisfied +87780,9151,Male,Loyal Customer,17,Personal Travel,Eco,227,2,5,2,3,2,1,1,3,3,4,4,1,5,1,273,358.0,neutral or dissatisfied +87781,117400,Female,Loyal Customer,67,Personal Travel,Eco,544,1,4,1,1,4,4,2,2,2,1,2,3,2,4,9,7.0,neutral or dissatisfied +87782,100798,Male,Loyal Customer,47,Business travel,Business,2528,4,1,1,1,4,4,4,4,4,4,4,4,4,3,48,81.0,neutral or dissatisfied +87783,92243,Female,Loyal Customer,72,Business travel,Eco,1670,4,2,2,2,2,2,4,5,5,4,5,2,5,4,0,0.0,neutral or dissatisfied +87784,53623,Male,Loyal Customer,49,Business travel,Business,1874,4,4,4,4,4,4,4,2,3,4,4,4,2,4,198,202.0,satisfied +87785,88271,Female,Loyal Customer,56,Business travel,Business,404,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +87786,39477,Male,Loyal Customer,55,Business travel,Eco,867,4,5,5,5,4,4,4,4,3,5,5,3,1,4,9,0.0,satisfied +87787,123040,Male,disloyal Customer,23,Business travel,Eco,631,5,0,5,1,2,5,2,2,3,3,5,4,4,2,19,22.0,satisfied +87788,128922,Female,Loyal Customer,52,Business travel,Business,236,4,4,4,4,2,4,4,5,5,5,5,3,5,4,45,37.0,satisfied +87789,63350,Female,Loyal Customer,69,Personal Travel,Eco,372,0,5,0,4,4,5,4,1,1,0,1,3,1,3,5,0.0,satisfied +87790,8948,Male,Loyal Customer,19,Personal Travel,Eco,328,3,5,3,4,3,3,1,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +87791,22895,Male,Loyal Customer,67,Business travel,Eco Plus,170,4,4,4,4,4,4,4,4,1,4,4,1,4,4,0,0.0,satisfied +87792,6713,Male,Loyal Customer,62,Personal Travel,Eco,438,3,3,3,3,5,3,5,5,1,1,3,3,3,5,0,1.0,neutral or dissatisfied +87793,7563,Female,Loyal Customer,51,Business travel,Business,3590,5,5,5,5,2,4,5,5,5,5,5,5,5,5,0,3.0,satisfied +87794,4990,Female,Loyal Customer,7,Business travel,Business,502,4,2,2,2,4,4,4,4,4,2,4,3,3,4,17,2.0,neutral or dissatisfied +87795,4986,Male,Loyal Customer,44,Business travel,Business,2106,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +87796,13667,Female,disloyal Customer,20,Business travel,Eco,462,2,3,3,4,4,3,4,4,2,3,4,2,4,4,9,2.0,neutral or dissatisfied +87797,76181,Male,Loyal Customer,35,Business travel,Business,2422,3,3,3,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +87798,11063,Male,Loyal Customer,12,Personal Travel,Eco,316,3,5,4,2,1,4,1,1,1,5,2,4,4,1,1,0.0,neutral or dissatisfied +87799,52615,Male,disloyal Customer,33,Business travel,Eco,119,2,2,2,4,4,2,2,4,3,3,4,3,3,4,34,15.0,neutral or dissatisfied +87800,25866,Female,Loyal Customer,27,Business travel,Eco Plus,692,4,1,1,1,4,4,4,4,1,3,1,4,5,4,14,20.0,satisfied +87801,129157,Female,Loyal Customer,25,Business travel,Business,679,2,1,1,1,2,2,2,2,1,2,3,3,3,2,102,90.0,neutral or dissatisfied +87802,6463,Male,Loyal Customer,64,Business travel,Eco Plus,296,2,3,3,3,2,2,2,2,2,3,3,2,4,2,0,17.0,neutral or dissatisfied +87803,71640,Female,Loyal Customer,23,Personal Travel,Eco,1182,4,5,4,5,3,4,3,3,5,5,3,5,4,3,0,0.0,neutral or dissatisfied +87804,111493,Male,Loyal Customer,31,Business travel,Business,3958,2,2,2,2,4,4,4,4,4,5,5,5,5,4,38,31.0,satisfied +87805,108743,Female,disloyal Customer,23,Business travel,Eco,515,1,4,1,4,5,1,5,5,4,4,5,4,4,5,3,0.0,neutral or dissatisfied +87806,112809,Male,Loyal Customer,47,Business travel,Business,1390,4,4,4,4,5,5,4,4,4,4,4,5,4,4,26,5.0,satisfied +87807,91207,Female,Loyal Customer,21,Personal Travel,Eco,223,2,5,2,3,1,2,1,1,5,3,4,3,4,1,19,21.0,neutral or dissatisfied +87808,99795,Male,Loyal Customer,31,Business travel,Business,584,2,4,4,4,2,2,2,2,2,5,3,4,4,2,0,14.0,neutral or dissatisfied +87809,122179,Female,Loyal Customer,40,Business travel,Business,546,4,4,4,4,4,4,4,5,5,5,5,3,5,3,3,0.0,satisfied +87810,71182,Female,Loyal Customer,60,Personal Travel,Business,733,2,2,2,3,4,3,4,2,2,2,1,3,2,1,3,0.0,neutral or dissatisfied +87811,61069,Female,Loyal Customer,51,Business travel,Business,1546,1,1,1,1,2,4,4,4,4,4,4,5,4,4,32,14.0,satisfied +87812,101449,Male,Loyal Customer,45,Business travel,Business,1591,4,4,4,4,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +87813,79705,Female,Loyal Customer,23,Personal Travel,Eco,762,3,5,3,3,1,3,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +87814,12512,Male,disloyal Customer,21,Business travel,Eco,190,1,0,1,4,2,1,2,2,3,4,2,3,4,2,0,0.0,neutral or dissatisfied +87815,126347,Male,Loyal Customer,32,Personal Travel,Eco,631,3,5,3,1,2,3,3,2,3,4,3,4,3,2,14,20.0,neutral or dissatisfied +87816,28659,Male,Loyal Customer,10,Personal Travel,Eco,2355,3,5,3,4,1,3,2,1,5,5,3,5,3,1,4,0.0,neutral or dissatisfied +87817,87143,Male,Loyal Customer,55,Business travel,Eco Plus,640,3,1,1,1,3,3,3,3,1,5,4,2,3,3,0,0.0,neutral or dissatisfied +87818,96210,Female,Loyal Customer,34,Business travel,Eco,460,3,4,4,4,3,3,3,3,4,5,4,2,3,3,76,72.0,neutral or dissatisfied +87819,119288,Female,Loyal Customer,59,Business travel,Business,2774,0,5,0,1,5,5,4,3,3,3,3,5,3,4,0,1.0,satisfied +87820,31469,Male,Loyal Customer,25,Business travel,Business,853,5,5,5,5,4,4,4,4,1,5,3,1,5,4,41,33.0,satisfied +87821,2744,Male,Loyal Customer,40,Business travel,Business,2969,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,5.0,satisfied +87822,5211,Female,Loyal Customer,62,Business travel,Business,3139,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +87823,19393,Female,Loyal Customer,50,Business travel,Eco Plus,844,5,1,1,1,1,3,1,4,4,5,4,2,4,4,0,0.0,satisfied +87824,22269,Male,Loyal Customer,34,Business travel,Eco,143,4,5,3,5,4,4,4,4,3,2,4,2,4,4,0,0.0,satisfied +87825,67538,Female,Loyal Customer,43,Business travel,Business,3051,2,3,3,3,3,2,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +87826,95001,Male,Loyal Customer,23,Personal Travel,Eco,319,3,3,3,4,4,3,4,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +87827,108060,Male,disloyal Customer,46,Business travel,Business,1166,1,1,1,2,3,1,3,3,5,4,5,3,5,3,15,1.0,neutral or dissatisfied +87828,44297,Female,Loyal Customer,29,Personal Travel,Eco,563,1,3,1,4,2,1,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +87829,62525,Male,Loyal Customer,39,Business travel,Business,1744,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +87830,36836,Male,Loyal Customer,47,Business travel,Eco,369,5,3,5,5,5,5,5,5,3,4,2,2,2,5,7,10.0,satisfied +87831,112210,Male,Loyal Customer,45,Business travel,Business,1199,5,5,5,5,5,5,5,5,5,5,5,5,5,3,22,15.0,satisfied +87832,123208,Female,Loyal Customer,43,Personal Travel,Eco,468,3,4,3,2,5,4,5,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +87833,61017,Female,Loyal Customer,17,Business travel,Business,3365,1,1,1,1,1,1,1,3,4,4,4,1,2,1,82,84.0,neutral or dissatisfied +87834,55023,Male,Loyal Customer,56,Business travel,Business,1608,2,2,4,2,4,3,5,4,4,4,4,4,4,3,0,0.0,satisfied +87835,64578,Female,Loyal Customer,48,Business travel,Business,3390,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +87836,33457,Female,Loyal Customer,9,Personal Travel,Eco,2409,1,4,1,4,1,3,3,3,3,3,4,3,2,3,0,50.0,neutral or dissatisfied +87837,61723,Male,Loyal Customer,53,Business travel,Business,1635,3,2,2,2,4,2,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +87838,89278,Male,Loyal Customer,46,Business travel,Business,3688,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +87839,103742,Male,Loyal Customer,33,Personal Travel,Eco,466,2,4,2,3,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +87840,43475,Female,Loyal Customer,36,Business travel,Business,1500,1,5,4,5,1,1,1,4,4,2,3,1,2,1,106,139.0,neutral or dissatisfied +87841,126733,Male,Loyal Customer,62,Business travel,Business,2521,2,5,5,5,5,3,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +87842,48848,Male,Loyal Customer,15,Personal Travel,Business,308,3,1,3,1,4,3,4,4,1,3,1,2,2,4,0,0.0,neutral or dissatisfied +87843,121657,Male,Loyal Customer,53,Business travel,Business,328,0,0,0,4,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +87844,63044,Female,Loyal Customer,37,Personal Travel,Eco,967,0,5,0,4,2,0,2,2,5,4,4,5,4,2,7,0.0,satisfied +87845,39426,Male,Loyal Customer,45,Business travel,Business,129,1,1,1,1,1,3,5,4,4,4,3,3,4,5,32,45.0,satisfied +87846,83862,Female,Loyal Customer,64,Personal Travel,Eco,425,3,4,3,5,3,5,5,5,2,4,5,5,5,5,186,195.0,neutral or dissatisfied +87847,52712,Female,Loyal Customer,8,Personal Travel,Eco,1162,3,4,3,3,4,3,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +87848,122750,Male,Loyal Customer,26,Personal Travel,Eco,651,3,4,3,2,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +87849,28758,Male,Loyal Customer,35,Business travel,Eco,1024,2,3,3,3,2,2,2,2,2,1,3,2,3,2,0,0.0,neutral or dissatisfied +87850,95490,Male,Loyal Customer,39,Business travel,Business,239,3,3,3,3,3,5,5,5,5,5,5,5,5,4,35,24.0,satisfied +87851,15703,Male,disloyal Customer,25,Business travel,Eco,479,3,0,3,5,3,3,3,3,4,5,2,4,2,3,99,109.0,neutral or dissatisfied +87852,90210,Female,Loyal Customer,37,Personal Travel,Eco,1084,1,2,2,3,3,2,3,3,1,2,4,3,4,3,52,40.0,neutral or dissatisfied +87853,21601,Female,Loyal Customer,55,Business travel,Eco,853,4,4,4,4,1,2,4,4,4,4,4,3,4,3,37,31.0,satisfied +87854,107187,Female,disloyal Customer,25,Business travel,Eco,402,2,0,2,5,5,2,5,5,4,2,3,4,5,5,8,3.0,neutral or dissatisfied +87855,84119,Female,Loyal Customer,44,Business travel,Business,1900,2,1,1,1,1,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +87856,93723,Female,disloyal Customer,27,Business travel,Eco,230,2,0,2,4,1,2,1,1,3,3,3,1,5,1,0,0.0,neutral or dissatisfied +87857,26137,Female,Loyal Customer,46,Business travel,Eco,270,4,1,1,1,2,1,3,4,4,4,4,5,4,2,7,4.0,satisfied +87858,52985,Female,Loyal Customer,34,Business travel,Business,1190,4,4,4,4,2,3,3,4,4,4,4,2,4,3,1,20.0,satisfied +87859,29797,Female,Loyal Customer,27,Business travel,Business,3967,5,5,5,5,3,3,3,3,5,4,3,4,3,3,0,0.0,satisfied +87860,87289,Female,Loyal Customer,48,Personal Travel,Eco,577,4,5,4,1,5,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +87861,89561,Female,Loyal Customer,40,Business travel,Business,3415,3,3,3,3,3,4,5,4,4,4,4,3,4,5,17,0.0,satisfied +87862,49172,Male,Loyal Customer,36,Business travel,Eco,209,3,5,3,5,3,3,3,3,1,4,3,5,2,3,0,0.0,satisfied +87863,76545,Female,Loyal Customer,45,Business travel,Business,2398,4,4,4,4,5,5,4,4,4,4,4,3,4,3,0,2.0,satisfied +87864,75999,Male,Loyal Customer,56,Personal Travel,Eco Plus,228,3,1,3,3,3,3,4,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +87865,90334,Female,Loyal Customer,48,Business travel,Business,3416,1,1,1,1,4,4,4,5,5,5,5,4,5,3,8,0.0,satisfied +87866,111609,Male,disloyal Customer,47,Business travel,Business,1014,2,2,2,1,4,2,4,4,3,4,4,5,5,4,3,0.0,neutral or dissatisfied +87867,80542,Female,disloyal Customer,22,Business travel,Eco,816,4,4,4,4,1,4,1,1,4,2,4,3,4,1,0,0.0,satisfied +87868,67436,Female,Loyal Customer,58,Business travel,Eco,321,5,4,4,4,5,2,5,5,5,5,5,4,5,2,0,0.0,satisfied +87869,77473,Female,Loyal Customer,32,Personal Travel,Eco,507,3,4,3,3,2,3,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +87870,78302,Female,Loyal Customer,70,Personal Travel,Eco,1598,2,4,2,1,3,5,5,3,3,2,5,3,3,3,0,0.0,neutral or dissatisfied +87871,51004,Male,Loyal Customer,24,Personal Travel,Eco,262,4,4,4,2,1,4,4,1,1,5,3,3,5,1,0,0.0,neutral or dissatisfied +87872,29644,Female,Loyal Customer,14,Personal Travel,Eco,1448,4,1,4,4,2,4,2,2,2,5,4,1,3,2,0,0.0,satisfied +87873,85513,Female,Loyal Customer,46,Business travel,Business,214,0,5,0,2,5,5,5,3,3,3,2,3,3,4,0,0.0,satisfied +87874,44354,Female,disloyal Customer,29,Business travel,Business,596,2,2,2,3,1,2,1,1,4,4,3,4,3,1,0,7.0,neutral or dissatisfied +87875,47195,Male,Loyal Customer,36,Business travel,Eco,279,5,1,1,1,5,5,5,5,5,2,2,2,3,5,2,0.0,satisfied +87876,11620,Male,Loyal Customer,29,Personal Travel,Eco,772,2,3,2,3,2,2,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +87877,2778,Male,disloyal Customer,44,Business travel,Business,764,1,1,1,3,1,1,1,1,5,3,5,5,4,1,16,26.0,neutral or dissatisfied +87878,86635,Male,Loyal Customer,25,Business travel,Business,2454,1,1,5,1,1,1,1,1,3,2,3,3,4,1,64,44.0,neutral or dissatisfied +87879,92706,Male,Loyal Customer,39,Business travel,Business,2153,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,4.0,satisfied +87880,43639,Female,disloyal Customer,37,Business travel,Eco,1034,5,5,5,1,4,5,4,4,3,3,3,2,3,4,9,0.0,satisfied +87881,57553,Female,disloyal Customer,26,Business travel,Business,1597,2,2,2,3,5,2,5,5,2,4,4,4,3,5,0,17.0,neutral or dissatisfied +87882,110529,Female,Loyal Customer,42,Business travel,Business,551,3,3,3,3,4,4,4,4,4,4,4,5,4,4,65,55.0,satisfied +87883,76753,Female,Loyal Customer,53,Business travel,Business,3162,1,1,1,1,2,4,5,3,3,4,3,4,3,5,0,5.0,satisfied +87884,45621,Female,disloyal Customer,29,Business travel,Eco,260,2,2,3,3,5,3,5,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +87885,98797,Male,Loyal Customer,53,Personal Travel,Eco,630,3,3,3,3,3,3,5,3,1,2,3,2,4,3,4,0.0,neutral or dissatisfied +87886,27133,Male,disloyal Customer,39,Business travel,Business,2640,1,1,1,1,1,3,3,3,1,5,2,3,4,3,2,0.0,neutral or dissatisfied +87887,124358,Female,Loyal Customer,57,Business travel,Business,3351,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,21.0,satisfied +87888,85776,Female,Loyal Customer,45,Business travel,Business,2689,3,3,3,3,5,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +87889,37223,Female,Loyal Customer,60,Business travel,Business,1041,2,2,2,2,5,4,4,4,4,4,4,4,4,3,0,3.0,satisfied +87890,108295,Female,Loyal Customer,44,Business travel,Business,1728,2,2,4,2,4,3,5,4,4,4,4,4,4,5,48,26.0,satisfied +87891,115413,Male,disloyal Customer,37,Business travel,Eco,447,3,3,3,2,1,3,1,1,4,3,2,1,3,1,130,126.0,neutral or dissatisfied +87892,63192,Female,Loyal Customer,47,Business travel,Business,2080,2,2,3,2,5,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +87893,28434,Female,Loyal Customer,50,Business travel,Eco,2496,5,1,1,1,5,5,5,1,5,4,5,5,2,5,35,58.0,satisfied +87894,37161,Female,Loyal Customer,32,Personal Travel,Eco,1046,3,5,2,5,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +87895,120251,Male,Loyal Customer,9,Personal Travel,Eco,1325,4,5,4,3,3,4,5,3,3,5,3,3,5,3,0,0.0,neutral or dissatisfied +87896,95767,Male,Loyal Customer,37,Personal Travel,Eco,181,2,5,2,3,2,2,2,2,5,3,5,2,2,2,36,29.0,neutral or dissatisfied +87897,68367,Female,Loyal Customer,26,Business travel,Business,2546,5,5,5,5,5,5,5,5,5,4,4,3,5,5,19,7.0,satisfied +87898,105594,Male,Loyal Customer,52,Business travel,Business,2942,1,2,1,1,5,5,4,2,2,2,2,5,2,4,1,0.0,satisfied +87899,411,Female,Loyal Customer,49,Business travel,Business,2739,0,5,0,3,2,4,5,4,4,4,2,5,4,4,1,0.0,satisfied +87900,13885,Female,Loyal Customer,57,Personal Travel,Eco,667,3,4,3,1,2,4,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +87901,14809,Male,Loyal Customer,15,Personal Travel,Eco,155,2,5,2,5,1,2,1,1,5,1,3,5,4,1,0,12.0,neutral or dissatisfied +87902,96146,Male,disloyal Customer,23,Business travel,Eco,460,3,0,3,5,3,3,3,3,4,4,5,3,5,3,10,0.0,neutral or dissatisfied +87903,73379,Male,Loyal Customer,67,Business travel,Business,3388,1,1,1,1,4,4,4,1,1,1,1,1,1,3,0,10.0,neutral or dissatisfied +87904,91587,Female,Loyal Customer,44,Business travel,Business,1340,5,5,5,5,4,5,5,5,5,5,5,4,5,4,13,7.0,satisfied +87905,23081,Female,Loyal Customer,44,Business travel,Eco,864,5,4,4,4,3,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +87906,70534,Male,Loyal Customer,46,Business travel,Business,1258,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,,satisfied +87907,117208,Male,Loyal Customer,64,Personal Travel,Eco,325,4,3,4,2,2,4,2,2,4,2,2,3,5,2,17,11.0,neutral or dissatisfied +87908,45222,Male,Loyal Customer,72,Business travel,Business,1779,3,3,3,3,3,3,3,4,5,3,4,3,3,3,290,317.0,neutral or dissatisfied +87909,93464,Male,Loyal Customer,49,Personal Travel,Eco,605,2,4,1,1,3,1,3,3,3,1,3,2,4,3,94,84.0,neutral or dissatisfied +87910,37831,Male,Loyal Customer,24,Business travel,Business,2824,4,4,4,4,4,4,4,4,3,4,3,3,2,4,0,0.0,satisfied +87911,48041,Female,Loyal Customer,36,Business travel,Business,2481,4,4,4,4,5,2,5,4,4,4,4,2,4,1,0,1.0,satisfied +87912,39363,Male,Loyal Customer,33,Business travel,Business,2755,2,2,2,2,2,2,2,2,4,4,4,3,4,2,17,16.0,neutral or dissatisfied +87913,17708,Female,Loyal Customer,42,Business travel,Business,3036,3,3,3,3,2,4,5,5,5,4,5,2,5,1,13,1.0,satisfied +87914,83569,Female,Loyal Customer,22,Business travel,Business,1739,3,5,5,5,3,3,3,3,2,4,3,3,4,3,0,0.0,neutral or dissatisfied +87915,47852,Female,Loyal Customer,48,Business travel,Business,3772,2,2,2,2,1,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +87916,22880,Female,Loyal Customer,23,Personal Travel,Eco,151,2,4,2,5,3,2,3,3,4,2,4,3,5,3,6,0.0,neutral or dissatisfied +87917,129810,Male,Loyal Customer,9,Personal Travel,Eco,337,2,4,2,3,1,2,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +87918,92482,Male,Loyal Customer,25,Business travel,Business,1947,3,1,1,1,3,3,3,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +87919,73659,Female,disloyal Customer,20,Business travel,Business,204,4,0,4,3,1,4,1,1,5,5,4,5,5,1,0,0.0,satisfied +87920,59433,Male,Loyal Customer,57,Business travel,Business,2338,5,5,5,5,5,4,4,2,2,2,2,4,2,4,25,0.0,satisfied +87921,61614,Female,disloyal Customer,24,Business travel,Business,1303,4,0,4,2,5,4,5,5,3,4,4,5,5,5,0,0.0,satisfied +87922,32109,Female,disloyal Customer,39,Business travel,Business,163,4,4,4,3,5,4,5,5,3,1,4,3,5,5,0,3.0,neutral or dissatisfied +87923,85907,Female,disloyal Customer,12,Business travel,Eco,761,3,3,3,3,3,3,3,3,2,4,4,2,4,3,50,59.0,neutral or dissatisfied +87924,34398,Male,disloyal Customer,52,Business travel,Eco,612,3,4,3,3,3,4,4,3,4,4,4,4,4,4,134,129.0,neutral or dissatisfied +87925,59435,Female,Loyal Customer,44,Personal Travel,Eco,746,1,4,1,3,5,1,3,3,3,1,3,4,3,4,7,0.0,neutral or dissatisfied +87926,3846,Male,Loyal Customer,36,Personal Travel,Eco,710,3,4,3,4,5,3,5,5,3,2,5,3,4,5,46,46.0,neutral or dissatisfied +87927,50662,Male,Loyal Customer,17,Personal Travel,Eco,110,0,2,0,4,2,0,2,2,4,4,3,1,4,2,0,0.0,satisfied +87928,106470,Female,disloyal Customer,22,Business travel,Eco,1300,2,2,2,3,3,2,3,3,2,2,3,3,4,3,7,9.0,neutral or dissatisfied +87929,27114,Female,Loyal Customer,24,Business travel,Business,2715,5,5,5,5,2,2,2,3,4,5,5,2,4,2,0,0.0,satisfied +87930,89968,Female,Loyal Customer,21,Personal Travel,Eco,1416,2,2,2,2,3,2,3,3,4,4,3,4,2,3,0,0.0,neutral or dissatisfied +87931,5296,Female,Loyal Customer,18,Personal Travel,Eco,190,3,4,3,3,1,3,1,1,2,4,3,3,4,1,0,2.0,neutral or dissatisfied +87932,29146,Male,Loyal Customer,16,Personal Travel,Eco,697,3,3,3,3,2,3,1,2,1,5,3,2,4,2,0,0.0,neutral or dissatisfied +87933,48654,Male,Loyal Customer,60,Business travel,Business,3457,0,5,0,4,4,5,4,2,2,2,2,3,2,5,6,2.0,satisfied +87934,57821,Female,Loyal Customer,22,Business travel,Eco,622,2,3,3,3,2,2,3,2,1,3,2,2,2,2,7,6.0,neutral or dissatisfied +87935,63302,Female,Loyal Customer,35,Business travel,Business,372,1,0,0,4,3,4,3,1,1,0,4,4,1,4,0,0.0,neutral or dissatisfied +87936,11813,Female,Loyal Customer,55,Business travel,Business,3890,4,4,4,4,5,4,5,3,3,3,3,5,3,5,17,33.0,satisfied +87937,114123,Male,Loyal Customer,32,Personal Travel,Business,846,3,4,3,3,3,3,3,3,2,5,4,1,1,3,24,27.0,neutral or dissatisfied +87938,8635,Male,Loyal Customer,47,Business travel,Business,227,5,5,5,5,2,5,4,4,4,4,4,3,4,5,0,3.0,satisfied +87939,27995,Male,Loyal Customer,64,Personal Travel,Eco,1616,2,4,2,2,4,2,4,4,4,5,5,4,4,4,1,0.0,neutral or dissatisfied +87940,83646,Male,Loyal Customer,53,Business travel,Business,1752,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,5.0,satisfied +87941,41313,Male,Loyal Customer,28,Business travel,Eco,802,4,1,1,1,4,4,4,4,2,1,5,5,2,4,0,0.0,satisfied +87942,42311,Male,Loyal Customer,17,Personal Travel,Eco,726,3,1,3,3,2,3,2,2,2,5,3,2,4,2,26,16.0,neutral or dissatisfied +87943,105729,Female,disloyal Customer,22,Business travel,Business,663,4,0,4,3,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +87944,64645,Male,Loyal Customer,59,Business travel,Business,2813,0,0,0,4,3,5,4,5,5,5,5,3,5,5,5,15.0,satisfied +87945,21453,Male,disloyal Customer,20,Business travel,Eco,433,5,1,5,3,4,5,4,4,3,3,3,4,5,4,0,0.0,satisfied +87946,62022,Male,Loyal Customer,38,Business travel,Eco,2475,4,4,4,4,4,4,4,4,3,1,4,1,4,4,30,9.0,neutral or dissatisfied +87947,97539,Female,Loyal Customer,41,Business travel,Business,675,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +87948,98921,Female,Loyal Customer,44,Business travel,Business,2268,1,1,1,1,5,4,5,4,4,4,4,3,4,3,27,27.0,satisfied +87949,23276,Male,disloyal Customer,59,Business travel,Eco,456,4,5,4,4,3,4,3,3,2,3,3,5,5,3,1,6.0,neutral or dissatisfied +87950,30144,Female,Loyal Customer,17,Personal Travel,Eco,31,2,4,0,3,1,0,1,1,4,3,5,4,5,1,11,11.0,neutral or dissatisfied +87951,103042,Female,Loyal Customer,58,Business travel,Business,460,2,4,4,4,3,4,4,2,2,2,2,4,2,3,29,24.0,neutral or dissatisfied +87952,64331,Male,disloyal Customer,49,Business travel,Business,1192,2,2,2,2,5,2,5,5,4,3,4,4,4,5,17,33.0,neutral or dissatisfied +87953,95690,Male,Loyal Customer,36,Business travel,Business,237,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,15.0,satisfied +87954,45025,Male,disloyal Customer,12,Personal Travel,Eco Plus,118,2,3,2,4,4,2,4,4,4,1,1,1,5,4,24,9.0,neutral or dissatisfied +87955,121382,Male,Loyal Customer,23,Personal Travel,Eco,2279,2,4,2,3,4,2,4,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +87956,60454,Male,Loyal Customer,49,Business travel,Business,3265,4,4,2,4,3,4,5,5,5,5,5,3,5,5,10,0.0,satisfied +87957,39247,Female,Loyal Customer,57,Business travel,Business,1606,4,4,4,4,2,1,2,4,4,4,4,2,4,3,2,0.0,satisfied +87958,128521,Female,disloyal Customer,7,Personal Travel,Eco,370,3,5,3,1,3,3,4,3,5,1,4,3,1,3,0,15.0,neutral or dissatisfied +87959,76090,Female,Loyal Customer,59,Personal Travel,Eco,669,2,5,2,4,5,5,4,4,4,2,4,3,4,4,7,13.0,neutral or dissatisfied +87960,40645,Male,Loyal Customer,66,Personal Travel,Eco Plus,411,3,5,3,4,2,3,2,2,2,3,2,2,5,2,0,0.0,neutral or dissatisfied +87961,18465,Female,Loyal Customer,33,Business travel,Eco,192,4,4,5,4,4,4,4,2,1,5,2,4,1,4,259,257.0,satisfied +87962,121097,Male,Loyal Customer,14,Personal Travel,Eco,1558,2,5,1,4,1,1,1,1,5,3,3,4,4,1,0,4.0,neutral or dissatisfied +87963,85417,Female,Loyal Customer,34,Business travel,Business,2195,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +87964,768,Female,Loyal Customer,52,Business travel,Business,1920,3,2,2,2,4,4,3,3,3,3,3,3,3,3,13,13.0,neutral or dissatisfied +87965,80332,Male,Loyal Customer,35,Personal Travel,Eco,746,2,4,2,5,2,2,2,2,5,2,1,3,4,2,0,0.0,neutral or dissatisfied +87966,1158,Male,Loyal Customer,25,Personal Travel,Eco,158,3,2,3,3,2,3,2,2,1,1,3,1,3,2,92,96.0,neutral or dissatisfied +87967,117545,Male,disloyal Customer,26,Business travel,Business,872,4,4,4,5,5,4,5,5,4,4,4,4,4,5,0,0.0,satisfied +87968,91012,Female,Loyal Customer,59,Personal Travel,Eco,515,3,3,3,4,3,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +87969,81816,Male,disloyal Customer,10,Business travel,Eco,1306,2,2,2,3,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +87970,4270,Female,Loyal Customer,53,Business travel,Business,1820,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,11.0,satisfied +87971,126084,Female,Loyal Customer,55,Business travel,Business,2185,2,2,5,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +87972,22100,Female,Loyal Customer,48,Business travel,Eco Plus,782,5,1,1,1,5,5,5,4,4,3,1,5,5,5,131,120.0,satisfied +87973,48291,Female,Loyal Customer,49,Business travel,Eco,807,4,5,5,5,3,4,1,4,4,4,4,4,4,1,0,0.0,satisfied +87974,74292,Male,Loyal Customer,38,Personal Travel,Eco,2288,1,1,1,3,5,1,5,5,3,3,3,1,4,5,0,0.0,neutral or dissatisfied +87975,41530,Male,Loyal Customer,39,Business travel,Business,1242,3,3,3,3,3,3,3,4,4,4,4,3,4,5,0,2.0,satisfied +87976,69263,Male,Loyal Customer,22,Personal Travel,Eco,733,0,3,0,3,2,3,2,2,5,4,5,2,4,2,0,9.0,satisfied +87977,5746,Female,disloyal Customer,46,Business travel,Business,859,4,4,4,2,1,4,1,1,5,5,4,5,5,1,0,0.0,satisfied +87978,120659,Female,Loyal Customer,52,Business travel,Business,280,5,5,5,5,3,5,5,5,5,5,5,5,5,5,9,4.0,satisfied +87979,11348,Male,Loyal Customer,10,Personal Travel,Eco,224,2,4,2,3,3,2,2,3,5,4,4,3,4,3,8,4.0,neutral or dissatisfied +87980,72087,Female,Loyal Customer,30,Personal Travel,Eco,2556,2,3,2,2,3,2,5,3,1,3,3,4,2,3,13,9.0,neutral or dissatisfied +87981,30153,Female,Loyal Customer,35,Personal Travel,Eco,571,4,5,4,4,4,4,4,4,4,2,5,3,4,4,13,4.0,neutral or dissatisfied +87982,79790,Male,Loyal Customer,51,Business travel,Business,3376,2,2,2,2,2,5,5,5,5,5,5,4,5,5,6,7.0,satisfied +87983,75266,Female,Loyal Customer,53,Personal Travel,Eco,1744,3,5,3,3,5,4,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +87984,97244,Female,Loyal Customer,54,Business travel,Business,3129,3,3,3,3,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +87985,1089,Female,Loyal Customer,46,Personal Travel,Eco,247,3,4,3,1,5,4,4,3,3,3,3,3,3,4,8,6.0,neutral or dissatisfied +87986,115076,Male,disloyal Customer,22,Business travel,Eco,371,2,4,2,2,2,2,2,2,5,2,5,5,4,2,20,34.0,neutral or dissatisfied +87987,87751,Female,disloyal Customer,20,Business travel,Eco,214,2,0,2,2,5,2,5,5,4,2,5,5,4,5,3,13.0,neutral or dissatisfied +87988,66697,Female,disloyal Customer,26,Business travel,Business,802,3,0,3,4,2,3,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +87989,62656,Female,Loyal Customer,58,Personal Travel,Eco,1846,1,5,1,3,3,1,2,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +87990,52458,Male,Loyal Customer,50,Business travel,Eco Plus,261,2,5,5,5,3,2,3,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +87991,48309,Female,Loyal Customer,23,Personal Travel,Eco,1499,1,5,1,3,3,1,3,3,3,4,3,3,5,3,80,82.0,neutral or dissatisfied +87992,78775,Female,Loyal Customer,59,Business travel,Eco,432,3,4,4,4,1,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +87993,1752,Female,Loyal Customer,55,Business travel,Business,2793,5,5,5,5,3,4,5,5,5,5,5,5,5,5,40,56.0,satisfied +87994,63762,Female,Loyal Customer,21,Personal Travel,Eco,2422,4,4,3,4,4,3,4,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +87995,70675,Female,Loyal Customer,29,Business travel,Business,447,1,3,3,3,1,2,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +87996,14106,Male,Loyal Customer,59,Personal Travel,Eco,371,2,5,2,2,3,2,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +87997,31970,Female,Loyal Customer,46,Business travel,Business,163,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +87998,73087,Female,Loyal Customer,48,Personal Travel,Eco,1085,1,4,1,3,2,3,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +87999,19127,Male,Loyal Customer,66,Personal Travel,Eco,323,2,3,2,4,3,2,3,3,3,4,1,2,4,3,0,0.0,neutral or dissatisfied +88000,21304,Male,Loyal Customer,21,Personal Travel,Eco,714,2,4,2,2,1,2,1,1,3,5,4,3,5,1,123,105.0,neutral or dissatisfied +88001,44844,Female,Loyal Customer,23,Business travel,Business,1694,2,2,2,2,5,5,5,5,2,3,2,1,3,5,0,0.0,satisfied +88002,20966,Male,Loyal Customer,57,Business travel,Business,451,3,3,3,3,5,1,3,4,4,4,4,2,4,4,0,0.0,satisfied +88003,4395,Male,Loyal Customer,65,Personal Travel,Eco,473,2,5,2,1,2,5,5,3,5,1,5,5,3,5,146,157.0,neutral or dissatisfied +88004,99431,Female,Loyal Customer,24,Personal Travel,Eco,314,2,2,2,3,2,2,2,2,4,1,3,3,4,2,17,29.0,neutral or dissatisfied +88005,37939,Male,Loyal Customer,40,Personal Travel,Eco,1023,1,4,2,3,4,2,4,4,5,3,5,3,3,4,0,0.0,neutral or dissatisfied +88006,33679,Female,Loyal Customer,39,Business travel,Business,805,4,4,4,4,2,2,2,4,4,4,4,5,4,5,43,66.0,satisfied +88007,124741,Male,Loyal Customer,56,Personal Travel,Eco Plus,399,1,4,1,1,5,1,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +88008,7605,Male,Loyal Customer,48,Business travel,Eco,802,4,1,2,1,4,4,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +88009,114106,Female,Loyal Customer,52,Business travel,Business,819,3,3,5,3,3,4,5,5,5,5,5,3,5,5,6,6.0,satisfied +88010,59547,Male,Loyal Customer,44,Business travel,Business,3447,5,5,4,5,2,5,4,4,4,4,4,3,4,4,64,47.0,satisfied +88011,15553,Female,Loyal Customer,61,Business travel,Business,3634,1,1,5,1,5,1,1,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +88012,59282,Female,disloyal Customer,40,Business travel,Business,3302,1,1,1,3,1,5,2,4,1,3,4,2,1,2,34,19.0,neutral or dissatisfied +88013,54080,Male,disloyal Customer,43,Business travel,Eco,1016,2,2,2,1,1,2,1,1,1,2,3,5,4,1,23,0.0,neutral or dissatisfied +88014,79474,Male,Loyal Customer,50,Business travel,Business,2613,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,1.0,satisfied +88015,13876,Male,Loyal Customer,12,Business travel,Business,3566,1,1,3,1,3,3,3,3,2,1,5,2,5,3,0,2.0,satisfied +88016,107984,Male,Loyal Customer,36,Business travel,Business,271,3,3,3,3,4,4,4,5,5,4,5,5,5,5,38,39.0,satisfied +88017,33681,Female,Loyal Customer,33,Business travel,Business,1663,2,2,2,2,4,4,3,4,4,4,4,5,4,4,0,3.0,satisfied +88018,108677,Female,Loyal Customer,47,Business travel,Business,577,5,5,5,5,4,5,4,5,5,5,5,3,5,5,30,47.0,satisfied +88019,87280,Male,Loyal Customer,36,Business travel,Business,577,2,3,3,3,5,3,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +88020,16965,Male,Loyal Customer,53,Business travel,Eco,195,2,1,1,1,2,2,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +88021,120200,Male,Loyal Customer,34,Business travel,Business,1938,4,4,4,4,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +88022,7139,Female,Loyal Customer,40,Business travel,Business,135,3,3,3,3,2,5,5,4,4,4,5,3,4,4,0,45.0,satisfied +88023,57006,Male,Loyal Customer,27,Personal Travel,Eco,2565,3,0,3,5,3,4,4,5,4,5,5,4,3,4,1,0.0,neutral or dissatisfied +88024,65566,Female,Loyal Customer,37,Business travel,Business,3636,2,2,2,2,4,4,5,5,5,5,4,3,5,4,0,0.0,satisfied +88025,56220,Male,Loyal Customer,41,Business travel,Business,1608,4,4,4,4,4,5,5,5,5,5,5,5,5,3,3,11.0,satisfied +88026,41546,Male,disloyal Customer,25,Business travel,Eco,1070,1,1,1,4,4,1,4,4,2,3,3,2,4,4,75,87.0,neutral or dissatisfied +88027,41893,Male,Loyal Customer,46,Business travel,Business,129,0,4,0,4,3,5,3,5,5,5,5,5,5,2,0,0.0,satisfied +88028,126020,Male,Loyal Customer,40,Business travel,Business,1875,5,5,2,5,3,5,5,1,1,2,1,4,1,5,0,0.0,satisfied +88029,11236,Male,Loyal Customer,16,Personal Travel,Eco,667,5,5,5,5,2,5,2,2,4,4,4,3,5,2,0,0.0,satisfied +88030,24526,Female,Loyal Customer,31,Business travel,Business,892,1,4,4,4,1,1,1,1,1,1,2,1,3,1,0,0.0,neutral or dissatisfied +88031,38425,Female,Loyal Customer,18,Personal Travel,Eco,965,3,5,3,1,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +88032,32573,Male,Loyal Customer,60,Business travel,Business,3753,2,2,2,2,4,3,2,5,5,5,3,3,5,1,0,0.0,satisfied +88033,116429,Female,Loyal Customer,38,Personal Travel,Eco,337,4,3,4,4,1,4,1,1,2,5,5,3,5,1,0,7.0,neutral or dissatisfied +88034,90220,Male,Loyal Customer,7,Personal Travel,Eco,957,2,5,2,1,3,2,3,3,3,2,5,3,5,3,2,5.0,neutral or dissatisfied +88035,125543,Female,Loyal Customer,62,Business travel,Eco,226,2,5,5,5,1,3,3,2,2,2,2,4,2,2,45,31.0,neutral or dissatisfied +88036,97136,Male,disloyal Customer,43,Business travel,Eco,1004,3,3,3,4,3,3,3,3,2,2,2,2,3,3,59,54.0,neutral or dissatisfied +88037,31005,Male,disloyal Customer,21,Business travel,Eco,391,1,1,1,2,4,1,4,4,3,1,2,2,3,4,43,42.0,neutral or dissatisfied +88038,88664,Male,Loyal Customer,51,Personal Travel,Eco,442,1,4,3,3,3,3,3,3,1,4,1,5,2,3,20,17.0,neutral or dissatisfied +88039,103664,Female,Loyal Customer,39,Business travel,Eco,251,3,2,2,2,3,3,3,3,4,2,4,3,4,3,15,18.0,neutral or dissatisfied +88040,93733,Male,Loyal Customer,52,Business travel,Business,2332,4,4,4,4,5,5,5,5,5,5,5,5,5,4,52,57.0,satisfied +88041,64142,Male,Loyal Customer,37,Business travel,Business,989,5,5,5,5,5,5,4,4,4,4,4,4,4,3,7,0.0,satisfied +88042,84833,Female,Loyal Customer,33,Business travel,Business,516,3,3,3,3,4,3,2,3,3,3,3,1,3,4,0,7.0,neutral or dissatisfied +88043,94103,Female,Loyal Customer,21,Personal Travel,Business,277,2,4,2,3,2,2,2,2,3,4,4,4,3,2,7,72.0,neutral or dissatisfied +88044,14668,Female,Loyal Customer,50,Business travel,Business,3254,3,2,2,2,4,4,3,3,3,3,3,3,3,2,42,36.0,neutral or dissatisfied +88045,48835,Female,Loyal Customer,26,Personal Travel,Business,207,4,1,4,3,3,4,2,3,3,4,2,1,3,3,77,78.0,neutral or dissatisfied +88046,61221,Female,Loyal Customer,13,Business travel,Business,1635,3,2,2,2,3,3,3,3,3,4,4,4,4,3,1,9.0,neutral or dissatisfied +88047,99105,Male,disloyal Customer,21,Business travel,Eco,453,4,0,4,2,5,4,1,5,4,2,3,3,1,5,9,1.0,satisfied +88048,4865,Female,Loyal Customer,17,Personal Travel,Eco,408,2,4,2,3,3,2,3,3,5,3,5,3,4,3,5,3.0,neutral or dissatisfied +88049,115470,Male,Loyal Customer,60,Business travel,Business,2175,2,2,2,2,3,5,5,5,5,5,5,4,5,3,10,0.0,satisfied +88050,33922,Male,Loyal Customer,24,Personal Travel,Business,818,2,5,2,1,3,2,3,3,3,5,3,4,5,3,0,6.0,neutral or dissatisfied +88051,107290,Female,disloyal Customer,25,Business travel,Eco,283,2,4,2,4,2,2,2,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +88052,49183,Male,Loyal Customer,62,Business travel,Eco,156,4,1,1,1,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +88053,110831,Female,disloyal Customer,9,Business travel,Eco,849,2,2,2,3,2,2,2,2,4,3,3,1,3,2,44,61.0,neutral or dissatisfied +88054,127374,Female,Loyal Customer,35,Business travel,Business,3983,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +88055,82597,Male,Loyal Customer,37,Business travel,Eco,408,2,4,4,4,2,2,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +88056,126233,Female,Loyal Customer,41,Business travel,Eco,190,5,3,3,3,5,5,5,5,4,1,3,3,1,5,0,0.0,satisfied +88057,32702,Female,Loyal Customer,33,Business travel,Eco,216,2,4,4,4,2,2,2,2,3,3,3,1,4,2,8,6.0,neutral or dissatisfied +88058,24536,Male,Loyal Customer,28,Personal Travel,Business,696,3,5,3,2,5,3,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +88059,39973,Male,disloyal Customer,22,Business travel,Eco,1404,4,4,4,2,2,4,3,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +88060,41693,Female,Loyal Customer,17,Personal Travel,Eco,936,3,4,3,4,2,3,2,2,3,1,3,2,4,2,12,14.0,neutral or dissatisfied +88061,44364,Female,Loyal Customer,35,Business travel,Business,3505,2,2,2,2,4,1,5,4,4,4,4,4,4,1,0,0.0,satisfied +88062,3311,Female,disloyal Customer,40,Business travel,Business,240,1,1,1,3,1,1,1,1,5,5,4,4,4,1,2,5.0,neutral or dissatisfied +88063,127323,Male,disloyal Customer,28,Business travel,Business,507,2,2,2,4,2,2,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +88064,46904,Female,disloyal Customer,27,Business travel,Eco,737,1,1,1,3,1,1,1,1,3,2,3,2,3,1,1,1.0,neutral or dissatisfied +88065,24781,Male,Loyal Customer,50,Business travel,Business,128,2,4,4,4,5,4,4,3,3,3,2,2,3,1,0,0.0,neutral or dissatisfied +88066,102277,Male,Loyal Customer,31,Business travel,Business,1706,4,2,2,2,4,3,4,4,1,5,4,4,3,4,2,6.0,neutral or dissatisfied +88067,81529,Female,Loyal Customer,29,Business travel,Eco,1124,4,1,3,3,4,4,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +88068,93930,Male,Loyal Customer,41,Business travel,Business,3544,4,4,4,4,5,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +88069,77421,Male,Loyal Customer,65,Personal Travel,Eco,588,2,3,2,3,5,2,5,5,4,2,3,1,3,5,0,0.0,neutral or dissatisfied +88070,118921,Male,Loyal Customer,33,Personal Travel,Eco,587,3,1,3,3,4,3,4,4,1,4,4,3,3,4,36,29.0,neutral or dissatisfied +88071,78297,Male,Loyal Customer,65,Personal Travel,Eco,1598,3,1,4,2,5,4,3,5,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +88072,2761,Male,Loyal Customer,44,Personal Travel,Eco Plus,772,4,4,4,3,2,4,2,2,2,5,1,2,1,2,0,0.0,neutral or dissatisfied +88073,87227,Male,Loyal Customer,33,Personal Travel,Eco,946,1,2,1,3,5,1,5,5,2,4,3,2,3,5,9,5.0,neutral or dissatisfied +88074,103620,Female,Loyal Customer,41,Business travel,Business,251,0,0,0,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +88075,68392,Male,disloyal Customer,28,Business travel,Business,1045,4,4,4,3,1,4,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +88076,27414,Male,Loyal Customer,25,Business travel,Business,1508,5,5,5,5,4,5,4,4,1,5,3,4,1,4,0,0.0,satisfied +88077,84721,Male,Loyal Customer,55,Business travel,Business,3325,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +88078,95411,Male,Loyal Customer,24,Personal Travel,Eco,239,4,4,0,3,2,0,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +88079,38701,Male,disloyal Customer,23,Business travel,Eco,2583,4,4,4,4,3,4,3,3,3,4,5,3,4,3,24,28.0,satisfied +88080,67997,Male,Loyal Customer,60,Personal Travel,Eco Plus,1464,3,4,3,1,3,3,1,3,4,4,2,1,1,3,1,5.0,neutral or dissatisfied +88081,48379,Female,Loyal Customer,47,Personal Travel,Eco,674,5,5,5,2,5,4,4,2,2,5,2,5,2,3,8,1.0,satisfied +88082,84147,Female,disloyal Customer,7,Business travel,Eco,1355,3,2,2,1,3,3,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +88083,12043,Male,disloyal Customer,38,Business travel,Business,351,2,2,2,3,1,2,1,1,3,4,3,2,3,1,26,38.0,neutral or dissatisfied +88084,114228,Female,Loyal Customer,39,Business travel,Business,853,3,3,3,3,2,5,5,4,4,4,4,3,4,5,48,44.0,satisfied +88085,31248,Female,Loyal Customer,44,Business travel,Eco,524,5,1,1,1,3,4,5,5,5,5,5,1,5,5,68,58.0,satisfied +88086,20853,Male,Loyal Customer,56,Personal Travel,Eco,508,2,5,4,1,3,4,3,3,4,4,5,3,4,3,33,53.0,neutral or dissatisfied +88087,55830,Female,Loyal Customer,52,Business travel,Business,1416,1,1,1,1,3,4,5,4,4,4,4,4,4,3,9,20.0,satisfied +88088,106239,Female,disloyal Customer,25,Business travel,Eco Plus,471,3,4,3,3,2,3,2,2,1,1,4,3,3,2,0,0.0,neutral or dissatisfied +88089,128533,Male,Loyal Customer,54,Personal Travel,Eco,338,1,4,1,1,2,1,2,2,5,5,4,3,5,2,11,7.0,neutral or dissatisfied +88090,14293,Male,disloyal Customer,42,Business travel,Eco,429,3,4,2,5,1,2,1,1,1,1,2,4,1,1,0,0.0,neutral or dissatisfied +88091,87298,Male,Loyal Customer,61,Personal Travel,Eco,577,2,1,2,3,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +88092,69420,Male,Loyal Customer,71,Business travel,Business,3979,4,4,4,4,1,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +88093,90356,Female,Loyal Customer,39,Business travel,Business,270,4,4,4,4,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +88094,17769,Male,disloyal Customer,12,Business travel,Business,1075,5,0,4,4,3,4,3,3,1,1,3,5,3,3,11,42.0,satisfied +88095,18025,Female,disloyal Customer,28,Business travel,Business,488,3,4,4,4,5,4,5,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +88096,107355,Female,Loyal Customer,52,Business travel,Business,1837,1,1,1,1,5,4,3,4,4,4,4,4,4,2,0,0.0,satisfied +88097,105947,Male,Loyal Customer,38,Personal Travel,Business,2295,3,3,3,3,3,5,5,3,3,3,2,5,3,5,78,94.0,neutral or dissatisfied +88098,77116,Male,Loyal Customer,16,Personal Travel,Eco,1481,4,1,4,3,1,4,1,1,1,1,3,2,4,1,2,0.0,satisfied +88099,69700,Male,Loyal Customer,29,Business travel,Business,1372,3,3,3,3,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +88100,608,Female,Loyal Customer,30,Business travel,Business,2100,4,4,2,4,5,4,5,5,3,4,4,3,5,5,0,0.0,satisfied +88101,57374,Female,disloyal Customer,62,Business travel,Business,414,4,4,4,3,3,4,3,3,3,5,5,3,5,3,6,1.0,neutral or dissatisfied +88102,74303,Male,Loyal Customer,34,Personal Travel,Eco Plus,2288,4,4,3,4,3,3,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +88103,84143,Male,Loyal Customer,66,Personal Travel,Eco Plus,782,2,4,2,1,5,2,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +88104,54422,Female,Loyal Customer,7,Personal Travel,Eco,305,2,5,2,1,4,2,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +88105,64967,Female,Loyal Customer,51,Business travel,Eco,151,4,3,3,3,3,2,1,4,4,4,4,2,4,4,0,0.0,satisfied +88106,41474,Female,Loyal Customer,29,Business travel,Business,1504,5,4,5,5,5,5,5,5,5,2,2,3,2,5,0,0.0,satisfied +88107,87626,Female,disloyal Customer,50,Business travel,Business,591,1,1,1,3,1,1,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +88108,13181,Female,Loyal Customer,40,Business travel,Business,2887,5,5,5,5,3,5,1,4,4,4,4,2,4,4,16,0.0,satisfied +88109,20105,Female,disloyal Customer,30,Business travel,Eco,416,3,2,3,3,3,3,3,3,3,5,4,3,3,3,0,0.0,neutral or dissatisfied +88110,51748,Male,Loyal Customer,41,Personal Travel,Eco,455,3,2,2,4,3,2,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +88111,15781,Female,Loyal Customer,36,Personal Travel,Eco,254,3,5,3,3,2,3,2,2,3,2,4,4,4,2,0,2.0,neutral or dissatisfied +88112,126778,Female,disloyal Customer,22,Business travel,Eco,2296,4,4,4,3,3,4,3,3,4,5,3,4,4,3,0,8.0,neutral or dissatisfied +88113,45731,Female,Loyal Customer,45,Personal Travel,Eco Plus,1024,3,2,3,3,4,4,4,2,2,3,2,1,2,2,42,43.0,neutral or dissatisfied +88114,49962,Female,Loyal Customer,44,Business travel,Business,190,3,3,3,3,1,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +88115,99453,Male,disloyal Customer,25,Business travel,Business,283,4,0,4,1,3,4,3,3,3,3,5,4,4,3,1,0.0,neutral or dissatisfied +88116,76693,Male,Loyal Customer,13,Personal Travel,Eco,516,1,4,4,5,1,4,1,1,3,4,4,4,5,1,15,18.0,neutral or dissatisfied +88117,51700,Female,disloyal Customer,29,Business travel,Eco,251,4,3,4,4,4,5,5,3,5,4,3,5,4,5,211,190.0,neutral or dissatisfied +88118,123231,Male,Loyal Customer,17,Personal Travel,Eco,650,3,5,2,2,5,2,5,5,5,4,3,4,3,5,40,49.0,neutral or dissatisfied +88119,85807,Male,Loyal Customer,23,Personal Travel,Eco,526,2,4,4,2,1,4,1,1,5,3,5,3,4,1,78,78.0,neutral or dissatisfied +88120,87077,Female,Loyal Customer,31,Business travel,Business,594,4,5,4,5,4,4,4,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +88121,69930,Male,Loyal Customer,63,Personal Travel,Eco Plus,1514,2,4,1,3,5,1,1,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +88122,19207,Female,Loyal Customer,52,Business travel,Eco,459,1,3,3,3,2,3,3,1,1,1,1,3,1,3,0,3.0,neutral or dissatisfied +88123,36938,Male,Loyal Customer,38,Business travel,Eco,718,4,4,4,4,4,4,4,4,3,4,3,4,4,4,36,39.0,satisfied +88124,95501,Male,Loyal Customer,32,Business travel,Eco Plus,187,2,2,2,2,2,3,2,2,4,1,3,2,4,2,1,0.0,neutral or dissatisfied +88125,33420,Male,Loyal Customer,52,Business travel,Eco,2355,2,2,2,2,2,2,2,2,2,3,4,2,3,2,0,40.0,neutral or dissatisfied +88126,90680,Male,Loyal Customer,21,Business travel,Business,2455,1,1,2,1,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +88127,98050,Female,Loyal Customer,9,Business travel,Business,1797,1,5,5,5,1,1,1,1,1,3,2,2,3,1,0,0.0,neutral or dissatisfied +88128,109155,Male,Loyal Customer,46,Business travel,Business,4000,2,2,2,2,3,5,5,4,4,4,4,5,4,4,33,27.0,satisfied +88129,113266,Male,Loyal Customer,34,Business travel,Business,1527,0,0,0,3,5,5,4,2,2,2,2,4,2,5,4,0.0,satisfied +88130,22266,Female,disloyal Customer,54,Business travel,Eco,238,4,4,4,4,2,4,2,2,5,4,1,3,1,2,91,81.0,satisfied +88131,120475,Female,Loyal Customer,14,Personal Travel,Eco,366,3,5,3,3,4,3,4,4,3,5,5,1,5,4,0,10.0,neutral or dissatisfied +88132,112635,Female,disloyal Customer,24,Business travel,Eco,602,2,2,2,3,1,2,1,1,3,1,3,4,3,1,97,94.0,neutral or dissatisfied +88133,28092,Male,Loyal Customer,36,Business travel,Business,533,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +88134,71803,Female,Loyal Customer,54,Business travel,Eco,1744,3,3,3,3,2,4,3,3,3,3,3,2,3,3,9,25.0,neutral or dissatisfied +88135,34089,Male,Loyal Customer,16,Personal Travel,Eco,2072,1,4,1,2,5,1,4,5,4,5,5,4,4,5,27,18.0,neutral or dissatisfied +88136,61226,Male,disloyal Customer,29,Business travel,Eco,862,2,2,2,3,3,2,3,3,3,1,4,1,4,3,0,14.0,neutral or dissatisfied +88137,35185,Male,Loyal Customer,58,Business travel,Business,3147,3,3,3,3,5,1,3,4,4,5,4,4,4,4,30,57.0,satisfied +88138,47818,Male,Loyal Customer,42,Business travel,Business,2505,5,4,5,5,1,1,5,5,5,5,5,4,5,5,0,0.0,satisfied +88139,100399,Female,disloyal Customer,26,Business travel,Business,1092,3,3,3,3,5,3,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +88140,23158,Male,Loyal Customer,8,Personal Travel,Eco,300,2,4,2,1,3,2,3,3,5,4,5,4,5,3,0,14.0,neutral or dissatisfied +88141,19610,Male,Loyal Customer,48,Business travel,Eco,416,5,2,2,2,5,5,5,5,4,4,1,2,5,5,116,106.0,satisfied +88142,111093,Female,Loyal Customer,8,Personal Travel,Eco,197,2,5,2,4,4,2,4,4,4,3,2,4,3,4,41,24.0,neutral or dissatisfied +88143,18153,Male,Loyal Customer,8,Personal Travel,Eco,296,3,5,3,3,2,3,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +88144,114599,Female,Loyal Customer,33,Business travel,Business,362,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +88145,15061,Female,Loyal Customer,48,Personal Travel,Eco,576,4,4,4,3,5,4,5,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +88146,81081,Female,Loyal Customer,45,Business travel,Business,1690,5,2,5,5,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +88147,87282,Female,disloyal Customer,26,Business travel,Business,577,0,0,0,3,5,0,5,5,3,5,4,5,5,5,0,0.0,satisfied +88148,75406,Female,Loyal Customer,48,Business travel,Business,2585,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +88149,74927,Female,disloyal Customer,29,Business travel,Business,2475,1,1,1,2,2,1,2,2,4,2,3,5,5,2,29,11.0,neutral or dissatisfied +88150,122813,Male,Loyal Customer,47,Personal Travel,Eco,599,3,5,3,2,2,3,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +88151,49748,Male,Loyal Customer,48,Business travel,Business,3777,1,1,1,1,5,1,2,5,5,5,5,3,5,2,0,22.0,satisfied +88152,8377,Male,Loyal Customer,42,Business travel,Eco,773,3,2,2,2,4,3,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +88153,22782,Male,Loyal Customer,53,Business travel,Business,170,4,4,4,4,5,4,5,4,4,4,3,3,4,5,14,2.0,satisfied +88154,41017,Female,disloyal Customer,25,Business travel,Eco,1195,4,4,4,3,5,4,3,5,2,4,4,3,1,5,0,0.0,satisfied +88155,79327,Female,Loyal Customer,42,Business travel,Business,2072,2,2,4,2,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +88156,29191,Male,Loyal Customer,14,Personal Travel,Eco Plus,954,2,4,2,4,5,2,5,5,1,1,1,1,2,5,0,16.0,neutral or dissatisfied +88157,113421,Female,Loyal Customer,64,Business travel,Business,2363,2,4,5,4,5,4,4,2,2,2,2,4,2,2,5,0.0,neutral or dissatisfied +88158,90708,Male,Loyal Customer,45,Business travel,Business,3444,2,2,2,2,5,5,5,4,3,5,5,5,5,5,183,178.0,satisfied +88159,69421,Male,Loyal Customer,50,Business travel,Business,3356,1,4,4,4,3,1,2,1,1,1,1,1,1,2,1,0.0,neutral or dissatisfied +88160,33548,Male,disloyal Customer,38,Business travel,Eco,399,2,5,1,2,1,1,1,1,4,1,5,3,3,1,42,28.0,neutral or dissatisfied +88161,74193,Male,Loyal Customer,25,Personal Travel,Eco,721,3,5,3,2,5,3,5,5,2,5,5,4,1,5,40,42.0,neutral or dissatisfied +88162,86686,Female,Loyal Customer,15,Personal Travel,Business,1747,1,5,1,1,5,1,5,5,3,2,4,4,5,5,4,25.0,neutral or dissatisfied +88163,54199,Female,Loyal Customer,49,Personal Travel,Eco,1400,3,3,3,5,5,4,5,2,2,3,1,1,2,3,0,0.0,neutral or dissatisfied +88164,117137,Female,Loyal Customer,24,Personal Travel,Eco,304,1,5,2,3,1,2,1,1,3,4,5,4,5,1,44,37.0,neutral or dissatisfied +88165,15893,Female,Loyal Customer,69,Business travel,Eco,378,4,3,5,3,3,2,4,5,5,4,5,4,5,4,0,0.0,satisfied +88166,18405,Male,disloyal Customer,24,Business travel,Eco,284,4,2,4,3,2,4,2,2,4,5,3,2,4,2,102,113.0,neutral or dissatisfied +88167,95417,Female,Loyal Customer,40,Business travel,Business,1809,3,3,3,3,3,4,4,5,5,5,5,5,5,3,3,0.0,satisfied +88168,13914,Male,Loyal Customer,33,Business travel,Business,192,3,3,3,3,5,5,4,5,1,3,5,2,5,5,0,0.0,satisfied +88169,34406,Female,Loyal Customer,15,Personal Travel,Eco,612,5,5,5,3,4,5,4,4,4,2,4,4,5,4,0,0.0,satisfied +88170,85198,Female,Loyal Customer,58,Business travel,Business,2852,2,5,5,5,2,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +88171,65768,Female,disloyal Customer,46,Business travel,Business,1061,3,3,3,3,5,3,5,5,3,2,4,3,4,5,0,5.0,satisfied +88172,16540,Male,Loyal Customer,43,Business travel,Business,2104,5,5,4,5,2,5,3,5,5,5,5,4,5,3,0,0.0,satisfied +88173,30897,Male,disloyal Customer,11,Business travel,Eco,826,2,2,2,3,3,2,3,3,4,5,3,1,3,3,17,6.0,neutral or dissatisfied +88174,20336,Female,disloyal Customer,23,Business travel,Eco,287,3,0,4,2,2,4,2,2,5,1,4,5,4,2,42,34.0,neutral or dissatisfied +88175,26715,Female,Loyal Customer,17,Personal Travel,Eco,404,3,4,3,3,5,3,5,5,5,3,4,3,4,5,4,0.0,neutral or dissatisfied +88176,83725,Male,Loyal Customer,53,Business travel,Business,2275,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,9.0,satisfied +88177,97760,Female,Loyal Customer,65,Personal Travel,Eco,587,3,5,3,5,3,4,5,1,1,3,1,4,1,4,3,24.0,neutral or dissatisfied +88178,90978,Female,disloyal Customer,39,Business travel,Eco,366,1,0,2,5,4,2,4,4,3,1,2,2,1,4,4,0.0,neutral or dissatisfied +88179,104753,Male,Loyal Customer,37,Personal Travel,Eco,1407,2,4,2,2,2,2,2,2,4,1,5,5,5,2,4,7.0,neutral or dissatisfied +88180,96685,Male,Loyal Customer,25,Business travel,Business,2063,1,1,1,1,5,5,5,5,4,2,5,3,4,5,0,0.0,satisfied +88181,88181,Female,Loyal Customer,53,Business travel,Business,2752,5,5,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +88182,77917,Female,Loyal Customer,41,Business travel,Business,214,2,2,2,2,2,4,5,5,5,5,5,5,5,3,0,2.0,satisfied +88183,22931,Female,disloyal Customer,47,Business travel,Eco,817,2,2,2,1,5,2,5,5,4,2,4,4,1,5,0,7.0,neutral or dissatisfied +88184,97943,Male,Loyal Customer,39,Business travel,Business,3297,2,1,1,1,2,2,2,2,2,1,2,3,2,2,5,1.0,neutral or dissatisfied +88185,45877,Male,Loyal Customer,49,Business travel,Eco,563,5,1,1,1,5,5,5,5,3,2,2,5,3,5,6,24.0,satisfied +88186,55317,Female,Loyal Customer,51,Business travel,Business,1325,3,4,4,4,5,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +88187,5637,Female,Loyal Customer,49,Business travel,Business,3804,3,3,3,3,5,4,4,5,5,4,5,4,5,4,42,32.0,satisfied +88188,89628,Female,disloyal Customer,45,Business travel,Business,1089,3,3,3,5,4,3,4,4,5,4,5,3,5,4,117,111.0,neutral or dissatisfied +88189,121709,Male,Loyal Customer,57,Business travel,Eco,683,1,0,0,3,4,1,2,4,2,4,4,4,4,4,30,33.0,neutral or dissatisfied +88190,31000,Male,Loyal Customer,40,Business travel,Eco,391,4,1,5,1,4,4,4,4,2,4,5,5,1,4,0,2.0,satisfied +88191,13968,Male,Loyal Customer,60,Personal Travel,Eco,192,3,5,0,4,3,0,3,3,3,2,5,3,5,3,26,24.0,neutral or dissatisfied +88192,110166,Female,Loyal Customer,47,Personal Travel,Eco,1056,3,4,3,3,4,5,4,4,4,3,3,4,4,4,37,18.0,neutral or dissatisfied +88193,9304,Male,Loyal Customer,51,Business travel,Business,542,3,3,3,3,3,5,4,3,3,3,3,5,3,3,52,67.0,satisfied +88194,28698,Male,Loyal Customer,30,Personal Travel,Business,2172,1,5,2,4,4,2,4,4,4,4,4,5,4,4,3,13.0,neutral or dissatisfied +88195,6312,Male,Loyal Customer,40,Business travel,Business,1536,5,5,5,5,2,5,4,5,5,5,5,5,5,5,94,109.0,satisfied +88196,95578,Female,Loyal Customer,46,Business travel,Business,2309,3,1,1,1,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +88197,9861,Female,Loyal Customer,27,Personal Travel,Eco,642,4,2,4,3,3,4,3,3,2,4,2,3,2,3,0,0.0,satisfied +88198,12441,Male,Loyal Customer,58,Personal Travel,Eco,383,3,2,3,2,1,3,1,1,1,1,3,2,3,1,0,0.0,neutral or dissatisfied +88199,118778,Male,Loyal Customer,69,Personal Travel,Eco,304,3,2,3,3,5,3,5,5,1,1,4,2,4,5,15,8.0,neutral or dissatisfied +88200,93357,Female,disloyal Customer,59,Business travel,Eco,436,4,0,4,4,2,4,2,2,2,5,5,1,2,2,0,0.0,neutral or dissatisfied +88201,116707,Female,Loyal Customer,42,Business travel,Eco Plus,325,5,5,5,5,1,2,3,5,5,5,5,3,5,4,12,0.0,satisfied +88202,106146,Female,Loyal Customer,42,Business travel,Eco,302,1,5,5,5,2,3,4,1,1,1,1,3,1,2,9,2.0,neutral or dissatisfied +88203,57927,Male,Loyal Customer,15,Business travel,Business,2642,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +88204,17900,Female,Loyal Customer,51,Business travel,Business,1930,1,3,3,3,2,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +88205,108905,Male,Loyal Customer,41,Business travel,Business,3309,2,2,2,2,5,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +88206,39409,Male,Loyal Customer,42,Personal Travel,Eco,521,3,4,5,1,3,5,2,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +88207,98329,Female,disloyal Customer,28,Business travel,Business,1189,2,2,2,3,1,2,1,1,4,2,4,4,5,1,2,0.0,neutral or dissatisfied +88208,128790,Male,disloyal Customer,35,Business travel,Business,2586,3,3,3,1,3,5,5,5,3,5,4,5,3,5,79,54.0,neutral or dissatisfied +88209,47849,Male,Loyal Customer,28,Business travel,Business,3159,2,2,2,2,5,5,5,5,5,4,3,1,2,5,0,0.0,satisfied +88210,27415,Male,Loyal Customer,54,Business travel,Eco,954,4,5,5,5,4,4,4,4,1,2,2,5,3,4,0,0.0,satisfied +88211,116391,Female,Loyal Customer,52,Personal Travel,Eco,325,4,5,4,4,1,2,4,3,3,4,3,5,3,4,32,30.0,neutral or dissatisfied +88212,90360,Male,Loyal Customer,44,Business travel,Business,2000,1,2,2,2,1,3,4,1,1,1,1,3,1,4,53,75.0,neutral or dissatisfied +88213,83394,Male,Loyal Customer,45,Business travel,Business,2673,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +88214,36371,Male,Loyal Customer,41,Business travel,Eco,200,5,3,2,3,5,5,5,5,3,4,4,5,3,5,0,0.0,satisfied +88215,12919,Male,Loyal Customer,62,Business travel,Eco,456,5,5,5,5,5,5,5,5,5,1,3,5,5,5,0,5.0,satisfied +88216,31374,Male,Loyal Customer,52,Personal Travel,Eco,977,1,4,1,5,3,1,3,3,4,2,5,5,4,3,0,5.0,neutral or dissatisfied +88217,29872,Female,Loyal Customer,37,Business travel,Business,3011,0,1,1,3,2,3,1,3,3,1,1,4,3,5,28,25.0,satisfied +88218,51140,Female,Loyal Customer,30,Personal Travel,Eco,308,2,1,2,3,1,2,2,1,4,2,2,4,2,1,0,0.0,neutral or dissatisfied +88219,10072,Male,disloyal Customer,21,Business travel,Eco,441,3,4,3,3,1,3,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +88220,58301,Male,disloyal Customer,20,Business travel,Eco,1739,4,4,4,5,2,4,2,2,5,5,4,5,5,2,0,32.0,satisfied +88221,84995,Female,Loyal Customer,43,Business travel,Business,1590,3,3,5,3,2,5,4,5,5,5,5,4,5,4,1,4.0,satisfied +88222,19376,Female,Loyal Customer,21,Personal Travel,Eco,476,2,4,2,3,2,2,2,2,4,5,3,3,4,2,91,92.0,neutral or dissatisfied +88223,106240,Male,Loyal Customer,25,Personal Travel,Eco Plus,471,2,4,1,3,5,1,5,5,1,5,3,1,5,5,0,0.0,neutral or dissatisfied +88224,125201,Female,Loyal Customer,60,Business travel,Eco,651,2,5,5,5,1,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +88225,118804,Female,Loyal Customer,15,Personal Travel,Eco,368,3,4,3,2,3,3,3,3,1,5,4,1,1,3,0,0.0,neutral or dissatisfied +88226,32316,Female,disloyal Customer,54,Business travel,Eco,101,1,3,1,3,2,1,1,2,4,3,2,4,2,2,0,0.0,neutral or dissatisfied +88227,88112,Male,disloyal Customer,27,Business travel,Business,545,4,4,4,3,2,4,1,2,5,3,5,4,4,2,0,0.0,satisfied +88228,52995,Male,Loyal Customer,58,Business travel,Business,1190,4,4,4,4,1,5,2,4,4,4,4,3,4,1,7,11.0,satisfied +88229,127209,Male,Loyal Customer,52,Business travel,Eco Plus,325,1,4,4,4,1,1,1,1,4,2,4,2,3,1,0,2.0,neutral or dissatisfied +88230,79570,Female,Loyal Customer,55,Business travel,Business,3346,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +88231,25341,Female,Loyal Customer,46,Business travel,Eco Plus,837,5,3,3,3,1,5,1,5,5,5,5,5,5,2,0,2.0,satisfied +88232,40523,Female,Loyal Customer,34,Personal Travel,Eco Plus,150,4,4,4,1,4,4,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +88233,75182,Male,disloyal Customer,20,Business travel,Eco,1149,2,2,2,2,3,2,3,3,4,4,4,3,5,3,80,67.0,neutral or dissatisfied +88234,110935,Male,Loyal Customer,58,Personal Travel,Eco,406,3,5,3,1,1,3,1,1,4,5,3,5,5,1,0,14.0,neutral or dissatisfied +88235,24172,Female,Loyal Customer,50,Business travel,Business,147,2,2,2,2,3,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +88236,5392,Male,Loyal Customer,47,Personal Travel,Eco,785,2,4,2,4,4,2,4,4,4,5,4,3,5,4,0,17.0,neutral or dissatisfied +88237,74818,Male,Loyal Customer,60,Personal Travel,Eco Plus,1171,3,4,3,3,3,3,3,3,5,5,3,3,4,3,19,2.0,neutral or dissatisfied +88238,59813,Female,disloyal Customer,35,Business travel,Business,1065,2,2,2,5,3,2,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +88239,89350,Female,disloyal Customer,43,Business travel,Eco,1141,4,4,4,5,3,4,3,3,4,3,1,1,3,3,41,18.0,neutral or dissatisfied +88240,83370,Female,Loyal Customer,18,Personal Travel,Eco,1124,2,5,3,5,5,3,3,5,5,4,5,3,5,5,20,12.0,neutral or dissatisfied +88241,66320,Male,Loyal Customer,58,Personal Travel,Eco,852,1,5,1,3,2,1,4,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +88242,86838,Male,Loyal Customer,44,Business travel,Business,3689,1,5,5,5,4,3,4,1,1,1,1,4,1,4,67,50.0,neutral or dissatisfied +88243,35982,Male,Loyal Customer,52,Personal Travel,Eco,632,2,5,2,2,5,2,5,5,3,2,5,5,5,5,5,0.0,neutral or dissatisfied +88244,85539,Female,disloyal Customer,24,Business travel,Eco,317,2,5,2,5,5,2,5,5,3,4,5,5,5,5,0,2.0,neutral or dissatisfied +88245,98950,Male,Loyal Customer,55,Business travel,Business,569,3,5,5,5,1,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +88246,69933,Female,Loyal Customer,53,Business travel,Business,2174,5,5,5,5,3,5,5,4,4,4,4,3,4,3,15,3.0,satisfied +88247,488,Male,Loyal Customer,48,Business travel,Business,89,4,4,4,4,4,4,5,4,4,4,4,4,4,5,19,16.0,satisfied +88248,94679,Male,Loyal Customer,55,Business travel,Business,2898,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +88249,104360,Female,Loyal Customer,14,Personal Travel,Eco Plus,452,3,3,1,3,4,1,4,4,2,3,3,3,4,4,0,1.0,neutral or dissatisfied +88250,84936,Male,Loyal Customer,41,Personal Travel,Eco,547,4,4,3,4,5,3,4,5,4,3,4,1,5,5,0,0.0,neutral or dissatisfied +88251,101365,Female,Loyal Customer,56,Business travel,Business,1986,1,1,5,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +88252,50018,Female,Loyal Customer,17,Business travel,Eco,308,3,4,4,4,3,3,2,3,4,2,2,1,2,3,0,0.0,neutral or dissatisfied +88253,7166,Female,Loyal Customer,51,Business travel,Business,139,3,3,4,3,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +88254,21263,Male,disloyal Customer,37,Business travel,Eco Plus,503,1,1,1,2,5,1,5,5,4,5,2,1,5,5,24,27.0,neutral or dissatisfied +88255,129135,Male,Loyal Customer,33,Business travel,Business,3837,4,5,4,4,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +88256,45117,Female,Loyal Customer,19,Personal Travel,Eco,177,3,1,3,2,2,3,1,2,4,2,1,3,1,2,4,0.0,neutral or dissatisfied +88257,119153,Male,Loyal Customer,38,Business travel,Business,3113,2,1,1,1,1,3,4,2,2,2,2,4,2,4,17,15.0,neutral or dissatisfied +88258,68401,Female,Loyal Customer,58,Business travel,Business,1045,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +88259,47900,Female,Loyal Customer,66,Business travel,Business,412,3,4,3,3,1,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +88260,116817,Male,Loyal Customer,46,Business travel,Business,338,5,5,5,5,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +88261,85033,Female,Loyal Customer,69,Personal Travel,Eco,1590,2,5,1,4,5,3,4,4,4,1,4,4,4,4,18,15.0,neutral or dissatisfied +88262,101858,Female,Loyal Customer,61,Personal Travel,Eco,519,4,5,4,4,4,5,4,5,5,4,5,4,5,4,7,5.0,satisfied +88263,126330,Female,Loyal Customer,20,Personal Travel,Eco,650,1,4,1,4,4,1,4,4,4,2,5,5,4,4,0,10.0,neutral or dissatisfied +88264,7325,Female,Loyal Customer,52,Business travel,Business,2104,0,5,0,3,5,5,5,4,4,4,4,4,4,3,63,67.0,satisfied +88265,69356,Male,Loyal Customer,54,Business travel,Business,1096,3,3,3,3,5,4,4,2,2,2,2,4,2,5,3,6.0,satisfied +88266,67698,Male,Loyal Customer,24,Business travel,Business,3322,2,4,4,4,2,2,2,2,4,3,2,1,2,2,0,0.0,neutral or dissatisfied +88267,4250,Male,Loyal Customer,19,Personal Travel,Eco,1020,3,0,4,1,4,4,4,4,4,2,4,2,2,4,0,0.0,neutral or dissatisfied +88268,27742,Female,Loyal Customer,26,Business travel,Business,1448,2,2,2,2,4,4,4,4,3,1,3,4,4,4,0,0.0,satisfied +88269,35206,Male,Loyal Customer,44,Business travel,Business,2317,3,3,3,3,4,4,1,5,5,5,5,4,5,2,116,104.0,satisfied +88270,124607,Male,Loyal Customer,59,Business travel,Eco,1671,4,4,4,4,4,4,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +88271,55931,Female,Loyal Customer,34,Personal Travel,Eco,723,3,4,3,2,4,3,4,4,2,3,5,5,3,4,0,0.0,neutral or dissatisfied +88272,45985,Male,Loyal Customer,67,Business travel,Eco,483,4,3,3,3,4,4,4,4,2,1,4,4,3,4,6,3.0,neutral or dissatisfied +88273,63980,Female,Loyal Customer,68,Personal Travel,Eco Plus,1192,2,4,2,3,4,3,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +88274,96203,Female,disloyal Customer,28,Business travel,Eco,546,4,0,4,3,4,4,4,4,1,5,3,4,3,4,26,20.0,neutral or dissatisfied +88275,71620,Female,Loyal Customer,30,Business travel,Business,1182,5,5,5,5,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +88276,99014,Male,Loyal Customer,33,Personal Travel,Eco Plus,543,4,5,4,5,5,4,5,5,4,5,4,3,4,5,2,1.0,satisfied +88277,102053,Male,Loyal Customer,10,Personal Travel,Business,414,5,5,5,2,3,5,4,3,1,4,5,1,1,3,11,0.0,satisfied +88278,18008,Male,disloyal Customer,18,Business travel,Eco,618,0,2,0,5,1,0,1,1,2,1,3,1,2,1,0,0.0,satisfied +88279,4932,Female,Loyal Customer,51,Business travel,Business,334,5,5,5,5,5,5,5,4,4,5,4,3,4,5,23,25.0,satisfied +88280,15916,Female,Loyal Customer,48,Business travel,Business,607,1,1,1,1,5,5,4,5,5,5,5,4,5,3,6,0.0,satisfied +88281,115435,Female,Loyal Customer,60,Business travel,Eco,446,3,5,5,5,1,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +88282,28028,Male,Loyal Customer,23,Personal Travel,Eco,763,1,2,1,3,1,1,5,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +88283,94516,Female,Loyal Customer,41,Business travel,Business,323,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +88284,51695,Female,disloyal Customer,20,Business travel,Eco,370,2,2,2,3,3,2,3,3,3,5,3,1,4,3,0,0.0,neutral or dissatisfied +88285,67627,Female,Loyal Customer,50,Business travel,Business,1507,4,4,4,4,2,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +88286,87053,Female,Loyal Customer,41,Business travel,Business,594,4,4,4,4,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +88287,71258,Female,Loyal Customer,9,Personal Travel,Eco,733,5,4,4,2,4,4,4,4,4,1,3,5,1,4,0,0.0,satisfied +88288,3308,Male,disloyal Customer,38,Business travel,Business,240,2,2,2,4,1,2,1,1,1,3,4,2,4,1,5,0.0,neutral or dissatisfied +88289,117689,Male,Loyal Customer,43,Business travel,Business,1814,1,1,1,1,2,3,5,5,5,5,5,3,5,4,8,0.0,satisfied +88290,88570,Female,Loyal Customer,22,Personal Travel,Eco,545,3,2,3,3,3,3,3,3,4,2,2,2,2,3,0,0.0,neutral or dissatisfied +88291,96097,Female,Loyal Customer,15,Personal Travel,Eco,775,2,5,2,2,2,2,2,2,4,5,5,3,4,2,3,2.0,neutral or dissatisfied +88292,29635,Female,disloyal Customer,27,Business travel,Eco,1048,2,2,2,3,3,2,4,3,2,5,3,1,3,3,73,64.0,neutral or dissatisfied +88293,16565,Female,Loyal Customer,44,Business travel,Eco,872,5,4,4,4,4,1,1,5,5,5,5,2,5,4,0,0.0,satisfied +88294,14847,Male,Loyal Customer,13,Personal Travel,Business,315,2,5,2,5,2,2,4,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +88295,22640,Male,Loyal Customer,34,Personal Travel,Eco,300,3,1,3,4,4,3,4,4,1,3,4,4,3,4,0,0.0,neutral or dissatisfied +88296,40092,Male,Loyal Customer,40,Business travel,Business,200,5,5,5,5,5,4,5,5,5,5,5,3,5,1,78,77.0,satisfied +88297,15091,Male,Loyal Customer,38,Business travel,Eco,239,4,1,1,1,4,5,4,4,3,2,2,5,3,4,0,0.0,satisfied +88298,47696,Male,Loyal Customer,40,Personal Travel,Eco,715,4,5,4,3,3,4,3,3,2,5,5,5,2,3,0,6.0,neutral or dissatisfied +88299,22285,Female,Loyal Customer,45,Business travel,Eco,145,4,4,3,4,4,3,1,4,4,4,4,5,4,2,0,0.0,satisfied +88300,89066,Female,Loyal Customer,52,Business travel,Business,1892,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +88301,4595,Male,disloyal Customer,23,Business travel,Eco,416,1,1,1,3,2,1,2,2,3,5,3,4,3,2,41,81.0,neutral or dissatisfied +88302,121150,Female,Loyal Customer,42,Business travel,Business,2402,1,1,1,1,2,3,4,4,4,4,4,4,4,4,4,0.0,satisfied +88303,587,Female,Loyal Customer,66,Business travel,Business,2883,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +88304,96926,Female,Loyal Customer,47,Business travel,Business,816,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +88305,64899,Male,Loyal Customer,37,Business travel,Business,3567,4,3,3,3,4,3,3,4,4,4,4,3,4,2,2,0.0,neutral or dissatisfied +88306,58826,Female,Loyal Customer,53,Personal Travel,Eco,1005,2,5,3,3,4,4,4,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +88307,50952,Male,Loyal Customer,24,Personal Travel,Eco,363,1,5,1,1,3,1,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +88308,111430,Male,Loyal Customer,65,Personal Travel,Eco,896,2,4,2,4,3,2,2,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +88309,61454,Male,Loyal Customer,50,Business travel,Business,2288,5,5,5,5,3,4,4,5,5,5,5,5,5,3,5,0.0,satisfied +88310,123891,Female,Loyal Customer,55,Personal Travel,Eco,544,5,4,2,1,5,2,4,3,3,2,3,1,3,1,0,0.0,satisfied +88311,102892,Female,Loyal Customer,49,Business travel,Business,1037,2,3,2,2,5,5,5,3,3,5,5,5,3,5,167,159.0,satisfied +88312,59672,Male,Loyal Customer,22,Personal Travel,Eco,854,3,5,3,2,5,3,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +88313,20840,Female,disloyal Customer,45,Business travel,Eco,108,3,0,2,2,1,2,1,1,4,4,3,1,1,1,27,17.0,neutral or dissatisfied +88314,107590,Male,Loyal Customer,47,Business travel,Business,1594,5,5,5,5,3,5,4,2,2,2,2,5,2,5,12,16.0,satisfied +88315,88961,Female,Loyal Customer,39,Business travel,Business,1340,2,2,2,2,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +88316,1697,Male,disloyal Customer,26,Business travel,Business,364,3,0,3,2,3,3,5,3,4,3,5,4,4,3,7,7.0,neutral or dissatisfied +88317,77466,Female,Loyal Customer,50,Business travel,Business,3486,4,4,4,4,3,4,3,4,4,4,4,1,4,2,8,5.0,neutral or dissatisfied +88318,10111,Male,disloyal Customer,18,Business travel,Business,984,4,0,3,1,1,3,1,1,4,2,4,3,5,1,119,116.0,satisfied +88319,110816,Female,Loyal Customer,41,Personal Travel,Eco,849,3,4,3,2,5,3,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +88320,59190,Male,Loyal Customer,48,Business travel,Business,1440,1,1,1,1,3,5,4,4,4,4,4,4,4,4,56,46.0,satisfied +88321,124792,Female,Loyal Customer,39,Business travel,Business,280,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +88322,76916,Male,Loyal Customer,17,Business travel,Eco Plus,630,5,3,3,3,5,5,4,5,3,4,1,5,5,5,0,1.0,satisfied +88323,33883,Male,Loyal Customer,33,Personal Travel,Eco,1105,4,3,4,5,4,4,4,4,2,1,3,5,4,4,30,26.0,satisfied +88324,69688,Female,Loyal Customer,8,Personal Travel,Eco Plus,569,1,5,1,1,5,1,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +88325,42045,Male,Loyal Customer,59,Business travel,Business,3630,0,4,0,3,2,1,1,2,2,2,2,3,2,4,0,0.0,satisfied +88326,90014,Female,Loyal Customer,60,Business travel,Business,1983,4,4,4,4,2,5,5,3,3,4,3,5,3,3,2,0.0,satisfied +88327,127347,Male,Loyal Customer,60,Business travel,Business,3634,3,3,3,3,3,3,4,4,4,4,3,4,4,2,34,69.0,neutral or dissatisfied +88328,90236,Male,Loyal Customer,56,Personal Travel,Eco Plus,1086,2,2,2,4,3,2,3,3,1,4,3,1,3,3,0,0.0,neutral or dissatisfied +88329,4726,Male,Loyal Customer,27,Business travel,Business,2661,4,4,4,4,4,5,4,4,3,4,5,4,5,4,23,26.0,satisfied +88330,37507,Male,Loyal Customer,49,Business travel,Business,3527,4,4,4,4,1,1,4,4,4,4,4,5,4,1,34,24.0,satisfied +88331,12983,Female,Loyal Customer,41,Business travel,Business,3658,2,2,2,2,5,4,1,5,5,5,5,1,5,1,50,35.0,satisfied +88332,68445,Male,Loyal Customer,56,Business travel,Business,1303,2,2,2,2,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +88333,79882,Female,disloyal Customer,45,Business travel,Business,1035,4,4,4,1,1,4,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +88334,43712,Female,Loyal Customer,25,Personal Travel,Eco,489,1,4,1,2,3,1,3,3,3,4,2,2,5,3,0,0.0,neutral or dissatisfied +88335,46622,Female,Loyal Customer,41,Business travel,Eco,125,2,1,1,1,2,2,2,2,4,4,3,5,2,2,0,0.0,satisfied +88336,5679,Male,Loyal Customer,54,Business travel,Business,3558,2,5,5,5,3,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +88337,79068,Male,Loyal Customer,53,Business travel,Eco,356,4,4,4,4,4,4,4,4,1,1,1,4,1,4,0,13.0,satisfied +88338,70667,Male,Loyal Customer,47,Business travel,Business,1525,4,4,4,4,4,5,5,4,4,5,4,5,4,4,0,12.0,satisfied +88339,113142,Female,disloyal Customer,25,Business travel,Business,628,2,0,2,4,5,2,5,5,3,2,4,3,4,5,32,47.0,neutral or dissatisfied +88340,88098,Female,Loyal Customer,26,Business travel,Business,2309,5,5,5,5,4,4,4,4,5,3,5,3,4,4,13,12.0,satisfied +88341,18840,Female,Loyal Customer,58,Business travel,Eco,448,4,5,5,5,4,4,4,3,2,1,1,4,1,4,134,123.0,satisfied +88342,41754,Female,Loyal Customer,51,Business travel,Business,3148,5,5,5,5,3,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +88343,68438,Female,Loyal Customer,35,Personal Travel,Eco Plus,1045,3,4,3,4,2,3,5,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +88344,67248,Female,Loyal Customer,48,Personal Travel,Eco,1102,3,3,3,3,4,5,1,4,4,3,4,2,4,5,0,0.0,neutral or dissatisfied +88345,117819,Male,Loyal Customer,49,Personal Travel,Eco,328,3,4,2,2,2,2,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +88346,115285,Female,Loyal Customer,55,Business travel,Business,2354,2,2,2,2,5,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +88347,84343,Male,Loyal Customer,22,Business travel,Business,3408,4,4,4,4,4,4,4,4,5,2,5,3,5,4,5,3.0,satisfied +88348,46002,Male,Loyal Customer,61,Personal Travel,Eco,483,4,0,4,3,3,4,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +88349,55186,Female,disloyal Customer,29,Business travel,Eco Plus,1379,2,2,2,4,2,2,2,2,1,3,3,3,4,2,2,0.0,neutral or dissatisfied +88350,104870,Female,Loyal Customer,55,Business travel,Eco,327,3,2,2,2,2,3,2,3,3,3,3,1,3,2,73,76.0,neutral or dissatisfied +88351,71254,Female,Loyal Customer,39,Business travel,Business,2392,3,3,3,3,5,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +88352,37227,Female,Loyal Customer,54,Business travel,Business,2278,2,4,4,4,2,3,3,2,2,2,2,1,2,2,9,79.0,neutral or dissatisfied +88353,31443,Female,Loyal Customer,43,Personal Travel,Eco,1541,3,2,3,4,4,2,4,3,3,3,3,1,3,2,46,35.0,neutral or dissatisfied +88354,37439,Female,disloyal Customer,36,Business travel,Eco,828,2,2,2,3,5,2,5,5,4,3,4,4,1,5,0,0.0,neutral or dissatisfied +88355,87429,Female,Loyal Customer,38,Personal Travel,Eco Plus,425,4,4,5,1,5,5,5,5,3,3,4,3,4,5,9,11.0,satisfied +88356,36179,Female,Loyal Customer,31,Personal Travel,Eco,1674,3,5,3,3,1,3,3,1,2,2,2,2,3,1,0,0.0,neutral or dissatisfied +88357,30594,Female,Loyal Customer,44,Business travel,Business,3051,5,5,5,5,2,5,4,5,5,5,5,5,5,5,2,2.0,satisfied +88358,126509,Male,disloyal Customer,43,Business travel,Business,1849,5,5,5,1,2,5,2,2,4,2,4,5,4,2,0,0.0,satisfied +88359,73852,Female,Loyal Customer,53,Personal Travel,Eco,1810,4,1,4,2,4,3,3,3,3,4,3,2,3,1,1,5.0,neutral or dissatisfied +88360,56556,Male,Loyal Customer,54,Business travel,Business,1023,2,2,5,2,5,4,5,4,4,4,4,4,4,5,1,0.0,satisfied +88361,84340,Female,Loyal Customer,31,Business travel,Business,606,2,5,2,2,4,4,4,4,5,2,4,4,4,4,7,0.0,satisfied +88362,82484,Male,Loyal Customer,40,Business travel,Eco Plus,502,3,2,2,2,3,3,3,3,2,4,4,1,3,3,0,9.0,neutral or dissatisfied +88363,65000,Female,Loyal Customer,37,Business travel,Business,3528,1,1,4,1,2,4,3,5,5,5,5,1,5,5,0,0.0,satisfied +88364,128981,Male,Loyal Customer,29,Personal Travel,Eco,414,4,5,4,1,2,4,2,2,4,2,5,4,3,2,0,19.0,neutral or dissatisfied +88365,85380,Male,Loyal Customer,57,Business travel,Business,2496,5,5,3,5,4,5,4,5,5,5,5,4,5,5,17,24.0,satisfied +88366,23673,Male,Loyal Customer,46,Business travel,Business,3847,2,2,2,2,4,2,3,5,5,5,5,1,5,5,16,18.0,satisfied +88367,55043,Female,disloyal Customer,30,Business travel,Eco,1346,3,3,3,2,4,3,4,4,4,4,2,4,2,4,0,0.0,neutral or dissatisfied +88368,117640,Female,Loyal Customer,49,Personal Travel,Eco,843,2,4,1,3,2,3,4,3,3,1,3,1,3,4,18,8.0,neutral or dissatisfied +88369,85111,Female,Loyal Customer,56,Business travel,Business,2353,5,5,5,5,4,5,4,4,4,5,4,3,4,4,6,9.0,satisfied +88370,127675,Female,Loyal Customer,56,Personal Travel,Eco,2153,3,4,3,3,4,3,5,3,3,3,4,3,3,4,16,1.0,neutral or dissatisfied +88371,16370,Male,Loyal Customer,51,Business travel,Business,1325,5,1,5,5,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +88372,70747,Female,Loyal Customer,57,Business travel,Business,1658,1,1,1,1,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +88373,12795,Male,Loyal Customer,57,Business travel,Eco,641,4,4,4,4,4,4,4,4,3,1,4,5,5,4,20,33.0,satisfied +88374,105151,Female,disloyal Customer,25,Business travel,Eco,281,3,1,3,2,5,3,5,5,3,4,3,1,3,5,28,20.0,neutral or dissatisfied +88375,48098,Male,Loyal Customer,46,Business travel,Eco,192,5,1,3,3,5,5,5,5,1,4,5,2,3,5,0,4.0,satisfied +88376,8747,Female,Loyal Customer,15,Personal Travel,Eco Plus,227,3,5,3,1,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +88377,78257,Male,Loyal Customer,31,Business travel,Business,3346,3,5,4,4,3,3,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +88378,39866,Male,Loyal Customer,60,Business travel,Eco,221,5,1,1,1,5,5,5,5,5,2,2,5,1,5,0,0.0,satisfied +88379,22209,Female,Loyal Customer,51,Personal Travel,Eco,633,1,5,1,2,2,4,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +88380,114856,Female,Loyal Customer,49,Business travel,Business,3232,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +88381,57439,Male,Loyal Customer,58,Business travel,Eco,1735,3,2,2,2,3,3,3,3,2,2,4,3,4,3,35,114.0,neutral or dissatisfied +88382,120740,Male,disloyal Customer,31,Business travel,Business,1089,2,2,2,4,3,2,5,3,3,2,3,2,3,3,0,1.0,neutral or dissatisfied +88383,17536,Female,disloyal Customer,80,Business travel,Business,252,1,1,1,3,4,4,1,1,1,1,1,4,1,4,8,4.0,neutral or dissatisfied +88384,91042,Male,Loyal Customer,54,Personal Travel,Eco,270,2,4,2,1,4,2,4,4,5,4,5,3,5,4,0,2.0,neutral or dissatisfied +88385,33342,Male,Loyal Customer,18,Business travel,Eco,2409,5,1,4,4,5,5,5,5,3,3,4,4,5,5,12,9.0,satisfied +88386,64581,Female,Loyal Customer,42,Business travel,Business,247,3,3,3,3,2,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +88387,77907,Female,Loyal Customer,56,Personal Travel,Eco,456,2,4,2,3,3,4,4,5,5,2,5,3,5,3,0,4.0,neutral or dissatisfied +88388,11294,Female,Loyal Customer,59,Personal Travel,Eco,158,4,5,4,2,4,4,5,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +88389,35520,Female,Loyal Customer,37,Personal Travel,Eco,1005,3,4,3,3,3,3,3,3,5,2,4,4,4,3,115,114.0,neutral or dissatisfied +88390,73789,Female,Loyal Customer,28,Business travel,Business,3394,3,3,3,3,5,5,4,5,3,2,4,3,5,5,0,2.0,satisfied +88391,114812,Male,Loyal Customer,43,Business travel,Business,480,3,3,3,3,4,5,5,3,3,4,3,5,3,4,9,0.0,satisfied +88392,58627,Female,Loyal Customer,58,Personal Travel,Business,867,1,3,1,5,4,4,5,5,5,1,5,4,5,5,11,0.0,neutral or dissatisfied +88393,111174,Female,Loyal Customer,7,Personal Travel,Business,1506,3,2,3,3,1,3,1,1,1,2,4,2,4,1,8,0.0,neutral or dissatisfied +88394,52300,Male,Loyal Customer,62,Business travel,Business,261,1,5,5,5,5,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +88395,90284,Male,disloyal Customer,49,Business travel,Business,757,1,1,1,4,4,1,5,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +88396,76835,Female,Loyal Customer,64,Personal Travel,Business,1195,1,5,1,2,5,3,5,2,2,1,2,5,2,3,2,0.0,neutral or dissatisfied +88397,57954,Male,disloyal Customer,35,Business travel,Eco,1062,3,3,3,3,2,3,2,2,1,2,1,5,5,2,0,0.0,neutral or dissatisfied +88398,9454,Female,Loyal Customer,27,Personal Travel,Eco,288,3,2,3,3,3,3,3,1,4,3,3,3,2,3,223,221.0,neutral or dissatisfied +88399,105105,Female,Loyal Customer,43,Business travel,Business,220,3,3,3,3,2,5,5,4,4,4,5,4,4,4,98,96.0,satisfied +88400,10481,Female,Loyal Customer,50,Business travel,Business,1849,0,0,0,2,2,4,4,2,2,2,2,3,2,4,31,33.0,satisfied +88401,121178,Female,Loyal Customer,41,Personal Travel,Eco,2521,3,2,3,4,3,1,1,4,1,2,4,1,1,1,36,36.0,neutral or dissatisfied +88402,21908,Female,disloyal Customer,36,Business travel,Eco,448,2,3,2,1,3,2,3,3,2,2,1,3,2,3,0,11.0,neutral or dissatisfied +88403,59238,Male,Loyal Customer,70,Personal Travel,Eco,649,2,3,2,3,3,2,3,3,1,5,4,2,4,3,0,11.0,neutral or dissatisfied +88404,16295,Female,Loyal Customer,38,Business travel,Eco Plus,748,5,3,2,3,5,5,5,5,4,5,1,1,1,5,0,0.0,satisfied +88405,86982,Male,Loyal Customer,60,Business travel,Business,507,3,4,4,4,2,4,3,3,3,3,3,2,3,2,39,34.0,neutral or dissatisfied +88406,113483,Female,Loyal Customer,43,Business travel,Business,223,2,2,2,2,3,5,4,4,4,4,5,5,4,4,0,0.0,satisfied +88407,98418,Male,Loyal Customer,25,Business travel,Business,2176,1,1,1,1,4,5,4,4,5,4,5,4,4,4,0,0.0,satisfied +88408,70267,Male,Loyal Customer,33,Business travel,Business,1921,1,5,5,5,1,1,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +88409,16415,Female,Loyal Customer,34,Business travel,Business,1688,5,5,5,5,5,5,1,3,3,4,3,3,3,1,32,11.0,satisfied +88410,96497,Male,Loyal Customer,47,Business travel,Eco,302,4,5,5,5,4,4,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +88411,46851,Female,Loyal Customer,49,Business travel,Eco,846,4,3,3,3,4,4,3,4,4,4,4,4,4,2,12,1.0,satisfied +88412,93683,Male,Loyal Customer,57,Personal Travel,Business,1452,1,5,1,3,5,5,5,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +88413,13567,Male,Loyal Customer,34,Personal Travel,Eco,227,2,5,0,3,4,0,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +88414,11655,Female,disloyal Customer,30,Business travel,Eco,878,4,4,4,5,3,4,5,3,3,1,3,5,4,3,0,0.0,neutral or dissatisfied +88415,101155,Female,Loyal Customer,46,Business travel,Business,1235,3,3,3,3,3,4,4,2,2,2,2,5,2,4,77,46.0,satisfied +88416,5733,Female,Loyal Customer,23,Personal Travel,Eco Plus,196,4,5,0,3,1,0,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +88417,97794,Female,Loyal Customer,18,Personal Travel,Eco,471,2,5,2,5,3,2,3,3,4,2,5,5,5,3,4,0.0,neutral or dissatisfied +88418,126081,Male,Loyal Customer,42,Business travel,Business,468,1,1,1,1,4,4,5,3,3,3,3,4,3,4,0,15.0,satisfied +88419,91046,Male,Loyal Customer,50,Personal Travel,Eco,581,3,5,3,3,3,3,3,3,5,4,4,4,4,3,1,0.0,neutral or dissatisfied +88420,117060,Female,Loyal Customer,43,Business travel,Business,3270,1,1,1,1,5,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +88421,88187,Male,Loyal Customer,25,Business travel,Business,1544,3,4,2,2,3,3,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +88422,116951,Male,Loyal Customer,58,Business travel,Business,369,3,3,2,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +88423,350,Female,Loyal Customer,25,Business travel,Business,853,5,5,5,5,4,4,4,4,5,5,5,4,5,4,0,12.0,satisfied +88424,92130,Female,Loyal Customer,46,Personal Travel,Eco,1535,2,2,3,4,5,4,3,3,3,3,3,2,3,3,4,0.0,neutral or dissatisfied +88425,60087,Male,Loyal Customer,46,Business travel,Business,3791,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +88426,85752,Male,disloyal Customer,22,Business travel,Eco,526,1,4,1,2,4,1,4,4,4,2,5,3,5,4,0,0.0,neutral or dissatisfied +88427,122526,Female,Loyal Customer,29,Business travel,Business,3672,5,5,5,5,5,5,5,5,4,2,4,5,4,5,9,3.0,satisfied +88428,113956,Male,Loyal Customer,25,Business travel,Business,1750,4,4,4,4,3,3,3,3,4,2,4,4,4,3,0,0.0,satisfied +88429,78583,Female,Loyal Customer,21,Personal Travel,Eco,630,2,5,2,4,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +88430,55699,Female,disloyal Customer,23,Business travel,Eco,1025,3,3,3,2,2,3,2,2,3,1,3,1,3,2,0,6.0,neutral or dissatisfied +88431,100315,Female,Loyal Customer,45,Business travel,Business,2174,3,3,3,3,5,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +88432,41380,Female,disloyal Customer,51,Business travel,Eco,563,3,5,3,3,5,3,3,5,1,1,3,4,1,5,57,56.0,neutral or dissatisfied +88433,16929,Male,Loyal Customer,44,Business travel,Business,820,3,3,3,3,4,4,2,4,4,4,4,5,4,3,0,0.0,satisfied +88434,77069,Male,Loyal Customer,39,Business travel,Business,3789,3,5,3,5,1,4,3,3,3,3,3,4,3,1,21,12.0,neutral or dissatisfied +88435,1106,Male,Loyal Customer,14,Personal Travel,Eco,102,2,3,2,3,1,2,1,1,5,5,3,1,2,1,0,3.0,neutral or dissatisfied +88436,88518,Female,Loyal Customer,35,Personal Travel,Eco,406,2,4,2,3,5,2,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +88437,68831,Female,Loyal Customer,43,Business travel,Business,3287,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +88438,88240,Female,Loyal Customer,56,Business travel,Business,581,3,3,3,3,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +88439,63591,Female,disloyal Customer,55,Business travel,Eco,633,3,0,3,5,4,3,4,4,5,2,4,1,2,4,0,0.0,neutral or dissatisfied +88440,83033,Male,disloyal Customer,22,Business travel,Business,1084,5,1,5,3,2,5,2,2,5,2,4,5,4,2,0,25.0,satisfied +88441,62114,Female,disloyal Customer,21,Business travel,Business,2434,5,0,5,2,3,0,3,3,3,4,4,4,5,3,0,30.0,satisfied +88442,66585,Female,Loyal Customer,44,Business travel,Business,761,1,1,1,1,4,4,5,5,5,5,5,4,5,5,18,18.0,satisfied +88443,41853,Female,disloyal Customer,25,Business travel,Eco,483,2,5,2,5,2,2,2,2,4,1,1,3,3,2,0,26.0,neutral or dissatisfied +88444,108499,Male,Loyal Customer,53,Business travel,Business,287,4,4,4,4,2,4,5,5,5,5,5,5,5,3,37,39.0,satisfied +88445,17649,Male,Loyal Customer,45,Business travel,Eco,1008,4,1,3,3,4,4,4,4,1,4,2,5,2,4,60,63.0,satisfied +88446,125700,Male,Loyal Customer,65,Personal Travel,Eco,899,5,4,5,4,5,5,2,5,1,2,4,4,3,5,43,32.0,satisfied +88447,40883,Male,Loyal Customer,53,Personal Travel,Eco,590,3,4,2,4,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +88448,54953,Female,Loyal Customer,45,Business travel,Business,1379,2,2,2,2,3,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +88449,32505,Female,disloyal Customer,20,Business travel,Eco,163,1,4,1,4,5,1,3,5,2,4,3,3,4,5,0,0.0,neutral or dissatisfied +88450,55556,Male,Loyal Customer,45,Business travel,Business,3870,3,3,3,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +88451,55269,Female,Loyal Customer,23,Personal Travel,Eco,2007,2,4,2,1,2,2,2,3,4,4,5,2,4,2,172,143.0,neutral or dissatisfied +88452,21822,Male,disloyal Customer,50,Business travel,Business,352,3,3,3,2,4,3,4,4,5,1,4,5,1,4,0,0.0,neutral or dissatisfied +88453,112947,Male,Loyal Customer,22,Personal Travel,Eco,1164,4,5,4,3,4,4,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +88454,15289,Female,Loyal Customer,43,Personal Travel,Eco,500,3,5,3,4,4,4,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +88455,99503,Female,Loyal Customer,62,Personal Travel,Eco,283,3,4,3,3,2,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +88456,112279,Female,Loyal Customer,60,Personal Travel,Eco,1546,2,2,2,3,2,3,3,2,2,2,2,2,2,2,16,5.0,neutral or dissatisfied +88457,80487,Male,Loyal Customer,30,Personal Travel,Eco Plus,1299,3,5,3,5,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +88458,96238,Male,Loyal Customer,40,Business travel,Business,2260,4,1,1,1,1,4,4,4,4,4,4,1,4,3,24,9.0,neutral or dissatisfied +88459,50885,Female,Loyal Customer,20,Personal Travel,Eco,89,2,3,2,4,2,2,2,2,4,1,4,3,4,2,0,3.0,neutral or dissatisfied +88460,35935,Male,Loyal Customer,13,Personal Travel,Eco,2381,3,4,3,3,3,3,3,3,1,3,4,3,3,3,2,0.0,neutral or dissatisfied +88461,69403,Male,disloyal Customer,23,Business travel,Eco,1096,1,1,1,3,3,1,5,3,3,1,2,1,2,3,0,7.0,neutral or dissatisfied +88462,115811,Female,disloyal Customer,44,Business travel,Eco,358,3,3,3,3,4,3,4,4,4,2,3,2,3,4,14,11.0,neutral or dissatisfied +88463,14034,Male,Loyal Customer,62,Personal Travel,Eco,1117,0,5,0,5,5,0,5,5,4,5,5,5,5,5,0,0.0,satisfied +88464,70951,Male,Loyal Customer,8,Personal Travel,Eco,612,4,5,5,1,4,5,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +88465,111468,Male,Loyal Customer,21,Personal Travel,Eco,836,2,4,2,1,3,2,5,3,3,4,4,4,4,3,18,0.0,neutral or dissatisfied +88466,129028,Female,Loyal Customer,45,Business travel,Business,2704,1,1,1,1,5,4,4,3,5,3,5,4,4,4,0,0.0,satisfied +88467,17679,Male,Loyal Customer,60,Business travel,Business,393,4,4,4,4,3,4,4,4,4,4,4,1,4,1,0,11.0,satisfied +88468,123778,Female,Loyal Customer,40,Business travel,Business,544,1,1,1,1,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +88469,101834,Male,Loyal Customer,51,Personal Travel,Eco,1521,1,5,1,1,5,1,1,5,5,5,4,3,4,5,28,12.0,neutral or dissatisfied +88470,43376,Male,Loyal Customer,44,Personal Travel,Eco,531,3,4,3,1,5,3,3,5,3,4,4,4,4,5,0,11.0,neutral or dissatisfied +88471,96016,Female,Loyal Customer,58,Business travel,Business,3332,4,4,4,4,4,5,5,4,4,4,4,3,4,5,5,14.0,satisfied +88472,44816,Male,Loyal Customer,30,Business travel,Eco Plus,978,4,3,3,3,4,4,4,4,2,4,4,1,1,4,36,26.0,satisfied +88473,31845,Female,Loyal Customer,26,Business travel,Business,2640,2,4,4,4,2,2,2,2,1,2,1,4,3,2,28,0.0,neutral or dissatisfied +88474,58511,Female,Loyal Customer,40,Personal Travel,Eco,719,4,5,4,4,5,4,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +88475,752,Female,Loyal Customer,47,Business travel,Business,3824,0,4,0,2,4,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +88476,70661,Male,Loyal Customer,46,Business travel,Business,1505,1,4,4,4,4,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +88477,95209,Male,Loyal Customer,45,Personal Travel,Eco,562,3,4,3,5,1,3,1,1,3,3,5,3,4,1,16,7.0,neutral or dissatisfied +88478,73534,Female,Loyal Customer,47,Business travel,Business,2461,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +88479,77615,Male,Loyal Customer,20,Business travel,Business,1971,3,3,3,3,4,4,4,4,4,2,5,4,4,4,0,0.0,satisfied +88480,72256,Male,Loyal Customer,30,Business travel,Business,2324,2,1,1,1,2,2,2,2,4,4,3,4,3,2,1,7.0,neutral or dissatisfied +88481,109243,Female,Loyal Customer,12,Personal Travel,Eco,483,1,4,5,3,4,5,4,4,3,5,4,3,4,4,53,53.0,neutral or dissatisfied +88482,98642,Female,Loyal Customer,23,Business travel,Business,966,3,4,1,4,3,3,3,3,4,1,2,3,2,3,0,4.0,neutral or dissatisfied +88483,59602,Male,Loyal Customer,60,Business travel,Business,3714,3,3,2,3,3,5,4,2,2,2,2,3,2,5,25,4.0,satisfied +88484,39275,Male,disloyal Customer,20,Business travel,Eco,67,5,0,5,5,5,5,5,5,3,3,5,3,3,5,0,0.0,satisfied +88485,71511,Male,Loyal Customer,44,Business travel,Business,1780,1,1,1,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +88486,64772,Female,Loyal Customer,60,Business travel,Business,469,3,3,3,3,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +88487,126397,Male,Loyal Customer,64,Personal Travel,Eco,328,3,0,3,5,5,3,5,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +88488,68507,Female,Loyal Customer,62,Personal Travel,Eco,1303,1,4,2,2,3,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +88489,34923,Male,Loyal Customer,29,Business travel,Business,187,0,4,0,3,2,2,2,2,1,1,4,1,3,2,0,0.0,satisfied +88490,87039,Female,Loyal Customer,48,Business travel,Business,645,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +88491,73412,Male,Loyal Customer,45,Business travel,Business,1772,3,1,1,1,3,3,3,1,4,2,1,3,3,3,123,151.0,neutral or dissatisfied +88492,30714,Female,disloyal Customer,36,Business travel,Eco,1123,4,4,4,5,5,4,5,5,5,3,2,5,3,5,0,7.0,neutral or dissatisfied +88493,84945,Female,Loyal Customer,51,Business travel,Business,1989,4,4,4,4,3,5,5,4,4,4,4,5,4,5,5,0.0,satisfied +88494,95996,Male,disloyal Customer,25,Business travel,Business,583,1,0,1,3,5,1,5,5,4,5,5,4,5,5,15,14.0,neutral or dissatisfied +88495,4809,Male,Loyal Customer,46,Business travel,Eco Plus,438,2,4,4,4,2,2,2,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +88496,91498,Female,Loyal Customer,55,Personal Travel,Eco,391,2,5,4,1,3,1,3,4,4,4,4,1,4,5,0,4.0,neutral or dissatisfied +88497,105998,Female,Loyal Customer,23,Business travel,Business,1999,3,3,3,3,5,5,5,5,4,4,3,5,5,5,25,35.0,satisfied +88498,14730,Male,Loyal Customer,17,Personal Travel,Eco Plus,419,3,3,3,1,5,3,5,5,1,4,3,2,1,5,0,0.0,neutral or dissatisfied +88499,104157,Female,disloyal Customer,21,Business travel,Eco,349,4,0,4,5,3,4,3,3,4,4,4,5,4,3,0,0.0,satisfied +88500,46337,Female,Loyal Customer,29,Business travel,Business,2801,2,2,5,2,2,2,2,2,4,1,1,2,5,2,0,6.0,satisfied +88501,77145,Female,Loyal Customer,39,Business travel,Business,1865,1,1,1,1,4,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +88502,97609,Female,disloyal Customer,30,Business travel,Eco,442,2,1,2,2,4,2,4,4,2,3,2,1,2,4,31,28.0,neutral or dissatisfied +88503,120494,Female,Loyal Customer,61,Personal Travel,Eco,337,4,4,4,3,3,4,3,1,1,4,1,2,1,4,0,0.0,satisfied +88504,127304,Male,Loyal Customer,18,Business travel,Business,1979,1,1,1,1,1,1,1,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +88505,77584,Female,Loyal Customer,31,Business travel,Business,689,1,1,1,1,5,5,5,5,3,5,4,5,5,5,0,0.0,satisfied +88506,1087,Male,Loyal Customer,52,Personal Travel,Eco,229,1,5,1,1,4,1,4,4,3,5,5,5,5,4,0,1.0,neutral or dissatisfied +88507,40829,Male,Loyal Customer,40,Business travel,Business,588,3,2,2,2,5,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +88508,9896,Male,Loyal Customer,51,Business travel,Business,3342,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +88509,48064,Female,Loyal Customer,52,Business travel,Business,192,0,4,0,4,2,4,5,4,4,4,4,5,4,3,118,125.0,satisfied +88510,12145,Female,Loyal Customer,56,Business travel,Business,1075,4,4,4,4,1,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +88511,114528,Female,Loyal Customer,14,Personal Travel,Business,417,2,5,2,1,3,2,2,3,1,5,1,4,1,3,0,0.0,neutral or dissatisfied +88512,9775,Male,Loyal Customer,61,Business travel,Eco,383,3,1,4,4,4,3,4,4,2,5,3,1,4,4,42,28.0,neutral or dissatisfied +88513,52485,Female,Loyal Customer,14,Personal Travel,Eco Plus,370,2,5,2,4,3,2,3,3,3,4,5,2,1,3,0,0.0,neutral or dissatisfied +88514,33858,Male,Loyal Customer,39,Personal Travel,Eco,1562,2,3,3,3,2,3,2,2,2,1,3,2,4,2,53,90.0,neutral or dissatisfied +88515,6382,Female,Loyal Customer,21,Business travel,Eco,296,3,3,3,3,3,3,3,3,4,1,4,1,4,3,6,16.0,neutral or dissatisfied +88516,12947,Female,Loyal Customer,44,Personal Travel,Eco,794,1,4,1,4,1,3,3,5,3,4,4,3,3,3,137,113.0,neutral or dissatisfied +88517,68628,Male,disloyal Customer,24,Business travel,Eco,175,2,0,2,3,5,2,5,5,3,4,5,3,5,5,0,2.0,neutral or dissatisfied +88518,1654,Female,Loyal Customer,53,Business travel,Business,2230,3,3,3,3,3,5,5,3,3,3,3,5,3,3,6,3.0,satisfied +88519,118180,Female,Loyal Customer,29,Business travel,Eco,1444,2,2,2,2,2,2,2,2,4,4,3,3,4,2,0,0.0,neutral or dissatisfied +88520,55259,Female,Loyal Customer,55,Business travel,Eco Plus,609,4,4,4,4,3,1,4,4,4,4,4,5,4,3,14,10.0,satisfied +88521,107140,Female,Loyal Customer,51,Business travel,Business,1864,3,3,3,3,4,5,4,4,4,4,4,5,4,3,5,10.0,satisfied +88522,95274,Female,Loyal Customer,69,Personal Travel,Eco,239,3,4,3,5,1,3,5,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +88523,79571,Female,Loyal Customer,37,Business travel,Business,1511,5,5,2,5,4,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +88524,79453,Female,Loyal Customer,51,Business travel,Business,1183,2,2,2,2,2,5,5,5,5,5,5,4,5,3,33,19.0,satisfied +88525,46454,Female,disloyal Customer,23,Business travel,Business,141,4,0,5,4,4,5,4,4,5,4,5,4,5,4,54,51.0,satisfied +88526,29870,Female,Loyal Customer,38,Business travel,Eco,399,5,5,2,5,5,5,5,5,4,3,3,1,3,5,0,0.0,satisfied +88527,55951,Female,Loyal Customer,37,Business travel,Business,1620,3,3,1,3,3,4,4,5,5,4,5,5,5,3,0,0.0,satisfied +88528,76873,Male,Loyal Customer,46,Business travel,Business,1794,5,5,2,5,3,4,4,4,4,4,4,5,4,3,2,0.0,satisfied +88529,12598,Female,Loyal Customer,62,Personal Travel,Eco,542,4,4,4,4,3,3,2,1,1,4,1,4,1,1,0,0.0,neutral or dissatisfied +88530,56173,Female,disloyal Customer,62,Business travel,Eco,1000,4,4,4,2,3,4,3,3,4,4,1,2,3,3,18,29.0,neutral or dissatisfied +88531,38676,Male,Loyal Customer,54,Personal Travel,Eco,2602,3,4,3,5,2,3,2,2,4,5,4,2,2,2,49,21.0,neutral or dissatisfied +88532,118563,Female,Loyal Customer,39,Business travel,Business,3706,0,0,0,4,5,4,4,1,1,1,1,3,1,5,0,0.0,satisfied +88533,115457,Female,disloyal Customer,23,Business travel,Eco,372,3,3,3,3,3,3,3,3,1,3,2,2,3,3,12,2.0,neutral or dissatisfied +88534,95305,Female,Loyal Customer,59,Personal Travel,Eco,562,4,5,4,3,5,5,5,1,1,4,1,4,1,4,0,12.0,neutral or dissatisfied +88535,113502,Male,disloyal Customer,20,Business travel,Eco,258,5,0,5,1,3,5,1,3,5,3,5,5,5,3,0,0.0,satisfied +88536,96242,Female,Loyal Customer,38,Personal Travel,Eco,546,4,4,4,2,2,4,2,2,1,5,1,2,3,2,0,0.0,satisfied +88537,4276,Male,Loyal Customer,13,Business travel,Eco,502,3,4,4,4,3,3,1,3,3,3,4,3,3,3,23,29.0,neutral or dissatisfied +88538,1911,Male,Loyal Customer,40,Business travel,Business,383,4,4,5,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +88539,90186,Female,Loyal Customer,16,Personal Travel,Eco,957,3,5,3,2,1,3,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +88540,12638,Male,disloyal Customer,25,Business travel,Eco,844,2,2,2,2,3,2,3,3,2,4,1,3,4,3,16,2.0,neutral or dissatisfied +88541,50190,Female,disloyal Customer,58,Business travel,Eco,308,3,3,3,4,5,3,5,5,1,2,4,4,3,5,0,5.0,neutral or dissatisfied +88542,99441,Female,Loyal Customer,41,Personal Travel,Eco Plus,314,2,4,2,4,3,4,4,3,3,2,2,3,3,4,19,44.0,neutral or dissatisfied +88543,123811,Female,Loyal Customer,52,Business travel,Business,544,5,5,5,5,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +88544,120892,Male,Loyal Customer,42,Business travel,Business,951,2,2,2,2,5,5,5,2,2,2,2,3,2,4,59,73.0,satisfied +88545,49383,Male,disloyal Customer,34,Business travel,Business,363,3,3,3,4,5,3,5,5,4,3,4,2,4,5,0,0.0,neutral or dissatisfied +88546,8379,Male,Loyal Customer,56,Business travel,Eco,773,5,5,5,5,5,5,5,5,4,4,5,5,4,5,21,27.0,satisfied +88547,67274,Female,Loyal Customer,15,Personal Travel,Eco,1121,2,4,1,3,4,1,4,4,4,2,4,4,4,4,8,7.0,neutral or dissatisfied +88548,21028,Male,Loyal Customer,65,Business travel,Eco,227,5,2,2,2,4,5,4,4,1,5,5,3,3,4,0,0.0,satisfied +88549,84795,Male,Loyal Customer,46,Business travel,Business,2275,4,4,4,4,5,5,4,4,4,4,4,3,4,3,22,15.0,satisfied +88550,96713,Male,Loyal Customer,51,Business travel,Business,696,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +88551,127718,Male,Loyal Customer,39,Business travel,Business,1645,4,2,4,4,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +88552,30184,Male,Loyal Customer,43,Business travel,Eco Plus,31,5,5,4,5,4,5,4,4,4,3,5,5,2,4,0,0.0,satisfied +88553,28645,Male,Loyal Customer,27,Personal Travel,Eco,2614,1,5,1,1,4,1,2,4,3,3,4,4,4,4,12,,neutral or dissatisfied +88554,12314,Female,Loyal Customer,38,Business travel,Business,2112,3,3,3,3,1,4,1,4,4,4,4,2,4,5,1,1.0,satisfied +88555,34768,Male,Loyal Customer,40,Business travel,Business,3889,5,5,5,5,4,2,4,5,5,5,5,5,5,1,0,0.0,satisfied +88556,44047,Male,Loyal Customer,46,Personal Travel,Eco,67,1,4,1,2,2,1,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +88557,35116,Male,Loyal Customer,19,Business travel,Business,1028,4,4,4,4,5,5,5,5,3,3,2,4,1,5,0,0.0,satisfied +88558,63089,Female,Loyal Customer,44,Business travel,Business,1726,2,2,2,2,4,5,5,3,3,3,3,3,3,4,7,0.0,satisfied +88559,76564,Male,Loyal Customer,20,Business travel,Eco,547,1,4,4,4,1,1,1,1,3,5,4,4,4,1,5,10.0,neutral or dissatisfied +88560,94055,Male,Loyal Customer,37,Business travel,Business,239,4,4,4,4,5,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +88561,73773,Male,Loyal Customer,21,Personal Travel,Eco,204,4,5,4,4,2,4,2,2,3,5,3,5,3,2,0,1.0,neutral or dissatisfied +88562,81453,Female,Loyal Customer,40,Business travel,Business,3253,2,2,2,2,5,4,5,4,4,4,4,4,4,4,8,3.0,satisfied +88563,120581,Male,Loyal Customer,58,Business travel,Business,980,4,4,4,4,2,4,4,5,5,5,5,4,5,4,14,9.0,satisfied +88564,24880,Female,Loyal Customer,13,Business travel,Business,534,4,4,4,4,5,5,5,5,3,5,2,2,1,5,2,0.0,satisfied +88565,10602,Male,disloyal Customer,22,Business travel,Eco,166,2,0,2,4,3,2,1,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +88566,90740,Female,disloyal Customer,50,Business travel,Eco,594,3,2,3,3,4,3,2,4,1,5,2,4,3,4,12,9.0,neutral or dissatisfied +88567,85469,Female,disloyal Customer,27,Business travel,Eco,152,1,1,1,3,3,1,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +88568,85238,Male,disloyal Customer,37,Business travel,Eco,296,4,0,4,3,2,4,2,2,1,1,2,3,3,2,0,0.0,neutral or dissatisfied +88569,78780,Female,disloyal Customer,30,Business travel,Business,432,0,0,0,2,4,0,4,4,5,2,5,4,4,4,0,0.0,satisfied +88570,98483,Female,Loyal Customer,42,Business travel,Business,3378,4,4,4,4,4,4,4,5,4,5,4,4,5,4,158,142.0,satisfied +88571,56604,Female,Loyal Customer,61,Business travel,Business,3132,3,3,3,3,5,3,3,3,3,3,3,2,3,1,69,69.0,neutral or dissatisfied +88572,127669,Male,Loyal Customer,48,Business travel,Eco,2153,1,3,3,3,1,1,1,1,2,4,2,4,3,1,0,10.0,neutral or dissatisfied +88573,58900,Female,Loyal Customer,40,Business travel,Eco,888,5,5,5,5,5,4,5,5,3,1,3,4,2,5,42,75.0,neutral or dissatisfied +88574,77614,Male,Loyal Customer,58,Business travel,Business,3554,5,5,5,5,4,4,4,4,4,4,4,4,4,5,14,9.0,satisfied +88575,17068,Male,Loyal Customer,47,Business travel,Business,282,1,1,1,1,4,5,4,5,5,5,5,1,5,5,0,0.0,satisfied +88576,46147,Female,Loyal Customer,39,Business travel,Eco,627,2,3,3,3,2,2,2,2,1,3,2,3,2,2,17,22.0,neutral or dissatisfied +88577,18234,Female,disloyal Customer,55,Business travel,Eco,137,5,5,5,3,5,4,2,3,5,4,1,2,1,2,355,346.0,satisfied +88578,26640,Male,Loyal Customer,59,Business travel,Eco,406,4,2,2,2,4,4,4,4,2,2,3,2,2,4,6,0.0,satisfied +88579,75858,Male,Loyal Customer,11,Personal Travel,Eco,1440,2,5,1,2,4,1,4,4,3,4,5,3,5,4,21,0.0,neutral or dissatisfied +88580,82318,Female,Loyal Customer,39,Business travel,Business,1566,1,3,1,1,5,4,4,5,5,5,5,3,5,5,38,38.0,satisfied +88581,20262,Male,disloyal Customer,36,Business travel,Business,235,3,3,3,5,1,3,3,1,5,2,2,4,4,1,61,60.0,neutral or dissatisfied +88582,92178,Male,Loyal Customer,30,Business travel,Eco,1979,2,5,5,5,2,2,2,2,3,2,2,4,3,2,36,31.0,neutral or dissatisfied +88583,110168,Male,Loyal Customer,63,Personal Travel,Eco,1072,3,2,3,3,2,3,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +88584,99066,Female,Loyal Customer,43,Business travel,Business,2237,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +88585,14715,Female,Loyal Customer,66,Personal Travel,Eco,419,1,3,1,4,5,3,3,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +88586,73346,Female,disloyal Customer,24,Business travel,Business,1197,2,1,2,3,4,2,4,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +88587,129563,Female,Loyal Customer,11,Personal Travel,Eco,2342,2,5,2,1,5,2,5,5,4,2,2,1,5,5,74,66.0,neutral or dissatisfied +88588,5908,Male,Loyal Customer,39,Business travel,Business,67,4,4,4,4,3,4,2,5,5,5,5,1,5,2,0,0.0,satisfied +88589,79037,Female,Loyal Customer,41,Business travel,Business,2097,3,3,3,3,2,5,5,5,5,5,5,3,5,3,24,11.0,satisfied +88590,70810,Female,Loyal Customer,26,Business travel,Business,624,2,1,1,1,2,2,2,2,1,3,3,3,4,2,12,39.0,neutral or dissatisfied +88591,28362,Male,Loyal Customer,33,Personal Travel,Eco Plus,867,1,1,1,4,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +88592,77427,Male,Loyal Customer,26,Personal Travel,Eco,588,3,5,3,3,3,3,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +88593,64889,Female,disloyal Customer,27,Business travel,Eco,247,4,4,4,3,3,4,3,3,4,5,3,1,4,3,0,11.0,neutral or dissatisfied +88594,40469,Male,Loyal Customer,46,Business travel,Business,2649,4,4,4,4,2,3,5,4,4,4,4,1,4,2,0,0.0,satisfied +88595,69543,Female,Loyal Customer,44,Business travel,Eco,2475,2,1,1,1,2,1,1,1,1,3,4,1,1,1,0,0.0,neutral or dissatisfied +88596,49415,Female,Loyal Customer,37,Business travel,Business,2441,5,5,5,5,1,4,1,5,5,5,5,5,5,5,0,0.0,satisfied +88597,127045,Female,Loyal Customer,66,Business travel,Eco,304,3,1,1,1,3,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +88598,89858,Male,disloyal Customer,46,Business travel,Business,1501,2,2,2,5,3,2,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +88599,51515,Female,Loyal Customer,53,Business travel,Business,261,0,0,0,4,1,4,2,4,4,1,1,3,4,3,0,0.0,satisfied +88600,101164,Female,Loyal Customer,14,Business travel,Eco,583,4,5,5,5,4,4,3,4,2,5,4,2,4,4,20,19.0,neutral or dissatisfied +88601,8482,Female,Loyal Customer,43,Personal Travel,Eco,1187,1,4,1,2,5,3,4,2,2,1,1,4,2,3,2,12.0,neutral or dissatisfied +88602,87045,Male,Loyal Customer,56,Business travel,Business,3233,3,3,3,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +88603,67084,Male,disloyal Customer,25,Business travel,Eco,1017,3,3,3,2,2,3,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +88604,76338,Female,Loyal Customer,48,Business travel,Business,2411,2,2,2,2,5,4,5,5,5,5,5,3,5,4,44,64.0,satisfied +88605,115277,Female,disloyal Customer,38,Business travel,Business,417,4,3,3,4,5,3,5,5,5,3,5,5,4,5,20,7.0,neutral or dissatisfied +88606,105467,Male,Loyal Customer,33,Business travel,Business,495,3,3,3,3,5,5,5,5,4,4,4,3,5,5,3,0.0,satisfied +88607,81875,Male,Loyal Customer,34,Personal Travel,Eco,1050,2,5,2,2,2,2,2,2,5,3,4,5,5,2,6,0.0,neutral or dissatisfied +88608,79512,Female,disloyal Customer,34,Business travel,Business,749,2,2,2,2,3,2,1,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +88609,84474,Male,Loyal Customer,54,Personal Travel,Eco,1142,2,5,2,2,2,2,2,2,1,3,5,3,2,2,0,0.0,neutral or dissatisfied +88610,77368,Female,disloyal Customer,24,Business travel,Eco,588,3,1,3,2,1,3,1,1,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +88611,50829,Male,Loyal Customer,45,Personal Travel,Eco,134,3,4,0,3,4,0,4,4,5,2,5,3,4,4,4,0.0,neutral or dissatisfied +88612,80558,Female,Loyal Customer,48,Business travel,Business,1747,2,2,2,2,3,3,5,4,4,4,4,5,4,5,3,13.0,satisfied +88613,2573,Female,Loyal Customer,53,Business travel,Business,3106,1,3,3,3,2,3,2,2,2,2,1,2,2,1,0,0.0,neutral or dissatisfied +88614,76039,Female,disloyal Customer,29,Business travel,Business,669,5,5,5,3,4,5,4,4,3,2,4,4,4,4,61,39.0,satisfied +88615,56796,Male,Loyal Customer,49,Business travel,Business,1605,3,3,3,3,2,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +88616,41766,Male,Loyal Customer,51,Business travel,Business,3681,2,2,2,2,5,1,2,2,2,2,2,1,2,1,0,5.0,neutral or dissatisfied +88617,65578,Male,Loyal Customer,20,Business travel,Business,237,3,3,3,3,5,5,5,5,4,5,5,4,4,5,15,10.0,satisfied +88618,70636,Male,Loyal Customer,54,Personal Travel,Eco Plus,1217,1,3,1,1,5,1,3,5,5,1,3,5,5,5,0,7.0,neutral or dissatisfied +88619,45579,Female,Loyal Customer,12,Personal Travel,Business,260,3,4,0,3,4,0,4,4,2,4,4,2,3,4,38,20.0,neutral or dissatisfied +88620,17937,Female,Loyal Customer,35,Business travel,Eco,95,5,2,2,2,5,5,5,5,3,1,1,1,3,5,10,2.0,satisfied +88621,60329,Male,Loyal Customer,48,Business travel,Business,1024,3,3,3,3,2,5,5,5,5,5,5,5,5,4,0,29.0,satisfied +88622,126483,Male,Loyal Customer,30,Business travel,Business,1849,1,2,2,2,1,1,1,1,2,5,2,4,4,1,0,0.0,neutral or dissatisfied +88623,64981,Female,Loyal Customer,30,Business travel,Business,247,2,2,2,2,4,4,4,4,1,3,2,1,5,4,0,0.0,satisfied +88624,101036,Male,Loyal Customer,47,Personal Travel,Eco Plus,806,3,2,3,4,5,3,5,5,2,2,3,1,4,5,18,0.0,neutral or dissatisfied +88625,117003,Female,Loyal Customer,57,Business travel,Business,2303,5,5,2,5,3,4,4,5,5,5,5,4,5,3,19,13.0,satisfied +88626,94905,Male,disloyal Customer,22,Business travel,Eco,187,4,0,4,3,3,4,5,3,2,1,3,5,2,3,0,0.0,satisfied +88627,126818,Female,Loyal Customer,59,Business travel,Business,2077,5,5,5,5,2,4,4,5,5,5,5,3,5,4,6,0.0,satisfied +88628,33356,Female,Loyal Customer,27,Business travel,Business,2349,4,5,4,4,5,5,5,5,2,4,5,1,3,5,4,0.0,satisfied +88629,85419,Male,Loyal Customer,61,Business travel,Business,2998,2,2,4,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +88630,98893,Male,Loyal Customer,22,Business travel,Business,3714,5,5,5,5,5,5,5,5,5,4,4,4,4,5,5,0.0,satisfied +88631,68585,Male,Loyal Customer,32,Personal Travel,Eco,1616,1,2,1,2,5,1,5,5,1,4,1,4,2,5,0,0.0,neutral or dissatisfied +88632,2237,Female,Loyal Customer,55,Business travel,Business,859,4,4,4,4,4,4,4,4,4,4,4,5,4,5,40,26.0,satisfied +88633,62428,Female,Loyal Customer,37,Business travel,Eco,170,5,1,1,1,5,5,5,5,3,5,2,2,5,5,0,0.0,satisfied +88634,56935,Female,Loyal Customer,44,Business travel,Business,2454,2,2,2,2,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +88635,42804,Female,Loyal Customer,40,Business travel,Eco,677,4,2,2,2,4,4,4,4,3,5,5,2,1,4,13,14.0,satisfied +88636,35544,Female,Loyal Customer,65,Personal Travel,Eco,1069,2,3,2,5,5,3,3,4,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +88637,18890,Female,Loyal Customer,39,Business travel,Business,448,3,3,3,3,3,4,2,4,4,4,4,3,4,1,6,3.0,satisfied +88638,2889,Female,Loyal Customer,25,Personal Travel,Eco,409,3,3,3,3,4,3,4,4,2,1,4,5,1,4,9,21.0,neutral or dissatisfied +88639,117326,Female,Loyal Customer,34,Personal Travel,Eco Plus,370,3,4,2,5,2,2,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +88640,61746,Male,disloyal Customer,29,Business travel,Eco,1379,2,2,2,4,1,2,1,1,5,5,5,3,2,1,4,0.0,neutral or dissatisfied +88641,37449,Female,Loyal Customer,26,Business travel,Business,1165,1,1,2,1,5,5,5,5,4,5,3,2,2,5,42,15.0,satisfied +88642,118199,Female,Loyal Customer,43,Personal Travel,Eco,1444,0,0,0,2,5,5,5,3,3,0,3,5,3,4,13,2.0,satisfied +88643,15524,Female,disloyal Customer,20,Business travel,Eco,164,2,2,2,3,1,2,1,1,4,3,3,1,3,1,0,3.0,neutral or dissatisfied +88644,79828,Female,Loyal Customer,51,Business travel,Business,1080,2,2,2,2,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +88645,2760,Female,Loyal Customer,38,Personal Travel,Eco Plus,695,3,4,3,3,2,3,3,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +88646,34632,Male,Loyal Customer,36,Business travel,Business,2333,4,4,4,4,4,3,2,5,5,5,5,3,5,2,0,0.0,satisfied +88647,39650,Female,Loyal Customer,43,Business travel,Eco,1136,5,4,4,4,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +88648,98981,Female,Loyal Customer,17,Personal Travel,Eco,569,1,4,1,4,1,1,1,1,5,2,5,3,4,1,9,1.0,neutral or dissatisfied +88649,108392,Female,Loyal Customer,48,Business travel,Business,1855,5,5,5,5,2,4,4,3,3,3,3,3,3,4,13,0.0,satisfied +88650,76997,Female,Loyal Customer,57,Business travel,Business,1611,5,5,3,5,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +88651,93560,Male,Loyal Customer,40,Business travel,Business,2903,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +88652,55614,Male,Loyal Customer,32,Personal Travel,Eco,404,2,4,2,3,4,2,4,4,3,2,4,3,5,4,20,0.0,neutral or dissatisfied +88653,68835,Female,Loyal Customer,20,Personal Travel,Business,1061,5,5,5,1,3,5,3,3,4,2,4,5,4,3,0,0.0,satisfied +88654,63493,Female,Loyal Customer,29,Personal Travel,Eco,651,1,2,2,4,2,2,2,2,4,3,4,3,3,2,10,0.0,neutral or dissatisfied +88655,82,Male,Loyal Customer,39,Personal Travel,Eco,108,1,2,1,4,2,1,2,2,3,1,4,2,4,2,0,7.0,neutral or dissatisfied +88656,126305,Female,Loyal Customer,13,Personal Travel,Eco,507,2,2,2,2,3,2,3,3,4,3,2,3,3,3,0,1.0,neutral or dissatisfied +88657,83772,Male,Loyal Customer,10,Personal Travel,Eco,926,2,4,2,1,4,2,4,4,4,3,5,2,5,4,0,0.0,neutral or dissatisfied +88658,96971,Male,Loyal Customer,56,Business travel,Business,2287,4,4,4,4,5,4,4,4,4,4,4,3,4,5,2,0.0,satisfied +88659,28371,Male,Loyal Customer,56,Business travel,Eco,763,4,1,1,1,4,4,4,4,4,4,4,1,3,4,0,0.0,satisfied +88660,118647,Female,Loyal Customer,44,Business travel,Eco,368,2,2,4,2,1,4,4,2,2,2,2,4,2,1,51,48.0,neutral or dissatisfied +88661,62650,Male,Loyal Customer,23,Personal Travel,Eco,1744,2,4,2,3,2,2,2,2,4,5,3,5,4,2,0,0.0,neutral or dissatisfied +88662,47436,Male,Loyal Customer,59,Business travel,Business,1589,5,5,5,5,3,1,1,4,4,4,4,1,4,2,0,0.0,satisfied +88663,76556,Female,disloyal Customer,30,Business travel,Eco,516,3,2,2,3,4,2,4,4,1,4,4,1,4,4,0,0.0,neutral or dissatisfied +88664,125858,Female,Loyal Customer,47,Business travel,Eco,1013,1,4,4,4,3,2,2,1,1,1,1,3,1,1,12,28.0,neutral or dissatisfied +88665,78373,Male,disloyal Customer,30,Business travel,Business,980,4,4,4,3,4,4,4,4,5,4,5,5,5,4,0,0.0,satisfied +88666,122560,Male,Loyal Customer,64,Personal Travel,Eco,500,2,5,2,2,4,2,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +88667,120688,Male,Loyal Customer,26,Personal Travel,Eco,280,3,5,3,2,5,3,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +88668,63581,Female,Loyal Customer,48,Business travel,Business,2133,2,2,3,2,5,4,4,2,2,2,2,4,2,5,96,75.0,satisfied +88669,65484,Male,Loyal Customer,70,Personal Travel,Eco,1303,2,5,2,2,3,2,5,3,1,1,4,1,5,3,5,0.0,neutral or dissatisfied +88670,107439,Male,Loyal Customer,27,Personal Travel,Eco,468,4,4,4,5,3,4,3,3,5,4,5,5,4,3,3,0.0,neutral or dissatisfied +88671,64096,Female,Loyal Customer,64,Personal Travel,Eco,919,4,4,5,3,4,5,1,4,4,5,4,5,4,5,0,1.0,neutral or dissatisfied +88672,85897,Female,Loyal Customer,42,Business travel,Business,3823,2,3,3,3,2,2,1,2,2,2,2,2,2,2,2,0.0,neutral or dissatisfied +88673,127855,Male,disloyal Customer,44,Business travel,Business,1276,4,4,4,3,3,4,3,3,5,4,4,5,5,3,3,4.0,satisfied +88674,31540,Female,Loyal Customer,15,Personal Travel,Eco,862,3,4,3,5,2,3,2,2,4,1,5,5,2,2,0,0.0,neutral or dissatisfied +88675,18860,Male,disloyal Customer,21,Business travel,Eco,503,4,1,4,3,3,4,3,3,3,1,2,1,2,3,3,0.0,neutral or dissatisfied +88676,61682,Male,Loyal Customer,46,Business travel,Business,1609,2,2,2,2,5,3,4,4,4,4,4,4,4,3,5,0.0,satisfied +88677,68797,Male,Loyal Customer,58,Personal Travel,Eco,1021,3,4,4,4,5,4,5,5,1,2,5,4,5,5,0,0.0,neutral or dissatisfied +88678,85681,Female,Loyal Customer,36,Personal Travel,Business,1547,1,5,1,5,2,5,4,1,1,1,4,5,1,5,12,11.0,neutral or dissatisfied +88679,55737,Male,Loyal Customer,40,Business travel,Business,2052,3,3,3,3,3,3,5,4,4,4,4,3,4,3,0,2.0,satisfied +88680,109006,Male,Loyal Customer,49,Business travel,Business,928,1,1,1,1,4,5,4,4,4,3,4,4,4,3,0,8.0,satisfied +88681,47912,Male,Loyal Customer,40,Personal Travel,Eco,329,3,5,2,4,4,2,4,4,5,1,5,1,2,4,0,0.0,neutral or dissatisfied +88682,40231,Female,disloyal Customer,23,Business travel,Eco,358,2,0,3,3,4,3,1,4,1,1,5,4,3,4,0,0.0,neutral or dissatisfied +88683,1938,Male,Loyal Customer,51,Business travel,Business,190,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +88684,64554,Male,Loyal Customer,33,Business travel,Business,2841,2,2,2,2,4,4,4,4,3,5,5,3,5,4,3,0.0,satisfied +88685,3244,Male,Loyal Customer,69,Business travel,Business,479,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +88686,12455,Male,Loyal Customer,64,Personal Travel,Eco,201,0,4,0,2,3,0,3,3,1,4,5,3,1,3,0,0.0,satisfied +88687,2474,Female,Loyal Customer,38,Business travel,Business,1817,3,3,3,3,4,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +88688,66680,Male,Loyal Customer,59,Business travel,Business,802,1,1,1,1,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +88689,3798,Female,Loyal Customer,15,Personal Travel,Eco Plus,599,2,5,2,3,5,2,2,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +88690,5764,Male,Loyal Customer,55,Personal Travel,Eco,859,2,2,2,3,2,2,2,2,4,4,3,2,4,2,2,24.0,neutral or dissatisfied +88691,83038,Male,Loyal Customer,34,Business travel,Business,2778,1,1,1,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +88692,35218,Female,Loyal Customer,37,Business travel,Business,1766,3,5,2,5,3,3,3,2,3,4,4,3,3,3,108,133.0,neutral or dissatisfied +88693,37218,Male,disloyal Customer,28,Business travel,Business,972,3,3,3,3,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +88694,33741,Male,Loyal Customer,25,Personal Travel,Eco Plus,899,1,4,1,5,5,1,5,5,1,1,1,3,4,5,0,0.0,neutral or dissatisfied +88695,111337,Male,Loyal Customer,34,Personal Travel,Eco,283,5,4,5,4,1,5,1,1,4,4,5,4,5,1,0,0.0,satisfied +88696,40665,Male,Loyal Customer,26,Business travel,Business,2009,3,1,1,1,3,2,3,3,2,4,2,4,1,3,52,59.0,neutral or dissatisfied +88697,81295,Male,Loyal Customer,43,Personal Travel,Eco,1029,2,2,1,4,4,1,4,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +88698,76378,Male,Loyal Customer,24,Business travel,Business,1573,1,3,4,3,1,2,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +88699,72369,Female,Loyal Customer,47,Business travel,Business,2165,5,5,5,5,4,4,5,3,3,3,3,3,3,4,0,3.0,satisfied +88700,87604,Female,Loyal Customer,40,Business travel,Business,606,5,5,5,5,4,4,5,4,4,4,4,5,4,5,7,7.0,satisfied +88701,65521,Female,disloyal Customer,50,Business travel,Business,1493,5,5,5,3,5,5,2,5,4,4,5,3,5,5,1,6.0,satisfied +88702,94243,Female,Loyal Customer,42,Business travel,Business,239,1,1,1,1,2,4,4,5,5,5,5,4,5,3,2,4.0,satisfied +88703,4467,Female,Loyal Customer,35,Personal Travel,Eco,1005,0,4,0,2,3,0,1,3,3,2,5,3,5,3,80,75.0,satisfied +88704,49621,Male,Loyal Customer,41,Business travel,Eco,158,5,1,1,1,5,5,5,5,1,5,3,2,5,5,0,0.0,satisfied +88705,67685,Female,disloyal Customer,26,Business travel,Eco,1205,4,4,4,4,1,4,1,1,1,1,4,1,4,1,0,0.0,neutral or dissatisfied +88706,47071,Female,Loyal Customer,34,Personal Travel,Eco,351,1,5,1,3,3,1,5,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +88707,54207,Male,Loyal Customer,43,Business travel,Eco Plus,1504,1,1,1,1,1,1,1,1,1,5,4,1,3,1,11,74.0,neutral or dissatisfied +88708,107333,Male,disloyal Customer,29,Business travel,Business,632,2,2,2,1,1,2,1,1,4,5,5,3,5,1,21,7.0,neutral or dissatisfied +88709,98949,Male,Loyal Customer,22,Business travel,Eco,479,2,3,3,3,2,2,1,2,3,2,4,2,4,2,23,28.0,neutral or dissatisfied +88710,52106,Female,Loyal Customer,33,Personal Travel,Eco,639,3,5,3,1,5,3,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +88711,113673,Male,Loyal Customer,54,Personal Travel,Eco,226,1,5,0,2,1,0,1,1,5,5,4,5,4,1,17,7.0,neutral or dissatisfied +88712,118995,Female,Loyal Customer,42,Business travel,Business,1772,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,1.0,satisfied +88713,16538,Female,Loyal Customer,39,Business travel,Business,2202,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +88714,124999,Female,Loyal Customer,53,Business travel,Business,184,2,3,3,3,2,3,3,0,0,1,2,3,0,4,0,0.0,neutral or dissatisfied +88715,104781,Female,Loyal Customer,46,Business travel,Business,587,5,5,5,5,5,5,4,5,5,5,5,4,5,3,18,25.0,satisfied +88716,114907,Female,Loyal Customer,52,Business travel,Business,2568,3,3,3,3,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +88717,83687,Male,Loyal Customer,43,Business travel,Business,1517,1,1,1,1,1,2,1,5,5,5,4,3,5,2,0,0.0,satisfied +88718,66596,Female,disloyal Customer,19,Business travel,Eco,761,1,1,1,4,5,1,5,5,3,1,3,3,4,5,0,7.0,neutral or dissatisfied +88719,60241,Male,Loyal Customer,42,Personal Travel,Eco,1546,2,4,2,4,4,2,4,4,3,5,4,4,4,4,22,11.0,neutral or dissatisfied +88720,13583,Male,Loyal Customer,17,Personal Travel,Eco,106,2,3,0,2,2,0,2,2,2,3,1,4,5,2,0,0.0,neutral or dissatisfied +88721,57597,Female,Loyal Customer,48,Personal Travel,Eco Plus,1597,4,5,4,3,5,4,4,1,1,4,1,3,1,4,36,3.0,neutral or dissatisfied +88722,87420,Female,Loyal Customer,67,Personal Travel,Eco,425,3,2,3,4,2,4,3,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +88723,13530,Male,Loyal Customer,55,Business travel,Business,152,3,3,3,3,1,2,4,4,4,4,4,1,4,5,0,4.0,satisfied +88724,26560,Male,Loyal Customer,38,Business travel,Business,2969,3,3,3,3,3,4,5,4,4,4,4,3,4,5,6,0.0,satisfied +88725,24425,Female,Loyal Customer,33,Business travel,Eco,634,3,3,5,3,3,3,3,3,4,3,3,3,3,3,0,7.0,neutral or dissatisfied +88726,122577,Male,Loyal Customer,56,Business travel,Business,2226,5,5,5,5,4,4,5,4,4,5,4,4,4,3,0,24.0,satisfied +88727,98595,Female,Loyal Customer,44,Business travel,Business,3618,2,2,2,2,2,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +88728,34315,Male,Loyal Customer,25,Business travel,Eco Plus,280,2,4,4,4,2,3,2,2,3,1,3,2,4,2,25,9.0,neutral or dissatisfied +88729,97006,Female,Loyal Customer,22,Personal Travel,Eco,359,1,4,1,3,3,1,3,3,2,5,3,2,3,3,3,32.0,neutral or dissatisfied +88730,67601,Male,Loyal Customer,37,Business travel,Business,1438,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,6.0,satisfied +88731,1247,Male,Loyal Customer,48,Personal Travel,Eco,102,1,3,1,4,1,1,1,1,4,1,1,4,2,1,1,0.0,neutral or dissatisfied +88732,49736,Female,Loyal Customer,40,Business travel,Eco,421,4,1,1,1,4,4,4,4,2,5,2,1,3,4,0,0.0,satisfied +88733,117462,Female,Loyal Customer,20,Personal Travel,Eco Plus,1107,3,3,3,4,5,3,5,5,4,2,4,4,5,5,9,40.0,neutral or dissatisfied +88734,3456,Male,Loyal Customer,67,Business travel,Eco Plus,315,2,4,4,4,2,2,2,2,3,1,4,1,4,2,0,0.0,neutral or dissatisfied +88735,92966,Female,Loyal Customer,17,Personal Travel,Eco,1694,1,3,1,4,1,1,5,1,2,1,4,4,4,1,8,0.0,neutral or dissatisfied +88736,98633,Male,Loyal Customer,55,Business travel,Business,2027,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +88737,85333,Male,Loyal Customer,54,Business travel,Business,1855,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +88738,63174,Male,Loyal Customer,56,Business travel,Business,3943,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +88739,9224,Female,Loyal Customer,47,Business travel,Business,157,2,2,2,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +88740,49459,Male,disloyal Customer,61,Business travel,Eco,262,2,0,2,2,5,2,5,5,3,2,4,3,5,5,86,77.0,neutral or dissatisfied +88741,76035,Male,Loyal Customer,66,Business travel,Business,2271,0,0,0,2,4,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +88742,47391,Male,Loyal Customer,36,Business travel,Business,3922,1,1,3,1,5,5,1,4,4,4,4,4,4,4,0,0.0,satisfied +88743,114363,Female,Loyal Customer,42,Business travel,Business,3332,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +88744,10515,Female,Loyal Customer,47,Business travel,Business,201,1,1,1,1,2,5,5,4,4,4,5,5,4,5,18,29.0,satisfied +88745,50728,Female,Loyal Customer,8,Personal Travel,Eco,109,3,3,0,2,3,0,4,3,4,1,2,2,1,3,0,0.0,neutral or dissatisfied +88746,28913,Female,Loyal Customer,68,Business travel,Business,3849,1,4,3,4,5,4,4,1,1,1,1,2,1,3,2,0.0,neutral or dissatisfied +88747,67888,Female,Loyal Customer,69,Personal Travel,Eco,1235,4,3,5,1,5,1,2,4,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +88748,2453,Male,Loyal Customer,56,Personal Travel,Business,674,1,5,1,5,5,5,5,3,3,1,3,5,3,5,0,0.0,neutral or dissatisfied +88749,33141,Female,Loyal Customer,52,Personal Travel,Eco,102,2,3,2,4,1,4,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +88750,37838,Female,Loyal Customer,51,Business travel,Business,3333,4,4,4,4,5,5,3,4,4,4,4,2,4,1,37,24.0,satisfied +88751,82201,Female,Loyal Customer,41,Business travel,Business,2541,3,3,3,3,3,5,5,5,5,5,5,3,5,4,0,26.0,satisfied +88752,18322,Female,Loyal Customer,49,Personal Travel,Eco,705,2,5,2,3,2,5,5,1,1,2,5,5,1,4,0,0.0,neutral or dissatisfied +88753,124066,Female,Loyal Customer,30,Personal Travel,Eco,2153,2,4,2,1,2,2,2,4,5,4,5,2,4,2,400,412.0,neutral or dissatisfied +88754,39326,Female,Loyal Customer,43,Business travel,Eco Plus,67,4,4,4,4,1,2,5,4,4,4,4,4,4,2,1,3.0,satisfied +88755,59133,Female,Loyal Customer,26,Personal Travel,Eco,1846,4,4,4,1,4,4,4,4,5,4,3,4,4,4,16,0.0,neutral or dissatisfied +88756,41328,Male,Loyal Customer,42,Business travel,Business,689,2,2,2,2,5,2,3,2,2,2,2,1,2,2,1,0.0,neutral or dissatisfied +88757,57732,Male,disloyal Customer,66,Business travel,Eco,1287,3,3,3,3,2,3,2,2,1,5,4,1,4,2,107,94.0,neutral or dissatisfied +88758,1861,Male,disloyal Customer,22,Business travel,Business,931,5,0,5,4,4,5,4,4,3,2,4,4,5,4,0,0.0,satisfied +88759,20519,Female,Loyal Customer,42,Business travel,Business,633,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +88760,27239,Male,Loyal Customer,41,Personal Travel,Eco,1024,2,4,2,3,3,2,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +88761,127074,Female,disloyal Customer,36,Business travel,Eco,304,3,4,3,3,5,3,5,5,4,3,3,1,3,5,1,10.0,neutral or dissatisfied +88762,122156,Female,Loyal Customer,55,Business travel,Business,2266,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,10.0,satisfied +88763,50416,Male,Loyal Customer,39,Business travel,Business,262,2,2,2,2,4,5,2,4,4,4,4,2,4,3,0,0.0,satisfied +88764,35094,Male,Loyal Customer,47,Business travel,Business,1041,3,5,5,5,4,3,3,3,3,3,3,2,3,4,0,17.0,neutral or dissatisfied +88765,86511,Female,Loyal Customer,41,Personal Travel,Eco,853,3,4,3,4,5,3,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +88766,50136,Female,disloyal Customer,40,Business travel,Business,109,3,3,3,4,1,3,1,1,4,5,4,4,4,1,46,49.0,neutral or dissatisfied +88767,121153,Female,Loyal Customer,66,Business travel,Eco,2370,3,1,1,1,3,3,3,1,2,2,4,3,2,3,133,100.0,neutral or dissatisfied +88768,30720,Female,Loyal Customer,55,Personal Travel,Eco,1123,1,4,1,5,5,5,5,4,4,1,4,5,4,3,6,5.0,neutral or dissatisfied +88769,2087,Female,Loyal Customer,11,Personal Travel,Eco,785,3,5,3,1,4,3,4,4,3,3,4,5,5,4,0,5.0,neutral or dissatisfied +88770,88190,Male,Loyal Customer,33,Business travel,Business,594,3,3,3,3,4,3,4,4,5,5,5,4,4,4,0,0.0,satisfied +88771,95956,Female,Loyal Customer,35,Personal Travel,Business,795,3,5,3,4,5,5,5,2,2,3,2,4,2,4,32,18.0,neutral or dissatisfied +88772,49783,Male,Loyal Customer,39,Business travel,Business,3300,5,5,5,5,5,2,5,4,4,5,3,5,4,4,0,0.0,satisfied +88773,57591,Female,Loyal Customer,28,Personal Travel,Eco,1597,4,5,4,3,4,4,2,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +88774,30068,Male,Loyal Customer,69,Personal Travel,Eco,261,4,2,4,2,3,4,3,3,4,4,3,4,2,3,0,0.0,satisfied +88775,18536,Female,Loyal Customer,53,Business travel,Business,305,4,4,4,4,4,3,1,4,4,4,4,4,4,3,0,0.0,satisfied +88776,55444,Female,Loyal Customer,37,Personal Travel,Eco,2521,3,4,3,2,3,5,5,4,4,3,5,5,3,5,7,37.0,neutral or dissatisfied +88777,45950,Male,Loyal Customer,37,Personal Travel,Eco,563,2,3,2,3,2,3,4,3,1,2,3,4,1,4,63,133.0,neutral or dissatisfied +88778,123285,Female,Loyal Customer,70,Personal Travel,Eco,507,3,5,3,3,5,5,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +88779,86203,Female,Loyal Customer,62,Business travel,Business,1835,1,1,1,1,3,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +88780,128431,Female,disloyal Customer,23,Business travel,Business,370,4,4,4,5,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +88781,37850,Female,Loyal Customer,33,Business travel,Business,937,1,1,1,1,2,5,3,4,4,4,4,4,4,5,26,5.0,satisfied +88782,129581,Male,Loyal Customer,52,Business travel,Business,3949,0,1,1,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +88783,70821,Female,Loyal Customer,45,Personal Travel,Eco,624,2,4,2,3,3,4,5,3,3,2,3,5,3,5,0,6.0,neutral or dissatisfied +88784,113928,Male,Loyal Customer,66,Business travel,Business,1728,5,5,5,5,3,5,5,4,4,4,4,4,4,5,8,0.0,satisfied +88785,113504,Male,Loyal Customer,40,Business travel,Business,226,1,2,2,2,3,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +88786,31463,Male,Loyal Customer,25,Business travel,Business,2097,3,3,3,3,4,4,4,4,3,1,1,4,4,4,8,6.0,satisfied +88787,39836,Male,Loyal Customer,69,Business travel,Eco,272,3,5,2,2,3,3,3,3,3,1,5,1,2,3,0,2.0,satisfied +88788,74088,Female,disloyal Customer,22,Business travel,Eco,769,4,4,4,2,1,4,1,1,3,4,5,3,4,1,0,0.0,satisfied +88789,59609,Male,Loyal Customer,37,Business travel,Eco,854,3,2,2,2,3,3,3,3,4,3,3,3,2,3,0,15.0,neutral or dissatisfied +88790,106432,Male,Loyal Customer,39,Business travel,Business,643,3,3,3,3,4,4,5,4,4,4,4,5,4,4,16,10.0,satisfied +88791,79643,Male,disloyal Customer,30,Business travel,Eco,762,2,2,2,1,4,2,4,4,4,4,1,1,4,4,18,3.0,neutral or dissatisfied +88792,48871,Male,Loyal Customer,61,Business travel,Eco,109,2,5,5,5,2,2,2,2,3,1,5,1,2,2,42,31.0,satisfied +88793,4346,Male,Loyal Customer,38,Business travel,Business,3475,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +88794,115880,Male,Loyal Customer,68,Business travel,Business,2146,1,4,4,4,1,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +88795,62182,Female,Loyal Customer,56,Business travel,Business,2565,4,4,4,4,2,5,4,4,4,4,4,5,4,4,4,0.0,satisfied +88796,17157,Female,Loyal Customer,52,Personal Travel,Business,643,2,5,2,2,3,5,5,5,5,2,4,4,5,3,10,0.0,neutral or dissatisfied +88797,106391,Male,disloyal Customer,34,Business travel,Eco,488,3,3,3,3,3,3,3,3,1,1,3,1,3,3,17,6.0,neutral or dissatisfied +88798,122644,Female,disloyal Customer,34,Business travel,Business,361,2,2,2,3,5,2,2,5,5,5,4,4,5,5,7,5.0,neutral or dissatisfied +88799,50561,Female,Loyal Customer,52,Personal Travel,Eco,156,1,5,0,3,3,4,4,5,5,0,3,4,5,3,0,0.0,neutral or dissatisfied +88800,24956,Female,Loyal Customer,47,Personal Travel,Eco Plus,1747,4,2,4,4,1,4,3,5,5,4,2,1,5,2,10,0.0,satisfied +88801,116133,Male,Loyal Customer,28,Personal Travel,Eco,362,1,4,1,3,2,1,2,2,3,2,5,3,5,2,24,16.0,neutral or dissatisfied +88802,110203,Female,Loyal Customer,39,Business travel,Business,1756,3,3,3,3,2,4,5,5,5,5,5,3,5,3,7,0.0,satisfied +88803,97497,Male,Loyal Customer,67,Personal Travel,Eco,670,2,5,2,2,3,2,3,3,3,5,4,5,5,3,48,38.0,neutral or dissatisfied +88804,2624,Female,Loyal Customer,48,Business travel,Business,2451,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,1.0,satisfied +88805,44679,Male,Loyal Customer,63,Business travel,Eco,268,1,4,2,4,1,1,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +88806,100281,Female,Loyal Customer,27,Business travel,Business,1079,2,3,3,3,2,2,2,2,1,1,4,2,3,2,12,0.0,neutral or dissatisfied +88807,98020,Male,Loyal Customer,43,Business travel,Business,2405,4,4,5,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +88808,115098,Male,Loyal Customer,39,Business travel,Business,447,5,5,5,5,3,4,4,4,4,4,4,5,4,5,72,69.0,satisfied +88809,61324,Female,Loyal Customer,11,Personal Travel,Eco Plus,967,2,4,2,3,4,2,4,4,5,5,4,3,4,4,38,38.0,neutral or dissatisfied +88810,29352,Male,Loyal Customer,14,Personal Travel,Eco Plus,2588,2,5,1,3,1,1,1,1,2,3,4,2,5,1,0,0.0,neutral or dissatisfied +88811,71077,Female,Loyal Customer,31,Personal Travel,Eco,802,3,5,3,2,1,3,1,1,3,2,3,2,5,1,9,0.0,neutral or dissatisfied +88812,59120,Male,Loyal Customer,14,Personal Travel,Eco,1846,4,4,4,4,2,4,2,2,1,3,2,1,3,2,2,0.0,neutral or dissatisfied +88813,44999,Female,Loyal Customer,60,Business travel,Eco,118,4,5,5,5,1,4,4,4,4,4,4,4,4,3,0,10.0,neutral or dissatisfied +88814,99922,Male,Loyal Customer,20,Business travel,Business,764,4,4,4,4,2,2,2,2,4,2,4,5,4,2,7,18.0,satisfied +88815,9554,Female,Loyal Customer,42,Business travel,Business,2686,4,3,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +88816,11658,Male,Loyal Customer,50,Personal Travel,Eco,925,1,3,0,4,3,0,5,3,3,2,4,5,5,3,27,17.0,neutral or dissatisfied +88817,57053,Female,Loyal Customer,54,Personal Travel,Eco,2133,2,3,2,4,1,5,5,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +88818,100228,Male,Loyal Customer,43,Business travel,Business,1052,4,4,4,4,3,5,4,5,5,5,5,5,5,5,30,28.0,satisfied +88819,35139,Female,Loyal Customer,55,Business travel,Eco,1010,5,1,1,1,4,3,2,5,5,5,5,3,5,4,5,5.0,satisfied +88820,48002,Male,Loyal Customer,27,Business travel,Eco Plus,834,1,4,4,4,1,1,1,1,3,1,4,1,3,1,0,23.0,neutral or dissatisfied +88821,54149,Male,Loyal Customer,60,Business travel,Eco,1372,5,5,5,5,5,5,5,5,2,5,5,1,1,5,0,0.0,satisfied +88822,122861,Male,Loyal Customer,52,Business travel,Eco,226,3,2,2,2,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +88823,126878,Male,Loyal Customer,22,Personal Travel,Eco,2125,1,3,1,4,4,1,1,4,3,5,3,2,3,4,0,0.0,neutral or dissatisfied +88824,52890,Female,Loyal Customer,61,Personal Travel,Eco,836,4,5,4,5,4,5,4,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +88825,744,Female,Loyal Customer,43,Business travel,Business,312,1,1,1,1,3,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +88826,94791,Male,Loyal Customer,59,Business travel,Eco,528,3,3,3,3,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +88827,77781,Male,Loyal Customer,10,Personal Travel,Eco,696,1,4,1,3,5,1,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +88828,54137,Female,Loyal Customer,51,Business travel,Business,1504,4,4,4,4,5,2,5,3,3,3,3,2,3,2,4,0.0,satisfied +88829,125169,Male,Loyal Customer,36,Business travel,Eco,689,3,4,4,4,3,3,3,4,3,4,3,3,2,3,152,164.0,neutral or dissatisfied +88830,80202,Female,Loyal Customer,18,Personal Travel,Eco,2475,1,5,2,4,2,1,1,3,1,4,3,1,5,1,0,20.0,neutral or dissatisfied +88831,118782,Male,Loyal Customer,66,Personal Travel,Eco,647,3,5,3,2,5,3,5,5,3,1,1,2,2,5,0,0.0,neutral or dissatisfied +88832,11110,Male,Loyal Customer,29,Personal Travel,Eco,517,1,4,1,5,1,2,2,1,1,1,3,2,1,2,165,156.0,neutral or dissatisfied +88833,88584,Female,Loyal Customer,30,Personal Travel,Eco,404,2,2,2,3,4,2,4,4,1,5,3,3,3,4,0,11.0,neutral or dissatisfied +88834,103836,Male,Loyal Customer,45,Business travel,Eco,1048,3,4,4,4,3,3,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +88835,30463,Male,Loyal Customer,48,Business travel,Business,495,3,3,3,3,2,1,2,5,5,5,5,2,5,4,21,21.0,satisfied +88836,13480,Male,Loyal Customer,44,Business travel,Business,3353,4,4,4,4,2,4,5,4,4,4,4,5,4,5,13,12.0,satisfied +88837,34499,Female,disloyal Customer,28,Business travel,Eco,1428,1,2,2,1,3,1,3,3,4,1,2,2,1,3,9,14.0,neutral or dissatisfied +88838,58353,Male,disloyal Customer,28,Business travel,Business,599,4,4,4,4,2,4,2,2,3,5,5,5,5,2,53,54.0,satisfied +88839,93985,Male,Loyal Customer,31,Personal Travel,Eco,1315,0,4,0,2,5,4,5,5,4,5,4,4,5,5,0,0.0,satisfied +88840,68489,Male,Loyal Customer,60,Business travel,Eco,903,3,3,3,3,2,3,2,2,1,2,3,1,4,2,3,14.0,neutral or dissatisfied +88841,69386,Female,Loyal Customer,49,Business travel,Business,3065,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +88842,101981,Male,Loyal Customer,48,Personal Travel,Eco,628,5,4,5,2,3,5,3,3,5,5,4,4,5,3,16,0.0,satisfied +88843,79945,Female,disloyal Customer,9,Business travel,Eco,950,2,2,2,4,1,2,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +88844,107186,Female,disloyal Customer,55,Business travel,Eco,268,3,1,3,2,1,3,1,1,3,2,1,2,2,1,0,0.0,neutral or dissatisfied +88845,29704,Male,Loyal Customer,19,Personal Travel,Eco,1542,5,4,5,3,4,4,4,4,4,2,3,4,5,4,0,0.0,satisfied +88846,912,Female,Loyal Customer,47,Business travel,Business,2728,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +88847,14947,Male,Loyal Customer,30,Business travel,Business,3962,5,5,4,5,5,5,5,5,1,1,1,4,3,5,6,12.0,satisfied +88848,104995,Female,Loyal Customer,29,Personal Travel,Eco,314,4,4,4,1,3,4,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +88849,97621,Male,Loyal Customer,56,Business travel,Business,3314,3,3,3,3,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +88850,117999,Female,Loyal Customer,26,Personal Travel,Eco Plus,365,2,5,5,2,5,5,5,5,5,5,4,3,4,5,16,20.0,neutral or dissatisfied +88851,69215,Female,disloyal Customer,26,Business travel,Business,733,1,0,1,3,5,1,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +88852,63449,Female,Loyal Customer,65,Personal Travel,Eco,447,1,3,3,4,4,3,4,2,2,3,5,4,2,4,4,7.0,neutral or dissatisfied +88853,53452,Female,Loyal Customer,26,Business travel,Eco,2253,4,2,2,2,4,4,4,4,3,2,4,3,2,4,0,,satisfied +88854,63227,Female,Loyal Customer,40,Business travel,Business,372,5,5,5,5,4,5,4,5,5,5,5,4,5,4,20,10.0,satisfied +88855,54681,Female,Loyal Customer,69,Business travel,Business,964,1,2,4,2,4,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +88856,61356,Male,Loyal Customer,44,Personal Travel,Eco,602,1,3,1,3,5,1,5,5,1,1,4,2,3,5,2,0.0,neutral or dissatisfied +88857,32606,Female,Loyal Customer,24,Business travel,Business,1700,2,3,3,3,3,3,2,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +88858,45760,Female,Loyal Customer,38,Business travel,Business,216,5,5,5,5,4,4,4,5,5,5,3,2,5,3,0,0.0,satisfied +88859,81573,Male,Loyal Customer,69,Personal Travel,Eco,936,4,5,4,1,5,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +88860,1941,Male,Loyal Customer,51,Business travel,Business,1839,4,4,5,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +88861,34320,Male,disloyal Customer,23,Business travel,Eco,1472,5,5,5,5,5,5,5,5,3,3,5,1,5,5,1,0.0,satisfied +88862,4217,Male,Loyal Customer,40,Personal Travel,Eco,888,3,5,3,5,2,3,2,2,4,3,5,4,5,2,0,17.0,neutral or dissatisfied +88863,1411,Male,Loyal Customer,57,Personal Travel,Eco Plus,396,4,4,4,2,4,4,2,4,3,2,4,4,4,4,0,0.0,satisfied +88864,113559,Female,disloyal Customer,24,Business travel,Eco,197,3,4,3,1,5,3,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +88865,87256,Male,Loyal Customer,52,Business travel,Business,1843,3,3,3,3,4,4,4,5,5,5,5,5,5,3,36,19.0,satisfied +88866,57942,Female,Loyal Customer,37,Personal Travel,Eco,837,2,2,2,4,2,2,2,2,4,2,3,1,3,2,16,10.0,neutral or dissatisfied +88867,69970,Female,Loyal Customer,31,Business travel,Business,3547,2,3,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +88868,10378,Female,Loyal Customer,50,Business travel,Business,3777,5,1,5,5,5,4,4,4,4,5,5,4,4,4,47,34.0,satisfied +88869,54584,Female,Loyal Customer,19,Personal Travel,Eco,3904,3,5,2,4,2,5,5,3,3,4,4,5,5,5,14,23.0,neutral or dissatisfied +88870,27823,Male,disloyal Customer,50,Business travel,Eco,1048,3,3,3,3,1,3,1,1,4,4,3,3,3,1,0,8.0,neutral or dissatisfied +88871,114559,Male,Loyal Customer,38,Personal Travel,Business,337,4,3,4,2,2,3,2,5,5,4,4,3,5,3,4,0.0,neutral or dissatisfied +88872,72392,Female,Loyal Customer,58,Business travel,Business,1599,1,1,1,1,4,5,5,4,4,4,4,4,4,3,0,5.0,satisfied +88873,10899,Female,Loyal Customer,26,Business travel,Business,1977,3,3,3,3,3,3,3,3,4,5,4,5,4,3,37,33.0,satisfied +88874,126296,Male,Loyal Customer,58,Personal Travel,Eco,328,2,5,2,3,2,2,2,2,4,3,4,3,5,2,6,4.0,neutral or dissatisfied +88875,25690,Female,Loyal Customer,61,Business travel,Business,3130,5,5,4,5,5,4,3,3,3,4,3,2,3,4,0,4.0,satisfied +88876,31869,Male,Loyal Customer,23,Business travel,Business,2603,5,5,5,5,4,4,4,4,2,5,1,2,5,4,0,0.0,satisfied +88877,9677,Female,Loyal Customer,36,Business travel,Eco,284,1,1,1,1,1,1,1,1,3,1,3,2,2,1,0,1.0,neutral or dissatisfied +88878,105019,Male,Loyal Customer,54,Business travel,Business,2463,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +88879,63006,Female,Loyal Customer,24,Business travel,Business,3510,3,1,1,1,3,3,3,3,1,4,3,3,3,3,36,31.0,neutral or dissatisfied +88880,12559,Female,Loyal Customer,31,Personal Travel,Eco,871,2,2,2,3,2,4,4,4,4,2,2,4,3,4,290,276.0,neutral or dissatisfied +88881,18876,Female,disloyal Customer,25,Business travel,Eco,503,1,2,1,4,2,1,4,2,4,4,3,4,4,2,2,0.0,neutral or dissatisfied +88882,111443,Male,Loyal Customer,30,Business travel,Business,2950,3,3,3,3,4,4,4,4,4,5,5,3,5,4,10,4.0,satisfied +88883,59389,Female,Loyal Customer,50,Personal Travel,Eco,2399,0,4,1,3,5,4,5,3,3,1,3,4,3,4,0,0.0,satisfied +88884,17578,Male,disloyal Customer,17,Business travel,Eco,1034,2,2,2,4,3,2,3,3,5,5,5,2,3,3,15,0.0,neutral or dissatisfied +88885,56755,Male,Loyal Customer,50,Business travel,Business,3238,2,2,2,2,4,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +88886,61244,Male,disloyal Customer,43,Business travel,Eco,567,1,0,1,4,5,1,5,5,4,2,2,3,5,5,0,1.0,neutral or dissatisfied +88887,79768,Female,Loyal Customer,31,Business travel,Business,1076,2,5,2,2,5,5,5,5,3,3,4,4,4,5,0,13.0,satisfied +88888,99457,Female,disloyal Customer,45,Business travel,Business,307,3,3,3,2,3,3,3,3,4,4,4,3,5,3,0,8.0,neutral or dissatisfied +88889,73573,Male,Loyal Customer,52,Business travel,Business,3377,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +88890,85200,Male,Loyal Customer,47,Business travel,Eco,689,1,1,1,1,1,1,1,1,1,1,4,3,4,1,0,7.0,neutral or dissatisfied +88891,31430,Male,Loyal Customer,24,Personal Travel,Eco,1703,2,4,2,2,4,2,4,4,3,1,5,5,2,4,35,36.0,neutral or dissatisfied +88892,93489,Male,Loyal Customer,31,Business travel,Business,1753,1,1,1,1,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +88893,98490,Female,Loyal Customer,42,Business travel,Business,668,3,3,1,3,5,5,4,4,4,4,4,4,4,5,1,11.0,satisfied +88894,128459,Female,Loyal Customer,63,Personal Travel,Eco,370,4,4,4,3,3,4,3,4,4,4,2,3,4,3,9,8.0,neutral or dissatisfied +88895,129025,Male,Loyal Customer,29,Personal Travel,Eco,2611,3,2,3,4,3,3,3,1,3,3,3,3,2,3,0,0.0,neutral or dissatisfied +88896,70015,Male,Loyal Customer,49,Business travel,Business,583,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +88897,14804,Male,Loyal Customer,42,Business travel,Business,1784,5,5,5,5,3,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +88898,120035,Female,disloyal Customer,36,Business travel,Business,328,3,3,3,1,1,3,1,1,5,2,5,3,5,1,0,9.0,neutral or dissatisfied +88899,93821,Male,Loyal Customer,69,Business travel,Business,391,4,4,4,4,1,4,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +88900,56163,Female,Loyal Customer,39,Business travel,Business,1504,1,1,3,1,2,5,5,4,4,4,4,3,4,4,8,0.0,satisfied +88901,83707,Female,Loyal Customer,63,Personal Travel,Eco,577,4,5,4,1,5,4,5,5,5,4,5,5,5,4,21,19.0,neutral or dissatisfied +88902,127080,Female,Loyal Customer,42,Business travel,Eco,370,4,1,1,1,1,2,1,4,4,4,4,3,4,3,0,0.0,satisfied +88903,56318,Female,Loyal Customer,49,Business travel,Business,2174,0,5,0,2,3,4,4,5,5,5,5,4,5,4,11,0.0,satisfied +88904,26056,Male,Loyal Customer,45,Personal Travel,Eco,432,2,4,2,3,1,2,1,1,5,2,4,4,3,1,0,0.0,neutral or dissatisfied +88905,32937,Female,Loyal Customer,23,Personal Travel,Eco,101,1,5,1,3,4,1,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +88906,86854,Male,Loyal Customer,63,Personal Travel,Eco,692,4,5,4,3,2,4,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +88907,47744,Female,Loyal Customer,53,Business travel,Business,1855,3,3,3,3,2,2,1,5,5,5,5,5,5,4,59,47.0,satisfied +88908,13202,Female,Loyal Customer,11,Personal Travel,Eco,542,2,4,2,3,4,2,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +88909,90592,Female,Loyal Customer,31,Business travel,Business,2353,2,2,2,2,2,2,2,2,5,3,4,2,2,2,145,186.0,neutral or dissatisfied +88910,121218,Male,Loyal Customer,41,Business travel,Business,2075,4,4,4,4,4,3,4,4,4,4,4,3,4,3,0,14.0,satisfied +88911,25057,Male,disloyal Customer,23,Business travel,Eco,594,3,3,3,3,5,3,5,5,1,2,4,4,3,5,0,0.0,neutral or dissatisfied +88912,106603,Female,disloyal Customer,17,Business travel,Business,589,4,0,4,1,2,4,2,2,4,4,5,5,5,2,4,0.0,satisfied +88913,60935,Male,disloyal Customer,25,Business travel,Business,888,3,5,3,2,3,3,3,3,3,3,4,4,5,3,28,27.0,neutral or dissatisfied +88914,102825,Male,Loyal Customer,45,Business travel,Business,342,5,5,5,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +88915,58040,Female,Loyal Customer,30,Business travel,Business,589,5,5,5,5,2,2,2,2,5,4,4,4,4,2,0,0.0,satisfied +88916,128332,Male,Loyal Customer,34,Business travel,Business,1696,1,1,1,1,4,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +88917,63328,Male,Loyal Customer,44,Business travel,Business,2590,2,2,2,2,1,2,2,2,2,2,2,4,2,1,36,37.0,neutral or dissatisfied +88918,81013,Female,disloyal Customer,20,Business travel,Eco,1399,5,5,5,5,1,5,1,1,4,4,5,5,5,1,0,2.0,satisfied +88919,99258,Male,Loyal Customer,20,Personal Travel,Business,833,3,4,3,4,5,3,5,5,3,4,4,4,4,5,17,2.0,neutral or dissatisfied +88920,103892,Female,disloyal Customer,23,Business travel,Eco,1242,3,3,3,3,1,3,1,1,4,4,5,3,4,1,25,17.0,satisfied +88921,126334,Male,Loyal Customer,29,Personal Travel,Eco,468,3,4,4,3,3,4,2,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +88922,68816,Male,Loyal Customer,19,Business travel,Eco Plus,1021,2,1,2,1,2,1,2,2,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +88923,87685,Male,Loyal Customer,8,Personal Travel,Eco,606,5,5,5,1,2,5,2,2,4,5,4,5,5,2,102,97.0,satisfied +88924,22605,Male,Loyal Customer,31,Business travel,Eco,300,3,1,1,1,3,3,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +88925,89733,Male,Loyal Customer,64,Personal Travel,Eco,1076,3,4,3,4,2,3,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +88926,26938,Male,Loyal Customer,31,Business travel,Business,2378,4,4,4,4,4,4,4,4,2,5,5,5,1,4,5,0.0,satisfied +88927,114454,Female,Loyal Customer,35,Business travel,Business,390,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +88928,69469,Male,Loyal Customer,64,Personal Travel,Eco,944,2,1,2,3,1,2,1,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +88929,44624,Male,Loyal Customer,51,Business travel,Business,67,1,1,1,1,2,4,5,4,4,4,4,3,4,5,116,107.0,satisfied +88930,121594,Female,Loyal Customer,8,Personal Travel,Eco,936,3,5,3,3,1,3,5,1,5,4,4,4,4,1,0,24.0,neutral or dissatisfied +88931,2219,Female,disloyal Customer,41,Business travel,Business,642,3,3,3,2,3,3,3,3,5,2,4,4,5,3,53,53.0,neutral or dissatisfied +88932,116578,Female,Loyal Customer,46,Business travel,Business,2681,2,2,5,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +88933,27051,Female,Loyal Customer,64,Business travel,Eco,209,5,5,5,5,5,5,5,5,5,5,5,2,5,5,0,24.0,satisfied +88934,60288,Female,Loyal Customer,58,Business travel,Business,2047,3,3,2,3,4,5,5,5,5,5,5,5,5,4,5,0.0,satisfied +88935,76539,Male,disloyal Customer,39,Business travel,Business,534,2,2,2,5,5,2,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +88936,115829,Female,Loyal Customer,48,Business travel,Eco,373,3,4,4,4,1,3,2,3,3,3,3,4,3,5,0,0.0,satisfied +88937,36862,Male,Loyal Customer,35,Business travel,Business,273,5,5,5,5,5,2,1,5,5,5,5,4,5,1,8,0.0,satisfied +88938,114846,Female,Loyal Customer,51,Business travel,Business,2252,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +88939,123983,Female,Loyal Customer,36,Business travel,Business,3943,5,5,5,5,3,5,5,5,5,5,4,3,5,3,18,17.0,satisfied +88940,108170,Male,Loyal Customer,22,Personal Travel,Eco,990,3,4,3,4,4,3,4,4,3,2,4,3,4,4,19,16.0,neutral or dissatisfied +88941,60398,Male,Loyal Customer,10,Personal Travel,Eco,1452,5,3,5,3,5,5,5,5,4,1,4,3,4,5,1,0.0,satisfied +88942,110947,Female,Loyal Customer,55,Business travel,Business,404,1,1,1,1,5,5,4,4,4,5,4,5,4,4,23,21.0,satisfied +88943,100716,Male,disloyal Customer,42,Business travel,Eco,328,1,2,1,3,4,1,1,4,2,4,4,2,4,4,0,4.0,neutral or dissatisfied +88944,4547,Male,Loyal Customer,52,Personal Travel,Eco,719,3,1,3,2,2,3,2,2,4,2,2,3,3,2,0,7.0,neutral or dissatisfied +88945,46946,Female,Loyal Customer,8,Personal Travel,Eco,948,1,3,1,2,5,1,2,5,5,5,3,2,1,5,0,0.0,neutral or dissatisfied +88946,105570,Male,Loyal Customer,43,Business travel,Business,2120,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,12.0,satisfied +88947,42884,Female,Loyal Customer,48,Business travel,Business,3565,4,1,4,4,4,4,5,4,4,4,4,4,4,4,15,31.0,satisfied +88948,86216,Female,Loyal Customer,72,Business travel,Eco,356,2,3,3,3,1,4,4,3,3,2,3,2,3,4,1,4.0,neutral or dissatisfied +88949,52611,Female,Loyal Customer,49,Business travel,Eco,160,3,4,4,4,3,4,3,4,4,3,4,1,4,2,0,3.0,neutral or dissatisfied +88950,65130,Female,Loyal Customer,53,Personal Travel,Eco,469,2,4,2,4,5,5,5,3,3,2,3,5,3,3,2,9.0,neutral or dissatisfied +88951,128361,Female,Loyal Customer,26,Business travel,Business,1835,5,5,5,5,4,4,4,4,5,4,5,4,4,4,1,8.0,satisfied +88952,23883,Female,Loyal Customer,14,Business travel,Business,579,4,4,1,4,5,4,5,5,3,5,5,4,5,5,0,0.0,satisfied +88953,2768,Male,Loyal Customer,34,Business travel,Business,1587,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +88954,28517,Male,Loyal Customer,38,Business travel,Business,2640,5,5,3,5,1,5,4,5,5,5,5,1,5,5,5,0.0,satisfied +88955,26972,Male,Loyal Customer,29,Business travel,Business,954,4,4,4,4,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +88956,71509,Male,Loyal Customer,52,Business travel,Business,1197,4,4,4,4,5,4,4,5,5,4,5,5,5,3,0,9.0,satisfied +88957,37597,Male,Loyal Customer,33,Business travel,Business,2055,4,4,5,4,4,4,4,4,5,2,5,5,1,4,0,0.0,satisfied +88958,19821,Male,disloyal Customer,11,Business travel,Eco,528,1,2,1,4,3,1,3,3,4,5,4,1,3,3,123,113.0,neutral or dissatisfied +88959,105071,Female,Loyal Customer,19,Personal Travel,Business,289,5,5,5,4,1,5,4,1,4,4,4,3,5,1,0,0.0,satisfied +88960,28638,Female,Loyal Customer,44,Business travel,Eco,2404,2,1,1,1,2,2,2,4,4,1,2,2,1,2,160,149.0,neutral or dissatisfied +88961,27235,Female,Loyal Customer,45,Business travel,Business,2183,3,3,3,3,2,2,4,2,2,2,2,1,2,1,120,110.0,satisfied +88962,58726,Male,Loyal Customer,38,Business travel,Business,1182,2,2,2,2,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +88963,52910,Male,disloyal Customer,43,Business travel,Eco,679,4,4,4,1,2,4,4,2,2,2,5,1,5,2,1,9.0,neutral or dissatisfied +88964,72724,Male,Loyal Customer,24,Business travel,Eco Plus,929,2,1,1,1,2,2,2,2,1,2,2,1,2,2,1,11.0,neutral or dissatisfied +88965,123170,Male,disloyal Customer,17,Business travel,Eco,631,3,3,3,3,4,3,4,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +88966,125851,Male,Loyal Customer,60,Business travel,Business,3216,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +88967,26828,Female,disloyal Customer,49,Business travel,Eco,224,3,0,3,1,3,3,3,3,1,1,3,3,4,3,0,0.0,neutral or dissatisfied +88968,127124,Male,Loyal Customer,62,Personal Travel,Eco,338,1,1,1,3,4,1,4,4,4,4,3,4,3,4,20,0.0,neutral or dissatisfied +88969,73741,Male,Loyal Customer,31,Personal Travel,Eco,204,3,5,3,1,2,3,2,2,5,2,1,3,2,2,0,0.0,neutral or dissatisfied +88970,67156,Male,Loyal Customer,72,Business travel,Business,1764,1,2,2,2,4,3,3,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +88971,77892,Male,Loyal Customer,22,Business travel,Business,2629,5,5,2,5,1,2,1,1,4,2,5,4,5,1,0,15.0,satisfied +88972,105032,Female,disloyal Customer,25,Business travel,Eco,361,2,3,2,2,1,2,1,1,4,4,2,2,3,1,46,58.0,neutral or dissatisfied +88973,121945,Male,Loyal Customer,38,Business travel,Business,1888,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +88974,27970,Female,disloyal Customer,24,Business travel,Eco,1448,3,3,3,4,3,3,3,3,4,5,2,1,3,3,0,0.0,neutral or dissatisfied +88975,21959,Male,disloyal Customer,30,Business travel,Eco,448,2,2,2,4,3,2,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +88976,114762,Male,Loyal Customer,29,Business travel,Business,1688,4,4,4,4,5,5,5,5,4,4,4,5,5,5,19,24.0,satisfied +88977,87424,Male,Loyal Customer,43,Business travel,Business,1700,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +88978,76524,Female,Loyal Customer,27,Business travel,Business,2800,4,4,4,4,2,2,2,2,3,3,5,4,5,2,52,47.0,satisfied +88979,16795,Male,Loyal Customer,30,Business travel,Business,1017,5,5,2,5,5,5,5,5,2,1,3,5,5,5,0,0.0,satisfied +88980,113067,Male,Loyal Customer,46,Business travel,Business,3299,5,5,5,5,4,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +88981,31637,Female,Loyal Customer,36,Business travel,Business,2920,1,1,1,1,5,3,1,5,5,5,5,3,5,4,0,18.0,satisfied +88982,21700,Female,Loyal Customer,15,Personal Travel,Eco,708,1,4,1,3,5,1,5,5,5,4,5,5,4,5,85,112.0,neutral or dissatisfied +88983,38499,Female,disloyal Customer,21,Business travel,Business,1322,4,0,4,1,2,4,2,2,1,2,4,4,2,2,0,16.0,satisfied +88984,35333,Female,Loyal Customer,52,Business travel,Business,2363,3,4,4,4,1,3,3,3,3,4,3,4,3,1,2,0.0,neutral or dissatisfied +88985,50689,Female,Loyal Customer,21,Personal Travel,Eco,421,2,2,2,3,1,2,1,1,2,1,2,2,2,1,3,19.0,neutral or dissatisfied +88986,56673,Male,Loyal Customer,42,Personal Travel,Eco,1085,3,4,3,3,4,3,4,4,3,5,5,4,4,4,3,0.0,neutral or dissatisfied +88987,108074,Male,Loyal Customer,48,Business travel,Business,997,5,5,5,5,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +88988,8531,Female,Loyal Customer,52,Business travel,Business,862,1,1,3,1,3,4,4,5,5,5,5,3,5,5,34,30.0,satisfied +88989,46863,Female,Loyal Customer,28,Business travel,Business,3209,3,3,3,3,5,5,5,5,1,4,2,2,4,5,81,67.0,satisfied +88990,11497,Female,Loyal Customer,46,Personal Travel,Eco Plus,295,2,2,2,3,2,3,3,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +88991,87247,Female,Loyal Customer,26,Business travel,Business,3236,1,1,1,1,5,5,5,5,3,5,5,5,4,5,3,0.0,satisfied +88992,107813,Male,disloyal Customer,19,Business travel,Business,349,1,2,1,3,4,1,2,4,4,2,4,4,4,4,28,19.0,neutral or dissatisfied +88993,96853,Male,Loyal Customer,36,Business travel,Business,2136,2,5,5,5,4,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +88994,96371,Female,disloyal Customer,36,Business travel,Business,1407,2,2,2,3,5,2,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +88995,30105,Male,Loyal Customer,67,Personal Travel,Eco,183,3,4,3,3,5,3,5,5,5,4,4,3,4,5,21,16.0,neutral or dissatisfied +88996,31888,Male,Loyal Customer,42,Business travel,Business,2762,5,5,5,5,4,4,3,5,5,5,5,1,5,3,0,0.0,satisfied +88997,89527,Male,Loyal Customer,45,Personal Travel,Business,950,2,0,2,3,4,3,3,2,2,2,2,5,2,1,0,0.0,neutral or dissatisfied +88998,54518,Female,Loyal Customer,17,Personal Travel,Eco,925,5,5,5,2,4,5,4,4,3,3,4,3,5,4,0,0.0,satisfied +88999,32471,Male,Loyal Customer,43,Business travel,Business,3329,1,2,2,2,4,3,3,3,3,3,1,4,3,1,0,0.0,neutral or dissatisfied +89000,72417,Male,Loyal Customer,29,Business travel,Business,3868,5,5,5,5,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +89001,60413,Female,Loyal Customer,29,Business travel,Business,1452,5,5,5,5,4,4,4,4,4,5,4,5,4,4,6,0.0,satisfied +89002,74670,Male,Loyal Customer,26,Personal Travel,Eco,1205,2,3,2,2,1,2,1,1,4,1,4,1,2,1,0,1.0,neutral or dissatisfied +89003,50150,Female,disloyal Customer,25,Business travel,Eco,109,2,2,2,3,3,2,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +89004,13869,Male,Loyal Customer,53,Business travel,Eco,667,5,5,5,5,5,5,5,5,1,4,4,3,2,5,7,0.0,satisfied +89005,14619,Male,Loyal Customer,70,Business travel,Business,2120,2,3,3,3,5,3,3,2,2,2,2,3,2,1,109,131.0,neutral or dissatisfied +89006,28647,Female,Loyal Customer,36,Personal Travel,Eco,2378,3,4,3,1,3,4,3,4,2,3,4,3,3,3,149,123.0,neutral or dissatisfied +89007,78862,Male,Loyal Customer,8,Personal Travel,Eco Plus,447,3,2,3,3,1,3,4,1,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +89008,22141,Male,Loyal Customer,44,Business travel,Eco Plus,350,5,5,5,5,5,5,5,5,4,4,2,1,4,5,37,33.0,satisfied +89009,22389,Female,disloyal Customer,36,Business travel,Eco,143,2,1,2,3,3,2,3,3,1,3,2,2,3,3,23,23.0,neutral or dissatisfied +89010,13264,Male,Loyal Customer,42,Personal Travel,Eco,657,5,1,5,3,2,1,2,2,3,3,3,3,4,2,0,0.0,satisfied +89011,101945,Male,Loyal Customer,43,Business travel,Business,1751,2,5,2,2,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +89012,14674,Male,Loyal Customer,58,Personal Travel,Eco,416,3,3,3,3,5,3,5,5,1,1,3,2,4,5,0,0.0,neutral or dissatisfied +89013,46658,Male,Loyal Customer,31,Business travel,Business,2699,4,1,1,1,1,1,4,1,2,4,4,4,3,1,0,8.0,neutral or dissatisfied +89014,41549,Female,Loyal Customer,36,Business travel,Business,1482,4,5,5,5,2,3,3,4,4,4,4,1,4,2,4,41.0,neutral or dissatisfied +89015,72041,Male,Loyal Customer,50,Business travel,Business,4243,3,4,4,4,3,3,3,2,4,2,2,3,2,3,0,5.0,neutral or dissatisfied +89016,16376,Female,Loyal Customer,17,Business travel,Eco,1215,4,3,3,3,4,4,3,4,2,4,4,1,3,4,0,0.0,satisfied +89017,53636,Female,Loyal Customer,13,Personal Travel,Eco,1874,3,1,3,2,1,3,1,1,4,2,2,2,3,1,7,0.0,neutral or dissatisfied +89018,92146,Female,Loyal Customer,57,Business travel,Business,1522,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +89019,98098,Female,Loyal Customer,54,Personal Travel,Eco,265,3,2,0,2,2,3,2,2,2,0,2,3,2,1,0,0.0,neutral or dissatisfied +89020,62608,Female,Loyal Customer,58,Personal Travel,Eco,1744,1,5,1,4,4,5,5,5,5,1,2,5,5,3,0,0.0,neutral or dissatisfied +89021,92068,Male,Loyal Customer,51,Business travel,Business,1535,1,2,2,2,5,4,4,1,1,1,1,4,1,4,3,0.0,neutral or dissatisfied +89022,128344,Female,Loyal Customer,42,Business travel,Business,3836,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +89023,126805,Female,Loyal Customer,56,Business travel,Business,2296,5,5,4,5,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +89024,89201,Female,Loyal Customer,21,Personal Travel,Eco,2139,1,5,1,2,5,1,1,5,5,5,4,3,4,5,37,55.0,neutral or dissatisfied +89025,53906,Male,Loyal Customer,15,Personal Travel,Eco,140,3,5,3,3,5,3,3,5,3,3,1,1,3,5,0,0.0,neutral or dissatisfied +89026,98870,Male,Loyal Customer,37,Business travel,Eco,991,2,4,2,4,2,2,2,2,2,5,4,2,3,2,0,0.0,neutral or dissatisfied +89027,17823,Male,disloyal Customer,20,Personal Travel,Eco,1075,3,5,3,3,1,3,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +89028,42389,Male,Loyal Customer,17,Personal Travel,Eco,838,3,4,3,3,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +89029,50040,Male,disloyal Customer,55,Business travel,Eco,86,2,3,2,4,1,2,1,1,4,2,4,3,3,1,0,1.0,neutral or dissatisfied +89030,90432,Female,Loyal Customer,57,Business travel,Business,406,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +89031,51844,Female,Loyal Customer,10,Personal Travel,Eco Plus,451,4,3,4,3,3,4,2,3,5,1,2,1,4,3,0,0.0,neutral or dissatisfied +89032,106540,Female,Loyal Customer,67,Personal Travel,Eco Plus,321,2,4,2,2,5,3,4,5,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +89033,122966,Male,Loyal Customer,60,Business travel,Business,2253,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +89034,116084,Male,Loyal Customer,32,Personal Travel,Eco,337,2,5,2,3,5,2,5,5,5,4,5,4,5,5,6,0.0,neutral or dissatisfied +89035,121007,Female,Loyal Customer,49,Personal Travel,Eco,920,3,4,2,4,3,5,4,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +89036,109424,Male,Loyal Customer,52,Business travel,Business,861,3,1,1,1,5,3,2,3,3,3,3,3,3,3,85,61.0,neutral or dissatisfied +89037,74202,Female,Loyal Customer,59,Business travel,Business,3984,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +89038,10714,Female,Loyal Customer,35,Business travel,Business,2969,2,3,3,3,4,3,2,2,2,2,2,3,2,2,0,1.0,neutral or dissatisfied +89039,96396,Female,Loyal Customer,27,Business travel,Business,3514,1,1,1,1,4,4,4,4,5,4,5,4,4,4,7,4.0,satisfied +89040,87097,Male,Loyal Customer,59,Business travel,Eco,594,2,1,1,1,2,2,2,2,1,5,3,1,2,2,11,0.0,neutral or dissatisfied +89041,60609,Male,Loyal Customer,56,Business travel,Eco,991,2,4,4,4,2,2,2,2,1,1,4,3,4,2,0,1.0,neutral or dissatisfied +89042,103031,Female,Loyal Customer,32,Business travel,Business,3846,5,5,5,5,5,5,5,5,4,3,4,4,4,5,4,0.0,satisfied +89043,119035,Male,disloyal Customer,49,Business travel,Business,2378,3,3,3,3,1,3,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +89044,76168,Female,Loyal Customer,70,Personal Travel,Eco,546,2,3,2,1,5,1,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +89045,46746,Female,Loyal Customer,16,Personal Travel,Eco,125,3,1,0,2,4,0,4,4,3,5,2,4,2,4,38,42.0,neutral or dissatisfied +89046,7529,Male,Loyal Customer,26,Business travel,Business,1788,5,5,5,5,3,3,3,3,3,5,4,5,4,3,0,0.0,satisfied +89047,41388,Male,Loyal Customer,38,Business travel,Business,2583,4,3,3,3,1,3,2,4,4,4,4,3,4,2,0,4.0,neutral or dissatisfied +89048,45576,Male,Loyal Customer,48,Business travel,Business,2056,3,3,3,3,5,4,5,4,4,4,4,5,4,3,76,85.0,satisfied +89049,8880,Male,Loyal Customer,64,Business travel,Business,2802,2,3,3,3,3,3,4,3,3,3,2,2,3,2,45,41.0,neutral or dissatisfied +89050,18067,Male,Loyal Customer,18,Personal Travel,Eco,488,2,0,2,3,1,2,1,1,4,3,4,4,5,1,2,0.0,neutral or dissatisfied +89051,67112,Female,Loyal Customer,44,Business travel,Business,1869,4,4,5,4,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +89052,26221,Female,Loyal Customer,70,Personal Travel,Eco,515,2,4,2,3,2,5,5,3,3,2,3,3,3,5,1,0.0,neutral or dissatisfied +89053,100165,Female,disloyal Customer,36,Business travel,Eco,325,3,4,3,3,1,3,4,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +89054,44678,Female,Loyal Customer,38,Business travel,Business,67,4,1,1,1,1,3,4,3,3,2,4,4,3,4,26,103.0,neutral or dissatisfied +89055,24550,Male,Loyal Customer,25,Business travel,Eco,874,5,2,2,2,5,5,5,5,4,1,4,1,3,5,19,7.0,satisfied +89056,126523,Male,Loyal Customer,44,Personal Travel,Eco,196,3,2,3,2,3,3,3,3,4,3,2,3,1,3,0,33.0,neutral or dissatisfied +89057,111072,Male,Loyal Customer,51,Personal Travel,Eco,319,2,2,2,4,5,2,5,5,4,2,4,2,3,5,0,0.0,neutral or dissatisfied +89058,43785,Female,Loyal Customer,54,Personal Travel,Eco,546,3,1,3,3,5,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +89059,23059,Female,disloyal Customer,22,Business travel,Eco,820,1,1,1,3,1,1,5,1,4,5,3,3,4,1,2,0.0,neutral or dissatisfied +89060,29237,Male,Loyal Customer,31,Business travel,Eco,550,4,5,4,4,4,4,4,4,1,5,2,5,1,4,0,3.0,satisfied +89061,105307,Female,Loyal Customer,30,Personal Travel,Eco,738,3,4,3,3,4,3,4,4,3,3,4,4,5,4,17,14.0,neutral or dissatisfied +89062,67984,Male,Loyal Customer,41,Business travel,Eco Plus,771,5,3,4,3,5,5,5,5,3,1,1,5,4,5,0,,satisfied +89063,35811,Female,Loyal Customer,40,Business travel,Eco,1065,4,5,1,5,4,4,4,4,1,1,2,5,2,4,24,22.0,satisfied +89064,47700,Female,Loyal Customer,8,Personal Travel,Eco,1334,2,5,2,2,5,2,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +89065,34661,Female,Loyal Customer,53,Business travel,Business,301,3,3,4,3,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +89066,84159,Male,Loyal Customer,54,Business travel,Business,503,4,4,4,4,5,4,4,3,3,3,3,4,3,3,0,3.0,satisfied +89067,59477,Male,Loyal Customer,46,Business travel,Business,811,5,5,5,5,4,4,5,5,5,5,5,5,5,4,16,0.0,satisfied +89068,65172,Female,Loyal Customer,20,Personal Travel,Eco,224,2,5,2,3,1,2,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +89069,82271,Male,disloyal Customer,28,Business travel,Business,1481,5,5,5,3,1,5,1,1,4,5,5,4,5,1,0,0.0,satisfied +89070,104927,Male,Loyal Customer,60,Personal Travel,Eco,210,4,2,4,3,3,4,3,3,1,5,3,2,2,3,0,0.0,neutral or dissatisfied +89071,124028,Male,Loyal Customer,23,Personal Travel,Eco,184,3,1,3,3,1,3,1,1,4,1,2,3,3,1,25,61.0,neutral or dissatisfied +89072,58927,Male,Loyal Customer,11,Personal Travel,Eco,888,3,4,3,4,3,3,3,3,5,4,4,4,4,3,17,11.0,neutral or dissatisfied +89073,78830,Male,Loyal Customer,60,Personal Travel,Eco,432,4,2,4,3,3,4,3,3,1,2,4,2,4,3,0,0.0,satisfied +89074,23853,Male,Loyal Customer,28,Business travel,Business,3557,3,3,3,3,4,4,4,1,2,2,2,4,1,4,225,219.0,satisfied +89075,38259,Female,Loyal Customer,32,Business travel,Eco,1133,4,2,2,2,4,3,4,4,4,4,3,1,4,4,39,26.0,neutral or dissatisfied +89076,81111,Male,Loyal Customer,62,Business travel,Eco,991,3,3,3,3,3,3,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +89077,123930,Male,Loyal Customer,10,Personal Travel,Eco,544,4,4,4,4,1,4,1,1,3,2,5,3,3,1,0,0.0,neutral or dissatisfied +89078,15397,Male,disloyal Customer,23,Business travel,Eco,433,4,4,4,1,4,4,4,4,2,1,5,4,3,4,0,0.0,satisfied +89079,18622,Male,Loyal Customer,37,Personal Travel,Eco,253,3,3,3,3,2,3,5,2,1,4,4,4,1,2,0,0.0,neutral or dissatisfied +89080,39982,Male,Loyal Customer,25,Personal Travel,Eco,1404,1,1,1,4,4,1,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +89081,61520,Male,Loyal Customer,18,Personal Travel,Eco,2253,4,5,4,1,4,4,4,4,4,4,5,4,5,4,0,0.0,neutral or dissatisfied +89082,123265,Male,Loyal Customer,24,Personal Travel,Eco,631,1,5,2,3,2,2,2,2,3,3,5,3,4,2,72,74.0,neutral or dissatisfied +89083,93748,Female,Loyal Customer,51,Business travel,Business,2907,4,4,4,4,4,5,5,5,5,5,5,4,5,5,19,12.0,satisfied +89084,117084,Male,Loyal Customer,57,Business travel,Business,304,2,4,4,4,3,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +89085,49794,Male,disloyal Customer,40,Business travel,Eco,190,2,1,2,3,5,2,5,5,3,5,3,2,2,5,0,0.0,neutral or dissatisfied +89086,96862,Male,Loyal Customer,62,Business travel,Eco,557,4,5,5,5,5,4,5,5,1,5,3,5,3,5,19,17.0,satisfied +89087,9331,Male,Loyal Customer,58,Business travel,Eco Plus,542,3,3,3,3,3,3,3,3,1,1,3,2,3,3,3,0.0,neutral or dissatisfied +89088,74494,Male,disloyal Customer,26,Business travel,Business,1205,3,3,3,4,2,3,1,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +89089,71842,Male,Loyal Customer,58,Business travel,Eco,1846,2,4,4,4,2,2,2,2,3,2,4,1,3,2,0,6.0,neutral or dissatisfied +89090,119545,Male,Loyal Customer,31,Personal Travel,Eco,759,3,1,3,2,4,3,5,4,4,2,3,3,3,4,0,30.0,neutral or dissatisfied +89091,127040,Female,Loyal Customer,60,Business travel,Business,338,2,5,5,5,1,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +89092,74690,Male,Loyal Customer,20,Personal Travel,Eco,1464,2,1,2,3,5,2,5,5,1,1,4,2,3,5,0,9.0,neutral or dissatisfied +89093,50420,Female,Loyal Customer,55,Business travel,Business,77,2,2,2,2,4,3,5,5,5,5,5,2,5,5,0,0.0,satisfied +89094,91914,Male,Loyal Customer,53,Business travel,Business,2475,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +89095,18044,Female,Loyal Customer,22,Business travel,Eco,605,5,3,3,3,5,5,5,5,4,2,3,3,4,5,83,84.0,satisfied +89096,63073,Female,Loyal Customer,69,Personal Travel,Eco,967,2,5,2,2,4,4,5,1,1,2,5,4,1,4,27,12.0,neutral or dissatisfied +89097,43084,Male,Loyal Customer,20,Personal Travel,Eco,192,2,1,2,3,2,2,2,2,1,2,4,3,4,2,39,75.0,neutral or dissatisfied +89098,81067,Female,Loyal Customer,30,Business travel,Business,931,2,4,3,4,2,2,2,2,2,5,3,2,3,2,0,0.0,neutral or dissatisfied +89099,76544,Female,disloyal Customer,33,Business travel,Business,357,4,4,4,3,3,4,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +89100,56227,Female,Loyal Customer,14,Personal Travel,Eco,1608,3,5,3,4,1,3,1,1,5,4,4,3,5,1,7,10.0,neutral or dissatisfied +89101,9120,Male,Loyal Customer,40,Personal Travel,Eco,707,3,5,3,1,3,3,3,3,5,2,5,4,5,3,4,11.0,neutral or dissatisfied +89102,123074,Female,disloyal Customer,20,Business travel,Business,650,5,0,5,4,1,5,1,1,4,4,5,4,4,1,63,116.0,satisfied +89103,98278,Male,Loyal Customer,59,Business travel,Eco,1072,2,1,1,1,1,2,1,1,3,3,4,3,4,1,11,14.0,neutral or dissatisfied +89104,3172,Male,Loyal Customer,52,Business travel,Business,585,1,1,1,1,4,4,4,4,4,4,4,3,4,5,0,3.0,satisfied +89105,31729,Male,Loyal Customer,68,Personal Travel,Eco,853,3,1,3,4,2,3,3,2,4,2,4,4,3,2,44,44.0,neutral or dissatisfied +89106,89794,Male,Loyal Customer,30,Personal Travel,Eco,1035,3,4,3,3,1,3,1,1,4,4,5,5,4,1,12,0.0,neutral or dissatisfied +89107,31356,Female,Loyal Customer,43,Business travel,Eco,692,4,4,4,4,5,3,3,4,4,4,4,4,4,1,0,0.0,satisfied +89108,53221,Female,Loyal Customer,43,Business travel,Business,2723,1,4,4,4,4,1,1,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +89109,63731,Female,Loyal Customer,59,Personal Travel,Eco,1660,2,5,2,1,2,5,4,3,3,2,3,5,3,5,9,0.0,neutral or dissatisfied +89110,121205,Female,Loyal Customer,49,Personal Travel,Eco Plus,2370,5,4,5,3,5,2,2,3,2,4,5,2,3,2,105,115.0,satisfied +89111,57252,Male,Loyal Customer,51,Business travel,Business,2113,3,3,3,3,5,4,4,4,4,4,4,3,4,5,0,1.0,satisfied +89112,73560,Female,Loyal Customer,58,Business travel,Business,3635,1,1,4,1,5,5,5,5,5,5,4,4,5,4,1,0.0,satisfied +89113,73831,Female,Loyal Customer,66,Personal Travel,Eco,1194,1,5,1,1,3,4,5,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +89114,114560,Male,Loyal Customer,68,Personal Travel,Business,337,1,4,3,3,4,3,3,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +89115,82225,Female,disloyal Customer,40,Business travel,Business,405,2,2,2,3,3,2,1,3,4,1,4,3,4,3,13,12.0,neutral or dissatisfied +89116,22740,Female,disloyal Customer,38,Business travel,Eco,147,2,0,1,4,2,1,2,2,5,2,2,2,2,2,0,3.0,neutral or dissatisfied +89117,57705,Female,Loyal Customer,55,Personal Travel,Eco,867,3,3,3,4,2,3,4,4,4,3,5,4,4,1,3,7.0,neutral or dissatisfied +89118,18507,Male,Loyal Customer,57,Business travel,Business,253,1,1,1,1,2,5,2,5,5,5,5,4,5,4,0,0.0,satisfied +89119,76629,Female,Loyal Customer,40,Business travel,Eco,134,1,3,3,3,1,1,1,1,1,1,3,1,4,1,7,1.0,neutral or dissatisfied +89120,81245,Female,disloyal Customer,47,Business travel,Eco,530,4,0,4,3,2,4,2,2,2,2,1,4,2,2,0,0.0,neutral or dissatisfied +89121,59336,Male,disloyal Customer,39,Business travel,Business,1150,4,3,3,4,3,3,4,3,5,2,4,5,4,3,0,0.0,satisfied +89122,113080,Male,Loyal Customer,49,Business travel,Business,543,2,5,5,5,5,3,4,2,2,2,2,2,2,3,61,56.0,neutral or dissatisfied +89123,69071,Female,Loyal Customer,55,Business travel,Business,1389,5,5,5,5,3,5,4,5,5,5,5,4,5,5,15,0.0,satisfied +89124,18003,Female,disloyal Customer,37,Business travel,Eco,332,2,3,2,4,5,2,2,5,2,2,4,3,3,5,55,58.0,neutral or dissatisfied +89125,91175,Female,Loyal Customer,24,Personal Travel,Eco,271,3,2,3,3,3,3,2,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +89126,87397,Male,Loyal Customer,29,Business travel,Business,2860,5,5,5,5,2,2,2,2,5,4,4,2,1,2,0,0.0,satisfied +89127,35265,Female,disloyal Customer,21,Business travel,Eco,1144,5,5,5,4,2,5,2,2,1,1,1,4,3,2,0,0.0,satisfied +89128,116980,Female,Loyal Customer,42,Business travel,Eco,451,3,1,1,1,2,3,3,2,2,3,2,3,2,3,23,21.0,neutral or dissatisfied +89129,117923,Male,disloyal Customer,23,Business travel,Eco,255,3,4,2,4,3,2,3,3,4,5,3,4,4,3,4,1.0,neutral or dissatisfied +89130,34847,Female,Loyal Customer,11,Personal Travel,Eco Plus,209,3,2,3,2,5,3,5,5,4,1,2,1,2,5,18,2.0,neutral or dissatisfied +89131,18585,Male,disloyal Customer,22,Business travel,Eco,192,3,5,4,2,2,4,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +89132,123476,Male,Loyal Customer,35,Business travel,Business,2077,3,3,3,3,2,5,5,4,4,4,4,5,4,4,1,5.0,satisfied +89133,73391,Male,Loyal Customer,48,Business travel,Eco,1182,2,4,4,4,2,2,2,2,2,1,3,4,3,2,3,87.0,neutral or dissatisfied +89134,46336,Male,disloyal Customer,20,Business travel,Eco,589,3,2,3,2,5,3,5,5,1,1,2,3,2,5,3,8.0,neutral or dissatisfied +89135,62721,Male,disloyal Customer,21,Business travel,Eco,783,3,3,3,1,3,2,2,1,2,1,1,2,3,2,0,1.0,neutral or dissatisfied +89136,46174,Male,Loyal Customer,60,Personal Travel,Eco,516,2,2,2,4,2,2,2,2,1,1,4,1,3,2,31,27.0,neutral or dissatisfied +89137,40648,Male,disloyal Customer,25,Business travel,Business,541,0,4,0,3,3,0,4,3,5,4,5,3,5,3,3,0.0,satisfied +89138,72769,Male,Loyal Customer,46,Business travel,Business,2201,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +89139,98489,Male,disloyal Customer,39,Business travel,Business,668,4,4,4,1,4,5,5,5,5,4,5,5,3,5,430,438.0,satisfied +89140,5301,Male,Loyal Customer,39,Personal Travel,Eco,293,5,4,4,3,1,4,1,1,4,5,4,3,4,1,0,0.0,satisfied +89141,34671,Male,Loyal Customer,15,Personal Travel,Business,301,3,4,3,2,4,3,2,4,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +89142,83148,Female,Loyal Customer,20,Personal Travel,Eco,1127,2,4,2,4,2,2,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +89143,41835,Female,Loyal Customer,45,Business travel,Business,462,4,4,4,4,3,2,5,5,5,5,5,1,5,5,0,0.0,satisfied +89144,20669,Female,disloyal Customer,13,Business travel,Eco,552,1,0,0,2,5,0,5,5,1,4,2,1,5,5,0,0.0,neutral or dissatisfied +89145,85261,Female,Loyal Customer,33,Personal Travel,Eco,813,2,4,2,1,4,2,4,4,5,3,4,3,4,4,2,0.0,neutral or dissatisfied +89146,55665,Female,Loyal Customer,41,Business travel,Business,3238,4,5,5,5,1,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +89147,42558,Female,Loyal Customer,36,Personal Travel,Business,622,4,5,4,4,3,1,4,5,5,4,5,2,5,3,4,4.0,satisfied +89148,87792,Female,disloyal Customer,20,Business travel,Eco,143,3,3,3,4,3,3,3,3,3,4,4,3,4,3,2,13.0,neutral or dissatisfied +89149,90541,Male,Loyal Customer,29,Business travel,Business,3220,4,4,4,4,5,5,5,5,3,2,5,3,5,5,25,26.0,satisfied +89150,122871,Female,Loyal Customer,15,Personal Travel,Eco,226,3,4,3,4,4,3,1,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +89151,571,Male,Loyal Customer,46,Business travel,Business,113,3,3,3,3,3,5,5,5,5,5,5,4,5,3,9,3.0,satisfied +89152,118395,Male,Loyal Customer,52,Business travel,Business,2823,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +89153,98320,Female,disloyal Customer,39,Business travel,Eco,1147,3,3,3,1,4,3,4,4,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +89154,83752,Female,disloyal Customer,54,Business travel,Eco,783,2,2,2,3,4,2,4,4,1,3,3,3,4,4,116,102.0,neutral or dissatisfied +89155,58667,Female,disloyal Customer,36,Business travel,Eco Plus,467,1,1,1,4,1,1,1,1,5,5,2,5,4,1,0,0.0,neutral or dissatisfied +89156,34061,Female,Loyal Customer,25,Business travel,Business,1674,3,4,4,4,3,3,3,3,1,5,3,2,4,3,0,0.0,neutral or dissatisfied +89157,115954,Female,Loyal Customer,48,Personal Travel,Eco,333,4,5,4,3,3,5,5,1,1,4,1,1,1,2,0,0.0,satisfied +89158,106761,Female,Loyal Customer,63,Personal Travel,Eco,829,1,4,1,4,4,4,5,2,2,1,2,3,2,4,14,7.0,neutral or dissatisfied +89159,31758,Female,disloyal Customer,23,Business travel,Eco,602,2,5,2,5,4,2,4,4,1,4,2,2,3,4,0,0.0,neutral or dissatisfied +89160,119296,Male,Loyal Customer,46,Business travel,Business,2596,3,3,3,3,4,5,5,5,5,5,4,4,5,3,0,0.0,satisfied +89161,121374,Male,Loyal Customer,33,Business travel,Business,2279,3,3,3,3,4,4,4,4,4,5,4,5,4,4,26,24.0,satisfied +89162,36302,Female,disloyal Customer,22,Business travel,Eco,395,3,0,3,3,3,3,3,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +89163,84083,Male,Loyal Customer,70,Personal Travel,Eco,879,3,0,3,2,5,3,5,5,3,3,4,2,2,5,3,0.0,neutral or dissatisfied +89164,116484,Male,Loyal Customer,29,Personal Travel,Eco,404,3,4,3,4,3,3,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +89165,127554,Female,Loyal Customer,54,Business travel,Business,2053,1,1,1,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +89166,2133,Male,disloyal Customer,35,Business travel,Eco,404,2,1,2,3,1,2,1,1,1,5,3,1,4,1,38,29.0,neutral or dissatisfied +89167,114194,Female,Loyal Customer,57,Business travel,Business,909,2,2,2,2,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +89168,2830,Female,Loyal Customer,47,Business travel,Business,409,5,5,5,5,5,5,5,4,4,4,4,5,4,5,0,10.0,satisfied +89169,78600,Male,Loyal Customer,47,Personal Travel,Eco,2454,2,1,2,3,1,2,1,1,2,2,3,4,3,1,0,15.0,neutral or dissatisfied +89170,4837,Male,Loyal Customer,32,Business travel,Business,2448,4,5,5,5,4,4,4,4,1,4,3,4,3,4,106,105.0,neutral or dissatisfied +89171,36065,Female,disloyal Customer,19,Business travel,Eco,399,4,2,3,3,2,3,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +89172,102856,Male,Loyal Customer,58,Business travel,Business,2243,1,1,1,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +89173,95527,Female,Loyal Customer,32,Personal Travel,Eco Plus,189,0,5,0,3,1,0,4,1,4,4,5,3,5,1,1,0.0,satisfied +89174,77956,Female,Loyal Customer,48,Business travel,Business,1783,4,4,5,4,4,4,5,4,4,4,4,5,4,3,19,13.0,satisfied +89175,25856,Male,Loyal Customer,26,Personal Travel,Eco,692,2,5,2,5,1,2,3,1,5,3,4,5,4,1,1,7.0,neutral or dissatisfied +89176,50130,Male,Loyal Customer,44,Business travel,Business,3997,2,1,1,1,3,4,3,3,3,3,2,1,3,4,59,59.0,neutral or dissatisfied +89177,32272,Male,Loyal Customer,38,Business travel,Eco,163,4,3,3,3,4,4,4,4,1,2,2,1,5,4,0,0.0,satisfied +89178,17300,Female,Loyal Customer,36,Business travel,Business,2366,5,5,5,5,3,4,2,5,5,5,5,1,5,3,106,108.0,satisfied +89179,96951,Male,Loyal Customer,45,Business travel,Business,775,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,8.0,satisfied +89180,58412,Male,Loyal Customer,42,Business travel,Eco,733,4,1,1,1,4,4,4,4,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +89181,9195,Female,Loyal Customer,53,Business travel,Eco Plus,363,3,4,4,4,4,2,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +89182,123518,Male,Loyal Customer,12,Personal Travel,Eco,2296,0,5,0,1,0,1,1,5,2,4,5,1,3,1,0,3.0,satisfied +89183,121267,Female,Loyal Customer,40,Personal Travel,Eco,2075,3,2,4,3,2,4,2,2,3,3,3,3,3,2,8,0.0,neutral or dissatisfied +89184,54400,Male,Loyal Customer,47,Business travel,Business,3059,0,0,0,5,3,2,5,1,1,1,1,1,1,4,38,26.0,satisfied +89185,113100,Female,Loyal Customer,25,Personal Travel,Eco,569,2,2,2,4,4,2,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +89186,100059,Male,Loyal Customer,22,Personal Travel,Eco,220,4,3,4,3,4,5,5,4,3,3,3,5,1,5,182,169.0,neutral or dissatisfied +89187,10031,Male,Loyal Customer,27,Business travel,Business,2489,4,4,4,4,5,5,5,5,4,2,4,4,4,5,0,0.0,satisfied +89188,8435,Male,Loyal Customer,29,Personal Travel,Eco,862,2,5,2,4,1,2,3,1,5,5,5,4,4,1,12,58.0,neutral or dissatisfied +89189,59884,Male,Loyal Customer,46,Business travel,Business,3109,2,2,2,2,3,4,4,2,2,2,2,3,2,3,42,22.0,satisfied +89190,74361,Female,Loyal Customer,39,Business travel,Business,1235,2,2,2,2,2,4,4,3,3,3,3,5,3,3,5,3.0,satisfied +89191,54858,Male,Loyal Customer,56,Business travel,Eco,985,2,1,1,1,2,2,2,2,3,5,3,2,3,2,0,3.0,neutral or dissatisfied +89192,110316,Female,Loyal Customer,51,Business travel,Business,1961,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +89193,91515,Male,Loyal Customer,66,Personal Travel,Eco,1620,3,5,2,1,3,2,5,3,1,3,4,1,1,3,30,32.0,neutral or dissatisfied +89194,101363,Male,Loyal Customer,70,Business travel,Business,1986,4,2,2,2,2,4,4,4,4,4,4,2,4,2,19,0.0,neutral or dissatisfied +89195,114268,Male,Loyal Customer,77,Business travel,Business,1511,1,3,3,3,5,4,4,1,1,1,1,2,1,3,20,9.0,neutral or dissatisfied +89196,122361,Male,Loyal Customer,25,Business travel,Business,3641,4,4,4,4,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +89197,126517,Male,Loyal Customer,18,Personal Travel,Eco,313,1,5,1,3,1,1,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +89198,102239,Female,Loyal Customer,48,Business travel,Business,3606,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +89199,27567,Female,Loyal Customer,42,Personal Travel,Eco,954,2,5,1,3,4,4,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +89200,40411,Male,Loyal Customer,53,Business travel,Eco,175,3,3,3,3,3,3,3,3,1,4,2,4,4,3,0,0.0,satisfied +89201,13772,Male,Loyal Customer,22,Business travel,Eco,837,5,1,1,1,5,5,3,5,2,2,3,2,1,5,5,2.0,satisfied +89202,32752,Female,disloyal Customer,38,Business travel,Eco,101,3,1,3,3,4,3,1,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +89203,47732,Male,Loyal Customer,41,Business travel,Business,2672,1,3,5,3,1,4,4,1,1,1,1,1,1,4,50,55.0,neutral or dissatisfied +89204,125384,Female,Loyal Customer,51,Business travel,Business,1440,5,5,5,5,5,4,5,3,3,4,3,3,3,3,0,18.0,satisfied +89205,39050,Female,Loyal Customer,41,Personal Travel,Eco Plus,313,1,4,3,3,5,4,5,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +89206,16190,Male,Loyal Customer,49,Business travel,Eco,277,4,5,2,5,4,4,4,4,2,4,4,4,3,4,43,42.0,satisfied +89207,124641,Female,Loyal Customer,57,Business travel,Business,399,2,5,2,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +89208,67228,Female,Loyal Customer,17,Personal Travel,Eco,964,4,3,4,3,4,4,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +89209,73888,Female,Loyal Customer,22,Business travel,Business,2342,1,1,1,1,2,2,2,2,4,3,5,3,4,2,1,0.0,satisfied +89210,122246,Male,Loyal Customer,61,Business travel,Eco,173,1,4,3,4,1,1,1,1,2,4,3,3,4,1,22,11.0,neutral or dissatisfied +89211,102264,Female,disloyal Customer,27,Business travel,Eco,397,4,1,4,3,3,4,3,3,4,4,4,1,3,3,38,33.0,neutral or dissatisfied +89212,98204,Male,Loyal Customer,51,Personal Travel,Eco,327,2,4,2,5,3,2,3,3,3,2,4,3,5,3,44,41.0,neutral or dissatisfied +89213,86250,Female,Loyal Customer,44,Personal Travel,Eco,356,1,5,1,2,5,4,5,5,5,1,5,2,5,4,0,0.0,neutral or dissatisfied +89214,29033,Female,Loyal Customer,57,Business travel,Business,556,2,2,2,2,3,5,2,4,4,5,4,5,4,3,0,0.0,satisfied +89215,17050,Female,Loyal Customer,37,Business travel,Eco,1134,4,2,2,2,4,4,4,4,3,2,3,2,3,4,0,0.0,satisfied +89216,115138,Female,Loyal Customer,49,Business travel,Business,1990,5,5,5,5,2,4,4,5,5,5,5,3,5,5,21,6.0,satisfied +89217,51671,Female,disloyal Customer,21,Business travel,Eco,261,2,3,2,3,1,2,1,1,4,2,4,3,3,1,2,6.0,neutral or dissatisfied +89218,109104,Male,Loyal Customer,51,Personal Travel,Eco,849,1,4,1,1,2,1,2,2,3,3,5,5,4,2,32,36.0,neutral or dissatisfied +89219,524,Female,Loyal Customer,50,Business travel,Business,3425,4,4,5,4,3,5,4,5,5,5,5,3,5,4,3,0.0,satisfied +89220,17290,Female,Loyal Customer,25,Business travel,Business,403,3,3,5,3,4,4,4,4,3,5,4,2,4,4,2,4.0,satisfied +89221,83942,Male,Loyal Customer,51,Business travel,Business,1664,2,2,3,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +89222,7883,Male,disloyal Customer,22,Business travel,Eco,948,4,4,4,2,5,4,5,5,1,4,3,5,4,5,0,2.0,satisfied +89223,119986,Male,Loyal Customer,46,Business travel,Business,1009,3,3,3,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +89224,113962,Female,Loyal Customer,60,Business travel,Business,1790,5,5,5,5,4,4,4,2,2,2,2,3,2,4,109,103.0,satisfied +89225,107375,Female,Loyal Customer,31,Business travel,Business,2148,5,5,5,5,4,4,4,4,4,3,5,5,5,4,0,0.0,satisfied +89226,84502,Male,disloyal Customer,40,Business travel,Business,2556,4,4,4,3,5,4,5,5,3,4,5,3,5,5,1,0.0,neutral or dissatisfied +89227,26172,Male,Loyal Customer,37,Business travel,Business,3475,3,1,1,1,4,4,3,3,3,3,3,1,3,4,25,30.0,neutral or dissatisfied +89228,90005,Male,Loyal Customer,50,Business travel,Business,684,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +89229,77448,Male,Loyal Customer,47,Business travel,Business,507,4,4,4,4,4,5,5,3,3,3,3,4,3,5,90,77.0,satisfied +89230,8833,Male,Loyal Customer,47,Business travel,Business,3678,2,5,2,2,3,5,4,3,3,3,3,4,3,3,2,20.0,satisfied +89231,83674,Male,Loyal Customer,41,Business travel,Business,2916,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +89232,57814,Female,disloyal Customer,45,Business travel,Business,622,3,3,3,1,4,3,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +89233,129782,Female,Loyal Customer,10,Personal Travel,Eco,337,2,3,5,2,4,5,4,4,5,1,3,4,4,4,0,0.0,neutral or dissatisfied +89234,69582,Male,Loyal Customer,65,Personal Travel,Eco,2475,2,1,2,3,2,5,5,3,1,4,4,5,3,5,0,0.0,neutral or dissatisfied +89235,122284,Male,Loyal Customer,16,Personal Travel,Eco,544,4,1,4,3,5,4,5,5,4,5,3,2,2,5,2,0.0,neutral or dissatisfied +89236,89865,Male,disloyal Customer,23,Business travel,Business,1306,5,0,5,1,3,5,2,3,5,2,5,3,5,3,40,35.0,satisfied +89237,103955,Female,Loyal Customer,26,Personal Travel,Eco,770,4,5,4,1,3,4,3,3,3,4,4,2,5,3,0,0.0,satisfied +89238,127707,Male,Loyal Customer,46,Business travel,Business,3007,2,2,2,2,4,4,4,5,5,5,5,3,5,4,8,12.0,satisfied +89239,62563,Male,Loyal Customer,71,Business travel,Eco,1781,3,5,5,5,3,3,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +89240,114746,Female,Loyal Customer,53,Business travel,Business,333,2,2,2,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +89241,24081,Male,Loyal Customer,16,Personal Travel,Eco Plus,866,0,5,0,3,4,0,4,4,4,3,5,4,5,4,0,0.0,satisfied +89242,89113,Male,disloyal Customer,42,Business travel,Eco,1425,2,2,2,4,1,2,1,1,4,3,2,1,4,1,3,8.0,neutral or dissatisfied +89243,57994,Male,Loyal Customer,50,Business travel,Business,1943,2,2,2,2,4,3,4,5,5,5,5,5,5,3,9,0.0,satisfied +89244,93625,Male,disloyal Customer,65,Business travel,Eco,304,1,0,1,3,1,1,1,1,2,4,2,2,5,1,2,47.0,neutral or dissatisfied +89245,105021,Female,Loyal Customer,44,Business travel,Business,2510,1,5,5,5,5,4,3,1,1,1,1,4,1,1,24,20.0,neutral or dissatisfied +89246,35824,Female,disloyal Customer,27,Business travel,Eco,1065,4,4,4,1,3,4,3,3,3,5,4,3,4,3,0,0.0,satisfied +89247,106462,Female,Loyal Customer,48,Business travel,Business,1300,5,5,5,5,5,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +89248,32426,Female,Loyal Customer,39,Business travel,Business,216,2,1,1,1,3,3,2,3,3,3,2,1,3,2,0,10.0,neutral or dissatisfied +89249,94373,Female,Loyal Customer,32,Business travel,Business,1706,0,5,0,4,2,2,2,2,3,3,4,5,5,2,0,0.0,satisfied +89250,37295,Male,disloyal Customer,24,Business travel,Eco,1028,2,2,2,4,3,2,3,3,2,2,3,4,3,3,7,3.0,neutral or dissatisfied +89251,112569,Male,Loyal Customer,43,Business travel,Business,2071,4,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +89252,123469,Male,Loyal Customer,56,Business travel,Business,2125,5,5,5,5,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +89253,14513,Male,disloyal Customer,28,Business travel,Eco Plus,402,1,2,2,1,2,2,3,2,5,4,3,4,2,2,3,3.0,neutral or dissatisfied +89254,45045,Female,Loyal Customer,61,Business travel,Business,342,4,4,4,4,5,5,1,4,4,4,4,5,4,4,0,2.0,satisfied +89255,23463,Female,disloyal Customer,22,Business travel,Eco,576,3,2,3,4,4,3,4,4,1,4,3,3,4,4,0,0.0,neutral or dissatisfied +89256,115901,Male,disloyal Customer,21,Business travel,Eco,447,4,3,4,4,5,4,5,5,2,3,1,3,1,5,0,0.0,satisfied +89257,64466,Female,Loyal Customer,41,Business travel,Business,3587,0,5,1,4,2,4,5,3,3,3,3,3,3,3,19,14.0,satisfied +89258,13877,Male,Loyal Customer,56,Business travel,Business,2075,1,1,1,1,3,3,3,1,1,1,1,1,1,1,24,21.0,neutral or dissatisfied +89259,17021,Female,disloyal Customer,40,Business travel,Business,781,3,3,3,4,3,3,3,3,1,5,3,1,3,3,3,8.0,neutral or dissatisfied +89260,52084,Female,Loyal Customer,11,Business travel,Business,639,1,1,1,1,4,4,4,4,1,2,5,5,5,4,0,0.0,satisfied +89261,75789,Male,Loyal Customer,14,Personal Travel,Eco,813,4,1,4,3,4,4,4,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +89262,96184,Female,disloyal Customer,39,Business travel,Business,460,3,3,3,4,3,3,3,3,4,3,3,1,4,3,0,4.0,neutral or dissatisfied +89263,57172,Female,disloyal Customer,26,Business travel,Business,2227,4,4,4,4,5,4,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +89264,87428,Female,Loyal Customer,56,Business travel,Eco Plus,425,4,5,5,5,2,2,1,5,5,4,5,4,5,3,62,66.0,satisfied +89265,114658,Male,Loyal Customer,41,Business travel,Business,2109,3,3,3,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +89266,40263,Male,Loyal Customer,56,Business travel,Business,2728,1,1,1,1,1,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +89267,118035,Female,Loyal Customer,42,Business travel,Business,1044,1,1,1,1,3,4,5,5,5,4,5,5,5,3,17,18.0,satisfied +89268,107225,Male,disloyal Customer,37,Business travel,Eco,251,2,0,2,4,3,2,3,3,1,4,1,1,5,3,0,0.0,neutral or dissatisfied +89269,16649,Female,Loyal Customer,24,Business travel,Business,488,3,1,1,1,3,3,3,3,3,2,3,1,4,3,30,25.0,neutral or dissatisfied +89270,76920,Male,Loyal Customer,39,Business travel,Business,1823,4,4,4,4,5,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +89271,118050,Female,disloyal Customer,25,Business travel,Business,1262,2,0,2,2,4,2,4,4,5,4,4,5,5,4,7,0.0,neutral or dissatisfied +89272,22717,Male,Loyal Customer,58,Business travel,Business,3575,0,5,0,1,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +89273,24477,Female,disloyal Customer,25,Business travel,Eco,547,2,2,3,4,1,3,1,1,1,3,4,4,4,1,5,14.0,neutral or dissatisfied +89274,16671,Male,Loyal Customer,16,Personal Travel,Eco,488,1,4,1,2,3,1,4,3,5,2,4,4,4,3,3,0.0,neutral or dissatisfied +89275,31277,Female,Loyal Customer,25,Business travel,Business,533,1,3,3,3,1,1,1,1,4,5,1,4,1,1,0,0.0,neutral or dissatisfied +89276,19263,Female,Loyal Customer,51,Personal Travel,Eco,802,2,4,2,4,2,3,4,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +89277,51217,Female,Loyal Customer,32,Business travel,Eco Plus,266,5,3,3,3,5,5,5,5,4,4,3,2,1,5,8,7.0,satisfied +89278,4698,Male,Loyal Customer,12,Personal Travel,Eco,364,3,4,3,4,5,3,5,5,3,5,3,3,4,5,0,1.0,neutral or dissatisfied +89279,21030,Male,Loyal Customer,41,Business travel,Business,106,0,5,1,3,3,1,5,5,5,5,5,3,5,1,82,72.0,satisfied +89280,86709,Male,disloyal Customer,29,Business travel,Business,1747,4,3,3,3,3,3,3,3,5,5,4,4,4,3,0,0.0,satisfied +89281,11231,Female,Loyal Customer,26,Personal Travel,Eco,140,2,4,2,1,2,2,2,2,1,1,2,5,3,2,0,15.0,neutral or dissatisfied +89282,111213,Female,Loyal Customer,29,Business travel,Business,1546,5,5,5,5,4,4,4,4,5,4,5,4,4,4,0,0.0,satisfied +89283,124654,Female,disloyal Customer,26,Business travel,Eco,399,2,1,2,3,1,2,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +89284,123725,Female,Loyal Customer,68,Business travel,Eco Plus,214,1,5,5,5,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +89285,70167,Female,disloyal Customer,38,Business travel,Business,550,1,1,1,1,4,1,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +89286,54255,Female,Loyal Customer,65,Personal Travel,Eco,1222,3,4,3,3,3,4,3,2,2,3,2,2,2,1,4,0.0,neutral or dissatisfied +89287,87226,Female,Loyal Customer,20,Personal Travel,Eco,946,4,2,4,2,4,4,4,4,2,2,3,3,2,4,0,0.0,neutral or dissatisfied +89288,21969,Female,disloyal Customer,34,Business travel,Eco,551,2,0,2,1,2,2,2,2,3,4,4,2,5,2,0,0.0,neutral or dissatisfied +89289,18753,Male,Loyal Customer,11,Personal Travel,Eco,1167,3,5,3,3,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +89290,64145,Female,disloyal Customer,47,Business travel,Business,989,4,4,4,2,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +89291,66455,Male,Loyal Customer,17,Personal Travel,Eco,1217,2,4,2,3,2,5,5,2,3,3,4,5,3,5,145,138.0,neutral or dissatisfied +89292,36052,Male,disloyal Customer,33,Business travel,Eco,399,3,0,3,2,1,3,1,1,3,1,4,4,2,1,0,5.0,neutral or dissatisfied +89293,97221,Female,Loyal Customer,8,Personal Travel,Eco Plus,1164,4,4,4,2,3,4,3,3,3,5,3,5,4,3,15,15.0,neutral or dissatisfied +89294,93904,Male,Loyal Customer,69,Personal Travel,Eco,588,1,3,1,3,1,1,1,1,1,3,3,1,4,1,0,0.0,neutral or dissatisfied +89295,117234,Male,Loyal Customer,60,Personal Travel,Eco,369,1,5,1,3,2,1,1,2,3,5,4,2,3,2,4,7.0,neutral or dissatisfied +89296,109773,Female,Loyal Customer,59,Business travel,Business,971,4,4,4,4,3,4,5,4,4,4,4,4,4,4,91,87.0,satisfied +89297,105251,Male,Loyal Customer,29,Business travel,Business,2106,5,5,5,5,5,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +89298,103198,Male,Loyal Customer,64,Personal Travel,Eco,814,3,0,3,1,4,3,4,4,4,3,4,5,4,4,0,3.0,neutral or dissatisfied +89299,38989,Male,Loyal Customer,40,Business travel,Business,113,5,5,5,5,1,3,4,4,4,4,5,3,4,1,0,4.0,satisfied +89300,76972,Male,Loyal Customer,33,Business travel,Eco Plus,1990,3,3,2,3,3,4,3,3,4,2,3,3,3,3,2,0.0,neutral or dissatisfied +89301,41945,Female,disloyal Customer,21,Business travel,Business,575,3,1,3,4,1,3,1,1,1,3,3,4,3,1,0,4.0,neutral or dissatisfied +89302,82616,Male,Loyal Customer,47,Personal Travel,Eco,528,4,2,4,3,2,4,2,2,1,4,4,2,3,2,3,35.0,neutral or dissatisfied +89303,106605,Female,Loyal Customer,47,Business travel,Business,2061,1,3,3,3,4,4,3,1,1,1,1,1,1,3,38,32.0,neutral or dissatisfied +89304,54202,Male,Loyal Customer,58,Personal Travel,Eco,1400,3,5,3,3,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +89305,67993,Male,Loyal Customer,31,Personal Travel,Eco Plus,1126,3,4,3,3,4,3,4,4,4,4,4,3,4,4,0,2.0,neutral or dissatisfied +89306,85503,Female,Loyal Customer,55,Personal Travel,Eco,214,3,0,3,4,2,5,5,1,1,3,1,3,1,5,15,11.0,neutral or dissatisfied +89307,116299,Female,Loyal Customer,14,Personal Travel,Eco,296,2,5,2,1,4,2,4,4,5,4,4,4,5,4,35,27.0,neutral or dissatisfied +89308,25418,Male,Loyal Customer,17,Business travel,Eco Plus,990,4,2,2,2,4,4,5,4,1,5,5,1,1,4,0,0.0,satisfied +89309,95171,Male,Loyal Customer,52,Personal Travel,Eco,233,2,2,2,4,4,2,4,4,3,1,4,3,4,4,8,6.0,neutral or dissatisfied +89310,108289,Female,Loyal Customer,41,Business travel,Business,1838,1,5,5,5,3,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +89311,103882,Female,Loyal Customer,63,Personal Travel,Eco,1072,3,3,3,4,3,3,3,3,3,3,3,3,3,2,43,47.0,neutral or dissatisfied +89312,55219,Female,Loyal Customer,30,Business travel,Business,3873,3,3,3,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +89313,40546,Female,disloyal Customer,46,Business travel,Eco,391,1,0,1,1,4,1,4,4,3,4,1,5,1,4,1,0.0,neutral or dissatisfied +89314,111701,Female,Loyal Customer,17,Business travel,Business,495,2,3,3,3,2,2,2,2,3,2,4,3,3,2,2,0.0,neutral or dissatisfied +89315,106614,Female,Loyal Customer,39,Business travel,Business,1216,4,5,5,5,2,2,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +89316,115100,Male,Loyal Customer,39,Business travel,Business,3665,3,3,3,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +89317,64002,Female,Loyal Customer,21,Business travel,Business,2969,1,2,4,2,1,1,1,1,2,1,4,1,3,1,0,0.0,neutral or dissatisfied +89318,73289,Male,Loyal Customer,59,Business travel,Business,2441,5,5,5,5,5,4,4,4,4,4,4,3,4,4,11,28.0,satisfied +89319,94261,Female,Loyal Customer,34,Business travel,Business,239,0,0,0,4,3,4,4,4,4,4,4,5,4,4,85,76.0,satisfied +89320,44235,Female,Loyal Customer,42,Business travel,Business,224,0,0,0,2,4,3,3,3,3,3,3,5,3,2,0,0.0,satisfied +89321,73672,Female,disloyal Customer,39,Business travel,Business,192,1,1,1,4,4,1,4,4,4,3,3,4,3,4,9,1.0,neutral or dissatisfied +89322,82435,Male,Loyal Customer,42,Business travel,Business,2577,2,3,5,3,2,3,3,2,2,1,2,3,2,1,10,24.0,neutral or dissatisfied +89323,56835,Female,Loyal Customer,43,Personal Travel,Eco,1605,2,4,2,2,4,5,4,3,3,2,3,4,3,3,3,9.0,neutral or dissatisfied +89324,68951,Male,Loyal Customer,16,Personal Travel,Eco Plus,646,2,4,2,4,2,2,2,2,5,1,3,3,2,2,0,0.0,neutral or dissatisfied +89325,11223,Female,Loyal Customer,20,Personal Travel,Eco,309,2,5,2,1,2,1,1,5,4,4,5,1,4,1,228,226.0,neutral or dissatisfied +89326,75795,Male,Loyal Customer,26,Personal Travel,Eco,868,3,4,2,1,3,2,3,3,5,2,4,2,1,3,11,16.0,neutral or dissatisfied +89327,102789,Female,Loyal Customer,16,Personal Travel,Eco,1099,2,1,2,3,3,2,3,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +89328,40385,Female,Loyal Customer,54,Personal Travel,Eco,1250,3,4,3,2,3,3,5,1,1,3,1,4,1,4,0,13.0,neutral or dissatisfied +89329,18085,Male,Loyal Customer,40,Personal Travel,Eco,488,2,3,2,1,5,2,5,5,4,5,3,5,4,5,0,0.0,neutral or dissatisfied +89330,11331,Female,Loyal Customer,13,Personal Travel,Eco,316,2,4,2,4,4,2,2,4,4,2,2,1,5,4,111,112.0,neutral or dissatisfied +89331,95037,Male,Loyal Customer,58,Personal Travel,Eco,239,2,3,0,4,4,0,4,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +89332,84926,Female,Loyal Customer,70,Personal Travel,Eco,547,3,2,2,2,4,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +89333,20363,Female,Loyal Customer,51,Business travel,Eco,287,5,5,5,5,5,1,1,5,5,5,5,1,5,4,2,0.0,satisfied +89334,33866,Male,Loyal Customer,9,Personal Travel,Eco,1562,3,3,3,3,5,3,5,5,1,3,3,2,3,5,0,0.0,neutral or dissatisfied +89335,67376,Male,Loyal Customer,49,Business travel,Eco,641,1,4,4,4,1,1,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +89336,24064,Male,Loyal Customer,39,Business travel,Eco Plus,427,4,5,5,5,4,4,4,4,5,3,2,1,5,4,7,14.0,satisfied +89337,67956,Female,Loyal Customer,40,Business travel,Business,3861,2,2,2,2,3,5,4,2,2,3,2,4,2,5,0,0.0,satisfied +89338,41249,Female,Loyal Customer,24,Business travel,Business,852,5,5,5,5,4,4,4,4,5,5,3,2,2,4,0,0.0,satisfied +89339,120550,Female,disloyal Customer,38,Business travel,Business,1481,4,4,4,1,3,4,3,3,4,2,3,5,5,3,2,0.0,satisfied +89340,12622,Male,Loyal Customer,43,Personal Travel,Eco,802,1,5,1,1,2,1,2,2,2,2,1,5,1,2,8,0.0,neutral or dissatisfied +89341,91956,Female,Loyal Customer,65,Personal Travel,Eco,2446,4,4,3,1,2,5,4,5,5,3,5,5,5,4,5,0.0,satisfied +89342,15105,Female,Loyal Customer,20,Personal Travel,Eco,322,2,3,2,4,2,2,2,2,4,2,3,4,3,2,0,4.0,neutral or dissatisfied +89343,6106,Female,disloyal Customer,26,Business travel,Business,409,3,1,3,2,4,3,4,4,3,2,2,4,1,4,69,100.0,neutral or dissatisfied +89344,66108,Female,Loyal Customer,25,Business travel,Business,583,4,4,4,4,4,4,4,4,5,5,5,4,5,4,0,0.0,satisfied +89345,33284,Male,Loyal Customer,37,Personal Travel,Eco Plus,163,2,3,2,3,5,2,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +89346,37256,Female,Loyal Customer,34,Business travel,Business,1074,4,4,4,4,3,3,3,3,3,4,3,1,3,2,15,14.0,satisfied +89347,7509,Female,disloyal Customer,64,Business travel,Business,762,2,2,2,2,5,2,5,5,5,4,4,4,4,5,0,0.0,satisfied +89348,86633,Female,Loyal Customer,16,Business travel,Business,746,3,3,3,3,3,3,3,3,3,1,4,2,3,3,1,14.0,neutral or dissatisfied +89349,56946,Male,Loyal Customer,30,Business travel,Business,2454,3,1,1,1,3,3,3,3,5,2,3,3,1,3,22,6.0,neutral or dissatisfied +89350,129270,Female,Loyal Customer,32,Business travel,Business,2521,2,2,2,2,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +89351,93090,Female,Loyal Customer,30,Personal Travel,Eco,860,3,5,3,2,2,3,2,2,1,1,5,4,2,2,0,0.0,neutral or dissatisfied +89352,107649,Male,Loyal Customer,31,Business travel,Business,251,4,4,4,4,5,5,5,5,5,2,5,4,5,5,10,0.0,satisfied +89353,102199,Male,Loyal Customer,44,Business travel,Business,2488,3,3,3,3,3,5,4,5,5,5,5,5,5,5,13,14.0,satisfied +89354,94582,Female,Loyal Customer,43,Business travel,Eco,323,3,4,4,4,5,3,4,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +89355,24623,Male,Loyal Customer,62,Business travel,Eco,266,4,5,5,5,4,4,4,4,5,2,3,4,4,4,7,0.0,satisfied +89356,28958,Male,disloyal Customer,23,Business travel,Eco,679,3,3,3,3,3,4,5,3,5,3,3,5,2,5,142,140.0,neutral or dissatisfied +89357,79757,Male,disloyal Customer,25,Business travel,Business,1089,0,0,0,4,1,0,5,1,3,3,4,3,4,1,5,0.0,satisfied +89358,99001,Male,Loyal Customer,42,Business travel,Business,479,4,4,4,4,5,5,4,5,5,5,5,5,5,4,0,1.0,satisfied +89359,45546,Male,Loyal Customer,56,Personal Travel,Eco,566,4,4,4,1,3,4,3,3,5,4,5,4,5,3,34,17.0,neutral or dissatisfied +89360,61171,Male,disloyal Customer,20,Business travel,Eco,967,3,3,3,5,4,3,4,4,3,3,5,3,4,4,4,0.0,satisfied +89361,122571,Male,Loyal Customer,41,Business travel,Business,728,5,5,5,5,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +89362,114621,Male,disloyal Customer,25,Business travel,Business,308,1,5,1,3,3,1,3,3,3,5,5,4,5,3,4,0.0,neutral or dissatisfied +89363,96,Female,Loyal Customer,34,Personal Travel,Eco Plus,173,2,4,0,2,3,0,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +89364,52245,Male,Loyal Customer,18,Business travel,Business,651,4,4,4,4,4,4,4,4,5,1,1,5,2,4,76,62.0,satisfied +89365,80568,Male,disloyal Customer,19,Business travel,Eco,1747,2,2,2,4,5,2,5,5,3,2,4,4,4,5,4,0.0,neutral or dissatisfied +89366,83978,Female,Loyal Customer,60,Business travel,Business,3243,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +89367,97447,Female,Loyal Customer,16,Business travel,Business,670,2,2,2,2,4,5,4,4,3,2,5,4,5,4,0,0.0,satisfied +89368,89251,Female,Loyal Customer,36,Personal Travel,Eco Plus,1919,2,2,2,4,2,2,2,2,3,5,3,4,3,2,4,0.0,neutral or dissatisfied +89369,85745,Female,Loyal Customer,45,Business travel,Business,2897,2,2,2,2,5,4,5,5,5,4,5,5,5,3,0,11.0,satisfied +89370,64956,Male,Loyal Customer,46,Business travel,Business,1721,2,4,4,4,5,4,4,2,2,2,2,1,2,2,12,16.0,neutral or dissatisfied +89371,107793,Female,Loyal Customer,49,Business travel,Business,349,2,1,2,1,2,3,3,2,2,2,2,2,2,4,27,12.0,neutral or dissatisfied +89372,58727,Male,Loyal Customer,28,Business travel,Business,1620,4,4,4,4,3,3,3,3,3,5,5,4,4,3,0,0.0,satisfied +89373,44952,Male,Loyal Customer,53,Personal Travel,Eco,397,3,4,3,4,1,3,1,1,3,4,4,4,4,1,1,0.0,neutral or dissatisfied +89374,90520,Female,disloyal Customer,32,Business travel,Business,515,3,3,3,4,2,3,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +89375,97946,Male,Loyal Customer,49,Business travel,Business,483,1,2,2,2,5,3,3,1,1,1,1,3,1,1,6,3.0,neutral or dissatisfied +89376,45585,Male,Loyal Customer,32,Business travel,Eco,260,4,3,4,4,4,4,4,4,5,4,5,4,5,4,17,22.0,satisfied +89377,28489,Female,disloyal Customer,15,Business travel,Eco Plus,1739,5,0,5,3,2,5,2,2,5,5,5,3,4,2,0,0.0,satisfied +89378,71991,Male,Loyal Customer,58,Personal Travel,Eco,1440,4,4,5,4,3,5,3,3,5,4,3,3,4,3,1,6.0,neutral or dissatisfied +89379,49642,Male,Loyal Customer,33,Business travel,Eco,86,5,5,5,5,5,5,5,5,4,1,2,4,3,5,0,0.0,satisfied +89380,84510,Female,disloyal Customer,28,Business travel,Business,2556,3,3,3,1,2,3,4,2,4,2,3,4,5,2,0,0.0,neutral or dissatisfied +89381,65539,Female,Loyal Customer,55,Business travel,Business,175,2,2,5,2,4,4,5,5,5,5,4,3,5,4,87,72.0,satisfied +89382,71059,Female,Loyal Customer,17,Personal Travel,Eco,802,4,1,4,2,5,4,5,5,4,1,2,2,1,5,6,0.0,satisfied +89383,128787,Female,Loyal Customer,56,Business travel,Business,2475,4,4,4,4,5,5,5,5,4,4,4,5,4,5,0,0.0,satisfied +89384,50273,Male,disloyal Customer,18,Business travel,Eco,262,2,2,2,3,2,2,2,2,5,4,4,2,1,2,244,261.0,neutral or dissatisfied +89385,23829,Male,Loyal Customer,61,Business travel,Eco,731,2,1,1,1,3,2,3,3,3,2,4,4,3,3,74,94.0,neutral or dissatisfied +89386,53442,Female,Loyal Customer,51,Business travel,Eco,2253,5,1,1,1,1,5,3,5,5,5,5,5,5,5,21,11.0,satisfied +89387,36680,Female,Loyal Customer,26,Personal Travel,Eco,1249,3,4,3,3,3,3,3,3,3,5,4,4,4,3,0,10.0,neutral or dissatisfied +89388,129174,Male,Loyal Customer,45,Personal Travel,Eco,679,1,5,1,5,2,1,2,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +89389,66701,Female,Loyal Customer,49,Business travel,Business,1808,5,5,5,5,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +89390,50127,Male,Loyal Customer,46,Business travel,Business,3473,1,5,2,5,3,3,3,2,2,2,1,1,2,2,0,0.0,neutral or dissatisfied +89391,61661,Female,Loyal Customer,43,Business travel,Business,2124,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +89392,11168,Female,Loyal Customer,42,Personal Travel,Eco,308,3,1,3,4,4,4,4,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +89393,33786,Female,Loyal Customer,26,Business travel,Business,2747,1,5,5,5,1,1,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +89394,56880,Male,Loyal Customer,52,Business travel,Business,2425,4,4,4,4,5,5,5,5,3,3,4,5,4,5,5,0.0,satisfied +89395,21299,Female,Loyal Customer,63,Business travel,Business,292,2,2,2,2,4,5,5,5,5,4,5,1,5,5,0,0.0,satisfied +89396,96029,Female,Loyal Customer,34,Business travel,Business,2672,3,3,3,3,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +89397,31595,Female,disloyal Customer,29,Business travel,Eco,602,3,2,3,3,4,3,4,4,3,3,4,4,4,4,9,7.0,neutral or dissatisfied +89398,117431,Male,Loyal Customer,26,Business travel,Business,2833,5,5,5,5,5,4,5,5,3,4,4,3,5,5,27,43.0,satisfied +89399,113538,Female,disloyal Customer,20,Business travel,Eco,258,1,1,1,3,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +89400,107877,Female,Loyal Customer,53,Personal Travel,Eco,228,4,3,4,3,4,1,1,5,5,4,1,3,5,5,0,0.0,neutral or dissatisfied +89401,120028,Male,Loyal Customer,55,Business travel,Business,2448,5,5,3,5,4,5,5,5,5,5,5,5,5,4,0,6.0,satisfied +89402,60296,Female,Loyal Customer,52,Personal Travel,Eco,783,1,5,1,3,4,5,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +89403,35628,Male,Loyal Customer,40,Personal Travel,Eco Plus,1080,2,5,2,4,4,2,4,4,3,2,5,5,4,4,0,5.0,neutral or dissatisfied +89404,19684,Female,Loyal Customer,56,Business travel,Eco,409,4,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +89405,120414,Male,disloyal Customer,17,Business travel,Eco,449,3,3,4,3,3,4,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +89406,62255,Female,Loyal Customer,43,Business travel,Business,2565,2,2,2,2,4,3,4,5,5,5,5,3,5,5,1,0.0,satisfied +89407,66636,Male,Loyal Customer,30,Business travel,Business,2679,2,2,1,2,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +89408,20671,Female,disloyal Customer,27,Business travel,Eco,552,2,4,2,4,2,2,2,2,2,5,3,1,5,2,0,1.0,neutral or dissatisfied +89409,55191,Male,Loyal Customer,42,Business travel,Eco Plus,1635,1,2,2,2,1,1,1,1,3,2,4,2,3,1,12,6.0,neutral or dissatisfied +89410,122594,Female,disloyal Customer,36,Business travel,Business,728,4,4,4,2,2,4,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +89411,23746,Male,Loyal Customer,31,Business travel,Business,3477,2,2,2,2,4,4,4,4,1,5,2,5,3,4,0,13.0,satisfied +89412,19098,Female,Loyal Customer,39,Business travel,Eco,265,4,4,3,4,4,4,4,4,5,1,1,3,3,4,0,0.0,satisfied +89413,38609,Male,Loyal Customer,32,Business travel,Business,2260,2,5,5,5,2,2,2,2,3,1,3,2,3,2,0,18.0,neutral or dissatisfied +89414,27009,Male,disloyal Customer,22,Business travel,Eco,467,4,0,4,1,5,4,5,5,3,5,4,4,1,5,0,0.0,satisfied +89415,92236,Male,Loyal Customer,64,Personal Travel,Eco Plus,1956,2,5,2,4,2,1,1,5,3,3,5,1,4,1,570,567.0,neutral or dissatisfied +89416,105057,Male,Loyal Customer,44,Business travel,Business,1539,5,5,5,5,4,5,5,5,5,5,5,5,5,3,53,52.0,satisfied +89417,124287,Male,Loyal Customer,50,Business travel,Business,3539,3,3,3,3,4,5,5,4,4,4,4,5,4,5,9,2.0,satisfied +89418,11562,Female,disloyal Customer,26,Business travel,Business,771,3,0,3,3,2,3,3,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +89419,42764,Male,Loyal Customer,40,Business travel,Business,4000,4,4,4,4,5,3,5,5,5,4,5,3,5,5,0,0.0,satisfied +89420,66420,Female,Loyal Customer,59,Personal Travel,Eco,1562,2,5,2,1,2,3,5,5,5,2,5,3,5,4,0,8.0,neutral or dissatisfied +89421,3400,Male,disloyal Customer,26,Business travel,Eco,315,1,0,2,1,2,2,2,2,3,1,3,3,2,2,6,0.0,neutral or dissatisfied +89422,92082,Male,disloyal Customer,42,Business travel,Eco,1344,1,1,1,2,5,1,5,5,4,5,1,2,2,5,91,82.0,neutral or dissatisfied +89423,67321,Female,Loyal Customer,30,Personal Travel,Eco Plus,964,2,1,2,3,1,2,1,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +89424,38598,Male,Loyal Customer,31,Business travel,Eco,231,5,2,5,5,5,5,5,5,2,2,2,3,1,5,22,14.0,satisfied +89425,103346,Female,Loyal Customer,51,Personal Travel,Eco,1139,2,1,2,2,4,3,2,5,5,2,1,4,5,2,0,0.0,neutral or dissatisfied +89426,4371,Male,Loyal Customer,48,Business travel,Business,473,3,3,4,3,3,3,3,3,3,3,3,1,3,2,4,0.0,neutral or dissatisfied +89427,62271,Male,Loyal Customer,54,Business travel,Business,2543,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +89428,32698,Male,Loyal Customer,40,Business travel,Eco,102,5,5,4,5,5,5,5,5,3,3,2,4,1,5,0,4.0,satisfied +89429,23122,Female,Loyal Customer,38,Business travel,Eco,223,4,2,2,2,4,4,4,4,2,2,5,3,4,4,1,3.0,satisfied +89430,67731,Female,disloyal Customer,24,Business travel,Eco,1235,3,3,3,2,1,3,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +89431,52198,Female,disloyal Customer,45,Business travel,Eco,455,2,0,2,4,2,2,5,2,2,2,1,3,3,2,0,0.0,neutral or dissatisfied +89432,92084,Male,Loyal Customer,34,Business travel,Business,1535,4,5,4,4,2,4,4,5,5,5,5,3,5,5,10,0.0,satisfied +89433,20162,Male,Loyal Customer,40,Business travel,Business,403,1,1,1,1,1,4,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +89434,6372,Male,Loyal Customer,28,Business travel,Business,1628,3,1,1,1,3,3,3,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +89435,15577,Female,Loyal Customer,47,Business travel,Business,3779,3,3,3,3,1,2,5,5,5,4,5,5,5,1,39,35.0,satisfied +89436,102223,Male,Loyal Customer,47,Business travel,Eco,386,4,4,4,4,4,4,4,4,2,3,3,3,4,4,0,10.0,neutral or dissatisfied +89437,59324,Male,disloyal Customer,20,Business travel,Eco,1338,1,1,1,2,4,1,4,4,4,4,3,4,4,4,2,0.0,neutral or dissatisfied +89438,32360,Female,Loyal Customer,40,Business travel,Eco,101,4,4,4,4,4,4,4,4,1,1,1,1,4,4,2,3.0,satisfied +89439,43987,Male,Loyal Customer,53,Business travel,Business,1686,4,4,4,4,5,4,5,4,4,4,4,5,4,2,5,0.0,satisfied +89440,34051,Female,disloyal Customer,30,Business travel,Eco,1674,5,5,5,1,1,5,1,1,5,3,4,2,5,1,120,107.0,satisfied +89441,111369,Male,disloyal Customer,37,Business travel,Business,1173,3,3,3,1,2,3,2,2,4,5,4,4,4,2,12,53.0,neutral or dissatisfied +89442,58479,Male,Loyal Customer,58,Business travel,Eco,719,1,2,2,2,1,1,1,1,1,1,3,1,3,1,36,33.0,neutral or dissatisfied +89443,90158,Male,Loyal Customer,67,Personal Travel,Eco,957,1,4,1,5,3,1,3,3,3,5,4,3,5,3,106,99.0,neutral or dissatisfied +89444,100504,Male,disloyal Customer,29,Business travel,Eco,580,2,2,2,3,5,2,5,5,4,5,3,3,4,5,0,0.0,neutral or dissatisfied +89445,22121,Male,Loyal Customer,55,Personal Travel,Eco,694,2,4,2,3,5,2,5,5,4,3,4,5,5,5,4,18.0,neutral or dissatisfied +89446,54915,Female,Loyal Customer,72,Business travel,Eco Plus,985,3,5,5,5,1,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +89447,55465,Male,Loyal Customer,43,Business travel,Business,1825,3,3,3,3,3,3,5,2,2,2,2,4,2,5,13,12.0,satisfied +89448,30622,Female,Loyal Customer,32,Business travel,Eco,258,0,0,0,1,1,4,1,1,2,2,2,4,1,1,0,16.0,satisfied +89449,113514,Male,Loyal Customer,55,Business travel,Eco,414,2,3,3,3,2,2,2,2,1,2,3,2,3,2,53,46.0,neutral or dissatisfied +89450,45687,Female,Loyal Customer,26,Business travel,Eco,896,4,3,3,3,4,4,5,4,1,4,2,3,5,4,0,0.0,satisfied +89451,25888,Female,Loyal Customer,66,Business travel,Eco,907,4,2,2,2,1,2,4,4,4,4,4,4,4,1,0,0.0,satisfied +89452,124639,Female,Loyal Customer,44,Business travel,Business,399,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +89453,62929,Female,Loyal Customer,54,Business travel,Business,3139,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +89454,63713,Female,Loyal Customer,46,Business travel,Business,1660,3,3,3,3,2,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +89455,91015,Male,Loyal Customer,28,Personal Travel,Eco,250,4,4,0,1,4,0,3,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +89456,67694,Female,Loyal Customer,31,Business travel,Business,3438,2,5,5,5,2,2,2,2,4,5,2,1,2,2,0,5.0,neutral or dissatisfied +89457,44192,Male,Loyal Customer,41,Business travel,Eco,157,4,2,2,2,4,4,4,4,3,1,4,1,4,4,0,0.0,satisfied +89458,71956,Female,disloyal Customer,23,Business travel,Eco,1440,3,2,2,4,3,3,3,3,4,3,4,3,4,3,9,30.0,neutral or dissatisfied +89459,102043,Female,disloyal Customer,40,Business travel,Business,386,3,3,3,4,5,3,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +89460,124447,Male,Loyal Customer,44,Business travel,Business,3868,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +89461,64665,Male,disloyal Customer,27,Business travel,Business,247,0,0,0,1,4,0,4,4,3,2,4,5,4,4,25,26.0,satisfied +89462,58638,Female,Loyal Customer,47,Business travel,Business,867,2,2,2,2,2,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +89463,71692,Male,Loyal Customer,15,Personal Travel,Eco,1120,2,5,2,4,3,2,3,3,4,4,4,5,5,3,20,17.0,neutral or dissatisfied +89464,22292,Male,Loyal Customer,31,Business travel,Eco,238,4,5,5,5,4,4,4,4,5,5,1,3,3,4,0,0.0,satisfied +89465,118507,Male,Loyal Customer,35,Business travel,Eco,369,1,5,5,5,1,1,1,1,4,5,3,2,3,1,49,38.0,neutral or dissatisfied +89466,23876,Female,Loyal Customer,44,Business travel,Business,589,2,2,2,2,4,4,5,4,4,4,4,3,4,3,22,47.0,satisfied +89467,62302,Female,Loyal Customer,32,Business travel,Eco,414,1,5,4,5,1,1,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +89468,14424,Male,Loyal Customer,22,Personal Travel,Eco,585,4,2,4,4,5,4,5,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +89469,84928,Female,Loyal Customer,34,Personal Travel,Eco,516,2,1,2,2,4,2,4,4,2,1,2,3,2,4,0,1.0,neutral or dissatisfied +89470,50916,Female,Loyal Customer,58,Personal Travel,Eco,190,2,3,0,1,4,3,4,5,5,0,5,2,5,4,0,0.0,neutral or dissatisfied +89471,106424,Female,disloyal Customer,40,Personal Travel,Eco,488,2,2,2,4,1,2,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +89472,42231,Female,Loyal Customer,55,Business travel,Business,2817,2,4,4,4,3,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +89473,33025,Female,Loyal Customer,69,Personal Travel,Eco,102,3,3,3,1,5,4,3,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +89474,108226,Male,Loyal Customer,7,Personal Travel,Business,895,3,5,3,1,4,3,2,4,5,5,5,3,4,4,20,18.0,neutral or dissatisfied +89475,91783,Female,Loyal Customer,43,Personal Travel,Eco,532,4,5,4,3,5,4,5,3,3,4,3,5,3,3,0,0.0,neutral or dissatisfied +89476,76745,Male,Loyal Customer,57,Business travel,Business,2932,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +89477,77432,Female,Loyal Customer,66,Personal Travel,Eco,588,3,4,3,3,2,4,3,5,5,3,5,4,5,3,41,68.0,neutral or dissatisfied +89478,40828,Female,Loyal Customer,25,Business travel,Business,541,3,3,3,3,3,3,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +89479,95242,Male,Loyal Customer,25,Personal Travel,Eco,562,3,5,2,1,5,2,5,5,5,3,2,3,5,5,19,9.0,neutral or dissatisfied +89480,119548,Female,Loyal Customer,18,Personal Travel,Eco,857,2,1,2,3,1,2,2,1,3,3,3,1,2,1,15,21.0,neutral or dissatisfied +89481,100062,Female,Loyal Customer,63,Personal Travel,Eco,277,1,1,1,4,3,4,3,3,3,1,3,3,3,1,26,39.0,neutral or dissatisfied +89482,85571,Male,disloyal Customer,19,Business travel,Eco,259,2,4,2,3,1,2,1,1,1,2,3,1,4,1,0,0.0,neutral or dissatisfied +89483,36883,Female,Loyal Customer,34,Business travel,Eco,1182,4,2,2,2,4,4,4,4,2,2,4,1,4,4,2,0.0,neutral or dissatisfied +89484,83071,Female,Loyal Customer,41,Business travel,Eco,1127,1,2,2,2,1,2,1,1,3,2,3,1,4,1,0,0.0,neutral or dissatisfied +89485,73207,Female,Loyal Customer,52,Personal Travel,Eco,1258,1,5,1,1,4,3,5,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +89486,27048,Female,disloyal Customer,38,Business travel,Eco,1491,4,4,4,3,5,4,5,5,5,2,3,1,2,5,0,13.0,satisfied +89487,60768,Female,disloyal Customer,23,Business travel,Eco,628,3,3,3,4,1,3,1,1,3,5,4,4,3,1,3,0.0,neutral or dissatisfied +89488,125883,Female,Loyal Customer,25,Personal Travel,Eco,920,5,5,5,3,1,5,1,1,2,2,1,3,5,1,54,43.0,satisfied +89489,74953,Female,disloyal Customer,55,Business travel,Business,2475,2,2,2,3,1,2,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +89490,119516,Female,Loyal Customer,58,Business travel,Business,3318,4,2,2,2,5,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +89491,112677,Female,disloyal Customer,50,Business travel,Business,672,3,4,4,3,2,3,2,2,4,2,5,3,4,2,0,0.0,neutral or dissatisfied +89492,17666,Female,Loyal Customer,44,Business travel,Eco Plus,1008,5,3,2,3,1,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +89493,664,Male,Loyal Customer,58,Business travel,Business,2620,1,1,1,1,3,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +89494,115109,Female,Loyal Customer,44,Business travel,Business,371,4,4,4,4,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +89495,115868,Female,Loyal Customer,37,Business travel,Business,480,2,3,3,3,5,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +89496,3187,Female,Loyal Customer,50,Business travel,Business,585,4,1,1,1,4,3,3,4,4,4,4,1,4,1,69,91.0,neutral or dissatisfied +89497,118807,Female,Loyal Customer,7,Personal Travel,Eco,651,2,3,3,3,3,3,3,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +89498,92499,Male,Loyal Customer,16,Business travel,Business,1892,5,5,3,5,4,4,4,4,2,4,2,1,3,4,0,0.0,satisfied +89499,58605,Male,Loyal Customer,39,Personal Travel,Eco,334,2,4,2,3,2,2,3,2,3,1,3,3,3,2,41,41.0,neutral or dissatisfied +89500,68879,Male,disloyal Customer,22,Business travel,Eco,1061,3,3,3,4,3,3,3,3,5,4,4,3,4,3,0,0.0,satisfied +89501,100601,Female,Loyal Customer,50,Business travel,Business,2737,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +89502,88315,Female,disloyal Customer,25,Business travel,Business,406,1,5,1,1,1,1,1,1,5,4,5,3,4,1,1,0.0,neutral or dissatisfied +89503,18486,Male,Loyal Customer,30,Business travel,Business,2497,3,4,5,4,2,2,3,2,4,4,4,4,4,2,45,40.0,neutral or dissatisfied +89504,93663,Female,disloyal Customer,52,Business travel,Eco,717,2,2,2,3,5,2,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +89505,37708,Male,Loyal Customer,24,Personal Travel,Eco,1069,3,4,2,2,4,2,4,4,2,5,2,2,5,4,0,0.0,neutral or dissatisfied +89506,48817,Male,Loyal Customer,9,Personal Travel,Business,326,2,1,2,3,4,2,4,4,1,3,2,3,3,4,0,0.0,neutral or dissatisfied +89507,93617,Female,Loyal Customer,41,Business travel,Business,577,2,4,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +89508,118340,Female,Loyal Customer,72,Business travel,Business,202,3,2,2,2,1,3,4,4,4,3,3,1,4,4,13,8.0,neutral or dissatisfied +89509,54627,Male,disloyal Customer,29,Business travel,Eco,854,3,3,3,4,1,3,1,1,1,4,4,3,3,1,25,5.0,neutral or dissatisfied +89510,113723,Male,Loyal Customer,49,Personal Travel,Eco,223,1,5,1,4,4,1,4,4,4,2,5,4,5,4,5,8.0,neutral or dissatisfied +89511,67574,Male,disloyal Customer,39,Business travel,Business,1235,1,1,1,3,4,1,4,4,4,3,4,3,5,4,1,0.0,neutral or dissatisfied +89512,118078,Female,Loyal Customer,28,Business travel,Business,3099,2,2,4,2,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +89513,43706,Male,Loyal Customer,56,Business travel,Eco,196,4,5,5,5,4,4,4,4,3,4,4,2,4,4,52,39.0,neutral or dissatisfied +89514,16390,Male,Loyal Customer,50,Business travel,Eco,463,4,4,2,2,4,4,4,4,2,5,4,2,4,4,125,129.0,satisfied +89515,93487,Female,Loyal Customer,31,Business travel,Business,1107,4,4,4,4,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +89516,30365,Female,Loyal Customer,48,Business travel,Business,641,2,2,2,2,3,5,2,5,5,5,5,4,5,5,38,37.0,satisfied +89517,111657,Male,Loyal Customer,42,Personal Travel,Eco Plus,1558,2,3,2,2,5,2,5,5,2,3,3,3,3,5,106,122.0,neutral or dissatisfied +89518,20996,Female,disloyal Customer,50,Business travel,Eco Plus,689,1,1,1,1,4,1,4,4,5,5,3,3,5,4,48,55.0,neutral or dissatisfied +89519,119328,Female,Loyal Customer,40,Personal Travel,Eco,214,2,1,2,4,2,2,2,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +89520,126332,Male,Loyal Customer,18,Personal Travel,Eco,600,2,2,2,3,3,2,3,3,2,5,4,1,3,3,3,0.0,neutral or dissatisfied +89521,45814,Male,Loyal Customer,43,Business travel,Eco,411,3,1,1,1,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +89522,90781,Male,Loyal Customer,54,Business travel,Business,3813,5,5,5,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +89523,95424,Male,Loyal Customer,39,Business travel,Business,3220,3,3,3,3,3,4,5,4,4,4,4,5,4,3,11,5.0,satisfied +89524,63939,Male,Loyal Customer,39,Personal Travel,Eco,1192,3,4,3,5,1,3,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +89525,128739,Male,disloyal Customer,43,Business travel,Business,2402,5,5,5,4,4,5,4,4,4,4,5,5,5,4,0,0.0,satisfied +89526,87596,Female,Loyal Customer,35,Personal Travel,Eco,432,3,5,3,2,4,3,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +89527,38201,Male,disloyal Customer,16,Business travel,Business,1121,5,0,5,4,3,5,3,3,5,5,4,5,4,3,8,9.0,satisfied +89528,36970,Female,Loyal Customer,44,Business travel,Eco,805,4,1,1,1,4,3,3,4,4,4,4,4,4,2,95,86.0,satisfied +89529,31259,Male,Loyal Customer,38,Business travel,Business,533,1,4,1,1,5,2,2,4,4,4,4,3,4,5,4,3.0,satisfied +89530,98891,Female,Loyal Customer,30,Business travel,Eco Plus,991,1,1,1,1,1,1,1,1,1,5,2,2,2,1,2,0.0,neutral or dissatisfied +89531,5205,Male,Loyal Customer,39,Business travel,Business,190,1,3,3,3,1,3,3,4,4,4,1,3,4,2,0,0.0,neutral or dissatisfied +89532,30225,Female,Loyal Customer,60,Business travel,Eco,896,4,5,5,5,3,5,4,4,4,4,4,2,4,3,2,23.0,satisfied +89533,102373,Male,Loyal Customer,31,Business travel,Business,1811,5,5,3,5,5,5,5,5,2,5,4,2,4,5,0,0.0,satisfied +89534,33436,Male,disloyal Customer,24,Business travel,Eco,1056,2,2,2,1,4,2,4,4,5,1,5,2,3,4,0,2.0,neutral or dissatisfied +89535,37497,Female,disloyal Customer,22,Business travel,Eco,1056,5,5,5,1,2,5,2,2,1,5,1,2,5,2,0,0.0,satisfied +89536,53379,Male,Loyal Customer,48,Personal Travel,Eco,1452,3,4,3,4,5,3,4,5,2,5,4,3,3,5,4,0.0,neutral or dissatisfied +89537,7774,Male,Loyal Customer,47,Business travel,Business,2535,3,2,2,2,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +89538,56753,Male,Loyal Customer,44,Business travel,Business,3786,4,4,4,4,3,4,5,4,4,4,4,4,4,3,58,34.0,satisfied +89539,92737,Female,Loyal Customer,36,Business travel,Business,1759,2,3,3,3,3,4,3,2,2,2,2,2,2,1,14,5.0,neutral or dissatisfied +89540,58209,Male,Loyal Customer,21,Personal Travel,Eco,925,2,2,3,2,5,3,5,5,2,3,3,2,2,5,0,0.0,neutral or dissatisfied +89541,72423,Female,Loyal Customer,59,Business travel,Business,1910,1,1,1,1,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +89542,83838,Male,Loyal Customer,45,Business travel,Business,448,1,5,5,5,1,1,1,4,5,3,4,1,4,1,389,420.0,neutral or dissatisfied +89543,99948,Male,Loyal Customer,39,Business travel,Business,486,3,4,4,4,3,3,3,3,3,3,3,1,3,2,0,15.0,neutral or dissatisfied +89544,5965,Female,disloyal Customer,26,Business travel,Business,691,2,0,2,3,4,2,4,4,5,5,5,3,5,4,0,8.0,neutral or dissatisfied +89545,5219,Female,Loyal Customer,33,Business travel,Business,190,1,4,4,4,5,4,4,2,2,2,1,2,2,2,0,0.0,neutral or dissatisfied +89546,116761,Female,Loyal Customer,34,Personal Travel,Eco Plus,342,3,4,3,3,2,3,2,2,1,4,3,2,4,2,3,0.0,neutral or dissatisfied +89547,9864,Male,Loyal Customer,53,Personal Travel,Eco,642,1,4,1,4,3,1,3,3,4,4,3,3,3,3,0,12.0,neutral or dissatisfied +89548,96141,Female,Loyal Customer,42,Business travel,Business,3962,3,3,3,3,3,5,5,5,5,5,5,4,5,3,38,39.0,satisfied +89549,3307,Female,disloyal Customer,22,Business travel,Business,240,5,4,5,3,4,5,4,4,5,3,4,3,4,4,6,11.0,satisfied +89550,96873,Male,Loyal Customer,28,Personal Travel,Eco,781,2,4,2,2,2,2,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +89551,73507,Male,Loyal Customer,53,Business travel,Business,3044,3,3,3,3,4,5,4,3,3,3,3,5,3,5,0,30.0,satisfied +89552,114547,Male,Loyal Customer,48,Personal Travel,Business,447,4,2,4,4,3,4,3,2,2,4,2,1,2,2,27,27.0,neutral or dissatisfied +89553,49472,Female,Loyal Customer,44,Business travel,Business,3175,0,4,0,5,1,2,2,1,1,1,1,1,1,1,34,29.0,satisfied +89554,103875,Female,Loyal Customer,21,Personal Travel,Eco,869,3,4,4,2,1,4,1,1,4,2,1,4,4,1,3,0.0,neutral or dissatisfied +89555,39033,Female,Loyal Customer,69,Personal Travel,Eco,406,4,4,4,3,3,4,4,2,2,4,2,5,2,5,101,98.0,satisfied +89556,97413,Female,disloyal Customer,36,Business travel,Business,570,3,3,3,2,3,3,4,3,3,4,4,3,4,3,50,44.0,neutral or dissatisfied +89557,9660,Male,Loyal Customer,55,Business travel,Business,277,0,0,0,4,5,5,5,1,1,1,1,4,1,3,0,0.0,satisfied +89558,11239,Male,Loyal Customer,26,Personal Travel,Eco,201,4,2,4,3,5,4,5,5,1,4,4,4,4,5,0,12.0,neutral or dissatisfied +89559,101515,Female,Loyal Customer,39,Business travel,Business,2753,2,2,2,2,3,2,2,5,5,5,5,2,5,3,0,0.0,satisfied +89560,87812,Male,Loyal Customer,53,Business travel,Business,214,4,4,4,4,3,5,4,5,5,5,4,5,5,3,0,0.0,satisfied +89561,51642,Female,Loyal Customer,60,Business travel,Eco,509,2,2,2,2,3,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +89562,20319,Female,Loyal Customer,57,Business travel,Business,287,0,0,0,4,4,4,5,5,5,5,5,5,5,5,0,1.0,satisfied +89563,54842,Female,Loyal Customer,52,Business travel,Business,3767,2,3,2,2,4,4,5,5,5,5,5,3,5,4,8,0.0,satisfied +89564,11116,Female,Loyal Customer,50,Personal Travel,Eco,458,3,4,3,1,2,1,1,1,1,3,4,3,1,4,32,33.0,neutral or dissatisfied +89565,22910,Female,disloyal Customer,30,Business travel,Business,667,3,4,4,4,4,1,1,2,3,3,3,1,1,1,338,334.0,neutral or dissatisfied +89566,100866,Female,Loyal Customer,52,Business travel,Business,1605,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +89567,61068,Female,Loyal Customer,53,Business travel,Business,1703,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +89568,91841,Male,Loyal Customer,63,Business travel,Business,1797,5,4,5,5,2,3,4,4,4,4,4,3,4,5,9,0.0,satisfied +89569,111516,Male,Loyal Customer,13,Personal Travel,Eco,391,3,5,3,4,4,3,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +89570,98039,Male,Loyal Customer,59,Business travel,Business,1797,1,1,4,1,3,4,4,4,4,4,4,4,4,3,19,35.0,satisfied +89571,46607,Female,disloyal Customer,24,Business travel,Eco,125,3,3,3,4,1,3,4,1,2,4,3,2,3,1,6,12.0,neutral or dissatisfied +89572,33773,Male,Loyal Customer,64,Personal Travel,Eco,1990,2,1,2,3,3,2,3,3,2,2,3,3,3,3,38,5.0,neutral or dissatisfied +89573,24396,Female,disloyal Customer,37,Business travel,Eco Plus,669,4,4,4,3,5,4,5,5,4,2,1,5,2,5,0,0.0,neutral or dissatisfied +89574,5505,Male,Loyal Customer,67,Personal Travel,Eco,948,3,2,3,3,1,3,1,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +89575,80157,Male,Loyal Customer,58,Business travel,Business,2475,2,1,1,1,2,2,2,3,5,4,4,2,1,2,8,19.0,neutral or dissatisfied +89576,71279,Male,Loyal Customer,14,Personal Travel,Eco,733,1,3,1,4,2,1,2,2,1,1,3,1,4,2,3,0.0,neutral or dissatisfied +89577,119089,Female,Loyal Customer,28,Business travel,Business,2028,1,1,4,1,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +89578,6849,Female,Loyal Customer,45,Personal Travel,Eco Plus,235,4,4,4,2,3,5,4,5,5,4,1,5,5,4,0,0.0,satisfied +89579,64914,Female,Loyal Customer,51,Business travel,Business,3107,3,5,5,5,2,3,3,3,3,3,3,2,3,1,5,0.0,neutral or dissatisfied +89580,68387,Female,Loyal Customer,54,Business travel,Business,1045,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +89581,83011,Female,Loyal Customer,26,Business travel,Business,1127,2,2,2,2,4,5,4,4,3,5,4,3,5,4,0,6.0,satisfied +89582,83377,Male,Loyal Customer,42,Personal Travel,Eco,1124,2,5,2,2,3,2,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +89583,631,Female,Loyal Customer,42,Business travel,Business,164,0,4,0,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +89584,86199,Female,Loyal Customer,44,Business travel,Business,3542,4,4,4,4,4,4,4,5,4,4,4,4,4,4,149,138.0,satisfied +89585,78448,Male,Loyal Customer,42,Business travel,Business,2065,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +89586,107444,Male,Loyal Customer,18,Personal Travel,Eco,725,4,5,4,3,5,4,3,5,2,2,5,5,2,5,101,92.0,neutral or dissatisfied +89587,30596,Male,disloyal Customer,36,Business travel,Business,472,2,2,2,1,2,2,2,2,5,1,5,5,1,2,20,21.0,neutral or dissatisfied +89588,6784,Male,Loyal Customer,56,Business travel,Business,1962,4,3,3,3,3,4,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +89589,107119,Female,Loyal Customer,51,Business travel,Business,3987,3,3,3,3,4,5,4,5,5,5,5,3,5,5,25,29.0,satisfied +89590,36978,Male,Loyal Customer,28,Business travel,Eco,759,4,5,5,5,4,4,4,4,4,5,5,5,1,4,2,0.0,satisfied +89591,108957,Male,Loyal Customer,25,Business travel,Business,667,1,1,5,1,4,4,4,4,5,4,5,3,4,4,0,0.0,satisfied +89592,68675,Male,Loyal Customer,61,Business travel,Business,175,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,1.0,satisfied +89593,70197,Female,disloyal Customer,25,Business travel,Eco,258,1,3,1,4,3,1,3,3,4,4,3,3,4,3,0,24.0,neutral or dissatisfied +89594,105960,Female,disloyal Customer,20,Business travel,Eco,2295,2,2,2,3,3,2,3,3,1,2,4,4,4,3,9,9.0,neutral or dissatisfied +89595,62640,Male,Loyal Customer,40,Personal Travel,Eco,1846,2,0,1,4,2,1,2,2,5,1,5,1,3,2,12,0.0,neutral or dissatisfied +89596,2765,Female,disloyal Customer,49,Business travel,Business,764,1,1,1,3,3,1,3,3,5,3,4,4,4,3,66,59.0,neutral or dissatisfied +89597,17186,Male,Loyal Customer,52,Personal Travel,Eco,643,4,2,4,2,4,4,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +89598,17124,Male,disloyal Customer,27,Business travel,Eco,1211,2,2,2,3,2,2,2,2,1,1,3,4,3,2,0,6.0,neutral or dissatisfied +89599,11027,Female,Loyal Customer,33,Business travel,Business,247,1,1,1,1,2,1,2,4,4,4,4,3,4,3,0,0.0,satisfied +89600,29061,Female,Loyal Customer,24,Personal Travel,Eco,978,3,4,3,2,1,3,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +89601,43984,Female,Loyal Customer,37,Business travel,Eco,397,5,2,2,2,5,5,5,5,2,4,1,4,4,5,5,14.0,satisfied +89602,14569,Female,disloyal Customer,26,Business travel,Eco,986,4,4,4,5,5,4,5,5,2,3,5,4,2,5,31,36.0,neutral or dissatisfied +89603,76512,Female,Loyal Customer,48,Business travel,Business,481,5,5,5,5,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +89604,33389,Female,Loyal Customer,20,Business travel,Business,2614,2,2,2,2,4,3,4,4,2,5,3,1,3,4,0,0.0,satisfied +89605,95367,Female,Loyal Customer,40,Personal Travel,Eco,677,3,4,2,2,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +89606,50637,Male,Loyal Customer,7,Personal Travel,Eco,262,1,2,1,3,2,1,2,2,2,4,4,3,4,2,122,118.0,neutral or dissatisfied +89607,4184,Male,Loyal Customer,47,Business travel,Business,2625,3,3,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +89608,78939,Male,Loyal Customer,15,Personal Travel,Eco,501,5,3,5,4,5,5,5,5,2,5,4,4,3,5,0,0.0,satisfied +89609,90311,Male,Loyal Customer,33,Business travel,Eco Plus,757,3,1,1,1,3,3,3,1,5,3,4,3,4,3,148,142.0,neutral or dissatisfied +89610,14609,Male,Loyal Customer,52,Business travel,Business,1636,3,1,3,3,2,2,4,4,4,4,4,4,4,4,0,0.0,satisfied +89611,87061,Male,Loyal Customer,29,Business travel,Business,3961,1,1,1,1,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +89612,46692,Female,Loyal Customer,22,Personal Travel,Eco,125,3,1,3,3,4,3,4,4,4,1,3,1,4,4,87,101.0,neutral or dissatisfied +89613,96653,Female,Loyal Customer,54,Personal Travel,Eco,937,2,4,2,3,4,4,4,2,2,2,2,5,2,5,0,6.0,neutral or dissatisfied +89614,32758,Female,Loyal Customer,62,Business travel,Eco,163,5,5,5,5,1,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +89615,24488,Female,Loyal Customer,35,Business travel,Business,3236,3,3,3,3,3,5,3,4,4,4,4,2,4,5,0,3.0,satisfied +89616,19700,Female,disloyal Customer,25,Business travel,Eco,409,2,4,2,2,1,2,1,1,2,3,4,1,5,1,108,98.0,neutral or dissatisfied +89617,41179,Male,Loyal Customer,15,Personal Travel,Eco Plus,468,4,5,4,4,5,4,5,5,3,2,4,5,4,5,2,7.0,neutral or dissatisfied +89618,69336,Female,Loyal Customer,44,Business travel,Business,3652,4,4,4,4,2,5,5,5,5,5,5,3,5,4,43,34.0,satisfied +89619,19340,Female,Loyal Customer,26,Personal Travel,Eco,694,2,4,2,5,2,2,2,2,3,3,5,3,4,2,42,22.0,neutral or dissatisfied +89620,17801,Male,disloyal Customer,24,Business travel,Business,1075,5,0,5,2,1,5,2,1,1,4,2,3,3,1,0,0.0,satisfied +89621,80759,Female,disloyal Customer,37,Business travel,Business,440,1,1,1,2,4,1,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +89622,57386,Female,disloyal Customer,20,Business travel,Eco,472,1,4,1,3,5,1,3,5,5,4,5,5,5,5,52,67.0,neutral or dissatisfied +89623,56437,Female,Loyal Customer,48,Business travel,Business,3774,1,1,1,1,4,4,2,4,4,4,4,3,4,1,15,1.0,satisfied +89624,65842,Female,disloyal Customer,22,Business travel,Eco,1389,3,3,3,4,3,3,3,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +89625,20196,Female,disloyal Customer,24,Business travel,Eco,349,5,3,5,3,3,5,3,3,2,5,4,3,3,3,0,0.0,satisfied +89626,114219,Male,Loyal Customer,41,Business travel,Eco,957,4,1,3,1,4,4,4,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +89627,80812,Male,Loyal Customer,41,Business travel,Business,2233,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,4.0,satisfied +89628,1573,Male,disloyal Customer,22,Business travel,Eco,140,4,0,4,4,4,4,3,4,4,4,4,3,4,4,0,9.0,satisfied +89629,93799,Male,Loyal Customer,48,Business travel,Eco,1259,4,2,2,2,4,4,4,4,3,1,4,2,3,4,0,0.0,neutral or dissatisfied +89630,91878,Female,Loyal Customer,55,Personal Travel,Business,2586,3,1,3,3,1,2,3,1,1,3,2,3,1,1,0,0.0,neutral or dissatisfied +89631,85601,Female,Loyal Customer,70,Business travel,Business,192,2,2,2,2,3,3,4,3,3,3,2,3,3,3,5,4.0,neutral or dissatisfied +89632,16665,Female,Loyal Customer,32,Personal Travel,Eco,488,4,1,4,2,5,4,5,5,1,4,1,3,3,5,0,0.0,neutral or dissatisfied +89633,26162,Male,disloyal Customer,25,Business travel,Eco,515,2,3,2,4,5,2,5,5,1,2,5,3,2,5,33,28.0,neutral or dissatisfied +89634,93500,Male,Loyal Customer,7,Personal Travel,Eco,1107,2,1,2,3,2,2,2,2,1,1,4,1,4,2,1,0.0,neutral or dissatisfied +89635,108909,Female,Loyal Customer,29,Business travel,Eco,1066,3,3,3,3,2,3,3,4,3,3,4,3,4,3,209,210.0,neutral or dissatisfied +89636,20201,Male,Loyal Customer,40,Business travel,Business,346,0,0,0,2,5,4,4,5,5,5,5,5,5,3,21,33.0,satisfied +89637,103218,Male,Loyal Customer,54,Business travel,Business,3960,4,4,1,4,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +89638,125977,Female,Loyal Customer,23,Business travel,Business,650,4,4,4,4,4,4,4,4,1,1,3,1,2,4,0,8.0,neutral or dissatisfied +89639,33576,Female,disloyal Customer,25,Business travel,Eco,399,1,5,1,5,3,1,3,3,2,1,3,2,5,3,13,4.0,neutral or dissatisfied +89640,31835,Female,Loyal Customer,46,Personal Travel,Eco,2762,2,4,2,4,2,4,4,2,1,4,4,4,3,4,6,0.0,neutral or dissatisfied +89641,61944,Female,Loyal Customer,42,Business travel,Eco,2161,4,1,4,1,2,2,2,4,4,4,4,1,4,3,40,33.0,neutral or dissatisfied +89642,104093,Male,Loyal Customer,66,Personal Travel,Eco,588,1,5,1,4,3,1,3,3,4,2,5,4,4,3,8,9.0,neutral or dissatisfied +89643,19504,Female,Loyal Customer,33,Business travel,Business,508,2,2,2,2,2,2,2,1,3,3,4,2,3,2,142,138.0,neutral or dissatisfied +89644,58133,Female,Loyal Customer,64,Personal Travel,Eco Plus,589,3,4,3,2,2,5,4,3,3,3,2,3,3,5,37,26.0,neutral or dissatisfied +89645,5752,Female,Loyal Customer,48,Business travel,Business,2569,1,2,2,2,1,4,4,1,1,1,1,1,1,4,4,0.0,neutral or dissatisfied +89646,58545,Male,Loyal Customer,29,Business travel,Business,1514,2,2,2,2,4,4,4,4,5,5,4,5,4,4,9,24.0,satisfied +89647,78507,Male,Loyal Customer,41,Business travel,Eco,266,4,1,1,1,4,4,4,4,5,1,1,5,5,4,0,0.0,satisfied +89648,51213,Female,Loyal Customer,62,Business travel,Eco Plus,89,5,4,4,4,1,3,1,5,5,5,5,5,5,3,0,0.0,satisfied +89649,47051,Male,disloyal Customer,11,Business travel,Eco,639,1,2,0,4,1,0,1,1,4,2,4,2,4,1,3,0.0,neutral or dissatisfied +89650,92030,Female,disloyal Customer,30,Business travel,Business,1522,3,3,3,4,5,3,5,5,5,3,4,3,4,5,0,6.0,neutral or dissatisfied +89651,70784,Male,disloyal Customer,33,Business travel,Business,328,3,3,3,5,4,3,4,4,3,3,5,5,4,4,0,0.0,neutral or dissatisfied +89652,36711,Male,disloyal Customer,25,Business travel,Business,1121,0,0,0,4,4,0,4,4,4,3,5,4,5,4,0,0.0,satisfied +89653,78986,Male,disloyal Customer,25,Business travel,Business,377,3,4,3,5,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +89654,70733,Female,Loyal Customer,53,Personal Travel,Eco,675,5,5,5,3,2,4,5,3,3,5,3,3,3,3,0,0.0,satisfied +89655,98572,Male,Loyal Customer,56,Business travel,Business,2407,5,5,4,5,2,2,2,5,5,4,4,2,3,2,357,362.0,satisfied +89656,123069,Male,disloyal Customer,22,Business travel,Eco,468,4,0,4,1,5,4,5,5,5,5,4,3,5,5,6,0.0,neutral or dissatisfied +89657,74033,Female,Loyal Customer,55,Personal Travel,Eco,1471,2,2,2,4,1,3,3,3,3,2,2,2,3,1,0,3.0,neutral or dissatisfied +89658,73347,Male,disloyal Customer,27,Business travel,Eco,1197,1,1,1,4,2,1,2,2,4,5,4,3,3,2,10,0.0,neutral or dissatisfied +89659,45442,Male,Loyal Customer,56,Business travel,Eco Plus,649,5,1,1,1,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +89660,117872,Male,Loyal Customer,53,Business travel,Business,255,4,4,3,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +89661,56309,Female,Loyal Customer,40,Business travel,Business,3898,2,2,2,2,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +89662,115174,Male,Loyal Customer,47,Business travel,Business,447,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +89663,93037,Female,disloyal Customer,25,Business travel,Business,317,4,0,4,4,4,4,2,4,4,2,4,4,5,4,121,110.0,satisfied +89664,39850,Female,Loyal Customer,45,Business travel,Business,2442,0,0,0,4,4,5,1,4,4,4,4,2,4,4,0,4.0,satisfied +89665,94532,Male,Loyal Customer,28,Business travel,Eco,528,1,5,1,5,1,1,1,1,4,5,4,1,3,1,0,0.0,neutral or dissatisfied +89666,96756,Female,Loyal Customer,58,Business travel,Business,3406,3,5,5,5,3,4,3,3,3,3,3,1,3,1,12,5.0,neutral or dissatisfied +89667,90337,Male,Loyal Customer,49,Business travel,Business,271,5,4,5,5,4,5,4,4,4,4,4,4,4,3,0,4.0,satisfied +89668,42564,Female,Loyal Customer,46,Business travel,Business,2286,1,1,1,1,1,4,5,5,5,5,4,4,5,2,0,0.0,satisfied +89669,52544,Male,Loyal Customer,46,Business travel,Business,119,5,5,4,5,4,2,5,5,5,4,5,4,5,2,0,0.0,satisfied +89670,50628,Female,Loyal Customer,26,Personal Travel,Eco,89,3,4,3,5,2,3,3,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +89671,6152,Male,Loyal Customer,77,Business travel,Business,409,3,5,5,5,3,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +89672,30308,Female,Loyal Customer,15,Personal Travel,Eco,1476,4,4,4,5,1,4,1,1,3,2,5,5,4,1,37,17.0,satisfied +89673,60902,Female,Loyal Customer,46,Business travel,Business,3993,2,3,2,2,2,4,4,5,5,5,5,3,5,4,0,25.0,satisfied +89674,20651,Female,Loyal Customer,28,Business travel,Business,3437,4,4,4,4,4,4,4,4,3,5,3,2,5,4,0,0.0,satisfied +89675,61557,Female,Loyal Customer,13,Business travel,Eco Plus,2442,1,1,1,1,1,1,3,1,3,4,4,4,4,1,47,42.0,neutral or dissatisfied +89676,101714,Female,Loyal Customer,46,Business travel,Business,986,5,5,3,5,5,5,5,3,3,3,3,4,3,3,41,9.0,satisfied +89677,62423,Female,Loyal Customer,50,Business travel,Business,1911,3,3,3,3,4,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +89678,15801,Male,Loyal Customer,70,Personal Travel,Eco,282,2,3,2,3,2,2,2,2,3,2,4,1,3,2,45,100.0,neutral or dissatisfied +89679,48239,Female,Loyal Customer,19,Personal Travel,Eco,236,3,5,3,2,4,3,5,4,2,4,1,3,1,4,0,0.0,neutral or dissatisfied +89680,93260,Male,Loyal Customer,26,Personal Travel,Business,564,3,2,3,3,3,3,3,3,1,4,4,4,4,3,10,8.0,neutral or dissatisfied +89681,54463,Male,Loyal Customer,27,Business travel,Business,3097,3,3,3,3,5,5,5,5,4,3,5,4,5,5,0,0.0,satisfied +89682,92929,Female,Loyal Customer,16,Business travel,Business,3234,3,1,3,1,4,4,3,4,3,4,3,2,3,4,1,0.0,neutral or dissatisfied +89683,99868,Female,Loyal Customer,43,Business travel,Business,2929,5,5,4,5,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +89684,42889,Female,Loyal Customer,39,Business travel,Business,1736,1,1,1,1,1,2,2,4,4,5,5,4,4,1,0,0.0,satisfied +89685,29785,Female,Loyal Customer,49,Business travel,Eco,399,5,3,3,3,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +89686,76555,Male,disloyal Customer,37,Business travel,Business,481,4,4,4,3,3,4,3,3,4,3,5,4,5,3,0,0.0,satisfied +89687,40824,Male,Loyal Customer,22,Business travel,Business,3605,4,5,5,5,4,3,4,4,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +89688,97859,Male,Loyal Customer,38,Personal Travel,Business,722,2,3,2,3,3,1,4,5,5,2,4,5,5,3,1,16.0,neutral or dissatisfied +89689,118442,Female,Loyal Customer,36,Business travel,Business,3843,4,4,4,4,5,4,5,4,4,4,4,3,4,5,37,34.0,satisfied +89690,49855,Male,Loyal Customer,50,Business travel,Business,109,2,2,2,2,3,5,2,4,4,4,5,4,4,2,0,0.0,satisfied +89691,67371,Female,Loyal Customer,42,Business travel,Business,641,4,4,4,4,2,4,4,5,5,5,5,3,5,3,0,2.0,satisfied +89692,103360,Female,Loyal Customer,34,Business travel,Business,1938,3,5,5,5,3,3,3,4,2,3,3,3,4,3,176,167.0,neutral or dissatisfied +89693,109869,Female,Loyal Customer,24,Business travel,Eco,1034,3,2,2,2,3,3,4,3,3,4,4,4,4,3,37,34.0,neutral or dissatisfied +89694,31868,Male,Loyal Customer,36,Business travel,Business,2603,1,3,3,3,1,1,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +89695,112793,Female,Loyal Customer,26,Business travel,Business,1476,4,4,4,4,4,4,4,4,4,5,5,4,4,4,176,159.0,satisfied +89696,7466,Male,Loyal Customer,57,Business travel,Business,2938,4,4,5,4,4,4,5,2,2,2,2,4,2,4,9,13.0,satisfied +89697,88882,Male,disloyal Customer,25,Business travel,Business,859,1,4,1,1,5,1,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +89698,43699,Male,Loyal Customer,25,Business travel,Business,3040,4,4,4,4,4,4,4,4,3,4,3,1,3,4,0,0.0,satisfied +89699,51917,Male,Loyal Customer,69,Personal Travel,Eco,601,4,5,4,2,3,4,3,3,2,2,5,2,5,3,0,1.0,neutral or dissatisfied +89700,55005,Male,disloyal Customer,20,Business travel,Eco,984,3,3,3,4,2,3,2,2,4,2,4,3,3,2,1,0.0,neutral or dissatisfied +89701,124442,Female,disloyal Customer,25,Business travel,Eco Plus,1044,3,4,3,3,5,3,4,5,4,5,3,4,3,5,0,0.0,neutral or dissatisfied +89702,69311,Female,Loyal Customer,57,Personal Travel,Business,1096,4,2,4,3,4,4,3,4,4,4,4,4,4,2,0,0.0,satisfied +89703,86338,Female,Loyal Customer,31,Business travel,Business,1669,1,1,1,1,4,5,4,4,3,2,5,3,4,4,2,14.0,satisfied +89704,48240,Female,Loyal Customer,42,Personal Travel,Eco,236,2,3,2,3,2,3,2,3,3,2,3,4,3,5,20,16.0,neutral or dissatisfied +89705,115357,Male,Loyal Customer,55,Business travel,Eco,308,3,1,1,1,3,3,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +89706,29826,Female,Loyal Customer,60,Business travel,Eco,539,3,4,2,4,3,3,3,2,5,4,3,3,3,3,228,230.0,satisfied +89707,105080,Male,disloyal Customer,39,Business travel,Business,220,3,3,3,5,1,3,1,1,4,3,4,5,5,1,11,9.0,neutral or dissatisfied +89708,120601,Female,Loyal Customer,12,Personal Travel,Eco,980,1,2,0,4,3,0,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +89709,40565,Female,disloyal Customer,23,Business travel,Eco,216,4,3,4,3,3,4,3,3,2,1,3,3,2,3,0,0.0,neutral or dissatisfied +89710,104381,Female,Loyal Customer,65,Personal Travel,Eco,228,3,5,3,1,3,5,4,2,2,3,2,4,2,5,125,120.0,neutral or dissatisfied +89711,108486,Female,Loyal Customer,60,Business travel,Business,570,5,2,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +89712,101227,Male,Loyal Customer,47,Business travel,Business,1562,3,3,3,3,3,4,5,5,5,5,5,5,5,3,2,0.0,satisfied +89713,83685,Female,disloyal Customer,72,Business travel,Eco,177,1,1,0,3,0,3,3,3,3,4,4,3,3,3,350,399.0,neutral or dissatisfied +89714,51808,Male,Loyal Customer,69,Personal Travel,Eco,651,2,2,3,3,3,3,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +89715,37006,Female,Loyal Customer,28,Personal Travel,Eco,805,1,3,1,3,3,1,3,3,1,5,4,2,5,3,17,8.0,neutral or dissatisfied +89716,113940,Female,Loyal Customer,33,Business travel,Business,1728,3,3,3,3,2,4,4,4,4,4,4,5,4,3,4,0.0,satisfied +89717,85841,Male,Loyal Customer,33,Personal Travel,Eco,526,3,5,3,3,3,3,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +89718,34402,Female,Loyal Customer,31,Business travel,Business,3469,1,1,1,1,4,4,4,4,5,5,4,5,3,4,27,30.0,satisfied +89719,3464,Male,Loyal Customer,40,Personal Travel,Eco Plus,296,4,4,4,4,3,4,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +89720,1123,Female,Loyal Customer,42,Personal Travel,Eco,164,3,5,3,2,5,5,5,4,4,3,1,4,4,5,0,0.0,neutral or dissatisfied +89721,83766,Female,disloyal Customer,38,Business travel,Business,926,4,4,4,2,1,4,1,1,4,4,4,5,4,1,0,0.0,satisfied +89722,51993,Female,disloyal Customer,23,Business travel,Eco,1119,4,4,4,3,4,4,4,4,3,4,2,5,2,4,0,2.0,neutral or dissatisfied +89723,102560,Female,Loyal Customer,39,Business travel,Business,3262,5,5,5,5,5,5,4,5,5,4,5,5,5,4,12,11.0,satisfied +89724,88628,Male,Loyal Customer,43,Personal Travel,Eco,581,3,5,3,2,3,3,3,3,5,3,5,3,4,3,9,20.0,neutral or dissatisfied +89725,24392,Female,Loyal Customer,11,Personal Travel,Eco,669,1,5,1,1,3,1,5,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +89726,81590,Female,Loyal Customer,62,Personal Travel,Business,334,2,2,2,3,4,3,3,4,4,2,5,2,4,3,0,1.0,neutral or dissatisfied +89727,122331,Female,Loyal Customer,25,Personal Travel,Eco Plus,541,1,5,3,3,3,3,5,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +89728,103659,Male,Loyal Customer,55,Business travel,Business,1724,2,2,3,2,5,4,5,5,5,5,5,4,5,4,3,0.0,satisfied +89729,107305,Male,Loyal Customer,68,Personal Travel,Eco,307,2,5,2,2,4,2,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +89730,26557,Female,Loyal Customer,47,Business travel,Business,1528,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +89731,5463,Female,Loyal Customer,15,Personal Travel,Eco,265,5,5,5,1,3,5,3,3,5,5,4,3,4,3,0,0.0,satisfied +89732,107891,Female,disloyal Customer,57,Business travel,Business,861,4,4,4,5,4,4,4,4,4,4,4,4,5,4,15,0.0,satisfied +89733,3013,Female,Loyal Customer,47,Business travel,Business,3597,2,2,2,2,5,5,5,5,5,5,5,4,5,3,9,0.0,satisfied +89734,56729,Male,Loyal Customer,55,Personal Travel,Eco,1085,3,5,3,5,5,3,5,5,5,4,5,4,4,5,0,12.0,neutral or dissatisfied +89735,82462,Female,Loyal Customer,68,Personal Travel,Eco,502,1,5,1,5,3,4,5,1,1,1,1,4,1,4,38,57.0,neutral or dissatisfied +89736,113772,Male,Loyal Customer,54,Personal Travel,Eco,397,2,5,2,2,4,2,4,4,3,5,5,3,5,4,23,10.0,neutral or dissatisfied +89737,117604,Male,Loyal Customer,66,Business travel,Business,843,1,4,4,4,2,3,4,1,1,1,1,1,1,2,0,4.0,neutral or dissatisfied +89738,28602,Female,Loyal Customer,57,Personal Travel,Business,2676,4,2,4,4,3,3,4,2,2,4,2,1,2,3,0,0.0,neutral or dissatisfied +89739,29588,Male,Loyal Customer,30,Business travel,Business,3375,4,4,4,4,5,5,5,5,3,1,2,2,3,5,101,97.0,satisfied +89740,2612,Male,Loyal Customer,47,Personal Travel,Eco,227,3,3,3,3,4,3,4,4,3,5,2,1,2,4,17,29.0,neutral or dissatisfied +89741,59310,Female,Loyal Customer,31,Business travel,Eco,2556,2,1,1,1,2,2,2,2,2,3,1,3,2,2,4,0.0,neutral or dissatisfied +89742,35227,Female,Loyal Customer,35,Business travel,Business,2458,4,4,5,4,4,2,1,4,4,4,4,3,4,4,0,0.0,satisfied +89743,20929,Male,Loyal Customer,52,Business travel,Eco,803,3,5,5,5,3,3,3,3,3,2,1,3,5,3,0,0.0,satisfied +89744,37885,Male,Loyal Customer,34,Business travel,Business,3103,1,1,1,1,5,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +89745,92592,Male,Loyal Customer,10,Business travel,Eco,2218,4,4,4,4,4,4,2,4,2,4,3,3,3,4,0,0.0,neutral or dissatisfied +89746,68209,Male,Loyal Customer,51,Business travel,Business,2644,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,4.0,satisfied +89747,16026,Female,Loyal Customer,47,Personal Travel,Eco,794,3,3,2,4,1,3,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +89748,30336,Female,Loyal Customer,24,Business travel,Eco,391,2,3,3,3,2,2,4,2,1,3,4,4,3,2,15,44.0,neutral or dissatisfied +89749,95832,Male,disloyal Customer,22,Business travel,Business,580,0,0,0,2,5,0,5,5,5,5,4,5,5,5,0,4.0,satisfied +89750,66207,Male,Loyal Customer,45,Business travel,Business,460,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +89751,24820,Male,Loyal Customer,24,Business travel,Business,2678,2,2,2,2,4,4,4,4,5,2,5,1,5,4,5,17.0,satisfied +89752,70742,Female,Loyal Customer,15,Personal Travel,Eco,675,0,4,0,1,1,0,1,1,4,4,5,5,5,1,0,0.0,satisfied +89753,81833,Male,Loyal Customer,45,Personal Travel,Eco,1306,2,5,2,1,1,2,1,1,3,5,3,5,5,1,0,0.0,neutral or dissatisfied +89754,109393,Male,Loyal Customer,49,Personal Travel,Eco,1189,3,4,3,1,2,3,2,2,5,5,5,3,4,2,12,1.0,neutral or dissatisfied +89755,40217,Male,Loyal Customer,31,Business travel,Business,3916,3,3,4,3,3,4,3,3,2,1,1,4,2,3,0,2.0,satisfied +89756,52160,Female,Loyal Customer,37,Business travel,Eco,370,3,1,1,1,3,5,3,3,4,2,5,1,4,3,13,11.0,satisfied +89757,81518,Female,Loyal Customer,45,Business travel,Business,1124,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +89758,63588,Female,disloyal Customer,22,Business travel,Eco,2133,5,5,5,3,2,5,2,2,5,2,5,5,5,2,0,0.0,satisfied +89759,44040,Female,Loyal Customer,43,Business travel,Eco,67,5,1,4,1,3,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +89760,118213,Female,Loyal Customer,44,Personal Travel,Eco Plus,1444,2,3,2,3,1,3,2,1,1,2,1,2,1,1,11,3.0,neutral or dissatisfied +89761,34321,Female,Loyal Customer,45,Business travel,Business,2454,2,2,5,2,4,5,2,4,4,4,4,2,4,5,9,0.0,satisfied +89762,81440,Male,Loyal Customer,46,Business travel,Business,393,2,2,2,2,5,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +89763,107247,Female,disloyal Customer,44,Business travel,Business,307,2,2,2,4,4,2,1,4,3,2,5,5,5,4,0,3.0,neutral or dissatisfied +89764,81812,Male,Loyal Customer,48,Business travel,Business,1487,3,5,3,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +89765,8489,Male,Loyal Customer,31,Business travel,Business,677,1,1,1,1,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +89766,31583,Female,Loyal Customer,41,Business travel,Business,602,2,2,2,2,1,5,2,5,5,5,5,5,5,4,7,14.0,satisfied +89767,40396,Female,Loyal Customer,45,Business travel,Business,3621,0,4,0,2,4,5,5,3,3,3,2,4,3,5,0,0.0,satisfied +89768,108646,Female,disloyal Customer,38,Business travel,Business,762,1,1,1,1,2,1,1,2,4,2,5,5,4,2,8,0.0,neutral or dissatisfied +89769,48914,Female,Loyal Customer,41,Business travel,Business,3975,0,0,0,2,4,1,2,2,2,2,2,4,2,2,0,0.0,satisfied +89770,42275,Male,Loyal Customer,35,Business travel,Business,3873,5,5,5,5,5,5,1,4,4,5,4,4,4,1,0,0.0,satisfied +89771,17075,Female,Loyal Customer,49,Business travel,Business,2829,2,3,3,3,2,2,2,1,1,3,3,2,2,2,145,136.0,neutral or dissatisfied +89772,34282,Female,Loyal Customer,37,Business travel,Business,280,1,3,3,3,3,4,4,1,1,1,1,3,1,2,76,56.0,neutral or dissatisfied +89773,78351,Female,Loyal Customer,8,Personal Travel,Eco,1547,3,4,3,2,5,3,5,5,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +89774,12923,Female,Loyal Customer,65,Business travel,Eco,456,2,3,3,3,5,2,2,2,2,2,2,1,2,3,22,20.0,neutral or dissatisfied +89775,36265,Female,disloyal Customer,22,Business travel,Eco,728,5,5,5,2,2,5,1,2,3,5,3,2,4,2,0,0.0,satisfied +89776,104113,Female,Loyal Customer,35,Business travel,Business,2834,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,6.0,satisfied +89777,113908,Female,Loyal Customer,7,Personal Travel,Eco,2295,4,5,4,1,5,4,5,5,1,1,4,3,2,5,5,11.0,neutral or dissatisfied +89778,42861,Male,Loyal Customer,27,Business travel,Eco Plus,328,0,0,0,3,3,0,3,3,5,5,2,2,4,3,0,0.0,satisfied +89779,129851,Male,Loyal Customer,22,Personal Travel,Eco,308,2,1,2,4,3,2,2,3,4,3,3,2,3,3,0,0.0,neutral or dissatisfied +89780,109512,Male,Loyal Customer,51,Business travel,Business,1517,1,4,3,4,1,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +89781,35877,Female,Loyal Customer,30,Personal Travel,Eco,1065,0,5,1,4,1,1,1,1,3,2,5,5,4,1,61,52.0,satisfied +89782,49026,Male,Loyal Customer,43,Business travel,Business,109,2,2,4,2,2,4,2,4,4,4,4,4,4,5,0,0.0,satisfied +89783,83020,Female,Loyal Customer,59,Business travel,Eco,1127,1,4,4,4,2,3,3,1,1,1,1,2,1,1,3,39.0,neutral or dissatisfied +89784,102490,Female,Loyal Customer,38,Personal Travel,Eco,197,2,5,2,1,2,2,2,2,5,3,4,3,4,2,12,18.0,neutral or dissatisfied +89785,42918,Female,disloyal Customer,18,Business travel,Eco,422,3,3,3,3,2,3,2,2,3,3,2,3,1,2,0,0.0,neutral or dissatisfied +89786,84940,Male,Loyal Customer,27,Personal Travel,Eco,547,2,1,2,4,4,2,4,4,2,3,3,3,4,4,0,6.0,neutral or dissatisfied +89787,42237,Male,Loyal Customer,29,Business travel,Business,3756,3,3,3,3,3,5,3,3,2,4,5,4,1,3,9,3.0,satisfied +89788,121686,Female,Loyal Customer,64,Personal Travel,Eco,328,2,3,2,3,4,2,3,4,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +89789,85755,Female,disloyal Customer,44,Business travel,Business,666,4,4,4,4,4,4,4,4,5,3,4,3,4,4,12,1.0,satisfied +89790,115632,Female,Loyal Customer,45,Business travel,Business,296,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +89791,114364,Female,Loyal Customer,59,Business travel,Eco Plus,967,3,1,5,1,4,4,4,3,3,3,3,4,3,1,27,10.0,neutral or dissatisfied +89792,8665,Male,Loyal Customer,39,Business travel,Business,227,2,2,3,2,5,5,4,5,5,5,5,4,5,5,2,3.0,satisfied +89793,102968,Male,disloyal Customer,27,Business travel,Business,546,1,1,1,3,5,1,5,5,1,2,4,2,3,5,0,7.0,neutral or dissatisfied +89794,89407,Female,Loyal Customer,36,Business travel,Business,2208,0,5,0,4,2,4,4,4,4,4,4,5,4,3,7,3.0,satisfied +89795,98237,Female,Loyal Customer,41,Business travel,Business,1072,4,4,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +89796,57940,Male,Loyal Customer,59,Business travel,Business,837,5,5,5,5,3,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +89797,80629,Male,Loyal Customer,53,Business travel,Business,282,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +89798,89452,Female,Loyal Customer,41,Personal Travel,Eco,134,1,0,1,4,1,1,2,1,1,1,5,5,2,1,0,10.0,neutral or dissatisfied +89799,27409,Female,Loyal Customer,40,Business travel,Eco,679,2,3,3,3,2,2,2,2,3,4,3,1,4,2,22,39.0,neutral or dissatisfied +89800,117121,Female,disloyal Customer,36,Business travel,Eco,304,1,0,1,4,1,1,1,1,3,3,2,5,4,1,0,0.0,neutral or dissatisfied +89801,56431,Female,Loyal Customer,44,Business travel,Business,2550,4,4,4,4,3,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +89802,44330,Male,Loyal Customer,9,Personal Travel,Eco,828,3,5,3,3,5,3,4,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +89803,126811,Male,Loyal Customer,59,Business travel,Business,2125,2,2,2,2,3,4,4,4,4,4,4,4,4,5,117,117.0,satisfied +89804,122800,Female,disloyal Customer,24,Business travel,Eco,599,2,0,2,3,4,2,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +89805,34279,Male,disloyal Customer,26,Business travel,Eco,496,2,2,2,4,5,2,1,5,4,1,3,1,4,5,0,0.0,neutral or dissatisfied +89806,88432,Male,Loyal Customer,33,Business travel,Business,3537,1,5,4,5,1,1,1,1,1,1,4,2,3,1,69,67.0,neutral or dissatisfied +89807,17241,Male,Loyal Customer,54,Business travel,Business,2888,4,3,3,3,2,3,4,4,4,4,4,3,4,4,40,27.0,neutral or dissatisfied +89808,18563,Male,Loyal Customer,33,Business travel,Business,1802,2,2,2,2,4,4,3,4,3,2,5,3,4,4,0,0.0,satisfied +89809,112515,Male,Loyal Customer,36,Personal Travel,Eco,819,4,4,4,4,5,4,5,5,3,1,4,1,3,5,0,0.0,neutral or dissatisfied +89810,64498,Male,Loyal Customer,59,Business travel,Business,469,3,3,5,3,3,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +89811,93350,Female,Loyal Customer,35,Business travel,Business,836,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +89812,9630,Male,Loyal Customer,47,Business travel,Eco Plus,228,2,5,5,5,2,2,2,2,2,4,4,4,3,2,49,41.0,neutral or dissatisfied +89813,24047,Female,Loyal Customer,13,Personal Travel,Eco,595,3,4,3,5,4,3,4,4,3,1,2,3,2,4,0,0.0,neutral or dissatisfied +89814,93875,Male,Loyal Customer,51,Business travel,Business,2652,2,2,2,2,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +89815,34368,Male,Loyal Customer,61,Personal Travel,Eco,541,3,5,3,4,5,3,1,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +89816,8910,Female,Loyal Customer,51,Personal Travel,Eco,510,3,4,3,4,4,4,5,2,2,3,2,4,2,5,8,29.0,neutral or dissatisfied +89817,87005,Female,Loyal Customer,60,Personal Travel,Eco,907,1,4,2,4,5,4,5,3,3,2,3,4,3,4,13,1.0,neutral or dissatisfied +89818,62017,Female,Loyal Customer,20,Business travel,Business,2586,3,3,3,3,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +89819,81497,Female,Loyal Customer,33,Personal Travel,Eco,528,2,5,2,3,4,2,4,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +89820,4738,Female,Loyal Customer,50,Business travel,Business,888,4,4,4,4,5,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +89821,76317,Male,disloyal Customer,35,Business travel,Eco,2182,3,2,2,2,4,3,4,4,2,4,4,2,2,4,2,0.0,neutral or dissatisfied +89822,15908,Male,Loyal Customer,54,Business travel,Business,566,3,3,5,3,4,4,1,5,5,4,5,2,5,5,65,69.0,satisfied +89823,61148,Female,Loyal Customer,39,Business travel,Business,1544,4,4,4,4,3,5,4,4,4,4,4,5,4,3,7,5.0,satisfied +89824,46009,Male,Loyal Customer,29,Business travel,Eco Plus,483,4,2,2,2,4,4,4,4,3,2,2,2,2,4,16,4.0,satisfied +89825,90124,Male,Loyal Customer,58,Business travel,Business,3833,1,1,1,1,5,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +89826,88177,Female,Loyal Customer,31,Business travel,Business,515,5,5,3,5,3,3,3,3,3,3,5,5,5,3,13,5.0,satisfied +89827,38933,Male,Loyal Customer,57,Personal Travel,Eco,298,2,5,2,3,1,2,1,1,4,2,5,3,4,1,0,8.0,neutral or dissatisfied +89828,86814,Female,Loyal Customer,24,Business travel,Business,484,5,5,5,5,5,4,5,5,4,5,4,4,3,5,1,0.0,neutral or dissatisfied +89829,104890,Female,Loyal Customer,41,Personal Travel,Eco Plus,327,3,0,3,5,4,4,4,4,4,3,4,4,4,3,15,6.0,neutral or dissatisfied +89830,124421,Female,Loyal Customer,23,Business travel,Business,3397,3,3,2,3,5,4,5,5,3,4,5,3,4,5,0,0.0,satisfied +89831,88004,Male,Loyal Customer,49,Business travel,Business,3599,4,4,4,4,4,5,5,5,5,5,5,5,5,3,17,23.0,satisfied +89832,121616,Male,Loyal Customer,55,Personal Travel,Eco,912,3,4,3,4,2,3,2,2,1,4,3,4,4,2,20,7.0,neutral or dissatisfied +89833,118978,Male,Loyal Customer,22,Business travel,Eco Plus,570,2,5,4,5,2,2,3,2,1,1,3,1,3,2,26,24.0,neutral or dissatisfied +89834,29026,Male,Loyal Customer,58,Business travel,Eco,697,4,1,1,1,4,4,4,4,2,4,3,2,2,4,3,0.0,satisfied +89835,8956,Male,disloyal Customer,30,Business travel,Business,812,1,1,1,5,5,1,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +89836,7167,Male,Loyal Customer,46,Business travel,Business,2264,2,4,5,5,4,4,4,3,3,3,2,3,3,2,0,13.0,neutral or dissatisfied +89837,119553,Male,Loyal Customer,68,Personal Travel,Eco,759,1,4,1,2,4,1,4,4,5,5,5,3,4,4,3,10.0,neutral or dissatisfied +89838,73871,Female,Loyal Customer,58,Business travel,Business,3581,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +89839,90986,Female,disloyal Customer,21,Business travel,Eco,271,3,3,3,3,2,3,2,2,4,1,3,3,4,2,0,20.0,neutral or dissatisfied +89840,76131,Male,Loyal Customer,49,Business travel,Business,689,3,3,3,3,4,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +89841,10739,Male,Loyal Customer,45,Business travel,Business,2039,2,2,2,2,3,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +89842,64163,Female,Loyal Customer,10,Personal Travel,Eco,989,2,4,2,3,5,2,5,5,3,1,3,5,5,5,0,0.0,neutral or dissatisfied +89843,64187,Male,Loyal Customer,19,Personal Travel,Eco,1047,1,5,1,4,3,1,3,3,3,3,4,3,5,3,17,28.0,neutral or dissatisfied +89844,46232,Female,Loyal Customer,31,Business travel,Business,594,1,1,1,1,5,5,5,5,4,3,4,2,2,5,7,8.0,satisfied +89845,118120,Female,Loyal Customer,43,Personal Travel,Eco,1300,4,4,4,1,5,4,5,4,4,4,4,5,4,3,8,4.0,neutral or dissatisfied +89846,87586,Male,Loyal Customer,61,Personal Travel,Eco,432,1,1,1,3,5,1,5,5,1,1,3,3,4,5,45,40.0,neutral or dissatisfied +89847,33845,Male,Loyal Customer,49,Business travel,Business,1562,3,2,2,2,3,3,3,3,3,3,3,3,3,2,13,5.0,neutral or dissatisfied +89848,21821,Male,Loyal Customer,60,Business travel,Eco Plus,241,1,4,4,4,1,1,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +89849,64759,Male,Loyal Customer,37,Business travel,Business,282,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +89850,2734,Female,disloyal Customer,26,Business travel,Business,772,2,3,3,5,4,3,2,4,5,4,4,3,4,4,0,6.0,neutral or dissatisfied +89851,74314,Female,Loyal Customer,60,Business travel,Business,1126,3,3,3,3,2,4,4,4,4,5,4,4,4,5,0,10.0,satisfied +89852,125462,Female,disloyal Customer,28,Business travel,Eco,2845,3,3,3,2,4,3,2,4,1,5,2,1,2,4,0,0.0,neutral or dissatisfied +89853,15482,Male,Loyal Customer,63,Personal Travel,Eco,377,5,4,5,4,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +89854,91366,Female,Loyal Customer,17,Personal Travel,Eco Plus,240,2,4,2,3,5,2,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +89855,125035,Female,Loyal Customer,51,Business travel,Business,2300,2,2,2,2,5,5,5,4,4,5,5,5,3,5,0,0.0,satisfied +89856,16661,Female,disloyal Customer,36,Business travel,Eco,488,1,4,1,3,1,1,1,1,2,2,3,2,3,1,21,22.0,neutral or dissatisfied +89857,94528,Female,Loyal Customer,45,Business travel,Business,3440,4,3,4,4,5,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +89858,38715,Male,Loyal Customer,42,Personal Travel,Eco,2342,1,4,2,2,5,2,1,5,3,2,5,5,2,5,1,0.0,neutral or dissatisfied +89859,55410,Male,Loyal Customer,21,Personal Travel,Eco,1290,4,5,4,5,3,4,3,3,3,3,5,4,5,3,10,0.0,neutral or dissatisfied +89860,124154,Male,Loyal Customer,47,Business travel,Business,2133,3,3,3,3,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +89861,33095,Female,Loyal Customer,32,Personal Travel,Eco,163,3,5,0,2,2,0,4,2,2,5,2,3,4,2,0,0.0,neutral or dissatisfied +89862,19433,Female,Loyal Customer,36,Personal Travel,Eco,645,5,4,5,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +89863,14698,Male,Loyal Customer,78,Business travel,Eco,317,3,4,5,5,3,3,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +89864,26120,Female,disloyal Customer,44,Business travel,Business,406,2,2,2,4,5,2,5,5,1,1,3,1,3,5,24,14.0,neutral or dissatisfied +89865,116985,Female,Loyal Customer,46,Business travel,Business,2613,1,1,1,1,3,5,4,4,4,5,4,3,4,4,23,25.0,satisfied +89866,61049,Female,disloyal Customer,8,Business travel,Business,1546,3,0,3,4,3,3,3,3,4,5,5,5,4,3,4,0.0,neutral or dissatisfied +89867,98125,Male,Loyal Customer,46,Personal Travel,Eco,472,1,0,1,2,2,1,2,2,4,3,5,3,4,2,0,18.0,neutral or dissatisfied +89868,12987,Male,Loyal Customer,40,Business travel,Eco,374,2,2,2,2,2,2,2,2,5,3,5,1,5,2,0,0.0,satisfied +89869,113036,Female,Loyal Customer,46,Business travel,Business,543,1,1,1,1,3,4,4,4,4,4,4,5,4,4,10,0.0,satisfied +89870,111947,Male,Loyal Customer,44,Business travel,Business,770,4,4,4,4,5,5,5,5,5,5,5,4,5,4,34,27.0,satisfied +89871,11754,Male,Loyal Customer,67,Business travel,Eco,395,2,2,2,2,2,2,2,2,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +89872,17954,Male,Loyal Customer,31,Business travel,Business,500,3,3,3,3,3,3,3,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +89873,103425,Female,Loyal Customer,12,Personal Travel,Eco,237,3,5,3,3,3,3,2,3,5,4,5,5,4,3,6,9.0,neutral or dissatisfied +89874,16652,Female,Loyal Customer,25,Business travel,Business,3033,2,4,4,4,2,2,2,2,2,3,4,1,4,2,30,74.0,neutral or dissatisfied +89875,112056,Female,Loyal Customer,43,Business travel,Business,1754,2,5,2,2,2,5,5,3,3,3,3,3,3,4,3,0.0,satisfied +89876,86601,Female,Loyal Customer,17,Business travel,Business,746,4,4,4,4,4,4,4,4,4,5,5,3,5,4,89,77.0,satisfied +89877,117062,Female,Loyal Customer,27,Business travel,Eco,646,3,2,2,2,3,3,3,3,4,2,3,4,3,3,6,0.0,neutral or dissatisfied +89878,9182,Male,disloyal Customer,44,Business travel,Business,363,1,1,1,4,4,1,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +89879,107350,Female,Loyal Customer,47,Business travel,Eco,584,1,2,2,2,5,2,3,1,1,1,1,3,1,4,29,14.0,neutral or dissatisfied +89880,84379,Female,Loyal Customer,53,Business travel,Business,591,4,3,4,3,3,2,2,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +89881,48133,Female,Loyal Customer,46,Business travel,Business,2422,1,1,1,1,2,1,1,4,4,4,4,3,4,4,24,20.0,satisfied +89882,4580,Female,Loyal Customer,50,Business travel,Business,2955,1,1,1,1,4,5,4,3,3,3,3,5,3,5,26,22.0,satisfied +89883,121923,Female,disloyal Customer,21,Business travel,Eco,449,5,0,5,3,2,5,2,2,5,2,5,3,5,2,0,0.0,satisfied +89884,123311,Male,Loyal Customer,56,Business travel,Business,3877,5,5,5,5,5,4,5,4,4,4,4,5,4,4,43,19.0,satisfied +89885,19274,Male,Loyal Customer,41,Business travel,Eco,430,5,5,5,5,5,4,5,5,3,5,5,3,3,5,0,11.0,satisfied +89886,34527,Female,disloyal Customer,26,Business travel,Business,636,3,3,3,4,3,3,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +89887,1368,Female,Loyal Customer,68,Business travel,Business,2563,4,1,1,1,4,2,2,4,4,3,4,4,4,3,0,10.0,neutral or dissatisfied +89888,47750,Female,Loyal Customer,47,Business travel,Business,2717,3,2,3,3,2,3,2,5,5,5,5,1,5,3,38,29.0,satisfied +89889,87181,Female,Loyal Customer,59,Business travel,Business,2983,3,2,2,2,1,4,4,3,3,3,3,2,3,1,3,0.0,neutral or dissatisfied +89890,42073,Male,Loyal Customer,21,Personal Travel,Eco,106,1,5,0,3,4,0,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +89891,49970,Female,disloyal Customer,46,Business travel,Eco,373,1,2,2,3,2,2,2,2,2,2,4,3,3,2,8,4.0,neutral or dissatisfied +89892,110618,Female,disloyal Customer,21,Business travel,Business,719,0,0,0,4,5,0,5,5,4,2,4,3,4,5,0,0.0,satisfied +89893,65534,Male,Loyal Customer,23,Personal Travel,Eco Plus,1616,2,5,2,4,5,2,3,5,3,5,4,5,4,5,24,43.0,neutral or dissatisfied +89894,102626,Male,Loyal Customer,41,Business travel,Business,365,2,3,3,3,5,4,4,2,2,3,2,1,2,2,43,40.0,neutral or dissatisfied +89895,90281,Female,Loyal Customer,39,Business travel,Eco,773,1,4,4,4,1,1,1,1,2,4,3,3,2,1,0,7.0,neutral or dissatisfied +89896,25535,Female,Loyal Customer,14,Personal Travel,Eco,481,1,2,1,1,5,1,5,5,3,2,1,1,2,5,1,0.0,neutral or dissatisfied +89897,121306,Male,Loyal Customer,59,Business travel,Business,1009,3,3,3,3,3,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +89898,115647,Female,Loyal Customer,61,Business travel,Eco,337,2,2,2,2,3,3,4,2,2,2,2,3,2,2,0,7.0,neutral or dissatisfied +89899,93375,Female,disloyal Customer,35,Business travel,Business,671,3,3,3,1,5,3,3,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +89900,22182,Female,Loyal Customer,48,Business travel,Business,3130,3,1,1,1,1,4,3,3,3,3,3,1,3,1,5,15.0,neutral or dissatisfied +89901,94029,Female,Loyal Customer,56,Business travel,Business,3835,4,4,4,4,2,5,5,4,4,4,4,4,4,3,0,2.0,satisfied +89902,4260,Female,Loyal Customer,26,Business travel,Business,502,5,5,5,5,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +89903,67432,Male,Loyal Customer,49,Business travel,Business,2205,1,1,1,1,4,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +89904,125096,Female,Loyal Customer,49,Business travel,Business,3613,5,5,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +89905,9004,Female,Loyal Customer,48,Business travel,Business,1729,4,5,5,5,3,2,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +89906,91726,Female,Loyal Customer,44,Business travel,Business,2250,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +89907,114699,Female,Loyal Customer,45,Business travel,Business,2553,1,1,1,1,3,5,5,4,4,4,4,5,4,3,4,0.0,satisfied +89908,76016,Female,Loyal Customer,54,Business travel,Business,2760,0,0,0,1,3,4,4,3,3,3,3,3,3,5,0,1.0,satisfied +89909,45696,Female,Loyal Customer,24,Personal Travel,Eco,826,2,4,2,3,2,2,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +89910,83742,Female,disloyal Customer,24,Business travel,Business,1183,5,5,5,2,2,5,2,2,4,2,4,4,5,2,6,12.0,satisfied +89911,78265,Male,Loyal Customer,47,Personal Travel,Eco,903,4,4,4,2,1,4,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +89912,722,Female,Loyal Customer,58,Business travel,Business,3798,2,2,2,2,3,5,4,5,5,5,5,5,5,5,5,4.0,satisfied +89913,22226,Female,Loyal Customer,61,Business travel,Eco Plus,533,4,4,3,4,1,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +89914,36583,Male,Loyal Customer,68,Business travel,Eco,1121,2,3,3,3,2,2,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +89915,62098,Female,Loyal Customer,52,Business travel,Business,2454,3,3,3,3,3,5,4,4,4,4,4,5,4,3,15,8.0,satisfied +89916,113972,Female,disloyal Customer,25,Business travel,Eco,1463,1,1,1,3,1,1,1,1,3,4,3,4,3,1,31,19.0,neutral or dissatisfied +89917,62904,Male,Loyal Customer,39,Personal Travel,Business,862,3,4,3,5,5,4,5,3,3,3,2,5,3,3,41,18.0,neutral or dissatisfied +89918,8639,Female,Loyal Customer,45,Business travel,Business,280,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +89919,110877,Female,Loyal Customer,54,Business travel,Business,3430,5,5,5,5,3,5,5,5,5,5,5,5,5,5,13,2.0,satisfied +89920,103844,Male,Loyal Customer,56,Business travel,Eco,1072,4,5,5,5,4,4,4,4,2,3,4,4,3,4,68,47.0,neutral or dissatisfied +89921,2390,Female,disloyal Customer,23,Business travel,Business,641,4,0,4,4,5,4,5,5,3,4,4,5,5,5,0,0.0,satisfied +89922,59274,Female,Loyal Customer,10,Personal Travel,Eco Plus,4243,4,4,4,4,4,5,5,3,4,3,3,5,1,5,69,109.0,satisfied +89923,22929,Female,Loyal Customer,47,Business travel,Business,2769,5,5,5,5,4,2,3,4,4,4,4,3,4,3,0,0.0,satisfied +89924,60183,Male,Loyal Customer,43,Business travel,Business,1777,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +89925,5026,Female,Loyal Customer,48,Personal Travel,Business,303,2,4,2,2,5,4,5,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +89926,35174,Male,Loyal Customer,19,Business travel,Business,2476,3,3,3,3,4,4,4,4,2,3,2,5,1,4,0,0.0,satisfied +89927,2674,Female,Loyal Customer,60,Personal Travel,Eco,597,4,4,4,3,3,4,1,5,5,4,1,4,5,1,0,3.0,satisfied +89928,7852,Female,Loyal Customer,45,Business travel,Business,1005,1,1,1,1,2,4,4,4,4,4,4,5,4,4,8,0.0,satisfied +89929,31625,Female,Loyal Customer,55,Business travel,Eco,846,4,3,3,3,2,4,4,4,4,4,4,1,4,4,0,0.0,satisfied +89930,21456,Female,Loyal Customer,22,Business travel,Business,306,0,0,0,4,1,1,1,1,1,1,2,1,1,1,50,48.0,satisfied +89931,95213,Female,Loyal Customer,45,Personal Travel,Eco,677,3,1,3,3,3,4,3,5,5,3,1,1,5,3,5,0.0,neutral or dissatisfied +89932,115318,Male,Loyal Customer,45,Business travel,Business,417,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +89933,8736,Male,Loyal Customer,53,Business travel,Business,3824,0,5,0,4,4,4,5,4,4,4,4,3,4,5,26,15.0,satisfied +89934,104651,Female,Loyal Customer,40,Personal Travel,Eco,1754,0,1,0,4,1,0,1,1,3,1,4,2,4,1,0,0.0,satisfied +89935,2626,Male,disloyal Customer,27,Business travel,Business,227,1,0,0,3,1,0,1,1,5,2,5,5,5,1,3,2.0,neutral or dissatisfied +89936,28689,Male,disloyal Customer,30,Business travel,Eco,1231,4,4,4,1,1,4,1,1,3,4,5,3,2,1,0,0.0,satisfied +89937,87479,Female,disloyal Customer,28,Business travel,Business,321,5,5,5,1,3,5,3,3,4,4,5,5,5,3,0,0.0,satisfied +89938,40264,Female,disloyal Customer,36,Business travel,Eco,347,4,4,4,4,3,4,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +89939,51898,Male,Loyal Customer,40,Business travel,Business,507,1,1,1,1,1,1,3,5,5,5,5,4,5,3,54,48.0,satisfied +89940,96770,Female,Loyal Customer,46,Business travel,Business,3678,5,5,5,5,4,4,5,4,4,4,4,4,4,5,10,0.0,satisfied +89941,114151,Male,Loyal Customer,52,Business travel,Business,3382,2,2,3,2,3,4,5,4,4,4,4,5,4,5,34,31.0,satisfied +89942,97414,Female,Loyal Customer,37,Business travel,Business,1935,1,1,1,1,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +89943,59392,Male,Loyal Customer,55,Personal Travel,Eco,2486,1,1,1,4,5,1,4,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +89944,91326,Female,Loyal Customer,52,Business travel,Eco Plus,442,1,5,5,5,2,4,3,1,1,1,1,3,1,2,4,0.0,neutral or dissatisfied +89945,45424,Female,disloyal Customer,36,Business travel,Eco,649,3,2,3,3,5,3,5,5,4,3,4,4,3,5,0,0.0,neutral or dissatisfied +89946,60704,Female,Loyal Customer,47,Business travel,Business,1725,3,3,3,3,2,3,4,5,5,5,5,4,5,5,0,6.0,satisfied +89947,128723,Male,Loyal Customer,33,Personal Travel,Eco,1235,2,5,2,3,2,2,2,2,5,4,4,5,4,2,0,5.0,neutral or dissatisfied +89948,82216,Male,Loyal Customer,42,Business travel,Business,3836,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +89949,81231,Female,disloyal Customer,36,Business travel,Eco,449,3,2,3,4,3,3,2,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +89950,42013,Female,Loyal Customer,44,Business travel,Eco,116,4,4,4,4,5,2,1,4,4,4,4,2,4,1,0,0.0,satisfied +89951,108977,Male,disloyal Customer,21,Business travel,Business,957,2,1,2,4,5,2,5,5,3,3,4,2,4,5,37,23.0,neutral or dissatisfied +89952,104373,Female,disloyal Customer,27,Business travel,Eco,228,2,3,2,3,3,2,3,3,3,2,3,2,3,3,19,8.0,neutral or dissatisfied +89953,40063,Female,Loyal Customer,56,Business travel,Business,3756,2,2,2,2,5,3,1,4,4,4,4,2,4,3,0,0.0,satisfied +89954,101412,Male,Loyal Customer,37,Personal Travel,Eco,486,1,4,1,3,2,1,2,2,4,4,4,3,4,2,8,0.0,neutral or dissatisfied +89955,91930,Male,Loyal Customer,16,Business travel,Business,2475,1,3,3,3,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +89956,85013,Female,Loyal Customer,23,Business travel,Eco,1590,4,1,1,1,4,4,2,4,3,5,3,4,4,4,32,34.0,neutral or dissatisfied +89957,95917,Female,Loyal Customer,49,Business travel,Business,1411,4,4,5,4,5,5,5,4,4,4,4,3,4,5,15,14.0,satisfied +89958,115269,Female,Loyal Customer,51,Business travel,Business,1821,2,2,2,2,5,5,5,5,5,5,5,3,5,5,11,9.0,satisfied +89959,64103,Male,Loyal Customer,39,Business travel,Business,919,5,5,5,5,5,5,5,2,2,2,2,3,2,3,65,98.0,satisfied +89960,62140,Male,Loyal Customer,30,Business travel,Business,2434,5,5,5,5,4,4,4,4,4,3,3,5,4,4,0,5.0,satisfied +89961,107209,Female,Loyal Customer,13,Personal Travel,Eco,668,3,5,3,4,3,3,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +89962,33493,Female,Loyal Customer,62,Personal Travel,Eco,2496,2,3,2,2,5,1,5,2,2,2,2,1,2,4,24,56.0,neutral or dissatisfied +89963,2197,Female,Loyal Customer,19,Personal Travel,Eco,685,2,4,2,4,5,2,5,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +89964,47350,Male,Loyal Customer,19,Business travel,Business,599,2,5,5,5,2,2,2,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +89965,48956,Male,disloyal Customer,24,Business travel,Eco,109,2,5,2,1,2,2,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +89966,7968,Female,Loyal Customer,20,Personal Travel,Eco,594,2,3,2,4,4,2,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +89967,117129,Female,Loyal Customer,8,Personal Travel,Eco,369,3,3,1,3,3,1,3,3,4,4,3,4,3,3,16,5.0,neutral or dissatisfied +89968,118631,Male,Loyal Customer,63,Business travel,Eco,338,2,2,2,2,2,2,2,2,2,4,3,1,4,2,20,10.0,neutral or dissatisfied +89969,29640,Male,Loyal Customer,42,Personal Travel,Eco,1448,5,3,5,2,1,5,1,1,3,3,5,4,2,1,0,0.0,satisfied +89970,111048,Male,Loyal Customer,33,Business travel,Business,2304,3,3,4,3,4,4,4,4,4,1,2,2,4,4,0,0.0,satisfied +89971,123777,Female,Loyal Customer,35,Business travel,Business,541,5,5,5,5,2,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +89972,49062,Female,Loyal Customer,35,Business travel,Business,2558,4,1,4,4,4,1,5,4,4,4,4,4,4,1,0,0.0,satisfied +89973,117678,Male,Loyal Customer,36,Business travel,Business,2075,3,3,3,3,2,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +89974,56725,Male,Loyal Customer,43,Personal Travel,Eco,937,3,2,3,2,1,3,1,1,2,4,2,1,3,1,0,0.0,neutral or dissatisfied +89975,74302,Female,Loyal Customer,16,Personal Travel,Eco Plus,2288,2,5,2,1,2,2,2,2,5,3,1,3,4,2,0,10.0,neutral or dissatisfied +89976,95040,Female,Loyal Customer,39,Personal Travel,Eco,239,1,5,1,1,4,1,4,4,5,5,4,3,2,4,29,24.0,neutral or dissatisfied +89977,125351,Female,Loyal Customer,56,Business travel,Business,3639,1,1,3,1,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +89978,83565,Female,Loyal Customer,52,Business travel,Business,936,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +89979,110589,Male,Loyal Customer,69,Personal Travel,Eco,643,4,5,4,4,3,4,5,3,4,2,5,4,5,3,30,24.0,neutral or dissatisfied +89980,17887,Female,Loyal Customer,17,Personal Travel,Eco,425,1,1,1,3,4,1,1,4,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +89981,109808,Female,disloyal Customer,22,Business travel,Eco,1033,5,5,5,3,2,5,2,2,5,2,4,5,4,2,0,0.0,satisfied +89982,60879,Male,disloyal Customer,36,Business travel,Business,1062,2,2,2,3,4,2,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +89983,84211,Female,Loyal Customer,46,Business travel,Eco,432,2,3,2,3,1,3,4,2,2,2,2,1,2,4,0,13.0,neutral or dissatisfied +89984,96352,Female,Loyal Customer,17,Personal Travel,Eco,1609,4,5,4,2,4,4,1,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +89985,45248,Male,Loyal Customer,36,Business travel,Eco Plus,1013,4,2,2,2,4,4,4,4,3,4,3,4,2,4,0,3.0,satisfied +89986,26024,Male,Loyal Customer,39,Business travel,Eco,321,4,5,5,5,4,4,4,4,2,2,4,3,2,4,8,27.0,satisfied +89987,36231,Male,Loyal Customer,64,Personal Travel,Eco,280,3,5,3,2,1,3,1,1,4,3,2,3,3,1,0,0.0,neutral or dissatisfied +89988,43064,Female,Loyal Customer,66,Business travel,Business,3814,4,1,1,1,1,1,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +89989,107423,Female,Loyal Customer,37,Personal Travel,Eco,725,5,5,5,5,5,5,5,5,2,5,4,2,5,5,0,0.0,satisfied +89990,90078,Male,disloyal Customer,24,Business travel,Eco,983,3,3,3,4,3,3,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +89991,116906,Male,disloyal Customer,44,Business travel,Business,370,1,1,1,4,3,1,3,3,4,4,4,4,4,3,32,26.0,neutral or dissatisfied +89992,21844,Male,Loyal Customer,45,Business travel,Business,2217,2,4,1,1,4,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +89993,76895,Male,disloyal Customer,29,Business travel,Business,630,2,3,3,4,2,3,2,2,5,5,4,4,4,2,7,0.0,neutral or dissatisfied +89994,21559,Male,disloyal Customer,42,Business travel,Eco Plus,331,3,3,3,2,3,3,3,3,1,5,3,5,5,3,90,95.0,neutral or dissatisfied +89995,73638,Male,Loyal Customer,26,Business travel,Business,1811,5,5,5,5,5,5,4,5,4,2,4,3,5,5,0,0.0,satisfied +89996,30480,Male,disloyal Customer,38,Business travel,Eco,801,4,4,4,3,2,4,3,2,1,2,4,1,5,2,34,53.0,satisfied +89997,39970,Male,disloyal Customer,29,Business travel,Eco,1262,1,1,1,3,5,1,5,5,3,5,5,5,3,5,0,0.0,neutral or dissatisfied +89998,91373,Male,Loyal Customer,28,Personal Travel,Eco Plus,581,3,1,4,3,3,4,3,3,3,3,3,2,4,3,0,37.0,neutral or dissatisfied +89999,87186,Male,Loyal Customer,30,Business travel,Business,946,4,4,4,4,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +90000,19601,Female,Loyal Customer,33,Personal Travel,Eco Plus,108,4,5,0,2,3,0,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +90001,121327,Female,Loyal Customer,36,Personal Travel,Eco,1009,2,5,2,1,1,2,1,1,4,3,2,4,2,1,0,0.0,neutral or dissatisfied +90002,120566,Female,Loyal Customer,47,Personal Travel,Eco,2176,4,4,4,5,4,4,2,4,4,4,4,3,4,4,0,0.0,satisfied +90003,120318,Male,Loyal Customer,56,Business travel,Business,268,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +90004,16146,Female,Loyal Customer,36,Business travel,Eco,277,5,4,4,4,5,5,5,5,4,2,2,5,3,5,178,174.0,satisfied +90005,35799,Male,Loyal Customer,35,Business travel,Eco Plus,200,2,2,2,2,2,2,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +90006,99536,Female,Loyal Customer,57,Business travel,Business,3217,4,4,4,4,2,4,5,2,2,3,2,4,2,4,17,15.0,satisfied +90007,29397,Female,disloyal Customer,37,Business travel,Eco,878,1,1,1,2,2,1,2,2,4,5,5,5,2,2,0,0.0,neutral or dissatisfied +90008,73654,Male,Loyal Customer,23,Business travel,Business,1823,2,5,5,5,2,2,2,2,1,2,3,1,3,2,44,34.0,neutral or dissatisfied +90009,104811,Male,Loyal Customer,48,Personal Travel,Eco,587,4,4,3,2,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +90010,89759,Female,Loyal Customer,46,Personal Travel,Eco,1035,3,5,3,2,2,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +90011,4648,Female,Loyal Customer,48,Business travel,Business,3551,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +90012,34852,Female,disloyal Customer,18,Business travel,Eco,1826,4,4,4,3,3,4,1,3,4,5,4,2,4,3,14,0.0,neutral or dissatisfied +90013,104837,Female,Loyal Customer,53,Personal Travel,Eco,472,5,2,5,3,1,4,4,4,4,5,4,3,4,3,0,1.0,satisfied +90014,100668,Female,Loyal Customer,46,Business travel,Business,677,4,4,4,4,3,5,5,4,4,4,4,3,4,4,104,104.0,satisfied +90015,16293,Male,Loyal Customer,14,Personal Travel,Eco,946,1,4,1,3,1,1,1,1,4,1,2,5,3,1,33,48.0,neutral or dissatisfied +90016,35096,Female,Loyal Customer,19,Business travel,Business,1560,4,4,4,4,5,5,5,5,4,5,4,2,1,5,0,30.0,satisfied +90017,95097,Female,Loyal Customer,8,Personal Travel,Eco,341,3,1,3,2,4,3,4,4,1,3,1,2,2,4,0,0.0,neutral or dissatisfied +90018,10829,Male,Loyal Customer,45,Business travel,Business,3743,1,1,1,1,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +90019,92895,Male,Loyal Customer,55,Business travel,Business,3932,2,2,4,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +90020,25039,Female,Loyal Customer,24,Personal Travel,Eco,907,3,1,3,3,4,3,4,4,1,2,4,2,3,4,6,0.0,neutral or dissatisfied +90021,104948,Female,disloyal Customer,38,Business travel,Business,1180,3,3,3,3,5,3,5,5,5,3,5,3,5,5,111,98.0,neutral or dissatisfied +90022,74825,Male,Loyal Customer,45,Personal Travel,Eco Plus,1235,3,4,3,4,3,3,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +90023,74044,Male,Loyal Customer,39,Business travel,Business,1194,1,2,5,2,5,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +90024,112807,Male,Loyal Customer,54,Business travel,Business,1933,5,5,5,5,2,5,4,3,3,3,3,3,3,5,11,6.0,satisfied +90025,22205,Female,Loyal Customer,44,Personal Travel,Eco,533,2,1,5,3,2,2,2,2,2,5,2,1,2,3,0,0.0,neutral or dissatisfied +90026,55245,Female,Loyal Customer,60,Personal Travel,Eco,1009,1,5,1,3,3,4,4,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +90027,57102,Female,Loyal Customer,56,Business travel,Business,3047,2,2,2,2,2,5,4,5,5,5,5,5,5,5,65,52.0,satisfied +90028,94811,Male,Loyal Customer,38,Business travel,Eco,239,4,5,5,5,4,4,4,4,4,4,3,1,3,4,34,34.0,neutral or dissatisfied +90029,18961,Female,Loyal Customer,55,Business travel,Eco Plus,500,1,2,4,2,1,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +90030,23378,Female,Loyal Customer,54,Personal Travel,Eco,1014,4,1,5,3,5,5,3,1,2,2,2,3,1,3,259,244.0,neutral or dissatisfied +90031,80272,Female,Loyal Customer,56,Personal Travel,Business,746,2,4,2,2,2,1,5,5,4,5,4,5,5,5,141,134.0,neutral or dissatisfied +90032,100979,Male,disloyal Customer,30,Business travel,Eco,1112,2,2,2,2,3,2,3,3,4,3,2,3,2,3,15,22.0,neutral or dissatisfied +90033,71777,Female,Loyal Customer,58,Business travel,Business,1723,5,5,5,5,5,5,5,5,4,5,5,5,4,5,158,151.0,satisfied +90034,57802,Female,Loyal Customer,23,Business travel,Business,3686,2,2,2,2,5,5,5,5,3,2,4,5,5,5,11,6.0,satisfied +90035,9365,Male,Loyal Customer,43,Business travel,Business,2025,2,2,3,2,4,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +90036,59117,Female,Loyal Customer,52,Personal Travel,Eco,1744,4,4,4,3,2,4,2,3,3,4,3,2,3,2,67,69.0,neutral or dissatisfied +90037,101868,Male,disloyal Customer,26,Business travel,Eco,1747,4,3,3,3,2,4,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +90038,113438,Female,Loyal Customer,41,Business travel,Business,386,5,5,5,5,3,5,4,4,4,4,4,4,4,5,2,2.0,satisfied +90039,18229,Female,Loyal Customer,26,Business travel,Business,3633,4,2,2,2,2,2,4,2,2,5,3,2,3,2,0,18.0,neutral or dissatisfied +90040,128744,Female,Loyal Customer,42,Business travel,Eco,2521,4,1,1,1,4,4,4,4,4,2,3,4,3,4,0,0.0,neutral or dissatisfied +90041,46469,Female,Loyal Customer,47,Business travel,Business,2566,2,4,5,5,5,3,3,3,3,3,2,1,3,4,28,24.0,neutral or dissatisfied +90042,91801,Female,Loyal Customer,28,Personal Travel,Eco,588,1,1,1,4,5,1,4,5,1,2,3,2,4,5,0,0.0,neutral or dissatisfied +90043,121277,Male,Loyal Customer,57,Business travel,Business,1814,2,3,2,2,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +90044,51055,Female,Loyal Customer,57,Personal Travel,Eco,190,3,4,0,1,3,4,5,4,4,0,4,5,4,4,0,0.0,neutral or dissatisfied +90045,36325,Female,Loyal Customer,62,Business travel,Eco,395,2,4,4,4,4,3,3,2,2,2,2,4,2,4,0,2.0,neutral or dissatisfied +90046,105784,Male,Loyal Customer,25,Personal Travel,Eco,925,3,5,3,1,5,3,5,5,3,2,4,3,5,5,16,23.0,neutral or dissatisfied +90047,102204,Female,Loyal Customer,51,Business travel,Business,2139,3,3,3,3,3,4,5,5,5,5,5,4,5,3,11,3.0,satisfied +90048,73782,Female,Loyal Customer,46,Personal Travel,Eco,192,3,5,3,3,3,4,4,4,4,3,4,3,4,4,3,0.0,neutral or dissatisfied +90049,76853,Female,disloyal Customer,24,Business travel,Eco,989,4,4,4,3,3,4,3,3,3,1,4,1,4,3,5,0.0,satisfied +90050,37045,Female,Loyal Customer,69,Personal Travel,Eco,1105,3,1,3,2,1,3,3,2,2,3,2,1,2,1,11,15.0,neutral or dissatisfied +90051,43911,Female,Loyal Customer,45,Personal Travel,Eco,255,2,1,2,3,3,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +90052,116527,Female,Loyal Customer,42,Personal Travel,Eco,390,1,5,1,4,3,4,4,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +90053,71926,Female,Loyal Customer,46,Business travel,Business,1726,5,5,5,5,3,3,4,4,4,4,4,5,4,5,11,0.0,satisfied +90054,58332,Male,Loyal Customer,52,Personal Travel,Eco,1739,1,4,1,2,1,1,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +90055,8670,Male,Loyal Customer,45,Business travel,Business,2619,5,5,5,5,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +90056,62833,Female,Loyal Customer,52,Business travel,Business,2399,4,4,4,4,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +90057,35886,Male,Loyal Customer,14,Personal Travel,Eco,937,1,3,1,4,4,1,4,4,3,1,4,2,4,4,9,20.0,neutral or dissatisfied +90058,94604,Male,Loyal Customer,75,Business travel,Business,2377,3,1,1,1,3,3,4,3,3,3,3,4,3,3,1,0.0,neutral or dissatisfied +90059,93091,Female,Loyal Customer,61,Personal Travel,Eco,860,1,4,1,3,4,5,4,1,1,1,1,4,1,3,4,0.0,neutral or dissatisfied +90060,119159,Male,Loyal Customer,35,Business travel,Business,2091,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +90061,60481,Female,disloyal Customer,29,Business travel,Eco,862,4,4,4,4,5,4,1,5,4,4,3,2,4,5,13,16.0,neutral or dissatisfied +90062,48688,Female,Loyal Customer,26,Business travel,Business,109,5,5,3,5,4,4,4,4,4,5,4,4,4,4,6,0.0,satisfied +90063,22656,Male,Loyal Customer,10,Personal Travel,Eco Plus,300,2,3,2,4,5,2,5,5,4,3,2,1,3,5,33,32.0,neutral or dissatisfied +90064,108464,Male,Loyal Customer,21,Personal Travel,Eco,1444,3,1,3,3,3,3,3,3,4,1,2,4,2,3,16,9.0,neutral or dissatisfied +90065,86160,Male,Loyal Customer,40,Business travel,Business,2457,5,5,5,5,2,4,5,5,5,5,5,4,5,3,3,0.0,satisfied +90066,62956,Male,Loyal Customer,52,Business travel,Business,967,4,4,4,4,5,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +90067,1933,Male,disloyal Customer,39,Business travel,Business,285,2,2,2,4,1,2,1,1,4,3,3,2,4,1,11,14.0,neutral or dissatisfied +90068,3567,Male,Loyal Customer,30,Personal Travel,Eco,227,3,5,3,5,3,3,3,3,4,2,4,3,5,3,9,13.0,neutral or dissatisfied +90069,99514,Male,Loyal Customer,49,Personal Travel,Eco,307,3,5,3,2,3,3,3,3,2,5,3,4,3,3,0,9.0,neutral or dissatisfied +90070,65897,Female,Loyal Customer,41,Business travel,Business,569,2,2,2,2,2,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +90071,129698,Male,Loyal Customer,47,Business travel,Business,308,3,3,3,3,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +90072,96777,Female,Loyal Customer,18,Business travel,Business,3286,3,3,2,3,5,5,5,5,4,3,5,3,4,5,0,0.0,satisfied +90073,84431,Female,Loyal Customer,49,Personal Travel,Eco,591,1,4,1,2,4,4,4,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +90074,109532,Male,disloyal Customer,26,Business travel,Eco,434,3,0,3,1,4,3,4,4,3,5,4,4,1,4,0,0.0,neutral or dissatisfied +90075,108772,Female,Loyal Customer,55,Business travel,Business,404,2,2,2,2,4,5,4,5,5,5,5,5,5,4,9,18.0,satisfied +90076,19750,Female,Loyal Customer,36,Business travel,Eco,462,4,4,4,4,4,4,4,4,1,2,4,1,2,4,48,44.0,satisfied +90077,49053,Male,Loyal Customer,60,Business travel,Business,156,2,2,2,2,1,4,1,5,5,5,3,4,5,3,0,0.0,satisfied +90078,20695,Male,Loyal Customer,50,Business travel,Eco,779,2,1,1,1,2,2,2,2,2,5,3,2,2,2,73,86.0,neutral or dissatisfied +90079,122514,Female,Loyal Customer,60,Personal Travel,Eco,930,1,5,1,2,5,4,5,3,3,1,3,4,3,4,3,0.0,neutral or dissatisfied +90080,51339,Female,Loyal Customer,54,Business travel,Eco Plus,262,2,1,4,1,2,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +90081,17341,Female,Loyal Customer,41,Business travel,Business,3874,5,5,5,5,1,5,2,4,4,4,4,3,4,1,0,0.0,satisfied +90082,40702,Male,Loyal Customer,54,Business travel,Business,3086,3,5,3,3,5,3,5,3,3,5,3,5,3,1,0,0.0,satisfied +90083,7219,Female,Loyal Customer,49,Business travel,Eco,135,1,2,2,2,5,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +90084,109024,Female,disloyal Customer,39,Business travel,Business,849,3,3,3,3,3,3,3,3,3,3,3,4,4,3,129,122.0,neutral or dissatisfied +90085,14099,Male,Loyal Customer,63,Personal Travel,Eco,371,4,3,4,4,3,4,3,3,1,4,3,4,3,3,0,32.0,satisfied +90086,75478,Female,Loyal Customer,70,Personal Travel,Eco,2585,2,5,2,5,2,3,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +90087,63521,Female,Loyal Customer,67,Business travel,Business,1009,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +90088,14059,Male,Loyal Customer,31,Business travel,Business,1599,4,5,5,5,4,4,4,4,2,3,3,4,4,4,169,217.0,neutral or dissatisfied +90089,109016,Male,Loyal Customer,18,Business travel,Business,2982,1,1,1,1,4,4,4,4,3,5,5,5,5,4,8,9.0,satisfied +90090,16378,Male,Loyal Customer,25,Business travel,Eco Plus,1215,4,3,3,3,4,4,3,4,5,2,4,2,1,4,2,0.0,satisfied +90091,66802,Male,Loyal Customer,14,Business travel,Business,731,3,4,4,4,3,3,3,3,1,2,3,3,4,3,23,8.0,neutral or dissatisfied +90092,31390,Female,Loyal Customer,60,Personal Travel,Eco,895,4,5,4,4,3,4,5,3,3,4,3,3,3,3,42,69.0,neutral or dissatisfied +90093,51827,Female,disloyal Customer,23,Business travel,Eco Plus,370,0,0,0,1,5,0,2,5,2,4,3,4,4,5,0,0.0,satisfied +90094,3094,Male,Loyal Customer,36,Business travel,Business,194,1,1,1,1,4,3,2,5,5,5,5,4,5,2,0,11.0,satisfied +90095,90556,Female,disloyal Customer,23,Business travel,Eco,271,5,4,5,3,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +90096,10800,Male,Loyal Customer,57,Business travel,Business,3653,3,3,3,3,4,3,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +90097,78058,Male,Loyal Customer,49,Personal Travel,Eco,152,1,5,1,2,2,1,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +90098,93531,Female,Loyal Customer,60,Business travel,Business,3639,3,2,2,2,5,1,1,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +90099,110120,Female,Loyal Customer,41,Business travel,Business,882,1,0,0,2,2,3,3,5,5,0,5,4,5,4,9,8.0,neutral or dissatisfied +90100,126269,Female,disloyal Customer,23,Business travel,Eco,190,5,3,5,2,3,5,3,3,3,2,3,4,2,3,0,0.0,satisfied +90101,101203,Male,Loyal Customer,68,Personal Travel,Eco,1235,0,5,0,3,2,0,2,2,3,1,5,5,1,2,1,0.0,satisfied +90102,32131,Male,Loyal Customer,37,Business travel,Business,101,1,1,1,1,1,1,3,4,4,4,4,1,4,2,0,0.0,satisfied +90103,79527,Female,Loyal Customer,31,Business travel,Business,762,1,1,1,1,3,4,3,3,3,4,4,5,4,3,0,0.0,satisfied +90104,49705,Female,disloyal Customer,37,Business travel,Eco,190,2,0,2,2,3,2,5,3,1,3,4,3,3,3,0,1.0,neutral or dissatisfied +90105,90688,Male,Loyal Customer,40,Business travel,Business,2564,1,1,1,1,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +90106,116179,Female,Loyal Customer,45,Personal Travel,Eco,447,2,4,2,4,2,4,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +90107,116350,Female,Loyal Customer,42,Personal Travel,Eco,358,4,4,4,4,1,4,3,3,3,4,3,2,3,3,14,17.0,neutral or dissatisfied +90108,51236,Male,Loyal Customer,52,Business travel,Eco Plus,156,5,2,2,2,5,5,5,5,2,2,2,1,3,5,0,0.0,satisfied +90109,99259,Female,Loyal Customer,56,Business travel,Business,2234,2,2,2,2,4,5,4,5,5,5,5,4,5,4,58,52.0,satisfied +90110,49663,Male,Loyal Customer,53,Business travel,Eco,86,5,3,5,3,5,5,5,5,4,3,4,4,3,5,0,0.0,satisfied +90111,110639,Male,Loyal Customer,31,Personal Travel,Business,829,2,4,2,4,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +90112,101836,Male,Loyal Customer,14,Personal Travel,Eco,1521,4,4,4,4,3,4,3,3,3,3,5,4,3,3,0,2.0,neutral or dissatisfied +90113,25483,Female,disloyal Customer,26,Business travel,Eco,547,4,4,4,2,3,4,3,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +90114,70016,Male,Loyal Customer,68,Business travel,Business,583,3,3,3,3,3,4,5,5,5,5,5,3,5,4,1,0.0,satisfied +90115,128032,Female,Loyal Customer,34,Business travel,Business,1440,1,1,1,1,3,4,3,1,1,1,1,4,1,4,3,0.0,neutral or dissatisfied +90116,64204,Male,Loyal Customer,67,Personal Travel,Eco,853,1,1,1,4,1,1,1,1,3,1,3,1,3,1,10,18.0,neutral or dissatisfied +90117,76373,Female,Loyal Customer,28,Business travel,Business,931,2,2,2,2,3,4,3,3,3,4,5,5,4,3,29,33.0,satisfied +90118,51855,Female,Loyal Customer,66,Business travel,Business,3758,3,3,3,3,3,3,3,4,4,4,4,5,4,4,5,16.0,satisfied +90119,38313,Male,Loyal Customer,31,Business travel,Eco,1666,4,3,3,3,4,4,4,4,3,2,4,2,1,4,57,39.0,satisfied +90120,35537,Male,Loyal Customer,58,Personal Travel,Eco,944,3,3,3,4,2,3,2,2,1,1,4,4,4,2,0,0.0,neutral or dissatisfied +90121,106915,Female,Loyal Customer,26,Business travel,Business,1259,5,5,5,5,5,5,5,5,4,2,5,5,5,5,0,0.0,satisfied +90122,31889,Male,Loyal Customer,35,Business travel,Business,2762,1,4,4,4,3,2,2,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +90123,120197,Female,Loyal Customer,57,Business travel,Business,2534,5,5,5,5,3,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +90124,96073,Female,Loyal Customer,30,Personal Travel,Eco,795,1,4,0,1,4,0,4,4,5,5,5,4,4,4,18,13.0,neutral or dissatisfied +90125,58491,Female,Loyal Customer,9,Business travel,Business,3787,2,1,1,1,2,2,2,2,3,1,4,2,4,2,0,0.0,neutral or dissatisfied +90126,7257,Female,Loyal Customer,45,Personal Travel,Eco,135,3,2,3,3,3,3,4,5,5,3,5,3,5,1,41,33.0,neutral or dissatisfied +90127,44530,Female,Loyal Customer,39,Business travel,Eco,157,2,1,1,1,2,2,2,2,3,2,4,1,3,2,0,0.0,satisfied +90128,114385,Male,Loyal Customer,48,Business travel,Business,853,3,1,3,3,2,4,4,4,4,4,4,4,4,3,16,12.0,satisfied +90129,101652,Male,Loyal Customer,42,Business travel,Business,1733,2,2,2,2,4,3,4,4,4,4,4,5,4,5,26,21.0,satisfied +90130,11595,Female,Loyal Customer,38,Business travel,Business,257,3,3,3,3,3,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +90131,1,Male,disloyal Customer,48,Business travel,Business,821,3,3,3,3,5,3,5,5,3,2,5,4,5,5,2,5.0,neutral or dissatisfied +90132,92824,Male,Loyal Customer,30,Business travel,Business,1587,4,4,4,4,3,3,3,3,4,3,4,4,5,3,0,0.0,satisfied +90133,67051,Female,disloyal Customer,39,Business travel,Business,1017,2,2,2,4,5,2,5,5,4,3,4,2,3,5,0,0.0,neutral or dissatisfied +90134,74543,Male,Loyal Customer,50,Business travel,Business,1464,1,1,1,1,5,5,5,4,4,4,4,3,4,5,16,17.0,satisfied +90135,60735,Male,Loyal Customer,57,Business travel,Business,1725,2,2,2,2,5,4,4,3,2,3,4,4,5,4,143,121.0,satisfied +90136,77924,Male,Loyal Customer,44,Personal Travel,Business,214,1,0,1,5,1,5,5,4,2,5,5,5,5,5,83,142.0,neutral or dissatisfied +90137,80751,Male,Loyal Customer,21,Personal Travel,Eco,393,2,4,2,1,5,2,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +90138,76656,Male,Loyal Customer,64,Personal Travel,Eco,547,3,0,4,3,1,4,1,1,5,3,3,3,5,1,0,0.0,neutral or dissatisfied +90139,119037,Female,Loyal Customer,61,Business travel,Business,2378,2,4,4,4,5,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +90140,1741,Male,Loyal Customer,61,Personal Travel,Eco,489,1,2,1,4,2,1,2,2,2,1,3,3,3,2,0,9.0,neutral or dissatisfied +90141,112119,Female,disloyal Customer,26,Business travel,Business,977,2,2,2,4,3,2,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +90142,34697,Female,disloyal Customer,24,Business travel,Eco,209,5,5,5,1,3,5,3,3,1,3,5,2,1,3,12,25.0,satisfied +90143,19902,Female,Loyal Customer,32,Business travel,Eco,296,5,5,5,5,5,5,5,5,1,5,3,1,5,5,7,0.0,satisfied +90144,89461,Female,Loyal Customer,36,Personal Travel,Eco,151,1,5,1,1,5,1,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +90145,14641,Female,disloyal Customer,20,Business travel,Eco,948,5,5,5,2,5,5,5,5,2,3,1,2,1,5,0,0.0,satisfied +90146,120657,Female,Loyal Customer,53,Business travel,Business,3675,4,4,4,4,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +90147,108641,Female,disloyal Customer,37,Business travel,Eco,528,3,3,4,3,4,4,4,4,3,1,4,1,4,4,8,0.0,neutral or dissatisfied +90148,65642,Male,Loyal Customer,46,Personal Travel,Eco Plus,175,3,5,3,2,5,3,5,5,3,2,5,4,4,5,5,0.0,neutral or dissatisfied +90149,48408,Female,Loyal Customer,54,Business travel,Business,846,4,4,4,4,3,4,4,5,5,5,5,3,5,4,11,0.0,satisfied +90150,41866,Female,Loyal Customer,62,Personal Travel,Eco,483,3,4,3,3,4,2,3,3,3,3,3,2,3,1,0,13.0,neutral or dissatisfied +90151,80247,Male,Loyal Customer,48,Personal Travel,Eco,1269,4,5,4,3,5,4,4,5,4,3,4,5,5,5,0,0.0,satisfied +90152,122663,Female,Loyal Customer,54,Business travel,Business,361,3,3,2,3,5,4,4,4,4,4,4,5,4,4,0,5.0,satisfied +90153,90714,Male,Loyal Customer,48,Business travel,Business,2123,2,4,4,4,1,4,4,2,2,2,2,3,2,3,9,0.0,neutral or dissatisfied +90154,15742,Male,Loyal Customer,17,Personal Travel,Business,544,3,2,4,2,4,1,1,1,1,3,3,1,4,1,269,264.0,neutral or dissatisfied +90155,99599,Female,Loyal Customer,57,Personal Travel,Eco,802,3,4,3,3,4,5,1,1,1,3,1,5,1,5,1,0.0,neutral or dissatisfied +90156,54290,Male,Loyal Customer,28,Business travel,Business,1075,2,2,2,2,4,4,4,4,1,2,3,2,3,4,0,0.0,satisfied +90157,17234,Female,Loyal Customer,32,Business travel,Business,872,2,2,2,2,5,4,5,5,5,5,4,2,2,5,0,0.0,satisfied +90158,74880,Female,Loyal Customer,53,Business travel,Business,2475,5,5,5,5,2,5,4,4,4,4,4,5,4,4,2,0.0,satisfied +90159,44760,Female,disloyal Customer,20,Business travel,Eco,1250,3,3,3,3,5,3,5,5,1,3,3,2,4,5,0,0.0,neutral or dissatisfied +90160,12018,Female,Loyal Customer,38,Business travel,Eco,376,2,1,1,1,2,2,2,2,3,2,2,2,2,2,0,0.0,satisfied +90161,89857,Male,Loyal Customer,32,Business travel,Business,1310,5,5,5,5,4,4,4,4,5,2,5,3,4,4,0,28.0,satisfied +90162,36551,Female,Loyal Customer,31,Business travel,Business,1883,5,5,1,5,3,4,3,3,1,4,1,1,2,3,22,0.0,satisfied +90163,116130,Male,Loyal Customer,20,Personal Travel,Eco,308,1,1,1,4,4,1,2,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +90164,33750,Female,disloyal Customer,21,Business travel,Business,266,2,3,2,3,4,2,4,4,4,4,3,2,2,4,0,0.0,neutral or dissatisfied +90165,96456,Female,Loyal Customer,33,Business travel,Business,436,2,2,2,2,4,4,3,2,2,2,2,3,2,4,2,3.0,neutral or dissatisfied +90166,91943,Male,Loyal Customer,54,Personal Travel,Eco,2475,4,1,4,1,5,4,5,5,4,5,1,2,1,5,0,0.0,satisfied +90167,97100,Female,disloyal Customer,25,Business travel,Eco,1242,3,4,4,4,4,4,4,4,4,3,4,2,4,4,0,7.0,neutral or dissatisfied +90168,27019,Male,Loyal Customer,26,Personal Travel,Eco,867,1,4,1,4,3,1,3,3,4,2,3,4,4,3,0,4.0,neutral or dissatisfied +90169,82554,Male,Loyal Customer,51,Business travel,Business,3656,3,2,3,3,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +90170,16855,Male,Loyal Customer,42,Business travel,Business,2140,1,1,4,1,3,2,3,4,4,4,4,4,4,5,6,30.0,satisfied +90171,18417,Female,disloyal Customer,29,Business travel,Eco,750,3,3,3,4,5,3,1,5,2,3,3,2,4,5,0,0.0,neutral or dissatisfied +90172,33024,Female,Loyal Customer,30,Personal Travel,Eco,163,2,5,2,2,3,2,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +90173,97705,Female,Loyal Customer,39,Personal Travel,Eco,456,3,3,1,2,3,1,3,3,3,2,3,4,3,3,29,25.0,neutral or dissatisfied +90174,111638,Male,Loyal Customer,45,Business travel,Business,1290,3,3,3,3,5,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +90175,114089,Female,Loyal Customer,44,Personal Travel,Eco,1892,3,5,3,1,1,2,1,2,2,3,5,3,2,3,0,0.0,neutral or dissatisfied +90176,112705,Female,disloyal Customer,22,Business travel,Eco,671,3,3,3,4,3,3,4,3,4,2,3,1,3,3,31,15.0,neutral or dissatisfied +90177,26343,Female,Loyal Customer,52,Business travel,Eco,861,2,1,2,2,1,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +90178,3381,Male,Loyal Customer,35,Business travel,Business,315,1,5,5,5,4,3,2,1,1,1,1,3,1,3,11,26.0,neutral or dissatisfied +90179,7694,Female,Loyal Customer,23,Personal Travel,Eco,604,1,4,1,1,4,1,4,4,3,5,2,1,4,4,0,1.0,neutral or dissatisfied +90180,113439,Male,Loyal Customer,57,Business travel,Business,236,0,0,0,3,5,5,5,4,4,5,5,3,4,4,0,0.0,satisfied +90181,26027,Female,Loyal Customer,67,Personal Travel,Eco,321,4,5,4,3,5,5,2,2,2,4,2,2,2,4,0,0.0,satisfied +90182,14837,Female,disloyal Customer,18,Business travel,Eco,261,5,3,5,3,1,5,1,1,5,1,2,2,2,1,0,0.0,satisfied +90183,128331,Female,Loyal Customer,52,Business travel,Business,1601,2,2,5,2,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +90184,59824,Female,disloyal Customer,22,Business travel,Business,997,4,0,3,1,5,3,5,5,5,5,4,5,4,5,0,0.0,satisfied +90185,109912,Female,disloyal Customer,57,Business travel,Eco,673,2,2,2,1,3,2,1,3,2,3,5,4,2,3,0,0.0,neutral or dissatisfied +90186,32753,Male,Loyal Customer,36,Business travel,Business,2811,1,1,1,1,1,1,5,4,4,4,5,2,4,1,0,12.0,satisfied +90187,46075,Female,Loyal Customer,39,Business travel,Eco,541,4,4,4,4,4,4,4,4,5,2,3,5,4,4,0,19.0,satisfied +90188,29322,Female,Loyal Customer,21,Personal Travel,Eco,834,1,4,1,5,5,1,5,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +90189,11651,Female,disloyal Customer,22,Business travel,Business,925,5,0,5,1,2,5,2,2,4,4,5,5,5,2,59,61.0,satisfied +90190,70656,Female,Loyal Customer,23,Personal Travel,Eco,946,3,3,3,4,3,3,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +90191,77371,Male,Loyal Customer,22,Business travel,Business,3610,1,5,5,5,1,1,1,1,2,2,3,4,2,1,0,0.0,neutral or dissatisfied +90192,117265,Female,Loyal Customer,24,Personal Travel,Eco,369,2,3,2,3,2,2,1,2,2,2,2,3,2,2,2,0.0,neutral or dissatisfied +90193,103197,Male,Loyal Customer,65,Personal Travel,Eco,814,3,2,3,3,3,3,2,3,2,3,1,4,3,3,1,0.0,neutral or dissatisfied +90194,69768,Male,disloyal Customer,28,Business travel,Business,1085,4,4,4,5,3,4,3,3,4,5,4,5,4,3,0,0.0,satisfied +90195,95374,Female,Loyal Customer,8,Personal Travel,Eco,239,1,4,1,3,5,1,5,5,5,5,4,4,4,5,1,0.0,neutral or dissatisfied +90196,75470,Male,Loyal Customer,22,Personal Travel,Eco,2342,5,3,5,4,1,5,1,1,4,1,1,5,3,1,0,0.0,satisfied +90197,37751,Female,Loyal Customer,17,Business travel,Eco Plus,950,4,4,3,4,4,4,4,4,4,5,3,4,5,4,0,0.0,satisfied +90198,67752,Male,Loyal Customer,29,Business travel,Business,3823,3,3,3,3,5,5,5,5,3,4,5,4,4,5,30,5.0,satisfied +90199,8443,Female,Loyal Customer,19,Business travel,Eco,590,3,5,5,5,3,3,3,3,1,5,3,3,3,3,0,0.0,neutral or dissatisfied +90200,18327,Female,Loyal Customer,48,Business travel,Business,2513,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,4.0,satisfied +90201,114277,Female,Loyal Customer,26,Personal Travel,Eco,819,1,5,1,3,3,1,3,3,3,4,3,3,4,3,28,26.0,neutral or dissatisfied +90202,101436,Male,Loyal Customer,43,Business travel,Business,345,5,2,5,5,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +90203,87131,Male,Loyal Customer,54,Personal Travel,Eco,645,3,2,3,4,3,3,3,3,2,5,3,2,4,3,3,4.0,neutral or dissatisfied +90204,13077,Female,Loyal Customer,39,Business travel,Business,562,5,5,5,5,4,5,5,5,5,5,5,5,5,5,3,0.0,satisfied +90205,75508,Male,Loyal Customer,49,Business travel,Business,2527,3,3,3,3,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +90206,41798,Male,Loyal Customer,69,Business travel,Eco,257,3,2,2,2,3,3,3,3,2,3,1,5,2,3,0,0.0,satisfied +90207,14942,Female,Loyal Customer,44,Business travel,Business,528,1,1,3,1,5,4,1,5,5,5,5,1,5,5,40,37.0,satisfied +90208,66946,Male,Loyal Customer,40,Business travel,Business,985,4,4,4,4,5,5,5,4,4,4,4,4,4,3,5,0.0,satisfied +90209,91204,Male,Loyal Customer,13,Personal Travel,Eco,581,2,1,2,2,3,2,3,3,4,4,3,4,2,3,0,10.0,neutral or dissatisfied +90210,119390,Female,disloyal Customer,20,Business travel,Business,399,0,5,0,1,4,0,4,4,4,4,4,5,5,4,0,0.0,satisfied +90211,83176,Male,Loyal Customer,60,Business travel,Business,3558,1,1,1,1,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +90212,103295,Male,Loyal Customer,34,Personal Travel,Eco,872,0,3,0,3,1,0,1,1,1,3,3,1,4,1,0,0.0,satisfied +90213,106467,Male,Loyal Customer,41,Business travel,Business,2028,3,3,3,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +90214,97776,Female,Loyal Customer,46,Business travel,Business,1884,5,5,5,5,3,5,4,4,4,4,4,5,4,5,48,41.0,satisfied +90215,128848,Female,Loyal Customer,54,Personal Travel,Eco,2475,2,4,1,3,1,2,4,4,3,3,3,4,1,4,19,9.0,neutral or dissatisfied +90216,55119,Male,Loyal Customer,28,Personal Travel,Eco,1504,2,5,2,2,3,2,4,3,4,4,3,5,4,3,0,0.0,neutral or dissatisfied +90217,105436,Female,Loyal Customer,65,Personal Travel,Eco Plus,452,3,4,3,2,5,5,4,5,5,3,5,3,5,4,30,22.0,neutral or dissatisfied +90218,116659,Male,Loyal Customer,49,Business travel,Business,2475,0,0,0,4,2,4,4,5,5,1,1,3,5,5,55,57.0,satisfied +90219,12228,Male,Loyal Customer,66,Personal Travel,Business,190,4,5,4,4,5,5,5,5,5,4,5,4,5,4,59,58.0,neutral or dissatisfied +90220,52866,Female,Loyal Customer,49,Business travel,Business,1024,3,3,3,3,1,5,4,5,5,5,5,4,5,3,12,4.0,satisfied +90221,16588,Male,Loyal Customer,61,Personal Travel,Eco,872,1,2,1,3,3,1,3,3,2,2,4,3,3,3,46,42.0,neutral or dissatisfied +90222,50276,Male,Loyal Customer,38,Business travel,Business,2379,1,1,2,2,5,4,4,1,1,1,1,4,1,3,0,17.0,neutral or dissatisfied +90223,52317,Male,Loyal Customer,35,Business travel,Business,1729,2,2,2,2,1,2,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +90224,95090,Male,Loyal Customer,11,Personal Travel,Eco,277,3,2,3,4,2,3,5,2,1,5,3,2,4,2,1,7.0,neutral or dissatisfied +90225,9391,Female,Loyal Customer,43,Business travel,Eco,372,2,3,3,3,3,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +90226,116968,Female,Loyal Customer,40,Business travel,Business,370,4,4,4,4,2,5,4,5,5,4,5,3,5,4,1,0.0,satisfied +90227,11931,Female,Loyal Customer,10,Personal Travel,Eco Plus,501,2,2,2,3,3,2,3,3,2,2,4,2,3,3,45,42.0,neutral or dissatisfied +90228,97894,Female,Loyal Customer,44,Business travel,Business,483,1,4,1,1,2,4,4,4,4,4,4,5,4,5,11,0.0,satisfied +90229,70090,Female,disloyal Customer,23,Business travel,Eco,550,2,5,2,2,4,2,4,4,4,2,4,5,4,4,0,3.0,neutral or dissatisfied +90230,103689,Male,disloyal Customer,19,Business travel,Eco,405,2,2,3,3,5,3,5,5,2,5,3,4,3,5,0,0.0,neutral or dissatisfied +90231,104901,Male,Loyal Customer,17,Business travel,Business,1565,1,5,5,5,1,1,1,1,3,3,4,2,3,1,7,19.0,neutral or dissatisfied +90232,101335,Female,Loyal Customer,25,Business travel,Business,1771,1,1,1,1,4,4,4,4,4,5,4,4,4,4,25,0.0,satisfied +90233,67332,Female,disloyal Customer,27,Business travel,Business,1471,4,4,4,3,4,4,4,4,5,2,4,3,4,4,24,6.0,satisfied +90234,124205,Male,Loyal Customer,35,Business travel,Business,2176,2,4,4,4,4,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +90235,41607,Male,Loyal Customer,38,Personal Travel,Eco,1235,1,2,1,1,2,1,2,2,4,1,1,4,1,2,18,22.0,neutral or dissatisfied +90236,120345,Male,Loyal Customer,39,Business travel,Business,2356,3,5,4,5,4,4,3,3,3,3,3,2,3,1,5,0.0,neutral or dissatisfied +90237,104359,Male,Loyal Customer,45,Personal Travel,Eco Plus,409,1,3,1,3,2,1,2,2,3,4,2,2,3,2,73,48.0,neutral or dissatisfied +90238,117708,Male,disloyal Customer,24,Business travel,Business,1009,5,0,5,2,5,5,5,5,3,5,4,4,5,5,40,24.0,satisfied +90239,74287,Male,Loyal Customer,47,Business travel,Eco,788,4,5,5,5,4,4,4,4,5,1,3,2,5,4,0,0.0,satisfied +90240,98348,Male,Loyal Customer,12,Business travel,Business,1563,1,1,1,1,5,5,5,5,4,3,5,5,4,5,5,2.0,satisfied +90241,8438,Female,disloyal Customer,21,Business travel,Eco Plus,862,3,1,3,4,5,3,5,5,2,2,3,2,3,5,10,2.0,neutral or dissatisfied +90242,80243,Male,disloyal Customer,26,Business travel,Eco,1269,2,2,2,4,4,2,4,4,2,2,4,4,3,4,0,14.0,neutral or dissatisfied +90243,26004,Male,Loyal Customer,47,Business travel,Eco,425,4,5,5,5,4,4,4,4,5,1,3,4,5,4,0,0.0,satisfied +90244,121821,Male,Loyal Customer,46,Business travel,Business,2413,4,4,5,4,4,4,4,5,5,5,5,4,5,4,78,73.0,satisfied +90245,40993,Male,Loyal Customer,28,Business travel,Eco Plus,984,3,5,5,5,5,5,5,5,3,2,2,5,5,5,12,0.0,satisfied +90246,11389,Male,Loyal Customer,44,Business travel,Business,2081,0,4,0,1,2,4,5,4,4,4,3,5,4,5,0,0.0,satisfied +90247,112139,Female,Loyal Customer,48,Business travel,Business,895,1,1,5,1,4,4,4,4,4,4,4,5,4,4,4,12.0,satisfied +90248,76406,Male,Loyal Customer,55,Business travel,Business,2390,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +90249,44656,Male,Loyal Customer,33,Business travel,Eco,67,4,5,5,5,4,5,4,4,3,3,1,4,3,4,0,0.0,satisfied +90250,9566,Female,Loyal Customer,42,Business travel,Business,283,5,5,5,5,4,4,4,4,4,4,4,4,4,5,19,10.0,satisfied +90251,11743,Male,Loyal Customer,33,Business travel,Business,395,2,2,2,2,2,1,2,2,4,3,3,1,3,2,29,48.0,neutral or dissatisfied +90252,103209,Female,disloyal Customer,23,Business travel,Business,1482,5,0,5,3,4,5,3,4,4,1,4,5,5,4,0,0.0,satisfied +90253,29678,Male,Loyal Customer,77,Business travel,Eco Plus,1448,2,5,5,5,2,2,2,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +90254,65646,Male,disloyal Customer,23,Business travel,Eco,1021,2,2,2,5,3,2,1,3,4,2,4,3,4,3,0,11.0,neutral or dissatisfied +90255,66621,Female,Loyal Customer,57,Business travel,Business,802,5,4,4,4,1,2,3,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +90256,79181,Male,Loyal Customer,75,Business travel,Eco,922,5,2,4,4,5,5,5,2,3,4,3,5,5,5,0,0.0,satisfied +90257,87601,Female,Loyal Customer,67,Business travel,Business,1761,5,5,5,5,3,5,5,5,5,5,5,4,5,5,0,11.0,satisfied +90258,124690,Female,Loyal Customer,48,Business travel,Business,2129,5,5,5,5,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +90259,66493,Female,Loyal Customer,57,Business travel,Business,2319,2,2,2,2,3,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +90260,102312,Male,Loyal Customer,38,Business travel,Business,2775,3,2,2,2,3,2,1,3,3,3,3,3,3,2,10,12.0,neutral or dissatisfied +90261,86747,Female,Loyal Customer,30,Business travel,Business,821,4,4,4,4,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +90262,4220,Male,Loyal Customer,61,Personal Travel,Eco,888,3,5,3,1,5,3,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +90263,124770,Male,Loyal Customer,42,Business travel,Business,280,5,5,5,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +90264,11075,Male,Loyal Customer,18,Personal Travel,Eco,216,5,0,5,4,3,5,2,3,5,2,4,1,4,3,0,0.0,satisfied +90265,7791,Male,Loyal Customer,44,Business travel,Business,3867,2,2,3,2,2,4,4,5,5,4,5,5,5,5,105,105.0,satisfied +90266,86270,Female,Loyal Customer,11,Personal Travel,Eco,356,2,5,2,3,2,2,2,2,4,4,5,3,4,2,7,2.0,neutral or dissatisfied +90267,81715,Female,Loyal Customer,21,Personal Travel,Eco Plus,907,2,5,2,3,4,2,4,4,3,5,4,5,5,4,32,37.0,neutral or dissatisfied +90268,93597,Male,Loyal Customer,30,Business travel,Business,704,4,4,2,4,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +90269,97030,Male,Loyal Customer,34,Personal Travel,Eco Plus,883,1,4,1,4,1,1,1,1,2,2,3,3,3,1,0,0.0,neutral or dissatisfied +90270,22001,Female,Loyal Customer,44,Personal Travel,Eco,500,2,1,2,4,3,4,4,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +90271,114909,Male,Loyal Customer,61,Business travel,Business,337,5,5,5,5,3,4,4,4,4,4,4,4,4,4,31,33.0,satisfied +90272,4076,Female,Loyal Customer,44,Business travel,Business,2350,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +90273,23445,Male,disloyal Customer,28,Business travel,Eco,516,4,5,3,3,2,3,2,2,5,1,2,1,5,2,5,0.0,neutral or dissatisfied +90274,104786,Female,Loyal Customer,40,Business travel,Business,587,1,1,1,1,5,5,5,4,4,4,4,4,4,5,13,7.0,satisfied +90275,47243,Male,disloyal Customer,36,Business travel,Business,588,2,2,2,3,3,2,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +90276,46555,Male,Loyal Customer,30,Business travel,Eco,141,5,2,2,2,5,5,5,5,5,2,1,2,3,5,71,67.0,satisfied +90277,32321,Female,Loyal Customer,62,Business travel,Eco,101,5,3,5,5,5,5,2,5,5,5,5,2,5,3,0,0.0,satisfied +90278,94772,Female,Loyal Customer,43,Business travel,Business,2441,2,2,2,2,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +90279,37625,Male,Loyal Customer,29,Personal Travel,Eco,950,3,1,3,3,1,3,1,1,3,1,3,4,4,1,0,0.0,neutral or dissatisfied +90280,38363,Female,Loyal Customer,35,Personal Travel,Eco,1050,5,4,5,1,5,5,5,5,5,2,5,4,4,5,1,0.0,satisfied +90281,9131,Male,Loyal Customer,45,Business travel,Business,707,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +90282,3961,Male,Loyal Customer,43,Personal Travel,Eco,764,3,5,4,2,1,4,1,1,4,2,5,3,4,1,10,37.0,neutral or dissatisfied +90283,71796,Female,Loyal Customer,44,Business travel,Eco,1723,3,3,3,3,3,1,3,3,3,3,3,3,3,2,6,4.0,neutral or dissatisfied +90284,2682,Male,Loyal Customer,36,Personal Travel,Eco,539,4,4,4,2,5,4,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +90285,34931,Male,Loyal Customer,23,Personal Travel,Eco,187,2,5,2,3,3,2,3,3,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +90286,119355,Female,Loyal Customer,11,Personal Travel,Eco Plus,214,1,3,1,4,4,1,4,4,2,4,3,3,2,4,6,0.0,neutral or dissatisfied +90287,123969,Male,disloyal Customer,62,Business travel,Business,184,4,4,4,3,4,5,5,4,5,4,4,5,5,5,125,134.0,satisfied +90288,49814,Female,Loyal Customer,57,Business travel,Eco,89,3,2,2,2,1,4,4,3,3,3,3,3,3,3,110,99.0,neutral or dissatisfied +90289,69396,Female,Loyal Customer,36,Business travel,Eco,1096,2,5,5,5,2,2,2,2,3,2,2,2,3,2,0,29.0,neutral or dissatisfied +90290,97519,Male,Loyal Customer,47,Business travel,Business,439,4,4,5,4,5,5,5,4,4,4,4,4,4,4,10,6.0,satisfied +90291,77657,Male,disloyal Customer,48,Business travel,Eco,813,2,2,2,4,4,2,4,4,1,1,3,1,3,4,0,25.0,neutral or dissatisfied +90292,45856,Female,Loyal Customer,61,Business travel,Eco Plus,391,2,2,2,2,3,3,3,2,2,2,2,1,2,1,0,2.0,neutral or dissatisfied +90293,44303,Female,Loyal Customer,29,Business travel,Business,1428,5,5,5,5,5,5,5,5,2,3,4,2,3,5,0,0.0,satisfied +90294,102227,Male,Loyal Customer,52,Business travel,Business,2814,2,2,2,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +90295,49251,Male,disloyal Customer,41,Business travel,Business,363,3,3,3,3,4,3,4,4,4,2,5,4,5,4,4,0.0,neutral or dissatisfied +90296,118560,Male,Loyal Customer,59,Business travel,Business,2641,0,0,0,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +90297,67617,Male,Loyal Customer,43,Business travel,Business,1235,5,5,5,5,5,4,5,5,5,5,5,4,5,5,23,0.0,satisfied +90298,47460,Male,Loyal Customer,50,Personal Travel,Eco,558,4,4,4,4,4,4,5,4,4,4,4,2,3,4,0,0.0,neutral or dissatisfied +90299,57070,Male,Loyal Customer,12,Business travel,Business,2065,3,3,3,3,3,3,3,3,2,5,4,3,3,3,22,0.0,neutral or dissatisfied +90300,34515,Male,Loyal Customer,9,Personal Travel,Eco,1521,4,5,4,4,1,4,1,1,5,5,4,3,5,1,5,0.0,neutral or dissatisfied +90301,32943,Male,Loyal Customer,32,Personal Travel,Eco,163,3,4,3,4,3,3,2,3,5,3,5,4,4,3,7,5.0,neutral or dissatisfied +90302,117581,Male,Loyal Customer,51,Business travel,Eco,1020,1,1,1,1,1,1,1,1,3,3,2,1,2,1,14,0.0,neutral or dissatisfied +90303,12997,Male,Loyal Customer,34,Business travel,Eco,374,5,2,2,2,5,5,5,5,4,4,1,2,4,5,1,0.0,satisfied +90304,106806,Female,Loyal Customer,51,Personal Travel,Eco,977,2,5,2,3,5,4,5,1,1,2,1,5,1,4,15,19.0,neutral or dissatisfied +90305,88239,Male,Loyal Customer,37,Business travel,Business,404,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,5.0,satisfied +90306,41616,Female,Loyal Customer,56,Business travel,Eco Plus,1334,5,1,1,1,4,1,2,5,5,5,5,4,5,3,11,21.0,satisfied +90307,74987,Female,Loyal Customer,77,Business travel,Eco Plus,2586,3,2,2,2,4,2,3,3,3,3,3,2,3,1,21,0.0,neutral or dissatisfied +90308,64512,Female,Loyal Customer,51,Personal Travel,Business,282,4,2,4,3,3,2,3,3,3,4,5,2,3,4,25,23.0,neutral or dissatisfied +90309,82463,Female,Loyal Customer,28,Personal Travel,Eco,502,5,4,5,4,1,5,2,1,5,5,4,3,4,1,0,0.0,satisfied +90310,105616,Male,Loyal Customer,55,Business travel,Business,925,2,2,2,2,4,4,4,5,5,5,5,5,5,3,19,2.0,satisfied +90311,29794,Female,Loyal Customer,52,Business travel,Eco,548,4,4,4,4,3,1,5,4,4,4,4,5,4,2,0,0.0,satisfied +90312,129587,Female,Loyal Customer,56,Business travel,Business,308,2,2,2,2,2,5,5,4,4,4,4,5,4,5,12,10.0,satisfied +90313,56382,Male,Loyal Customer,47,Business travel,Eco Plus,200,2,5,5,5,2,2,2,2,3,1,4,3,2,2,0,0.0,satisfied +90314,31027,Female,Loyal Customer,25,Business travel,Business,2734,5,5,4,5,5,4,5,5,4,2,5,4,5,5,0,0.0,satisfied +90315,99268,Female,Loyal Customer,50,Business travel,Eco,833,2,3,5,3,3,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +90316,24090,Female,disloyal Customer,24,Business travel,Eco,554,3,5,3,2,3,3,3,3,5,3,3,5,3,3,0,0.0,neutral or dissatisfied +90317,129445,Male,Loyal Customer,8,Personal Travel,Eco,236,2,4,0,1,2,0,2,2,5,3,5,4,5,2,4,0.0,neutral or dissatisfied +90318,125136,Female,Loyal Customer,30,Personal Travel,Eco,361,3,4,3,2,1,3,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +90319,43130,Female,Loyal Customer,35,Business travel,Eco Plus,259,2,1,1,1,2,2,2,2,4,3,3,3,4,2,19,27.0,neutral or dissatisfied +90320,14559,Male,Loyal Customer,53,Personal Travel,Eco Plus,368,2,4,2,4,1,2,1,1,1,1,4,1,1,1,0,0.0,neutral or dissatisfied +90321,59278,Male,Loyal Customer,56,Business travel,Business,3302,1,1,5,1,3,2,2,3,5,4,5,2,5,2,0,0.0,satisfied +90322,114634,Male,Loyal Customer,44,Business travel,Business,2891,5,5,5,5,2,4,4,5,5,5,5,4,5,5,9,0.0,satisfied +90323,108890,Male,Loyal Customer,46,Business travel,Business,1183,1,1,1,1,2,5,5,5,5,5,5,4,5,4,27,30.0,satisfied +90324,81739,Male,Loyal Customer,48,Business travel,Business,1306,3,3,3,3,3,5,5,4,4,4,4,3,4,4,6,0.0,satisfied +90325,28305,Female,Loyal Customer,60,Business travel,Business,867,3,3,3,3,2,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +90326,15732,Male,Loyal Customer,26,Personal Travel,Eco,419,4,4,4,1,4,4,4,4,4,1,4,4,5,4,0,0.0,satisfied +90327,71642,Male,Loyal Customer,22,Personal Travel,Eco,1197,4,5,4,5,2,4,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +90328,106464,Male,disloyal Customer,29,Business travel,Business,1300,4,4,4,3,1,4,5,1,4,5,5,3,4,1,0,0.0,satisfied +90329,90772,Female,Loyal Customer,39,Business travel,Business,2233,4,2,2,2,3,4,3,2,2,4,3,3,3,3,264,258.0,neutral or dissatisfied +90330,44453,Male,Loyal Customer,23,Business travel,Eco,802,5,4,4,4,5,5,4,5,2,3,3,5,4,5,0,0.0,satisfied +90331,116040,Male,Loyal Customer,29,Personal Travel,Eco,446,4,5,4,2,5,4,5,5,3,2,5,4,4,5,0,0.0,satisfied +90332,101865,Male,disloyal Customer,38,Business travel,Business,1747,3,4,4,4,2,4,2,2,3,4,5,4,4,2,8,0.0,neutral or dissatisfied +90333,118941,Male,Loyal Customer,33,Personal Travel,Eco Plus,1618,2,5,3,2,3,3,3,3,1,1,4,4,4,3,3,0.0,neutral or dissatisfied +90334,89985,Male,Loyal Customer,18,Business travel,Eco Plus,1487,4,5,4,5,4,5,4,4,2,1,3,2,3,4,0,0.0,satisfied +90335,50935,Male,Loyal Customer,55,Personal Travel,Eco,89,1,3,1,3,5,1,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +90336,77922,Male,Loyal Customer,47,Personal Travel,Business,214,4,1,4,3,2,3,4,4,4,4,5,2,4,1,17,65.0,satisfied +90337,99606,Female,Loyal Customer,44,Business travel,Business,808,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +90338,82558,Male,Loyal Customer,42,Business travel,Business,528,5,5,4,5,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +90339,68917,Female,Loyal Customer,15,Personal Travel,Eco,936,2,3,2,1,3,2,3,3,4,3,3,3,1,3,0,0.0,neutral or dissatisfied +90340,122922,Female,Loyal Customer,22,Personal Travel,Business,590,4,5,4,3,3,4,3,3,2,3,5,1,1,3,0,11.0,satisfied +90341,100032,Female,disloyal Customer,38,Business travel,Eco,220,3,1,3,4,4,3,4,4,1,5,3,3,3,4,15,7.0,neutral or dissatisfied +90342,34367,Male,Loyal Customer,43,Personal Travel,Eco,541,5,5,5,1,3,5,3,3,3,5,4,3,4,3,0,0.0,satisfied +90343,48619,Male,Loyal Customer,9,Personal Travel,Eco Plus,776,2,4,2,2,2,1,4,4,3,4,5,4,3,4,191,188.0,neutral or dissatisfied +90344,11179,Male,Loyal Customer,42,Personal Travel,Eco,224,3,5,3,2,3,3,3,3,5,4,4,4,4,3,0,1.0,neutral or dissatisfied +90345,76855,Female,Loyal Customer,49,Personal Travel,Eco,989,3,5,3,1,2,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +90346,102656,Male,Loyal Customer,43,Business travel,Business,255,1,1,1,1,3,4,4,5,5,5,5,5,5,5,62,38.0,satisfied +90347,114966,Male,Loyal Customer,58,Business travel,Business,447,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +90348,113578,Male,Loyal Customer,42,Business travel,Business,2053,4,4,4,4,1,5,3,5,5,5,5,5,5,2,52,52.0,satisfied +90349,14795,Male,disloyal Customer,43,Business travel,Eco,95,1,0,1,1,2,1,2,2,1,3,2,2,2,2,0,0.0,neutral or dissatisfied +90350,39202,Male,Loyal Customer,50,Business travel,Business,2452,1,1,1,1,5,5,4,5,5,5,5,5,5,3,9,17.0,satisfied +90351,87745,Male,Loyal Customer,39,Business travel,Business,3313,2,5,5,5,3,3,3,3,3,2,2,2,3,4,0,0.0,neutral or dissatisfied +90352,125951,Female,Loyal Customer,34,Business travel,Business,3078,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +90353,119293,Female,Loyal Customer,43,Business travel,Business,3761,2,4,4,4,5,4,3,2,2,2,2,3,2,1,0,3.0,neutral or dissatisfied +90354,50520,Female,Loyal Customer,7,Personal Travel,Eco,77,4,5,4,1,2,4,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +90355,113369,Female,Loyal Customer,35,Business travel,Business,386,5,5,5,5,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +90356,34647,Male,Loyal Customer,13,Personal Travel,Eco,541,5,5,5,2,3,5,3,3,5,4,5,5,5,3,0,0.0,satisfied +90357,50543,Female,Loyal Customer,13,Personal Travel,Eco,238,1,5,1,3,2,1,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +90358,122736,Male,Loyal Customer,53,Business travel,Business,1567,3,4,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +90359,38558,Male,Loyal Customer,13,Personal Travel,Eco,2586,1,2,1,3,2,1,2,2,4,1,4,3,3,2,0,0.0,neutral or dissatisfied +90360,80040,Female,Loyal Customer,39,Personal Travel,Eco,1035,4,4,4,3,2,4,2,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +90361,104566,Male,disloyal Customer,22,Business travel,Eco,369,3,5,2,3,3,2,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +90362,4174,Female,Loyal Customer,35,Personal Travel,Eco,431,1,2,1,4,3,1,1,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +90363,107043,Female,disloyal Customer,39,Business travel,Business,480,2,2,2,2,1,2,3,1,2,2,3,2,2,1,0,0.0,neutral or dissatisfied +90364,94125,Male,Loyal Customer,34,Business travel,Business,2692,3,3,2,3,4,4,5,5,5,5,5,3,5,3,12,0.0,satisfied +90365,113191,Male,Loyal Customer,34,Business travel,Business,1991,2,2,2,2,2,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +90366,116506,Male,Loyal Customer,59,Personal Travel,Eco,417,3,2,3,2,2,3,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +90367,659,Male,Loyal Customer,49,Business travel,Business,229,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,1.0,satisfied +90368,54347,Female,Loyal Customer,18,Personal Travel,Eco Plus,1597,4,1,3,2,3,3,3,3,3,1,2,2,3,3,0,0.0,satisfied +90369,42969,Female,Loyal Customer,30,Business travel,Eco,236,5,2,3,3,5,5,5,5,3,5,1,4,3,5,17,13.0,satisfied +90370,1668,Male,Loyal Customer,19,Personal Travel,Eco,551,2,3,2,1,4,2,4,4,5,2,1,5,2,4,0,0.0,neutral or dissatisfied +90371,107396,Male,disloyal Customer,29,Business travel,Eco,725,2,2,2,1,2,2,2,2,3,3,1,3,1,2,0,14.0,neutral or dissatisfied +90372,85052,Male,Loyal Customer,57,Business travel,Business,1821,3,5,5,5,2,3,3,3,3,3,3,1,3,4,0,5.0,neutral or dissatisfied +90373,67467,Female,Loyal Customer,40,Personal Travel,Eco,641,1,5,1,3,1,1,1,1,3,2,5,3,4,1,3,0.0,neutral or dissatisfied +90374,111184,Male,Loyal Customer,37,Business travel,Business,1703,4,4,4,4,3,3,5,4,4,5,4,3,4,3,0,0.0,satisfied +90375,39940,Female,Loyal Customer,41,Business travel,Business,3210,3,2,4,2,1,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +90376,72323,Female,Loyal Customer,59,Business travel,Business,1732,1,1,1,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +90377,102052,Female,Loyal Customer,53,Business travel,Business,258,1,4,4,4,4,3,3,1,1,1,1,1,1,3,60,56.0,neutral or dissatisfied +90378,2019,Male,Loyal Customer,41,Business travel,Business,3292,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +90379,115556,Female,Loyal Customer,56,Business travel,Eco,337,2,3,1,1,5,3,4,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +90380,57204,Male,disloyal Customer,29,Business travel,Business,1514,0,0,0,3,5,0,5,5,4,3,4,4,5,5,1,26.0,satisfied +90381,77868,Female,Loyal Customer,49,Business travel,Business,1404,4,4,4,4,5,4,4,5,5,5,5,4,5,4,2,0.0,satisfied +90382,100353,Female,Loyal Customer,29,Personal Travel,Eco,1053,5,4,5,2,2,4,2,2,4,2,5,4,5,2,1,0.0,satisfied +90383,7258,Female,Loyal Customer,51,Personal Travel,Eco,116,1,4,1,4,1,3,4,3,3,1,1,4,3,4,6,0.0,neutral or dissatisfied +90384,7338,Male,Loyal Customer,50,Business travel,Business,606,4,4,4,4,5,5,5,5,5,5,5,3,5,5,15,13.0,satisfied +90385,120824,Female,Loyal Customer,38,Business travel,Business,3808,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,26.0,satisfied +90386,7585,Female,Loyal Customer,49,Personal Travel,Eco,594,2,3,2,2,1,3,3,4,4,2,4,3,4,1,13,16.0,neutral or dissatisfied +90387,39492,Female,Loyal Customer,18,Business travel,Eco,1368,5,3,3,3,5,5,3,5,4,3,1,4,2,5,0,0.0,satisfied +90388,13833,Male,Loyal Customer,28,Business travel,Business,628,2,3,3,3,2,2,2,2,2,2,4,1,4,2,48,31.0,neutral or dissatisfied +90389,6521,Female,Loyal Customer,44,Business travel,Business,199,3,4,4,4,4,4,4,2,2,2,3,1,2,1,25,17.0,neutral or dissatisfied +90390,49460,Male,disloyal Customer,20,Business travel,Eco,134,0,4,0,1,3,0,3,3,3,3,2,1,5,3,0,2.0,satisfied +90391,59224,Female,Loyal Customer,40,Business travel,Business,2846,5,5,5,5,4,4,4,5,4,5,4,4,4,4,0,0.0,satisfied +90392,118178,Female,Loyal Customer,38,Business travel,Business,1440,1,1,1,1,5,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +90393,114774,Male,Loyal Customer,46,Business travel,Business,2078,5,5,5,5,4,4,4,3,4,5,4,4,5,4,167,159.0,satisfied +90394,10178,Male,Loyal Customer,40,Business travel,Business,1559,0,4,0,3,4,5,4,5,5,5,5,5,5,4,16,38.0,satisfied +90395,108156,Male,Loyal Customer,29,Personal Travel,Eco,1105,1,5,1,4,2,1,2,2,5,5,5,3,5,2,29,16.0,neutral or dissatisfied +90396,86934,Female,Loyal Customer,30,Business travel,Eco Plus,352,0,0,0,1,5,0,4,5,4,5,2,3,5,5,0,0.0,satisfied +90397,68527,Male,Loyal Customer,54,Business travel,Business,2266,5,5,5,5,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +90398,29859,Male,disloyal Customer,26,Business travel,Eco,725,1,1,1,3,1,1,1,1,5,1,5,2,2,1,72,68.0,neutral or dissatisfied +90399,82049,Male,Loyal Customer,44,Business travel,Business,1532,1,1,1,1,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +90400,96501,Male,Loyal Customer,24,Business travel,Eco,436,2,5,5,5,2,2,3,2,2,5,3,2,2,2,0,0.0,neutral or dissatisfied +90401,100040,Female,Loyal Customer,34,Business travel,Business,2433,4,4,4,4,1,1,5,4,4,4,4,5,4,3,0,0.0,satisfied +90402,32099,Female,Loyal Customer,36,Business travel,Business,101,3,3,4,3,5,1,5,4,4,4,4,4,4,3,0,0.0,satisfied +90403,61551,Female,disloyal Customer,29,Business travel,Business,2419,2,2,2,1,3,2,3,3,4,4,3,3,5,3,27,48.0,neutral or dissatisfied +90404,68577,Male,disloyal Customer,15,Business travel,Eco,1616,4,4,4,4,3,4,3,3,1,4,3,1,3,3,16,0.0,satisfied +90405,124488,Male,disloyal Customer,25,Business travel,Business,930,5,0,5,2,1,5,1,1,5,5,4,5,5,1,14,0.0,satisfied +90406,8954,Female,Loyal Customer,51,Personal Travel,Eco Plus,328,3,2,3,3,5,4,3,4,4,3,4,4,4,2,10,11.0,neutral or dissatisfied +90407,40752,Male,Loyal Customer,23,Business travel,Business,541,3,3,3,3,4,4,4,4,5,5,1,4,4,4,0,0.0,satisfied +90408,69732,Female,Loyal Customer,66,Personal Travel,Eco,1372,4,5,5,1,4,3,4,5,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +90409,34613,Male,Loyal Customer,11,Personal Travel,Eco,1598,2,5,2,4,1,2,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +90410,121753,Female,Loyal Customer,38,Business travel,Business,1931,5,2,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +90411,114949,Female,Loyal Customer,57,Business travel,Business,446,1,1,1,1,3,5,4,5,5,5,5,4,5,5,17,9.0,satisfied +90412,967,Male,Loyal Customer,43,Business travel,Business,309,3,3,3,3,5,3,3,3,3,3,3,3,3,3,0,6.0,neutral or dissatisfied +90413,21359,Female,Loyal Customer,26,Personal Travel,Eco,674,4,5,4,2,4,4,5,4,5,3,4,4,4,4,0,0.0,satisfied +90414,26485,Male,Loyal Customer,48,Personal Travel,Eco Plus,787,5,5,5,2,1,5,1,1,5,5,5,5,5,1,0,0.0,satisfied +90415,114996,Male,Loyal Customer,53,Business travel,Business,2167,1,1,2,1,5,5,4,4,4,4,4,5,4,4,4,2.0,satisfied +90416,32257,Female,Loyal Customer,24,Business travel,Business,2566,3,3,3,3,4,4,3,4,1,2,4,4,2,4,0,0.0,satisfied +90417,121668,Male,Loyal Customer,51,Business travel,Business,3497,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +90418,129564,Female,Loyal Customer,29,Personal Travel,Eco,2218,3,4,3,2,3,3,3,3,2,3,3,2,2,3,5,0.0,neutral or dissatisfied +90419,28088,Male,Loyal Customer,46,Business travel,Business,3896,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +90420,65110,Female,Loyal Customer,25,Personal Travel,Eco,190,4,4,4,5,3,4,1,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +90421,54611,Male,Loyal Customer,18,Business travel,Business,964,5,5,3,5,4,4,4,4,4,4,3,2,4,4,8,1.0,satisfied +90422,118060,Male,Loyal Customer,60,Business travel,Eco,644,4,1,1,1,4,4,4,4,3,4,2,3,1,4,4,7.0,satisfied +90423,3426,Male,Loyal Customer,70,Personal Travel,Eco,296,4,4,4,1,1,4,1,1,5,4,5,5,5,1,0,5.0,neutral or dissatisfied +90424,111530,Female,Loyal Customer,58,Business travel,Business,883,3,5,1,5,3,3,4,3,3,3,3,3,3,4,1,0.0,neutral or dissatisfied +90425,8125,Male,disloyal Customer,33,Business travel,Business,335,4,4,4,3,4,4,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +90426,83109,Male,Loyal Customer,15,Personal Travel,Eco,983,3,3,2,5,5,2,3,5,2,5,5,2,5,5,1,6.0,neutral or dissatisfied +90427,124213,Female,Loyal Customer,28,Personal Travel,Eco,2176,2,4,2,1,4,2,4,4,3,4,2,4,1,4,0,0.0,neutral or dissatisfied +90428,9580,Male,Loyal Customer,35,Business travel,Business,228,1,4,4,4,5,3,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +90429,75849,Male,disloyal Customer,23,Business travel,Eco,1037,3,3,3,4,3,3,2,3,1,2,4,1,4,3,18,103.0,neutral or dissatisfied +90430,9727,Female,Loyal Customer,48,Business travel,Eco Plus,212,4,5,2,5,1,3,3,5,5,4,5,1,5,3,51,53.0,neutral or dissatisfied +90431,58092,Female,Loyal Customer,46,Business travel,Business,2279,0,4,0,2,2,2,1,2,2,2,2,3,2,5,34,27.0,satisfied +90432,89463,Male,Loyal Customer,15,Personal Travel,Eco,134,1,3,0,4,3,0,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +90433,50174,Female,disloyal Customer,39,Business travel,Business,266,2,2,2,2,3,2,1,3,3,4,2,2,5,3,0,0.0,neutral or dissatisfied +90434,62812,Female,Loyal Customer,46,Personal Travel,Eco,2486,3,3,4,3,1,4,4,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +90435,20724,Male,Loyal Customer,23,Personal Travel,Eco,707,3,2,4,3,4,4,4,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +90436,95135,Male,Loyal Customer,29,Personal Travel,Eco,148,3,4,3,3,1,3,1,1,3,5,5,5,4,1,4,0.0,neutral or dissatisfied +90437,46782,Female,Loyal Customer,17,Business travel,Business,850,4,4,4,4,5,5,5,5,5,4,4,3,5,5,11,4.0,satisfied +90438,74572,Female,disloyal Customer,24,Business travel,Eco,1438,3,2,2,4,4,3,3,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +90439,27783,Female,Loyal Customer,21,Business travel,Eco,1448,5,5,5,5,5,5,4,5,5,5,1,2,3,5,1,0.0,satisfied +90440,127046,Female,Loyal Customer,22,Business travel,Business,1571,1,0,0,4,2,0,3,2,3,1,3,2,4,2,0,0.0,neutral or dissatisfied +90441,18317,Female,Loyal Customer,30,Business travel,Eco,705,4,2,1,1,4,4,4,4,1,3,4,4,4,4,0,0.0,satisfied +90442,43383,Male,Loyal Customer,56,Personal Travel,Eco,402,1,4,1,3,4,1,4,4,3,2,4,3,5,4,0,0.0,neutral or dissatisfied +90443,83995,Female,Loyal Customer,65,Business travel,Business,1800,1,1,1,1,5,5,1,4,4,4,4,4,4,2,0,,satisfied +90444,49317,Female,disloyal Customer,22,Business travel,Eco,89,3,0,3,2,1,3,1,1,1,4,5,4,5,1,0,3.0,neutral or dissatisfied +90445,91592,Male,Loyal Customer,51,Business travel,Business,3462,2,4,4,4,2,3,4,2,2,2,2,2,2,1,1,6.0,neutral or dissatisfied +90446,47714,Female,Loyal Customer,29,Personal Travel,Eco Plus,1428,4,4,4,4,2,4,4,2,2,2,3,1,3,2,0,0.0,satisfied +90447,83765,Male,Loyal Customer,52,Personal Travel,Business,926,2,4,2,3,3,5,4,1,1,2,1,4,1,4,28,4.0,neutral or dissatisfied +90448,74904,Male,Loyal Customer,55,Business travel,Business,2475,5,2,5,5,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +90449,12302,Female,Loyal Customer,60,Business travel,Business,2109,0,0,0,1,2,4,1,2,2,4,4,2,2,5,0,0.0,satisfied +90450,109319,Female,Loyal Customer,33,Personal Travel,Eco,1136,0,3,0,4,3,0,3,3,1,5,3,2,4,3,31,24.0,satisfied +90451,123065,Female,disloyal Customer,45,Business travel,Eco,650,2,1,2,3,5,2,5,5,3,2,3,4,2,5,70,97.0,neutral or dissatisfied +90452,78169,Female,Loyal Customer,49,Business travel,Business,259,2,2,2,2,4,4,4,5,5,5,5,3,5,3,2,0.0,satisfied +90453,121997,Male,Loyal Customer,45,Business travel,Business,2558,1,1,1,1,2,5,5,3,3,4,5,5,3,5,9,13.0,satisfied +90454,53247,Female,Loyal Customer,23,Business travel,Eco Plus,589,3,3,3,3,3,4,5,3,4,4,3,1,5,3,75,113.0,satisfied +90455,58759,Male,Loyal Customer,39,Business travel,Business,1120,4,4,4,4,5,4,4,5,5,5,5,4,5,3,0,9.0,satisfied +90456,118493,Male,disloyal Customer,29,Business travel,Business,647,2,1,1,2,5,1,4,5,5,3,4,3,4,5,12,9.0,neutral or dissatisfied +90457,13317,Female,Loyal Customer,51,Business travel,Business,3775,2,2,2,2,5,5,5,5,5,5,5,4,5,3,4,0.0,satisfied +90458,76227,Male,Loyal Customer,46,Business travel,Business,1399,1,1,5,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +90459,45032,Male,disloyal Customer,16,Business travel,Eco,867,2,2,2,4,3,2,2,3,2,4,3,1,2,3,0,0.0,neutral or dissatisfied +90460,3278,Male,Loyal Customer,65,Personal Travel,Eco,419,1,4,1,4,5,1,5,5,3,4,3,3,4,5,85,65.0,neutral or dissatisfied +90461,71008,Male,Loyal Customer,54,Business travel,Business,1921,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +90462,29253,Female,disloyal Customer,22,Business travel,Business,834,4,3,4,3,1,4,1,1,4,3,4,3,2,1,0,0.0,satisfied +90463,67131,Male,Loyal Customer,22,Business travel,Eco,1121,4,5,4,5,4,4,2,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +90464,95818,Female,Loyal Customer,41,Business travel,Business,1428,5,5,5,5,5,4,5,2,2,2,2,5,2,3,26,18.0,satisfied +90465,91951,Female,Loyal Customer,54,Personal Travel,Eco,2475,3,5,3,3,3,3,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +90466,18493,Female,Loyal Customer,38,Business travel,Business,3307,1,1,1,1,5,5,4,4,4,4,4,1,4,4,0,0.0,satisfied +90467,110308,Female,Loyal Customer,52,Business travel,Business,842,5,5,5,5,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +90468,55177,Female,disloyal Customer,23,Business travel,Business,1317,0,1,0,3,1,0,5,1,4,5,4,5,4,1,6,0.0,satisfied +90469,45516,Female,Loyal Customer,54,Business travel,Business,2396,3,3,3,3,5,3,2,3,3,3,3,4,3,3,0,0.0,satisfied +90470,56870,Female,Loyal Customer,48,Business travel,Business,2454,5,5,5,5,4,4,4,4,2,4,5,4,4,4,196,198.0,satisfied +90471,30918,Male,disloyal Customer,31,Business travel,Eco,896,3,3,3,4,5,3,5,5,4,1,4,4,4,5,8,46.0,neutral or dissatisfied +90472,126533,Male,Loyal Customer,32,Business travel,Business,1945,5,5,4,5,4,4,4,4,3,5,4,4,5,4,6,0.0,satisfied +90473,13760,Male,Loyal Customer,18,Personal Travel,Eco,441,3,5,3,5,2,3,1,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +90474,66668,Male,Loyal Customer,29,Business travel,Business,802,4,4,4,4,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +90475,35132,Male,Loyal Customer,40,Business travel,Eco,1010,4,5,5,5,4,4,4,4,1,5,1,5,2,4,0,7.0,satisfied +90476,9658,Male,disloyal Customer,26,Business travel,Business,212,1,0,1,2,5,1,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +90477,67308,Male,Loyal Customer,41,Business travel,Eco Plus,964,1,2,2,2,1,1,1,1,3,5,4,1,3,1,14,0.0,neutral or dissatisfied +90478,55324,Female,Loyal Customer,48,Business travel,Eco,1117,2,3,3,3,2,3,4,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +90479,106790,Female,Loyal Customer,54,Personal Travel,Business,977,3,5,3,5,4,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +90480,118614,Male,Loyal Customer,42,Business travel,Business,1832,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +90481,116654,Male,Loyal Customer,56,Business travel,Business,1850,2,2,2,2,3,5,5,5,5,5,5,4,5,3,1,0.0,satisfied +90482,77178,Male,Loyal Customer,60,Business travel,Business,2179,1,1,5,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +90483,32651,Female,disloyal Customer,32,Business travel,Eco,163,2,4,2,4,5,2,2,5,4,2,4,4,4,5,10,14.0,neutral or dissatisfied +90484,70231,Female,Loyal Customer,54,Personal Travel,Eco,1068,1,4,1,2,2,5,4,4,4,1,4,4,4,3,21,12.0,neutral or dissatisfied +90485,93615,Male,Loyal Customer,57,Business travel,Business,577,4,4,5,4,3,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +90486,50247,Female,disloyal Customer,22,Business travel,Eco,86,4,0,4,2,3,4,3,3,1,1,1,3,1,3,0,0.0,satisfied +90487,33142,Male,Loyal Customer,8,Personal Travel,Eco,102,2,5,2,3,4,2,4,4,3,3,4,4,4,4,6,5.0,neutral or dissatisfied +90488,126514,Male,Loyal Customer,39,Business travel,Business,3718,3,3,3,3,4,5,4,4,4,4,4,5,4,3,9,11.0,satisfied +90489,59482,Female,Loyal Customer,40,Business travel,Business,2080,5,1,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +90490,116330,Female,Loyal Customer,20,Personal Travel,Eco,480,3,1,3,3,3,3,1,3,2,3,3,4,2,3,22,18.0,neutral or dissatisfied +90491,63321,Male,disloyal Customer,33,Business travel,Eco,372,2,1,2,1,1,2,1,1,4,3,1,1,2,1,18,12.0,neutral or dissatisfied +90492,26815,Female,Loyal Customer,44,Business travel,Business,2139,1,1,1,1,5,4,3,1,1,1,1,4,1,1,1,7.0,neutral or dissatisfied +90493,64357,Female,disloyal Customer,35,Business travel,Eco,1192,1,1,1,4,1,4,4,3,2,3,3,4,1,4,147,132.0,neutral or dissatisfied +90494,126982,Female,Loyal Customer,39,Business travel,Business,3780,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +90495,101041,Female,Loyal Customer,40,Business travel,Business,3538,1,1,1,1,3,4,4,4,4,4,4,4,4,4,24,13.0,satisfied +90496,97634,Female,Loyal Customer,59,Personal Travel,Eco,748,1,1,1,4,4,4,4,1,1,1,1,2,1,2,14,26.0,neutral or dissatisfied +90497,8339,Female,Loyal Customer,41,Business travel,Business,2812,3,3,3,3,2,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +90498,49703,Male,Loyal Customer,57,Business travel,Business,2136,3,3,3,3,2,3,5,3,3,4,4,2,3,1,0,0.0,satisfied +90499,123092,Male,Loyal Customer,48,Business travel,Business,3274,1,3,3,3,3,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +90500,90468,Male,Loyal Customer,47,Business travel,Business,2857,2,2,2,2,3,3,3,3,4,4,5,3,3,3,161,187.0,satisfied +90501,28199,Male,Loyal Customer,34,Personal Travel,Eco,873,1,2,1,4,4,1,5,4,1,1,4,4,3,4,8,1.0,neutral or dissatisfied +90502,119839,Male,Loyal Customer,35,Business travel,Business,2148,5,5,5,5,5,4,4,5,5,5,5,5,5,3,16,5.0,satisfied +90503,80900,Male,Loyal Customer,47,Business travel,Business,341,0,0,0,1,4,5,5,5,5,5,5,3,5,4,2,0.0,satisfied +90504,121624,Male,Loyal Customer,69,Personal Travel,Eco,912,1,5,1,2,2,1,2,2,2,1,3,5,4,2,0,0.0,neutral or dissatisfied +90505,92491,Female,Loyal Customer,34,Business travel,Business,1892,1,1,1,1,3,3,2,5,5,5,5,2,5,3,14,0.0,satisfied +90506,39566,Male,Loyal Customer,47,Business travel,Business,3121,5,5,5,5,4,1,5,4,4,4,4,4,4,1,15,30.0,satisfied +90507,84708,Male,Loyal Customer,53,Business travel,Business,1907,1,1,1,1,4,4,4,1,1,1,1,2,1,2,46,35.0,neutral or dissatisfied +90508,47649,Male,Loyal Customer,51,Business travel,Eco,1269,4,1,1,1,4,4,4,4,4,5,3,1,3,4,85,88.0,neutral or dissatisfied +90509,18400,Male,Loyal Customer,63,Business travel,Eco,284,5,5,5,5,5,5,5,5,2,4,5,4,2,5,97,88.0,satisfied +90510,120664,Female,Loyal Customer,33,Business travel,Business,3404,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +90511,87241,Female,Loyal Customer,46,Business travel,Business,3260,5,5,5,5,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +90512,33578,Female,Loyal Customer,25,Business travel,Business,2708,4,4,4,4,5,5,5,5,2,1,1,4,2,5,0,0.0,satisfied +90513,93352,Male,Loyal Customer,51,Business travel,Business,3843,4,4,4,4,3,4,5,5,5,5,5,4,5,3,52,49.0,satisfied +90514,55403,Female,Loyal Customer,58,Business travel,Business,1558,5,5,5,5,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +90515,49371,Female,disloyal Customer,20,Business travel,Eco,209,0,0,0,1,2,0,2,2,1,1,3,5,4,2,8,21.0,satisfied +90516,24412,Female,Loyal Customer,27,Business travel,Business,2352,1,1,1,1,4,4,4,4,2,1,5,4,5,4,0,16.0,satisfied +90517,84971,Female,Loyal Customer,65,Personal Travel,Eco Plus,481,2,2,2,4,1,4,4,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +90518,64631,Female,disloyal Customer,48,Business travel,Business,190,1,1,1,5,1,1,1,1,5,3,5,3,4,1,24,20.0,neutral or dissatisfied +90519,104317,Female,disloyal Customer,36,Business travel,Business,409,3,3,3,4,4,3,4,4,3,2,4,3,4,4,98,95.0,neutral or dissatisfied +90520,45021,Male,Loyal Customer,16,Personal Travel,Eco,359,4,4,4,2,3,4,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +90521,57350,Male,Loyal Customer,61,Business travel,Business,1720,2,2,1,2,5,2,3,4,4,4,4,3,4,3,74,97.0,satisfied +90522,76318,Male,disloyal Customer,40,Business travel,Eco,682,2,2,2,5,2,2,2,2,2,5,3,5,3,2,0,0.0,neutral or dissatisfied +90523,88527,Female,Loyal Customer,50,Personal Travel,Eco,594,2,3,2,2,5,4,1,5,5,2,5,4,5,1,3,0.0,neutral or dissatisfied +90524,61665,Female,Loyal Customer,33,Business travel,Business,1379,3,3,3,3,5,5,5,4,4,4,4,4,4,3,3,0.0,satisfied +90525,53034,Male,Loyal Customer,44,Business travel,Eco,1208,1,2,2,2,1,1,1,1,3,5,3,4,4,1,0,0.0,neutral or dissatisfied +90526,100605,Female,Loyal Customer,23,Personal Travel,Eco,718,4,3,4,4,5,4,5,5,5,5,1,5,4,5,9,20.0,neutral or dissatisfied +90527,51057,Female,Loyal Customer,52,Personal Travel,Eco,109,2,2,0,4,2,4,4,4,4,0,4,3,4,2,0,0.0,neutral or dissatisfied +90528,63716,Male,Loyal Customer,43,Business travel,Business,1660,2,2,3,2,4,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +90529,99988,Male,disloyal Customer,26,Business travel,Business,281,4,0,4,4,5,4,5,5,3,3,5,3,5,5,72,70.0,satisfied +90530,122297,Male,Loyal Customer,65,Personal Travel,Eco,603,3,5,3,1,4,3,4,4,1,1,1,5,5,4,0,0.0,neutral or dissatisfied +90531,29992,Female,disloyal Customer,26,Business travel,Eco,31,4,0,4,1,3,4,3,3,5,3,5,5,2,3,0,0.0,neutral or dissatisfied +90532,5879,Female,disloyal Customer,24,Business travel,Business,173,0,0,0,4,5,0,5,5,4,5,5,5,5,5,0,0.0,satisfied +90533,41288,Male,Loyal Customer,67,Personal Travel,Eco,542,1,4,1,4,1,1,1,1,4,4,4,4,5,1,28,36.0,neutral or dissatisfied +90534,47016,Male,disloyal Customer,25,Business travel,Business,351,5,1,5,5,2,5,2,2,5,3,5,3,5,2,0,0.0,satisfied +90535,81997,Female,Loyal Customer,55,Business travel,Business,1535,3,3,3,3,4,3,2,3,3,3,3,4,3,1,39,59.0,neutral or dissatisfied +90536,27888,Male,disloyal Customer,35,Business travel,Eco,1376,2,2,2,3,2,5,5,1,2,2,2,5,1,5,0,0.0,neutral or dissatisfied +90537,88389,Female,Loyal Customer,43,Business travel,Business,2650,2,3,3,3,4,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +90538,32576,Female,Loyal Customer,31,Business travel,Business,216,1,4,4,4,3,3,1,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +90539,91773,Female,disloyal Customer,22,Business travel,Business,588,2,4,3,3,2,3,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +90540,45142,Male,Loyal Customer,44,Business travel,Business,3443,1,1,1,1,2,1,4,5,5,5,4,3,5,3,18,16.0,satisfied +90541,1820,Female,disloyal Customer,25,Business travel,Eco,408,2,3,1,4,1,1,4,1,1,5,3,1,3,1,0,12.0,neutral or dissatisfied +90542,38812,Male,Loyal Customer,50,Personal Travel,Eco,354,2,4,2,3,5,2,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +90543,69451,Female,Loyal Customer,28,Personal Travel,Eco,944,2,3,2,3,4,2,4,4,4,5,3,2,3,4,0,7.0,neutral or dissatisfied +90544,11100,Male,Loyal Customer,58,Personal Travel,Eco,482,1,3,1,3,3,1,3,3,4,2,1,5,2,3,26,29.0,neutral or dissatisfied +90545,45179,Male,Loyal Customer,36,Business travel,Eco Plus,174,4,5,5,5,4,4,4,4,1,2,3,4,3,4,0,0.0,satisfied +90546,92073,Male,Loyal Customer,16,Business travel,Business,1532,3,3,3,3,5,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +90547,57358,Male,Loyal Customer,67,Personal Travel,Eco,414,3,3,3,5,3,3,3,3,5,4,4,2,2,3,16,0.0,neutral or dissatisfied +90548,98838,Male,Loyal Customer,53,Personal Travel,Eco,444,3,5,3,1,5,3,5,5,4,2,5,4,5,5,41,28.0,neutral or dissatisfied +90549,15561,Female,Loyal Customer,60,Business travel,Business,296,5,5,5,5,5,2,5,5,5,5,5,4,5,1,31,49.0,satisfied +90550,125428,Female,Loyal Customer,48,Business travel,Eco,735,4,5,5,5,2,3,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +90551,28118,Male,Loyal Customer,24,Business travel,Eco,550,5,4,4,4,5,5,5,5,1,4,5,4,1,5,0,0.0,satisfied +90552,117825,Female,Loyal Customer,18,Personal Travel,Eco,328,1,2,2,3,2,2,2,2,3,3,3,2,3,2,26,36.0,neutral or dissatisfied +90553,118642,Male,Loyal Customer,21,Business travel,Eco,647,3,2,2,2,3,3,4,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +90554,76464,Female,Loyal Customer,13,Personal Travel,Business,534,4,5,4,4,4,4,4,4,5,5,5,4,5,4,30,21.0,neutral or dissatisfied +90555,123622,Female,disloyal Customer,27,Business travel,Business,214,5,5,5,2,5,5,5,5,3,2,4,4,5,5,2,2.0,satisfied +90556,77958,Female,Loyal Customer,51,Business travel,Business,332,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +90557,96408,Male,Loyal Customer,68,Personal Travel,Eco,1246,3,4,3,4,2,3,2,2,4,4,3,4,4,2,16,12.0,neutral or dissatisfied +90558,93169,Male,Loyal Customer,13,Personal Travel,Eco,1066,3,5,3,3,1,3,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +90559,23076,Female,Loyal Customer,53,Personal Travel,Eco,1174,1,5,1,5,5,4,5,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +90560,44476,Male,Loyal Customer,48,Business travel,Eco,692,4,2,4,4,4,4,4,4,1,1,2,4,2,4,0,0.0,satisfied +90561,49688,Female,Loyal Customer,42,Business travel,Business,1780,1,1,1,1,4,4,3,5,5,5,5,1,5,2,0,7.0,satisfied +90562,76665,Female,Loyal Customer,23,Personal Travel,Eco,534,2,5,2,3,5,2,3,5,4,5,4,4,4,5,25,42.0,neutral or dissatisfied +90563,86942,Male,Loyal Customer,36,Personal Travel,Business,907,4,5,4,3,4,5,4,2,2,4,2,3,2,3,0,13.0,neutral or dissatisfied +90564,121337,Male,Loyal Customer,35,Business travel,Business,430,4,4,2,4,2,4,5,5,5,5,5,5,5,4,0,1.0,satisfied +90565,123004,Male,Loyal Customer,53,Business travel,Business,3876,4,4,4,4,3,4,4,3,3,3,3,5,3,4,76,71.0,satisfied +90566,84161,Male,Loyal Customer,27,Personal Travel,Eco,503,5,5,5,5,3,5,2,3,5,3,4,3,5,3,0,0.0,satisfied +90567,28011,Female,Loyal Customer,33,Business travel,Business,2191,5,5,5,5,3,4,5,4,4,4,4,4,4,2,13,6.0,satisfied +90568,57099,Female,Loyal Customer,53,Business travel,Business,3011,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +90569,103782,Male,Loyal Customer,49,Business travel,Business,3332,2,5,2,2,5,5,4,5,5,5,5,4,5,5,14,2.0,satisfied +90570,65071,Female,Loyal Customer,33,Personal Travel,Eco,190,2,5,2,3,1,2,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +90571,22225,Female,Loyal Customer,29,Business travel,Eco Plus,773,4,5,5,5,4,4,4,4,4,2,2,2,2,4,0,12.0,neutral or dissatisfied +90572,20894,Female,disloyal Customer,30,Business travel,Eco,961,2,2,2,1,3,2,3,3,4,4,3,3,5,3,4,0.0,neutral or dissatisfied +90573,18444,Male,disloyal Customer,20,Business travel,Eco,262,1,2,1,4,2,1,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +90574,53335,Male,disloyal Customer,27,Business travel,Business,326,4,4,4,4,3,4,3,3,3,2,4,4,4,3,0,0.0,satisfied +90575,46731,Male,Loyal Customer,9,Personal Travel,Eco,196,4,5,4,2,4,4,5,4,4,4,4,3,5,4,0,11.0,neutral or dissatisfied +90576,121479,Female,Loyal Customer,26,Personal Travel,Eco,331,2,5,2,5,5,2,3,5,4,4,4,4,3,5,0,0.0,neutral or dissatisfied +90577,74566,Male,Loyal Customer,59,Business travel,Eco,1205,3,2,2,2,3,3,3,3,1,3,4,3,4,3,0,0.0,neutral or dissatisfied +90578,62577,Female,Loyal Customer,46,Business travel,Eco,1723,3,5,5,5,4,3,3,3,3,3,3,1,3,1,3,0.0,neutral or dissatisfied +90579,75116,Female,disloyal Customer,41,Business travel,Business,1347,4,4,4,4,2,4,2,2,3,4,4,4,5,2,0,0.0,satisfied +90580,43424,Male,Loyal Customer,28,Personal Travel,Eco Plus,531,1,5,1,3,4,1,4,4,4,5,5,4,4,4,4,13.0,neutral or dissatisfied +90581,100170,Female,Loyal Customer,44,Personal Travel,Eco,523,1,4,1,3,3,5,5,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +90582,111897,Female,Loyal Customer,39,Personal Travel,Eco,628,2,5,2,2,5,2,5,5,4,2,4,3,5,5,13,8.0,neutral or dissatisfied +90583,77422,Female,Loyal Customer,67,Personal Travel,Eco,626,2,4,2,1,3,5,4,3,3,2,3,3,3,5,8,4.0,neutral or dissatisfied +90584,41817,Male,Loyal Customer,63,Personal Travel,Eco,196,1,1,0,3,5,0,5,5,1,4,2,1,2,5,0,0.0,neutral or dissatisfied +90585,37543,Female,Loyal Customer,13,Business travel,Business,1035,3,5,5,5,3,3,3,3,1,1,4,2,4,3,36,16.0,neutral or dissatisfied +90586,50842,Female,Loyal Customer,57,Personal Travel,Eco,373,3,0,3,4,3,4,5,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +90587,92861,Male,Loyal Customer,32,Business travel,Business,2519,4,4,4,4,4,4,4,4,4,4,3,5,5,4,0,0.0,satisfied +90588,16805,Female,disloyal Customer,25,Business travel,Eco,645,4,3,4,3,5,4,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +90589,48461,Male,Loyal Customer,54,Business travel,Eco,916,4,3,3,3,4,4,4,4,5,3,1,5,3,4,0,0.0,satisfied +90590,121139,Male,Loyal Customer,17,Business travel,Eco,2521,2,1,1,1,2,1,2,4,4,3,3,2,1,2,0,22.0,neutral or dissatisfied +90591,124952,Female,Loyal Customer,36,Personal Travel,Eco Plus,728,3,5,3,1,2,3,2,2,4,2,4,2,5,2,0,0.0,neutral or dissatisfied +90592,106551,Female,Loyal Customer,27,Personal Travel,Eco,719,3,5,2,3,3,2,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +90593,126871,Female,Loyal Customer,65,Personal Travel,Eco,2296,1,5,2,3,4,5,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +90594,70727,Male,disloyal Customer,9,Business travel,Eco,675,2,2,2,3,1,2,3,1,2,3,3,1,3,1,0,6.0,neutral or dissatisfied +90595,67133,Male,Loyal Customer,51,Business travel,Business,929,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +90596,96007,Male,Loyal Customer,24,Business travel,Business,1090,2,5,5,5,2,2,2,2,2,3,4,4,3,2,1,5.0,neutral or dissatisfied +90597,120750,Male,Loyal Customer,42,Business travel,Business,3118,5,5,5,5,3,5,5,2,2,2,2,5,2,3,3,0.0,satisfied +90598,7748,Female,Loyal Customer,43,Business travel,Business,3550,4,4,4,4,2,5,5,5,5,5,5,4,5,4,4,25.0,satisfied +90599,75357,Female,disloyal Customer,26,Business travel,Business,1277,5,5,5,2,5,4,4,3,2,5,4,4,4,4,50,52.0,satisfied +90600,121276,Female,Loyal Customer,48,Business travel,Business,2075,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +90601,16998,Female,Loyal Customer,21,Personal Travel,Eco,843,4,4,4,3,5,4,2,5,4,5,4,3,4,5,0,0.0,satisfied +90602,82362,Male,Loyal Customer,55,Personal Travel,Eco,453,3,4,3,4,1,3,1,1,3,5,4,3,5,1,68,69.0,neutral or dissatisfied +90603,119326,Female,Loyal Customer,26,Personal Travel,Eco,214,4,5,4,5,1,4,1,1,5,4,5,5,4,1,0,0.0,satisfied +90604,102725,Female,Loyal Customer,15,Personal Travel,Eco,601,4,5,4,1,2,4,5,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +90605,84761,Male,Loyal Customer,22,Business travel,Business,2616,3,3,3,3,4,5,4,4,3,5,4,5,5,4,0,0.0,satisfied +90606,73443,Male,Loyal Customer,52,Personal Travel,Eco,1005,1,5,1,5,3,1,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +90607,114176,Female,Loyal Customer,52,Business travel,Business,3461,3,3,2,3,5,5,5,3,3,3,3,5,3,3,1,0.0,satisfied +90608,43943,Female,disloyal Customer,23,Business travel,Eco,473,4,0,4,1,5,4,5,5,5,2,4,5,5,5,0,0.0,satisfied +90609,28260,Male,Loyal Customer,52,Business travel,Business,3561,2,4,4,4,2,4,4,2,2,2,2,4,2,2,0,11.0,neutral or dissatisfied +90610,19477,Male,disloyal Customer,21,Business travel,Eco,177,4,5,4,5,4,4,3,4,4,5,4,2,1,4,0,1.0,satisfied +90611,87321,Female,Loyal Customer,59,Personal Travel,Eco Plus,577,3,4,3,3,5,4,5,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +90612,62388,Female,Loyal Customer,54,Business travel,Eco,1204,4,3,3,3,2,1,3,4,4,4,4,1,4,3,0,0.0,satisfied +90613,60955,Male,Loyal Customer,26,Business travel,Business,888,1,1,1,1,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +90614,83435,Female,Loyal Customer,59,Business travel,Business,3591,3,3,3,3,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +90615,44590,Female,Loyal Customer,45,Personal Travel,Eco,177,1,4,1,3,1,5,5,1,2,3,3,5,4,5,125,158.0,neutral or dissatisfied +90616,10767,Female,Loyal Customer,79,Business travel,Business,316,4,1,1,1,2,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +90617,49928,Female,Loyal Customer,58,Business travel,Business,1633,2,1,5,1,3,4,3,2,2,2,2,3,2,2,84,113.0,neutral or dissatisfied +90618,26835,Male,disloyal Customer,30,Business travel,Business,224,2,1,1,2,2,1,2,2,2,4,2,3,3,2,0,0.0,neutral or dissatisfied +90619,15434,Female,disloyal Customer,26,Business travel,Eco,164,5,4,4,2,2,4,2,2,2,1,2,4,5,2,0,0.0,satisfied +90620,48623,Female,Loyal Customer,34,Personal Travel,Eco Plus,845,4,5,4,2,5,4,5,5,4,3,5,3,4,5,0,0.0,satisfied +90621,32079,Female,Loyal Customer,48,Business travel,Eco,216,4,3,3,3,2,3,3,4,4,4,4,5,4,5,0,0.0,satisfied +90622,104480,Male,Loyal Customer,50,Personal Travel,Eco,1671,4,3,4,3,2,4,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +90623,32234,Female,Loyal Customer,62,Business travel,Business,101,2,2,2,2,5,3,3,4,4,4,5,3,4,1,1,4.0,satisfied +90624,105488,Female,Loyal Customer,52,Business travel,Business,516,3,5,3,3,4,4,4,5,5,5,5,3,5,4,5,0.0,satisfied +90625,65264,Female,disloyal Customer,56,Business travel,Business,224,3,3,3,3,2,3,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +90626,2526,Female,Loyal Customer,26,Business travel,Business,280,4,2,4,4,5,5,5,5,3,5,4,3,4,5,14,11.0,satisfied +90627,80866,Male,Loyal Customer,26,Personal Travel,Eco,692,2,5,2,3,4,2,1,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +90628,114105,Female,Loyal Customer,41,Business travel,Business,862,2,2,2,2,3,4,5,4,4,5,4,4,4,3,3,0.0,satisfied +90629,13283,Male,Loyal Customer,10,Personal Travel,Eco,468,3,4,3,2,3,3,3,3,4,3,5,3,5,3,0,28.0,neutral or dissatisfied +90630,21631,Male,Loyal Customer,14,Personal Travel,Eco,780,5,2,5,4,3,5,3,3,1,1,4,2,3,3,31,24.0,satisfied +90631,36606,Male,Loyal Customer,38,Business travel,Business,2410,3,3,3,3,4,5,2,4,4,4,4,4,4,4,2,0.0,satisfied +90632,106322,Female,Loyal Customer,55,Business travel,Business,2811,3,3,5,3,5,4,5,5,5,5,5,4,5,4,28,27.0,satisfied +90633,63748,Female,Loyal Customer,30,Personal Travel,Eco,1660,1,4,1,3,4,1,4,4,3,4,3,1,3,4,20,13.0,neutral or dissatisfied +90634,9299,Female,disloyal Customer,18,Business travel,Eco,542,0,0,0,4,3,0,3,3,4,3,5,5,4,3,0,0.0,satisfied +90635,15619,Female,Loyal Customer,25,Personal Travel,Eco,292,3,5,5,3,3,5,3,3,5,5,5,5,5,3,123,106.0,neutral or dissatisfied +90636,64551,Male,disloyal Customer,37,Business travel,Business,551,4,4,4,4,3,4,3,3,5,3,4,5,5,3,0,0.0,satisfied +90637,72265,Female,disloyal Customer,17,Business travel,Eco,921,1,1,1,4,4,1,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +90638,91867,Female,Loyal Customer,45,Business travel,Business,2239,4,4,5,4,5,5,5,3,3,2,3,5,3,3,0,0.0,satisfied +90639,13019,Male,Loyal Customer,17,Business travel,Eco,374,2,3,3,3,2,1,1,2,1,5,3,3,3,2,7,0.0,neutral or dissatisfied +90640,124190,Female,Loyal Customer,46,Business travel,Business,2176,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +90641,38154,Male,Loyal Customer,39,Personal Travel,Eco,1185,2,4,3,3,4,3,4,4,3,1,2,3,3,4,75,72.0,neutral or dissatisfied +90642,11078,Male,Loyal Customer,56,Personal Travel,Eco,301,4,4,4,3,1,4,1,1,5,4,4,5,4,1,0,5.0,neutral or dissatisfied +90643,11026,Female,Loyal Customer,65,Business travel,Eco,308,5,4,4,4,5,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +90644,113992,Male,Loyal Customer,62,Business travel,Business,3230,3,3,3,3,4,2,1,4,4,4,4,1,4,5,9,9.0,satisfied +90645,32340,Male,disloyal Customer,55,Business travel,Eco,163,5,0,5,5,3,5,3,3,3,2,5,4,2,3,0,1.0,satisfied +90646,68500,Female,Loyal Customer,11,Personal Travel,Eco,1303,2,5,2,4,3,2,1,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +90647,10465,Male,disloyal Customer,52,Business travel,Business,667,3,3,3,2,4,3,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +90648,103446,Male,Loyal Customer,49,Business travel,Business,2674,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +90649,46581,Male,Loyal Customer,37,Business travel,Business,141,0,5,0,5,4,2,1,1,1,1,1,4,1,2,0,0.0,satisfied +90650,16220,Female,Loyal Customer,24,Personal Travel,Eco Plus,199,1,5,1,2,3,1,4,3,3,2,4,5,4,3,0,0.0,neutral or dissatisfied +90651,26575,Male,Loyal Customer,52,Business travel,Eco,406,4,3,3,3,4,4,4,4,4,4,3,5,3,4,0,0.0,satisfied +90652,63533,Female,Loyal Customer,35,Business travel,Business,1009,3,5,5,5,2,3,3,3,3,3,3,2,3,2,98,78.0,neutral or dissatisfied +90653,103974,Female,Loyal Customer,46,Business travel,Eco Plus,370,3,4,4,4,3,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +90654,26909,Male,Loyal Customer,41,Business travel,Business,1770,2,2,2,2,2,4,4,5,5,5,5,4,5,2,0,0.0,satisfied +90655,79234,Male,Loyal Customer,63,Personal Travel,Eco,1521,3,4,3,4,3,3,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +90656,6630,Male,Loyal Customer,41,Personal Travel,Eco,719,2,5,2,3,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +90657,86812,Female,Loyal Customer,77,Business travel,Business,2651,3,5,5,5,2,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +90658,67812,Male,Loyal Customer,56,Business travel,Business,3991,4,3,4,4,4,3,4,5,5,5,5,2,5,1,74,51.0,satisfied +90659,104380,Male,disloyal Customer,16,Business travel,Eco,228,3,3,3,4,5,3,5,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +90660,2269,Male,Loyal Customer,19,Business travel,Business,2606,2,2,2,2,5,5,5,5,3,3,4,4,5,5,8,25.0,satisfied +90661,124502,Male,disloyal Customer,47,Business travel,Business,930,3,3,3,3,4,3,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +90662,17263,Male,Loyal Customer,52,Personal Travel,Eco,872,4,4,4,1,4,4,4,4,4,1,4,3,2,4,0,0.0,neutral or dissatisfied +90663,21597,Male,Loyal Customer,41,Business travel,Business,780,1,1,1,1,1,4,3,5,5,5,5,1,5,4,0,0.0,satisfied +90664,8441,Female,Loyal Customer,40,Business travel,Business,590,3,3,3,3,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +90665,19005,Female,Loyal Customer,42,Business travel,Eco,788,5,5,2,2,1,3,4,5,5,5,5,1,5,4,0,0.0,satisfied +90666,87747,Female,disloyal Customer,38,Business travel,Business,143,4,4,4,4,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +90667,117676,Male,Loyal Customer,47,Business travel,Business,1814,5,5,5,5,5,4,5,5,5,5,5,5,5,3,5,2.0,satisfied +90668,7910,Male,disloyal Customer,18,Business travel,Eco,1020,3,3,3,4,1,3,1,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +90669,67814,Female,disloyal Customer,36,Business travel,Eco,1038,2,2,2,3,5,2,2,5,1,2,4,3,4,5,3,12.0,neutral or dissatisfied +90670,124341,Female,disloyal Customer,23,Business travel,Business,1037,0,0,0,2,3,0,3,3,3,5,5,4,5,3,0,0.0,satisfied +90671,123328,Female,Loyal Customer,42,Business travel,Eco Plus,250,5,2,1,2,5,5,2,5,5,5,5,5,5,4,0,0.0,satisfied +90672,41537,Female,Loyal Customer,31,Business travel,Business,1211,3,3,3,3,5,5,5,5,1,2,1,5,5,5,0,0.0,satisfied +90673,27449,Female,disloyal Customer,32,Business travel,Eco,937,1,1,1,3,1,1,3,1,1,1,4,2,3,1,0,0.0,neutral or dissatisfied +90674,3343,Female,Loyal Customer,42,Business travel,Business,2578,2,2,2,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +90675,115973,Female,Loyal Customer,50,Personal Travel,Eco,372,2,2,2,3,4,3,4,4,4,2,4,2,4,4,2,7.0,neutral or dissatisfied +90676,3003,Female,Loyal Customer,43,Business travel,Business,987,5,5,5,5,5,4,5,5,5,5,5,4,5,5,0,11.0,satisfied +90677,51911,Male,Loyal Customer,19,Personal Travel,Eco,601,4,5,4,4,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +90678,128207,Male,Loyal Customer,45,Business travel,Business,2889,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +90679,43989,Female,disloyal Customer,38,Business travel,Eco,334,4,0,4,4,1,4,1,1,4,2,3,1,4,1,17,7.0,satisfied +90680,80396,Male,Loyal Customer,67,Personal Travel,Eco,422,3,3,3,3,5,3,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +90681,87768,Male,disloyal Customer,49,Business travel,Business,214,3,3,3,4,4,3,4,4,4,4,5,3,5,4,0,0.0,satisfied +90682,102536,Male,Loyal Customer,26,Personal Travel,Eco,223,1,5,1,2,1,1,1,1,4,2,5,3,4,1,1,0.0,neutral or dissatisfied +90683,93868,Female,disloyal Customer,29,Business travel,Eco,588,2,1,2,3,2,2,2,2,2,3,3,4,3,2,0,0.0,neutral or dissatisfied +90684,51404,Female,Loyal Customer,45,Personal Travel,Eco Plus,156,3,5,3,3,3,5,5,3,5,5,5,5,5,5,160,155.0,neutral or dissatisfied +90685,93797,Female,disloyal Customer,29,Business travel,Eco,1259,3,3,3,3,5,3,5,5,2,5,3,1,3,5,25,33.0,neutral or dissatisfied +90686,61966,Female,Loyal Customer,57,Business travel,Business,2400,2,2,2,2,5,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +90687,18826,Male,disloyal Customer,24,Business travel,Eco,448,3,0,3,2,2,3,4,2,1,4,4,1,4,2,2,9.0,neutral or dissatisfied +90688,97503,Female,Loyal Customer,41,Personal Travel,Eco,822,3,5,3,1,5,3,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +90689,16721,Female,Loyal Customer,48,Business travel,Business,2348,5,5,5,5,5,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +90690,43714,Male,Loyal Customer,34,Personal Travel,Eco,196,2,4,2,1,1,2,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +90691,16618,Female,Loyal Customer,24,Personal Travel,Eco,1008,2,4,1,5,3,1,3,3,3,2,5,5,4,3,43,56.0,neutral or dissatisfied +90692,2332,Female,Loyal Customer,62,Personal Travel,Eco,630,3,5,3,5,2,3,1,1,1,3,2,1,1,2,27,21.0,neutral or dissatisfied +90693,94834,Female,Loyal Customer,46,Business travel,Business,239,3,4,4,4,1,4,3,3,3,2,3,2,3,4,9,6.0,neutral or dissatisfied +90694,111376,Male,Loyal Customer,35,Business travel,Eco,1111,2,1,1,1,2,3,2,2,4,3,3,2,4,2,11,26.0,neutral or dissatisfied +90695,69091,Female,Loyal Customer,41,Personal Travel,Eco,1389,4,4,4,2,4,4,4,4,4,4,4,3,5,4,56,66.0,neutral or dissatisfied +90696,11510,Female,Loyal Customer,56,Personal Travel,Eco Plus,201,2,5,2,4,4,5,4,3,3,2,2,1,3,5,0,0.0,neutral or dissatisfied +90697,11327,Male,Loyal Customer,27,Personal Travel,Eco,229,4,4,4,3,1,4,1,1,5,3,5,4,5,1,44,48.0,neutral or dissatisfied +90698,33179,Male,Loyal Customer,37,Business travel,Eco Plus,101,4,5,5,5,4,4,4,4,1,5,5,4,4,4,0,11.0,satisfied +90699,108439,Male,Loyal Customer,27,Business travel,Business,1440,2,2,2,2,4,4,4,4,4,3,4,3,5,4,15,28.0,satisfied +90700,128708,Female,Loyal Customer,67,Business travel,Business,2042,1,2,2,2,3,2,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +90701,22581,Male,Loyal Customer,35,Business travel,Business,300,4,4,4,4,5,2,2,4,4,4,4,3,4,1,0,0.0,satisfied +90702,39306,Male,Loyal Customer,33,Personal Travel,Eco,67,3,5,3,4,4,3,4,4,3,5,4,4,4,4,7,0.0,neutral or dissatisfied +90703,16946,Male,Loyal Customer,51,Personal Travel,Eco,820,2,2,2,3,3,2,3,3,2,1,3,2,3,3,0,0.0,neutral or dissatisfied +90704,31404,Male,Loyal Customer,45,Personal Travel,Eco Plus,1199,3,4,3,4,1,3,1,1,4,4,3,2,3,1,3,22.0,neutral or dissatisfied +90705,80634,Male,Loyal Customer,38,Business travel,Business,282,0,0,0,1,5,5,4,3,3,2,2,4,3,5,0,0.0,satisfied +90706,54141,Male,Loyal Customer,43,Business travel,Business,1400,4,4,4,4,1,3,4,4,4,4,4,2,4,2,0,0.0,satisfied +90707,71045,Male,Loyal Customer,23,Business travel,Business,1671,3,3,3,3,3,3,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +90708,71800,Female,Loyal Customer,49,Business travel,Business,1723,3,3,4,3,3,4,4,5,5,5,5,5,5,5,30,15.0,satisfied +90709,72050,Female,disloyal Customer,23,Business travel,Business,1179,4,0,4,3,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +90710,117436,Male,Loyal Customer,52,Business travel,Business,3271,4,4,4,4,2,4,5,5,5,5,5,4,5,4,17,46.0,satisfied +90711,63313,Male,disloyal Customer,18,Business travel,Eco,337,2,0,2,3,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +90712,98927,Male,Loyal Customer,30,Business travel,Business,1835,2,3,3,3,2,2,2,2,3,2,3,1,2,2,0,0.0,neutral or dissatisfied +90713,95133,Male,Loyal Customer,10,Personal Travel,Eco,562,1,5,1,5,2,1,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +90714,47053,Male,Loyal Customer,54,Business travel,Eco,639,2,5,5,5,2,2,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +90715,48671,Male,disloyal Customer,42,Business travel,Business,209,4,4,4,1,3,4,3,3,4,5,5,3,4,3,0,0.0,satisfied +90716,54254,Male,Loyal Customer,25,Personal Travel,Eco,1222,0,1,0,3,2,0,2,2,3,5,2,1,4,2,0,0.0,satisfied +90717,21228,Male,Loyal Customer,15,Personal Travel,Eco,317,5,5,3,1,5,3,5,5,5,2,5,5,1,5,8,0.0,satisfied +90718,85568,Male,Loyal Customer,55,Business travel,Business,2520,5,4,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +90719,4617,Male,Loyal Customer,46,Personal Travel,Eco,719,3,5,3,2,2,3,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +90720,91352,Female,Loyal Customer,16,Personal Travel,Eco Plus,404,2,4,2,2,2,2,3,2,3,5,4,5,4,2,32,26.0,neutral or dissatisfied +90721,103486,Female,disloyal Customer,20,Business travel,Eco,440,1,1,1,4,4,1,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +90722,96870,Male,disloyal Customer,35,Business travel,Eco,957,1,1,1,4,5,1,5,5,3,5,3,3,3,5,34,25.0,neutral or dissatisfied +90723,17713,Male,disloyal Customer,27,Business travel,Business,383,4,4,4,4,1,4,1,1,5,3,5,4,5,1,8,4.0,satisfied +90724,119509,Female,Loyal Customer,45,Business travel,Business,892,3,5,3,5,4,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +90725,82430,Male,Loyal Customer,58,Business travel,Business,2696,3,3,2,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +90726,60325,Female,Loyal Customer,40,Business travel,Business,2010,4,4,4,4,4,4,5,2,2,3,2,3,2,4,7,14.0,satisfied +90727,108716,Female,Loyal Customer,50,Business travel,Business,321,3,3,5,3,2,5,5,5,5,5,5,4,5,5,66,53.0,satisfied +90728,112639,Male,Loyal Customer,16,Personal Travel,Eco Plus,602,2,5,2,3,4,2,4,4,3,4,5,5,5,4,11,11.0,neutral or dissatisfied +90729,89583,Female,Loyal Customer,50,Business travel,Business,1096,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,49.0,satisfied +90730,17085,Male,Loyal Customer,27,Business travel,Business,3738,3,3,3,3,5,4,5,5,1,2,1,3,2,5,79,99.0,satisfied +90731,106352,Female,Loyal Customer,48,Business travel,Business,1902,3,3,3,3,5,5,5,5,5,5,5,4,5,5,16,0.0,satisfied +90732,81783,Female,Loyal Customer,35,Business travel,Eco,1306,2,1,1,1,2,2,2,2,3,5,4,1,4,2,9,0.0,neutral or dissatisfied +90733,69409,Male,Loyal Customer,62,Business travel,Business,2767,2,2,4,4,5,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +90734,4997,Male,disloyal Customer,22,Business travel,Eco,502,2,1,1,3,5,1,2,5,2,4,2,4,3,5,0,9.0,neutral or dissatisfied +90735,14591,Male,Loyal Customer,31,Personal Travel,Eco,986,3,4,3,2,3,3,2,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +90736,124796,Female,Loyal Customer,54,Business travel,Business,1841,3,1,3,3,4,5,5,5,5,5,5,5,5,5,1,10.0,satisfied +90737,102888,Female,Loyal Customer,42,Business travel,Business,2256,1,1,1,1,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +90738,32597,Male,Loyal Customer,55,Business travel,Eco,102,4,1,1,1,4,4,4,4,1,1,5,4,4,4,0,0.0,satisfied +90739,80643,Male,Loyal Customer,57,Business travel,Business,1591,2,2,2,2,2,4,5,5,5,5,5,4,5,4,1,5.0,satisfied +90740,22275,Male,Loyal Customer,47,Business travel,Eco,143,5,1,1,1,5,5,5,5,5,4,3,3,2,5,17,11.0,satisfied +90741,80547,Female,Loyal Customer,52,Business travel,Business,1747,3,3,2,3,5,5,4,4,4,4,4,3,4,4,0,2.0,satisfied +90742,11523,Male,Loyal Customer,35,Personal Travel,Eco Plus,482,4,3,4,4,1,4,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +90743,121917,Female,Loyal Customer,31,Personal Travel,Eco,366,3,1,3,4,1,3,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +90744,86373,Female,Loyal Customer,40,Business travel,Business,1760,5,3,5,5,3,4,5,5,5,5,5,3,5,5,2,2.0,satisfied +90745,6429,Male,Loyal Customer,21,Personal Travel,Eco,240,3,5,3,3,4,3,2,4,4,4,4,5,5,4,3,2.0,neutral or dissatisfied +90746,74319,Male,Loyal Customer,46,Business travel,Business,3733,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +90747,121087,Female,Loyal Customer,47,Personal Travel,Eco,196,4,4,4,1,2,5,5,3,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +90748,129004,Female,disloyal Customer,17,Business travel,Eco,2704,3,3,3,3,1,3,1,1,2,4,4,1,3,1,0,,neutral or dissatisfied +90749,49399,Female,Loyal Customer,46,Business travel,Business,2360,3,5,5,5,1,3,3,1,1,1,3,2,1,4,17,17.0,neutral or dissatisfied +90750,121546,Female,disloyal Customer,32,Business travel,Business,912,2,2,2,1,2,2,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +90751,109694,Female,disloyal Customer,42,Business travel,Business,802,2,2,2,4,3,2,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +90752,43422,Male,Loyal Customer,32,Personal Travel,Eco Plus,358,2,5,2,1,5,2,5,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +90753,83622,Female,Loyal Customer,66,Personal Travel,Eco,409,4,4,4,1,2,1,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +90754,24276,Male,Loyal Customer,59,Personal Travel,Eco,170,1,4,1,3,5,1,5,5,3,2,5,3,5,5,0,6.0,neutral or dissatisfied +90755,72209,Male,Loyal Customer,44,Personal Travel,Eco,2724,2,5,2,4,2,3,3,3,5,3,4,3,4,3,5,0.0,neutral or dissatisfied +90756,68963,Female,Loyal Customer,49,Business travel,Business,2385,1,1,1,1,5,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +90757,113476,Female,disloyal Customer,20,Business travel,Business,258,4,3,4,3,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +90758,122021,Male,Loyal Customer,30,Business travel,Eco,130,4,5,5,5,4,4,4,4,3,1,3,3,4,4,0,3.0,neutral or dissatisfied +90759,60283,Male,Loyal Customer,25,Business travel,Business,2218,2,2,2,2,4,4,4,4,5,5,5,4,5,4,11,0.0,satisfied +90760,109879,Male,disloyal Customer,49,Business travel,Business,1165,3,3,3,3,3,3,5,3,3,4,4,1,4,3,5,4.0,neutral or dissatisfied +90761,113226,Female,disloyal Customer,54,Business travel,Business,397,5,5,5,3,5,5,3,5,4,4,4,5,4,5,2,0.0,satisfied +90762,59589,Male,Loyal Customer,54,Business travel,Business,1582,4,4,4,4,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +90763,4415,Male,Loyal Customer,60,Business travel,Business,762,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +90764,44733,Male,Loyal Customer,53,Business travel,Eco Plus,67,4,3,3,3,4,4,4,4,2,2,3,1,1,4,7,10.0,satisfied +90765,85284,Male,Loyal Customer,60,Personal Travel,Eco,813,2,0,2,3,1,2,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +90766,13485,Female,Loyal Customer,13,Personal Travel,Business,106,3,5,0,1,3,0,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +90767,52672,Female,Loyal Customer,55,Personal Travel,Eco,110,2,1,0,3,2,2,3,1,1,0,1,2,1,4,0,0.0,neutral or dissatisfied +90768,65432,Male,Loyal Customer,43,Personal Travel,Eco,2165,3,4,3,4,2,3,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +90769,2636,Male,Loyal Customer,41,Business travel,Business,3955,4,5,4,4,2,5,5,4,4,4,4,3,4,5,3,0.0,satisfied +90770,84707,Female,Loyal Customer,55,Business travel,Business,481,2,2,3,3,4,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +90771,53385,Female,Loyal Customer,28,Personal Travel,Eco,1452,3,4,3,3,1,3,1,1,1,2,4,4,3,1,0,0.0,neutral or dissatisfied +90772,18316,Male,Loyal Customer,25,Business travel,Business,715,3,3,3,3,3,4,3,3,1,4,2,1,2,3,124,110.0,satisfied +90773,125190,Female,Loyal Customer,38,Business travel,Business,651,2,4,2,2,5,5,5,4,4,4,4,5,4,5,4,0.0,satisfied +90774,7407,Male,Loyal Customer,22,Business travel,Business,3754,2,2,2,2,4,4,4,4,3,3,4,5,4,4,34,38.0,satisfied +90775,35347,Female,disloyal Customer,35,Business travel,Eco,1047,3,3,3,3,3,3,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +90776,28316,Male,Loyal Customer,35,Business travel,Business,2065,2,1,1,1,4,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +90777,14431,Female,Loyal Customer,29,Personal Travel,Business,674,2,4,2,2,5,2,5,5,5,4,4,3,4,5,21,19.0,neutral or dissatisfied +90778,82221,Male,disloyal Customer,30,Business travel,Eco,405,2,4,2,3,3,2,2,3,2,1,3,4,4,3,0,0.0,neutral or dissatisfied +90779,124004,Female,disloyal Customer,37,Business travel,Eco,184,3,1,3,3,1,3,1,1,4,1,3,1,3,1,19,15.0,neutral or dissatisfied +90780,36214,Female,disloyal Customer,36,Business travel,Eco,280,1,2,1,3,4,1,2,4,2,5,2,4,3,4,0,0.0,neutral or dissatisfied +90781,49757,Female,disloyal Customer,21,Business travel,Business,373,4,0,4,1,2,4,2,2,5,5,4,2,1,2,10,13.0,satisfied +90782,125390,Female,disloyal Customer,22,Business travel,Eco,761,3,3,3,4,3,3,3,3,2,5,3,2,3,3,12,57.0,neutral or dissatisfied +90783,79292,Female,disloyal Customer,42,Business travel,Business,2248,1,1,1,5,2,1,3,2,3,2,5,4,4,2,7,0.0,neutral or dissatisfied +90784,108312,Male,disloyal Customer,30,Business travel,Business,1325,5,5,5,3,4,5,4,4,4,2,4,5,4,4,4,0.0,satisfied +90785,5943,Female,Loyal Customer,16,Personal Travel,Eco Plus,212,3,1,3,4,3,3,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +90786,3008,Male,disloyal Customer,23,Business travel,Business,987,5,0,5,3,1,5,1,1,3,3,4,3,4,1,0,0.0,satisfied +90787,37712,Female,Loyal Customer,51,Personal Travel,Eco,1035,4,4,4,3,4,5,5,3,3,4,3,5,3,4,51,61.0,neutral or dissatisfied +90788,8222,Male,Loyal Customer,20,Personal Travel,Eco,402,1,4,1,4,3,1,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +90789,119606,Male,Loyal Customer,65,Personal Travel,Eco,1979,3,5,3,3,2,3,2,2,3,5,5,4,4,2,3,0.0,neutral or dissatisfied +90790,3887,Female,Loyal Customer,58,Business travel,Business,3708,0,4,0,2,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +90791,104907,Female,Loyal Customer,34,Personal Travel,Eco,1565,2,5,2,3,3,2,3,3,5,4,5,4,5,3,0,18.0,neutral or dissatisfied +90792,78350,Female,Loyal Customer,32,Personal Travel,Eco,1547,1,5,1,3,3,1,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +90793,39884,Female,Loyal Customer,54,Personal Travel,Eco,221,3,5,3,1,1,3,3,4,4,3,4,1,4,2,0,8.0,neutral or dissatisfied +90794,36391,Male,disloyal Customer,30,Business travel,Eco,870,3,3,3,1,3,2,5,5,5,3,3,5,4,5,118,153.0,neutral or dissatisfied +90795,12712,Female,Loyal Customer,29,Business travel,Business,1875,4,4,4,4,4,4,4,4,4,2,3,1,1,4,0,0.0,satisfied +90796,50617,Female,Loyal Customer,53,Personal Travel,Eco,373,4,4,4,3,3,5,5,5,5,4,5,5,5,4,7,0.0,satisfied +90797,77240,Female,Loyal Customer,41,Business travel,Business,1590,5,5,5,5,5,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +90798,43827,Male,Loyal Customer,46,Business travel,Business,1731,2,2,2,2,3,1,4,5,5,4,5,4,5,4,0,0.0,satisfied +90799,110631,Male,Loyal Customer,23,Personal Travel,Eco,727,2,3,2,2,2,2,2,2,2,2,1,1,4,2,0,0.0,neutral or dissatisfied +90800,40381,Female,Loyal Customer,20,Personal Travel,Eco,1250,2,3,2,4,2,2,2,2,2,2,3,3,4,2,13,0.0,neutral or dissatisfied +90801,18731,Female,Loyal Customer,43,Personal Travel,Business,1167,4,4,4,3,3,4,4,2,2,4,2,1,2,3,0,0.0,neutral or dissatisfied +90802,75649,Male,Loyal Customer,56,Business travel,Business,3397,3,1,1,1,5,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +90803,44837,Male,Loyal Customer,32,Personal Travel,Eco Plus,462,2,3,2,2,1,2,1,1,4,2,4,1,4,1,46,61.0,neutral or dissatisfied +90804,122031,Male,Loyal Customer,57,Business travel,Business,130,5,5,5,5,5,4,5,4,4,4,5,3,4,4,31,25.0,satisfied +90805,79767,Male,disloyal Customer,50,Business travel,Business,1096,5,5,5,4,1,5,1,1,4,5,5,5,4,1,0,0.0,satisfied +90806,40498,Female,Loyal Customer,40,Personal Travel,Eco,461,3,4,3,1,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +90807,93398,Female,Loyal Customer,17,Business travel,Business,671,4,4,4,4,4,4,4,4,5,5,4,3,5,4,0,12.0,satisfied +90808,22763,Male,Loyal Customer,24,Business travel,Business,302,0,0,0,4,4,4,4,4,3,3,3,1,3,4,0,0.0,satisfied +90809,57002,Female,Loyal Customer,38,Personal Travel,Eco,2454,3,2,3,2,3,3,3,2,2,3,2,3,3,3,0,14.0,neutral or dissatisfied +90810,99221,Male,Loyal Customer,33,Business travel,Eco,541,1,2,2,2,1,1,1,1,4,3,3,1,3,1,0,8.0,neutral or dissatisfied +90811,1961,Female,Loyal Customer,65,Business travel,Business,1888,5,3,5,5,2,1,2,4,4,4,4,3,4,3,1,2.0,satisfied +90812,126950,Female,disloyal Customer,62,Business travel,Business,647,1,1,1,1,2,1,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +90813,704,Male,Loyal Customer,55,Business travel,Business,2900,0,1,1,4,2,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +90814,48863,Male,Loyal Customer,53,Business travel,Eco,337,4,3,3,3,4,4,4,4,4,4,5,3,3,4,17,11.0,satisfied +90815,72908,Female,Loyal Customer,41,Business travel,Business,3635,2,2,2,2,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +90816,90719,Female,Loyal Customer,47,Business travel,Business,406,4,4,4,4,4,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +90817,88051,Female,Loyal Customer,45,Business travel,Business,545,3,3,3,3,2,5,4,5,5,5,5,5,5,4,39,33.0,satisfied +90818,16571,Female,Loyal Customer,10,Business travel,Business,872,1,4,4,4,2,1,1,1,5,3,3,1,4,1,277,345.0,neutral or dissatisfied +90819,41363,Female,Loyal Customer,56,Business travel,Eco,563,5,4,4,4,5,5,5,5,5,5,5,2,5,5,0,0.0,satisfied +90820,117457,Female,Loyal Customer,61,Personal Travel,Eco,1107,2,4,2,1,4,4,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +90821,105342,Female,disloyal Customer,45,Business travel,Business,452,5,4,4,2,3,5,3,3,4,3,4,4,5,3,21,6.0,satisfied +90822,198,Male,disloyal Customer,57,Business travel,Business,213,4,4,4,5,3,4,3,3,5,3,4,4,5,3,0,0.0,satisfied +90823,106593,Female,Loyal Customer,50,Personal Travel,Business,986,2,5,1,5,5,4,5,4,4,1,4,5,4,5,0,5.0,neutral or dissatisfied +90824,46367,Female,disloyal Customer,49,Business travel,Eco,1013,1,1,1,4,3,1,3,3,1,5,3,3,3,3,47,45.0,neutral or dissatisfied +90825,129509,Female,Loyal Customer,26,Personal Travel,Eco,1846,4,4,4,3,3,4,3,3,4,2,5,4,1,3,0,6.0,neutral or dissatisfied +90826,58159,Female,Loyal Customer,59,Business travel,Business,2202,2,2,2,2,4,4,5,5,5,5,5,3,5,5,10,11.0,satisfied +90827,78799,Female,disloyal Customer,27,Business travel,Eco,154,2,3,2,4,1,2,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +90828,4151,Female,Loyal Customer,46,Business travel,Business,427,3,3,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +90829,25793,Male,Loyal Customer,56,Business travel,Eco,762,2,4,4,4,2,2,2,2,4,4,4,4,3,2,0,0.0,neutral or dissatisfied +90830,70000,Female,Loyal Customer,38,Personal Travel,Eco,236,2,5,0,4,2,0,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +90831,72246,Male,Loyal Customer,52,Business travel,Business,3311,3,3,2,3,4,4,5,4,4,4,4,3,4,4,1,3.0,satisfied +90832,8413,Male,Loyal Customer,41,Business travel,Business,862,5,5,5,5,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +90833,15228,Male,Loyal Customer,30,Business travel,Business,529,3,3,3,3,5,5,5,5,4,2,5,4,5,5,108,84.0,satisfied +90834,39875,Female,Loyal Customer,26,Personal Travel,Eco,221,0,2,0,4,5,0,5,5,2,5,3,4,3,5,0,0.0,satisfied +90835,32180,Male,disloyal Customer,47,Business travel,Eco,101,3,0,3,4,4,3,4,4,5,1,2,3,3,4,0,0.0,neutral or dissatisfied +90836,127740,Male,Loyal Customer,32,Business travel,Business,3998,4,4,4,4,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +90837,50761,Female,Loyal Customer,16,Personal Travel,Eco,109,1,2,1,2,2,1,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +90838,23007,Male,Loyal Customer,10,Personal Travel,Eco,489,3,0,4,3,2,4,3,2,5,2,5,4,4,2,0,10.0,neutral or dissatisfied +90839,32313,Male,Loyal Customer,45,Business travel,Business,3178,5,5,5,5,4,1,1,4,4,4,5,4,4,2,8,7.0,satisfied +90840,23943,Male,Loyal Customer,48,Business travel,Business,936,5,5,5,5,1,5,5,5,5,5,5,2,5,3,12,0.0,satisfied +90841,112044,Female,Loyal Customer,27,Business travel,Eco,1015,1,4,4,4,1,1,1,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +90842,64425,Female,Loyal Customer,27,Business travel,Business,3729,2,2,5,2,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +90843,128788,Female,disloyal Customer,30,Business travel,Business,1288,4,4,4,1,4,1,1,3,5,5,5,1,5,1,0,3.0,satisfied +90844,32901,Female,Loyal Customer,45,Personal Travel,Eco,163,3,2,0,4,3,3,4,2,2,0,2,1,2,3,0,0.0,neutral or dissatisfied +90845,81601,Male,Loyal Customer,51,Business travel,Eco,349,3,3,3,3,3,3,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +90846,57079,Male,Loyal Customer,42,Business travel,Business,1519,4,4,4,4,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +90847,1167,Female,Loyal Customer,13,Personal Travel,Eco,164,2,4,2,3,2,1,1,5,5,5,5,1,5,1,291,317.0,neutral or dissatisfied +90848,62620,Male,Loyal Customer,45,Personal Travel,Eco,1744,2,4,2,5,3,2,3,3,4,4,4,4,4,3,32,22.0,neutral or dissatisfied +90849,49205,Female,Loyal Customer,31,Business travel,Business,3123,4,4,2,4,4,4,4,4,4,2,1,1,4,4,10,0.0,satisfied +90850,641,Male,Loyal Customer,58,Business travel,Business,3585,3,3,3,3,1,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +90851,69391,Male,Loyal Customer,22,Business travel,Business,3533,5,5,5,5,3,4,3,3,5,5,5,5,4,3,61,80.0,satisfied +90852,8525,Male,Loyal Customer,23,Personal Travel,Eco,862,3,4,3,2,3,3,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +90853,24816,Female,Loyal Customer,56,Business travel,Eco,991,3,2,2,2,4,2,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +90854,56216,Female,Loyal Customer,45,Business travel,Business,1585,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +90855,129569,Female,Loyal Customer,41,Business travel,Business,2218,5,4,5,5,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +90856,72301,Female,Loyal Customer,29,Personal Travel,Eco,919,4,5,4,5,3,4,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +90857,83380,Male,Loyal Customer,66,Personal Travel,Eco,1124,4,1,4,4,2,4,2,2,1,3,2,3,3,2,0,0.0,satisfied +90858,90150,Male,disloyal Customer,63,Business travel,Eco,583,2,0,2,4,2,2,2,5,5,5,5,2,5,2,217,217.0,neutral or dissatisfied +90859,82736,Female,Loyal Customer,59,Business travel,Business,1925,2,4,4,4,1,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +90860,116318,Male,Loyal Customer,60,Personal Travel,Eco,371,3,1,3,3,4,3,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +90861,23925,Male,Loyal Customer,21,Personal Travel,Eco,579,3,4,3,3,3,3,2,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +90862,108778,Male,Loyal Customer,59,Business travel,Business,545,4,5,5,5,4,4,4,4,4,4,4,1,4,3,11,0.0,neutral or dissatisfied +90863,44321,Male,Loyal Customer,47,Personal Travel,Eco,318,1,5,1,3,4,1,4,4,5,5,3,3,1,4,0,0.0,neutral or dissatisfied +90864,93082,Male,Loyal Customer,29,Business travel,Business,2515,1,1,1,1,1,1,1,1,1,1,3,1,4,1,35,37.0,neutral or dissatisfied +90865,34834,Male,Loyal Customer,37,Business travel,Eco Plus,264,2,2,2,2,2,2,2,2,2,1,4,2,4,2,7,0.0,neutral or dissatisfied +90866,86999,Female,Loyal Customer,29,Personal Travel,Eco,907,2,5,2,4,2,2,2,2,5,5,5,3,4,2,0,1.0,neutral or dissatisfied +90867,41422,Female,Loyal Customer,24,Personal Travel,Eco,913,3,4,3,3,5,3,5,5,3,4,4,5,4,5,4,10.0,neutral or dissatisfied +90868,16659,Male,disloyal Customer,52,Business travel,Eco,488,2,3,2,4,3,2,3,3,1,3,3,1,3,3,0,0.0,neutral or dissatisfied +90869,14808,Female,disloyal Customer,40,Business travel,Business,95,5,5,5,4,2,5,2,2,1,3,2,4,1,2,3,16.0,satisfied +90870,8373,Female,disloyal Customer,26,Business travel,Eco,773,4,4,4,3,5,4,5,5,3,5,4,4,3,5,0,0.0,neutral or dissatisfied +90871,52149,Male,Loyal Customer,51,Business travel,Business,455,1,5,5,5,1,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +90872,13048,Female,Loyal Customer,49,Personal Travel,Eco,374,3,4,3,5,3,3,1,5,5,3,5,4,5,1,6,3.0,neutral or dissatisfied +90873,91238,Female,Loyal Customer,15,Personal Travel,Eco,442,4,4,4,4,3,4,3,3,5,4,5,3,5,3,3,0.0,neutral or dissatisfied +90874,85777,Male,Loyal Customer,67,Business travel,Eco,666,3,3,3,3,3,3,3,2,3,4,3,3,4,3,149,132.0,neutral or dissatisfied +90875,90419,Male,Loyal Customer,54,Business travel,Business,270,2,2,4,2,5,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +90876,16558,Male,Loyal Customer,39,Business travel,Eco,872,4,5,5,5,4,4,4,5,3,4,2,4,5,4,137,127.0,satisfied +90877,114081,Male,Loyal Customer,61,Business travel,Business,1947,1,3,3,3,1,3,2,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +90878,26894,Male,Loyal Customer,24,Personal Travel,Eco,689,1,5,1,5,1,1,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +90879,21436,Male,Loyal Customer,52,Business travel,Eco,164,4,4,4,4,5,4,5,5,3,2,2,2,4,5,43,39.0,satisfied +90880,77205,Female,disloyal Customer,25,Business travel,Eco,2994,2,2,2,4,2,4,2,2,1,4,4,2,3,2,306,278.0,neutral or dissatisfied +90881,26683,Male,Loyal Customer,47,Personal Travel,Eco,515,4,4,4,1,4,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +90882,100457,Male,Loyal Customer,43,Business travel,Business,2011,2,2,2,2,5,5,5,4,4,4,4,5,4,3,17,8.0,satisfied +90883,24740,Male,Loyal Customer,35,Business travel,Eco,447,1,3,3,3,1,2,1,1,4,1,2,4,5,1,0,0.0,satisfied +90884,125396,Male,Loyal Customer,54,Business travel,Business,1790,5,5,5,5,2,5,2,2,2,2,2,4,2,3,0,0.0,satisfied +90885,37938,Female,Loyal Customer,7,Personal Travel,Eco,1065,4,5,4,2,2,4,2,2,5,2,5,4,4,2,2,0.0,neutral or dissatisfied +90886,126416,Female,Loyal Customer,49,Business travel,Business,2146,1,1,2,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +90887,82557,Female,Loyal Customer,53,Business travel,Business,2243,1,1,1,1,5,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +90888,71259,Female,Loyal Customer,36,Personal Travel,Eco,733,5,3,5,2,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +90889,28446,Female,disloyal Customer,28,Business travel,Eco Plus,2496,3,3,3,4,3,4,4,2,2,2,3,4,4,4,0,0.0,neutral or dissatisfied +90890,85650,Female,Loyal Customer,54,Personal Travel,Eco Plus,259,2,4,2,4,3,4,5,1,1,2,1,1,1,5,76,67.0,neutral or dissatisfied +90891,81855,Male,Loyal Customer,27,Business travel,Business,1416,2,2,2,2,5,5,5,5,5,3,4,4,4,5,5,34.0,satisfied +90892,48021,Female,Loyal Customer,35,Business travel,Business,1630,3,3,3,3,4,1,2,5,5,5,5,4,5,3,0,0.0,satisfied +90893,111978,Male,Loyal Customer,16,Personal Travel,Eco,770,3,5,3,4,4,3,4,4,3,3,4,5,5,4,48,44.0,neutral or dissatisfied +90894,28558,Male,Loyal Customer,38,Business travel,Eco Plus,2640,5,5,5,5,5,5,5,5,2,2,5,4,3,5,0,0.0,satisfied +90895,6136,Female,disloyal Customer,47,Business travel,Eco,409,1,4,1,4,4,1,4,4,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +90896,48031,Male,Loyal Customer,68,Personal Travel,Eco,1187,2,1,2,2,2,2,2,2,2,5,2,1,1,2,0,0.0,neutral or dissatisfied +90897,48094,Female,Loyal Customer,25,Business travel,Business,414,5,5,5,5,4,4,4,4,3,5,4,5,4,4,6,21.0,satisfied +90898,41682,Male,Loyal Customer,30,Personal Travel,Eco,347,3,5,5,4,3,5,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +90899,37015,Male,Loyal Customer,69,Personal Travel,Eco,759,2,4,2,4,2,2,2,2,3,4,4,4,5,2,4,0.0,neutral or dissatisfied +90900,12590,Female,disloyal Customer,17,Business travel,Eco,542,2,4,2,3,5,2,5,5,3,1,4,4,3,5,0,0.0,neutral or dissatisfied +90901,11669,Male,Loyal Customer,67,Personal Travel,Eco,1117,2,2,2,3,5,2,5,5,2,2,3,4,2,5,0,0.0,neutral or dissatisfied +90902,31471,Female,Loyal Customer,46,Business travel,Eco,853,4,1,5,1,1,5,5,4,4,4,4,4,4,4,17,0.0,satisfied +90903,124043,Male,Loyal Customer,54,Business travel,Business,3304,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +90904,113679,Male,Loyal Customer,54,Personal Travel,Eco,414,1,2,1,4,1,4,4,3,4,4,4,4,1,4,178,165.0,neutral or dissatisfied +90905,5333,Female,Loyal Customer,47,Business travel,Business,812,5,5,5,5,2,5,5,4,4,4,4,4,4,4,124,112.0,satisfied +90906,104166,Female,Loyal Customer,46,Business travel,Eco,349,3,4,4,4,2,1,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +90907,124835,Female,Loyal Customer,62,Personal Travel,Eco,280,1,4,1,3,4,4,4,4,4,1,4,4,4,3,0,4.0,neutral or dissatisfied +90908,23575,Female,Loyal Customer,20,Business travel,Business,792,3,3,3,3,4,4,4,4,3,3,1,1,3,4,6,0.0,satisfied +90909,104709,Female,disloyal Customer,31,Business travel,Eco,779,2,2,2,4,2,2,2,2,1,4,2,1,3,2,36,23.0,neutral or dissatisfied +90910,84645,Male,Loyal Customer,30,Personal Travel,Eco Plus,669,4,4,4,3,5,4,5,5,5,2,4,3,5,5,81,67.0,neutral or dissatisfied +90911,112904,Female,disloyal Customer,23,Business travel,Eco,1129,3,3,3,3,3,5,3,1,2,4,4,3,3,3,201,190.0,neutral or dissatisfied +90912,118881,Male,Loyal Customer,13,Personal Travel,Eco,1136,2,4,2,3,3,2,3,3,3,5,5,4,5,3,7,4.0,neutral or dissatisfied +90913,29930,Male,Loyal Customer,8,Business travel,Business,571,2,2,5,2,5,5,5,5,1,3,4,5,1,5,0,0.0,satisfied +90914,41529,Male,Loyal Customer,23,Business travel,Business,1211,2,2,2,2,4,4,4,4,2,3,5,5,1,4,13,0.0,satisfied +90915,67688,Female,Loyal Customer,22,Business travel,Business,3834,1,2,2,2,1,1,1,1,3,2,2,3,3,1,4,11.0,neutral or dissatisfied +90916,18022,Female,Loyal Customer,60,Business travel,Eco Plus,332,2,4,4,4,1,2,2,2,2,2,2,2,2,1,64,79.0,neutral or dissatisfied +90917,111205,Male,Loyal Customer,54,Business travel,Business,1546,1,1,1,1,4,4,5,4,4,4,4,3,4,3,15,21.0,satisfied +90918,114744,Female,Loyal Customer,52,Business travel,Eco,308,3,4,4,4,2,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +90919,64906,Male,Loyal Customer,51,Business travel,Business,190,3,3,3,3,5,4,4,5,5,5,4,4,5,4,0,0.0,satisfied +90920,115028,Female,Loyal Customer,45,Business travel,Business,2899,3,3,5,3,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +90921,94433,Female,Loyal Customer,70,Business travel,Business,2207,3,1,2,1,4,4,3,3,3,3,3,4,3,3,5,3.0,neutral or dissatisfied +90922,25334,Female,Loyal Customer,28,Personal Travel,Eco,837,2,4,2,4,4,2,4,4,4,4,4,5,5,4,7,0.0,neutral or dissatisfied +90923,122273,Male,Loyal Customer,32,Personal Travel,Eco,544,2,5,2,4,3,2,3,3,1,1,3,1,1,3,0,0.0,neutral or dissatisfied +90924,27211,Female,Loyal Customer,61,Personal Travel,Eco,2717,2,5,2,1,2,4,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +90925,37275,Male,Loyal Customer,31,Business travel,Business,1035,4,4,4,4,4,4,4,4,4,1,3,4,1,4,31,19.0,satisfied +90926,4433,Female,Loyal Customer,42,Business travel,Business,3670,2,1,1,1,4,3,4,2,2,2,2,3,2,3,0,9.0,neutral or dissatisfied +90927,26481,Male,Loyal Customer,39,Business travel,Eco Plus,925,4,4,4,4,4,4,4,4,2,1,2,5,3,4,0,0.0,satisfied +90928,87990,Female,Loyal Customer,47,Business travel,Business,581,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +90929,66379,Male,Loyal Customer,22,Business travel,Business,1562,3,3,3,3,4,4,4,4,4,4,5,5,5,4,21,0.0,satisfied +90930,12502,Female,Loyal Customer,14,Personal Travel,Eco Plus,192,2,5,0,4,4,0,4,4,5,4,5,5,5,4,10,8.0,neutral or dissatisfied +90931,96421,Male,Loyal Customer,55,Business travel,Business,1246,2,2,2,2,2,5,4,5,5,5,5,4,5,4,7,0.0,satisfied +90932,76787,Male,disloyal Customer,24,Business travel,Business,546,0,5,0,4,2,0,2,2,4,4,4,3,4,2,0,0.0,satisfied +90933,27544,Female,Loyal Customer,10,Personal Travel,Eco,954,3,1,3,2,3,3,3,3,2,5,1,1,1,3,0,0.0,neutral or dissatisfied +90934,58243,Male,disloyal Customer,25,Business travel,Business,925,3,4,3,2,3,3,5,3,4,2,5,4,5,3,6,10.0,neutral or dissatisfied +90935,105078,Male,Loyal Customer,34,Business travel,Business,2360,1,1,1,1,3,4,5,4,4,4,4,5,4,3,13,0.0,satisfied +90936,66227,Female,Loyal Customer,33,Business travel,Business,2067,3,4,4,4,4,3,4,3,3,4,3,4,3,3,57,73.0,neutral or dissatisfied +90937,32830,Female,Loyal Customer,23,Business travel,Eco,163,5,1,1,1,5,5,4,5,4,5,3,4,4,5,0,0.0,satisfied +90938,106079,Female,Loyal Customer,54,Business travel,Business,3516,5,5,3,5,3,5,5,5,5,5,5,5,5,3,106,104.0,satisfied +90939,103167,Male,Loyal Customer,54,Business travel,Business,272,0,0,0,4,4,5,5,3,3,3,3,4,3,3,12,3.0,satisfied +90940,49155,Female,disloyal Customer,39,Business travel,Business,373,4,4,4,4,1,4,1,1,3,1,2,4,4,1,17,15.0,satisfied +90941,77945,Female,Loyal Customer,32,Business travel,Business,214,3,3,3,3,4,4,5,4,4,3,4,4,5,4,0,0.0,satisfied +90942,50218,Female,Loyal Customer,55,Business travel,Eco,86,3,1,1,1,3,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +90943,124312,Female,Loyal Customer,31,Business travel,Business,1508,1,1,1,1,5,5,5,5,4,4,3,3,3,5,10,0.0,satisfied +90944,71173,Male,Loyal Customer,28,Business travel,Business,733,5,5,4,5,5,5,5,5,3,5,4,5,5,5,219,249.0,satisfied +90945,100455,Male,disloyal Customer,39,Business travel,Business,180,4,4,4,2,4,4,4,4,5,5,5,4,4,4,10,5.0,satisfied +90946,102914,Female,Loyal Customer,54,Business travel,Business,3428,5,5,5,5,3,5,5,4,4,4,4,5,4,5,41,21.0,satisfied +90947,18547,Female,Loyal Customer,22,Business travel,Business,192,5,5,5,5,5,5,3,5,2,4,4,4,1,5,4,2.0,satisfied +90948,20704,Female,Loyal Customer,35,Personal Travel,Eco,510,1,4,5,2,1,5,1,1,2,2,4,5,2,1,48,35.0,neutral or dissatisfied +90949,71001,Male,disloyal Customer,54,Business travel,Business,978,5,5,5,3,5,5,5,5,3,2,4,3,4,5,7,0.0,satisfied +90950,88020,Male,Loyal Customer,47,Business travel,Business,250,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +90951,92904,Female,Loyal Customer,49,Business travel,Business,3970,4,4,4,4,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +90952,71013,Male,disloyal Customer,7,Business travel,Eco,802,3,3,3,3,5,3,5,5,1,2,3,2,4,5,19,1.0,neutral or dissatisfied +90953,35599,Female,Loyal Customer,10,Business travel,Eco Plus,1010,3,1,1,1,3,4,1,3,1,5,4,3,4,3,0,0.0,neutral or dissatisfied +90954,128967,Male,Loyal Customer,46,Personal Travel,Eco,414,2,2,2,1,4,2,4,4,1,3,2,1,2,4,0,0.0,neutral or dissatisfied +90955,38180,Male,Loyal Customer,57,Personal Travel,Eco,1249,3,4,3,1,4,3,4,4,4,5,3,5,4,4,0,0.0,neutral or dissatisfied +90956,53014,Female,Loyal Customer,31,Business travel,Eco,1190,3,5,5,5,3,3,3,3,3,1,4,1,3,3,3,0.0,neutral or dissatisfied +90957,96938,Female,Loyal Customer,28,Business travel,Business,1975,2,2,2,2,4,4,4,4,4,4,4,3,5,4,72,59.0,satisfied +90958,113641,Female,Loyal Customer,53,Personal Travel,Eco,397,3,4,3,1,5,4,4,2,2,3,2,3,2,4,122,104.0,neutral or dissatisfied +90959,41038,Male,Loyal Customer,27,Business travel,Business,3875,3,3,3,3,5,5,5,5,1,4,4,5,2,5,0,0.0,satisfied +90960,129263,Female,Loyal Customer,45,Business travel,Business,2521,2,2,2,2,3,3,5,4,4,4,4,4,4,4,20,10.0,satisfied +90961,17743,Female,disloyal Customer,22,Business travel,Business,101,4,1,4,3,5,4,5,5,1,1,3,4,4,5,0,0.0,neutral or dissatisfied +90962,60410,Female,Loyal Customer,59,Personal Travel,Eco,1452,1,1,0,4,4,3,3,3,3,0,3,1,3,4,83,90.0,neutral or dissatisfied +90963,84075,Male,Loyal Customer,30,Business travel,Business,879,1,5,5,5,1,1,1,1,1,3,4,1,4,1,0,5.0,neutral or dissatisfied +90964,111711,Male,Loyal Customer,55,Business travel,Business,3807,2,4,4,4,3,3,3,2,2,2,2,4,2,1,7,0.0,neutral or dissatisfied +90965,706,Male,Loyal Customer,45,Business travel,Business,2987,1,1,1,1,2,4,4,5,5,5,4,5,5,3,0,0.0,satisfied +90966,63735,Male,Loyal Customer,26,Personal Travel,Eco,1660,4,1,4,4,5,4,5,5,2,1,4,2,3,5,0,0.0,satisfied +90967,17865,Female,disloyal Customer,20,Business travel,Eco,425,2,5,2,2,4,2,2,4,5,2,2,3,3,4,62,51.0,neutral or dissatisfied +90968,109293,Male,Loyal Customer,55,Business travel,Business,1072,4,4,4,4,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +90969,21170,Female,Loyal Customer,50,Business travel,Business,3397,2,3,3,3,3,4,3,4,4,4,2,4,4,2,0,0.0,neutral or dissatisfied +90970,104538,Male,Loyal Customer,26,Business travel,Business,1047,2,4,4,4,2,3,2,2,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +90971,8348,Female,disloyal Customer,9,Business travel,Eco,783,1,1,1,2,3,1,3,3,1,4,3,1,2,3,0,0.0,neutral or dissatisfied +90972,17349,Male,Loyal Customer,29,Business travel,Business,563,5,5,5,5,4,5,4,4,3,3,5,3,5,4,100,87.0,satisfied +90973,47811,Male,disloyal Customer,25,Business travel,Eco,817,3,3,3,4,4,3,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +90974,118271,Female,Loyal Customer,48,Business travel,Business,602,3,3,3,3,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +90975,8543,Male,Loyal Customer,56,Business travel,Business,109,4,4,4,4,4,5,5,5,5,5,4,4,5,4,0,17.0,satisfied +90976,50201,Female,disloyal Customer,29,Business travel,Eco,89,2,5,2,3,4,2,4,4,1,4,3,2,2,4,1,0.0,neutral or dissatisfied +90977,86094,Male,Loyal Customer,59,Business travel,Business,226,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +90978,40580,Male,disloyal Customer,43,Business travel,Eco,391,3,2,3,3,3,3,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +90979,43524,Female,Loyal Customer,55,Personal Travel,Eco Plus,594,3,4,3,3,4,4,4,1,1,3,1,1,1,2,4,0.0,neutral or dissatisfied +90980,10368,Male,Loyal Customer,41,Business travel,Business,201,4,4,4,4,2,4,4,4,4,4,5,5,4,3,0,0.0,satisfied +90981,34307,Female,Loyal Customer,55,Personal Travel,Eco,280,3,4,4,1,3,5,1,2,2,4,2,1,2,2,0,0.0,neutral or dissatisfied +90982,11724,Male,Loyal Customer,57,Business travel,Business,3014,3,3,3,3,3,4,4,5,5,4,5,5,5,5,4,6.0,satisfied +90983,74460,Male,disloyal Customer,25,Business travel,Business,1464,0,0,0,4,5,0,5,5,5,3,4,5,5,5,21,27.0,satisfied +90984,114107,Male,disloyal Customer,49,Business travel,Business,819,4,4,4,3,4,4,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +90985,74066,Female,Loyal Customer,39,Business travel,Business,3660,4,2,2,2,2,3,3,4,4,4,4,4,4,1,65,55.0,neutral or dissatisfied +90986,9509,Female,Loyal Customer,24,Personal Travel,Eco,239,1,5,1,4,4,1,4,4,5,4,5,4,4,4,32,20.0,neutral or dissatisfied +90987,86958,Male,Loyal Customer,57,Business travel,Business,3519,2,2,2,2,2,5,4,5,5,5,5,4,5,5,29,26.0,satisfied +90988,30354,Male,Loyal Customer,51,Business travel,Business,862,3,3,3,3,4,5,3,5,5,5,5,3,5,5,0,0.0,satisfied +90989,10222,Male,Loyal Customer,38,Business travel,Business,216,5,5,5,5,3,4,5,4,4,4,4,4,4,4,29,24.0,satisfied +90990,119055,Female,Loyal Customer,68,Personal Travel,Eco,2279,3,3,3,3,2,3,2,2,2,3,2,2,2,1,2,8.0,neutral or dissatisfied +90991,111129,Male,Loyal Customer,41,Business travel,Business,1180,3,3,3,3,5,5,5,3,2,4,4,5,4,5,132,130.0,satisfied +90992,36561,Male,Loyal Customer,58,Business travel,Business,2958,3,4,4,4,2,4,3,3,3,3,3,2,3,4,29,40.0,neutral or dissatisfied +90993,99750,Male,disloyal Customer,35,Business travel,Eco,255,2,0,2,3,1,2,1,1,3,1,1,4,1,1,0,0.0,neutral or dissatisfied +90994,104808,Female,Loyal Customer,21,Personal Travel,Eco,587,2,3,2,4,4,2,4,4,4,1,3,1,4,4,8,0.0,neutral or dissatisfied +90995,65021,Male,disloyal Customer,17,Business travel,Eco,551,2,0,3,3,2,3,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +90996,84556,Male,Loyal Customer,68,Personal Travel,Eco,2556,3,1,4,4,5,4,5,5,2,5,3,2,4,5,0,0.0,neutral or dissatisfied +90997,87086,Female,Loyal Customer,47,Business travel,Eco,594,2,2,2,2,5,3,4,3,3,2,3,2,3,3,73,60.0,neutral or dissatisfied +90998,34845,Male,Loyal Customer,67,Personal Travel,Eco Plus,301,3,5,3,3,5,3,5,5,2,1,4,2,5,5,0,12.0,neutral or dissatisfied +90999,118633,Female,Loyal Customer,65,Business travel,Eco,325,3,1,1,1,5,3,3,3,3,3,3,3,3,2,27,16.0,neutral or dissatisfied +91000,71344,Female,Loyal Customer,65,Personal Travel,Eco,1514,3,4,3,2,5,4,4,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +91001,8530,Female,Loyal Customer,56,Business travel,Business,3408,4,4,4,4,3,5,4,5,5,5,5,3,5,3,93,92.0,satisfied +91002,103264,Male,Loyal Customer,53,Business travel,Business,888,5,5,5,5,2,5,4,5,5,5,5,5,5,3,9,0.0,satisfied +91003,68993,Male,Loyal Customer,52,Business travel,Eco,2422,3,3,3,3,3,3,3,1,1,3,4,3,4,3,0,0.0,neutral or dissatisfied +91004,97713,Male,disloyal Customer,12,Business travel,Eco,942,2,2,2,4,1,2,1,1,3,1,3,2,3,1,73,67.0,neutral or dissatisfied +91005,75192,Male,Loyal Customer,25,Business travel,Business,1726,1,3,3,3,1,1,1,1,2,3,3,1,4,1,32,5.0,neutral or dissatisfied +91006,30185,Male,disloyal Customer,37,Business travel,Eco Plus,253,1,0,0,4,4,0,4,4,1,4,3,5,3,4,13,12.0,neutral or dissatisfied +91007,25299,Female,Loyal Customer,80,Business travel,Business,3318,1,3,3,3,5,4,3,1,1,1,1,1,1,3,13,6.0,neutral or dissatisfied +91008,96866,Female,Loyal Customer,67,Business travel,Eco,381,3,5,3,3,2,4,4,3,3,3,3,3,3,4,21,21.0,neutral or dissatisfied +91009,80755,Female,Loyal Customer,31,Business travel,Eco Plus,393,3,1,1,1,3,3,3,3,4,3,1,3,2,3,0,0.0,neutral or dissatisfied +91010,70979,Female,Loyal Customer,30,Business travel,Business,802,2,1,2,2,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +91011,109260,Female,Loyal Customer,58,Business travel,Business,3451,5,5,5,5,5,5,4,3,3,3,3,3,3,5,0,3.0,satisfied +91012,89831,Female,Loyal Customer,52,Personal Travel,Eco Plus,1076,2,5,1,1,3,5,5,2,2,1,3,5,2,4,0,0.0,neutral or dissatisfied +91013,60803,Female,Loyal Customer,40,Personal Travel,Eco,472,4,0,4,1,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +91014,116288,Female,Loyal Customer,59,Personal Travel,Eco,372,3,0,3,3,2,5,2,2,2,3,4,5,2,5,64,67.0,neutral or dissatisfied +91015,84277,Male,Loyal Customer,52,Business travel,Business,2463,3,2,2,2,2,4,4,3,3,2,3,3,3,1,33,34.0,neutral or dissatisfied +91016,11463,Male,Loyal Customer,49,Business travel,Eco Plus,667,2,4,4,4,2,2,2,2,2,3,2,4,3,2,35,39.0,neutral or dissatisfied +91017,99823,Female,Loyal Customer,32,Business travel,Business,680,1,1,1,1,4,4,4,4,5,4,4,4,5,4,2,14.0,satisfied +91018,29968,Male,disloyal Customer,38,Business travel,Eco,373,4,1,4,1,4,4,4,4,1,2,1,2,2,4,0,0.0,neutral or dissatisfied +91019,110572,Female,Loyal Customer,48,Business travel,Eco,488,3,5,5,5,1,3,3,3,3,3,3,3,3,1,15,17.0,neutral or dissatisfied +91020,47074,Female,Loyal Customer,8,Personal Travel,Eco,639,3,4,3,2,5,3,5,5,3,5,5,3,4,5,9,0.0,neutral or dissatisfied +91021,29508,Male,Loyal Customer,63,Personal Travel,Eco,1216,4,5,3,1,4,3,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +91022,104951,Female,Loyal Customer,50,Business travel,Business,337,3,3,2,2,5,4,3,3,3,3,3,3,3,1,39,55.0,neutral or dissatisfied +91023,84360,Female,Loyal Customer,26,Business travel,Business,2709,2,2,2,2,5,5,5,5,4,2,5,5,5,5,0,11.0,satisfied +91024,113320,Male,Loyal Customer,58,Business travel,Business,2746,4,4,4,4,4,5,5,5,5,5,5,3,5,3,22,12.0,satisfied +91025,34214,Female,Loyal Customer,17,Personal Travel,Eco,1046,1,5,1,1,4,1,1,4,3,3,5,3,5,4,1,20.0,neutral or dissatisfied +91026,923,Male,Loyal Customer,43,Business travel,Business,2954,3,2,2,2,5,4,4,2,2,1,3,3,2,3,0,0.0,neutral or dissatisfied +91027,28884,Female,Loyal Customer,21,Business travel,Business,954,2,3,3,3,2,2,2,2,4,2,2,4,3,2,12,6.0,neutral or dissatisfied +91028,126855,Male,Loyal Customer,46,Personal Travel,Eco,2296,1,5,0,4,4,0,4,4,3,5,4,3,2,4,0,0.0,neutral or dissatisfied +91029,14468,Male,Loyal Customer,17,Personal Travel,Eco,761,5,4,5,1,2,5,1,2,3,2,5,5,5,2,0,0.0,satisfied +91030,94184,Female,Loyal Customer,51,Business travel,Business,3937,4,1,4,4,4,5,4,5,5,5,5,3,5,3,1,0.0,satisfied +91031,83695,Male,Loyal Customer,11,Personal Travel,Eco,577,4,5,4,2,1,4,1,1,5,3,5,4,5,1,10,12.0,neutral or dissatisfied +91032,66974,Female,Loyal Customer,46,Business travel,Business,918,3,3,3,3,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +91033,7600,Female,Loyal Customer,58,Business travel,Business,2896,1,1,1,1,2,5,4,5,5,5,5,5,5,3,21,40.0,satisfied +91034,118724,Male,Loyal Customer,15,Personal Travel,Eco,646,4,3,4,4,2,4,2,2,1,1,4,3,3,2,2,0.0,neutral or dissatisfied +91035,43286,Male,Loyal Customer,51,Business travel,Eco,436,1,3,3,3,1,1,1,1,4,5,3,2,4,1,0,11.0,neutral or dissatisfied +91036,18935,Male,Loyal Customer,23,Personal Travel,Eco,448,4,4,4,5,4,4,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +91037,14948,Female,Loyal Customer,40,Business travel,Business,554,2,2,2,2,1,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +91038,75421,Female,Loyal Customer,32,Business travel,Business,2342,1,2,2,2,1,1,1,1,1,1,2,3,4,1,37,24.0,neutral or dissatisfied +91039,50256,Male,Loyal Customer,65,Business travel,Business,421,2,2,2,2,4,3,3,2,2,2,2,1,2,2,0,8.0,neutral or dissatisfied +91040,75726,Female,Loyal Customer,43,Business travel,Eco,813,3,1,1,1,5,3,4,3,3,3,3,2,3,3,4,3.0,neutral or dissatisfied +91041,36548,Male,Loyal Customer,50,Business travel,Eco,1185,4,5,5,5,3,4,3,3,4,4,5,3,5,3,8,0.0,satisfied +91042,79814,Female,Loyal Customer,40,Business travel,Business,1690,5,5,5,5,2,4,5,4,4,4,4,4,4,4,8,0.0,satisfied +91043,91512,Male,Loyal Customer,52,Business travel,Eco,1620,2,4,4,4,2,2,2,2,2,5,3,3,4,2,0,0.0,neutral or dissatisfied +91044,123155,Female,disloyal Customer,37,Business travel,Business,328,2,2,2,2,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +91045,73464,Female,Loyal Customer,70,Personal Travel,Eco,1144,2,2,2,4,5,3,3,5,5,2,5,3,5,3,1,0.0,neutral or dissatisfied +91046,110129,Female,Loyal Customer,16,Business travel,Business,1780,1,1,1,1,2,2,2,2,3,4,5,4,5,2,3,0.0,satisfied +91047,58119,Female,Loyal Customer,58,Personal Travel,Eco,612,3,4,3,5,5,4,5,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +91048,49587,Male,Loyal Customer,45,Business travel,Eco,363,4,5,5,5,4,4,4,4,5,5,2,1,4,4,0,9.0,satisfied +91049,123593,Male,Loyal Customer,65,Personal Travel,Eco,1773,2,4,1,3,3,1,3,3,3,4,3,4,2,3,0,12.0,neutral or dissatisfied +91050,124331,Male,Loyal Customer,62,Personal Travel,Eco Plus,255,4,0,4,2,2,4,2,2,5,2,4,4,4,2,19,17.0,neutral or dissatisfied +91051,110559,Male,disloyal Customer,28,Business travel,Eco,551,1,3,1,3,2,1,2,2,4,5,3,1,4,2,20,15.0,neutral or dissatisfied +91052,2357,Male,disloyal Customer,48,Business travel,Business,925,2,3,3,5,5,2,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +91053,21190,Female,disloyal Customer,23,Business travel,Eco,153,3,4,4,4,2,4,2,2,1,2,2,1,1,2,0,0.0,neutral or dissatisfied +91054,78204,Male,Loyal Customer,36,Business travel,Business,192,3,4,3,3,3,3,4,2,2,2,3,4,2,2,45,48.0,neutral or dissatisfied +91055,99099,Female,disloyal Customer,21,Business travel,Eco,181,3,2,3,4,3,3,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +91056,54174,Male,Loyal Customer,37,Business travel,Business,1000,1,5,5,5,3,4,3,1,1,2,1,1,1,4,46,29.0,neutral or dissatisfied +91057,126669,Male,Loyal Customer,64,Personal Travel,Business,2276,2,5,2,2,2,4,4,5,5,2,5,3,5,3,13,0.0,neutral or dissatisfied +91058,26297,Male,Loyal Customer,33,Business travel,Business,1199,2,2,2,2,5,5,5,5,5,3,3,3,4,5,0,0.0,satisfied +91059,70757,Male,Loyal Customer,58,Business travel,Eco,333,4,3,5,3,4,4,4,4,4,2,1,5,5,4,16,10.0,satisfied +91060,88378,Female,disloyal Customer,29,Business travel,Business,646,5,5,5,4,5,5,5,5,4,4,5,3,5,5,0,1.0,satisfied +91061,117420,Male,Loyal Customer,33,Business travel,Business,1460,3,5,3,3,4,4,4,4,4,4,5,3,5,4,36,37.0,satisfied +91062,123760,Male,Loyal Customer,39,Business travel,Business,544,5,3,5,5,2,5,4,5,5,5,5,3,5,3,0,4.0,satisfied +91063,77944,Male,Loyal Customer,36,Business travel,Business,2884,3,3,3,3,4,4,5,4,4,4,5,5,4,4,0,0.0,satisfied +91064,105765,Male,Loyal Customer,64,Business travel,Business,1699,2,2,2,2,3,1,1,4,4,4,4,5,4,5,1,0.0,satisfied +91065,93711,Female,Loyal Customer,13,Personal Travel,Eco,689,2,5,2,3,4,2,1,4,3,4,4,3,4,4,4,7.0,neutral or dissatisfied +91066,82486,Male,Loyal Customer,63,Personal Travel,Eco Plus,502,3,4,3,1,1,3,4,1,5,4,4,4,5,1,102,87.0,neutral or dissatisfied +91067,49232,Female,Loyal Customer,34,Business travel,Eco,110,4,2,3,2,4,4,4,4,3,4,2,1,1,4,0,0.0,satisfied +91068,32439,Male,Loyal Customer,31,Business travel,Business,3326,0,4,0,1,1,1,1,1,1,4,5,3,2,1,0,0.0,satisfied +91069,84691,Female,Loyal Customer,24,Personal Travel,Eco,2182,1,4,1,3,3,1,3,3,4,5,4,1,3,3,10,1.0,neutral or dissatisfied +91070,8197,Female,Loyal Customer,54,Business travel,Eco,125,5,2,2,2,3,5,5,5,5,5,5,4,5,1,1,0.0,satisfied +91071,85362,Female,Loyal Customer,35,Personal Travel,Eco Plus,689,2,4,1,5,3,1,3,3,3,3,5,1,5,3,7,15.0,neutral or dissatisfied +91072,66902,Female,Loyal Customer,8,Personal Travel,Business,929,3,4,3,4,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +91073,54734,Male,Loyal Customer,12,Personal Travel,Eco,965,3,5,3,3,4,3,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +91074,55164,Male,Loyal Customer,38,Personal Travel,Eco,1609,2,4,2,1,3,2,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +91075,124192,Female,Loyal Customer,30,Business travel,Business,2176,2,2,2,2,5,5,5,5,3,2,4,3,4,5,2,20.0,satisfied +91076,79156,Male,Loyal Customer,54,Business travel,Eco,2239,3,2,2,2,3,3,3,3,3,1,4,3,3,3,0,6.0,neutral or dissatisfied +91077,39166,Female,Loyal Customer,61,Business travel,Business,3382,1,1,1,1,5,4,3,3,3,3,1,2,3,4,0,0.0,neutral or dissatisfied +91078,86995,Female,Loyal Customer,67,Personal Travel,Eco,907,1,2,2,4,5,3,4,2,2,2,2,2,2,2,2,0.0,neutral or dissatisfied +91079,31754,Female,Loyal Customer,47,Business travel,Business,2334,1,1,1,1,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +91080,125360,Male,Loyal Customer,68,Personal Travel,Eco,599,1,5,1,4,5,1,2,5,2,4,3,1,1,5,7,14.0,neutral or dissatisfied +91081,106794,Male,disloyal Customer,29,Business travel,Eco,977,3,3,3,4,4,3,4,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +91082,78596,Female,Loyal Customer,47,Business travel,Business,2454,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +91083,168,Male,Loyal Customer,37,Personal Travel,Eco,227,3,5,3,4,4,3,4,4,3,2,5,3,5,4,36,43.0,neutral or dissatisfied +91084,50683,Male,Loyal Customer,14,Personal Travel,Eco,373,3,3,1,3,4,1,3,4,4,5,4,3,3,4,0,0.0,neutral or dissatisfied +91085,19266,Male,Loyal Customer,26,Business travel,Eco Plus,802,2,1,1,1,2,2,4,2,3,3,4,4,4,2,0,36.0,neutral or dissatisfied +91086,20503,Female,Loyal Customer,10,Personal Travel,Eco,130,4,2,4,3,4,4,3,4,1,2,4,3,4,4,22,26.0,neutral or dissatisfied +91087,122414,Male,Loyal Customer,50,Business travel,Eco,1916,3,4,4,4,3,3,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +91088,32164,Female,Loyal Customer,37,Business travel,Eco,201,4,5,5,5,4,4,4,4,2,2,3,5,1,4,5,7.0,satisfied +91089,56127,Male,Loyal Customer,57,Business travel,Business,1400,2,2,2,2,3,5,5,4,4,4,4,5,4,4,25,26.0,satisfied +91090,83141,Male,Loyal Customer,55,Personal Travel,Eco,1145,3,4,3,4,2,3,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +91091,121932,Male,Loyal Customer,45,Business travel,Business,3280,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +91092,122116,Male,Loyal Customer,46,Business travel,Business,2231,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,11.0,satisfied +91093,103236,Male,Loyal Customer,59,Business travel,Business,3778,1,1,1,1,5,5,5,5,5,5,5,4,5,5,16,14.0,satisfied +91094,29586,Female,disloyal Customer,26,Business travel,Eco,680,2,2,2,3,4,2,4,4,5,5,5,2,1,4,8,4.0,neutral or dissatisfied +91095,31655,Female,disloyal Customer,23,Business travel,Eco,862,4,4,4,4,5,4,5,5,5,3,4,2,1,5,0,3.0,satisfied +91096,6351,Female,Loyal Customer,50,Business travel,Business,3197,4,4,4,4,2,5,5,5,5,5,5,3,5,5,0,8.0,satisfied +91097,94789,Female,Loyal Customer,57,Business travel,Business,273,4,4,4,4,4,4,3,4,4,3,4,1,4,2,41,52.0,neutral or dissatisfied +91098,63164,Female,Loyal Customer,41,Business travel,Business,2856,0,0,0,2,3,5,4,4,4,4,4,5,4,3,35,32.0,satisfied +91099,50092,Male,Loyal Customer,46,Business travel,Eco,372,2,1,1,1,2,2,2,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +91100,82033,Female,Loyal Customer,54,Personal Travel,Eco,1535,2,1,2,2,3,1,1,1,1,2,1,3,1,4,3,24.0,neutral or dissatisfied +91101,28545,Female,Loyal Customer,46,Personal Travel,Eco,2688,2,5,2,5,2,3,3,4,2,5,5,3,4,3,0,14.0,neutral or dissatisfied +91102,79000,Female,disloyal Customer,32,Business travel,Business,356,2,2,2,2,2,2,2,2,3,5,5,4,5,2,56,44.0,neutral or dissatisfied +91103,76339,Male,Loyal Customer,56,Business travel,Business,3942,3,3,5,3,5,4,4,5,5,5,5,4,5,3,5,3.0,satisfied +91104,37487,Female,Loyal Customer,47,Business travel,Business,2229,2,5,5,5,1,3,3,2,2,3,2,4,2,1,7,8.0,neutral or dissatisfied +91105,71042,Female,disloyal Customer,8,Business travel,Eco,802,4,4,4,3,2,4,2,2,1,4,4,4,4,2,11,7.0,neutral or dissatisfied +91106,122718,Female,Loyal Customer,51,Business travel,Business,2080,3,3,3,3,4,5,5,4,4,4,4,3,4,4,2,0.0,satisfied +91107,57713,Female,disloyal Customer,26,Business travel,Eco Plus,867,3,3,3,4,2,3,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +91108,126876,Male,Loyal Customer,46,Personal Travel,Eco,2296,4,5,4,3,5,4,5,5,3,4,5,5,4,5,5,0.0,neutral or dissatisfied +91109,38409,Female,Loyal Customer,35,Personal Travel,Business,965,2,4,2,5,4,5,5,5,5,2,5,4,5,4,0,6.0,neutral or dissatisfied +91110,83948,Male,disloyal Customer,37,Business travel,Business,373,2,2,2,1,4,2,1,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +91111,1359,Male,Loyal Customer,17,Business travel,Business,396,1,5,5,5,1,2,1,1,3,3,3,1,3,1,3,6.0,neutral or dissatisfied +91112,542,Male,disloyal Customer,34,Business travel,Business,312,2,2,2,3,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +91113,47388,Female,Loyal Customer,26,Business travel,Business,588,5,5,5,5,3,3,3,3,4,5,4,5,5,3,0,0.0,satisfied +91114,118227,Male,disloyal Customer,20,Business travel,Eco,1587,2,1,1,1,5,2,5,5,4,2,3,4,5,5,0,0.0,neutral or dissatisfied +91115,84467,Female,Loyal Customer,29,Business travel,Business,2979,2,2,2,2,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +91116,21757,Female,Loyal Customer,44,Personal Travel,Eco Plus,563,3,5,3,3,3,4,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +91117,74627,Male,disloyal Customer,26,Business travel,Eco,1031,3,3,3,3,5,3,3,5,4,2,3,3,5,5,0,0.0,neutral or dissatisfied +91118,125059,Male,Loyal Customer,66,Personal Travel,Business,90,2,4,2,4,2,4,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +91119,109794,Male,Loyal Customer,42,Business travel,Business,1915,5,5,1,5,2,4,5,4,4,4,4,4,4,3,9,2.0,satisfied +91120,11283,Male,Loyal Customer,57,Personal Travel,Eco,224,1,1,1,2,1,1,1,1,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +91121,56465,Male,Loyal Customer,19,Business travel,Eco Plus,719,1,3,3,3,1,1,3,1,3,3,4,2,3,1,0,0.0,neutral or dissatisfied +91122,115186,Female,disloyal Customer,38,Business travel,Business,337,2,2,2,1,1,2,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +91123,52619,Male,Loyal Customer,35,Business travel,Business,3601,2,2,4,2,4,1,3,5,5,5,5,2,5,5,0,0.0,satisfied +91124,7266,Female,Loyal Customer,30,Personal Travel,Eco,116,3,4,3,4,1,3,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +91125,17266,Male,Loyal Customer,30,Personal Travel,Eco,1092,2,3,2,2,2,2,2,2,4,4,2,3,4,2,8,5.0,neutral or dissatisfied +91126,126713,Male,disloyal Customer,37,Business travel,Business,2402,2,1,1,5,5,1,5,5,4,5,3,4,4,5,8,0.0,neutral or dissatisfied +91127,92501,Female,disloyal Customer,16,Business travel,Eco,1892,3,3,3,3,3,3,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +91128,11142,Male,Loyal Customer,16,Personal Travel,Eco,312,4,4,5,3,1,5,1,1,4,3,4,4,4,1,87,92.0,neutral or dissatisfied +91129,61980,Female,Loyal Customer,44,Personal Travel,Business,2475,1,4,1,2,5,4,4,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +91130,82822,Female,Loyal Customer,34,Personal Travel,Business,594,1,4,1,3,2,4,5,2,2,1,2,4,2,4,2,0.0,neutral or dissatisfied +91131,15315,Female,Loyal Customer,49,Business travel,Business,2159,2,1,1,1,5,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +91132,48588,Female,Loyal Customer,28,Personal Travel,Eco,916,2,5,2,3,2,2,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +91133,91309,Male,Loyal Customer,57,Business travel,Eco Plus,406,2,4,4,4,2,2,2,2,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +91134,71596,Female,Loyal Customer,26,Business travel,Business,1504,1,4,4,4,1,1,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +91135,88254,Male,Loyal Customer,48,Business travel,Eco,406,3,5,5,5,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +91136,100899,Female,Loyal Customer,31,Business travel,Business,3113,3,1,1,1,3,3,3,3,1,1,4,4,4,3,0,1.0,neutral or dissatisfied +91137,99125,Male,Loyal Customer,29,Personal Travel,Eco,237,4,5,4,1,1,4,1,1,3,4,5,4,4,1,16,13.0,neutral or dissatisfied +91138,121093,Male,Loyal Customer,36,Business travel,Eco,1158,4,5,5,5,4,5,4,4,2,2,5,3,4,4,0,0.0,satisfied +91139,82451,Male,Loyal Customer,44,Business travel,Business,502,3,3,3,3,3,4,4,3,3,3,3,1,3,1,92,81.0,neutral or dissatisfied +91140,95190,Female,Loyal Customer,39,Personal Travel,Eco,189,2,1,2,2,5,2,2,5,4,2,3,3,3,5,37,17.0,neutral or dissatisfied +91141,87877,Male,Loyal Customer,39,Business travel,Business,3089,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +91142,122130,Female,disloyal Customer,24,Business travel,Eco,544,4,4,4,1,1,4,1,1,4,4,4,5,5,1,80,68.0,neutral or dissatisfied +91143,114941,Female,Loyal Customer,47,Business travel,Business,3814,3,3,3,3,3,4,5,5,5,5,5,5,5,4,2,12.0,satisfied +91144,47306,Female,Loyal Customer,23,Business travel,Business,2766,3,3,3,3,2,2,2,2,1,1,3,3,4,2,0,0.0,satisfied +91145,92053,Male,Loyal Customer,18,Business travel,Business,1517,5,5,4,5,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +91146,75574,Female,Loyal Customer,50,Business travel,Business,2420,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +91147,125281,Female,Loyal Customer,50,Business travel,Business,3962,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +91148,128539,Female,Loyal Customer,58,Business travel,Business,370,2,2,5,2,2,5,4,4,4,3,4,5,4,5,33,28.0,satisfied +91149,29099,Female,Loyal Customer,19,Personal Travel,Eco,679,3,5,2,3,3,2,1,3,4,5,4,4,5,3,14,16.0,neutral or dissatisfied +91150,75112,Male,Loyal Customer,43,Business travel,Business,1846,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +91151,35430,Male,Loyal Customer,11,Personal Travel,Eco,1076,5,3,5,3,5,5,5,5,2,4,2,4,3,5,37,28.0,satisfied +91152,10559,Male,Loyal Customer,25,Business travel,Business,2010,1,1,1,1,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +91153,51032,Female,Loyal Customer,30,Personal Travel,Eco,193,3,4,0,3,5,0,5,5,4,5,3,4,4,5,0,0.0,neutral or dissatisfied +91154,86353,Male,disloyal Customer,21,Business travel,Business,762,4,0,4,2,3,4,3,3,4,5,4,4,5,3,34,47.0,satisfied +91155,33911,Female,Loyal Customer,42,Business travel,Eco,636,4,2,2,2,2,5,3,5,5,4,5,4,5,2,0,0.0,satisfied +91156,123761,Female,Loyal Customer,42,Business travel,Business,3523,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +91157,63379,Male,Loyal Customer,57,Personal Travel,Eco,337,4,1,4,1,2,4,2,2,4,3,1,1,2,2,8,0.0,neutral or dissatisfied +91158,87620,Male,Loyal Customer,42,Business travel,Business,606,1,1,3,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +91159,92653,Male,Loyal Customer,24,Personal Travel,Eco,453,2,5,2,3,3,2,4,3,5,4,2,1,3,3,0,0.0,neutral or dissatisfied +91160,112982,Female,Loyal Customer,53,Personal Travel,Eco Plus,1642,1,5,1,1,4,3,5,4,4,1,5,3,4,5,6,0.0,neutral or dissatisfied +91161,110590,Female,Loyal Customer,51,Personal Travel,Eco,551,3,5,2,3,5,4,5,2,2,2,2,4,2,4,8,1.0,neutral or dissatisfied +91162,43222,Male,Loyal Customer,9,Personal Travel,Eco,423,3,2,3,4,2,3,2,2,3,1,4,3,4,2,42,69.0,neutral or dissatisfied +91163,53740,Male,Loyal Customer,31,Personal Travel,Eco,1208,3,1,3,2,2,3,2,2,1,1,2,2,3,2,0,0.0,neutral or dissatisfied +91164,65635,Female,Loyal Customer,21,Personal Travel,Eco,237,2,5,2,3,1,2,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +91165,115373,Male,disloyal Customer,36,Business travel,Business,446,3,2,2,3,2,2,2,2,5,4,5,5,5,2,21,11.0,neutral or dissatisfied +91166,68280,Male,Loyal Customer,43,Personal Travel,Eco Plus,631,2,4,2,5,2,1,1,3,5,5,5,1,4,1,381,353.0,neutral or dissatisfied +91167,2879,Female,Loyal Customer,48,Personal Travel,Eco,475,3,5,3,4,2,3,2,3,3,3,1,4,3,1,10,46.0,neutral or dissatisfied +91168,107116,Male,Loyal Customer,43,Business travel,Business,842,2,2,2,2,3,4,5,4,4,5,4,5,4,3,33,21.0,satisfied +91169,8878,Male,Loyal Customer,44,Business travel,Business,222,4,4,4,4,1,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +91170,128574,Male,Loyal Customer,49,Business travel,Business,2552,1,1,3,1,5,5,5,4,3,3,5,5,4,5,9,0.0,satisfied +91171,70851,Female,disloyal Customer,32,Business travel,Business,761,4,4,4,4,5,4,5,5,4,2,4,3,5,5,5,0.0,neutral or dissatisfied +91172,56493,Male,disloyal Customer,20,Business travel,Business,1068,5,0,5,2,2,5,2,2,5,4,4,5,5,2,6,19.0,satisfied +91173,107293,Male,Loyal Customer,47,Business travel,Business,3410,1,4,4,4,3,1,2,1,1,1,1,1,1,4,11,17.0,neutral or dissatisfied +91174,49236,Female,Loyal Customer,36,Business travel,Business,373,5,5,5,5,1,1,5,4,4,4,4,4,4,3,25,24.0,satisfied +91175,84418,Female,Loyal Customer,63,Personal Travel,Eco,606,4,3,4,4,1,1,2,2,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +91176,82260,Female,disloyal Customer,48,Business travel,Business,1481,2,2,2,4,4,2,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +91177,42407,Male,Loyal Customer,38,Business travel,Eco Plus,838,5,1,1,1,5,5,5,5,3,4,2,2,3,5,0,0.0,satisfied +91178,29069,Male,Loyal Customer,9,Personal Travel,Eco,954,1,2,1,3,5,1,5,5,2,2,3,2,4,5,0,0.0,neutral or dissatisfied +91179,99296,Male,Loyal Customer,45,Business travel,Business,337,4,3,4,4,5,5,5,4,4,4,4,4,4,4,33,17.0,satisfied +91180,40878,Male,Loyal Customer,69,Personal Travel,Eco,584,2,5,2,1,2,2,5,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +91181,16957,Female,Loyal Customer,41,Business travel,Business,1131,1,1,1,1,3,2,5,4,4,4,4,5,4,3,123,116.0,satisfied +91182,88470,Male,disloyal Customer,37,Business travel,Eco,404,2,2,2,4,5,2,5,5,1,2,3,3,4,5,15,23.0,neutral or dissatisfied +91183,81452,Male,Loyal Customer,52,Business travel,Business,1822,1,1,1,1,5,5,4,3,3,3,3,4,3,3,22,19.0,satisfied +91184,61012,Male,Loyal Customer,45,Business travel,Business,3365,4,4,4,4,4,4,4,5,4,5,4,4,3,4,0,34.0,satisfied +91185,66792,Female,Loyal Customer,11,Personal Travel,Eco,3784,4,5,3,1,3,1,1,5,5,4,4,1,5,1,24,17.0,neutral or dissatisfied +91186,54769,Male,Loyal Customer,58,Business travel,Eco Plus,854,5,2,2,2,5,5,5,5,2,3,2,1,3,5,1,0.0,satisfied +91187,27203,Female,disloyal Customer,30,Business travel,Eco,992,3,2,2,4,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +91188,4017,Male,Loyal Customer,53,Business travel,Business,479,1,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +91189,5359,Male,Loyal Customer,47,Business travel,Business,2340,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +91190,15931,Female,Loyal Customer,61,Business travel,Eco,566,3,3,3,3,4,4,4,3,3,3,3,3,3,3,0,4.0,neutral or dissatisfied +91191,19568,Female,Loyal Customer,44,Business travel,Business,2250,0,3,0,4,1,4,1,1,1,1,1,4,1,5,48,45.0,satisfied +91192,8240,Male,Loyal Customer,20,Personal Travel,Eco,125,1,2,1,3,5,1,5,5,4,1,2,4,2,5,0,0.0,neutral or dissatisfied +91193,31024,Male,Loyal Customer,33,Business travel,Eco Plus,391,4,1,1,1,4,4,4,4,1,1,3,3,2,4,2,12.0,satisfied +91194,90286,Female,disloyal Customer,48,Business travel,Eco,757,2,1,1,3,1,1,1,1,1,1,3,2,3,1,5,0.0,neutral or dissatisfied +91195,88806,Female,Loyal Customer,41,Business travel,Eco Plus,515,3,4,4,4,2,1,2,4,4,3,4,4,4,1,22,32.0,neutral or dissatisfied +91196,2295,Female,Loyal Customer,51,Business travel,Business,690,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +91197,56930,Male,Loyal Customer,49,Business travel,Business,2434,5,5,5,5,5,5,5,3,2,4,5,5,5,5,7,6.0,satisfied +91198,102642,Female,Loyal Customer,52,Business travel,Business,3766,5,5,5,5,2,4,5,5,5,5,5,5,5,5,1,0.0,satisfied +91199,28206,Female,Loyal Customer,27,Personal Travel,Eco,933,2,4,2,5,2,2,1,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +91200,60652,Male,Loyal Customer,22,Business travel,Business,1620,4,4,4,4,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +91201,109165,Female,Loyal Customer,26,Business travel,Business,612,5,5,5,5,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +91202,9356,Female,Loyal Customer,60,Business travel,Business,401,2,2,2,2,2,4,4,4,4,4,4,5,4,5,31,42.0,satisfied +91203,76411,Female,Loyal Customer,62,Business travel,Business,405,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +91204,71516,Female,disloyal Customer,36,Business travel,Business,1182,2,2,2,3,4,2,4,4,5,2,5,4,5,4,20,6.0,neutral or dissatisfied +91205,93584,Male,Loyal Customer,12,Personal Travel,Eco,159,1,4,1,1,3,1,3,3,1,5,3,5,1,3,0,0.0,neutral or dissatisfied +91206,83372,Female,Loyal Customer,33,Personal Travel,Eco,1124,3,5,3,3,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +91207,66306,Female,Loyal Customer,30,Business travel,Business,3874,3,3,3,3,4,5,4,4,4,5,5,4,4,4,9,14.0,satisfied +91208,29368,Female,Loyal Customer,28,Business travel,Business,2355,1,1,1,1,4,4,4,4,2,4,4,1,5,4,0,0.0,satisfied +91209,16096,Male,disloyal Customer,20,Business travel,Eco,303,3,1,3,4,5,3,5,5,4,1,3,3,3,5,0,0.0,neutral or dissatisfied +91210,81000,Male,Loyal Customer,49,Personal Travel,Eco,297,1,4,5,4,2,5,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +91211,78698,Male,disloyal Customer,34,Business travel,Business,447,4,4,4,2,1,4,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +91212,17840,Female,Loyal Customer,46,Personal Travel,Eco Plus,1214,1,0,1,1,2,5,4,4,4,1,1,4,4,3,0,0.0,neutral or dissatisfied +91213,125084,Male,Loyal Customer,60,Business travel,Business,361,5,5,5,5,5,5,4,3,3,3,3,5,3,3,0,7.0,satisfied +91214,115205,Male,disloyal Customer,41,Business travel,Eco,308,2,1,2,4,5,2,5,5,1,5,3,1,3,5,0,0.0,neutral or dissatisfied +91215,66903,Female,Loyal Customer,54,Personal Travel,Business,1121,2,4,2,3,2,5,4,5,2,4,4,4,3,4,126,132.0,neutral or dissatisfied +91216,24890,Male,Loyal Customer,58,Business travel,Eco,397,5,3,4,3,5,5,5,5,3,5,4,5,2,5,0,0.0,satisfied +91217,48530,Male,disloyal Customer,20,Business travel,Eco,376,2,0,2,3,1,2,1,1,1,2,4,5,1,1,45,32.0,neutral or dissatisfied +91218,32496,Male,Loyal Customer,39,Business travel,Eco,216,5,3,4,4,5,5,5,5,2,3,4,1,1,5,0,0.0,satisfied +91219,55738,Male,Loyal Customer,39,Personal Travel,Eco,2052,3,4,4,3,4,4,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +91220,23297,Male,Loyal Customer,39,Business travel,Business,456,4,4,4,4,5,1,4,3,3,3,3,1,3,2,1,12.0,satisfied +91221,43115,Male,Loyal Customer,53,Personal Travel,Eco,192,4,5,4,4,5,4,5,5,4,5,5,3,4,5,20,10.0,neutral or dissatisfied +91222,100986,Male,Loyal Customer,58,Business travel,Business,867,3,3,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +91223,49401,Male,Loyal Customer,64,Business travel,Business,308,3,3,3,3,2,2,2,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +91224,124324,Female,Loyal Customer,34,Personal Travel,Eco,255,1,4,0,4,4,0,4,4,3,5,4,4,5,4,68,64.0,neutral or dissatisfied +91225,86718,Female,Loyal Customer,40,Business travel,Eco,247,5,3,3,3,5,5,5,5,5,2,2,1,3,5,0,0.0,satisfied +91226,37875,Male,Loyal Customer,46,Business travel,Eco,1065,3,5,5,5,3,3,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +91227,39893,Female,Loyal Customer,62,Personal Travel,Eco,272,3,0,3,4,3,4,4,5,5,3,2,4,5,3,0,0.0,neutral or dissatisfied +91228,32851,Male,Loyal Customer,51,Personal Travel,Eco,102,1,5,1,2,3,1,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +91229,11576,Female,disloyal Customer,26,Business travel,Eco,468,3,1,3,4,4,3,5,4,2,2,3,1,4,4,0,0.0,neutral or dissatisfied +91230,76186,Male,Loyal Customer,58,Business travel,Business,2422,3,3,3,3,2,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +91231,99965,Female,Loyal Customer,54,Business travel,Business,2838,3,3,3,3,3,4,1,4,4,4,4,5,4,4,0,0.0,satisfied +91232,91886,Female,Loyal Customer,35,Business travel,Business,2586,5,5,5,5,4,3,4,2,2,2,2,4,2,4,0,0.0,satisfied +91233,116589,Male,Loyal Customer,60,Business travel,Business,2884,1,1,1,1,3,5,4,5,5,5,5,3,5,5,1,0.0,satisfied +91234,120845,Male,disloyal Customer,38,Business travel,Business,951,1,1,1,1,1,1,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +91235,33618,Male,Loyal Customer,61,Business travel,Eco,413,1,2,2,2,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +91236,111955,Male,disloyal Customer,29,Business travel,Eco,770,4,4,4,4,4,4,4,4,3,2,4,1,4,4,0,6.0,neutral or dissatisfied +91237,89053,Male,disloyal Customer,31,Business travel,Business,1919,1,1,1,3,2,1,2,2,3,2,5,3,4,2,0,9.0,neutral or dissatisfied +91238,113034,Female,Loyal Customer,46,Business travel,Business,2829,4,4,4,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +91239,92235,Male,Loyal Customer,23,Personal Travel,Eco Plus,2079,4,0,4,4,3,4,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +91240,16972,Male,Loyal Customer,48,Business travel,Eco,209,5,4,4,4,5,5,5,5,3,5,5,4,3,5,0,13.0,satisfied +91241,45004,Female,disloyal Customer,16,Business travel,Eco,359,3,4,3,4,4,3,3,4,2,3,4,1,3,4,15,8.0,neutral or dissatisfied +91242,12233,Male,Loyal Customer,35,Business travel,Eco,201,4,3,3,3,4,5,4,4,5,5,3,1,5,4,0,0.0,satisfied +91243,88383,Male,Loyal Customer,42,Business travel,Business,3570,1,3,4,3,5,3,3,3,3,3,1,3,3,4,0,0.0,neutral or dissatisfied +91244,52668,Female,Loyal Customer,19,Personal Travel,Eco,160,1,5,0,3,2,0,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +91245,63425,Male,Loyal Customer,51,Personal Travel,Eco,337,4,5,4,2,2,4,2,2,4,5,5,4,5,2,0,0.0,neutral or dissatisfied +91246,21991,Male,Loyal Customer,62,Personal Travel,Eco,448,2,5,2,2,3,2,3,3,4,5,4,4,5,3,7,0.0,neutral or dissatisfied +91247,98410,Male,disloyal Customer,70,Business travel,Business,462,1,1,1,5,5,1,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +91248,39498,Male,Loyal Customer,19,Personal Travel,Eco Plus,1368,1,4,1,4,3,1,3,3,2,5,4,1,4,3,38,31.0,neutral or dissatisfied +91249,14789,Male,disloyal Customer,18,Business travel,Eco,622,4,3,4,3,3,4,3,3,2,5,3,1,2,3,0,0.0,neutral or dissatisfied +91250,58889,Male,Loyal Customer,58,Business travel,Business,1554,1,1,1,1,5,5,4,4,4,4,4,4,4,5,20,4.0,satisfied +91251,120252,Female,Loyal Customer,50,Business travel,Business,1496,2,2,2,2,2,5,4,4,4,4,4,5,4,3,0,4.0,satisfied +91252,118106,Male,disloyal Customer,23,Business travel,Eco,829,2,2,2,4,5,2,5,5,2,1,3,4,3,5,0,7.0,neutral or dissatisfied +91253,106913,Female,Loyal Customer,46,Business travel,Business,3924,5,5,5,5,5,5,4,4,4,4,4,4,4,5,23,13.0,satisfied +91254,124198,Male,Loyal Customer,42,Business travel,Business,2176,4,4,4,4,5,3,4,4,4,4,4,4,4,3,17,0.0,satisfied +91255,66546,Male,disloyal Customer,26,Business travel,Business,328,5,0,5,1,2,5,2,2,3,2,4,3,5,2,0,1.0,satisfied +91256,51712,Male,disloyal Customer,24,Business travel,Eco,651,2,0,2,3,3,2,3,3,3,5,1,1,3,3,0,0.0,neutral or dissatisfied +91257,109545,Female,Loyal Customer,38,Personal Travel,Eco,993,3,4,3,1,3,3,3,3,5,5,4,3,4,3,1,2.0,neutral or dissatisfied +91258,2441,Male,Loyal Customer,14,Personal Travel,Eco,641,2,5,3,3,4,3,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +91259,98527,Female,Loyal Customer,24,Personal Travel,Eco,668,1,5,1,3,4,1,4,4,4,2,4,3,4,4,14,13.0,neutral or dissatisfied +91260,86770,Female,Loyal Customer,54,Business travel,Business,2372,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +91261,126341,Male,Loyal Customer,56,Personal Travel,Eco,507,5,5,5,4,1,5,5,1,3,3,4,5,5,1,0,0.0,satisfied +91262,117609,Female,Loyal Customer,36,Business travel,Eco,347,4,3,3,3,4,4,4,4,1,4,5,1,4,4,0,0.0,satisfied +91263,35534,Male,Loyal Customer,64,Personal Travel,Eco,1144,1,4,1,3,3,1,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +91264,4396,Female,Loyal Customer,54,Personal Travel,Eco,607,2,4,2,4,3,3,3,3,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +91265,59086,Female,disloyal Customer,22,Business travel,Eco,1478,3,2,2,3,3,4,1,1,4,3,4,1,2,1,182,139.0,neutral or dissatisfied +91266,57528,Female,disloyal Customer,33,Business travel,Business,413,2,3,3,3,4,3,2,4,4,5,5,4,5,4,0,0.0,neutral or dissatisfied +91267,23042,Male,Loyal Customer,50,Business travel,Business,1500,1,1,1,1,1,4,4,5,5,5,4,5,5,4,107,98.0,satisfied +91268,115224,Female,disloyal Customer,24,Business travel,Eco,337,4,0,4,4,1,4,1,1,4,3,5,4,5,1,51,50.0,neutral or dissatisfied +91269,12191,Female,Loyal Customer,43,Personal Travel,Eco,1214,3,4,3,3,4,3,4,1,1,3,1,2,1,1,91,64.0,neutral or dissatisfied +91270,36588,Male,Loyal Customer,24,Business travel,Business,2429,1,1,1,1,5,5,5,5,1,4,4,4,3,5,3,0.0,satisfied +91271,23532,Male,disloyal Customer,22,Business travel,Eco,472,3,0,3,2,1,3,1,1,3,3,2,2,1,1,33,30.0,neutral or dissatisfied +91272,97654,Female,Loyal Customer,40,Business travel,Business,491,1,1,1,1,2,4,5,4,4,4,4,4,4,3,3,0.0,satisfied +91273,102701,Female,Loyal Customer,55,Business travel,Eco,255,3,3,3,3,2,4,3,3,3,3,3,4,3,3,13,39.0,neutral or dissatisfied +91274,84239,Male,disloyal Customer,23,Business travel,Business,432,5,0,5,1,5,5,5,5,5,3,5,5,5,5,21,9.0,satisfied +91275,18767,Male,disloyal Customer,27,Business travel,Business,448,5,5,5,1,1,5,1,1,3,4,4,4,5,1,0,0.0,satisfied +91276,115111,Female,Loyal Customer,43,Business travel,Business,447,5,5,5,5,2,5,5,5,5,5,5,3,5,4,41,32.0,satisfied +91277,50511,Female,Loyal Customer,43,Personal Travel,Eco,89,3,4,3,1,2,4,4,5,5,3,5,4,5,3,0,10.0,neutral or dissatisfied +91278,58850,Male,Loyal Customer,53,Business travel,Business,3240,2,2,2,2,5,4,4,5,5,5,5,5,5,4,3,6.0,satisfied +91279,39055,Female,Loyal Customer,54,Personal Travel,Eco Plus,391,3,4,3,5,3,4,4,1,1,3,1,5,1,3,25,35.0,neutral or dissatisfied +91280,115590,Male,Loyal Customer,72,Business travel,Eco,358,3,4,4,4,3,3,3,3,2,4,4,3,4,3,0,0.0,neutral or dissatisfied +91281,109845,Male,disloyal Customer,24,Business travel,Eco,1053,3,3,3,2,4,3,4,4,5,4,5,5,5,4,23,19.0,neutral or dissatisfied +91282,97121,Female,disloyal Customer,45,Business travel,Business,1164,3,3,3,3,4,3,4,4,4,5,5,4,5,4,1,1.0,neutral or dissatisfied +91283,35370,Female,Loyal Customer,29,Business travel,Business,1637,1,2,3,2,1,1,1,1,2,4,3,2,3,1,19,76.0,neutral or dissatisfied +91284,79739,Female,disloyal Customer,48,Business travel,Business,749,4,4,4,4,5,4,2,5,3,5,5,4,5,5,6,0.0,satisfied +91285,127769,Female,Loyal Customer,26,Personal Travel,Eco,255,4,5,4,3,5,4,2,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +91286,105543,Female,Loyal Customer,32,Personal Travel,Eco,611,1,2,1,3,3,1,3,3,3,4,3,2,3,3,6,1.0,neutral or dissatisfied +91287,110472,Male,Loyal Customer,38,Personal Travel,Eco,925,2,1,2,4,1,2,1,1,2,4,3,2,3,1,1,0.0,neutral or dissatisfied +91288,96108,Female,Loyal Customer,12,Personal Travel,Eco,1090,1,3,1,4,2,1,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +91289,107127,Female,Loyal Customer,51,Personal Travel,Eco,842,4,5,4,1,5,4,4,2,2,4,2,5,2,5,11,2.0,satisfied +91290,33031,Male,Loyal Customer,8,Personal Travel,Eco,102,3,1,3,3,2,3,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +91291,126892,Male,Loyal Customer,46,Business travel,Business,2244,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +91292,90669,Female,Loyal Customer,12,Business travel,Business,3050,2,1,1,1,2,2,2,2,2,1,4,4,3,2,1,0.0,neutral or dissatisfied +91293,82566,Female,Loyal Customer,50,Business travel,Business,1710,1,1,1,1,5,4,5,3,3,4,3,5,3,3,0,2.0,satisfied +91294,117830,Male,Loyal Customer,63,Personal Travel,Eco,328,3,3,3,3,2,3,2,2,1,2,3,3,2,2,0,0.0,neutral or dissatisfied +91295,82494,Female,Loyal Customer,24,Personal Travel,Eco,488,1,0,1,1,5,1,5,5,3,5,4,4,4,5,23,90.0,neutral or dissatisfied +91296,10626,Female,disloyal Customer,33,Business travel,Eco,134,2,0,1,3,4,1,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +91297,82991,Male,Loyal Customer,65,Business travel,Eco,983,3,2,2,2,3,3,3,3,1,1,2,4,3,3,0,0.0,neutral or dissatisfied +91298,90622,Male,Loyal Customer,28,Business travel,Business,1820,4,4,4,4,3,3,3,3,5,3,5,3,4,3,0,0.0,satisfied +91299,76372,Female,Loyal Customer,43,Business travel,Business,2573,2,2,2,2,5,5,5,4,2,5,5,5,4,5,141,137.0,satisfied +91300,128453,Female,Loyal Customer,19,Personal Travel,Eco,325,1,5,1,2,3,1,3,3,1,5,1,2,3,3,3,1.0,neutral or dissatisfied +91301,126875,Male,Loyal Customer,62,Personal Travel,Eco,2296,1,5,0,1,3,0,3,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +91302,43305,Female,Loyal Customer,42,Business travel,Eco,436,2,4,4,4,4,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +91303,63087,Male,Loyal Customer,19,Personal Travel,Eco,967,3,4,3,4,4,3,2,4,3,2,5,4,4,4,0,0.0,neutral or dissatisfied +91304,82740,Female,Loyal Customer,50,Business travel,Business,409,4,4,2,4,2,4,4,5,5,5,5,3,5,3,0,23.0,satisfied +91305,88089,Female,Loyal Customer,56,Business travel,Business,240,2,2,2,2,5,5,5,5,2,4,4,5,5,5,147,139.0,satisfied +91306,123420,Male,Loyal Customer,24,Personal Travel,Eco,1337,3,5,3,4,4,3,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +91307,101785,Female,Loyal Customer,47,Business travel,Business,1521,1,1,1,1,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +91308,126604,Male,disloyal Customer,36,Business travel,Eco,1337,1,1,1,2,3,1,3,3,2,1,2,4,3,3,0,9.0,neutral or dissatisfied +91309,109384,Male,Loyal Customer,34,Personal Travel,Eco,1189,2,4,2,2,5,2,5,5,5,5,5,3,4,5,33,20.0,neutral or dissatisfied +91310,98456,Female,Loyal Customer,34,Business travel,Eco,210,3,4,4,4,3,3,3,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +91311,124921,Female,Loyal Customer,38,Business travel,Business,3943,5,3,3,3,4,3,4,5,5,4,5,2,5,3,3,32.0,neutral or dissatisfied +91312,93462,Male,Loyal Customer,45,Personal Travel,Eco,605,2,4,2,1,2,2,3,2,3,4,5,3,5,2,3,0.0,neutral or dissatisfied +91313,127667,Female,Loyal Customer,28,Business travel,Business,2153,4,4,4,4,4,4,4,4,1,2,2,1,2,4,0,0.0,neutral or dissatisfied +91314,70752,Male,Loyal Customer,31,Business travel,Business,1953,4,4,4,4,4,4,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +91315,85167,Female,Loyal Customer,48,Business travel,Business,813,3,2,2,2,5,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +91316,40635,Male,Loyal Customer,16,Business travel,Eco Plus,391,5,2,2,2,5,5,4,5,4,3,1,5,3,5,0,0.0,satisfied +91317,122540,Female,Loyal Customer,40,Business travel,Business,500,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +91318,43078,Female,Loyal Customer,35,Personal Travel,Eco,391,3,5,3,3,1,3,1,1,1,5,2,3,2,1,0,0.0,neutral or dissatisfied +91319,83852,Female,Loyal Customer,17,Personal Travel,Eco,425,2,0,4,3,5,4,5,5,1,3,4,4,4,5,1,4.0,neutral or dissatisfied +91320,18870,Male,Loyal Customer,20,Business travel,Business,1934,2,3,3,3,2,2,2,2,1,3,4,3,4,2,0,0.0,neutral or dissatisfied +91321,88141,Male,disloyal Customer,42,Business travel,Business,270,5,5,5,1,5,5,5,5,3,4,5,3,4,5,11,9.0,satisfied +91322,53684,Male,disloyal Customer,38,Business travel,Eco,1208,2,2,2,1,1,2,1,1,2,4,2,5,4,1,50,37.0,neutral or dissatisfied +91323,97535,Male,disloyal Customer,26,Business travel,Eco,675,3,3,3,3,2,3,2,2,2,3,3,3,3,2,4,0.0,neutral or dissatisfied +91324,20518,Female,Loyal Customer,41,Business travel,Business,3321,3,3,3,3,5,5,5,4,2,4,5,5,5,5,151,184.0,satisfied +91325,4697,Female,Loyal Customer,45,Personal Travel,Eco,364,3,1,3,3,2,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +91326,69634,Male,Loyal Customer,55,Business travel,Business,569,3,3,3,3,5,4,4,5,5,5,5,5,5,4,6,0.0,satisfied +91327,108051,Female,Loyal Customer,66,Personal Travel,Eco,591,4,5,4,4,4,4,5,3,3,4,3,3,3,5,105,84.0,neutral or dissatisfied +91328,127742,Male,disloyal Customer,38,Business travel,Eco,255,3,3,3,4,2,3,2,2,3,2,4,4,3,2,32,20.0,neutral or dissatisfied +91329,22308,Female,Loyal Customer,45,Business travel,Eco,83,2,4,4,4,3,2,3,2,2,2,2,2,2,3,0,0.0,satisfied +91330,115809,Female,Loyal Customer,52,Business travel,Business,3195,1,1,1,1,5,4,3,4,4,4,4,4,4,2,32,23.0,satisfied +91331,107808,Male,Loyal Customer,60,Business travel,Business,3494,0,0,0,4,4,5,4,4,4,4,4,5,4,3,24,8.0,satisfied +91332,21385,Male,Loyal Customer,68,Business travel,Business,3531,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +91333,125098,Male,disloyal Customer,38,Business travel,Business,361,2,2,2,4,3,2,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +91334,73509,Male,Loyal Customer,30,Business travel,Eco Plus,1182,3,3,3,3,3,3,3,3,4,3,3,4,3,3,2,0.0,neutral or dissatisfied +91335,107942,Male,Loyal Customer,21,Personal Travel,Eco,611,3,5,3,1,5,3,5,5,2,4,2,1,2,5,0,0.0,neutral or dissatisfied +91336,94573,Female,Loyal Customer,56,Business travel,Business,319,0,0,0,4,5,4,5,1,1,1,1,4,1,3,34,19.0,satisfied +91337,113511,Male,Loyal Customer,41,Business travel,Business,3857,4,4,5,4,2,5,5,4,4,4,4,3,4,5,6,0.0,satisfied +91338,80635,Female,disloyal Customer,24,Business travel,Business,282,4,4,4,1,1,4,1,1,3,3,4,4,5,1,8,0.0,satisfied +91339,85299,Female,Loyal Customer,21,Personal Travel,Eco,731,2,4,2,1,5,2,5,5,5,3,2,3,1,5,7,0.0,neutral or dissatisfied +91340,96784,Male,Loyal Customer,54,Business travel,Business,928,1,1,1,1,5,5,5,3,3,3,3,3,3,3,91,124.0,satisfied +91341,93701,Male,Loyal Customer,40,Business travel,Business,1452,5,5,1,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +91342,121678,Male,Loyal Customer,60,Personal Travel,Eco,328,3,0,3,3,4,3,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +91343,81521,Female,disloyal Customer,50,Business travel,Business,1124,2,2,2,3,3,2,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +91344,88772,Female,Loyal Customer,40,Business travel,Business,240,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +91345,51654,Male,disloyal Customer,23,Business travel,Eco,370,1,3,1,3,5,1,5,5,2,3,4,4,4,5,0,0.0,neutral or dissatisfied +91346,125130,Male,Loyal Customer,42,Personal Travel,Eco,361,3,5,3,2,2,3,4,2,4,3,4,4,5,2,13,30.0,neutral or dissatisfied +91347,34885,Male,Loyal Customer,27,Business travel,Eco Plus,2248,0,1,1,5,1,5,3,1,5,5,3,3,3,3,0,2.0,satisfied +91348,76206,Male,Loyal Customer,37,Business travel,Business,2422,5,5,5,5,4,3,5,3,3,2,3,4,3,3,9,29.0,satisfied +91349,88815,Female,Loyal Customer,24,Business travel,Eco Plus,406,2,4,4,4,2,2,2,2,1,2,3,2,4,2,14,12.0,neutral or dissatisfied +91350,22306,Female,Loyal Customer,24,Business travel,Business,3369,2,2,2,2,4,4,3,4,3,5,2,2,5,4,0,0.0,satisfied +91351,98834,Male,Loyal Customer,38,Personal Travel,Eco,763,3,5,3,1,5,3,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +91352,29165,Female,Loyal Customer,28,Business travel,Eco Plus,679,4,1,1,1,4,4,4,4,2,4,3,3,2,4,27,34.0,satisfied +91353,55232,Female,disloyal Customer,22,Business travel,Eco,1009,2,2,2,3,1,2,1,1,4,3,3,3,3,1,0,5.0,neutral or dissatisfied +91354,84278,Male,Loyal Customer,56,Personal Travel,Eco,334,1,5,1,5,4,1,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +91355,8439,Male,Loyal Customer,41,Business travel,Business,1881,5,5,5,5,2,5,4,2,2,2,2,4,2,3,59,66.0,satisfied +91356,15782,Female,Loyal Customer,64,Personal Travel,Eco,254,3,3,3,1,2,2,1,3,3,3,4,4,3,2,0,24.0,neutral or dissatisfied +91357,45185,Male,Loyal Customer,17,Personal Travel,Eco Plus,174,1,4,0,4,2,0,1,2,5,5,5,4,4,2,27,40.0,neutral or dissatisfied +91358,108731,Female,Loyal Customer,61,Personal Travel,Eco,591,3,5,3,4,4,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +91359,100072,Male,Loyal Customer,8,Personal Travel,Eco,289,2,4,2,4,1,2,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +91360,86695,Female,Loyal Customer,47,Business travel,Business,1747,4,4,4,4,5,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +91361,52443,Female,Loyal Customer,67,Personal Travel,Eco,751,4,5,4,3,3,5,5,5,5,4,3,3,5,4,0,0.0,neutral or dissatisfied +91362,75762,Female,Loyal Customer,46,Personal Travel,Eco,868,2,4,2,3,3,4,3,2,2,2,2,3,2,3,1,4.0,neutral or dissatisfied +91363,83560,Male,Loyal Customer,21,Personal Travel,Eco Plus,1865,4,2,4,2,2,4,2,2,1,4,3,4,3,2,74,80.0,neutral or dissatisfied +91364,51052,Female,Loyal Customer,51,Personal Travel,Eco,308,2,3,5,3,1,4,1,2,2,5,4,1,2,1,0,0.0,neutral or dissatisfied +91365,95432,Male,Loyal Customer,57,Business travel,Business,1534,1,1,1,1,4,5,4,4,4,4,4,4,4,4,0,1.0,satisfied +91366,105593,Female,Loyal Customer,38,Business travel,Business,3385,2,2,2,2,3,4,4,4,4,4,4,5,4,5,20,7.0,satisfied +91367,82452,Male,Loyal Customer,47,Business travel,Eco,502,4,5,1,5,4,4,4,4,3,1,4,2,4,4,0,19.0,neutral or dissatisfied +91368,83813,Male,Loyal Customer,52,Business travel,Business,1945,1,1,1,1,4,4,5,4,4,4,4,3,4,5,14,24.0,satisfied +91369,76359,Female,Loyal Customer,16,Personal Travel,Eco Plus,1851,2,4,2,2,2,2,2,2,2,1,4,5,1,2,0,3.0,neutral or dissatisfied +91370,84174,Female,disloyal Customer,72,Business travel,Eco,231,1,2,1,4,2,1,2,2,2,2,3,4,3,2,0,18.0,neutral or dissatisfied +91371,41610,Male,Loyal Customer,23,Personal Travel,Eco,1504,2,4,2,5,5,2,5,5,3,2,3,4,5,5,5,6.0,neutral or dissatisfied +91372,6195,Male,Loyal Customer,45,Business travel,Business,2772,3,5,3,3,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +91373,63510,Male,disloyal Customer,35,Business travel,Business,1009,4,4,4,3,4,4,3,4,2,4,2,4,2,4,1,0.0,neutral or dissatisfied +91374,7544,Male,Loyal Customer,56,Business travel,Business,3944,5,5,5,5,2,5,5,4,4,5,4,5,4,5,0,7.0,satisfied +91375,40691,Male,Loyal Customer,27,Business travel,Business,3978,4,5,4,4,5,5,5,5,2,5,2,4,1,5,0,0.0,satisfied +91376,52456,Male,Loyal Customer,46,Business travel,Eco Plus,370,5,1,4,1,5,5,5,5,2,3,2,5,5,5,0,0.0,satisfied +91377,61547,Male,Loyal Customer,48,Business travel,Business,2419,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +91378,77642,Male,Loyal Customer,26,Business travel,Business,3232,3,3,3,3,3,3,3,3,1,4,3,4,4,3,22,24.0,neutral or dissatisfied +91379,97375,Male,Loyal Customer,61,Personal Travel,Eco,843,3,4,3,2,3,3,3,3,3,5,4,3,5,3,2,6.0,neutral or dissatisfied +91380,55833,Female,disloyal Customer,41,Business travel,Eco,1416,3,3,3,3,1,3,1,1,3,5,4,1,3,1,7,4.0,neutral or dissatisfied +91381,120559,Male,Loyal Customer,35,Business travel,Business,2176,2,4,4,4,2,2,2,4,5,3,4,2,1,2,6,61.0,neutral or dissatisfied +91382,100123,Female,Loyal Customer,39,Business travel,Business,725,5,4,5,5,5,5,5,5,4,5,4,5,3,5,282,263.0,satisfied +91383,63952,Female,Loyal Customer,46,Personal Travel,Eco,1172,3,3,3,3,4,2,4,3,3,3,3,2,3,1,48,66.0,neutral or dissatisfied +91384,80813,Female,Loyal Customer,39,Business travel,Business,692,2,2,2,2,5,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +91385,61470,Female,Loyal Customer,40,Business travel,Business,2288,1,1,1,1,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +91386,69080,Male,Loyal Customer,30,Personal Travel,Eco,1389,3,5,3,3,2,3,2,2,5,2,4,1,2,2,14,41.0,neutral or dissatisfied +91387,111713,Female,Loyal Customer,58,Personal Travel,Eco,495,5,5,5,3,4,5,5,3,3,5,3,4,3,3,0,6.0,satisfied +91388,9361,Female,Loyal Customer,50,Business travel,Business,2643,4,4,4,4,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +91389,100679,Female,Loyal Customer,53,Business travel,Eco,889,3,1,4,1,4,3,3,3,3,3,3,3,3,1,71,63.0,neutral or dissatisfied +91390,57393,Male,Loyal Customer,57,Business travel,Business,472,1,1,1,1,3,3,4,1,1,1,1,1,1,2,78,56.0,neutral or dissatisfied +91391,61543,Female,Loyal Customer,43,Personal Travel,Eco,2288,5,2,5,4,4,4,4,1,1,5,1,4,1,2,30,0.0,satisfied +91392,24818,Female,disloyal Customer,20,Business travel,Eco,861,2,2,2,3,2,4,4,2,4,2,2,4,4,4,131,108.0,neutral or dissatisfied +91393,21595,Female,Loyal Customer,37,Business travel,Business,2494,1,1,1,1,1,2,4,4,4,5,4,1,4,3,7,0.0,satisfied +91394,64808,Female,Loyal Customer,42,Business travel,Business,2866,5,5,5,5,3,4,4,5,5,5,5,3,5,4,128,128.0,satisfied +91395,30020,Female,Loyal Customer,40,Business travel,Business,2851,2,3,3,3,2,3,4,2,2,2,2,3,2,1,34,43.0,neutral or dissatisfied +91396,114518,Male,disloyal Customer,21,Business travel,Eco,337,2,1,2,2,3,2,2,3,1,2,2,3,1,3,5,12.0,neutral or dissatisfied +91397,24469,Female,Loyal Customer,36,Business travel,Business,547,1,1,1,1,3,5,2,5,5,5,5,1,5,5,7,0.0,satisfied +91398,122888,Female,Loyal Customer,55,Business travel,Business,1621,2,2,2,2,2,4,4,5,5,5,5,4,5,4,1,24.0,satisfied +91399,18988,Male,Loyal Customer,56,Business travel,Business,451,2,3,3,3,5,3,4,2,2,2,2,1,2,3,97,78.0,neutral or dissatisfied +91400,99242,Male,Loyal Customer,52,Personal Travel,Eco,495,2,5,4,4,5,4,5,5,5,4,5,4,4,5,0,5.0,neutral or dissatisfied +91401,13949,Female,Loyal Customer,40,Personal Travel,Eco,192,5,5,5,4,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +91402,59005,Male,Loyal Customer,36,Business travel,Business,1744,2,2,2,2,2,4,4,3,3,2,3,5,3,3,11,21.0,satisfied +91403,85992,Male,disloyal Customer,36,Business travel,Eco,447,3,3,3,4,1,3,1,1,3,1,4,4,4,1,4,0.0,neutral or dissatisfied +91404,74426,Male,disloyal Customer,29,Business travel,Business,1242,4,4,4,3,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +91405,52784,Female,Loyal Customer,9,Business travel,Business,1874,2,5,5,5,2,3,2,2,2,3,4,2,4,2,0,42.0,neutral or dissatisfied +91406,20835,Female,Loyal Customer,38,Business travel,Business,457,4,3,4,4,4,3,1,4,4,4,4,5,4,1,0,0.0,satisfied +91407,82299,Male,Loyal Customer,55,Business travel,Business,1795,1,1,1,1,4,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +91408,116768,Female,Loyal Customer,52,Personal Travel,Eco Plus,308,2,4,2,2,5,4,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +91409,117978,Male,Loyal Customer,14,Personal Travel,Eco,601,4,4,4,4,1,4,1,1,3,4,4,3,5,1,2,3.0,neutral or dissatisfied +91410,64321,Male,Loyal Customer,46,Business travel,Business,3993,2,2,4,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +91411,82698,Male,Loyal Customer,33,Business travel,Business,632,1,3,2,3,1,1,1,1,1,1,3,1,2,1,0,0.0,neutral or dissatisfied +91412,12366,Male,Loyal Customer,70,Business travel,Eco,201,2,1,5,1,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +91413,44956,Male,Loyal Customer,50,Personal Travel,Eco,397,4,5,4,3,5,4,5,5,3,5,4,5,5,5,3,3.0,neutral or dissatisfied +91414,65355,Female,Loyal Customer,54,Business travel,Business,2942,1,1,2,1,5,4,4,5,5,5,5,3,5,5,2,7.0,satisfied +91415,124652,Male,Loyal Customer,19,Personal Travel,Business,399,2,4,2,2,4,2,1,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +91416,97532,Female,disloyal Customer,70,Business travel,Business,439,1,0,0,3,1,1,1,1,4,2,4,3,5,1,24,21.0,neutral or dissatisfied +91417,8450,Male,disloyal Customer,20,Business travel,Eco,1379,4,4,4,2,5,4,5,5,5,5,5,3,5,5,49,49.0,satisfied +91418,37153,Female,Loyal Customer,66,Business travel,Business,729,2,2,2,2,3,4,2,4,4,4,4,2,4,4,7,18.0,satisfied +91419,7489,Male,Loyal Customer,9,Business travel,Business,3612,4,3,3,3,4,4,4,4,3,1,4,1,3,4,0,0.0,neutral or dissatisfied +91420,72090,Female,Loyal Customer,23,Personal Travel,Eco,2504,1,4,1,4,2,1,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +91421,53692,Male,Loyal Customer,31,Business travel,Eco,1208,5,5,1,5,5,5,5,5,2,4,2,3,5,5,81,87.0,satisfied +91422,123305,Female,Loyal Customer,59,Business travel,Business,2209,2,2,2,2,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +91423,117442,Female,Loyal Customer,49,Business travel,Business,1107,1,1,1,1,5,4,4,3,3,3,3,3,3,4,21,15.0,satisfied +91424,53456,Male,disloyal Customer,8,Business travel,Eco,2419,2,2,2,4,2,4,4,3,1,3,3,4,3,4,0,23.0,neutral or dissatisfied +91425,57711,Female,Loyal Customer,59,Personal Travel,Eco,867,1,2,1,4,2,4,3,4,4,1,4,1,4,3,19,20.0,neutral or dissatisfied +91426,64648,Male,disloyal Customer,37,Business travel,Business,247,2,2,2,4,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +91427,6016,Female,Loyal Customer,27,Business travel,Business,2787,2,5,5,5,2,2,2,2,1,2,4,1,3,2,4,0.0,neutral or dissatisfied +91428,8488,Male,Loyal Customer,22,Business travel,Eco,677,4,2,2,2,4,4,3,4,3,3,3,2,2,4,28,31.0,neutral or dissatisfied +91429,120031,Female,disloyal Customer,15,Business travel,Eco,511,2,3,2,4,4,2,2,4,3,5,3,4,3,4,24,35.0,neutral or dissatisfied +91430,84316,Female,Loyal Customer,41,Business travel,Business,3912,2,2,2,2,5,5,5,4,4,4,4,3,4,3,13,69.0,satisfied +91431,111055,Male,disloyal Customer,50,Business travel,Business,268,2,2,2,2,5,2,5,5,3,3,1,3,2,5,7,12.0,neutral or dissatisfied +91432,122522,Female,Loyal Customer,44,Business travel,Business,500,2,2,2,2,3,4,4,5,5,4,5,3,5,4,14,0.0,satisfied +91433,73786,Male,Loyal Customer,24,Business travel,Business,192,5,5,4,5,4,4,4,4,3,3,4,3,4,4,33,34.0,satisfied +91434,55405,Male,disloyal Customer,40,Business travel,Business,1558,2,3,3,3,4,3,4,4,3,2,5,4,5,4,12,8.0,neutral or dissatisfied +91435,64329,Male,Loyal Customer,26,Business travel,Business,2079,2,2,2,2,3,4,3,3,5,3,4,3,5,3,0,0.0,satisfied +91436,97084,Male,disloyal Customer,27,Business travel,Business,715,4,4,4,2,2,4,2,2,3,5,4,5,5,2,1,5.0,satisfied +91437,25075,Male,Loyal Customer,47,Business travel,Eco,957,3,3,3,3,3,3,3,3,2,1,3,1,4,3,83,73.0,neutral or dissatisfied +91438,48249,Male,Loyal Customer,16,Personal Travel,Eco,192,4,5,4,2,4,4,4,4,3,2,5,4,5,4,49,51.0,neutral or dissatisfied +91439,87629,Male,Loyal Customer,33,Business travel,Business,2414,2,2,2,2,4,4,4,4,4,3,5,5,4,4,0,0.0,satisfied +91440,34769,Male,disloyal Customer,20,Business travel,Eco,264,3,1,3,4,5,3,5,5,3,3,4,4,3,5,0,0.0,neutral or dissatisfied +91441,1732,Male,Loyal Customer,37,Business travel,Business,1692,3,4,4,4,3,4,4,3,3,3,3,2,3,2,30,38.0,neutral or dissatisfied +91442,85690,Female,Loyal Customer,46,Business travel,Business,1547,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +91443,129792,Male,Loyal Customer,22,Personal Travel,Eco,308,1,5,1,2,4,1,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +91444,122352,Female,disloyal Customer,24,Business travel,Business,529,4,5,4,4,3,4,5,3,5,3,5,3,4,3,0,0.0,satisfied +91445,70535,Male,disloyal Customer,22,Business travel,Eco,1258,5,5,5,1,4,5,4,4,3,4,4,4,4,4,0,0.0,satisfied +91446,117241,Male,Loyal Customer,49,Personal Travel,Eco,304,3,3,3,3,4,3,5,4,3,3,4,4,1,4,3,0.0,neutral or dissatisfied +91447,73583,Female,Loyal Customer,52,Business travel,Business,3714,0,4,0,3,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +91448,93210,Male,Loyal Customer,48,Personal Travel,Eco,1845,2,5,2,2,5,2,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +91449,128688,Female,Loyal Customer,43,Personal Travel,Eco,2288,3,4,3,5,3,4,4,1,4,4,4,4,1,4,4,11.0,neutral or dissatisfied +91450,51145,Male,Loyal Customer,34,Personal Travel,Eco,158,1,5,0,3,4,0,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +91451,50686,Female,Loyal Customer,43,Personal Travel,Eco,89,2,4,2,1,4,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +91452,78288,Female,Loyal Customer,59,Business travel,Business,1598,3,2,2,2,3,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +91453,123216,Female,Loyal Customer,49,Personal Travel,Eco,631,3,4,3,5,2,4,4,4,4,3,4,3,4,4,13,17.0,neutral or dissatisfied +91454,42915,Female,Loyal Customer,7,Personal Travel,Eco,200,2,3,0,4,4,0,4,4,3,2,2,3,2,4,0,0.0,neutral or dissatisfied +91455,92766,Female,Loyal Customer,25,Personal Travel,Eco Plus,1276,4,4,5,1,2,5,2,2,5,5,3,3,4,2,0,0.0,satisfied +91456,106982,Female,Loyal Customer,43,Personal Travel,Eco,1036,2,1,2,3,2,4,3,1,1,2,3,1,1,3,0,2.0,neutral or dissatisfied +91457,101980,Male,Loyal Customer,62,Personal Travel,Eco,628,1,5,1,2,3,1,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +91458,49650,Female,Loyal Customer,37,Business travel,Business,250,1,4,2,2,2,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +91459,123774,Female,Loyal Customer,16,Personal Travel,Business,546,1,3,1,3,1,1,1,1,1,5,4,5,5,1,0,10.0,neutral or dissatisfied +91460,56719,Female,Loyal Customer,32,Personal Travel,Eco,1023,2,4,2,2,2,3,3,3,5,5,4,3,3,3,156,152.0,neutral or dissatisfied +91461,44928,Male,Loyal Customer,36,Personal Travel,Eco,258,3,4,3,4,5,3,5,5,1,4,3,4,3,5,70,105.0,neutral or dissatisfied +91462,7715,Male,Loyal Customer,51,Business travel,Business,3143,3,3,3,3,3,4,4,4,4,4,4,4,4,3,0,6.0,satisfied +91463,23348,Female,Loyal Customer,49,Business travel,Eco Plus,674,2,2,2,2,3,2,4,2,2,2,2,5,2,5,0,0.0,satisfied +91464,30779,Male,Loyal Customer,65,Business travel,Business,3987,2,2,2,2,3,1,2,4,4,4,4,5,4,1,21,25.0,satisfied +91465,85866,Female,Loyal Customer,24,Personal Travel,Business,2172,3,1,3,3,4,3,2,4,4,3,2,2,2,4,0,4.0,neutral or dissatisfied +91466,72941,Male,Loyal Customer,17,Business travel,Business,1089,2,2,2,2,4,5,4,4,4,4,4,3,4,4,10,0.0,satisfied +91467,16473,Male,Loyal Customer,23,Business travel,Eco Plus,445,5,3,3,3,5,5,3,5,3,5,3,2,4,5,82,91.0,satisfied +91468,97559,Male,disloyal Customer,38,Business travel,Business,337,2,2,2,2,1,2,1,1,3,3,5,5,5,1,63,61.0,neutral or dissatisfied +91469,23510,Male,Loyal Customer,57,Business travel,Business,1698,0,0,0,3,1,3,5,5,5,5,5,5,5,2,8,12.0,satisfied +91470,44424,Male,disloyal Customer,15,Business travel,Eco,542,0,0,0,2,3,0,1,3,5,3,4,3,4,3,10,0.0,satisfied +91471,89752,Male,Loyal Customer,22,Personal Travel,Eco,1076,1,4,1,4,5,1,5,5,3,4,5,3,4,5,0,26.0,neutral or dissatisfied +91472,28424,Female,Loyal Customer,60,Business travel,Eco,1399,2,5,5,5,4,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +91473,46238,Female,disloyal Customer,27,Business travel,Eco,524,2,0,2,1,3,2,3,3,3,3,4,5,1,3,0,0.0,neutral or dissatisfied +91474,55322,Female,disloyal Customer,23,Business travel,Eco,1325,2,2,2,4,2,2,5,2,1,2,4,3,3,2,0,0.0,neutral or dissatisfied +91475,76119,Female,Loyal Customer,54,Business travel,Business,2770,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +91476,129403,Female,Loyal Customer,41,Business travel,Business,236,4,4,4,4,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +91477,58441,Female,Loyal Customer,50,Personal Travel,Eco,723,2,4,2,3,2,2,4,4,4,2,4,3,4,2,7,0.0,neutral or dissatisfied +91478,111032,Male,Loyal Customer,32,Business travel,Business,3040,4,5,4,4,4,4,4,4,1,1,4,2,3,4,31,31.0,neutral or dissatisfied +91479,49298,Male,Loyal Customer,63,Business travel,Business,363,4,4,4,4,1,1,3,5,5,5,5,4,5,5,0,0.0,satisfied +91480,2785,Female,Loyal Customer,49,Business travel,Business,1589,4,4,2,4,4,4,4,4,3,4,5,4,4,4,180,221.0,satisfied +91481,18953,Male,Loyal Customer,9,Personal Travel,Eco,448,4,5,4,5,4,4,4,4,2,1,5,3,1,4,17,14.0,neutral or dissatisfied +91482,36563,Male,Loyal Customer,32,Business travel,Eco,1237,5,2,5,2,5,5,5,5,1,4,5,2,4,5,25,124.0,satisfied +91483,110424,Male,Loyal Customer,45,Business travel,Business,2577,2,4,2,2,4,2,5,4,4,4,4,1,4,3,0,0.0,satisfied +91484,43650,Male,Loyal Customer,26,Business travel,Business,1659,1,1,1,1,5,5,5,5,4,1,3,1,3,5,0,14.0,satisfied +91485,10052,Male,Loyal Customer,65,Personal Travel,Eco,326,2,3,2,5,5,2,5,5,1,5,3,5,5,5,0,0.0,neutral or dissatisfied +91486,65426,Female,Loyal Customer,10,Business travel,Business,2165,3,2,2,2,3,3,3,3,1,2,2,4,3,3,0,0.0,neutral or dissatisfied +91487,96680,Male,Loyal Customer,21,Personal Travel,Eco Plus,937,2,4,2,4,2,2,2,2,1,1,1,5,1,2,0,0.0,neutral or dissatisfied +91488,59198,Female,Loyal Customer,24,Business travel,Business,1440,1,3,3,3,1,1,1,1,4,4,3,2,4,1,13,9.0,neutral or dissatisfied +91489,29865,Female,Loyal Customer,33,Business travel,Business,2872,5,5,5,5,1,5,5,4,4,4,3,3,4,1,0,0.0,satisfied +91490,66997,Male,Loyal Customer,47,Business travel,Business,1119,4,4,4,4,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +91491,60802,Female,Loyal Customer,57,Personal Travel,Eco,472,4,4,4,4,2,4,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +91492,7537,Female,Loyal Customer,16,Personal Travel,Eco,762,1,4,1,2,1,4,4,5,4,4,4,4,3,4,243,256.0,neutral or dissatisfied +91493,12396,Female,Loyal Customer,37,Business travel,Eco,190,4,1,1,1,4,4,4,4,5,2,2,4,4,4,3,0.0,satisfied +91494,44026,Male,disloyal Customer,40,Business travel,Eco Plus,680,5,5,5,3,2,5,2,2,1,4,1,3,1,2,4,0.0,satisfied +91495,51946,Female,Loyal Customer,38,Business travel,Eco,843,5,4,2,4,5,5,5,5,5,5,1,1,2,5,0,0.0,satisfied +91496,88858,Female,Loyal Customer,35,Business travel,Eco Plus,271,1,4,4,4,1,1,1,1,3,1,3,3,3,1,0,31.0,neutral or dissatisfied +91497,81418,Female,Loyal Customer,30,Business travel,Business,393,3,5,3,5,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +91498,118615,Female,disloyal Customer,27,Business travel,Eco,647,3,1,3,4,3,3,3,3,4,5,3,4,3,3,85,77.0,neutral or dissatisfied +91499,100867,Female,Loyal Customer,23,Business travel,Business,1605,3,2,2,2,3,3,3,3,2,3,4,3,3,3,0,9.0,neutral or dissatisfied +91500,110756,Male,Loyal Customer,28,Business travel,Business,3732,1,1,5,1,5,5,5,5,3,3,4,5,5,5,3,0.0,satisfied +91501,52953,Male,Loyal Customer,15,Personal Travel,Eco,1448,4,5,4,4,2,4,5,2,5,1,3,5,3,2,0,0.0,neutral or dissatisfied +91502,30345,Female,Loyal Customer,67,Personal Travel,Eco,391,1,4,1,4,5,5,5,1,1,1,4,3,1,5,0,0.0,neutral or dissatisfied +91503,60469,Female,Loyal Customer,55,Business travel,Business,862,2,2,4,2,1,2,2,2,2,2,2,3,2,1,61,64.0,neutral or dissatisfied +91504,31426,Male,Loyal Customer,11,Personal Travel,Eco,1546,4,5,4,3,4,4,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +91505,73732,Male,Loyal Customer,63,Personal Travel,Eco,192,4,5,4,4,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +91506,60428,Male,Loyal Customer,8,Personal Travel,Business,862,2,1,2,3,3,2,3,3,4,5,4,3,3,3,10,35.0,neutral or dissatisfied +91507,15490,Female,Loyal Customer,62,Personal Travel,Eco,164,2,4,2,2,3,5,4,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +91508,23852,Male,disloyal Customer,37,Business travel,Eco,552,2,4,2,4,2,2,2,2,4,1,1,4,5,2,106,118.0,neutral or dissatisfied +91509,87944,Male,Loyal Customer,7,Personal Travel,Business,250,3,5,3,4,3,3,3,3,3,5,5,5,4,3,0,3.0,neutral or dissatisfied +91510,6423,Female,Loyal Customer,50,Personal Travel,Eco,240,1,4,1,3,5,3,3,5,5,1,5,1,5,4,1,39.0,neutral or dissatisfied +91511,122633,Female,Loyal Customer,41,Business travel,Business,2340,4,4,4,4,2,5,5,4,4,4,4,5,4,4,16,9.0,satisfied +91512,26158,Male,Loyal Customer,33,Business travel,Business,581,2,2,2,2,4,4,4,4,3,2,4,1,5,4,1,0.0,satisfied +91513,100207,Female,disloyal Customer,26,Business travel,Eco,762,3,3,3,3,5,3,5,5,1,5,3,2,3,5,8,12.0,neutral or dissatisfied +91514,125685,Male,Loyal Customer,44,Business travel,Eco,814,1,3,3,3,1,1,1,1,3,2,4,4,3,1,0,1.0,neutral or dissatisfied +91515,5159,Male,Loyal Customer,45,Personal Travel,Eco,622,2,1,2,4,3,2,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +91516,49563,Male,Loyal Customer,29,Business travel,Business,326,2,2,2,2,4,4,4,4,3,4,5,4,3,4,0,0.0,satisfied +91517,107584,Female,Loyal Customer,49,Personal Travel,Eco Plus,1521,3,4,3,4,3,5,5,5,5,3,5,4,5,5,31,23.0,neutral or dissatisfied +91518,122407,Male,Loyal Customer,9,Personal Travel,Eco Plus,529,3,5,3,1,4,3,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +91519,11418,Male,Loyal Customer,22,Business travel,Business,166,2,2,2,2,5,4,5,5,5,3,4,4,4,5,0,0.0,satisfied +91520,36207,Female,Loyal Customer,39,Business travel,Business,2137,3,2,2,2,2,4,4,3,3,3,3,3,3,4,20,10.0,neutral or dissatisfied +91521,122963,Female,Loyal Customer,46,Business travel,Business,3141,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,4.0,satisfied +91522,125262,Male,Loyal Customer,46,Business travel,Business,1488,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,7.0,satisfied +91523,69901,Male,Loyal Customer,53,Business travel,Business,1514,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +91524,63393,Female,Loyal Customer,64,Personal Travel,Eco,337,2,4,3,2,3,5,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +91525,125937,Female,Loyal Customer,15,Personal Travel,Eco,1013,1,1,1,4,3,1,1,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +91526,124329,Female,Loyal Customer,69,Personal Travel,Eco Plus,255,2,2,0,3,2,4,3,4,4,0,4,1,4,3,0,0.0,neutral or dissatisfied +91527,6999,Female,disloyal Customer,22,Business travel,Eco,196,2,0,3,5,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +91528,69006,Female,disloyal Customer,37,Business travel,Business,1389,3,3,3,3,5,3,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +91529,34107,Female,Loyal Customer,40,Business travel,Eco,1189,2,1,1,1,2,2,2,2,3,3,4,2,4,2,0,8.0,satisfied +91530,116557,Male,Loyal Customer,21,Personal Travel,Eco,333,2,5,2,1,1,2,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +91531,19060,Male,Loyal Customer,27,Business travel,Eco,569,5,5,3,3,5,5,5,5,2,3,4,5,1,5,0,50.0,satisfied +91532,36460,Male,Loyal Customer,66,Personal Travel,Eco,867,2,5,2,1,2,2,2,2,5,2,2,5,4,2,70,83.0,neutral or dissatisfied +91533,79084,Male,Loyal Customer,49,Personal Travel,Eco,331,2,5,2,3,4,2,1,4,4,4,4,5,5,4,0,14.0,neutral or dissatisfied +91534,39582,Female,Loyal Customer,14,Business travel,Business,679,2,2,2,2,5,5,5,5,3,3,5,3,2,5,0,0.0,satisfied +91535,72250,Female,Loyal Customer,66,Business travel,Business,919,2,2,2,2,4,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +91536,32737,Male,Loyal Customer,63,Business travel,Eco,101,4,5,5,5,4,4,4,4,5,3,1,3,2,4,0,0.0,satisfied +91537,26032,Male,Loyal Customer,33,Personal Travel,Eco,321,3,4,3,4,4,3,4,4,4,4,3,4,3,4,0,0.0,neutral or dissatisfied +91538,6135,Male,disloyal Customer,28,Business travel,Business,501,5,5,5,3,1,5,1,1,3,3,4,3,5,1,0,0.0,satisfied +91539,100138,Female,Loyal Customer,59,Business travel,Business,3318,5,5,5,5,5,5,5,3,5,5,4,5,4,5,191,177.0,satisfied +91540,109863,Male,disloyal Customer,23,Business travel,Eco,1034,2,2,2,1,2,2,3,2,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +91541,39139,Female,Loyal Customer,13,Personal Travel,Eco,228,3,5,3,3,1,3,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +91542,20570,Female,Loyal Customer,43,Business travel,Business,3956,1,1,1,1,2,3,4,5,5,5,5,2,5,1,61,69.0,satisfied +91543,35135,Male,disloyal Customer,23,Business travel,Eco,1076,5,5,5,1,2,5,2,2,4,1,5,1,2,2,0,0.0,satisfied +91544,36395,Male,Loyal Customer,7,Personal Travel,Eco,2381,2,5,2,2,3,2,3,3,4,2,5,2,5,3,0,0.0,neutral or dissatisfied +91545,17663,Male,Loyal Customer,13,Personal Travel,Eco,1008,1,5,2,5,5,2,5,5,5,3,4,4,4,5,45,30.0,neutral or dissatisfied +91546,91528,Female,Loyal Customer,14,Business travel,Business,680,1,1,1,1,5,5,5,5,4,4,4,5,5,5,81,108.0,satisfied +91547,112933,Male,Loyal Customer,28,Personal Travel,Eco,1129,4,5,4,4,4,4,4,4,5,5,4,3,4,4,3,4.0,neutral or dissatisfied +91548,10591,Female,disloyal Customer,38,Business travel,Business,216,3,4,4,3,4,4,4,4,5,2,5,5,5,4,0,4.0,neutral or dissatisfied +91549,63066,Female,Loyal Customer,62,Personal Travel,Eco,862,3,4,2,3,4,1,1,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +91550,71553,Female,disloyal Customer,25,Business travel,Eco,1182,2,1,1,4,3,1,3,3,3,4,3,1,4,3,13,17.0,neutral or dissatisfied +91551,18224,Male,Loyal Customer,51,Business travel,Eco,224,4,3,4,4,4,4,4,4,5,2,4,1,2,4,0,0.0,satisfied +91552,118658,Female,disloyal Customer,36,Business travel,Eco,304,2,2,2,2,1,2,1,1,3,3,2,2,3,1,8,10.0,neutral or dissatisfied +91553,30814,Female,Loyal Customer,15,Business travel,Business,2538,3,3,3,3,3,2,3,3,4,5,2,2,3,3,7,0.0,neutral or dissatisfied +91554,5676,Male,Loyal Customer,35,Business travel,Business,3190,2,2,2,2,5,3,4,2,2,2,2,2,2,2,26,26.0,neutral or dissatisfied +91555,3011,Male,Loyal Customer,26,Business travel,Eco,862,3,3,3,3,3,3,1,3,2,1,4,3,4,3,2,0.0,neutral or dissatisfied +91556,73797,Male,Loyal Customer,50,Business travel,Eco Plus,192,4,5,5,5,4,4,4,4,2,5,4,2,4,4,9,22.0,neutral or dissatisfied +91557,73254,Male,disloyal Customer,37,Business travel,Business,275,3,4,4,1,1,4,1,1,5,2,5,1,4,1,0,0.0,neutral or dissatisfied +91558,81281,Male,disloyal Customer,26,Business travel,Business,1020,2,2,2,1,3,2,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +91559,17626,Female,Loyal Customer,60,Business travel,Business,3387,1,1,2,1,4,4,5,4,4,4,4,4,4,5,23,19.0,satisfied +91560,128619,Female,Loyal Customer,63,Business travel,Eco,954,3,4,4,4,1,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +91561,43586,Female,disloyal Customer,25,Business travel,Business,228,3,5,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +91562,13677,Male,Loyal Customer,60,Personal Travel,Eco,462,1,3,1,4,3,1,3,3,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +91563,109287,Male,Loyal Customer,57,Business travel,Business,3463,1,1,1,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +91564,41158,Male,Loyal Customer,29,Personal Travel,Eco,429,4,1,4,2,3,4,3,3,1,5,2,4,3,3,0,0.0,satisfied +91565,26430,Male,Loyal Customer,66,Business travel,Eco,842,4,3,2,3,4,4,4,4,1,4,2,4,5,4,0,0.0,satisfied +91566,65050,Female,Loyal Customer,63,Personal Travel,Eco,190,2,2,2,3,3,2,2,3,3,2,3,3,3,2,4,0.0,neutral or dissatisfied +91567,48251,Male,Loyal Customer,55,Personal Travel,Eco,236,4,5,4,3,4,4,4,4,5,5,5,5,4,4,0,3.0,neutral or dissatisfied +91568,64704,Female,Loyal Customer,32,Business travel,Business,551,2,2,2,2,4,4,4,4,4,2,4,3,4,4,0,0.0,satisfied +91569,28911,Male,Loyal Customer,37,Business travel,Eco,978,1,3,3,3,1,1,1,1,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +91570,25928,Female,Loyal Customer,17,Business travel,Business,3774,2,4,4,4,2,3,2,2,1,5,3,2,4,2,0,4.0,neutral or dissatisfied +91571,126810,Male,Loyal Customer,58,Business travel,Business,2296,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +91572,94495,Female,Loyal Customer,39,Business travel,Business,277,3,5,5,5,3,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +91573,59822,Male,Loyal Customer,28,Personal Travel,Business,937,4,2,4,3,2,4,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +91574,60758,Male,disloyal Customer,40,Business travel,Business,628,4,4,4,2,5,4,1,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +91575,53796,Female,Loyal Customer,66,Business travel,Business,140,5,5,5,5,2,3,2,4,4,4,4,2,4,1,32,35.0,satisfied +91576,31958,Female,disloyal Customer,26,Business travel,Business,102,3,3,3,4,4,3,3,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +91577,110080,Female,Loyal Customer,25,Personal Travel,Business,882,2,2,2,4,4,2,3,4,4,4,3,1,4,4,5,0.0,neutral or dissatisfied +91578,112912,Male,Loyal Customer,39,Business travel,Eco,990,2,5,5,5,2,2,2,2,3,2,3,1,3,2,22,10.0,neutral or dissatisfied +91579,19617,Female,Loyal Customer,47,Personal Travel,Eco,416,3,3,2,3,4,4,3,1,1,2,1,1,1,5,0,,neutral or dissatisfied +91580,26598,Female,disloyal Customer,37,Business travel,Eco,270,0,3,0,4,2,0,2,2,4,3,3,3,3,2,14,41.0,satisfied +91581,16924,Female,Loyal Customer,25,Business travel,Business,2490,5,5,2,5,4,4,4,4,1,3,4,1,5,4,0,0.0,satisfied +91582,5747,Male,disloyal Customer,25,Business travel,Business,859,2,0,2,3,4,2,4,4,4,2,5,4,5,4,0,1.0,neutral or dissatisfied +91583,72046,Male,Loyal Customer,25,Business travel,Business,2486,2,2,2,2,5,5,5,5,4,2,5,3,5,5,3,0.0,satisfied +91584,93613,Male,Loyal Customer,18,Business travel,Business,1654,5,5,5,5,3,3,3,3,4,5,4,4,4,3,0,0.0,satisfied +91585,120960,Male,Loyal Customer,60,Business travel,Business,2842,1,1,1,1,2,5,4,3,3,3,3,5,3,3,32,48.0,satisfied +91586,94040,Male,Loyal Customer,54,Business travel,Business,2378,2,5,2,2,3,5,5,5,5,5,5,4,5,5,11,0.0,satisfied +91587,73669,Male,Loyal Customer,47,Business travel,Business,2544,3,3,3,3,2,4,5,4,4,4,5,5,4,4,2,0.0,satisfied +91588,8236,Male,Loyal Customer,32,Personal Travel,Eco,335,3,5,3,3,1,3,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +91589,10852,Male,disloyal Customer,18,Business travel,Eco,458,4,2,4,4,2,4,2,2,4,4,3,4,4,2,22,38.0,neutral or dissatisfied +91590,129784,Female,Loyal Customer,7,Personal Travel,Eco,337,5,4,5,2,2,5,2,2,5,3,2,4,2,2,0,0.0,satisfied +91591,100923,Male,disloyal Customer,27,Business travel,Business,838,5,5,5,2,4,5,4,4,3,5,5,5,4,4,0,0.0,satisfied +91592,95497,Female,Loyal Customer,36,Business travel,Eco Plus,239,3,1,1,1,3,3,3,3,2,2,4,2,4,3,14,12.0,neutral or dissatisfied +91593,9761,Male,Loyal Customer,53,Business travel,Business,1515,2,2,2,2,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +91594,30187,Male,Loyal Customer,46,Business travel,Eco Plus,261,4,4,4,4,4,4,4,4,4,1,4,3,3,4,0,1.0,neutral or dissatisfied +91595,10908,Female,Loyal Customer,36,Business travel,Business,312,2,4,4,4,2,3,4,2,2,2,2,1,2,2,43,41.0,neutral or dissatisfied +91596,1765,Male,Loyal Customer,49,Business travel,Business,2951,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +91597,43889,Female,Loyal Customer,39,Business travel,Business,3178,1,1,1,1,5,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +91598,92814,Male,Loyal Customer,15,Business travel,Business,1541,4,3,4,4,4,4,4,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +91599,98151,Male,Loyal Customer,60,Business travel,Business,3058,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +91600,54012,Female,Loyal Customer,57,Business travel,Eco,1091,4,4,4,4,3,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +91601,115487,Male,disloyal Customer,27,Business travel,Eco,337,3,1,3,4,3,3,2,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +91602,91465,Female,Loyal Customer,72,Business travel,Business,3008,2,4,4,4,5,2,3,2,2,2,2,4,2,2,6,7.0,neutral or dissatisfied +91603,91607,Female,disloyal Customer,50,Business travel,Business,1184,5,5,5,1,4,5,1,4,5,4,5,3,4,4,0,0.0,satisfied +91604,129149,Male,disloyal Customer,23,Business travel,Business,954,4,0,5,1,2,5,3,2,5,2,5,4,5,2,64,56.0,satisfied +91605,100405,Female,disloyal Customer,24,Business travel,Eco,1079,3,4,4,4,3,4,3,3,2,4,4,3,3,3,1,0.0,neutral or dissatisfied +91606,111254,Female,Loyal Customer,46,Business travel,Eco,472,2,4,4,4,5,4,4,1,1,2,1,1,1,1,13,0.0,neutral or dissatisfied +91607,57734,Female,Loyal Customer,43,Business travel,Eco,1754,1,3,3,3,1,1,2,1,1,1,1,2,1,3,9,0.0,neutral or dissatisfied +91608,58524,Male,Loyal Customer,10,Personal Travel,Eco,719,4,3,4,2,3,4,3,3,2,3,3,1,2,3,2,0.0,neutral or dissatisfied +91609,112762,Male,Loyal Customer,50,Business travel,Business,2467,3,3,3,3,3,5,5,1,1,2,1,5,1,5,0,9.0,satisfied +91610,44721,Male,Loyal Customer,48,Personal Travel,Eco,67,1,3,1,3,5,1,5,5,4,1,2,1,2,5,0,0.0,neutral or dissatisfied +91611,97605,Male,Loyal Customer,31,Business travel,Business,442,3,4,4,4,3,3,3,3,4,5,4,3,4,3,94,79.0,neutral or dissatisfied +91612,115480,Female,disloyal Customer,25,Business travel,Eco,333,2,2,2,2,5,2,5,5,4,1,1,3,2,5,37,14.0,neutral or dissatisfied +91613,101918,Female,disloyal Customer,38,Business travel,Business,1984,2,2,2,2,3,2,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +91614,48444,Female,Loyal Customer,46,Business travel,Eco,916,4,5,5,5,1,5,4,4,4,4,4,2,4,1,0,0.0,satisfied +91615,114457,Female,Loyal Customer,51,Business travel,Business,1801,4,4,4,4,4,4,5,4,4,4,4,4,4,4,16,1.0,satisfied +91616,40377,Male,Loyal Customer,30,Business travel,Business,2579,5,5,5,5,4,4,4,4,1,4,3,3,1,4,0,0.0,satisfied +91617,43704,Male,Loyal Customer,39,Business travel,Eco,257,4,4,4,4,4,4,4,4,1,5,3,1,3,4,0,0.0,neutral or dissatisfied +91618,103501,Female,disloyal Customer,26,Business travel,Business,1047,5,5,5,3,1,5,1,1,3,4,4,4,5,1,0,0.0,satisfied +91619,89859,Female,Loyal Customer,29,Business travel,Business,1487,1,1,1,1,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +91620,105867,Female,Loyal Customer,48,Personal Travel,Eco Plus,925,2,4,2,4,5,4,5,4,4,2,5,4,4,3,2,0.0,neutral or dissatisfied +91621,76112,Male,Loyal Customer,47,Business travel,Business,1997,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,2.0,satisfied +91622,2105,Female,Loyal Customer,59,Personal Travel,Eco,812,3,2,3,2,5,1,2,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +91623,115705,Male,Loyal Customer,48,Business travel,Business,3685,3,2,2,2,2,2,3,3,3,3,3,3,3,1,76,66.0,neutral or dissatisfied +91624,28764,Female,Loyal Customer,13,Personal Travel,Eco,1024,2,5,2,5,5,2,5,5,5,3,3,1,4,5,0,0.0,neutral or dissatisfied +91625,16518,Male,Loyal Customer,34,Business travel,Eco Plus,246,3,5,5,5,3,4,3,3,1,4,3,2,1,3,0,0.0,satisfied +91626,76542,Male,Loyal Customer,29,Business travel,Business,3448,3,5,5,5,3,3,3,3,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +91627,47720,Male,disloyal Customer,33,Business travel,Business,329,3,3,3,4,3,3,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +91628,108138,Female,Loyal Customer,51,Business travel,Eco,997,3,4,2,4,1,3,3,3,3,3,3,4,3,1,3,20.0,neutral or dissatisfied +91629,104453,Male,Loyal Customer,44,Business travel,Business,1123,1,2,2,2,4,4,4,1,1,1,1,1,1,3,3,34.0,neutral or dissatisfied +91630,77669,Female,Loyal Customer,50,Business travel,Business,3543,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +91631,59582,Female,disloyal Customer,25,Business travel,Business,956,2,0,2,2,1,2,5,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +91632,73990,Male,Loyal Customer,47,Business travel,Business,1972,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +91633,8302,Female,Loyal Customer,44,Business travel,Business,3535,5,2,5,5,3,4,4,5,5,5,4,5,5,5,0,0.0,satisfied +91634,119845,Female,disloyal Customer,29,Business travel,Business,936,0,0,0,4,4,0,1,4,4,3,5,5,4,4,0,0.0,satisfied +91635,42747,Female,Loyal Customer,41,Business travel,Business,1536,5,5,5,5,3,1,5,4,4,4,4,2,4,5,4,17.0,satisfied +91636,44288,Female,disloyal Customer,27,Business travel,Eco,1123,4,4,4,3,5,4,5,5,4,4,5,2,2,5,8,7.0,satisfied +91637,57263,Male,Loyal Customer,53,Business travel,Business,628,3,4,4,4,2,3,3,3,3,3,3,3,3,1,1,1.0,neutral or dissatisfied +91638,77865,Male,Loyal Customer,58,Business travel,Business,1262,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +91639,43349,Male,Loyal Customer,37,Business travel,Business,1737,4,5,5,5,5,4,4,4,4,4,4,3,4,4,45,59.0,neutral or dissatisfied +91640,81329,Female,Loyal Customer,46,Business travel,Business,1299,5,5,4,5,4,5,4,5,5,5,5,5,5,4,6,88.0,satisfied +91641,24044,Female,Loyal Customer,47,Personal Travel,Eco,562,2,4,2,3,4,5,5,5,5,2,5,5,5,4,7,18.0,neutral or dissatisfied +91642,44177,Female,Loyal Customer,50,Business travel,Business,157,2,2,2,2,4,3,4,5,5,5,5,4,5,2,0,0.0,satisfied +91643,63778,Male,Loyal Customer,40,Business travel,Business,1721,5,5,5,5,3,4,4,5,5,5,5,5,5,5,28,14.0,satisfied +91644,49533,Male,disloyal Customer,32,Business travel,Business,363,2,2,2,2,1,2,1,1,5,4,5,1,5,1,63,57.0,neutral or dissatisfied +91645,46409,Male,Loyal Customer,38,Business travel,Business,458,2,2,2,2,1,5,2,4,4,4,4,4,4,5,14,6.0,satisfied +91646,678,Female,Loyal Customer,54,Business travel,Business,164,5,1,5,5,4,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +91647,42076,Male,Loyal Customer,56,Business travel,Eco Plus,116,5,3,3,3,5,5,5,5,3,5,4,4,2,5,1,4.0,satisfied +91648,113454,Male,disloyal Customer,21,Business travel,Eco,258,1,4,1,2,5,1,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +91649,13872,Male,Loyal Customer,32,Business travel,Business,2554,5,5,3,5,5,5,5,5,4,5,5,2,2,5,0,0.0,satisfied +91650,112461,Male,disloyal Customer,43,Business travel,Eco,567,3,4,3,4,5,3,5,5,3,1,1,3,2,5,24,62.0,neutral or dissatisfied +91651,115723,Male,disloyal Customer,17,Business travel,Eco,446,1,1,2,3,4,2,4,4,3,4,3,4,3,4,9,0.0,neutral or dissatisfied +91652,108233,Female,Loyal Customer,42,Business travel,Business,895,4,4,4,4,5,5,5,5,5,5,5,4,5,5,7,0.0,satisfied +91653,104028,Female,Loyal Customer,48,Business travel,Business,3209,2,2,2,2,2,4,5,5,5,5,5,3,5,5,53,51.0,satisfied +91654,22542,Male,Loyal Customer,53,Personal Travel,Eco Plus,208,2,3,0,3,3,0,3,3,2,3,5,2,4,3,0,0.0,neutral or dissatisfied +91655,111019,Male,Loyal Customer,52,Business travel,Eco,319,3,5,4,5,3,3,3,3,3,4,4,3,3,3,74,71.0,neutral or dissatisfied +91656,19892,Male,Loyal Customer,43,Business travel,Business,1999,3,3,3,3,5,1,2,5,5,4,5,1,5,1,33,26.0,satisfied +91657,125804,Male,Loyal Customer,51,Business travel,Business,1758,1,1,1,1,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +91658,73812,Male,Loyal Customer,33,Personal Travel,Eco Plus,204,2,1,2,1,2,2,2,2,2,1,1,2,1,2,0,0.0,neutral or dissatisfied +91659,92609,Female,Loyal Customer,34,Personal Travel,Eco,2218,3,1,3,3,5,3,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +91660,119029,Male,Loyal Customer,19,Personal Travel,Eco,1460,3,4,3,1,3,3,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +91661,13430,Male,Loyal Customer,35,Business travel,Eco,475,2,2,2,2,2,3,2,2,3,5,3,3,4,2,0,8.0,neutral or dissatisfied +91662,123165,Male,Loyal Customer,40,Business travel,Eco,231,4,4,4,4,4,4,4,4,3,1,2,2,1,4,0,4.0,satisfied +91663,116363,Female,Loyal Customer,55,Personal Travel,Eco,337,3,4,3,3,2,4,4,5,5,3,5,5,5,5,4,0.0,neutral or dissatisfied +91664,67664,Female,Loyal Customer,24,Business travel,Business,1438,3,2,2,2,3,3,3,3,2,2,4,4,3,3,23,4.0,neutral or dissatisfied +91665,99839,Female,Loyal Customer,56,Business travel,Business,2932,4,4,4,4,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +91666,3359,Female,Loyal Customer,38,Business travel,Business,1546,4,4,4,4,4,5,5,5,5,5,5,3,5,5,0,11.0,satisfied +91667,127612,Female,Loyal Customer,45,Business travel,Business,1773,2,2,2,2,4,3,4,3,3,3,3,4,3,4,1,0.0,satisfied +91668,110201,Male,Loyal Customer,34,Personal Travel,Eco Plus,1048,2,3,2,4,2,2,2,4,5,3,4,2,1,2,165,181.0,neutral or dissatisfied +91669,110180,Female,Loyal Customer,43,Personal Travel,Eco,1072,3,5,3,3,4,5,5,3,3,3,3,3,3,3,63,64.0,neutral or dissatisfied +91670,33956,Female,Loyal Customer,36,Business travel,Eco,1554,4,1,1,1,4,4,4,4,3,3,2,2,4,4,0,0.0,satisfied +91671,83173,Male,Loyal Customer,29,Personal Travel,Business,549,2,3,2,3,3,2,3,3,4,5,4,2,3,3,0,0.0,neutral or dissatisfied +91672,129009,Male,Loyal Customer,36,Business travel,Business,2704,2,2,2,2,2,2,2,5,5,5,5,2,4,2,7,0.0,satisfied +91673,47771,Male,disloyal Customer,28,Business travel,Eco,817,2,2,2,2,5,2,5,5,5,5,1,5,4,5,0,0.0,neutral or dissatisfied +91674,6820,Male,Loyal Customer,14,Personal Travel,Eco,235,3,5,0,2,3,0,3,3,4,3,4,3,5,3,3,0.0,neutral or dissatisfied +91675,87684,Male,disloyal Customer,80,Business travel,Eco,206,3,4,4,3,5,4,5,5,1,1,4,3,3,5,0,24.0,neutral or dissatisfied +91676,88555,Male,Loyal Customer,9,Personal Travel,Eco,270,3,0,3,2,4,3,4,4,4,2,5,5,4,4,13,6.0,neutral or dissatisfied +91677,84791,Female,Loyal Customer,26,Business travel,Business,3911,2,2,2,2,5,5,5,5,3,5,4,4,4,5,0,0.0,satisfied +91678,39695,Female,Loyal Customer,63,Business travel,Business,205,4,4,4,4,2,5,5,5,5,5,4,4,5,5,32,,satisfied +91679,40664,Female,disloyal Customer,26,Business travel,Business,588,3,2,3,3,3,3,3,3,3,2,3,3,4,3,125,114.0,neutral or dissatisfied +91680,100697,Female,Loyal Customer,17,Personal Travel,Eco,677,1,5,1,1,2,1,2,2,3,3,5,3,5,2,58,46.0,neutral or dissatisfied +91681,92740,Male,Loyal Customer,75,Business travel,Business,898,1,5,5,5,4,4,3,1,1,1,1,3,1,2,24,1.0,neutral or dissatisfied +91682,90898,Female,disloyal Customer,25,Business travel,Eco,404,2,2,2,2,4,2,5,4,4,1,3,4,2,4,18,10.0,neutral or dissatisfied +91683,39408,Female,Loyal Customer,36,Personal Travel,Eco,521,2,4,5,3,4,5,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +91684,71393,Male,Loyal Customer,35,Business travel,Eco Plus,258,5,1,1,1,5,5,5,5,1,2,1,5,3,5,53,77.0,satisfied +91685,100629,Female,Loyal Customer,43,Business travel,Business,3614,4,4,4,4,4,4,5,5,5,5,5,5,5,5,8,4.0,satisfied +91686,55952,Female,Loyal Customer,30,Business travel,Business,1620,1,1,1,1,5,4,5,5,5,2,3,3,5,5,22,6.0,satisfied +91687,61584,Male,Loyal Customer,30,Personal Travel,Business,1504,5,4,5,3,5,5,5,5,3,5,5,4,4,5,1,0.0,satisfied +91688,54492,Female,Loyal Customer,9,Business travel,Business,1608,4,4,4,4,5,5,5,5,1,1,1,2,5,5,0,0.0,satisfied +91689,9027,Female,disloyal Customer,23,Business travel,Eco,212,1,2,1,4,4,1,4,4,1,4,3,3,3,4,0,0.0,neutral or dissatisfied +91690,109734,Male,Loyal Customer,16,Personal Travel,Eco,587,5,3,5,4,3,5,3,3,2,5,3,2,3,3,0,0.0,satisfied +91691,70961,Female,Loyal Customer,42,Business travel,Business,3235,4,4,3,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +91692,29464,Female,disloyal Customer,25,Business travel,Eco,1008,3,3,3,4,2,3,2,2,2,5,5,2,1,2,0,0.0,neutral or dissatisfied +91693,111809,Male,Loyal Customer,9,Personal Travel,Eco,349,2,2,2,2,1,2,1,1,1,5,2,1,3,1,19,29.0,neutral or dissatisfied +91694,103723,Male,disloyal Customer,32,Personal Travel,Eco,251,3,4,3,4,5,3,5,5,5,4,5,3,5,5,1,11.0,neutral or dissatisfied +91695,113390,Male,Loyal Customer,39,Business travel,Business,386,5,5,5,5,2,5,4,3,3,3,3,5,3,5,7,0.0,satisfied +91696,39287,Male,Loyal Customer,58,Personal Travel,Eco,67,1,5,1,3,1,1,1,1,5,3,5,5,5,1,16,15.0,neutral or dissatisfied +91697,20944,Female,disloyal Customer,21,Business travel,Eco,689,4,5,5,4,4,5,5,4,1,5,1,4,1,4,0,0.0,satisfied +91698,114242,Female,Loyal Customer,59,Business travel,Business,3805,4,4,4,4,2,4,5,4,4,4,4,4,4,4,11,0.0,satisfied +91699,99621,Female,Loyal Customer,52,Business travel,Business,1224,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +91700,70514,Female,Loyal Customer,52,Personal Travel,Eco,867,2,5,1,3,4,5,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +91701,123196,Male,Loyal Customer,63,Personal Travel,Eco,547,2,0,2,4,3,2,2,3,4,2,5,4,5,3,3,14.0,neutral or dissatisfied +91702,54793,Male,Loyal Customer,39,Personal Travel,Business,862,0,4,0,3,4,3,4,5,5,0,5,1,5,2,6,0.0,satisfied +91703,81299,Male,Loyal Customer,18,Business travel,Eco Plus,1020,4,1,1,1,4,4,1,4,4,1,4,3,3,4,42,36.0,neutral or dissatisfied +91704,42019,Male,Loyal Customer,30,Business travel,Business,1931,5,5,5,5,5,5,5,5,3,3,5,3,3,5,0,0.0,satisfied +91705,52776,Female,disloyal Customer,28,Business travel,Eco,1314,5,5,5,2,3,5,3,3,2,1,3,1,2,3,0,0.0,satisfied +91706,23508,Male,Loyal Customer,36,Business travel,Business,349,0,0,0,3,3,1,5,5,5,5,5,1,5,3,0,0.0,satisfied +91707,85272,Female,Loyal Customer,33,Personal Travel,Eco,874,2,0,2,5,1,2,1,1,5,5,5,3,4,1,50,36.0,neutral or dissatisfied +91708,51124,Female,Loyal Customer,19,Personal Travel,Eco,109,1,4,1,3,5,1,5,5,4,3,4,4,5,5,14,7.0,neutral or dissatisfied +91709,125181,Male,Loyal Customer,55,Personal Travel,Business,651,2,4,2,4,2,2,3,4,4,2,4,1,4,2,5,0.0,neutral or dissatisfied +91710,91412,Female,Loyal Customer,52,Business travel,Business,2874,1,1,1,1,2,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +91711,115804,Female,Loyal Customer,36,Business travel,Business,325,5,5,5,5,1,1,5,4,4,4,4,4,4,2,0,0.0,satisfied +91712,61139,Male,Loyal Customer,55,Business travel,Business,2037,5,5,5,5,2,5,4,3,3,3,3,3,3,5,11,2.0,satisfied +91713,13404,Female,Loyal Customer,43,Business travel,Business,2605,2,4,4,4,1,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +91714,107418,Male,Loyal Customer,59,Business travel,Eco,725,4,2,1,2,4,4,4,4,5,2,3,5,5,4,0,0.0,satisfied +91715,88643,Male,Loyal Customer,59,Personal Travel,Eco,270,5,4,5,4,5,5,4,5,5,3,4,3,5,5,0,0.0,satisfied +91716,6981,Female,Loyal Customer,44,Business travel,Business,3458,5,5,5,5,2,5,4,4,4,4,4,5,4,5,29,41.0,satisfied +91717,35234,Female,disloyal Customer,25,Business travel,Eco,1076,4,4,4,3,3,4,3,3,2,2,2,2,3,3,2,0.0,neutral or dissatisfied +91718,108790,Female,disloyal Customer,24,Business travel,Eco,404,0,0,0,2,5,0,5,5,2,1,4,2,5,5,4,4.0,satisfied +91719,71113,Female,Loyal Customer,52,Business travel,Eco,2072,4,5,5,5,4,2,2,4,4,4,4,2,4,2,1,0.0,satisfied +91720,104266,Female,Loyal Customer,37,Business travel,Business,456,1,0,0,3,2,4,4,5,5,0,5,4,5,3,0,6.0,neutral or dissatisfied +91721,114793,Female,disloyal Customer,38,Business travel,Business,390,1,1,1,4,2,1,3,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +91722,127640,Female,Loyal Customer,60,Personal Travel,Eco,1773,3,2,3,2,4,2,1,2,2,3,2,1,2,3,3,14.0,neutral or dissatisfied +91723,22313,Male,Loyal Customer,59,Business travel,Business,2830,2,2,2,2,3,3,2,5,5,5,3,3,5,3,0,0.0,satisfied +91724,87087,Male,Loyal Customer,53,Business travel,Eco,640,4,4,4,4,4,4,4,4,2,5,4,1,3,4,26,22.0,neutral or dissatisfied +91725,104894,Female,disloyal Customer,21,Business travel,Business,1565,5,4,5,5,4,5,4,4,3,5,4,4,5,4,15,20.0,satisfied +91726,56826,Female,Loyal Customer,20,Personal Travel,Eco,1725,2,5,3,4,3,3,3,3,4,5,5,3,5,3,109,105.0,neutral or dissatisfied +91727,40485,Female,Loyal Customer,10,Personal Travel,Eco,175,2,2,2,3,4,2,2,4,1,5,2,3,3,4,0,0.0,neutral or dissatisfied +91728,57932,Male,Loyal Customer,25,Business travel,Business,1167,4,4,4,4,4,4,4,4,5,2,4,5,4,4,0,0.0,satisfied +91729,61825,Male,Loyal Customer,21,Personal Travel,Eco,1379,3,4,4,2,3,4,4,3,5,4,4,3,4,3,16,23.0,neutral or dissatisfied +91730,28275,Female,disloyal Customer,48,Business travel,Eco,2402,3,3,3,3,3,2,2,3,2,3,3,2,1,2,0,0.0,neutral or dissatisfied +91731,92589,Male,Loyal Customer,26,Business travel,Business,2342,1,1,1,1,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +91732,74855,Male,disloyal Customer,50,Business travel,Business,1995,4,4,4,5,3,4,3,3,4,5,4,4,4,3,0,0.0,satisfied +91733,48353,Female,Loyal Customer,57,Business travel,Business,2714,4,4,4,4,1,2,5,2,2,2,2,4,2,1,0,0.0,satisfied +91734,12103,Male,disloyal Customer,22,Business travel,Eco,1034,3,3,3,4,1,3,1,1,5,5,5,5,5,1,12,6.0,satisfied +91735,8191,Female,disloyal Customer,23,Business travel,Eco,125,5,3,5,3,2,5,2,2,2,5,2,4,1,2,0,0.0,satisfied +91736,65497,Female,Loyal Customer,22,Personal Travel,Eco,1303,2,4,2,2,1,2,1,1,5,2,4,3,5,1,2,17.0,neutral or dissatisfied +91737,55181,Female,Loyal Customer,46,Business travel,Business,1379,4,4,4,4,3,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +91738,79826,Female,Loyal Customer,56,Business travel,Business,2273,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,10.0,satisfied +91739,64458,Male,Loyal Customer,38,Personal Travel,Eco,989,4,4,4,2,3,4,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +91740,103161,Male,Loyal Customer,40,Business travel,Business,2715,0,0,0,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +91741,112802,Male,Loyal Customer,51,Business travel,Business,1129,2,3,3,3,4,4,3,2,2,2,2,1,2,1,10,12.0,neutral or dissatisfied +91742,18293,Female,Loyal Customer,65,Business travel,Eco,240,3,2,2,2,1,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +91743,37279,Male,Loyal Customer,33,Business travel,Business,3389,5,5,5,5,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +91744,77209,Female,Loyal Customer,61,Personal Travel,Eco,2994,3,3,3,4,3,2,2,2,5,3,4,2,1,2,0,3.0,neutral or dissatisfied +91745,862,Male,Loyal Customer,55,Business travel,Business,2480,0,5,0,2,2,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +91746,39234,Male,Loyal Customer,48,Business travel,Eco,268,4,5,5,5,4,4,4,4,5,1,2,1,5,4,0,0.0,satisfied +91747,91353,Female,Loyal Customer,52,Personal Travel,Eco Plus,250,3,4,0,5,2,5,5,4,4,0,4,3,4,3,34,61.0,neutral or dissatisfied +91748,19084,Male,Loyal Customer,41,Business travel,Eco,296,5,1,1,1,5,5,5,5,5,4,3,2,5,5,0,0.0,satisfied +91749,40110,Female,Loyal Customer,33,Business travel,Eco,200,4,2,2,2,4,4,4,4,4,5,3,4,3,4,0,0.0,satisfied +91750,127070,Female,disloyal Customer,29,Business travel,Business,651,5,5,5,1,2,5,2,2,4,3,5,4,4,2,0,0.0,satisfied +91751,7204,Female,Loyal Customer,43,Business travel,Business,1759,5,5,5,5,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +91752,77380,Female,Loyal Customer,44,Business travel,Business,2969,2,3,2,2,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +91753,96741,Male,Loyal Customer,51,Business travel,Eco Plus,696,3,2,3,2,3,3,3,3,2,5,2,1,3,3,14,10.0,neutral or dissatisfied +91754,125327,Male,disloyal Customer,33,Business travel,Business,599,1,1,1,3,4,1,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +91755,39301,Male,Loyal Customer,69,Personal Travel,Eco,67,2,2,2,3,4,2,4,4,1,4,4,1,4,4,63,60.0,neutral or dissatisfied +91756,66369,Female,Loyal Customer,22,Personal Travel,Eco,986,1,5,1,4,3,1,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +91757,83242,Male,Loyal Customer,47,Business travel,Business,1979,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +91758,101535,Male,Loyal Customer,52,Personal Travel,Eco,345,2,2,2,3,1,2,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +91759,88702,Male,Loyal Customer,46,Personal Travel,Eco,240,3,4,3,4,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +91760,120442,Female,Loyal Customer,55,Business travel,Business,3040,3,3,3,3,1,4,3,3,3,3,3,1,3,1,4,16.0,neutral or dissatisfied +91761,126027,Male,Loyal Customer,55,Business travel,Business,3052,4,4,4,4,4,4,4,5,5,5,5,5,5,4,23,40.0,satisfied +91762,3251,Male,Loyal Customer,46,Business travel,Business,3540,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +91763,120599,Female,Loyal Customer,43,Personal Travel,Eco,980,3,4,3,4,3,5,4,4,4,3,4,5,4,5,42,49.0,neutral or dissatisfied +91764,88316,Male,disloyal Customer,38,Business travel,Eco,406,3,2,3,3,3,3,3,3,4,2,3,1,4,3,4,0.0,neutral or dissatisfied +91765,111379,Male,disloyal Customer,25,Business travel,Business,1173,5,0,5,3,4,5,4,4,4,4,5,5,4,4,7,4.0,satisfied +91766,114146,Female,Loyal Customer,43,Business travel,Business,3179,2,2,4,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +91767,96979,Female,Loyal Customer,32,Business travel,Business,2304,4,4,4,4,4,3,4,4,5,4,5,5,5,4,0,24.0,satisfied +91768,27924,Male,Loyal Customer,13,Personal Travel,Eco,689,4,4,4,1,1,4,3,1,5,2,5,3,5,1,46,33.0,neutral or dissatisfied +91769,85633,Female,Loyal Customer,44,Personal Travel,Eco,259,3,3,3,4,1,5,1,4,4,3,4,4,4,2,23,10.0,neutral or dissatisfied +91770,109178,Male,Loyal Customer,31,Business travel,Business,391,2,2,2,2,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +91771,84827,Female,Loyal Customer,52,Business travel,Business,481,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +91772,113714,Male,Loyal Customer,59,Personal Travel,Eco,236,3,2,3,3,4,3,2,4,3,1,4,1,4,4,0,0.0,neutral or dissatisfied +91773,21997,Male,Loyal Customer,25,Personal Travel,Eco,503,2,4,2,3,1,2,1,1,5,4,4,4,5,1,117,96.0,neutral or dissatisfied +91774,28516,Male,Loyal Customer,53,Business travel,Business,2701,5,5,5,5,3,4,1,2,2,2,2,4,2,2,0,0.0,satisfied +91775,33933,Female,disloyal Customer,49,Business travel,Eco,1072,3,3,3,3,4,3,4,4,2,3,4,1,4,4,55,73.0,neutral or dissatisfied +91776,13649,Male,Loyal Customer,32,Business travel,Eco,196,4,4,4,4,4,4,4,4,5,3,4,1,4,4,0,0.0,satisfied +91777,36429,Female,Loyal Customer,39,Business travel,Business,1567,1,1,2,1,4,2,4,4,4,4,4,2,4,2,0,0.0,satisfied +91778,17044,Male,Loyal Customer,22,Business travel,Business,1134,2,2,2,2,5,5,5,5,3,1,2,1,3,5,47,39.0,satisfied +91779,61971,Female,Loyal Customer,29,Personal Travel,Eco,2400,2,4,2,3,2,2,3,2,5,2,3,3,5,2,1,0.0,neutral or dissatisfied +91780,80292,Male,disloyal Customer,34,Business travel,Business,746,2,2,2,3,2,4,4,5,2,5,5,4,5,4,297,290.0,neutral or dissatisfied +91781,34312,Male,Loyal Customer,13,Personal Travel,Eco,496,1,4,1,3,5,1,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +91782,28713,Female,Loyal Customer,61,Business travel,Eco,2554,3,4,4,4,3,3,3,4,4,1,2,3,4,3,0,0.0,neutral or dissatisfied +91783,125847,Female,disloyal Customer,23,Business travel,Eco,951,5,5,5,2,3,5,3,3,4,4,5,4,4,3,7,18.0,satisfied +91784,57281,Female,Loyal Customer,25,Personal Travel,Eco,628,3,4,3,4,3,3,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +91785,65966,Female,Loyal Customer,30,Business travel,Business,1372,3,2,2,2,3,3,3,3,3,4,3,3,3,3,26,28.0,neutral or dissatisfied +91786,55922,Male,Loyal Customer,48,Personal Travel,Eco,733,4,4,4,1,2,4,5,2,1,4,4,3,2,2,0,0.0,neutral or dissatisfied +91787,48454,Female,Loyal Customer,52,Business travel,Eco,848,4,2,2,2,4,2,5,4,4,4,4,5,4,5,0,0.0,satisfied +91788,70550,Male,Loyal Customer,47,Business travel,Business,3641,1,1,1,1,3,4,4,1,1,1,1,1,1,3,0,11.0,neutral or dissatisfied +91789,126252,Male,Loyal Customer,46,Business travel,Eco,250,3,4,4,4,3,3,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +91790,16154,Female,disloyal Customer,39,Business travel,Business,284,2,3,3,1,3,3,3,3,2,2,2,5,4,3,0,0.0,neutral or dissatisfied +91791,73380,Male,Loyal Customer,29,Business travel,Business,2443,1,5,5,5,1,1,1,1,4,5,3,4,3,1,52,70.0,neutral or dissatisfied +91792,89304,Male,Loyal Customer,67,Personal Travel,Eco,453,4,1,1,4,4,1,3,4,3,1,3,2,4,4,0,0.0,neutral or dissatisfied +91793,28773,Female,Loyal Customer,59,Business travel,Business,3155,1,1,1,1,3,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +91794,4578,Female,Loyal Customer,48,Business travel,Business,3778,4,4,4,4,5,5,5,3,5,5,4,5,4,5,45,139.0,satisfied +91795,91708,Female,disloyal Customer,9,Business travel,Business,588,4,0,5,2,5,5,5,5,3,3,5,5,5,5,0,0.0,satisfied +91796,42012,Female,Loyal Customer,38,Business travel,Eco,116,3,3,3,3,3,4,3,3,4,3,2,5,5,3,11,17.0,satisfied +91797,85054,Male,disloyal Customer,28,Business travel,Business,731,2,1,1,2,4,1,4,4,4,2,2,2,2,4,13,10.0,neutral or dissatisfied +91798,60890,Male,Loyal Customer,56,Personal Travel,Eco,1062,2,4,2,3,4,2,4,4,4,4,4,4,4,4,1,0.0,neutral or dissatisfied +91799,126653,Male,Loyal Customer,59,Personal Travel,Eco,602,2,2,2,3,4,2,4,4,2,3,4,1,4,4,0,0.0,neutral or dissatisfied +91800,20549,Female,Loyal Customer,23,Business travel,Business,2117,4,4,4,4,4,4,4,4,3,1,5,5,2,4,23,17.0,satisfied +91801,613,Male,Loyal Customer,55,Business travel,Business,3534,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +91802,102230,Male,disloyal Customer,36,Business travel,Eco,397,2,2,2,3,2,2,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +91803,9273,Female,disloyal Customer,21,Business travel,Business,1201,5,4,5,1,2,5,1,2,4,5,5,3,4,2,22,25.0,satisfied +91804,121286,Female,Loyal Customer,56,Business travel,Business,2282,5,5,5,5,4,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +91805,122228,Female,Loyal Customer,55,Business travel,Business,3810,4,4,3,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +91806,50100,Male,Loyal Customer,33,Business travel,Eco,209,5,2,2,2,5,5,5,5,3,3,1,4,1,5,0,0.0,satisfied +91807,13226,Female,Loyal Customer,48,Business travel,Eco,468,2,3,3,3,4,5,3,2,2,2,2,3,2,3,0,0.0,satisfied +91808,120871,Female,Loyal Customer,49,Business travel,Business,2035,1,1,1,1,2,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +91809,82284,Male,Loyal Customer,58,Personal Travel,Eco,1481,4,4,4,1,1,4,1,1,1,5,2,4,2,1,1,19.0,neutral or dissatisfied +91810,39504,Male,Loyal Customer,23,Business travel,Business,852,5,5,4,5,5,5,5,5,5,4,2,3,2,5,0,0.0,satisfied +91811,46018,Male,Loyal Customer,41,Business travel,Eco,996,3,3,3,3,3,3,3,3,1,3,1,3,2,3,0,5.0,satisfied +91812,99054,Female,Loyal Customer,54,Business travel,Business,181,3,3,3,3,5,4,5,5,5,5,5,3,5,4,8,6.0,satisfied +91813,53968,Male,Loyal Customer,16,Personal Travel,Eco,1117,3,4,3,2,4,3,4,4,4,3,5,4,5,4,6,0.0,neutral or dissatisfied +91814,55961,Male,Loyal Customer,53,Business travel,Business,1620,4,4,4,4,5,4,5,4,4,4,4,4,4,5,0,5.0,satisfied +91815,87283,Female,Loyal Customer,59,Business travel,Business,2932,4,4,4,4,4,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +91816,55498,Male,Loyal Customer,25,Personal Travel,Eco,1739,1,5,1,4,5,1,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +91817,21363,Female,disloyal Customer,21,Business travel,Eco,674,3,2,2,1,1,2,1,1,5,1,3,2,4,1,17,13.0,neutral or dissatisfied +91818,55030,Male,disloyal Customer,46,Business travel,Eco,1303,2,2,2,3,2,2,2,2,2,4,3,1,3,2,0,3.0,neutral or dissatisfied +91819,32481,Male,Loyal Customer,42,Business travel,Eco,163,3,4,4,4,3,3,3,3,1,4,2,1,2,3,0,0.0,neutral or dissatisfied +91820,47709,Male,Loyal Customer,31,Business travel,Eco Plus,1211,2,2,2,2,2,2,2,2,4,5,3,2,3,2,0,10.0,neutral or dissatisfied +91821,54182,Male,Loyal Customer,35,Business travel,Business,1400,3,3,3,3,4,4,4,3,3,3,3,4,3,3,0,16.0,neutral or dissatisfied +91822,119625,Female,Loyal Customer,26,Business travel,Business,1927,3,3,3,3,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +91823,1023,Male,Loyal Customer,40,Business travel,Eco,164,2,5,5,5,2,2,2,2,2,1,3,1,4,2,98,111.0,neutral or dissatisfied +91824,37394,Male,disloyal Customer,27,Business travel,Eco,944,3,3,3,3,3,3,3,3,4,4,5,5,3,3,0,0.0,neutral or dissatisfied +91825,87853,Female,Loyal Customer,57,Personal Travel,Eco,214,3,0,0,4,2,3,3,5,5,0,5,5,5,2,31,43.0,neutral or dissatisfied +91826,35363,Male,Loyal Customer,23,Business travel,Business,944,1,4,4,4,1,1,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +91827,98174,Female,Loyal Customer,41,Business travel,Business,327,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +91828,56142,Female,disloyal Customer,22,Business travel,Eco,1400,2,2,2,3,1,2,4,1,5,2,5,3,4,1,0,14.0,neutral or dissatisfied +91829,80185,Male,Loyal Customer,27,Personal Travel,Eco,2586,1,3,1,3,1,5,1,3,1,4,4,1,4,1,3,28.0,neutral or dissatisfied +91830,109233,Male,Loyal Customer,39,Personal Travel,Eco,793,3,4,3,3,2,3,2,2,4,5,4,5,5,2,17,6.0,neutral or dissatisfied +91831,103706,Male,Loyal Customer,10,Personal Travel,Eco,251,3,5,3,1,4,3,4,4,1,2,1,1,3,4,8,4.0,neutral or dissatisfied +91832,129362,Male,disloyal Customer,36,Business travel,Business,2565,3,2,2,2,2,2,2,2,5,3,5,4,4,2,4,0.0,neutral or dissatisfied +91833,97821,Female,Loyal Customer,65,Business travel,Eco,395,2,4,4,4,2,4,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +91834,105669,Female,disloyal Customer,37,Business travel,Business,663,2,1,1,5,4,1,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +91835,11356,Female,Loyal Customer,59,Personal Travel,Eco,191,1,5,1,3,5,4,5,3,3,1,3,3,3,5,9,7.0,neutral or dissatisfied +91836,24465,Male,Loyal Customer,28,Business travel,Eco,516,4,5,5,5,4,4,4,4,4,2,3,3,3,4,29,44.0,satisfied +91837,3919,Female,Loyal Customer,9,Personal Travel,Eco,213,3,4,3,4,5,3,5,5,3,2,3,2,4,5,0,0.0,neutral or dissatisfied +91838,84531,Male,Loyal Customer,41,Business travel,Business,2615,3,3,2,3,5,3,2,3,3,3,3,1,3,2,30,0.0,neutral or dissatisfied +91839,21989,Female,Loyal Customer,36,Personal Travel,Eco,448,2,4,2,2,2,2,2,2,3,2,4,5,4,2,34,23.0,neutral or dissatisfied +91840,105637,Female,disloyal Customer,22,Business travel,Eco,842,2,2,2,2,2,2,2,2,1,4,3,4,3,2,13,23.0,neutral or dissatisfied +91841,28485,Female,Loyal Customer,51,Business travel,Eco,1739,3,1,2,2,5,2,2,2,2,3,2,4,2,4,27,16.0,neutral or dissatisfied +91842,51520,Female,Loyal Customer,33,Business travel,Business,509,1,1,1,1,3,2,5,5,5,5,5,3,5,2,0,0.0,satisfied +91843,122906,Female,Loyal Customer,59,Business travel,Business,547,3,2,2,2,4,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +91844,27082,Male,disloyal Customer,34,Business travel,Eco,2496,2,2,2,5,5,2,5,5,4,1,3,1,1,5,0,0.0,neutral or dissatisfied +91845,25184,Male,Loyal Customer,54,Business travel,Business,3346,2,3,3,3,4,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +91846,108311,Female,Loyal Customer,46,Business travel,Business,1728,4,4,4,4,3,3,5,5,5,5,5,3,5,3,65,74.0,satisfied +91847,15915,Male,Loyal Customer,57,Business travel,Eco,528,5,3,3,3,4,5,4,4,2,2,3,4,3,4,53,52.0,satisfied +91848,98783,Female,Loyal Customer,38,Business travel,Eco,630,2,4,4,4,2,2,2,2,3,2,3,2,3,2,11,0.0,neutral or dissatisfied +91849,1400,Male,disloyal Customer,33,Personal Travel,Eco Plus,89,4,3,4,3,1,4,1,1,2,3,3,1,4,1,5,8.0,neutral or dissatisfied +91850,63497,Female,Loyal Customer,42,Business travel,Business,1956,4,1,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +91851,120817,Female,Loyal Customer,48,Personal Travel,Eco,666,2,3,2,3,1,3,4,2,2,2,2,2,2,4,0,10.0,neutral or dissatisfied +91852,50113,Male,Loyal Customer,49,Business travel,Business,2790,5,4,4,4,2,4,4,5,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +91853,64716,Female,Loyal Customer,58,Business travel,Business,3342,5,5,5,5,3,4,5,5,5,5,5,4,5,5,13,1.0,satisfied +91854,92397,Male,Loyal Customer,34,Business travel,Business,1947,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,6.0,satisfied +91855,50020,Female,Loyal Customer,44,Business travel,Business,156,5,5,5,5,3,3,4,5,5,5,4,3,5,5,0,0.0,satisfied +91856,98697,Female,Loyal Customer,70,Personal Travel,Eco,861,2,5,2,1,3,4,4,2,2,2,4,3,2,5,0,0.0,neutral or dissatisfied +91857,125731,Female,Loyal Customer,54,Business travel,Business,2659,1,4,1,1,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +91858,91151,Male,Loyal Customer,29,Personal Travel,Eco,594,1,1,1,1,4,1,3,4,3,2,2,2,1,4,0,0.0,neutral or dissatisfied +91859,123122,Female,Loyal Customer,31,Business travel,Business,600,1,2,2,2,1,1,1,1,2,4,2,2,3,1,2,8.0,neutral or dissatisfied +91860,50869,Male,Loyal Customer,48,Personal Travel,Eco,363,2,5,5,3,1,5,1,1,5,2,4,5,4,1,8,0.0,neutral or dissatisfied +91861,127515,Female,disloyal Customer,55,Business travel,Eco Plus,2075,2,2,2,3,3,2,3,3,2,4,2,3,3,3,0,0.0,neutral or dissatisfied +91862,55701,Female,Loyal Customer,31,Business travel,Business,1798,4,4,4,4,4,4,4,4,1,3,4,1,4,4,7,10.0,neutral or dissatisfied +91863,55805,Female,Loyal Customer,49,Personal Travel,Business,1416,2,4,2,3,1,2,4,1,1,2,1,2,1,3,9,0.0,neutral or dissatisfied +91864,27028,Male,Loyal Customer,32,Business travel,Eco Plus,867,0,0,0,3,2,0,1,2,5,1,5,1,3,2,0,0.0,satisfied +91865,44473,Male,disloyal Customer,38,Business travel,Eco Plus,196,4,4,4,2,2,4,2,2,1,1,2,3,1,2,0,0.0,neutral or dissatisfied +91866,16216,Female,Loyal Customer,39,Business travel,Eco Plus,277,3,2,2,2,3,3,3,3,2,5,4,3,2,3,0,0.0,satisfied +91867,54895,Male,Loyal Customer,66,Personal Travel,Eco,862,0,4,0,3,2,0,2,2,4,5,5,4,5,2,3,0.0,satisfied +91868,17595,Female,Loyal Customer,33,Business travel,Eco,695,2,2,4,2,2,3,2,2,2,3,4,1,3,2,2,0.0,neutral or dissatisfied +91869,78183,Female,Loyal Customer,46,Business travel,Eco,259,1,4,4,4,3,4,4,1,1,1,1,2,1,1,21,18.0,neutral or dissatisfied +91870,43232,Male,disloyal Customer,38,Business travel,Eco,637,3,3,3,1,3,3,3,3,1,3,5,5,3,3,0,6.0,neutral or dissatisfied +91871,127421,Female,Loyal Customer,70,Personal Travel,Eco,868,4,5,4,4,1,3,1,3,3,4,3,4,3,2,0,0.0,satisfied +91872,112799,Female,disloyal Customer,20,Business travel,Eco,1357,1,1,1,3,4,1,4,4,4,3,5,4,4,4,57,33.0,neutral or dissatisfied +91873,71281,Male,Loyal Customer,58,Personal Travel,Eco,733,2,2,2,4,2,2,2,2,3,4,3,2,3,2,0,0.0,neutral or dissatisfied +91874,46824,Female,disloyal Customer,30,Business travel,Eco,776,3,3,3,3,1,3,1,1,3,1,3,3,4,1,7,9.0,neutral or dissatisfied +91875,35637,Female,Loyal Customer,64,Business travel,Eco,1626,2,4,4,4,5,2,3,2,2,2,2,4,2,1,54,57.0,neutral or dissatisfied +91876,39646,Male,Loyal Customer,36,Personal Travel,Eco,1190,2,4,2,2,1,2,1,1,5,3,5,4,5,1,5,11.0,neutral or dissatisfied +91877,109454,Female,Loyal Customer,52,Business travel,Business,2316,4,4,5,4,3,5,5,4,4,4,4,5,4,3,59,57.0,satisfied +91878,18077,Female,Loyal Customer,58,Personal Travel,Eco,488,2,2,2,4,5,4,4,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +91879,127024,Female,Loyal Customer,47,Business travel,Eco,647,3,3,3,3,2,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +91880,103328,Male,Loyal Customer,38,Personal Travel,Eco,1139,1,4,1,4,1,1,1,1,5,3,5,3,4,1,14,10.0,neutral or dissatisfied +91881,80669,Female,disloyal Customer,36,Business travel,Eco,421,2,0,2,4,2,2,2,2,3,4,4,3,2,2,0,0.0,neutral or dissatisfied +91882,118325,Female,Loyal Customer,48,Business travel,Eco,639,2,5,5,5,2,2,2,2,2,2,2,4,2,2,6,0.0,neutral or dissatisfied +91883,6890,Female,Loyal Customer,59,Business travel,Business,3004,1,1,1,1,4,4,5,5,5,5,5,5,5,4,58,61.0,satisfied +91884,111194,Female,Loyal Customer,48,Business travel,Business,1506,2,2,2,2,4,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +91885,48831,Male,Loyal Customer,7,Personal Travel,Business,86,3,4,3,2,1,3,1,1,4,2,5,4,5,1,4,0.0,neutral or dissatisfied +91886,43815,Male,disloyal Customer,32,Business travel,Business,174,1,1,1,3,4,1,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +91887,113513,Female,Loyal Customer,37,Business travel,Business,226,5,5,5,5,5,5,5,4,4,4,4,3,4,5,3,0.0,satisfied +91888,111008,Male,disloyal Customer,23,Business travel,Business,240,4,4,3,2,1,3,1,1,5,5,4,4,4,1,6,5.0,satisfied +91889,125155,Male,Loyal Customer,20,Business travel,Business,1933,3,3,3,3,4,4,4,4,5,4,4,5,4,4,0,0.0,satisfied +91890,53729,Male,Loyal Customer,46,Personal Travel,Eco,1208,1,1,0,3,3,0,3,3,3,4,4,1,3,3,0,0.0,neutral or dissatisfied +91891,51669,Female,disloyal Customer,26,Business travel,Eco,370,3,5,3,5,3,3,3,3,3,2,1,2,1,3,0,0.0,neutral or dissatisfied +91892,106228,Female,Loyal Customer,53,Personal Travel,Eco,471,2,1,3,2,4,3,2,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +91893,86202,Male,Loyal Customer,60,Business travel,Business,2489,4,2,4,4,5,4,3,4,4,4,4,3,4,4,0,8.0,neutral or dissatisfied +91894,67294,Male,Loyal Customer,48,Business travel,Business,3373,3,3,3,3,2,5,5,5,5,5,5,4,5,5,75,63.0,satisfied +91895,118774,Male,Loyal Customer,53,Personal Travel,Eco,304,4,4,4,5,3,4,3,3,3,3,4,4,4,3,8,1.0,neutral or dissatisfied +91896,76067,Female,Loyal Customer,35,Business travel,Business,669,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +91897,22388,Female,Loyal Customer,35,Business travel,Business,3230,1,3,3,3,1,4,3,2,2,3,1,3,2,3,74,123.0,neutral or dissatisfied +91898,69298,Male,Loyal Customer,15,Personal Travel,Eco Plus,733,2,2,3,4,2,3,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +91899,81259,Female,Loyal Customer,22,Business travel,Business,2210,4,4,4,4,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +91900,72845,Male,Loyal Customer,42,Business travel,Business,1713,5,5,5,5,2,5,5,3,3,3,3,4,3,4,22,,satisfied +91901,67083,Male,disloyal Customer,11,Business travel,Eco,1017,4,4,4,3,1,4,1,1,2,4,3,2,4,1,53,97.0,neutral or dissatisfied +91902,32255,Male,disloyal Customer,23,Business travel,Eco,163,1,4,1,5,5,1,1,5,3,3,5,1,5,5,0,0.0,neutral or dissatisfied +91903,7034,Female,disloyal Customer,36,Business travel,Eco Plus,299,4,4,4,3,4,4,2,4,2,4,4,4,3,4,0,22.0,neutral or dissatisfied +91904,61724,Female,Loyal Customer,31,Business travel,Eco,1346,3,4,4,4,3,3,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +91905,111665,Female,disloyal Customer,54,Business travel,Business,991,3,2,2,4,4,3,3,4,3,4,4,3,5,4,8,3.0,satisfied +91906,87547,Female,Loyal Customer,48,Business travel,Business,2713,5,4,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +91907,84965,Male,Loyal Customer,44,Personal Travel,Eco Plus,534,1,4,1,2,2,1,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +91908,31406,Female,Loyal Customer,56,Personal Travel,Business,1546,3,5,3,4,2,5,5,3,3,3,3,3,3,4,11,12.0,neutral or dissatisfied +91909,13105,Male,Loyal Customer,35,Business travel,Business,427,1,1,1,1,3,1,1,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +91910,36924,Female,Loyal Customer,55,Business travel,Business,1968,4,4,4,4,2,5,4,5,5,5,5,4,5,4,0,6.0,satisfied +91911,108882,Female,disloyal Customer,25,Business travel,Business,1066,2,4,2,3,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +91912,68883,Male,Loyal Customer,40,Business travel,Eco,1061,2,1,1,1,2,2,2,2,2,5,4,1,4,2,0,0.0,neutral or dissatisfied +91913,92029,Female,Loyal Customer,48,Business travel,Business,1535,4,4,4,4,5,4,5,5,5,5,5,5,5,3,5,0.0,satisfied +91914,116309,Male,Loyal Customer,43,Personal Travel,Eco,296,3,4,2,3,5,2,5,5,4,4,5,5,4,5,4,0.0,neutral or dissatisfied +91915,107091,Female,Loyal Customer,46,Business travel,Business,745,3,3,2,3,5,4,5,5,5,5,5,3,5,5,4,2.0,satisfied +91916,106661,Female,disloyal Customer,35,Business travel,Eco,1590,3,3,3,2,4,3,4,4,3,2,1,3,2,4,0,10.0,neutral or dissatisfied +91917,102561,Male,Loyal Customer,53,Business travel,Business,414,2,2,2,2,2,4,5,3,3,4,3,3,3,3,4,4.0,satisfied +91918,54305,Male,Loyal Customer,52,Business travel,Eco,1597,5,1,5,1,5,5,5,5,5,3,4,3,5,5,0,0.0,satisfied +91919,126628,Male,Loyal Customer,48,Business travel,Business,3201,3,3,3,3,3,5,4,5,5,5,5,5,5,3,30,26.0,satisfied +91920,1975,Female,Loyal Customer,41,Personal Travel,Eco,383,3,4,3,3,1,3,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +91921,42748,Male,disloyal Customer,25,Business travel,Eco,419,1,1,1,3,3,1,3,3,2,3,3,2,3,3,12,16.0,neutral or dissatisfied +91922,94513,Female,Loyal Customer,69,Business travel,Business,2093,2,1,4,4,4,3,4,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +91923,49918,Male,Loyal Customer,56,Business travel,Business,3778,0,0,0,1,5,3,4,5,5,5,5,1,5,1,0,0.0,satisfied +91924,31666,Male,Loyal Customer,58,Business travel,Eco,846,1,1,1,1,1,1,1,1,1,2,4,3,3,1,0,1.0,neutral or dissatisfied +91925,104765,Female,Loyal Customer,29,Personal Travel,Eco,1246,2,5,3,4,3,3,3,3,5,5,3,3,4,3,0,3.0,neutral or dissatisfied +91926,45689,Male,Loyal Customer,37,Business travel,Business,3267,4,4,4,4,4,3,3,2,2,2,2,5,2,4,0,0.0,satisfied +91927,106205,Male,Loyal Customer,38,Personal Travel,Eco Plus,302,2,2,2,3,4,2,4,4,4,3,4,2,3,4,0,0.0,neutral or dissatisfied +91928,109381,Female,Loyal Customer,32,Business travel,Business,1189,1,0,0,3,0,3,3,4,1,3,3,3,4,3,309,302.0,neutral or dissatisfied +91929,46048,Female,Loyal Customer,56,Personal Travel,Eco,996,5,5,5,3,5,5,5,4,4,5,4,5,4,4,0,3.0,satisfied +91930,117413,Female,Loyal Customer,51,Business travel,Eco Plus,1136,3,5,5,5,3,3,4,3,3,3,3,3,3,4,0,12.0,neutral or dissatisfied +91931,70006,Male,Loyal Customer,34,Personal Travel,Eco,236,4,4,4,1,1,4,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +91932,5030,Female,Loyal Customer,44,Business travel,Business,3932,0,4,0,5,2,5,5,4,4,4,4,5,4,5,0,16.0,satisfied +91933,76590,Male,Loyal Customer,30,Business travel,Business,481,4,4,4,4,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +91934,111681,Female,Loyal Customer,23,Business travel,Eco Plus,991,1,3,3,3,1,1,1,1,1,3,3,4,3,1,8,9.0,neutral or dissatisfied +91935,63815,Female,Loyal Customer,56,Business travel,Business,1918,5,4,5,5,5,4,5,5,5,5,5,3,5,5,10,0.0,satisfied +91936,18156,Female,Loyal Customer,51,Business travel,Eco,430,5,4,4,4,5,1,1,5,5,5,5,1,5,3,5,8.0,satisfied +91937,23271,Female,Loyal Customer,45,Business travel,Business,3355,3,2,2,2,1,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +91938,84273,Female,disloyal Customer,21,Business travel,Business,334,4,0,3,3,5,3,5,5,4,3,4,3,4,5,0,0.0,satisfied +91939,72104,Female,Loyal Customer,24,Business travel,Business,2486,1,2,1,1,4,4,4,4,4,4,4,3,4,4,7,6.0,satisfied +91940,61338,Male,Loyal Customer,46,Business travel,Business,3760,2,2,2,2,3,4,4,4,4,4,4,3,4,5,12,0.0,satisfied +91941,16494,Male,Loyal Customer,47,Business travel,Eco,282,5,1,1,1,5,5,5,5,1,4,4,5,3,5,0,0.0,satisfied +91942,105626,Female,Loyal Customer,56,Business travel,Business,1931,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +91943,44448,Female,disloyal Customer,23,Business travel,Eco,1203,3,3,3,4,4,3,4,4,1,3,3,1,4,4,0,6.0,neutral or dissatisfied +91944,106504,Male,Loyal Customer,70,Personal Travel,Eco,495,3,4,3,3,5,3,5,5,4,3,4,4,4,5,13,0.0,neutral or dissatisfied +91945,122217,Male,Loyal Customer,49,Business travel,Eco,546,2,4,4,4,2,2,2,2,3,4,4,4,3,2,2,10.0,neutral or dissatisfied +91946,17735,Female,disloyal Customer,20,Business travel,Eco,456,2,2,2,3,2,3,4,2,5,3,4,4,3,4,168,181.0,neutral or dissatisfied +91947,3704,Male,Loyal Customer,51,Personal Travel,Eco,431,0,4,0,1,2,0,2,2,4,4,4,5,5,2,37,121.0,satisfied +91948,76970,Male,disloyal Customer,46,Business travel,Business,1990,3,4,4,2,4,3,4,4,3,5,4,5,5,4,10,11.0,neutral or dissatisfied +91949,53798,Female,Loyal Customer,43,Business travel,Business,191,0,4,0,4,2,2,3,2,2,2,2,1,2,3,0,0.0,satisfied +91950,127584,Female,Loyal Customer,42,Business travel,Business,1773,4,4,4,4,3,3,4,5,5,4,5,3,5,4,0,0.0,satisfied +91951,107183,Female,disloyal Customer,26,Business travel,Business,402,4,5,4,5,2,4,2,2,4,3,5,3,4,2,0,0.0,satisfied +91952,83899,Male,Loyal Customer,45,Business travel,Business,1050,5,5,3,5,1,4,1,5,5,5,5,4,5,1,0,0.0,satisfied +91953,100987,Female,Loyal Customer,25,Business travel,Business,867,5,4,5,5,5,5,5,5,3,3,5,3,4,5,6,5.0,satisfied +91954,23461,Male,Loyal Customer,24,Business travel,Business,576,2,2,2,2,2,2,2,2,2,2,2,4,2,2,81,83.0,neutral or dissatisfied +91955,72752,Male,disloyal Customer,63,Business travel,Eco,406,1,0,1,4,5,1,5,5,1,1,1,2,2,5,0,3.0,neutral or dissatisfied +91956,53122,Female,Loyal Customer,60,Personal Travel,Eco,2065,1,4,1,3,3,3,4,5,5,1,4,4,5,4,0,0.0,neutral or dissatisfied +91957,110126,Female,Loyal Customer,50,Business travel,Business,1048,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +91958,127686,Male,Loyal Customer,49,Business travel,Business,2133,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,2.0,satisfied +91959,12824,Male,Loyal Customer,53,Business travel,Business,3778,4,4,3,4,4,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +91960,12685,Male,Loyal Customer,62,Business travel,Eco,689,4,5,5,5,4,4,4,2,1,3,4,4,5,4,144,122.0,satisfied +91961,23211,Female,Loyal Customer,23,Business travel,Business,326,3,3,3,3,4,4,4,4,1,4,3,2,2,4,30,34.0,satisfied +91962,40111,Male,Loyal Customer,48,Business travel,Business,422,5,5,5,5,1,1,4,5,5,5,5,4,5,1,0,0.0,satisfied +91963,53330,Male,disloyal Customer,42,Business travel,Eco Plus,758,4,4,4,4,2,4,2,2,5,3,1,4,1,2,0,0.0,neutral or dissatisfied +91964,11375,Male,Loyal Customer,45,Personal Travel,Eco,312,3,2,3,4,2,3,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +91965,61249,Female,Loyal Customer,59,Personal Travel,Eco,967,4,2,4,3,4,4,3,5,5,4,1,1,5,3,13,1.0,satisfied +91966,50603,Male,Loyal Customer,11,Personal Travel,Eco,156,2,1,2,3,5,2,2,5,2,1,4,1,3,5,81,103.0,neutral or dissatisfied +91967,104024,Male,Loyal Customer,58,Business travel,Business,1262,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,2.0,satisfied +91968,77442,Female,Loyal Customer,18,Personal Travel,Eco Plus,588,4,5,3,2,2,3,2,2,4,5,4,4,4,2,79,72.0,neutral or dissatisfied +91969,37121,Female,Loyal Customer,53,Business travel,Business,1189,5,5,5,5,1,1,4,5,5,5,5,1,5,3,0,0.0,satisfied +91970,95932,Female,Loyal Customer,55,Business travel,Business,1813,4,4,4,4,5,3,3,4,4,4,4,1,4,3,26,11.0,neutral or dissatisfied +91971,81498,Male,Loyal Customer,26,Personal Travel,Eco,528,3,3,3,1,1,3,1,1,4,2,2,4,1,1,0,0.0,neutral or dissatisfied +91972,114857,Male,Loyal Customer,53,Business travel,Business,1925,1,1,1,1,5,4,5,5,5,5,5,4,5,3,16,11.0,satisfied +91973,21090,Male,disloyal Customer,22,Business travel,Eco,227,5,5,5,2,1,5,1,1,4,4,4,2,5,1,0,0.0,satisfied +91974,105363,Male,disloyal Customer,30,Business travel,Business,369,4,4,4,3,1,4,1,1,3,2,5,3,4,1,23,11.0,neutral or dissatisfied +91975,84142,Male,Loyal Customer,47,Business travel,Business,782,2,2,2,2,2,5,4,5,5,5,5,4,5,5,61,87.0,satisfied +91976,70516,Male,Loyal Customer,44,Personal Travel,Eco,867,2,5,2,1,4,2,5,4,4,1,2,4,1,4,0,3.0,neutral or dissatisfied +91977,52252,Male,Loyal Customer,22,Business travel,Business,370,4,4,4,4,5,5,5,5,5,1,3,5,2,5,0,0.0,satisfied +91978,82473,Female,Loyal Customer,69,Personal Travel,Eco,502,3,3,4,3,3,3,2,2,2,4,2,2,2,2,0,0.0,neutral or dissatisfied +91979,78672,Male,Loyal Customer,23,Business travel,Business,1657,3,3,3,3,4,4,4,4,4,4,5,4,4,4,0,1.0,satisfied +91980,42433,Female,Loyal Customer,40,Business travel,Business,1119,1,1,1,1,3,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +91981,36642,Male,Loyal Customer,67,Personal Travel,Eco,1197,0,4,0,4,5,0,5,5,1,3,5,3,4,5,0,0.0,satisfied +91982,82061,Female,disloyal Customer,20,Business travel,Business,1298,3,2,3,2,5,3,5,5,3,2,3,2,3,5,0,0.0,neutral or dissatisfied +91983,4005,Male,Loyal Customer,60,Business travel,Business,479,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +91984,121989,Female,Loyal Customer,50,Business travel,Business,2714,4,4,1,4,3,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +91985,56782,Male,Loyal Customer,63,Personal Travel,Eco Plus,1068,3,3,3,4,5,3,5,5,3,5,4,3,1,5,32,0.0,neutral or dissatisfied +91986,122921,Male,Loyal Customer,38,Personal Travel,Business,600,2,1,1,3,2,2,3,5,5,1,5,3,5,1,0,0.0,neutral or dissatisfied +91987,102784,Female,Loyal Customer,14,Business travel,Eco,1099,2,2,2,2,2,2,2,2,2,3,3,1,3,2,0,4.0,neutral or dissatisfied +91988,78402,Female,disloyal Customer,59,Business travel,Business,201,3,3,3,2,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +91989,4766,Male,Loyal Customer,31,Business travel,Business,403,3,3,3,3,5,5,5,5,5,5,5,4,4,5,19,30.0,satisfied +91990,78735,Female,disloyal Customer,25,Business travel,Business,447,3,5,3,1,4,3,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +91991,64953,Female,Loyal Customer,37,Business travel,Eco,247,3,4,2,4,3,3,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +91992,66459,Female,Loyal Customer,14,Personal Travel,Eco,1217,1,5,1,1,4,1,2,4,3,2,5,4,4,4,3,10.0,neutral or dissatisfied +91993,57955,Female,Loyal Customer,33,Personal Travel,Eco,1062,4,5,4,4,4,2,2,3,5,4,4,2,4,2,175,165.0,neutral or dissatisfied +91994,89567,Male,Loyal Customer,30,Business travel,Business,2034,4,4,4,4,4,4,4,4,5,4,5,4,4,4,4,6.0,satisfied +91995,2483,Male,Loyal Customer,60,Business travel,Business,715,4,4,4,4,4,5,5,5,5,5,5,4,5,3,42,33.0,satisfied +91996,43807,Female,Loyal Customer,60,Business travel,Business,3908,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +91997,122838,Male,Loyal Customer,27,Business travel,Business,3416,2,2,2,2,4,4,4,4,5,2,4,5,5,4,1,0.0,satisfied +91998,49295,Female,Loyal Customer,45,Business travel,Eco,308,4,5,5,5,5,3,2,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +91999,24684,Female,Loyal Customer,44,Business travel,Business,761,1,1,1,1,4,3,2,4,4,4,4,3,4,5,11,0.0,satisfied +92000,26852,Male,Loyal Customer,65,Personal Travel,Eco,224,4,2,4,3,5,4,5,5,4,2,4,1,3,5,0,0.0,neutral or dissatisfied +92001,15747,Female,disloyal Customer,37,Business travel,Eco,461,3,0,3,1,4,3,4,4,1,2,2,2,1,4,0,0.0,neutral or dissatisfied +92002,21966,Female,Loyal Customer,48,Business travel,Business,448,3,3,3,3,3,3,4,3,3,3,3,3,3,1,13,2.0,neutral or dissatisfied +92003,126897,Male,Loyal Customer,58,Business travel,Business,2296,2,2,2,2,5,3,4,4,4,4,4,3,4,5,0,8.0,satisfied +92004,125787,Female,Loyal Customer,50,Business travel,Business,2751,4,2,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +92005,61691,Female,disloyal Customer,25,Business travel,Business,1138,5,0,4,5,5,4,5,5,3,4,4,4,5,5,2,0.0,satisfied +92006,13924,Male,disloyal Customer,24,Business travel,Eco,317,3,4,3,1,3,3,3,3,2,1,5,4,4,3,27,17.0,neutral or dissatisfied +92007,66622,Male,Loyal Customer,55,Business travel,Business,1860,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +92008,66287,Female,Loyal Customer,25,Personal Travel,Eco Plus,550,4,2,4,4,3,4,3,3,3,2,3,4,4,3,0,0.0,satisfied +92009,128492,Male,Loyal Customer,46,Personal Travel,Eco,647,3,5,3,1,4,3,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +92010,99214,Male,Loyal Customer,39,Business travel,Business,1729,5,5,5,5,4,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +92011,112454,Male,disloyal Customer,25,Business travel,Eco,853,3,3,3,4,1,3,1,1,1,1,5,1,2,1,20,4.0,neutral or dissatisfied +92012,15921,Male,Loyal Customer,48,Business travel,Eco,723,4,5,5,5,4,4,4,4,4,1,2,1,2,4,0,35.0,satisfied +92013,126839,Female,Loyal Customer,31,Business travel,Business,2125,3,3,3,3,2,2,2,2,3,2,5,4,5,2,3,0.0,satisfied +92014,101440,Male,Loyal Customer,48,Business travel,Business,1793,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +92015,46897,Female,disloyal Customer,39,Business travel,Business,959,4,4,4,3,4,4,4,4,2,5,5,3,3,4,32,63.0,satisfied +92016,73922,Female,Loyal Customer,12,Business travel,Business,2585,4,4,4,4,4,4,4,3,3,3,5,4,4,4,4,22.0,satisfied +92017,20742,Female,Loyal Customer,40,Business travel,Business,3590,1,4,4,4,4,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +92018,79207,Male,Loyal Customer,58,Business travel,Business,1990,4,1,2,2,1,2,4,4,4,4,4,4,4,4,29,20.0,neutral or dissatisfied +92019,43015,Female,disloyal Customer,24,Business travel,Eco,236,3,0,3,1,2,3,5,2,3,5,5,3,4,2,0,2.0,neutral or dissatisfied +92020,54998,Female,Loyal Customer,21,Business travel,Business,2699,2,2,2,2,5,4,5,5,3,5,5,4,5,5,0,0.0,satisfied +92021,106225,Male,Loyal Customer,34,Business travel,Business,3947,2,1,1,1,5,4,4,2,2,2,2,4,2,3,8,0.0,neutral or dissatisfied +92022,41370,Male,disloyal Customer,14,Business travel,Eco,563,3,0,4,3,2,4,2,2,4,2,5,5,1,2,0,2.0,neutral or dissatisfied +92023,9647,Male,disloyal Customer,24,Business travel,Business,284,0,0,0,2,2,0,2,2,4,4,4,3,4,2,0,0.0,satisfied +92024,102852,Female,Loyal Customer,68,Personal Travel,Eco,423,3,4,3,1,5,4,4,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +92025,77275,Male,disloyal Customer,22,Business travel,Eco,1237,5,4,4,2,2,4,2,2,4,2,3,4,5,2,0,0.0,satisfied +92026,114214,Female,Loyal Customer,41,Business travel,Business,2715,3,1,2,1,3,2,2,3,3,3,3,2,3,2,30,7.0,neutral or dissatisfied +92027,76654,Female,Loyal Customer,50,Personal Travel,Eco,534,3,4,3,3,3,5,4,2,2,3,2,4,2,4,21,7.0,neutral or dissatisfied +92028,92858,Male,Loyal Customer,54,Personal Travel,Business,2519,3,3,3,3,3,4,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +92029,90603,Male,Loyal Customer,39,Business travel,Business,515,3,3,3,3,4,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +92030,8811,Male,disloyal Customer,37,Business travel,Eco,122,4,0,4,1,1,4,1,1,5,4,4,1,3,1,0,0.0,neutral or dissatisfied +92031,125287,Female,Loyal Customer,56,Business travel,Business,3357,3,2,2,2,1,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +92032,1913,Male,disloyal Customer,34,Business travel,Business,383,3,3,3,3,5,3,5,5,4,3,5,5,4,5,45,46.0,neutral or dissatisfied +92033,80593,Male,Loyal Customer,41,Business travel,Business,1747,3,3,3,3,5,3,5,4,4,4,4,3,4,5,2,0.0,satisfied +92034,36568,Female,Loyal Customer,58,Business travel,Eco,1121,5,5,5,5,2,4,2,5,5,5,5,1,5,4,71,61.0,satisfied +92035,27253,Male,Loyal Customer,39,Business travel,Business,2448,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +92036,115888,Male,disloyal Customer,80,Business travel,Eco,325,2,0,2,4,5,2,5,5,1,2,5,5,4,5,0,0.0,neutral or dissatisfied +92037,126576,Male,Loyal Customer,52,Personal Travel,Eco,1558,5,4,5,4,1,5,1,1,4,4,5,3,4,1,0,0.0,satisfied +92038,5493,Female,Loyal Customer,48,Business travel,Business,2589,4,4,4,4,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +92039,56850,Female,Loyal Customer,44,Business travel,Business,2565,1,1,1,1,5,5,5,4,4,4,5,5,3,5,0,2.0,satisfied +92040,89204,Male,Loyal Customer,61,Personal Travel,Eco,1919,2,4,3,4,5,3,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +92041,110248,Female,Loyal Customer,29,Personal Travel,Eco,1138,1,5,1,2,4,1,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +92042,28686,Male,Loyal Customer,10,Personal Travel,Eco,2777,3,2,3,4,3,5,5,2,1,4,4,5,1,5,0,0.0,neutral or dissatisfied +92043,65067,Male,Loyal Customer,52,Personal Travel,Eco,469,2,5,2,1,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +92044,57304,Male,Loyal Customer,54,Personal Travel,Business,414,3,3,3,4,2,3,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +92045,122408,Male,Loyal Customer,47,Business travel,Business,1916,2,2,2,2,2,4,4,4,4,4,4,3,4,3,5,0.0,satisfied +92046,76523,Female,Loyal Customer,57,Business travel,Business,3082,4,4,4,4,5,4,4,4,4,5,4,5,4,4,0,5.0,satisfied +92047,8470,Female,Loyal Customer,37,Personal Travel,Business,1187,1,4,1,4,2,5,5,2,2,1,3,4,2,5,0,2.0,neutral or dissatisfied +92048,56988,Male,Loyal Customer,17,Personal Travel,Eco,2454,4,3,3,3,3,3,3,4,4,2,2,3,2,3,18,59.0,neutral or dissatisfied +92049,46388,Male,disloyal Customer,50,Business travel,Eco,511,5,3,5,3,3,5,3,3,5,1,1,4,3,3,0,0.0,satisfied +92050,119904,Female,Loyal Customer,19,Personal Travel,Eco Plus,912,2,5,2,1,3,2,4,3,5,4,5,5,5,3,2,0.0,neutral or dissatisfied +92051,119954,Male,Loyal Customer,66,Business travel,Eco,1009,2,2,4,2,2,2,2,2,4,5,3,4,3,2,0,,neutral or dissatisfied +92052,66259,Male,Loyal Customer,52,Personal Travel,Eco,550,1,0,1,4,2,1,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +92053,84777,Male,disloyal Customer,25,Business travel,Business,534,4,5,4,5,3,4,3,3,3,5,4,4,5,3,16,7.0,satisfied +92054,79861,Female,Loyal Customer,35,Business travel,Business,2845,4,4,4,4,4,5,4,4,4,5,4,3,4,3,54,21.0,satisfied +92055,36105,Female,Loyal Customer,32,Business travel,Eco Plus,399,4,4,4,4,4,4,4,4,5,2,5,1,1,4,1,0.0,satisfied +92056,43136,Male,Loyal Customer,48,Business travel,Eco Plus,391,4,5,5,5,4,4,4,4,3,1,3,3,4,4,0,0.0,neutral or dissatisfied +92057,79464,Female,Loyal Customer,31,Personal Travel,Eco,1183,5,5,5,2,2,5,2,2,4,5,5,5,5,2,95,114.0,satisfied +92058,125993,Male,Loyal Customer,11,Personal Travel,Business,468,3,1,1,3,3,1,3,3,4,4,3,4,3,3,0,12.0,neutral or dissatisfied +92059,20248,Female,Loyal Customer,31,Business travel,Business,1711,3,3,3,3,5,5,5,5,1,1,3,4,2,5,5,16.0,satisfied +92060,81028,Male,Loyal Customer,55,Business travel,Business,1175,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +92061,104194,Male,Loyal Customer,53,Business travel,Business,2854,5,5,5,5,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +92062,97441,Female,Loyal Customer,65,Personal Travel,Eco,585,3,4,3,2,4,5,4,3,3,3,3,4,3,3,3,2.0,neutral or dissatisfied +92063,61291,Male,Loyal Customer,50,Personal Travel,Eco,967,3,5,3,5,5,3,5,5,5,4,5,4,4,5,24,23.0,neutral or dissatisfied +92064,45356,Male,Loyal Customer,30,Personal Travel,Eco,150,2,2,2,3,3,2,3,3,4,3,4,3,4,3,0,16.0,neutral or dissatisfied +92065,104704,Male,Loyal Customer,47,Personal Travel,Eco,159,3,5,3,2,3,3,3,3,4,5,5,5,5,3,18,16.0,neutral or dissatisfied +92066,16609,Male,Loyal Customer,40,Business travel,Business,3230,1,1,1,1,3,1,1,5,5,5,5,4,5,5,0,0.0,satisfied +92067,105510,Female,Loyal Customer,60,Business travel,Business,611,2,2,2,2,2,5,4,5,5,4,5,4,5,5,66,78.0,satisfied +92068,3508,Female,Loyal Customer,51,Business travel,Eco,568,2,1,1,1,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +92069,78021,Female,disloyal Customer,45,Business travel,Eco,214,1,0,2,5,4,2,4,4,2,3,5,2,2,4,0,0.0,neutral or dissatisfied +92070,5904,Female,Loyal Customer,57,Business travel,Business,215,4,4,5,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +92071,119403,Female,Loyal Customer,23,Business travel,Business,2798,2,1,1,1,2,2,2,2,4,5,2,3,2,2,25,33.0,neutral or dissatisfied +92072,3817,Male,Loyal Customer,51,Business travel,Business,650,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +92073,79942,Female,disloyal Customer,25,Business travel,Eco,1069,1,1,1,3,1,3,3,4,1,4,4,3,3,3,113,136.0,neutral or dissatisfied +92074,6045,Female,disloyal Customer,22,Business travel,Eco,630,4,3,4,4,1,4,1,1,4,4,3,4,3,1,3,33.0,neutral or dissatisfied +92075,67338,Male,Loyal Customer,57,Business travel,Business,1471,1,2,2,2,5,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +92076,62652,Female,Loyal Customer,27,Personal Travel,Eco,1744,1,4,1,4,2,1,2,2,3,3,3,4,5,2,0,0.0,neutral or dissatisfied +92077,115799,Female,disloyal Customer,24,Business travel,Eco,372,4,4,4,4,2,4,2,2,2,1,5,3,2,2,61,45.0,satisfied +92078,100678,Male,Loyal Customer,61,Business travel,Business,1974,2,5,5,5,1,3,4,2,2,2,2,2,2,4,6,6.0,neutral or dissatisfied +92079,52430,Female,Loyal Customer,40,Personal Travel,Eco,425,5,2,2,4,5,2,4,5,1,3,2,1,3,5,0,0.0,satisfied +92080,124650,Male,Loyal Customer,60,Personal Travel,Business,399,4,4,4,2,4,4,4,2,2,4,2,3,2,5,10,11.0,neutral or dissatisfied +92081,127685,Female,Loyal Customer,50,Business travel,Business,2133,4,4,4,4,2,4,4,5,5,5,5,4,5,5,0,3.0,satisfied +92082,94263,Male,disloyal Customer,29,Business travel,Business,677,4,4,4,1,2,4,2,2,3,4,5,4,4,2,0,0.0,satisfied +92083,5715,Male,Loyal Customer,62,Personal Travel,Eco,436,1,4,1,1,5,1,5,5,2,4,5,5,3,5,0,0.0,neutral or dissatisfied +92084,2127,Male,disloyal Customer,34,Business travel,Business,404,1,1,1,3,4,1,4,4,1,2,2,3,3,4,28,62.0,neutral or dissatisfied +92085,105796,Female,Loyal Customer,66,Personal Travel,Eco,919,2,5,1,3,2,4,5,5,5,1,5,5,5,4,23,35.0,neutral or dissatisfied +92086,26417,Female,Loyal Customer,51,Business travel,Business,2028,2,3,3,3,4,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +92087,68669,Female,disloyal Customer,38,Business travel,Eco,175,2,1,2,4,2,1,1,1,1,3,4,1,3,1,276,263.0,neutral or dissatisfied +92088,29037,Male,Loyal Customer,20,Personal Travel,Eco,987,4,5,4,5,5,4,5,5,3,3,5,3,5,5,11,0.0,satisfied +92089,112724,Male,Loyal Customer,42,Personal Travel,Eco,605,3,2,3,3,2,3,2,2,1,1,3,2,4,2,10,7.0,neutral or dissatisfied +92090,49221,Male,Loyal Customer,45,Business travel,Eco,109,5,5,5,5,4,5,4,4,2,4,5,2,3,4,5,5.0,satisfied +92091,101185,Female,Loyal Customer,15,Personal Travel,Eco,758,3,5,4,4,3,4,5,3,1,2,5,3,2,3,0,0.0,neutral or dissatisfied +92092,32728,Female,Loyal Customer,52,Business travel,Eco,102,5,2,2,2,1,3,5,5,5,5,5,4,5,3,0,3.0,satisfied +92093,1783,Female,disloyal Customer,24,Business travel,Eco,408,2,0,2,2,4,2,4,4,5,5,5,4,5,4,39,51.0,neutral or dissatisfied +92094,85741,Male,Loyal Customer,20,Business travel,Business,2672,3,3,1,3,4,4,4,4,3,4,4,3,5,4,11,0.0,satisfied +92095,116475,Female,Loyal Customer,34,Personal Travel,Eco,337,3,5,3,2,5,3,1,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +92096,10885,Male,Loyal Customer,40,Business travel,Business,1506,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +92097,29950,Female,Loyal Customer,61,Business travel,Eco,95,4,2,2,2,2,1,1,3,3,4,3,2,3,1,0,0.0,satisfied +92098,60877,Male,disloyal Customer,21,Business travel,Business,1062,5,0,5,2,5,5,5,5,4,2,5,5,5,5,25,31.0,satisfied +92099,33727,Female,Loyal Customer,47,Personal Travel,Eco,814,4,0,4,1,2,5,5,5,5,4,5,4,5,3,9,6.0,neutral or dissatisfied +92100,51095,Female,Loyal Customer,21,Personal Travel,Eco,158,2,4,2,1,3,2,3,3,5,2,5,5,4,3,81,82.0,neutral or dissatisfied +92101,91480,Female,Loyal Customer,67,Personal Travel,Eco,859,3,4,3,4,2,4,4,1,1,3,5,5,1,4,0,0.0,neutral or dissatisfied +92102,25743,Female,disloyal Customer,25,Business travel,Eco Plus,432,4,0,4,3,5,4,5,5,3,2,3,1,2,5,14,21.0,neutral or dissatisfied +92103,99358,Female,Loyal Customer,27,Business travel,Eco Plus,1771,2,5,5,5,2,2,2,2,3,4,2,2,3,2,0,0.0,neutral or dissatisfied +92104,47054,Male,Loyal Customer,34,Business travel,Business,2399,1,1,1,1,1,3,3,4,4,4,4,4,4,4,0,0.0,satisfied +92105,92583,Male,Loyal Customer,30,Business travel,Business,1947,1,1,1,1,4,4,4,4,3,2,4,3,5,4,7,0.0,satisfied +92106,86871,Male,Loyal Customer,50,Business travel,Business,484,3,3,3,3,5,5,4,5,5,5,5,4,5,5,27,11.0,satisfied +92107,104245,Female,Loyal Customer,37,Business travel,Business,3537,2,5,2,5,4,3,3,2,2,2,2,2,2,1,0,16.0,neutral or dissatisfied +92108,129358,Male,Loyal Customer,68,Personal Travel,Eco Plus,2586,2,3,1,1,2,1,2,2,5,1,3,1,3,2,0,0.0,neutral or dissatisfied +92109,13845,Male,Loyal Customer,11,Personal Travel,Eco,628,3,4,3,3,4,3,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +92110,33742,Male,Loyal Customer,46,Business travel,Eco,2277,4,2,2,2,4,5,5,3,4,4,4,5,1,5,144,158.0,satisfied +92111,85635,Female,Loyal Customer,70,Personal Travel,Eco,153,3,4,3,3,4,4,4,3,3,3,3,4,3,2,0,6.0,neutral or dissatisfied +92112,18372,Female,Loyal Customer,55,Personal Travel,Eco,169,1,5,0,3,1,2,5,4,4,0,4,4,4,1,38,26.0,neutral or dissatisfied +92113,26202,Female,Loyal Customer,23,Business travel,Eco,406,1,4,4,4,1,1,4,1,1,1,3,4,3,1,0,0.0,neutral or dissatisfied +92114,49873,Male,disloyal Customer,25,Business travel,Eco,78,2,0,2,3,5,2,5,5,4,4,3,4,4,5,12,4.0,neutral or dissatisfied +92115,56605,Female,Loyal Customer,72,Business travel,Eco,1065,2,1,1,1,5,3,2,2,2,2,2,1,2,3,3,0.0,neutral or dissatisfied +92116,12503,Male,Loyal Customer,66,Personal Travel,Eco Plus,253,2,1,2,3,5,2,5,5,2,4,2,2,3,5,0,4.0,neutral or dissatisfied +92117,15717,Male,Loyal Customer,49,Business travel,Eco,419,1,1,1,1,1,1,1,1,4,4,2,1,3,1,90,71.0,neutral or dissatisfied +92118,57781,Male,Loyal Customer,17,Personal Travel,Eco,2704,4,0,4,2,4,4,4,5,4,3,5,4,1,4,5,0.0,satisfied +92119,117700,Male,disloyal Customer,43,Business travel,Business,2075,3,4,4,1,1,3,1,1,4,3,5,5,4,1,19,0.0,neutral or dissatisfied +92120,1670,Male,Loyal Customer,33,Personal Travel,Business,561,3,4,2,4,4,2,4,4,3,2,5,3,5,4,10,48.0,neutral or dissatisfied +92121,50032,Female,Loyal Customer,30,Business travel,Eco,78,1,5,5,5,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +92122,64601,Male,Loyal Customer,49,Business travel,Business,190,3,3,3,3,5,5,4,4,4,4,5,5,4,5,0,3.0,satisfied +92123,22122,Male,Loyal Customer,28,Personal Travel,Eco,694,3,4,3,3,4,3,4,4,4,3,5,5,5,4,15,1.0,neutral or dissatisfied +92124,85216,Female,disloyal Customer,43,Business travel,Eco,689,1,1,1,4,1,1,2,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +92125,67844,Male,Loyal Customer,49,Personal Travel,Eco,1235,4,4,4,4,4,4,4,4,3,2,4,3,5,4,3,0.0,satisfied +92126,6854,Female,disloyal Customer,20,Business travel,Eco,622,2,4,2,3,5,2,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +92127,25872,Female,Loyal Customer,50,Business travel,Business,907,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +92128,11317,Female,Loyal Customer,34,Personal Travel,Eco,201,4,5,4,1,2,4,2,2,5,2,3,5,1,2,23,20.0,neutral or dissatisfied +92129,81214,Male,Loyal Customer,43,Business travel,Business,1426,3,4,4,4,3,3,3,3,3,3,3,3,3,3,0,1.0,neutral or dissatisfied +92130,23101,Male,Loyal Customer,44,Business travel,Business,2042,3,3,3,3,4,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +92131,77119,Male,Loyal Customer,60,Personal Travel,Eco,1481,2,1,2,4,5,2,4,5,2,5,4,1,3,5,0,0.0,neutral or dissatisfied +92132,90379,Female,Loyal Customer,47,Business travel,Business,3311,4,4,4,4,4,5,4,3,3,4,3,4,3,3,0,0.0,satisfied +92133,96460,Female,Loyal Customer,50,Business travel,Business,302,3,3,1,3,3,5,5,4,4,4,4,4,4,5,6,4.0,satisfied +92134,1838,Female,Loyal Customer,34,Personal Travel,Eco,408,2,1,2,3,5,2,5,5,1,2,3,4,3,5,0,0.0,neutral or dissatisfied +92135,115602,Male,disloyal Customer,26,Business travel,Business,480,1,1,1,3,2,1,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +92136,92375,Male,Loyal Customer,51,Personal Travel,Business,1892,1,5,1,3,2,2,2,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +92137,15935,Female,Loyal Customer,26,Business travel,Business,528,1,4,4,4,1,1,1,3,4,3,3,1,1,1,183,180.0,neutral or dissatisfied +92138,27461,Female,disloyal Customer,44,Business travel,Eco,697,3,4,4,2,4,4,4,4,1,3,2,2,3,4,0,0.0,neutral or dissatisfied +92139,126471,Male,disloyal Customer,14,Business travel,Eco,1039,2,2,2,3,4,2,4,4,4,4,3,2,3,4,0,8.0,neutral or dissatisfied +92140,95997,Male,disloyal Customer,17,Business travel,Business,1235,5,0,5,2,5,5,4,5,5,3,4,4,4,5,0,2.0,satisfied +92141,68536,Male,Loyal Customer,42,Business travel,Business,1013,3,3,3,3,4,3,4,3,3,3,3,4,3,2,20,91.0,neutral or dissatisfied +92142,15214,Female,Loyal Customer,37,Business travel,Eco,529,3,4,4,4,3,3,3,3,4,4,5,5,5,3,0,0.0,satisfied +92143,36731,Male,Loyal Customer,60,Personal Travel,Business,1754,5,5,5,1,5,3,1,4,4,5,4,1,4,3,0,0.0,satisfied +92144,92077,Female,Loyal Customer,37,Business travel,Business,1589,5,5,5,5,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +92145,35126,Female,disloyal Customer,19,Business travel,Eco,828,4,3,3,3,5,3,5,5,4,2,3,4,3,5,0,0.0,satisfied +92146,100384,Female,Loyal Customer,27,Personal Travel,Eco,1073,1,5,1,4,2,1,2,2,4,5,4,3,5,2,0,8.0,neutral or dissatisfied +92147,85466,Male,disloyal Customer,20,Business travel,Eco,214,2,0,2,5,3,2,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +92148,43109,Female,Loyal Customer,27,Personal Travel,Eco,192,4,4,4,5,1,4,2,1,5,3,4,4,4,1,0,0.0,satisfied +92149,68184,Female,Loyal Customer,64,Personal Travel,Eco,603,3,1,3,3,4,3,4,1,1,3,1,1,1,4,15,9.0,neutral or dissatisfied +92150,112108,Female,Loyal Customer,20,Personal Travel,Eco,1062,3,4,3,4,5,3,5,5,5,4,4,5,5,5,50,38.0,neutral or dissatisfied +92151,38241,Female,Loyal Customer,16,Business travel,Eco,1050,4,5,5,5,4,4,5,4,3,2,1,1,1,4,38,31.0,satisfied +92152,101126,Male,Loyal Customer,54,Business travel,Business,795,1,1,1,1,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +92153,50550,Female,Loyal Customer,52,Personal Travel,Eco,86,4,5,0,3,2,2,2,3,3,0,3,1,3,1,0,0.0,satisfied +92154,117460,Female,Loyal Customer,64,Personal Travel,Eco,1107,3,3,2,3,5,5,4,4,4,2,4,3,4,5,15,23.0,neutral or dissatisfied +92155,128382,Female,Loyal Customer,38,Business travel,Eco,355,4,4,4,4,4,4,4,4,1,4,3,3,3,4,4,8.0,neutral or dissatisfied +92156,121217,Female,Loyal Customer,47,Business travel,Business,2075,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +92157,31414,Male,Loyal Customer,56,Business travel,Business,1546,4,4,4,4,1,1,1,5,5,5,5,5,5,2,0,0.0,satisfied +92158,62528,Female,Loyal Customer,39,Business travel,Business,1726,4,4,4,4,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +92159,66751,Female,Loyal Customer,17,Personal Travel,Eco,802,2,5,2,5,3,2,3,3,1,2,5,4,2,3,60,57.0,neutral or dissatisfied +92160,103656,Male,Loyal Customer,30,Business travel,Business,466,5,5,5,5,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +92161,108828,Female,Loyal Customer,43,Business travel,Business,1199,1,1,1,1,5,5,5,5,5,5,5,3,5,5,51,50.0,satisfied +92162,88165,Female,Loyal Customer,47,Business travel,Business,3547,3,3,3,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +92163,39091,Female,Loyal Customer,27,Business travel,Business,1886,2,2,1,2,4,4,4,4,5,5,2,5,5,4,0,11.0,satisfied +92164,112887,Male,Loyal Customer,35,Business travel,Business,1642,3,1,1,1,2,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +92165,110790,Male,disloyal Customer,19,Business travel,Eco,990,2,2,2,3,3,2,3,3,3,1,4,1,4,3,0,0.0,neutral or dissatisfied +92166,99269,Female,Loyal Customer,42,Business travel,Business,833,4,4,4,4,2,5,5,3,3,4,3,4,3,3,22,34.0,satisfied +92167,16010,Male,disloyal Customer,43,Business travel,Eco,380,3,3,3,3,1,3,1,1,4,5,3,3,4,1,0,8.0,neutral or dissatisfied +92168,22195,Female,Loyal Customer,38,Business travel,Eco,133,1,0,0,4,2,0,2,2,2,4,3,2,4,2,19,8.0,neutral or dissatisfied +92169,29773,Female,Loyal Customer,51,Personal Travel,Business,503,3,4,3,2,5,5,4,3,3,3,2,5,3,4,0,0.0,neutral or dissatisfied +92170,64618,Female,disloyal Customer,44,Business travel,Business,224,3,3,3,5,3,3,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +92171,32554,Male,Loyal Customer,47,Business travel,Eco,163,5,5,5,5,5,5,5,5,1,4,5,5,4,5,0,0.0,satisfied +92172,113707,Male,Loyal Customer,49,Personal Travel,Eco,414,2,5,2,3,4,2,4,4,3,5,5,3,3,4,86,83.0,neutral or dissatisfied +92173,56070,Male,Loyal Customer,22,Personal Travel,Eco,2586,2,1,2,3,2,4,4,3,5,3,4,4,3,4,0,23.0,neutral or dissatisfied +92174,57159,Female,Loyal Customer,35,Personal Travel,Eco,1824,3,5,3,3,2,3,2,2,5,5,4,4,5,2,24,19.0,neutral or dissatisfied +92175,84702,Male,Loyal Customer,30,Business travel,Business,3875,5,2,5,5,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +92176,118937,Male,disloyal Customer,43,Business travel,Eco,1618,3,3,3,3,2,3,4,2,4,4,4,2,3,2,6,0.0,neutral or dissatisfied +92177,69031,Female,disloyal Customer,45,Business travel,Business,1389,4,4,4,2,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +92178,32918,Male,Loyal Customer,47,Personal Travel,Eco,101,3,5,3,1,3,3,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +92179,104455,Male,Loyal Customer,59,Business travel,Business,1015,5,5,5,5,4,5,4,4,4,3,4,5,4,3,0,0.0,satisfied +92180,107356,Female,disloyal Customer,39,Business travel,Eco,184,3,3,3,3,2,3,2,2,3,3,4,2,3,2,38,27.0,neutral or dissatisfied +92181,32556,Female,Loyal Customer,69,Business travel,Business,2595,3,3,3,3,4,3,3,5,5,5,5,2,5,1,0,0.0,satisfied +92182,111455,Female,Loyal Customer,48,Personal Travel,Eco,1024,0,2,0,4,5,4,4,2,2,0,2,3,2,1,14,7.0,satisfied +92183,96046,Female,disloyal Customer,45,Business travel,Business,1069,4,4,4,3,3,4,1,3,5,4,5,4,5,3,3,0.0,satisfied +92184,128299,Female,Loyal Customer,40,Business travel,Business,3301,0,0,0,2,5,4,5,5,5,5,5,5,5,4,89,78.0,satisfied +92185,16302,Male,Loyal Customer,38,Business travel,Eco,594,3,4,2,2,3,4,3,3,2,5,3,4,5,3,0,1.0,satisfied +92186,44861,Male,disloyal Customer,38,Business travel,Eco,585,3,0,3,1,2,3,2,2,4,4,5,3,4,2,0,5.0,neutral or dissatisfied +92187,65559,Female,disloyal Customer,24,Business travel,Business,175,5,0,5,2,3,0,4,3,3,2,4,4,5,3,3,0.0,satisfied +92188,2931,Male,Loyal Customer,41,Personal Travel,Eco,859,1,5,1,1,5,1,5,5,4,2,5,5,4,5,0,98.0,neutral or dissatisfied +92189,72629,Male,Loyal Customer,22,Personal Travel,Eco,1017,1,0,1,5,1,1,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +92190,126053,Male,Loyal Customer,28,Business travel,Business,600,1,1,1,1,4,5,4,4,4,2,5,3,5,4,0,0.0,satisfied +92191,75151,Male,Loyal Customer,45,Business travel,Eco,1726,1,5,5,5,2,1,2,2,3,3,4,2,4,2,102,90.0,neutral or dissatisfied +92192,31801,Male,Loyal Customer,39,Business travel,Eco Plus,2640,4,4,4,4,4,5,4,4,4,4,4,2,5,4,0,0.0,satisfied +92193,38427,Female,Loyal Customer,23,Personal Travel,Eco,965,1,1,1,1,1,1,1,1,4,2,2,4,1,1,30,27.0,neutral or dissatisfied +92194,82956,Female,Loyal Customer,34,Personal Travel,Business,1084,2,4,2,1,4,5,5,5,5,2,5,3,5,4,2,0.0,neutral or dissatisfied +92195,56027,Female,disloyal Customer,27,Business travel,Eco,1064,1,1,1,3,1,2,2,1,2,4,3,2,3,2,5,62.0,neutral or dissatisfied +92196,46103,Female,disloyal Customer,27,Business travel,Eco,1201,4,5,5,2,4,5,4,4,3,4,4,4,2,4,53,42.0,satisfied +92197,36248,Female,disloyal Customer,23,Business travel,Eco,612,5,3,5,1,5,5,5,5,1,4,1,1,4,5,0,0.0,satisfied +92198,78154,Female,disloyal Customer,39,Business travel,Business,259,2,2,2,5,2,2,2,2,4,5,4,5,5,2,0,8.0,neutral or dissatisfied +92199,86171,Male,disloyal Customer,23,Business travel,Eco,226,4,3,4,4,4,4,4,4,1,3,3,4,4,4,0,0.0,neutral or dissatisfied +92200,103905,Female,Loyal Customer,77,Business travel,Eco Plus,869,4,5,5,5,2,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +92201,88982,Male,Loyal Customer,35,Personal Travel,Eco,1199,1,2,1,3,4,1,3,4,4,3,3,3,4,4,0,0.0,neutral or dissatisfied +92202,120662,Female,disloyal Customer,26,Business travel,Eco,280,3,3,3,3,2,3,2,2,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +92203,24925,Male,Loyal Customer,36,Personal Travel,Eco,762,2,4,2,3,2,4,3,4,2,5,5,3,4,3,161,176.0,neutral or dissatisfied +92204,38443,Male,disloyal Customer,27,Business travel,Eco,588,3,2,3,3,4,3,4,4,2,1,3,1,3,4,15,14.0,neutral or dissatisfied +92205,81102,Male,Loyal Customer,45,Business travel,Business,991,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +92206,17336,Female,disloyal Customer,30,Business travel,Eco,563,2,0,2,5,2,2,2,2,3,2,3,2,2,2,12,9.0,neutral or dissatisfied +92207,86616,Male,Loyal Customer,50,Business travel,Business,2392,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +92208,59643,Female,disloyal Customer,17,Business travel,Eco,964,1,1,1,5,3,1,5,3,1,1,4,4,5,3,0,5.0,neutral or dissatisfied +92209,84043,Female,Loyal Customer,25,Personal Travel,Business,757,1,4,1,3,4,1,4,4,3,4,5,3,4,4,0,27.0,neutral or dissatisfied +92210,13182,Female,disloyal Customer,22,Business travel,Eco,419,3,3,3,3,3,3,3,3,3,2,3,5,5,3,0,6.0,neutral or dissatisfied +92211,114436,Male,Loyal Customer,52,Business travel,Business,1598,2,5,5,5,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +92212,23490,Female,Loyal Customer,44,Business travel,Eco Plus,488,4,4,4,4,4,3,3,4,4,4,4,1,4,3,0,0.0,satisfied +92213,100479,Female,Loyal Customer,51,Business travel,Business,580,3,3,3,3,5,4,5,5,5,5,5,4,5,5,17,2.0,satisfied +92214,116792,Male,Loyal Customer,56,Personal Travel,Eco Plus,417,1,3,1,4,5,1,5,5,4,4,5,3,5,5,27,21.0,neutral or dissatisfied +92215,8584,Female,Loyal Customer,30,Personal Travel,Eco,308,0,4,0,3,2,0,2,2,3,4,5,4,4,2,0,0.0,satisfied +92216,37639,Female,Loyal Customer,70,Personal Travel,Eco,972,2,2,2,4,4,3,3,3,3,2,3,4,3,2,11,0.0,neutral or dissatisfied +92217,99534,Male,disloyal Customer,22,Business travel,Business,808,4,0,4,2,2,4,2,2,5,2,5,5,5,2,0,0.0,satisfied +92218,2110,Male,Loyal Customer,37,Business travel,Eco Plus,412,1,3,3,3,1,1,1,1,1,4,2,1,1,1,0,0.0,neutral or dissatisfied +92219,44940,Male,disloyal Customer,26,Business travel,Eco,334,2,4,2,5,5,2,5,5,5,2,4,5,5,5,0,0.0,neutral or dissatisfied +92220,73861,Male,Loyal Customer,46,Business travel,Business,1709,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,13.0,satisfied +92221,92383,Female,Loyal Customer,55,Business travel,Business,2139,2,2,2,2,5,5,4,4,4,4,4,5,4,5,27,12.0,satisfied +92222,68967,Male,Loyal Customer,50,Business travel,Eco,700,3,2,2,2,3,3,3,3,2,5,2,1,2,3,34,27.0,neutral or dissatisfied +92223,46519,Male,disloyal Customer,59,Business travel,Eco,125,2,5,2,4,5,2,2,5,2,5,5,1,5,5,35,29.0,neutral or dissatisfied +92224,5545,Female,Loyal Customer,57,Personal Travel,Eco,431,0,5,0,2,2,5,5,5,5,0,5,3,5,5,0,0.0,satisfied +92225,96152,Female,Loyal Customer,58,Business travel,Business,546,5,5,5,5,2,1,1,3,2,4,5,1,5,1,294,288.0,satisfied +92226,30573,Female,Loyal Customer,54,Business travel,Business,628,2,4,4,4,2,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +92227,7794,Female,disloyal Customer,30,Business travel,Business,710,4,5,5,4,5,5,5,5,3,2,4,4,4,5,44,48.0,satisfied +92228,49357,Male,disloyal Customer,44,Business travel,Eco,308,4,4,4,2,4,4,4,4,4,4,1,4,3,4,58,77.0,satisfied +92229,14217,Female,Loyal Customer,21,Personal Travel,Eco,714,3,4,3,1,4,3,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +92230,106879,Male,Loyal Customer,23,Business travel,Business,3150,1,1,4,1,4,5,4,4,3,4,5,4,4,4,0,0.0,satisfied +92231,93787,Male,disloyal Customer,24,Business travel,Eco,1259,2,2,2,3,5,2,5,5,3,3,5,5,5,5,8,0.0,neutral or dissatisfied +92232,68101,Male,Loyal Customer,56,Business travel,Eco,413,3,5,2,5,3,3,3,3,4,4,2,1,2,3,0,0.0,neutral or dissatisfied +92233,18787,Male,Loyal Customer,37,Business travel,Eco,448,4,4,4,4,4,4,4,4,4,5,2,2,5,4,1,0.0,satisfied +92234,127951,Male,Loyal Customer,57,Business travel,Business,1999,3,3,5,3,3,4,5,4,4,4,4,4,4,4,39,43.0,satisfied +92235,54025,Female,Loyal Customer,45,Personal Travel,Eco,1091,4,1,4,3,5,3,4,4,4,4,4,2,4,2,2,0.0,neutral or dissatisfied +92236,84879,Male,Loyal Customer,43,Personal Travel,Eco,547,2,3,2,4,5,2,3,5,4,3,3,4,3,5,0,0.0,neutral or dissatisfied +92237,48344,Female,disloyal Customer,29,Business travel,Eco,522,2,4,2,3,2,2,5,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +92238,103480,Female,Loyal Customer,49,Business travel,Business,3496,1,1,1,1,5,5,5,4,3,4,4,5,3,5,188,242.0,satisfied +92239,108742,Male,disloyal Customer,25,Business travel,Business,581,4,0,4,3,4,4,4,4,3,5,4,3,5,4,17,2.0,satisfied +92240,128017,Male,Loyal Customer,45,Business travel,Business,1440,4,4,4,4,5,4,5,4,4,4,4,5,4,4,83,84.0,satisfied +92241,111075,Male,Loyal Customer,7,Personal Travel,Eco,268,2,5,2,3,5,2,5,5,3,2,4,2,2,5,73,64.0,neutral or dissatisfied +92242,60365,Female,disloyal Customer,34,Business travel,Business,1452,3,3,3,2,4,3,2,4,3,3,5,4,5,4,5,0.0,neutral or dissatisfied +92243,48512,Male,Loyal Customer,42,Business travel,Business,845,3,4,3,3,5,4,5,5,5,5,5,1,5,4,0,0.0,satisfied +92244,125498,Female,Loyal Customer,50,Business travel,Business,2750,2,2,2,2,2,5,4,4,4,4,4,3,4,3,6,0.0,satisfied +92245,17605,Female,Loyal Customer,50,Business travel,Business,3462,1,1,1,1,2,4,4,4,4,4,5,2,4,5,0,0.0,satisfied +92246,17808,Male,Loyal Customer,46,Business travel,Business,1075,1,4,4,4,5,3,3,1,1,1,1,1,1,3,0,6.0,neutral or dissatisfied +92247,126835,Male,disloyal Customer,29,Business travel,Eco,1491,2,2,2,4,1,2,3,1,2,2,3,1,3,1,6,3.0,neutral or dissatisfied +92248,124280,Female,Loyal Customer,46,Business travel,Eco,601,3,4,4,4,2,4,4,3,3,3,3,1,3,3,2,0.0,neutral or dissatisfied +92249,13040,Male,Loyal Customer,15,Personal Travel,Eco,438,3,5,3,1,3,3,3,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +92250,40091,Female,Loyal Customer,40,Business travel,Business,200,1,1,1,1,5,2,2,4,4,4,4,5,4,2,0,0.0,satisfied +92251,7965,Male,Loyal Customer,66,Personal Travel,Eco,594,2,2,2,3,3,2,3,3,3,3,3,1,3,3,0,11.0,neutral or dissatisfied +92252,20157,Female,Loyal Customer,23,Business travel,Business,1553,1,1,2,1,5,5,5,5,5,1,1,1,4,5,13,0.0,satisfied +92253,9723,Male,Loyal Customer,61,Personal Travel,Eco,199,3,5,3,2,5,3,5,5,5,3,5,3,2,5,0,0.0,neutral or dissatisfied +92254,79112,Female,Loyal Customer,36,Personal Travel,Eco,377,4,4,4,4,5,4,2,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +92255,38195,Male,Loyal Customer,58,Personal Travel,Eco,1185,3,4,3,3,2,3,2,2,4,2,3,2,3,2,13,0.0,neutral or dissatisfied +92256,81014,Male,Loyal Customer,42,Business travel,Business,1399,2,2,2,2,2,4,4,4,4,4,4,3,4,5,55,54.0,satisfied +92257,103237,Female,disloyal Customer,20,Business travel,Eco,409,1,1,1,3,4,1,4,4,4,1,3,4,2,4,31,28.0,neutral or dissatisfied +92258,126623,Female,Loyal Customer,22,Business travel,Business,1610,2,2,2,2,2,2,2,2,3,2,5,5,4,2,0,6.0,satisfied +92259,38660,Female,Loyal Customer,45,Business travel,Business,1111,1,1,1,1,3,3,2,5,5,5,5,3,5,4,0,0.0,satisfied +92260,123006,Male,Loyal Customer,60,Business travel,Business,3261,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,9.0,satisfied +92261,108695,Female,Loyal Customer,64,Personal Travel,Eco,577,1,4,1,1,3,5,4,2,2,1,5,4,2,5,34,36.0,neutral or dissatisfied +92262,109727,Female,Loyal Customer,37,Business travel,Eco,468,5,3,3,3,5,5,5,5,1,3,3,3,2,5,17,8.0,satisfied +92263,55097,Female,Loyal Customer,36,Business travel,Business,1009,4,2,2,2,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +92264,99942,Female,Loyal Customer,48,Business travel,Business,1986,3,1,4,1,1,4,3,3,3,3,3,4,3,3,0,1.0,neutral or dissatisfied +92265,46049,Male,Loyal Customer,54,Personal Travel,Eco,991,2,5,1,3,4,1,4,4,5,2,4,4,5,4,6,13.0,neutral or dissatisfied +92266,128087,Female,disloyal Customer,44,Business travel,Eco,995,3,3,3,4,3,3,3,2,5,3,3,3,1,3,34,36.0,neutral or dissatisfied +92267,99227,Female,Loyal Customer,34,Business travel,Business,2570,1,4,5,4,5,4,4,1,1,1,1,4,1,4,6,3.0,neutral or dissatisfied +92268,15440,Female,Loyal Customer,41,Business travel,Eco,164,1,2,2,2,1,1,1,1,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +92269,60962,Female,Loyal Customer,29,Business travel,Business,1721,2,4,4,4,2,3,2,2,1,1,3,2,3,2,56,72.0,neutral or dissatisfied +92270,128683,Male,Loyal Customer,67,Personal Travel,Eco,2419,2,4,2,2,2,4,4,3,4,2,3,4,2,4,52,53.0,neutral or dissatisfied +92271,81981,Female,Loyal Customer,51,Business travel,Eco,1589,2,3,3,3,1,1,2,2,2,2,2,2,2,1,29,39.0,neutral or dissatisfied +92272,12055,Female,Loyal Customer,61,Business travel,Business,376,2,2,1,2,4,4,3,2,2,2,2,2,2,4,69,58.0,neutral or dissatisfied +92273,77028,Male,Loyal Customer,16,Business travel,Eco,422,4,4,4,4,4,5,4,4,2,1,5,5,2,4,0,0.0,satisfied +92274,14501,Male,Loyal Customer,59,Business travel,Eco,328,4,4,4,4,4,4,4,4,3,2,3,2,4,4,0,0.0,neutral or dissatisfied +92275,5539,Female,Loyal Customer,36,Personal Travel,Eco,404,1,5,1,4,4,1,4,4,4,3,4,4,5,4,0,6.0,neutral or dissatisfied +92276,21639,Male,Loyal Customer,10,Personal Travel,Eco,780,2,5,2,2,4,2,3,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +92277,55413,Female,Loyal Customer,67,Personal Travel,Eco,1290,3,5,2,1,3,5,4,5,5,2,5,3,5,3,47,11.0,neutral or dissatisfied +92278,59553,Female,Loyal Customer,53,Business travel,Business,854,5,5,5,5,2,5,4,4,4,4,4,5,4,3,17,0.0,satisfied +92279,54696,Male,disloyal Customer,24,Business travel,Eco,787,3,3,3,3,4,3,4,4,3,4,4,2,3,4,0,7.0,neutral or dissatisfied +92280,86456,Female,Loyal Customer,31,Business travel,Business,1727,1,1,5,1,5,5,5,5,5,5,4,5,4,5,14,3.0,satisfied +92281,108872,Female,Loyal Customer,26,Business travel,Business,1587,5,5,5,5,4,5,4,4,4,4,5,5,4,4,15,4.0,satisfied +92282,68891,Male,Loyal Customer,33,Business travel,Eco,1061,4,4,4,4,4,4,4,4,5,4,4,1,2,4,0,2.0,satisfied +92283,14366,Male,Loyal Customer,65,Personal Travel,Eco,948,3,3,3,3,3,3,2,3,1,3,2,1,2,3,0,0.0,neutral or dissatisfied +92284,50739,Female,Loyal Customer,47,Personal Travel,Eco,86,1,5,1,4,2,3,3,4,4,1,4,1,4,5,112,112.0,neutral or dissatisfied +92285,82828,Female,Loyal Customer,23,Business travel,Business,594,5,5,4,5,3,4,3,3,5,5,4,3,4,3,0,0.0,satisfied +92286,111525,Male,Loyal Customer,42,Business travel,Business,3208,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +92287,70828,Male,Loyal Customer,51,Business travel,Business,761,4,4,4,4,4,5,4,5,5,5,5,5,5,5,125,121.0,satisfied +92288,89259,Female,Loyal Customer,57,Business travel,Business,453,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +92289,16553,Female,Loyal Customer,36,Business travel,Eco,1092,4,2,2,2,4,4,4,4,1,2,3,2,4,4,0,0.0,satisfied +92290,107169,Male,Loyal Customer,58,Business travel,Business,3441,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +92291,67912,Male,Loyal Customer,67,Personal Travel,Eco,1313,2,5,2,3,3,2,3,3,3,5,5,4,5,3,21,13.0,neutral or dissatisfied +92292,6189,Male,Loyal Customer,13,Personal Travel,Eco,475,0,3,0,1,2,0,2,2,2,1,3,5,1,2,0,0.0,satisfied +92293,29462,Male,Loyal Customer,47,Personal Travel,Eco,421,4,5,4,4,4,4,4,4,5,3,4,2,3,4,2,9.0,neutral or dissatisfied +92294,102916,Female,disloyal Customer,37,Business travel,Business,317,2,2,2,4,2,2,2,2,3,4,5,5,4,2,1,0.0,satisfied +92295,123080,Male,Loyal Customer,60,Business travel,Business,600,3,3,3,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +92296,28230,Female,Loyal Customer,36,Business travel,Business,1009,3,4,3,3,2,4,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +92297,56253,Female,Loyal Customer,57,Business travel,Business,2664,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +92298,58769,Female,disloyal Customer,23,Business travel,Eco,1012,3,3,3,4,1,3,1,1,4,3,4,4,4,1,0,3.0,neutral or dissatisfied +92299,37809,Male,Loyal Customer,25,Personal Travel,Eco Plus,944,3,5,3,4,3,3,3,3,4,2,2,1,5,3,2,1.0,neutral or dissatisfied +92300,10333,Female,Loyal Customer,43,Business travel,Business,3824,5,5,5,5,5,4,4,4,4,5,4,3,4,4,1,0.0,satisfied +92301,78332,Male,disloyal Customer,30,Business travel,Business,1547,5,5,5,4,4,5,4,4,5,5,5,5,5,4,0,0.0,satisfied +92302,67359,Male,Loyal Customer,54,Business travel,Business,3590,3,3,3,3,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +92303,66805,Female,Loyal Customer,70,Personal Travel,Business,731,2,2,3,4,4,4,4,1,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +92304,23796,Male,Loyal Customer,40,Business travel,Eco,438,2,4,4,4,2,3,2,2,4,3,1,5,1,2,0,0.0,satisfied +92305,128174,Male,disloyal Customer,65,Business travel,Business,349,3,3,3,3,2,3,2,2,3,2,4,3,4,2,3,0.0,neutral or dissatisfied +92306,91130,Male,Loyal Customer,68,Personal Travel,Eco,366,3,5,3,5,4,3,4,4,3,5,5,1,2,4,0,0.0,neutral or dissatisfied +92307,12761,Male,Loyal Customer,7,Personal Travel,Eco,689,2,4,2,3,1,2,1,1,3,2,4,4,4,1,2,0.0,neutral or dissatisfied +92308,42494,Male,Loyal Customer,55,Business travel,Eco Plus,693,1,1,1,1,1,1,1,3,1,3,3,1,4,1,259,248.0,neutral or dissatisfied +92309,128722,Male,Loyal Customer,36,Personal Travel,Eco,1464,5,1,5,3,1,5,1,1,1,3,2,4,3,1,0,0.0,satisfied +92310,108766,Female,disloyal Customer,21,Business travel,Eco,404,5,4,5,2,4,5,4,4,4,5,4,3,5,4,32,33.0,satisfied +92311,109201,Female,Loyal Customer,28,Business travel,Eco,612,3,3,4,3,3,3,3,3,1,5,4,2,4,3,17,11.0,neutral or dissatisfied +92312,86497,Female,Loyal Customer,29,Personal Travel,Eco,762,1,4,1,3,3,1,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +92313,101860,Female,Loyal Customer,65,Personal Travel,Eco,519,4,5,4,2,4,5,5,2,2,4,2,4,2,3,0,0.0,satisfied +92314,25248,Female,Loyal Customer,47,Business travel,Eco Plus,787,5,2,3,2,5,3,2,5,5,5,5,4,5,4,0,0.0,satisfied +92315,30235,Female,Loyal Customer,43,Business travel,Eco,826,3,2,2,2,2,2,2,3,3,3,3,1,3,4,12,30.0,neutral or dissatisfied +92316,99723,Female,disloyal Customer,23,Business travel,Business,255,0,3,0,3,5,0,5,5,4,2,4,5,4,5,4,6.0,satisfied +92317,115600,Female,Loyal Customer,24,Business travel,Business,2956,2,2,3,2,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +92318,7861,Male,Loyal Customer,36,Business travel,Business,1693,2,2,3,2,2,5,5,4,4,4,4,4,4,5,0,16.0,satisfied +92319,84128,Female,Loyal Customer,38,Business travel,Business,1569,2,5,5,5,5,3,4,2,2,3,2,2,2,2,0,2.0,neutral or dissatisfied +92320,108603,Female,Loyal Customer,45,Business travel,Business,696,2,2,2,2,1,4,4,2,2,2,2,3,2,1,44,30.0,neutral or dissatisfied +92321,108385,Female,Loyal Customer,57,Personal Travel,Eco,1855,3,4,3,3,1,3,3,5,5,3,5,4,5,2,51,61.0,neutral or dissatisfied +92322,120623,Male,disloyal Customer,61,Business travel,Business,280,1,0,0,3,1,3,3,4,4,5,4,3,3,3,147,136.0,neutral or dissatisfied +92323,5767,Female,Loyal Customer,55,Business travel,Business,1997,1,1,1,1,4,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +92324,49577,Female,Loyal Customer,60,Business travel,Business,308,2,2,2,2,3,3,5,5,5,5,5,2,5,2,8,16.0,satisfied +92325,103988,Female,Loyal Customer,38,Business travel,Business,1363,3,3,3,3,3,5,5,5,5,5,5,4,5,3,14,8.0,satisfied +92326,29542,Male,Loyal Customer,48,Business travel,Business,1448,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +92327,90047,Female,Loyal Customer,34,Business travel,Business,2417,2,2,2,2,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +92328,13916,Male,Loyal Customer,34,Business travel,Business,2682,3,3,3,3,2,3,5,5,5,5,5,1,5,3,68,63.0,satisfied +92329,101101,Male,Loyal Customer,46,Business travel,Business,2082,5,5,4,5,4,4,5,4,4,4,4,5,4,3,14,4.0,satisfied +92330,80557,Male,Loyal Customer,58,Business travel,Business,1747,1,1,2,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +92331,124203,Female,Loyal Customer,22,Business travel,Business,2176,2,4,3,3,2,2,2,2,2,1,3,2,4,2,18,4.0,neutral or dissatisfied +92332,44005,Male,Loyal Customer,37,Business travel,Business,2869,3,3,3,3,3,2,3,5,5,5,5,1,5,1,2,0.0,satisfied +92333,50855,Male,Loyal Customer,31,Personal Travel,Eco,373,2,3,2,5,4,2,4,4,1,2,1,4,2,4,0,33.0,neutral or dissatisfied +92334,110709,Female,Loyal Customer,35,Business travel,Business,2728,1,1,1,1,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +92335,119485,Female,disloyal Customer,36,Business travel,Business,759,4,4,4,2,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +92336,121353,Female,Loyal Customer,36,Personal Travel,Eco,430,4,4,4,2,2,4,1,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +92337,115631,Male,Loyal Customer,64,Business travel,Business,3656,3,4,4,4,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +92338,113905,Male,disloyal Customer,20,Business travel,Eco,2295,2,2,2,3,4,2,2,4,1,1,4,1,4,4,3,0.0,neutral or dissatisfied +92339,63478,Male,Loyal Customer,11,Personal Travel,Eco Plus,337,1,4,1,1,5,1,5,5,3,5,4,5,4,5,23,23.0,neutral or dissatisfied +92340,70042,Male,Loyal Customer,22,Personal Travel,Eco,583,4,4,4,3,4,4,2,4,5,2,4,4,4,4,0,0.0,satisfied +92341,57578,Male,Loyal Customer,40,Business travel,Business,1597,2,2,2,2,3,4,5,4,4,4,4,3,4,4,6,0.0,satisfied +92342,95985,Male,Loyal Customer,66,Business travel,Business,2558,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +92343,87370,Male,Loyal Customer,43,Business travel,Business,2503,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,5.0,satisfied +92344,114772,Female,Loyal Customer,64,Business travel,Business,3961,1,1,4,1,3,4,5,4,4,5,4,3,4,3,23,18.0,satisfied +92345,67011,Male,disloyal Customer,24,Business travel,Eco,1121,4,4,4,2,5,4,5,5,5,3,4,3,4,5,0,0.0,satisfied +92346,1107,Female,Loyal Customer,24,Personal Travel,Eco,164,3,4,3,4,3,4,4,5,2,4,5,4,3,4,423,417.0,neutral or dissatisfied +92347,56538,Male,disloyal Customer,11,Business travel,Eco,937,1,1,1,1,2,1,2,2,3,2,5,3,4,2,17,14.0,neutral or dissatisfied +92348,7260,Female,Loyal Customer,55,Personal Travel,Eco,135,2,1,2,4,5,4,3,1,1,2,1,2,1,4,0,2.0,neutral or dissatisfied +92349,84164,Male,Loyal Customer,43,Business travel,Eco Plus,503,1,3,3,3,1,1,1,1,4,5,3,1,3,1,0,26.0,neutral or dissatisfied +92350,98759,Female,Loyal Customer,12,Business travel,Business,1814,2,3,3,3,2,2,2,2,1,5,4,1,4,2,25,12.0,neutral or dissatisfied +92351,53771,Male,Loyal Customer,47,Personal Travel,Eco,1195,3,4,3,2,4,3,4,4,3,2,5,5,5,4,76,61.0,neutral or dissatisfied +92352,83589,Male,Loyal Customer,64,Business travel,Business,1583,4,4,4,4,3,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +92353,105309,Male,Loyal Customer,58,Personal Travel,Eco,738,4,4,4,4,2,4,3,2,3,4,5,4,5,2,31,27.0,neutral or dissatisfied +92354,108969,Female,Loyal Customer,51,Business travel,Business,667,4,4,4,4,4,5,4,5,5,5,5,4,5,3,9,1.0,satisfied +92355,93628,Male,Loyal Customer,24,Personal Travel,Eco,577,2,3,1,4,5,1,5,5,4,4,3,1,4,5,0,4.0,neutral or dissatisfied +92356,55719,Female,Loyal Customer,28,Business travel,Eco Plus,1025,3,4,4,4,3,3,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +92357,82125,Female,disloyal Customer,18,Business travel,Eco,2519,2,2,2,4,5,2,5,5,1,5,3,4,4,5,3,0.0,neutral or dissatisfied +92358,33471,Female,Loyal Customer,26,Business travel,Business,2917,5,5,5,5,5,5,5,3,3,5,5,5,2,5,0,5.0,satisfied +92359,33197,Male,Loyal Customer,39,Business travel,Eco Plus,163,4,1,1,1,4,4,4,4,4,3,2,4,1,4,0,0.0,satisfied +92360,89595,Male,disloyal Customer,25,Business travel,Eco,1076,2,3,3,1,1,3,1,1,5,3,5,3,5,1,34,47.0,satisfied +92361,108360,Male,Loyal Customer,64,Business travel,Business,3949,5,5,5,5,3,4,1,4,4,4,4,2,4,1,0,0.0,satisfied +92362,89456,Female,Loyal Customer,56,Personal Travel,Eco,134,4,0,0,4,5,3,5,4,4,0,4,5,4,1,67,56.0,neutral or dissatisfied +92363,114029,Female,Loyal Customer,44,Personal Travel,Eco Plus,1728,4,5,4,1,3,4,4,3,3,4,2,3,3,3,0,26.0,neutral or dissatisfied +92364,121908,Male,Loyal Customer,32,Personal Travel,Eco,337,2,2,2,3,3,2,1,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +92365,104003,Female,disloyal Customer,23,Business travel,Eco,934,2,2,2,3,2,2,2,2,1,2,4,4,5,2,0,0.0,neutral or dissatisfied +92366,45785,Male,disloyal Customer,41,Business travel,Eco,391,3,5,3,2,4,3,2,4,2,4,2,4,1,4,0,0.0,neutral or dissatisfied +92367,21215,Male,Loyal Customer,53,Business travel,Business,1612,0,0,0,1,1,1,2,3,3,3,3,5,3,2,0,0.0,satisfied +92368,91399,Female,Loyal Customer,23,Personal Travel,Eco,2342,3,5,3,4,1,3,1,1,1,1,4,3,1,1,0,0.0,neutral or dissatisfied +92369,44286,Male,Loyal Customer,56,Business travel,Business,1015,1,1,1,1,2,3,4,1,1,2,1,1,1,4,7,0.0,neutral or dissatisfied +92370,26588,Female,disloyal Customer,38,Business travel,Eco,404,2,4,2,1,2,2,2,2,5,2,2,4,1,2,1,3.0,neutral or dissatisfied +92371,64109,Female,Loyal Customer,46,Business travel,Business,2288,5,5,3,5,3,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +92372,71027,Female,disloyal Customer,30,Business travel,Eco,802,3,3,3,3,3,4,4,4,5,4,3,4,4,4,146,137.0,neutral or dissatisfied +92373,85152,Female,Loyal Customer,25,Business travel,Eco,731,1,2,2,2,1,1,2,1,2,1,3,1,4,1,12,18.0,neutral or dissatisfied +92374,68409,Male,Loyal Customer,53,Business travel,Eco,1045,3,2,2,2,3,3,3,3,2,5,3,2,3,3,0,0.0,neutral or dissatisfied +92375,37530,Female,Loyal Customer,25,Business travel,Business,1028,3,1,1,1,3,3,3,3,1,1,4,3,4,3,3,5.0,neutral or dissatisfied +92376,86777,Female,Loyal Customer,47,Business travel,Business,3862,4,2,2,2,3,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +92377,55888,Male,Loyal Customer,26,Business travel,Business,723,5,5,5,5,5,5,5,5,3,4,4,5,5,5,0,1.0,satisfied +92378,52531,Male,disloyal Customer,44,Business travel,Eco,119,1,0,1,4,4,1,4,4,3,4,2,5,1,4,0,0.0,neutral or dissatisfied +92379,35136,Female,disloyal Customer,19,Business travel,Eco,1076,4,4,4,3,4,4,4,4,3,5,5,5,4,4,6,30.0,satisfied +92380,108958,Male,disloyal Customer,30,Business travel,Business,667,2,2,2,3,1,2,1,1,4,3,4,5,4,1,3,0.0,neutral or dissatisfied +92381,1439,Female,Loyal Customer,31,Business travel,Business,772,4,4,4,4,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +92382,73664,Male,Loyal Customer,67,Business travel,Business,3583,3,3,3,3,3,5,4,5,5,5,5,3,5,4,26,15.0,satisfied +92383,127161,Female,Loyal Customer,30,Personal Travel,Eco,338,2,2,2,4,2,2,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +92384,118451,Female,disloyal Customer,34,Business travel,Business,370,2,2,2,1,4,2,3,4,5,5,5,4,4,4,48,44.0,neutral or dissatisfied +92385,66116,Female,disloyal Customer,24,Business travel,Eco,583,1,4,1,3,4,1,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +92386,88951,Male,disloyal Customer,22,Business travel,Eco,1199,3,3,3,4,4,3,4,4,1,4,3,3,3,4,3,0.0,neutral or dissatisfied +92387,62566,Male,Loyal Customer,8,Business travel,Business,1744,3,1,2,1,3,3,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +92388,79294,Female,Loyal Customer,42,Business travel,Business,2248,3,3,3,3,2,3,5,5,5,4,5,3,5,4,0,0.0,satisfied +92389,93279,Male,Loyal Customer,34,Personal Travel,Eco,867,2,5,2,3,3,2,3,3,4,2,4,3,4,3,1,0.0,neutral or dissatisfied +92390,3652,Male,disloyal Customer,23,Business travel,Eco,431,5,0,5,5,1,5,1,1,5,2,5,4,4,1,0,0.0,satisfied +92391,98993,Male,Loyal Customer,42,Personal Travel,Eco,479,1,2,3,3,4,3,4,4,1,2,3,4,2,4,46,39.0,neutral or dissatisfied +92392,43297,Female,Loyal Customer,60,Business travel,Eco,402,3,4,4,4,3,3,2,3,3,3,3,1,3,4,0,0.0,satisfied +92393,45110,Female,Loyal Customer,35,Business travel,Eco,157,3,4,4,4,3,3,3,1,5,3,2,3,3,3,131,131.0,neutral or dissatisfied +92394,117623,Male,Loyal Customer,65,Personal Travel,Eco,347,1,5,1,3,3,1,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +92395,22457,Male,Loyal Customer,56,Personal Travel,Eco,145,2,4,2,5,4,2,4,4,3,5,2,4,5,4,0,0.0,neutral or dissatisfied +92396,46525,Male,Loyal Customer,45,Business travel,Business,1733,3,3,3,3,1,2,2,5,5,5,3,3,5,3,81,97.0,satisfied +92397,84839,Male,Loyal Customer,55,Business travel,Eco,547,2,5,1,5,2,2,2,2,1,1,4,1,4,2,12,1.0,neutral or dissatisfied +92398,115102,Male,Loyal Customer,50,Business travel,Business,3616,3,3,3,3,3,4,5,4,4,4,4,3,4,5,1,0.0,satisfied +92399,23668,Male,disloyal Customer,24,Business travel,Eco,212,3,1,3,4,2,3,2,2,4,2,4,3,4,2,0,8.0,neutral or dissatisfied +92400,71418,Male,Loyal Customer,49,Business travel,Business,867,5,5,5,5,2,4,4,4,4,4,4,4,4,3,5,5.0,satisfied +92401,43101,Male,Loyal Customer,31,Personal Travel,Eco,391,3,5,3,1,1,3,1,1,5,4,4,5,5,1,0,0.0,neutral or dissatisfied +92402,101782,Female,Loyal Customer,40,Business travel,Business,1521,2,5,5,5,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +92403,71884,Female,Loyal Customer,16,Personal Travel,Eco,1744,2,3,2,3,4,2,4,4,2,5,1,5,3,4,0,13.0,neutral or dissatisfied +92404,28522,Male,Loyal Customer,58,Business travel,Business,2640,3,3,3,3,5,5,3,5,5,5,5,3,5,5,0,0.0,satisfied +92405,88148,Female,Loyal Customer,45,Business travel,Business,594,3,1,1,1,3,3,4,3,3,3,3,4,3,1,0,6.0,neutral or dissatisfied +92406,36199,Female,Loyal Customer,32,Business travel,Business,2765,3,3,3,3,5,5,5,5,3,2,4,2,4,5,4,0.0,satisfied +92407,121018,Male,Loyal Customer,54,Personal Travel,Eco,920,2,5,2,1,3,2,3,3,4,2,4,3,4,3,2,1.0,neutral or dissatisfied +92408,69119,Male,disloyal Customer,39,Business travel,Eco,1045,2,2,2,2,2,2,2,2,2,4,1,4,2,2,61,48.0,neutral or dissatisfied +92409,53788,Male,disloyal Customer,48,Business travel,Eco,191,2,0,2,5,5,2,4,5,4,2,4,1,1,5,0,0.0,neutral or dissatisfied +92410,66334,Male,Loyal Customer,54,Business travel,Business,986,1,2,1,1,4,4,4,3,3,3,3,5,3,5,22,31.0,satisfied +92411,10351,Male,Loyal Customer,58,Business travel,Business,201,4,3,4,4,2,4,4,4,4,4,5,5,4,4,17,17.0,satisfied +92412,66549,Male,Loyal Customer,63,Business travel,Business,1533,3,3,3,3,4,4,3,3,3,3,3,3,3,1,20,16.0,neutral or dissatisfied +92413,10035,Male,Loyal Customer,22,Business travel,Business,2686,2,2,2,2,5,5,5,5,4,3,1,1,5,5,0,0.0,satisfied +92414,104005,Female,Loyal Customer,62,Personal Travel,Eco,1592,3,5,4,2,5,3,4,2,2,4,4,5,2,4,15,12.0,neutral or dissatisfied +92415,91077,Female,Loyal Customer,67,Personal Travel,Eco,406,2,4,2,3,5,4,5,5,5,2,5,4,5,5,0,1.0,neutral or dissatisfied +92416,38314,Male,Loyal Customer,25,Business travel,Business,1666,5,5,5,5,4,4,4,4,3,4,2,4,4,4,126,132.0,satisfied +92417,112041,Female,Loyal Customer,41,Business travel,Business,3048,3,3,3,3,2,5,5,5,5,5,5,5,5,3,8,0.0,satisfied +92418,60922,Female,Loyal Customer,23,Business travel,Business,888,1,1,1,1,2,2,2,2,4,2,5,4,4,2,12,0.0,satisfied +92419,63423,Female,Loyal Customer,42,Personal Travel,Eco,447,1,4,2,2,4,5,4,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +92420,127725,Male,Loyal Customer,43,Business travel,Business,2154,4,4,1,4,2,5,5,5,5,4,5,4,5,4,15,11.0,satisfied +92421,43060,Female,Loyal Customer,69,Business travel,Business,2885,5,5,5,5,4,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +92422,63659,Female,Loyal Customer,27,Business travel,Business,2405,4,2,4,4,4,5,4,4,4,4,3,5,4,4,13,0.0,satisfied +92423,29902,Male,disloyal Customer,57,Business travel,Eco,261,3,0,3,1,1,3,1,1,2,3,3,5,3,1,0,0.0,neutral or dissatisfied +92424,89606,Male,Loyal Customer,46,Business travel,Business,2691,2,2,2,2,4,4,4,5,5,5,5,4,5,3,57,32.0,satisfied +92425,67291,Male,Loyal Customer,52,Business travel,Business,1121,5,5,3,5,3,5,4,4,4,4,4,5,4,4,14,54.0,satisfied +92426,42318,Male,Loyal Customer,68,Personal Travel,Eco,834,2,4,2,1,3,2,3,3,3,3,5,3,5,3,0,21.0,neutral or dissatisfied +92427,38237,Male,disloyal Customer,22,Business travel,Business,1133,5,0,5,2,3,5,3,3,1,1,1,4,4,3,0,0.0,satisfied +92428,100428,Female,disloyal Customer,36,Business travel,Business,1620,1,1,1,2,2,1,2,2,3,4,4,4,5,2,63,61.0,neutral or dissatisfied +92429,120396,Female,disloyal Customer,32,Business travel,Eco,449,3,3,3,3,1,3,2,1,4,2,3,3,4,1,30,44.0,neutral or dissatisfied +92430,121494,Female,Loyal Customer,23,Business travel,Business,3888,1,1,1,1,5,5,5,5,4,4,4,4,5,5,0,0.0,satisfied +92431,25594,Female,Loyal Customer,21,Personal Travel,Eco,874,3,4,3,2,2,3,2,2,3,2,5,5,1,2,0,0.0,neutral or dissatisfied +92432,66136,Female,Loyal Customer,26,Personal Travel,Eco,583,3,5,3,4,2,3,1,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +92433,125255,Male,Loyal Customer,14,Personal Travel,Eco,427,3,4,3,1,2,3,2,2,5,2,5,2,4,2,32,70.0,neutral or dissatisfied +92434,9456,Male,Loyal Customer,36,Personal Travel,Eco,362,2,4,2,3,3,2,3,3,3,5,4,3,5,3,0,16.0,neutral or dissatisfied +92435,42310,Female,Loyal Customer,52,Personal Travel,Eco,451,3,3,5,2,5,1,3,2,2,5,2,3,2,5,26,19.0,neutral or dissatisfied +92436,76910,Female,Loyal Customer,48,Business travel,Business,3114,5,5,5,5,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +92437,102891,Female,Loyal Customer,7,Business travel,Business,2856,1,2,2,2,1,1,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +92438,26242,Male,Loyal Customer,10,Personal Travel,Eco,270,2,4,0,3,2,0,3,2,4,5,4,3,4,2,42,36.0,neutral or dissatisfied +92439,123039,Male,Loyal Customer,53,Business travel,Business,2620,1,1,1,1,1,4,4,1,1,1,1,4,1,1,0,6.0,neutral or dissatisfied +92440,53869,Female,Loyal Customer,38,Business travel,Eco,140,5,2,2,2,5,5,5,5,1,2,5,5,2,5,120,122.0,satisfied +92441,121122,Female,Loyal Customer,46,Business travel,Business,2370,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +92442,87593,Male,Loyal Customer,28,Personal Travel,Eco,432,4,1,4,2,4,4,4,4,2,5,2,3,2,4,0,0.0,satisfied +92443,12088,Male,Loyal Customer,50,Business travel,Business,1034,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +92444,110177,Male,Loyal Customer,35,Personal Travel,Eco,1072,2,4,2,3,3,2,4,3,3,2,5,5,4,3,29,18.0,neutral or dissatisfied +92445,42570,Male,Loyal Customer,39,Business travel,Business,3262,3,3,2,3,5,5,5,5,5,5,5,2,5,5,0,0.0,satisfied +92446,110057,Female,Loyal Customer,51,Personal Travel,Eco,2039,2,5,2,1,3,4,4,1,1,2,1,5,1,3,49,48.0,neutral or dissatisfied +92447,19439,Male,Loyal Customer,50,Business travel,Eco Plus,645,4,2,2,2,4,4,4,4,3,1,1,4,4,4,112,96.0,satisfied +92448,5519,Female,Loyal Customer,38,Business travel,Business,3522,3,5,3,3,5,5,4,3,3,4,3,4,3,5,5,15.0,satisfied +92449,18254,Male,Loyal Customer,15,Personal Travel,Eco,179,2,3,2,2,5,2,5,5,3,1,2,3,3,5,0,0.0,neutral or dissatisfied +92450,114380,Male,Loyal Customer,51,Personal Travel,Eco Plus,850,1,5,1,1,3,1,1,3,4,2,5,3,4,3,5,0.0,neutral or dissatisfied +92451,48095,Male,Loyal Customer,27,Business travel,Business,173,3,3,3,3,5,5,4,5,4,2,4,1,2,5,0,0.0,satisfied +92452,127844,Female,Loyal Customer,35,Business travel,Business,2044,2,5,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +92453,24733,Female,Loyal Customer,40,Business travel,Business,2813,5,5,5,5,5,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +92454,43540,Female,Loyal Customer,64,Personal Travel,Eco,643,2,4,2,1,2,4,5,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +92455,76229,Female,disloyal Customer,25,Business travel,Eco,1399,2,2,2,4,4,2,4,4,3,2,3,1,3,4,29,17.0,neutral or dissatisfied +92456,98727,Male,Loyal Customer,27,Business travel,Business,1558,4,4,4,4,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +92457,47441,Male,disloyal Customer,24,Business travel,Eco,199,1,0,1,2,2,1,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +92458,45353,Male,Loyal Customer,9,Personal Travel,Eco,150,2,1,0,3,4,0,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +92459,19246,Male,Loyal Customer,22,Personal Travel,Eco,782,3,5,3,1,3,3,5,3,4,2,4,5,4,3,18,19.0,neutral or dissatisfied +92460,121341,Male,Loyal Customer,80,Business travel,Business,3613,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +92461,118356,Female,Loyal Customer,32,Personal Travel,Eco,602,2,5,2,1,2,2,2,2,4,2,4,5,4,2,56,71.0,neutral or dissatisfied +92462,117150,Female,Loyal Customer,36,Personal Travel,Eco,621,3,4,3,3,4,3,2,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +92463,27826,Female,disloyal Customer,24,Business travel,Eco,680,4,4,4,1,3,4,3,3,4,1,4,1,3,3,0,0.0,satisfied +92464,18746,Female,disloyal Customer,28,Business travel,Eco,1167,2,2,2,4,2,2,2,2,2,4,1,2,3,2,0,0.0,neutral or dissatisfied +92465,80852,Male,Loyal Customer,36,Business travel,Eco,292,1,4,2,4,1,1,1,1,4,5,3,2,4,1,0,0.0,neutral or dissatisfied +92466,115953,Male,Loyal Customer,40,Personal Travel,Eco,446,3,5,3,3,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +92467,9025,Male,Loyal Customer,40,Business travel,Eco,160,2,3,3,3,2,2,2,2,2,3,4,1,3,2,0,0.0,neutral or dissatisfied +92468,82446,Male,Loyal Customer,28,Business travel,Business,3240,2,4,5,5,2,2,2,2,4,4,3,3,3,2,19,28.0,neutral or dissatisfied +92469,100927,Female,Loyal Customer,64,Personal Travel,Eco,838,4,4,4,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +92470,59154,Female,Loyal Customer,55,Business travel,Business,1846,1,1,1,1,2,3,4,4,4,5,4,3,4,3,13,0.0,satisfied +92471,127417,Female,Loyal Customer,12,Personal Travel,Eco,1009,2,4,2,5,5,2,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +92472,75903,Male,disloyal Customer,20,Business travel,Eco,203,3,2,3,4,4,3,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +92473,29032,Female,Loyal Customer,36,Business travel,Eco,556,2,3,3,3,2,2,2,2,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +92474,67462,Female,Loyal Customer,67,Personal Travel,Eco,592,3,3,3,4,1,3,3,2,2,3,2,2,2,1,63,55.0,neutral or dissatisfied +92475,37066,Female,disloyal Customer,25,Business travel,Eco,1188,2,2,2,3,4,2,4,4,4,1,4,2,4,4,38,21.0,neutral or dissatisfied +92476,63358,Male,Loyal Customer,41,Personal Travel,Eco,447,3,5,3,3,1,3,1,1,4,4,5,5,5,1,70,54.0,neutral or dissatisfied +92477,36804,Female,disloyal Customer,10,Business travel,Eco Plus,2588,1,0,1,1,1,5,5,2,4,4,2,5,2,5,0,0.0,neutral or dissatisfied +92478,14071,Female,Loyal Customer,55,Business travel,Eco,371,5,1,1,1,2,1,5,5,5,5,5,5,5,5,14,5.0,satisfied +92479,53445,Female,Loyal Customer,53,Business travel,Eco,2288,5,2,2,2,3,5,2,5,5,5,5,4,5,1,0,24.0,satisfied +92480,18989,Male,Loyal Customer,35,Business travel,Business,451,4,1,1,1,2,3,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +92481,20860,Female,Loyal Customer,55,Personal Travel,Eco,457,0,4,0,1,5,5,5,3,3,0,3,3,3,5,0,0.0,satisfied +92482,68152,Female,Loyal Customer,52,Business travel,Business,603,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +92483,111981,Female,Loyal Customer,27,Personal Travel,Eco,770,2,4,2,4,3,2,3,3,3,3,4,5,5,3,60,42.0,neutral or dissatisfied +92484,3534,Male,Loyal Customer,61,Personal Travel,Eco,557,1,5,1,3,5,1,4,5,1,4,1,3,1,5,0,21.0,neutral or dissatisfied +92485,112172,Male,Loyal Customer,45,Personal Travel,Eco,895,2,4,2,2,1,2,1,1,3,3,5,4,4,1,0,2.0,neutral or dissatisfied +92486,41499,Male,Loyal Customer,24,Business travel,Eco,1242,0,5,0,4,5,0,5,5,4,2,2,4,4,5,92,87.0,satisfied +92487,108888,Male,disloyal Customer,25,Business travel,Eco,1066,4,3,3,2,4,3,4,4,3,4,4,3,4,4,16,2.0,satisfied +92488,9646,Female,Loyal Customer,52,Business travel,Business,3354,5,5,5,5,2,4,4,4,4,4,4,4,4,3,10,0.0,satisfied +92489,65469,Male,Loyal Customer,27,Business travel,Business,2238,4,1,1,1,4,4,4,4,4,2,3,3,2,4,98,83.0,neutral or dissatisfied +92490,20128,Female,Loyal Customer,14,Personal Travel,Eco,416,1,5,2,2,3,2,3,3,3,2,1,4,1,3,50,40.0,neutral or dissatisfied +92491,94489,Male,disloyal Customer,20,Business travel,Eco,239,2,1,2,3,3,2,3,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +92492,76155,Male,Loyal Customer,29,Business travel,Business,2208,2,3,3,3,2,2,2,2,2,2,3,2,3,2,0,10.0,neutral or dissatisfied +92493,106528,Female,Loyal Customer,7,Personal Travel,Eco,271,3,2,3,3,4,3,4,4,3,2,3,2,3,4,6,0.0,neutral or dissatisfied +92494,51130,Male,Loyal Customer,44,Personal Travel,Eco,109,3,4,3,4,3,3,3,3,3,3,4,2,5,3,0,5.0,neutral or dissatisfied +92495,17995,Male,Loyal Customer,67,Business travel,Business,1650,3,4,4,4,5,1,1,3,3,2,3,4,3,3,47,38.0,neutral or dissatisfied +92496,59632,Female,Loyal Customer,25,Business travel,Business,1805,3,2,2,2,3,3,3,3,1,1,3,2,3,3,3,7.0,neutral or dissatisfied +92497,74829,Female,Loyal Customer,54,Business travel,Business,1171,3,3,3,3,5,5,4,3,3,4,3,5,3,4,0,10.0,satisfied +92498,82911,Male,Loyal Customer,62,Personal Travel,Eco,640,2,5,2,3,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +92499,103068,Male,disloyal Customer,23,Business travel,Eco,460,1,1,1,3,2,1,4,2,4,4,3,2,4,2,9,0.0,neutral or dissatisfied +92500,51941,Female,disloyal Customer,19,Business travel,Eco,936,3,3,3,2,5,3,5,5,2,1,5,2,5,5,0,0.0,neutral or dissatisfied +92501,40705,Female,Loyal Customer,31,Business travel,Business,588,2,2,2,2,5,5,5,5,2,2,5,5,1,5,0,0.0,satisfied +92502,13412,Female,Loyal Customer,28,Business travel,Business,3952,1,1,1,1,4,4,4,4,4,1,3,3,5,4,0,0.0,satisfied +92503,77329,Male,Loyal Customer,51,Business travel,Business,1626,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +92504,57645,Male,Loyal Customer,56,Business travel,Business,1848,4,4,4,4,4,2,5,4,4,4,4,3,4,1,0,0.0,satisfied +92505,3784,Female,Loyal Customer,50,Business travel,Business,2340,2,2,2,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +92506,18411,Female,Loyal Customer,54,Personal Travel,Eco,284,2,5,2,5,3,5,3,4,4,2,4,4,4,1,44,44.0,neutral or dissatisfied +92507,20042,Female,disloyal Customer,22,Business travel,Business,607,4,3,4,4,4,4,4,4,3,2,4,1,3,4,90,94.0,neutral or dissatisfied +92508,124101,Female,Loyal Customer,24,Business travel,Business,2657,2,2,2,2,4,4,4,4,3,3,5,3,4,4,0,14.0,satisfied +92509,49694,Male,Loyal Customer,36,Business travel,Business,3516,4,4,4,4,2,4,1,5,5,4,5,3,5,1,0,0.0,satisfied +92510,43215,Female,Loyal Customer,57,Business travel,Eco,423,5,3,3,3,4,1,2,5,5,5,5,3,5,5,0,0.0,satisfied +92511,5170,Female,disloyal Customer,21,Business travel,Eco,351,3,0,3,1,5,3,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +92512,109544,Male,Loyal Customer,23,Personal Travel,Eco,951,1,3,1,3,4,1,4,4,2,5,4,2,4,4,1,0.0,neutral or dissatisfied +92513,67328,Female,Loyal Customer,45,Business travel,Business,1471,2,4,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +92514,42702,Male,Loyal Customer,42,Personal Travel,Eco,604,1,1,1,3,4,1,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +92515,86317,Female,Loyal Customer,39,Personal Travel,Eco Plus,306,5,4,5,2,3,5,3,3,4,5,4,4,4,3,0,0.0,satisfied +92516,3143,Male,Loyal Customer,36,Business travel,Business,140,1,5,5,5,4,3,4,4,4,4,1,4,4,3,0,0.0,neutral or dissatisfied +92517,99230,Female,Loyal Customer,44,Business travel,Business,2203,4,4,4,4,3,4,5,5,5,5,5,4,5,4,38,36.0,satisfied +92518,5775,Male,Loyal Customer,57,Business travel,Business,2377,5,5,5,5,2,4,5,5,5,5,5,3,5,4,16,35.0,satisfied +92519,115191,Female,disloyal Customer,39,Business travel,Business,446,2,2,2,5,3,2,3,3,4,3,4,3,5,3,2,0.0,neutral or dissatisfied +92520,18382,Female,Loyal Customer,44,Business travel,Business,493,2,2,5,2,5,5,5,4,2,5,5,5,5,5,100,132.0,satisfied +92521,110941,Male,Loyal Customer,54,Personal Travel,Eco,404,2,4,2,4,3,2,3,3,5,3,4,5,5,3,7,0.0,neutral or dissatisfied +92522,55462,Female,Loyal Customer,19,Personal Travel,Business,1825,4,4,4,4,5,4,5,5,4,4,3,5,4,5,0,0.0,neutral or dissatisfied +92523,39550,Female,Loyal Customer,52,Business travel,Eco,954,2,5,5,5,1,5,2,2,2,2,2,5,2,4,0,0.0,satisfied +92524,75799,Male,Loyal Customer,48,Personal Travel,Eco,813,3,0,3,4,1,3,1,1,5,4,2,4,3,1,0,0.0,neutral or dissatisfied +92525,86075,Male,Loyal Customer,37,Personal Travel,Eco Plus,447,2,5,4,3,4,4,2,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +92526,123056,Female,Loyal Customer,33,Business travel,Business,650,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +92527,47664,Female,disloyal Customer,8,Business travel,Eco,1155,1,1,1,4,3,1,3,3,1,4,4,5,4,3,0,0.0,neutral or dissatisfied +92528,12008,Male,Loyal Customer,46,Business travel,Business,3060,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +92529,57377,Male,disloyal Customer,35,Business travel,Eco Plus,414,1,2,2,3,1,2,1,1,2,4,3,3,2,1,13,11.0,neutral or dissatisfied +92530,28290,Male,disloyal Customer,24,Business travel,Eco,467,1,4,1,4,2,1,2,2,4,1,3,1,4,2,0,1.0,neutral or dissatisfied +92531,96856,Female,Loyal Customer,33,Business travel,Business,3070,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +92532,62293,Male,Loyal Customer,35,Business travel,Business,414,3,3,3,3,2,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +92533,80226,Male,Loyal Customer,28,Personal Travel,Eco,2153,3,4,3,4,1,3,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +92534,75839,Female,disloyal Customer,25,Business travel,Business,1440,4,4,4,2,1,4,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +92535,20509,Female,Loyal Customer,17,Personal Travel,Eco,139,1,0,1,3,3,1,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +92536,50300,Female,Loyal Customer,38,Business travel,Business,3157,3,2,5,2,1,3,3,3,3,3,3,2,3,3,0,13.0,neutral or dissatisfied +92537,89415,Female,Loyal Customer,70,Business travel,Eco,134,3,1,1,1,2,3,3,3,3,3,3,2,3,4,15,19.0,neutral or dissatisfied +92538,48442,Female,disloyal Customer,42,Business travel,Eco,846,3,3,3,2,4,3,4,4,5,3,1,3,3,4,8,13.0,neutral or dissatisfied +92539,85237,Male,disloyal Customer,25,Business travel,Eco,874,2,2,2,4,3,2,3,3,4,1,1,2,5,3,47,42.0,neutral or dissatisfied +92540,124831,Male,Loyal Customer,58,Personal Travel,Eco,280,2,4,2,3,1,2,1,1,4,1,4,4,4,1,0,20.0,neutral or dissatisfied +92541,29162,Female,Loyal Customer,17,Business travel,Eco Plus,605,5,4,4,4,5,5,5,5,4,2,5,2,3,5,0,2.0,satisfied +92542,40660,Female,Loyal Customer,41,Business travel,Business,590,3,3,5,3,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +92543,125879,Female,Loyal Customer,61,Business travel,Business,592,2,5,5,5,2,2,1,2,2,2,2,2,2,1,15,5.0,neutral or dissatisfied +92544,111112,Female,Loyal Customer,56,Personal Travel,Eco Plus,319,4,5,4,1,4,3,3,4,2,4,4,3,5,3,137,151.0,neutral or dissatisfied +92545,115661,Male,Loyal Customer,49,Business travel,Business,3503,5,5,5,5,4,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +92546,56262,Male,disloyal Customer,37,Business travel,Eco,404,4,4,4,3,1,4,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +92547,84102,Male,Loyal Customer,67,Personal Travel,Eco Plus,773,3,5,3,2,4,3,4,4,5,4,5,5,5,4,1,0.0,neutral or dissatisfied +92548,112057,Female,Loyal Customer,54,Business travel,Business,1754,4,4,4,4,4,4,5,5,5,5,5,3,5,3,18,0.0,satisfied +92549,127111,Male,Loyal Customer,52,Personal Travel,Eco,338,2,5,2,1,5,2,4,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +92550,22418,Female,Loyal Customer,20,Business travel,Business,3577,4,2,2,2,4,4,4,4,1,4,1,1,4,4,0,5.0,neutral or dissatisfied +92551,118156,Male,Loyal Customer,49,Business travel,Business,1444,3,3,3,3,5,5,4,4,4,4,4,5,4,4,6,2.0,satisfied +92552,82999,Male,Loyal Customer,46,Business travel,Eco,983,3,3,3,3,3,3,3,3,3,4,4,4,3,3,0,1.0,neutral or dissatisfied +92553,71944,Female,Loyal Customer,36,Business travel,Business,1440,4,4,4,4,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +92554,4084,Male,Loyal Customer,40,Business travel,Business,3888,2,4,4,4,4,3,4,2,2,2,2,2,2,2,0,21.0,neutral or dissatisfied +92555,23779,Female,Loyal Customer,39,Business travel,Business,2595,2,2,2,2,3,1,2,4,4,4,4,4,4,3,0,29.0,satisfied +92556,47948,Male,Loyal Customer,51,Personal Travel,Eco,329,2,4,2,5,3,2,3,3,4,4,5,1,5,3,1,13.0,neutral or dissatisfied +92557,128631,Female,Loyal Customer,14,Personal Travel,Eco,954,2,5,2,3,4,2,4,4,2,1,2,2,3,4,39,28.0,neutral or dissatisfied +92558,87284,Male,Loyal Customer,35,Business travel,Business,2669,2,2,2,2,5,2,3,4,4,4,4,2,4,5,7,2.0,satisfied +92559,2536,Female,disloyal Customer,40,Business travel,Business,227,3,2,2,4,2,2,1,2,3,4,4,3,5,2,22,22.0,neutral or dissatisfied +92560,98597,Female,Loyal Customer,54,Business travel,Business,3213,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,6.0,satisfied +92561,1505,Male,Loyal Customer,64,Personal Travel,Eco,737,2,1,2,3,3,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +92562,83947,Female,Loyal Customer,53,Business travel,Business,373,3,3,1,3,2,4,5,4,4,4,4,5,4,5,0,1.0,satisfied +92563,95329,Female,Loyal Customer,38,Personal Travel,Eco,239,2,5,0,1,2,0,2,2,3,4,1,5,5,2,0,0.0,neutral or dissatisfied +92564,79515,Male,Loyal Customer,29,Business travel,Business,3135,2,4,2,2,4,4,4,4,3,2,5,3,5,4,9,0.0,satisfied +92565,90259,Female,disloyal Customer,34,Business travel,Business,879,2,2,2,1,3,2,4,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +92566,20116,Male,Loyal Customer,40,Business travel,Business,2420,2,4,4,4,3,4,4,2,2,2,2,1,2,4,0,3.0,neutral or dissatisfied +92567,107465,Male,Loyal Customer,48,Business travel,Business,3843,2,2,2,2,4,4,4,5,5,5,5,4,5,5,6,0.0,satisfied +92568,83720,Female,Loyal Customer,40,Personal Travel,Eco Plus,577,2,5,2,4,1,2,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +92569,6208,Male,disloyal Customer,34,Business travel,Business,462,1,1,1,1,5,1,3,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +92570,54908,Male,Loyal Customer,42,Business travel,Business,3372,5,4,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +92571,91272,Female,Loyal Customer,13,Personal Travel,Eco,270,3,0,3,5,3,3,3,3,5,5,4,5,4,3,0,8.0,neutral or dissatisfied +92572,123597,Female,Loyal Customer,17,Personal Travel,Eco,1773,1,3,1,4,5,1,5,5,1,5,4,1,4,5,0,34.0,neutral or dissatisfied +92573,115235,Female,Loyal Customer,38,Business travel,Business,1588,4,1,1,1,2,4,4,4,4,4,4,3,4,4,17,12.0,neutral or dissatisfied +92574,27962,Male,Loyal Customer,31,Personal Travel,Eco,1874,3,4,3,2,5,3,1,5,3,3,1,4,5,5,30,29.0,neutral or dissatisfied +92575,56146,Male,Loyal Customer,37,Business travel,Business,1400,1,4,4,4,1,4,4,1,1,1,1,4,1,2,9,0.0,neutral or dissatisfied +92576,126486,Female,disloyal Customer,75,Business travel,Eco,349,3,0,3,1,4,3,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +92577,74484,Female,Loyal Customer,40,Business travel,Business,3620,5,5,5,5,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +92578,59211,Female,Loyal Customer,67,Personal Travel,Eco,1440,1,4,1,3,5,4,4,5,5,1,5,5,5,4,1,3.0,neutral or dissatisfied +92579,7556,Female,Loyal Customer,57,Business travel,Eco,206,3,1,1,1,3,3,3,2,3,4,4,3,4,3,57,138.0,neutral or dissatisfied +92580,80136,Male,disloyal Customer,24,Business travel,Eco,1130,4,4,4,1,4,3,3,5,4,4,5,3,3,3,0,7.0,satisfied +92581,123317,Female,Loyal Customer,55,Business travel,Business,2935,1,3,1,1,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +92582,47526,Male,Loyal Customer,68,Personal Travel,Eco,532,3,5,2,1,1,2,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +92583,27584,Male,Loyal Customer,51,Personal Travel,Eco,679,1,4,1,3,3,1,3,3,4,4,4,3,4,3,0,12.0,neutral or dissatisfied +92584,118653,Male,disloyal Customer,24,Business travel,Eco,651,2,2,2,4,3,2,3,3,3,3,4,1,4,3,22,42.0,neutral or dissatisfied +92585,48712,Female,Loyal Customer,56,Business travel,Business,209,4,4,4,4,4,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +92586,105639,Male,Loyal Customer,55,Business travel,Business,787,5,5,5,5,5,4,5,5,5,5,5,3,5,4,24,21.0,satisfied +92587,47974,Female,Loyal Customer,40,Personal Travel,Eco,412,2,5,2,2,5,2,5,5,3,5,5,5,4,5,15,16.0,neutral or dissatisfied +92588,70207,Male,Loyal Customer,60,Personal Travel,Eco,258,2,1,2,3,1,2,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +92589,87113,Female,Loyal Customer,48,Personal Travel,Eco,594,4,2,4,4,4,3,3,1,1,4,1,2,1,4,0,0.0,neutral or dissatisfied +92590,46050,Female,Loyal Customer,13,Personal Travel,Eco,996,1,5,1,3,2,1,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +92591,77029,Female,Loyal Customer,52,Business travel,Eco,368,5,3,3,3,4,4,2,5,5,5,5,4,5,1,0,0.0,satisfied +92592,110705,Female,disloyal Customer,36,Business travel,Eco Plus,605,3,3,3,3,3,3,3,3,1,4,4,4,3,3,22,16.0,neutral or dissatisfied +92593,79662,Male,Loyal Customer,52,Personal Travel,Eco,712,5,4,5,4,1,5,1,1,1,4,2,5,4,1,0,0.0,satisfied +92594,58645,Female,Loyal Customer,65,Business travel,Business,867,3,2,2,2,1,4,3,3,3,3,3,2,3,2,7,24.0,neutral or dissatisfied +92595,21494,Female,Loyal Customer,70,Personal Travel,Eco,306,2,4,2,5,1,3,1,1,1,2,1,3,1,5,5,0.0,neutral or dissatisfied +92596,50557,Male,Loyal Customer,41,Personal Travel,Eco,193,2,4,2,3,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +92597,95909,Male,Loyal Customer,27,Business travel,Eco Plus,580,4,5,5,5,4,4,4,4,3,3,3,3,4,4,12,1.0,satisfied +92598,70110,Male,Loyal Customer,25,Business travel,Eco,460,3,4,4,4,3,3,2,3,3,5,3,4,3,3,7,0.0,neutral or dissatisfied +92599,36777,Female,Loyal Customer,35,Business travel,Business,2588,3,2,2,2,3,3,3,3,4,3,2,3,1,3,1,1.0,neutral or dissatisfied +92600,95141,Female,Loyal Customer,58,Personal Travel,Eco,189,2,4,2,3,3,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +92601,79205,Female,Loyal Customer,28,Business travel,Business,1990,3,3,3,3,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +92602,30912,Male,Loyal Customer,17,Business travel,Business,896,1,1,1,1,4,4,4,4,3,2,4,4,3,4,0,2.0,satisfied +92603,78143,Male,Loyal Customer,56,Business travel,Business,1903,0,0,0,1,4,4,4,1,1,1,1,4,1,5,0,0.0,satisfied +92604,89442,Male,Loyal Customer,33,Personal Travel,Eco,134,1,4,1,4,4,1,3,4,2,3,4,2,4,4,1,0.0,neutral or dissatisfied +92605,86073,Female,Loyal Customer,50,Personal Travel,Eco Plus,528,2,1,2,2,5,2,2,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +92606,100149,Female,disloyal Customer,23,Business travel,Eco,468,3,3,3,3,4,3,4,4,2,2,4,1,3,4,37,35.0,neutral or dissatisfied +92607,14438,Male,disloyal Customer,24,Business travel,Eco,674,4,4,4,3,5,4,5,5,4,2,1,3,5,5,21,5.0,neutral or dissatisfied +92608,68495,Female,Loyal Customer,26,Personal Travel,Eco,1303,2,5,2,3,5,2,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +92609,126368,Female,Loyal Customer,8,Personal Travel,Eco,631,2,1,2,4,3,2,3,3,1,4,4,1,4,3,3,1.0,neutral or dissatisfied +92610,48348,Female,Loyal Customer,28,Business travel,Business,522,2,3,3,3,2,2,2,2,3,1,3,2,4,2,0,3.0,neutral or dissatisfied +92611,64697,Female,disloyal Customer,22,Business travel,Business,190,5,0,5,4,3,5,1,3,4,4,4,4,4,3,0,0.0,satisfied +92612,2316,Male,Loyal Customer,35,Personal Travel,Eco,672,2,2,2,2,2,2,2,2,2,3,2,3,1,2,0,6.0,neutral or dissatisfied +92613,114582,Female,Loyal Customer,40,Business travel,Business,337,5,5,5,5,4,4,5,5,5,5,5,5,5,4,13,6.0,satisfied +92614,108671,Female,Loyal Customer,54,Personal Travel,Eco,484,4,0,4,4,5,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +92615,27711,Male,Loyal Customer,39,Business travel,Business,1448,2,1,1,1,4,2,3,2,2,2,2,1,2,2,5,0.0,neutral or dissatisfied +92616,124155,Male,disloyal Customer,39,Business travel,Business,2133,5,5,5,5,2,5,2,2,4,5,4,5,4,2,0,0.0,satisfied +92617,46827,Male,Loyal Customer,35,Business travel,Eco,776,4,3,3,3,4,4,4,4,4,4,1,2,1,4,5,2.0,satisfied +92618,12443,Female,Loyal Customer,26,Personal Travel,Eco,201,1,4,1,5,4,1,4,4,5,3,2,2,5,4,17,11.0,neutral or dissatisfied +92619,117512,Female,disloyal Customer,20,Business travel,Eco Plus,507,2,1,2,4,2,4,4,2,2,3,4,4,4,4,177,184.0,neutral or dissatisfied +92620,75923,Female,Loyal Customer,44,Business travel,Business,1560,1,1,3,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +92621,80203,Male,Loyal Customer,68,Personal Travel,Eco,2586,2,4,2,2,2,4,4,5,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +92622,23952,Female,Loyal Customer,54,Business travel,Eco,936,2,5,5,5,5,3,3,2,2,2,2,2,2,2,8,0.0,neutral or dissatisfied +92623,87955,Male,Loyal Customer,28,Business travel,Business,581,2,2,2,2,2,2,2,2,5,3,4,5,5,2,18,7.0,satisfied +92624,77899,Female,Loyal Customer,58,Business travel,Business,1804,3,3,3,3,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +92625,76815,Male,Loyal Customer,57,Business travel,Business,3593,2,2,2,2,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +92626,19591,Female,Loyal Customer,64,Personal Travel,Eco,173,3,4,3,1,4,3,5,1,1,3,1,4,1,5,26,17.0,neutral or dissatisfied +92627,92830,Female,Loyal Customer,33,Personal Travel,Eco,1587,4,5,4,4,3,4,2,3,5,4,3,4,5,3,0,0.0,satisfied +92628,79200,Male,Loyal Customer,57,Business travel,Business,1990,3,3,3,3,2,4,5,1,1,2,1,5,1,4,30,49.0,satisfied +92629,68319,Male,Loyal Customer,39,Business travel,Business,2165,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +92630,82242,Female,Loyal Customer,30,Personal Travel,Eco,405,3,4,2,1,4,2,4,4,3,3,5,3,5,4,20,17.0,neutral or dissatisfied +92631,92842,Male,Loyal Customer,19,Personal Travel,Eco,1587,3,4,3,1,4,3,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +92632,20467,Male,Loyal Customer,14,Personal Travel,Eco,177,3,1,3,3,2,3,2,2,2,5,3,2,3,2,22,19.0,neutral or dissatisfied +92633,119234,Female,Loyal Customer,39,Personal Travel,Eco,290,2,4,2,2,2,2,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +92634,69040,Male,Loyal Customer,52,Business travel,Business,1389,5,5,4,5,5,5,5,5,5,5,5,4,5,4,25,5.0,satisfied +92635,13312,Male,disloyal Customer,77,Business travel,Eco,448,3,3,3,4,2,3,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +92636,63411,Male,Loyal Customer,69,Personal Travel,Eco,447,3,4,3,1,3,3,3,3,4,2,3,5,3,3,0,4.0,neutral or dissatisfied +92637,44527,Male,Loyal Customer,47,Business travel,Eco,157,2,3,3,3,2,2,2,2,5,4,1,1,2,2,1,0.0,satisfied +92638,123418,Female,disloyal Customer,38,Business travel,Eco,937,2,2,2,3,4,2,4,4,4,4,2,2,3,4,6,30.0,neutral or dissatisfied +92639,59530,Male,Loyal Customer,40,Business travel,Business,3117,1,1,1,1,4,4,3,1,1,1,1,2,1,1,2,0.0,neutral or dissatisfied +92640,95170,Female,Loyal Customer,11,Personal Travel,Eco,239,4,2,4,3,5,4,5,5,1,1,4,4,4,5,22,18.0,neutral or dissatisfied +92641,104030,Male,Loyal Customer,26,Business travel,Business,3161,4,4,4,4,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +92642,45148,Male,disloyal Customer,25,Business travel,Eco,174,1,4,1,1,1,1,1,1,1,3,1,1,4,1,59,60.0,neutral or dissatisfied +92643,93538,Male,Loyal Customer,31,Personal Travel,Eco,1218,3,4,3,5,3,3,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +92644,107005,Male,Loyal Customer,38,Business travel,Business,2519,4,4,4,4,5,5,4,5,5,5,5,3,5,5,0,21.0,satisfied +92645,15313,Male,Loyal Customer,42,Business travel,Eco,599,3,5,5,5,3,3,3,3,2,1,4,1,3,3,0,0.0,neutral or dissatisfied +92646,37894,Male,Loyal Customer,27,Business travel,Business,937,1,3,3,3,1,1,1,1,3,3,4,2,4,1,55,38.0,neutral or dissatisfied +92647,59025,Male,disloyal Customer,23,Business travel,Eco,1346,3,3,3,2,3,3,3,3,5,4,4,5,5,3,1,0.0,neutral or dissatisfied +92648,32785,Female,Loyal Customer,37,Business travel,Business,163,3,3,3,3,4,2,2,4,4,4,4,4,4,5,0,0.0,satisfied +92649,36616,Male,Loyal Customer,55,Business travel,Eco,1010,2,2,2,2,2,2,2,2,4,2,2,3,3,2,50,53.0,neutral or dissatisfied +92650,2146,Male,Loyal Customer,49,Personal Travel,Eco Plus,404,3,4,3,4,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +92651,98717,Male,Loyal Customer,49,Business travel,Eco Plus,592,4,4,2,4,4,4,4,4,2,4,2,2,4,4,5,7.0,satisfied +92652,52764,Female,Loyal Customer,39,Business travel,Business,1874,1,1,1,1,4,5,2,5,5,5,5,4,5,3,41,26.0,satisfied +92653,101914,Female,Loyal Customer,13,Personal Travel,Eco,2039,3,5,3,4,5,3,5,5,4,3,4,5,5,5,7,0.0,neutral or dissatisfied +92654,74453,Male,Loyal Customer,23,Business travel,Business,1464,3,3,3,3,3,4,3,3,5,5,5,4,4,3,18,0.0,satisfied +92655,57507,Female,disloyal Customer,32,Business travel,Business,235,3,3,3,4,2,3,3,2,5,4,4,4,5,2,11,79.0,neutral or dissatisfied +92656,117660,Female,Loyal Customer,38,Business travel,Business,1449,4,4,4,4,2,5,5,5,5,5,5,3,5,4,30,9.0,satisfied +92657,115073,Female,disloyal Customer,40,Business travel,Business,371,4,4,4,2,1,4,1,1,4,2,4,4,4,1,1,0.0,satisfied +92658,109739,Female,Loyal Customer,14,Personal Travel,Eco,587,2,5,2,3,5,2,5,5,5,3,5,4,5,5,4,6.0,neutral or dissatisfied +92659,35338,Male,Loyal Customer,57,Business travel,Eco,1010,4,4,4,4,4,4,4,4,3,2,4,1,4,4,0,0.0,neutral or dissatisfied +92660,6588,Female,Loyal Customer,56,Personal Travel,Eco,528,2,5,2,5,5,4,4,3,3,2,3,4,3,3,102,109.0,neutral or dissatisfied +92661,6537,Female,Loyal Customer,50,Business travel,Business,3761,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,21.0,satisfied +92662,111951,Male,Loyal Customer,40,Business travel,Eco,770,3,3,3,3,3,2,3,3,1,1,4,1,4,3,29,49.0,neutral or dissatisfied +92663,30174,Male,Loyal Customer,62,Personal Travel,Eco,539,2,5,2,2,3,2,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +92664,79957,Female,Loyal Customer,43,Business travel,Eco,544,5,2,2,2,3,1,5,5,5,5,5,5,5,5,0,0.0,satisfied +92665,24614,Female,Loyal Customer,23,Business travel,Business,3530,3,5,5,5,3,3,3,3,4,3,4,3,3,3,0,7.0,neutral or dissatisfied +92666,35024,Male,Loyal Customer,35,Personal Travel,Eco,740,3,4,3,4,3,3,3,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +92667,124459,Female,Loyal Customer,44,Business travel,Business,980,2,4,4,4,1,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +92668,103462,Male,Loyal Customer,32,Personal Travel,Eco,393,1,5,1,4,5,1,5,5,1,5,5,4,2,5,35,32.0,neutral or dissatisfied +92669,41741,Male,Loyal Customer,15,Personal Travel,Eco,695,3,4,3,3,3,3,3,3,5,3,5,5,5,3,0,9.0,neutral or dissatisfied +92670,50974,Female,Loyal Customer,31,Personal Travel,Eco,134,3,0,0,4,2,0,2,2,3,3,1,2,3,2,0,0.0,neutral or dissatisfied +92671,42524,Male,Loyal Customer,41,Business travel,Business,2231,1,1,1,1,4,4,2,4,4,4,4,1,4,2,5,1.0,satisfied +92672,60850,Male,Loyal Customer,17,Personal Travel,Eco,1754,1,3,1,2,4,1,4,4,4,3,2,1,3,4,64,85.0,neutral or dissatisfied +92673,116723,Female,disloyal Customer,30,Business travel,Eco Plus,446,1,1,1,4,2,1,2,2,2,2,3,3,4,2,71,78.0,neutral or dissatisfied +92674,104376,Female,Loyal Customer,39,Business travel,Eco,228,3,2,2,2,3,3,3,3,2,3,4,4,4,3,22,43.0,neutral or dissatisfied +92675,49548,Female,Loyal Customer,46,Business travel,Business,3736,4,4,4,4,3,2,1,5,5,5,5,2,5,4,0,0.0,satisfied +92676,12755,Female,Loyal Customer,22,Personal Travel,Eco,689,4,3,4,4,4,4,2,4,3,3,3,3,3,4,0,5.0,neutral or dissatisfied +92677,84852,Female,Loyal Customer,39,Business travel,Business,116,4,1,1,1,1,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +92678,32928,Female,Loyal Customer,43,Personal Travel,Eco,163,2,5,2,2,2,4,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +92679,1808,Female,Loyal Customer,41,Business travel,Business,2433,2,2,2,2,2,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +92680,10553,Female,Loyal Customer,48,Business travel,Business,1718,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +92681,63979,Female,Loyal Customer,10,Personal Travel,Eco Plus,1192,2,4,2,1,5,2,5,5,4,5,4,3,4,5,6,17.0,neutral or dissatisfied +92682,61552,Female,Loyal Customer,60,Business travel,Business,2253,2,2,2,2,3,3,4,4,4,4,4,4,4,4,1,0.0,satisfied +92683,54792,Male,Loyal Customer,44,Personal Travel,Business,862,2,5,2,3,2,4,4,3,3,2,3,3,3,5,9,0.0,neutral or dissatisfied +92684,102012,Male,Loyal Customer,60,Business travel,Business,397,3,3,3,3,5,5,4,5,5,5,5,4,5,4,29,22.0,satisfied +92685,31223,Female,Loyal Customer,60,Personal Travel,Eco,628,2,5,2,4,3,5,4,3,3,2,3,5,3,4,7,6.0,neutral or dissatisfied +92686,115090,Female,disloyal Customer,47,Business travel,Business,446,3,3,3,5,4,3,4,4,4,3,5,3,4,4,14,6.0,neutral or dissatisfied +92687,29215,Male,Loyal Customer,24,Business travel,Business,3428,3,3,3,3,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +92688,17202,Female,Loyal Customer,28,Business travel,Business,2568,1,1,1,1,4,4,4,4,2,5,5,3,5,4,0,0.0,satisfied +92689,58952,Female,Loyal Customer,30,Personal Travel,Eco Plus,888,3,5,3,4,2,3,5,2,3,5,4,4,4,2,10,0.0,neutral or dissatisfied +92690,51675,Female,disloyal Customer,23,Business travel,Eco,509,4,4,4,4,5,4,5,5,4,5,3,3,4,5,41,29.0,neutral or dissatisfied +92691,88953,Female,Loyal Customer,49,Business travel,Business,2288,1,1,1,1,2,5,5,5,5,5,5,3,5,3,0,21.0,satisfied +92692,67972,Female,Loyal Customer,34,Business travel,Eco Plus,1235,2,3,3,3,2,2,2,2,1,3,3,2,4,2,1,9.0,neutral or dissatisfied +92693,51010,Male,Loyal Customer,61,Personal Travel,Eco,109,2,5,2,3,4,2,4,4,4,1,4,4,2,4,11,9.0,neutral or dissatisfied +92694,51337,Male,Loyal Customer,37,Business travel,Eco Plus,109,4,5,5,5,4,4,4,4,2,2,5,3,2,4,0,0.0,satisfied +92695,100243,Female,Loyal Customer,52,Business travel,Business,3213,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +92696,53840,Male,disloyal Customer,39,Business travel,Eco,191,1,4,1,4,3,1,3,3,5,4,5,4,3,3,0,31.0,neutral or dissatisfied +92697,80023,Female,Loyal Customer,35,Personal Travel,Eco,1069,3,1,3,4,4,3,1,4,4,1,3,2,3,4,4,0.0,neutral or dissatisfied +92698,98651,Female,disloyal Customer,29,Business travel,Eco,920,3,3,3,4,5,3,5,5,1,2,4,1,4,5,12,3.0,neutral or dissatisfied +92699,10703,Female,Loyal Customer,54,Business travel,Business,2118,3,3,2,3,2,5,5,4,4,4,4,5,4,4,29,30.0,satisfied +92700,2533,Female,Loyal Customer,51,Business travel,Business,304,2,2,2,2,4,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +92701,315,Female,Loyal Customer,25,Business travel,Business,3380,1,1,1,1,5,5,5,5,3,4,5,4,5,5,2,3.0,satisfied +92702,27739,Male,disloyal Customer,27,Business travel,Eco,1483,2,2,2,2,1,2,1,1,3,5,4,2,1,1,10,0.0,neutral or dissatisfied +92703,92509,Female,Loyal Customer,42,Personal Travel,Eco,1892,4,5,4,2,2,1,5,2,2,4,2,4,2,2,0,0.0,satisfied +92704,58504,Male,Loyal Customer,29,Business travel,Business,719,2,2,2,2,2,2,2,1,1,3,3,2,2,2,129,158.0,neutral or dissatisfied +92705,101329,Female,Loyal Customer,60,Business travel,Business,2092,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +92706,60556,Male,Loyal Customer,47,Business travel,Eco Plus,641,1,5,5,5,1,1,1,1,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +92707,111267,Female,Loyal Customer,34,Business travel,Business,459,4,4,2,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +92708,1740,Female,Loyal Customer,66,Personal Travel,Eco,364,3,1,4,1,3,2,2,3,3,4,3,3,3,2,15,15.0,neutral or dissatisfied +92709,16133,Male,Loyal Customer,53,Personal Travel,Eco,725,2,2,2,3,1,2,1,1,2,3,4,4,4,1,0,4.0,neutral or dissatisfied +92710,47271,Male,Loyal Customer,58,Business travel,Eco,588,4,5,5,5,4,4,4,4,4,5,4,5,3,4,4,0.0,satisfied +92711,87200,Female,Loyal Customer,42,Business travel,Eco,946,3,4,2,2,4,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +92712,102885,Male,Loyal Customer,42,Personal Travel,Eco Plus,472,3,2,3,3,2,3,2,2,4,4,3,1,3,2,39,43.0,neutral or dissatisfied +92713,32432,Female,Loyal Customer,41,Business travel,Eco,163,1,4,5,4,1,1,1,1,3,4,4,3,4,1,12,12.0,neutral or dissatisfied +92714,61240,Female,disloyal Customer,17,Business travel,Eco,967,2,2,2,3,5,2,5,5,5,1,4,3,3,5,0,0.0,neutral or dissatisfied +92715,126428,Male,Loyal Customer,37,Business travel,Eco Plus,468,5,1,1,1,5,5,5,5,2,3,3,3,1,5,0,0.0,satisfied +92716,79123,Male,Loyal Customer,9,Personal Travel,Eco,356,4,5,4,1,4,4,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +92717,9771,Male,Loyal Customer,33,Business travel,Business,383,4,1,1,1,4,4,4,4,4,5,3,4,3,4,49,23.0,neutral or dissatisfied +92718,75254,Female,Loyal Customer,68,Personal Travel,Eco,1744,2,5,3,4,4,5,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +92719,125964,Female,Loyal Customer,50,Business travel,Business,1852,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,7.0,satisfied +92720,124027,Female,Loyal Customer,24,Personal Travel,Eco,184,5,4,5,4,1,5,1,1,3,3,4,3,4,1,0,0.0,satisfied +92721,14227,Male,Loyal Customer,38,Business travel,Eco Plus,714,5,4,4,4,5,5,5,5,1,4,5,5,4,5,45,21.0,satisfied +92722,101569,Male,Loyal Customer,40,Personal Travel,Eco Plus,345,4,5,4,4,5,4,2,5,3,5,4,5,4,5,19,11.0,neutral or dissatisfied +92723,73297,Female,Loyal Customer,40,Business travel,Business,3093,2,1,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +92724,116763,Male,Loyal Customer,28,Personal Travel,Eco Plus,325,2,4,4,3,4,4,4,4,3,2,2,3,4,4,1,0.0,neutral or dissatisfied +92725,38113,Female,Loyal Customer,62,Business travel,Eco,1237,3,4,4,4,5,2,3,3,3,3,3,2,3,4,18,0.0,neutral or dissatisfied +92726,37214,Male,Loyal Customer,45,Business travel,Business,950,1,1,1,1,3,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +92727,51726,Male,Loyal Customer,68,Personal Travel,Eco,370,4,1,4,2,2,4,2,2,3,5,3,3,2,2,21,18.0,satisfied +92728,27772,Male,Loyal Customer,37,Business travel,Business,1737,3,3,1,3,4,3,4,2,2,2,2,2,2,1,0,0.0,satisfied +92729,73817,Female,Loyal Customer,58,Business travel,Business,2069,0,4,0,1,3,5,5,2,2,4,4,4,2,4,0,0.0,satisfied +92730,3896,Male,Loyal Customer,45,Business travel,Business,213,2,2,2,2,3,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +92731,18523,Male,Loyal Customer,50,Business travel,Business,2085,2,2,2,2,5,4,4,5,5,5,4,5,5,1,63,65.0,satisfied +92732,122889,Female,Loyal Customer,58,Business travel,Business,226,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +92733,73630,Female,disloyal Customer,24,Business travel,Eco,192,1,1,1,4,1,5,5,1,3,3,4,5,3,5,160,175.0,neutral or dissatisfied +92734,95665,Male,Loyal Customer,27,Personal Travel,Eco Plus,928,3,4,3,1,5,3,2,5,3,2,4,5,5,5,21,24.0,neutral or dissatisfied +92735,124579,Male,Loyal Customer,55,Business travel,Business,500,3,3,3,3,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +92736,87125,Male,Loyal Customer,63,Personal Travel,Eco,594,3,2,3,4,5,3,5,5,4,3,4,2,3,5,13,3.0,neutral or dissatisfied +92737,52041,Male,Loyal Customer,63,Personal Travel,Eco Plus,328,3,1,3,4,1,3,1,1,3,1,4,3,3,1,0,0.0,neutral or dissatisfied +92738,123643,Female,disloyal Customer,61,Business travel,Business,214,1,1,1,5,4,1,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +92739,106186,Female,Loyal Customer,57,Personal Travel,Eco,436,4,2,4,3,3,3,3,5,5,4,5,2,5,4,1,4.0,neutral or dissatisfied +92740,25326,Male,Loyal Customer,18,Business travel,Business,3926,5,5,5,5,3,3,3,3,5,3,1,5,5,3,0,0.0,satisfied +92741,118294,Female,disloyal Customer,9,Business travel,Eco,639,1,3,1,4,1,1,1,1,4,4,3,4,4,1,1,0.0,neutral or dissatisfied +92742,120118,Female,Loyal Customer,41,Personal Travel,Eco,1576,3,3,3,3,1,3,1,1,4,4,2,3,4,1,0,0.0,neutral or dissatisfied +92743,102470,Male,Loyal Customer,46,Personal Travel,Eco,236,2,4,2,4,1,2,1,1,5,5,4,5,5,1,0,1.0,neutral or dissatisfied +92744,129511,Female,Loyal Customer,67,Personal Travel,Eco,1744,2,5,1,2,4,3,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +92745,42942,Male,disloyal Customer,23,Business travel,Business,236,4,5,4,4,1,4,1,1,3,5,5,5,5,1,0,0.0,satisfied +92746,79690,Male,Loyal Customer,69,Personal Travel,Eco,762,2,4,2,4,1,2,1,1,3,3,3,1,3,1,22,27.0,neutral or dissatisfied +92747,5320,Female,Loyal Customer,8,Personal Travel,Eco Plus,285,3,4,3,4,1,3,1,1,4,1,4,3,3,1,0,0.0,neutral or dissatisfied +92748,13038,Male,Loyal Customer,15,Personal Travel,Eco,374,3,0,3,3,4,3,1,4,1,2,5,2,2,4,0,0.0,neutral or dissatisfied +92749,107207,Female,Loyal Customer,62,Personal Travel,Eco,402,1,5,1,2,2,4,5,5,5,1,5,3,5,4,34,17.0,neutral or dissatisfied +92750,107741,Male,Loyal Customer,24,Personal Travel,Eco,251,3,3,3,1,3,3,3,3,1,4,3,3,1,3,12,7.0,neutral or dissatisfied +92751,124848,Male,Loyal Customer,22,Personal Travel,Eco,280,3,5,5,3,3,5,3,3,3,5,5,3,4,3,3,0.0,neutral or dissatisfied +92752,89133,Female,disloyal Customer,40,Business travel,Business,1892,4,4,4,1,4,4,3,4,4,2,4,4,5,4,4,0.0,neutral or dissatisfied +92753,63235,Female,disloyal Customer,37,Business travel,Business,337,3,3,3,3,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +92754,11820,Female,disloyal Customer,21,Business travel,Eco,1091,5,5,5,3,2,5,2,2,5,3,4,5,5,2,5,0.0,satisfied +92755,114803,Male,Loyal Customer,49,Business travel,Business,372,1,1,5,1,5,5,4,5,5,5,5,5,5,5,12,8.0,satisfied +92756,8183,Male,Loyal Customer,36,Business travel,Eco,294,3,1,1,1,3,3,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +92757,112246,Female,Loyal Customer,34,Business travel,Business,1546,4,4,4,4,3,4,4,5,5,5,5,4,5,4,41,48.0,satisfied +92758,68902,Female,Loyal Customer,54,Personal Travel,Eco,936,4,5,4,1,3,4,4,3,3,4,4,3,3,5,58,42.0,satisfied +92759,115369,Female,Loyal Customer,52,Business travel,Business,3849,3,2,2,2,3,3,3,3,3,2,3,4,3,4,34,23.0,neutral or dissatisfied +92760,13539,Female,Loyal Customer,44,Business travel,Business,2867,3,4,4,4,2,3,4,3,3,3,3,4,3,3,40,56.0,neutral or dissatisfied +92761,78434,Male,disloyal Customer,49,Business travel,Business,666,2,3,3,4,5,2,5,5,5,4,5,3,4,5,0,15.0,neutral or dissatisfied +92762,80591,Female,Loyal Customer,55,Personal Travel,Eco,1747,5,5,5,2,5,4,4,1,1,5,4,5,1,4,33,3.0,satisfied +92763,103859,Female,Loyal Customer,56,Personal Travel,Eco,1048,4,4,3,3,4,5,4,5,5,3,5,5,5,3,20,14.0,satisfied +92764,123343,Female,Loyal Customer,37,Personal Travel,Eco Plus,650,1,2,1,3,5,1,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +92765,59266,Male,Loyal Customer,30,Business travel,Eco,4963,1,1,1,1,1,1,1,2,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +92766,126214,Male,Loyal Customer,58,Business travel,Business,650,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,1.0,satisfied +92767,78766,Female,Loyal Customer,39,Business travel,Business,1824,2,5,5,5,1,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +92768,113120,Male,Loyal Customer,10,Personal Travel,Eco,479,1,1,5,3,1,5,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +92769,55555,Female,Loyal Customer,48,Personal Travel,Eco,550,4,4,4,3,5,3,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +92770,6607,Male,Loyal Customer,17,Personal Travel,Eco,528,1,5,1,1,5,1,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +92771,10641,Female,disloyal Customer,27,Business travel,Eco,517,2,2,2,3,2,2,1,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +92772,85396,Female,disloyal Customer,21,Business travel,Business,332,4,0,4,5,1,4,1,1,5,5,5,3,4,1,0,0.0,satisfied +92773,69502,Male,Loyal Customer,11,Personal Travel,Eco Plus,1096,3,1,4,4,5,4,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +92774,109278,Male,disloyal Customer,26,Business travel,Business,1136,1,1,1,4,1,1,1,1,4,2,4,3,4,1,29,31.0,neutral or dissatisfied +92775,90537,Male,Loyal Customer,60,Business travel,Business,3947,0,0,0,3,2,4,5,1,1,1,1,3,1,5,44,58.0,satisfied +92776,94662,Male,Loyal Customer,42,Business travel,Business,323,4,3,3,3,3,2,3,4,4,3,4,4,4,3,4,10.0,neutral or dissatisfied +92777,107061,Female,Loyal Customer,7,Personal Travel,Eco,395,1,0,1,4,5,1,5,5,5,4,5,4,5,5,38,32.0,neutral or dissatisfied +92778,68538,Male,disloyal Customer,25,Business travel,Eco,1013,2,2,2,3,2,2,2,2,1,3,2,1,3,2,0,,neutral or dissatisfied +92779,75195,Male,disloyal Customer,8,Business travel,Business,1723,3,0,3,2,2,3,2,2,3,2,3,3,4,2,15,0.0,neutral or dissatisfied +92780,28419,Male,Loyal Customer,36,Business travel,Business,1399,4,4,4,4,2,5,4,2,2,2,2,1,2,5,0,0.0,satisfied +92781,93522,Female,Loyal Customer,50,Business travel,Business,1977,3,3,3,3,5,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +92782,103934,Female,Loyal Customer,29,Business travel,Business,533,2,2,2,2,4,4,4,4,4,3,5,4,4,4,1,12.0,satisfied +92783,83147,Male,Loyal Customer,41,Personal Travel,Eco,957,3,1,3,3,3,3,3,3,2,3,4,2,3,3,0,0.0,neutral or dissatisfied +92784,129769,Male,Loyal Customer,7,Personal Travel,Eco,308,1,3,1,3,2,1,2,2,1,5,4,1,3,2,0,0.0,neutral or dissatisfied +92785,94603,Female,disloyal Customer,22,Business travel,Eco,248,1,0,1,3,2,1,2,2,5,4,4,3,5,2,11,4.0,neutral or dissatisfied +92786,129495,Female,Loyal Customer,12,Personal Travel,Business,1744,1,4,1,2,1,1,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +92787,76852,Female,Loyal Customer,50,Business travel,Business,3677,4,4,2,4,2,3,1,4,4,4,4,3,4,4,23,25.0,satisfied +92788,38094,Male,Loyal Customer,21,Business travel,Business,1814,4,5,5,5,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +92789,122717,Male,Loyal Customer,27,Business travel,Business,2573,3,3,3,3,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +92790,42687,Male,Loyal Customer,49,Business travel,Eco,627,2,2,2,2,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +92791,109077,Female,Loyal Customer,45,Personal Travel,Eco,849,2,3,2,3,1,1,1,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +92792,51578,Female,Loyal Customer,62,Business travel,Business,3656,0,0,0,1,1,3,2,1,1,1,1,4,1,1,0,0.0,satisfied +92793,55960,Male,disloyal Customer,22,Business travel,Eco,1266,1,0,0,3,3,0,3,3,5,4,5,4,4,3,23,0.0,neutral or dissatisfied +92794,99744,Female,Loyal Customer,35,Business travel,Business,2204,3,5,5,5,5,4,4,3,3,3,3,1,3,1,14,12.0,neutral or dissatisfied +92795,111373,Male,disloyal Customer,37,Business travel,Business,1173,1,1,1,1,5,1,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +92796,38550,Female,Loyal Customer,39,Business travel,Business,3241,2,1,1,1,5,4,4,2,2,2,2,1,2,1,12,26.0,neutral or dissatisfied +92797,53483,Male,disloyal Customer,29,Business travel,Eco,761,3,3,3,3,3,1,1,1,4,3,4,1,2,1,58,72.0,neutral or dissatisfied +92798,18654,Male,Loyal Customer,54,Personal Travel,Eco,253,3,4,3,1,4,3,4,4,3,2,3,4,1,4,0,0.0,neutral or dissatisfied +92799,110311,Male,disloyal Customer,22,Business travel,Eco,842,2,2,2,4,3,2,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +92800,75601,Male,Loyal Customer,8,Personal Travel,Eco,337,1,3,1,3,3,1,3,3,4,3,1,5,4,3,16,10.0,neutral or dissatisfied +92801,68293,Female,Loyal Customer,35,Business travel,Business,1797,3,5,5,5,3,2,3,3,3,3,3,4,3,4,10,15.0,neutral or dissatisfied +92802,112215,Female,disloyal Customer,25,Business travel,Business,1199,1,0,1,3,3,1,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +92803,68371,Male,Loyal Customer,61,Personal Travel,Business,1045,1,4,1,1,5,5,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +92804,9652,Male,Loyal Customer,52,Business travel,Business,3980,0,4,0,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +92805,76055,Female,Loyal Customer,50,Business travel,Business,669,5,5,5,5,2,5,5,4,4,4,4,5,4,4,0,29.0,satisfied +92806,46554,Male,disloyal Customer,27,Business travel,Eco,125,1,5,1,3,4,1,5,4,5,2,4,2,2,4,0,0.0,neutral or dissatisfied +92807,86733,Male,Loyal Customer,9,Personal Travel,Eco,1747,1,0,1,4,5,1,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +92808,3287,Male,Loyal Customer,57,Personal Travel,Eco,479,1,2,1,3,5,1,5,5,3,3,3,4,3,5,0,14.0,neutral or dissatisfied +92809,80383,Female,disloyal Customer,20,Business travel,Eco,368,2,4,2,3,2,2,2,2,4,3,4,4,4,2,7,0.0,neutral or dissatisfied +92810,44628,Male,Loyal Customer,46,Business travel,Business,67,1,1,1,1,2,5,4,4,4,4,5,5,4,5,0,9.0,satisfied +92811,55848,Female,Loyal Customer,9,Personal Travel,Eco,1416,2,5,2,4,2,2,1,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +92812,65075,Female,Loyal Customer,50,Personal Travel,Eco,190,2,5,2,2,3,5,5,2,2,2,2,4,2,4,3,0.0,neutral or dissatisfied +92813,77144,Female,Loyal Customer,29,Business travel,Business,1865,3,3,5,3,4,4,4,4,4,3,4,5,4,4,9,0.0,satisfied +92814,62436,Female,Loyal Customer,44,Business travel,Business,1943,3,3,3,3,5,5,5,5,5,5,5,5,5,4,59,62.0,satisfied +92815,100277,Female,Loyal Customer,29,Business travel,Business,3637,4,4,4,4,4,4,4,4,3,2,5,4,5,4,0,1.0,satisfied +92816,119610,Female,Loyal Customer,43,Personal Travel,Eco,1979,1,1,1,4,2,3,3,3,3,1,3,2,3,4,96,112.0,neutral or dissatisfied +92817,94571,Male,Loyal Customer,33,Business travel,Business,189,3,1,1,1,3,3,3,3,2,2,2,4,2,3,49,49.0,neutral or dissatisfied +92818,93567,Female,disloyal Customer,21,Business travel,Eco,159,1,0,1,1,4,1,4,4,5,4,5,5,4,4,4,0.0,neutral or dissatisfied +92819,120171,Male,Loyal Customer,53,Business travel,Eco,335,2,5,5,5,2,2,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +92820,123114,Male,disloyal Customer,26,Business travel,Eco,631,2,3,2,3,4,2,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +92821,119947,Female,Loyal Customer,26,Business travel,Eco,1009,2,4,4,4,2,2,3,2,3,1,4,3,3,2,0,0.0,neutral or dissatisfied +92822,121230,Male,Loyal Customer,55,Business travel,Business,2075,5,5,3,5,3,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +92823,3466,Male,Loyal Customer,18,Personal Travel,Eco Plus,213,1,3,1,5,4,1,4,4,4,3,2,1,4,4,11,28.0,neutral or dissatisfied +92824,1882,Male,Loyal Customer,7,Personal Travel,Eco,931,2,4,2,1,4,2,4,4,4,3,4,5,4,4,1,7.0,neutral or dissatisfied +92825,57798,Male,Loyal Customer,54,Business travel,Business,3911,3,3,3,3,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +92826,93048,Female,Loyal Customer,16,Personal Travel,Eco,317,2,4,4,3,5,4,5,5,2,5,3,1,1,5,0,0.0,neutral or dissatisfied +92827,15909,Male,disloyal Customer,52,Business travel,Eco,738,5,5,5,3,1,5,1,1,3,1,2,2,3,1,0,22.0,satisfied +92828,11137,Male,Loyal Customer,40,Personal Travel,Eco,312,2,5,2,2,5,2,5,5,3,5,4,3,4,5,1,0.0,neutral or dissatisfied +92829,9019,Female,Loyal Customer,45,Business travel,Business,2734,4,4,4,4,3,5,5,5,5,5,4,4,5,3,6,8.0,satisfied +92830,34234,Female,Loyal Customer,27,Business travel,Eco Plus,1179,2,2,2,2,2,2,2,2,2,5,4,2,3,2,17,20.0,neutral or dissatisfied +92831,41843,Female,Loyal Customer,28,Personal Travel,Eco,462,1,1,1,3,3,1,3,3,1,2,2,1,3,3,0,2.0,neutral or dissatisfied +92832,32550,Male,disloyal Customer,39,Business travel,Eco,163,3,0,2,3,5,2,5,5,2,5,2,5,3,5,4,7.0,neutral or dissatisfied +92833,49627,Female,disloyal Customer,50,Business travel,Eco,86,3,0,3,1,5,3,5,5,4,2,3,4,5,5,0,4.0,neutral or dissatisfied +92834,115539,Female,disloyal Customer,42,Business travel,Eco,325,1,2,1,2,5,1,5,5,1,1,2,1,2,5,0,0.0,neutral or dissatisfied +92835,125585,Male,Loyal Customer,28,Business travel,Business,1587,3,3,3,3,5,5,5,5,3,4,4,4,4,5,0,6.0,satisfied +92836,11307,Female,Loyal Customer,52,Personal Travel,Eco,316,3,2,3,4,4,3,3,1,1,3,1,4,1,2,0,0.0,neutral or dissatisfied +92837,58230,Male,Loyal Customer,66,Personal Travel,Eco,925,3,4,3,3,2,3,2,2,3,2,4,5,5,2,11,27.0,neutral or dissatisfied +92838,22662,Male,Loyal Customer,59,Business travel,Business,2010,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,4.0,satisfied +92839,22664,Female,Loyal Customer,24,Business travel,Business,589,3,5,5,5,3,3,3,3,3,4,2,1,3,3,2,2.0,neutral or dissatisfied +92840,100490,Female,Loyal Customer,44,Business travel,Business,580,2,2,2,2,3,4,5,5,5,5,5,3,5,4,12,1.0,satisfied +92841,10141,Male,Loyal Customer,58,Business travel,Business,1936,1,1,1,1,5,5,5,4,4,4,4,5,4,5,1,0.0,satisfied +92842,87288,Female,Loyal Customer,76,Business travel,Business,177,2,2,2,2,1,2,2,4,4,4,4,4,4,5,0,0.0,satisfied +92843,70619,Male,Loyal Customer,34,Business travel,Business,1217,4,1,1,1,4,3,3,4,4,4,4,2,4,2,33,39.0,neutral or dissatisfied +92844,74262,Male,Loyal Customer,49,Business travel,Business,748,2,2,2,2,2,5,4,4,4,4,4,5,4,4,0,15.0,satisfied +92845,99999,Male,Loyal Customer,47,Business travel,Business,3629,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,4.0,satisfied +92846,105554,Female,Loyal Customer,48,Personal Travel,Eco,611,5,3,5,3,4,4,3,4,4,5,4,2,4,3,6,0.0,satisfied +92847,104433,Female,Loyal Customer,43,Personal Travel,Eco,1036,3,4,3,3,5,5,4,3,3,3,4,5,3,5,0,0.0,neutral or dissatisfied +92848,13305,Male,Loyal Customer,36,Business travel,Business,3846,4,2,2,2,1,4,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +92849,107016,Male,disloyal Customer,17,Personal Travel,Eco Plus,972,1,4,1,2,2,1,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +92850,62926,Male,disloyal Customer,18,Business travel,Eco,967,3,3,3,1,2,3,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +92851,68719,Female,Loyal Customer,36,Personal Travel,Eco,175,3,4,3,3,4,3,3,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +92852,13905,Female,Loyal Customer,47,Business travel,Business,153,1,1,1,1,3,4,2,5,5,5,5,5,5,3,29,11.0,satisfied +92853,106775,Male,Loyal Customer,12,Personal Travel,Eco,829,2,5,2,3,4,2,5,4,4,3,4,4,5,4,5,0.0,neutral or dissatisfied +92854,67719,Male,Loyal Customer,29,Business travel,Business,3479,2,3,3,3,2,2,2,2,3,2,3,2,4,2,6,3.0,neutral or dissatisfied +92855,20988,Female,Loyal Customer,55,Personal Travel,Eco,731,2,3,2,3,3,2,3,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +92856,52482,Female,Loyal Customer,29,Personal Travel,Eco Plus,451,1,4,1,4,2,1,2,2,4,3,3,4,3,2,20,19.0,neutral or dissatisfied +92857,4362,Male,Loyal Customer,53,Business travel,Business,2355,2,2,2,2,5,5,5,4,5,5,4,5,5,5,144,137.0,satisfied +92858,38219,Female,Loyal Customer,63,Personal Travel,Eco Plus,1185,2,3,2,2,4,4,2,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +92859,2757,Male,Loyal Customer,56,Personal Travel,Eco,695,3,4,3,3,5,3,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +92860,91078,Male,Loyal Customer,57,Personal Travel,Eco,240,2,4,0,4,0,1,1,5,3,4,4,1,4,1,253,243.0,neutral or dissatisfied +92861,105182,Male,Loyal Customer,19,Personal Travel,Eco,220,3,0,0,2,3,0,3,3,2,3,1,2,4,3,50,45.0,neutral or dissatisfied +92862,113836,Female,Loyal Customer,65,Personal Travel,Eco Plus,223,3,0,3,1,2,4,4,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +92863,84536,Female,Loyal Customer,56,Business travel,Business,2615,2,4,3,4,4,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +92864,51445,Male,Loyal Customer,61,Personal Travel,Eco Plus,421,3,3,3,4,3,3,3,3,3,1,1,1,1,3,0,0.0,neutral or dissatisfied +92865,4352,Female,Loyal Customer,49,Business travel,Business,3593,1,1,1,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +92866,64000,Female,Loyal Customer,37,Business travel,Business,2942,3,2,2,2,2,2,3,3,3,3,3,2,3,4,13,19.0,neutral or dissatisfied +92867,93073,Female,Loyal Customer,66,Personal Travel,Eco,297,3,4,3,3,5,5,5,4,4,3,4,5,4,5,0,23.0,neutral or dissatisfied +92868,44124,Female,Loyal Customer,57,Business travel,Eco,74,4,4,4,4,1,1,1,4,4,4,4,4,4,1,0,0.0,satisfied +92869,123860,Female,disloyal Customer,25,Business travel,Business,546,3,0,3,1,5,3,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +92870,63915,Female,Loyal Customer,57,Business travel,Business,1685,2,1,1,1,5,3,4,2,2,1,2,1,2,1,0,0.0,neutral or dissatisfied +92871,7949,Male,disloyal Customer,26,Business travel,Business,594,2,2,2,2,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +92872,64001,Male,disloyal Customer,43,Business travel,Eco,212,1,0,1,5,2,1,2,2,4,2,3,1,5,2,0,0.0,neutral or dissatisfied +92873,64549,Female,Loyal Customer,42,Business travel,Business,190,4,4,4,4,2,5,4,4,4,4,5,5,4,3,1,0.0,satisfied +92874,112406,Female,Loyal Customer,28,Business travel,Business,3830,1,1,5,1,3,3,3,3,3,3,5,3,4,3,2,4.0,satisfied +92875,60438,Male,Loyal Customer,48,Business travel,Business,862,3,2,3,3,5,5,5,2,2,2,2,3,2,4,2,6.0,satisfied +92876,109490,Male,Loyal Customer,49,Business travel,Business,966,3,5,3,3,5,4,5,5,5,5,5,5,5,4,19,4.0,satisfied +92877,11907,Female,Loyal Customer,58,Business travel,Business,2297,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +92878,126054,Male,Loyal Customer,49,Business travel,Business,600,5,5,5,5,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +92879,73796,Male,Loyal Customer,68,Business travel,Eco Plus,192,2,4,4,4,3,2,3,3,4,3,2,4,2,3,70,72.0,neutral or dissatisfied +92880,30331,Male,Loyal Customer,60,Business travel,Business,2111,3,4,4,4,3,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +92881,27008,Male,Loyal Customer,52,Business travel,Eco,867,5,3,3,3,5,5,5,5,3,5,2,1,2,5,0,6.0,satisfied +92882,17643,Male,Loyal Customer,46,Business travel,Business,2747,1,1,1,1,5,5,2,4,4,4,4,5,4,3,28,27.0,satisfied +92883,81655,Male,Loyal Customer,52,Business travel,Business,907,3,1,1,1,3,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +92884,70111,Female,Loyal Customer,50,Business travel,Business,550,5,5,5,5,4,5,5,5,5,4,5,5,5,4,31,19.0,satisfied +92885,67476,Male,Loyal Customer,18,Personal Travel,Eco,641,3,4,3,3,5,3,1,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +92886,48142,Female,Loyal Customer,47,Business travel,Eco,259,3,1,1,1,4,3,4,3,3,3,3,4,3,1,2,0.0,neutral or dissatisfied +92887,37131,Female,Loyal Customer,32,Business travel,Business,1970,2,4,2,2,4,4,4,4,5,5,3,2,1,4,111,120.0,satisfied +92888,52865,Male,Loyal Customer,44,Business travel,Business,2142,1,1,1,1,2,2,1,5,5,5,5,2,5,5,1,0.0,satisfied +92889,38166,Female,Loyal Customer,39,Personal Travel,Eco,1249,2,5,2,3,5,2,5,5,4,5,4,5,4,5,9,0.0,neutral or dissatisfied +92890,8347,Female,Loyal Customer,57,Business travel,Business,3755,4,4,4,4,2,5,4,2,2,2,2,5,2,3,0,21.0,satisfied +92891,91233,Female,Loyal Customer,21,Personal Travel,Eco,404,2,4,2,2,2,2,2,2,4,4,5,4,5,2,0,2.0,neutral or dissatisfied +92892,100588,Male,Loyal Customer,58,Personal Travel,Eco,486,1,1,1,4,4,1,2,4,3,3,2,4,4,4,10,4.0,neutral or dissatisfied +92893,73625,Male,disloyal Customer,37,Business travel,Business,192,1,1,1,1,5,1,1,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +92894,90875,Female,Loyal Customer,30,Business travel,Eco,366,1,5,5,5,1,1,1,1,1,2,3,4,3,1,88,105.0,neutral or dissatisfied +92895,31487,Female,disloyal Customer,14,Business travel,Eco,916,3,3,3,4,5,3,5,5,3,4,3,2,5,5,6,29.0,neutral or dissatisfied +92896,34233,Female,disloyal Customer,25,Business travel,Eco Plus,1237,4,1,4,3,1,4,1,1,2,4,4,4,4,1,20,9.0,neutral or dissatisfied +92897,505,Male,Loyal Customer,52,Business travel,Business,164,0,4,0,4,2,5,5,2,2,2,2,4,2,5,20,9.0,satisfied +92898,75843,Male,disloyal Customer,13,Business travel,Eco,798,2,2,2,3,2,1,3,1,2,4,4,3,1,3,313,303.0,neutral or dissatisfied +92899,35572,Female,Loyal Customer,30,Business travel,Eco Plus,1047,4,2,1,2,4,4,4,4,3,4,3,4,4,4,0,0.0,satisfied +92900,42513,Female,Loyal Customer,22,Business travel,Business,3889,4,4,4,4,4,4,4,4,4,2,3,4,1,4,0,0.0,satisfied +92901,129357,Male,Loyal Customer,22,Business travel,Eco Plus,2475,1,1,5,5,1,1,3,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +92902,79191,Male,Loyal Customer,60,Business travel,Business,1990,2,2,5,2,2,4,4,5,5,5,5,4,5,4,4,4.0,satisfied +92903,21654,Male,Loyal Customer,52,Business travel,Business,1532,3,1,1,1,2,3,2,3,3,3,3,2,3,2,44,36.0,neutral or dissatisfied +92904,95529,Male,Loyal Customer,24,Personal Travel,Eco Plus,528,1,5,1,2,2,1,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +92905,119445,Male,Loyal Customer,14,Personal Travel,Eco Plus,399,3,4,5,2,5,5,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +92906,35977,Female,Loyal Customer,36,Personal Travel,Eco Plus,231,2,5,2,3,5,2,5,5,3,3,1,5,2,5,0,0.0,neutral or dissatisfied +92907,51913,Male,Loyal Customer,43,Personal Travel,Eco,601,2,5,2,3,4,2,5,4,3,1,5,2,5,4,0,0.0,neutral or dissatisfied +92908,113786,Male,Loyal Customer,58,Business travel,Business,2944,1,1,5,1,4,5,5,4,4,4,4,3,4,4,19,12.0,satisfied +92909,50371,Male,Loyal Customer,48,Business travel,Business,2097,1,1,4,4,5,3,4,4,4,4,1,3,4,1,0,0.0,neutral or dissatisfied +92910,125101,Male,Loyal Customer,55,Business travel,Business,361,4,4,1,4,5,3,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +92911,57884,Female,disloyal Customer,38,Business travel,Business,305,5,5,5,5,5,5,4,5,3,2,4,5,5,5,6,0.0,satisfied +92912,23337,Female,Loyal Customer,55,Personal Travel,Eco,563,1,1,1,3,4,3,3,4,4,1,4,4,4,2,38,131.0,neutral or dissatisfied +92913,65137,Male,Loyal Customer,47,Personal Travel,Eco,224,1,2,0,3,4,0,4,4,4,5,3,4,3,4,52,49.0,neutral or dissatisfied +92914,837,Female,Loyal Customer,43,Business travel,Business,3923,1,3,3,3,3,2,2,4,4,4,1,2,4,3,7,8.0,neutral or dissatisfied +92915,40895,Male,Loyal Customer,36,Personal Travel,Eco,558,3,4,3,3,4,3,2,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +92916,67330,Female,Loyal Customer,56,Business travel,Business,1471,3,3,5,3,3,4,5,4,4,5,4,5,4,5,6,1.0,satisfied +92917,38358,Female,disloyal Customer,26,Business travel,Eco,1111,4,4,4,4,2,4,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +92918,114404,Female,Loyal Customer,33,Business travel,Business,296,2,2,2,2,3,4,5,5,5,5,5,5,5,4,2,0.0,satisfied +92919,34957,Female,Loyal Customer,57,Business travel,Eco Plus,187,4,4,4,4,1,3,4,4,4,4,4,4,4,2,0,0.0,satisfied +92920,48144,Male,Loyal Customer,32,Business travel,Eco,259,5,3,3,3,5,5,5,5,1,3,2,3,3,5,61,55.0,satisfied +92921,119007,Male,Loyal Customer,17,Personal Travel,Eco,459,2,5,2,1,4,2,5,4,3,2,4,3,4,4,22,13.0,neutral or dissatisfied +92922,76962,Female,Loyal Customer,60,Personal Travel,Eco,1990,3,3,3,4,3,3,3,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +92923,22641,Male,Loyal Customer,30,Personal Travel,Eco,223,2,4,2,2,5,2,5,5,5,2,4,3,5,5,27,16.0,neutral or dissatisfied +92924,114116,Female,disloyal Customer,19,Business travel,Eco,909,3,4,4,3,1,4,1,1,4,2,4,2,4,1,5,0.0,neutral or dissatisfied +92925,54093,Female,Loyal Customer,50,Personal Travel,Eco,1416,2,2,2,3,2,4,4,5,5,2,5,3,5,2,38,39.0,neutral or dissatisfied +92926,124755,Female,Loyal Customer,61,Personal Travel,Business,280,1,4,1,4,4,4,5,1,1,1,1,5,1,5,0,44.0,neutral or dissatisfied +92927,20438,Male,disloyal Customer,20,Business travel,Business,177,3,2,3,3,5,3,5,5,2,5,3,4,2,5,0,0.0,neutral or dissatisfied +92928,43525,Male,Loyal Customer,55,Personal Travel,Eco Plus,455,2,3,2,4,4,2,4,4,4,2,3,2,1,4,43,32.0,neutral or dissatisfied +92929,64719,Male,Loyal Customer,37,Business travel,Eco,469,3,3,3,3,3,3,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +92930,74334,Female,Loyal Customer,45,Business travel,Business,1688,4,3,2,3,1,2,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +92931,80066,Female,Loyal Customer,16,Personal Travel,Eco,1047,3,5,4,3,4,3,3,3,3,4,5,3,4,3,309,407.0,neutral or dissatisfied +92932,86446,Female,disloyal Customer,27,Business travel,Eco,712,3,3,3,3,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +92933,88017,Male,disloyal Customer,66,Business travel,Business,404,1,1,1,5,5,1,5,5,3,2,4,4,5,5,0,6.0,neutral or dissatisfied +92934,65369,Male,Loyal Customer,56,Business travel,Eco,631,3,4,4,4,3,3,3,4,1,3,4,3,2,3,96,145.0,neutral or dissatisfied +92935,56294,Female,Loyal Customer,52,Personal Travel,Eco,2227,1,5,1,2,4,4,5,5,5,1,5,5,5,4,1,7.0,neutral or dissatisfied +92936,54448,Female,disloyal Customer,46,Business travel,Business,844,2,2,2,2,4,2,1,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +92937,54603,Male,Loyal Customer,25,Business travel,Eco,965,5,3,3,3,5,5,5,5,2,1,1,1,5,5,15,44.0,satisfied +92938,99993,Male,Loyal Customer,44,Business travel,Business,3306,1,1,1,1,2,4,5,5,5,5,5,4,5,5,20,21.0,satisfied +92939,68784,Female,Loyal Customer,29,Business travel,Business,2327,3,5,5,5,3,3,3,3,3,1,3,3,4,3,115,103.0,neutral or dissatisfied +92940,113627,Male,Loyal Customer,43,Personal Travel,Eco,258,2,5,0,4,5,0,5,5,4,4,2,1,4,5,2,12.0,neutral or dissatisfied +92941,18049,Female,disloyal Customer,26,Business travel,Eco,488,3,1,3,2,1,3,1,1,1,1,3,4,2,1,35,18.0,neutral or dissatisfied +92942,50331,Female,disloyal Customer,39,Business travel,Eco,373,1,4,2,5,1,2,3,1,4,4,2,2,4,1,0,0.0,neutral or dissatisfied +92943,70813,Male,disloyal Customer,18,Business travel,Eco,624,2,2,2,4,2,2,2,2,1,2,4,4,4,2,0,0.0,neutral or dissatisfied +92944,104477,Female,Loyal Customer,49,Personal Travel,Eco,1671,4,4,5,3,5,5,1,3,3,5,3,5,3,1,1,0.0,neutral or dissatisfied +92945,89377,Male,Loyal Customer,59,Business travel,Business,151,2,2,2,2,5,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +92946,83611,Male,disloyal Customer,47,Business travel,Eco,409,1,0,1,3,5,1,5,5,3,5,4,3,4,5,51,49.0,neutral or dissatisfied +92947,88053,Male,Loyal Customer,49,Business travel,Business,581,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,3.0,satisfied +92948,44111,Female,Loyal Customer,53,Personal Travel,Eco,257,4,2,0,4,4,3,4,4,4,0,5,1,4,1,24,34.0,neutral or dissatisfied +92949,120920,Female,Loyal Customer,55,Business travel,Business,1872,1,1,1,1,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +92950,16760,Male,Loyal Customer,52,Business travel,Eco,569,2,5,5,5,2,2,2,2,1,4,3,3,1,2,107,106.0,satisfied +92951,28971,Male,disloyal Customer,29,Business travel,Eco,987,2,2,2,1,1,2,1,1,2,5,3,2,4,1,0,0.0,neutral or dissatisfied +92952,123017,Female,Loyal Customer,40,Business travel,Business,3333,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +92953,58763,Male,Loyal Customer,44,Business travel,Business,2465,4,4,4,4,4,5,4,3,3,3,3,5,3,5,6,0.0,satisfied +92954,48517,Female,Loyal Customer,27,Business travel,Business,1864,2,2,2,2,4,5,4,4,5,2,4,4,1,4,0,0.0,satisfied +92955,78990,Male,Loyal Customer,39,Business travel,Business,2473,1,1,5,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +92956,47668,Male,Loyal Customer,40,Business travel,Eco,869,5,3,3,3,5,5,5,5,1,5,2,1,3,5,0,0.0,satisfied +92957,71933,Female,disloyal Customer,9,Business travel,Business,1744,4,4,4,3,5,4,5,5,5,3,3,3,5,5,4,5.0,satisfied +92958,40918,Female,Loyal Customer,14,Personal Travel,Eco,532,3,5,3,4,4,3,2,4,3,4,5,3,5,4,0,0.0,neutral or dissatisfied +92959,45354,Male,Loyal Customer,34,Personal Travel,Eco,222,2,5,2,4,1,2,1,1,4,4,5,2,2,1,0,0.0,neutral or dissatisfied +92960,1764,Male,Loyal Customer,47,Business travel,Business,408,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +92961,15459,Male,Loyal Customer,72,Business travel,Eco,433,5,3,3,3,5,5,5,5,2,4,3,4,1,5,0,0.0,satisfied +92962,67572,Female,Loyal Customer,28,Business travel,Business,1438,1,1,1,1,4,4,4,4,5,5,4,3,5,4,0,13.0,satisfied +92963,54825,Female,Loyal Customer,35,Business travel,Business,2820,4,4,4,4,5,4,3,4,4,4,4,1,4,1,62,47.0,satisfied +92964,90728,Male,Loyal Customer,59,Business travel,Business,2284,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +92965,84325,Male,Loyal Customer,42,Business travel,Business,3475,4,4,5,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +92966,10834,Male,disloyal Customer,27,Business travel,Eco,166,2,3,2,3,4,2,4,4,4,4,4,2,3,4,0,0.0,neutral or dissatisfied +92967,100871,Female,Loyal Customer,45,Personal Travel,Eco,1605,1,4,1,2,3,5,4,3,3,1,3,3,3,3,2,0.0,neutral or dissatisfied +92968,24833,Male,Loyal Customer,36,Business travel,Eco,861,4,2,2,2,4,4,4,4,1,2,3,4,2,4,0,0.0,satisfied +92969,64788,Female,Loyal Customer,60,Business travel,Business,354,3,3,3,3,5,5,4,5,5,4,5,3,5,5,116,97.0,satisfied +92970,91057,Male,Loyal Customer,28,Personal Travel,Eco,271,4,0,4,4,1,4,1,1,5,2,4,2,5,1,0,0.0,neutral or dissatisfied +92971,6937,Male,Loyal Customer,56,Business travel,Business,501,5,5,3,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +92972,114168,Male,Loyal Customer,50,Business travel,Business,2352,3,3,2,3,4,4,5,5,5,5,5,3,5,5,31,27.0,satisfied +92973,52342,Female,Loyal Customer,33,Business travel,Business,1957,2,2,3,2,1,3,1,5,5,5,5,3,5,5,0,0.0,satisfied +92974,83688,Male,Loyal Customer,33,Business travel,Business,3789,4,3,5,3,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +92975,26599,Male,Loyal Customer,40,Business travel,Business,404,4,4,4,4,1,4,5,4,4,4,4,5,4,1,6,11.0,satisfied +92976,46395,Female,Loyal Customer,58,Personal Travel,Eco,911,3,5,3,5,3,4,2,1,1,3,1,3,1,4,127,121.0,neutral or dissatisfied +92977,89458,Male,Loyal Customer,35,Personal Travel,Eco,134,2,4,2,3,5,2,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +92978,3229,Male,disloyal Customer,38,Business travel,Business,419,5,5,5,2,4,5,3,4,5,5,4,5,4,4,0,0.0,satisfied +92979,102468,Female,Loyal Customer,7,Personal Travel,Eco,407,2,4,2,3,5,2,5,5,3,2,5,5,1,5,8,10.0,neutral or dissatisfied +92980,37069,Male,disloyal Customer,17,Business travel,Eco,1072,3,3,3,2,5,3,5,5,1,2,5,3,1,5,0,2.0,neutral or dissatisfied +92981,68707,Male,Loyal Customer,42,Personal Travel,Eco,175,3,5,3,2,5,3,5,5,3,4,5,4,5,5,27,24.0,neutral or dissatisfied +92982,116012,Male,Loyal Customer,43,Personal Travel,Eco,308,3,4,3,4,2,3,3,2,2,5,3,2,4,2,0,0.0,neutral or dissatisfied +92983,25539,Female,Loyal Customer,13,Personal Travel,Eco,547,5,5,5,2,4,5,4,4,2,1,3,4,5,4,0,1.0,satisfied +92984,91249,Female,Loyal Customer,47,Personal Travel,Eco,404,4,2,4,3,4,4,4,4,4,4,4,2,4,4,9,0.0,satisfied +92985,63079,Male,Loyal Customer,65,Personal Travel,Eco,967,4,5,4,1,3,4,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +92986,118825,Female,disloyal Customer,45,Business travel,Business,325,2,2,2,1,5,2,5,5,3,5,5,5,5,5,15,0.0,neutral or dissatisfied +92987,38787,Female,Loyal Customer,38,Business travel,Business,1715,2,2,2,2,2,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +92988,72634,Female,Loyal Customer,49,Personal Travel,Eco,1119,2,5,3,3,4,4,5,5,5,3,5,4,5,4,0,19.0,neutral or dissatisfied +92989,87965,Male,disloyal Customer,25,Business travel,Business,250,5,0,5,3,1,5,1,1,4,5,5,4,5,1,11,4.0,satisfied +92990,1041,Female,Loyal Customer,71,Business travel,Eco,102,4,5,5,5,5,3,4,4,4,4,4,2,4,1,8,6.0,neutral or dissatisfied +92991,105693,Female,disloyal Customer,47,Business travel,Business,787,1,1,1,4,2,1,2,2,3,5,5,3,5,2,13,6.0,neutral or dissatisfied +92992,15976,Male,Loyal Customer,42,Business travel,Business,794,3,4,3,3,3,4,4,2,2,3,2,4,2,3,0,0.0,satisfied +92993,79507,Male,Loyal Customer,40,Business travel,Business,712,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,6.0,satisfied +92994,100624,Female,disloyal Customer,25,Business travel,Eco Plus,1121,2,2,2,3,2,5,5,2,2,3,2,5,4,5,218,422.0,neutral or dissatisfied +92995,96024,Female,Loyal Customer,39,Business travel,Eco,1069,1,4,4,4,1,1,1,1,1,1,2,1,3,1,19,10.0,neutral or dissatisfied +92996,71194,Male,Loyal Customer,35,Business travel,Business,3714,2,2,2,2,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +92997,118019,Male,Loyal Customer,48,Personal Travel,Eco,1037,2,1,2,2,2,2,2,2,2,3,1,4,1,2,0,0.0,neutral or dissatisfied +92998,30832,Male,Loyal Customer,39,Personal Travel,Eco,1026,3,5,3,2,5,3,5,5,4,2,4,4,5,5,1,4.0,neutral or dissatisfied +92999,99192,Male,Loyal Customer,46,Business travel,Eco Plus,351,3,3,3,3,3,3,3,3,4,2,3,4,3,3,0,0.0,neutral or dissatisfied +93000,27381,Male,Loyal Customer,39,Business travel,Eco,954,5,2,2,2,5,5,5,5,5,4,1,1,1,5,2,23.0,satisfied +93001,44580,Male,Loyal Customer,36,Business travel,Business,3422,1,2,2,2,3,1,1,1,1,1,1,2,1,2,3,36.0,neutral or dissatisfied +93002,119230,Female,Loyal Customer,16,Personal Travel,Eco,331,3,4,5,4,4,5,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +93003,99444,Male,Loyal Customer,10,Personal Travel,Eco Plus,337,1,5,1,3,2,1,2,2,3,4,4,3,4,2,1,2.0,neutral or dissatisfied +93004,27360,Female,Loyal Customer,48,Business travel,Business,697,5,5,5,5,5,5,2,4,4,4,4,4,4,4,0,0.0,satisfied +93005,22375,Male,disloyal Customer,24,Business travel,Eco,145,3,1,3,4,3,3,3,3,2,2,4,3,3,3,48,32.0,neutral or dissatisfied +93006,84461,Female,Loyal Customer,10,Personal Travel,Eco,290,2,4,2,3,2,2,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +93007,26164,Female,Loyal Customer,57,Business travel,Eco,515,1,5,5,5,4,4,4,1,1,1,1,3,1,3,46,44.0,neutral or dissatisfied +93008,5101,Female,Loyal Customer,8,Personal Travel,Eco,122,4,1,0,4,2,0,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +93009,17763,Male,Loyal Customer,43,Business travel,Business,2634,3,3,3,3,3,4,4,5,5,5,5,3,5,4,14,0.0,satisfied +93010,1095,Female,Loyal Customer,61,Personal Travel,Eco,229,2,5,2,3,4,5,5,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +93011,58084,Female,Loyal Customer,58,Business travel,Business,2904,1,1,1,1,4,4,4,4,4,4,4,4,4,3,6,0.0,satisfied +93012,121034,Female,Loyal Customer,25,Personal Travel,Eco,951,2,5,2,2,2,2,1,2,2,4,4,2,1,2,0,0.0,neutral or dissatisfied +93013,71744,Male,Loyal Customer,28,Personal Travel,Business,1744,3,5,3,2,5,3,5,5,4,4,3,5,5,5,2,17.0,neutral or dissatisfied +93014,15730,Female,Loyal Customer,18,Personal Travel,Eco,419,3,5,3,4,3,3,3,3,3,3,5,5,5,3,9,38.0,neutral or dissatisfied +93015,883,Female,Loyal Customer,15,Business travel,Business,270,2,3,3,3,2,2,2,2,3,2,3,4,2,2,0,0.0,neutral or dissatisfied +93016,68487,Female,Loyal Customer,37,Business travel,Eco,1303,3,3,3,3,3,2,3,3,3,5,3,1,4,3,0,22.0,neutral or dissatisfied +93017,86099,Male,Loyal Customer,47,Personal Travel,Business,306,3,5,3,2,3,5,4,1,1,3,2,5,1,4,0,0.0,neutral or dissatisfied +93018,60031,Male,Loyal Customer,56,Personal Travel,Eco,997,1,5,1,5,4,1,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +93019,83584,Female,Loyal Customer,13,Personal Travel,Eco,936,2,3,2,3,3,2,3,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +93020,89767,Female,Loyal Customer,9,Personal Travel,Eco,1096,2,2,2,4,3,2,3,3,3,1,4,2,3,3,0,0.0,neutral or dissatisfied +93021,32807,Male,Loyal Customer,33,Business travel,Business,2771,1,5,5,5,4,3,1,4,3,1,4,1,4,4,0,0.0,neutral or dissatisfied +93022,109313,Male,Loyal Customer,61,Business travel,Business,2929,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +93023,40001,Male,Loyal Customer,54,Personal Travel,Business,575,2,4,2,3,2,4,5,3,3,2,3,5,3,3,0,4.0,neutral or dissatisfied +93024,18020,Male,Loyal Customer,45,Business travel,Eco Plus,241,4,5,5,5,4,4,4,4,2,4,2,2,3,4,0,0.0,satisfied +93025,109186,Female,disloyal Customer,41,Business travel,Eco,616,4,3,4,4,5,4,5,5,2,2,3,4,4,5,15,17.0,neutral or dissatisfied +93026,120998,Female,Loyal Customer,54,Business travel,Eco,520,4,2,4,4,5,3,4,4,4,4,4,2,4,1,7,104.0,neutral or dissatisfied +93027,115504,Female,Loyal Customer,34,Business travel,Business,371,1,1,4,1,2,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +93028,7101,Female,Loyal Customer,48,Personal Travel,Eco,177,4,2,4,3,2,4,3,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +93029,56201,Male,Loyal Customer,61,Personal Travel,Eco,1400,1,4,2,3,4,2,4,4,5,4,3,4,4,4,0,0.0,neutral or dissatisfied +93030,111880,Female,Loyal Customer,72,Business travel,Business,628,4,3,3,3,4,4,3,4,4,4,4,4,4,4,1,2.0,neutral or dissatisfied +93031,61468,Female,Loyal Customer,60,Business travel,Business,2419,2,2,2,2,4,5,5,5,5,4,5,5,5,3,11,0.0,satisfied +93032,4667,Female,Loyal Customer,62,Business travel,Business,2690,4,3,5,3,3,4,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +93033,37039,Male,Loyal Customer,46,Business travel,Eco,994,2,1,1,1,3,2,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +93034,95369,Female,Loyal Customer,57,Personal Travel,Eco,248,2,5,2,2,3,5,4,3,3,2,3,5,3,3,25,21.0,neutral or dissatisfied +93035,16148,Female,Loyal Customer,58,Business travel,Business,277,4,4,4,4,3,2,3,4,4,4,4,1,4,2,0,0.0,satisfied +93036,66524,Female,Loyal Customer,36,Business travel,Business,447,4,4,4,4,4,5,5,4,4,4,4,4,4,3,5,11.0,satisfied +93037,1159,Male,Loyal Customer,33,Personal Travel,Eco,247,3,2,0,2,3,0,3,3,2,2,3,1,3,3,0,7.0,neutral or dissatisfied +93038,29407,Female,Loyal Customer,19,Personal Travel,Eco,2541,2,4,2,1,2,5,5,2,2,4,3,5,5,5,1,5.0,neutral or dissatisfied +93039,90858,Female,Loyal Customer,39,Business travel,Eco,444,3,2,2,2,3,3,3,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +93040,105618,Male,Loyal Customer,43,Business travel,Business,2259,5,3,5,5,4,5,5,5,5,4,5,5,5,3,11,18.0,satisfied +93041,95457,Male,Loyal Customer,50,Business travel,Business,1895,5,5,5,5,2,5,4,5,5,5,4,5,5,4,0,0.0,satisfied +93042,107277,Female,Loyal Customer,42,Business travel,Business,2257,1,3,3,3,5,4,4,1,1,1,1,3,1,2,10,3.0,neutral or dissatisfied +93043,34597,Male,disloyal Customer,35,Business travel,Eco,1598,2,2,2,2,2,2,2,2,3,4,1,3,2,2,0,26.0,neutral or dissatisfied +93044,86496,Male,Loyal Customer,68,Personal Travel,Eco,762,2,2,2,4,2,2,1,2,4,4,3,2,4,2,0,0.0,neutral or dissatisfied +93045,92688,Female,Loyal Customer,38,Personal Travel,Eco,507,0,4,0,4,1,0,1,1,4,4,4,5,4,1,13,1.0,satisfied +93046,56904,Female,Loyal Customer,33,Business travel,Business,2454,3,5,5,5,3,3,3,2,4,3,3,3,3,3,7,16.0,neutral or dissatisfied +93047,111224,Female,Loyal Customer,56,Personal Travel,Eco,1447,1,4,1,4,2,1,1,5,5,1,5,5,5,1,19,20.0,neutral or dissatisfied +93048,75729,Male,Loyal Customer,46,Business travel,Business,868,2,2,2,2,3,4,5,5,5,5,5,4,5,5,1,5.0,satisfied +93049,112853,Male,Loyal Customer,44,Business travel,Business,2632,2,2,5,2,5,4,4,3,3,3,3,3,3,3,11,0.0,satisfied +93050,49921,Female,Loyal Customer,47,Business travel,Eco,156,5,5,5,5,4,3,4,4,4,5,4,2,4,4,0,0.0,satisfied +93051,86548,Female,Loyal Customer,41,Business travel,Business,3757,2,2,2,2,2,4,4,4,4,4,4,5,4,3,20,2.0,satisfied +93052,109026,Female,Loyal Customer,57,Business travel,Business,994,3,4,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +93053,49375,Female,Loyal Customer,43,Business travel,Business,3434,0,3,0,4,4,2,4,4,4,4,4,5,4,5,7,11.0,satisfied +93054,115874,Female,Loyal Customer,32,Business travel,Business,2509,3,3,3,3,5,5,5,5,3,2,1,4,1,5,0,0.0,satisfied +93055,58141,Male,Loyal Customer,52,Business travel,Business,925,3,1,1,1,2,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +93056,77355,Female,disloyal Customer,20,Business travel,Eco,532,2,1,2,3,5,2,5,5,4,5,4,2,3,5,0,9.0,neutral or dissatisfied +93057,43301,Female,disloyal Customer,36,Business travel,Eco,387,2,1,2,3,3,2,2,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +93058,50326,Female,Loyal Customer,39,Business travel,Business,3823,4,4,4,4,3,1,2,5,5,5,5,3,5,2,27,14.0,satisfied +93059,53476,Female,Loyal Customer,25,Business travel,Eco,2419,2,2,2,2,2,4,2,4,2,2,3,2,4,2,0,0.0,neutral or dissatisfied +93060,36439,Female,Loyal Customer,7,Personal Travel,Eco,369,2,4,2,2,3,2,3,3,5,3,1,1,1,3,0,0.0,neutral or dissatisfied +93061,29171,Female,Loyal Customer,22,Business travel,Eco Plus,937,2,3,3,3,2,2,1,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +93062,104885,Female,Loyal Customer,25,Personal Travel,Eco,327,3,0,2,4,5,2,1,5,4,4,4,4,5,5,40,36.0,neutral or dissatisfied +93063,52102,Male,Loyal Customer,7,Personal Travel,Eco,438,2,5,2,3,4,2,2,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +93064,45001,Female,Loyal Customer,39,Business travel,Eco,222,3,3,3,3,3,3,3,3,3,3,5,5,5,3,0,0.0,satisfied +93065,15323,Male,Loyal Customer,30,Business travel,Business,589,3,3,3,3,4,4,4,4,3,2,3,3,3,4,0,0.0,satisfied +93066,33300,Male,Loyal Customer,25,Personal Travel,Eco Plus,102,2,5,2,1,4,2,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +93067,112929,Female,Loyal Customer,25,Personal Travel,Eco,1129,3,5,3,2,5,3,5,5,3,2,4,3,4,5,15,15.0,neutral or dissatisfied +93068,43688,Female,Loyal Customer,36,Business travel,Business,257,2,2,2,2,2,1,4,4,4,4,4,5,4,4,0,1.0,satisfied +93069,19029,Male,Loyal Customer,44,Personal Travel,Eco,871,4,1,4,3,5,4,5,5,4,5,3,4,2,5,0,0.0,satisfied +93070,11277,Male,Loyal Customer,51,Personal Travel,Eco,191,2,1,2,2,5,2,5,5,1,3,3,2,2,5,0,0.0,neutral or dissatisfied +93071,40382,Female,Loyal Customer,55,Personal Travel,Eco,1250,3,3,3,4,1,3,4,2,2,3,2,4,2,3,0,3.0,neutral or dissatisfied +93072,80602,Female,Loyal Customer,56,Personal Travel,Eco,2039,3,4,2,3,2,4,5,1,1,2,5,4,1,4,44,12.0,neutral or dissatisfied +93073,69758,Female,Loyal Customer,48,Personal Travel,Eco,1085,3,4,3,3,5,4,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +93074,122903,Female,Loyal Customer,39,Business travel,Business,2551,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +93075,26628,Male,Loyal Customer,45,Business travel,Business,404,5,5,5,5,1,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +93076,128604,Female,Loyal Customer,56,Business travel,Business,3846,5,2,5,5,2,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +93077,93007,Female,Loyal Customer,59,Business travel,Business,1524,1,4,4,4,2,2,3,1,1,1,1,1,1,2,0,6.0,neutral or dissatisfied +93078,40569,Male,disloyal Customer,38,Business travel,Eco,411,4,1,4,3,5,4,3,5,2,4,4,1,4,5,0,0.0,neutral or dissatisfied +93079,21500,Male,Loyal Customer,63,Personal Travel,Eco,377,1,2,1,2,4,1,4,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +93080,78561,Male,Loyal Customer,58,Business travel,Eco Plus,266,3,2,2,2,3,3,3,3,3,5,4,2,4,3,4,10.0,neutral or dissatisfied +93081,64628,Female,Loyal Customer,53,Business travel,Business,190,3,3,3,3,3,5,4,5,5,4,4,4,5,4,0,0.0,satisfied +93082,22503,Male,Loyal Customer,36,Personal Travel,Eco,143,3,3,0,3,2,0,2,2,1,5,4,3,1,2,0,0.0,neutral or dissatisfied +93083,97712,Male,Loyal Customer,16,Business travel,Eco,942,1,1,3,1,1,1,2,1,1,3,3,4,2,1,25,20.0,neutral or dissatisfied +93084,29386,Female,Loyal Customer,28,Business travel,Eco,2466,2,2,5,2,2,2,2,3,4,2,4,2,3,2,0,56.0,neutral or dissatisfied +93085,102526,Female,Loyal Customer,25,Personal Travel,Eco,226,1,2,1,4,3,1,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +93086,28557,Female,Loyal Customer,26,Business travel,Eco Plus,2688,5,3,3,3,5,5,5,5,3,3,4,2,5,5,11,14.0,satisfied +93087,75814,Female,Loyal Customer,24,Personal Travel,Eco Plus,868,4,2,4,3,1,4,1,1,3,2,2,1,2,1,16,11.0,neutral or dissatisfied +93088,103248,Male,Loyal Customer,45,Business travel,Eco,667,3,1,1,1,2,3,2,2,1,1,3,1,3,2,124,112.0,neutral or dissatisfied +93089,16969,Female,Loyal Customer,35,Business travel,Eco Plus,195,4,1,4,1,4,4,4,4,2,5,4,2,5,4,0,0.0,satisfied +93090,88903,Male,Loyal Customer,17,Personal Travel,Eco,859,0,2,0,3,1,0,1,1,4,5,3,1,4,1,0,0.0,satisfied +93091,97665,Female,Loyal Customer,54,Business travel,Business,491,1,1,2,1,5,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +93092,33670,Male,Loyal Customer,29,Personal Travel,Eco Plus,413,4,5,4,2,1,4,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +93093,17456,Male,Loyal Customer,27,Personal Travel,Eco Plus,351,1,1,1,4,5,1,5,5,4,4,3,3,3,5,13,4.0,neutral or dissatisfied +93094,34796,Female,Loyal Customer,14,Personal Travel,Eco,209,3,5,3,3,4,3,4,4,5,4,5,3,1,4,38,39.0,neutral or dissatisfied +93095,75106,Male,Loyal Customer,62,Personal Travel,Business,1726,3,4,3,3,3,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +93096,64348,Female,Loyal Customer,31,Business travel,Business,3188,5,5,5,5,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +93097,73164,Female,Loyal Customer,55,Personal Travel,Eco,1145,3,5,3,4,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +93098,71454,Female,Loyal Customer,59,Business travel,Business,867,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +93099,16106,Female,disloyal Customer,22,Business travel,Eco,349,3,0,3,5,2,3,2,2,1,2,3,3,4,2,0,2.0,neutral or dissatisfied +93100,50367,Male,disloyal Customer,50,Business travel,Eco,156,1,0,1,4,1,1,1,1,4,4,1,4,1,1,0,0.0,neutral or dissatisfied +93101,23455,Female,Loyal Customer,30,Business travel,Eco,604,5,4,4,4,5,5,5,5,2,5,5,2,3,5,5,0.0,satisfied +93102,70112,Female,Loyal Customer,30,Business travel,Business,2795,2,1,1,1,2,2,2,2,2,5,4,3,4,2,35,38.0,neutral or dissatisfied +93103,16328,Female,Loyal Customer,46,Personal Travel,Eco,628,2,4,2,3,2,5,5,4,2,5,5,5,4,5,161,161.0,neutral or dissatisfied +93104,101699,Male,Loyal Customer,35,Business travel,Eco Plus,1500,4,3,3,3,4,5,4,4,1,5,2,1,2,4,14,0.0,satisfied +93105,17559,Male,disloyal Customer,28,Business travel,Eco,1034,3,3,3,2,5,3,5,5,2,1,2,5,3,5,0,0.0,neutral or dissatisfied +93106,123125,Male,Loyal Customer,31,Business travel,Business,3323,2,5,5,5,2,2,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +93107,103840,Male,Loyal Customer,41,Business travel,Business,979,3,3,3,3,4,5,4,5,5,4,5,3,5,4,3,0.0,satisfied +93108,92907,Female,Loyal Customer,57,Business travel,Business,3841,3,3,3,3,5,4,4,5,5,5,4,3,5,5,0,14.0,satisfied +93109,111462,Male,Loyal Customer,53,Personal Travel,Eco,1024,1,4,2,4,4,2,4,4,3,5,3,2,1,4,3,0.0,neutral or dissatisfied +93110,16995,Female,Loyal Customer,56,Business travel,Eco,843,5,2,2,2,2,2,3,4,4,5,4,5,4,5,0,0.0,satisfied +93111,105150,Female,disloyal Customer,39,Business travel,Business,289,3,3,3,3,4,3,4,4,3,2,4,4,4,4,10,9.0,neutral or dissatisfied +93112,23757,Male,Loyal Customer,11,Personal Travel,Eco,1083,1,4,1,1,4,1,4,4,3,3,5,3,4,4,0,6.0,neutral or dissatisfied +93113,9143,Female,Loyal Customer,65,Business travel,Business,3146,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,12.0,satisfied +93114,39920,Male,Loyal Customer,32,Business travel,Business,1087,5,5,2,5,4,4,4,4,1,1,4,1,1,4,0,0.0,satisfied +93115,30058,Female,Loyal Customer,37,Business travel,Eco,171,2,4,4,4,2,2,2,2,3,4,4,2,3,2,298,281.0,neutral or dissatisfied +93116,17683,Male,Loyal Customer,58,Business travel,Business,3206,5,5,5,5,3,1,5,5,5,5,5,5,5,2,0,0.0,satisfied +93117,104918,Female,Loyal Customer,58,Business travel,Business,2120,2,2,2,2,2,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +93118,49261,Male,Loyal Customer,56,Business travel,Eco,363,4,4,2,2,4,4,4,4,4,5,5,2,4,4,3,0.0,satisfied +93119,64258,Female,Loyal Customer,52,Business travel,Business,1660,2,3,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +93120,36159,Male,disloyal Customer,28,Business travel,Eco,795,3,3,3,4,1,3,1,1,5,4,4,2,2,1,42,43.0,neutral or dissatisfied +93121,24840,Female,Loyal Customer,25,Personal Travel,Eco,894,2,2,2,4,3,2,3,3,3,1,3,2,4,3,61,55.0,neutral or dissatisfied +93122,42213,Male,Loyal Customer,42,Business travel,Business,1634,5,5,5,5,1,5,2,5,5,5,5,5,5,3,0,0.0,satisfied +93123,48205,Male,Loyal Customer,20,Business travel,Eco,259,3,3,5,3,3,3,3,3,4,5,3,2,4,3,0,0.0,neutral or dissatisfied +93124,7507,Female,Loyal Customer,50,Business travel,Business,1995,5,5,5,5,5,5,4,4,4,4,4,4,4,4,88,56.0,satisfied +93125,91705,Male,Loyal Customer,44,Business travel,Business,588,3,3,3,3,4,4,4,3,4,5,4,4,3,4,146,131.0,satisfied +93126,78563,Female,Loyal Customer,57,Business travel,Business,630,2,2,2,2,4,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +93127,27573,Female,Loyal Customer,25,Personal Travel,Eco,978,4,5,4,2,5,4,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +93128,64503,Male,Loyal Customer,51,Business travel,Business,3038,4,5,5,5,2,4,3,4,4,3,4,2,4,3,6,2.0,neutral or dissatisfied +93129,90778,Female,Loyal Customer,52,Business travel,Business,646,5,5,5,5,5,5,5,5,5,5,5,4,5,4,20,14.0,satisfied +93130,9738,Male,Loyal Customer,39,Business travel,Business,908,5,5,5,5,5,5,5,5,5,5,5,5,5,4,97,82.0,satisfied +93131,59942,Male,Loyal Customer,52,Business travel,Eco,1068,2,3,3,3,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +93132,15173,Female,disloyal Customer,28,Business travel,Eco,416,3,0,3,5,2,3,3,2,5,2,2,1,4,2,3,0.0,neutral or dissatisfied +93133,51718,Male,Loyal Customer,41,Personal Travel,Eco,451,3,4,3,2,3,3,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +93134,53196,Male,Loyal Customer,58,Business travel,Business,589,1,1,1,1,3,4,4,1,1,1,1,3,1,3,13,8.0,neutral or dissatisfied +93135,12793,Male,Loyal Customer,26,Business travel,Eco,641,3,3,3,3,3,4,5,3,2,1,1,5,1,3,0,0.0,satisfied +93136,21961,Male,Loyal Customer,49,Business travel,Business,500,2,1,5,5,1,3,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +93137,124773,Female,Loyal Customer,39,Business travel,Business,3700,1,4,4,4,1,4,3,1,1,1,1,3,1,4,105,121.0,neutral or dissatisfied +93138,58055,Male,Loyal Customer,59,Business travel,Business,589,3,3,3,3,3,4,5,4,4,5,4,3,4,3,2,16.0,satisfied +93139,93239,Male,Loyal Customer,46,Business travel,Business,3834,4,4,4,4,5,5,5,5,5,5,5,3,5,3,11,1.0,satisfied +93140,110715,Male,disloyal Customer,22,Business travel,Eco,997,3,3,3,3,4,3,4,4,2,5,4,2,3,4,0,,neutral or dissatisfied +93141,23798,Male,Loyal Customer,46,Business travel,Business,2747,4,1,1,1,5,3,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +93142,13468,Male,Loyal Customer,24,Personal Travel,Eco,491,1,0,1,1,4,1,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +93143,70009,Female,Loyal Customer,57,Business travel,Business,1883,4,4,4,4,3,5,4,3,3,4,3,5,3,3,0,5.0,satisfied +93144,67466,Female,Loyal Customer,55,Personal Travel,Eco,721,3,5,3,5,4,4,4,5,5,3,5,4,5,5,21,37.0,neutral or dissatisfied +93145,9512,Female,Loyal Customer,49,Personal Travel,Eco,239,3,5,3,1,2,1,4,4,4,3,3,3,4,3,0,0.0,neutral or dissatisfied +93146,84157,Male,Loyal Customer,42,Business travel,Business,1355,3,3,3,3,5,5,5,4,5,5,4,5,5,5,423,403.0,satisfied +93147,78717,Male,Loyal Customer,58,Business travel,Business,554,5,4,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +93148,114605,Male,Loyal Customer,44,Business travel,Business,325,1,1,1,1,5,4,5,5,5,5,5,4,5,4,66,80.0,satisfied +93149,20991,Male,disloyal Customer,40,Business travel,Eco Plus,689,1,0,0,3,3,0,3,3,1,1,4,3,4,3,0,1.0,neutral or dissatisfied +93150,62976,Female,disloyal Customer,25,Business travel,Eco,967,2,2,2,4,1,2,2,1,3,1,3,3,4,1,85,94.0,neutral or dissatisfied +93151,11971,Male,Loyal Customer,53,Business travel,Business,667,4,4,4,4,3,5,4,5,5,5,5,5,5,3,10,24.0,satisfied +93152,21292,Male,Loyal Customer,52,Business travel,Eco,620,2,2,2,2,2,2,2,2,2,3,2,2,3,2,0,4.0,neutral or dissatisfied +93153,67343,Male,Loyal Customer,63,Personal Travel,Eco,1471,4,4,4,3,3,4,3,3,4,4,4,4,4,3,0,7.0,neutral or dissatisfied +93154,33290,Female,Loyal Customer,10,Personal Travel,Eco Plus,216,4,4,4,3,5,4,5,5,3,2,4,4,3,5,0,0.0,neutral or dissatisfied +93155,72677,Male,Loyal Customer,37,Personal Travel,Eco,1121,4,4,4,2,5,4,5,5,4,4,5,5,4,5,0,6.0,neutral or dissatisfied +93156,128481,Male,Loyal Customer,61,Personal Travel,Eco,370,3,3,3,4,2,3,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +93157,88162,Female,Loyal Customer,35,Business travel,Business,545,2,2,2,2,5,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +93158,37781,Female,Loyal Customer,29,Business travel,Eco Plus,1010,0,0,0,3,3,0,3,3,4,1,1,1,2,3,0,0.0,satisfied +93159,54623,Male,Loyal Customer,43,Business travel,Eco,965,4,4,4,4,4,4,4,4,4,3,5,5,2,4,0,1.0,satisfied +93160,55048,Male,disloyal Customer,22,Business travel,Eco,1379,5,5,5,2,4,5,4,4,5,3,4,4,4,4,9,19.0,satisfied +93161,100896,Male,disloyal Customer,30,Business travel,Eco,377,2,2,2,4,4,2,4,4,4,5,4,3,4,4,35,29.0,neutral or dissatisfied +93162,19252,Male,disloyal Customer,26,Business travel,Eco,420,4,0,4,4,5,4,5,5,2,2,3,2,5,5,16,0.0,satisfied +93163,15246,Male,Loyal Customer,60,Personal Travel,Eco,529,1,4,1,5,2,1,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +93164,78484,Male,Loyal Customer,41,Business travel,Eco,526,1,0,0,3,4,1,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +93165,123688,Male,Loyal Customer,43,Business travel,Business,2008,1,1,1,1,4,1,3,5,5,5,3,1,5,5,0,0.0,satisfied +93166,109116,Male,Loyal Customer,50,Business travel,Eco Plus,781,1,2,2,2,1,1,1,1,1,5,1,3,1,1,13,20.0,neutral or dissatisfied +93167,25980,Male,Loyal Customer,30,Personal Travel,Business,577,1,4,1,2,1,1,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +93168,6808,Male,Loyal Customer,20,Personal Travel,Eco,235,3,4,0,3,4,0,4,4,4,1,3,1,4,4,30,35.0,neutral or dissatisfied +93169,8927,Male,disloyal Customer,39,Business travel,Business,984,1,2,2,2,5,2,5,5,3,2,5,5,5,5,2,0.0,neutral or dissatisfied +93170,17008,Female,Loyal Customer,54,Business travel,Business,3899,4,4,2,4,4,4,5,5,5,5,5,5,5,3,104,98.0,satisfied +93171,92290,Female,Loyal Customer,49,Business travel,Business,1814,4,4,4,4,2,5,4,4,4,4,4,4,4,3,8,16.0,satisfied +93172,4350,Male,Loyal Customer,52,Business travel,Business,2957,2,2,2,2,4,5,5,4,4,4,4,3,4,4,0,29.0,satisfied +93173,32375,Male,Loyal Customer,43,Business travel,Business,3305,0,3,0,4,4,5,5,5,5,1,1,2,5,1,0,0.0,satisfied +93174,26256,Female,disloyal Customer,29,Business travel,Eco Plus,406,3,3,3,2,3,3,3,3,3,2,2,4,3,3,24,20.0,neutral or dissatisfied +93175,31708,Female,Loyal Customer,64,Personal Travel,Eco,853,2,4,2,1,3,4,5,3,3,2,5,4,3,5,0,0.0,neutral or dissatisfied +93176,20263,Female,disloyal Customer,21,Business travel,Eco,228,2,4,2,3,1,2,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +93177,17717,Female,Loyal Customer,53,Business travel,Business,3703,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +93178,45451,Male,Loyal Customer,55,Business travel,Business,674,1,2,2,2,3,3,3,1,1,1,1,1,1,3,0,1.0,neutral or dissatisfied +93179,77441,Female,Loyal Customer,36,Personal Travel,Eco Plus,626,2,4,2,3,1,2,5,1,5,3,5,4,4,1,23,22.0,neutral or dissatisfied +93180,91466,Male,disloyal Customer,50,Business travel,Eco,459,2,0,2,1,2,2,2,2,1,5,3,1,3,2,69,67.0,neutral or dissatisfied +93181,23382,Male,Loyal Customer,9,Personal Travel,Eco Plus,1162,2,1,2,4,3,2,3,3,2,5,2,1,3,3,60,44.0,neutral or dissatisfied +93182,5199,Male,Loyal Customer,57,Business travel,Business,3697,3,3,4,3,5,5,4,5,5,5,5,5,5,5,45,32.0,satisfied +93183,27848,Female,Loyal Customer,9,Personal Travel,Eco,1448,1,1,1,1,2,1,2,2,4,1,1,2,1,2,0,0.0,neutral or dissatisfied +93184,21671,Female,Loyal Customer,40,Business travel,Eco,708,1,2,2,2,1,1,1,1,3,5,4,1,4,1,10,6.0,neutral or dissatisfied +93185,71201,Male,Loyal Customer,29,Business travel,Business,733,1,1,1,1,4,4,4,4,5,4,4,4,5,4,107,138.0,satisfied +93186,4203,Male,Loyal Customer,48,Business travel,Business,888,2,2,2,2,3,5,4,4,4,5,4,5,4,5,9,12.0,satisfied +93187,109877,Female,Loyal Customer,55,Business travel,Business,1204,1,1,1,1,3,4,5,5,5,5,5,4,5,5,33,,satisfied +93188,2070,Female,Loyal Customer,50,Business travel,Business,2303,3,5,5,5,2,2,3,3,3,4,3,2,3,4,0,6.0,neutral or dissatisfied +93189,73788,Male,Loyal Customer,39,Business travel,Business,1920,2,2,2,2,4,5,4,5,5,5,4,4,5,5,9,6.0,satisfied +93190,63555,Male,Loyal Customer,33,Business travel,Eco Plus,1009,2,3,3,3,2,2,2,2,3,4,3,1,3,2,3,0.0,neutral or dissatisfied +93191,14951,Male,Loyal Customer,58,Business travel,Business,154,3,2,2,2,3,4,4,2,2,2,3,1,2,2,1,6.0,neutral or dissatisfied +93192,59614,Male,disloyal Customer,35,Business travel,Business,787,2,2,2,3,5,2,5,5,3,5,5,5,4,5,70,49.0,neutral or dissatisfied +93193,118872,Male,Loyal Customer,39,Business travel,Business,1136,3,3,3,3,2,4,5,4,4,4,4,4,4,5,5,0.0,satisfied +93194,8730,Male,Loyal Customer,25,Personal Travel,Eco,227,1,4,1,3,2,1,2,2,5,5,1,3,1,2,0,1.0,neutral or dissatisfied +93195,97076,Male,disloyal Customer,55,Business travel,Business,1390,5,5,5,4,2,5,4,2,3,2,5,3,5,2,31,28.0,satisfied +93196,113937,Male,Loyal Customer,53,Business travel,Business,1728,2,2,4,2,2,4,5,2,2,2,2,5,2,3,1,0.0,satisfied +93197,22175,Female,Loyal Customer,51,Business travel,Business,633,1,1,1,1,3,3,4,3,3,3,3,4,3,4,69,59.0,satisfied +93198,71197,Female,Loyal Customer,43,Business travel,Business,2710,5,1,5,5,3,4,5,3,3,3,3,5,3,3,26,10.0,satisfied +93199,73461,Female,Loyal Customer,14,Personal Travel,Eco,1144,1,5,1,2,2,1,2,2,2,5,5,5,1,2,0,18.0,neutral or dissatisfied +93200,105388,Male,Loyal Customer,48,Business travel,Eco,369,4,2,2,2,4,4,4,4,3,3,4,1,3,4,0,0.0,neutral or dissatisfied +93201,117976,Female,Loyal Customer,9,Personal Travel,Eco,255,3,4,3,1,1,3,1,1,4,3,4,4,4,1,23,21.0,neutral or dissatisfied +93202,66587,Male,Loyal Customer,40,Business travel,Business,761,3,3,3,3,2,5,5,5,5,5,5,5,5,5,2,8.0,satisfied +93203,89791,Female,Loyal Customer,58,Personal Travel,Eco,1035,3,4,3,5,3,5,5,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +93204,110008,Female,disloyal Customer,20,Business travel,Business,1142,5,0,5,3,2,5,4,2,3,4,4,3,5,2,0,0.0,satisfied +93205,35862,Female,Loyal Customer,31,Personal Travel,Eco,937,3,3,3,1,1,3,1,1,3,1,5,4,4,1,0,0.0,neutral or dissatisfied +93206,77374,Female,disloyal Customer,24,Business travel,Business,626,3,4,3,3,1,3,2,1,3,2,4,2,3,1,0,0.0,neutral or dissatisfied +93207,120676,Female,Loyal Customer,39,Business travel,Business,2412,3,2,2,2,5,4,3,3,3,3,3,2,3,2,3,9.0,neutral or dissatisfied +93208,104129,Male,Loyal Customer,54,Business travel,Business,1649,3,3,3,3,4,4,4,4,4,4,4,3,4,5,27,41.0,satisfied +93209,48154,Male,Loyal Customer,47,Business travel,Eco,236,4,1,1,1,4,4,4,4,3,3,3,3,3,4,0,0.0,satisfied +93210,14829,Female,Loyal Customer,26,Personal Travel,Eco,314,4,5,4,5,3,4,3,3,4,5,5,3,4,3,11,8.0,neutral or dissatisfied +93211,26820,Male,Loyal Customer,32,Business travel,Business,224,0,5,0,5,1,1,1,1,2,1,2,5,4,1,7,8.0,satisfied +93212,35583,Male,Loyal Customer,51,Business travel,Eco Plus,1097,4,5,5,5,4,4,4,4,5,4,1,4,3,4,0,0.0,satisfied +93213,103750,Female,Loyal Customer,35,Business travel,Business,3652,4,4,4,4,5,4,5,5,5,5,5,3,5,5,7,3.0,satisfied +93214,122467,Female,Loyal Customer,46,Business travel,Business,575,4,2,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +93215,12812,Female,disloyal Customer,30,Business travel,Eco,641,3,0,3,3,4,3,4,4,2,2,2,5,3,4,0,0.0,neutral or dissatisfied +93216,112300,Male,Loyal Customer,39,Business travel,Business,171,4,4,3,4,2,4,1,4,4,4,4,3,4,4,2,0.0,satisfied +93217,92060,Male,Loyal Customer,42,Business travel,Business,1454,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +93218,85585,Female,Loyal Customer,24,Business travel,Business,2740,4,4,4,4,4,4,4,4,3,1,4,4,3,4,3,0.0,neutral or dissatisfied +93219,97186,Male,Loyal Customer,35,Personal Travel,Eco,1390,3,5,3,3,4,3,4,4,2,1,4,2,4,4,31,46.0,neutral or dissatisfied +93220,62297,Male,Loyal Customer,20,Business travel,Business,2391,2,1,1,1,2,2,2,2,2,4,3,2,3,2,0,0.0,neutral or dissatisfied +93221,114244,Male,Loyal Customer,18,Business travel,Business,3200,3,1,4,1,3,3,3,3,4,1,3,1,3,3,13,14.0,neutral or dissatisfied +93222,1349,Male,Loyal Customer,58,Business travel,Business,2430,3,2,5,5,3,3,4,3,3,3,3,4,3,4,4,10.0,neutral or dissatisfied +93223,129166,Female,Loyal Customer,24,Personal Travel,Eco,679,4,1,5,2,3,5,3,3,1,2,3,4,3,3,3,9.0,satisfied +93224,27791,Male,Loyal Customer,35,Business travel,Eco,1533,4,1,1,1,4,4,4,4,5,2,4,2,5,4,0,0.0,satisfied +93225,95682,Male,Loyal Customer,70,Business travel,Business,419,1,4,5,5,1,3,3,1,1,1,1,1,1,1,66,53.0,neutral or dissatisfied +93226,77688,Male,Loyal Customer,38,Business travel,Business,3538,3,1,3,1,1,4,4,3,3,3,3,2,3,4,16,16.0,neutral or dissatisfied +93227,18318,Female,disloyal Customer,28,Business travel,Eco,715,2,2,2,4,2,2,2,2,3,3,5,3,1,2,0,0.0,neutral or dissatisfied +93228,99638,Female,Loyal Customer,70,Personal Travel,Eco Plus,1224,2,4,2,1,5,2,3,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +93229,59244,Female,Loyal Customer,52,Personal Travel,Eco,4817,3,5,3,5,3,1,4,4,4,3,4,4,4,4,45,16.0,neutral or dissatisfied +93230,82091,Male,Loyal Customer,56,Business travel,Business,1950,2,2,4,2,4,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +93231,70577,Male,Loyal Customer,20,Personal Travel,Eco,1258,1,5,1,4,2,1,2,2,3,5,3,5,4,2,0,10.0,neutral or dissatisfied +93232,73378,Male,Loyal Customer,15,Business travel,Business,1005,1,1,1,1,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +93233,119313,Male,disloyal Customer,22,Business travel,Business,214,5,0,5,4,5,5,2,5,4,3,4,1,3,5,0,0.0,satisfied +93234,54432,Male,Loyal Customer,61,Personal Travel,Eco,305,3,4,4,1,2,4,1,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +93235,5409,Female,Loyal Customer,26,Personal Travel,Eco,785,3,5,3,4,2,3,3,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +93236,5808,Male,Loyal Customer,17,Business travel,Business,273,2,5,5,5,2,2,2,2,4,5,3,1,4,2,3,10.0,neutral or dissatisfied +93237,42932,Male,Loyal Customer,51,Business travel,Business,3724,1,1,1,1,2,4,4,5,5,5,5,3,5,4,6,0.0,satisfied +93238,37635,Male,Loyal Customer,65,Personal Travel,Eco,1074,3,4,3,3,5,3,5,5,5,3,5,3,4,5,11,20.0,neutral or dissatisfied +93239,106252,Female,Loyal Customer,18,Business travel,Business,1167,4,4,1,4,5,5,5,5,5,3,4,4,4,5,0,0.0,satisfied +93240,42706,Male,Loyal Customer,63,Personal Travel,Eco,604,5,4,5,3,2,5,2,2,5,4,5,5,4,2,0,0.0,satisfied +93241,6754,Female,disloyal Customer,23,Business travel,Eco,122,1,0,1,2,4,1,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +93242,72015,Female,Loyal Customer,50,Business travel,Business,3711,3,3,3,3,5,5,5,3,2,5,5,5,3,5,3,0.0,satisfied +93243,79410,Female,disloyal Customer,79,Business travel,Eco,102,2,2,2,3,3,2,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +93244,15248,Male,Loyal Customer,7,Personal Travel,Eco,445,2,2,2,3,3,2,3,3,2,4,3,3,3,3,8,20.0,neutral or dissatisfied +93245,31065,Female,Loyal Customer,19,Personal Travel,Eco,862,3,5,3,2,3,3,3,3,4,2,5,5,4,3,78,91.0,neutral or dissatisfied +93246,56267,Male,Loyal Customer,51,Personal Travel,Eco,404,1,4,4,4,2,4,3,2,1,2,2,1,1,2,0,8.0,neutral or dissatisfied +93247,110401,Female,disloyal Customer,29,Business travel,Eco,919,4,4,4,4,5,4,5,5,2,3,3,1,4,5,17,9.0,neutral or dissatisfied +93248,121580,Female,disloyal Customer,26,Business travel,Eco,1032,3,3,3,3,5,3,5,5,4,5,3,3,4,5,1,0.0,neutral or dissatisfied +93249,109461,Male,disloyal Customer,21,Business travel,Eco,966,4,4,4,3,2,4,2,2,5,3,5,4,4,2,0,4.0,satisfied +93250,118248,Female,disloyal Customer,28,Business travel,Business,1972,1,1,1,3,2,1,2,2,4,5,5,3,5,2,1,0.0,neutral or dissatisfied +93251,117086,Male,Loyal Customer,25,Business travel,Business,1766,2,5,5,5,2,2,2,2,4,2,3,4,3,2,0,26.0,neutral or dissatisfied +93252,112083,Female,Loyal Customer,54,Personal Travel,Eco,1491,1,2,1,2,4,1,3,4,4,1,4,4,4,4,34,6.0,neutral or dissatisfied +93253,103043,Male,Loyal Customer,34,Business travel,Business,1882,2,4,4,4,4,4,4,2,2,3,2,2,2,4,15,3.0,neutral or dissatisfied +93254,40153,Male,Loyal Customer,49,Business travel,Business,463,4,4,4,4,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +93255,48297,Male,Loyal Customer,51,Business travel,Business,1499,1,1,1,1,4,4,4,1,1,1,1,3,1,2,9,8.0,neutral or dissatisfied +93256,23500,Male,Loyal Customer,52,Business travel,Eco,303,5,5,5,5,5,5,5,5,4,1,1,3,5,5,66,63.0,satisfied +93257,97478,Female,Loyal Customer,46,Business travel,Eco,756,4,5,5,5,1,3,2,3,3,4,3,1,3,2,22,32.0,neutral or dissatisfied +93258,63840,Male,disloyal Customer,25,Business travel,Business,1192,0,3,0,3,2,0,4,2,4,3,4,4,4,2,0,0.0,satisfied +93259,63743,Female,Loyal Customer,30,Personal Travel,Eco,1660,4,4,4,2,4,4,4,4,5,5,3,3,5,4,2,0.0,neutral or dissatisfied +93260,84641,Male,Loyal Customer,39,Business travel,Eco Plus,269,2,5,5,5,2,2,2,2,2,3,4,2,3,2,56,31.0,neutral or dissatisfied +93261,129867,Female,disloyal Customer,20,Business travel,Eco,447,4,0,4,3,4,4,5,4,3,3,4,4,5,4,0,4.0,satisfied +93262,65123,Male,Loyal Customer,68,Personal Travel,Eco,469,3,4,3,4,3,3,2,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +93263,124728,Male,Loyal Customer,21,Personal Travel,Eco,399,2,4,2,3,1,2,1,1,4,5,5,4,4,1,4,17.0,neutral or dissatisfied +93264,118672,Male,Loyal Customer,37,Business travel,Business,3652,2,2,2,2,5,2,2,5,5,5,5,1,5,4,10,2.0,satisfied +93265,114576,Female,Loyal Customer,56,Business travel,Business,372,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +93266,48122,Female,disloyal Customer,29,Business travel,Eco,192,1,0,0,5,2,0,2,2,1,1,1,5,4,2,0,0.0,neutral or dissatisfied +93267,8072,Female,disloyal Customer,38,Business travel,Business,294,3,3,3,2,1,3,1,1,3,5,5,4,4,1,0,0.0,satisfied +93268,6580,Female,disloyal Customer,26,Business travel,Eco,607,2,3,2,3,2,2,2,2,3,5,3,2,2,2,0,0.0,neutral or dissatisfied +93269,105763,Male,Loyal Customer,44,Business travel,Eco,525,1,3,3,3,1,1,1,1,3,3,4,1,3,1,0,30.0,neutral or dissatisfied +93270,98862,Female,Loyal Customer,41,Personal Travel,Eco,1751,4,2,4,3,1,4,1,1,1,3,3,4,3,1,0,,neutral or dissatisfied +93271,123493,Female,Loyal Customer,40,Business travel,Business,2296,5,5,5,5,4,3,5,4,4,5,4,3,4,3,1,0.0,satisfied +93272,86594,Male,Loyal Customer,53,Business travel,Business,746,4,4,4,4,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +93273,102269,Female,Loyal Customer,39,Business travel,Business,3784,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +93274,112095,Female,Loyal Customer,47,Business travel,Business,2383,1,1,1,1,5,4,5,4,4,4,4,3,4,5,28,14.0,satisfied +93275,88996,Female,disloyal Customer,16,Business travel,Eco,1184,3,4,4,3,3,4,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +93276,69952,Female,Loyal Customer,12,Personal Travel,Eco,2174,5,2,5,4,2,5,4,2,2,5,4,4,4,2,0,0.0,satisfied +93277,111368,Female,Loyal Customer,26,Business travel,Business,2026,1,1,1,1,5,5,5,5,4,3,5,5,4,5,3,20.0,satisfied +93278,83428,Male,Loyal Customer,27,Personal Travel,Eco,632,1,4,1,1,4,1,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +93279,65623,Male,Loyal Customer,28,Personal Travel,Eco,175,3,3,3,1,1,3,1,1,1,4,5,5,5,1,0,0.0,neutral or dissatisfied +93280,128370,Male,Loyal Customer,50,Business travel,Business,338,0,0,0,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +93281,33078,Female,Loyal Customer,51,Personal Travel,Eco,163,3,5,3,2,4,5,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +93282,62135,Female,Loyal Customer,59,Business travel,Business,2454,2,2,3,2,4,4,4,5,5,4,4,4,5,4,134,123.0,satisfied +93283,69371,Female,Loyal Customer,30,Business travel,Business,3270,4,2,2,2,4,4,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +93284,59155,Male,Loyal Customer,35,Business travel,Business,1846,4,4,4,4,4,4,4,5,5,5,5,4,5,4,111,88.0,satisfied +93285,21598,Male,Loyal Customer,41,Business travel,Business,3525,2,2,4,2,4,2,5,4,4,4,4,1,4,1,21,27.0,satisfied +93286,127233,Male,Loyal Customer,64,Personal Travel,Eco,1460,2,4,2,4,3,2,3,3,4,3,5,5,5,3,0,22.0,neutral or dissatisfied +93287,45412,Male,Loyal Customer,49,Business travel,Eco,458,4,4,4,4,4,4,4,4,3,3,5,1,4,4,0,0.0,satisfied +93288,72158,Female,Loyal Customer,31,Personal Travel,Eco,731,2,5,2,1,1,2,1,1,4,3,3,4,5,1,0,0.0,neutral or dissatisfied +93289,91475,Male,Loyal Customer,28,Personal Travel,Eco,859,1,5,1,2,2,1,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +93290,122142,Female,disloyal Customer,26,Business travel,Business,544,2,0,2,5,5,2,4,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +93291,78504,Male,disloyal Customer,65,Business travel,Business,266,4,4,4,2,2,4,2,2,1,1,2,4,1,2,0,0.0,neutral or dissatisfied +93292,66405,Female,disloyal Customer,62,Business travel,Eco,1562,3,3,3,2,3,3,3,3,2,1,2,2,3,3,4,0.0,neutral or dissatisfied +93293,36467,Male,Loyal Customer,46,Personal Travel,Eco Plus,867,4,5,4,4,4,4,1,4,4,4,5,1,1,4,0,0.0,neutral or dissatisfied +93294,26384,Female,Loyal Customer,11,Personal Travel,Eco Plus,861,4,1,4,2,2,4,2,2,2,2,3,1,2,2,16,11.0,satisfied +93295,68833,Female,Loyal Customer,27,Business travel,Business,1550,3,3,3,3,2,2,2,2,4,4,5,5,4,2,0,0.0,satisfied +93296,28046,Female,Loyal Customer,34,Business travel,Business,1739,3,3,3,3,2,5,3,5,5,5,5,2,5,5,0,0.0,satisfied +93297,67097,Female,disloyal Customer,23,Business travel,Eco,1119,2,3,3,4,4,3,4,4,3,1,4,1,3,4,78,111.0,neutral or dissatisfied +93298,63613,Female,disloyal Customer,23,Business travel,Business,1440,0,5,0,4,3,0,3,3,4,5,4,4,5,3,0,0.0,satisfied +93299,83743,Female,disloyal Customer,21,Business travel,Eco,1183,1,1,1,3,2,1,2,2,4,5,2,4,2,2,0,0.0,neutral or dissatisfied +93300,67420,Female,Loyal Customer,32,Business travel,Business,641,1,1,1,1,1,2,1,1,5,2,4,3,5,1,0,0.0,satisfied +93301,83026,Male,Loyal Customer,54,Business travel,Business,1145,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +93302,81113,Female,disloyal Customer,25,Business travel,Business,991,4,2,4,1,2,4,2,2,5,5,5,4,5,2,0,0.0,satisfied +93303,84220,Male,disloyal Customer,30,Business travel,Eco,432,1,0,1,2,3,1,5,3,1,4,3,4,3,3,0,14.0,neutral or dissatisfied +93304,53790,Male,disloyal Customer,21,Business travel,Eco,140,1,4,1,4,3,1,3,3,5,3,3,1,2,3,0,0.0,neutral or dissatisfied +93305,125903,Female,Loyal Customer,29,Personal Travel,Eco,993,2,5,2,4,4,2,4,4,3,2,5,3,4,4,11,5.0,neutral or dissatisfied +93306,76870,Male,disloyal Customer,25,Business travel,Eco,427,3,3,3,3,3,3,3,3,3,1,3,1,3,3,45,20.0,neutral or dissatisfied +93307,25017,Male,Loyal Customer,33,Business travel,Business,2529,2,5,5,5,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +93308,110147,Male,Loyal Customer,9,Business travel,Business,3868,3,3,3,3,3,3,3,3,2,4,3,3,2,3,8,19.0,neutral or dissatisfied +93309,127319,Male,Loyal Customer,51,Business travel,Business,1979,3,3,3,3,4,5,5,5,5,5,5,3,5,4,47,35.0,satisfied +93310,11867,Female,Loyal Customer,51,Business travel,Eco,912,2,4,4,4,2,2,3,2,2,2,2,2,2,1,30,34.0,neutral or dissatisfied +93311,43065,Male,disloyal Customer,35,Business travel,Business,236,1,1,1,4,2,1,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +93312,35551,Female,Loyal Customer,53,Personal Travel,Eco,1069,1,2,1,3,4,3,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +93313,21669,Female,Loyal Customer,49,Business travel,Business,3713,1,1,1,1,3,4,3,5,5,5,5,2,5,2,72,64.0,satisfied +93314,75863,Male,Loyal Customer,17,Business travel,Eco Plus,1437,3,5,5,5,3,2,4,3,2,2,4,2,3,3,26,53.0,neutral or dissatisfied +93315,28931,Female,Loyal Customer,57,Business travel,Eco,679,4,3,3,3,4,2,5,4,4,4,4,2,4,1,0,0.0,satisfied +93316,52541,Male,disloyal Customer,20,Business travel,Eco,119,2,0,2,1,3,2,3,3,3,5,3,5,2,3,0,0.0,neutral or dissatisfied +93317,30877,Female,Loyal Customer,28,Personal Travel,Eco,1546,1,5,1,4,2,1,2,2,4,5,5,4,5,2,7,17.0,neutral or dissatisfied +93318,55707,Male,Loyal Customer,17,Personal Travel,Eco,1062,2,5,2,2,2,2,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +93319,119261,Female,Loyal Customer,57,Business travel,Business,2233,2,2,2,2,4,4,5,4,4,4,5,5,4,3,27,0.0,satisfied +93320,87049,Female,Loyal Customer,48,Business travel,Business,594,2,2,2,2,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +93321,74414,Female,disloyal Customer,60,Business travel,Business,1235,4,4,4,2,1,4,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +93322,43801,Female,Loyal Customer,16,Personal Travel,Eco,913,2,2,1,4,1,1,1,1,1,1,3,4,4,1,0,0.0,neutral or dissatisfied +93323,20458,Female,Loyal Customer,43,Business travel,Business,3465,1,3,3,3,5,4,3,2,2,2,1,2,2,1,0,0.0,neutral or dissatisfied +93324,11778,Female,Loyal Customer,53,Personal Travel,Eco,429,3,4,3,3,5,1,1,1,1,3,5,2,1,2,0,0.0,neutral or dissatisfied +93325,106035,Female,Loyal Customer,46,Personal Travel,Eco,682,4,4,4,3,4,1,1,1,1,4,4,2,1,1,15,7.0,neutral or dissatisfied +93326,10859,Male,Loyal Customer,42,Business travel,Business,2392,5,5,5,5,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +93327,72797,Male,Loyal Customer,14,Personal Travel,Eco,1045,2,2,2,2,5,2,1,5,2,3,3,1,2,5,0,,neutral or dissatisfied +93328,8563,Female,Loyal Customer,58,Business travel,Business,109,2,1,1,1,3,3,3,1,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +93329,8653,Female,disloyal Customer,32,Business travel,Business,227,2,1,1,1,2,1,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +93330,25266,Male,Loyal Customer,70,Business travel,Eco,425,3,5,5,5,3,3,3,3,2,4,3,2,4,3,0,0.0,neutral or dissatisfied +93331,39360,Female,Loyal Customer,28,Business travel,Eco,826,5,2,2,2,5,5,5,5,3,2,5,1,2,5,43,39.0,satisfied +93332,100111,Male,Loyal Customer,44,Business travel,Business,3138,4,4,2,4,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +93333,44635,Male,Loyal Customer,57,Business travel,Eco,67,3,5,5,5,3,3,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +93334,80540,Male,Loyal Customer,26,Business travel,Business,1747,2,2,5,2,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +93335,7806,Male,disloyal Customer,25,Business travel,Business,710,2,5,3,1,3,3,3,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +93336,123986,Male,disloyal Customer,40,Business travel,Business,184,2,2,2,1,3,2,3,3,4,2,4,4,5,3,0,81.0,neutral or dissatisfied +93337,59045,Male,Loyal Customer,14,Business travel,Business,1846,2,2,2,2,2,2,2,2,4,3,3,3,4,2,26,38.0,neutral or dissatisfied +93338,83212,Female,disloyal Customer,12,Business travel,Eco,1123,2,2,2,3,4,2,4,4,3,4,4,4,4,4,0,10.0,neutral or dissatisfied +93339,15451,Female,Loyal Customer,57,Business travel,Eco,433,4,5,5,5,3,5,3,4,4,4,4,4,4,3,77,98.0,satisfied +93340,29229,Male,disloyal Customer,24,Business travel,Eco,569,2,0,2,2,2,2,2,2,3,5,3,4,1,2,0,5.0,neutral or dissatisfied +93341,60297,Female,Loyal Customer,41,Personal Travel,Eco,783,1,5,1,2,2,1,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +93342,63929,Male,Loyal Customer,21,Personal Travel,Eco,1192,1,4,2,4,4,2,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +93343,21785,Male,Loyal Customer,30,Business travel,Business,352,1,1,1,1,4,4,4,4,5,2,3,3,2,4,0,1.0,satisfied +93344,42375,Female,Loyal Customer,25,Personal Travel,Eco,451,1,4,1,1,1,5,5,5,5,4,5,5,4,5,154,177.0,neutral or dissatisfied +93345,92168,Male,Loyal Customer,56,Business travel,Business,1979,1,1,1,1,2,3,5,4,4,4,4,4,4,5,40,21.0,satisfied +93346,114881,Male,disloyal Customer,27,Business travel,Business,371,3,3,3,5,2,3,1,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +93347,62334,Male,Loyal Customer,53,Personal Travel,Eco,414,2,2,2,3,4,2,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +93348,10668,Male,Loyal Customer,52,Business travel,Business,1766,4,5,4,4,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +93349,37876,Female,disloyal Customer,24,Business travel,Eco,1065,4,4,4,3,2,4,3,2,4,2,4,2,4,2,10,17.0,neutral or dissatisfied +93350,112763,Male,Loyal Customer,46,Business travel,Business,2302,2,2,2,2,4,4,4,4,3,4,5,4,3,4,221,212.0,satisfied +93351,27660,Male,disloyal Customer,27,Business travel,Eco,1216,2,2,2,1,5,2,5,5,3,2,4,1,4,5,0,0.0,neutral or dissatisfied +93352,56856,Female,Loyal Customer,25,Business travel,Business,2425,1,1,1,1,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +93353,44444,Female,Loyal Customer,16,Personal Travel,Eco,420,3,3,3,1,2,3,2,2,3,5,4,4,2,2,0,0.0,neutral or dissatisfied +93354,104843,Female,Loyal Customer,54,Personal Travel,Eco,472,2,3,5,2,3,5,5,3,3,5,1,3,3,2,0,0.0,neutral or dissatisfied +93355,44465,Male,Loyal Customer,39,Business travel,Business,2951,3,3,2,3,5,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +93356,7130,Male,Loyal Customer,38,Business travel,Business,135,2,2,2,2,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +93357,108004,Male,Loyal Customer,17,Personal Travel,Eco,271,5,0,5,5,5,5,5,5,1,2,1,5,3,5,0,0.0,satisfied +93358,1631,Female,disloyal Customer,54,Business travel,Eco,599,2,3,2,4,2,2,2,2,4,4,4,1,3,2,0,0.0,neutral or dissatisfied +93359,62178,Female,disloyal Customer,23,Business travel,Eco,2565,4,4,4,3,1,4,1,1,3,3,4,3,3,1,4,21.0,neutral or dissatisfied +93360,13680,Male,Loyal Customer,36,Business travel,Eco,954,3,3,3,3,3,3,3,1,1,4,2,3,3,3,531,485.0,satisfied +93361,17537,Female,Loyal Customer,68,Business travel,Business,297,5,5,5,5,3,3,4,4,4,5,4,3,4,2,54,67.0,satisfied +93362,28454,Male,Loyal Customer,28,Business travel,Business,2588,2,2,2,2,5,5,5,3,4,3,3,5,2,5,1,12.0,satisfied +93363,122597,Male,Loyal Customer,53,Business travel,Business,728,4,1,1,1,1,2,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +93364,8028,Female,Loyal Customer,48,Business travel,Business,335,2,4,2,2,2,5,4,4,4,4,4,3,4,3,0,8.0,satisfied +93365,59778,Male,Loyal Customer,60,Personal Travel,Eco,1062,2,4,2,4,4,2,4,4,3,4,5,3,4,4,0,2.0,neutral or dissatisfied +93366,106423,Male,Loyal Customer,17,Personal Travel,Eco,488,3,5,3,3,3,3,3,3,5,5,5,3,4,3,31,30.0,neutral or dissatisfied +93367,63110,Female,Loyal Customer,65,Personal Travel,Eco Plus,967,4,4,4,3,5,5,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +93368,118870,Female,Loyal Customer,53,Business travel,Business,1136,4,4,4,4,2,4,4,4,4,4,4,3,4,4,11,24.0,satisfied +93369,78162,Female,Loyal Customer,52,Business travel,Business,2740,2,2,2,2,5,4,5,4,4,5,4,4,4,5,52,57.0,satisfied +93370,85504,Male,Loyal Customer,64,Personal Travel,Eco,332,2,3,2,3,1,2,1,1,5,1,3,3,4,1,0,0.0,neutral or dissatisfied +93371,81175,Male,Loyal Customer,39,Business travel,Business,3240,4,4,5,4,5,4,4,5,5,5,5,4,5,3,12,25.0,satisfied +93372,22020,Female,Loyal Customer,37,Business travel,Eco Plus,448,4,5,5,5,4,4,4,4,5,4,3,2,1,4,0,6.0,satisfied +93373,67215,Male,Loyal Customer,15,Personal Travel,Eco,1119,4,5,4,1,3,4,3,3,5,4,5,3,4,3,6,77.0,neutral or dissatisfied +93374,4573,Male,Loyal Customer,56,Business travel,Business,416,5,5,5,5,2,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +93375,71771,Female,Loyal Customer,47,Business travel,Business,1846,5,5,5,5,4,5,5,3,3,4,3,5,3,5,30,18.0,satisfied +93376,19347,Male,Loyal Customer,39,Business travel,Business,2670,3,3,1,1,2,3,3,3,3,2,3,1,3,1,34,29.0,neutral or dissatisfied +93377,75324,Male,Loyal Customer,22,Business travel,Business,2556,4,4,4,4,3,3,3,3,5,2,5,4,4,3,0,0.0,satisfied +93378,99002,Female,Loyal Customer,50,Business travel,Business,2117,2,2,2,2,2,4,4,4,4,4,4,4,4,5,47,33.0,satisfied +93379,112100,Female,Loyal Customer,50,Business travel,Business,1062,4,1,4,1,4,4,4,4,4,4,4,3,4,4,25,0.0,neutral or dissatisfied +93380,92180,Male,disloyal Customer,41,Business travel,Business,1979,4,4,4,1,4,4,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +93381,18143,Female,Loyal Customer,23,Personal Travel,Eco Plus,750,2,4,2,4,4,2,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +93382,61379,Female,disloyal Customer,30,Business travel,Eco,679,3,3,3,4,2,3,2,2,4,1,4,4,3,2,8,0.0,neutral or dissatisfied +93383,16313,Female,disloyal Customer,40,Business travel,Business,628,3,3,3,2,3,3,3,3,3,1,3,2,3,3,31,54.0,neutral or dissatisfied +93384,55053,Male,disloyal Customer,37,Business travel,Business,1379,2,2,2,2,4,2,3,4,5,4,5,4,5,4,0,3.0,neutral or dissatisfied +93385,104235,Male,Loyal Customer,21,Business travel,Business,3455,2,2,2,2,5,5,5,5,3,4,4,5,5,5,11,19.0,satisfied +93386,106425,Male,Loyal Customer,10,Personal Travel,Eco,551,2,1,2,4,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +93387,17906,Male,Loyal Customer,18,Business travel,Eco,789,4,3,3,3,4,4,5,4,5,3,1,3,1,4,20,6.0,satisfied +93388,114770,Female,Loyal Customer,31,Business travel,Business,296,2,2,2,2,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +93389,47249,Male,Loyal Customer,49,Business travel,Business,3655,3,3,1,3,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +93390,54381,Female,Loyal Customer,39,Business travel,Business,305,0,0,0,5,5,4,5,3,3,3,3,5,3,4,8,1.0,satisfied +93391,78660,Female,Loyal Customer,23,Personal Travel,Eco Plus,2172,4,4,4,4,5,4,5,5,3,4,3,3,4,5,0,4.0,neutral or dissatisfied +93392,119426,Male,Loyal Customer,8,Personal Travel,Eco,399,2,5,2,4,4,2,4,4,3,4,4,3,5,4,1,0.0,neutral or dissatisfied +93393,56232,Female,Loyal Customer,65,Personal Travel,Eco,1608,2,5,1,1,2,5,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +93394,87482,Male,Loyal Customer,53,Business travel,Eco,321,3,5,5,5,3,3,3,3,4,5,4,1,3,3,17,3.0,neutral or dissatisfied +93395,113283,Female,Loyal Customer,66,Business travel,Business,2103,4,4,4,4,4,5,5,5,5,5,5,3,5,5,74,,satisfied +93396,119764,Male,Loyal Customer,58,Personal Travel,Eco Plus,1325,3,5,3,3,2,3,2,2,4,5,5,4,4,2,9,24.0,neutral or dissatisfied +93397,56706,Female,Loyal Customer,30,Personal Travel,Eco,937,3,4,3,4,1,3,1,1,4,1,1,2,4,1,0,0.0,neutral or dissatisfied +93398,56974,Male,Loyal Customer,64,Personal Travel,Eco,2454,5,1,5,4,5,2,2,3,4,3,3,2,4,2,5,0.0,satisfied +93399,97065,Female,Loyal Customer,58,Business travel,Business,1357,3,3,3,3,3,5,4,3,3,3,3,4,3,4,7,4.0,satisfied +93400,87901,Female,Loyal Customer,55,Business travel,Business,3569,1,1,1,1,4,4,5,5,5,5,5,4,5,5,6,3.0,satisfied +93401,52960,Male,Loyal Customer,54,Business travel,Business,2306,2,2,2,2,5,3,4,5,5,4,5,2,5,3,53,52.0,satisfied +93402,112143,Female,Loyal Customer,27,Business travel,Business,1755,4,4,4,4,5,4,5,5,3,4,5,5,5,5,7,0.0,satisfied +93403,84826,Female,Loyal Customer,40,Business travel,Eco,481,2,2,4,4,2,1,2,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +93404,97773,Female,Loyal Customer,57,Business travel,Business,471,5,4,5,5,5,5,5,4,3,5,5,5,4,5,150,159.0,satisfied +93405,98911,Male,Loyal Customer,45,Business travel,Business,479,4,4,2,4,4,4,4,4,4,4,4,5,4,5,25,28.0,satisfied +93406,79098,Female,Loyal Customer,46,Personal Travel,Eco,356,1,4,1,3,5,4,5,4,4,1,2,3,4,5,24,45.0,neutral or dissatisfied +93407,126945,Male,Loyal Customer,40,Business travel,Business,2593,1,1,3,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +93408,95869,Male,Loyal Customer,26,Business travel,Business,2558,4,4,4,4,4,4,4,4,4,5,4,3,5,4,19,1.0,satisfied +93409,28081,Male,Loyal Customer,43,Business travel,Eco,2172,4,2,2,2,4,4,4,4,4,1,5,2,5,4,0,0.0,satisfied +93410,54058,Female,Loyal Customer,32,Business travel,Business,1416,4,4,4,4,1,2,1,1,1,2,5,2,5,1,82,81.0,satisfied +93411,61154,Male,Loyal Customer,31,Business travel,Business,967,2,2,2,2,3,4,3,3,5,3,5,3,4,3,17,12.0,satisfied +93412,34016,Female,Loyal Customer,63,Personal Travel,Eco,1598,5,4,5,3,3,4,5,5,5,5,4,5,5,5,10,19.0,satisfied +93413,49984,Male,disloyal Customer,24,Business travel,Eco,199,3,4,3,2,4,3,1,4,1,4,3,3,2,4,0,0.0,neutral or dissatisfied +93414,33419,Male,Loyal Customer,29,Business travel,Business,2409,1,1,1,1,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +93415,17487,Female,Loyal Customer,46,Business travel,Eco,241,4,5,2,5,1,4,1,4,4,4,4,3,4,4,0,0.0,satisfied +93416,98980,Male,Loyal Customer,69,Personal Travel,Eco,543,2,3,2,5,4,2,4,4,3,3,4,4,1,4,9,0.0,neutral or dissatisfied +93417,91555,Female,Loyal Customer,66,Personal Travel,Eco,680,3,4,3,4,3,5,5,3,3,3,3,4,3,5,1,19.0,neutral or dissatisfied +93418,117479,Female,Loyal Customer,48,Business travel,Business,507,1,1,1,1,2,4,5,5,5,5,5,4,5,4,51,52.0,satisfied +93419,34158,Female,disloyal Customer,21,Business travel,Eco,1046,2,3,3,2,4,3,4,4,1,4,5,1,2,4,41,41.0,neutral or dissatisfied +93420,28963,Female,Loyal Customer,39,Business travel,Business,3078,4,4,4,4,4,1,5,4,4,4,4,5,4,3,2,0.0,satisfied +93421,69682,Female,Loyal Customer,23,Personal Travel,Eco,569,3,4,3,1,3,3,1,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +93422,46874,Male,Loyal Customer,31,Business travel,Business,964,2,2,2,2,5,5,5,5,1,5,3,3,1,5,0,0.0,satisfied +93423,80518,Male,Loyal Customer,61,Personal Travel,Eco,1749,2,1,2,3,3,2,4,3,2,5,4,2,3,3,7,1.0,neutral or dissatisfied +93424,93804,Male,Loyal Customer,46,Personal Travel,Eco,1259,3,4,4,4,5,4,5,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +93425,121370,Female,Loyal Customer,26,Business travel,Eco Plus,1670,2,5,5,5,2,2,4,2,3,4,2,3,3,2,0,0.0,neutral or dissatisfied +93426,84286,Female,Loyal Customer,65,Business travel,Business,3332,4,4,4,4,5,5,5,3,5,5,5,5,4,5,318,313.0,satisfied +93427,16781,Male,Loyal Customer,12,Personal Travel,Eco,569,2,2,2,4,2,3,3,3,4,4,3,3,4,3,179,161.0,neutral or dissatisfied +93428,17324,Female,Loyal Customer,52,Personal Travel,Eco,438,4,4,4,3,4,4,5,5,5,4,1,3,5,3,0,23.0,neutral or dissatisfied +93429,5955,Male,Loyal Customer,50,Business travel,Business,1250,4,4,4,4,5,3,4,4,4,4,4,3,4,1,0,48.0,neutral or dissatisfied +93430,38121,Female,disloyal Customer,29,Business travel,Eco,1237,4,3,3,3,1,3,1,1,1,1,1,4,5,1,0,0.0,satisfied +93431,9532,Female,disloyal Customer,27,Business travel,Business,228,1,1,1,2,3,1,3,3,5,5,4,4,4,3,7,0.0,neutral or dissatisfied +93432,53235,Female,Loyal Customer,18,Personal Travel,Eco,612,5,1,5,1,1,5,1,1,1,4,1,3,1,1,0,4.0,satisfied +93433,43562,Male,Loyal Customer,42,Personal Travel,Eco,637,4,5,4,5,4,4,4,4,3,3,5,4,5,4,20,25.0,neutral or dissatisfied +93434,116665,Female,Loyal Customer,48,Business travel,Business,3837,0,0,0,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +93435,120132,Female,Loyal Customer,26,Business travel,Business,1475,2,2,2,2,4,5,4,4,3,4,4,3,4,4,0,0.0,satisfied +93436,15155,Male,Loyal Customer,52,Personal Travel,Eco,1042,3,4,3,1,2,3,3,2,5,5,4,4,5,2,3,14.0,neutral or dissatisfied +93437,23482,Male,Loyal Customer,56,Personal Travel,Eco,488,2,0,2,2,1,2,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +93438,50471,Male,disloyal Customer,37,Business travel,Eco,421,1,2,1,3,2,1,2,2,3,1,4,2,3,2,7,7.0,neutral or dissatisfied +93439,81587,Female,disloyal Customer,20,Business travel,Eco,334,3,4,3,4,3,3,3,3,4,4,4,4,5,3,1,0.0,neutral or dissatisfied +93440,62161,Female,Loyal Customer,48,Business travel,Business,2454,5,5,5,5,4,5,5,4,4,4,4,4,4,4,5,27.0,satisfied +93441,18938,Female,Loyal Customer,16,Personal Travel,Eco,500,2,3,2,3,3,2,3,3,1,1,1,1,3,3,0,4.0,neutral or dissatisfied +93442,3437,Female,Loyal Customer,62,Personal Travel,Eco,296,1,4,1,3,5,5,4,5,5,1,3,5,5,4,89,79.0,neutral or dissatisfied +93443,22207,Female,Loyal Customer,59,Personal Travel,Eco,773,4,4,4,4,4,5,4,5,5,4,5,4,5,5,21,23.0,neutral or dissatisfied +93444,35957,Male,Loyal Customer,35,Business travel,Eco,231,2,4,4,4,2,2,2,2,4,2,4,4,3,2,0,0.0,neutral or dissatisfied +93445,4157,Female,Loyal Customer,58,Personal Travel,Eco,431,5,5,5,3,3,5,4,2,2,5,2,4,2,5,0,0.0,satisfied +93446,73248,Male,disloyal Customer,37,Business travel,Business,675,1,1,1,3,1,1,1,1,4,5,5,5,4,1,1,16.0,neutral or dissatisfied +93447,7524,Male,Loyal Customer,55,Business travel,Business,3840,5,4,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +93448,126361,Female,Loyal Customer,30,Personal Travel,Eco,650,2,3,2,3,4,2,4,4,3,2,4,2,5,4,50,52.0,neutral or dissatisfied +93449,77805,Male,Loyal Customer,10,Personal Travel,Eco,874,2,1,2,3,2,2,4,2,1,3,4,1,3,2,0,0.0,neutral or dissatisfied +93450,51253,Female,disloyal Customer,26,Business travel,Eco Plus,110,2,0,2,2,5,2,4,5,3,3,5,4,1,5,0,0.0,neutral or dissatisfied +93451,43072,Female,Loyal Customer,18,Personal Travel,Eco,173,3,2,3,3,4,3,4,4,2,2,4,1,3,4,1,0.0,neutral or dissatisfied +93452,3989,Male,Loyal Customer,20,Personal Travel,Business,419,1,2,1,3,3,1,3,3,2,1,4,2,3,3,19,22.0,neutral or dissatisfied +93453,74881,Female,Loyal Customer,46,Business travel,Business,2475,4,4,4,4,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +93454,88556,Female,Loyal Customer,52,Personal Travel,Eco,240,3,4,3,3,3,5,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +93455,22183,Female,disloyal Customer,22,Business travel,Eco,633,2,2,2,3,5,2,5,5,2,5,2,1,2,5,0,0.0,neutral or dissatisfied +93456,96962,Female,Loyal Customer,47,Business travel,Business,883,5,5,5,5,5,5,5,5,5,5,5,4,5,5,4,0.0,satisfied +93457,121008,Female,Loyal Customer,64,Personal Travel,Eco,992,3,4,3,1,2,4,4,5,5,3,5,5,5,5,24,10.0,neutral or dissatisfied +93458,4383,Male,Loyal Customer,66,Personal Travel,Eco,473,4,2,3,3,2,3,2,2,1,4,2,4,2,2,0,0.0,satisfied +93459,96027,Female,disloyal Customer,21,Business travel,Eco,1235,3,3,3,3,5,3,5,5,3,3,4,1,3,5,25,19.0,neutral or dissatisfied +93460,46307,Female,Loyal Customer,34,Personal Travel,Business,1069,3,4,3,3,3,4,5,1,1,3,3,5,1,4,0,0.0,neutral or dissatisfied +93461,58761,Female,disloyal Customer,37,Business travel,Business,1050,5,5,5,1,1,5,1,1,3,3,4,4,4,1,28,41.0,satisfied +93462,82818,Female,Loyal Customer,41,Business travel,Business,645,3,3,3,3,5,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +93463,77146,Male,Loyal Customer,32,Business travel,Business,1865,4,4,4,4,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +93464,52295,Male,Loyal Customer,52,Business travel,Business,2342,5,5,5,5,4,4,1,4,4,4,4,5,4,5,0,5.0,satisfied +93465,39345,Female,Loyal Customer,42,Personal Travel,Eco Plus,774,2,5,2,3,5,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +93466,70395,Male,Loyal Customer,56,Business travel,Business,3249,5,5,5,5,4,3,5,5,5,5,5,5,5,4,105,102.0,satisfied +93467,94316,Male,Loyal Customer,43,Business travel,Business,248,4,4,4,4,4,5,5,5,5,5,5,4,5,3,11,0.0,satisfied +93468,16421,Female,disloyal Customer,50,Business travel,Eco,529,4,0,4,1,2,4,2,2,4,5,2,3,4,2,3,35.0,satisfied +93469,98516,Female,Loyal Customer,34,Business travel,Business,2049,4,4,4,4,1,1,4,5,5,5,5,1,5,1,0,0.0,satisfied +93470,75553,Female,Loyal Customer,46,Business travel,Business,337,3,3,3,3,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +93471,64465,Female,Loyal Customer,43,Business travel,Eco Plus,989,3,3,3,3,4,2,2,3,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +93472,48634,Male,Loyal Customer,49,Business travel,Business,3973,1,1,1,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +93473,108292,Female,Loyal Customer,21,Personal Travel,Business,1750,2,4,2,4,2,5,5,2,1,3,3,5,4,5,209,228.0,neutral or dissatisfied +93474,9678,Male,Loyal Customer,44,Business travel,Business,1854,0,4,0,1,3,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +93475,77160,Male,Loyal Customer,29,Business travel,Business,1450,2,5,5,5,2,2,2,2,3,5,3,1,4,2,0,0.0,neutral or dissatisfied +93476,3966,Female,Loyal Customer,24,Personal Travel,Eco,764,3,4,3,5,2,3,3,2,4,4,3,1,1,2,0,0.0,neutral or dissatisfied +93477,85845,Male,Loyal Customer,35,Personal Travel,Eco,666,5,4,5,3,1,5,1,1,1,5,4,1,3,1,0,0.0,satisfied +93478,90549,Male,disloyal Customer,25,Business travel,Business,250,4,2,4,4,2,4,5,2,4,2,4,3,4,2,0,0.0,satisfied +93479,2819,Male,disloyal Customer,44,Business travel,Business,409,2,2,2,3,1,2,1,1,3,2,5,5,4,1,9,21.0,neutral or dissatisfied +93480,29564,Female,Loyal Customer,31,Business travel,Business,1448,4,4,4,4,3,3,3,3,4,5,1,1,3,3,0,0.0,satisfied +93481,103801,Male,disloyal Customer,38,Business travel,Business,1056,1,1,1,3,3,1,3,3,3,5,5,4,4,3,1,0.0,neutral or dissatisfied +93482,16871,Male,disloyal Customer,36,Business travel,Eco,746,2,2,2,1,1,2,1,1,4,4,5,2,3,1,0,21.0,neutral or dissatisfied +93483,75707,Male,Loyal Customer,46,Business travel,Business,1570,2,2,2,2,2,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +93484,24478,Female,Loyal Customer,53,Business travel,Business,3312,2,2,1,2,4,4,3,2,2,3,2,2,2,2,0,43.0,neutral or dissatisfied +93485,24347,Female,Loyal Customer,50,Personal Travel,Eco,634,4,4,5,5,4,5,5,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +93486,58038,Male,Loyal Customer,7,Personal Travel,Business,612,4,5,4,4,4,4,4,4,5,4,1,3,5,4,61,43.0,neutral or dissatisfied +93487,73455,Female,Loyal Customer,33,Personal Travel,Eco,1197,2,3,3,2,5,3,5,5,3,4,5,2,1,5,32,11.0,neutral or dissatisfied +93488,2705,Male,Loyal Customer,29,Business travel,Business,562,2,5,5,5,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +93489,90039,Male,Loyal Customer,41,Business travel,Business,1586,1,1,1,1,2,5,4,3,3,4,3,4,3,3,15,7.0,satisfied +93490,20013,Male,Loyal Customer,28,Personal Travel,Eco,589,3,5,4,4,2,4,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +93491,45015,Male,Loyal Customer,38,Personal Travel,Eco,359,2,4,2,4,2,2,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +93492,16851,Male,Loyal Customer,60,Personal Travel,Business,746,2,5,2,2,3,1,2,3,3,2,3,1,3,3,28,41.0,neutral or dissatisfied +93493,16731,Female,Loyal Customer,31,Business travel,Business,2789,3,5,5,5,3,3,3,3,1,4,4,1,3,3,11,1.0,neutral or dissatisfied +93494,36392,Male,disloyal Customer,24,Business travel,Eco,1140,4,4,4,3,4,2,2,3,2,3,4,2,4,2,0,0.0,satisfied +93495,127907,Female,Loyal Customer,11,Personal Travel,Eco,1671,2,1,2,4,3,2,3,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +93496,40021,Male,Loyal Customer,46,Business travel,Eco,575,4,2,2,2,4,4,4,4,5,5,1,3,2,4,0,0.0,satisfied +93497,88946,Male,Loyal Customer,47,Business travel,Business,1352,3,3,3,3,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +93498,83807,Female,disloyal Customer,36,Business travel,Business,425,2,3,3,2,2,3,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +93499,58001,Female,Loyal Customer,23,Business travel,Business,1943,2,2,2,2,2,2,2,2,3,3,3,3,4,2,0,10.0,satisfied +93500,64412,Female,Loyal Customer,49,Personal Travel,Eco Plus,1172,2,5,2,3,4,5,5,5,5,2,3,5,5,4,0,0.0,neutral or dissatisfied +93501,121006,Male,Loyal Customer,69,Personal Travel,Eco,992,1,5,1,2,3,1,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +93502,33798,Male,Loyal Customer,43,Business travel,Eco,1428,5,1,1,1,3,5,3,3,2,5,2,3,5,3,0,0.0,satisfied +93503,18575,Male,Loyal Customer,41,Business travel,Eco,190,3,2,2,2,3,3,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +93504,90153,Male,disloyal Customer,44,Business travel,Eco,727,3,3,3,2,4,3,1,4,3,2,1,2,5,4,0,0.0,neutral or dissatisfied +93505,85917,Female,disloyal Customer,20,Business travel,Eco,274,1,1,2,4,5,2,5,5,3,2,4,3,4,5,99,108.0,neutral or dissatisfied +93506,44505,Female,Loyal Customer,46,Personal Travel,Eco,503,3,3,3,2,3,3,4,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +93507,3565,Female,Loyal Customer,44,Business travel,Business,227,4,4,4,4,4,3,2,5,5,5,5,1,5,4,0,0.0,satisfied +93508,61585,Male,Loyal Customer,60,Personal Travel,Business,1464,3,5,4,5,4,5,5,2,2,4,2,5,2,4,0,1.0,neutral or dissatisfied +93509,60121,Male,Loyal Customer,44,Business travel,Eco,1182,3,5,4,4,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +93510,58997,Female,Loyal Customer,41,Business travel,Business,1846,2,2,2,2,5,5,5,5,4,3,4,5,4,5,342,323.0,satisfied +93511,13913,Female,Loyal Customer,39,Business travel,Eco,192,2,5,5,5,2,2,2,2,5,4,5,4,2,2,0,0.0,satisfied +93512,79562,Male,Loyal Customer,42,Business travel,Business,3908,2,5,2,2,3,4,4,5,5,5,5,4,5,5,37,31.0,satisfied +93513,89234,Female,Loyal Customer,39,Business travel,Eco Plus,2139,3,5,5,5,3,3,3,3,1,4,3,3,3,3,0,0.0,neutral or dissatisfied +93514,112277,Female,Loyal Customer,70,Personal Travel,Eco,1506,4,5,4,3,2,3,5,4,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +93515,16157,Male,disloyal Customer,36,Business travel,Business,277,4,4,4,3,2,4,2,2,1,1,4,2,5,2,82,67.0,neutral or dissatisfied +93516,115149,Male,Loyal Customer,42,Business travel,Business,2078,1,1,1,1,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +93517,104414,Female,Loyal Customer,47,Business travel,Business,1036,2,2,2,2,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +93518,111541,Female,Loyal Customer,29,Business travel,Business,3315,2,2,2,2,3,4,3,3,4,4,4,3,4,3,9,9.0,satisfied +93519,6401,Male,Loyal Customer,62,Personal Travel,Eco,240,3,5,3,4,3,3,3,3,2,4,3,3,2,3,7,0.0,neutral or dissatisfied +93520,52215,Male,Loyal Customer,59,Business travel,Business,3843,1,1,1,1,3,3,2,4,4,4,4,4,4,2,0,0.0,satisfied +93521,129337,Female,Loyal Customer,17,Business travel,Business,2475,2,5,4,4,2,2,2,2,4,3,3,2,4,2,3,9.0,neutral or dissatisfied +93522,117356,Male,Loyal Customer,30,Business travel,Business,2050,3,2,2,2,3,3,3,3,2,2,4,1,3,3,0,0.0,neutral or dissatisfied +93523,82801,Male,disloyal Customer,40,Business travel,Business,235,3,3,3,2,3,3,4,3,3,2,5,3,4,3,0,7.0,neutral or dissatisfied +93524,93415,Female,disloyal Customer,21,Business travel,Eco,605,3,3,3,3,3,3,3,3,4,3,3,2,4,3,73,66.0,neutral or dissatisfied +93525,76666,Female,Loyal Customer,37,Personal Travel,Eco,534,3,4,3,3,2,3,2,2,5,3,5,5,4,2,0,56.0,neutral or dissatisfied +93526,46198,Male,Loyal Customer,53,Personal Travel,Eco,423,3,1,3,4,3,3,3,3,4,5,2,1,3,3,20,13.0,neutral or dissatisfied +93527,34316,Female,disloyal Customer,39,Business travel,Eco Plus,280,4,4,4,3,3,4,3,3,3,2,4,1,3,3,0,0.0,neutral or dissatisfied +93528,24853,Male,Loyal Customer,11,Business travel,Eco Plus,861,3,1,2,1,3,4,3,3,3,1,1,2,2,3,0,0.0,satisfied +93529,82152,Male,Loyal Customer,57,Business travel,Eco,311,1,5,5,5,1,1,1,1,2,5,3,3,4,1,26,15.0,neutral or dissatisfied +93530,122777,Female,Loyal Customer,33,Personal Travel,Business,599,2,0,2,3,3,3,3,3,3,2,3,5,3,2,0,7.0,neutral or dissatisfied +93531,57658,Female,Loyal Customer,11,Personal Travel,Eco,200,2,4,0,1,1,0,1,1,5,2,5,4,4,1,34,13.0,neutral or dissatisfied +93532,34696,Female,disloyal Customer,35,Business travel,Eco,301,3,0,2,3,5,2,5,5,4,2,5,1,3,5,0,0.0,neutral or dissatisfied +93533,63432,Male,Loyal Customer,39,Personal Travel,Eco,372,3,0,3,5,5,3,4,5,5,3,4,4,3,5,0,0.0,neutral or dissatisfied +93534,57980,Female,Loyal Customer,19,Business travel,Business,589,1,5,5,5,1,1,1,1,2,1,1,1,1,1,1,0.0,neutral or dissatisfied +93535,53774,Female,Loyal Customer,15,Business travel,Eco Plus,1195,5,4,4,4,5,5,5,5,5,3,3,2,4,5,1,7.0,satisfied +93536,73145,Female,disloyal Customer,22,Business travel,Business,1068,4,0,4,4,3,4,3,3,3,2,4,4,5,3,0,0.0,satisfied +93537,61785,Male,Loyal Customer,47,Personal Travel,Eco,1346,1,5,1,5,5,1,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +93538,21358,Male,Loyal Customer,61,Personal Travel,Eco,761,4,4,4,4,3,4,3,3,4,2,4,5,5,3,0,0.0,satisfied +93539,103320,Male,disloyal Customer,25,Business travel,Business,1371,4,4,4,2,2,4,2,2,4,5,4,3,4,2,0,1.0,satisfied +93540,101240,Male,Loyal Customer,59,Business travel,Business,1587,4,4,4,4,2,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +93541,46429,Female,Loyal Customer,40,Personal Travel,Eco,649,4,1,4,3,3,4,3,3,2,3,4,4,3,3,15,15.0,neutral or dissatisfied +93542,2402,Female,disloyal Customer,23,Business travel,Eco,641,2,4,2,3,1,2,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +93543,97178,Female,Loyal Customer,23,Personal Travel,Eco,1164,2,5,2,5,5,2,5,5,4,5,4,3,5,5,8,6.0,neutral or dissatisfied +93544,69594,Female,Loyal Customer,63,Personal Travel,Eco,2475,2,5,2,3,2,1,1,1,3,5,5,1,2,1,0,0.0,neutral or dissatisfied +93545,40868,Female,Loyal Customer,36,Personal Travel,Eco,590,2,4,3,3,4,3,4,4,4,4,4,1,4,4,2,0.0,neutral or dissatisfied +93546,13335,Female,Loyal Customer,47,Business travel,Eco,748,5,4,4,4,1,2,2,5,5,5,5,1,5,5,0,0.0,satisfied +93547,80459,Male,Loyal Customer,38,Business travel,Business,1299,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +93548,128372,Female,Loyal Customer,42,Business travel,Business,2919,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +93549,34154,Female,Loyal Customer,28,Business travel,Eco,1179,5,3,5,5,5,5,5,5,1,2,5,3,2,5,0,0.0,satisfied +93550,23601,Male,Loyal Customer,48,Business travel,Business,589,1,5,5,5,5,3,3,1,1,1,1,1,1,2,4,27.0,neutral or dissatisfied +93551,71830,Female,Loyal Customer,51,Business travel,Eco,1744,2,1,2,1,4,2,4,2,2,2,2,1,2,3,13,0.0,neutral or dissatisfied +93552,30311,Male,Loyal Customer,22,Personal Travel,Eco,1476,2,5,1,3,3,1,2,3,5,4,5,4,5,3,0,40.0,neutral or dissatisfied +93553,85663,Female,Loyal Customer,59,Business travel,Business,1889,3,3,3,3,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +93554,112162,Male,Loyal Customer,41,Business travel,Business,1982,2,2,2,2,2,5,2,5,5,5,5,1,5,1,0,0.0,satisfied +93555,122523,Male,Loyal Customer,56,Business travel,Business,500,2,2,2,2,3,5,5,4,4,4,4,3,4,4,4,3.0,satisfied +93556,2062,Male,Loyal Customer,56,Business travel,Business,3222,3,3,3,3,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +93557,29940,Female,disloyal Customer,58,Business travel,Eco,261,1,4,1,4,1,1,1,1,4,4,3,1,3,1,18,15.0,neutral or dissatisfied +93558,63356,Male,Loyal Customer,34,Personal Travel,Eco,337,4,5,4,3,1,4,1,1,4,3,5,4,4,1,1,0.0,neutral or dissatisfied +93559,75480,Male,Loyal Customer,10,Personal Travel,Eco,2342,3,4,3,5,4,3,1,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +93560,29360,Female,Loyal Customer,43,Business travel,Business,2378,1,1,5,1,3,4,2,5,5,5,5,1,5,1,38,36.0,satisfied +93561,96746,Male,Loyal Customer,69,Personal Travel,Eco Plus,696,2,5,2,1,4,2,4,4,5,2,4,1,5,4,21,23.0,neutral or dissatisfied +93562,49771,Female,disloyal Customer,39,Business travel,Eco,89,1,3,2,4,5,2,5,5,4,3,2,1,2,5,0,0.0,neutral or dissatisfied +93563,107260,Female,Loyal Customer,40,Business travel,Business,307,4,4,4,4,3,5,4,5,5,5,5,5,5,5,9,7.0,satisfied +93564,102771,Male,Loyal Customer,57,Business travel,Business,1618,5,3,5,5,2,5,5,2,2,2,2,5,2,4,10,0.0,satisfied +93565,65015,Female,disloyal Customer,26,Business travel,Eco,224,2,4,2,4,4,2,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +93566,3479,Male,Loyal Customer,60,Business travel,Business,3026,2,2,2,2,4,4,4,3,5,5,4,4,4,4,304,297.0,satisfied +93567,114675,Female,disloyal Customer,24,Business travel,Eco,296,2,0,2,2,1,2,3,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +93568,28956,Male,disloyal Customer,27,Business travel,Eco,937,0,0,0,5,3,0,3,3,1,3,2,1,3,3,0,0.0,satisfied +93569,109183,Female,Loyal Customer,42,Business travel,Business,2747,2,2,2,2,2,4,5,3,3,3,3,4,3,5,0,4.0,satisfied +93570,123865,Female,disloyal Customer,17,Business travel,Eco,573,3,2,3,3,4,3,4,4,2,5,4,4,4,4,0,13.0,neutral or dissatisfied +93571,66191,Male,Loyal Customer,46,Business travel,Business,3962,1,1,1,1,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +93572,119108,Female,Loyal Customer,42,Business travel,Eco,707,5,4,4,4,4,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +93573,14494,Female,Loyal Customer,11,Personal Travel,Eco Plus,541,1,5,1,2,3,1,3,3,4,4,4,5,4,3,32,33.0,neutral or dissatisfied +93574,92798,Female,Loyal Customer,44,Business travel,Business,1587,2,2,2,2,2,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +93575,80385,Female,disloyal Customer,22,Business travel,Eco,368,4,5,4,1,4,4,4,4,4,1,3,3,5,4,0,0.0,neutral or dissatisfied +93576,35589,Female,Loyal Customer,72,Business travel,Eco Plus,1035,2,3,3,3,2,3,2,2,2,2,2,1,2,3,62,62.0,neutral or dissatisfied +93577,119301,Female,disloyal Customer,22,Business travel,Eco,214,3,2,3,4,4,3,4,4,4,1,4,2,3,4,0,0.0,neutral or dissatisfied +93578,104297,Female,Loyal Customer,27,Personal Travel,Eco,440,3,2,3,2,5,3,4,5,3,1,2,1,3,5,0,0.0,neutral or dissatisfied +93579,64595,Male,Loyal Customer,50,Business travel,Business,2103,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +93580,117749,Male,Loyal Customer,26,Personal Travel,Eco,833,4,4,4,2,3,4,3,3,4,2,5,4,4,3,16,0.0,neutral or dissatisfied +93581,88133,Female,Loyal Customer,46,Business travel,Business,404,3,3,3,3,2,4,5,4,4,4,4,5,4,5,17,6.0,satisfied +93582,51187,Male,Loyal Customer,35,Business travel,Eco Plus,153,1,5,5,5,1,2,1,1,1,2,4,3,4,1,0,0.0,neutral or dissatisfied +93583,82385,Female,Loyal Customer,49,Business travel,Business,2772,3,5,3,3,5,5,4,5,5,5,5,5,5,3,58,44.0,satisfied +93584,87041,Female,disloyal Customer,44,Business travel,Business,645,3,3,3,3,2,3,2,2,3,2,4,4,5,2,10,13.0,neutral or dissatisfied +93585,64211,Female,disloyal Customer,28,Business travel,Business,799,4,4,4,3,4,4,4,4,3,5,4,4,4,4,41,47.0,satisfied +93586,73142,Male,Loyal Customer,12,Personal Travel,Eco,1068,1,5,1,1,4,1,4,4,5,2,5,5,4,4,0,6.0,neutral or dissatisfied +93587,28942,Female,Loyal Customer,24,Business travel,Business,2651,5,5,5,5,4,4,4,4,4,2,3,1,2,4,1,4.0,satisfied +93588,14388,Female,Loyal Customer,40,Business travel,Business,3662,3,3,3,3,1,1,3,4,4,4,4,1,4,4,0,0.0,satisfied +93589,105913,Female,Loyal Customer,41,Personal Travel,Eco,283,2,4,2,2,5,2,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +93590,63118,Female,Loyal Customer,42,Business travel,Business,2249,2,2,3,2,3,4,5,5,5,5,5,5,5,5,1,0.0,satisfied +93591,12274,Male,Loyal Customer,45,Business travel,Eco,192,5,2,2,2,5,5,5,5,5,3,4,3,3,5,0,0.0,satisfied +93592,109496,Female,disloyal Customer,23,Business travel,Eco,993,3,3,3,1,4,3,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +93593,48104,Male,Loyal Customer,49,Business travel,Business,236,3,3,3,3,1,3,4,5,5,5,5,3,5,3,23,20.0,satisfied +93594,119139,Male,Loyal Customer,58,Business travel,Business,3037,4,4,4,4,4,5,5,5,5,4,5,5,5,4,11,40.0,satisfied +93595,55003,Male,Loyal Customer,25,Business travel,Business,1635,3,2,2,2,3,3,3,3,4,1,1,3,3,3,17,6.0,neutral or dissatisfied +93596,23589,Male,disloyal Customer,38,Business travel,Eco,1024,2,2,2,5,4,2,4,4,4,5,4,1,4,4,16,5.0,neutral or dissatisfied +93597,24559,Male,disloyal Customer,39,Business travel,Eco,296,3,0,3,5,4,3,4,4,5,4,2,3,3,4,3,12.0,neutral or dissatisfied +93598,97753,Female,disloyal Customer,65,Business travel,Eco,387,4,1,4,4,1,4,1,1,1,4,4,2,3,1,24,14.0,neutral or dissatisfied +93599,27087,Female,Loyal Customer,55,Personal Travel,Eco,2496,3,4,4,3,4,3,5,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +93600,29071,Female,Loyal Customer,23,Personal Travel,Eco,672,1,4,0,3,4,0,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +93601,110276,Male,Loyal Customer,60,Personal Travel,Business,925,4,3,4,1,2,3,4,4,4,4,4,1,4,4,80,69.0,satisfied +93602,31296,Female,Loyal Customer,31,Personal Travel,Eco Plus,533,1,2,1,3,1,1,1,1,1,4,3,1,4,1,0,0.0,neutral or dissatisfied +93603,19199,Male,Loyal Customer,23,Personal Travel,Eco,542,2,5,2,3,4,2,4,4,5,4,3,4,3,4,0,0.0,neutral or dissatisfied +93604,125114,Female,disloyal Customer,34,Business travel,Eco,361,3,4,3,4,1,3,1,1,3,3,3,1,4,1,31,115.0,neutral or dissatisfied +93605,27646,Female,Loyal Customer,42,Personal Travel,Eco Plus,987,2,4,2,1,3,4,4,4,4,2,4,4,4,3,9,14.0,neutral or dissatisfied +93606,44207,Female,Loyal Customer,33,Personal Travel,Eco,157,4,5,4,2,4,4,4,4,4,2,5,3,5,4,40,84.0,neutral or dissatisfied +93607,33886,Male,Loyal Customer,10,Personal Travel,Eco,994,1,5,1,2,2,1,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +93608,122488,Female,Loyal Customer,21,Personal Travel,Eco,808,1,5,1,2,4,1,4,4,5,4,4,5,4,4,0,15.0,neutral or dissatisfied +93609,51730,Male,Loyal Customer,69,Personal Travel,Eco,237,3,5,3,1,1,3,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +93610,39535,Male,disloyal Customer,28,Business travel,Business,954,4,4,4,5,4,4,4,4,4,5,5,3,5,4,13,14.0,satisfied +93611,86628,Male,Loyal Customer,39,Business travel,Business,746,1,5,5,5,2,3,3,1,1,1,1,4,1,2,22,15.0,neutral or dissatisfied +93612,42296,Female,Loyal Customer,33,Business travel,Eco,550,2,2,2,2,2,2,2,2,1,5,3,2,4,2,0,0.0,neutral or dissatisfied +93613,46455,Female,Loyal Customer,49,Business travel,Business,2551,2,2,2,2,2,5,5,5,5,5,5,4,5,3,40,66.0,satisfied +93614,125735,Female,disloyal Customer,21,Business travel,Eco,814,4,4,4,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +93615,5809,Male,disloyal Customer,39,Business travel,Eco,177,3,2,3,3,3,3,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +93616,45292,Male,Loyal Customer,35,Business travel,Eco,188,4,3,3,3,4,4,4,4,5,1,3,3,2,4,0,0.0,satisfied +93617,75171,Female,Loyal Customer,52,Business travel,Business,1723,5,5,5,5,2,3,4,5,5,5,5,4,5,3,12,0.0,satisfied +93618,100757,Female,Loyal Customer,54,Business travel,Business,1504,1,3,1,1,5,5,4,4,4,5,4,4,4,3,0,14.0,satisfied +93619,86987,Female,Loyal Customer,58,Personal Travel,Eco,907,4,5,3,3,5,5,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +93620,109045,Male,disloyal Customer,26,Business travel,Business,488,2,2,2,1,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +93621,38876,Female,Loyal Customer,59,Business travel,Business,3361,1,4,4,4,5,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +93622,16787,Male,disloyal Customer,29,Business travel,Eco Plus,642,2,2,2,3,2,5,5,3,1,3,4,5,4,5,124,145.0,neutral or dissatisfied +93623,112903,Male,Loyal Customer,53,Business travel,Eco,1313,3,1,2,1,3,3,3,3,2,4,4,4,3,3,1,0.0,neutral or dissatisfied +93624,6256,Male,Loyal Customer,12,Personal Travel,Eco Plus,594,1,4,1,3,3,1,3,3,2,3,3,4,3,3,45,29.0,neutral or dissatisfied +93625,14618,Male,disloyal Customer,24,Business travel,Eco,450,5,4,5,4,5,5,5,5,2,2,4,4,3,5,26,43.0,satisfied +93626,42732,Male,Loyal Customer,52,Business travel,Business,3064,2,2,3,2,4,4,1,3,3,5,3,4,3,2,0,0.0,satisfied +93627,9418,Male,Loyal Customer,9,Personal Travel,Business,288,1,5,5,4,1,5,1,1,3,4,5,4,5,1,51,51.0,neutral or dissatisfied +93628,53562,Male,Loyal Customer,39,Business travel,Business,2416,3,3,3,3,3,3,1,5,5,4,5,3,5,3,0,0.0,satisfied +93629,38686,Female,Loyal Customer,58,Business travel,Eco Plus,2704,4,2,2,2,3,3,1,3,3,4,3,3,3,3,0,0.0,satisfied +93630,41371,Female,Loyal Customer,37,Business travel,Business,2031,3,4,4,4,4,3,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +93631,75907,Female,Loyal Customer,41,Business travel,Business,2040,1,3,3,3,4,3,3,2,2,2,1,3,2,1,0,0.0,neutral or dissatisfied +93632,114305,Male,Loyal Customer,46,Personal Travel,Eco,846,3,4,3,3,1,3,1,1,1,3,2,5,4,1,30,15.0,neutral or dissatisfied +93633,37660,Male,Loyal Customer,41,Personal Travel,Eco,1076,1,5,1,3,1,1,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +93634,22534,Male,Loyal Customer,69,Personal Travel,Eco Plus,145,1,2,0,3,2,0,2,2,4,5,4,4,3,2,30,18.0,neutral or dissatisfied +93635,73639,Female,Loyal Customer,58,Business travel,Business,192,4,4,4,4,2,5,5,5,5,5,4,3,5,3,0,0.0,satisfied +93636,122858,Female,Loyal Customer,33,Business travel,Business,2086,0,0,0,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +93637,26305,Male,Loyal Customer,41,Personal Travel,Eco Plus,1199,0,4,0,2,5,0,5,5,2,1,4,5,3,5,14,3.0,satisfied +93638,36780,Male,Loyal Customer,70,Business travel,Eco,2704,3,1,1,1,3,3,3,4,5,3,3,3,1,3,2,19.0,neutral or dissatisfied +93639,71318,Female,disloyal Customer,9,Business travel,Eco,895,0,0,0,4,3,0,4,3,3,3,4,5,4,3,5,1.0,satisfied +93640,49174,Female,Loyal Customer,40,Business travel,Eco,262,4,2,2,2,4,4,4,4,2,1,2,4,2,4,94,97.0,satisfied +93641,91659,Male,Loyal Customer,48,Personal Travel,Eco,1340,4,4,5,5,2,5,2,2,3,2,3,4,5,2,0,0.0,neutral or dissatisfied +93642,39379,Male,Loyal Customer,45,Business travel,Business,3960,3,3,3,3,5,3,2,5,5,5,5,1,5,5,0,1.0,satisfied +93643,90245,Female,disloyal Customer,23,Business travel,Eco,721,4,5,5,3,5,5,5,5,4,3,3,3,3,5,6,0.0,neutral or dissatisfied +93644,51639,Male,disloyal Customer,43,Business travel,Eco,370,2,3,2,4,3,2,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +93645,122746,Male,disloyal Customer,37,Business travel,Eco,251,5,4,5,3,4,5,5,4,5,1,3,2,2,4,0,0.0,satisfied +93646,94146,Female,Loyal Customer,41,Business travel,Business,239,2,2,2,2,4,5,5,4,4,4,4,5,4,5,2,0.0,satisfied +93647,81633,Female,disloyal Customer,28,Business travel,Business,907,4,4,4,3,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +93648,52616,Female,Loyal Customer,47,Business travel,Eco,119,3,4,4,4,4,2,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +93649,96434,Female,Loyal Customer,50,Business travel,Business,436,4,4,4,4,5,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +93650,86137,Male,Loyal Customer,38,Business travel,Business,2266,4,5,4,4,5,4,4,5,5,5,5,4,5,3,18,14.0,satisfied +93651,17156,Female,Loyal Customer,61,Personal Travel,Business,643,4,5,4,3,2,4,5,3,3,4,5,5,3,4,0,0.0,satisfied +93652,87236,Female,Loyal Customer,46,Business travel,Business,2514,2,1,2,2,2,5,5,5,5,5,5,3,5,3,24,10.0,satisfied +93653,18723,Female,Loyal Customer,13,Personal Travel,Eco Plus,262,5,3,5,5,1,5,5,1,4,5,1,1,2,1,0,0.0,satisfied +93654,2083,Male,Loyal Customer,65,Personal Travel,Eco,733,1,5,1,1,5,1,5,5,4,5,2,4,1,5,0,0.0,neutral or dissatisfied +93655,23933,Male,Loyal Customer,37,Business travel,Eco Plus,189,4,5,5,5,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +93656,48880,Male,disloyal Customer,21,Business travel,Eco,373,4,0,4,5,2,4,2,2,2,4,4,2,3,2,0,0.0,satisfied +93657,105181,Male,Loyal Customer,50,Personal Travel,Eco,281,3,3,1,3,2,1,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +93658,34037,Male,Loyal Customer,19,Personal Travel,Eco Plus,1617,1,4,1,4,5,1,5,5,4,2,4,4,4,5,11,27.0,neutral or dissatisfied +93659,52562,Male,Loyal Customer,17,Business travel,Business,160,2,2,2,2,3,2,2,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +93660,109488,Male,Loyal Customer,28,Business travel,Business,966,5,5,5,5,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +93661,93891,Male,disloyal Customer,28,Business travel,Eco,588,3,2,3,3,1,3,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +93662,23313,Female,Loyal Customer,20,Business travel,Business,3317,1,2,2,2,1,1,1,1,3,3,3,1,4,1,201,190.0,neutral or dissatisfied +93663,28513,Female,disloyal Customer,55,Business travel,Eco,1359,3,3,3,3,3,3,2,3,4,1,5,1,1,3,0,0.0,neutral or dissatisfied +93664,99906,Male,Loyal Customer,64,Personal Travel,Eco,738,1,4,1,3,3,1,3,3,4,4,5,3,5,3,18,4.0,neutral or dissatisfied +93665,76537,Male,Loyal Customer,47,Business travel,Business,2031,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +93666,71540,Female,Loyal Customer,57,Business travel,Business,1801,2,2,2,2,5,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +93667,91885,Male,Loyal Customer,47,Business travel,Business,2475,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +93668,22594,Female,disloyal Customer,38,Business travel,Eco,300,4,0,4,4,5,4,1,5,3,2,5,3,4,5,0,0.0,satisfied +93669,81941,Female,Loyal Customer,51,Business travel,Business,1522,2,2,2,2,4,4,5,5,5,5,5,5,5,3,10,0.0,satisfied +93670,13176,Female,Loyal Customer,20,Personal Travel,Business,419,0,4,0,3,2,0,2,2,3,1,3,5,5,2,2,18.0,satisfied +93671,27619,Female,Loyal Customer,36,Business travel,Eco Plus,605,4,2,2,2,4,4,4,4,2,4,2,2,1,4,0,0.0,satisfied +93672,44685,Female,Loyal Customer,51,Business travel,Business,108,1,2,2,2,5,3,3,2,2,2,1,1,2,2,0,0.0,neutral or dissatisfied +93673,63871,Male,Loyal Customer,10,Business travel,Business,2448,2,3,3,3,3,2,2,1,1,4,3,2,1,2,208,204.0,neutral or dissatisfied +93674,116082,Male,Loyal Customer,55,Personal Travel,Eco,371,2,0,2,4,1,2,1,1,4,3,1,1,1,1,27,22.0,neutral or dissatisfied +93675,111563,Male,Loyal Customer,39,Business travel,Business,2694,5,5,5,5,2,5,4,5,5,5,5,4,5,3,10,10.0,satisfied +93676,17215,Male,Loyal Customer,10,Personal Travel,Eco,1107,4,2,4,3,4,4,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +93677,43354,Male,Loyal Customer,54,Business travel,Eco,387,4,2,2,2,4,4,4,4,4,5,2,5,1,4,0,0.0,satisfied +93678,82543,Male,Loyal Customer,39,Personal Travel,Eco,629,3,5,3,3,3,3,4,3,4,3,4,4,5,3,15,17.0,neutral or dissatisfied +93679,42773,Female,Loyal Customer,41,Business travel,Eco Plus,493,5,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +93680,64387,Male,Loyal Customer,35,Personal Travel,Eco,1172,2,3,2,3,2,2,2,2,3,2,3,4,4,2,10,2.0,neutral or dissatisfied +93681,54061,Female,disloyal Customer,39,Business travel,Business,1416,1,1,1,1,3,1,3,3,1,3,3,5,3,3,0,0.0,neutral or dissatisfied +93682,31348,Female,Loyal Customer,11,Business travel,Eco,1069,2,3,3,3,2,3,1,2,2,1,3,4,4,2,0,0.0,neutral or dissatisfied +93683,98686,Male,Loyal Customer,65,Personal Travel,Eco,920,1,1,0,4,2,0,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +93684,30689,Male,Loyal Customer,54,Business travel,Eco,680,5,5,4,5,4,5,4,4,4,2,5,4,4,4,27,21.0,satisfied +93685,4037,Male,Loyal Customer,36,Business travel,Eco,479,4,3,3,3,4,4,4,4,1,2,3,1,4,4,8,0.0,neutral or dissatisfied +93686,87614,Male,Loyal Customer,43,Personal Travel,Business,591,3,4,3,2,4,4,5,4,4,3,4,5,4,5,26,12.0,neutral or dissatisfied +93687,100359,Male,Loyal Customer,70,Personal Travel,Eco,1052,1,3,1,2,3,1,5,3,3,3,3,4,1,3,0,0.0,neutral or dissatisfied +93688,20875,Female,Loyal Customer,43,Business travel,Eco Plus,357,2,2,2,2,2,2,2,3,1,4,4,2,4,2,187,185.0,neutral or dissatisfied +93689,8955,Female,Loyal Customer,42,Personal Travel,Eco Plus,328,2,2,2,4,3,4,4,4,4,2,1,3,4,2,0,0.0,neutral or dissatisfied +93690,35088,Male,disloyal Customer,22,Business travel,Eco,944,1,1,1,3,1,1,1,1,5,1,1,5,5,1,2,0.0,neutral or dissatisfied +93691,84181,Male,Loyal Customer,66,Personal Travel,Eco Plus,231,2,4,2,2,2,2,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +93692,124242,Male,Loyal Customer,55,Business travel,Business,1916,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +93693,78456,Female,disloyal Customer,39,Business travel,Business,666,5,5,5,1,5,5,5,5,3,5,4,4,4,5,0,44.0,satisfied +93694,54718,Male,Loyal Customer,13,Personal Travel,Eco,965,4,5,4,3,5,4,5,5,5,2,4,3,4,5,0,0.0,satisfied +93695,23193,Female,disloyal Customer,25,Business travel,Eco Plus,250,2,5,2,4,1,2,1,1,3,1,2,4,4,1,0,0.0,neutral or dissatisfied +93696,82499,Male,Loyal Customer,57,Business travel,Business,2031,3,2,3,3,4,4,4,4,4,4,4,5,4,5,15,0.0,satisfied +93697,4269,Male,Loyal Customer,26,Business travel,Business,2638,2,4,4,4,2,2,2,2,1,5,3,1,3,2,0,0.0,neutral or dissatisfied +93698,45239,Female,Loyal Customer,70,Personal Travel,Eco,1031,3,3,3,3,5,4,3,1,1,3,1,4,1,3,26,34.0,neutral or dissatisfied +93699,78000,Male,Loyal Customer,37,Business travel,Business,227,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +93700,21099,Male,Loyal Customer,40,Business travel,Business,227,3,2,2,2,4,3,3,3,3,3,3,2,3,1,32,30.0,neutral or dissatisfied +93701,108375,Female,Loyal Customer,28,Personal Travel,Eco,1855,3,4,3,3,1,3,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +93702,104692,Male,Loyal Customer,53,Business travel,Business,1879,1,1,1,1,2,5,4,5,5,5,5,5,5,5,2,0.0,satisfied +93703,80253,Female,Loyal Customer,33,Business travel,Eco Plus,1269,2,5,5,5,2,2,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +93704,31132,Male,Loyal Customer,33,Business travel,Business,1825,3,1,1,1,3,3,3,3,4,1,3,2,3,3,2,38.0,neutral or dissatisfied +93705,68644,Male,Loyal Customer,44,Business travel,Business,2730,2,2,2,2,2,4,5,4,4,4,5,5,4,5,0,0.0,satisfied +93706,75620,Female,Loyal Customer,62,Personal Travel,Eco,337,4,5,4,3,5,5,5,2,2,4,2,4,2,2,36,17.0,neutral or dissatisfied +93707,82229,Male,disloyal Customer,21,Business travel,Eco,405,2,3,2,3,1,2,1,1,1,3,3,2,4,1,0,0.0,neutral or dissatisfied +93708,87287,Female,Loyal Customer,47,Business travel,Eco,177,4,1,1,1,4,1,5,4,4,4,4,3,4,4,9,5.0,satisfied +93709,114955,Male,disloyal Customer,33,Business travel,Business,404,2,2,2,5,4,2,5,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +93710,113528,Male,Loyal Customer,17,Business travel,Business,386,1,1,1,1,4,4,4,4,4,3,5,3,5,4,2,0.0,satisfied +93711,114059,Female,Loyal Customer,44,Business travel,Business,1947,3,4,4,4,3,2,3,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +93712,116910,Female,Loyal Customer,58,Business travel,Business,3652,2,2,2,2,4,4,5,3,3,3,3,4,3,3,33,16.0,satisfied +93713,61332,Male,Loyal Customer,45,Business travel,Business,3447,4,4,4,4,4,4,4,4,4,4,4,4,4,5,52,46.0,satisfied +93714,9204,Male,Loyal Customer,53,Business travel,Business,3481,0,4,1,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +93715,116180,Female,Loyal Customer,26,Personal Travel,Eco,337,2,5,2,3,4,2,5,4,4,2,4,3,5,4,16,16.0,neutral or dissatisfied +93716,67353,Female,Loyal Customer,18,Personal Travel,Eco,1471,1,3,1,2,3,1,3,3,3,5,3,1,2,3,0,0.0,neutral or dissatisfied +93717,41948,Male,Loyal Customer,44,Business travel,Business,3013,3,3,3,3,3,1,4,5,5,5,5,5,5,1,0,0.0,satisfied +93718,12970,Male,Loyal Customer,44,Business travel,Business,438,5,5,1,5,3,4,5,5,5,5,5,4,5,5,0,2.0,satisfied +93719,83162,Female,Loyal Customer,46,Business travel,Eco Plus,1127,4,3,1,1,5,3,4,4,4,4,4,3,4,2,119,121.0,neutral or dissatisfied +93720,19049,Female,Loyal Customer,32,Business travel,Business,3505,3,3,3,3,3,3,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +93721,61550,Male,Loyal Customer,11,Business travel,Business,2288,2,2,2,2,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +93722,76607,Male,Loyal Customer,53,Business travel,Eco,481,2,1,1,1,2,2,2,2,4,3,2,4,2,2,0,11.0,neutral or dissatisfied +93723,68985,Female,Loyal Customer,38,Personal Travel,Eco,2239,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +93724,47227,Male,Loyal Customer,30,Business travel,Eco Plus,748,0,0,0,1,2,0,4,2,2,1,5,1,1,2,0,0.0,satisfied +93725,34344,Male,Loyal Customer,53,Business travel,Business,2160,2,2,2,2,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +93726,106615,Female,Loyal Customer,29,Business travel,Business,3206,2,2,2,2,5,5,5,5,5,3,4,5,4,5,27,14.0,satisfied +93727,48802,Female,Loyal Customer,45,Business travel,Business,1987,4,4,4,4,5,5,5,5,5,5,5,4,5,3,0,2.0,satisfied +93728,8831,Female,Loyal Customer,20,Business travel,Eco Plus,522,2,3,3,3,2,2,3,2,1,3,3,4,3,2,61,70.0,neutral or dissatisfied +93729,87938,Male,Loyal Customer,70,Personal Travel,Business,581,3,4,2,1,5,5,4,4,4,2,4,4,4,5,5,0.0,neutral or dissatisfied +93730,118602,Male,disloyal Customer,37,Business travel,Business,338,3,3,3,5,5,3,2,5,5,5,5,3,4,5,5,0.0,neutral or dissatisfied +93731,90692,Male,Loyal Customer,10,Business travel,Business,2095,3,2,2,2,3,3,3,3,4,3,3,1,4,3,51,40.0,neutral or dissatisfied +93732,4470,Female,Loyal Customer,28,Personal Travel,Eco,1005,4,5,4,3,1,4,1,1,5,3,1,1,4,1,113,110.0,neutral or dissatisfied +93733,35707,Female,Loyal Customer,58,Personal Travel,Eco,2576,2,4,2,2,2,4,2,3,5,4,5,2,1,2,0,18.0,neutral or dissatisfied +93734,84864,Male,Loyal Customer,7,Personal Travel,Eco,547,5,4,5,4,5,5,5,5,1,5,3,2,4,5,7,0.0,satisfied +93735,12381,Female,Loyal Customer,37,Business travel,Business,262,2,1,3,1,5,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +93736,81355,Male,Loyal Customer,10,Personal Travel,Eco,1299,2,4,2,2,4,2,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +93737,107242,Male,disloyal Customer,22,Business travel,Eco,307,1,4,1,2,4,1,4,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +93738,57436,Female,Loyal Customer,33,Business travel,Business,1735,4,4,4,4,3,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +93739,10949,Female,Loyal Customer,39,Business travel,Business,2630,2,2,2,2,5,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +93740,19754,Female,disloyal Customer,20,Business travel,Eco,462,1,4,1,3,3,1,3,3,2,5,3,4,3,3,5,5.0,neutral or dissatisfied +93741,103915,Male,Loyal Customer,55,Business travel,Eco,533,2,3,2,3,2,2,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +93742,11784,Male,Loyal Customer,68,Personal Travel,Eco,429,1,0,1,2,2,1,2,2,4,1,4,2,1,2,0,1.0,neutral or dissatisfied +93743,50349,Female,Loyal Customer,32,Business travel,Eco,56,5,3,3,3,5,5,5,5,3,2,1,1,4,5,26,17.0,satisfied +93744,57089,Male,Loyal Customer,40,Business travel,Business,2042,1,1,4,1,4,5,5,5,5,5,5,5,5,5,6,3.0,satisfied +93745,45553,Male,Loyal Customer,46,Business travel,Business,1596,4,4,4,4,3,5,4,4,4,4,4,4,4,3,2,3.0,satisfied +93746,50128,Female,Loyal Customer,44,Business travel,Eco,190,4,3,3,3,3,1,5,4,4,4,4,5,4,1,0,0.0,satisfied +93747,123459,Male,Loyal Customer,42,Business travel,Business,2125,1,3,1,1,2,4,4,5,5,4,5,3,5,4,43,30.0,satisfied +93748,105954,Male,Loyal Customer,53,Business travel,Business,2329,1,1,1,1,5,5,5,5,5,4,5,4,5,4,24,39.0,satisfied +93749,73204,Male,Loyal Customer,31,Personal Travel,Eco,1258,1,4,1,3,2,1,2,2,3,5,5,3,5,2,12,4.0,neutral or dissatisfied +93750,111554,Female,Loyal Customer,49,Business travel,Business,2989,3,3,3,3,2,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +93751,36986,Male,Loyal Customer,43,Business travel,Business,1916,2,1,1,1,3,2,2,2,2,2,2,3,2,1,3,0.0,neutral or dissatisfied +93752,41293,Female,Loyal Customer,19,Personal Travel,Eco,802,1,4,1,2,2,1,2,2,3,2,1,3,2,2,10,20.0,neutral or dissatisfied +93753,87905,Female,Loyal Customer,41,Business travel,Business,270,0,0,0,4,3,5,4,4,4,4,4,4,4,4,27,27.0,satisfied +93754,10733,Female,Loyal Customer,42,Business travel,Eco,224,4,3,3,3,1,2,2,3,3,4,3,1,3,2,53,42.0,neutral or dissatisfied +93755,95495,Female,Loyal Customer,52,Business travel,Business,3756,5,5,2,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +93756,19217,Female,Loyal Customer,31,Business travel,Eco,459,2,1,5,1,2,2,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +93757,90686,Male,Loyal Customer,17,Business travel,Business,366,2,4,4,4,2,2,2,2,1,1,4,1,3,2,56,48.0,neutral or dissatisfied +93758,99373,Male,disloyal Customer,25,Business travel,Business,337,2,0,2,2,3,2,3,3,3,5,5,4,5,3,64,55.0,neutral or dissatisfied +93759,90548,Male,disloyal Customer,37,Business travel,Business,444,3,3,3,1,4,3,4,4,3,2,4,5,5,4,2,0.0,neutral or dissatisfied +93760,78447,Female,Loyal Customer,47,Business travel,Business,2953,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +93761,119432,Female,Loyal Customer,19,Personal Travel,Eco,399,2,4,2,1,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +93762,119222,Male,Loyal Customer,21,Personal Travel,Eco,257,4,3,4,3,4,4,4,4,3,3,1,4,2,4,0,0.0,neutral or dissatisfied +93763,15235,Male,Loyal Customer,46,Business travel,Eco,416,2,4,4,4,2,2,2,2,2,1,4,3,4,2,0,22.0,neutral or dissatisfied +93764,26905,Male,Loyal Customer,32,Business travel,Eco,1874,4,5,5,5,4,4,4,4,5,2,5,2,1,4,0,0.0,satisfied +93765,33119,Male,Loyal Customer,44,Personal Travel,Eco,102,3,1,3,2,3,3,2,3,3,4,3,4,3,3,3,0.0,neutral or dissatisfied +93766,51449,Female,Loyal Customer,15,Personal Travel,Eco Plus,308,1,5,1,5,3,1,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +93767,55939,Male,Loyal Customer,11,Personal Travel,Eco Plus,733,4,4,4,2,3,4,3,3,1,3,5,5,1,3,39,34.0,neutral or dissatisfied +93768,81205,Male,disloyal Customer,22,Business travel,Eco,1426,4,4,4,1,2,4,2,2,5,3,5,3,4,2,13,0.0,satisfied +93769,64565,Female,Loyal Customer,27,Business travel,Business,1763,1,1,3,1,3,3,3,3,3,3,4,5,4,3,0,0.0,satisfied +93770,71219,Male,Loyal Customer,39,Business travel,Business,2588,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +93771,14289,Male,disloyal Customer,23,Business travel,Eco,395,0,4,1,4,5,1,5,5,4,3,5,3,4,5,0,0.0,satisfied +93772,4829,Female,disloyal Customer,40,Business travel,Business,408,3,3,3,4,1,3,1,1,1,5,3,4,4,1,0,1.0,neutral or dissatisfied +93773,21584,Male,Loyal Customer,25,Personal Travel,Eco Plus,399,2,5,2,2,5,2,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +93774,69526,Male,Loyal Customer,47,Business travel,Business,2586,4,4,4,4,4,4,4,3,5,4,4,4,3,4,0,0.0,satisfied +93775,5434,Female,disloyal Customer,24,Business travel,Eco,265,3,2,3,3,3,3,3,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +93776,34120,Male,disloyal Customer,48,Business travel,Eco,1046,5,5,5,1,2,5,2,2,4,3,2,1,3,2,0,0.0,satisfied +93777,51229,Female,disloyal Customer,32,Business travel,Eco Plus,193,2,2,2,1,2,2,3,2,3,2,3,4,2,2,0,0.0,neutral or dissatisfied +93778,96155,Male,Loyal Customer,48,Business travel,Business,460,2,2,2,2,5,5,4,3,3,4,3,4,3,5,7,4.0,satisfied +93779,106466,Female,disloyal Customer,23,Business travel,Eco,1300,2,1,1,4,2,2,4,2,3,2,4,3,5,2,6,0.0,neutral or dissatisfied +93780,109735,Female,Loyal Customer,7,Personal Travel,Eco,680,3,4,3,1,4,3,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +93781,3794,Female,Loyal Customer,40,Business travel,Business,599,5,5,5,5,3,5,5,4,4,4,4,5,4,3,62,51.0,satisfied +93782,76420,Male,Loyal Customer,50,Business travel,Eco,405,1,4,4,4,1,1,1,1,3,5,4,3,3,1,45,38.0,neutral or dissatisfied +93783,44223,Male,Loyal Customer,45,Business travel,Business,3586,1,1,1,1,4,3,3,4,4,4,5,3,4,4,0,0.0,satisfied +93784,91568,Male,Loyal Customer,23,Business travel,Business,1123,1,1,3,1,5,4,5,5,4,4,5,4,5,5,0,0.0,satisfied +93785,57355,Female,Loyal Customer,36,Business travel,Business,2527,1,5,5,5,4,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +93786,75198,Female,disloyal Customer,25,Business travel,Eco,1274,3,3,3,2,3,2,2,2,4,3,2,2,3,2,131,111.0,neutral or dissatisfied +93787,45176,Female,Loyal Customer,42,Personal Travel,Eco,130,1,1,0,3,5,4,4,2,2,0,2,3,2,4,0,6.0,neutral or dissatisfied +93788,42461,Male,Loyal Customer,28,Business travel,Eco Plus,866,5,2,2,2,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +93789,28819,Male,disloyal Customer,28,Business travel,Eco,1050,4,4,4,4,5,4,5,5,2,1,3,2,2,5,0,0.0,satisfied +93790,35277,Female,Loyal Customer,34,Business travel,Business,944,1,1,1,1,5,1,2,5,5,5,5,4,5,3,0,5.0,satisfied +93791,105207,Male,Loyal Customer,11,Personal Travel,Eco,1670,3,5,3,3,2,3,4,2,3,4,4,3,4,2,6,0.0,neutral or dissatisfied +93792,28107,Female,Loyal Customer,46,Business travel,Eco,859,5,5,5,5,4,3,3,5,5,5,5,2,5,4,0,0.0,satisfied +93793,15374,Female,Loyal Customer,46,Business travel,Eco,331,4,3,3,3,2,5,2,3,3,4,3,1,3,1,58,49.0,satisfied +93794,55196,Female,Loyal Customer,25,Personal Travel,Eco Plus,1379,3,3,3,3,3,3,4,3,4,3,1,5,1,3,6,0.0,neutral or dissatisfied +93795,100060,Female,Loyal Customer,66,Personal Travel,Eco,220,2,0,0,4,5,5,4,3,3,0,3,3,3,4,7,10.0,neutral or dissatisfied +93796,103352,Female,Loyal Customer,60,Business travel,Business,1940,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +93797,53427,Male,Loyal Customer,27,Business travel,Business,2253,2,2,2,2,2,2,2,2,2,3,5,4,5,2,0,0.0,satisfied +93798,16899,Female,Loyal Customer,8,Personal Travel,Eco,746,4,5,4,3,3,4,3,3,3,4,5,5,5,3,53,76.0,neutral or dissatisfied +93799,39758,Male,Loyal Customer,39,Business travel,Eco,546,4,5,5,5,4,4,4,4,3,2,2,4,4,4,0,0.0,satisfied +93800,49358,Male,Loyal Customer,66,Business travel,Eco,109,4,1,4,1,4,4,4,4,4,4,3,2,3,4,21,15.0,satisfied +93801,72853,Female,Loyal Customer,51,Business travel,Business,3441,1,2,2,2,3,4,4,1,1,1,1,2,1,4,17,6.0,neutral or dissatisfied +93802,59242,Male,Loyal Customer,49,Business travel,Business,4817,2,2,2,2,5,5,5,5,3,4,5,5,3,5,20,0.0,satisfied +93803,6367,Male,Loyal Customer,40,Business travel,Business,240,4,4,4,4,5,5,4,5,5,5,5,3,5,4,32,38.0,satisfied +93804,87309,Male,Loyal Customer,13,Personal Travel,Eco,577,3,5,3,4,4,3,4,4,5,2,4,5,4,4,32,21.0,neutral or dissatisfied +93805,66741,Female,Loyal Customer,9,Personal Travel,Eco,802,1,5,1,2,3,1,3,3,1,5,3,4,3,3,0,7.0,neutral or dissatisfied +93806,128835,Female,Loyal Customer,45,Business travel,Business,1517,2,2,2,2,4,4,4,4,3,1,2,4,3,4,0,0.0,satisfied +93807,34439,Female,Loyal Customer,27,Business travel,Business,2422,3,3,3,3,3,3,3,3,3,5,3,5,1,3,0,0.0,satisfied +93808,50602,Male,Loyal Customer,54,Personal Travel,Eco,78,1,4,0,5,5,0,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +93809,113547,Male,Loyal Customer,40,Business travel,Business,3584,1,5,5,5,1,3,2,1,1,1,1,3,1,1,118,131.0,neutral or dissatisfied +93810,22979,Female,Loyal Customer,25,Business travel,Business,3026,3,3,1,3,3,3,3,3,1,1,4,3,4,3,0,0.0,neutral or dissatisfied +93811,80925,Male,disloyal Customer,24,Business travel,Eco,341,3,4,4,4,5,4,5,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +93812,16576,Female,Loyal Customer,42,Business travel,Business,2101,4,4,4,4,3,5,5,4,4,4,4,4,4,5,28,35.0,satisfied +93813,112834,Female,Loyal Customer,41,Business travel,Business,1476,3,3,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +93814,105225,Female,Loyal Customer,59,Business travel,Business,377,3,3,3,3,2,5,5,2,2,2,2,3,2,4,56,33.0,satisfied +93815,57354,Male,Loyal Customer,63,Business travel,Eco,414,4,2,5,5,4,4,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +93816,122754,Male,Loyal Customer,63,Personal Travel,Eco,651,2,1,1,2,3,1,3,3,2,1,2,3,3,3,0,0.0,neutral or dissatisfied +93817,80019,Male,Loyal Customer,66,Personal Travel,Eco,944,4,5,4,3,5,4,5,5,3,4,1,5,2,5,0,0.0,satisfied +93818,90437,Female,Loyal Customer,39,Business travel,Eco,271,2,5,4,5,2,2,2,2,3,1,4,2,3,2,0,0.0,neutral or dissatisfied +93819,64302,Male,Loyal Customer,48,Business travel,Business,3161,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +93820,28229,Male,Loyal Customer,45,Business travel,Eco,1009,1,2,2,2,2,1,2,2,1,4,4,1,4,2,0,9.0,neutral or dissatisfied +93821,39236,Female,disloyal Customer,85,Business travel,Business,67,4,4,4,3,4,4,4,2,1,5,4,4,4,4,0,0.0,satisfied +93822,5967,Male,Loyal Customer,65,Business travel,Business,3304,3,4,4,4,2,3,3,4,1,4,3,3,1,3,102,140.0,neutral or dissatisfied +93823,31780,Female,Loyal Customer,18,Personal Travel,Eco,602,3,2,3,3,4,3,4,4,1,2,3,2,3,4,18,28.0,neutral or dissatisfied +93824,58593,Male,Loyal Customer,54,Business travel,Business,2083,3,5,3,3,3,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +93825,63371,Male,Loyal Customer,34,Personal Travel,Eco,337,3,4,3,4,4,3,1,4,3,5,5,5,5,4,17,0.0,neutral or dissatisfied +93826,51799,Female,Loyal Customer,58,Personal Travel,Eco,369,4,4,5,4,4,2,2,3,3,5,3,1,3,5,0,0.0,neutral or dissatisfied +93827,117335,Male,Loyal Customer,46,Business travel,Business,296,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +93828,73288,Female,Loyal Customer,37,Business travel,Business,1197,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +93829,76403,Female,Loyal Customer,11,Personal Travel,Eco Plus,931,2,4,2,2,5,2,5,5,3,2,4,5,4,5,2,3.0,neutral or dissatisfied +93830,88209,Male,disloyal Customer,37,Business travel,Business,404,5,5,5,1,1,5,1,1,4,5,4,5,5,1,0,0.0,satisfied +93831,117014,Female,Loyal Customer,58,Business travel,Eco,304,3,5,5,5,5,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +93832,31714,Male,Loyal Customer,43,Personal Travel,Eco,916,3,5,4,1,3,4,2,3,3,1,4,2,1,3,5,1.0,neutral or dissatisfied +93833,13608,Female,disloyal Customer,33,Business travel,Eco Plus,152,3,3,3,3,3,3,3,3,2,1,3,4,3,3,98,84.0,neutral or dissatisfied +93834,69757,Male,Loyal Customer,11,Personal Travel,Eco,1085,3,3,3,4,4,3,3,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +93835,16537,Male,Loyal Customer,25,Business travel,Business,1134,4,4,4,4,4,4,4,4,5,2,4,5,5,4,0,0.0,satisfied +93836,84882,Male,Loyal Customer,11,Personal Travel,Eco,547,1,5,1,5,2,1,2,2,3,4,5,2,4,2,0,0.0,neutral or dissatisfied +93837,110707,Male,Loyal Customer,12,Personal Travel,Eco Plus,837,2,4,3,4,2,3,3,2,4,3,5,4,4,2,13,15.0,neutral or dissatisfied +93838,11104,Female,Loyal Customer,28,Personal Travel,Eco,163,4,5,4,5,1,4,1,1,5,2,5,3,4,1,0,0.0,satisfied +93839,61183,Male,disloyal Customer,37,Business travel,Eco,967,2,2,2,2,2,2,2,2,1,2,3,4,2,2,0,0.0,neutral or dissatisfied +93840,119343,Female,Loyal Customer,38,Personal Travel,Eco,214,1,4,1,3,5,1,5,5,1,2,4,4,4,5,0,2.0,neutral or dissatisfied +93841,44935,Male,Loyal Customer,42,Business travel,Business,397,4,4,4,4,5,4,2,4,4,4,4,2,4,1,0,0.0,satisfied +93842,11730,Female,disloyal Customer,38,Business travel,Eco,395,2,4,1,3,2,1,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +93843,114967,Female,Loyal Customer,59,Business travel,Business,337,0,0,0,4,5,5,4,5,5,4,4,4,5,5,0,0.0,satisfied +93844,25540,Female,Loyal Customer,43,Personal Travel,Eco,516,1,4,1,1,2,2,1,4,4,1,4,1,4,3,5,0.0,neutral or dissatisfied +93845,17625,Female,Loyal Customer,18,Personal Travel,Eco,622,2,4,3,4,4,3,2,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +93846,84907,Male,Loyal Customer,34,Personal Travel,Eco,481,2,4,2,4,1,2,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +93847,34487,Male,Loyal Customer,23,Business travel,Business,1990,5,5,5,5,5,5,5,5,3,3,5,4,2,5,4,0.0,satisfied +93848,88671,Male,Loyal Customer,22,Personal Travel,Eco,271,4,0,4,4,5,4,5,5,3,1,5,5,2,5,17,14.0,neutral or dissatisfied +93849,129458,Male,Loyal Customer,56,Business travel,Business,2764,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +93850,11194,Female,Loyal Customer,15,Personal Travel,Eco,429,2,3,2,3,4,2,5,4,1,2,3,3,3,4,34,27.0,neutral or dissatisfied +93851,114202,Female,disloyal Customer,25,Business travel,Eco,948,3,3,3,4,5,3,5,5,1,5,3,4,3,5,5,2.0,neutral or dissatisfied +93852,48321,Male,Loyal Customer,69,Personal Travel,Eco,1203,3,1,3,3,2,3,2,2,2,5,4,3,4,2,11,9.0,neutral or dissatisfied +93853,15599,Female,disloyal Customer,24,Business travel,Eco,229,4,2,5,3,4,5,4,4,3,5,3,3,3,4,0,0.0,neutral or dissatisfied +93854,68396,Female,Loyal Customer,54,Business travel,Business,3323,1,1,1,1,4,5,4,5,5,4,5,4,5,5,16,6.0,satisfied +93855,5876,Female,Loyal Customer,55,Business travel,Business,173,2,2,2,2,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +93856,8289,Male,Loyal Customer,66,Personal Travel,Eco,294,2,5,2,1,5,2,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +93857,2662,Male,disloyal Customer,29,Business travel,Eco,622,4,4,4,3,5,4,5,5,4,5,3,2,3,5,0,0.0,neutral or dissatisfied +93858,66156,Male,Loyal Customer,60,Business travel,Business,3440,2,2,2,2,4,4,4,4,4,4,4,3,4,4,69,66.0,satisfied +93859,92539,Male,Loyal Customer,14,Personal Travel,Eco,1947,1,5,1,1,5,1,5,5,4,2,3,5,5,5,4,0.0,neutral or dissatisfied +93860,113115,Female,Loyal Customer,66,Personal Travel,Eco,569,2,4,2,2,3,3,3,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +93861,60192,Female,Loyal Customer,20,Personal Travel,Eco Plus,1197,4,5,4,2,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +93862,79477,Female,disloyal Customer,23,Business travel,Eco,762,1,2,2,3,4,2,4,4,4,4,4,3,4,4,3,0.0,neutral or dissatisfied +93863,71854,Male,Loyal Customer,45,Business travel,Business,3189,2,2,2,2,2,2,2,1,4,4,4,2,4,2,217,206.0,neutral or dissatisfied +93864,53050,Male,Loyal Customer,31,Personal Travel,Eco,1208,3,1,3,3,5,3,5,5,3,1,3,4,4,5,0,7.0,neutral or dissatisfied +93865,87364,Female,Loyal Customer,18,Business travel,Eco,425,2,5,5,5,2,2,2,2,4,5,3,4,4,2,66,65.0,neutral or dissatisfied +93866,79340,Female,Loyal Customer,32,Business travel,Business,2468,3,3,3,3,3,3,3,3,3,4,3,2,2,3,0,0.0,neutral or dissatisfied +93867,44019,Male,Loyal Customer,21,Personal Travel,Eco Plus,397,2,5,2,3,2,4,4,5,3,5,4,4,5,4,168,163.0,neutral or dissatisfied +93868,117600,Female,Loyal Customer,63,Business travel,Eco,347,2,5,5,5,2,3,3,2,1,4,3,3,2,3,243,238.0,neutral or dissatisfied +93869,101432,Female,Loyal Customer,30,Business travel,Business,345,1,4,1,4,1,1,1,1,1,5,4,1,3,1,13,9.0,neutral or dissatisfied +93870,56567,Female,Loyal Customer,45,Business travel,Business,1023,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +93871,96193,Male,disloyal Customer,70,Business travel,Eco,666,3,1,3,4,4,3,4,4,3,5,4,2,3,4,0,0.0,neutral or dissatisfied +93872,43953,Male,Loyal Customer,49,Business travel,Business,3377,1,5,5,5,2,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +93873,56223,Female,Loyal Customer,38,Business travel,Eco,1608,2,4,2,2,2,2,2,4,5,3,3,2,3,2,138,132.0,neutral or dissatisfied +93874,97417,Female,disloyal Customer,24,Business travel,Eco,587,2,1,2,2,2,2,3,2,4,1,2,3,3,2,23,,neutral or dissatisfied +93875,34304,Female,Loyal Customer,43,Personal Travel,Eco,280,1,4,1,3,4,4,4,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +93876,101549,Female,Loyal Customer,11,Personal Travel,Eco,345,2,5,2,1,2,2,4,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +93877,76196,Male,disloyal Customer,33,Business travel,Eco,752,2,2,2,3,5,2,5,5,1,5,4,4,4,5,0,0.0,neutral or dissatisfied +93878,120923,Female,Loyal Customer,44,Business travel,Business,1983,4,4,4,4,3,4,4,5,5,5,5,5,5,3,49,66.0,satisfied +93879,78551,Female,disloyal Customer,36,Business travel,Business,666,2,2,2,4,3,2,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +93880,97914,Male,disloyal Customer,24,Business travel,Eco,616,4,0,4,4,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +93881,106189,Male,Loyal Customer,45,Personal Travel,Eco,302,2,4,2,1,3,2,2,3,4,3,5,4,4,3,14,25.0,neutral or dissatisfied +93882,123475,Male,Loyal Customer,44,Business travel,Business,2296,5,5,1,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +93883,60058,Female,Loyal Customer,47,Personal Travel,Eco Plus,997,2,5,2,3,4,5,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +93884,23447,Female,disloyal Customer,38,Business travel,Eco,516,2,0,2,5,2,5,5,5,5,4,2,5,2,5,101,175.0,neutral or dissatisfied +93885,17513,Female,Loyal Customer,46,Business travel,Business,352,3,3,3,3,4,5,1,5,5,5,5,4,5,2,0,0.0,satisfied +93886,77112,Male,Loyal Customer,32,Business travel,Business,1481,2,2,2,2,2,2,2,2,2,4,1,4,1,2,0,18.0,neutral or dissatisfied +93887,77168,Female,Loyal Customer,51,Business travel,Business,1355,5,5,5,5,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +93888,81614,Female,Loyal Customer,37,Personal Travel,Eco,334,1,4,1,1,5,1,5,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +93889,47739,Female,Loyal Customer,52,Personal Travel,Business,817,1,1,2,4,1,4,4,4,4,2,2,4,4,2,0,0.0,neutral or dissatisfied +93890,80928,Male,Loyal Customer,40,Business travel,Business,3082,0,0,0,4,2,3,3,1,1,1,1,4,1,2,3,14.0,satisfied +93891,25889,Male,Loyal Customer,26,Business travel,Business,3078,2,1,1,1,2,2,2,2,1,4,3,3,3,2,0,12.0,neutral or dissatisfied +93892,5207,Female,Loyal Customer,62,Business travel,Business,2114,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +93893,75639,Female,Loyal Customer,57,Business travel,Business,304,3,3,3,3,3,1,1,3,3,3,3,2,3,4,74,77.0,neutral or dissatisfied +93894,38086,Female,Loyal Customer,52,Business travel,Eco,1197,5,2,2,2,5,3,2,5,5,5,5,4,5,5,63,57.0,satisfied +93895,106102,Female,Loyal Customer,52,Business travel,Business,2599,1,1,5,1,5,4,5,4,4,4,4,4,4,4,6,14.0,satisfied +93896,20077,Female,Loyal Customer,30,Personal Travel,Eco,738,3,4,3,2,1,3,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +93897,86805,Male,disloyal Customer,22,Business travel,Business,484,5,0,5,1,3,5,3,3,5,5,5,3,4,3,7,1.0,satisfied +93898,14754,Male,Loyal Customer,41,Business travel,Eco,463,1,1,1,1,1,1,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +93899,16516,Male,Loyal Customer,56,Personal Travel,Eco Plus,246,1,1,1,4,3,1,5,3,3,2,3,3,4,3,5,9.0,neutral or dissatisfied +93900,76042,Female,Loyal Customer,51,Business travel,Business,1835,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,3.0,satisfied +93901,65620,Male,Loyal Customer,41,Personal Travel,Eco,237,2,1,2,3,5,2,2,5,3,3,2,4,2,5,13,4.0,neutral or dissatisfied +93902,56699,Female,Loyal Customer,62,Personal Travel,Eco,937,2,4,1,2,2,5,4,5,5,1,5,4,5,5,0,11.0,neutral or dissatisfied +93903,123592,Male,Loyal Customer,60,Personal Travel,Eco,1773,3,4,3,3,1,3,1,1,3,2,3,2,5,1,0,0.0,neutral or dissatisfied +93904,82024,Female,Loyal Customer,30,Personal Travel,Eco,1535,2,5,2,2,1,2,1,1,5,5,4,4,5,1,11,0.0,neutral or dissatisfied +93905,30218,Male,Loyal Customer,55,Personal Travel,Eco Plus,571,3,5,3,3,2,3,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +93906,23053,Male,disloyal Customer,28,Business travel,Eco,820,2,2,2,4,5,2,2,5,3,2,2,3,2,5,26,14.0,neutral or dissatisfied +93907,97832,Male,Loyal Customer,33,Business travel,Business,395,1,1,2,1,3,4,3,3,1,5,5,5,1,3,5,0.0,satisfied +93908,42154,Male,Loyal Customer,28,Personal Travel,Business,838,3,2,3,2,5,3,2,5,3,1,2,3,1,5,0,0.0,neutral or dissatisfied +93909,56103,Male,disloyal Customer,16,Business travel,Eco,787,1,1,1,3,1,1,1,4,4,2,2,1,3,1,32,32.0,neutral or dissatisfied +93910,119951,Female,Loyal Customer,23,Business travel,Business,2793,3,2,2,2,3,3,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +93911,103234,Male,Loyal Customer,33,Business travel,Business,1863,1,1,1,1,5,5,5,5,3,5,5,5,5,5,4,0.0,satisfied +93912,96329,Female,disloyal Customer,33,Business travel,Business,359,3,3,3,1,4,3,4,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +93913,33241,Male,disloyal Customer,25,Business travel,Eco Plus,101,1,1,1,3,2,1,2,2,2,5,3,2,4,2,7,7.0,neutral or dissatisfied +93914,44134,Male,Loyal Customer,40,Business travel,Business,98,1,1,1,1,5,2,5,5,5,5,4,1,5,5,0,0.0,satisfied +93915,85001,Male,disloyal Customer,34,Business travel,Eco,998,3,3,3,3,3,5,5,3,4,1,3,5,4,5,173,171.0,neutral or dissatisfied +93916,74509,Male,Loyal Customer,56,Business travel,Business,1171,2,2,2,2,5,5,5,4,4,5,4,3,4,4,5,0.0,satisfied +93917,38038,Female,Loyal Customer,42,Business travel,Business,1185,3,3,3,3,3,3,5,4,4,4,4,1,4,4,0,0.0,satisfied +93918,100846,Female,Loyal Customer,7,Personal Travel,Eco,711,2,3,2,3,2,2,2,2,1,5,5,3,4,2,80,66.0,neutral or dissatisfied +93919,112031,Female,Loyal Customer,52,Business travel,Business,680,5,5,5,5,3,4,4,4,4,4,4,4,4,4,18,2.0,satisfied +93920,16707,Female,Loyal Customer,28,Business travel,Business,284,3,5,5,5,3,3,3,3,3,5,4,3,4,3,35,36.0,neutral or dissatisfied +93921,2433,Male,Loyal Customer,36,Personal Travel,Eco,604,2,3,2,3,3,2,3,3,4,3,3,1,4,3,38,26.0,neutral or dissatisfied +93922,29572,Female,Loyal Customer,22,Business travel,Business,1533,3,3,3,3,4,4,4,4,3,5,5,5,3,4,0,0.0,satisfied +93923,59678,Female,Loyal Customer,47,Personal Travel,Eco,787,3,5,3,4,2,3,5,2,2,3,2,5,2,5,8,0.0,neutral or dissatisfied +93924,14992,Male,Loyal Customer,31,Personal Travel,Eco,476,3,5,3,5,4,3,4,4,2,4,3,1,2,4,0,0.0,neutral or dissatisfied +93925,25949,Male,Loyal Customer,24,Business travel,Business,946,3,3,3,3,4,4,4,4,5,3,5,5,5,4,38,26.0,satisfied +93926,119609,Female,Loyal Customer,40,Personal Travel,Eco,1979,4,5,4,3,4,4,4,4,2,4,1,2,5,4,0,3.0,neutral or dissatisfied +93927,1172,Male,Loyal Customer,58,Personal Travel,Eco,282,2,5,2,3,4,2,2,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +93928,106938,Female,Loyal Customer,47,Personal Travel,Business,937,2,4,2,2,3,2,5,3,3,2,3,4,3,3,32,19.0,neutral or dissatisfied +93929,101931,Male,Loyal Customer,48,Business travel,Business,3939,3,2,2,2,2,4,4,3,3,3,3,3,3,4,8,0.0,neutral or dissatisfied +93930,20349,Female,Loyal Customer,22,Business travel,Eco,287,5,1,1,1,5,5,4,5,3,2,1,1,5,5,0,0.0,satisfied +93931,38269,Male,Loyal Customer,40,Business travel,Business,2361,3,1,2,2,4,3,4,3,3,3,3,2,3,3,6,4.0,neutral or dissatisfied +93932,97785,Female,disloyal Customer,25,Business travel,Business,471,4,0,4,2,4,4,4,4,5,5,4,3,4,4,1,0.0,neutral or dissatisfied +93933,128266,Female,Loyal Customer,54,Business travel,Business,3305,2,2,2,2,2,2,3,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +93934,115019,Male,Loyal Customer,47,Business travel,Business,3369,3,3,3,3,2,5,5,4,4,4,4,3,4,3,12,5.0,satisfied +93935,51600,Male,Loyal Customer,32,Business travel,Business,2811,2,2,2,2,5,5,5,5,3,4,2,2,1,5,0,0.0,satisfied +93936,21428,Female,Loyal Customer,32,Business travel,Eco,164,0,0,0,3,1,0,1,1,4,2,5,1,5,1,0,0.0,satisfied +93937,41773,Male,Loyal Customer,57,Personal Travel,Eco,872,2,1,2,4,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +93938,18187,Female,disloyal Customer,33,Business travel,Eco,346,4,4,4,2,4,1,1,3,1,3,4,1,5,1,204,188.0,neutral or dissatisfied +93939,72983,Female,Loyal Customer,52,Business travel,Business,2607,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +93940,54839,Female,Loyal Customer,49,Business travel,Business,1803,3,3,3,3,3,4,5,4,4,4,4,4,4,4,0,8.0,satisfied +93941,73591,Female,Loyal Customer,57,Business travel,Business,3876,1,1,1,1,4,5,4,5,5,5,4,5,5,4,0,1.0,satisfied +93942,10580,Female,Loyal Customer,40,Business travel,Business,2686,2,2,4,2,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +93943,116948,Female,Loyal Customer,57,Business travel,Business,2913,1,1,1,1,2,5,4,4,4,4,4,3,4,3,57,56.0,satisfied +93944,84463,Female,Loyal Customer,56,Personal Travel,Eco,290,3,4,3,1,3,5,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +93945,99028,Male,Loyal Customer,26,Business travel,Business,1009,1,1,1,1,5,5,5,5,4,5,5,3,5,5,24,13.0,satisfied +93946,87067,Female,disloyal Customer,25,Business travel,Eco,594,2,1,1,3,3,1,3,3,2,3,3,1,3,3,14,7.0,neutral or dissatisfied +93947,30113,Male,Loyal Customer,31,Personal Travel,Eco,539,2,2,2,3,5,2,5,5,3,2,4,3,4,5,1,1.0,neutral or dissatisfied +93948,85000,Male,Loyal Customer,38,Business travel,Eco,1590,2,2,2,2,2,2,2,2,1,4,3,1,4,2,0,12.0,neutral or dissatisfied +93949,10693,Male,Loyal Customer,46,Business travel,Business,308,3,3,3,3,3,5,5,4,4,4,4,4,4,5,4,0.0,satisfied +93950,100425,Female,Loyal Customer,9,Personal Travel,Business,1620,3,4,3,3,3,3,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +93951,99617,Female,Loyal Customer,31,Business travel,Business,2765,3,3,3,3,5,5,5,5,5,4,5,4,4,5,23,13.0,satisfied +93952,96392,Male,Loyal Customer,52,Business travel,Business,1617,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +93953,108186,Female,Loyal Customer,63,Personal Travel,Eco,990,2,4,2,3,4,3,4,3,3,2,3,1,3,1,7,16.0,neutral or dissatisfied +93954,8869,Female,Loyal Customer,24,Business travel,Business,622,1,1,1,1,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +93955,90411,Female,Loyal Customer,28,Business travel,Business,545,3,3,3,3,5,4,5,5,4,2,4,4,4,5,0,1.0,satisfied +93956,6017,Male,Loyal Customer,40,Business travel,Eco,672,3,4,4,4,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +93957,43482,Male,Loyal Customer,34,Business travel,Business,624,3,2,2,2,2,3,3,3,3,3,3,2,3,2,32,33.0,neutral or dissatisfied +93958,43247,Male,Loyal Customer,49,Personal Travel,Business,436,0,4,0,1,2,5,5,3,3,0,3,5,3,3,0,0.0,satisfied +93959,23372,Male,Loyal Customer,69,Personal Travel,Eco,1162,3,3,3,4,2,3,5,2,4,4,3,1,3,2,1,0.0,neutral or dissatisfied +93960,62905,Female,Loyal Customer,27,Personal Travel,Business,853,4,4,4,3,1,4,1,1,4,2,5,4,4,1,0,1.0,neutral or dissatisfied +93961,75558,Male,Loyal Customer,43,Business travel,Business,337,1,1,1,1,4,3,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +93962,21061,Male,Loyal Customer,37,Business travel,Business,106,4,2,4,4,4,3,1,4,4,5,5,2,4,2,0,0.0,satisfied +93963,35323,Male,Loyal Customer,42,Business travel,Business,3534,2,3,3,3,3,4,3,2,2,3,2,3,2,1,53,75.0,neutral or dissatisfied +93964,80650,Male,Loyal Customer,45,Business travel,Business,821,5,5,5,5,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +93965,81681,Male,disloyal Customer,37,Business travel,Eco,907,3,3,3,3,3,3,3,3,2,4,2,1,2,3,0,11.0,neutral or dissatisfied +93966,17218,Male,Loyal Customer,54,Business travel,Business,2644,3,3,3,3,4,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +93967,53573,Male,Loyal Customer,41,Business travel,Business,1195,1,1,2,1,1,5,2,4,4,4,4,2,4,2,0,0.0,satisfied +93968,108555,Female,Loyal Customer,25,Business travel,Business,735,5,5,5,5,2,2,2,2,4,2,4,5,5,2,0,0.0,satisfied +93969,64391,Male,Loyal Customer,56,Personal Travel,Eco,1172,2,1,2,3,5,2,5,5,3,5,3,4,4,5,30,23.0,neutral or dissatisfied +93970,112219,Female,Loyal Customer,35,Business travel,Business,2125,3,1,1,1,1,3,4,3,3,3,3,1,3,4,63,55.0,neutral or dissatisfied +93971,120636,Female,Loyal Customer,46,Business travel,Business,3278,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +93972,57036,Female,Loyal Customer,21,Business travel,Eco Plus,2454,5,3,3,3,5,5,5,5,1,4,5,1,4,5,0,0.0,satisfied +93973,47438,Female,disloyal Customer,27,Business travel,Eco,188,3,5,2,3,3,2,3,3,5,2,1,2,4,3,0,0.0,neutral or dissatisfied +93974,84687,Female,Loyal Customer,51,Personal Travel,Eco,2182,1,1,2,3,5,3,3,4,4,2,4,4,4,3,0,2.0,neutral or dissatisfied +93975,110629,Female,Loyal Customer,57,Personal Travel,Eco,727,1,1,1,3,1,3,3,1,1,1,1,1,1,3,2,3.0,neutral or dissatisfied +93976,121850,Female,disloyal Customer,39,Business travel,Business,449,3,3,3,4,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +93977,28196,Male,Loyal Customer,11,Personal Travel,Eco,550,1,2,1,2,4,1,4,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +93978,12044,Female,Loyal Customer,35,Business travel,Business,376,2,1,2,2,3,5,4,5,5,5,5,2,5,4,0,0.0,satisfied +93979,32490,Female,Loyal Customer,34,Business travel,Business,2514,3,3,3,3,4,1,1,4,4,4,5,3,4,2,0,4.0,satisfied +93980,126736,Male,Loyal Customer,47,Business travel,Eco,2521,2,3,2,3,2,2,2,2,1,5,2,4,4,2,0,0.0,neutral or dissatisfied +93981,85213,Male,Loyal Customer,21,Business travel,Eco,813,4,2,2,2,4,4,2,4,4,3,4,3,4,4,95,79.0,neutral or dissatisfied +93982,109915,Male,Loyal Customer,55,Personal Travel,Eco,1034,5,5,5,1,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +93983,50646,Male,Loyal Customer,53,Personal Travel,Eco,250,3,1,3,3,3,3,3,3,3,5,4,2,4,3,0,2.0,neutral or dissatisfied +93984,14602,Female,Loyal Customer,57,Personal Travel,Eco,1021,3,0,3,3,2,5,5,5,5,3,2,3,5,3,35,54.0,neutral or dissatisfied +93985,87100,Male,Loyal Customer,11,Personal Travel,Eco,645,2,2,1,4,4,1,1,4,3,4,3,4,3,4,9,4.0,neutral or dissatisfied +93986,93295,Female,disloyal Customer,52,Business travel,Business,564,5,5,5,5,3,5,3,3,5,3,5,3,5,3,32,36.0,satisfied +93987,109087,Male,Loyal Customer,69,Personal Travel,Eco,571,1,4,1,3,1,1,1,1,1,1,3,2,4,1,0,0.0,neutral or dissatisfied +93988,67070,Female,Loyal Customer,41,Business travel,Business,985,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +93989,876,Female,disloyal Customer,20,Business travel,Eco,134,4,3,5,3,4,5,4,4,1,1,4,4,4,4,0,0.0,neutral or dissatisfied +93990,19195,Male,Loyal Customer,23,Business travel,Business,2057,1,5,3,5,1,1,1,1,1,5,4,4,3,1,22,19.0,neutral or dissatisfied +93991,83802,Male,Loyal Customer,56,Business travel,Business,3476,3,3,3,3,4,4,5,5,5,5,5,4,5,3,4,3.0,satisfied +93992,39469,Male,Loyal Customer,47,Business travel,Business,2302,2,2,2,2,1,3,4,2,2,2,2,2,2,4,95,89.0,neutral or dissatisfied +93993,113232,Female,Loyal Customer,43,Business travel,Business,3720,1,1,1,1,4,4,3,1,1,1,1,3,1,3,4,0.0,neutral or dissatisfied +93994,23179,Female,Loyal Customer,59,Personal Travel,Eco,250,3,5,3,2,4,5,5,4,4,3,4,5,4,3,83,107.0,neutral or dissatisfied +93995,36710,Male,Loyal Customer,41,Business travel,Eco Plus,1249,4,5,5,5,4,4,4,4,3,4,5,3,5,4,0,24.0,satisfied +93996,23428,Female,Loyal Customer,44,Business travel,Business,1688,5,5,5,5,1,5,2,4,4,4,4,1,4,2,13,0.0,satisfied +93997,58481,Male,Loyal Customer,25,Business travel,Business,719,1,1,1,1,5,5,5,5,5,3,5,5,5,5,17,1.0,satisfied +93998,75469,Male,Loyal Customer,19,Personal Travel,Eco,2218,4,4,4,3,5,4,5,5,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +93999,66952,Male,Loyal Customer,40,Business travel,Business,1017,4,4,4,4,2,5,4,4,4,4,4,4,4,4,5,0.0,satisfied +94000,92701,Male,Loyal Customer,60,Business travel,Business,1710,2,4,2,2,2,5,5,5,5,5,5,4,5,5,53,55.0,satisfied +94001,44468,Female,Loyal Customer,53,Business travel,Eco,196,2,2,2,2,5,4,4,2,2,2,2,3,2,3,77,90.0,neutral or dissatisfied +94002,21087,Male,disloyal Customer,62,Business travel,Business,227,2,2,2,3,2,2,2,2,2,4,3,2,4,2,0,0.0,neutral or dissatisfied +94003,73784,Male,Loyal Customer,56,Business travel,Business,3097,3,3,3,3,3,5,4,5,5,5,4,3,5,4,13,4.0,satisfied +94004,26404,Male,Loyal Customer,41,Personal Travel,Eco,1084,1,5,2,3,4,2,1,4,4,4,5,3,5,4,11,3.0,neutral or dissatisfied +94005,28014,Female,disloyal Customer,28,Business travel,Eco,763,2,2,2,4,1,2,1,1,2,4,3,4,3,1,2,0.0,neutral or dissatisfied +94006,129558,Female,Loyal Customer,67,Personal Travel,Eco,2342,3,4,3,4,2,4,4,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +94007,54386,Male,Loyal Customer,56,Business travel,Business,3789,5,5,5,5,1,5,2,3,3,4,3,2,3,2,71,68.0,satisfied +94008,98620,Male,Loyal Customer,51,Business travel,Eco,861,3,2,2,2,3,3,3,3,1,3,3,2,4,3,0,3.0,neutral or dissatisfied +94009,125960,Male,Loyal Customer,37,Personal Travel,Eco Plus,993,1,1,1,3,1,1,1,1,1,5,2,4,2,1,0,0.0,neutral or dissatisfied +94010,123733,Male,Loyal Customer,24,Personal Travel,Eco Plus,214,2,0,0,2,3,0,3,3,3,3,4,5,5,3,0,1.0,neutral or dissatisfied +94011,67451,Female,Loyal Customer,32,Personal Travel,Eco,592,3,5,3,1,5,3,5,5,5,1,1,3,1,5,63,65.0,neutral or dissatisfied +94012,20293,Male,Loyal Customer,47,Personal Travel,Eco,137,1,2,1,3,2,1,2,2,4,5,3,2,4,2,40,33.0,neutral or dissatisfied +94013,111760,Female,Loyal Customer,18,Business travel,Business,1436,3,3,3,3,4,5,4,4,5,4,3,1,1,4,0,0.0,satisfied +94014,122950,Female,Loyal Customer,57,Business travel,Eco,507,3,2,2,2,3,4,4,4,4,3,4,1,4,4,0,28.0,neutral or dissatisfied +94015,90240,Female,disloyal Customer,20,Business travel,Business,1121,2,1,2,4,4,2,5,4,4,1,3,3,4,4,1,0.0,neutral or dissatisfied +94016,118365,Female,Loyal Customer,31,Business travel,Eco Plus,602,3,2,2,2,3,3,3,3,1,2,2,3,2,3,0,0.0,neutral or dissatisfied +94017,95979,Male,Loyal Customer,38,Business travel,Business,583,4,4,4,4,5,5,5,4,4,4,4,4,4,5,3,0.0,satisfied +94018,14453,Female,Loyal Customer,54,Business travel,Eco,761,2,3,3,3,1,4,4,1,1,2,1,1,1,2,100,89.0,neutral or dissatisfied +94019,94128,Male,Loyal Customer,48,Business travel,Business,1920,1,1,1,1,4,5,4,5,5,5,5,4,5,5,14,14.0,satisfied +94020,28984,Male,disloyal Customer,25,Business travel,Eco,671,1,1,1,3,2,1,2,2,4,5,3,2,3,2,0,0.0,neutral or dissatisfied +94021,28531,Female,Loyal Customer,51,Business travel,Business,2688,2,4,4,4,1,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +94022,116499,Male,Loyal Customer,9,Personal Travel,Eco,373,1,2,1,3,4,1,4,4,4,5,2,2,3,4,1,0.0,neutral or dissatisfied +94023,25738,Female,Loyal Customer,44,Personal Travel,Eco,447,0,4,0,4,3,4,5,5,5,0,2,3,5,4,0,0.0,satisfied +94024,41206,Male,Loyal Customer,43,Business travel,Eco,1091,3,5,5,5,3,3,3,2,1,4,3,3,4,3,173,170.0,neutral or dissatisfied +94025,30254,Female,Loyal Customer,47,Personal Travel,Business,836,1,4,1,4,5,5,4,3,3,1,5,3,3,5,0,0.0,neutral or dissatisfied +94026,32580,Male,Loyal Customer,36,Business travel,Eco,102,4,1,1,1,4,4,4,4,1,3,4,4,4,4,0,0.0,satisfied +94027,102172,Female,disloyal Customer,27,Business travel,Business,488,1,2,2,3,5,2,5,5,3,4,4,3,5,5,0,5.0,neutral or dissatisfied +94028,72584,Female,Loyal Customer,36,Business travel,Eco,719,4,5,5,5,4,4,4,4,4,5,4,2,3,4,0,0.0,neutral or dissatisfied +94029,17330,Female,Loyal Customer,26,Business travel,Eco Plus,403,3,2,4,4,3,3,2,3,1,4,4,4,4,3,0,7.0,neutral or dissatisfied +94030,34693,Female,Loyal Customer,38,Business travel,Business,264,3,3,3,3,4,4,3,4,4,4,4,2,4,3,56,53.0,satisfied +94031,65813,Male,Loyal Customer,32,Business travel,Business,1389,2,2,2,2,5,5,5,5,4,5,5,5,5,5,67,79.0,satisfied +94032,6554,Male,Loyal Customer,38,Business travel,Business,1604,2,2,2,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +94033,122071,Male,Loyal Customer,39,Business travel,Business,1949,2,2,2,2,3,3,1,5,5,5,4,5,5,1,1,0.0,satisfied +94034,114258,Male,disloyal Customer,26,Business travel,Eco,557,4,0,4,1,5,4,5,5,2,2,3,4,3,5,0,0.0,satisfied +94035,99250,Male,Loyal Customer,25,Personal Travel,Eco,541,2,2,2,4,1,2,1,1,2,2,4,3,4,1,0,0.0,neutral or dissatisfied +94036,7934,Female,disloyal Customer,22,Business travel,Eco,194,4,0,4,2,3,4,3,3,3,2,5,4,4,3,0,0.0,satisfied +94037,96793,Female,Loyal Customer,56,Business travel,Business,781,2,2,3,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +94038,16520,Female,Loyal Customer,60,Business travel,Business,2520,1,3,3,3,2,4,4,2,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +94039,74711,Male,Loyal Customer,15,Personal Travel,Eco,1235,0,5,0,5,2,0,2,2,4,5,4,3,5,2,4,1.0,satisfied +94040,88068,Female,Loyal Customer,60,Business travel,Business,1704,5,5,5,5,2,5,4,4,4,4,4,4,4,5,11,12.0,satisfied +94041,27101,Male,disloyal Customer,24,Business travel,Eco,819,3,3,3,5,2,3,2,2,4,5,4,2,4,2,0,0.0,neutral or dissatisfied +94042,49747,Male,Loyal Customer,33,Business travel,Business,3680,4,4,4,4,4,4,4,4,1,3,2,1,1,4,0,1.0,satisfied +94043,64414,Male,Loyal Customer,24,Personal Travel,Eco Plus,1192,4,5,4,4,2,4,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +94044,126258,Female,Loyal Customer,40,Business travel,Eco,250,4,2,2,2,4,4,4,4,4,5,4,3,1,4,0,0.0,satisfied +94045,128274,Male,Loyal Customer,37,Personal Travel,Business,338,4,4,4,4,5,5,5,2,2,4,2,4,2,5,0,0.0,satisfied +94046,64636,Male,disloyal Customer,22,Business travel,Eco,551,3,5,3,1,4,3,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +94047,17938,Male,disloyal Customer,42,Business travel,Business,214,2,2,2,3,5,2,5,5,4,2,3,1,4,5,15,11.0,neutral or dissatisfied +94048,77348,Male,disloyal Customer,52,Business travel,Business,626,3,3,3,4,2,3,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +94049,124629,Female,Loyal Customer,62,Personal Travel,Eco,1671,3,4,3,2,5,2,2,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +94050,32232,Female,Loyal Customer,41,Business travel,Business,101,3,3,3,3,3,2,5,4,4,4,4,2,4,2,0,3.0,satisfied +94051,30486,Female,Loyal Customer,41,Business travel,Business,2469,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +94052,81154,Female,Loyal Customer,58,Business travel,Business,1668,3,3,3,3,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +94053,99374,Male,Loyal Customer,69,Business travel,Business,337,1,1,1,1,2,5,5,5,5,4,5,3,5,5,43,34.0,satisfied +94054,87235,Male,disloyal Customer,20,Business travel,Eco,577,4,4,3,2,3,3,3,3,5,2,4,5,4,3,0,7.0,satisfied +94055,55649,Male,Loyal Customer,39,Business travel,Business,296,3,3,3,3,4,4,4,4,3,5,5,4,5,4,143,224.0,satisfied +94056,1973,Male,Loyal Customer,12,Personal Travel,Eco,293,2,5,2,4,5,2,5,5,3,5,4,3,5,5,12,12.0,neutral or dissatisfied +94057,127001,Male,Loyal Customer,35,Business travel,Business,647,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +94058,26956,Female,Loyal Customer,53,Business travel,Business,1901,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,4.0,satisfied +94059,68417,Female,Loyal Customer,61,Personal Travel,Eco,1045,0,3,0,3,2,3,2,4,4,0,4,4,4,5,0,3.0,satisfied +94060,35431,Female,Loyal Customer,28,Personal Travel,Eco,1056,2,4,2,2,2,2,5,2,4,5,5,5,4,2,2,0.0,neutral or dissatisfied +94061,60384,Female,Loyal Customer,34,Business travel,Business,1452,1,0,0,3,5,4,3,3,3,0,3,2,3,4,0,0.0,neutral or dissatisfied +94062,42124,Male,Loyal Customer,31,Personal Travel,Eco,991,3,5,4,1,1,4,1,1,3,4,4,5,4,1,0,9.0,neutral or dissatisfied +94063,27954,Male,disloyal Customer,12,Business travel,Eco,1770,4,4,4,3,1,4,1,1,2,4,4,3,4,1,22,15.0,neutral or dissatisfied +94064,51965,Male,Loyal Customer,43,Business travel,Eco,347,3,1,5,1,4,3,4,4,3,5,4,3,4,4,0,0.0,satisfied +94065,83337,Female,Loyal Customer,60,Personal Travel,Eco,2105,4,4,5,3,2,3,3,4,4,5,2,3,4,3,0,0.0,neutral or dissatisfied +94066,129393,Male,Loyal Customer,48,Business travel,Business,3629,1,1,1,1,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +94067,109194,Male,Loyal Customer,72,Business travel,Business,1828,4,1,2,2,5,2,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +94068,15432,Male,Loyal Customer,39,Business travel,Business,3593,3,3,5,3,4,4,4,4,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +94069,110817,Female,Loyal Customer,57,Personal Travel,Eco,1105,3,1,3,3,2,4,5,2,2,3,2,5,2,4,0,6.0,neutral or dissatisfied +94070,78938,Male,Loyal Customer,9,Personal Travel,Eco,500,2,5,2,3,2,2,2,2,2,4,2,3,4,2,0,0.0,neutral or dissatisfied +94071,94359,Male,Loyal Customer,55,Business travel,Business,293,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +94072,93230,Female,Loyal Customer,46,Personal Travel,Eco,1460,3,5,3,5,2,4,4,4,4,3,4,3,4,5,21,19.0,neutral or dissatisfied +94073,80587,Male,Loyal Customer,41,Personal Travel,Eco,1747,2,5,2,3,4,2,4,4,3,5,2,2,2,4,0,0.0,neutral or dissatisfied +94074,49348,Female,Loyal Customer,40,Business travel,Eco,110,3,4,3,4,3,4,3,3,1,1,1,1,2,3,0,0.0,satisfied +94075,14895,Female,disloyal Customer,30,Business travel,Eco,315,4,4,4,4,4,4,4,4,4,2,4,2,4,4,0,8.0,neutral or dissatisfied +94076,100303,Male,Loyal Customer,25,Business travel,Business,1011,4,4,4,4,4,4,4,4,5,5,5,3,4,4,0,0.0,satisfied +94077,68580,Female,Loyal Customer,29,Personal Travel,Eco,1616,3,4,3,2,2,3,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +94078,110240,Male,Loyal Customer,41,Business travel,Business,3369,2,4,4,4,3,3,3,2,2,2,2,3,2,4,6,6.0,neutral or dissatisfied +94079,33283,Female,Loyal Customer,26,Personal Travel,Eco Plus,102,2,5,2,1,3,2,3,3,1,2,4,1,4,3,68,65.0,neutral or dissatisfied +94080,97087,Male,disloyal Customer,25,Business travel,Business,1208,0,4,0,2,3,0,3,3,5,2,3,4,5,3,83,70.0,satisfied +94081,124169,Male,Loyal Customer,31,Personal Travel,Eco,2133,3,3,3,4,1,3,1,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +94082,47334,Male,Loyal Customer,27,Business travel,Business,501,2,1,1,1,2,2,2,2,3,1,3,3,4,2,79,59.0,neutral or dissatisfied +94083,91660,Male,Loyal Customer,20,Personal Travel,Eco,1199,3,4,3,3,3,3,3,3,4,3,4,1,5,3,9,5.0,neutral or dissatisfied +94084,60018,Male,Loyal Customer,33,Personal Travel,Eco,997,4,4,4,2,3,4,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +94085,36789,Female,disloyal Customer,80,Business travel,Business,1111,3,3,3,3,3,3,3,3,5,3,3,3,1,3,0,47.0,neutral or dissatisfied +94086,72690,Male,Loyal Customer,43,Personal Travel,Eco,918,3,5,3,1,5,3,5,5,4,5,4,3,5,5,22,9.0,neutral or dissatisfied +94087,59337,Female,disloyal Customer,13,Business travel,Eco,1412,3,3,3,3,2,3,2,2,3,2,3,5,5,2,0,0.0,neutral or dissatisfied +94088,101988,Female,Loyal Customer,60,Personal Travel,Eco,628,2,1,2,3,3,2,2,4,4,2,4,1,4,2,16,4.0,neutral or dissatisfied +94089,83979,Male,disloyal Customer,45,Business travel,Eco,321,3,3,3,2,3,3,3,3,2,4,3,4,2,3,1,0.0,neutral or dissatisfied +94090,14435,Male,Loyal Customer,32,Business travel,Business,761,1,1,1,1,5,5,5,5,3,5,1,4,5,5,0,0.0,satisfied +94091,55131,Male,Loyal Customer,30,Personal Travel,Eco,1609,3,1,2,2,5,2,5,5,1,5,1,4,2,5,0,8.0,neutral or dissatisfied +94092,101709,Female,Loyal Customer,53,Business travel,Eco,1624,1,2,2,2,4,3,3,2,2,1,2,3,2,2,4,0.0,neutral or dissatisfied +94093,120038,Male,Loyal Customer,60,Business travel,Business,3983,5,2,5,5,3,4,4,4,4,4,4,3,4,3,0,6.0,satisfied +94094,106660,Male,disloyal Customer,19,Business travel,Eco,1267,1,1,1,4,1,1,4,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +94095,74942,Female,disloyal Customer,29,Business travel,Eco,2475,2,2,2,3,3,2,4,3,2,3,2,4,3,3,0,0.0,neutral or dissatisfied +94096,126958,Male,Loyal Customer,28,Business travel,Business,1877,2,2,2,2,5,4,5,5,3,5,4,3,5,5,11,3.0,satisfied +94097,9762,Male,Loyal Customer,47,Business travel,Business,1961,2,3,2,2,2,5,5,4,4,4,4,4,4,4,55,41.0,satisfied +94098,116064,Female,Loyal Customer,10,Personal Travel,Eco,337,4,3,4,3,2,4,2,2,2,1,4,2,3,2,30,37.0,neutral or dissatisfied +94099,18620,Female,Loyal Customer,68,Personal Travel,Eco,253,2,5,0,3,2,5,3,5,5,0,5,1,5,2,0,0.0,neutral or dissatisfied +94100,15083,Female,Loyal Customer,37,Business travel,Business,2114,1,2,2,2,5,4,3,1,1,1,1,3,1,1,64,50.0,neutral or dissatisfied +94101,78804,Female,Loyal Customer,26,Personal Travel,Eco,554,1,1,1,3,4,1,5,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +94102,65159,Male,Loyal Customer,25,Personal Travel,Eco,469,4,4,4,3,2,4,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +94103,34600,Male,Loyal Customer,59,Personal Travel,Eco,1598,2,5,2,1,2,3,3,3,4,5,5,3,4,3,199,180.0,neutral or dissatisfied +94104,71852,Female,Loyal Customer,72,Business travel,Business,152,5,5,5,5,2,5,2,5,5,5,3,1,5,3,0,0.0,satisfied +94105,103531,Female,Loyal Customer,44,Business travel,Business,2652,1,1,1,1,3,4,5,4,4,4,4,3,4,4,35,36.0,satisfied +94106,43894,Male,disloyal Customer,24,Business travel,Eco,144,1,2,1,2,2,1,4,2,1,5,1,2,1,2,0,0.0,neutral or dissatisfied +94107,121704,Male,disloyal Customer,38,Business travel,Business,683,4,4,4,3,1,4,1,1,5,5,4,5,5,1,0,0.0,satisfied +94108,31552,Male,Loyal Customer,59,Personal Travel,Eco,846,3,4,3,3,4,3,2,4,4,4,4,3,5,4,14,8.0,neutral or dissatisfied +94109,88042,Female,Loyal Customer,41,Business travel,Business,594,3,3,3,3,5,5,5,4,4,5,5,5,4,5,160,216.0,satisfied +94110,6741,Female,Loyal Customer,51,Business travel,Business,2235,3,5,3,3,2,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +94111,53620,Male,Loyal Customer,64,Business travel,Business,1874,2,3,3,3,2,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +94112,121514,Female,disloyal Customer,34,Business travel,Business,912,4,4,4,5,4,4,4,4,3,2,4,5,5,4,0,1.0,neutral or dissatisfied +94113,118974,Female,Loyal Customer,68,Personal Travel,Eco,570,3,3,3,4,4,3,3,1,1,3,1,4,1,4,2,2.0,neutral or dissatisfied +94114,11615,Female,Loyal Customer,56,Personal Travel,Eco,468,3,1,3,4,1,4,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +94115,7917,Female,Loyal Customer,20,Personal Travel,Eco,1020,2,5,3,3,3,3,3,3,2,4,2,1,5,3,11,2.0,neutral or dissatisfied +94116,90057,Male,Loyal Customer,16,Business travel,Eco,957,2,4,4,4,2,2,4,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +94117,118525,Male,Loyal Customer,19,Business travel,Business,3381,4,4,4,4,3,3,3,3,4,3,5,3,5,3,0,0.0,satisfied +94118,38438,Male,Loyal Customer,22,Business travel,Eco,2277,4,5,5,5,4,4,4,4,5,3,3,1,1,4,3,0.0,satisfied +94119,129237,Male,Loyal Customer,44,Business travel,Business,1464,2,3,3,3,4,2,2,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +94120,75446,Female,disloyal Customer,30,Business travel,Eco,1077,3,3,3,3,5,3,5,5,1,4,2,4,4,5,5,0.0,neutral or dissatisfied +94121,41842,Male,Loyal Customer,49,Personal Travel,Eco,462,2,4,5,4,4,5,4,4,4,2,4,5,4,4,0,17.0,neutral or dissatisfied +94122,42258,Female,Loyal Customer,36,Business travel,Business,2178,3,3,3,3,1,5,2,5,5,5,5,5,5,3,0,0.0,satisfied +94123,121980,Male,Loyal Customer,54,Business travel,Business,2214,2,2,2,2,4,4,5,4,4,4,4,5,4,5,1,2.0,satisfied +94124,19012,Male,Loyal Customer,39,Business travel,Business,2249,2,2,2,2,4,5,5,5,5,5,5,1,5,2,0,0.0,satisfied +94125,12127,Male,Loyal Customer,45,Business travel,Eco Plus,1097,4,3,3,3,4,4,4,4,3,1,5,4,2,4,156,161.0,satisfied +94126,80943,Male,Loyal Customer,63,Personal Travel,Eco,352,2,5,2,2,4,2,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +94127,108725,Male,Loyal Customer,60,Business travel,Eco,591,4,2,2,2,4,4,4,4,1,5,3,1,3,4,34,33.0,neutral or dissatisfied +94128,120553,Male,Loyal Customer,27,Business travel,Business,2176,3,2,2,2,3,2,3,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +94129,110380,Female,Loyal Customer,69,Business travel,Business,842,2,2,2,2,4,4,4,2,2,2,2,1,2,2,8,0.0,neutral or dissatisfied +94130,127398,Male,disloyal Customer,29,Business travel,Eco,868,1,1,1,3,3,1,3,3,3,1,4,1,3,3,5,0.0,neutral or dissatisfied +94131,125657,Male,disloyal Customer,42,Business travel,Business,759,3,3,3,1,4,3,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +94132,84914,Female,Loyal Customer,26,Personal Travel,Eco,547,3,1,3,2,1,3,1,1,4,1,3,3,3,1,13,2.0,neutral or dissatisfied +94133,92874,Male,Loyal Customer,39,Business travel,Business,2212,1,1,1,1,2,5,4,4,4,4,5,5,4,5,35,40.0,satisfied +94134,30080,Male,Loyal Customer,40,Personal Travel,Eco,539,2,5,2,3,2,2,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +94135,98165,Female,Loyal Customer,22,Personal Travel,Eco,562,3,2,3,4,4,3,4,4,3,1,4,1,3,4,35,26.0,neutral or dissatisfied +94136,4630,Female,disloyal Customer,32,Business travel,Business,364,4,4,4,4,4,5,5,4,3,4,4,5,5,5,140,135.0,neutral or dissatisfied +94137,16033,Male,Loyal Customer,39,Personal Travel,Eco,780,2,5,2,1,4,2,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +94138,6448,Female,Loyal Customer,61,Personal Travel,Eco,315,3,4,3,3,1,5,3,2,2,3,2,5,2,1,0,0.0,neutral or dissatisfied +94139,95389,Female,Loyal Customer,70,Personal Travel,Eco,562,2,4,2,1,5,4,5,4,4,2,1,4,4,5,0,0.0,neutral or dissatisfied +94140,1449,Male,disloyal Customer,48,Business travel,Business,772,2,2,2,2,2,2,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +94141,72359,Male,Loyal Customer,55,Business travel,Business,985,3,3,3,3,2,4,4,3,3,4,3,5,3,3,0,2.0,satisfied +94142,64723,Female,Loyal Customer,54,Business travel,Business,2486,1,1,1,1,4,5,4,5,5,5,4,3,5,5,5,0.0,satisfied +94143,68741,Female,Loyal Customer,43,Business travel,Business,185,3,3,3,3,2,3,3,5,5,4,3,4,5,5,0,23.0,satisfied +94144,107456,Male,Loyal Customer,15,Personal Travel,Eco Plus,468,3,5,3,1,5,3,5,5,4,5,5,4,4,5,20,21.0,neutral or dissatisfied +94145,59624,Female,Loyal Customer,40,Business travel,Business,787,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +94146,6805,Female,Loyal Customer,59,Business travel,Business,3708,1,3,5,3,2,1,2,1,1,1,1,3,1,1,23,14.0,neutral or dissatisfied +94147,74903,Male,Loyal Customer,58,Business travel,Business,2586,1,1,1,1,2,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +94148,25620,Female,Loyal Customer,40,Business travel,Business,3583,4,4,3,4,4,3,3,2,2,2,2,4,2,4,1,0.0,satisfied +94149,83333,Female,Loyal Customer,22,Business travel,Business,2105,4,4,4,4,2,2,2,2,5,5,2,3,2,2,0,0.0,satisfied +94150,128103,Female,Loyal Customer,14,Business travel,Eco Plus,2917,4,5,5,5,4,3,4,3,5,2,4,4,1,4,5,26.0,neutral or dissatisfied +94151,82701,Male,Loyal Customer,48,Business travel,Eco,232,4,5,5,5,4,4,4,4,5,1,1,4,3,4,0,0.0,satisfied +94152,35402,Female,disloyal Customer,35,Business travel,Eco,1097,3,3,3,1,1,3,2,1,4,4,2,3,3,1,0,29.0,neutral or dissatisfied +94153,107371,Female,Loyal Customer,41,Business travel,Eco Plus,584,2,1,2,1,4,2,2,2,2,2,2,2,2,2,6,2.0,neutral or dissatisfied +94154,117424,Female,Loyal Customer,62,Business travel,Business,1460,3,3,4,3,1,3,3,3,3,3,3,4,3,1,43,25.0,neutral or dissatisfied +94155,68612,Female,disloyal Customer,27,Business travel,Business,237,3,3,3,3,3,3,3,3,3,3,4,3,4,3,199,188.0,neutral or dissatisfied +94156,111962,Male,Loyal Customer,32,Business travel,Business,3861,2,2,2,2,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +94157,22124,Male,Loyal Customer,18,Personal Travel,Eco,694,3,5,3,3,5,3,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +94158,68702,Male,Loyal Customer,29,Personal Travel,Eco,175,4,5,0,1,3,0,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +94159,57748,Female,disloyal Customer,21,Business travel,Eco,2704,1,1,1,4,1,5,5,3,2,5,4,5,4,5,10,0.0,neutral or dissatisfied +94160,36048,Female,Loyal Customer,63,Business travel,Business,399,3,2,3,3,5,1,1,2,2,2,2,4,2,5,0,0.0,satisfied +94161,111775,Female,Loyal Customer,40,Business travel,Business,1620,4,4,4,4,3,5,5,5,5,5,5,4,5,4,75,73.0,satisfied +94162,82171,Female,Loyal Customer,67,Personal Travel,Eco,237,1,4,1,2,3,4,5,2,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +94163,110852,Male,Loyal Customer,33,Business travel,Business,2465,4,4,4,4,2,2,2,2,5,4,5,3,5,2,0,0.0,satisfied +94164,122456,Male,Loyal Customer,40,Business travel,Business,808,5,5,5,5,3,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +94165,97939,Female,disloyal Customer,59,Business travel,Eco,483,2,2,2,3,2,2,4,3,1,3,4,4,1,4,179,168.0,neutral or dissatisfied +94166,48579,Female,Loyal Customer,32,Personal Travel,Eco,959,2,5,2,4,1,2,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +94167,10711,Female,Loyal Customer,48,Business travel,Business,3391,2,5,5,5,2,4,4,2,2,2,2,3,2,1,19,10.0,neutral or dissatisfied +94168,120653,Female,Loyal Customer,41,Business travel,Eco,280,1,2,2,2,1,1,1,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +94169,14007,Male,Loyal Customer,25,Business travel,Business,2391,3,3,3,3,4,5,5,5,1,5,3,5,2,5,178,153.0,satisfied +94170,43062,Male,Loyal Customer,46,Business travel,Eco,259,5,2,2,2,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +94171,123376,Male,Loyal Customer,53,Personal Travel,Eco,644,2,4,2,1,2,2,2,2,3,3,5,5,4,2,0,16.0,neutral or dissatisfied +94172,16793,Male,Loyal Customer,22,Business travel,Business,1017,5,5,5,5,4,5,4,4,5,2,5,2,4,4,0,0.0,satisfied +94173,35931,Female,Loyal Customer,53,Business travel,Business,3329,3,3,3,3,3,1,1,2,2,2,2,3,2,3,0,5.0,satisfied +94174,9353,Male,disloyal Customer,58,Business travel,Business,401,4,4,4,2,3,4,3,3,4,2,4,4,5,3,1,0.0,satisfied +94175,28596,Female,Loyal Customer,40,Business travel,Business,2614,1,1,3,1,2,4,5,5,5,4,5,3,5,5,20,0.0,satisfied +94176,7649,Female,disloyal Customer,22,Business travel,Eco,767,5,5,5,5,1,5,2,1,5,2,5,4,4,1,0,0.0,satisfied +94177,109851,Male,Loyal Customer,40,Business travel,Business,1130,2,5,5,5,1,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +94178,34780,Male,Loyal Customer,37,Personal Travel,Eco,264,2,1,2,4,2,2,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +94179,51747,Male,Loyal Customer,45,Personal Travel,Eco,370,3,5,3,3,4,3,4,4,1,2,2,5,1,4,0,0.0,neutral or dissatisfied +94180,115492,Female,Loyal Customer,47,Business travel,Business,3966,3,3,3,3,2,5,4,4,4,4,4,5,4,5,5,0.0,satisfied +94181,113757,Male,Loyal Customer,43,Personal Travel,Eco,236,1,4,1,2,2,1,4,2,4,4,5,4,4,2,2,0.0,neutral or dissatisfied +94182,35079,Female,Loyal Customer,39,Business travel,Business,1818,2,2,2,2,2,5,3,5,5,5,5,1,5,5,0,6.0,satisfied +94183,91184,Female,Loyal Customer,27,Personal Travel,Eco,270,4,4,4,3,5,4,5,5,1,2,3,2,3,5,0,0.0,satisfied +94184,129181,Male,Loyal Customer,25,Business travel,Business,2288,4,4,4,4,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +94185,52090,Male,disloyal Customer,29,Business travel,Business,351,3,3,3,5,3,3,3,3,3,4,5,1,4,3,0,0.0,neutral or dissatisfied +94186,128100,Female,Loyal Customer,63,Personal Travel,Eco,2860,2,5,2,1,2,4,4,5,4,5,5,4,3,4,0,16.0,neutral or dissatisfied +94187,101804,Male,Loyal Customer,58,Business travel,Business,1521,4,4,4,4,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +94188,73101,Female,Loyal Customer,30,Business travel,Business,2174,5,5,5,5,5,5,5,5,4,2,3,3,5,5,0,0.0,satisfied +94189,73228,Female,Loyal Customer,28,Personal Travel,Eco,946,3,2,3,2,5,3,4,5,4,2,3,2,2,5,0,0.0,neutral or dissatisfied +94190,34636,Male,Loyal Customer,43,Business travel,Eco,427,2,4,4,4,2,2,2,2,4,1,2,2,3,2,0,13.0,neutral or dissatisfied +94191,128733,Female,disloyal Customer,37,Business travel,Business,1235,4,4,4,4,5,4,5,5,3,2,5,5,4,5,0,5.0,neutral or dissatisfied +94192,106206,Male,Loyal Customer,13,Personal Travel,Eco Plus,436,4,5,4,2,4,4,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +94193,107637,Female,Loyal Customer,41,Business travel,Business,251,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,12.0,satisfied +94194,128630,Male,Loyal Customer,35,Personal Travel,Eco,954,4,4,5,3,1,5,1,1,2,3,2,2,5,1,0,0.0,satisfied +94195,96105,Female,Loyal Customer,43,Personal Travel,Eco,1235,1,5,1,2,3,5,2,1,1,1,1,4,1,2,0,1.0,neutral or dissatisfied +94196,15195,Male,disloyal Customer,25,Business travel,Eco,544,1,1,1,3,2,1,2,2,1,2,2,4,3,2,0,0.0,neutral or dissatisfied +94197,66583,Female,Loyal Customer,43,Business travel,Business,3197,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,8.0,satisfied +94198,37289,Male,Loyal Customer,43,Business travel,Eco,944,2,2,3,3,2,2,2,2,4,2,3,5,1,2,13,7.0,satisfied +94199,2780,Female,Loyal Customer,42,Business travel,Business,1847,3,3,3,3,5,4,4,4,4,4,4,4,4,4,35,35.0,satisfied +94200,122357,Male,Loyal Customer,59,Business travel,Business,1900,4,4,2,4,4,5,5,4,4,4,4,4,4,3,87,69.0,satisfied +94201,98940,Male,disloyal Customer,27,Business travel,Eco,543,2,1,3,4,5,3,5,5,1,5,4,2,3,5,13,12.0,neutral or dissatisfied +94202,64285,Male,Loyal Customer,35,Business travel,Business,2922,3,3,3,3,4,5,4,1,1,2,1,3,1,5,0,0.0,satisfied +94203,30870,Male,Loyal Customer,20,Business travel,Business,1546,3,2,2,2,3,3,3,3,3,1,4,4,3,3,11,8.0,neutral or dissatisfied +94204,46464,Female,Loyal Customer,49,Business travel,Business,1533,3,4,4,4,3,4,3,2,2,2,3,4,2,1,0,6.0,neutral or dissatisfied +94205,23186,Female,Loyal Customer,42,Personal Travel,Eco,300,4,5,5,4,3,5,5,4,4,5,4,5,4,5,75,93.0,neutral or dissatisfied +94206,79454,Female,disloyal Customer,26,Business travel,Business,1183,2,0,2,5,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +94207,36941,Female,Loyal Customer,30,Business travel,Business,718,2,2,2,2,1,2,1,1,5,2,3,3,5,1,0,0.0,satisfied +94208,58030,Female,Loyal Customer,12,Business travel,Business,1721,2,2,2,2,4,4,4,4,4,3,3,3,5,4,1,0.0,satisfied +94209,118564,Female,Loyal Customer,42,Business travel,Business,3751,2,2,2,2,4,4,4,3,2,4,4,4,3,4,186,188.0,satisfied +94210,29018,Female,Loyal Customer,48,Business travel,Eco,279,3,5,5,5,3,3,3,3,3,3,3,2,3,3,7,2.0,neutral or dissatisfied +94211,27005,Male,Loyal Customer,38,Business travel,Business,3391,2,2,2,2,4,5,2,5,5,5,5,1,5,5,0,0.0,satisfied +94212,16236,Female,Loyal Customer,56,Business travel,Business,1650,3,2,2,2,2,3,4,3,3,2,3,4,3,4,0,18.0,neutral or dissatisfied +94213,52483,Male,Loyal Customer,11,Personal Travel,Eco Plus,455,2,4,2,1,5,2,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +94214,89677,Female,Loyal Customer,71,Business travel,Business,3060,1,5,5,5,1,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +94215,33304,Male,Loyal Customer,43,Personal Travel,Eco Plus,216,3,4,3,4,3,3,3,3,1,4,4,5,4,3,0,0.0,neutral or dissatisfied +94216,129584,Male,Loyal Customer,44,Business travel,Business,2380,0,0,0,4,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +94217,85561,Male,Loyal Customer,33,Business travel,Eco,259,1,2,2,2,1,2,1,1,1,2,4,1,3,1,41,42.0,neutral or dissatisfied +94218,65162,Female,Loyal Customer,49,Personal Travel,Eco,247,3,4,3,2,5,4,5,2,2,3,2,5,2,4,15,3.0,neutral or dissatisfied +94219,31334,Male,Loyal Customer,38,Business travel,Eco,1062,5,1,1,1,5,5,5,5,5,3,5,1,1,5,0,0.0,satisfied +94220,71019,Male,disloyal Customer,28,Business travel,Business,802,5,5,5,5,2,5,2,2,3,3,4,5,4,2,34,4.0,satisfied +94221,36658,Male,Loyal Customer,66,Personal Travel,Eco,1249,2,4,2,1,2,4,2,3,4,4,5,2,4,2,35,154.0,neutral or dissatisfied +94222,64843,Female,disloyal Customer,36,Business travel,Eco,190,4,2,4,4,5,4,5,5,1,2,3,2,3,5,29,13.0,neutral or dissatisfied +94223,58630,Male,Loyal Customer,42,Business travel,Business,867,4,4,4,4,4,5,4,5,5,5,5,5,5,5,24,9.0,satisfied +94224,75662,Female,Loyal Customer,43,Business travel,Business,304,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +94225,63382,Male,Loyal Customer,56,Personal Travel,Eco,372,3,2,3,3,4,3,1,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +94226,17678,Male,Loyal Customer,32,Personal Travel,Eco Plus,282,3,4,3,5,2,3,1,2,4,4,5,2,5,2,0,6.0,neutral or dissatisfied +94227,47010,Female,Loyal Customer,23,Business travel,Business,2010,3,3,3,3,5,5,5,5,2,1,4,3,4,5,27,22.0,satisfied +94228,79624,Female,Loyal Customer,40,Business travel,Business,2172,2,2,2,2,2,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +94229,60370,Female,Loyal Customer,56,Business travel,Business,1452,1,4,4,4,5,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +94230,77748,Male,Loyal Customer,56,Business travel,Business,2627,1,1,1,1,2,3,4,4,4,4,4,4,4,5,16,43.0,satisfied +94231,113501,Male,Loyal Customer,47,Business travel,Business,2043,4,4,5,4,5,5,4,4,4,4,4,4,4,5,37,37.0,satisfied +94232,35870,Male,Loyal Customer,22,Personal Travel,Eco,1065,3,5,3,5,1,3,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +94233,38471,Female,Loyal Customer,48,Business travel,Business,2201,1,1,1,1,4,2,3,5,5,5,5,1,5,4,110,96.0,satisfied +94234,87896,Female,Loyal Customer,45,Business travel,Business,646,4,4,4,4,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +94235,66298,Male,disloyal Customer,19,Business travel,Eco,852,3,3,3,3,2,3,2,2,1,1,4,3,3,2,13,7.0,neutral or dissatisfied +94236,28445,Female,Loyal Customer,31,Personal Travel,Eco,2496,3,5,3,4,3,2,2,3,4,4,5,2,3,2,27,38.0,neutral or dissatisfied +94237,37798,Female,disloyal Customer,38,Business travel,Eco Plus,572,2,2,2,1,3,2,5,3,5,2,1,5,5,3,0,0.0,neutral or dissatisfied +94238,4550,Male,Loyal Customer,36,Personal Travel,Eco Plus,719,3,4,3,3,3,3,3,3,1,3,2,3,1,3,14,13.0,neutral or dissatisfied +94239,36707,Female,Loyal Customer,65,Personal Travel,Eco,1211,4,4,4,1,1,3,1,1,1,4,1,3,1,4,59,63.0,neutral or dissatisfied +94240,50644,Male,Loyal Customer,18,Personal Travel,Eco,209,2,5,0,3,3,0,3,3,5,5,3,5,3,3,0,0.0,neutral or dissatisfied +94241,5167,Male,Loyal Customer,60,Business travel,Business,3967,4,4,5,4,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +94242,46584,Female,disloyal Customer,27,Business travel,Eco,152,5,4,5,3,1,5,1,1,4,1,3,3,2,1,0,0.0,satisfied +94243,18557,Male,disloyal Customer,27,Business travel,Eco,262,1,1,1,2,5,1,5,5,3,5,3,2,2,5,0,0.0,neutral or dissatisfied +94244,120690,Male,Loyal Customer,30,Personal Travel,Eco,280,1,5,4,2,2,4,2,2,3,2,5,4,5,2,0,11.0,neutral or dissatisfied +94245,112140,Male,Loyal Customer,40,Business travel,Business,1548,1,1,2,1,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +94246,10536,Male,Loyal Customer,52,Business travel,Business,74,5,5,3,5,5,4,5,4,4,4,5,3,4,3,0,0.0,satisfied +94247,38322,Male,Loyal Customer,37,Personal Travel,Business,1050,1,5,1,3,5,4,4,5,5,1,4,5,5,4,0,0.0,neutral or dissatisfied +94248,62416,Male,disloyal Customer,42,Business travel,Business,913,4,4,4,3,4,4,4,4,3,3,3,4,4,4,23,17.0,satisfied +94249,42089,Female,Loyal Customer,47,Business travel,Business,3509,4,4,4,4,3,5,4,5,5,5,5,4,5,3,13,17.0,satisfied +94250,84350,Female,Loyal Customer,40,Business travel,Eco,606,4,5,1,5,4,4,4,4,2,1,4,2,3,4,108,105.0,neutral or dissatisfied +94251,126776,Female,Loyal Customer,54,Personal Travel,Eco Plus,2402,1,4,1,2,4,5,4,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +94252,116561,Female,Loyal Customer,11,Personal Travel,Eco,358,3,5,3,2,1,3,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +94253,41452,Female,Loyal Customer,60,Business travel,Business,1242,4,4,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +94254,41560,Male,Loyal Customer,70,Business travel,Eco,1028,4,4,4,4,4,4,4,4,4,2,2,5,4,4,0,0.0,satisfied +94255,73311,Female,Loyal Customer,53,Business travel,Business,1005,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +94256,127163,Female,Loyal Customer,39,Personal Travel,Eco,646,3,1,3,1,1,3,1,1,1,4,2,3,1,1,0,0.0,neutral or dissatisfied +94257,107871,Female,Loyal Customer,70,Personal Travel,Eco,228,3,1,3,3,2,3,3,2,2,3,2,3,2,3,25,20.0,neutral or dissatisfied +94258,66258,Male,Loyal Customer,12,Personal Travel,Eco,460,3,3,3,4,3,3,3,3,1,4,2,1,5,3,0,0.0,neutral or dissatisfied +94259,46182,Male,Loyal Customer,40,Personal Travel,Eco Plus,627,3,1,3,4,5,3,5,5,2,1,3,3,4,5,34,53.0,neutral or dissatisfied +94260,98034,Female,Loyal Customer,62,Personal Travel,Eco Plus,1014,2,1,3,2,3,1,2,1,1,3,1,4,1,1,0,12.0,neutral or dissatisfied +94261,84275,Male,Loyal Customer,49,Business travel,Eco,334,2,4,4,4,2,2,2,2,4,5,3,1,4,2,0,0.0,neutral or dissatisfied +94262,59842,Male,Loyal Customer,47,Business travel,Business,1917,5,5,5,5,5,5,5,5,5,5,5,4,5,3,8,2.0,satisfied +94263,20857,Female,Loyal Customer,39,Personal Travel,Eco,357,2,5,2,3,2,4,4,4,4,5,5,4,3,4,222,219.0,neutral or dissatisfied +94264,127527,Male,disloyal Customer,24,Business travel,Eco,1009,5,5,5,2,5,5,2,5,3,2,5,3,4,5,4,0.0,satisfied +94265,62339,Male,Loyal Customer,54,Business travel,Business,3728,1,1,2,1,5,5,4,4,4,3,4,4,4,5,0,1.0,satisfied +94266,103874,Female,Loyal Customer,70,Personal Travel,Eco,634,3,5,3,1,2,5,5,5,5,3,1,5,5,3,0,0.0,neutral or dissatisfied +94267,27972,Male,Loyal Customer,15,Personal Travel,Eco,1616,4,4,4,4,1,4,1,1,4,5,5,3,5,1,2,0.0,neutral or dissatisfied +94268,28567,Male,disloyal Customer,21,Business travel,Eco,818,3,2,2,1,1,3,1,1,4,5,3,4,5,1,0,0.0,neutral or dissatisfied +94269,13541,Female,Loyal Customer,54,Business travel,Eco,214,4,1,3,1,1,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +94270,79171,Male,Loyal Customer,39,Business travel,Business,2422,5,5,5,5,5,5,5,3,4,5,4,5,5,5,0,0.0,satisfied +94271,119113,Female,Loyal Customer,18,Personal Travel,Eco,1107,3,2,3,3,2,3,2,2,2,1,3,1,2,2,9,0.0,neutral or dissatisfied +94272,97687,Female,Loyal Customer,30,Business travel,Eco Plus,272,2,3,3,3,2,3,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +94273,88627,Male,Loyal Customer,32,Personal Travel,Eco,250,2,4,2,2,3,2,3,3,5,2,5,5,5,3,35,24.0,neutral or dissatisfied +94274,26810,Female,Loyal Customer,14,Personal Travel,Eco,2139,1,5,1,2,1,1,1,1,3,2,5,5,4,1,3,0.0,neutral or dissatisfied +94275,103949,Male,Loyal Customer,36,Business travel,Eco,133,3,2,2,2,3,3,3,3,4,1,2,3,2,3,7,0.0,satisfied +94276,46777,Male,Loyal Customer,64,Personal Travel,Eco Plus,141,3,5,3,2,5,3,5,5,3,4,5,3,1,5,33,27.0,neutral or dissatisfied +94277,74581,Male,disloyal Customer,9,Business travel,Eco,1171,1,1,1,3,2,1,1,2,4,4,2,1,2,2,0,0.0,neutral or dissatisfied +94278,124309,Female,Loyal Customer,37,Business travel,Eco,255,2,5,5,5,2,2,2,2,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +94279,8260,Female,Loyal Customer,35,Personal Travel,Eco,530,2,3,5,3,4,5,4,4,1,1,4,3,4,4,0,0.0,neutral or dissatisfied +94280,51382,Female,Loyal Customer,49,Personal Travel,Eco Plus,193,2,2,0,3,0,1,1,1,2,4,4,1,2,1,150,,neutral or dissatisfied +94281,91909,Female,Loyal Customer,56,Business travel,Business,2475,3,3,3,3,4,5,5,5,5,5,5,5,5,3,16,4.0,satisfied +94282,37892,Female,disloyal Customer,10,Business travel,Eco,1065,1,2,2,2,1,2,1,1,1,3,3,3,2,1,16,3.0,neutral or dissatisfied +94283,82647,Female,Loyal Customer,44,Business travel,Business,2991,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +94284,65924,Male,Loyal Customer,52,Personal Travel,Eco,569,3,2,3,1,4,3,2,4,1,5,2,4,2,4,0,0.0,neutral or dissatisfied +94285,74122,Male,Loyal Customer,23,Business travel,Business,2122,3,3,3,3,5,5,5,5,4,3,5,5,4,5,10,0.0,satisfied +94286,17547,Female,Loyal Customer,30,Business travel,Business,970,4,4,4,4,4,4,4,4,2,5,1,5,1,4,9,0.0,satisfied +94287,85064,Female,disloyal Customer,25,Business travel,Business,874,2,0,3,3,3,3,3,3,5,4,4,3,4,3,0,0.0,neutral or dissatisfied +94288,68933,Male,disloyal Customer,28,Business travel,Business,646,2,2,2,2,4,2,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +94289,6250,Female,Loyal Customer,12,Personal Travel,Eco,413,2,1,2,3,4,2,3,4,4,5,2,1,3,4,19,17.0,neutral or dissatisfied +94290,81409,Female,disloyal Customer,25,Business travel,Business,448,5,0,5,2,3,5,3,3,3,3,5,5,4,3,0,0.0,satisfied +94291,30616,Female,disloyal Customer,39,Business travel,Business,524,1,1,1,4,2,1,2,2,2,2,3,4,4,2,8,21.0,neutral or dissatisfied +94292,4139,Female,Loyal Customer,27,Business travel,Business,2380,2,5,2,5,2,2,2,2,2,1,3,2,2,2,0,0.0,neutral or dissatisfied +94293,165,Male,Loyal Customer,29,Personal Travel,Eco,227,2,5,0,3,2,0,2,2,4,5,5,3,5,2,52,56.0,neutral or dissatisfied +94294,1669,Male,Loyal Customer,20,Personal Travel,Eco Plus,435,3,1,1,3,1,1,1,1,1,5,2,1,2,1,0,0.0,neutral or dissatisfied +94295,81466,Female,disloyal Customer,15,Business travel,Business,528,4,4,4,1,3,4,3,3,3,5,4,3,5,3,0,3.0,satisfied +94296,50353,Male,Loyal Customer,38,Business travel,Eco,262,4,2,2,2,4,4,4,4,4,2,4,3,4,4,0,19.0,neutral or dissatisfied +94297,57710,Male,Loyal Customer,60,Personal Travel,Eco,867,3,4,3,2,2,3,2,2,1,1,3,4,1,2,7,26.0,neutral or dissatisfied +94298,40267,Male,Loyal Customer,67,Personal Travel,Eco,387,0,5,0,1,3,0,3,3,5,5,4,4,4,3,0,0.0,satisfied +94299,16818,Female,Loyal Customer,57,Business travel,Business,3509,4,4,3,4,4,3,5,2,2,2,2,4,2,1,17,10.0,satisfied +94300,113564,Female,disloyal Customer,16,Business travel,Eco,223,5,0,5,4,5,5,5,5,5,3,4,3,5,5,0,0.0,satisfied +94301,112662,Male,Loyal Customer,40,Business travel,Business,3842,4,4,4,4,4,4,5,4,4,4,4,5,4,5,32,24.0,satisfied +94302,19395,Female,Loyal Customer,37,Business travel,Eco,261,4,5,5,5,4,4,4,4,5,5,1,1,5,4,0,0.0,satisfied +94303,9208,Female,Loyal Customer,52,Business travel,Business,3049,3,2,2,2,5,3,3,4,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +94304,79403,Female,Loyal Customer,7,Business travel,Eco,502,4,3,3,4,4,4,4,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +94305,75684,Male,disloyal Customer,46,Business travel,Business,868,3,4,4,5,5,3,2,5,3,5,5,3,4,5,6,0.0,satisfied +94306,1527,Female,Loyal Customer,13,Business travel,Business,3935,1,1,1,1,4,4,4,4,3,5,5,4,5,4,2,0.0,satisfied +94307,28113,Male,disloyal Customer,18,Business travel,Eco,859,5,5,5,5,2,5,2,2,4,4,3,3,3,2,0,0.0,satisfied +94308,98004,Female,Loyal Customer,67,Personal Travel,Eco Plus,483,1,5,5,5,3,4,5,2,2,5,1,4,2,1,5,0.0,neutral or dissatisfied +94309,16387,Female,Loyal Customer,31,Business travel,Eco,463,5,5,5,5,5,5,5,5,5,4,5,4,1,5,0,5.0,satisfied +94310,63976,Female,Loyal Customer,48,Personal Travel,Eco Plus,1158,3,5,3,2,2,4,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +94311,18415,Male,Loyal Customer,41,Business travel,Eco,750,5,5,5,5,5,5,5,5,3,5,5,2,1,5,0,0.0,satisfied +94312,4906,Female,Loyal Customer,57,Business travel,Business,1020,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,9.0,satisfied +94313,7777,Female,Loyal Customer,56,Personal Travel,Eco,1080,5,4,5,4,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +94314,87794,Male,Loyal Customer,51,Business travel,Business,214,1,1,1,1,2,5,4,4,4,4,5,5,4,5,5,0.0,satisfied +94315,7045,Male,Loyal Customer,48,Personal Travel,Eco Plus,299,1,5,1,5,4,1,4,4,5,4,4,3,5,4,16,9.0,neutral or dissatisfied +94316,67121,Male,Loyal Customer,63,Business travel,Eco,985,3,5,5,5,2,3,2,2,2,3,2,1,2,2,0,18.0,neutral or dissatisfied +94317,5750,Male,Loyal Customer,58,Business travel,Business,2820,3,4,5,4,1,2,3,3,3,3,3,4,3,4,14,6.0,neutral or dissatisfied +94318,9692,Male,Loyal Customer,57,Business travel,Business,2517,4,2,2,2,1,4,3,2,2,2,4,3,2,1,18,0.0,neutral or dissatisfied +94319,78312,Female,Loyal Customer,56,Personal Travel,Eco Plus,1598,1,4,1,3,3,3,5,3,3,1,3,5,3,5,0,7.0,neutral or dissatisfied +94320,77150,Male,Loyal Customer,20,Business travel,Business,1865,3,4,3,4,3,3,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +94321,93231,Female,disloyal Customer,24,Business travel,Eco,1460,5,5,5,3,5,5,1,5,3,4,4,3,4,5,31,13.0,satisfied +94322,98435,Female,Loyal Customer,49,Business travel,Business,1910,5,5,5,5,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +94323,41621,Male,Loyal Customer,32,Personal Travel,Eco Plus,1482,1,5,1,3,3,1,3,3,5,4,5,4,4,3,58,56.0,neutral or dissatisfied +94324,115387,Female,Loyal Customer,47,Business travel,Business,446,2,1,1,1,1,2,3,2,2,2,2,1,2,2,3,2.0,neutral or dissatisfied +94325,53567,Male,Loyal Customer,39,Business travel,Eco,1195,3,3,3,3,3,4,3,3,2,5,2,3,5,3,18,0.0,satisfied +94326,102262,Female,Loyal Customer,26,Business travel,Business,3987,4,4,4,4,3,3,3,3,3,2,5,4,4,3,0,0.0,satisfied +94327,86813,Female,disloyal Customer,24,Business travel,Business,692,4,4,4,5,3,4,2,3,4,4,4,3,5,3,0,0.0,satisfied +94328,34413,Male,Loyal Customer,13,Personal Travel,Eco,612,3,3,3,3,2,3,2,2,3,5,3,5,3,2,0,0.0,neutral or dissatisfied +94329,103117,Male,Loyal Customer,39,Personal Travel,Eco,460,4,5,4,5,5,4,3,5,5,2,5,5,1,5,0,0.0,neutral or dissatisfied +94330,43392,Female,Loyal Customer,63,Personal Travel,Eco,463,3,3,3,4,4,3,4,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +94331,68925,Male,Loyal Customer,24,Business travel,Eco Plus,661,5,4,4,4,5,5,3,5,2,2,2,4,5,5,0,0.0,satisfied +94332,34305,Male,Loyal Customer,29,Personal Travel,Eco,280,1,2,1,4,5,1,5,5,3,3,4,4,3,5,16,0.0,neutral or dissatisfied +94333,44919,Female,Loyal Customer,62,Personal Travel,Eco,466,1,5,1,1,4,5,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +94334,20571,Male,disloyal Customer,38,Business travel,Eco,165,1,4,1,4,3,1,5,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +94335,18823,Male,Loyal Customer,22,Business travel,Business,3658,1,5,5,5,1,1,1,1,2,5,4,1,4,1,80,72.0,neutral or dissatisfied +94336,111303,Female,Loyal Customer,56,Business travel,Business,3034,1,2,2,2,2,3,4,1,1,1,1,2,1,3,81,70.0,neutral or dissatisfied +94337,92229,Male,Loyal Customer,69,Personal Travel,Eco,1979,1,2,1,3,1,1,1,1,2,4,4,2,3,1,2,10.0,neutral or dissatisfied +94338,99033,Female,Loyal Customer,39,Business travel,Business,1009,1,1,1,1,3,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +94339,71897,Female,Loyal Customer,30,Personal Travel,Eco,1829,4,5,4,4,3,4,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +94340,67566,Female,Loyal Customer,37,Business travel,Business,3547,2,2,2,2,2,5,5,3,3,2,3,3,3,4,41,10.0,satisfied +94341,12917,Female,Loyal Customer,44,Business travel,Business,641,1,1,1,1,4,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +94342,46020,Male,Loyal Customer,31,Business travel,Business,3865,2,2,2,2,5,5,5,5,2,5,3,1,4,5,0,0.0,satisfied +94343,95069,Male,Loyal Customer,27,Personal Travel,Eco,528,1,4,1,3,1,1,1,1,4,3,5,4,4,1,5,3.0,neutral or dissatisfied +94344,81917,Male,Loyal Customer,54,Business travel,Business,1589,1,1,1,1,3,4,4,4,4,4,4,5,4,3,51,72.0,satisfied +94345,67217,Male,Loyal Customer,22,Personal Travel,Eco,929,1,5,1,4,4,1,4,4,5,5,1,4,3,4,7,0.0,neutral or dissatisfied +94346,90830,Female,Loyal Customer,68,Business travel,Eco,404,3,4,4,4,4,2,3,3,3,3,3,1,3,1,1,19.0,neutral or dissatisfied +94347,22213,Female,Loyal Customer,35,Personal Travel,Eco,633,2,5,2,4,5,2,5,5,5,5,5,4,5,5,55,42.0,neutral or dissatisfied +94348,115531,Female,disloyal Customer,19,Business travel,Eco,480,1,2,1,4,5,1,3,5,2,4,4,2,4,5,28,28.0,neutral or dissatisfied +94349,25401,Female,Loyal Customer,69,Business travel,Eco,1105,1,4,4,4,5,4,3,1,1,1,1,1,1,4,24,13.0,neutral or dissatisfied +94350,106454,Male,disloyal Customer,15,Business travel,Business,1157,0,0,0,4,2,0,2,2,3,5,5,4,5,2,2,0.0,satisfied +94351,66744,Female,Loyal Customer,66,Personal Travel,Eco,802,4,3,4,5,4,5,4,5,5,4,3,3,5,3,59,64.0,neutral or dissatisfied +94352,82887,Female,Loyal Customer,15,Personal Travel,Eco,640,4,4,4,4,1,4,1,1,3,2,5,5,4,1,0,0.0,satisfied +94353,94932,Male,Loyal Customer,37,Business travel,Business,187,1,1,1,1,2,5,2,4,4,4,5,2,4,4,2,3.0,satisfied +94354,128468,Male,Loyal Customer,68,Personal Travel,Eco,621,2,5,2,2,4,2,4,4,3,4,5,4,4,4,10,10.0,neutral or dissatisfied +94355,6323,Female,Loyal Customer,41,Business travel,Business,315,2,1,1,1,4,4,4,2,2,2,2,4,2,2,6,0.0,neutral or dissatisfied +94356,17951,Male,Loyal Customer,36,Business travel,Business,1962,1,1,1,1,2,1,4,4,4,5,4,1,4,1,0,0.0,satisfied +94357,15927,Female,Loyal Customer,31,Business travel,Business,607,1,1,1,1,4,4,4,4,5,4,3,2,1,4,0,0.0,satisfied +94358,129696,Male,Loyal Customer,18,Business travel,Business,1708,2,4,4,4,2,2,2,2,2,1,4,2,4,2,0,22.0,neutral or dissatisfied +94359,120524,Male,Loyal Customer,52,Business travel,Business,3656,2,3,4,3,5,1,1,1,1,1,2,3,1,2,0,0.0,neutral or dissatisfied +94360,48224,Female,Loyal Customer,67,Personal Travel,Eco,259,4,1,4,2,2,2,1,5,5,4,5,3,5,1,7,2.0,neutral or dissatisfied +94361,113994,Female,disloyal Customer,41,Business travel,Business,228,1,0,0,4,5,0,5,5,3,5,3,1,4,5,0,0.0,neutral or dissatisfied +94362,111354,Male,Loyal Customer,55,Personal Travel,Eco,777,1,3,1,2,4,1,4,4,2,2,2,4,2,4,0,23.0,neutral or dissatisfied +94363,108834,Male,Loyal Customer,48,Business travel,Business,3938,1,3,3,3,4,2,3,1,1,1,1,4,1,4,0,12.0,neutral or dissatisfied +94364,3706,Male,Loyal Customer,17,Personal Travel,Eco,431,2,5,2,5,2,2,2,4,2,4,5,2,5,2,234,255.0,neutral or dissatisfied +94365,91738,Female,Loyal Customer,25,Business travel,Business,626,2,4,4,4,2,2,2,2,2,2,3,3,3,2,43,55.0,neutral or dissatisfied +94366,15306,Female,Loyal Customer,29,Business travel,Business,589,2,2,2,2,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +94367,4841,Male,Loyal Customer,79,Business travel,Business,408,2,2,2,2,5,3,3,2,2,2,2,4,2,1,0,8.0,neutral or dissatisfied +94368,96918,Male,Loyal Customer,28,Personal Travel,Eco,972,1,5,1,1,2,1,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +94369,82869,Male,Loyal Customer,49,Business travel,Business,3466,4,2,2,2,4,4,4,4,4,4,4,2,4,4,7,9.0,neutral or dissatisfied +94370,68700,Female,Loyal Customer,16,Personal Travel,Eco,175,2,4,2,3,5,2,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +94371,27661,Male,Loyal Customer,35,Business travel,Business,1107,3,3,3,3,1,5,1,4,4,5,4,4,4,1,0,10.0,satisfied +94372,51475,Female,Loyal Customer,44,Business travel,Business,3551,5,5,3,5,3,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +94373,97063,Male,disloyal Customer,20,Business travel,Eco,1390,2,2,2,4,5,2,5,5,2,4,3,3,4,5,60,56.0,neutral or dissatisfied +94374,43294,Female,Loyal Customer,37,Business travel,Business,2829,5,5,3,5,3,3,2,4,4,4,4,5,4,2,0,1.0,satisfied +94375,94018,Female,Loyal Customer,53,Business travel,Business,2031,1,1,1,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +94376,68716,Male,Loyal Customer,58,Personal Travel,Eco,175,2,5,2,5,5,2,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +94377,69851,Male,disloyal Customer,14,Personal Travel,Eco,1055,4,3,4,4,3,4,3,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +94378,84227,Male,Loyal Customer,53,Personal Travel,Eco,432,3,5,3,3,5,3,2,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +94379,121723,Male,Loyal Customer,44,Personal Travel,Eco Plus,683,2,4,3,4,5,3,5,5,4,4,5,4,5,5,0,8.0,neutral or dissatisfied +94380,6421,Female,Loyal Customer,38,Personal Travel,Eco,240,1,4,1,3,1,1,1,1,3,1,4,4,4,1,55,59.0,neutral or dissatisfied +94381,7663,Male,Loyal Customer,23,Business travel,Eco,604,3,4,4,4,3,3,2,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +94382,79473,Male,Loyal Customer,50,Business travel,Business,760,2,2,5,2,3,5,4,4,4,4,4,4,4,5,27,13.0,satisfied +94383,53706,Female,Loyal Customer,46,Business travel,Eco,808,2,3,3,3,5,3,5,2,2,2,2,2,2,3,0,0.0,satisfied +94384,125610,Male,disloyal Customer,32,Business travel,Business,814,2,2,2,4,3,2,4,3,1,5,4,1,4,3,12,14.0,neutral or dissatisfied +94385,28953,Female,Loyal Customer,39,Business travel,Business,3287,4,2,3,2,3,3,3,4,4,4,4,4,4,2,91,113.0,neutral or dissatisfied +94386,24400,Female,Loyal Customer,53,Business travel,Business,3954,2,4,2,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +94387,120370,Male,Loyal Customer,36,Business travel,Business,449,5,5,5,5,4,4,4,3,2,5,5,4,5,4,163,148.0,satisfied +94388,126562,Male,Loyal Customer,44,Business travel,Business,1558,1,1,1,1,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +94389,44961,Male,Loyal Customer,45,Business travel,Eco Plus,349,5,1,1,1,4,5,4,4,1,4,4,4,2,4,5,8.0,satisfied +94390,123137,Female,Loyal Customer,49,Business travel,Eco,590,4,1,1,1,2,4,3,4,4,4,4,2,4,1,35,52.0,neutral or dissatisfied +94391,426,Female,Loyal Customer,39,Business travel,Business,1770,4,1,1,1,1,3,4,4,4,4,4,1,4,4,0,2.0,neutral or dissatisfied +94392,7212,Female,Loyal Customer,72,Business travel,Business,139,1,4,4,4,2,2,1,2,2,2,1,2,2,3,0,0.0,neutral or dissatisfied +94393,80075,Male,Loyal Customer,41,Business travel,Business,2211,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,18.0,satisfied +94394,51727,Male,Loyal Customer,39,Personal Travel,Eco,369,2,5,2,5,1,2,1,1,4,5,2,5,2,1,0,0.0,neutral or dissatisfied +94395,107810,Female,Loyal Customer,18,Business travel,Business,349,4,4,2,4,4,4,4,4,2,2,3,4,4,4,0,0.0,neutral or dissatisfied +94396,83085,Male,Loyal Customer,38,Business travel,Business,583,1,1,5,1,1,2,5,4,4,4,4,5,4,3,20,16.0,satisfied +94397,90101,Female,disloyal Customer,23,Business travel,Eco,813,1,1,1,4,5,1,5,5,2,4,4,2,4,5,0,0.0,neutral or dissatisfied +94398,124638,Female,Loyal Customer,51,Personal Travel,Eco Plus,1671,2,3,2,3,5,2,4,5,5,2,5,3,5,4,12,23.0,neutral or dissatisfied +94399,28007,Male,Loyal Customer,39,Business travel,Business,1778,1,1,1,1,2,1,4,4,4,5,4,2,4,3,0,8.0,satisfied +94400,117550,Male,disloyal Customer,40,Business travel,Business,347,1,1,1,4,2,1,1,2,5,5,4,3,5,2,5,1.0,neutral or dissatisfied +94401,19508,Female,Loyal Customer,35,Business travel,Eco,566,4,3,2,3,4,5,4,4,4,5,1,1,2,4,0,8.0,satisfied +94402,65183,Male,Loyal Customer,52,Personal Travel,Eco,190,1,4,1,3,2,1,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +94403,1264,Male,Loyal Customer,37,Personal Travel,Eco,134,2,0,0,3,1,0,2,1,4,2,3,2,4,1,1,0.0,neutral or dissatisfied +94404,109517,Female,Loyal Customer,38,Business travel,Business,1542,2,1,1,1,3,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +94405,74540,Female,Loyal Customer,29,Business travel,Eco,1205,3,2,2,2,3,3,3,3,2,2,3,1,2,3,0,36.0,neutral or dissatisfied +94406,59496,Male,Loyal Customer,63,Personal Travel,Eco,811,1,3,0,2,5,0,5,5,2,3,5,2,3,5,0,0.0,neutral or dissatisfied +94407,79910,Female,Loyal Customer,45,Business travel,Business,1089,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +94408,71476,Female,Loyal Customer,53,Personal Travel,Eco,837,3,5,3,2,3,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +94409,121823,Male,disloyal Customer,36,Business travel,Business,337,1,1,1,1,1,1,5,5,4,5,5,5,4,5,170,159.0,neutral or dissatisfied +94410,87095,Female,disloyal Customer,36,Business travel,Eco,194,3,3,3,3,5,3,5,5,1,1,3,3,4,5,0,5.0,neutral or dissatisfied +94411,27142,Male,Loyal Customer,22,Business travel,Business,2677,2,2,2,2,5,4,4,1,3,4,4,4,4,4,0,0.0,satisfied +94412,89331,Female,Loyal Customer,52,Business travel,Business,1587,2,2,2,2,3,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +94413,73043,Male,Loyal Customer,30,Personal Travel,Eco,1096,2,4,2,4,5,2,5,5,3,1,3,3,3,5,0,0.0,neutral or dissatisfied +94414,69924,Female,Loyal Customer,40,Business travel,Business,1671,5,5,5,5,3,3,4,4,4,4,4,3,4,4,0,0.0,satisfied +94415,58890,Male,Loyal Customer,14,Business travel,Business,888,2,2,2,2,2,2,2,2,1,3,3,1,4,2,5,0.0,neutral or dissatisfied +94416,36413,Female,Loyal Customer,51,Business travel,Eco,369,4,5,5,5,2,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +94417,79753,Female,Loyal Customer,41,Business travel,Business,1686,1,1,1,1,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +94418,38317,Female,Loyal Customer,10,Personal Travel,Eco,1666,2,0,2,3,3,2,3,3,3,3,4,3,4,3,17,21.0,neutral or dissatisfied +94419,77189,Male,Loyal Customer,49,Personal Travel,Eco,290,3,5,3,2,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +94420,8014,Female,disloyal Customer,58,Business travel,Business,294,2,2,2,5,1,2,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +94421,51100,Male,Loyal Customer,30,Personal Travel,Eco,109,2,2,2,4,1,2,5,1,2,3,3,4,4,1,0,9.0,neutral or dissatisfied +94422,92823,Male,disloyal Customer,28,Business travel,Eco,753,2,2,2,3,4,2,4,4,3,5,2,2,3,4,0,0.0,neutral or dissatisfied +94423,47494,Female,Loyal Customer,13,Personal Travel,Eco,558,2,2,2,4,5,2,5,5,2,3,4,1,4,5,0,4.0,neutral or dissatisfied +94424,54893,Female,Loyal Customer,20,Personal Travel,Eco,862,1,4,1,4,2,1,2,2,5,3,4,4,4,2,0,1.0,neutral or dissatisfied +94425,87221,Male,Loyal Customer,34,Personal Travel,Eco,946,1,4,1,4,3,1,3,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +94426,9049,Female,Loyal Customer,59,Business travel,Business,108,3,3,3,3,3,5,4,5,5,5,4,4,5,5,0,0.0,satisfied +94427,54859,Male,Loyal Customer,28,Business travel,Eco,985,3,2,2,2,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +94428,37727,Female,Loyal Customer,38,Personal Travel,Eco,1056,3,5,3,3,3,3,3,3,1,1,2,1,3,3,0,0.0,neutral or dissatisfied +94429,104543,Male,Loyal Customer,44,Personal Travel,Eco,1256,3,4,4,2,5,4,5,5,4,2,5,2,1,5,0,0.0,neutral or dissatisfied +94430,55370,Female,Loyal Customer,44,Business travel,Business,2459,4,4,4,4,5,5,5,4,4,5,4,5,4,5,161,201.0,satisfied +94431,127394,Female,Loyal Customer,54,Business travel,Business,1009,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +94432,121813,Male,Loyal Customer,65,Business travel,Business,449,3,5,5,5,3,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +94433,93265,Male,Loyal Customer,44,Business travel,Business,2712,4,4,4,4,4,5,5,4,4,4,4,5,4,3,59,40.0,satisfied +94434,53352,Male,Loyal Customer,31,Business travel,Business,1452,4,4,3,4,4,4,4,4,2,2,3,4,5,4,0,16.0,satisfied +94435,68922,Male,disloyal Customer,35,Business travel,Business,1061,4,4,4,4,2,4,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +94436,83175,Male,Loyal Customer,43,Business travel,Business,1713,4,4,4,4,4,4,5,5,5,5,5,4,5,3,105,95.0,satisfied +94437,96584,Male,Loyal Customer,35,Business travel,Business,3482,1,1,2,1,2,4,5,4,4,4,4,4,4,3,107,98.0,satisfied +94438,97664,Male,Loyal Customer,59,Business travel,Business,1532,5,5,5,5,4,4,4,5,5,5,5,4,5,3,6,0.0,satisfied +94439,61326,Female,Loyal Customer,57,Personal Travel,Eco Plus,862,1,5,2,2,2,4,5,2,2,2,2,3,2,5,10,0.0,neutral or dissatisfied +94440,6821,Male,Loyal Customer,11,Personal Travel,Eco,223,1,5,0,4,3,0,3,3,5,4,4,3,5,3,10,8.0,neutral or dissatisfied +94441,86721,Female,Loyal Customer,16,Business travel,Business,1747,2,3,3,3,2,2,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +94442,103970,Male,disloyal Customer,38,Business travel,Business,533,5,5,5,1,2,5,2,2,5,4,5,4,4,2,0,0.0,satisfied +94443,28114,Female,Loyal Customer,57,Business travel,Eco,873,4,1,1,1,4,1,3,4,4,4,4,3,4,2,0,0.0,satisfied +94444,21924,Female,Loyal Customer,48,Business travel,Eco,551,2,4,4,4,2,1,3,2,2,2,2,3,2,5,45,24.0,satisfied +94445,75302,Male,disloyal Customer,17,Business travel,Eco,1394,5,5,5,3,5,4,4,5,3,5,4,4,5,4,0,0.0,satisfied +94446,98253,Male,Loyal Customer,37,Business travel,Business,1136,1,1,1,1,2,4,4,5,5,4,5,5,5,5,6,16.0,satisfied +94447,74391,Male,Loyal Customer,48,Business travel,Business,2366,1,1,1,1,3,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +94448,65475,Male,Loyal Customer,24,Business travel,Eco,1067,3,4,4,4,3,3,2,3,3,3,1,3,1,3,0,0.0,neutral or dissatisfied +94449,42104,Female,Loyal Customer,55,Business travel,Business,3249,5,5,3,5,5,4,4,4,4,4,4,4,4,4,0,1.0,satisfied +94450,35880,Female,Loyal Customer,54,Personal Travel,Eco,937,2,5,2,4,2,1,4,5,5,2,5,4,5,2,4,15.0,neutral or dissatisfied +94451,95510,Female,Loyal Customer,37,Business travel,Eco Plus,323,3,3,3,3,3,3,3,3,4,2,3,4,3,3,20,12.0,neutral or dissatisfied +94452,18825,Male,Loyal Customer,54,Business travel,Eco,503,2,2,2,2,2,2,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +94453,4366,Male,Loyal Customer,43,Business travel,Business,1768,3,5,5,5,3,3,3,1,3,3,4,3,3,3,242,278.0,neutral or dissatisfied +94454,19332,Female,Loyal Customer,53,Personal Travel,Eco,743,5,4,5,4,2,5,5,5,5,5,5,4,5,5,19,2.0,satisfied +94455,121550,Female,disloyal Customer,34,Business travel,Business,936,1,0,0,5,2,0,2,2,4,4,5,3,5,2,35,20.0,neutral or dissatisfied +94456,97392,Female,disloyal Customer,45,Business travel,Eco Plus,843,1,1,1,4,2,1,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +94457,9453,Male,Loyal Customer,25,Personal Travel,Eco,368,2,5,2,5,3,2,3,3,1,2,5,1,2,3,0,0.0,neutral or dissatisfied +94458,51118,Female,Loyal Customer,28,Personal Travel,Eco,337,2,4,2,1,2,2,2,2,3,2,2,2,4,2,0,0.0,neutral or dissatisfied +94459,96610,Female,Loyal Customer,51,Business travel,Business,1036,3,3,3,3,3,4,5,3,3,3,3,4,3,3,92,104.0,satisfied +94460,97826,Male,Loyal Customer,54,Business travel,Business,395,4,4,4,4,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +94461,13556,Female,Loyal Customer,31,Business travel,Business,2452,5,5,5,5,4,4,3,4,2,5,1,3,4,4,0,0.0,satisfied +94462,21152,Female,Loyal Customer,34,Business travel,Business,3549,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +94463,128091,Male,Loyal Customer,13,Personal Travel,Eco,2845,2,0,2,3,2,5,5,5,5,4,4,5,1,5,4,13.0,neutral or dissatisfied +94464,107300,Male,Loyal Customer,40,Personal Travel,Eco,283,1,5,2,3,1,2,1,1,4,5,5,4,5,1,5,0.0,neutral or dissatisfied +94465,97041,Female,disloyal Customer,37,Business travel,Business,1642,4,4,4,3,1,4,1,1,4,3,4,4,5,1,95,105.0,neutral or dissatisfied +94466,83349,Male,Loyal Customer,38,Business travel,Business,2381,1,3,3,3,1,1,1,4,2,3,4,1,2,1,2,37.0,neutral or dissatisfied +94467,103917,Female,Loyal Customer,51,Business travel,Business,770,1,1,1,1,2,5,5,2,2,3,2,3,2,4,25,24.0,satisfied +94468,13933,Female,Loyal Customer,57,Business travel,Eco,192,5,2,5,2,4,1,5,5,5,5,5,3,5,4,0,0.0,satisfied +94469,110955,Female,Loyal Customer,39,Personal Travel,Eco Plus,545,4,1,4,4,1,4,1,1,1,5,3,3,3,1,0,0.0,neutral or dissatisfied +94470,13258,Female,Loyal Customer,57,Business travel,Eco,657,4,1,1,1,2,3,1,3,3,4,3,4,3,4,0,0.0,satisfied +94471,80948,Male,Loyal Customer,46,Business travel,Business,2419,5,5,5,5,4,5,4,4,4,4,4,3,4,5,3,1.0,satisfied +94472,40182,Male,Loyal Customer,35,Business travel,Business,387,3,3,3,3,2,2,1,5,5,5,5,5,5,2,0,0.0,satisfied +94473,102849,Male,Loyal Customer,32,Personal Travel,Eco,423,1,1,1,4,3,1,3,3,1,2,4,2,4,3,1,0.0,neutral or dissatisfied +94474,18158,Male,Loyal Customer,19,Personal Travel,Eco,430,3,4,3,1,2,3,2,2,5,3,5,3,4,2,0,29.0,neutral or dissatisfied +94475,70791,Male,Loyal Customer,62,Business travel,Business,328,1,1,1,1,2,3,4,1,1,1,1,3,1,3,1,12.0,neutral or dissatisfied +94476,55215,Female,Loyal Customer,32,Business travel,Business,3970,5,5,5,5,5,5,5,5,4,3,4,5,5,5,10,15.0,satisfied +94477,38082,Female,Loyal Customer,64,Business travel,Business,2586,3,3,3,3,1,4,1,4,4,4,4,1,4,2,0,4.0,satisfied +94478,120116,Male,disloyal Customer,40,Business travel,Business,1176,5,5,5,4,5,5,4,5,4,5,3,2,5,5,0,0.0,satisfied +94479,124219,Male,Loyal Customer,50,Business travel,Business,2176,1,1,1,1,2,4,5,5,5,5,5,5,5,3,84,101.0,satisfied +94480,22478,Female,Loyal Customer,32,Personal Travel,Eco,143,5,4,0,3,1,0,1,1,5,5,5,3,5,1,0,2.0,satisfied +94481,127450,Male,Loyal Customer,59,Business travel,Business,2075,4,4,4,4,3,4,4,5,5,5,5,3,5,5,2,0.0,satisfied +94482,101391,Female,Loyal Customer,43,Business travel,Business,1599,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +94483,99267,Male,Loyal Customer,45,Business travel,Business,833,1,1,1,1,4,5,4,4,4,4,4,4,4,5,3,0.0,satisfied +94484,66869,Female,Loyal Customer,26,Business travel,Eco Plus,731,2,2,2,2,2,2,1,2,1,3,2,2,3,2,27,9.0,neutral or dissatisfied +94485,16080,Female,Loyal Customer,27,Business travel,Eco Plus,744,0,0,0,5,4,0,1,4,4,5,2,2,1,4,20,15.0,satisfied +94486,27950,Female,Loyal Customer,16,Business travel,Business,1660,2,3,3,3,2,2,2,2,4,1,3,2,3,2,50,57.0,neutral or dissatisfied +94487,7037,Female,disloyal Customer,23,Business travel,Eco,234,4,4,4,3,4,4,4,4,4,3,4,5,4,4,0,0.0,satisfied +94488,21593,Female,Loyal Customer,38,Business travel,Business,1919,2,2,2,2,2,1,2,4,4,4,4,2,4,3,1,0.0,satisfied +94489,127868,Female,disloyal Customer,26,Business travel,Business,1276,4,4,4,5,3,4,3,3,5,4,5,3,4,3,0,1.0,satisfied +94490,72166,Female,Loyal Customer,51,Personal Travel,Eco Plus,731,3,3,3,1,2,4,4,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +94491,118079,Female,disloyal Customer,23,Business travel,Eco,1276,1,1,1,3,3,1,3,3,4,3,3,2,3,3,49,29.0,neutral or dissatisfied +94492,24610,Male,Loyal Customer,26,Business travel,Business,2869,1,1,1,1,4,4,4,4,4,4,1,4,4,4,0,0.0,satisfied +94493,96527,Male,Loyal Customer,47,Personal Travel,Eco,436,4,4,4,3,2,4,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +94494,3543,Male,disloyal Customer,38,Business travel,Business,227,2,2,2,3,1,2,1,1,4,3,3,3,3,1,85,115.0,neutral or dissatisfied +94495,36261,Female,Loyal Customer,36,Business travel,Eco,612,4,4,4,4,4,5,4,4,5,1,2,3,4,4,0,0.0,satisfied +94496,105377,Female,Loyal Customer,43,Business travel,Business,369,3,5,5,5,5,3,4,3,3,3,3,1,3,3,30,37.0,neutral or dissatisfied +94497,51084,Female,Loyal Customer,38,Personal Travel,Eco,373,3,4,3,1,5,3,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +94498,35292,Female,Loyal Customer,47,Business travel,Eco,972,4,1,4,4,4,4,1,4,4,4,4,2,4,2,0,9.0,satisfied +94499,95211,Male,Loyal Customer,60,Personal Travel,Eco,239,3,4,3,5,3,3,3,3,3,2,5,4,5,3,73,69.0,neutral or dissatisfied +94500,63649,Female,Loyal Customer,52,Business travel,Business,1448,4,4,4,4,3,4,4,5,5,5,5,5,5,3,2,0.0,satisfied +94501,13555,Female,Loyal Customer,51,Business travel,Business,2179,2,2,2,2,5,2,2,5,5,5,5,4,5,1,22,4.0,satisfied +94502,109838,Female,disloyal Customer,26,Business travel,Business,1130,3,3,3,2,5,3,5,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +94503,82815,Male,Loyal Customer,33,Business travel,Business,235,5,5,5,5,5,5,5,5,3,2,5,3,4,5,0,0.0,satisfied +94504,25863,Female,Loyal Customer,56,Personal Travel,Eco,692,1,5,1,3,4,5,4,1,1,1,1,5,1,3,0,0.0,neutral or dissatisfied +94505,19875,Male,Loyal Customer,14,Personal Travel,Business,240,3,3,3,2,2,3,1,2,4,3,4,3,3,2,0,0.0,neutral or dissatisfied +94506,67396,Female,disloyal Customer,24,Business travel,Eco,592,2,0,2,2,5,2,5,5,3,3,4,4,5,5,0,0.0,neutral or dissatisfied +94507,107920,Female,disloyal Customer,26,Business travel,Business,611,2,2,2,3,2,5,5,2,4,3,4,5,1,5,186,203.0,neutral or dissatisfied +94508,42883,Male,Loyal Customer,30,Business travel,Eco Plus,867,5,2,4,2,5,5,5,5,3,3,2,5,5,5,0,0.0,satisfied +94509,40004,Female,disloyal Customer,25,Business travel,Eco,618,5,0,5,3,1,5,1,1,1,3,4,5,2,1,4,0.0,satisfied +94510,56550,Male,Loyal Customer,29,Business travel,Business,2778,4,4,4,4,4,4,4,4,3,5,5,5,4,4,0,0.0,satisfied +94511,110962,Female,Loyal Customer,39,Business travel,Business,240,4,4,4,4,4,4,5,4,4,4,4,5,4,5,5,0.0,satisfied +94512,1245,Female,Loyal Customer,15,Personal Travel,Eco,158,4,5,4,2,5,4,5,5,3,3,4,3,4,5,7,4.0,neutral or dissatisfied +94513,125770,Male,disloyal Customer,26,Business travel,Business,1013,1,1,1,1,4,1,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +94514,49730,Female,Loyal Customer,24,Business travel,Business,3736,1,1,1,1,4,4,4,4,4,2,4,4,1,4,2,3.0,satisfied +94515,41664,Female,disloyal Customer,22,Business travel,Eco,843,3,2,2,4,5,2,5,5,1,2,4,4,3,5,0,4.0,neutral or dissatisfied +94516,14191,Male,disloyal Customer,12,Business travel,Eco,714,3,4,4,3,4,1,5,3,3,4,3,5,2,5,193,189.0,neutral or dissatisfied +94517,110509,Male,disloyal Customer,19,Business travel,Eco,842,2,2,2,4,4,2,4,4,3,1,3,4,3,4,0,14.0,neutral or dissatisfied +94518,15897,Male,disloyal Customer,45,Business travel,Eco,378,3,5,3,4,4,3,4,4,5,5,5,1,5,4,1,0.0,neutral or dissatisfied +94519,50984,Female,Loyal Customer,36,Personal Travel,Eco,372,3,3,3,1,1,3,1,1,3,5,3,3,5,1,0,0.0,neutral or dissatisfied +94520,48245,Male,Loyal Customer,70,Personal Travel,Eco,236,4,5,4,1,4,4,4,5,3,4,5,4,4,4,136,136.0,neutral or dissatisfied +94521,82713,Female,Loyal Customer,60,Personal Travel,Eco,632,1,3,1,3,2,4,3,4,4,1,4,4,4,2,73,85.0,neutral or dissatisfied +94522,112765,Male,Loyal Customer,42,Business travel,Business,590,2,4,4,4,2,4,3,2,2,2,2,1,2,3,48,39.0,neutral or dissatisfied +94523,57160,Male,Loyal Customer,59,Business travel,Business,1824,3,3,1,3,2,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +94524,45854,Female,Loyal Customer,40,Business travel,Eco Plus,391,3,2,5,2,3,3,3,2,4,3,3,3,4,3,225,216.0,neutral or dissatisfied +94525,70213,Female,Loyal Customer,65,Personal Travel,Eco,258,2,3,0,3,2,2,3,4,4,0,4,1,4,2,32,40.0,neutral or dissatisfied +94526,128694,Female,Loyal Customer,29,Business travel,Business,1504,2,2,2,2,3,4,3,3,4,3,5,3,5,3,0,0.0,satisfied +94527,1853,Female,Loyal Customer,26,Personal Travel,Eco Plus,408,3,5,3,5,1,3,1,1,4,2,5,3,4,1,12,40.0,neutral or dissatisfied +94528,75246,Female,Loyal Customer,69,Personal Travel,Eco,1723,4,5,4,2,5,5,5,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +94529,20279,Male,Loyal Customer,51,Personal Travel,Eco,235,4,5,0,1,4,0,4,4,5,5,4,5,5,4,6,0.0,neutral or dissatisfied +94530,83351,Male,Loyal Customer,52,Personal Travel,Business,1124,2,4,2,1,2,4,4,2,2,2,5,5,2,4,9,0.0,neutral or dissatisfied +94531,88482,Female,Loyal Customer,43,Business travel,Business,271,2,1,2,1,4,4,4,2,2,2,2,2,2,1,23,17.0,neutral or dissatisfied +94532,36266,Female,Loyal Customer,60,Business travel,Business,3617,4,5,5,5,1,3,3,4,4,4,4,3,4,2,20,36.0,neutral or dissatisfied +94533,61250,Male,Loyal Customer,58,Personal Travel,Eco,862,2,5,2,3,2,2,3,2,5,3,4,5,4,2,17,30.0,neutral or dissatisfied +94534,116449,Male,Loyal Customer,61,Personal Travel,Eco,337,2,3,2,3,1,2,1,1,2,3,2,3,1,1,0,0.0,neutral or dissatisfied +94535,1111,Female,Loyal Customer,38,Personal Travel,Eco,89,3,5,3,5,3,3,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +94536,97315,Male,Loyal Customer,57,Business travel,Business,2937,0,0,0,1,5,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +94537,86752,Female,Loyal Customer,42,Personal Travel,Eco,821,3,2,3,4,3,4,3,4,4,3,5,4,4,4,0,2.0,neutral or dissatisfied +94538,68189,Female,Loyal Customer,56,Business travel,Business,597,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +94539,107768,Female,Loyal Customer,60,Business travel,Business,2619,4,4,4,4,5,5,4,5,5,4,5,3,5,3,4,0.0,satisfied +94540,117938,Female,Loyal Customer,45,Business travel,Business,365,3,3,3,3,4,4,5,5,5,4,5,4,5,5,7,1.0,satisfied +94541,41450,Female,Loyal Customer,48,Business travel,Business,1334,4,1,1,1,1,2,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +94542,118380,Female,Loyal Customer,49,Business travel,Business,1866,4,4,4,4,2,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +94543,40575,Male,Loyal Customer,53,Business travel,Eco,517,4,2,2,2,4,4,4,4,1,3,4,1,3,4,0,0.0,neutral or dissatisfied +94544,54987,Female,disloyal Customer,26,Business travel,Business,1608,0,0,0,3,5,0,5,5,4,2,5,3,4,5,0,0.0,satisfied +94545,94168,Male,Loyal Customer,60,Business travel,Business,239,4,1,4,4,2,4,4,3,3,4,3,5,3,4,0,0.0,satisfied +94546,64334,Female,disloyal Customer,25,Business travel,Business,1192,2,4,2,3,5,2,3,5,4,4,4,4,4,5,9,0.0,neutral or dissatisfied +94547,23982,Female,Loyal Customer,29,Business travel,Business,562,2,2,2,2,4,4,4,4,5,5,4,3,5,4,79,66.0,satisfied +94548,126025,Female,Loyal Customer,44,Business travel,Business,600,3,3,3,3,5,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +94549,106919,Male,Loyal Customer,42,Business travel,Business,1259,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +94550,49723,Male,Loyal Customer,58,Business travel,Eco,250,4,5,5,5,4,4,4,4,5,2,3,4,4,4,0,0.0,satisfied +94551,84612,Male,Loyal Customer,56,Business travel,Eco,669,2,4,3,4,2,2,2,2,2,3,3,4,4,2,21,7.0,neutral or dissatisfied +94552,25021,Male,Loyal Customer,14,Business travel,Business,3872,1,3,1,1,5,5,5,5,1,5,4,4,4,5,8,3.0,satisfied +94553,5286,Male,Loyal Customer,37,Personal Travel,Eco,190,5,1,5,1,5,5,5,5,2,2,2,1,1,5,0,0.0,satisfied +94554,54332,Male,Loyal Customer,16,Personal Travel,Eco,1597,2,2,2,2,1,2,1,1,2,4,2,3,3,1,1,0.0,neutral or dissatisfied +94555,92878,Female,Loyal Customer,49,Personal Travel,Business,134,4,0,4,1,5,4,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +94556,55086,Male,disloyal Customer,25,Business travel,Eco,1379,3,3,3,3,1,3,1,1,2,5,4,3,4,1,5,0.0,neutral or dissatisfied +94557,88873,Male,disloyal Customer,25,Business travel,Business,859,3,0,3,1,5,3,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +94558,39297,Male,Loyal Customer,14,Personal Travel,Eco,67,3,5,3,1,1,3,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +94559,46694,Male,Loyal Customer,70,Personal Travel,Eco,73,4,4,0,4,4,0,4,4,3,3,4,4,5,4,53,72.0,neutral or dissatisfied +94560,56789,Female,Loyal Customer,45,Business travel,Business,1728,2,2,2,2,4,4,4,2,2,2,2,4,2,4,60,67.0,satisfied +94561,67114,Female,Loyal Customer,31,Business travel,Business,1748,3,5,5,5,3,3,3,3,4,1,3,3,3,3,14,17.0,neutral or dissatisfied +94562,124750,Female,Loyal Customer,37,Business travel,Business,2617,3,4,4,4,4,3,3,3,3,3,3,3,3,2,32,29.0,neutral or dissatisfied +94563,14613,Female,disloyal Customer,20,Business travel,Eco,448,2,1,2,3,1,2,1,1,2,1,3,1,4,1,0,2.0,neutral or dissatisfied +94564,20924,Female,Loyal Customer,47,Business travel,Eco,689,5,1,1,1,4,1,3,5,5,5,5,3,5,4,0,0.0,satisfied +94565,49049,Male,Loyal Customer,57,Business travel,Business,209,4,5,4,4,5,5,1,5,5,5,5,3,5,4,0,4.0,satisfied +94566,14349,Male,Loyal Customer,36,Personal Travel,Eco,395,1,3,1,1,3,1,4,3,3,5,4,4,1,3,0,0.0,neutral or dissatisfied +94567,86939,Female,Loyal Customer,29,Business travel,Business,907,2,2,2,2,2,2,2,2,2,1,1,4,2,2,0,0.0,neutral or dissatisfied +94568,8842,Male,Loyal Customer,24,Personal Travel,Eco Plus,552,4,5,4,4,2,4,2,2,2,2,2,1,4,2,0,10.0,neutral or dissatisfied +94569,116655,Male,Loyal Customer,52,Business travel,Business,2237,3,3,3,3,4,5,5,4,4,4,4,3,4,5,15,0.0,satisfied +94570,15610,Female,Loyal Customer,48,Personal Travel,Eco,288,3,4,3,2,4,4,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +94571,108737,Female,Loyal Customer,46,Business travel,Business,404,5,5,1,5,2,5,5,5,5,4,5,3,5,3,0,8.0,satisfied +94572,119235,Female,Loyal Customer,28,Personal Travel,Eco,331,2,5,2,1,1,2,1,1,1,3,3,4,4,1,0,1.0,neutral or dissatisfied +94573,92147,Female,Loyal Customer,30,Business travel,Business,1589,2,2,2,2,4,4,4,4,3,4,3,3,4,4,0,0.0,satisfied +94574,126107,Female,Loyal Customer,53,Business travel,Business,1774,2,1,2,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +94575,38800,Male,Loyal Customer,8,Personal Travel,Eco,353,4,3,5,4,3,5,3,3,1,5,2,1,3,3,13,18.0,neutral or dissatisfied +94576,127978,Female,Loyal Customer,29,Business travel,Business,3601,1,1,1,1,5,5,5,5,4,2,4,3,4,5,0,0.0,satisfied +94577,47430,Male,Loyal Customer,56,Business travel,Eco,141,2,4,5,4,2,2,2,2,2,1,3,3,4,2,0,0.0,neutral or dissatisfied +94578,87704,Male,Loyal Customer,8,Personal Travel,Eco,606,4,4,4,3,2,4,2,2,1,5,3,3,4,2,0,0.0,neutral or dissatisfied +94579,41444,Female,Loyal Customer,19,Personal Travel,Eco Plus,913,1,5,1,3,5,1,5,5,5,3,5,4,5,5,5,0.0,neutral or dissatisfied +94580,8757,Female,disloyal Customer,43,Business travel,Eco,747,2,2,2,1,1,2,1,1,1,1,2,2,5,1,0,0.0,neutral or dissatisfied +94581,32457,Female,disloyal Customer,50,Business travel,Eco,101,3,4,3,3,1,3,1,1,2,4,2,5,1,1,0,0.0,neutral or dissatisfied +94582,46572,Male,Loyal Customer,47,Business travel,Eco,141,5,3,3,3,5,5,5,3,2,5,5,5,4,5,142,158.0,satisfied +94583,78748,Female,Loyal Customer,37,Business travel,Eco,432,4,5,5,5,4,3,4,4,1,5,4,1,4,4,0,0.0,neutral or dissatisfied +94584,75925,Female,Loyal Customer,49,Business travel,Business,1551,2,5,5,5,4,4,4,3,3,3,2,3,3,4,0,0.0,neutral or dissatisfied +94585,26887,Female,disloyal Customer,43,Business travel,Eco,689,2,2,2,3,4,2,4,4,3,1,3,2,4,4,15,0.0,neutral or dissatisfied +94586,81542,Female,Loyal Customer,55,Personal Travel,Eco,1124,2,5,2,2,2,3,5,5,5,2,5,5,5,3,4,13.0,neutral or dissatisfied +94587,77864,Female,Loyal Customer,54,Personal Travel,Eco Plus,731,2,4,3,3,1,2,2,1,1,3,3,4,1,5,13,12.0,neutral or dissatisfied +94588,60055,Female,Loyal Customer,53,Personal Travel,Eco Plus,1023,3,3,3,2,5,3,2,5,5,3,5,3,5,5,17,12.0,neutral or dissatisfied +94589,119200,Female,Loyal Customer,59,Business travel,Business,331,4,2,2,2,5,4,3,4,4,4,4,1,4,4,3,1.0,neutral or dissatisfied +94590,25709,Female,disloyal Customer,20,Business travel,Eco,447,1,4,1,4,2,1,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +94591,99817,Female,Loyal Customer,31,Business travel,Business,534,1,1,1,1,4,4,4,4,4,5,4,3,4,4,5,8.0,satisfied +94592,115251,Female,Loyal Customer,24,Business travel,Business,2895,2,1,1,1,2,2,2,2,1,3,3,3,4,2,0,0.0,neutral or dissatisfied +94593,4301,Male,Loyal Customer,52,Personal Travel,Eco,502,4,5,4,1,3,4,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +94594,22438,Female,Loyal Customer,45,Personal Travel,Eco,145,3,4,3,4,5,2,5,5,5,3,4,1,5,2,12,23.0,neutral or dissatisfied +94595,72058,Male,Loyal Customer,39,Business travel,Business,2556,5,5,5,5,5,3,4,4,4,4,4,5,4,4,60,60.0,satisfied +94596,102507,Male,Loyal Customer,7,Personal Travel,Eco,414,3,2,3,4,2,3,2,2,4,3,4,2,3,2,12,0.0,neutral or dissatisfied +94597,86207,Female,Loyal Customer,41,Business travel,Business,226,3,1,1,1,3,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +94598,125332,Male,Loyal Customer,47,Business travel,Business,1974,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +94599,90568,Female,Loyal Customer,40,Business travel,Business,594,2,2,1,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +94600,25541,Female,Loyal Customer,60,Personal Travel,Eco,547,2,4,2,3,2,4,3,5,5,2,1,5,5,3,8,3.0,neutral or dissatisfied +94601,125083,Female,disloyal Customer,44,Business travel,Eco,361,2,1,1,2,3,1,3,3,4,5,1,4,1,3,0,38.0,neutral or dissatisfied +94602,19491,Female,Loyal Customer,42,Business travel,Business,3737,2,4,4,4,1,4,3,2,2,2,2,1,2,4,41,50.0,neutral or dissatisfied +94603,68320,Male,disloyal Customer,14,Business travel,Eco,2165,3,3,3,2,3,3,5,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +94604,93957,Female,Loyal Customer,51,Business travel,Business,3706,2,2,2,2,2,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +94605,118951,Male,Loyal Customer,41,Business travel,Business,682,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +94606,62556,Female,Loyal Customer,58,Business travel,Business,1744,2,2,4,2,2,5,4,2,2,2,2,3,2,5,4,0.0,satisfied +94607,61527,Male,Loyal Customer,13,Personal Travel,Eco,2419,5,4,5,4,2,5,4,2,3,1,3,3,4,2,0,0.0,satisfied +94608,15696,Female,Loyal Customer,42,Business travel,Business,419,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +94609,67802,Female,Loyal Customer,25,Business travel,Business,3154,2,2,4,2,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +94610,107473,Female,Loyal Customer,56,Business travel,Business,711,2,2,2,2,2,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +94611,115377,Male,Loyal Customer,30,Business travel,Business,2713,2,2,2,2,2,2,2,2,4,4,3,4,4,2,14,5.0,neutral or dissatisfied +94612,23985,Male,Loyal Customer,38,Business travel,Business,427,2,5,2,2,2,2,1,3,3,3,3,5,3,2,0,0.0,satisfied +94613,103230,Female,Loyal Customer,45,Business travel,Business,2904,1,1,1,1,5,5,5,5,5,5,5,4,5,3,9,0.0,satisfied +94614,122002,Male,disloyal Customer,27,Business travel,Business,130,4,4,4,1,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +94615,2089,Male,Loyal Customer,45,Personal Travel,Eco,812,3,3,3,3,5,3,5,5,1,5,3,3,3,5,0,2.0,neutral or dissatisfied +94616,79420,Male,Loyal Customer,23,Personal Travel,Eco,502,2,5,2,4,2,2,2,2,5,4,5,3,4,2,8,0.0,neutral or dissatisfied +94617,93276,Female,disloyal Customer,45,Business travel,Business,867,5,5,5,2,1,5,1,1,5,5,5,3,4,1,14,4.0,satisfied +94618,69717,Female,Loyal Customer,33,Business travel,Business,1372,1,1,1,1,4,2,5,4,4,5,4,2,4,5,0,0.0,satisfied +94619,120341,Male,disloyal Customer,24,Business travel,Eco,337,4,0,4,1,2,4,2,2,3,5,5,3,4,2,25,35.0,satisfied +94620,69793,Male,Loyal Customer,51,Business travel,Business,1345,2,3,5,3,3,3,4,2,2,2,2,4,2,2,0,3.0,neutral or dissatisfied +94621,19953,Female,Loyal Customer,66,Personal Travel,Eco,315,3,4,3,1,5,4,5,4,4,3,3,4,4,4,30,26.0,neutral or dissatisfied +94622,120458,Female,Loyal Customer,30,Personal Travel,Eco,413,3,2,3,3,3,3,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +94623,122261,Male,Loyal Customer,50,Personal Travel,Eco,541,2,2,2,3,5,2,5,5,4,5,4,4,4,5,9,0.0,neutral or dissatisfied +94624,2755,Female,Loyal Customer,18,Personal Travel,Eco,772,1,4,1,3,2,1,2,2,1,2,3,2,3,2,0,,neutral or dissatisfied +94625,70206,Female,Loyal Customer,24,Personal Travel,Eco,258,2,5,2,1,4,2,3,4,1,4,4,3,5,4,10,6.0,neutral or dissatisfied +94626,97793,Female,Loyal Customer,71,Business travel,Business,2166,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +94627,337,Male,Loyal Customer,37,Personal Travel,Eco,821,2,5,2,1,5,2,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +94628,16288,Male,Loyal Customer,44,Personal Travel,Eco,748,3,5,3,4,3,3,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +94629,99934,Female,Loyal Customer,51,Personal Travel,Eco,764,2,4,2,4,4,2,1,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +94630,78741,Male,Loyal Customer,46,Business travel,Business,2388,1,1,1,1,4,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +94631,17405,Male,Loyal Customer,61,Business travel,Eco,376,4,3,3,3,4,4,4,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +94632,65312,Male,Loyal Customer,52,Personal Travel,Business,432,1,5,1,5,1,3,3,3,4,5,4,3,5,3,197,193.0,neutral or dissatisfied +94633,42080,Female,Loyal Customer,65,Business travel,Eco Plus,116,2,5,5,5,2,2,2,1,3,3,4,2,1,2,134,131.0,neutral or dissatisfied +94634,79749,Female,Loyal Customer,11,Personal Travel,Eco Plus,712,3,5,3,4,3,3,3,3,1,3,4,5,3,3,0,3.0,neutral or dissatisfied +94635,82866,Female,Loyal Customer,51,Business travel,Business,2831,3,3,3,3,4,4,4,5,5,5,5,3,5,3,4,0.0,satisfied +94636,24515,Male,Loyal Customer,8,Business travel,Eco Plus,547,2,4,4,4,2,2,3,2,3,3,3,4,3,2,0,5.0,neutral or dissatisfied +94637,49403,Male,Loyal Customer,36,Business travel,Eco,373,4,3,3,3,4,4,4,4,5,2,5,4,3,4,0,0.0,satisfied +94638,122588,Female,Loyal Customer,46,Business travel,Business,3057,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +94639,60788,Male,Loyal Customer,57,Business travel,Business,2178,4,4,4,4,2,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +94640,37375,Male,disloyal Customer,29,Business travel,Eco,944,2,2,2,5,1,2,1,1,4,3,2,3,4,1,107,94.0,neutral or dissatisfied +94641,71704,Male,Loyal Customer,41,Personal Travel,Eco Plus,1182,2,5,2,3,4,2,4,4,5,2,5,3,4,4,39,25.0,neutral or dissatisfied +94642,46004,Male,Loyal Customer,54,Personal Travel,Eco,483,2,5,2,3,4,2,4,4,5,2,5,2,4,4,0,3.0,neutral or dissatisfied +94643,26372,Male,Loyal Customer,46,Business travel,Business,2868,1,1,1,1,3,3,4,4,4,4,4,5,4,3,0,3.0,satisfied +94644,51147,Female,Loyal Customer,54,Personal Travel,Eco,209,2,3,2,3,2,4,3,3,3,2,3,1,3,1,40,17.0,neutral or dissatisfied +94645,21177,Male,disloyal Customer,39,Business travel,Eco,192,4,0,4,4,1,4,1,1,1,5,4,4,4,1,0,0.0,satisfied +94646,120849,Male,Loyal Customer,51,Business travel,Business,593,1,1,2,1,5,4,5,5,5,5,5,4,5,4,3,19.0,satisfied +94647,86254,Female,Loyal Customer,22,Personal Travel,Eco,356,4,4,4,4,2,4,2,2,5,2,5,4,4,2,7,0.0,neutral or dissatisfied +94648,94635,Female,Loyal Customer,54,Business travel,Business,1707,2,2,3,2,4,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +94649,116623,Female,Loyal Customer,42,Business travel,Eco Plus,373,2,4,5,4,3,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +94650,23224,Male,disloyal Customer,23,Business travel,Eco,476,2,4,2,5,5,2,2,5,1,5,3,5,1,5,0,0.0,neutral or dissatisfied +94651,39413,Female,Loyal Customer,43,Business travel,Eco Plus,521,3,2,2,2,1,1,1,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +94652,3931,Female,Loyal Customer,48,Business travel,Business,1728,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,12.0,satisfied +94653,30807,Male,Loyal Customer,25,Business travel,Business,2699,2,2,2,2,4,4,4,4,3,4,3,2,5,4,0,0.0,satisfied +94654,59939,Female,Loyal Customer,51,Business travel,Business,2730,3,3,3,3,5,5,4,4,4,4,4,3,4,4,9,0.0,satisfied +94655,103591,Male,Loyal Customer,45,Business travel,Eco,451,1,4,4,4,1,1,1,1,1,3,2,4,2,1,28,24.0,neutral or dissatisfied +94656,62499,Male,disloyal Customer,31,Business travel,Business,1846,2,1,1,4,5,1,4,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +94657,116923,Male,Loyal Customer,41,Business travel,Business,3338,1,1,1,1,2,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +94658,24225,Male,Loyal Customer,38,Business travel,Business,170,3,3,3,3,5,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +94659,9048,Female,Loyal Customer,58,Business travel,Business,3107,3,3,3,3,2,5,4,4,4,4,4,3,4,4,5,0.0,satisfied +94660,111370,Male,Loyal Customer,56,Business travel,Business,2642,5,5,4,5,3,5,4,1,1,2,1,5,1,4,1,14.0,satisfied +94661,123195,Male,Loyal Customer,25,Personal Travel,Eco,600,3,5,3,3,5,3,5,5,5,5,2,1,1,5,0,0.0,neutral or dissatisfied +94662,74214,Male,Loyal Customer,22,Personal Travel,Eco Plus,592,2,3,2,2,1,2,1,1,1,2,3,2,1,1,0,0.0,neutral or dissatisfied +94663,64977,Female,Loyal Customer,49,Business travel,Eco,190,3,1,3,1,1,3,3,3,3,3,3,3,3,4,4,1.0,neutral or dissatisfied +94664,109205,Male,Loyal Customer,26,Business travel,Business,3974,3,3,3,3,3,3,3,3,1,3,3,4,3,3,4,1.0,neutral or dissatisfied +94665,3578,Male,Loyal Customer,39,Business travel,Eco Plus,227,3,1,1,1,3,2,3,3,2,1,3,3,4,3,0,0.0,neutral or dissatisfied +94666,94366,Male,disloyal Customer,23,Business travel,Business,323,4,0,4,1,5,4,5,5,5,5,4,3,5,5,11,3.0,satisfied +94667,45269,Female,Loyal Customer,23,Personal Travel,Business,175,4,2,4,2,3,4,5,3,3,4,2,4,3,3,0,0.0,neutral or dissatisfied +94668,103287,Female,Loyal Customer,55,Business travel,Business,3787,5,5,3,5,5,5,5,4,4,4,4,3,4,3,121,121.0,satisfied +94669,80117,Male,Loyal Customer,13,Personal Travel,Eco,1620,4,5,4,5,5,4,5,5,4,3,5,5,5,5,0,7.0,neutral or dissatisfied +94670,4179,Male,Loyal Customer,64,Personal Travel,Eco,431,4,5,4,3,4,4,4,4,4,2,4,5,5,4,0,8.0,neutral or dissatisfied +94671,49938,Female,Loyal Customer,33,Business travel,Business,2866,4,4,4,4,4,1,3,4,4,5,4,2,4,2,0,4.0,satisfied +94672,49206,Male,Loyal Customer,58,Business travel,Business,2304,5,3,5,5,4,4,2,5,5,5,5,3,5,4,49,54.0,satisfied +94673,33166,Male,Loyal Customer,57,Personal Travel,Eco,216,3,0,3,4,3,3,3,3,3,3,5,3,4,3,60,63.0,neutral or dissatisfied +94674,102598,Male,Loyal Customer,55,Personal Travel,Eco Plus,223,5,4,5,1,4,5,4,4,4,2,4,5,5,4,0,0.0,satisfied +94675,97213,Male,Loyal Customer,43,Business travel,Business,1525,4,4,5,4,5,5,5,5,5,5,5,5,5,5,223,210.0,satisfied +94676,110573,Male,Loyal Customer,43,Business travel,Business,2068,1,1,4,1,3,5,5,5,5,5,5,4,5,5,13,0.0,satisfied +94677,55825,Female,Loyal Customer,59,Business travel,Business,1416,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +94678,20007,Male,Loyal Customer,30,Personal Travel,Eco,599,3,1,3,4,3,3,3,3,4,2,4,3,3,3,36,44.0,neutral or dissatisfied +94679,80401,Male,Loyal Customer,24,Business travel,Eco Plus,422,2,5,5,5,2,2,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +94680,81909,Male,Loyal Customer,53,Personal Travel,Eco,680,2,1,2,3,1,2,1,1,1,3,2,1,2,1,0,6.0,neutral or dissatisfied +94681,10975,Female,Loyal Customer,42,Business travel,Eco,224,3,5,5,5,1,4,4,3,3,3,3,4,3,4,17,19.0,neutral or dissatisfied +94682,42203,Female,Loyal Customer,38,Business travel,Business,329,4,4,4,4,5,1,3,5,5,5,5,2,5,4,51,58.0,satisfied +94683,55227,Female,Loyal Customer,46,Business travel,Business,1895,2,2,2,2,5,5,5,4,4,4,4,4,4,4,7,0.0,satisfied +94684,26693,Female,Loyal Customer,55,Personal Travel,Eco,406,3,5,2,4,3,5,2,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +94685,18306,Female,Loyal Customer,33,Personal Travel,Eco Plus,813,0,2,0,3,3,0,4,3,2,1,4,4,4,3,0,0.0,satisfied +94686,6496,Male,Loyal Customer,40,Personal Travel,Eco,557,4,5,4,2,4,4,4,4,2,4,4,3,1,4,0,0.0,satisfied +94687,103712,Female,Loyal Customer,41,Personal Travel,Eco,405,3,5,3,1,4,3,4,4,5,1,4,5,1,4,0,0.0,neutral or dissatisfied +94688,19038,Male,disloyal Customer,12,Business travel,Eco Plus,788,2,0,2,4,4,2,4,4,2,4,4,3,3,4,2,18.0,neutral or dissatisfied +94689,112354,Male,Loyal Customer,55,Business travel,Business,2134,3,3,3,3,5,4,5,5,5,5,5,3,5,5,30,24.0,satisfied +94690,64762,Female,Loyal Customer,59,Business travel,Business,2806,4,4,4,4,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +94691,14922,Female,Loyal Customer,43,Business travel,Eco Plus,343,5,3,3,3,2,1,5,5,5,5,5,1,5,1,35,28.0,satisfied +94692,26109,Male,Loyal Customer,33,Business travel,Business,406,2,2,2,2,2,3,2,2,3,2,4,3,5,2,0,0.0,satisfied +94693,48559,Female,Loyal Customer,11,Personal Travel,Eco,833,2,4,2,3,2,4,4,4,5,4,4,4,4,4,213,207.0,neutral or dissatisfied +94694,21352,Female,Loyal Customer,42,Personal Travel,Eco,761,3,4,3,2,1,4,3,5,5,3,5,3,5,1,16,12.0,neutral or dissatisfied +94695,48349,Male,Loyal Customer,59,Business travel,Eco,674,5,3,3,3,5,5,5,5,4,5,3,1,1,5,0,0.0,satisfied +94696,24771,Male,disloyal Customer,14,Business travel,Eco,528,3,1,2,4,1,2,1,1,3,1,4,1,4,1,14,13.0,neutral or dissatisfied +94697,82665,Female,Loyal Customer,32,Personal Travel,Eco,120,1,2,1,4,5,1,5,5,2,4,3,1,3,5,0,0.0,neutral or dissatisfied +94698,114442,Female,Loyal Customer,54,Business travel,Business,308,3,3,3,3,5,5,5,5,5,5,5,4,5,4,2,9.0,satisfied +94699,85073,Female,Loyal Customer,24,Business travel,Business,689,2,2,2,2,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +94700,51978,Female,Loyal Customer,21,Personal Travel,Eco,347,5,4,5,2,2,5,2,2,4,4,4,3,5,2,0,0.0,satisfied +94701,115865,Male,Loyal Customer,37,Business travel,Business,446,2,2,2,2,2,1,2,5,5,4,5,5,5,1,0,0.0,satisfied +94702,76914,Female,Loyal Customer,25,Business travel,Eco Plus,630,2,4,4,4,2,2,2,2,1,5,3,3,3,2,0,0.0,neutral or dissatisfied +94703,95032,Male,Loyal Customer,57,Personal Travel,Eco,528,3,4,3,2,3,3,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +94704,68479,Male,disloyal Customer,25,Business travel,Business,1067,4,2,4,1,3,4,3,3,2,3,2,4,1,3,0,3.0,neutral or dissatisfied +94705,93725,Male,Loyal Customer,34,Personal Travel,Eco,630,3,1,3,1,3,3,3,3,4,4,1,3,1,3,61,53.0,neutral or dissatisfied +94706,32508,Male,Loyal Customer,50,Business travel,Eco,102,5,5,5,5,5,5,5,5,5,1,1,3,1,5,0,0.0,satisfied +94707,34607,Female,Loyal Customer,24,Personal Travel,Eco,1617,1,4,2,4,2,2,2,2,5,2,3,5,4,2,25,28.0,neutral or dissatisfied +94708,86653,Male,Loyal Customer,26,Personal Travel,Eco,746,1,2,1,3,1,1,1,1,1,1,3,1,3,1,31,24.0,neutral or dissatisfied +94709,33215,Male,Loyal Customer,34,Business travel,Eco Plus,101,5,3,3,3,5,5,5,5,4,3,5,3,5,5,3,5.0,satisfied +94710,93086,Male,Loyal Customer,30,Business travel,Business,2236,3,2,5,2,3,2,3,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +94711,74630,Male,disloyal Customer,39,Business travel,Eco,805,4,5,5,3,5,5,5,5,5,5,2,3,2,5,0,0.0,neutral or dissatisfied +94712,102125,Male,Loyal Customer,45,Business travel,Business,3776,5,5,5,5,3,5,5,5,5,4,5,4,5,5,1,0.0,satisfied +94713,120637,Male,Loyal Customer,51,Business travel,Business,2893,2,2,2,2,5,4,5,5,5,4,5,5,5,3,18,10.0,satisfied +94714,51277,Female,disloyal Customer,40,Business travel,Business,372,2,2,2,3,4,2,4,4,4,1,5,1,2,4,0,0.0,neutral or dissatisfied +94715,81777,Female,Loyal Customer,53,Business travel,Business,1416,5,5,4,5,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +94716,120393,Male,Loyal Customer,53,Business travel,Business,3531,4,4,4,4,4,2,2,4,4,4,4,2,4,2,5,0.0,neutral or dissatisfied +94717,398,Male,Loyal Customer,52,Business travel,Business,134,4,4,4,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +94718,5438,Male,disloyal Customer,32,Business travel,Business,265,2,2,2,2,2,2,1,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +94719,31349,Female,Loyal Customer,30,Personal Travel,Eco,1069,3,4,3,3,3,3,3,3,3,3,4,3,4,3,114,116.0,neutral or dissatisfied +94720,3333,Male,Loyal Customer,31,Business travel,Business,3466,2,2,2,2,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +94721,32274,Female,Loyal Customer,35,Business travel,Eco,163,5,4,4,4,5,4,5,5,2,5,4,4,2,5,0,0.0,satisfied +94722,71226,Female,disloyal Customer,21,Business travel,Eco,733,2,2,2,3,2,2,2,1,4,4,4,2,3,2,106,145.0,neutral or dissatisfied +94723,38482,Female,Loyal Customer,41,Personal Travel,Eco,846,3,5,3,1,5,3,3,5,4,1,5,2,2,5,0,0.0,neutral or dissatisfied +94724,38176,Female,Loyal Customer,57,Personal Travel,Eco,1091,4,1,4,2,4,3,3,2,1,3,2,3,1,3,271,,neutral or dissatisfied +94725,12260,Male,Loyal Customer,42,Business travel,Eco,190,4,3,3,3,4,4,4,4,4,2,1,5,4,4,0,0.0,satisfied +94726,53492,Female,Loyal Customer,13,Personal Travel,Eco,2253,5,4,5,2,5,4,4,3,5,3,5,4,3,4,238,211.0,satisfied +94727,80155,Female,Loyal Customer,35,Business travel,Business,2586,5,1,5,5,4,4,4,3,5,4,5,4,4,4,0,0.0,satisfied +94728,12579,Female,Loyal Customer,41,Business travel,Eco,542,4,5,5,5,3,4,3,3,4,4,5,1,2,3,93,102.0,satisfied +94729,31916,Female,Loyal Customer,48,Business travel,Business,3489,0,5,0,1,2,5,4,1,1,1,1,5,1,5,0,0.0,satisfied +94730,38304,Female,Loyal Customer,9,Personal Travel,Eco,2583,2,5,2,3,2,4,4,1,1,4,5,4,3,4,9,12.0,neutral or dissatisfied +94731,100216,Male,Loyal Customer,66,Personal Travel,Eco,762,2,5,3,4,4,3,4,4,5,3,5,5,5,4,2,29.0,neutral or dissatisfied +94732,82187,Female,Loyal Customer,30,Business travel,Business,1927,4,4,4,4,4,4,4,4,5,3,3,5,5,4,4,0.0,satisfied +94733,20666,Female,disloyal Customer,23,Business travel,Eco,552,3,1,3,3,1,3,1,1,2,3,3,4,2,1,63,64.0,neutral or dissatisfied +94734,82421,Female,Loyal Customer,31,Business travel,Business,509,5,5,5,5,5,4,5,5,5,3,5,5,5,5,3,14.0,satisfied +94735,27147,Female,disloyal Customer,38,Business travel,Eco,1437,3,3,3,3,3,3,3,1,2,4,3,3,4,3,0,0.0,neutral or dissatisfied +94736,119750,Female,Loyal Customer,19,Personal Travel,Eco,1303,2,3,2,4,5,2,1,5,4,2,3,3,4,5,0,22.0,neutral or dissatisfied +94737,10025,Female,Loyal Customer,68,Personal Travel,Business,630,3,4,3,3,4,5,4,5,5,3,5,3,5,5,0,4.0,neutral or dissatisfied +94738,93519,Female,Loyal Customer,22,Business travel,Business,3650,2,2,2,2,4,4,4,4,3,2,4,4,5,4,10,33.0,satisfied +94739,64178,Female,Loyal Customer,49,Business travel,Eco Plus,589,5,2,2,2,4,4,1,4,4,5,4,5,4,2,0,0.0,satisfied +94740,126387,Female,Loyal Customer,30,Personal Travel,Eco,590,4,2,5,4,4,5,4,4,1,5,3,3,3,4,0,4.0,neutral or dissatisfied +94741,34979,Male,Loyal Customer,35,Business travel,Eco,273,2,1,2,1,2,2,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +94742,120967,Male,Loyal Customer,44,Business travel,Business,1013,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +94743,82830,Female,Loyal Customer,48,Business travel,Business,3313,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,14.0,satisfied +94744,20548,Male,Loyal Customer,11,Business travel,Eco,633,1,4,4,4,1,1,4,1,1,4,3,2,3,1,0,10.0,neutral or dissatisfied +94745,75011,Female,Loyal Customer,47,Business travel,Business,3052,2,2,5,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +94746,35408,Female,disloyal Customer,24,Business travel,Eco,944,3,3,3,3,1,3,1,1,4,3,3,1,4,1,39,19.0,neutral or dissatisfied +94747,112620,Female,Loyal Customer,67,Personal Travel,Eco,602,2,4,2,3,1,4,3,2,2,2,1,1,2,4,17,20.0,neutral or dissatisfied +94748,88866,Female,Loyal Customer,33,Business travel,Business,859,2,2,2,2,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +94749,11066,Male,Loyal Customer,24,Personal Travel,Eco,201,2,4,2,3,3,2,3,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +94750,3353,Female,Loyal Customer,60,Business travel,Business,2567,5,5,5,5,3,4,4,5,5,5,5,5,5,4,1,0.0,satisfied +94751,92272,Male,Loyal Customer,36,Business travel,Business,1900,2,2,2,2,4,3,5,5,5,5,5,4,5,3,7,26.0,satisfied +94752,46990,Male,Loyal Customer,51,Personal Travel,Eco,776,3,5,3,3,3,3,5,3,3,5,4,5,5,3,0,7.0,neutral or dissatisfied +94753,55223,Female,Loyal Customer,54,Business travel,Business,3724,3,3,3,3,4,5,5,3,3,4,3,4,3,3,5,9.0,satisfied +94754,60795,Female,Loyal Customer,51,Business travel,Business,3581,5,5,5,5,4,4,5,4,4,5,4,4,4,5,49,54.0,satisfied +94755,12760,Female,Loyal Customer,24,Personal Travel,Eco,851,2,4,2,4,2,2,1,2,1,2,4,4,3,2,4,0.0,neutral or dissatisfied +94756,92095,Male,disloyal Customer,29,Business travel,Eco,1088,4,4,4,4,3,4,3,3,4,2,2,1,4,3,7,0.0,neutral or dissatisfied +94757,127860,Female,disloyal Customer,24,Business travel,Eco,1276,3,3,3,4,1,3,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +94758,122624,Male,Loyal Customer,10,Personal Travel,Eco,728,3,3,3,1,3,3,3,3,3,2,1,1,3,3,0,0.0,neutral or dissatisfied +94759,114368,Male,Loyal Customer,10,Business travel,Business,1577,5,5,5,5,4,4,4,4,5,2,5,4,5,4,73,,satisfied +94760,91292,Female,Loyal Customer,48,Business travel,Business,3979,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +94761,69228,Female,Loyal Customer,39,Business travel,Business,733,2,5,5,5,1,2,3,2,2,2,2,4,2,3,16,21.0,neutral or dissatisfied +94762,25146,Female,Loyal Customer,25,Business travel,Eco,406,5,2,2,2,5,5,4,5,2,5,2,5,1,5,66,65.0,satisfied +94763,123456,Female,Loyal Customer,26,Business travel,Business,2296,1,1,1,1,4,3,3,3,3,4,4,3,3,3,117,147.0,satisfied +94764,20155,Male,disloyal Customer,21,Business travel,Eco,438,3,0,4,3,4,4,4,4,2,3,1,4,1,4,0,40.0,neutral or dissatisfied +94765,48478,Male,Loyal Customer,43,Business travel,Business,3520,5,5,5,5,4,4,1,5,5,5,5,2,5,4,0,0.0,satisfied +94766,33977,Male,Loyal Customer,22,Business travel,Business,1598,1,1,2,1,5,5,5,5,3,5,4,2,5,5,45,41.0,satisfied +94767,46952,Female,Loyal Customer,64,Personal Travel,Eco,844,2,5,2,2,5,5,5,1,1,2,1,3,1,3,0,1.0,neutral or dissatisfied +94768,125049,Female,Loyal Customer,42,Personal Travel,Eco,2300,2,5,2,1,2,1,3,3,4,3,4,3,5,3,0,34.0,neutral or dissatisfied +94769,68009,Female,disloyal Customer,40,Business travel,Business,304,3,3,3,1,4,3,4,4,5,4,4,5,5,4,22,13.0,neutral or dissatisfied +94770,21963,Female,Loyal Customer,33,Business travel,Business,500,2,3,3,3,1,3,3,2,2,2,2,4,2,4,24,11.0,neutral or dissatisfied +94771,23392,Male,Loyal Customer,63,Business travel,Eco,300,5,3,3,3,5,5,5,5,4,1,3,4,2,5,6,0.0,satisfied +94772,24649,Male,Loyal Customer,44,Business travel,Eco,834,5,5,3,3,5,5,5,5,3,1,1,5,4,5,0,0.0,satisfied +94773,124864,Male,Loyal Customer,77,Business travel,Eco Plus,280,2,3,3,3,2,2,2,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +94774,23411,Female,Loyal Customer,30,Business travel,Business,495,4,2,4,4,3,3,3,3,5,2,1,3,5,3,32,59.0,satisfied +94775,40226,Female,disloyal Customer,24,Business travel,Eco,347,1,3,1,3,3,1,2,3,2,3,5,2,4,3,0,3.0,neutral or dissatisfied +94776,97980,Male,Loyal Customer,62,Personal Travel,Eco,616,2,4,2,4,2,2,2,2,5,2,3,1,2,2,0,0.0,neutral or dissatisfied +94777,44936,Female,Loyal Customer,24,Business travel,Business,397,2,2,2,2,5,5,5,5,1,1,1,1,2,5,7,13.0,satisfied +94778,30733,Male,Loyal Customer,50,Business travel,Business,3665,3,2,5,2,2,4,3,3,3,3,3,1,3,3,8,12.0,neutral or dissatisfied +94779,56990,Female,Loyal Customer,41,Personal Travel,Eco,2454,4,2,3,3,1,3,1,1,2,1,2,2,3,1,1,0.0,satisfied +94780,76744,Female,disloyal Customer,22,Business travel,Eco,205,3,1,3,4,1,3,1,1,2,1,4,1,3,1,59,52.0,neutral or dissatisfied +94781,26281,Male,Loyal Customer,24,Personal Travel,Eco,859,4,4,4,5,2,4,2,2,4,2,4,3,5,2,3,0.0,neutral or dissatisfied +94782,107615,Male,Loyal Customer,17,Business travel,Business,423,1,1,3,1,3,4,3,3,3,3,4,4,5,3,0,0.0,satisfied +94783,115657,Female,Loyal Customer,42,Business travel,Eco,447,2,1,1,1,4,4,3,2,2,2,2,3,2,1,15,3.0,neutral or dissatisfied +94784,90668,Male,Loyal Customer,47,Business travel,Business,250,4,2,4,4,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +94785,81203,Male,Loyal Customer,42,Business travel,Business,1426,1,1,1,1,5,4,5,2,2,2,2,5,2,5,0,3.0,satisfied +94786,5798,Female,disloyal Customer,38,Business travel,Eco,177,3,2,3,4,3,3,3,1,1,4,4,3,3,3,118,138.0,neutral or dissatisfied +94787,129818,Male,Loyal Customer,42,Personal Travel,Eco,337,1,3,1,1,3,1,3,3,2,5,5,4,4,3,0,0.0,neutral or dissatisfied +94788,68238,Male,disloyal Customer,21,Business travel,Eco,631,4,3,5,3,4,5,4,4,1,4,4,4,4,4,0,0.0,neutral or dissatisfied +94789,26482,Female,Loyal Customer,35,Business travel,Eco Plus,925,4,5,5,5,4,4,4,4,3,1,1,2,3,4,0,0.0,satisfied +94790,120543,Female,Loyal Customer,48,Business travel,Business,2176,3,3,3,3,5,5,5,5,5,5,5,4,5,5,7,32.0,satisfied +94791,118307,Male,Loyal Customer,56,Business travel,Business,2028,4,4,1,4,3,5,4,5,5,5,5,3,5,4,18,10.0,satisfied +94792,7591,Female,Loyal Customer,50,Business travel,Business,594,2,2,2,2,4,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +94793,77606,Male,disloyal Customer,37,Business travel,Business,696,5,4,4,3,5,4,5,5,5,2,5,5,5,5,0,0.0,satisfied +94794,70647,Female,disloyal Customer,24,Business travel,Eco,946,3,3,3,3,1,3,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +94795,71321,Male,disloyal Customer,25,Business travel,Eco,1514,1,1,1,3,2,1,1,2,4,4,3,4,2,2,47,63.0,neutral or dissatisfied +94796,54689,Female,disloyal Customer,26,Business travel,Eco,854,2,2,2,4,1,2,1,1,2,4,4,1,3,1,0,29.0,neutral or dissatisfied +94797,16404,Male,Loyal Customer,68,Personal Travel,Eco,463,1,3,5,5,5,5,5,5,5,3,2,5,3,5,0,0.0,neutral or dissatisfied +94798,99852,Male,Loyal Customer,42,Personal Travel,Eco,534,2,5,2,2,4,2,4,4,5,3,5,5,5,4,1,5.0,neutral or dissatisfied +94799,40441,Male,disloyal Customer,21,Business travel,Eco,188,2,5,2,4,5,2,5,5,2,5,5,2,3,5,0,0.0,neutral or dissatisfied +94800,11071,Male,Loyal Customer,65,Personal Travel,Eco,201,2,4,0,4,4,0,3,4,1,3,4,3,4,4,0,1.0,neutral or dissatisfied +94801,121133,Male,Loyal Customer,56,Business travel,Business,2402,2,2,2,2,5,5,5,3,3,5,5,5,3,5,3,19.0,satisfied +94802,95903,Female,Loyal Customer,34,Personal Travel,Eco,580,2,4,2,3,1,2,1,1,1,1,1,1,2,1,7,1.0,neutral or dissatisfied +94803,37314,Female,Loyal Customer,45,Business travel,Eco,1165,5,3,5,5,5,5,5,1,4,2,1,5,4,5,143,128.0,satisfied +94804,17602,Male,Loyal Customer,31,Business travel,Business,1705,0,3,0,4,2,2,2,2,1,4,3,5,1,2,0,29.0,satisfied +94805,54661,Female,disloyal Customer,15,Business travel,Eco,964,4,4,4,5,4,4,4,4,2,3,5,2,3,4,7,0.0,satisfied +94806,4888,Male,Loyal Customer,54,Business travel,Business,500,3,3,3,3,2,4,4,5,5,5,5,3,5,4,0,23.0,satisfied +94807,21622,Female,Loyal Customer,28,Business travel,Eco,853,2,4,4,4,2,2,2,2,1,1,2,4,2,2,0,0.0,neutral or dissatisfied +94808,112728,Female,Loyal Customer,69,Personal Travel,Eco,671,3,4,3,4,2,4,5,5,5,3,5,3,5,3,2,0.0,neutral or dissatisfied +94809,34572,Female,Loyal Customer,31,Business travel,Business,1598,4,4,5,4,4,4,4,4,5,3,4,2,4,4,0,0.0,satisfied +94810,91936,Male,Loyal Customer,42,Business travel,Eco,975,4,2,2,2,5,4,5,5,5,5,2,4,4,5,0,0.0,satisfied +94811,98290,Female,Loyal Customer,10,Personal Travel,Eco,1188,0,1,0,2,1,0,1,1,3,5,1,4,2,1,0,0.0,satisfied +94812,27710,Male,disloyal Customer,24,Business travel,Business,1448,3,2,3,4,5,3,5,5,3,4,4,1,3,5,2,0.0,neutral or dissatisfied +94813,53094,Female,Loyal Customer,28,Personal Travel,Eco,224,4,5,0,4,5,0,5,5,5,4,5,5,5,5,105,107.0,neutral or dissatisfied +94814,52623,Male,Loyal Customer,23,Business travel,Business,110,3,3,3,3,4,4,3,4,4,3,3,3,2,4,0,0.0,satisfied +94815,104800,Male,disloyal Customer,22,Business travel,Eco,587,1,2,1,2,2,1,2,2,4,3,1,2,2,2,14,7.0,neutral or dissatisfied +94816,85225,Male,disloyal Customer,24,Business travel,Eco,874,2,2,2,2,5,2,5,5,2,3,5,1,1,5,0,0.0,neutral or dissatisfied +94817,94617,Female,Loyal Customer,43,Business travel,Business,239,3,3,3,3,4,5,5,4,4,4,4,3,4,3,6,0.0,satisfied +94818,46767,Female,disloyal Customer,75,Business travel,Eco Plus,125,1,2,2,2,1,1,1,1,5,5,5,2,2,1,0,0.0,neutral or dissatisfied +94819,2580,Male,disloyal Customer,20,Business travel,Eco,280,3,0,3,1,2,3,2,2,1,2,1,4,5,2,6,5.0,neutral or dissatisfied +94820,117154,Female,Loyal Customer,36,Personal Travel,Eco,621,3,2,3,4,2,3,3,2,1,4,4,2,3,2,0,0.0,neutral or dissatisfied +94821,97171,Female,Loyal Customer,63,Personal Travel,Eco,1390,5,4,5,1,2,4,5,4,4,5,3,4,4,5,0,0.0,satisfied +94822,85439,Female,Loyal Customer,42,Business travel,Business,3322,1,1,4,1,3,4,5,4,4,4,5,3,4,5,1,0.0,satisfied +94823,86533,Female,Loyal Customer,47,Personal Travel,Eco,762,2,5,2,2,5,5,5,2,2,2,3,3,2,4,9,0.0,neutral or dissatisfied +94824,23269,Male,Loyal Customer,43,Business travel,Business,1854,3,3,3,3,4,5,4,4,4,4,4,4,4,5,72,83.0,satisfied +94825,17463,Female,Loyal Customer,65,Personal Travel,Eco,677,2,5,1,4,1,5,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +94826,49714,Male,disloyal Customer,25,Business travel,Eco,78,3,3,3,4,5,3,5,5,4,4,3,2,4,5,0,0.0,neutral or dissatisfied +94827,71015,Female,disloyal Customer,28,Business travel,Business,802,0,0,0,2,2,0,2,2,4,4,5,4,5,2,1,34.0,satisfied +94828,101679,Female,Loyal Customer,17,Business travel,Business,1500,5,5,2,5,4,4,4,4,5,4,5,3,4,4,95,84.0,satisfied +94829,104389,Male,disloyal Customer,20,Business travel,Eco,228,5,0,5,3,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +94830,124065,Male,Loyal Customer,36,Personal Travel,Eco,2153,2,4,2,4,2,2,2,2,3,1,2,3,3,2,0,38.0,neutral or dissatisfied +94831,27859,Male,Loyal Customer,17,Personal Travel,Eco,680,3,4,3,5,2,3,2,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +94832,116250,Male,Loyal Customer,70,Personal Travel,Eco,325,3,2,3,3,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +94833,61268,Female,Loyal Customer,34,Personal Travel,Eco,853,3,4,3,4,2,3,1,2,5,5,4,5,4,2,0,2.0,neutral or dissatisfied +94834,97593,Female,disloyal Customer,23,Business travel,Business,442,5,0,5,1,1,5,1,1,4,3,4,4,5,1,15,8.0,satisfied +94835,87214,Male,Loyal Customer,70,Personal Travel,Eco,946,1,4,1,5,4,1,1,4,3,4,3,4,2,4,0,1.0,neutral or dissatisfied +94836,105407,Female,Loyal Customer,31,Business travel,Business,3348,3,3,3,3,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +94837,33700,Male,Loyal Customer,61,Business travel,Eco,667,3,4,2,4,3,3,3,3,4,3,2,2,2,3,0,5.0,neutral or dissatisfied +94838,11919,Female,Loyal Customer,58,Personal Travel,Eco,501,3,1,3,2,5,2,3,5,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +94839,28471,Male,Loyal Customer,27,Business travel,Business,1721,5,5,5,5,5,5,5,5,3,2,4,2,2,5,0,0.0,satisfied +94840,34539,Male,Loyal Customer,23,Personal Travel,Eco,636,1,5,1,2,2,1,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +94841,2486,Female,Loyal Customer,54,Business travel,Business,1379,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,1.0,satisfied +94842,97490,Male,Loyal Customer,19,Personal Travel,Eco,822,2,2,2,3,1,2,1,1,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +94843,54409,Female,Loyal Customer,35,Business travel,Business,2445,2,2,2,2,1,5,2,5,5,5,5,5,5,4,0,24.0,satisfied +94844,108349,Male,Loyal Customer,32,Business travel,Eco,1750,2,2,2,2,2,2,2,2,4,1,2,2,4,2,7,13.0,neutral or dissatisfied +94845,72610,Male,Loyal Customer,11,Personal Travel,Eco,1121,3,4,3,4,2,3,5,2,3,3,4,3,5,2,3,0.0,neutral or dissatisfied +94846,27025,Female,Loyal Customer,38,Personal Travel,Eco,867,2,4,2,3,3,2,4,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +94847,18242,Male,Loyal Customer,20,Business travel,Business,228,3,1,1,1,3,3,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +94848,127482,Female,disloyal Customer,38,Business travel,Eco,575,2,4,2,2,5,2,5,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +94849,94512,Male,Loyal Customer,53,Business travel,Business,2527,3,3,3,3,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +94850,78907,Male,Loyal Customer,32,Business travel,Eco,980,1,3,3,3,1,1,1,1,1,1,4,1,4,1,0,0.0,neutral or dissatisfied +94851,40741,Male,Loyal Customer,49,Business travel,Business,2770,3,3,3,3,4,4,4,3,3,3,3,1,3,2,27,37.0,neutral or dissatisfied +94852,33151,Male,Loyal Customer,30,Personal Travel,Eco,216,3,2,3,4,1,3,3,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +94853,21194,Female,disloyal Customer,26,Business travel,Eco,317,1,3,1,3,2,1,2,2,3,5,3,2,4,2,0,6.0,neutral or dissatisfied +94854,114253,Male,disloyal Customer,23,Business travel,Eco,853,2,1,1,2,5,1,5,5,1,2,1,5,5,5,3,10.0,neutral or dissatisfied +94855,111141,Male,Loyal Customer,46,Business travel,Eco,1050,2,3,2,2,2,2,2,2,1,5,2,4,2,2,112,97.0,neutral or dissatisfied +94856,108008,Female,Loyal Customer,63,Personal Travel,Eco,271,2,0,2,1,5,5,4,1,1,2,1,3,1,3,6,3.0,neutral or dissatisfied +94857,118184,Female,Loyal Customer,44,Business travel,Business,1444,5,5,5,5,2,5,4,4,4,4,4,3,4,5,96,97.0,satisfied +94858,127055,Male,Loyal Customer,31,Business travel,Business,647,4,4,5,5,4,4,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +94859,94020,Male,Loyal Customer,59,Business travel,Business,189,3,1,3,3,5,5,5,4,4,4,5,3,4,3,1,2.0,satisfied +94860,26216,Female,Loyal Customer,65,Personal Travel,Eco,515,3,4,3,4,4,4,5,3,3,3,3,3,3,4,11,0.0,neutral or dissatisfied +94861,103396,Male,Loyal Customer,47,Business travel,Eco,237,2,2,3,2,2,2,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +94862,46427,Male,Loyal Customer,58,Personal Travel,Eco,458,2,5,2,3,1,2,1,1,3,4,5,3,4,1,0,0.0,neutral or dissatisfied +94863,31034,Male,Loyal Customer,26,Business travel,Eco,862,4,1,1,1,4,4,5,4,2,2,3,2,2,4,0,0.0,satisfied +94864,95511,Female,Loyal Customer,51,Business travel,Business,441,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +94865,63690,Male,Loyal Customer,39,Business travel,Business,3170,1,1,3,1,2,2,2,4,2,4,5,2,5,2,350,318.0,satisfied +94866,36083,Female,Loyal Customer,29,Personal Travel,Eco,474,3,3,3,2,3,3,3,3,2,2,1,3,4,3,0,4.0,neutral or dissatisfied +94867,103745,Male,Loyal Customer,51,Business travel,Business,3248,2,2,2,2,4,5,4,4,4,4,4,5,4,4,20,0.0,satisfied +94868,33415,Female,Loyal Customer,47,Business travel,Business,2556,5,5,5,5,4,4,4,4,4,4,3,4,1,4,0,0.0,satisfied +94869,109693,Female,Loyal Customer,31,Business travel,Business,1590,2,2,2,2,5,5,5,5,5,2,5,4,5,5,19,1.0,satisfied +94870,29845,Female,Loyal Customer,35,Business travel,Business,261,0,0,0,2,5,3,2,2,2,2,2,5,2,4,44,58.0,satisfied +94871,121607,Male,Loyal Customer,40,Personal Travel,Eco,912,2,4,2,3,2,2,3,2,3,2,4,3,4,2,0,3.0,neutral or dissatisfied +94872,55475,Male,Loyal Customer,36,Personal Travel,Eco,1825,1,4,2,4,1,2,1,1,4,3,4,4,1,1,0,0.0,neutral or dissatisfied +94873,94694,Male,Loyal Customer,53,Business travel,Business,239,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +94874,72912,Female,Loyal Customer,26,Business travel,Business,1089,4,4,4,4,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +94875,28429,Female,Loyal Customer,32,Business travel,Eco,2496,5,1,1,1,5,5,5,3,4,4,1,5,5,5,0,0.0,satisfied +94876,18934,Female,Loyal Customer,17,Personal Travel,Eco,448,1,4,1,3,2,1,1,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +94877,38515,Female,Loyal Customer,43,Business travel,Business,2446,1,1,1,1,4,5,2,5,5,5,5,3,5,4,19,0.0,satisfied +94878,90185,Female,Loyal Customer,61,Personal Travel,Eco,983,3,4,3,2,3,4,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +94879,39214,Female,disloyal Customer,23,Business travel,Eco,67,5,0,5,5,5,5,5,5,2,5,5,5,5,5,15,6.0,satisfied +94880,63067,Female,Loyal Customer,62,Personal Travel,Eco,862,1,5,0,4,3,4,4,4,4,0,4,4,4,3,0,0.0,neutral or dissatisfied +94881,96599,Male,disloyal Customer,18,Business travel,Business,937,5,0,4,2,3,4,3,3,3,2,5,3,4,3,3,0.0,satisfied +94882,44436,Male,Loyal Customer,60,Business travel,Business,588,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,3.0,satisfied +94883,124838,Male,Loyal Customer,20,Personal Travel,Eco,280,2,4,2,5,1,2,5,1,4,5,4,5,5,1,0,46.0,neutral or dissatisfied +94884,109494,Female,Loyal Customer,41,Business travel,Business,3130,4,5,5,5,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +94885,97715,Male,Loyal Customer,19,Personal Travel,Eco,942,2,4,2,4,5,2,4,5,5,4,3,1,5,5,14,20.0,neutral or dissatisfied +94886,32451,Female,Loyal Customer,54,Business travel,Business,2652,1,4,4,4,2,4,3,2,2,2,1,2,2,4,0,0.0,neutral or dissatisfied +94887,74416,Female,Loyal Customer,40,Business travel,Business,1126,1,1,2,1,5,5,4,5,5,5,5,4,5,5,14,14.0,satisfied +94888,128616,Male,disloyal Customer,30,Business travel,Business,679,4,3,3,2,4,3,4,4,4,3,4,3,5,4,0,0.0,satisfied +94889,115794,Female,Loyal Customer,36,Business travel,Business,2554,5,5,5,5,2,3,4,4,4,4,4,3,4,5,29,25.0,satisfied +94890,117087,Male,Loyal Customer,30,Business travel,Business,3023,2,5,5,5,2,2,2,2,2,2,4,4,4,2,4,0.0,neutral or dissatisfied +94891,1830,Female,Loyal Customer,16,Personal Travel,Eco,408,2,1,2,4,2,2,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +94892,105328,Female,Loyal Customer,48,Business travel,Business,528,1,1,1,1,4,5,5,4,4,5,4,4,4,4,53,48.0,satisfied +94893,63552,Female,Loyal Customer,57,Business travel,Business,1009,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +94894,91162,Male,Loyal Customer,38,Personal Travel,Eco,581,1,5,1,1,4,1,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +94895,51257,Male,disloyal Customer,37,Business travel,Eco Plus,109,3,3,3,3,5,3,5,5,2,1,3,4,2,5,103,95.0,neutral or dissatisfied +94896,71931,Female,Loyal Customer,47,Business travel,Business,1723,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,23.0,satisfied +94897,40061,Female,Loyal Customer,30,Business travel,Eco,866,4,2,2,2,4,4,4,4,4,4,2,1,4,4,5,0.0,satisfied +94898,118955,Female,disloyal Customer,30,Business travel,Eco,682,2,2,2,1,2,2,2,2,2,1,2,4,3,2,0,0.0,neutral or dissatisfied +94899,73169,Female,disloyal Customer,25,Business travel,Business,1258,3,0,3,3,3,3,3,3,4,2,4,1,3,3,0,11.0,neutral or dissatisfied +94900,105832,Male,Loyal Customer,57,Personal Travel,Eco,842,4,5,4,5,1,4,1,1,4,5,4,3,5,1,92,102.0,neutral or dissatisfied +94901,33298,Male,Loyal Customer,67,Personal Travel,Eco Plus,201,2,5,0,4,3,0,3,3,3,2,1,2,4,3,0,8.0,neutral or dissatisfied +94902,102777,Female,Loyal Customer,64,Business travel,Eco,1099,1,2,2,2,4,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +94903,34546,Male,Loyal Customer,65,Personal Travel,Business,1598,2,5,2,4,4,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +94904,36601,Male,Loyal Customer,44,Business travel,Business,1197,2,2,2,2,1,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +94905,18680,Male,Loyal Customer,12,Personal Travel,Eco,190,2,2,0,4,3,0,2,3,4,4,3,1,3,3,0,8.0,neutral or dissatisfied +94906,13130,Female,Loyal Customer,37,Business travel,Business,1827,2,2,2,2,3,3,3,2,2,2,2,3,2,2,0,2.0,neutral or dissatisfied +94907,59538,Female,disloyal Customer,21,Business travel,Eco,964,3,3,3,1,1,3,1,1,4,3,4,3,5,1,0,0.0,neutral or dissatisfied +94908,62670,Male,Loyal Customer,51,Business travel,Eco Plus,1726,2,3,3,3,2,2,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +94909,117410,Male,Loyal Customer,18,Business travel,Business,1717,1,4,4,4,1,1,1,1,2,1,4,2,3,1,0,0.0,neutral or dissatisfied +94910,54899,Female,Loyal Customer,48,Personal Travel,Eco,862,2,4,2,3,4,5,4,1,1,2,1,4,1,4,13,4.0,neutral or dissatisfied +94911,74565,Male,Loyal Customer,9,Business travel,Business,1205,4,4,5,4,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +94912,122862,Male,Loyal Customer,42,Business travel,Eco,226,3,1,1,1,3,3,3,3,2,2,2,4,3,3,0,0.0,neutral or dissatisfied +94913,23228,Male,Loyal Customer,60,Business travel,Business,116,2,2,2,2,3,5,5,4,4,4,3,1,4,3,0,0.0,satisfied +94914,48296,Male,Loyal Customer,33,Business travel,Business,1499,4,4,4,4,3,3,3,3,3,5,2,3,2,3,14,13.0,satisfied +94915,5273,Male,Loyal Customer,9,Personal Travel,Eco,295,4,4,4,2,5,4,5,5,4,3,5,5,5,5,0,7.0,neutral or dissatisfied +94916,17722,Male,disloyal Customer,46,Business travel,Eco,383,2,4,2,4,2,1,3,2,4,2,2,3,2,3,231,225.0,neutral or dissatisfied +94917,11540,Male,Loyal Customer,45,Business travel,Business,3126,1,1,3,1,5,5,5,5,4,4,4,5,5,5,159,151.0,satisfied +94918,28427,Male,Loyal Customer,22,Personal Travel,Eco Plus,1399,1,3,1,4,3,1,3,3,2,3,4,1,4,3,6,0.0,neutral or dissatisfied +94919,128537,Male,Loyal Customer,58,Business travel,Business,651,5,5,5,5,4,5,5,4,4,4,4,5,4,4,8,5.0,satisfied +94920,71819,Female,disloyal Customer,28,Business travel,Business,1723,1,1,1,2,3,1,3,3,5,5,4,3,4,3,2,0.0,neutral or dissatisfied +94921,36678,Male,Loyal Customer,61,Personal Travel,Eco,1197,4,4,4,1,2,4,2,2,4,5,5,2,5,2,0,20.0,neutral or dissatisfied +94922,42283,Female,Loyal Customer,47,Business travel,Eco,838,3,5,5,5,1,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +94923,21736,Male,disloyal Customer,23,Business travel,Eco,563,4,5,4,1,4,4,4,4,2,4,5,3,4,4,5,0.0,neutral or dissatisfied +94924,11583,Male,Loyal Customer,45,Business travel,Business,468,3,3,3,3,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +94925,19851,Female,Loyal Customer,38,Business travel,Business,693,1,1,5,1,1,3,3,1,1,1,1,4,1,3,7,2.0,neutral or dissatisfied +94926,110844,Male,Loyal Customer,52,Business travel,Business,2832,2,2,2,2,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +94927,93527,Male,Loyal Customer,46,Business travel,Business,2461,5,4,5,5,2,5,5,5,5,5,5,5,5,4,48,38.0,satisfied +94928,107046,Male,Loyal Customer,65,Business travel,Business,2035,1,1,1,1,3,5,5,5,5,5,5,5,5,3,5,0.0,satisfied +94929,14119,Male,Loyal Customer,34,Business travel,Business,2530,4,5,5,5,1,3,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +94930,55875,Male,Loyal Customer,45,Business travel,Business,473,5,5,5,5,5,5,5,4,4,5,4,3,4,3,0,0.0,satisfied +94931,21198,Male,Loyal Customer,38,Business travel,Eco,192,5,2,2,2,5,5,5,5,4,5,1,3,2,5,5,5.0,satisfied +94932,80312,Female,Loyal Customer,28,Business travel,Business,746,3,3,3,3,5,5,5,5,5,2,5,2,4,5,9,0.0,satisfied +94933,122586,Female,disloyal Customer,25,Business travel,Business,728,3,5,3,5,2,3,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +94934,61509,Female,Loyal Customer,56,Personal Travel,Eco,2419,2,5,2,2,5,4,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +94935,89292,Female,disloyal Customer,29,Business travel,Business,453,4,4,4,4,1,4,4,1,4,4,5,3,4,1,2,0.0,neutral or dissatisfied +94936,82669,Female,Loyal Customer,38,Business travel,Business,3495,5,5,5,5,3,5,5,3,3,4,4,5,3,4,0,0.0,satisfied +94937,90634,Male,disloyal Customer,30,Business travel,Business,646,5,5,5,3,3,5,3,3,5,3,4,3,4,3,0,0.0,satisfied +94938,14310,Male,Loyal Customer,43,Business travel,Business,1604,3,2,2,2,2,2,2,3,3,3,3,3,3,3,72,73.0,neutral or dissatisfied +94939,9246,Male,Loyal Customer,16,Personal Travel,Eco,157,4,5,4,5,3,4,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +94940,120186,Male,Loyal Customer,42,Business travel,Business,1325,2,1,2,2,3,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +94941,102214,Female,Loyal Customer,62,Business travel,Eco,414,3,2,2,2,1,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +94942,113352,Female,Loyal Customer,35,Business travel,Business,1676,0,0,0,4,5,5,4,5,5,5,5,3,5,5,48,43.0,satisfied +94943,77957,Female,Loyal Customer,58,Business travel,Business,2945,4,4,4,4,3,5,5,5,5,5,5,5,5,3,11,7.0,satisfied +94944,27836,Male,Loyal Customer,33,Personal Travel,Eco,1448,3,5,3,1,2,3,2,2,2,4,2,4,4,2,0,0.0,neutral or dissatisfied +94945,57023,Male,Loyal Customer,58,Business travel,Business,2454,5,1,5,5,4,4,4,4,4,4,4,4,5,4,16,26.0,satisfied +94946,25270,Male,disloyal Customer,25,Business travel,Eco,425,3,0,3,3,4,3,4,4,3,4,4,1,3,4,77,87.0,neutral or dissatisfied +94947,75569,Male,disloyal Customer,21,Business travel,Business,337,5,0,4,2,3,4,3,3,4,5,5,3,5,3,0,0.0,satisfied +94948,32766,Male,disloyal Customer,22,Business travel,Eco,163,4,4,4,1,4,4,3,4,4,5,2,4,3,4,0,0.0,satisfied +94949,128535,Male,Loyal Customer,46,Personal Travel,Eco,304,2,1,1,2,3,1,3,3,4,2,2,3,2,3,0,0.0,neutral or dissatisfied +94950,98,Male,Loyal Customer,44,Business travel,Business,562,4,4,4,4,3,4,5,4,4,4,4,3,4,5,0,11.0,satisfied +94951,74181,Female,Loyal Customer,68,Personal Travel,Eco,641,3,5,2,2,2,4,5,1,1,2,1,4,1,4,15,0.0,neutral or dissatisfied +94952,45181,Female,Loyal Customer,40,Business travel,Eco Plus,174,1,4,4,4,1,1,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +94953,19063,Male,Loyal Customer,24,Business travel,Business,2233,1,1,1,1,4,4,4,4,3,4,1,2,5,4,0,0.0,satisfied +94954,34369,Male,Loyal Customer,9,Personal Travel,Eco,541,2,5,2,1,3,2,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +94955,103121,Female,Loyal Customer,36,Personal Travel,Eco,546,3,4,3,4,5,3,5,5,4,3,4,1,1,5,16,9.0,neutral or dissatisfied +94956,36368,Female,Loyal Customer,33,Business travel,Business,200,3,3,3,3,4,2,5,4,4,4,5,4,4,5,0,0.0,satisfied +94957,102473,Male,Loyal Customer,15,Personal Travel,Eco,414,2,4,2,4,4,2,4,4,5,5,5,2,5,4,23,14.0,neutral or dissatisfied +94958,113695,Female,Loyal Customer,26,Personal Travel,Eco,386,1,4,1,1,3,1,3,3,5,5,3,2,2,3,7,2.0,neutral or dissatisfied +94959,70584,Male,Loyal Customer,27,Personal Travel,Eco,1258,4,5,4,3,3,4,4,3,3,5,5,5,4,3,5,0.0,satisfied +94960,52662,Male,Loyal Customer,11,Personal Travel,Eco,119,2,5,2,3,4,2,4,4,1,3,4,2,1,4,0,0.0,neutral or dissatisfied +94961,33463,Female,Loyal Customer,7,Personal Travel,Eco Plus,2614,2,5,2,2,2,4,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +94962,29996,Female,Loyal Customer,27,Business travel,Business,3277,2,2,2,2,5,5,5,5,4,5,2,5,5,5,4,3.0,satisfied +94963,73715,Female,Loyal Customer,42,Business travel,Eco,192,4,1,1,1,1,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +94964,9945,Female,disloyal Customer,23,Business travel,Eco,534,3,2,3,4,4,3,4,4,2,2,3,2,4,4,0,0.0,neutral or dissatisfied +94965,61349,Male,Loyal Customer,59,Business travel,Business,602,3,3,3,3,2,4,5,4,4,4,4,3,4,5,19,7.0,satisfied +94966,16450,Male,Loyal Customer,55,Personal Travel,Eco,529,4,5,4,2,1,4,1,1,5,2,4,3,5,1,0,0.0,satisfied +94967,111536,Female,disloyal Customer,24,Business travel,Eco,883,4,4,4,2,1,4,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +94968,5509,Male,Loyal Customer,8,Business travel,Eco Plus,948,3,3,5,5,3,3,2,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +94969,77968,Male,Loyal Customer,40,Business travel,Business,3434,3,3,3,3,4,4,4,4,4,4,4,5,4,3,0,9.0,satisfied +94970,51547,Female,Loyal Customer,38,Business travel,Eco,370,4,4,4,4,4,4,4,4,2,2,4,4,4,4,0,11.0,satisfied +94971,68268,Male,Loyal Customer,65,Personal Travel,Eco,631,2,3,2,2,1,2,2,1,4,3,3,4,2,1,0,8.0,neutral or dissatisfied +94972,13265,Male,Loyal Customer,7,Personal Travel,Eco,468,3,4,3,3,1,3,2,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +94973,79576,Male,disloyal Customer,34,Business travel,Business,794,1,0,0,5,0,3,4,3,2,5,5,4,4,4,64,134.0,neutral or dissatisfied +94974,76193,Female,Loyal Customer,13,Business travel,Business,2422,1,1,1,1,3,2,3,3,4,3,3,4,4,3,0,0.0,satisfied +94975,8608,Male,Loyal Customer,45,Business travel,Business,1371,4,4,4,4,5,4,4,3,3,4,3,4,3,3,22,19.0,satisfied +94976,102987,Female,Loyal Customer,41,Business travel,Business,546,1,1,1,1,4,4,4,4,4,4,4,3,4,4,55,51.0,satisfied +94977,77594,Female,Loyal Customer,30,Business travel,Business,3371,4,4,4,4,4,4,4,4,5,5,5,5,5,4,100,101.0,satisfied +94978,93925,Female,Loyal Customer,43,Business travel,Business,3845,2,2,2,2,2,4,4,5,5,5,5,3,5,4,43,47.0,satisfied +94979,63820,Male,Loyal Customer,49,Business travel,Business,3979,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +94980,71213,Male,Loyal Customer,57,Business travel,Business,3449,2,2,3,2,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +94981,98142,Male,Loyal Customer,57,Business travel,Business,745,3,3,3,3,5,4,4,3,3,3,3,2,3,2,26,17.0,neutral or dissatisfied +94982,20218,Male,Loyal Customer,35,Business travel,Business,179,1,1,1,1,1,1,5,4,4,4,5,2,4,3,0,0.0,satisfied +94983,106344,Female,Loyal Customer,60,Business travel,Business,2067,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +94984,19435,Female,Loyal Customer,10,Personal Travel,Eco,645,1,5,1,3,4,1,4,4,1,1,4,2,2,4,0,0.0,neutral or dissatisfied +94985,57530,Female,disloyal Customer,39,Business travel,Business,413,4,4,4,2,1,4,1,1,2,2,2,3,3,1,1,0.0,neutral or dissatisfied +94986,18186,Male,disloyal Customer,42,Business travel,Business,224,3,3,3,1,5,3,2,5,2,1,5,2,3,5,0,0.0,neutral or dissatisfied +94987,79604,Female,Loyal Customer,14,Business travel,Business,3883,2,4,4,4,2,2,2,2,3,2,3,2,3,2,0,21.0,neutral or dissatisfied +94988,121376,Female,Loyal Customer,43,Business travel,Business,2279,3,3,3,3,2,3,5,4,4,4,4,5,4,4,0,0.0,satisfied +94989,34442,Male,Loyal Customer,63,Business travel,Eco Plus,2422,1,1,1,1,1,1,1,4,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +94990,52209,Male,Loyal Customer,46,Business travel,Eco,651,5,4,4,4,4,5,4,4,3,1,5,3,5,4,0,2.0,satisfied +94991,103676,Male,Loyal Customer,39,Business travel,Business,251,4,5,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +94992,45323,Female,Loyal Customer,40,Business travel,Business,188,5,5,5,5,1,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +94993,129030,Female,Loyal Customer,7,Personal Travel,Eco Plus,2611,2,4,2,3,2,2,2,4,5,4,3,2,4,2,36,16.0,neutral or dissatisfied +94994,80131,Male,Loyal Customer,53,Business travel,Business,2586,5,5,5,5,4,4,4,3,2,4,5,4,3,4,0,5.0,satisfied +94995,59386,Male,Loyal Customer,34,Personal Travel,Eco,2399,2,4,2,5,4,2,4,4,4,2,5,3,4,4,7,0.0,neutral or dissatisfied +94996,85986,Female,Loyal Customer,58,Business travel,Business,3147,2,2,2,2,3,5,4,4,4,5,4,3,4,4,8,0.0,satisfied +94997,102804,Female,Loyal Customer,37,Business travel,Business,342,1,1,1,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +94998,67480,Male,Loyal Customer,19,Personal Travel,Eco,721,4,5,4,4,2,4,2,2,5,5,4,3,4,2,10,0.0,neutral or dissatisfied +94999,100711,Male,Loyal Customer,60,Business travel,Business,2638,1,1,1,1,5,5,5,5,5,4,5,5,5,3,9,0.0,satisfied +95000,70881,Female,Loyal Customer,58,Personal Travel,Eco Plus,761,1,4,1,3,4,4,5,3,3,1,3,5,3,4,19,13.0,neutral or dissatisfied +95001,127380,Female,Loyal Customer,49,Business travel,Business,2125,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +95002,114348,Female,Loyal Customer,20,Personal Travel,Eco,909,1,3,1,4,4,1,4,4,1,2,4,2,4,4,0,0.0,neutral or dissatisfied +95003,67430,Male,Loyal Customer,46,Business travel,Eco,641,1,5,5,5,1,1,1,1,2,3,4,2,4,1,28,36.0,neutral or dissatisfied +95004,12864,Male,Loyal Customer,47,Business travel,Eco Plus,528,3,3,3,3,3,3,3,3,4,3,2,3,4,3,205,187.0,neutral or dissatisfied +95005,6869,Female,Loyal Customer,38,Personal Travel,Eco,622,3,4,3,4,2,3,2,2,2,2,3,3,3,2,0,0.0,neutral or dissatisfied +95006,80098,Male,Loyal Customer,21,Business travel,Business,1620,5,5,5,5,3,4,3,3,3,5,4,4,5,3,0,0.0,satisfied +95007,109999,Female,disloyal Customer,46,Business travel,Business,1142,3,2,2,2,1,3,4,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +95008,57792,Male,Loyal Customer,63,Business travel,Eco Plus,2704,1,0,0,3,1,5,5,2,2,3,3,5,3,5,3,0.0,neutral or dissatisfied +95009,52318,Female,disloyal Customer,35,Business travel,Eco,493,2,1,2,4,5,2,5,5,4,4,4,1,4,5,4,3.0,neutral or dissatisfied +95010,41695,Male,Loyal Customer,70,Personal Travel,Eco,347,3,4,3,2,1,3,1,1,3,3,5,4,4,1,0,1.0,neutral or dissatisfied +95011,25672,Male,Loyal Customer,66,Personal Travel,Eco,761,5,5,5,5,4,5,4,4,3,4,4,5,4,4,35,28.0,satisfied +95012,113412,Female,disloyal Customer,20,Business travel,Eco,414,3,0,2,4,2,3,4,3,2,4,4,4,5,4,169,172.0,neutral or dissatisfied +95013,64406,Female,Loyal Customer,29,Business travel,Business,2691,4,4,5,4,4,3,4,4,4,5,4,5,4,4,0,0.0,satisfied +95014,110160,Female,Loyal Customer,16,Personal Travel,Eco,1048,2,5,2,3,2,2,2,2,5,4,4,5,5,2,36,35.0,neutral or dissatisfied +95015,123485,Female,Loyal Customer,50,Business travel,Eco,2125,3,2,2,2,2,4,4,3,3,3,3,4,3,4,57,53.0,neutral or dissatisfied +95016,129049,Female,Loyal Customer,33,Business travel,Business,1846,3,3,3,3,5,4,4,3,3,3,3,2,3,1,0,20.0,neutral or dissatisfied +95017,101673,Female,Loyal Customer,57,Personal Travel,Eco,2106,2,3,2,2,2,3,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +95018,9424,Male,Loyal Customer,46,Business travel,Business,3867,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +95019,14786,Female,Loyal Customer,40,Business travel,Business,2527,3,3,3,3,4,4,4,4,4,4,4,3,4,1,0,13.0,satisfied +95020,56941,Female,Loyal Customer,45,Business travel,Business,2434,3,3,3,3,3,3,3,2,5,2,4,3,1,3,0,0.0,neutral or dissatisfied +95021,92495,Male,Loyal Customer,68,Business travel,Eco,639,3,2,1,2,4,3,4,4,1,5,5,5,1,4,0,0.0,satisfied +95022,58178,Female,Loyal Customer,51,Business travel,Business,2236,1,1,1,1,2,4,4,4,4,4,4,3,4,5,7,0.0,satisfied +95023,15852,Male,Loyal Customer,59,Business travel,Business,332,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +95024,63282,Female,Loyal Customer,44,Business travel,Business,1545,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,2.0,satisfied +95025,123510,Male,Loyal Customer,12,Personal Travel,Eco,2125,3,4,4,4,3,4,3,3,3,1,3,3,3,3,18,23.0,neutral or dissatisfied +95026,92195,Male,Loyal Customer,22,Business travel,Business,2079,1,1,1,1,4,4,4,4,5,4,3,5,4,4,22,1.0,satisfied +95027,61669,Female,disloyal Customer,16,Business travel,Eco,997,3,3,3,3,4,3,2,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +95028,90674,Male,Loyal Customer,41,Business travel,Business,406,3,3,3,3,4,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +95029,102616,Male,disloyal Customer,49,Business travel,Eco,1294,2,2,2,3,4,2,2,4,4,3,3,3,4,4,17,17.0,neutral or dissatisfied +95030,95592,Female,Loyal Customer,51,Business travel,Eco,670,3,5,5,5,1,3,4,3,3,3,3,4,3,4,2,0.0,neutral or dissatisfied +95031,116090,Male,Loyal Customer,10,Personal Travel,Eco,342,3,4,3,3,3,3,1,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +95032,3726,Male,Loyal Customer,36,Personal Travel,Eco,431,3,3,3,1,1,3,1,1,1,3,2,4,2,1,0,3.0,neutral or dissatisfied +95033,101604,Male,disloyal Customer,45,Business travel,Eco,1371,2,2,2,3,5,2,5,5,4,2,3,3,3,5,6,16.0,neutral or dissatisfied +95034,116422,Male,Loyal Customer,22,Personal Travel,Eco,342,2,2,2,2,3,2,3,3,3,3,2,3,2,3,1,0.0,neutral or dissatisfied +95035,102516,Female,Loyal Customer,45,Personal Travel,Eco,223,3,3,3,1,3,5,5,5,5,3,2,3,5,4,18,10.0,neutral or dissatisfied +95036,56906,Female,Loyal Customer,72,Business travel,Business,2454,3,3,3,3,5,5,5,4,2,3,4,5,3,5,21,89.0,satisfied +95037,104859,Female,disloyal Customer,38,Business travel,Eco,327,3,2,3,3,4,3,3,4,2,1,4,2,4,4,11,19.0,neutral or dissatisfied +95038,3619,Male,Loyal Customer,51,Business travel,Business,3662,3,3,3,3,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +95039,91832,Male,Loyal Customer,59,Business travel,Business,626,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +95040,119396,Female,Loyal Customer,46,Business travel,Business,399,1,1,1,1,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +95041,115756,Female,Loyal Customer,76,Business travel,Business,2062,1,5,5,5,4,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +95042,26842,Female,Loyal Customer,61,Business travel,Eco,224,2,3,3,3,1,4,4,3,3,2,3,1,3,1,0,4.0,neutral or dissatisfied +95043,99822,Male,Loyal Customer,26,Business travel,Business,2448,1,1,1,1,2,2,2,2,3,5,4,5,4,2,0,0.0,satisfied +95044,57986,Male,Loyal Customer,13,Personal Travel,Eco,589,5,4,5,1,5,5,5,5,5,5,4,3,4,5,14,0.0,satisfied +95045,120448,Female,Loyal Customer,69,Personal Travel,Eco,366,2,5,5,3,5,3,3,2,2,5,2,1,2,4,17,40.0,neutral or dissatisfied +95046,39105,Female,Loyal Customer,58,Business travel,Business,3361,1,2,2,2,5,4,3,2,2,2,1,2,2,1,0,0.0,neutral or dissatisfied +95047,9505,Female,Loyal Customer,60,Personal Travel,Eco,322,3,2,3,4,1,4,4,3,3,3,2,4,3,1,0,0.0,neutral or dissatisfied +95048,96272,Female,Loyal Customer,10,Personal Travel,Eco,460,3,4,3,4,2,3,2,2,4,5,1,2,5,2,0,0.0,neutral or dissatisfied +95049,80368,Male,Loyal Customer,48,Business travel,Business,3156,3,3,3,3,2,5,4,4,4,4,4,5,4,3,36,29.0,satisfied +95050,63025,Female,Loyal Customer,58,Business travel,Business,3584,2,4,4,4,2,4,4,2,2,2,2,3,2,4,48,32.0,neutral or dissatisfied +95051,114181,Female,Loyal Customer,43,Business travel,Business,2580,4,4,4,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +95052,42139,Female,Loyal Customer,58,Business travel,Business,3206,4,4,4,4,4,5,5,2,2,2,2,3,2,5,0,12.0,satisfied +95053,30399,Female,Loyal Customer,31,Personal Travel,Eco,862,2,4,1,5,1,1,2,1,3,5,5,4,5,1,14,7.0,neutral or dissatisfied +95054,39312,Male,Loyal Customer,49,Personal Travel,Eco,67,1,4,1,4,1,1,1,1,3,2,4,4,4,1,13,8.0,neutral or dissatisfied +95055,80933,Male,Loyal Customer,35,Personal Travel,Eco,341,3,4,3,4,3,3,3,3,4,3,4,3,5,3,58,65.0,neutral or dissatisfied +95056,86625,Female,disloyal Customer,11,Business travel,Eco,746,5,5,5,2,4,5,4,4,5,2,5,5,4,4,1,1.0,satisfied +95057,26419,Female,Loyal Customer,56,Personal Travel,Business,925,2,5,2,4,2,1,1,2,2,2,2,2,2,1,2,0.0,neutral or dissatisfied +95058,72855,Female,Loyal Customer,51,Business travel,Business,700,2,2,2,2,3,3,3,2,2,2,2,2,2,4,4,0.0,neutral or dissatisfied +95059,32300,Female,Loyal Customer,39,Business travel,Eco,101,2,4,3,4,2,2,2,2,1,2,2,1,3,2,0,0.0,neutral or dissatisfied +95060,119160,Female,Loyal Customer,57,Business travel,Business,3449,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +95061,74538,Male,Loyal Customer,33,Business travel,Business,3182,1,1,1,1,5,5,5,5,3,4,5,3,4,5,33,17.0,satisfied +95062,50879,Female,Loyal Customer,32,Personal Travel,Eco,421,1,4,1,3,1,1,2,1,2,4,4,4,4,1,0,0.0,neutral or dissatisfied +95063,98636,Female,disloyal Customer,30,Business travel,Business,873,3,3,3,3,2,3,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +95064,84646,Male,Loyal Customer,70,Personal Travel,Eco Plus,669,3,5,2,4,2,2,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +95065,47512,Female,Loyal Customer,17,Personal Travel,Eco,599,3,3,2,3,2,2,2,2,3,4,4,3,3,2,31,21.0,neutral or dissatisfied +95066,91977,Male,Loyal Customer,41,Business travel,Business,2446,2,2,2,2,2,4,4,3,3,4,3,5,3,3,0,24.0,satisfied +95067,92074,Female,disloyal Customer,50,Business travel,Business,1535,3,3,3,4,3,3,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +95068,73221,Female,Loyal Customer,52,Business travel,Business,2176,3,3,3,3,2,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +95069,103483,Male,Loyal Customer,36,Business travel,Business,440,2,3,3,3,5,4,3,2,2,2,2,2,2,4,4,0.0,neutral or dissatisfied +95070,55684,Male,disloyal Customer,37,Business travel,Business,1062,1,1,1,3,4,1,5,4,5,2,4,5,4,4,0,11.0,neutral or dissatisfied +95071,111358,Male,disloyal Customer,25,Business travel,Business,1173,4,5,4,1,5,4,5,5,5,4,5,4,4,5,45,42.0,satisfied +95072,42066,Female,Loyal Customer,49,Personal Travel,Eco,241,1,5,1,4,2,4,4,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +95073,4150,Male,Loyal Customer,29,Business travel,Business,3455,5,5,5,5,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +95074,18741,Female,disloyal Customer,44,Business travel,Eco,1167,1,1,1,2,1,1,1,1,4,3,5,2,4,1,0,0.0,neutral or dissatisfied +95075,48102,Female,Loyal Customer,30,Business travel,Eco,236,4,3,3,3,4,4,4,4,1,1,3,2,3,4,0,0.0,satisfied +95076,82918,Male,Loyal Customer,23,Personal Travel,Eco,594,1,4,1,1,2,1,2,2,1,4,1,4,2,2,78,67.0,neutral or dissatisfied +95077,112052,Male,Loyal Customer,7,Personal Travel,Eco Plus,1015,3,1,3,3,3,3,3,3,4,2,4,3,3,3,4,0.0,neutral or dissatisfied +95078,31651,Female,Loyal Customer,38,Business travel,Business,2351,3,3,3,3,2,4,3,5,5,5,5,5,5,4,4,0.0,satisfied +95079,2258,Female,disloyal Customer,29,Business travel,Business,925,4,4,4,2,1,4,1,1,5,3,4,4,5,1,0,83.0,satisfied +95080,41918,Male,Loyal Customer,42,Business travel,Business,2352,2,5,5,5,1,4,4,3,3,2,2,1,3,4,0,6.0,neutral or dissatisfied +95081,97147,Female,disloyal Customer,21,Business travel,Eco,1476,4,4,4,2,4,4,3,4,5,2,4,2,2,4,6,4.0,neutral or dissatisfied +95082,35476,Male,Loyal Customer,19,Personal Travel,Eco,944,1,2,1,4,5,1,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +95083,50013,Male,disloyal Customer,50,Business travel,Eco,158,3,1,3,3,2,3,2,2,3,3,3,2,3,2,83,98.0,neutral or dissatisfied +95084,33169,Male,Loyal Customer,49,Personal Travel,Eco,102,1,4,1,5,4,1,4,4,3,1,4,1,2,4,0,1.0,neutral or dissatisfied +95085,28646,Female,Loyal Customer,66,Personal Travel,Eco,2466,0,4,0,5,2,5,5,5,5,0,5,4,5,5,0,0.0,satisfied +95086,115914,Female,Loyal Customer,24,Business travel,Business,2118,2,2,2,2,2,2,2,2,3,2,3,3,4,2,123,121.0,neutral or dissatisfied +95087,70526,Male,Loyal Customer,33,Business travel,Business,1666,2,2,2,2,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +95088,37365,Male,Loyal Customer,25,Business travel,Business,3680,5,5,5,5,4,4,4,4,2,4,2,4,1,4,2,1.0,satisfied +95089,35358,Female,Loyal Customer,47,Business travel,Business,1503,2,4,4,4,5,3,2,2,2,2,2,4,2,1,89,75.0,neutral or dissatisfied +95090,42362,Female,Loyal Customer,18,Personal Travel,Eco,846,1,4,1,3,5,1,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +95091,114426,Female,Loyal Customer,56,Business travel,Business,1699,3,3,3,3,4,5,5,4,4,4,4,3,4,3,73,71.0,satisfied +95092,15834,Female,Loyal Customer,41,Business travel,Business,3582,2,2,2,2,3,4,4,2,2,2,2,5,2,3,89,54.0,satisfied +95093,65827,Female,Loyal Customer,60,Business travel,Eco,1389,2,4,3,4,3,4,4,2,2,2,2,1,2,3,18,11.0,neutral or dissatisfied +95094,13875,Female,Loyal Customer,32,Business travel,Business,578,2,4,4,4,2,2,2,2,4,1,3,4,3,2,32,37.0,neutral or dissatisfied +95095,91635,Female,Loyal Customer,43,Business travel,Business,799,2,2,5,2,3,5,1,5,5,5,5,3,5,2,0,0.0,satisfied +95096,64166,Female,Loyal Customer,22,Personal Travel,Eco,989,2,3,2,4,2,2,2,2,4,5,4,2,4,2,0,0.0,neutral or dissatisfied +95097,38688,Male,Loyal Customer,52,Business travel,Eco Plus,2704,4,3,3,3,4,4,4,4,5,4,5,4,4,4,24,2.0,satisfied +95098,118538,Female,disloyal Customer,66,Business travel,Business,370,4,4,4,1,1,4,1,1,3,4,4,3,4,1,3,0.0,satisfied +95099,8352,Male,Loyal Customer,19,Personal Travel,Eco,783,3,5,3,2,4,3,4,4,3,5,5,4,4,4,16,18.0,neutral or dissatisfied +95100,64015,Female,Loyal Customer,17,Business travel,Business,3545,2,2,2,2,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +95101,74520,Female,Loyal Customer,60,Business travel,Eco,1438,2,4,4,4,5,4,4,1,1,2,1,3,1,2,33,3.0,neutral or dissatisfied +95102,19861,Male,disloyal Customer,23,Business travel,Eco,693,2,2,2,3,3,2,3,3,2,4,3,2,4,3,3,1.0,neutral or dissatisfied +95103,128670,Male,disloyal Customer,26,Business travel,Business,2288,5,5,5,4,1,5,1,1,4,4,4,3,4,1,1,0.0,satisfied +95104,126026,Female,Loyal Customer,36,Business travel,Business,1518,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +95105,4807,Female,Loyal Customer,56,Personal Travel,Eco,315,4,5,4,3,5,4,4,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +95106,50605,Male,Loyal Customer,29,Personal Travel,Eco,266,4,4,4,2,2,4,2,2,4,2,1,5,1,2,0,0.0,neutral or dissatisfied +95107,129870,Male,disloyal Customer,20,Business travel,Eco,447,2,2,2,1,4,2,4,4,2,4,2,2,2,4,8,0.0,neutral or dissatisfied +95108,125826,Female,disloyal Customer,18,Business travel,Eco,951,3,3,3,4,5,3,5,5,3,2,4,4,3,5,4,13.0,neutral or dissatisfied +95109,59535,Female,Loyal Customer,47,Business travel,Business,854,4,4,4,4,5,5,5,4,4,5,4,5,4,5,0,9.0,satisfied +95110,82257,Female,Loyal Customer,44,Business travel,Business,1481,1,1,5,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +95111,20180,Male,Loyal Customer,27,Personal Travel,Eco,403,3,5,3,4,4,3,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +95112,53650,Male,Loyal Customer,31,Business travel,Eco Plus,1874,2,1,1,1,2,3,2,2,1,2,2,2,3,2,1,24.0,neutral or dissatisfied +95113,129072,Male,Loyal Customer,52,Business travel,Business,2342,3,5,1,5,3,3,3,2,4,3,4,3,2,3,0,7.0,neutral or dissatisfied +95114,114313,Female,Loyal Customer,23,Personal Travel,Eco,862,3,4,3,4,5,3,5,5,4,4,4,5,5,5,70,74.0,neutral or dissatisfied +95115,127459,Male,disloyal Customer,44,Business travel,Business,2075,3,3,3,3,2,3,5,2,4,5,3,4,5,2,0,0.0,neutral or dissatisfied +95116,118143,Male,Loyal Customer,47,Business travel,Business,1444,1,1,1,1,5,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +95117,108438,Female,Loyal Customer,43,Business travel,Business,1440,3,1,1,1,1,3,3,3,3,3,3,4,3,2,17,14.0,neutral or dissatisfied +95118,10816,Male,Loyal Customer,51,Business travel,Business,3420,2,5,5,5,5,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +95119,5881,Male,Loyal Customer,51,Business travel,Business,1650,3,3,3,3,2,4,5,5,5,5,4,3,5,4,27,29.0,satisfied +95120,26174,Female,disloyal Customer,34,Business travel,Eco,406,2,0,2,3,2,2,2,2,2,3,3,4,3,2,8,7.0,neutral or dissatisfied +95121,81063,Female,Loyal Customer,38,Personal Travel,Eco Plus,1399,1,5,1,2,5,1,5,5,3,5,3,3,4,5,8,38.0,neutral or dissatisfied +95122,23413,Female,disloyal Customer,36,Business travel,Eco,541,1,4,0,3,4,0,4,4,2,2,4,4,1,4,1,2.0,neutral or dissatisfied +95123,40275,Female,Loyal Customer,10,Personal Travel,Eco,436,3,5,3,4,2,3,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +95124,2588,Male,Loyal Customer,40,Personal Travel,Eco,304,1,5,1,3,4,1,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +95125,105462,Female,Loyal Customer,51,Personal Travel,Eco Plus,998,2,4,2,3,2,1,5,1,1,2,1,5,1,4,71,69.0,neutral or dissatisfied +95126,126832,Male,Loyal Customer,49,Business travel,Eco,2296,2,5,5,5,2,2,2,2,3,2,2,1,3,2,0,0.0,neutral or dissatisfied +95127,21892,Male,disloyal Customer,22,Business travel,Eco,551,2,4,2,2,3,2,3,3,1,1,4,2,5,3,0,0.0,neutral or dissatisfied +95128,45135,Female,Loyal Customer,62,Business travel,Eco,130,5,1,1,1,3,1,5,3,3,5,3,3,3,1,4,6.0,satisfied +95129,9686,Male,disloyal Customer,21,Business travel,Eco,277,1,1,1,2,1,1,1,4,2,3,2,1,2,1,111,160.0,neutral or dissatisfied +95130,118999,Male,Loyal Customer,58,Business travel,Business,479,1,1,1,1,4,4,5,3,3,4,3,5,3,4,2,0.0,satisfied +95131,93735,Female,Loyal Customer,48,Business travel,Business,368,4,4,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +95132,19463,Female,Loyal Customer,32,Business travel,Business,1859,3,3,3,3,4,4,4,4,2,4,5,5,4,4,5,11.0,satisfied +95133,8419,Male,Loyal Customer,16,Business travel,Business,862,1,0,0,4,3,0,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +95134,83681,Female,Loyal Customer,50,Business travel,Business,577,4,4,4,4,3,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +95135,80220,Male,Loyal Customer,48,Business travel,Business,2153,2,2,2,2,3,3,3,4,5,5,5,3,3,3,140,177.0,satisfied +95136,62601,Male,Loyal Customer,9,Personal Travel,Eco,1744,2,2,2,3,2,2,2,2,2,4,3,2,4,2,15,4.0,neutral or dissatisfied +95137,92216,Female,Loyal Customer,47,Personal Travel,Eco,2079,3,1,3,3,4,2,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +95138,10189,Female,Loyal Customer,57,Business travel,Business,295,2,2,2,2,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +95139,88690,Male,Loyal Customer,36,Personal Travel,Eco,406,1,4,1,3,4,1,4,4,1,5,3,2,4,4,0,0.0,neutral or dissatisfied +95140,4249,Male,Loyal Customer,49,Personal Travel,Eco,1020,4,2,4,3,2,4,2,2,3,3,3,2,3,2,18,15.0,neutral or dissatisfied +95141,41028,Female,disloyal Customer,29,Business travel,Eco,1195,1,1,1,4,4,1,4,4,3,3,4,1,3,4,6,10.0,neutral or dissatisfied +95142,16364,Male,Loyal Customer,33,Personal Travel,Eco,319,3,4,3,3,5,3,5,5,3,5,4,1,3,5,0,4.0,neutral or dissatisfied +95143,30267,Female,Loyal Customer,50,Business travel,Business,1024,3,4,4,4,1,4,4,3,3,3,3,2,3,1,16,2.0,neutral or dissatisfied +95144,26673,Male,Loyal Customer,14,Personal Travel,Eco,406,3,5,3,1,5,3,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +95145,108435,Male,disloyal Customer,10,Business travel,Eco,832,3,3,3,3,3,3,3,3,1,3,4,4,4,3,5,2.0,neutral or dissatisfied +95146,47020,Female,Loyal Customer,14,Personal Travel,Business,351,4,2,4,4,3,4,3,3,1,2,3,3,4,3,0,0.0,neutral or dissatisfied +95147,32337,Female,Loyal Customer,33,Business travel,Business,163,5,5,5,5,3,1,4,4,4,4,3,5,4,1,0,4.0,satisfied +95148,28603,Male,Loyal Customer,20,Business travel,Eco,2384,3,2,2,2,3,4,5,3,3,3,5,2,1,3,0,0.0,satisfied +95149,81673,Male,disloyal Customer,21,Business travel,Eco,907,1,0,0,2,2,0,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +95150,108694,Female,Loyal Customer,20,Personal Travel,Eco,577,2,4,2,4,2,2,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +95151,61170,Female,disloyal Customer,39,Business travel,Business,862,3,3,3,3,4,3,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +95152,126756,Female,Loyal Customer,31,Personal Travel,Eco,2402,3,5,3,4,3,3,1,3,4,5,3,3,5,3,0,0.0,neutral or dissatisfied +95153,75231,Female,Loyal Customer,34,Personal Travel,Eco,1846,3,2,3,4,5,3,1,5,1,5,3,3,3,5,104,104.0,neutral or dissatisfied +95154,22858,Male,Loyal Customer,12,Personal Travel,Eco,170,4,5,4,2,5,4,5,5,4,4,5,5,4,5,2,0.0,satisfied +95155,3606,Female,Loyal Customer,56,Personal Travel,Eco,999,3,5,3,3,4,5,4,4,4,3,4,3,4,3,67,73.0,neutral or dissatisfied +95156,120592,Female,Loyal Customer,37,Business travel,Eco,580,4,2,2,2,4,4,4,4,4,2,4,1,2,4,0,0.0,satisfied +95157,122842,Male,Loyal Customer,40,Business travel,Business,2263,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +95158,125945,Female,Loyal Customer,48,Personal Travel,Eco,861,3,5,3,4,2,5,4,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +95159,52316,Male,Loyal Customer,72,Business travel,Business,2842,2,2,2,2,4,1,1,4,4,4,4,2,4,4,0,5.0,satisfied +95160,110986,Female,Loyal Customer,60,Business travel,Business,2564,0,0,0,3,2,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +95161,117770,Female,disloyal Customer,15,Business travel,Eco,1891,4,4,4,3,2,4,2,2,3,4,3,4,4,2,11,0.0,satisfied +95162,51508,Female,Loyal Customer,56,Business travel,Business,3294,4,4,4,4,2,3,3,4,4,4,4,3,4,4,83,79.0,satisfied +95163,128232,Female,Loyal Customer,16,Personal Travel,Eco,602,2,5,2,5,2,2,2,2,1,3,4,1,2,2,0,0.0,neutral or dissatisfied +95164,122984,Female,Loyal Customer,52,Business travel,Business,600,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +95165,54414,Female,Loyal Customer,16,Business travel,Eco,305,2,2,2,2,2,2,3,2,1,5,4,4,3,2,0,1.0,neutral or dissatisfied +95166,72132,Female,Loyal Customer,33,Business travel,Business,3946,1,1,3,1,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +95167,45997,Male,Loyal Customer,65,Personal Travel,Eco,483,1,3,1,4,3,1,3,3,2,4,2,4,3,3,0,0.0,neutral or dissatisfied +95168,66732,Male,Loyal Customer,36,Personal Travel,Eco,802,2,3,2,4,5,2,1,5,5,5,2,1,4,5,0,0.0,neutral or dissatisfied +95169,54294,Male,Loyal Customer,56,Business travel,Business,2587,3,3,3,3,4,3,4,3,3,3,3,2,3,4,37,40.0,neutral or dissatisfied +95170,71115,Female,Loyal Customer,22,Personal Travel,Eco,2072,1,4,1,3,3,1,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +95171,22974,Male,disloyal Customer,26,Business travel,Eco,528,1,3,1,4,3,1,3,3,1,3,4,2,3,3,50,54.0,neutral or dissatisfied +95172,128127,Female,Loyal Customer,66,Personal Travel,Eco,1587,2,4,2,5,2,3,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +95173,128229,Female,Loyal Customer,30,Business travel,Business,602,2,5,5,5,2,2,2,2,2,5,3,4,4,2,3,13.0,neutral or dissatisfied +95174,41819,Male,Loyal Customer,65,Personal Travel,Eco,257,2,5,2,5,4,2,4,4,1,1,1,1,5,4,0,0.0,neutral or dissatisfied +95175,46224,Male,Loyal Customer,38,Business travel,Business,3383,1,5,5,5,1,3,4,1,1,1,1,3,1,1,18,2.0,neutral or dissatisfied +95176,1413,Male,Loyal Customer,39,Personal Travel,Eco Plus,312,2,5,2,1,1,2,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +95177,4774,Female,Loyal Customer,36,Business travel,Business,438,3,3,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +95178,36928,Female,Loyal Customer,49,Business travel,Eco,867,5,5,5,5,3,5,3,5,5,5,5,3,5,4,0,0.0,satisfied +95179,84010,Female,Loyal Customer,42,Personal Travel,Eco,321,4,3,4,1,1,1,5,4,4,4,4,1,4,4,104,90.0,neutral or dissatisfied +95180,63290,Female,Loyal Customer,37,Business travel,Business,337,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +95181,13339,Male,Loyal Customer,36,Business travel,Business,3485,2,4,2,2,4,4,2,4,4,4,4,1,4,2,0,0.0,satisfied +95182,120071,Male,disloyal Customer,40,Business travel,Business,683,2,2,2,2,2,2,2,2,4,4,5,5,5,2,55,57.0,neutral or dissatisfied +95183,28297,Male,Loyal Customer,41,Business travel,Eco,867,5,4,4,4,5,5,5,5,1,4,1,4,1,5,0,0.0,satisfied +95184,14719,Male,Loyal Customer,48,Personal Travel,Eco,419,3,4,3,3,2,3,2,2,4,5,3,4,2,2,0,22.0,neutral or dissatisfied +95185,96133,Female,Loyal Customer,70,Business travel,Business,666,3,2,2,2,4,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +95186,31035,Female,Loyal Customer,22,Business travel,Business,641,5,5,5,5,5,5,5,5,5,2,2,5,5,5,96,112.0,satisfied +95187,112800,Male,Loyal Customer,25,Business travel,Business,1642,3,3,3,3,3,4,3,3,5,4,4,3,5,3,19,1.0,satisfied +95188,25371,Male,disloyal Customer,20,Business travel,Eco,591,2,1,2,3,4,2,4,4,2,5,3,4,4,4,0,0.0,neutral or dissatisfied +95189,9535,Female,Loyal Customer,54,Business travel,Business,3289,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,20.0,satisfied +95190,125058,Female,Loyal Customer,46,Personal Travel,Business,90,2,5,2,1,5,5,5,5,5,2,5,3,5,4,0,25.0,neutral or dissatisfied +95191,44060,Male,disloyal Customer,25,Business travel,Eco,1075,3,3,3,3,2,3,2,2,2,3,3,3,3,2,12,51.0,neutral or dissatisfied +95192,84216,Male,Loyal Customer,57,Business travel,Eco,432,4,3,3,3,4,4,4,4,2,2,4,2,4,4,9,13.0,neutral or dissatisfied +95193,119135,Female,Loyal Customer,50,Personal Travel,Eco,356,2,4,2,4,5,4,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +95194,121926,Female,Loyal Customer,47,Business travel,Business,3743,5,5,2,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +95195,36724,Female,Loyal Customer,16,Personal Travel,Eco Plus,1237,2,1,2,2,2,2,2,2,4,2,3,1,3,2,0,5.0,neutral or dissatisfied +95196,94151,Female,Loyal Customer,39,Business travel,Business,293,2,2,2,2,3,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +95197,13510,Male,Loyal Customer,60,Business travel,Business,227,3,3,3,3,4,2,4,5,5,5,5,1,5,1,68,61.0,satisfied +95198,82143,Male,Loyal Customer,55,Business travel,Business,2360,3,3,5,3,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +95199,29559,Female,Loyal Customer,44,Business travel,Business,1448,3,4,3,3,2,3,2,4,4,4,4,4,4,5,0,0.0,satisfied +95200,127218,Male,Loyal Customer,35,Personal Travel,Eco Plus,647,3,4,3,3,1,3,1,1,3,3,2,2,3,1,0,0.0,neutral or dissatisfied +95201,113749,Male,Loyal Customer,32,Personal Travel,Eco,386,2,4,2,3,2,2,2,2,4,2,5,4,4,2,76,74.0,neutral or dissatisfied +95202,89976,Female,Loyal Customer,27,Business travel,Business,1310,2,5,2,2,5,5,5,5,3,2,4,5,4,5,0,3.0,satisfied +95203,26076,Male,Loyal Customer,41,Business travel,Eco,591,2,1,1,1,2,2,2,2,1,1,1,5,2,2,0,0.0,satisfied +95204,128686,Male,Loyal Customer,49,Personal Travel,Eco,2442,3,4,3,4,3,3,2,4,3,3,4,2,3,2,110,116.0,neutral or dissatisfied +95205,32634,Female,Loyal Customer,57,Business travel,Eco,216,5,5,5,5,2,5,3,5,5,5,5,1,5,4,0,0.0,satisfied +95206,77634,Male,Loyal Customer,60,Business travel,Business,731,5,5,5,5,2,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +95207,12123,Female,Loyal Customer,18,Personal Travel,Eco,1034,2,5,2,3,2,2,3,2,3,3,4,4,5,2,7,0.0,neutral or dissatisfied +95208,103214,Female,Loyal Customer,58,Business travel,Business,1677,1,1,1,1,2,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +95209,64896,Female,Loyal Customer,49,Business travel,Eco,247,1,4,4,4,5,2,2,1,1,1,1,4,1,3,22,34.0,neutral or dissatisfied +95210,93933,Female,Loyal Customer,42,Business travel,Business,507,3,3,3,3,3,4,3,3,3,4,3,3,3,4,43,12.0,neutral or dissatisfied +95211,129669,Male,Loyal Customer,40,Business travel,Business,3682,4,2,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +95212,32820,Female,disloyal Customer,50,Business travel,Eco,101,4,1,4,2,5,4,5,5,3,5,1,3,2,5,0,0.0,neutral or dissatisfied +95213,85862,Female,Loyal Customer,52,Business travel,Business,2172,5,5,5,5,4,3,4,4,4,4,4,3,4,4,6,0.0,satisfied +95214,119351,Female,Loyal Customer,11,Personal Travel,Eco Plus,214,2,3,2,5,2,2,2,2,1,5,1,5,2,2,0,0.0,neutral or dissatisfied +95215,125784,Male,Loyal Customer,50,Business travel,Business,920,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +95216,121967,Male,Loyal Customer,57,Business travel,Business,2271,2,5,5,5,4,3,2,2,2,2,2,3,2,4,5,52.0,neutral or dissatisfied +95217,83701,Male,Loyal Customer,61,Personal Travel,Eco,577,3,4,3,3,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +95218,2109,Male,Loyal Customer,28,Business travel,Eco Plus,812,2,4,4,4,2,3,2,2,4,1,3,3,4,2,5,0.0,neutral or dissatisfied +95219,43796,Male,Loyal Customer,58,Business travel,Eco Plus,282,4,2,2,2,4,4,4,4,1,3,4,3,1,4,0,18.0,satisfied +95220,35114,Male,Loyal Customer,54,Business travel,Business,1056,4,4,4,4,5,4,2,5,5,5,5,3,5,1,0,39.0,satisfied +95221,10757,Female,disloyal Customer,27,Business travel,Business,191,2,2,2,3,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +95222,9533,Male,Loyal Customer,52,Business travel,Business,2864,4,4,4,4,2,5,5,5,5,5,5,3,5,4,41,41.0,satisfied +95223,124945,Female,disloyal Customer,23,Business travel,Eco,728,3,3,3,3,5,3,1,5,5,5,4,3,5,5,0,5.0,neutral or dissatisfied +95224,115897,Male,Loyal Customer,43,Business travel,Business,308,2,2,3,2,1,3,5,4,4,4,4,1,4,5,77,73.0,satisfied +95225,41256,Female,disloyal Customer,21,Business travel,Eco,1034,3,4,4,3,3,4,3,3,3,3,4,4,3,3,18,15.0,neutral or dissatisfied +95226,128146,Female,Loyal Customer,24,Business travel,Business,1788,5,5,5,5,4,4,4,4,3,3,4,5,5,4,15,16.0,satisfied +95227,23995,Female,Loyal Customer,43,Business travel,Eco,562,4,4,4,4,4,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +95228,48627,Female,disloyal Customer,36,Business travel,Eco Plus,548,4,4,4,3,4,4,4,4,5,1,5,3,3,4,0,0.0,neutral or dissatisfied +95229,81968,Female,Loyal Customer,60,Business travel,Business,1589,4,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +95230,57776,Female,disloyal Customer,23,Business travel,Business,2704,1,1,1,3,1,2,2,4,4,4,3,2,4,2,34,61.0,neutral or dissatisfied +95231,44067,Female,Loyal Customer,23,Personal Travel,Eco,456,3,3,3,3,5,3,5,5,2,1,5,3,1,5,0,8.0,neutral or dissatisfied +95232,6718,Male,Loyal Customer,12,Personal Travel,Eco,438,2,4,2,2,1,2,1,1,3,4,4,5,5,1,17,60.0,neutral or dissatisfied +95233,35362,Female,disloyal Customer,28,Business travel,Eco,1097,2,2,2,4,5,2,5,5,3,5,4,3,4,5,22,51.0,neutral or dissatisfied +95234,94332,Female,Loyal Customer,45,Business travel,Business,2141,0,0,0,3,5,5,4,2,2,5,5,4,2,3,70,62.0,satisfied +95235,121630,Male,Loyal Customer,22,Business travel,Business,2876,4,4,4,4,5,4,5,5,4,3,5,3,4,5,0,0.0,satisfied +95236,22319,Female,Loyal Customer,44,Business travel,Eco,145,4,5,5,5,2,5,2,4,4,4,4,3,4,1,2,0.0,satisfied +95237,89980,Male,Loyal Customer,46,Business travel,Eco Plus,1487,2,2,2,2,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +95238,74758,Male,Loyal Customer,19,Personal Travel,Eco,1126,3,2,3,4,5,3,5,5,3,1,2,1,4,5,16,10.0,neutral or dissatisfied +95239,17472,Male,Loyal Customer,36,Business travel,Business,1570,3,3,3,3,5,3,2,5,5,5,5,2,5,4,0,0.0,satisfied +95240,36649,Female,Loyal Customer,50,Personal Travel,Eco,1185,3,4,3,1,3,5,5,5,5,3,5,5,5,5,0,5.0,neutral or dissatisfied +95241,46809,Male,Loyal Customer,37,Business travel,Business,964,3,1,3,3,3,3,4,4,4,4,4,2,4,5,0,26.0,satisfied +95242,86134,Male,Loyal Customer,58,Business travel,Business,1506,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +95243,28443,Female,Loyal Customer,62,Personal Travel,Eco,2496,2,5,2,2,2,2,2,3,4,3,4,2,5,2,3,18.0,neutral or dissatisfied +95244,117716,Female,Loyal Customer,32,Personal Travel,Eco,1009,1,4,1,5,4,1,4,4,5,4,5,4,5,4,1,0.0,neutral or dissatisfied +95245,109129,Male,disloyal Customer,42,Business travel,Business,793,1,1,1,3,3,1,3,3,5,3,5,5,4,3,0,0.0,neutral or dissatisfied +95246,98307,Male,Loyal Customer,51,Business travel,Business,1565,2,2,2,2,2,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +95247,59067,Female,Loyal Customer,19,Business travel,Business,1781,3,2,3,2,3,3,3,3,1,3,4,2,4,3,5,25.0,neutral or dissatisfied +95248,19777,Female,Loyal Customer,43,Business travel,Eco,667,4,3,3,3,5,4,1,4,4,4,4,2,4,3,0,0.0,satisfied +95249,11856,Female,Loyal Customer,46,Business travel,Business,912,2,3,3,3,3,4,3,2,2,2,2,1,2,2,103,95.0,neutral or dissatisfied +95250,84840,Female,disloyal Customer,51,Business travel,Eco,547,3,2,3,2,4,3,2,4,2,4,2,1,2,4,17,29.0,neutral or dissatisfied +95251,126597,Male,disloyal Customer,25,Business travel,Eco,1337,3,3,3,3,1,3,1,1,2,5,4,3,4,1,0,0.0,neutral or dissatisfied +95252,17190,Female,disloyal Customer,38,Personal Travel,Eco,643,3,3,4,4,3,4,2,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +95253,70240,Male,disloyal Customer,41,Business travel,Business,1592,4,4,4,3,5,4,4,5,4,5,5,4,4,5,0,0.0,satisfied +95254,117257,Female,Loyal Customer,44,Personal Travel,Eco,451,3,5,4,4,4,5,4,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +95255,11269,Female,Loyal Customer,25,Personal Travel,Eco,429,1,4,1,2,1,1,1,1,3,2,3,3,2,1,0,0.0,neutral or dissatisfied +95256,50160,Male,Loyal Customer,33,Business travel,Business,3284,3,4,4,4,3,3,3,3,1,5,4,3,3,3,15,24.0,neutral or dissatisfied +95257,33597,Female,Loyal Customer,54,Business travel,Eco,474,2,5,5,5,5,2,1,2,2,2,2,4,2,4,0,0.0,satisfied +95258,80390,Male,Loyal Customer,15,Personal Travel,Eco,422,2,5,5,4,5,5,3,5,2,1,4,2,2,5,0,0.0,neutral or dissatisfied +95259,48391,Female,Loyal Customer,40,Personal Travel,Eco,674,1,4,0,1,2,0,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +95260,117894,Male,Loyal Customer,54,Business travel,Business,3304,4,4,4,4,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +95261,103896,Female,Loyal Customer,39,Business travel,Business,882,1,1,1,1,2,5,5,2,2,2,2,5,2,3,96,109.0,satisfied +95262,111175,Female,disloyal Customer,50,Business travel,Business,1506,4,3,3,4,5,4,3,5,4,2,5,5,5,5,23,6.0,satisfied +95263,120425,Female,Loyal Customer,27,Business travel,Business,2802,2,5,2,2,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +95264,59253,Female,Loyal Customer,57,Business travel,Business,3904,3,3,3,3,4,4,4,4,3,4,4,4,3,4,28,0.0,satisfied +95265,98752,Female,Loyal Customer,42,Business travel,Business,1814,1,1,1,1,5,4,4,4,4,4,4,3,4,4,33,49.0,satisfied +95266,19818,Female,disloyal Customer,34,Business travel,Eco,654,2,5,2,5,2,2,2,2,3,5,3,1,3,2,0,1.0,neutral or dissatisfied +95267,83365,Male,disloyal Customer,26,Business travel,Business,1124,2,2,2,3,1,2,1,1,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +95268,58245,Male,disloyal Customer,10,Business travel,Eco,925,3,3,3,3,1,3,1,1,3,2,2,4,2,1,29,59.0,neutral or dissatisfied +95269,122231,Male,Loyal Customer,26,Business travel,Eco,573,3,5,5,5,3,3,1,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +95270,97868,Male,Loyal Customer,52,Business travel,Business,1875,3,3,3,3,5,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +95271,83289,Male,Loyal Customer,63,Personal Travel,Eco,2079,4,1,4,3,2,4,2,2,3,2,4,3,4,2,66,91.0,neutral or dissatisfied +95272,42544,Female,Loyal Customer,35,Business travel,Eco,986,4,4,4,4,4,4,4,4,4,1,4,4,3,4,9,47.0,neutral or dissatisfied +95273,17940,Male,disloyal Customer,23,Business travel,Eco,95,2,2,2,2,5,2,5,5,1,2,3,1,2,5,81,81.0,neutral or dissatisfied +95274,89817,Male,Loyal Customer,22,Business travel,Eco Plus,1069,1,5,2,5,1,1,2,1,2,4,2,4,2,1,0,4.0,neutral or dissatisfied +95275,63415,Female,Loyal Customer,32,Personal Travel,Eco,337,3,5,3,5,5,3,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +95276,23319,Male,Loyal Customer,75,Business travel,Business,2041,4,3,3,3,5,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +95277,13254,Female,Loyal Customer,32,Business travel,Business,3567,1,1,1,1,1,1,1,1,1,3,3,4,3,1,0,0.0,neutral or dissatisfied +95278,69605,Female,Loyal Customer,30,Personal Travel,Eco,2475,1,2,1,4,1,3,3,4,5,3,3,3,2,3,0,16.0,neutral or dissatisfied +95279,13223,Female,Loyal Customer,40,Business travel,Business,2984,4,4,4,4,5,1,3,5,5,5,5,1,5,2,26,44.0,satisfied +95280,69906,Male,Loyal Customer,55,Business travel,Business,1514,3,3,5,3,3,5,4,5,5,5,5,3,5,4,6,15.0,satisfied +95281,14577,Male,disloyal Customer,29,Business travel,Eco,986,2,3,3,3,1,3,1,1,2,2,4,1,3,1,113,96.0,neutral or dissatisfied +95282,100623,Female,disloyal Customer,28,Business travel,Business,1121,2,2,2,4,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +95283,118910,Female,Loyal Customer,58,Personal Travel,Eco,570,4,1,4,4,1,4,3,1,1,4,1,2,1,1,6,0.0,neutral or dissatisfied +95284,30753,Male,Loyal Customer,10,Personal Travel,Eco,977,3,5,3,3,2,3,2,2,3,2,4,4,4,2,51,46.0,neutral or dissatisfied +95285,5532,Female,Loyal Customer,52,Business travel,Business,2504,5,5,5,5,5,4,3,4,4,4,4,1,4,1,0,0.0,satisfied +95286,12267,Female,Loyal Customer,55,Business travel,Eco,253,5,1,1,1,5,4,3,5,5,5,5,3,5,5,13,13.0,satisfied +95287,47265,Female,Loyal Customer,10,Personal Travel,Business,584,2,5,2,4,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +95288,106263,Male,Loyal Customer,34,Business travel,Business,1500,4,4,4,4,3,4,4,2,2,2,2,4,2,5,0,5.0,satisfied +95289,86861,Female,Loyal Customer,56,Personal Travel,Eco,484,4,4,4,4,2,3,3,1,1,4,1,3,1,4,15,10.0,neutral or dissatisfied +95290,8172,Male,Loyal Customer,44,Business travel,Business,3790,3,5,5,5,2,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +95291,100013,Male,Loyal Customer,62,Business travel,Business,220,2,5,5,5,4,4,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +95292,63322,Male,Loyal Customer,75,Business travel,Business,3122,3,1,5,1,2,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +95293,22998,Male,Loyal Customer,27,Personal Travel,Eco,528,2,3,3,3,3,3,3,3,4,1,4,2,4,3,10,9.0,neutral or dissatisfied +95294,119735,Male,Loyal Customer,27,Personal Travel,Eco,1430,1,4,1,4,5,1,5,5,5,4,3,5,5,5,0,0.0,neutral or dissatisfied +95295,39068,Female,Loyal Customer,35,Business travel,Business,1908,2,2,2,2,4,4,3,2,2,2,2,3,2,4,24,34.0,neutral or dissatisfied +95296,58006,Female,disloyal Customer,35,Business travel,Business,1162,4,4,4,3,3,4,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +95297,6291,Female,Loyal Customer,63,Personal Travel,Eco,585,4,4,4,4,2,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +95298,128006,Female,Loyal Customer,59,Personal Travel,Eco,1488,3,1,4,4,1,4,3,5,5,4,5,2,5,4,0,0.0,neutral or dissatisfied +95299,69849,Male,Loyal Customer,22,Personal Travel,Eco,1055,3,4,3,3,4,3,4,4,3,5,5,5,4,4,17,1.0,neutral or dissatisfied +95300,120894,Male,Loyal Customer,60,Business travel,Business,1665,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +95301,83188,Female,Loyal Customer,16,Personal Travel,Business,1123,3,5,3,5,3,3,3,3,3,5,5,3,5,3,0,8.0,neutral or dissatisfied +95302,111240,Male,Loyal Customer,41,Personal Travel,Eco Plus,1506,1,5,1,3,5,1,1,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +95303,114049,Male,Loyal Customer,40,Business travel,Business,3032,2,2,2,2,3,5,4,4,4,4,4,3,4,3,53,36.0,satisfied +95304,22177,Female,Loyal Customer,40,Business travel,Eco,633,4,5,5,5,4,4,4,4,1,5,4,2,4,4,18,16.0,neutral or dissatisfied +95305,21294,Female,Loyal Customer,39,Business travel,Business,620,3,4,4,4,1,3,3,3,3,3,3,4,3,2,35,6.0,neutral or dissatisfied +95306,78167,Female,Loyal Customer,41,Business travel,Business,3945,4,4,3,4,4,4,5,5,5,5,5,5,5,3,0,23.0,satisfied +95307,69024,Female,Loyal Customer,25,Business travel,Business,1389,5,5,5,5,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +95308,98362,Male,Loyal Customer,76,Business travel,Eco,789,2,4,4,4,2,2,2,2,3,4,4,1,4,2,120,112.0,neutral or dissatisfied +95309,17697,Male,Loyal Customer,33,Business travel,Eco,854,4,1,1,1,5,5,5,5,1,3,4,1,1,5,82,68.0,satisfied +95310,29373,Male,Loyal Customer,43,Business travel,Eco,2404,5,5,5,5,4,5,4,4,2,2,5,3,4,4,0,0.0,satisfied +95311,1055,Male,Loyal Customer,59,Personal Travel,Eco,247,0,3,0,3,3,0,3,3,3,5,2,4,2,3,0,0.0,satisfied +95312,111549,Male,disloyal Customer,24,Business travel,Eco,883,3,3,3,1,2,3,2,2,3,4,5,5,5,2,61,44.0,neutral or dissatisfied +95313,14681,Female,Loyal Customer,44,Business travel,Business,2876,5,5,3,5,4,4,4,4,4,5,5,4,5,4,134,117.0,satisfied +95314,22064,Male,Loyal Customer,51,Business travel,Eco,304,3,4,4,4,3,3,3,3,2,3,3,1,3,3,25,11.0,neutral or dissatisfied +95315,102952,Male,Loyal Customer,67,Personal Travel,Eco,719,2,5,2,2,2,2,2,2,5,4,5,3,4,2,2,0.0,neutral or dissatisfied +95316,62663,Male,Loyal Customer,59,Business travel,Business,1744,1,1,1,1,4,5,5,5,5,5,5,4,5,4,8,0.0,satisfied +95317,29421,Female,Loyal Customer,34,Business travel,Eco Plus,2409,3,1,1,1,3,3,3,4,5,4,3,3,3,3,0,8.0,neutral or dissatisfied +95318,1304,Female,Loyal Customer,60,Personal Travel,Eco,164,3,4,3,4,5,5,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +95319,27679,Female,Loyal Customer,57,Business travel,Eco,1107,4,2,2,2,4,2,3,4,4,4,4,5,4,5,0,0.0,satisfied +95320,115218,Male,Loyal Customer,36,Business travel,Business,342,2,2,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +95321,36295,Male,Loyal Customer,62,Business travel,Business,1616,1,1,1,1,5,3,5,5,5,5,5,4,5,5,13,11.0,satisfied +95322,78451,Female,disloyal Customer,25,Business travel,Business,666,4,0,4,3,4,5,5,3,2,5,5,5,3,5,153,137.0,satisfied +95323,117524,Male,Loyal Customer,53,Business travel,Business,1640,2,4,3,3,2,3,3,2,2,2,2,2,2,2,4,0.0,neutral or dissatisfied +95324,84391,Female,Loyal Customer,65,Business travel,Eco,606,2,2,2,2,3,3,4,3,3,2,3,2,3,4,18,57.0,neutral or dissatisfied +95325,75540,Female,Loyal Customer,36,Business travel,Business,337,0,1,1,3,2,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +95326,34944,Male,Loyal Customer,40,Personal Travel,Eco,395,3,5,3,5,1,3,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +95327,122082,Female,Loyal Customer,54,Personal Travel,Eco,130,4,2,4,3,3,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +95328,21501,Female,Loyal Customer,36,Personal Travel,Eco,164,4,5,4,4,1,4,4,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +95329,59848,Female,disloyal Customer,25,Business travel,Business,1068,5,0,5,1,3,5,3,3,4,5,4,4,4,3,0,0.0,satisfied +95330,74067,Female,Loyal Customer,31,Business travel,Business,641,3,2,2,2,3,3,3,3,1,5,3,2,4,3,82,114.0,neutral or dissatisfied +95331,66633,Male,Loyal Customer,52,Business travel,Business,802,1,1,1,1,3,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +95332,112490,Male,Loyal Customer,34,Personal Travel,Eco,909,3,5,3,3,2,3,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +95333,94657,Male,Loyal Customer,51,Business travel,Business,293,5,5,5,5,5,4,5,5,5,5,5,3,5,3,25,36.0,satisfied +95334,16937,Male,Loyal Customer,28,Business travel,Business,820,3,3,3,3,4,4,4,4,3,3,1,3,1,4,0,2.0,satisfied +95335,98515,Male,Loyal Customer,49,Business travel,Eco,402,2,2,2,2,2,2,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +95336,118675,Male,Loyal Customer,42,Business travel,Business,2026,0,0,0,4,3,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +95337,53405,Female,Loyal Customer,44,Personal Travel,Business,2288,4,5,5,4,5,1,1,5,1,3,4,1,1,1,3,73.0,neutral or dissatisfied +95338,100089,Female,Loyal Customer,32,Business travel,Business,717,1,1,1,1,5,5,5,5,3,2,5,5,5,5,37,39.0,satisfied +95339,25826,Male,Loyal Customer,38,Business travel,Business,692,3,3,3,3,1,4,2,4,4,4,4,5,4,1,18,41.0,satisfied +95340,123816,Male,Loyal Customer,31,Business travel,Business,544,5,5,5,5,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +95341,2077,Female,disloyal Customer,34,Business travel,Eco,812,4,4,4,4,1,4,1,1,1,4,4,4,4,1,7,11.0,neutral or dissatisfied +95342,92,Female,Loyal Customer,50,Business travel,Business,2035,5,5,5,5,4,5,4,5,5,5,4,3,5,5,0,34.0,satisfied +95343,5185,Male,disloyal Customer,21,Business travel,Eco,383,0,5,0,5,3,0,3,3,3,2,5,4,4,3,0,0.0,satisfied +95344,92642,Female,Loyal Customer,65,Business travel,Business,3891,3,3,5,3,4,3,3,5,5,5,5,1,5,4,0,0.0,satisfied +95345,26629,Female,Loyal Customer,34,Business travel,Business,3916,3,4,2,2,2,3,3,3,3,3,3,2,3,3,1,21.0,neutral or dissatisfied +95346,111079,Male,Loyal Customer,45,Personal Travel,Eco,197,2,5,2,2,4,2,4,4,4,3,2,2,4,4,0,11.0,neutral or dissatisfied +95347,123111,Female,disloyal Customer,23,Business travel,Eco,507,1,0,1,3,3,1,3,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +95348,3998,Male,Loyal Customer,37,Business travel,Business,3385,4,4,4,4,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +95349,95984,Female,disloyal Customer,29,Business travel,Business,1235,4,4,4,5,5,4,5,5,5,3,4,5,5,5,0,2.0,neutral or dissatisfied +95350,108177,Female,Loyal Customer,43,Personal Travel,Eco,990,3,1,3,4,3,2,3,3,2,4,4,3,3,3,294,316.0,neutral or dissatisfied +95351,114283,Male,Loyal Customer,23,Personal Travel,Eco,862,2,3,2,3,1,2,1,1,2,2,4,2,4,1,30,32.0,neutral or dissatisfied +95352,16125,Female,Loyal Customer,10,Personal Travel,Eco,799,0,5,0,2,2,0,2,2,5,2,2,2,5,2,14,0.0,satisfied +95353,4695,Male,Loyal Customer,31,Personal Travel,Eco,364,2,4,2,3,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +95354,54390,Male,Loyal Customer,49,Business travel,Eco,305,4,5,3,5,4,4,4,4,3,4,1,3,1,4,0,0.0,satisfied +95355,87281,Male,Loyal Customer,40,Business travel,Business,577,2,1,1,1,4,2,1,2,2,2,2,3,2,3,6,12.0,neutral or dissatisfied +95356,20851,Male,Loyal Customer,63,Personal Travel,Eco,515,4,4,3,3,1,3,1,1,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +95357,40921,Female,Loyal Customer,31,Personal Travel,Eco,590,2,5,2,2,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +95358,36762,Female,disloyal Customer,35,Business travel,Eco,2704,4,4,4,3,4,4,4,1,1,1,3,4,1,4,160,181.0,neutral or dissatisfied +95359,78604,Female,Loyal Customer,55,Business travel,Business,1426,3,3,3,3,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +95360,2212,Female,Loyal Customer,46,Business travel,Business,2115,3,1,1,1,5,4,4,3,3,3,3,4,3,4,27,27.0,neutral or dissatisfied +95361,64,Male,Loyal Customer,56,Business travel,Business,173,1,1,1,1,5,5,4,3,3,4,5,5,3,5,0,3.0,satisfied +95362,92800,Male,disloyal Customer,25,Business travel,Business,1587,4,0,4,4,4,3,3,4,2,4,5,3,3,3,152,165.0,satisfied +95363,36053,Female,Loyal Customer,53,Business travel,Business,399,4,4,4,4,5,3,2,4,4,4,4,4,4,3,5,10.0,neutral or dissatisfied +95364,65334,Female,Loyal Customer,24,Business travel,Business,631,1,1,1,1,4,4,4,4,5,3,4,5,4,4,0,6.0,satisfied +95365,20197,Male,Loyal Customer,10,Personal Travel,Eco,349,1,4,1,2,5,1,5,5,3,2,5,3,4,5,60,51.0,neutral or dissatisfied +95366,21891,Male,Loyal Customer,53,Business travel,Eco,551,5,4,4,4,4,5,4,4,1,1,1,1,5,4,65,78.0,satisfied +95367,119910,Male,Loyal Customer,60,Business travel,Business,3171,5,5,2,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +95368,118597,Male,disloyal Customer,28,Business travel,Eco,370,3,3,3,4,5,3,5,5,4,1,3,1,4,5,17,46.0,neutral or dissatisfied +95369,118548,Female,Loyal Customer,40,Business travel,Business,3187,3,3,3,3,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +95370,77475,Female,disloyal Customer,55,Business travel,Eco Plus,107,3,3,3,3,3,3,1,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +95371,62644,Male,Loyal Customer,64,Personal Travel,Eco,1846,3,5,3,3,1,3,1,1,5,4,5,3,5,1,0,11.0,neutral or dissatisfied +95372,114139,Male,disloyal Customer,25,Business travel,Business,846,1,4,1,3,1,1,1,1,5,5,4,5,4,1,5,0.0,neutral or dissatisfied +95373,83702,Male,Loyal Customer,13,Personal Travel,Eco,577,5,4,5,2,2,5,2,2,5,3,5,5,5,2,0,0.0,satisfied +95374,9584,Female,Loyal Customer,56,Business travel,Eco,296,4,3,3,3,1,5,5,4,4,4,4,5,4,4,114,116.0,satisfied +95375,83961,Male,Loyal Customer,59,Business travel,Business,2746,1,1,1,1,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +95376,108941,Female,Loyal Customer,48,Personal Travel,Eco,1066,3,4,3,3,5,4,4,2,2,3,4,2,2,2,13,4.0,neutral or dissatisfied +95377,3492,Male,Loyal Customer,46,Business travel,Business,3252,2,3,3,3,4,4,4,2,2,3,2,2,2,1,77,61.0,neutral or dissatisfied +95378,80350,Male,Loyal Customer,56,Personal Travel,Business,422,2,2,2,3,2,4,4,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +95379,34983,Female,Loyal Customer,33,Personal Travel,Eco,273,3,1,3,3,2,3,2,2,4,5,4,4,4,2,0,14.0,neutral or dissatisfied +95380,64461,Female,Loyal Customer,44,Business travel,Business,989,2,2,2,2,2,4,4,5,5,5,5,3,5,4,31,32.0,satisfied +95381,108363,Female,Loyal Customer,37,Business travel,Eco,290,3,4,4,4,3,3,3,3,1,5,4,1,4,3,45,38.0,neutral or dissatisfied +95382,41858,Female,Loyal Customer,47,Business travel,Business,3314,5,5,5,5,4,3,5,5,5,5,5,4,5,3,0,7.0,satisfied +95383,124176,Male,disloyal Customer,48,Business travel,Eco,289,3,1,3,4,1,3,1,1,2,4,3,4,4,1,5,19.0,neutral or dissatisfied +95384,14572,Male,disloyal Customer,35,Business travel,Eco,1021,4,4,4,3,3,4,3,3,2,2,1,3,4,3,0,0.0,neutral or dissatisfied +95385,85657,Male,disloyal Customer,23,Business travel,Business,903,5,0,5,4,2,5,1,2,3,2,4,4,4,2,47,47.0,satisfied +95386,111186,Female,Loyal Customer,22,Business travel,Business,1546,3,3,3,3,3,2,3,3,5,5,5,4,4,3,103,117.0,satisfied +95387,73352,Male,Loyal Customer,48,Business travel,Business,1005,3,3,3,3,3,4,4,5,5,5,5,5,5,4,6,4.0,satisfied +95388,35734,Female,Loyal Customer,40,Personal Travel,Eco Plus,2446,4,4,3,2,3,3,3,1,1,4,5,3,4,3,0,35.0,neutral or dissatisfied +95389,65127,Male,Loyal Customer,36,Personal Travel,Eco,247,2,1,0,2,2,0,2,2,4,2,3,1,3,2,0,0.0,neutral or dissatisfied +95390,107911,Male,Loyal Customer,43,Business travel,Business,461,4,4,4,4,5,5,4,4,4,4,4,1,4,5,0,0.0,satisfied +95391,47603,Male,Loyal Customer,49,Business travel,Business,1428,4,4,4,4,5,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +95392,65788,Female,Loyal Customer,49,Business travel,Business,1389,1,5,1,1,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +95393,25070,Female,Loyal Customer,29,Personal Travel,Eco,594,3,1,3,3,5,3,5,5,4,2,3,4,4,5,8,0.0,neutral or dissatisfied +95394,97627,Male,Loyal Customer,43,Personal Travel,Eco,764,1,3,1,2,2,1,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +95395,49437,Male,disloyal Customer,35,Business travel,Eco,109,3,3,3,3,1,3,4,1,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +95396,61988,Female,Loyal Customer,39,Business travel,Business,2586,4,4,5,4,5,3,5,5,5,5,5,3,5,5,0,1.0,satisfied +95397,43803,Female,Loyal Customer,57,Business travel,Business,2609,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +95398,45873,Female,Loyal Customer,27,Business travel,Business,3169,3,3,3,3,2,2,2,2,1,3,1,2,5,2,49,34.0,satisfied +95399,21451,Male,Loyal Customer,16,Business travel,Business,331,1,5,5,5,1,1,1,1,2,1,4,2,4,1,0,0.0,neutral or dissatisfied +95400,54653,Female,Loyal Customer,31,Business travel,Business,2920,2,2,2,2,5,5,5,5,3,4,3,1,5,5,19,20.0,satisfied +95401,20764,Female,Loyal Customer,54,Business travel,Business,3953,3,5,5,5,4,3,4,3,3,3,3,2,3,3,10,5.0,neutral or dissatisfied +95402,14230,Female,Loyal Customer,50,Business travel,Eco Plus,692,5,5,5,5,5,4,2,5,5,5,5,5,5,4,0,0.0,satisfied +95403,30109,Female,Loyal Customer,8,Personal Travel,Eco,503,2,5,2,3,3,2,3,3,5,3,4,3,4,3,3,10.0,neutral or dissatisfied +95404,63851,Female,Loyal Customer,55,Business travel,Business,1192,2,2,2,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +95405,58211,Female,Loyal Customer,31,Personal Travel,Eco,925,1,5,1,3,5,1,5,5,3,4,5,3,4,5,44,36.0,neutral or dissatisfied +95406,117952,Male,Loyal Customer,44,Business travel,Eco,365,3,1,1,1,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +95407,105966,Male,disloyal Customer,25,Business travel,Business,1404,0,0,0,3,1,0,1,1,5,2,5,4,4,1,0,0.0,satisfied +95408,45028,Male,disloyal Customer,20,Business travel,Eco,867,1,1,1,4,5,1,5,5,2,3,4,4,3,5,69,81.0,neutral or dissatisfied +95409,124124,Male,Loyal Customer,42,Business travel,Eco,529,4,1,1,1,4,4,4,4,3,3,2,2,2,4,0,4.0,neutral or dissatisfied +95410,31688,Female,Loyal Customer,54,Business travel,Eco,967,2,1,1,1,5,2,3,2,2,2,2,2,2,3,27,35.0,neutral or dissatisfied +95411,101776,Male,Loyal Customer,70,Personal Travel,Business,1521,2,4,2,2,2,5,5,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +95412,127750,Female,Loyal Customer,60,Personal Travel,Eco,255,0,5,0,2,3,1,2,2,2,0,2,2,2,3,0,7.0,satisfied +95413,76708,Male,Loyal Customer,58,Personal Travel,Eco,534,3,4,3,3,2,3,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +95414,47814,Female,disloyal Customer,28,Business travel,Eco,726,1,1,1,4,5,1,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +95415,75170,Male,Loyal Customer,58,Business travel,Business,1744,3,3,3,3,3,4,5,5,5,5,5,4,5,5,7,0.0,satisfied +95416,43886,Female,Loyal Customer,63,Business travel,Business,199,1,2,2,2,4,3,4,1,1,1,1,2,1,3,37,20.0,neutral or dissatisfied +95417,2616,Male,Loyal Customer,19,Personal Travel,Eco,227,1,5,1,3,5,1,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +95418,79742,Female,Loyal Customer,52,Business travel,Business,3397,1,1,5,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +95419,43210,Male,disloyal Customer,28,Business travel,Business,423,3,3,3,1,4,3,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +95420,20021,Male,disloyal Customer,30,Business travel,Business,723,2,2,2,2,3,2,3,3,3,1,3,2,3,3,19,20.0,neutral or dissatisfied +95421,44587,Male,Loyal Customer,67,Personal Travel,Eco,157,1,4,1,1,4,1,4,4,5,3,4,3,5,4,0,23.0,neutral or dissatisfied +95422,38005,Female,Loyal Customer,49,Business travel,Business,1211,5,5,5,5,3,4,4,5,3,4,5,4,2,4,138,142.0,satisfied +95423,47656,Male,Loyal Customer,14,Business travel,Business,3351,3,2,2,2,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +95424,39163,Male,Loyal Customer,59,Business travel,Business,237,2,3,3,3,5,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +95425,77156,Female,Loyal Customer,23,Business travel,Business,1428,2,2,2,2,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +95426,96839,Female,disloyal Customer,28,Business travel,Eco,1041,1,1,1,4,5,1,3,5,1,4,3,2,4,5,71,62.0,neutral or dissatisfied +95427,60736,Male,Loyal Customer,49,Business travel,Business,1605,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +95428,106899,Male,Loyal Customer,48,Personal Travel,Eco,577,4,5,4,2,4,4,4,4,3,2,4,5,5,4,8,1.0,neutral or dissatisfied +95429,91605,Male,Loyal Customer,38,Business travel,Business,1312,3,5,3,3,2,4,4,5,5,5,5,4,5,5,0,65.0,satisfied +95430,33187,Female,Loyal Customer,42,Business travel,Eco Plus,101,4,5,5,5,5,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +95431,85315,Male,Loyal Customer,63,Personal Travel,Eco,874,2,4,2,3,3,2,3,3,4,5,4,3,3,3,0,2.0,neutral or dissatisfied +95432,91985,Male,Loyal Customer,45,Business travel,Business,236,0,1,1,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +95433,83373,Male,Loyal Customer,70,Personal Travel,Eco,1124,2,4,2,1,4,2,4,4,5,2,3,4,5,4,5,11.0,neutral or dissatisfied +95434,76592,Female,Loyal Customer,28,Business travel,Eco,534,3,5,5,5,3,3,3,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +95435,3050,Male,Loyal Customer,14,Personal Travel,Eco,489,2,0,2,3,5,2,5,5,5,3,4,3,4,5,76,70.0,neutral or dissatisfied +95436,67591,Female,disloyal Customer,45,Business travel,Business,1464,2,3,3,2,3,2,1,3,4,2,4,4,4,3,49,41.0,neutral or dissatisfied +95437,51733,Female,Loyal Customer,15,Personal Travel,Eco,370,3,2,3,3,4,3,4,4,4,3,1,3,3,4,0,0.0,neutral or dissatisfied +95438,14374,Female,Loyal Customer,50,Personal Travel,Eco,1215,4,0,4,3,3,4,1,5,5,4,1,4,5,4,0,0.0,neutral or dissatisfied +95439,5712,Female,Loyal Customer,33,Personal Travel,Eco,147,1,4,1,5,2,1,2,2,1,5,3,5,3,2,0,5.0,neutral or dissatisfied +95440,88444,Female,Loyal Customer,55,Business travel,Eco,444,4,5,5,5,4,4,4,4,4,4,4,1,4,1,5,29.0,neutral or dissatisfied +95441,30278,Male,Loyal Customer,41,Personal Travel,Eco,1024,1,4,1,2,5,1,5,5,3,4,5,5,5,5,4,0.0,neutral or dissatisfied +95442,74439,Male,Loyal Customer,34,Business travel,Business,1242,5,5,5,5,4,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +95443,110279,Female,Loyal Customer,12,Personal Travel,Business,925,2,2,2,4,3,2,3,3,3,5,3,1,4,3,0,0.0,neutral or dissatisfied +95444,36090,Male,Loyal Customer,34,Personal Travel,Eco,399,2,1,2,3,2,2,2,2,2,5,3,1,4,2,2,0.0,neutral or dissatisfied +95445,97153,Female,Loyal Customer,54,Business travel,Business,1076,2,2,2,2,4,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +95446,91787,Female,Loyal Customer,14,Personal Travel,Eco,532,3,4,3,1,1,3,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +95447,3744,Male,Loyal Customer,24,Personal Travel,Eco,544,3,3,3,4,3,3,2,3,4,5,1,1,2,3,0,5.0,neutral or dissatisfied +95448,46602,Female,Loyal Customer,75,Business travel,Eco,125,3,1,1,1,1,2,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +95449,45290,Male,Loyal Customer,56,Business travel,Eco,150,4,4,4,4,5,4,5,5,2,2,1,5,5,5,0,0.0,satisfied +95450,46252,Female,Loyal Customer,62,Business travel,Eco,194,3,3,3,3,3,2,1,3,3,3,3,4,3,1,3,7.0,neutral or dissatisfied +95451,29072,Female,Loyal Customer,10,Personal Travel,Eco,671,3,5,3,4,4,3,2,4,2,1,4,2,2,4,0,0.0,neutral or dissatisfied +95452,85379,Male,Loyal Customer,52,Business travel,Business,152,4,3,3,3,2,3,4,3,3,3,4,4,3,2,27,31.0,neutral or dissatisfied +95453,45109,Male,Loyal Customer,36,Business travel,Business,157,3,2,3,3,4,2,2,4,4,4,5,1,4,2,107,97.0,satisfied +95454,121574,Male,Loyal Customer,60,Business travel,Business,2790,5,5,5,5,5,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +95455,3475,Female,Loyal Customer,38,Business travel,Business,2071,1,3,3,3,3,4,4,1,1,2,1,1,1,2,18,0.0,neutral or dissatisfied +95456,81872,Male,Loyal Customer,42,Business travel,Business,1516,2,2,2,2,4,4,4,2,2,2,2,4,2,3,8,0.0,satisfied +95457,122517,Male,Loyal Customer,52,Personal Travel,Eco,930,2,5,2,5,3,2,3,3,5,5,4,5,4,3,3,18.0,neutral or dissatisfied +95458,88554,Female,Loyal Customer,26,Personal Travel,Eco,581,3,5,3,5,3,3,3,3,5,3,4,3,5,3,7,4.0,neutral or dissatisfied +95459,10272,Male,Loyal Customer,53,Personal Travel,Business,224,1,4,1,4,3,4,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +95460,92793,Male,Loyal Customer,59,Business travel,Business,1587,1,1,1,1,2,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +95461,49338,Female,Loyal Customer,46,Business travel,Eco,373,5,3,4,4,5,5,5,1,2,1,4,5,5,5,226,217.0,satisfied +95462,100067,Male,Loyal Customer,22,Personal Travel,Eco,289,3,5,3,3,5,3,5,5,3,5,4,3,4,5,0,6.0,neutral or dissatisfied +95463,101757,Female,Loyal Customer,67,Personal Travel,Eco,1590,3,5,2,1,4,5,5,3,3,2,1,3,3,4,0,12.0,neutral or dissatisfied +95464,91666,Male,Loyal Customer,40,Business travel,Eco Plus,799,5,3,3,3,5,5,5,5,1,4,1,3,4,5,0,0.0,satisfied +95465,95475,Male,disloyal Customer,20,Business travel,Eco,248,4,0,4,5,2,4,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +95466,47359,Male,disloyal Customer,51,Business travel,Eco,599,2,3,2,3,1,2,1,1,2,2,4,4,4,1,0,0.0,neutral or dissatisfied +95467,123489,Female,disloyal Customer,25,Business travel,Eco,720,3,3,3,4,3,4,4,3,2,3,3,4,2,4,0,6.0,neutral or dissatisfied +95468,69354,Male,disloyal Customer,14,Business travel,Eco,1089,3,3,3,1,5,3,1,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +95469,48431,Male,Loyal Customer,27,Business travel,Business,2039,1,1,1,1,4,4,4,4,5,2,1,4,1,4,92,87.0,satisfied +95470,107832,Female,Loyal Customer,19,Personal Travel,Eco,349,3,4,3,1,1,3,1,1,4,4,4,3,4,1,10,16.0,neutral or dissatisfied +95471,88429,Female,Loyal Customer,46,Business travel,Eco,594,1,3,3,3,2,3,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +95472,128550,Female,disloyal Customer,22,Business travel,Business,646,5,4,5,4,5,5,5,5,5,2,5,3,5,5,6,20.0,satisfied +95473,90374,Female,Loyal Customer,41,Business travel,Business,406,3,1,1,1,2,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +95474,18484,Female,Loyal Customer,34,Business travel,Business,2808,3,3,4,3,1,5,1,4,4,4,4,5,4,4,0,0.0,satisfied +95475,28299,Male,Loyal Customer,23,Business travel,Eco,867,4,5,5,5,4,5,4,4,5,5,2,3,3,4,0,3.0,satisfied +95476,91259,Male,Loyal Customer,63,Personal Travel,Eco,515,2,5,2,2,1,2,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +95477,61778,Male,Loyal Customer,24,Personal Travel,Eco,1608,3,4,3,1,2,3,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +95478,76703,Male,Loyal Customer,46,Personal Travel,Eco,481,3,4,2,3,4,2,4,4,1,3,4,2,3,4,0,0.0,neutral or dissatisfied +95479,18101,Female,Loyal Customer,27,Business travel,Business,610,1,1,1,1,5,4,5,5,3,3,3,2,2,5,0,0.0,satisfied +95480,38191,Female,Loyal Customer,64,Personal Travel,Eco,1249,4,1,4,2,4,2,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +95481,85677,Male,Loyal Customer,32,Business travel,Eco Plus,903,3,1,5,1,3,3,3,3,2,1,4,1,4,3,57,40.0,neutral or dissatisfied +95482,15215,Male,Loyal Customer,46,Business travel,Business,2723,4,4,4,4,2,3,2,4,4,4,4,4,4,5,0,11.0,satisfied +95483,127029,Male,disloyal Customer,24,Business travel,Eco,338,3,4,3,3,2,3,2,2,5,5,5,5,5,2,39,26.0,neutral or dissatisfied +95484,43098,Male,Loyal Customer,20,Personal Travel,Eco,173,5,5,5,5,3,5,2,3,5,2,4,3,4,3,0,0.0,satisfied +95485,122619,Male,Loyal Customer,18,Personal Travel,Eco,728,3,5,3,3,4,3,4,4,5,5,5,5,3,4,0,0.0,neutral or dissatisfied +95486,53174,Male,Loyal Customer,39,Business travel,Business,589,4,4,4,4,4,3,3,4,4,4,4,2,4,1,0,2.0,satisfied +95487,7337,Female,Loyal Customer,26,Business travel,Business,606,2,2,2,2,4,5,4,4,4,2,5,4,4,4,10,9.0,satisfied +95488,2192,Female,Loyal Customer,29,Personal Travel,Eco,685,2,4,2,4,3,2,3,3,5,2,5,4,4,3,42,34.0,neutral or dissatisfied +95489,89267,Male,Loyal Customer,36,Business travel,Business,2158,1,1,1,1,2,4,4,4,4,4,4,5,4,3,4,0.0,satisfied +95490,120757,Male,Loyal Customer,42,Business travel,Business,678,5,5,5,5,5,5,5,4,5,5,5,5,3,5,74,138.0,satisfied +95491,34587,Male,Loyal Customer,39,Business travel,Business,1598,3,5,5,5,5,2,3,3,3,4,3,2,3,3,3,0.0,neutral or dissatisfied +95492,84705,Female,Loyal Customer,54,Business travel,Business,357,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +95493,52142,Male,Loyal Customer,46,Business travel,Business,2805,2,1,1,1,5,4,4,2,2,2,2,4,2,3,96,111.0,neutral or dissatisfied +95494,118990,Male,Loyal Customer,37,Business travel,Business,479,1,1,1,1,4,4,5,4,4,4,4,4,4,4,10,1.0,satisfied +95495,89382,Female,Loyal Customer,43,Business travel,Business,3596,0,4,0,1,3,5,5,5,5,5,5,5,5,5,4,10.0,satisfied +95496,128051,Male,Loyal Customer,42,Personal Travel,Eco,735,4,2,4,3,2,4,2,2,4,3,4,4,3,2,3,0.0,neutral or dissatisfied +95497,124688,Male,disloyal Customer,21,Business travel,Eco,399,5,0,5,2,4,5,4,4,5,4,4,3,5,4,13,14.0,satisfied +95498,112931,Male,Loyal Customer,64,Personal Travel,Eco,1390,4,4,4,5,3,4,3,3,4,5,4,5,5,3,28,28.0,neutral or dissatisfied +95499,124891,Female,Loyal Customer,54,Business travel,Business,728,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +95500,127660,Male,disloyal Customer,23,Business travel,Eco,850,2,2,2,1,5,2,5,5,4,5,5,3,4,5,0,19.0,neutral or dissatisfied +95501,55472,Female,Loyal Customer,52,Personal Travel,Eco,1825,4,5,4,3,3,5,4,2,2,4,2,3,2,5,0,0.0,satisfied +95502,12822,Female,Loyal Customer,28,Business travel,Business,3179,3,3,3,3,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +95503,48752,Female,Loyal Customer,58,Business travel,Business,363,4,1,1,1,2,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +95504,36637,Male,Loyal Customer,51,Personal Travel,Eco,1121,3,4,3,1,2,3,2,2,4,5,3,5,5,2,52,69.0,neutral or dissatisfied +95505,79275,Male,Loyal Customer,34,Personal Travel,Eco,2454,4,2,4,3,4,1,1,4,5,3,3,1,1,1,0,5.0,neutral or dissatisfied +95506,34185,Female,disloyal Customer,57,Business travel,Eco,729,2,2,2,4,1,2,1,1,4,2,3,1,4,1,25,17.0,neutral or dissatisfied +95507,62307,Male,Loyal Customer,53,Business travel,Eco,414,1,4,4,4,1,1,1,1,1,1,3,1,4,1,12,2.0,neutral or dissatisfied +95508,94486,Female,Loyal Customer,56,Business travel,Business,2815,3,3,1,3,2,5,4,4,4,4,4,4,4,4,0,1.0,satisfied +95509,12220,Male,Loyal Customer,23,Personal Travel,Business,383,2,4,2,2,2,2,2,2,2,1,2,2,2,2,1,15.0,neutral or dissatisfied +95510,103809,Female,disloyal Customer,9,Business travel,Eco,1048,3,3,3,4,5,3,5,5,2,4,4,4,4,5,38,28.0,neutral or dissatisfied +95511,52480,Male,Loyal Customer,33,Personal Travel,Eco Plus,751,4,4,5,3,2,5,2,2,5,4,2,5,4,2,48,51.0,neutral or dissatisfied +95512,127473,Female,disloyal Customer,43,Business travel,Eco,1212,4,4,4,3,2,4,2,2,4,5,2,2,4,2,9,1.0,neutral or dissatisfied +95513,99799,Male,Loyal Customer,37,Business travel,Business,632,5,5,5,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +95514,69089,Male,Loyal Customer,35,Personal Travel,Eco,1389,3,1,2,4,5,2,5,5,2,2,4,2,4,5,0,0.0,neutral or dissatisfied +95515,121689,Male,Loyal Customer,61,Personal Travel,Eco,328,2,0,2,3,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +95516,5169,Female,Loyal Customer,40,Business travel,Business,1651,3,1,1,1,3,2,2,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +95517,77949,Male,Loyal Customer,55,Business travel,Business,3546,0,0,0,3,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +95518,81161,Male,Loyal Customer,51,Personal Travel,Business,196,2,5,2,3,2,5,5,3,3,2,3,5,3,4,20,22.0,neutral or dissatisfied +95519,98210,Female,Loyal Customer,14,Personal Travel,Eco Plus,327,4,0,4,4,2,4,2,2,5,5,5,3,5,2,24,23.0,neutral or dissatisfied +95520,54249,Male,disloyal Customer,24,Business travel,Eco,1222,3,3,3,4,4,3,4,4,4,3,4,4,4,4,3,0.0,neutral or dissatisfied +95521,47135,Female,Loyal Customer,55,Business travel,Eco,954,4,4,4,4,2,1,4,4,4,4,4,3,4,2,30,19.0,satisfied +95522,19186,Male,Loyal Customer,20,Business travel,Business,542,4,4,2,4,5,5,5,5,3,3,3,3,1,5,0,0.0,satisfied +95523,43257,Male,disloyal Customer,28,Business travel,Eco,531,3,5,3,4,3,3,3,3,2,2,3,3,2,3,0,0.0,neutral or dissatisfied +95524,61799,Female,Loyal Customer,26,Personal Travel,Eco,1346,3,5,3,2,2,3,4,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +95525,65563,Male,Loyal Customer,48,Business travel,Business,175,4,5,4,4,4,4,4,5,5,5,5,3,5,3,11,6.0,satisfied +95526,69151,Male,Loyal Customer,29,Business travel,Eco Plus,2248,2,5,5,5,2,2,2,3,3,2,3,2,1,2,12,25.0,neutral or dissatisfied +95527,76514,Male,Loyal Customer,55,Business travel,Business,3381,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,6.0,satisfied +95528,106567,Female,Loyal Customer,45,Personal Travel,Eco,1024,4,3,4,4,3,2,2,3,3,4,1,3,3,4,0,0.0,satisfied +95529,93109,Female,Loyal Customer,32,Business travel,Eco Plus,641,3,1,1,1,3,3,3,3,4,2,3,3,4,3,4,10.0,neutral or dissatisfied +95530,74511,Female,Loyal Customer,44,Business travel,Business,1235,1,1,1,1,3,4,4,4,4,4,4,5,4,4,8,0.0,satisfied +95531,25585,Female,disloyal Customer,27,Business travel,Eco,874,4,4,4,4,2,4,1,2,1,4,4,3,1,2,0,4.0,neutral or dissatisfied +95532,93256,Male,Loyal Customer,47,Personal Travel,Eco,1180,3,5,3,5,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +95533,30879,Male,Loyal Customer,25,Personal Travel,Eco,1607,4,5,4,5,5,4,1,5,3,5,5,5,5,5,41,20.0,neutral or dissatisfied +95534,92835,Female,Loyal Customer,41,Personal Travel,Eco,1587,3,4,3,3,4,3,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +95535,79110,Female,Loyal Customer,24,Personal Travel,Eco,226,2,4,0,2,1,0,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +95536,50053,Female,Loyal Customer,38,Business travel,Business,1888,2,2,3,2,2,4,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +95537,29136,Female,Loyal Customer,55,Personal Travel,Eco,679,3,5,3,5,1,4,2,5,5,3,5,2,5,3,46,44.0,neutral or dissatisfied +95538,82635,Male,Loyal Customer,32,Personal Travel,Eco,528,3,4,3,4,1,3,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +95539,14097,Male,Loyal Customer,31,Personal Travel,Eco,399,3,5,3,2,2,3,2,2,4,2,4,4,5,2,20,0.0,neutral or dissatisfied +95540,54472,Female,Loyal Customer,46,Business travel,Eco,925,5,4,4,4,2,2,3,5,5,5,5,3,5,5,31,34.0,satisfied +95541,85644,Female,Loyal Customer,45,Business travel,Business,1833,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +95542,77199,Female,Loyal Customer,77,Business travel,Eco Plus,290,2,5,5,5,3,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +95543,124706,Male,Loyal Customer,66,Personal Travel,Eco,399,1,4,4,2,3,4,3,3,4,5,4,5,4,3,0,6.0,neutral or dissatisfied +95544,38456,Male,disloyal Customer,23,Business travel,Eco,1226,1,1,1,3,4,1,4,4,2,5,4,3,4,4,0,0.0,neutral or dissatisfied +95545,57025,Male,Loyal Customer,43,Business travel,Business,2454,4,4,4,4,4,4,4,3,3,4,5,4,5,4,0,18.0,satisfied +95546,92649,Female,Loyal Customer,17,Personal Travel,Eco,453,3,5,3,2,3,3,3,3,3,5,4,4,2,3,0,0.0,neutral or dissatisfied +95547,20871,Female,Loyal Customer,53,Personal Travel,Eco,534,2,4,5,1,3,4,5,2,2,5,2,3,2,3,32,20.0,neutral or dissatisfied +95548,70401,Female,disloyal Customer,68,Business travel,Eco,1162,1,1,1,2,4,1,4,4,2,2,2,1,4,4,0,0.0,neutral or dissatisfied +95549,52217,Male,Loyal Customer,43,Business travel,Eco,425,5,2,2,2,5,5,5,5,2,3,3,3,5,5,0,0.0,satisfied +95550,77122,Male,Loyal Customer,32,Personal Travel,Eco,1481,4,5,4,3,5,4,5,5,4,4,3,3,5,5,0,0.0,satisfied +95551,2061,Male,disloyal Customer,70,Business travel,Business,785,1,1,1,2,1,1,1,1,4,1,2,2,3,1,0,0.0,neutral or dissatisfied +95552,43451,Male,Loyal Customer,27,Business travel,Business,3797,5,2,5,5,3,4,3,3,1,3,3,3,3,3,0,0.0,satisfied +95553,61922,Female,Loyal Customer,22,Personal Travel,Eco,550,3,3,3,4,4,3,4,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +95554,67519,Female,Loyal Customer,56,Business travel,Business,2701,5,5,5,5,4,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +95555,110033,Male,disloyal Customer,49,Business travel,Business,1984,3,3,3,1,5,3,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +95556,7324,Male,Loyal Customer,13,Personal Travel,Eco Plus,135,3,0,3,1,1,3,1,1,3,4,5,3,5,1,42,125.0,neutral or dissatisfied +95557,49204,Female,Loyal Customer,46,Business travel,Eco,262,2,2,2,2,3,2,3,2,2,2,2,2,2,4,0,6.0,satisfied +95558,29482,Male,Loyal Customer,37,Business travel,Business,1821,5,5,5,5,3,4,1,4,4,4,4,1,4,5,5,11.0,satisfied +95559,7729,Male,Loyal Customer,35,Personal Travel,Eco,806,2,4,3,4,2,3,2,2,2,2,3,5,1,2,0,0.0,neutral or dissatisfied +95560,109235,Male,Loyal Customer,42,Personal Travel,Eco,793,2,4,2,3,4,2,4,4,5,3,4,3,4,4,8,0.0,neutral or dissatisfied +95561,40871,Male,Loyal Customer,22,Personal Travel,Eco,590,2,1,2,3,3,2,3,3,4,5,3,2,4,3,0,0.0,neutral or dissatisfied +95562,22398,Male,disloyal Customer,32,Business travel,Eco,208,3,4,3,3,2,3,2,2,2,2,3,4,4,2,116,,neutral or dissatisfied +95563,4167,Female,Loyal Customer,52,Personal Travel,Eco,431,3,5,3,5,4,4,5,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +95564,45357,Female,Loyal Customer,16,Personal Travel,Eco,150,2,5,2,3,5,2,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +95565,61679,Male,Loyal Customer,72,Business travel,Business,2721,2,2,2,2,5,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +95566,27665,Male,disloyal Customer,31,Business travel,Business,1107,4,4,4,3,4,4,4,4,2,5,2,4,3,4,57,42.0,neutral or dissatisfied +95567,100172,Male,Loyal Customer,32,Personal Travel,Eco,725,1,3,0,2,5,0,1,5,1,4,3,4,2,5,0,6.0,neutral or dissatisfied +95568,96268,Male,Loyal Customer,8,Personal Travel,Eco,546,2,2,2,3,2,2,2,2,1,2,2,1,2,2,0,0.0,neutral or dissatisfied +95569,7841,Male,disloyal Customer,54,Business travel,Business,1005,4,4,4,5,5,4,5,5,3,5,4,4,4,5,0,0.0,satisfied +95570,124009,Male,Loyal Customer,55,Business travel,Business,184,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +95571,80394,Female,Loyal Customer,53,Personal Travel,Eco,422,3,5,3,2,3,4,2,5,5,3,5,2,5,5,0,0.0,neutral or dissatisfied +95572,34729,Male,Loyal Customer,33,Business travel,Eco,301,4,4,4,4,5,5,5,5,4,1,5,3,5,5,3,0.0,satisfied +95573,73863,Male,Loyal Customer,41,Business travel,Business,1810,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +95574,128580,Female,Loyal Customer,22,Business travel,Business,2552,5,5,5,5,1,2,1,1,5,5,5,3,4,1,22,2.0,satisfied +95575,51826,Female,Loyal Customer,71,Business travel,Eco Plus,355,4,1,1,1,1,5,1,4,4,4,4,2,4,4,0,0.0,satisfied +95576,81928,Female,Loyal Customer,29,Personal Travel,Business,1535,3,4,3,3,3,3,3,3,3,2,4,4,4,3,12,0.0,neutral or dissatisfied +95577,4020,Female,Loyal Customer,46,Business travel,Business,483,3,3,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +95578,76917,Male,Loyal Customer,17,Personal Travel,Eco Plus,630,3,4,3,4,5,3,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +95579,125652,Male,disloyal Customer,32,Business travel,Business,759,3,3,3,2,5,3,5,5,5,2,5,4,4,5,15,6.0,neutral or dissatisfied +95580,39911,Male,Loyal Customer,63,Personal Travel,Eco Plus,272,3,4,3,2,3,3,1,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +95581,34429,Male,Loyal Customer,41,Business travel,Business,1831,2,2,2,2,4,2,5,4,4,4,4,1,4,1,20,15.0,satisfied +95582,1128,Female,Loyal Customer,7,Personal Travel,Eco,158,4,4,4,1,1,4,1,1,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +95583,110648,Female,Loyal Customer,45,Business travel,Business,837,1,1,1,1,2,5,5,4,4,4,4,5,4,4,6,2.0,satisfied +95584,6003,Female,Loyal Customer,46,Business travel,Business,3017,1,1,3,1,3,4,4,4,4,4,4,5,4,3,12,3.0,satisfied +95585,38465,Male,Loyal Customer,43,Business travel,Business,3112,5,5,5,5,5,4,5,5,5,5,5,3,5,3,76,68.0,satisfied +95586,1989,Female,Loyal Customer,39,Personal Travel,Eco,383,3,4,3,3,4,3,4,4,4,5,5,5,2,4,9,1.0,neutral or dissatisfied +95587,114514,Male,Loyal Customer,39,Business travel,Business,1898,0,0,0,1,4,5,4,2,2,5,5,3,2,3,0,0.0,satisfied +95588,63102,Male,Loyal Customer,45,Business travel,Business,846,3,3,3,3,5,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +95589,8519,Female,Loyal Customer,16,Personal Travel,Eco,862,3,4,3,4,4,3,4,4,5,5,4,5,5,4,21,10.0,neutral or dissatisfied +95590,66409,Female,Loyal Customer,42,Business travel,Business,1162,2,5,3,5,3,4,4,2,2,2,2,2,2,2,11,19.0,neutral or dissatisfied +95591,124122,Male,Loyal Customer,59,Business travel,Business,529,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +95592,112456,Male,disloyal Customer,26,Business travel,Eco,862,2,2,2,4,1,2,1,1,1,4,3,4,4,1,3,2.0,neutral or dissatisfied +95593,75694,Male,disloyal Customer,22,Business travel,Eco,868,3,3,3,5,2,3,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +95594,45441,Female,Loyal Customer,61,Personal Travel,Eco,458,3,5,3,4,3,1,5,4,4,3,4,2,4,1,30,21.0,neutral or dissatisfied +95595,37979,Male,Loyal Customer,35,Personal Travel,Business,1185,4,4,4,4,2,3,4,2,2,4,2,4,2,3,0,0.0,satisfied +95596,40415,Female,disloyal Customer,23,Business travel,Eco,461,4,1,4,3,4,4,4,4,3,4,3,3,2,4,0,5.0,neutral or dissatisfied +95597,21782,Male,disloyal Customer,25,Business travel,Eco,241,5,0,5,1,4,5,4,4,5,1,3,3,5,4,0,0.0,satisfied +95598,6555,Male,disloyal Customer,24,Business travel,Business,473,4,0,4,4,5,4,5,5,5,4,5,5,4,5,10,2.0,satisfied +95599,75063,Male,Loyal Customer,54,Business travel,Business,2611,2,2,2,2,2,3,5,4,4,4,4,5,4,5,0,14.0,satisfied +95600,34053,Male,Loyal Customer,44,Business travel,Eco,1674,5,5,5,5,5,5,5,5,1,1,4,3,4,5,0,0.0,satisfied +95601,25831,Male,Loyal Customer,52,Business travel,Business,3395,3,3,3,3,4,1,3,3,3,4,3,5,3,1,0,0.0,satisfied +95602,7672,Female,disloyal Customer,29,Business travel,Eco,641,2,1,2,3,5,2,4,5,3,5,4,3,3,5,50,40.0,neutral or dissatisfied +95603,27755,Female,Loyal Customer,16,Business travel,Business,1448,1,1,5,1,4,4,4,4,3,3,2,2,3,4,3,0.0,satisfied +95604,78080,Male,Loyal Customer,60,Business travel,Business,1943,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +95605,88034,Male,Loyal Customer,37,Business travel,Business,1909,4,4,2,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +95606,121366,Male,Loyal Customer,22,Personal Travel,Eco,1670,1,4,1,3,4,1,4,4,3,2,4,4,5,4,0,3.0,neutral or dissatisfied +95607,103073,Female,disloyal Customer,21,Business travel,Business,266,4,4,4,3,3,4,3,3,1,1,3,4,3,3,1,0.0,neutral or dissatisfied +95608,126971,Male,Loyal Customer,22,Business travel,Business,647,4,4,4,4,4,4,4,4,3,3,5,5,5,4,15,10.0,satisfied +95609,37722,Female,Loyal Customer,10,Personal Travel,Eco,1035,2,3,2,2,1,2,1,1,2,1,3,1,2,1,0,0.0,neutral or dissatisfied +95610,60305,Male,Loyal Customer,47,Business travel,Business,406,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +95611,18691,Male,Loyal Customer,37,Personal Travel,Eco,127,3,2,3,3,1,3,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +95612,118861,Male,Loyal Customer,35,Personal Travel,Eco Plus,368,2,3,2,3,3,2,3,3,4,2,1,1,1,3,44,38.0,neutral or dissatisfied +95613,47891,Female,Loyal Customer,32,Business travel,Business,315,1,1,1,1,5,5,5,5,2,4,4,5,4,5,5,0.0,satisfied +95614,3642,Male,Loyal Customer,54,Business travel,Business,3620,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +95615,40886,Female,Loyal Customer,34,Personal Travel,Eco,588,2,5,2,4,3,2,3,3,4,5,5,5,2,3,7,0.0,neutral or dissatisfied +95616,86829,Female,disloyal Customer,25,Business travel,Business,484,5,0,5,4,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +95617,75560,Female,disloyal Customer,25,Business travel,Business,337,2,4,2,4,2,2,2,2,5,4,4,4,5,2,0,0.0,neutral or dissatisfied +95618,75472,Female,Loyal Customer,20,Personal Travel,Eco,2218,3,3,3,1,3,3,3,3,2,4,4,5,5,3,1,0.0,neutral or dissatisfied +95619,106502,Male,Loyal Customer,65,Personal Travel,Eco,495,1,5,1,4,1,1,1,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +95620,525,Female,Loyal Customer,30,Business travel,Business,134,2,2,2,2,4,4,5,4,5,4,5,5,4,4,61,58.0,satisfied +95621,42938,Female,Loyal Customer,50,Business travel,Business,414,5,5,4,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +95622,92477,Female,Loyal Customer,59,Business travel,Business,1892,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +95623,77321,Male,Loyal Customer,25,Business travel,Business,3549,1,1,1,1,5,5,5,5,5,4,4,3,5,5,0,26.0,satisfied +95624,11646,Female,Loyal Customer,43,Business travel,Business,2970,4,4,4,4,5,4,4,2,2,2,2,3,2,4,12,0.0,satisfied +95625,15239,Female,Loyal Customer,25,Business travel,Business,3644,4,4,5,4,5,5,5,5,2,3,1,2,3,5,0,0.0,satisfied +95626,57826,Female,Loyal Customer,35,Personal Travel,Eco,622,3,3,3,3,2,3,2,2,3,2,4,4,3,2,5,49.0,neutral or dissatisfied +95627,11708,Male,disloyal Customer,45,Business travel,Business,429,5,5,5,5,3,5,3,3,5,5,4,5,4,3,0,0.0,satisfied +95628,22580,Male,disloyal Customer,29,Business travel,Eco,300,4,4,4,2,3,4,3,3,4,3,2,5,3,3,0,0.0,neutral or dissatisfied +95629,2906,Female,Loyal Customer,14,Personal Travel,Eco,491,4,5,3,1,3,3,3,3,4,2,4,5,5,3,0,0.0,satisfied +95630,51782,Male,Loyal Customer,28,Personal Travel,Eco,237,3,5,0,1,4,0,4,4,4,4,4,3,4,4,78,82.0,neutral or dissatisfied +95631,59352,Female,Loyal Customer,31,Business travel,Business,2399,4,5,2,2,4,4,4,4,1,5,4,1,3,4,0,0.0,neutral or dissatisfied +95632,10897,Female,Loyal Customer,17,Business travel,Business,74,2,1,5,1,4,3,2,4,4,4,3,1,3,4,25,13.0,neutral or dissatisfied +95633,103452,Female,disloyal Customer,39,Business travel,Business,448,3,3,3,4,1,3,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +95634,110579,Male,Loyal Customer,52,Business travel,Eco,488,4,1,1,1,4,4,4,4,1,2,2,1,2,4,27,28.0,neutral or dissatisfied +95635,82595,Female,Loyal Customer,50,Business travel,Business,3191,4,3,4,4,3,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +95636,129456,Female,Loyal Customer,60,Business travel,Business,1958,5,5,5,5,3,5,5,4,4,4,4,4,4,3,12,0.0,satisfied +95637,20706,Male,Loyal Customer,33,Personal Travel,Eco,584,2,4,2,3,2,2,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +95638,92637,Male,Loyal Customer,52,Business travel,Business,3031,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +95639,31398,Male,Loyal Customer,58,Business travel,Eco,1199,1,2,2,2,1,1,1,1,2,4,4,4,3,1,0,0.0,neutral or dissatisfied +95640,33816,Female,Loyal Customer,42,Business travel,Eco,1121,3,2,2,2,1,2,3,3,3,3,3,5,3,2,0,0.0,satisfied +95641,52942,Female,Loyal Customer,47,Personal Travel,Eco Plus,679,1,5,1,4,4,4,4,4,4,1,4,5,4,4,17,18.0,neutral or dissatisfied +95642,103290,Female,disloyal Customer,26,Business travel,Eco,872,3,3,3,3,5,3,4,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +95643,61559,Female,Loyal Customer,57,Business travel,Eco Plus,753,3,4,4,4,2,3,3,3,3,3,3,1,3,3,0,5.0,neutral or dissatisfied +95644,56802,Female,Loyal Customer,42,Business travel,Business,1605,2,2,2,2,4,4,5,5,5,5,5,4,5,4,4,0.0,satisfied +95645,32150,Male,Loyal Customer,36,Business travel,Business,163,5,5,4,5,1,1,2,3,3,4,5,1,3,2,0,2.0,satisfied +95646,24037,Male,Loyal Customer,15,Personal Travel,Eco,562,2,4,2,4,1,2,1,1,5,4,4,3,4,1,1,0.0,neutral or dissatisfied +95647,73626,Male,Loyal Customer,44,Business travel,Business,3722,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +95648,27537,Female,Loyal Customer,31,Personal Travel,Eco,1050,3,3,3,3,4,3,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +95649,33539,Male,Loyal Customer,47,Business travel,Business,3255,3,3,3,3,3,5,4,4,4,4,4,5,4,4,10,0.0,satisfied +95650,119249,Female,Loyal Customer,19,Personal Travel,Eco Plus,331,3,4,3,2,5,3,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +95651,38481,Male,Loyal Customer,49,Personal Travel,Eco,846,2,4,2,4,4,2,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +95652,53315,Male,Loyal Customer,60,Personal Travel,Eco,758,3,4,2,3,5,2,5,5,4,5,4,5,5,5,52,62.0,neutral or dissatisfied +95653,14941,Male,Loyal Customer,21,Business travel,Business,554,3,3,3,3,4,4,4,4,5,1,5,1,3,4,0,0.0,satisfied +95654,37370,Female,Loyal Customer,30,Business travel,Business,1010,5,5,5,5,4,4,4,4,2,2,1,3,1,4,0,0.0,satisfied +95655,78995,Male,disloyal Customer,42,Business travel,Business,226,3,3,3,3,4,3,3,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +95656,97903,Male,Loyal Customer,59,Business travel,Business,616,1,1,1,1,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +95657,1997,Male,Loyal Customer,23,Personal Travel,Eco,351,2,4,5,2,3,5,3,3,5,5,5,4,4,3,3,0.0,neutral or dissatisfied +95658,78944,Male,Loyal Customer,38,Business travel,Business,501,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +95659,7817,Female,Loyal Customer,22,Business travel,Business,2576,1,0,0,3,5,0,3,5,4,2,3,4,3,5,68,65.0,neutral or dissatisfied +95660,82416,Male,Loyal Customer,54,Business travel,Business,3519,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +95661,89360,Female,Loyal Customer,12,Personal Travel,Eco,1587,2,5,2,1,5,2,5,5,4,2,4,4,5,5,0,2.0,neutral or dissatisfied +95662,66216,Male,Loyal Customer,50,Business travel,Eco,550,4,5,5,5,4,4,4,4,3,3,1,3,2,4,0,0.0,neutral or dissatisfied +95663,12962,Male,disloyal Customer,50,Business travel,Eco Plus,674,2,2,2,3,1,2,3,1,4,5,4,2,3,1,0,0.0,neutral or dissatisfied +95664,128703,Female,disloyal Customer,26,Business travel,Business,1464,4,4,4,4,5,4,5,5,3,3,5,3,5,5,0,28.0,satisfied +95665,77218,Female,Loyal Customer,47,Business travel,Business,1590,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +95666,62088,Female,Loyal Customer,7,Personal Travel,Eco Plus,2586,2,5,2,3,3,2,3,3,4,5,4,5,4,3,6,11.0,neutral or dissatisfied +95667,87659,Male,Loyal Customer,62,Business travel,Business,1531,2,2,5,2,2,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +95668,107661,Female,Loyal Customer,53,Business travel,Business,405,3,4,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +95669,29553,Female,Loyal Customer,25,Business travel,Eco,680,5,5,5,5,5,5,5,5,2,1,2,1,1,5,0,0.0,satisfied +95670,101733,Female,Loyal Customer,54,Business travel,Business,2863,2,2,2,2,2,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +95671,15242,Female,Loyal Customer,57,Personal Travel,Eco,529,2,5,2,3,2,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +95672,92300,Female,Loyal Customer,32,Business travel,Business,2556,2,2,2,2,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +95673,64999,Female,disloyal Customer,20,Business travel,Eco,247,2,4,2,3,3,2,3,3,2,1,4,1,3,3,0,0.0,neutral or dissatisfied +95674,18904,Male,Loyal Customer,23,Personal Travel,Eco,448,3,4,3,4,5,3,5,5,4,4,5,3,5,5,0,19.0,neutral or dissatisfied +95675,96269,Female,Loyal Customer,52,Personal Travel,Eco,687,2,4,3,4,3,4,5,1,1,3,1,5,1,4,27,39.0,neutral or dissatisfied +95676,66671,Female,Loyal Customer,50,Business travel,Business,3643,2,2,2,2,2,4,5,4,4,4,4,5,4,3,2,6.0,satisfied +95677,120239,Female,Loyal Customer,68,Personal Travel,Eco,1325,2,4,2,3,2,3,5,3,3,2,2,4,3,3,0,0.0,neutral or dissatisfied +95678,14817,Male,Loyal Customer,42,Personal Travel,Eco Plus,95,1,4,1,1,1,1,5,1,2,1,1,3,4,1,115,120.0,neutral or dissatisfied +95679,107235,Female,Loyal Customer,43,Personal Travel,Eco,583,3,4,3,3,2,5,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +95680,112459,Female,Loyal Customer,53,Business travel,Eco,453,5,1,1,1,2,1,3,5,5,5,5,2,5,4,1,0.0,satisfied +95681,83780,Female,Loyal Customer,49,Business travel,Business,2399,2,2,2,2,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +95682,8218,Female,Loyal Customer,12,Personal Travel,Eco,125,0,5,0,3,5,0,5,5,4,5,3,3,3,5,4,4.0,satisfied +95683,3712,Male,Loyal Customer,60,Personal Travel,Eco,431,3,5,3,4,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +95684,19160,Male,Loyal Customer,34,Business travel,Business,304,1,2,2,2,5,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +95685,128877,Male,disloyal Customer,25,Business travel,Business,2454,4,4,4,2,4,2,2,4,4,5,4,2,3,2,0,1.0,satisfied +95686,119884,Male,Loyal Customer,68,Personal Travel,Eco,936,4,5,4,2,5,4,5,5,5,5,5,3,4,5,21,0.0,neutral or dissatisfied +95687,38869,Male,Loyal Customer,46,Personal Travel,Eco,2300,2,4,3,1,4,3,4,4,2,3,4,2,2,4,12,1.0,neutral or dissatisfied +95688,129590,Male,Loyal Customer,53,Business travel,Business,1967,1,1,1,1,2,4,4,5,5,5,5,5,5,3,9,12.0,satisfied +95689,7141,Female,Loyal Customer,45,Business travel,Business,116,2,1,1,1,5,4,4,4,4,4,2,1,4,2,0,8.0,neutral or dissatisfied +95690,37509,Male,Loyal Customer,72,Business travel,Business,2009,2,2,2,2,4,4,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +95691,113040,Male,disloyal Customer,24,Business travel,Eco,569,4,0,4,3,3,4,3,3,3,2,5,4,4,3,19,9.0,neutral or dissatisfied +95692,56366,Female,Loyal Customer,16,Personal Travel,Eco,200,3,5,3,4,4,3,4,4,2,2,5,5,5,4,0,0.0,neutral or dissatisfied +95693,15269,Male,Loyal Customer,39,Business travel,Eco,500,3,5,5,5,3,3,3,3,5,3,5,1,1,3,8,0.0,satisfied +95694,105005,Male,Loyal Customer,57,Business travel,Business,255,1,1,1,1,4,4,5,5,5,5,5,4,5,3,49,48.0,satisfied +95695,41185,Female,Loyal Customer,58,Business travel,Eco,429,2,2,2,2,4,3,4,2,2,2,2,2,2,4,16,33.0,neutral or dissatisfied +95696,70582,Female,Loyal Customer,47,Personal Travel,Eco,1258,1,5,1,4,2,4,5,3,3,1,1,3,3,3,0,10.0,neutral or dissatisfied +95697,4387,Male,Loyal Customer,9,Personal Travel,Eco,607,4,4,4,2,1,4,1,1,4,2,5,3,5,1,2,17.0,neutral or dissatisfied +95698,31199,Female,Loyal Customer,43,Business travel,Business,3947,4,4,4,4,5,2,3,4,4,4,4,3,4,4,19,9.0,satisfied +95699,56074,Female,Loyal Customer,69,Personal Travel,Eco,2475,3,2,3,4,3,2,2,3,2,3,4,2,1,2,9,4.0,neutral or dissatisfied +95700,125265,Male,Loyal Customer,28,Business travel,Business,1488,2,2,2,2,5,5,5,5,4,3,5,4,5,5,0,5.0,satisfied +95701,31661,Female,disloyal Customer,26,Business travel,Eco,853,2,3,3,3,5,3,5,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +95702,94537,Male,disloyal Customer,27,Business travel,Business,189,0,0,0,5,4,0,4,4,5,4,4,4,5,4,0,0.0,satisfied +95703,35263,Female,Loyal Customer,38,Business travel,Business,1056,4,4,4,4,4,4,4,1,5,3,4,4,4,4,267,287.0,satisfied +95704,25551,Male,Loyal Customer,26,Personal Travel,Eco Plus,516,3,2,3,3,1,3,1,1,1,1,4,4,4,1,11,9.0,neutral or dissatisfied +95705,50741,Male,Loyal Customer,18,Personal Travel,Eco,262,4,5,4,2,1,4,1,1,5,3,5,2,2,1,0,0.0,neutral or dissatisfied +95706,15431,Male,disloyal Customer,20,Business travel,Eco,377,2,4,2,4,4,2,4,4,1,1,3,2,4,4,108,95.0,neutral or dissatisfied +95707,115536,Female,disloyal Customer,65,Business travel,Eco,308,4,1,4,3,2,4,5,2,1,2,3,2,2,2,0,3.0,neutral or dissatisfied +95708,104188,Male,Loyal Customer,40,Business travel,Business,349,2,2,2,2,5,5,5,4,4,4,4,5,4,5,12,5.0,satisfied +95709,27347,Male,Loyal Customer,53,Business travel,Eco,679,3,2,1,2,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +95710,31962,Female,Loyal Customer,47,Business travel,Business,3405,3,3,3,3,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +95711,91839,Male,Loyal Customer,59,Personal Travel,Eco Plus,626,2,5,3,2,2,3,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +95712,12337,Female,Loyal Customer,37,Business travel,Business,190,3,3,3,3,3,2,2,4,4,4,4,4,4,5,0,0.0,satisfied +95713,72524,Male,Loyal Customer,47,Business travel,Eco,918,1,3,3,3,1,1,1,1,3,4,2,3,2,1,0,0.0,neutral or dissatisfied +95714,90489,Female,Loyal Customer,47,Business travel,Business,3447,2,2,2,2,5,4,4,2,2,2,2,3,2,5,1,8.0,satisfied +95715,74803,Male,Loyal Customer,59,Business travel,Business,1464,2,2,2,2,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +95716,24013,Male,disloyal Customer,39,Business travel,Eco,427,2,0,2,3,4,2,3,4,3,3,1,1,4,4,0,0.0,neutral or dissatisfied +95717,58694,Male,Loyal Customer,45,Business travel,Business,4243,3,2,3,3,4,3,3,5,4,3,4,3,3,3,0,0.0,satisfied +95718,25813,Female,Loyal Customer,44,Business travel,Business,1747,4,4,3,4,1,5,4,5,5,5,5,5,5,1,0,17.0,satisfied +95719,88081,Male,Loyal Customer,47,Business travel,Business,3624,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +95720,111521,Female,Loyal Customer,73,Business travel,Eco Plus,391,4,2,2,2,4,4,4,3,3,4,3,3,3,1,0,4.0,neutral or dissatisfied +95721,98600,Male,Loyal Customer,44,Business travel,Business,992,4,4,4,4,3,5,5,4,4,4,4,4,4,3,37,16.0,satisfied +95722,11209,Male,Loyal Customer,19,Personal Travel,Eco,163,4,4,0,2,2,0,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +95723,97993,Male,Loyal Customer,42,Business travel,Business,1599,1,1,1,1,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +95724,48038,Female,Loyal Customer,42,Business travel,Eco,677,4,1,1,1,1,4,3,4,4,4,4,2,4,3,0,0.0,satisfied +95725,69711,Female,disloyal Customer,21,Business travel,Eco,1372,3,3,3,1,5,3,3,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +95726,67871,Female,Loyal Customer,18,Personal Travel,Eco,1464,3,4,3,5,1,3,1,1,3,5,4,5,5,1,27,31.0,neutral or dissatisfied +95727,18056,Male,disloyal Customer,23,Business travel,Eco,488,4,0,4,3,4,4,4,4,5,1,5,3,3,4,0,0.0,neutral or dissatisfied +95728,126415,Female,disloyal Customer,24,Business travel,Business,631,3,2,3,3,1,3,1,1,4,2,4,1,4,1,1,0.0,neutral or dissatisfied +95729,126121,Female,Loyal Customer,40,Business travel,Business,2430,1,4,4,4,2,3,4,1,1,1,1,1,1,2,26,15.0,neutral or dissatisfied +95730,72607,Male,Loyal Customer,15,Personal Travel,Eco,1119,1,5,1,4,3,1,3,3,5,3,5,5,5,3,1,0.0,neutral or dissatisfied +95731,96748,Female,Loyal Customer,64,Personal Travel,Eco Plus,696,3,5,3,3,2,5,5,4,4,3,5,5,4,3,14,0.0,neutral or dissatisfied +95732,30841,Female,Loyal Customer,41,Business travel,Business,2467,2,1,1,1,3,3,4,2,2,2,2,3,2,2,0,25.0,neutral or dissatisfied +95733,120107,Female,Loyal Customer,28,Business travel,Business,1576,3,3,3,3,5,5,5,5,4,2,4,3,5,5,0,0.0,satisfied +95734,122634,Female,disloyal Customer,44,Business travel,Business,728,4,4,4,5,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +95735,115348,Female,Loyal Customer,17,Business travel,Business,1626,1,2,2,2,1,1,1,1,4,4,3,2,3,1,0,0.0,neutral or dissatisfied +95736,78261,Male,Loyal Customer,25,Business travel,Business,903,3,3,3,3,5,5,5,5,4,5,5,5,4,5,0,0.0,satisfied +95737,97097,Male,Loyal Customer,53,Business travel,Business,2330,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +95738,103649,Male,Loyal Customer,49,Business travel,Business,405,4,4,4,4,2,4,5,4,4,5,4,4,4,3,15,6.0,satisfied +95739,105541,Male,disloyal Customer,19,Business travel,Eco,611,1,3,1,3,3,1,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +95740,105581,Female,Loyal Customer,65,Personal Travel,Eco,577,2,4,2,4,2,5,4,1,1,2,1,5,1,5,2,0.0,neutral or dissatisfied +95741,10270,Male,Loyal Customer,26,Personal Travel,Business,316,2,0,2,1,2,2,4,2,5,4,5,3,4,2,1,0.0,neutral or dissatisfied +95742,46217,Male,Loyal Customer,30,Business travel,Business,752,4,4,4,4,3,3,3,3,1,4,2,5,2,3,14,1.0,satisfied +95743,50395,Female,Loyal Customer,37,Business travel,Business,373,4,4,4,4,3,3,5,4,4,4,4,5,4,1,0,0.0,satisfied +95744,78892,Female,Loyal Customer,31,Business travel,Business,1727,5,5,4,5,5,5,5,5,4,3,3,4,4,5,0,0.0,satisfied +95745,55118,Male,Loyal Customer,42,Personal Travel,Eco,1346,3,5,3,2,1,3,1,1,3,3,4,5,5,1,40,26.0,neutral or dissatisfied +95746,23298,Female,Loyal Customer,38,Business travel,Business,2032,5,5,5,5,2,2,4,2,2,2,2,5,2,3,2,0.0,satisfied +95747,91625,Male,Loyal Customer,60,Business travel,Business,3980,3,3,3,3,3,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +95748,104905,Female,Loyal Customer,46,Business travel,Business,1789,2,2,2,2,3,2,1,4,4,4,4,1,4,5,0,0.0,satisfied +95749,3651,Male,Loyal Customer,54,Business travel,Business,3790,3,3,3,3,5,4,5,1,1,2,1,4,1,4,0,18.0,satisfied +95750,24388,Female,Loyal Customer,23,Personal Travel,Eco,669,1,5,1,4,3,1,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +95751,68435,Male,Loyal Customer,28,Business travel,Eco Plus,1045,2,3,3,3,2,2,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +95752,64731,Male,Loyal Customer,58,Business travel,Business,2637,2,2,2,2,4,4,5,4,4,4,4,3,4,5,21,22.0,satisfied +95753,72863,Male,Loyal Customer,48,Personal Travel,Eco,700,3,5,3,1,2,3,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +95754,4228,Male,Loyal Customer,55,Business travel,Business,1020,3,3,2,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +95755,39747,Female,Loyal Customer,33,Personal Travel,Eco Plus,162,2,2,2,4,1,2,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +95756,48738,Male,Loyal Customer,53,Business travel,Business,3033,4,4,4,4,1,4,3,3,3,3,4,4,3,1,42,36.0,neutral or dissatisfied +95757,93611,Female,Loyal Customer,57,Business travel,Business,577,2,2,2,2,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +95758,77159,Male,Loyal Customer,33,Business travel,Business,1450,4,4,4,4,3,3,3,3,5,2,4,4,4,3,0,0.0,satisfied +95759,120851,Male,Loyal Customer,30,Personal Travel,Business,920,4,4,3,2,1,3,1,1,4,4,5,5,4,1,0,0.0,satisfied +95760,19890,Female,disloyal Customer,45,Business travel,Eco,315,2,0,2,3,2,2,2,2,5,3,3,2,3,2,0,0.0,neutral or dissatisfied +95761,83799,Male,Loyal Customer,40,Business travel,Business,2209,3,3,3,3,2,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +95762,103784,Female,Loyal Customer,40,Business travel,Business,2721,1,1,4,1,3,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +95763,15507,Male,Loyal Customer,32,Personal Travel,Eco,433,1,1,1,3,1,1,1,1,3,2,2,3,2,1,0,0.0,neutral or dissatisfied +95764,18321,Female,Loyal Customer,32,Personal Travel,Eco,715,2,4,2,1,5,2,5,5,5,4,1,3,3,5,4,0.0,neutral or dissatisfied +95765,35740,Female,Loyal Customer,38,Business travel,Business,2153,4,4,5,4,4,4,1,5,5,5,5,4,5,2,2,0.0,satisfied +95766,129704,Female,Loyal Customer,58,Business travel,Business,3670,0,0,0,3,3,4,5,3,3,3,3,4,3,4,1,1.0,satisfied +95767,71493,Female,Loyal Customer,24,Personal Travel,Business,1120,4,1,4,4,5,4,5,5,4,4,3,4,3,5,8,4.0,satisfied +95768,42814,Male,Loyal Customer,77,Business travel,Business,277,1,0,0,4,5,4,3,1,1,0,1,3,1,1,1,0.0,neutral or dissatisfied +95769,9719,Female,Loyal Customer,49,Personal Travel,Eco,277,4,4,4,4,1,3,3,1,1,4,1,2,1,4,1,0.0,satisfied +95770,42895,Female,Loyal Customer,40,Business travel,Business,200,2,2,2,2,2,3,2,3,3,4,5,2,3,1,0,0.0,satisfied +95771,81602,Female,disloyal Customer,25,Business travel,Eco,334,1,3,1,4,4,1,4,4,4,3,4,4,3,4,0,0.0,neutral or dissatisfied +95772,11130,Female,Loyal Customer,34,Personal Travel,Eco,316,4,4,4,2,1,4,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +95773,15956,Male,Loyal Customer,53,Personal Travel,Eco,528,2,4,4,4,2,4,3,2,3,1,4,3,3,2,31,65.0,neutral or dissatisfied +95774,47354,Male,disloyal Customer,26,Business travel,Eco,588,3,1,3,4,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +95775,121467,Female,Loyal Customer,10,Personal Travel,Eco,290,2,5,2,3,3,2,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +95776,102208,Female,Loyal Customer,48,Business travel,Business,414,5,5,5,5,3,5,5,4,4,4,4,4,4,3,22,6.0,satisfied +95777,92416,Female,Loyal Customer,27,Business travel,Business,1919,5,5,5,5,4,4,4,4,5,5,3,5,5,4,0,24.0,satisfied +95778,74922,Female,Loyal Customer,40,Business travel,Business,2475,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +95779,113111,Female,Loyal Customer,15,Personal Travel,Eco,543,3,3,3,5,2,3,2,2,1,1,4,3,2,2,0,0.0,neutral or dissatisfied +95780,83540,Female,Loyal Customer,48,Business travel,Business,1121,5,5,3,5,4,4,5,2,2,2,2,4,2,5,0,16.0,satisfied +95781,40029,Male,Loyal Customer,53,Personal Travel,Eco,618,3,5,3,1,5,3,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +95782,83587,Male,Loyal Customer,69,Personal Travel,Eco,936,1,4,1,1,3,1,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +95783,10813,Male,Loyal Customer,40,Business travel,Business,216,2,2,2,2,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +95784,4484,Male,Loyal Customer,31,Business travel,Business,1147,2,2,2,2,5,5,5,5,5,2,5,4,4,5,12,67.0,satisfied +95785,97570,Male,disloyal Customer,22,Business travel,Eco,448,3,4,3,2,3,2,2,4,4,4,5,2,4,2,153,154.0,neutral or dissatisfied +95786,41745,Female,Loyal Customer,18,Personal Travel,Eco,700,2,3,2,4,3,2,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +95787,28111,Female,Loyal Customer,24,Business travel,Business,1529,3,3,3,3,4,4,4,4,5,5,3,4,4,4,0,0.0,satisfied +95788,94136,Male,disloyal Customer,21,Business travel,Business,189,4,5,4,4,3,4,4,3,4,4,4,4,4,3,0,0.0,satisfied +95789,24790,Male,Loyal Customer,49,Personal Travel,Eco,447,2,4,4,1,1,4,1,1,5,5,5,3,5,1,42,26.0,neutral or dissatisfied +95790,53400,Female,Loyal Customer,26,Business travel,Business,2253,3,2,3,3,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +95791,5288,Male,Loyal Customer,45,Personal Travel,Eco,351,1,4,1,4,1,1,1,1,3,4,5,5,4,1,39,38.0,neutral or dissatisfied +95792,121986,Male,disloyal Customer,36,Business travel,Business,130,2,1,1,4,1,1,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +95793,46164,Male,Loyal Customer,45,Personal Travel,Eco,604,2,2,1,2,4,1,4,4,2,4,3,1,3,4,4,23.0,neutral or dissatisfied +95794,35945,Female,disloyal Customer,20,Business travel,Eco,231,5,0,5,4,5,5,5,5,1,3,5,1,2,5,0,0.0,satisfied +95795,48906,Male,Loyal Customer,45,Business travel,Eco,337,4,2,2,2,4,4,4,4,5,2,4,2,5,4,0,0.0,satisfied +95796,75050,Male,Loyal Customer,54,Business travel,Business,1592,1,1,1,1,3,2,3,1,1,1,1,2,1,4,7,13.0,neutral or dissatisfied +95797,36292,Male,Loyal Customer,57,Business travel,Business,2901,5,5,5,5,2,1,5,4,4,4,4,1,4,3,0,5.0,satisfied +95798,116177,Male,Loyal Customer,43,Personal Travel,Eco,342,2,5,2,4,3,2,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +95799,111766,Female,Loyal Customer,21,Personal Travel,Eco Plus,1436,1,2,1,3,4,1,4,4,2,4,2,4,4,4,92,98.0,neutral or dissatisfied +95800,104272,Male,Loyal Customer,46,Business travel,Business,1733,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,3.0,satisfied +95801,101296,Male,Loyal Customer,52,Personal Travel,Eco,444,3,4,2,4,1,2,1,1,3,3,4,4,4,1,3,0.0,neutral or dissatisfied +95802,91392,Male,Loyal Customer,33,Business travel,Business,2218,4,3,3,3,4,4,4,4,1,1,2,1,4,4,0,0.0,neutral or dissatisfied +95803,75461,Female,Loyal Customer,8,Personal Travel,Eco,2342,4,3,5,4,2,5,2,2,5,4,4,2,3,2,0,0.0,neutral or dissatisfied +95804,16463,Female,Loyal Customer,37,Personal Travel,Eco,416,1,1,1,4,2,1,2,2,4,4,3,1,3,2,39,53.0,neutral or dissatisfied +95805,64728,Female,Loyal Customer,49,Business travel,Business,190,2,2,2,2,4,5,5,4,4,4,5,4,4,5,96,84.0,satisfied +95806,61137,Male,Loyal Customer,42,Business travel,Business,2522,2,2,2,2,5,5,4,4,4,4,4,5,4,4,17,0.0,satisfied +95807,72959,Female,Loyal Customer,40,Business travel,Business,3212,1,4,4,4,3,4,3,1,1,1,1,3,1,1,37,11.0,neutral or dissatisfied +95808,49930,Male,disloyal Customer,22,Business travel,Eco,89,3,3,3,3,1,3,1,1,5,2,3,2,5,1,0,0.0,neutral or dissatisfied +95809,85017,Male,Loyal Customer,36,Business travel,Eco,1190,1,2,2,2,1,1,1,1,4,2,1,1,2,1,2,0.0,neutral or dissatisfied +95810,84844,Female,Loyal Customer,31,Business travel,Business,3118,1,3,5,3,1,1,1,1,1,5,4,3,4,1,0,0.0,neutral or dissatisfied +95811,29175,Female,Loyal Customer,63,Business travel,Eco Plus,697,4,5,5,5,4,3,4,4,4,4,4,2,4,5,0,0.0,satisfied +95812,41108,Male,disloyal Customer,35,Business travel,Eco,667,1,1,1,2,4,1,4,4,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +95813,54705,Female,disloyal Customer,47,Business travel,Eco,564,1,1,1,3,2,1,2,2,1,3,3,2,4,2,25,38.0,neutral or dissatisfied +95814,108551,Female,Loyal Customer,40,Personal Travel,Eco Plus,511,3,5,3,3,2,3,4,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +95815,111743,Male,disloyal Customer,12,Business travel,Eco,1154,3,3,3,3,1,3,1,1,4,4,3,2,4,1,5,18.0,neutral or dissatisfied +95816,26183,Male,Loyal Customer,47,Business travel,Business,406,2,1,1,1,5,3,3,2,2,2,2,3,2,1,0,8.0,neutral or dissatisfied +95817,69325,Male,Loyal Customer,33,Business travel,Business,3212,1,1,1,1,5,5,5,5,3,5,5,4,4,5,2,46.0,satisfied +95818,43152,Male,Loyal Customer,50,Business travel,Eco Plus,192,4,1,1,1,4,4,4,2,4,4,4,4,1,4,109,132.0,neutral or dissatisfied +95819,72675,Male,Loyal Customer,70,Personal Travel,Eco,964,3,4,3,3,5,3,5,5,3,2,5,4,5,5,0,9.0,neutral or dissatisfied +95820,24052,Male,disloyal Customer,13,Personal Travel,Eco,427,3,3,3,3,4,3,4,4,1,1,1,4,2,4,0,0.0,neutral or dissatisfied +95821,68874,Female,Loyal Customer,32,Business travel,Business,1061,1,1,1,1,4,5,4,4,3,2,5,5,5,4,9,0.0,satisfied +95822,6251,Female,Loyal Customer,17,Personal Travel,Eco,678,2,4,2,3,1,2,1,1,3,3,5,4,5,1,1,39.0,neutral or dissatisfied +95823,110738,Female,Loyal Customer,56,Business travel,Business,2751,3,3,4,3,3,4,4,5,5,5,5,3,5,3,126,94.0,satisfied +95824,77906,Female,Loyal Customer,14,Personal Travel,Eco,456,4,4,4,2,5,4,5,5,5,5,5,5,4,5,10,13.0,neutral or dissatisfied +95825,59895,Male,disloyal Customer,23,Business travel,Eco,1065,5,4,4,2,2,4,2,2,5,2,4,4,4,2,26,20.0,satisfied +95826,126694,Female,Loyal Customer,53,Business travel,Business,2370,1,1,2,1,3,4,5,4,4,4,4,4,4,3,24,0.0,satisfied +95827,33088,Female,Loyal Customer,43,Personal Travel,Eco,102,1,1,0,4,3,4,3,5,5,0,5,3,5,4,0,0.0,neutral or dissatisfied +95828,42816,Female,Loyal Customer,65,Personal Travel,Eco,710,3,4,3,2,3,4,4,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +95829,114874,Female,Loyal Customer,48,Business travel,Business,447,5,2,5,5,2,4,5,4,4,4,4,4,4,4,0,4.0,satisfied +95830,94416,Female,Loyal Customer,58,Business travel,Business,3319,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +95831,21323,Male,Loyal Customer,43,Business travel,Business,2550,2,2,5,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +95832,13436,Male,Loyal Customer,48,Business travel,Business,1929,4,5,5,5,2,4,3,4,4,4,4,4,4,1,15,14.0,neutral or dissatisfied +95833,119618,Male,Loyal Customer,35,Business travel,Business,1606,2,4,4,4,5,3,3,2,2,2,2,1,2,2,0,1.0,neutral or dissatisfied +95834,51837,Male,Loyal Customer,37,Business travel,Eco Plus,251,3,4,4,4,3,3,3,3,4,4,4,3,4,3,0,1.0,neutral or dissatisfied +95835,30708,Male,disloyal Customer,34,Business travel,Eco,464,2,1,2,3,5,2,2,5,1,1,3,4,3,5,83,94.0,neutral or dissatisfied +95836,90531,Female,disloyal Customer,22,Business travel,Business,581,5,4,5,2,1,5,1,1,4,4,4,3,5,1,0,0.0,satisfied +95837,125269,Male,Loyal Customer,59,Business travel,Eco,1488,2,5,5,5,2,2,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +95838,67998,Female,disloyal Customer,7,Business travel,Business,1464,4,4,4,4,5,4,5,5,5,3,4,3,4,5,0,0.0,satisfied +95839,115007,Male,Loyal Customer,41,Business travel,Business,446,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +95840,84209,Male,Loyal Customer,27,Business travel,Business,2338,2,2,2,2,2,2,2,2,1,5,3,1,3,2,13,9.0,neutral or dissatisfied +95841,24541,Male,disloyal Customer,15,Business travel,Eco,696,3,3,3,4,4,3,4,4,3,4,2,1,1,4,0,0.0,neutral or dissatisfied +95842,28572,Male,Loyal Customer,41,Business travel,Eco,2607,4,1,3,1,4,4,4,4,4,2,4,1,4,4,0,0.0,satisfied +95843,58396,Female,disloyal Customer,24,Business travel,Eco,473,0,0,0,4,2,0,2,2,3,5,4,3,5,2,0,0.0,satisfied +95844,86649,Female,Loyal Customer,37,Personal Travel,Eco,746,1,5,1,3,3,1,5,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +95845,23991,Male,Loyal Customer,57,Business travel,Eco,562,4,5,5,5,4,4,4,4,3,5,3,5,2,4,0,0.0,satisfied +95846,5226,Male,Loyal Customer,39,Business travel,Business,2616,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +95847,77286,Female,Loyal Customer,59,Personal Travel,Eco,1931,1,4,2,3,2,1,1,5,2,3,5,1,3,1,180,169.0,neutral or dissatisfied +95848,13377,Female,Loyal Customer,56,Personal Travel,Eco,946,1,3,1,3,2,3,2,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +95849,76323,Male,Loyal Customer,36,Personal Travel,Eco,2182,1,2,1,3,1,1,1,1,3,5,4,2,3,1,0,0.0,neutral or dissatisfied +95850,71477,Male,Loyal Customer,48,Personal Travel,Eco,837,1,5,1,4,3,1,4,3,5,2,2,1,3,3,0,0.0,neutral or dissatisfied +95851,44905,Male,Loyal Customer,37,Business travel,Business,1118,2,2,3,2,3,5,2,4,4,4,4,1,4,5,0,1.0,satisfied +95852,38723,Male,disloyal Customer,20,Business travel,Business,353,1,1,1,2,4,1,4,4,2,3,2,4,3,4,0,0.0,neutral or dissatisfied +95853,42707,Male,Loyal Customer,13,Personal Travel,Eco,604,0,4,0,2,1,0,1,1,5,3,5,4,4,1,0,0.0,satisfied +95854,49967,Male,Loyal Customer,44,Business travel,Business,3092,3,3,3,3,4,2,2,3,3,3,3,1,3,3,47,46.0,neutral or dissatisfied +95855,85409,Female,Loyal Customer,59,Business travel,Business,214,2,2,2,2,3,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +95856,37919,Female,Loyal Customer,36,Personal Travel,Eco,997,3,2,4,4,4,1,1,4,3,4,4,1,3,1,251,221.0,neutral or dissatisfied +95857,111180,Male,Loyal Customer,49,Business travel,Business,1546,5,5,5,5,5,5,5,5,5,5,5,3,5,4,28,36.0,satisfied +95858,4897,Male,Loyal Customer,43,Business travel,Business,1020,1,3,1,1,4,4,5,4,4,5,4,4,4,4,0,29.0,satisfied +95859,41008,Female,disloyal Customer,37,Business travel,Eco Plus,1201,1,1,1,3,5,1,5,5,1,4,4,3,3,5,63,60.0,neutral or dissatisfied +95860,45125,Male,Loyal Customer,52,Personal Travel,Eco,157,2,4,2,5,3,2,4,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +95861,52486,Male,Loyal Customer,14,Personal Travel,Eco Plus,451,3,5,3,1,1,3,5,1,5,1,4,3,3,1,0,0.0,neutral or dissatisfied +95862,123794,Male,disloyal Customer,24,Business travel,Eco,544,1,0,1,3,3,1,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +95863,127110,Male,Loyal Customer,65,Personal Travel,Eco,304,3,4,3,2,2,3,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +95864,90936,Male,Loyal Customer,59,Business travel,Business,115,3,3,3,3,2,2,5,4,4,4,5,4,4,4,30,38.0,satisfied +95865,23774,Male,disloyal Customer,47,Business travel,Eco,374,4,4,4,4,4,4,4,4,2,1,2,1,5,4,5,9.0,satisfied +95866,89030,Female,Loyal Customer,51,Business travel,Business,1947,5,5,5,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +95867,29345,Female,Loyal Customer,13,Personal Travel,Eco Plus,569,2,4,2,3,1,2,1,1,5,4,4,5,5,1,0,0.0,neutral or dissatisfied +95868,96641,Female,Loyal Customer,58,Business travel,Business,2407,3,3,3,3,2,5,4,4,4,4,4,3,4,4,1,5.0,satisfied +95869,51184,Female,Loyal Customer,51,Business travel,Eco Plus,109,4,2,2,2,2,4,1,4,4,4,4,3,4,3,0,0.0,satisfied +95870,7463,Female,Loyal Customer,45,Business travel,Business,510,3,3,3,3,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +95871,60430,Female,Loyal Customer,57,Business travel,Business,862,4,4,4,4,5,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +95872,75509,Female,Loyal Customer,44,Business travel,Business,2527,1,2,2,2,2,3,4,1,1,1,1,2,1,3,3,0.0,neutral or dissatisfied +95873,9166,Female,Loyal Customer,29,Personal Travel,Eco,946,5,1,5,3,5,5,5,5,4,4,3,1,3,5,0,0.0,satisfied +95874,12394,Male,Loyal Customer,34,Business travel,Eco,201,3,4,4,4,3,3,3,3,2,2,4,3,4,3,3,0.0,neutral or dissatisfied +95875,66609,Male,Loyal Customer,40,Personal Travel,Eco,761,2,4,2,5,2,2,2,2,3,3,5,3,4,2,3,4.0,neutral or dissatisfied +95876,57859,Female,Loyal Customer,56,Personal Travel,Eco,2329,1,5,0,3,0,3,2,4,2,4,5,2,4,2,0,0.0,neutral or dissatisfied +95877,6266,Female,Loyal Customer,39,Business travel,Business,585,1,1,1,1,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +95878,47822,Male,Loyal Customer,47,Business travel,Business,834,2,2,2,2,2,1,4,4,4,4,4,3,4,3,7,12.0,satisfied +95879,81693,Female,Loyal Customer,52,Personal Travel,Eco,907,4,5,4,2,3,4,4,2,2,4,2,3,2,5,5,16.0,neutral or dissatisfied +95880,21772,Female,Loyal Customer,35,Business travel,Eco,352,5,3,3,3,5,5,5,5,4,3,4,3,1,5,0,0.0,satisfied +95881,45270,Female,Loyal Customer,41,Personal Travel,Business,222,1,4,1,3,1,4,4,4,4,1,5,1,4,3,0,0.0,neutral or dissatisfied +95882,76741,Male,disloyal Customer,35,Business travel,Business,205,3,3,3,3,1,3,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +95883,115325,Female,Loyal Customer,31,Business travel,Eco,337,1,4,4,4,1,1,1,1,2,1,1,2,1,1,24,12.0,neutral or dissatisfied +95884,3671,Female,Loyal Customer,43,Business travel,Business,3118,2,4,4,4,2,3,4,2,2,2,2,4,2,4,2,0.0,neutral or dissatisfied +95885,86138,Male,Loyal Customer,50,Business travel,Business,3848,0,0,0,5,4,5,5,1,1,1,1,5,1,3,0,4.0,satisfied +95886,50743,Female,Loyal Customer,68,Personal Travel,Eco,372,5,4,5,1,2,4,4,4,4,5,4,3,4,3,0,4.0,satisfied +95887,35000,Female,Loyal Customer,37,Business travel,Business,1182,2,3,3,3,2,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +95888,32885,Male,Loyal Customer,14,Personal Travel,Eco,163,4,4,4,3,2,4,2,2,1,1,3,4,4,2,0,1.0,neutral or dissatisfied +95889,25752,Male,Loyal Customer,20,Business travel,Business,1529,5,5,5,5,4,4,4,4,2,2,5,4,1,4,4,0.0,satisfied +95890,64291,Male,Loyal Customer,60,Business travel,Business,1158,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +95891,99333,Male,Loyal Customer,37,Personal Travel,Eco,337,4,5,4,1,5,4,5,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +95892,70843,Female,Loyal Customer,48,Business travel,Business,761,1,1,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +95893,45437,Female,Loyal Customer,68,Personal Travel,Eco,649,3,3,3,4,2,4,2,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +95894,25219,Male,Loyal Customer,57,Business travel,Eco,787,5,1,3,1,5,5,5,5,2,4,2,5,1,5,0,4.0,satisfied +95895,73368,Female,Loyal Customer,47,Business travel,Business,3898,3,3,3,3,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +95896,22444,Male,Loyal Customer,59,Personal Travel,Eco,143,2,2,0,3,2,0,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +95897,26644,Female,Loyal Customer,52,Business travel,Eco,404,3,2,2,2,4,3,3,3,3,3,3,2,3,1,3,9.0,neutral or dissatisfied +95898,79229,Male,Loyal Customer,56,Business travel,Business,1521,5,5,3,5,2,5,5,3,3,3,3,5,3,3,8,0.0,satisfied +95899,79688,Male,Loyal Customer,50,Personal Travel,Eco,762,2,4,3,4,2,3,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +95900,121902,Male,Loyal Customer,69,Personal Travel,Eco,449,1,5,3,5,3,3,4,3,1,1,1,4,2,3,0,0.0,neutral or dissatisfied +95901,69171,Male,disloyal Customer,18,Business travel,Eco,187,3,0,3,2,3,3,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +95902,41434,Female,Loyal Customer,59,Personal Travel,Eco,809,5,2,5,2,3,3,2,3,3,5,3,2,3,1,0,0.0,satisfied +95903,46045,Female,Loyal Customer,26,Business travel,Business,991,1,1,3,1,5,5,5,5,4,3,5,4,5,5,0,0.0,satisfied +95904,104962,Female,Loyal Customer,51,Business travel,Business,3498,4,4,4,4,3,4,4,4,4,4,4,5,4,3,40,50.0,satisfied +95905,8022,Male,disloyal Customer,26,Business travel,Business,402,3,0,3,5,4,3,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +95906,12480,Male,Loyal Customer,68,Personal Travel,Eco,383,2,5,2,2,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +95907,124355,Male,disloyal Customer,17,Business travel,Business,808,4,4,3,2,3,3,3,3,3,2,4,4,4,3,0,0.0,satisfied +95908,6850,Male,Loyal Customer,39,Business travel,Business,1803,3,3,3,3,3,3,3,3,2,4,5,3,3,3,72,143.0,satisfied +95909,123428,Female,Loyal Customer,40,Business travel,Business,2296,4,4,4,4,5,4,4,4,4,4,4,3,4,5,8,68.0,satisfied +95910,83241,Male,disloyal Customer,43,Business travel,Business,1979,3,3,3,1,2,3,2,2,5,3,5,4,5,2,0,0.0,satisfied +95911,104963,Male,Loyal Customer,52,Business travel,Business,337,5,5,5,5,2,4,5,4,4,5,4,5,4,4,8,14.0,satisfied +95912,129653,Female,Loyal Customer,50,Business travel,Business,2958,5,5,5,5,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +95913,11881,Female,Loyal Customer,52,Personal Travel,Eco,912,2,2,2,3,2,3,3,4,3,3,2,3,1,3,149,138.0,neutral or dissatisfied +95914,118534,Female,Loyal Customer,37,Business travel,Business,3018,4,4,4,4,5,5,5,4,4,4,4,4,4,3,6,9.0,satisfied +95915,2037,Male,Loyal Customer,60,Business travel,Business,812,1,1,1,1,5,5,5,5,5,5,5,5,5,3,1,0.0,satisfied +95916,57936,Female,disloyal Customer,27,Business travel,Business,437,4,4,4,3,5,4,5,5,1,4,4,2,4,5,0,0.0,neutral or dissatisfied +95917,9991,Male,Loyal Customer,51,Personal Travel,Eco,457,1,4,1,5,4,1,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +95918,66445,Female,Loyal Customer,44,Business travel,Business,3459,5,5,5,5,3,4,4,1,1,2,1,4,1,5,0,0.0,satisfied +95919,87179,Female,Loyal Customer,36,Business travel,Eco,946,4,3,3,3,4,4,4,4,2,3,3,1,3,4,24,7.0,neutral or dissatisfied +95920,119880,Female,Loyal Customer,39,Personal Travel,Eco,936,4,5,4,5,4,4,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +95921,79397,Female,Loyal Customer,16,Business travel,Business,2486,4,2,2,2,4,4,4,4,2,5,4,2,3,4,66,47.0,neutral or dissatisfied +95922,105415,Male,disloyal Customer,42,Business travel,Business,452,5,5,5,1,5,5,1,5,4,5,5,4,4,5,93,83.0,satisfied +95923,78923,Female,disloyal Customer,38,Business travel,Business,500,4,4,4,3,1,4,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +95924,52196,Male,Loyal Customer,33,Business travel,Business,598,3,3,3,3,5,5,5,5,3,2,4,5,1,5,0,0.0,satisfied +95925,131,Female,disloyal Customer,28,Business travel,Business,562,3,3,3,4,5,3,5,5,1,4,3,1,3,5,115,116.0,neutral or dissatisfied +95926,22638,Female,Loyal Customer,54,Personal Travel,Eco,300,4,4,4,5,5,3,1,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +95927,84901,Male,Loyal Customer,52,Personal Travel,Eco,481,4,2,5,1,3,5,3,3,3,5,1,1,2,3,19,8.0,neutral or dissatisfied +95928,89368,Female,disloyal Customer,21,Business travel,Eco,1377,3,4,4,4,2,3,2,2,3,3,3,4,5,2,5,0.0,neutral or dissatisfied +95929,36932,Male,disloyal Customer,18,Business travel,Eco,867,4,5,5,3,2,5,2,2,1,3,3,2,3,2,126,111.0,neutral or dissatisfied +95930,29259,Female,Loyal Customer,9,Business travel,Business,2377,1,1,1,1,5,5,5,5,5,3,1,5,5,5,0,0.0,satisfied +95931,83783,Male,Loyal Customer,52,Business travel,Business,3697,2,2,2,2,3,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +95932,79415,Female,Loyal Customer,28,Personal Travel,Eco,502,2,4,5,3,2,5,5,2,4,3,3,4,2,2,3,0.0,neutral or dissatisfied +95933,29710,Male,Loyal Customer,35,Business travel,Eco,2304,4,5,5,5,4,4,4,4,3,2,4,5,2,4,0,0.0,satisfied +95934,10746,Female,Loyal Customer,24,Business travel,Eco,295,2,3,3,3,2,2,3,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +95935,127572,Male,Loyal Customer,57,Personal Travel,Eco,1670,1,3,1,4,4,1,4,4,3,1,4,1,4,4,0,0.0,neutral or dissatisfied +95936,95065,Female,Loyal Customer,38,Personal Travel,Eco,248,2,5,2,5,5,2,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +95937,81435,Female,Loyal Customer,67,Personal Travel,Eco,448,4,4,5,5,4,5,4,1,1,5,1,3,1,3,3,0.0,neutral or dissatisfied +95938,121780,Female,Loyal Customer,46,Business travel,Business,449,3,3,3,3,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +95939,90756,Male,Loyal Customer,25,Business travel,Business,3257,5,5,5,5,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +95940,24302,Male,Loyal Customer,27,Business travel,Eco Plus,170,4,3,3,3,4,4,4,4,3,1,3,5,4,4,0,6.0,satisfied +95941,39781,Male,Loyal Customer,52,Personal Travel,Eco,521,2,4,2,3,1,2,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +95942,116727,Male,Loyal Customer,74,Business travel,Eco Plus,447,5,3,3,3,5,5,5,5,2,5,1,2,4,5,1,0.0,satisfied +95943,121297,Male,Loyal Customer,53,Business travel,Business,1732,4,4,4,4,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +95944,81198,Female,Loyal Customer,52,Business travel,Business,1426,1,1,1,1,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +95945,109334,Male,Loyal Customer,66,Personal Travel,Eco,1072,1,4,1,3,4,1,4,4,4,3,4,5,5,4,12,10.0,neutral or dissatisfied +95946,69593,Male,Loyal Customer,29,Personal Travel,Eco,2475,3,1,3,3,3,3,3,1,3,3,3,3,1,3,0,0.0,neutral or dissatisfied +95947,73390,Female,disloyal Customer,22,Business travel,Eco,1012,1,1,1,4,1,1,5,1,4,1,4,1,3,1,0,0.0,neutral or dissatisfied +95948,95878,Male,Loyal Customer,58,Business travel,Eco,759,2,4,4,4,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +95949,111579,Female,Loyal Customer,52,Personal Travel,Eco,775,4,5,4,2,3,5,4,3,3,4,5,3,3,5,0,0.0,satisfied +95950,20598,Male,Loyal Customer,54,Business travel,Eco Plus,206,2,5,5,5,2,2,2,2,4,1,4,4,3,2,0,0.0,neutral or dissatisfied +95951,109299,Female,disloyal Customer,25,Business travel,Eco,1188,2,2,2,4,5,2,5,5,4,2,3,1,4,5,0,12.0,neutral or dissatisfied +95952,105013,Male,disloyal Customer,24,Business travel,Eco,255,2,0,2,1,5,2,5,5,3,5,4,5,4,5,16,22.0,neutral or dissatisfied +95953,25508,Female,disloyal Customer,20,Business travel,Eco,481,1,2,1,2,1,1,1,1,4,5,3,1,2,1,93,82.0,neutral or dissatisfied +95954,48007,Male,Loyal Customer,61,Business travel,Eco Plus,384,4,5,5,5,4,4,4,4,4,1,1,3,4,4,0,0.0,satisfied +95955,29109,Male,Loyal Customer,31,Personal Travel,Eco,697,4,3,4,3,4,4,5,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +95956,74999,Male,Loyal Customer,47,Business travel,Business,2454,4,4,4,4,2,3,5,4,4,5,4,3,4,4,1,0.0,satisfied +95957,108859,Male,disloyal Customer,22,Business travel,Eco,943,1,1,1,4,1,1,1,1,2,4,4,4,4,1,13,42.0,neutral or dissatisfied +95958,66806,Male,Loyal Customer,43,Personal Travel,Business,731,3,5,3,4,1,1,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +95959,108208,Male,Loyal Customer,40,Business travel,Eco,777,1,2,4,4,1,1,1,1,1,1,3,2,3,1,5,0.0,neutral or dissatisfied +95960,4769,Female,disloyal Customer,26,Business travel,Business,403,5,0,5,4,1,5,1,1,3,5,4,5,4,1,0,0.0,satisfied +95961,21762,Female,Loyal Customer,36,Personal Travel,Business,341,5,5,5,1,5,4,4,2,2,5,2,4,2,4,0,0.0,satisfied +95962,47505,Female,Loyal Customer,47,Personal Travel,Eco,590,3,5,3,3,4,4,4,2,2,3,2,3,2,3,0,3.0,neutral or dissatisfied +95963,111417,Female,Loyal Customer,33,Business travel,Business,896,4,4,4,4,3,4,5,5,5,5,5,4,5,4,29,18.0,satisfied +95964,2139,Female,Loyal Customer,10,Personal Travel,Eco,431,3,5,4,2,4,4,4,4,5,4,5,4,5,4,1,3.0,neutral or dissatisfied +95965,9402,Female,Loyal Customer,41,Personal Travel,Eco,182,3,5,3,3,4,3,3,4,4,1,5,1,2,4,0,12.0,neutral or dissatisfied +95966,8804,Male,disloyal Customer,26,Business travel,Eco,552,4,1,4,3,3,4,2,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +95967,107814,Male,disloyal Customer,26,Business travel,Business,349,3,3,3,4,2,3,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +95968,6070,Female,Loyal Customer,34,Personal Travel,Eco,925,2,1,2,4,2,2,2,2,1,1,4,4,4,2,0,0.0,neutral or dissatisfied +95969,72439,Male,Loyal Customer,47,Business travel,Business,1121,1,1,3,1,3,5,5,5,5,5,5,5,5,4,14,27.0,satisfied +95970,106323,Male,Loyal Customer,49,Business travel,Business,2516,3,3,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +95971,78887,Male,disloyal Customer,28,Business travel,Business,1727,2,2,2,3,2,2,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +95972,83559,Female,Loyal Customer,27,Personal Travel,Eco,1865,3,1,4,3,4,4,4,1,3,3,4,4,4,4,98,138.0,neutral or dissatisfied +95973,91193,Male,Loyal Customer,63,Personal Travel,Eco,515,1,4,1,3,5,1,5,5,4,5,3,1,5,5,0,2.0,neutral or dissatisfied +95974,109926,Male,Loyal Customer,52,Personal Travel,Eco,1079,1,4,1,5,1,1,1,1,3,2,5,3,4,1,27,10.0,neutral or dissatisfied +95975,68812,Female,Loyal Customer,27,Personal Travel,Eco,1021,3,3,3,4,2,3,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +95976,129366,Male,Loyal Customer,52,Business travel,Business,2454,2,4,4,4,1,2,3,2,2,2,2,4,2,1,0,5.0,neutral or dissatisfied +95977,16601,Female,disloyal Customer,27,Business travel,Eco,1008,3,3,3,1,4,3,4,4,2,2,4,1,2,4,0,0.0,neutral or dissatisfied +95978,47964,Male,Loyal Customer,32,Personal Travel,Eco,838,2,4,3,4,3,3,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +95979,54545,Female,Loyal Customer,31,Personal Travel,Eco,925,3,5,2,4,5,2,5,5,1,5,3,1,5,5,28,32.0,neutral or dissatisfied +95980,126798,Female,disloyal Customer,41,Business travel,Business,2125,1,1,1,3,2,1,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +95981,75369,Male,disloyal Customer,39,Business travel,Business,2342,3,3,3,1,4,3,4,4,4,2,3,4,5,4,0,0.0,neutral or dissatisfied +95982,31881,Female,Loyal Customer,62,Personal Travel,Eco Plus,4983,3,2,3,3,3,4,4,2,1,3,4,4,1,4,0,0.0,neutral or dissatisfied +95983,19344,Female,Loyal Customer,16,Personal Travel,Eco,694,3,4,3,4,3,5,5,4,3,5,4,5,4,5,201,180.0,neutral or dissatisfied +95984,41603,Female,Loyal Customer,39,Personal Travel,Eco,1242,1,4,1,1,3,1,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +95985,9319,Male,Loyal Customer,59,Business travel,Eco,542,2,5,5,5,2,2,2,2,3,1,3,2,3,2,27,16.0,neutral or dissatisfied +95986,47594,Male,Loyal Customer,50,Business travel,Eco,1211,5,1,3,1,5,5,5,5,1,5,3,1,5,5,0,0.0,satisfied +95987,102502,Male,Loyal Customer,59,Personal Travel,Eco,223,5,4,5,3,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +95988,72240,Male,Loyal Customer,56,Business travel,Business,2771,1,4,4,4,1,4,4,1,1,1,1,1,1,1,68,68.0,neutral or dissatisfied +95989,43888,Female,Loyal Customer,31,Business travel,Eco,114,0,0,0,3,2,0,2,2,1,2,2,3,4,2,0,0.0,satisfied +95990,88536,Male,Loyal Customer,31,Personal Travel,Eco,581,2,4,2,3,2,2,2,2,3,1,3,1,4,2,8,7.0,neutral or dissatisfied +95991,81825,Female,Loyal Customer,14,Personal Travel,Eco,1416,3,4,3,5,3,3,3,3,4,5,3,1,1,3,0,1.0,neutral or dissatisfied +95992,3667,Female,disloyal Customer,24,Business travel,Business,431,5,5,5,1,3,5,3,3,4,2,5,5,5,3,29,2.0,satisfied +95993,33821,Female,Loyal Customer,46,Personal Travel,Eco,1521,1,2,1,4,5,4,3,4,4,1,4,3,4,4,70,63.0,neutral or dissatisfied +95994,45352,Male,Loyal Customer,57,Personal Travel,Eco,222,2,5,2,3,5,2,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +95995,40943,Male,Loyal Customer,33,Personal Travel,Eco Plus,588,4,4,4,2,5,4,5,5,5,1,1,4,2,5,0,0.0,neutral or dissatisfied +95996,100090,Female,Loyal Customer,54,Business travel,Business,2391,5,5,3,5,2,5,4,4,4,5,4,3,4,5,3,1.0,satisfied +95997,17146,Female,disloyal Customer,25,Business travel,Eco,926,2,2,2,3,5,2,5,5,2,3,4,3,3,5,0,27.0,neutral or dissatisfied +95998,39173,Female,Loyal Customer,39,Business travel,Business,3948,2,3,3,3,2,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +95999,73662,Female,disloyal Customer,38,Business travel,Business,204,4,4,4,4,2,4,2,2,3,5,5,5,4,2,0,0.0,satisfied +96000,31804,Male,Loyal Customer,43,Personal Travel,Eco Plus,2677,4,3,4,2,4,3,3,4,1,3,2,3,3,3,0,0.0,neutral or dissatisfied +96001,38179,Female,Loyal Customer,13,Personal Travel,Eco,1185,1,2,1,3,3,1,3,3,4,1,3,2,3,3,16,0.0,neutral or dissatisfied +96002,50491,Male,Loyal Customer,59,Personal Travel,Eco,262,4,5,4,2,3,4,3,3,5,2,1,2,2,3,6,7.0,satisfied +96003,118786,Female,Loyal Customer,65,Personal Travel,Eco,304,1,2,1,4,2,4,4,5,5,1,5,2,5,4,18,15.0,neutral or dissatisfied +96004,61766,Male,Loyal Customer,40,Personal Travel,Eco,1346,2,5,2,4,1,2,4,1,5,5,4,4,4,1,0,0.0,neutral or dissatisfied +96005,85205,Female,Loyal Customer,45,Business travel,Business,3607,2,2,3,2,5,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +96006,129211,Female,Loyal Customer,31,Personal Travel,Eco,2419,1,4,1,4,2,1,4,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +96007,72900,Female,Loyal Customer,46,Business travel,Business,1667,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +96008,9023,Male,Loyal Customer,47,Business travel,Business,108,1,1,1,1,5,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +96009,64638,Male,disloyal Customer,69,Business travel,Business,469,2,2,2,4,2,2,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +96010,13587,Female,Loyal Customer,24,Personal Travel,Eco,106,2,4,2,2,3,2,3,3,5,1,2,4,3,3,0,0.0,neutral or dissatisfied +96011,23963,Male,Loyal Customer,52,Personal Travel,Eco,639,2,4,2,2,4,2,4,4,3,3,5,5,4,4,62,57.0,neutral or dissatisfied +96012,127266,Female,Loyal Customer,44,Business travel,Business,3948,3,2,2,2,3,3,3,3,3,3,3,3,3,2,18,11.0,neutral or dissatisfied +96013,3398,Female,disloyal Customer,47,Business travel,Eco,213,3,3,3,4,2,3,2,2,5,2,5,3,1,2,9,16.0,neutral or dissatisfied +96014,24785,Male,Loyal Customer,35,Personal Travel,Eco,432,1,5,1,2,3,1,3,3,4,3,4,4,5,3,10,28.0,neutral or dissatisfied +96015,27020,Male,Loyal Customer,47,Personal Travel,Eco,954,4,3,5,3,4,5,4,4,2,4,4,1,3,4,0,0.0,neutral or dissatisfied +96016,74504,Female,Loyal Customer,49,Business travel,Business,3351,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +96017,9270,Male,disloyal Customer,24,Business travel,Business,441,4,0,4,3,2,4,2,2,5,2,4,4,5,2,0,0.0,satisfied +96018,89643,Male,Loyal Customer,16,Business travel,Business,950,3,1,3,1,3,3,3,3,1,5,3,2,2,3,19,6.0,neutral or dissatisfied +96019,116151,Female,Loyal Customer,68,Personal Travel,Eco,342,2,4,2,4,2,4,3,5,5,2,3,2,5,4,0,0.0,neutral or dissatisfied +96020,55979,Female,Loyal Customer,64,Personal Travel,Eco,1620,4,3,4,4,3,2,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +96021,39027,Male,Loyal Customer,8,Personal Travel,Eco,113,2,2,0,3,2,0,1,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +96022,101555,Male,Loyal Customer,67,Personal Travel,Eco,345,1,4,1,3,4,1,4,4,4,2,5,5,4,4,26,17.0,neutral or dissatisfied +96023,55138,Male,Loyal Customer,16,Personal Travel,Eco,1379,3,4,3,4,2,3,2,2,5,5,4,4,4,2,2,4.0,neutral or dissatisfied +96024,99236,Male,Loyal Customer,53,Business travel,Business,3344,1,1,1,1,4,4,5,4,4,4,4,3,4,5,2,4.0,satisfied +96025,35794,Male,Loyal Customer,18,Personal Travel,Eco,200,2,4,2,3,3,2,3,3,2,1,3,3,4,3,0,0.0,neutral or dissatisfied +96026,3865,Female,Loyal Customer,45,Personal Travel,Business,213,2,0,2,3,3,4,4,1,1,2,1,4,1,3,47,50.0,neutral or dissatisfied +96027,41761,Male,disloyal Customer,28,Business travel,Eco,491,1,4,1,3,4,1,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +96028,31216,Female,Loyal Customer,27,Personal Travel,Eco,628,2,4,2,5,2,2,2,2,5,2,5,4,4,2,20,56.0,neutral or dissatisfied +96029,85349,Male,Loyal Customer,60,Business travel,Business,2131,1,1,1,1,2,5,4,4,4,4,4,4,4,3,12,0.0,satisfied +96030,24300,Male,Loyal Customer,48,Business travel,Eco Plus,147,5,4,4,4,5,5,5,5,5,3,1,2,4,5,0,0.0,satisfied +96031,55244,Female,Loyal Customer,60,Personal Travel,Eco,1009,2,5,2,3,1,1,1,3,3,2,3,4,3,3,0,1.0,neutral or dissatisfied +96032,38156,Female,Loyal Customer,69,Personal Travel,Eco,1121,1,4,1,1,4,3,4,2,2,1,1,4,2,3,32,15.0,neutral or dissatisfied +96033,23644,Male,Loyal Customer,33,Business travel,Business,2358,2,2,2,2,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +96034,992,Male,Loyal Customer,55,Business travel,Business,1920,5,1,5,5,4,2,4,4,4,4,4,2,4,5,7,5.0,satisfied +96035,25647,Male,Loyal Customer,41,Personal Travel,Eco,526,3,5,3,2,2,3,5,2,4,5,5,4,5,2,7,0.0,neutral or dissatisfied +96036,70711,Female,Loyal Customer,25,Business travel,Business,3491,1,1,1,1,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +96037,47319,Male,Loyal Customer,41,Business travel,Eco,599,4,5,5,5,4,4,4,4,2,1,4,5,3,4,79,69.0,satisfied +96038,116811,Male,disloyal Customer,33,Business travel,Business,370,4,5,5,3,3,5,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +96039,32097,Female,disloyal Customer,23,Business travel,Eco,163,5,0,5,4,3,5,3,3,5,3,5,1,3,3,0,0.0,satisfied +96040,116573,Male,Loyal Customer,55,Business travel,Business,2682,3,3,3,3,4,5,5,4,4,5,4,4,4,4,6,1.0,satisfied +96041,113145,Male,disloyal Customer,30,Business travel,Business,677,1,1,1,4,3,1,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +96042,50973,Female,Loyal Customer,42,Personal Travel,Eco,209,4,4,4,4,2,4,3,3,3,4,3,2,3,2,77,82.0,neutral or dissatisfied +96043,29841,Female,Loyal Customer,51,Business travel,Business,3859,4,4,5,4,5,5,5,5,5,5,5,1,5,2,0,0.0,satisfied +96044,125812,Female,Loyal Customer,60,Business travel,Eco,920,2,5,5,5,4,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +96045,76646,Male,Loyal Customer,20,Personal Travel,Eco,516,1,5,1,3,4,1,4,4,3,2,5,5,4,4,38,55.0,neutral or dissatisfied +96046,6914,Male,Loyal Customer,33,Personal Travel,Eco,265,4,1,0,4,1,0,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +96047,54446,Female,disloyal Customer,49,Business travel,Eco Plus,305,4,5,5,2,1,4,1,1,4,4,2,1,5,1,0,0.0,neutral or dissatisfied +96048,119205,Female,disloyal Customer,40,Business travel,Business,257,5,5,5,5,5,5,4,5,5,4,5,5,4,5,0,1.0,satisfied +96049,78602,Female,Loyal Customer,51,Personal Travel,Eco,2454,1,5,1,2,5,3,5,5,5,1,4,3,5,5,0,0.0,neutral or dissatisfied +96050,2503,Male,Loyal Customer,45,Business travel,Business,227,2,1,1,1,5,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +96051,58838,Male,Loyal Customer,21,Personal Travel,Eco Plus,1012,3,2,3,2,4,3,4,4,1,2,3,3,2,4,12,12.0,neutral or dissatisfied +96052,30472,Male,Loyal Customer,45,Personal Travel,Business,377,1,5,1,4,5,5,5,3,3,1,3,5,3,3,86,60.0,neutral or dissatisfied +96053,105643,Female,Loyal Customer,57,Business travel,Business,925,2,2,2,2,2,5,4,4,4,4,4,5,4,4,39,38.0,satisfied +96054,54579,Male,disloyal Customer,23,Business travel,Business,3904,4,0,4,4,4,3,4,5,4,3,5,4,5,4,5,1.0,satisfied +96055,28497,Female,Loyal Customer,63,Personal Travel,Business,2688,1,5,1,2,1,3,3,5,1,4,5,3,4,3,0,20.0,neutral or dissatisfied +96056,73676,Male,Loyal Customer,33,Business travel,Business,204,3,5,4,5,1,1,3,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +96057,73985,Female,disloyal Customer,12,Business travel,Eco,2585,3,3,3,3,3,3,3,3,3,4,4,3,3,3,0,25.0,neutral or dissatisfied +96058,128241,Male,Loyal Customer,63,Personal Travel,Eco,602,2,5,2,4,2,2,2,2,3,4,4,4,4,2,0,0.0,neutral or dissatisfied +96059,88831,Female,Loyal Customer,33,Personal Travel,Eco Plus,515,3,5,3,1,3,3,5,3,3,2,5,4,5,3,1,56.0,neutral or dissatisfied +96060,112034,Male,Loyal Customer,27,Business travel,Business,3615,3,5,3,3,4,4,4,4,3,2,4,3,5,4,31,29.0,satisfied +96061,54523,Male,Loyal Customer,68,Personal Travel,Eco,925,2,2,2,3,4,2,4,4,2,3,3,1,3,4,6,21.0,neutral or dissatisfied +96062,91851,Female,disloyal Customer,35,Personal Travel,Eco,1797,5,4,5,3,2,5,2,2,4,5,4,4,3,2,9,0.0,satisfied +96063,117611,Male,Loyal Customer,39,Business travel,Eco,620,2,3,4,3,2,2,2,2,4,3,3,2,4,2,32,25.0,neutral or dissatisfied +96064,106934,Male,Loyal Customer,57,Business travel,Business,3649,3,3,3,3,4,4,4,4,4,4,4,3,4,3,21,27.0,satisfied +96065,5770,Female,disloyal Customer,18,Business travel,Eco,665,3,3,3,4,4,3,4,4,2,5,4,3,4,4,0,0.0,neutral or dissatisfied +96066,64744,Female,disloyal Customer,27,Business travel,Business,190,4,4,4,3,3,4,3,3,3,5,5,3,5,3,0,0.0,satisfied +96067,28814,Male,Loyal Customer,30,Business travel,Business,2168,4,4,4,4,5,5,5,5,1,3,1,3,2,5,0,0.0,satisfied +96068,27057,Male,Loyal Customer,29,Personal Travel,Eco,1709,2,4,2,2,2,2,2,2,4,1,5,4,3,2,45,28.0,neutral or dissatisfied +96069,86800,Female,Loyal Customer,25,Business travel,Business,1563,5,5,2,5,3,3,3,3,3,2,4,4,4,3,0,0.0,satisfied +96070,25004,Male,Loyal Customer,70,Personal Travel,Eco,692,2,4,2,3,4,2,4,4,5,5,4,3,4,4,31,34.0,neutral or dissatisfied +96071,120978,Female,Loyal Customer,51,Business travel,Business,2568,1,5,5,5,3,4,3,1,1,1,1,4,1,1,46,39.0,neutral or dissatisfied +96072,35153,Male,Loyal Customer,31,Business travel,Business,1668,2,4,4,4,2,2,2,2,2,2,4,1,3,2,50,47.0,neutral or dissatisfied +96073,129361,Male,Loyal Customer,43,Business travel,Business,2454,3,5,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +96074,67187,Female,Loyal Customer,28,Personal Travel,Eco,1121,4,1,4,3,2,4,2,2,2,2,3,4,4,2,84,98.0,satisfied +96075,36738,Female,disloyal Customer,25,Business travel,Eco,1754,4,4,4,3,2,4,2,2,4,4,4,5,2,2,0,0.0,satisfied +96076,106931,Male,Loyal Customer,57,Business travel,Business,937,1,1,1,1,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +96077,34621,Male,Loyal Customer,57,Business travel,Eco,2454,4,5,5,5,4,3,3,5,3,5,3,3,5,3,11,12.0,satisfied +96078,6855,Male,Loyal Customer,72,Business travel,Business,3903,3,5,5,5,3,3,3,3,3,3,3,4,3,3,48,50.0,neutral or dissatisfied +96079,42386,Female,Loyal Customer,26,Personal Travel,Eco,726,2,4,2,3,5,2,5,5,3,5,4,2,4,5,0,0.0,neutral or dissatisfied +96080,9101,Male,Loyal Customer,22,Personal Travel,Business,765,2,5,2,3,2,2,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +96081,89773,Female,Loyal Customer,70,Personal Travel,Eco,1076,4,4,4,5,5,4,5,4,4,4,5,4,4,4,18,21.0,neutral or dissatisfied +96082,102007,Female,disloyal Customer,22,Business travel,Eco,628,3,2,3,3,4,3,4,4,1,2,4,4,4,4,23,28.0,neutral or dissatisfied +96083,65104,Male,Loyal Customer,67,Personal Travel,Eco,354,2,5,2,4,4,2,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +96084,75603,Male,Loyal Customer,43,Personal Travel,Eco,337,4,5,4,3,1,4,1,1,4,2,5,5,5,1,13,6.0,neutral or dissatisfied +96085,78229,Female,Loyal Customer,32,Personal Travel,Eco,153,4,2,4,3,4,4,3,4,2,4,3,3,3,4,0,0.0,satisfied +96086,36240,Female,disloyal Customer,23,Business travel,Business,612,2,1,2,4,2,2,2,2,2,1,3,4,3,2,0,0.0,neutral or dissatisfied +96087,82351,Female,Loyal Customer,17,Business travel,Business,453,1,2,2,2,1,1,1,1,4,4,4,4,4,1,28,44.0,neutral or dissatisfied +96088,25282,Male,Loyal Customer,43,Business travel,Eco,321,3,2,2,2,3,3,3,3,2,2,1,2,3,3,0,0.0,satisfied +96089,20951,Female,disloyal Customer,26,Business travel,Eco,803,1,1,1,2,1,4,5,1,1,3,3,5,2,5,145,126.0,neutral or dissatisfied +96090,26697,Female,Loyal Customer,58,Personal Travel,Eco,404,2,4,2,5,3,4,5,1,1,2,1,4,1,4,14,6.0,neutral or dissatisfied +96091,6186,Male,Loyal Customer,14,Personal Travel,Eco,409,2,4,3,4,4,3,4,4,1,4,4,4,1,4,0,0.0,neutral or dissatisfied +96092,29046,Female,Loyal Customer,25,Personal Travel,Eco,954,3,5,2,2,3,2,3,3,3,4,5,3,4,3,0,8.0,neutral or dissatisfied +96093,51579,Female,disloyal Customer,20,Business travel,Eco,598,4,0,4,4,5,4,4,5,1,2,5,4,1,5,0,,satisfied +96094,32608,Male,Loyal Customer,48,Business travel,Business,2209,3,3,3,3,2,3,1,5,5,5,5,5,5,5,6,3.0,satisfied +96095,35943,Male,disloyal Customer,24,Business travel,Business,231,3,2,3,4,4,3,3,4,4,3,4,2,3,4,45,39.0,neutral or dissatisfied +96096,72643,Female,Loyal Customer,39,Personal Travel,Eco,1121,2,4,2,5,2,2,2,2,4,3,5,4,4,2,0,19.0,neutral or dissatisfied +96097,120459,Female,Loyal Customer,9,Personal Travel,Eco,337,3,1,3,2,3,3,3,3,3,5,2,4,2,3,0,0.0,neutral or dissatisfied +96098,59002,Male,Loyal Customer,45,Business travel,Business,1846,3,3,3,3,4,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +96099,52192,Male,Loyal Customer,33,Business travel,Business,3060,2,2,2,2,4,4,4,4,3,4,3,5,3,4,0,0.0,satisfied +96100,38979,Female,disloyal Customer,36,Business travel,Eco,313,1,0,1,5,1,1,1,1,3,5,1,2,5,1,5,4.0,neutral or dissatisfied +96101,29361,Male,Loyal Customer,11,Business travel,Eco,2409,1,5,5,5,1,4,1,1,4,3,4,1,1,1,0,6.0,neutral or dissatisfied +96102,11044,Female,Loyal Customer,33,Personal Travel,Eco,429,5,4,5,5,4,5,3,4,3,2,1,3,2,4,17,4.0,satisfied +96103,57585,Male,Loyal Customer,41,Business travel,Business,997,5,5,5,5,1,4,1,3,3,5,3,1,3,4,0,0.0,satisfied +96104,52019,Male,Loyal Customer,38,Business travel,Eco,328,2,1,4,4,2,2,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +96105,1371,Female,Loyal Customer,20,Business travel,Business,2868,3,3,3,3,4,4,5,4,5,4,4,3,5,4,0,0.0,satisfied +96106,16594,Female,Loyal Customer,28,Business travel,Business,2320,3,3,3,3,3,4,3,3,3,5,5,3,4,3,39,35.0,satisfied +96107,98998,Female,Loyal Customer,53,Personal Travel,Eco,543,2,5,2,3,3,2,3,1,1,2,1,1,1,3,13,24.0,neutral or dissatisfied +96108,115297,Male,Loyal Customer,46,Business travel,Business,342,5,5,5,5,4,4,5,4,4,4,4,5,4,4,46,37.0,satisfied +96109,21953,Male,disloyal Customer,10,Business travel,Eco,551,3,4,3,4,3,3,3,3,3,3,4,1,4,3,1,0.0,neutral or dissatisfied +96110,7442,Female,Loyal Customer,45,Personal Travel,Eco,552,3,1,3,4,4,5,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +96111,33910,Male,disloyal Customer,36,Business travel,Eco,636,2,3,2,3,1,2,1,1,4,1,2,3,3,1,0,5.0,neutral or dissatisfied +96112,25350,Female,Loyal Customer,42,Personal Travel,Eco,691,2,4,2,1,2,5,4,2,2,2,2,5,2,4,6,0.0,neutral or dissatisfied +96113,32224,Male,Loyal Customer,51,Business travel,Business,3744,1,1,1,1,3,4,5,4,4,4,3,5,4,3,0,0.0,satisfied +96114,17271,Female,Loyal Customer,50,Personal Travel,Eco,1092,3,3,2,4,3,5,2,3,3,2,1,1,3,4,0,0.0,neutral or dissatisfied +96115,24813,Female,Loyal Customer,44,Business travel,Business,2286,1,1,1,1,2,4,3,5,5,5,5,1,5,2,0,0.0,satisfied +96116,127729,Female,Loyal Customer,44,Business travel,Business,2350,2,2,2,2,4,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +96117,97749,Female,disloyal Customer,30,Business travel,Eco,587,2,1,2,4,5,2,5,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +96118,52112,Male,Loyal Customer,7,Personal Travel,Eco,639,3,2,3,4,1,3,1,1,3,1,4,4,4,1,18,0.0,neutral or dissatisfied +96119,15134,Male,disloyal Customer,28,Business travel,Eco,1042,1,1,1,2,5,1,5,5,4,2,1,2,3,5,0,0.0,neutral or dissatisfied +96120,93524,Female,Loyal Customer,44,Business travel,Business,1218,1,1,5,1,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +96121,122325,Female,Loyal Customer,48,Business travel,Eco Plus,546,1,4,4,4,5,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +96122,60051,Female,Loyal Customer,45,Business travel,Eco Plus,665,3,4,4,4,3,4,4,3,3,3,3,2,3,1,67,47.0,neutral or dissatisfied +96123,26646,Female,Loyal Customer,25,Business travel,Business,2238,2,3,3,3,2,2,2,2,4,1,3,4,3,2,10,9.0,neutral or dissatisfied +96124,81775,Female,Loyal Customer,45,Business travel,Business,3063,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +96125,60774,Female,Loyal Customer,58,Personal Travel,Eco,628,5,1,5,3,1,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +96126,75148,Male,disloyal Customer,28,Business travel,Business,1157,5,5,5,3,5,5,5,5,3,3,5,4,4,5,0,18.0,satisfied +96127,109487,Male,Loyal Customer,34,Business travel,Business,834,3,3,3,3,3,4,4,5,5,4,5,4,5,5,2,0.0,satisfied +96128,41768,Male,Loyal Customer,35,Business travel,Business,3024,2,1,1,1,3,4,4,2,2,2,2,3,2,2,21,12.0,neutral or dissatisfied +96129,99383,Male,Loyal Customer,40,Business travel,Business,2084,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +96130,28035,Male,Loyal Customer,29,Business travel,Business,2537,3,5,3,3,3,3,3,3,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +96131,16252,Male,Loyal Customer,45,Business travel,Eco,748,2,3,3,3,2,2,2,2,3,4,4,5,2,2,0,3.0,satisfied +96132,31912,Male,disloyal Customer,24,Business travel,Business,101,0,0,0,1,5,0,4,5,3,2,5,4,4,5,0,0.0,satisfied +96133,91241,Male,Loyal Customer,22,Personal Travel,Eco,444,4,4,4,3,2,4,2,2,2,5,4,1,3,2,0,0.0,satisfied +96134,85136,Male,Loyal Customer,19,Business travel,Business,2411,3,3,3,3,3,3,3,3,5,4,4,3,5,3,23,14.0,satisfied +96135,29325,Male,Loyal Customer,20,Personal Travel,Eco,933,2,5,2,2,4,2,5,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +96136,45895,Male,Loyal Customer,42,Business travel,Eco,913,4,1,1,1,4,4,4,4,2,3,2,4,1,4,0,0.0,satisfied +96137,44422,Male,Loyal Customer,30,Business travel,Business,2845,3,3,3,3,3,2,3,3,2,2,4,2,3,3,118,107.0,neutral or dissatisfied +96138,93842,Male,Loyal Customer,53,Personal Travel,Eco,391,1,4,1,1,2,1,2,2,5,5,1,4,3,2,25,15.0,neutral or dissatisfied +96139,9285,Female,Loyal Customer,70,Business travel,Business,3598,3,3,5,3,3,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +96140,14288,Female,Loyal Customer,44,Business travel,Eco,395,5,5,5,5,3,1,1,5,5,5,5,3,5,2,6,8.0,satisfied +96141,11377,Male,Loyal Customer,51,Business travel,Business,2843,4,4,4,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +96142,65113,Male,Loyal Customer,60,Personal Travel,Eco,190,2,1,2,4,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +96143,34897,Male,Loyal Customer,55,Business travel,Eco,187,5,4,4,4,5,5,5,5,4,2,3,5,4,5,0,0.0,satisfied +96144,97957,Female,disloyal Customer,30,Business travel,Eco,684,2,2,2,3,3,2,3,3,2,4,4,1,3,3,8,7.0,neutral or dissatisfied +96145,61950,Female,disloyal Customer,40,Business travel,Business,2052,3,3,3,4,3,3,3,3,4,5,2,1,3,3,0,2.0,neutral or dissatisfied +96146,47901,Female,Loyal Customer,32,Business travel,Business,329,1,1,1,1,5,5,5,5,5,3,1,5,5,5,0,0.0,satisfied +96147,33588,Male,Loyal Customer,44,Business travel,Business,1896,1,1,1,1,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +96148,63182,Male,disloyal Customer,20,Business travel,Eco,447,2,5,2,5,4,2,4,4,3,4,5,4,5,4,7,3.0,neutral or dissatisfied +96149,116152,Female,Loyal Customer,35,Personal Travel,Eco,333,2,4,2,5,2,2,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +96150,100294,Male,Loyal Customer,45,Business travel,Business,1165,2,2,3,2,4,4,4,5,5,4,5,3,5,4,65,91.0,satisfied +96151,82181,Female,Loyal Customer,11,Personal Travel,Eco Plus,237,1,4,1,4,2,1,3,2,3,1,4,3,3,2,12,7.0,neutral or dissatisfied +96152,127791,Female,disloyal Customer,28,Business travel,Business,1262,2,2,2,5,3,2,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +96153,29427,Female,Loyal Customer,42,Business travel,Eco,2149,5,5,4,4,3,5,3,5,5,5,5,4,5,3,0,0.0,satisfied +96154,116732,Male,Loyal Customer,55,Personal Travel,Eco Plus,308,2,5,2,3,5,2,5,5,3,5,5,5,5,5,71,71.0,neutral or dissatisfied +96155,34237,Male,Loyal Customer,22,Business travel,Eco Plus,1189,5,1,1,1,5,5,3,5,5,2,1,4,1,5,0,0.0,satisfied +96156,34863,Female,Loyal Customer,42,Business travel,Business,2248,5,5,3,5,3,4,1,5,5,5,5,1,5,1,1,0.0,satisfied +96157,76677,Female,Loyal Customer,67,Personal Travel,Eco,516,3,3,3,2,5,3,2,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +96158,74864,Male,Loyal Customer,55,Personal Travel,Eco,1995,4,3,4,3,2,4,2,2,1,5,4,1,3,2,4,0.0,neutral or dissatisfied +96159,78087,Male,Loyal Customer,41,Personal Travel,Eco Plus,152,3,4,3,1,1,3,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +96160,53265,Female,Loyal Customer,33,Business travel,Eco,811,5,2,2,2,5,5,5,5,4,4,3,3,4,5,38,52.0,satisfied +96161,42325,Female,Loyal Customer,70,Personal Travel,Eco,834,3,5,3,3,2,4,2,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +96162,53795,Male,Loyal Customer,41,Business travel,Business,140,5,3,5,5,1,5,2,5,5,5,3,5,5,1,21,17.0,satisfied +96163,23325,Male,Loyal Customer,31,Business travel,Business,3497,2,2,2,2,4,5,4,4,4,5,2,3,4,4,3,2.0,satisfied +96164,1554,Female,Loyal Customer,63,Personal Travel,Eco,922,1,5,1,1,2,5,4,2,2,1,2,4,2,5,8,9.0,neutral or dissatisfied +96165,72725,Female,Loyal Customer,77,Business travel,Eco Plus,585,2,2,2,2,5,4,3,2,2,2,2,4,2,4,49,107.0,neutral or dissatisfied +96166,44604,Male,Loyal Customer,25,Business travel,Business,566,3,1,3,3,2,2,2,2,4,1,4,1,4,2,36,11.0,satisfied +96167,113637,Male,Loyal Customer,7,Personal Travel,Eco,488,1,4,1,5,2,1,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +96168,120928,Female,Loyal Customer,53,Business travel,Business,1807,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +96169,94982,Male,Loyal Customer,38,Business travel,Business,3496,4,5,5,5,4,3,3,1,1,2,4,1,1,1,4,0.0,neutral or dissatisfied +96170,128396,Male,Loyal Customer,23,Business travel,Business,647,3,5,5,5,3,3,3,3,3,3,3,1,3,3,22,27.0,neutral or dissatisfied +96171,113244,Female,Loyal Customer,46,Personal Travel,Business,226,5,5,5,1,2,4,4,2,2,5,2,4,2,4,0,0.0,satisfied +96172,38808,Male,Loyal Customer,37,Personal Travel,Eco,354,3,5,3,2,5,3,1,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +96173,66062,Male,Loyal Customer,64,Personal Travel,Eco,1055,1,2,1,3,2,1,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +96174,33023,Male,Loyal Customer,19,Personal Travel,Eco,102,1,4,0,3,5,0,5,5,2,2,3,5,4,5,0,0.0,neutral or dissatisfied +96175,116860,Female,Loyal Customer,36,Business travel,Business,1789,4,4,4,4,3,4,4,5,5,5,5,5,5,3,23,25.0,satisfied +96176,88567,Male,Loyal Customer,16,Personal Travel,Eco,581,4,4,4,2,1,4,1,1,3,5,5,4,4,1,0,0.0,satisfied +96177,94009,Female,disloyal Customer,22,Business travel,Business,239,5,5,5,4,5,5,5,5,4,2,4,3,4,5,0,0.0,satisfied +96178,83640,Female,disloyal Customer,34,Business travel,Business,577,2,2,2,1,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +96179,112273,Female,Loyal Customer,44,Business travel,Business,1106,1,1,1,1,4,4,4,1,1,1,1,3,1,4,21,21.0,neutral or dissatisfied +96180,29476,Male,Loyal Customer,37,Business travel,Eco,1107,3,4,4,4,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +96181,55914,Male,Loyal Customer,12,Personal Travel,Eco,473,5,5,5,3,4,5,4,4,5,3,4,3,4,4,4,9.0,satisfied +96182,98302,Female,Loyal Customer,46,Business travel,Business,1188,5,5,5,5,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +96183,119817,Female,Loyal Customer,57,Business travel,Business,2583,2,2,2,2,4,4,4,4,4,4,4,5,4,4,14,16.0,satisfied +96184,69320,Female,Loyal Customer,40,Business travel,Business,1089,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +96185,79733,Female,disloyal Customer,49,Business travel,Eco Plus,712,2,2,2,4,1,2,5,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +96186,75998,Female,Loyal Customer,58,Personal Travel,Eco Plus,297,5,4,5,4,5,4,5,3,3,5,3,4,3,3,0,0.0,satisfied +96187,114230,Male,Loyal Customer,24,Business travel,Business,850,5,5,5,5,4,4,4,4,5,3,5,5,5,4,11,5.0,satisfied +96188,100180,Male,Loyal Customer,44,Personal Travel,Eco,523,3,4,3,1,3,3,3,3,2,2,5,5,4,3,0,0.0,neutral or dissatisfied +96189,101609,Male,Loyal Customer,26,Business travel,Business,1701,2,2,2,2,3,4,3,3,3,2,4,3,5,3,0,0.0,satisfied +96190,3718,Female,Loyal Customer,28,Personal Travel,Eco,431,4,1,4,3,2,4,2,2,2,2,4,2,3,2,0,0.0,neutral or dissatisfied +96191,61511,Male,Loyal Customer,43,Personal Travel,Eco,2288,5,1,5,2,1,5,1,1,3,4,2,4,1,1,32,22.0,satisfied +96192,56410,Female,disloyal Customer,26,Business travel,Business,719,5,5,5,3,4,5,4,4,4,4,5,4,5,4,6,5.0,satisfied +96193,40022,Male,Loyal Customer,72,Business travel,Business,3808,3,2,2,2,5,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +96194,76648,Female,Loyal Customer,25,Personal Travel,Eco,547,3,3,3,3,4,3,4,4,1,2,3,3,3,4,27,35.0,neutral or dissatisfied +96195,53381,Female,Loyal Customer,48,Personal Travel,Eco,1452,3,4,3,2,1,2,4,2,2,3,2,2,2,5,0,0.0,neutral or dissatisfied +96196,14141,Female,Loyal Customer,42,Personal Travel,Eco,413,2,1,4,4,2,3,4,2,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +96197,111598,Male,Loyal Customer,28,Business travel,Eco Plus,883,1,1,1,1,1,2,1,1,2,2,4,4,4,1,23,9.0,neutral or dissatisfied +96198,83880,Female,Loyal Customer,57,Business travel,Business,1670,5,5,5,5,3,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +96199,94673,Male,Loyal Customer,71,Business travel,Eco,239,1,4,5,4,1,1,1,1,4,3,3,4,3,1,0,0.0,neutral or dissatisfied +96200,86480,Male,Loyal Customer,7,Personal Travel,Eco,762,4,5,5,3,4,5,4,4,2,1,2,3,2,4,0,0.0,satisfied +96201,127424,Female,Loyal Customer,45,Personal Travel,Eco,872,1,1,1,3,5,3,3,3,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +96202,123783,Male,disloyal Customer,22,Business travel,Business,544,0,5,0,4,1,0,1,1,4,3,4,3,4,1,0,20.0,satisfied +96203,82492,Female,Loyal Customer,13,Business travel,Business,2827,2,1,5,5,2,2,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +96204,42485,Female,Loyal Customer,44,Business travel,Business,2565,2,2,2,2,1,4,4,2,2,2,2,1,2,4,0,4.0,neutral or dissatisfied +96205,57550,Female,Loyal Customer,53,Business travel,Business,1597,5,5,5,5,4,3,4,4,4,5,4,5,4,3,1,7.0,satisfied +96206,41050,Female,Loyal Customer,16,Personal Travel,Eco,1086,2,3,2,4,4,2,4,4,5,1,1,2,1,4,0,3.0,neutral or dissatisfied +96207,31516,Male,Loyal Customer,22,Business travel,Eco,853,4,4,4,4,4,4,3,4,2,5,2,4,2,4,1,0.0,neutral or dissatisfied +96208,121970,Female,Loyal Customer,34,Business travel,Business,130,4,5,5,5,3,4,3,2,2,2,4,2,2,4,0,0.0,neutral or dissatisfied +96209,68547,Male,Loyal Customer,26,Personal Travel,Eco,1013,2,1,2,3,5,2,5,5,4,2,2,3,3,5,0,0.0,neutral or dissatisfied +96210,118328,Male,disloyal Customer,23,Business travel,Eco,602,3,2,3,1,4,3,4,4,4,2,1,2,2,4,3,0.0,neutral or dissatisfied +96211,120906,Male,disloyal Customer,20,Business travel,Eco,920,2,2,2,5,1,2,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +96212,19842,Female,Loyal Customer,9,Personal Travel,Business,693,2,4,2,3,3,2,3,3,3,4,5,5,5,3,54,37.0,neutral or dissatisfied +96213,47609,Female,Loyal Customer,46,Business travel,Eco,1211,5,5,4,4,3,2,4,5,5,5,5,2,5,3,18,11.0,satisfied +96214,38917,Male,disloyal Customer,33,Business travel,Eco,205,3,2,3,3,2,3,2,2,1,2,3,4,3,2,0,17.0,neutral or dissatisfied +96215,26353,Female,Loyal Customer,56,Business travel,Business,991,4,4,1,4,2,3,4,4,4,4,4,4,4,1,40,37.0,neutral or dissatisfied +96216,6735,Female,Loyal Customer,60,Business travel,Business,1776,4,4,4,4,4,4,5,3,3,4,3,3,3,4,0,0.0,satisfied +96217,20553,Male,Loyal Customer,39,Business travel,Business,1597,3,3,4,3,3,2,1,4,4,4,4,2,4,5,0,0.0,satisfied +96218,126324,Female,Loyal Customer,25,Personal Travel,Eco,631,1,5,1,4,4,1,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +96219,46786,Male,Loyal Customer,23,Business travel,Business,948,5,5,5,5,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +96220,93049,Female,Loyal Customer,34,Business travel,Eco Plus,317,3,1,1,1,3,3,3,3,2,2,4,1,4,3,40,36.0,neutral or dissatisfied +96221,68329,Female,Loyal Customer,51,Personal Travel,Eco,2165,0,5,0,1,5,3,5,5,5,0,3,4,5,3,10,6.0,satisfied +96222,128653,Male,Loyal Customer,22,Personal Travel,Business,2419,2,1,2,2,5,2,5,5,2,2,3,3,3,5,9,0.0,neutral or dissatisfied +96223,19467,Male,Loyal Customer,39,Business travel,Business,84,0,3,0,2,5,2,4,2,2,3,3,5,2,4,0,0.0,satisfied +96224,67382,Female,disloyal Customer,40,Business travel,Business,641,5,5,5,3,2,5,2,2,3,4,5,3,4,2,12,18.0,satisfied +96225,63422,Female,Loyal Customer,57,Personal Travel,Eco,337,3,5,3,3,4,4,4,2,2,3,2,4,2,5,74,73.0,neutral or dissatisfied +96226,17045,Female,Loyal Customer,48,Business travel,Business,1134,4,4,5,4,1,4,1,3,3,4,3,3,3,1,0,0.0,satisfied +96227,18232,Female,Loyal Customer,36,Business travel,Eco,228,2,3,3,3,2,2,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +96228,13146,Female,Loyal Customer,38,Personal Travel,Eco,595,4,2,4,3,2,4,2,2,1,4,2,1,3,2,0,0.0,neutral or dissatisfied +96229,92865,Female,Loyal Customer,41,Business travel,Eco,2519,2,1,1,1,2,2,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +96230,8232,Female,Loyal Customer,48,Personal Travel,Eco,402,2,5,2,2,3,4,4,4,4,2,4,3,4,3,6,5.0,neutral or dissatisfied +96231,15112,Female,Loyal Customer,19,Business travel,Business,1042,5,5,5,5,3,4,3,3,1,3,4,1,4,3,0,2.0,satisfied +96232,113698,Male,Loyal Customer,53,Personal Travel,Eco,258,1,5,1,4,1,1,1,1,5,2,1,3,1,1,36,34.0,neutral or dissatisfied +96233,81165,Male,Loyal Customer,33,Business travel,Business,2087,3,4,4,4,1,1,3,1,2,1,3,2,3,1,30,27.0,neutral or dissatisfied +96234,66356,Female,Loyal Customer,32,Business travel,Business,3826,1,1,1,1,3,3,3,3,4,3,4,5,4,3,0,0.0,satisfied +96235,43313,Female,Loyal Customer,46,Business travel,Business,2607,2,2,2,2,4,3,1,4,4,4,4,3,4,3,2,0.0,satisfied +96236,12955,Female,Loyal Customer,60,Business travel,Eco Plus,456,4,3,4,3,2,3,1,4,4,4,4,2,4,1,0,0.0,satisfied +96237,14267,Female,Loyal Customer,69,Business travel,Business,429,4,3,4,4,2,2,4,5,5,5,5,3,5,4,35,25.0,satisfied +96238,103740,Male,Loyal Customer,15,Personal Travel,Eco,405,2,4,2,2,3,2,1,3,4,3,4,5,4,3,30,25.0,neutral or dissatisfied +96239,129764,Female,Loyal Customer,42,Business travel,Business,1631,5,5,5,5,4,1,1,4,4,4,4,5,4,1,0,0.0,satisfied +96240,110013,Female,Loyal Customer,25,Business travel,Business,1204,3,4,4,4,3,2,3,3,2,4,4,1,3,3,104,91.0,neutral or dissatisfied +96241,52862,Male,Loyal Customer,35,Business travel,Eco,1024,5,4,4,4,5,5,5,5,4,2,5,5,3,5,39,36.0,satisfied +96242,104124,Male,Loyal Customer,60,Business travel,Business,3433,3,3,3,3,4,5,4,5,5,5,5,5,5,5,21,7.0,satisfied +96243,89160,Female,Loyal Customer,18,Personal Travel,Eco,1947,4,5,4,2,3,4,3,3,5,3,4,3,5,3,0,3.0,satisfied +96244,60880,Male,disloyal Customer,24,Business travel,Business,1062,5,4,5,3,4,5,1,4,3,4,5,3,5,4,3,4.0,satisfied +96245,36129,Male,Loyal Customer,15,Business travel,Eco,1609,0,4,0,4,5,0,5,5,5,1,5,3,3,5,0,0.0,satisfied +96246,82947,Female,disloyal Customer,23,Business travel,Business,957,2,3,2,3,5,2,5,5,2,1,3,4,3,5,33,22.0,neutral or dissatisfied +96247,122289,Male,Loyal Customer,38,Personal Travel,Eco,544,1,1,1,2,1,1,5,1,4,4,1,2,1,1,18,22.0,neutral or dissatisfied +96248,121497,Female,Loyal Customer,46,Business travel,Business,331,0,0,0,2,4,4,5,1,1,1,1,4,1,5,1,0.0,satisfied +96249,6021,Male,disloyal Customer,23,Business travel,Eco,691,1,1,1,4,2,1,1,2,3,2,5,4,4,2,3,0.0,neutral or dissatisfied +96250,105398,Male,Loyal Customer,61,Personal Travel,Eco,369,2,5,1,2,5,1,1,5,4,4,1,5,1,5,31,18.0,neutral or dissatisfied +96251,95618,Male,Loyal Customer,44,Personal Travel,Eco,670,2,1,2,2,5,2,5,5,4,2,3,4,3,5,0,0.0,neutral or dissatisfied +96252,33162,Female,Loyal Customer,25,Personal Travel,Eco,101,1,4,1,3,2,1,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +96253,40556,Male,disloyal Customer,38,Business travel,Eco,391,4,4,4,1,2,4,2,2,1,3,5,3,2,2,0,0.0,neutral or dissatisfied +96254,129309,Female,Loyal Customer,60,Business travel,Business,2475,3,3,3,3,2,5,5,4,4,4,4,4,4,4,13,18.0,satisfied +96255,68505,Female,Loyal Customer,12,Personal Travel,Eco,1303,4,3,4,1,4,4,4,4,2,2,4,3,3,4,0,0.0,satisfied +96256,87777,Male,Loyal Customer,57,Business travel,Business,143,2,2,2,2,5,4,4,3,3,4,4,5,3,3,49,52.0,satisfied +96257,107131,Male,Loyal Customer,49,Personal Travel,Eco,842,1,4,1,3,3,1,4,3,1,4,1,3,3,3,53,32.0,neutral or dissatisfied +96258,9449,Male,Loyal Customer,7,Personal Travel,Eco,362,0,4,0,5,3,0,3,3,3,4,5,4,5,3,0,0.0,satisfied +96259,59110,Female,Loyal Customer,19,Personal Travel,Eco,1846,1,2,1,3,5,1,2,5,2,3,2,4,3,5,4,0.0,neutral or dissatisfied +96260,68410,Male,Loyal Customer,25,Business travel,Business,2067,2,2,1,2,4,4,4,4,1,4,5,2,5,4,0,0.0,satisfied +96261,67528,Male,Loyal Customer,58,Business travel,Business,1614,3,3,1,3,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +96262,45370,Female,Loyal Customer,17,Personal Travel,Eco,175,2,5,2,2,2,2,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +96263,13932,Male,disloyal Customer,24,Business travel,Eco,259,3,0,3,3,5,3,5,5,2,1,4,4,4,5,90,78.0,neutral or dissatisfied +96264,42379,Female,Loyal Customer,8,Personal Travel,Eco,834,2,5,2,1,1,2,3,1,5,2,2,5,4,1,0,0.0,neutral or dissatisfied +96265,57088,Female,Loyal Customer,36,Business travel,Business,2199,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +96266,129104,Female,Loyal Customer,30,Personal Travel,Eco,2342,3,3,4,2,4,5,5,1,1,3,3,5,1,5,0,21.0,neutral or dissatisfied +96267,59501,Male,Loyal Customer,49,Business travel,Business,2491,1,1,1,1,4,5,5,5,5,5,5,3,5,3,12,0.0,satisfied +96268,9618,Female,Loyal Customer,23,Personal Travel,Eco,228,2,4,0,1,4,0,2,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +96269,25133,Male,Loyal Customer,47,Business travel,Business,2677,1,4,4,4,5,3,4,1,1,1,1,3,1,2,9,19.0,neutral or dissatisfied +96270,104722,Male,Loyal Customer,21,Business travel,Business,1407,5,5,4,5,4,4,4,4,4,5,5,4,5,4,10,24.0,satisfied +96271,28839,Female,Loyal Customer,17,Business travel,Business,2390,2,2,2,2,5,5,5,5,1,1,4,2,4,5,0,0.0,satisfied +96272,122309,Male,Loyal Customer,54,Personal Travel,Eco,541,4,5,4,5,1,4,1,1,3,4,5,3,4,1,0,33.0,neutral or dissatisfied +96273,72669,Female,Loyal Customer,40,Personal Travel,Eco,1121,2,5,3,4,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +96274,97039,Male,Loyal Customer,10,Business travel,Business,1129,5,5,3,5,5,5,5,5,3,5,4,3,5,5,4,1.0,satisfied +96275,2260,Female,Loyal Customer,66,Business travel,Business,1825,1,1,3,1,4,5,5,5,5,5,5,5,5,3,20,17.0,satisfied +96276,2806,Male,Loyal Customer,42,Business travel,Business,3931,3,3,3,3,2,4,4,5,5,5,5,4,5,4,33,25.0,satisfied +96277,126349,Female,Loyal Customer,44,Personal Travel,Eco,507,2,4,2,2,5,4,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +96278,63944,Female,Loyal Customer,38,Personal Travel,Eco,1212,1,0,1,5,3,1,3,3,5,1,4,5,1,3,0,0.0,neutral or dissatisfied +96279,110965,Male,Loyal Customer,39,Business travel,Business,197,3,4,4,4,3,3,3,2,2,2,3,3,2,1,14,5.0,neutral or dissatisfied +96280,107948,Male,Loyal Customer,23,Business travel,Business,3553,4,4,4,4,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +96281,4821,Male,Loyal Customer,53,Business travel,Business,2096,2,2,2,2,5,5,5,4,4,5,4,4,4,3,0,10.0,satisfied +96282,98914,Male,Loyal Customer,58,Business travel,Business,2621,5,5,5,5,4,4,4,5,3,5,5,4,3,4,187,190.0,satisfied +96283,102280,Female,Loyal Customer,38,Business travel,Business,2465,2,2,5,5,4,3,4,3,3,3,2,3,3,2,16,12.0,neutral or dissatisfied +96284,49156,Male,Loyal Customer,51,Business travel,Eco,278,4,1,1,1,4,4,4,4,5,3,2,1,3,4,0,0.0,satisfied +96285,60906,Female,disloyal Customer,37,Business travel,Eco,589,3,1,3,3,4,3,5,4,1,5,3,1,4,4,4,0.0,neutral or dissatisfied +96286,12206,Male,Loyal Customer,36,Business travel,Business,3300,2,2,5,2,1,4,3,2,2,2,2,1,2,1,76,60.0,neutral or dissatisfied +96287,59587,Male,Loyal Customer,47,Business travel,Business,787,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +96288,74811,Female,disloyal Customer,39,Business travel,Eco Plus,1031,1,1,1,3,3,1,3,3,2,4,2,5,1,3,0,0.0,neutral or dissatisfied +96289,45103,Male,disloyal Customer,33,Business travel,Eco,157,4,0,4,4,3,4,3,3,4,5,3,3,2,3,0,0.0,neutral or dissatisfied +96290,12708,Male,disloyal Customer,18,Business travel,Eco,803,1,1,1,3,2,1,2,2,3,1,2,5,2,2,14,13.0,neutral or dissatisfied +96291,83308,Male,disloyal Customer,25,Business travel,Eco,1234,3,3,3,4,3,3,3,3,3,5,3,4,4,3,13,2.0,neutral or dissatisfied +96292,99326,Male,Loyal Customer,30,Personal Travel,Eco,448,1,4,1,3,5,1,5,5,3,5,3,3,5,5,0,0.0,neutral or dissatisfied +96293,44969,Female,Loyal Customer,43,Business travel,Business,359,4,4,4,4,5,2,2,5,5,5,5,5,5,2,84,81.0,satisfied +96294,65929,Female,Loyal Customer,36,Personal Travel,Eco,569,4,5,3,1,5,3,3,5,4,3,4,5,5,5,9,7.0,neutral or dissatisfied +96295,128846,Male,Loyal Customer,59,Personal Travel,Eco,2586,3,3,3,4,3,2,2,3,1,3,2,2,1,2,8,0.0,neutral or dissatisfied +96296,97020,Male,disloyal Customer,26,Business travel,Business,794,2,2,2,3,3,2,3,3,4,2,5,4,4,3,0,10.0,neutral or dissatisfied +96297,75384,Female,Loyal Customer,44,Business travel,Business,2330,4,4,4,4,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +96298,15664,Male,Loyal Customer,26,Business travel,Eco,764,3,1,1,1,3,4,3,3,3,2,3,1,3,3,10,1.0,satisfied +96299,31242,Male,Loyal Customer,50,Business travel,Business,1755,2,1,1,1,4,2,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +96300,122154,Female,disloyal Customer,27,Business travel,Business,541,5,5,5,2,2,5,5,2,5,5,5,4,4,2,0,0.0,satisfied +96301,127445,Female,Loyal Customer,33,Personal Travel,Eco Plus,872,2,2,2,4,2,2,2,2,3,1,4,3,3,2,0,19.0,neutral or dissatisfied +96302,58687,Male,Loyal Customer,51,Business travel,Business,299,5,5,5,5,5,4,4,5,5,5,5,3,5,4,14,2.0,satisfied +96303,4613,Male,disloyal Customer,25,Business travel,Eco,719,2,2,2,3,2,2,2,2,1,1,4,1,3,2,0,6.0,neutral or dissatisfied +96304,82301,Male,Loyal Customer,40,Business travel,Business,986,2,2,2,2,3,5,5,3,3,3,3,5,3,4,0,10.0,satisfied +96305,53966,Female,Loyal Customer,31,Personal Travel,Eco,1325,3,1,3,2,1,3,1,1,3,2,1,2,2,1,36,26.0,neutral or dissatisfied +96306,82217,Male,Loyal Customer,51,Business travel,Business,405,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +96307,78445,Female,Loyal Customer,43,Business travel,Business,526,3,3,3,3,4,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +96308,73126,Female,Loyal Customer,27,Personal Travel,Eco Plus,2174,4,1,4,3,2,4,4,2,1,5,3,3,4,2,14,10.0,neutral or dissatisfied +96309,1044,Female,disloyal Customer,30,Business travel,Eco,134,3,0,4,2,3,4,3,3,1,5,2,3,3,3,0,0.0,neutral or dissatisfied +96310,64239,Male,disloyal Customer,11,Business travel,Eco,1412,2,2,2,4,5,2,5,5,1,2,2,2,3,5,13,22.0,neutral or dissatisfied +96311,122219,Male,Loyal Customer,55,Business travel,Eco,544,1,2,2,2,1,1,1,1,2,5,2,3,3,1,3,7.0,neutral or dissatisfied +96312,54499,Female,disloyal Customer,26,Business travel,Eco,925,1,2,2,3,3,2,1,3,3,3,4,4,4,3,6,1.0,neutral or dissatisfied +96313,95140,Male,Loyal Customer,9,Personal Travel,Eco,239,2,3,2,4,5,2,5,5,5,5,3,1,5,5,22,22.0,neutral or dissatisfied +96314,70900,Male,disloyal Customer,26,Business travel,Eco,1328,1,1,1,3,4,1,4,4,3,5,3,1,3,4,14,4.0,neutral or dissatisfied +96315,53517,Female,Loyal Customer,56,Personal Travel,Eco,2288,3,3,3,4,1,2,5,3,3,3,3,3,3,3,7,13.0,neutral or dissatisfied +96316,20125,Male,Loyal Customer,45,Personal Travel,Eco,416,1,3,1,5,1,1,1,2,5,4,2,1,2,1,219,224.0,neutral or dissatisfied +96317,22750,Female,Loyal Customer,59,Business travel,Eco,170,4,3,3,3,4,3,1,5,5,4,5,3,5,4,39,34.0,satisfied +96318,75447,Male,Loyal Customer,47,Business travel,Eco,2342,2,3,3,3,2,2,2,2,1,5,2,3,3,2,0,0.0,neutral or dissatisfied +96319,16891,Male,disloyal Customer,21,Business travel,Eco,746,3,3,3,3,2,3,2,2,2,2,4,2,4,2,60,84.0,neutral or dissatisfied +96320,5535,Male,Loyal Customer,65,Business travel,Business,431,5,5,5,5,2,2,4,5,5,5,5,2,5,3,0,0.0,satisfied +96321,94583,Female,Loyal Customer,25,Business travel,Business,189,3,5,4,5,2,3,3,2,4,5,2,2,2,2,20,26.0,neutral or dissatisfied +96322,92700,Female,Loyal Customer,19,Personal Travel,Eco,507,4,4,4,1,1,4,1,1,3,3,5,3,4,1,37,22.0,neutral or dissatisfied +96323,40808,Male,Loyal Customer,30,Business travel,Business,558,2,1,3,3,2,2,2,2,1,3,1,2,2,2,0,0.0,neutral or dissatisfied +96324,94823,Female,Loyal Customer,59,Business travel,Business,1784,4,5,5,5,3,4,3,2,2,2,4,2,2,4,0,0.0,neutral or dissatisfied +96325,94341,Female,Loyal Customer,53,Business travel,Business,1645,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +96326,102245,Female,Loyal Customer,53,Business travel,Business,3872,2,4,4,4,5,4,4,2,2,2,2,2,2,4,68,62.0,neutral or dissatisfied +96327,21187,Male,Loyal Customer,28,Business travel,Business,192,2,2,2,2,4,4,5,4,4,5,4,4,5,4,0,0.0,satisfied +96328,101362,Female,Loyal Customer,22,Business travel,Business,2237,4,5,2,2,4,4,4,4,1,4,1,4,2,4,1,0.0,neutral or dissatisfied +96329,87708,Male,Loyal Customer,28,Personal Travel,Eco,591,2,3,2,4,5,2,5,5,1,3,3,2,3,5,65,47.0,neutral or dissatisfied +96330,122040,Female,disloyal Customer,24,Business travel,Business,130,4,0,4,2,5,4,5,5,4,3,4,3,4,5,0,0.0,satisfied +96331,50826,Male,Loyal Customer,16,Personal Travel,Eco,308,3,3,3,4,3,3,3,3,2,3,3,2,3,3,0,0.0,neutral or dissatisfied +96332,62260,Male,Loyal Customer,42,Business travel,Business,2434,2,2,2,2,2,4,4,5,5,5,5,5,5,5,2,0.0,satisfied +96333,38286,Female,Loyal Customer,8,Business travel,Eco Plus,1050,1,4,5,5,1,1,4,1,4,3,3,1,4,1,86,63.0,neutral or dissatisfied +96334,126165,Female,disloyal Customer,22,Business travel,Business,507,5,5,5,1,2,5,2,2,5,5,4,4,5,2,0,0.0,satisfied +96335,124673,Male,disloyal Customer,44,Business travel,Business,399,3,4,4,3,4,3,4,4,4,2,5,3,5,4,0,7.0,neutral or dissatisfied +96336,99550,Female,Loyal Customer,49,Business travel,Business,3333,1,1,1,1,3,5,4,5,5,5,5,3,5,5,11,0.0,satisfied +96337,68330,Male,Loyal Customer,53,Personal Travel,Eco,2165,3,5,4,3,1,4,4,1,3,3,5,3,5,1,0,1.0,neutral or dissatisfied +96338,22357,Female,Loyal Customer,54,Business travel,Business,2397,3,3,3,3,4,1,3,4,4,4,4,4,4,4,7,10.0,satisfied +96339,10808,Male,Loyal Customer,38,Business travel,Business,2383,3,2,2,2,1,4,4,2,2,2,3,4,2,2,0,0.0,neutral or dissatisfied +96340,89279,Female,Loyal Customer,36,Business travel,Business,3874,3,5,4,5,1,3,4,3,3,3,3,3,3,3,0,15.0,neutral or dissatisfied +96341,10432,Male,Loyal Customer,53,Business travel,Business,2069,3,3,3,3,3,5,4,5,5,5,4,4,5,4,0,12.0,satisfied +96342,122564,Female,Loyal Customer,31,Business travel,Business,1559,5,5,5,5,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +96343,33000,Male,Loyal Customer,61,Personal Travel,Eco,216,2,4,2,2,2,2,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +96344,58443,Male,Loyal Customer,29,Personal Travel,Eco,733,4,4,4,3,5,4,4,5,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +96345,125150,Female,Loyal Customer,35,Business travel,Eco,1999,2,2,2,2,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +96346,103564,Female,Loyal Customer,53,Business travel,Business,3375,3,4,3,3,2,4,4,4,4,4,4,3,4,3,7,8.0,satisfied +96347,116803,Male,Loyal Customer,54,Personal Travel,Eco Plus,358,2,5,2,1,3,2,3,3,3,3,5,3,5,3,54,50.0,neutral or dissatisfied +96348,52859,Female,Loyal Customer,40,Business travel,Eco Plus,1721,5,5,5,5,5,5,5,5,5,2,4,3,1,5,5,0.0,satisfied +96349,1780,Female,Loyal Customer,44,Business travel,Business,2592,2,1,1,1,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +96350,52452,Male,Loyal Customer,31,Business travel,Eco Plus,651,5,5,5,5,5,5,5,5,3,4,1,2,1,5,0,0.0,satisfied +96351,109886,Female,Loyal Customer,23,Business travel,Eco,1053,4,1,1,1,4,4,1,4,3,1,3,3,3,4,16,14.0,neutral or dissatisfied +96352,145,Male,Loyal Customer,16,Business travel,Business,227,4,1,1,1,3,4,4,4,2,4,4,4,3,4,265,260.0,neutral or dissatisfied +96353,48384,Male,Loyal Customer,12,Personal Travel,Eco,587,4,5,4,3,3,4,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +96354,95151,Female,Loyal Customer,22,Personal Travel,Eco,189,4,4,4,3,3,4,3,3,4,3,4,5,4,3,0,2.0,neutral or dissatisfied +96355,12798,Female,Loyal Customer,29,Business travel,Business,817,2,2,2,2,5,5,5,5,4,2,1,3,2,5,92,,satisfied +96356,50583,Female,Loyal Customer,55,Personal Travel,Eco,308,4,4,4,2,3,1,5,5,5,4,5,1,5,2,0,0.0,satisfied +96357,18145,Male,Loyal Customer,69,Personal Travel,Eco,926,2,4,2,5,2,3,2,4,3,4,5,2,3,2,95,159.0,neutral or dissatisfied +96358,101690,Female,Loyal Customer,42,Business travel,Business,1500,3,3,3,3,2,4,5,5,5,5,5,5,5,5,12,0.0,satisfied +96359,46248,Male,Loyal Customer,46,Business travel,Eco,279,2,3,3,3,2,2,2,2,2,1,2,3,4,2,29,27.0,satisfied +96360,102604,Female,Loyal Customer,18,Personal Travel,Eco Plus,414,4,3,4,4,2,4,3,2,1,1,3,1,1,2,36,27.0,neutral or dissatisfied +96361,73963,Female,Loyal Customer,67,Personal Travel,Eco,2585,2,4,2,2,2,4,2,4,2,3,5,2,5,2,83,86.0,neutral or dissatisfied +96362,86786,Female,Loyal Customer,55,Business travel,Business,2867,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +96363,24110,Female,disloyal Customer,20,Business travel,Eco,779,2,2,2,3,5,2,5,5,4,2,3,1,3,5,4,35.0,neutral or dissatisfied +96364,110023,Male,Loyal Customer,50,Personal Travel,Eco,1204,3,5,3,5,5,3,5,5,3,3,4,3,5,5,100,96.0,neutral or dissatisfied +96365,44841,Female,disloyal Customer,24,Business travel,Eco,760,2,2,2,3,3,2,3,3,3,1,4,2,3,3,9,12.0,neutral or dissatisfied +96366,40595,Female,Loyal Customer,38,Business travel,Eco,391,2,4,4,4,2,1,2,2,3,2,4,4,4,2,26,19.0,neutral or dissatisfied +96367,53430,Female,Loyal Customer,38,Business travel,Business,2288,2,2,2,2,5,4,3,4,4,5,4,1,4,2,4,13.0,satisfied +96368,85363,Male,Loyal Customer,41,Personal Travel,Eco Plus,874,1,5,1,1,5,1,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +96369,50897,Female,Loyal Customer,47,Personal Travel,Eco,134,1,1,1,3,3,3,3,5,5,1,1,2,5,2,0,0.0,neutral or dissatisfied +96370,62061,Male,disloyal Customer,50,Personal Travel,Eco,2475,1,5,1,3,4,1,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +96371,39376,Female,Loyal Customer,26,Business travel,Business,1700,1,1,1,1,3,3,3,3,3,5,2,3,5,3,0,0.0,satisfied +96372,111599,Male,Loyal Customer,33,Business travel,Eco Plus,883,1,1,1,1,1,1,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +96373,10504,Male,Loyal Customer,54,Business travel,Business,2531,3,3,3,3,5,4,4,5,5,5,4,3,5,5,0,0.0,satisfied +96374,56976,Female,Loyal Customer,56,Personal Travel,Eco,2565,3,4,3,3,3,1,5,2,5,4,1,5,3,5,17,25.0,neutral or dissatisfied +96375,49910,Male,Loyal Customer,23,Business travel,Business,207,0,5,0,4,5,2,2,5,1,3,3,1,4,5,0,2.0,satisfied +96376,57741,Male,disloyal Customer,25,Business travel,Eco,1190,5,5,5,1,5,5,5,5,2,4,5,5,4,5,0,20.0,satisfied +96377,114238,Female,disloyal Customer,24,Business travel,Eco,909,0,0,0,3,5,0,5,5,3,3,4,5,5,5,0,0.0,satisfied +96378,110289,Female,Loyal Customer,52,Business travel,Business,925,1,1,1,1,4,5,4,4,4,4,4,3,4,3,54,44.0,satisfied +96379,6585,Female,Loyal Customer,68,Personal Travel,Eco,473,5,3,1,5,1,2,5,2,2,1,2,2,2,1,2,22.0,satisfied +96380,12938,Male,Loyal Customer,57,Personal Travel,Eco,674,1,4,1,3,3,1,3,3,5,4,4,4,4,3,0,7.0,neutral or dissatisfied +96381,36643,Male,Loyal Customer,14,Personal Travel,Eco,1249,3,5,3,2,5,3,5,5,4,2,4,5,4,5,8,17.0,neutral or dissatisfied +96382,75844,Female,disloyal Customer,39,Business travel,Business,1440,1,1,1,3,4,1,4,4,3,2,3,3,4,4,24,0.0,neutral or dissatisfied +96383,6515,Male,Loyal Customer,72,Business travel,Business,3138,1,1,1,1,1,2,3,1,1,1,1,2,1,4,39,28.0,neutral or dissatisfied +96384,129100,Female,Loyal Customer,57,Personal Travel,Eco,2583,2,2,2,4,2,1,5,2,1,4,4,5,1,5,0,0.0,neutral or dissatisfied +96385,82539,Female,Loyal Customer,51,Business travel,Business,440,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +96386,96978,Female,Loyal Customer,50,Business travel,Business,3772,1,1,4,1,2,5,5,5,5,5,5,5,5,5,21,18.0,satisfied +96387,87320,Female,Loyal Customer,56,Business travel,Eco Plus,177,3,5,5,5,1,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +96388,41069,Male,disloyal Customer,43,Business travel,Eco,667,4,3,4,3,1,4,4,1,5,4,1,2,5,1,13,16.0,neutral or dissatisfied +96389,43293,Female,Loyal Customer,59,Business travel,Eco,402,5,4,4,4,2,2,5,4,4,5,4,5,4,5,66,63.0,satisfied +96390,8176,Male,Loyal Customer,46,Business travel,Business,402,1,3,3,3,3,2,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +96391,119336,Male,Loyal Customer,48,Personal Travel,Eco,214,1,0,1,3,4,1,4,4,4,2,5,3,5,4,0,0.0,neutral or dissatisfied +96392,85359,Male,Loyal Customer,52,Personal Travel,Eco Plus,689,5,4,5,2,2,5,2,2,3,4,4,4,4,2,0,1.0,satisfied +96393,23062,Male,Loyal Customer,43,Business travel,Business,2732,4,4,4,4,2,5,2,5,5,5,5,3,5,3,0,0.0,satisfied +96394,29016,Female,disloyal Customer,39,Business travel,Eco,578,4,0,4,1,2,4,1,2,3,4,3,1,1,2,0,0.0,neutral or dissatisfied +96395,67832,Female,disloyal Customer,29,Business travel,Eco,1171,2,1,1,1,3,1,3,3,4,2,2,1,2,3,0,0.0,neutral or dissatisfied +96396,6223,Male,disloyal Customer,23,Business travel,Business,413,4,5,4,5,2,4,2,2,3,5,5,5,5,2,0,100.0,satisfied +96397,61923,Male,Loyal Customer,28,Personal Travel,Eco,550,4,0,4,4,3,4,3,3,1,4,2,3,4,3,0,0.0,neutral or dissatisfied +96398,115682,Male,Loyal Customer,55,Business travel,Business,447,4,4,4,4,3,4,4,4,4,4,4,3,4,3,13,4.0,satisfied +96399,85350,Male,Loyal Customer,20,Business travel,Eco Plus,731,2,3,5,3,2,2,1,2,3,4,3,3,4,2,86,65.0,neutral or dissatisfied +96400,90223,Female,disloyal Customer,47,Business travel,Business,1084,1,2,2,1,2,1,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +96401,124232,Female,Loyal Customer,49,Business travel,Business,1916,5,5,3,5,3,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +96402,46882,Female,disloyal Customer,25,Business travel,Eco,909,3,3,3,4,5,3,2,5,3,1,3,4,3,5,22,20.0,neutral or dissatisfied +96403,65102,Female,Loyal Customer,54,Personal Travel,Eco,282,1,4,1,1,2,3,1,3,3,1,5,3,3,2,10,0.0,neutral or dissatisfied +96404,75564,Male,Loyal Customer,47,Business travel,Business,337,3,3,3,3,5,3,3,3,3,3,3,4,3,3,32,21.0,neutral or dissatisfied +96405,11201,Female,Loyal Customer,23,Personal Travel,Eco,429,3,0,3,4,5,3,5,5,5,2,5,4,5,5,34,36.0,neutral or dissatisfied +96406,21265,Female,disloyal Customer,25,Business travel,Business,620,1,4,1,4,3,1,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +96407,89322,Male,disloyal Customer,23,Business travel,Eco,957,4,4,4,3,2,4,2,2,4,4,3,5,4,2,32,38.0,satisfied +96408,88912,Male,Loyal Customer,57,Personal Travel,Eco,859,4,4,4,1,3,4,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +96409,44637,Female,Loyal Customer,33,Business travel,Eco,173,5,4,4,4,5,5,5,5,4,4,1,4,4,5,25,41.0,satisfied +96410,105718,Female,Loyal Customer,33,Business travel,Business,883,3,4,4,4,3,3,3,4,1,3,2,3,2,3,181,169.0,neutral or dissatisfied +96411,77498,Female,Loyal Customer,45,Personal Travel,Eco,989,2,2,2,4,4,4,4,2,2,2,5,1,2,4,0,6.0,neutral or dissatisfied +96412,4985,Female,Loyal Customer,58,Business travel,Business,502,1,1,2,1,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +96413,51072,Female,Loyal Customer,39,Personal Travel,Eco,86,0,5,0,1,2,0,2,2,3,3,5,4,4,2,0,0.0,satisfied +96414,73138,Female,Loyal Customer,25,Personal Travel,Eco,1068,4,1,4,3,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +96415,68703,Male,Loyal Customer,34,Personal Travel,Eco,237,1,3,0,2,1,0,1,1,2,4,4,5,3,1,0,0.0,neutral or dissatisfied +96416,96706,Female,Loyal Customer,13,Business travel,Business,3313,2,1,1,1,2,2,2,2,1,2,3,1,3,2,22,30.0,neutral or dissatisfied +96417,10494,Female,Loyal Customer,45,Business travel,Business,3937,2,5,5,5,1,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +96418,125280,Male,Loyal Customer,52,Business travel,Business,678,2,2,2,2,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +96419,68461,Female,Loyal Customer,55,Business travel,Business,2585,5,5,3,5,4,5,4,5,5,5,5,4,5,4,0,10.0,satisfied +96420,110277,Female,Loyal Customer,69,Personal Travel,Business,883,2,2,2,4,2,5,5,3,2,3,3,5,4,5,156,152.0,neutral or dissatisfied +96421,99917,Female,Loyal Customer,46,Business travel,Business,1428,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +96422,43007,Female,Loyal Customer,52,Business travel,Business,236,0,0,0,3,4,5,3,5,5,1,1,4,5,1,6,7.0,satisfied +96423,30249,Female,Loyal Customer,52,Business travel,Business,836,2,2,5,2,5,5,4,5,5,5,5,3,5,4,0,1.0,satisfied +96424,119630,Female,Loyal Customer,66,Personal Travel,Business,1727,4,5,4,3,1,4,5,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +96425,129232,Female,Loyal Customer,57,Business travel,Business,1464,1,1,1,1,2,5,4,2,2,2,2,3,2,3,66,65.0,satisfied +96426,79041,Male,disloyal Customer,24,Business travel,Business,356,5,4,5,1,1,5,1,1,5,4,4,4,5,1,0,0.0,satisfied +96427,84524,Male,Loyal Customer,47,Business travel,Business,2615,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +96428,18149,Female,Loyal Customer,39,Business travel,Eco,296,3,1,5,1,3,3,3,3,4,3,2,1,3,3,0,0.0,neutral or dissatisfied +96429,91173,Male,Loyal Customer,65,Personal Travel,Eco,581,1,4,1,5,2,1,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +96430,87730,Male,Loyal Customer,10,Personal Travel,Business,4502,4,2,5,4,5,3,3,2,3,4,4,3,3,3,6,2.0,neutral or dissatisfied +96431,99592,Male,Loyal Customer,66,Personal Travel,Eco,829,2,5,2,3,3,2,3,3,4,4,4,3,5,3,12,27.0,neutral or dissatisfied +96432,37332,Female,Loyal Customer,53,Business travel,Eco,944,5,5,5,5,1,3,3,5,5,5,5,3,5,5,0,0.0,satisfied +96433,75337,Male,Loyal Customer,43,Business travel,Business,1056,3,3,3,3,3,3,2,2,2,2,2,5,2,5,1,2.0,satisfied +96434,2603,Male,Loyal Customer,43,Personal Travel,Eco,280,2,5,2,3,3,2,3,3,5,3,5,3,4,3,0,6.0,neutral or dissatisfied +96435,76109,Female,Loyal Customer,39,Personal Travel,Eco Plus,669,2,5,1,2,1,1,1,1,4,2,5,5,5,1,41,39.0,neutral or dissatisfied +96436,26321,Female,Loyal Customer,49,Business travel,Business,3848,2,4,4,4,2,4,3,2,2,3,2,1,2,2,67,70.0,neutral or dissatisfied +96437,78956,Female,Loyal Customer,31,Business travel,Business,3271,3,4,3,3,5,5,5,5,5,5,4,4,4,5,2,12.0,satisfied +96438,50922,Female,Loyal Customer,70,Personal Travel,Eco,372,3,4,3,3,4,4,3,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +96439,65277,Female,Loyal Customer,44,Personal Travel,Eco Plus,551,4,2,4,4,3,3,3,1,1,4,4,3,1,1,0,0.0,satisfied +96440,71409,Female,Loyal Customer,51,Business travel,Business,3220,2,2,2,2,5,2,2,5,5,5,5,3,5,3,21,14.0,satisfied +96441,87775,Male,Loyal Customer,58,Business travel,Business,214,0,5,0,4,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +96442,89253,Female,Loyal Customer,41,Business travel,Business,453,4,4,4,4,3,4,5,4,4,4,4,5,4,5,4,17.0,satisfied +96443,50333,Female,Loyal Customer,51,Business travel,Business,199,3,3,1,3,4,4,2,3,3,4,5,5,3,1,12,5.0,satisfied +96444,69546,Female,disloyal Customer,25,Business travel,Business,2475,1,4,2,3,2,3,3,5,3,4,5,3,5,3,0,28.0,neutral or dissatisfied +96445,30776,Male,disloyal Customer,24,Business travel,Eco,834,2,2,2,1,2,3,3,2,2,1,3,3,3,3,131,135.0,neutral or dissatisfied +96446,121126,Male,disloyal Customer,43,Business travel,Eco,1127,3,3,3,3,3,2,2,2,5,4,4,2,1,2,8,0.0,neutral or dissatisfied +96447,115875,Male,Loyal Customer,40,Business travel,Business,2899,4,4,4,4,3,1,1,5,5,5,5,1,5,5,0,0.0,satisfied +96448,78640,Female,Loyal Customer,56,Business travel,Business,2172,4,4,4,4,3,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +96449,29719,Male,Loyal Customer,55,Business travel,Business,2777,3,3,3,3,4,4,4,3,2,5,5,4,4,4,0,0.0,satisfied +96450,4,Male,Loyal Customer,50,Business travel,Business,1905,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +96451,63719,Female,disloyal Customer,26,Business travel,Business,1140,4,4,4,1,3,4,3,3,5,4,5,5,5,3,0,0.0,satisfied +96452,13517,Male,disloyal Customer,40,Business travel,Eco,152,5,0,5,4,2,5,2,2,4,5,3,3,4,2,0,0.0,satisfied +96453,72491,Male,Loyal Customer,33,Business travel,Business,1102,2,3,3,3,2,2,2,2,2,4,3,4,3,2,10,0.0,neutral or dissatisfied +96454,20854,Female,Loyal Customer,60,Personal Travel,Eco,457,2,4,2,3,3,5,4,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +96455,94336,Female,Loyal Customer,49,Business travel,Business,189,0,4,0,3,3,4,4,2,2,2,2,4,2,4,5,3.0,satisfied +96456,27889,Male,disloyal Customer,35,Business travel,Eco,1477,1,1,1,5,1,2,2,3,1,3,2,2,4,2,0,0.0,neutral or dissatisfied +96457,95270,Female,Loyal Customer,24,Personal Travel,Eco,189,3,5,3,4,1,3,1,1,5,5,4,4,5,1,20,8.0,neutral or dissatisfied +96458,119685,Female,Loyal Customer,52,Personal Travel,Business,1496,1,1,1,3,4,3,4,1,1,1,1,3,1,2,0,17.0,neutral or dissatisfied +96459,62370,Male,Loyal Customer,29,Business travel,Business,2704,5,5,5,5,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +96460,42469,Female,disloyal Customer,42,Business travel,Eco,395,3,0,3,2,2,3,2,2,4,5,3,2,1,2,62,102.0,neutral or dissatisfied +96461,82846,Female,Loyal Customer,52,Business travel,Business,594,2,2,2,2,5,4,5,4,4,4,4,5,4,3,3,0.0,satisfied +96462,100950,Male,Loyal Customer,14,Business travel,Business,3207,3,3,3,3,5,5,5,5,5,5,5,4,4,5,0,1.0,satisfied +96463,3890,Female,Loyal Customer,72,Business travel,Business,2286,1,5,5,5,5,4,4,2,2,2,1,1,2,1,0,0.0,neutral or dissatisfied +96464,100514,Female,Loyal Customer,34,Business travel,Business,2022,4,2,2,2,1,3,3,4,4,4,4,4,4,3,83,81.0,neutral or dissatisfied +96465,126371,Female,Loyal Customer,70,Personal Travel,Eco,650,2,5,2,3,4,2,5,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +96466,12912,Male,disloyal Customer,20,Business travel,Eco,809,3,3,3,3,1,3,1,1,4,2,2,1,2,1,59,60.0,neutral or dissatisfied +96467,49013,Male,Loyal Customer,31,Business travel,Business,2927,5,5,5,5,5,5,4,5,5,2,4,4,2,5,0,0.0,satisfied +96468,21266,Female,Loyal Customer,49,Business travel,Business,3639,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +96469,122422,Male,Loyal Customer,31,Business travel,Business,1916,2,5,5,5,2,2,2,2,3,5,4,4,3,2,2,8.0,neutral or dissatisfied +96470,22471,Male,Loyal Customer,17,Personal Travel,Eco,143,2,5,0,3,1,0,5,1,2,2,5,2,3,1,0,0.0,neutral or dissatisfied +96471,41321,Female,Loyal Customer,43,Personal Travel,Eco,802,3,5,3,3,2,4,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +96472,10946,Female,Loyal Customer,17,Business travel,Business,3347,3,5,5,5,3,2,3,3,1,1,3,4,2,3,14,7.0,neutral or dissatisfied +96473,127801,Male,Loyal Customer,46,Business travel,Business,3247,3,3,3,3,3,4,5,5,5,5,5,4,5,4,3,0.0,satisfied +96474,12066,Male,Loyal Customer,47,Personal Travel,Eco,376,2,4,2,1,1,2,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +96475,88505,Female,Loyal Customer,43,Business travel,Business,3612,3,3,3,3,5,2,3,4,4,4,4,2,4,3,0,0.0,satisfied +96476,104720,Male,Loyal Customer,57,Business travel,Business,1407,2,2,2,2,4,5,4,5,5,5,5,5,5,5,6,0.0,satisfied +96477,21053,Male,disloyal Customer,54,Business travel,Eco,106,1,4,1,2,5,1,5,5,2,3,1,1,3,5,0,0.0,neutral or dissatisfied +96478,35349,Female,Loyal Customer,43,Business travel,Eco,1069,5,2,2,2,2,1,3,5,5,5,5,5,5,2,5,0.0,satisfied +96479,103105,Female,Loyal Customer,69,Personal Travel,Eco,687,3,5,2,2,5,5,5,5,5,2,5,3,5,5,10,2.0,neutral or dissatisfied +96480,65968,Female,Loyal Customer,29,Business travel,Business,1372,3,3,3,3,5,5,5,5,3,2,4,5,4,5,43,4.0,satisfied +96481,21379,Male,Loyal Customer,36,Business travel,Eco,528,2,1,5,1,2,2,2,2,4,4,4,2,4,2,26,8.0,neutral or dissatisfied +96482,118336,Male,Loyal Customer,46,Business travel,Eco,602,2,5,5,5,2,2,2,2,2,5,3,2,4,2,0,0.0,neutral or dissatisfied +96483,31937,Male,Loyal Customer,57,Business travel,Business,1677,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,5.0,satisfied +96484,22626,Male,Loyal Customer,30,Personal Travel,Eco,300,4,5,3,2,5,3,5,5,5,5,1,3,2,5,0,0.0,neutral or dissatisfied +96485,44708,Male,Loyal Customer,7,Personal Travel,Eco,67,2,5,2,4,5,2,5,5,4,4,5,4,5,5,28,29.0,neutral or dissatisfied +96486,96183,Female,Loyal Customer,55,Business travel,Business,460,3,3,3,3,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +96487,102753,Female,Loyal Customer,57,Personal Travel,Eco Plus,365,1,5,1,2,1,5,5,3,4,5,4,5,3,5,199,192.0,neutral or dissatisfied +96488,30954,Male,disloyal Customer,20,Business travel,Eco,1024,2,2,2,3,2,4,4,1,2,3,4,4,2,4,131,164.0,neutral or dissatisfied +96489,128083,Male,Loyal Customer,34,Business travel,Business,2845,1,0,0,3,0,2,2,3,2,3,3,2,1,2,0,0.0,neutral or dissatisfied +96490,66007,Male,disloyal Customer,54,Business travel,Business,1055,2,2,2,2,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +96491,43375,Female,Loyal Customer,30,Personal Travel,Eco,531,2,4,2,1,3,2,3,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +96492,59596,Male,disloyal Customer,21,Business travel,Eco,854,3,3,3,4,3,3,3,3,5,2,4,5,4,3,7,0.0,neutral or dissatisfied +96493,123001,Female,Loyal Customer,48,Business travel,Business,631,2,2,2,2,2,4,4,4,4,4,4,3,4,5,12,129.0,satisfied +96494,107788,Male,Loyal Customer,33,Personal Travel,Eco,666,4,4,5,5,3,5,3,3,2,2,4,5,3,3,39,18.0,neutral or dissatisfied +96495,46273,Male,Loyal Customer,52,Personal Travel,Eco,679,4,4,4,4,5,4,3,5,1,3,5,2,5,5,0,0.0,neutral or dissatisfied +96496,39711,Male,Loyal Customer,50,Business travel,Business,2824,0,5,0,2,4,1,1,1,1,1,1,1,1,3,0,0.0,satisfied +96497,111690,Male,Loyal Customer,29,Business travel,Business,1793,4,4,4,4,4,4,4,4,3,2,5,3,4,4,17,1.0,satisfied +96498,2637,Male,Loyal Customer,17,Personal Travel,Business,622,2,4,2,5,3,2,3,3,5,2,4,5,5,3,10,0.0,neutral or dissatisfied +96499,8628,Male,Loyal Customer,42,Business travel,Business,3893,5,5,5,5,4,4,4,5,3,5,5,4,4,4,129,143.0,satisfied +96500,112706,Male,disloyal Customer,39,Business travel,Eco,671,4,4,4,3,1,4,1,1,2,3,4,1,4,1,12,4.0,neutral or dissatisfied +96501,17369,Female,Loyal Customer,21,Personal Travel,Eco Plus,563,2,4,2,3,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +96502,57514,Male,Loyal Customer,16,Personal Travel,Eco,235,3,1,3,4,3,3,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +96503,273,Male,Loyal Customer,53,Business travel,Business,3357,2,2,2,2,5,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +96504,73550,Male,Loyal Customer,67,Personal Travel,Eco,594,2,5,2,2,1,2,1,1,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +96505,92619,Female,Loyal Customer,50,Business travel,Business,3157,3,3,3,3,3,5,4,4,4,4,4,3,4,5,78,84.0,satisfied +96506,44862,Male,Loyal Customer,35,Personal Travel,Eco,693,2,5,2,2,3,2,3,3,3,2,4,3,4,3,18,27.0,neutral or dissatisfied +96507,63537,Male,Loyal Customer,69,Business travel,Business,609,3,4,4,4,1,4,4,3,3,3,3,3,3,3,10,3.0,neutral or dissatisfied +96508,58510,Male,Loyal Customer,63,Personal Travel,Eco,719,2,4,2,2,5,2,5,5,4,2,5,4,4,5,10,0.0,neutral or dissatisfied +96509,67780,Female,Loyal Customer,57,Business travel,Eco,1438,1,2,2,2,4,3,4,1,1,1,1,1,1,1,7,10.0,neutral or dissatisfied +96510,119040,Female,Loyal Customer,52,Personal Travel,Eco,2378,1,4,1,1,4,3,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +96511,25360,Female,disloyal Customer,21,Business travel,Eco,591,4,0,4,1,5,4,5,5,4,3,3,4,2,5,9,0.0,satisfied +96512,126148,Female,disloyal Customer,22,Business travel,Business,468,5,5,5,4,4,5,4,4,3,2,5,3,5,4,0,0.0,satisfied +96513,15847,Male,Loyal Customer,49,Personal Travel,Eco,1107,3,2,3,2,3,3,3,3,3,4,2,3,3,3,0,0.0,neutral or dissatisfied +96514,115388,Female,Loyal Customer,36,Business travel,Eco,337,4,1,1,1,4,4,4,4,1,4,4,4,3,4,363,350.0,neutral or dissatisfied +96515,117574,Male,Loyal Customer,34,Business travel,Business,347,2,3,3,3,4,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +96516,31972,Male,disloyal Customer,33,Business travel,Business,101,2,2,2,4,4,2,3,4,3,5,3,2,4,4,0,0.0,neutral or dissatisfied +96517,76241,Male,Loyal Customer,31,Business travel,Eco,1399,2,3,3,3,2,3,2,2,2,4,3,2,4,2,6,13.0,neutral or dissatisfied +96518,101596,Male,disloyal Customer,25,Business travel,Eco,1371,1,0,0,3,4,1,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +96519,29811,Female,Loyal Customer,43,Business travel,Eco,95,5,2,2,2,5,3,4,5,5,5,5,3,5,2,0,0.0,satisfied +96520,70436,Male,Loyal Customer,49,Business travel,Business,3048,1,1,1,1,2,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +96521,106916,Female,Loyal Customer,42,Business travel,Business,2725,1,1,1,1,2,4,5,4,4,4,4,5,4,5,26,13.0,satisfied +96522,14845,Female,Loyal Customer,51,Personal Travel,Business,315,2,5,4,5,2,5,4,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +96523,124487,Male,Loyal Customer,26,Business travel,Business,1724,2,2,2,2,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +96524,80224,Male,Loyal Customer,59,Personal Travel,Eco,2153,3,4,3,3,1,3,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +96525,59736,Female,Loyal Customer,15,Personal Travel,Eco Plus,965,2,3,2,3,1,2,1,1,2,5,3,2,4,1,23,16.0,neutral or dissatisfied +96526,109377,Female,disloyal Customer,21,Business travel,Eco,1046,1,1,1,4,3,1,3,3,2,4,3,1,4,3,39,23.0,neutral or dissatisfied +96527,107957,Male,Loyal Customer,43,Business travel,Business,3980,3,3,4,3,4,5,4,4,4,4,4,5,4,5,12,0.0,satisfied +96528,125978,Female,Loyal Customer,31,Business travel,Business,2503,1,4,4,4,1,1,1,1,1,3,4,4,4,1,5,5.0,neutral or dissatisfied +96529,40313,Male,Loyal Customer,21,Personal Travel,Eco,358,2,5,2,4,5,2,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +96530,61507,Male,Loyal Customer,45,Business travel,Eco,753,4,2,2,2,4,4,4,4,1,2,3,2,2,4,0,8.0,satisfied +96531,38974,Female,disloyal Customer,21,Business travel,Business,113,5,0,5,2,1,5,1,1,3,1,2,4,2,1,0,17.0,satisfied +96532,15285,Male,Loyal Customer,57,Personal Travel,Eco,500,3,3,1,3,5,1,5,5,2,5,4,2,4,5,44,31.0,neutral or dissatisfied +96533,17418,Female,Loyal Customer,54,Business travel,Business,1626,3,3,3,3,5,5,3,5,5,5,5,2,5,1,34,38.0,satisfied +96534,102850,Male,Loyal Customer,30,Personal Travel,Eco,423,4,4,3,3,5,3,5,5,1,5,4,4,3,5,34,24.0,neutral or dissatisfied +96535,39098,Female,Loyal Customer,41,Business travel,Business,3805,4,4,4,4,2,1,3,4,4,4,4,2,4,3,7,4.0,satisfied +96536,30295,Male,Loyal Customer,24,Business travel,Business,1476,4,4,4,4,4,4,4,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +96537,30156,Male,Loyal Customer,23,Personal Travel,Eco,539,4,4,5,4,4,5,4,4,5,2,5,5,4,4,0,0.0,neutral or dissatisfied +96538,61138,Male,Loyal Customer,47,Business travel,Business,967,2,1,1,1,2,4,3,2,2,2,2,4,2,3,34,22.0,neutral or dissatisfied +96539,65735,Female,Loyal Customer,40,Business travel,Eco,1061,2,1,1,1,2,2,2,2,3,4,2,2,2,2,0,0.0,neutral or dissatisfied +96540,105103,Female,disloyal Customer,49,Business travel,Business,220,3,3,3,2,5,3,4,5,4,4,5,5,4,5,61,91.0,satisfied +96541,11727,Male,Loyal Customer,34,Business travel,Business,429,2,2,2,2,1,4,4,2,2,3,2,2,2,2,91,78.0,neutral or dissatisfied +96542,97418,Female,disloyal Customer,20,Business travel,Business,570,0,5,0,1,5,0,5,5,5,4,4,4,4,5,6,0.0,satisfied +96543,104706,Male,Loyal Customer,49,Business travel,Business,2240,1,1,3,1,3,4,5,5,5,5,4,3,5,5,52,31.0,satisfied +96544,60841,Female,Loyal Customer,49,Business travel,Eco,1754,2,5,5,5,1,3,2,2,2,2,2,3,2,2,9,0.0,neutral or dissatisfied +96545,40697,Male,Loyal Customer,37,Business travel,Business,2538,1,1,1,1,3,1,4,4,4,4,4,3,4,2,0,0.0,satisfied +96546,10328,Female,disloyal Customer,20,Business travel,Eco,308,2,2,2,3,5,2,5,5,4,4,4,4,3,5,11,16.0,neutral or dissatisfied +96547,108026,Male,Loyal Customer,47,Business travel,Business,3666,2,2,2,2,3,5,4,5,5,5,5,3,5,4,72,63.0,satisfied +96548,120950,Male,Loyal Customer,44,Business travel,Business,1564,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +96549,35016,Female,Loyal Customer,57,Business travel,Eco,740,3,1,1,1,2,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +96550,91767,Male,Loyal Customer,38,Business travel,Eco,190,4,5,4,5,4,4,4,4,1,5,4,4,1,4,5,5.0,satisfied +96551,14859,Female,Loyal Customer,54,Business travel,Eco,315,5,3,3,3,1,3,1,5,5,5,5,4,5,2,121,127.0,satisfied +96552,25696,Female,Loyal Customer,62,Business travel,Business,3699,2,4,2,2,4,2,3,5,5,5,5,2,5,5,0,0.0,satisfied +96553,97142,Male,Loyal Customer,37,Business travel,Business,1357,2,1,1,1,3,4,3,2,2,2,2,3,2,3,14,12.0,neutral or dissatisfied +96554,36602,Male,Loyal Customer,48,Business travel,Eco,1121,1,4,4,4,1,1,1,1,1,5,3,1,4,1,44,75.0,neutral or dissatisfied +96555,59431,Male,Loyal Customer,36,Personal Travel,Eco Plus,2367,2,5,2,3,2,3,3,3,3,3,4,3,5,3,196,150.0,neutral or dissatisfied +96556,16103,Female,Loyal Customer,20,Personal Travel,Eco,349,3,5,3,3,1,3,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +96557,100178,Male,Loyal Customer,8,Personal Travel,Eco,523,3,4,3,2,3,3,5,3,5,4,5,4,4,3,11,54.0,neutral or dissatisfied +96558,127875,Male,Loyal Customer,7,Personal Travel,Eco,1276,2,4,2,1,3,2,1,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +96559,103583,Female,Loyal Customer,15,Personal Travel,Eco,254,2,3,0,4,3,0,3,3,3,3,3,3,3,3,41,40.0,neutral or dissatisfied +96560,13942,Female,Loyal Customer,23,Business travel,Business,153,2,2,2,2,5,5,3,5,2,4,3,2,4,5,55,67.0,satisfied +96561,15516,Male,Loyal Customer,29,Business travel,Eco Plus,331,5,1,1,1,5,4,5,5,5,4,5,2,1,5,0,0.0,satisfied +96562,12796,Male,Loyal Customer,26,Business travel,Business,489,4,4,4,4,5,5,5,5,4,4,2,1,5,5,36,36.0,satisfied +96563,65969,Male,disloyal Customer,49,Business travel,Business,1372,4,4,4,5,4,4,4,4,3,4,4,4,5,4,13,0.0,satisfied +96564,109185,Female,disloyal Customer,24,Business travel,Business,616,5,2,5,3,1,5,1,1,4,2,5,3,4,1,0,0.0,satisfied +96565,98543,Male,Loyal Customer,58,Business travel,Business,3069,5,5,5,5,3,5,5,5,5,5,5,3,5,5,1,18.0,satisfied +96566,69139,Male,Loyal Customer,39,Business travel,Business,2248,4,4,2,4,5,5,5,3,5,4,5,5,3,5,3,10.0,satisfied +96567,125545,Female,disloyal Customer,18,Business travel,Eco,226,1,1,1,4,4,1,3,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +96568,114207,Female,disloyal Customer,36,Business travel,Business,862,4,4,4,1,2,4,2,2,3,5,4,4,4,2,0,1.0,neutral or dissatisfied +96569,32590,Male,Loyal Customer,44,Business travel,Eco,101,4,1,1,1,3,4,3,3,4,4,4,2,4,3,0,1.0,neutral or dissatisfied +96570,122544,Male,Loyal Customer,53,Business travel,Business,500,2,2,2,2,3,5,5,5,5,5,5,4,5,5,30,23.0,satisfied +96571,69623,Female,Loyal Customer,17,Personal Travel,Eco Plus,2475,2,4,2,3,2,2,2,4,3,4,3,2,2,2,150,164.0,neutral or dissatisfied +96572,84719,Female,Loyal Customer,46,Business travel,Business,3892,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +96573,4405,Female,Loyal Customer,33,Personal Travel,Eco Plus,618,1,4,2,3,2,5,2,5,2,4,4,2,4,2,355,342.0,neutral or dissatisfied +96574,5499,Male,Loyal Customer,53,Business travel,Business,3361,2,2,2,2,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +96575,13542,Female,disloyal Customer,39,Business travel,Eco,106,1,2,1,2,4,1,4,4,3,4,3,4,2,4,0,0.0,neutral or dissatisfied +96576,102667,Male,Loyal Customer,64,Business travel,Eco,255,3,3,1,3,3,3,3,3,2,5,4,4,4,3,16,9.0,neutral or dissatisfied +96577,77679,Female,disloyal Customer,24,Business travel,Business,731,4,3,3,3,4,3,4,4,3,5,5,5,4,4,0,0.0,satisfied +96578,64130,Male,Loyal Customer,36,Personal Travel,Eco Plus,2288,5,3,5,4,5,5,5,3,1,3,4,5,3,5,0,0.0,satisfied +96579,77020,Female,disloyal Customer,37,Business travel,Eco,368,1,0,1,3,1,1,1,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +96580,93592,Male,Loyal Customer,49,Business travel,Business,3733,0,4,0,4,5,5,5,4,4,5,5,5,4,5,135,142.0,satisfied +96581,85747,Male,Loyal Customer,48,Business travel,Business,666,4,4,4,4,3,3,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +96582,12792,Male,Loyal Customer,26,Business travel,Business,2685,3,3,3,3,4,4,4,1,5,3,1,4,4,4,123,132.0,satisfied +96583,104716,Female,Loyal Customer,15,Personal Travel,Business,1342,3,5,3,4,1,3,3,1,5,2,3,4,4,1,1,16.0,neutral or dissatisfied +96584,110154,Female,disloyal Customer,44,Business travel,Eco,482,3,2,3,4,5,3,5,5,2,3,3,4,3,5,0,0.0,neutral or dissatisfied +96585,13837,Male,Loyal Customer,55,Business travel,Business,1536,4,4,3,4,1,5,1,4,4,4,4,4,4,4,0,0.0,satisfied +96586,62983,Male,disloyal Customer,39,Business travel,Eco,862,2,3,3,3,2,3,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +96587,60381,Male,Loyal Customer,21,Business travel,Business,1452,2,2,2,2,3,4,3,3,3,4,5,3,4,3,54,38.0,satisfied +96588,121141,Male,Loyal Customer,26,Business travel,Business,2402,2,2,3,2,5,4,4,3,3,5,4,4,3,4,286,330.0,satisfied +96589,12444,Female,Loyal Customer,7,Personal Travel,Eco,127,2,1,2,4,2,2,2,2,3,1,4,2,3,2,75,63.0,neutral or dissatisfied +96590,6901,Male,Loyal Customer,38,Business travel,Eco,265,4,3,3,3,4,4,4,4,3,2,4,3,3,4,44,54.0,neutral or dissatisfied +96591,37043,Male,Loyal Customer,34,Personal Travel,Eco,1105,4,5,4,1,5,4,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +96592,1324,Female,Loyal Customer,48,Business travel,Business,3883,0,4,0,1,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +96593,69166,Female,Loyal Customer,39,Business travel,Business,3226,3,3,3,3,4,4,5,4,4,4,5,5,4,5,0,0.0,satisfied +96594,30946,Male,Loyal Customer,12,Business travel,Business,3634,3,5,5,5,3,3,3,3,2,2,3,4,3,3,31,23.0,neutral or dissatisfied +96595,98176,Male,Loyal Customer,30,Business travel,Business,3497,1,1,1,1,3,4,3,3,4,2,5,3,4,3,0,1.0,satisfied +96596,127388,Female,Loyal Customer,25,Business travel,Business,1009,2,2,2,2,3,3,3,3,4,2,5,3,4,3,5,0.0,satisfied +96597,61761,Female,Loyal Customer,61,Personal Travel,Eco,1303,2,5,2,1,4,3,5,5,5,2,3,3,5,5,4,0.0,neutral or dissatisfied +96598,20500,Female,Loyal Customer,27,Personal Travel,Eco,139,3,5,0,3,4,0,2,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +96599,13633,Male,disloyal Customer,25,Business travel,Eco,1014,2,2,2,3,4,2,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +96600,78317,Male,disloyal Customer,10,Business travel,Eco,1930,3,3,3,2,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +96601,4241,Female,Loyal Customer,48,Business travel,Eco,1020,2,5,5,5,1,3,4,2,2,2,2,2,2,4,33,42.0,neutral or dissatisfied +96602,6363,Male,Loyal Customer,41,Business travel,Business,3653,0,4,0,5,4,4,4,2,2,2,2,5,2,4,0,4.0,satisfied +96603,91837,Female,Loyal Customer,47,Personal Travel,Eco Plus,626,2,5,3,5,4,5,4,5,5,3,5,4,5,3,4,0.0,neutral or dissatisfied +96604,68773,Male,disloyal Customer,21,Business travel,Eco,861,4,3,3,3,4,3,4,4,1,1,2,2,3,4,3,0.0,neutral or dissatisfied +96605,107377,Male,Loyal Customer,7,Personal Travel,Business,468,1,1,1,3,2,1,2,2,1,5,4,1,4,2,93,80.0,neutral or dissatisfied +96606,100159,Female,Loyal Customer,37,Business travel,Business,317,3,5,5,5,1,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +96607,30034,Male,disloyal Customer,20,Business travel,Eco,123,1,0,1,4,3,1,3,3,3,4,1,3,1,3,0,0.0,neutral or dissatisfied +96608,54252,Female,Loyal Customer,37,Business travel,Business,822,5,5,5,5,3,3,2,3,3,3,3,1,3,2,9,0.0,satisfied +96609,86243,Male,Loyal Customer,45,Personal Travel,Eco,356,3,3,3,4,3,3,3,3,3,2,4,3,3,3,0,15.0,neutral or dissatisfied +96610,62847,Male,Loyal Customer,20,Business travel,Eco Plus,2504,4,4,4,4,4,2,4,4,2,4,3,4,3,4,0,0.0,neutral or dissatisfied +96611,39977,Male,Loyal Customer,50,Business travel,Business,1979,3,3,4,3,1,1,5,3,3,3,3,2,3,1,0,0.0,satisfied +96612,106419,Female,Loyal Customer,38,Personal Travel,Eco,488,2,5,2,3,4,2,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +96613,2226,Female,disloyal Customer,45,Business travel,Eco,859,4,5,5,4,3,5,3,3,2,4,3,1,3,3,53,59.0,neutral or dissatisfied +96614,4321,Female,disloyal Customer,30,Business travel,Eco,589,2,1,2,3,2,2,2,2,4,4,3,3,4,2,36,40.0,neutral or dissatisfied +96615,18647,Male,Loyal Customer,24,Personal Travel,Eco,201,2,3,2,4,4,2,4,4,4,2,4,4,3,4,17,5.0,neutral or dissatisfied +96616,32514,Female,disloyal Customer,59,Business travel,Eco,102,4,3,4,5,1,4,1,1,1,3,1,5,1,1,0,0.0,neutral or dissatisfied +96617,39188,Male,Loyal Customer,57,Business travel,Eco Plus,237,4,4,3,3,4,4,4,4,5,3,4,1,4,4,0,13.0,satisfied +96618,92284,Female,Loyal Customer,12,Personal Travel,Eco,2036,3,5,3,3,1,3,4,1,4,3,3,4,5,1,16,0.0,neutral or dissatisfied +96619,87322,Male,Loyal Customer,56,Personal Travel,Eco Plus,577,2,4,2,4,2,2,1,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +96620,111573,Female,disloyal Customer,20,Business travel,Eco,483,3,0,3,3,5,3,2,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +96621,4955,Female,Loyal Customer,59,Business travel,Business,2802,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,2.0,satisfied +96622,44463,Male,disloyal Customer,40,Business travel,Eco,196,3,0,3,3,5,3,5,5,3,1,4,3,5,5,0,0.0,neutral or dissatisfied +96623,112617,Male,Loyal Customer,45,Personal Travel,Eco,602,3,5,3,2,5,3,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +96624,63858,Female,Loyal Customer,54,Business travel,Business,2484,2,2,2,2,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +96625,109826,Male,Loyal Customer,49,Business travel,Business,1079,4,4,4,4,3,5,5,5,5,5,5,4,5,3,21,11.0,satisfied +96626,122971,Male,Loyal Customer,48,Business travel,Business,2413,3,3,3,3,4,5,4,5,5,5,5,3,5,5,20,10.0,satisfied +96627,123617,Male,Loyal Customer,52,Business travel,Business,3432,0,4,0,4,3,4,5,4,4,4,4,4,4,3,0,5.0,satisfied +96628,77065,Female,Loyal Customer,44,Business travel,Business,991,3,3,3,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +96629,109004,Female,Loyal Customer,40,Business travel,Business,2346,2,2,2,2,3,4,4,4,4,4,4,3,4,3,39,36.0,satisfied +96630,94163,Male,disloyal Customer,25,Business travel,Business,148,4,0,3,3,3,3,3,3,4,4,5,3,4,3,30,22.0,satisfied +96631,78584,Female,Loyal Customer,8,Personal Travel,Eco,630,2,5,2,2,4,2,5,4,3,2,4,3,5,4,65,71.0,neutral or dissatisfied +96632,41987,Male,Loyal Customer,60,Personal Travel,Business,106,4,4,4,5,4,4,5,2,2,4,4,3,2,3,0,0.0,satisfied +96633,88787,Female,disloyal Customer,45,Business travel,Eco Plus,594,3,2,2,3,4,3,4,4,3,2,3,2,3,4,13,12.0,neutral or dissatisfied +96634,73105,Male,Loyal Customer,28,Business travel,Business,2174,2,1,2,2,5,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +96635,2265,Male,Loyal Customer,50,Business travel,Business,690,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +96636,24103,Female,Loyal Customer,40,Business travel,Eco,779,4,2,5,2,4,4,4,4,1,2,3,4,4,4,0,2.0,satisfied +96637,47347,Female,Loyal Customer,48,Business travel,Business,588,3,3,2,3,1,3,2,5,5,4,5,1,5,1,0,0.0,satisfied +96638,56086,Male,Loyal Customer,46,Business travel,Eco Plus,2586,3,2,2,2,3,3,3,1,2,2,3,3,2,3,37,34.0,neutral or dissatisfied +96639,88497,Female,Loyal Customer,65,Business travel,Business,181,3,5,5,5,2,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +96640,21025,Female,Loyal Customer,33,Business travel,Eco,106,5,5,5,5,5,5,5,5,1,4,3,2,3,5,0,0.0,satisfied +96641,52596,Female,disloyal Customer,22,Business travel,Eco,119,4,0,4,2,4,4,2,4,3,3,2,2,2,4,0,4.0,satisfied +96642,60725,Male,Loyal Customer,46,Personal Travel,Eco,1725,3,4,3,5,1,3,1,1,5,4,4,4,4,1,2,0.0,neutral or dissatisfied +96643,118031,Female,disloyal Customer,27,Business travel,Business,1262,2,2,2,3,3,2,3,3,3,2,5,5,4,3,6,14.0,neutral or dissatisfied +96644,27402,Female,disloyal Customer,46,Business travel,Eco,978,3,3,3,1,5,3,5,5,4,4,2,1,1,5,0,8.0,neutral or dissatisfied +96645,90456,Male,Loyal Customer,39,Business travel,Business,545,1,1,1,1,2,5,5,2,2,2,2,5,2,3,29,5.0,satisfied +96646,68064,Female,Loyal Customer,29,Business travel,Business,3818,3,3,3,3,5,5,5,5,5,4,5,3,4,5,0,0.0,satisfied +96647,77812,Male,Loyal Customer,46,Personal Travel,Eco,689,3,2,3,3,4,3,4,4,2,4,2,3,2,4,0,6.0,neutral or dissatisfied +96648,91296,Female,Loyal Customer,47,Business travel,Business,581,3,3,3,3,2,5,5,5,5,5,5,4,5,5,34,27.0,satisfied +96649,113461,Female,Loyal Customer,39,Business travel,Business,236,0,0,0,3,2,4,4,3,3,3,3,5,3,4,3,0.0,satisfied +96650,54401,Female,Loyal Customer,61,Business travel,Eco,305,2,4,4,4,1,4,4,2,2,2,2,4,2,3,7,0.0,neutral or dissatisfied +96651,86495,Male,Loyal Customer,43,Personal Travel,Eco,794,2,3,2,4,4,2,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +96652,9784,Male,Loyal Customer,15,Personal Travel,Eco,383,2,4,2,5,5,2,5,5,4,5,5,3,5,5,0,10.0,neutral or dissatisfied +96653,16444,Male,Loyal Customer,42,Business travel,Eco,529,2,5,5,5,2,2,2,2,2,3,4,4,4,2,0,0.0,neutral or dissatisfied +96654,66410,Male,disloyal Customer,37,Business travel,Business,1162,2,2,2,3,4,2,3,4,4,5,5,2,1,4,0,0.0,neutral or dissatisfied +96655,18171,Female,disloyal Customer,38,Business travel,Eco,363,2,4,2,3,3,2,5,3,1,3,3,1,4,3,87,74.0,neutral or dissatisfied +96656,114787,Female,Loyal Customer,64,Business travel,Business,371,3,3,3,3,5,5,5,4,4,4,4,3,4,5,15,11.0,satisfied +96657,120120,Female,Loyal Customer,62,Personal Travel,Eco,1576,1,5,1,1,3,5,4,4,4,1,4,3,4,5,0,2.0,neutral or dissatisfied +96658,69286,Female,Loyal Customer,60,Personal Travel,Eco,733,2,3,2,3,1,5,5,2,2,2,3,3,2,4,0,0.0,neutral or dissatisfied +96659,1983,Male,Loyal Customer,40,Personal Travel,Eco,293,1,4,2,4,1,2,1,1,3,3,5,5,4,1,27,35.0,neutral or dissatisfied +96660,20628,Male,Loyal Customer,26,Personal Travel,Eco,783,3,2,3,3,3,3,3,3,1,2,2,1,3,3,3,0.0,neutral or dissatisfied +96661,26506,Female,Loyal Customer,29,Business travel,Business,829,3,1,1,1,3,3,3,3,2,3,3,3,4,3,0,0.0,neutral or dissatisfied +96662,121703,Male,Loyal Customer,22,Business travel,Business,2277,4,4,4,4,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +96663,55847,Male,Loyal Customer,25,Personal Travel,Eco,1416,3,4,3,3,3,3,3,3,4,5,3,3,5,3,65,63.0,neutral or dissatisfied +96664,114200,Female,disloyal Customer,39,Business travel,Business,862,2,2,2,1,3,2,3,3,3,2,5,4,5,3,18,2.0,neutral or dissatisfied +96665,83669,Female,Loyal Customer,44,Business travel,Business,577,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +96666,58102,Male,Loyal Customer,68,Personal Travel,Eco,612,2,4,2,3,2,2,2,2,4,4,2,1,1,2,3,0.0,neutral or dissatisfied +96667,86192,Male,Loyal Customer,59,Business travel,Business,226,2,2,2,2,4,5,5,5,5,5,5,3,5,3,7,0.0,satisfied +96668,9542,Male,Loyal Customer,42,Business travel,Business,3719,2,2,2,2,3,5,5,5,5,5,5,3,5,5,49,49.0,satisfied +96669,32971,Male,Loyal Customer,18,Personal Travel,Eco,101,3,4,0,3,4,0,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +96670,93647,Female,Loyal Customer,55,Business travel,Business,547,3,3,3,3,4,4,5,2,2,2,2,3,2,3,0,4.0,satisfied +96671,48437,Male,Loyal Customer,52,Business travel,Business,819,5,5,5,5,1,4,2,5,5,5,5,1,5,1,62,50.0,satisfied +96672,51214,Female,Loyal Customer,35,Business travel,Eco Plus,372,5,2,2,2,5,4,5,5,4,4,4,5,1,5,0,0.0,satisfied +96673,24171,Male,Loyal Customer,42,Business travel,Eco,134,2,2,2,2,2,2,2,2,3,4,3,2,1,2,143,159.0,neutral or dissatisfied +96674,89709,Female,Loyal Customer,56,Personal Travel,Eco,1080,2,1,2,3,2,4,4,2,2,2,2,3,2,4,0,11.0,neutral or dissatisfied +96675,85110,Female,Loyal Customer,57,Business travel,Business,689,5,5,5,5,2,4,5,2,2,2,2,5,2,5,32,11.0,satisfied +96676,56351,Male,Loyal Customer,9,Personal Travel,Eco,200,5,4,5,4,2,5,2,2,4,4,4,4,5,2,2,10.0,satisfied +96677,50551,Female,Loyal Customer,62,Personal Travel,Eco,304,1,1,1,2,5,3,2,3,3,1,1,4,3,4,2,10.0,neutral or dissatisfied +96678,129230,Female,disloyal Customer,48,Business travel,Business,1464,5,5,5,3,5,5,5,5,4,4,5,4,5,5,0,0.0,satisfied +96679,126141,Male,Loyal Customer,54,Business travel,Eco,590,2,5,2,5,3,2,3,3,2,5,4,4,4,3,35,14.0,neutral or dissatisfied +96680,114517,Male,disloyal Customer,30,Business travel,Business,337,2,2,2,3,5,2,3,5,3,1,3,3,3,5,0,21.0,neutral or dissatisfied +96681,13194,Female,Loyal Customer,63,Business travel,Business,3075,2,4,2,2,4,2,3,3,3,3,3,4,3,2,2,0.0,satisfied +96682,25921,Male,disloyal Customer,33,Business travel,Eco,594,2,3,2,3,3,2,3,3,1,5,1,4,4,3,8,0.0,neutral or dissatisfied +96683,45539,Male,Loyal Customer,49,Business travel,Business,3566,3,1,1,1,3,4,3,3,3,3,3,1,3,2,48,41.0,neutral or dissatisfied +96684,106475,Female,Loyal Customer,53,Business travel,Business,3739,4,4,4,4,2,4,5,4,4,4,4,5,4,4,47,29.0,satisfied +96685,125397,Male,Loyal Customer,51,Business travel,Business,1440,2,2,5,2,2,5,3,5,5,5,5,4,5,2,8,2.0,satisfied +96686,123525,Female,Loyal Customer,38,Business travel,Business,2296,4,4,4,4,5,5,5,3,5,3,5,5,4,5,0,17.0,satisfied +96687,49284,Male,Loyal Customer,52,Business travel,Business,3641,2,2,2,2,5,1,3,4,4,4,4,5,4,1,0,0.0,satisfied +96688,122227,Female,Loyal Customer,51,Business travel,Business,1548,2,2,2,2,5,2,2,2,2,2,2,4,2,3,0,12.0,neutral or dissatisfied +96689,62868,Female,disloyal Customer,22,Business travel,Eco,712,2,2,2,3,5,2,5,5,1,3,2,3,3,5,29,25.0,neutral or dissatisfied +96690,86186,Female,Loyal Customer,72,Business travel,Business,2004,2,4,4,4,2,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +96691,94651,Female,disloyal Customer,40,Business travel,Business,189,2,2,2,4,3,2,3,3,2,5,3,2,4,3,0,0.0,neutral or dissatisfied +96692,86870,Female,Loyal Customer,46,Business travel,Business,484,2,2,2,2,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +96693,44210,Male,Loyal Customer,49,Business travel,Business,235,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +96694,79824,Male,Loyal Customer,40,Business travel,Business,950,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,4.0,satisfied +96695,103137,Male,Loyal Customer,66,Business travel,Eco Plus,460,1,4,4,4,1,1,1,3,5,4,3,1,3,1,248,255.0,neutral or dissatisfied +96696,36014,Male,disloyal Customer,34,Business travel,Eco,399,3,0,3,3,1,3,1,1,2,1,3,3,3,1,0,0.0,neutral or dissatisfied +96697,18189,Male,Loyal Customer,35,Business travel,Eco,228,3,2,3,2,3,3,3,3,4,5,5,4,5,3,8,0.0,satisfied +96698,73198,Female,Loyal Customer,77,Business travel,Business,2353,5,5,5,5,2,1,4,4,4,4,4,2,4,4,0,0.0,satisfied +96699,80013,Male,Loyal Customer,7,Personal Travel,Eco,1069,2,1,2,1,2,2,2,2,3,5,1,1,2,2,0,0.0,neutral or dissatisfied +96700,15675,Female,disloyal Customer,30,Business travel,Eco,641,3,0,3,3,1,3,5,1,4,5,1,3,4,1,0,0.0,neutral or dissatisfied +96701,86618,Female,disloyal Customer,36,Business travel,Business,746,2,3,3,4,2,3,3,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +96702,18423,Male,Loyal Customer,43,Business travel,Eco,955,5,2,2,2,5,5,5,5,1,5,2,4,5,5,0,0.0,satisfied +96703,1784,Female,disloyal Customer,40,Business travel,Business,408,2,2,2,2,2,2,5,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +96704,50882,Female,Loyal Customer,24,Personal Travel,Eco,373,2,2,2,3,4,2,4,4,2,4,3,4,4,4,2,0.0,neutral or dissatisfied +96705,54844,Male,Loyal Customer,58,Business travel,Eco,775,2,2,1,2,2,2,2,2,2,5,4,3,4,2,0,14.0,neutral or dissatisfied +96706,6370,Male,Loyal Customer,55,Business travel,Eco,315,3,4,4,4,4,3,4,4,3,2,3,2,4,4,4,7.0,neutral or dissatisfied +96707,14716,Male,Loyal Customer,44,Personal Travel,Eco,419,2,3,2,4,5,2,5,5,1,5,2,5,2,5,9,0.0,neutral or dissatisfied +96708,42597,Male,Loyal Customer,56,Personal Travel,Eco,1201,2,4,2,4,3,2,4,3,1,4,3,5,2,3,32,21.0,neutral or dissatisfied +96709,49889,Male,Loyal Customer,20,Business travel,Business,250,2,3,2,3,2,2,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +96710,73623,Male,Loyal Customer,42,Business travel,Business,1833,4,4,5,4,3,4,5,4,4,4,5,4,4,4,0,0.0,satisfied +96711,52811,Female,disloyal Customer,18,Business travel,Eco,2402,1,2,2,3,3,1,3,3,3,2,5,1,3,3,5,0.0,neutral or dissatisfied +96712,62604,Male,Loyal Customer,26,Personal Travel,Eco,1846,5,4,5,3,3,5,5,3,3,1,2,2,4,3,0,2.0,satisfied +96713,114498,Male,disloyal Customer,24,Business travel,Eco,446,0,4,0,1,2,0,2,2,3,2,5,4,5,2,63,63.0,satisfied +96714,53364,Male,Loyal Customer,20,Business travel,Business,1452,1,1,1,1,5,5,5,5,2,1,5,5,3,5,0,0.0,satisfied +96715,52918,Male,Loyal Customer,54,Business travel,Business,679,3,3,3,3,5,5,5,4,3,3,4,5,2,5,182,158.0,satisfied +96716,4272,Male,Loyal Customer,58,Business travel,Eco,502,4,4,4,4,4,4,4,4,4,3,4,3,3,4,0,0.0,neutral or dissatisfied +96717,73512,Female,Loyal Customer,16,Business travel,Eco Plus,1144,4,2,2,2,4,4,4,4,3,2,5,3,4,4,2,0.0,satisfied +96718,91560,Male,Loyal Customer,12,Personal Travel,Eco,680,4,4,4,2,3,4,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +96719,69049,Female,Loyal Customer,54,Business travel,Business,1389,3,3,3,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +96720,59976,Female,Loyal Customer,14,Personal Travel,Eco,937,0,4,0,4,3,0,3,3,5,4,5,5,4,3,11,4.0,satisfied +96721,58047,Male,Loyal Customer,53,Business travel,Business,2530,4,4,4,4,4,4,4,5,5,5,5,5,5,5,0,33.0,satisfied +96722,111441,Female,Loyal Customer,57,Business travel,Business,2721,2,2,2,2,5,5,4,4,4,4,4,5,4,4,18,13.0,satisfied +96723,126739,Female,Loyal Customer,43,Business travel,Business,1021,3,3,3,3,5,3,4,3,3,3,3,4,3,3,0,7.0,neutral or dissatisfied +96724,119782,Male,Loyal Customer,31,Personal Travel,Business,912,4,4,5,3,2,5,1,2,5,5,4,5,5,2,0,0.0,satisfied +96725,103354,Male,Loyal Customer,49,Business travel,Business,1587,3,3,3,3,5,4,4,5,5,5,5,5,5,4,57,47.0,satisfied +96726,78417,Male,disloyal Customer,39,Business travel,Eco,453,1,4,1,4,3,1,3,3,2,4,4,3,4,3,71,70.0,neutral or dissatisfied +96727,121951,Male,Loyal Customer,31,Business travel,Business,347,2,2,2,2,4,4,4,4,5,2,4,3,4,4,0,0.0,satisfied +96728,7126,Female,Loyal Customer,60,Business travel,Business,139,0,5,0,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +96729,58432,Female,Loyal Customer,61,Business travel,Business,3377,3,3,3,3,4,4,3,3,3,3,3,1,3,1,13,0.0,neutral or dissatisfied +96730,104592,Female,Loyal Customer,31,Personal Travel,Eco,369,2,5,2,4,3,2,1,3,1,3,5,1,3,3,1,7.0,neutral or dissatisfied +96731,65975,Female,disloyal Customer,21,Business travel,Eco,1372,3,3,3,3,5,3,5,5,3,1,3,1,4,5,10,0.0,neutral or dissatisfied +96732,12878,Male,Loyal Customer,42,Business travel,Business,3433,4,4,4,4,5,3,2,5,5,5,5,2,5,2,28,39.0,satisfied +96733,24888,Female,Loyal Customer,42,Business travel,Eco,397,4,3,3,3,4,2,2,4,4,4,4,5,4,1,0,0.0,satisfied +96734,48048,Male,Loyal Customer,51,Business travel,Eco,710,4,1,1,1,4,4,4,4,5,2,2,2,4,4,0,0.0,satisfied +96735,45530,Female,Loyal Customer,50,Business travel,Eco,154,3,1,1,1,4,1,1,3,3,3,3,3,3,3,0,3.0,neutral or dissatisfied +96736,63134,Male,disloyal Customer,22,Business travel,Eco,447,3,4,3,3,1,3,1,1,3,3,4,4,4,1,10,5.0,neutral or dissatisfied +96737,80082,Female,Loyal Customer,25,Business travel,Eco Plus,950,1,2,2,2,1,1,4,1,3,4,3,2,4,1,82,52.0,neutral or dissatisfied +96738,125009,Male,Loyal Customer,29,Personal Travel,Eco,184,2,4,2,4,1,2,5,1,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +96739,16566,Female,Loyal Customer,39,Business travel,Business,3119,5,5,5,5,5,5,1,4,4,5,4,5,4,1,0,0.0,satisfied +96740,75687,Female,Loyal Customer,25,Business travel,Business,868,5,5,3,5,4,5,4,4,4,3,5,4,5,4,0,0.0,satisfied +96741,83416,Female,disloyal Customer,25,Business travel,Eco,632,2,2,2,3,4,2,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +96742,115960,Female,Loyal Customer,12,Personal Travel,Eco,337,2,1,2,4,4,2,4,4,2,1,4,4,4,4,2,0.0,neutral or dissatisfied +96743,79047,Female,disloyal Customer,30,Business travel,Eco,356,2,4,2,3,2,2,5,2,2,1,3,2,4,2,0,10.0,neutral or dissatisfied +96744,127807,Female,disloyal Customer,29,Business travel,Eco,1044,2,2,2,3,5,2,5,5,4,4,4,4,3,5,44,36.0,neutral or dissatisfied +96745,9851,Female,Loyal Customer,62,Business travel,Business,717,3,5,5,5,3,2,3,3,3,3,3,2,3,1,55,31.0,neutral or dissatisfied +96746,9037,Male,Loyal Customer,42,Business travel,Business,3401,2,2,5,2,3,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +96747,75806,Female,Loyal Customer,42,Business travel,Business,2194,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +96748,118539,Male,Loyal Customer,38,Business travel,Business,2531,3,3,3,3,4,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +96749,124815,Female,Loyal Customer,45,Business travel,Business,280,3,3,3,3,3,3,3,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +96750,35810,Female,Loyal Customer,37,Business travel,Eco,937,5,2,2,2,5,5,5,5,4,4,3,5,5,5,0,0.0,satisfied +96751,114598,Female,Loyal Customer,48,Business travel,Business,358,2,2,2,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +96752,93089,Female,Loyal Customer,69,Personal Travel,Eco,860,2,4,2,4,5,5,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +96753,81024,Female,Loyal Customer,30,Business travel,Business,1399,4,4,4,4,5,5,5,5,4,4,4,4,4,5,15,38.0,satisfied +96754,35556,Female,Loyal Customer,53,Personal Travel,Eco,972,2,2,2,4,4,3,3,4,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +96755,112127,Male,Loyal Customer,7,Personal Travel,Eco,977,4,5,4,4,4,4,4,4,4,5,4,4,3,4,189,185.0,neutral or dissatisfied +96756,83542,Male,Loyal Customer,23,Business travel,Business,1121,2,2,1,2,4,4,4,4,5,3,5,3,5,4,7,0.0,satisfied +96757,59139,Female,Loyal Customer,36,Personal Travel,Eco,1726,1,5,1,3,5,1,5,5,4,5,5,5,5,5,14,0.0,neutral or dissatisfied +96758,70386,Female,Loyal Customer,24,Business travel,Business,1562,4,4,4,4,3,3,3,3,4,3,5,3,4,3,0,0.0,satisfied +96759,70827,Male,Loyal Customer,56,Business travel,Business,3670,1,1,1,1,3,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +96760,90513,Female,Loyal Customer,60,Business travel,Business,1606,3,3,3,3,5,5,4,4,4,4,4,3,4,5,1,2.0,satisfied +96761,28969,Female,Loyal Customer,42,Business travel,Eco,605,5,3,3,3,2,2,5,5,5,5,5,2,5,4,0,0.0,satisfied +96762,33849,Male,Loyal Customer,33,Business travel,Business,1698,2,4,4,4,2,2,2,2,4,1,2,4,4,2,0,0.0,neutral or dissatisfied +96763,117595,Female,Loyal Customer,60,Business travel,Eco,872,3,2,2,2,4,4,4,3,3,3,3,1,3,4,16,0.0,neutral or dissatisfied +96764,121906,Male,Loyal Customer,12,Personal Travel,Eco,366,3,4,3,3,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +96765,99217,Female,Loyal Customer,53,Business travel,Business,1855,2,2,2,2,4,5,4,3,3,4,3,3,3,4,3,5.0,satisfied +96766,95073,Male,Loyal Customer,42,Personal Travel,Eco,239,4,5,4,5,5,4,5,5,4,5,4,4,5,5,31,29.0,neutral or dissatisfied +96767,64473,Female,disloyal Customer,23,Business travel,Business,224,5,0,5,3,2,5,4,2,3,2,5,3,5,2,130,121.0,satisfied +96768,92948,Male,Loyal Customer,35,Personal Travel,Eco,151,2,2,2,2,3,2,3,3,3,5,3,1,2,3,47,70.0,neutral or dissatisfied +96769,31033,Female,disloyal Customer,23,Business travel,Eco,775,4,4,4,1,2,4,2,2,5,4,5,4,3,2,46,68.0,satisfied +96770,11554,Female,Loyal Customer,30,Business travel,Business,3432,1,1,1,1,5,5,5,4,2,4,4,5,3,5,140,125.0,satisfied +96771,76926,Male,Loyal Customer,70,Business travel,Eco,1823,3,4,4,4,3,3,3,3,2,4,3,4,4,3,0,0.0,neutral or dissatisfied +96772,94804,Male,disloyal Customer,20,Business travel,Business,277,1,1,1,3,3,1,3,3,3,5,3,2,3,3,4,6.0,neutral or dissatisfied +96773,126131,Female,Loyal Customer,30,Business travel,Business,3576,1,1,1,1,5,5,5,5,4,2,4,3,4,5,7,0.0,satisfied +96774,14403,Male,Loyal Customer,39,Personal Travel,Eco,789,4,5,3,3,3,4,4,4,5,5,5,4,4,4,160,144.0,neutral or dissatisfied +96775,111061,Male,Loyal Customer,49,Personal Travel,Eco,197,2,2,2,2,2,2,2,2,3,1,2,2,2,2,42,31.0,neutral or dissatisfied +96776,52642,Male,Loyal Customer,30,Personal Travel,Eco,160,3,5,3,4,5,3,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +96777,2870,Female,Loyal Customer,39,Business travel,Business,3827,2,3,3,3,4,4,3,2,2,2,2,3,2,4,24,22.0,neutral or dissatisfied +96778,45332,Male,Loyal Customer,58,Business travel,Business,2009,0,5,0,2,4,2,3,4,4,4,4,3,4,1,0,0.0,satisfied +96779,36943,Female,Loyal Customer,48,Business travel,Business,718,3,5,5,5,4,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +96780,88800,Female,Loyal Customer,27,Business travel,Eco Plus,406,2,3,3,3,2,2,2,2,1,2,3,2,4,2,35,41.0,neutral or dissatisfied +96781,69234,Male,Loyal Customer,39,Business travel,Business,3692,1,1,1,1,2,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +96782,72465,Male,Loyal Customer,26,Business travel,Business,1017,3,3,3,3,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +96783,107913,Female,Loyal Customer,58,Personal Travel,Eco,861,3,5,3,2,2,4,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +96784,13737,Female,Loyal Customer,57,Business travel,Business,441,2,2,2,2,2,1,3,5,5,5,5,4,5,2,0,0.0,satisfied +96785,14363,Female,Loyal Customer,80,Business travel,Business,548,3,3,3,3,2,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +96786,106556,Female,Loyal Customer,13,Personal Travel,Eco Plus,719,4,5,4,2,2,4,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +96787,82384,Male,Loyal Customer,31,Business travel,Business,500,5,5,5,5,4,4,4,4,5,2,5,5,4,4,52,43.0,satisfied +96788,65602,Male,Loyal Customer,33,Business travel,Eco,237,5,5,3,3,5,5,5,5,3,3,5,1,3,5,31,33.0,satisfied +96789,93446,Male,Loyal Customer,65,Personal Travel,Eco,605,3,5,3,3,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +96790,55575,Female,Loyal Customer,51,Business travel,Business,3863,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +96791,60971,Female,Loyal Customer,69,Personal Travel,Eco,888,1,4,2,1,3,4,5,4,4,2,4,4,4,3,1,23.0,neutral or dissatisfied +96792,22417,Female,disloyal Customer,27,Business travel,Eco,143,1,2,2,4,1,2,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +96793,65915,Female,disloyal Customer,24,Business travel,Eco,569,0,5,0,4,4,0,1,4,5,5,4,4,5,4,46,38.0,satisfied +96794,57854,Male,Loyal Customer,18,Business travel,Business,2457,1,2,2,2,2,1,1,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +96795,13966,Male,Loyal Customer,29,Personal Travel,Eco,317,3,1,1,4,2,1,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +96796,20981,Male,disloyal Customer,56,Personal Travel,Eco,689,3,1,3,4,3,3,3,3,2,1,4,3,3,3,0,0.0,neutral or dissatisfied +96797,18559,Male,Loyal Customer,20,Business travel,Business,127,2,5,5,5,2,2,2,2,2,4,3,4,3,2,7,1.0,neutral or dissatisfied +96798,106443,Female,Loyal Customer,10,Business travel,Business,3436,2,2,2,2,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +96799,51892,Female,Loyal Customer,47,Business travel,Business,1885,4,4,4,4,2,3,5,5,5,4,5,2,5,1,0,0.0,satisfied +96800,125257,Female,disloyal Customer,34,Business travel,Eco Plus,427,2,3,3,3,3,3,3,3,3,2,4,1,3,3,0,0.0,neutral or dissatisfied +96801,35037,Male,Loyal Customer,52,Business travel,Business,1872,1,1,1,1,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +96802,13129,Male,Loyal Customer,16,Business travel,Business,3216,4,2,2,2,4,4,4,4,4,4,4,2,3,4,0,3.0,neutral or dissatisfied +96803,30910,Male,Loyal Customer,39,Business travel,Business,896,4,4,4,4,3,4,1,5,5,5,5,3,5,4,50,47.0,satisfied +96804,97310,Female,Loyal Customer,27,Business travel,Business,3975,2,2,2,2,4,4,4,4,5,5,5,3,5,4,7,1.0,satisfied +96805,96031,Male,Loyal Customer,46,Business travel,Business,1235,3,4,4,4,3,3,3,3,3,3,3,1,3,4,2,0.0,neutral or dissatisfied +96806,8945,Female,Loyal Customer,55,Business travel,Business,1867,3,3,3,3,2,4,4,4,4,4,4,2,4,5,0,0.0,satisfied +96807,110209,Female,disloyal Customer,38,Business travel,Business,1310,5,5,5,1,4,5,4,4,5,3,5,4,4,4,4,0.0,satisfied +96808,76189,Female,Loyal Customer,35,Business travel,Business,2422,3,4,2,4,5,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +96809,26296,Male,Loyal Customer,36,Business travel,Business,1934,2,2,2,2,1,4,1,5,5,5,5,3,5,2,11,9.0,satisfied +96810,1319,Male,Loyal Customer,53,Business travel,Business,2999,4,4,4,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +96811,51251,Male,Loyal Customer,31,Business travel,Eco Plus,86,4,1,1,1,4,4,4,4,5,3,1,3,1,4,0,0.0,satisfied +96812,80817,Male,Loyal Customer,53,Business travel,Business,484,5,5,5,5,3,4,5,5,5,5,5,3,5,3,14,8.0,satisfied +96813,93774,Female,Loyal Customer,59,Business travel,Business,1865,4,4,4,4,2,3,4,4,4,4,4,5,4,4,0,2.0,satisfied +96814,91340,Female,Loyal Customer,20,Personal Travel,Eco Plus,270,2,5,2,2,4,2,1,4,5,5,5,4,4,4,4,20.0,neutral or dissatisfied +96815,51040,Female,Loyal Customer,18,Personal Travel,Eco,266,2,3,2,4,2,2,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +96816,76264,Male,Loyal Customer,29,Business travel,Business,1927,5,5,5,5,4,4,4,4,5,5,5,5,5,4,2,0.0,satisfied +96817,57592,Male,Loyal Customer,32,Personal Travel,Eco,1597,4,4,4,1,5,4,5,5,3,4,5,4,5,5,0,1.0,neutral or dissatisfied +96818,95183,Male,Loyal Customer,61,Personal Travel,Eco,496,2,3,2,1,3,2,3,3,5,2,2,4,2,3,0,0.0,neutral or dissatisfied +96819,87670,Female,Loyal Customer,38,Business travel,Business,3445,2,1,1,1,1,2,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +96820,96148,Female,Loyal Customer,44,Business travel,Business,546,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +96821,89323,Female,Loyal Customer,44,Business travel,Business,1587,3,3,3,3,3,5,5,4,4,4,4,5,4,5,0,7.0,satisfied +96822,78844,Male,disloyal Customer,27,Business travel,Business,554,3,3,3,4,2,3,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +96823,84012,Female,Loyal Customer,29,Personal Travel,Eco,373,3,0,3,5,1,3,1,1,4,2,4,5,1,1,0,2.0,neutral or dissatisfied +96824,11336,Female,Loyal Customer,27,Personal Travel,Eco,517,3,5,3,3,2,3,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +96825,15188,Female,Loyal Customer,43,Business travel,Eco,544,5,2,2,2,2,5,5,5,5,5,5,3,5,1,0,0.0,satisfied +96826,74194,Female,Loyal Customer,14,Personal Travel,Eco,592,2,4,2,4,2,2,2,2,5,3,4,1,1,2,0,0.0,neutral or dissatisfied +96827,41323,Female,Loyal Customer,46,Personal Travel,Eco,1041,1,5,1,3,4,4,4,5,5,1,5,5,5,4,0,20.0,neutral or dissatisfied +96828,111537,Female,Loyal Customer,56,Business travel,Business,3698,2,2,2,2,3,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +96829,12388,Female,Loyal Customer,38,Business travel,Business,2374,2,2,2,2,5,4,3,3,3,3,2,3,3,1,23,25.0,neutral or dissatisfied +96830,28500,Female,Loyal Customer,26,Business travel,Business,2677,3,3,3,3,4,5,4,4,5,5,5,3,5,4,20,0.0,satisfied +96831,87015,Male,disloyal Customer,24,Business travel,Eco Plus,907,1,2,1,4,2,1,2,2,2,5,4,2,3,2,0,17.0,neutral or dissatisfied +96832,5582,Female,Loyal Customer,51,Business travel,Eco Plus,501,3,1,5,5,3,4,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +96833,46332,Female,Loyal Customer,31,Business travel,Business,589,3,3,5,3,4,4,4,4,2,2,3,1,1,4,17,9.0,satisfied +96834,80329,Female,Loyal Customer,34,Personal Travel,Eco,746,4,5,4,3,5,4,5,5,5,2,1,2,2,5,46,76.0,neutral or dissatisfied +96835,112026,Male,disloyal Customer,39,Business travel,Business,280,5,5,5,2,5,5,5,5,4,5,3,4,1,5,10,15.0,satisfied +96836,88569,Female,Loyal Customer,7,Personal Travel,Eco,646,5,2,5,4,2,5,2,2,4,3,4,2,4,2,0,0.0,satisfied +96837,33120,Female,Loyal Customer,59,Personal Travel,Eco,216,1,4,1,4,3,3,4,4,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +96838,31561,Female,disloyal Customer,40,Business travel,Business,853,2,2,2,2,3,2,3,3,5,5,3,5,5,3,0,0.0,neutral or dissatisfied +96839,113084,Male,Loyal Customer,27,Business travel,Eco,543,4,4,4,4,4,4,4,4,2,5,4,1,4,4,15,5.0,neutral or dissatisfied +96840,5403,Female,Loyal Customer,64,Personal Travel,Eco,733,1,5,1,4,2,4,2,3,3,1,1,3,3,5,0,0.0,neutral or dissatisfied +96841,33534,Female,Loyal Customer,38,Business travel,Business,413,4,4,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +96842,1811,Male,Loyal Customer,21,Business travel,Business,3784,2,4,4,4,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +96843,96333,Female,Loyal Customer,16,Personal Travel,Eco,359,3,1,3,3,2,3,2,2,1,1,3,3,4,2,103,95.0,neutral or dissatisfied +96844,36507,Male,Loyal Customer,44,Business travel,Business,2619,2,2,2,2,2,2,1,5,5,5,5,5,5,4,0,0.0,satisfied +96845,53319,Male,Loyal Customer,61,Personal Travel,Eco,758,2,4,3,4,3,3,2,3,2,4,3,2,3,3,0,0.0,neutral or dissatisfied +96846,72799,Female,Loyal Customer,65,Personal Travel,Eco,1045,3,4,3,4,4,3,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +96847,55065,Male,Loyal Customer,23,Business travel,Business,1504,2,4,4,4,2,2,2,2,4,5,4,3,4,2,52,29.0,neutral or dissatisfied +96848,12021,Male,Loyal Customer,37,Business travel,Eco,376,5,4,2,4,5,5,5,5,3,1,4,5,1,5,0,0.0,satisfied +96849,54722,Female,Loyal Customer,28,Personal Travel,Eco,787,0,4,1,4,3,1,3,3,3,3,5,5,4,3,0,0.0,satisfied +96850,63711,Female,disloyal Customer,42,Business travel,Eco,1660,3,3,3,3,5,3,5,5,3,4,4,1,4,5,13,0.0,neutral or dissatisfied +96851,62876,Male,Loyal Customer,66,Personal Travel,Eco,2446,1,5,0,4,2,0,2,2,1,1,5,4,3,2,6,0.0,neutral or dissatisfied +96852,23022,Male,disloyal Customer,23,Business travel,Eco,927,3,3,3,1,5,3,3,5,3,1,1,2,5,5,0,0.0,neutral or dissatisfied +96853,566,Female,Loyal Customer,52,Business travel,Business,2145,0,4,0,5,2,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +96854,100056,Male,Loyal Customer,64,Personal Travel,Eco,289,1,5,1,3,5,1,5,5,3,4,5,3,4,5,0,1.0,neutral or dissatisfied +96855,104638,Female,Loyal Customer,53,Personal Travel,Eco Plus,861,1,5,2,3,2,1,1,4,3,4,4,1,5,1,137,160.0,neutral or dissatisfied +96856,49936,Female,disloyal Customer,27,Business travel,Eco,134,2,2,2,4,3,2,3,3,3,3,4,3,4,3,23,25.0,neutral or dissatisfied +96857,118932,Male,disloyal Customer,24,Business travel,Eco,791,2,2,2,4,4,2,4,4,4,2,4,3,4,4,13,8.0,neutral or dissatisfied +96858,112445,Female,Loyal Customer,66,Business travel,Business,862,3,3,3,3,5,3,4,3,3,3,3,4,3,4,40,35.0,neutral or dissatisfied +96859,124904,Female,Loyal Customer,48,Business travel,Business,728,1,1,2,1,4,4,5,3,3,3,3,3,3,4,2,14.0,satisfied +96860,110093,Male,Loyal Customer,41,Business travel,Business,3836,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +96861,80722,Male,Loyal Customer,33,Business travel,Business,3296,4,4,4,4,3,3,3,3,3,2,4,5,5,3,0,5.0,satisfied +96862,26758,Male,Loyal Customer,39,Business travel,Business,1725,3,4,4,4,5,4,3,3,3,3,3,1,3,1,6,4.0,neutral or dissatisfied +96863,92574,Male,Loyal Customer,35,Business travel,Eco Plus,1947,3,4,4,4,3,3,3,3,3,1,2,2,3,3,1,0.0,neutral or dissatisfied +96864,124758,Male,Loyal Customer,54,Business travel,Business,280,1,1,1,1,4,4,4,4,4,4,4,5,4,3,0,5.0,satisfied +96865,115574,Female,Loyal Customer,49,Business travel,Business,2576,1,1,1,1,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +96866,128772,Male,Loyal Customer,42,Personal Travel,Eco,550,2,0,3,3,2,3,2,2,4,2,5,3,4,2,2,0.0,neutral or dissatisfied +96867,21870,Female,disloyal Customer,24,Business travel,Eco,500,1,0,1,4,3,1,3,3,3,4,5,5,5,3,67,65.0,neutral or dissatisfied +96868,11618,Female,Loyal Customer,35,Personal Travel,Eco,657,4,5,4,3,5,4,5,5,5,1,4,4,4,5,0,0.0,neutral or dissatisfied +96869,49512,Male,Loyal Customer,60,Business travel,Eco,373,5,2,3,2,5,5,5,5,5,3,1,1,2,5,0,0.0,satisfied +96870,5327,Female,Loyal Customer,47,Business travel,Business,1671,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +96871,108563,Female,Loyal Customer,36,Business travel,Eco Plus,735,3,2,2,2,3,2,3,3,4,5,3,1,4,3,12,9.0,neutral or dissatisfied +96872,22261,Male,disloyal Customer,38,Business travel,Eco,143,1,3,1,1,2,1,2,2,2,2,1,1,5,2,0,0.0,neutral or dissatisfied +96873,102567,Male,Loyal Customer,47,Business travel,Business,2808,4,4,4,4,3,4,5,3,3,3,3,3,3,3,1,0.0,satisfied +96874,93871,Female,disloyal Customer,26,Business travel,Business,590,5,5,5,1,2,5,2,2,5,3,4,5,5,2,0,10.0,satisfied +96875,129012,Male,disloyal Customer,15,Business travel,Business,1363,5,0,5,3,5,5,5,5,4,3,4,3,5,5,6,0.0,satisfied +96876,90046,Male,Loyal Customer,42,Business travel,Business,957,3,3,3,3,3,4,4,4,4,4,4,5,4,4,92,88.0,satisfied +96877,834,Female,disloyal Customer,20,Business travel,Business,134,2,4,2,3,5,2,5,5,2,1,4,3,3,5,0,0.0,neutral or dissatisfied +96878,26192,Female,Loyal Customer,69,Business travel,Eco,545,1,5,5,5,4,2,2,1,1,1,1,3,1,4,11,1.0,neutral or dissatisfied +96879,51352,Female,disloyal Customer,38,Business travel,Eco Plus,308,2,2,2,3,4,2,4,4,3,2,4,1,4,4,22,17.0,neutral or dissatisfied +96880,62698,Female,Loyal Customer,23,Business travel,Business,2338,4,4,4,4,4,4,4,4,5,5,5,3,5,4,18,1.0,satisfied +96881,57458,Female,Loyal Customer,27,Business travel,Eco,334,1,3,3,3,1,1,1,1,4,3,4,3,4,1,0,16.0,neutral or dissatisfied +96882,19722,Male,Loyal Customer,52,Personal Travel,Eco,409,2,4,2,1,5,2,5,5,4,5,5,5,4,5,65,64.0,neutral or dissatisfied +96883,75840,Male,disloyal Customer,60,Business travel,Business,1440,2,2,2,1,2,2,2,2,5,5,5,4,4,2,4,0.0,neutral or dissatisfied +96884,42757,Female,Loyal Customer,43,Business travel,Business,493,3,3,3,3,5,4,4,4,4,4,4,4,4,1,0,0.0,satisfied +96885,53588,Male,Loyal Customer,56,Personal Travel,Eco,391,1,3,1,2,3,1,3,3,1,1,3,5,5,3,4,0.0,neutral or dissatisfied +96886,120337,Female,Loyal Customer,56,Personal Travel,Eco Plus,268,2,3,2,4,1,2,1,2,2,2,2,5,2,1,0,0.0,neutral or dissatisfied +96887,24444,Female,disloyal Customer,24,Business travel,Business,481,5,0,5,5,3,5,3,3,4,4,5,3,5,3,0,0.0,satisfied +96888,70119,Male,Loyal Customer,36,Business travel,Business,550,3,1,3,1,4,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +96889,87628,Female,Loyal Customer,21,Business travel,Business,591,1,1,1,1,3,4,3,3,4,3,4,4,4,3,0,0.0,satisfied +96890,88047,Female,Loyal Customer,37,Business travel,Business,3541,5,5,5,5,3,5,5,5,5,5,5,4,5,3,55,41.0,satisfied +96891,17646,Male,Loyal Customer,26,Business travel,Business,1752,1,1,1,1,5,5,5,5,2,5,5,1,5,5,0,0.0,satisfied +96892,44282,Male,Loyal Customer,30,Personal Travel,Eco Plus,222,4,0,4,1,2,4,2,2,4,3,4,3,4,2,0,0.0,satisfied +96893,27256,Male,disloyal Customer,35,Business travel,Business,978,2,3,3,2,5,3,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +96894,15368,Female,Loyal Customer,52,Business travel,Business,399,1,1,5,1,3,1,2,2,2,2,2,2,2,2,0,0.0,satisfied +96895,56959,Female,Loyal Customer,35,Business travel,Business,2454,2,2,2,2,4,4,4,4,2,5,2,4,1,4,3,15.0,satisfied +96896,123293,Male,disloyal Customer,38,Business travel,Business,631,2,2,2,1,5,2,5,5,3,4,4,5,5,5,7,8.0,neutral or dissatisfied +96897,121956,Female,Loyal Customer,67,Business travel,Business,1918,2,1,1,1,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +96898,97636,Female,Loyal Customer,55,Personal Travel,Eco,748,5,4,5,2,4,4,4,2,2,5,2,3,2,4,1,0.0,satisfied +96899,116249,Female,Loyal Customer,20,Personal Travel,Eco,480,1,4,1,3,3,1,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +96900,20844,Male,Loyal Customer,53,Personal Travel,Eco,515,2,4,2,4,3,2,3,3,3,4,5,5,3,3,7,0.0,neutral or dissatisfied +96901,34706,Male,disloyal Customer,55,Business travel,Eco,209,3,0,3,4,5,3,5,5,2,1,4,3,1,5,0,0.0,neutral or dissatisfied +96902,15419,Male,Loyal Customer,36,Business travel,Eco,433,1,4,4,4,1,1,1,1,4,2,4,1,4,1,88,92.0,neutral or dissatisfied +96903,85195,Male,Loyal Customer,49,Business travel,Eco,689,2,2,2,2,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +96904,58488,Male,Loyal Customer,27,Business travel,Business,719,1,4,4,4,1,1,1,1,4,5,3,3,3,1,32,7.0,neutral or dissatisfied +96905,67520,Male,Loyal Customer,44,Business travel,Business,1438,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,9.0,satisfied +96906,26947,Male,Loyal Customer,58,Personal Travel,Eco,2402,2,4,2,5,2,2,2,2,3,3,4,4,5,2,42,62.0,neutral or dissatisfied +96907,34078,Male,Loyal Customer,48,Business travel,Eco Plus,1674,2,5,5,5,2,2,2,2,3,4,1,2,2,2,76,66.0,neutral or dissatisfied +96908,79920,Male,Loyal Customer,48,Business travel,Business,3360,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +96909,85912,Female,Loyal Customer,36,Business travel,Business,2863,4,3,3,3,1,3,3,4,4,3,4,4,4,3,129,124.0,neutral or dissatisfied +96910,66649,Male,Loyal Customer,41,Business travel,Business,802,3,3,3,3,3,5,4,4,4,4,4,5,4,5,83,92.0,satisfied +96911,104173,Male,disloyal Customer,26,Business travel,Business,349,3,3,3,2,5,3,5,5,1,1,3,2,2,5,33,32.0,neutral or dissatisfied +96912,100732,Female,Loyal Customer,20,Business travel,Business,2191,1,5,5,5,1,1,1,1,4,5,3,2,4,1,102,92.0,neutral or dissatisfied +96913,7612,Female,Loyal Customer,32,Personal Travel,Eco,825,4,5,4,4,4,4,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +96914,121950,Male,Loyal Customer,43,Business travel,Business,2900,0,0,0,1,3,5,4,2,2,2,2,3,2,3,8,0.0,satisfied +96915,40167,Male,disloyal Customer,37,Business travel,Business,347,2,2,2,3,5,2,5,5,4,2,4,2,5,5,0,0.0,neutral or dissatisfied +96916,67945,Female,Loyal Customer,42,Personal Travel,Eco,1205,3,4,3,4,5,4,4,5,5,3,5,2,5,3,106,89.0,neutral or dissatisfied +96917,16816,Male,Loyal Customer,26,Business travel,Eco,645,5,3,3,3,5,5,4,5,2,5,3,2,3,5,101,98.0,satisfied +96918,11699,Male,Loyal Customer,46,Business travel,Business,3933,4,4,4,4,5,4,4,4,4,4,4,3,4,3,4,24.0,satisfied +96919,28825,Female,Loyal Customer,33,Business travel,Business,937,1,1,4,1,5,2,3,3,3,3,3,3,3,2,0,0.0,satisfied +96920,99688,Female,Loyal Customer,76,Business travel,Business,3758,1,2,2,2,2,4,4,1,1,1,1,3,1,1,10,17.0,neutral or dissatisfied +96921,56056,Female,Loyal Customer,52,Personal Travel,Eco,2475,5,0,5,2,5,3,3,3,2,4,4,3,4,3,0,0.0,satisfied +96922,121643,Female,Loyal Customer,25,Personal Travel,Eco Plus,936,1,1,1,3,3,1,3,3,4,5,2,4,3,3,90,76.0,neutral or dissatisfied +96923,89296,Female,Loyal Customer,67,Business travel,Business,2311,1,1,1,1,2,2,5,5,5,5,5,1,5,2,14,16.0,satisfied +96924,106071,Female,Loyal Customer,23,Personal Travel,Business,436,2,4,2,2,4,2,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +96925,54004,Male,Loyal Customer,40,Business travel,Business,395,4,4,4,4,4,5,4,5,5,5,5,1,5,4,53,55.0,satisfied +96926,20596,Female,disloyal Customer,7,Business travel,Eco Plus,606,4,0,4,4,1,4,1,1,1,2,3,3,4,1,22,24.0,neutral or dissatisfied +96927,22653,Female,Loyal Customer,44,Business travel,Eco Plus,250,3,4,3,4,3,1,2,3,3,3,3,3,3,4,16,4.0,satisfied +96928,6290,Male,Loyal Customer,17,Personal Travel,Eco,585,3,5,3,3,2,3,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +96929,105895,Male,Loyal Customer,45,Business travel,Business,283,5,5,5,5,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +96930,126688,Female,disloyal Customer,38,Business travel,Business,1422,4,4,4,1,5,4,5,5,4,5,4,3,4,5,0,0.0,satisfied +96931,108547,Female,Loyal Customer,10,Personal Travel,Eco,512,1,1,1,3,4,1,5,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +96932,77622,Female,disloyal Customer,24,Business travel,Business,731,5,0,5,4,1,5,1,1,4,3,4,3,4,1,14,3.0,satisfied +96933,99835,Male,Loyal Customer,22,Business travel,Business,2274,3,3,4,4,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +96934,52047,Male,Loyal Customer,36,Business travel,Business,2159,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +96935,97906,Female,Loyal Customer,59,Business travel,Business,3025,3,2,2,2,3,4,4,3,3,3,3,4,3,1,2,10.0,neutral or dissatisfied +96936,56579,Female,Loyal Customer,60,Business travel,Business,1068,3,3,2,3,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +96937,73185,Male,Loyal Customer,53,Business travel,Business,2194,5,5,5,5,5,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +96938,4803,Female,Loyal Customer,48,Personal Travel,Eco,403,2,4,5,3,4,4,4,4,4,5,4,4,4,5,32,27.0,neutral or dissatisfied +96939,105849,Female,Loyal Customer,58,Business travel,Business,2931,2,2,3,2,4,5,4,5,5,5,5,5,5,5,31,27.0,satisfied +96940,84409,Female,Loyal Customer,20,Personal Travel,Eco,591,2,4,2,1,4,2,4,4,3,3,5,5,4,4,11,7.0,neutral or dissatisfied +96941,102808,Female,Loyal Customer,50,Business travel,Eco,342,1,3,3,3,1,3,4,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +96942,95661,Female,Loyal Customer,56,Personal Travel,Eco,928,3,4,3,2,5,5,5,5,5,3,5,3,5,3,9,4.0,neutral or dissatisfied +96943,129274,Male,Loyal Customer,43,Personal Travel,Eco,2402,2,4,2,3,2,2,2,2,3,5,3,4,4,2,83,68.0,neutral or dissatisfied +96944,20137,Female,disloyal Customer,26,Business travel,Eco Plus,416,1,0,1,2,2,1,4,2,2,3,2,4,4,2,97,102.0,neutral or dissatisfied +96945,126390,Female,Loyal Customer,30,Personal Travel,Eco,507,3,5,3,1,4,3,2,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +96946,121028,Male,Loyal Customer,35,Personal Travel,Eco,992,3,4,2,3,3,2,3,3,4,4,5,3,5,3,2,,neutral or dissatisfied +96947,87351,Male,Loyal Customer,39,Business travel,Business,425,4,4,3,4,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +96948,104282,Male,Loyal Customer,49,Personal Travel,Business,440,1,5,1,3,2,5,1,1,1,1,1,4,1,1,7,2.0,neutral or dissatisfied +96949,88236,Male,Loyal Customer,46,Business travel,Business,3714,5,5,5,5,3,4,5,4,4,4,4,3,4,5,0,1.0,satisfied +96950,74413,Male,Loyal Customer,35,Business travel,Business,1438,5,5,5,5,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +96951,93497,Female,disloyal Customer,29,Business travel,Eco,1107,1,0,0,2,5,0,5,5,3,5,2,1,2,5,27,10.0,neutral or dissatisfied +96952,59523,Female,Loyal Customer,46,Business travel,Business,1516,1,4,1,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +96953,93402,Male,Loyal Customer,31,Business travel,Business,3151,3,3,3,3,3,3,3,3,2,2,3,2,3,3,47,35.0,neutral or dissatisfied +96954,61643,Female,Loyal Customer,40,Business travel,Business,1379,3,1,1,1,3,2,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +96955,67137,Male,disloyal Customer,11,Business travel,Business,985,5,0,5,1,5,0,5,5,3,4,5,3,4,5,18,4.0,satisfied +96956,96564,Male,Loyal Customer,55,Business travel,Business,2651,0,0,0,1,5,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +96957,129127,Male,Loyal Customer,49,Business travel,Business,2953,4,4,4,4,5,4,4,2,2,2,2,4,2,4,1,12.0,satisfied +96958,54782,Male,Loyal Customer,19,Business travel,Eco Plus,787,5,2,2,2,5,5,4,5,2,2,1,5,4,5,2,0.0,satisfied +96959,71112,Male,Loyal Customer,48,Business travel,Business,2072,2,2,2,2,5,3,4,4,4,4,4,4,4,4,4,0.0,satisfied +96960,116645,Female,Loyal Customer,37,Business travel,Business,3777,4,4,4,4,3,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +96961,53843,Female,Loyal Customer,57,Business travel,Business,1792,1,1,1,1,3,4,2,5,5,5,3,4,5,2,0,0.0,satisfied +96962,73425,Female,Loyal Customer,63,Personal Travel,Eco,1197,2,5,2,3,2,2,2,4,5,4,4,2,4,2,198,188.0,neutral or dissatisfied +96963,108433,Male,Loyal Customer,39,Business travel,Business,1440,3,3,3,3,3,4,5,3,3,3,3,3,3,4,3,7.0,satisfied +96964,59709,Female,Loyal Customer,55,Business travel,Business,2551,2,2,2,2,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +96965,124277,Female,Loyal Customer,44,Business travel,Business,2152,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +96966,106451,Female,disloyal Customer,31,Business travel,Business,1670,2,2,2,3,2,2,2,2,3,3,3,4,4,2,3,21.0,neutral or dissatisfied +96967,82856,Male,Loyal Customer,39,Business travel,Business,2714,4,4,4,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +96968,98248,Female,disloyal Customer,22,Business travel,Eco,1200,3,3,3,1,3,3,3,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +96969,74754,Female,Loyal Customer,26,Personal Travel,Eco,1464,1,5,2,4,4,2,4,4,4,2,4,3,4,4,14,57.0,neutral or dissatisfied +96970,32660,Female,Loyal Customer,61,Business travel,Business,2193,3,2,2,2,3,2,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +96971,116829,Male,Loyal Customer,58,Business travel,Business,1566,2,3,3,3,2,2,1,2,2,2,2,1,2,1,14,21.0,neutral or dissatisfied +96972,21977,Female,Loyal Customer,40,Personal Travel,Eco,551,4,2,4,3,5,4,4,5,1,5,4,3,3,5,0,9.0,satisfied +96973,86659,Female,Loyal Customer,14,Personal Travel,Eco,746,4,5,4,3,2,4,2,2,3,2,5,3,5,2,2,0.0,satisfied +96974,38669,Female,Loyal Customer,9,Personal Travel,Eco,2588,1,5,1,3,3,1,3,3,4,2,4,5,5,3,5,0.0,neutral or dissatisfied +96975,97756,Male,Loyal Customer,64,Personal Travel,Eco,587,5,4,5,2,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +96976,2473,Male,Loyal Customer,28,Personal Travel,Eco,773,4,4,4,5,5,4,5,5,2,1,4,4,5,5,0,0.0,neutral or dissatisfied +96977,89404,Female,disloyal Customer,17,Business travel,Eco,134,3,2,3,3,5,3,5,5,3,3,2,1,2,5,0,0.0,neutral or dissatisfied +96978,49786,Male,disloyal Customer,21,Business travel,Eco,250,2,4,2,4,3,2,3,3,2,1,2,4,1,3,0,15.0,neutral or dissatisfied +96979,112847,Male,Loyal Customer,48,Business travel,Business,3286,3,3,3,3,5,5,5,5,5,5,5,5,5,4,31,26.0,satisfied +96980,106672,Male,Loyal Customer,51,Business travel,Business,2704,1,1,1,1,5,4,5,5,5,5,5,5,5,4,94,85.0,satisfied +96981,48515,Female,Loyal Customer,45,Business travel,Eco,846,3,1,1,1,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +96982,101494,Female,Loyal Customer,62,Business travel,Business,345,0,0,0,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +96983,30949,Male,Loyal Customer,23,Business travel,Eco,1024,4,2,2,2,4,4,3,4,2,3,3,3,3,4,4,7.0,neutral or dissatisfied +96984,111164,Female,Loyal Customer,44,Business travel,Business,2858,1,1,1,1,2,5,4,2,2,2,2,3,2,5,2,0.0,satisfied +96985,117193,Female,Loyal Customer,44,Personal Travel,Eco,651,3,1,3,3,2,4,3,4,4,3,4,1,4,2,0,2.0,neutral or dissatisfied +96986,105000,Female,Loyal Customer,48,Business travel,Business,3075,0,0,0,1,4,4,5,5,5,5,5,4,5,4,57,60.0,satisfied +96987,76072,Female,Loyal Customer,28,Business travel,Business,3044,4,4,5,4,3,3,3,3,4,4,4,4,4,3,6,0.0,satisfied +96988,38661,Female,Loyal Customer,54,Business travel,Business,1204,1,1,1,1,2,1,5,5,5,5,5,2,5,3,0,0.0,satisfied +96989,112970,Female,Loyal Customer,43,Business travel,Business,1390,1,1,1,1,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +96990,95503,Female,disloyal Customer,20,Business travel,Eco,562,4,2,3,4,4,3,4,4,3,1,3,1,3,4,0,2.0,neutral or dissatisfied +96991,112419,Male,Loyal Customer,32,Business travel,Business,3157,4,4,4,4,4,4,4,4,5,2,4,4,5,4,0,0.0,satisfied +96992,78489,Male,Loyal Customer,59,Business travel,Business,666,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +96993,17213,Female,Loyal Customer,27,Business travel,Eco,1107,2,4,4,4,2,2,2,2,4,4,3,3,4,2,0,0.0,neutral or dissatisfied +96994,24132,Female,Loyal Customer,26,Personal Travel,Eco,584,3,2,2,3,4,2,4,4,1,2,2,3,3,4,0,0.0,neutral or dissatisfied +96995,57672,Female,Loyal Customer,51,Personal Travel,Eco Plus,200,4,3,4,3,4,4,3,2,2,4,2,1,2,1,36,48.0,neutral or dissatisfied +96996,2129,Female,Loyal Customer,78,Business travel,Business,3235,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +96997,22611,Male,Loyal Customer,52,Business travel,Business,223,3,3,3,3,5,1,5,3,3,4,3,5,3,3,77,83.0,satisfied +96998,116695,Female,disloyal Customer,34,Business travel,Business,373,2,2,2,3,5,2,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +96999,77426,Male,Loyal Customer,56,Personal Travel,Eco,599,2,2,2,4,1,2,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +97000,36982,Female,Loyal Customer,35,Business travel,Business,805,2,3,3,3,3,2,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +97001,112926,Female,Loyal Customer,56,Personal Travel,Eco,715,3,4,3,1,2,3,1,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +97002,46369,Male,Loyal Customer,41,Business travel,Business,2533,1,1,1,1,4,4,4,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +97003,21285,Female,Loyal Customer,46,Business travel,Business,1786,3,3,3,3,1,4,4,5,5,5,5,5,5,2,0,0.0,satisfied +97004,93848,Male,Loyal Customer,69,Personal Travel,Eco,391,3,4,3,1,3,3,3,3,5,2,4,3,4,3,6,3.0,neutral or dissatisfied +97005,116114,Female,Loyal Customer,46,Personal Travel,Eco,308,1,4,1,3,5,4,3,1,1,1,2,4,1,4,9,10.0,neutral or dissatisfied +97006,39016,Male,Loyal Customer,57,Business travel,Eco,313,3,5,5,5,4,3,4,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +97007,9033,Male,Loyal Customer,50,Business travel,Business,160,2,2,2,2,2,5,5,5,5,5,5,4,5,4,65,67.0,satisfied +97008,35332,Female,disloyal Customer,54,Business travel,Eco,944,3,3,3,4,3,3,5,3,1,1,4,1,3,3,5,8.0,neutral or dissatisfied +97009,14090,Female,disloyal Customer,20,Business travel,Eco,201,0,5,0,4,3,0,3,3,2,1,3,4,2,3,0,0.0,satisfied +97010,49111,Male,Loyal Customer,50,Business travel,Business,109,1,1,1,1,4,3,1,4,4,4,5,3,4,4,0,4.0,satisfied +97011,63495,Male,Loyal Customer,48,Business travel,Business,2018,4,4,4,4,5,3,4,4,4,4,4,3,4,4,27,0.0,satisfied +97012,57413,Male,Loyal Customer,56,Business travel,Business,3759,5,5,5,5,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +97013,25089,Female,Loyal Customer,48,Business travel,Eco,149,4,2,2,2,4,2,3,4,4,4,4,3,4,1,0,4.0,satisfied +97014,35960,Female,Loyal Customer,45,Business travel,Eco,231,2,1,3,1,5,5,1,3,3,2,3,5,3,5,0,0.0,satisfied +97015,61546,Male,Loyal Customer,55,Business travel,Business,2288,4,4,4,4,5,3,4,5,5,5,5,4,5,3,9,0.0,satisfied +97016,48883,Female,Loyal Customer,48,Business travel,Eco,109,5,4,4,4,5,3,1,5,5,5,5,5,5,3,0,0.0,satisfied +97017,42400,Female,Loyal Customer,46,Business travel,Eco Plus,329,3,3,3,3,3,3,3,2,2,3,3,3,4,3,293,282.0,neutral or dissatisfied +97018,23541,Male,Loyal Customer,45,Personal Travel,Eco,472,3,1,3,2,2,3,4,2,4,3,2,3,1,2,14,11.0,neutral or dissatisfied +97019,418,Female,Loyal Customer,48,Business travel,Business,270,5,5,5,5,4,5,5,5,5,5,5,5,5,4,0,5.0,satisfied +97020,99914,Female,Loyal Customer,45,Personal Travel,Eco,1428,3,4,3,4,3,2,2,5,5,4,4,2,5,2,193,184.0,neutral or dissatisfied +97021,114163,Female,Loyal Customer,47,Business travel,Business,862,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +97022,129627,Female,disloyal Customer,50,Business travel,Business,447,4,4,4,1,4,1,1,3,2,5,5,1,5,1,279,293.0,satisfied +97023,6064,Male,Loyal Customer,45,Personal Travel,Eco,672,1,5,1,4,3,1,3,3,5,5,4,5,5,3,2,23.0,neutral or dissatisfied +97024,111056,Male,Loyal Customer,26,Personal Travel,Eco,319,0,2,0,3,3,0,3,3,3,4,3,2,4,3,0,0.0,satisfied +97025,124080,Male,Loyal Customer,54,Business travel,Eco Plus,80,3,5,5,5,3,3,3,3,2,5,4,3,4,3,0,11.0,neutral or dissatisfied +97026,9403,Female,disloyal Customer,43,Business travel,Business,182,1,1,1,4,4,1,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +97027,10990,Male,Loyal Customer,45,Business travel,Eco,163,1,5,5,5,1,1,1,1,2,4,4,1,3,1,24,19.0,neutral or dissatisfied +97028,116583,Female,Loyal Customer,39,Business travel,Business,1960,2,2,5,2,5,5,4,5,5,5,5,5,5,3,43,30.0,satisfied +97029,87188,Female,Loyal Customer,47,Business travel,Business,3282,1,1,1,1,2,4,5,5,5,5,5,3,5,4,12,2.0,satisfied +97030,47984,Female,Loyal Customer,57,Personal Travel,Eco,412,2,4,2,4,3,5,4,2,2,2,2,5,2,3,7,6.0,neutral or dissatisfied +97031,47257,Male,Loyal Customer,70,Business travel,Business,599,2,5,5,5,4,3,2,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +97032,22946,Male,Loyal Customer,56,Business travel,Eco,528,5,3,3,3,5,5,5,5,2,5,5,4,4,5,0,0.0,satisfied +97033,71310,Male,Loyal Customer,53,Business travel,Business,1514,1,1,1,1,4,4,5,4,4,4,4,3,4,4,17,38.0,satisfied +97034,91341,Female,Loyal Customer,41,Personal Travel,Eco Plus,545,5,3,5,2,4,3,2,1,1,5,1,1,1,3,0,1.0,satisfied +97035,29487,Male,Loyal Customer,28,Business travel,Business,3410,1,2,2,2,1,1,1,1,4,2,3,1,3,1,0,3.0,neutral or dissatisfied +97036,79162,Male,Loyal Customer,38,Business travel,Eco Plus,739,5,3,3,3,5,5,5,5,3,5,5,1,3,5,13,0.0,satisfied +97037,113432,Female,Loyal Customer,46,Business travel,Business,2381,1,1,5,1,3,5,4,4,4,4,4,4,4,3,51,95.0,satisfied +97038,54322,Female,Loyal Customer,31,Business travel,Business,1597,2,4,1,4,2,2,2,4,1,2,4,2,3,2,185,160.0,neutral or dissatisfied +97039,122908,Female,disloyal Customer,24,Business travel,Business,650,1,1,1,1,4,1,5,4,1,3,1,1,1,4,6,1.0,neutral or dissatisfied +97040,51342,Male,disloyal Customer,27,Business travel,Eco Plus,109,2,2,2,4,2,2,2,2,2,4,3,5,4,2,0,0.0,neutral or dissatisfied +97041,43105,Male,Loyal Customer,24,Personal Travel,Eco,391,2,5,2,4,4,2,1,4,5,1,4,1,5,4,0,0.0,neutral or dissatisfied +97042,112858,Female,Loyal Customer,40,Business travel,Business,1642,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +97043,125008,Female,Loyal Customer,32,Personal Travel,Eco,184,3,3,3,3,5,3,4,5,3,2,3,2,2,5,5,13.0,neutral or dissatisfied +97044,129381,Female,Loyal Customer,39,Business travel,Eco,954,1,2,2,2,1,1,1,1,4,4,4,1,4,1,3,10.0,neutral or dissatisfied +97045,7268,Male,Loyal Customer,69,Personal Travel,Eco,116,2,1,2,3,2,2,2,2,4,1,2,2,3,2,46,30.0,neutral or dissatisfied +97046,36356,Female,Loyal Customer,54,Business travel,Business,3420,2,2,2,2,2,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +97047,73525,Male,Loyal Customer,44,Business travel,Business,594,4,4,3,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +97048,38548,Female,Loyal Customer,35,Business travel,Business,2586,4,3,4,4,3,4,3,4,4,4,4,3,4,1,0,0.0,satisfied +97049,496,Female,Loyal Customer,34,Business travel,Business,3008,5,5,5,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +97050,79136,Male,Loyal Customer,50,Business travel,Business,1550,1,1,5,1,4,5,4,4,4,4,4,4,4,3,56,78.0,satisfied +97051,126162,Male,Loyal Customer,52,Business travel,Business,2319,3,3,3,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +97052,55704,Female,Loyal Customer,61,Personal Travel,Eco,1025,1,5,1,4,2,5,4,5,5,1,2,5,5,5,0,0.0,neutral or dissatisfied +97053,113214,Male,disloyal Customer,37,Business travel,Business,236,3,3,3,2,5,3,5,5,4,2,2,4,2,5,57,45.0,neutral or dissatisfied +97054,63862,Male,Loyal Customer,26,Business travel,Business,2321,1,1,1,1,4,5,4,4,4,2,4,4,5,4,0,0.0,satisfied +97055,113026,Female,disloyal Customer,27,Business travel,Business,479,3,3,3,2,1,3,1,1,3,2,4,4,4,1,38,34.0,neutral or dissatisfied +97056,1295,Female,Loyal Customer,18,Personal Travel,Eco,134,3,4,3,1,2,3,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +97057,96221,Female,Loyal Customer,54,Business travel,Business,460,3,5,3,3,3,5,4,3,3,3,3,3,3,3,1,0.0,satisfied +97058,58778,Male,disloyal Customer,26,Business travel,Business,1182,1,1,1,3,1,1,1,1,3,2,3,3,3,1,8,30.0,neutral or dissatisfied +97059,78388,Male,Loyal Customer,53,Business travel,Business,580,1,3,3,3,2,3,3,1,1,1,1,2,1,1,24,0.0,neutral or dissatisfied +97060,119263,Male,Loyal Customer,49,Business travel,Business,2762,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +97061,121911,Female,Loyal Customer,58,Personal Travel,Eco,449,2,4,2,2,3,4,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +97062,31713,Male,Loyal Customer,67,Personal Travel,Eco,967,3,5,3,4,3,5,5,3,4,4,5,5,3,5,265,259.0,neutral or dissatisfied +97063,56801,Female,Loyal Customer,48,Business travel,Business,1605,1,1,1,1,3,5,4,4,4,4,4,4,4,4,55,65.0,satisfied +97064,65577,Female,Loyal Customer,17,Business travel,Business,175,4,2,2,2,2,2,4,2,4,2,3,2,3,2,4,1.0,neutral or dissatisfied +97065,38423,Female,Loyal Customer,27,Business travel,Business,2712,3,3,3,3,4,4,4,4,4,2,2,5,5,4,0,0.0,satisfied +97066,95395,Male,Loyal Customer,10,Personal Travel,Eco,562,3,5,3,4,4,3,4,4,5,3,3,5,5,4,0,0.0,neutral or dissatisfied +97067,33174,Female,Loyal Customer,21,Personal Travel,Eco,102,4,3,4,4,1,4,1,1,1,3,5,2,2,1,0,0.0,neutral or dissatisfied +97068,73632,Female,Loyal Customer,44,Business travel,Business,1909,4,4,4,4,2,4,4,5,5,5,4,3,5,5,10,0.0,satisfied +97069,80525,Male,Loyal Customer,23,Personal Travel,Eco Plus,1749,2,3,2,2,3,2,3,3,2,2,2,1,3,3,0,0.0,neutral or dissatisfied +97070,81334,Female,disloyal Customer,20,Business travel,Eco,1299,3,3,3,3,3,4,4,1,4,3,4,4,3,4,151,146.0,neutral or dissatisfied +97071,82641,Male,Loyal Customer,32,Personal Travel,Eco Plus,528,3,5,3,3,3,3,1,3,5,2,5,4,4,3,6,25.0,neutral or dissatisfied +97072,102578,Male,Loyal Customer,40,Business travel,Business,1982,2,2,2,2,3,5,4,4,4,5,5,5,4,5,95,87.0,satisfied +97073,35325,Male,Loyal Customer,55,Business travel,Business,989,2,3,5,5,2,3,3,2,2,2,2,1,2,1,2,31.0,neutral or dissatisfied +97074,67145,Male,Loyal Customer,45,Business travel,Eco,564,2,1,1,1,3,2,3,3,4,5,1,3,3,3,0,0.0,satisfied +97075,47610,Male,Loyal Customer,51,Business travel,Business,1482,4,4,4,4,5,5,2,5,5,5,5,1,5,1,3,19.0,satisfied +97076,79637,Female,Loyal Customer,30,Business travel,Business,762,3,3,3,3,3,3,3,3,1,1,4,1,4,3,0,0.0,neutral or dissatisfied +97077,116405,Female,Loyal Customer,59,Personal Travel,Eco,308,2,4,2,2,5,5,5,1,1,2,1,4,1,3,10,8.0,neutral or dissatisfied +97078,118824,Male,disloyal Customer,37,Business travel,Business,369,2,1,1,2,4,1,4,4,5,5,4,5,5,4,4,5.0,neutral or dissatisfied +97079,16489,Female,Loyal Customer,53,Business travel,Eco,143,2,2,4,4,2,2,2,2,2,2,2,2,2,3,3,0.0,neutral or dissatisfied +97080,95459,Male,Loyal Customer,58,Business travel,Eco Plus,187,2,3,3,3,3,2,3,3,1,1,4,1,3,3,1,2.0,neutral or dissatisfied +97081,128460,Male,Loyal Customer,50,Personal Travel,Eco,621,2,4,2,1,1,2,1,1,1,5,3,5,4,1,0,0.0,neutral or dissatisfied +97082,70575,Male,Loyal Customer,9,Personal Travel,Eco,1258,2,5,2,4,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +97083,84489,Female,Loyal Customer,22,Personal Travel,Eco,2994,4,1,4,2,4,4,4,3,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +97084,105156,Male,Loyal Customer,58,Business travel,Business,2102,4,4,4,4,5,4,1,5,5,5,5,4,5,3,0,0.0,satisfied +97085,27985,Male,Loyal Customer,47,Personal Travel,Eco,2350,4,2,4,4,4,4,4,4,3,5,3,1,3,4,0,13.0,neutral or dissatisfied +97086,63275,Male,Loyal Customer,35,Business travel,Business,2812,2,2,2,2,3,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +97087,64275,Male,Loyal Customer,55,Personal Travel,Business,1158,2,5,2,3,4,4,4,4,4,2,4,3,4,3,0,5.0,neutral or dissatisfied +97088,113166,Male,Loyal Customer,51,Business travel,Eco,628,2,3,3,3,2,2,2,2,1,5,4,4,3,2,10,16.0,neutral or dissatisfied +97089,28422,Female,Loyal Customer,58,Business travel,Business,1399,3,5,2,2,5,3,4,3,3,3,3,2,3,1,9,0.0,neutral or dissatisfied +97090,103504,Female,Loyal Customer,29,Business travel,Business,3612,5,5,5,5,4,4,4,4,5,3,4,5,5,4,2,0.0,satisfied +97091,33344,Male,Loyal Customer,31,Business travel,Business,2399,1,1,1,1,4,4,4,4,5,4,5,4,1,4,0,10.0,satisfied +97092,47613,Female,Loyal Customer,29,Business travel,Business,2759,3,3,3,3,4,5,4,4,3,2,5,1,5,4,15,26.0,satisfied +97093,12991,Male,Loyal Customer,31,Business travel,Eco,438,0,0,0,3,4,0,1,4,4,4,5,3,5,4,0,20.0,satisfied +97094,49211,Male,disloyal Customer,24,Business travel,Eco,250,3,0,3,4,3,3,3,3,2,4,3,2,5,3,0,0.0,neutral or dissatisfied +97095,82873,Male,Loyal Customer,40,Business travel,Eco,645,4,2,2,2,4,4,4,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +97096,19987,Male,Loyal Customer,30,Business travel,Business,3710,1,1,5,1,4,4,4,4,5,2,5,2,2,4,46,44.0,satisfied +97097,20257,Male,Loyal Customer,43,Business travel,Business,1680,2,4,4,4,3,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +97098,118686,Female,disloyal Customer,14,Personal Travel,Eco,325,1,2,1,4,3,1,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +97099,70845,Female,Loyal Customer,49,Business travel,Business,761,2,5,5,5,1,3,3,2,2,2,2,4,2,4,0,9.0,neutral or dissatisfied +97100,62945,Male,Loyal Customer,27,Business travel,Business,862,2,2,3,2,5,5,5,5,5,3,4,3,5,5,0,0.0,satisfied +97101,54147,Male,Loyal Customer,24,Business travel,Business,1504,2,2,2,2,5,5,5,5,4,5,4,1,4,5,40,15.0,satisfied +97102,9046,Female,disloyal Customer,22,Business travel,Eco,173,5,3,5,3,2,5,2,2,5,2,5,4,4,2,24,18.0,satisfied +97103,69021,Female,disloyal Customer,22,Business travel,Eco,1389,2,2,2,2,1,2,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +97104,86991,Female,Loyal Customer,36,Personal Travel,Eco,907,2,5,2,2,1,2,4,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +97105,123474,Female,Loyal Customer,50,Business travel,Business,2296,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +97106,13241,Female,Loyal Customer,38,Business travel,Eco,657,5,5,3,3,5,5,5,5,5,2,1,5,4,5,0,0.0,satisfied +97107,79561,Male,Loyal Customer,47,Business travel,Business,3709,5,5,5,5,2,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +97108,109180,Male,Loyal Customer,40,Business travel,Business,3003,2,2,2,2,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +97109,53154,Female,Loyal Customer,29,Business travel,Business,589,2,2,3,2,4,5,4,4,3,2,4,3,4,4,8,3.0,satisfied +97110,41141,Female,Loyal Customer,11,Personal Travel,Eco,191,1,4,1,5,3,1,1,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +97111,108690,Male,Loyal Customer,54,Business travel,Eco,577,1,5,5,5,1,1,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +97112,116812,Female,disloyal Customer,22,Business travel,Business,651,5,5,5,1,4,5,4,4,4,2,5,5,4,4,0,0.0,satisfied +97113,104058,Female,Loyal Customer,70,Personal Travel,Eco,1262,2,4,2,4,4,4,5,5,5,2,3,3,5,3,52,45.0,neutral or dissatisfied +97114,13424,Female,disloyal Customer,62,Business travel,Eco,409,2,0,2,4,4,2,3,4,4,1,2,3,1,4,0,0.0,neutral or dissatisfied +97115,72973,Female,Loyal Customer,25,Business travel,Eco,944,1,5,5,5,1,1,3,1,2,1,4,1,3,1,3,0.0,neutral or dissatisfied +97116,61222,Male,disloyal Customer,26,Business travel,Business,967,3,3,3,1,5,3,2,5,5,4,5,5,4,5,8,2.0,neutral or dissatisfied +97117,108306,Female,disloyal Customer,25,Business travel,Business,1750,5,5,5,4,3,5,3,3,4,4,5,4,4,3,0,0.0,satisfied +97118,107795,Female,Loyal Customer,54,Business travel,Business,349,5,5,5,5,4,5,4,3,3,4,3,4,3,3,27,23.0,satisfied +97119,94315,Female,Loyal Customer,43,Business travel,Business,3663,0,1,1,3,3,4,4,3,3,2,2,4,3,5,0,10.0,satisfied +97120,10530,Female,Loyal Customer,17,Business travel,Business,312,3,3,3,3,4,4,4,4,3,2,4,4,4,4,0,1.0,satisfied +97121,4114,Male,Loyal Customer,24,Business travel,Business,3700,4,4,4,4,5,4,5,5,3,2,5,4,5,5,0,0.0,satisfied +97122,34031,Female,disloyal Customer,62,Business travel,Eco Plus,1598,1,1,1,1,3,1,3,3,3,4,5,1,4,3,0,5.0,neutral or dissatisfied +97123,114167,Female,Loyal Customer,59,Business travel,Business,1821,3,3,3,3,3,4,4,4,4,4,4,4,4,5,111,95.0,satisfied +97124,32671,Female,Loyal Customer,35,Business travel,Eco,101,2,5,5,5,2,2,2,2,1,5,1,5,5,2,0,0.0,satisfied +97125,58795,Female,Loyal Customer,30,Business travel,Eco,1012,4,1,1,1,4,4,4,4,2,2,5,2,2,4,9,0.0,satisfied +97126,128727,Female,Loyal Customer,57,Personal Travel,Eco,1235,1,3,1,3,5,2,3,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +97127,42572,Female,disloyal Customer,62,Business travel,Eco,296,3,1,3,3,5,3,5,5,4,1,3,1,3,5,66,54.0,neutral or dissatisfied +97128,109265,Female,Loyal Customer,67,Personal Travel,Eco Plus,483,3,1,2,1,4,1,2,5,5,2,5,3,5,2,32,33.0,neutral or dissatisfied +97129,90996,Female,Loyal Customer,58,Business travel,Eco,581,4,1,1,1,4,5,1,4,4,4,4,4,4,3,0,0.0,satisfied +97130,69011,Female,Loyal Customer,41,Business travel,Business,1389,3,3,3,3,4,5,5,4,4,4,4,4,4,3,16,16.0,satisfied +97131,77589,Male,Loyal Customer,45,Business travel,Business,731,2,2,2,2,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +97132,124006,Male,Loyal Customer,55,Business travel,Business,184,4,3,3,3,2,4,4,2,2,2,4,4,2,1,0,0.0,neutral or dissatisfied +97133,60710,Male,Loyal Customer,22,Business travel,Business,1605,3,3,3,3,3,3,3,3,3,1,1,3,2,3,96,90.0,neutral or dissatisfied +97134,125659,Female,Loyal Customer,56,Business travel,Eco,857,3,4,4,4,2,3,2,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +97135,120174,Male,Loyal Customer,28,Personal Travel,Eco,335,1,4,1,1,2,1,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +97136,126226,Female,disloyal Customer,36,Business travel,Eco,200,3,4,3,3,4,3,1,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +97137,31944,Female,Loyal Customer,59,Business travel,Business,102,0,5,1,4,3,4,4,5,5,3,3,5,5,4,0,5.0,satisfied +97138,58059,Male,Loyal Customer,43,Business travel,Business,3466,3,3,3,3,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +97139,70862,Male,Loyal Customer,30,Business travel,Business,3416,1,1,1,1,5,5,5,5,5,3,2,1,4,5,0,0.0,satisfied +97140,99572,Female,disloyal Customer,29,Business travel,Business,802,2,2,2,4,4,2,4,4,4,4,5,4,4,4,0,5.0,neutral or dissatisfied +97141,98646,Male,Loyal Customer,30,Business travel,Eco,861,1,1,2,1,1,1,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +97142,104040,Female,Loyal Customer,60,Business travel,Business,1972,4,4,4,4,5,5,5,5,5,5,5,4,5,4,24,26.0,satisfied +97143,127171,Male,Loyal Customer,10,Personal Travel,Eco,304,1,5,1,1,5,1,4,5,3,5,4,5,5,5,51,38.0,neutral or dissatisfied +97144,124622,Male,Loyal Customer,39,Business travel,Business,1671,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +97145,48912,Male,Loyal Customer,39,Business travel,Eco,266,5,2,2,2,5,5,5,5,1,4,3,1,2,5,3,0.0,satisfied +97146,60293,Male,Loyal Customer,45,Business travel,Business,1773,2,4,4,4,5,3,3,2,2,2,2,4,2,4,8,21.0,neutral or dissatisfied +97147,34603,Female,Loyal Customer,18,Personal Travel,Eco,1598,3,2,3,3,5,3,5,5,3,1,3,1,2,5,2,0.0,neutral or dissatisfied +97148,4448,Male,Loyal Customer,70,Personal Travel,Eco,762,1,3,1,3,4,1,4,4,3,2,3,1,4,4,0,0.0,neutral or dissatisfied +97149,128249,Male,Loyal Customer,51,Business travel,Business,370,5,5,3,5,3,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +97150,96442,Male,Loyal Customer,33,Business travel,Business,3526,5,5,5,5,5,5,5,5,3,4,4,4,5,5,11,0.0,satisfied +97151,117097,Male,Loyal Customer,15,Business travel,Business,3794,3,1,1,1,3,3,3,3,2,1,3,2,3,3,18,11.0,neutral or dissatisfied +97152,120558,Female,Loyal Customer,27,Business travel,Business,2176,1,5,5,5,1,1,1,1,3,3,4,1,3,1,47,50.0,neutral or dissatisfied +97153,87414,Female,Loyal Customer,52,Personal Travel,Eco,425,3,2,3,4,5,4,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +97154,16611,Female,disloyal Customer,27,Business travel,Eco,1008,2,2,2,3,4,2,2,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +97155,72866,Female,Loyal Customer,22,Personal Travel,Eco,700,3,5,3,1,2,3,2,2,3,1,3,4,1,2,2,2.0,neutral or dissatisfied +97156,93765,Male,Loyal Customer,40,Personal Travel,Eco,368,1,3,1,5,4,1,2,4,3,4,1,3,5,4,0,0.0,neutral or dissatisfied +97157,79585,Female,Loyal Customer,34,Business travel,Business,2424,1,1,1,1,3,5,4,5,5,4,5,3,5,5,2,48.0,satisfied +97158,46128,Male,Loyal Customer,47,Business travel,Eco,604,4,5,5,5,4,4,4,4,4,2,3,3,4,4,0,2.0,satisfied +97159,44609,Female,disloyal Customer,20,Business travel,Eco,566,4,1,4,3,4,4,5,4,3,4,2,4,3,4,27,18.0,neutral or dissatisfied +97160,68614,Female,Loyal Customer,24,Personal Travel,Business,237,3,2,3,4,2,3,2,2,2,1,4,3,3,2,16,12.0,neutral or dissatisfied +97161,31827,Female,Loyal Customer,41,Business travel,Business,2762,4,4,4,4,4,4,4,1,4,5,1,4,5,4,0,23.0,satisfied +97162,75157,Male,disloyal Customer,22,Business travel,Eco,1166,2,2,2,3,1,2,1,1,4,3,3,4,3,1,0,11.0,neutral or dissatisfied +97163,16381,Male,Loyal Customer,48,Business travel,Eco,463,4,3,3,3,4,4,4,4,4,4,4,3,2,4,0,0.0,satisfied +97164,39399,Female,disloyal Customer,23,Business travel,Eco,521,2,4,2,4,3,2,1,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +97165,25147,Female,Loyal Customer,46,Business travel,Eco,406,4,4,4,4,5,2,2,4,4,4,4,4,4,1,0,4.0,neutral or dissatisfied +97166,25830,Female,Loyal Customer,30,Business travel,Business,484,2,2,2,2,4,4,4,4,4,2,4,1,2,4,1,0.0,satisfied +97167,20444,Male,Loyal Customer,45,Business travel,Business,84,4,4,4,4,1,4,4,5,5,5,4,2,5,1,14,10.0,satisfied +97168,16568,Female,Loyal Customer,29,Business travel,Eco,1092,4,5,5,5,4,4,4,4,2,5,4,5,4,4,0,0.0,satisfied +97169,32092,Female,Loyal Customer,63,Business travel,Business,3090,0,5,0,3,2,3,3,1,1,1,1,2,1,3,0,0.0,satisfied +97170,58585,Female,disloyal Customer,45,Business travel,Business,334,1,1,1,4,5,1,5,5,3,5,5,4,4,5,4,27.0,neutral or dissatisfied +97171,65844,Female,disloyal Customer,37,Business travel,Eco,1389,3,3,3,4,5,3,5,5,4,2,3,2,3,5,0,6.0,neutral or dissatisfied +97172,20688,Female,Loyal Customer,46,Business travel,Eco,779,4,4,4,4,1,4,1,4,4,4,4,5,4,3,0,0.0,satisfied +97173,48889,Male,Loyal Customer,35,Business travel,Eco,262,4,3,3,3,4,4,4,4,1,2,3,1,2,4,0,0.0,satisfied +97174,103089,Male,Loyal Customer,17,Personal Travel,Eco,460,0,4,0,1,4,0,4,4,4,2,3,5,4,4,0,0.0,satisfied +97175,119012,Male,Loyal Customer,26,Business travel,Business,479,2,2,5,2,5,5,5,5,4,5,5,4,5,5,0,8.0,satisfied +97176,103990,Male,Loyal Customer,41,Business travel,Business,1363,5,5,5,5,3,5,5,5,5,5,5,3,5,3,4,14.0,satisfied +97177,93150,Female,Loyal Customer,55,Business travel,Business,2133,2,3,3,3,1,3,4,2,2,3,2,3,2,2,0,18.0,neutral or dissatisfied +97178,112833,Male,disloyal Customer,18,Business travel,Business,1390,4,0,4,2,3,4,3,3,3,3,5,5,4,3,6,0.0,satisfied +97179,112320,Male,Loyal Customer,44,Business travel,Business,3829,1,1,1,1,3,5,5,4,4,4,4,4,4,5,25,25.0,satisfied +97180,103670,Female,Loyal Customer,50,Business travel,Business,405,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +97181,105199,Male,Loyal Customer,39,Personal Travel,Eco Plus,281,5,3,5,4,4,5,4,4,1,5,4,3,3,4,32,15.0,satisfied +97182,27956,Female,disloyal Customer,36,Business travel,Eco,1770,1,1,1,3,3,1,3,3,2,3,1,1,2,3,0,12.0,neutral or dissatisfied +97183,40135,Female,Loyal Customer,46,Personal Travel,Eco Plus,422,4,3,4,3,5,2,4,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +97184,28112,Female,Loyal Customer,44,Business travel,Business,2613,2,3,2,2,5,4,3,5,5,5,5,1,5,5,0,8.0,satisfied +97185,112493,Male,Loyal Customer,55,Personal Travel,Eco,909,4,5,4,4,2,4,2,2,4,4,1,3,4,2,0,0.0,neutral or dissatisfied +97186,36495,Male,disloyal Customer,45,Business travel,Business,1121,3,3,3,3,4,3,4,4,4,2,3,5,2,4,0,26.0,neutral or dissatisfied +97187,127300,Female,Loyal Customer,56,Business travel,Business,1979,5,5,5,5,5,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +97188,93349,Male,Loyal Customer,48,Business travel,Business,1966,4,4,4,4,2,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +97189,121086,Female,Loyal Customer,53,Personal Travel,Eco,196,3,5,3,1,5,5,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +97190,60218,Male,Loyal Customer,51,Business travel,Business,1546,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,19.0,satisfied +97191,105813,Female,Loyal Customer,46,Personal Travel,Eco,842,2,2,2,2,1,2,3,2,2,2,2,3,2,1,6,0.0,neutral or dissatisfied +97192,28726,Female,Loyal Customer,35,Personal Travel,Eco,2717,3,5,3,3,3,2,2,5,5,4,4,2,4,2,7,19.0,neutral or dissatisfied +97193,76154,Female,disloyal Customer,21,Business travel,Eco,689,4,4,4,4,2,4,2,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +97194,17673,Male,disloyal Customer,27,Business travel,Business,282,1,1,1,4,4,1,4,4,5,5,2,5,5,4,79,59.0,neutral or dissatisfied +97195,51097,Male,Loyal Customer,36,Personal Travel,Eco,250,2,4,0,2,4,0,4,4,5,3,5,4,4,4,82,62.0,neutral or dissatisfied +97196,71518,Male,Loyal Customer,25,Business travel,Business,1144,4,3,3,3,4,4,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +97197,90345,Male,Loyal Customer,41,Business travel,Business,3989,3,3,3,3,3,5,4,5,5,5,5,5,5,5,18,26.0,satisfied +97198,6606,Male,Loyal Customer,47,Personal Travel,Eco,473,2,1,2,2,3,2,3,3,2,3,3,3,2,3,0,0.0,neutral or dissatisfied +97199,39337,Female,Loyal Customer,51,Business travel,Business,774,4,4,4,4,2,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +97200,122527,Male,disloyal Customer,52,Business travel,Business,500,5,5,5,1,5,5,4,5,5,5,4,3,5,5,12,0.0,satisfied +97201,80733,Female,Loyal Customer,45,Business travel,Eco,393,4,2,2,2,3,4,4,3,3,4,3,1,3,3,5,2.0,neutral or dissatisfied +97202,48770,Female,disloyal Customer,19,Business travel,Business,109,2,2,2,4,2,2,2,2,3,4,4,4,4,2,0,7.0,neutral or dissatisfied +97203,96211,Male,Loyal Customer,66,Business travel,Business,2799,1,5,5,5,2,3,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +97204,83233,Male,Loyal Customer,46,Business travel,Business,2079,1,1,1,1,4,5,4,4,4,4,4,4,4,3,0,41.0,satisfied +97205,69534,Female,disloyal Customer,36,Business travel,Business,2475,4,4,4,1,4,1,1,5,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +97206,55772,Female,Loyal Customer,53,Business travel,Eco,599,1,4,4,4,3,4,3,1,1,1,1,1,1,3,8,2.0,neutral or dissatisfied +97207,97231,Female,disloyal Customer,27,Business travel,Business,296,2,2,2,4,4,2,4,4,1,2,3,4,3,4,33,26.0,neutral or dissatisfied +97208,63151,Male,Loyal Customer,49,Business travel,Business,447,1,1,1,1,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +97209,29328,Female,Loyal Customer,32,Personal Travel,Eco,859,2,4,2,3,2,2,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +97210,91675,Female,Loyal Customer,29,Personal Travel,Eco,954,3,3,3,2,4,3,4,4,4,4,1,4,3,4,6,14.0,neutral or dissatisfied +97211,111697,Male,Loyal Customer,47,Business travel,Business,495,1,1,1,1,2,4,4,1,1,1,1,4,1,1,17,5.0,neutral or dissatisfied +97212,47338,Male,disloyal Customer,25,Business travel,Eco,599,2,0,2,2,5,2,5,5,3,4,4,5,5,5,46,40.0,neutral or dissatisfied +97213,84213,Female,Loyal Customer,39,Business travel,Business,432,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +97214,17687,Male,Loyal Customer,54,Business travel,Eco,503,1,2,2,2,1,1,1,1,3,2,4,4,4,1,23,17.0,neutral or dissatisfied +97215,128389,Female,Loyal Customer,71,Business travel,Eco,338,3,4,4,4,3,3,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +97216,40392,Male,disloyal Customer,49,Business travel,Business,222,1,1,1,3,5,1,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +97217,115848,Male,Loyal Customer,57,Business travel,Business,373,4,2,2,2,1,3,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +97218,106447,Female,Loyal Customer,61,Personal Travel,Eco,1062,4,1,4,4,4,4,3,3,3,4,3,3,3,2,1,0.0,satisfied +97219,107947,Female,Loyal Customer,37,Personal Travel,Eco,611,2,4,2,5,1,2,1,1,4,1,5,5,5,1,51,43.0,neutral or dissatisfied +97220,23345,Male,Loyal Customer,33,Personal Travel,Eco,794,3,4,3,1,1,3,1,1,5,5,4,5,4,1,0,0.0,neutral or dissatisfied +97221,40541,Female,Loyal Customer,49,Business travel,Business,2429,1,1,1,1,5,5,2,5,5,5,5,5,5,3,0,0.0,satisfied +97222,79369,Male,Loyal Customer,43,Business travel,Business,3998,1,1,1,1,3,4,5,5,5,4,5,4,5,5,4,0.0,satisfied +97223,117848,Female,disloyal Customer,38,Business travel,Eco,1180,3,3,3,4,1,3,1,1,4,5,2,4,3,1,9,0.0,neutral or dissatisfied +97224,36497,Male,Loyal Customer,33,Business travel,Business,3899,2,2,2,2,4,4,4,4,5,5,5,1,4,4,0,0.0,satisfied +97225,28923,Female,disloyal Customer,30,Business travel,Eco,697,2,2,2,2,2,2,3,2,2,3,5,4,2,2,0,0.0,neutral or dissatisfied +97226,92022,Female,Loyal Customer,55,Business travel,Business,1535,1,1,1,1,2,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +97227,129221,Male,Loyal Customer,54,Business travel,Business,1464,1,1,1,1,5,4,5,5,5,5,5,5,5,5,1,0.0,satisfied +97228,78118,Male,Loyal Customer,40,Business travel,Business,1797,3,3,3,3,5,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +97229,69255,Male,disloyal Customer,22,Business travel,Eco,733,1,1,1,3,3,1,3,3,2,5,2,4,3,3,0,0.0,neutral or dissatisfied +97230,2320,Male,disloyal Customer,33,Personal Travel,Eco,630,4,5,3,1,5,3,1,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +97231,8363,Male,Loyal Customer,55,Business travel,Business,2942,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +97232,55867,Male,Loyal Customer,8,Business travel,Business,2753,1,5,5,5,1,1,1,1,1,1,3,4,4,1,30,23.0,neutral or dissatisfied +97233,25072,Female,Loyal Customer,54,Business travel,Eco,957,5,4,4,4,4,1,4,5,5,5,5,4,5,3,10,17.0,satisfied +97234,99718,Male,Loyal Customer,57,Business travel,Business,3872,5,5,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +97235,61006,Female,disloyal Customer,44,Business travel,Business,3365,3,3,3,2,3,4,4,4,2,3,4,4,4,4,7,0.0,neutral or dissatisfied +97236,116328,Female,Loyal Customer,12,Personal Travel,Eco,337,4,5,3,3,2,3,2,2,5,2,4,5,5,2,53,49.0,neutral or dissatisfied +97237,54727,Female,Loyal Customer,30,Personal Travel,Eco,787,3,5,2,1,2,2,2,2,4,3,4,3,4,2,8,13.0,neutral or dissatisfied +97238,83336,Female,Loyal Customer,62,Personal Travel,Eco,2105,2,3,2,1,2,4,4,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +97239,18570,Female,Loyal Customer,43,Business travel,Business,1541,2,4,4,4,2,1,1,1,1,1,2,3,1,1,11,10.0,neutral or dissatisfied +97240,56573,Female,disloyal Customer,18,Business travel,Eco,1068,3,3,3,2,2,3,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +97241,50667,Male,Loyal Customer,55,Personal Travel,Eco,109,2,5,2,5,5,2,5,5,4,5,5,5,5,5,58,70.0,neutral or dissatisfied +97242,69284,Female,Loyal Customer,66,Personal Travel,Eco,733,1,4,1,3,4,3,4,3,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +97243,27187,Male,Loyal Customer,24,Personal Travel,Eco,2681,1,2,1,4,3,1,3,3,3,1,4,1,4,3,92,,neutral or dissatisfied +97244,99577,Male,Loyal Customer,62,Business travel,Eco,429,2,1,1,1,2,2,2,2,2,2,3,1,4,2,88,74.0,neutral or dissatisfied +97245,88311,Male,Loyal Customer,39,Business travel,Eco,406,1,3,3,3,1,1,1,1,1,2,4,2,4,1,0,2.0,neutral or dissatisfied +97246,5155,Female,Loyal Customer,68,Personal Travel,Eco,622,2,3,2,4,3,3,3,3,3,2,3,3,3,2,17,19.0,neutral or dissatisfied +97247,32770,Male,Loyal Customer,37,Business travel,Business,163,0,3,0,5,5,2,2,3,3,3,3,1,3,5,0,0.0,satisfied +97248,60090,Male,Loyal Customer,23,Business travel,Business,2166,3,3,3,3,5,5,5,5,5,2,5,4,4,5,1,0.0,satisfied +97249,121015,Female,Loyal Customer,41,Personal Travel,Eco,861,2,5,2,3,3,2,3,3,4,4,4,3,4,3,0,10.0,neutral or dissatisfied +97250,57760,Male,Loyal Customer,47,Business travel,Business,2704,1,1,1,1,5,5,5,4,5,4,5,5,3,5,0,0.0,satisfied +97251,91922,Female,Loyal Customer,28,Business travel,Business,2586,5,5,5,5,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +97252,76071,Male,Loyal Customer,27,Business travel,Business,2306,2,5,5,5,2,2,2,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +97253,83629,Female,Loyal Customer,48,Personal Travel,Eco,409,2,4,2,4,2,5,5,1,1,2,1,3,1,5,7,0.0,neutral or dissatisfied +97254,33847,Male,Loyal Customer,54,Business travel,Business,1609,4,4,4,4,2,3,2,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +97255,39128,Female,disloyal Customer,37,Business travel,Eco,119,1,4,1,3,5,1,5,5,2,2,3,2,4,5,8,0.0,neutral or dissatisfied +97256,18404,Female,Loyal Customer,24,Business travel,Business,2216,0,0,0,3,4,4,4,4,4,2,4,4,3,4,0,0.0,satisfied +97257,76044,Female,Loyal Customer,30,Business travel,Business,669,2,1,2,2,5,5,5,5,5,3,4,3,5,5,2,0.0,satisfied +97258,35873,Male,Loyal Customer,13,Personal Travel,Eco,1065,3,1,3,3,5,3,4,5,2,2,3,1,2,5,11,0.0,neutral or dissatisfied +97259,81807,Male,Loyal Customer,37,Business travel,Eco,1306,2,4,4,4,2,1,2,2,1,2,4,4,3,2,0,1.0,neutral or dissatisfied +97260,30851,Male,Loyal Customer,46,Personal Travel,Eco,899,4,4,4,3,4,1,1,5,4,4,4,1,5,1,213,213.0,neutral or dissatisfied +97261,12250,Male,Loyal Customer,65,Business travel,Business,3963,5,5,5,5,2,1,5,5,5,5,4,3,5,1,0,1.0,satisfied +97262,32472,Male,disloyal Customer,24,Business travel,Eco,102,4,5,4,2,2,4,2,2,4,1,2,1,1,2,0,0.0,neutral or dissatisfied +97263,29695,Male,Loyal Customer,49,Business travel,Business,1542,3,3,2,3,4,5,3,4,4,4,4,5,4,2,0,1.0,satisfied +97264,10254,Male,Loyal Customer,61,Personal Travel,Business,163,1,5,0,4,5,5,5,5,5,0,5,5,5,5,0,0.0,neutral or dissatisfied +97265,74294,Female,Loyal Customer,20,Personal Travel,Eco,2288,2,1,2,3,5,2,5,5,2,2,3,1,2,5,0,0.0,neutral or dissatisfied +97266,95872,Male,Loyal Customer,24,Business travel,Business,759,1,3,3,3,1,1,1,1,2,3,4,3,4,1,27,15.0,neutral or dissatisfied +97267,15325,Female,Loyal Customer,45,Business travel,Business,3231,3,2,2,2,2,4,3,3,3,3,3,1,3,1,91,78.0,neutral or dissatisfied +97268,97199,Female,Loyal Customer,31,Personal Travel,Eco,1390,2,4,2,3,2,2,5,2,2,1,1,4,3,2,68,51.0,neutral or dissatisfied +97269,57318,Male,disloyal Customer,22,Business travel,Business,414,4,0,4,5,1,4,1,1,5,5,5,5,5,1,0,28.0,satisfied +97270,127452,Female,Loyal Customer,28,Personal Travel,Business,1814,3,5,3,5,1,3,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +97271,25470,Male,Loyal Customer,23,Personal Travel,Business,516,1,5,1,1,1,1,1,1,5,5,2,3,2,1,10,0.0,neutral or dissatisfied +97272,129611,Male,disloyal Customer,24,Business travel,Eco,337,4,5,4,2,2,4,2,2,3,2,5,4,4,2,0,10.0,satisfied +97273,128121,Male,disloyal Customer,46,Business travel,Eco,1587,4,4,4,1,5,4,5,5,4,4,1,2,2,5,126,118.0,neutral or dissatisfied +97274,82413,Female,Loyal Customer,43,Business travel,Business,102,4,4,4,4,4,5,4,5,3,5,4,4,3,4,140,156.0,satisfied +97275,61757,Female,Loyal Customer,16,Personal Travel,Eco,1346,2,4,3,3,5,3,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +97276,69109,Male,Loyal Customer,32,Personal Travel,Eco Plus,1521,2,5,2,4,3,2,4,3,5,4,4,5,4,3,67,58.0,neutral or dissatisfied +97277,58264,Male,Loyal Customer,45,Business travel,Business,1507,4,4,3,4,2,5,5,4,4,4,4,4,4,5,9,0.0,satisfied +97278,47089,Female,Loyal Customer,59,Personal Travel,Eco,438,2,4,2,3,5,5,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +97279,128843,Female,Loyal Customer,11,Personal Travel,Eco,2475,4,2,4,3,4,5,3,3,2,4,3,3,3,3,0,0.0,satisfied +97280,96964,Female,Loyal Customer,49,Business travel,Business,3635,3,3,3,3,3,5,4,2,2,2,2,5,2,4,0,6.0,satisfied +97281,99753,Male,Loyal Customer,24,Personal Travel,Eco,255,3,5,3,4,5,3,5,5,1,3,5,2,3,5,18,17.0,neutral or dissatisfied +97282,70479,Male,Loyal Customer,47,Business travel,Business,3683,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +97283,111632,Female,Loyal Customer,57,Business travel,Business,1558,4,4,4,4,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +97284,50507,Male,Loyal Customer,8,Personal Travel,Eco,109,4,1,4,4,2,4,2,2,4,5,3,1,3,2,9,5.0,neutral or dissatisfied +97285,10407,Female,Loyal Customer,43,Business travel,Business,3383,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +97286,102472,Male,Loyal Customer,9,Personal Travel,Eco,386,3,5,3,3,1,3,1,1,5,3,4,4,4,1,0,4.0,neutral or dissatisfied +97287,54828,Male,Loyal Customer,46,Business travel,Business,3382,2,2,2,2,3,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +97288,83330,Male,disloyal Customer,25,Business travel,Eco,954,3,3,3,4,3,3,3,3,4,4,2,4,4,3,0,12.0,neutral or dissatisfied +97289,84701,Female,disloyal Customer,26,Business travel,Business,481,3,0,2,3,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +97290,124782,Female,Loyal Customer,37,Business travel,Business,2444,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +97291,114889,Male,Loyal Customer,41,Business travel,Business,1723,5,5,5,5,3,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +97292,44416,Female,disloyal Customer,21,Business travel,Eco,265,2,0,2,2,3,2,3,3,3,2,3,3,5,3,0,2.0,neutral or dissatisfied +97293,494,Female,disloyal Customer,32,Business travel,Business,309,3,3,3,1,4,3,4,4,5,5,5,5,4,4,0,0.0,neutral or dissatisfied +97294,57674,Male,Loyal Customer,53,Business travel,Business,2564,3,3,3,3,5,5,4,4,4,4,5,5,4,3,0,0.0,satisfied +97295,121656,Male,Loyal Customer,36,Business travel,Business,511,5,1,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +97296,8614,Male,Loyal Customer,39,Personal Travel,Eco,1371,3,5,3,1,2,3,2,2,4,4,3,5,4,2,0,0.0,neutral or dissatisfied +97297,119871,Male,Loyal Customer,64,Personal Travel,Eco,936,2,3,2,2,3,2,2,3,1,1,5,4,3,3,0,5.0,neutral or dissatisfied +97298,73318,Female,Loyal Customer,48,Business travel,Business,1120,1,1,1,1,4,4,4,5,5,4,5,4,5,3,0,0.0,satisfied +97299,79519,Male,disloyal Customer,45,Business travel,Business,762,3,3,3,4,2,3,2,2,5,2,4,5,5,2,58,43.0,neutral or dissatisfied +97300,55578,Female,Loyal Customer,42,Business travel,Business,3001,3,3,3,3,3,2,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +97301,105249,Male,Loyal Customer,23,Business travel,Business,2106,4,4,4,4,5,5,5,5,5,5,3,4,5,5,5,0.0,satisfied +97302,37864,Male,Loyal Customer,26,Business travel,Eco,1068,4,3,3,3,4,4,2,4,3,5,3,1,3,4,48,43.0,neutral or dissatisfied +97303,107002,Male,Loyal Customer,26,Personal Travel,Eco,1036,4,4,4,4,3,4,3,3,3,3,4,4,5,3,6,3.0,neutral or dissatisfied +97304,50983,Female,Loyal Customer,20,Personal Travel,Eco,337,3,5,3,3,4,3,4,4,3,3,4,5,4,4,0,2.0,neutral or dissatisfied +97305,129819,Female,Loyal Customer,12,Personal Travel,Eco,337,4,5,4,5,4,4,4,4,3,1,1,1,3,4,18,34.0,neutral or dissatisfied +97306,121179,Male,Loyal Customer,58,Personal Travel,Eco,2402,1,4,1,3,1,1,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +97307,6709,Male,Loyal Customer,15,Personal Travel,Eco,438,1,4,1,5,4,1,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +97308,33843,Female,disloyal Customer,27,Business travel,Eco,1562,2,2,2,2,2,2,2,2,1,4,4,5,1,2,0,0.0,neutral or dissatisfied +97309,123826,Male,disloyal Customer,36,Business travel,Business,541,1,2,2,2,3,2,3,3,4,3,5,4,5,3,7,7.0,neutral or dissatisfied +97310,86562,Male,Loyal Customer,15,Personal Travel,Eco Plus,760,5,5,5,3,4,5,4,4,3,3,5,3,4,4,16,8.0,satisfied +97311,93360,Male,disloyal Customer,22,Business travel,Eco,1024,2,2,2,2,2,2,2,2,3,5,2,4,2,2,106,97.0,neutral or dissatisfied +97312,28782,Male,Loyal Customer,40,Business travel,Business,2732,4,4,4,4,5,5,4,4,4,5,4,4,4,4,0,0.0,satisfied +97313,70306,Male,Loyal Customer,53,Business travel,Business,3716,3,3,3,3,3,5,4,4,4,4,4,5,4,4,54,54.0,satisfied +97314,92379,Female,Loyal Customer,45,Personal Travel,Business,1947,2,4,3,4,2,4,5,4,4,3,5,5,4,3,49,31.0,neutral or dissatisfied +97315,25979,Female,Loyal Customer,30,Personal Travel,Business,577,5,5,5,1,3,5,3,3,4,3,5,5,4,3,0,0.0,satisfied +97316,61938,Female,Loyal Customer,36,Business travel,Business,2161,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +97317,17614,Female,disloyal Customer,23,Business travel,Eco,622,2,5,3,4,2,3,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +97318,16839,Male,Loyal Customer,44,Personal Travel,Eco,645,2,1,2,2,5,2,5,5,2,3,1,3,2,5,65,63.0,neutral or dissatisfied +97319,80543,Female,Loyal Customer,41,Business travel,Business,1747,4,4,4,4,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +97320,94432,Male,disloyal Customer,22,Business travel,Business,239,4,0,4,3,2,4,2,2,4,4,4,5,4,2,0,5.0,satisfied +97321,119444,Female,Loyal Customer,35,Personal Travel,Eco Plus,399,1,4,1,4,4,1,4,4,4,2,5,5,4,4,0,7.0,neutral or dissatisfied +97322,7182,Female,disloyal Customer,23,Business travel,Eco,135,4,2,4,4,2,4,2,2,3,2,4,3,3,2,49,111.0,neutral or dissatisfied +97323,49145,Male,disloyal Customer,35,Business travel,Eco,207,4,5,4,2,1,4,1,1,5,1,2,2,3,1,0,0.0,neutral or dissatisfied +97324,112001,Female,Loyal Customer,28,Business travel,Eco Plus,533,1,4,4,4,1,2,1,1,2,2,4,3,3,1,46,50.0,neutral or dissatisfied +97325,67054,Male,disloyal Customer,27,Business travel,Business,1121,3,3,3,5,2,3,2,2,3,4,5,4,4,2,5,0.0,neutral or dissatisfied +97326,99248,Female,Loyal Customer,10,Personal Travel,Eco,541,2,4,2,3,2,2,2,2,4,3,5,2,2,2,0,0.0,neutral or dissatisfied +97327,122175,Female,Loyal Customer,48,Business travel,Business,546,2,2,2,2,4,5,4,5,5,5,5,4,5,4,55,42.0,satisfied +97328,47331,Female,disloyal Customer,17,Business travel,Eco,588,2,0,2,2,4,2,4,4,3,4,2,5,5,4,0,0.0,neutral or dissatisfied +97329,97742,Male,disloyal Customer,27,Business travel,Eco,587,3,2,2,4,2,2,2,2,3,4,3,4,3,2,36,26.0,neutral or dissatisfied +97330,45497,Male,Loyal Customer,54,Personal Travel,Eco,522,3,4,3,3,1,3,3,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +97331,129203,Male,Loyal Customer,43,Business travel,Business,2419,1,1,1,1,5,5,5,3,5,5,4,5,4,5,304,288.0,satisfied +97332,73080,Male,Loyal Customer,56,Business travel,Business,2154,5,5,3,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +97333,54051,Female,disloyal Customer,20,Business travel,Eco,1416,3,3,3,1,2,3,2,2,1,2,5,1,3,2,0,0.0,neutral or dissatisfied +97334,58470,Male,Loyal Customer,17,Business travel,Business,3482,4,4,4,4,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +97335,78951,Male,Loyal Customer,32,Business travel,Business,356,3,3,2,3,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +97336,97838,Female,Loyal Customer,7,Personal Travel,Eco,480,1,1,1,3,4,1,4,4,2,2,3,3,3,4,29,31.0,neutral or dissatisfied +97337,68398,Male,disloyal Customer,26,Business travel,Eco,1045,3,3,3,3,2,3,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +97338,38657,Male,disloyal Customer,38,Business travel,Business,2704,4,4,4,4,3,4,3,3,5,5,5,4,3,3,0,0.0,satisfied +97339,14128,Male,Loyal Customer,40,Business travel,Business,2657,5,5,5,5,2,2,1,2,2,2,2,3,2,2,67,64.0,satisfied +97340,49634,Female,Loyal Customer,58,Business travel,Business,1812,3,3,4,3,1,1,5,5,5,5,4,3,5,4,97,121.0,satisfied +97341,37426,Male,disloyal Customer,31,Business travel,Eco,1056,1,1,1,3,2,1,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +97342,23452,Male,Loyal Customer,35,Business travel,Business,3212,3,2,4,2,1,2,3,3,3,3,3,2,3,1,6,26.0,neutral or dissatisfied +97343,68664,Female,Loyal Customer,63,Business travel,Business,2157,4,4,4,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +97344,45973,Female,Loyal Customer,17,Personal Travel,Eco,872,2,1,1,3,4,1,4,4,3,5,2,2,3,4,71,73.0,neutral or dissatisfied +97345,42259,Male,Loyal Customer,48,Business travel,Eco,748,3,4,4,4,3,3,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +97346,44439,Male,Loyal Customer,12,Personal Travel,Eco,588,2,1,2,4,5,2,5,5,4,1,3,3,4,5,5,34.0,neutral or dissatisfied +97347,54365,Female,Loyal Customer,29,Business travel,Eco Plus,1235,5,3,3,3,5,5,5,5,2,3,3,4,5,5,0,0.0,satisfied +97348,116804,Male,Loyal Customer,59,Personal Travel,Eco Plus,296,2,5,2,1,2,2,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +97349,14726,Male,Loyal Customer,58,Business travel,Eco Plus,419,3,3,3,3,3,3,3,3,5,4,1,5,2,3,0,9.0,satisfied +97350,42639,Female,Loyal Customer,60,Personal Travel,Eco,546,3,3,3,4,1,5,2,3,3,3,3,4,3,4,4,0.0,neutral or dissatisfied +97351,88846,Male,Loyal Customer,31,Personal Travel,Eco Plus,404,2,5,2,3,5,2,1,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +97352,15556,Male,Loyal Customer,58,Personal Travel,Business,229,2,4,2,5,5,5,4,4,4,2,4,3,4,5,2,0.0,neutral or dissatisfied +97353,50597,Male,Loyal Customer,44,Personal Travel,Eco,266,1,0,1,3,1,1,5,3,5,4,4,5,3,5,186,175.0,neutral or dissatisfied +97354,16971,Male,Loyal Customer,51,Business travel,Business,209,4,4,4,4,2,3,1,5,5,5,5,5,5,3,5,5.0,satisfied +97355,76059,Male,disloyal Customer,24,Business travel,Eco,669,0,0,0,2,4,0,4,4,5,5,5,3,5,4,10,4.0,satisfied +97356,35350,Female,disloyal Customer,22,Business travel,Eco,1069,3,3,3,4,1,3,1,1,1,4,4,3,4,1,92,101.0,neutral or dissatisfied +97357,121735,Male,Loyal Customer,41,Business travel,Eco,1475,5,3,2,3,5,5,5,5,1,2,1,2,1,5,7,0.0,satisfied +97358,27931,Female,Loyal Customer,51,Personal Travel,Business,1660,3,0,3,3,4,5,4,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +97359,93581,Male,Loyal Customer,43,Business travel,Eco,159,5,1,1,1,5,5,5,5,1,4,5,3,3,5,0,0.0,satisfied +97360,63544,Male,Loyal Customer,65,Personal Travel,Eco,1009,3,4,4,1,5,4,5,5,1,4,1,3,2,5,4,7.0,neutral or dissatisfied +97361,4042,Female,disloyal Customer,18,Business travel,Eco,483,4,4,4,4,5,4,3,5,1,4,3,4,4,5,9,16.0,neutral or dissatisfied +97362,14848,Male,Loyal Customer,56,Business travel,Eco,315,5,5,5,5,5,5,5,5,4,1,2,4,4,5,41,69.0,satisfied +97363,81964,Male,Loyal Customer,50,Business travel,Business,1522,5,5,5,5,4,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +97364,67136,Female,Loyal Customer,52,Business travel,Business,1881,1,1,4,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +97365,34648,Male,Loyal Customer,36,Personal Travel,Eco,541,4,4,4,1,5,4,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +97366,57747,Female,Loyal Customer,59,Business travel,Business,2704,2,2,2,2,4,4,4,5,4,3,5,4,5,4,18,16.0,satisfied +97367,92012,Male,Loyal Customer,8,Personal Travel,Business,1589,2,4,2,3,3,2,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +97368,80959,Female,Loyal Customer,43,Business travel,Business,1620,3,3,3,3,3,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +97369,55835,Female,disloyal Customer,35,Business travel,Eco,1416,2,2,2,4,2,2,5,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +97370,97923,Female,Loyal Customer,25,Business travel,Business,3807,3,3,3,3,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +97371,91519,Female,Loyal Customer,35,Personal Travel,Eco,1620,1,4,0,2,4,0,4,4,4,2,4,3,5,4,2,0.0,neutral or dissatisfied +97372,52781,Female,Loyal Customer,47,Business travel,Business,1874,1,4,4,4,3,4,4,1,1,1,1,2,1,4,48,25.0,neutral or dissatisfied +97373,58754,Male,Loyal Customer,23,Business travel,Business,1012,4,4,4,4,4,4,4,4,5,5,4,4,4,4,8,12.0,satisfied +97374,96263,Female,Loyal Customer,62,Personal Travel,Eco,546,4,3,4,2,5,1,5,3,3,4,3,4,3,4,8,7.0,neutral or dissatisfied +97375,12854,Female,Loyal Customer,52,Personal Travel,Eco,528,3,4,3,3,2,5,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +97376,55608,Male,Loyal Customer,32,Business travel,Business,404,1,1,1,1,5,5,5,5,1,4,1,4,3,5,23,0.0,satisfied +97377,56601,Female,Loyal Customer,30,Business travel,Business,3577,5,5,5,5,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +97378,69163,Male,Loyal Customer,54,Business travel,Business,187,3,3,4,3,5,5,5,4,4,4,4,4,4,5,105,94.0,satisfied +97379,62419,Female,disloyal Customer,18,Business travel,Eco,2457,3,4,4,3,2,3,4,2,3,4,3,1,3,2,0,4.0,neutral or dissatisfied +97380,112530,Male,Loyal Customer,28,Personal Travel,Eco,862,1,1,1,1,5,1,5,5,3,2,1,3,2,5,10,7.0,neutral or dissatisfied +97381,33464,Male,Loyal Customer,32,Personal Travel,Eco Plus,2556,4,2,4,4,4,2,2,3,1,3,4,2,2,2,0,0.0,neutral or dissatisfied +97382,29316,Male,Loyal Customer,18,Personal Travel,Eco,569,2,5,2,3,2,2,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +97383,17260,Male,disloyal Customer,18,Personal Travel,Eco,1092,2,5,2,5,2,2,2,2,2,3,2,5,1,2,0,0.0,neutral or dissatisfied +97384,11989,Male,Loyal Customer,59,Personal Travel,Eco,667,2,3,2,3,4,2,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +97385,29038,Female,Loyal Customer,47,Personal Travel,Eco,954,1,4,1,4,4,3,4,3,3,1,3,3,3,1,0,10.0,neutral or dissatisfied +97386,21384,Male,disloyal Customer,27,Business travel,Business,306,1,2,2,4,4,2,4,4,3,5,3,1,3,4,0,0.0,neutral or dissatisfied +97387,45011,Male,Loyal Customer,59,Personal Travel,Eco,235,2,4,2,3,2,4,4,5,3,2,3,4,2,4,172,191.0,neutral or dissatisfied +97388,39804,Female,Loyal Customer,56,Business travel,Business,3428,2,2,2,2,1,4,3,4,4,5,4,3,4,4,0,0.0,satisfied +97389,76093,Male,Loyal Customer,44,Personal Travel,Eco,669,2,3,2,3,2,2,2,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +97390,107971,Female,Loyal Customer,21,Business travel,Business,1783,2,3,3,3,2,2,2,1,4,3,4,2,4,2,503,507.0,neutral or dissatisfied +97391,18844,Female,Loyal Customer,24,Business travel,Business,3356,3,3,3,3,5,5,5,5,1,2,2,4,2,5,0,0.0,satisfied +97392,29475,Male,Loyal Customer,57,Business travel,Eco,1107,4,4,4,4,4,4,4,4,3,5,5,4,5,4,145,141.0,satisfied +97393,11845,Female,Loyal Customer,31,Business travel,Business,3037,1,1,3,1,2,2,2,2,3,4,4,4,4,2,127,,satisfied +97394,19625,Female,Loyal Customer,31,Personal Travel,Business,642,3,4,3,1,2,3,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +97395,114138,Male,Loyal Customer,43,Business travel,Business,909,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +97396,43976,Female,Loyal Customer,23,Business travel,Business,3798,1,1,1,1,5,5,5,5,2,5,5,5,3,5,0,0.0,satisfied +97397,119519,Male,disloyal Customer,29,Business travel,Eco,759,2,2,2,2,3,2,3,3,2,5,2,2,2,3,0,0.0,neutral or dissatisfied +97398,25331,Male,disloyal Customer,30,Business travel,Eco,829,1,1,1,3,4,1,4,4,2,5,2,3,3,4,0,0.0,neutral or dissatisfied +97399,70898,Female,Loyal Customer,61,Business travel,Business,1721,4,1,1,1,5,3,3,4,4,4,4,3,4,1,89,90.0,neutral or dissatisfied +97400,88428,Female,Loyal Customer,58,Business travel,Business,3747,1,1,1,1,4,5,4,4,4,4,4,4,4,4,6,0.0,satisfied +97401,72018,Female,Loyal Customer,68,Business travel,Business,3784,2,2,3,2,4,4,4,5,2,3,5,4,4,4,0,0.0,satisfied +97402,89370,Male,disloyal Customer,36,Business travel,Business,134,4,4,4,4,5,4,2,5,5,5,5,3,4,5,0,1.0,neutral or dissatisfied +97403,112748,Male,Loyal Customer,43,Business travel,Business,588,4,4,4,4,5,5,5,4,4,4,4,5,4,5,43,27.0,satisfied +97404,46612,Male,disloyal Customer,28,Business travel,Eco,152,1,1,1,3,4,1,4,4,1,4,3,4,2,4,8,0.0,neutral or dissatisfied +97405,41224,Female,disloyal Customer,27,Business travel,Eco,1042,3,3,3,4,5,3,5,5,2,5,4,3,5,5,26,13.0,neutral or dissatisfied +97406,83715,Male,Loyal Customer,16,Business travel,Eco Plus,577,2,5,5,5,2,2,4,2,2,5,3,1,3,2,9,46.0,neutral or dissatisfied +97407,44971,Female,Loyal Customer,56,Business travel,Business,118,5,5,5,5,1,1,4,4,4,4,4,1,4,3,0,0.0,satisfied +97408,71119,Male,disloyal Customer,12,Business travel,Eco,678,3,3,3,3,5,3,1,5,1,4,4,1,3,5,91,99.0,neutral or dissatisfied +97409,92429,Female,Loyal Customer,46,Business travel,Business,1919,4,4,3,4,3,4,4,5,5,5,5,3,5,4,2,6.0,satisfied +97410,57827,Male,Loyal Customer,44,Personal Travel,Eco,622,2,3,2,4,1,2,1,1,2,4,1,4,5,1,2,0.0,neutral or dissatisfied +97411,83876,Male,Loyal Customer,26,Business travel,Eco,1670,3,5,5,5,3,3,1,3,4,2,4,1,3,3,7,15.0,neutral or dissatisfied +97412,122087,Male,Loyal Customer,52,Personal Travel,Eco,83,3,1,3,3,4,3,4,4,3,5,3,1,3,4,0,0.0,neutral or dissatisfied +97413,86360,Male,disloyal Customer,22,Business travel,Eco,762,4,4,4,2,5,4,5,5,3,5,4,3,4,5,0,2.0,neutral or dissatisfied +97414,56419,Female,Loyal Customer,39,Business travel,Business,2635,3,5,3,3,2,5,4,4,4,4,4,4,4,5,25,6.0,satisfied +97415,101326,Male,Loyal Customer,52,Personal Travel,Eco,986,3,4,3,3,5,3,5,5,4,2,3,4,4,5,40,31.0,neutral or dissatisfied +97416,116678,Male,Loyal Customer,53,Business travel,Eco Plus,371,4,1,1,1,4,4,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +97417,121720,Male,Loyal Customer,7,Personal Travel,Eco,683,3,5,3,4,3,3,3,3,2,1,4,3,5,3,0,0.0,neutral or dissatisfied +97418,36782,Female,Loyal Customer,39,Business travel,Business,2704,1,3,3,3,2,1,1,2,4,2,4,1,3,1,0,25.0,neutral or dissatisfied +97419,938,Female,Loyal Customer,56,Business travel,Business,3755,2,2,2,2,5,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +97420,70430,Male,Loyal Customer,50,Business travel,Business,187,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +97421,122632,Female,Loyal Customer,39,Personal Travel,Eco,728,3,2,3,3,3,3,3,3,2,1,2,3,3,3,0,0.0,neutral or dissatisfied +97422,113753,Male,Loyal Customer,39,Personal Travel,Eco,397,1,4,3,1,2,3,3,2,3,4,5,4,5,2,9,16.0,neutral or dissatisfied +97423,106308,Female,disloyal Customer,21,Business travel,Eco,998,3,3,3,3,5,3,5,5,3,5,4,1,4,5,30,29.0,neutral or dissatisfied +97424,37928,Female,Loyal Customer,52,Personal Travel,Eco,1023,4,5,4,1,4,3,4,4,4,4,4,4,4,2,0,0.0,satisfied +97425,5884,Female,Loyal Customer,60,Business travel,Business,2865,2,2,5,5,3,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +97426,59568,Male,Loyal Customer,52,Business travel,Business,1690,3,3,3,3,3,5,4,5,5,5,5,3,5,3,8,7.0,satisfied +97427,93556,Female,Loyal Customer,48,Business travel,Business,719,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +97428,25366,Male,Loyal Customer,54,Business travel,Eco,591,5,4,4,4,5,5,5,5,2,4,2,2,1,5,22,15.0,satisfied +97429,76534,Male,Loyal Customer,23,Business travel,Business,3810,3,3,3,3,5,4,5,5,4,2,5,3,5,5,0,0.0,satisfied +97430,127520,Female,disloyal Customer,23,Business travel,Eco,1009,5,5,5,2,5,5,5,5,5,2,4,3,5,5,123,113.0,satisfied +97431,108164,Female,Loyal Customer,44,Personal Travel,Eco,1105,2,3,3,2,1,5,1,3,3,3,3,3,3,1,26,25.0,neutral or dissatisfied +97432,66465,Female,Loyal Customer,31,Business travel,Eco Plus,1217,3,5,5,5,3,3,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +97433,15853,Female,Loyal Customer,34,Business travel,Business,2536,5,1,5,5,5,5,5,1,5,3,1,5,2,5,271,243.0,satisfied +97434,117801,Male,Loyal Customer,56,Business travel,Business,328,2,5,2,2,2,5,4,4,4,4,4,5,4,4,4,0.0,satisfied +97435,30073,Female,Loyal Customer,49,Personal Travel,Eco,571,5,5,5,4,5,5,5,5,5,5,5,3,5,3,9,0.0,satisfied +97436,88072,Female,Loyal Customer,42,Business travel,Business,3480,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +97437,95268,Female,Loyal Customer,41,Personal Travel,Eco,277,1,4,3,3,5,3,5,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +97438,124572,Female,Loyal Customer,24,Business travel,Business,500,1,5,1,1,3,4,3,3,5,3,5,4,4,3,0,0.0,satisfied +97439,37396,Female,Loyal Customer,23,Business travel,Business,2134,5,5,5,5,4,4,4,4,5,1,1,5,1,4,0,0.0,satisfied +97440,117049,Male,Loyal Customer,24,Business travel,Business,2744,1,0,0,4,0,5,1,2,5,3,4,1,4,1,131,135.0,neutral or dissatisfied +97441,25257,Male,Loyal Customer,53,Business travel,Business,2166,4,4,4,4,5,3,4,4,4,4,4,2,4,5,0,0.0,satisfied +97442,3053,Male,Loyal Customer,63,Business travel,Business,3482,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +97443,48211,Female,Loyal Customer,49,Personal Travel,Eco,259,3,2,3,1,1,1,1,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +97444,116222,Male,Loyal Customer,46,Personal Travel,Eco,308,3,5,3,3,2,3,2,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +97445,33985,Male,Loyal Customer,24,Business travel,Eco,1598,5,2,4,4,5,5,3,5,1,5,3,1,3,5,0,0.0,satisfied +97446,101959,Female,disloyal Customer,23,Business travel,Eco,628,3,3,3,4,3,3,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +97447,101395,Male,Loyal Customer,54,Business travel,Business,3727,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +97448,4914,Male,Loyal Customer,77,Business travel,Eco,1020,1,3,3,3,1,1,1,1,2,3,3,1,3,1,0,0.0,neutral or dissatisfied +97449,124333,Female,Loyal Customer,57,Personal Travel,Business,1037,2,4,2,3,3,4,4,3,3,2,3,5,3,3,0,30.0,neutral or dissatisfied +97450,104879,Male,Loyal Customer,14,Personal Travel,Eco,327,4,3,4,4,4,4,4,4,4,5,5,4,5,4,13,8.0,neutral or dissatisfied +97451,101108,Female,Loyal Customer,45,Business travel,Business,583,5,5,5,5,3,5,4,4,4,4,4,5,4,4,2,0.0,satisfied +97452,69081,Male,Loyal Customer,56,Personal Travel,Eco,1389,3,5,3,2,2,3,2,2,3,2,3,3,5,2,0,0.0,neutral or dissatisfied +97453,12074,Female,Loyal Customer,24,Business travel,Eco Plus,351,5,2,2,2,5,5,4,5,1,3,4,2,4,5,0,0.0,satisfied +97454,70246,Female,Loyal Customer,43,Business travel,Eco,1592,3,1,5,1,4,4,3,3,3,3,3,3,3,3,0,12.0,neutral or dissatisfied +97455,10950,Female,Loyal Customer,54,Business travel,Business,3801,5,5,5,5,3,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +97456,55238,Male,Loyal Customer,75,Business travel,Business,609,2,2,2,2,1,4,5,4,4,4,4,5,4,5,0,1.0,satisfied +97457,95679,Male,Loyal Customer,61,Business travel,Business,419,4,4,4,4,4,5,4,2,2,2,2,3,2,3,69,51.0,satisfied +97458,8210,Male,disloyal Customer,28,Business travel,Eco,125,1,4,1,1,4,1,4,4,1,1,2,5,4,4,0,0.0,neutral or dissatisfied +97459,35532,Female,Loyal Customer,34,Personal Travel,Eco,1053,1,4,1,3,5,1,1,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +97460,100837,Male,Loyal Customer,54,Business travel,Business,711,1,1,1,1,4,5,4,5,5,5,5,3,5,4,5,0.0,satisfied +97461,54741,Male,Loyal Customer,18,Personal Travel,Eco,861,2,3,1,1,2,1,3,2,4,2,5,4,4,2,14,7.0,neutral or dissatisfied +97462,103125,Female,Loyal Customer,21,Personal Travel,Eco,460,2,4,2,2,2,2,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +97463,116671,Male,Loyal Customer,47,Business travel,Eco Plus,333,1,1,1,1,1,1,1,1,2,2,3,2,4,1,5,0.0,neutral or dissatisfied +97464,55978,Female,Loyal Customer,8,Personal Travel,Eco,1620,2,4,2,1,1,2,1,1,5,5,3,5,5,1,8,0.0,neutral or dissatisfied +97465,108040,Female,disloyal Customer,23,Business travel,Eco,306,2,2,2,3,4,2,4,4,1,5,4,3,4,4,2,0.0,neutral or dissatisfied +97466,81512,Male,Loyal Customer,41,Business travel,Business,1124,5,5,5,5,3,4,5,5,5,5,5,4,5,5,0,3.0,satisfied +97467,6996,Female,Loyal Customer,53,Business travel,Eco,299,3,5,5,5,4,4,3,3,3,3,3,2,3,1,109,110.0,neutral or dissatisfied +97468,71161,Male,Loyal Customer,44,Personal Travel,Eco,646,1,3,1,1,5,1,5,5,2,3,3,2,4,5,21,14.0,neutral or dissatisfied +97469,28324,Male,Loyal Customer,23,Business travel,Business,2589,5,5,5,5,5,5,5,5,1,2,4,3,1,5,0,14.0,satisfied +97470,110131,Female,Loyal Customer,46,Business travel,Business,3809,1,1,1,1,4,4,4,5,5,5,5,3,5,3,3,11.0,satisfied +97471,47620,Female,Loyal Customer,47,Business travel,Business,2997,1,1,1,1,5,3,5,4,4,4,4,1,4,2,6,8.0,satisfied +97472,90370,Male,Loyal Customer,56,Business travel,Business,3319,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +97473,11217,Male,Loyal Customer,61,Personal Travel,Eco,312,2,4,2,2,4,2,5,4,5,3,5,3,5,4,2,0.0,neutral or dissatisfied +97474,62091,Female,Loyal Customer,39,Business travel,Business,2454,2,2,2,2,2,5,5,4,4,4,4,4,4,3,21,15.0,satisfied +97475,98369,Female,Loyal Customer,67,Personal Travel,Eco,1046,4,4,4,4,5,5,5,3,3,4,1,3,3,5,0,0.0,neutral or dissatisfied +97476,89314,Male,Loyal Customer,39,Business travel,Business,1587,1,1,4,1,5,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +97477,48446,Male,Loyal Customer,44,Business travel,Business,2187,5,5,5,5,5,3,5,4,4,4,4,4,4,2,23,12.0,satisfied +97478,110597,Male,disloyal Customer,33,Personal Travel,Eco,551,3,2,3,3,3,3,5,3,4,2,2,4,3,3,94,89.0,neutral or dissatisfied +97479,48365,Male,Loyal Customer,35,Business travel,Business,2187,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,3.0,satisfied +97480,24268,Female,Loyal Customer,39,Personal Travel,Eco,147,4,5,4,4,2,4,2,2,5,5,5,5,5,2,0,0.0,satisfied +97481,41885,Female,Loyal Customer,49,Business travel,Eco,413,2,1,1,1,3,3,3,3,3,2,3,4,3,2,14,29.0,neutral or dissatisfied +97482,14508,Male,Loyal Customer,71,Business travel,Eco,402,3,3,2,3,3,3,3,4,3,3,4,3,3,3,222,208.0,neutral or dissatisfied +97483,19208,Male,Loyal Customer,44,Business travel,Eco,459,3,3,3,3,3,3,3,3,2,2,1,5,5,3,0,0.0,satisfied +97484,114269,Male,Loyal Customer,22,Business travel,Business,850,1,1,1,1,4,4,4,4,2,1,2,3,5,4,0,0.0,satisfied +97485,52898,Male,Loyal Customer,22,Business travel,Eco Plus,1024,5,1,1,1,5,5,3,5,2,3,2,4,3,5,0,0.0,satisfied +97486,74856,Male,Loyal Customer,51,Business travel,Business,1995,1,1,5,1,5,4,5,2,2,3,2,5,2,3,0,0.0,satisfied +97487,23072,Female,Loyal Customer,10,Business travel,Eco Plus,820,5,3,2,2,5,5,4,5,1,5,4,5,5,5,0,0.0,satisfied +97488,53274,Male,Loyal Customer,29,Business travel,Business,3677,2,2,2,2,4,4,4,4,4,2,2,3,5,4,2,0.0,satisfied +97489,32400,Male,Loyal Customer,42,Business travel,Eco,101,2,5,5,5,2,2,2,2,1,1,5,1,5,2,0,0.0,satisfied +97490,128487,Male,Loyal Customer,13,Personal Travel,Eco,370,4,5,4,4,4,4,2,4,1,3,2,2,4,4,0,0.0,satisfied +97491,41982,Male,Loyal Customer,47,Business travel,Eco Plus,618,5,3,2,3,5,5,5,5,3,4,1,1,4,5,0,0.0,satisfied +97492,123167,Female,Loyal Customer,76,Business travel,Business,200,0,4,0,2,4,4,2,1,1,1,1,2,1,1,1,0.0,satisfied +97493,128831,Male,Loyal Customer,46,Business travel,Business,2586,3,2,2,2,3,3,3,1,5,2,4,3,2,3,12,10.0,neutral or dissatisfied +97494,80815,Male,disloyal Customer,26,Business travel,Eco,692,1,0,0,4,3,0,3,3,3,4,3,2,3,3,4,6.0,neutral or dissatisfied +97495,72846,Female,Loyal Customer,50,Business travel,Business,1013,1,1,1,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +97496,2305,Male,disloyal Customer,15,Business travel,Eco,672,2,2,2,3,2,2,2,2,4,1,4,2,3,2,24,24.0,neutral or dissatisfied +97497,93610,Male,Loyal Customer,25,Business travel,Eco,704,3,1,3,1,3,3,3,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +97498,60534,Female,Loyal Customer,47,Personal Travel,Eco,862,3,4,3,4,4,5,4,3,3,3,2,3,3,3,14,0.0,neutral or dissatisfied +97499,21618,Male,disloyal Customer,27,Business travel,Eco,780,4,4,4,2,4,4,4,4,2,1,3,1,2,4,0,14.0,neutral or dissatisfied +97500,5287,Male,Loyal Customer,30,Personal Travel,Eco,190,5,5,5,3,1,5,1,1,5,4,4,4,4,1,0,0.0,satisfied +97501,97841,Female,Loyal Customer,22,Personal Travel,Eco,395,3,5,3,4,4,3,4,4,4,5,5,5,5,4,27,33.0,neutral or dissatisfied +97502,103466,Female,Loyal Customer,29,Business travel,Business,3934,4,4,4,4,5,5,5,5,5,2,4,3,5,5,15,14.0,satisfied +97503,50717,Male,Loyal Customer,26,Personal Travel,Eco,89,3,3,0,2,5,0,3,5,2,5,2,2,1,5,6,8.0,neutral or dissatisfied +97504,118219,Male,Loyal Customer,49,Business travel,Eco,735,4,5,5,5,5,4,5,5,2,4,3,1,4,5,0,9.0,neutral or dissatisfied +97505,7239,Female,Loyal Customer,33,Business travel,Eco,139,5,4,4,4,5,5,5,5,3,3,3,5,5,5,0,0.0,satisfied +97506,101387,Female,disloyal Customer,20,Business travel,Business,486,5,0,5,1,2,5,2,2,5,4,4,4,4,2,0,0.0,satisfied +97507,46110,Female,Loyal Customer,31,Business travel,Eco,1085,3,3,2,3,3,3,3,3,1,3,4,4,4,3,10,7.0,neutral or dissatisfied +97508,75834,Male,Loyal Customer,60,Business travel,Eco,1440,3,1,1,1,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +97509,76273,Female,Loyal Customer,58,Business travel,Business,1927,2,2,2,2,3,5,5,4,4,5,4,4,4,3,5,19.0,satisfied +97510,118927,Male,Loyal Customer,57,Business travel,Business,570,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +97511,42567,Female,Loyal Customer,59,Business travel,Business,240,2,1,2,2,3,1,1,4,4,4,4,4,4,5,69,90.0,satisfied +97512,104983,Male,Loyal Customer,47,Business travel,Business,1513,2,2,2,2,4,5,5,4,4,4,4,4,4,3,12,0.0,satisfied +97513,119585,Male,Loyal Customer,77,Business travel,Eco,2276,3,4,4,4,3,3,3,4,2,1,2,3,2,3,0,14.0,neutral or dissatisfied +97514,88874,Female,Loyal Customer,54,Business travel,Business,1617,1,1,1,1,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +97515,33229,Female,disloyal Customer,39,Business travel,Eco Plus,101,4,4,4,4,1,4,1,1,5,1,5,4,3,1,0,0.0,satisfied +97516,55741,Female,Loyal Customer,21,Personal Travel,Eco,2052,2,4,2,4,3,2,3,3,3,5,3,5,5,3,0,0.0,neutral or dissatisfied +97517,60139,Male,Loyal Customer,46,Business travel,Business,1850,1,3,3,3,3,3,2,1,1,1,1,2,1,1,0,7.0,neutral or dissatisfied +97518,47217,Female,Loyal Customer,32,Personal Travel,Eco,954,2,4,2,4,1,2,1,1,1,5,3,4,3,1,0,9.0,neutral or dissatisfied +97519,33499,Male,Loyal Customer,50,Business travel,Business,965,2,2,2,2,3,4,4,2,2,3,2,3,2,5,0,0.0,satisfied +97520,73844,Male,disloyal Customer,37,Business travel,Business,1810,2,2,2,3,4,2,1,4,4,2,5,3,5,4,0,2.0,neutral or dissatisfied +97521,111684,Male,Loyal Customer,30,Personal Travel,Business,495,3,2,4,2,2,4,2,2,4,1,3,1,2,2,11,0.0,neutral or dissatisfied +97522,129265,Female,Loyal Customer,51,Business travel,Business,2521,2,2,2,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +97523,96202,Male,Loyal Customer,78,Business travel,Business,460,4,4,4,4,1,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +97524,105218,Male,disloyal Customer,24,Business travel,Business,377,0,5,0,1,3,0,3,3,3,3,4,5,5,3,12,0.0,satisfied +97525,123958,Female,Loyal Customer,45,Business travel,Business,2581,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +97526,125051,Male,Loyal Customer,50,Personal Travel,Eco,2300,3,4,2,3,2,1,1,4,2,4,4,1,3,1,3,26.0,neutral or dissatisfied +97527,26190,Male,Loyal Customer,41,Business travel,Eco,515,2,3,3,3,3,2,3,3,2,2,4,3,3,3,98,98.0,neutral or dissatisfied +97528,3511,Female,Loyal Customer,52,Business travel,Eco Plus,968,1,2,2,2,4,2,1,1,1,1,1,1,1,3,17,23.0,neutral or dissatisfied +97529,118845,Female,Loyal Customer,66,Business travel,Eco Plus,304,3,5,4,4,5,4,4,3,3,3,3,4,3,2,53,43.0,neutral or dissatisfied +97530,74346,Female,Loyal Customer,34,Personal Travel,Business,1464,4,4,4,2,3,3,5,2,2,4,2,5,2,3,48,42.0,neutral or dissatisfied +97531,116797,Male,Loyal Customer,20,Personal Travel,Eco Plus,390,3,2,3,3,1,3,1,1,3,1,4,1,4,1,79,71.0,neutral or dissatisfied +97532,115653,Male,Loyal Customer,23,Business travel,Business,3968,2,3,3,3,2,1,2,2,1,1,3,3,3,2,59,56.0,neutral or dissatisfied +97533,9959,Male,Loyal Customer,36,Business travel,Business,108,3,3,3,3,5,4,5,4,4,4,5,3,4,5,0,4.0,satisfied +97534,101676,Male,disloyal Customer,22,Business travel,Eco,1135,2,2,2,1,4,2,2,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +97535,37013,Female,Loyal Customer,37,Personal Travel,Eco,899,2,3,2,3,3,2,2,3,2,2,2,4,3,3,10,15.0,neutral or dissatisfied +97536,115406,Female,Loyal Customer,59,Business travel,Business,308,1,1,1,1,4,5,4,5,5,5,5,4,5,3,16,22.0,satisfied +97537,6294,Female,Loyal Customer,60,Business travel,Business,693,3,3,3,3,5,5,5,4,4,4,4,4,4,3,28,6.0,satisfied +97538,25063,Female,Loyal Customer,25,Personal Travel,Eco,594,5,1,5,4,5,5,4,5,4,4,3,1,4,5,2,0.0,satisfied +97539,99569,Female,Loyal Customer,45,Business travel,Business,1648,1,3,3,3,5,4,4,1,1,1,1,3,1,2,62,56.0,neutral or dissatisfied +97540,24083,Male,Loyal Customer,39,Business travel,Business,1606,5,5,5,5,4,2,5,4,4,4,4,4,4,1,0,0.0,satisfied +97541,64689,Female,disloyal Customer,39,Business travel,Business,224,3,3,3,2,2,3,2,2,4,5,4,5,4,2,0,12.0,neutral or dissatisfied +97542,122774,Male,Loyal Customer,39,Business travel,Business,599,3,3,3,3,3,4,5,4,4,4,4,3,4,3,28,22.0,satisfied +97543,40360,Female,Loyal Customer,25,Business travel,Business,2906,2,2,2,2,5,5,5,5,1,5,4,1,5,5,0,0.0,satisfied +97544,112550,Female,Loyal Customer,49,Business travel,Business,957,5,5,5,5,5,5,5,4,4,4,4,4,4,3,84,75.0,satisfied +97545,46514,Female,Loyal Customer,51,Business travel,Business,1809,4,4,4,4,1,1,3,4,4,5,5,3,4,3,19,15.0,satisfied +97546,40572,Male,Loyal Customer,36,Business travel,Eco,216,4,5,5,5,4,4,4,4,5,5,2,2,2,4,0,0.0,satisfied +97547,47971,Female,Loyal Customer,60,Personal Travel,Eco,315,4,3,2,2,5,3,1,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +97548,56313,Male,Loyal Customer,56,Personal Travel,Business,200,3,4,3,4,3,1,1,1,5,4,1,1,4,1,328,337.0,neutral or dissatisfied +97549,44361,Female,Loyal Customer,45,Business travel,Eco,196,5,2,2,2,2,3,4,5,5,5,5,2,5,1,0,0.0,satisfied +97550,106604,Male,disloyal Customer,62,Business travel,Eco,589,1,1,1,3,4,1,4,4,2,2,3,4,4,4,0,0.0,neutral or dissatisfied +97551,76653,Female,Loyal Customer,14,Personal Travel,Eco,547,2,4,2,1,1,2,2,1,2,2,1,5,2,1,39,38.0,neutral or dissatisfied +97552,46419,Female,Loyal Customer,45,Business travel,Business,458,2,2,2,2,3,2,4,4,4,4,4,1,4,4,2,0.0,satisfied +97553,103608,Male,Loyal Customer,7,Personal Travel,Business,405,3,4,3,3,1,3,1,1,5,4,4,4,4,1,119,118.0,neutral or dissatisfied +97554,93154,Male,disloyal Customer,34,Business travel,Eco,1243,1,1,1,1,5,1,5,5,1,5,1,2,3,5,53,67.0,neutral or dissatisfied +97555,75872,Male,Loyal Customer,42,Business travel,Business,1972,3,2,3,3,3,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +97556,31656,Female,disloyal Customer,18,Business travel,Eco,846,3,3,3,5,1,3,1,1,2,4,4,1,2,1,4,0.0,neutral or dissatisfied +97557,33871,Male,Loyal Customer,46,Business travel,Business,2847,1,5,1,1,4,5,4,3,3,3,3,3,3,5,28,19.0,satisfied +97558,119022,Male,Loyal Customer,39,Business travel,Business,1460,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,14.0,satisfied +97559,125895,Male,Loyal Customer,52,Personal Travel,Eco,993,3,5,3,3,3,3,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +97560,14873,Female,disloyal Customer,19,Business travel,Eco,296,3,4,3,3,3,5,5,2,5,3,4,5,3,5,264,253.0,neutral or dissatisfied +97561,97518,Male,Loyal Customer,43,Business travel,Business,3930,4,4,4,4,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +97562,87870,Male,Loyal Customer,35,Business travel,Business,2173,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +97563,38895,Male,Loyal Customer,40,Business travel,Eco,410,4,3,3,3,4,4,4,4,5,5,3,3,4,4,0,5.0,satisfied +97564,56823,Male,Loyal Customer,45,Personal Travel,Eco,1605,3,5,3,1,3,3,3,3,4,5,5,5,5,3,11,0.0,neutral or dissatisfied +97565,43019,Male,Loyal Customer,55,Business travel,Eco,259,3,2,3,2,3,3,3,3,4,5,3,2,4,3,0,0.0,neutral or dissatisfied +97566,122210,Male,Loyal Customer,37,Business travel,Business,2907,3,1,1,1,1,3,3,3,3,3,3,2,3,1,3,0.0,neutral or dissatisfied +97567,54884,Female,Loyal Customer,43,Personal Travel,Eco,862,3,4,4,3,2,5,5,5,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +97568,2510,Female,Loyal Customer,48,Business travel,Business,181,2,5,5,5,2,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +97569,7662,Male,Loyal Customer,51,Business travel,Business,3923,2,4,2,4,2,4,4,2,2,2,2,1,2,4,35,63.0,neutral or dissatisfied +97570,107482,Male,Loyal Customer,54,Business travel,Business,711,2,2,2,2,4,4,5,4,4,4,4,5,4,4,15,0.0,satisfied +97571,94915,Male,disloyal Customer,37,Business travel,Eco,239,3,3,3,4,1,3,1,1,4,4,4,4,3,1,10,20.0,neutral or dissatisfied +97572,85533,Female,Loyal Customer,33,Business travel,Business,3372,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +97573,117852,Male,Loyal Customer,50,Personal Travel,Eco,2133,2,2,3,4,5,3,5,5,4,4,3,4,4,5,8,1.0,neutral or dissatisfied +97574,88559,Male,Loyal Customer,10,Personal Travel,Eco,406,3,5,3,2,2,3,2,2,4,4,4,3,4,2,8,8.0,neutral or dissatisfied +97575,11771,Male,Loyal Customer,9,Personal Travel,Eco,429,1,1,1,3,3,1,3,3,4,4,2,3,3,3,0,0.0,neutral or dissatisfied +97576,42767,Male,Loyal Customer,55,Business travel,Business,493,2,2,2,2,5,5,5,5,5,5,5,3,5,1,0,0.0,satisfied +97577,20992,Female,Loyal Customer,26,Business travel,Eco Plus,689,4,1,1,1,4,4,4,4,1,1,1,5,3,4,0,0.0,satisfied +97578,116895,Male,Loyal Customer,41,Business travel,Business,3185,0,0,0,2,3,4,4,5,5,5,5,4,5,5,10,5.0,satisfied +97579,67795,Male,Loyal Customer,7,Business travel,Business,1438,5,5,5,5,2,2,2,2,3,3,4,4,4,2,0,0.0,satisfied +97580,82032,Female,Loyal Customer,19,Personal Travel,Eco,1535,1,4,1,4,5,1,1,5,2,5,4,1,4,5,55,42.0,neutral or dissatisfied +97581,62828,Female,Loyal Customer,46,Personal Travel,Eco,2367,1,4,1,2,4,4,4,2,2,1,2,5,2,5,1,0.0,neutral or dissatisfied +97582,112316,Male,Loyal Customer,58,Business travel,Business,2232,1,1,1,1,5,4,5,4,4,4,4,4,4,3,6,3.0,satisfied +97583,6422,Male,Loyal Customer,28,Personal Travel,Eco,315,2,1,2,1,3,2,3,3,1,3,2,3,2,3,0,0.0,neutral or dissatisfied +97584,99432,Male,Loyal Customer,29,Personal Travel,Eco,406,3,1,2,3,2,2,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +97585,104343,Male,Loyal Customer,18,Personal Travel,Eco,409,1,4,2,2,5,2,5,5,5,2,4,4,4,5,10,9.0,neutral or dissatisfied +97586,83328,Female,Loyal Customer,16,Business travel,Business,2105,2,2,2,2,4,4,4,4,5,5,3,3,4,4,4,0.0,satisfied +97587,81178,Male,Loyal Customer,42,Business travel,Business,2114,4,3,4,4,4,4,5,4,4,4,4,3,4,5,0,17.0,satisfied +97588,100725,Female,Loyal Customer,45,Business travel,Business,1816,0,0,0,1,5,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +97589,43775,Male,Loyal Customer,63,Personal Travel,Eco,481,1,4,3,1,5,3,5,5,4,5,1,2,1,5,0,5.0,neutral or dissatisfied +97590,80603,Female,disloyal Customer,25,Business travel,Business,236,2,5,2,3,3,2,3,3,5,2,4,5,4,3,0,3.0,neutral or dissatisfied +97591,104316,Female,Loyal Customer,40,Business travel,Business,2782,4,4,4,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +97592,67497,Male,Loyal Customer,59,Personal Travel,Eco Plus,769,3,5,3,5,2,3,2,2,5,2,5,4,4,2,12,2.0,neutral or dissatisfied +97593,116672,Female,disloyal Customer,23,Business travel,Eco,337,4,2,4,3,1,4,1,1,3,5,4,4,4,1,14,12.0,neutral or dissatisfied +97594,119465,Female,Loyal Customer,47,Business travel,Business,2327,4,4,4,4,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +97595,74392,Male,Loyal Customer,49,Business travel,Business,3845,1,1,1,1,5,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +97596,102339,Male,Loyal Customer,53,Business travel,Business,258,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +97597,57403,Male,Loyal Customer,44,Business travel,Business,2757,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +97598,13850,Male,Loyal Customer,65,Personal Travel,Eco Plus,602,4,2,4,4,4,4,4,4,4,3,4,4,4,4,5,1.0,neutral or dissatisfied +97599,68011,Male,disloyal Customer,20,Business travel,Business,280,5,0,5,1,2,5,2,2,3,4,5,5,5,2,0,0.0,satisfied +97600,106196,Male,Loyal Customer,40,Personal Travel,Eco,302,3,1,3,3,2,3,1,2,3,4,3,4,4,2,1,0.0,neutral or dissatisfied +97601,43193,Female,Loyal Customer,23,Business travel,Business,651,4,4,4,4,4,4,4,4,4,4,4,2,1,4,0,0.0,satisfied +97602,84572,Female,disloyal Customer,14,Business travel,Eco,967,1,1,1,4,3,1,3,3,4,5,2,3,4,3,0,0.0,neutral or dissatisfied +97603,127251,Female,Loyal Customer,42,Business travel,Business,1566,4,4,4,4,4,4,5,3,3,4,3,4,3,5,0,3.0,satisfied +97604,109740,Female,Loyal Customer,41,Personal Travel,Eco,680,4,4,3,2,4,3,4,4,3,4,4,4,5,4,0,0.0,neutral or dissatisfied +97605,65494,Male,Loyal Customer,24,Personal Travel,Eco,1303,3,3,3,4,4,3,4,4,1,4,3,1,3,4,10,0.0,neutral or dissatisfied +97606,88,Female,Loyal Customer,52,Personal Travel,Eco,67,2,5,2,1,3,4,4,1,1,2,1,5,1,4,2,0.0,neutral or dissatisfied +97607,84854,Male,Loyal Customer,44,Business travel,Eco,147,2,2,2,2,3,2,3,3,3,1,2,1,2,3,0,0.0,satisfied +97608,65068,Male,Loyal Customer,18,Personal Travel,Eco,469,1,4,1,3,3,1,3,3,5,4,4,5,4,3,0,2.0,neutral or dissatisfied +97609,41043,Male,disloyal Customer,21,Business travel,Business,1086,3,2,3,4,2,3,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +97610,80044,Male,Loyal Customer,8,Personal Travel,Eco,1010,4,4,4,1,4,4,4,4,5,2,1,5,5,4,0,0.0,neutral or dissatisfied +97611,101053,Male,Loyal Customer,37,Business travel,Business,368,3,4,4,4,4,4,4,3,3,3,3,4,3,2,44,36.0,neutral or dissatisfied +97612,65402,Female,Loyal Customer,55,Personal Travel,Eco,432,2,4,3,1,2,5,4,2,2,3,2,4,2,3,3,5.0,neutral or dissatisfied +97613,127277,Female,Loyal Customer,35,Personal Travel,Eco,1020,1,0,2,5,4,2,1,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +97614,87012,Female,Loyal Customer,15,Personal Travel,Eco,907,1,4,1,4,2,1,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +97615,124753,Female,Loyal Customer,35,Personal Travel,Business,280,3,4,3,1,2,5,4,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +97616,70976,Male,Loyal Customer,41,Business travel,Business,978,2,2,2,2,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +97617,88587,Male,Loyal Customer,13,Personal Travel,Eco,404,3,5,3,3,2,3,2,2,4,3,2,4,4,2,4,0.0,neutral or dissatisfied +97618,99304,Female,Loyal Customer,58,Business travel,Business,2285,1,1,1,1,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +97619,16861,Female,disloyal Customer,23,Business travel,Eco,746,2,2,2,2,2,2,2,2,2,3,4,4,2,2,0,25.0,neutral or dissatisfied +97620,8553,Male,Loyal Customer,44,Business travel,Business,2784,1,1,4,1,4,5,4,4,4,4,5,5,4,5,4,6.0,satisfied +97621,13363,Female,Loyal Customer,39,Personal Travel,Eco,946,0,3,0,1,2,0,1,2,5,2,1,2,2,2,0,0.0,satisfied +97622,80767,Male,Loyal Customer,24,Personal Travel,Eco,629,1,4,1,3,3,1,3,3,3,5,5,4,5,3,0,1.0,neutral or dissatisfied +97623,24264,Male,Loyal Customer,46,Personal Travel,Eco,147,3,4,3,3,4,3,4,4,4,3,4,4,4,4,9,4.0,neutral or dissatisfied +97624,5334,Female,Loyal Customer,42,Business travel,Business,2616,3,3,3,3,2,5,4,2,2,3,2,3,2,4,60,38.0,satisfied +97625,47296,Female,Loyal Customer,36,Business travel,Eco,541,5,2,2,2,5,4,5,5,1,4,5,4,3,5,3,0.0,satisfied +97626,15530,Male,Loyal Customer,60,Personal Travel,Eco Plus,399,1,5,1,5,1,1,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +97627,21192,Female,disloyal Customer,33,Business travel,Eco,192,2,5,2,3,5,2,5,5,3,2,5,2,5,5,0,0.0,neutral or dissatisfied +97628,36345,Male,Loyal Customer,49,Personal Travel,Eco,187,3,4,3,4,3,3,3,3,3,4,5,3,4,3,0,9.0,neutral or dissatisfied +97629,101009,Male,Loyal Customer,36,Business travel,Eco,564,3,1,1,1,3,3,3,3,3,5,2,3,2,3,6,13.0,neutral or dissatisfied +97630,76310,Male,Loyal Customer,28,Business travel,Business,2182,3,3,4,3,4,4,4,4,4,2,3,5,5,4,12,17.0,satisfied +97631,15156,Male,Loyal Customer,57,Personal Travel,Eco,1042,3,4,3,3,1,3,1,1,3,4,5,4,5,1,6,0.0,neutral or dissatisfied +97632,20027,Male,Loyal Customer,54,Business travel,Eco,566,5,4,1,4,5,5,5,5,4,5,3,4,3,5,1,6.0,satisfied +97633,122362,Female,Loyal Customer,58,Business travel,Business,2186,3,3,5,3,3,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +97634,90626,Female,Loyal Customer,56,Business travel,Business,366,1,1,1,1,2,5,5,4,4,4,4,5,4,3,34,32.0,satisfied +97635,41957,Male,Loyal Customer,25,Business travel,Business,1984,2,5,5,5,2,2,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +97636,8375,Male,Loyal Customer,38,Business travel,Business,3403,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +97637,115196,Female,disloyal Customer,48,Business travel,Business,325,4,4,4,1,5,4,5,5,3,3,4,3,4,5,26,14.0,neutral or dissatisfied +97638,49441,Male,Loyal Customer,56,Business travel,Eco,207,5,4,4,4,5,5,5,5,4,3,1,1,3,5,0,0.0,satisfied +97639,69998,Male,Loyal Customer,46,Personal Travel,Eco,236,3,4,3,3,4,3,4,4,5,5,4,3,4,4,0,3.0,neutral or dissatisfied +97640,110896,Female,disloyal Customer,21,Business travel,Business,404,3,1,3,3,3,3,3,3,4,5,2,3,3,3,13,11.0,neutral or dissatisfied +97641,51126,Female,Loyal Customer,8,Personal Travel,Eco,421,3,3,4,2,3,4,3,3,1,4,2,1,3,3,2,0.0,neutral or dissatisfied +97642,44752,Female,Loyal Customer,32,Personal Travel,Eco,589,2,4,2,2,3,2,3,3,4,2,2,5,5,3,70,69.0,neutral or dissatisfied +97643,23196,Male,Loyal Customer,30,Business travel,Eco Plus,223,5,4,4,4,5,5,5,5,5,4,3,1,2,5,0,1.0,satisfied +97644,102751,Female,disloyal Customer,39,Business travel,Business,255,2,2,2,4,2,2,2,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +97645,111787,Male,Loyal Customer,60,Personal Travel,Eco,1620,1,5,1,2,3,1,3,3,4,4,4,3,4,3,6,8.0,neutral or dissatisfied +97646,84047,Male,Loyal Customer,52,Business travel,Business,2394,5,5,5,5,4,4,4,3,4,5,5,4,5,4,189,185.0,satisfied +97647,33778,Female,Loyal Customer,51,Business travel,Eco,588,5,5,5,5,5,5,5,5,5,5,5,1,5,5,0,0.0,satisfied +97648,7142,Female,Loyal Customer,39,Business travel,Business,139,2,2,2,2,3,5,4,4,4,4,4,5,4,3,61,70.0,satisfied +97649,16739,Female,Loyal Customer,15,Personal Travel,Eco,1167,3,4,2,4,2,2,2,2,5,2,3,4,4,2,24,22.0,neutral or dissatisfied +97650,86294,Female,Loyal Customer,37,Personal Travel,Eco,356,2,4,2,3,3,2,3,3,3,5,4,5,5,3,22,24.0,neutral or dissatisfied +97651,50422,Male,disloyal Customer,39,Business travel,Business,266,2,3,3,1,1,3,1,1,4,2,2,3,5,1,6,0.0,neutral or dissatisfied +97652,5104,Female,Loyal Customer,18,Personal Travel,Eco,223,4,4,4,3,4,4,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +97653,53296,Female,Loyal Customer,35,Business travel,Eco,758,4,4,4,4,4,4,4,4,3,3,4,2,3,4,0,0.0,satisfied +97654,92670,Male,disloyal Customer,25,Business travel,Business,507,4,0,3,3,4,3,4,4,3,4,5,3,5,4,1,0.0,neutral or dissatisfied +97655,93580,Male,disloyal Customer,25,Business travel,Eco,159,1,4,1,4,1,5,5,3,2,3,4,5,4,5,411,425.0,neutral or dissatisfied +97656,11957,Female,Loyal Customer,57,Business travel,Business,781,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +97657,78014,Male,Loyal Customer,37,Business travel,Business,1636,4,2,3,2,5,4,3,1,1,1,4,4,1,4,0,0.0,neutral or dissatisfied +97658,54555,Female,Loyal Customer,36,Personal Travel,Eco,925,3,4,3,3,5,3,5,5,3,2,1,4,2,5,0,0.0,neutral or dissatisfied +97659,24529,Female,Loyal Customer,15,Personal Travel,Eco,892,3,5,3,3,4,3,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +97660,43671,Male,disloyal Customer,30,Business travel,Eco,695,3,3,3,3,3,1,1,3,3,4,4,1,3,1,155,141.0,neutral or dissatisfied +97661,46578,Female,disloyal Customer,37,Business travel,Eco,125,3,1,2,3,4,2,4,4,3,3,2,3,2,4,0,0.0,neutral or dissatisfied +97662,55639,Female,Loyal Customer,39,Business travel,Business,563,4,4,4,4,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +97663,66634,Female,Loyal Customer,35,Business travel,Business,2286,1,1,1,1,5,5,4,5,5,5,5,4,5,3,24,17.0,satisfied +97664,76315,Male,Loyal Customer,39,Business travel,Business,2182,1,1,1,1,3,1,2,1,1,1,1,3,1,1,3,5.0,neutral or dissatisfied +97665,2091,Female,Loyal Customer,20,Personal Travel,Eco,785,1,5,1,4,1,1,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +97666,94704,Male,Loyal Customer,54,Business travel,Eco,248,3,2,4,2,3,3,3,3,1,1,3,4,3,3,25,15.0,neutral or dissatisfied +97667,47444,Female,Loyal Customer,42,Business travel,Eco,226,1,4,4,4,1,3,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +97668,13574,Female,Loyal Customer,39,Personal Travel,Eco,152,3,5,3,2,2,3,1,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +97669,60222,Male,Loyal Customer,23,Business travel,Business,1703,2,2,3,2,4,4,4,4,3,2,5,5,5,4,22,4.0,satisfied +97670,15470,Female,Loyal Customer,26,Personal Travel,Eco,164,4,2,4,4,4,4,4,4,3,5,3,2,3,4,32,46.0,neutral or dissatisfied +97671,3548,Female,Loyal Customer,57,Business travel,Business,1826,0,0,0,4,1,1,1,4,4,5,4,1,4,1,44,150.0,satisfied +97672,11912,Male,Loyal Customer,37,Business travel,Business,2999,2,5,5,5,3,4,4,4,4,4,2,2,4,3,0,0.0,neutral or dissatisfied +97673,8749,Female,disloyal Customer,23,Business travel,Eco,1147,3,3,3,1,1,3,1,1,3,5,4,5,5,1,22,0.0,neutral or dissatisfied +97674,45831,Male,Loyal Customer,44,Personal Travel,Eco,411,2,1,2,2,3,2,3,3,1,4,1,4,2,3,0,45.0,neutral or dissatisfied +97675,30671,Male,Loyal Customer,28,Personal Travel,Eco Plus,770,5,2,5,2,3,5,3,3,4,2,2,4,3,3,0,0.0,satisfied +97676,40959,Male,Loyal Customer,44,Business travel,Business,601,5,5,5,5,2,4,4,5,5,5,5,2,5,2,0,0.0,satisfied +97677,129580,Male,Loyal Customer,31,Business travel,Business,2691,4,4,4,4,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +97678,11114,Male,Loyal Customer,54,Personal Travel,Eco,216,3,4,3,1,2,3,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +97679,118504,Female,Loyal Customer,57,Business travel,Business,621,2,2,1,2,3,5,5,5,5,5,5,4,5,3,1,2.0,satisfied +97680,26987,Female,Loyal Customer,50,Business travel,Business,2535,4,4,4,4,2,1,4,5,5,5,5,2,5,1,7,6.0,satisfied +97681,121247,Male,disloyal Customer,23,Business travel,Eco,2075,2,2,2,3,1,2,1,1,2,2,4,4,4,1,0,0.0,neutral or dissatisfied +97682,56029,Female,Loyal Customer,48,Business travel,Business,2586,4,4,4,4,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +97683,93274,Male,Loyal Customer,28,Business travel,Business,867,1,2,2,2,1,1,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +97684,84030,Female,Loyal Customer,45,Personal Travel,Eco Plus,321,2,4,2,4,2,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +97685,116306,Male,Loyal Customer,27,Personal Travel,Eco,404,3,5,3,1,1,3,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +97686,128728,Female,Loyal Customer,51,Personal Travel,Eco,1504,4,3,4,4,5,3,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +97687,92328,Male,Loyal Customer,57,Business travel,Business,2615,3,3,3,3,5,5,5,5,4,5,5,5,3,5,0,3.0,satisfied +97688,106116,Female,Loyal Customer,41,Business travel,Business,3226,4,4,4,4,5,4,4,4,4,4,4,3,4,5,26,16.0,satisfied +97689,45368,Male,Loyal Customer,45,Personal Travel,Eco,188,4,5,4,4,4,2,2,5,5,4,5,2,4,2,221,252.0,neutral or dissatisfied +97690,40972,Female,Loyal Customer,24,Personal Travel,Eco,601,3,2,3,2,4,3,4,4,4,1,3,3,2,4,0,0.0,neutral or dissatisfied +97691,39618,Female,Loyal Customer,58,Personal Travel,Eco,954,3,5,3,3,4,1,5,3,3,3,3,4,3,3,29,37.0,neutral or dissatisfied +97692,7547,Female,Loyal Customer,50,Business travel,Business,1725,1,1,3,1,3,4,4,4,4,4,4,3,4,5,0,48.0,satisfied +97693,96551,Female,Loyal Customer,31,Business travel,Eco Plus,436,3,1,1,1,3,3,3,3,3,5,3,3,4,3,54,44.0,neutral or dissatisfied +97694,11094,Male,Loyal Customer,67,Personal Travel,Eco,295,2,5,2,3,5,2,5,5,4,4,5,2,4,5,8,0.0,neutral or dissatisfied +97695,82313,Male,Loyal Customer,60,Business travel,Business,3879,2,5,5,5,3,2,1,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +97696,80721,Female,Loyal Customer,41,Personal Travel,Eco,1156,2,5,2,5,3,2,3,3,5,4,4,3,5,3,58,41.0,neutral or dissatisfied +97697,41298,Female,Loyal Customer,7,Personal Travel,Eco,844,3,4,3,3,4,3,2,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +97698,38735,Female,Loyal Customer,48,Business travel,Eco,354,4,5,5,5,1,2,2,4,4,4,4,4,4,2,0,0.0,satisfied +97699,70628,Male,Loyal Customer,55,Personal Travel,Eco,1217,3,0,3,3,3,2,3,1,3,2,3,3,4,3,127,145.0,neutral or dissatisfied +97700,123121,Female,disloyal Customer,9,Business travel,Eco,590,1,2,2,3,2,2,2,2,2,4,3,2,4,2,11,47.0,neutral or dissatisfied +97701,93788,Female,Loyal Customer,8,Business travel,Business,1259,2,3,5,3,2,2,2,2,4,2,3,4,4,2,17,18.0,neutral or dissatisfied +97702,93922,Male,Loyal Customer,47,Business travel,Business,3464,4,4,4,4,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +97703,1177,Female,Loyal Customer,38,Personal Travel,Eco,229,3,5,3,2,1,3,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +97704,37925,Female,Loyal Customer,47,Personal Travel,Eco,1065,1,5,1,1,2,5,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +97705,10812,Female,Loyal Customer,49,Business travel,Business,3403,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +97706,88712,Female,Loyal Customer,66,Personal Travel,Eco,515,1,4,1,3,3,5,4,4,4,1,4,4,4,5,41,53.0,neutral or dissatisfied +97707,80249,Male,Loyal Customer,70,Personal Travel,Eco,1269,1,1,1,2,1,1,1,1,3,1,1,1,2,1,0,0.0,neutral or dissatisfied +97708,40117,Female,disloyal Customer,22,Business travel,Eco,200,0,5,0,5,4,0,5,4,2,5,5,1,1,4,0,0.0,satisfied +97709,11808,Male,Loyal Customer,21,Personal Travel,Eco Plus,429,2,3,2,3,2,2,2,2,2,1,1,3,4,2,0,11.0,neutral or dissatisfied +97710,101559,Female,disloyal Customer,61,Business travel,Business,345,1,0,0,3,3,1,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +97711,14190,Female,Loyal Customer,59,Business travel,Eco,692,5,1,1,1,5,2,3,5,5,5,5,5,5,5,4,17.0,satisfied +97712,68834,Male,disloyal Customer,31,Business travel,Business,1061,2,1,1,4,3,1,3,3,1,4,4,4,4,3,39,37.0,neutral or dissatisfied +97713,76740,Female,Loyal Customer,59,Business travel,Business,205,4,4,4,4,5,4,4,5,5,5,4,5,5,4,0,10.0,satisfied +97714,2086,Male,Loyal Customer,62,Personal Travel,Eco,812,4,3,4,3,4,4,4,4,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +97715,71287,Male,Loyal Customer,10,Business travel,Business,733,4,4,4,4,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +97716,42435,Female,Loyal Customer,33,Personal Travel,Eco,1119,3,5,3,3,4,3,5,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +97717,80392,Female,Loyal Customer,67,Personal Travel,Eco,368,2,4,2,3,3,3,3,5,5,2,2,2,5,3,0,3.0,neutral or dissatisfied +97718,94202,Male,Loyal Customer,46,Business travel,Business,148,0,5,0,4,4,4,5,5,5,5,4,4,5,5,0,1.0,satisfied +97719,27132,Female,Loyal Customer,48,Business travel,Eco,2640,5,1,1,1,5,5,5,5,5,4,3,5,3,5,0,43.0,satisfied +97720,2531,Female,Loyal Customer,56,Business travel,Business,227,4,4,4,4,2,5,5,3,3,4,3,5,3,3,2,1.0,satisfied +97721,39787,Female,disloyal Customer,26,Business travel,Business,184,3,3,3,3,2,3,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +97722,3361,Female,Loyal Customer,34,Business travel,Business,315,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,8.0,satisfied +97723,78631,Male,Loyal Customer,47,Personal Travel,Eco,1426,3,3,3,2,2,3,2,2,1,3,3,3,2,2,0,0.0,neutral or dissatisfied +97724,56,Female,Loyal Customer,56,Business travel,Business,2485,2,2,2,2,5,5,4,4,4,5,5,5,4,3,0,0.0,satisfied +97725,63982,Male,Loyal Customer,45,Personal Travel,Eco Plus,1158,2,3,2,2,5,2,4,5,4,3,1,1,2,5,2,0.0,neutral or dissatisfied +97726,100714,Male,Loyal Customer,48,Business travel,Business,328,0,0,0,4,2,5,5,4,4,4,4,3,4,3,1,5.0,satisfied +97727,47019,Female,Loyal Customer,31,Personal Travel,Business,602,5,5,5,1,5,5,4,5,5,4,5,5,4,5,0,7.0,satisfied +97728,21066,Female,disloyal Customer,20,Business travel,Eco,227,4,0,4,4,4,4,1,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +97729,36183,Male,Loyal Customer,49,Business travel,Eco Plus,1674,2,2,1,2,2,2,2,2,1,5,2,4,3,2,0,0.0,neutral or dissatisfied +97730,59145,Male,Loyal Customer,31,Personal Travel,Eco,1744,4,4,4,3,3,4,5,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +97731,102732,Female,Loyal Customer,8,Personal Travel,Eco,365,1,5,1,4,5,1,5,5,4,3,5,4,5,5,17,7.0,neutral or dissatisfied +97732,108959,Female,Loyal Customer,60,Business travel,Business,2059,3,3,4,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +97733,22132,Female,Loyal Customer,53,Business travel,Eco,566,2,2,2,2,4,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +97734,25840,Male,disloyal Customer,36,Business travel,Eco,484,1,4,1,3,4,1,4,4,2,3,4,3,3,4,0,0.0,neutral or dissatisfied +97735,36228,Male,Loyal Customer,40,Personal Travel,Eco,280,1,3,1,4,4,1,4,4,1,1,4,1,3,4,0,0.0,neutral or dissatisfied +97736,6939,Female,Loyal Customer,45,Business travel,Business,588,4,4,4,4,2,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +97737,123030,Female,disloyal Customer,37,Business travel,Business,468,4,4,4,3,1,4,1,1,5,4,5,3,5,1,2,9.0,satisfied +97738,92039,Male,disloyal Customer,22,Business travel,Eco,1517,3,3,3,4,2,3,3,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +97739,57512,Female,Loyal Customer,53,Business travel,Business,2372,1,1,1,1,2,4,5,4,4,4,5,2,4,4,33,52.0,satisfied +97740,70653,Male,Loyal Customer,35,Business travel,Business,946,2,3,3,3,1,3,4,2,2,2,2,4,2,3,11,0.0,neutral or dissatisfied +97741,108514,Female,disloyal Customer,27,Business travel,Eco,519,3,1,3,3,2,3,2,2,4,3,4,1,4,2,1,2.0,neutral or dissatisfied +97742,100744,Male,Loyal Customer,30,Personal Travel,Eco,328,0,0,0,3,2,0,2,2,5,4,5,5,4,2,0,0.0,satisfied +97743,71775,Male,Loyal Customer,49,Business travel,Business,1726,1,1,1,1,2,3,5,5,5,5,5,3,5,4,2,5.0,satisfied +97744,122059,Female,Loyal Customer,53,Business travel,Business,130,1,1,1,1,2,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +97745,116068,Male,Loyal Customer,10,Personal Travel,Eco,390,3,1,3,3,2,3,3,2,3,1,4,2,3,2,21,19.0,neutral or dissatisfied +97746,75864,Female,disloyal Customer,24,Business travel,Business,1440,4,0,4,2,1,4,1,1,5,4,4,3,4,1,0,0.0,satisfied +97747,27283,Female,Loyal Customer,64,Personal Travel,Business,679,3,5,3,1,3,4,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +97748,46070,Female,Loyal Customer,26,Business travel,Business,3344,3,3,3,3,4,4,4,4,5,5,3,4,2,4,0,0.0,satisfied +97749,94409,Female,Loyal Customer,69,Business travel,Business,1930,2,5,5,5,5,3,3,2,2,2,2,1,2,2,4,8.0,neutral or dissatisfied +97750,34905,Male,Loyal Customer,56,Business travel,Eco,395,4,3,3,3,4,4,4,4,4,2,4,5,2,4,0,0.0,satisfied +97751,7621,Male,disloyal Customer,23,Business travel,Business,641,4,0,4,2,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +97752,112522,Male,Loyal Customer,43,Personal Travel,Eco,967,3,5,3,3,2,3,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +97753,22231,Female,Loyal Customer,42,Business travel,Business,143,5,5,5,5,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +97754,73440,Male,Loyal Customer,11,Personal Travel,Eco,1182,4,4,4,4,5,4,5,5,1,1,2,2,4,5,0,0.0,neutral or dissatisfied +97755,124900,Male,Loyal Customer,41,Business travel,Business,2611,5,5,5,5,5,4,5,4,4,4,4,3,4,5,3,0.0,satisfied +97756,57817,Female,disloyal Customer,40,Business travel,Business,622,1,2,2,4,3,2,3,3,5,3,4,4,5,3,1,7.0,neutral or dissatisfied +97757,64937,Female,disloyal Customer,24,Business travel,Eco,551,3,2,2,3,3,2,1,3,4,3,4,4,4,3,23,16.0,neutral or dissatisfied +97758,19062,Female,Loyal Customer,48,Business travel,Business,3959,5,5,5,5,1,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +97759,53989,Male,Loyal Customer,54,Business travel,Eco,1825,4,1,5,5,4,4,4,4,2,1,4,2,2,4,0,0.0,satisfied +97760,74888,Female,Loyal Customer,43,Business travel,Business,1086,5,5,5,5,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +97761,40714,Male,Loyal Customer,39,Business travel,Business,2828,1,1,1,1,5,2,4,4,4,3,4,1,4,1,75,58.0,satisfied +97762,55731,Male,Loyal Customer,50,Business travel,Business,2052,4,3,4,4,2,4,4,4,4,5,4,3,4,3,4,11.0,satisfied +97763,11461,Male,Loyal Customer,49,Business travel,Eco Plus,201,3,2,3,2,3,3,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +97764,53167,Male,Loyal Customer,25,Business travel,Business,3393,3,3,3,3,5,5,5,5,5,3,2,3,5,5,3,0.0,satisfied +97765,16011,Female,Loyal Customer,22,Business travel,Business,380,3,1,3,1,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +97766,129111,Female,Loyal Customer,9,Personal Travel,Eco,2342,0,4,0,4,2,0,2,2,4,5,3,5,3,2,0,0.0,satisfied +97767,129874,Female,Loyal Customer,28,Personal Travel,Eco Plus,337,4,2,4,4,3,4,3,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +97768,128225,Male,Loyal Customer,52,Business travel,Eco,602,2,4,4,4,2,2,2,2,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +97769,39199,Female,Loyal Customer,68,Personal Travel,Eco,318,5,5,3,4,3,1,3,5,5,3,5,3,5,3,0,0.0,satisfied +97770,63171,Female,Loyal Customer,47,Business travel,Business,447,5,5,5,5,4,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +97771,29911,Female,Loyal Customer,43,Business travel,Business,2975,3,3,3,3,4,1,4,4,4,4,4,4,4,4,22,32.0,satisfied +97772,79921,Male,disloyal Customer,21,Business travel,Eco,950,2,3,3,5,3,3,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +97773,504,Male,Loyal Customer,39,Business travel,Business,2068,1,1,1,1,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +97774,69780,Male,Loyal Customer,30,Business travel,Business,1345,2,2,2,2,3,3,3,3,3,5,4,4,4,3,0,0.0,satisfied +97775,16159,Male,Loyal Customer,51,Business travel,Eco,199,2,2,2,2,2,2,2,2,5,1,3,3,2,2,16,21.0,satisfied +97776,111144,Female,Loyal Customer,44,Business travel,Business,3679,5,3,5,5,2,2,3,4,4,4,4,3,4,1,17,5.0,satisfied +97777,112969,Female,Loyal Customer,45,Business travel,Business,3137,4,4,4,4,2,5,5,5,5,5,5,4,5,3,9,0.0,satisfied +97778,3489,Male,Loyal Customer,50,Business travel,Business,3018,5,5,5,5,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +97779,30221,Male,Loyal Customer,48,Business travel,Business,1109,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,13.0,satisfied +97780,6244,Female,Loyal Customer,44,Personal Travel,Eco,594,2,1,2,2,2,1,2,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +97781,127802,Female,Loyal Customer,49,Business travel,Business,2328,1,1,1,1,3,5,4,4,4,4,4,3,4,4,47,40.0,satisfied +97782,26219,Male,Loyal Customer,23,Personal Travel,Eco,270,4,3,0,4,4,0,4,4,4,4,4,1,3,4,9,0.0,neutral or dissatisfied +97783,42450,Male,Loyal Customer,41,Business travel,Eco,866,2,1,1,1,1,2,1,1,2,5,3,1,4,1,0,9.0,neutral or dissatisfied +97784,90490,Male,Loyal Customer,48,Business travel,Business,3895,2,2,2,2,3,4,4,5,5,5,5,3,5,4,30,27.0,satisfied +97785,93286,Male,Loyal Customer,11,Personal Travel,Eco,806,3,4,3,3,2,3,2,2,3,2,3,1,3,2,3,3.0,neutral or dissatisfied +97786,125215,Male,Loyal Customer,9,Personal Travel,Eco,651,1,1,1,4,3,1,3,3,3,5,2,1,4,3,0,0.0,neutral or dissatisfied +97787,67796,Female,disloyal Customer,13,Business travel,Business,1205,0,5,0,2,3,0,3,3,3,2,4,4,4,3,9,1.0,satisfied +97788,93974,Male,Loyal Customer,49,Business travel,Eco,1218,2,4,4,4,2,2,2,2,1,3,4,2,4,2,1,0.0,neutral or dissatisfied +97789,61208,Male,disloyal Customer,48,Business travel,Business,862,4,3,3,5,3,4,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +97790,97701,Female,Loyal Customer,52,Business travel,Business,3536,3,1,1,1,4,4,4,3,3,3,3,4,3,2,0,13.0,neutral or dissatisfied +97791,98762,Female,Loyal Customer,54,Business travel,Business,314,4,1,1,1,3,3,3,4,4,4,4,3,4,1,2,0.0,neutral or dissatisfied +97792,115083,Male,Loyal Customer,36,Business travel,Eco,480,3,5,5,5,3,3,3,3,1,3,3,1,3,3,0,0.0,neutral or dissatisfied +97793,78191,Female,Loyal Customer,43,Business travel,Business,3367,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +97794,71295,Male,Loyal Customer,68,Personal Travel,Eco Plus,733,1,4,1,3,4,1,4,4,2,5,4,1,3,4,0,0.0,neutral or dissatisfied +97795,59948,Male,disloyal Customer,22,Business travel,Business,937,4,0,4,2,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +97796,52946,Male,Loyal Customer,58,Business travel,Eco,1448,3,5,3,5,3,3,3,3,3,2,4,1,4,3,0,0.0,neutral or dissatisfied +97797,96008,Male,disloyal Customer,26,Business travel,Business,1069,1,1,1,4,2,1,3,2,4,3,3,3,3,2,0,2.0,neutral or dissatisfied +97798,112063,Male,Loyal Customer,41,Personal Travel,Eco,1754,2,1,3,1,3,3,3,3,2,3,1,3,2,3,125,92.0,neutral or dissatisfied +97799,17434,Male,disloyal Customer,26,Business travel,Business,351,3,1,3,3,3,3,3,3,4,1,4,2,4,3,13,8.0,neutral or dissatisfied +97800,9923,Male,Loyal Customer,45,Business travel,Business,508,5,5,5,5,5,5,5,2,2,2,2,5,2,4,0,1.0,satisfied +97801,54236,Female,Loyal Customer,56,Business travel,Eco,1222,2,5,5,5,2,2,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +97802,93657,Female,disloyal Customer,24,Business travel,Business,542,4,0,4,2,2,4,2,2,3,4,5,5,4,2,0,0.0,satisfied +97803,43146,Female,Loyal Customer,62,Personal Travel,Eco Plus,192,1,3,1,3,1,2,2,3,2,3,3,2,3,2,209,213.0,neutral or dissatisfied +97804,22982,Male,disloyal Customer,21,Business travel,Eco,817,3,3,3,1,5,3,5,5,4,1,2,1,1,5,0,0.0,neutral or dissatisfied +97805,45348,Male,Loyal Customer,25,Personal Travel,Eco,188,3,2,0,3,5,0,1,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +97806,44594,Female,disloyal Customer,23,Business travel,Eco,157,2,5,2,4,2,2,3,2,1,4,5,3,3,2,0,0.0,neutral or dissatisfied +97807,56799,Female,Loyal Customer,36,Business travel,Business,1605,4,4,4,4,2,5,4,4,4,3,4,5,4,3,5,0.0,satisfied +97808,104290,Male,Loyal Customer,40,Business travel,Business,440,1,1,1,1,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +97809,79465,Female,Loyal Customer,25,Personal Travel,Eco,1183,0,1,0,2,2,0,4,2,4,1,3,1,3,2,0,0.0,satisfied +97810,13759,Female,Loyal Customer,60,Personal Travel,Eco,401,2,4,2,3,3,2,3,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +97811,74129,Male,Loyal Customer,59,Business travel,Eco,641,2,3,3,3,2,2,2,2,1,2,4,1,3,2,15,11.0,neutral or dissatisfied +97812,44670,Female,Loyal Customer,64,Business travel,Eco,268,5,5,5,5,4,4,2,5,5,5,5,4,5,2,0,0.0,satisfied +97813,36354,Male,Loyal Customer,78,Business travel,Eco Plus,395,4,2,2,2,4,4,4,4,3,4,3,4,1,4,0,2.0,satisfied +97814,92009,Male,Loyal Customer,13,Personal Travel,Business,1535,1,2,1,3,4,1,4,4,3,1,3,3,2,4,0,6.0,neutral or dissatisfied +97815,124404,Male,Loyal Customer,7,Personal Travel,Business,1262,2,5,2,3,1,2,1,1,3,4,3,4,4,1,0,0.0,neutral or dissatisfied +97816,84051,Female,Loyal Customer,54,Business travel,Business,2870,2,2,2,2,4,5,5,5,5,5,5,5,5,3,0,9.0,satisfied +97817,14334,Female,Loyal Customer,25,Personal Travel,Eco,429,2,4,2,3,2,2,2,2,5,3,1,2,2,2,0,0.0,neutral or dissatisfied +97818,74602,Male,Loyal Customer,61,Business travel,Business,1464,1,3,3,3,5,3,4,1,1,1,1,1,1,4,5,0.0,neutral or dissatisfied +97819,43042,Female,disloyal Customer,26,Business travel,Eco,236,4,1,4,3,3,4,4,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +97820,39514,Male,disloyal Customer,57,Business travel,Eco,852,1,1,1,3,3,1,3,3,2,1,2,4,2,3,2,30.0,neutral or dissatisfied +97821,5344,Male,Loyal Customer,44,Business travel,Eco,785,3,5,5,5,3,3,3,3,1,4,3,2,3,3,32,37.0,neutral or dissatisfied +97822,7722,Male,disloyal Customer,40,Business travel,Business,859,2,2,2,1,1,2,1,1,5,3,5,3,5,1,0,,neutral or dissatisfied +97823,12867,Female,Loyal Customer,19,Personal Travel,Eco Plus,489,3,0,3,1,1,3,1,1,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +97824,14489,Female,Loyal Customer,33,Personal Travel,Eco,495,1,4,3,4,3,3,3,3,5,4,4,3,4,3,103,98.0,neutral or dissatisfied +97825,80297,Female,Loyal Customer,33,Business travel,Business,2574,4,5,5,5,5,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +97826,20050,Male,Loyal Customer,32,Business travel,Business,3447,5,5,5,5,4,4,4,4,2,4,2,3,5,4,0,0.0,satisfied +97827,31681,Male,Loyal Customer,72,Business travel,Eco,846,3,3,2,3,3,3,3,3,1,5,3,3,2,3,21,16.0,neutral or dissatisfied +97828,67005,Male,disloyal Customer,30,Business travel,Business,929,4,4,4,3,3,4,3,3,3,5,5,4,5,3,24,27.0,satisfied +97829,61174,Female,Loyal Customer,33,Business travel,Business,909,4,4,4,4,3,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +97830,82018,Male,Loyal Customer,22,Personal Travel,Eco,1517,3,5,3,4,3,3,3,3,3,3,3,5,5,3,0,0.0,neutral or dissatisfied +97831,63890,Female,Loyal Customer,58,Business travel,Business,1192,2,2,1,2,2,5,4,4,4,4,4,3,4,3,0,3.0,satisfied +97832,118785,Male,Loyal Customer,66,Personal Travel,Eco,621,3,1,3,2,5,3,5,5,3,4,3,2,3,5,23,33.0,neutral or dissatisfied +97833,55923,Female,Loyal Customer,49,Personal Travel,Eco,733,2,3,2,3,4,4,3,5,5,2,5,3,5,2,20,12.0,neutral or dissatisfied +97834,26902,Male,disloyal Customer,15,Business travel,Eco,1330,3,3,3,3,4,3,2,4,4,4,5,2,2,4,0,0.0,neutral or dissatisfied +97835,11538,Female,Loyal Customer,60,Business travel,Business,1987,1,1,1,1,4,4,4,4,4,4,4,4,4,3,77,74.0,satisfied +97836,97619,Female,Loyal Customer,49,Business travel,Business,2576,5,5,5,5,5,5,5,4,4,4,4,4,4,4,18,19.0,satisfied +97837,40438,Male,disloyal Customer,22,Business travel,Business,222,4,0,4,2,5,4,5,5,5,1,3,4,4,5,0,0.0,satisfied +97838,68926,Female,Loyal Customer,33,Personal Travel,Eco Plus,1061,2,4,2,1,1,2,2,1,4,4,5,4,5,1,36,30.0,neutral or dissatisfied +97839,62555,Female,Loyal Customer,59,Business travel,Business,1723,2,2,2,2,5,4,5,5,5,5,5,4,5,3,6,6.0,satisfied +97840,54222,Female,Loyal Customer,56,Business travel,Eco,1222,5,5,5,5,2,5,2,5,5,5,5,1,5,5,0,0.0,satisfied +97841,18556,Female,Loyal Customer,68,Business travel,Eco,127,4,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +97842,9551,Female,disloyal Customer,29,Business travel,Business,228,3,3,3,3,4,3,3,4,4,2,5,4,5,4,0,1.0,neutral or dissatisfied +97843,50261,Female,Loyal Customer,37,Business travel,Business,193,1,2,2,2,3,3,3,4,4,4,1,2,4,2,0,0.0,neutral or dissatisfied +97844,126398,Female,Loyal Customer,55,Business travel,Business,600,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +97845,105819,Female,Loyal Customer,14,Personal Travel,Eco,883,3,5,3,3,1,3,1,1,3,2,1,2,2,1,11,13.0,neutral or dissatisfied +97846,50305,Male,disloyal Customer,33,Business travel,Eco,89,2,1,2,3,5,2,5,5,2,4,4,1,3,5,0,11.0,neutral or dissatisfied +97847,93665,Female,Loyal Customer,53,Business travel,Business,2618,1,1,1,1,4,4,5,4,4,4,4,3,4,5,0,5.0,satisfied +97848,69635,Male,disloyal Customer,27,Business travel,Business,569,1,2,2,3,1,2,1,1,5,2,4,5,5,1,58,60.0,neutral or dissatisfied +97849,17028,Female,Loyal Customer,47,Personal Travel,Eco,781,2,4,2,3,5,2,3,2,2,2,2,1,2,5,0,0.0,neutral or dissatisfied +97850,21345,Female,Loyal Customer,32,Business travel,Business,761,4,4,4,4,5,5,5,5,1,3,4,3,3,5,2,0.0,satisfied +97851,121652,Female,disloyal Customer,34,Business travel,Business,328,3,3,3,3,5,3,5,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +97852,35732,Male,Loyal Customer,25,Personal Travel,Eco Plus,2475,1,4,1,4,1,5,5,3,2,3,3,5,3,5,27,13.0,neutral or dissatisfied +97853,90040,Female,Loyal Customer,53,Business travel,Business,1127,3,3,2,3,4,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +97854,78930,Male,Loyal Customer,44,Business travel,Business,1825,3,3,3,3,3,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +97855,22268,Male,disloyal Customer,20,Business travel,Eco,238,3,4,3,2,4,3,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +97856,36219,Female,disloyal Customer,25,Business travel,Eco,496,4,0,4,3,4,4,3,4,5,2,1,2,5,4,0,0.0,neutral or dissatisfied +97857,80820,Female,Loyal Customer,28,Business travel,Business,3724,5,5,5,5,4,4,4,4,3,3,5,4,4,4,10,3.0,satisfied +97858,4449,Male,Loyal Customer,56,Business travel,Business,3214,4,4,4,4,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +97859,11242,Male,Loyal Customer,16,Personal Travel,Eco,201,4,1,4,4,2,4,2,2,3,5,4,1,3,2,5,0.0,neutral or dissatisfied +97860,106882,Female,Loyal Customer,28,Business travel,Business,2255,3,1,1,1,3,3,3,3,4,3,3,2,4,3,6,0.0,neutral or dissatisfied +97861,117401,Female,Loyal Customer,32,Business travel,Business,544,5,5,5,5,4,3,4,4,4,5,4,5,5,4,17,7.0,satisfied +97862,80849,Female,Loyal Customer,32,Business travel,Business,3802,3,3,3,3,5,4,5,5,1,5,1,2,3,5,0,0.0,satisfied +97863,28725,Female,Loyal Customer,37,Personal Travel,Eco,2717,3,4,3,4,3,2,2,3,4,3,4,2,5,2,0,0.0,neutral or dissatisfied +97864,89699,Female,disloyal Customer,38,Business travel,Eco,669,4,4,4,3,3,4,3,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +97865,77888,Male,Loyal Customer,22,Business travel,Eco Plus,700,3,5,2,5,3,3,4,3,2,3,3,2,4,3,0,0.0,neutral or dissatisfied +97866,45059,Female,disloyal Customer,28,Business travel,Eco,342,4,0,4,3,1,4,1,1,3,3,2,5,5,1,43,46.0,satisfied +97867,122365,Female,Loyal Customer,40,Business travel,Business,2690,3,1,3,3,5,4,5,5,5,5,5,3,5,4,51,37.0,satisfied +97868,82263,Male,Loyal Customer,55,Business travel,Business,1481,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +97869,2556,Male,Loyal Customer,30,Business travel,Business,2438,0,0,0,2,2,2,2,2,3,4,4,5,5,2,0,0.0,satisfied +97870,39625,Male,Loyal Customer,61,Personal Travel,Eco,965,3,5,3,3,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +97871,19850,Female,Loyal Customer,63,Business travel,Eco,585,2,1,1,1,3,1,5,2,2,2,2,3,2,4,3,1.0,satisfied +97872,102625,Male,Loyal Customer,40,Business travel,Business,255,4,3,3,3,1,3,3,4,4,3,4,3,4,2,31,22.0,neutral or dissatisfied +97873,121055,Male,disloyal Customer,32,Personal Travel,Eco,1013,3,3,3,3,4,3,4,4,3,1,4,1,4,4,0,0.0,neutral or dissatisfied +97874,13174,Female,Loyal Customer,53,Business travel,Business,1630,4,1,1,1,4,4,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +97875,40782,Female,Loyal Customer,50,Business travel,Eco,588,2,2,2,2,3,3,4,2,2,2,2,1,2,4,7,2.0,neutral or dissatisfied +97876,48419,Male,Loyal Customer,32,Business travel,Business,1553,5,3,5,5,5,5,5,5,5,2,5,5,1,5,97,96.0,satisfied +97877,7681,Male,Loyal Customer,58,Business travel,Eco,204,1,1,1,1,1,1,1,1,3,3,2,1,1,1,0,0.0,neutral or dissatisfied +97878,65241,Male,Loyal Customer,49,Business travel,Business,190,3,3,3,3,3,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +97879,77739,Male,Loyal Customer,30,Business travel,Business,689,2,2,5,2,5,5,5,5,1,2,5,2,2,5,28,13.0,satisfied +97880,84857,Female,Loyal Customer,43,Business travel,Business,134,2,2,3,2,2,2,4,5,5,5,5,4,5,5,0,0.0,satisfied +97881,88299,Female,disloyal Customer,38,Business travel,Eco,271,2,4,2,3,3,2,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +97882,70164,Female,Loyal Customer,24,Personal Travel,Eco,460,1,1,1,3,3,1,3,3,3,3,3,2,3,3,28,14.0,neutral or dissatisfied +97883,107827,Female,Loyal Customer,25,Personal Travel,Eco,349,2,2,2,3,5,2,5,5,4,4,4,3,3,5,31,27.0,neutral or dissatisfied +97884,14225,Female,Loyal Customer,16,Personal Travel,Eco,620,4,5,3,1,3,3,2,3,3,5,5,5,4,3,0,0.0,satisfied +97885,82909,Male,Loyal Customer,55,Personal Travel,Eco,594,2,1,2,3,3,2,4,3,3,5,3,1,3,3,1,0.0,neutral or dissatisfied +97886,1431,Female,Loyal Customer,32,Business travel,Business,772,1,1,1,1,5,5,5,5,3,5,4,5,4,5,8,1.0,satisfied +97887,41563,Female,Loyal Customer,59,Business travel,Business,1516,1,1,1,1,2,3,5,3,3,3,3,4,3,4,8,5.0,satisfied +97888,52663,Female,Loyal Customer,55,Personal Travel,Eco,160,3,2,3,4,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +97889,69057,Male,Loyal Customer,38,Business travel,Eco,1389,2,3,3,3,3,2,2,4,4,2,2,2,3,2,138,137.0,neutral or dissatisfied +97890,116378,Male,Loyal Customer,40,Personal Travel,Eco,417,2,4,2,3,3,2,3,3,4,5,3,1,3,3,31,38.0,neutral or dissatisfied +97891,48692,Male,Loyal Customer,47,Business travel,Business,373,2,2,5,2,2,5,4,4,4,4,4,5,4,4,38,33.0,satisfied +97892,93837,Male,disloyal Customer,47,Business travel,Eco,391,3,3,3,4,5,3,5,5,4,2,4,4,3,5,128,120.0,neutral or dissatisfied +97893,95882,Male,disloyal Customer,18,Business travel,Eco,759,2,2,2,3,3,2,3,3,1,3,3,2,4,3,7,12.0,neutral or dissatisfied +97894,6335,Female,Loyal Customer,42,Business travel,Business,296,1,1,1,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +97895,8646,Female,Loyal Customer,40,Business travel,Business,3707,2,2,2,2,3,5,4,4,4,4,4,4,4,4,17,11.0,satisfied +97896,71096,Female,Loyal Customer,41,Personal Travel,Eco Plus,802,2,5,2,2,5,4,4,4,4,2,4,4,4,4,7,24.0,neutral or dissatisfied +97897,1312,Male,Loyal Customer,55,Business travel,Business,2220,0,4,0,3,4,5,4,3,3,3,3,4,3,3,1,0.0,satisfied +97898,111658,Female,Loyal Customer,22,Business travel,Business,991,2,2,2,2,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +97899,79250,Female,disloyal Customer,38,Business travel,Business,1598,5,5,5,5,1,5,1,1,3,4,4,3,4,1,0,0.0,satisfied +97900,40148,Female,disloyal Customer,24,Business travel,Eco,387,5,2,5,4,1,5,1,1,4,3,5,3,4,1,0,0.0,satisfied +97901,123421,Female,Loyal Customer,36,Personal Travel,Eco,1337,2,5,2,3,1,2,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +97902,85671,Female,Loyal Customer,65,Personal Travel,Eco,903,2,4,2,1,3,4,5,2,2,2,2,5,2,3,24,20.0,neutral or dissatisfied +97903,78890,Female,disloyal Customer,24,Business travel,Eco,1241,3,3,3,4,3,3,3,3,4,3,4,3,5,3,7,9.0,neutral or dissatisfied +97904,23944,Female,Loyal Customer,41,Business travel,Eco,936,1,1,1,1,1,1,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +97905,54883,Female,Loyal Customer,36,Personal Travel,Eco,934,2,4,2,2,4,2,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +97906,33532,Female,Loyal Customer,15,Personal Travel,Eco,228,3,1,3,3,4,3,5,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +97907,62618,Male,Loyal Customer,42,Personal Travel,Eco,1846,2,4,1,3,2,1,2,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +97908,47298,Female,Loyal Customer,44,Business travel,Business,588,1,1,1,1,4,5,5,2,2,2,2,1,2,5,0,4.0,satisfied +97909,117557,Female,Loyal Customer,42,Business travel,Business,3918,1,1,1,1,3,4,4,2,2,3,2,3,2,4,22,12.0,satisfied +97910,74035,Female,Loyal Customer,62,Business travel,Business,1471,2,2,2,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +97911,127919,Male,Loyal Customer,60,Personal Travel,Business,2300,3,4,3,2,2,4,5,1,1,3,3,3,1,5,0,0.0,neutral or dissatisfied +97912,87613,Female,Loyal Customer,68,Personal Travel,Business,606,3,4,3,5,4,5,5,2,2,3,2,5,2,3,0,7.0,neutral or dissatisfied +97913,88343,Male,Loyal Customer,45,Business travel,Business,3818,3,1,5,1,1,4,3,3,3,3,3,2,3,1,1,14.0,neutral or dissatisfied +97914,106188,Male,Loyal Customer,35,Personal Travel,Eco,436,4,4,4,3,4,4,4,4,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +97915,20070,Male,Loyal Customer,66,Personal Travel,Eco,607,4,4,3,3,5,3,5,5,5,5,4,5,5,5,20,,neutral or dissatisfied +97916,98992,Male,Loyal Customer,49,Personal Travel,Eco,543,2,5,3,2,5,3,5,5,2,3,5,4,3,5,17,11.0,neutral or dissatisfied +97917,15332,Female,Loyal Customer,33,Personal Travel,Eco,589,3,3,3,2,3,3,3,3,5,1,1,3,2,3,0,0.0,neutral or dissatisfied +97918,124409,Female,Loyal Customer,22,Business travel,Business,1044,5,5,5,5,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +97919,99526,Female,Loyal Customer,70,Personal Travel,Eco,528,1,4,1,4,5,3,3,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +97920,123933,Female,Loyal Customer,31,Personal Travel,Eco,544,4,4,4,3,2,4,2,2,1,4,2,2,3,2,0,0.0,neutral or dissatisfied +97921,57878,Male,disloyal Customer,48,Business travel,Business,305,3,3,3,5,1,3,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +97922,105053,Male,Loyal Customer,70,Personal Travel,Eco,255,3,2,3,3,5,3,5,5,3,3,2,4,3,5,0,0.0,neutral or dissatisfied +97923,2189,Female,Loyal Customer,54,Business travel,Business,3734,1,1,1,1,2,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +97924,65419,Male,Loyal Customer,38,Personal Travel,Eco Plus,631,2,4,2,3,3,2,3,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +97925,67186,Female,Loyal Customer,45,Personal Travel,Eco,985,3,4,2,4,4,5,5,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +97926,280,Male,Loyal Customer,44,Personal Travel,Eco,825,4,5,4,3,3,4,3,3,4,5,5,4,4,3,0,0.0,satisfied +97927,52553,Male,Loyal Customer,45,Business travel,Business,119,0,4,0,1,5,4,1,4,4,3,3,2,4,1,0,0.0,satisfied +97928,5851,Female,Loyal Customer,24,Business travel,Business,2726,1,1,1,1,4,4,4,4,4,3,4,3,5,4,0,0.0,satisfied +97929,86755,Female,Loyal Customer,16,Personal Travel,Eco,821,2,2,2,4,2,2,2,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +97930,14304,Male,Loyal Customer,39,Business travel,Eco,175,4,5,2,5,4,4,4,4,3,5,3,1,1,4,0,0.0,satisfied +97931,108018,Female,disloyal Customer,25,Business travel,Business,589,0,0,0,4,1,0,1,1,3,4,4,5,5,1,2,0.0,satisfied +97932,85729,Female,Loyal Customer,48,Business travel,Business,3456,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +97933,24994,Male,Loyal Customer,27,Business travel,Business,2773,1,0,0,4,2,0,2,2,3,3,3,2,3,2,7,6.0,neutral or dissatisfied +97934,116728,Female,Loyal Customer,32,Personal Travel,Eco Plus,337,4,5,4,3,4,4,4,4,4,3,5,5,4,4,1,0.0,satisfied +97935,126151,Female,Loyal Customer,49,Business travel,Business,2536,3,4,4,4,2,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +97936,88762,Male,Loyal Customer,44,Business travel,Business,3689,4,4,4,4,5,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +97937,27616,Female,Loyal Customer,16,Personal Travel,Eco,1050,2,5,2,4,2,2,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +97938,71237,Female,Loyal Customer,12,Business travel,Business,733,3,3,3,3,3,3,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +97939,26181,Male,disloyal Customer,20,Business travel,Eco,406,1,3,1,4,5,1,5,5,1,3,3,4,3,5,0,0.0,neutral or dissatisfied +97940,103699,Male,Loyal Customer,7,Personal Travel,Eco,405,2,5,2,4,4,2,1,4,2,5,2,2,1,4,11,1.0,neutral or dissatisfied +97941,47136,Female,Loyal Customer,47,Business travel,Eco,954,4,5,5,5,1,4,1,4,4,4,4,2,4,1,0,6.0,satisfied +97942,52056,Male,Loyal Customer,48,Business travel,Business,2378,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +97943,67493,Female,Loyal Customer,26,Business travel,Business,641,3,3,3,3,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +97944,18685,Male,Loyal Customer,22,Personal Travel,Eco,190,3,5,3,5,4,3,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +97945,26917,Female,disloyal Customer,38,Business travel,Eco,160,1,3,1,3,2,1,2,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +97946,113313,Male,Loyal Customer,34,Business travel,Business,488,4,1,1,1,5,3,4,4,4,4,4,1,4,4,12,14.0,neutral or dissatisfied +97947,96920,Female,Loyal Customer,45,Personal Travel,Eco,849,4,4,4,3,2,2,5,4,4,4,4,2,4,5,1,0.0,neutral or dissatisfied +97948,42041,Female,disloyal Customer,43,Business travel,Eco,116,2,2,2,3,5,2,5,5,1,5,4,1,4,5,5,8.0,neutral or dissatisfied +97949,65341,Female,Loyal Customer,42,Business travel,Business,631,4,4,4,4,5,4,4,5,5,5,5,5,5,3,6,3.0,satisfied +97950,55364,Female,disloyal Customer,50,Business travel,Business,678,4,3,3,2,5,4,5,5,5,4,5,3,5,5,14,12.0,satisfied +97951,115442,Female,Loyal Customer,37,Business travel,Business,1748,2,2,2,2,5,5,4,4,4,4,4,4,4,5,11,3.0,satisfied +97952,55438,Female,disloyal Customer,40,Business travel,Business,2521,2,2,2,4,2,3,3,2,1,4,4,3,1,3,4,0.0,neutral or dissatisfied +97953,97647,Male,Loyal Customer,31,Business travel,Business,1587,3,4,3,4,3,3,3,3,1,3,3,2,4,3,100,81.0,neutral or dissatisfied +97954,97388,Female,disloyal Customer,21,Business travel,Eco,843,3,3,3,4,4,3,4,4,3,3,3,2,4,4,14,7.0,neutral or dissatisfied +97955,101281,Male,Loyal Customer,60,Business travel,Business,444,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +97956,52126,Female,Loyal Customer,30,Personal Travel,Eco Plus,639,1,4,0,4,4,0,3,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +97957,4410,Female,Loyal Customer,57,Business travel,Business,762,2,3,3,3,2,2,2,3,3,4,4,2,4,2,146,134.0,neutral or dissatisfied +97958,2759,Male,Loyal Customer,58,Personal Travel,Eco Plus,772,1,4,1,2,4,1,4,4,4,3,1,1,2,4,0,0.0,neutral or dissatisfied +97959,9354,Male,Loyal Customer,49,Business travel,Business,3171,2,2,2,2,5,4,5,4,4,4,4,4,4,5,73,91.0,satisfied +97960,77665,Male,Loyal Customer,43,Business travel,Business,1890,2,3,3,3,3,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +97961,10674,Male,Loyal Customer,52,Business travel,Business,3096,3,3,3,3,2,4,5,4,4,4,5,4,4,3,0,0.0,satisfied +97962,69272,Female,Loyal Customer,20,Personal Travel,Eco,733,2,3,2,4,2,2,2,2,2,4,3,4,4,2,0,0.0,neutral or dissatisfied +97963,30258,Female,disloyal Customer,20,Business travel,Eco,1024,4,4,4,4,1,4,1,1,3,2,3,3,4,1,0,4.0,neutral or dissatisfied +97964,9781,Female,Loyal Customer,20,Personal Travel,Eco,383,1,4,1,5,1,1,1,1,1,3,5,1,4,1,0,9.0,neutral or dissatisfied +97965,83381,Male,Loyal Customer,26,Personal Travel,Eco,1124,3,4,3,3,4,3,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +97966,554,Female,Loyal Customer,39,Business travel,Business,3514,2,2,2,2,5,4,4,4,4,4,5,3,4,4,0,10.0,satisfied +97967,61985,Female,Loyal Customer,15,Personal Travel,Business,2475,3,4,3,4,3,3,3,4,3,3,4,3,3,3,205,201.0,neutral or dissatisfied +97968,39780,Male,Loyal Customer,14,Personal Travel,Eco,546,4,1,4,3,3,4,3,3,3,5,4,3,3,3,0,0.0,satisfied +97969,74552,Male,Loyal Customer,19,Business travel,Business,3936,1,1,4,1,3,3,3,3,3,2,5,4,5,3,23,5.0,satisfied +97970,27383,Female,Loyal Customer,52,Business travel,Business,3815,4,3,3,3,4,4,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +97971,18094,Male,Loyal Customer,32,Business travel,Eco Plus,605,5,3,3,3,5,5,5,3,3,3,5,5,3,5,133,116.0,satisfied +97972,59964,Male,Loyal Customer,37,Business travel,Business,3259,3,2,2,2,3,3,3,4,4,3,4,3,3,3,219,207.0,neutral or dissatisfied +97973,96243,Male,Loyal Customer,13,Personal Travel,Eco,328,2,2,2,4,2,2,2,2,1,3,4,1,4,2,20,18.0,neutral or dissatisfied +97974,7422,Female,Loyal Customer,14,Business travel,Business,2804,1,1,4,1,3,3,3,3,3,5,5,3,5,3,0,0.0,satisfied +97975,29684,Female,Loyal Customer,49,Personal Travel,Eco Plus,1448,2,1,2,4,4,4,3,1,1,2,2,2,1,3,0,0.0,neutral or dissatisfied +97976,105428,Female,Loyal Customer,67,Personal Travel,Eco,452,3,4,3,2,5,4,4,1,1,3,1,5,1,4,10,0.0,neutral or dissatisfied +97977,49150,Male,Loyal Customer,59,Business travel,Eco,109,5,2,2,2,5,5,5,5,2,2,5,5,4,5,0,0.0,satisfied +97978,51441,Female,Loyal Customer,61,Personal Travel,Eco Plus,363,3,5,3,4,3,5,5,1,1,3,1,5,1,5,5,5.0,neutral or dissatisfied +97979,61651,Female,Loyal Customer,50,Business travel,Business,1635,4,4,4,4,4,3,4,5,5,5,5,4,5,4,5,0.0,satisfied +97980,79206,Male,Loyal Customer,31,Business travel,Business,1990,1,5,5,5,1,1,1,1,2,4,4,2,3,1,1,3.0,neutral or dissatisfied +97981,66941,Male,disloyal Customer,30,Business travel,Business,985,2,2,2,4,2,2,2,4,3,4,4,2,4,2,135,137.0,neutral or dissatisfied +97982,30521,Female,Loyal Customer,35,Business travel,Eco,464,4,1,1,1,4,4,4,4,1,4,4,4,1,4,202,213.0,satisfied +97983,14753,Female,Loyal Customer,55,Business travel,Business,463,1,0,0,3,3,3,3,5,5,0,2,4,5,1,0,0.0,neutral or dissatisfied +97984,29298,Male,Loyal Customer,45,Business travel,Business,3069,3,3,3,3,3,3,2,5,5,5,5,3,5,2,4,0.0,satisfied +97985,88345,Female,disloyal Customer,44,Business travel,Business,406,2,2,2,3,3,2,3,3,5,5,5,3,4,3,14,5.0,neutral or dissatisfied +97986,70051,Female,Loyal Customer,18,Personal Travel,Eco,583,2,4,2,5,1,2,1,1,4,4,4,3,5,1,0,1.0,neutral or dissatisfied +97987,13521,Male,Loyal Customer,40,Business travel,Business,106,3,3,3,3,1,1,5,4,4,4,4,1,4,1,0,0.0,satisfied +97988,86677,Female,Loyal Customer,39,Business travel,Eco Plus,952,3,3,1,3,3,3,3,3,2,5,4,1,3,3,14,15.0,neutral or dissatisfied +97989,94538,Male,Loyal Customer,51,Business travel,Business,239,2,3,2,2,2,4,5,4,4,4,4,5,4,3,44,47.0,satisfied +97990,86034,Female,Loyal Customer,13,Personal Travel,Eco,432,3,4,3,3,4,3,2,4,5,2,5,5,4,4,10,8.0,neutral or dissatisfied +97991,46043,Male,Loyal Customer,18,Business travel,Eco,996,1,1,1,1,1,1,3,1,3,3,4,2,3,1,26,39.0,neutral or dissatisfied +97992,63490,Male,disloyal Customer,8,Business travel,Eco,651,3,2,3,3,2,3,5,2,1,2,3,4,3,2,0,0.0,neutral or dissatisfied +97993,62431,Male,Loyal Customer,48,Personal Travel,Eco,1670,4,0,4,3,4,4,3,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +97994,52359,Male,Loyal Customer,62,Personal Travel,Eco,237,2,4,2,3,2,2,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +97995,40230,Male,Loyal Customer,76,Business travel,Eco,347,4,2,4,2,4,4,4,4,1,1,3,3,2,4,0,0.0,satisfied +97996,56352,Male,Loyal Customer,37,Personal Travel,Eco,200,3,4,0,1,4,0,4,4,4,4,5,5,5,4,16,38.0,neutral or dissatisfied +97997,34184,Male,Loyal Customer,50,Business travel,Business,2916,3,3,3,3,4,4,4,3,3,3,3,1,3,5,0,0.0,satisfied +97998,19173,Male,Loyal Customer,45,Personal Travel,Eco Plus,304,2,2,2,4,5,2,4,5,2,4,4,2,3,5,3,0.0,neutral or dissatisfied +97999,52649,Female,Loyal Customer,36,Personal Travel,Eco,110,3,2,3,3,2,3,2,2,2,4,3,4,4,2,0,0.0,neutral or dissatisfied +98000,104700,Female,Loyal Customer,39,Business travel,Business,3933,2,2,2,2,2,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +98001,31489,Female,disloyal Customer,23,Business travel,Eco,862,2,2,2,2,5,2,5,5,3,1,5,3,4,5,27,41.0,neutral or dissatisfied +98002,27065,Female,Loyal Customer,58,Business travel,Business,1399,2,1,1,1,2,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +98003,77457,Female,Loyal Customer,54,Business travel,Business,2978,1,1,2,1,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +98004,34362,Male,disloyal Customer,22,Business travel,Eco,141,2,4,2,4,1,2,1,1,3,3,3,2,3,1,12,13.0,neutral or dissatisfied +98005,71756,Male,Loyal Customer,38,Business travel,Business,1726,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +98006,44252,Male,Loyal Customer,61,Business travel,Eco,359,4,4,4,4,5,4,5,5,1,4,2,4,4,5,0,0.0,satisfied +98007,19532,Female,disloyal Customer,27,Business travel,Eco,173,4,0,4,2,5,4,5,5,1,1,5,4,2,5,0,0.0,neutral or dissatisfied +98008,117597,Female,Loyal Customer,22,Business travel,Business,1932,4,4,4,4,3,4,3,3,5,4,4,5,4,3,17,2.0,satisfied +98009,14714,Male,Loyal Customer,12,Personal Travel,Eco,419,3,4,3,2,4,3,4,4,5,3,2,1,1,4,0,0.0,neutral or dissatisfied +98010,19002,Male,disloyal Customer,15,Business travel,Eco,871,3,3,3,3,4,3,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +98011,48870,Male,disloyal Customer,41,Business travel,Eco,373,4,0,4,4,1,4,1,1,2,5,3,5,1,1,12,1.0,neutral or dissatisfied +98012,25892,Female,Loyal Customer,54,Business travel,Business,3098,3,3,3,3,2,4,5,5,5,5,5,3,5,2,0,0.0,satisfied +98013,74242,Female,Loyal Customer,55,Business travel,Business,1709,4,4,4,4,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +98014,35048,Male,disloyal Customer,25,Business travel,Eco,1074,1,1,1,5,2,1,5,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +98015,96304,Male,Loyal Customer,8,Business travel,Business,546,4,4,5,4,4,4,4,4,5,3,5,5,5,4,1,0.0,satisfied +98016,120385,Male,Loyal Customer,50,Business travel,Business,2064,3,3,3,3,4,4,5,5,5,4,5,5,5,5,7,12.0,satisfied +98017,30647,Female,Loyal Customer,25,Business travel,Business,370,4,4,4,4,5,5,5,5,5,2,4,3,2,5,0,0.0,satisfied +98018,118305,Male,Loyal Customer,31,Business travel,Business,602,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +98019,124104,Male,disloyal Customer,9,Business travel,Business,529,5,0,5,2,1,5,1,1,5,5,5,5,5,1,0,0.0,satisfied +98020,94199,Female,Loyal Customer,58,Business travel,Business,2086,1,1,1,1,3,5,5,4,4,4,4,5,4,5,40,27.0,satisfied +98021,105709,Female,Loyal Customer,34,Business travel,Business,787,4,4,2,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +98022,10497,Male,Loyal Customer,20,Business travel,Business,308,4,4,4,4,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +98023,26177,Male,Loyal Customer,76,Business travel,Business,2741,3,5,5,5,5,3,4,3,3,3,3,2,3,1,15,14.0,neutral or dissatisfied +98024,45970,Male,Loyal Customer,31,Business travel,Business,3029,1,1,1,1,4,4,4,4,2,1,5,5,3,4,0,0.0,satisfied +98025,49380,Male,disloyal Customer,40,Business travel,Eco,134,3,0,3,2,3,3,4,3,5,1,5,1,5,3,0,1.0,neutral or dissatisfied +98026,102124,Male,Loyal Customer,35,Business travel,Business,197,1,1,1,1,4,4,5,5,5,5,4,5,5,5,16,7.0,satisfied +98027,6341,Female,disloyal Customer,22,Business travel,Business,240,5,0,5,4,1,5,1,1,5,3,5,4,5,1,0,0.0,satisfied +98028,29969,Male,Loyal Customer,47,Business travel,Eco,198,4,4,4,4,4,4,4,4,3,2,4,3,3,4,0,4.0,neutral or dissatisfied +98029,120772,Female,disloyal Customer,35,Business travel,Eco,678,1,2,2,3,5,2,5,5,2,2,4,2,4,5,0,0.0,neutral or dissatisfied +98030,34299,Male,Loyal Customer,59,Personal Travel,Eco,496,3,3,3,3,4,3,4,4,5,4,1,1,5,4,13,0.0,neutral or dissatisfied +98031,41487,Male,Loyal Customer,44,Business travel,Eco,1482,4,4,4,4,4,4,4,4,1,4,3,3,1,4,0,8.0,satisfied +98032,117551,Female,disloyal Customer,44,Business travel,Business,347,2,2,2,3,1,2,1,1,4,4,5,4,4,1,5,0.0,neutral or dissatisfied +98033,97997,Female,Loyal Customer,51,Business travel,Business,1614,2,2,2,2,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +98034,119793,Female,Loyal Customer,47,Business travel,Business,936,4,4,3,4,4,5,4,4,4,4,4,5,4,5,55,34.0,satisfied +98035,42950,Male,Loyal Customer,32,Business travel,Business,3985,0,0,0,4,3,3,3,3,2,3,2,2,4,3,0,0.0,satisfied +98036,21608,Female,Loyal Customer,29,Business travel,Business,1805,4,5,3,5,4,4,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +98037,75156,Male,disloyal Customer,28,Business travel,Eco,1332,1,2,2,4,5,1,3,5,2,5,4,1,3,5,2,0.0,neutral or dissatisfied +98038,47665,Male,Loyal Customer,40,Business travel,Eco,1064,4,2,2,2,4,4,4,4,5,2,2,2,1,4,47,30.0,satisfied +98039,89855,Female,Loyal Customer,39,Business travel,Business,1310,4,4,2,4,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +98040,50230,Male,Loyal Customer,33,Business travel,Business,304,1,4,4,4,1,1,1,1,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +98041,67980,Male,Loyal Customer,15,Business travel,Eco Plus,1188,3,3,3,3,3,3,2,3,1,4,3,4,4,3,50,40.0,neutral or dissatisfied +98042,78937,Female,Loyal Customer,28,Personal Travel,Eco,500,1,4,1,3,4,1,4,4,4,2,5,4,4,4,11,0.0,neutral or dissatisfied +98043,12474,Female,Loyal Customer,43,Personal Travel,Eco,253,4,3,4,5,1,2,3,3,3,4,3,2,3,2,62,61.0,neutral or dissatisfied +98044,108697,Male,Loyal Customer,41,Personal Travel,Eco,577,3,4,3,3,2,3,2,2,5,4,5,5,5,2,67,64.0,neutral or dissatisfied +98045,124686,Female,Loyal Customer,69,Business travel,Business,3174,1,2,2,2,5,3,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +98046,117890,Female,Loyal Customer,44,Business travel,Business,2865,1,1,1,1,3,4,4,4,4,4,4,5,4,4,3,2.0,satisfied +98047,68253,Female,Loyal Customer,44,Personal Travel,Eco,432,2,4,2,4,4,4,4,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +98048,6566,Female,Loyal Customer,52,Business travel,Business,3483,5,5,5,5,2,5,5,4,4,4,4,5,4,4,18,7.0,satisfied +98049,128442,Female,disloyal Customer,29,Business travel,Eco,251,4,3,3,3,2,3,2,2,2,1,3,1,4,2,0,7.0,neutral or dissatisfied +98050,83520,Female,Loyal Customer,49,Personal Travel,Eco,946,3,2,3,4,1,3,3,1,1,3,1,4,1,4,6,43.0,neutral or dissatisfied +98051,64990,Female,Loyal Customer,41,Business travel,Business,3189,3,3,3,3,3,4,1,5,5,5,5,3,5,5,0,0.0,satisfied +98052,53952,Female,Loyal Customer,23,Business travel,Business,3018,3,3,3,3,4,4,4,4,3,1,3,5,2,4,0,0.0,satisfied +98053,86542,Male,Loyal Customer,26,Personal Travel,Eco,760,3,5,3,2,4,3,4,4,5,4,4,4,4,4,7,0.0,neutral or dissatisfied +98054,33822,Female,Loyal Customer,46,Personal Travel,Eco,1428,3,5,3,1,3,4,1,3,4,3,4,1,3,1,296,301.0,neutral or dissatisfied +98055,112812,Male,Loyal Customer,40,Business travel,Business,1999,1,1,2,1,2,4,4,4,4,5,4,5,4,4,46,48.0,satisfied +98056,33408,Male,disloyal Customer,26,Business travel,Eco,1351,4,4,4,1,1,4,1,1,1,4,5,5,3,1,0,3.0,neutral or dissatisfied +98057,95875,Female,Loyal Customer,72,Business travel,Business,3555,2,3,3,3,2,2,2,2,2,2,2,1,2,2,27,10.0,neutral or dissatisfied +98058,4143,Male,Loyal Customer,43,Business travel,Business,544,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +98059,123279,Male,Loyal Customer,26,Personal Travel,Eco,631,2,5,2,5,2,2,2,2,2,1,4,3,3,2,18,12.0,neutral or dissatisfied +98060,8990,Female,Loyal Customer,49,Business travel,Business,2363,1,1,5,1,3,5,4,4,4,4,4,5,4,4,108,97.0,satisfied +98061,122715,Female,Loyal Customer,69,Personal Travel,Business,651,4,2,4,3,5,4,3,1,1,4,1,2,1,1,0,0.0,neutral or dissatisfied +98062,75566,Female,disloyal Customer,37,Business travel,Business,337,3,3,3,4,2,3,2,2,5,5,4,4,4,2,0,28.0,neutral or dissatisfied +98063,4675,Female,Loyal Customer,40,Business travel,Eco,364,5,2,2,2,5,5,5,5,4,2,5,1,2,5,8,3.0,satisfied +98064,106209,Female,Loyal Customer,49,Business travel,Business,3690,0,0,0,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +98065,96798,Female,disloyal Customer,38,Business travel,Business,928,4,4,4,5,4,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +98066,56079,Male,Loyal Customer,37,Personal Travel,Eco,2475,3,5,4,3,4,2,2,2,4,5,4,2,5,2,1,0.0,neutral or dissatisfied +98067,32545,Male,Loyal Customer,25,Business travel,Business,2996,2,2,3,2,4,4,3,4,1,3,5,3,3,4,9,13.0,satisfied +98068,116229,Female,Loyal Customer,23,Personal Travel,Eco,417,1,5,4,5,2,4,2,2,4,5,5,5,1,2,12,14.0,neutral or dissatisfied +98069,14004,Male,Loyal Customer,51,Business travel,Business,3377,5,5,4,5,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +98070,46442,Female,Loyal Customer,26,Personal Travel,Eco,1304,3,4,3,2,1,3,1,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +98071,62635,Female,Loyal Customer,70,Personal Travel,Eco,1744,2,3,2,3,1,3,4,5,5,2,5,1,5,5,3,0.0,neutral or dissatisfied +98072,77269,Male,Loyal Customer,35,Personal Travel,Eco Plus,1590,3,1,3,1,2,3,2,2,1,3,1,4,2,2,0,45.0,neutral or dissatisfied +98073,37904,Male,disloyal Customer,55,Business travel,Eco,623,3,2,3,4,1,3,1,1,4,1,3,3,3,1,23,29.0,neutral or dissatisfied +98074,37443,Female,Loyal Customer,28,Business travel,Business,2595,4,4,4,4,3,4,3,3,3,2,4,3,3,3,0,0.0,satisfied +98075,41925,Male,Loyal Customer,32,Business travel,Business,129,2,1,1,1,2,2,2,2,2,2,4,3,4,2,39,45.0,neutral or dissatisfied +98076,82166,Male,Loyal Customer,63,Personal Travel,Eco,237,1,2,0,4,2,0,2,2,4,5,3,2,3,2,27,47.0,neutral or dissatisfied +98077,85323,Female,Loyal Customer,65,Personal Travel,Eco,731,2,3,2,3,5,4,3,3,3,2,3,3,3,3,14,42.0,neutral or dissatisfied +98078,117204,Male,Loyal Customer,37,Personal Travel,Eco,325,3,4,3,4,3,3,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +98079,73616,Male,Loyal Customer,51,Business travel,Business,2055,4,4,5,4,3,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +98080,92437,Male,Loyal Customer,43,Business travel,Business,1892,4,2,4,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +98081,14163,Female,Loyal Customer,49,Personal Travel,Business,692,1,5,1,4,4,4,4,2,2,1,2,4,2,5,76,72.0,neutral or dissatisfied +98082,108942,Male,Loyal Customer,48,Business travel,Eco Plus,1066,3,3,3,3,3,3,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +98083,119893,Female,disloyal Customer,21,Business travel,Eco,912,1,1,1,5,4,1,4,4,4,3,4,4,5,4,0,7.0,neutral or dissatisfied +98084,72318,Male,Loyal Customer,24,Personal Travel,Eco Plus,919,3,2,3,3,4,3,4,4,3,5,3,4,4,4,12,12.0,neutral or dissatisfied +98085,90277,Female,Loyal Customer,46,Business travel,Business,3334,3,4,3,3,4,4,4,3,2,4,4,4,5,4,152,163.0,satisfied +98086,46748,Female,Loyal Customer,60,Personal Travel,Eco,125,3,2,3,2,1,2,3,1,1,3,1,4,1,3,50,67.0,neutral or dissatisfied +98087,77379,Male,disloyal Customer,26,Business travel,Eco,590,3,3,3,3,2,3,2,2,4,3,3,4,3,2,0,0.0,neutral or dissatisfied +98088,54243,Male,disloyal Customer,14,Business travel,Eco,1222,3,3,3,4,2,3,2,2,3,2,3,4,4,2,89,104.0,neutral or dissatisfied +98089,75916,Female,Loyal Customer,61,Personal Travel,Eco,597,3,5,3,5,1,5,5,5,5,3,5,4,5,5,19,7.0,neutral or dissatisfied +98090,64354,Male,disloyal Customer,26,Business travel,Business,1172,2,3,3,3,4,3,4,4,2,3,4,3,4,4,0,5.0,neutral or dissatisfied +98091,11313,Female,Loyal Customer,40,Personal Travel,Eco,316,3,3,1,2,5,1,5,5,1,5,2,3,3,5,1,7.0,neutral or dissatisfied +98092,21926,Male,Loyal Customer,37,Business travel,Eco,448,4,1,1,1,4,4,4,4,5,2,4,4,2,4,0,4.0,satisfied +98093,125347,Female,Loyal Customer,27,Business travel,Business,599,3,3,3,3,3,4,3,3,4,5,5,3,4,3,0,0.0,satisfied +98094,74373,Female,Loyal Customer,41,Business travel,Business,2173,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +98095,7966,Male,Loyal Customer,53,Personal Travel,Eco,594,3,4,3,3,5,3,5,5,2,1,4,4,3,5,0,0.0,neutral or dissatisfied +98096,9249,Male,Loyal Customer,10,Personal Travel,Eco,100,2,1,0,3,5,0,5,5,4,4,4,1,3,5,0,0.0,neutral or dissatisfied +98097,124799,Male,Loyal Customer,45,Business travel,Business,3884,0,0,0,2,2,5,5,3,3,3,3,3,3,5,10,4.0,satisfied +98098,71722,Female,disloyal Customer,35,Business travel,Eco,888,4,3,3,3,4,3,5,4,2,2,4,3,4,4,13,9.0,neutral or dissatisfied +98099,65653,Male,disloyal Customer,21,Business travel,Eco,1021,3,3,3,2,5,3,5,5,3,5,3,3,2,5,36,42.0,neutral or dissatisfied +98100,11433,Female,disloyal Customer,18,Business travel,Eco,201,4,0,4,4,5,4,5,5,4,3,5,5,4,5,0,0.0,satisfied +98101,62331,Male,Loyal Customer,21,Personal Travel,Eco,414,1,1,1,4,2,1,2,2,1,2,4,3,3,2,0,0.0,neutral or dissatisfied +98102,65464,Male,disloyal Customer,25,Business travel,Eco,1303,3,3,3,3,5,3,5,5,3,2,5,5,5,5,2,0.0,neutral or dissatisfied +98103,114833,Female,Loyal Customer,39,Business travel,Business,1602,5,5,5,5,4,4,5,4,4,4,4,4,4,5,19,11.0,satisfied +98104,18227,Male,Loyal Customer,70,Business travel,Business,346,2,1,1,1,5,2,2,2,2,2,2,2,2,1,106,104.0,neutral or dissatisfied +98105,15254,Female,Loyal Customer,34,Personal Travel,Eco,445,2,5,2,4,1,2,1,1,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +98106,72044,Male,Loyal Customer,52,Business travel,Business,2486,3,3,3,3,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +98107,108023,Female,disloyal Customer,29,Business travel,Eco Plus,589,1,1,1,3,4,1,1,4,3,5,4,4,3,4,0,0.0,neutral or dissatisfied +98108,104047,Female,Loyal Customer,23,Business travel,Business,1262,1,1,1,1,1,1,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +98109,74397,Female,Loyal Customer,45,Business travel,Business,2875,3,3,3,3,5,4,5,5,5,5,5,5,5,4,16,0.0,satisfied +98110,21067,Female,disloyal Customer,17,Business travel,Eco,227,2,2,2,4,2,2,2,2,4,2,3,3,3,2,2,40.0,neutral or dissatisfied +98111,31537,Female,Loyal Customer,63,Personal Travel,Eco,846,1,5,1,3,3,4,4,2,2,1,2,3,2,4,24,30.0,neutral or dissatisfied +98112,24123,Female,Loyal Customer,42,Personal Travel,Eco,510,2,5,4,2,5,4,5,4,4,4,4,4,4,4,75,68.0,neutral or dissatisfied +98113,96036,Male,Loyal Customer,24,Business travel,Business,3376,1,0,0,2,3,0,3,3,2,5,2,4,2,3,11,24.0,neutral or dissatisfied +98114,529,Male,Loyal Customer,54,Business travel,Business,2526,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +98115,71749,Female,Loyal Customer,52,Business travel,Business,1829,2,2,2,2,4,5,4,4,4,5,4,4,4,5,5,5.0,satisfied +98116,34518,Female,Loyal Customer,21,Personal Travel,Eco,1428,4,4,4,3,2,4,2,2,5,5,4,3,3,2,0,3.0,neutral or dissatisfied +98117,102631,Male,Loyal Customer,47,Business travel,Business,255,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +98118,41510,Male,Loyal Customer,30,Business travel,Business,3802,5,3,3,3,5,4,5,5,2,1,4,3,3,5,13,23.0,neutral or dissatisfied +98119,101427,Male,Loyal Customer,33,Business travel,Business,3579,2,2,2,2,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +98120,81653,Female,Loyal Customer,52,Business travel,Business,3074,3,3,3,3,4,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +98121,39494,Male,Loyal Customer,44,Business travel,Business,1368,1,3,3,3,2,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +98122,30467,Male,Loyal Customer,50,Business travel,Eco,495,5,5,5,5,5,5,5,5,4,4,1,5,3,5,6,5.0,satisfied +98123,6682,Female,Loyal Customer,39,Business travel,Business,403,4,4,4,4,2,4,5,4,4,4,4,4,4,5,15,0.0,satisfied +98124,104201,Female,Loyal Customer,60,Personal Travel,Eco,1310,3,5,3,3,3,4,5,4,4,3,4,5,4,3,58,44.0,neutral or dissatisfied +98125,61419,Female,Loyal Customer,44,Business travel,Eco Plus,279,4,1,1,1,4,1,3,4,4,4,4,1,4,3,6,1.0,satisfied +98126,84566,Female,disloyal Customer,38,Personal Travel,Eco,2399,3,4,3,3,3,3,3,4,5,5,5,3,3,3,185,186.0,neutral or dissatisfied +98127,41366,Female,Loyal Customer,36,Business travel,Eco,809,4,3,3,3,4,5,4,4,4,5,1,5,2,4,0,0.0,satisfied +98128,4618,Male,Loyal Customer,56,Personal Travel,Eco,719,1,1,1,2,4,1,4,4,3,4,2,2,2,4,3,0.0,neutral or dissatisfied +98129,58940,Male,Loyal Customer,49,Business travel,Business,3690,1,1,1,1,3,4,5,5,5,5,5,5,5,3,90,88.0,satisfied +98130,47422,Female,Loyal Customer,52,Business travel,Eco,190,5,1,1,1,5,1,5,5,5,5,5,2,5,3,6,6.0,satisfied +98131,10284,Male,Loyal Customer,55,Business travel,Business,301,3,3,3,3,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +98132,90106,Male,disloyal Customer,41,Business travel,Business,1145,4,4,4,1,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +98133,57243,Male,disloyal Customer,42,Business travel,Business,804,4,5,5,1,4,4,4,4,3,2,5,5,4,4,0,26.0,satisfied +98134,89764,Male,Loyal Customer,29,Personal Travel,Eco,1089,3,4,3,2,4,3,4,4,5,2,1,1,2,4,0,0.0,neutral or dissatisfied +98135,106195,Female,Loyal Customer,70,Personal Travel,Eco,436,2,3,2,3,4,3,3,2,2,2,1,3,2,3,13,3.0,neutral or dissatisfied +98136,98123,Female,Loyal Customer,34,Personal Travel,Eco,426,2,2,1,4,1,1,1,1,1,3,4,3,4,1,36,34.0,neutral or dissatisfied +98137,73292,Male,disloyal Customer,44,Business travel,Business,1182,5,5,5,2,2,5,2,2,3,2,5,3,4,2,106,117.0,satisfied +98138,55062,Male,disloyal Customer,22,Business travel,Business,1399,5,0,5,1,5,5,4,5,3,2,4,4,5,5,106,110.0,satisfied +98139,77030,Female,Loyal Customer,59,Personal Travel,Eco,368,3,3,3,1,2,1,1,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +98140,103978,Male,Loyal Customer,46,Business travel,Business,1334,4,4,4,4,5,4,4,4,4,4,4,5,4,4,3,0.0,satisfied +98141,121715,Male,Loyal Customer,28,Personal Travel,Eco,683,2,4,2,4,1,2,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +98142,94014,Male,disloyal Customer,61,Business travel,Business,323,4,4,4,4,4,3,3,3,5,4,4,3,4,3,185,176.0,satisfied +98143,122688,Female,Loyal Customer,42,Business travel,Business,361,4,1,1,1,5,2,2,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +98144,59586,Male,Loyal Customer,28,Business travel,Business,787,1,2,2,2,1,1,1,1,1,3,2,2,2,1,2,29.0,neutral or dissatisfied +98145,30245,Male,Loyal Customer,54,Personal Travel,Eco,896,2,2,2,4,4,2,4,4,1,3,4,2,3,4,0,3.0,neutral or dissatisfied +98146,86860,Male,Loyal Customer,34,Personal Travel,Eco,484,1,0,1,4,4,1,5,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +98147,121319,Female,Loyal Customer,69,Personal Travel,Eco,1009,3,3,3,4,3,1,3,4,4,3,4,4,4,1,1,0.0,neutral or dissatisfied +98148,39331,Female,Loyal Customer,61,Personal Travel,Eco Plus,268,2,0,2,3,4,5,1,1,1,2,2,2,1,4,7,0.0,neutral or dissatisfied +98149,77826,Male,Loyal Customer,19,Personal Travel,Eco,731,1,4,1,3,5,1,5,5,1,1,3,4,4,5,0,0.0,neutral or dissatisfied +98150,86047,Female,Loyal Customer,40,Personal Travel,Eco,528,2,5,5,1,5,5,5,5,5,5,4,4,4,5,13,0.0,neutral or dissatisfied +98151,106723,Male,Loyal Customer,47,Business travel,Business,837,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +98152,63364,Female,Loyal Customer,63,Personal Travel,Eco,337,2,2,2,4,4,3,3,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +98153,10191,Male,Loyal Customer,42,Business travel,Business,216,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +98154,24959,Female,Loyal Customer,41,Business travel,Business,226,1,1,1,1,4,4,3,4,4,4,4,5,4,2,0,0.0,satisfied +98155,58768,Female,Loyal Customer,32,Business travel,Eco,1120,1,4,4,4,1,1,1,1,4,2,3,3,4,1,11,20.0,neutral or dissatisfied +98156,63795,Female,Loyal Customer,12,Personal Travel,Eco,1721,4,1,4,2,2,4,3,2,3,1,3,1,2,2,0,0.0,neutral or dissatisfied +98157,80938,Male,Loyal Customer,38,Personal Travel,Eco,341,2,4,2,4,3,2,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +98158,89488,Female,Loyal Customer,35,Business travel,Business,1931,1,1,1,1,4,2,1,4,4,5,4,4,4,1,0,0.0,satisfied +98159,40391,Female,Loyal Customer,54,Business travel,Business,1905,5,5,5,5,2,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +98160,108293,Female,Loyal Customer,26,Personal Travel,Business,1750,2,3,2,3,1,2,1,1,2,4,5,3,1,1,71,74.0,neutral or dissatisfied +98161,99740,Male,Loyal Customer,35,Business travel,Business,1794,0,0,0,5,3,5,4,1,1,1,1,5,1,5,0,1.0,satisfied +98162,37171,Male,Loyal Customer,68,Personal Travel,Eco,1046,2,4,2,3,4,2,4,4,4,4,4,4,4,4,0,8.0,neutral or dissatisfied +98163,42536,Female,Loyal Customer,53,Business travel,Business,1782,2,2,2,2,2,1,2,3,3,2,3,3,3,3,3,3.0,satisfied +98164,71215,Male,Loyal Customer,50,Business travel,Business,733,5,5,5,5,5,5,4,4,4,4,4,5,4,3,4,0.0,satisfied +98165,16232,Female,Loyal Customer,48,Personal Travel,Eco,266,2,2,0,3,3,3,4,2,2,0,2,3,2,4,0,0.0,neutral or dissatisfied +98166,38912,Male,Loyal Customer,28,Business travel,Business,162,2,2,2,2,2,2,2,2,2,1,4,3,4,2,0,12.0,neutral or dissatisfied +98167,72980,Female,Loyal Customer,49,Business travel,Business,2586,1,5,5,5,3,2,2,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +98168,7321,Female,Loyal Customer,34,Personal Travel,Eco Plus,135,3,0,3,4,1,3,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +98169,71049,Male,disloyal Customer,34,Business travel,Eco,802,2,2,2,4,1,2,1,1,4,3,4,1,4,1,98,112.0,neutral or dissatisfied +98170,120259,Female,Loyal Customer,57,Business travel,Business,237,3,5,3,3,5,5,4,4,4,4,4,3,4,3,27,26.0,satisfied +98171,34325,Male,disloyal Customer,39,Business travel,Business,846,2,2,2,4,5,2,1,5,1,5,4,2,4,5,0,0.0,neutral or dissatisfied +98172,114552,Male,Loyal Customer,36,Personal Travel,Business,342,1,5,1,1,3,5,4,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +98173,101237,Female,Loyal Customer,51,Business travel,Business,1587,1,4,1,1,4,4,5,4,4,4,4,5,4,4,8,0.0,satisfied +98174,37777,Female,Loyal Customer,34,Business travel,Eco Plus,1069,5,2,1,2,5,5,5,5,2,2,4,5,1,5,0,0.0,satisfied +98175,72289,Female,Loyal Customer,69,Personal Travel,Eco,919,2,1,2,3,4,3,2,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +98176,97786,Female,disloyal Customer,39,Business travel,Business,471,3,3,3,4,4,3,4,4,3,2,3,1,3,4,0,7.0,neutral or dissatisfied +98177,129114,Female,Loyal Customer,56,Business travel,Business,2342,4,4,5,4,4,4,4,4,3,5,4,4,3,4,0,10.0,satisfied +98178,26376,Female,Loyal Customer,28,Personal Travel,Eco,991,3,5,3,4,2,3,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +98179,120103,Female,Loyal Customer,44,Business travel,Business,1576,2,2,2,2,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +98180,118799,Female,Loyal Customer,26,Personal Travel,Eco,647,3,1,3,4,3,3,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +98181,27988,Female,Loyal Customer,9,Personal Travel,Eco Plus,2350,4,2,4,4,2,4,2,2,3,2,4,4,3,2,0,1.0,neutral or dissatisfied +98182,18716,Male,Loyal Customer,62,Personal Travel,Eco Plus,253,2,1,2,3,3,2,3,3,2,1,4,4,4,3,0,0.0,neutral or dissatisfied +98183,119664,Female,Loyal Customer,25,Personal Travel,Eco,507,1,5,1,1,3,1,3,3,4,4,4,5,4,3,66,50.0,neutral or dissatisfied +98184,43160,Male,Loyal Customer,44,Business travel,Business,3037,2,2,2,2,2,3,4,4,4,4,4,1,4,5,0,0.0,satisfied +98185,58998,Female,Loyal Customer,41,Business travel,Business,1726,1,1,1,1,5,4,5,3,3,3,3,4,3,5,13,13.0,satisfied +98186,89299,Male,Loyal Customer,13,Personal Travel,Eco,453,1,5,1,5,3,1,3,3,3,4,4,5,4,3,63,56.0,neutral or dissatisfied +98187,42049,Male,Loyal Customer,37,Business travel,Eco,116,4,2,2,2,4,4,4,4,1,4,2,2,2,4,0,0.0,satisfied +98188,61674,Male,Loyal Customer,51,Business travel,Business,1346,1,1,1,1,5,5,4,5,5,5,5,4,5,3,11,0.0,satisfied +98189,58440,Male,Loyal Customer,62,Personal Travel,Eco,528,2,4,2,1,4,2,4,4,3,5,5,4,5,4,3,0.0,neutral or dissatisfied +98190,125957,Male,Loyal Customer,35,Business travel,Eco Plus,993,2,5,5,5,2,2,2,2,3,1,4,2,3,2,1,0.0,neutral or dissatisfied +98191,3986,Male,Loyal Customer,46,Business travel,Business,419,4,4,4,4,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +98192,9956,Male,Loyal Customer,43,Business travel,Business,515,5,5,3,5,2,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +98193,3518,Male,Loyal Customer,43,Business travel,Business,557,2,2,2,2,3,5,4,4,4,4,4,3,4,5,0,9.0,satisfied +98194,101722,Female,Loyal Customer,57,Personal Travel,Eco,986,1,5,1,3,3,5,5,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +98195,80248,Male,Loyal Customer,14,Personal Travel,Eco,1269,5,5,5,5,5,5,5,5,4,3,4,4,5,5,6,0.0,satisfied +98196,56957,Male,Loyal Customer,29,Business travel,Eco,2454,3,3,4,3,3,3,3,4,1,2,4,3,2,3,8,0.0,neutral or dissatisfied +98197,29731,Male,disloyal Customer,25,Business travel,Eco,1107,2,1,1,2,4,2,4,4,3,4,3,1,2,4,0,0.0,neutral or dissatisfied +98198,9015,Male,Loyal Customer,51,Business travel,Business,3406,4,4,4,4,3,4,5,4,4,4,4,4,4,3,60,71.0,satisfied +98199,38571,Male,Loyal Customer,69,Personal Travel,Eco,2446,3,4,3,4,3,3,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +98200,66302,Male,disloyal Customer,25,Business travel,Business,852,1,0,1,3,4,1,4,4,3,5,5,4,4,4,20,28.0,neutral or dissatisfied +98201,24754,Male,disloyal Customer,22,Business travel,Eco,447,3,5,3,3,2,3,2,2,5,5,4,5,4,2,0,1.0,neutral or dissatisfied +98202,20873,Male,Loyal Customer,25,Business travel,Eco Plus,508,4,4,1,4,4,5,4,1,4,1,4,4,4,4,139,122.0,satisfied +98203,54089,Female,Loyal Customer,34,Personal Travel,Eco,1416,1,5,1,5,1,1,1,1,3,4,4,4,4,1,0,0.0,neutral or dissatisfied +98204,32824,Male,disloyal Customer,18,Business travel,Eco,163,5,5,5,4,3,5,3,3,2,1,2,1,2,3,1,0.0,satisfied +98205,8045,Male,Loyal Customer,45,Business travel,Business,3885,0,0,0,1,4,4,5,3,3,3,3,3,3,3,0,3.0,satisfied +98206,85413,Female,disloyal Customer,33,Business travel,Business,214,3,3,3,3,4,3,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +98207,54461,Male,Loyal Customer,51,Business travel,Eco,802,4,2,2,2,4,4,4,4,3,4,3,4,5,4,18,10.0,satisfied +98208,98383,Female,Loyal Customer,47,Business travel,Business,1131,2,2,2,2,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +98209,79983,Female,Loyal Customer,64,Personal Travel,Eco,1069,4,3,4,3,3,3,4,2,2,4,2,4,2,1,0,0.0,neutral or dissatisfied +98210,87158,Male,Loyal Customer,47,Business travel,Business,946,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +98211,83398,Female,Loyal Customer,44,Business travel,Business,2093,1,1,1,1,5,4,4,3,3,4,3,3,3,3,0,7.0,satisfied +98212,98250,Female,Loyal Customer,48,Business travel,Business,2215,5,5,5,5,3,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +98213,104842,Female,Loyal Customer,56,Personal Travel,Eco,472,4,2,4,3,1,4,4,1,1,4,1,3,1,2,0,16.0,neutral or dissatisfied +98214,2753,Male,Loyal Customer,39,Business travel,Eco,372,2,5,5,5,2,2,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +98215,57875,Male,Loyal Customer,15,Personal Travel,Business,305,4,4,4,5,1,4,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +98216,107398,Female,Loyal Customer,28,Business travel,Business,3559,3,4,4,4,3,3,3,3,1,3,3,3,4,3,29,18.0,neutral or dissatisfied +98217,32067,Male,disloyal Customer,48,Business travel,Business,216,4,4,4,3,1,4,1,1,2,5,1,1,5,1,3,1.0,neutral or dissatisfied +98218,94488,Male,disloyal Customer,66,Business travel,Eco,562,1,0,1,4,4,1,4,4,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +98219,20808,Female,Loyal Customer,41,Business travel,Business,534,3,3,3,3,1,2,5,4,4,4,4,1,4,2,0,0.0,satisfied +98220,120160,Female,Loyal Customer,45,Personal Travel,Eco,2378,3,2,3,4,3,1,1,4,5,2,3,1,1,1,4,4.0,neutral or dissatisfied +98221,22773,Female,Loyal Customer,63,Business travel,Business,2889,0,5,0,4,1,2,3,1,1,1,1,4,1,3,0,0.0,satisfied +98222,21475,Female,disloyal Customer,34,Business travel,Eco,399,2,0,2,4,4,2,4,4,5,1,1,5,1,4,0,0.0,neutral or dissatisfied +98223,85245,Female,Loyal Customer,19,Personal Travel,Eco,813,3,4,4,3,4,4,4,4,4,3,3,1,4,4,7,1.0,neutral or dissatisfied +98224,6078,Male,Loyal Customer,15,Personal Travel,Eco,630,2,1,2,2,2,2,2,2,4,2,3,3,3,2,0,19.0,neutral or dissatisfied +98225,65519,Female,disloyal Customer,43,Business travel,Business,1616,2,2,2,3,5,2,5,5,3,4,4,4,4,5,25,35.0,neutral or dissatisfied +98226,8598,Female,Loyal Customer,37,Business travel,Eco Plus,109,4,1,1,1,4,4,4,4,3,3,3,1,4,4,0,0.0,neutral or dissatisfied +98227,45487,Male,disloyal Customer,23,Business travel,Eco,187,1,3,1,4,2,1,2,2,1,3,3,1,3,2,34,36.0,neutral or dissatisfied +98228,101149,Male,Loyal Customer,58,Business travel,Business,2252,3,3,3,3,5,4,5,5,5,5,5,3,5,4,4,1.0,satisfied +98229,54452,Male,Loyal Customer,56,Business travel,Business,1529,1,1,1,1,4,5,5,4,4,4,4,3,4,4,16,0.0,satisfied +98230,45242,Female,Loyal Customer,63,Personal Travel,Eco,911,3,4,3,3,5,5,4,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +98231,74324,Male,Loyal Customer,59,Business travel,Business,2957,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +98232,121119,Male,Loyal Customer,57,Business travel,Business,2402,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +98233,108220,Male,Loyal Customer,26,Personal Travel,Eco,777,4,4,4,3,1,4,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +98234,72242,Male,Loyal Customer,27,Business travel,Business,919,1,1,1,1,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +98235,86342,Female,Loyal Customer,39,Business travel,Business,2988,1,1,1,1,2,5,5,3,3,4,3,3,3,5,25,19.0,satisfied +98236,70702,Female,Loyal Customer,7,Personal Travel,Eco,837,2,1,2,3,1,2,1,1,2,5,3,2,4,1,2,12.0,neutral or dissatisfied +98237,75983,Female,Loyal Customer,34,Personal Travel,Eco,297,2,4,2,5,5,2,5,5,4,4,4,5,5,5,68,64.0,neutral or dissatisfied +98238,68945,Female,Loyal Customer,67,Personal Travel,Eco,646,3,5,3,2,4,5,2,4,4,3,4,3,4,4,7,0.0,neutral or dissatisfied +98239,58925,Female,Loyal Customer,25,Personal Travel,Eco,888,2,5,2,1,1,2,1,1,5,5,5,3,4,1,25,3.0,neutral or dissatisfied +98240,1120,Male,Loyal Customer,58,Personal Travel,Eco,354,2,4,2,1,1,2,2,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +98241,19795,Male,Loyal Customer,49,Personal Travel,Eco,578,3,5,3,1,4,3,4,4,4,2,4,3,5,4,114,115.0,neutral or dissatisfied +98242,112261,Male,Loyal Customer,38,Business travel,Business,1506,1,2,2,2,3,3,4,1,1,2,1,1,1,4,16,8.0,neutral or dissatisfied +98243,46577,Male,Loyal Customer,52,Business travel,Business,2772,0,4,0,4,3,4,5,1,1,1,1,1,1,2,73,79.0,satisfied +98244,36003,Male,Loyal Customer,68,Personal Travel,Business,399,2,1,2,4,1,3,3,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +98245,64584,Female,Loyal Customer,60,Business travel,Business,1658,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +98246,118964,Female,Loyal Customer,51,Personal Travel,Business,570,2,5,2,3,3,5,5,3,3,2,5,5,3,4,0,0.0,neutral or dissatisfied +98247,3858,Male,Loyal Customer,7,Personal Travel,Eco Plus,650,2,3,2,3,1,2,1,1,2,4,3,2,4,1,0,0.0,neutral or dissatisfied +98248,61303,Male,Loyal Customer,46,Personal Travel,Eco,853,1,4,1,3,3,1,3,3,3,1,4,2,4,3,22,15.0,neutral or dissatisfied +98249,121351,Male,Loyal Customer,38,Personal Travel,Eco,430,3,5,3,3,4,3,4,4,5,4,4,4,4,4,19,21.0,neutral or dissatisfied +98250,101816,Female,Loyal Customer,43,Business travel,Business,1521,2,5,4,5,5,2,1,2,2,2,2,3,2,1,11,0.0,neutral or dissatisfied +98251,46839,Male,Loyal Customer,39,Business travel,Eco,846,5,5,5,5,5,5,5,1,3,3,3,5,3,5,184,174.0,satisfied +98252,5041,Female,Loyal Customer,22,Business travel,Business,2857,4,1,1,1,4,4,4,4,1,2,3,1,3,4,46,51.0,neutral or dissatisfied +98253,56497,Female,Loyal Customer,41,Business travel,Business,937,4,4,4,4,2,5,4,4,4,4,4,4,4,3,59,54.0,satisfied +98254,36104,Female,Loyal Customer,20,Personal Travel,Eco,399,2,4,2,2,2,2,2,2,4,2,5,4,4,2,0,10.0,neutral or dissatisfied +98255,45863,Female,Loyal Customer,44,Business travel,Business,1809,3,3,3,3,4,4,4,5,3,5,5,4,4,4,147,135.0,satisfied +98256,120192,Male,Loyal Customer,30,Business travel,Business,2454,5,5,5,5,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +98257,87259,Female,Loyal Customer,55,Business travel,Business,3281,5,5,5,5,3,5,5,5,5,5,5,5,5,3,8,0.0,satisfied +98258,114951,Male,Loyal Customer,38,Business travel,Business,417,5,2,5,5,5,4,4,4,4,4,4,3,4,3,37,29.0,satisfied +98259,7206,Female,Loyal Customer,57,Business travel,Business,139,0,5,0,5,2,5,5,1,1,1,1,3,1,4,20,35.0,satisfied +98260,86033,Female,Loyal Customer,32,Personal Travel,Eco,528,2,4,2,4,4,2,4,4,3,3,4,4,4,4,13,8.0,neutral or dissatisfied +98261,25945,Female,Loyal Customer,59,Personal Travel,Eco Plus,594,2,4,2,4,1,4,3,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +98262,63945,Female,Loyal Customer,70,Personal Travel,Eco,1172,4,4,4,1,2,4,4,3,3,4,3,5,3,3,0,0.0,neutral or dissatisfied +98263,87471,Female,disloyal Customer,45,Business travel,Business,373,4,4,4,2,5,4,5,5,5,3,5,3,5,5,12,19.0,satisfied +98264,65663,Male,Loyal Customer,29,Business travel,Business,926,2,2,2,2,4,4,4,4,3,2,4,4,4,4,0,18.0,satisfied +98265,4190,Male,Loyal Customer,31,Business travel,Business,1783,4,4,4,4,2,2,2,2,3,4,4,5,5,2,7,0.0,satisfied +98266,122700,Female,Loyal Customer,52,Personal Travel,Eco,361,2,2,2,3,1,4,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +98267,120466,Female,Loyal Customer,52,Personal Travel,Eco,337,1,3,1,3,1,2,2,5,5,2,2,2,5,2,167,161.0,neutral or dissatisfied +98268,127207,Male,Loyal Customer,44,Business travel,Eco Plus,338,4,2,3,2,4,4,4,4,5,1,3,5,3,4,0,0.0,satisfied +98269,37511,Female,disloyal Customer,27,Business travel,Eco,989,3,3,3,3,1,3,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +98270,40069,Male,disloyal Customer,27,Business travel,Eco,493,3,0,3,3,1,3,1,1,3,4,3,4,5,1,0,0.0,neutral or dissatisfied +98271,27586,Female,Loyal Customer,14,Personal Travel,Eco,954,1,1,1,3,1,1,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +98272,66532,Female,disloyal Customer,38,Business travel,Business,733,4,4,4,2,5,4,4,5,5,2,5,3,4,5,69,65.0,neutral or dissatisfied +98273,89348,Male,Loyal Customer,35,Business travel,Business,1587,4,4,4,4,1,2,2,5,5,5,5,4,5,3,0,7.0,satisfied +98274,105949,Female,disloyal Customer,22,Business travel,Eco,1248,3,3,3,1,4,3,4,4,3,4,4,3,4,4,6,3.0,neutral or dissatisfied +98275,70098,Male,Loyal Customer,50,Business travel,Business,3822,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +98276,26619,Male,Loyal Customer,22,Business travel,Business,2735,2,2,2,2,4,4,4,4,3,4,5,2,2,4,0,1.0,satisfied +98277,39809,Male,Loyal Customer,38,Business travel,Business,272,3,3,3,3,1,3,3,4,4,4,4,2,4,3,0,0.0,satisfied +98278,36953,Female,Loyal Customer,39,Business travel,Business,759,5,5,5,5,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +98279,114788,Male,Loyal Customer,61,Business travel,Business,2695,2,4,4,4,3,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +98280,4825,Male,Loyal Customer,46,Business travel,Business,2983,1,4,4,4,4,3,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +98281,106577,Female,Loyal Customer,27,Personal Travel,Eco,1506,4,5,4,1,5,4,5,5,4,2,1,1,3,5,1,6.0,neutral or dissatisfied +98282,90723,Female,disloyal Customer,36,Business travel,Business,581,3,3,3,2,4,3,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +98283,27934,Female,Loyal Customer,31,Business travel,Eco,1770,5,2,2,2,5,5,5,5,1,2,4,4,2,5,9,0.0,satisfied +98284,90157,Male,Loyal Customer,58,Personal Travel,Eco,1145,3,4,3,3,3,3,3,3,3,5,5,3,4,3,1,0.0,neutral or dissatisfied +98285,24543,Female,Loyal Customer,42,Business travel,Eco,874,4,1,1,1,5,5,4,4,4,4,4,4,4,2,0,1.0,satisfied +98286,123031,Male,Loyal Customer,53,Business travel,Business,2819,5,5,5,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +98287,116658,Female,Loyal Customer,57,Business travel,Eco Plus,308,3,5,4,5,4,3,3,3,3,3,3,3,3,2,11,13.0,neutral or dissatisfied +98288,111739,Female,Loyal Customer,38,Business travel,Business,2938,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,1.0,satisfied +98289,24475,Female,Loyal Customer,25,Business travel,Business,1897,2,5,5,5,2,2,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +98290,106147,Male,Loyal Customer,39,Business travel,Business,436,5,5,5,5,4,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +98291,80633,Male,Loyal Customer,44,Business travel,Business,282,2,4,4,4,5,3,3,2,2,2,2,3,2,3,4,7.0,neutral or dissatisfied +98292,87798,Female,disloyal Customer,33,Business travel,Eco,214,1,4,1,3,5,1,5,5,1,4,3,3,4,5,0,0.0,neutral or dissatisfied +98293,109128,Female,Loyal Customer,58,Business travel,Business,2458,1,1,4,1,5,5,4,5,5,5,5,4,5,4,11,0.0,satisfied +98294,82345,Male,Loyal Customer,59,Business travel,Business,2172,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +98295,12921,Male,Loyal Customer,53,Business travel,Business,163,5,5,5,5,2,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +98296,74834,Female,Loyal Customer,46,Business travel,Business,1797,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +98297,12184,Female,Loyal Customer,66,Business travel,Business,2204,2,2,2,2,4,3,4,5,5,5,5,1,5,1,0,0.0,satisfied +98298,30255,Male,disloyal Customer,30,Business travel,Eco,836,0,0,0,3,3,0,4,3,3,4,4,1,1,3,0,12.0,satisfied +98299,62867,Male,Loyal Customer,25,Business travel,Business,2446,1,1,1,1,5,5,5,5,3,3,3,3,5,5,1,0.0,satisfied +98300,47387,Male,disloyal Customer,32,Business travel,Eco,541,1,4,1,4,3,1,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +98301,21927,Female,disloyal Customer,21,Business travel,Eco,448,1,2,1,2,4,1,4,4,4,2,3,4,2,4,2,0.0,neutral or dissatisfied +98302,99977,Female,Loyal Customer,36,Business travel,Business,220,2,2,2,2,3,4,5,5,5,5,4,4,5,3,0,0.0,satisfied +98303,21896,Male,Loyal Customer,42,Business travel,Business,448,5,5,5,5,3,2,4,4,4,4,4,3,4,1,0,0.0,satisfied +98304,31914,Female,Loyal Customer,53,Business travel,Business,163,1,1,1,1,4,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +98305,107458,Male,Loyal Customer,21,Personal Travel,Eco Plus,523,4,4,4,4,4,4,4,4,3,3,5,3,5,4,0,0.0,neutral or dissatisfied +98306,71195,Female,Loyal Customer,50,Business travel,Business,2610,3,3,3,3,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +98307,124841,Female,Loyal Customer,48,Personal Travel,Eco,280,1,2,1,2,5,3,2,5,5,1,5,2,5,1,0,9.0,neutral or dissatisfied +98308,116507,Female,Loyal Customer,69,Personal Travel,Eco,337,2,5,3,1,5,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +98309,3165,Male,Loyal Customer,26,Business travel,Business,585,3,3,2,3,5,5,5,5,3,5,5,5,5,5,0,0.0,satisfied +98310,47191,Male,Loyal Customer,57,Business travel,Eco,965,1,2,5,2,1,1,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +98311,108334,Female,Loyal Customer,21,Business travel,Business,1728,2,2,2,2,2,2,2,2,2,3,1,4,1,2,29,27.0,neutral or dissatisfied +98312,70283,Male,disloyal Customer,11,Business travel,Eco,852,3,3,3,3,1,3,1,1,4,2,3,3,4,1,0,3.0,neutral or dissatisfied +98313,91013,Female,Loyal Customer,25,Personal Travel,Eco,240,3,4,3,3,3,3,3,3,4,4,5,3,4,3,0,8.0,neutral or dissatisfied +98314,96993,Male,Loyal Customer,16,Personal Travel,Eco,794,1,5,1,3,3,1,3,3,3,3,4,4,5,3,0,9.0,neutral or dissatisfied +98315,69576,Female,disloyal Customer,25,Business travel,Eco,2586,3,3,3,2,3,1,4,4,3,1,3,4,4,4,0,0.0,neutral or dissatisfied +98316,10635,Male,Loyal Customer,45,Business travel,Business,316,1,1,4,1,2,5,5,4,4,4,4,3,4,5,64,53.0,satisfied +98317,108699,Male,disloyal Customer,18,Business travel,Eco,577,2,5,2,3,1,2,1,1,4,2,3,5,2,1,0,0.0,neutral or dissatisfied +98318,90453,Male,Loyal Customer,43,Business travel,Business,1897,5,5,4,5,3,5,4,4,4,4,4,3,4,3,14,6.0,satisfied +98319,65596,Female,Loyal Customer,42,Business travel,Eco,237,2,2,2,2,5,2,3,2,2,2,2,1,2,2,30,31.0,neutral or dissatisfied +98320,32310,Female,Loyal Customer,56,Business travel,Eco,163,4,1,1,1,4,5,4,4,4,4,4,3,4,2,0,0.0,satisfied +98321,85940,Male,Loyal Customer,54,Business travel,Business,2553,2,2,1,2,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +98322,44701,Male,Loyal Customer,13,Personal Travel,Eco,67,1,4,0,1,4,0,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +98323,32088,Female,Loyal Customer,61,Business travel,Business,3930,4,3,4,4,5,5,1,5,5,5,3,5,5,1,0,0.0,satisfied +98324,68198,Female,disloyal Customer,25,Business travel,Business,631,3,2,3,4,5,3,5,5,2,2,4,1,4,5,0,0.0,neutral or dissatisfied +98325,53552,Male,disloyal Customer,27,Business travel,Eco,1956,3,3,3,3,1,3,1,1,4,2,3,5,1,1,2,0.0,neutral or dissatisfied +98326,32258,Female,Loyal Customer,57,Business travel,Eco,163,4,4,4,4,5,5,1,4,4,4,4,3,4,2,32,37.0,satisfied +98327,38453,Female,Loyal Customer,51,Business travel,Eco,1226,2,2,5,2,3,3,5,2,2,2,2,3,2,4,0,0.0,satisfied +98328,120955,Male,Loyal Customer,31,Business travel,Eco,992,1,5,5,5,1,1,1,1,4,2,2,2,2,1,0,0.0,neutral or dissatisfied +98329,124000,Female,Loyal Customer,43,Business travel,Eco,184,3,1,1,1,3,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +98330,41445,Male,Loyal Customer,31,Business travel,Business,1334,1,1,1,1,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +98331,87265,Male,Loyal Customer,25,Business travel,Business,3904,4,4,1,4,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +98332,74941,Male,Loyal Customer,14,Business travel,Eco,2475,2,3,3,3,2,2,2,2,2,4,2,1,4,2,32,10.0,neutral or dissatisfied +98333,92047,Male,disloyal Customer,30,Business travel,Business,1535,2,2,2,1,2,2,2,2,5,2,4,4,5,2,17,9.0,neutral or dissatisfied +98334,19359,Female,Loyal Customer,24,Business travel,Eco,692,4,1,1,1,4,4,4,4,3,3,4,2,1,4,5,0.0,satisfied +98335,45005,Male,Loyal Customer,39,Business travel,Eco,118,1,2,2,2,1,1,1,1,1,4,4,1,3,1,0,2.0,neutral or dissatisfied +98336,18896,Male,Loyal Customer,30,Business travel,Business,2733,3,4,4,4,3,3,3,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +98337,108678,Female,Loyal Customer,54,Business travel,Business,577,3,3,3,3,2,5,5,4,4,5,4,5,4,4,10,1.0,satisfied +98338,83871,Female,Loyal Customer,21,Personal Travel,Eco Plus,425,2,1,2,3,1,2,1,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +98339,41851,Male,disloyal Customer,22,Business travel,Eco,300,2,5,2,3,4,2,4,4,3,2,1,4,5,4,0,0.0,neutral or dissatisfied +98340,84097,Female,Loyal Customer,55,Business travel,Business,3578,1,1,1,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +98341,63376,Male,Loyal Customer,17,Personal Travel,Eco,337,1,4,3,5,4,3,4,4,5,3,4,4,4,4,2,0.0,neutral or dissatisfied +98342,64911,Female,Loyal Customer,39,Business travel,Business,3684,2,5,5,5,3,2,3,2,3,4,3,3,3,3,182,160.0,neutral or dissatisfied +98343,81086,Male,Loyal Customer,36,Business travel,Business,3739,2,1,4,4,5,1,1,2,2,2,2,2,2,4,57,88.0,neutral or dissatisfied +98344,20556,Male,disloyal Customer,28,Business travel,Eco,565,3,4,3,3,1,3,1,1,1,1,3,2,4,1,29,9.0,neutral or dissatisfied +98345,95478,Male,Loyal Customer,50,Business travel,Business,3077,4,4,4,4,5,5,4,4,4,4,4,3,4,4,5,0.0,satisfied +98346,15381,Male,Loyal Customer,31,Business travel,Eco,306,5,3,3,3,5,5,5,5,5,2,1,2,2,5,4,0.0,satisfied +98347,29662,Male,Loyal Customer,37,Personal Travel,Eco,1448,4,5,4,3,4,4,1,4,3,4,3,5,3,4,14,1.0,neutral or dissatisfied +98348,94529,Female,Loyal Customer,60,Business travel,Business,189,3,3,4,3,5,5,4,5,5,5,4,5,5,3,0,0.0,satisfied +98349,94564,Female,Loyal Customer,41,Business travel,Business,3311,1,1,1,1,2,4,5,4,4,4,5,5,4,3,34,28.0,satisfied +98350,2380,Female,Loyal Customer,40,Business travel,Business,1924,5,5,5,5,5,5,5,5,5,5,5,5,5,4,8,0.0,satisfied +98351,121743,Male,Loyal Customer,51,Personal Travel,Eco,1475,3,5,3,3,3,3,3,3,5,2,4,4,4,3,0,4.0,neutral or dissatisfied +98352,8486,Female,Loyal Customer,44,Business travel,Business,3390,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +98353,96060,Female,Loyal Customer,44,Business travel,Eco,395,5,5,5,5,3,2,4,5,5,5,5,5,5,3,0,0.0,satisfied +98354,33352,Male,Loyal Customer,55,Business travel,Business,2409,2,2,5,5,3,2,3,2,2,2,2,2,2,4,44,18.0,neutral or dissatisfied +98355,110917,Female,Loyal Customer,16,Business travel,Business,581,2,2,2,2,2,2,2,2,3,1,3,1,4,2,20,16.0,neutral or dissatisfied +98356,65330,Male,Loyal Customer,24,Business travel,Business,631,2,2,2,2,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +98357,10555,Female,Loyal Customer,48,Business travel,Business,3194,1,1,1,1,4,4,4,4,4,4,4,4,4,4,5,9.0,satisfied +98358,77391,Male,Loyal Customer,9,Personal Travel,Eco,590,2,4,2,2,5,2,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +98359,62239,Female,Loyal Customer,26,Personal Travel,Eco,2565,2,3,2,3,5,2,5,5,4,2,3,2,4,5,1,0.0,neutral or dissatisfied +98360,14485,Male,Loyal Customer,11,Personal Travel,Eco,541,5,1,5,2,1,5,1,1,4,3,3,4,2,1,0,3.0,satisfied +98361,92827,Male,disloyal Customer,38,Business travel,Business,1187,1,1,1,3,3,1,3,3,2,4,3,2,3,3,0,0.0,neutral or dissatisfied +98362,87579,Male,Loyal Customer,44,Personal Travel,Eco,432,3,3,3,3,5,3,5,5,2,2,3,2,4,5,19,11.0,neutral or dissatisfied +98363,4516,Male,Loyal Customer,53,Business travel,Eco Plus,551,4,5,5,5,4,4,4,4,1,1,3,1,4,4,108,123.0,neutral or dissatisfied +98364,32619,Female,Loyal Customer,46,Business travel,Eco,102,2,1,1,1,2,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +98365,59758,Male,disloyal Customer,35,Business travel,Business,927,4,3,3,3,4,3,4,4,4,5,5,5,5,4,5,6.0,neutral or dissatisfied +98366,119411,Female,Loyal Customer,63,Business travel,Eco,399,2,5,5,5,4,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +98367,5692,Male,Loyal Customer,51,Business travel,Eco,234,1,5,2,5,1,1,1,1,1,1,3,2,3,1,0,15.0,neutral or dissatisfied +98368,17992,Male,disloyal Customer,27,Business travel,Eco,618,2,3,2,3,1,2,1,1,4,3,4,2,3,1,55,43.0,neutral or dissatisfied +98369,88732,Female,Loyal Customer,25,Personal Travel,Eco,581,4,5,4,4,4,4,4,4,5,2,4,5,4,4,2,4.0,satisfied +98370,52095,Male,Loyal Customer,50,Personal Travel,Eco,639,3,5,4,1,3,4,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +98371,116455,Male,Loyal Customer,49,Personal Travel,Eco,371,1,2,1,4,3,1,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +98372,111058,Female,Loyal Customer,49,Personal Travel,Eco,319,1,1,3,3,2,4,3,5,5,3,5,2,5,4,0,0.0,neutral or dissatisfied +98373,38018,Female,Loyal Customer,54,Business travel,Business,3280,3,5,5,5,5,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +98374,65254,Male,Loyal Customer,61,Business travel,Eco Plus,190,3,1,1,1,3,3,3,3,1,1,3,1,3,3,34,29.0,neutral or dissatisfied +98375,83833,Male,Loyal Customer,43,Business travel,Business,2198,3,4,4,4,4,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +98376,77414,Male,Loyal Customer,45,Personal Travel,Eco,588,2,5,2,4,3,2,1,3,2,2,1,4,5,3,0,0.0,neutral or dissatisfied +98377,13348,Female,Loyal Customer,36,Business travel,Business,3650,1,4,4,4,4,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +98378,45850,Female,Loyal Customer,60,Business travel,Eco Plus,391,4,1,1,1,2,1,4,4,4,4,4,3,4,1,0,0.0,satisfied +98379,34637,Female,Loyal Customer,40,Business travel,Eco,427,4,5,5,5,4,4,4,4,2,1,2,3,4,4,1,0.0,satisfied +98380,125692,Female,disloyal Customer,30,Business travel,Eco,899,1,2,2,3,2,2,2,2,3,4,4,3,3,2,23,21.0,neutral or dissatisfied +98381,17072,Female,Loyal Customer,66,Personal Travel,Eco,282,1,4,4,4,4,5,4,3,3,4,4,3,3,4,0,0.0,neutral or dissatisfied +98382,49881,Female,disloyal Customer,24,Business travel,Eco,109,4,2,4,4,3,4,3,3,4,4,3,3,4,3,0,7.0,neutral or dissatisfied +98383,111547,Male,disloyal Customer,36,Business travel,Eco,883,3,3,3,3,2,3,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +98384,124189,Male,Loyal Customer,60,Personal Travel,Business,2176,4,5,4,1,2,2,1,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +98385,45555,Male,Loyal Customer,13,Business travel,Business,3771,5,5,5,5,3,3,3,3,3,1,1,3,3,3,0,0.0,satisfied +98386,128328,Female,Loyal Customer,41,Business travel,Business,2951,2,2,2,2,2,4,4,2,2,2,2,5,2,4,95,95.0,satisfied +98387,9927,Female,disloyal Customer,34,Business travel,Business,357,4,4,4,3,1,4,1,1,5,5,5,4,5,1,13,21.0,neutral or dissatisfied +98388,48707,Male,Loyal Customer,59,Business travel,Business,1552,1,1,1,1,2,5,4,5,5,5,5,3,5,4,36,31.0,satisfied +98389,61321,Female,Loyal Customer,10,Business travel,Eco Plus,862,2,3,3,3,2,2,2,2,4,4,4,4,3,2,37,18.0,neutral or dissatisfied +98390,900,Male,Loyal Customer,40,Business travel,Business,2582,1,4,4,4,1,2,2,1,1,1,1,2,1,1,0,2.0,neutral or dissatisfied +98391,114397,Female,Loyal Customer,59,Business travel,Business,2212,3,1,3,3,4,5,4,5,5,5,5,4,5,5,55,44.0,satisfied +98392,127361,Male,Loyal Customer,29,Business travel,Eco Plus,507,4,5,5,5,4,4,4,4,3,1,4,3,3,4,0,0.0,neutral or dissatisfied +98393,87623,Female,Loyal Customer,60,Business travel,Business,1888,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +98394,60357,Female,disloyal Customer,27,Business travel,Business,1452,3,3,3,3,1,3,4,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +98395,66095,Male,Loyal Customer,64,Personal Travel,Eco Plus,1055,3,3,3,3,2,3,2,2,4,3,3,2,3,2,20,17.0,neutral or dissatisfied +98396,115532,Female,disloyal Customer,27,Business travel,Business,337,2,2,2,2,1,2,1,1,3,3,5,3,5,1,6,0.0,neutral or dissatisfied +98397,39660,Male,disloyal Customer,23,Business travel,Business,224,0,0,0,3,1,0,1,1,2,5,2,3,4,1,10,13.0,satisfied +98398,64228,Male,disloyal Customer,39,Business travel,Business,1660,2,2,2,1,5,2,5,5,5,4,4,4,4,5,0,6.0,neutral or dissatisfied +98399,87157,Female,Loyal Customer,44,Personal Travel,Business,946,3,2,3,3,4,3,4,5,5,3,5,2,5,4,15,12.0,neutral or dissatisfied +98400,66044,Male,Loyal Customer,58,Business travel,Business,1055,4,4,4,4,4,5,5,4,4,4,4,4,4,4,10,0.0,satisfied +98401,120935,Male,Loyal Customer,57,Business travel,Business,2321,2,2,2,2,4,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +98402,76961,Female,disloyal Customer,17,Business travel,Eco,1990,1,1,1,4,3,1,3,3,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +98403,58789,Female,Loyal Customer,37,Business travel,Eco,864,1,1,3,1,1,2,1,1,2,3,4,4,3,1,0,0.0,neutral or dissatisfied +98404,47662,Male,disloyal Customer,28,Business travel,Eco,1235,4,4,4,2,4,4,4,4,1,4,1,4,4,4,0,0.0,neutral or dissatisfied +98405,69812,Female,Loyal Customer,46,Business travel,Business,2699,5,2,5,5,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +98406,3312,Female,Loyal Customer,51,Business travel,Business,240,4,4,4,4,4,4,4,4,4,4,4,4,4,3,2,0.0,satisfied +98407,87273,Male,Loyal Customer,56,Business travel,Business,2903,3,3,2,3,4,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +98408,101613,Female,Loyal Customer,39,Business travel,Business,3848,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +98409,121151,Female,disloyal Customer,36,Business travel,Eco,853,2,2,2,3,2,4,4,3,4,2,2,4,3,4,0,34.0,neutral or dissatisfied +98410,14991,Female,Loyal Customer,47,Business travel,Business,3781,4,4,4,4,3,3,4,3,3,3,3,2,3,3,0,0.0,satisfied +98411,93397,Male,Loyal Customer,38,Business travel,Business,671,1,1,1,1,2,4,4,4,4,4,4,5,4,4,24,22.0,satisfied +98412,1544,Female,Loyal Customer,45,Business travel,Business,1833,2,2,2,2,4,2,3,2,2,2,2,5,2,4,69,99.0,satisfied +98413,64819,Male,Loyal Customer,48,Business travel,Business,3873,4,2,4,2,2,2,3,4,4,4,4,1,4,3,0,4.0,neutral or dissatisfied +98414,71146,Male,Loyal Customer,40,Business travel,Business,2121,1,1,1,1,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +98415,55057,Female,disloyal Customer,8,Business travel,Eco,1635,2,2,2,3,4,2,4,4,3,5,5,5,4,4,6,0.0,neutral or dissatisfied +98416,35933,Female,Loyal Customer,67,Personal Travel,Eco,2381,3,2,2,3,5,3,3,1,1,2,1,2,1,4,85,61.0,neutral or dissatisfied +98417,104632,Male,Loyal Customer,27,Personal Travel,Eco,861,2,5,2,1,5,2,5,5,3,5,4,4,4,5,7,30.0,neutral or dissatisfied +98418,110939,Female,Loyal Customer,50,Personal Travel,Eco,581,1,4,1,1,4,5,4,1,1,1,1,3,1,3,6,0.0,neutral or dissatisfied +98419,80290,Male,Loyal Customer,56,Business travel,Business,1522,1,1,1,1,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +98420,105798,Female,Loyal Customer,16,Personal Travel,Eco,787,2,3,2,4,1,2,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +98421,95154,Male,Loyal Customer,57,Personal Travel,Eco,277,2,3,3,4,1,3,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +98422,26534,Male,Loyal Customer,60,Business travel,Business,705,4,4,4,4,3,3,5,4,4,4,4,2,4,3,0,0.0,satisfied +98423,129507,Female,Loyal Customer,29,Business travel,Eco,1744,5,4,1,4,5,5,5,5,1,4,4,5,3,5,0,3.0,satisfied +98424,6969,Male,disloyal Customer,26,Business travel,Business,299,2,0,2,3,3,2,3,3,4,2,4,4,4,3,0,8.0,neutral or dissatisfied +98425,106515,Female,Loyal Customer,59,Business travel,Eco,271,1,4,4,4,2,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +98426,26763,Female,Loyal Customer,22,Personal Travel,Eco,859,4,4,4,3,3,4,3,3,5,3,4,5,5,3,55,52.0,neutral or dissatisfied +98427,81078,Female,Loyal Customer,45,Business travel,Business,931,2,2,2,2,5,4,5,2,2,2,2,4,2,4,3,0.0,satisfied +98428,36868,Male,Loyal Customer,55,Personal Travel,Eco,273,4,3,4,4,2,4,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +98429,20158,Female,disloyal Customer,17,Business travel,Eco,403,2,0,2,2,5,2,5,5,2,4,4,2,2,5,4,0.0,neutral or dissatisfied +98430,37987,Female,Loyal Customer,28,Business travel,Business,2751,3,3,3,3,5,5,5,5,4,5,3,2,4,5,0,0.0,satisfied +98431,46654,Male,Loyal Customer,33,Business travel,Business,2006,0,4,0,1,4,4,4,4,1,3,5,4,3,4,70,102.0,satisfied +98432,73144,Male,Loyal Customer,53,Personal Travel,Eco,1068,3,1,3,4,5,3,5,5,4,3,4,2,4,5,0,19.0,neutral or dissatisfied +98433,1310,Male,Loyal Customer,55,Business travel,Business,3611,0,5,0,2,4,5,4,4,4,4,4,3,4,3,12,8.0,satisfied +98434,43421,Female,Loyal Customer,13,Personal Travel,Eco Plus,436,1,1,1,4,2,1,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +98435,93157,Male,Loyal Customer,52,Business travel,Business,3984,2,2,2,2,1,3,2,5,5,5,5,2,5,3,0,3.0,satisfied +98436,83660,Female,Loyal Customer,17,Business travel,Business,3812,2,2,2,2,5,4,5,5,3,3,4,3,4,5,0,0.0,satisfied +98437,78040,Female,Loyal Customer,13,Personal Travel,Eco,332,3,4,2,2,5,2,1,5,5,3,4,3,4,5,1,0.0,neutral or dissatisfied +98438,69944,Male,Loyal Customer,36,Business travel,Business,2174,5,5,5,5,5,3,5,4,4,4,4,4,4,3,21,0.0,satisfied +98439,95465,Female,Loyal Customer,47,Business travel,Business,1995,4,4,4,4,3,4,4,2,2,2,2,5,2,4,57,47.0,satisfied +98440,6011,Male,disloyal Customer,22,Business travel,Eco,630,1,3,1,3,1,1,1,1,4,1,2,2,2,1,0,46.0,neutral or dissatisfied +98441,123375,Male,Loyal Customer,42,Personal Travel,Eco,644,3,4,2,3,3,2,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +98442,128469,Female,Loyal Customer,49,Personal Travel,Eco,647,3,5,3,1,5,5,2,5,5,3,5,1,5,4,13,19.0,neutral or dissatisfied +98443,24538,Female,Loyal Customer,43,Business travel,Eco,874,5,2,2,2,1,3,3,5,5,5,5,1,5,4,0,0.0,satisfied +98444,42857,Female,Loyal Customer,10,Personal Travel,Eco,328,1,0,1,2,4,1,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +98445,128821,Male,Loyal Customer,47,Business travel,Eco,2586,2,4,4,4,2,2,2,4,4,3,4,2,2,2,0,0.0,neutral or dissatisfied +98446,20953,Female,Loyal Customer,45,Business travel,Eco,689,3,5,5,5,1,4,5,3,3,3,3,3,3,3,0,,satisfied +98447,2574,Male,disloyal Customer,24,Business travel,Business,227,4,3,5,2,4,5,4,4,1,2,3,5,1,4,0,0.0,satisfied +98448,50452,Female,Loyal Customer,40,Business travel,Eco,109,4,5,5,5,4,4,4,4,5,3,2,4,4,4,3,5.0,satisfied +98449,57021,Female,Loyal Customer,28,Personal Travel,Eco,2454,3,2,3,3,3,5,5,1,3,3,4,5,1,5,98,70.0,neutral or dissatisfied +98450,69383,Male,disloyal Customer,19,Business travel,Eco,1096,3,3,3,4,3,3,3,3,4,2,3,2,4,3,0,0.0,neutral or dissatisfied +98451,124392,Male,Loyal Customer,64,Personal Travel,Eco,808,3,4,3,3,5,3,3,5,1,1,3,1,3,5,0,0.0,neutral or dissatisfied +98452,66714,Female,Loyal Customer,8,Personal Travel,Eco,978,0,4,0,2,4,0,1,4,4,2,4,3,5,4,12,0.0,satisfied +98453,87121,Female,Loyal Customer,26,Personal Travel,Eco,594,4,4,4,5,4,4,4,4,4,1,1,1,4,4,0,1.0,neutral or dissatisfied +98454,110798,Male,Loyal Customer,56,Personal Travel,Eco,997,4,4,4,4,2,4,1,2,1,2,4,3,4,2,21,18.0,neutral or dissatisfied +98455,117767,Female,Loyal Customer,57,Personal Travel,Eco,1670,3,4,3,4,5,2,3,3,3,3,3,5,3,1,5,0.0,neutral or dissatisfied +98456,66211,Female,Loyal Customer,58,Business travel,Eco,460,4,2,2,2,2,2,1,4,4,4,4,3,4,2,31,92.0,neutral or dissatisfied +98457,79699,Male,Loyal Customer,22,Personal Travel,Eco,712,2,4,3,1,1,3,1,1,3,2,4,3,5,1,0,25.0,neutral or dissatisfied +98458,5149,Male,Loyal Customer,51,Business travel,Business,622,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +98459,18284,Male,Loyal Customer,50,Business travel,Business,705,1,1,1,1,5,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +98460,17417,Female,Loyal Customer,18,Business travel,Business,351,3,1,1,1,3,3,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +98461,118262,Male,Loyal Customer,28,Personal Travel,Eco,1788,3,5,3,3,3,3,3,3,5,4,3,4,5,3,24,11.0,neutral or dissatisfied +98462,95954,Female,Loyal Customer,58,Business travel,Business,2076,1,2,2,2,1,2,3,1,1,1,1,4,1,2,81,78.0,neutral or dissatisfied +98463,25526,Female,Loyal Customer,64,Personal Travel,Eco,481,3,4,2,4,2,3,5,2,2,2,2,5,2,5,33,16.0,neutral or dissatisfied +98464,41497,Male,Loyal Customer,56,Business travel,Business,1428,4,4,4,4,4,2,3,5,5,5,5,5,5,5,5,16.0,satisfied +98465,71629,Female,Loyal Customer,50,Business travel,Eco,720,4,4,4,4,2,2,5,4,4,4,4,2,4,1,0,0.0,satisfied +98466,42137,Female,disloyal Customer,28,Business travel,Business,838,3,3,3,5,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +98467,86114,Female,Loyal Customer,52,Business travel,Business,1663,3,3,3,3,4,5,4,5,5,5,5,4,5,5,40,36.0,satisfied +98468,65709,Female,Loyal Customer,33,Business travel,Business,1061,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +98469,84675,Female,Loyal Customer,47,Business travel,Business,2182,3,3,3,3,5,5,5,5,4,4,5,5,3,5,143,117.0,satisfied +98470,66053,Male,Loyal Customer,48,Business travel,Business,655,1,1,1,1,4,3,3,4,4,4,4,3,4,3,6,37.0,satisfied +98471,13595,Female,Loyal Customer,65,Personal Travel,Eco,106,2,4,2,5,4,4,4,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +98472,26589,Female,Loyal Customer,49,Business travel,Eco,270,5,5,5,5,1,5,4,5,5,5,5,4,5,2,13,14.0,satisfied +98473,123656,Female,Loyal Customer,51,Business travel,Business,214,3,3,3,3,3,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +98474,117792,Female,Loyal Customer,42,Business travel,Business,328,5,2,2,2,1,3,4,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +98475,35457,Male,Loyal Customer,7,Personal Travel,Eco,1069,3,5,3,5,2,3,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +98476,98841,Male,Loyal Customer,45,Business travel,Business,2025,4,4,2,4,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +98477,83010,Female,Loyal Customer,59,Business travel,Business,957,4,4,4,4,5,5,5,5,5,5,5,3,5,5,81,67.0,satisfied +98478,129202,Female,disloyal Customer,26,Business travel,Business,2419,5,5,5,4,2,5,2,2,4,2,3,4,5,2,0,0.0,satisfied +98479,39980,Male,Loyal Customer,61,Personal Travel,Eco,1404,3,1,3,4,4,3,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +98480,26036,Female,Loyal Customer,61,Business travel,Eco Plus,321,2,3,3,3,3,2,2,2,2,2,2,3,2,2,10,12.0,neutral or dissatisfied +98481,1986,Male,Loyal Customer,27,Personal Travel,Eco,190,3,3,3,2,4,3,4,4,4,3,2,4,2,4,0,0.0,neutral or dissatisfied +98482,125907,Female,Loyal Customer,14,Personal Travel,Eco,920,1,4,0,3,5,0,5,5,4,4,5,5,5,5,12,0.0,neutral or dissatisfied +98483,107789,Female,Loyal Customer,41,Business travel,Business,1545,4,4,5,4,2,4,5,3,3,4,3,5,3,3,51,43.0,satisfied +98484,84746,Male,Loyal Customer,25,Business travel,Business,3923,5,5,5,5,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +98485,98780,Male,Loyal Customer,53,Business travel,Business,630,2,2,2,2,2,2,2,4,3,5,4,2,5,2,203,185.0,satisfied +98486,54631,Female,Loyal Customer,35,Business travel,Eco,964,4,5,5,5,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +98487,93280,Female,Loyal Customer,68,Personal Travel,Eco,806,3,1,3,4,1,3,3,3,3,3,3,4,3,4,10,4.0,neutral or dissatisfied +98488,48434,Female,Loyal Customer,52,Business travel,Eco,850,4,3,3,3,2,2,4,5,5,4,5,4,5,3,61,66.0,satisfied +98489,92885,Male,Loyal Customer,56,Business travel,Business,2287,2,2,2,2,5,5,5,5,5,4,4,3,5,4,0,12.0,satisfied +98490,13505,Male,Loyal Customer,79,Business travel,Eco,106,5,4,4,4,5,5,5,5,1,1,4,5,5,5,0,0.0,satisfied +98491,13898,Male,Loyal Customer,58,Business travel,Business,153,0,4,0,1,5,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +98492,84778,Male,disloyal Customer,12,Business travel,Eco,547,2,5,2,3,5,2,5,5,4,2,5,4,5,5,1,1.0,neutral or dissatisfied +98493,28021,Female,Loyal Customer,23,Business travel,Business,763,3,4,1,4,3,3,3,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +98494,31052,Female,Loyal Customer,57,Business travel,Eco,775,2,1,1,1,2,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +98495,119950,Female,Loyal Customer,28,Business travel,Eco,868,3,1,1,1,3,3,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +98496,93307,Male,Loyal Customer,35,Business travel,Business,1733,1,1,1,1,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +98497,104466,Male,Loyal Customer,54,Personal Travel,Eco,1123,3,1,3,4,1,3,1,1,4,3,2,2,3,1,0,0.0,neutral or dissatisfied +98498,33838,Female,Loyal Customer,58,Business travel,Eco,1609,4,3,3,3,4,3,4,4,4,4,4,4,4,2,75,68.0,satisfied +98499,11804,Male,Loyal Customer,50,Personal Travel,Eco Plus,429,4,1,4,3,5,4,3,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +98500,100313,Male,disloyal Customer,50,Business travel,Business,1079,3,3,3,3,5,3,5,5,2,3,2,1,2,5,14,26.0,neutral or dissatisfied +98501,48058,Female,Loyal Customer,61,Personal Travel,Eco,896,1,5,1,3,3,4,5,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +98502,21033,Male,Loyal Customer,50,Business travel,Business,3541,2,2,2,2,5,2,2,5,5,5,5,4,5,4,11,23.0,satisfied +98503,62443,Male,Loyal Customer,52,Business travel,Business,1744,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +98504,90256,Male,Loyal Customer,50,Business travel,Business,3116,4,5,5,5,2,3,3,4,4,4,4,4,4,1,7,0.0,neutral or dissatisfied +98505,7452,Male,Loyal Customer,47,Business travel,Business,552,1,1,1,1,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +98506,52264,Male,Loyal Customer,30,Business travel,Business,370,2,2,2,2,5,4,5,5,5,3,3,2,4,5,23,27.0,satisfied +98507,113132,Male,Loyal Customer,42,Personal Travel,Eco Plus,543,3,4,3,3,1,3,3,1,5,4,5,4,5,1,17,10.0,neutral or dissatisfied +98508,13266,Female,Loyal Customer,15,Personal Travel,Eco,657,4,4,5,3,2,5,2,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +98509,53514,Male,Loyal Customer,61,Personal Travel,Eco,2419,0,5,0,4,4,0,4,4,5,5,3,3,5,4,2,0.0,satisfied +98510,63341,Male,Loyal Customer,35,Business travel,Business,447,4,4,4,4,5,1,2,4,4,4,4,1,4,3,0,0.0,satisfied +98511,24278,Female,Loyal Customer,46,Personal Travel,Eco,170,1,5,1,2,2,5,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +98512,46251,Male,Loyal Customer,36,Business travel,Business,2514,2,4,4,4,4,3,3,2,2,2,2,4,2,1,45,45.0,neutral or dissatisfied +98513,43189,Female,Loyal Customer,56,Business travel,Business,3591,4,4,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +98514,97232,Male,Loyal Customer,17,Personal Travel,Business,393,2,3,2,3,4,2,4,4,2,4,4,2,3,4,3,5.0,neutral or dissatisfied +98515,125311,Female,Loyal Customer,46,Personal Travel,Eco,678,3,4,3,3,3,5,5,2,2,3,2,3,2,4,3,17.0,neutral or dissatisfied +98516,99840,Female,disloyal Customer,27,Business travel,Eco,534,3,2,3,3,2,3,2,2,4,3,3,2,3,2,23,44.0,neutral or dissatisfied +98517,34688,Male,Loyal Customer,34,Business travel,Business,301,4,4,4,4,4,1,1,5,5,5,5,3,5,5,0,0.0,satisfied +98518,21204,Male,Loyal Customer,46,Business travel,Business,2135,3,5,5,5,3,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +98519,123873,Female,Loyal Customer,28,Business travel,Business,1773,2,4,4,4,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +98520,47601,Female,disloyal Customer,41,Business travel,Eco,1269,3,3,3,3,1,3,1,1,1,5,3,2,3,1,0,0.0,neutral or dissatisfied +98521,106800,Male,Loyal Customer,55,Business travel,Business,2328,2,2,2,2,2,4,3,2,2,2,2,1,2,4,7,1.0,neutral or dissatisfied +98522,66663,Male,Loyal Customer,43,Business travel,Business,978,5,3,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +98523,62947,Female,disloyal Customer,20,Business travel,Business,862,0,0,0,2,3,0,3,3,5,5,5,5,5,3,0,0.0,satisfied +98524,45741,Male,disloyal Customer,33,Business travel,Business,391,2,2,2,4,5,2,5,5,3,5,5,3,4,5,53,78.0,neutral or dissatisfied +98525,53256,Male,Loyal Customer,53,Personal Travel,Eco Plus,589,4,5,4,3,5,4,5,5,4,5,4,3,5,5,0,0.0,satisfied +98526,47937,Male,Loyal Customer,45,Personal Travel,Eco,834,1,4,1,1,1,1,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +98527,42226,Male,disloyal Customer,32,Business travel,Eco,412,3,0,3,4,2,3,2,2,1,5,1,1,1,2,0,0.0,neutral or dissatisfied +98528,43284,Female,Loyal Customer,58,Business travel,Eco,463,4,4,4,4,4,1,1,4,4,4,4,4,4,3,0,0.0,satisfied +98529,32280,Male,Loyal Customer,57,Business travel,Eco,101,4,2,4,4,4,4,4,4,3,5,2,2,1,4,0,0.0,satisfied +98530,13961,Female,Loyal Customer,67,Personal Travel,Eco,153,2,2,2,4,2,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +98531,55439,Male,Loyal Customer,63,Personal Travel,Eco,2136,3,4,3,4,2,3,2,2,2,2,3,4,3,2,1,3.0,neutral or dissatisfied +98532,66002,Male,Loyal Customer,58,Business travel,Business,3339,4,2,2,2,3,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +98533,59869,Female,Loyal Customer,38,Business travel,Business,1085,1,1,1,1,3,5,4,4,4,4,4,4,4,5,8,0.0,satisfied +98534,115035,Male,Loyal Customer,39,Business travel,Business,446,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +98535,58487,Male,Loyal Customer,56,Business travel,Business,2932,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +98536,27933,Male,Loyal Customer,48,Business travel,Eco,1874,5,2,2,2,5,5,5,5,4,1,4,4,1,5,0,0.0,satisfied +98537,80671,Female,Loyal Customer,34,Personal Travel,Eco,821,4,1,4,4,4,4,4,4,3,5,3,1,3,4,0,6.0,neutral or dissatisfied +98538,28849,Male,Loyal Customer,44,Business travel,Eco,1050,4,5,5,5,4,4,4,4,1,5,2,3,5,4,0,0.0,satisfied +98539,19843,Female,Loyal Customer,23,Business travel,Business,2863,3,3,3,3,4,4,4,4,5,1,1,4,5,4,42,47.0,satisfied +98540,127002,Female,Loyal Customer,26,Business travel,Business,3750,1,1,1,1,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +98541,50383,Male,Loyal Customer,51,Business travel,Business,2662,1,3,3,3,4,3,3,3,3,2,1,2,3,2,2,9.0,neutral or dissatisfied +98542,105575,Female,disloyal Customer,43,Business travel,Eco,577,3,0,4,4,1,4,1,1,3,3,3,1,4,1,32,46.0,neutral or dissatisfied +98543,100393,Female,Loyal Customer,59,Personal Travel,Eco,1165,3,2,3,3,4,3,3,4,4,3,4,3,4,2,5,21.0,neutral or dissatisfied +98544,122222,Female,Loyal Customer,32,Business travel,Eco,646,5,3,3,3,5,4,5,5,2,4,2,2,2,5,16,0.0,neutral or dissatisfied +98545,128422,Male,Loyal Customer,42,Business travel,Business,3447,2,1,1,1,3,3,4,2,2,2,2,3,2,1,30,33.0,neutral or dissatisfied +98546,64646,Male,Loyal Customer,54,Business travel,Business,2310,5,5,5,5,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +98547,36734,Male,Loyal Customer,56,Business travel,Eco,1754,2,1,1,1,2,2,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +98548,49269,Male,Loyal Customer,64,Business travel,Business,308,5,5,5,5,4,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +98549,115870,Male,Loyal Customer,52,Business travel,Eco,337,5,1,2,1,5,5,5,5,4,5,4,4,2,5,0,0.0,satisfied +98550,67036,Male,Loyal Customer,55,Business travel,Business,964,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +98551,6236,Male,Loyal Customer,9,Business travel,Business,3488,2,1,1,1,2,2,2,2,4,1,3,3,4,2,85,106.0,neutral or dissatisfied +98552,120881,Male,Loyal Customer,46,Business travel,Business,1796,3,3,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +98553,125127,Male,Loyal Customer,31,Personal Travel,Eco,361,3,4,3,4,3,3,3,3,3,2,5,4,5,3,1,32.0,neutral or dissatisfied +98554,128557,Female,Loyal Customer,48,Business travel,Business,651,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +98555,105146,Male,Loyal Customer,55,Business travel,Eco,277,2,4,4,4,2,2,2,2,2,4,4,1,3,2,7,13.0,neutral or dissatisfied +98556,36984,Male,disloyal Customer,48,Business travel,Eco,667,2,2,2,2,3,2,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +98557,86493,Female,Loyal Customer,13,Personal Travel,Eco,762,1,5,1,4,2,1,2,2,4,3,5,4,4,2,0,6.0,neutral or dissatisfied +98558,40988,Male,Loyal Customer,47,Business travel,Business,1731,3,3,5,3,4,2,2,3,3,3,3,4,3,2,0,17.0,neutral or dissatisfied +98559,69914,Male,Loyal Customer,44,Personal Travel,Eco,1514,2,5,2,3,5,2,5,5,5,5,4,3,5,5,0,0.0,neutral or dissatisfied +98560,104667,Male,disloyal Customer,19,Business travel,Eco,641,4,4,4,4,3,4,3,3,1,1,4,1,4,3,49,56.0,neutral or dissatisfied +98561,29928,Female,Loyal Customer,37,Business travel,Eco,548,1,1,1,1,1,1,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +98562,39928,Male,Loyal Customer,72,Business travel,Eco,1086,3,1,1,1,3,3,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +98563,94728,Female,Loyal Customer,39,Business travel,Business,187,1,1,1,1,3,3,2,3,3,3,1,1,3,3,0,0.0,neutral or dissatisfied +98564,70547,Female,Loyal Customer,50,Business travel,Business,1258,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +98565,62170,Male,disloyal Customer,46,Business travel,Business,2565,3,4,4,3,2,3,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +98566,117569,Male,Loyal Customer,41,Business travel,Business,2802,0,0,0,1,5,5,4,1,1,1,1,4,1,3,15,12.0,satisfied +98567,50087,Female,Loyal Customer,31,Business travel,Business,3388,0,0,0,1,5,5,5,5,1,2,3,4,5,5,0,0.0,satisfied +98568,23460,Female,Loyal Customer,39,Business travel,Eco,516,3,5,5,5,3,2,3,3,4,1,4,1,3,3,4,23.0,neutral or dissatisfied +98569,19683,Male,Loyal Customer,37,Business travel,Eco,475,4,2,2,2,4,4,4,1,1,3,5,4,5,4,291,310.0,satisfied +98570,14969,Female,Loyal Customer,34,Business travel,Business,2636,3,3,3,3,1,3,5,4,4,4,4,1,4,5,0,0.0,satisfied +98571,15849,Male,Loyal Customer,34,Personal Travel,Eco,888,3,4,3,3,4,3,4,4,3,5,4,4,5,4,47,57.0,neutral or dissatisfied +98572,97905,Female,Loyal Customer,54,Business travel,Business,3277,3,3,5,3,5,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +98573,37605,Female,Loyal Customer,49,Personal Travel,Eco,1069,1,2,1,2,5,2,3,3,3,1,3,2,3,4,41,46.0,neutral or dissatisfied +98574,35698,Female,Loyal Customer,29,Personal Travel,Eco,2586,2,2,2,4,2,2,2,4,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +98575,18812,Male,Loyal Customer,41,Business travel,Eco,448,4,5,5,5,3,4,3,3,2,3,5,3,3,3,7,0.0,satisfied +98576,38376,Male,Loyal Customer,30,Personal Travel,Eco,1180,3,2,3,2,3,3,3,3,3,3,3,1,2,3,0,26.0,neutral or dissatisfied +98577,83151,Male,Loyal Customer,9,Personal Travel,Eco,813,4,2,4,3,4,4,4,4,1,2,3,3,4,4,0,9.0,neutral or dissatisfied +98578,105692,Female,Loyal Customer,45,Business travel,Business,3179,5,5,5,5,5,5,4,4,4,4,4,4,4,3,8,3.0,satisfied +98579,26408,Male,disloyal Customer,19,Business travel,Eco,1249,4,4,4,1,2,4,2,2,2,5,2,5,2,2,0,3.0,satisfied +98580,52314,Female,disloyal Customer,40,Business travel,Business,237,3,4,4,4,3,4,3,3,3,5,3,1,4,3,2,2.0,neutral or dissatisfied +98581,77231,Male,disloyal Customer,26,Business travel,Eco,1590,1,1,1,4,5,1,5,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +98582,62354,Female,Loyal Customer,39,Personal Travel,Eco,1735,1,5,1,5,1,1,1,1,4,5,3,5,5,1,23,0.0,neutral or dissatisfied +98583,21529,Male,Loyal Customer,44,Personal Travel,Eco,377,2,4,2,5,5,2,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +98584,55002,Male,Loyal Customer,40,Business travel,Business,1379,3,3,3,3,2,5,4,3,3,3,3,3,3,5,4,0.0,satisfied +98585,107669,Female,Loyal Customer,56,Business travel,Business,251,0,0,0,5,2,4,5,1,1,1,1,3,1,5,1,0.0,satisfied +98586,8898,Female,Loyal Customer,43,Business travel,Business,539,2,2,2,2,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +98587,30862,Female,Loyal Customer,56,Business travel,Business,1607,2,2,2,2,4,4,3,5,5,5,5,1,5,3,0,0.0,satisfied +98588,12530,Male,Loyal Customer,67,Business travel,Eco,871,5,2,2,2,5,5,5,5,5,4,2,4,4,5,33,26.0,satisfied +98589,66531,Male,disloyal Customer,22,Business travel,Business,733,4,3,4,1,4,4,4,4,5,2,4,4,5,4,2,0.0,satisfied +98590,56652,Female,disloyal Customer,57,Business travel,Eco,665,4,4,4,3,2,4,1,2,4,5,4,3,3,2,37,91.0,neutral or dissatisfied +98591,124436,Female,Loyal Customer,30,Business travel,Business,1262,5,5,5,5,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +98592,114425,Male,Loyal Customer,54,Business travel,Business,2175,4,4,4,4,3,4,5,5,5,5,5,3,5,3,129,128.0,satisfied +98593,107138,Female,Loyal Customer,53,Business travel,Business,3217,1,1,4,1,5,5,4,5,5,5,5,3,5,5,56,42.0,satisfied +98594,24622,Male,Loyal Customer,23,Business travel,Business,2080,3,1,1,1,1,1,3,1,3,2,3,2,3,1,29,27.0,neutral or dissatisfied +98595,78656,Male,Loyal Customer,24,Personal Travel,Eco,2172,3,4,3,2,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +98596,3104,Male,Loyal Customer,9,Personal Travel,Eco,594,2,2,3,2,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +98597,36364,Male,Loyal Customer,49,Business travel,Business,200,2,2,2,2,1,1,2,4,4,4,3,2,4,3,26,23.0,satisfied +98598,39223,Male,disloyal Customer,20,Business travel,Business,268,0,0,0,3,5,0,5,5,4,5,5,5,3,5,0,9.0,satisfied +98599,31990,Female,Loyal Customer,23,Personal Travel,Business,102,2,5,2,3,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +98600,63526,Male,Loyal Customer,34,Business travel,Business,1009,1,1,1,1,3,4,5,5,5,5,5,4,5,5,23,3.0,satisfied +98601,8216,Female,Loyal Customer,39,Business travel,Eco,402,2,3,2,3,2,2,2,2,4,4,3,2,3,2,0,0.0,satisfied +98602,48216,Female,Loyal Customer,47,Personal Travel,Eco,236,2,5,2,5,3,5,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +98603,55886,Female,Loyal Customer,30,Business travel,Business,3754,3,3,3,3,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +98604,124181,Male,Loyal Customer,45,Business travel,Business,2089,5,2,5,5,2,5,5,4,4,5,4,5,4,4,0,11.0,satisfied +98605,28285,Male,Loyal Customer,27,Business travel,Business,1658,5,5,5,5,4,4,4,4,4,2,5,4,4,4,3,0.0,satisfied +98606,3833,Male,Loyal Customer,56,Business travel,Business,2118,0,0,0,4,5,1,2,2,2,2,2,3,2,3,12,5.0,satisfied +98607,58129,Female,disloyal Customer,25,Business travel,Business,589,0,0,1,4,4,1,4,4,3,2,5,4,5,4,0,2.0,satisfied +98608,61556,Male,Loyal Customer,27,Business travel,Eco Plus,2419,3,4,4,4,3,3,3,3,2,1,2,2,3,3,0,0.0,neutral or dissatisfied +98609,93692,Female,Loyal Customer,36,Business travel,Eco,1452,2,3,2,2,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +98610,47693,Male,Loyal Customer,39,Personal Travel,Eco,1211,3,5,2,2,3,2,3,3,2,5,3,2,5,3,0,5.0,neutral or dissatisfied +98611,92185,Female,disloyal Customer,30,Business travel,Eco,1091,3,3,3,4,5,3,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +98612,80695,Male,Loyal Customer,27,Business travel,Business,1585,4,4,4,4,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +98613,57917,Male,Loyal Customer,30,Personal Travel,Eco,305,4,4,4,1,4,4,4,4,4,3,5,5,5,4,85,75.0,neutral or dissatisfied +98614,7613,Male,Loyal Customer,32,Personal Travel,Eco,802,4,3,4,3,2,4,2,2,1,2,3,5,3,2,35,17.0,neutral or dissatisfied +98615,9960,Female,Loyal Customer,50,Business travel,Business,134,1,5,5,5,3,1,2,1,1,1,1,3,1,3,61,49.0,neutral or dissatisfied +98616,18211,Male,Loyal Customer,41,Business travel,Business,2740,5,5,5,5,1,4,1,4,4,4,4,2,4,5,0,0.0,satisfied +98617,4715,Male,Loyal Customer,69,Personal Travel,Eco Plus,364,4,2,4,3,4,4,4,4,2,3,3,3,4,4,0,7.0,neutral or dissatisfied +98618,64277,Female,Loyal Customer,46,Business travel,Business,1158,2,2,2,2,3,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +98619,125930,Male,Loyal Customer,21,Personal Travel,Eco,951,2,4,2,5,3,2,3,3,2,5,5,4,4,3,0,0.0,neutral or dissatisfied +98620,81711,Female,Loyal Customer,27,Business travel,Business,1727,3,3,3,3,5,5,5,5,4,5,5,5,5,5,0,10.0,satisfied +98621,99739,Female,disloyal Customer,22,Business travel,Eco,361,4,0,4,4,4,4,4,4,3,5,3,1,4,4,0,9.0,neutral or dissatisfied +98622,21341,Male,Loyal Customer,30,Business travel,Business,2310,3,1,1,1,3,3,3,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +98623,10772,Female,Loyal Customer,44,Business travel,Business,1755,2,1,1,1,4,2,2,2,2,2,2,2,2,1,94,85.0,neutral or dissatisfied +98624,33186,Female,disloyal Customer,21,Business travel,Eco,101,3,1,3,3,3,3,3,3,2,5,4,1,3,3,0,0.0,neutral or dissatisfied +98625,128333,Male,Loyal Customer,61,Business travel,Business,3936,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +98626,7739,Female,disloyal Customer,25,Business travel,Business,489,4,5,4,2,1,4,1,1,5,3,5,4,4,1,0,1.0,satisfied +98627,23484,Female,Loyal Customer,45,Personal Travel,Eco,516,3,4,3,3,3,5,2,5,5,3,5,2,5,2,102,95.0,neutral or dissatisfied +98628,89238,Female,Loyal Customer,48,Business travel,Eco Plus,2092,2,2,2,2,2,3,3,2,2,2,2,1,2,4,37,38.0,neutral or dissatisfied +98629,96795,Female,Loyal Customer,45,Business travel,Business,1758,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +98630,41500,Female,disloyal Customer,44,Business travel,Eco,1269,2,2,2,4,4,2,4,4,3,1,5,4,4,4,22,12.0,neutral or dissatisfied +98631,81760,Male,Loyal Customer,59,Business travel,Business,1604,5,1,5,5,5,5,4,5,5,5,5,3,5,3,92,76.0,satisfied +98632,27699,Male,Loyal Customer,31,Business travel,Eco Plus,1107,5,4,4,4,5,5,5,5,2,4,4,1,2,5,0,0.0,satisfied +98633,65311,Female,Loyal Customer,42,Business travel,Business,231,4,4,4,4,5,4,4,5,5,5,5,5,5,4,8,6.0,satisfied +98634,36612,Male,Loyal Customer,46,Business travel,Business,3969,1,4,4,4,4,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +98635,23947,Male,Loyal Customer,39,Business travel,Eco,936,4,4,4,4,4,3,4,4,4,4,4,2,4,4,14,12.0,neutral or dissatisfied +98636,7116,Male,Loyal Customer,54,Personal Travel,Eco,157,2,4,2,2,2,2,2,2,3,4,4,3,4,2,0,,neutral or dissatisfied +98637,3804,Male,Loyal Customer,44,Business travel,Business,2619,1,2,1,1,4,4,4,5,5,4,5,3,5,3,18,17.0,satisfied +98638,5405,Female,Loyal Customer,59,Personal Travel,Eco,785,2,5,2,4,4,4,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +98639,4685,Male,Loyal Customer,46,Personal Travel,Eco,364,2,4,2,3,3,2,3,3,5,5,4,4,4,3,9,16.0,neutral or dissatisfied +98640,116188,Male,Loyal Customer,38,Personal Travel,Eco,362,1,2,5,2,3,5,3,3,3,1,3,4,2,3,41,31.0,neutral or dissatisfied +98641,23092,Female,Loyal Customer,17,Business travel,Eco Plus,794,1,3,3,3,1,1,2,1,1,1,3,3,3,1,30,33.0,neutral or dissatisfied +98642,115015,Male,Loyal Customer,59,Business travel,Business,1978,4,4,3,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +98643,50690,Male,Loyal Customer,9,Personal Travel,Eco,134,3,4,3,2,4,3,4,4,5,2,5,3,3,4,0,0.0,neutral or dissatisfied +98644,105266,Female,Loyal Customer,46,Personal Travel,Eco,2106,2,3,2,3,3,4,3,4,4,2,4,1,4,1,0,7.0,neutral or dissatisfied +98645,14621,Male,Loyal Customer,54,Personal Travel,Eco,450,4,5,4,3,3,4,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +98646,70414,Male,Loyal Customer,43,Business travel,Business,1562,5,5,4,5,2,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +98647,108082,Male,Loyal Customer,20,Business travel,Eco,1166,1,3,3,3,1,1,3,1,2,4,3,3,3,1,0,25.0,neutral or dissatisfied +98648,110553,Female,Loyal Customer,34,Business travel,Business,1932,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +98649,52817,Female,Loyal Customer,39,Business travel,Business,902,4,4,4,4,2,2,5,5,5,5,5,1,5,1,42,23.0,satisfied +98650,128252,Male,Loyal Customer,57,Business travel,Business,2286,2,5,2,2,4,5,4,4,4,4,4,4,4,3,0,1.0,satisfied +98651,49098,Male,Loyal Customer,48,Business travel,Business,2967,3,3,4,3,3,5,5,5,5,5,5,5,5,2,1,2.0,satisfied +98652,18435,Male,disloyal Customer,20,Business travel,Eco,285,2,4,3,5,4,3,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +98653,9188,Male,disloyal Customer,44,Business travel,Business,363,3,3,3,3,2,3,2,2,4,3,3,1,3,2,14,18.0,neutral or dissatisfied +98654,120098,Female,Loyal Customer,44,Personal Travel,Business,1576,1,4,1,1,3,5,4,3,3,1,3,3,3,5,0,0.0,neutral or dissatisfied +98655,126060,Male,disloyal Customer,27,Business travel,Business,507,2,2,2,1,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +98656,72379,Male,Loyal Customer,36,Business travel,Business,2657,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +98657,10450,Female,Loyal Customer,33,Business travel,Business,74,0,4,0,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +98658,97644,Female,Loyal Customer,38,Business travel,Business,1587,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,3.0,satisfied +98659,4706,Male,Loyal Customer,13,Personal Travel,Eco,364,3,4,3,2,5,3,5,5,3,4,4,4,4,5,0,15.0,neutral or dissatisfied +98660,27443,Male,Loyal Customer,9,Business travel,Eco,605,1,3,3,3,1,1,3,1,4,1,3,2,2,1,0,0.0,neutral or dissatisfied +98661,118206,Male,Loyal Customer,55,Personal Travel,Eco,1444,4,2,4,2,5,4,5,5,3,4,1,4,1,5,3,0.0,neutral or dissatisfied +98662,43702,Male,disloyal Customer,39,Business travel,Eco,196,3,1,3,4,5,3,5,5,1,1,4,3,3,5,0,0.0,neutral or dissatisfied +98663,85984,Female,Loyal Customer,53,Business travel,Business,554,2,2,2,2,2,5,4,5,5,5,5,3,5,3,28,35.0,satisfied +98664,40151,Male,Loyal Customer,23,Business travel,Business,3473,3,3,3,3,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +98665,128301,Female,Loyal Customer,31,Business travel,Business,370,2,2,2,2,5,5,5,5,4,2,5,5,5,5,16,9.0,satisfied +98666,95198,Female,Loyal Customer,46,Personal Travel,Eco,192,2,5,0,1,3,5,4,2,2,0,2,3,2,3,0,9.0,neutral or dissatisfied +98667,105236,Female,Loyal Customer,21,Personal Travel,Eco,377,1,1,1,2,1,2,4,3,4,2,3,4,3,4,315,297.0,neutral or dissatisfied +98668,105376,Male,Loyal Customer,41,Business travel,Business,3965,4,4,2,4,3,4,4,2,2,3,2,4,2,4,33,5.0,satisfied +98669,47580,Female,Loyal Customer,44,Personal Travel,Business,1428,3,4,3,2,5,5,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +98670,51789,Male,Loyal Customer,35,Personal Travel,Eco,370,2,3,2,3,1,2,1,1,2,1,3,3,4,1,0,8.0,neutral or dissatisfied +98671,32253,Male,Loyal Customer,53,Business travel,Business,1756,3,3,3,3,3,1,5,4,4,4,5,2,4,4,0,0.0,satisfied +98672,73637,Male,Loyal Customer,40,Business travel,Business,192,1,1,1,1,3,4,4,5,5,5,4,4,5,4,56,48.0,satisfied +98673,109181,Female,disloyal Customer,45,Business travel,Eco,616,2,4,2,4,2,2,2,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +98674,70911,Female,Loyal Customer,27,Personal Travel,Eco Plus,1721,1,4,1,4,1,1,5,1,2,2,2,4,3,1,3,16.0,neutral or dissatisfied +98675,44045,Male,Loyal Customer,51,Personal Travel,Eco,67,2,5,2,1,5,2,5,5,5,4,5,4,5,5,3,18.0,neutral or dissatisfied +98676,22410,Female,Loyal Customer,58,Business travel,Business,143,1,4,3,4,5,2,1,3,3,3,1,3,3,1,0,0.0,neutral or dissatisfied +98677,117030,Female,Loyal Customer,39,Business travel,Business,2865,1,5,5,5,2,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +98678,97276,Female,Loyal Customer,52,Business travel,Business,872,4,4,4,4,4,4,4,4,4,4,4,4,4,3,74,65.0,satisfied +98679,114132,Female,Loyal Customer,43,Business travel,Business,3696,4,4,4,4,2,5,5,5,5,5,5,5,5,5,24,30.0,satisfied +98680,41587,Female,Loyal Customer,21,Personal Travel,Eco,1428,3,4,3,5,5,3,5,5,4,3,4,3,4,5,0,17.0,neutral or dissatisfied +98681,50823,Male,Loyal Customer,18,Personal Travel,Eco,326,4,2,4,3,2,4,2,2,4,2,4,3,4,2,63,58.0,neutral or dissatisfied +98682,3814,Female,Loyal Customer,46,Business travel,Business,1887,5,5,1,5,4,5,5,3,3,2,3,4,3,4,112,108.0,satisfied +98683,32755,Female,Loyal Customer,30,Business travel,Eco,102,4,2,1,2,4,4,4,4,1,2,1,5,2,4,0,0.0,satisfied +98684,46461,Male,Loyal Customer,47,Business travel,Business,73,2,2,2,2,3,4,4,4,4,4,5,3,4,4,71,66.0,satisfied +98685,114072,Female,disloyal Customer,9,Business travel,Eco,868,3,3,3,4,3,3,3,3,4,2,2,3,3,3,65,59.0,neutral or dissatisfied +98686,104752,Female,Loyal Customer,54,Personal Travel,Eco,1246,5,2,5,4,3,4,4,4,4,5,4,4,4,1,8,0.0,satisfied +98687,5911,Female,Loyal Customer,39,Personal Travel,Eco,212,4,1,4,1,3,4,2,3,1,2,2,2,2,3,4,0.0,neutral or dissatisfied +98688,14768,Male,Loyal Customer,55,Personal Travel,Eco,463,3,4,2,1,1,2,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +98689,41524,Female,Loyal Customer,30,Business travel,Business,1269,3,4,4,4,3,3,3,3,4,1,4,3,4,3,0,8.0,neutral or dissatisfied +98690,29646,Female,Loyal Customer,37,Personal Travel,Eco,1448,5,2,5,3,4,5,4,4,4,4,3,1,3,4,14,0.0,satisfied +98691,104840,Female,Loyal Customer,19,Personal Travel,Eco,472,3,3,3,4,4,3,4,4,1,1,4,4,4,4,35,23.0,neutral or dissatisfied +98692,1723,Female,Loyal Customer,45,Business travel,Business,3551,2,5,5,5,4,4,4,2,2,2,2,4,2,4,3,5.0,neutral or dissatisfied +98693,72172,Female,Loyal Customer,41,Personal Travel,Business,594,3,5,3,4,4,5,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +98694,56585,Female,Loyal Customer,35,Business travel,Business,997,3,5,2,2,2,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +98695,83678,Male,disloyal Customer,12,Business travel,Eco,577,2,4,2,3,1,2,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +98696,43512,Female,Loyal Customer,52,Personal Travel,Eco,594,3,2,3,3,5,2,3,3,3,3,3,4,3,3,0,25.0,neutral or dissatisfied +98697,88228,Female,Loyal Customer,59,Business travel,Business,3038,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +98698,49479,Male,Loyal Customer,44,Business travel,Eco,109,5,1,1,1,5,5,5,5,5,2,4,5,5,5,5,42.0,satisfied +98699,50177,Male,Loyal Customer,45,Business travel,Business,1828,3,3,3,3,1,5,4,5,5,5,5,3,5,2,0,0.0,satisfied +98700,15754,Female,Loyal Customer,22,Business travel,Eco,544,3,5,5,5,3,3,2,3,4,1,3,1,3,3,58,77.0,neutral or dissatisfied +98701,95648,Female,Loyal Customer,40,Business travel,Business,2005,2,2,2,2,3,4,5,4,4,4,4,5,4,3,0,2.0,satisfied +98702,57635,Female,Loyal Customer,39,Business travel,Business,200,3,3,3,3,5,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +98703,46260,Male,Loyal Customer,23,Personal Travel,Eco,455,4,4,2,2,5,2,5,5,4,2,4,4,4,5,1,11.0,neutral or dissatisfied +98704,54621,Male,Loyal Customer,26,Business travel,Eco,854,5,3,3,3,5,5,5,5,1,4,4,5,3,5,0,0.0,satisfied +98705,4823,Female,Loyal Customer,29,Business travel,Business,500,3,2,2,2,3,3,3,3,1,1,4,2,3,3,0,0.0,neutral or dissatisfied +98706,77869,Male,Loyal Customer,54,Business travel,Business,2618,3,3,3,3,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +98707,56017,Female,Loyal Customer,54,Business travel,Business,2586,4,5,4,4,4,4,4,3,3,4,4,4,4,4,0,0.0,satisfied +98708,116505,Male,Loyal Customer,8,Personal Travel,Eco,325,2,1,2,3,4,2,4,4,3,5,3,4,4,4,7,0.0,neutral or dissatisfied +98709,98776,Male,disloyal Customer,31,Business travel,Business,1814,4,4,4,5,4,4,4,4,3,2,4,4,5,4,80,59.0,neutral or dissatisfied +98710,77091,Female,Loyal Customer,47,Business travel,Business,1481,3,3,3,3,2,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +98711,116282,Female,Loyal Customer,11,Personal Travel,Eco,362,1,4,1,1,1,1,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +98712,72638,Female,Loyal Customer,34,Personal Travel,Eco,929,2,1,1,3,1,1,4,1,4,3,2,1,2,1,0,0.0,neutral or dissatisfied +98713,13662,Female,Loyal Customer,54,Business travel,Business,3928,4,4,2,4,2,3,2,4,4,4,4,1,4,4,0,0.0,satisfied +98714,22943,Female,Loyal Customer,28,Business travel,Eco,489,5,5,5,5,5,5,5,5,4,5,1,2,4,5,0,2.0,satisfied +98715,51603,Female,Loyal Customer,33,Business travel,Business,1812,5,5,5,5,5,1,2,5,5,5,5,4,5,5,0,0.0,satisfied +98716,94197,Female,Loyal Customer,58,Business travel,Business,293,4,4,4,4,5,5,5,4,4,4,4,5,4,5,1,0.0,satisfied +98717,51757,Male,Loyal Customer,57,Personal Travel,Eco,509,2,5,2,2,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +98718,12341,Female,Loyal Customer,23,Business travel,Business,201,1,1,1,1,2,2,1,2,1,2,2,3,3,2,48,45.0,neutral or dissatisfied +98719,40674,Female,Loyal Customer,22,Personal Travel,Business,599,2,1,2,3,5,2,5,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +98720,46313,Male,Loyal Customer,29,Business travel,Eco Plus,1069,5,5,5,5,5,5,5,5,2,5,3,3,5,5,42,53.0,satisfied +98721,42214,Female,Loyal Customer,66,Business travel,Business,2303,5,5,5,5,4,5,4,4,4,4,4,3,4,2,0,0.0,satisfied +98722,113736,Female,Loyal Customer,70,Personal Travel,Eco,414,1,4,1,3,3,4,3,5,5,1,4,5,5,3,0,0.0,neutral or dissatisfied +98723,16059,Male,Loyal Customer,26,Business travel,Eco,744,3,1,1,1,3,3,4,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +98724,28050,Female,Loyal Customer,45,Personal Travel,Eco,1739,4,5,4,2,4,4,4,1,1,4,1,3,1,5,3,58.0,neutral or dissatisfied +98725,43501,Male,Loyal Customer,32,Personal Travel,Eco,624,1,5,1,3,1,1,1,1,4,5,2,4,3,1,114,119.0,neutral or dissatisfied +98726,85785,Female,Loyal Customer,42,Business travel,Business,666,5,5,2,5,4,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +98727,87865,Male,Loyal Customer,19,Personal Travel,Eco,214,1,0,0,4,1,0,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +98728,59688,Female,Loyal Customer,47,Personal Travel,Eco,854,2,5,2,3,4,5,5,2,2,2,1,4,2,5,7,14.0,neutral or dissatisfied +98729,80846,Female,Loyal Customer,37,Business travel,Business,484,3,2,2,2,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +98730,67128,Male,Loyal Customer,24,Business travel,Business,3384,2,2,4,2,2,2,2,2,2,1,4,3,4,2,2,4.0,neutral or dissatisfied +98731,85760,Female,disloyal Customer,26,Business travel,Business,526,0,0,0,2,2,0,2,2,3,2,5,5,5,2,0,0.0,satisfied +98732,79597,Female,Loyal Customer,51,Business travel,Business,1962,5,5,5,5,4,4,5,5,5,5,5,5,5,5,37,33.0,satisfied +98733,44400,Female,disloyal Customer,40,Business travel,Business,323,4,4,4,5,4,3,3,1,1,4,4,3,4,3,106,143.0,satisfied +98734,70725,Male,Loyal Customer,28,Business travel,Business,1739,1,1,1,1,2,2,2,2,4,3,5,4,5,2,0,0.0,satisfied +98735,101590,Male,Loyal Customer,56,Personal Travel,Eco Plus,1099,4,5,4,3,1,4,1,1,4,4,5,3,1,1,0,0.0,neutral or dissatisfied +98736,76451,Male,Loyal Customer,43,Business travel,Business,481,5,5,5,5,4,5,5,5,5,5,5,3,5,5,61,52.0,satisfied +98737,73493,Male,Loyal Customer,43,Personal Travel,Eco,1120,1,5,1,4,2,1,5,2,3,3,4,5,4,2,0,6.0,neutral or dissatisfied +98738,83594,Female,disloyal Customer,33,Business travel,Business,409,2,2,2,1,3,2,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +98739,120823,Male,Loyal Customer,51,Personal Travel,Eco,666,2,4,2,2,5,2,5,5,4,2,5,3,5,5,15,31.0,neutral or dissatisfied +98740,21185,Female,Loyal Customer,36,Business travel,Eco,192,1,1,1,1,1,1,1,1,1,5,4,1,3,1,79,86.0,neutral or dissatisfied +98741,24749,Female,Loyal Customer,66,Business travel,Business,3640,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +98742,15559,Male,Loyal Customer,57,Business travel,Business,2951,0,0,0,2,3,5,2,5,5,5,5,1,5,1,16,20.0,satisfied +98743,78392,Female,Loyal Customer,15,Personal Travel,Eco,980,3,1,3,1,3,3,3,3,3,5,2,1,2,3,0,0.0,neutral or dissatisfied +98744,81748,Male,disloyal Customer,49,Business travel,Business,1310,1,1,1,3,1,1,1,1,4,3,4,5,5,1,0,17.0,neutral or dissatisfied +98745,67197,Male,Loyal Customer,36,Personal Travel,Eco,1017,1,4,1,4,4,1,4,4,4,4,2,4,3,4,0,0.0,neutral or dissatisfied +98746,8485,Male,Loyal Customer,31,Business travel,Business,677,5,5,5,5,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +98747,41393,Female,disloyal Customer,20,Business travel,Eco,563,0,0,0,5,5,0,5,5,2,3,1,3,2,5,0,0.0,satisfied +98748,63070,Female,Loyal Customer,7,Personal Travel,Eco,967,3,2,3,3,5,3,5,5,4,2,4,3,4,5,22,12.0,neutral or dissatisfied +98749,5177,Male,Loyal Customer,48,Personal Travel,Business,351,1,5,1,3,3,4,5,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +98750,115150,Female,Loyal Customer,27,Business travel,Business,1524,2,2,2,2,5,5,5,5,3,3,4,5,4,5,51,32.0,satisfied +98751,104982,Male,Loyal Customer,36,Business travel,Eco,337,1,3,3,3,1,1,1,1,1,1,3,3,3,1,8,17.0,neutral or dissatisfied +98752,3281,Male,Loyal Customer,69,Personal Travel,Eco,479,3,5,3,4,5,3,5,5,2,3,5,2,4,5,0,0.0,neutral or dissatisfied +98753,12468,Male,Loyal Customer,58,Personal Travel,Eco,383,3,4,3,5,3,4,4,3,3,5,4,4,5,4,200,196.0,neutral or dissatisfied +98754,68579,Male,Loyal Customer,40,Business travel,Business,3866,4,4,4,4,1,4,2,4,4,4,4,3,4,2,0,2.0,satisfied +98755,2092,Male,Loyal Customer,51,Personal Travel,Eco,812,3,2,3,2,1,3,1,1,3,4,2,4,2,1,0,0.0,neutral or dissatisfied +98756,53239,Male,Loyal Customer,25,Personal Travel,Eco,589,3,2,3,4,4,3,4,4,3,3,3,1,4,4,34,22.0,neutral or dissatisfied +98757,80537,Female,Loyal Customer,34,Business travel,Business,1747,1,1,1,1,3,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +98758,18887,Male,Loyal Customer,56,Business travel,Business,448,1,5,5,5,1,1,1,3,2,3,4,1,4,1,204,218.0,neutral or dissatisfied +98759,77180,Male,Loyal Customer,58,Business travel,Business,1510,1,1,1,1,5,4,4,4,4,4,4,3,4,5,2,0.0,satisfied +98760,8970,Female,Loyal Customer,58,Business travel,Business,725,1,1,2,1,4,4,5,5,5,5,5,5,5,4,88,76.0,satisfied +98761,13278,Female,Loyal Customer,34,Personal Travel,Eco,657,1,3,1,1,2,1,2,2,3,1,5,1,3,2,0,0.0,neutral or dissatisfied +98762,127222,Female,Loyal Customer,23,Business travel,Business,1460,3,3,3,3,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +98763,24511,Female,Loyal Customer,45,Personal Travel,Eco,547,2,4,2,2,2,3,2,4,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +98764,85373,Male,Loyal Customer,42,Business travel,Business,3115,3,3,3,3,2,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +98765,107812,Male,disloyal Customer,27,Business travel,Business,349,3,3,3,5,2,3,2,2,4,5,5,3,5,2,25,23.0,neutral or dissatisfied +98766,20641,Male,Loyal Customer,70,Personal Travel,Eco,752,3,5,3,4,4,3,4,4,4,2,5,3,5,4,0,3.0,neutral or dissatisfied +98767,83859,Male,Loyal Customer,57,Personal Travel,Eco,425,3,5,2,4,1,2,1,1,3,4,5,5,5,1,14,8.0,neutral or dissatisfied +98768,57411,Female,Loyal Customer,48,Business travel,Business,2454,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +98769,29019,Female,Loyal Customer,52,Business travel,Business,587,5,5,5,5,3,5,5,4,4,4,4,1,4,1,0,0.0,satisfied +98770,15659,Male,Loyal Customer,69,Personal Travel,Business,764,1,5,1,1,3,1,4,2,2,1,2,3,2,5,2,7.0,neutral or dissatisfied +98771,96178,Female,Loyal Customer,58,Business travel,Business,3549,4,4,4,4,3,5,5,4,4,4,4,3,4,5,57,57.0,satisfied +98772,17677,Male,Loyal Customer,52,Personal Travel,Eco Plus,282,2,0,2,2,5,2,5,5,5,3,5,3,5,5,86,79.0,neutral or dissatisfied +98773,98067,Male,Loyal Customer,62,Business travel,Business,1449,3,5,5,5,1,4,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +98774,64270,Female,Loyal Customer,58,Business travel,Business,2555,1,5,5,5,5,4,3,1,1,1,1,4,1,3,41,56.0,neutral or dissatisfied +98775,98773,Male,Loyal Customer,58,Personal Travel,Eco,1814,3,5,3,3,1,3,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +98776,22161,Female,Loyal Customer,46,Business travel,Eco,533,4,5,5,5,1,2,4,5,5,4,5,5,5,3,0,0.0,satisfied +98777,86927,Male,Loyal Customer,31,Personal Travel,Eco,341,1,5,1,3,2,1,2,2,4,3,4,5,4,2,64,59.0,neutral or dissatisfied +98778,60193,Male,Loyal Customer,40,Personal Travel,Eco Plus,1005,1,4,2,4,3,2,3,3,5,2,4,5,4,3,13,6.0,neutral or dissatisfied +98779,120538,Female,Loyal Customer,8,Personal Travel,Business,2176,0,4,0,4,4,0,4,4,4,1,5,3,2,4,0,0.0,satisfied +98780,23793,Female,Loyal Customer,33,Business travel,Business,2519,2,2,2,2,3,2,5,4,4,4,4,5,4,2,0,0.0,satisfied +98781,2827,Female,disloyal Customer,26,Business travel,Business,491,2,5,2,2,4,2,4,4,5,5,5,4,5,4,77,61.0,neutral or dissatisfied +98782,65571,Female,disloyal Customer,22,Business travel,Business,237,2,2,2,4,3,2,1,3,2,4,3,3,3,3,16,17.0,neutral or dissatisfied +98783,13688,Female,Loyal Customer,24,Business travel,Business,3778,3,3,2,3,5,5,5,3,5,3,2,5,3,5,140,144.0,satisfied +98784,91245,Male,Loyal Customer,48,Personal Travel,Eco,404,3,4,3,5,3,3,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +98785,66912,Male,Loyal Customer,47,Business travel,Business,929,5,5,4,5,5,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +98786,104325,Female,disloyal Customer,35,Business travel,Eco,409,3,2,3,4,1,3,1,1,4,1,3,1,3,1,17,16.0,neutral or dissatisfied +98787,120504,Female,Loyal Customer,36,Business travel,Eco Plus,449,1,2,2,2,1,1,1,1,4,2,3,3,3,1,23,26.0,neutral or dissatisfied +98788,6892,Female,Loyal Customer,53,Business travel,Business,265,0,0,0,4,3,5,4,5,5,5,5,4,5,5,125,125.0,satisfied +98789,65601,Female,Loyal Customer,28,Business travel,Business,237,5,5,5,5,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +98790,110250,Female,Loyal Customer,7,Personal Travel,Eco,1147,1,5,1,1,3,1,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +98791,113721,Female,Loyal Customer,27,Personal Travel,Eco,223,3,2,3,3,5,3,3,5,4,3,4,1,3,5,3,0.0,neutral or dissatisfied +98792,24825,Male,Loyal Customer,49,Business travel,Business,3121,1,1,1,1,4,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +98793,68872,Female,Loyal Customer,26,Business travel,Business,936,1,3,4,4,1,1,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +98794,90844,Female,Loyal Customer,42,Business travel,Business,3499,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +98795,68294,Male,disloyal Customer,42,Business travel,Business,1797,5,5,5,1,5,5,5,5,3,3,3,4,4,5,0,0.0,satisfied +98796,3117,Female,disloyal Customer,22,Business travel,Eco,1013,1,1,1,3,5,1,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +98797,32089,Male,disloyal Customer,40,Business travel,Eco,102,3,0,3,1,3,3,3,3,5,2,1,2,4,3,14,13.0,neutral or dissatisfied +98798,40796,Male,Loyal Customer,50,Business travel,Eco,532,4,4,4,4,4,4,4,4,2,2,5,3,3,4,0,0.0,satisfied +98799,124191,Male,Loyal Customer,48,Business travel,Business,2176,1,1,5,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +98800,14589,Female,Loyal Customer,17,Personal Travel,Eco,986,0,2,0,4,3,0,3,3,4,3,3,2,4,3,0,0.0,satisfied +98801,123150,Male,Loyal Customer,31,Business travel,Business,507,4,4,3,4,5,4,5,5,5,3,4,5,4,5,0,5.0,satisfied +98802,35077,Female,Loyal Customer,17,Personal Travel,Business,1069,2,4,2,3,4,2,4,4,2,5,4,4,5,4,0,0.0,neutral or dissatisfied +98803,30063,Male,Loyal Customer,30,Business travel,Eco,234,0,0,0,3,3,0,3,3,1,1,3,1,1,3,0,0.0,satisfied +98804,98824,Male,disloyal Customer,25,Business travel,Eco,763,3,3,3,3,4,3,4,4,1,1,3,2,3,4,78,99.0,neutral or dissatisfied +98805,71594,Female,Loyal Customer,22,Business travel,Business,2505,2,4,4,4,2,2,2,2,1,5,3,4,3,2,0,0.0,neutral or dissatisfied +98806,97085,Male,disloyal Customer,28,Business travel,Business,1129,4,3,3,3,1,3,1,1,4,3,4,3,5,1,0,0.0,satisfied +98807,30292,Female,Loyal Customer,18,Business travel,Business,1476,1,1,1,1,4,4,4,4,1,1,1,2,5,4,0,20.0,satisfied +98808,51369,Female,Loyal Customer,31,Personal Travel,Eco Plus,373,1,3,1,3,3,1,3,3,1,2,1,5,2,3,0,0.0,neutral or dissatisfied +98809,24735,Female,Loyal Customer,57,Business travel,Business,432,5,5,3,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +98810,94203,Male,Loyal Customer,26,Business travel,Business,2604,4,4,5,4,3,3,3,3,4,4,5,4,4,3,64,57.0,satisfied +98811,74729,Male,Loyal Customer,31,Personal Travel,Eco,1235,1,5,1,4,5,1,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +98812,7169,Female,Loyal Customer,46,Business travel,Business,116,1,5,5,5,1,2,2,3,3,3,1,4,3,3,47,99.0,neutral or dissatisfied +98813,47224,Female,Loyal Customer,58,Personal Travel,Eco,620,3,4,2,3,3,5,5,3,3,2,3,4,3,5,15,4.0,neutral or dissatisfied +98814,64012,Female,disloyal Customer,27,Business travel,Business,919,2,2,2,2,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +98815,16030,Female,Loyal Customer,69,Personal Travel,Eco,780,2,5,2,1,2,5,4,3,3,2,5,4,3,4,41,35.0,neutral or dissatisfied +98816,107302,Female,Loyal Customer,33,Personal Travel,Eco,307,2,5,2,5,5,2,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +98817,123067,Male,Loyal Customer,47,Business travel,Business,1988,1,1,1,1,4,4,5,4,4,4,4,4,4,4,0,1.0,satisfied +98818,71993,Female,Loyal Customer,68,Personal Travel,Eco,1440,3,4,3,2,3,4,4,4,4,5,4,4,5,4,213,186.0,neutral or dissatisfied +98819,14704,Female,disloyal Customer,36,Business travel,Eco,419,1,1,1,3,3,1,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +98820,77051,Female,disloyal Customer,22,Business travel,Eco,920,0,0,0,4,2,0,2,2,5,4,3,4,5,2,0,0.0,satisfied +98821,108538,Female,Loyal Customer,57,Personal Travel,Eco Plus,649,2,4,2,2,4,5,2,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +98822,46894,Male,Loyal Customer,52,Business travel,Eco,964,3,4,1,1,3,3,3,3,2,5,2,3,1,3,0,0.0,satisfied +98823,69374,Male,Loyal Customer,22,Business travel,Business,2510,3,1,2,1,3,3,3,3,2,3,3,3,3,3,250,271.0,neutral or dissatisfied +98824,41258,Male,Loyal Customer,56,Personal Travel,Eco,1034,5,5,5,1,2,5,2,2,4,4,4,4,5,2,0,0.0,satisfied +98825,21981,Male,Loyal Customer,64,Personal Travel,Eco,551,3,4,3,3,2,3,1,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +98826,119539,Male,Loyal Customer,53,Personal Travel,Eco,759,2,4,2,3,1,2,1,1,4,2,4,5,4,1,0,8.0,neutral or dissatisfied +98827,45535,Male,Loyal Customer,22,Business travel,Business,566,1,1,1,1,4,4,4,4,5,1,3,1,5,4,0,0.0,satisfied +98828,84520,Male,Loyal Customer,41,Business travel,Business,2556,4,4,4,4,5,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +98829,86946,Male,Loyal Customer,32,Business travel,Eco,907,4,2,2,2,4,4,4,4,3,5,4,2,4,4,9,14.0,neutral or dissatisfied +98830,29370,Female,Loyal Customer,32,Business travel,Eco,2404,5,1,2,1,5,5,5,5,4,2,4,1,2,5,0,0.0,satisfied +98831,101884,Male,Loyal Customer,50,Business travel,Business,1984,1,1,1,1,4,4,4,3,3,3,3,4,3,4,44,13.0,satisfied +98832,61325,Male,Loyal Customer,59,Personal Travel,Eco Plus,846,3,1,3,3,2,3,2,2,1,1,4,3,4,2,66,82.0,neutral or dissatisfied +98833,20876,Female,Loyal Customer,25,Business travel,Eco Plus,534,0,3,0,3,3,0,3,3,4,2,1,2,3,3,0,0.0,satisfied +98834,59241,Male,disloyal Customer,30,Business travel,Eco Plus,649,3,3,3,1,5,3,5,5,2,5,1,2,4,5,13,10.0,neutral or dissatisfied +98835,53127,Female,Loyal Customer,46,Personal Travel,Eco,2065,2,4,2,4,3,5,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +98836,117956,Female,Loyal Customer,55,Business travel,Business,2134,2,3,3,3,3,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +98837,109497,Female,Loyal Customer,46,Business travel,Business,3117,5,5,5,5,3,4,4,5,5,5,5,3,5,5,33,35.0,satisfied +98838,1471,Female,Loyal Customer,11,Personal Travel,Eco,772,3,2,3,3,3,3,3,3,1,4,3,2,3,3,35,30.0,neutral or dissatisfied +98839,4964,Female,Loyal Customer,12,Personal Travel,Eco,931,2,5,2,1,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +98840,115975,Male,Loyal Customer,17,Personal Travel,Eco,308,4,5,4,5,5,4,5,5,5,2,2,3,4,5,0,4.0,neutral or dissatisfied +98841,76233,Female,Loyal Customer,48,Business travel,Business,1399,3,1,1,1,3,3,2,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +98842,67965,Female,Loyal Customer,58,Business travel,Business,1235,2,2,5,2,5,4,5,4,4,4,4,5,4,5,0,38.0,satisfied +98843,5696,Male,disloyal Customer,36,Business travel,Eco,196,4,4,4,4,3,4,3,3,3,3,4,4,4,3,3,28.0,neutral or dissatisfied +98844,106683,Male,Loyal Customer,31,Personal Travel,Eco,451,1,3,1,3,2,1,2,2,1,5,4,3,3,2,82,78.0,neutral or dissatisfied +98845,47322,Female,Loyal Customer,20,Business travel,Business,599,4,4,4,4,3,4,3,3,4,3,2,2,4,3,48,40.0,satisfied +98846,114126,Female,Loyal Customer,24,Business travel,Business,3904,1,1,3,1,4,4,4,4,4,4,4,5,5,4,8,7.0,satisfied +98847,72161,Male,Loyal Customer,20,Business travel,Business,1888,2,2,3,2,5,5,5,5,5,4,5,5,5,5,0,4.0,satisfied +98848,15009,Male,disloyal Customer,43,Business travel,Eco,557,3,4,3,4,3,3,5,3,3,4,4,1,5,3,0,0.0,neutral or dissatisfied +98849,32420,Male,Loyal Customer,55,Business travel,Business,102,5,3,5,5,4,2,5,4,4,4,4,2,4,3,0,0.0,satisfied +98850,122125,Female,Loyal Customer,7,Personal Travel,Eco Plus,130,2,3,2,4,5,2,5,5,3,4,3,3,4,5,16,20.0,neutral or dissatisfied +98851,54415,Male,Loyal Customer,43,Business travel,Business,3378,2,3,3,3,1,3,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +98852,117636,Male,Loyal Customer,16,Personal Travel,Eco,872,2,4,2,4,5,2,3,5,2,4,5,1,1,5,3,0.0,neutral or dissatisfied +98853,50016,Female,disloyal Customer,40,Business travel,Business,262,4,4,4,1,4,4,4,4,5,2,5,2,3,4,55,70.0,satisfied +98854,81094,Female,Loyal Customer,22,Personal Travel,Eco,931,2,4,1,1,1,1,1,1,4,5,5,5,4,1,15,1.0,neutral or dissatisfied +98855,54984,Male,disloyal Customer,25,Business travel,Eco,1355,4,4,4,5,5,4,5,5,5,2,4,3,5,5,3,0.0,satisfied +98856,49451,Male,Loyal Customer,50,Business travel,Eco,158,4,2,2,2,4,4,4,1,3,4,1,4,5,4,134,130.0,satisfied +98857,129312,Male,disloyal Customer,35,Business travel,Business,2586,3,3,3,4,3,3,5,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +98858,104671,Male,Loyal Customer,8,Personal Travel,Eco,641,3,5,3,3,4,3,4,4,5,2,5,4,5,4,81,68.0,neutral or dissatisfied +98859,101104,Male,Loyal Customer,38,Business travel,Business,3824,3,3,3,3,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +98860,91844,Male,Loyal Customer,45,Business travel,Business,1619,3,3,5,3,2,4,5,5,5,5,5,4,5,3,1,0.0,satisfied +98861,2057,Male,Loyal Customer,42,Business travel,Business,733,1,1,2,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +98862,78306,Female,Loyal Customer,54,Business travel,Business,1598,5,5,5,5,3,3,4,5,5,5,5,4,5,4,3,0.0,satisfied +98863,100160,Male,Loyal Customer,34,Business travel,Business,725,4,2,2,2,3,3,3,4,4,4,4,2,4,4,45,63.0,neutral or dissatisfied +98864,111842,Male,disloyal Customer,38,Business travel,Business,628,4,3,3,1,2,3,2,2,3,2,5,3,4,2,51,36.0,satisfied +98865,124481,Female,Loyal Customer,58,Business travel,Business,930,1,1,1,1,3,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +98866,57684,Male,Loyal Customer,57,Business travel,Business,3447,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +98867,103035,Male,Loyal Customer,36,Business travel,Business,2253,2,5,5,5,2,3,3,2,2,2,2,3,2,2,10,0.0,neutral or dissatisfied +98868,124070,Female,Loyal Customer,22,Personal Travel,Eco,2153,3,4,3,1,5,3,4,5,4,3,4,5,5,5,10,5.0,neutral or dissatisfied +98869,107258,Male,Loyal Customer,31,Business travel,Business,283,2,5,5,5,2,1,2,2,3,5,2,3,3,2,1,0.0,neutral or dissatisfied +98870,96118,Female,Loyal Customer,44,Business travel,Business,1522,1,1,1,1,2,4,4,2,2,2,2,5,2,4,2,0.0,satisfied +98871,5585,Female,Loyal Customer,28,Business travel,Business,2064,4,4,4,4,4,4,4,4,4,3,5,5,5,4,0,0.0,satisfied +98872,115130,Female,Loyal Customer,57,Business travel,Business,2830,2,2,2,2,2,5,4,4,4,4,4,4,4,3,11,8.0,satisfied +98873,97192,Female,Loyal Customer,44,Personal Travel,Eco,715,1,5,1,1,4,1,5,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +98874,104447,Female,Loyal Customer,30,Personal Travel,Eco Plus,1138,4,5,4,4,1,4,1,1,4,5,4,3,5,1,1,21.0,neutral or dissatisfied +98875,65010,Female,Loyal Customer,39,Business travel,Business,2807,2,2,2,2,3,4,5,4,4,4,5,4,4,5,71,72.0,satisfied +98876,50684,Female,Loyal Customer,24,Personal Travel,Eco,209,3,5,3,4,5,3,5,5,5,1,2,1,2,5,0,10.0,neutral or dissatisfied +98877,112849,Male,disloyal Customer,36,Business travel,Business,1476,3,3,3,1,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +98878,28022,Female,disloyal Customer,15,Business travel,Eco,763,4,4,4,1,2,4,2,2,5,3,2,1,4,2,0,0.0,neutral or dissatisfied +98879,129659,Male,Loyal Customer,58,Business travel,Business,2825,2,2,3,2,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +98880,79160,Male,Loyal Customer,51,Personal Travel,Eco,2239,4,5,4,3,3,4,2,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +98881,73079,Female,Loyal Customer,27,Business travel,Business,3810,1,1,1,1,5,5,5,5,5,3,4,4,4,5,37,67.0,satisfied +98882,34484,Male,Loyal Customer,7,Personal Travel,Eco,266,3,3,3,4,1,3,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +98883,97791,Female,disloyal Customer,36,Business travel,Eco,471,3,2,4,4,3,4,3,3,4,2,4,2,3,3,8,0.0,neutral or dissatisfied +98884,43570,Male,disloyal Customer,26,Business travel,Eco,1200,2,2,2,3,5,2,5,5,3,1,4,5,3,5,0,0.0,neutral or dissatisfied +98885,42366,Male,Loyal Customer,69,Personal Travel,Eco,329,1,3,1,1,5,1,5,5,2,1,5,1,4,5,49,54.0,neutral or dissatisfied +98886,80752,Female,Loyal Customer,32,Personal Travel,Eco,393,3,5,3,3,4,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +98887,56890,Male,Loyal Customer,45,Business travel,Business,2425,3,3,3,3,4,4,4,3,4,3,5,4,3,4,0,5.0,satisfied +98888,42204,Female,Loyal Customer,43,Business travel,Business,1939,1,1,1,1,5,1,5,5,5,5,5,2,5,3,0,1.0,satisfied +98889,33032,Female,Loyal Customer,38,Personal Travel,Eco,101,3,5,3,1,2,3,3,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +98890,46191,Male,Loyal Customer,39,Business travel,Business,3523,2,3,3,3,5,4,3,2,2,2,2,1,2,2,10,1.0,neutral or dissatisfied +98891,52065,Male,disloyal Customer,33,Business travel,Business,351,3,3,3,1,2,3,2,2,3,5,2,2,1,2,0,0.0,neutral or dissatisfied +98892,30157,Male,Loyal Customer,35,Personal Travel,Eco,539,2,5,4,2,4,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +98893,25099,Male,Loyal Customer,60,Personal Travel,Eco,369,3,3,3,3,4,3,4,4,1,4,3,3,3,4,0,0.0,neutral or dissatisfied +98894,129233,Female,Loyal Customer,53,Business travel,Business,1903,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +98895,104140,Male,Loyal Customer,68,Personal Travel,Eco,448,3,4,3,2,3,3,5,3,4,2,2,2,4,3,0,0.0,neutral or dissatisfied +98896,89026,Male,disloyal Customer,22,Business travel,Eco,1284,2,2,2,4,2,2,2,2,4,4,4,3,4,2,18,0.0,neutral or dissatisfied +98897,103692,Female,Loyal Customer,39,Business travel,Business,405,4,1,1,1,4,4,4,4,3,3,3,4,3,4,196,218.0,neutral or dissatisfied +98898,107124,Male,disloyal Customer,20,Business travel,Eco,842,3,3,3,4,4,3,4,4,1,5,4,2,3,4,8,0.0,neutral or dissatisfied +98899,60708,Male,Loyal Customer,14,Business travel,Business,1605,2,1,1,1,2,2,2,2,2,1,3,2,3,2,2,0.0,neutral or dissatisfied +98900,127945,Female,Loyal Customer,7,Personal Travel,Eco Plus,2300,3,1,3,3,1,3,1,1,3,4,3,3,4,1,0,7.0,neutral or dissatisfied +98901,88786,Female,Loyal Customer,50,Business travel,Business,3438,2,2,2,2,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +98902,35889,Male,Loyal Customer,33,Personal Travel,Eco,1065,3,4,3,3,2,3,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +98903,95345,Female,Loyal Customer,8,Personal Travel,Eco,248,2,4,2,1,1,2,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +98904,117263,Male,Loyal Customer,47,Personal Travel,Eco,338,3,4,3,4,2,3,2,2,5,2,5,4,4,2,3,0.0,neutral or dissatisfied +98905,19498,Female,disloyal Customer,26,Business travel,Eco,350,4,0,3,3,3,3,3,3,5,5,1,1,1,3,2,15.0,satisfied +98906,61697,Male,Loyal Customer,65,Business travel,Business,1379,2,5,5,5,5,3,3,2,2,2,2,3,2,2,4,1.0,neutral or dissatisfied +98907,123998,Male,Loyal Customer,41,Business travel,Business,3021,0,5,0,2,3,5,5,1,1,1,1,3,1,3,0,0.0,satisfied +98908,66706,Male,Loyal Customer,14,Business travel,Business,802,3,1,1,1,3,4,3,3,2,5,4,4,4,3,13,0.0,neutral or dissatisfied +98909,14303,Male,Loyal Customer,33,Business travel,Eco,429,1,3,3,3,1,1,1,1,1,1,1,1,2,1,3,5.0,neutral or dissatisfied +98910,84019,Female,Loyal Customer,46,Personal Travel,Eco,373,2,5,2,1,3,1,1,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +98911,115767,Female,Loyal Customer,36,Business travel,Eco,447,1,1,2,1,1,1,1,1,4,2,4,4,4,1,1,0.0,neutral or dissatisfied +98912,17691,Female,Loyal Customer,69,Business travel,Eco Plus,349,5,2,2,2,1,5,2,5,5,5,5,2,5,5,0,1.0,satisfied +98913,81822,Male,disloyal Customer,27,Business travel,Eco,906,1,1,1,4,5,1,5,5,2,2,3,3,4,5,0,19.0,neutral or dissatisfied +98914,33181,Female,disloyal Customer,57,Business travel,Eco Plus,216,1,1,1,3,5,1,4,5,4,3,1,2,5,5,0,0.0,neutral or dissatisfied +98915,84130,Female,Loyal Customer,26,Personal Travel,Eco,1569,1,4,1,2,3,1,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +98916,85008,Male,Loyal Customer,43,Business travel,Eco,1590,1,2,2,2,1,1,1,1,2,5,4,1,4,1,0,0.0,neutral or dissatisfied +98917,57566,Female,Loyal Customer,58,Business travel,Eco,1597,3,5,5,5,1,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +98918,80818,Female,Loyal Customer,50,Business travel,Business,2299,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +98919,118421,Female,Loyal Customer,44,Business travel,Business,370,2,2,2,2,5,5,4,4,4,4,4,5,4,4,11,12.0,satisfied +98920,45733,Female,disloyal Customer,26,Business travel,Eco,1063,3,3,3,2,5,3,4,5,2,2,1,2,2,5,0,0.0,neutral or dissatisfied +98921,125164,Female,Loyal Customer,31,Business travel,Business,3440,3,2,2,2,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +98922,75178,Male,Loyal Customer,51,Business travel,Business,1652,4,4,4,4,5,3,5,5,5,5,5,5,5,5,39,16.0,satisfied +98923,52066,Female,disloyal Customer,26,Business travel,Eco,639,4,3,4,3,3,4,3,3,5,1,1,4,1,3,7,0.0,neutral or dissatisfied +98924,42380,Male,Loyal Customer,14,Personal Travel,Eco,817,3,3,4,5,1,4,1,1,2,1,4,2,2,1,0,0.0,neutral or dissatisfied +98925,14486,Female,Loyal Customer,34,Personal Travel,Eco,495,2,5,2,1,3,2,4,3,5,3,5,5,4,3,7,0.0,neutral or dissatisfied +98926,82697,Female,Loyal Customer,42,Business travel,Business,1746,3,3,3,3,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +98927,126023,Male,Loyal Customer,45,Business travel,Business,3063,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,5.0,satisfied +98928,59791,Male,Loyal Customer,56,Business travel,Business,1025,1,1,2,1,4,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +98929,38114,Female,disloyal Customer,20,Business travel,Eco,1121,3,4,4,2,1,4,1,1,2,4,1,2,4,1,0,0.0,neutral or dissatisfied +98930,67563,Male,Loyal Customer,42,Business travel,Business,1126,1,1,1,1,5,5,5,2,2,2,2,3,2,3,8,0.0,satisfied +98931,54810,Male,Loyal Customer,44,Business travel,Business,2539,1,1,1,1,3,3,5,2,2,2,2,2,2,5,0,0.0,satisfied +98932,2318,Male,Loyal Customer,37,Personal Travel,Eco,1041,4,4,4,5,2,4,2,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +98933,119800,Male,Loyal Customer,47,Business travel,Business,2857,2,2,3,2,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +98934,69749,Female,Loyal Customer,36,Business travel,Eco,1085,2,1,1,1,2,2,2,2,3,5,4,1,4,2,3,0.0,neutral or dissatisfied +98935,30934,Female,disloyal Customer,25,Business travel,Eco,1024,1,1,1,3,3,1,3,3,5,4,4,3,4,3,5,3.0,neutral or dissatisfied +98936,105505,Female,Loyal Customer,59,Business travel,Business,2937,2,2,2,2,3,4,5,5,5,5,5,4,5,4,26,22.0,satisfied +98937,128463,Male,Loyal Customer,62,Personal Travel,Eco,647,3,4,2,2,3,2,4,3,4,5,2,1,5,3,0,0.0,neutral or dissatisfied +98938,58897,Male,Loyal Customer,56,Business travel,Eco,888,1,1,1,1,1,1,1,1,2,3,3,2,3,1,14,29.0,neutral or dissatisfied +98939,79872,Male,Loyal Customer,36,Business travel,Business,3196,3,2,2,2,2,2,2,3,3,3,3,3,3,2,67,99.0,neutral or dissatisfied +98940,38168,Male,Loyal Customer,52,Personal Travel,Eco,1121,1,4,1,2,4,1,4,4,5,4,4,4,5,4,0,7.0,neutral or dissatisfied +98941,80324,Female,Loyal Customer,41,Personal Travel,Eco,746,2,4,2,3,1,2,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +98942,72536,Female,Loyal Customer,27,Business travel,Business,2738,3,3,3,3,3,3,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +98943,90818,Female,Loyal Customer,55,Business travel,Business,3243,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +98944,697,Male,Loyal Customer,43,Business travel,Business,3908,4,4,4,4,3,5,5,5,5,5,5,5,5,3,11,7.0,satisfied +98945,102393,Male,disloyal Customer,15,Business travel,Eco,386,3,3,3,3,4,3,4,4,2,2,3,3,3,4,14,30.0,neutral or dissatisfied +98946,19609,Male,Loyal Customer,65,Business travel,Business,3663,3,3,3,3,2,4,3,4,4,4,4,5,4,5,1,,satisfied +98947,104114,Female,disloyal Customer,21,Business travel,Eco,297,3,3,3,4,4,3,3,4,2,4,4,1,3,4,51,53.0,neutral or dissatisfied +98948,50987,Male,Loyal Customer,29,Personal Travel,Eco,86,3,4,3,1,3,3,3,3,5,1,5,1,3,3,0,0.0,neutral or dissatisfied +98949,74844,Male,Loyal Customer,34,Business travel,Business,1797,4,4,4,4,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +98950,22620,Male,Loyal Customer,48,Personal Travel,Eco,300,2,5,2,2,1,2,1,1,3,4,3,3,3,1,3,0.0,neutral or dissatisfied +98951,67389,Male,Loyal Customer,29,Business travel,Business,1832,1,1,1,1,4,5,4,4,4,5,4,5,5,4,1,0.0,satisfied +98952,6056,Female,Loyal Customer,8,Personal Travel,Eco,672,2,4,2,3,1,2,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +98953,84285,Male,Loyal Customer,64,Personal Travel,Eco,334,2,3,1,3,1,1,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +98954,9966,Female,disloyal Customer,17,Business travel,Eco,534,4,2,4,3,4,4,4,1,3,4,4,4,1,4,183,196.0,neutral or dissatisfied +98955,90316,Female,disloyal Customer,21,Business travel,Business,829,5,0,5,2,4,5,4,4,5,5,4,4,5,4,0,1.0,satisfied +98956,48862,Female,Loyal Customer,54,Business travel,Business,2871,4,4,4,4,4,2,1,4,4,4,5,2,4,2,0,26.0,satisfied +98957,75162,Female,Loyal Customer,42,Business travel,Business,1846,4,4,4,4,4,5,5,5,5,5,5,5,5,5,34,80.0,satisfied +98958,22627,Female,Loyal Customer,42,Personal Travel,Eco,300,3,3,3,3,3,3,3,5,5,3,5,1,5,3,52,62.0,neutral or dissatisfied +98959,34385,Female,Loyal Customer,48,Business travel,Eco,612,4,2,2,2,5,3,2,4,4,4,4,5,4,5,5,0.0,satisfied +98960,121784,Female,Loyal Customer,45,Business travel,Business,337,4,1,1,1,5,4,4,4,4,4,4,3,4,2,0,22.0,neutral or dissatisfied +98961,91476,Female,Loyal Customer,64,Personal Travel,Eco,859,3,4,3,2,4,5,5,5,5,3,1,4,5,3,0,0.0,neutral or dissatisfied +98962,53756,Female,Loyal Customer,27,Business travel,Eco,1195,5,5,5,5,5,5,5,5,4,4,3,5,5,5,55,48.0,satisfied +98963,7611,Female,Loyal Customer,9,Personal Travel,Eco,825,1,4,1,4,2,1,3,2,5,2,5,5,4,2,22,29.0,neutral or dissatisfied +98964,38560,Female,Loyal Customer,63,Personal Travel,Eco,2569,2,3,2,4,2,4,5,1,1,2,1,2,1,2,30,25.0,neutral or dissatisfied +98965,18554,Male,Loyal Customer,49,Business travel,Eco,305,3,4,4,4,2,3,2,2,1,3,4,1,4,2,35,25.0,neutral or dissatisfied +98966,54018,Male,Loyal Customer,54,Business travel,Eco,691,5,2,2,2,4,5,4,4,2,3,5,5,2,4,0,0.0,satisfied +98967,63230,Female,Loyal Customer,60,Business travel,Business,2942,4,4,4,4,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +98968,17041,Male,Loyal Customer,27,Business travel,Eco,1134,5,3,3,3,5,5,5,5,1,5,1,1,3,5,51,37.0,satisfied +98969,101917,Male,Loyal Customer,47,Business travel,Business,2039,1,1,1,1,3,4,4,3,3,3,3,4,3,3,36,17.0,satisfied +98970,108210,Female,disloyal Customer,26,Business travel,Eco,777,3,3,3,3,1,3,1,1,3,3,2,1,2,1,0,0.0,neutral or dissatisfied +98971,61056,Male,Loyal Customer,43,Business travel,Business,1703,1,1,1,1,3,4,5,4,4,4,4,5,4,4,5,5.0,satisfied +98972,23493,Male,Loyal Customer,61,Business travel,Business,2784,1,1,1,1,2,5,5,4,4,5,4,5,4,3,56,79.0,satisfied +98973,99716,Male,Loyal Customer,64,Personal Travel,Eco Plus,667,4,5,4,2,3,4,4,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +98974,124888,Male,disloyal Customer,37,Business travel,Business,728,2,2,2,4,2,2,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +98975,19983,Male,Loyal Customer,30,Business travel,Business,599,5,5,5,5,2,2,2,2,5,1,2,1,1,2,0,0.0,satisfied +98976,90233,Male,Loyal Customer,34,Personal Travel,Eco Plus,1127,2,5,2,1,5,2,5,5,3,5,4,3,4,5,0,0.0,neutral or dissatisfied +98977,37683,Male,Loyal Customer,16,Personal Travel,Eco,1010,2,3,2,3,3,2,4,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +98978,76325,Female,Loyal Customer,55,Personal Travel,Eco,2182,3,5,3,2,2,2,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +98979,35818,Male,Loyal Customer,29,Business travel,Business,937,4,3,4,4,5,5,5,5,1,4,2,3,2,5,0,41.0,satisfied +98980,120360,Male,Loyal Customer,53,Business travel,Business,2787,4,4,1,4,4,5,4,4,4,4,4,3,4,5,0,6.0,satisfied +98981,40128,Male,Loyal Customer,65,Personal Travel,Eco,200,2,4,2,1,4,2,4,4,5,4,1,1,4,4,0,0.0,neutral or dissatisfied +98982,70217,Female,Loyal Customer,39,Business travel,Business,258,4,4,4,4,3,5,5,4,4,5,4,4,4,5,83,98.0,satisfied +98983,26925,Male,Loyal Customer,22,Personal Travel,Eco,1770,2,1,2,4,5,2,2,5,1,4,4,1,3,5,0,5.0,neutral or dissatisfied +98984,52533,Female,disloyal Customer,37,Business travel,Eco,119,3,3,3,1,4,3,3,4,4,3,3,4,3,4,9,13.0,neutral or dissatisfied +98985,27234,Male,disloyal Customer,38,Business travel,Eco,624,4,0,4,1,4,4,2,4,4,3,2,4,2,4,0,0.0,neutral or dissatisfied +98986,25343,Female,Loyal Customer,31,Business travel,Eco Plus,829,3,5,5,5,3,3,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +98987,36243,Male,Loyal Customer,50,Business travel,Eco,612,4,3,3,3,4,4,4,4,5,1,4,2,1,4,0,0.0,satisfied +98988,100202,Male,Loyal Customer,59,Personal Travel,Eco Plus,725,1,1,1,3,5,1,1,5,2,1,3,4,3,5,0,0.0,neutral or dissatisfied +98989,49635,Female,disloyal Customer,27,Business travel,Eco,308,1,0,0,2,1,0,1,1,1,2,5,1,3,1,0,0.0,neutral or dissatisfied +98990,101423,Female,Loyal Customer,56,Business travel,Business,345,3,3,3,3,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +98991,112361,Male,Loyal Customer,21,Business travel,Business,862,4,4,4,4,4,4,4,4,4,4,4,3,4,4,69,61.0,satisfied +98992,92593,Male,Loyal Customer,35,Business travel,Eco,2218,3,4,4,4,3,3,3,3,1,2,4,4,4,3,0,7.0,neutral or dissatisfied +98993,19649,Male,disloyal Customer,17,Business travel,Eco,763,4,4,4,4,2,4,2,2,1,2,4,4,3,2,0,0.0,satisfied +98994,18966,Female,disloyal Customer,55,Business travel,Eco Plus,151,4,4,4,3,4,4,5,4,5,3,4,5,1,4,0,0.0,neutral or dissatisfied +98995,122660,Female,Loyal Customer,27,Business travel,Business,361,2,2,2,2,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +98996,104181,Female,Loyal Customer,56,Personal Travel,Eco,349,3,5,4,3,5,5,5,4,4,4,3,5,4,3,0,0.0,neutral or dissatisfied +98997,56551,Male,Loyal Customer,45,Business travel,Business,937,5,5,5,5,5,5,5,4,4,4,4,5,4,5,67,101.0,satisfied +98998,73216,Female,Loyal Customer,62,Personal Travel,Eco Plus,1258,4,4,4,4,4,4,5,2,2,4,2,3,2,4,27,27.0,neutral or dissatisfied +98999,13470,Female,Loyal Customer,19,Personal Travel,Eco,409,2,4,1,4,4,1,4,4,4,3,3,1,4,4,6,6.0,neutral or dissatisfied +99000,50196,Male,Loyal Customer,23,Business travel,Business,373,2,5,5,5,2,2,2,2,3,2,3,3,4,2,11,6.0,neutral or dissatisfied +99001,11254,Female,Loyal Customer,10,Personal Travel,Eco,517,3,4,3,4,1,3,1,1,3,1,5,1,2,1,0,0.0,neutral or dissatisfied +99002,88256,Male,Loyal Customer,46,Business travel,Eco,581,3,4,4,4,3,3,3,3,1,1,2,3,2,3,18,14.0,neutral or dissatisfied +99003,47508,Male,Loyal Customer,50,Personal Travel,Eco,584,3,5,3,3,4,3,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +99004,104637,Female,disloyal Customer,25,Business travel,Eco Plus,861,2,0,1,3,1,1,1,1,3,4,4,4,3,1,0,0.0,neutral or dissatisfied +99005,87734,Female,Loyal Customer,56,Business travel,Business,4502,3,3,5,3,5,5,5,3,3,5,4,5,3,5,0,0.0,satisfied +99006,73052,Female,Loyal Customer,38,Business travel,Business,1089,4,4,4,4,3,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +99007,102498,Male,Loyal Customer,41,Personal Travel,Eco,258,3,1,3,4,3,3,3,3,4,1,4,1,3,3,22,8.0,neutral or dissatisfied +99008,109575,Male,Loyal Customer,44,Personal Travel,Eco,966,1,4,1,3,2,1,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +99009,13057,Female,disloyal Customer,15,Business travel,Eco,936,5,5,5,4,5,5,5,5,1,2,5,2,4,5,0,1.0,satisfied +99010,42110,Female,Loyal Customer,26,Business travel,Business,2677,3,2,2,2,3,3,3,2,5,3,4,3,2,3,150,139.0,neutral or dissatisfied +99011,52266,Male,Loyal Customer,78,Business travel,Business,370,3,2,5,2,4,3,2,3,3,3,3,3,3,4,59,60.0,neutral or dissatisfied +99012,48430,Male,Loyal Customer,26,Business travel,Business,833,3,3,3,3,4,4,4,4,1,4,3,2,2,4,0,0.0,satisfied +99013,31341,Female,Loyal Customer,34,Business travel,Eco Plus,1062,3,5,5,5,3,4,3,3,3,1,3,5,5,3,8,10.0,satisfied +99014,103434,Male,Loyal Customer,50,Business travel,Eco Plus,237,3,5,5,5,3,3,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +99015,60855,Female,Loyal Customer,55,Business travel,Eco Plus,1754,3,1,1,1,2,4,4,3,3,3,3,2,3,1,0,8.0,neutral or dissatisfied +99016,86012,Female,disloyal Customer,23,Business travel,Eco,528,0,3,0,5,3,0,1,3,3,2,5,5,5,3,0,0.0,satisfied +99017,38603,Female,Loyal Customer,34,Business travel,Business,231,3,2,2,2,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +99018,23489,Male,Loyal Customer,26,Business travel,Eco Plus,488,5,1,1,1,5,4,3,5,4,1,3,2,3,5,41,41.0,neutral or dissatisfied +99019,126970,Male,Loyal Customer,50,Business travel,Business,646,1,1,1,1,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +99020,44406,Female,Loyal Customer,10,Personal Travel,Eco,342,3,2,3,1,2,3,2,2,4,4,2,1,1,2,0,8.0,neutral or dissatisfied +99021,71818,Female,Loyal Customer,45,Business travel,Business,1829,3,3,3,3,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +99022,63852,Female,Loyal Customer,41,Business travel,Business,3574,2,2,2,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +99023,106956,Male,disloyal Customer,25,Business travel,Business,1036,0,0,1,4,5,1,5,5,4,2,5,3,4,5,11,0.0,satisfied +99024,101062,Male,Loyal Customer,30,Business travel,Business,368,4,4,4,4,4,4,4,4,1,2,3,2,5,4,0,0.0,satisfied +99025,82767,Female,Loyal Customer,35,Personal Travel,Eco,409,3,5,3,3,1,3,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +99026,72662,Male,Loyal Customer,41,Personal Travel,Eco,1121,4,5,5,3,1,5,1,1,5,4,4,3,4,1,4,0.0,neutral or dissatisfied +99027,5758,Female,Loyal Customer,45,Business travel,Business,459,1,2,2,2,5,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +99028,75085,Female,Loyal Customer,55,Business travel,Business,1814,1,1,1,1,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +99029,51182,Female,Loyal Customer,60,Business travel,Eco Plus,326,5,5,5,5,4,1,1,5,5,5,5,1,5,1,0,0.0,satisfied +99030,96245,Female,Loyal Customer,59,Personal Travel,Eco,687,0,5,0,4,3,5,4,2,2,0,2,3,2,3,4,0.0,satisfied +99031,54604,Female,Loyal Customer,46,Business travel,Business,1698,3,3,1,3,1,4,2,4,4,4,4,2,4,3,0,0.0,satisfied +99032,19464,Male,Loyal Customer,33,Business travel,Business,3475,4,4,4,4,5,5,5,5,4,2,5,5,5,5,0,7.0,satisfied +99033,120898,Male,Loyal Customer,39,Business travel,Business,861,2,3,3,3,1,4,3,2,2,2,2,2,2,2,16,14.0,neutral or dissatisfied +99034,11728,Male,Loyal Customer,59,Business travel,Business,3462,5,5,5,5,4,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +99035,34419,Female,disloyal Customer,20,Business travel,Eco,728,2,2,2,4,5,2,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +99036,60672,Female,Loyal Customer,40,Business travel,Business,1620,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +99037,13332,Female,Loyal Customer,48,Business travel,Business,748,1,1,1,1,5,2,2,4,4,4,4,1,4,3,0,0.0,satisfied +99038,105876,Male,Loyal Customer,78,Business travel,Business,3179,3,2,2,2,5,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +99039,67087,Male,Loyal Customer,36,Business travel,Eco,929,2,5,5,5,2,2,2,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +99040,73900,Male,disloyal Customer,25,Business travel,Eco,748,3,4,4,1,4,3,3,3,5,4,4,3,3,3,10,11.0,neutral or dissatisfied +99041,38183,Male,Loyal Customer,54,Personal Travel,Eco,1121,3,3,3,4,3,3,2,3,4,2,4,2,3,3,39,39.0,neutral or dissatisfied +99042,96453,Male,Loyal Customer,48,Business travel,Business,3239,3,3,5,3,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +99043,91050,Male,Loyal Customer,22,Personal Travel,Eco,270,3,0,3,4,3,3,3,3,5,5,5,4,5,3,36,72.0,neutral or dissatisfied +99044,6659,Male,disloyal Customer,22,Business travel,Business,438,4,1,4,4,1,4,4,1,2,4,3,1,3,1,0,22.0,neutral or dissatisfied +99045,59733,Male,Loyal Customer,44,Personal Travel,Eco Plus,964,2,1,2,1,3,2,3,3,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +99046,7946,Male,disloyal Customer,33,Business travel,Business,594,2,2,2,5,4,2,3,4,4,4,4,5,4,4,72,58.0,neutral or dissatisfied +99047,79276,Female,Loyal Customer,42,Personal Travel,Eco,2454,3,2,3,3,2,3,3,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +99048,51267,Female,Loyal Customer,34,Business travel,Eco Plus,109,0,0,0,1,3,0,3,3,1,5,4,3,4,3,0,0.0,satisfied +99049,1260,Male,Loyal Customer,38,Personal Travel,Eco,164,2,5,0,5,5,0,5,5,3,5,4,5,4,5,4,0.0,neutral or dissatisfied +99050,123848,Female,Loyal Customer,28,Business travel,Eco,544,4,3,3,3,4,4,4,4,4,3,4,3,3,4,0,0.0,neutral or dissatisfied +99051,46926,Female,disloyal Customer,25,Business travel,Eco,419,3,2,3,4,2,3,2,2,2,4,3,1,4,2,15,4.0,neutral or dissatisfied +99052,64534,Female,disloyal Customer,33,Business travel,Business,551,4,4,4,4,3,4,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +99053,25954,Female,Loyal Customer,43,Business travel,Business,946,1,4,1,1,1,1,5,5,5,5,5,1,5,5,0,7.0,satisfied +99054,94091,Male,Loyal Customer,25,Personal Travel,Business,189,1,4,1,3,1,1,1,1,2,1,4,3,3,1,3,0.0,neutral or dissatisfied +99055,52889,Male,Loyal Customer,52,Personal Travel,Eco,836,4,1,4,3,5,4,1,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +99056,110859,Male,Loyal Customer,21,Business travel,Business,2666,2,2,2,2,4,4,4,4,3,2,4,5,4,4,0,1.0,satisfied +99057,129054,Male,Loyal Customer,40,Business travel,Business,244,0,0,0,1,5,2,5,1,1,1,1,2,1,4,0,0.0,satisfied +99058,4254,Female,Loyal Customer,44,Personal Travel,Eco Plus,1020,2,4,2,3,2,3,4,2,2,2,2,4,2,3,0,15.0,neutral or dissatisfied +99059,34536,Male,disloyal Customer,18,Business travel,Eco,636,3,0,3,3,3,3,3,3,2,2,2,2,1,3,0,0.0,neutral or dissatisfied +99060,97411,Female,Loyal Customer,43,Business travel,Business,587,4,4,4,4,4,4,5,5,5,5,5,4,5,3,25,26.0,satisfied +99061,108529,Female,Loyal Customer,38,Business travel,Business,649,2,2,2,2,3,5,5,3,3,3,3,3,3,4,0,17.0,satisfied +99062,34968,Female,disloyal Customer,37,Business travel,Eco,273,0,0,0,4,3,0,3,3,2,4,3,2,1,3,0,0.0,satisfied +99063,17809,Female,disloyal Customer,29,Business travel,Eco,1075,1,1,1,2,3,1,3,3,2,4,2,4,2,3,8,0.0,neutral or dissatisfied +99064,59299,Female,Loyal Customer,31,Business travel,Business,2338,1,1,1,1,4,4,4,4,3,5,5,5,5,4,9,0.0,satisfied +99065,73629,Male,Loyal Customer,49,Business travel,Business,2586,4,3,4,4,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +99066,91124,Female,Loyal Customer,8,Personal Travel,Eco,271,3,4,4,1,4,4,4,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +99067,80399,Male,Loyal Customer,51,Business travel,Business,368,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +99068,127997,Male,disloyal Customer,37,Business travel,Business,1488,2,2,2,4,4,2,4,4,3,5,5,4,4,4,1,0.0,neutral or dissatisfied +99069,7810,Male,disloyal Customer,29,Business travel,Eco,710,1,1,1,3,3,1,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +99070,9068,Male,Loyal Customer,43,Business travel,Business,3979,3,3,3,3,5,4,4,5,5,5,4,4,5,4,0,0.0,satisfied +99071,35578,Female,Loyal Customer,39,Business travel,Eco Plus,950,5,5,5,5,5,5,5,5,5,1,1,1,1,5,0,8.0,satisfied +99072,116687,Female,Loyal Customer,38,Business travel,Business,3291,2,2,2,2,3,4,4,3,3,4,3,3,3,3,11,3.0,satisfied +99073,104756,Female,Loyal Customer,69,Personal Travel,Eco,1407,2,5,3,2,4,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +99074,88707,Female,Loyal Customer,68,Personal Travel,Eco,515,3,1,3,3,4,3,4,4,4,3,4,4,4,2,44,32.0,neutral or dissatisfied +99075,110546,Male,Loyal Customer,30,Business travel,Business,2842,3,3,3,3,3,3,3,3,4,5,3,3,4,3,8,6.0,neutral or dissatisfied +99076,16420,Female,disloyal Customer,20,Business travel,Eco,529,4,4,4,4,3,4,3,3,2,2,1,2,1,3,51,48.0,neutral or dissatisfied +99077,46280,Female,Loyal Customer,45,Business travel,Eco Plus,455,4,3,3,3,5,2,2,4,4,4,4,3,4,3,12,36.0,satisfied +99078,125419,Male,Loyal Customer,57,Business travel,Business,735,1,1,1,1,3,5,4,5,5,5,5,4,5,3,6,7.0,satisfied +99079,81070,Male,Loyal Customer,49,Business travel,Business,931,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +99080,110710,Female,Loyal Customer,47,Business travel,Business,1166,5,5,5,5,4,4,5,4,4,4,4,4,4,5,20,9.0,satisfied +99081,19691,Male,Loyal Customer,24,Business travel,Business,3434,1,1,1,1,5,5,5,5,5,1,3,1,2,5,29,27.0,satisfied +99082,74970,Male,Loyal Customer,56,Personal Travel,Eco,2586,2,4,2,3,2,2,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +99083,6525,Male,Loyal Customer,63,Personal Travel,Eco,599,3,0,3,2,3,1,1,4,5,4,4,1,3,1,106,149.0,neutral or dissatisfied +99084,55464,Female,Loyal Customer,39,Business travel,Business,1825,4,4,4,4,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +99085,4562,Male,Loyal Customer,44,Business travel,Business,2715,3,3,4,3,5,3,4,5,5,4,5,2,5,3,74,82.0,satisfied +99086,39114,Female,disloyal Customer,62,Business travel,Eco,297,3,0,3,3,3,3,3,3,2,3,3,5,3,3,1,0.0,neutral or dissatisfied +99087,113033,Female,Loyal Customer,41,Business travel,Business,569,5,5,5,5,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +99088,120177,Female,Loyal Customer,45,Business travel,Business,1927,4,4,5,4,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +99089,113525,Female,disloyal Customer,46,Business travel,Eco,386,4,1,4,4,3,4,3,3,2,5,3,4,3,3,3,0.0,neutral or dissatisfied +99090,51976,Male,Loyal Customer,54,Business travel,Eco,347,1,0,0,3,3,1,3,3,3,5,4,1,3,3,2,0.0,neutral or dissatisfied +99091,121428,Female,Loyal Customer,38,Business travel,Business,2522,1,3,3,3,3,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +99092,88691,Male,Loyal Customer,8,Personal Travel,Eco,404,3,5,3,1,5,3,5,5,4,2,4,5,4,5,0,2.0,neutral or dissatisfied +99093,121957,Female,Loyal Customer,25,Business travel,Business,430,1,1,1,1,3,3,3,3,3,5,4,5,5,3,9,5.0,satisfied +99094,69341,Female,Loyal Customer,57,Business travel,Business,2992,2,2,2,2,4,4,4,4,2,4,4,4,5,4,155,161.0,satisfied +99095,10250,Male,Loyal Customer,67,Personal Travel,Business,191,1,4,1,4,2,5,4,1,1,1,1,4,1,4,5,10.0,neutral or dissatisfied +99096,90983,Male,Loyal Customer,75,Business travel,Business,1703,2,2,2,2,5,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +99097,65814,Male,Loyal Customer,30,Business travel,Business,1389,5,5,5,5,4,4,4,4,3,3,4,3,4,4,6,0.0,satisfied +99098,29177,Female,disloyal Customer,22,Business travel,Eco Plus,954,1,1,0,3,4,0,4,4,2,5,3,4,3,4,0,0.0,neutral or dissatisfied +99099,24328,Female,disloyal Customer,38,Business travel,Eco,1083,3,2,2,4,5,2,5,5,4,5,1,3,1,5,3,0.0,neutral or dissatisfied +99100,129797,Male,Loyal Customer,45,Personal Travel,Eco,337,1,5,3,1,4,3,4,4,5,2,5,3,5,4,1,0.0,neutral or dissatisfied +99101,90413,Female,Loyal Customer,55,Business travel,Business,2115,5,3,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +99102,44579,Male,Loyal Customer,35,Business travel,Business,2505,5,5,5,5,5,2,4,4,4,4,5,3,4,5,51,53.0,satisfied +99103,37133,Female,Loyal Customer,25,Business travel,Business,3104,2,4,4,4,2,2,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +99104,33949,Female,Loyal Customer,53,Personal Travel,Eco,1188,4,1,4,4,4,2,4,2,2,4,1,2,2,2,0,0.0,neutral or dissatisfied +99105,105537,Male,Loyal Customer,59,Business travel,Business,611,5,5,5,5,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +99106,36291,Male,Loyal Customer,41,Business travel,Business,2905,5,5,5,5,2,3,5,4,4,4,5,1,4,1,0,0.0,satisfied +99107,100868,Female,Loyal Customer,22,Business travel,Eco,1605,1,5,5,5,1,1,4,1,3,4,2,3,3,1,65,56.0,neutral or dissatisfied +99108,22849,Male,Loyal Customer,54,Personal Travel,Eco,302,3,4,3,3,1,3,1,1,3,5,4,4,4,1,41,30.0,neutral or dissatisfied +99109,68618,Male,Loyal Customer,35,Business travel,Business,3476,5,5,5,5,4,4,4,4,4,4,4,5,4,5,51,28.0,satisfied +99110,66961,Male,Loyal Customer,51,Business travel,Business,3465,1,1,3,1,3,4,5,1,1,2,1,4,1,4,0,0.0,satisfied +99111,15474,Male,Loyal Customer,68,Personal Travel,Eco,331,1,5,1,2,4,1,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +99112,58827,Female,Loyal Customer,39,Personal Travel,Eco,1182,1,4,1,3,3,1,3,3,4,5,3,2,3,3,99,101.0,neutral or dissatisfied +99113,73940,Female,Loyal Customer,48,Business travel,Business,2585,3,3,3,3,4,3,3,5,4,5,5,3,3,3,0,0.0,satisfied +99114,2923,Female,Loyal Customer,41,Business travel,Business,859,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +99115,67973,Male,Loyal Customer,41,Business travel,Business,1752,3,3,3,3,4,4,4,4,4,4,4,3,4,4,23,19.0,satisfied +99116,24673,Female,Loyal Customer,43,Business travel,Business,2088,3,3,2,3,4,2,2,4,4,4,4,2,4,2,0,0.0,satisfied +99117,61864,Female,Loyal Customer,65,Personal Travel,Eco Plus,1379,5,4,5,4,3,5,2,1,1,5,1,2,1,4,4,0.0,satisfied +99118,26422,Male,Loyal Customer,35,Business travel,Eco,787,4,3,3,3,4,4,4,4,4,4,3,2,2,4,0,0.0,satisfied +99119,23840,Female,Loyal Customer,20,Personal Travel,Eco,705,4,4,4,3,4,4,4,4,4,2,4,4,4,4,120,127.0,neutral or dissatisfied +99120,113138,Male,Loyal Customer,60,Business travel,Business,2583,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +99121,94934,Female,disloyal Customer,18,Business travel,Eco,239,5,4,5,4,1,5,1,1,1,5,1,2,5,1,3,0.0,satisfied +99122,20756,Female,Loyal Customer,65,Business travel,Eco Plus,363,2,3,1,3,1,3,3,2,2,2,2,3,2,3,30,14.0,neutral or dissatisfied +99123,116530,Male,Loyal Customer,31,Personal Travel,Eco,446,4,5,4,3,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +99124,75701,Male,Loyal Customer,54,Business travel,Business,2610,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +99125,39150,Female,Loyal Customer,32,Business travel,Eco Plus,190,5,4,5,5,5,5,5,5,3,3,3,5,5,5,0,1.0,satisfied +99126,20594,Female,Loyal Customer,27,Business travel,Eco Plus,606,5,2,2,2,5,5,5,5,3,2,4,5,2,5,0,10.0,satisfied +99127,66797,Female,Loyal Customer,27,Business travel,Business,3711,4,4,4,4,4,4,4,5,4,4,4,4,3,4,0,4.0,satisfied +99128,129825,Female,Loyal Customer,17,Personal Travel,Eco,447,3,4,3,2,2,3,2,2,4,2,5,4,5,2,50,67.0,neutral or dissatisfied +99129,14692,Female,disloyal Customer,26,Business travel,Eco,419,2,0,1,4,4,1,5,4,4,4,4,3,1,4,33,8.0,neutral or dissatisfied +99130,122256,Male,Loyal Customer,54,Personal Travel,Eco,546,1,2,1,4,2,1,2,2,1,5,4,4,4,2,0,0.0,neutral or dissatisfied +99131,98459,Male,disloyal Customer,40,Business travel,Eco,210,2,2,1,4,5,1,3,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +99132,110907,Female,Loyal Customer,18,Business travel,Business,2870,2,1,1,1,2,2,2,2,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +99133,20624,Female,Loyal Customer,34,Business travel,Business,3158,4,4,4,4,4,4,1,5,5,5,5,1,5,4,0,0.0,satisfied +99134,3701,Female,disloyal Customer,17,Business travel,Eco,544,3,0,3,4,3,3,3,3,2,3,2,1,5,3,0,0.0,neutral or dissatisfied +99135,110989,Male,Loyal Customer,38,Business travel,Business,197,5,5,4,5,5,4,5,5,5,5,4,5,5,3,48,27.0,satisfied +99136,29494,Male,Loyal Customer,60,Business travel,Business,2771,1,4,4,4,2,4,4,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +99137,56137,Female,Loyal Customer,27,Business travel,Business,1400,4,4,1,4,3,3,3,3,5,2,4,3,5,3,10,0.0,satisfied +99138,94153,Male,Loyal Customer,41,Business travel,Business,1939,2,2,5,2,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +99139,25758,Male,Loyal Customer,39,Business travel,Business,2126,3,3,3,3,2,2,4,5,5,5,5,3,5,3,1,0.0,satisfied +99140,99464,Female,Loyal Customer,17,Business travel,Business,1704,2,2,2,2,2,2,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +99141,56766,Female,Loyal Customer,42,Business travel,Business,937,3,3,4,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +99142,22898,Female,disloyal Customer,24,Business travel,Eco,170,1,2,1,3,2,1,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +99143,116411,Male,Loyal Customer,53,Personal Travel,Eco,358,3,5,3,3,5,3,3,5,5,3,4,4,4,5,5,4.0,neutral or dissatisfied +99144,117668,Male,Loyal Customer,60,Personal Travel,Eco,1449,2,4,2,2,2,2,2,2,4,5,2,5,3,2,1,3.0,neutral or dissatisfied +99145,109868,Male,Loyal Customer,43,Business travel,Business,1744,2,2,2,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +99146,33907,Female,Loyal Customer,52,Business travel,Eco Plus,1504,4,1,1,1,5,1,1,4,4,4,4,4,4,3,7,17.0,neutral or dissatisfied +99147,27752,Female,Loyal Customer,43,Business travel,Eco,1448,3,5,5,5,5,3,4,3,3,3,3,3,3,2,12,0.0,neutral or dissatisfied +99148,1422,Male,Loyal Customer,7,Personal Travel,Eco Plus,247,2,4,2,4,5,2,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +99149,43174,Female,Loyal Customer,69,Personal Travel,Eco,781,0,5,0,4,5,5,4,2,2,0,5,5,2,3,0,0.0,satisfied +99150,128769,Male,Loyal Customer,43,Personal Travel,Eco,550,4,0,4,3,1,4,1,1,3,3,5,3,4,1,0,0.0,satisfied +99151,13625,Female,Loyal Customer,53,Business travel,Business,1162,3,3,3,3,5,4,4,4,4,4,4,5,4,1,0,0.0,satisfied +99152,49865,Female,disloyal Customer,23,Business travel,Eco,89,0,0,0,3,3,0,3,3,2,2,1,5,3,3,8,4.0,satisfied +99153,113909,Male,Loyal Customer,25,Personal Travel,Eco,2295,1,4,1,3,2,1,2,2,4,2,3,1,4,2,14,8.0,neutral or dissatisfied +99154,98650,Male,Loyal Customer,40,Business travel,Business,434,3,3,3,3,5,4,4,3,3,3,3,4,3,1,26,17.0,neutral or dissatisfied +99155,40607,Male,Loyal Customer,49,Personal Travel,Eco,391,4,5,2,3,5,2,2,5,3,3,4,4,5,5,1,0.0,neutral or dissatisfied +99156,36033,Male,Loyal Customer,52,Business travel,Business,1843,5,5,5,5,1,5,2,3,3,3,3,3,3,5,0,0.0,satisfied +99157,40344,Male,disloyal Customer,26,Business travel,Eco,920,1,0,0,2,1,0,1,1,5,2,2,5,4,1,0,0.0,neutral or dissatisfied +99158,64409,Female,Loyal Customer,32,Business travel,Business,1172,4,4,4,4,5,4,5,5,4,5,5,3,5,5,5,0.0,satisfied +99159,80986,Male,Loyal Customer,49,Business travel,Business,3276,5,5,4,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +99160,21307,Female,Loyal Customer,69,Personal Travel,Eco,620,1,5,1,2,4,5,5,1,1,1,1,5,1,4,7,15.0,neutral or dissatisfied +99161,47651,Female,disloyal Customer,26,Business travel,Eco,1235,2,2,2,5,4,2,4,4,3,5,3,1,2,4,12,0.0,neutral or dissatisfied +99162,124784,Female,Loyal Customer,45,Business travel,Business,3234,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,19.0,satisfied +99163,50940,Male,Loyal Customer,35,Personal Travel,Eco,250,3,4,3,4,1,3,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +99164,127689,Male,Loyal Customer,55,Business travel,Business,2133,2,2,5,2,5,3,4,2,2,2,2,3,2,3,43,44.0,satisfied +99165,74691,Female,Loyal Customer,54,Personal Travel,Eco,1464,2,3,2,3,5,3,4,2,2,2,2,1,2,3,30,21.0,neutral or dissatisfied +99166,81697,Female,Loyal Customer,52,Personal Travel,Eco,907,1,4,1,3,4,5,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +99167,80498,Male,disloyal Customer,25,Business travel,Eco,1233,1,1,1,1,4,1,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +99168,73177,Female,Loyal Customer,29,Business travel,Business,2797,2,3,2,2,4,4,4,4,5,3,5,5,5,4,0,0.0,satisfied +99169,40609,Male,Loyal Customer,26,Personal Travel,Eco,391,3,4,4,3,1,4,1,1,2,5,2,5,4,1,0,0.0,neutral or dissatisfied +99170,110642,Female,Loyal Customer,39,Business travel,Business,1959,2,2,2,2,3,4,4,4,4,4,4,4,4,4,19,11.0,satisfied +99171,90312,Male,Loyal Customer,44,Business travel,Business,2139,4,4,4,4,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +99172,61290,Male,Loyal Customer,21,Personal Travel,Eco,846,2,1,2,2,4,2,5,4,4,1,3,3,3,4,0,0.0,neutral or dissatisfied +99173,79792,Female,Loyal Customer,51,Business travel,Business,1080,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +99174,93633,Male,Loyal Customer,14,Personal Travel,Eco,704,3,3,3,2,5,3,5,5,4,3,3,2,2,5,0,0.0,neutral or dissatisfied +99175,102785,Female,Loyal Customer,42,Business travel,Business,1698,3,3,3,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +99176,39171,Female,Loyal Customer,58,Business travel,Eco,237,3,2,2,2,2,3,4,3,3,3,3,4,3,1,0,4.0,neutral or dissatisfied +99177,100248,Female,Loyal Customer,41,Business travel,Business,3215,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +99178,34258,Male,Loyal Customer,57,Personal Travel,Business,496,4,4,4,5,3,4,4,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +99179,103600,Male,disloyal Customer,36,Business travel,Business,251,2,2,2,3,2,2,2,2,2,2,4,1,3,2,19,17.0,neutral or dissatisfied +99180,73720,Female,disloyal Customer,23,Business travel,Eco,192,3,2,3,3,1,3,5,1,3,1,3,3,4,1,66,50.0,neutral or dissatisfied +99181,91853,Male,Loyal Customer,41,Personal Travel,Eco,1619,1,5,1,1,3,1,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +99182,40227,Male,Loyal Customer,49,Business travel,Business,387,1,2,2,2,1,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +99183,88382,Male,disloyal Customer,26,Business travel,Eco,594,1,1,1,4,1,1,1,1,3,1,3,4,4,1,30,25.0,neutral or dissatisfied +99184,103603,Female,Loyal Customer,31,Business travel,Business,3845,1,1,1,1,5,5,5,5,5,3,5,4,4,5,19,14.0,satisfied +99185,49470,Male,Loyal Customer,59,Business travel,Business,3116,0,5,0,3,4,1,4,2,2,2,1,5,2,2,16,15.0,satisfied +99186,96207,Female,Loyal Customer,39,Business travel,Business,3000,2,5,5,5,4,3,4,2,2,2,2,4,2,3,36,37.0,neutral or dissatisfied +99187,52605,Female,Loyal Customer,47,Business travel,Business,2692,4,4,4,4,3,2,4,4,4,4,5,3,4,5,0,0.0,satisfied +99188,86329,Male,Loyal Customer,25,Business travel,Business,3491,4,3,3,3,4,4,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +99189,127454,Female,Loyal Customer,20,Personal Travel,Business,1814,3,2,3,4,4,3,4,4,1,2,4,1,4,4,3,0.0,neutral or dissatisfied +99190,8688,Female,Loyal Customer,38,Business travel,Business,3529,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +99191,36150,Female,disloyal Customer,23,Business travel,Eco,818,4,4,4,3,3,4,2,3,1,5,3,1,4,3,0,0.0,neutral or dissatisfied +99192,128513,Male,Loyal Customer,45,Personal Travel,Eco,370,1,4,1,4,3,1,3,3,2,1,4,1,3,3,13,12.0,neutral or dissatisfied +99193,118843,Female,disloyal Customer,29,Business travel,Eco Plus,338,2,2,2,4,1,2,1,1,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +99194,32231,Female,disloyal Customer,29,Business travel,Eco,163,2,0,2,2,5,2,5,5,1,2,3,1,3,5,0,6.0,neutral or dissatisfied +99195,63061,Male,Loyal Customer,41,Personal Travel,Eco,967,3,5,4,3,3,4,3,3,4,5,4,3,4,3,45,36.0,neutral or dissatisfied +99196,71962,Male,disloyal Customer,25,Business travel,Business,1440,5,0,5,3,4,0,4,4,3,5,4,4,5,4,0,2.0,satisfied +99197,84516,Female,Loyal Customer,51,Business travel,Business,2556,2,2,2,2,3,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +99198,41238,Female,Loyal Customer,36,Business travel,Eco,781,4,1,1,1,4,4,4,4,2,5,4,1,1,4,0,0.0,satisfied +99199,105816,Female,Loyal Customer,52,Personal Travel,Eco,787,2,4,2,4,2,4,4,2,2,2,2,5,2,5,13,0.0,neutral or dissatisfied +99200,17465,Male,disloyal Customer,22,Business travel,Business,241,4,0,4,1,4,4,5,4,4,5,4,5,4,4,15,3.0,satisfied +99201,32461,Male,Loyal Customer,53,Business travel,Business,2721,2,2,2,2,5,4,4,4,4,4,3,5,4,1,0,0.0,satisfied +99202,59690,Male,Loyal Customer,39,Personal Travel,Eco,861,3,5,3,3,5,3,5,5,3,2,5,3,5,5,30,23.0,neutral or dissatisfied +99203,40049,Male,disloyal Customer,18,Business travel,Eco,926,1,1,1,4,4,1,4,4,2,3,4,2,4,4,52,36.0,neutral or dissatisfied +99204,4074,Male,Loyal Customer,62,Personal Travel,Eco Plus,479,2,4,2,2,3,2,2,3,3,4,1,4,5,3,0,0.0,neutral or dissatisfied +99205,75918,Male,Loyal Customer,50,Business travel,Business,3823,1,1,3,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +99206,49332,Female,disloyal Customer,30,Business travel,Eco,250,1,0,1,1,3,1,3,3,1,2,2,1,4,3,0,0.0,neutral or dissatisfied +99207,99895,Male,Loyal Customer,36,Business travel,Business,338,0,0,0,3,3,3,5,3,3,3,3,1,3,2,0,3.0,satisfied +99208,36340,Male,Loyal Customer,11,Personal Travel,Eco,187,3,3,3,2,2,3,5,2,5,5,2,1,4,2,3,0.0,neutral or dissatisfied +99209,44336,Male,Loyal Customer,23,Business travel,Eco,230,2,4,4,4,2,1,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +99210,8638,Female,Loyal Customer,51,Business travel,Business,304,0,0,0,3,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +99211,13408,Female,Loyal Customer,48,Business travel,Eco,491,4,4,4,4,4,4,2,4,4,4,4,4,4,1,0,0.0,satisfied +99212,67579,Female,Loyal Customer,23,Business travel,Business,1464,5,5,5,5,4,4,4,4,5,4,4,4,5,4,0,8.0,satisfied +99213,116141,Female,Loyal Customer,27,Personal Travel,Eco,373,2,1,5,2,4,5,3,4,1,5,2,2,3,4,57,57.0,neutral or dissatisfied +99214,100628,Male,Loyal Customer,30,Business travel,Business,3066,0,0,0,3,1,5,5,1,5,3,4,5,4,1,11,9.0,satisfied +99215,67374,Male,Loyal Customer,55,Business travel,Business,3204,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,24.0,satisfied +99216,108892,Female,Loyal Customer,33,Business travel,Business,3001,5,5,5,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +99217,26868,Female,Loyal Customer,27,Business travel,Business,2329,4,4,4,4,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +99218,86944,Male,Loyal Customer,39,Business travel,Business,1997,3,1,3,3,2,4,4,4,4,4,4,3,4,4,6,8.0,satisfied +99219,77675,Female,Loyal Customer,50,Business travel,Business,1665,5,5,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +99220,111206,Male,disloyal Customer,23,Business travel,Eco,1244,3,3,3,5,1,3,1,1,3,4,4,4,4,1,6,1.0,neutral or dissatisfied +99221,29287,Female,disloyal Customer,51,Business travel,Eco,569,3,4,2,3,4,2,4,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +99222,70500,Male,Loyal Customer,28,Personal Travel,Eco,867,2,4,2,2,2,2,2,2,3,3,2,4,5,2,0,0.0,neutral or dissatisfied +99223,91150,Male,Loyal Customer,34,Personal Travel,Eco,404,4,4,4,4,1,4,1,1,1,3,4,2,3,1,9,22.0,neutral or dissatisfied +99224,109416,Male,Loyal Customer,43,Business travel,Business,3553,2,2,2,2,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +99225,61278,Female,Loyal Customer,50,Personal Travel,Eco,967,3,4,3,4,5,5,5,3,3,3,3,5,3,3,15,25.0,neutral or dissatisfied +99226,10522,Male,Loyal Customer,43,Business travel,Business,1786,2,2,2,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +99227,33831,Female,disloyal Customer,7,Business travel,Eco,1155,3,3,3,4,2,3,2,2,1,5,3,3,4,2,11,0.0,neutral or dissatisfied +99228,45726,Male,Loyal Customer,19,Personal Travel,Eco,852,5,4,5,1,5,5,5,5,3,5,5,4,5,5,0,11.0,satisfied +99229,59225,Male,Loyal Customer,25,Business travel,Business,2846,4,4,4,4,5,5,5,4,5,3,4,5,4,5,116,133.0,satisfied +99230,33266,Male,Loyal Customer,27,Personal Travel,Eco Plus,101,1,4,1,3,2,1,2,2,4,5,2,3,4,2,0,10.0,neutral or dissatisfied +99231,19529,Female,Loyal Customer,37,Business travel,Business,1575,2,2,2,2,1,3,3,4,4,4,5,1,4,4,30,23.0,satisfied +99232,63701,Female,Loyal Customer,8,Personal Travel,Eco,853,3,3,3,4,3,3,3,3,2,2,4,2,3,3,10,0.0,neutral or dissatisfied +99233,37895,Male,Loyal Customer,40,Business travel,Business,3577,3,1,1,1,3,3,3,3,3,3,3,3,2,3,480,471.0,neutral or dissatisfied +99234,60166,Female,Loyal Customer,63,Personal Travel,Eco,1005,4,5,4,3,2,4,3,5,5,4,1,3,5,1,71,40.0,neutral or dissatisfied +99235,116508,Male,Loyal Customer,55,Personal Travel,Eco,296,3,5,2,5,1,2,4,1,5,3,5,4,5,1,5,0.0,neutral or dissatisfied +99236,27356,Female,Loyal Customer,42,Business travel,Business,671,3,3,3,3,5,3,5,3,3,2,3,4,3,4,0,0.0,satisfied +99237,32366,Female,Loyal Customer,44,Business travel,Business,102,5,5,5,5,5,4,1,4,4,4,5,5,4,3,0,0.0,satisfied +99238,17298,Male,Loyal Customer,34,Business travel,Business,3173,5,5,5,5,1,3,3,4,4,4,4,5,4,1,21,19.0,satisfied +99239,38894,Female,Loyal Customer,52,Personal Travel,Business,162,2,4,2,3,3,4,4,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +99240,27845,Male,Loyal Customer,10,Personal Travel,Eco,1448,2,1,2,4,5,2,4,5,1,3,3,4,4,5,0,0.0,neutral or dissatisfied +99241,98523,Male,Loyal Customer,25,Personal Travel,Eco,668,3,4,3,1,3,3,4,3,4,3,5,3,5,3,10,50.0,neutral or dissatisfied +99242,56735,Male,Loyal Customer,23,Personal Travel,Eco,1085,4,5,4,2,2,4,2,2,4,3,4,3,5,2,46,50.0,neutral or dissatisfied +99243,117692,Female,Loyal Customer,51,Business travel,Eco,575,5,3,3,3,2,1,1,5,5,5,5,4,5,2,12,5.0,satisfied +99244,64908,Male,Loyal Customer,34,Business travel,Eco,190,2,3,2,3,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +99245,25260,Male,disloyal Customer,23,Business travel,Eco,425,5,3,5,2,2,5,2,2,5,5,5,5,2,2,42,41.0,satisfied +99246,15002,Female,Loyal Customer,38,Personal Travel,Eco,1201,2,2,2,4,5,2,2,5,3,5,3,1,3,5,0,0.0,neutral or dissatisfied +99247,11000,Male,Loyal Customer,47,Business travel,Business,216,5,5,5,5,1,3,3,4,4,4,4,3,4,4,0,0.0,satisfied +99248,75705,Female,Loyal Customer,45,Business travel,Business,1934,3,5,5,5,5,2,1,3,3,3,3,2,3,2,110,101.0,neutral or dissatisfied +99249,121264,Female,Loyal Customer,39,Personal Travel,Eco,2075,3,5,3,3,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +99250,34409,Female,Loyal Customer,51,Personal Travel,Eco,612,2,3,2,3,2,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +99251,39705,Female,Loyal Customer,29,Business travel,Eco,320,4,1,1,1,4,4,4,4,1,2,2,1,1,4,0,0.0,satisfied +99252,126678,Female,Loyal Customer,15,Personal Travel,Eco Plus,2276,1,4,1,1,4,1,4,4,4,5,1,3,2,4,19,12.0,neutral or dissatisfied +99253,7778,Male,Loyal Customer,31,Personal Travel,Eco,1080,3,5,4,5,1,4,1,1,5,5,5,3,5,1,0,0.0,neutral or dissatisfied +99254,106852,Female,Loyal Customer,58,Business travel,Business,577,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +99255,41593,Male,Loyal Customer,40,Personal Travel,Eco,1235,3,1,2,4,4,2,4,4,4,3,3,1,3,4,20,7.0,neutral or dissatisfied +99256,87880,Female,Loyal Customer,32,Personal Travel,Eco Plus,214,4,3,0,2,3,0,3,3,5,1,4,2,1,3,0,0.0,neutral or dissatisfied +99257,57794,Female,Loyal Customer,9,Personal Travel,Eco Plus,2704,4,5,4,1,4,1,1,5,3,5,4,1,5,1,27,30.0,neutral or dissatisfied +99258,38158,Male,Loyal Customer,13,Personal Travel,Eco,1197,3,4,3,3,1,3,1,1,2,2,4,1,4,1,1,0.0,neutral or dissatisfied +99259,76616,Female,Loyal Customer,30,Business travel,Business,516,4,4,3,4,2,2,2,2,4,3,4,3,4,2,0,0.0,satisfied +99260,120728,Male,Loyal Customer,43,Personal Travel,Business,1089,2,4,2,3,1,3,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +99261,68608,Male,Loyal Customer,26,Business travel,Business,1739,1,1,1,1,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +99262,78679,Male,Loyal Customer,69,Business travel,Business,674,2,2,5,2,5,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +99263,5065,Male,disloyal Customer,56,Business travel,Business,235,3,3,3,3,2,3,2,2,1,3,2,1,2,2,0,0.0,neutral or dissatisfied +99264,96347,Female,disloyal Customer,19,Business travel,Eco,1609,3,3,3,2,4,3,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +99265,49861,Female,Loyal Customer,53,Business travel,Eco,262,2,1,1,1,3,3,3,2,2,2,2,1,2,2,1,0.0,neutral or dissatisfied +99266,52062,Female,Loyal Customer,32,Business travel,Business,3708,3,3,5,3,5,5,5,5,2,2,2,1,3,5,0,12.0,satisfied +99267,9212,Male,Loyal Customer,51,Business travel,Business,100,0,5,0,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +99268,18611,Male,Loyal Customer,36,Business travel,Business,3361,2,1,1,1,4,3,3,1,1,1,2,3,1,1,0,0.0,neutral or dissatisfied +99269,23582,Female,Loyal Customer,31,Business travel,Eco Plus,792,4,1,1,1,4,4,4,4,5,1,4,4,5,4,0,23.0,satisfied +99270,72028,Female,Loyal Customer,46,Business travel,Business,3784,3,3,3,3,5,5,5,3,5,3,4,5,4,5,0,0.0,satisfied +99271,127558,Male,Loyal Customer,32,Personal Travel,Eco Plus,1009,3,4,3,3,2,3,5,2,3,3,2,1,4,2,0,0.0,neutral or dissatisfied +99272,37160,Male,Loyal Customer,65,Personal Travel,Eco,1189,3,5,3,1,3,3,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +99273,98272,Male,disloyal Customer,14,Business travel,Eco,1136,2,2,2,3,4,2,4,4,1,3,3,2,3,4,0,0.0,neutral or dissatisfied +99274,44126,Male,disloyal Customer,54,Business travel,Eco,198,3,0,3,3,4,3,4,4,4,3,2,4,4,4,0,0.0,neutral or dissatisfied +99275,15523,Female,disloyal Customer,37,Business travel,Eco Plus,164,3,3,3,4,5,3,5,5,4,2,4,4,3,5,33,28.0,neutral or dissatisfied +99276,68777,Male,Loyal Customer,40,Business travel,Eco,861,2,1,1,1,2,2,2,2,1,5,2,4,3,2,6,11.0,neutral or dissatisfied +99277,93750,Male,disloyal Customer,26,Business travel,Eco,368,2,1,2,4,4,2,4,4,2,3,4,3,4,4,19,11.0,neutral or dissatisfied +99278,9396,Female,Loyal Customer,67,Personal Travel,Eco,372,2,5,2,5,2,5,4,3,3,2,3,5,3,3,13,11.0,neutral or dissatisfied +99279,26369,Female,Loyal Customer,42,Business travel,Business,1891,3,3,3,3,1,2,1,5,5,5,5,4,5,3,0,0.0,satisfied +99280,128369,Female,Loyal Customer,48,Business travel,Business,3463,1,1,1,1,4,4,4,5,5,5,5,3,5,4,50,33.0,satisfied +99281,80968,Male,Loyal Customer,42,Business travel,Business,297,0,0,0,4,5,4,4,2,2,2,2,4,2,5,19,21.0,satisfied +99282,125532,Female,Loyal Customer,43,Business travel,Business,1557,3,3,3,3,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +99283,38129,Female,Loyal Customer,55,Business travel,Business,2919,1,1,1,1,1,1,1,3,3,4,3,1,1,1,131,105.0,neutral or dissatisfied +99284,99423,Male,Loyal Customer,49,Personal Travel,Eco,337,2,4,5,3,3,5,3,3,5,5,5,5,4,3,44,34.0,neutral or dissatisfied +99285,7196,Male,Loyal Customer,32,Business travel,Business,3800,2,2,2,2,1,1,2,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +99286,31189,Male,disloyal Customer,33,Business travel,Eco,628,3,5,3,3,2,3,2,2,5,4,1,1,4,2,71,72.0,neutral or dissatisfied +99287,119856,Male,Loyal Customer,33,Business travel,Business,1530,4,4,4,4,2,2,2,2,4,1,1,5,4,2,0,0.0,satisfied +99288,97730,Male,Loyal Customer,60,Business travel,Business,587,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,2.0,satisfied +99289,16352,Male,Loyal Customer,7,Personal Travel,Eco,160,3,4,3,1,2,3,2,2,3,3,5,5,4,2,25,11.0,neutral or dissatisfied +99290,84574,Male,Loyal Customer,64,Personal Travel,Eco Plus,2486,3,4,3,3,1,3,1,1,2,3,4,3,3,1,0,5.0,neutral or dissatisfied +99291,84522,Female,Loyal Customer,47,Business travel,Eco,2556,2,4,4,4,4,2,2,2,2,2,2,4,2,4,0,2.0,neutral or dissatisfied +99292,71048,Male,Loyal Customer,22,Business travel,Business,1599,3,1,1,1,3,3,3,3,4,4,3,2,3,3,6,0.0,neutral or dissatisfied +99293,111747,Male,Loyal Customer,9,Personal Travel,Eco,1224,4,0,4,2,4,4,4,3,5,4,4,4,5,4,134,133.0,satisfied +99294,77743,Male,Loyal Customer,52,Business travel,Business,3280,3,3,3,3,3,4,3,5,5,5,5,3,5,5,0,0.0,satisfied +99295,72288,Male,Loyal Customer,16,Personal Travel,Eco,919,3,1,3,4,4,3,4,4,2,1,3,3,3,4,0,9.0,neutral or dissatisfied +99296,89355,Female,Loyal Customer,40,Business travel,Business,1899,3,5,5,5,2,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +99297,58117,Male,Loyal Customer,59,Personal Travel,Eco,589,2,4,2,2,3,2,3,3,4,4,5,3,4,3,19,46.0,neutral or dissatisfied +99298,28416,Male,disloyal Customer,19,Business travel,Eco,1399,3,3,3,4,3,3,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +99299,1735,Male,Loyal Customer,49,Personal Travel,Eco,327,2,0,2,4,5,2,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +99300,35659,Male,Loyal Customer,45,Business travel,Business,2475,4,4,4,4,2,2,2,5,4,4,3,2,1,2,35,176.0,satisfied +99301,43070,Male,Loyal Customer,26,Personal Travel,Eco,236,1,5,1,1,2,1,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +99302,9972,Female,Loyal Customer,30,Personal Travel,Eco,357,1,2,2,3,4,2,4,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +99303,103588,Female,Loyal Customer,31,Business travel,Business,2489,3,3,3,3,5,5,5,5,4,4,4,4,5,5,0,0.0,satisfied +99304,84760,Female,Loyal Customer,55,Business travel,Business,3809,1,1,1,1,2,4,5,5,5,5,5,3,5,5,1,0.0,satisfied +99305,65616,Female,Loyal Customer,17,Personal Travel,Eco,237,3,5,3,4,4,3,4,4,5,4,5,5,5,4,63,61.0,neutral or dissatisfied +99306,97783,Female,Loyal Customer,54,Business travel,Business,3862,3,3,3,3,3,4,5,4,4,4,4,3,4,5,23,18.0,satisfied +99307,53137,Female,Loyal Customer,45,Business travel,Eco,413,4,3,3,3,2,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +99308,124504,Male,Loyal Customer,42,Business travel,Eco,530,5,4,4,4,5,5,5,5,3,3,2,4,3,5,0,0.0,satisfied +99309,32147,Male,Loyal Customer,33,Business travel,Business,102,0,5,0,4,1,1,1,1,1,4,4,4,2,1,12,14.0,satisfied +99310,13749,Male,Loyal Customer,62,Personal Travel,Eco,401,2,4,3,3,5,3,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +99311,12278,Female,Loyal Customer,54,Business travel,Business,1994,3,3,3,3,5,5,5,5,5,5,3,4,5,4,0,0.0,satisfied +99312,128645,Female,Loyal Customer,43,Business travel,Business,2536,2,2,2,2,5,5,4,5,5,5,5,4,5,5,18,5.0,satisfied +99313,93290,Female,Loyal Customer,15,Personal Travel,Eco,564,3,5,3,3,1,3,1,1,3,4,4,4,4,1,0,1.0,neutral or dissatisfied +99314,7470,Male,disloyal Customer,22,Business travel,Eco,510,1,0,1,3,5,1,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +99315,51983,Female,Loyal Customer,46,Personal Travel,Eco,347,4,1,4,3,2,3,4,5,5,4,1,4,5,1,0,3.0,neutral or dissatisfied +99316,93147,Female,Loyal Customer,70,Business travel,Business,1075,2,2,2,2,4,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +99317,7703,Female,Loyal Customer,11,Personal Travel,Eco,604,2,4,2,5,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +99318,96244,Male,Loyal Customer,19,Personal Travel,Eco,546,1,5,3,4,5,3,5,5,4,3,1,4,4,5,13,0.0,neutral or dissatisfied +99319,90016,Male,Loyal Customer,41,Business travel,Business,2135,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +99320,83939,Female,Loyal Customer,56,Business travel,Business,3175,2,2,2,2,4,5,4,4,4,4,4,3,4,5,0,7.0,satisfied +99321,54283,Male,Loyal Customer,31,Personal Travel,Eco,1034,1,5,1,4,2,1,4,2,3,4,4,4,4,2,12,0.0,neutral or dissatisfied +99322,122139,Female,Loyal Customer,8,Personal Travel,Business,541,1,4,1,4,4,1,2,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +99323,107068,Female,Loyal Customer,35,Personal Travel,Eco,395,3,4,3,3,4,3,5,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +99324,102118,Male,Loyal Customer,39,Business travel,Business,2257,5,5,5,5,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +99325,54223,Male,Loyal Customer,48,Business travel,Eco,1222,3,2,2,2,3,3,3,3,2,2,3,2,5,3,0,4.0,satisfied +99326,34787,Male,Loyal Customer,16,Personal Travel,Eco,264,2,4,2,3,2,2,2,3,4,4,5,2,4,2,115,134.0,neutral or dissatisfied +99327,124457,Male,Loyal Customer,60,Business travel,Business,2725,5,5,5,5,5,5,5,4,4,4,4,5,4,4,17,11.0,satisfied +99328,68562,Female,Loyal Customer,45,Business travel,Business,1616,4,4,4,4,2,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +99329,31993,Female,Loyal Customer,55,Personal Travel,Business,101,1,3,1,3,2,2,1,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +99330,79593,Male,Loyal Customer,46,Business travel,Business,762,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,15.0,satisfied +99331,9474,Male,Loyal Customer,47,Business travel,Eco Plus,310,3,2,4,2,4,3,4,4,4,4,3,1,3,4,16,4.0,neutral or dissatisfied +99332,72735,Male,Loyal Customer,8,Personal Travel,Eco Plus,985,1,4,2,4,1,2,1,1,4,2,4,4,5,1,1,0.0,neutral or dissatisfied +99333,31250,Female,Loyal Customer,39,Business travel,Eco,524,3,2,2,2,3,4,3,3,3,4,2,4,5,3,16,16.0,satisfied +99334,113238,Male,Loyal Customer,61,Personal Travel,Business,397,4,4,3,4,2,5,4,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +99335,63245,Female,Loyal Customer,47,Business travel,Eco,337,2,5,5,5,3,3,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +99336,9094,Female,Loyal Customer,37,Business travel,Business,2480,2,2,2,2,3,5,5,4,4,4,5,4,4,4,0,0.0,satisfied +99337,86048,Female,Loyal Customer,58,Personal Travel,Eco,554,1,5,1,3,5,5,5,2,2,1,2,5,2,5,0,1.0,neutral or dissatisfied +99338,79141,Female,disloyal Customer,22,Business travel,Eco Plus,226,3,0,4,3,1,4,1,1,1,3,4,3,5,1,0,0.0,neutral or dissatisfied +99339,50962,Female,Loyal Customer,40,Personal Travel,Eco,363,3,1,3,3,2,3,2,2,1,1,3,2,4,2,6,1.0,neutral or dissatisfied +99340,127712,Male,Loyal Customer,56,Personal Travel,Business,601,1,4,1,3,2,1,1,4,4,1,4,3,4,1,13,12.0,neutral or dissatisfied +99341,28067,Female,Loyal Customer,65,Business travel,Business,2631,3,1,1,1,3,3,3,4,5,1,2,3,1,3,0,0.0,neutral or dissatisfied +99342,55746,Male,Loyal Customer,55,Business travel,Business,1737,4,4,2,4,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +99343,76803,Male,Loyal Customer,60,Personal Travel,Eco,689,3,5,3,2,5,3,5,5,5,4,5,3,5,5,0,1.0,neutral or dissatisfied +99344,81987,Male,Loyal Customer,58,Business travel,Eco,1532,3,1,1,1,3,3,3,3,3,4,2,1,3,3,52,41.0,neutral or dissatisfied +99345,108152,Male,Loyal Customer,28,Personal Travel,Eco,1166,1,3,1,4,2,1,2,2,4,2,2,1,4,2,0,0.0,neutral or dissatisfied +99346,63960,Male,Loyal Customer,35,Personal Travel,Eco,1172,1,5,1,4,3,1,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +99347,102039,Male,Loyal Customer,40,Business travel,Business,397,2,3,3,3,2,2,2,2,2,2,2,1,2,3,3,6.0,neutral or dissatisfied +99348,126700,Female,Loyal Customer,52,Business travel,Business,2402,1,1,1,1,2,3,4,4,4,4,4,5,4,5,0,8.0,satisfied +99349,43391,Female,Loyal Customer,43,Personal Travel,Eco,347,4,4,3,1,4,4,4,3,3,3,1,4,3,4,1,0.0,neutral or dissatisfied +99350,67525,Female,Loyal Customer,59,Business travel,Business,1464,2,1,5,1,1,3,4,2,2,2,2,1,2,2,2,7.0,neutral or dissatisfied +99351,37600,Male,Loyal Customer,14,Personal Travel,Eco,944,5,5,5,3,4,5,4,4,1,5,2,5,1,4,0,0.0,satisfied +99352,67027,Female,Loyal Customer,46,Business travel,Business,2421,1,1,1,1,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +99353,18184,Male,Loyal Customer,36,Business travel,Business,179,2,2,2,2,4,3,4,4,4,4,5,3,4,1,0,4.0,satisfied +99354,95308,Female,Loyal Customer,40,Personal Travel,Eco,239,1,3,1,2,3,1,4,3,2,3,1,2,2,3,30,15.0,neutral or dissatisfied +99355,85488,Female,Loyal Customer,44,Personal Travel,Eco,332,4,5,4,3,4,5,4,3,3,4,3,4,3,4,16,3.0,neutral or dissatisfied +99356,47729,Male,Loyal Customer,42,Business travel,Business,2687,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +99357,96874,Female,disloyal Customer,18,Personal Travel,Eco,1041,1,2,1,3,3,1,3,3,2,1,4,2,4,3,18,4.0,neutral or dissatisfied +99358,53114,Male,disloyal Customer,26,Business travel,Eco,1101,4,4,4,3,4,4,4,4,4,1,1,2,2,4,2,0.0,neutral or dissatisfied +99359,8555,Male,Loyal Customer,56,Business travel,Business,109,1,1,1,1,5,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +99360,40426,Female,Loyal Customer,52,Business travel,Business,3488,2,4,2,2,1,5,2,5,5,5,5,3,5,4,0,0.0,satisfied +99361,6628,Female,Loyal Customer,55,Personal Travel,Eco,719,1,5,1,1,2,5,4,2,2,1,2,4,2,5,36,70.0,neutral or dissatisfied +99362,76415,Male,Loyal Customer,53,Business travel,Business,3962,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +99363,35647,Female,Loyal Customer,41,Business travel,Eco,2475,4,4,4,4,4,5,5,1,4,3,3,5,3,5,0,0.0,satisfied +99364,118973,Female,Loyal Customer,27,Personal Travel,Eco,570,2,5,2,2,1,2,2,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +99365,61498,Female,disloyal Customer,34,Business travel,Business,2419,4,4,4,3,5,4,5,5,5,5,4,3,5,5,31,1.0,neutral or dissatisfied +99366,75593,Male,Loyal Customer,70,Business travel,Business,3550,4,4,4,4,2,2,5,5,5,5,5,5,5,1,8,4.0,satisfied +99367,90430,Female,Loyal Customer,55,Business travel,Business,444,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +99368,28881,Male,Loyal Customer,31,Business travel,Business,1050,3,3,5,3,4,4,4,4,2,3,5,3,5,4,0,0.0,satisfied +99369,65321,Male,Loyal Customer,46,Business travel,Business,1526,1,1,1,1,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +99370,106372,Female,Loyal Customer,22,Business travel,Business,2730,3,4,4,4,3,3,3,3,2,4,1,1,2,3,83,81.0,neutral or dissatisfied +99371,97767,Male,Loyal Customer,42,Business travel,Business,471,5,3,5,5,2,4,4,5,5,5,5,5,5,4,1,0.0,satisfied +99372,34172,Female,disloyal Customer,44,Business travel,Eco,1237,3,3,3,3,4,3,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +99373,117118,Male,disloyal Customer,22,Business travel,Eco,370,1,1,1,3,2,1,2,2,1,4,3,1,4,2,5,0.0,neutral or dissatisfied +99374,66017,Male,Loyal Customer,57,Business travel,Business,2937,1,1,1,1,5,5,5,4,4,4,4,3,4,5,23,18.0,satisfied +99375,70092,Female,Loyal Customer,52,Business travel,Business,2919,5,5,5,5,3,4,5,2,2,2,2,5,2,5,22,26.0,satisfied +99376,26545,Female,Loyal Customer,34,Personal Travel,Eco,990,2,5,2,5,5,2,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +99377,118566,Female,Loyal Customer,47,Business travel,Business,370,2,2,2,2,4,4,4,4,4,4,4,5,4,4,19,12.0,satisfied +99378,29563,Male,Loyal Customer,56,Business travel,Business,1448,4,4,4,4,1,3,5,5,5,5,5,5,5,4,0,1.0,satisfied +99379,74275,Male,Loyal Customer,41,Business travel,Business,2288,5,5,5,5,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +99380,38264,Female,Loyal Customer,9,Business travel,Business,2921,4,2,2,2,4,4,4,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +99381,29638,Female,disloyal Customer,44,Business travel,Eco,1048,2,2,2,4,2,2,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +99382,101928,Female,Loyal Customer,44,Business travel,Business,3145,1,1,1,1,3,4,4,5,5,5,5,4,5,5,41,21.0,satisfied +99383,108273,Male,Loyal Customer,41,Personal Travel,Eco,895,3,4,3,3,2,3,2,2,1,1,3,1,4,2,33,32.0,neutral or dissatisfied +99384,106960,Male,Loyal Customer,60,Business travel,Business,2877,5,5,5,5,4,4,5,4,4,4,4,5,4,3,12,31.0,satisfied +99385,35459,Female,Loyal Customer,65,Personal Travel,Eco,1080,3,3,2,2,4,4,1,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +99386,111703,Female,disloyal Customer,62,Business travel,Eco,495,3,2,3,3,5,3,5,5,4,1,3,2,4,5,9,0.0,neutral or dissatisfied +99387,31904,Female,Loyal Customer,57,Business travel,Business,101,1,1,1,1,3,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +99388,90058,Female,disloyal Customer,19,Business travel,Eco,983,3,3,3,5,2,3,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +99389,100463,Female,disloyal Customer,21,Business travel,Eco,580,4,0,4,3,3,4,3,3,4,5,5,3,4,3,0,0.0,satisfied +99390,82549,Male,disloyal Customer,22,Business travel,Eco,440,2,4,2,5,3,2,3,3,3,4,4,3,4,3,1,0.0,neutral or dissatisfied +99391,86681,Male,disloyal Customer,15,Business travel,Business,1259,4,4,4,2,5,4,5,5,4,3,4,5,4,5,28,6.0,satisfied +99392,74978,Male,Loyal Customer,22,Personal Travel,Eco,2475,3,3,4,1,3,4,2,3,3,3,5,3,3,3,0,0.0,neutral or dissatisfied +99393,31643,Male,disloyal Customer,30,Business travel,Eco,846,3,3,3,4,2,3,2,2,3,3,1,1,2,2,0,0.0,neutral or dissatisfied +99394,54206,Female,Loyal Customer,34,Business travel,Eco Plus,1400,0,0,0,3,2,0,2,2,5,1,1,1,4,2,0,0.0,satisfied +99395,20954,Male,Loyal Customer,53,Business travel,Eco,689,2,4,4,4,2,2,2,2,3,3,3,3,3,2,0,9.0,neutral or dissatisfied +99396,81954,Female,Loyal Customer,35,Business travel,Business,1589,1,1,4,1,5,4,5,5,5,4,5,5,5,4,23,0.0,satisfied +99397,121727,Male,Loyal Customer,51,Business travel,Business,1475,5,5,5,5,5,4,4,5,5,4,5,4,5,5,0,4.0,satisfied +99398,15484,Female,Loyal Customer,34,Personal Travel,Eco,164,2,4,0,2,2,0,2,2,3,5,4,5,4,2,29,38.0,neutral or dissatisfied +99399,16199,Female,Loyal Customer,63,Personal Travel,Eco,212,2,1,2,3,4,4,3,3,3,2,3,1,3,1,23,18.0,neutral or dissatisfied +99400,18791,Female,Loyal Customer,36,Business travel,Eco,551,4,5,3,5,4,4,4,4,3,1,5,3,3,4,0,0.0,satisfied +99401,65043,Male,Loyal Customer,7,Personal Travel,Eco,190,4,5,4,3,5,4,5,5,3,3,4,4,5,5,58,50.0,neutral or dissatisfied +99402,20391,Male,Loyal Customer,31,Business travel,Business,1792,1,1,1,1,5,5,5,5,4,4,3,5,5,5,0,0.0,satisfied +99403,19044,Male,Loyal Customer,70,Business travel,Business,2893,3,3,3,3,1,2,3,4,4,4,4,5,4,1,0,0.0,satisfied +99404,120915,Female,Loyal Customer,30,Business travel,Business,3940,2,2,2,2,4,4,4,4,5,4,5,4,5,4,46,35.0,satisfied +99405,85525,Male,disloyal Customer,64,Business travel,Business,259,2,2,2,3,4,2,4,4,4,1,4,4,4,4,0,4.0,neutral or dissatisfied +99406,107233,Male,disloyal Customer,38,Business travel,Eco,691,2,2,2,3,4,2,4,4,1,1,4,4,3,4,26,10.0,neutral or dissatisfied +99407,11910,Female,Loyal Customer,48,Business travel,Business,344,0,0,0,3,5,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +99408,105114,Male,Loyal Customer,35,Business travel,Business,277,4,3,3,3,3,2,2,4,4,4,4,3,4,3,58,44.0,neutral or dissatisfied +99409,46843,Male,Loyal Customer,33,Business travel,Business,1721,5,5,5,5,4,4,4,4,5,3,4,2,5,4,27,14.0,satisfied +99410,101474,Female,Loyal Customer,54,Business travel,Business,345,3,1,1,1,4,3,3,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +99411,64296,Female,Loyal Customer,49,Business travel,Business,1669,3,3,2,3,4,4,4,5,5,5,5,4,5,4,46,36.0,satisfied +99412,55013,Female,Loyal Customer,43,Business travel,Business,1635,1,1,1,1,2,3,4,3,3,3,3,4,3,3,0,0.0,satisfied +99413,3710,Female,Loyal Customer,33,Personal Travel,Eco,427,3,4,3,3,2,3,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +99414,128198,Male,Loyal Customer,64,Personal Travel,Business,602,4,4,4,2,4,4,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +99415,59498,Female,Loyal Customer,26,Personal Travel,Eco,811,2,2,2,3,5,2,4,5,1,1,3,4,4,5,0,0.0,neutral or dissatisfied +99416,10160,Male,Loyal Customer,31,Personal Travel,Eco,1195,2,4,2,1,5,2,1,5,4,2,3,4,4,5,0,7.0,neutral or dissatisfied +99417,35235,Female,disloyal Customer,48,Business travel,Eco,1069,3,3,3,1,5,3,5,5,1,2,3,3,2,5,23,38.0,neutral or dissatisfied +99418,96480,Male,Loyal Customer,44,Business travel,Business,3457,2,4,4,4,3,2,3,2,2,2,2,4,2,3,53,59.0,neutral or dissatisfied +99419,13664,Female,Loyal Customer,42,Business travel,Business,462,3,3,4,3,4,1,1,4,4,4,4,3,4,4,26,19.0,satisfied +99420,53275,Female,disloyal Customer,23,Business travel,Eco,921,1,1,1,4,3,1,3,3,5,3,1,2,5,3,0,0.0,neutral or dissatisfied +99421,43566,Female,Loyal Customer,58,Business travel,Eco Plus,770,1,3,3,3,5,3,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +99422,84811,Female,disloyal Customer,27,Business travel,Business,516,4,4,4,1,3,4,3,3,3,3,4,4,4,3,96,78.0,satisfied +99423,86348,Female,Loyal Customer,35,Business travel,Business,762,3,3,3,3,5,5,5,5,5,5,5,4,5,3,12,13.0,satisfied +99424,52205,Male,disloyal Customer,37,Business travel,Eco,370,1,4,0,3,1,0,3,1,1,4,2,1,2,1,0,0.0,neutral or dissatisfied +99425,61237,Male,disloyal Customer,36,Business travel,Eco,567,2,0,1,3,3,1,3,3,1,4,4,1,3,3,0,0.0,neutral or dissatisfied +99426,57857,Male,Loyal Customer,49,Personal Travel,Eco,2457,4,2,4,4,4,5,5,2,1,2,3,5,3,5,0,0.0,neutral or dissatisfied +99427,37041,Male,Loyal Customer,50,Business travel,Business,994,3,5,5,5,2,3,3,3,3,3,3,4,3,4,112,103.0,neutral or dissatisfied +99428,94039,Male,disloyal Customer,22,Business travel,Eco,323,5,4,5,3,1,5,4,1,5,3,4,4,5,1,0,0.0,satisfied +99429,103714,Female,Loyal Customer,48,Personal Travel,Eco,405,2,4,2,1,2,4,4,1,1,2,2,5,1,3,8,1.0,neutral or dissatisfied +99430,51488,Male,Loyal Customer,40,Business travel,Business,451,2,2,2,2,3,4,4,4,4,4,4,4,4,5,0,2.0,satisfied +99431,57910,Male,Loyal Customer,16,Personal Travel,Eco,305,1,4,1,3,1,1,1,1,1,1,2,2,5,1,2,0.0,neutral or dissatisfied +99432,128436,Male,Loyal Customer,49,Business travel,Eco,338,2,3,3,3,2,2,2,2,4,2,3,4,3,2,15,7.0,neutral or dissatisfied +99433,97321,Female,disloyal Customer,24,Business travel,Eco,347,1,1,0,3,5,0,5,5,2,2,3,2,4,5,34,34.0,neutral or dissatisfied +99434,111070,Male,Loyal Customer,8,Personal Travel,Eco,268,3,3,3,4,4,3,4,4,1,4,4,4,4,4,23,20.0,neutral or dissatisfied +99435,111645,Male,Loyal Customer,18,Personal Travel,Eco,1290,1,5,1,1,2,1,2,2,5,4,4,5,4,2,26,14.0,neutral or dissatisfied +99436,105552,Female,Loyal Customer,9,Personal Travel,Eco,611,2,3,2,3,3,2,3,3,4,2,4,5,5,3,21,31.0,neutral or dissatisfied +99437,28854,Female,disloyal Customer,38,Business travel,Eco,987,3,3,3,3,5,3,3,5,1,2,5,2,1,5,0,0.0,satisfied +99438,18467,Male,Loyal Customer,44,Business travel,Business,2597,3,3,3,3,3,5,5,5,5,5,3,5,5,2,49,50.0,satisfied +99439,103615,Male,Loyal Customer,60,Business travel,Business,3262,1,1,1,1,5,4,5,5,5,5,5,3,5,4,8,0.0,satisfied +99440,13345,Male,disloyal Customer,24,Business travel,Eco,748,2,2,2,5,1,2,1,1,1,2,3,5,2,1,87,68.0,neutral or dissatisfied +99441,82441,Male,Loyal Customer,45,Business travel,Business,502,3,5,5,5,3,3,2,3,3,3,3,1,3,3,0,44.0,neutral or dissatisfied +99442,16286,Male,Loyal Customer,50,Personal Travel,Eco,748,3,4,3,3,5,3,4,5,5,5,4,4,4,5,1,7.0,neutral or dissatisfied +99443,2657,Female,Loyal Customer,42,Business travel,Business,597,2,1,2,2,3,4,4,3,3,4,3,3,3,3,0,0.0,satisfied +99444,72057,Male,Loyal Customer,50,Business travel,Business,2486,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +99445,55851,Female,Loyal Customer,40,Personal Travel,Eco,1416,4,4,4,3,1,4,1,1,2,4,4,1,3,1,129,129.0,neutral or dissatisfied +99446,87572,Male,Loyal Customer,38,Business travel,Business,2057,2,1,1,1,4,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +99447,44541,Male,Loyal Customer,39,Personal Travel,Eco,157,3,4,0,2,3,0,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +99448,53727,Male,Loyal Customer,21,Personal Travel,Eco,1190,4,4,4,4,1,4,1,1,5,3,3,3,4,1,8,0.0,satisfied +99449,105625,Male,Loyal Customer,56,Business travel,Business,1555,2,2,2,2,4,5,5,5,5,5,5,5,5,5,4,0.0,satisfied +99450,35167,Female,disloyal Customer,13,Business travel,Eco,1144,3,3,3,3,4,3,4,4,2,1,4,4,3,4,0,12.0,neutral or dissatisfied +99451,96940,Male,Loyal Customer,68,Personal Travel,Business,794,4,4,4,1,3,4,5,2,2,4,2,4,2,3,5,21.0,neutral or dissatisfied +99452,117566,Male,Loyal Customer,42,Business travel,Business,2263,2,2,2,2,5,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +99453,68865,Female,Loyal Customer,45,Business travel,Business,3879,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +99454,93196,Male,Loyal Customer,45,Business travel,Business,896,1,1,1,1,5,5,5,4,4,4,4,3,4,4,17,9.0,satisfied +99455,106885,Female,Loyal Customer,49,Business travel,Business,2080,3,1,1,1,2,4,4,3,3,3,3,1,3,1,14,12.0,neutral or dissatisfied +99456,121596,Male,Loyal Customer,63,Personal Travel,Eco,912,3,1,3,3,5,3,5,5,4,4,2,2,2,5,40,28.0,neutral or dissatisfied +99457,54473,Male,Loyal Customer,39,Business travel,Eco,925,4,4,4,4,4,4,4,4,2,4,5,3,4,4,62,46.0,satisfied +99458,94520,Male,Loyal Customer,37,Business travel,Business,3440,3,3,3,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +99459,20494,Male,Loyal Customer,71,Business travel,Business,3297,0,3,0,4,1,2,3,3,3,3,3,1,3,1,1,0.0,satisfied +99460,79219,Female,Loyal Customer,55,Personal Travel,Eco,1990,2,3,3,4,4,4,3,5,5,3,5,4,5,1,1,0.0,neutral or dissatisfied +99461,56968,Male,Loyal Customer,28,Business travel,Business,2454,1,1,1,1,5,5,5,5,3,2,2,1,5,5,0,0.0,satisfied +99462,33317,Female,Loyal Customer,46,Personal Travel,Business,2556,2,5,2,4,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +99463,7787,Female,Loyal Customer,40,Business travel,Business,710,2,2,4,2,4,4,4,4,4,4,4,3,4,3,1,19.0,satisfied +99464,72313,Female,disloyal Customer,20,Business travel,Eco Plus,521,4,5,4,1,4,4,4,4,5,2,1,5,3,4,0,0.0,satisfied +99465,106099,Male,Loyal Customer,56,Business travel,Business,3835,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +99466,59023,Male,Loyal Customer,13,Business travel,Business,1846,3,1,1,1,3,3,3,3,2,3,3,4,3,3,38,16.0,neutral or dissatisfied +99467,116835,Female,Loyal Customer,50,Business travel,Business,651,3,4,4,4,3,1,2,3,3,3,3,3,3,4,0,3.0,neutral or dissatisfied +99468,64307,Male,Loyal Customer,43,Business travel,Business,3410,3,3,3,3,5,4,5,4,4,4,4,4,4,3,20,5.0,satisfied +99469,27242,Female,Loyal Customer,59,Personal Travel,Eco,1024,1,1,1,3,1,3,2,5,5,1,5,1,5,1,0,0.0,neutral or dissatisfied +99470,119087,Female,Loyal Customer,56,Business travel,Business,1020,5,5,5,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +99471,7120,Female,Loyal Customer,24,Business travel,Eco Plus,273,1,2,2,2,1,1,3,1,2,5,4,4,4,1,56,42.0,neutral or dissatisfied +99472,5958,Male,Loyal Customer,50,Business travel,Business,1250,3,4,2,4,4,3,3,3,3,3,3,4,3,4,4,2.0,neutral or dissatisfied +99473,125450,Male,disloyal Customer,21,Business travel,Eco,874,5,5,5,4,1,5,1,1,5,2,5,5,4,1,0,0.0,satisfied +99474,12421,Male,Loyal Customer,51,Personal Travel,Eco,127,1,1,1,3,5,1,5,5,3,2,2,1,2,5,0,0.0,neutral or dissatisfied +99475,92500,Male,Loyal Customer,74,Business travel,Business,2469,1,5,5,5,1,1,1,3,2,3,3,1,1,1,368,350.0,neutral or dissatisfied +99476,70076,Male,disloyal Customer,27,Business travel,Business,550,5,5,5,3,2,5,2,2,4,4,4,4,5,2,0,0.0,satisfied +99477,81781,Male,Loyal Customer,46,Business travel,Business,1416,3,3,3,3,5,5,4,5,5,5,5,5,5,5,14,0.0,satisfied +99478,78130,Female,disloyal Customer,24,Business travel,Business,259,5,0,5,4,4,5,4,4,3,2,5,3,5,4,32,30.0,satisfied +99479,2872,Female,Loyal Customer,68,Personal Travel,Eco,491,2,3,3,2,4,1,2,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +99480,95038,Male,Loyal Customer,14,Personal Travel,Eco,277,4,5,4,2,3,4,4,3,1,2,3,4,3,3,0,0.0,satisfied +99481,57027,Female,Loyal Customer,46,Business travel,Business,2454,3,3,3,3,5,3,5,4,4,4,4,3,4,4,2,0.0,satisfied +99482,114472,Male,Loyal Customer,40,Business travel,Business,3973,3,3,3,3,2,4,4,3,3,3,3,5,3,3,10,2.0,satisfied +99483,90826,Female,disloyal Customer,39,Business travel,Business,250,2,2,2,4,5,2,3,5,5,2,5,4,4,5,0,0.0,satisfied +99484,70769,Female,Loyal Customer,58,Business travel,Business,2354,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +99485,59640,Male,Loyal Customer,42,Business travel,Eco,787,2,2,2,2,2,2,2,2,1,4,2,1,3,2,74,60.0,neutral or dissatisfied +99486,36184,Female,Loyal Customer,45,Business travel,Business,280,4,1,1,1,2,4,3,4,4,4,4,4,4,1,111,131.0,neutral or dissatisfied +99487,15740,Female,Loyal Customer,59,Personal Travel,Eco,419,3,3,3,3,1,2,3,5,5,3,5,2,5,3,78,66.0,neutral or dissatisfied +99488,31701,Male,Loyal Customer,62,Personal Travel,Eco,853,2,5,2,4,3,2,3,3,3,5,5,3,4,3,17,4.0,neutral or dissatisfied +99489,110761,Male,Loyal Customer,44,Business travel,Business,2457,2,2,2,2,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +99490,39867,Male,disloyal Customer,16,Business travel,Business,272,4,5,4,1,2,4,2,2,2,1,4,5,4,2,0,0.0,satisfied +99491,19895,Male,Loyal Customer,28,Business travel,Eco,296,4,5,1,5,4,4,4,4,2,3,3,4,1,4,0,0.0,satisfied +99492,75507,Male,Loyal Customer,61,Personal Travel,Eco Plus,2342,1,4,1,4,2,1,2,2,4,2,2,5,5,2,3,0.0,neutral or dissatisfied +99493,6273,Male,Loyal Customer,62,Business travel,Business,2994,2,3,3,3,1,2,2,2,2,2,2,2,2,4,31,58.0,neutral or dissatisfied +99494,120476,Male,Loyal Customer,15,Personal Travel,Eco,449,3,3,3,4,4,3,4,4,5,4,5,2,5,4,21,6.0,neutral or dissatisfied +99495,113521,Male,Loyal Customer,42,Business travel,Eco,236,3,5,3,5,3,3,3,3,1,2,4,1,4,3,29,19.0,neutral or dissatisfied +99496,77538,Male,disloyal Customer,16,Business travel,Eco,986,2,2,2,3,1,2,1,1,3,5,4,3,5,1,37,44.0,neutral or dissatisfied +99497,90872,Male,Loyal Customer,25,Business travel,Business,594,1,0,0,4,1,0,1,1,3,4,3,1,4,1,62,80.0,neutral or dissatisfied +99498,116669,Male,Loyal Customer,22,Business travel,Business,3744,2,2,5,2,4,4,4,4,3,4,5,3,4,4,0,0.0,satisfied +99499,55174,Male,Loyal Customer,49,Personal Travel,Eco,1346,2,4,2,4,2,2,2,2,3,5,4,5,5,2,5,0.0,neutral or dissatisfied +99500,24186,Male,Loyal Customer,31,Business travel,Business,3415,5,5,5,5,4,4,3,4,3,5,5,2,1,4,58,49.0,satisfied +99501,114193,Female,Loyal Customer,41,Business travel,Business,1887,5,5,5,5,2,4,5,4,4,4,4,4,4,4,119,101.0,satisfied +99502,25259,Female,Loyal Customer,31,Business travel,Business,425,2,3,3,3,2,2,2,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +99503,103832,Male,Loyal Customer,69,Business travel,Business,1695,5,5,5,5,3,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +99504,109530,Male,disloyal Customer,25,Business travel,Eco,566,3,2,3,3,3,3,3,3,1,1,4,2,3,3,5,2.0,neutral or dissatisfied +99505,121881,Female,Loyal Customer,25,Personal Travel,Eco,449,2,5,2,2,4,2,4,4,4,2,5,5,5,4,0,2.0,neutral or dissatisfied +99506,8569,Male,Loyal Customer,39,Business travel,Business,2455,0,5,0,4,5,5,4,1,1,1,1,4,1,3,5,6.0,satisfied +99507,20035,Female,Loyal Customer,37,Business travel,Business,2203,4,2,5,2,2,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +99508,129746,Female,Loyal Customer,55,Business travel,Business,337,0,0,0,1,5,1,1,5,5,5,5,2,5,4,15,41.0,satisfied +99509,15317,Male,Loyal Customer,32,Business travel,Business,3307,2,2,2,2,2,2,2,2,1,4,3,2,3,2,0,2.0,neutral or dissatisfied +99510,20286,Female,Loyal Customer,30,Personal Travel,Eco,228,4,1,4,4,5,4,5,5,3,2,3,1,4,5,0,0.0,neutral or dissatisfied +99511,119887,Female,Loyal Customer,61,Personal Travel,Eco,936,1,4,1,3,3,5,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +99512,12926,Female,Loyal Customer,29,Personal Travel,Eco,456,4,3,4,5,3,4,5,3,1,1,2,4,4,3,0,0.0,neutral or dissatisfied +99513,54876,Male,Loyal Customer,65,Personal Travel,Eco,862,2,4,2,4,2,2,2,2,3,3,4,5,5,2,3,1.0,neutral or dissatisfied +99514,115812,Female,Loyal Customer,39,Business travel,Business,362,5,2,2,2,5,4,4,5,5,4,5,3,5,1,10,7.0,neutral or dissatisfied +99515,36197,Male,disloyal Customer,30,Business travel,Business,280,2,2,2,2,1,2,1,1,2,1,2,3,3,1,54,29.0,neutral or dissatisfied +99516,118890,Male,Loyal Customer,46,Business travel,Business,3223,5,2,5,5,4,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +99517,90975,Male,Loyal Customer,29,Business travel,Eco,404,3,1,5,5,3,3,3,3,3,4,4,3,3,3,41,57.0,neutral or dissatisfied +99518,21972,Female,disloyal Customer,21,Business travel,Eco,448,2,0,2,4,1,2,3,1,1,2,3,3,1,1,0,0.0,neutral or dissatisfied +99519,120465,Male,Loyal Customer,24,Personal Travel,Eco,449,0,2,0,3,5,0,3,5,2,5,4,2,3,5,1,0.0,satisfied +99520,133,Female,disloyal Customer,26,Business travel,Business,227,3,3,3,3,3,3,4,3,2,1,3,2,3,3,38,44.0,neutral or dissatisfied +99521,114652,Female,Loyal Customer,30,Business travel,Business,2159,1,1,3,1,5,5,5,5,5,5,4,5,4,5,7,0.0,satisfied +99522,105122,Male,Loyal Customer,37,Business travel,Business,3868,2,2,2,2,5,5,4,5,5,5,5,4,5,4,6,2.0,satisfied +99523,125110,Female,disloyal Customer,22,Business travel,Eco,361,4,4,4,3,5,4,5,5,4,1,4,2,4,5,0,0.0,neutral or dissatisfied +99524,59524,Male,Loyal Customer,42,Business travel,Business,3759,1,1,1,1,5,5,5,5,5,5,5,4,5,5,4,7.0,satisfied +99525,118329,Male,Loyal Customer,60,Business travel,Business,3326,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +99526,105808,Female,Loyal Customer,58,Personal Travel,Eco,787,3,5,4,3,3,5,4,2,2,4,1,5,2,5,36,51.0,neutral or dissatisfied +99527,1351,Female,Loyal Customer,56,Business travel,Business,3867,3,4,3,3,3,4,5,4,4,4,5,4,4,3,0,0.0,satisfied +99528,75197,Male,disloyal Customer,36,Business travel,Eco,923,2,2,2,3,5,2,5,5,3,4,2,3,3,5,0,0.0,neutral or dissatisfied +99529,35311,Male,Loyal Customer,50,Business travel,Eco,1028,2,3,3,3,1,2,1,1,2,2,3,4,3,1,66,53.0,satisfied +99530,54698,Male,Loyal Customer,50,Business travel,Business,2063,2,1,1,1,4,4,4,2,2,2,2,1,2,4,46,35.0,neutral or dissatisfied +99531,53709,Male,Loyal Customer,38,Business travel,Business,808,2,2,2,2,5,3,1,4,4,4,4,2,4,1,17,0.0,satisfied +99532,43194,Male,Loyal Customer,38,Business travel,Eco,651,4,5,4,5,4,4,4,4,1,5,5,3,4,4,0,0.0,satisfied +99533,60397,Female,Loyal Customer,43,Personal Travel,Eco,1452,2,3,2,2,1,2,2,4,4,2,4,1,4,4,51,32.0,neutral or dissatisfied +99534,17503,Female,Loyal Customer,63,Business travel,Eco,341,4,3,5,3,2,3,2,4,4,4,4,1,4,3,0,0.0,satisfied +99535,59700,Female,Loyal Customer,69,Personal Travel,Eco,964,1,5,1,3,3,5,4,5,5,1,1,4,5,5,0,5.0,neutral or dissatisfied +99536,23442,Female,Loyal Customer,51,Business travel,Business,627,4,4,4,4,2,2,3,4,4,4,4,1,4,2,50,73.0,satisfied +99537,65898,Male,Loyal Customer,38,Business travel,Business,569,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +99538,15967,Female,disloyal Customer,23,Business travel,Eco,723,2,2,2,4,2,2,2,2,2,1,1,3,5,2,24,17.0,neutral or dissatisfied +99539,57353,Male,Loyal Customer,34,Business travel,Business,3601,4,1,1,1,1,3,4,4,4,3,4,3,4,2,8,7.0,neutral or dissatisfied +99540,118682,Female,disloyal Customer,17,Business travel,Eco,369,5,2,5,1,1,5,1,1,1,4,1,3,4,1,0,0.0,satisfied +99541,31838,Female,Loyal Customer,32,Personal Travel,Eco Plus,2762,3,0,3,5,3,2,3,3,2,5,4,3,5,3,0,16.0,neutral or dissatisfied +99542,66721,Female,Loyal Customer,30,Personal Travel,Eco,802,1,3,1,5,5,1,5,5,1,2,1,4,2,5,31,18.0,neutral or dissatisfied +99543,76834,Female,Loyal Customer,14,Personal Travel,Eco,1851,1,4,1,4,3,1,3,3,4,4,4,1,2,3,0,0.0,neutral or dissatisfied +99544,87029,Female,Loyal Customer,30,Personal Travel,Business,594,4,1,4,3,1,4,1,1,1,1,3,3,2,1,67,46.0,neutral or dissatisfied +99545,115652,Female,disloyal Customer,43,Business travel,Eco,404,2,3,2,2,5,2,5,5,4,5,3,4,2,5,6,0.0,neutral or dissatisfied +99546,94752,Male,Loyal Customer,60,Business travel,Eco,189,1,2,5,2,1,1,1,1,2,2,3,1,2,1,45,50.0,neutral or dissatisfied +99547,75260,Female,Loyal Customer,46,Personal Travel,Eco,1744,1,2,1,3,5,1,3,5,5,1,1,4,5,4,2,10.0,neutral or dissatisfied +99548,83697,Female,Loyal Customer,56,Personal Travel,Eco,577,2,2,2,2,1,3,3,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +99549,46415,Female,disloyal Customer,30,Business travel,Business,458,3,3,3,2,2,3,2,2,2,1,2,2,3,2,0,12.0,neutral or dissatisfied +99550,53713,Male,Loyal Customer,17,Personal Travel,Eco,1208,2,1,2,3,4,2,5,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +99551,80168,Female,disloyal Customer,17,Business travel,Eco,817,3,3,3,4,3,1,1,3,4,2,4,1,2,1,35,13.0,neutral or dissatisfied +99552,2774,Male,Loyal Customer,57,Business travel,Business,764,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +99553,124776,Male,Loyal Customer,47,Business travel,Business,280,3,3,3,3,3,4,4,4,4,4,4,3,4,5,14,0.0,satisfied +99554,62648,Male,Loyal Customer,27,Personal Travel,Eco,1744,2,5,1,1,3,1,3,3,5,4,4,4,4,3,1,7.0,neutral or dissatisfied +99555,94435,Male,Loyal Customer,53,Business travel,Business,233,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +99556,27916,Female,Loyal Customer,47,Business travel,Eco,689,5,2,2,2,4,5,2,5,5,5,5,4,5,4,0,0.0,satisfied +99557,106347,Male,Loyal Customer,60,Personal Travel,Business,551,3,1,3,2,2,2,3,1,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +99558,80207,Female,Loyal Customer,60,Personal Travel,Eco Plus,2475,3,2,3,3,3,4,5,2,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +99559,98260,Female,Loyal Customer,59,Business travel,Business,1188,3,3,3,3,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +99560,39819,Female,Loyal Customer,67,Business travel,Business,221,4,4,4,4,2,4,1,4,4,4,5,5,4,4,85,101.0,satisfied +99561,100171,Male,Loyal Customer,27,Personal Travel,Eco,725,3,5,3,3,4,3,4,4,4,4,3,5,4,4,10,40.0,neutral or dissatisfied +99562,37011,Male,Loyal Customer,51,Personal Travel,Eco,805,1,5,1,1,3,1,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +99563,27145,Male,Loyal Customer,25,Business travel,Eco,2681,5,3,3,3,5,3,5,4,1,3,2,5,2,5,0,24.0,satisfied +99564,17664,Male,Loyal Customer,31,Personal Travel,Eco,1008,5,5,5,4,1,5,1,1,5,4,5,3,5,1,0,0.0,satisfied +99565,120669,Male,Loyal Customer,49,Business travel,Business,280,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +99566,11299,Female,Loyal Customer,63,Personal Travel,Eco,163,1,5,1,4,3,4,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +99567,7310,Female,Loyal Customer,29,Business travel,Eco Plus,130,2,3,3,3,2,2,2,2,1,4,4,2,3,2,0,5.0,neutral or dissatisfied +99568,8132,Male,Loyal Customer,30,Business travel,Business,3440,3,3,3,3,3,3,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +99569,48774,Female,Loyal Customer,50,Business travel,Business,1769,1,1,1,1,2,5,4,4,4,4,5,3,4,4,0,4.0,satisfied +99570,113133,Male,Loyal Customer,26,Personal Travel,Eco Plus,543,2,3,2,3,3,2,3,3,1,1,4,5,5,3,33,13.0,neutral or dissatisfied +99571,79936,Male,Loyal Customer,49,Business travel,Business,1767,1,1,1,1,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +99572,103244,Female,Loyal Customer,33,Personal Travel,Eco,409,1,5,1,5,4,1,4,4,4,1,5,2,4,4,0,0.0,neutral or dissatisfied +99573,28991,Male,Loyal Customer,54,Business travel,Eco,937,2,3,3,3,2,2,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +99574,81889,Female,disloyal Customer,24,Business travel,Eco,680,2,1,1,1,4,1,4,4,4,5,1,4,2,4,0,0.0,neutral or dissatisfied +99575,43931,Male,Loyal Customer,47,Business travel,Eco Plus,199,4,2,2,2,4,4,4,4,1,3,2,2,5,4,10,12.0,satisfied +99576,107498,Female,disloyal Customer,27,Business travel,Eco,311,3,1,3,3,1,3,1,1,4,5,3,3,4,1,29,16.0,neutral or dissatisfied +99577,54285,Female,Loyal Customer,57,Business travel,Eco,1075,5,2,2,2,4,3,3,5,5,5,5,3,5,2,0,0.0,satisfied +99578,107261,Female,Loyal Customer,39,Business travel,Business,3273,3,3,3,3,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +99579,921,Male,Loyal Customer,55,Business travel,Business,1568,2,5,5,5,3,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +99580,114175,Female,Loyal Customer,48,Business travel,Business,909,2,2,2,2,4,5,4,2,2,2,2,3,2,3,6,0.0,satisfied +99581,44986,Female,Loyal Customer,30,Business travel,Business,3556,1,1,3,1,5,5,4,5,4,2,4,5,4,5,0,8.0,satisfied +99582,128327,Female,Loyal Customer,39,Business travel,Business,1705,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,10.0,satisfied +99583,37461,Male,disloyal Customer,24,Business travel,Eco,1069,2,2,2,2,4,2,4,4,2,1,3,2,2,4,3,4.0,neutral or dissatisfied +99584,31704,Male,Loyal Customer,18,Personal Travel,Eco,967,3,4,3,4,5,3,5,5,4,1,3,1,3,5,95,79.0,neutral or dissatisfied +99585,90200,Male,Loyal Customer,41,Personal Travel,Eco,1084,4,4,4,2,5,4,5,5,5,2,5,5,5,5,0,0.0,satisfied +99586,33621,Male,Loyal Customer,46,Business travel,Business,1901,5,5,5,5,1,1,4,5,5,5,5,3,5,5,22,25.0,satisfied +99587,33740,Male,Loyal Customer,31,Business travel,Eco Plus,899,2,1,1,1,2,2,2,2,4,2,4,3,3,2,0,14.0,neutral or dissatisfied +99588,7807,Female,Loyal Customer,34,Business travel,Business,2419,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,9.0,satisfied +99589,2836,Female,disloyal Customer,59,Business travel,Eco,475,2,4,2,3,3,2,1,3,1,5,4,3,3,3,1,0.0,neutral or dissatisfied +99590,83126,Male,Loyal Customer,7,Personal Travel,Eco,1145,2,3,2,3,3,2,5,3,4,1,3,1,2,3,0,0.0,neutral or dissatisfied +99591,39538,Female,Loyal Customer,33,Business travel,Business,3477,4,4,4,4,2,4,3,5,5,5,5,1,5,2,0,30.0,satisfied +99592,62631,Male,Loyal Customer,23,Personal Travel,Eco,1726,5,4,5,3,3,5,3,3,3,3,3,3,5,3,2,0.0,satisfied +99593,10104,Male,Loyal Customer,57,Personal Travel,Eco,1195,2,5,2,1,3,2,3,3,5,4,4,4,4,3,89,85.0,neutral or dissatisfied +99594,37775,Male,Loyal Customer,27,Business travel,Eco Plus,1069,5,1,1,1,5,5,5,1,2,4,1,5,3,5,92,158.0,satisfied +99595,73487,Female,Loyal Customer,70,Personal Travel,Eco,1120,3,4,3,1,3,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +99596,60434,Male,Loyal Customer,57,Business travel,Business,641,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +99597,72736,Male,Loyal Customer,11,Personal Travel,Eco Plus,1102,3,4,3,4,4,3,5,4,5,3,1,5,4,4,2,0.0,neutral or dissatisfied +99598,38278,Male,Loyal Customer,60,Personal Travel,Eco,1111,3,4,3,3,3,3,3,3,1,5,3,1,3,3,17,0.0,neutral or dissatisfied +99599,48630,Female,Loyal Customer,45,Business travel,Business,1939,0,4,0,3,5,5,5,4,4,2,2,4,4,4,0,0.0,satisfied +99600,100417,Female,Loyal Customer,22,Personal Travel,Eco Plus,1092,4,5,3,5,1,3,1,1,2,2,4,2,5,1,64,46.0,neutral or dissatisfied +99601,86959,Male,Loyal Customer,24,Business travel,Eco,907,2,5,5,5,2,2,3,2,3,4,4,4,3,2,20,13.0,neutral or dissatisfied +99602,73523,Male,Loyal Customer,42,Business travel,Business,594,5,5,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +99603,48355,Female,disloyal Customer,24,Business travel,Eco,587,2,2,3,4,4,3,3,4,2,5,3,1,4,4,3,5.0,neutral or dissatisfied +99604,14699,Male,Loyal Customer,36,Business travel,Eco,479,4,1,1,1,4,4,4,4,2,4,3,2,3,4,0,0.0,satisfied +99605,56473,Female,Loyal Customer,45,Personal Travel,Eco Plus,719,1,5,1,5,4,5,5,5,5,1,5,5,5,3,0,12.0,neutral or dissatisfied +99606,83836,Male,Loyal Customer,31,Business travel,Eco,425,2,2,2,2,2,2,2,2,2,3,3,1,4,2,0,0.0,neutral or dissatisfied +99607,111132,Female,Loyal Customer,49,Business travel,Business,1111,5,5,2,5,2,5,5,5,5,5,5,3,5,3,16,0.0,satisfied +99608,108300,Female,Loyal Customer,48,Business travel,Business,1750,5,5,5,5,3,4,5,5,5,5,5,4,5,4,27,26.0,satisfied +99609,7902,Male,disloyal Customer,37,Business travel,Business,1020,3,3,3,3,2,3,2,2,5,4,5,5,5,2,2,0.0,neutral or dissatisfied +99610,120402,Male,disloyal Customer,23,Business travel,Eco,366,5,5,5,2,3,5,3,3,3,5,5,5,5,3,0,0.0,satisfied +99611,127035,Female,Loyal Customer,36,Business travel,Business,370,1,1,1,1,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +99612,39294,Female,Loyal Customer,43,Personal Travel,Eco,67,1,4,1,3,3,5,4,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +99613,110702,Male,Loyal Customer,44,Business travel,Business,829,1,1,1,1,3,4,4,4,4,4,4,4,4,5,11,2.0,satisfied +99614,11572,Male,Loyal Customer,56,Business travel,Business,3856,2,2,2,2,5,4,5,5,5,5,5,4,5,5,60,65.0,satisfied +99615,126682,Male,Loyal Customer,40,Business travel,Business,2370,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,38.0,satisfied +99616,114901,Male,Loyal Customer,39,Business travel,Business,2738,1,1,1,1,2,4,5,2,2,2,2,4,2,5,0,0.0,satisfied +99617,101658,Male,Loyal Customer,52,Business travel,Business,2106,5,5,5,5,2,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +99618,59256,Female,Loyal Customer,45,Personal Travel,Eco,3904,1,4,1,1,1,5,5,3,2,3,4,5,4,5,2,0.0,neutral or dissatisfied +99619,86489,Female,Loyal Customer,19,Personal Travel,Eco,712,4,3,4,1,5,4,5,5,3,1,2,3,1,5,0,0.0,neutral or dissatisfied +99620,22670,Female,Loyal Customer,59,Business travel,Eco,579,4,5,5,5,4,5,5,5,5,3,3,5,3,5,147,144.0,satisfied +99621,19678,Female,Loyal Customer,57,Business travel,Eco,409,4,5,5,5,3,2,5,4,4,4,4,5,4,3,22,23.0,satisfied +99622,78015,Male,Loyal Customer,46,Business travel,Business,2275,1,1,1,1,2,2,3,4,4,3,1,4,4,1,0,0.0,neutral or dissatisfied +99623,58105,Male,Loyal Customer,12,Personal Travel,Eco,612,4,4,4,2,5,4,4,5,1,3,1,1,3,5,0,0.0,satisfied +99624,114845,Male,disloyal Customer,26,Business travel,Business,480,0,0,0,1,1,0,1,1,4,5,5,5,5,1,18,7.0,satisfied +99625,79642,Female,Loyal Customer,39,Business travel,Business,1952,3,3,3,3,1,5,2,5,5,5,5,4,5,5,112,94.0,satisfied +99626,91969,Male,Loyal Customer,14,Personal Travel,Eco,2475,2,1,2,3,4,2,3,4,3,2,4,1,3,4,25,5.0,neutral or dissatisfied +99627,80457,Female,Loyal Customer,36,Business travel,Business,1299,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,4.0,satisfied +99628,70998,Male,Loyal Customer,47,Business travel,Business,3245,4,4,4,4,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +99629,7091,Male,Loyal Customer,48,Business travel,Business,177,4,1,1,1,3,3,3,2,2,2,4,3,2,4,1,0.0,neutral or dissatisfied +99630,50868,Male,Loyal Customer,34,Personal Travel,Eco,86,3,5,0,3,4,0,2,4,3,4,1,2,3,4,0,0.0,neutral or dissatisfied +99631,74554,Female,Loyal Customer,38,Business travel,Business,2286,1,1,1,1,4,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +99632,76302,Female,Loyal Customer,45,Business travel,Business,2182,3,3,3,3,5,5,4,2,2,3,2,3,2,3,0,0.0,satisfied +99633,14173,Female,Loyal Customer,30,Business travel,Business,2627,4,4,4,4,4,4,4,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +99634,20521,Female,Loyal Customer,25,Personal Travel,Business,565,2,5,2,5,4,2,4,4,2,4,2,1,3,4,18,43.0,neutral or dissatisfied +99635,108512,Female,Loyal Customer,48,Business travel,Business,2817,1,1,1,1,3,5,4,5,5,5,5,3,5,3,15,17.0,satisfied +99636,19290,Male,disloyal Customer,24,Business travel,Eco,299,2,5,2,2,1,2,1,1,3,1,1,4,3,1,0,0.0,neutral or dissatisfied +99637,39,Female,Loyal Customer,46,Business travel,Business,67,3,3,3,3,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +99638,113466,Male,Loyal Customer,31,Business travel,Business,397,2,1,1,1,2,2,2,2,1,3,3,1,3,2,14,6.0,neutral or dissatisfied +99639,70432,Female,Loyal Customer,40,Business travel,Business,187,2,2,4,2,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +99640,13954,Male,Loyal Customer,54,Personal Travel,Eco,153,2,4,2,3,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +99641,94819,Female,disloyal Customer,22,Business travel,Eco,277,1,2,1,4,3,1,3,3,2,4,3,3,4,3,30,30.0,neutral or dissatisfied +99642,27249,Male,Loyal Customer,55,Personal Travel,Eco Plus,1024,1,4,1,3,5,1,5,5,5,3,4,3,4,5,0,1.0,neutral or dissatisfied +99643,17762,Female,Loyal Customer,69,Personal Travel,Eco Plus,383,3,5,3,3,5,5,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +99644,80830,Male,Loyal Customer,36,Business travel,Business,3281,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,7.0,satisfied +99645,11925,Male,Loyal Customer,22,Personal Travel,Eco,744,1,3,1,2,5,1,5,5,1,2,3,1,2,5,0,0.0,neutral or dissatisfied +99646,69489,Male,Loyal Customer,29,Business travel,Eco Plus,1089,2,2,5,2,2,2,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +99647,118281,Female,Loyal Customer,29,Business travel,Business,1919,4,4,3,4,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +99648,116911,Male,Loyal Customer,58,Business travel,Business,1926,5,5,5,5,5,5,5,3,3,3,3,3,3,5,34,18.0,satisfied +99649,86713,Male,Loyal Customer,63,Business travel,Business,1747,4,4,4,4,4,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +99650,118692,Male,Loyal Customer,69,Personal Travel,Eco,646,3,4,3,5,1,3,1,1,1,3,5,2,3,1,0,0.0,neutral or dissatisfied +99651,10080,Male,Loyal Customer,57,Personal Travel,Eco,258,3,5,0,2,5,0,5,5,4,5,5,2,2,5,34,25.0,neutral or dissatisfied +99652,4794,Male,Loyal Customer,63,Personal Travel,Eco,315,3,3,4,1,3,4,3,3,1,5,3,5,1,3,3,4.0,neutral or dissatisfied +99653,78652,Female,Loyal Customer,29,Personal Travel,Eco,2172,2,5,2,4,3,2,3,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +99654,65303,Female,Loyal Customer,53,Personal Travel,Eco Plus,224,2,4,2,1,2,5,5,4,4,2,4,5,4,4,16,16.0,neutral or dissatisfied +99655,104774,Female,disloyal Customer,22,Business travel,Eco,587,3,4,3,2,2,3,2,2,4,4,4,4,4,2,28,32.0,neutral or dissatisfied +99656,104162,Female,Loyal Customer,70,Business travel,Business,2556,2,5,5,5,2,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +99657,39943,Female,disloyal Customer,23,Business travel,Eco,686,3,3,3,4,4,3,4,4,2,5,4,2,3,4,14,18.0,neutral or dissatisfied +99658,128512,Male,Loyal Customer,63,Personal Travel,Eco,325,3,4,3,2,3,3,3,3,5,1,1,4,5,3,0,1.0,neutral or dissatisfied +99659,101039,Female,Loyal Customer,44,Personal Travel,Business,368,2,4,2,4,2,4,3,3,3,2,3,1,3,1,3,0.0,neutral or dissatisfied +99660,50708,Male,Loyal Customer,64,Personal Travel,Eco,278,2,4,2,3,5,2,5,5,4,5,4,4,3,5,0,0.0,neutral or dissatisfied +99661,128211,Female,Loyal Customer,51,Business travel,Business,3531,5,5,4,5,4,5,4,5,5,5,5,4,5,3,0,32.0,satisfied +99662,119860,Male,Loyal Customer,32,Personal Travel,Eco,936,5,2,5,3,3,5,5,3,3,4,2,1,3,3,5,1.0,satisfied +99663,9152,Male,Loyal Customer,24,Personal Travel,Eco,227,2,5,2,3,3,2,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +99664,99486,Male,Loyal Customer,34,Personal Travel,Eco,283,4,5,4,2,4,4,4,4,5,4,5,3,4,4,20,16.0,satisfied +99665,6383,Female,Loyal Customer,76,Business travel,Business,3316,1,5,5,5,2,3,3,2,2,2,1,4,2,2,0,0.0,neutral or dissatisfied +99666,113861,Male,Loyal Customer,55,Business travel,Business,1592,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +99667,8094,Female,Loyal Customer,33,Business travel,Business,402,3,3,3,3,4,4,5,5,5,5,5,5,5,3,27,24.0,satisfied +99668,36714,Male,Loyal Customer,24,Business travel,Eco Plus,1249,4,2,2,2,4,4,3,4,1,5,2,3,4,4,23,59.0,satisfied +99669,57326,Male,Loyal Customer,40,Business travel,Business,3554,4,4,4,4,4,5,4,2,2,2,2,3,2,5,8,39.0,satisfied +99670,11756,Female,Loyal Customer,41,Business travel,Business,429,4,4,4,4,2,3,1,5,5,5,5,5,5,5,0,0.0,satisfied +99671,27856,Female,Loyal Customer,70,Personal Travel,Eco,1448,3,4,3,2,2,5,2,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +99672,86605,Male,disloyal Customer,42,Business travel,Business,746,4,4,4,4,3,4,3,3,3,2,4,3,5,3,6,0.0,satisfied +99673,92217,Female,Loyal Customer,53,Personal Travel,Eco,2079,2,0,3,5,3,4,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +99674,114295,Female,Loyal Customer,48,Personal Travel,Eco,948,4,4,4,3,2,4,4,3,3,4,3,1,3,4,3,0.0,neutral or dissatisfied +99675,71584,Female,Loyal Customer,27,Business travel,Business,1197,3,3,3,3,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +99676,101114,Male,disloyal Customer,29,Business travel,Business,758,5,5,5,4,4,5,1,4,4,5,4,3,4,4,6,0.0,satisfied +99677,6734,Female,disloyal Customer,28,Business travel,Eco,334,2,4,1,3,4,1,4,4,4,2,4,1,3,4,2,6.0,neutral or dissatisfied +99678,59081,Male,Loyal Customer,37,Business travel,Business,244,4,2,3,2,4,4,4,3,3,4,3,4,1,4,242,246.0,neutral or dissatisfied +99679,109402,Female,Loyal Customer,44,Business travel,Business,1608,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +99680,9409,Female,Loyal Customer,36,Business travel,Eco,1136,2,5,2,5,2,2,2,2,1,2,3,2,3,2,40,28.0,neutral or dissatisfied +99681,123810,Male,Loyal Customer,59,Business travel,Business,603,5,5,5,5,4,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +99682,84033,Male,Loyal Customer,58,Business travel,Business,757,5,5,5,5,4,5,5,5,5,5,5,3,5,3,19,2.0,satisfied +99683,120901,Male,disloyal Customer,38,Business travel,Business,920,1,1,1,3,2,1,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +99684,68415,Female,Loyal Customer,16,Personal Travel,Eco,1045,4,5,4,3,5,4,5,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +99685,26849,Female,Loyal Customer,34,Personal Travel,Eco,224,5,4,5,3,3,5,5,3,4,2,4,3,4,3,0,0.0,satisfied +99686,18640,Female,Loyal Customer,42,Personal Travel,Eco,262,1,5,1,4,3,3,4,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +99687,86110,Female,Loyal Customer,46,Business travel,Business,1972,3,3,3,3,2,5,4,5,5,5,5,5,5,3,17,11.0,satisfied +99688,51108,Male,Loyal Customer,26,Personal Travel,Eco,86,4,5,4,3,1,4,1,1,3,3,4,4,5,1,25,24.0,neutral or dissatisfied +99689,66900,Female,Loyal Customer,57,Personal Travel,Business,918,1,3,1,4,2,3,4,4,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +99690,10784,Female,Loyal Customer,28,Business travel,Business,3823,3,3,3,3,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +99691,54557,Male,Loyal Customer,63,Personal Travel,Eco,925,2,5,2,1,5,2,2,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +99692,95570,Female,Loyal Customer,68,Personal Travel,Eco Plus,248,2,5,2,1,2,5,4,2,2,2,2,4,2,5,3,0.0,neutral or dissatisfied +99693,110295,Male,Loyal Customer,25,Business travel,Business,1850,2,2,2,2,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +99694,34327,Female,disloyal Customer,29,Business travel,Eco,846,3,3,3,3,2,3,4,2,3,5,3,5,5,2,26,22.0,neutral or dissatisfied +99695,37554,Female,Loyal Customer,40,Business travel,Business,3650,3,3,3,3,5,3,2,5,5,5,5,5,5,4,23,0.0,satisfied +99696,96992,Male,Loyal Customer,18,Personal Travel,Eco,775,3,1,3,2,2,3,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +99697,72475,Female,disloyal Customer,39,Business travel,Business,1017,2,2,2,4,3,2,3,3,5,5,5,4,4,3,101,92.0,satisfied +99698,14137,Male,disloyal Customer,19,Business travel,Eco,413,3,4,3,3,1,3,1,1,1,4,4,2,4,1,28,25.0,neutral or dissatisfied +99699,72804,Male,Loyal Customer,69,Personal Travel,Eco,1045,5,5,5,3,2,5,2,2,4,4,4,4,4,2,0,0.0,satisfied +99700,49818,Male,disloyal Customer,39,Business travel,Eco,207,2,5,2,1,2,2,2,2,3,2,4,4,5,2,0,6.0,neutral or dissatisfied +99701,92264,Female,Loyal Customer,57,Business travel,Business,2036,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +99702,10505,Male,Loyal Customer,37,Business travel,Eco,316,1,1,1,1,1,1,1,1,2,4,3,4,3,1,0,7.0,neutral or dissatisfied +99703,98905,Female,Loyal Customer,41,Business travel,Business,3919,4,4,4,4,4,4,5,4,4,4,4,3,4,3,4,1.0,satisfied +99704,119441,Female,Loyal Customer,23,Business travel,Eco Plus,399,2,2,2,2,2,2,2,2,4,4,3,3,3,2,0,0.0,neutral or dissatisfied +99705,19264,Male,Loyal Customer,33,Personal Travel,Eco,802,3,2,3,2,5,3,5,5,1,4,2,4,3,5,13,31.0,neutral or dissatisfied +99706,61100,Female,Loyal Customer,15,Personal Travel,Eco,1546,4,5,4,5,4,4,4,4,3,4,3,3,4,4,12,0.0,neutral or dissatisfied +99707,47551,Female,disloyal Customer,45,Business travel,Eco Plus,599,2,2,2,3,4,2,4,4,3,5,3,4,4,4,10,0.0,neutral or dissatisfied +99708,72770,Male,Loyal Customer,43,Business travel,Business,3608,4,4,4,4,3,4,4,4,4,4,4,4,4,5,14,0.0,satisfied +99709,7259,Male,Loyal Customer,15,Personal Travel,Eco,135,2,0,2,4,3,2,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +99710,118524,Male,Loyal Customer,52,Business travel,Business,621,2,2,2,2,2,4,4,2,2,2,2,4,2,4,54,47.0,satisfied +99711,41228,Female,Loyal Customer,65,Personal Travel,Eco,1042,2,5,2,3,5,4,3,3,3,2,3,3,3,3,44,40.0,neutral or dissatisfied +99712,57738,Male,Loyal Customer,53,Business travel,Eco Plus,1754,4,5,5,5,4,4,4,4,2,5,4,3,3,4,4,0.0,neutral or dissatisfied +99713,6396,Male,Loyal Customer,53,Business travel,Business,2556,4,4,4,4,2,2,4,5,5,5,5,3,5,4,0,0.0,satisfied +99714,43158,Male,Loyal Customer,15,Personal Travel,Eco,1368,3,4,3,5,1,3,1,1,3,3,4,4,5,1,0,38.0,neutral or dissatisfied +99715,77555,Male,Loyal Customer,21,Personal Travel,Eco,986,3,4,4,3,5,4,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +99716,25054,Male,Loyal Customer,32,Business travel,Business,2343,2,2,2,2,4,4,4,4,5,2,4,2,5,4,44,46.0,satisfied +99717,22300,Male,disloyal Customer,27,Business travel,Eco,238,2,5,2,2,2,2,2,2,4,4,3,5,5,2,26,55.0,neutral or dissatisfied +99718,86571,Female,Loyal Customer,32,Business travel,Business,1269,3,2,2,2,3,3,3,3,1,5,3,3,4,3,4,0.0,neutral or dissatisfied +99719,26748,Male,Loyal Customer,38,Business travel,Business,859,1,1,1,1,1,3,2,5,5,5,5,3,5,2,0,0.0,satisfied +99720,128362,Male,Loyal Customer,39,Business travel,Business,3882,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +99721,98018,Male,Loyal Customer,55,Business travel,Business,3446,2,4,5,4,1,3,3,2,2,2,2,1,2,4,7,0.0,neutral or dissatisfied +99722,27996,Female,Loyal Customer,49,Business travel,Business,1776,4,4,4,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +99723,115712,Male,Loyal Customer,63,Business travel,Business,3958,3,3,1,3,3,3,3,3,3,3,3,3,3,4,11,0.0,neutral or dissatisfied +99724,75204,Male,Loyal Customer,42,Business travel,Business,1744,1,0,0,1,2,2,2,4,4,0,4,2,4,4,7,0.0,neutral or dissatisfied +99725,117236,Female,Loyal Customer,63,Personal Travel,Eco,325,3,2,2,2,5,2,2,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +99726,118985,Male,Loyal Customer,34,Personal Travel,Business,479,1,5,1,1,1,2,2,5,5,1,5,4,5,2,17,13.0,neutral or dissatisfied +99727,42584,Female,Loyal Customer,29,Personal Travel,Eco,296,3,1,3,4,2,3,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +99728,125958,Female,Loyal Customer,67,Personal Travel,Eco Plus,920,4,3,4,2,2,2,3,2,2,4,2,3,2,3,0,0.0,satisfied +99729,33353,Female,Loyal Customer,29,Business travel,Eco,2614,3,1,1,1,3,2,3,3,3,4,2,1,2,3,0,0.0,neutral or dissatisfied +99730,77684,Female,Loyal Customer,60,Business travel,Eco,874,3,2,2,2,4,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +99731,36338,Male,Loyal Customer,13,Personal Travel,Eco,187,2,5,2,2,2,2,2,2,5,5,5,5,4,2,50,48.0,neutral or dissatisfied +99732,5842,Male,Loyal Customer,42,Business travel,Business,3664,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,5.0,satisfied +99733,72449,Female,disloyal Customer,25,Business travel,Business,1017,4,5,4,2,5,4,5,5,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +99734,114722,Male,disloyal Customer,47,Business travel,Business,446,3,3,3,5,2,3,2,2,3,2,5,4,4,2,52,43.0,neutral or dissatisfied +99735,65945,Male,disloyal Customer,9,Business travel,Business,1372,0,0,0,2,3,0,3,3,4,2,4,5,4,3,6,0.0,satisfied +99736,100954,Male,Loyal Customer,22,Business travel,Business,1204,1,1,1,1,1,2,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +99737,105824,Male,Loyal Customer,44,Personal Travel,Eco,925,4,4,4,4,5,4,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +99738,117909,Male,Loyal Customer,52,Business travel,Business,1641,1,1,1,1,2,5,5,4,4,4,4,5,4,4,1,1.0,satisfied +99739,52686,Male,Loyal Customer,34,Personal Travel,Eco,119,3,1,3,3,4,3,4,4,3,5,4,2,3,4,0,0.0,neutral or dissatisfied +99740,70362,Female,disloyal Customer,22,Business travel,Business,1145,4,3,5,2,3,5,3,3,3,2,5,3,5,3,0,0.0,satisfied +99741,14101,Female,Loyal Customer,54,Personal Travel,Eco,371,2,4,2,4,1,3,3,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +99742,38760,Female,Loyal Customer,33,Business travel,Business,3601,2,1,1,1,3,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +99743,82455,Female,disloyal Customer,21,Business travel,Eco,102,3,3,3,4,5,3,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +99744,112864,Male,Loyal Customer,43,Business travel,Business,1129,2,2,2,2,5,5,5,5,5,5,5,3,5,5,45,45.0,satisfied +99745,90938,Female,Loyal Customer,29,Business travel,Eco,515,3,2,1,2,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +99746,47574,Male,disloyal Customer,46,Business travel,Business,1334,3,3,3,3,1,3,1,1,5,4,5,4,4,1,7,18.0,neutral or dissatisfied +99747,41305,Female,Loyal Customer,21,Business travel,Business,3284,4,4,4,4,5,5,5,5,5,3,4,4,4,5,0,0.0,satisfied +99748,70715,Female,Loyal Customer,46,Business travel,Business,2068,2,2,4,2,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +99749,53830,Female,Loyal Customer,39,Business travel,Eco,224,5,5,5,5,5,5,5,5,4,4,3,3,4,5,0,0.0,satisfied +99750,81746,Male,Loyal Customer,49,Business travel,Business,2565,2,3,2,2,2,4,5,4,4,4,4,3,4,3,5,0.0,satisfied +99751,120371,Female,Loyal Customer,53,Business travel,Business,449,3,3,3,3,2,5,4,4,4,4,4,4,4,5,40,102.0,satisfied +99752,3559,Male,disloyal Customer,21,Business travel,Business,227,1,3,1,3,1,1,1,2,3,3,3,1,3,1,182,184.0,neutral or dissatisfied +99753,116460,Male,Loyal Customer,57,Personal Travel,Eco,337,1,4,1,1,1,1,1,1,3,4,4,3,5,1,36,24.0,neutral or dissatisfied +99754,100415,Male,Loyal Customer,36,Personal Travel,Eco Plus,1034,3,4,3,3,5,3,5,5,4,5,4,4,5,5,72,70.0,neutral or dissatisfied +99755,94574,Female,Loyal Customer,45,Business travel,Business,3187,3,3,4,3,4,4,5,4,4,4,4,4,4,5,1,0.0,satisfied +99756,84714,Female,Loyal Customer,44,Personal Travel,Business,547,4,1,4,4,1,2,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +99757,113181,Female,Loyal Customer,33,Personal Travel,Eco,677,1,5,1,4,5,1,3,5,3,2,5,4,5,5,31,30.0,neutral or dissatisfied +99758,76900,Female,Loyal Customer,37,Business travel,Eco,230,1,2,2,2,1,1,1,1,2,2,3,4,4,1,0,13.0,neutral or dissatisfied +99759,36800,Female,Loyal Customer,40,Personal Travel,Eco,2611,1,3,1,4,1,2,2,1,5,5,5,2,4,2,128,135.0,neutral or dissatisfied +99760,15190,Female,Loyal Customer,60,Business travel,Eco,544,4,5,5,5,4,3,3,4,4,4,4,3,4,2,21,1.0,neutral or dissatisfied +99761,93369,Female,Loyal Customer,61,Personal Travel,Eco,836,3,4,3,4,3,4,5,4,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +99762,73973,Male,Loyal Customer,17,Personal Travel,Eco,2585,4,4,4,4,4,5,3,5,2,4,5,3,4,3,0,0.0,neutral or dissatisfied +99763,111439,Female,Loyal Customer,45,Business travel,Business,3769,5,5,5,5,5,5,5,4,4,4,4,3,4,4,1,8.0,satisfied +99764,59675,Male,Loyal Customer,16,Personal Travel,Eco,787,2,4,2,3,3,2,3,3,3,4,4,3,3,3,15,26.0,neutral or dissatisfied +99765,35893,Female,Loyal Customer,33,Personal Travel,Eco,1065,2,5,2,2,1,2,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +99766,49955,Female,Loyal Customer,35,Business travel,Eco,77,1,5,5,5,1,1,1,1,3,5,3,1,3,1,0,10.0,neutral or dissatisfied +99767,10448,Male,Loyal Customer,36,Business travel,Business,2011,2,2,2,2,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +99768,60567,Female,Loyal Customer,30,Personal Travel,Eco Plus,862,4,5,4,5,2,4,2,2,5,2,4,5,5,2,4,0.0,neutral or dissatisfied +99769,98116,Female,Loyal Customer,76,Business travel,Business,2015,3,5,5,5,5,3,2,3,3,3,3,1,3,1,25,18.0,neutral or dissatisfied +99770,59957,Male,Loyal Customer,29,Business travel,Eco,1065,3,5,5,5,3,3,3,3,2,1,1,4,1,3,0,0.0,neutral or dissatisfied +99771,96357,Female,Loyal Customer,61,Personal Travel,Eco,1609,2,5,2,2,3,4,5,2,2,2,2,4,2,4,2,0.0,neutral or dissatisfied +99772,82470,Male,Loyal Customer,55,Personal Travel,Eco,502,2,5,2,5,5,2,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +99773,43784,Male,Loyal Customer,9,Personal Travel,Eco,481,1,5,1,2,3,1,3,3,3,2,1,4,5,3,0,0.0,neutral or dissatisfied +99774,37117,Male,Loyal Customer,14,Business travel,Business,2958,3,3,3,3,5,5,5,5,1,3,4,3,3,5,0,0.0,satisfied +99775,59237,Female,Loyal Customer,32,Personal Travel,Eco,649,0,2,0,3,2,0,2,2,2,2,4,4,4,2,0,3.0,satisfied +99776,121953,Female,Loyal Customer,57,Business travel,Business,430,2,2,2,2,5,5,4,2,2,2,2,3,2,5,2,0.0,satisfied +99777,107425,Female,Loyal Customer,8,Personal Travel,Eco,468,3,4,3,5,3,3,3,3,4,5,5,4,4,3,28,19.0,neutral or dissatisfied +99778,69333,Female,Loyal Customer,41,Business travel,Business,2623,2,2,2,2,3,4,4,5,5,5,5,3,5,5,10,3.0,satisfied +99779,11338,Female,Loyal Customer,53,Personal Travel,Eco,163,2,5,2,4,1,3,2,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +99780,26719,Male,disloyal Customer,38,Personal Travel,Eco,404,2,4,2,3,2,2,2,2,4,3,5,5,5,2,50,49.0,neutral or dissatisfied +99781,111666,Female,disloyal Customer,25,Business travel,Eco,991,4,4,4,3,1,4,1,1,3,4,4,2,3,1,17,0.0,neutral or dissatisfied +99782,105629,Male,Loyal Customer,49,Business travel,Business,1559,3,3,3,3,3,4,5,5,5,5,5,4,5,4,2,5.0,satisfied +99783,29270,Male,Loyal Customer,41,Business travel,Business,2522,1,1,1,1,4,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +99784,30471,Male,Loyal Customer,39,Personal Travel,Eco Plus,495,1,3,1,4,2,1,1,2,2,4,3,3,4,2,0,4.0,neutral or dissatisfied +99785,36457,Male,disloyal Customer,23,Business travel,Eco,867,3,3,3,3,5,3,4,5,3,4,4,2,3,5,0,1.0,neutral or dissatisfied +99786,2550,Female,Loyal Customer,57,Business travel,Business,304,2,2,2,2,4,5,5,4,4,4,4,5,4,3,2,0.0,satisfied +99787,71298,Male,Loyal Customer,10,Business travel,Business,1514,3,3,3,3,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +99788,71028,Male,Loyal Customer,31,Business travel,Business,2110,4,1,4,4,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +99789,113246,Female,Loyal Customer,23,Personal Travel,Business,226,2,4,2,1,5,2,5,5,4,5,4,4,4,5,4,0.0,neutral or dissatisfied +99790,108066,Female,Loyal Customer,39,Personal Travel,Business,990,2,2,2,2,3,2,3,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +99791,94207,Female,Loyal Customer,48,Business travel,Business,323,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +99792,61890,Female,Loyal Customer,28,Personal Travel,Eco,2136,3,5,3,3,3,3,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +99793,84287,Female,disloyal Customer,56,Business travel,Eco Plus,349,4,4,4,4,1,4,4,1,2,2,1,5,2,1,7,0.0,satisfied +99794,82234,Female,Loyal Customer,35,Personal Travel,Eco,405,0,5,0,3,2,0,2,2,5,3,4,5,4,2,2,0.0,satisfied +99795,27439,Male,Loyal Customer,22,Business travel,Business,679,2,5,5,5,2,2,2,2,3,5,4,3,4,2,68,66.0,neutral or dissatisfied +99796,119563,Male,Loyal Customer,33,Personal Travel,Eco,759,4,5,4,2,5,4,5,5,3,3,4,5,4,5,0,1.0,satisfied +99797,101548,Female,Loyal Customer,8,Personal Travel,Eco,345,1,4,1,4,5,1,5,5,4,2,5,4,4,5,31,28.0,neutral or dissatisfied +99798,72840,Female,Loyal Customer,36,Personal Travel,Eco,1013,2,3,2,3,3,2,4,3,4,3,3,3,3,3,0,0.0,neutral or dissatisfied +99799,86482,Female,Loyal Customer,26,Personal Travel,Eco,762,2,5,2,1,4,2,4,4,5,4,5,5,5,4,4,0.0,neutral or dissatisfied +99800,120619,Female,Loyal Customer,25,Personal Travel,Business,280,5,5,5,3,4,5,4,4,3,2,4,3,4,4,0,0.0,satisfied +99801,77252,Female,disloyal Customer,38,Business travel,Eco,1190,2,2,2,1,2,2,2,2,5,5,2,1,4,2,0,7.0,neutral or dissatisfied +99802,95375,Female,Loyal Customer,34,Personal Travel,Eco,189,3,4,3,4,1,3,1,1,4,2,3,3,4,1,1,0.0,neutral or dissatisfied +99803,20256,Female,Loyal Customer,36,Business travel,Eco,346,3,3,4,4,3,3,3,3,4,2,2,3,3,3,0,0.0,satisfied +99804,96625,Male,Loyal Customer,52,Business travel,Business,972,1,1,1,1,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +99805,23462,Male,Loyal Customer,49,Business travel,Business,516,3,4,3,3,5,5,1,4,4,4,4,3,4,3,0,0.0,satisfied +99806,3674,Male,disloyal Customer,33,Business travel,Business,427,2,2,2,4,4,2,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +99807,87518,Female,Loyal Customer,9,Personal Travel,Eco,373,2,2,2,4,2,2,4,2,2,2,4,3,3,2,0,0.0,neutral or dissatisfied +99808,25307,Female,Loyal Customer,51,Business travel,Business,2997,1,1,1,1,5,2,1,4,4,4,4,1,4,5,0,0.0,satisfied +99809,25196,Female,Loyal Customer,24,Business travel,Eco Plus,577,5,3,3,3,5,4,5,5,2,4,1,1,4,5,11,1.0,satisfied +99810,22011,Female,Loyal Customer,23,Personal Travel,Eco,551,3,2,3,3,4,3,4,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +99811,34565,Male,Loyal Customer,35,Business travel,Eco,1598,3,2,2,2,3,3,3,3,3,5,4,3,3,3,101,122.0,satisfied +99812,83041,Male,Loyal Customer,29,Business travel,Eco,1127,1,3,3,3,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +99813,49822,Female,Loyal Customer,38,Business travel,Business,3982,2,5,5,5,2,3,2,1,1,1,2,1,1,1,9,12.0,neutral or dissatisfied +99814,106022,Male,Loyal Customer,35,Business travel,Business,2658,1,1,1,1,2,5,4,4,4,4,4,5,4,3,29,,satisfied +99815,66099,Male,Loyal Customer,11,Business travel,Business,583,5,4,5,5,5,5,5,5,5,2,4,5,5,5,7,3.0,satisfied +99816,32125,Male,Loyal Customer,48,Business travel,Eco,101,4,5,5,5,4,4,4,4,4,2,1,2,1,4,0,0.0,satisfied +99817,121103,Male,Loyal Customer,31,Business travel,Business,2402,5,5,5,5,5,5,5,5,4,4,3,5,4,5,0,0.0,satisfied +99818,110281,Female,Loyal Customer,62,Personal Travel,Business,663,4,5,4,3,3,2,4,4,4,4,4,4,4,5,29,25.0,neutral or dissatisfied +99819,34964,Male,disloyal Customer,37,Business travel,Business,273,3,3,3,5,5,3,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +99820,59539,Male,Loyal Customer,45,Business travel,Business,861,2,2,3,2,5,5,4,5,5,5,5,5,5,4,17,6.0,satisfied +99821,115688,Male,disloyal Customer,33,Business travel,Business,362,4,4,4,3,3,4,3,3,1,3,3,3,3,3,27,22.0,neutral or dissatisfied +99822,84120,Female,disloyal Customer,27,Business travel,Eco,1388,1,1,1,3,1,1,1,1,4,4,3,3,3,1,0,12.0,neutral or dissatisfied +99823,63483,Male,Loyal Customer,22,Personal Travel,Eco Plus,337,1,4,1,2,1,1,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +99824,41155,Male,Loyal Customer,15,Personal Travel,Eco,295,4,4,4,1,4,4,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +99825,65324,Male,Loyal Customer,40,Business travel,Business,631,1,1,2,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +99826,129005,Female,Loyal Customer,40,Business travel,Business,2704,3,3,3,3,3,3,3,5,2,4,5,3,4,3,17,0.0,satisfied +99827,1728,Female,Loyal Customer,55,Business travel,Business,1983,5,5,5,5,4,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +99828,12673,Female,Loyal Customer,45,Business travel,Business,3314,5,5,5,5,3,2,5,5,5,5,5,2,5,5,47,29.0,satisfied +99829,54067,Male,Loyal Customer,54,Business travel,Business,1416,5,5,5,5,2,1,1,4,4,4,4,1,4,1,4,0.0,satisfied +99830,37407,Female,Loyal Customer,28,Business travel,Business,3581,1,3,3,3,1,1,1,1,1,5,4,3,3,1,0,0.0,neutral or dissatisfied +99831,60557,Male,Loyal Customer,40,Business travel,Eco Plus,934,1,2,2,2,1,1,1,1,3,5,4,2,3,1,0,0.0,neutral or dissatisfied +99832,95201,Female,Loyal Customer,51,Personal Travel,Eco,189,3,4,0,1,4,5,4,1,1,0,1,4,1,3,0,0.0,neutral or dissatisfied +99833,13586,Male,Loyal Customer,62,Personal Travel,Eco,227,2,5,0,3,4,0,1,4,3,1,1,3,3,4,0,0.0,neutral or dissatisfied +99834,115861,Female,Loyal Customer,37,Business travel,Eco,373,5,1,1,1,5,5,5,5,5,4,1,5,1,5,36,37.0,satisfied +99835,38435,Female,Loyal Customer,30,Business travel,Business,2277,5,5,5,5,4,4,4,4,2,5,5,1,5,4,18,2.0,satisfied +99836,81017,Male,Loyal Customer,42,Business travel,Business,3309,4,3,3,3,4,3,3,4,4,4,4,1,4,3,62,60.0,neutral or dissatisfied +99837,122653,Male,disloyal Customer,42,Business travel,Business,361,5,5,5,3,2,5,2,2,3,3,4,5,5,2,0,0.0,satisfied +99838,72768,Male,Loyal Customer,49,Business travel,Business,1045,4,4,4,4,4,5,4,4,4,5,4,4,4,3,3,0.0,satisfied +99839,30051,Male,Loyal Customer,47,Business travel,Business,1632,0,0,0,3,4,5,4,3,3,3,3,2,3,3,0,0.0,satisfied +99840,24546,Female,Loyal Customer,33,Business travel,Eco,696,0,0,0,3,4,0,4,4,2,3,5,2,3,4,2,1.0,satisfied +99841,67711,Male,Loyal Customer,47,Business travel,Eco,1126,3,4,4,4,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +99842,107879,Female,Loyal Customer,56,Personal Travel,Eco,228,3,4,3,1,5,5,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +99843,39559,Male,disloyal Customer,40,Business travel,Eco,954,2,2,2,3,1,2,1,1,3,1,1,4,4,1,0,0.0,neutral or dissatisfied +99844,75985,Male,Loyal Customer,38,Personal Travel,Eco,297,4,2,4,4,5,4,5,5,3,4,3,4,3,5,0,0.0,satisfied +99845,85203,Female,disloyal Customer,36,Business travel,Business,874,4,4,4,2,3,4,3,3,4,4,5,3,4,3,0,2.0,neutral or dissatisfied +99846,68558,Male,Loyal Customer,59,Personal Travel,Eco,2136,3,4,3,1,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +99847,25730,Male,Loyal Customer,9,Personal Travel,Eco,447,4,4,4,3,4,4,4,4,4,3,3,3,3,4,0,0.0,neutral or dissatisfied +99848,2128,Female,disloyal Customer,21,Business travel,Eco,404,4,4,4,5,5,4,5,5,5,2,4,4,5,5,0,0.0,satisfied +99849,85715,Male,Loyal Customer,44,Personal Travel,Eco Plus,1547,4,5,4,2,3,4,5,3,4,3,3,4,4,3,27,41.0,neutral or dissatisfied +99850,29068,Female,Loyal Customer,9,Personal Travel,Eco,954,3,4,4,3,4,4,4,4,4,3,4,5,4,4,72,67.0,neutral or dissatisfied +99851,46084,Female,disloyal Customer,29,Business travel,Eco,541,2,3,2,3,5,2,5,5,4,3,3,2,3,5,31,28.0,neutral or dissatisfied +99852,35808,Female,Loyal Customer,48,Business travel,Eco,937,5,4,4,4,1,2,1,5,5,5,5,3,5,2,0,0.0,satisfied +99853,40564,Female,Loyal Customer,25,Business travel,Business,3656,4,4,4,4,3,3,3,3,1,1,4,1,5,3,0,0.0,satisfied +99854,1100,Female,Loyal Customer,28,Personal Travel,Eco,282,2,4,2,5,5,2,5,5,4,1,2,4,1,5,0,0.0,neutral or dissatisfied +99855,62220,Male,Loyal Customer,21,Personal Travel,Eco,2425,4,5,4,2,5,4,4,5,3,1,3,2,1,5,0,0.0,neutral or dissatisfied +99856,5565,Female,Loyal Customer,48,Business travel,Business,2668,4,4,4,4,4,4,4,2,2,2,4,2,2,1,33,39.0,neutral or dissatisfied +99857,89622,Female,Loyal Customer,43,Business travel,Business,1076,3,3,3,3,2,5,4,3,3,2,3,4,3,4,50,31.0,satisfied +99858,77357,Male,disloyal Customer,27,Business travel,Business,626,0,0,0,3,3,0,3,3,3,2,5,4,5,3,0,0.0,satisfied +99859,60761,Male,Loyal Customer,9,Business travel,Business,804,3,1,1,1,3,3,3,3,3,4,3,3,3,3,11,17.0,neutral or dissatisfied +99860,32647,Male,disloyal Customer,27,Business travel,Business,216,2,2,2,4,2,2,2,2,1,5,3,1,3,2,9,10.0,neutral or dissatisfied +99861,14232,Male,Loyal Customer,70,Personal Travel,Eco Plus,692,2,4,2,3,4,2,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +99862,64779,Male,Loyal Customer,60,Business travel,Business,551,1,1,4,1,2,4,4,3,3,3,3,5,3,5,17,0.0,satisfied +99863,5277,Male,Loyal Customer,23,Personal Travel,Eco,383,2,5,2,1,3,2,3,3,2,2,2,5,5,3,0,0.0,neutral or dissatisfied +99864,38770,Male,Loyal Customer,48,Business travel,Eco,387,3,5,5,5,3,3,3,3,1,2,3,1,1,3,0,0.0,neutral or dissatisfied +99865,94280,Male,disloyal Customer,16,Business travel,Business,496,5,4,5,4,5,5,5,5,3,4,4,4,5,5,1,0.0,satisfied +99866,22658,Male,Loyal Customer,25,Personal Travel,Eco Plus,250,3,5,0,1,1,0,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +99867,127537,Female,disloyal Customer,46,Business travel,Business,1009,3,3,3,1,5,3,3,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +99868,88355,Male,disloyal Customer,11,Business travel,Eco,581,2,1,2,3,5,2,5,5,3,4,4,2,4,5,2,9.0,neutral or dissatisfied +99869,102841,Female,Loyal Customer,39,Business travel,Business,3926,3,3,3,3,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +99870,53110,Female,Loyal Customer,39,Business travel,Business,2065,3,3,3,3,4,4,4,5,5,5,4,4,5,4,281,243.0,satisfied +99871,51630,Female,Loyal Customer,53,Business travel,Business,3226,4,4,4,4,3,1,4,5,5,5,5,3,5,1,0,0.0,satisfied +99872,108190,Male,Loyal Customer,27,Business travel,Eco Plus,997,3,4,4,4,3,3,3,3,3,5,4,2,4,3,43,29.0,neutral or dissatisfied +99873,107782,Female,Loyal Customer,31,Business travel,Business,666,4,4,4,4,2,2,2,2,4,3,4,4,4,2,7,27.0,satisfied +99874,61548,Female,disloyal Customer,44,Business travel,Business,2288,2,2,2,1,5,2,5,5,3,5,5,3,4,5,1,0.0,neutral or dissatisfied +99875,38470,Male,Loyal Customer,24,Business travel,Business,846,3,3,3,3,4,4,4,4,4,3,4,5,2,4,0,0.0,satisfied +99876,78363,Male,disloyal Customer,22,Business travel,Eco,980,3,3,3,5,4,3,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +99877,104133,Female,Loyal Customer,43,Business travel,Business,3076,3,3,5,3,4,4,4,5,5,5,5,5,5,5,9,0.0,satisfied +99878,27554,Female,Loyal Customer,24,Personal Travel,Eco,697,1,4,1,4,4,1,4,4,4,4,3,4,3,4,1,9.0,neutral or dissatisfied +99879,99275,Female,Loyal Customer,45,Business travel,Business,833,2,2,2,2,3,4,5,4,4,4,4,4,4,4,12,12.0,satisfied +99880,40079,Female,Loyal Customer,26,Personal Travel,Eco,493,0,1,0,3,3,0,1,3,3,2,4,1,3,3,0,0.0,satisfied +99881,78740,Female,Loyal Customer,52,Business travel,Business,1651,4,4,4,4,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +99882,18785,Female,Loyal Customer,53,Business travel,Business,448,4,4,4,4,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +99883,127498,Female,Loyal Customer,70,Personal Travel,Eco,2075,4,4,5,3,5,3,4,2,2,5,2,4,2,1,0,0.0,satisfied +99884,83001,Female,Loyal Customer,40,Business travel,Business,1084,2,3,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +99885,48527,Female,disloyal Customer,25,Business travel,Eco,850,1,1,1,3,2,1,2,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +99886,14020,Male,Loyal Customer,49,Personal Travel,Eco,182,2,5,0,2,2,0,2,2,4,3,2,3,3,2,0,18.0,neutral or dissatisfied +99887,32840,Male,Loyal Customer,44,Personal Travel,Eco,101,4,4,4,3,3,4,3,3,3,3,4,5,4,3,0,0.0,satisfied +99888,2497,Female,Loyal Customer,14,Personal Travel,Eco,1379,1,5,0,3,1,0,1,1,3,2,3,3,4,1,60,58.0,neutral or dissatisfied +99889,27997,Male,Loyal Customer,45,Business travel,Business,2055,3,3,5,3,3,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +99890,34689,Male,Loyal Customer,50,Business travel,Eco,264,5,5,5,5,5,5,5,5,3,2,1,4,2,5,0,0.0,satisfied +99891,58021,Male,disloyal Customer,61,Personal Travel,Eco,1721,4,3,5,2,4,5,4,4,4,4,1,4,2,4,0,0.0,satisfied +99892,29024,Female,disloyal Customer,37,Business travel,Eco,205,2,4,2,2,2,2,2,2,4,3,5,2,2,2,0,0.0,neutral or dissatisfied +99893,65442,Female,disloyal Customer,50,Business travel,Business,1303,4,4,4,4,5,4,5,5,2,4,4,3,4,5,0,0.0,neutral or dissatisfied +99894,100101,Male,disloyal Customer,42,Business travel,Business,725,3,3,3,4,4,3,4,4,4,5,4,3,4,4,7,11.0,neutral or dissatisfied +99895,5856,Male,Loyal Customer,49,Business travel,Business,3720,5,5,5,5,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +99896,124289,Male,Loyal Customer,35,Business travel,Business,1785,4,1,1,1,3,4,4,4,4,4,4,2,4,3,105,95.0,neutral or dissatisfied +99897,82755,Female,Loyal Customer,56,Business travel,Business,1916,2,1,5,5,2,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +99898,79335,Female,Loyal Customer,40,Business travel,Business,3911,5,5,5,5,4,4,4,3,4,4,4,4,4,4,371,339.0,satisfied +99899,87137,Male,Loyal Customer,26,Business travel,Eco Plus,594,1,2,2,2,1,1,2,1,1,3,3,4,4,1,0,0.0,neutral or dissatisfied +99900,91558,Male,Loyal Customer,54,Personal Travel,Eco,680,2,4,2,3,4,2,4,4,4,5,4,5,5,4,101,127.0,neutral or dissatisfied +99901,59641,Male,Loyal Customer,42,Business travel,Eco,565,5,3,3,3,5,5,5,5,3,4,1,2,5,5,0,0.0,satisfied +99902,72993,Male,Loyal Customer,69,Business travel,Eco,696,3,3,3,3,3,3,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +99903,42807,Male,disloyal Customer,43,Business travel,Eco,710,3,3,3,3,1,3,1,1,4,1,5,4,3,1,0,10.0,neutral or dissatisfied +99904,120557,Female,disloyal Customer,38,Business travel,Eco,676,3,3,3,4,5,3,5,5,2,1,4,2,4,5,3,19.0,neutral or dissatisfied +99905,54175,Male,disloyal Customer,37,Business travel,Eco,1000,2,3,3,2,2,3,2,2,3,2,1,4,5,2,0,0.0,neutral or dissatisfied +99906,48929,Female,Loyal Customer,52,Business travel,Eco,326,5,1,1,1,4,4,2,4,4,5,4,5,4,4,0,0.0,satisfied +99907,90613,Female,Loyal Customer,20,Business travel,Business,2471,1,4,2,2,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +99908,34242,Male,Loyal Customer,33,Personal Travel,Eco Plus,1046,2,4,2,1,2,2,2,2,4,3,4,3,5,2,87,65.0,neutral or dissatisfied +99909,114714,Male,disloyal Customer,37,Business travel,Business,325,5,5,5,3,3,5,3,3,3,5,5,3,5,3,0,0.0,satisfied +99910,58195,Male,disloyal Customer,29,Business travel,Eco,802,1,1,1,2,2,1,2,2,1,4,2,2,2,2,82,76.0,neutral or dissatisfied +99911,99262,Male,Loyal Customer,29,Business travel,Business,2510,2,5,5,5,2,1,2,2,4,2,4,3,3,2,48,34.0,neutral or dissatisfied +99912,118456,Female,disloyal Customer,47,Business travel,Business,451,3,3,3,3,5,3,5,5,5,3,5,4,5,5,4,0.0,neutral or dissatisfied +99913,61940,Male,disloyal Customer,26,Business travel,Business,2052,3,3,3,3,2,3,3,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +99914,7115,Female,Loyal Customer,21,Personal Travel,Eco,157,2,5,2,3,1,2,1,1,3,4,5,4,5,1,91,109.0,neutral or dissatisfied +99915,104803,Male,Loyal Customer,20,Personal Travel,Eco,787,3,5,3,2,5,3,5,5,2,4,3,5,2,5,4,19.0,neutral or dissatisfied +99916,104037,Male,Loyal Customer,53,Business travel,Eco,1262,2,4,4,4,2,2,2,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +99917,97545,Male,Loyal Customer,65,Personal Travel,Eco,675,2,5,2,3,5,2,5,5,5,5,5,4,5,5,8,0.0,neutral or dissatisfied +99918,17025,Male,Loyal Customer,19,Personal Travel,Eco,781,4,4,4,3,5,4,5,5,3,3,5,3,4,5,0,20.0,neutral or dissatisfied +99919,66591,Male,Loyal Customer,46,Business travel,Business,761,4,4,4,4,2,4,5,4,4,4,4,5,4,3,7,0.0,satisfied +99920,52271,Female,Loyal Customer,16,Business travel,Business,370,1,4,4,4,1,1,1,1,1,5,4,3,4,1,54,72.0,neutral or dissatisfied +99921,60856,Male,Loyal Customer,59,Business travel,Business,1491,3,3,3,3,2,4,5,4,4,5,4,5,4,3,20,0.0,satisfied +99922,52164,Female,disloyal Customer,58,Business travel,Eco,261,2,0,2,1,4,2,4,4,2,5,1,4,4,4,0,0.0,neutral or dissatisfied +99923,14317,Female,Loyal Customer,21,Business travel,Business,2260,2,2,2,2,2,2,2,2,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +99924,9469,Male,disloyal Customer,66,Business travel,Business,368,2,1,1,3,2,2,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +99925,38400,Male,Loyal Customer,44,Business travel,Eco,1754,5,5,2,5,5,5,5,5,4,2,3,4,5,5,0,0.0,satisfied +99926,79190,Male,Loyal Customer,51,Business travel,Business,1990,3,3,3,3,5,5,5,5,3,3,5,5,3,5,157,160.0,satisfied +99927,96596,Female,Loyal Customer,23,Personal Travel,Eco,861,3,4,3,4,2,3,2,2,4,4,5,3,4,2,2,6.0,neutral or dissatisfied +99928,124723,Female,Loyal Customer,43,Personal Travel,Eco,399,3,4,3,2,3,4,4,4,4,3,4,3,4,3,0,6.0,neutral or dissatisfied +99929,92987,Female,disloyal Customer,19,Business travel,Business,738,5,3,5,2,3,5,3,3,5,3,4,5,5,3,0,0.0,satisfied +99930,114137,Male,disloyal Customer,30,Business travel,Business,862,3,3,3,3,5,3,5,5,4,5,4,4,5,5,4,2.0,neutral or dissatisfied +99931,22371,Female,Loyal Customer,33,Business travel,Eco,83,0,0,0,3,4,0,4,4,4,1,2,1,4,4,0,0.0,satisfied +99932,110122,Male,Loyal Customer,23,Business travel,Business,1948,3,3,3,3,4,4,4,4,4,5,4,4,4,4,1,8.0,satisfied +99933,1202,Male,Loyal Customer,25,Personal Travel,Eco,113,3,3,3,1,3,3,3,3,5,4,2,1,2,3,0,0.0,neutral or dissatisfied +99934,4701,Male,Loyal Customer,18,Personal Travel,Eco,327,4,0,4,1,1,4,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +99935,50768,Female,Loyal Customer,14,Personal Travel,Eco,77,3,4,0,4,5,0,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +99936,97734,Female,Loyal Customer,45,Business travel,Eco,787,3,2,2,2,4,4,3,3,3,3,3,3,3,4,19,45.0,neutral or dissatisfied +99937,40589,Male,disloyal Customer,22,Business travel,Eco,391,2,3,2,4,2,2,2,2,2,5,3,1,4,2,5,10.0,neutral or dissatisfied +99938,117332,Male,Loyal Customer,47,Business travel,Business,296,1,1,1,1,4,5,5,4,4,4,4,4,4,4,4,0.0,satisfied +99939,44158,Male,Loyal Customer,53,Business travel,Eco,229,4,5,5,5,4,4,4,4,4,3,5,4,1,4,0,0.0,satisfied +99940,125603,Male,Loyal Customer,40,Personal Travel,Eco,1587,4,4,4,3,2,4,2,2,3,5,4,3,4,2,55,68.0,satisfied +99941,75228,Male,disloyal Customer,17,Business travel,Eco,1723,3,3,3,4,3,1,1,2,2,4,4,1,2,1,188,175.0,neutral or dissatisfied +99942,90690,Female,Loyal Customer,49,Business travel,Business,3162,5,1,5,5,5,4,5,3,3,2,3,5,3,3,0,0.0,satisfied +99943,13946,Male,Loyal Customer,41,Business travel,Eco,153,5,4,4,4,5,5,5,5,2,2,2,3,2,5,0,0.0,satisfied +99944,91080,Male,Loyal Customer,66,Personal Travel,Eco,581,3,5,3,3,4,3,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +99945,107436,Male,Loyal Customer,49,Personal Travel,Eco,468,2,4,2,3,2,2,3,2,3,2,5,4,4,2,40,30.0,neutral or dissatisfied +99946,121733,Male,Loyal Customer,48,Business travel,Business,1075,4,4,4,4,5,3,5,5,5,5,5,2,5,3,0,0.0,satisfied +99947,117170,Male,Loyal Customer,10,Personal Travel,Eco,370,4,1,4,4,4,4,4,4,4,2,3,4,4,4,3,0.0,neutral or dissatisfied +99948,80132,Female,disloyal Customer,35,Business travel,Business,2586,2,2,2,4,2,2,3,5,3,4,5,3,5,3,39,14.0,neutral or dissatisfied +99949,71872,Male,Loyal Customer,49,Personal Travel,Eco,1723,2,5,2,4,3,2,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +99950,129562,Female,Loyal Customer,24,Personal Travel,Eco,2583,4,3,4,3,5,4,5,5,3,5,3,2,2,5,0,0.0,neutral or dissatisfied +99951,49209,Male,Loyal Customer,43,Business travel,Business,3267,3,3,4,3,2,3,5,5,5,5,5,5,5,3,0,2.0,satisfied +99952,91680,Male,Loyal Customer,17,Business travel,Business,1843,1,1,1,1,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +99953,14796,Male,Loyal Customer,41,Business travel,Eco,95,5,3,3,3,5,5,5,5,2,5,3,2,3,5,38,17.0,satisfied +99954,119647,Male,Loyal Customer,34,Business travel,Business,1868,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +99955,109407,Female,disloyal Customer,24,Business travel,Business,951,5,0,5,3,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +99956,296,Female,Loyal Customer,47,Business travel,Business,2262,3,4,4,4,5,4,3,3,3,3,3,2,3,3,0,8.0,neutral or dissatisfied +99957,50375,Male,Loyal Customer,44,Business travel,Business,3720,4,4,4,4,2,1,5,5,5,5,5,1,5,4,0,0.0,satisfied +99958,101336,Male,disloyal Customer,30,Business travel,Eco,1321,4,4,4,3,5,4,5,5,2,5,1,1,3,5,0,0.0,neutral or dissatisfied +99959,7942,Female,disloyal Customer,26,Business travel,Business,594,3,5,3,2,2,3,2,2,3,5,4,4,5,2,29,25.0,neutral or dissatisfied +99960,33836,Male,disloyal Customer,29,Business travel,Eco,1562,3,3,3,4,3,3,3,3,2,2,5,4,4,3,0,0.0,neutral or dissatisfied +99961,51290,Female,Loyal Customer,69,Business travel,Eco Plus,109,4,2,4,4,2,2,1,4,4,4,4,2,4,1,0,0.0,satisfied +99962,70892,Female,disloyal Customer,26,Business travel,Business,1721,4,4,4,3,2,4,2,2,4,2,4,5,5,2,21,44.0,neutral or dissatisfied +99963,126914,Male,Loyal Customer,49,Business travel,Business,3489,2,2,2,2,2,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +99964,87718,Male,disloyal Customer,26,Business travel,Business,606,3,2,2,1,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +99965,113428,Female,Loyal Customer,60,Business travel,Business,2536,5,5,5,5,4,5,5,5,5,5,4,4,5,5,9,5.0,satisfied +99966,3675,Male,disloyal Customer,20,Business travel,Eco,427,4,2,4,4,4,4,4,4,2,1,4,3,4,4,0,0.0,neutral or dissatisfied +99967,51324,Male,Loyal Customer,23,Business travel,Eco Plus,421,4,2,2,2,4,4,1,4,2,5,4,1,3,4,0,0.0,neutral or dissatisfied +99968,4785,Male,Loyal Customer,38,Business travel,Eco,403,5,4,4,4,5,5,5,5,2,1,4,5,1,5,0,0.0,satisfied +99969,107322,Female,Loyal Customer,56,Business travel,Business,584,3,1,4,1,4,4,3,3,3,3,3,2,3,4,11,0.0,neutral or dissatisfied +99970,1550,Female,Loyal Customer,61,Personal Travel,Eco,862,2,3,2,1,1,2,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +99971,73448,Female,Loyal Customer,39,Personal Travel,Eco,1197,1,5,1,3,4,1,3,4,4,2,5,4,4,4,0,11.0,neutral or dissatisfied +99972,34532,Male,Loyal Customer,29,Business travel,Business,636,2,2,2,2,5,5,5,5,3,2,5,2,1,5,0,0.0,satisfied +99973,30535,Male,Loyal Customer,57,Personal Travel,Eco,683,4,4,4,3,2,4,2,2,3,4,4,3,4,2,0,2.0,neutral or dissatisfied +99974,113971,Female,Loyal Customer,47,Business travel,Business,1728,3,3,3,3,2,3,4,3,3,2,3,4,3,4,1,43.0,satisfied +99975,47933,Male,Loyal Customer,52,Personal Travel,Eco,834,2,5,2,2,5,2,5,5,3,3,4,4,5,5,89,97.0,neutral or dissatisfied +99976,105859,Female,Loyal Customer,60,Business travel,Business,925,1,1,1,1,4,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +99977,32024,Male,Loyal Customer,36,Business travel,Business,101,2,2,2,2,1,2,2,4,4,4,3,3,4,1,9,19.0,satisfied +99978,31855,Female,Loyal Customer,36,Personal Travel,Eco,2640,1,1,2,2,1,2,1,1,2,4,3,2,2,1,0,0.0,neutral or dissatisfied +99979,41640,Female,Loyal Customer,22,Personal Travel,Business,936,4,3,4,4,2,4,2,2,5,2,4,2,3,2,10,5.0,satisfied +99980,37046,Female,Loyal Customer,66,Personal Travel,Eco,994,3,1,3,3,2,4,4,1,1,3,1,1,1,3,0,0.0,neutral or dissatisfied +99981,23834,Male,Loyal Customer,53,Business travel,Eco,715,5,2,5,2,5,5,5,5,2,4,2,1,3,5,0,0.0,satisfied +99982,93258,Female,Loyal Customer,58,Business travel,Business,806,1,1,1,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +99983,89787,Male,Loyal Customer,62,Personal Travel,Eco,1005,3,4,2,3,2,2,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +99984,22413,Male,Loyal Customer,72,Business travel,Business,2794,4,4,4,4,5,4,2,5,5,5,3,4,5,4,0,0.0,satisfied +99985,64594,Male,Loyal Customer,60,Business travel,Business,247,0,1,1,2,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +99986,127425,Male,Loyal Customer,35,Personal Travel,Eco,868,3,2,3,2,2,3,5,2,2,5,2,4,3,2,0,0.0,neutral or dissatisfied +99987,8922,Male,Loyal Customer,45,Personal Travel,Eco,661,4,1,4,4,2,4,2,2,3,3,4,3,4,2,0,0.0,satisfied +99988,9016,Male,disloyal Customer,39,Business travel,Business,160,3,3,3,2,5,3,5,5,5,5,5,3,4,5,4,2.0,neutral or dissatisfied +99989,27524,Male,Loyal Customer,57,Personal Travel,Eco,954,1,2,1,3,1,1,1,1,4,2,4,2,4,1,3,13.0,neutral or dissatisfied +99990,46973,Female,Loyal Customer,38,Personal Travel,Eco,916,1,3,1,3,5,1,5,5,2,4,4,1,4,5,0,0.0,neutral or dissatisfied +99991,45939,Male,Loyal Customer,70,Personal Travel,Eco,563,1,5,1,2,1,1,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +99992,70570,Male,Loyal Customer,35,Personal Travel,Eco,1258,3,5,3,3,3,3,3,3,4,2,4,3,5,3,0,14.0,neutral or dissatisfied +99993,66378,Male,Loyal Customer,48,Business travel,Business,1562,3,3,1,3,3,5,5,5,5,5,5,5,5,5,50,59.0,satisfied +99994,118939,Female,disloyal Customer,27,Business travel,Business,1618,5,5,5,3,4,5,4,4,3,3,5,4,4,4,0,0.0,satisfied +99995,12942,Male,Loyal Customer,8,Personal Travel,Eco,563,3,5,3,4,1,3,4,1,5,4,5,5,4,1,35,21.0,neutral or dissatisfied +99996,47237,Male,Loyal Customer,61,Personal Travel,Eco Plus,945,1,1,1,4,3,1,3,3,3,3,4,1,4,3,40,46.0,neutral or dissatisfied +99997,41508,Male,Loyal Customer,43,Business travel,Business,1464,3,3,4,3,3,1,1,5,5,5,5,4,5,3,0,0.0,satisfied +99998,107935,Female,disloyal Customer,22,Business travel,Business,611,4,2,4,3,3,4,2,3,2,5,4,1,3,3,15,6.0,neutral or dissatisfied +99999,123143,Male,Loyal Customer,41,Business travel,Business,590,2,4,4,4,4,4,4,2,2,2,2,1,2,2,4,15.0,neutral or dissatisfied +100000,59215,Female,Loyal Customer,56,Personal Travel,Eco,1440,2,5,2,3,4,3,4,2,2,2,2,3,2,5,12,20.0,neutral or dissatisfied +100001,129565,Female,Loyal Customer,48,Personal Travel,Eco,2583,1,5,1,2,2,3,2,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +100002,102003,Male,Loyal Customer,40,Business travel,Business,3352,2,2,2,2,2,4,5,4,4,4,4,3,4,3,2,1.0,satisfied +100003,44475,Female,Loyal Customer,13,Personal Travel,Business,589,1,5,1,4,3,1,3,3,3,1,1,1,3,3,23,19.0,neutral or dissatisfied +100004,8974,Female,Loyal Customer,31,Business travel,Business,725,2,2,2,2,5,5,5,5,5,2,5,4,4,5,0,0.0,satisfied +100005,31800,Female,Loyal Customer,34,Business travel,Eco Plus,2640,4,2,2,2,4,4,4,3,4,3,5,4,3,4,0,12.0,satisfied +100006,60991,Male,Loyal Customer,70,Personal Travel,Eco Plus,888,2,1,2,3,3,2,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +100007,80760,Female,disloyal Customer,41,Business travel,Business,629,1,1,1,2,3,1,3,3,3,3,4,4,4,3,0,12.0,neutral or dissatisfied +100008,67199,Male,Loyal Customer,57,Personal Travel,Eco,1102,1,4,1,1,2,1,2,2,5,3,1,1,4,2,0,0.0,neutral or dissatisfied +100009,8562,Female,Loyal Customer,37,Business travel,Business,109,3,3,3,3,3,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +100010,66994,Female,Loyal Customer,53,Business travel,Business,1119,3,1,1,1,1,3,3,3,3,3,3,2,3,4,0,10.0,neutral or dissatisfied +100011,12732,Male,Loyal Customer,20,Personal Travel,Eco,689,2,4,2,2,3,2,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +100012,120023,Male,Loyal Customer,45,Personal Travel,Eco,328,3,0,3,1,5,3,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +100013,61758,Female,Loyal Customer,27,Personal Travel,Eco,1346,2,5,2,3,2,2,2,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +100014,98041,Female,Loyal Customer,43,Business travel,Business,1751,4,4,4,4,4,4,5,3,3,4,3,3,3,5,13,15.0,satisfied +100015,22454,Female,Loyal Customer,23,Personal Travel,Eco,208,3,2,3,4,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +100016,39377,Male,Loyal Customer,47,Business travel,Eco,521,2,1,1,1,2,2,2,2,4,4,5,3,2,2,0,0.0,satisfied +100017,124252,Male,Loyal Customer,38,Personal Travel,Eco,1916,3,5,3,1,4,3,4,4,5,2,5,3,5,4,3,0.0,neutral or dissatisfied +100018,117506,Female,Loyal Customer,22,Personal Travel,Eco,507,2,2,2,3,4,2,4,4,1,2,4,1,4,4,3,0.0,neutral or dissatisfied +100019,74420,Male,Loyal Customer,51,Business travel,Business,1438,4,4,5,4,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +100020,102847,Male,Loyal Customer,65,Business travel,Business,1561,4,2,2,2,3,4,4,4,4,4,4,1,4,1,2,8.0,neutral or dissatisfied +100021,110606,Male,disloyal Customer,24,Business travel,Eco Plus,488,1,2,0,3,3,0,2,3,2,5,3,4,3,3,3,0.0,neutral or dissatisfied +100022,119731,Female,disloyal Customer,54,Business travel,Eco,925,1,2,2,3,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +100023,19923,Female,disloyal Customer,23,Business travel,Eco,240,1,2,1,4,1,1,1,1,4,2,3,3,3,1,76,77.0,neutral or dissatisfied +100024,59699,Female,Loyal Customer,35,Personal Travel,Eco,861,2,5,2,3,2,2,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +100025,83644,Male,Loyal Customer,28,Personal Travel,Business,577,3,4,3,3,1,3,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +100026,103249,Male,Loyal Customer,50,Business travel,Business,667,4,4,4,4,5,4,5,2,2,2,2,3,2,5,14,4.0,satisfied +100027,8674,Male,Loyal Customer,48,Business travel,Business,227,1,1,1,1,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +100028,102494,Female,Loyal Customer,50,Personal Travel,Eco,386,3,4,3,2,2,5,4,5,5,3,5,5,5,4,9,4.0,neutral or dissatisfied +100029,98216,Male,Loyal Customer,56,Business travel,Business,842,2,2,2,2,4,5,4,3,3,4,3,4,3,3,0,2.0,satisfied +100030,126188,Female,Loyal Customer,19,Business travel,Business,328,3,1,1,1,3,3,3,3,1,1,4,3,4,3,16,8.0,neutral or dissatisfied +100031,30041,Male,Loyal Customer,54,Business travel,Eco,213,2,4,4,4,2,2,2,4,5,4,3,2,2,2,172,168.0,neutral or dissatisfied +100032,56479,Female,disloyal Customer,33,Business travel,Business,4963,2,2,2,1,2,3,3,3,4,5,5,3,4,3,75,171.0,neutral or dissatisfied +100033,40686,Male,disloyal Customer,30,Business travel,Eco,588,1,4,1,3,2,1,1,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +100034,108733,Female,Loyal Customer,62,Personal Travel,Eco,591,3,4,3,3,3,5,5,1,1,3,1,3,1,5,50,62.0,neutral or dissatisfied +100035,62237,Female,Loyal Customer,7,Personal Travel,Eco,2565,3,4,3,1,3,3,3,3,5,1,2,3,4,3,0,0.0,neutral or dissatisfied +100036,34024,Female,Loyal Customer,10,Personal Travel,Eco,1617,4,5,4,3,4,4,4,4,3,4,4,4,5,4,12,14.0,neutral or dissatisfied +100037,22986,Female,Loyal Customer,49,Personal Travel,Eco,817,3,4,3,4,4,2,4,3,3,3,3,4,3,4,2,0.0,neutral or dissatisfied +100038,121484,Female,Loyal Customer,9,Personal Travel,Eco,257,2,1,2,4,3,2,3,3,3,1,4,1,3,3,0,0.0,neutral or dissatisfied +100039,3082,Female,Loyal Customer,50,Business travel,Business,1761,5,5,5,5,4,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +100040,23106,Female,Loyal Customer,35,Business travel,Business,3418,2,2,2,2,2,3,5,5,5,5,5,4,5,2,0,0.0,satisfied +100041,86765,Male,Loyal Customer,58,Business travel,Business,2742,1,1,1,1,2,4,4,5,5,5,5,4,5,3,88,96.0,satisfied +100042,51734,Male,Loyal Customer,9,Personal Travel,Eco,425,3,2,3,4,3,3,3,3,2,2,2,2,3,3,0,0.0,neutral or dissatisfied +100043,58679,Female,Loyal Customer,14,Personal Travel,Eco Plus,622,2,4,3,3,3,3,3,3,5,5,5,3,4,3,144,147.0,neutral or dissatisfied +100044,86907,Female,Loyal Customer,39,Business travel,Business,341,3,3,3,3,5,4,5,5,5,5,5,5,5,3,5,7.0,satisfied +100045,28212,Male,Loyal Customer,51,Personal Travel,Eco,859,1,5,1,1,1,1,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +100046,96289,Male,Loyal Customer,33,Personal Travel,Eco,460,2,5,2,5,1,2,1,1,3,3,5,3,5,1,19,8.0,neutral or dissatisfied +100047,124619,Female,Loyal Customer,23,Business travel,Eco,1671,1,5,5,5,1,1,1,1,2,1,1,3,1,1,1,24.0,neutral or dissatisfied +100048,33053,Female,Loyal Customer,15,Personal Travel,Eco,102,0,5,0,2,3,0,3,3,1,5,2,4,2,3,0,0.0,satisfied +100049,92949,Male,Loyal Customer,23,Personal Travel,Eco,134,1,3,1,2,1,1,1,1,3,5,2,3,3,1,0,0.0,neutral or dissatisfied +100050,3207,Female,Loyal Customer,14,Personal Travel,Eco,585,2,2,2,3,3,2,3,3,3,2,4,4,4,3,3,5.0,neutral or dissatisfied +100051,31544,Female,Loyal Customer,11,Personal Travel,Eco,853,5,4,5,1,2,5,2,2,3,2,5,4,5,2,0,0.0,satisfied +100052,114115,Female,Loyal Customer,34,Business travel,Business,957,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +100053,106491,Female,disloyal Customer,34,Business travel,Business,495,2,2,2,4,2,2,4,2,5,5,5,3,4,2,0,0.0,neutral or dissatisfied +100054,62072,Female,Loyal Customer,47,Personal Travel,Eco,2586,5,4,5,3,5,4,1,4,4,4,4,4,4,5,0,0.0,satisfied +100055,98615,Male,Loyal Customer,55,Business travel,Business,920,4,4,4,4,3,4,4,5,5,5,5,3,5,3,21,76.0,satisfied +100056,124025,Male,Loyal Customer,14,Personal Travel,Eco,184,2,3,0,3,2,0,2,2,2,5,5,3,5,2,0,0.0,neutral or dissatisfied +100057,89131,Female,Loyal Customer,39,Business travel,Eco,1947,4,3,3,3,4,4,4,4,4,4,3,3,2,4,100,80.0,neutral or dissatisfied +100058,116856,Male,Loyal Customer,41,Business travel,Business,451,5,5,4,5,2,5,5,4,4,4,4,4,4,4,3,0.0,satisfied +100059,45653,Female,Loyal Customer,21,Personal Travel,Eco,260,4,1,4,2,1,4,1,1,3,4,1,3,1,1,0,0.0,neutral or dissatisfied +100060,81976,Female,Loyal Customer,23,Business travel,Business,1535,1,1,1,1,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +100061,96585,Female,Loyal Customer,42,Business travel,Business,1840,2,2,2,2,5,4,5,4,4,4,4,5,4,3,20,10.0,satisfied +100062,48519,Female,disloyal Customer,20,Business travel,Eco,844,2,2,2,2,4,2,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +100063,66841,Female,Loyal Customer,24,Business travel,Business,331,4,4,2,4,3,4,3,3,1,3,3,5,3,3,2,0.0,satisfied +100064,20760,Female,Loyal Customer,43,Business travel,Business,1949,5,5,5,5,3,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +100065,75506,Male,Loyal Customer,19,Personal Travel,Eco Plus,2585,2,4,2,5,2,2,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +100066,17012,Female,Loyal Customer,31,Business travel,Business,781,3,3,3,3,3,3,3,4,1,2,5,3,3,3,206,213.0,satisfied +100067,92058,Male,Loyal Customer,56,Business travel,Eco,1576,4,3,3,3,4,4,4,4,1,2,4,3,3,4,0,0.0,neutral or dissatisfied +100068,31103,Male,Loyal Customer,67,Personal Travel,Eco,1014,2,3,2,1,2,4,2,4,1,2,5,2,2,2,223,215.0,neutral or dissatisfied +100069,102319,Female,Loyal Customer,59,Business travel,Business,2463,1,1,4,1,2,5,4,5,5,5,5,3,5,4,59,46.0,satisfied +100070,27116,Female,Loyal Customer,26,Personal Travel,Business,2677,2,1,2,2,2,3,3,1,4,2,2,3,2,3,0,0.0,neutral or dissatisfied +100071,9521,Male,disloyal Customer,48,Business travel,Business,288,4,4,4,3,4,5,5,3,3,4,3,5,3,5,255,255.0,neutral or dissatisfied +100072,45995,Male,Loyal Customer,32,Personal Travel,Eco,483,4,1,4,4,2,4,2,2,2,2,3,3,3,2,35,28.0,neutral or dissatisfied +100073,96483,Male,Loyal Customer,43,Business travel,Business,2122,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +100074,89222,Male,Loyal Customer,16,Personal Travel,Eco,2139,2,4,2,2,1,2,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +100075,40962,Female,Loyal Customer,25,Business travel,Eco,507,5,2,5,2,5,5,5,5,2,3,3,2,4,5,0,4.0,satisfied +100076,11211,Female,Loyal Customer,12,Personal Travel,Eco,429,1,4,1,4,3,1,3,3,1,1,4,1,4,3,9,57.0,neutral or dissatisfied +100077,124657,Female,disloyal Customer,32,Business travel,Business,399,2,2,2,2,1,2,1,1,3,3,4,3,5,1,0,10.0,neutral or dissatisfied +100078,118459,Male,Loyal Customer,46,Business travel,Business,451,1,1,1,1,5,5,4,4,4,5,4,3,4,3,35,28.0,satisfied +100079,37865,Male,disloyal Customer,27,Business travel,Eco,1023,3,4,4,3,4,4,4,4,1,4,5,1,4,4,3,0.0,neutral or dissatisfied +100080,23206,Female,disloyal Customer,25,Business travel,Eco Plus,223,2,3,2,2,3,2,3,3,2,4,1,3,5,3,0,0.0,neutral or dissatisfied +100081,102444,Male,Loyal Customer,36,Personal Travel,Eco,226,2,5,0,2,3,0,3,3,4,2,4,4,4,3,5,1.0,neutral or dissatisfied +100082,100749,Male,Loyal Customer,41,Personal Travel,Eco,328,2,3,1,3,2,1,2,2,1,2,3,1,2,2,9,4.0,neutral or dissatisfied +100083,60723,Female,Loyal Customer,26,Personal Travel,Eco,1605,1,5,0,3,0,5,5,5,3,4,3,5,1,5,196,169.0,neutral or dissatisfied +100084,56593,Male,Loyal Customer,43,Business travel,Eco,997,3,2,5,2,3,3,3,3,3,3,3,4,4,3,9,29.0,neutral or dissatisfied +100085,81223,Female,Loyal Customer,58,Personal Travel,Eco,1426,3,5,3,2,2,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +100086,120962,Male,Loyal Customer,47,Business travel,Business,1646,5,5,5,5,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +100087,11052,Female,Loyal Customer,63,Personal Travel,Eco,429,5,3,5,2,4,2,1,4,4,5,2,1,4,5,26,27.0,satisfied +100088,16279,Male,Loyal Customer,43,Personal Travel,Eco,946,4,3,4,1,1,4,1,1,5,3,1,3,3,1,29,23.0,neutral or dissatisfied +100089,99143,Male,Loyal Customer,37,Business travel,Business,181,2,2,2,2,3,4,5,5,5,5,5,4,5,3,6,0.0,satisfied +100090,50241,Male,Loyal Customer,39,Business travel,Business,86,4,1,1,1,2,4,3,1,1,2,4,2,1,3,20,12.0,neutral or dissatisfied +100091,19544,Female,Loyal Customer,60,Business travel,Eco,108,4,4,4,4,1,3,4,4,4,4,4,3,4,3,2,0.0,satisfied +100092,62954,Female,Loyal Customer,43,Business travel,Business,3683,3,3,3,3,5,5,5,5,4,5,4,5,5,5,202,207.0,satisfied +100093,11541,Female,Loyal Customer,41,Business travel,Business,2945,4,4,4,4,3,5,5,3,3,4,3,3,3,3,0,0.0,satisfied +100094,47395,Female,Loyal Customer,57,Business travel,Business,2146,3,2,2,2,1,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +100095,96898,Male,Loyal Customer,18,Personal Travel,Eco,957,1,4,1,4,4,1,4,4,4,5,5,5,4,4,1,0.0,neutral or dissatisfied +100096,10630,Male,Loyal Customer,30,Business travel,Business,309,3,4,4,4,3,3,3,3,1,3,3,2,3,3,0,0.0,neutral or dissatisfied +100097,98565,Female,Loyal Customer,39,Personal Travel,Business,920,2,4,2,3,2,5,4,2,2,2,1,3,2,5,1,0.0,neutral or dissatisfied +100098,4657,Female,Loyal Customer,49,Business travel,Business,2230,5,5,3,5,5,5,4,4,4,4,4,4,4,3,0,12.0,satisfied +100099,40461,Male,disloyal Customer,37,Business travel,Eco,290,1,3,1,3,1,1,1,1,1,1,4,3,3,1,0,0.0,neutral or dissatisfied +100100,79538,Female,Loyal Customer,41,Business travel,Business,3696,5,5,5,5,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +100101,81337,Male,disloyal Customer,54,Business travel,Eco,1299,1,1,1,3,1,1,1,1,3,1,3,1,4,1,8,3.0,neutral or dissatisfied +100102,28481,Female,Loyal Customer,18,Personal Travel,Eco Plus,1721,3,3,3,3,2,3,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +100103,17637,Female,Loyal Customer,10,Personal Travel,Eco,783,3,5,3,3,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +100104,126202,Female,disloyal Customer,36,Business travel,Eco,650,2,2,3,4,2,3,2,2,2,3,3,1,3,2,70,64.0,neutral or dissatisfied +100105,39178,Male,Loyal Customer,13,Personal Travel,Eco,287,5,2,5,4,2,5,2,2,3,3,4,3,4,2,0,0.0,satisfied +100106,77913,Female,Loyal Customer,59,Business travel,Business,3558,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +100107,116115,Male,Loyal Customer,40,Personal Travel,Eco,447,2,4,2,3,5,2,5,5,5,5,4,3,4,5,14,24.0,neutral or dissatisfied +100108,79725,Male,Loyal Customer,19,Personal Travel,Eco,762,3,5,3,3,2,3,4,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +100109,67517,Male,disloyal Customer,24,Business travel,Business,1464,4,4,4,3,1,4,1,1,5,5,4,4,4,1,11,16.0,satisfied +100110,5961,Female,Loyal Customer,30,Personal Travel,Eco,1250,4,4,4,4,1,4,3,1,5,3,3,3,4,1,0,0.0,neutral or dissatisfied +100111,78718,Female,disloyal Customer,22,Business travel,Business,447,5,0,5,2,3,0,3,3,5,5,5,3,5,3,0,25.0,satisfied +100112,23989,Male,Loyal Customer,20,Business travel,Eco,595,5,1,1,1,5,5,5,5,5,1,3,3,4,5,0,0.0,satisfied +100113,121876,Male,disloyal Customer,24,Business travel,Eco,449,1,3,1,4,3,1,3,3,3,4,3,1,3,3,24,28.0,neutral or dissatisfied +100114,49220,Female,Loyal Customer,55,Business travel,Eco,158,4,5,5,5,2,5,1,4,4,4,4,3,4,5,0,0.0,satisfied +100115,3258,Female,disloyal Customer,24,Business travel,Eco,483,3,2,3,3,3,3,3,3,3,4,3,1,3,3,130,127.0,neutral or dissatisfied +100116,68517,Female,Loyal Customer,60,Business travel,Business,3136,5,3,5,5,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +100117,12091,Female,Loyal Customer,53,Business travel,Business,1034,2,2,2,2,4,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +100118,77351,Female,disloyal Customer,23,Business travel,Eco,588,3,2,3,2,3,3,2,3,1,2,2,3,2,3,2,0.0,neutral or dissatisfied +100119,65712,Female,disloyal Customer,27,Business travel,Eco,1061,3,3,3,4,5,3,5,5,3,3,4,3,4,5,4,13.0,neutral or dissatisfied +100120,18074,Female,Loyal Customer,53,Personal Travel,Eco,488,3,5,3,3,4,5,5,2,2,3,2,5,2,4,0,0.0,neutral or dissatisfied +100121,86875,Male,Loyal Customer,8,Business travel,Eco Plus,692,2,4,4,4,2,2,1,2,3,4,4,1,3,2,8,29.0,neutral or dissatisfied +100122,9751,Female,Loyal Customer,69,Business travel,Business,2642,4,2,4,4,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +100123,44327,Female,Loyal Customer,40,Business travel,Eco,471,5,1,1,1,5,5,5,5,5,1,4,5,1,5,390,362.0,satisfied +100124,84950,Female,Loyal Customer,43,Business travel,Eco Plus,516,1,4,5,4,1,2,3,1,1,1,1,1,1,3,30,25.0,neutral or dissatisfied +100125,106927,Female,Loyal Customer,40,Personal Travel,Eco,1259,1,4,1,4,2,1,2,2,4,4,5,3,5,2,118,98.0,neutral or dissatisfied +100126,62938,Female,Loyal Customer,31,Business travel,Business,3906,2,1,1,1,2,3,2,2,4,2,4,3,4,2,22,38.0,neutral or dissatisfied +100127,69536,Male,disloyal Customer,26,Business travel,Business,2475,1,2,2,1,2,1,1,4,3,5,5,1,3,1,0,6.0,neutral or dissatisfied +100128,59080,Female,Loyal Customer,33,Business travel,Business,1723,4,4,4,4,2,1,4,4,4,4,4,5,4,2,0,0.0,satisfied +100129,113988,Female,Loyal Customer,52,Business travel,Business,1728,3,5,5,5,3,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +100130,110060,Male,Loyal Customer,47,Business travel,Business,1984,4,3,4,4,2,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +100131,12546,Female,Loyal Customer,33,Business travel,Eco,788,4,5,4,5,4,4,4,4,4,1,4,5,4,4,8,0.0,satisfied +100132,12700,Male,Loyal Customer,44,Business travel,Business,3145,1,5,5,5,4,2,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +100133,59267,Female,Loyal Customer,13,Personal Travel,Eco,4963,0,5,0,1,0,1,1,3,4,5,5,1,3,1,3,0.0,satisfied +100134,60550,Male,Loyal Customer,41,Business travel,Business,862,2,2,2,2,5,5,5,5,5,5,5,5,5,4,21,16.0,satisfied +100135,89528,Female,Loyal Customer,28,Business travel,Business,3415,4,4,4,4,3,3,3,3,3,3,5,3,5,3,0,0.0,satisfied +100136,98936,Female,Loyal Customer,34,Business travel,Business,2554,4,1,2,1,5,3,4,4,4,4,4,4,4,4,0,3.0,neutral or dissatisfied +100137,7330,Female,Loyal Customer,43,Business travel,Business,606,4,4,4,4,4,5,5,5,5,5,5,5,5,3,41,40.0,satisfied +100138,44702,Female,Loyal Customer,7,Personal Travel,Eco,67,1,4,1,1,2,1,4,2,4,3,4,5,5,2,7,0.0,neutral or dissatisfied +100139,62775,Female,Loyal Customer,39,Business travel,Business,2556,3,4,4,4,3,3,3,3,5,4,3,3,3,3,14,50.0,neutral or dissatisfied +100140,125264,Male,Loyal Customer,56,Business travel,Business,1488,4,4,4,4,2,4,4,4,4,4,4,4,4,3,73,91.0,satisfied +100141,86984,Male,Loyal Customer,17,Personal Travel,Eco,907,0,5,0,5,4,0,2,4,3,4,4,4,4,4,1,0.0,satisfied +100142,84081,Female,Loyal Customer,23,Personal Travel,Eco,757,5,4,5,2,5,5,5,5,5,3,5,5,5,5,0,0.0,satisfied +100143,19398,Female,Loyal Customer,56,Business travel,Eco,261,4,2,2,2,3,5,2,4,4,4,4,3,4,5,0,0.0,satisfied +100144,64141,Female,Loyal Customer,48,Business travel,Business,989,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +100145,73943,Male,Loyal Customer,39,Business travel,Eco,2218,2,4,4,4,2,2,2,2,1,5,4,4,3,2,0,0.0,neutral or dissatisfied +100146,103142,Male,Loyal Customer,46,Personal Travel,Eco Plus,460,3,4,3,1,5,3,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +100147,59622,Male,Loyal Customer,46,Business travel,Business,861,1,1,1,1,3,5,4,5,5,4,5,3,5,4,3,2.0,satisfied +100148,70001,Male,Loyal Customer,37,Personal Travel,Eco,236,2,4,2,3,4,2,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +100149,25699,Male,disloyal Customer,43,Business travel,Eco,528,2,0,2,1,1,2,1,1,2,1,3,5,3,1,0,0.0,neutral or dissatisfied +100150,126491,Male,Loyal Customer,36,Personal Travel,Eco,1788,1,2,1,4,3,1,3,3,1,2,2,2,4,3,3,0.0,neutral or dissatisfied +100151,110065,Female,Loyal Customer,17,Business travel,Business,3968,4,4,4,4,3,3,3,3,4,2,5,5,4,3,20,9.0,satisfied +100152,72081,Female,Loyal Customer,27,Business travel,Business,2556,3,5,5,5,3,3,3,3,4,1,1,2,2,3,0,0.0,neutral or dissatisfied +100153,42541,Male,Loyal Customer,35,Business travel,Eco,1174,5,3,3,3,5,5,5,5,5,3,5,5,4,5,153,152.0,satisfied +100154,69135,Male,Loyal Customer,33,Personal Travel,Business,2248,1,4,1,4,5,1,5,5,5,3,5,3,5,5,0,9.0,neutral or dissatisfied +100155,35478,Female,Loyal Customer,28,Personal Travel,Eco,1076,2,1,2,3,2,2,2,2,4,2,3,2,3,2,0,3.0,neutral or dissatisfied +100156,1105,Male,Loyal Customer,30,Personal Travel,Eco,102,2,4,2,3,4,2,4,4,3,1,5,5,2,4,0,0.0,neutral or dissatisfied +100157,28322,Male,Loyal Customer,18,Business travel,Business,3282,4,4,3,4,4,4,4,4,1,5,3,3,1,4,0,0.0,satisfied +100158,69478,Male,Loyal Customer,18,Personal Travel,Eco,1096,4,4,4,3,1,4,1,1,3,5,3,3,3,1,0,0.0,satisfied +100159,60588,Female,Loyal Customer,12,Personal Travel,Eco,1290,5,4,5,3,5,5,5,5,3,5,5,5,4,5,0,12.0,satisfied +100160,35627,Male,Loyal Customer,37,Personal Travel,Eco Plus,1028,1,4,2,4,4,2,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +100161,112022,Male,Loyal Customer,64,Business travel,Eco,680,2,1,4,4,2,2,2,2,1,3,3,3,3,2,0,4.0,neutral or dissatisfied +100162,106050,Male,Loyal Customer,70,Personal Travel,Eco,452,1,5,2,2,5,2,5,5,2,2,1,1,4,5,0,5.0,neutral or dissatisfied +100163,125312,Male,Loyal Customer,55,Personal Travel,Eco,678,3,3,3,1,1,3,1,1,3,5,5,3,4,1,17,8.0,neutral or dissatisfied +100164,99693,Male,disloyal Customer,19,Business travel,Eco,442,2,3,2,5,1,2,3,1,3,5,4,3,2,1,2,5.0,neutral or dissatisfied +100165,61129,Male,disloyal Customer,13,Business travel,Eco,853,3,3,3,4,3,3,3,3,4,4,4,2,4,3,0,4.0,neutral or dissatisfied +100166,15073,Male,Loyal Customer,38,Personal Travel,Business,239,4,2,4,3,2,4,4,1,1,4,1,4,1,1,0,0.0,neutral or dissatisfied +100167,48869,Female,Loyal Customer,40,Business travel,Business,3018,3,3,3,3,5,1,3,5,5,5,5,4,5,5,70,72.0,satisfied +100168,75301,Male,Loyal Customer,48,Business travel,Business,2504,4,4,2,4,4,4,4,5,2,5,4,4,3,4,0,12.0,satisfied +100169,119233,Male,Loyal Customer,47,Personal Travel,Eco,331,3,1,3,4,1,3,1,1,3,2,3,1,3,1,0,10.0,neutral or dissatisfied +100170,42527,Male,Loyal Customer,53,Personal Travel,Eco,328,4,1,4,3,1,4,1,1,1,1,4,3,3,1,0,0.0,neutral or dissatisfied +100171,41225,Female,Loyal Customer,63,Personal Travel,Eco,1042,1,4,1,3,3,5,5,1,1,1,1,3,1,5,6,0.0,neutral or dissatisfied +100172,68862,Male,Loyal Customer,41,Business travel,Business,936,3,3,3,3,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +100173,126124,Male,Loyal Customer,39,Business travel,Business,468,3,3,3,3,4,5,4,3,3,3,3,5,3,3,7,5.0,satisfied +100174,20337,Female,Loyal Customer,58,Business travel,Business,323,1,1,3,1,1,3,4,4,4,4,4,4,4,5,52,46.0,satisfied +100175,97571,Female,Loyal Customer,43,Business travel,Eco,448,2,1,5,5,4,4,4,2,2,2,2,4,2,1,1,0.0,neutral or dissatisfied +100176,95007,Female,Loyal Customer,39,Personal Travel,Eco,277,3,1,4,3,5,4,5,5,4,3,4,2,4,5,18,7.0,neutral or dissatisfied +100177,11843,Female,Loyal Customer,56,Personal Travel,Eco Plus,986,2,5,2,3,4,4,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +100178,49513,Female,disloyal Customer,39,Business travel,Business,372,3,3,3,3,5,3,5,5,3,2,4,2,4,5,49,45.0,neutral or dissatisfied +100179,102792,Male,Loyal Customer,15,Personal Travel,Eco,1099,4,0,4,2,4,4,4,4,3,5,5,4,5,4,0,7.0,neutral or dissatisfied +100180,124111,Female,disloyal Customer,23,Business travel,Eco,529,5,0,5,2,3,5,5,3,5,3,4,3,5,3,0,0.0,satisfied +100181,56099,Female,Loyal Customer,42,Business travel,Business,2402,3,3,3,3,4,4,4,4,2,4,4,4,3,4,26,23.0,satisfied +100182,54066,Male,disloyal Customer,39,Business travel,Eco,1416,4,4,4,3,5,4,3,5,4,2,4,2,3,5,24,7.0,neutral or dissatisfied +100183,118158,Female,Loyal Customer,36,Business travel,Business,1444,2,3,1,1,1,3,3,2,2,2,2,3,2,3,1,0.0,neutral or dissatisfied +100184,46148,Male,Loyal Customer,53,Business travel,Eco,516,1,3,3,3,1,1,1,1,4,1,3,4,3,1,21,13.0,neutral or dissatisfied +100185,80333,Female,Loyal Customer,32,Personal Travel,Eco,746,1,1,1,2,3,1,1,3,1,3,2,1,2,3,0,15.0,neutral or dissatisfied +100186,27581,Female,Loyal Customer,26,Personal Travel,Eco,954,3,5,3,2,1,3,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +100187,87338,Male,Loyal Customer,8,Personal Travel,Business,425,1,5,1,3,2,1,2,2,4,1,4,4,1,2,8,0.0,neutral or dissatisfied +100188,125745,Female,Loyal Customer,46,Business travel,Business,1997,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +100189,93416,Female,Loyal Customer,44,Business travel,Business,605,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +100190,120646,Male,disloyal Customer,28,Business travel,Business,280,4,4,4,3,4,4,3,4,5,5,4,4,4,4,0,0.0,satisfied +100191,44431,Female,disloyal Customer,29,Business travel,Eco,542,2,1,1,3,4,1,4,4,3,4,2,3,3,4,26,22.0,neutral or dissatisfied +100192,8241,Female,Loyal Customer,62,Personal Travel,Eco,402,3,4,3,3,4,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +100193,116719,Female,disloyal Customer,30,Business travel,Eco Plus,342,3,4,4,4,4,4,4,4,1,5,2,1,5,4,0,0.0,neutral or dissatisfied +100194,78381,Male,Loyal Customer,22,Business travel,Business,980,4,4,1,4,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +100195,105380,Male,Loyal Customer,39,Business travel,Business,3707,3,4,4,4,5,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +100196,84482,Female,Loyal Customer,52,Business travel,Business,3663,2,5,2,2,4,4,5,4,4,4,4,3,4,2,0,0.0,satisfied +100197,99594,Male,Loyal Customer,24,Personal Travel,Eco,930,4,1,4,4,2,4,2,2,2,2,3,4,3,2,13,13.0,neutral or dissatisfied +100198,125988,Male,Loyal Customer,48,Personal Travel,Business,650,2,2,2,3,5,4,3,2,2,2,2,4,2,4,0,7.0,neutral or dissatisfied +100199,18735,Female,Loyal Customer,42,Business travel,Eco,1167,5,2,2,2,2,2,3,5,5,5,5,4,5,4,49,60.0,satisfied +100200,109816,Male,Loyal Customer,51,Business travel,Business,2808,2,2,2,2,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +100201,18648,Male,Loyal Customer,57,Personal Travel,Eco,192,3,5,3,1,4,3,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +100202,99891,Male,Loyal Customer,60,Business travel,Business,738,1,1,1,1,5,5,5,4,4,4,4,3,4,3,30,26.0,satisfied +100203,27635,Male,Loyal Customer,22,Business travel,Eco Plus,954,0,3,0,4,3,0,3,3,5,4,3,2,1,3,5,8.0,satisfied +100204,104603,Female,Loyal Customer,26,Personal Travel,Eco,369,1,3,1,3,2,1,2,2,1,4,3,4,4,2,0,0.0,neutral or dissatisfied +100205,77438,Male,Loyal Customer,55,Business travel,Business,2018,4,4,4,4,3,4,5,1,1,2,1,5,1,3,0,0.0,satisfied +100206,90715,Female,disloyal Customer,24,Business travel,Eco,271,4,0,4,3,3,4,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +100207,38357,Female,Loyal Customer,58,Business travel,Business,3782,1,2,2,2,1,3,3,1,1,2,1,3,1,2,0,8.0,neutral or dissatisfied +100208,14358,Female,Loyal Customer,39,Business travel,Eco Plus,429,3,3,3,3,3,2,3,3,2,5,3,2,3,3,28,62.0,neutral or dissatisfied +100209,76026,Female,Loyal Customer,37,Business travel,Business,1502,0,0,0,3,1,2,5,3,3,3,5,5,3,1,5,0.0,satisfied +100210,74132,Male,Loyal Customer,28,Business travel,Eco,641,3,2,2,2,3,3,3,3,4,4,4,3,3,3,17,12.0,neutral or dissatisfied +100211,49046,Female,disloyal Customer,21,Business travel,Eco,421,3,5,3,2,2,3,5,2,4,5,2,2,3,2,0,0.0,neutral or dissatisfied +100212,82608,Male,Loyal Customer,41,Business travel,Eco,128,4,3,3,3,3,4,3,3,3,4,1,2,3,3,0,3.0,satisfied +100213,10598,Female,Loyal Customer,57,Business travel,Business,2292,5,5,5,5,2,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +100214,123528,Female,disloyal Customer,26,Business travel,Business,1290,5,5,5,4,3,5,5,3,3,5,5,3,5,3,1,0.0,satisfied +100215,55165,Male,Loyal Customer,9,Personal Travel,Eco,1346,2,4,2,1,1,2,3,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +100216,31289,Female,Loyal Customer,27,Business travel,Eco Plus,533,4,3,4,3,4,4,4,4,5,4,3,3,4,4,0,0.0,satisfied +100217,51502,Male,disloyal Customer,58,Business travel,Eco,370,4,5,4,3,1,4,5,1,2,1,3,1,4,1,3,0.0,neutral or dissatisfied +100218,87406,Male,Loyal Customer,33,Personal Travel,Eco,425,4,0,4,4,1,4,1,1,4,3,4,5,4,1,0,0.0,satisfied +100219,79199,Female,Loyal Customer,33,Business travel,Business,1990,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,5.0,satisfied +100220,18477,Male,disloyal Customer,30,Business travel,Eco,253,3,5,3,3,1,3,1,1,5,5,1,4,1,1,0,0.0,neutral or dissatisfied +100221,79308,Female,Loyal Customer,36,Business travel,Business,2925,1,1,1,1,1,1,1,3,2,3,3,1,2,1,0,29.0,neutral or dissatisfied +100222,30369,Female,Loyal Customer,48,Business travel,Business,1618,3,3,2,3,5,3,2,5,5,4,5,1,5,3,0,0.0,satisfied +100223,49015,Female,disloyal Customer,45,Business travel,Eco,373,4,0,4,2,4,4,4,4,2,4,1,1,5,4,0,0.0,neutral or dissatisfied +100224,45094,Male,disloyal Customer,27,Business travel,Business,157,1,1,1,4,5,1,5,5,3,3,4,3,4,5,0,13.0,neutral or dissatisfied +100225,2286,Female,Loyal Customer,41,Business travel,Business,925,4,4,4,4,3,5,4,4,4,4,4,3,4,5,77,87.0,satisfied +100226,89211,Female,Loyal Customer,17,Personal Travel,Eco,1947,4,5,4,4,2,4,3,2,3,3,5,3,4,2,3,0.0,neutral or dissatisfied +100227,105477,Male,Loyal Customer,47,Personal Travel,Eco,495,1,4,1,3,2,1,2,2,4,4,4,5,5,2,0,0.0,neutral or dissatisfied +100228,124121,Female,Loyal Customer,52,Business travel,Eco,529,3,3,4,3,4,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +100229,124250,Female,Loyal Customer,16,Personal Travel,Eco,1916,3,3,3,2,2,3,2,2,5,5,5,1,2,2,0,0.0,neutral or dissatisfied +100230,63378,Male,Loyal Customer,30,Personal Travel,Eco,337,2,5,2,1,5,2,5,5,5,4,5,3,4,5,15,4.0,neutral or dissatisfied +100231,84380,Male,Loyal Customer,46,Business travel,Eco,606,1,3,2,3,1,1,1,1,4,1,3,1,3,1,15,12.0,neutral or dissatisfied +100232,65860,Male,Loyal Customer,21,Personal Travel,Eco,1389,3,4,3,4,4,3,2,4,5,5,4,5,4,4,24,9.0,neutral or dissatisfied +100233,62486,Female,Loyal Customer,47,Business travel,Business,1781,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +100234,4792,Male,Loyal Customer,56,Personal Travel,Eco,403,3,5,3,5,4,3,4,4,5,2,5,3,5,4,30,36.0,neutral or dissatisfied +100235,129608,Male,Loyal Customer,58,Business travel,Business,3772,3,3,3,3,2,5,5,4,4,4,4,5,4,5,20,14.0,satisfied +100236,54053,Female,Loyal Customer,48,Business travel,Business,1416,1,4,4,4,3,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +100237,42770,Male,Loyal Customer,41,Business travel,Eco,493,4,4,4,4,4,4,4,4,2,4,4,5,2,4,40,23.0,satisfied +100238,108852,Male,Loyal Customer,45,Business travel,Business,1947,1,1,1,1,5,3,5,4,4,5,4,3,4,5,1,3.0,satisfied +100239,111710,Male,Loyal Customer,57,Business travel,Business,2578,1,4,4,4,3,4,4,1,1,2,1,4,1,2,7,8.0,neutral or dissatisfied +100240,70361,Female,Loyal Customer,52,Business travel,Business,1145,5,5,5,5,3,4,5,5,5,4,5,3,5,3,3,0.0,satisfied +100241,37489,Male,Loyal Customer,41,Business travel,Eco,1069,3,4,4,4,3,3,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +100242,101798,Male,Loyal Customer,42,Business travel,Business,1521,3,3,3,3,5,5,4,5,5,5,5,4,5,5,18,9.0,satisfied +100243,41639,Male,Loyal Customer,33,Business travel,Business,1680,1,1,1,1,5,5,5,5,4,5,5,3,4,5,0,0.0,satisfied +100244,66300,Male,disloyal Customer,36,Business travel,Eco,852,1,1,1,2,5,1,5,5,1,1,2,1,2,5,3,0.0,neutral or dissatisfied +100245,103535,Female,Loyal Customer,55,Business travel,Business,967,5,5,5,5,4,5,5,3,3,4,3,5,3,4,102,91.0,satisfied +100246,105687,Female,Loyal Customer,52,Business travel,Business,663,1,1,1,1,2,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +100247,13865,Female,Loyal Customer,51,Business travel,Business,2016,5,5,4,5,3,4,1,5,5,5,5,3,5,4,0,0.0,satisfied +100248,899,Male,Loyal Customer,36,Business travel,Business,3426,4,4,4,4,1,3,4,2,2,2,4,3,2,1,0,0.0,neutral or dissatisfied +100249,110471,Male,Loyal Customer,37,Personal Travel,Eco,919,1,3,1,4,2,1,4,2,1,3,2,1,4,2,0,0.0,neutral or dissatisfied +100250,75336,Male,disloyal Customer,26,Business travel,Eco,1056,2,2,2,2,5,2,5,5,5,3,3,4,5,5,1,0.0,neutral or dissatisfied +100251,97036,Male,disloyal Customer,36,Business travel,Business,1642,4,4,4,5,1,4,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +100252,43829,Female,Loyal Customer,51,Business travel,Business,153,5,5,4,5,3,3,4,5,5,5,5,5,5,2,0,0.0,satisfied +100253,101156,Male,disloyal Customer,37,Business travel,Eco,583,2,1,1,2,1,1,1,1,1,4,2,2,2,1,27,15.0,neutral or dissatisfied +100254,124145,Male,Loyal Customer,42,Business travel,Business,1594,4,4,4,4,2,5,5,2,2,2,2,3,2,4,0,6.0,satisfied +100255,114401,Female,Loyal Customer,30,Business travel,Business,1948,4,4,4,4,4,4,4,4,4,5,4,3,4,4,22,7.0,satisfied +100256,89079,Female,disloyal Customer,23,Business travel,Eco,852,3,4,4,3,3,5,5,4,3,4,3,5,4,5,37,72.0,neutral or dissatisfied +100257,2975,Female,disloyal Customer,45,Business travel,Business,462,4,4,4,4,5,4,5,5,3,3,4,5,4,5,0,0.0,satisfied +100258,3908,Female,Loyal Customer,27,Personal Travel,Eco,213,3,1,0,3,2,0,3,2,3,5,4,2,3,2,81,104.0,neutral or dissatisfied +100259,76006,Female,Loyal Customer,50,Business travel,Business,237,3,3,2,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +100260,45720,Female,Loyal Customer,43,Business travel,Business,452,1,1,1,1,2,5,2,2,2,2,2,5,2,5,63,43.0,satisfied +100261,71637,Female,Loyal Customer,53,Personal Travel,Eco,1005,4,5,4,1,5,4,4,3,3,4,3,3,3,4,5,0.0,satisfied +100262,62902,Female,Loyal Customer,54,Personal Travel,Business,853,4,1,4,3,3,4,3,5,5,4,5,3,5,4,0,6.0,neutral or dissatisfied +100263,97437,Female,Loyal Customer,52,Personal Travel,Eco Plus,587,4,5,4,2,2,5,5,4,4,4,4,3,4,3,50,82.0,neutral or dissatisfied +100264,22013,Female,Loyal Customer,22,Personal Travel,Eco,448,2,3,2,3,1,2,1,1,4,3,5,3,2,1,41,40.0,neutral or dissatisfied +100265,55782,Female,Loyal Customer,28,Personal Travel,Eco,646,4,3,4,2,1,4,1,1,3,3,5,4,1,1,0,0.0,satisfied +100266,48919,Female,Loyal Customer,53,Business travel,Business,3956,4,4,4,4,1,1,1,5,5,5,5,5,5,5,0,0.0,satisfied +100267,13399,Male,Loyal Customer,46,Personal Travel,Eco,505,3,5,3,2,3,3,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +100268,54033,Female,Loyal Customer,10,Personal Travel,Business,1416,4,4,3,2,2,3,2,2,3,1,5,4,3,2,9,4.0,satisfied +100269,52002,Female,Loyal Customer,47,Personal Travel,Eco,1119,4,2,5,3,2,3,4,4,4,5,4,3,4,2,0,2.0,neutral or dissatisfied +100270,119965,Female,disloyal Customer,12,Personal Travel,Eco,868,3,3,3,2,1,3,1,1,2,4,1,3,4,1,0,3.0,neutral or dissatisfied +100271,86629,Female,Loyal Customer,52,Business travel,Business,2960,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +100272,1521,Male,Loyal Customer,30,Business travel,Business,3179,4,1,4,4,4,4,4,4,4,5,5,3,5,4,0,0.0,satisfied +100273,13881,Male,Loyal Customer,60,Business travel,Eco,667,1,2,2,2,1,1,1,1,4,1,1,2,1,1,0,1.0,neutral or dissatisfied +100274,117384,Female,Loyal Customer,52,Business travel,Business,3649,3,3,3,3,3,4,5,4,4,4,4,4,4,5,0,2.0,satisfied +100275,82700,Male,Loyal Customer,11,Business travel,Eco,632,1,3,3,3,1,1,3,1,3,2,3,3,3,1,37,28.0,neutral or dissatisfied +100276,43418,Male,Loyal Customer,20,Business travel,Eco Plus,358,4,2,2,2,4,4,4,4,5,2,5,2,2,4,0,0.0,satisfied +100277,26843,Female,Loyal Customer,22,Business travel,Eco,224,0,3,1,5,4,1,4,4,5,1,2,4,4,4,0,0.0,satisfied +100278,129761,Female,Loyal Customer,24,Business travel,Business,2425,4,4,4,4,5,5,5,5,1,5,1,5,5,5,0,0.0,satisfied +100279,55499,Female,Loyal Customer,28,Personal Travel,Eco,1739,0,4,0,3,1,0,4,1,5,5,3,4,4,1,0,0.0,satisfied +100280,68383,Male,Loyal Customer,43,Business travel,Business,1045,2,2,2,2,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +100281,129342,Female,Loyal Customer,57,Personal Travel,Eco,2586,5,3,5,3,3,3,2,3,3,5,3,5,3,3,0,0.0,satisfied +100282,18488,Male,Loyal Customer,43,Business travel,Business,253,4,4,4,4,3,1,4,5,5,5,5,5,5,1,0,3.0,satisfied +100283,69736,Male,Loyal Customer,53,Business travel,Business,1372,1,1,5,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +100284,128834,Female,disloyal Customer,40,Business travel,Business,1086,2,3,3,3,3,5,3,1,5,4,3,3,2,3,36,29.0,neutral or dissatisfied +100285,105725,Female,Loyal Customer,38,Business travel,Eco,925,4,5,5,5,4,4,4,4,3,1,4,1,4,4,0,14.0,neutral or dissatisfied +100286,17478,Male,disloyal Customer,25,Business travel,Business,352,5,5,5,3,5,5,5,5,4,1,4,4,5,5,0,0.0,satisfied +100287,112150,Female,Loyal Customer,51,Business travel,Eco,895,3,3,3,3,1,2,1,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +100288,123790,Female,Loyal Customer,47,Business travel,Business,2517,3,3,5,3,3,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +100289,100205,Male,disloyal Customer,28,Business travel,Business,762,2,2,2,1,1,2,4,1,4,5,5,3,4,1,6,5.0,neutral or dissatisfied +100290,12596,Female,Loyal Customer,66,Business travel,Eco,142,4,4,4,4,1,5,2,4,4,4,4,4,4,3,33,49.0,satisfied +100291,43691,Female,Loyal Customer,39,Business travel,Business,257,2,2,2,2,5,4,2,5,5,5,5,4,5,1,0,2.0,satisfied +100292,124249,Female,Loyal Customer,37,Personal Travel,Eco,1916,1,5,1,3,3,1,3,3,5,3,4,3,5,3,12,8.0,neutral or dissatisfied +100293,79552,Female,Loyal Customer,44,Business travel,Business,2575,1,1,2,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +100294,7695,Female,Loyal Customer,26,Personal Travel,Eco,604,1,5,1,4,4,1,4,4,4,3,4,5,5,4,0,4.0,neutral or dissatisfied +100295,128094,Female,Loyal Customer,52,Personal Travel,Eco,2979,3,3,3,3,3,3,3,1,5,1,2,3,2,3,48,40.0,neutral or dissatisfied +100296,28922,Male,Loyal Customer,23,Business travel,Business,978,5,5,5,5,3,3,3,3,5,3,3,4,4,3,0,0.0,satisfied +100297,50580,Female,Loyal Customer,13,Personal Travel,Eco,109,3,4,3,3,2,3,2,2,3,1,2,2,3,2,0,0.0,neutral or dissatisfied +100298,121576,Male,Loyal Customer,50,Business travel,Business,1032,4,4,4,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +100299,31759,Female,Loyal Customer,24,Business travel,Business,2809,3,3,3,3,5,5,5,5,1,1,1,3,4,5,17,14.0,satisfied +100300,107547,Female,Loyal Customer,60,Business travel,Business,1521,4,4,4,4,2,4,5,4,4,4,4,4,4,4,7,1.0,satisfied +100301,13098,Male,disloyal Customer,23,Business travel,Eco,562,1,0,1,3,2,1,2,2,1,2,1,5,2,2,0,0.0,neutral or dissatisfied +100302,126926,Male,Loyal Customer,39,Business travel,Business,3980,1,1,5,1,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +100303,72324,Male,Loyal Customer,36,Business travel,Business,1121,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,30.0,satisfied +100304,11977,Female,Loyal Customer,42,Business travel,Business,1844,5,5,5,5,4,4,4,5,5,5,5,5,5,3,0,7.0,satisfied +100305,123206,Female,Loyal Customer,42,Personal Travel,Eco,507,1,4,1,3,1,1,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +100306,90760,Male,disloyal Customer,29,Business travel,Eco,545,3,0,3,3,3,3,3,3,1,1,4,4,4,3,15,20.0,neutral or dissatisfied +100307,47797,Male,disloyal Customer,22,Business travel,Eco,462,3,4,3,4,1,3,1,1,3,3,1,3,2,1,0,0.0,neutral or dissatisfied +100308,85872,Female,Loyal Customer,60,Business travel,Business,2172,3,3,3,3,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +100309,79423,Male,Loyal Customer,64,Personal Travel,Eco,502,4,3,4,3,5,4,5,5,3,2,4,1,4,5,0,0.0,neutral or dissatisfied +100310,92087,Male,Loyal Customer,55,Business travel,Business,1576,1,5,5,5,1,4,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +100311,126442,Female,Loyal Customer,12,Personal Travel,Eco Plus,631,3,1,4,3,4,4,4,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +100312,125005,Female,disloyal Customer,21,Business travel,Eco,184,1,4,1,4,5,1,5,5,3,5,3,3,3,5,30,14.0,neutral or dissatisfied +100313,67403,Female,disloyal Customer,29,Business travel,Eco,641,4,2,4,3,2,4,2,2,3,2,4,4,3,2,13,6.0,neutral or dissatisfied +100314,25606,Female,disloyal Customer,24,Business travel,Eco,526,3,0,3,2,5,3,2,5,3,3,2,2,5,5,29,36.0,neutral or dissatisfied +100315,55411,Female,Loyal Customer,33,Personal Travel,Eco,1558,2,5,3,1,2,3,5,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +100316,20588,Male,Loyal Customer,59,Personal Travel,Eco,533,3,2,3,3,3,4,4,2,1,3,2,4,1,4,256,242.0,neutral or dissatisfied +100317,28074,Female,Loyal Customer,26,Personal Travel,Eco,2607,3,2,3,3,3,4,4,3,3,3,4,4,1,4,56,98.0,neutral or dissatisfied +100318,65528,Male,Loyal Customer,17,Personal Travel,Eco,1616,3,4,2,5,5,2,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +100319,166,Female,Loyal Customer,44,Personal Travel,Eco,227,2,3,0,1,2,4,2,4,4,0,4,3,4,3,31,25.0,neutral or dissatisfied +100320,49858,Female,disloyal Customer,22,Business travel,Eco,156,4,3,4,2,4,4,4,4,5,2,4,1,1,4,0,0.0,satisfied +100321,74661,Male,Loyal Customer,29,Personal Travel,Eco,1205,3,1,3,4,5,3,2,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +100322,125490,Male,Loyal Customer,54,Personal Travel,Eco Plus,2917,1,1,1,2,2,1,2,2,3,4,2,4,2,2,16,0.0,neutral or dissatisfied +100323,44888,Female,Loyal Customer,43,Business travel,Business,2690,2,1,2,2,3,4,3,5,5,5,5,3,5,1,0,5.0,satisfied +100324,44556,Female,disloyal Customer,26,Business travel,Eco Plus,128,5,5,5,1,2,5,2,2,4,2,2,5,5,2,0,0.0,satisfied +100325,34982,Male,Loyal Customer,52,Personal Travel,Eco,273,3,4,4,1,1,4,1,1,2,3,2,5,1,1,0,8.0,neutral or dissatisfied +100326,65902,Female,Loyal Customer,58,Business travel,Eco,569,1,1,1,1,4,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +100327,24938,Male,Loyal Customer,41,Personal Travel,Eco,2106,3,1,3,1,1,3,1,1,4,5,2,1,2,1,0,0.0,neutral or dissatisfied +100328,40805,Male,disloyal Customer,30,Business travel,Eco,584,4,2,5,3,5,5,5,5,2,5,4,2,4,5,0,0.0,neutral or dissatisfied +100329,22760,Male,Loyal Customer,61,Business travel,Business,2516,1,3,3,3,2,3,3,3,3,3,1,4,3,2,3,0.0,neutral or dissatisfied +100330,21730,Male,disloyal Customer,28,Business travel,Eco,563,3,5,3,3,1,3,1,1,2,3,2,1,2,1,13,20.0,neutral or dissatisfied +100331,77804,Female,Loyal Customer,13,Personal Travel,Eco,1282,3,1,3,3,5,3,5,5,1,2,4,1,3,5,13,4.0,neutral or dissatisfied +100332,103087,Female,Loyal Customer,40,Personal Travel,Eco,460,1,5,4,1,4,4,5,4,1,4,5,3,3,4,0,0.0,neutral or dissatisfied +100333,18856,Female,disloyal Customer,29,Business travel,Eco,551,2,1,2,3,1,2,1,1,2,2,3,2,3,1,0,0.0,neutral or dissatisfied +100334,45843,Male,Loyal Customer,41,Personal Travel,Eco,517,2,2,2,4,4,2,4,4,2,4,4,1,3,4,26,10.0,neutral or dissatisfied +100335,24408,Female,Loyal Customer,16,Business travel,Business,634,4,4,4,4,5,5,5,5,1,2,1,1,3,5,0,0.0,satisfied +100336,100789,Female,Loyal Customer,69,Personal Travel,Business,748,3,4,3,3,4,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +100337,61441,Female,Loyal Customer,54,Business travel,Business,2419,1,1,1,1,3,3,5,5,5,5,5,5,5,5,4,0.0,satisfied +100338,61364,Female,Loyal Customer,47,Personal Travel,Eco Plus,2405,4,5,4,5,3,2,4,3,3,4,3,4,3,4,3,3.0,neutral or dissatisfied +100339,7209,Female,Loyal Customer,42,Business travel,Business,135,4,4,4,4,4,4,4,4,4,4,5,5,4,3,0,4.0,satisfied +100340,281,Male,Loyal Customer,51,Personal Travel,Eco,825,3,4,3,1,5,3,5,5,3,3,5,4,5,5,0,0.0,neutral or dissatisfied +100341,55029,Male,Loyal Customer,49,Business travel,Business,1609,4,4,4,4,4,4,4,4,4,4,4,4,4,3,10,0.0,satisfied +100342,87341,Male,disloyal Customer,50,Business travel,Business,425,2,2,2,2,3,2,5,3,4,3,4,4,4,3,5,0.0,satisfied +100343,40979,Male,Loyal Customer,12,Personal Travel,Eco Plus,601,5,5,5,1,1,5,1,1,5,2,3,5,1,1,0,0.0,satisfied +100344,65122,Male,Loyal Customer,46,Personal Travel,Eco,190,1,4,1,2,5,1,5,5,2,5,5,3,4,5,0,0.0,neutral or dissatisfied +100345,10113,Female,disloyal Customer,14,Business travel,Eco,984,2,2,2,3,4,2,4,4,4,4,4,1,3,4,0,0.0,neutral or dissatisfied +100346,66094,Male,Loyal Customer,62,Personal Travel,Eco Plus,1345,4,4,4,5,2,4,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +100347,50359,Male,disloyal Customer,19,Business travel,Eco,238,3,1,3,4,2,3,5,2,4,1,3,1,3,2,70,66.0,neutral or dissatisfied +100348,101008,Female,Loyal Customer,46,Business travel,Business,806,2,2,2,2,5,5,5,4,4,4,4,5,5,5,140,116.0,satisfied +100349,9297,Male,Loyal Customer,50,Business travel,Business,2753,5,5,5,5,5,5,4,4,4,4,4,4,4,4,3,2.0,satisfied +100350,97229,Male,Loyal Customer,46,Business travel,Business,3859,1,5,5,5,4,4,4,1,1,2,1,3,1,2,1,1.0,neutral or dissatisfied +100351,129409,Female,Loyal Customer,42,Business travel,Business,2402,4,4,2,4,2,5,4,4,4,4,4,3,4,5,9,12.0,satisfied +100352,107103,Female,disloyal Customer,24,Business travel,Business,562,4,0,4,4,4,5,2,5,5,5,4,2,5,2,140,178.0,satisfied +100353,56212,Male,Loyal Customer,36,Business travel,Business,2080,2,2,2,2,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +100354,77256,Male,Loyal Customer,66,Personal Travel,Eco,1590,2,3,3,2,1,3,1,1,2,2,2,2,3,1,0,2.0,neutral or dissatisfied +100355,46608,Female,disloyal Customer,43,Business travel,Eco,125,2,0,2,1,3,2,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +100356,121061,Female,Loyal Customer,43,Personal Travel,Eco,1013,2,1,2,3,5,4,4,5,5,2,5,3,5,3,14,5.0,neutral or dissatisfied +100357,105830,Male,Loyal Customer,45,Personal Travel,Eco,798,2,1,2,3,2,2,2,2,2,3,4,2,4,2,0,0.0,neutral or dissatisfied +100358,41575,Female,Loyal Customer,37,Personal Travel,Eco,1269,3,5,3,5,1,3,1,1,4,3,5,4,4,1,4,0.0,neutral or dissatisfied +100359,93570,Female,disloyal Customer,37,Business travel,Business,159,5,5,5,4,4,5,4,4,3,5,4,3,4,4,0,0.0,satisfied +100360,24996,Male,Loyal Customer,19,Personal Travel,Eco,484,5,1,5,4,4,5,4,4,3,2,3,2,3,4,60,77.0,satisfied +100361,118609,Male,Loyal Customer,27,Business travel,Business,3481,2,5,5,5,2,2,2,2,2,1,4,4,3,2,86,106.0,neutral or dissatisfied +100362,57739,Female,disloyal Customer,25,Business travel,Eco Plus,1754,1,4,1,4,5,1,4,5,3,4,2,2,4,5,0,0.0,neutral or dissatisfied +100363,128113,Male,Loyal Customer,48,Business travel,Business,1587,4,4,4,4,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +100364,83134,Male,Loyal Customer,68,Personal Travel,Eco,1086,5,2,5,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +100365,54565,Female,Loyal Customer,58,Business travel,Eco Plus,925,5,3,3,3,4,3,5,5,5,5,5,1,5,3,28,17.0,satisfied +100366,44865,Male,Loyal Customer,45,Personal Travel,Business,315,1,4,1,4,3,4,4,2,2,1,4,4,2,3,50,47.0,neutral or dissatisfied +100367,42216,Male,disloyal Customer,47,Business travel,Eco,412,3,3,3,5,2,3,2,2,4,3,3,3,5,2,0,0.0,neutral or dissatisfied +100368,45753,Male,Loyal Customer,50,Business travel,Eco,216,5,5,5,5,5,5,5,5,4,2,3,4,4,5,0,0.0,satisfied +100369,128760,Male,Loyal Customer,48,Business travel,Eco,550,3,2,1,2,4,3,4,4,4,3,3,1,4,4,0,22.0,neutral or dissatisfied +100370,96642,Male,Loyal Customer,48,Business travel,Eco,972,2,3,3,3,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +100371,414,Male,Loyal Customer,51,Business travel,Business,3458,0,4,0,1,2,5,5,2,2,2,2,5,2,3,0,2.0,satisfied +100372,10115,Male,disloyal Customer,21,Business travel,Eco,984,4,4,4,1,4,4,4,4,5,5,4,4,4,4,6,0.0,satisfied +100373,34480,Female,Loyal Customer,12,Personal Travel,Eco,266,4,2,4,3,4,4,4,4,3,1,3,4,4,4,0,0.0,neutral or dissatisfied +100374,108192,Male,disloyal Customer,31,Business travel,Eco Plus,990,3,2,2,4,5,2,5,5,3,4,3,4,3,5,51,44.0,neutral or dissatisfied +100375,85620,Female,Loyal Customer,33,Personal Travel,Eco,259,1,3,1,4,2,1,2,2,1,5,4,2,1,2,0,10.0,neutral or dissatisfied +100376,10020,Female,Loyal Customer,45,Personal Travel,Eco Plus,457,3,5,3,2,4,5,5,4,4,3,4,5,4,5,0,14.0,neutral or dissatisfied +100377,13753,Male,Loyal Customer,46,Personal Travel,Eco,384,2,5,2,3,4,2,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +100378,107369,Male,Loyal Customer,60,Business travel,Business,3717,3,3,3,3,3,3,3,3,5,5,5,3,3,3,262,233.0,satisfied +100379,62125,Female,Loyal Customer,25,Business travel,Business,2434,3,3,3,3,3,2,3,3,1,5,2,1,4,3,0,0.0,neutral or dissatisfied +100380,62735,Male,Loyal Customer,42,Business travel,Business,2449,5,5,5,5,3,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +100381,65636,Female,Loyal Customer,38,Business travel,Business,2617,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +100382,76326,Female,disloyal Customer,21,Personal Travel,Eco,2182,2,2,2,1,1,2,1,1,2,4,2,1,1,1,0,1.0,neutral or dissatisfied +100383,48854,Male,Loyal Customer,12,Personal Travel,Business,109,3,4,0,1,3,0,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +100384,107201,Female,Loyal Customer,59,Personal Travel,Eco,402,2,4,2,5,5,5,5,2,2,2,2,3,2,3,1,0.0,neutral or dissatisfied +100385,124156,Male,Loyal Customer,45,Business travel,Business,2133,4,4,4,4,3,4,4,5,5,4,5,4,5,5,0,8.0,satisfied +100386,48841,Male,Loyal Customer,24,Personal Travel,Business,250,3,5,3,3,3,3,3,3,3,4,5,4,4,3,0,2.0,neutral or dissatisfied +100387,1367,Male,Loyal Customer,50,Business travel,Business,3890,4,2,2,2,3,3,3,2,2,2,4,3,2,1,0,0.0,neutral or dissatisfied +100388,128169,Male,disloyal Customer,27,Business travel,Eco,1119,4,4,4,4,3,4,3,3,4,4,2,1,3,3,2,0.0,neutral or dissatisfied +100389,103443,Female,disloyal Customer,28,Business travel,Business,393,1,1,1,3,5,1,5,5,5,5,5,5,5,5,23,17.0,neutral or dissatisfied +100390,76694,Female,Loyal Customer,45,Personal Travel,Eco,547,2,5,2,5,4,5,4,5,5,2,5,5,5,5,0,17.0,neutral or dissatisfied +100391,116448,Female,Loyal Customer,50,Personal Travel,Eco,342,2,5,2,5,3,1,2,1,1,2,5,4,1,4,0,0.0,neutral or dissatisfied +100392,66677,Male,Loyal Customer,56,Business travel,Business,802,2,2,2,2,2,5,4,5,5,5,5,4,5,3,11,4.0,satisfied +100393,127050,Male,Loyal Customer,77,Business travel,Business,2541,4,3,2,3,1,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +100394,91034,Female,Loyal Customer,32,Personal Travel,Eco,581,4,2,3,4,1,3,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +100395,29197,Male,Loyal Customer,33,Personal Travel,Eco Plus,1050,2,5,2,2,2,2,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +100396,101316,Male,disloyal Customer,30,Business travel,Business,986,1,1,1,4,4,1,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +100397,94850,Female,disloyal Customer,40,Business travel,Business,293,4,4,4,4,2,4,1,2,2,3,3,2,3,2,25,27.0,neutral or dissatisfied +100398,22430,Female,Loyal Customer,25,Personal Travel,Eco,238,3,4,0,2,3,0,3,3,1,2,2,1,4,3,0,0.0,neutral or dissatisfied +100399,89249,Male,Loyal Customer,53,Personal Travel,Eco Plus,1947,5,4,5,2,2,5,2,2,3,3,5,5,4,2,0,0.0,satisfied +100400,95233,Male,Loyal Customer,24,Personal Travel,Eco,248,2,5,2,2,2,2,2,2,4,3,4,3,5,2,0,1.0,neutral or dissatisfied +100401,99854,Male,Loyal Customer,7,Personal Travel,Eco,468,4,1,4,3,1,4,1,1,4,2,4,3,4,1,89,100.0,neutral or dissatisfied +100402,7063,Male,Loyal Customer,47,Business travel,Business,157,4,4,4,4,3,4,4,5,5,5,4,5,5,3,0,0.0,satisfied +100403,100702,Male,Loyal Customer,27,Personal Travel,Eco,628,2,2,1,3,4,1,1,4,4,4,4,4,3,4,18,13.0,neutral or dissatisfied +100404,106725,Male,Loyal Customer,45,Business travel,Business,829,1,1,1,1,5,4,5,3,3,3,3,4,3,3,5,9.0,satisfied +100405,39153,Female,Loyal Customer,58,Business travel,Eco Plus,119,2,4,4,4,4,3,3,2,2,2,2,2,2,3,30,51.0,neutral or dissatisfied +100406,114065,Female,Loyal Customer,40,Business travel,Business,1892,1,1,1,1,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +100407,81989,Female,Loyal Customer,22,Business travel,Eco,1589,4,2,2,2,4,4,1,4,1,5,2,1,2,4,97,97.0,neutral or dissatisfied +100408,127663,Female,Loyal Customer,50,Business travel,Business,2153,4,4,2,4,5,3,5,5,5,5,5,3,5,5,5,21.0,satisfied +100409,47627,Female,Loyal Customer,45,Business travel,Business,1211,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +100410,101746,Male,Loyal Customer,31,Business travel,Business,1590,1,1,1,1,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +100411,106598,Female,Loyal Customer,21,Personal Travel,Eco,986,3,4,3,2,4,3,2,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +100412,120833,Male,disloyal Customer,26,Business travel,Business,861,2,3,3,4,2,3,2,2,5,4,4,4,5,2,0,13.0,neutral or dissatisfied +100413,45398,Female,disloyal Customer,22,Business travel,Eco,458,2,0,3,3,4,3,4,4,5,4,4,5,5,4,18,6.0,neutral or dissatisfied +100414,80076,Female,Loyal Customer,53,Business travel,Eco Plus,1010,2,2,2,2,5,1,2,2,2,2,2,4,2,3,24,7.0,neutral or dissatisfied +100415,97984,Female,Loyal Customer,16,Personal Travel,Eco,616,4,1,4,3,5,4,5,5,1,4,3,1,4,5,20,3.0,neutral or dissatisfied +100416,51181,Female,Loyal Customer,49,Business travel,Eco Plus,110,4,4,4,4,3,5,1,4,4,4,4,3,4,3,15,16.0,satisfied +100417,119963,Female,disloyal Customer,34,Business travel,Eco,1009,3,3,3,5,2,3,2,2,5,5,2,5,4,2,0,0.0,neutral or dissatisfied +100418,19466,Male,Loyal Customer,36,Business travel,Business,1901,3,3,3,3,5,4,3,5,5,5,5,1,5,5,0,0.0,satisfied +100419,67849,Female,Loyal Customer,30,Personal Travel,Eco,1171,3,5,2,5,5,2,4,5,4,5,3,4,5,5,25,22.0,neutral or dissatisfied +100420,124515,Female,Loyal Customer,59,Business travel,Business,3331,3,4,4,4,3,2,2,3,3,3,3,3,3,3,19,9.0,neutral or dissatisfied +100421,42031,Male,Loyal Customer,52,Business travel,Eco,116,5,4,4,4,5,5,5,5,2,2,5,1,3,5,0,0.0,satisfied +100422,6529,Female,Loyal Customer,64,Personal Travel,Eco,599,2,4,2,1,1,5,3,2,2,2,2,3,2,3,28,77.0,neutral or dissatisfied +100423,81031,Male,Loyal Customer,47,Business travel,Business,1399,1,5,5,5,4,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +100424,29123,Female,Loyal Customer,29,Personal Travel,Eco,679,3,5,2,5,2,2,2,2,5,5,4,3,4,2,0,1.0,neutral or dissatisfied +100425,120748,Female,Loyal Customer,68,Personal Travel,Business,678,2,5,2,3,2,5,4,4,4,2,4,4,4,5,130,110.0,neutral or dissatisfied +100426,97901,Male,Loyal Customer,42,Business travel,Business,2803,1,1,1,1,5,4,4,5,5,5,5,4,5,3,4,,satisfied +100427,41100,Female,Loyal Customer,25,Business travel,Business,2346,0,0,0,3,5,5,5,5,5,3,3,5,5,5,4,12.0,satisfied +100428,80491,Male,Loyal Customer,55,Business travel,Business,1749,5,5,5,5,2,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +100429,34448,Male,Loyal Customer,73,Business travel,Business,3466,3,3,3,3,3,4,4,3,3,3,3,4,3,1,0,3.0,neutral or dissatisfied +100430,87988,Male,Loyal Customer,49,Business travel,Business,2017,2,2,2,2,2,4,5,5,5,5,5,4,5,5,0,3.0,satisfied +100431,59449,Male,disloyal Customer,20,Business travel,Eco,811,2,2,2,1,1,2,1,1,5,4,4,5,5,1,1,0.0,neutral or dissatisfied +100432,121688,Male,Loyal Customer,63,Personal Travel,Eco,328,4,4,4,2,1,4,2,1,1,4,4,5,1,1,0,0.0,satisfied +100433,20634,Male,Loyal Customer,40,Business travel,Business,3988,4,4,4,4,1,3,2,5,5,4,5,3,5,1,0,21.0,satisfied +100434,113550,Male,Loyal Customer,42,Business travel,Business,197,3,3,3,3,3,2,3,3,3,3,3,2,3,3,9,7.0,neutral or dissatisfied +100435,69376,Male,disloyal Customer,27,Business travel,Business,1089,1,1,1,2,2,1,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +100436,105975,Female,Loyal Customer,65,Personal Travel,Eco,2329,1,5,1,2,1,3,3,3,4,3,4,3,4,3,5,9.0,neutral or dissatisfied +100437,8276,Female,Loyal Customer,69,Personal Travel,Eco,294,4,5,4,3,2,5,4,4,4,4,4,3,4,5,10,3.0,satisfied +100438,46924,Female,disloyal Customer,39,Business travel,Eco,337,2,0,1,3,5,1,5,5,5,5,5,5,1,5,0,0.0,neutral or dissatisfied +100439,989,Female,Loyal Customer,48,Business travel,Eco,158,3,5,5,5,1,4,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +100440,49929,Male,Loyal Customer,40,Business travel,Eco,209,5,1,5,1,5,5,5,5,3,1,4,4,2,5,76,61.0,satisfied +100441,100609,Female,Loyal Customer,60,Business travel,Business,1670,3,3,3,3,4,3,5,4,4,4,4,3,4,5,0,1.0,satisfied +100442,15569,Female,Loyal Customer,55,Business travel,Business,229,3,3,3,3,3,1,1,3,3,3,3,1,3,1,72,87.0,neutral or dissatisfied +100443,91722,Male,Loyal Customer,53,Business travel,Business,590,2,2,2,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +100444,94523,Female,Loyal Customer,51,Business travel,Business,248,2,2,2,2,2,5,5,5,5,4,5,3,5,5,1,0.0,satisfied +100445,82457,Female,Loyal Customer,75,Business travel,Eco,102,5,1,1,1,5,4,2,5,5,5,5,3,5,4,0,0.0,satisfied +100446,25688,Female,Loyal Customer,58,Business travel,Business,447,5,5,1,5,2,4,5,4,4,4,4,1,4,4,2,0.0,satisfied +100447,52444,Male,Loyal Customer,26,Personal Travel,Eco,493,3,4,3,3,3,3,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +100448,67151,Male,Loyal Customer,66,Business travel,Eco,564,3,2,2,2,3,3,3,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +100449,92677,Female,Loyal Customer,34,Business travel,Business,3290,4,4,4,4,3,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +100450,48324,Male,disloyal Customer,24,Business travel,Eco,587,4,4,5,1,1,5,1,1,4,3,4,5,4,1,87,75.0,neutral or dissatisfied +100451,51185,Female,disloyal Customer,32,Business travel,Eco Plus,158,2,2,2,1,4,2,2,4,2,4,2,2,3,4,0,0.0,neutral or dissatisfied +100452,103133,Male,Loyal Customer,50,Business travel,Eco Plus,687,4,5,5,5,4,4,4,4,2,5,4,3,4,4,0,0.0,neutral or dissatisfied +100453,79321,Male,Loyal Customer,28,Business travel,Eco,1020,1,4,4,4,1,2,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +100454,34559,Female,disloyal Customer,28,Business travel,Eco,1598,4,5,5,1,3,4,3,3,1,4,4,3,4,3,37,16.0,neutral or dissatisfied +100455,75428,Male,disloyal Customer,18,Business travel,Business,1021,4,0,4,1,4,4,4,4,5,4,3,5,4,4,2,4.0,satisfied +100456,92883,Male,Loyal Customer,49,Business travel,Business,1919,0,4,1,4,3,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +100457,87592,Female,Loyal Customer,26,Personal Travel,Eco,432,3,3,2,4,2,2,2,2,3,1,5,4,3,2,0,0.0,neutral or dissatisfied +100458,48591,Male,Loyal Customer,31,Personal Travel,Eco,959,2,5,2,4,2,2,2,2,5,5,5,4,5,2,25,9.0,neutral or dissatisfied +100459,35597,Male,Loyal Customer,46,Business travel,Eco Plus,972,2,5,5,5,3,2,3,3,1,3,3,3,3,3,119,126.0,neutral or dissatisfied +100460,105331,Male,Loyal Customer,39,Business travel,Business,409,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +100461,15458,Male,Loyal Customer,53,Business travel,Business,399,1,4,4,4,4,4,4,1,1,1,1,2,1,4,58,77.0,neutral or dissatisfied +100462,125060,Male,Loyal Customer,48,Business travel,Business,90,3,3,3,3,3,5,5,5,5,5,4,4,5,5,0,4.0,satisfied +100463,24627,Female,Loyal Customer,8,Personal Travel,Eco,666,2,3,2,5,4,2,4,4,3,4,5,2,4,4,1,59.0,neutral or dissatisfied +100464,27084,Female,Loyal Customer,25,Business travel,Business,2496,3,4,4,4,3,3,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +100465,70622,Female,Loyal Customer,12,Business travel,Eco,1217,1,5,5,5,1,1,3,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +100466,122798,Female,Loyal Customer,22,Business travel,Eco,599,3,5,5,5,3,3,3,3,1,2,4,3,3,3,13,18.0,neutral or dissatisfied +100467,10459,Male,Loyal Customer,59,Business travel,Business,2086,1,1,1,1,5,4,4,4,4,4,4,3,4,3,22,14.0,satisfied +100468,21441,Male,disloyal Customer,23,Business travel,Eco,164,2,0,2,4,3,2,3,3,4,3,2,5,4,3,17,15.0,neutral or dissatisfied +100469,27963,Male,Loyal Customer,14,Personal Travel,Eco,1660,3,4,3,1,2,3,2,2,5,3,5,5,4,2,2,6.0,neutral or dissatisfied +100470,20041,Male,disloyal Customer,40,Business travel,Eco,723,5,5,5,1,2,5,2,2,4,2,5,3,4,2,0,0.0,satisfied +100471,106351,Female,Loyal Customer,59,Business travel,Business,2653,5,5,5,5,5,5,5,1,1,2,1,4,1,3,54,50.0,satisfied +100472,125662,Male,disloyal Customer,49,Business travel,Eco,899,3,3,3,3,2,3,2,2,4,3,4,1,3,2,0,13.0,neutral or dissatisfied +100473,37681,Female,Loyal Customer,14,Personal Travel,Eco,1069,3,5,3,1,5,3,3,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +100474,49272,Female,Loyal Customer,25,Business travel,Business,109,1,1,1,1,5,5,5,5,2,4,1,1,3,5,86,76.0,satisfied +100475,48264,Female,Loyal Customer,18,Personal Travel,Eco,259,3,4,3,4,1,3,1,1,1,3,3,3,4,1,0,0.0,neutral or dissatisfied +100476,116420,Male,Loyal Customer,15,Personal Travel,Eco,417,3,5,3,5,5,3,5,5,4,4,5,5,1,5,12,10.0,neutral or dissatisfied +100477,14425,Male,Loyal Customer,48,Business travel,Eco Plus,585,2,5,5,5,2,2,2,2,1,2,3,3,4,2,1,0.0,neutral or dissatisfied +100478,71492,Female,Loyal Customer,47,Business travel,Business,3740,3,3,5,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +100479,11125,Male,Loyal Customer,9,Personal Travel,Eco,74,3,5,3,4,4,3,4,4,5,4,4,3,5,4,5,0.0,neutral or dissatisfied +100480,108409,Male,disloyal Customer,41,Business travel,Eco,144,1,2,1,4,3,1,3,3,3,2,4,2,3,3,6,0.0,neutral or dissatisfied +100481,120064,Male,Loyal Customer,55,Business travel,Business,683,4,4,2,4,2,4,4,4,4,5,4,3,4,5,9,86.0,satisfied +100482,60563,Female,Loyal Customer,9,Personal Travel,Eco Plus,862,2,5,2,5,4,2,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +100483,116436,Male,Loyal Customer,52,Personal Travel,Eco,417,2,3,2,2,4,2,1,4,4,3,3,4,3,4,6,4.0,neutral or dissatisfied +100484,7243,Male,Loyal Customer,22,Personal Travel,Eco,135,0,0,0,3,2,0,2,2,2,4,5,3,4,2,30,26.0,satisfied +100485,113822,Female,Loyal Customer,14,Personal Travel,Eco Plus,236,4,5,4,5,2,4,2,2,4,4,4,3,4,2,1,0.0,neutral or dissatisfied +100486,47820,Female,disloyal Customer,23,Business travel,Eco,550,3,3,3,3,3,3,2,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +100487,88679,Male,Loyal Customer,66,Personal Travel,Eco,404,1,4,1,1,2,1,2,2,5,5,4,5,4,2,15,11.0,neutral or dissatisfied +100488,72311,Female,Loyal Customer,55,Business travel,Business,2018,1,1,1,1,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +100489,82200,Male,Loyal Customer,54,Business travel,Eco Plus,1927,3,4,4,4,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +100490,122758,Male,Loyal Customer,61,Personal Travel,Eco,651,1,4,1,4,3,1,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +100491,53451,Female,disloyal Customer,18,Business travel,Eco,1103,1,1,1,1,1,2,2,5,5,3,5,2,2,2,0,0.0,neutral or dissatisfied +100492,42327,Male,Loyal Customer,24,Personal Travel,Eco,726,2,2,2,3,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +100493,65607,Male,Loyal Customer,23,Business travel,Business,2024,1,4,2,2,4,4,1,4,2,5,3,1,3,4,112,107.0,neutral or dissatisfied +100494,42626,Female,Loyal Customer,38,Business travel,Business,546,2,2,2,2,2,2,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +100495,123416,Male,Loyal Customer,65,Business travel,Eco,937,2,4,4,4,2,2,2,2,1,2,4,2,3,2,0,7.0,neutral or dissatisfied +100496,87332,Female,Loyal Customer,59,Business travel,Business,2736,2,2,2,2,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +100497,89167,Female,Loyal Customer,14,Personal Travel,Eco,2092,3,5,3,1,4,3,3,4,4,2,5,3,4,4,5,0.0,neutral or dissatisfied +100498,32015,Male,Loyal Customer,34,Business travel,Business,1525,5,5,5,5,4,3,2,5,5,5,5,2,5,2,0,0.0,satisfied +100499,39534,Female,Loyal Customer,48,Business travel,Business,945,1,3,3,3,5,1,2,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +100500,87034,Female,Loyal Customer,53,Business travel,Business,2717,2,2,2,2,4,5,5,4,4,4,4,3,4,5,7,5.0,satisfied +100501,9979,Female,Loyal Customer,29,Personal Travel,Eco,515,5,5,5,3,5,5,4,5,4,3,4,5,4,5,0,0.0,satisfied +100502,51877,Male,Loyal Customer,37,Personal Travel,Eco,771,1,4,1,2,2,1,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +100503,24404,Female,Loyal Customer,47,Business travel,Eco,634,4,4,4,4,4,5,2,4,4,4,4,5,4,5,0,4.0,satisfied +100504,113868,Female,Loyal Customer,17,Personal Travel,Eco,1363,2,5,2,3,2,2,2,2,5,3,3,5,5,2,0,0.0,neutral or dissatisfied +100505,40736,Female,Loyal Customer,49,Business travel,Business,599,4,4,4,4,1,4,3,4,4,4,4,3,4,3,21,14.0,satisfied +100506,89832,Male,Loyal Customer,38,Personal Travel,Eco Plus,1089,1,5,1,4,3,1,3,3,3,3,2,1,2,3,37,19.0,neutral or dissatisfied +100507,36136,Male,Loyal Customer,46,Business travel,Business,1162,4,4,4,4,4,2,4,5,5,5,5,4,5,3,38,27.0,satisfied +100508,113601,Female,Loyal Customer,55,Business travel,Eco,197,4,5,5,5,2,1,4,4,4,4,4,4,4,2,0,0.0,satisfied +100509,124601,Female,Loyal Customer,49,Personal Travel,Eco,500,4,5,2,2,1,3,2,1,1,2,1,3,1,2,38,32.0,neutral or dissatisfied +100510,78335,Male,Loyal Customer,49,Business travel,Eco,1547,2,1,1,1,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +100511,47300,Female,Loyal Customer,35,Business travel,Eco,588,1,5,5,5,1,1,1,1,1,2,4,4,3,1,0,0.0,neutral or dissatisfied +100512,124735,Male,Loyal Customer,13,Personal Travel,Eco,399,3,4,3,3,3,3,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +100513,111116,Female,Loyal Customer,52,Business travel,Business,2119,3,3,3,3,2,5,5,5,5,5,5,4,5,5,39,24.0,satisfied +100514,56581,Male,Loyal Customer,56,Business travel,Business,997,3,3,3,3,4,5,5,5,5,5,5,5,5,5,25,17.0,satisfied +100515,89879,Female,disloyal Customer,11,Business travel,Eco,1416,4,4,4,3,5,4,5,5,3,3,3,1,4,5,0,14.0,neutral or dissatisfied +100516,118826,Female,disloyal Customer,23,Business travel,Eco,325,3,1,3,2,2,3,2,2,2,2,3,2,2,2,35,39.0,neutral or dissatisfied +100517,91762,Male,Loyal Customer,54,Business travel,Business,3144,2,5,5,5,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +100518,24823,Male,Loyal Customer,48,Business travel,Business,3263,5,5,5,5,5,4,4,3,3,3,3,3,3,4,2,0.0,satisfied +100519,32518,Male,disloyal Customer,56,Business travel,Eco,101,3,2,3,4,3,3,3,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +100520,122939,Male,disloyal Customer,24,Business travel,Eco,600,3,0,3,1,2,3,2,2,5,5,5,4,4,2,32,56.0,neutral or dissatisfied +100521,35429,Male,Loyal Customer,32,Personal Travel,Eco,1069,2,4,2,2,5,2,5,5,3,1,1,4,3,5,50,55.0,neutral or dissatisfied +100522,61805,Male,Loyal Customer,26,Personal Travel,Eco,1303,2,4,1,5,3,1,3,3,3,2,3,4,5,3,0,0.0,neutral or dissatisfied +100523,8760,Female,Loyal Customer,33,Personal Travel,Eco,1147,0,5,0,5,5,0,5,5,5,2,5,5,4,5,0,0.0,satisfied +100524,48407,Female,Loyal Customer,54,Business travel,Business,3612,1,1,1,1,5,4,4,2,2,2,2,3,2,4,0,7.0,satisfied +100525,72498,Male,disloyal Customer,20,Business travel,Business,1121,4,0,4,3,2,4,2,2,5,4,4,4,5,2,0,10.0,satisfied +100526,106909,Male,Loyal Customer,49,Business travel,Business,2864,2,2,2,2,3,5,5,5,5,5,5,5,5,4,0,4.0,satisfied +100527,97091,Male,Loyal Customer,50,Business travel,Business,1390,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,10.0,satisfied +100528,65789,Female,Loyal Customer,47,Business travel,Business,1389,5,5,5,5,2,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +100529,112019,Female,Loyal Customer,24,Business travel,Business,2333,5,5,4,5,4,4,4,4,3,4,4,5,5,4,17,6.0,satisfied +100530,22176,Male,Loyal Customer,31,Business travel,Business,533,2,2,2,2,5,5,5,5,1,1,4,3,4,5,0,0.0,satisfied +100531,108005,Male,Loyal Customer,60,Personal Travel,Eco,271,3,1,2,2,1,2,1,1,2,3,2,1,2,1,36,21.0,neutral or dissatisfied +100532,110045,Male,Loyal Customer,62,Business travel,Business,2039,2,4,4,4,3,1,2,2,2,2,2,4,2,4,5,25.0,neutral or dissatisfied +100533,76716,Female,Loyal Customer,28,Business travel,Eco Plus,481,4,1,1,1,4,4,4,4,1,1,3,4,2,4,0,0.0,neutral or dissatisfied +100534,14212,Female,Loyal Customer,61,Personal Travel,Eco,526,4,5,4,4,4,4,4,1,1,4,1,4,1,5,0,0.0,satisfied +100535,104585,Male,Loyal Customer,60,Business travel,Business,369,5,5,5,5,3,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +100536,70842,Male,Loyal Customer,43,Business travel,Business,2484,4,4,4,4,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +100537,17632,Female,disloyal Customer,22,Business travel,Eco,980,4,4,4,3,2,4,2,2,4,4,3,5,3,2,0,0.0,neutral or dissatisfied +100538,64212,Male,Loyal Customer,47,Business travel,Business,1660,1,1,1,1,2,5,4,4,4,4,4,5,4,5,0,4.0,satisfied +100539,15873,Male,Loyal Customer,31,Business travel,Business,3720,3,1,1,1,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +100540,70326,Male,Loyal Customer,39,Business travel,Business,986,5,5,1,5,4,4,4,3,3,3,3,4,3,4,0,17.0,satisfied +100541,60015,Female,Loyal Customer,19,Personal Travel,Eco,997,1,4,1,4,3,1,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +100542,97970,Male,Loyal Customer,8,Personal Travel,Eco,483,3,1,3,3,2,3,2,2,3,4,2,2,3,2,16,7.0,neutral or dissatisfied +100543,66377,Male,Loyal Customer,23,Business travel,Business,1562,2,2,3,2,4,4,4,4,3,2,4,3,5,4,3,47.0,satisfied +100544,20389,Male,disloyal Customer,33,Business travel,Eco,588,2,0,2,3,4,2,2,4,4,3,5,1,2,4,36,28.0,neutral or dissatisfied +100545,49692,Male,disloyal Customer,42,Business travel,Business,363,2,2,2,1,5,2,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +100546,55454,Male,Loyal Customer,38,Personal Travel,Business,2327,2,4,2,3,3,5,5,3,3,2,3,3,3,4,1,0.0,neutral or dissatisfied +100547,75781,Female,Loyal Customer,58,Personal Travel,Eco,868,5,1,5,4,4,4,4,5,5,5,5,2,5,1,3,0.0,satisfied +100548,53069,Female,Loyal Customer,39,Personal Travel,Eco,1190,3,5,3,3,4,3,4,4,5,4,3,5,5,4,0,2.0,neutral or dissatisfied +100549,4466,Male,Loyal Customer,56,Business travel,Business,605,1,1,1,1,2,2,1,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +100550,32566,Male,disloyal Customer,33,Business travel,Eco,101,3,2,3,4,1,3,1,1,2,5,4,1,4,1,0,0.0,neutral or dissatisfied +100551,128620,Male,Loyal Customer,45,Business travel,Business,679,4,4,4,4,4,4,5,5,5,5,5,3,5,3,2,0.0,satisfied +100552,66439,Male,Loyal Customer,32,Business travel,Business,2053,5,5,5,5,4,4,4,4,5,2,5,3,4,4,41,31.0,satisfied +100553,39848,Female,Loyal Customer,21,Business travel,Eco,272,0,5,0,4,5,0,3,5,5,5,5,3,5,5,0,1.0,satisfied +100554,55315,Female,Loyal Customer,58,Business travel,Business,1325,1,0,0,3,1,4,3,5,5,0,5,4,5,1,3,11.0,neutral or dissatisfied +100555,91161,Male,Loyal Customer,12,Personal Travel,Eco,594,4,2,4,4,2,4,2,2,1,2,3,1,4,2,20,11.0,neutral or dissatisfied +100556,53299,Male,Loyal Customer,11,Business travel,Business,758,2,5,5,5,2,2,2,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +100557,93511,Female,Loyal Customer,29,Business travel,Eco Plus,1107,2,5,2,5,2,2,2,2,4,4,3,4,4,2,10,0.0,neutral or dissatisfied +100558,23531,Male,Loyal Customer,59,Business travel,Business,3965,1,1,2,1,2,5,3,4,4,4,4,2,4,1,0,0.0,satisfied +100559,113781,Female,Loyal Customer,50,Business travel,Business,414,4,4,4,4,5,5,5,4,4,4,4,4,4,4,65,48.0,satisfied +100560,79835,Female,Loyal Customer,45,Business travel,Business,3077,2,2,2,2,3,4,4,4,4,4,4,5,4,3,0,12.0,satisfied +100561,46417,Female,disloyal Customer,24,Business travel,Business,649,5,0,5,2,1,5,1,1,2,1,2,3,2,1,8,7.0,satisfied +100562,37415,Male,Loyal Customer,44,Business travel,Eco,950,5,1,1,1,5,5,5,5,3,4,4,3,2,5,44,39.0,satisfied +100563,57339,Male,disloyal Customer,36,Business travel,Business,236,2,2,2,4,2,2,2,2,3,1,4,3,4,2,0,0.0,neutral or dissatisfied +100564,12029,Male,disloyal Customer,42,Business travel,Business,351,3,3,3,4,2,3,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +100565,111823,Female,Loyal Customer,33,Business travel,Business,1605,3,3,3,3,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +100566,51529,Male,Loyal Customer,45,Business travel,Eco,451,4,2,2,2,4,4,4,4,5,5,1,5,1,4,0,0.0,satisfied +100567,82971,Female,Loyal Customer,54,Business travel,Business,2800,5,5,5,5,4,4,4,3,3,3,3,5,3,4,26,6.0,satisfied +100568,26398,Male,Loyal Customer,33,Business travel,Business,3669,3,3,3,3,5,5,5,5,5,1,3,1,1,5,0,0.0,satisfied +100569,99222,Male,disloyal Customer,28,Business travel,Eco,495,3,0,3,3,2,3,2,2,3,2,4,1,4,2,0,8.0,neutral or dissatisfied +100570,117844,Female,Loyal Customer,60,Business travel,Business,2133,3,3,3,3,2,3,5,4,4,4,4,3,4,4,1,3.0,satisfied +100571,11508,Male,Loyal Customer,17,Personal Travel,Eco Plus,140,2,3,2,2,3,2,3,3,2,4,3,1,2,3,123,124.0,neutral or dissatisfied +100572,4414,Male,disloyal Customer,29,Business travel,Business,762,5,5,5,5,4,5,4,4,5,5,5,4,5,4,0,0.0,satisfied +100573,123436,Female,Loyal Customer,45,Business travel,Business,2296,3,3,3,3,2,2,2,5,5,5,5,2,3,2,0,4.0,satisfied +100574,14031,Male,Loyal Customer,27,Business travel,Business,1117,2,4,4,4,2,2,2,2,1,1,3,2,3,2,49,19.0,neutral or dissatisfied +100575,42034,Female,Loyal Customer,31,Business travel,Eco,106,3,1,1,1,3,2,3,3,1,2,2,3,3,3,0,4.0,neutral or dissatisfied +100576,4043,Female,Loyal Customer,37,Business travel,Eco,419,3,4,3,3,3,3,3,3,1,2,4,4,4,3,9,12.0,neutral or dissatisfied +100577,16230,Female,Loyal Customer,38,Business travel,Business,266,2,4,4,4,2,3,4,2,2,2,2,3,2,1,0,24.0,neutral or dissatisfied +100578,18762,Male,Loyal Customer,16,Personal Travel,Eco,837,2,5,2,5,1,2,1,1,5,2,4,4,4,1,1,14.0,neutral or dissatisfied +100579,99148,Female,Loyal Customer,60,Personal Travel,Eco Plus,419,2,3,2,5,3,5,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +100580,41555,Female,disloyal Customer,43,Business travel,Eco,715,1,1,1,3,5,1,5,5,2,5,1,3,3,5,5,5.0,neutral or dissatisfied +100581,74230,Female,Loyal Customer,41,Business travel,Business,888,3,3,3,3,4,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +100582,107294,Male,Loyal Customer,41,Business travel,Eco,283,3,3,3,3,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +100583,7352,Male,disloyal Customer,47,Business travel,Business,864,4,4,4,2,3,4,3,3,3,2,4,5,4,3,0,0.0,satisfied +100584,103419,Male,Loyal Customer,49,Personal Travel,Eco,237,3,4,3,4,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +100585,49892,Female,Loyal Customer,18,Business travel,Business,308,2,1,1,1,2,2,2,2,2,5,4,3,4,2,0,0.0,neutral or dissatisfied +100586,87340,Male,Loyal Customer,52,Business travel,Business,425,3,3,3,3,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +100587,31630,Female,Loyal Customer,48,Business travel,Business,3642,1,1,1,1,3,1,5,4,4,4,4,5,4,2,0,0.0,satisfied +100588,1579,Male,disloyal Customer,23,Business travel,Eco,237,2,3,2,4,4,2,4,4,4,2,3,4,4,4,24,29.0,neutral or dissatisfied +100589,94940,Male,Loyal Customer,42,Business travel,Business,3003,3,3,3,3,5,3,4,5,5,5,3,5,5,4,29,14.0,satisfied +100590,59301,Female,Loyal Customer,42,Business travel,Business,2367,3,3,3,3,3,3,5,4,4,4,4,3,4,3,26,3.0,satisfied +100591,19912,Male,disloyal Customer,39,Business travel,Eco,240,2,3,2,3,2,3,3,4,1,4,4,3,4,3,148,128.0,neutral or dissatisfied +100592,89708,Female,Loyal Customer,38,Personal Travel,Eco,950,2,5,2,3,3,2,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +100593,42601,Female,Loyal Customer,42,Business travel,Eco,866,3,4,4,4,1,3,4,3,3,3,3,4,3,1,32,26.0,neutral or dissatisfied +100594,75036,Male,Loyal Customer,43,Personal Travel,Eco,236,4,4,4,2,3,4,3,3,5,3,5,4,4,3,11,3.0,satisfied +100595,129831,Female,Loyal Customer,28,Personal Travel,Eco,447,1,3,1,5,3,1,3,3,1,1,4,1,5,3,23,16.0,neutral or dissatisfied +100596,61074,Female,Loyal Customer,59,Business travel,Business,1546,4,3,3,3,4,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +100597,19634,Female,disloyal Customer,25,Business travel,Eco,642,0,2,0,3,2,0,2,2,5,2,4,4,4,2,0,0.0,satisfied +100598,74010,Female,Loyal Customer,45,Business travel,Business,1471,1,3,3,3,4,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +100599,4535,Male,disloyal Customer,26,Business travel,Business,677,3,3,3,3,4,3,4,4,5,2,4,5,5,4,0,13.0,neutral or dissatisfied +100600,108015,Female,Loyal Customer,41,Business travel,Eco,589,2,3,3,3,1,2,1,1,2,3,3,3,3,1,11,1.0,neutral or dissatisfied +100601,127749,Male,Loyal Customer,34,Business travel,Business,2689,1,1,1,1,5,5,1,4,4,4,4,1,4,3,0,0.0,satisfied +100602,83686,Male,Loyal Customer,32,Business travel,Business,577,2,1,1,1,2,2,2,2,4,2,4,3,4,2,0,7.0,neutral or dissatisfied +100603,94675,Male,Loyal Customer,56,Business travel,Business,3226,0,4,1,4,5,5,5,1,1,1,1,4,1,4,38,41.0,satisfied +100604,12143,Male,disloyal Customer,31,Business travel,Eco,1042,1,1,1,1,4,1,4,4,5,5,2,5,1,4,6,0.0,neutral or dissatisfied +100605,116892,Female,Loyal Customer,51,Business travel,Business,3886,0,0,0,3,5,4,5,5,5,5,5,3,5,5,9,0.0,satisfied +100606,96339,Male,Loyal Customer,26,Business travel,Business,1609,5,5,3,5,5,5,5,5,3,4,4,3,4,5,34,5.0,satisfied +100607,62667,Female,Loyal Customer,57,Business travel,Business,1846,5,5,4,5,5,5,4,5,5,5,5,5,5,4,32,48.0,satisfied +100608,117422,Male,disloyal Customer,26,Business travel,Business,1460,2,2,2,5,4,2,4,4,4,2,4,5,5,4,13,20.0,neutral or dissatisfied +100609,48820,Male,Loyal Customer,68,Personal Travel,Business,209,4,5,4,3,3,5,2,4,4,4,4,4,4,5,0,1.0,satisfied +100610,58390,Female,disloyal Customer,30,Business travel,Business,733,4,4,4,2,5,4,5,5,4,3,4,3,4,5,36,29.0,satisfied +100611,101139,Female,Loyal Customer,60,Business travel,Business,2117,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +100612,23230,Female,Loyal Customer,71,Business travel,Business,3064,1,3,3,3,5,3,3,2,2,2,1,3,2,1,0,0.0,neutral or dissatisfied +100613,48499,Female,Loyal Customer,42,Business travel,Eco,833,2,5,5,5,4,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +100614,50798,Female,disloyal Customer,60,Personal Travel,Eco,250,3,3,3,2,2,3,1,2,3,3,3,1,3,2,2,3.0,neutral or dissatisfied +100615,102315,Female,Loyal Customer,33,Business travel,Business,3381,1,2,2,2,4,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +100616,120343,Female,Loyal Customer,50,Business travel,Business,366,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +100617,42276,Male,Loyal Customer,40,Business travel,Business,550,1,1,1,1,3,1,5,4,4,4,4,2,4,3,0,2.0,satisfied +100618,127818,Female,Loyal Customer,40,Business travel,Business,3407,3,2,1,2,4,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +100619,77507,Male,Loyal Customer,48,Personal Travel,Eco Plus,989,2,5,2,4,1,2,3,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +100620,81041,Female,Loyal Customer,28,Business travel,Business,2252,3,4,4,4,3,3,3,3,1,2,4,3,3,3,0,0.0,neutral or dissatisfied +100621,111716,Female,Loyal Customer,49,Personal Travel,Eco,541,3,5,3,3,3,5,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +100622,51921,Female,disloyal Customer,29,Business travel,Eco Plus,507,4,4,4,3,3,4,3,3,5,4,2,2,3,3,0,0.0,neutral or dissatisfied +100623,89035,Female,Loyal Customer,27,Business travel,Business,1947,3,3,3,3,3,2,3,3,4,2,3,4,5,3,3,0.0,satisfied +100624,18939,Male,Loyal Customer,44,Personal Travel,Eco,448,1,5,1,1,1,1,1,1,5,3,4,4,5,1,0,8.0,neutral or dissatisfied +100625,58922,Female,Loyal Customer,24,Personal Travel,Eco,888,2,5,2,5,4,2,4,4,2,2,5,5,4,4,29,30.0,neutral or dissatisfied +100626,81620,Female,Loyal Customer,52,Business travel,Business,1509,3,3,3,3,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +100627,119670,Male,Loyal Customer,33,Personal Travel,Eco,507,2,1,2,2,1,2,1,1,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +100628,34090,Female,Loyal Customer,27,Business travel,Business,1129,5,5,5,5,5,5,5,5,3,5,4,5,5,5,0,0.0,satisfied +100629,2828,Female,Loyal Customer,37,Business travel,Business,2620,1,1,1,1,2,5,4,2,2,2,2,5,2,4,0,25.0,satisfied +100630,19860,Male,Loyal Customer,50,Business travel,Eco,185,4,1,1,1,4,4,4,4,1,4,3,5,4,4,2,0.0,satisfied +100631,3199,Female,Loyal Customer,53,Personal Travel,Eco,693,3,4,3,5,2,4,5,5,5,3,5,4,5,3,46,70.0,neutral or dissatisfied +100632,88659,Male,Loyal Customer,66,Personal Travel,Eco,404,1,4,1,3,4,1,4,4,3,4,4,3,4,4,1,2.0,neutral or dissatisfied +100633,67095,Male,Loyal Customer,57,Business travel,Eco,964,2,4,3,3,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +100634,118257,Male,disloyal Customer,17,Business travel,Eco,935,2,1,1,4,4,2,4,4,5,3,5,4,4,4,2,0.0,satisfied +100635,47837,Male,disloyal Customer,38,Business travel,Eco,838,1,1,1,3,2,1,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +100636,116588,Male,Loyal Customer,55,Business travel,Business,337,3,3,3,3,5,4,4,3,3,4,3,4,3,4,3,5.0,satisfied +100637,10213,Female,Loyal Customer,55,Business travel,Business,163,2,2,2,2,4,4,4,5,5,5,4,5,5,3,0,0.0,satisfied +100638,94930,Female,Loyal Customer,58,Business travel,Business,3712,4,5,3,5,3,4,3,3,3,3,4,1,3,4,90,88.0,neutral or dissatisfied +100639,119611,Female,Loyal Customer,59,Personal Travel,Eco,1979,3,5,3,3,5,5,5,5,5,3,5,2,5,5,0,0.0,neutral or dissatisfied +100640,35493,Female,Loyal Customer,67,Personal Travel,Eco,950,2,1,2,4,1,2,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +100641,41425,Female,Loyal Customer,54,Personal Travel,Eco,641,1,3,0,3,3,3,3,5,5,0,5,1,5,4,10,0.0,neutral or dissatisfied +100642,61937,Female,Loyal Customer,9,Personal Travel,Eco Plus,550,4,1,4,4,2,4,3,2,2,1,2,1,4,2,2,0.0,neutral or dissatisfied +100643,35743,Female,disloyal Customer,21,Business travel,Business,653,2,1,2,4,4,2,4,4,1,2,3,1,4,4,0,0.0,neutral or dissatisfied +100644,22171,Male,Loyal Customer,36,Business travel,Business,533,2,1,1,1,1,2,1,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +100645,73110,Male,Loyal Customer,41,Business travel,Eco,2174,2,5,2,5,2,2,2,2,3,2,3,3,3,2,7,5.0,neutral or dissatisfied +100646,22465,Male,Loyal Customer,53,Personal Travel,Eco,143,2,4,2,3,5,2,5,5,4,2,4,5,3,5,0,0.0,neutral or dissatisfied +100647,116681,Male,Loyal Customer,49,Business travel,Business,3663,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +100648,32425,Male,Loyal Customer,28,Business travel,Eco,216,2,5,5,5,2,2,2,2,4,5,3,1,4,2,0,0.0,neutral or dissatisfied +100649,59753,Male,Loyal Customer,56,Business travel,Business,2120,1,3,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +100650,82249,Female,Loyal Customer,60,Personal Travel,Eco Plus,405,2,3,3,1,1,2,3,5,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +100651,72506,Female,Loyal Customer,29,Business travel,Business,1780,2,1,5,1,2,2,2,2,1,4,4,3,3,2,0,0.0,neutral or dissatisfied +100652,1525,Female,Loyal Customer,42,Business travel,Business,1740,4,4,4,4,2,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +100653,102508,Male,Loyal Customer,54,Personal Travel,Eco,407,0,4,0,3,5,0,4,5,3,3,5,5,1,5,10,0.0,satisfied +100654,56486,Female,Loyal Customer,53,Personal Travel,Eco,746,3,5,3,4,5,5,4,5,5,3,5,4,5,3,0,9.0,neutral or dissatisfied +100655,76974,Male,Loyal Customer,28,Business travel,Business,1969,4,4,3,4,5,5,5,5,5,3,4,5,4,5,0,0.0,satisfied +100656,121941,Female,Loyal Customer,60,Business travel,Business,430,4,5,5,5,3,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +100657,24120,Male,Loyal Customer,42,Personal Travel,Eco,584,2,5,2,4,3,2,4,3,5,5,5,3,4,3,12,38.0,neutral or dissatisfied +100658,10922,Female,Loyal Customer,35,Business travel,Business,191,0,4,0,3,3,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +100659,58082,Male,Loyal Customer,40,Business travel,Eco,589,2,5,5,5,2,2,2,2,4,4,4,2,2,2,250,258.0,neutral or dissatisfied +100660,25550,Female,Loyal Customer,22,Business travel,Eco Plus,481,4,2,2,2,4,4,4,4,3,2,3,3,5,4,0,0.0,satisfied +100661,111591,Female,Loyal Customer,23,Personal Travel,Eco,794,3,5,3,5,2,3,2,2,3,3,4,3,4,2,7,3.0,neutral or dissatisfied +100662,25742,Female,Loyal Customer,51,Personal Travel,Eco Plus,528,2,5,2,1,4,4,5,1,1,2,1,3,1,4,0,1.0,neutral or dissatisfied +100663,66515,Female,Loyal Customer,10,Personal Travel,Eco,447,3,4,3,2,3,3,1,3,3,3,5,4,4,3,2,0.0,neutral or dissatisfied +100664,56633,Male,Loyal Customer,43,Business travel,Business,2927,2,3,3,3,5,4,3,2,2,2,2,4,2,2,33,27.0,neutral or dissatisfied +100665,128047,Male,Loyal Customer,55,Business travel,Business,2542,5,3,5,5,2,5,5,4,4,4,4,5,4,5,0,8.0,satisfied +100666,100941,Female,Loyal Customer,51,Business travel,Business,2294,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +100667,84031,Male,Loyal Customer,25,Personal Travel,Eco Plus,321,4,5,4,3,4,4,5,4,3,2,4,1,4,4,82,70.0,neutral or dissatisfied +100668,30614,Female,disloyal Customer,28,Business travel,Eco Plus,472,0,0,0,1,3,0,3,3,3,3,4,2,2,3,0,0.0,satisfied +100669,121699,Female,Loyal Customer,44,Business travel,Business,283,0,0,0,1,3,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +100670,60461,Male,disloyal Customer,26,Business travel,Business,985,2,2,2,2,1,2,2,1,4,3,4,3,4,1,0,18.0,neutral or dissatisfied +100671,34175,Male,Loyal Customer,38,Business travel,Business,2563,5,5,5,5,2,3,3,5,5,5,5,1,5,3,0,0.0,satisfied +100672,8434,Female,Loyal Customer,37,Personal Travel,Eco,862,1,5,1,1,4,1,1,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +100673,126977,Male,Loyal Customer,49,Business travel,Business,304,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +100674,9872,Female,Loyal Customer,43,Business travel,Business,508,5,5,5,5,4,5,4,4,4,4,4,4,4,5,7,7.0,satisfied +100675,53142,Male,Loyal Customer,21,Personal Travel,Eco,413,5,5,5,4,3,5,3,3,5,2,5,3,5,3,0,0.0,satisfied +100676,54751,Male,Loyal Customer,23,Personal Travel,Eco,964,3,4,3,3,5,3,5,5,2,4,3,1,3,5,13,9.0,neutral or dissatisfied +100677,33964,Male,Loyal Customer,33,Business travel,Business,1598,4,1,4,4,3,4,3,3,4,3,4,4,5,3,0,0.0,satisfied +100678,34004,Male,Loyal Customer,69,Business travel,Business,1576,2,3,3,3,3,2,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +100679,59443,Male,Loyal Customer,46,Personal Travel,Eco,606,4,4,4,5,3,4,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +100680,4628,Male,Loyal Customer,60,Business travel,Business,3805,1,1,1,1,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +100681,19937,Female,Loyal Customer,10,Personal Travel,Eco,315,3,5,3,2,4,3,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +100682,35764,Male,Loyal Customer,38,Business travel,Business,200,5,5,5,5,5,5,5,3,1,5,3,5,5,5,157,,satisfied +100683,14470,Female,Loyal Customer,7,Personal Travel,Eco,761,2,5,2,1,5,2,5,5,4,5,4,5,4,5,37,26.0,neutral or dissatisfied +100684,42989,Female,Loyal Customer,41,Business travel,Eco,236,5,5,5,5,5,5,5,5,4,5,1,3,2,5,0,4.0,satisfied +100685,124186,Female,Loyal Customer,40,Business travel,Business,2176,2,2,4,2,5,3,5,3,3,4,3,3,3,4,0,5.0,satisfied +100686,22944,Female,Loyal Customer,29,Business travel,Business,2694,3,5,5,5,3,4,3,3,2,4,3,1,4,3,27,17.0,neutral or dissatisfied +100687,16336,Male,Loyal Customer,34,Personal Travel,Eco,628,2,4,2,1,3,2,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +100688,50084,Female,disloyal Customer,58,Business travel,Eco,421,3,2,3,3,4,3,4,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +100689,7172,Female,Loyal Customer,43,Business travel,Business,2285,2,3,3,3,3,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +100690,88421,Male,Loyal Customer,51,Business travel,Business,3438,3,3,5,3,5,4,4,4,4,4,4,4,4,5,7,1.0,satisfied +100691,89515,Female,Loyal Customer,37,Business travel,Business,1010,5,3,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +100692,114963,Male,Loyal Customer,32,Business travel,Business,333,4,4,4,4,4,4,4,4,2,4,4,3,4,4,0,0.0,neutral or dissatisfied +100693,16326,Female,Loyal Customer,61,Business travel,Eco,228,5,2,2,2,1,2,5,5,5,5,5,3,5,1,0,0.0,satisfied +100694,48648,Male,Loyal Customer,49,Business travel,Business,156,5,5,5,5,3,4,5,5,5,5,4,4,5,3,78,81.0,satisfied +100695,88612,Female,Loyal Customer,10,Personal Travel,Eco,366,2,5,2,1,3,2,3,3,2,5,2,5,4,3,1,0.0,neutral or dissatisfied +100696,42970,Female,Loyal Customer,45,Business travel,Eco,391,4,3,3,3,4,1,4,4,4,4,4,4,4,5,1,0.0,satisfied +100697,7097,Male,Loyal Customer,36,Business travel,Eco,273,2,5,5,5,2,1,2,2,2,5,3,4,3,2,20,26.0,neutral or dissatisfied +100698,87821,Female,disloyal Customer,16,Business travel,Eco,214,1,2,1,3,2,1,2,2,3,2,4,1,3,2,9,9.0,neutral or dissatisfied +100699,66617,Male,Loyal Customer,44,Business travel,Business,978,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +100700,1863,Female,Loyal Customer,55,Business travel,Business,2039,5,5,5,5,3,5,5,5,5,5,5,3,5,5,0,6.0,satisfied +100701,29881,Female,Loyal Customer,59,Business travel,Eco,261,5,1,3,1,2,4,1,5,5,5,5,5,5,4,0,0.0,satisfied +100702,58600,Male,Loyal Customer,8,Personal Travel,Eco,334,3,4,3,2,5,3,5,5,5,3,5,5,5,5,2,0.0,neutral or dissatisfied +100703,107251,Female,disloyal Customer,44,Business travel,Business,283,2,2,2,3,1,2,5,1,4,5,4,4,5,1,10,11.0,satisfied +100704,83788,Male,Loyal Customer,45,Business travel,Business,3877,2,2,2,2,5,4,4,4,4,4,4,4,4,3,5,0.0,satisfied +100705,72903,Male,Loyal Customer,54,Business travel,Business,1096,5,5,5,5,2,4,5,5,5,5,5,5,5,5,7,27.0,satisfied +100706,35645,Female,Loyal Customer,52,Business travel,Business,2586,1,1,1,1,4,4,4,3,3,3,5,4,5,4,123,164.0,satisfied +100707,24038,Female,Loyal Customer,56,Personal Travel,Eco,427,1,1,1,3,1,2,3,1,1,1,1,3,1,4,14,22.0,neutral or dissatisfied +100708,98310,Male,Loyal Customer,66,Personal Travel,Eco,1565,4,3,4,4,2,4,2,2,2,2,3,3,4,2,0,2.0,neutral or dissatisfied +100709,84148,Female,Loyal Customer,43,Business travel,Business,1355,4,4,4,4,5,5,5,3,3,4,3,3,3,5,20,0.0,satisfied +100710,58868,Male,disloyal Customer,21,Business travel,Business,888,5,3,5,1,3,3,3,3,3,4,5,5,4,3,70,91.0,satisfied +100711,95026,Female,Loyal Customer,19,Personal Travel,Eco,239,1,4,1,3,4,1,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +100712,85704,Female,Loyal Customer,29,Personal Travel,Eco,1547,3,3,3,2,4,3,4,4,1,4,2,4,3,4,1,0.0,neutral or dissatisfied +100713,7753,Male,Loyal Customer,64,Personal Travel,Eco,1013,4,4,3,3,4,3,4,4,4,4,3,1,3,4,7,19.0,neutral or dissatisfied +100714,123368,Female,disloyal Customer,29,Business travel,Business,644,4,3,3,4,3,3,2,3,5,3,5,5,4,3,1,0.0,satisfied +100715,38863,Female,Loyal Customer,31,Business travel,Business,2300,5,5,5,5,4,4,4,4,4,5,3,3,2,4,0,0.0,satisfied +100716,107936,Female,Loyal Customer,57,Business travel,Eco,611,2,5,5,5,3,3,3,2,2,2,2,2,2,4,21,21.0,neutral or dissatisfied +100717,11995,Female,Loyal Customer,69,Personal Travel,Eco,643,3,4,3,4,3,5,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +100718,17450,Male,Loyal Customer,66,Business travel,Eco Plus,351,2,3,3,3,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +100719,19117,Male,Loyal Customer,66,Business travel,Business,1679,4,1,1,1,2,4,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +100720,13504,Male,Loyal Customer,39,Business travel,Business,3292,4,4,4,4,3,4,1,5,5,5,4,1,5,3,0,0.0,satisfied +100721,2805,Female,Loyal Customer,48,Business travel,Business,3367,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +100722,108524,Male,Loyal Customer,52,Business travel,Business,3838,2,2,2,2,3,4,4,4,4,4,4,3,4,4,76,82.0,satisfied +100723,80776,Female,disloyal Customer,20,Business travel,Eco,692,5,5,5,2,5,4,5,5,4,2,4,4,5,5,18,16.0,satisfied +100724,27658,Male,Loyal Customer,48,Business travel,Business,3369,1,1,1,1,3,4,5,4,4,4,4,5,4,2,0,0.0,satisfied +100725,3542,Male,disloyal Customer,72,Business travel,Business,227,4,4,4,2,3,4,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +100726,64372,Female,Loyal Customer,65,Personal Travel,Eco,1192,4,2,4,3,2,2,2,2,2,4,2,1,2,1,4,0.0,satisfied +100727,55113,Female,Loyal Customer,10,Personal Travel,Eco,1379,3,3,3,1,5,3,5,5,3,5,5,5,2,5,25,0.0,neutral or dissatisfied +100728,15466,Male,Loyal Customer,54,Personal Travel,Eco,377,5,5,5,2,2,5,2,2,3,2,5,4,4,2,108,120.0,satisfied +100729,104915,Male,Loyal Customer,52,Business travel,Business,210,4,4,4,4,4,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +100730,9100,Male,Loyal Customer,57,Business travel,Business,3912,1,1,5,1,5,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +100731,95531,Male,Loyal Customer,24,Personal Travel,Eco Plus,192,3,4,0,3,5,0,5,5,5,2,5,3,5,5,30,12.0,neutral or dissatisfied +100732,91364,Male,Loyal Customer,41,Personal Travel,Eco Plus,515,2,1,2,3,2,4,4,3,3,3,3,4,3,4,190,182.0,neutral or dissatisfied +100733,111791,Male,Loyal Customer,60,Personal Travel,Eco Plus,1620,1,4,1,2,5,1,5,5,5,5,3,4,4,5,0,0.0,neutral or dissatisfied +100734,78038,Male,Loyal Customer,30,Personal Travel,Eco,214,2,0,2,3,2,2,2,2,5,3,5,3,5,2,21,25.0,neutral or dissatisfied +100735,111642,Male,Loyal Customer,33,Business travel,Business,1558,3,3,3,3,3,3,3,3,4,4,4,4,3,3,17,28.0,neutral or dissatisfied +100736,63129,Female,disloyal Customer,22,Business travel,Business,372,5,0,5,2,1,5,1,1,3,3,4,4,4,1,0,0.0,satisfied +100737,56450,Female,Loyal Customer,40,Personal Travel,Eco,719,3,4,3,1,1,3,1,1,3,5,5,5,5,1,12,0.0,neutral or dissatisfied +100738,43343,Female,Loyal Customer,77,Business travel,Business,387,3,5,5,5,3,4,3,3,3,3,3,2,3,1,0,2.0,neutral or dissatisfied +100739,77761,Female,disloyal Customer,19,Business travel,Eco,689,2,2,2,3,5,2,5,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +100740,107087,Male,Loyal Customer,47,Business travel,Business,2931,3,3,3,3,2,5,4,4,4,4,4,4,4,4,20,12.0,satisfied +100741,79566,Female,disloyal Customer,27,Business travel,Business,762,3,3,3,1,3,3,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +100742,1946,Female,Loyal Customer,35,Business travel,Business,2225,1,4,4,4,3,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +100743,1404,Male,Loyal Customer,7,Personal Travel,Eco Plus,482,1,5,1,4,2,1,1,2,1,4,2,4,4,2,0,0.0,neutral or dissatisfied +100744,96328,Female,Loyal Customer,65,Business travel,Business,3772,4,4,4,4,2,4,5,4,4,4,4,4,4,3,15,10.0,satisfied +100745,15433,Female,Loyal Customer,28,Business travel,Business,3357,3,5,5,5,3,3,3,3,4,5,3,4,3,3,4,0.0,neutral or dissatisfied +100746,94526,Male,Loyal Customer,58,Business travel,Business,2782,1,1,1,1,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +100747,9607,Female,Loyal Customer,59,Personal Travel,Eco,288,3,4,3,2,3,5,5,5,5,3,1,4,5,4,27,20.0,neutral or dissatisfied +100748,83468,Male,Loyal Customer,28,Business travel,Eco,946,2,5,5,5,2,2,2,2,3,3,4,4,3,2,0,13.0,neutral or dissatisfied +100749,123395,Male,Loyal Customer,30,Business travel,Business,1337,5,5,5,5,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +100750,73165,Male,Loyal Customer,28,Personal Travel,Eco,1145,2,5,2,1,4,2,4,4,5,3,4,5,5,4,0,3.0,neutral or dissatisfied +100751,26155,Male,Loyal Customer,23,Business travel,Eco,404,4,4,4,4,4,4,5,4,1,4,2,2,1,4,11,16.0,satisfied +100752,55032,Female,Loyal Customer,51,Business travel,Business,1303,4,4,4,4,4,4,5,4,4,4,4,5,4,5,1,0.0,satisfied +100753,31121,Male,disloyal Customer,20,Business travel,Eco,991,1,1,1,1,5,1,5,5,5,1,5,1,1,5,0,9.0,neutral or dissatisfied +100754,63676,Female,disloyal Customer,24,Business travel,Eco,1047,5,0,0,1,4,0,4,4,4,2,4,4,4,4,0,0.0,satisfied +100755,75631,Female,Loyal Customer,16,Personal Travel,Eco Plus,337,3,2,3,4,1,3,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +100756,72109,Male,Loyal Customer,42,Business travel,Business,1982,2,2,2,2,2,5,4,5,5,5,5,4,5,4,60,56.0,satisfied +100757,76360,Male,Loyal Customer,48,Business travel,Business,1695,3,3,3,3,2,5,4,3,3,3,3,4,3,4,76,86.0,satisfied +100758,123799,Female,Loyal Customer,43,Business travel,Business,3141,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +100759,115261,Male,disloyal Customer,23,Business travel,Eco,337,3,2,4,3,5,4,5,5,2,4,2,3,3,5,47,31.0,neutral or dissatisfied +100760,101995,Female,Loyal Customer,68,Personal Travel,Eco,628,3,5,3,4,5,5,5,3,3,3,3,4,3,3,21,26.0,neutral or dissatisfied +100761,83426,Female,Loyal Customer,64,Personal Travel,Eco,632,2,5,2,5,5,4,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +100762,31905,Female,Loyal Customer,49,Business travel,Business,2045,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +100763,80346,Male,Loyal Customer,50,Business travel,Business,368,3,2,2,2,5,3,4,3,3,3,3,1,3,3,0,2.0,neutral or dissatisfied +100764,87441,Male,Loyal Customer,46,Business travel,Business,1648,0,0,0,2,3,5,5,4,4,4,4,3,4,5,21,18.0,satisfied +100765,5274,Female,Loyal Customer,24,Personal Travel,Eco,190,4,5,0,1,2,0,5,2,3,4,4,4,5,2,0,0.0,satisfied +100766,15070,Female,Loyal Customer,23,Business travel,Eco Plus,488,4,5,5,5,4,5,4,4,5,4,1,5,1,4,0,62.0,satisfied +100767,40183,Male,Loyal Customer,36,Business travel,Business,3147,5,5,5,5,4,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +100768,49193,Male,Loyal Customer,40,Business travel,Business,373,5,5,5,5,3,2,3,5,5,4,5,1,5,1,0,24.0,satisfied +100769,82678,Female,Loyal Customer,48,Business travel,Business,632,2,2,2,2,5,4,4,3,3,4,3,4,3,3,0,0.0,satisfied +100770,25999,Male,Loyal Customer,47,Business travel,Eco Plus,577,5,2,2,2,5,5,5,5,5,1,3,2,2,5,0,0.0,satisfied +100771,112531,Male,Loyal Customer,17,Personal Travel,Eco,957,4,4,4,1,5,4,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +100772,75288,Male,Loyal Customer,56,Business travel,Business,1652,4,4,4,4,5,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +100773,42647,Male,Loyal Customer,29,Personal Travel,Eco,481,3,2,3,4,5,3,4,5,4,2,3,1,3,5,0,13.0,neutral or dissatisfied +100774,84698,Female,Loyal Customer,56,Personal Travel,Eco Plus,2182,3,3,3,2,2,3,3,1,1,3,1,1,1,3,39,45.0,neutral or dissatisfied +100775,82666,Female,Loyal Customer,28,Personal Travel,Eco,120,4,5,0,4,2,0,2,2,1,4,4,2,3,2,0,1.0,satisfied +100776,89394,Female,disloyal Customer,27,Business travel,Eco,151,3,2,2,2,3,2,3,3,2,5,3,1,2,3,0,0.0,neutral or dissatisfied +100777,61624,Male,Loyal Customer,40,Business travel,Business,1608,4,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +100778,22890,Male,Loyal Customer,45,Personal Travel,Eco,147,4,3,0,2,3,0,3,3,4,1,2,3,1,3,57,45.0,neutral or dissatisfied +100779,43163,Female,Loyal Customer,56,Business travel,Eco,840,2,4,4,4,5,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +100780,45069,Male,Loyal Customer,20,Personal Travel,Eco,323,2,2,2,3,3,2,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +100781,42617,Female,Loyal Customer,35,Business travel,Business,481,4,4,4,4,1,5,5,5,5,5,5,1,5,2,0,0.0,satisfied +100782,79154,Female,Loyal Customer,51,Personal Travel,Eco Plus,306,2,4,2,2,5,5,4,1,1,2,4,4,1,4,0,0.0,neutral or dissatisfied +100783,103180,Female,Loyal Customer,17,Personal Travel,Eco,491,1,3,1,3,1,1,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +100784,87738,Male,Loyal Customer,42,Business travel,Business,4502,5,5,5,5,2,2,2,4,4,4,5,2,5,2,4,4.0,satisfied +100785,114519,Female,Loyal Customer,45,Personal Travel,Business,446,4,4,4,4,3,4,4,1,1,4,1,5,1,5,20,30.0,neutral or dissatisfied +100786,107280,Male,disloyal Customer,65,Business travel,Business,307,1,1,1,3,5,1,2,5,4,5,5,5,5,5,26,18.0,neutral or dissatisfied +100787,85815,Female,Loyal Customer,7,Personal Travel,Eco,666,3,5,3,2,5,3,5,5,3,3,2,5,4,5,18,23.0,neutral or dissatisfied +100788,103336,Male,Loyal Customer,20,Personal Travel,Eco,1139,3,1,4,3,3,4,5,3,4,4,2,1,3,3,9,7.0,neutral or dissatisfied +100789,10384,Male,disloyal Customer,24,Business travel,Eco,301,4,0,4,3,1,4,1,1,5,2,5,5,5,1,0,0.0,satisfied +100790,115347,Male,disloyal Customer,36,Business travel,Business,446,4,4,4,1,5,4,5,5,3,2,5,5,5,5,19,13.0,neutral or dissatisfied +100791,67842,Female,Loyal Customer,67,Personal Travel,Eco,1235,5,0,5,1,2,4,5,4,4,5,4,5,4,4,4,0.0,satisfied +100792,50204,Female,Loyal Customer,34,Business travel,Eco,207,5,3,3,3,5,5,5,5,3,5,1,1,2,5,0,0.0,satisfied +100793,52529,Male,Loyal Customer,43,Business travel,Business,160,4,2,4,4,2,3,4,4,4,4,5,2,4,1,0,0.0,satisfied +100794,93644,Male,Loyal Customer,13,Personal Travel,Eco Plus,577,1,4,0,2,2,0,2,2,5,4,5,4,5,2,2,10.0,neutral or dissatisfied +100795,93092,Female,Loyal Customer,31,Personal Travel,Eco,860,3,4,3,3,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +100796,19407,Female,Loyal Customer,43,Business travel,Business,645,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +100797,112525,Male,Loyal Customer,65,Personal Travel,Eco,862,3,4,3,1,2,3,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +100798,55433,Female,disloyal Customer,38,Business travel,Business,1134,5,5,5,3,5,3,3,3,5,4,5,3,4,3,65,81.0,satisfied +100799,9350,Male,Loyal Customer,53,Business travel,Business,441,1,1,5,1,4,5,4,5,5,4,5,3,5,3,0,0.0,satisfied +100800,125159,Female,Loyal Customer,39,Business travel,Business,3040,3,3,4,3,3,4,5,4,4,4,4,3,4,5,2,14.0,satisfied +100801,35113,Female,Loyal Customer,34,Business travel,Eco,1076,4,3,1,1,4,5,4,4,3,4,2,1,2,4,0,0.0,satisfied +100802,102942,Male,Loyal Customer,42,Business travel,Business,949,3,3,3,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +100803,56575,Female,Loyal Customer,46,Business travel,Business,1085,5,5,5,5,4,4,5,4,4,4,4,5,4,4,6,1.0,satisfied +100804,89104,Male,Loyal Customer,47,Business travel,Business,1919,3,3,3,3,5,5,4,5,5,5,5,3,5,5,3,5.0,satisfied +100805,78729,Male,Loyal Customer,55,Business travel,Business,3154,5,1,5,5,3,4,4,2,2,2,2,3,2,3,0,12.0,satisfied +100806,71565,Female,Loyal Customer,31,Business travel,Business,1197,3,4,4,4,3,3,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +100807,28512,Male,Loyal Customer,35,Business travel,Eco,2640,4,2,2,2,4,4,4,4,5,4,4,1,2,4,0,0.0,satisfied +100808,68606,Male,Loyal Customer,21,Personal Travel,Eco,1739,4,5,4,4,5,4,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +100809,84545,Male,Loyal Customer,12,Personal Travel,Eco,2556,3,5,3,3,1,3,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +100810,40101,Female,Loyal Customer,24,Business travel,Eco,368,3,5,5,5,3,3,2,3,2,5,4,4,4,3,0,0.0,neutral or dissatisfied +100811,40378,Male,disloyal Customer,75,Business travel,Eco,850,3,3,3,4,5,3,5,5,1,2,3,3,4,5,0,0.0,neutral or dissatisfied +100812,6918,Male,Loyal Customer,44,Personal Travel,Eco,265,3,1,3,2,4,3,4,4,1,1,1,1,3,4,0,0.0,neutral or dissatisfied +100813,79999,Female,Loyal Customer,10,Personal Travel,Eco,950,0,2,0,4,3,0,3,3,1,3,4,4,3,3,0,0.0,satisfied +100814,6035,Female,Loyal Customer,45,Business travel,Eco,1041,3,3,3,3,2,4,4,3,3,3,3,3,3,4,0,14.0,neutral or dissatisfied +100815,32042,Male,Loyal Customer,45,Business travel,Business,2306,4,4,4,4,4,1,1,5,5,5,5,3,5,4,0,0.0,satisfied +100816,1661,Male,disloyal Customer,26,Business travel,Eco,151,1,0,1,3,3,1,3,3,3,4,1,4,5,3,0,0.0,neutral or dissatisfied +100817,127038,Male,disloyal Customer,20,Business travel,Eco,304,4,3,4,5,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +100818,110950,Female,disloyal Customer,22,Business travel,Eco,404,2,2,2,4,5,2,5,5,2,5,3,1,4,5,11,10.0,neutral or dissatisfied +100819,129709,Male,Loyal Customer,39,Business travel,Business,447,2,1,3,3,1,3,3,2,2,2,2,2,2,1,40,43.0,neutral or dissatisfied +100820,31598,Male,Loyal Customer,64,Business travel,Business,202,3,1,1,1,4,4,3,2,2,1,3,2,2,2,5,10.0,neutral or dissatisfied +100821,121558,Female,disloyal Customer,21,Business travel,Eco,936,2,1,1,3,2,1,4,2,3,5,3,3,3,2,0,2.0,neutral or dissatisfied +100822,48036,Male,Loyal Customer,38,Business travel,Business,2873,2,4,4,4,4,4,3,2,2,2,2,1,2,2,35,21.0,neutral or dissatisfied +100823,84693,Male,Loyal Customer,32,Personal Travel,Eco,2182,5,4,5,4,2,5,2,2,3,3,4,1,3,2,0,0.0,satisfied +100824,41036,Female,disloyal Customer,13,Business travel,Eco,1086,2,2,2,3,3,2,3,3,1,1,5,2,3,3,0,2.0,neutral or dissatisfied +100825,7999,Female,disloyal Customer,23,Business travel,Eco,125,3,0,2,1,3,2,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +100826,12298,Male,Loyal Customer,52,Business travel,Business,253,2,2,2,2,5,5,1,5,5,5,5,3,5,4,0,5.0,satisfied +100827,79349,Female,Loyal Customer,62,Personal Travel,Eco,1020,4,2,5,3,3,1,2,5,5,5,5,4,5,1,4,0.0,satisfied +100828,86865,Male,Loyal Customer,62,Personal Travel,Eco,692,3,5,3,2,5,3,5,5,4,4,5,3,5,5,13,0.0,neutral or dissatisfied +100829,1546,Male,Loyal Customer,31,Personal Travel,Eco,987,3,1,2,3,5,2,5,5,3,4,3,2,4,5,0,9.0,neutral or dissatisfied +100830,16301,Male,Loyal Customer,44,Business travel,Business,2157,1,1,1,1,3,1,2,5,5,5,5,5,5,3,77,77.0,satisfied +100831,111086,Female,Loyal Customer,27,Personal Travel,Eco,268,3,1,3,3,4,3,4,4,2,1,3,2,4,4,8,10.0,neutral or dissatisfied +100832,109357,Male,Loyal Customer,19,Business travel,Business,3452,3,3,3,3,5,5,5,5,3,2,4,5,4,5,1,3.0,satisfied +100833,120951,Female,disloyal Customer,20,Business travel,Eco,861,1,1,1,3,4,1,4,4,4,5,3,1,3,4,36,51.0,neutral or dissatisfied +100834,56193,Male,Loyal Customer,13,Personal Travel,Eco,1504,1,3,1,5,5,1,5,5,3,3,1,1,1,5,0,0.0,neutral or dissatisfied +100835,124920,Female,Loyal Customer,39,Business travel,Business,328,0,0,0,1,4,3,1,1,1,1,1,3,1,1,4,8.0,satisfied +100836,33073,Female,Loyal Customer,53,Personal Travel,Eco,101,0,5,0,4,2,4,4,3,3,0,3,4,3,4,0,0.0,satisfied +100837,828,Female,Loyal Customer,61,Business travel,Business,396,4,4,4,4,3,4,5,4,4,4,4,5,4,4,13,2.0,satisfied +100838,36375,Male,Loyal Customer,63,Business travel,Business,200,3,2,2,2,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +100839,83003,Female,disloyal Customer,46,Business travel,Business,1084,3,3,3,4,4,3,4,4,5,2,5,3,5,4,6,26.0,neutral or dissatisfied +100840,60589,Male,Loyal Customer,34,Personal Travel,Eco,1558,1,5,2,4,5,2,5,5,4,2,4,5,5,5,6,0.0,neutral or dissatisfied +100841,120959,Male,Loyal Customer,44,Business travel,Eco,992,4,4,4,4,5,4,5,5,3,1,4,1,3,5,0,24.0,neutral or dissatisfied +100842,121481,Female,Loyal Customer,64,Personal Travel,Eco,331,2,4,2,1,1,1,1,4,4,2,4,1,4,5,1,2.0,neutral or dissatisfied +100843,35946,Female,Loyal Customer,59,Business travel,Business,231,5,5,5,5,2,1,1,4,4,4,4,3,4,5,0,0.0,satisfied +100844,72865,Female,Loyal Customer,69,Personal Travel,Eco,700,1,2,1,2,4,3,2,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +100845,89932,Male,disloyal Customer,47,Business travel,Eco,906,3,3,3,4,1,3,3,1,5,2,5,2,4,1,13,0.0,neutral or dissatisfied +100846,44292,Female,Loyal Customer,19,Personal Travel,Eco,1123,1,4,1,1,4,1,4,4,4,2,5,3,4,4,0,9.0,neutral or dissatisfied +100847,119242,Female,Loyal Customer,52,Business travel,Business,2708,1,1,1,1,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +100848,62427,Female,disloyal Customer,11,Business travel,Eco,1108,5,5,5,3,2,5,2,2,5,2,3,5,5,2,0,0.0,satisfied +100849,96435,Female,Loyal Customer,45,Business travel,Business,302,0,0,0,3,4,4,5,4,4,4,4,4,4,4,5,0.0,satisfied +100850,27184,Male,Loyal Customer,52,Personal Travel,Eco,2677,2,5,2,5,2,2,2,4,4,3,1,2,3,2,0,21.0,neutral or dissatisfied +100851,31172,Female,Loyal Customer,57,Business travel,Eco Plus,516,5,5,2,5,5,5,1,4,4,5,4,3,4,2,0,0.0,satisfied +100852,114249,Female,Loyal Customer,23,Business travel,Business,2814,3,3,3,3,3,3,3,3,1,4,3,1,3,3,0,0.0,neutral or dissatisfied +100853,55061,Female,Loyal Customer,16,Business travel,Business,1379,3,3,3,3,4,4,4,4,3,3,4,3,4,4,13,0.0,satisfied +100854,57128,Female,Loyal Customer,12,Personal Travel,Eco,1222,1,3,1,2,1,1,1,1,3,5,2,1,1,1,71,52.0,neutral or dissatisfied +100855,125447,Female,Loyal Customer,35,Business travel,Business,2860,2,2,2,2,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +100856,2223,Female,disloyal Customer,29,Business travel,Business,859,3,2,2,3,5,2,5,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +100857,22256,Female,Loyal Customer,39,Business travel,Business,208,2,2,2,2,4,4,2,5,5,5,5,2,5,1,2,23.0,satisfied +100858,63859,Female,Loyal Customer,59,Business travel,Business,2417,2,2,2,2,3,4,4,5,5,5,5,3,5,5,2,8.0,satisfied +100859,83893,Female,Loyal Customer,55,Business travel,Business,1450,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +100860,10846,Male,Loyal Customer,38,Business travel,Business,312,2,3,3,3,5,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +100861,97807,Male,Loyal Customer,8,Personal Travel,Business,395,2,5,2,4,5,2,5,5,5,4,5,4,5,5,2,0.0,neutral or dissatisfied +100862,63202,Male,disloyal Customer,39,Business travel,Business,372,3,3,3,3,3,3,3,3,4,3,5,3,5,3,26,21.0,satisfied +100863,77472,Female,Loyal Customer,62,Personal Travel,Eco,507,2,4,2,5,4,5,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +100864,97173,Male,Loyal Customer,17,Personal Travel,Eco,1390,3,1,3,3,5,3,5,5,1,1,3,4,3,5,4,0.0,neutral or dissatisfied +100865,26187,Male,Loyal Customer,47,Business travel,Business,581,3,3,3,3,5,3,1,5,5,5,5,1,5,5,0,0.0,satisfied +100866,46790,Female,disloyal Customer,29,Business travel,Business,776,2,2,2,4,1,2,1,1,2,4,4,4,4,1,35,45.0,neutral or dissatisfied +100867,115497,Male,Loyal Customer,33,Business travel,Business,1713,5,5,5,5,5,5,5,5,3,2,4,5,5,5,0,0.0,satisfied +100868,34732,Male,Loyal Customer,35,Business travel,Business,301,5,5,5,5,1,3,1,4,4,4,4,4,4,1,7,0.0,satisfied +100869,110000,Male,Loyal Customer,29,Business travel,Business,1142,3,3,3,3,2,2,2,2,4,5,4,5,4,2,19,9.0,satisfied +100870,47699,Female,Loyal Customer,35,Personal Travel,Eco,1464,2,4,2,3,2,2,2,2,5,5,5,5,4,2,41,24.0,neutral or dissatisfied +100871,30101,Female,Loyal Customer,66,Personal Travel,Eco,261,2,4,0,3,4,3,3,5,5,0,5,1,5,2,0,0.0,neutral or dissatisfied +100872,18848,Female,Loyal Customer,39,Business travel,Eco,551,4,4,4,4,4,4,4,4,5,2,2,2,5,4,0,0.0,satisfied +100873,1078,Female,Loyal Customer,20,Personal Travel,Eco,102,4,3,4,1,3,4,3,3,1,3,5,5,4,3,3,0.0,neutral or dissatisfied +100874,74029,Female,disloyal Customer,29,Business travel,Eco,1471,1,1,1,4,4,1,4,4,2,2,4,1,4,4,0,0.0,neutral or dissatisfied +100875,47839,Male,Loyal Customer,25,Business travel,Business,1963,2,1,1,1,2,2,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +100876,88013,Female,Loyal Customer,41,Business travel,Business,2986,3,3,3,3,3,4,4,3,3,3,3,4,3,3,16,9.0,satisfied +100877,116137,Male,Loyal Customer,11,Personal Travel,Eco,333,1,5,1,5,2,1,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +100878,49417,Female,Loyal Customer,32,Business travel,Business,2685,4,1,4,4,5,5,5,5,1,4,4,1,3,5,34,26.0,satisfied +100879,84305,Male,Loyal Customer,58,Personal Travel,Eco,235,2,5,2,2,2,4,4,4,4,5,5,4,3,4,273,259.0,neutral or dissatisfied +100880,44988,Male,disloyal Customer,27,Business travel,Business,224,3,3,3,4,3,3,3,3,1,4,3,2,3,3,0,0.0,neutral or dissatisfied +100881,13728,Female,disloyal Customer,34,Business travel,Eco,401,2,0,1,4,5,1,5,5,4,2,4,4,3,5,116,105.0,neutral or dissatisfied +100882,75500,Female,Loyal Customer,40,Personal Travel,Eco Plus,2585,3,4,3,4,5,3,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +100883,20230,Female,Loyal Customer,37,Business travel,Business,3864,1,1,5,1,3,1,4,5,5,5,5,4,5,1,5,13.0,satisfied +100884,75865,Male,Loyal Customer,61,Business travel,Eco Plus,1040,2,5,5,5,2,2,2,2,5,4,2,3,1,2,0,0.0,satisfied +100885,12662,Female,Loyal Customer,28,Business travel,Business,2744,1,1,1,1,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +100886,41995,Female,Loyal Customer,31,Business travel,Eco,106,4,2,2,2,4,4,4,4,1,3,4,2,3,4,15,14.0,satisfied +100887,111612,Male,Loyal Customer,40,Business travel,Business,1014,1,1,2,1,3,4,4,4,4,4,4,4,4,4,21,14.0,satisfied +100888,90881,Male,Loyal Customer,58,Business travel,Eco,250,4,4,4,4,4,4,4,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +100889,54300,Male,Loyal Customer,25,Personal Travel,Eco,1075,5,4,4,3,3,4,2,3,5,2,5,5,5,3,0,0.0,satisfied +100890,10640,Female,Loyal Customer,55,Business travel,Business,295,0,0,0,3,5,4,4,1,1,1,1,4,1,5,10,15.0,satisfied +100891,7373,Female,Loyal Customer,22,Personal Travel,Eco,783,2,4,2,4,3,2,3,3,4,4,5,3,4,3,1,0.0,neutral or dissatisfied +100892,8326,Male,Loyal Customer,7,Personal Travel,Eco Plus,402,3,5,3,2,3,3,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +100893,15687,Female,Loyal Customer,61,Business travel,Eco,335,4,2,2,2,5,2,2,4,4,4,4,3,4,4,20,0.0,satisfied +100894,64991,Female,Loyal Customer,46,Business travel,Eco,190,2,5,5,5,2,2,2,1,5,3,3,2,4,2,122,143.0,neutral or dissatisfied +100895,47321,Female,Loyal Customer,53,Business travel,Business,501,2,4,4,4,4,4,4,2,2,2,2,2,2,1,0,1.0,neutral or dissatisfied +100896,67060,Male,disloyal Customer,10,Business travel,Business,985,4,4,4,4,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +100897,76549,Female,Loyal Customer,31,Business travel,Business,481,2,2,2,2,5,5,5,5,4,2,5,3,5,5,0,14.0,satisfied +100898,92468,Male,Loyal Customer,25,Business travel,Business,1892,2,2,2,2,2,2,2,2,1,5,3,3,4,2,0,0.0,neutral or dissatisfied +100899,38059,Male,Loyal Customer,38,Business travel,Business,1997,4,4,4,4,2,2,5,4,4,4,4,2,4,5,12,0.0,satisfied +100900,38667,Male,Loyal Customer,47,Personal Travel,Eco,2704,3,5,3,3,4,3,4,4,4,1,3,1,4,4,0,0.0,neutral or dissatisfied +100901,68866,Male,Loyal Customer,55,Business travel,Eco,1061,3,1,1,1,3,3,3,3,1,1,4,2,3,3,0,2.0,neutral or dissatisfied +100902,76037,Female,disloyal Customer,37,Business travel,Eco Plus,311,3,3,3,5,1,3,5,1,4,5,2,3,2,1,0,0.0,neutral or dissatisfied +100903,85858,Male,Loyal Customer,35,Personal Travel,Eco Plus,666,2,5,2,3,4,2,4,4,4,5,2,1,4,4,14,7.0,neutral or dissatisfied +100904,41021,Female,Loyal Customer,54,Business travel,Business,3425,1,5,1,1,1,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +100905,124588,Male,Loyal Customer,55,Business travel,Eco,500,4,2,2,2,4,4,4,4,3,4,4,1,4,4,8,6.0,neutral or dissatisfied +100906,28236,Female,disloyal Customer,21,Business travel,Eco,1009,2,2,2,1,2,2,2,2,1,1,4,1,2,2,0,0.0,neutral or dissatisfied +100907,113950,Male,Loyal Customer,41,Business travel,Business,1838,2,2,1,2,2,4,4,4,4,4,4,3,4,5,10,1.0,satisfied +100908,35160,Female,disloyal Customer,18,Business travel,Eco,1076,2,2,2,1,5,2,5,5,2,5,1,4,3,5,0,0.0,neutral or dissatisfied +100909,5921,Male,Loyal Customer,41,Personal Travel,Eco,67,2,2,2,2,2,3,3,3,5,1,2,3,2,3,314,352.0,neutral or dissatisfied +100910,38962,Male,Loyal Customer,57,Personal Travel,Business,313,2,5,2,1,4,4,5,5,5,2,5,3,5,4,5,0.0,neutral or dissatisfied +100911,110450,Male,Loyal Customer,55,Personal Travel,Eco,925,2,4,2,3,2,2,2,2,5,3,4,5,4,2,10,13.0,neutral or dissatisfied +100912,100935,Female,Loyal Customer,43,Business travel,Business,838,4,4,4,4,3,5,5,4,4,4,4,3,4,4,0,8.0,satisfied +100913,57325,Female,Loyal Customer,47,Business travel,Business,236,1,1,3,1,3,5,4,4,4,4,4,3,4,3,47,45.0,satisfied +100914,65468,Female,disloyal Customer,36,Business travel,Business,1303,4,4,4,5,5,4,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +100915,43430,Male,Loyal Customer,9,Business travel,Business,913,1,1,1,1,3,3,3,3,4,3,3,2,1,3,0,0.0,satisfied +100916,64993,Male,Loyal Customer,56,Business travel,Business,190,0,5,1,3,1,1,1,4,4,4,4,1,4,2,0,0.0,satisfied +100917,103537,Male,disloyal Customer,30,Business travel,Business,738,5,5,5,3,5,5,5,5,4,5,4,5,5,5,0,0.0,satisfied +100918,107380,Female,Loyal Customer,59,Business travel,Business,1938,3,3,3,3,2,5,5,4,4,4,4,5,4,4,5,0.0,satisfied +100919,64249,Male,Loyal Customer,16,Personal Travel,Eco,1660,3,4,3,1,4,3,4,4,3,3,5,4,5,4,0,3.0,neutral or dissatisfied +100920,50614,Male,Loyal Customer,19,Personal Travel,Eco,373,3,1,3,4,5,3,2,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +100921,18599,Female,Loyal Customer,31,Business travel,Business,2369,5,5,5,5,5,5,3,5,1,5,5,2,4,5,9,9.0,satisfied +100922,49253,Female,Loyal Customer,33,Business travel,Eco,262,5,3,3,3,5,5,5,5,3,5,3,5,4,5,0,0.0,satisfied +100923,69639,Female,Loyal Customer,41,Business travel,Business,3660,3,3,3,3,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +100924,32254,Female,Loyal Customer,56,Business travel,Business,2732,1,1,1,1,3,5,2,4,4,4,5,2,4,2,0,0.0,satisfied +100925,63864,Female,Loyal Customer,31,Business travel,Business,3364,2,2,2,2,2,2,2,2,2,5,3,4,2,2,0,0.0,neutral or dissatisfied +100926,100854,Female,Loyal Customer,44,Personal Travel,Eco,711,1,3,0,3,4,4,4,2,2,0,2,4,2,4,30,35.0,neutral or dissatisfied +100927,48099,Female,Loyal Customer,61,Business travel,Business,2169,3,3,3,3,1,2,1,5,5,5,5,5,5,4,0,0.0,satisfied +100928,66798,Female,Loyal Customer,32,Business travel,Eco Plus,3784,1,1,2,1,1,1,1,3,3,3,2,1,2,1,4,54.0,neutral or dissatisfied +100929,90801,Female,Loyal Customer,49,Business travel,Business,581,3,3,3,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +100930,120900,Female,disloyal Customer,43,Business travel,Business,1013,4,4,4,3,2,4,2,2,5,4,4,4,5,2,39,69.0,satisfied +100931,97488,Male,Loyal Customer,26,Business travel,Eco,670,2,2,2,2,2,2,1,2,2,3,3,1,3,2,2,1.0,neutral or dissatisfied +100932,81143,Male,disloyal Customer,49,Business travel,Business,1310,4,3,3,3,3,4,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +100933,85963,Female,Loyal Customer,41,Business travel,Business,447,4,4,4,4,5,4,4,3,3,4,3,5,3,4,0,4.0,satisfied +100934,120029,Female,Loyal Customer,40,Business travel,Business,328,5,5,5,5,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +100935,41436,Male,Loyal Customer,43,Personal Travel,Eco,641,1,5,1,3,4,1,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +100936,6260,Male,Loyal Customer,9,Personal Travel,Business,585,0,5,0,2,3,0,3,3,5,2,4,3,4,3,0,0.0,satisfied +100937,785,Male,disloyal Customer,40,Business travel,Business,270,4,4,4,4,4,4,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +100938,86639,Female,Loyal Customer,13,Business travel,Business,746,3,1,1,1,3,3,3,3,3,1,4,1,4,3,0,0.0,neutral or dissatisfied +100939,6467,Male,Loyal Customer,64,Business travel,Eco Plus,315,2,2,2,2,2,2,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +100940,100120,Female,Loyal Customer,31,Business travel,Business,2548,3,1,1,1,3,3,3,3,2,5,3,2,4,3,0,0.0,neutral or dissatisfied +100941,63219,Male,Loyal Customer,48,Business travel,Business,1539,3,3,3,3,2,4,5,5,5,5,5,5,5,5,5,0.0,satisfied +100942,14863,Male,Loyal Customer,59,Business travel,Eco,343,3,4,4,4,3,3,3,3,2,3,3,1,3,3,12,15.0,neutral or dissatisfied +100943,104378,Male,Loyal Customer,39,Business travel,Business,228,1,1,1,1,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +100944,359,Male,Loyal Customer,55,Business travel,Business,3431,0,4,0,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +100945,19033,Female,Loyal Customer,7,Personal Travel,Eco,828,1,4,1,1,3,1,3,3,3,3,4,5,5,3,69,58.0,neutral or dissatisfied +100946,75263,Female,Loyal Customer,52,Personal Travel,Eco,1744,5,1,5,3,2,3,4,3,3,5,4,3,3,1,0,0.0,satisfied +100947,79849,Male,Loyal Customer,56,Business travel,Business,1047,5,5,5,5,4,5,5,4,4,4,4,4,4,5,15,19.0,satisfied +100948,37622,Male,Loyal Customer,35,Personal Travel,Eco,828,4,5,4,1,5,4,5,5,3,4,5,3,4,5,3,0.0,neutral or dissatisfied +100949,124991,Female,Loyal Customer,37,Business travel,Eco,184,1,1,1,1,1,1,1,1,1,3,3,4,4,1,0,2.0,neutral or dissatisfied +100950,96388,Female,Loyal Customer,40,Business travel,Business,3997,5,5,5,5,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +100951,25170,Female,Loyal Customer,25,Business travel,Business,2009,3,3,5,3,3,3,3,3,5,5,3,5,2,3,5,22.0,satisfied +100952,55246,Male,Loyal Customer,31,Personal Travel,Eco,1009,3,2,3,2,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +100953,9827,Male,disloyal Customer,52,Business travel,Business,476,4,4,4,3,3,4,3,3,4,5,5,4,4,3,0,0.0,satisfied +100954,830,Female,disloyal Customer,27,Business travel,Business,89,3,3,3,3,3,3,3,3,3,1,4,1,4,3,57,52.0,neutral or dissatisfied +100955,107076,Male,Loyal Customer,45,Personal Travel,Eco,395,4,5,4,4,3,4,2,3,5,3,5,5,4,3,42,79.0,neutral or dissatisfied +100956,125185,Male,Loyal Customer,40,Business travel,Business,651,5,5,5,5,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +100957,119718,Male,Loyal Customer,45,Business travel,Business,1325,4,3,3,3,1,3,2,4,4,4,4,4,4,4,126,117.0,neutral or dissatisfied +100958,101510,Female,Loyal Customer,38,Business travel,Business,345,1,5,5,5,2,4,4,1,1,1,1,1,1,2,7,7.0,neutral or dissatisfied +100959,94057,Male,Loyal Customer,80,Business travel,Business,3923,3,1,1,1,4,4,4,3,3,2,3,2,3,2,1,2.0,neutral or dissatisfied +100960,121992,Male,Loyal Customer,61,Business travel,Business,2257,5,5,5,5,2,5,4,5,5,5,5,4,5,4,36,24.0,satisfied +100961,3237,Male,Loyal Customer,42,Business travel,Business,479,5,5,5,5,4,4,4,4,3,4,4,4,4,4,183,187.0,satisfied +100962,51361,Female,Loyal Customer,51,Business travel,Eco Plus,77,2,2,2,2,2,3,3,2,2,2,2,2,2,4,0,,neutral or dissatisfied +100963,9211,Male,Loyal Customer,57,Business travel,Business,100,0,4,0,5,4,5,5,5,5,5,1,3,5,5,0,0.0,satisfied +100964,43410,Male,Loyal Customer,37,Business travel,Eco Plus,463,4,2,2,2,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +100965,85913,Female,Loyal Customer,47,Business travel,Business,761,1,2,2,2,1,3,3,1,1,1,1,1,1,1,8,0.0,neutral or dissatisfied +100966,49834,Male,disloyal Customer,22,Business travel,Eco,209,3,1,3,2,3,3,3,3,4,1,2,2,2,3,0,0.0,neutral or dissatisfied +100967,122720,Male,Loyal Customer,25,Business travel,Business,651,2,2,2,2,3,3,3,3,5,3,4,5,5,3,2,0.0,satisfied +100968,90455,Male,Loyal Customer,36,Business travel,Business,545,1,1,1,1,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +100969,44552,Male,Loyal Customer,36,Personal Travel,Eco,157,3,4,0,2,4,0,4,4,5,3,4,3,5,4,86,62.0,neutral or dissatisfied +100970,124193,Female,disloyal Customer,22,Business travel,Eco,1094,3,3,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +100971,101186,Female,Loyal Customer,7,Personal Travel,Eco,1235,3,4,3,4,2,3,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +100972,44404,Male,Loyal Customer,32,Personal Travel,Eco,342,3,3,3,2,2,3,2,2,5,1,1,2,1,2,9,27.0,neutral or dissatisfied +100973,77903,Male,Loyal Customer,51,Business travel,Eco,456,3,2,2,2,3,3,3,3,4,1,4,2,4,3,6,2.0,neutral or dissatisfied +100974,118851,Female,Loyal Customer,13,Personal Travel,Eco Plus,651,1,2,1,3,4,1,4,4,4,2,3,1,3,4,0,0.0,neutral or dissatisfied +100975,98975,Female,Loyal Customer,39,Personal Travel,Eco,479,2,3,4,2,2,4,2,2,1,3,4,3,1,2,0,0.0,neutral or dissatisfied +100976,10214,Male,Loyal Customer,45,Business travel,Business,2590,5,5,5,5,5,4,4,5,5,5,5,3,5,4,48,43.0,satisfied +100977,129413,Male,Loyal Customer,44,Business travel,Business,1881,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +100978,116380,Female,Loyal Customer,35,Personal Travel,Eco,333,3,5,3,4,5,3,5,5,5,3,5,3,4,5,32,27.0,neutral or dissatisfied +100979,45954,Male,Loyal Customer,60,Personal Travel,Eco,563,2,4,2,4,3,2,4,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +100980,98443,Female,Loyal Customer,25,Business travel,Business,1749,2,3,3,3,2,2,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +100981,153,Female,Loyal Customer,35,Business travel,Business,227,3,3,3,3,5,4,4,5,5,5,5,4,5,3,0,10.0,satisfied +100982,127335,Female,Loyal Customer,52,Business travel,Business,1616,4,4,4,4,4,5,4,4,4,4,4,5,4,4,7,0.0,satisfied +100983,127576,Female,Loyal Customer,17,Personal Travel,Eco,1670,3,0,3,3,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +100984,58364,Female,Loyal Customer,53,Personal Travel,Eco,646,2,2,2,4,3,3,4,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +100985,30606,Female,Loyal Customer,11,Personal Travel,Eco,472,5,2,5,3,4,5,4,4,1,1,3,2,3,4,0,0.0,satisfied +100986,47630,Male,Loyal Customer,39,Business travel,Eco,1235,5,4,4,4,5,5,5,5,3,3,5,3,5,5,0,5.0,satisfied +100987,111050,Female,Loyal Customer,51,Business travel,Business,3543,3,3,3,3,1,3,3,5,5,4,5,1,5,5,2,0.0,satisfied +100988,84067,Female,Loyal Customer,43,Business travel,Business,3065,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +100989,49522,Female,disloyal Customer,23,Business travel,Eco,110,4,0,5,4,5,3,3,1,3,1,1,3,4,3,157,154.0,satisfied +100990,41048,Female,Loyal Customer,50,Personal Travel,Eco,1087,3,3,3,4,5,5,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +100991,54968,Female,Loyal Customer,45,Business travel,Business,1346,2,2,2,2,3,5,4,4,4,4,4,3,4,3,36,37.0,satisfied +100992,55868,Female,Loyal Customer,12,Personal Travel,Business,473,0,4,0,3,1,0,1,1,2,5,4,3,3,1,14,44.0,satisfied +100993,16025,Male,Loyal Customer,31,Personal Travel,Eco,853,2,4,2,4,2,2,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +100994,57029,Female,Loyal Customer,56,Business travel,Business,2565,5,5,5,5,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +100995,66344,Male,Loyal Customer,41,Business travel,Business,1951,5,5,5,5,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +100996,105243,Male,Loyal Customer,56,Business travel,Eco Plus,377,4,2,2,2,4,4,4,4,1,4,3,1,4,4,55,50.0,neutral or dissatisfied +100997,39054,Male,Loyal Customer,51,Personal Travel,Eco Plus,230,3,5,3,1,2,3,2,2,4,3,4,4,5,2,0,12.0,neutral or dissatisfied +100998,99501,Male,Loyal Customer,57,Personal Travel,Eco,283,1,4,1,3,3,1,3,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +100999,16267,Female,disloyal Customer,30,Business travel,Eco,946,1,1,1,3,1,1,1,1,1,4,4,4,2,1,0,0.0,neutral or dissatisfied +101000,72906,Female,Loyal Customer,47,Business travel,Business,944,2,2,2,2,2,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +101001,99935,Male,Loyal Customer,37,Personal Travel,Eco,764,1,4,1,3,4,1,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +101002,20435,Female,Loyal Customer,17,Personal Travel,Eco Plus,299,3,5,3,2,2,3,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +101003,89955,Male,Loyal Customer,51,Personal Travel,Eco,1310,2,5,3,5,2,3,2,2,5,4,3,5,5,2,24,19.0,neutral or dissatisfied +101004,33224,Female,Loyal Customer,33,Business travel,Eco Plus,216,2,3,3,3,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +101005,113595,Female,Loyal Customer,37,Business travel,Eco,397,3,2,2,2,3,3,3,1,1,3,4,3,1,3,161,150.0,neutral or dissatisfied +101006,1275,Female,Loyal Customer,38,Personal Travel,Eco,309,1,5,1,1,2,1,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +101007,23363,Male,Loyal Customer,51,Business travel,Eco,1014,4,1,1,1,4,4,4,4,3,2,4,3,5,4,0,0.0,satisfied +101008,2210,Male,Loyal Customer,38,Personal Travel,Eco Plus,624,1,5,1,3,2,1,2,2,3,3,5,4,4,2,20,62.0,neutral or dissatisfied +101009,64398,Male,Loyal Customer,7,Personal Travel,Eco,1172,2,2,2,3,2,2,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +101010,40712,Female,Loyal Customer,59,Business travel,Eco,558,5,1,1,1,1,3,4,5,5,5,5,2,5,3,0,0.0,satisfied +101011,122882,Female,Loyal Customer,60,Personal Travel,Eco,226,1,5,1,5,2,5,5,3,3,1,1,3,3,3,0,3.0,neutral or dissatisfied +101012,104562,Male,Loyal Customer,57,Business travel,Business,369,2,1,2,2,4,4,5,5,5,5,5,3,5,3,35,26.0,satisfied +101013,43292,Male,Loyal Customer,29,Business travel,Business,2738,1,2,2,2,1,1,1,1,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +101014,116482,Female,Loyal Customer,10,Personal Travel,Eco,333,2,3,2,3,3,2,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +101015,101140,Female,Loyal Customer,48,Business travel,Business,3473,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +101016,112104,Female,Loyal Customer,10,Personal Travel,Eco,1062,1,3,1,5,4,1,4,4,3,5,5,4,1,4,0,0.0,neutral or dissatisfied +101017,61692,Female,disloyal Customer,26,Business travel,Eco,765,4,4,4,3,4,2,2,3,5,3,4,2,3,2,160,154.0,neutral or dissatisfied +101018,69818,Male,Loyal Customer,45,Business travel,Business,3164,1,1,1,1,3,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +101019,94509,Male,Loyal Customer,42,Business travel,Business,148,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,1.0,satisfied +101020,118779,Female,Loyal Customer,14,Personal Travel,Eco,370,2,0,2,1,1,2,1,1,4,4,4,5,5,1,2,0.0,neutral or dissatisfied +101021,86937,Male,disloyal Customer,21,Business travel,Business,907,5,4,5,1,4,5,4,4,5,4,5,5,4,4,4,1.0,satisfied +101022,109525,Female,disloyal Customer,26,Business travel,Eco,834,2,3,3,3,2,3,2,2,1,4,4,2,3,2,7,0.0,neutral or dissatisfied +101023,65993,Male,Loyal Customer,10,Personal Travel,Eco Plus,1372,3,4,4,4,4,4,5,4,4,5,3,3,4,4,3,0.0,neutral or dissatisfied +101024,35912,Male,Loyal Customer,32,Business travel,Eco,2248,2,2,2,2,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +101025,4910,Male,Loyal Customer,64,Business travel,Business,3730,3,2,2,2,3,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +101026,49993,Female,Loyal Customer,39,Business travel,Eco,89,2,2,5,2,2,2,2,2,1,2,1,4,2,2,68,67.0,neutral or dissatisfied +101027,16000,Female,disloyal Customer,38,Business travel,Eco,794,2,1,1,3,4,1,5,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +101028,73192,Female,Loyal Customer,32,Business travel,Eco,1258,3,2,2,2,3,3,3,3,3,4,2,2,3,3,0,0.0,neutral or dissatisfied +101029,107078,Female,Loyal Customer,62,Personal Travel,Eco,480,2,1,2,2,1,2,3,2,2,2,4,2,2,2,0,0.0,neutral or dissatisfied +101030,91348,Female,Loyal Customer,28,Personal Travel,Eco Plus,366,5,5,5,4,2,5,2,2,5,2,3,1,3,2,0,0.0,satisfied +101031,37263,Female,disloyal Customer,26,Business travel,Eco,1076,3,3,3,2,5,3,5,5,3,2,4,2,3,5,3,0.0,neutral or dissatisfied +101032,56377,Male,Loyal Customer,22,Business travel,Business,2215,4,4,4,4,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +101033,60878,Female,Loyal Customer,60,Business travel,Business,1899,5,5,3,5,5,5,4,4,4,4,4,3,4,4,85,91.0,satisfied +101034,74051,Female,Loyal Customer,20,Personal Travel,Eco,1194,4,4,3,1,3,3,3,3,4,5,5,4,4,3,0,8.0,neutral or dissatisfied +101035,113966,Male,Loyal Customer,27,Business travel,Business,1790,4,4,4,4,4,4,4,4,2,4,2,2,3,4,19,7.0,neutral or dissatisfied +101036,67890,Female,Loyal Customer,60,Personal Travel,Eco,1171,2,5,2,2,4,5,4,3,3,2,3,3,3,5,17,4.0,neutral or dissatisfied +101037,54129,Female,disloyal Customer,35,Business travel,Eco,1400,4,4,4,3,3,4,3,3,1,4,3,3,5,3,20,3.0,neutral or dissatisfied +101038,94627,Female,disloyal Customer,29,Business travel,Business,189,0,0,0,3,5,0,5,5,4,5,5,4,4,5,0,0.0,satisfied +101039,116216,Female,Loyal Customer,58,Personal Travel,Eco,325,3,1,4,3,4,3,2,2,2,4,2,3,2,4,15,16.0,neutral or dissatisfied +101040,95521,Male,disloyal Customer,19,Business travel,Eco,441,3,5,2,3,3,2,3,3,2,3,5,2,3,3,0,0.0,neutral or dissatisfied +101041,58081,Female,Loyal Customer,53,Business travel,Business,2480,4,4,4,4,4,4,4,2,3,3,3,4,2,4,394,392.0,neutral or dissatisfied +101042,22200,Male,Loyal Customer,61,Personal Travel,Eco,533,1,4,1,3,3,1,3,3,3,5,4,4,5,3,115,106.0,neutral or dissatisfied +101043,114412,Female,Loyal Customer,46,Business travel,Business,2185,2,2,2,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +101044,95033,Male,Loyal Customer,57,Personal Travel,Eco,293,3,2,1,3,1,1,1,1,2,1,2,4,3,1,0,0.0,neutral or dissatisfied +101045,111864,Male,disloyal Customer,17,Business travel,Eco,628,3,5,3,4,4,3,4,4,3,3,4,5,4,4,39,17.0,neutral or dissatisfied +101046,19988,Female,disloyal Customer,26,Business travel,Eco,589,3,3,3,4,3,3,2,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +101047,7632,Male,Loyal Customer,51,Business travel,Business,2534,2,2,2,2,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +101048,123153,Female,disloyal Customer,27,Business travel,Eco,328,2,0,2,3,4,2,4,4,1,5,3,4,3,4,0,0.0,neutral or dissatisfied +101049,15104,Male,Loyal Customer,37,Personal Travel,Eco,322,2,5,2,4,4,2,4,4,4,3,3,2,3,4,0,0.0,neutral or dissatisfied +101050,55457,Female,disloyal Customer,30,Business travel,Eco,1046,3,3,3,3,1,3,1,1,4,2,4,2,4,1,9,9.0,neutral or dissatisfied +101051,20595,Female,Loyal Customer,66,Business travel,Eco Plus,533,5,5,5,5,4,2,1,5,5,5,5,3,5,1,0,0.0,satisfied +101052,81218,Male,Loyal Customer,38,Personal Travel,Eco,1426,2,4,2,3,3,2,3,3,2,1,3,2,3,3,60,120.0,neutral or dissatisfied +101053,97589,Male,disloyal Customer,63,Business travel,Eco Plus,337,1,1,1,4,2,1,2,2,1,2,3,2,3,2,102,101.0,neutral or dissatisfied +101054,44699,Male,Loyal Customer,11,Personal Travel,Eco,173,1,5,0,4,2,0,2,2,2,2,1,5,5,2,15,24.0,neutral or dissatisfied +101055,28314,Female,disloyal Customer,26,Business travel,Eco,867,3,4,4,1,4,4,4,4,1,2,3,3,2,4,7,0.0,neutral or dissatisfied +101056,116767,Female,Loyal Customer,9,Personal Travel,Eco Plus,404,3,4,2,2,4,2,4,4,3,5,5,3,5,4,1,0.0,neutral or dissatisfied +101057,99879,Female,disloyal Customer,22,Business travel,Eco,1436,2,2,2,5,2,2,2,4,3,5,4,2,3,2,196,205.0,neutral or dissatisfied +101058,22040,Female,Loyal Customer,15,Personal Travel,Eco Plus,448,3,5,1,3,1,1,1,2,2,4,3,1,1,1,178,163.0,neutral or dissatisfied +101059,22488,Male,Loyal Customer,16,Personal Travel,Eco,145,2,4,2,5,2,2,2,2,3,5,4,4,5,2,81,75.0,neutral or dissatisfied +101060,66552,Male,Loyal Customer,36,Business travel,Business,2951,4,4,5,4,4,4,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +101061,78670,Male,Loyal Customer,44,Business travel,Business,761,3,3,3,3,5,4,4,5,5,5,5,4,5,5,40,25.0,satisfied +101062,91278,Male,Loyal Customer,61,Business travel,Business,1817,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +101063,97815,Male,Loyal Customer,50,Business travel,Business,1973,5,5,5,5,5,5,5,5,5,5,5,4,5,4,5,0.0,satisfied +101064,117454,Female,Loyal Customer,56,Personal Travel,Eco,1107,1,4,1,3,5,3,4,5,5,1,5,1,5,4,27,24.0,neutral or dissatisfied +101065,104619,Male,Loyal Customer,34,Business travel,Business,861,3,3,3,3,5,5,5,2,2,3,2,4,2,4,0,0.0,satisfied +101066,37169,Female,Loyal Customer,42,Personal Travel,Eco,1189,1,4,0,1,3,3,4,5,5,0,5,4,5,3,1,0.0,neutral or dissatisfied +101067,11802,Male,disloyal Customer,17,Business travel,Eco Plus,395,2,3,2,2,1,2,1,1,1,3,5,3,2,1,0,0.0,neutral or dissatisfied +101068,66679,Female,Loyal Customer,34,Business travel,Business,802,4,3,2,2,2,3,3,4,4,4,4,3,4,2,0,9.0,neutral or dissatisfied +101069,102557,Female,Loyal Customer,58,Personal Travel,Eco,226,3,3,3,2,1,3,2,3,3,3,4,4,3,3,22,10.0,neutral or dissatisfied +101070,82347,Female,disloyal Customer,78,Business travel,Eco,453,1,1,1,2,2,1,2,2,3,5,3,4,3,2,0,0.0,neutral or dissatisfied +101071,43625,Female,Loyal Customer,59,Personal Travel,Eco,252,1,2,1,3,3,3,3,2,2,1,2,1,2,1,0,0.0,neutral or dissatisfied +101072,1328,Female,Loyal Customer,47,Business travel,Business,134,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +101073,22975,Female,disloyal Customer,20,Business travel,Eco,641,5,5,5,2,2,5,2,2,3,3,3,5,2,2,0,0.0,satisfied +101074,23286,Female,disloyal Customer,32,Business travel,Eco,359,2,4,2,4,4,2,4,4,3,1,4,4,2,4,0,0.0,neutral or dissatisfied +101075,2102,Male,Loyal Customer,66,Personal Travel,Eco,733,2,5,2,1,1,2,1,1,2,5,3,4,4,1,2,7.0,neutral or dissatisfied +101076,8075,Female,Loyal Customer,44,Business travel,Business,3384,5,5,4,5,5,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +101077,39071,Female,Loyal Customer,60,Business travel,Business,337,2,2,2,2,4,5,2,4,4,4,4,4,4,1,0,0.0,satisfied +101078,29821,Male,disloyal Customer,26,Business travel,Eco,548,2,0,2,3,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +101079,84790,Female,Loyal Customer,53,Business travel,Business,534,5,5,5,5,5,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +101080,79730,Male,Loyal Customer,50,Personal Travel,Eco,762,2,5,2,1,3,2,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +101081,37017,Male,Loyal Customer,61,Personal Travel,Eco,899,3,2,4,4,2,4,2,2,3,2,3,3,4,2,16,16.0,neutral or dissatisfied +101082,62376,Female,Loyal Customer,44,Business travel,Business,2704,4,4,4,4,3,5,5,5,5,5,5,5,5,5,8,0.0,satisfied +101083,77562,Female,disloyal Customer,24,Business travel,Eco,986,3,3,3,1,3,3,3,3,3,2,5,4,5,3,79,62.0,neutral or dissatisfied +101084,49005,Male,disloyal Customer,39,Business travel,Eco,373,1,4,1,3,3,1,3,3,4,5,1,1,3,3,0,0.0,neutral or dissatisfied +101085,120478,Female,Loyal Customer,67,Personal Travel,Eco,366,2,4,2,3,2,3,4,4,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +101086,35783,Female,disloyal Customer,80,Business travel,Eco,200,1,4,1,4,4,1,4,4,2,3,4,2,4,4,107,115.0,neutral or dissatisfied +101087,109492,Male,Loyal Customer,38,Business travel,Business,861,4,4,4,4,4,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +101088,81504,Female,Loyal Customer,42,Personal Travel,Eco,528,3,5,2,3,5,5,5,2,2,2,2,4,2,4,0,8.0,neutral or dissatisfied +101089,30582,Male,Loyal Customer,31,Personal Travel,Eco,628,0,5,0,4,5,0,5,5,5,3,5,3,4,5,5,5.0,satisfied +101090,22562,Male,disloyal Customer,26,Business travel,Eco,300,2,0,2,2,2,2,2,2,1,1,3,4,2,2,0,0.0,neutral or dissatisfied +101091,108989,Female,Loyal Customer,55,Business travel,Business,3147,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +101092,94555,Female,Loyal Customer,26,Business travel,Business,248,0,0,0,1,1,1,1,1,4,5,4,4,4,1,0,0.0,satisfied +101093,104740,Female,Loyal Customer,43,Business travel,Eco,1342,1,1,1,1,1,4,4,1,1,1,1,4,1,2,31,4.0,neutral or dissatisfied +101094,59088,Female,disloyal Customer,22,Business travel,Eco,346,4,0,4,5,2,4,2,2,3,3,1,3,4,2,29,30.0,satisfied +101095,82483,Male,Loyal Customer,40,Business travel,Business,502,3,3,3,3,3,4,4,4,4,4,4,5,4,5,7,0.0,satisfied +101096,113935,Female,Loyal Customer,52,Business travel,Business,1838,1,1,1,1,4,4,4,5,3,4,5,4,3,4,151,385.0,satisfied +101097,15272,Male,Loyal Customer,49,Business travel,Business,1892,5,5,5,5,4,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +101098,62258,Male,Loyal Customer,9,Business travel,Eco Plus,2565,2,3,3,3,2,3,2,2,2,5,2,3,3,2,108,99.0,neutral or dissatisfied +101099,71688,Male,Loyal Customer,21,Personal Travel,Eco,1182,2,4,2,5,5,2,5,5,3,2,4,3,5,5,9,10.0,neutral or dissatisfied +101100,29396,Female,disloyal Customer,29,Business travel,Eco,1235,1,1,1,4,2,1,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +101101,26311,Male,Loyal Customer,56,Business travel,Business,447,4,4,5,4,4,1,5,5,5,5,5,1,5,1,0,8.0,satisfied +101102,101586,Female,Loyal Customer,30,Personal Travel,Eco,1099,3,3,3,5,2,3,2,2,1,5,1,1,3,2,4,8.0,neutral or dissatisfied +101103,13809,Female,disloyal Customer,25,Business travel,Eco,617,3,0,3,2,1,3,1,1,3,3,5,2,2,1,16,7.0,neutral or dissatisfied +101104,122444,Male,Loyal Customer,53,Business travel,Business,2418,4,4,3,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +101105,9980,Female,Loyal Customer,26,Personal Travel,Eco,508,3,4,3,4,2,3,2,2,4,2,4,3,4,2,27,40.0,neutral or dissatisfied +101106,63392,Female,Loyal Customer,36,Personal Travel,Eco,447,2,4,2,3,4,2,4,4,3,5,5,4,4,4,0,0.0,neutral or dissatisfied +101107,110903,Male,Loyal Customer,41,Business travel,Business,581,2,1,1,1,2,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +101108,76471,Female,Loyal Customer,44,Business travel,Business,2481,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +101109,96619,Female,Loyal Customer,47,Business travel,Business,1772,2,2,2,2,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +101110,9431,Male,Loyal Customer,54,Business travel,Eco,362,3,5,5,5,3,3,3,3,2,5,2,4,3,3,46,46.0,neutral or dissatisfied +101111,92709,Female,disloyal Customer,19,Business travel,Eco,818,4,4,4,2,5,4,5,5,4,4,3,4,5,5,0,8.0,neutral or dissatisfied +101112,101664,Male,Loyal Customer,35,Business travel,Business,2106,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +101113,22661,Female,disloyal Customer,37,Business travel,Business,579,3,3,3,4,1,3,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +101114,77962,Female,Loyal Customer,39,Business travel,Business,2140,2,5,2,2,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +101115,10761,Female,Loyal Customer,65,Business travel,Business,2223,1,2,2,2,5,3,3,3,3,3,1,2,3,3,0,0.0,neutral or dissatisfied +101116,33033,Male,Loyal Customer,51,Personal Travel,Eco,201,4,3,4,3,2,4,2,2,4,5,4,1,4,2,0,0.0,satisfied +101117,115316,Female,Loyal Customer,47,Business travel,Business,296,2,1,1,1,5,3,4,2,2,2,2,2,2,4,47,38.0,neutral or dissatisfied +101118,27437,Female,Loyal Customer,28,Business travel,Business,954,1,1,1,1,5,5,5,5,2,1,1,1,3,5,0,0.0,satisfied +101119,46711,Male,Loyal Customer,13,Personal Travel,Eco,212,1,0,0,4,5,0,5,5,5,2,5,4,4,5,4,2.0,neutral or dissatisfied +101120,103972,Female,Loyal Customer,10,Business travel,Eco Plus,770,2,3,3,3,2,2,4,2,4,4,3,2,3,2,16,15.0,neutral or dissatisfied +101121,22576,Female,disloyal Customer,55,Business travel,Eco,223,3,0,2,3,4,2,4,4,5,4,4,3,3,4,42,40.0,neutral or dissatisfied +101122,44523,Male,disloyal Customer,36,Business travel,Eco,157,3,1,3,3,4,3,4,4,1,3,2,2,3,4,0,0.0,neutral or dissatisfied +101123,123823,Male,Loyal Customer,42,Business travel,Business,3169,2,2,2,2,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +101124,113192,Female,Loyal Customer,60,Business travel,Business,3294,1,1,1,1,5,4,5,4,4,4,4,4,4,5,7,0.0,satisfied +101125,19632,Female,disloyal Customer,21,Business travel,Eco,642,3,1,3,2,4,3,4,4,1,5,1,1,2,4,2,13.0,neutral or dissatisfied +101126,66268,Female,Loyal Customer,67,Personal Travel,Eco,550,3,4,3,4,4,4,4,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +101127,41830,Male,Loyal Customer,28,Business travel,Eco Plus,489,4,5,5,5,4,4,4,4,3,2,5,3,4,4,2,0.0,satisfied +101128,100584,Male,Loyal Customer,47,Personal Travel,Eco,486,3,0,3,3,5,3,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +101129,96134,Female,Loyal Customer,47,Business travel,Business,546,1,1,1,1,2,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +101130,73226,Male,Loyal Customer,50,Business travel,Eco,946,2,4,5,5,2,2,2,2,4,4,4,2,3,2,0,0.0,neutral or dissatisfied +101131,113175,Female,Loyal Customer,64,Personal Travel,Eco,677,2,5,2,3,3,1,5,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +101132,45276,Female,Loyal Customer,48,Business travel,Business,2699,0,5,0,1,3,2,3,5,5,5,5,1,5,2,0,0.0,satisfied +101133,19885,Female,Loyal Customer,53,Business travel,Business,2752,2,2,2,2,2,5,3,5,5,5,5,5,5,5,97,102.0,satisfied +101134,1488,Male,Loyal Customer,45,Business travel,Business,3544,2,2,2,2,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +101135,107846,Female,Loyal Customer,39,Business travel,Eco Plus,349,1,2,2,2,1,1,1,1,3,3,2,3,2,1,67,63.0,neutral or dissatisfied +101136,20975,Female,Loyal Customer,43,Personal Travel,Eco,689,4,4,4,3,5,5,5,3,3,4,3,4,3,5,0,2.0,satisfied +101137,8663,Male,Loyal Customer,39,Business travel,Business,181,0,5,0,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +101138,72255,Male,Loyal Customer,50,Business travel,Business,1784,2,2,2,2,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +101139,6595,Female,Loyal Customer,67,Personal Travel,Eco,607,2,4,2,2,3,4,4,2,2,2,2,3,2,3,2,0.0,neutral or dissatisfied +101140,67732,Male,Loyal Customer,26,Business travel,Eco,1235,4,4,4,4,4,3,2,4,1,2,3,4,3,4,0,0.0,neutral or dissatisfied +101141,105622,Male,Loyal Customer,23,Business travel,Business,1941,2,2,2,2,2,2,2,2,3,3,4,4,4,2,4,5.0,satisfied +101142,114970,Male,Loyal Customer,44,Business travel,Business,358,1,1,1,1,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +101143,113299,Male,disloyal Customer,24,Business travel,Eco,407,4,0,4,2,5,4,5,5,4,5,5,3,4,5,16,4.0,satisfied +101144,124996,Male,disloyal Customer,38,Business travel,Eco,184,4,4,4,3,5,4,5,5,1,3,4,2,4,5,0,0.0,neutral or dissatisfied +101145,110183,Female,Loyal Customer,9,Personal Travel,Eco,1072,2,2,2,2,5,2,5,5,3,5,2,1,2,5,0,8.0,neutral or dissatisfied +101146,49519,Female,Loyal Customer,39,Business travel,Eco,363,4,2,2,2,4,4,4,4,2,2,5,5,5,4,8,1.0,satisfied +101147,89541,Female,disloyal Customer,36,Business travel,Business,950,2,2,2,3,4,2,2,4,3,4,5,5,5,4,7,4.0,neutral or dissatisfied +101148,6201,Female,Loyal Customer,33,Personal Travel,Eco Plus,491,3,4,3,3,2,3,2,2,4,1,3,2,4,2,4,4.0,neutral or dissatisfied +101149,64295,Male,disloyal Customer,46,Business travel,Business,1158,3,2,2,3,2,3,2,2,4,2,4,4,5,2,23,18.0,neutral or dissatisfied +101150,114834,Male,Loyal Customer,57,Business travel,Business,417,4,5,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +101151,75304,Female,Loyal Customer,47,Business travel,Business,2615,2,2,2,2,5,5,5,4,3,3,5,5,3,5,0,70.0,satisfied +101152,45592,Female,Loyal Customer,46,Business travel,Eco,230,4,3,3,3,2,1,1,4,4,4,4,4,4,1,0,0.0,satisfied +101153,88566,Male,Loyal Customer,58,Personal Travel,Eco,581,2,4,2,3,5,2,5,5,3,3,4,4,4,5,14,34.0,neutral or dissatisfied +101154,76979,Male,Loyal Customer,65,Personal Travel,Eco,1969,1,5,1,3,1,1,1,1,4,5,5,5,5,1,67,43.0,neutral or dissatisfied +101155,69015,Male,Loyal Customer,39,Business travel,Business,1417,4,4,4,4,2,4,4,5,5,5,5,3,5,5,10,55.0,satisfied +101156,95480,Female,Loyal Customer,56,Business travel,Business,3221,2,2,2,2,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +101157,73286,Male,disloyal Customer,24,Business travel,Business,1005,5,0,5,3,2,5,2,2,5,3,5,3,4,2,59,51.0,satisfied +101158,114606,Female,Loyal Customer,42,Business travel,Business,2693,2,2,2,2,3,4,4,4,4,4,4,5,4,4,1,6.0,satisfied +101159,33127,Female,Loyal Customer,27,Personal Travel,Eco,163,4,4,4,3,2,4,1,2,1,1,4,3,3,2,0,0.0,satisfied +101160,57969,Male,Loyal Customer,30,Business travel,Eco Plus,1911,0,0,0,4,2,0,2,2,1,5,3,3,2,2,0,0.0,satisfied +101161,109685,Male,Loyal Customer,51,Personal Travel,Eco,829,1,4,1,1,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +101162,88157,Male,Loyal Customer,59,Business travel,Business,515,3,3,3,3,4,4,5,5,5,5,5,4,5,5,2,0.0,satisfied +101163,33459,Male,disloyal Customer,43,Business travel,Eco Plus,2409,2,2,2,3,2,1,4,4,5,3,5,4,5,4,0,10.0,neutral or dissatisfied +101164,6705,Female,Loyal Customer,49,Personal Travel,Eco,438,2,5,2,5,4,5,5,4,4,2,1,4,4,3,44,73.0,neutral or dissatisfied +101165,27735,Female,disloyal Customer,29,Business travel,Eco,1448,4,4,4,2,3,4,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +101166,2915,Female,Loyal Customer,26,Personal Travel,Eco Plus,409,4,5,4,2,4,4,4,4,5,3,1,1,2,4,0,0.0,satisfied +101167,117423,Male,Loyal Customer,43,Business travel,Business,1460,4,2,4,4,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +101168,127936,Female,Loyal Customer,65,Personal Travel,Eco,2300,3,3,3,4,2,5,4,3,3,3,3,1,3,5,0,0.0,neutral or dissatisfied +101169,53306,Female,Loyal Customer,17,Personal Travel,Eco,758,4,5,4,1,4,4,4,4,5,2,5,5,1,4,6,0.0,neutral or dissatisfied +101170,24860,Female,Loyal Customer,46,Business travel,Business,2848,5,5,5,5,2,1,1,5,5,5,5,5,5,4,0,0.0,satisfied +101171,34870,Female,Loyal Customer,13,Business travel,Business,2248,1,4,2,4,1,1,1,1,5,2,3,1,4,1,400,393.0,neutral or dissatisfied +101172,15151,Male,Loyal Customer,46,Personal Travel,Eco,1042,3,1,3,4,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +101173,26045,Male,disloyal Customer,16,Business travel,Eco,432,1,1,1,4,2,1,2,2,4,3,3,2,4,2,0,17.0,neutral or dissatisfied +101174,40938,Female,disloyal Customer,35,Business travel,Eco Plus,590,2,2,2,4,3,2,1,3,1,1,4,4,4,3,19,19.0,neutral or dissatisfied +101175,84053,Male,Loyal Customer,49,Business travel,Business,932,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,9.0,satisfied +101176,12682,Female,Loyal Customer,20,Business travel,Eco,689,4,5,5,5,4,4,3,4,3,5,5,3,1,4,9,0.0,satisfied +101177,40794,Male,Loyal Customer,34,Business travel,Business,3760,2,2,2,2,3,1,4,3,3,4,3,3,3,4,0,0.0,satisfied +101178,26932,Female,Loyal Customer,29,Business travel,Eco Plus,1874,3,2,1,2,3,3,3,3,1,1,2,2,4,3,20,31.0,neutral or dissatisfied +101179,15514,Male,Loyal Customer,60,Personal Travel,Eco,306,3,5,3,5,2,3,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +101180,84877,Female,Loyal Customer,43,Personal Travel,Eco,481,2,3,2,4,1,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +101181,122610,Female,disloyal Customer,35,Business travel,Business,728,3,3,3,3,2,3,1,2,3,2,5,4,5,2,5,0.0,neutral or dissatisfied +101182,78086,Female,Loyal Customer,35,Personal Travel,Eco Plus,332,4,3,4,4,5,4,5,5,3,4,1,4,5,5,1,0.0,neutral or dissatisfied +101183,88878,Female,disloyal Customer,25,Business travel,Business,859,4,0,4,3,5,4,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +101184,40970,Male,Loyal Customer,49,Personal Travel,Eco,507,3,4,3,2,5,3,5,5,4,3,5,4,5,5,2,0.0,neutral or dissatisfied +101185,57238,Male,Loyal Customer,40,Business travel,Business,628,5,5,5,5,4,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +101186,115576,Female,Loyal Customer,38,Business travel,Business,3687,4,4,4,4,5,4,5,5,5,5,5,3,5,3,6,0.0,satisfied +101187,8595,Male,Loyal Customer,42,Personal Travel,Eco,308,3,2,3,4,4,3,4,4,3,1,3,3,4,4,47,55.0,neutral or dissatisfied +101188,26083,Male,disloyal Customer,25,Business travel,Eco,591,3,3,3,4,2,3,2,2,1,4,1,2,4,2,0,2.0,neutral or dissatisfied +101189,74187,Male,Loyal Customer,15,Personal Travel,Eco,641,3,4,3,3,1,3,1,1,3,4,3,1,3,1,0,0.0,neutral or dissatisfied +101190,104892,Male,Loyal Customer,53,Business travel,Business,1565,1,1,1,1,2,4,5,4,4,4,4,3,4,5,15,19.0,satisfied +101191,87024,Male,disloyal Customer,26,Business travel,Business,240,0,0,0,3,4,0,1,4,3,4,4,5,5,4,8,0.0,satisfied +101192,58941,Female,Loyal Customer,49,Business travel,Business,888,2,2,2,2,2,4,5,5,5,5,5,4,5,5,18,6.0,satisfied +101193,19803,Female,Loyal Customer,62,Personal Travel,Business,632,1,1,1,3,5,4,3,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +101194,116864,Male,disloyal Customer,30,Business travel,Business,647,2,2,2,2,5,2,5,5,3,2,5,3,5,5,65,51.0,neutral or dissatisfied +101195,48223,Male,Loyal Customer,45,Personal Travel,Eco,173,3,5,3,3,4,3,4,4,2,4,4,3,1,4,0,0.0,neutral or dissatisfied +101196,109752,Female,Loyal Customer,54,Business travel,Business,2189,2,2,2,2,3,4,4,5,5,5,5,3,5,5,25,14.0,satisfied +101197,115555,Male,disloyal Customer,38,Business travel,Business,325,3,4,4,2,4,4,4,4,4,5,4,3,4,4,7,0.0,satisfied +101198,129842,Male,Loyal Customer,59,Personal Travel,Eco,337,2,4,2,5,4,2,4,4,3,4,5,4,4,4,3,12.0,neutral or dissatisfied +101199,22075,Male,Loyal Customer,23,Personal Travel,Eco,304,3,5,3,3,5,3,5,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +101200,50097,Female,disloyal Customer,25,Business travel,Eco,372,3,2,3,3,1,3,1,1,3,2,4,3,3,1,0,12.0,neutral or dissatisfied +101201,76304,Male,disloyal Customer,26,Business travel,Business,2182,4,4,4,1,5,4,4,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +101202,119661,Female,disloyal Customer,21,Business travel,Eco,507,2,0,1,4,4,1,4,4,3,5,5,3,3,4,0,0.0,neutral or dissatisfied +101203,126096,Male,Loyal Customer,55,Business travel,Business,3685,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +101204,85960,Female,Loyal Customer,57,Business travel,Business,447,1,1,1,1,5,5,5,3,3,4,3,4,3,5,2,0.0,satisfied +101205,41936,Male,Loyal Customer,16,Personal Travel,Eco,129,1,3,0,4,3,0,3,3,3,2,4,3,5,3,0,18.0,neutral or dissatisfied +101206,108544,Male,Loyal Customer,75,Business travel,Eco,111,3,3,3,3,3,3,3,3,2,5,2,5,3,3,0,0.0,satisfied +101207,25691,Female,Loyal Customer,53,Business travel,Business,432,2,3,2,2,4,1,3,5,5,5,5,3,5,1,5,5.0,satisfied +101208,103963,Male,Loyal Customer,21,Personal Travel,Eco,770,1,4,1,2,4,1,4,4,4,4,4,5,5,4,6,0.0,neutral or dissatisfied +101209,48279,Male,Loyal Customer,11,Personal Travel,Eco Plus,236,5,5,5,2,1,5,1,1,5,5,4,4,4,1,0,0.0,satisfied +101210,99847,Male,Loyal Customer,69,Personal Travel,Eco,587,0,5,0,3,3,0,3,3,3,3,5,4,5,3,0,0.0,satisfied +101211,43112,Female,Loyal Customer,23,Personal Travel,Eco,414,1,5,1,3,5,1,5,5,3,2,5,1,3,5,44,22.0,neutral or dissatisfied +101212,7350,Male,Loyal Customer,49,Business travel,Business,1878,1,1,1,1,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +101213,106636,Female,Loyal Customer,45,Personal Travel,Eco,306,4,3,4,4,4,3,3,5,5,4,5,2,5,3,32,56.0,neutral or dissatisfied +101214,118047,Female,disloyal Customer,24,Business travel,Eco,1262,4,4,4,3,5,4,3,5,2,1,3,2,3,5,8,0.0,neutral or dissatisfied +101215,4159,Male,Loyal Customer,12,Personal Travel,Eco,431,3,5,3,3,5,3,5,5,3,2,4,1,1,5,17,33.0,neutral or dissatisfied +101216,89735,Male,Loyal Customer,16,Personal Travel,Eco,1089,2,5,2,1,1,2,1,1,1,2,4,4,1,1,0,0.0,neutral or dissatisfied +101217,619,Male,Loyal Customer,43,Business travel,Business,312,5,5,5,5,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +101218,27100,Female,Loyal Customer,45,Business travel,Eco,1721,5,5,5,5,4,4,2,5,5,5,5,3,5,4,0,0.0,satisfied +101219,117323,Male,Loyal Customer,13,Personal Travel,Eco Plus,338,4,2,4,3,4,4,1,4,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +101220,25924,Female,Loyal Customer,50,Business travel,Eco,594,4,5,5,5,3,4,1,4,4,4,4,2,4,2,0,0.0,satisfied +101221,76166,Male,Loyal Customer,14,Personal Travel,Eco,546,3,3,2,3,2,2,2,2,4,4,3,1,2,2,57,56.0,neutral or dissatisfied +101222,96410,Male,Loyal Customer,26,Personal Travel,Eco,1407,3,4,2,4,1,2,1,1,2,4,5,4,1,1,0,0.0,neutral or dissatisfied +101223,15362,Female,Loyal Customer,33,Business travel,Eco,331,4,5,5,5,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +101224,15015,Female,Loyal Customer,39,Business travel,Business,157,1,5,5,5,3,1,3,2,5,1,1,3,2,3,172,163.0,neutral or dissatisfied +101225,129827,Male,Loyal Customer,18,Personal Travel,Eco,308,4,4,4,5,1,4,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +101226,13492,Male,disloyal Customer,39,Business travel,Eco,106,1,0,1,1,1,1,1,1,4,4,5,1,5,1,33,24.0,neutral or dissatisfied +101227,49974,Female,Loyal Customer,52,Business travel,Eco,134,2,3,3,3,3,4,3,2,2,2,2,1,2,2,0,0.0,satisfied +101228,46678,Female,Loyal Customer,52,Personal Travel,Eco,125,4,1,4,4,5,3,4,5,5,4,5,4,5,1,0,0.0,neutral or dissatisfied +101229,5578,Female,Loyal Customer,61,Personal Travel,Eco,501,4,4,2,1,4,4,4,3,3,2,2,3,3,5,8,66.0,neutral or dissatisfied +101230,84773,Male,Loyal Customer,30,Business travel,Business,3014,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0.0,satisfied +101231,124338,Female,disloyal Customer,35,Business travel,Eco,1037,3,3,3,4,4,3,4,4,1,2,3,4,4,4,0,6.0,neutral or dissatisfied +101232,116239,Female,Loyal Customer,15,Personal Travel,Eco,417,2,3,2,4,4,2,5,4,2,2,1,2,1,4,0,0.0,neutral or dissatisfied +101233,118884,Female,Loyal Customer,47,Business travel,Business,3182,4,4,2,4,2,5,5,5,5,5,5,4,5,5,1,0.0,satisfied +101234,68540,Male,Loyal Customer,59,Business travel,Business,2802,3,3,3,3,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +101235,53227,Female,Loyal Customer,7,Personal Travel,Eco,612,3,2,3,2,1,3,1,1,4,1,3,1,2,1,10,7.0,neutral or dissatisfied +101236,68610,Male,Loyal Customer,33,Business travel,Business,3744,4,2,4,4,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +101237,93061,Female,Loyal Customer,48,Business travel,Business,297,3,3,3,3,2,4,4,4,4,4,4,3,4,5,3,0.0,satisfied +101238,54835,Male,Loyal Customer,54,Business travel,Business,641,1,1,1,1,4,5,5,5,5,5,5,3,5,5,12,8.0,satisfied +101239,6648,Female,Loyal Customer,48,Business travel,Business,3431,3,1,1,1,1,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +101240,107848,Female,Loyal Customer,56,Personal Travel,Eco Plus,349,2,4,2,3,3,3,1,4,4,2,4,3,4,4,5,0.0,neutral or dissatisfied +101241,96805,Female,disloyal Customer,28,Business travel,Business,994,1,1,1,4,2,1,2,2,3,5,4,5,5,2,13,0.0,neutral or dissatisfied +101242,89777,Female,Loyal Customer,15,Personal Travel,Eco,1069,3,1,3,4,5,3,5,5,2,3,3,4,4,5,4,,neutral or dissatisfied +101243,93915,Male,Loyal Customer,37,Business travel,Business,3962,1,3,1,1,4,5,5,5,5,5,5,4,5,5,0,14.0,satisfied +101244,34330,Male,Loyal Customer,42,Business travel,Business,846,3,3,3,3,5,3,3,4,4,4,4,5,4,1,0,0.0,satisfied +101245,63720,Female,Loyal Customer,51,Business travel,Business,1660,5,5,5,5,3,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +101246,117870,Female,disloyal Customer,36,Business travel,Business,255,3,2,2,1,5,2,5,5,3,3,5,4,5,5,6,1.0,neutral or dissatisfied +101247,90553,Female,disloyal Customer,25,Business travel,Business,404,5,0,5,3,2,5,2,2,5,5,5,5,5,2,0,0.0,satisfied +101248,106386,Female,Loyal Customer,55,Business travel,Eco,488,1,5,5,5,1,4,4,1,1,1,1,3,1,3,77,70.0,neutral or dissatisfied +101249,119526,Male,Loyal Customer,64,Personal Travel,Eco,814,1,3,1,3,5,1,3,5,1,3,3,2,3,5,28,22.0,neutral or dissatisfied +101250,33183,Male,Loyal Customer,34,Business travel,Eco Plus,216,4,2,2,2,4,4,4,4,4,1,2,1,5,4,0,17.0,satisfied +101251,56541,Female,Loyal Customer,56,Business travel,Business,1065,3,1,3,3,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +101252,72307,Female,Loyal Customer,18,Personal Travel,Eco,919,4,4,4,3,1,4,1,1,5,5,5,5,5,1,7,14.0,neutral or dissatisfied +101253,69017,Female,Loyal Customer,29,Business travel,Business,1389,1,1,1,1,4,4,4,4,3,3,5,4,5,4,0,0.0,satisfied +101254,7553,Male,disloyal Customer,25,Business travel,Business,606,2,0,1,4,5,1,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +101255,24165,Male,disloyal Customer,23,Business travel,Eco,302,0,0,0,1,3,0,2,3,4,5,2,1,5,3,0,0.0,satisfied +101256,101442,Female,Loyal Customer,45,Business travel,Business,2709,0,0,0,4,5,5,5,1,1,1,1,3,1,5,20,16.0,satisfied +101257,31740,Female,Loyal Customer,53,Business travel,Eco Plus,967,4,2,2,2,3,1,3,4,4,4,4,5,4,5,0,0.0,satisfied +101258,82052,Female,Loyal Customer,56,Business travel,Business,1535,1,1,3,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +101259,94132,Male,Loyal Customer,45,Business travel,Business,2902,4,4,4,4,2,5,5,5,5,5,5,3,5,4,16,5.0,satisfied +101260,32543,Male,Loyal Customer,32,Business travel,Business,3467,0,5,1,3,3,3,3,3,2,5,3,3,4,3,0,0.0,satisfied +101261,72921,Female,disloyal Customer,11,Business travel,Eco,1096,2,2,2,4,5,2,5,5,2,5,3,3,3,5,0,0.0,neutral or dissatisfied +101262,82762,Female,Loyal Customer,14,Personal Travel,Eco,409,3,4,3,3,1,3,1,1,4,1,3,3,4,1,0,37.0,neutral or dissatisfied +101263,97651,Female,Loyal Customer,28,Personal Travel,Eco,1587,2,5,2,1,3,2,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +101264,79266,Female,Loyal Customer,19,Personal Travel,Eco,1598,1,4,1,3,5,1,5,5,3,2,3,5,5,5,103,100.0,neutral or dissatisfied +101265,55682,Male,Loyal Customer,50,Business travel,Business,1544,3,3,3,3,2,4,4,4,4,5,4,3,4,3,1,0.0,satisfied +101266,51816,Female,Loyal Customer,61,Business travel,Eco Plus,370,5,5,5,5,4,4,5,5,5,5,5,1,5,5,0,0.0,satisfied +101267,79264,Male,Loyal Customer,61,Personal Travel,Eco,1598,0,4,0,2,4,0,4,4,3,3,4,4,4,4,0,0.0,satisfied +101268,61901,Female,disloyal Customer,36,Business travel,Business,550,2,1,1,2,3,1,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +101269,85809,Female,Loyal Customer,57,Personal Travel,Eco,526,2,4,2,1,2,2,5,3,2,4,4,5,4,5,188,199.0,neutral or dissatisfied +101270,82058,Male,Loyal Customer,31,Personal Travel,Eco Plus,1535,5,4,5,2,3,5,3,3,3,5,3,3,5,3,9,0.0,satisfied +101271,21117,Female,Loyal Customer,44,Personal Travel,Eco,214,2,1,2,4,1,3,3,4,4,2,4,2,4,1,72,67.0,neutral or dissatisfied +101272,55817,Male,Loyal Customer,55,Business travel,Business,1416,1,1,1,1,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +101273,92615,Male,Loyal Customer,57,Personal Travel,Business,453,2,3,2,2,5,3,5,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +101274,71995,Female,Loyal Customer,66,Personal Travel,Eco,1440,1,4,0,2,3,3,5,4,4,0,4,5,4,5,10,28.0,neutral or dissatisfied +101275,43735,Male,Loyal Customer,9,Personal Travel,Eco,615,3,1,3,2,3,3,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +101276,26528,Female,disloyal Customer,21,Business travel,Business,990,1,4,1,4,5,1,5,5,1,2,3,2,3,5,6,13.0,neutral or dissatisfied +101277,110799,Male,Loyal Customer,70,Personal Travel,Eco,849,3,1,3,2,5,3,4,5,3,1,3,4,2,5,0,0.0,neutral or dissatisfied +101278,49115,Female,Loyal Customer,32,Business travel,Business,1784,1,1,1,1,5,5,5,5,2,2,4,3,4,5,0,4.0,satisfied +101279,86844,Female,Loyal Customer,53,Personal Travel,Eco,484,3,0,3,5,3,5,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +101280,104701,Female,Loyal Customer,69,Personal Travel,Eco,159,3,5,3,3,2,5,4,3,3,3,1,4,3,3,11,10.0,neutral or dissatisfied +101281,86071,Male,Loyal Customer,33,Personal Travel,Eco Plus,528,3,4,3,3,2,3,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +101282,108592,Female,Loyal Customer,77,Business travel,Business,2172,2,3,4,3,3,2,1,2,2,2,2,2,2,1,14,0.0,neutral or dissatisfied +101283,60060,Female,Loyal Customer,48,Personal Travel,Eco Plus,1023,1,3,1,3,3,5,4,4,4,1,5,5,4,3,3,0.0,neutral or dissatisfied +101284,82300,Female,Loyal Customer,30,Business travel,Business,3659,1,1,5,1,1,2,1,1,4,4,4,4,4,1,54,47.0,satisfied +101285,111461,Male,Loyal Customer,25,Personal Travel,Eco,1024,4,4,4,4,4,4,4,4,4,2,4,3,5,4,7,9.0,neutral or dissatisfied +101286,127172,Female,Loyal Customer,26,Personal Travel,Eco,338,1,4,1,3,5,1,1,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +101287,54951,Female,Loyal Customer,21,Business travel,Business,1504,5,5,1,5,5,5,5,5,5,2,4,4,4,5,12,6.0,satisfied +101288,79148,Female,Loyal Customer,59,Personal Travel,Eco Plus,356,4,1,4,3,2,2,2,2,2,4,3,3,2,3,59,52.0,neutral or dissatisfied +101289,129154,Male,Loyal Customer,59,Business travel,Business,954,4,4,4,4,2,4,4,4,4,4,4,3,4,5,52,59.0,satisfied +101290,43723,Male,Loyal Customer,42,Personal Travel,Eco,257,3,4,0,4,3,0,3,3,2,2,4,1,4,3,0,0.0,neutral or dissatisfied +101291,44052,Female,Loyal Customer,64,Personal Travel,Eco,67,2,5,2,1,5,5,5,3,3,2,4,5,3,3,0,11.0,neutral or dissatisfied +101292,100326,Male,Loyal Customer,56,Business travel,Business,1871,2,5,5,5,1,4,3,2,2,2,2,3,2,3,0,14.0,neutral or dissatisfied +101293,21746,Male,Loyal Customer,40,Business travel,Eco,563,4,4,4,4,4,4,4,4,4,4,3,2,4,4,8,0.0,satisfied +101294,30783,Male,Loyal Customer,26,Business travel,Business,834,2,5,5,5,2,2,2,2,3,1,2,2,2,2,4,9.0,neutral or dissatisfied +101295,28675,Male,disloyal Customer,16,Business travel,Business,1309,5,4,5,1,5,5,2,4,4,4,5,2,4,2,0,1.0,satisfied +101296,24811,Male,disloyal Customer,27,Business travel,Eco,861,1,1,1,3,2,1,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +101297,92203,Female,Loyal Customer,56,Business travel,Business,2079,1,5,2,5,3,3,3,1,1,1,1,2,1,3,31,37.0,neutral or dissatisfied +101298,106848,Female,Loyal Customer,57,Personal Travel,Eco,1733,2,4,2,2,2,3,4,2,2,2,2,4,2,5,15,5.0,neutral or dissatisfied +101299,69810,Male,Loyal Customer,52,Business travel,Business,2754,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +101300,28529,Male,Loyal Customer,32,Business travel,Eco,2677,2,1,1,1,2,2,2,2,3,3,2,1,3,2,0,0.0,neutral or dissatisfied +101301,33688,Male,Loyal Customer,35,Business travel,Business,759,3,3,4,3,2,1,2,5,5,5,5,3,5,2,0,58.0,satisfied +101302,2543,Male,Loyal Customer,33,Business travel,Eco,280,2,3,3,3,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +101303,14384,Male,Loyal Customer,17,Business travel,Eco,789,0,5,0,3,2,0,2,2,3,5,4,3,1,2,5,1.0,satisfied +101304,8412,Female,Loyal Customer,60,Business travel,Business,2149,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +101305,127849,Male,Loyal Customer,49,Business travel,Business,3615,1,4,4,4,3,4,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +101306,27718,Male,Loyal Customer,16,Personal Travel,Business,909,3,3,3,4,5,3,5,5,5,4,3,1,1,5,0,0.0,neutral or dissatisfied +101307,22486,Female,Loyal Customer,19,Personal Travel,Eco,83,1,5,1,4,2,1,4,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +101308,64763,Male,Loyal Customer,40,Business travel,Business,1843,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +101309,10078,Male,disloyal Customer,37,Business travel,Business,258,4,4,4,3,3,4,2,3,5,3,5,3,4,3,22,0.0,neutral or dissatisfied +101310,43057,Male,Loyal Customer,43,Business travel,Eco,192,3,5,5,5,4,3,4,4,2,1,5,1,1,4,0,0.0,satisfied +101311,94584,Female,Loyal Customer,41,Business travel,Business,1735,2,2,2,2,2,4,4,4,4,4,4,4,4,3,19,16.0,satisfied +101312,70176,Female,Loyal Customer,46,Business travel,Business,258,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +101313,45826,Male,Loyal Customer,32,Personal Travel,Eco,216,4,0,0,2,4,0,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +101314,11099,Male,Loyal Customer,23,Personal Travel,Eco,163,1,4,1,1,3,1,5,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +101315,91589,Female,disloyal Customer,22,Business travel,Business,1199,4,5,4,1,4,4,1,4,5,5,5,3,4,4,0,0.0,satisfied +101316,33943,Male,Loyal Customer,50,Business travel,Eco,1188,5,1,5,1,5,5,5,5,3,5,4,3,3,5,54,50.0,satisfied +101317,8415,Male,Loyal Customer,45,Business travel,Business,1622,4,4,4,4,4,5,5,4,4,4,4,4,4,4,1,0.0,satisfied +101318,32011,Male,Loyal Customer,36,Business travel,Eco,216,4,4,4,4,4,4,4,4,3,4,1,2,4,4,0,0.0,satisfied +101319,45215,Female,Loyal Customer,37,Business travel,Eco,1013,1,1,1,1,1,1,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +101320,47619,Female,Loyal Customer,46,Business travel,Business,1504,4,4,4,4,1,1,3,4,4,4,4,2,4,5,0,0.0,satisfied +101321,35954,Male,Loyal Customer,39,Business travel,Business,231,2,1,1,1,2,4,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +101322,27309,Female,Loyal Customer,59,Business travel,Eco,697,5,1,1,1,2,4,2,5,5,5,5,1,5,2,0,0.0,satisfied +101323,94023,Female,Loyal Customer,52,Business travel,Business,2979,4,4,4,4,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +101324,57367,Male,Loyal Customer,17,Personal Travel,Eco,414,2,5,2,4,2,2,2,2,3,3,5,2,3,2,0,0.0,neutral or dissatisfied +101325,14440,Female,Loyal Customer,22,Business travel,Eco,674,4,5,5,5,5,5,4,5,4,1,2,2,4,5,117,131.0,satisfied +101326,16495,Male,Loyal Customer,46,Business travel,Business,143,1,4,4,4,2,2,1,2,2,2,1,3,2,3,11,10.0,neutral or dissatisfied +101327,18810,Male,Loyal Customer,27,Business travel,Business,2689,3,5,5,5,3,3,3,3,2,3,2,2,2,3,18,11.0,neutral or dissatisfied +101328,22783,Female,disloyal Customer,24,Business travel,Eco,147,3,4,3,2,4,3,4,4,2,2,1,3,3,4,0,0.0,neutral or dissatisfied +101329,87790,Male,disloyal Customer,21,Business travel,Business,214,1,3,1,4,1,1,1,1,2,5,3,4,3,1,0,0.0,neutral or dissatisfied +101330,59322,Female,Loyal Customer,20,Business travel,Business,2399,1,1,1,1,4,4,4,4,4,4,4,3,4,4,11,3.0,satisfied +101331,8192,Male,disloyal Customer,20,Business travel,Eco,335,3,3,3,2,4,3,4,4,5,1,5,2,3,4,0,0.0,neutral or dissatisfied +101332,63283,Male,Loyal Customer,62,Business travel,Business,3086,2,1,2,1,3,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +101333,65410,Female,disloyal Customer,20,Business travel,Business,631,4,0,4,4,2,4,2,2,4,2,4,5,4,2,0,0.0,satisfied +101334,12132,Male,Loyal Customer,28,Business travel,Business,2406,2,2,5,2,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +101335,10144,Female,Loyal Customer,41,Business travel,Business,1706,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +101336,81634,Female,Loyal Customer,47,Business travel,Business,907,5,5,5,5,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +101337,90429,Male,disloyal Customer,22,Business travel,Eco,581,4,5,4,3,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +101338,50578,Female,Loyal Customer,40,Personal Travel,Eco,209,1,4,1,5,2,1,2,2,2,4,5,2,5,2,0,3.0,neutral or dissatisfied +101339,53914,Female,Loyal Customer,50,Personal Travel,Eco,191,1,4,1,4,3,4,4,2,2,1,2,1,2,3,10,0.0,neutral or dissatisfied +101340,104327,Male,Loyal Customer,34,Business travel,Business,409,1,4,4,4,1,3,3,1,1,1,1,4,1,4,0,44.0,neutral or dissatisfied +101341,18778,Male,disloyal Customer,30,Business travel,Eco,448,2,0,2,1,1,2,3,1,2,3,3,2,3,1,0,0.0,neutral or dissatisfied +101342,70125,Male,Loyal Customer,40,Business travel,Business,550,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +101343,37949,Male,Loyal Customer,61,Personal Travel,Eco Plus,1068,4,4,4,1,4,4,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +101344,9337,Female,Loyal Customer,54,Business travel,Business,3048,1,1,1,1,4,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +101345,56282,Female,disloyal Customer,44,Business travel,Business,2227,5,4,4,3,5,1,1,5,2,4,4,1,3,1,0,25.0,satisfied +101346,50351,Female,Loyal Customer,33,Business travel,Business,207,1,1,1,1,3,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +101347,17482,Male,disloyal Customer,24,Business travel,Eco,341,3,0,3,3,3,3,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +101348,7052,Male,Loyal Customer,42,Business travel,Business,3350,4,2,2,2,4,4,4,3,3,3,4,1,3,1,0,0.0,neutral or dissatisfied +101349,22690,Male,Loyal Customer,52,Business travel,Eco,579,2,5,5,5,2,1,1,4,5,3,3,1,1,1,155,167.0,neutral or dissatisfied +101350,3402,Male,Loyal Customer,47,Business travel,Eco,296,1,3,3,3,1,1,1,1,4,5,3,4,4,1,24,22.0,neutral or dissatisfied +101351,24951,Female,Loyal Customer,10,Business travel,Business,1747,2,2,2,2,2,2,2,2,1,2,3,3,3,2,33,23.0,neutral or dissatisfied +101352,65516,Female,Loyal Customer,48,Business travel,Business,1616,2,2,2,2,2,4,5,3,3,3,3,3,3,4,0,11.0,satisfied +101353,76163,Male,Loyal Customer,63,Personal Travel,Eco,689,2,5,1,2,3,1,2,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +101354,128293,Female,disloyal Customer,26,Business travel,Business,621,4,4,4,1,2,4,2,2,3,3,5,5,5,2,0,0.0,satisfied +101355,77503,Female,Loyal Customer,28,Personal Travel,Eco,1195,4,5,4,1,2,4,2,2,4,3,4,4,5,2,0,0.0,neutral or dissatisfied +101356,114011,Female,Loyal Customer,15,Personal Travel,Eco,1750,4,4,4,1,5,4,4,5,3,2,5,5,1,5,10,7.0,neutral or dissatisfied +101357,49006,Male,Loyal Customer,40,Business travel,Eco,209,4,4,4,4,4,4,4,4,1,3,4,4,4,4,0,7.0,neutral or dissatisfied +101358,3480,Male,Loyal Customer,38,Business travel,Business,3764,3,3,3,3,5,5,4,3,3,4,3,3,3,5,0,19.0,satisfied +101359,64482,Male,Loyal Customer,56,Business travel,Business,3476,1,5,5,5,2,3,3,1,1,1,1,4,1,4,21,17.0,neutral or dissatisfied +101360,4608,Male,disloyal Customer,26,Business travel,Business,719,4,4,4,1,5,4,5,5,4,4,5,3,4,5,0,6.0,satisfied +101361,43122,Male,Loyal Customer,46,Personal Travel,Eco,236,3,5,3,5,4,3,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +101362,16399,Female,Loyal Customer,13,Personal Travel,Eco,533,3,5,3,2,4,3,2,4,4,2,5,5,5,4,5,5.0,neutral or dissatisfied +101363,44655,Male,Loyal Customer,43,Business travel,Business,1673,2,2,2,2,2,2,4,5,5,5,3,1,5,5,7,2.0,satisfied +101364,105340,Male,Loyal Customer,45,Business travel,Eco,528,3,5,5,5,3,3,3,3,1,5,3,1,4,3,21,17.0,neutral or dissatisfied +101365,23547,Male,Loyal Customer,25,Personal Travel,Eco,455,2,4,2,4,4,2,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +101366,88945,Female,Loyal Customer,28,Business travel,Business,1352,5,1,5,5,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +101367,48096,Male,Loyal Customer,36,Business travel,Business,259,5,5,5,5,2,4,3,4,4,4,4,4,4,1,0,0.0,satisfied +101368,62343,Male,Loyal Customer,10,Personal Travel,Eco Plus,414,1,0,4,5,2,4,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +101369,127334,Male,Loyal Customer,46,Business travel,Business,507,3,3,5,3,3,5,4,4,4,4,4,4,4,4,11,4.0,satisfied +101370,8508,Female,Loyal Customer,47,Business travel,Business,737,1,1,1,1,3,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +101371,60094,Female,disloyal Customer,29,Business travel,Business,1012,4,4,4,2,2,4,5,2,4,5,5,5,4,2,0,4.0,satisfied +101372,62888,Female,Loyal Customer,60,Business travel,Business,967,4,4,5,4,5,5,5,4,4,4,4,5,4,5,31,21.0,satisfied +101373,45640,Female,Loyal Customer,68,Personal Travel,Eco,260,1,2,1,4,1,4,3,2,2,1,2,1,2,1,0,35.0,neutral or dissatisfied +101374,120394,Female,disloyal Customer,44,Business travel,Business,337,5,5,5,3,1,5,1,1,4,4,4,3,4,1,8,12.0,satisfied +101375,122899,Male,Loyal Customer,38,Business travel,Business,631,4,4,4,4,5,4,4,5,5,5,5,4,5,4,14,55.0,satisfied +101376,3939,Male,Loyal Customer,38,Business travel,Business,3194,3,3,3,3,5,5,5,5,5,5,5,4,5,4,41,52.0,satisfied +101377,51320,Male,Loyal Customer,36,Business travel,Eco Plus,77,1,4,4,4,1,1,1,1,3,2,3,3,4,1,38,27.0,neutral or dissatisfied +101378,5407,Male,Loyal Customer,47,Personal Travel,Eco,785,3,4,3,1,3,3,3,3,3,3,5,3,5,3,45,28.0,neutral or dissatisfied +101379,77759,Female,Loyal Customer,56,Business travel,Business,289,4,4,4,4,2,4,4,4,4,4,4,4,4,4,6,26.0,neutral or dissatisfied +101380,32557,Male,Loyal Customer,70,Business travel,Business,1582,3,4,4,4,4,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +101381,12176,Female,Loyal Customer,45,Business travel,Business,986,2,1,4,1,2,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +101382,76965,Female,Loyal Customer,29,Personal Travel,Eco,1990,2,1,2,3,1,2,1,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +101383,104579,Male,Loyal Customer,47,Business travel,Business,2239,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +101384,110237,Male,Loyal Customer,40,Business travel,Business,3341,3,3,3,3,3,5,5,4,4,4,4,3,4,3,63,53.0,satisfied +101385,48182,Female,Loyal Customer,37,Business travel,Business,2582,4,3,3,3,3,3,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +101386,7820,Male,Loyal Customer,45,Business travel,Eco,310,5,5,5,5,5,5,5,5,5,3,1,5,3,5,0,0.0,satisfied +101387,92506,Male,Loyal Customer,51,Personal Travel,Eco,2139,4,5,3,4,2,3,2,2,5,5,4,5,5,2,0,0.0,satisfied +101388,4840,Female,Loyal Customer,39,Business travel,Eco,408,1,1,1,1,1,1,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +101389,5230,Female,disloyal Customer,25,Business travel,Business,293,4,5,4,3,2,4,2,2,4,4,5,5,5,2,29,53.0,neutral or dissatisfied +101390,62117,Female,Loyal Customer,56,Business travel,Business,2454,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +101391,119310,Female,Loyal Customer,36,Business travel,Business,3643,5,5,5,5,3,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +101392,59021,Male,Loyal Customer,46,Business travel,Business,1846,3,5,5,5,2,2,4,3,3,2,3,2,3,2,0,8.0,neutral or dissatisfied +101393,67835,Male,disloyal Customer,43,Business travel,Eco,771,2,2,2,3,3,2,3,3,4,4,3,4,3,3,7,17.0,neutral or dissatisfied +101394,9318,Male,Loyal Customer,58,Business travel,Business,419,2,5,5,5,4,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +101395,60187,Female,Loyal Customer,39,Business travel,Business,1005,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +101396,39156,Female,Loyal Customer,43,Business travel,Business,237,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +101397,112935,Male,Loyal Customer,41,Personal Travel,Eco,1476,1,4,1,4,2,1,2,2,3,3,3,3,1,2,4,0.0,neutral or dissatisfied +101398,109625,Male,Loyal Customer,36,Business travel,Business,2951,3,2,2,2,4,2,2,3,3,3,3,4,3,1,0,4.0,neutral or dissatisfied +101399,107243,Male,Loyal Customer,62,Business travel,Business,3463,2,2,2,2,4,4,4,5,5,5,5,5,5,5,0,6.0,satisfied +101400,93051,Female,Loyal Customer,54,Personal Travel,Eco Plus,436,3,4,3,4,5,4,4,1,1,3,1,3,1,5,7,42.0,neutral or dissatisfied +101401,48970,Female,disloyal Customer,25,Business travel,Eco,77,3,3,2,1,4,2,4,4,1,1,4,2,4,4,0,0.0,neutral or dissatisfied +101402,126140,Female,Loyal Customer,32,Business travel,Business,3904,4,4,4,4,4,4,4,4,4,5,4,3,5,4,16,2.0,satisfied +101403,33777,Female,Loyal Customer,39,Business travel,Business,2355,5,5,5,5,4,1,3,1,1,2,1,1,1,1,11,4.0,satisfied +101404,95793,Female,Loyal Customer,53,Business travel,Business,2778,4,4,4,4,3,5,4,4,4,5,4,3,4,3,8,7.0,satisfied +101405,35308,Male,Loyal Customer,25,Business travel,Business,2944,2,5,5,5,2,2,2,2,3,5,3,3,4,2,16,31.0,neutral or dissatisfied +101406,120143,Male,Loyal Customer,45,Business travel,Business,3310,2,2,2,2,2,1,2,4,4,4,4,4,4,1,0,0.0,satisfied +101407,74815,Male,Loyal Customer,43,Personal Travel,Eco Plus,1235,3,4,4,3,4,4,3,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +101408,14916,Male,Loyal Customer,15,Personal Travel,Eco,315,3,2,3,4,4,3,1,4,1,2,3,4,4,4,0,13.0,neutral or dissatisfied +101409,66516,Male,Loyal Customer,14,Personal Travel,Eco,447,2,5,2,2,4,2,4,4,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +101410,4640,Female,Loyal Customer,41,Business travel,Business,364,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +101411,17414,Female,Loyal Customer,47,Business travel,Business,351,5,5,5,5,4,1,4,5,5,5,5,4,5,2,0,0.0,satisfied +101412,17567,Female,Loyal Customer,59,Business travel,Eco,1034,3,2,2,2,5,4,4,3,3,3,3,1,3,2,3,0.0,neutral or dissatisfied +101413,101878,Female,Loyal Customer,30,Personal Travel,Eco,1747,3,3,3,4,1,3,5,1,1,5,3,4,4,1,5,0.0,neutral or dissatisfied +101414,52590,Female,Loyal Customer,58,Business travel,Business,2343,3,3,3,3,1,3,2,4,4,4,5,1,4,2,0,5.0,satisfied +101415,39706,Male,Loyal Customer,38,Business travel,Business,3612,2,2,2,2,3,5,3,5,5,5,5,3,5,5,0,0.0,satisfied +101416,59207,Female,Loyal Customer,79,Business travel,Business,1584,2,3,3,3,2,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +101417,97522,Female,Loyal Customer,51,Business travel,Business,2174,3,4,4,4,5,2,1,3,3,3,3,4,3,3,55,50.0,neutral or dissatisfied +101418,99931,Female,Loyal Customer,62,Personal Travel,Eco,764,4,4,4,5,3,5,4,3,3,4,3,3,3,4,20,22.0,neutral or dissatisfied +101419,9694,Female,Loyal Customer,16,Personal Travel,Eco,277,4,2,4,3,5,4,5,5,4,3,3,1,2,5,120,97.0,neutral or dissatisfied +101420,83501,Male,Loyal Customer,33,Personal Travel,Eco,946,2,5,2,3,2,2,2,2,3,5,2,2,2,2,0,0.0,neutral or dissatisfied +101421,21925,Male,Loyal Customer,46,Business travel,Business,448,1,1,1,1,1,3,1,5,5,5,5,1,5,4,0,0.0,satisfied +101422,48005,Female,Loyal Customer,45,Business travel,Eco Plus,834,3,2,2,2,3,4,3,3,3,3,3,1,3,2,0,24.0,neutral or dissatisfied +101423,45823,Female,Loyal Customer,60,Personal Travel,Eco,391,1,4,2,3,2,4,4,5,5,2,5,4,5,4,8,0.0,neutral or dissatisfied +101424,106217,Male,Loyal Customer,49,Business travel,Business,3865,1,1,1,1,3,5,4,4,4,4,4,4,4,5,5,0.0,satisfied +101425,9787,Male,Loyal Customer,16,Personal Travel,Eco,456,3,4,3,1,5,3,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +101426,89142,Female,Loyal Customer,41,Business travel,Business,2320,1,1,1,1,3,2,1,5,5,5,5,5,5,5,0,0.0,satisfied +101427,108031,Female,Loyal Customer,41,Business travel,Business,2905,0,0,0,3,3,4,4,3,3,3,3,4,3,5,5,2.0,satisfied +101428,61425,Female,Loyal Customer,48,Business travel,Business,2288,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +101429,86757,Female,Loyal Customer,62,Personal Travel,Eco,821,4,4,5,2,4,5,4,2,2,5,2,5,2,5,0,0.0,neutral or dissatisfied +101430,122477,Male,Loyal Customer,9,Business travel,Business,575,3,3,5,3,3,3,3,3,2,4,2,1,3,3,58,47.0,neutral or dissatisfied +101431,17833,Male,Loyal Customer,32,Business travel,Eco Plus,931,3,4,4,4,3,3,3,3,4,1,3,1,4,3,0,0.0,neutral or dissatisfied +101432,51389,Male,Loyal Customer,29,Personal Travel,Eco Plus,363,1,1,1,2,4,1,4,4,3,2,3,4,2,4,0,0.0,neutral or dissatisfied +101433,5520,Male,Loyal Customer,75,Business travel,Business,2350,3,3,3,3,2,5,5,4,4,4,4,5,4,5,0,7.0,satisfied +101434,4147,Male,Loyal Customer,52,Business travel,Business,2960,4,1,1,1,5,2,2,4,4,4,4,1,4,4,8,0.0,neutral or dissatisfied +101435,42014,Female,Loyal Customer,68,Business travel,Eco,116,5,4,2,4,5,2,3,5,5,5,5,2,5,2,0,0.0,satisfied +101436,86827,Female,disloyal Customer,65,Business travel,Eco,484,2,2,3,4,1,3,1,1,2,5,3,1,4,1,0,0.0,neutral or dissatisfied +101437,74424,Female,Loyal Customer,51,Business travel,Business,1660,1,1,1,1,5,4,4,5,5,5,5,5,5,5,17,9.0,satisfied +101438,64973,Female,disloyal Customer,24,Business travel,Eco,247,3,4,4,4,1,4,1,1,5,2,5,2,1,1,0,2.0,neutral or dissatisfied +101439,5726,Female,Loyal Customer,74,Business travel,Eco Plus,299,4,1,1,1,4,3,3,1,3,1,2,3,4,3,115,138.0,neutral or dissatisfied +101440,50934,Male,Loyal Customer,22,Personal Travel,Eco,78,3,2,3,3,3,3,3,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +101441,13868,Male,Loyal Customer,41,Business travel,Eco,760,3,1,2,1,3,3,3,3,4,1,2,3,2,3,0,1.0,neutral or dissatisfied +101442,34047,Female,Loyal Customer,67,Personal Travel,Business,1674,3,4,4,5,1,4,5,1,1,4,1,1,1,3,65,61.0,neutral or dissatisfied +101443,18520,Female,Loyal Customer,30,Business travel,Business,3029,5,5,3,5,4,4,4,4,1,2,5,5,1,4,0,0.0,satisfied +101444,80851,Female,Loyal Customer,48,Business travel,Business,292,2,2,2,2,4,3,4,2,2,3,2,4,2,1,7,38.0,neutral or dissatisfied +101445,19366,Male,Loyal Customer,52,Personal Travel,Business,476,2,4,4,3,1,2,4,1,1,4,1,5,1,4,8,0.0,neutral or dissatisfied +101446,21245,Male,Loyal Customer,46,Business travel,Eco Plus,192,4,2,4,2,3,4,3,3,2,5,3,4,2,3,0,2.0,satisfied +101447,120908,Female,Loyal Customer,45,Business travel,Business,2529,5,5,5,5,2,5,5,5,5,5,5,4,5,3,0,17.0,satisfied +101448,123154,Female,Loyal Customer,32,Business travel,Business,3783,2,1,3,1,2,2,2,2,2,2,3,1,3,2,54,51.0,neutral or dissatisfied +101449,23871,Female,disloyal Customer,26,Business travel,Eco Plus,522,3,3,3,4,3,3,3,3,1,1,3,3,3,3,0,10.0,neutral or dissatisfied +101450,92526,Female,Loyal Customer,18,Personal Travel,Eco,1947,3,4,3,3,1,3,1,1,3,3,3,3,5,1,0,0.0,neutral or dissatisfied +101451,127697,Female,disloyal Customer,25,Business travel,Business,2133,4,4,4,5,5,4,3,5,5,2,3,3,4,5,12,0.0,neutral or dissatisfied +101452,10147,Male,Loyal Customer,41,Business travel,Eco,801,3,5,5,5,3,3,3,3,5,5,2,2,2,3,11,0.0,satisfied +101453,24193,Female,Loyal Customer,37,Business travel,Eco,147,4,3,3,3,4,4,4,4,4,5,2,3,2,4,0,0.0,satisfied +101454,85937,Male,Loyal Customer,30,Personal Travel,Business,554,3,5,3,4,3,3,2,3,4,5,5,3,5,3,2,0.0,neutral or dissatisfied +101455,44374,Female,Loyal Customer,52,Business travel,Eco Plus,596,5,2,5,5,1,1,4,4,4,5,4,4,4,5,0,0.0,satisfied +101456,54949,Male,Loyal Customer,45,Personal Travel,Business,1379,2,1,2,3,3,1,3,2,2,2,2,3,2,1,1,0.0,neutral or dissatisfied +101457,50119,Male,disloyal Customer,15,Business travel,Eco,153,3,1,3,3,5,3,4,5,3,1,3,1,4,5,0,0.0,neutral or dissatisfied +101458,52751,Female,Loyal Customer,29,Business travel,Eco Plus,2306,5,2,3,2,5,5,5,5,5,4,3,2,2,5,0,0.0,satisfied +101459,107869,Male,disloyal Customer,43,Business travel,Business,228,2,2,2,4,4,2,4,4,1,3,3,2,3,4,21,6.0,neutral or dissatisfied +101460,3659,Female,disloyal Customer,37,Business travel,Eco,431,3,1,3,3,5,3,5,5,2,4,3,1,4,5,6,0.0,neutral or dissatisfied +101461,25129,Female,Loyal Customer,30,Business travel,Business,1249,2,2,2,2,4,4,4,4,4,3,4,5,3,4,26,30.0,satisfied +101462,98641,Female,Loyal Customer,35,Business travel,Business,966,1,5,5,5,2,3,3,1,1,1,1,4,1,4,96,95.0,neutral or dissatisfied +101463,22615,Female,Loyal Customer,26,Personal Travel,Eco,223,5,4,5,1,5,5,5,5,5,4,5,5,4,5,96,87.0,satisfied +101464,112131,Female,Loyal Customer,22,Personal Travel,Business,895,3,5,3,3,4,3,4,4,1,2,3,2,4,4,28,16.0,neutral or dissatisfied +101465,118413,Male,Loyal Customer,48,Business travel,Business,325,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +101466,129578,Male,Loyal Customer,32,Personal Travel,Eco Plus,2342,1,4,1,4,3,1,3,3,3,3,4,1,3,3,28,31.0,neutral or dissatisfied +101467,88801,Male,Loyal Customer,55,Business travel,Business,2422,2,2,2,2,5,4,4,5,5,5,5,5,5,5,8,6.0,satisfied +101468,26310,Male,disloyal Customer,25,Business travel,Eco,1493,1,1,1,3,1,1,1,1,2,4,3,1,4,1,8,20.0,neutral or dissatisfied +101469,111724,Female,Loyal Customer,38,Personal Travel,Eco,541,2,5,3,4,2,3,2,2,3,2,5,3,5,2,1,0.0,neutral or dissatisfied +101470,60019,Female,Loyal Customer,57,Personal Travel,Eco,1065,3,4,3,1,2,4,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +101471,45685,Female,Loyal Customer,32,Business travel,Business,896,3,3,3,3,4,4,4,4,1,3,5,1,3,4,0,0.0,satisfied +101472,29721,Female,disloyal Customer,26,Business travel,Eco,2874,1,1,1,1,1,2,2,2,5,4,5,2,2,2,0,0.0,neutral or dissatisfied +101473,115255,Female,Loyal Customer,52,Business travel,Business,3858,0,0,0,3,3,5,4,4,4,4,4,3,4,4,24,16.0,satisfied +101474,46620,Male,Loyal Customer,30,Business travel,Eco,251,1,5,3,5,1,1,1,1,3,4,4,1,4,1,0,8.0,neutral or dissatisfied +101475,42489,Female,Loyal Customer,25,Business travel,Business,1726,1,2,2,2,1,1,1,1,2,2,3,4,3,1,0,5.0,neutral or dissatisfied +101476,202,Male,disloyal Customer,38,Business travel,Business,213,3,3,3,3,5,3,5,5,5,4,5,4,4,5,17,4.0,neutral or dissatisfied +101477,114980,Male,Loyal Customer,42,Business travel,Business,373,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +101478,83246,Male,Loyal Customer,59,Business travel,Business,1979,3,3,4,3,4,4,4,3,3,3,3,4,3,4,0,1.0,satisfied +101479,17831,Male,Loyal Customer,37,Business travel,Eco Plus,1075,1,2,2,2,1,2,1,1,2,1,1,3,2,1,0,0.0,satisfied +101480,31969,Male,Loyal Customer,47,Business travel,Business,101,2,3,3,3,3,4,4,1,1,1,2,4,1,3,0,0.0,neutral or dissatisfied +101481,116628,Male,Loyal Customer,57,Business travel,Business,3070,2,2,2,2,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +101482,48553,Male,Loyal Customer,21,Personal Travel,Eco,850,2,4,2,4,1,2,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +101483,89453,Female,Loyal Customer,18,Personal Travel,Eco,134,2,4,2,4,5,2,5,5,2,4,3,3,4,5,0,0.0,neutral or dissatisfied +101484,97536,Female,disloyal Customer,34,Business travel,Eco,462,3,1,3,2,1,3,1,1,4,2,2,2,2,1,0,0.0,neutral or dissatisfied +101485,124261,Female,Loyal Customer,55,Personal Travel,Eco Plus,1916,4,4,5,3,5,2,4,5,5,5,2,1,5,2,0,0.0,neutral or dissatisfied +101486,66864,Male,Loyal Customer,37,Personal Travel,Eco,731,1,4,1,2,4,1,4,4,1,5,1,3,5,4,0,0.0,neutral or dissatisfied +101487,90921,Male,Loyal Customer,54,Business travel,Eco,181,4,5,5,5,5,4,5,5,3,5,1,2,2,5,0,0.0,satisfied +101488,73383,Female,Loyal Customer,59,Business travel,Business,3800,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +101489,111699,Female,Loyal Customer,48,Business travel,Business,541,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +101490,53526,Male,Loyal Customer,61,Personal Travel,Eco,2288,1,2,1,3,1,1,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +101491,25932,Female,Loyal Customer,52,Personal Travel,Eco,594,4,1,4,4,1,4,3,5,5,4,5,1,5,2,5,10.0,neutral or dissatisfied +101492,35635,Female,Loyal Customer,33,Business travel,Eco,1626,5,2,4,4,5,5,5,5,3,3,5,3,3,5,32,29.0,satisfied +101493,48433,Female,Loyal Customer,43,Business travel,Eco,916,4,5,2,2,1,5,1,4,4,4,4,3,4,1,6,0.0,satisfied +101494,115893,Female,disloyal Customer,24,Business travel,Eco,358,4,2,4,5,4,4,4,4,5,4,5,4,2,4,0,0.0,satisfied +101495,15012,Male,Loyal Customer,44,Business travel,Business,3284,1,1,4,1,2,5,3,4,4,4,4,1,4,5,0,0.0,satisfied +101496,120205,Male,Loyal Customer,57,Business travel,Business,1430,3,3,3,3,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +101497,58026,Female,Loyal Customer,12,Personal Travel,Eco,1721,1,5,1,4,1,1,4,1,4,2,4,3,4,1,9,8.0,neutral or dissatisfied +101498,117203,Female,Loyal Customer,65,Personal Travel,Eco,451,4,4,4,3,4,1,5,5,5,4,5,3,5,5,0,0.0,satisfied +101499,94739,Female,Loyal Customer,54,Business travel,Business,3654,4,5,3,5,4,4,4,4,4,4,4,3,4,1,25,19.0,neutral or dissatisfied +101500,87787,Male,disloyal Customer,20,Business travel,Business,214,2,1,2,2,4,2,3,4,4,1,2,4,3,4,0,0.0,neutral or dissatisfied +101501,96796,Female,Loyal Customer,56,Business travel,Business,3885,4,4,5,4,5,5,5,4,4,4,4,3,4,3,8,3.0,satisfied +101502,50129,Male,Loyal Customer,56,Business travel,Eco,199,3,5,5,5,3,3,3,3,2,3,3,3,2,3,0,0.0,neutral or dissatisfied +101503,98423,Female,Loyal Customer,49,Business travel,Business,1910,4,4,3,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +101504,58155,Female,Loyal Customer,42,Business travel,Business,3789,4,4,4,4,5,4,5,3,3,3,3,3,3,3,9,7.0,satisfied +101505,120456,Male,Loyal Customer,8,Personal Travel,Eco,337,5,1,5,3,2,5,2,2,4,1,2,3,3,2,0,0.0,satisfied +101506,23565,Female,Loyal Customer,46,Business travel,Eco,680,5,4,4,4,5,5,5,5,5,5,5,2,5,5,0,0.0,satisfied +101507,105919,Female,Loyal Customer,58,Business travel,Business,2863,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +101508,113942,Male,Loyal Customer,43,Business travel,Business,1855,1,1,1,1,3,5,5,5,5,5,5,5,5,5,3,2.0,satisfied +101509,25860,Female,Loyal Customer,50,Personal Travel,Eco,484,3,0,3,4,2,5,4,2,2,3,2,4,2,5,3,0.0,neutral or dissatisfied +101510,106153,Female,disloyal Customer,26,Business travel,Eco,436,3,2,4,4,3,4,3,3,4,5,3,1,4,3,0,0.0,neutral or dissatisfied +101511,101405,Male,Loyal Customer,66,Personal Travel,Eco,486,3,0,3,3,3,3,3,3,4,2,4,3,4,3,48,38.0,neutral or dissatisfied +101512,63496,Female,Loyal Customer,49,Personal Travel,Eco,2018,5,4,5,3,5,4,4,4,4,5,5,5,4,5,0,0.0,satisfied +101513,83,Male,Loyal Customer,58,Personal Travel,Eco,215,2,2,2,4,2,4,4,3,2,3,4,4,3,4,254,254.0,neutral or dissatisfied +101514,121863,Male,Loyal Customer,58,Business travel,Business,2790,5,5,5,5,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +101515,81734,Male,Loyal Customer,38,Business travel,Business,1306,3,3,3,3,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +101516,25698,Female,disloyal Customer,43,Business travel,Eco,528,1,0,1,4,4,1,4,4,3,2,5,3,1,4,43,51.0,neutral or dissatisfied +101517,95702,Female,disloyal Customer,23,Business travel,Eco,181,2,4,2,1,4,2,2,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +101518,84659,Female,disloyal Customer,41,Business travel,Business,2182,1,1,1,4,5,1,5,5,5,3,5,4,4,5,3,16.0,neutral or dissatisfied +101519,99776,Male,Loyal Customer,47,Business travel,Business,1871,5,5,5,5,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +101520,118266,Female,Loyal Customer,68,Personal Travel,Eco Plus,1788,2,4,2,4,2,4,5,4,4,2,4,5,4,4,8,0.0,neutral or dissatisfied +101521,91394,Female,disloyal Customer,44,Business travel,Eco,1304,3,3,3,3,4,3,4,4,4,3,3,4,3,4,12,11.0,neutral or dissatisfied +101522,33167,Male,Loyal Customer,31,Personal Travel,Eco,163,3,4,3,3,3,3,3,3,3,4,4,3,5,3,0,1.0,neutral or dissatisfied +101523,14712,Female,Loyal Customer,49,Personal Travel,Eco,419,4,1,4,4,3,3,4,3,3,4,3,4,3,1,5,0.0,neutral or dissatisfied +101524,40033,Male,Loyal Customer,32,Personal Travel,Eco,618,3,5,3,2,5,3,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +101525,115030,Female,disloyal Customer,41,Business travel,Business,342,5,5,5,4,2,5,2,2,5,2,5,5,4,2,27,19.0,satisfied +101526,25221,Female,Loyal Customer,40,Business travel,Eco,919,3,1,1,1,3,3,3,3,1,2,4,2,3,3,15,15.0,neutral or dissatisfied +101527,76605,Female,disloyal Customer,20,Business travel,Eco,481,2,3,2,4,1,2,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +101528,74447,Male,Loyal Customer,44,Business travel,Business,1431,4,4,4,4,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +101529,23787,Male,Loyal Customer,61,Business travel,Eco,374,3,4,4,4,3,3,3,3,2,2,4,1,4,3,12,1.0,neutral or dissatisfied +101530,38464,Female,Loyal Customer,10,Personal Travel,Eco Plus,1504,1,4,1,4,4,1,1,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +101531,26879,Male,Loyal Customer,39,Personal Travel,Business,689,4,4,4,1,3,5,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +101532,74223,Female,Loyal Customer,61,Personal Travel,Eco,1746,4,3,4,4,1,4,3,3,3,4,4,2,3,2,0,,neutral or dissatisfied +101533,20895,Female,Loyal Customer,17,Personal Travel,Eco,961,4,5,5,4,1,5,1,1,5,5,4,5,4,1,84,65.0,neutral or dissatisfied +101534,11429,Female,Loyal Customer,60,Business travel,Business,2080,0,4,0,3,2,4,5,4,4,4,5,3,4,5,2,0.0,satisfied +101535,52453,Male,Loyal Customer,49,Business travel,Eco Plus,237,4,1,5,1,4,4,4,4,3,2,5,3,1,4,9,6.0,satisfied +101536,38282,Female,Loyal Customer,34,Personal Travel,Eco,1173,2,2,2,4,5,2,4,5,4,4,2,2,3,5,58,56.0,neutral or dissatisfied +101537,45484,Male,Loyal Customer,49,Business travel,Business,122,1,3,3,3,2,3,4,4,4,4,1,4,4,3,0,0.0,neutral or dissatisfied +101538,1943,Female,Loyal Customer,39,Business travel,Business,2092,2,2,2,2,2,4,4,5,5,5,5,4,5,5,9,0.0,satisfied +101539,62598,Female,Loyal Customer,47,Business travel,Business,346,0,1,1,2,5,3,5,5,5,5,5,1,5,4,5,58.0,satisfied +101540,35184,Male,Loyal Customer,25,Business travel,Business,2230,1,1,1,1,4,4,4,4,3,1,5,2,2,4,2,13.0,satisfied +101541,56438,Male,Loyal Customer,60,Business travel,Eco,319,3,3,3,3,3,3,3,3,5,5,5,5,5,3,0,0.0,satisfied +101542,88277,Female,disloyal Customer,25,Business travel,Business,594,2,4,2,4,5,2,5,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +101543,17772,Male,Loyal Customer,31,Business travel,Business,3094,3,1,1,1,3,4,3,3,2,3,1,1,5,3,0,0.0,neutral or dissatisfied +101544,111506,Male,Loyal Customer,60,Business travel,Business,3887,1,1,1,1,3,4,4,4,4,4,4,4,4,5,8,4.0,satisfied +101545,129470,Female,Loyal Customer,31,Business travel,Business,2611,1,2,2,2,1,1,1,1,1,3,2,1,4,1,2,0.0,neutral or dissatisfied +101546,69676,Male,Loyal Customer,39,Personal Travel,Eco,569,4,4,4,2,4,4,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +101547,85343,Male,Loyal Customer,47,Business travel,Business,3071,5,5,5,5,5,5,4,5,5,4,5,5,5,4,0,2.0,satisfied +101548,59236,Female,Loyal Customer,55,Personal Travel,Eco,649,4,5,4,4,4,1,5,2,2,4,2,1,2,5,0,0.0,satisfied +101549,120970,Male,Loyal Customer,48,Business travel,Business,951,2,2,3,2,3,4,4,4,4,4,4,3,4,3,0,5.0,satisfied +101550,125409,Male,Loyal Customer,25,Personal Travel,Eco Plus,1440,2,5,2,4,1,2,1,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +101551,95822,Female,Loyal Customer,54,Business travel,Business,1428,4,2,2,2,4,4,4,4,4,4,4,1,4,2,3,0.0,neutral or dissatisfied +101552,129809,Female,Loyal Customer,21,Personal Travel,Eco,421,2,4,2,4,2,2,2,2,3,2,2,4,4,2,0,0.0,neutral or dissatisfied +101553,25411,Female,Loyal Customer,40,Personal Travel,Eco,1105,2,5,2,2,3,2,3,3,2,5,2,2,3,3,3,24.0,neutral or dissatisfied +101554,102919,Male,Loyal Customer,56,Business travel,Business,1730,4,4,4,4,5,5,5,3,3,4,3,4,3,3,1,0.0,satisfied +101555,100969,Female,Loyal Customer,47,Personal Travel,Eco,1142,3,3,3,1,5,1,4,2,2,3,1,3,2,2,0,10.0,neutral or dissatisfied +101556,54530,Female,Loyal Customer,67,Personal Travel,Eco,925,3,5,3,3,4,4,1,4,4,3,4,4,4,4,3,7.0,neutral or dissatisfied +101557,28164,Male,Loyal Customer,55,Business travel,Business,3413,5,3,3,3,5,3,3,5,5,4,5,1,5,2,0,4.0,neutral or dissatisfied +101558,26601,Female,Loyal Customer,33,Business travel,Business,1936,2,2,2,2,4,4,1,4,4,4,4,2,4,1,0,0.0,satisfied +101559,87164,Female,disloyal Customer,31,Business travel,Eco,946,2,2,2,3,2,2,2,2,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +101560,48865,Female,Loyal Customer,44,Business travel,Eco,304,2,1,1,1,5,5,3,2,2,2,2,5,2,3,0,0.0,satisfied +101561,2279,Female,Loyal Customer,26,Business travel,Business,1720,2,2,2,2,2,2,2,2,5,3,4,3,5,2,34,38.0,satisfied +101562,97002,Male,Loyal Customer,10,Personal Travel,Eco,775,1,2,1,3,3,1,3,3,4,5,4,1,3,3,0,4.0,neutral or dissatisfied +101563,42880,Female,Loyal Customer,52,Personal Travel,Eco,867,2,4,2,3,4,5,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +101564,121329,Male,disloyal Customer,28,Business travel,Business,1009,3,3,3,4,4,3,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +101565,86236,Female,Loyal Customer,63,Personal Travel,Eco,356,0,5,0,2,0,5,5,5,3,5,5,5,4,5,178,163.0,satisfied +101566,105967,Female,Loyal Customer,48,Business travel,Business,2329,1,1,1,1,5,5,5,5,5,3,5,5,4,5,2,0.0,satisfied +101567,85269,Female,Loyal Customer,39,Personal Travel,Eco,689,1,4,1,4,3,1,3,3,4,4,5,5,5,3,24,22.0,neutral or dissatisfied +101568,95012,Female,Loyal Customer,8,Personal Travel,Eco,189,5,4,0,4,3,0,1,3,4,2,5,4,5,3,0,0.0,satisfied +101569,113213,Female,Loyal Customer,41,Business travel,Business,258,2,1,1,1,5,3,2,2,2,2,2,4,2,2,30,13.0,neutral or dissatisfied +101570,49531,Male,Loyal Customer,57,Business travel,Eco,266,5,3,3,3,5,5,5,5,3,4,5,3,2,5,0,6.0,satisfied +101571,19253,Male,Loyal Customer,57,Business travel,Business,420,4,3,2,3,2,3,3,4,4,4,4,2,4,2,46,43.0,neutral or dissatisfied +101572,66566,Male,Loyal Customer,40,Business travel,Business,3569,2,2,2,2,3,4,4,5,5,5,5,5,5,4,90,92.0,satisfied +101573,91419,Male,Loyal Customer,59,Business travel,Business,549,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,28.0,satisfied +101574,101499,Female,Loyal Customer,29,Business travel,Business,345,3,3,4,3,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +101575,127011,Male,Loyal Customer,46,Business travel,Business,2104,2,2,2,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +101576,125189,Male,disloyal Customer,25,Business travel,Business,651,3,5,2,3,2,2,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +101577,35566,Female,Loyal Customer,49,Business travel,Eco Plus,1028,2,1,1,1,5,4,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +101578,8943,Female,Loyal Customer,38,Business travel,Business,2480,1,2,2,2,4,3,3,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +101579,71105,Female,Loyal Customer,29,Business travel,Eco Plus,802,4,3,2,2,4,3,4,4,4,3,3,1,4,4,0,0.0,neutral or dissatisfied +101580,66993,Male,Loyal Customer,57,Business travel,Business,964,1,1,1,1,4,5,5,3,3,3,3,3,3,3,14,14.0,satisfied +101581,123158,Female,Loyal Customer,57,Business travel,Business,107,2,2,2,2,4,1,5,4,4,4,3,3,4,2,0,0.0,satisfied +101582,20938,Female,Loyal Customer,10,Business travel,Business,689,4,5,5,5,4,4,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +101583,15587,Male,disloyal Customer,64,Business travel,Business,229,3,3,3,4,1,3,1,1,2,1,4,1,4,1,0,0.0,neutral or dissatisfied +101584,75575,Female,disloyal Customer,23,Business travel,Eco,337,2,0,2,3,5,2,3,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +101585,107463,Male,Loyal Customer,45,Business travel,Business,1768,5,5,5,5,2,4,5,5,5,5,5,4,5,5,13,0.0,satisfied +101586,22914,Male,Loyal Customer,42,Business travel,Business,630,3,2,4,4,5,3,3,3,3,4,3,3,3,4,9,0.0,neutral or dissatisfied +101587,106210,Female,Loyal Customer,52,Business travel,Eco Plus,436,5,5,5,5,1,1,4,5,5,5,5,2,5,3,6,16.0,satisfied +101588,19278,Male,Loyal Customer,45,Business travel,Eco,430,3,3,3,3,3,3,3,3,4,3,4,1,2,3,0,0.0,satisfied +101589,94942,Male,Loyal Customer,63,Business travel,Business,192,4,5,5,5,2,4,3,1,1,1,4,1,1,4,12,14.0,neutral or dissatisfied +101590,58340,Female,Loyal Customer,59,Business travel,Business,3297,0,0,0,5,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +101591,50244,Female,disloyal Customer,38,Business travel,Eco,77,3,4,3,4,2,3,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +101592,123378,Female,Loyal Customer,40,Personal Travel,Eco,644,2,5,2,3,4,2,4,4,4,4,4,4,5,4,13,0.0,neutral or dissatisfied +101593,91276,Female,Loyal Customer,48,Business travel,Business,240,1,1,1,1,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +101594,16418,Male,Loyal Customer,44,Business travel,Eco,416,4,5,5,5,4,4,4,4,4,4,3,3,2,4,1,0.0,satisfied +101595,30664,Female,disloyal Customer,22,Business travel,Eco Plus,770,2,5,1,4,2,1,2,2,2,5,5,1,2,2,0,29.0,neutral or dissatisfied +101596,106409,Female,Loyal Customer,46,Personal Travel,Eco,488,2,4,2,4,2,3,5,4,4,2,4,5,4,4,49,43.0,neutral or dissatisfied +101597,64046,Male,Loyal Customer,59,Business travel,Eco,919,2,1,1,1,2,2,2,2,2,1,1,3,1,2,0,0.0,neutral or dissatisfied +101598,75093,Male,Loyal Customer,28,Business travel,Business,1723,4,4,2,4,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +101599,17108,Male,Loyal Customer,28,Personal Travel,Eco,466,3,4,3,1,2,3,2,2,5,2,5,3,4,2,72,88.0,neutral or dissatisfied +101600,69244,Male,Loyal Customer,23,Business travel,Business,733,2,2,3,2,2,2,2,2,4,4,1,3,2,2,0,0.0,neutral or dissatisfied +101601,17395,Male,Loyal Customer,44,Business travel,Eco,351,5,5,5,5,5,5,5,5,4,1,1,3,5,5,45,32.0,satisfied +101602,119316,Female,Loyal Customer,26,Personal Travel,Eco,214,3,1,3,4,3,3,3,3,2,2,4,4,3,3,0,7.0,neutral or dissatisfied +101603,78367,Male,Loyal Customer,48,Personal Travel,Business,726,1,1,1,4,1,4,3,1,1,1,1,4,1,1,0,13.0,neutral or dissatisfied +101604,60544,Male,Loyal Customer,17,Personal Travel,Eco,862,3,5,3,2,4,3,4,4,5,4,5,3,5,4,10,30.0,neutral or dissatisfied +101605,104769,Female,Loyal Customer,29,Business travel,Eco Plus,1246,4,1,1,1,3,4,4,2,2,4,3,4,1,4,186,173.0,neutral or dissatisfied +101606,54541,Male,Loyal Customer,30,Personal Travel,Eco,925,3,5,3,4,2,3,5,2,3,2,5,4,5,2,2,0.0,neutral or dissatisfied +101607,35095,Female,Loyal Customer,45,Business travel,Business,2836,2,2,4,2,5,1,1,4,4,4,4,5,4,5,0,0.0,satisfied +101608,11844,Male,Loyal Customer,31,Personal Travel,Eco Plus,986,2,4,3,2,3,3,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +101609,108574,Female,disloyal Customer,26,Business travel,Business,696,4,4,4,1,5,4,5,5,5,4,5,5,5,5,1,0.0,neutral or dissatisfied +101610,26744,Male,Loyal Customer,58,Business travel,Business,3101,5,5,5,5,3,4,4,4,4,4,4,5,4,3,3,8.0,satisfied +101611,48905,Female,Loyal Customer,30,Business travel,Business,109,0,3,0,4,4,5,5,4,2,4,4,1,5,4,0,0.0,satisfied +101612,85227,Female,Loyal Customer,30,Business travel,Business,3998,3,3,3,3,4,4,4,4,4,4,1,2,1,4,0,0.0,satisfied +101613,127412,Male,Loyal Customer,64,Personal Travel,Eco,868,5,4,5,4,3,5,3,3,3,3,3,2,3,3,0,0.0,satisfied +101614,70387,Male,Loyal Customer,47,Business travel,Business,1562,3,3,3,3,4,4,4,3,4,5,4,4,5,4,188,194.0,satisfied +101615,4895,Female,Loyal Customer,27,Business travel,Business,3539,3,5,5,5,3,3,3,3,2,4,2,4,3,3,0,0.0,neutral or dissatisfied +101616,100753,Female,Loyal Customer,26,Personal Travel,Eco,328,1,5,1,4,5,1,5,5,5,5,5,3,4,5,13,27.0,neutral or dissatisfied +101617,53305,Male,Loyal Customer,30,Business travel,Eco,811,4,2,4,2,4,4,4,4,2,4,3,1,3,4,0,0.0,neutral or dissatisfied +101618,118800,Male,Loyal Customer,21,Personal Travel,Eco,338,3,5,3,2,3,3,3,3,2,1,1,5,5,3,24,24.0,neutral or dissatisfied +101619,100050,Male,Loyal Customer,23,Personal Travel,Eco,220,2,3,2,2,1,2,1,1,4,5,5,5,5,1,9,0.0,neutral or dissatisfied +101620,41144,Male,Loyal Customer,41,Personal Travel,Eco,216,4,0,4,1,3,4,4,3,3,4,3,3,1,3,25,20.0,neutral or dissatisfied +101621,51429,Male,Loyal Customer,15,Personal Travel,Eco Plus,262,3,2,3,4,4,3,4,4,2,4,4,4,4,4,3,3.0,neutral or dissatisfied +101622,62208,Female,Loyal Customer,29,Personal Travel,Eco,2565,2,3,2,3,2,2,2,2,1,4,4,1,4,2,13,0.0,neutral or dissatisfied +101623,128602,Female,Loyal Customer,31,Business travel,Business,3971,3,3,3,3,5,5,5,5,5,2,5,4,5,5,0,5.0,satisfied +101624,76486,Male,Loyal Customer,55,Business travel,Business,2062,3,3,3,3,2,5,5,4,4,4,4,4,4,5,40,45.0,satisfied +101625,100347,Female,Loyal Customer,8,Personal Travel,Eco,1033,2,1,2,3,4,2,4,4,2,1,4,3,3,4,0,0.0,neutral or dissatisfied +101626,74546,Female,disloyal Customer,24,Business travel,Business,1235,0,1,0,4,5,0,5,5,4,5,4,3,4,5,0,0.0,satisfied +101627,11484,Male,Loyal Customer,65,Personal Travel,Eco Plus,429,3,1,3,4,5,3,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +101628,24229,Male,Loyal Customer,47,Business travel,Business,3207,2,3,3,3,1,4,4,2,2,2,2,3,2,4,27,19.0,neutral or dissatisfied +101629,10276,Male,Loyal Customer,58,Personal Travel,Business,158,2,4,2,3,2,4,5,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +101630,95653,Male,Loyal Customer,22,Business travel,Business,2083,4,4,4,4,4,4,4,4,3,5,4,4,4,4,5,0.0,satisfied +101631,25574,Male,Loyal Customer,22,Business travel,Eco,696,5,2,2,2,5,5,4,5,2,1,1,4,3,5,26,22.0,satisfied +101632,38228,Female,Loyal Customer,48,Business travel,Business,2987,4,5,5,5,5,3,2,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +101633,69617,Female,Loyal Customer,53,Business travel,Business,2586,5,5,5,5,4,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +101634,110969,Female,Loyal Customer,25,Personal Travel,Business,268,2,0,2,5,3,2,3,3,5,4,5,3,4,3,118,115.0,neutral or dissatisfied +101635,19214,Female,Loyal Customer,59,Business travel,Business,3598,4,4,2,4,4,3,5,5,5,5,5,1,5,1,0,0.0,satisfied +101636,101471,Male,Loyal Customer,60,Business travel,Business,345,2,2,2,2,4,4,4,4,4,4,4,4,4,4,14,7.0,satisfied +101637,70545,Female,Loyal Customer,55,Business travel,Business,1258,5,5,5,5,3,4,4,5,5,5,5,5,5,5,0,6.0,satisfied +101638,35479,Male,Loyal Customer,48,Personal Travel,Eco,1076,1,5,1,4,2,1,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +101639,78403,Male,Loyal Customer,43,Business travel,Business,453,3,3,3,3,4,5,5,3,3,3,3,5,3,5,0,8.0,satisfied +101640,53338,Male,disloyal Customer,22,Business travel,Eco,816,2,2,2,3,1,2,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +101641,116026,Female,Loyal Customer,9,Personal Travel,Eco,371,1,1,1,4,4,1,4,4,1,3,3,4,3,4,49,38.0,neutral or dissatisfied +101642,11552,Female,disloyal Customer,23,Business travel,Eco,657,5,5,5,3,3,5,3,3,4,3,4,3,4,3,40,32.0,satisfied +101643,34727,Male,Loyal Customer,53,Business travel,Business,2121,1,1,1,1,3,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +101644,42001,Male,disloyal Customer,47,Business travel,Eco,116,1,4,2,2,4,2,4,4,3,2,3,2,2,4,0,0.0,neutral or dissatisfied +101645,75222,Male,disloyal Customer,17,Business travel,Eco,794,2,2,2,3,5,2,5,5,3,1,3,3,4,5,8,0.0,neutral or dissatisfied +101646,12028,Male,Loyal Customer,46,Business travel,Business,376,4,4,4,4,3,4,1,3,3,3,3,5,3,5,0,0.0,satisfied +101647,15170,Male,disloyal Customer,24,Business travel,Eco,430,4,5,4,3,1,4,1,1,1,3,4,3,5,1,0,0.0,neutral or dissatisfied +101648,6452,Female,disloyal Customer,49,Business travel,Business,296,4,4,4,1,4,4,4,4,5,5,4,5,4,4,12,17.0,satisfied +101649,43213,Male,Loyal Customer,11,Personal Travel,Business,472,4,4,4,3,5,4,5,5,4,2,1,2,1,5,0,0.0,satisfied +101650,70663,Male,Loyal Customer,52,Business travel,Business,447,4,4,3,4,4,5,4,5,5,4,5,4,5,5,0,3.0,satisfied +101651,39816,Male,disloyal Customer,24,Business travel,Eco,132,3,0,3,2,3,3,3,3,4,3,2,4,2,3,0,3.0,neutral or dissatisfied +101652,27610,Male,Loyal Customer,39,Personal Travel,Eco,679,4,3,4,3,1,4,1,1,2,5,5,1,5,1,11,0.0,neutral or dissatisfied +101653,92432,Male,Loyal Customer,56,Business travel,Business,1892,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +101654,23268,Male,Loyal Customer,57,Business travel,Business,2242,3,3,3,3,2,4,4,3,3,3,3,5,3,3,4,0.0,satisfied +101655,120589,Female,Loyal Customer,35,Business travel,Business,980,2,2,2,2,2,5,5,5,5,5,5,4,5,3,2,9.0,satisfied +101656,2559,Female,Loyal Customer,50,Business travel,Business,2673,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +101657,55311,Male,disloyal Customer,60,Business travel,Business,1117,2,1,1,4,2,3,3,5,3,5,5,3,3,3,196,206.0,neutral or dissatisfied +101658,125094,Male,Loyal Customer,47,Business travel,Business,2602,4,4,4,4,5,5,4,5,5,5,5,5,5,5,12,39.0,satisfied +101659,98252,Female,Loyal Customer,32,Business travel,Business,2494,5,5,5,5,5,5,5,5,3,4,4,4,5,5,11,2.0,satisfied +101660,105382,Male,Loyal Customer,37,Business travel,Business,1933,1,5,1,1,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +101661,83052,Male,Loyal Customer,41,Business travel,Business,2081,1,4,4,4,2,3,3,1,1,1,1,2,1,2,12,38.0,neutral or dissatisfied +101662,13289,Female,Loyal Customer,30,Business travel,Eco Plus,657,3,1,1,1,5,5,5,5,4,2,5,1,5,5,85,74.0,satisfied +101663,50356,Male,disloyal Customer,19,Business travel,Eco,153,2,2,2,3,5,2,5,5,4,1,3,1,3,5,76,79.0,neutral or dissatisfied +101664,84499,Male,Loyal Customer,60,Personal Travel,Eco,4502,2,2,2,3,2,4,4,2,1,5,4,4,4,4,28,0.0,neutral or dissatisfied +101665,103217,Male,disloyal Customer,21,Business travel,Eco,462,4,0,4,4,1,4,1,1,3,5,5,5,4,1,11,9.0,satisfied +101666,126200,Female,disloyal Customer,35,Business travel,Eco,507,1,1,1,3,5,1,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +101667,1401,Female,Loyal Customer,70,Personal Travel,Eco Plus,134,1,1,0,1,4,1,2,3,3,0,5,4,3,1,0,0.0,neutral or dissatisfied +101668,21909,Male,Loyal Customer,55,Business travel,Business,2442,5,5,2,5,1,4,3,4,4,4,4,4,4,4,14,7.0,satisfied +101669,106063,Male,disloyal Customer,34,Business travel,Business,302,3,3,3,3,4,3,3,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +101670,39881,Male,Loyal Customer,10,Personal Travel,Eco,132,2,5,2,2,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +101671,6493,Female,Loyal Customer,7,Personal Travel,Eco,557,3,5,3,2,3,3,3,3,1,1,1,4,3,3,0,0.0,neutral or dissatisfied +101672,64483,Male,Loyal Customer,39,Business travel,Business,551,1,1,1,1,2,5,5,4,4,4,4,4,4,4,4,8.0,satisfied +101673,43245,Male,Loyal Customer,24,Personal Travel,Business,402,3,4,3,3,3,3,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +101674,27419,Male,Loyal Customer,60,Business travel,Eco,954,3,5,5,5,3,3,3,3,4,3,5,1,4,3,0,0.0,satisfied +101675,45887,Male,Loyal Customer,42,Business travel,Eco,927,4,3,3,3,4,4,4,4,3,1,3,4,4,4,12,21.0,satisfied +101676,29330,Female,Loyal Customer,7,Personal Travel,Eco,834,2,5,2,4,2,2,2,2,3,2,4,4,5,2,1,0.0,neutral or dissatisfied +101677,71713,Male,Loyal Customer,50,Business travel,Business,2708,3,3,2,3,5,5,5,5,5,5,5,3,5,5,14,8.0,satisfied +101678,66036,Female,disloyal Customer,26,Business travel,Business,1055,3,3,3,3,2,3,2,2,3,3,4,5,4,2,1,0.0,neutral or dissatisfied +101679,50711,Male,Loyal Customer,69,Personal Travel,Eco,363,3,5,3,5,5,3,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +101680,108358,Female,Loyal Customer,35,Business travel,Business,1728,5,5,5,5,3,3,3,4,5,3,2,3,5,3,137,120.0,satisfied +101681,16992,Male,Loyal Customer,53,Business travel,Eco,843,5,5,5,5,5,5,5,5,2,4,1,3,1,5,0,4.0,satisfied +101682,34564,Female,Loyal Customer,46,Business travel,Business,1576,3,3,3,3,3,4,2,4,4,4,4,1,4,3,0,36.0,satisfied +101683,51880,Female,Loyal Customer,51,Business travel,Business,3967,3,1,1,1,2,3,3,3,3,3,3,2,3,4,0,21.0,neutral or dissatisfied +101684,46884,Male,Loyal Customer,14,Business travel,Business,845,4,1,1,1,4,4,4,4,2,3,4,4,3,4,183,173.0,neutral or dissatisfied +101685,55918,Male,Loyal Customer,13,Personal Travel,Eco,473,1,5,4,2,1,4,4,1,5,3,2,4,5,1,0,0.0,neutral or dissatisfied +101686,119626,Male,Loyal Customer,51,Business travel,Business,1927,2,2,2,2,2,5,5,4,4,4,4,4,4,4,38,12.0,satisfied +101687,11146,Male,Loyal Customer,36,Personal Travel,Eco,308,2,5,2,2,4,2,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +101688,81330,Male,Loyal Customer,31,Business travel,Business,2817,3,3,3,3,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +101689,23438,Male,Loyal Customer,59,Business travel,Eco,576,4,1,1,1,4,4,4,4,4,1,3,4,1,4,20,11.0,satisfied +101690,12749,Male,Loyal Customer,68,Personal Travel,Eco,721,2,5,3,3,2,3,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +101691,60452,Male,Loyal Customer,30,Business travel,Business,2059,2,2,2,2,4,4,4,4,3,3,4,4,5,4,57,65.0,satisfied +101692,98134,Male,Loyal Customer,65,Personal Travel,Eco,426,4,4,4,2,2,4,1,2,4,5,4,3,4,2,0,5.0,neutral or dissatisfied +101693,23236,Female,Loyal Customer,70,Personal Travel,Eco,116,3,2,0,3,3,3,2,2,2,0,2,4,2,1,0,4.0,neutral or dissatisfied +101694,80709,Male,Loyal Customer,64,Personal Travel,Eco Plus,748,2,4,2,1,4,2,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +101695,2225,Male,Loyal Customer,59,Business travel,Business,2652,1,1,1,1,5,3,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +101696,128625,Male,Loyal Customer,23,Business travel,Eco,679,2,1,4,4,2,2,3,2,1,4,2,3,2,2,0,0.0,neutral or dissatisfied +101697,104605,Male,Loyal Customer,25,Personal Travel,Eco,369,4,4,4,2,4,4,4,4,3,4,4,2,5,4,0,0.0,neutral or dissatisfied +101698,86789,Male,Loyal Customer,16,Business travel,Business,3963,1,1,1,1,4,4,4,4,3,2,5,5,4,4,3,3.0,satisfied +101699,84616,Female,Loyal Customer,39,Business travel,Business,1962,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +101700,98690,Male,Loyal Customer,16,Personal Travel,Eco,873,2,0,2,2,5,2,5,5,3,5,4,5,5,5,0,11.0,neutral or dissatisfied +101701,5571,Male,Loyal Customer,45,Personal Travel,Eco,501,1,3,1,4,4,1,4,4,3,3,3,5,5,4,116,86.0,neutral or dissatisfied +101702,7041,Male,disloyal Customer,19,Business travel,Eco Plus,196,4,2,4,4,2,4,2,2,4,5,3,3,4,2,21,10.0,neutral or dissatisfied +101703,69337,Male,Loyal Customer,47,Business travel,Business,3018,4,4,4,4,2,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +101704,71986,Male,Loyal Customer,25,Personal Travel,Eco,1440,4,5,4,4,3,4,4,3,3,3,4,4,4,3,0,0.0,satisfied +101705,86231,Female,disloyal Customer,56,Business travel,Eco,226,3,0,3,4,4,3,1,4,4,1,3,3,5,4,96,109.0,neutral or dissatisfied +101706,91244,Male,Loyal Customer,47,Personal Travel,Eco,366,1,2,1,3,5,1,5,5,1,2,4,3,4,5,0,0.0,neutral or dissatisfied +101707,1606,Female,Loyal Customer,41,Personal Travel,Eco Plus,140,2,5,0,2,4,2,2,3,3,0,3,1,3,2,0,0.0,neutral or dissatisfied +101708,65117,Male,Loyal Customer,61,Personal Travel,Eco,354,2,5,2,3,3,2,3,3,3,2,5,5,5,3,0,5.0,neutral or dissatisfied +101709,19774,Male,Loyal Customer,40,Business travel,Eco,667,5,5,5,5,5,5,5,5,4,5,2,5,5,5,0,3.0,satisfied +101710,25529,Male,Loyal Customer,64,Personal Travel,Eco,481,3,4,3,3,4,3,4,4,3,1,1,5,4,4,0,0.0,neutral or dissatisfied +101711,17459,Male,disloyal Customer,19,Business travel,Business,351,3,4,3,4,5,3,4,5,3,4,4,3,3,5,0,0.0,neutral or dissatisfied +101712,57218,Male,Loyal Customer,41,Business travel,Business,3077,2,2,5,2,2,5,1,5,5,5,5,1,5,2,6,0.0,satisfied +101713,13686,Male,Loyal Customer,44,Business travel,Business,2828,3,3,3,3,3,5,4,5,5,5,5,2,5,1,0,11.0,satisfied +101714,107136,Male,Loyal Customer,59,Business travel,Eco Plus,442,3,4,4,4,3,3,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +101715,120973,Female,Loyal Customer,21,Business travel,Business,3735,2,5,5,5,2,3,2,2,2,4,4,4,3,2,0,7.0,neutral or dissatisfied +101716,121568,Male,disloyal Customer,29,Business travel,Business,1095,5,5,5,3,4,5,4,4,4,3,5,4,5,4,0,0.0,satisfied +101717,1385,Female,Loyal Customer,14,Personal Travel,Eco Plus,102,1,1,1,2,4,1,4,4,2,5,2,2,1,4,0,0.0,neutral or dissatisfied +101718,51743,Female,Loyal Customer,62,Personal Travel,Eco,261,2,5,2,2,4,2,1,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +101719,37158,Male,Loyal Customer,60,Business travel,Business,3535,1,1,2,1,5,4,1,5,5,5,5,1,5,2,0,0.0,satisfied +101720,7541,Female,Loyal Customer,7,Personal Travel,Eco,762,3,2,3,3,5,3,5,5,1,2,4,4,4,5,0,0.0,neutral or dissatisfied +101721,26290,Male,Loyal Customer,26,Personal Travel,Business,1199,3,5,3,1,1,3,1,1,1,1,5,3,3,1,9,17.0,neutral or dissatisfied +101722,103991,Female,disloyal Customer,29,Business travel,Business,1363,5,5,5,2,2,5,2,2,4,4,4,4,5,2,0,0.0,satisfied +101723,30926,Female,Loyal Customer,39,Business travel,Eco Plus,896,4,2,2,2,4,4,4,4,2,4,2,1,3,4,0,0.0,satisfied +101724,52351,Male,Loyal Customer,46,Personal Travel,Eco,425,4,3,4,3,1,4,1,1,3,5,4,4,3,1,0,0.0,satisfied +101725,16668,Male,Loyal Customer,47,Personal Travel,Eco,605,1,5,1,3,2,1,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +101726,127793,Female,Loyal Customer,50,Business travel,Business,2267,3,2,2,2,3,2,1,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +101727,91038,Female,Loyal Customer,66,Personal Travel,Eco,406,2,4,2,5,4,4,5,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +101728,38240,Female,Loyal Customer,31,Business travel,Business,1173,4,4,4,4,4,4,4,4,3,3,4,3,1,4,18,12.0,satisfied +101729,95300,Male,Loyal Customer,42,Personal Travel,Eco,187,4,4,0,1,3,0,3,3,4,2,4,4,4,3,4,0.0,neutral or dissatisfied +101730,11567,Female,Loyal Customer,42,Business travel,Business,468,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +101731,32309,Male,disloyal Customer,38,Business travel,Eco,101,1,5,1,5,3,1,3,3,4,3,5,1,3,3,0,0.0,neutral or dissatisfied +101732,115633,Male,Loyal Customer,44,Business travel,Business,3139,5,5,5,5,5,4,5,5,5,5,5,3,5,5,7,0.0,satisfied +101733,38797,Male,Loyal Customer,52,Personal Travel,Eco,354,1,4,1,4,3,1,1,3,4,2,4,4,4,3,0,9.0,neutral or dissatisfied +101734,12423,Female,Loyal Customer,57,Personal Travel,Eco,190,4,5,0,1,3,4,4,5,5,0,5,5,5,3,27,25.0,neutral or dissatisfied +101735,95712,Female,Loyal Customer,49,Business travel,Business,2362,2,2,4,2,5,5,5,4,4,4,4,5,4,4,3,11.0,satisfied +101736,127583,Male,Loyal Customer,45,Business travel,Business,273,0,0,0,4,3,5,5,2,2,2,2,3,2,4,1,0.0,satisfied +101737,99365,Male,Loyal Customer,46,Personal Travel,Eco,409,3,4,3,2,3,3,3,3,3,4,5,4,5,3,7,0.0,neutral or dissatisfied +101738,122866,Male,Loyal Customer,40,Business travel,Business,226,0,0,0,2,3,5,5,3,3,1,1,5,3,4,0,0.0,satisfied +101739,3917,Female,Loyal Customer,35,Personal Travel,Eco,290,1,4,1,1,2,1,2,2,3,5,4,4,5,2,8,0.0,neutral or dissatisfied +101740,7454,Male,Loyal Customer,53,Business travel,Business,522,2,2,2,2,3,5,4,2,2,2,2,3,2,5,12,0.0,satisfied +101741,113896,Male,Loyal Customer,13,Business travel,Business,2329,5,5,5,5,4,4,4,4,3,2,5,3,5,4,1,0.0,satisfied +101742,96813,Female,Loyal Customer,40,Business travel,Business,3314,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +101743,108506,Male,disloyal Customer,40,Business travel,Business,119,1,1,1,3,5,1,5,5,4,3,3,3,4,5,20,20.0,neutral or dissatisfied +101744,81870,Male,Loyal Customer,58,Business travel,Business,1050,2,2,2,2,5,5,5,4,4,4,4,3,4,3,17,110.0,satisfied +101745,97379,Male,Loyal Customer,43,Personal Travel,Eco,843,3,5,3,1,1,3,1,1,3,2,4,5,5,1,31,40.0,neutral or dissatisfied +101746,10370,Male,disloyal Customer,38,Business travel,Business,247,5,5,5,2,1,5,1,1,4,2,4,5,5,1,87,76.0,satisfied +101747,69338,Female,disloyal Customer,18,Business travel,Eco,1089,4,4,4,3,2,4,2,2,5,4,4,4,5,2,0,0.0,satisfied +101748,100206,Female,Loyal Customer,35,Business travel,Business,762,2,1,1,1,3,4,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +101749,62248,Female,Loyal Customer,27,Personal Travel,Eco,2565,1,4,1,4,2,1,2,2,3,2,5,1,1,2,28,0.0,neutral or dissatisfied +101750,112200,Female,disloyal Customer,40,Business travel,Business,649,2,2,2,3,4,2,4,4,3,5,4,5,4,4,21,11.0,neutral or dissatisfied +101751,110431,Female,disloyal Customer,25,Business travel,Eco,842,3,3,3,2,1,3,1,1,2,5,4,5,1,1,2,0.0,neutral or dissatisfied +101752,59557,Female,Loyal Customer,29,Business travel,Business,964,1,1,1,1,5,5,5,5,3,4,4,5,4,5,10,0.0,satisfied +101753,65617,Male,Loyal Customer,70,Personal Travel,Eco,237,1,5,1,1,1,1,1,1,4,5,4,4,4,1,17,15.0,neutral or dissatisfied +101754,19576,Female,Loyal Customer,37,Business travel,Eco,160,5,4,4,4,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +101755,123151,Female,disloyal Customer,26,Business travel,Eco,600,3,2,2,3,4,2,4,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +101756,123612,Male,Loyal Customer,54,Business travel,Eco Plus,1773,4,5,1,1,4,4,4,4,2,4,3,2,3,4,5,11.0,neutral or dissatisfied +101757,80980,Female,Loyal Customer,62,Business travel,Business,297,3,5,5,5,2,3,3,3,3,2,3,3,3,4,50,39.0,neutral or dissatisfied +101758,103682,Male,Loyal Customer,47,Business travel,Business,405,5,5,5,5,2,4,4,4,4,4,4,4,4,4,6,7.0,satisfied +101759,110161,Male,Loyal Customer,39,Personal Travel,Eco,882,4,1,4,2,4,4,1,4,2,2,2,1,2,4,2,0.0,satisfied +101760,17948,Female,Loyal Customer,34,Business travel,Eco Plus,214,4,2,5,5,4,4,4,4,4,5,5,1,5,4,0,0.0,satisfied +101761,93447,Female,Loyal Customer,23,Personal Travel,Eco,671,3,5,3,4,5,3,5,5,3,2,4,5,5,5,0,8.0,neutral or dissatisfied +101762,2308,Female,Loyal Customer,60,Business travel,Eco,291,2,2,2,2,1,2,1,2,2,2,2,3,2,3,50,43.0,neutral or dissatisfied +101763,49406,Female,disloyal Customer,35,Business travel,Eco,89,2,0,1,2,2,1,2,2,2,4,2,3,5,2,0,0.0,neutral or dissatisfied +101764,128913,Male,Loyal Customer,20,Personal Travel,Eco,2248,5,5,5,4,2,5,5,2,5,5,5,5,4,2,0,0.0,satisfied +101765,21181,Male,Loyal Customer,43,Business travel,Business,192,0,5,0,2,5,2,1,3,3,3,3,5,3,2,89,81.0,satisfied +101766,22461,Female,Loyal Customer,28,Personal Travel,Eco,238,2,5,2,5,2,2,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +101767,43240,Female,Loyal Customer,35,Business travel,Business,1909,4,4,4,4,4,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +101768,32066,Female,Loyal Customer,32,Business travel,Eco,102,4,1,1,1,4,4,4,4,3,1,3,5,4,4,0,0.0,satisfied +101769,75021,Male,Loyal Customer,56,Business travel,Business,236,2,2,2,2,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +101770,92389,Male,Loyal Customer,32,Business travel,Business,2092,5,5,5,5,4,4,4,4,5,2,4,4,4,4,4,0.0,satisfied +101771,5256,Male,disloyal Customer,24,Business travel,Eco,293,2,4,2,3,1,2,1,1,4,1,4,4,3,1,26,26.0,neutral or dissatisfied +101772,10099,Male,Loyal Customer,49,Personal Travel,Eco,961,2,4,2,4,2,4,4,3,2,4,5,4,4,4,343,338.0,neutral or dissatisfied +101773,52895,Female,Loyal Customer,26,Personal Travel,Eco,836,4,4,5,4,5,5,5,5,5,4,5,1,2,5,51,38.0,neutral or dissatisfied +101774,3808,Female,Loyal Customer,45,Business travel,Business,710,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +101775,127026,Female,Loyal Customer,34,Business travel,Business,3287,2,2,2,2,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +101776,105317,Female,Loyal Customer,47,Personal Travel,Business,452,1,5,1,3,1,3,3,5,3,5,5,3,5,3,210,192.0,neutral or dissatisfied +101777,28575,Female,Loyal Customer,34,Business travel,Business,2562,3,3,3,3,2,5,5,5,5,5,5,4,5,2,0,0.0,satisfied +101778,127833,Male,Loyal Customer,33,Personal Travel,Eco,1044,3,3,3,4,5,3,4,5,4,3,3,5,1,5,0,17.0,neutral or dissatisfied +101779,43328,Male,Loyal Customer,30,Business travel,Business,436,5,2,2,2,5,4,5,5,4,1,3,3,3,5,0,11.0,neutral or dissatisfied +101780,86035,Male,Loyal Customer,55,Personal Travel,Eco,447,2,5,2,2,2,2,4,2,4,5,4,3,4,2,29,24.0,neutral or dissatisfied +101781,101651,Female,Loyal Customer,64,Personal Travel,Eco,1749,3,3,3,4,3,4,3,5,5,3,1,3,5,3,37,24.0,neutral or dissatisfied +101782,36425,Female,Loyal Customer,36,Business travel,Eco,369,2,2,2,2,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +101783,106404,Female,Loyal Customer,31,Personal Travel,Eco,674,5,5,5,3,2,5,2,2,5,4,4,4,4,2,88,66.0,satisfied +101784,26115,Female,Loyal Customer,63,Business travel,Business,2703,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +101785,69714,Female,Loyal Customer,35,Business travel,Eco,1372,3,4,4,4,3,3,3,3,1,5,4,3,1,3,0,0.0,satisfied +101786,98083,Male,Loyal Customer,22,Business travel,Business,3581,4,4,4,4,5,5,5,5,5,2,4,3,5,5,4,0.0,satisfied +101787,33017,Male,Loyal Customer,65,Personal Travel,Eco,163,4,5,4,4,5,4,5,5,4,4,5,5,5,5,11,13.0,neutral or dissatisfied +101788,50740,Female,Loyal Customer,36,Personal Travel,Eco,89,1,4,1,3,3,1,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +101789,126299,Female,Loyal Customer,30,Personal Travel,Eco,328,4,4,4,4,4,4,4,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +101790,109768,Female,Loyal Customer,39,Business travel,Business,2578,2,2,2,2,4,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +101791,105245,Male,Loyal Customer,58,Business travel,Business,377,3,3,3,3,3,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +101792,102926,Female,disloyal Customer,37,Business travel,Eco,317,1,3,2,4,5,2,5,5,3,3,3,4,4,5,61,61.0,neutral or dissatisfied +101793,18268,Female,Loyal Customer,66,Personal Travel,Eco,224,3,5,0,3,5,1,3,2,2,0,4,1,2,2,1,0.0,neutral or dissatisfied +101794,103639,Female,Loyal Customer,41,Business travel,Business,3059,0,0,0,3,2,5,5,4,4,4,4,5,4,3,0,8.0,satisfied +101795,110262,Female,Loyal Customer,37,Business travel,Business,787,1,1,1,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +101796,116201,Male,Loyal Customer,39,Personal Travel,Eco,325,3,1,3,4,3,3,3,3,2,1,4,4,4,3,2,0.0,neutral or dissatisfied +101797,127187,Male,Loyal Customer,43,Business travel,Business,2611,3,5,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +101798,14044,Male,Loyal Customer,35,Business travel,Business,363,4,4,4,4,5,3,1,2,2,2,2,3,2,5,6,0.0,satisfied +101799,6815,Female,Loyal Customer,49,Personal Travel,Eco,122,4,3,4,3,5,5,5,5,5,4,5,3,5,5,0,4.0,neutral or dissatisfied +101800,126645,Female,Loyal Customer,55,Business travel,Business,602,1,1,1,1,3,4,5,4,4,4,4,5,4,5,0,7.0,satisfied +101801,23504,Male,Loyal Customer,31,Business travel,Business,3288,2,2,2,2,4,5,4,4,5,3,2,2,4,4,50,45.0,satisfied +101802,36790,Male,Loyal Customer,50,Business travel,Eco,1102,3,3,3,3,3,3,3,3,5,4,4,3,2,3,13,0.0,neutral or dissatisfied +101803,85521,Male,Loyal Customer,38,Personal Travel,Eco Plus,332,4,1,5,3,1,5,1,1,4,2,3,1,3,1,107,96.0,neutral or dissatisfied +101804,79555,Female,Loyal Customer,57,Business travel,Business,1816,4,4,4,4,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +101805,57251,Female,disloyal Customer,38,Business travel,Business,628,3,3,3,5,1,3,1,1,4,3,4,5,4,1,0,0.0,satisfied +101806,44673,Male,Loyal Customer,50,Business travel,Business,1516,5,5,5,5,5,5,2,5,5,5,5,5,5,2,0,0.0,satisfied +101807,17055,Male,disloyal Customer,20,Business travel,Eco,1134,2,2,2,3,1,2,1,1,4,5,4,4,4,1,0,9.0,neutral or dissatisfied +101808,94436,Male,Loyal Customer,77,Business travel,Business,1625,3,3,4,3,3,2,2,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +101809,111832,Female,Loyal Customer,53,Business travel,Eco,1605,2,3,3,3,3,2,4,2,2,2,2,4,2,4,23,16.0,neutral or dissatisfied +101810,45578,Male,Loyal Customer,70,Personal Travel,Business,230,4,5,0,1,5,4,5,2,2,0,2,4,2,4,9,0.0,satisfied +101811,70075,Female,Loyal Customer,45,Business travel,Business,3448,4,5,5,5,1,3,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +101812,103666,Female,Loyal Customer,50,Business travel,Business,251,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +101813,63113,Female,Loyal Customer,42,Personal Travel,Eco Plus,909,3,4,2,1,4,4,1,5,5,2,5,2,5,1,36,18.0,neutral or dissatisfied +101814,48212,Male,Loyal Customer,50,Personal Travel,Eco,259,2,3,2,2,5,2,5,5,1,1,3,2,5,5,0,0.0,neutral or dissatisfied +101815,10165,Male,disloyal Customer,37,Business travel,Business,224,5,5,5,5,4,5,4,4,4,2,4,5,5,4,0,0.0,satisfied +101816,33253,Male,Loyal Customer,58,Business travel,Eco Plus,163,4,5,3,3,3,4,3,3,4,2,1,4,3,3,0,0.0,satisfied +101817,6766,Male,Loyal Customer,54,Business travel,Business,1764,5,5,5,5,3,4,4,5,5,5,5,5,5,3,2,0.0,satisfied +101818,129477,Female,Loyal Customer,49,Business travel,Business,2704,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +101819,44274,Female,Loyal Customer,24,Business travel,Eco Plus,118,4,4,5,4,4,4,4,4,4,1,1,4,3,4,0,0.0,satisfied +101820,88314,Male,Loyal Customer,56,Business travel,Eco,646,4,2,2,2,4,4,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +101821,40297,Female,Loyal Customer,47,Personal Travel,Eco,436,3,5,3,1,4,5,4,4,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +101822,90550,Female,Loyal Customer,39,Business travel,Business,2055,3,3,3,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +101823,105898,Female,Loyal Customer,41,Business travel,Business,283,2,2,3,2,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +101824,40133,Male,disloyal Customer,25,Business travel,Eco Plus,200,3,0,3,1,4,3,1,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +101825,85783,Female,Loyal Customer,38,Business travel,Business,2325,1,1,1,1,2,4,5,5,5,5,5,5,5,4,21,7.0,satisfied +101826,91179,Female,Loyal Customer,65,Personal Travel,Eco,594,1,4,1,5,2,4,1,3,3,1,3,2,3,2,0,1.0,neutral or dissatisfied +101827,92028,Male,Loyal Customer,27,Business travel,Business,1589,3,3,3,3,5,5,5,5,4,2,5,4,4,5,0,0.0,satisfied +101828,45042,Female,Loyal Customer,59,Business travel,Business,2021,0,0,0,5,5,1,4,5,5,5,5,4,5,5,2,0.0,satisfied +101829,29365,Male,Loyal Customer,28,Business travel,Eco,2614,0,0,0,4,0,4,4,1,2,4,3,4,3,4,0,0.0,satisfied +101830,85918,Female,Loyal Customer,51,Personal Travel,Eco,761,3,4,3,4,3,4,5,1,1,3,1,5,1,4,17,14.0,neutral or dissatisfied +101831,7872,Female,Loyal Customer,10,Business travel,Business,3778,2,2,2,2,2,2,2,2,4,5,4,4,4,2,34,25.0,neutral or dissatisfied +101832,103798,Female,disloyal Customer,37,Business travel,Business,1072,3,2,2,2,5,2,5,5,4,2,5,5,4,5,13,15.0,neutral or dissatisfied +101833,8203,Female,disloyal Customer,25,Business travel,Eco,335,1,3,1,3,1,1,1,1,1,2,4,1,3,1,0,0.0,neutral or dissatisfied +101834,9970,Female,Loyal Customer,25,Personal Travel,Eco,457,1,4,1,3,1,1,1,1,2,1,3,3,4,1,0,2.0,neutral or dissatisfied +101835,99875,Female,Loyal Customer,47,Business travel,Business,1436,3,3,3,3,4,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +101836,106420,Male,Loyal Customer,24,Personal Travel,Eco,551,3,2,3,3,5,3,4,5,2,1,3,3,3,5,10,8.0,neutral or dissatisfied +101837,24487,Male,Loyal Customer,21,Business travel,Business,547,3,1,1,1,3,3,3,3,2,3,4,3,3,3,106,116.0,neutral or dissatisfied +101838,58200,Male,disloyal Customer,8,Business travel,Eco,925,1,1,1,4,3,1,3,3,2,2,4,4,3,3,9,4.0,neutral or dissatisfied +101839,60149,Male,Loyal Customer,70,Personal Travel,Eco,1005,4,1,3,3,4,3,4,4,4,5,2,4,3,4,0,0.0,satisfied +101840,90598,Female,disloyal Customer,22,Business travel,Business,594,5,4,5,1,2,4,2,2,4,3,4,4,4,2,71,66.0,satisfied +101841,40668,Female,Loyal Customer,30,Business travel,Business,3152,5,5,5,5,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +101842,26125,Female,Loyal Customer,66,Personal Travel,Business,406,2,4,2,4,3,5,4,1,1,2,1,4,1,3,3,8.0,neutral or dissatisfied +101843,50168,Female,disloyal Customer,62,Business travel,Eco,363,4,2,4,3,1,4,4,1,1,2,3,4,4,1,16,39.0,neutral or dissatisfied +101844,117352,Male,disloyal Customer,21,Business travel,Business,296,5,1,5,2,3,5,3,3,5,3,4,5,5,3,69,69.0,satisfied +101845,29040,Male,Loyal Customer,36,Personal Travel,Eco,697,3,1,4,4,5,4,5,5,2,2,3,4,3,5,0,0.0,neutral or dissatisfied +101846,125837,Male,Loyal Customer,66,Business travel,Business,3499,2,2,4,2,3,3,3,2,2,2,2,3,2,3,3,0.0,neutral or dissatisfied +101847,31257,Female,Loyal Customer,60,Business travel,Eco,533,4,4,4,4,3,4,1,4,4,4,4,4,4,3,2,7.0,satisfied +101848,44706,Male,Loyal Customer,18,Personal Travel,Eco,67,3,3,3,4,3,3,3,3,5,3,5,5,4,3,2,0.0,neutral or dissatisfied +101849,123228,Male,Loyal Customer,54,Personal Travel,Eco,468,1,4,1,4,4,1,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +101850,37981,Male,Loyal Customer,54,Personal Travel,Business,1237,2,4,2,4,2,4,4,3,3,2,3,5,3,3,43,16.0,neutral or dissatisfied +101851,31882,Female,disloyal Customer,18,Business travel,Eco,1219,2,2,2,4,2,2,2,2,1,5,4,2,4,2,0,0.0,neutral or dissatisfied +101852,27465,Female,Loyal Customer,18,Business travel,Eco,1050,3,2,2,2,3,3,2,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +101853,101196,Female,Loyal Customer,57,Personal Travel,Eco,1235,2,5,2,5,5,1,4,4,4,2,4,1,4,3,3,0.0,neutral or dissatisfied +101854,51384,Male,Loyal Customer,59,Personal Travel,Eco Plus,78,3,5,3,1,2,3,2,2,5,4,5,4,5,2,6,2.0,neutral or dissatisfied +101855,193,Female,Loyal Customer,50,Business travel,Business,213,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +101856,15335,Male,Loyal Customer,11,Personal Travel,Eco,599,2,1,3,3,2,3,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +101857,26428,Male,Loyal Customer,25,Business travel,Business,787,3,4,4,4,3,3,3,3,3,4,4,3,3,3,2,0.0,neutral or dissatisfied +101858,3046,Female,Loyal Customer,23,Personal Travel,Eco,489,3,1,3,1,1,3,2,1,2,3,1,2,1,1,0,0.0,neutral or dissatisfied +101859,69444,Female,Loyal Customer,66,Personal Travel,Eco,1096,2,1,2,3,1,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +101860,112796,Male,disloyal Customer,44,Business travel,Business,1476,1,1,1,4,5,1,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +101861,94219,Female,Loyal Customer,48,Business travel,Business,3993,5,5,5,5,3,4,4,4,4,4,4,5,4,3,54,52.0,satisfied +101862,75249,Female,Loyal Customer,47,Personal Travel,Eco,1726,2,5,2,4,4,5,5,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +101863,64254,Male,Loyal Customer,70,Personal Travel,Eco,1660,3,2,3,4,4,3,4,4,1,2,4,2,3,4,0,6.0,neutral or dissatisfied +101864,94035,Male,disloyal Customer,44,Business travel,Business,239,4,4,4,3,5,4,5,5,3,5,4,3,5,5,0,0.0,satisfied +101865,80164,Male,disloyal Customer,27,Business travel,Eco,1126,4,4,4,4,1,4,1,1,2,5,4,3,4,1,0,6.0,neutral or dissatisfied +101866,81866,Male,Loyal Customer,53,Business travel,Business,1050,3,5,4,5,2,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +101867,46634,Male,Loyal Customer,38,Business travel,Business,1633,1,3,3,3,4,4,3,3,3,3,1,2,3,1,0,0.0,neutral or dissatisfied +101868,113620,Male,Loyal Customer,58,Personal Travel,Eco,223,1,4,1,2,2,1,2,2,4,5,5,4,4,2,0,3.0,neutral or dissatisfied +101869,106048,Male,Loyal Customer,42,Business travel,Eco,452,2,5,2,2,2,2,2,2,2,3,4,2,4,2,7,14.0,neutral or dissatisfied +101870,101790,Female,Loyal Customer,52,Business travel,Business,1521,4,2,4,4,4,4,5,5,5,5,5,3,5,3,8,1.0,satisfied +101871,9924,Male,Loyal Customer,43,Business travel,Business,3959,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +101872,101780,Female,Loyal Customer,50,Business travel,Business,1521,3,3,3,3,3,4,5,4,4,4,4,4,4,4,7,0.0,satisfied +101873,47147,Female,Loyal Customer,42,Business travel,Business,965,3,3,3,3,1,3,5,3,3,3,3,2,3,4,0,0.0,satisfied +101874,84875,Female,Loyal Customer,50,Personal Travel,Eco,547,4,5,4,4,1,5,5,5,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +101875,34441,Female,Loyal Customer,31,Personal Travel,Eco,2422,2,4,2,3,2,1,1,5,2,5,4,1,4,1,0,7.0,neutral or dissatisfied +101876,37693,Male,Loyal Customer,51,Personal Travel,Eco,1005,0,4,1,3,5,1,4,5,4,3,5,3,5,5,7,9.0,satisfied +101877,45501,Male,Loyal Customer,61,Personal Travel,Eco,674,4,4,4,4,4,5,5,3,2,3,3,5,4,5,190,184.0,neutral or dissatisfied +101878,45600,Female,disloyal Customer,45,Business travel,Eco,313,5,0,5,2,1,5,1,1,2,1,2,5,2,1,21,16.0,satisfied +101879,51987,Male,Loyal Customer,57,Business travel,Eco Plus,347,4,5,3,5,4,4,4,4,2,3,5,1,2,4,0,8.0,satisfied +101880,37234,Male,disloyal Customer,37,Business travel,Business,718,4,4,4,3,4,4,2,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +101881,84749,Female,Loyal Customer,28,Business travel,Business,2673,4,4,4,4,4,4,4,4,4,4,5,4,4,4,10,0.0,satisfied +101882,34790,Male,Loyal Customer,8,Personal Travel,Eco,264,2,5,2,1,5,2,5,5,5,5,2,5,3,5,15,25.0,neutral or dissatisfied +101883,90125,Female,Loyal Customer,42,Business travel,Business,3994,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +101884,96437,Female,Loyal Customer,42,Business travel,Business,436,2,2,2,2,4,5,4,4,4,4,4,4,4,3,25,22.0,satisfied +101885,94082,Female,Loyal Customer,46,Business travel,Business,1979,0,5,0,4,3,5,4,1,1,1,1,5,1,4,0,0.0,satisfied +101886,116147,Male,Loyal Customer,61,Personal Travel,Eco,362,2,4,2,2,2,2,5,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +101887,113178,Female,Loyal Customer,23,Personal Travel,Eco,889,2,2,2,4,5,2,4,5,2,5,4,2,4,5,17,4.0,neutral or dissatisfied +101888,102906,Male,Loyal Customer,49,Business travel,Business,3085,1,5,5,5,1,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +101889,85173,Female,Loyal Customer,55,Business travel,Eco,813,2,5,5,5,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +101890,118662,Male,Loyal Customer,62,Business travel,Business,338,1,1,1,1,1,3,3,1,1,1,1,4,1,2,37,19.0,neutral or dissatisfied +101891,62666,Female,Loyal Customer,48,Business travel,Business,1726,1,1,1,1,3,3,5,2,2,2,2,5,2,3,0,0.0,satisfied +101892,55125,Female,Loyal Customer,58,Personal Travel,Eco,1608,3,5,3,4,4,3,5,3,3,3,4,3,3,3,0,6.0,neutral or dissatisfied +101893,47800,Female,Loyal Customer,41,Business travel,Eco,329,4,3,3,3,4,4,4,4,3,1,2,5,4,4,0,0.0,satisfied +101894,37239,Male,Loyal Customer,22,Personal Travel,Business,1118,3,4,3,3,1,3,1,1,3,3,5,3,5,1,0,8.0,neutral or dissatisfied +101895,17439,Female,Loyal Customer,40,Personal Travel,Eco,351,2,5,2,3,2,2,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +101896,94063,Female,Loyal Customer,43,Business travel,Business,1937,4,5,5,5,3,3,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +101897,25791,Male,Loyal Customer,42,Business travel,Business,2794,2,2,1,2,4,5,3,2,2,2,2,2,2,2,0,0.0,satisfied +101898,19462,Male,Loyal Customer,63,Business travel,Business,177,5,5,5,5,2,5,5,4,4,4,4,2,4,5,0,0.0,satisfied +101899,19489,Female,Loyal Customer,27,Business travel,Eco Plus,177,4,3,3,3,4,4,4,4,1,3,2,2,2,4,0,5.0,satisfied +101900,53176,Female,Loyal Customer,48,Business travel,Eco,589,5,1,5,1,1,2,1,5,5,5,5,4,5,1,12,3.0,satisfied +101901,31021,Female,Loyal Customer,40,Personal Travel,Eco,391,3,2,3,4,3,3,3,3,1,1,4,4,4,3,0,8.0,neutral or dissatisfied +101902,94499,Female,Loyal Customer,34,Business travel,Business,189,5,5,5,5,4,5,4,5,5,5,5,4,5,5,12,10.0,satisfied +101903,64061,Male,Loyal Customer,38,Business travel,Business,919,1,5,5,5,1,3,3,1,1,1,1,3,1,3,0,1.0,neutral or dissatisfied +101904,91678,Male,Loyal Customer,55,Business travel,Business,2264,3,5,3,3,4,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +101905,45325,Male,Loyal Customer,58,Business travel,Business,188,4,4,4,4,3,1,3,4,4,4,5,3,4,2,29,39.0,satisfied +101906,77193,Male,Loyal Customer,18,Personal Travel,Eco,290,5,4,5,1,2,5,2,2,5,5,4,5,5,2,0,0.0,satisfied +101907,88360,Female,Loyal Customer,50,Business travel,Eco,404,2,5,5,5,4,3,4,2,2,2,2,4,2,1,0,1.0,neutral or dissatisfied +101908,93309,Male,Loyal Customer,40,Personal Travel,Eco,1733,4,4,4,4,2,4,2,2,2,2,3,3,3,2,10,0.0,neutral or dissatisfied +101909,7185,Female,Loyal Customer,46,Business travel,Business,135,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +101910,74845,Male,disloyal Customer,37,Business travel,Eco Plus,297,1,1,1,4,4,1,2,4,5,2,1,4,2,4,0,0.0,neutral or dissatisfied +101911,34687,Female,Loyal Customer,56,Business travel,Business,3057,0,0,0,3,3,2,1,4,4,4,4,5,4,1,4,4.0,satisfied +101912,77763,Female,Loyal Customer,13,Personal Travel,Eco,874,4,1,4,3,2,4,2,2,3,1,4,4,4,2,0,0.0,satisfied +101913,85328,Female,Loyal Customer,14,Personal Travel,Eco,696,4,4,4,1,3,4,3,3,4,5,5,4,5,3,1,2.0,satisfied +101914,34219,Male,Loyal Customer,57,Personal Travel,Eco,1189,3,1,3,3,2,3,2,2,2,5,3,2,4,2,0,12.0,neutral or dissatisfied +101915,16041,Male,Loyal Customer,29,Personal Travel,Eco Plus,780,4,3,4,3,3,4,3,3,3,3,3,1,4,3,0,0.0,satisfied +101916,101941,Male,Loyal Customer,54,Business travel,Business,3640,5,5,5,5,5,4,4,3,3,3,3,5,3,5,6,0.0,satisfied +101917,10712,Male,Loyal Customer,46,Business travel,Business,3532,2,3,3,3,3,3,4,2,2,3,2,3,2,3,3,0.0,neutral or dissatisfied +101918,114629,Female,disloyal Customer,58,Business travel,Business,296,4,4,4,3,1,4,1,1,3,4,4,4,4,1,0,0.0,satisfied +101919,46028,Female,Loyal Customer,42,Business travel,Business,991,5,5,5,5,2,4,2,4,4,4,4,5,4,2,43,81.0,satisfied +101920,5702,Female,Loyal Customer,7,Personal Travel,Eco,234,1,5,0,1,0,4,4,4,4,5,1,4,2,4,724,705.0,neutral or dissatisfied +101921,7576,Male,Loyal Customer,28,Business travel,Business,2368,4,4,3,4,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +101922,86000,Male,Loyal Customer,48,Business travel,Business,2182,2,4,2,4,3,3,4,2,2,2,2,4,2,2,0,3.0,neutral or dissatisfied +101923,74454,Male,Loyal Customer,39,Business travel,Business,1859,3,3,3,3,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +101924,4029,Female,Loyal Customer,28,Business travel,Business,479,1,1,1,1,4,4,4,4,5,4,5,5,4,4,5,0.0,satisfied +101925,123822,Female,Loyal Customer,25,Business travel,Business,3007,2,3,3,3,2,2,2,2,1,2,2,4,3,2,0,0.0,neutral or dissatisfied +101926,112128,Female,Loyal Customer,14,Personal Travel,Eco,977,1,4,1,1,3,1,3,3,3,2,4,3,5,3,19,6.0,neutral or dissatisfied +101927,123130,Female,Loyal Customer,8,Business travel,Eco,631,1,3,3,3,1,1,4,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +101928,119528,Male,Loyal Customer,36,Personal Travel,Eco,899,3,1,3,3,5,3,5,5,4,1,3,4,4,5,0,0.0,neutral or dissatisfied +101929,102774,Male,Loyal Customer,44,Business travel,Business,1099,5,5,5,5,2,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +101930,96096,Male,Loyal Customer,24,Personal Travel,Eco,583,2,4,2,1,3,2,3,3,3,3,5,4,5,3,70,72.0,neutral or dissatisfied +101931,89872,Female,Loyal Customer,56,Business travel,Business,2791,1,1,1,1,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +101932,118228,Female,Loyal Customer,42,Business travel,Business,1587,2,2,2,2,5,3,5,5,5,5,5,4,5,5,4,0.0,satisfied +101933,38149,Female,Loyal Customer,37,Personal Travel,Eco,1197,2,4,1,3,4,1,4,4,5,3,4,4,5,4,3,0.0,neutral or dissatisfied +101934,26107,Male,Loyal Customer,42,Business travel,Eco Plus,591,4,1,1,1,4,4,4,4,3,4,4,1,4,4,1,0.0,neutral or dissatisfied +101935,100232,Male,disloyal Customer,22,Business travel,Eco,971,4,4,4,5,4,4,4,4,4,3,5,3,4,4,2,5.0,satisfied +101936,85646,Male,Loyal Customer,44,Business travel,Business,3100,0,4,1,5,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +101937,71340,Male,Loyal Customer,70,Personal Travel,Eco,1514,3,5,3,1,4,3,4,4,5,3,3,4,4,4,0,0.0,neutral or dissatisfied +101938,2045,Male,Loyal Customer,33,Business travel,Business,812,2,3,3,3,2,2,2,2,3,1,3,3,4,2,33,20.0,neutral or dissatisfied +101939,104192,Female,Loyal Customer,54,Business travel,Eco Plus,349,1,5,5,5,2,1,1,1,1,1,1,2,1,1,0,19.0,neutral or dissatisfied +101940,110162,Female,Loyal Customer,8,Personal Travel,Eco,1048,4,5,4,4,5,4,5,5,4,2,4,3,5,5,23,30.0,neutral or dissatisfied +101941,108947,Female,Loyal Customer,30,Personal Travel,Eco Plus,1183,1,4,2,4,1,2,1,1,3,5,5,3,4,1,22,10.0,neutral or dissatisfied +101942,111691,Male,Loyal Customer,51,Business travel,Business,3980,5,5,5,5,4,4,4,5,5,5,5,5,5,5,53,51.0,satisfied +101943,102142,Female,Loyal Customer,59,Business travel,Business,407,2,2,4,2,5,5,5,5,5,5,4,5,5,5,172,168.0,satisfied +101944,121825,Female,Loyal Customer,60,Business travel,Business,1908,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +101945,99071,Female,Loyal Customer,44,Business travel,Business,3532,3,1,3,3,1,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +101946,43113,Female,Loyal Customer,15,Personal Travel,Eco,236,2,5,2,1,3,2,2,3,3,3,4,5,4,3,25,54.0,neutral or dissatisfied +101947,80940,Male,Loyal Customer,25,Personal Travel,Eco,341,3,4,3,3,3,3,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +101948,26436,Female,Loyal Customer,41,Business travel,Eco,787,5,4,4,4,5,5,5,5,5,4,4,5,2,5,8,18.0,satisfied +101949,31646,Female,Loyal Customer,27,Business travel,Eco,862,0,0,0,2,3,3,5,3,2,4,1,4,5,3,5,0.0,satisfied +101950,26188,Female,disloyal Customer,42,Business travel,Eco,404,4,4,4,5,2,4,3,2,4,4,1,5,4,2,10,4.0,neutral or dissatisfied +101951,66505,Female,Loyal Customer,61,Business travel,Eco,447,4,3,3,3,3,2,2,4,4,4,4,2,4,1,0,0.0,satisfied +101952,106572,Female,disloyal Customer,24,Business travel,Eco,1133,5,5,5,1,1,5,1,1,3,5,5,5,5,1,0,0.0,satisfied +101953,22188,Female,disloyal Customer,19,Business travel,Eco,633,3,2,3,4,1,3,1,1,3,3,3,1,3,1,2,0.0,neutral or dissatisfied +101954,43552,Female,Loyal Customer,44,Business travel,Eco,403,4,5,5,5,5,5,5,4,4,4,4,2,4,1,0,0.0,satisfied +101955,44759,Female,Loyal Customer,47,Business travel,Business,2233,5,5,5,5,1,1,2,4,4,4,4,1,4,1,20,40.0,satisfied +101956,20022,Female,Loyal Customer,44,Business travel,Business,473,1,1,1,1,1,4,3,1,1,1,1,1,1,1,17,30.0,neutral or dissatisfied +101957,124893,Female,disloyal Customer,25,Business travel,Business,728,3,5,3,2,4,3,4,4,4,3,5,5,5,4,5,11.0,neutral or dissatisfied +101958,40020,Female,Loyal Customer,56,Business travel,Eco,575,5,4,4,4,1,5,2,5,5,5,5,5,5,1,0,0.0,satisfied +101959,49932,Female,disloyal Customer,22,Business travel,Eco,266,3,2,3,4,5,3,5,5,3,1,4,4,3,5,0,0.0,neutral or dissatisfied +101960,10578,Female,Loyal Customer,40,Business travel,Business,458,5,5,5,5,3,4,5,5,5,5,5,3,5,5,0,5.0,satisfied +101961,17311,Female,disloyal Customer,21,Business travel,Eco,403,3,3,3,3,4,3,4,4,4,2,4,1,3,4,9,40.0,neutral or dissatisfied +101962,38724,Male,Loyal Customer,51,Business travel,Business,2128,4,4,4,4,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +101963,112945,Male,Loyal Customer,21,Personal Travel,Eco,1164,2,4,2,2,5,2,5,5,5,2,4,2,2,5,0,0.0,neutral or dissatisfied +101964,96119,Male,Loyal Customer,55,Business travel,Business,583,1,1,1,1,4,4,4,4,4,4,4,4,4,5,16,16.0,satisfied +101965,19078,Male,Loyal Customer,56,Personal Travel,Eco,642,1,5,1,4,2,1,2,2,4,3,4,3,5,2,31,27.0,neutral or dissatisfied +101966,83463,Female,Loyal Customer,72,Business travel,Business,2564,4,4,3,4,5,5,4,5,5,5,5,3,5,3,0,7.0,satisfied +101967,104012,Male,Loyal Customer,43,Personal Travel,Eco,1489,3,5,3,1,5,3,5,5,5,1,5,5,1,5,19,5.0,neutral or dissatisfied +101968,34875,Female,Loyal Customer,38,Personal Travel,Eco,2248,0,5,0,3,3,0,3,3,4,5,5,3,4,3,3,0.0,satisfied +101969,12699,Male,Loyal Customer,60,Business travel,Business,3758,1,4,4,4,2,2,2,1,1,1,1,3,1,3,69,57.0,neutral or dissatisfied +101970,116045,Male,Loyal Customer,67,Personal Travel,Eco,325,2,4,2,3,5,2,3,5,4,4,2,1,1,5,0,0.0,neutral or dissatisfied +101971,91033,Female,Loyal Customer,58,Personal Travel,Eco,646,2,5,2,4,2,5,2,5,5,2,5,4,5,5,5,0.0,neutral or dissatisfied +101972,92620,Male,Loyal Customer,44,Business travel,Business,453,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,10.0,satisfied +101973,65433,Male,Loyal Customer,61,Personal Travel,Eco,2165,5,5,5,1,3,5,4,3,4,5,3,5,5,3,8,0.0,satisfied +101974,93041,Female,Loyal Customer,55,Business travel,Business,2774,2,2,2,2,3,4,4,5,5,5,5,3,5,5,24,26.0,satisfied +101975,91690,Male,Loyal Customer,37,Personal Travel,Business,626,4,5,4,3,5,5,5,5,5,4,5,3,5,5,4,1.0,satisfied +101976,112922,Female,Loyal Customer,11,Personal Travel,Eco,1390,1,4,1,2,4,1,4,4,4,4,3,1,5,4,0,0.0,neutral or dissatisfied +101977,32618,Male,Loyal Customer,19,Business travel,Eco,101,5,1,1,1,5,5,4,5,4,5,1,4,4,5,0,5.0,satisfied +101978,53515,Female,Loyal Customer,8,Personal Travel,Eco,2288,3,1,3,3,1,3,1,1,3,4,4,1,3,1,4,0.0,neutral or dissatisfied +101979,114662,Female,disloyal Customer,22,Business travel,Eco,446,4,4,4,3,2,4,2,2,3,4,5,5,5,2,0,5.0,satisfied +101980,118446,Female,Loyal Customer,47,Business travel,Business,325,4,4,4,4,4,5,5,5,5,4,5,5,5,4,85,82.0,satisfied +101981,82283,Male,Loyal Customer,69,Personal Travel,Eco,1481,3,2,3,1,3,3,3,3,1,1,1,4,2,3,9,0.0,neutral or dissatisfied +101982,71925,Female,Loyal Customer,51,Business travel,Business,1744,3,3,3,3,2,5,4,5,5,5,5,4,5,5,73,69.0,satisfied +101983,61052,Male,Loyal Customer,38,Business travel,Eco,1607,2,1,1,1,2,2,2,2,3,5,2,1,3,2,0,0.0,neutral or dissatisfied +101984,112664,Female,Loyal Customer,30,Business travel,Business,723,1,1,1,1,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +101985,64397,Male,Loyal Customer,19,Personal Travel,Eco,1192,3,2,3,4,4,3,4,4,1,1,4,2,4,4,0,0.0,neutral or dissatisfied +101986,23281,Male,Loyal Customer,42,Business travel,Eco,563,4,1,3,1,4,4,4,4,5,3,1,2,5,4,0,5.0,satisfied +101987,813,Male,disloyal Customer,37,Business travel,Business,247,2,2,2,4,3,2,3,3,4,3,4,4,4,3,2,6.0,neutral or dissatisfied +101988,125042,Male,Loyal Customer,38,Business travel,Business,2043,5,5,5,5,4,5,5,5,1,4,5,5,3,5,0,4.0,satisfied +101989,116581,Female,Loyal Customer,34,Business travel,Business,417,4,4,4,4,3,4,5,5,5,5,5,4,5,4,2,3.0,satisfied +101990,52171,Female,disloyal Customer,40,Business travel,Business,370,3,3,3,5,3,3,3,3,3,2,4,5,2,3,0,0.0,neutral or dissatisfied +101991,80335,Female,Loyal Customer,27,Business travel,Eco Plus,746,1,2,2,2,1,1,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +101992,7224,Male,Loyal Customer,54,Business travel,Business,139,3,1,1,1,5,4,3,1,1,1,3,3,1,4,3,18.0,neutral or dissatisfied +101993,74765,Female,Loyal Customer,68,Personal Travel,Eco,1438,2,4,2,2,5,4,4,1,1,2,1,5,1,4,24,2.0,neutral or dissatisfied +101994,36428,Male,disloyal Customer,23,Business travel,Eco,369,2,3,2,2,5,2,5,5,2,5,3,3,3,5,1,0.0,neutral or dissatisfied +101995,74368,Female,Loyal Customer,45,Business travel,Business,3188,1,1,1,1,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +101996,60321,Male,Loyal Customer,56,Business travel,Business,3793,4,4,4,4,3,5,4,4,4,4,4,4,4,3,4,2.0,satisfied +101997,115845,Male,Loyal Customer,42,Business travel,Eco,372,4,3,3,3,4,4,4,4,5,1,1,5,1,4,0,0.0,satisfied +101998,117043,Male,Loyal Customer,41,Business travel,Business,3858,2,2,2,2,3,4,5,4,4,4,4,4,4,5,52,28.0,satisfied +101999,114417,Male,Loyal Customer,36,Business travel,Business,3353,2,2,2,2,4,5,5,3,3,4,3,5,3,5,2,0.0,satisfied +102000,7393,Female,disloyal Customer,37,Business travel,Business,522,1,1,1,2,5,1,5,5,5,2,4,3,4,5,30,29.0,neutral or dissatisfied +102001,99421,Female,Loyal Customer,52,Personal Travel,Eco,337,1,5,1,1,4,1,3,5,5,1,5,3,5,1,0,0.0,neutral or dissatisfied +102002,103888,Male,Loyal Customer,38,Personal Travel,Eco,882,2,4,2,1,1,2,1,1,4,3,5,4,5,1,1,0.0,neutral or dissatisfied +102003,69976,Male,Loyal Customer,56,Business travel,Business,2290,1,1,1,1,3,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +102004,36683,Male,Loyal Customer,51,Personal Travel,Eco,1237,3,5,3,2,4,3,2,4,5,4,3,3,5,4,0,0.0,neutral or dissatisfied +102005,17448,Female,Loyal Customer,39,Business travel,Eco Plus,376,3,3,5,3,3,3,3,3,3,5,2,1,5,3,0,0.0,satisfied +102006,24414,Male,Loyal Customer,22,Business travel,Business,2556,1,2,2,2,1,1,1,1,1,3,4,3,3,1,0,0.0,neutral or dissatisfied +102007,86783,Female,disloyal Customer,25,Business travel,Business,484,4,5,4,5,3,4,2,3,3,5,4,3,5,3,27,15.0,satisfied +102008,89416,Male,Loyal Customer,52,Business travel,Business,134,0,5,0,4,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +102009,40951,Female,Loyal Customer,67,Personal Travel,Eco Plus,599,1,5,1,2,2,3,3,4,4,1,4,4,4,3,16,6.0,neutral or dissatisfied +102010,119620,Female,disloyal Customer,34,Business travel,Business,335,2,2,2,3,5,2,5,5,4,2,5,5,5,5,0,0.0,neutral or dissatisfied +102011,34996,Female,disloyal Customer,29,Business travel,Eco,1182,2,2,2,4,2,1,4,2,2,3,3,4,2,4,171,183.0,neutral or dissatisfied +102012,43952,Male,disloyal Customer,15,Business travel,Business,473,3,4,3,4,4,3,4,4,2,3,3,2,3,4,0,0.0,neutral or dissatisfied +102013,126458,Female,disloyal Customer,31,Business travel,Business,1849,3,3,3,3,3,3,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +102014,59468,Male,Loyal Customer,48,Business travel,Business,2888,4,4,4,4,4,4,4,5,5,5,5,3,5,4,31,29.0,satisfied +102015,8862,Female,disloyal Customer,23,Business travel,Eco,539,5,0,4,1,3,4,3,3,3,2,5,3,5,3,55,51.0,satisfied +102016,16224,Female,Loyal Customer,44,Business travel,Business,3101,3,2,2,2,1,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +102017,85665,Male,Loyal Customer,45,Business travel,Business,903,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +102018,81475,Female,Loyal Customer,45,Business travel,Business,528,3,3,3,3,3,4,4,3,3,3,3,1,3,1,1,0.0,neutral or dissatisfied +102019,95604,Male,Loyal Customer,36,Business travel,Business,670,4,4,4,4,4,4,5,3,3,4,3,4,3,4,27,17.0,satisfied +102020,75190,Male,Loyal Customer,21,Business travel,Eco,1829,1,2,2,2,1,1,2,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +102021,43686,Female,disloyal Customer,44,Business travel,Eco,196,2,5,2,5,4,2,4,4,3,4,1,1,5,4,0,0.0,neutral or dissatisfied +102022,116873,Female,Loyal Customer,25,Business travel,Eco,368,1,4,4,4,1,1,3,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +102023,68419,Female,Loyal Customer,42,Personal Travel,Eco,1045,1,1,1,3,5,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +102024,107200,Female,Loyal Customer,28,Personal Travel,Eco,668,4,4,4,4,3,4,3,3,5,4,4,3,5,3,49,52.0,neutral or dissatisfied +102025,86705,Female,disloyal Customer,11,Business travel,Business,1747,0,0,0,3,4,0,5,4,4,5,3,3,4,4,0,0.0,satisfied +102026,46953,Male,Loyal Customer,64,Personal Travel,Eco,959,2,5,2,4,2,2,2,2,3,3,4,3,5,2,5,23.0,neutral or dissatisfied +102027,52747,Male,disloyal Customer,37,Business travel,Eco,806,1,1,1,2,4,1,4,4,5,1,2,3,4,4,0,0.0,neutral or dissatisfied +102028,73777,Male,Loyal Customer,68,Personal Travel,Eco,192,2,3,2,4,1,2,3,1,1,1,4,3,3,1,3,0.0,neutral or dissatisfied +102029,35718,Male,Loyal Customer,33,Personal Travel,Eco,2586,4,5,4,2,4,5,5,4,2,3,5,5,5,5,0,13.0,neutral or dissatisfied +102030,230,Female,disloyal Customer,44,Business travel,Business,213,2,2,2,5,2,2,2,2,3,4,4,5,4,2,6,40.0,neutral or dissatisfied +102031,55176,Female,Loyal Customer,34,Personal Travel,Eco,1608,3,4,3,4,1,3,5,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +102032,56819,Male,disloyal Customer,25,Business travel,Eco,959,4,4,4,3,3,4,3,3,4,5,4,3,3,3,65,36.0,neutral or dissatisfied +102033,20659,Male,disloyal Customer,25,Business travel,Eco,552,3,0,2,4,1,2,1,1,1,1,4,2,3,1,7,9.0,neutral or dissatisfied +102034,101660,Male,Loyal Customer,51,Business travel,Business,2106,3,3,3,3,5,5,4,3,3,3,3,5,3,4,3,0.0,satisfied +102035,88411,Male,Loyal Customer,56,Business travel,Business,1929,2,2,4,2,4,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +102036,92021,Female,disloyal Customer,19,Business travel,Business,1589,0,4,0,3,3,0,2,3,4,4,5,5,5,3,22,7.0,satisfied +102037,111750,Female,Loyal Customer,28,Personal Travel,Eco,1224,3,2,2,3,3,2,1,3,1,5,4,4,3,3,28,21.0,neutral or dissatisfied +102038,94144,Female,Loyal Customer,55,Business travel,Business,3679,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +102039,54502,Female,Loyal Customer,38,Business travel,Eco,925,4,2,2,2,4,4,4,4,3,1,1,4,3,4,2,0.0,satisfied +102040,30022,Female,Loyal Customer,52,Business travel,Business,571,2,1,1,1,5,4,3,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +102041,57699,Male,Loyal Customer,47,Personal Travel,Eco,867,5,5,5,2,1,5,1,1,5,3,5,5,5,1,0,0.0,satisfied +102042,118695,Male,Loyal Customer,68,Personal Travel,Eco,370,0,2,0,4,4,0,4,4,3,2,3,2,3,4,0,0.0,satisfied +102043,16214,Female,Loyal Customer,53,Business travel,Eco Plus,284,2,3,3,3,1,2,2,2,2,2,2,3,2,4,48,53.0,neutral or dissatisfied +102044,22579,Female,Loyal Customer,41,Business travel,Business,3799,5,5,5,5,4,5,3,4,4,4,4,3,4,1,95,89.0,satisfied +102045,92859,Male,Loyal Customer,31,Business travel,Business,2519,2,2,2,2,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +102046,97528,Female,Loyal Customer,48,Personal Travel,Eco,439,2,5,2,3,5,4,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +102047,94769,Male,disloyal Customer,21,Business travel,Eco,248,2,2,2,3,3,2,1,3,4,4,4,3,3,3,1,0.0,neutral or dissatisfied +102048,13559,Male,Loyal Customer,45,Personal Travel,Eco,152,3,4,3,4,1,3,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +102049,57335,Female,disloyal Customer,23,Business travel,Eco,414,3,0,3,2,2,3,2,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +102050,68810,Female,Loyal Customer,19,Personal Travel,Eco,861,2,4,2,2,1,2,2,1,4,5,4,5,4,1,26,18.0,neutral or dissatisfied +102051,126150,Female,Loyal Customer,36,Business travel,Business,3218,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +102052,13561,Male,Loyal Customer,65,Personal Travel,Eco,152,3,5,3,1,4,3,4,4,4,4,4,4,5,4,0,6.0,neutral or dissatisfied +102053,66982,Male,disloyal Customer,49,Business travel,Business,929,3,3,3,3,5,3,5,5,5,2,5,3,4,5,0,4.0,satisfied +102054,23006,Male,Loyal Customer,39,Personal Travel,Eco,528,3,4,3,1,3,5,5,4,1,2,3,5,3,5,200,201.0,neutral or dissatisfied +102055,5139,Female,Loyal Customer,19,Business travel,Eco Plus,184,3,5,5,5,3,4,1,3,4,4,4,2,4,3,67,43.0,neutral or dissatisfied +102056,13489,Male,Loyal Customer,51,Business travel,Business,3716,5,5,5,5,2,1,1,4,4,4,5,4,4,5,0,0.0,satisfied +102057,5415,Male,disloyal Customer,65,Business travel,Business,589,4,4,4,3,4,4,4,4,3,2,5,3,4,4,0,0.0,satisfied +102058,7010,Female,Loyal Customer,15,Personal Travel,Eco,234,0,3,0,3,0,3,3,4,3,4,4,3,2,3,151,214.0,satisfied +102059,123302,Male,Loyal Customer,29,Business travel,Business,600,3,3,3,3,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +102060,114822,Female,Loyal Customer,45,Business travel,Business,2389,0,0,0,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +102061,89301,Female,Loyal Customer,25,Personal Travel,Eco,453,1,4,1,1,4,1,4,4,4,1,2,4,3,4,0,51.0,neutral or dissatisfied +102062,160,Female,Loyal Customer,42,Personal Travel,Eco,227,2,4,2,2,4,4,5,4,4,2,3,5,4,4,55,59.0,neutral or dissatisfied +102063,82996,Female,Loyal Customer,42,Business travel,Business,957,1,1,1,1,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +102064,2598,Female,Loyal Customer,46,Personal Travel,Eco,280,1,5,1,1,3,5,5,1,1,1,1,3,1,4,13,15.0,neutral or dissatisfied +102065,77176,Female,Loyal Customer,54,Personal Travel,Eco,1355,2,3,2,4,5,4,3,4,4,2,4,3,4,4,0,6.0,neutral or dissatisfied +102066,24260,Female,Loyal Customer,62,Personal Travel,Eco,170,2,4,2,2,3,5,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +102067,36729,Male,Loyal Customer,49,Personal Travel,Eco Plus,1249,2,5,2,3,2,3,3,3,4,5,4,3,4,3,230,,neutral or dissatisfied +102068,112709,Male,Loyal Customer,50,Business travel,Eco,671,2,4,4,4,2,2,2,2,4,1,1,3,1,2,9,7.0,neutral or dissatisfied +102069,30672,Female,disloyal Customer,32,Business travel,Business,680,2,2,2,3,3,2,1,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +102070,79296,Female,disloyal Customer,20,Business travel,Eco,1273,3,3,3,3,3,3,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +102071,120449,Female,Loyal Customer,15,Personal Travel,Eco,366,2,5,4,4,4,4,4,4,5,5,3,2,4,4,0,18.0,neutral or dissatisfied +102072,6538,Female,disloyal Customer,38,Business travel,Business,473,3,3,3,2,2,3,2,2,5,3,5,5,5,2,0,40.0,neutral or dissatisfied +102073,84269,Male,Loyal Customer,43,Business travel,Business,349,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +102074,12738,Female,Loyal Customer,16,Personal Travel,Eco,721,4,4,4,3,4,5,5,3,2,5,2,5,4,5,337,330.0,neutral or dissatisfied +102075,81527,Female,Loyal Customer,30,Business travel,Business,1124,2,5,4,5,2,2,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +102076,11968,Male,disloyal Customer,65,Business travel,Business,643,4,3,3,2,2,4,4,2,3,2,5,3,4,2,0,9.0,satisfied +102077,110643,Female,disloyal Customer,39,Business travel,Business,829,4,4,4,3,4,4,4,4,3,4,4,4,4,4,24,26.0,satisfied +102078,23851,Female,Loyal Customer,23,Business travel,Business,552,4,4,4,4,2,2,2,2,2,1,4,4,5,2,0,2.0,satisfied +102079,9001,Female,Loyal Customer,17,Personal Travel,Eco Plus,252,3,3,0,1,3,0,3,3,1,5,3,4,1,3,109,95.0,neutral or dissatisfied +102080,111039,Male,Loyal Customer,42,Business travel,Business,197,1,3,3,3,2,2,2,2,2,3,1,2,2,1,4,25.0,neutral or dissatisfied +102081,128549,Female,Loyal Customer,58,Business travel,Business,2473,5,5,4,5,3,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +102082,93006,Female,Loyal Customer,29,Business travel,Business,1524,4,4,4,4,3,3,3,3,3,5,4,5,5,3,0,0.0,satisfied +102083,115426,Male,disloyal Customer,62,Business travel,Business,362,4,4,4,3,4,4,5,4,3,2,4,1,4,4,3,0.0,neutral or dissatisfied +102084,52355,Female,Loyal Customer,67,Personal Travel,Eco,370,4,5,4,1,5,3,5,5,5,4,5,4,5,2,34,25.0,satisfied +102085,77086,Male,Loyal Customer,44,Business travel,Business,3469,2,2,2,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +102086,68995,Male,disloyal Customer,28,Business travel,Eco,974,2,2,2,2,2,2,2,4,3,1,1,2,2,2,17,0.0,neutral or dissatisfied +102087,52734,Female,Loyal Customer,45,Business travel,Business,2306,5,5,5,5,1,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +102088,35345,Female,Loyal Customer,15,Business travel,Eco,1069,4,4,4,4,4,4,3,4,1,3,4,3,3,4,0,0.0,neutral or dissatisfied +102089,78216,Male,Loyal Customer,20,Personal Travel,Eco,153,1,4,0,2,5,0,4,5,4,2,4,4,5,5,2,6.0,neutral or dissatisfied +102090,93209,Female,Loyal Customer,43,Personal Travel,Eco,1845,2,4,2,1,2,4,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +102091,82315,Female,Loyal Customer,26,Business travel,Business,610,3,3,3,3,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +102092,90151,Female,Loyal Customer,65,Business travel,Eco,557,5,5,5,5,1,2,1,5,5,5,5,2,5,1,0,0.0,satisfied +102093,88459,Male,disloyal Customer,47,Business travel,Eco,406,0,0,0,2,5,0,5,5,4,4,1,2,3,5,5,0.0,satisfied +102094,50409,Female,disloyal Customer,21,Business travel,Eco,110,1,1,1,3,2,1,3,2,3,4,4,4,3,2,50,47.0,neutral or dissatisfied +102095,126571,Female,Loyal Customer,58,Business travel,Business,1711,2,2,2,2,5,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +102096,86443,Female,Loyal Customer,54,Business travel,Business,2608,2,1,1,1,4,2,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +102097,129526,Male,Loyal Customer,50,Business travel,Business,2342,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +102098,77741,Male,Loyal Customer,48,Business travel,Eco,874,4,5,5,5,4,4,4,4,2,3,3,1,2,4,0,0.0,satisfied +102099,93071,Female,Loyal Customer,51,Personal Travel,Eco,297,4,4,4,3,4,5,5,4,4,4,4,3,4,5,22,13.0,neutral or dissatisfied +102100,109881,Male,Loyal Customer,57,Business travel,Business,1204,2,3,3,3,4,4,4,2,2,2,2,2,2,2,18,0.0,neutral or dissatisfied +102101,2022,Female,Loyal Customer,42,Business travel,Business,812,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +102102,106290,Female,Loyal Customer,24,Personal Travel,Eco,689,2,4,2,3,5,2,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +102103,14092,Male,Loyal Customer,57,Business travel,Business,201,0,5,0,3,2,1,4,5,5,3,3,4,5,5,15,1.0,satisfied +102104,86470,Male,disloyal Customer,36,Business travel,Business,362,2,2,2,2,2,2,2,2,2,4,5,2,4,2,0,3.0,neutral or dissatisfied +102105,53355,Female,Loyal Customer,12,Business travel,Business,1476,2,2,2,2,2,2,2,2,4,2,4,4,3,2,19,24.0,neutral or dissatisfied +102106,7808,Female,Loyal Customer,39,Business travel,Business,650,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +102107,112418,Female,Loyal Customer,54,Business travel,Business,3616,4,2,2,2,4,4,4,4,4,4,4,4,4,2,42,23.0,neutral or dissatisfied +102108,106387,Male,Loyal Customer,39,Business travel,Business,1699,1,1,1,1,5,4,5,4,4,4,4,5,4,4,72,62.0,satisfied +102109,24144,Female,Loyal Customer,43,Business travel,Business,151,1,1,4,1,1,4,3,4,4,4,5,2,4,1,0,0.0,satisfied +102110,65816,Male,Loyal Customer,45,Business travel,Business,1389,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +102111,66899,Male,Loyal Customer,58,Business travel,Business,2269,1,1,1,1,2,5,5,4,4,4,4,5,4,5,9,1.0,satisfied +102112,102335,Male,Loyal Customer,71,Business travel,Business,258,2,4,4,4,2,4,3,2,2,3,2,2,2,3,22,13.0,neutral or dissatisfied +102113,94821,Female,Loyal Customer,25,Business travel,Business,192,2,4,4,4,2,2,2,2,2,1,4,1,4,2,4,5.0,neutral or dissatisfied +102114,114627,Female,Loyal Customer,46,Business travel,Business,1502,2,2,2,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +102115,2681,Female,Loyal Customer,26,Personal Travel,Eco,622,1,4,1,3,5,1,5,5,5,2,4,3,5,5,0,3.0,neutral or dissatisfied +102116,27237,Female,Loyal Customer,12,Personal Travel,Eco,1024,4,2,4,3,1,4,1,1,3,1,3,1,3,1,0,0.0,satisfied +102117,40066,Female,Loyal Customer,26,Personal Travel,Business,493,2,4,2,1,5,2,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +102118,68855,Male,Loyal Customer,46,Business travel,Business,3666,2,2,2,2,2,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +102119,56546,Male,Loyal Customer,41,Business travel,Business,937,5,5,5,5,5,4,4,5,5,5,5,5,5,5,77,60.0,satisfied +102120,10791,Female,Loyal Customer,72,Business travel,Business,482,1,2,2,2,2,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +102121,62981,Female,Loyal Customer,50,Business travel,Business,967,3,1,1,1,2,4,3,3,3,3,3,4,3,1,1,0.0,neutral or dissatisfied +102122,126546,Female,Loyal Customer,35,Personal Travel,Eco,644,2,4,1,4,5,1,5,5,4,3,3,4,4,5,8,24.0,neutral or dissatisfied +102123,39422,Female,Loyal Customer,66,Business travel,Eco,129,5,3,3,3,3,1,1,5,5,5,5,3,5,4,0,1.0,satisfied +102124,56073,Female,Loyal Customer,27,Personal Travel,Eco,2475,1,5,1,3,2,1,2,2,1,5,5,5,4,2,0,0.0,neutral or dissatisfied +102125,3583,Male,Loyal Customer,43,Business travel,Business,3337,4,4,4,4,4,5,5,5,5,5,5,4,5,4,35,38.0,satisfied +102126,22650,Male,Loyal Customer,61,Business travel,Eco Plus,300,5,3,1,1,4,5,4,4,5,5,5,1,1,4,53,39.0,satisfied +102127,108341,Female,Loyal Customer,47,Business travel,Business,1706,2,4,1,4,3,2,4,2,2,2,2,2,2,3,3,0.0,neutral or dissatisfied +102128,125620,Female,Loyal Customer,27,Personal Travel,Business,759,4,5,4,2,3,4,3,3,5,2,4,3,5,3,0,0.0,satisfied +102129,7815,Male,Loyal Customer,49,Business travel,Eco,650,2,2,2,2,2,2,2,2,4,4,3,1,2,2,0,7.0,neutral or dissatisfied +102130,19132,Female,Loyal Customer,10,Personal Travel,Eco,287,2,5,3,3,3,1,1,5,4,5,4,1,4,1,127,133.0,neutral or dissatisfied +102131,21386,Female,Loyal Customer,46,Personal Travel,Business,331,3,0,3,3,2,3,1,4,4,3,2,3,4,3,0,0.0,neutral or dissatisfied +102132,102814,Male,Loyal Customer,55,Business travel,Business,342,5,5,5,5,4,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +102133,46412,Male,disloyal Customer,30,Business travel,Eco,458,3,0,3,4,3,3,3,3,4,3,2,5,1,3,0,0.0,neutral or dissatisfied +102134,51557,Male,Loyal Customer,27,Business travel,Business,3209,2,2,4,2,3,3,3,3,5,3,4,5,4,3,12,1.0,satisfied +102135,111871,Male,Loyal Customer,55,Business travel,Business,3893,2,3,5,5,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +102136,13007,Female,Loyal Customer,53,Business travel,Eco,438,5,3,3,3,5,4,5,5,5,5,5,1,5,2,0,0.0,satisfied +102137,9728,Female,Loyal Customer,66,Personal Travel,Eco Plus,277,1,2,3,4,3,3,4,3,3,3,3,4,3,3,10,0.0,neutral or dissatisfied +102138,41368,Male,disloyal Customer,27,Business travel,Eco,809,2,1,1,3,1,5,5,3,4,3,3,5,2,5,184,169.0,neutral or dissatisfied +102139,107211,Female,Loyal Customer,45,Business travel,Business,3363,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +102140,10687,Female,disloyal Customer,26,Business travel,Business,295,5,0,5,5,5,5,5,5,4,2,4,5,4,5,0,10.0,satisfied +102141,69566,Male,Loyal Customer,59,Business travel,Business,2586,1,3,3,3,1,1,1,1,1,4,3,1,4,1,83,116.0,neutral or dissatisfied +102142,81462,Female,Loyal Customer,55,Business travel,Business,408,4,4,4,4,2,4,5,5,5,5,5,3,5,5,19,13.0,satisfied +102143,2355,Female,Loyal Customer,33,Business travel,Business,3068,5,5,5,5,2,5,5,5,5,5,5,3,5,3,39,25.0,satisfied +102144,38814,Male,Loyal Customer,49,Personal Travel,Eco,353,3,1,3,3,4,3,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +102145,36628,Female,disloyal Customer,36,Business travel,Eco,785,1,1,1,3,2,1,2,2,1,1,4,3,5,2,0,0.0,neutral or dissatisfied +102146,58670,Female,Loyal Customer,35,Business travel,Business,2672,2,2,2,2,5,4,5,4,4,4,4,4,4,4,15,14.0,satisfied +102147,116212,Female,Loyal Customer,63,Personal Travel,Eco,358,3,5,3,5,3,5,4,4,4,3,4,5,4,5,10,0.0,neutral or dissatisfied +102148,112731,Female,Loyal Customer,38,Personal Travel,Eco,671,3,5,3,1,1,3,1,1,3,5,4,5,4,1,43,36.0,neutral or dissatisfied +102149,83882,Female,Loyal Customer,8,Personal Travel,Eco,1670,2,4,2,4,2,2,2,2,2,2,1,1,1,2,0,4.0,neutral or dissatisfied +102150,18712,Female,Loyal Customer,52,Personal Travel,Eco Plus,190,5,4,5,3,2,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +102151,113027,Male,Loyal Customer,43,Business travel,Business,543,1,1,1,1,5,5,5,5,5,5,5,5,5,3,42,49.0,satisfied +102152,49330,Female,Loyal Customer,35,Business travel,Business,3371,4,4,4,4,1,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +102153,129705,Male,Loyal Customer,56,Business travel,Business,3734,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +102154,50315,Female,Loyal Customer,35,Business travel,Business,2815,5,5,5,5,5,1,1,5,5,5,4,3,5,5,0,0.0,satisfied +102155,59853,Male,Loyal Customer,49,Business travel,Business,1065,5,5,5,5,5,5,4,5,5,5,5,5,5,4,29,0.0,satisfied +102156,79926,Male,Loyal Customer,37,Business travel,Business,1089,2,4,4,4,3,4,3,2,2,2,2,2,2,3,0,12.0,neutral or dissatisfied +102157,51356,Male,Loyal Customer,15,Business travel,Eco Plus,337,2,4,4,4,2,2,2,2,2,1,4,2,4,2,100,99.0,neutral or dissatisfied +102158,36327,Female,disloyal Customer,22,Business travel,Eco,187,3,3,3,4,4,3,2,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +102159,106803,Female,Loyal Customer,47,Business travel,Eco,977,5,3,4,3,2,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +102160,48037,Female,Loyal Customer,69,Personal Travel,Business,677,2,4,3,3,5,4,4,1,1,3,1,3,1,1,0,16.0,neutral or dissatisfied +102161,108493,Female,Loyal Customer,62,Personal Travel,Eco,570,2,5,3,1,5,4,4,2,2,3,5,4,2,3,5,9.0,neutral or dissatisfied +102162,9167,Male,Loyal Customer,47,Business travel,Business,3644,2,2,2,2,2,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +102163,75539,Female,disloyal Customer,25,Business travel,Business,337,2,4,2,1,1,2,1,1,3,2,4,5,4,1,0,0.0,neutral or dissatisfied +102164,118002,Female,Loyal Customer,54,Personal Travel,Eco Plus,255,1,3,1,5,1,2,3,3,3,1,3,3,3,1,117,121.0,neutral or dissatisfied +102165,2702,Female,Loyal Customer,32,Business travel,Business,562,3,3,3,3,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +102166,79603,Female,Loyal Customer,49,Business travel,Eco,762,4,4,4,4,1,4,4,5,5,4,5,1,5,4,73,87.0,neutral or dissatisfied +102167,36465,Male,Loyal Customer,65,Personal Travel,Eco,867,4,3,4,4,4,4,4,4,2,3,4,3,3,4,102,129.0,neutral or dissatisfied +102168,116572,Female,Loyal Customer,42,Business travel,Business,1908,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +102169,35249,Male,Loyal Customer,38,Business travel,Business,944,1,1,1,1,2,4,1,4,4,4,4,3,4,3,0,8.0,satisfied +102170,74396,Female,Loyal Customer,44,Business travel,Business,1464,1,1,2,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +102171,120065,Male,Loyal Customer,53,Business travel,Business,2090,5,5,5,5,3,4,5,4,4,4,4,4,4,5,30,19.0,satisfied +102172,58671,Male,Loyal Customer,44,Business travel,Business,2205,1,5,4,4,4,3,4,2,2,1,1,1,2,2,1,0.0,neutral or dissatisfied +102173,46543,Male,Loyal Customer,41,Business travel,Business,3246,2,2,2,2,1,1,2,2,2,2,2,1,2,3,0,4.0,neutral or dissatisfied +102174,110547,Male,Loyal Customer,40,Business travel,Eco,551,3,2,2,2,3,3,3,3,4,1,4,1,3,3,0,5.0,neutral or dissatisfied +102175,12427,Male,Loyal Customer,63,Personal Travel,Eco,201,2,3,0,4,3,0,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +102176,44056,Male,disloyal Customer,37,Business travel,Eco Plus,237,1,1,1,4,2,1,2,2,4,4,3,4,3,2,5,9.0,neutral or dissatisfied +102177,7502,Male,Loyal Customer,50,Personal Travel,Eco Plus,925,4,4,4,1,1,4,1,1,5,5,3,5,3,1,1,0.0,neutral or dissatisfied +102178,28478,Female,Loyal Customer,11,Personal Travel,Eco,1721,1,4,1,3,3,1,5,3,4,3,3,3,4,3,0,0.0,neutral or dissatisfied +102179,16320,Female,disloyal Customer,22,Business travel,Eco,628,4,5,4,2,2,4,2,2,2,1,2,1,2,2,0,0.0,satisfied +102180,40590,Male,Loyal Customer,49,Business travel,Eco,391,4,3,3,3,4,4,4,4,4,5,4,4,3,4,0,3.0,neutral or dissatisfied +102181,96296,Female,Loyal Customer,69,Personal Travel,Eco,460,3,4,3,3,5,4,4,5,5,3,5,4,5,3,19,21.0,neutral or dissatisfied +102182,104757,Male,Loyal Customer,37,Personal Travel,Eco,1407,2,4,2,4,5,2,2,5,5,4,3,1,3,5,43,48.0,neutral or dissatisfied +102183,119379,Male,disloyal Customer,45,Business travel,Business,399,5,5,5,4,2,5,3,2,4,2,4,4,5,2,0,0.0,satisfied +102184,97179,Male,Loyal Customer,65,Personal Travel,Eco,1211,3,0,3,3,1,3,1,1,5,4,5,4,4,1,6,6.0,neutral or dissatisfied +102185,99672,Female,Loyal Customer,46,Personal Travel,Eco,1050,1,5,1,2,4,4,4,4,4,1,4,3,4,3,8,0.0,neutral or dissatisfied +102186,63223,Male,disloyal Customer,23,Business travel,Eco,447,1,4,1,1,2,1,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +102187,78103,Male,Loyal Customer,7,Personal Travel,Eco,655,3,1,2,4,1,2,1,1,3,1,2,4,3,1,3,0.0,neutral or dissatisfied +102188,50888,Male,Loyal Customer,21,Personal Travel,Eco,363,1,4,5,3,5,5,5,5,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +102189,28995,Female,disloyal Customer,30,Business travel,Eco,954,1,1,1,3,3,1,3,3,1,1,5,2,1,3,0,0.0,neutral or dissatisfied +102190,116492,Male,Loyal Customer,41,Personal Travel,Eco,417,4,3,4,2,3,4,2,3,3,4,1,5,3,3,37,37.0,neutral or dissatisfied +102191,26583,Male,Loyal Customer,68,Business travel,Eco,404,4,4,4,4,4,4,4,4,4,3,2,3,5,4,2,0.0,satisfied +102192,78989,Male,Loyal Customer,52,Business travel,Business,3201,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +102193,19822,Male,Loyal Customer,58,Business travel,Eco,528,3,1,1,1,3,3,3,3,3,1,3,3,3,3,124,125.0,neutral or dissatisfied +102194,114859,Female,Loyal Customer,52,Business travel,Business,3554,2,2,2,2,5,5,5,4,4,4,4,4,4,3,7,1.0,satisfied +102195,67939,Female,Loyal Customer,22,Personal Travel,Eco,1235,3,0,3,1,3,3,4,3,4,5,4,3,4,3,14,0.0,neutral or dissatisfied +102196,2263,Female,Loyal Customer,39,Business travel,Business,691,5,5,5,5,5,5,5,4,4,4,4,5,4,3,0,8.0,satisfied +102197,118754,Female,Loyal Customer,27,Personal Travel,Eco,338,1,5,1,1,5,1,5,5,5,5,4,3,5,5,1,3.0,neutral or dissatisfied +102198,58895,Female,Loyal Customer,46,Business travel,Eco,888,2,4,4,4,5,4,3,2,2,2,2,4,2,2,0,6.0,neutral or dissatisfied +102199,375,Male,Loyal Customer,53,Business travel,Business,2235,3,3,3,3,5,4,5,4,4,4,4,4,4,5,0,3.0,satisfied +102200,122580,Male,Loyal Customer,41,Business travel,Business,2714,3,3,5,3,5,4,5,4,4,4,4,3,4,5,14,1.0,satisfied +102201,71889,Female,Loyal Customer,27,Personal Travel,Eco,1723,1,4,1,2,2,1,2,2,4,2,4,4,5,2,0,5.0,neutral or dissatisfied +102202,26827,Male,Loyal Customer,68,Business travel,Business,2743,3,4,4,4,1,3,3,3,3,3,3,3,3,4,20,22.0,neutral or dissatisfied +102203,47252,Female,disloyal Customer,25,Business travel,Business,588,2,4,2,3,1,2,1,1,4,5,5,4,4,1,0,2.0,neutral or dissatisfied +102204,10519,Female,Loyal Customer,42,Business travel,Business,1876,5,5,5,5,2,4,4,5,5,5,4,5,5,5,0,0.0,satisfied +102205,62181,Female,Loyal Customer,11,Business travel,Eco,2434,2,1,1,1,2,2,3,2,3,5,3,3,3,2,7,29.0,neutral or dissatisfied +102206,37437,Male,disloyal Customer,27,Business travel,Eco,950,4,4,4,2,2,4,2,2,3,5,2,4,3,2,0,2.0,satisfied +102207,21556,Female,disloyal Customer,25,Business travel,Eco Plus,399,3,4,3,4,2,3,1,2,2,2,2,1,5,2,0,0.0,neutral or dissatisfied +102208,108417,Male,Loyal Customer,50,Business travel,Business,3766,2,2,3,2,3,4,4,2,2,2,2,3,2,1,13,15.0,neutral or dissatisfied +102209,54731,Male,Loyal Customer,16,Personal Travel,Eco,787,2,4,2,2,2,2,2,2,3,3,1,4,2,2,9,11.0,neutral or dissatisfied +102210,26632,Male,Loyal Customer,53,Business travel,Eco,270,5,5,5,5,5,5,5,5,3,5,3,2,3,5,0,22.0,satisfied +102211,64279,Female,Loyal Customer,41,Business travel,Business,1192,1,1,2,1,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +102212,27205,Male,Loyal Customer,59,Business travel,Eco,2717,5,1,1,1,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +102213,53060,Male,Loyal Customer,70,Personal Travel,Eco,1208,3,1,3,4,2,3,2,2,2,4,4,4,3,2,0,0.0,neutral or dissatisfied +102214,57665,Female,Loyal Customer,21,Personal Travel,Eco,200,2,5,0,4,4,0,4,4,4,1,2,2,5,4,20,0.0,neutral or dissatisfied +102215,16307,Male,disloyal Customer,26,Business travel,Eco,628,5,0,5,3,5,5,5,5,3,1,5,4,5,5,21,23.0,satisfied +102216,125310,Female,Loyal Customer,40,Personal Travel,Eco,678,3,4,3,5,4,3,4,4,3,2,4,5,5,4,0,2.0,neutral or dissatisfied +102217,65413,Male,disloyal Customer,37,Business travel,Business,631,3,4,4,4,3,4,3,3,5,4,5,3,5,3,10,0.0,satisfied +102218,44800,Female,disloyal Customer,39,Business travel,Business,1041,3,3,3,4,4,3,1,4,5,2,2,3,4,4,1,0.0,neutral or dissatisfied +102219,61908,Female,disloyal Customer,22,Business travel,Eco,550,3,5,3,2,4,3,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +102220,16453,Male,Loyal Customer,17,Personal Travel,Eco,416,3,1,5,3,3,5,3,3,4,4,4,2,3,3,33,33.0,neutral or dissatisfied +102221,109076,Female,Loyal Customer,39,Personal Travel,Eco,781,3,5,3,1,4,3,1,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +102222,62490,Male,Loyal Customer,51,Business travel,Business,1744,4,4,4,4,3,5,5,4,4,5,4,3,4,3,42,34.0,satisfied +102223,32134,Female,Loyal Customer,35,Business travel,Business,3936,3,1,5,5,5,3,4,2,2,3,3,1,2,1,0,1.0,neutral or dissatisfied +102224,50298,Female,Loyal Customer,41,Business travel,Eco,308,5,4,4,4,5,5,5,5,1,1,4,2,2,5,0,0.0,satisfied +102225,13076,Male,disloyal Customer,35,Business travel,Business,427,2,2,2,4,3,2,3,3,4,4,4,3,5,3,3,1.0,neutral or dissatisfied +102226,80081,Female,Loyal Customer,30,Business travel,Business,1096,4,4,4,4,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +102227,20413,Male,Loyal Customer,34,Business travel,Eco,196,5,4,5,4,5,5,5,5,2,1,2,3,5,5,0,0.0,satisfied +102228,42972,Male,disloyal Customer,37,Business travel,Eco,259,4,0,4,3,2,4,2,2,2,4,5,3,3,2,0,0.0,satisfied +102229,38652,Female,disloyal Customer,29,Business travel,Eco,710,1,1,1,3,4,1,4,4,1,3,3,3,4,4,0,0.0,neutral or dissatisfied +102230,21824,Male,Loyal Customer,30,Personal Travel,Eco,907,3,4,3,4,4,3,4,4,2,5,3,3,4,4,0,0.0,neutral or dissatisfied +102231,107084,Female,Loyal Customer,70,Personal Travel,Eco Plus,395,3,2,3,4,5,4,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +102232,30490,Male,Loyal Customer,43,Business travel,Eco,627,5,5,5,5,5,5,5,5,3,4,5,3,1,5,0,0.0,satisfied +102233,110630,Female,Loyal Customer,41,Personal Travel,Eco,727,2,5,2,5,1,2,4,1,2,5,4,1,1,1,0,6.0,neutral or dissatisfied +102234,99679,Male,disloyal Customer,42,Business travel,Business,442,3,3,3,4,2,3,5,2,4,5,4,3,5,2,14,6.0,neutral or dissatisfied +102235,125091,Female,Loyal Customer,46,Business travel,Business,1782,2,2,2,2,2,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +102236,60315,Female,Loyal Customer,47,Business travel,Business,836,2,2,2,2,4,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +102237,58453,Male,Loyal Customer,63,Personal Travel,Eco,733,3,3,3,4,4,3,4,4,2,5,3,3,4,4,0,0.0,neutral or dissatisfied +102238,70177,Male,Loyal Customer,58,Business travel,Business,258,5,5,5,5,2,4,5,5,5,5,5,3,5,5,39,51.0,satisfied +102239,39552,Male,Loyal Customer,50,Business travel,Business,965,5,5,5,5,1,4,2,3,3,3,3,4,3,5,0,0.0,satisfied +102240,51284,Female,Loyal Customer,39,Business travel,Eco Plus,86,2,5,5,5,2,2,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +102241,60316,Female,Loyal Customer,29,Business travel,Business,1024,1,1,2,1,5,5,5,5,4,4,5,4,5,5,1,0.0,satisfied +102242,91262,Female,Loyal Customer,24,Personal Travel,Eco,404,2,2,5,4,4,5,4,4,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +102243,29961,Male,Loyal Customer,37,Business travel,Eco,160,5,3,3,3,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +102244,110179,Male,Loyal Customer,54,Personal Travel,Eco,869,4,4,4,3,3,4,3,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +102245,27126,Female,Loyal Customer,47,Business travel,Business,2640,5,5,5,5,4,5,1,4,4,4,4,1,4,2,0,0.0,satisfied +102246,113856,Male,Loyal Customer,48,Business travel,Business,1363,2,2,2,2,4,4,4,2,2,3,2,5,2,3,22,20.0,satisfied +102247,84783,Female,Loyal Customer,37,Business travel,Business,2942,2,2,3,2,5,4,3,2,2,1,2,3,2,2,15,13.0,neutral or dissatisfied +102248,119482,Male,Loyal Customer,47,Business travel,Business,899,5,5,5,5,2,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +102249,22923,Male,disloyal Customer,26,Business travel,Business,528,1,1,1,1,5,1,5,5,4,5,4,4,4,5,0,70.0,neutral or dissatisfied +102250,72552,Male,disloyal Customer,23,Business travel,Eco,918,2,2,2,4,2,2,2,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +102251,71322,Male,Loyal Customer,41,Business travel,Business,1514,2,5,5,5,5,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +102252,78230,Male,Loyal Customer,49,Personal Travel,Eco,153,2,1,2,1,2,2,4,2,4,3,1,2,1,2,33,32.0,neutral or dissatisfied +102253,103034,Male,disloyal Customer,74,Business travel,Eco,460,4,2,4,2,3,4,3,3,1,4,3,4,3,3,2,2.0,neutral or dissatisfied +102254,42587,Female,Loyal Customer,43,Personal Travel,Eco,554,3,5,3,3,2,5,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +102255,33655,Female,Loyal Customer,52,Personal Travel,Eco,413,4,5,4,1,5,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +102256,114765,Male,disloyal Customer,25,Business travel,Business,333,5,0,5,4,2,5,2,2,5,5,5,5,5,2,0,4.0,satisfied +102257,36627,Female,Loyal Customer,36,Business travel,Eco,721,2,4,4,4,2,3,2,2,5,1,5,4,5,2,0,11.0,satisfied +102258,117210,Male,Loyal Customer,10,Personal Travel,Eco,338,3,5,3,5,2,3,2,2,4,4,5,3,4,2,8,1.0,neutral or dissatisfied +102259,76613,Male,disloyal Customer,32,Business travel,Business,547,2,2,2,3,5,2,2,5,3,2,5,5,5,5,0,0.0,neutral or dissatisfied +102260,8035,Female,Loyal Customer,38,Business travel,Business,3174,2,2,2,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +102261,87639,Male,disloyal Customer,22,Business travel,Eco,606,4,0,4,5,5,4,5,5,3,5,5,3,4,5,0,0.0,neutral or dissatisfied +102262,70102,Female,Loyal Customer,24,Business travel,Eco,460,3,2,4,2,3,1,3,4,2,4,4,3,2,3,123,146.0,neutral or dissatisfied +102263,7255,Male,Loyal Customer,58,Personal Travel,Eco,130,1,0,1,2,1,1,1,1,4,4,5,3,5,1,0,0.0,neutral or dissatisfied +102264,110429,Male,Loyal Customer,41,Business travel,Eco,442,1,5,5,5,1,1,1,1,2,3,4,1,4,1,73,59.0,neutral or dissatisfied +102265,120607,Male,Loyal Customer,28,Business travel,Business,3625,5,5,5,5,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +102266,75365,Male,Loyal Customer,48,Personal Travel,Eco Plus,2486,3,1,3,4,1,3,1,1,3,4,3,1,3,1,2,0.0,neutral or dissatisfied +102267,68096,Female,Loyal Customer,46,Business travel,Business,3743,5,5,4,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +102268,87331,Female,Loyal Customer,43,Business travel,Business,1592,1,1,1,1,4,5,4,4,4,5,4,4,4,5,0,1.0,satisfied +102269,128245,Female,Loyal Customer,9,Personal Travel,Eco Plus,602,3,4,3,4,1,3,3,1,1,2,3,2,4,1,1,3.0,neutral or dissatisfied +102270,109055,Female,Loyal Customer,44,Business travel,Business,1041,4,3,3,3,3,4,4,2,2,3,2,4,3,4,180,174.0,neutral or dissatisfied +102271,33060,Female,Loyal Customer,34,Personal Travel,Eco,216,1,0,0,3,4,0,1,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +102272,6780,Female,Loyal Customer,40,Business travel,Business,3005,5,5,5,5,4,4,5,5,5,4,5,3,5,4,0,5.0,satisfied +102273,125362,Male,Loyal Customer,61,Personal Travel,Eco,599,3,2,3,3,3,3,3,3,4,1,4,2,3,3,0,0.0,neutral or dissatisfied +102274,48513,Male,Loyal Customer,52,Business travel,Eco,853,4,1,5,1,4,4,4,4,2,3,2,3,4,4,7,0.0,satisfied +102275,57045,Female,Loyal Customer,60,Business travel,Business,2133,4,4,4,4,5,3,5,4,4,4,4,3,4,5,5,0.0,satisfied +102276,80258,Male,Loyal Customer,59,Business travel,Business,1969,2,2,2,2,2,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +102277,25452,Male,Loyal Customer,54,Personal Travel,Eco,669,1,4,1,5,3,1,3,3,4,5,5,4,4,3,0,6.0,neutral or dissatisfied +102278,23389,Male,Loyal Customer,38,Business travel,Eco,300,3,3,5,3,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +102279,122013,Male,Loyal Customer,49,Business travel,Eco,185,1,5,5,5,2,1,2,2,4,5,3,2,2,2,0,0.0,neutral or dissatisfied +102280,27488,Female,disloyal Customer,25,Business travel,Eco,937,3,3,3,4,1,3,1,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +102281,9556,Male,Loyal Customer,44,Business travel,Eco,292,2,4,2,4,2,2,2,2,4,1,4,4,3,2,105,108.0,neutral or dissatisfied +102282,127633,Female,disloyal Customer,35,Business travel,Eco,1337,3,3,3,4,3,3,3,3,1,3,3,4,4,3,22,26.0,neutral or dissatisfied +102283,95444,Female,Loyal Customer,47,Business travel,Business,2432,5,5,5,5,5,4,5,5,5,5,5,3,5,4,0,1.0,satisfied +102284,87295,Male,Loyal Customer,52,Personal Travel,Eco,577,3,5,3,4,4,3,4,4,5,4,4,5,5,4,34,17.0,neutral or dissatisfied +102285,23033,Male,Loyal Customer,41,Personal Travel,Eco,1020,3,3,3,3,2,3,2,2,3,5,1,1,1,2,0,0.0,neutral or dissatisfied +102286,24317,Female,Loyal Customer,52,Business travel,Business,3252,3,5,5,5,4,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +102287,103232,Male,Loyal Customer,67,Business travel,Business,3182,4,2,2,2,5,2,2,4,4,4,4,4,4,3,27,17.0,neutral or dissatisfied +102288,78874,Male,Loyal Customer,62,Personal Travel,Eco Plus,1995,1,1,1,4,1,1,1,1,4,1,4,1,4,1,12,0.0,neutral or dissatisfied +102289,56820,Female,Loyal Customer,50,Business travel,Eco,1005,4,1,5,1,4,5,4,4,4,4,4,4,4,4,0,4.0,satisfied +102290,81373,Female,disloyal Customer,26,Business travel,Eco Plus,282,2,2,2,4,5,2,5,5,2,4,4,3,4,5,6,1.0,neutral or dissatisfied +102291,31092,Female,disloyal Customer,29,Business travel,Eco,1014,2,2,2,2,3,2,3,3,3,2,3,4,3,3,0,21.0,neutral or dissatisfied +102292,38919,Male,Loyal Customer,48,Business travel,Business,2516,2,2,2,2,1,4,3,5,5,5,5,5,5,5,0,0.0,satisfied +102293,34926,Male,Loyal Customer,41,Business travel,Eco,187,3,3,3,3,3,3,3,1,5,2,2,3,4,3,274,310.0,neutral or dissatisfied +102294,37282,Female,Loyal Customer,25,Business travel,Eco,1053,5,1,5,5,5,5,4,5,1,1,2,1,5,5,0,0.0,satisfied +102295,68023,Female,Loyal Customer,30,Personal Travel,Eco,304,1,5,1,1,4,1,3,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +102296,25055,Female,disloyal Customer,10,Business travel,Eco,594,3,0,3,2,4,3,4,4,4,4,1,1,5,4,5,2.0,neutral or dissatisfied +102297,121685,Male,Loyal Customer,35,Personal Travel,Eco,328,1,2,1,4,4,1,4,4,2,5,4,2,3,4,19,17.0,neutral or dissatisfied +102298,90534,Male,Loyal Customer,57,Business travel,Business,2160,1,1,5,1,3,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +102299,41395,Female,disloyal Customer,34,Business travel,Eco,563,1,3,1,3,2,1,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +102300,91874,Female,disloyal Customer,46,Business travel,Business,1185,4,5,5,4,5,4,5,5,5,2,4,4,4,5,7,0.0,satisfied +102301,99053,Male,Loyal Customer,47,Business travel,Business,453,3,3,2,3,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +102302,51374,Male,Loyal Customer,65,Personal Travel,Eco Plus,337,3,4,3,2,4,3,3,4,3,1,1,2,5,4,0,0.0,neutral or dissatisfied +102303,68246,Male,Loyal Customer,36,Business travel,Eco,231,4,5,5,5,4,4,4,4,5,1,3,4,1,4,1,2.0,satisfied +102304,56580,Male,Loyal Customer,10,Business travel,Business,997,4,5,4,4,4,4,4,4,3,4,4,5,4,4,2,4.0,satisfied +102305,102606,Male,Loyal Customer,22,Personal Travel,Eco Plus,258,2,3,2,4,4,2,4,4,2,3,4,2,3,4,0,0.0,neutral or dissatisfied +102306,21725,Female,Loyal Customer,51,Business travel,Business,563,4,4,4,4,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +102307,43981,Male,Loyal Customer,22,Personal Travel,Eco,411,4,5,4,2,2,4,2,2,3,5,1,2,3,2,0,0.0,neutral or dissatisfied +102308,104233,Male,Loyal Customer,29,Business travel,Business,1276,1,1,1,1,5,5,5,5,3,5,4,4,5,5,46,28.0,satisfied +102309,14542,Female,Loyal Customer,18,Business travel,Eco,368,4,4,4,4,4,4,3,4,3,5,3,1,3,4,126,103.0,neutral or dissatisfied +102310,7254,Female,Loyal Customer,45,Personal Travel,Eco,135,2,5,2,1,2,5,5,2,2,2,2,4,2,4,0,1.0,neutral or dissatisfied +102311,82497,Female,Loyal Customer,47,Personal Travel,Eco,488,4,0,4,3,5,4,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +102312,11449,Male,disloyal Customer,18,Business travel,Eco,201,3,2,3,3,5,3,5,5,4,3,4,3,3,5,43,47.0,neutral or dissatisfied +102313,42177,Female,Loyal Customer,31,Business travel,Business,3492,3,3,3,3,3,3,3,3,3,4,5,2,2,3,0,0.0,satisfied +102314,12124,Male,Loyal Customer,13,Personal Travel,Eco,1034,2,5,2,3,1,2,1,1,5,4,5,4,5,1,3,0.0,neutral or dissatisfied +102315,96772,Female,Loyal Customer,46,Business travel,Business,2366,3,3,3,3,3,5,5,3,3,4,3,4,3,5,42,35.0,satisfied +102316,101611,Female,Loyal Customer,44,Business travel,Business,2145,3,3,3,3,4,4,4,4,4,5,4,3,4,3,25,0.0,satisfied +102317,52369,Male,Loyal Customer,55,Personal Travel,Eco,451,4,4,4,3,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +102318,58849,Female,Loyal Customer,17,Personal Travel,Eco,783,4,4,4,4,5,4,5,5,4,3,4,5,4,5,11,0.0,satisfied +102319,86798,Female,Loyal Customer,45,Business travel,Business,3337,2,2,2,2,2,5,5,4,4,5,4,5,4,5,0,10.0,satisfied +102320,89731,Male,Loyal Customer,55,Personal Travel,Eco,1069,3,5,3,3,4,3,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +102321,95810,Female,Loyal Customer,45,Personal Travel,Eco,920,4,4,4,3,3,4,4,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +102322,83557,Male,Loyal Customer,24,Personal Travel,Eco,1865,2,5,2,1,4,2,4,4,5,2,5,3,2,4,0,0.0,neutral or dissatisfied +102323,91416,Female,Loyal Customer,70,Business travel,Eco,650,5,4,1,4,5,2,1,4,4,5,4,5,4,4,0,0.0,satisfied +102324,314,Female,Loyal Customer,59,Business travel,Business,2160,2,2,2,2,2,4,4,4,4,4,4,3,4,5,0,9.0,satisfied +102325,89931,Male,disloyal Customer,18,Business travel,Eco,1416,5,5,5,4,2,5,2,2,4,5,2,4,5,2,0,0.0,satisfied +102326,65315,Male,Loyal Customer,14,Personal Travel,Business,631,2,4,2,3,4,2,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +102327,88481,Male,Loyal Customer,56,Business travel,Business,444,3,3,3,3,4,1,3,5,5,4,5,2,5,5,1,0.0,satisfied +102328,28326,Male,disloyal Customer,40,Business travel,Eco,867,1,1,1,5,4,1,4,4,2,3,4,1,5,4,0,0.0,neutral or dissatisfied +102329,11684,Male,Loyal Customer,8,Personal Travel,Business,429,1,5,1,1,5,1,1,5,2,5,2,5,2,5,0,0.0,neutral or dissatisfied +102330,15823,Male,Loyal Customer,43,Personal Travel,Eco Plus,143,5,4,5,4,3,5,3,3,3,5,3,4,3,3,0,0.0,satisfied +102331,95732,Male,Loyal Customer,55,Business travel,Business,237,2,2,2,2,4,5,4,4,4,4,4,4,4,3,3,1.0,satisfied +102332,68481,Female,Loyal Customer,24,Business travel,Business,3445,2,3,4,3,2,2,2,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +102333,76947,Male,disloyal Customer,31,Business travel,Business,1990,3,3,3,1,5,3,5,5,3,4,4,3,5,5,5,0.0,neutral or dissatisfied +102334,28294,Female,Loyal Customer,48,Business travel,Eco,954,4,4,4,4,5,5,5,4,4,4,4,1,4,1,0,0.0,satisfied +102335,26467,Male,Loyal Customer,34,Personal Travel,Eco,842,3,2,3,2,4,3,4,4,4,1,3,1,2,4,0,0.0,neutral or dissatisfied +102336,36059,Female,Loyal Customer,52,Business travel,Business,2005,1,1,1,1,4,4,1,4,4,4,4,5,4,2,0,0.0,satisfied +102337,24364,Female,Loyal Customer,40,Business travel,Business,3859,4,4,4,4,5,5,4,4,4,4,4,5,4,1,0,0.0,satisfied +102338,56147,Male,Loyal Customer,31,Business travel,Business,1400,3,3,3,3,3,2,3,3,3,2,4,3,5,3,0,0.0,satisfied +102339,15500,Female,Loyal Customer,30,Personal Travel,Eco,433,2,2,2,4,3,2,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +102340,51201,Female,Loyal Customer,35,Business travel,Eco Plus,266,5,5,5,5,5,5,5,5,3,4,4,5,2,5,0,1.0,satisfied +102341,49264,Male,Loyal Customer,53,Business travel,Business,109,5,2,5,5,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +102342,56485,Male,Loyal Customer,32,Business travel,Business,746,2,4,2,2,5,5,5,5,1,4,1,2,2,5,0,0.0,satisfied +102343,23377,Male,Loyal Customer,19,Personal Travel,Eco,1162,3,3,3,3,4,3,2,4,3,2,4,4,4,4,0,44.0,neutral or dissatisfied +102344,39788,Male,Loyal Customer,52,Business travel,Business,3930,2,2,2,2,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +102345,19327,Male,disloyal Customer,15,Business travel,Eco,743,2,2,2,1,5,2,1,5,4,3,5,1,2,5,11,0.0,neutral or dissatisfied +102346,127787,Female,Loyal Customer,60,Personal Travel,Eco,1037,2,5,2,3,2,4,4,3,3,2,4,4,3,5,0,0.0,neutral or dissatisfied +102347,91407,Female,disloyal Customer,20,Business travel,Eco,883,3,3,3,4,1,3,1,1,2,3,3,2,3,1,0,13.0,neutral or dissatisfied +102348,126396,Female,Loyal Customer,39,Personal Travel,Eco,650,1,2,1,4,2,1,5,2,1,5,3,3,4,2,8,0.0,neutral or dissatisfied +102349,21672,Female,disloyal Customer,23,Business travel,Eco,746,2,2,2,2,2,2,2,2,1,1,1,3,3,2,0,0.0,neutral or dissatisfied +102350,36723,Male,Loyal Customer,66,Personal Travel,Eco Plus,1249,1,4,1,2,2,1,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +102351,126817,Male,disloyal Customer,16,Business travel,Eco,723,2,2,2,3,3,2,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +102352,41597,Male,Loyal Customer,52,Personal Travel,Eco,1235,3,3,3,3,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +102353,67728,Female,Loyal Customer,22,Business travel,Business,1710,1,0,0,4,5,0,5,5,1,2,4,2,4,5,125,118.0,neutral or dissatisfied +102354,108427,Female,disloyal Customer,20,Business travel,Eco,886,2,2,2,4,4,2,4,4,4,2,4,4,4,4,5,14.0,neutral or dissatisfied +102355,23695,Female,Loyal Customer,43,Business travel,Eco,251,4,1,1,1,4,2,5,4,4,4,4,5,4,3,0,0.0,satisfied +102356,44576,Female,Loyal Customer,51,Business travel,Business,3884,4,4,4,4,1,1,4,5,5,5,5,5,5,2,0,0.0,satisfied +102357,8876,Female,disloyal Customer,22,Business travel,Eco,622,1,3,1,4,4,1,4,4,2,5,3,4,3,4,5,44.0,neutral or dissatisfied +102358,107263,Male,disloyal Customer,24,Business travel,Eco,307,1,0,1,2,1,1,1,1,3,5,5,3,5,1,18,18.0,neutral or dissatisfied +102359,69895,Male,Loyal Customer,46,Business travel,Business,1671,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +102360,70287,Male,Loyal Customer,53,Business travel,Business,2634,5,5,1,5,4,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +102361,45163,Male,disloyal Customer,16,Business travel,Eco,174,3,2,3,3,4,3,4,4,2,4,4,4,3,4,0,14.0,neutral or dissatisfied +102362,112759,Female,Loyal Customer,40,Business travel,Business,2479,3,4,3,3,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +102363,47431,Male,disloyal Customer,38,Business travel,Eco,188,4,4,5,3,3,5,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +102364,44900,Female,Loyal Customer,44,Personal Travel,Eco,536,2,5,2,2,3,5,4,1,1,2,4,3,1,5,0,0.0,neutral or dissatisfied +102365,119907,Female,Loyal Customer,54,Personal Travel,Eco Plus,936,5,3,5,3,2,3,3,4,4,5,4,3,4,1,0,0.0,satisfied +102366,94162,Male,Loyal Customer,53,Business travel,Business,1548,5,5,5,5,4,4,5,5,5,5,5,5,5,4,18,10.0,satisfied +102367,16714,Male,Loyal Customer,54,Personal Travel,Eco,284,3,5,3,1,1,3,1,1,5,3,2,4,4,1,0,0.0,neutral or dissatisfied +102368,89187,Female,Loyal Customer,20,Personal Travel,Eco,2139,2,5,2,1,3,2,3,3,5,2,4,3,5,3,58,38.0,neutral or dissatisfied +102369,116489,Male,Loyal Customer,17,Personal Travel,Eco,308,1,1,1,2,3,1,3,3,4,4,2,3,1,3,1,0.0,neutral or dissatisfied +102370,129084,Male,Loyal Customer,61,Business travel,Business,2583,4,3,3,3,4,4,4,4,5,3,3,4,3,4,68,68.0,neutral or dissatisfied +102371,54918,Female,disloyal Customer,23,Business travel,Eco,462,3,1,3,2,3,3,3,3,1,2,1,3,1,3,23,24.0,neutral or dissatisfied +102372,87707,Male,Loyal Customer,57,Personal Travel,Eco,606,5,5,5,2,3,5,3,3,5,4,5,5,4,3,4,3.0,satisfied +102373,47166,Female,Loyal Customer,43,Business travel,Business,945,2,2,2,2,3,4,2,4,4,4,4,1,4,1,0,0.0,satisfied +102374,51553,Female,Loyal Customer,45,Business travel,Business,370,2,2,3,2,2,3,5,5,5,5,5,2,5,2,0,0.0,satisfied +102375,14396,Male,Loyal Customer,60,Personal Travel,Eco,789,2,2,2,1,4,2,4,4,2,4,2,1,1,4,0,0.0,neutral or dissatisfied +102376,128278,Female,Loyal Customer,18,Personal Travel,Business,621,1,5,1,3,4,1,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +102377,25143,Male,Loyal Customer,36,Business travel,Eco Plus,1249,4,5,5,5,4,4,4,4,1,3,5,5,2,4,16,0.0,satisfied +102378,75143,Female,Loyal Customer,46,Business travel,Business,1846,5,5,3,5,4,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +102379,53472,Female,Loyal Customer,40,Business travel,Business,2442,3,3,3,3,3,2,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +102380,25279,Female,Loyal Customer,78,Business travel,Eco Plus,425,2,3,3,3,1,3,3,2,2,2,2,5,2,3,0,0.0,satisfied +102381,88229,Male,Loyal Customer,40,Business travel,Business,404,3,3,5,3,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +102382,119497,Male,Loyal Customer,47,Business travel,Business,759,1,4,1,1,5,5,5,4,4,4,4,3,4,3,24,19.0,satisfied +102383,129067,Male,disloyal Customer,27,Business travel,Business,346,0,0,0,4,1,0,1,1,1,3,5,2,4,1,0,4.0,satisfied +102384,71241,Male,Loyal Customer,58,Business travel,Eco,733,3,3,3,3,3,3,3,3,3,1,2,4,2,3,55,,neutral or dissatisfied +102385,59914,Female,Loyal Customer,50,Business travel,Business,937,2,2,2,2,2,5,4,4,4,4,4,4,4,5,22,0.0,satisfied +102386,54136,Female,Loyal Customer,29,Business travel,Business,1400,3,3,3,3,3,4,3,3,5,5,4,2,4,3,13,0.0,satisfied +102387,109599,Female,Loyal Customer,50,Personal Travel,Eco Plus,861,1,5,1,4,5,5,4,2,2,1,2,5,2,5,15,23.0,neutral or dissatisfied +102388,99864,Female,disloyal Customer,24,Business travel,Eco,587,1,0,1,4,1,1,1,1,5,4,4,5,5,1,0,4.0,neutral or dissatisfied +102389,116392,Female,Loyal Customer,54,Personal Travel,Eco,447,4,4,3,1,4,5,4,5,5,3,5,5,5,3,10,0.0,neutral or dissatisfied +102390,20928,Male,Loyal Customer,18,Business travel,Business,2671,2,5,5,5,2,2,2,2,3,3,2,1,2,2,0,0.0,neutral or dissatisfied +102391,115538,Male,Loyal Customer,38,Business travel,Eco,371,3,1,1,1,3,3,3,3,3,2,3,2,3,3,25,13.0,neutral or dissatisfied +102392,26627,Female,Loyal Customer,56,Business travel,Business,3312,4,4,4,4,2,4,2,4,4,4,4,4,4,4,0,0.0,satisfied +102393,53242,Male,Loyal Customer,57,Personal Travel,Eco,612,1,5,1,5,1,1,1,1,2,5,2,3,4,1,36,12.0,neutral or dissatisfied +102394,4882,Male,Loyal Customer,25,Personal Travel,Eco,408,3,2,3,4,1,3,1,1,1,3,3,1,4,1,0,0.0,neutral or dissatisfied +102395,10047,Female,disloyal Customer,38,Business travel,Eco,326,3,2,3,4,1,3,1,1,3,4,3,3,3,1,0,4.0,neutral or dissatisfied +102396,14855,Male,Loyal Customer,24,Business travel,Eco,343,4,4,4,4,4,4,3,4,3,3,5,3,4,4,0,0.0,satisfied +102397,113634,Male,Loyal Customer,68,Personal Travel,Eco,223,3,5,3,3,1,3,1,1,5,5,5,3,4,1,0,0.0,neutral or dissatisfied +102398,89339,Female,Loyal Customer,59,Business travel,Business,1587,3,3,3,3,2,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +102399,29075,Female,Loyal Customer,63,Personal Travel,Eco,954,3,5,3,3,4,1,2,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +102400,99199,Male,Loyal Customer,31,Personal Travel,Business,691,1,4,2,1,4,2,4,4,5,3,5,5,4,4,18,17.0,neutral or dissatisfied +102401,14172,Male,Loyal Customer,15,Business travel,Business,2860,3,3,2,3,5,5,5,5,3,4,2,3,5,5,0,0.0,satisfied +102402,11652,Female,Loyal Customer,46,Business travel,Eco,837,2,3,3,3,4,3,2,2,2,2,2,3,2,2,0,11.0,neutral or dissatisfied +102403,56539,Female,Loyal Customer,23,Business travel,Business,1085,1,1,1,1,5,5,5,5,3,3,5,4,5,5,0,1.0,satisfied +102404,11369,Female,Loyal Customer,17,Personal Travel,Eco,201,1,5,0,3,5,0,2,5,1,1,5,3,5,5,0,0.0,neutral or dissatisfied +102405,15630,Female,Loyal Customer,30,Personal Travel,Eco,228,2,5,2,3,5,2,1,5,3,2,4,4,4,5,39,27.0,neutral or dissatisfied +102406,1348,Female,Loyal Customer,30,Business travel,Business,3578,1,1,1,1,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +102407,8632,Female,disloyal Customer,34,Business travel,Business,280,1,1,1,4,1,1,4,1,3,2,4,3,5,1,22,31.0,neutral or dissatisfied +102408,129740,Male,disloyal Customer,44,Business travel,Eco,337,3,2,3,1,3,3,3,3,4,1,1,1,2,3,0,2.0,neutral or dissatisfied +102409,53770,Male,Loyal Customer,50,Personal Travel,Eco,1195,1,4,1,3,1,1,2,1,4,4,3,4,4,1,17,10.0,neutral or dissatisfied +102410,97847,Female,Loyal Customer,45,Personal Travel,Eco,395,2,4,2,3,3,5,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +102411,64341,Male,Loyal Customer,53,Business travel,Business,2476,2,2,5,5,4,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +102412,1496,Male,Loyal Customer,39,Business travel,Eco,337,1,4,4,4,1,1,1,1,2,1,3,1,4,1,9,1.0,neutral or dissatisfied +102413,82651,Male,Loyal Customer,41,Business travel,Business,2906,1,1,1,1,2,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +102414,60907,Male,Loyal Customer,43,Personal Travel,Eco,589,2,1,2,3,3,2,3,3,4,3,3,3,3,3,8,0.0,neutral or dissatisfied +102415,3139,Male,disloyal Customer,22,Business travel,Business,140,0,0,0,5,2,0,3,2,4,5,4,3,4,2,4,23.0,satisfied +102416,78293,Male,Loyal Customer,44,Business travel,Eco,998,3,2,1,2,3,3,3,4,2,2,1,3,2,3,225,230.0,satisfied +102417,38489,Male,Loyal Customer,11,Personal Travel,Business,2569,2,1,2,3,4,2,4,4,2,4,3,2,4,4,0,0.0,neutral or dissatisfied +102418,11420,Female,Loyal Customer,51,Business travel,Business,1774,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +102419,43561,Male,Loyal Customer,46,Personal Travel,Eco,770,1,4,1,3,3,1,2,3,3,4,4,4,4,3,0,10.0,neutral or dissatisfied +102420,111028,Male,Loyal Customer,42,Business travel,Business,197,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +102421,106801,Female,Loyal Customer,28,Business travel,Business,977,3,3,3,3,3,3,3,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +102422,114354,Female,Loyal Customer,25,Business travel,Business,853,1,1,1,1,3,3,3,3,4,2,5,5,5,3,2,23.0,satisfied +102423,108534,Male,Loyal Customer,33,Personal Travel,Eco,649,3,4,3,3,5,3,5,5,1,3,3,2,3,5,27,8.0,neutral or dissatisfied +102424,128569,Male,disloyal Customer,27,Business travel,Business,110,1,1,1,2,2,1,2,2,5,5,4,4,4,2,0,14.0,neutral or dissatisfied +102425,115366,Male,Loyal Customer,38,Business travel,Business,372,4,2,4,2,1,4,4,4,4,3,4,2,4,1,14,7.0,neutral or dissatisfied +102426,93546,Male,disloyal Customer,11,Business travel,Eco,585,2,4,3,4,1,3,4,1,1,1,4,4,3,1,6,0.0,neutral or dissatisfied +102427,93603,Female,Loyal Customer,48,Business travel,Eco,577,1,2,2,2,2,3,4,1,1,1,1,1,1,1,0,28.0,neutral or dissatisfied +102428,84861,Male,Loyal Customer,35,Business travel,Business,2863,5,2,5,5,4,4,1,5,5,4,5,5,5,3,0,0.0,satisfied +102429,92422,Female,Loyal Customer,48,Business travel,Business,2092,5,5,5,5,5,3,4,4,4,4,4,5,4,5,7,0.0,satisfied +102430,113073,Female,Loyal Customer,44,Business travel,Business,2935,5,5,3,5,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +102431,118292,Male,Loyal Customer,57,Business travel,Business,2020,5,5,5,5,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +102432,89871,Male,disloyal Customer,29,Business travel,Eco,1501,3,3,3,4,2,3,1,2,1,2,3,4,3,2,7,12.0,neutral or dissatisfied +102433,26543,Female,Loyal Customer,39,Personal Travel,Eco,990,1,4,1,4,2,1,2,2,4,2,4,4,4,2,3,15.0,neutral or dissatisfied +102434,34447,Female,Loyal Customer,40,Business travel,Business,228,1,1,5,1,5,1,3,4,4,4,4,3,4,3,0,0.0,satisfied +102435,50252,Male,disloyal Customer,36,Business travel,Eco,262,1,4,1,3,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +102436,63161,Female,Loyal Customer,56,Business travel,Business,337,0,1,1,1,5,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +102437,90621,Male,disloyal Customer,24,Business travel,Eco,404,1,2,1,4,5,1,4,5,3,1,3,3,4,5,0,26.0,neutral or dissatisfied +102438,59841,Male,Loyal Customer,44,Business travel,Business,1085,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +102439,45470,Female,disloyal Customer,16,Business travel,Eco,522,4,0,4,4,3,4,3,3,1,2,5,3,4,3,0,0.0,satisfied +102440,60039,Male,Loyal Customer,52,Business travel,Business,2109,4,4,4,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +102441,75653,Male,Loyal Customer,57,Business travel,Business,2815,0,0,0,4,3,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +102442,38754,Male,Loyal Customer,36,Business travel,Eco,354,4,4,4,4,4,4,4,4,2,1,1,2,5,4,0,0.0,satisfied +102443,14839,Female,Loyal Customer,45,Personal Travel,Eco,261,3,3,3,3,2,3,4,1,1,3,1,1,1,1,4,0.0,neutral or dissatisfied +102444,44691,Female,disloyal Customer,55,Business travel,Eco,67,1,1,0,4,2,0,2,2,1,1,4,2,4,2,37,28.0,neutral or dissatisfied +102445,87392,Male,Loyal Customer,37,Business travel,Eco,425,2,3,5,3,2,2,2,2,3,2,2,1,2,2,0,0.0,neutral or dissatisfied +102446,47137,Male,Loyal Customer,50,Business travel,Business,945,5,5,5,5,2,4,3,5,5,5,5,1,5,2,0,0.0,satisfied +102447,72553,Female,Loyal Customer,38,Business travel,Business,2434,4,4,4,4,5,3,3,4,4,3,4,2,4,1,0,0.0,neutral or dissatisfied +102448,57409,Female,Loyal Customer,39,Business travel,Business,455,4,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +102449,14308,Male,Loyal Customer,23,Business travel,Eco,429,2,4,4,4,2,2,1,2,4,4,2,2,2,2,0,4.0,neutral or dissatisfied +102450,74664,Male,Loyal Customer,50,Personal Travel,Eco,1242,4,2,4,4,4,4,4,2,3,2,4,4,4,4,139,123.0,neutral or dissatisfied +102451,128958,Female,Loyal Customer,49,Business travel,Business,236,1,4,4,4,3,1,1,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +102452,32665,Male,Loyal Customer,59,Business travel,Eco,101,5,3,5,3,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +102453,123714,Male,Loyal Customer,51,Personal Travel,Eco,214,3,4,3,3,1,3,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +102454,10307,Female,disloyal Customer,33,Business travel,Business,216,1,1,1,1,2,1,2,2,5,2,5,4,4,2,10,0.0,neutral or dissatisfied +102455,85132,Male,Loyal Customer,46,Business travel,Business,3860,3,3,3,3,3,5,4,4,4,4,4,5,4,3,23,12.0,satisfied +102456,12716,Female,disloyal Customer,28,Business travel,Eco,803,3,4,4,4,1,4,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +102457,74518,Male,Loyal Customer,58,Business travel,Business,3003,3,3,4,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +102458,28527,Female,Loyal Customer,25,Business travel,Business,2688,1,1,1,1,1,1,1,1,1,1,4,2,4,1,0,0.0,neutral or dissatisfied +102459,116650,Female,Loyal Customer,47,Business travel,Eco Plus,296,2,4,4,4,3,3,4,2,2,2,2,2,2,2,25,21.0,neutral or dissatisfied +102460,52510,Male,Loyal Customer,57,Business travel,Business,160,3,3,3,3,3,1,5,4,4,4,5,3,4,1,2,0.0,satisfied +102461,23250,Male,Loyal Customer,44,Business travel,Business,783,5,4,5,5,2,5,2,5,5,5,5,3,5,5,0,0.0,satisfied +102462,52601,Female,disloyal Customer,21,Business travel,Eco,119,3,2,3,3,5,3,1,5,3,1,3,2,4,5,0,6.0,neutral or dissatisfied +102463,37924,Male,Loyal Customer,38,Personal Travel,Eco,1023,3,2,3,3,3,3,3,3,2,1,2,2,3,3,27,45.0,neutral or dissatisfied +102464,116135,Male,Loyal Customer,24,Personal Travel,Eco,325,1,4,1,3,4,1,4,4,1,4,3,2,1,4,0,0.0,neutral or dissatisfied +102465,71828,Female,disloyal Customer,13,Business travel,Eco,1479,4,3,3,3,1,4,1,1,2,5,2,3,3,1,0,0.0,neutral or dissatisfied +102466,63570,Female,Loyal Customer,41,Business travel,Eco,1737,3,4,4,4,3,3,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +102467,68199,Female,Loyal Customer,29,Business travel,Business,1684,3,3,2,3,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +102468,2185,Female,Loyal Customer,60,Business travel,Eco,624,1,4,4,4,4,3,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +102469,87690,Male,Loyal Customer,66,Personal Travel,Eco,606,4,5,4,3,4,4,4,4,4,2,5,5,5,4,90,76.0,neutral or dissatisfied +102470,98221,Female,Loyal Customer,25,Business travel,Business,842,5,5,5,5,4,4,4,5,5,5,4,4,3,4,140,129.0,satisfied +102471,95006,Male,Loyal Customer,57,Personal Travel,Eco,239,4,4,4,3,4,4,4,4,4,5,1,4,1,4,3,0.0,satisfied +102472,1188,Male,Loyal Customer,34,Personal Travel,Eco,113,1,1,1,3,5,1,5,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +102473,94852,Female,Loyal Customer,28,Business travel,Eco,677,2,3,3,3,2,2,2,2,4,1,3,3,3,2,94,92.0,neutral or dissatisfied +102474,11850,Female,Loyal Customer,53,Business travel,Business,3917,2,2,2,2,2,5,4,4,4,4,4,5,4,4,30,35.0,satisfied +102475,4890,Male,Loyal Customer,34,Business travel,Eco Plus,408,4,4,4,4,4,4,4,4,1,1,4,1,4,4,0,0.0,neutral or dissatisfied +102476,35155,Male,Loyal Customer,26,Business travel,Business,1005,5,5,5,5,5,5,5,5,1,1,3,5,1,5,14,0.0,satisfied +102477,25881,Female,disloyal Customer,34,Business travel,Eco,907,4,4,4,3,2,4,2,2,4,5,3,3,2,2,23,21.0,neutral or dissatisfied +102478,3074,Male,Loyal Customer,54,Business travel,Business,413,2,2,2,2,3,4,4,5,5,5,5,4,5,4,54,95.0,satisfied +102479,8243,Male,disloyal Customer,33,Personal Travel,Eco,335,3,4,3,4,4,3,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +102480,76593,Female,Loyal Customer,47,Business travel,Eco,481,1,3,3,3,5,4,4,1,1,1,1,3,1,1,0,38.0,neutral or dissatisfied +102481,65398,Male,Loyal Customer,62,Personal Travel,Eco,631,3,5,3,1,2,3,4,2,3,2,2,4,2,2,0,0.0,neutral or dissatisfied +102482,106694,Female,disloyal Customer,51,Business travel,Business,516,4,4,4,4,5,4,5,5,5,4,4,4,5,5,0,0.0,satisfied +102483,126413,Female,Loyal Customer,53,Business travel,Business,631,1,1,3,1,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +102484,38574,Male,Loyal Customer,47,Personal Travel,Eco,2475,3,3,3,1,3,3,3,3,1,2,1,2,2,3,2,15.0,neutral or dissatisfied +102485,16980,Male,Loyal Customer,44,Personal Travel,Eco Plus,209,2,3,0,2,4,0,4,4,2,2,2,2,3,4,0,0.0,neutral or dissatisfied +102486,102447,Female,Loyal Customer,56,Personal Travel,Eco,236,1,4,0,3,1,4,1,5,5,0,5,2,5,4,20,12.0,neutral or dissatisfied +102487,129023,Male,Loyal Customer,52,Personal Travel,Eco,2611,3,4,2,4,2,5,5,2,2,4,3,5,1,5,0,0.0,neutral or dissatisfied +102488,41734,Female,disloyal Customer,33,Business travel,Eco,695,2,2,2,3,5,2,5,5,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +102489,72734,Male,Loyal Customer,28,Personal Travel,Eco Plus,1119,3,5,3,3,4,3,4,4,4,5,2,3,4,4,0,0.0,neutral or dissatisfied +102490,87721,Male,Loyal Customer,28,Business travel,Eco Plus,606,2,4,4,4,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +102491,10639,Male,Loyal Customer,43,Business travel,Business,247,2,2,2,2,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +102492,27451,Male,Loyal Customer,31,Business travel,Business,937,3,1,1,1,3,3,3,3,2,4,4,4,4,3,22,16.0,neutral or dissatisfied +102493,15491,Male,Loyal Customer,39,Personal Travel,Eco,306,2,4,2,2,1,2,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +102494,121424,Male,Loyal Customer,37,Business travel,Business,3461,2,5,5,5,4,4,3,2,2,2,2,2,2,4,68,61.0,neutral or dissatisfied +102495,93710,Male,Loyal Customer,52,Personal Travel,Eco,689,2,4,2,3,3,2,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +102496,28642,Male,Loyal Customer,26,Business travel,Business,2466,4,4,4,4,3,4,3,3,1,4,4,4,2,3,0,0.0,satisfied +102497,109468,Female,Loyal Customer,31,Business travel,Business,3411,3,3,3,3,4,4,4,3,4,5,4,4,3,4,272,267.0,satisfied +102498,112428,Male,disloyal Customer,27,Business travel,Eco,846,2,2,2,2,1,2,2,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +102499,45413,Male,disloyal Customer,69,Business travel,Eco,458,4,0,4,4,4,4,1,4,3,2,5,5,1,4,43,57.0,satisfied +102500,46223,Male,disloyal Customer,19,Business travel,Eco,752,4,4,4,3,3,4,3,3,4,2,2,4,4,3,3,73.0,neutral or dissatisfied +102501,118975,Female,Loyal Customer,50,Personal Travel,Eco,570,1,5,1,3,4,4,5,2,2,1,2,4,2,3,2,0.0,neutral or dissatisfied +102502,43159,Male,Loyal Customer,64,Business travel,Eco Plus,968,4,5,5,5,4,4,4,4,5,1,3,2,1,4,7,16.0,satisfied +102503,88872,Male,Loyal Customer,20,Business travel,Business,859,3,3,3,3,5,5,5,5,3,5,5,4,5,5,5,1.0,satisfied +102504,84823,Female,Loyal Customer,44,Business travel,Business,3003,2,1,1,1,2,3,3,2,2,2,2,1,2,4,12,10.0,neutral or dissatisfied +102505,123871,Female,Loyal Customer,59,Business travel,Business,544,2,2,2,2,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +102506,69766,Male,Loyal Customer,38,Business travel,Business,3944,4,4,4,4,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +102507,45756,Female,disloyal Customer,58,Business travel,Eco,411,3,0,3,2,1,3,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +102508,44213,Female,Loyal Customer,16,Personal Travel,Business,224,4,3,4,4,3,4,3,3,1,1,4,3,4,3,0,0.0,neutral or dissatisfied +102509,66043,Female,Loyal Customer,52,Business travel,Business,2183,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0,2.0,satisfied +102510,107013,Female,Loyal Customer,60,Business travel,Business,2783,5,5,4,5,2,4,5,4,4,4,4,3,4,3,18,0.0,satisfied +102511,104339,Female,Loyal Customer,7,Personal Travel,Eco,528,4,4,4,4,5,4,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +102512,5966,Male,disloyal Customer,30,Business travel,Business,925,4,5,5,2,3,5,3,3,3,4,5,5,5,3,76,83.0,satisfied +102513,64019,Female,Loyal Customer,25,Business travel,Business,2199,5,5,5,5,2,2,2,2,4,5,4,3,4,2,0,0.0,satisfied +102514,128109,Female,Loyal Customer,31,Business travel,Business,1587,1,1,1,1,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +102515,60182,Female,Loyal Customer,59,Personal Travel,Eco,1120,2,4,2,2,2,4,5,4,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +102516,32296,Female,Loyal Customer,43,Business travel,Eco,84,4,5,5,5,5,5,3,4,4,4,4,3,4,5,0,3.0,satisfied +102517,3324,Male,Loyal Customer,58,Business travel,Business,1834,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +102518,36635,Female,Loyal Customer,43,Business travel,Business,2529,2,4,5,5,4,1,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +102519,95310,Female,Loyal Customer,56,Personal Travel,Eco,319,3,5,5,3,5,5,4,1,1,5,1,5,1,1,11,6.0,neutral or dissatisfied +102520,102465,Female,Loyal Customer,63,Personal Travel,Eco,258,2,4,2,3,3,2,3,4,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +102521,51346,Female,disloyal Customer,34,Business travel,Eco Plus,304,4,4,4,4,3,4,3,3,5,5,3,5,2,3,26,45.0,neutral or dissatisfied +102522,27627,Male,Loyal Customer,36,Business travel,Eco Plus,1050,4,2,2,2,4,4,4,4,3,4,4,3,5,4,5,7.0,satisfied +102523,905,Female,disloyal Customer,39,Business travel,Business,354,3,3,3,3,1,3,1,1,2,3,4,1,4,1,33,27.0,neutral or dissatisfied +102524,43337,Male,Loyal Customer,36,Business travel,Eco,387,3,5,2,5,3,3,3,3,1,1,1,2,1,3,0,1.0,neutral or dissatisfied +102525,72142,Female,Loyal Customer,27,Personal Travel,Eco,731,1,3,0,3,3,0,4,3,1,3,3,1,4,3,1,0.0,neutral or dissatisfied +102526,53789,Female,Loyal Customer,42,Business travel,Business,3330,0,3,0,1,3,2,1,2,2,2,2,3,2,5,9,2.0,satisfied +102527,43368,Male,Loyal Customer,65,Personal Travel,Eco,358,4,4,4,4,4,4,4,4,5,2,5,4,5,4,0,0.0,satisfied +102528,69010,Female,Loyal Customer,48,Business travel,Business,1391,1,1,1,1,3,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +102529,36957,Male,Loyal Customer,44,Business travel,Business,899,5,5,5,5,4,4,4,4,5,4,2,4,1,4,188,203.0,satisfied +102530,105642,Male,disloyal Customer,18,Business travel,Eco,925,4,4,4,3,2,4,2,2,4,5,5,4,5,2,103,98.0,neutral or dissatisfied +102531,103407,Male,Loyal Customer,45,Business travel,Business,3829,4,1,3,1,1,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +102532,93364,Male,Loyal Customer,25,Personal Travel,Eco,836,4,2,4,4,5,4,3,5,3,1,4,2,4,5,58,24.0,neutral or dissatisfied +102533,104506,Female,Loyal Customer,19,Business travel,Business,1609,4,4,4,4,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +102534,99721,Female,Loyal Customer,67,Personal Travel,Business,255,3,0,3,3,2,3,2,5,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +102535,5257,Male,Loyal Customer,48,Business travel,Business,383,2,4,1,4,2,4,4,2,2,2,2,4,2,4,0,17.0,neutral or dissatisfied +102536,117863,Female,Loyal Customer,47,Business travel,Business,365,1,5,2,2,5,2,1,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +102537,45751,Female,Loyal Customer,39,Business travel,Business,3282,2,1,1,1,5,4,3,2,2,2,2,4,2,4,0,4.0,neutral or dissatisfied +102538,123115,Female,disloyal Customer,18,Business travel,Eco,631,1,2,1,3,5,1,3,5,2,2,3,1,3,5,0,7.0,neutral or dissatisfied +102539,62958,Female,Loyal Customer,29,Business travel,Business,1577,1,1,1,1,3,4,3,3,4,5,5,4,4,3,0,0.0,satisfied +102540,44766,Female,Loyal Customer,45,Business travel,Business,3281,2,2,2,2,3,5,3,5,5,5,5,1,5,2,84,80.0,satisfied +102541,120096,Male,Loyal Customer,70,Personal Travel,Business,1576,3,2,3,3,2,4,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +102542,91049,Female,Loyal Customer,28,Personal Travel,Eco,545,3,2,4,3,1,4,3,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +102543,106765,Male,Loyal Customer,37,Personal Travel,Eco,945,2,2,1,2,2,1,2,2,1,5,3,3,2,2,0,0.0,neutral or dissatisfied +102544,21383,Female,Loyal Customer,49,Business travel,Business,433,2,2,2,2,3,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +102545,79775,Female,Loyal Customer,29,Business travel,Business,1035,4,4,4,4,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +102546,25413,Male,Loyal Customer,59,Personal Travel,Eco,990,1,4,1,2,5,1,5,5,3,3,5,3,5,5,11,3.0,neutral or dissatisfied +102547,94540,Female,Loyal Customer,55,Business travel,Business,2155,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,1.0,satisfied +102548,125503,Male,Loyal Customer,31,Business travel,Business,666,1,0,0,4,3,0,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +102549,28664,Female,Loyal Customer,48,Personal Travel,Eco,2541,3,5,3,2,3,5,4,4,4,3,4,5,4,3,41,9.0,neutral or dissatisfied +102550,74836,Male,disloyal Customer,29,Business travel,Eco,1797,3,3,3,4,3,3,3,3,2,5,3,3,4,3,0,2.0,neutral or dissatisfied +102551,1273,Male,Loyal Customer,11,Personal Travel,Eco,229,1,5,1,4,2,1,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +102552,27684,Female,disloyal Customer,29,Business travel,Eco,1107,2,1,1,1,5,1,3,5,4,1,5,5,3,5,0,,neutral or dissatisfied +102553,70806,Male,Loyal Customer,50,Business travel,Business,624,3,3,3,3,5,4,4,4,4,4,4,4,4,5,0,7.0,satisfied +102554,61734,Male,disloyal Customer,38,Business travel,Eco,979,3,3,3,3,3,1,1,2,4,4,4,1,1,1,158,147.0,neutral or dissatisfied +102555,55533,Female,Loyal Customer,49,Business travel,Business,3852,2,2,2,2,4,4,4,5,5,5,5,4,5,4,30,9.0,satisfied +102556,68928,Male,Loyal Customer,49,Business travel,Business,646,4,3,4,4,5,5,5,3,2,5,5,5,4,5,216,235.0,satisfied +102557,39193,Female,Loyal Customer,54,Business travel,Eco,318,4,2,2,2,1,4,5,4,4,4,4,1,4,1,0,0.0,satisfied +102558,24346,Female,Loyal Customer,14,Personal Travel,Eco,634,4,5,4,1,4,4,4,4,4,5,5,3,4,4,15,17.0,neutral or dissatisfied +102559,92233,Female,Loyal Customer,72,Business travel,Eco Plus,1979,1,1,1,1,2,3,3,1,1,1,1,1,1,3,4,0.0,neutral or dissatisfied +102560,86684,Male,Loyal Customer,50,Personal Travel,Business,1747,3,4,3,4,4,4,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +102561,100470,Female,Loyal Customer,42,Business travel,Business,2603,4,4,4,4,4,4,5,5,5,5,5,3,5,4,84,80.0,satisfied +102562,60733,Male,Loyal Customer,55,Personal Travel,Eco,1605,2,4,2,4,3,2,2,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +102563,101881,Male,Loyal Customer,23,Business travel,Business,1747,2,2,2,2,5,5,5,5,5,2,5,5,5,5,16,8.0,satisfied +102564,9149,Male,Loyal Customer,45,Business travel,Business,227,5,5,5,5,2,4,1,5,5,5,5,1,5,2,0,0.0,satisfied +102565,102866,Female,Loyal Customer,50,Business travel,Business,3737,2,2,2,2,5,4,4,2,2,2,2,3,2,5,35,25.0,satisfied +102566,5887,Female,Loyal Customer,54,Business travel,Eco,108,4,3,4,4,3,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +102567,55592,Male,disloyal Customer,38,Business travel,Business,419,2,2,2,2,3,2,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +102568,35744,Female,Loyal Customer,50,Personal Travel,Eco,2153,5,5,5,3,5,5,5,4,2,3,4,5,4,5,113,133.0,satisfied +102569,60339,Female,Loyal Customer,62,Business travel,Business,1024,4,1,1,1,1,4,3,4,4,3,4,3,4,2,29,35.0,neutral or dissatisfied +102570,126482,Male,Loyal Customer,57,Business travel,Eco,1849,3,3,3,3,3,3,3,3,2,4,3,3,4,3,0,0.0,neutral or dissatisfied +102571,6783,Female,Loyal Customer,45,Business travel,Business,3810,1,1,1,1,4,5,4,4,4,4,4,3,4,3,70,111.0,satisfied +102572,107653,Female,Loyal Customer,37,Personal Travel,Business,251,2,5,2,3,2,4,5,3,3,2,3,4,3,3,7,8.0,neutral or dissatisfied +102573,112599,Female,Loyal Customer,34,Business travel,Business,602,2,5,5,5,1,2,3,2,2,2,2,3,2,4,3,0.0,neutral or dissatisfied +102574,120938,Male,Loyal Customer,24,Business travel,Business,920,4,4,4,4,5,4,5,5,5,3,5,3,5,5,0,0.0,satisfied +102575,62530,Male,Loyal Customer,39,Business travel,Business,1744,1,1,1,1,3,4,4,5,5,5,5,4,5,3,0,12.0,satisfied +102576,99462,Male,Loyal Customer,49,Business travel,Business,2266,2,2,2,2,5,5,5,5,5,5,5,5,5,3,19,19.0,satisfied +102577,103473,Female,Loyal Customer,13,Personal Travel,Business,382,1,4,1,2,2,1,2,2,3,4,5,5,5,2,1,14.0,neutral or dissatisfied +102578,80496,Female,Loyal Customer,54,Business travel,Business,1749,1,1,1,1,5,3,5,4,4,4,4,5,4,3,0,3.0,satisfied +102579,77137,Female,Loyal Customer,33,Business travel,Business,2105,3,3,3,3,2,2,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +102580,81297,Male,Loyal Customer,23,Business travel,Business,3675,3,3,2,3,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +102581,103903,Female,Loyal Customer,34,Personal Travel,Eco Plus,869,5,4,5,3,5,5,5,5,2,2,4,1,3,5,0,0.0,satisfied +102582,71787,Male,Loyal Customer,39,Business travel,Business,1723,5,5,5,5,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +102583,120015,Female,Loyal Customer,55,Personal Travel,Eco,328,3,0,3,4,2,5,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +102584,66826,Male,Loyal Customer,60,Business travel,Business,731,5,5,5,5,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +102585,108796,Female,Loyal Customer,27,Personal Travel,Eco,581,2,5,2,2,1,2,1,1,3,2,4,5,4,1,5,10.0,neutral or dissatisfied +102586,10187,Female,Loyal Customer,25,Business travel,Business,140,3,3,3,3,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +102587,52100,Male,Loyal Customer,10,Personal Travel,Eco,639,1,5,2,1,2,2,1,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +102588,18141,Male,Loyal Customer,25,Personal Travel,Eco,750,1,4,2,4,3,2,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +102589,44561,Female,Loyal Customer,9,Personal Travel,Eco Plus,157,2,4,0,3,3,0,2,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +102590,74286,Male,disloyal Customer,29,Business travel,Business,1130,5,5,5,2,4,5,4,4,4,3,5,3,5,4,0,0.0,satisfied +102591,93161,Female,Loyal Customer,32,Personal Travel,Eco,1066,3,5,3,3,3,3,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +102592,124666,Male,disloyal Customer,22,Business travel,Eco,399,3,0,3,1,5,3,3,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +102593,78049,Male,Loyal Customer,40,Personal Travel,Eco,214,2,4,0,5,5,0,5,5,5,4,4,4,4,5,27,40.0,neutral or dissatisfied +102594,95263,Female,Loyal Customer,17,Personal Travel,Eco,248,3,4,3,2,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +102595,109958,Male,Loyal Customer,66,Personal Travel,Eco,1073,4,4,4,2,3,4,2,3,5,5,4,3,5,3,43,11.0,satisfied +102596,81294,Female,Loyal Customer,33,Personal Travel,Eco,1020,4,4,4,3,1,4,4,1,5,4,1,3,3,1,56,43.0,neutral or dissatisfied +102597,90368,Male,disloyal Customer,22,Business travel,Business,545,4,1,4,2,1,4,1,1,5,2,5,3,4,1,0,0.0,satisfied +102598,35807,Male,Loyal Customer,19,Personal Travel,Business,1065,1,1,1,2,1,1,1,1,2,3,1,3,2,1,20,16.0,neutral or dissatisfied +102599,109967,Female,Loyal Customer,41,Personal Travel,Eco,1079,2,5,3,5,3,3,3,3,4,4,5,5,2,3,11,7.0,neutral or dissatisfied +102600,75199,Male,disloyal Customer,34,Business travel,Business,1744,3,3,3,2,2,3,2,2,5,4,5,5,5,2,12,0.0,neutral or dissatisfied +102601,95576,Male,Loyal Customer,57,Business travel,Business,2050,4,4,4,4,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +102602,13762,Female,Loyal Customer,51,Business travel,Eco Plus,401,5,2,2,2,5,5,5,2,2,5,2,5,3,5,296,276.0,satisfied +102603,93653,Female,Loyal Customer,66,Business travel,Eco Plus,547,2,4,4,4,1,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +102604,30229,Male,Loyal Customer,22,Business travel,Business,896,3,1,3,3,3,3,3,3,4,3,3,1,2,3,0,6.0,satisfied +102605,118514,Male,Loyal Customer,50,Business travel,Business,1690,0,0,0,3,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +102606,67171,Male,Loyal Customer,17,Personal Travel,Eco,964,5,5,5,4,3,5,3,3,5,3,5,5,4,3,6,0.0,satisfied +102607,94955,Female,Loyal Customer,48,Business travel,Eco,187,4,2,3,2,1,1,1,5,5,4,5,4,5,4,1,5.0,satisfied +102608,1068,Female,Loyal Customer,24,Personal Travel,Eco,354,2,1,2,4,1,2,1,1,3,3,3,1,3,1,15,19.0,neutral or dissatisfied +102609,66787,Female,Loyal Customer,64,Personal Travel,Eco,3711,3,3,3,1,3,1,1,2,2,2,2,1,5,1,358,369.0,neutral or dissatisfied +102610,98736,Female,Loyal Customer,58,Business travel,Business,1558,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +102611,113251,Female,Loyal Customer,55,Personal Travel,Business,488,5,0,5,4,5,2,1,5,5,5,5,5,5,2,0,0.0,satisfied +102612,70560,Male,Loyal Customer,61,Business travel,Business,1258,3,1,1,1,4,3,4,3,3,3,3,1,3,3,17,0.0,neutral or dissatisfied +102613,11522,Female,Loyal Customer,42,Personal Travel,Eco Plus,308,3,2,3,4,3,4,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +102614,47851,Male,disloyal Customer,24,Business travel,Eco,329,1,5,1,5,3,1,3,3,5,2,2,5,1,3,15,0.0,neutral or dissatisfied +102615,11626,Female,Loyal Customer,48,Business travel,Business,1792,3,3,3,3,5,5,4,4,4,4,4,3,4,4,6,0.0,satisfied +102616,113335,Male,Loyal Customer,40,Business travel,Business,236,4,4,3,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +102617,43601,Male,disloyal Customer,32,Business travel,Eco,190,2,3,3,4,3,3,3,3,4,3,3,2,2,3,0,0.0,neutral or dissatisfied +102618,117173,Male,Loyal Customer,46,Personal Travel,Eco,304,2,5,5,1,3,5,3,3,4,5,5,5,4,3,0,5.0,neutral or dissatisfied +102619,79887,Female,Loyal Customer,42,Business travel,Business,3820,4,5,5,5,5,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +102620,3137,Female,Loyal Customer,39,Business travel,Business,3475,1,1,1,1,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +102621,77389,Male,Loyal Customer,52,Business travel,Business,190,3,2,2,2,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +102622,82892,Female,Loyal Customer,15,Personal Travel,Eco,594,2,1,2,2,4,2,4,4,2,1,2,1,3,4,5,32.0,neutral or dissatisfied +102623,40584,Female,Loyal Customer,58,Business travel,Eco,391,2,3,3,3,4,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +102624,103353,Female,Loyal Customer,32,Business travel,Business,342,3,3,2,3,4,4,4,4,4,2,5,3,4,4,1,0.0,satisfied +102625,124844,Female,Loyal Customer,38,Personal Travel,Eco,280,3,4,3,3,3,3,3,3,3,3,5,5,4,3,7,0.0,neutral or dissatisfied +102626,93085,Female,Loyal Customer,24,Business travel,Business,860,4,4,4,4,5,5,5,5,4,3,5,4,5,5,1,0.0,satisfied +102627,23443,Female,Loyal Customer,49,Business travel,Eco,488,5,1,1,1,4,1,2,5,5,5,5,4,5,2,0,38.0,satisfied +102628,65584,Female,disloyal Customer,32,Business travel,Eco,237,3,1,3,4,2,3,2,2,3,4,3,4,4,2,10,12.0,neutral or dissatisfied +102629,125303,Female,Loyal Customer,65,Business travel,Eco,278,2,1,1,1,2,2,1,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +102630,48456,Male,Loyal Customer,22,Business travel,Business,3003,5,5,5,5,4,4,4,4,4,5,4,5,1,4,0,0.0,satisfied +102631,62141,Female,Loyal Customer,11,Business travel,Business,2565,2,1,4,1,2,2,2,2,2,5,3,4,3,2,51,25.0,neutral or dissatisfied +102632,96869,Male,Loyal Customer,58,Business travel,Business,3117,2,2,2,2,5,1,2,4,4,4,4,2,4,1,4,9.0,satisfied +102633,59044,Female,Loyal Customer,61,Business travel,Business,1744,1,1,1,1,4,3,2,1,1,2,1,4,1,1,27,3.0,neutral or dissatisfied +102634,75847,Male,Loyal Customer,39,Business travel,Eco,1037,5,5,5,5,5,5,5,5,4,3,4,4,1,5,0,0.0,satisfied +102635,76849,Male,Loyal Customer,45,Business travel,Business,1195,3,3,3,3,2,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +102636,43670,Female,disloyal Customer,54,Business travel,Eco,295,2,0,2,4,1,2,1,1,5,2,3,2,3,1,0,0.0,neutral or dissatisfied +102637,129637,Male,Loyal Customer,59,Business travel,Business,447,2,2,2,2,5,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +102638,57361,Male,Loyal Customer,48,Personal Travel,Eco,236,3,4,3,1,3,3,2,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +102639,42432,Male,Loyal Customer,32,Business travel,Business,3092,1,4,4,4,1,2,1,1,3,5,2,4,2,1,0,0.0,neutral or dissatisfied +102640,40271,Female,Loyal Customer,52,Personal Travel,Eco,387,3,4,3,3,5,5,5,5,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +102641,71903,Male,Loyal Customer,10,Personal Travel,Eco,1726,3,4,2,3,2,2,2,2,1,4,3,4,5,2,3,9.0,neutral or dissatisfied +102642,2331,Female,Loyal Customer,22,Personal Travel,Eco,672,2,4,2,4,2,2,2,2,2,2,4,3,3,2,0,1.0,neutral or dissatisfied +102643,32044,Male,disloyal Customer,22,Business travel,Eco,102,0,3,0,3,4,0,4,4,5,4,4,5,3,4,0,0.0,satisfied +102644,83158,Male,disloyal Customer,24,Business travel,Business,957,4,4,4,4,4,4,1,4,3,2,4,4,4,4,14,15.0,satisfied +102645,27464,Female,disloyal Customer,49,Business travel,Eco,697,2,2,2,2,4,2,4,4,3,5,3,1,3,4,0,4.0,neutral or dissatisfied +102646,125820,Male,Loyal Customer,44,Business travel,Business,742,4,4,4,4,5,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +102647,4513,Male,Loyal Customer,17,Personal Travel,Eco,435,1,3,1,3,5,1,1,5,2,1,4,2,3,5,0,0.0,neutral or dissatisfied +102648,113919,Male,Loyal Customer,41,Business travel,Eco,170,5,5,2,5,5,5,5,5,1,1,2,1,3,5,0,0.0,satisfied +102649,100156,Male,disloyal Customer,34,Business travel,Business,725,3,3,3,1,2,3,4,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +102650,40757,Male,Loyal Customer,25,Business travel,Business,2195,2,2,2,2,3,3,3,3,2,5,5,3,5,3,0,0.0,satisfied +102651,72830,Female,Loyal Customer,36,Business travel,Eco,1013,4,1,1,1,4,4,4,4,3,3,2,1,3,4,5,0.0,neutral or dissatisfied +102652,126287,Male,Loyal Customer,45,Personal Travel,Eco,590,4,5,3,3,5,3,5,5,5,4,5,4,5,5,23,17.0,neutral or dissatisfied +102653,75287,Male,disloyal Customer,26,Business travel,Business,1744,4,4,4,2,1,4,1,1,3,4,3,4,5,1,0,0.0,neutral or dissatisfied +102654,122367,Female,Loyal Customer,48,Business travel,Business,529,3,2,2,2,1,3,3,3,3,3,3,2,3,4,7,0.0,neutral or dissatisfied +102655,91532,Female,Loyal Customer,44,Business travel,Business,3251,4,4,4,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +102656,2729,Female,disloyal Customer,32,Business travel,Business,772,4,4,4,3,5,4,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +102657,95616,Female,disloyal Customer,36,Business travel,Eco,422,2,5,2,4,3,2,3,3,1,4,3,2,5,3,8,7.0,neutral or dissatisfied +102658,61641,Male,disloyal Customer,17,Business travel,Eco,1235,2,2,2,3,4,2,4,4,5,5,5,5,5,4,0,0.0,satisfied +102659,5019,Male,Loyal Customer,45,Business travel,Business,2910,5,5,5,5,5,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +102660,80782,Male,Loyal Customer,21,Business travel,Business,2321,2,5,5,5,2,3,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +102661,120975,Male,disloyal Customer,28,Business travel,Eco,992,3,3,3,3,4,3,4,4,4,4,4,3,3,4,2,0.0,neutral or dissatisfied +102662,17944,Male,Loyal Customer,7,Personal Travel,Eco,95,3,4,3,3,5,3,3,5,3,1,2,3,5,5,0,4.0,neutral or dissatisfied +102663,106093,Male,Loyal Customer,48,Business travel,Business,302,2,2,2,2,4,4,4,4,4,4,4,4,4,5,27,19.0,satisfied +102664,128009,Female,Loyal Customer,66,Personal Travel,Eco,1488,3,2,3,3,3,3,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +102665,113481,Male,Loyal Customer,68,Business travel,Business,2171,2,2,2,2,4,5,5,4,4,4,4,3,4,4,9,8.0,satisfied +102666,59465,Female,Loyal Customer,34,Business travel,Business,2559,3,3,3,3,3,4,5,4,4,4,4,5,4,5,12,0.0,satisfied +102667,50595,Female,Loyal Customer,18,Personal Travel,Eco,262,4,3,4,4,1,4,2,1,2,2,2,4,1,1,0,0.0,neutral or dissatisfied +102668,84050,Female,Loyal Customer,27,Business travel,Business,2871,5,5,5,5,5,5,5,5,3,3,5,3,4,5,0,9.0,satisfied +102669,47522,Male,Loyal Customer,39,Personal Travel,Eco,501,2,4,3,3,4,3,4,4,4,3,5,4,5,4,1,10.0,neutral or dissatisfied +102670,91855,Male,Loyal Customer,46,Personal Travel,Eco,1797,2,5,2,5,4,2,4,4,2,5,5,4,3,4,0,0.0,neutral or dissatisfied +102671,104558,Male,Loyal Customer,48,Business travel,Business,1778,4,4,4,4,2,4,5,5,5,5,5,3,5,4,9,25.0,satisfied +102672,82930,Female,disloyal Customer,24,Business travel,Eco,594,0,0,0,4,3,0,3,3,3,2,4,5,5,3,53,52.0,satisfied +102673,60190,Male,disloyal Customer,29,Business travel,Eco Plus,1197,3,4,4,4,5,4,1,5,3,4,3,4,4,5,0,0.0,neutral or dissatisfied +102674,96123,Male,Loyal Customer,62,Personal Travel,Eco Plus,1235,1,5,1,3,2,1,2,2,5,3,4,4,4,2,1,0.0,neutral or dissatisfied +102675,65509,Female,Loyal Customer,40,Business travel,Business,1616,4,4,4,4,3,3,5,4,4,4,4,4,4,3,10,13.0,satisfied +102676,77978,Female,Loyal Customer,58,Business travel,Business,3430,3,3,3,3,2,4,5,4,4,4,4,4,4,3,6,15.0,satisfied +102677,83937,Male,disloyal Customer,43,Business travel,Business,373,3,3,3,3,2,3,2,2,4,2,5,3,5,2,0,13.0,neutral or dissatisfied +102678,65002,Male,disloyal Customer,25,Business travel,Eco,151,1,5,1,5,2,1,2,2,3,2,1,1,3,2,7,2.0,neutral or dissatisfied +102679,62913,Female,Loyal Customer,44,Business travel,Business,862,5,5,4,5,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +102680,55989,Female,disloyal Customer,19,Business travel,Business,1367,0,0,0,3,0,3,3,4,5,5,4,3,4,3,0,0.0,satisfied +102681,83568,Female,Loyal Customer,57,Business travel,Business,936,3,3,3,3,5,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +102682,61884,Male,Loyal Customer,56,Business travel,Business,2521,5,5,5,5,4,3,4,5,5,5,5,3,5,4,0,0.0,satisfied +102683,13469,Female,Loyal Customer,20,Personal Travel,Eco,475,2,2,2,1,2,2,2,2,4,5,1,4,2,2,44,56.0,neutral or dissatisfied +102684,122531,Female,Loyal Customer,49,Business travel,Business,500,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +102685,104888,Male,Loyal Customer,44,Business travel,Business,3034,3,3,3,3,5,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +102686,2085,Male,Loyal Customer,32,Personal Travel,Eco,733,4,3,4,4,1,4,1,1,2,1,5,1,2,1,0,0.0,neutral or dissatisfied +102687,1228,Male,Loyal Customer,20,Personal Travel,Eco,229,3,5,3,1,3,3,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +102688,122814,Male,Loyal Customer,62,Personal Travel,Eco,599,2,1,2,4,3,2,3,3,3,4,3,1,3,3,31,30.0,neutral or dissatisfied +102689,75176,Male,disloyal Customer,40,Business travel,Business,1726,4,4,4,3,2,4,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +102690,10840,Female,Loyal Customer,61,Business travel,Eco,429,2,4,4,4,3,2,2,2,2,2,2,4,2,3,4,6.0,neutral or dissatisfied +102691,95016,Male,Loyal Customer,10,Personal Travel,Eco,239,3,5,3,1,3,3,5,3,1,1,2,5,2,3,0,0.0,neutral or dissatisfied +102692,127989,Male,Loyal Customer,15,Personal Travel,Eco,1149,2,5,2,3,1,2,1,1,4,5,4,5,4,1,0,9.0,neutral or dissatisfied +102693,77353,Male,Loyal Customer,42,Business travel,Business,3255,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +102694,90882,Male,disloyal Customer,24,Business travel,Business,223,4,4,4,3,3,4,3,3,5,5,5,5,4,3,0,9.0,satisfied +102695,55275,Male,Loyal Customer,35,Personal Travel,Eco Plus,1839,5,4,5,2,4,5,4,4,4,4,3,3,5,4,0,2.0,satisfied +102696,116087,Male,Loyal Customer,37,Personal Travel,Eco,333,3,5,3,5,3,3,3,3,3,2,4,3,5,3,10,0.0,neutral or dissatisfied +102697,17000,Male,Loyal Customer,61,Business travel,Eco Plus,843,5,1,1,1,5,5,5,5,5,5,4,2,3,5,0,0.0,satisfied +102698,65188,Female,Loyal Customer,56,Personal Travel,Eco,247,4,1,4,4,3,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +102699,30884,Male,Loyal Customer,56,Business travel,Eco Plus,1106,3,3,3,3,3,3,3,3,3,1,3,3,3,3,0,14.0,neutral or dissatisfied +102700,88287,Female,Loyal Customer,58,Business travel,Eco,271,2,2,2,2,4,2,2,2,2,2,2,1,2,1,0,6.0,neutral or dissatisfied +102701,4501,Male,Loyal Customer,55,Business travel,Business,435,3,3,2,3,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +102702,115295,Male,disloyal Customer,27,Business travel,Business,296,1,1,1,3,5,1,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +102703,103327,Female,Loyal Customer,63,Personal Travel,Eco,1139,3,3,3,2,3,2,2,1,2,5,3,2,4,2,200,169.0,neutral or dissatisfied +102704,102729,Female,Loyal Customer,50,Personal Travel,Eco,365,2,4,2,3,5,4,5,5,5,2,3,5,5,3,0,0.0,neutral or dissatisfied +102705,103260,Male,Loyal Customer,51,Business travel,Business,1528,3,3,5,3,2,3,4,3,3,3,3,1,3,2,11,0.0,neutral or dissatisfied +102706,57148,Male,Loyal Customer,54,Business travel,Business,1824,1,4,2,4,2,4,4,1,1,1,1,1,1,2,3,5.0,neutral or dissatisfied +102707,91450,Female,Loyal Customer,42,Business travel,Business,859,4,4,4,4,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +102708,23448,Female,disloyal Customer,8,Business travel,Business,488,2,1,1,2,3,1,3,3,1,4,2,3,2,3,53,50.0,neutral or dissatisfied +102709,98861,Female,disloyal Customer,35,Business travel,Eco,925,3,3,3,3,5,3,5,5,3,4,5,1,5,5,0,0.0,neutral or dissatisfied +102710,120699,Male,Loyal Customer,41,Personal Travel,Eco,280,3,4,2,3,2,1,4,4,4,4,4,4,5,4,136,131.0,neutral or dissatisfied +102711,46637,Male,Loyal Customer,62,Business travel,Business,125,1,2,2,2,5,3,4,2,2,2,1,3,2,2,3,2.0,neutral or dissatisfied +102712,41101,Female,Loyal Customer,37,Business travel,Business,295,4,4,4,4,2,3,3,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +102713,28928,Female,Loyal Customer,49,Business travel,Eco,671,4,4,4,4,2,4,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +102714,69707,Male,Loyal Customer,25,Business travel,Business,1372,1,5,5,5,1,1,1,1,3,1,4,4,4,1,0,0.0,neutral or dissatisfied +102715,76079,Male,Loyal Customer,58,Business travel,Business,3169,2,5,4,5,5,4,4,2,2,2,2,2,2,1,61,48.0,neutral or dissatisfied +102716,14001,Female,Loyal Customer,29,Personal Travel,Eco,160,3,4,3,3,1,3,1,1,3,3,5,4,4,1,0,0.0,neutral or dissatisfied +102717,83624,Female,Loyal Customer,19,Personal Travel,Eco,409,3,5,3,2,2,3,2,2,5,2,5,5,5,2,4,0.0,neutral or dissatisfied +102718,109559,Male,Loyal Customer,19,Personal Travel,Eco,920,2,5,2,3,5,2,1,5,4,2,5,4,4,5,0,3.0,neutral or dissatisfied +102719,26412,Male,Loyal Customer,64,Personal Travel,Eco,1249,1,5,1,3,2,1,2,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +102720,31134,Male,disloyal Customer,25,Business travel,Eco,591,1,4,1,1,5,1,3,5,5,3,3,2,1,5,0,0.0,neutral or dissatisfied +102721,127684,Male,Loyal Customer,23,Personal Travel,Business,2133,3,5,3,2,1,3,1,1,3,2,3,3,5,1,1,5.0,neutral or dissatisfied +102722,46914,Female,disloyal Customer,11,Business travel,Eco,737,3,3,3,4,4,3,4,4,2,1,4,3,4,4,27,76.0,neutral or dissatisfied +102723,93029,Female,Loyal Customer,51,Personal Travel,Business,436,3,4,3,4,2,4,5,1,1,3,1,4,1,3,21,14.0,neutral or dissatisfied +102724,57600,Female,Loyal Customer,25,Business travel,Business,2684,1,1,1,1,2,2,2,2,5,4,5,4,5,2,10,7.0,satisfied +102725,16836,Male,Loyal Customer,60,Personal Travel,Eco,645,3,5,3,2,1,3,3,1,4,5,4,3,1,1,12,7.0,neutral or dissatisfied +102726,65184,Male,Loyal Customer,49,Personal Travel,Eco,551,4,5,4,2,3,4,3,3,5,3,1,5,5,3,0,0.0,neutral or dissatisfied +102727,116232,Female,Loyal Customer,33,Personal Travel,Eco,358,2,4,2,1,1,2,1,1,4,2,4,5,5,1,25,17.0,neutral or dissatisfied +102728,78612,Male,Loyal Customer,27,Business travel,Business,1426,1,1,1,1,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +102729,17458,Female,Loyal Customer,29,Personal Travel,Eco Plus,351,5,5,5,1,4,5,4,4,3,3,4,5,5,4,0,0.0,satisfied +102730,72555,Male,Loyal Customer,40,Business travel,Business,929,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +102731,1156,Male,Loyal Customer,69,Personal Travel,Eco,113,3,3,3,2,3,3,3,3,1,2,2,3,4,3,0,0.0,neutral or dissatisfied +102732,120352,Female,Loyal Customer,59,Business travel,Business,449,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +102733,85543,Male,Loyal Customer,46,Business travel,Business,259,4,5,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +102734,22875,Female,Loyal Customer,42,Personal Travel,Eco,147,3,5,3,3,3,4,5,4,4,3,4,3,4,4,5,0.0,neutral or dissatisfied +102735,18875,Female,Loyal Customer,30,Business travel,Business,3042,1,4,4,4,1,1,1,1,3,2,2,2,3,1,11,8.0,neutral or dissatisfied +102736,104441,Male,Loyal Customer,9,Personal Travel,Eco,1041,3,4,3,2,3,2,2,4,3,5,5,2,4,2,158,156.0,neutral or dissatisfied +102737,94596,Male,Loyal Customer,31,Business travel,Business,562,4,4,5,4,2,2,2,2,5,3,4,5,5,2,0,0.0,satisfied +102738,64114,Female,Loyal Customer,57,Business travel,Business,2288,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +102739,7866,Female,disloyal Customer,30,Business travel,Business,948,3,3,3,4,1,3,1,1,3,2,5,4,4,1,4,0.0,neutral or dissatisfied +102740,50892,Female,Loyal Customer,57,Personal Travel,Eco,86,2,4,2,3,3,4,4,3,3,2,2,4,3,5,0,0.0,neutral or dissatisfied +102741,29225,Female,Loyal Customer,38,Personal Travel,Business,834,4,2,4,4,2,3,4,2,2,4,2,1,2,1,1,1.0,satisfied +102742,21616,Female,disloyal Customer,39,Business travel,Business,780,3,3,3,3,4,3,4,4,4,5,4,4,4,4,20,19.0,neutral or dissatisfied +102743,44110,Female,Loyal Customer,11,Personal Travel,Eco,408,2,4,2,5,3,2,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +102744,32802,Female,disloyal Customer,38,Business travel,Eco,101,4,3,4,4,1,4,1,1,1,2,4,3,3,1,0,2.0,neutral or dissatisfied +102745,85801,Male,Loyal Customer,45,Business travel,Eco,266,4,4,4,4,4,4,4,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +102746,51223,Female,disloyal Customer,37,Business travel,Eco Plus,86,4,4,4,2,2,4,2,2,4,3,3,4,2,2,0,0.0,neutral or dissatisfied +102747,9393,Male,Loyal Customer,63,Business travel,Business,2151,4,4,4,4,5,2,4,4,4,4,4,2,4,1,0,0.0,satisfied +102748,70758,Female,Loyal Customer,45,Personal Travel,Eco,733,4,4,4,1,4,5,1,3,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +102749,28838,Male,disloyal Customer,49,Business travel,Eco,978,1,1,1,1,5,1,5,5,5,5,4,5,1,5,5,4.0,neutral or dissatisfied +102750,76687,Female,Loyal Customer,36,Personal Travel,Eco,516,5,4,5,3,3,5,3,3,4,2,2,4,5,3,0,0.0,satisfied +102751,97134,Male,Loyal Customer,28,Business travel,Business,1551,2,3,2,2,2,2,2,2,3,3,4,2,3,2,13,6.0,neutral or dissatisfied +102752,45186,Female,Loyal Customer,40,Business travel,Business,1437,5,1,5,5,2,3,5,5,5,5,5,2,5,2,48,62.0,satisfied +102753,113579,Male,Loyal Customer,37,Business travel,Business,3986,0,4,0,3,5,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +102754,67781,Male,Loyal Customer,21,Business travel,Business,1464,5,5,5,5,5,5,5,5,5,5,5,4,4,5,0,0.0,satisfied +102755,121567,Female,disloyal Customer,25,Business travel,Business,936,3,5,3,3,5,3,2,5,5,3,5,3,4,5,2,0.0,neutral or dissatisfied +102756,117074,Female,Loyal Customer,25,Business travel,Business,647,1,1,1,1,1,1,1,1,1,2,4,1,4,1,16,7.0,neutral or dissatisfied +102757,18972,Female,Loyal Customer,70,Personal Travel,Eco Plus,500,4,4,4,2,2,4,4,4,4,4,4,4,4,5,0,7.0,neutral or dissatisfied +102758,123227,Female,Loyal Customer,70,Personal Travel,Eco,600,3,4,3,4,2,4,4,3,3,3,3,2,3,2,0,4.0,neutral or dissatisfied +102759,124960,Female,disloyal Customer,27,Business travel,Business,184,4,4,4,2,3,4,3,3,4,3,4,4,5,3,0,0.0,satisfied +102760,104338,Male,Loyal Customer,70,Personal Travel,Eco,452,3,4,3,1,3,3,3,3,1,1,1,4,2,3,0,0.0,neutral or dissatisfied +102761,78669,Female,disloyal Customer,40,Business travel,Business,674,3,4,4,5,4,4,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +102762,41437,Male,Loyal Customer,38,Business travel,Eco Plus,641,5,1,1,1,5,5,5,5,3,4,4,1,2,5,44,53.0,satisfied +102763,6184,Male,Loyal Customer,16,Personal Travel,Eco,409,3,4,3,3,2,3,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +102764,31772,Female,disloyal Customer,27,Business travel,Eco,602,3,3,3,3,3,3,3,3,3,2,3,3,3,3,0,15.0,neutral or dissatisfied +102765,100838,Male,disloyal Customer,25,Business travel,Eco,711,2,1,1,2,5,1,5,5,2,1,3,4,2,5,5,0.0,neutral or dissatisfied +102766,25355,Male,Loyal Customer,53,Personal Travel,Business,591,4,4,4,5,5,2,4,4,4,4,4,4,4,3,0,0.0,satisfied +102767,86888,Female,Loyal Customer,51,Business travel,Business,2993,2,2,3,2,4,5,5,4,4,4,4,3,4,4,13,13.0,satisfied +102768,99886,Female,disloyal Customer,22,Business travel,Eco,738,4,4,4,2,3,4,2,3,4,2,5,5,5,3,0,0.0,satisfied +102769,44486,Male,Loyal Customer,36,Personal Travel,Eco,476,3,2,3,1,3,3,4,3,3,1,2,4,3,4,175,159.0,neutral or dissatisfied +102770,95675,Female,Loyal Customer,53,Business travel,Business,1761,2,2,2,2,2,4,5,3,3,4,3,3,3,5,12,16.0,satisfied +102771,66779,Female,Loyal Customer,45,Business travel,Business,3122,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +102772,82084,Female,disloyal Customer,30,Business travel,Business,1276,5,5,5,1,5,5,5,5,4,4,4,4,4,5,42,23.0,satisfied +102773,96988,Female,Loyal Customer,56,Business travel,Business,883,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +102774,86161,Male,disloyal Customer,24,Business travel,Business,356,0,0,0,5,3,0,3,3,4,5,5,3,5,3,0,0.0,satisfied +102775,19400,Female,disloyal Customer,22,Business travel,Eco,261,4,2,4,4,2,4,2,2,3,5,4,4,4,2,37,34.0,neutral or dissatisfied +102776,127173,Female,Loyal Customer,13,Personal Travel,Eco,304,4,1,4,4,1,4,5,1,1,2,4,2,4,1,0,0.0,neutral or dissatisfied +102777,84121,Female,Loyal Customer,23,Business travel,Business,400,1,1,1,1,4,4,4,4,4,3,5,5,1,4,0,5.0,satisfied +102778,110132,Female,disloyal Customer,29,Business travel,Eco,1072,1,1,1,3,5,1,5,5,3,4,3,2,4,5,0,0.0,neutral or dissatisfied +102779,100563,Male,Loyal Customer,41,Personal Travel,Business,486,2,2,2,3,1,3,3,5,5,2,3,3,5,4,36,30.0,neutral or dissatisfied +102780,91217,Male,Loyal Customer,67,Personal Travel,Eco,594,2,3,2,3,3,2,3,3,1,2,3,1,3,3,0,0.0,neutral or dissatisfied +102781,53832,Female,Loyal Customer,39,Business travel,Business,224,5,5,3,5,1,3,1,5,5,5,5,3,5,4,106,100.0,satisfied +102782,72084,Female,Loyal Customer,44,Personal Travel,Eco,2556,4,5,4,3,1,3,4,1,1,4,1,5,1,4,0,0.0,neutral or dissatisfied +102783,40683,Male,Loyal Customer,46,Business travel,Business,588,1,1,1,1,2,4,5,5,5,5,5,5,5,2,22,0.0,satisfied +102784,78505,Male,Loyal Customer,45,Business travel,Business,2645,0,4,0,1,5,1,5,5,5,5,5,3,5,3,46,67.0,satisfied +102785,8025,Male,Loyal Customer,42,Business travel,Business,3276,0,4,0,2,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +102786,40594,Female,Loyal Customer,42,Business travel,Eco,391,5,2,2,2,3,2,5,5,5,5,5,4,5,3,0,0.0,satisfied +102787,14511,Male,Loyal Customer,36,Personal Travel,Eco,328,3,0,1,4,3,1,3,3,3,1,4,5,2,3,0,0.0,neutral or dissatisfied +102788,29915,Male,Loyal Customer,22,Business travel,Business,1567,3,1,1,1,3,3,3,3,1,5,4,3,4,3,0,16.0,neutral or dissatisfied +102789,82605,Male,Loyal Customer,23,Business travel,Business,3099,3,4,4,4,3,4,3,3,1,2,3,4,2,3,0,0.0,neutral or dissatisfied +102790,42349,Male,Loyal Customer,24,Personal Travel,Eco,748,0,4,0,3,5,0,5,5,4,5,5,5,2,5,0,2.0,satisfied +102791,7369,Female,Loyal Customer,27,Business travel,Business,2361,3,1,3,1,3,3,3,3,1,4,4,4,3,3,0,0.0,neutral or dissatisfied +102792,45371,Male,Loyal Customer,55,Personal Travel,Eco,290,3,4,3,2,4,3,4,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +102793,10267,Female,Loyal Customer,65,Personal Travel,Business,270,4,4,4,1,2,5,4,1,1,4,1,3,1,5,0,0.0,satisfied +102794,29578,Female,Loyal Customer,35,Business travel,Business,1448,4,4,5,4,3,3,1,5,5,4,5,1,5,5,1,0.0,satisfied +102795,85048,Female,Loyal Customer,40,Business travel,Business,3010,5,5,5,5,5,4,4,4,4,4,4,5,4,5,39,26.0,satisfied +102796,105503,Female,disloyal Customer,24,Business travel,Eco,611,2,0,2,1,4,2,4,4,4,2,4,3,4,4,12,0.0,neutral or dissatisfied +102797,30629,Female,Loyal Customer,49,Business travel,Eco,533,5,3,3,3,3,4,2,5,5,5,5,1,5,2,5,4.0,satisfied +102798,8103,Female,Loyal Customer,52,Business travel,Business,3222,3,3,3,3,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +102799,35715,Female,Loyal Customer,29,Personal Travel,Eco,2475,2,4,2,5,2,2,2,1,3,5,3,2,4,2,110,116.0,neutral or dissatisfied +102800,40016,Male,Loyal Customer,33,Business travel,Business,525,5,5,5,5,4,4,4,4,5,3,3,3,2,4,0,0.0,satisfied +102801,108569,Male,Loyal Customer,48,Business travel,Business,3354,5,5,5,5,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +102802,101939,Female,disloyal Customer,44,Business travel,Business,628,2,2,2,5,5,2,5,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +102803,102530,Male,Loyal Customer,61,Personal Travel,Eco,397,3,5,3,1,4,3,2,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +102804,121775,Male,Loyal Customer,39,Business travel,Business,2162,4,4,4,4,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +102805,62070,Male,Loyal Customer,11,Personal Travel,Eco,2586,2,5,2,4,3,2,3,3,4,4,3,4,5,3,0,0.0,neutral or dissatisfied +102806,48533,Female,Loyal Customer,53,Business travel,Business,516,1,1,5,1,5,1,4,5,5,5,5,1,5,5,0,0.0,satisfied +102807,67393,Male,Loyal Customer,43,Business travel,Business,641,2,5,5,5,3,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +102808,85346,Male,Loyal Customer,41,Business travel,Eco Plus,696,1,5,5,5,1,1,1,1,3,1,3,2,4,1,0,0.0,neutral or dissatisfied +102809,93431,Female,Loyal Customer,25,Business travel,Business,1869,4,1,1,1,4,4,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +102810,76618,Female,Loyal Customer,33,Business travel,Business,481,5,5,5,5,3,4,3,4,4,4,4,3,4,3,0,2.0,satisfied +102811,61067,Female,Loyal Customer,31,Business travel,Business,1546,2,2,2,2,3,3,3,3,5,5,4,5,4,3,9,2.0,satisfied +102812,37626,Female,Loyal Customer,63,Personal Travel,Eco,1069,3,5,3,3,1,1,2,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +102813,109477,Male,disloyal Customer,21,Business travel,Eco,992,4,4,4,3,3,4,3,3,5,5,5,5,4,3,3,0.0,neutral or dissatisfied +102814,22889,Female,Loyal Customer,40,Personal Travel,Eco,134,3,4,3,3,4,3,4,4,4,2,4,4,4,4,111,101.0,neutral or dissatisfied +102815,16131,Female,Loyal Customer,68,Personal Travel,Eco,725,4,1,4,4,2,4,4,4,4,4,1,2,4,3,41,78.0,neutral or dissatisfied +102816,63466,Male,Loyal Customer,59,Business travel,Business,447,1,1,1,1,4,5,5,2,2,2,2,4,2,4,1,0.0,satisfied +102817,115260,Female,disloyal Customer,39,Business travel,Business,362,2,2,2,3,1,2,1,1,3,4,2,4,2,1,55,55.0,neutral or dissatisfied +102818,125900,Female,Loyal Customer,17,Personal Travel,Eco,992,4,4,4,3,3,4,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +102819,4754,Male,disloyal Customer,37,Business travel,Business,403,2,2,2,3,2,2,2,2,1,1,4,1,3,2,0,0.0,neutral or dissatisfied +102820,15102,Female,Loyal Customer,65,Personal Travel,Eco,322,2,4,1,4,3,5,1,2,2,1,2,1,2,3,0,4.0,neutral or dissatisfied +102821,47546,Male,Loyal Customer,60,Business travel,Eco Plus,588,3,3,3,3,3,3,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +102822,89862,Female,Loyal Customer,27,Business travel,Business,1416,5,5,3,5,4,4,4,4,5,5,5,4,4,4,15,9.0,satisfied +102823,14747,Male,disloyal Customer,27,Business travel,Eco,533,1,3,1,1,5,1,5,5,3,5,1,3,2,5,0,0.0,neutral or dissatisfied +102824,97576,Male,Loyal Customer,68,Business travel,Business,337,2,2,4,2,2,4,4,2,2,2,2,3,2,1,3,3.0,neutral or dissatisfied +102825,87092,Female,Loyal Customer,39,Business travel,Business,2727,5,5,5,5,3,3,3,5,5,5,3,4,5,4,0,0.0,satisfied +102826,75871,Female,Loyal Customer,43,Business travel,Business,1972,2,2,2,2,2,5,4,4,4,5,4,4,4,3,16,31.0,satisfied +102827,125910,Female,Loyal Customer,21,Personal Travel,Eco,992,1,5,1,4,1,2,2,5,3,5,5,2,3,2,156,253.0,neutral or dissatisfied +102828,71489,Male,Loyal Customer,41,Business travel,Business,1197,2,1,1,1,2,4,3,2,2,2,2,3,2,2,66,55.0,neutral or dissatisfied +102829,60861,Male,Loyal Customer,34,Business travel,Business,1491,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +102830,110802,Female,Loyal Customer,55,Personal Travel,Eco,997,3,4,3,3,5,5,5,5,5,3,5,5,5,3,8,2.0,neutral or dissatisfied +102831,62558,Female,Loyal Customer,43,Business travel,Eco,1846,3,4,4,4,4,2,4,3,3,3,3,3,3,3,21,16.0,neutral or dissatisfied +102832,59199,Male,Loyal Customer,27,Business travel,Business,1440,5,5,5,5,5,4,5,5,3,2,5,4,4,5,72,76.0,satisfied +102833,12830,Female,disloyal Customer,25,Business travel,Eco,528,1,4,1,5,1,1,1,1,5,5,2,2,1,1,0,0.0,neutral or dissatisfied +102834,129808,Female,Loyal Customer,69,Personal Travel,Eco,447,2,3,2,3,1,4,4,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +102835,35102,Female,Loyal Customer,27,Business travel,Business,2470,4,5,4,4,2,2,2,2,1,5,1,4,4,2,0,11.0,satisfied +102836,105617,Female,disloyal Customer,49,Business travel,Business,925,3,3,3,3,2,3,2,2,5,4,5,4,5,2,16,90.0,neutral or dissatisfied +102837,56185,Male,Loyal Customer,65,Personal Travel,Eco,1372,4,4,5,1,4,5,2,4,4,3,4,5,4,4,17,1.0,satisfied +102838,59930,Male,Loyal Customer,43,Business travel,Business,2595,3,3,3,3,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +102839,90070,Female,Loyal Customer,57,Business travel,Business,957,2,2,2,2,2,5,4,4,4,4,4,3,4,4,7,17.0,satisfied +102840,85087,Male,disloyal Customer,37,Business travel,Business,731,2,2,2,3,5,2,5,5,5,4,4,5,4,5,0,0.0,neutral or dissatisfied +102841,19420,Female,Loyal Customer,11,Business travel,Eco,645,3,5,5,5,3,3,2,3,1,2,3,2,4,3,13,4.0,neutral or dissatisfied +102842,107597,Female,disloyal Customer,45,Business travel,Business,423,2,2,2,5,4,2,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +102843,57312,Female,Loyal Customer,43,Business travel,Business,414,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,20.0,satisfied +102844,70591,Male,Loyal Customer,54,Business travel,Business,2611,1,1,1,1,4,3,3,5,4,5,4,3,3,3,0,0.0,satisfied +102845,38961,Female,disloyal Customer,33,Business travel,Business,406,2,2,2,3,5,2,1,5,2,2,3,2,4,5,80,99.0,neutral or dissatisfied +102846,34795,Female,Loyal Customer,56,Personal Travel,Eco,209,3,4,3,3,3,3,3,3,3,3,3,4,3,2,55,48.0,neutral or dissatisfied +102847,355,Male,Loyal Customer,16,Personal Travel,Eco Plus,821,2,3,2,3,5,2,5,5,4,1,2,3,2,5,0,0.0,neutral or dissatisfied +102848,14534,Female,Loyal Customer,78,Business travel,Eco,299,4,1,1,1,3,3,3,4,4,4,4,1,4,1,81,69.0,neutral or dissatisfied +102849,12234,Female,Loyal Customer,39,Business travel,Business,192,0,4,0,2,1,1,1,1,2,2,2,1,2,1,150,157.0,satisfied +102850,87634,Female,Loyal Customer,45,Business travel,Business,1760,4,4,2,4,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +102851,103227,Male,Loyal Customer,48,Personal Travel,Eco,462,4,4,4,2,1,4,2,1,5,3,4,3,5,1,0,0.0,neutral or dissatisfied +102852,73068,Female,disloyal Customer,19,Business travel,Business,1085,4,0,4,4,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +102853,61045,Female,Loyal Customer,46,Business travel,Business,1607,1,1,1,1,2,5,5,3,3,4,3,4,3,3,4,0.0,satisfied +102854,39095,Female,Loyal Customer,28,Personal Travel,Eco,984,1,4,1,3,5,1,2,5,3,2,4,3,4,5,71,62.0,neutral or dissatisfied +102855,79472,Female,Loyal Customer,50,Business travel,Business,762,5,5,5,5,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +102856,122282,Female,Loyal Customer,62,Personal Travel,Eco,541,2,1,2,2,1,2,3,4,4,2,4,1,4,1,21,1.0,neutral or dissatisfied +102857,113323,Male,Loyal Customer,47,Business travel,Business,2981,5,5,5,5,4,4,5,5,5,5,5,5,5,3,17,12.0,satisfied +102858,36161,Male,Loyal Customer,22,Business travel,Business,1674,5,5,5,5,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +102859,111387,Female,Loyal Customer,33,Business travel,Business,3012,2,4,4,4,2,4,3,2,2,2,2,3,2,4,51,29.0,neutral or dissatisfied +102860,50988,Female,Loyal Customer,60,Personal Travel,Eco,109,3,4,3,4,3,4,3,1,1,3,1,2,1,3,0,0.0,neutral or dissatisfied +102861,108830,Male,Loyal Customer,46,Business travel,Business,3774,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,9.0,satisfied +102862,59836,Male,Loyal Customer,52,Business travel,Business,2930,4,4,4,4,2,5,4,3,3,4,3,5,3,5,116,100.0,satisfied +102863,126797,Male,Loyal Customer,40,Business travel,Business,2296,5,5,5,5,2,5,4,3,3,3,3,5,3,5,0,5.0,satisfied +102864,67727,Male,Loyal Customer,50,Business travel,Business,1464,5,5,2,5,3,4,4,4,4,4,4,4,4,3,0,5.0,satisfied +102865,115128,Female,Loyal Customer,55,Business travel,Business,296,1,1,1,1,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +102866,1698,Male,disloyal Customer,27,Business travel,Business,364,5,5,5,1,5,5,4,5,5,2,5,4,4,5,0,4.0,satisfied +102867,9371,Female,disloyal Customer,54,Business travel,Eco,384,2,0,2,5,2,2,2,2,1,2,3,1,5,2,28,16.0,neutral or dissatisfied +102868,60070,Female,Loyal Customer,40,Business travel,Business,1005,1,1,4,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +102869,51354,Female,disloyal Customer,22,Business travel,Eco,109,1,0,1,5,3,1,3,3,1,1,5,3,5,3,0,0.0,neutral or dissatisfied +102870,124271,Male,Loyal Customer,41,Business travel,Business,3847,5,5,5,5,4,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +102871,29342,Female,Loyal Customer,54,Business travel,Eco Plus,834,4,3,3,3,5,3,3,4,4,4,4,3,4,5,0,0.0,satisfied +102872,74616,Female,disloyal Customer,75,Business travel,Eco,726,1,2,2,4,3,2,5,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +102873,22718,Female,Loyal Customer,59,Business travel,Business,151,0,5,0,3,4,4,4,1,1,1,1,4,1,4,0,0.0,satisfied +102874,82883,Female,disloyal Customer,21,Business travel,Eco,594,4,5,4,2,5,4,5,5,1,5,5,1,3,5,0,0.0,satisfied +102875,11875,Female,Loyal Customer,16,Personal Travel,Eco,912,3,5,3,5,2,3,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +102876,126338,Male,Loyal Customer,31,Personal Travel,Eco,468,4,5,3,4,3,3,3,3,4,3,5,5,4,3,0,6.0,neutral or dissatisfied +102877,4363,Female,Loyal Customer,30,Business travel,Business,2229,3,3,3,3,4,4,4,4,4,2,5,5,4,4,0,0.0,satisfied +102878,83930,Female,Loyal Customer,56,Business travel,Business,373,1,1,1,1,4,5,4,4,4,4,4,5,4,4,21,54.0,satisfied +102879,129351,Male,Loyal Customer,26,Personal Travel,Eco,2475,2,4,2,4,5,2,5,5,3,5,5,4,4,5,6,0.0,neutral or dissatisfied +102880,93335,Male,Loyal Customer,44,Business travel,Business,3183,1,1,1,1,3,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +102881,4477,Female,Loyal Customer,44,Business travel,Eco Plus,1005,4,1,1,1,3,3,3,4,4,4,4,2,4,1,0,13.0,neutral or dissatisfied +102882,92394,Male,Loyal Customer,53,Business travel,Business,2139,1,1,1,1,2,3,4,4,4,4,4,4,4,3,0,6.0,satisfied +102883,17916,Male,Loyal Customer,42,Business travel,Eco,789,5,1,1,1,5,5,5,5,5,5,4,1,4,5,0,0.0,satisfied +102884,1700,Female,disloyal Customer,22,Business travel,Business,364,0,0,0,4,4,0,4,4,5,5,5,5,4,4,11,7.0,satisfied +102885,68574,Female,Loyal Customer,24,Business travel,Eco,1616,2,3,3,3,2,2,3,2,4,4,2,2,3,2,0,0.0,neutral or dissatisfied +102886,100786,Male,Loyal Customer,52,Personal Travel,Eco,1411,3,3,2,5,3,2,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +102887,36272,Female,Loyal Customer,10,Personal Travel,Eco,728,4,5,4,5,2,4,2,2,3,1,4,2,3,2,0,0.0,neutral or dissatisfied +102888,124254,Male,Loyal Customer,54,Business travel,Business,1916,4,4,4,4,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +102889,19511,Male,Loyal Customer,14,Personal Travel,Eco,350,2,4,2,1,5,2,5,5,3,4,5,4,4,5,0,8.0,neutral or dissatisfied +102890,62687,Female,Loyal Customer,44,Business travel,Business,2367,2,5,5,5,2,2,2,4,3,1,3,2,4,2,28,42.0,neutral or dissatisfied +102891,83535,Female,Loyal Customer,41,Business travel,Eco,1121,1,1,1,1,1,1,1,1,2,3,3,3,4,1,0,4.0,neutral or dissatisfied +102892,44296,Female,Loyal Customer,66,Personal Travel,Eco,563,4,5,4,3,4,5,4,1,1,4,2,3,1,3,0,0.0,neutral or dissatisfied +102893,62998,Female,Loyal Customer,32,Business travel,Business,853,1,1,1,1,4,5,4,4,4,5,4,4,5,4,1,0.0,satisfied +102894,126321,Male,Loyal Customer,38,Personal Travel,Eco,650,1,2,1,3,4,1,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +102895,54410,Female,disloyal Customer,22,Business travel,Eco,305,4,3,4,5,5,4,5,5,5,3,2,4,1,5,0,0.0,satisfied +102896,43700,Male,disloyal Customer,23,Business travel,Eco,489,3,2,3,3,1,3,1,1,2,5,3,2,3,1,51,49.0,neutral or dissatisfied +102897,31152,Female,Loyal Customer,39,Business travel,Business,1943,3,3,2,3,5,3,3,5,5,5,5,3,5,2,0,0.0,satisfied +102898,91749,Female,disloyal Customer,19,Business travel,Eco,590,1,1,1,4,1,1,1,1,3,1,4,2,4,1,20,13.0,neutral or dissatisfied +102899,129482,Male,disloyal Customer,66,Business travel,Business,2611,2,2,2,3,5,2,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +102900,28311,Male,Loyal Customer,49,Business travel,Eco,867,4,1,1,1,4,4,4,4,5,3,4,4,1,4,0,0.0,satisfied +102901,17197,Female,disloyal Customer,21,Business travel,Eco,694,5,5,5,3,2,5,2,2,2,1,4,5,1,2,0,0.0,satisfied +102902,99050,Female,Loyal Customer,46,Business travel,Business,1603,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +102903,61666,Male,disloyal Customer,22,Business travel,Eco,1379,4,4,4,3,3,4,3,3,2,4,3,4,3,3,0,0.0,neutral or dissatisfied +102904,64315,Male,Loyal Customer,45,Business travel,Business,1554,3,5,5,5,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +102905,21049,Female,Loyal Customer,36,Business travel,Business,3998,3,3,3,3,4,1,4,4,4,4,5,4,4,1,33,24.0,satisfied +102906,95697,Male,disloyal Customer,38,Business travel,Business,419,4,4,4,3,4,4,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +102907,28729,Male,disloyal Customer,30,Business travel,Business,2717,2,2,2,4,2,3,3,3,1,5,2,3,5,3,21,57.0,neutral or dissatisfied +102908,68454,Female,Loyal Customer,29,Business travel,Business,1303,2,2,2,2,4,5,4,4,4,5,5,5,4,4,0,0.0,satisfied +102909,46657,Male,Loyal Customer,18,Business travel,Business,2942,0,3,0,5,4,4,4,4,5,3,1,3,2,4,0,0.0,satisfied +102910,123703,Female,Loyal Customer,33,Personal Travel,Eco,214,2,3,2,4,5,2,3,5,3,2,3,3,4,5,0,0.0,neutral or dissatisfied +102911,108182,Male,Loyal Customer,56,Personal Travel,Eco,990,3,5,3,3,3,3,3,3,3,4,5,3,4,3,1,1.0,neutral or dissatisfied +102912,109429,Male,Loyal Customer,48,Business travel,Business,2114,4,4,4,4,3,5,5,5,5,5,5,5,5,4,52,45.0,satisfied +102913,58708,Male,Loyal Customer,33,Business travel,Eco Plus,4243,2,5,5,5,3,2,2,4,5,3,3,2,3,2,16,13.0,neutral or dissatisfied +102914,26571,Male,Loyal Customer,57,Personal Travel,Business,406,2,3,2,3,4,3,3,1,1,2,4,4,1,1,0,0.0,neutral or dissatisfied +102915,23055,Female,Loyal Customer,50,Business travel,Eco,820,2,3,3,3,3,4,3,2,2,2,2,4,2,1,6,0.0,neutral or dissatisfied +102916,36064,Male,Loyal Customer,47,Business travel,Eco,413,4,2,2,2,4,4,4,4,1,2,2,5,2,4,0,0.0,satisfied +102917,62393,Male,Loyal Customer,37,Personal Travel,Eco,2704,3,5,3,3,4,3,4,4,5,4,1,4,5,4,0,0.0,neutral or dissatisfied +102918,22596,Male,disloyal Customer,34,Business travel,Eco,300,3,3,3,3,1,3,1,1,1,5,3,4,4,1,0,0.0,neutral or dissatisfied +102919,6837,Male,Loyal Customer,48,Personal Travel,Eco,137,1,1,1,3,5,1,4,5,2,1,2,2,3,5,0,0.0,neutral or dissatisfied +102920,63288,Male,Loyal Customer,50,Business travel,Business,337,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +102921,89017,Female,disloyal Customer,25,Business travel,Business,1892,2,1,2,3,1,2,1,1,4,4,2,4,4,1,21,0.0,neutral or dissatisfied +102922,60699,Male,disloyal Customer,36,Business travel,Business,1605,3,3,3,4,3,3,3,3,4,3,3,3,5,3,0,0.0,neutral or dissatisfied +102923,81938,Female,Loyal Customer,53,Business travel,Business,1454,2,2,2,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +102924,114483,Female,Loyal Customer,30,Business travel,Business,325,1,4,4,4,1,1,1,1,1,5,4,2,4,1,12,10.0,neutral or dissatisfied +102925,15401,Female,disloyal Customer,42,Business travel,Eco,377,3,4,4,5,1,4,1,1,1,1,1,4,5,1,0,0.0,neutral or dissatisfied +102926,64715,Female,Loyal Customer,59,Business travel,Business,3738,0,5,0,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +102927,33603,Male,Loyal Customer,23,Business travel,Business,2571,2,2,5,2,2,2,2,2,4,4,4,3,3,2,0,0.0,neutral or dissatisfied +102928,61977,Female,Loyal Customer,45,Business travel,Business,2586,4,3,4,4,4,5,5,5,2,5,5,5,5,5,242,221.0,satisfied +102929,115569,Male,disloyal Customer,36,Business travel,Business,480,4,4,4,1,2,4,2,2,4,5,4,5,5,2,0,5.0,neutral or dissatisfied +102930,4162,Male,Loyal Customer,19,Personal Travel,Eco,544,2,1,2,3,4,2,4,4,4,2,4,2,4,4,15,16.0,neutral or dissatisfied +102931,61984,Male,Loyal Customer,52,Personal Travel,Business,2586,3,1,3,2,3,2,2,4,3,3,3,2,4,2,163,123.0,neutral or dissatisfied +102932,125492,Male,Loyal Customer,57,Personal Travel,Eco Plus,2979,3,4,3,4,3,1,1,4,4,3,3,1,4,1,0,0.0,neutral or dissatisfied +102933,56624,Male,disloyal Customer,23,Business travel,Eco,937,1,1,1,4,1,1,1,1,2,4,3,2,4,1,116,99.0,neutral or dissatisfied +102934,19643,Male,disloyal Customer,39,Business travel,Eco Plus,642,3,3,3,4,5,3,2,5,1,3,3,4,1,5,0,0.0,neutral or dissatisfied +102935,103574,Female,Loyal Customer,37,Business travel,Eco,204,3,3,3,3,3,3,3,3,3,1,3,2,4,3,4,0.0,neutral or dissatisfied +102936,58764,Female,disloyal Customer,21,Business travel,Eco,1005,1,1,1,3,4,1,4,4,3,4,4,4,4,4,0,20.0,neutral or dissatisfied +102937,111961,Male,disloyal Customer,26,Business travel,Eco,533,4,2,4,3,2,4,2,2,2,2,3,3,3,2,12,2.0,neutral or dissatisfied +102938,85118,Female,Loyal Customer,33,Business travel,Business,2290,4,4,5,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +102939,51296,Female,Loyal Customer,25,Business travel,Eco Plus,337,1,3,3,3,1,1,3,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +102940,124733,Male,Loyal Customer,24,Personal Travel,Eco,399,0,4,0,3,1,0,1,1,4,3,5,3,4,1,0,0.0,satisfied +102941,60766,Male,Loyal Customer,39,Business travel,Business,3324,2,2,2,2,3,5,5,4,4,4,4,3,4,3,9,0.0,satisfied +102942,89084,Female,Loyal Customer,58,Business travel,Business,1919,2,2,2,2,2,4,4,4,4,5,4,3,4,3,43,19.0,satisfied +102943,85594,Male,Loyal Customer,35,Business travel,Business,2605,1,1,1,1,5,2,4,5,5,5,3,3,5,5,1,0.0,satisfied +102944,8039,Female,Loyal Customer,57,Business travel,Business,2026,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +102945,75502,Female,Loyal Customer,35,Personal Travel,Eco Plus,2342,2,3,2,4,4,2,4,4,5,3,5,2,3,4,12,21.0,neutral or dissatisfied +102946,22541,Male,Loyal Customer,19,Personal Travel,Eco Plus,143,1,5,1,3,4,1,2,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +102947,37702,Female,Loyal Customer,47,Personal Travel,Eco,1080,3,4,3,2,4,5,5,4,4,3,4,4,4,3,3,6.0,neutral or dissatisfied +102948,9748,Female,Loyal Customer,51,Personal Travel,Eco,908,3,4,3,3,1,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +102949,91442,Male,disloyal Customer,54,Business travel,Business,859,2,2,2,3,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +102950,51406,Female,Loyal Customer,22,Personal Travel,Eco Plus,262,1,5,1,1,1,1,1,1,3,2,1,1,5,1,0,0.0,neutral or dissatisfied +102951,96259,Female,Loyal Customer,20,Personal Travel,Eco,666,4,4,4,4,2,4,2,2,1,5,4,2,3,2,0,0.0,neutral or dissatisfied +102952,57317,Male,Loyal Customer,50,Business travel,Business,414,2,2,2,2,4,4,5,4,4,4,4,3,4,3,3,5.0,satisfied +102953,28073,Male,Loyal Customer,27,Personal Travel,Eco,2562,4,3,4,5,4,3,3,4,2,4,1,3,4,3,0,0.0,satisfied +102954,119075,Male,Loyal Customer,41,Business travel,Business,1107,1,2,1,1,5,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +102955,117232,Female,Loyal Customer,36,Personal Travel,Eco,621,4,5,4,5,3,4,3,3,5,5,4,3,4,3,12,1.0,neutral or dissatisfied +102956,125939,Male,Loyal Customer,60,Personal Travel,Eco,920,1,4,1,4,2,1,2,2,5,2,5,1,4,2,0,0.0,neutral or dissatisfied +102957,7342,Female,Loyal Customer,42,Business travel,Eco,606,1,3,3,3,5,3,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +102958,16093,Male,Loyal Customer,37,Business travel,Business,303,1,3,3,3,2,4,3,1,1,1,1,3,1,2,123,116.0,neutral or dissatisfied +102959,48825,Male,Loyal Customer,49,Personal Travel,Business,86,5,2,5,1,4,2,2,1,1,5,1,3,1,1,14,12.0,satisfied +102960,36787,Male,Loyal Customer,58,Business travel,Eco,1088,4,4,1,1,5,4,5,5,1,5,5,5,3,5,0,,satisfied +102961,18531,Male,Loyal Customer,35,Business travel,Eco,192,3,5,5,5,3,4,3,3,2,1,3,2,2,3,0,0.0,satisfied +102962,112816,Female,Loyal Customer,30,Business travel,Business,1390,4,2,2,2,4,4,4,4,2,4,3,3,4,4,0,0.0,neutral or dissatisfied +102963,11258,Male,Loyal Customer,28,Personal Travel,Eco,201,2,0,0,1,4,0,4,4,2,3,3,5,4,4,0,0.0,neutral or dissatisfied +102964,25836,Female,Loyal Customer,18,Business travel,Business,2206,1,1,1,1,5,5,5,5,4,1,1,2,3,5,0,0.0,satisfied +102965,35243,Female,Loyal Customer,24,Business travel,Business,1069,3,3,3,3,4,4,4,4,4,5,3,2,5,4,14,15.0,satisfied +102966,55610,Female,Loyal Customer,25,Business travel,Business,2669,3,5,5,5,3,3,3,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +102967,125336,Female,disloyal Customer,27,Business travel,Eco,599,1,4,1,4,5,1,5,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +102968,14372,Female,Loyal Customer,32,Business travel,Business,2560,1,1,1,1,5,5,5,5,3,3,3,2,1,5,0,0.0,satisfied +102969,13051,Male,Loyal Customer,24,Business travel,Eco Plus,438,4,1,1,1,4,4,5,4,5,5,3,5,4,4,0,0.0,satisfied +102970,115173,Male,disloyal Customer,36,Business travel,Business,371,1,1,1,5,3,1,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +102971,73342,Male,Loyal Customer,26,Business travel,Business,3694,1,1,1,1,2,2,2,2,4,5,4,4,5,2,0,4.0,satisfied +102972,95282,Female,Loyal Customer,36,Personal Travel,Eco,293,2,2,2,3,5,2,5,5,1,5,4,1,4,5,0,0.0,neutral or dissatisfied +102973,94993,Female,Loyal Customer,21,Personal Travel,Eco,319,5,3,5,3,2,5,5,2,1,1,3,1,3,2,28,20.0,satisfied +102974,95931,Female,Loyal Customer,71,Business travel,Eco,1104,2,2,3,2,2,3,4,2,2,2,2,3,2,2,5,0.0,neutral or dissatisfied +102975,98726,Male,disloyal Customer,36,Business travel,Business,1558,1,1,1,3,5,1,5,5,4,4,4,5,4,5,21,15.0,neutral or dissatisfied +102976,125473,Male,Loyal Customer,70,Personal Travel,Eco,2860,2,4,2,1,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +102977,94400,Female,Loyal Customer,59,Business travel,Business,3578,5,5,5,5,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +102978,80389,Female,Loyal Customer,17,Personal Travel,Eco,368,3,4,3,4,2,3,4,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +102979,93484,Female,Loyal Customer,41,Business travel,Business,2943,1,1,1,1,2,4,4,4,4,4,4,5,4,4,97,90.0,satisfied +102980,19436,Female,Loyal Customer,40,Personal Travel,Eco,645,4,4,4,3,1,4,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +102981,48330,Male,disloyal Customer,28,Business travel,Eco,522,3,0,3,2,4,3,4,4,5,4,4,2,4,4,2,0.0,neutral or dissatisfied +102982,24949,Female,Loyal Customer,36,Business travel,Business,1747,4,2,4,4,4,3,4,5,5,5,5,4,5,3,23,15.0,satisfied +102983,58349,Male,Loyal Customer,65,Personal Travel,Eco,296,4,5,4,1,3,4,3,3,3,2,4,5,4,3,1,0.0,neutral or dissatisfied +102984,71676,Male,Loyal Customer,66,Personal Travel,Eco,1197,2,3,2,1,4,2,3,4,4,4,1,5,3,4,0,0.0,neutral or dissatisfied +102985,14127,Male,disloyal Customer,46,Business travel,Eco,413,4,5,4,4,4,4,1,4,3,3,3,5,2,4,17,16.0,neutral or dissatisfied +102986,1408,Female,Loyal Customer,21,Personal Travel,Eco Plus,89,1,4,0,1,4,0,4,4,3,4,3,5,2,4,0,0.0,neutral or dissatisfied +102987,33035,Male,Loyal Customer,51,Personal Travel,Eco,102,4,5,4,5,4,4,3,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +102988,122693,Female,Loyal Customer,27,Personal Travel,Eco,361,2,4,2,1,1,2,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +102989,111857,Male,Loyal Customer,31,Business travel,Business,2554,4,4,4,4,5,5,5,5,4,3,4,3,4,5,28,3.0,satisfied +102990,123710,Male,Loyal Customer,24,Personal Travel,Eco,214,4,0,4,2,3,4,3,3,4,2,5,1,1,3,0,0.0,neutral or dissatisfied +102991,8919,Male,Loyal Customer,57,Business travel,Business,1741,4,4,4,4,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +102992,69992,Female,Loyal Customer,28,Personal Travel,Eco,236,2,3,0,4,2,0,2,2,2,2,3,3,3,2,0,2.0,neutral or dissatisfied +102993,6712,Female,Loyal Customer,14,Personal Travel,Eco,258,3,4,3,4,4,3,1,4,4,2,3,1,4,4,26,19.0,neutral or dissatisfied +102994,119504,Female,Loyal Customer,47,Business travel,Business,1854,3,2,3,3,2,5,4,4,4,4,4,5,4,3,0,14.0,satisfied +102995,35902,Male,Loyal Customer,8,Personal Travel,Eco Plus,1065,3,4,3,4,3,3,1,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +102996,99338,Female,Loyal Customer,21,Business travel,Business,1771,3,3,2,3,2,2,2,2,5,2,5,5,5,2,10,11.0,satisfied +102997,35041,Male,Loyal Customer,40,Business travel,Business,1584,4,4,4,4,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +102998,43461,Female,disloyal Customer,26,Business travel,Eco,624,0,0,1,2,3,1,4,3,3,1,4,1,4,3,0,0.0,satisfied +102999,110202,Female,Loyal Customer,21,Personal Travel,Eco Plus,979,3,5,3,1,2,3,2,2,3,5,5,3,4,2,0,3.0,neutral or dissatisfied +103000,77071,Female,disloyal Customer,47,Business travel,Business,991,4,4,4,4,1,4,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +103001,76074,Male,disloyal Customer,34,Business travel,Eco,669,1,1,1,3,5,1,5,5,3,3,4,3,3,5,0,0.0,neutral or dissatisfied +103002,129433,Male,disloyal Customer,26,Business travel,Business,414,4,4,4,5,2,4,2,2,4,2,5,5,5,2,0,0.0,satisfied +103003,14740,Male,Loyal Customer,55,Business travel,Eco,463,4,4,2,4,4,4,4,4,5,2,2,2,3,4,51,45.0,satisfied +103004,85345,Female,disloyal Customer,26,Business travel,Eco Plus,874,3,3,3,3,2,3,2,2,4,4,2,4,3,2,0,0.0,neutral or dissatisfied +103005,575,Female,Loyal Customer,54,Business travel,Business,2703,3,3,3,3,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +103006,42070,Female,Loyal Customer,65,Personal Travel,Eco,116,3,5,3,4,5,4,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +103007,19555,Male,disloyal Customer,33,Business travel,Eco,108,1,2,0,3,1,0,1,1,1,3,3,4,3,1,8,13.0,neutral or dissatisfied +103008,101354,Female,Loyal Customer,53,Business travel,Business,1986,4,5,5,5,1,3,3,4,4,4,4,3,4,3,16,0.0,neutral or dissatisfied +103009,47796,Female,Loyal Customer,56,Business travel,Business,2507,3,3,3,3,3,2,3,5,5,5,5,2,5,4,63,97.0,satisfied +103010,33124,Male,Loyal Customer,31,Personal Travel,Eco,101,3,5,3,1,3,3,3,3,3,5,5,3,4,3,23,34.0,neutral or dissatisfied +103011,121392,Male,Loyal Customer,48,Business travel,Business,2245,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +103012,70617,Male,Loyal Customer,24,Business travel,Business,3364,2,1,1,1,2,2,2,2,3,3,2,3,2,2,4,15.0,neutral or dissatisfied +103013,67995,Female,Loyal Customer,67,Personal Travel,Eco Plus,1171,3,4,3,2,2,3,4,3,3,3,3,4,3,3,0,2.0,neutral or dissatisfied +103014,60238,Male,disloyal Customer,35,Business travel,Eco,1455,2,1,1,2,4,2,4,4,4,5,1,2,2,4,18,14.0,neutral or dissatisfied +103015,78479,Female,Loyal Customer,56,Business travel,Business,2241,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,11.0,satisfied +103016,46097,Female,Loyal Customer,14,Personal Travel,Eco Plus,541,4,4,4,1,5,4,5,5,3,5,4,4,4,5,0,20.0,neutral or dissatisfied +103017,87386,Female,Loyal Customer,31,Business travel,Business,425,1,0,0,4,3,0,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +103018,46206,Female,Loyal Customer,53,Business travel,Business,679,2,4,4,4,2,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +103019,2236,Male,Loyal Customer,57,Personal Travel,Eco,642,1,4,0,4,4,0,4,4,3,2,5,4,5,4,0,13.0,neutral or dissatisfied +103020,59716,Male,Loyal Customer,56,Business travel,Business,964,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +103021,79554,Female,Loyal Customer,19,Business travel,Business,762,2,2,2,2,5,5,5,5,4,3,4,3,4,5,0,9.0,satisfied +103022,34456,Female,Loyal Customer,25,Personal Travel,Eco,228,4,5,4,1,1,4,3,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +103023,26794,Female,Loyal Customer,42,Business travel,Eco Plus,226,2,1,1,1,3,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +103024,54591,Male,Loyal Customer,41,Business travel,Business,854,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,2.0,satisfied +103025,125123,Female,Loyal Customer,31,Personal Travel,Eco,361,2,5,4,3,4,4,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +103026,15273,Female,Loyal Customer,39,Business travel,Business,3182,2,5,5,5,2,4,3,2,2,2,2,2,2,4,30,33.0,neutral or dissatisfied +103027,85800,Female,disloyal Customer,24,Business travel,Eco,126,2,3,2,1,2,2,2,2,2,5,2,5,3,2,0,0.0,neutral or dissatisfied +103028,24721,Male,disloyal Customer,32,Business travel,Eco,406,1,0,1,3,3,1,2,3,1,5,2,3,5,3,0,3.0,neutral or dissatisfied +103029,126860,Female,Loyal Customer,37,Personal Travel,Eco,2296,2,1,2,3,2,2,2,2,1,1,3,4,2,2,103,85.0,neutral or dissatisfied +103030,91933,Male,disloyal Customer,26,Business travel,Eco,2586,3,4,4,3,5,3,3,5,2,2,4,3,3,5,42,16.0,neutral or dissatisfied +103031,95194,Male,Loyal Customer,67,Personal Travel,Eco,562,1,2,1,2,1,1,1,1,1,1,2,3,3,1,18,21.0,neutral or dissatisfied +103032,109523,Male,disloyal Customer,22,Business travel,Eco,861,2,2,2,2,2,2,2,2,4,4,2,1,1,2,49,38.0,neutral or dissatisfied +103033,102503,Female,Loyal Customer,15,Personal Travel,Eco,197,1,1,0,3,5,0,5,5,2,2,4,3,4,5,16,6.0,neutral or dissatisfied +103034,28721,Female,Loyal Customer,65,Personal Travel,Eco,2717,1,4,1,2,1,1,4,5,3,3,4,4,5,4,1,25.0,neutral or dissatisfied +103035,4948,Female,Loyal Customer,70,Personal Travel,Business,931,3,4,3,4,3,3,3,5,5,3,3,1,5,4,5,6.0,neutral or dissatisfied +103036,128636,Female,Loyal Customer,23,Personal Travel,Eco,679,1,4,1,4,5,1,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +103037,76336,Female,Loyal Customer,47,Business travel,Business,1724,3,3,3,3,4,3,3,3,3,3,3,1,3,4,4,0.0,neutral or dissatisfied +103038,42908,Male,Loyal Customer,31,Personal Travel,Eco,200,2,4,2,2,3,2,3,3,4,2,4,4,5,3,116,111.0,neutral or dissatisfied +103039,35474,Female,Loyal Customer,21,Personal Travel,Eco,1041,4,4,4,5,2,4,2,2,5,2,4,4,5,2,9,0.0,neutral or dissatisfied +103040,114565,Male,Loyal Customer,55,Personal Travel,Business,371,1,1,1,2,3,1,2,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +103041,82574,Male,Loyal Customer,59,Business travel,Business,2140,5,5,5,5,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +103042,75118,Male,Loyal Customer,43,Business travel,Eco,1744,2,3,3,3,2,2,2,2,1,1,1,2,3,2,38,39.0,neutral or dissatisfied +103043,17841,Male,Loyal Customer,45,Business travel,Business,2828,1,1,1,1,5,3,4,5,5,5,5,5,5,4,17,3.0,satisfied +103044,83902,Male,Loyal Customer,66,Personal Travel,Eco,1678,3,2,3,2,4,3,4,4,4,3,2,3,2,4,0,0.0,neutral or dissatisfied +103045,33191,Female,Loyal Customer,31,Business travel,Eco Plus,101,5,5,5,5,5,5,5,5,3,2,5,2,4,5,0,0.0,satisfied +103046,126467,Male,Loyal Customer,29,Business travel,Business,1849,1,1,1,1,5,5,5,5,4,2,4,5,5,5,0,8.0,satisfied +103047,70625,Female,Loyal Customer,37,Business travel,Business,817,1,1,1,1,1,4,1,3,3,3,3,2,3,3,0,0.0,satisfied +103048,121421,Male,Loyal Customer,47,Business travel,Business,290,2,1,2,2,5,5,5,4,4,4,4,5,4,4,49,35.0,satisfied +103049,90651,Female,Loyal Customer,57,Business travel,Business,240,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,5.0,satisfied +103050,54819,Male,disloyal Customer,26,Business travel,Eco,862,1,1,1,1,1,3,3,1,5,3,1,3,5,3,146,135.0,neutral or dissatisfied +103051,4740,Female,Loyal Customer,40,Business travel,Eco,488,4,1,1,1,4,4,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +103052,64199,Female,disloyal Customer,48,Business travel,Eco,853,3,3,3,3,5,3,5,5,3,3,3,3,4,5,13,24.0,neutral or dissatisfied +103053,60013,Female,Loyal Customer,63,Personal Travel,Eco,1085,3,5,3,5,3,5,5,1,1,3,1,2,1,2,0,0.0,neutral or dissatisfied +103054,97673,Male,Loyal Customer,36,Business travel,Business,491,2,1,1,1,4,4,3,2,2,2,2,2,2,2,33,28.0,neutral or dissatisfied +103055,45515,Female,Loyal Customer,27,Personal Travel,Business,689,1,4,0,2,4,0,4,4,3,5,5,5,5,4,13,3.0,neutral or dissatisfied +103056,9629,Female,Loyal Customer,54,Personal Travel,Eco Plus,288,5,4,5,2,4,5,5,3,3,5,3,3,3,4,0,0.0,satisfied +103057,15346,Female,Loyal Customer,58,Business travel,Business,1897,1,1,1,1,3,4,4,5,5,5,5,5,5,3,46,40.0,satisfied +103058,54158,Female,Loyal Customer,37,Business travel,Business,1400,4,4,5,4,1,5,1,5,5,5,5,1,5,3,0,0.0,satisfied +103059,96397,Male,Loyal Customer,51,Business travel,Business,1407,3,3,3,3,3,4,5,5,5,5,5,3,5,5,0,1.0,satisfied +103060,45053,Female,disloyal Customer,22,Business travel,Business,265,0,3,0,2,4,0,4,4,2,3,1,1,3,4,35,29.0,satisfied +103061,77664,Female,disloyal Customer,29,Business travel,Business,696,1,1,1,3,3,1,3,3,3,2,4,5,5,3,0,0.0,neutral or dissatisfied +103062,111568,Male,Loyal Customer,43,Business travel,Eco,883,1,1,1,1,1,1,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +103063,115136,Female,Loyal Customer,47,Business travel,Business,3756,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +103064,106688,Male,Loyal Customer,30,Personal Travel,Business,516,3,5,3,2,5,3,4,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +103065,109812,Female,Loyal Customer,50,Business travel,Business,1011,3,3,3,3,3,5,4,4,4,4,4,5,4,4,58,42.0,satisfied +103066,61301,Female,Loyal Customer,64,Personal Travel,Eco,862,5,2,5,4,5,3,3,1,1,2,1,2,1,3,0,0.0,satisfied +103067,40175,Female,Loyal Customer,41,Business travel,Eco,347,5,3,3,3,5,5,5,5,2,1,4,4,2,5,0,0.0,satisfied +103068,2425,Male,Loyal Customer,15,Personal Travel,Eco,604,3,3,3,1,3,3,3,3,5,5,1,5,3,3,0,10.0,neutral or dissatisfied +103069,31685,Female,Loyal Customer,55,Business travel,Eco,846,3,4,4,4,1,4,3,3,3,3,3,4,3,2,51,40.0,neutral or dissatisfied +103070,90309,Female,Loyal Customer,53,Business travel,Business,2443,1,4,1,1,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +103071,6902,Male,disloyal Customer,25,Business travel,Eco,265,3,4,3,3,4,3,1,4,2,4,4,4,4,4,5,0.0,neutral or dissatisfied +103072,113267,Female,Loyal Customer,47,Business travel,Business,236,3,3,3,3,4,4,5,4,4,4,4,3,4,3,36,33.0,satisfied +103073,75284,Female,disloyal Customer,38,Business travel,Business,1846,2,2,2,3,5,2,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +103074,56769,Female,disloyal Customer,48,Business travel,Eco Plus,937,2,2,2,4,1,2,1,1,1,3,4,3,4,1,0,0.0,neutral or dissatisfied +103075,96597,Male,Loyal Customer,24,Personal Travel,Eco,861,3,4,3,1,5,3,5,5,4,5,5,3,4,5,0,3.0,neutral or dissatisfied +103076,74510,Male,Loyal Customer,57,Business travel,Business,2215,2,2,2,2,4,4,5,5,5,5,5,5,5,3,23,25.0,satisfied +103077,38904,Male,disloyal Customer,24,Business travel,Eco,320,3,3,3,1,4,3,3,4,1,2,5,4,4,4,0,0.0,neutral or dissatisfied +103078,129061,Female,Loyal Customer,27,Personal Travel,Eco,1744,3,4,3,2,3,3,4,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +103079,125271,Female,disloyal Customer,23,Business travel,Eco,1353,3,3,3,4,4,3,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +103080,125021,Male,Loyal Customer,38,Personal Travel,Eco,184,1,5,0,3,1,0,1,1,4,3,5,4,5,1,45,38.0,neutral or dissatisfied +103081,3084,Male,Loyal Customer,49,Business travel,Business,1703,4,4,4,4,4,4,5,2,2,2,2,5,2,3,54,53.0,satisfied +103082,70790,Female,disloyal Customer,36,Business travel,Business,328,3,3,3,3,2,3,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +103083,123272,Female,disloyal Customer,36,Personal Travel,Eco,631,3,1,3,3,3,3,2,3,1,4,4,4,4,3,0,0.0,neutral or dissatisfied +103084,82639,Female,Loyal Customer,48,Business travel,Eco Plus,128,4,2,2,2,2,1,2,4,4,4,4,2,4,5,0,0.0,satisfied +103085,30850,Male,Loyal Customer,8,Business travel,Eco,841,3,1,1,1,3,3,1,3,1,2,3,2,4,3,24,19.0,neutral or dissatisfied +103086,8010,Female,Loyal Customer,43,Business travel,Business,335,4,4,4,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +103087,123364,Male,Loyal Customer,23,Business travel,Business,644,3,3,3,3,3,3,3,3,2,3,3,1,4,3,39,22.0,neutral or dissatisfied +103088,125681,Male,Loyal Customer,47,Business travel,Business,814,5,5,5,5,4,5,5,4,4,4,4,3,4,5,47,45.0,satisfied +103089,23502,Male,Loyal Customer,28,Business travel,Business,303,2,2,2,2,4,4,4,4,2,4,4,2,2,4,0,3.0,satisfied +103090,115828,Male,disloyal Customer,40,Business travel,Eco,308,4,0,4,3,1,4,1,1,2,3,4,3,1,1,0,0.0,neutral or dissatisfied +103091,123178,Female,disloyal Customer,20,Business travel,Eco,416,2,3,2,4,5,2,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +103092,36344,Female,Loyal Customer,58,Personal Travel,Eco,187,1,4,1,3,2,4,5,3,3,1,3,4,3,4,12,48.0,neutral or dissatisfied +103093,56202,Male,Loyal Customer,44,Business travel,Business,1400,5,5,5,5,4,4,4,4,4,5,5,4,5,4,149,108.0,satisfied +103094,124649,Male,Loyal Customer,45,Personal Travel,Business,399,3,1,3,3,3,3,2,3,3,3,3,4,3,4,30,22.0,neutral or dissatisfied +103095,38873,Female,Loyal Customer,45,Business travel,Business,1582,1,1,1,1,5,3,2,4,4,4,4,1,4,3,0,0.0,satisfied +103096,39645,Male,Loyal Customer,36,Business travel,Business,2465,4,4,4,4,1,4,4,4,4,4,4,1,4,3,12,10.0,satisfied +103097,5261,Male,Loyal Customer,49,Business travel,Eco,383,2,3,3,3,2,2,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +103098,102237,Male,Loyal Customer,60,Business travel,Business,236,0,1,1,4,3,4,4,4,4,4,4,5,4,3,13,3.0,satisfied +103099,94951,Male,disloyal Customer,30,Business travel,Eco,187,1,2,1,4,4,1,3,4,2,4,4,2,3,4,21,17.0,neutral or dissatisfied +103100,12075,Female,Loyal Customer,36,Business travel,Eco Plus,376,5,4,4,4,5,5,5,5,3,5,4,5,3,5,10,10.0,satisfied +103101,99964,Female,Loyal Customer,48,Business travel,Business,3874,2,2,2,2,2,4,5,2,2,2,2,5,2,5,123,96.0,satisfied +103102,52766,Male,disloyal Customer,43,Business travel,Eco,1874,3,3,3,1,3,3,5,3,2,4,3,2,2,3,0,0.0,neutral or dissatisfied +103103,101102,Female,Loyal Customer,51,Business travel,Business,3768,5,5,5,5,4,4,5,5,5,5,5,5,5,5,38,26.0,satisfied +103104,98413,Female,Loyal Customer,30,Business travel,Eco Plus,675,3,2,2,2,3,3,3,3,4,3,4,3,3,3,72,61.0,neutral or dissatisfied +103105,4463,Female,Loyal Customer,33,Business travel,Business,1005,2,3,3,3,5,3,3,2,2,1,2,2,2,1,0,26.0,neutral or dissatisfied +103106,71269,Male,Loyal Customer,68,Personal Travel,Eco,733,3,3,3,4,2,3,2,2,2,5,2,5,3,2,0,0.0,neutral or dissatisfied +103107,119147,Female,Loyal Customer,18,Personal Travel,Eco Plus,119,2,4,0,1,5,0,5,5,5,3,5,5,1,5,1,11.0,neutral or dissatisfied +103108,120034,Male,Loyal Customer,32,Personal Travel,Eco Plus,328,1,3,1,2,5,1,5,5,3,3,3,5,1,5,0,0.0,neutral or dissatisfied +103109,75201,Female,Loyal Customer,22,Business travel,Business,1846,3,2,2,2,3,3,3,3,1,2,3,3,3,3,0,7.0,neutral or dissatisfied +103110,64068,Female,disloyal Customer,21,Business travel,Eco,521,5,0,5,2,1,5,1,1,3,1,2,3,3,1,0,0.0,satisfied +103111,45078,Female,Loyal Customer,51,Business travel,Business,188,4,4,3,4,2,2,5,4,4,4,3,2,4,1,0,8.0,satisfied +103112,24522,Female,Loyal Customer,57,Business travel,Business,892,2,2,5,2,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +103113,96188,Female,Loyal Customer,43,Business travel,Eco,666,3,5,5,5,3,4,4,3,3,3,3,2,3,3,12,10.0,neutral or dissatisfied +103114,99128,Female,Loyal Customer,34,Personal Travel,Eco,237,1,5,1,2,4,1,4,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +103115,33562,Male,Loyal Customer,45,Business travel,Eco,399,3,4,4,4,3,3,3,3,5,4,1,5,2,3,0,0.0,satisfied +103116,10050,Female,Loyal Customer,16,Business travel,Business,326,2,3,3,3,2,2,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +103117,1130,Female,Loyal Customer,15,Personal Travel,Eco,354,1,2,1,3,4,1,4,4,1,3,4,1,4,4,14,12.0,neutral or dissatisfied +103118,13925,Male,Loyal Customer,43,Business travel,Eco,192,4,4,4,4,4,4,4,4,2,2,1,3,2,4,45,29.0,satisfied +103119,44997,Male,Loyal Customer,55,Business travel,Business,3178,1,5,5,5,5,4,4,4,4,4,1,4,4,2,4,10.0,neutral or dissatisfied +103120,114943,Female,Loyal Customer,59,Business travel,Business,337,2,2,1,2,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +103121,127365,Male,disloyal Customer,28,Business travel,Business,1009,1,1,1,1,2,1,5,2,4,3,4,3,4,2,0,7.0,neutral or dissatisfied +103122,80307,Female,disloyal Customer,23,Business travel,Eco,746,1,1,1,3,3,1,3,3,4,5,4,4,3,3,0,23.0,neutral or dissatisfied +103123,111702,Male,Loyal Customer,12,Business travel,Business,495,3,5,5,5,3,3,3,3,2,5,4,1,4,3,31,24.0,neutral or dissatisfied +103124,101295,Male,Loyal Customer,28,Personal Travel,Eco,763,4,5,4,3,3,4,2,3,4,2,5,4,5,3,5,0.0,neutral or dissatisfied +103125,9757,Male,Loyal Customer,29,Personal Travel,Business,383,2,5,5,1,4,5,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +103126,55377,Female,Loyal Customer,50,Business travel,Eco,678,2,1,4,4,3,3,4,2,2,2,2,3,2,4,82,128.0,neutral or dissatisfied +103127,1860,Male,Loyal Customer,39,Business travel,Business,2609,5,5,3,5,5,4,5,4,4,4,4,5,4,4,44,42.0,satisfied +103128,73384,Male,Loyal Customer,60,Business travel,Business,2361,3,2,3,3,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +103129,27247,Female,disloyal Customer,28,Business travel,Eco Plus,1024,0,0,0,3,3,0,3,3,2,4,3,5,4,3,30,24.0,satisfied +103130,84518,Male,Loyal Customer,39,Business travel,Business,2504,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +103131,16476,Male,Loyal Customer,51,Business travel,Eco Plus,416,2,3,3,3,2,2,2,2,2,2,4,4,3,2,0,0.0,neutral or dissatisfied +103132,32285,Female,Loyal Customer,36,Business travel,Business,1649,1,1,1,1,1,5,3,5,5,5,5,2,5,3,0,0.0,satisfied +103133,51736,Female,Loyal Customer,62,Personal Travel,Eco,598,2,0,1,4,4,5,5,1,1,1,1,4,1,3,0,3.0,neutral or dissatisfied +103134,97066,Male,Loyal Customer,29,Business travel,Business,1642,1,1,1,1,4,4,4,4,5,3,4,3,4,4,0,0.0,satisfied +103135,31994,Female,Loyal Customer,33,Personal Travel,Business,102,3,4,3,2,3,1,3,2,2,3,2,4,2,4,13,25.0,neutral or dissatisfied +103136,39474,Female,Loyal Customer,52,Business travel,Business,2066,3,3,3,3,1,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +103137,114702,Male,disloyal Customer,26,Business travel,Business,337,1,0,1,2,5,1,5,5,4,3,5,5,4,5,66,49.0,neutral or dissatisfied +103138,22868,Female,Loyal Customer,61,Personal Travel,Eco,302,2,3,2,2,3,2,1,1,1,2,1,4,1,5,15,14.0,neutral or dissatisfied +103139,67091,Male,Loyal Customer,42,Business travel,Business,2140,1,1,1,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +103140,64081,Male,Loyal Customer,62,Personal Travel,Eco,919,4,5,5,5,4,5,4,4,4,5,4,5,4,4,0,2.0,neutral or dissatisfied +103141,68568,Female,Loyal Customer,52,Business travel,Business,1616,2,2,2,2,5,4,5,5,5,5,5,3,5,3,11,0.0,satisfied +103142,76518,Male,Loyal Customer,41,Business travel,Eco,481,1,3,3,3,1,1,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +103143,48572,Female,Loyal Customer,38,Personal Travel,Eco,845,3,4,3,5,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +103144,22994,Male,Loyal Customer,28,Personal Travel,Eco,489,3,1,3,3,1,3,1,1,2,3,3,3,3,1,24,21.0,neutral or dissatisfied +103145,1270,Female,Loyal Customer,40,Personal Travel,Eco,354,1,3,1,3,5,1,5,5,3,1,3,5,2,5,47,54.0,neutral or dissatisfied +103146,115213,Male,Loyal Customer,55,Business travel,Business,371,5,5,5,5,2,5,5,4,4,5,4,4,4,4,9,3.0,satisfied +103147,24281,Female,Loyal Customer,49,Personal Travel,Eco,134,5,3,5,4,3,3,3,4,4,5,4,1,4,2,1,2.0,satisfied +103148,93035,Female,disloyal Customer,40,Business travel,Business,317,2,2,2,3,4,2,3,4,3,3,4,5,5,4,53,49.0,neutral or dissatisfied +103149,25653,Female,Loyal Customer,44,Business travel,Eco Plus,526,5,1,1,1,4,2,2,4,4,5,4,2,4,1,0,0.0,satisfied +103150,33364,Male,Loyal Customer,37,Business travel,Eco,1114,2,5,5,5,2,2,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +103151,61685,Female,disloyal Customer,28,Business travel,Eco,1018,2,2,2,4,3,2,3,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +103152,82782,Male,disloyal Customer,24,Business travel,Business,231,0,0,0,4,0,4,4,4,4,5,4,4,4,4,168,178.0,satisfied +103153,7451,Female,Loyal Customer,25,Personal Travel,Eco,522,4,5,4,5,1,4,1,1,3,5,4,5,5,1,0,0.0,neutral or dissatisfied +103154,54906,Male,Loyal Customer,36,Business travel,Business,934,1,1,1,1,3,5,4,1,1,2,1,3,1,4,0,0.0,satisfied +103155,25795,Male,Loyal Customer,37,Business travel,Eco,362,5,3,3,3,5,5,5,5,5,1,5,4,3,5,0,0.0,satisfied +103156,57066,Female,Loyal Customer,60,Business travel,Business,2065,3,3,3,3,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +103157,100592,Male,Loyal Customer,38,Personal Travel,Eco,486,3,0,3,4,2,3,2,2,4,4,2,2,3,2,13,4.0,neutral or dissatisfied +103158,120056,Female,Loyal Customer,13,Personal Travel,Eco,237,1,4,0,3,3,0,5,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +103159,2379,Male,Loyal Customer,44,Business travel,Business,604,5,4,5,5,4,4,4,1,1,2,1,4,1,4,18,0.0,satisfied +103160,40405,Female,Loyal Customer,39,Business travel,Business,188,1,1,1,1,2,4,1,4,4,5,4,2,4,3,3,0.0,satisfied +103161,105528,Male,Loyal Customer,47,Business travel,Business,3777,1,1,1,1,3,4,4,5,5,5,5,3,5,5,27,22.0,satisfied +103162,63821,Female,disloyal Customer,8,Business travel,Business,1158,3,4,3,3,1,3,1,1,2,5,4,1,3,1,0,0.0,neutral or dissatisfied +103163,43517,Female,disloyal Customer,29,Business travel,Eco Plus,679,4,4,4,1,4,4,4,4,3,1,5,4,5,4,0,0.0,satisfied +103164,48604,Male,Loyal Customer,22,Personal Travel,Eco,763,2,4,3,2,2,3,2,2,5,2,4,5,5,2,0,2.0,neutral or dissatisfied +103165,32831,Male,Loyal Customer,35,Business travel,Eco,101,5,1,1,1,5,5,5,5,1,4,2,5,1,5,0,0.0,satisfied +103166,31088,Female,Loyal Customer,60,Business travel,Eco,1014,4,5,2,5,1,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +103167,112875,Male,Loyal Customer,52,Business travel,Business,2627,4,4,4,4,3,4,5,5,5,5,5,3,5,3,3,0.0,satisfied +103168,78527,Male,Loyal Customer,64,Personal Travel,Eco,620,3,4,4,1,3,4,3,3,4,3,4,5,4,3,6,32.0,neutral or dissatisfied +103169,3352,Male,Loyal Customer,57,Business travel,Business,3157,0,0,0,4,5,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +103170,124813,Female,Loyal Customer,67,Business travel,Eco,280,4,3,3,3,2,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +103171,21387,Female,Loyal Customer,36,Personal Travel,Business,399,3,4,3,1,5,4,5,3,3,3,3,4,3,4,96,90.0,neutral or dissatisfied +103172,26536,Female,Loyal Customer,54,Business travel,Business,3665,4,4,4,4,3,5,3,4,4,4,4,1,4,3,0,0.0,satisfied +103173,107268,Male,disloyal Customer,27,Business travel,Business,307,5,5,5,1,3,5,3,3,4,5,4,4,5,3,15,12.0,satisfied +103174,76641,Female,Loyal Customer,49,Personal Travel,Eco,516,4,4,1,3,2,4,1,5,5,1,5,1,5,3,0,12.0,neutral or dissatisfied +103175,305,Male,Loyal Customer,56,Business travel,Business,2204,1,1,1,1,4,4,5,4,4,4,4,5,4,4,55,49.0,satisfied +103176,26371,Male,Loyal Customer,41,Business travel,Eco,930,1,4,4,4,1,1,1,1,1,3,3,1,4,1,18,10.0,neutral or dissatisfied +103177,102652,Male,Loyal Customer,29,Business travel,Business,601,2,2,2,2,4,4,4,4,5,5,4,3,4,4,11,0.0,satisfied +103178,23216,Female,Loyal Customer,48,Business travel,Eco,326,2,2,2,2,5,3,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +103179,59330,Male,Loyal Customer,48,Business travel,Business,2486,1,1,1,1,2,3,5,4,4,4,4,3,4,5,12,0.0,satisfied +103180,49267,Male,Loyal Customer,36,Business travel,Eco,266,4,1,1,1,4,4,4,4,2,5,4,4,3,4,1,2.0,satisfied +103181,12807,Male,Loyal Customer,38,Business travel,Business,1867,1,4,1,1,4,4,5,4,4,4,4,5,4,1,0,0.0,satisfied +103182,103270,Female,Loyal Customer,12,Personal Travel,Eco,888,2,2,1,1,2,1,2,2,3,2,1,4,2,2,3,25.0,neutral or dissatisfied +103183,29501,Female,Loyal Customer,19,Personal Travel,Eco,1107,3,3,3,4,4,3,4,4,4,4,2,5,3,4,0,0.0,neutral or dissatisfied +103184,104017,Male,disloyal Customer,22,Business travel,Business,1262,4,0,3,3,5,3,5,5,5,3,5,4,5,5,9,11.0,satisfied +103185,79698,Male,Loyal Customer,37,Personal Travel,Eco,760,2,5,2,1,1,2,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +103186,74568,Female,Loyal Customer,43,Business travel,Business,1438,4,3,3,3,2,3,4,4,4,4,4,4,4,4,29,7.0,neutral or dissatisfied +103187,6222,Female,Loyal Customer,55,Business travel,Business,678,2,2,2,2,1,3,4,2,2,2,2,2,2,1,0,11.0,neutral or dissatisfied +103188,70753,Female,Loyal Customer,52,Business travel,Business,733,5,5,5,5,4,4,4,5,5,5,5,4,5,5,20,75.0,satisfied +103189,62455,Female,Loyal Customer,44,Business travel,Business,1846,3,4,4,4,1,4,4,3,3,3,3,2,3,2,11,0.0,neutral or dissatisfied +103190,1362,Female,Loyal Customer,38,Business travel,Business,134,0,5,0,4,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +103191,80915,Female,disloyal Customer,26,Business travel,Eco,352,2,2,1,3,2,1,5,2,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +103192,65176,Female,Loyal Customer,47,Personal Travel,Eco,190,3,4,3,2,5,5,5,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +103193,61090,Male,Loyal Customer,31,Personal Travel,Eco,1607,1,4,1,4,5,1,3,5,3,3,4,5,4,5,0,0.0,neutral or dissatisfied +103194,207,Female,Loyal Customer,40,Business travel,Business,213,0,5,0,5,5,4,5,4,4,1,1,3,4,3,0,0.0,satisfied +103195,117258,Male,Loyal Customer,53,Personal Travel,Eco,304,4,4,5,4,4,5,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +103196,73209,Male,Loyal Customer,11,Personal Travel,Eco,1258,4,4,4,3,3,4,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +103197,10075,Female,Loyal Customer,57,Business travel,Business,2390,4,4,4,4,3,4,4,2,2,3,2,3,2,5,0,16.0,satisfied +103198,80138,Female,Loyal Customer,55,Business travel,Business,2586,4,5,4,4,5,5,5,3,5,4,5,5,3,5,0,0.0,satisfied +103199,72648,Female,disloyal Customer,61,Personal Travel,Eco,1121,2,5,2,4,5,2,5,5,4,4,3,3,3,5,2,0.0,neutral or dissatisfied +103200,10865,Male,disloyal Customer,61,Business travel,Business,316,4,4,4,5,5,4,5,5,5,4,5,3,4,5,0,2.0,satisfied +103201,55361,Male,Loyal Customer,50,Business travel,Business,594,1,5,3,5,5,4,4,1,1,1,1,4,1,4,0,2.0,neutral or dissatisfied +103202,101037,Male,Loyal Customer,40,Personal Travel,Eco Plus,867,3,5,3,3,1,3,1,1,3,5,5,5,5,1,87,93.0,neutral or dissatisfied +103203,110640,Male,Loyal Customer,39,Personal Travel,Business,837,2,2,2,4,2,4,4,4,4,2,4,3,4,1,76,68.0,neutral or dissatisfied +103204,87313,Female,disloyal Customer,8,Business travel,Eco,577,3,4,3,3,2,3,3,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +103205,77237,Female,Loyal Customer,42,Business travel,Business,1590,4,4,4,4,2,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +103206,105688,Male,Loyal Customer,39,Business travel,Business,883,5,5,5,5,5,4,5,4,4,4,4,4,4,4,3,38.0,satisfied +103207,31252,Male,Loyal Customer,7,Personal Travel,Eco,524,4,5,4,2,4,4,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +103208,9078,Male,Loyal Customer,50,Personal Travel,Eco,108,1,5,0,2,5,0,4,5,5,2,4,5,4,5,0,8.0,neutral or dissatisfied +103209,124425,Male,Loyal Customer,20,Personal Travel,Eco,1044,5,4,5,3,4,5,4,4,1,5,4,2,1,4,0,0.0,satisfied +103210,128138,Male,Loyal Customer,51,Business travel,Business,1972,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +103211,16186,Female,Loyal Customer,46,Business travel,Eco,199,2,5,5,5,4,3,3,2,2,2,2,1,2,2,17,9.0,neutral or dissatisfied +103212,108878,Male,Loyal Customer,50,Business travel,Business,1066,3,3,3,3,2,5,5,5,5,5,5,3,5,5,9,0.0,satisfied +103213,127429,Male,Loyal Customer,28,Personal Travel,Eco,1009,3,5,3,1,1,3,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +103214,62526,Female,Loyal Customer,31,Business travel,Business,1744,2,3,3,3,2,2,2,2,2,2,3,3,4,2,1,24.0,neutral or dissatisfied +103215,85746,Male,Loyal Customer,38,Business travel,Business,3710,3,2,2,2,3,1,1,3,3,3,3,4,3,2,36,20.0,neutral or dissatisfied +103216,112778,Male,Loyal Customer,17,Personal Travel,Eco,590,3,4,3,1,4,3,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +103217,46570,Male,Loyal Customer,60,Business travel,Eco,125,1,4,5,5,1,1,1,1,2,5,4,1,3,1,0,8.0,neutral or dissatisfied +103218,73579,Male,Loyal Customer,48,Business travel,Business,204,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +103219,109389,Male,Loyal Customer,16,Personal Travel,Eco,1189,2,5,2,4,3,2,3,3,5,5,3,3,4,3,58,49.0,neutral or dissatisfied +103220,127462,Female,Loyal Customer,26,Business travel,Business,2075,5,1,5,5,4,4,4,4,3,5,3,4,4,4,15,0.0,satisfied +103221,34680,Male,Loyal Customer,20,Business travel,Eco,264,5,3,3,3,5,5,5,5,3,4,3,5,4,5,12,13.0,satisfied +103222,93858,Female,Loyal Customer,43,Business travel,Business,2082,1,1,2,1,5,4,5,4,4,5,4,4,4,4,8,0.0,satisfied +103223,64017,Female,Loyal Customer,49,Business travel,Business,921,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +103224,33701,Female,Loyal Customer,52,Business travel,Eco,899,2,1,1,1,3,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +103225,8356,Male,Loyal Customer,53,Business travel,Business,2777,2,2,3,2,3,4,4,2,2,2,2,1,2,3,34,40.0,neutral or dissatisfied +103226,16407,Female,Loyal Customer,58,Personal Travel,Eco,463,2,2,2,2,5,3,2,3,3,2,2,2,3,2,0,8.0,neutral or dissatisfied +103227,48875,Female,disloyal Customer,20,Business travel,Eco,421,3,0,3,1,3,3,4,3,3,4,2,1,3,3,0,0.0,neutral or dissatisfied +103228,28585,Female,Loyal Customer,16,Personal Travel,Eco,2562,2,4,2,3,5,2,4,5,5,1,3,3,4,5,0,0.0,neutral or dissatisfied +103229,75397,Female,Loyal Customer,31,Business travel,Business,2585,5,5,4,5,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +103230,57520,Female,Loyal Customer,42,Business travel,Business,3191,5,5,5,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +103231,39355,Male,disloyal Customer,21,Business travel,Eco,896,4,4,4,4,2,4,2,2,5,2,1,1,4,2,0,0.0,satisfied +103232,90678,Female,disloyal Customer,37,Business travel,Business,444,4,4,4,5,3,4,1,3,3,5,5,3,5,3,19,15.0,satisfied +103233,122483,Male,Loyal Customer,8,Personal Travel,Eco,575,2,5,2,3,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +103234,31217,Female,Loyal Customer,36,Personal Travel,Eco,628,2,4,2,3,3,2,3,3,5,2,4,5,4,3,83,77.0,neutral or dissatisfied +103235,57173,Female,Loyal Customer,30,Business travel,Business,2227,4,4,4,4,4,4,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +103236,66656,Female,Loyal Customer,45,Business travel,Business,3393,4,4,4,4,3,5,4,4,4,4,4,5,4,4,9,0.0,satisfied +103237,114757,Female,Loyal Customer,39,Business travel,Business,1922,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +103238,117980,Female,Loyal Customer,12,Personal Travel,Eco,255,2,3,2,4,4,2,4,4,3,1,5,5,3,4,1,7.0,neutral or dissatisfied +103239,115417,Male,Loyal Customer,33,Business travel,Business,2512,1,4,4,4,1,1,1,1,3,3,4,4,3,1,19,7.0,neutral or dissatisfied +103240,48394,Female,Loyal Customer,29,Personal Travel,Eco,674,4,5,4,4,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +103241,68890,Female,Loyal Customer,38,Business travel,Business,3963,1,1,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +103242,85500,Female,Loyal Customer,47,Personal Travel,Eco,214,3,4,3,3,5,5,4,3,3,3,3,3,3,5,2,0.0,neutral or dissatisfied +103243,116497,Female,Loyal Customer,70,Personal Travel,Eco,447,3,4,2,1,5,3,1,4,4,2,5,2,4,5,0,0.0,neutral or dissatisfied +103244,80283,Male,Loyal Customer,51,Business travel,Business,1888,5,5,5,5,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +103245,40358,Female,disloyal Customer,38,Business travel,Eco,1250,3,3,3,1,4,3,4,4,1,2,2,3,2,4,0,0.0,neutral or dissatisfied +103246,65299,Female,Loyal Customer,34,Personal Travel,Eco Plus,247,1,5,1,4,2,1,2,2,5,3,2,1,4,2,0,0.0,neutral or dissatisfied +103247,56447,Female,Loyal Customer,63,Personal Travel,Eco,719,2,4,2,5,3,5,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +103248,33184,Female,Loyal Customer,58,Business travel,Eco Plus,216,5,4,4,4,5,3,4,5,5,5,5,5,5,2,0,6.0,satisfied +103249,17736,Female,Loyal Customer,36,Business travel,Business,2550,3,3,3,3,4,4,5,5,5,5,5,3,5,5,5,13.0,satisfied +103250,110973,Female,disloyal Customer,20,Business travel,Eco,319,4,3,4,4,5,4,5,5,3,3,5,5,5,5,0,0.0,satisfied +103251,28234,Female,Loyal Customer,39,Business travel,Business,1009,5,5,5,5,2,2,5,5,5,5,5,1,5,1,0,0.0,satisfied +103252,12922,Female,disloyal Customer,36,Business travel,Eco,274,2,0,2,4,3,2,3,3,5,2,5,4,3,3,0,0.0,neutral or dissatisfied +103253,84244,Female,Loyal Customer,57,Personal Travel,Eco Plus,432,2,5,2,3,5,4,4,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +103254,39952,Male,Loyal Customer,49,Personal Travel,Eco,1086,4,2,4,4,4,4,4,4,3,4,4,3,4,4,0,0.0,satisfied +103255,42668,Male,Loyal Customer,54,Business travel,Eco,516,5,4,4,4,5,5,5,5,1,5,5,2,4,5,0,0.0,satisfied +103256,10480,Female,Loyal Customer,49,Business travel,Business,2726,1,1,1,1,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +103257,35921,Male,Loyal Customer,18,Business travel,Eco Plus,2248,5,2,2,2,5,5,3,5,4,5,3,5,5,5,0,2.0,satisfied +103258,100035,Male,Loyal Customer,56,Business travel,Business,1995,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +103259,66374,Male,Loyal Customer,30,Business travel,Eco Plus,986,2,5,2,2,2,3,2,2,4,1,4,2,4,2,0,1.0,neutral or dissatisfied +103260,20059,Female,Loyal Customer,55,Personal Travel,Eco,473,2,3,2,3,1,1,1,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +103261,14881,Female,Loyal Customer,17,Business travel,Business,2682,3,4,4,4,3,3,3,3,1,3,3,2,4,3,0,7.0,neutral or dissatisfied +103262,90971,Male,Loyal Customer,64,Business travel,Eco,145,4,1,1,1,4,4,4,4,5,4,4,1,5,4,0,18.0,satisfied +103263,40505,Male,Loyal Customer,10,Personal Travel,Eco,290,3,4,3,3,4,3,5,4,3,5,5,3,4,4,5,0.0,neutral or dissatisfied +103264,28957,Male,Loyal Customer,14,Business travel,Business,2961,1,3,3,3,1,1,1,1,1,3,2,3,2,1,10,17.0,neutral or dissatisfied +103265,7429,Male,Loyal Customer,54,Business travel,Business,122,2,3,3,3,2,4,3,2,2,1,2,1,2,2,36,28.0,neutral or dissatisfied +103266,8915,Female,disloyal Customer,25,Business travel,Business,661,3,4,3,4,5,3,3,5,3,4,4,3,4,5,16,14.0,neutral or dissatisfied +103267,28031,Female,Loyal Customer,52,Personal Travel,Eco Plus,763,3,3,3,4,5,1,1,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +103268,126760,Male,Loyal Customer,52,Personal Travel,Eco,2402,2,4,2,3,4,2,2,4,2,3,1,5,2,4,0,0.0,neutral or dissatisfied +103269,64654,Female,Loyal Customer,51,Business travel,Business,1506,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +103270,61722,Male,Loyal Customer,45,Business travel,Business,1635,5,4,5,5,3,4,4,4,4,4,4,3,4,4,9,3.0,satisfied +103271,124941,Female,Loyal Customer,26,Personal Travel,Eco,728,3,3,3,3,4,3,4,4,2,1,1,1,1,4,0,3.0,neutral or dissatisfied +103272,30694,Male,Loyal Customer,32,Business travel,Business,680,2,1,1,1,2,2,2,2,1,3,3,4,4,2,37,45.0,neutral or dissatisfied +103273,107384,Male,disloyal Customer,23,Business travel,Eco,725,3,3,3,2,5,3,5,5,4,5,5,4,5,5,29,15.0,neutral or dissatisfied +103274,53447,Female,Loyal Customer,25,Business travel,Business,2358,1,1,1,1,4,5,4,4,3,4,3,5,4,4,8,0.0,satisfied +103275,49489,Female,Loyal Customer,37,Business travel,Eco,89,5,1,4,4,5,5,5,5,3,4,3,4,1,5,0,0.0,satisfied +103276,89248,Male,Loyal Customer,16,Personal Travel,Eco Plus,1947,3,5,3,4,4,3,4,4,4,2,3,5,5,4,0,13.0,neutral or dissatisfied +103277,3584,Female,Loyal Customer,48,Business travel,Business,1569,3,1,1,1,5,3,4,3,3,3,3,1,3,1,0,2.0,neutral or dissatisfied +103278,81846,Male,Loyal Customer,48,Personal Travel,Eco,1487,3,4,3,2,1,3,1,1,3,3,5,3,5,1,30,24.0,neutral or dissatisfied +103279,94217,Female,Loyal Customer,47,Business travel,Business,187,1,1,1,1,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +103280,73682,Male,Loyal Customer,52,Business travel,Business,2285,4,2,2,2,1,4,3,3,3,3,4,3,3,2,0,0.0,neutral or dissatisfied +103281,34005,Male,disloyal Customer,9,Business travel,Eco,813,3,4,4,4,3,4,2,1,4,2,4,2,3,2,360,347.0,neutral or dissatisfied +103282,34818,Female,Loyal Customer,20,Personal Travel,Eco,264,2,4,2,3,3,2,3,3,2,4,4,4,3,3,0,0.0,neutral or dissatisfied +103283,31933,Male,disloyal Customer,35,Business travel,Business,102,3,3,3,2,3,3,3,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +103284,20387,Male,Loyal Customer,29,Business travel,Eco,588,4,1,1,1,4,4,4,4,1,5,4,2,5,4,5,0.0,satisfied +103285,36515,Male,Loyal Customer,28,Business travel,Business,2529,4,4,4,4,2,2,2,2,3,2,2,4,1,2,3,0.0,satisfied +103286,73804,Male,Loyal Customer,27,Business travel,Eco Plus,192,5,1,1,1,5,5,5,5,1,2,1,3,4,5,0,0.0,satisfied +103287,30900,Male,Loyal Customer,58,Business travel,Eco,896,2,4,5,4,2,2,2,2,3,4,1,5,5,2,0,0.0,satisfied +103288,13427,Female,disloyal Customer,37,Business travel,Eco,409,3,0,3,3,5,3,5,5,2,4,4,3,1,5,0,0.0,neutral or dissatisfied +103289,8796,Male,Loyal Customer,27,Business travel,Business,1839,2,5,1,5,2,3,2,2,2,4,3,4,3,2,50,57.0,neutral or dissatisfied +103290,19289,Female,disloyal Customer,39,Business travel,Business,299,4,4,4,3,2,4,2,2,4,3,2,4,3,2,89,107.0,neutral or dissatisfied +103291,38936,Female,Loyal Customer,66,Personal Travel,Eco,320,1,5,1,5,3,2,3,4,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +103292,113742,Female,Loyal Customer,10,Personal Travel,Eco,258,4,4,4,4,1,4,1,1,4,3,2,2,4,1,0,0.0,satisfied +103293,126159,Male,Loyal Customer,34,Business travel,Business,3108,4,3,3,3,1,3,3,4,4,3,4,4,4,3,0,3.0,neutral or dissatisfied +103294,9819,Male,Loyal Customer,56,Business travel,Business,451,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,21.0,satisfied +103295,113029,Female,Loyal Customer,29,Business travel,Business,3586,3,3,5,3,4,4,4,4,4,5,5,5,4,4,53,46.0,satisfied +103296,61701,Male,disloyal Customer,25,Business travel,Eco,1635,2,2,2,2,5,2,2,5,1,1,2,3,3,5,9,7.0,neutral or dissatisfied +103297,27014,Female,Loyal Customer,47,Personal Travel,Eco,867,2,5,2,4,1,1,2,4,4,2,1,4,4,1,0,0.0,neutral or dissatisfied +103298,129031,Female,Loyal Customer,31,Business travel,Business,1846,1,1,1,1,4,5,5,4,3,4,5,5,3,5,171,194.0,satisfied +103299,48487,Female,disloyal Customer,36,Business travel,Eco,964,3,3,3,1,4,3,3,4,5,4,5,5,1,4,42,37.0,neutral or dissatisfied +103300,45781,Female,disloyal Customer,39,Business travel,Business,391,5,5,5,1,4,5,4,4,4,4,5,4,1,4,88,79.0,satisfied +103301,40783,Female,disloyal Customer,25,Business travel,Eco,541,3,1,3,4,5,3,5,5,4,2,3,3,3,5,0,3.0,neutral or dissatisfied +103302,35833,Female,Loyal Customer,40,Business travel,Eco,1023,2,4,3,4,2,1,2,2,3,4,4,3,3,2,7,0.0,neutral or dissatisfied +103303,80763,Female,Loyal Customer,28,Business travel,Eco,629,4,2,2,2,4,4,4,4,2,1,3,1,3,4,114,103.0,neutral or dissatisfied +103304,95727,Female,Loyal Customer,42,Business travel,Business,181,0,4,1,1,4,5,5,3,3,3,3,4,3,4,7,0.0,satisfied +103305,21571,Female,Loyal Customer,46,Business travel,Eco Plus,164,3,3,3,3,3,4,3,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +103306,53918,Female,Loyal Customer,46,Business travel,Eco Plus,191,5,1,1,1,1,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +103307,32228,Male,Loyal Customer,49,Business travel,Business,3539,2,2,2,2,4,3,3,5,5,5,3,5,5,1,0,0.0,satisfied +103308,120576,Female,Loyal Customer,48,Personal Travel,Eco Plus,2176,1,1,1,3,4,4,4,5,5,1,3,2,5,4,0,0.0,neutral or dissatisfied +103309,125445,Female,Loyal Customer,59,Business travel,Business,2845,4,4,4,4,4,3,4,4,4,4,4,4,4,4,15,7.0,satisfied +103310,99564,Female,Loyal Customer,30,Business travel,Business,808,2,2,2,2,3,3,3,3,4,4,5,5,4,3,0,0.0,satisfied +103311,65391,Male,Loyal Customer,37,Personal Travel,Eco,432,4,4,4,1,2,4,1,2,5,2,5,4,4,2,103,103.0,neutral or dissatisfied +103312,21478,Male,Loyal Customer,53,Business travel,Eco,331,3,2,3,2,3,3,3,3,2,3,2,1,3,3,0,0.0,neutral or dissatisfied +103313,69023,Female,Loyal Customer,42,Business travel,Business,1389,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +103314,113776,Male,Loyal Customer,48,Personal Travel,Eco,386,4,5,4,4,3,4,3,3,3,3,4,5,5,3,37,37.0,neutral or dissatisfied +103315,60931,Male,Loyal Customer,55,Business travel,Business,1936,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +103316,107378,Female,Loyal Customer,52,Personal Travel,Business,725,3,2,3,3,3,3,4,3,3,3,3,2,3,1,32,26.0,neutral or dissatisfied +103317,46067,Male,Loyal Customer,25,Business travel,Business,495,2,1,1,1,2,2,2,2,2,1,3,4,3,2,0,17.0,neutral or dissatisfied +103318,112045,Female,disloyal Customer,25,Business travel,Eco,1015,3,3,3,4,3,3,3,3,5,2,4,2,5,3,0,0.0,neutral or dissatisfied +103319,12178,Female,Loyal Customer,30,Business travel,Business,1214,3,3,2,3,4,4,4,4,5,4,2,1,4,4,0,2.0,satisfied +103320,118053,Female,Loyal Customer,27,Business travel,Business,2078,4,4,4,4,5,5,5,5,3,4,4,5,5,5,3,0.0,satisfied +103321,92744,Male,Loyal Customer,35,Personal Travel,Eco,1298,5,5,5,3,2,5,2,2,4,3,3,5,4,2,0,0.0,satisfied +103322,97877,Male,Loyal Customer,49,Business travel,Business,3805,5,5,5,5,2,4,5,5,5,5,5,5,5,5,13,13.0,satisfied +103323,8657,Male,Loyal Customer,48,Business travel,Business,3717,1,1,3,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +103324,122084,Male,Loyal Customer,56,Personal Travel,Eco,130,3,0,0,3,3,0,3,3,2,4,5,3,4,3,0,0.0,neutral or dissatisfied +103325,62434,Male,Loyal Customer,42,Personal Travel,Eco Plus,1670,1,4,1,4,4,1,4,4,2,5,4,1,4,4,5,0.0,neutral or dissatisfied +103326,84465,Male,Loyal Customer,58,Business travel,Business,1873,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,10.0,satisfied +103327,80115,Female,Loyal Customer,62,Personal Travel,Eco,1626,0,5,0,3,5,3,4,1,1,0,5,3,1,4,0,0.0,satisfied +103328,10343,Female,Loyal Customer,54,Business travel,Business,2373,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +103329,1145,Male,Loyal Customer,27,Personal Travel,Eco,113,5,4,5,4,1,5,1,1,4,1,1,3,5,1,0,0.0,satisfied +103330,116052,Female,Loyal Customer,31,Personal Travel,Eco,333,3,5,3,3,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +103331,59476,Male,Loyal Customer,59,Business travel,Business,921,5,5,5,5,2,5,5,3,3,3,3,4,3,3,13,0.0,satisfied +103332,24416,Male,Loyal Customer,61,Business travel,Eco,634,1,2,2,2,1,1,1,1,1,2,3,2,4,1,0,0.0,neutral or dissatisfied +103333,111265,Male,Loyal Customer,29,Business travel,Business,1567,4,4,5,4,5,5,5,5,4,2,4,3,5,5,15,15.0,satisfied +103334,59821,Female,Loyal Customer,16,Personal Travel,Business,937,3,5,3,4,5,3,5,5,1,3,5,4,4,5,1,0.0,neutral or dissatisfied +103335,10235,Male,Loyal Customer,43,Business travel,Business,1517,1,5,1,1,1,4,4,2,2,2,1,3,2,3,0,0.0,neutral or dissatisfied +103336,17352,Female,Loyal Customer,11,Business travel,Business,1834,2,1,1,1,2,2,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +103337,91522,Male,Loyal Customer,36,Personal Travel,Eco Plus,1626,1,3,1,2,2,1,2,2,3,3,3,3,2,2,0,0.0,neutral or dissatisfied +103338,67165,Male,Loyal Customer,47,Personal Travel,Eco,985,4,5,3,1,5,3,5,5,3,3,4,4,4,5,4,0.0,satisfied +103339,27838,Male,Loyal Customer,47,Personal Travel,Eco,1448,3,2,3,3,3,3,3,3,1,5,1,3,2,3,0,0.0,neutral or dissatisfied +103340,40334,Female,Loyal Customer,70,Personal Travel,Eco Plus,347,2,5,2,4,3,4,5,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +103341,10621,Female,Loyal Customer,39,Business travel,Eco,458,1,2,2,2,1,1,1,1,4,2,2,4,3,1,31,31.0,neutral or dissatisfied +103342,107558,Female,Loyal Customer,10,Business travel,Business,1521,5,5,5,5,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +103343,13414,Female,disloyal Customer,32,Business travel,Eco,409,2,0,3,4,2,3,2,2,3,5,2,1,4,2,8,1.0,neutral or dissatisfied +103344,39585,Male,Loyal Customer,28,Business travel,Business,3864,1,1,1,1,2,2,2,2,5,4,5,1,1,2,0,0.0,satisfied +103345,95334,Male,Loyal Customer,47,Personal Travel,Eco,189,3,4,3,3,1,3,4,1,5,4,5,5,5,1,12,7.0,neutral or dissatisfied +103346,3742,Female,Loyal Customer,41,Personal Travel,Eco,544,3,3,3,4,2,3,2,2,3,4,3,1,5,2,75,81.0,neutral or dissatisfied +103347,100063,Female,Loyal Customer,68,Personal Travel,Eco,281,3,4,4,4,2,3,4,1,1,4,1,1,1,1,10,18.0,neutral or dissatisfied +103348,71554,Female,Loyal Customer,44,Business travel,Business,1197,2,2,2,2,3,5,5,4,4,4,4,4,4,3,1,0.0,satisfied +103349,25101,Female,Loyal Customer,14,Personal Travel,Eco,369,1,5,1,4,2,1,4,2,1,3,5,3,5,2,0,0.0,neutral or dissatisfied +103350,981,Male,Loyal Customer,57,Business travel,Business,2747,2,4,4,4,2,3,3,4,4,4,2,4,4,3,0,0.0,neutral or dissatisfied +103351,119995,Female,Loyal Customer,31,Business travel,Business,2532,5,3,5,5,4,4,4,4,5,4,4,3,4,4,0,16.0,satisfied +103352,115419,Female,Loyal Customer,52,Business travel,Business,2108,1,5,5,5,5,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +103353,55237,Female,disloyal Customer,25,Business travel,Business,1009,5,4,4,3,1,4,1,1,5,2,4,5,4,1,0,0.0,satisfied +103354,96736,Male,Loyal Customer,59,Personal Travel,Eco,696,4,4,4,3,5,4,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +103355,56625,Male,Loyal Customer,41,Business travel,Eco,937,1,4,4,4,1,1,1,1,1,3,2,4,2,1,0,0.0,neutral or dissatisfied +103356,29338,Female,Loyal Customer,17,Personal Travel,Eco,550,2,0,2,4,4,2,4,4,3,2,5,5,5,4,0,9.0,neutral or dissatisfied +103357,110139,Female,Loyal Customer,44,Business travel,Business,3891,5,5,5,5,2,4,5,3,3,3,3,3,3,3,54,38.0,satisfied +103358,24246,Female,Loyal Customer,66,Personal Travel,Eco,170,4,5,0,3,4,5,5,3,3,0,3,5,3,3,31,38.0,satisfied +103359,29741,Female,Loyal Customer,52,Business travel,Business,2119,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +103360,4014,Male,disloyal Customer,25,Business travel,Eco,483,3,2,3,4,3,5,5,2,2,3,4,5,3,5,300,317.0,neutral or dissatisfied +103361,32268,Female,Loyal Customer,36,Business travel,Eco,163,5,2,2,2,5,5,5,5,4,1,5,3,1,5,0,0.0,satisfied +103362,13709,Male,Loyal Customer,54,Business travel,Business,2231,2,2,2,2,5,4,4,4,4,4,4,4,4,4,79,83.0,satisfied +103363,37198,Female,Loyal Customer,55,Business travel,Eco Plus,1179,3,5,5,5,3,3,3,3,3,3,3,1,3,1,4,24.0,neutral or dissatisfied +103364,28869,Female,Loyal Customer,51,Business travel,Eco,956,4,5,5,5,2,5,4,4,4,4,4,3,4,2,0,0.0,satisfied +103365,93138,Female,disloyal Customer,12,Business travel,Eco,1075,1,1,1,3,1,1,1,1,2,2,3,3,3,1,9,0.0,neutral or dissatisfied +103366,101191,Male,Loyal Customer,54,Personal Travel,Eco,1090,3,3,3,4,4,3,2,4,2,2,2,2,1,4,20,1.0,neutral or dissatisfied +103367,45328,Male,Loyal Customer,48,Business travel,Eco,150,2,2,5,2,2,2,2,2,4,1,3,4,2,2,0,4.0,neutral or dissatisfied +103368,22531,Male,Loyal Customer,56,Personal Travel,Eco Plus,143,2,3,2,5,5,2,5,5,2,4,1,5,4,5,0,2.0,neutral or dissatisfied +103369,57542,Male,Loyal Customer,48,Personal Travel,Eco,413,1,4,5,2,2,5,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +103370,17852,Female,Loyal Customer,51,Personal Travel,Eco,615,2,4,2,3,2,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +103371,77216,Female,Loyal Customer,45,Business travel,Business,1590,2,2,5,2,2,5,5,4,4,4,4,3,4,3,10,3.0,satisfied +103372,28772,Female,Loyal Customer,30,Business travel,Business,1763,3,3,3,3,4,4,4,4,4,3,5,3,4,4,9,0.0,satisfied +103373,9565,Male,Loyal Customer,40,Business travel,Business,2917,0,0,0,1,5,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +103374,4570,Male,Loyal Customer,69,Personal Travel,Eco,561,2,4,2,4,1,2,1,1,3,1,3,2,4,1,0,0.0,neutral or dissatisfied +103375,107643,Female,Loyal Customer,40,Business travel,Business,3474,1,1,1,1,3,5,4,4,4,4,4,3,4,5,53,53.0,satisfied +103376,47654,Male,Loyal Customer,51,Business travel,Eco,1464,1,5,5,5,1,1,1,1,1,3,3,3,3,1,57,53.0,neutral or dissatisfied +103377,40387,Female,Loyal Customer,32,Business travel,Eco Plus,1250,5,3,3,3,5,5,5,5,1,2,3,1,3,5,0,0.0,satisfied +103378,87637,Female,Loyal Customer,51,Business travel,Business,591,2,2,2,2,2,5,4,4,4,4,4,5,4,3,13,12.0,satisfied +103379,9588,Female,Loyal Customer,33,Business travel,Business,3509,4,4,4,4,2,2,4,4,4,4,4,1,4,4,0,0.0,satisfied +103380,65204,Female,Loyal Customer,58,Business travel,Business,1794,1,1,1,1,2,4,5,4,4,4,4,5,4,4,1,0.0,satisfied +103381,128412,Male,Loyal Customer,26,Business travel,Business,647,1,5,5,5,1,1,1,1,1,5,4,1,4,1,4,0.0,neutral or dissatisfied +103382,16876,Female,disloyal Customer,10,Business travel,Eco,708,2,2,2,3,1,2,1,1,1,5,3,2,3,1,25,24.0,neutral or dissatisfied +103383,101754,Female,Loyal Customer,35,Business travel,Eco,1590,3,2,2,2,3,3,3,3,5,4,1,2,3,3,0,0.0,satisfied +103384,47064,Male,disloyal Customer,39,Business travel,Eco,239,3,5,3,2,5,3,5,5,1,4,3,3,2,5,10,0.0,neutral or dissatisfied +103385,118287,Female,Loyal Customer,25,Business travel,Business,2195,2,5,5,5,2,2,2,2,3,4,4,1,3,2,25,17.0,neutral or dissatisfied +103386,115873,Female,disloyal Customer,20,Business travel,Eco,308,5,4,5,3,4,5,4,4,1,5,4,3,4,4,1,0.0,satisfied +103387,16822,Female,Loyal Customer,24,Business travel,Business,645,3,4,4,4,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +103388,13705,Male,Loyal Customer,64,Personal Travel,Eco,483,2,3,2,4,4,2,3,4,2,1,3,4,4,4,0,12.0,neutral or dissatisfied +103389,36108,Female,Loyal Customer,34,Business travel,Eco Plus,399,3,4,4,4,3,3,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +103390,16942,Male,Loyal Customer,38,Business travel,Business,3195,2,2,2,2,3,4,3,4,4,4,4,4,4,1,0,0.0,satisfied +103391,72276,Male,Loyal Customer,45,Business travel,Business,2495,4,4,4,4,2,3,2,4,4,4,4,1,4,3,0,0.0,satisfied +103392,22624,Male,Loyal Customer,63,Personal Travel,Eco,300,2,4,2,3,5,2,1,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +103393,78817,Female,Loyal Customer,28,Personal Travel,Eco,447,2,5,2,3,1,2,1,1,4,2,4,3,4,1,0,20.0,neutral or dissatisfied +103394,120822,Male,Loyal Customer,40,Personal Travel,Eco,666,3,5,3,5,4,3,3,4,1,5,3,2,4,4,0,0.0,neutral or dissatisfied +103395,88324,Male,Loyal Customer,38,Business travel,Eco,581,2,3,3,3,2,2,2,2,3,1,3,2,3,2,5,30.0,neutral or dissatisfied +103396,78931,Male,Loyal Customer,46,Business travel,Business,2834,2,4,2,4,5,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +103397,33796,Female,disloyal Customer,22,Business travel,Eco,1284,3,3,3,4,5,3,5,5,1,1,4,1,4,5,0,11.0,neutral or dissatisfied +103398,35792,Male,Loyal Customer,41,Personal Travel,Eco,200,2,3,2,3,1,2,4,1,5,3,5,2,2,1,23,17.0,neutral or dissatisfied +103399,88697,Female,Loyal Customer,15,Personal Travel,Eco,406,3,4,3,1,1,3,1,1,4,3,5,4,4,1,1,1.0,neutral or dissatisfied +103400,95186,Female,Loyal Customer,45,Personal Travel,Eco,677,3,4,3,4,5,4,4,1,1,3,5,3,1,4,13,0.0,neutral or dissatisfied +103401,22973,Female,Loyal Customer,25,Business travel,Business,2199,1,3,3,3,1,1,1,1,1,4,2,3,2,1,44,48.0,neutral or dissatisfied +103402,101189,Male,Loyal Customer,10,Personal Travel,Eco,1090,3,3,3,3,5,3,5,5,1,4,4,1,4,5,10,0.0,neutral or dissatisfied +103403,122912,Female,Loyal Customer,15,Business travel,Business,2203,5,4,5,5,5,5,5,5,4,2,4,5,5,5,0,5.0,satisfied +103404,111763,Female,Loyal Customer,48,Personal Travel,Eco,1436,2,2,2,2,4,3,2,4,4,2,2,2,4,3,10,0.0,neutral or dissatisfied +103405,122614,Male,Loyal Customer,14,Personal Travel,Eco,728,2,5,2,3,2,2,2,2,1,4,1,2,3,2,0,0.0,neutral or dissatisfied +103406,3589,Male,Loyal Customer,29,Business travel,Business,3117,5,5,5,5,4,4,4,4,5,5,5,3,4,4,55,40.0,satisfied +103407,29972,Male,Loyal Customer,51,Business travel,Eco,261,1,2,2,2,2,1,2,2,1,5,2,2,2,2,0,0.0,neutral or dissatisfied +103408,112668,Male,Loyal Customer,50,Business travel,Eco,671,3,5,5,5,3,3,3,3,4,4,3,1,3,3,91,84.0,neutral or dissatisfied +103409,57981,Female,disloyal Customer,33,Business travel,Business,589,2,2,2,4,4,2,4,4,5,4,5,4,5,4,14,1.0,neutral or dissatisfied +103410,66477,Female,disloyal Customer,36,Business travel,Business,447,2,2,2,4,3,2,3,3,3,4,4,3,4,3,0,13.0,neutral or dissatisfied +103411,42388,Male,Loyal Customer,43,Personal Travel,Eco,329,1,4,1,4,2,1,5,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +103412,112855,Female,Loyal Customer,39,Business travel,Business,1476,5,5,2,5,5,5,4,4,4,4,4,4,4,5,13,13.0,satisfied +103413,67555,Female,Loyal Customer,58,Personal Travel,Business,1126,3,1,3,4,2,3,4,5,5,3,5,2,5,1,0,15.0,neutral or dissatisfied +103414,43868,Female,Loyal Customer,44,Business travel,Eco,199,4,3,3,3,1,4,4,4,4,4,4,4,4,3,9,2.0,satisfied +103415,99069,Female,Loyal Customer,44,Business travel,Eco,419,1,4,4,4,1,1,1,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +103416,103226,Male,Loyal Customer,46,Personal Travel,Eco,462,2,3,2,2,3,2,3,3,2,5,2,3,2,3,2,1.0,neutral or dissatisfied +103417,12459,Male,Loyal Customer,58,Personal Travel,Eco,190,3,4,3,4,4,3,4,4,3,2,5,4,4,4,41,41.0,neutral or dissatisfied +103418,60298,Male,Loyal Customer,27,Personal Travel,Eco,783,1,5,1,4,5,1,5,5,3,3,5,4,4,5,5,27.0,neutral or dissatisfied +103419,2064,Female,disloyal Customer,30,Business travel,Eco,812,3,3,3,3,5,3,4,5,2,2,3,4,3,5,22,11.0,neutral or dissatisfied +103420,119095,Female,Loyal Customer,24,Business travel,Eco,1020,3,1,1,1,3,3,2,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +103421,57231,Male,Loyal Customer,22,Personal Travel,Eco,1514,4,2,4,4,3,4,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +103422,63287,Female,disloyal Customer,38,Business travel,Business,337,5,5,5,1,3,5,3,3,5,3,5,4,4,3,4,1.0,satisfied +103423,102228,Male,disloyal Customer,38,Business travel,Eco,397,3,2,3,3,2,3,2,2,3,2,3,3,3,2,24,16.0,neutral or dissatisfied +103424,7697,Female,Loyal Customer,8,Personal Travel,Eco,767,4,5,4,2,1,4,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +103425,75229,Female,Loyal Customer,30,Personal Travel,Eco,1846,5,4,5,3,2,5,2,2,1,2,3,3,3,2,75,61.0,satisfied +103426,36481,Male,Loyal Customer,29,Business travel,Business,1197,4,4,4,4,4,4,4,4,4,2,4,5,5,4,2,0.0,satisfied +103427,34140,Male,Loyal Customer,40,Business travel,Business,1129,2,2,2,2,1,2,2,4,4,4,4,3,4,1,0,3.0,satisfied +103428,112880,Male,Loyal Customer,54,Business travel,Business,1164,5,5,4,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +103429,74398,Female,Loyal Customer,58,Business travel,Business,1235,1,1,1,1,3,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +103430,16529,Female,disloyal Customer,17,Business travel,Eco,209,1,3,1,4,2,1,2,2,3,1,3,2,4,2,119,117.0,neutral or dissatisfied +103431,442,Female,Loyal Customer,14,Personal Travel,Business,309,3,4,3,4,5,3,5,5,3,5,2,1,1,5,0,0.0,neutral or dissatisfied +103432,45797,Male,disloyal Customer,32,Business travel,Eco,391,4,0,4,5,4,4,4,4,3,4,1,3,2,4,28,18.0,neutral or dissatisfied +103433,27260,Female,Loyal Customer,41,Business travel,Business,3316,5,5,5,5,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +103434,84348,Male,Loyal Customer,20,Business travel,Business,2243,1,1,1,1,4,4,4,4,4,5,5,5,4,4,0,6.0,satisfied +103435,98989,Male,Loyal Customer,70,Personal Travel,Eco,569,2,5,2,1,5,2,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +103436,79446,Female,Loyal Customer,56,Personal Travel,Eco Plus,187,2,4,0,5,0,3,2,4,5,5,4,2,3,2,142,152.0,neutral or dissatisfied +103437,22208,Male,Loyal Customer,20,Personal Travel,Eco,633,4,2,4,4,3,4,3,3,1,1,3,4,3,3,0,0.0,neutral or dissatisfied +103438,107044,Male,disloyal Customer,25,Business travel,Eco,480,2,3,2,4,2,2,2,2,2,2,3,4,4,2,57,37.0,neutral or dissatisfied +103439,30110,Female,Loyal Customer,11,Personal Travel,Eco,725,3,3,3,3,1,3,1,1,1,5,1,4,3,1,0,10.0,neutral or dissatisfied +103440,111304,Male,Loyal Customer,43,Business travel,Business,3417,3,3,3,3,5,5,4,5,5,5,5,5,5,3,4,18.0,satisfied +103441,29489,Female,disloyal Customer,25,Business travel,Eco,1107,2,2,2,2,4,2,4,4,4,5,3,2,4,4,0,0.0,satisfied +103442,99824,Male,disloyal Customer,40,Business travel,Business,587,3,3,3,1,5,3,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +103443,112968,Female,Loyal Customer,34,Business travel,Business,1129,1,1,1,1,2,5,4,4,4,4,4,5,4,4,45,62.0,satisfied +103444,104123,Female,Loyal Customer,53,Business travel,Business,3732,5,5,5,5,2,4,4,4,4,4,4,5,4,3,81,71.0,satisfied +103445,70202,Male,Loyal Customer,19,Personal Travel,Eco,258,2,1,2,4,1,2,1,1,4,5,4,2,3,1,0,0.0,neutral or dissatisfied +103446,117622,Female,Loyal Customer,41,Personal Travel,Eco,1020,3,1,3,3,5,3,5,5,3,4,4,4,3,5,63,58.0,neutral or dissatisfied +103447,66199,Male,Loyal Customer,25,Business travel,Eco,550,2,2,2,2,2,2,2,2,3,3,4,2,4,2,16,8.0,neutral or dissatisfied +103448,59262,Male,Loyal Customer,43,Business travel,Business,4963,4,4,5,4,4,4,4,3,4,3,5,4,5,4,60,39.0,satisfied +103449,50198,Female,disloyal Customer,45,Business travel,Eco,337,2,1,2,3,1,2,1,1,1,1,3,3,3,1,7,11.0,neutral or dissatisfied +103450,1771,Female,disloyal Customer,21,Business travel,Business,408,4,0,4,5,3,4,3,3,5,2,4,5,5,3,0,0.0,satisfied +103451,31478,Male,disloyal Customer,46,Business travel,Eco,862,3,3,3,3,3,3,5,3,1,1,5,4,3,3,1,0.0,neutral or dissatisfied +103452,112334,Male,Loyal Customer,26,Business travel,Business,909,2,2,5,2,4,4,4,4,5,4,5,3,5,4,16,16.0,satisfied +103453,129751,Male,disloyal Customer,26,Business travel,Eco,447,1,2,1,3,1,1,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +103454,52117,Female,Loyal Customer,49,Business travel,Eco Plus,438,3,5,5,5,1,2,4,3,3,3,3,3,3,2,0,0.0,satisfied +103455,81856,Female,disloyal Customer,24,Business travel,Eco,1310,4,4,4,4,2,4,2,2,3,3,4,5,5,2,15,0.0,satisfied +103456,98128,Female,Loyal Customer,20,Personal Travel,Eco,472,2,2,2,3,2,5,5,2,4,2,2,5,1,5,121,137.0,neutral or dissatisfied +103457,71658,Female,Loyal Customer,67,Personal Travel,Eco,1182,4,5,4,4,2,4,5,2,2,4,2,4,2,5,71,119.0,neutral or dissatisfied +103458,45457,Female,Loyal Customer,19,Business travel,Eco,522,5,5,5,5,5,5,5,5,2,2,5,5,5,5,0,0.0,satisfied +103459,92065,Female,Loyal Customer,53,Business travel,Business,1589,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,2.0,satisfied +103460,68327,Male,disloyal Customer,63,Business travel,Eco,665,3,2,3,4,5,3,5,5,3,1,4,2,3,5,25,23.0,neutral or dissatisfied +103461,50665,Female,Loyal Customer,41,Personal Travel,Eco,363,3,4,3,2,5,3,5,5,3,2,5,3,5,5,0,2.0,neutral or dissatisfied +103462,31736,Female,disloyal Customer,32,Business travel,Eco Plus,853,3,3,3,5,2,3,2,2,5,2,2,4,5,2,77,74.0,neutral or dissatisfied +103463,95896,Female,Loyal Customer,51,Personal Travel,Eco,580,1,4,1,3,3,4,4,2,2,1,2,3,2,4,56,50.0,neutral or dissatisfied +103464,88676,Male,Loyal Customer,26,Personal Travel,Eco,271,1,2,1,3,4,1,4,4,2,2,3,2,2,4,0,0.0,neutral or dissatisfied +103465,23494,Male,Loyal Customer,39,Business travel,Business,303,2,2,2,2,3,4,5,4,4,4,4,3,4,4,46,56.0,satisfied +103466,82503,Female,disloyal Customer,23,Business travel,Business,760,5,4,5,3,4,5,4,4,4,2,4,3,5,4,31,74.0,satisfied +103467,62578,Male,Loyal Customer,30,Business travel,Business,1846,3,3,3,3,5,5,5,5,4,2,4,3,4,5,15,0.0,satisfied +103468,41255,Male,Loyal Customer,41,Business travel,Business,852,5,5,5,5,1,4,1,4,4,4,4,5,4,4,0,1.0,satisfied +103469,107828,Female,Loyal Customer,7,Personal Travel,Eco,349,3,4,3,4,4,3,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +103470,64526,Male,Loyal Customer,31,Business travel,Business,3394,4,4,4,4,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +103471,13756,Male,Loyal Customer,32,Personal Travel,Eco,441,2,1,2,3,3,2,4,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +103472,1536,Female,disloyal Customer,26,Business travel,Business,987,2,0,2,4,3,2,1,3,4,2,4,3,4,3,4,18.0,neutral or dissatisfied +103473,35749,Male,Loyal Customer,46,Personal Travel,Eco,1826,3,4,3,3,4,3,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +103474,80154,Male,disloyal Customer,24,Business travel,Eco,1383,1,1,1,3,1,4,4,4,2,3,2,4,4,4,12,26.0,neutral or dissatisfied +103475,72935,Male,Loyal Customer,56,Business travel,Business,3210,5,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +103476,45183,Male,Loyal Customer,66,Business travel,Eco Plus,174,2,4,4,4,2,2,2,2,2,2,4,2,4,2,0,0.0,neutral or dissatisfied +103477,52491,Female,Loyal Customer,7,Personal Travel,Eco Plus,451,1,5,1,4,1,1,1,1,5,2,4,4,5,1,0,6.0,neutral or dissatisfied +103478,76382,Male,Loyal Customer,25,Business travel,Business,2295,5,5,5,5,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +103479,50308,Female,disloyal Customer,27,Business travel,Eco,250,4,0,4,4,4,4,5,4,2,3,2,3,1,4,0,0.0,neutral or dissatisfied +103480,31366,Male,Loyal Customer,43,Business travel,Eco Plus,692,2,5,5,5,2,2,2,2,2,3,2,2,2,2,85,82.0,neutral or dissatisfied +103481,50176,Female,Loyal Customer,40,Business travel,Eco,156,1,4,4,4,1,1,1,1,2,4,3,3,2,1,95,89.0,neutral or dissatisfied +103482,54032,Female,Loyal Customer,18,Business travel,Business,1416,3,3,3,3,4,4,4,4,5,2,4,4,4,4,21,4.0,satisfied +103483,67603,Male,Loyal Customer,58,Business travel,Business,1438,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,4.0,satisfied +103484,24669,Female,Loyal Customer,23,Personal Travel,Eco Plus,834,4,5,3,4,5,3,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +103485,115724,Male,disloyal Customer,20,Business travel,Business,296,5,5,5,3,3,5,3,3,3,5,5,3,4,3,0,0.0,satisfied +103486,32586,Male,disloyal Customer,24,Business travel,Eco,101,3,4,3,1,5,3,4,5,5,2,5,2,5,5,0,0.0,neutral or dissatisfied +103487,110463,Female,Loyal Customer,32,Personal Travel,Eco,925,3,4,3,1,3,3,3,3,3,5,4,5,4,3,13,1.0,neutral or dissatisfied +103488,99135,Male,Loyal Customer,25,Personal Travel,Eco,181,2,5,0,2,3,0,3,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +103489,124462,Male,Loyal Customer,39,Business travel,Business,1516,3,4,4,4,2,4,3,3,3,3,3,1,3,1,4,24.0,neutral or dissatisfied +103490,83613,Female,Loyal Customer,51,Business travel,Eco,409,3,3,3,3,1,3,2,3,3,3,3,4,3,3,0,14.0,neutral or dissatisfied +103491,60226,Male,Loyal Customer,54,Business travel,Business,1703,3,5,5,5,2,2,2,3,3,3,3,4,3,2,50,27.0,neutral or dissatisfied +103492,78150,Male,Loyal Customer,45,Business travel,Business,3584,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +103493,59048,Female,Loyal Customer,10,Business travel,Business,1723,3,3,5,3,3,3,3,2,4,2,4,3,1,3,154,126.0,neutral or dissatisfied +103494,50438,Female,disloyal Customer,28,Business travel,Eco,153,2,0,2,1,3,2,3,3,2,3,2,1,4,3,0,0.0,neutral or dissatisfied +103495,51482,Female,Loyal Customer,40,Business travel,Business,425,4,4,4,4,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +103496,36001,Male,Loyal Customer,55,Business travel,Business,1536,3,1,1,1,4,4,3,3,3,3,3,1,3,2,0,4.0,neutral or dissatisfied +103497,61869,Female,Loyal Customer,60,Business travel,Business,2521,3,3,3,3,5,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +103498,2569,Male,Loyal Customer,53,Business travel,Business,280,2,2,2,2,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +103499,49965,Male,Loyal Customer,38,Business travel,Business,89,4,1,1,1,3,3,3,1,1,2,4,4,1,4,13,0.0,neutral or dissatisfied +103500,58351,Male,Loyal Customer,45,Personal Travel,Business,599,4,2,4,3,2,4,3,2,2,4,2,4,2,2,0,14.0,neutral or dissatisfied +103501,69227,Female,disloyal Customer,29,Business travel,Eco,733,3,3,3,3,3,3,3,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +103502,82765,Male,Loyal Customer,58,Personal Travel,Eco,409,3,2,3,4,2,3,1,2,3,5,4,1,3,2,0,0.0,neutral or dissatisfied +103503,27681,Female,Loyal Customer,59,Business travel,Eco,1107,4,2,2,2,2,3,1,4,4,4,4,3,4,4,0,0.0,satisfied +103504,89309,Female,Loyal Customer,71,Business travel,Eco Plus,453,4,5,5,5,2,3,3,4,4,4,4,3,4,1,8,16.0,neutral or dissatisfied +103505,49823,Male,Loyal Customer,48,Business travel,Eco,447,4,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +103506,35141,Female,Loyal Customer,28,Business travel,Business,1069,3,3,3,3,5,5,5,5,3,2,4,2,3,5,0,0.0,satisfied +103507,88036,Male,disloyal Customer,21,Business travel,Business,223,4,4,4,5,4,4,2,4,4,5,5,4,4,4,0,0.0,satisfied +103508,35414,Female,Loyal Customer,22,Business travel,Business,3182,2,2,2,2,5,5,5,5,5,4,2,4,3,5,0,0.0,satisfied +103509,90129,Male,Loyal Customer,30,Business travel,Business,2573,1,1,1,1,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +103510,78127,Male,Loyal Customer,44,Business travel,Business,196,0,4,0,4,2,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +103511,23935,Male,Loyal Customer,30,Business travel,Business,2300,5,5,2,5,5,5,5,2,5,3,5,5,5,5,147,138.0,satisfied +103512,76842,Male,Loyal Customer,43,Business travel,Business,3892,4,4,4,4,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +103513,22431,Female,Loyal Customer,34,Personal Travel,Eco,143,2,3,2,3,2,2,2,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +103514,30864,Female,Loyal Customer,31,Business travel,Business,1607,3,3,3,3,5,5,5,5,3,2,5,3,3,5,0,11.0,satisfied +103515,73284,Female,Loyal Customer,32,Business travel,Business,3113,3,3,3,3,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +103516,9026,Female,disloyal Customer,27,Business travel,Business,160,2,2,2,1,4,2,5,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +103517,94920,Female,Loyal Customer,57,Business travel,Business,187,1,1,1,1,3,4,1,4,4,4,4,3,4,1,51,44.0,satisfied +103518,121158,Male,Loyal Customer,24,Business travel,Eco,2402,2,5,1,1,2,4,2,4,2,3,3,2,4,2,0,19.0,neutral or dissatisfied +103519,92563,Male,Loyal Customer,60,Business travel,Business,1892,5,5,2,5,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +103520,111993,Male,Loyal Customer,48,Personal Travel,Eco,770,3,4,3,2,2,3,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +103521,118121,Female,Loyal Customer,26,Business travel,Business,1506,2,2,2,2,5,5,5,5,4,3,5,5,4,5,50,39.0,satisfied +103522,120453,Male,Loyal Customer,58,Personal Travel,Eco,337,3,2,3,4,3,3,3,3,2,1,4,3,3,3,0,0.0,neutral or dissatisfied +103523,98099,Female,Loyal Customer,22,Personal Travel,Eco,265,1,3,0,3,4,0,4,4,1,4,3,3,1,4,0,0.0,neutral or dissatisfied +103524,40064,Male,Loyal Customer,31,Personal Travel,Eco,866,3,1,3,3,4,3,4,4,3,1,3,3,3,4,0,1.0,neutral or dissatisfied +103525,10706,Male,Loyal Customer,42,Business travel,Business,458,1,1,1,1,3,5,4,3,3,3,3,5,3,4,0,0.0,satisfied +103526,40653,Male,Loyal Customer,17,Business travel,Business,588,4,4,3,4,5,5,5,5,4,2,5,3,4,5,1,0.0,satisfied +103527,49378,Female,disloyal Customer,34,Business travel,Eco,308,3,3,3,3,1,3,1,1,2,5,2,1,3,1,6,21.0,neutral or dissatisfied +103528,100840,Female,Loyal Customer,31,Business travel,Eco,711,4,1,1,1,4,4,4,4,2,1,4,1,1,4,0,0.0,satisfied +103529,99818,Female,disloyal Customer,42,Business travel,Business,680,3,3,3,1,2,3,2,2,3,3,5,4,5,2,0,0.0,satisfied +103530,105371,Male,Loyal Customer,43,Business travel,Business,2677,3,3,3,3,3,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +103531,88863,Male,Loyal Customer,34,Business travel,Business,2723,5,5,5,5,2,4,4,4,4,3,4,3,4,5,0,0.0,satisfied +103532,27212,Male,Loyal Customer,58,Personal Travel,Eco,2717,3,2,3,4,3,3,3,3,4,2,3,1,4,3,5,32.0,neutral or dissatisfied +103533,116945,Female,Loyal Customer,36,Business travel,Business,3179,2,2,2,2,3,5,5,4,4,4,4,3,4,5,11,7.0,satisfied +103534,121556,Female,Loyal Customer,51,Business travel,Business,3886,1,1,1,1,5,5,4,3,3,3,3,5,3,3,2,0.0,satisfied +103535,115193,Male,disloyal Customer,36,Business travel,Eco,325,4,1,4,4,2,4,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +103536,20882,Female,disloyal Customer,25,Business travel,Eco Plus,357,4,0,4,3,4,4,4,4,5,4,3,1,5,4,1,0.0,neutral or dissatisfied +103537,124814,Female,Loyal Customer,30,Business travel,Business,280,3,4,4,4,3,3,3,3,2,3,4,1,3,3,0,2.0,neutral or dissatisfied +103538,64471,Male,disloyal Customer,36,Business travel,Business,190,1,1,1,3,2,1,2,2,3,3,4,4,5,2,26,27.0,neutral or dissatisfied +103539,105215,Male,Loyal Customer,64,Business travel,Business,3498,1,1,1,1,5,5,4,5,5,4,5,5,5,3,77,61.0,satisfied +103540,45022,Female,Loyal Customer,33,Personal Travel,Eco,359,4,4,4,3,4,4,4,4,3,2,5,3,5,4,42,,neutral or dissatisfied +103541,104437,Male,Loyal Customer,41,Personal Travel,Eco,1024,1,5,0,3,1,0,1,1,4,5,5,3,4,1,0,20.0,neutral or dissatisfied +103542,57945,Female,Loyal Customer,56,Business travel,Business,1062,3,2,2,2,4,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +103543,25304,Male,Loyal Customer,65,Business travel,Business,2995,1,1,1,1,3,3,3,1,1,1,1,4,1,2,0,1.0,neutral or dissatisfied +103544,23843,Female,Loyal Customer,39,Business travel,Business,2796,2,2,2,2,3,4,4,2,2,3,2,4,2,5,0,0.0,satisfied +103545,125320,Female,Loyal Customer,28,Business travel,Business,3548,2,2,2,2,4,5,4,4,3,5,4,4,5,4,5,28.0,satisfied +103546,47775,Male,Loyal Customer,44,Business travel,Eco,315,4,5,3,5,4,4,4,4,2,1,2,1,2,4,1,0.0,neutral or dissatisfied +103547,19000,Female,disloyal Customer,39,Business travel,Business,788,4,4,4,3,4,2,2,2,5,3,1,2,2,2,196,184.0,satisfied +103548,72308,Female,Loyal Customer,67,Personal Travel,Eco,919,5,3,5,4,3,4,3,5,5,5,4,2,5,3,0,0.0,satisfied +103549,15691,Male,Loyal Customer,38,Personal Travel,Eco,335,3,4,3,3,2,3,2,2,5,4,5,3,4,2,48,47.0,neutral or dissatisfied +103550,113626,Male,Loyal Customer,14,Personal Travel,Eco,197,4,1,4,4,1,4,1,1,2,1,3,4,4,1,54,63.0,satisfied +103551,77141,Female,Loyal Customer,54,Personal Travel,Eco,2105,3,5,3,3,4,5,5,3,3,3,3,5,3,4,4,16.0,neutral or dissatisfied +103552,7134,Female,disloyal Customer,18,Business travel,Business,135,2,2,2,3,4,2,2,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +103553,120638,Female,Loyal Customer,43,Business travel,Business,3803,1,1,1,1,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +103554,71248,Female,disloyal Customer,21,Business travel,Business,733,5,5,5,3,2,5,2,2,3,3,5,3,4,2,0,0.0,satisfied +103555,40610,Female,Loyal Customer,64,Personal Travel,Eco,391,0,5,0,3,2,5,5,3,3,0,1,3,3,3,0,0.0,satisfied +103556,49685,Male,Loyal Customer,44,Business travel,Eco,109,2,2,2,2,2,2,2,2,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +103557,46456,Male,disloyal Customer,38,Business travel,Business,196,2,2,2,3,2,2,5,2,4,4,4,4,5,2,43,45.0,neutral or dissatisfied +103558,66495,Male,Loyal Customer,53,Business travel,Business,1638,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +103559,80386,Female,Loyal Customer,16,Business travel,Business,2821,2,2,5,2,5,5,5,5,1,1,4,3,4,5,3,0.0,satisfied +103560,16245,Male,Loyal Customer,58,Business travel,Eco,748,5,4,4,4,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +103561,32465,Female,Loyal Customer,58,Business travel,Business,3178,1,2,2,2,1,2,2,2,2,2,1,3,2,3,4,9.0,neutral or dissatisfied +103562,73563,Female,disloyal Customer,37,Business travel,Business,204,5,5,5,5,1,5,1,1,3,3,4,4,5,1,0,0.0,satisfied +103563,36362,Female,Loyal Customer,46,Business travel,Business,200,2,2,2,2,3,5,4,5,5,5,4,5,5,1,0,0.0,satisfied +103564,17431,Male,Loyal Customer,46,Business travel,Eco,376,2,5,5,5,2,2,2,2,3,3,3,5,1,2,6,0.0,satisfied +103565,68522,Female,Loyal Customer,59,Business travel,Business,3881,2,2,2,2,4,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +103566,3227,Female,disloyal Customer,65,Business travel,Business,419,1,1,1,4,1,1,1,1,4,2,4,1,3,1,118,102.0,neutral or dissatisfied +103567,15037,Male,Loyal Customer,33,Business travel,Business,2352,2,3,3,3,2,2,2,2,3,2,4,2,3,2,2,0.0,neutral or dissatisfied +103568,36927,Male,Loyal Customer,49,Business travel,Business,2543,2,2,2,2,4,2,1,5,5,5,5,3,5,2,2,0.0,satisfied +103569,88244,Female,Loyal Customer,54,Business travel,Business,3517,2,2,2,2,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +103570,54651,Male,disloyal Customer,24,Business travel,Eco,787,1,1,1,4,2,1,2,2,2,1,4,5,1,2,30,16.0,neutral or dissatisfied +103571,93292,Female,Loyal Customer,27,Personal Travel,Eco,867,1,4,1,4,1,3,3,1,4,3,3,3,3,3,247,240.0,neutral or dissatisfied +103572,107382,Male,Loyal Customer,42,Business travel,Business,1778,2,2,2,2,4,5,4,4,4,4,4,4,4,3,35,45.0,satisfied +103573,120007,Female,Loyal Customer,53,Business travel,Eco,328,3,5,5,5,1,3,4,3,3,3,3,3,3,4,0,12.0,neutral or dissatisfied +103574,84804,Female,Loyal Customer,45,Business travel,Business,547,2,2,2,2,2,5,5,5,5,4,5,3,5,5,5,0.0,satisfied +103575,91713,Female,Loyal Customer,60,Business travel,Business,1933,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,3.0,satisfied +103576,128612,Male,Loyal Customer,32,Business travel,Business,679,3,3,3,3,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +103577,9014,Female,Loyal Customer,46,Business travel,Business,212,1,1,1,1,5,5,4,5,5,5,4,4,5,4,0,0.0,satisfied +103578,27033,Male,Loyal Customer,35,Business travel,Eco Plus,867,5,4,4,4,5,5,5,5,5,2,2,3,5,5,0,0.0,satisfied +103579,75132,Male,Loyal Customer,51,Business travel,Business,1744,4,4,4,4,5,3,4,2,2,2,2,3,2,4,1,3.0,satisfied +103580,80644,Female,Loyal Customer,59,Business travel,Business,1785,2,1,2,2,5,5,5,3,3,3,3,3,3,3,0,12.0,satisfied +103581,42208,Male,Loyal Customer,26,Business travel,Business,834,1,1,1,1,3,4,3,3,3,1,4,3,4,3,0,6.0,satisfied +103582,98585,Female,disloyal Customer,39,Business travel,Business,861,1,1,1,1,2,1,2,2,5,5,4,5,5,2,16,12.0,neutral or dissatisfied +103583,57370,Male,Loyal Customer,59,Personal Travel,Eco,236,1,4,1,1,3,1,3,3,1,4,3,1,4,3,81,81.0,neutral or dissatisfied +103584,29566,Female,Loyal Customer,32,Business travel,Business,1533,4,4,4,4,4,4,4,4,3,3,1,4,3,4,0,0.0,satisfied +103585,4725,Female,disloyal Customer,26,Business travel,Business,888,2,0,2,5,5,2,1,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +103586,76685,Female,Loyal Customer,9,Personal Travel,Eco,547,1,2,1,3,5,1,5,5,2,2,2,4,4,5,0,0.0,neutral or dissatisfied +103587,121868,Female,disloyal Customer,43,Business travel,Eco,366,4,4,4,4,4,4,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +103588,29765,Male,Loyal Customer,25,Business travel,Business,725,3,3,3,3,3,3,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +103589,41239,Female,Loyal Customer,21,Business travel,Business,781,2,5,5,5,2,2,2,2,1,2,3,4,3,2,74,70.0,neutral or dissatisfied +103590,41272,Female,Loyal Customer,61,Business travel,Eco Plus,305,3,1,2,1,4,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +103591,107841,Female,Loyal Customer,7,Personal Travel,Eco,349,4,5,4,5,2,4,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +103592,20893,Male,Loyal Customer,22,Business travel,Business,961,4,4,4,4,3,3,3,2,4,4,2,3,2,3,159,157.0,satisfied +103593,8817,Male,Loyal Customer,26,Personal Travel,Eco,522,3,5,3,2,2,3,2,2,4,3,4,5,4,2,23,21.0,neutral or dissatisfied +103594,20707,Male,Loyal Customer,25,Personal Travel,Eco,510,2,5,2,2,2,2,2,2,5,5,5,4,4,2,98,91.0,neutral or dissatisfied +103595,12175,Male,Loyal Customer,39,Business travel,Eco,1042,1,2,2,2,1,2,1,1,2,5,2,1,2,1,0,0.0,neutral or dissatisfied +103596,44989,Male,Loyal Customer,37,Business travel,Eco,359,5,3,3,3,5,5,5,5,3,2,4,3,2,5,4,0.0,satisfied +103597,124401,Female,disloyal Customer,23,Business travel,Business,1044,1,2,1,2,5,1,5,5,1,3,3,4,3,5,0,0.0,neutral or dissatisfied +103598,28594,Male,Loyal Customer,32,Personal Travel,Eco Plus,2562,4,3,4,4,4,4,4,4,4,2,3,2,4,4,15,0.0,neutral or dissatisfied +103599,111326,Male,Loyal Customer,38,Business travel,Eco,283,3,4,4,4,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +103600,21721,Female,disloyal Customer,21,Business travel,Eco,821,5,5,5,2,4,5,4,4,5,5,2,4,4,4,1,0.0,satisfied +103601,11745,Male,Loyal Customer,42,Business travel,Business,429,2,1,5,1,3,4,3,2,2,2,2,1,2,1,0,2.0,neutral or dissatisfied +103602,27754,Female,Loyal Customer,35,Business travel,Business,1448,2,2,2,2,5,1,5,4,4,4,4,2,4,1,28,8.0,satisfied +103603,59890,Female,Loyal Customer,27,Business travel,Business,3666,2,2,3,2,4,4,4,4,5,5,5,4,4,4,18,0.0,satisfied +103604,47708,Male,Loyal Customer,24,Business travel,Eco Plus,1504,0,3,0,4,5,0,5,5,2,2,1,5,5,5,76,71.0,satisfied +103605,102479,Female,Loyal Customer,43,Personal Travel,Eco,226,2,4,2,5,4,5,5,3,3,2,5,4,3,5,2,0.0,neutral or dissatisfied +103606,127958,Male,disloyal Customer,72,Business travel,Business,1999,5,5,5,2,3,5,3,3,3,5,4,3,4,3,1,0.0,satisfied +103607,69723,Male,Loyal Customer,52,Personal Travel,Eco,1372,3,5,2,2,3,2,3,3,5,5,3,5,4,3,0,0.0,neutral or dissatisfied +103608,60447,Male,disloyal Customer,49,Business travel,Eco,862,2,2,2,2,2,2,1,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +103609,127108,Female,Loyal Customer,39,Personal Travel,Eco,370,4,3,4,3,5,4,2,5,1,1,5,5,5,5,2,0.0,satisfied +103610,7410,Female,Loyal Customer,21,Business travel,Business,522,2,4,4,4,2,2,2,2,3,2,2,4,2,2,0,0.0,neutral or dissatisfied +103611,1821,Female,Loyal Customer,29,Business travel,Business,408,2,1,1,1,2,3,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +103612,66478,Female,Loyal Customer,60,Business travel,Business,447,2,2,2,2,4,4,5,3,3,4,3,4,3,5,0,0.0,satisfied +103613,48243,Male,Loyal Customer,40,Personal Travel,Eco,414,3,5,3,3,2,3,2,2,1,3,2,2,5,2,127,129.0,neutral or dissatisfied +103614,51260,Female,Loyal Customer,57,Business travel,Eco Plus,86,3,5,5,5,3,3,3,3,5,3,4,3,3,3,146,150.0,neutral or dissatisfied +103615,22463,Male,Loyal Customer,9,Personal Travel,Eco,208,1,3,1,2,2,1,3,2,4,4,2,4,3,2,51,49.0,neutral or dissatisfied +103616,13465,Male,Loyal Customer,9,Personal Travel,Eco,409,2,5,5,5,1,5,2,1,1,1,5,4,3,1,0,0.0,neutral or dissatisfied +103617,46916,Female,disloyal Customer,38,Business travel,Eco,846,2,2,2,3,3,2,3,3,2,1,2,1,3,3,37,82.0,neutral or dissatisfied +103618,37139,Male,Loyal Customer,23,Business travel,Eco,1046,5,1,1,1,5,5,3,5,4,4,5,2,5,5,0,1.0,satisfied +103619,33938,Female,Loyal Customer,48,Business travel,Business,2734,2,1,1,1,3,3,1,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +103620,71650,Female,Loyal Customer,16,Personal Travel,Eco,1005,2,4,2,1,4,2,4,4,1,5,4,1,3,4,14,7.0,neutral or dissatisfied +103621,28142,Male,disloyal Customer,23,Business travel,Eco,859,3,3,3,4,2,3,2,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +103622,102628,Male,Loyal Customer,21,Personal Travel,Business,255,1,1,1,4,1,1,1,1,4,3,3,3,4,1,86,75.0,neutral or dissatisfied +103623,107455,Male,Loyal Customer,61,Personal Travel,Eco Plus,468,4,4,4,2,2,4,2,2,3,2,4,5,2,2,11,10.0,neutral or dissatisfied +103624,96199,Female,Loyal Customer,44,Business travel,Business,687,2,2,2,2,2,4,4,5,5,5,5,4,5,3,11,4.0,satisfied +103625,37933,Female,Loyal Customer,53,Personal Travel,Eco,1065,1,4,1,4,1,4,4,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +103626,5340,Male,disloyal Customer,23,Business travel,Eco,733,1,2,2,3,4,2,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +103627,106738,Male,Loyal Customer,46,Business travel,Business,945,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +103628,94002,Female,disloyal Customer,21,Business travel,Eco,148,4,0,4,3,5,4,5,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +103629,29705,Male,Loyal Customer,8,Personal Travel,Eco,1542,2,4,2,5,1,2,1,1,3,2,4,5,5,1,4,11.0,neutral or dissatisfied +103630,35080,Female,Loyal Customer,43,Business travel,Eco,944,5,2,2,2,1,1,4,5,5,5,5,1,5,1,14,0.0,satisfied +103631,123932,Male,Loyal Customer,13,Personal Travel,Eco,544,2,3,2,2,5,2,5,5,4,2,2,1,1,5,0,8.0,neutral or dissatisfied +103632,114884,Female,Loyal Customer,38,Business travel,Business,447,2,2,2,2,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +103633,99728,Male,Loyal Customer,36,Business travel,Business,2799,0,0,0,2,4,4,5,2,2,2,2,3,2,4,17,10.0,satisfied +103634,114896,Female,Loyal Customer,54,Business travel,Business,3089,3,3,3,3,3,4,5,5,5,5,5,4,5,4,53,43.0,satisfied +103635,78914,Male,Loyal Customer,43,Business travel,Business,980,1,2,1,1,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +103636,42742,Female,disloyal Customer,38,Business travel,Eco Plus,536,3,3,3,1,3,3,3,3,4,1,1,4,2,3,0,0.0,neutral or dissatisfied +103637,127367,Male,Loyal Customer,45,Business travel,Business,868,3,3,3,3,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +103638,125318,Female,Loyal Customer,52,Business travel,Business,2061,3,3,3,3,4,5,5,5,5,5,5,4,5,4,5,9.0,satisfied +103639,83503,Female,Loyal Customer,60,Personal Travel,Eco,946,2,4,2,4,5,4,4,5,5,2,5,1,5,4,8,17.0,neutral or dissatisfied +103640,69491,Male,Loyal Customer,52,Business travel,Eco Plus,1089,3,2,2,2,3,3,3,3,4,3,4,1,4,3,90,88.0,neutral or dissatisfied +103641,73541,Female,Loyal Customer,14,Personal Travel,Eco,594,3,4,3,5,4,3,2,4,4,1,2,3,1,4,0,0.0,neutral or dissatisfied +103642,43395,Female,Loyal Customer,23,Personal Travel,Eco,436,2,4,2,5,5,2,2,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +103643,33974,Male,Loyal Customer,27,Business travel,Eco,1576,5,2,2,2,5,5,5,5,4,3,2,3,5,5,0,0.0,satisfied +103644,103908,Male,Loyal Customer,51,Business travel,Business,2392,4,3,3,3,4,4,3,4,4,4,4,1,4,1,33,38.0,neutral or dissatisfied +103645,20600,Male,Loyal Customer,49,Personal Travel,Eco Plus,533,2,5,2,1,3,2,3,3,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +103646,77558,Female,Loyal Customer,34,Personal Travel,Eco,986,4,5,4,4,2,4,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +103647,113647,Male,Loyal Customer,38,Personal Travel,Eco,386,4,4,3,4,1,3,1,1,3,3,4,4,5,1,45,30.0,neutral or dissatisfied +103648,38750,Male,Loyal Customer,43,Business travel,Business,3890,4,4,2,4,4,2,1,5,5,5,5,2,5,2,0,0.0,satisfied +103649,30625,Female,Loyal Customer,48,Business travel,Business,533,2,1,1,1,1,3,4,2,2,2,2,3,2,1,18,30.0,neutral or dissatisfied +103650,31684,Male,disloyal Customer,64,Business travel,Eco,862,1,1,1,4,2,1,2,2,4,5,4,3,4,2,7,2.0,neutral or dissatisfied +103651,108633,Female,Loyal Customer,57,Personal Travel,Eco,1547,0,4,0,1,3,4,4,1,1,0,1,4,1,3,3,3.0,satisfied +103652,100911,Male,Loyal Customer,50,Personal Travel,Eco,377,4,5,4,4,1,4,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +103653,77513,Female,Loyal Customer,59,Business travel,Business,1587,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +103654,106138,Male,disloyal Customer,34,Business travel,Eco,302,4,4,4,3,2,4,1,2,2,2,4,3,4,2,6,0.0,neutral or dissatisfied +103655,69666,Female,Loyal Customer,23,Personal Travel,Eco,569,4,5,4,5,1,4,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +103656,102517,Female,Loyal Customer,10,Personal Travel,Eco,258,2,4,2,4,3,2,3,3,2,4,2,4,5,3,11,11.0,neutral or dissatisfied +103657,112564,Male,Loyal Customer,40,Business travel,Business,1721,1,1,5,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +103658,117470,Male,Loyal Customer,12,Personal Travel,Business,507,2,2,2,3,1,2,5,1,2,3,2,3,3,1,27,25.0,neutral or dissatisfied +103659,122824,Female,Loyal Customer,23,Personal Travel,Eco,599,4,4,4,3,1,4,2,1,2,2,4,2,4,1,0,0.0,satisfied +103660,35500,Female,Loyal Customer,26,Personal Travel,Eco,1102,2,4,2,3,3,2,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +103661,88205,Male,Loyal Customer,38,Business travel,Business,271,1,1,1,1,3,5,4,5,5,5,5,3,5,5,3,4.0,satisfied +103662,22210,Male,Loyal Customer,45,Personal Travel,Eco,565,2,4,2,2,3,2,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +103663,84436,Female,disloyal Customer,12,Business travel,Eco,591,3,2,3,3,1,3,1,1,2,4,3,2,4,1,0,0.0,neutral or dissatisfied +103664,58657,Female,Loyal Customer,28,Personal Travel,Eco,867,1,2,1,2,2,1,5,2,2,1,3,4,3,2,11,8.0,neutral or dissatisfied +103665,35472,Male,Loyal Customer,51,Personal Travel,Eco,1069,2,5,2,2,3,2,3,3,5,2,4,5,5,3,62,51.0,neutral or dissatisfied +103666,71190,Male,Loyal Customer,23,Business travel,Business,1914,1,1,1,1,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +103667,93509,Female,Loyal Customer,48,Business travel,Business,2603,2,2,2,2,2,5,4,5,5,5,5,3,5,5,3,2.0,satisfied +103668,41306,Male,Loyal Customer,35,Business travel,Business,802,2,2,2,2,5,4,2,4,4,4,4,4,4,3,0,0.0,satisfied +103669,49914,Female,Loyal Customer,36,Business travel,Eco,77,4,3,3,3,4,4,4,4,1,5,2,2,4,4,0,0.0,satisfied +103670,19552,Male,Loyal Customer,50,Business travel,Business,1578,1,5,5,5,3,3,3,3,3,2,1,2,3,3,67,72.0,neutral or dissatisfied +103671,18421,Male,Loyal Customer,10,Personal Travel,Eco,900,2,5,2,5,4,2,4,4,2,2,2,4,3,4,0,0.0,neutral or dissatisfied +103672,125789,Male,disloyal Customer,23,Business travel,Eco,992,1,1,1,3,4,1,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +103673,29541,Female,Loyal Customer,47,Business travel,Business,1448,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +103674,40633,Female,Loyal Customer,41,Business travel,Eco Plus,391,4,1,1,1,5,3,2,4,4,4,4,1,4,2,0,0.0,satisfied +103675,63028,Female,Loyal Customer,52,Business travel,Business,1947,1,2,2,2,1,3,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +103676,79071,Female,Loyal Customer,38,Business travel,Business,2251,1,1,1,1,5,3,3,1,1,1,1,1,1,4,1,8.0,neutral or dissatisfied +103677,10609,Male,Loyal Customer,50,Business travel,Business,2938,4,4,4,4,5,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +103678,77673,Male,disloyal Customer,28,Business travel,Business,813,3,3,3,3,2,3,3,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +103679,43318,Female,Loyal Customer,36,Business travel,Eco,463,4,4,4,4,4,4,4,4,5,1,5,1,2,4,0,10.0,satisfied +103680,48074,Female,Loyal Customer,60,Business travel,Business,192,1,4,4,4,2,2,1,2,2,2,1,3,2,2,10,6.0,neutral or dissatisfied +103681,128540,Female,Loyal Customer,43,Business travel,Business,2375,2,2,2,2,3,4,4,4,4,4,4,3,4,4,3,0.0,satisfied +103682,43106,Female,Loyal Customer,31,Personal Travel,Eco,236,2,4,2,4,5,2,5,5,5,5,3,2,5,5,0,0.0,neutral or dissatisfied +103683,17529,Female,disloyal Customer,24,Business travel,Eco Plus,241,0,2,0,3,2,0,1,2,3,4,2,5,3,2,1,0.0,satisfied +103684,55490,Male,disloyal Customer,38,Business travel,Business,1739,3,3,3,2,4,3,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +103685,116480,Male,Loyal Customer,42,Personal Travel,Eco,372,1,5,1,5,5,1,5,5,3,4,5,3,5,5,0,5.0,neutral or dissatisfied +103686,125968,Female,Loyal Customer,56,Business travel,Business,3546,5,5,3,5,2,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +103687,82140,Female,disloyal Customer,37,Business travel,Business,311,4,4,4,3,1,4,1,1,3,2,5,4,5,1,0,0.0,satisfied +103688,88793,Female,Loyal Customer,46,Business travel,Business,581,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +103689,1835,Male,Loyal Customer,30,Personal Travel,Eco,408,3,2,3,2,2,3,1,2,3,2,2,1,1,2,83,75.0,neutral or dissatisfied +103690,49113,Male,Loyal Customer,31,Business travel,Eco,308,2,5,3,5,2,2,2,2,4,3,2,3,2,2,0,0.0,neutral or dissatisfied +103691,19689,Male,disloyal Customer,45,Business travel,Eco,491,2,5,2,2,3,2,3,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +103692,32926,Male,Loyal Customer,63,Personal Travel,Eco,102,1,4,1,1,2,1,1,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +103693,37540,Male,disloyal Customer,19,Business travel,Eco,1076,2,1,1,4,3,1,3,3,1,4,3,4,4,3,30,34.0,neutral or dissatisfied +103694,36593,Male,Loyal Customer,46,Business travel,Eco,1197,1,2,2,2,1,1,1,4,3,3,3,1,1,1,260,263.0,neutral or dissatisfied +103695,95567,Male,Loyal Customer,27,Personal Travel,Eco Plus,239,2,4,2,2,5,2,5,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +103696,21223,Male,Loyal Customer,30,Personal Travel,Eco,192,2,5,2,3,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +103697,102950,Male,Loyal Customer,27,Business travel,Business,719,4,4,4,4,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +103698,54619,Male,Loyal Customer,48,Business travel,Eco,787,4,3,3,3,4,4,4,4,2,2,4,4,4,4,16,8.0,satisfied +103699,77995,Male,Loyal Customer,41,Business travel,Business,3127,2,2,2,2,2,5,5,4,4,4,5,3,4,4,0,0.0,satisfied +103700,50815,Male,Loyal Customer,24,Personal Travel,Eco,266,2,0,0,5,1,0,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +103701,94762,Female,Loyal Customer,64,Business travel,Eco,189,3,2,2,2,1,3,3,3,3,3,3,4,3,3,34,30.0,neutral or dissatisfied +103702,42552,Female,Loyal Customer,11,Personal Travel,Eco,1091,4,2,5,4,2,5,2,2,4,5,3,2,4,2,15,0.0,neutral or dissatisfied +103703,53484,Female,Loyal Customer,47,Business travel,Business,2048,3,3,3,3,4,1,4,4,4,4,4,1,4,2,41,13.0,satisfied +103704,119721,Female,Loyal Customer,62,Business travel,Business,1303,2,1,1,1,3,2,3,2,2,3,2,1,2,2,26,5.0,neutral or dissatisfied +103705,44063,Female,Loyal Customer,51,Business travel,Business,1802,3,3,4,3,5,4,4,2,3,1,5,4,2,4,158,243.0,satisfied +103706,113929,Male,Loyal Customer,55,Business travel,Business,1790,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +103707,64844,Female,Loyal Customer,57,Business travel,Business,282,5,5,5,5,4,4,4,5,3,5,4,4,4,4,204,202.0,satisfied +103708,108508,Male,Loyal Customer,37,Business travel,Business,2277,5,5,4,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +103709,122239,Female,Loyal Customer,45,Business travel,Business,546,2,2,2,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +103710,32393,Male,Loyal Customer,61,Business travel,Eco,163,5,2,2,2,4,5,4,4,2,3,2,5,4,4,2,6.0,satisfied +103711,88143,Male,Loyal Customer,52,Business travel,Business,581,4,4,4,4,4,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +103712,27667,Male,Loyal Customer,34,Business travel,Business,2848,4,3,4,4,5,4,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +103713,51483,Male,Loyal Customer,51,Business travel,Business,2362,2,2,2,2,2,5,4,4,4,4,4,5,4,3,0,10.0,satisfied +103714,23417,Male,Loyal Customer,37,Business travel,Business,541,3,3,3,3,4,3,3,3,3,4,3,2,3,3,10,2.0,neutral or dissatisfied +103715,17079,Male,Loyal Customer,8,Personal Travel,Business,416,4,3,4,3,2,4,2,2,1,3,2,5,4,2,31,17.0,neutral or dissatisfied +103716,79435,Female,Loyal Customer,47,Business travel,Eco Plus,502,2,5,1,5,3,1,2,2,2,2,2,4,2,3,75,60.0,neutral or dissatisfied +103717,74774,Male,Loyal Customer,44,Business travel,Business,1171,3,3,3,3,3,4,5,3,3,3,3,3,3,5,21,6.0,satisfied +103718,103831,Male,Loyal Customer,23,Business travel,Eco,1048,3,3,4,4,3,3,1,3,2,2,4,3,4,3,40,26.0,neutral or dissatisfied +103719,119944,Male,Loyal Customer,65,Business travel,Business,1009,3,3,3,3,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +103720,123671,Female,Loyal Customer,49,Business travel,Business,3473,5,4,5,5,3,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +103721,104319,Male,Loyal Customer,55,Business travel,Business,3165,3,3,3,3,5,5,4,4,4,4,4,4,4,3,12,2.0,satisfied +103722,32584,Female,Loyal Customer,50,Business travel,Business,216,4,4,4,4,2,3,3,2,2,2,4,2,2,2,0,0.0,neutral or dissatisfied +103723,73606,Male,Loyal Customer,46,Business travel,Business,1917,4,4,4,4,4,4,5,5,5,5,4,3,5,5,8,3.0,satisfied +103724,95532,Female,Loyal Customer,8,Personal Travel,Eco Plus,496,4,5,4,1,3,4,3,3,4,2,5,3,4,3,5,0.0,neutral or dissatisfied +103725,37609,Female,Loyal Customer,27,Personal Travel,Eco,1102,3,3,3,3,2,3,2,2,1,1,4,4,3,2,27,61.0,neutral or dissatisfied +103726,58549,Female,disloyal Customer,34,Business travel,Eco,1514,3,4,4,3,3,3,3,3,3,5,2,1,2,3,58,63.0,neutral or dissatisfied +103727,35286,Female,Loyal Customer,25,Business travel,Business,3990,3,3,2,2,3,3,3,3,1,4,2,4,3,3,0,12.0,neutral or dissatisfied +103728,15861,Female,Loyal Customer,49,Business travel,Business,3578,0,0,0,3,2,1,3,5,5,5,5,4,5,3,65,95.0,satisfied +103729,30928,Male,Loyal Customer,54,Personal Travel,Eco Plus,896,3,5,3,5,4,3,4,4,4,4,4,5,5,4,14,8.0,neutral or dissatisfied +103730,89730,Male,Loyal Customer,20,Personal Travel,Eco,1096,3,3,3,3,2,3,2,2,3,2,4,2,3,2,16,20.0,neutral or dissatisfied +103731,35310,Male,Loyal Customer,38,Business travel,Business,3199,3,3,3,3,1,3,5,4,4,4,4,3,4,2,5,21.0,satisfied +103732,128826,Male,Loyal Customer,50,Business travel,Business,2475,1,1,1,1,5,5,5,4,4,5,5,5,3,5,0,0.0,satisfied +103733,105948,Female,Loyal Customer,9,Personal Travel,Business,2329,4,5,4,2,4,1,1,4,2,3,4,1,5,1,7,0.0,satisfied +103734,32104,Female,Loyal Customer,44,Business travel,Business,2244,5,5,5,5,3,5,1,4,4,4,3,2,4,3,6,8.0,satisfied +103735,120145,Female,disloyal Customer,30,Business travel,Eco,710,3,2,2,4,5,3,2,5,3,1,2,1,2,5,0,0.0,neutral or dissatisfied +103736,120816,Male,Loyal Customer,63,Personal Travel,Eco,666,2,4,2,3,4,2,4,4,3,5,5,5,5,4,0,3.0,neutral or dissatisfied +103737,37272,Female,Loyal Customer,21,Business travel,Business,1118,4,4,4,4,5,5,5,5,1,4,1,3,3,5,5,0.0,satisfied +103738,114701,Female,Loyal Customer,47,Business travel,Business,2193,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +103739,24974,Male,Loyal Customer,42,Business travel,Eco,692,5,2,2,2,5,5,5,5,5,3,4,1,3,5,0,0.0,satisfied +103740,84507,Female,Loyal Customer,49,Business travel,Business,2486,4,4,4,4,4,5,4,4,4,4,4,4,4,3,46,14.0,satisfied +103741,107048,Male,Loyal Customer,27,Business travel,Business,2490,2,5,5,5,2,2,2,2,4,1,4,2,3,2,2,6.0,neutral or dissatisfied +103742,8779,Female,disloyal Customer,22,Business travel,Eco,552,4,0,4,1,1,4,1,1,5,3,4,3,5,1,0,69.0,neutral or dissatisfied +103743,105008,Male,Loyal Customer,60,Business travel,Business,255,4,4,4,4,2,4,5,3,3,4,3,5,3,3,23,11.0,satisfied +103744,127680,Female,Loyal Customer,10,Personal Travel,Eco Plus,2153,1,5,1,2,3,1,4,3,5,3,5,5,4,3,5,2.0,neutral or dissatisfied +103745,60796,Female,disloyal Customer,25,Business travel,Business,472,5,0,4,3,2,4,2,2,5,5,4,5,4,2,0,0.0,satisfied +103746,129077,Female,Loyal Customer,47,Business travel,Business,2583,3,3,3,3,5,5,5,3,2,4,4,5,3,5,0,0.0,satisfied +103747,78894,Female,Loyal Customer,47,Business travel,Business,1727,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +103748,102512,Male,Loyal Customer,44,Personal Travel,Eco,236,4,4,4,4,4,4,4,4,2,1,4,1,3,4,6,9.0,neutral or dissatisfied +103749,94961,Male,Loyal Customer,23,Business travel,Eco,277,2,3,4,3,2,3,1,2,3,2,4,1,4,2,0,0.0,neutral or dissatisfied +103750,9833,Male,Loyal Customer,52,Personal Travel,Eco,476,2,4,2,1,5,2,5,5,2,3,3,3,1,5,25,36.0,neutral or dissatisfied +103751,97371,Male,Loyal Customer,24,Personal Travel,Eco,347,1,2,1,4,1,1,3,1,1,4,3,3,4,1,65,62.0,neutral or dissatisfied +103752,96171,Female,Loyal Customer,39,Business travel,Business,2580,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,8.0,satisfied +103753,54203,Female,Loyal Customer,46,Personal Travel,Eco,1400,2,4,2,3,5,3,4,3,3,2,3,5,3,5,13,20.0,neutral or dissatisfied +103754,39901,Female,Loyal Customer,56,Business travel,Eco Plus,132,5,4,1,4,5,5,2,5,5,5,5,3,5,1,0,0.0,satisfied +103755,121593,Female,Loyal Customer,29,Personal Travel,Eco,936,3,4,3,1,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +103756,69641,Female,Loyal Customer,43,Business travel,Eco,569,2,2,2,2,1,3,4,2,2,2,2,1,2,3,0,44.0,neutral or dissatisfied +103757,62386,Female,Loyal Customer,47,Business travel,Business,1983,2,2,2,2,2,5,4,2,2,2,2,5,2,1,0,3.0,satisfied +103758,12382,Female,Loyal Customer,60,Business travel,Business,253,3,3,3,3,4,3,3,3,3,3,3,1,3,1,11,2.0,neutral or dissatisfied +103759,109720,Female,Loyal Customer,49,Business travel,Business,680,1,4,4,4,1,2,2,1,1,1,1,1,1,3,33,16.0,neutral or dissatisfied +103760,28755,Male,disloyal Customer,15,Business travel,Eco,1024,2,2,2,4,5,2,5,5,4,4,4,4,3,5,0,0.0,neutral or dissatisfied +103761,125301,Female,Loyal Customer,30,Business travel,Business,678,4,2,2,2,4,4,4,4,3,2,4,2,4,4,19,8.0,neutral or dissatisfied +103762,80223,Male,Loyal Customer,18,Business travel,Business,2153,3,4,3,3,3,3,3,3,2,4,3,3,4,3,30,9.0,neutral or dissatisfied +103763,93218,Female,Loyal Customer,24,Business travel,Business,1460,3,3,3,3,3,3,3,3,4,3,5,4,5,3,5,5.0,satisfied +103764,20934,Male,Loyal Customer,41,Business travel,Business,2394,5,5,5,5,5,5,4,4,4,4,4,3,4,1,0,16.0,satisfied +103765,129010,Male,Loyal Customer,18,Business travel,Business,2611,2,2,2,2,5,5,5,3,4,4,5,5,3,5,5,7.0,satisfied +103766,39923,Female,disloyal Customer,47,Business travel,Eco,1086,5,5,5,1,1,5,1,1,4,2,4,2,2,1,0,0.0,satisfied +103767,93320,Female,Loyal Customer,52,Business travel,Business,3449,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +103768,129401,Female,disloyal Customer,34,Business travel,Business,414,3,3,3,4,4,3,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +103769,90435,Female,Loyal Customer,22,Business travel,Business,270,2,2,4,2,4,4,4,4,5,2,5,3,4,4,44,37.0,satisfied +103770,109366,Male,Loyal Customer,38,Business travel,Business,2940,2,2,2,2,4,4,4,5,2,4,5,4,5,4,233,223.0,satisfied +103771,50501,Male,Loyal Customer,56,Personal Travel,Eco,109,5,5,5,4,5,5,5,5,4,4,5,5,5,5,0,0.0,satisfied +103772,52520,Female,Loyal Customer,35,Business travel,Business,110,5,5,5,5,1,4,2,4,4,4,3,1,4,2,0,0.0,satisfied +103773,21731,Female,disloyal Customer,28,Business travel,Eco,563,2,5,2,3,5,2,5,5,3,2,5,4,2,5,0,6.0,neutral or dissatisfied +103774,25506,Female,Loyal Customer,56,Business travel,Eco,481,2,4,4,4,2,3,2,2,2,2,2,1,2,3,3,0.0,neutral or dissatisfied +103775,58459,Male,Loyal Customer,53,Business travel,Business,733,5,5,5,5,5,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +103776,118324,Male,Loyal Customer,33,Business travel,Business,2811,4,4,4,4,4,4,4,4,5,4,4,5,4,4,28,19.0,satisfied +103777,63764,Female,Loyal Customer,37,Business travel,Business,1721,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +103778,37694,Male,Loyal Customer,21,Personal Travel,Eco,1005,2,1,2,2,5,2,5,5,1,4,3,4,2,5,24,10.0,neutral or dissatisfied +103779,51294,Female,Loyal Customer,21,Business travel,Eco Plus,209,3,4,5,4,3,3,2,3,4,5,4,1,3,3,2,19.0,neutral or dissatisfied +103780,76807,Male,Loyal Customer,66,Personal Travel,Eco,689,4,5,4,2,3,4,4,3,3,1,4,2,2,3,0,0.0,neutral or dissatisfied +103781,4887,Male,Loyal Customer,54,Business travel,Business,408,2,2,2,2,4,5,5,4,4,4,4,5,4,3,21,12.0,satisfied +103782,32506,Male,Loyal Customer,58,Business travel,Business,3283,5,5,5,5,2,3,5,4,4,4,5,1,4,5,0,0.0,satisfied +103783,41688,Male,Loyal Customer,11,Personal Travel,Eco,936,2,4,2,4,3,2,3,3,3,5,5,5,5,3,44,62.0,neutral or dissatisfied +103784,24509,Female,Loyal Customer,53,Personal Travel,Eco,547,3,3,3,3,2,3,3,5,5,3,2,4,5,2,0,9.0,neutral or dissatisfied +103785,26191,Female,disloyal Customer,26,Business travel,Eco,404,1,3,1,5,5,1,5,5,2,5,2,1,3,5,1,0.0,neutral or dissatisfied +103786,21424,Male,Loyal Customer,39,Business travel,Business,2934,1,1,1,1,1,3,3,5,5,5,5,1,5,4,0,2.0,satisfied +103787,55705,Female,Loyal Customer,25,Personal Travel,Eco,927,2,1,2,4,4,2,4,4,4,5,4,4,3,4,0,1.0,neutral or dissatisfied +103788,50584,Female,Loyal Customer,22,Personal Travel,Eco,86,1,4,1,1,4,1,5,4,3,5,5,4,4,4,1,4.0,neutral or dissatisfied +103789,81456,Male,Loyal Customer,60,Business travel,Business,2716,4,4,4,4,4,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +103790,68982,Female,Loyal Customer,14,Personal Travel,Eco,700,2,1,2,4,5,2,5,5,1,2,4,3,4,5,5,1.0,neutral or dissatisfied +103791,53746,Female,Loyal Customer,23,Personal Travel,Eco Plus,1208,1,5,1,3,2,1,2,2,5,5,5,2,3,2,11,16.0,neutral or dissatisfied +103792,99992,Female,Loyal Customer,47,Business travel,Business,220,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +103793,118871,Female,Loyal Customer,47,Business travel,Business,1551,1,1,1,1,2,5,4,4,4,4,4,5,4,3,22,25.0,satisfied +103794,60364,Female,Loyal Customer,54,Business travel,Business,1452,3,3,5,3,4,4,4,3,3,3,3,4,3,5,19,14.0,satisfied +103795,82805,Female,disloyal Customer,22,Business travel,Business,235,5,0,5,4,3,5,5,3,5,4,4,3,5,3,0,0.0,satisfied +103796,1024,Female,Loyal Customer,44,Business travel,Eco,312,3,1,1,1,2,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +103797,78441,Female,Loyal Customer,23,Business travel,Business,526,5,5,5,5,4,4,4,4,3,5,4,3,5,4,0,0.0,satisfied +103798,28511,Female,Loyal Customer,60,Business travel,Eco,2677,5,2,5,5,3,3,2,3,3,5,3,2,3,1,0,0.0,satisfied +103799,74654,Female,Loyal Customer,19,Personal Travel,Eco,1171,1,4,1,3,3,1,3,3,3,4,3,4,5,3,0,0.0,neutral or dissatisfied +103800,101871,Male,Loyal Customer,37,Business travel,Business,1890,3,3,3,3,4,2,4,5,5,5,5,4,5,1,13,0.0,satisfied +103801,7595,Male,Loyal Customer,58,Personal Travel,Eco Plus,594,2,4,1,4,4,1,5,4,4,4,1,5,3,4,0,0.0,neutral or dissatisfied +103802,107065,Male,Loyal Customer,60,Personal Travel,Eco,395,2,4,5,3,4,5,4,4,5,3,4,4,4,4,23,12.0,neutral or dissatisfied +103803,17824,Male,Loyal Customer,35,Personal Travel,Eco,1075,3,4,3,4,2,3,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +103804,104612,Male,Loyal Customer,46,Personal Travel,Eco Plus,369,2,5,2,4,3,2,3,3,4,2,1,5,4,3,0,0.0,neutral or dissatisfied +103805,11181,Female,Loyal Customer,52,Personal Travel,Eco,429,2,2,2,2,4,2,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +103806,89517,Female,disloyal Customer,36,Business travel,Business,550,3,2,2,2,2,2,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +103807,69001,Male,Loyal Customer,39,Business travel,Business,1391,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +103808,72016,Male,disloyal Customer,26,Business travel,Business,822,5,5,5,3,5,1,1,5,2,5,5,1,3,1,0,0.0,satisfied +103809,118511,Female,Loyal Customer,56,Business travel,Business,369,3,3,3,3,2,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +103810,6079,Male,Loyal Customer,48,Business travel,Business,2536,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +103811,12866,Male,Loyal Customer,27,Business travel,Eco Plus,641,4,4,4,4,4,4,4,4,4,5,4,3,4,4,38,40.0,neutral or dissatisfied +103812,98440,Female,disloyal Customer,28,Business travel,Business,814,2,2,2,3,2,3,5,5,4,5,5,5,3,5,212,212.0,neutral or dissatisfied +103813,13859,Male,disloyal Customer,34,Business travel,Business,667,4,4,4,4,4,4,4,4,3,4,4,5,4,4,0,22.0,neutral or dissatisfied +103814,70449,Male,Loyal Customer,64,Personal Travel,Eco,187,2,4,0,2,3,0,2,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +103815,36500,Female,Loyal Customer,42,Business travel,Eco,1121,3,1,1,1,5,4,4,3,3,3,3,1,3,2,1,0.0,satisfied +103816,98511,Male,Loyal Customer,42,Business travel,Business,3669,4,4,4,4,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +103817,39233,Female,disloyal Customer,22,Business travel,Eco,108,4,5,4,5,2,4,2,2,3,2,1,5,3,2,0,0.0,satisfied +103818,101767,Male,Loyal Customer,20,Personal Travel,Eco,1590,3,5,2,2,1,2,4,1,3,4,3,4,4,1,86,90.0,neutral or dissatisfied +103819,104499,Female,Loyal Customer,60,Business travel,Business,1609,3,3,3,3,2,4,5,5,5,5,5,5,5,3,0,15.0,satisfied +103820,78106,Male,Loyal Customer,59,Personal Travel,Eco,655,3,1,3,2,1,3,1,1,2,2,1,2,3,1,0,0.0,neutral or dissatisfied +103821,70595,Female,Loyal Customer,41,Business travel,Business,2611,4,1,1,1,3,4,4,3,4,1,3,4,1,4,11,9.0,neutral or dissatisfied +103822,112574,Female,Loyal Customer,35,Business travel,Business,1619,5,5,5,5,4,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +103823,92062,Female,disloyal Customer,15,Business travel,Eco,1522,2,2,2,2,2,2,3,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +103824,127405,Male,Loyal Customer,19,Business travel,Business,1639,1,1,1,1,5,5,5,5,4,5,5,4,1,5,0,0.0,satisfied +103825,82224,Female,Loyal Customer,58,Business travel,Business,1602,3,3,3,3,3,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +103826,80217,Female,disloyal Customer,25,Business travel,Business,2153,2,0,3,3,3,3,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +103827,64630,Male,Loyal Customer,57,Business travel,Business,247,1,1,1,1,3,5,4,4,4,4,4,4,4,5,18,19.0,satisfied +103828,40098,Female,disloyal Customer,21,Business travel,Eco,200,5,0,5,1,5,5,5,5,4,2,1,3,5,5,0,0.0,satisfied +103829,61179,Female,Loyal Customer,55,Business travel,Business,2340,5,5,5,5,2,5,5,4,4,4,4,3,4,4,108,107.0,satisfied +103830,123513,Female,Loyal Customer,59,Personal Travel,Eco,2296,1,4,1,1,5,3,4,1,1,1,1,4,1,3,5,0.0,neutral or dissatisfied +103831,33884,Female,Loyal Customer,58,Personal Travel,Eco,1105,2,5,3,4,5,5,1,3,3,3,3,5,3,5,3,3.0,neutral or dissatisfied +103832,47023,Female,Loyal Customer,49,Business travel,Eco,639,2,3,3,3,2,2,2,4,5,1,5,2,4,2,225,222.0,satisfied +103833,9583,Male,Loyal Customer,38,Business travel,Business,228,1,1,1,1,4,3,2,3,3,4,3,4,3,5,0,24.0,satisfied +103834,47308,Male,disloyal Customer,24,Business travel,Eco,588,4,4,4,2,2,4,2,2,2,1,2,1,5,2,0,0.0,satisfied +103835,34582,Male,Loyal Customer,36,Business travel,Eco,1598,4,5,5,5,4,4,4,4,1,3,4,2,4,4,0,0.0,satisfied +103836,115270,Male,Loyal Customer,39,Business travel,Business,371,3,3,3,3,5,5,4,4,4,4,4,4,4,4,6,0.0,satisfied +103837,128954,Male,disloyal Customer,38,Business travel,Business,414,4,3,3,1,2,3,2,2,5,4,5,4,4,2,0,0.0,neutral or dissatisfied +103838,58979,Male,Loyal Customer,51,Business travel,Business,1723,2,2,2,2,4,4,4,5,5,5,5,5,5,5,14,2.0,satisfied +103839,3047,Female,Loyal Customer,42,Personal Travel,Eco,489,2,5,2,2,5,4,1,3,3,2,3,5,3,2,51,59.0,neutral or dissatisfied +103840,84116,Male,disloyal Customer,37,Business travel,Business,1900,1,2,2,1,5,2,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +103841,80060,Female,Loyal Customer,28,Personal Travel,Eco,950,2,3,2,4,3,2,3,3,3,4,3,2,3,3,39,17.0,neutral or dissatisfied +103842,31913,Female,Loyal Customer,52,Business travel,Business,163,3,3,3,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +103843,89597,Female,Loyal Customer,42,Business travel,Business,1076,5,5,5,5,5,5,5,3,5,4,5,5,3,5,171,156.0,satisfied +103844,40682,Female,Loyal Customer,50,Business travel,Business,2411,4,4,5,4,3,5,2,5,5,5,5,3,5,3,0,0.0,satisfied +103845,58642,Male,Loyal Customer,77,Business travel,Eco,867,3,3,3,3,3,3,3,3,1,1,4,1,3,3,0,0.0,neutral or dissatisfied +103846,124875,Male,disloyal Customer,26,Business travel,Business,728,2,3,3,2,5,3,5,5,4,4,3,2,2,5,17,32.0,neutral or dissatisfied +103847,127971,Male,Loyal Customer,45,Business travel,Business,3727,4,4,4,4,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +103848,111508,Female,disloyal Customer,26,Business travel,Eco,391,1,0,1,4,3,1,4,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +103849,31695,Female,Loyal Customer,62,Business travel,Business,446,3,3,3,3,3,3,2,5,5,5,5,2,5,3,0,0.0,satisfied +103850,53018,Female,Loyal Customer,36,Business travel,Business,3331,3,1,1,1,1,3,3,3,3,3,3,4,3,3,0,32.0,neutral or dissatisfied +103851,112270,Male,disloyal Customer,8,Business travel,Eco,1036,3,3,3,1,5,3,5,5,3,4,4,5,4,5,1,0.0,neutral or dissatisfied +103852,119634,Male,Loyal Customer,55,Business travel,Eco,1727,3,3,3,3,3,3,3,3,2,1,2,4,3,3,7,10.0,neutral or dissatisfied +103853,41879,Female,Loyal Customer,49,Business travel,Eco,760,5,3,3,3,2,4,4,5,5,5,5,1,5,5,0,21.0,satisfied +103854,104745,Female,Loyal Customer,51,Business travel,Business,2212,5,5,5,5,3,2,5,4,4,4,4,5,4,3,24,37.0,satisfied +103855,86406,Male,Loyal Customer,72,Business travel,Business,1621,3,2,2,2,5,2,2,3,3,3,3,3,3,4,44,31.0,neutral or dissatisfied +103856,40825,Female,Loyal Customer,25,Business travel,Business,2813,1,1,1,1,1,1,1,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +103857,51504,Male,disloyal Customer,26,Business travel,Eco,370,2,3,2,5,5,2,5,5,3,3,5,3,3,5,0,0.0,neutral or dissatisfied +103858,69123,Male,Loyal Customer,51,Personal Travel,Eco,1598,0,5,0,2,3,0,1,3,3,2,3,3,4,3,1,1.0,satisfied +103859,46803,Male,Loyal Customer,50,Business travel,Eco,844,4,2,5,5,4,4,4,4,5,1,1,1,4,4,0,0.0,satisfied +103860,45825,Male,Loyal Customer,31,Personal Travel,Eco,411,3,5,3,5,1,3,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +103861,21720,Female,Loyal Customer,38,Business travel,Eco,821,4,4,5,4,4,4,4,4,5,4,3,5,5,4,23,0.0,satisfied +103862,69728,Female,Loyal Customer,8,Personal Travel,Eco,1372,3,4,3,1,2,3,2,2,3,3,3,5,4,2,0,13.0,neutral or dissatisfied +103863,16083,Male,disloyal Customer,22,Business travel,Eco,744,2,2,2,3,1,2,3,1,5,3,4,3,2,1,0,0.0,neutral or dissatisfied +103864,112054,Female,Loyal Customer,31,Personal Travel,Business,1754,1,2,2,4,2,2,2,2,4,1,4,3,3,2,12,2.0,neutral or dissatisfied +103865,46017,Male,Loyal Customer,35,Business travel,Business,3795,5,5,5,5,4,5,4,2,2,2,2,2,2,1,0,0.0,satisfied +103866,62394,Female,Loyal Customer,14,Personal Travel,Eco,2704,1,2,1,2,3,1,3,3,1,3,2,1,3,3,0,4.0,neutral or dissatisfied +103867,81857,Male,Loyal Customer,30,Business travel,Eco Plus,1416,3,2,2,2,3,3,3,3,2,4,3,2,3,3,0,24.0,neutral or dissatisfied +103868,37051,Female,Loyal Customer,57,Personal Travel,Eco Plus,1105,1,5,1,5,4,3,3,5,5,1,5,1,5,1,0,1.0,neutral or dissatisfied +103869,55713,Male,Loyal Customer,18,Personal Travel,Eco,895,4,5,4,3,4,1,1,3,5,4,5,1,3,1,212,206.0,neutral or dissatisfied +103870,76945,Female,Loyal Customer,48,Business travel,Business,1990,4,4,4,4,3,3,4,2,2,2,2,5,2,4,0,0.0,satisfied +103871,29448,Male,Loyal Customer,74,Business travel,Business,1587,1,3,3,3,2,3,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +103872,127906,Male,Loyal Customer,16,Personal Travel,Eco,1671,5,2,5,3,3,5,3,3,1,2,3,3,3,3,5,0.0,satisfied +103873,50932,Male,Loyal Customer,37,Personal Travel,Eco,86,1,5,1,2,1,1,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +103874,7527,Female,Loyal Customer,23,Business travel,Business,762,4,1,1,1,4,4,4,4,2,4,3,4,3,4,0,13.0,neutral or dissatisfied +103875,10393,Male,Loyal Customer,48,Business travel,Business,74,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +103876,98579,Female,Loyal Customer,58,Business travel,Business,1987,5,5,5,5,2,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +103877,14662,Male,Loyal Customer,27,Business travel,Eco Plus,162,5,4,4,4,5,5,5,5,2,3,4,2,3,5,0,0.0,satisfied +103878,15176,Male,Loyal Customer,37,Business travel,Business,2445,4,5,5,5,1,4,4,4,4,4,4,4,4,1,1,0.0,neutral or dissatisfied +103879,59339,Female,Loyal Customer,30,Business travel,Business,2338,1,1,1,1,4,4,4,4,3,4,4,5,5,4,2,0.0,satisfied +103880,124279,Male,Loyal Customer,42,Business travel,Business,1689,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +103881,9345,Female,Loyal Customer,51,Business travel,Business,384,2,2,2,2,5,5,5,4,4,4,4,3,4,3,54,51.0,satisfied +103882,35492,Male,Loyal Customer,8,Personal Travel,Eco,1028,2,5,2,4,4,2,4,4,3,3,4,4,5,4,11,0.0,neutral or dissatisfied +103883,110591,Female,Loyal Customer,65,Personal Travel,Eco,488,3,5,5,5,3,5,5,2,2,5,2,3,2,4,0,0.0,neutral or dissatisfied +103884,6737,Female,Loyal Customer,19,Personal Travel,Eco,334,2,5,2,1,5,2,5,5,3,2,4,3,5,5,25,11.0,neutral or dissatisfied +103885,122528,Male,Loyal Customer,40,Business travel,Business,500,4,4,4,4,5,4,4,3,3,3,3,5,3,4,47,26.0,satisfied +103886,92323,Male,disloyal Customer,36,Business travel,Business,2556,3,3,3,1,3,5,5,5,5,4,5,5,5,5,2,13.0,neutral or dissatisfied +103887,54253,Female,Loyal Customer,51,Personal Travel,Eco,1222,5,4,5,4,3,4,4,3,3,5,3,1,3,4,4,0.0,satisfied +103888,115517,Male,disloyal Customer,38,Business travel,Business,447,2,2,2,4,3,2,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +103889,123802,Female,Loyal Customer,43,Business travel,Business,3885,5,5,5,5,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +103890,80087,Female,Loyal Customer,56,Business travel,Eco Plus,550,3,5,5,5,2,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +103891,83013,Male,Loyal Customer,54,Business travel,Business,1991,5,5,5,5,2,5,5,4,4,5,4,5,4,4,35,31.0,satisfied +103892,46016,Female,disloyal Customer,37,Business travel,Business,596,3,3,3,4,3,3,3,3,1,1,3,1,4,3,110,121.0,neutral or dissatisfied +103893,3397,Female,Loyal Customer,58,Business travel,Business,296,3,3,5,3,2,3,4,3,3,3,3,1,3,1,0,29.0,neutral or dissatisfied +103894,86549,Male,Loyal Customer,26,Business travel,Business,712,4,4,4,4,5,5,5,5,3,4,4,3,4,5,17,26.0,satisfied +103895,66030,Female,disloyal Customer,24,Business travel,Eco,1055,1,1,1,2,1,1,1,1,3,3,5,5,4,1,13,10.0,neutral or dissatisfied +103896,71445,Male,Loyal Customer,57,Business travel,Eco,867,4,5,5,5,4,4,4,4,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +103897,102203,Female,Loyal Customer,60,Business travel,Business,1599,5,5,5,5,5,5,4,4,4,4,4,4,4,4,9,7.0,satisfied +103898,60666,Male,Loyal Customer,50,Personal Travel,Eco,1620,3,1,3,4,2,3,2,2,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +103899,94171,Female,disloyal Customer,23,Business travel,Eco,192,2,1,2,3,2,2,2,2,3,1,4,2,3,2,3,0.0,neutral or dissatisfied +103900,73097,Male,Loyal Customer,49,Business travel,Business,2347,4,4,4,4,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +103901,68825,Male,disloyal Customer,30,Business travel,Business,1995,1,1,1,3,4,1,5,4,3,2,4,5,5,4,7,14.0,neutral or dissatisfied +103902,54173,Female,disloyal Customer,22,Business travel,Eco,1000,1,1,1,5,1,1,1,1,4,5,1,5,4,1,0,0.0,neutral or dissatisfied +103903,62567,Male,Loyal Customer,27,Business travel,Business,1723,1,3,3,3,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied From 75f0b635420814c5e79f3c72d3493c7682d6e412 Mon Sep 17 00:00:00 2001 From: Charles Mensah Date: Tue, 9 Dec 2025 15:20:16 +0100 Subject: [PATCH 10/26] charles project --- first_project | 1 + 1 file changed, 1 insertion(+) create mode 160000 first_project diff --git a/first_project b/first_project new file mode 160000 index 00000000..1aba4142 --- /dev/null +++ b/first_project @@ -0,0 +1 @@ +Subproject commit 1aba41424a647ec544cf9ae5273ff0a75a570b0e From ad0ad7056bb44c3dc0c005d0cd9a76800092d225 Mon Sep 17 00:00:00 2001 From: Marta Date: Tue, 9 Dec 2025 17:53:53 +0100 Subject: [PATCH 11/26] Completed Data Cleaning, H1-H3 Analysis --- notebooks/Airline_Project1-Copy_marta.ipynb | 1940 +++++++++++++++++++ 1 file changed, 1940 insertions(+) create mode 100644 notebooks/Airline_Project1-Copy_marta.ipynb diff --git a/notebooks/Airline_Project1-Copy_marta.ipynb b/notebooks/Airline_Project1-Copy_marta.ipynb new file mode 100644 index 00000000..7c315000 --- /dev/null +++ b/notebooks/Airline_Project1-Copy_marta.ipynb @@ -0,0 +1,1940 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "561808a4-27ef-4523-892a-8584a31efefa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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Unnamed: 0idAgeFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online bookingGate locationFood and drinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutes
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
7796462FemaleLoyal Customer52Business travelBusiness203543...555545440.0satisfied
131383502MaleLoyal Customer33Personal TravelEco94642...445222400.0satisfied
161671142FemaleLoyal Customer26Business travelBusiness212333...45345444951.0satisfied
..................................................................
10389010389080087FemaleLoyal Customer56Business travelEco Plus55035...333343300.0satisfied
10389110389183013MaleLoyal Customer54Business travelBusiness199155...44545443531.0satisfied
10389410389486549MaleLoyal Customer26Business travelBusiness71244...53443451726.0satisfied
103897103897102203FemaleLoyal Customer60Business travelBusiness159955...444444497.0satisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
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45025 rows × 25 columns

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" + ], + "text/plain": [ + " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", + "2 2 110028 Female Loyal Customer 26 Business travel \n", + "4 4 119299 Male Loyal Customer 61 Business travel \n", + "7 7 96462 Female Loyal Customer 52 Business travel \n", + "13 13 83502 Male Loyal Customer 33 Personal Travel \n", + "16 16 71142 Female Loyal Customer 26 Business travel \n", + "... ... ... ... ... ... ... \n", + "103890 103890 80087 Female Loyal Customer 56 Business travel \n", + "103891 103891 83013 Male Loyal Customer 54 Business travel \n", + "103894 103894 86549 Male Loyal Customer 26 Business travel \n", + "103897 103897 102203 Female Loyal Customer 60 Business travel \n", + "103900 103900 73097 Male Loyal Customer 49 Business travel \n", + "\n", + " Class Flight Distance Inflight wifi service \\\n", + "2 Business 1142 2 \n", + "4 Business 214 3 \n", + "7 Business 2035 4 \n", + "13 Eco 946 4 \n", + "16 Business 2123 3 \n", + "... ... ... ... \n", + "103890 Eco Plus 550 3 \n", + "103891 Business 1991 5 \n", + "103894 Business 712 4 \n", + "103897 Business 1599 5 \n", + "103900 Business 2347 4 \n", + "\n", + " Departure/Arrival time convenient ... Inflight entertainment \\\n", + "2 2 ... 5 \n", + "4 3 ... 3 \n", + "7 3 ... 5 \n", + "13 2 ... 4 \n", + "16 3 ... 4 \n", + "... ... ... ... \n", + "103890 5 ... 3 \n", + "103891 5 ... 4 \n", + "103894 4 ... 5 \n", + "103897 5 ... 4 \n", + "103900 4 ... 5 \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "2 4 3 4 4 \n", + "4 3 4 4 3 \n", + "7 5 5 5 4 \n", + "13 4 5 2 2 \n", + "16 5 3 4 5 \n", + "... ... ... ... ... \n", + "103890 3 3 3 4 \n", + "103891 4 5 4 5 \n", + "103894 3 4 4 3 \n", + "103897 4 4 4 4 \n", + "103900 5 5 5 5 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "2 4 5 0 \n", + "4 3 3 0 \n", + "7 5 4 4 \n", + "13 2 4 0 \n", + "16 4 4 49 \n", + "... ... ... ... \n", + "103890 3 3 0 \n", + "103891 4 4 35 \n", + "103894 4 5 17 \n", + "103897 4 4 9 \n", + "103900 5 4 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction \n", + "2 0.0 satisfied \n", + "4 0.0 satisfied \n", + "7 0.0 satisfied \n", + "13 0.0 satisfied \n", + "16 51.0 satisfied \n", + "... ... ... \n", + "103890 0.0 satisfied \n", + "103891 31.0 satisfied \n", + "103894 26.0 satisfied \n", + "103897 7.0 satisfied \n", + "103900 0.0 satisfied \n", + "\n", + "[45025 rows x 25 columns]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfSatisfied" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Data cleaning complete. Ready for analysis!\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\Marta\\AppData\\Local\\Temp\\ipykernel_29024\\1995285321.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", + "\n", + "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", + "\n", + "\n", + " df['Arrival Delay in Minutes'].fillna(median_delay, inplace=True)\n" + ] + } + ], + "source": [ + "def clean_airloops_data(df):\n", + " # 1. Handle Missing Values: Fill 'Arrival Delay in Minutes' with the median\n", + " median_delay = df['Arrival Delay in Minutes'].median()\n", + " df['Arrival Delay in Minutes'].fillna(median_delay, inplace=True)\n", + "\n", + " # Note: If 'Inflight wifi service' has nulls (which it often does),\n", + " # we can fill those with 0, assuming 'No Service' or 'Not Applicable'.\n", + " if 'Inflight wifi service' in df.columns and df['Inflight wifi service'].isnull().any():\n", + " df['Inflight wifi service'].fillna(0, inplace=True)\n", + "\n", + " # 2. Drop Unnecessary Columns\n", + " cols_to_drop = ['Unnamed: 0']\n", + " df.drop(columns=cols_to_drop, inplace=True, errors='ignore')\n", + "\n", + " # 3. Create the Target Variable (satisfaction_binary)\n", + " # Using .map() is a simple, clear way to do binary encoding.\n", + " satisfaction_map = {'satisfied': 1, 'neutral or dissatisfied': 0}\n", + " df['satisfaction_binary'] = df['satisfaction'].map(satisfaction_map)\n", + " df.drop(columns=['satisfaction'], inplace=True)\n", + "\n", + " # 4. Format Column Names (Lowercase and Underscore)\n", + " df.columns = df.columns.str.lower().str.replace(' ', '_')\n", + "\n", + " print(\"\\nData cleaning complete. Ready for analysis!\")\n", + " return df\n", + "\n", + "# Apply the function to your DataFrame\n", + "df_cleaned = clean_airloops_data(df.copy())" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "1bbec001-ab5d-47ef-b248-567cfc4680bd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Class Distribution ---\n", + "class\n", + "Business 49665\n", + "Eco 46745\n", + "Eco Plus 7494\n", + "Name: count, dtype: int64\n", + "------------------------------\n", + "\n", + "--- Average Satisfaction by Class ---\n", + "class\n", + "Business 0.694251\n", + "Eco Plus 0.246064\n", + "Eco 0.186138\n", + "Name: satisfaction_binary, dtype: float64\n" + ] + } + ], + "source": [ + "# 1. Check Class Distribution (How many passengers in each class?)\n", + "print(\"--- Class Distribution ---\")\n", + "print(df_cleaned['class'].value_counts())\n", + "print(\"-\" * 30)\n", + "\n", + "# 2. Calculate Mean Satisfaction by Class\n", + "# The mean of 'satisfaction_binary' is the percentage of satisfied customers (1s)\n", + "satisfaction_by_class = df_cleaned.groupby('class')['satisfaction_binary'].mean().sort_values(ascending=False)\n", + "\n", + "print(\"\\n--- Average Satisfaction by Class ---\")\n", + "print(satisfaction_by_class)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "a93656bd-3d83-4c25-a002-b029618ce142", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plot saved as 'satisfaction_by_class_bar_chart.png'\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# The results you provided, stored in a DataFrame for plotting\n", + "satisfaction_data = {\n", + " 'Class': ['Business', 'Eco Plus', 'Eco'],\n", + " 'Average_Satisfaction': [0.694251, 0.246064, 0.186138]\n", + "}\n", + "plot_df = pd.DataFrame(satisfaction_data)\n", + "\n", + "# Sort the data for a cleaner visual presentation (highest to lowest)\n", + "plot_df = plot_df.sort_values(by='Average_Satisfaction', ascending=False)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "bars = plt.bar(plot_df['Class'], plot_df['Average_Satisfaction'], color=['#1f77b4', '#ff7f0e', '#2ca02c']) # Custom colors for visual separation\n", + "\n", + "# Add labels and title\n", + "plt.title('Average Passenger Satisfaction by Class', fontsize=14)\n", + "plt.xlabel('Travel Class', fontsize=12)\n", + "plt.ylabel('Average Satisfaction (Percentage)', fontsize=12)\n", + "plt.yticks([0.0, 0.2, 0.4, 0.6, 0.8, 1.0], ['0%', '20%', '40%', '60%', '80%', '100%']) # Format y-axis as percentages\n", + "\n", + "# Add the percentage values on top of the bars for clarity\n", + "for bar in bars:\n", + " yval = bar.get_height()\n", + " plt.text(bar.get_x() + bar.get_width()/2, yval + 0.01, f'{yval:.1%}', ha='center', va='bottom', fontsize=10)\n", + "\n", + "plt.grid(axis='y', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('satisfaction_by_class_bar_chart.png')\n", + "print(\"Plot saved as 'satisfaction_by_class_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "04285d9a-2d82-41ac-bcb3-ad70d26241f3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Customer Type Distribution ---\n", + "customer_type\n", + "Loyal Customer 84923\n", + "disloyal Customer 18981\n", + "Name: count, dtype: int64\n", + "------------------------------\n", + "\n", + "--- Average Satisfaction by Customer Type ---\n", + "customer_type\n", + "Loyal Customer 0.477291\n", + "disloyal Customer 0.236658\n", + "Name: satisfaction_binary, dtype: float64\n" + ] + } + ], + "source": [ + "#cleaned DataFrame is named 'df_cleaned'\n", + "\n", + "# 1. Check Customer Type Distribution\n", + "print(\"--- Customer Type Distribution ---\")\n", + "print(df_cleaned['customer_type'].value_counts())\n", + "print(\"-\" * 30)\n", + "\n", + "# 2. Calculate Mean Satisfaction by Customer Type\n", + "# The mean of 'satisfaction_binary' is the percentage of satisfied customers (1s)\n", + "satisfaction_by_customer_type = df_cleaned.groupby('customer_type')['satisfaction_binary'].mean().sort_values(ascending=False)\n", + "\n", + "print(\"\\n--- Average Satisfaction by Customer Type ---\")\n", + "print(satisfaction_by_customer_type)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "34c88420-425a-4fa8-b1c3-fae8267f4f28", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plot saved as 'satisfaction_by_customer_type_bar_chart.png'\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# The results you provided, stored in a DataFrame for plotting\n", + "satisfaction_data = {\n", + " 'Customer_Type': ['Loyal Customer', 'Disloyal Customer'],\n", + " 'Average_Satisfaction': [0.477291, 0.236658]\n", + "}\n", + "plot_df_h2 = pd.DataFrame(satisfaction_data)\n", + "\n", + "# Sort the data for presentation\n", + "plot_df_h2 = plot_df_h2.sort_values(by='Average_Satisfaction', ascending=False)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "bars = plt.bar(plot_df_h2['Customer_Type'], plot_df_h2['Average_Satisfaction'], color=['#3a5e8c', '#a63a50'])\n", + "\n", + "# Add labels and title\n", + "plt.title('Average Passenger Satisfaction: Loyal vs. Disloyal', fontsize=14)\n", + "plt.xlabel('Customer Type', fontsize=12)\n", + "plt.ylabel('Average Satisfaction (Percentage)', fontsize=12)\n", + "plt.yticks([0.0, 0.1, 0.2, 0.3, 0.4, 0.5], ['0%', '10%', '20%', '30%', '40%', '50%'])\n", + "\n", + "# Add the percentage values on top of the bars\n", + "for bar in bars:\n", + " yval = bar.get_height()\n", + " plt.text(bar.get_x() + bar.get_width()/2, yval + 0.01, f'{yval:.1%}', ha='center', va='bottom', fontsize=10)\n", + "\n", + "plt.grid(axis='y', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('satisfaction_by_customer_type_bar_chart.png')\n", + "print(\"Plot saved as 'satisfaction_by_customer_type_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "932da6b7-7591-43f7-8629-a8f47c20d0c6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- Correlation of Service Features with Satisfaction (r value) ---\n", + "online_boarding 0.503557\n", + "inflight_entertainment 0.398059\n", + "seat_comfort 0.349459\n", + "on-board_service 0.322383\n", + "leg_room_service 0.313131\n", + "cleanliness 0.305198\n", + "inflight_wifi_service 0.284245\n", + "baggage_handling 0.247749\n", + "inflight_service 0.244741\n", + "checkin_service 0.236174\n", + "food_and_drink 0.209936\n", + "ease_of_online_booking 0.171705\n", + "gate_location 0.000682\n", + "departure_delay_in_minutes -0.050494\n", + "departure/arrival_time_convenient -0.051601\n", + "arrival_delay_in_minutes -0.057435\n", + "Name: satisfaction_binary, dtype: float64\n" + ] + } + ], + "source": [ + "# Assuming your cleaned DataFrame is named 'df_cleaned'\n", + "\n", + "# 1. Identify Service Columns (The columns with rating scores or delay metrics)\n", + "# We include all rating columns and the delay columns.\n", + "service_columns = [\n", + " 'inflight_wifi_service',\n", + " 'departure/arrival_time_convenient',\n", + " 'ease_of_online_booking',\n", + " 'gate_location',\n", + " 'food_and_drink',\n", + " 'online_boarding',\n", + " 'seat_comfort',\n", + " 'inflight_entertainment',\n", + " 'on-board_service',\n", + " 'leg_room_service',\n", + " 'baggage_handling',\n", + " 'checkin_service',\n", + " 'inflight_service',\n", + " 'cleanliness',\n", + " 'departure_delay_in_minutes',\n", + " 'arrival_delay_in_minutes'\n", + "]\n", + "\n", + "# 2. Calculate Correlation with satisfaction_binary and sort the results\n", + "# The Pearson correlation coefficient (r) is used here.\n", + "correlation_results = df_cleaned[service_columns + ['satisfaction_binary']].corr()['satisfaction_binary'].sort_values(ascending=False)\n", + "\n", + "# Remove the correlation of the target variable with itself (which is always 1)\n", + "correlation_results = correlation_results.drop('satisfaction_binary')\n", + "\n", + "print(\"--- Correlation of Service Features with Satisfaction (r value) ---\")\n", + "print(correlation_results)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "d96a09e5-1756-473e-9ed4-26fb17828613", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Plot saved as 'service_correlation_bar_chart.png'\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "\n", + "# The results you provided, stored in a Series for plotting\n", + "data = {\n", + " 'online_boarding': 0.503557,\n", + " 'inflight_entertainment': 0.398059,\n", + " 'seat_comfort': 0.349459,\n", + " 'on-board_service': 0.322383,\n", + " 'leg_room_service': 0.313131,\n", + " 'cleanliness': 0.305198,\n", + " 'inflight_wifi_service': 0.284245,\n", + " 'baggage_handling': 0.247749,\n", + " 'inflight_service': 0.244741,\n", + " 'checkin_service': 0.236174,\n", + " 'food_and_drink': 0.209936,\n", + " 'ease_of_online_booking': 0.171705,\n", + " 'gate_location': 0.000682,\n", + " 'departure_delay_in_minutes': -0.050494,\n", + " 'departure/arrival_time_convenient': -0.051601,\n", + " 'arrival_delay_in_minutes': -0.057435\n", + "}\n", + "\n", + "correlation_results = pd.Series(data)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(10, 7))\n", + "\n", + "# Define colors: Green for positive correlation, Red for negative\n", + "colors = ['g' if x > 0 else 'r' for x in correlation_results]\n", + "\n", + "# Plot the horizontal bar chart\n", + "correlation_results.plot(kind='barh', color=colors)\n", + "\n", + "# Add labels and title\n", + "plt.title('Correlation (r) of Service Features with Passenger Satisfaction', fontsize=14)\n", + "plt.xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "plt.ylabel('Service Feature', fontsize=12)\n", + "\n", + "# Add a vertical line at r=0 for reference\n", + "plt.axvline(0, color='gray', linestyle='--', linewidth=0.8)\n", + "\n", + "plt.grid(axis='x', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('service_correlation_bar_chart.png')\n", + "print(\"Plot saved as 'service_correlation_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a61cea65-f81b-4393-8d6c-6ef0aed5f3c3", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 305914ce715b4aa64d53e9b2bfb1f6472b640f58 Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Tue, 9 Dec 2025 20:47:44 +0100 Subject: [PATCH 12/26] D2 commit --- notebooks/Airline_Project1.ipynb | 5617 ++++++++++++++++++++++++++---- 1 file changed, 4958 insertions(+), 659 deletions(-) diff --git a/notebooks/Airline_Project1.ipynb b/notebooks/Airline_Project1.ipynb index f2526582..a997ed4e 100644 --- a/notebooks/Airline_Project1.ipynb +++ b/notebooks/Airline_Project1.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": 1, "id": "561808a4-27ef-4523-892a-8584a31efefa", "metadata": {}, "outputs": [ @@ -402,7 +402,7 @@ "[103904 rows x 25 columns]" ] }, - "execution_count": 3, + "execution_count": 1, "metadata": {}, "output_type": "execute_result" } @@ -410,6 +410,11 @@ "source": [ "import pandas as pd\n", "import numpy as np\n", + "from scipy import stats\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", "\n", "df=pd.read_csv('train.csv')\n", "df" @@ -417,67 +422,33 @@ }, { "cell_type": "code", - "execution_count": 13, - "id": "45c65011-e822-4684-bc5d-b394ba4aafea", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "satisfaction\n", - "neutral or dissatisfied 58879\n", - "satisfied 45025\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df['satisfaction'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "caaec0b4-342d-4c69-ba35-41553e791c96", + "execution_count": 2, + "id": "a86604ec-da44-40c0-894e-0a118b9ca685", "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 84923\n", - "disloyal Customer 18981\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_9620\\1018124088.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" + ] } ], "source": [ - "df['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "6f945079-4c90-40ee-83b9-53af53e43388", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied=df[df['satisfaction'] == 'satisfied']\n", - "dfDisatisfied=df[df['satisfaction'] == 'neutral or dissatisfied']" + "binary_change= {\n", + " 'satisfied': 1,\n", + " 'neutral or dissatisfied': 0,\n", + "}\n", + "\n", + "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", + "df.drop(columns=['Unnamed: 0'], inplace=True)" ] }, { "cell_type": "code", - "execution_count": 20, - "id": "247db4d7-3a0d-4c98-ab26-f537b049e252", + "execution_count": 3, + "id": "d113003b-b385-4d24-a8a7-fade2501e0c2", "metadata": {}, "outputs": [ { @@ -501,18 +472,17 @@ " \n", " \n", " \n", - " Unnamed: 0\n", " id\n", + " Gender\n", + " Customer Type\n", " Age\n", + " Type of Travel\n", + " Class\n", " Flight Distance\n", " Inflight wifi service\n", " Departure/Arrival time convenient\n", " Ease of Online booking\n", - " Gate location\n", - " Food and drink\n", - " Online boarding\n", - " Seat comfort\n", - " Inflight entertainment\n", + " ...\n", " On-board service\n", " Leg room service\n", " Baggage handling\n", @@ -521,272 +491,3641 @@ " Cleanliness\n", " Departure Delay in Minutes\n", " Arrival Delay in Minutes\n", + " satisfaction\n", + " satisfaction_binary\n", " \n", " \n", " \n", " \n", - " count\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 45025.000000\n", - " 44897.000000\n", - " \n", - " \n", - " mean\n", - " 51789.242754\n", - " 65512.609928\n", - " 41.750583\n", - " 1530.140255\n", - " 3.161288\n", - " 2.970305\n", - " 3.031582\n", - " 2.977879\n", - " 3.521310\n", - 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103904 rows × 25 columns

\n", + "" + ], + "text/plain": [ + " id Gender Customer Type Age Type of Travel Class \\\n", + "0 70172 Male Loyal Customer 13 Personal Travel Eco Plus \n", + "1 5047 Male disloyal Customer 25 Business travel Business \n", + "2 110028 Female Loyal Customer 26 Business travel Business \n", + "3 24026 Female Loyal Customer 25 Business travel Business \n", + "4 119299 Male Loyal Customer 61 Business travel Business \n", + "... ... ... ... ... ... ... \n", + "103899 94171 Female disloyal Customer 23 Business travel Eco \n", + "103900 73097 Male Loyal Customer 49 Business travel Business \n", + "103901 68825 Male disloyal Customer 30 Business travel Business \n", + "103902 54173 Female disloyal Customer 22 Business travel Eco \n", + "103903 62567 Male Loyal Customer 27 Business travel Business \n", + "\n", + " Flight Distance Inflight wifi service \\\n", + "0 460 3 \n", + "1 235 3 \n", + "2 1142 2 \n", + "3 562 2 \n", + "4 214 3 \n", + "... ... ... \n", + "103899 192 2 \n", + "103900 2347 4 \n", + "103901 1995 1 \n", + "103902 1000 1 \n", + "103903 1723 1 \n", + "\n", + " Departure/Arrival time convenient Ease of Online booking ... \\\n", + "0 4 3 ... \n", + "1 2 3 ... \n", + "2 2 2 ... \n", + "3 5 5 ... \n", + "4 3 3 ... \n", + "... ... ... ... \n", + "103899 1 2 ... \n", + "103900 4 4 ... \n", + "103901 1 1 ... \n", + "103902 1 1 ... \n", + "103903 3 3 ... \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "0 4 3 4 4 \n", + "1 1 5 3 1 \n", + "2 4 3 4 4 \n", + "3 2 5 3 1 \n", + "4 3 4 4 3 \n", + "... ... ... ... ... \n", + "103899 3 1 4 2 \n", + "103900 5 5 5 5 \n", + "103901 3 2 4 5 \n", + "103902 4 5 1 5 \n", + "103903 1 1 4 4 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "0 5 5 25 \n", + "1 4 1 1 \n", + "2 4 5 0 \n", + "3 4 2 11 \n", + "4 3 3 0 \n", + "... ... ... ... \n", + "103899 3 2 3 \n", + "103900 5 4 0 \n", + "103901 5 4 7 \n", + "103902 4 1 0 \n", + "103903 3 1 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction satisfaction_binary \n", + "0 18.0 neutral or dissatisfied 0 \n", + "1 6.0 neutral or dissatisfied 0 \n", + "2 0.0 satisfied 1 \n", + "3 9.0 neutral or dissatisfied 0 \n", + "4 0.0 satisfied 1 \n", + "... ... ... ... \n", + "103899 0.0 neutral or dissatisfied 0 \n", + "103900 0.0 satisfied 1 \n", + "103901 14.0 neutral or dissatisfied 0 \n", + "103902 0.0 neutral or dissatisfied 0 \n", + "103903 0.0 neutral or dissatisfied 0 \n", + "\n", + "[103904 rows x 25 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "45c65011-e822-4684-bc5d-b394ba4aafea", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "satisfaction\n", + "neutral or dissatisfied 58879\n", + "satisfied 45025\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['satisfaction'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "caaec0b4-342d-4c69-ba35-41553e791c96", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 84923\n", + "disloyal Customer 18981\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "6f945079-4c90-40ee-83b9-53af53e43388", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", + "dfDisatisfied=df[df['satisfaction_binary'] == 0]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6abbfb4e-11bc-43d4-80e5-99626252e77b", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Type of Travel',\n", + " 'Class',\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "# --- 2. Initialize a Dictionary to Store Results ---\n", + "results = {\n", + " 'Metric': [],\n", + " 'Mean_Satisfied': [],\n", + " 'Mean_Dissatisfied': [],\n", + " 'T_Statistic': [],\n", + " 'P_Value': [],\n", + " 'Significance (α=0.05)': []\n", + "}\n", + "\n", + "# --- 3. Loop Through Columns and Perform T-Test ---\n", + "for col in metric_columns:\n", + " # 3a. Isolate and clean data for the current column\n", + " data_sat = dfSatisfied[col].dropna()\n", + " data_dis = dfDisatisfied[col].dropna()\n", + "\n", + " # Skip if one of the groups has no data\n", + " if len(data_sat) == 0 or len(data_dis) == 0:\n", + " continue\n", + "\n", + " # 3b. Perform Welch's T-Test (equal_var=False)\n", + " t_stat, p_value = stats.ttest_ind(\n", + " a=data_sat,\n", + " b=data_dis,\n", + " equal_var=False\n", + " )\n", + "\n", + " # 3c. Store Results\n", + " is_significant = 'Yes (Reject H0)' if p_value <= 0.05 else 'No (Fail to Reject H0)'\n", + "\n", + " results['Metric'].append(col)\n", + " results['Mean_Satisfied'].append(data_sat.mean())\n", + " results['Mean_Dissatisfied'].append(data_dis.mean())\n", + " results['T_Statistic'].append(t_stat)\n", + " results['P_Value'].append(p_value)\n", + " results['Significance (α=0.05)'].append(is_significant)\n", + "\n", + "# --- 4. Convert Results Dictionary to a DataFrame ---\n", + "results_df = pd.DataFrame(results)\n", + "\n", + "# --- 5. Print/Display Results ---\n", + "print(results_df.round(4))" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "3e5ecb36-ada2-4925-9e0d-2ae0996881c7", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['id',\n", + " 'Gender',\n", + " 'Customer Type',\n", + " 'Age',\n", + " 'Type of Travel',\n", + " 'Class',\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " 'satisfaction',\n", + " 'satisfaction_binary']" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "list(df)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "247db4d7-3a0d-4c98-ab26-f537b049e252", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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10389860666MaleLoyal Customer50Personal TravelEco1620313...43424200.0neutral or dissatisfied0
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58879 rows × 25 columns

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satisfactionneutral or dissatisfiedsatisfied
MetricStatistic
Agemean37.56668841.750583
median36.00000043.000000
std16.45982512.767833
Arrival Delay in Minutesmean17.12753612.630799
median0.0000000.000000
std40.56024835.962008
Baggage handlingmean3.3759913.966396
median4.0000004.000000
std1.1769781.099607
Checkin servicemean3.0429523.646041
median3.0000004.000000
std1.2811581.158732
Cleanlinessmean2.9361233.744342
median3.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.000000
std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.000000
std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.000000
std1.1756031.091486
Inflight wifi servicemean2.3996333.161288
median2.0000004.000000
std0.9643481.588697
Leg room servicemean2.9908123.822143
median3.0000004.000000
std1.3031591.175515
On-board servicemean3.0191583.857324
median3.0000004.000000
std1.2857901.127130
Online boardingmean2.6561254.027474
median3.0000004.000000
std1.1459051.191609
Seat comfortmean3.0362953.966530
median3.0000004.0000004.0000004.0000000.0000000.000000
75%77741.00000097691.00000051.0000002405.0000005.0000004.0000004.0000004.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000009.0000008.000000std1.3031421.142077
\n", + "
" + ], + "text/plain": [ + "satisfaction neutral or dissatisfied \\\n", + "Metric Statistic \n", + "Age mean 37.566688 \n", + " median 36.000000 \n", + " std 16.459825 \n", + "Arrival Delay in Minutes mean 17.127536 \n", + " median 0.000000 \n", + " std 40.560248 \n", + "Baggage handling mean 3.375991 \n", + " median 4.000000 \n", + " std 1.176978 \n", + "Checkin service mean 3.042952 \n", + " median 3.000000 \n", + " std 1.281158 \n", + "Cleanliness mean 2.936123 \n", + " median 3.000000 \n", + " std 1.325955 \n", + "Departure Delay in Minutes mean 16.503728 \n", + " median 0.000000 \n", + " std 40.191886 \n", + "Departure/Arrival time convenient mean 3.129112 \n", + " median 3.000000 \n", + " std 1.500368 \n", + "Ease of Online booking mean 2.546850 \n", + " median 3.000000 \n", + " std 1.205847 \n", + "Flight Distance mean 928.919971 \n", + " median 671.000000 \n", + " std 790.452308 \n", + "Food and drink mean 2.958050 \n", + " median 3.000000 \n", + " std 1.346607 \n", + "Gate location mean 2.976121 \n", + " median 3.000000 \n", + " std 1.198500 \n", + "Inflight entertainment mean 2.894156 \n", + " median 3.000000 \n", + " std 1.323619 \n", + "Inflight service mean 3.388814 \n", + " median 4.000000 \n", + " std 1.175603 \n", + "Inflight wifi service mean 2.399633 \n", + " median 2.000000 \n", + " std 0.964348 \n", + "Leg room service mean 2.990812 \n", + " median 3.000000 \n", + " std 1.303159 \n", + "On-board service mean 3.019158 \n", + " median 3.000000 \n", + " std 1.285790 \n", + "Online boarding mean 2.656125 \n", + " median 3.000000 \n", + " std 1.145905 \n", + "Seat comfort mean 3.036295 \n", + " median 3.000000 \n", + " std 1.303142 \n", + "\n", + "satisfaction satisfied \n", + "Metric Statistic \n", + "Age mean 41.750583 \n", + " median 43.000000 \n", + " std 12.767833 \n", + "Arrival Delay in Minutes mean 12.630799 \n", + " median 0.000000 \n", + " std 35.962008 \n", + "Baggage handling mean 3.966396 \n", + " median 4.000000 \n", + " std 1.099607 \n", + "Checkin service mean 3.646041 \n", + " median 4.000000 \n", + " std 1.158732 \n", + "Cleanliness mean 3.744342 \n", + " median 4.000000 \n", + " std 1.142247 \n", + "Departure Delay in Minutes mean 12.608084 \n", + " median 0.000000 \n", + " std 35.382595 \n", + "Departure/Arrival time convenient mean 2.970305 \n", + " median 3.000000 \n", + " std 1.552213 \n", + "Ease of Online booking mean 3.031582 \n", + " median 3.000000 \n", + " std 1.575306 \n", + "Flight Distance mean 1530.140255 \n", + " median 1250.000000 \n", + " std 1128.126574 \n", + "Food and drink mean 3.521310 \n", + " median 4.000000 \n", + " std 1.236187 \n", + "Gate location mean 2.977879 \n", + " median 3.000000 \n", + " std 1.374244 \n", + "Inflight entertainment mean 3.964931 \n", + " median 4.000000 \n", + " std 1.076907 \n", + "Inflight service mean 3.969461 \n", + " median 4.000000 \n", + " std 1.091486 \n", + "Inflight wifi service mean 3.161288 \n", + " median 4.000000 \n", + " std 1.588697 \n", + "Leg room service mean 3.822143 \n", + " median 4.000000 \n", + " std 1.175515 \n", + "On-board service mean 3.857324 \n", + " median 4.000000 \n", + " std 1.127130 \n", + "Online boarding mean 4.027474 \n", + " median 4.000000 \n", + " std 1.191609 \n", + "Seat comfort mean 3.966530 \n", + " median 4.000000 \n", + " std 1.142077 " + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numeric_cols_df = df.select_dtypes(include=np.number)\n", + "\n", + "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", + "metrics_to_analyze = [\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " 'Age' # Including age as a numeric metric to analyze\n", + "]\n", + "\n", + "# Filter down to the columns that actually exist and are numeric\n", + "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", + "\n", + "# --- 2. Melt the DataFrame ---\n", + "df_melted = df.melt(\n", + " id_vars=['satisfaction'],\n", + " value_vars=analysis_cols,\n", + " var_name='Metric', # This column now holds the name of the original column\n", + " value_name='Value' # This column now holds the numeric data\n", + ")\n", + "\n", + "# --- 3. Create the Pivot Table ---\n", + "pivot_stats = pd.pivot_table(\n", + " df_melted,\n", + " index=['Metric'],\n", + " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", + " values='Value',\n", + " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", + ")\n", + "\n", + "# --- 4. Re-orient to Vertical View ---\n", + "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", + "vertical_stats_table = pivot_stats.stack(level=0)\n", + "\n", + "# Rename the new index level for clarity\n", + "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", + "\n", + "# Display the final vertical table\n", + "vertical_stats_table" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "69231728-91ed-4a46-ae0c-826b298928b8", + "metadata": {}, + "outputs": [], + "source": [ + "# # --- 1. Define the CORRECTED Palette Dictionary ---\n", + "# # We use 'neutral or dissatisfied' as the key, mapped to a color.\n", + "# correct_palette = {\n", + "# 'satisfied': 'tab:blue',\n", + "# 'neutral or dissatisfied': 'tab:orange' # Mapped to orange, representing the non-satisfied group\n", + "# }\n", + "\n", + "# # --- 2. Create the Grouped Bar Plot with the new palette ---\n", + "# plt.figure(figsize=(16, 8))\n", + "\n", + "# sns.barplot(\n", + "# data=df_melted,\n", + "# x='Metric',\n", + "# y='Value',\n", + "# hue='satisfaction',\n", + "# errorbar='sd',\n", + "# palette=correct_palette # Use the corrected dictionary\n", + "# )\n", + "\n", + "# # --- 3. Format the Chart (rest of the code) ---\n", + "# plt.title('Mean of All Metrics Grouped by Satisfaction Status', fontsize=16)\n", + "# plt.ylabel('Mean Value (Mixed Scales)', fontsize=14)\n", + "# plt.xlabel('Metric', fontsize=14)\n", + "# plt.xticks(rotation=45, ha='right')\n", + "# plt.tight_layout()\n", + "# plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "2599980d-0244-44e9-bcd4-5cd3d5cb2d23", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# from sklearn.preprocessing import MinMaxScaler\n", + "# import matplotlib.pyplot as plt\n", + "# import seaborn as sns\n", + "\n", + "# # Assuming 'df' is your original DataFrame\n", + "# # ----------------------------------------------------\n", + "# # 1. Identify the numeric metric columns to scale\n", + "# # (Excluding categorical, ID, and the 'satisfaction' column)\n", + "\n", + "# metrics_to_scale = [\n", + "# 'Flight Distance', 'Inflight wifi service', 'Departure/Arrival time convenient',\n", + "# 'Ease of Online booking', 'Gate location', 'Food and drink', 'Online boarding',\n", + "# 'Seat comfort', 'Inflight entertainment', 'On-board service', 'Leg room service',\n", + "# 'Baggage handling', 'Checkin service', 'Inflight service', 'Cleanliness',\n", + "# 'Departure Delay in Minutes', 'Arrival Delay in Minutes', 'Age'\n", + "# ]\n", + "\n", + "# # Create a copy of the DataFrame columns to scale\n", + "# df_scaled = df[metrics_to_scale].copy()\n", + "\n", + "# # Initialize the scaler\n", + "# scaler = MinMaxScaler()\n", + "\n", + "# # Apply scaler to all columns in the copy\n", + "# df_scaled[metrics_to_scale] = scaler.fit_transform(df_scaled[metrics_to_scale])\n", + "\n", + "# # Merge the scaled metrics back into the original DataFrame (or a new one)\n", + "# df_normalized = df[['satisfaction']].copy()\n", + "# df_normalized = pd.concat([df_normalized, df_scaled], axis=1)\n", + "\n", + "# # ----------------------------------------------------\n", + "# # 2. Melt the Scaled Data\n", + "\n", + "# # Use the normalized DataFrame for melting\n", + "# df_melted_normalized = df_normalized.melt(\n", + "# id_vars=['satisfaction'],\n", + "# value_vars=metrics_to_scale,\n", + "# var_name='Metric',\n", + "# value_name='Normalized_Value' # New column name for the scaled values\n", + "# )\n", + "\n", + "# # ----------------------------------------------------\n", + "# # 3. Plot the Scaled Data\n", + "\n", + "# plt.figure(figsize=(16, 8))\n", + "\n", + "# correct_palette = {\n", + "# 'satisfied': 'tab:blue',\n", + "# 'neutral or dissatisfied': 'tab:orange'\n", + "# }\n", + "\n", + "# sns.barplot(\n", + "# data=df_melted_normalized,\n", + "# x='Metric',\n", + "# y='Normalized_Value', # Plotting the 0-to-1 scaled values\n", + "# hue='satisfaction',\n", + "# errorbar='sd',\n", + "# palette=correct_palette\n", + "# )\n", + "\n", + "# # --- Format the Chart ---\n", + "# plt.title('Mean of All Metrics Grouped by Satisfaction Status (Normalized)', fontsize=16)\n", + "# plt.ylabel('Normalized Mean Value (Range: 0 to 1)', fontsize=14)\n", + "# plt.xlabel('Metric', fontsize=14)\n", + "# plt.xticks(rotation=45, ha='right')\n", + "# plt.tight_layout()\n", + "# plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", + "metadata": {}, + "outputs": [], + "source": [ + "# import matplotlib.pyplot as plt\n", + "# import seaborn as sns\n", + "# import pandas as pd\n", + "# # Assuming df_melted is already in your environment from previous steps\n", + "\n", + "# # --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", + "# filtered_metrics_1to5 = [\n", + "# 'Inflight wifi service',\n", + "# 'Departure/Arrival time convenient',\n", + "# 'Ease of Online booking',\n", + "# 'Gate location',\n", + "# 'Food and drink',\n", + "# 'Online boarding',\n", + "# 'Seat comfort',\n", + "# 'Inflight entertainment',\n", + "# 'On-board service',\n", + "# 'Leg room service',\n", + "# 'Baggage handling',\n", + "# 'Checkin service',\n", + "# 'Inflight service',\n", + "# 'Cleanliness',\n", + "# ]\n", + "\n", + "# # --- 2. Filter the df_melted DataFrame ---\n", + "# # Only keep rows where the 'Metric' is in the list above\n", + "# df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", + "\n", + "\n", + "# # --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", + "# correct_palette = {\n", + "# 'satisfied': 'tab:blue',\n", + "# 'neutral or dissatisfied': 'tab:orange'\n", + "# }\n", + "\n", + "# # --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", + "# plt.figure(figsize=(16, 8))\n", + "\n", + "# sns.barplot(\n", + "# data=df_melted_filtered_1to5, # Using the filtered data\n", + "# x='Metric',\n", + "# y='Value',\n", + "# hue='satisfaction',\n", + "# errorbar='sd',\n", + "# palette=correct_palette\n", + "# )\n", + "\n", + "# # --- 5. Format the Chart ---\n", + "# plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", + "# plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", + "# plt.xlabel('Metric', fontsize=14)\n", + "# plt.xticks(rotation=45, ha='right')\n", + "# plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", + "# plt.tight_layout()\n", + "# plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "350b26b2-5a25-43aa-9ca2-c2b7edd64774", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "Mean Satisfied: 3.161\n", + "Mean Dissatisfied: 2.400\n", + "--------------------------------------\n", + "T-Statistic: 89.8547\n", + "P-Value: 0.0000000000\n" + ] + } + ], + "source": [ + "satisfied_ratings = dfSatisfied['Inflight wifi service'].dropna()\n", + "dissatisfied_ratings = dfDisatisfied['Inflight wifi service'].dropna()\n", + "\n", + "# Perform the Two-Sample T-Test (Welch's)\n", + "t_statistic, p_value = stats.ttest_ind(\n", + " a=satisfied_ratings,\n", + " b=dissatisfied_ratings,\n", + " equal_var=False\n", + ")\n", + "\n", + "# --- Output the Results ---\n", + "print(f\"--- T-Test Results for Inflight wifi service ---\")\n", + "print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", + "print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", + "print(\"-\" * 38)\n", + "print(f\"T-Statistic: {t_statistic:.4f}\")\n", + "print(f\"P-Value: {p_value:.10f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "id": "5a2bf756-8500-4adc-99af-1c48cd7e1d37", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "Mean Satisfied: 2.400\n", + "Mean Dissatisfied: 2.394\n", + "T-Statistic: 0.6064\n", + "P-Value: 0.5442639813\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "Mean Satisfied: 3.129\n", + "Mean Dissatisfied: 2.287\n", + "T-Statistic: 64.7514\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "Mean Satisfied: 2.547\n", + "Mean Dissatisfied: 2.394\n", + "T-Statistic: 15.5027\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "Mean Satisfied: 2.976\n", + "Mean Dissatisfied: 3.046\n", + "T-Statistic: -6.8515\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "Mean Satisfied: 2.958\n", + "Mean Dissatisfied: 3.011\n", + "T-Statistic: -4.1709\n", + "P-Value: 0.0000304613\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "Mean Satisfied: 2.656\n", + "Mean Dissatisfied: 2.425\n", + "T-Statistic: 23.2966\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "Mean Satisfied: 3.036\n", + "Mean Dissatisfied: 2.986\n", + "T-Statistic: 3.9404\n", + "P-Value: 0.0000816032\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "Mean Satisfied: 2.894\n", + "Mean Dissatisfied: 3.031\n", + "T-Statistic: -10.6884\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "Mean Satisfied: 3.019\n", + "Mean Dissatisfied: 3.078\n", + "T-Statistic: -4.9255\n", + "P-Value: 0.0000008475\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "Mean Satisfied: 2.991\n", + "Mean Dissatisfied: 3.166\n", + "T-Statistic: -14.1632\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "Mean Satisfied: 3.376\n", + "Mean Dissatisfied: 3.565\n", + "T-Statistic: -18.5273\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "Mean Satisfied: 3.043\n", + "Mean Dissatisfied: 3.059\n", + "T-Statistic: -1.3296\n", + "P-Value: 0.1836795869\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "Mean Satisfied: 3.389\n", + "Mean Dissatisfied: 3.570\n", + "T-Statistic: -17.6556\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "Mean Satisfied: 2.936\n", + "Mean Dissatisfied: 3.045\n", + "T-Statistic: -8.4732\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "Mean Satisfied: 16.504\n", + "Mean Dissatisfied: 15.856\n", + "T-Statistic: 1.7952\n", + "P-Value: 0.0726400300\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "Mean Satisfied: 17.128\n", + "Mean Dissatisfied: 16.484\n", + "T-Statistic: 1.7473\n", + "P-Value: 0.0805987692\n", + "--------------------------------------\n" + ] + } + ], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " satisfied_ratings = dfDisatisfied[col].dropna()\n", + " dissatisfied_ratings = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=satisfied_ratings,\n", + " b=dissatisfied_ratings,\n", + " equal_var=False\n", + " )\n", + "\n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", + " print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "91a9b0cd-b1f0-4851-8439-cf30868a1bf6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online booking...On-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfactionsatisfaction_binary
070172MaleLoyal Customer13Personal TravelEco Plus460343...4344552518.0neutral or dissatisfied0
15047Maledisloyal Customer25Business travelBusiness235323...15314116.0neutral or dissatisfied0
2110028FemaleLoyal Customer26Business travelBusiness1142222...43444500.0satisfied1
324026FemaleLoyal Customer25Business travelBusiness562255...253142119.0neutral or dissatisfied0
4119299MaleLoyal Customer61Business travelBusiness214333...34433300.0satisfied1
..................................................................
10389994171Femaledisloyal Customer23Business travelEco192212...31423230.0neutral or dissatisfied0
10390073097MaleLoyal Customer49Business travelBusiness2347444...55555400.0satisfied1
10390168825Maledisloyal Customer30Business travelBusiness1995111...324554714.0neutral or dissatisfied0
max103900.000000129879.00000085.0000004983.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000001305.0000001280.00000010390254173Femaledisloyal Customer22Business travelEco1000111...45154100.0neutral or dissatisfied0
10390362567MaleLoyal Customer27Business travelBusiness1723133...11443100.0neutral or dissatisfied0
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103904 rows × 25 columns

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" ], "text/plain": [ - " Unnamed: 0 id Age Flight Distance \\\n", - "count 45025.000000 45025.000000 45025.000000 45025.000000 \n", - "mean 51789.242754 65512.609928 41.750583 1530.140255 \n", - "std 30016.277260 37347.622538 12.767833 1128.126574 \n", - "min 2.000000 2.000000 7.000000 31.000000 \n", - "25% 25679.000000 33366.000000 32.000000 526.000000 \n", - "50% 51695.000000 65862.000000 43.000000 1250.000000 \n", - "75% 77741.000000 97691.000000 51.000000 2405.000000 \n", - "max 103900.000000 129879.000000 85.000000 4983.000000 \n", - "\n", - " Inflight wifi service Departure/Arrival time convenient \\\n", - "count 45025.000000 45025.000000 \n", - "mean 3.161288 2.970305 \n", - "std 1.588697 1.552213 \n", - "min 0.000000 0.000000 \n", - "25% 2.000000 2.000000 \n", - "50% 4.000000 3.000000 \n", - "75% 5.000000 4.000000 \n", - "max 5.000000 5.000000 \n", - "\n", - " Ease of Online booking Gate location Food and drink Online boarding \\\n", - "count 45025.000000 45025.000000 45025.000000 45025.000000 \n", - "mean 3.031582 2.977879 3.521310 4.027474 \n", - "std 1.575306 1.374244 1.236187 1.191609 \n", - "min 0.000000 0.000000 0.000000 0.000000 \n", - "25% 2.000000 2.000000 3.000000 4.000000 \n", - "50% 3.000000 3.000000 4.000000 4.000000 \n", - "75% 4.000000 4.000000 5.000000 5.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Seat comfort Inflight entertainment On-board service \\\n", - "count 45025.000000 45025.000000 45025.000000 \n", - "mean 3.966530 3.964931 3.857324 \n", - "std 1.142077 1.076907 1.127130 \n", - "min 1.000000 1.000000 1.000000 \n", - "25% 4.000000 4.000000 3.000000 \n", - "50% 4.000000 4.000000 4.000000 \n", - "75% 5.000000 5.000000 5.000000 \n", - "max 5.000000 5.000000 5.000000 \n", - "\n", - " Leg room service Baggage handling Checkin service Inflight service \\\n", - "count 45025.000000 45025.000000 45025.000000 45025.000000 \n", - "mean 3.822143 3.966396 3.646041 3.969461 \n", - "std 1.175515 1.099607 1.158732 1.091486 \n", - "min 0.000000 1.000000 1.000000 1.000000 \n", - "25% 3.000000 4.000000 3.000000 4.000000 \n", - "50% 4.000000 4.000000 4.000000 4.000000 \n", - "75% 5.000000 5.000000 5.000000 5.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Cleanliness Departure Delay in Minutes Arrival Delay in Minutes \n", - "count 45025.000000 45025.000000 44897.000000 \n", - "mean 3.744342 12.608084 12.630799 \n", - "std 1.142247 35.382595 35.962008 \n", - "min 1.000000 0.000000 0.000000 \n", - "25% 3.000000 0.000000 0.000000 \n", - "50% 4.000000 0.000000 0.000000 \n", - "75% 5.000000 9.000000 8.000000 \n", - "max 5.000000 1305.000000 1280.000000 " + " id Gender Customer Type Age Type of Travel Class \\\n", + "0 70172 Male Loyal Customer 13 Personal Travel Eco Plus \n", + "1 5047 Male disloyal Customer 25 Business travel Business \n", + "2 110028 Female Loyal Customer 26 Business travel Business \n", + "3 24026 Female Loyal Customer 25 Business travel Business \n", + "4 119299 Male Loyal Customer 61 Business travel Business \n", + "... ... ... ... ... ... ... \n", + "103899 94171 Female disloyal Customer 23 Business travel Eco \n", + "103900 73097 Male Loyal Customer 49 Business travel Business \n", + "103901 68825 Male disloyal Customer 30 Business travel Business \n", + "103902 54173 Female disloyal Customer 22 Business travel Eco \n", + "103903 62567 Male Loyal Customer 27 Business travel Business \n", + "\n", + " Flight Distance Inflight wifi service \\\n", + "0 460 3 \n", + "1 235 3 \n", + "2 1142 2 \n", + "3 562 2 \n", + "4 214 3 \n", + "... ... ... \n", + "103899 192 2 \n", + "103900 2347 4 \n", + "103901 1995 1 \n", + "103902 1000 1 \n", + "103903 1723 1 \n", + "\n", + " Departure/Arrival time convenient Ease of Online booking ... \\\n", + "0 4 3 ... \n", + "1 2 3 ... \n", + "2 2 2 ... \n", + "3 5 5 ... \n", + "4 3 3 ... \n", + "... ... ... ... \n", + "103899 1 2 ... \n", + "103900 4 4 ... \n", + "103901 1 1 ... \n", + "103902 1 1 ... \n", + "103903 3 3 ... \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "0 4 3 4 4 \n", + "1 1 5 3 1 \n", + "2 4 3 4 4 \n", + "3 2 5 3 1 \n", + "4 3 4 4 3 \n", + "... ... ... ... ... \n", + "103899 3 1 4 2 \n", + "103900 5 5 5 5 \n", + "103901 3 2 4 5 \n", + "103902 4 5 1 5 \n", + "103903 1 1 4 4 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "0 5 5 25 \n", + "1 4 1 1 \n", + "2 4 5 0 \n", + "3 4 2 11 \n", + "4 3 3 0 \n", + "... ... ... ... \n", + "103899 3 2 3 \n", + "103900 5 4 0 \n", + "103901 5 4 7 \n", + "103902 4 1 0 \n", + "103903 3 1 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction satisfaction_binary \n", + "0 18.0 neutral or dissatisfied 0 \n", + "1 6.0 neutral or dissatisfied 0 \n", + "2 0.0 satisfied 1 \n", + "3 9.0 neutral or dissatisfied 0 \n", + "4 0.0 satisfied 1 \n", + "... ... ... ... \n", + "103899 0.0 neutral or dissatisfied 0 \n", + "103900 0.0 satisfied 1 \n", + "103901 14.0 neutral or dissatisfied 0 \n", + "103902 0.0 neutral or dissatisfied 0 \n", + "103903 0.0 neutral or dissatisfied 0 \n", + "\n", + "[103904 rows x 25 columns]" ] }, - "execution_count": 20, + "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dfSatisfied.describe()" + "df" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "148a480d-158c-4ed5-b379-4b1b2d20a3a5", + "execution_count": 63, + "id": "60a773e7-2487-47bd-b868-94f7b60bf471", + "metadata": {}, + "outputs": [], + "source": [ + "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", + "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", + "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "a75fd6ab-fb8e-4ef8-ab12-ac19c28bc21a", "metadata": {}, "outputs": [ { @@ -810,7 +4149,6 @@ " \n", " \n", " \n", - " Unnamed: 0\n", " id\n", " Age\n", " Flight Distance\n", @@ -830,109 +4168,109 @@ " Cleanliness\n", " Departure Delay in Minutes\n", " Arrival Delay in Minutes\n", + " satisfaction_binary\n", " \n", " \n", " \n", " \n", " count\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58879.000000\n", - " 58697.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14489.000000\n", + " 14448.000000\n", + " 14489.0\n", " \n", " \n", " mean\n", - " 52075.578746\n", - " 64474.259176\n", - " 37.566688\n", - " 928.919971\n", - " 2.399633\n", - " 3.129112\n", - " 2.546850\n", - " 2.976121\n", - " 2.958050\n", - " 2.656125\n", - " 3.036295\n", - " 2.894156\n", - " 3.019158\n", - " 2.990812\n", - " 3.375991\n", - " 3.042952\n", - " 3.388814\n", - " 2.936123\n", - " 16.503728\n", - " 17.127536\n", + " 63540.052454\n", + " 31.096694\n", + " 709.715439\n", + " 2.394230\n", + " 2.287114\n", + " 2.394092\n", + " 3.045897\n", + " 3.011319\n", + " 2.425426\n", + " 2.985506\n", + " 3.030575\n", + " 3.078059\n", + " 3.166195\n", + " 3.564704\n", + " 3.058941\n", + " 3.569812\n", + " 3.044517\n", + " 15.856443\n", + " 16.484358\n", + " 0.0\n", " \n", " \n", " std\n", - " 29977.755481\n", - " 37546.516040\n", - " 16.459825\n", - " 790.452308\n", - " 0.964348\n", - " 1.500368\n", - " 1.205847\n", - " 1.198500\n", - " 1.346607\n", - " 1.145905\n", - " 1.303142\n", - " 1.323619\n", - " 1.285790\n", - " 1.303159\n", - " 1.176978\n", - " 1.281158\n", - " 1.175603\n", - " 1.325955\n", - " 40.191886\n", - " 40.560248\n", + " 37439.975203\n", + " 11.286122\n", + " 507.481985\n", + " 0.959929\n", + " 1.376962\n", + " 1.024201\n", + " 1.072035\n", + " 1.384624\n", + " 1.047718\n", + " 1.410376\n", + " 1.388937\n", + " 1.290407\n", + " 1.343065\n", + " 1.078106\n", + " 1.300556\n", + " 1.087478\n", + " 1.392283\n", + " 38.551476\n", + " 39.404446\n", + " 0.0\n", " \n", " \n", " min\n", - " 0.000000\n", " 1.000000\n", " 7.000000\n", " 31.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", " 1.000000\n", " 0.000000\n", " 0.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", - " 0.000000\n", " 1.000000\n", " 0.000000\n", " 0.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", + " 1.000000\n", " 0.000000\n", " 0.000000\n", - " 0.000000\n", + " 0.0\n", " \n", " \n", " 25%\n", - " 26174.500000\n", - " 31835.500000\n", - " 25.000000\n", - " 372.000000\n", - " 2.000000\n", + " 31094.000000\n", + " 23.000000\n", + " 337.000000\n", " 2.000000\n", + " 1.000000\n", " 2.000000\n", " 2.000000\n", " 2.000000\n", @@ -947,19 +4285,19 @@ " 2.000000\n", " 0.000000\n", " 0.000000\n", + " 0.0\n", " \n", " \n", " 50%\n", - " 52130.000000\n", - " 63970.000000\n", - " 36.000000\n", - " 671.000000\n", + " 61418.000000\n", + " 28.000000\n", + " 590.000000\n", + " 2.000000\n", + " 2.000000\n", " 2.000000\n", " 3.000000\n", " 3.000000\n", - " 3.000000\n", - " 3.000000\n", - " 3.000000\n", + " 2.000000\n", " 3.000000\n", " 3.000000\n", " 3.000000\n", @@ -970,15 +4308,15 @@ " 3.000000\n", " 0.000000\n", " 0.000000\n", + " 0.0\n", " \n", " \n", " 75%\n", - " 78063.500000\n", - " 97144.500000\n", - " 50.000000\n", - " 1158.000000\n", + " 96500.000000\n", + " 37.000000\n", + " 960.000000\n", + " 3.000000\n", " 3.000000\n", - " 4.000000\n", " 3.000000\n", " 4.000000\n", " 4.000000\n", @@ -991,16 +4329,16 @@ " 4.000000\n", " 4.000000\n", " 4.000000\n", + " 14.000000\n", " 15.000000\n", - " 17.000000\n", + " 0.0\n", " \n", " \n", " max\n", - " 103903.000000\n", - " 129880.000000\n", + " 129871.000000\n", " 85.000000\n", - " 4983.000000\n", - " 5.000000\n", + " 4963.000000\n", + " 4.000000\n", " 5.000000\n", " 5.000000\n", " 5.000000\n", @@ -1014,88 +4352,147 @@ " 5.000000\n", " 5.000000\n", " 5.000000\n", - " 1592.000000\n", - " 1584.000000\n", + " 921.000000\n", + " 924.000000\n", + " 0.0\n", " \n", " \n", "\n", "" ], "text/plain": [ - " Unnamed: 0 id Age Flight Distance \\\n", - "count 58879.000000 58879.000000 58879.000000 58879.000000 \n", - "mean 52075.578746 64474.259176 37.566688 928.919971 \n", - "std 29977.755481 37546.516040 16.459825 790.452308 \n", - "min 0.000000 1.000000 7.000000 31.000000 \n", - "25% 26174.500000 31835.500000 25.000000 372.000000 \n", - "50% 52130.000000 63970.000000 36.000000 671.000000 \n", - "75% 78063.500000 97144.500000 50.000000 1158.000000 \n", - "max 103903.000000 129880.000000 85.000000 4983.000000 \n", - "\n", - " Inflight wifi service Departure/Arrival time convenient \\\n", - "count 58879.000000 58879.000000 \n", - "mean 2.399633 3.129112 \n", - "std 0.964348 1.500368 \n", - "min 0.000000 0.000000 \n", - "25% 2.000000 2.000000 \n", - "50% 2.000000 3.000000 \n", - "75% 3.000000 4.000000 \n", - "max 5.000000 5.000000 \n", - "\n", - " Ease of Online booking Gate location Food and drink Online boarding \\\n", - "count 58879.000000 58879.000000 58879.000000 58879.000000 \n", - "mean 2.546850 2.976121 2.958050 2.656125 \n", - "std 1.205847 1.198500 1.346607 1.145905 \n", - "min 0.000000 1.000000 0.000000 0.000000 \n", - "25% 2.000000 2.000000 2.000000 2.000000 \n", - "50% 3.000000 3.000000 3.000000 3.000000 \n", - "75% 3.000000 4.000000 4.000000 3.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Seat comfort Inflight entertainment On-board service \\\n", - "count 58879.000000 58879.000000 58879.000000 \n", - "mean 3.036295 2.894156 3.019158 \n", - "std 1.303142 1.323619 1.285790 \n", - "min 0.000000 0.000000 0.000000 \n", - "25% 2.000000 2.000000 2.000000 \n", - "50% 3.000000 3.000000 3.000000 \n", - "75% 4.000000 4.000000 4.000000 \n", - "max 5.000000 5.000000 5.000000 \n", - "\n", - " Leg room service Baggage handling Checkin service Inflight service \\\n", - "count 58879.000000 58879.000000 58879.000000 58879.000000 \n", - "mean 2.990812 3.375991 3.042952 3.388814 \n", - "std 1.303159 1.176978 1.281158 1.175603 \n", - "min 0.000000 1.000000 0.000000 0.000000 \n", - "25% 2.000000 3.000000 2.000000 3.000000 \n", - "50% 3.000000 4.000000 3.000000 4.000000 \n", - "75% 4.000000 4.000000 4.000000 4.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Cleanliness Departure Delay in Minutes Arrival Delay in Minutes \n", - "count 58879.000000 58879.000000 58697.000000 \n", - "mean 2.936123 16.503728 17.127536 \n", - "std 1.325955 40.191886 40.560248 \n", - "min 0.000000 0.000000 0.000000 \n", - "25% 2.000000 0.000000 0.000000 \n", - "50% 3.000000 0.000000 0.000000 \n", - "75% 4.000000 15.000000 17.000000 \n", - "max 5.000000 1592.000000 1584.000000 " + " id Age Flight Distance Inflight wifi service \\\n", + "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", + "mean 63540.052454 31.096694 709.715439 2.394230 \n", + "std 37439.975203 11.286122 507.481985 0.959929 \n", + "min 1.000000 7.000000 31.000000 1.000000 \n", + "25% 31094.000000 23.000000 337.000000 2.000000 \n", + "50% 61418.000000 28.000000 590.000000 2.000000 \n", + "75% 96500.000000 37.000000 960.000000 3.000000 \n", + "max 129871.000000 85.000000 4963.000000 4.000000 \n", + "\n", + " Departure/Arrival time convenient Ease of Online booking \\\n", + "count 14489.000000 14489.000000 \n", + "mean 2.287114 2.394092 \n", + "std 1.376962 1.024201 \n", + "min 0.000000 0.000000 \n", + "25% 1.000000 2.000000 \n", + "50% 2.000000 2.000000 \n", + "75% 3.000000 3.000000 \n", + "max 5.000000 5.000000 \n", + "\n", + " Gate location Food and drink Online boarding Seat comfort \\\n", + "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", + "mean 3.045897 3.011319 2.425426 2.985506 \n", + "std 1.072035 1.384624 1.047718 1.410376 \n", + "min 1.000000 0.000000 0.000000 1.000000 \n", + "25% 2.000000 2.000000 2.000000 2.000000 \n", + "50% 3.000000 3.000000 2.000000 3.000000 \n", + "75% 4.000000 4.000000 3.000000 4.000000 \n", + "max 5.000000 5.000000 5.000000 5.000000 \n", + "\n", + " Inflight entertainment On-board service Leg room service \\\n", + "count 14489.000000 14489.000000 14489.000000 \n", + "mean 3.030575 3.078059 3.166195 \n", + "std 1.388937 1.290407 1.343065 \n", + "min 1.000000 1.000000 1.000000 \n", + "25% 2.000000 2.000000 2.000000 \n", + "50% 3.000000 3.000000 3.000000 \n", + "75% 4.000000 4.000000 4.000000 \n", + "max 5.000000 5.000000 5.000000 \n", + "\n", + " Baggage handling Checkin service Inflight service Cleanliness \\\n", + "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", + "mean 3.564704 3.058941 3.569812 3.044517 \n", + "std 1.078106 1.300556 1.087478 1.392283 \n", + "min 1.000000 1.000000 1.000000 1.000000 \n", + "25% 3.000000 2.000000 3.000000 2.000000 \n", + "50% 4.000000 3.000000 4.000000 3.000000 \n", + "75% 4.000000 4.000000 4.000000 4.000000 \n", + "max 5.000000 5.000000 5.000000 5.000000 \n", + "\n", + " Departure Delay in Minutes Arrival Delay in Minutes \\\n", + "count 14489.000000 14448.000000 \n", + "mean 15.856443 16.484358 \n", + "std 38.551476 39.404446 \n", + "min 0.000000 0.000000 \n", + "25% 0.000000 0.000000 \n", + "50% 0.000000 0.000000 \n", + "75% 14.000000 15.000000 \n", + "max 921.000000 924.000000 \n", + "\n", + " satisfaction_binary \n", + "count 14489.0 \n", + "mean 0.0 \n", + "std 0.0 \n", + "min 0.0 \n", + "25% 0.0 \n", + "50% 0.0 \n", + "75% 0.0 \n", + "max 0.0 " + ] + }, + "execution_count": 44, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfDisatisfied_disloyal.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "6ad6e2d8-eed3-446e-ae43-a6c5e127c8be", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 40533\n", + "disloyal Customer 4492\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfSatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "d4e77057-6266-4cd6-b6dc-4647799d96ff", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 44390\n", + "disloyal Customer 14489\n", + "Name: count, dtype: int64" ] }, - "execution_count": 19, + "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dfDisatisfied.describe()" + "dfDisatisfied['Customer Type'].value_counts()" ] }, { "cell_type": "code", - "execution_count": 21, - "id": "72c0cdfb-e081-478f-8977-85779113cd4f", + "execution_count": 46, + "id": "07ee2084-a56b-4321-a025-d13bb9e510dc", "metadata": {}, "outputs": [ { @@ -1119,7 +4516,6 @@ " \n", " \n", " \n", - " Unnamed: 0\n", " id\n", " Gender\n", " Customer Type\n", @@ -1129,8 +4525,8 @@ " Flight Distance\n", " Inflight wifi service\n", " Departure/Arrival time convenient\n", + " Ease of Online booking\n", " ...\n", - " Inflight entertainment\n", " On-board service\n", " Leg room service\n", " Baggage handling\n", @@ -1140,128 +4536,129 @@ " Departure Delay in Minutes\n", " Arrival Delay in Minutes\n", " satisfaction\n", + " satisfaction_binary\n", " \n", " \n", " \n", " \n", - " 2\n", - " 2\n", - " 110028\n", - " Female\n", - " Loyal Customer\n", - " 26\n", + " 1\n", + " 5047\n", + " Male\n", + " disloyal Customer\n", + " 25\n", " Business travel\n", " Business\n", - " 1142\n", - " 2\n", + " 235\n", + " 3\n", " 2\n", + " 3\n", " ...\n", + " 1\n", " 5\n", - " 4\n", " 3\n", + " 1\n", " 4\n", - " 4\n", - " 4\n", - " 5\n", + " 1\n", + " 1\n", + " 6.0\n", + " neutral or dissatisfied\n", " 0\n", - " 0.0\n", - " satisfied\n", " \n", " \n", - " 4\n", - " 4\n", - " 119299\n", + " 9\n", + " 65725\n", " Male\n", - " Loyal Customer\n", - " 61\n", + " disloyal Customer\n", + " 20\n", " Business travel\n", - " Business\n", - " 214\n", + " Eco\n", + " 1061\n", " 3\n", " 3\n", - " ...\n", " 3\n", + " ...\n", + " 2\n", " 3\n", " 4\n", " 4\n", " 3\n", - " 3\n", - " 3\n", + " 2\n", " 0\n", " 0.0\n", - " satisfied\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 7\n", - " 7\n", - " 96462\n", + " 10\n", + " 34991\n", " Female\n", - " Loyal Customer\n", - " 52\n", + " disloyal Customer\n", + " 24\n", " Business travel\n", - " Business\n", - " 2035\n", + " Eco\n", + " 1182\n", " 4\n", - " 3\n", - " ...\n", - " 5\n", " 5\n", " 5\n", + " ...\n", + " 3\n", + " 3\n", " 5\n", - " 4\n", + " 3\n", " 5\n", - " 4\n", - " 4\n", + " 2\n", + " 0\n", " 0.0\n", - " satisfied\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 13\n", - " 13\n", - " 83502\n", + " 15\n", + " 100580\n", " Male\n", - " Loyal Customer\n", - " 33\n", - " Personal Travel\n", + " disloyal Customer\n", + " 13\n", + " Business travel\n", " Eco\n", - " 946\n", - " 4\n", - " 2\n", - " ...\n", - " 4\n", - " 4\n", - " 5\n", + " 486\n", " 2\n", + " 1\n", " 2\n", + " ...\n", " 2\n", + " 1\n", " 4\n", - " 0\n", + " 1\n", + " 3\n", + " 4\n", + " 1\n", " 0.0\n", - " satisfied\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 16\n", - " 16\n", - " 71142\n", + " 31\n", + " 27809\n", " Female\n", - " Loyal Customer\n", - " 26\n", + " disloyal Customer\n", + " 15\n", " Business travel\n", - " Business\n", - " 2123\n", - " 3\n", - " 3\n", + " Eco\n", + " 1043\n", + " 2\n", + " 2\n", + " 2\n", " ...\n", - " 4\n", - " 5\n", " 3\n", + " 1\n", " 4\n", - " 5\n", - " 4\n", + " 2\n", " 4\n", - " 49\n", - " 51.0\n", - " satisfied\n", + " 5\n", + " 3\n", + " 0.0\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", " ...\n", @@ -1288,225 +4685,1127 @@ " ...\n", " \n", " \n", - " 103890\n", - " 103890\n", - " 80087\n", + " 103892\n", + " 46016\n", " Female\n", - " Loyal Customer\n", - " 56\n", + " disloyal Customer\n", + " 37\n", " Business travel\n", - " Eco Plus\n", - " 550\n", - " 3\n", - " 5\n", - " ...\n", + " Business\n", + " 596\n", " 3\n", " 3\n", " 3\n", + " ...\n", + " 1\n", + " 1\n", " 3\n", + " 1\n", " 4\n", " 3\n", - " 3\n", + " 110\n", + " 121.0\n", + " neutral or dissatisfied\n", " 0\n", - " 0.0\n", - " satisfied\n", " \n", " \n", - " 103891\n", - " 103891\n", - " 83013\n", - " Male\n", - " Loyal Customer\n", - " 54\n", + " 103895\n", + " 66030\n", + " Female\n", + " disloyal Customer\n", + " 24\n", " Business travel\n", - " Business\n", - " 1991\n", - " 5\n", - " 5\n", + " Eco\n", + " 1055\n", + " 1\n", + " 1\n", + " 1\n", " ...\n", - " 4\n", - " 4\n", + " 3\n", + " 3\n", " 5\n", - " 4\n", " 5\n", " 4\n", - " 4\n", - " 35\n", - " 31.0\n", - " satisfied\n", + " 1\n", + " 13\n", + " 10.0\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 103894\n", - " 103894\n", - " 86549\n", - " Male\n", - " Loyal Customer\n", - " 26\n", + " 103899\n", + " 94171\n", + " Female\n", + " disloyal Customer\n", + " 23\n", " Business travel\n", - " Business\n", - " 712\n", - " 4\n", - " 4\n", + " Eco\n", + " 192\n", + " 2\n", + " 1\n", + " 2\n", " ...\n", - " 5\n", " 3\n", + " 1\n", " 4\n", - " 4\n", + " 2\n", " 3\n", - " 4\n", - " 5\n", - " 17\n", - " 26.0\n", - " satisfied\n", + " 2\n", + " 3\n", + " 0.0\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 103897\n", - " 103897\n", - " 102203\n", - " Female\n", - " Loyal Customer\n", - " 60\n", + " 103901\n", + " 68825\n", + " Male\n", + " disloyal Customer\n", + " 30\n", " Business travel\n", " Business\n", - " 1599\n", - " 5\n", - " 5\n", + " 1995\n", + " 1\n", + " 1\n", + " 1\n", " ...\n", + " 3\n", + " 2\n", " 4\n", + " 5\n", + " 5\n", " 4\n", - " 4\n", - " 4\n", - " 4\n", - " 4\n", - " 4\n", - " 9\n", - " 7.0\n", - " satisfied\n", + " 7\n", + " 14.0\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", - " 103900\n", - " 103900\n", - " 73097\n", - " Male\n", - " Loyal Customer\n", - " 49\n", + " 103902\n", + " 54173\n", + " Female\n", + " disloyal Customer\n", + " 22\n", " Business travel\n", - " Business\n", - " 2347\n", - " 4\n", - " 4\n", + " Eco\n", + " 1000\n", + " 1\n", + " 1\n", + " 1\n", " ...\n", + " 4\n", " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", + " 1\n", " 5\n", " 4\n", + " 1\n", " 0\n", " 0.0\n", - " satisfied\n", + " neutral or dissatisfied\n", + " 0\n", " \n", " \n", "\n", - "

45025 rows × 25 columns

\n", + "

14489 rows × 25 columns

\n", "" ], "text/plain": [ - " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", - "2 2 110028 Female Loyal Customer 26 Business travel \n", - "4 4 119299 Male Loyal Customer 61 Business travel \n", - "7 7 96462 Female Loyal Customer 52 Business travel \n", - "13 13 83502 Male Loyal Customer 33 Personal Travel \n", - "16 16 71142 Female Loyal Customer 26 Business travel \n", - "... ... ... ... ... ... ... \n", - "103890 103890 80087 Female Loyal Customer 56 Business travel \n", - "103891 103891 83013 Male Loyal Customer 54 Business travel \n", - "103894 103894 86549 Male Loyal Customer 26 Business travel \n", - "103897 103897 102203 Female Loyal Customer 60 Business travel \n", - "103900 103900 73097 Male Loyal Customer 49 Business travel \n", + " id Gender Customer Type Age Type of Travel Class \\\n", + "1 5047 Male disloyal Customer 25 Business travel Business \n", + "9 65725 Male disloyal Customer 20 Business travel Eco \n", + "10 34991 Female disloyal Customer 24 Business travel Eco \n", + "15 100580 Male disloyal Customer 13 Business travel Eco \n", + "31 27809 Female disloyal Customer 15 Business travel Eco \n", + "... ... ... ... ... ... ... \n", + "103892 46016 Female disloyal Customer 37 Business travel Business \n", + "103895 66030 Female disloyal Customer 24 Business travel Eco \n", + "103899 94171 Female disloyal Customer 23 Business travel Eco \n", + "103901 68825 Male disloyal Customer 30 Business travel Business \n", + "103902 54173 Female disloyal Customer 22 Business travel Eco \n", "\n", - " Class Flight Distance Inflight wifi service \\\n", - "2 Business 1142 2 \n", - "4 Business 214 3 \n", - "7 Business 2035 4 \n", - "13 Eco 946 4 \n", - "16 Business 2123 3 \n", - "... ... ... ... \n", - "103890 Eco Plus 550 3 \n", - "103891 Business 1991 5 \n", - "103894 Business 712 4 \n", - "103897 Business 1599 5 \n", - "103900 Business 2347 4 \n", + " Flight Distance Inflight wifi service \\\n", + "1 235 3 \n", + "9 1061 3 \n", + "10 1182 4 \n", + "15 486 2 \n", + "31 1043 2 \n", + "... ... ... \n", + "103892 596 3 \n", + "103895 1055 1 \n", + "103899 192 2 \n", + "103901 1995 1 \n", + "103902 1000 1 \n", "\n", - " Departure/Arrival time convenient ... Inflight entertainment \\\n", - "2 2 ... 5 \n", - "4 3 ... 3 \n", - "7 3 ... 5 \n", - "13 2 ... 4 \n", - "16 3 ... 4 \n", - "... ... ... ... \n", - "103890 5 ... 3 \n", - "103891 5 ... 4 \n", - "103894 4 ... 5 \n", - "103897 5 ... 4 \n", - "103900 4 ... 5 \n", + " Departure/Arrival time convenient Ease of Online booking ... \\\n", + "1 2 3 ... \n", + "9 3 3 ... \n", + "10 5 5 ... \n", + "15 1 2 ... \n", + "31 2 2 ... \n", + "... ... ... ... \n", + "103892 3 3 ... \n", + "103895 1 1 ... \n", + "103899 1 2 ... \n", + "103901 1 1 ... \n", + "103902 1 1 ... \n", "\n", " On-board service Leg room service Baggage handling Checkin service \\\n", - "2 4 3 4 4 \n", - "4 3 4 4 3 \n", - "7 5 5 5 4 \n", - "13 4 5 2 2 \n", - "16 5 3 4 5 \n", + "1 1 5 3 1 \n", + "9 2 3 4 4 \n", + "10 3 3 5 3 \n", + "15 2 1 4 1 \n", + "31 3 1 4 2 \n", "... ... ... ... ... \n", - "103890 3 3 3 4 \n", - "103891 4 5 4 5 \n", - "103894 3 4 4 3 \n", - "103897 4 4 4 4 \n", - "103900 5 5 5 5 \n", + "103892 1 1 3 1 \n", + "103895 3 3 5 5 \n", + "103899 3 1 4 2 \n", + "103901 3 2 4 5 \n", + "103902 4 5 1 5 \n", "\n", " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "2 4 5 0 \n", - "4 3 3 0 \n", - "7 5 4 4 \n", - "13 2 4 0 \n", - "16 4 4 49 \n", + "1 4 1 1 \n", + "9 3 2 0 \n", + "10 5 2 0 \n", + "15 3 4 1 \n", + "31 4 5 3 \n", "... ... ... ... \n", - "103890 3 3 0 \n", - "103891 4 4 35 \n", - "103894 4 5 17 \n", - "103897 4 4 9 \n", - "103900 5 4 0 \n", + "103892 4 3 110 \n", + "103895 4 1 13 \n", + "103899 3 2 3 \n", + "103901 5 4 7 \n", + "103902 4 1 0 \n", "\n", - " Arrival Delay in Minutes satisfaction \n", - "2 0.0 satisfied \n", - "4 0.0 satisfied \n", - "7 0.0 satisfied \n", - "13 0.0 satisfied \n", - "16 51.0 satisfied \n", - "... ... ... \n", - "103890 0.0 satisfied \n", - "103891 31.0 satisfied \n", - "103894 26.0 satisfied \n", - "103897 7.0 satisfied \n", - "103900 0.0 satisfied \n", + " Arrival Delay in Minutes satisfaction satisfaction_binary \n", + "1 6.0 neutral or dissatisfied 0 \n", + "9 0.0 neutral or dissatisfied 0 \n", + "10 0.0 neutral or dissatisfied 0 \n", + "15 0.0 neutral or dissatisfied 0 \n", + "31 0.0 neutral or dissatisfied 0 \n", + "... ... ... ... \n", + "103892 121.0 neutral or dissatisfied 0 \n", + "103895 10.0 neutral or dissatisfied 0 \n", + "103899 0.0 neutral or dissatisfied 0 \n", + "103901 14.0 neutral or dissatisfied 0 \n", + "103902 0.0 neutral or dissatisfied 0 \n", "\n", - "[45025 rows x 25 columns]" + "[14489 rows x 25 columns]" ] }, - "execution_count": 21, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dfSatisfied" + "dfDisatisfied_disloyal" ] }, { "cell_type": "code", "execution_count": null, - "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", + "id": "9b45c0ab-c959-4130-820f-19a659973ecb", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "1cb9c038-2d28-4203-8cce-0146b91182e1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1: 2.400\n", + "df_2: 2.394\n", + "T-Statistic: 0.6064\n", + "P-Value: 0.5442639813\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1: 3.129\n", + "df_2: 2.287\n", + "T-Statistic: 64.7514\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1: 2.547\n", + "df_2: 2.394\n", + "T-Statistic: 15.5027\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1: 2.976\n", + "df_2: 3.046\n", + "T-Statistic: -6.8515\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1: 2.958\n", + "df_2: 3.011\n", + "T-Statistic: -4.1709\n", + "P-Value: 0.0000304613\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1: 2.656\n", + "df_2: 2.425\n", + "T-Statistic: 23.2966\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1: 3.036\n", + "df_2: 2.986\n", + "T-Statistic: 3.9404\n", + "P-Value: 0.0000816032\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1: 2.894\n", + "df_2: 3.031\n", + "T-Statistic: -10.6884\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1: 3.019\n", + "df_2: 3.078\n", + "T-Statistic: -4.9255\n", + "P-Value: 0.0000008475\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1: 2.991\n", + "df_2: 3.166\n", + "T-Statistic: -14.1632\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1: 3.376\n", + "df_2: 3.565\n", + "T-Statistic: -18.5273\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1: 3.043\n", + "df_2: 3.059\n", + "T-Statistic: -1.3296\n", + "P-Value: 0.1836795869\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1: 3.389\n", + "df_2: 3.570\n", + "T-Statistic: -17.6556\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1: 2.936\n", + "df_2: 3.045\n", + "T-Statistic: -8.4732\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1: 16.504\n", + "df_2: 15.856\n", + "T-Statistic: 1.7952\n", + "P-Value: 0.0726400300\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1: 17.128\n", + "df_2: 16.484\n", + "T-Statistic: 1.7473\n", + "P-Value: 0.0805987692\n", + "--------------------------------------\n" + ] + } + ], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " df_1 = dfDisatisfied[col].dropna()\n", + " df_2 = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1,\n", + " b=df_2,\n", + " equal_var=False\n", + " )\n", + " \n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1: {df_1.mean():.3f}\")\n", + " print(f\"df_2: {df_2.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "id": "c9f9a363-4c19-4991-ac52-524d8e388100", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1: 2.708\n", + "df_2: 2.394\n", + "T-Statistic: 25.3827\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1: 2.393\n", + "df_2: 2.287\n", + "T-Statistic: 6.5336\n", + "P-Value: 0.0000000001\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1: 2.699\n", + "df_2: 2.394\n", + "T-Statistic: 23.6742\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1: 2.993\n", + "df_2: 3.046\n", + "T-Statistic: -4.3473\n", + "P-Value: 0.0000138232\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1: 3.035\n", + "df_2: 3.011\n", + "T-Statistic: 1.5449\n", + "P-Value: 0.1223834903\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1: 2.710\n", + "df_2: 2.425\n", + "T-Statistic: 21.8571\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1: 2.994\n", + "df_2: 2.986\n", + "T-Statistic: 0.5733\n", + "P-Value: 0.5664729684\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1: 3.048\n", + "df_2: 3.031\n", + "T-Statistic: 1.1520\n", + "P-Value: 0.2493166368\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1: 3.228\n", + "df_2: 3.078\n", + "T-Statistic: 10.5906\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1: 3.218\n", + "df_2: 3.166\n", + "T-Statistic: 3.5105\n", + "P-Value: 0.0004478861\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1: 3.694\n", + "df_2: 3.565\n", + "T-Statistic: 10.7853\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1: 3.218\n", + "df_2: 3.059\n", + "T-Statistic: 11.1506\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1: 3.697\n", + "df_2: 3.570\n", + "T-Statistic: 10.5199\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1: 3.054\n", + "df_2: 3.045\n", + "T-Statistic: 0.6356\n", + "P-Value: 0.5250658229\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1: 15.142\n", + "df_2: 15.856\n", + "T-Statistic: -1.6897\n", + "P-Value: 0.0910916769\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1: 15.567\n", + "df_2: 16.484\n", + "T-Statistic: -2.1228\n", + "P-Value: 0.0337816494\n", + "--------------------------------------\n" + ] + } + ], + "source": [ + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " df_1 = dfDisloyal[col].dropna()\n", + " df_2 = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1,\n", + " b=df_2,\n", + " equal_var=False\n", + " )\n", + "\n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1: {df_1.mean():.3f}\")\n", + " print(f\"df_2: {df_2.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1 Mean: 2.708\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 25.3827\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1 Mean: 2.393\n", + "df_2 Mean: 2.287\n", + "T-Statistic: 6.5336\n", + "P-Value: 0.0000000001\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1 Mean: 2.699\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 23.6742\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1 Mean: 2.993\n", + "df_2 Mean: 3.046\n", + "T-Statistic: -4.3473\n", + "P-Value: 0.0000138232\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1 Mean: 3.035\n", + "df_2 Mean: 3.011\n", + "T-Statistic: 1.5449\n", + "P-Value: 0.1223834903\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1 Mean: 2.710\n", + "df_2 Mean: 2.425\n", + "T-Statistic: 21.8571\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1 Mean: 2.994\n", + "df_2 Mean: 2.986\n", + "T-Statistic: 0.5733\n", + "P-Value: 0.5664729684\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1 Mean: 3.048\n", + "df_2 Mean: 3.031\n", + "T-Statistic: 1.1520\n", + "P-Value: 0.2493166368\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1 Mean: 3.228\n", + "df_2 Mean: 3.078\n", + "T-Statistic: 10.5906\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1 Mean: 3.218\n", + "df_2 Mean: 3.166\n", + "T-Statistic: 3.5105\n", + "P-Value: 0.0004478861\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1 Mean: 3.694\n", + "df_2 Mean: 3.565\n", + "T-Statistic: 10.7853\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1 Mean: 3.218\n", + "df_2 Mean: 3.059\n", + "T-Statistic: 11.1506\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1 Mean: 3.697\n", + "df_2 Mean: 3.570\n", + "T-Statistic: 10.5199\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1 Mean: 3.054\n", + "df_2 Mean: 3.045\n", + "T-Statistic: 0.6356\n", + "P-Value: 0.5250658229\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1 Mean: 15.142\n", + "df_2 Mean: 15.856\n", + "T-Statistic: -1.6897\n", + "P-Value: 0.0910916769\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1 Mean: 15.567\n", + "df_2 Mean: 16.484\n", + "T-Statistic: -2.1228\n", + "P-Value: 0.0337816494\n", + "--------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisloyal[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disloyal vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "22aa3477-4a71-4966-8278-0fb39583ffae", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1 Mean: 2.400\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 0.6064\n", + "P-Value: 0.5442639813\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1 Mean: 3.129\n", + "df_2 Mean: 2.287\n", + "T-Statistic: 64.7514\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1 Mean: 2.547\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 15.5027\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1 Mean: 2.976\n", + "df_2 Mean: 3.046\n", + "T-Statistic: -6.8515\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1 Mean: 2.958\n", + "df_2 Mean: 3.011\n", + "T-Statistic: -4.1709\n", + "P-Value: 0.0000304613\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1 Mean: 2.656\n", + "df_2 Mean: 2.425\n", + "T-Statistic: 23.2966\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1 Mean: 3.036\n", + "df_2 Mean: 2.986\n", + "T-Statistic: 3.9404\n", + "P-Value: 0.0000816032\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1 Mean: 2.894\n", + "df_2 Mean: 3.031\n", + "T-Statistic: -10.6884\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1 Mean: 3.019\n", + "df_2 Mean: 3.078\n", + "T-Statistic: -4.9255\n", + "P-Value: 0.0000008475\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1 Mean: 2.991\n", + "df_2 Mean: 3.166\n", + "T-Statistic: -14.1632\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1 Mean: 3.376\n", + "df_2 Mean: 3.565\n", + "T-Statistic: -18.5273\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1 Mean: 3.043\n", + "df_2 Mean: 3.059\n", + "T-Statistic: -1.3296\n", + "P-Value: 0.1836795869\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1 Mean: 3.389\n", + "df_2 Mean: 3.570\n", + "T-Statistic: -17.6556\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1 Mean: 2.936\n", + "df_2 Mean: 3.045\n", + "T-Statistic: -8.4732\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1 Mean: 16.504\n", + "df_2 Mean: 15.856\n", + "T-Statistic: 1.7952\n", + "P-Value: 0.0726400300\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1 Mean: 17.128\n", + "df_2 Mean: 16.484\n", + "T-Statistic: 1.7473\n", + "P-Value: 0.0805987692\n", + "--------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisatisfied[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disatisfied vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "8b49a8ad-9ade-4c87-bfc1-8c41a0fc8cbc", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 84923\n", + "disloyal Customer 18981\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 71, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "eebaa851-4d41-4660-93f0-134a3cb071da", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 40533\n", + "disloyal Customer 4492\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfSatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "bfb858a8-9410-4699-8150-7f17f158580a", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 44390\n", + "disloyal Customer 14489\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dfDisatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = df['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on the entire population')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Disatisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Satisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d8bb127-282b-42d1-9d37-ffd35fbc1333", "metadata": {}, "outputs": [], "source": [] From d005c8d10d82dc8bdd7a15fede993ddf31b2a2c6 Mon Sep 17 00:00:00 2001 From: Marta Date: Wed, 10 Dec 2025 16:22:22 +0100 Subject: [PATCH 13/26] day 3, final charts --- Untitled.ipynb | 211 + data/raw/test.csv | 25977 ++++++++++++++++ notebooks/Airline_Project1-Copy_marta.ipynb | 316 +- notebooks/Airline_Project1.ipynb | 1492 +- .../satisfaction_by_class_bar_chart.png | Bin 0 -> 33393 bytes ...atisfaction_by_customer_type_bar_chart.png | Bin 0 -> 34519 bytes .../segmented_investment_comparison.png | Bin 0 -> 58214 bytes .../images/service_correlation_bar_chart.png | Bin 0 -> 72877 bytes ...lified_segmented_investment_comparison.png | Bin 0 -> 56309 bytes 9 files changed, 26550 insertions(+), 1446 deletions(-) create mode 100644 Untitled.ipynb create mode 100644 data/raw/test.csv create mode 100644 notebooks/images/satisfaction_by_class_bar_chart.png create mode 100644 notebooks/images/satisfaction_by_customer_type_bar_chart.png create mode 100644 notebooks/images/segmented_investment_comparison.png create mode 100644 notebooks/images/service_correlation_bar_chart.png create mode 100644 notebooks/images/simplified_segmented_investment_comparison.png diff --git a/Untitled.ipynb b/Untitled.ipynb new file mode 100644 index 00000000..143e8831 --- /dev/null +++ b/Untitled.ipynb @@ -0,0 +1,211 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 11, + "id": "f7fa551b-8cb6-4dd0-9d0f-f7dcfb0b4661", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- 📝 DataFrame General Information (Check for NaNs & Types) ---\n", + "\n", + "RangeIndex: 25976 entries, 0 to 25975\n", + "Data columns (total 25 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Unnamed: 0 25976 non-null int64 \n", + " 1 id 25976 non-null int64 \n", + " 2 Gender 25976 non-null object \n", + " 3 Customer Type 25976 non-null object \n", + " 4 Age 25976 non-null int64 \n", + " 5 Type of Travel 25976 non-null object \n", + " 6 Class 25976 non-null object \n", + " 7 Flight Distance 25976 non-null int64 \n", + " 8 Inflight wifi service 25976 non-null int64 \n", + " 9 Departure/Arrival time convenient 25976 non-null int64 \n", + " 10 Ease of Online booking 25976 non-null int64 \n", + " 11 Gate location 25976 non-null int64 \n", + " 12 Food and drink 25976 non-null int64 \n", + " 13 Online boarding 25976 non-null int64 \n", + " 14 Seat comfort 25976 non-null int64 \n", + " 15 Inflight entertainment 25976 non-null int64 \n", + " 16 On-board service 25976 non-null int64 \n", + " 17 Leg room service 25976 non-null int64 \n", + " 18 Baggage handling 25976 non-null int64 \n", + " 19 Checkin service 25976 non-null int64 \n", + " 20 Inflight service 25976 non-null int64 \n", + " 21 Cleanliness 25976 non-null int64 \n", + " 22 Departure Delay in Minutes 25976 non-null int64 \n", + " 23 Arrival Delay in Minutes 25893 non-null float64\n", + " 24 satisfaction 25976 non-null object \n", + "dtypes: float64(1), int64(19), object(5)\n", + "memory usage: 5.0+ MB\n", + "\n", + "--- 🧐 First Rows ---\n", + " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", + "0 0 19556 Female Loyal Customer 52 Business travel \n", + "1 1 90035 Female Loyal Customer 36 Business travel \n", + "2 2 12360 Male disloyal Customer 20 Business travel \n", + "3 3 77959 Male Loyal Customer 44 Business travel \n", + "4 4 36875 Female Loyal Customer 49 Business travel \n", + "\n", + " Class Flight Distance Inflight wifi service \\\n", + "0 Eco 160 5 \n", + "1 Business 2863 1 \n", + "2 Eco 192 2 \n", + "3 Business 3377 0 \n", + "4 Eco 1182 2 \n", + "\n", + " Departure/Arrival time convenient ... Inflight entertainment \\\n", + "0 4 ... 5 \n", + "1 1 ... 4 \n", + "2 0 ... 2 \n", + "3 0 ... 1 \n", + "4 3 ... 2 \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "0 5 5 5 2 \n", + "1 4 4 4 3 \n", + "2 4 1 3 2 \n", + "3 1 1 1 3 \n", + "4 2 2 2 4 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "0 5 5 50 \n", + "1 4 5 0 \n", + "2 2 2 0 \n", + "3 1 4 0 \n", + "4 2 4 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction \n", + "0 44.0 satisfied \n", + "1 0.0 satisfied \n", + "2 0.0 neutral or dissatisfied \n", + "3 6.0 satisfied \n", + "4 20.0 satisfied \n", + "\n", + "[5 rows x 25 columns]\n", + "\n", + "--- ✅ DATASET SIZE ---\n", + "Rows: 25976, Columns: 25\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# --- 1. Define the Loading Function ---\n", + "def load_and_explore_data(filepath):\n", + " \"\"\"Loads the CSV, displays basic info, and the first few rows.\"\"\"\n", + " \n", + " # 1. Loading\n", + " try:\n", + " # Tries to read the file using the path passed to the function\n", + " df = pd.read_csv(filepath, low_memory=False) \n", + " except FileNotFoundError:\n", + " # Error handling if the path is wrong\n", + " print(f\"Error: File not found at {filepath}. Please check the DATA_PATH.\")\n", + " return None\n", + " \n", + " print(\"--- 📝 DataFrame General Information (Check for NaNs & Types) ---\")\n", + " df.info()\n", + " \n", + " print(\"\\n--- 🧐 First Rows ---\")\n", + " print(df.head())\n", + " \n", + " print(\"\\n--- ✅ DATASET SIZE ---\")\n", + " print(f\"Rows: {df.shape[0]}, Columns: {df.shape[1]}\")\n", + " \n", + " return df\n", + "\n", + "# --- 2. Execution ---\n", + "# NOTE: We assume the file is in 'data/raw/test.csv' relative to your notebook.\n", + "DATA_PATH = 'data/raw/test.csv' \n", + "df_aero_vista = load_and_explore_data(DATA_PATH)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "b1587c75-8787-4305-abcb-518d3c9c07fe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 25976 entries, 0 to 25975\n", + "Data columns (total 25 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 Unnamed: 0 25976 non-null int64 \n", + " 1 id 25976 non-null int64 \n", + " 2 Gender 25976 non-null object \n", + " 3 Customer Type 25976 non-null object \n", + " 4 Age 25976 non-null int64 \n", + " 5 Type of Travel 25976 non-null object \n", + " 6 Class 25976 non-null object \n", + " 7 Flight Distance 25976 non-null int64 \n", + " 8 Inflight wifi service 25976 non-null int64 \n", + " 9 Departure/Arrival time convenient 25976 non-null int64 \n", + " 10 Ease of Online booking 25976 non-null int64 \n", + " 11 Gate location 25976 non-null int64 \n", + " 12 Food and drink 25976 non-null int64 \n", + " 13 Online boarding 25976 non-null int64 \n", + " 14 Seat comfort 25976 non-null int64 \n", + " 15 Inflight entertainment 25976 non-null int64 \n", + " 16 On-board service 25976 non-null int64 \n", + " 17 Leg room service 25976 non-null int64 \n", + " 18 Baggage handling 25976 non-null int64 \n", + " 19 Checkin service 25976 non-null int64 \n", + " 20 Inflight service 25976 non-null int64 \n", + " 21 Cleanliness 25976 non-null int64 \n", + " 22 Departure Delay in Minutes 25976 non-null int64 \n", + " 23 Arrival Delay in Minutes 25893 non-null float64\n", + " 24 satisfaction 25976 non-null object \n", + "dtypes: float64(1), int64(19), object(5)\n", + "memory usage: 5.0+ MB\n" + ] + } + ], + "source": [ + "\n", + "df_aero_vista.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bd922e5c-94cf-4080-8410-9c955e84233d", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "venv", + "language": "python", + "name": "venv" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/data/raw/test.csv b/data/raw/test.csv new file mode 100644 index 00000000..20664569 --- /dev/null +++ b/data/raw/test.csv @@ -0,0 +1,25977 @@ +,id,Gender,Customer Type,Age,Type of Travel,Class,Flight Distance,Inflight wifi service,Departure/Arrival time convenient,Ease of Online booking,Gate location,Food and drink,Online boarding,Seat comfort,Inflight entertainment,On-board service,Leg room service,Baggage handling,Checkin service,Inflight service,Cleanliness,Departure Delay in Minutes,Arrival Delay in Minutes,satisfaction +0,19556,Female,Loyal Customer,52,Business travel,Eco,160,5,4,3,4,3,4,3,5,5,5,5,2,5,5,50,44.0,satisfied +1,90035,Female,Loyal Customer,36,Business travel,Business,2863,1,1,3,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +2,12360,Male,disloyal Customer,20,Business travel,Eco,192,2,0,2,4,2,2,2,2,4,1,3,2,2,2,0,0.0,neutral or dissatisfied +3,77959,Male,Loyal Customer,44,Business travel,Business,3377,0,0,0,2,3,4,4,1,1,1,1,3,1,4,0,6.0,satisfied +4,36875,Female,Loyal Customer,49,Business travel,Eco,1182,2,3,4,3,4,1,2,2,2,2,2,4,2,4,0,20.0,satisfied +5,39177,Male,Loyal Customer,16,Business travel,Eco,311,3,3,3,3,5,5,3,5,4,3,1,1,2,5,0,0.0,satisfied +6,79433,Female,Loyal Customer,77,Business travel,Business,3987,5,5,5,5,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +7,97286,Female,Loyal Customer,43,Business travel,Business,2556,2,2,2,2,4,4,5,4,4,4,4,5,4,3,77,65.0,satisfied +8,27508,Male,Loyal Customer,47,Business travel,Eco,556,5,2,2,2,5,5,5,5,2,2,5,3,3,5,1,0.0,satisfied +9,62482,Female,Loyal Customer,46,Business travel,Business,1744,2,2,2,2,3,4,4,4,4,4,4,5,4,4,28,14.0,satisfied +10,47583,Female,Loyal Customer,47,Business travel,Eco,1235,4,1,1,1,5,1,5,3,3,4,3,1,3,4,29,19.0,satisfied +11,115550,Female,Loyal Customer,33,Business travel,Business,325,2,5,5,5,1,3,4,2,2,2,2,3,2,4,18,7.0,neutral or dissatisfied +12,119987,Female,Loyal Customer,46,Business travel,Business,1009,5,5,5,5,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +13,42141,Female,Loyal Customer,60,Business travel,Business,451,1,1,4,1,5,5,4,5,5,5,5,3,5,5,117,113.0,satisfied +14,2274,Female,Loyal Customer,52,Business travel,Business,925,2,2,2,2,5,5,4,4,4,4,4,3,4,5,10,0.0,satisfied +15,22470,Male,Loyal Customer,50,Personal Travel,Eco,83,3,4,0,3,2,0,2,2,4,2,4,4,5,2,5,2.0,neutral or dissatisfied +16,124915,Female,Loyal Customer,31,Business travel,Eco,728,2,5,5,5,2,2,2,2,4,3,3,4,3,2,2,0.0,neutral or dissatisfied +17,17836,Male,Loyal Customer,52,Personal Travel,Eco Plus,1075,5,4,5,3,4,5,4,4,3,5,5,4,5,4,0,0.0,satisfied +18,76872,Female,Loyal Customer,43,Personal Travel,Eco,1927,3,4,3,1,4,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +19,64287,Female,Loyal Customer,50,Business travel,Business,3799,5,5,5,5,4,5,4,4,4,5,4,5,4,5,8,0.0,satisfied +20,63995,Male,Loyal Customer,60,Business travel,Business,612,4,4,4,4,2,4,5,5,5,5,5,5,5,5,21,49.0,satisfied +21,75855,Male,Loyal Customer,43,Personal Travel,Eco,1437,3,4,3,4,2,3,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +22,106181,Male,Loyal Customer,55,Personal Travel,Eco,302,1,2,4,3,4,4,4,4,1,3,2,4,3,4,0,0.0,neutral or dissatisfied +23,44304,Male,Loyal Customer,25,Business travel,Business,1428,4,4,4,4,4,4,4,4,1,5,3,1,5,4,0,0.0,satisfied +24,82602,Female,disloyal Customer,30,Business travel,Eco,528,4,3,5,3,2,5,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +25,7823,Male,Loyal Customer,62,Personal Travel,Eco,710,3,5,3,4,2,3,2,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +26,127781,Male,Loyal Customer,24,Business travel,Business,3680,4,1,4,4,2,2,2,2,5,5,5,5,4,2,0,0.0,satisfied +27,34501,Female,Loyal Customer,22,Business travel,Eco,1521,4,1,1,1,4,4,4,4,1,4,1,1,5,4,3,13.0,satisfied +28,121658,Male,Loyal Customer,44,Business travel,Business,1543,3,5,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +29,20219,Male,Loyal Customer,51,Business travel,Eco,235,4,3,3,3,4,4,4,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +30,67551,Male,Loyal Customer,43,Personal Travel,Business,1235,1,5,1,1,1,1,4,3,3,1,5,4,3,5,0,0.0,neutral or dissatisfied +31,48994,Female,Loyal Customer,56,Business travel,Eco,308,2,3,3,3,5,2,5,2,2,2,2,2,2,2,0,0.0,satisfied +32,70811,Male,disloyal Customer,41,Business travel,Eco,624,2,3,2,4,5,2,5,5,4,3,3,1,4,5,0,0.0,neutral or dissatisfied +33,75241,Male,Loyal Customer,22,Personal Travel,Eco,1846,4,5,4,4,5,4,5,5,5,4,4,4,4,5,40,68.0,neutral or dissatisfied +34,12312,Female,Loyal Customer,53,Business travel,Eco,192,5,2,2,2,3,4,2,5,5,5,5,2,5,4,0,1.0,satisfied +35,48372,Male,Loyal Customer,12,Personal Travel,Eco,674,3,4,3,1,1,3,1,1,3,3,5,4,4,1,80,70.0,neutral or dissatisfied +36,51477,Female,Loyal Customer,39,Business travel,Business,370,3,3,3,3,2,4,5,4,4,4,4,4,4,5,10,12.0,satisfied +37,84204,Female,Loyal Customer,55,Business travel,Business,3169,1,1,1,1,3,5,4,5,5,5,5,3,5,5,73,68.0,satisfied +38,70990,Female,disloyal Customer,32,Business travel,Business,802,4,4,4,2,2,4,4,2,4,2,4,3,5,2,0,10.0,neutral or dissatisfied +39,101991,Female,Loyal Customer,40,Personal Travel,Eco,628,1,4,1,3,5,1,5,5,3,2,5,5,4,5,4,0.0,neutral or dissatisfied +40,87447,Female,disloyal Customer,42,Business travel,Business,373,3,3,3,5,4,3,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +41,16112,Male,disloyal Customer,24,Business travel,Eco,725,4,4,4,2,2,4,2,2,4,2,3,1,5,2,0,4.0,satisfied +42,16172,Male,Loyal Customer,22,Business travel,Business,277,3,3,3,3,3,3,3,1,5,4,3,3,2,3,116,177.0,neutral or dissatisfied +43,106558,Female,Loyal Customer,28,Business travel,Business,1024,1,1,1,1,4,4,4,4,5,3,5,5,4,4,0,3.0,satisfied +44,11536,Female,Loyal Customer,36,Business travel,Eco Plus,267,2,3,3,3,2,2,2,2,1,1,3,4,4,2,59,55.0,neutral or dissatisfied +45,47773,Female,Loyal Customer,62,Business travel,Eco,550,5,1,1,1,4,2,1,5,5,5,5,5,5,2,92,90.0,satisfied +46,70521,Female,Loyal Customer,60,Business travel,Business,1889,2,2,3,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +47,96283,Female,Loyal Customer,59,Personal Travel,Eco,460,2,5,2,5,3,3,4,5,5,2,4,1,5,2,4,2.0,neutral or dissatisfied +48,117993,Female,Loyal Customer,49,Business travel,Business,3295,4,4,3,4,2,5,4,5,5,5,5,5,5,3,0,4.0,satisfied +49,74703,Female,Loyal Customer,44,Personal Travel,Eco,1205,2,4,2,3,4,4,3,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +50,110840,Female,Loyal Customer,58,Personal Travel,Eco Plus,990,3,5,2,3,3,4,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +51,88249,Male,disloyal Customer,24,Business travel,Business,444,4,0,4,2,2,4,2,2,5,3,5,3,5,2,20,32.0,satisfied +52,125877,Female,Loyal Customer,53,Business travel,Eco,520,4,2,2,2,3,3,4,4,4,4,4,3,4,3,17,0.0,satisfied +53,83968,Male,Loyal Customer,56,Business travel,Eco,321,2,3,4,3,2,2,2,2,2,5,3,3,3,2,0,0.0,neutral or dissatisfied +54,122719,Female,Loyal Customer,30,Business travel,Business,651,3,3,4,3,5,5,5,5,4,5,4,3,5,5,0,0.0,satisfied +55,3949,Male,disloyal Customer,27,Business travel,Business,764,3,3,3,2,2,3,2,2,2,1,3,3,2,2,30,46.0,neutral or dissatisfied +56,45542,Male,Loyal Customer,27,Business travel,Business,566,3,3,3,3,5,5,5,5,4,3,1,1,1,5,0,0.0,satisfied +57,43742,Female,Loyal Customer,67,Personal Travel,Eco,626,3,4,3,1,2,4,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +58,122093,Female,Loyal Customer,32,Personal Travel,Eco,130,3,0,3,3,4,3,5,4,2,2,4,5,3,4,3,4.0,neutral or dissatisfied +59,121454,Male,disloyal Customer,36,Business travel,Eco,331,2,0,2,1,1,2,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +60,738,Male,Loyal Customer,44,Business travel,Business,158,3,3,3,3,5,4,5,4,4,5,4,4,4,5,66,57.0,satisfied +61,75235,Female,Loyal Customer,70,Personal Travel,Eco,1829,1,4,1,1,2,5,5,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +62,88653,Female,Loyal Customer,55,Personal Travel,Eco,646,3,2,3,4,4,3,4,5,5,3,5,4,5,3,0,3.0,neutral or dissatisfied +63,26594,Male,Loyal Customer,66,Business travel,Eco,404,4,1,1,1,4,4,4,4,3,1,3,2,5,4,9,6.0,satisfied +64,38339,Female,Loyal Customer,19,Business travel,Business,2738,5,5,5,5,3,4,3,3,5,3,3,1,2,3,0,0.0,satisfied +65,46063,Female,Loyal Customer,53,Personal Travel,Eco Plus,964,1,5,1,2,4,4,5,4,4,1,4,5,4,4,6,0.0,neutral or dissatisfied +66,27957,Male,Loyal Customer,22,Business travel,Business,1660,2,2,2,2,2,2,2,2,4,3,2,2,4,2,0,0.0,neutral or dissatisfied +67,17270,Female,Loyal Customer,69,Personal Travel,Eco,872,2,3,2,2,4,2,3,5,5,2,5,3,5,3,14,0.0,neutral or dissatisfied +68,87976,Female,Loyal Customer,42,Business travel,Business,1898,5,5,5,5,5,4,4,5,5,5,5,4,5,3,49,47.0,satisfied +69,31640,Female,Loyal Customer,41,Business travel,Business,967,2,2,2,2,2,3,5,4,4,4,4,5,4,5,44,40.0,satisfied +70,41461,Female,Loyal Customer,53,Personal Travel,Business,1242,3,4,3,5,3,3,5,1,1,3,1,4,1,4,3,0.0,neutral or dissatisfied +71,15143,Male,Loyal Customer,35,Business travel,Business,1042,3,2,2,2,2,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +72,78136,Female,Loyal Customer,54,Personal Travel,Business,153,3,5,3,5,2,4,5,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +73,120433,Male,Loyal Customer,44,Business travel,Business,366,3,3,2,3,2,5,4,4,4,4,4,3,4,4,5,24.0,satisfied +74,41440,Female,disloyal Customer,26,Business travel,Eco Plus,913,1,2,2,2,4,2,3,4,3,2,1,1,4,4,0,0.0,neutral or dissatisfied +75,15963,Female,Loyal Customer,44,Personal Travel,Eco,528,2,5,2,3,2,5,4,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +76,64303,Female,disloyal Customer,24,Business travel,Eco,1172,2,3,3,2,5,3,5,5,4,5,5,4,5,5,28,27.0,neutral or dissatisfied +77,3608,Female,Loyal Customer,54,Personal Travel,Eco,999,2,4,2,4,4,5,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +78,7744,Male,Loyal Customer,42,Business travel,Eco Plus,489,2,2,2,2,2,2,2,2,4,3,3,1,2,2,0,0.0,neutral or dissatisfied +79,21276,Male,disloyal Customer,36,Business travel,Eco,692,1,1,1,4,1,1,1,1,1,5,3,1,2,1,0,0.0,neutral or dissatisfied +80,58576,Female,Loyal Customer,61,Business travel,Business,1585,2,2,3,2,1,1,5,3,3,4,3,4,3,4,24,20.0,satisfied +81,53888,Female,Loyal Customer,50,Personal Travel,Eco,140,2,4,2,4,4,4,5,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +82,10980,Male,Loyal Customer,27,Business travel,Business,2729,3,3,3,3,5,5,5,5,4,4,4,5,2,5,44,52.0,satisfied +83,54151,Male,Loyal Customer,55,Business travel,Business,1400,3,5,5,5,4,3,2,3,3,3,3,1,3,4,1,0.0,neutral or dissatisfied +84,115641,Male,disloyal Customer,21,Business travel,Eco,447,2,2,1,4,1,1,1,1,4,4,3,4,3,1,7,0.0,neutral or dissatisfied +85,58584,Female,Loyal Customer,31,Personal Travel,Business,334,2,1,2,4,5,2,5,5,2,4,3,2,4,5,5,0.0,neutral or dissatisfied +86,50472,Female,disloyal Customer,37,Business travel,Eco,158,1,2,1,3,1,1,1,1,1,4,3,4,3,1,24,20.0,neutral or dissatisfied +87,102623,Female,Loyal Customer,50,Business travel,Business,3696,1,1,5,1,2,4,4,5,5,5,5,4,5,5,9,0.0,satisfied +88,31533,Female,Loyal Customer,21,Personal Travel,Eco,846,1,4,1,3,3,1,3,3,5,4,5,4,5,3,9,17.0,neutral or dissatisfied +89,42287,Female,Loyal Customer,53,Business travel,Eco,329,1,0,0,3,1,3,3,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +90,70467,Male,Loyal Customer,45,Business travel,Business,2580,3,3,3,3,3,4,4,5,5,5,5,3,5,4,0,11.0,satisfied +91,20461,Female,disloyal Customer,42,Business travel,Eco,84,3,5,3,1,5,3,5,5,5,5,3,5,4,5,0,34.0,neutral or dissatisfied +92,113346,Male,Loyal Customer,59,Business travel,Business,3358,3,3,3,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +93,115566,Female,Loyal Customer,54,Business travel,Eco,308,2,1,4,4,5,3,3,2,2,2,2,4,2,1,83,95.0,neutral or dissatisfied +94,119896,Female,Loyal Customer,46,Business travel,Business,912,1,1,1,1,2,4,4,4,4,4,4,5,4,4,5,0.0,satisfied +95,88853,Female,Loyal Customer,52,Personal Travel,Eco Plus,406,3,4,3,1,2,5,4,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +96,24895,Female,Loyal Customer,38,Personal Travel,Eco,397,2,5,2,2,5,2,5,5,5,4,4,5,5,5,0,0.0,neutral or dissatisfied +97,31122,Male,Loyal Customer,35,Business travel,Business,2409,3,3,3,3,1,4,3,4,4,4,4,3,4,3,0,0.0,satisfied +98,91231,Female,Loyal Customer,41,Personal Travel,Eco,545,2,2,2,3,4,2,4,4,1,3,4,1,4,4,0,0.0,neutral or dissatisfied +99,61426,Female,disloyal Customer,40,Business travel,Business,2419,2,2,2,3,4,2,4,4,3,2,3,3,5,4,0,0.0,neutral or dissatisfied +100,68873,Female,disloyal Customer,36,Business travel,Eco,1061,2,2,2,1,4,2,4,4,1,4,2,4,2,4,13,0.0,neutral or dissatisfied +101,125701,Male,Loyal Customer,67,Personal Travel,Eco,899,2,5,2,2,2,2,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +102,94999,Female,Loyal Customer,38,Personal Travel,Eco,293,4,4,4,4,5,4,5,5,2,2,4,4,4,5,5,0.0,satisfied +103,56694,Female,Loyal Customer,50,Personal Travel,Eco,1085,3,5,3,2,5,5,5,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +104,62010,Male,Loyal Customer,50,Business travel,Business,2475,5,5,5,5,2,5,4,2,2,2,2,3,2,5,0,0.0,satisfied +105,95868,Male,Loyal Customer,54,Business travel,Business,2544,5,5,3,5,5,4,5,3,3,3,3,4,3,5,62,66.0,satisfied +106,123064,Male,Loyal Customer,56,Business travel,Business,2556,4,4,4,4,4,5,4,4,4,4,4,3,4,5,117,113.0,satisfied +107,103418,Male,Loyal Customer,38,Personal Travel,Eco,237,3,4,3,4,2,3,2,2,3,3,4,4,3,2,0,2.0,neutral or dissatisfied +108,73456,Female,Loyal Customer,7,Personal Travel,Eco,1120,3,5,3,3,2,3,2,2,4,4,4,5,5,2,16,13.0,neutral or dissatisfied +109,8851,Female,Loyal Customer,32,Business travel,Business,2668,5,5,4,5,4,4,4,4,5,2,5,5,5,4,2,0.0,satisfied +110,64241,Male,Loyal Customer,45,Business travel,Eco,1660,4,1,1,1,4,4,4,4,2,5,2,4,3,4,0,7.0,neutral or dissatisfied +111,81723,Male,disloyal Customer,25,Business travel,Eco,1310,2,2,2,4,3,2,3,3,1,4,3,1,4,3,0,24.0,neutral or dissatisfied +112,88237,Female,Loyal Customer,45,Business travel,Business,2374,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +113,50619,Male,Loyal Customer,34,Personal Travel,Eco,209,3,4,0,1,1,0,1,1,1,5,5,2,3,1,0,0.0,neutral or dissatisfied +114,54444,Male,Loyal Customer,20,Personal Travel,Eco Plus,305,3,4,3,3,1,3,1,1,3,3,4,4,5,1,5,2.0,neutral or dissatisfied +115,64765,Female,disloyal Customer,36,Business travel,Eco,247,2,1,2,3,1,2,1,1,4,1,3,1,2,1,16,6.0,neutral or dissatisfied +116,15941,Male,disloyal Customer,36,Business travel,Eco,338,3,4,3,4,2,3,2,2,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +117,14965,Male,Loyal Customer,27,Business travel,Business,3200,1,1,1,1,5,5,5,5,4,5,2,2,1,5,0,0.0,satisfied +118,36897,Male,Loyal Customer,40,Personal Travel,Eco,1368,3,4,2,4,3,2,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +119,127954,Male,Loyal Customer,31,Business travel,Business,1999,4,5,4,4,5,5,5,5,4,4,4,3,4,5,0,4.0,satisfied +120,27872,Male,Loyal Customer,25,Business travel,Eco Plus,680,0,5,0,2,1,0,1,1,3,1,4,5,5,1,0,0.0,satisfied +121,35854,Male,Loyal Customer,42,Business travel,Business,537,2,2,2,2,1,5,3,5,5,5,5,4,5,3,0,0.0,satisfied +122,14527,Female,Loyal Customer,45,Business travel,Eco,288,5,1,1,1,1,2,3,5,5,5,5,1,5,3,29,40.0,satisfied +123,47021,Male,Loyal Customer,59,Personal Travel,Business,639,2,1,2,3,4,3,3,3,3,2,3,2,3,1,0,11.0,neutral or dissatisfied +124,11224,Male,Loyal Customer,34,Personal Travel,Eco,201,3,5,3,3,2,3,5,2,5,2,1,3,1,2,3,8.0,neutral or dissatisfied +125,3921,Female,Loyal Customer,22,Personal Travel,Eco,213,3,5,3,4,3,3,1,3,1,5,1,3,2,3,0,17.0,neutral or dissatisfied +126,69463,Male,Loyal Customer,21,Personal Travel,Eco,1096,2,2,2,4,2,2,3,2,3,1,3,2,4,2,0,0.0,neutral or dissatisfied +127,47050,Male,Loyal Customer,26,Business travel,Business,1680,3,1,1,1,3,3,3,3,1,2,4,2,3,3,27,10.0,neutral or dissatisfied +128,21970,Male,Loyal Customer,37,Business travel,Business,2401,2,2,2,2,5,3,1,4,4,4,4,1,4,5,94,86.0,satisfied +129,30046,Male,Loyal Customer,38,Business travel,Business,2746,2,2,2,2,2,5,2,4,4,4,4,1,4,5,0,0.0,satisfied +130,1256,Female,Loyal Customer,17,Personal Travel,Eco,89,3,4,3,1,5,3,3,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +131,73813,Male,Loyal Customer,15,Personal Travel,Eco Plus,192,2,4,2,3,5,2,5,5,5,4,5,5,5,5,5,8.0,neutral or dissatisfied +132,110928,Female,Loyal Customer,53,Personal Travel,Eco,404,3,3,3,4,4,4,4,5,5,3,5,1,5,2,0,0.0,neutral or dissatisfied +133,102981,Male,disloyal Customer,39,Business travel,Business,546,4,4,4,4,2,4,2,2,3,5,5,3,4,2,93,88.0,neutral or dissatisfied +134,61571,Male,Loyal Customer,40,Business travel,Business,2400,4,3,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +135,3796,Female,disloyal Customer,28,Business travel,Eco Plus,599,2,2,2,3,4,2,4,4,3,3,3,1,3,4,0,46.0,neutral or dissatisfied +136,73906,Female,disloyal Customer,27,Business travel,Business,2342,3,3,3,4,2,3,2,2,4,3,5,3,5,2,10,0.0,neutral or dissatisfied +137,74090,Female,Loyal Customer,41,Business travel,Business,3046,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +138,76645,Female,Loyal Customer,7,Personal Travel,Eco,516,2,4,2,3,5,2,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +139,100462,Male,disloyal Customer,48,Business travel,Business,759,3,3,3,2,2,3,2,2,4,2,5,4,5,2,2,1.0,neutral or dissatisfied +140,54164,Male,Loyal Customer,13,Business travel,Eco,1400,2,1,1,1,2,1,2,2,4,3,3,3,4,2,0,0.0,neutral or dissatisfied +141,6147,Female,Loyal Customer,48,Business travel,Business,491,3,3,3,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +142,1262,Female,Loyal Customer,49,Personal Travel,Eco,134,3,3,3,3,5,3,3,4,4,3,4,1,4,4,8,3.0,neutral or dissatisfied +143,20310,Male,disloyal Customer,26,Business travel,Business,900,5,5,5,3,1,5,1,1,4,3,5,5,5,1,5,0.0,satisfied +144,46896,Male,Loyal Customer,22,Business travel,Business,3648,2,2,2,2,3,3,3,3,2,4,3,5,3,3,0,0.0,satisfied +145,7237,Female,Loyal Customer,53,Business travel,Business,3769,3,1,5,1,1,3,1,2,4,3,4,1,2,1,180,178.0,neutral or dissatisfied +146,44293,Female,Loyal Customer,43,Business travel,Eco,563,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +147,52496,Male,Loyal Customer,56,Business travel,Business,3131,1,1,1,1,2,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +148,68263,Female,Loyal Customer,69,Personal Travel,Eco,631,3,5,2,5,3,3,4,5,5,2,5,1,5,1,0,0.0,neutral or dissatisfied +149,5289,Male,Loyal Customer,59,Personal Travel,Eco,351,4,3,4,4,1,4,1,1,1,5,4,2,4,1,0,0.0,satisfied +150,109359,Female,Loyal Customer,56,Business travel,Business,1189,5,5,3,5,5,4,5,2,2,2,2,4,2,3,9,0.0,satisfied +151,94988,Male,Loyal Customer,11,Personal Travel,Eco,562,5,5,5,5,3,5,3,3,4,4,5,1,2,3,0,0.0,satisfied +152,53605,Female,Loyal Customer,25,Business travel,Eco,1874,4,3,3,3,4,4,3,4,3,1,4,5,1,4,86,78.0,satisfied +153,11005,Female,disloyal Customer,29,Business travel,Eco,158,4,0,4,1,2,4,2,2,1,5,2,2,2,2,0,0.0,satisfied +154,14794,Female,Loyal Customer,48,Business travel,Eco,95,5,3,3,3,1,2,1,5,5,5,5,1,5,2,0,0.0,satisfied +155,49480,Female,Loyal Customer,42,Business travel,Business,266,1,1,1,1,4,3,4,4,4,4,4,2,4,1,0,0.0,satisfied +156,120440,Male,disloyal Customer,15,Business travel,Eco,449,1,4,1,2,3,1,4,3,1,3,5,4,5,3,0,0.0,neutral or dissatisfied +157,55823,Female,disloyal Customer,49,Business travel,Business,1416,3,4,4,2,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +158,107792,Male,Loyal Customer,41,Business travel,Business,2388,2,2,2,2,5,5,4,4,4,4,4,5,4,5,29,18.0,satisfied +159,80531,Male,Loyal Customer,43,Business travel,Business,1678,1,1,2,1,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +160,128145,Male,Loyal Customer,60,Business travel,Business,1972,5,5,2,5,4,3,5,5,5,5,5,5,5,3,0,0.0,satisfied +161,63370,Female,Loyal Customer,42,Personal Travel,Eco,337,4,1,4,3,3,3,3,3,3,4,1,2,3,2,0,0.0,satisfied +162,12452,Female,Loyal Customer,8,Personal Travel,Eco,253,3,3,3,1,4,3,4,4,5,5,2,4,3,4,0,0.0,neutral or dissatisfied +163,16145,Female,Loyal Customer,42,Business travel,Eco,212,5,3,3,3,5,3,5,5,5,5,5,5,5,2,82,72.0,satisfied +164,44418,Male,disloyal Customer,18,Business travel,Eco Plus,342,1,1,1,3,3,1,3,3,2,1,4,1,3,3,32,41.0,neutral or dissatisfied +165,95746,Male,Loyal Customer,47,Business travel,Business,3556,2,2,2,2,3,5,3,5,5,5,5,3,5,4,0,0.0,satisfied +166,41134,Female,disloyal Customer,27,Business travel,Eco,191,4,4,4,4,5,4,5,5,2,1,3,2,3,5,16,12.0,neutral or dissatisfied +167,3214,Female,Loyal Customer,67,Personal Travel,Eco Plus,693,3,1,3,1,5,1,2,1,1,3,1,1,1,4,100,91.0,neutral or dissatisfied +168,74101,Male,disloyal Customer,38,Business travel,Business,641,5,5,5,3,2,5,2,2,5,5,4,3,5,2,0,0.0,satisfied +169,106220,Female,disloyal Customer,20,Business travel,Eco,471,4,5,4,4,3,4,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +170,88134,Female,Loyal Customer,60,Business travel,Business,3823,2,2,1,2,4,4,4,5,5,4,5,3,5,3,1,0.0,satisfied +171,64475,Male,disloyal Customer,23,Business travel,Business,282,4,5,4,1,4,4,4,4,3,3,5,3,4,4,9,1.0,satisfied +172,123812,Male,disloyal Customer,25,Business travel,Business,544,3,5,3,1,2,3,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +173,88893,Female,Loyal Customer,38,Business travel,Business,2955,3,3,3,3,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +174,31244,Female,Loyal Customer,40,Business travel,Business,2806,1,1,1,1,3,1,5,5,5,5,5,5,5,5,0,4.0,satisfied +175,97762,Male,Loyal Customer,19,Personal Travel,Eco,587,3,4,3,5,1,3,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +176,59851,Female,Loyal Customer,61,Business travel,Business,2073,3,3,3,3,4,5,4,4,4,4,4,4,4,5,6,0.0,satisfied +177,25137,Male,Loyal Customer,44,Personal Travel,Eco,1249,3,4,3,3,5,3,5,5,5,2,3,4,4,5,25,6.0,neutral or dissatisfied +178,18412,Female,Loyal Customer,22,Personal Travel,Eco,284,3,5,3,1,3,3,3,3,4,5,5,3,5,3,34,35.0,neutral or dissatisfied +179,87192,Female,disloyal Customer,8,Business travel,Eco,946,2,2,2,2,3,2,3,3,1,5,3,4,3,3,2,0.0,neutral or dissatisfied +180,127062,Female,Loyal Customer,45,Business travel,Business,3947,3,4,4,4,3,4,4,3,3,3,3,4,3,3,25,16.0,neutral or dissatisfied +181,112169,Male,Loyal Customer,46,Personal Travel,Eco,895,4,5,4,1,1,4,1,1,2,1,3,3,5,1,40,25.0,satisfied +182,127798,Female,Loyal Customer,54,Business travel,Business,1634,3,2,5,2,4,4,4,3,3,3,3,3,3,1,90,77.0,neutral or dissatisfied +183,91778,Male,Loyal Customer,62,Personal Travel,Eco,588,2,1,1,2,1,1,1,1,1,4,3,2,3,1,0,0.0,neutral or dissatisfied +184,42609,Female,Loyal Customer,25,Business travel,Business,2533,5,5,5,5,2,2,2,2,5,1,2,1,3,2,0,0.0,satisfied +185,67482,Female,Loyal Customer,32,Personal Travel,Eco,641,3,4,3,2,2,3,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +186,91108,Female,Loyal Customer,65,Personal Travel,Eco,581,4,4,4,2,4,4,4,1,1,4,1,4,1,5,1,3.0,neutral or dissatisfied +187,102318,Male,disloyal Customer,40,Business travel,Business,223,2,2,2,4,2,2,2,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +188,51281,Female,Loyal Customer,30,Business travel,Eco Plus,326,0,0,0,5,2,0,2,2,4,1,3,4,5,2,0,0.0,satisfied +189,6528,Female,Loyal Customer,67,Personal Travel,Eco,599,3,1,3,2,1,1,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +190,121232,Male,Loyal Customer,51,Business travel,Business,2075,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +191,72478,Female,Loyal Customer,47,Business travel,Business,964,5,5,4,5,5,4,5,5,5,5,5,4,5,3,1,3.0,satisfied +192,122788,Female,Loyal Customer,38,Business travel,Eco,599,1,4,4,4,1,1,1,1,2,3,3,3,3,1,8,0.0,neutral or dissatisfied +193,5528,Male,Loyal Customer,54,Business travel,Business,3138,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +194,107726,Female,Loyal Customer,57,Personal Travel,Eco,251,1,5,0,5,3,2,3,1,1,0,3,5,1,3,0,4.0,neutral or dissatisfied +195,72606,Male,Loyal Customer,13,Personal Travel,Eco,1119,1,5,1,3,2,1,2,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +196,75522,Female,disloyal Customer,20,Business travel,Eco,337,4,0,4,3,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +197,125687,Female,Loyal Customer,45,Business travel,Business,759,2,2,2,2,2,2,1,2,2,2,2,3,2,4,23,94.0,neutral or dissatisfied +198,79908,Female,Loyal Customer,51,Business travel,Business,2344,2,2,2,2,3,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +199,117345,Male,disloyal Customer,25,Business travel,Business,296,0,0,0,3,2,0,2,2,4,4,4,5,5,2,0,0.0,satisfied +200,73465,Female,Loyal Customer,39,Personal Travel,Eco,1005,1,4,2,3,2,1,5,5,2,4,5,5,4,5,168,163.0,neutral or dissatisfied +201,95851,Female,Loyal Customer,46,Business travel,Business,580,3,3,3,3,3,5,4,4,4,4,4,3,4,5,18,16.0,satisfied +202,44992,Male,Loyal Customer,53,Business travel,Eco,359,1,3,3,3,1,1,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +203,70631,Female,Loyal Customer,61,Personal Travel,Eco,1217,0,4,0,1,5,5,5,4,4,0,4,4,4,4,0,0.0,satisfied +204,13761,Female,Loyal Customer,61,Business travel,Eco Plus,384,4,5,5,5,3,3,2,4,4,4,4,3,4,5,96,102.0,satisfied +205,74968,Male,Loyal Customer,16,Personal Travel,Eco,2586,3,5,3,4,4,3,4,4,5,2,4,5,4,4,45,42.0,neutral or dissatisfied +206,12371,Female,Loyal Customer,44,Business travel,Business,2903,2,1,1,1,2,3,3,2,2,2,2,3,2,1,0,1.0,neutral or dissatisfied +207,8378,Female,Loyal Customer,17,Business travel,Business,3170,5,5,5,5,5,5,5,5,1,3,3,1,5,5,16,0.0,satisfied +208,82080,Female,Loyal Customer,50,Business travel,Eco,1276,2,2,2,2,4,2,3,2,2,2,2,1,2,1,35,49.0,neutral or dissatisfied +209,107972,Female,disloyal Customer,40,Business travel,Business,825,4,4,4,3,5,4,5,5,5,3,4,3,5,5,0,4.0,satisfied +210,101228,Male,Loyal Customer,47,Business travel,Business,2204,5,5,5,5,4,4,4,2,2,2,2,4,2,3,6,0.0,satisfied +211,85577,Female,Loyal Customer,80,Business travel,Business,3464,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +212,2717,Female,Loyal Customer,38,Personal Travel,Eco,562,5,3,5,3,4,5,4,4,1,1,3,4,3,4,0,0.0,satisfied +213,88529,Male,Loyal Customer,31,Personal Travel,Eco,404,5,1,5,3,3,5,3,3,4,2,4,4,4,3,0,0.0,satisfied +214,91613,Male,Loyal Customer,59,Business travel,Business,1199,4,2,2,2,5,4,4,4,4,4,4,3,4,1,0,15.0,neutral or dissatisfied +215,88865,Female,Loyal Customer,22,Business travel,Business,1968,4,4,4,4,4,4,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +216,96960,Female,Loyal Customer,53,Business travel,Business,2560,5,5,5,5,5,4,5,3,3,3,3,3,3,3,0,3.0,satisfied +217,51191,Female,Loyal Customer,56,Business travel,Eco Plus,308,4,2,2,2,5,3,4,4,4,4,4,5,4,2,0,0.0,satisfied +218,9461,Female,Loyal Customer,48,Personal Travel,Eco,362,4,4,5,3,2,4,5,3,3,5,3,5,3,4,0,0.0,neutral or dissatisfied +219,66384,Male,disloyal Customer,38,Business travel,Business,1562,3,3,3,5,2,3,2,2,5,2,5,3,4,2,2,25.0,neutral or dissatisfied +220,41934,Male,Loyal Customer,64,Personal Travel,Eco,129,1,0,1,2,1,1,1,1,3,2,5,4,4,1,13,9.0,neutral or dissatisfied +221,25381,Male,Loyal Customer,67,Personal Travel,Eco,591,2,4,2,3,5,2,3,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +222,14757,Female,Loyal Customer,62,Business travel,Business,3692,2,2,4,2,3,4,2,4,4,4,4,1,4,2,0,0.0,satisfied +223,94013,Male,Loyal Customer,57,Business travel,Business,1859,1,1,1,1,2,5,5,4,4,4,4,5,4,5,16,15.0,satisfied +224,80107,Female,disloyal Customer,27,Business travel,Eco,986,2,1,1,3,1,2,1,1,1,5,1,1,3,1,24,32.0,neutral or dissatisfied +225,23590,Female,disloyal Customer,25,Business travel,Eco,1024,1,1,1,3,5,1,5,5,1,4,4,1,4,5,13,11.0,neutral or dissatisfied +226,110384,Female,Loyal Customer,52,Business travel,Eco,919,3,4,4,4,3,2,2,3,3,3,3,1,3,1,85,72.0,neutral or dissatisfied +227,15069,Female,Loyal Customer,45,Business travel,Eco Plus,576,4,2,2,2,3,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +228,17128,Female,disloyal Customer,23,Business travel,Eco,423,3,3,3,3,1,3,1,1,2,2,3,3,3,1,6,13.0,neutral or dissatisfied +229,54060,Male,Loyal Customer,55,Business travel,Eco,1416,5,2,2,2,5,5,5,5,4,3,5,2,5,5,1,0.0,satisfied +230,129240,Male,Loyal Customer,53,Business travel,Business,1464,3,2,2,2,5,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +231,97165,Female,Loyal Customer,9,Personal Travel,Eco,715,4,4,4,3,1,4,1,1,5,4,4,4,4,1,11,4.0,satisfied +232,111696,Male,Loyal Customer,33,Business travel,Business,541,2,2,3,2,4,4,4,4,5,2,5,3,4,4,86,85.0,satisfied +233,1887,Male,disloyal Customer,64,Business travel,Business,293,3,3,3,3,3,3,3,3,4,4,4,4,4,3,3,0.0,neutral or dissatisfied +234,89086,Female,disloyal Customer,8,Business travel,Eco,2092,2,3,3,3,4,2,4,4,4,3,3,3,3,4,26,23.0,neutral or dissatisfied +235,35485,Male,Loyal Customer,34,Personal Travel,Eco,1053,4,4,4,1,3,4,3,3,3,2,5,3,5,3,34,15.0,neutral or dissatisfied +236,35719,Male,Loyal Customer,59,Personal Travel,Eco,2521,1,1,1,3,1,3,5,2,3,3,2,5,2,5,0,2.0,neutral or dissatisfied +237,85669,Female,Loyal Customer,13,Business travel,Business,2544,3,1,3,3,3,3,3,3,4,3,4,3,3,3,0,0.0,neutral or dissatisfied +238,1137,Male,Loyal Customer,44,Personal Travel,Eco,158,4,4,4,2,2,4,2,2,2,5,1,4,5,2,0,0.0,neutral or dissatisfied +239,8358,Male,Loyal Customer,54,Business travel,Business,1741,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +240,17217,Male,Loyal Customer,36,Business travel,Business,2651,4,4,4,4,3,4,4,5,5,5,5,5,5,3,10,0.0,satisfied +241,44847,Female,Loyal Customer,11,Personal Travel,Eco,760,3,5,3,1,5,3,5,5,3,5,5,4,4,5,102,88.0,neutral or dissatisfied +242,96673,Female,Loyal Customer,32,Personal Travel,Eco,1036,1,5,1,2,5,1,5,5,5,5,5,5,4,5,12,9.0,neutral or dissatisfied +243,80152,Male,Loyal Customer,42,Business travel,Eco,2586,1,3,3,3,1,1,1,3,5,2,3,1,4,1,0,0.0,neutral or dissatisfied +244,82277,Female,disloyal Customer,27,Business travel,Eco,1081,1,1,1,4,2,1,2,2,1,5,3,3,1,2,4,0.0,neutral or dissatisfied +245,123927,Male,Loyal Customer,33,Personal Travel,Eco,646,2,4,2,3,3,2,3,3,4,1,3,2,5,3,1,0.0,neutral or dissatisfied +246,115766,Female,Loyal Customer,28,Business travel,Business,308,1,3,3,3,1,1,1,1,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +247,21134,Male,Loyal Customer,44,Personal Travel,Eco,227,4,5,0,1,2,0,2,2,3,4,4,5,5,2,0,0.0,satisfied +248,112062,Male,disloyal Customer,49,Business travel,Eco,1754,3,3,3,3,4,3,5,4,1,4,3,4,4,4,33,28.0,neutral or dissatisfied +249,28643,Male,Loyal Customer,59,Business travel,Business,2176,2,3,2,2,3,5,2,5,5,5,5,4,5,4,5,0.0,satisfied +250,108010,Male,disloyal Customer,20,Business travel,Business,271,0,0,0,1,1,0,1,1,5,4,4,4,4,1,0,0.0,satisfied +251,92145,Female,Loyal Customer,46,Business travel,Business,1522,3,2,3,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +252,115846,Male,Loyal Customer,36,Business travel,Eco,325,5,5,5,5,5,5,5,5,1,5,3,1,3,5,0,0.0,satisfied +253,99685,Female,Loyal Customer,62,Business travel,Business,3217,2,2,2,2,5,4,4,4,4,4,4,4,4,5,19,16.0,satisfied +254,112072,Male,Loyal Customer,59,Business travel,Business,1491,3,3,3,3,2,4,4,3,3,2,3,4,3,3,15,14.0,satisfied +255,119226,Female,Loyal Customer,29,Personal Travel,Eco,331,3,4,3,4,3,3,3,3,5,4,2,2,4,3,0,0.0,neutral or dissatisfied +256,115925,Female,disloyal Customer,41,Business travel,Business,371,2,2,2,1,1,2,1,1,4,4,2,1,1,1,35,30.0,neutral or dissatisfied +257,106552,Male,Loyal Customer,7,Personal Travel,Eco,727,1,5,1,3,4,1,4,4,4,1,1,5,4,4,0,0.0,neutral or dissatisfied +258,25126,Female,Loyal Customer,65,Personal Travel,Business,1249,3,5,3,2,4,4,4,3,3,3,3,4,3,5,40,44.0,neutral or dissatisfied +259,33426,Male,Loyal Customer,50,Business travel,Business,2614,2,2,2,2,5,4,4,2,4,4,2,4,2,4,0,9.0,satisfied +260,125844,Female,Loyal Customer,20,Business travel,Eco,951,2,3,3,3,2,2,4,2,3,5,3,1,4,2,57,41.0,neutral or dissatisfied +261,70328,Female,Loyal Customer,58,Business travel,Business,2498,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +262,88847,Female,Loyal Customer,45,Personal Travel,Eco Plus,545,2,5,2,2,4,1,1,2,2,2,4,4,2,3,14,20.0,neutral or dissatisfied +263,108398,Male,Loyal Customer,46,Personal Travel,Eco Plus,1838,1,5,1,3,5,1,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +264,97316,Female,Loyal Customer,43,Business travel,Business,3724,3,3,3,3,4,4,5,5,5,5,5,4,5,3,19,7.0,satisfied +265,124811,Male,disloyal Customer,26,Business travel,Business,280,2,2,2,2,2,2,2,2,2,3,2,2,3,2,0,6.0,neutral or dissatisfied +266,23012,Male,Loyal Customer,41,Business travel,Eco Plus,641,5,1,1,1,5,5,5,5,3,4,3,5,5,5,0,0.0,satisfied +267,18088,Female,Loyal Customer,50,Personal Travel,Eco,488,3,5,3,1,3,4,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +268,37982,Male,Loyal Customer,38,Personal Travel,Business,1237,3,4,3,1,4,3,4,5,5,3,5,5,5,5,6,0.0,neutral or dissatisfied +269,31332,Female,disloyal Customer,38,Business travel,Eco,1062,1,1,1,2,3,1,3,3,4,1,4,5,3,3,0,0.0,neutral or dissatisfied +270,97455,Female,Loyal Customer,55,Business travel,Business,2699,2,2,2,2,2,5,4,3,3,3,3,4,3,4,0,3.0,satisfied +271,28901,Female,Loyal Customer,49,Business travel,Business,679,1,1,1,1,2,5,4,4,4,4,4,2,4,1,51,71.0,satisfied +272,107606,Male,disloyal Customer,33,Business travel,Business,423,4,4,4,3,4,4,4,4,3,2,4,5,5,4,0,5.0,neutral or dissatisfied +273,53258,Female,Loyal Customer,57,Business travel,Business,4817,4,4,4,4,5,5,5,3,3,4,4,5,4,5,0,19.0,satisfied +274,14292,Female,Loyal Customer,35,Business travel,Business,3833,3,3,3,3,3,2,3,5,5,5,5,4,5,4,0,3.0,satisfied +275,68232,Female,Loyal Customer,40,Business travel,Business,2559,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +276,51224,Female,disloyal Customer,37,Business travel,Eco Plus,373,4,4,4,4,3,4,3,3,4,4,1,1,1,3,0,0.0,neutral or dissatisfied +277,121386,Female,Loyal Customer,52,Personal Travel,Eco,2279,2,5,2,3,2,4,2,5,3,4,5,2,4,2,17,79.0,neutral or dissatisfied +278,31668,Male,Loyal Customer,41,Business travel,Eco,862,2,2,2,2,2,2,2,2,3,5,2,3,3,2,0,0.0,satisfied +279,24628,Female,Loyal Customer,14,Personal Travel,Eco,666,3,3,3,2,3,1,1,4,2,1,5,1,4,1,243,251.0,neutral or dissatisfied +280,95876,Female,Loyal Customer,32,Business travel,Business,759,2,2,2,2,5,4,5,5,3,5,4,4,4,5,0,0.0,satisfied +281,62793,Male,Loyal Customer,11,Personal Travel,Eco,2338,2,4,2,3,2,1,1,3,2,4,5,1,4,1,152,151.0,neutral or dissatisfied +282,83516,Male,Loyal Customer,12,Personal Travel,Eco,946,1,3,1,5,2,1,2,2,1,3,2,2,3,2,0,0.0,neutral or dissatisfied +283,13221,Male,Loyal Customer,41,Business travel,Eco,772,4,3,3,3,4,4,4,4,2,1,4,4,3,4,0,0.0,satisfied +284,100404,Female,disloyal Customer,45,Business travel,Business,1011,3,2,2,5,4,3,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +285,121453,Male,disloyal Customer,21,Business travel,Eco,257,2,0,2,4,5,2,1,5,1,5,1,4,5,5,0,1.0,neutral or dissatisfied +286,21454,Female,Loyal Customer,31,Business travel,Eco,164,2,3,3,3,2,2,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +287,15937,Male,Loyal Customer,38,Business travel,Eco,166,4,3,2,3,4,4,4,4,5,5,4,4,5,4,17,17.0,satisfied +288,70105,Male,Loyal Customer,40,Business travel,Business,2280,4,4,4,4,3,5,5,5,5,5,5,4,5,5,19,38.0,satisfied +289,47540,Male,Loyal Customer,13,Personal Travel,Eco,590,5,4,5,2,5,5,5,5,4,4,4,4,4,5,0,0.0,satisfied +290,57561,Female,Loyal Customer,44,Business travel,Business,1597,2,2,2,2,3,4,4,2,2,2,2,5,2,4,0,5.0,satisfied +291,124103,Female,Loyal Customer,66,Business travel,Business,2264,3,5,4,5,5,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +292,125736,Female,Loyal Customer,30,Business travel,Eco Plus,814,5,5,5,5,5,5,5,5,3,2,1,2,3,5,0,0.0,satisfied +293,93362,Male,Loyal Customer,44,Personal Travel,Eco,1024,3,1,3,3,4,3,4,4,1,1,4,3,3,4,2,0.0,neutral or dissatisfied +294,95429,Female,Loyal Customer,53,Business travel,Business,3276,0,5,0,4,4,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +295,106943,Female,Loyal Customer,37,Business travel,Business,2567,2,2,4,2,4,4,4,5,5,5,5,3,5,5,0,12.0,satisfied +296,100691,Female,Loyal Customer,39,Personal Travel,Eco,889,2,5,2,3,3,2,3,3,3,3,4,3,4,3,38,30.0,neutral or dissatisfied +297,119948,Male,disloyal Customer,29,Business travel,Business,1009,2,2,2,4,3,2,3,3,3,5,4,5,4,3,0,0.0,neutral or dissatisfied +298,15778,Male,Loyal Customer,38,Business travel,Eco,198,4,5,5,5,4,4,4,4,3,4,4,4,3,4,42,65.0,neutral or dissatisfied +299,68342,Male,Loyal Customer,59,Business travel,Business,1598,3,3,3,3,4,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +300,24665,Male,Loyal Customer,19,Personal Travel,Eco,873,1,0,1,3,4,1,4,4,3,4,4,3,5,4,57,65.0,neutral or dissatisfied +301,81029,Female,Loyal Customer,39,Business travel,Business,1399,4,4,2,4,4,4,5,5,5,5,5,3,5,5,16,4.0,satisfied +302,70371,Male,Loyal Customer,22,Personal Travel,Eco,1145,3,5,3,1,4,3,4,4,5,2,4,5,5,4,0,10.0,neutral or dissatisfied +303,1386,Male,Loyal Customer,50,Personal Travel,Eco Plus,282,0,4,0,5,4,0,3,4,4,4,4,3,4,4,18,10.0,satisfied +304,35225,Male,Loyal Customer,22,Business travel,Eco,1076,5,1,1,1,5,5,5,5,3,1,2,2,1,5,47,62.0,satisfied +305,86204,Male,Loyal Customer,56,Business travel,Business,3927,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,1.0,satisfied +306,126370,Male,Loyal Customer,39,Personal Travel,Eco,507,3,5,4,2,4,4,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +307,116184,Male,Loyal Customer,29,Personal Travel,Eco,325,4,3,4,4,5,4,5,5,2,5,4,3,4,5,0,0.0,satisfied +308,89613,Male,Loyal Customer,42,Business travel,Business,3404,5,5,5,5,3,5,4,5,5,5,5,3,5,3,8,0.0,satisfied +309,99020,Male,Loyal Customer,56,Business travel,Business,2387,4,4,4,4,2,5,4,3,3,4,3,4,3,3,33,21.0,satisfied +310,18463,Male,Loyal Customer,27,Business travel,Business,192,3,3,3,3,4,4,3,4,2,3,2,1,3,4,0,1.0,satisfied +311,96637,Female,disloyal Customer,21,Business travel,Eco,972,2,2,2,3,4,2,4,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +312,114678,Female,Loyal Customer,42,Business travel,Business,362,1,1,1,1,4,5,4,5,5,4,5,4,5,5,0,17.0,satisfied +313,97639,Female,Loyal Customer,48,Business travel,Business,1587,1,1,1,1,5,4,5,4,4,4,4,4,4,3,60,68.0,satisfied +314,75061,Male,Loyal Customer,53,Business travel,Business,2611,4,5,4,4,4,3,5,4,4,4,4,3,4,4,0,0.0,satisfied +315,51744,Female,Loyal Customer,64,Personal Travel,Eco,651,4,5,4,4,2,4,4,2,2,4,2,3,2,5,0,0.0,neutral or dissatisfied +316,44413,Female,Loyal Customer,49,Personal Travel,Eco,342,3,4,3,2,4,4,4,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +317,2389,Female,Loyal Customer,49,Business travel,Business,1625,5,5,5,5,4,4,4,5,5,5,5,4,5,5,0,4.0,satisfied +318,105062,Male,Loyal Customer,23,Personal Travel,Eco Plus,361,2,4,3,2,3,3,3,3,5,5,4,4,5,3,0,0.0,neutral or dissatisfied +319,91464,Male,Loyal Customer,50,Business travel,Business,3511,3,5,3,5,1,1,1,3,3,3,3,4,3,3,0,29.0,neutral or dissatisfied +320,55721,Male,Loyal Customer,51,Personal Travel,Eco Plus,927,1,4,1,3,2,1,5,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +321,65726,Male,Loyal Customer,34,Business travel,Business,3666,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +322,8473,Female,Loyal Customer,49,Business travel,Business,1187,1,1,1,1,3,5,4,3,3,3,3,4,3,3,33,40.0,satisfied +323,13488,Female,Loyal Customer,56,Business travel,Eco,106,5,2,2,2,4,1,2,5,5,5,5,4,5,3,11,4.0,satisfied +324,58611,Male,Loyal Customer,46,Business travel,Business,235,2,2,2,2,3,5,4,4,4,4,4,3,4,3,24,24.0,satisfied +325,39607,Male,Loyal Customer,25,Personal Travel,Eco,965,2,5,2,1,2,2,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +326,41704,Female,Loyal Customer,68,Personal Travel,Eco Plus,936,3,4,3,1,4,4,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +327,126579,Female,Loyal Customer,10,Personal Travel,Eco,1558,2,4,2,2,1,2,1,1,3,2,3,4,4,1,91,93.0,neutral or dissatisfied +328,44232,Female,Loyal Customer,44,Business travel,Eco,222,4,1,1,1,2,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +329,44021,Male,Loyal Customer,61,Personal Travel,Business,680,4,4,4,1,3,4,4,1,1,4,2,4,1,3,2,0.0,neutral or dissatisfied +330,67502,Female,Loyal Customer,18,Personal Travel,Eco Plus,641,3,4,3,1,4,3,1,4,2,1,1,2,4,4,13,1.0,neutral or dissatisfied +331,19525,Female,Loyal Customer,58,Business travel,Business,3065,0,5,0,3,4,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +332,110015,Female,Loyal Customer,58,Business travel,Business,3736,2,1,1,1,2,2,2,2,2,3,2,2,2,3,52,41.0,neutral or dissatisfied +333,30960,Male,Loyal Customer,64,Personal Travel,Eco,1024,4,4,4,2,4,4,4,4,3,2,5,5,4,4,12,5.0,neutral or dissatisfied +334,2153,Male,Loyal Customer,66,Personal Travel,Business,685,2,4,2,1,5,4,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +335,115097,Female,disloyal Customer,21,Business travel,Business,296,4,0,4,4,4,4,5,4,4,3,5,4,4,4,19,12.0,satisfied +336,63204,Male,Loyal Customer,39,Business travel,Business,337,4,4,4,4,2,5,4,5,5,5,5,4,5,4,5,0.0,satisfied +337,113849,Male,Loyal Customer,50,Business travel,Business,1363,2,2,2,2,2,2,2,3,5,4,4,2,5,2,238,232.0,satisfied +338,95508,Female,Loyal Customer,43,Business travel,Eco Plus,189,1,2,2,2,4,3,3,1,1,1,1,4,1,2,13,11.0,neutral or dissatisfied +339,112350,Male,Loyal Customer,41,Business travel,Business,1620,4,4,4,4,4,5,5,2,2,2,2,5,2,5,7,0.0,satisfied +340,20650,Male,Loyal Customer,46,Business travel,Eco,552,4,4,4,4,4,4,4,4,3,3,2,2,3,4,4,0.0,satisfied +341,65517,Male,Loyal Customer,41,Business travel,Business,1616,4,4,4,4,5,5,5,4,4,5,4,3,4,5,2,6.0,satisfied +342,116988,Female,Loyal Customer,31,Business travel,Eco,646,3,4,5,5,3,3,3,3,1,5,4,4,3,3,0,0.0,neutral or dissatisfied +343,116210,Female,Loyal Customer,53,Personal Travel,Eco,404,4,4,4,4,5,4,5,3,3,4,5,5,3,5,21,13.0,neutral or dissatisfied +344,15218,Female,Loyal Customer,39,Business travel,Business,3601,2,2,2,2,4,5,2,4,4,4,4,1,4,3,0,0.0,satisfied +345,35387,Female,Loyal Customer,53,Business travel,Business,635,2,2,2,2,5,5,5,1,1,2,3,5,3,5,150,156.0,satisfied +346,20002,Male,Loyal Customer,25,Business travel,Eco,646,4,5,5,5,4,4,4,4,3,4,5,5,3,4,13,4.0,satisfied +347,102927,Female,disloyal Customer,20,Business travel,Eco,317,3,4,3,3,3,3,3,3,4,1,3,4,4,3,23,14.0,neutral or dissatisfied +348,92462,Male,disloyal Customer,46,Business travel,Eco,1892,3,3,3,3,2,3,2,2,3,4,4,4,3,2,0,0.0,neutral or dissatisfied +349,70950,Male,Loyal Customer,10,Personal Travel,Eco,612,3,4,2,3,1,2,1,1,2,5,3,5,3,1,0,0.0,neutral or dissatisfied +350,76034,Female,Loyal Customer,47,Business travel,Business,2609,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +351,97177,Male,Loyal Customer,32,Personal Travel,Eco,1357,3,3,2,3,5,2,5,5,2,5,4,4,3,5,4,0.0,neutral or dissatisfied +352,51719,Female,Loyal Customer,14,Personal Travel,Eco,237,2,4,2,4,2,2,2,2,3,5,5,4,5,2,3,12.0,neutral or dissatisfied +353,129201,Female,Loyal Customer,16,Business travel,Business,2442,2,2,2,2,4,4,4,4,3,3,3,5,5,4,0,0.0,satisfied +354,35558,Female,Loyal Customer,53,Personal Travel,Eco,950,1,5,0,4,2,5,4,1,1,0,1,4,1,3,0,0.0,neutral or dissatisfied +355,109398,Male,Loyal Customer,55,Business travel,Business,2896,1,1,1,1,3,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +356,65351,Female,Loyal Customer,28,Business travel,Business,1537,2,2,2,2,5,5,5,5,5,3,5,4,5,5,0,0.0,satisfied +357,102482,Female,Loyal Customer,49,Personal Travel,Eco,197,2,3,2,4,4,4,3,3,3,2,2,3,3,1,3,0.0,neutral or dissatisfied +358,17932,Male,Loyal Customer,54,Personal Travel,Eco Plus,789,1,4,1,3,1,1,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +359,122276,Female,Loyal Customer,70,Personal Travel,Eco,541,3,4,3,4,4,5,4,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +360,57484,Female,disloyal Customer,25,Business travel,Eco,782,2,2,2,4,1,2,1,1,3,4,4,4,3,1,9,19.0,neutral or dissatisfied +361,121069,Female,Loyal Customer,48,Business travel,Business,951,1,1,1,1,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +362,41414,Male,Loyal Customer,7,Personal Travel,Eco,563,2,4,2,2,2,2,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +363,49839,Male,Loyal Customer,39,Business travel,Eco,109,3,3,3,3,3,3,3,3,3,2,3,3,3,3,0,5.0,neutral or dissatisfied +364,48189,Male,Loyal Customer,79,Business travel,Eco,414,2,1,1,1,2,2,2,2,1,2,3,1,3,2,1,0.0,neutral or dissatisfied +365,82445,Female,disloyal Customer,28,Business travel,Business,502,4,4,4,3,5,4,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +366,108108,Male,Loyal Customer,41,Business travel,Business,990,4,4,4,4,4,4,5,4,4,4,4,3,4,3,37,38.0,satisfied +367,63984,Female,disloyal Customer,27,Business travel,Eco Plus,1192,1,1,1,4,1,1,1,1,1,4,4,4,4,1,0,32.0,neutral or dissatisfied +368,105287,Female,Loyal Customer,59,Business travel,Business,2869,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,1.0,satisfied +369,9385,Female,Loyal Customer,21,Personal Travel,Eco,401,3,2,5,3,5,5,5,5,3,2,3,4,3,5,71,117.0,neutral or dissatisfied +370,25265,Male,Loyal Customer,48,Business travel,Eco,425,5,4,4,4,5,5,5,5,4,3,1,5,4,5,0,0.0,satisfied +371,119844,Male,Loyal Customer,53,Business travel,Eco,1095,3,5,5,5,3,3,3,3,1,1,3,3,4,3,0,0.0,neutral or dissatisfied +372,33840,Female,Loyal Customer,42,Business travel,Business,1609,2,4,1,4,2,2,3,2,2,2,2,2,2,1,12,0.0,neutral or dissatisfied +373,81815,Female,disloyal Customer,48,Business travel,Eco,1310,1,1,1,4,1,1,1,1,2,5,4,2,4,1,52,27.0,neutral or dissatisfied +374,83524,Male,Loyal Customer,59,Personal Travel,Eco,946,4,2,3,2,1,3,1,1,4,1,3,3,3,1,0,0.0,satisfied +375,78999,Female,Loyal Customer,53,Business travel,Business,3804,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +376,46712,Male,Loyal Customer,24,Personal Travel,Eco,125,2,4,0,4,2,0,3,2,2,2,4,1,3,2,47,94.0,neutral or dissatisfied +377,41188,Male,Loyal Customer,56,Personal Travel,Eco,429,2,1,2,3,3,2,3,3,1,4,3,3,2,3,35,29.0,neutral or dissatisfied +378,5326,Female,Loyal Customer,42,Business travel,Business,3004,5,5,3,5,3,5,5,5,5,5,5,5,5,4,5,14.0,satisfied +379,80176,Female,disloyal Customer,24,Business travel,Eco,1455,2,2,2,3,2,4,4,2,4,4,1,4,3,4,0,0.0,neutral or dissatisfied +380,46900,Male,Loyal Customer,28,Business travel,Business,833,3,3,3,3,2,2,2,2,1,1,3,4,1,2,0,0.0,satisfied +381,89219,Female,Loyal Customer,17,Personal Travel,Eco,1892,1,1,1,2,1,1,2,1,2,4,2,2,3,1,0,0.0,neutral or dissatisfied +382,17928,Male,Loyal Customer,31,Business travel,Eco Plus,789,2,4,4,4,2,1,2,2,1,4,4,3,4,2,0,0.0,neutral or dissatisfied +383,55425,Male,Loyal Customer,60,Business travel,Business,2254,3,3,5,3,4,4,4,4,4,4,4,4,4,4,2,0.0,satisfied +384,88130,Male,disloyal Customer,39,Business travel,Business,444,4,4,4,3,1,4,1,1,5,2,5,4,5,1,12,16.0,satisfied +385,48354,Female,Loyal Customer,47,Business travel,Eco,522,4,5,5,5,3,2,1,4,4,4,4,2,4,2,40,26.0,satisfied +386,105905,Male,Loyal Customer,60,Business travel,Eco,283,3,4,4,4,3,3,3,3,2,2,4,2,4,3,20,16.0,neutral or dissatisfied +387,60943,Male,Loyal Customer,13,Business travel,Business,1529,5,5,3,5,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +388,101584,Male,disloyal Customer,29,Business travel,Business,1099,1,1,1,2,3,1,5,3,1,4,2,1,2,3,51,51.0,neutral or dissatisfied +389,71388,Female,Loyal Customer,45,Business travel,Business,2580,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +390,77866,Male,Loyal Customer,44,Business travel,Business,1262,1,1,3,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +391,49223,Female,Loyal Customer,50,Business travel,Eco,109,5,1,1,1,4,5,1,5,5,5,5,3,5,2,0,11.0,satisfied +392,106530,Female,Loyal Customer,26,Personal Travel,Eco,271,3,0,3,5,5,3,5,5,4,3,5,5,4,5,100,93.0,neutral or dissatisfied +393,28676,Female,Loyal Customer,27,Business travel,Business,2777,5,5,5,5,5,5,5,5,4,1,3,3,2,5,2,0.0,satisfied +394,39553,Male,Loyal Customer,16,Business travel,Business,2865,2,2,2,2,5,5,5,5,3,2,3,4,5,5,2,0.0,satisfied +395,109597,Female,disloyal Customer,24,Business travel,Eco,920,4,4,4,4,3,4,3,3,4,3,4,4,3,3,0,0.0,neutral or dissatisfied +396,62291,Male,disloyal Customer,34,Business travel,Business,414,3,3,3,1,1,3,1,1,5,4,5,4,5,1,2,0.0,neutral or dissatisfied +397,40177,Female,Loyal Customer,30,Business travel,Business,2154,3,3,3,3,5,5,5,5,1,1,4,2,4,5,0,0.0,satisfied +398,33413,Male,Loyal Customer,50,Business travel,Eco,2349,4,3,3,3,4,4,4,4,1,2,4,3,4,4,0,0.0,satisfied +399,127599,Male,disloyal Customer,21,Business travel,Eco,1773,3,3,3,4,4,3,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +400,66723,Male,Loyal Customer,61,Personal Travel,Eco,802,1,3,1,3,4,1,4,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +401,73698,Female,Loyal Customer,32,Business travel,Business,192,3,2,2,2,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +402,27641,Female,Loyal Customer,22,Personal Travel,Eco Plus,937,2,5,3,2,1,3,1,1,1,4,4,4,3,1,0,0.0,neutral or dissatisfied +403,83891,Male,Loyal Customer,46,Business travel,Business,1050,1,0,0,4,2,4,3,4,4,0,4,3,4,2,0,0.0,neutral or dissatisfied +404,51662,Female,disloyal Customer,15,Business travel,Eco,370,3,2,2,4,4,2,3,4,3,3,3,1,4,4,3,8.0,neutral or dissatisfied +405,19833,Female,Loyal Customer,29,Personal Travel,Eco,413,3,1,3,4,1,3,1,1,1,3,4,3,4,1,7,14.0,neutral or dissatisfied +406,63416,Female,Loyal Customer,12,Personal Travel,Eco,372,4,5,4,4,5,4,5,5,4,5,4,3,5,5,89,88.0,neutral or dissatisfied +407,7645,Male,disloyal Customer,50,Business travel,Business,641,2,2,2,3,1,2,1,1,3,2,5,4,5,1,7,17.0,neutral or dissatisfied +408,86002,Male,Loyal Customer,54,Business travel,Eco,528,2,3,1,3,2,2,2,2,1,4,3,2,2,2,0,0.0,neutral or dissatisfied +409,64457,Male,Loyal Customer,69,Personal Travel,Eco,989,1,4,1,1,5,1,5,5,3,2,4,4,5,5,6,3.0,neutral or dissatisfied +410,109551,Male,Loyal Customer,38,Personal Travel,Eco,920,1,2,1,3,3,1,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +411,86553,Female,disloyal Customer,25,Business travel,Eco Plus,853,1,1,1,4,4,1,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +412,17491,Male,Loyal Customer,26,Business travel,Eco,352,3,5,5,5,3,3,1,3,4,3,4,2,4,3,108,99.0,neutral or dissatisfied +413,114667,Female,Loyal Customer,53,Business travel,Business,2690,3,3,3,3,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +414,59149,Male,Loyal Customer,47,Business travel,Business,1846,2,2,2,2,5,4,4,4,4,4,4,4,4,5,62,55.0,satisfied +415,74892,Male,Loyal Customer,42,Business travel,Business,2475,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +416,15197,Male,disloyal Customer,19,Business travel,Eco,461,3,3,3,4,3,5,4,4,5,4,4,4,4,4,141,121.0,neutral or dissatisfied +417,6867,Male,Loyal Customer,63,Personal Travel,Eco,622,3,5,3,2,3,3,3,3,4,2,5,5,5,3,10,11.0,neutral or dissatisfied +418,111943,Male,disloyal Customer,18,Business travel,Eco,533,3,5,3,4,2,3,3,2,5,4,5,5,4,2,0,0.0,neutral or dissatisfied +419,46720,Male,Loyal Customer,52,Personal Travel,Eco,125,3,5,3,2,3,3,2,3,3,5,2,1,3,3,0,0.0,neutral or dissatisfied +420,67966,Male,Loyal Customer,60,Business travel,Eco Plus,1464,3,2,2,2,3,3,3,3,4,3,4,4,4,3,0,3.0,neutral or dissatisfied +421,33341,Male,Loyal Customer,38,Business travel,Business,2355,2,2,2,2,3,4,3,5,5,5,5,1,5,3,24,0.0,satisfied +422,50319,Male,Loyal Customer,41,Business travel,Eco,77,5,1,1,1,5,5,5,5,2,2,2,1,2,5,0,0.0,satisfied +423,82927,Male,Loyal Customer,41,Business travel,Business,2563,2,2,2,2,3,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +424,14562,Female,disloyal Customer,15,Business travel,Eco,986,2,2,2,5,1,2,1,1,5,5,5,5,4,1,0,6.0,neutral or dissatisfied +425,108335,Female,Loyal Customer,49,Business travel,Eco,1750,1,5,5,5,1,1,1,4,2,2,4,1,2,1,132,117.0,neutral or dissatisfied +426,97959,Male,Loyal Customer,18,Personal Travel,Eco,793,4,4,4,5,3,4,4,3,3,4,5,4,4,3,91,71.0,satisfied +427,1026,Female,Loyal Customer,39,Business travel,Eco,229,5,5,5,5,5,5,5,5,2,3,5,3,2,5,0,0.0,satisfied +428,26910,Female,Loyal Customer,25,Business travel,Business,1874,2,3,1,1,2,2,2,2,2,2,4,4,5,2,0,0.0,neutral or dissatisfied +429,14054,Male,disloyal Customer,28,Business travel,Business,319,5,5,5,3,4,5,5,4,5,4,4,3,4,4,0,0.0,satisfied +430,109458,Female,Loyal Customer,37,Business travel,Business,2571,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +431,51772,Female,Loyal Customer,31,Personal Travel,Eco,261,3,4,3,4,3,3,3,3,1,5,4,2,4,3,87,75.0,neutral or dissatisfied +432,15019,Female,Loyal Customer,32,Personal Travel,Eco,557,3,4,3,3,3,3,3,3,5,3,4,4,5,3,81,63.0,neutral or dissatisfied +433,23664,Female,disloyal Customer,25,Business travel,Eco,196,2,4,2,4,5,2,5,5,5,4,5,5,1,5,0,5.0,neutral or dissatisfied +434,6731,Male,Loyal Customer,55,Business travel,Business,3934,3,3,3,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +435,57753,Male,Loyal Customer,51,Business travel,Business,2704,4,4,4,4,5,5,5,3,4,3,4,5,4,5,60,75.0,satisfied +436,29788,Female,Loyal Customer,40,Business travel,Business,2334,0,4,1,2,4,1,3,5,5,5,5,3,5,2,0,0.0,satisfied +437,28336,Male,Loyal Customer,25,Business travel,Business,3848,1,2,1,1,4,4,4,4,1,5,2,1,2,4,0,0.0,satisfied +438,2878,Female,Loyal Customer,70,Personal Travel,Eco,409,3,5,3,3,2,4,5,5,5,3,1,3,5,3,0,14.0,neutral or dissatisfied +439,81675,Female,Loyal Customer,55,Business travel,Eco,907,2,3,3,3,4,4,3,2,2,2,2,1,2,3,19,11.0,neutral or dissatisfied +440,50905,Male,Loyal Customer,53,Personal Travel,Eco,262,1,5,1,1,5,1,5,5,3,1,1,3,1,5,70,55.0,neutral or dissatisfied +441,90850,Male,Loyal Customer,73,Business travel,Business,2141,1,1,1,1,3,4,3,2,2,2,1,3,2,4,0,0.0,neutral or dissatisfied +442,29340,Female,Loyal Customer,32,Business travel,Eco Plus,859,0,0,0,3,3,0,2,3,3,3,4,5,4,3,0,0.0,satisfied +443,68731,Male,Loyal Customer,30,Personal Travel,Eco Plus,237,1,1,1,2,4,1,5,4,1,4,3,4,3,4,0,0.0,neutral or dissatisfied +444,115978,Male,Loyal Customer,19,Personal Travel,Eco,308,1,4,4,3,5,4,5,5,4,5,5,3,4,5,91,92.0,neutral or dissatisfied +445,29829,Male,Loyal Customer,33,Business travel,Business,3679,2,2,2,2,5,5,5,5,3,3,5,2,2,5,0,0.0,satisfied +446,82401,Female,Loyal Customer,13,Personal Travel,Eco,501,3,4,3,4,2,3,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +447,80083,Male,Loyal Customer,53,Business travel,Eco Plus,550,3,4,4,4,3,3,3,3,5,1,3,4,3,3,0,0.0,satisfied +448,42783,Female,disloyal Customer,31,Business travel,Eco,1118,1,1,1,4,2,1,2,2,3,5,4,4,4,2,0,20.0,neutral or dissatisfied +449,39020,Male,Loyal Customer,62,Business travel,Business,3179,1,1,1,1,4,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +450,46111,Male,Loyal Customer,29,Personal Travel,Eco,1085,4,4,3,5,2,3,2,2,4,5,4,3,5,2,8,11.0,neutral or dissatisfied +451,66327,Male,Loyal Customer,57,Business travel,Business,2807,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,7.0,satisfied +452,43012,Male,Loyal Customer,34,Business travel,Business,3802,0,0,0,4,3,4,1,2,2,2,2,2,2,2,0,0.0,satisfied +453,82776,Male,disloyal Customer,45,Business travel,Eco,926,3,3,3,4,5,3,2,5,3,2,3,4,4,5,26,44.0,neutral or dissatisfied +454,48215,Female,Loyal Customer,65,Personal Travel,Eco,192,1,2,1,3,5,4,3,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +455,57441,Female,Loyal Customer,48,Business travel,Business,235,2,5,5,5,2,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +456,55928,Female,Loyal Customer,8,Personal Travel,Eco,733,4,2,4,2,3,4,3,3,1,1,1,4,2,3,0,0.0,neutral or dissatisfied +457,98446,Male,Loyal Customer,36,Personal Travel,Eco,814,1,0,1,2,5,1,5,5,4,5,5,1,5,5,32,12.0,neutral or dissatisfied +458,121273,Female,Loyal Customer,48,Business travel,Business,2075,4,4,4,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +459,59385,Female,Loyal Customer,10,Personal Travel,Eco,2338,3,4,3,3,5,3,5,5,3,2,4,5,5,5,1,0.0,neutral or dissatisfied +460,27078,Male,disloyal Customer,24,Business travel,Eco,834,4,4,4,4,5,4,5,5,1,2,5,3,1,5,14,0.0,satisfied +461,104661,Male,Loyal Customer,52,Business travel,Business,1778,4,4,4,4,2,5,4,3,3,3,3,5,3,5,4,7.0,satisfied +462,111483,Male,disloyal Customer,43,Business travel,Eco,1052,3,4,4,3,4,4,4,4,3,3,2,3,1,4,0,0.0,neutral or dissatisfied +463,11558,Female,Loyal Customer,21,Business travel,Business,657,2,2,2,2,5,5,5,5,5,2,4,5,4,5,6,0.0,satisfied +464,83673,Female,disloyal Customer,24,Business travel,Eco,577,3,3,3,3,2,3,2,2,2,3,3,4,2,2,0,0.0,neutral or dissatisfied +465,120382,Male,disloyal Customer,40,Business travel,Business,449,4,4,4,2,3,4,3,3,5,4,4,4,4,3,4,0.0,satisfied +466,82170,Female,Loyal Customer,8,Personal Travel,Eco,237,1,5,1,1,2,1,3,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +467,117397,Female,Loyal Customer,40,Business travel,Business,544,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +468,59357,Male,Loyal Customer,41,Business travel,Business,2556,4,4,4,4,4,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +469,91983,Female,Loyal Customer,67,Personal Travel,Eco Plus,2475,4,4,4,4,3,3,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +470,119617,Male,Loyal Customer,40,Business travel,Business,3034,2,2,3,2,4,5,5,4,4,4,4,4,4,4,8,28.0,satisfied +471,90639,Female,Loyal Customer,51,Business travel,Business,366,1,1,1,1,3,4,4,4,4,5,4,5,4,4,0,0.0,satisfied +472,59638,Female,Loyal Customer,59,Business travel,Business,956,2,1,1,1,5,3,3,2,2,2,2,4,2,1,1,13.0,neutral or dissatisfied +473,119074,Male,Loyal Customer,29,Business travel,Business,2218,3,3,2,3,3,3,3,3,4,3,5,4,4,3,0,0.0,satisfied +474,13395,Male,Loyal Customer,70,Personal Travel,Eco,456,0,1,0,4,4,0,4,4,1,4,4,4,4,4,19,45.0,satisfied +475,108871,Male,Loyal Customer,12,Personal Travel,Eco Plus,1892,4,1,4,2,5,4,5,5,2,3,2,1,2,5,28,45.0,neutral or dissatisfied +476,104029,Male,disloyal Customer,26,Business travel,Business,1262,0,0,0,3,4,0,3,4,4,2,4,5,4,4,9,0.0,satisfied +477,12025,Male,Loyal Customer,41,Business travel,Business,3423,3,3,3,3,4,2,4,5,5,5,5,4,5,1,0,0.0,satisfied +478,42755,Male,Loyal Customer,60,Business travel,Business,493,4,4,4,4,2,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +479,32936,Male,Loyal Customer,39,Personal Travel,Eco,163,3,5,3,1,1,3,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +480,53978,Female,Loyal Customer,68,Personal Travel,Eco,1117,3,2,3,3,3,3,3,5,5,3,5,2,5,4,7,0.0,neutral or dissatisfied +481,70029,Male,Loyal Customer,32,Business travel,Business,2187,2,2,2,2,3,4,3,3,4,4,4,4,4,3,0,0.0,satisfied +482,96407,Male,Loyal Customer,18,Personal Travel,Eco,1342,3,4,4,2,3,4,3,3,4,3,3,5,5,3,0,0.0,neutral or dissatisfied +483,127129,Male,Loyal Customer,15,Personal Travel,Eco,304,3,5,3,2,2,3,1,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +484,113946,Female,Loyal Customer,43,Business travel,Business,1750,1,3,1,1,5,5,4,4,4,4,4,4,4,5,0,7.0,satisfied +485,40606,Male,Loyal Customer,49,Personal Travel,Eco,216,3,4,0,3,3,0,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +486,7742,Male,Loyal Customer,25,Personal Travel,Eco,489,3,3,3,2,3,3,5,3,4,1,5,2,4,3,8,14.0,neutral or dissatisfied +487,128529,Female,Loyal Customer,50,Personal Travel,Eco,370,2,1,2,3,1,4,3,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +488,80556,Female,Loyal Customer,39,Business travel,Business,1747,2,2,2,2,4,4,4,3,4,5,4,4,4,4,132,123.0,satisfied +489,22155,Female,Loyal Customer,33,Business travel,Business,773,2,2,2,2,4,4,4,2,3,2,2,4,1,4,140,129.0,satisfied +490,56314,Male,Loyal Customer,17,Personal Travel,Business,200,3,1,3,4,2,3,2,2,4,1,3,4,3,2,40,27.0,neutral or dissatisfied +491,82206,Male,Loyal Customer,41,Business travel,Business,405,1,1,1,1,3,4,5,1,1,2,1,3,1,4,0,5.0,satisfied +492,68344,Male,Loyal Customer,31,Business travel,Business,1598,5,5,5,5,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +493,18464,Female,disloyal Customer,39,Business travel,Business,201,4,3,3,4,1,3,1,1,2,5,5,3,1,1,0,0.0,satisfied +494,129310,Male,Loyal Customer,64,Business travel,Business,2475,3,3,3,3,2,4,5,5,5,5,5,3,5,3,4,0.0,satisfied +495,70613,Male,Loyal Customer,52,Business travel,Business,3935,1,1,1,1,3,5,5,4,4,4,4,3,4,3,0,25.0,satisfied +496,8558,Female,Loyal Customer,30,Business travel,Business,2657,4,5,4,5,1,1,4,1,3,1,4,3,3,1,8,7.0,neutral or dissatisfied +497,86840,Female,Loyal Customer,42,Business travel,Eco,292,5,2,2,2,5,2,2,5,5,5,5,2,5,5,32,29.0,satisfied +498,122170,Female,Loyal Customer,48,Business travel,Business,544,2,2,2,2,4,4,5,4,4,5,4,3,4,5,62,46.0,satisfied +499,24839,Male,Loyal Customer,29,Personal Travel,Eco,861,1,1,1,4,4,1,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +500,87935,Female,disloyal Customer,23,Business travel,Eco,271,5,0,5,1,3,5,4,3,4,5,4,5,5,3,62,84.0,satisfied +501,10735,Male,Loyal Customer,74,Business travel,Eco,134,2,5,5,5,2,2,2,2,4,2,3,2,2,2,43,41.0,neutral or dissatisfied +502,118083,Male,Loyal Customer,60,Business travel,Business,1276,3,1,1,1,5,3,4,3,3,3,3,2,3,2,10,0.0,neutral or dissatisfied +503,15189,Female,Loyal Customer,46,Business travel,Business,3185,2,5,5,5,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +504,116832,Male,Loyal Customer,55,Business travel,Business,451,1,1,1,1,4,4,5,4,4,4,4,3,4,3,0,2.0,satisfied +505,99415,Male,Loyal Customer,41,Business travel,Business,1981,4,4,4,4,4,4,2,5,5,5,5,4,5,4,0,0.0,satisfied +506,111821,Male,Loyal Customer,59,Personal Travel,Business,1605,2,5,2,5,2,3,5,2,2,2,2,3,2,4,41,19.0,neutral or dissatisfied +507,60089,Male,Loyal Customer,57,Business travel,Business,1005,4,4,4,4,5,5,4,5,5,5,5,5,5,5,3,0.0,satisfied +508,51644,Female,Loyal Customer,36,Business travel,Eco,455,3,1,1,1,3,3,3,3,4,4,3,4,3,3,0,0.0,neutral or dissatisfied +509,129771,Male,Loyal Customer,16,Personal Travel,Eco,308,3,4,3,3,1,3,5,1,4,2,5,5,4,1,2,0.0,neutral or dissatisfied +510,5412,Female,Loyal Customer,54,Business travel,Business,812,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +511,98444,Female,disloyal Customer,38,Business travel,Eco,414,3,0,3,4,3,3,3,3,1,4,5,1,1,3,17,2.0,neutral or dissatisfied +512,39113,Male,Loyal Customer,36,Business travel,Eco,190,3,2,2,2,3,4,3,3,1,2,1,2,3,3,0,0.0,satisfied +513,36518,Female,Loyal Customer,25,Business travel,Business,1197,5,5,3,5,5,5,5,5,2,4,4,1,1,5,0,5.0,satisfied +514,119576,Female,Loyal Customer,55,Personal Travel,Eco Plus,814,3,2,3,4,2,3,3,3,3,3,3,2,3,1,25,19.0,neutral or dissatisfied +515,57227,Female,Loyal Customer,40,Personal Travel,Eco,1514,2,3,2,5,1,2,1,1,2,5,2,5,3,1,0,0.0,neutral or dissatisfied +516,107365,Female,Loyal Customer,21,Personal Travel,Eco,632,1,5,1,4,2,1,4,2,4,2,5,4,5,2,9,,neutral or dissatisfied +517,233,Female,disloyal Customer,38,Business travel,Business,213,3,4,4,4,1,4,1,1,2,3,3,1,4,1,0,0.0,neutral or dissatisfied +518,70295,Female,Loyal Customer,10,Personal Travel,Eco,852,2,5,2,2,4,2,4,4,4,5,5,4,4,4,1,1.0,neutral or dissatisfied +519,110124,Female,Loyal Customer,60,Business travel,Business,1056,1,1,5,1,4,4,4,4,2,4,4,4,3,4,214,210.0,satisfied +520,46382,Female,disloyal Customer,45,Business travel,Eco,1013,3,3,3,4,4,3,4,4,1,3,2,4,4,4,0,0.0,neutral or dissatisfied +521,121254,Male,disloyal Customer,54,Business travel,Eco,575,1,0,1,1,2,1,2,2,3,3,2,4,4,2,0,8.0,neutral or dissatisfied +522,92891,Male,Loyal Customer,51,Business travel,Business,3236,4,4,4,4,5,4,5,3,3,4,5,3,3,4,0,13.0,satisfied +523,57816,Male,Loyal Customer,44,Business travel,Business,2764,5,5,5,5,3,5,5,2,2,2,2,4,2,3,8,15.0,satisfied +524,36109,Female,Loyal Customer,46,Personal Travel,Eco Plus,399,2,4,3,2,4,4,5,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +525,1770,Male,disloyal Customer,20,Business travel,Business,408,5,0,5,2,3,5,3,3,3,5,5,3,4,3,0,0.0,satisfied +526,70400,Female,Loyal Customer,44,Business travel,Business,1162,4,4,4,4,4,1,2,4,4,4,4,2,4,2,0,4.0,satisfied +527,75299,Male,Loyal Customer,36,Personal Travel,Eco Plus,1744,2,1,2,4,1,2,1,1,3,1,2,4,4,1,0,0.0,neutral or dissatisfied +528,121885,Female,Loyal Customer,13,Personal Travel,Eco,366,4,4,4,5,5,4,5,5,4,4,4,3,4,5,63,47.0,neutral or dissatisfied +529,93772,Male,Loyal Customer,38,Personal Travel,Eco Plus,368,4,3,3,3,2,3,2,2,1,3,4,4,3,2,0,0.0,neutral or dissatisfied +530,15078,Female,Loyal Customer,33,Business travel,Business,239,1,1,1,1,5,5,1,4,4,4,4,4,4,1,0,0.0,satisfied +531,17597,Male,Loyal Customer,63,Personal Travel,Eco,695,2,1,2,3,2,2,2,2,1,3,4,1,3,2,7,32.0,neutral or dissatisfied +532,4927,Female,Loyal Customer,60,Business travel,Business,1020,4,4,4,4,3,4,4,5,5,5,5,4,5,5,5,0.0,satisfied +533,32994,Female,Loyal Customer,62,Personal Travel,Eco,163,3,2,3,4,2,3,3,3,3,3,1,1,3,2,0,0.0,neutral or dissatisfied +534,8213,Female,Loyal Customer,50,Business travel,Eco,125,4,3,1,3,2,4,3,3,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +535,53073,Female,Loyal Customer,24,Business travel,Eco Plus,1208,4,5,5,5,4,4,4,4,2,2,4,1,4,4,1,0.0,satisfied +536,19789,Female,Loyal Customer,15,Personal Travel,Eco,667,2,5,3,4,5,3,4,5,4,3,5,3,4,5,35,35.0,neutral or dissatisfied +537,84270,Male,Loyal Customer,34,Business travel,Business,334,3,4,4,4,1,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +538,74151,Female,Loyal Customer,36,Business travel,Business,2046,4,1,1,1,2,3,4,4,4,3,4,1,4,2,0,62.0,neutral or dissatisfied +539,117893,Female,Loyal Customer,50,Business travel,Business,1566,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +540,15249,Male,Loyal Customer,19,Personal Travel,Eco,445,4,4,2,3,2,2,2,2,1,5,3,1,3,2,2,0.0,satisfied +541,114937,Male,Loyal Customer,52,Business travel,Business,2590,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +542,85861,Male,Loyal Customer,50,Business travel,Business,2136,4,4,4,4,2,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +543,17158,Female,disloyal Customer,26,Business travel,Eco,643,1,1,1,3,1,1,2,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +544,128028,Female,disloyal Customer,49,Business travel,Business,1440,2,2,2,4,5,2,5,5,5,5,4,3,5,5,15,3.0,neutral or dissatisfied +545,3109,Male,Loyal Customer,54,Personal Travel,Eco Plus,594,1,3,2,2,4,2,4,4,5,4,2,4,4,4,0,0.0,neutral or dissatisfied +546,6332,Male,disloyal Customer,27,Business travel,Business,296,5,5,5,3,2,5,2,2,4,3,5,4,5,2,28,51.0,satisfied +547,129473,Male,Loyal Customer,60,Business travel,Business,2611,4,4,4,4,4,4,4,4,4,5,4,4,4,4,17,10.0,satisfied +548,70511,Male,Loyal Customer,10,Personal Travel,Eco,867,4,4,4,1,4,4,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +549,8529,Female,Loyal Customer,15,Personal Travel,Eco,862,1,5,1,4,4,1,4,4,4,3,4,5,5,4,0,1.0,neutral or dissatisfied +550,44101,Female,disloyal Customer,20,Business travel,Eco,257,3,1,3,3,3,3,3,3,4,2,3,2,4,3,6,0.0,neutral or dissatisfied +551,20031,Male,Loyal Customer,52,Business travel,Business,2398,2,2,2,2,2,5,1,4,4,4,4,5,4,5,109,100.0,satisfied +552,2103,Male,Loyal Customer,60,Personal Travel,Eco,812,1,2,1,2,2,1,2,2,4,5,1,3,2,2,38,22.0,neutral or dissatisfied +553,33484,Male,Loyal Customer,44,Business travel,Business,2496,4,4,4,4,2,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +554,41094,Female,Loyal Customer,50,Business travel,Eco,140,5,1,1,1,5,2,3,5,5,5,5,4,5,4,71,58.0,satisfied +555,76419,Male,Loyal Customer,40,Business travel,Business,3142,4,4,4,4,4,4,4,3,2,4,5,4,4,4,145,147.0,satisfied +556,107120,Female,disloyal Customer,23,Business travel,Eco,842,1,1,1,1,1,1,5,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +557,109543,Female,Loyal Customer,30,Personal Travel,Eco,861,4,1,3,2,4,3,4,4,3,5,2,4,3,4,26,14.0,neutral or dissatisfied +558,86687,Male,Loyal Customer,51,Personal Travel,Business,1747,2,4,3,3,1,3,4,5,5,3,2,1,5,3,10,0.0,neutral or dissatisfied +559,106144,Female,Loyal Customer,58,Business travel,Eco,302,2,1,1,1,5,2,3,2,2,2,2,4,2,3,17,3.0,neutral or dissatisfied +560,126649,Male,Loyal Customer,46,Personal Travel,Eco,602,5,4,5,2,2,5,2,2,4,2,5,5,5,2,0,0.0,satisfied +561,5451,Male,Loyal Customer,52,Business travel,Business,265,3,4,4,4,3,1,1,3,3,4,3,4,3,3,97,123.0,neutral or dissatisfied +562,99445,Male,disloyal Customer,20,Business travel,Business,283,5,0,5,2,5,5,5,5,4,5,5,5,5,5,13,8.0,satisfied +563,44102,Male,Loyal Customer,46,Business travel,Business,473,1,1,1,1,4,1,4,5,5,5,5,5,5,3,0,0.0,satisfied +564,81994,Male,disloyal Customer,46,Business travel,Eco,1253,3,3,3,3,2,3,2,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +565,54677,Female,Loyal Customer,46,Business travel,Business,2758,4,4,4,4,2,5,1,4,4,4,4,3,4,5,0,0.0,satisfied +566,32338,Male,Loyal Customer,56,Business travel,Business,3344,0,5,0,1,3,4,4,2,2,2,2,4,2,5,0,2.0,satisfied +567,56855,Male,Loyal Customer,54,Personal Travel,Business,2565,1,4,2,4,2,3,5,3,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +568,5993,Female,Loyal Customer,55,Business travel,Business,3494,5,5,5,5,3,5,5,3,3,3,3,5,3,5,1,0.0,satisfied +569,100442,Female,disloyal Customer,27,Business travel,Business,780,4,4,4,3,4,4,2,4,1,2,4,3,4,4,26,23.0,neutral or dissatisfied +570,74164,Male,Loyal Customer,52,Personal Travel,Eco,721,1,4,0,4,5,0,5,5,3,2,5,5,4,5,0,0.0,neutral or dissatisfied +571,59220,Male,Loyal Customer,18,Personal Travel,Eco,1440,1,4,1,1,5,1,5,5,3,3,3,5,4,5,3,0.0,neutral or dissatisfied +572,47033,Female,Loyal Customer,48,Business travel,Business,2624,3,3,3,3,2,2,1,4,4,4,4,2,4,1,0,0.0,satisfied +573,51724,Male,Loyal Customer,66,Personal Travel,Eco,493,2,5,2,3,5,2,5,5,5,5,5,4,5,5,15,0.0,neutral or dissatisfied +574,107246,Male,Loyal Customer,42,Business travel,Business,307,4,4,4,4,4,5,4,5,5,5,5,3,5,3,19,11.0,satisfied +575,102045,Male,Loyal Customer,43,Business travel,Business,2864,1,4,4,4,5,2,3,1,1,1,1,2,1,1,8,0.0,neutral or dissatisfied +576,80996,Male,Loyal Customer,36,Business travel,Business,2614,1,4,4,4,5,4,4,1,1,1,1,1,1,2,9,3.0,neutral or dissatisfied +577,55696,Male,Loyal Customer,50,Business travel,Business,2633,2,2,2,2,4,5,4,3,3,4,3,5,3,4,0,3.0,satisfied +578,4705,Female,Loyal Customer,45,Personal Travel,Eco,489,2,5,2,3,1,4,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +579,124533,Female,Loyal Customer,45,Business travel,Business,3139,2,3,5,5,1,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +580,89236,Female,Loyal Customer,56,Business travel,Business,2139,3,3,3,3,5,5,5,5,5,5,5,3,5,4,38,25.0,satisfied +581,27404,Male,Loyal Customer,42,Business travel,Eco,671,4,1,1,1,4,4,4,4,4,3,1,5,2,4,60,71.0,satisfied +582,66299,Female,Loyal Customer,58,Business travel,Business,1578,4,4,2,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +583,90250,Male,Loyal Customer,9,Personal Travel,Eco,1121,3,5,3,3,1,3,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +584,69604,Male,Loyal Customer,60,Personal Travel,Eco,2475,1,3,1,3,1,5,5,2,5,1,5,5,2,5,15,79.0,neutral or dissatisfied +585,62231,Female,Loyal Customer,52,Personal Travel,Eco,2454,1,1,1,4,4,3,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +586,127414,Male,Loyal Customer,50,Personal Travel,Eco,872,3,3,3,4,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +587,83287,Male,Loyal Customer,12,Personal Travel,Eco,1979,2,5,2,3,1,2,1,1,3,5,4,5,5,1,0,29.0,neutral or dissatisfied +588,62159,Female,Loyal Customer,50,Business travel,Eco,2425,2,5,5,5,5,2,3,2,2,2,2,1,2,2,2,0.0,neutral or dissatisfied +589,89936,Male,Loyal Customer,59,Personal Travel,Eco,1306,3,5,2,3,5,2,5,5,4,4,3,5,4,5,0,0.0,neutral or dissatisfied +590,92960,Female,disloyal Customer,21,Business travel,Business,1694,5,0,4,2,2,4,2,2,5,2,3,4,5,2,0,0.0,satisfied +591,96429,Male,Loyal Customer,58,Personal Travel,Business,302,1,5,1,1,3,5,4,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +592,20254,Male,Loyal Customer,51,Business travel,Business,2048,3,2,2,2,5,4,4,3,3,3,3,2,3,1,26,23.0,neutral or dissatisfied +593,80034,Male,Loyal Customer,21,Personal Travel,Eco,950,1,5,1,1,4,1,4,4,1,1,3,3,2,4,0,34.0,neutral or dissatisfied +594,120984,Male,Loyal Customer,44,Business travel,Business,861,4,5,2,2,3,4,3,4,4,4,4,4,4,4,0,3.0,neutral or dissatisfied +595,58651,Female,disloyal Customer,23,Business travel,Eco,467,2,0,2,2,2,2,2,2,1,3,2,4,3,2,7,0.0,neutral or dissatisfied +596,45129,Female,disloyal Customer,39,Business travel,Business,174,3,3,3,4,5,3,5,5,1,3,3,2,3,5,0,7.0,neutral or dissatisfied +597,64820,Female,Loyal Customer,30,Business travel,Business,3218,2,2,5,5,2,2,2,2,1,5,3,4,3,2,16,16.0,neutral or dissatisfied +598,22529,Female,Loyal Customer,26,Personal Travel,Eco Plus,143,4,2,4,4,4,4,4,4,1,3,3,3,3,4,12,2.0,satisfied +599,117917,Female,disloyal Customer,24,Business travel,Eco,255,5,0,4,2,1,4,1,1,5,4,5,5,5,1,0,2.0,satisfied +600,9639,Male,Loyal Customer,66,Personal Travel,Business,284,3,4,3,3,5,5,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +601,91209,Female,Loyal Customer,44,Personal Travel,Eco,404,3,4,3,3,2,1,3,3,3,3,3,5,3,1,7,0.0,neutral or dissatisfied +602,61396,Female,disloyal Customer,38,Business travel,Eco,279,4,0,4,3,5,4,4,5,3,5,2,4,5,5,10,0.0,satisfied +603,12717,Female,Loyal Customer,38,Business travel,Business,1884,1,1,1,1,5,2,5,4,4,5,4,4,4,5,0,0.0,satisfied +604,82915,Male,Loyal Customer,24,Personal Travel,Eco,594,3,3,4,4,2,4,2,2,3,1,3,1,2,2,0,0.0,neutral or dissatisfied +605,120263,Female,disloyal Customer,42,Business travel,Eco,237,3,3,3,3,1,3,1,1,3,3,3,2,3,1,93,123.0,neutral or dissatisfied +606,108065,Male,Loyal Customer,58,Business travel,Business,849,5,5,5,5,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +607,122726,Female,Loyal Customer,55,Business travel,Business,3136,4,4,4,4,5,4,4,4,4,4,4,4,4,3,56,61.0,satisfied +608,24852,Male,Loyal Customer,71,Business travel,Eco Plus,991,2,1,1,1,1,2,1,1,2,3,4,4,3,1,3,0.0,neutral or dissatisfied +609,117853,Female,Loyal Customer,47,Business travel,Business,2133,5,5,1,5,2,3,4,4,4,4,4,5,4,5,26,18.0,satisfied +610,81119,Male,Loyal Customer,52,Business travel,Business,3925,5,5,5,5,4,3,4,3,3,3,3,2,3,4,0,0.0,satisfied +611,16367,Male,Loyal Customer,18,Personal Travel,Eco,319,4,1,4,4,3,4,3,3,3,3,3,3,4,3,0,0.0,neutral or dissatisfied +612,44186,Male,Loyal Customer,33,Business travel,Eco,157,5,5,5,5,5,5,5,5,2,3,3,2,2,5,30,49.0,satisfied +613,113137,Male,Loyal Customer,35,Business travel,Eco Plus,543,3,1,3,3,3,3,3,3,2,3,3,4,4,3,48,42.0,neutral or dissatisfied +614,108721,Male,Loyal Customer,29,Business travel,Business,2778,2,2,2,2,4,4,4,4,4,4,4,4,4,4,114,95.0,satisfied +615,93342,Male,Loyal Customer,57,Business travel,Business,3882,5,5,5,5,4,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +616,75321,Female,Loyal Customer,46,Business travel,Business,2556,2,2,2,2,5,5,5,3,5,3,4,5,3,5,4,10.0,satisfied +617,49436,Female,Loyal Customer,39,Business travel,Business,209,5,5,5,5,2,4,5,4,4,4,3,1,4,1,0,2.0,satisfied +618,65748,Female,Loyal Customer,62,Personal Travel,Eco,936,0,3,0,3,1,2,1,3,3,0,3,4,3,3,0,0.0,satisfied +619,102057,Female,Loyal Customer,59,Personal Travel,Business,236,3,2,3,2,2,2,3,2,2,3,2,2,2,4,5,0.0,neutral or dissatisfied +620,39468,Male,Loyal Customer,67,Personal Travel,Eco Plus,129,1,4,1,3,2,1,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +621,28492,Female,Loyal Customer,20,Personal Travel,Eco,2846,2,4,2,4,2,3,3,4,3,4,5,3,3,3,0,0.0,neutral or dissatisfied +622,64793,Female,disloyal Customer,24,Business travel,Eco,247,4,5,4,5,5,4,5,5,5,5,4,5,4,5,5,0.0,satisfied +623,18513,Female,Loyal Customer,55,Business travel,Business,2187,0,4,0,2,4,4,5,4,3,2,5,5,2,5,277,275.0,satisfied +624,8799,Female,disloyal Customer,22,Business travel,Eco,522,5,0,5,5,4,5,4,4,5,2,5,5,4,4,0,0.0,satisfied +625,92140,Male,Loyal Customer,9,Personal Travel,Eco,1576,4,5,4,5,1,4,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +626,93211,Female,Loyal Customer,56,Personal Travel,Eco,1756,1,2,1,3,3,3,3,5,5,1,5,2,5,2,9,40.0,neutral or dissatisfied +627,66112,Male,Loyal Customer,47,Business travel,Business,583,3,2,2,2,5,4,3,3,3,3,3,2,3,1,1,0.0,neutral or dissatisfied +628,108771,Male,Loyal Customer,44,Business travel,Business,3548,4,1,4,4,5,5,4,4,4,5,4,5,4,4,0,8.0,satisfied +629,35164,Female,Loyal Customer,17,Business travel,Eco,944,5,4,4,4,5,5,3,5,3,1,4,1,2,5,0,0.0,satisfied +630,48375,Female,Loyal Customer,44,Personal Travel,Eco,522,2,4,2,2,5,4,5,3,3,2,3,3,3,4,10,6.0,neutral or dissatisfied +631,46358,Female,disloyal Customer,25,Business travel,Eco,1013,2,2,2,2,5,2,5,5,5,1,3,5,2,5,9,29.0,neutral or dissatisfied +632,128508,Male,Loyal Customer,63,Personal Travel,Eco,304,1,4,1,1,5,1,1,5,4,3,4,5,5,5,0,2.0,neutral or dissatisfied +633,98704,Female,Loyal Customer,49,Business travel,Business,2234,1,1,1,1,4,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +634,18274,Male,Loyal Customer,64,Business travel,Eco Plus,179,5,3,4,3,5,5,5,5,3,2,5,5,3,5,0,0.0,satisfied +635,20972,Female,Loyal Customer,33,Personal Travel,Eco,689,4,5,4,4,2,4,2,2,3,5,4,3,5,2,0,0.0,neutral or dissatisfied +636,79500,Female,Loyal Customer,22,Business travel,Business,2317,2,2,2,2,4,4,4,4,5,5,4,3,5,4,3,9.0,satisfied +637,93098,Male,Loyal Customer,72,Business travel,Business,2162,3,4,5,5,3,3,4,3,3,3,3,3,3,3,22,14.0,neutral or dissatisfied +638,36733,Female,Loyal Customer,45,Business travel,Business,1754,3,3,3,3,5,4,5,3,3,2,3,4,3,5,0,0.0,satisfied +639,45812,Male,disloyal Customer,38,Business travel,Eco,391,4,3,4,3,5,4,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +640,65598,Female,disloyal Customer,54,Business travel,Business,175,4,4,4,1,5,4,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +641,61803,Male,Loyal Customer,54,Personal Travel,Eco,1379,1,4,1,2,1,1,1,1,4,5,4,5,5,1,11,4.0,neutral or dissatisfied +642,36818,Male,Loyal Customer,33,Business travel,Eco Plus,2300,2,4,4,4,2,2,2,2,1,4,3,3,4,2,23,46.0,neutral or dissatisfied +643,32419,Female,Loyal Customer,51,Business travel,Eco,201,1,1,1,1,4,3,4,1,1,1,1,2,1,2,8,14.0,neutral or dissatisfied +644,57621,Female,Loyal Customer,74,Business travel,Business,200,3,3,3,3,5,4,5,4,4,4,4,3,4,5,18,79.0,satisfied +645,7577,Female,Loyal Customer,59,Business travel,Business,594,5,5,3,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +646,40216,Female,disloyal Customer,21,Business travel,Business,358,2,2,2,3,3,2,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +647,89656,Female,Loyal Customer,32,Business travel,Eco,950,3,5,5,5,3,3,3,3,2,3,3,2,4,3,14,8.0,neutral or dissatisfied +648,77601,Female,Loyal Customer,47,Business travel,Business,1561,5,5,5,5,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +649,13121,Female,Loyal Customer,45,Business travel,Business,427,2,4,4,4,1,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +650,15903,Female,Loyal Customer,36,Business travel,Business,1663,5,3,5,5,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +651,24590,Male,disloyal Customer,25,Business travel,Eco,526,1,0,1,3,2,1,2,2,1,4,2,5,4,2,0,57.0,neutral or dissatisfied +652,39616,Male,Loyal Customer,48,Personal Travel,Eco,965,1,1,1,3,2,1,2,2,1,3,3,1,3,2,0,0.0,neutral or dissatisfied +653,31853,Male,Loyal Customer,34,Business travel,Eco,2677,0,0,0,3,5,0,5,5,1,2,3,2,5,5,0,0.0,satisfied +654,62199,Female,Loyal Customer,8,Personal Travel,Eco,2454,3,1,3,2,1,3,1,1,1,5,3,1,3,1,0,0.0,neutral or dissatisfied +655,70191,Male,Loyal Customer,60,Business travel,Business,2159,0,0,0,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +656,108648,Male,Loyal Customer,9,Personal Travel,Eco,762,2,5,2,2,4,2,1,4,2,5,2,5,2,4,51,,neutral or dissatisfied +657,30969,Female,Loyal Customer,41,Business travel,Eco Plus,1024,4,2,2,2,3,1,4,4,4,4,4,2,4,4,37,55.0,satisfied +658,77620,Female,Loyal Customer,24,Business travel,Business,2748,3,3,3,3,3,3,3,3,3,4,3,1,3,3,15,7.0,neutral or dissatisfied +659,83491,Female,Loyal Customer,47,Business travel,Business,946,5,5,5,5,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +660,128941,Male,Loyal Customer,43,Business travel,Business,3489,4,4,4,4,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +661,22663,Male,Loyal Customer,49,Business travel,Business,589,5,5,4,5,4,4,4,4,4,5,4,5,4,3,9,0.0,satisfied +662,78836,Female,Loyal Customer,41,Personal Travel,Eco,554,4,4,4,2,2,4,5,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +663,85042,Female,disloyal Customer,24,Business travel,Business,731,0,0,0,3,1,0,1,1,3,4,5,3,4,1,10,19.0,satisfied +664,36786,Male,Loyal Customer,80,Business travel,Eco,1111,3,3,3,3,3,3,3,5,1,4,4,3,1,3,0,0.0,satisfied +665,43842,Male,disloyal Customer,27,Business travel,Eco,174,3,5,3,4,4,3,4,4,1,2,3,2,1,4,0,0.0,neutral or dissatisfied +666,120292,Female,Loyal Customer,34,Personal Travel,Eco,1576,4,4,4,3,5,4,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +667,70616,Male,disloyal Customer,13,Business travel,Eco,1217,1,0,0,3,2,0,4,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +668,108944,Male,Loyal Customer,29,Business travel,Eco Plus,1066,4,1,1,1,4,4,4,4,4,5,3,4,4,4,129,119.0,neutral or dissatisfied +669,109590,Female,Loyal Customer,55,Business travel,Business,1827,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +670,29471,Female,Loyal Customer,42,Personal Travel,Business,1216,4,1,4,3,4,2,3,1,1,4,2,3,1,4,0,2.0,neutral or dissatisfied +671,10953,Female,disloyal Customer,27,Business travel,Eco,191,2,1,3,3,4,3,4,4,1,5,4,3,4,4,24,18.0,neutral or dissatisfied +672,87170,Male,Loyal Customer,45,Business travel,Business,2920,1,1,4,1,4,5,4,4,4,4,4,4,4,4,9,1.0,satisfied +673,40114,Male,Loyal Customer,24,Business travel,Eco,368,0,3,0,1,4,0,4,4,4,1,5,3,5,4,5,5.0,satisfied +674,60959,Male,Loyal Customer,41,Business travel,Business,1981,1,3,3,3,5,4,4,1,1,1,1,4,1,1,10,6.0,neutral or dissatisfied +675,286,Female,Loyal Customer,41,Business travel,Business,802,3,4,3,3,2,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +676,99504,Male,Loyal Customer,38,Personal Travel,Eco,307,1,4,1,1,4,1,4,4,4,2,4,5,5,4,0,6.0,neutral or dissatisfied +677,118938,Male,Loyal Customer,67,Business travel,Business,1618,3,1,1,1,3,2,2,3,3,3,3,3,3,2,0,7.0,neutral or dissatisfied +678,28296,Male,Loyal Customer,37,Business travel,Business,2061,4,4,4,4,2,2,1,4,4,4,4,1,4,3,0,0.0,satisfied +679,101005,Male,Loyal Customer,49,Business travel,Business,2635,5,5,5,5,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +680,51263,Male,Loyal Customer,50,Business travel,Eco Plus,89,5,3,3,3,5,5,5,5,3,5,1,2,3,5,0,11.0,satisfied +681,1507,Male,Loyal Customer,51,Business travel,Business,587,5,5,5,5,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +682,72911,Male,Loyal Customer,51,Business travel,Business,1897,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +683,83439,Male,disloyal Customer,22,Business travel,Eco,632,2,1,2,3,4,2,4,4,3,4,3,4,3,4,0,0.0,neutral or dissatisfied +684,39694,Male,Loyal Customer,34,Personal Travel,Eco,1463,4,5,4,3,3,4,5,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +685,98976,Male,Loyal Customer,68,Personal Travel,Eco,569,2,4,2,3,3,2,3,3,5,5,5,3,4,3,33,28.0,neutral or dissatisfied +686,28365,Male,Loyal Customer,57,Business travel,Eco,763,5,3,3,3,5,5,5,5,2,4,2,5,3,5,0,34.0,satisfied +687,54710,Male,Loyal Customer,52,Business travel,Business,454,3,3,3,3,3,5,4,4,4,4,4,4,4,1,0,1.0,satisfied +688,65308,Male,Loyal Customer,40,Business travel,Business,631,1,0,0,4,4,3,3,3,3,0,5,1,3,1,16,16.0,neutral or dissatisfied +689,52434,Female,Loyal Customer,64,Personal Travel,Eco,455,2,5,2,4,3,4,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +690,36689,Female,Loyal Customer,65,Personal Travel,Eco,1121,2,5,2,4,5,4,4,4,4,2,1,3,4,3,6,4.0,neutral or dissatisfied +691,12776,Male,Loyal Customer,50,Personal Travel,Eco Plus,721,2,3,2,3,5,2,5,5,2,5,3,4,3,5,26,16.0,neutral or dissatisfied +692,94201,Female,disloyal Customer,20,Business travel,Business,239,4,0,5,5,1,5,1,1,4,4,4,5,5,1,0,1.0,satisfied +693,81388,Female,disloyal Customer,28,Business travel,Eco,874,2,2,2,3,2,2,2,2,4,5,3,4,2,2,0,0.0,neutral or dissatisfied +694,116463,Male,Loyal Customer,15,Personal Travel,Eco,447,1,5,1,5,2,1,3,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +695,66179,Male,disloyal Customer,21,Business travel,Business,550,5,4,5,4,4,5,4,4,5,4,4,5,5,4,25,18.0,satisfied +696,88102,Female,Loyal Customer,26,Business travel,Business,1947,4,4,4,4,5,5,5,5,4,4,4,5,5,5,493,485.0,satisfied +697,26949,Female,Loyal Customer,17,Personal Travel,Eco,2402,5,4,5,4,1,5,1,1,1,5,3,1,4,1,0,0.0,satisfied +698,124725,Female,Loyal Customer,64,Personal Travel,Eco,399,0,2,0,3,3,4,3,1,1,0,1,3,1,1,0,0.0,satisfied +699,115731,Female,Loyal Customer,44,Business travel,Eco,446,3,4,4,4,5,2,2,3,3,3,3,3,3,1,1,0.0,neutral or dissatisfied +700,99559,Female,Loyal Customer,47,Business travel,Business,829,1,1,1,1,3,5,5,5,5,5,5,4,5,4,28,27.0,satisfied +701,1307,Male,Loyal Customer,53,Business travel,Business,2935,5,5,5,5,3,4,5,5,5,5,5,3,5,3,3,2.0,satisfied +702,79670,Male,Loyal Customer,58,Personal Travel,Eco,760,2,2,3,1,1,3,1,1,2,4,2,4,2,1,72,60.0,neutral or dissatisfied +703,114149,Male,Loyal Customer,48,Business travel,Business,1975,3,2,2,2,5,3,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +704,13103,Female,Loyal Customer,44,Business travel,Business,3529,4,4,4,4,1,4,4,4,4,4,4,1,4,5,0,0.0,satisfied +705,59222,Male,Loyal Customer,60,Business travel,Business,1440,5,5,3,5,4,4,5,4,4,4,4,4,4,3,26,31.0,satisfied +706,94357,Male,Loyal Customer,51,Business travel,Business,3490,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +707,97449,Male,Loyal Customer,49,Business travel,Business,756,3,3,3,3,3,4,4,4,4,4,4,3,4,5,9,0.0,satisfied +708,125235,Female,disloyal Customer,14,Business travel,Eco,1149,3,3,3,3,2,3,3,2,2,1,3,1,4,2,6,57.0,neutral or dissatisfied +709,113769,Female,Loyal Customer,19,Personal Travel,Eco,236,2,1,0,4,4,0,4,4,4,3,3,3,3,4,0,0.0,neutral or dissatisfied +710,36549,Female,disloyal Customer,24,Business travel,Eco,1249,2,2,2,1,2,2,2,2,5,5,2,4,2,2,0,0.0,neutral or dissatisfied +711,108169,Female,Loyal Customer,50,Personal Travel,Eco,1166,4,1,5,2,2,2,3,4,4,5,4,2,4,1,5,0.0,neutral or dissatisfied +712,94873,Male,disloyal Customer,39,Business travel,Eco,189,1,3,1,3,3,1,3,3,2,5,3,3,4,3,1,2.0,neutral or dissatisfied +713,123289,Male,Loyal Customer,21,Personal Travel,Eco,650,0,4,0,4,2,0,2,2,4,2,4,2,4,2,0,0.0,satisfied +714,20734,Female,disloyal Customer,30,Business travel,Eco Plus,765,1,1,1,3,2,1,2,2,2,2,1,3,3,2,0,0.0,neutral or dissatisfied +715,33889,Male,Loyal Customer,7,Personal Travel,Eco Plus,1105,4,4,4,1,2,4,2,2,4,2,4,2,2,2,6,0.0,neutral or dissatisfied +716,74146,Male,Loyal Customer,40,Business travel,Eco,592,1,2,2,2,1,1,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +717,55240,Male,Loyal Customer,50,Business travel,Business,609,1,4,4,4,1,3,4,1,1,1,1,4,1,4,14,27.0,neutral or dissatisfied +718,23104,Female,Loyal Customer,28,Business travel,Business,223,3,3,3,3,4,4,5,4,1,4,3,2,2,4,0,2.0,satisfied +719,42011,Male,Loyal Customer,49,Business travel,Business,3283,5,5,5,5,5,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +720,115119,Male,Loyal Customer,58,Business travel,Business,372,2,2,2,2,2,4,4,4,4,5,4,4,4,5,13,10.0,satisfied +721,101659,Male,disloyal Customer,23,Business travel,Business,1059,0,4,0,3,3,0,3,3,4,2,3,5,4,3,5,0.0,satisfied +722,93261,Male,Loyal Customer,48,Business travel,Business,2923,5,5,5,5,5,5,4,4,4,4,4,5,4,4,6,0.0,satisfied +723,106610,Female,Loyal Customer,23,Personal Travel,Eco,589,1,5,1,5,2,1,2,2,5,5,5,4,4,2,6,0.0,neutral or dissatisfied +724,91460,Male,Loyal Customer,56,Business travel,Business,859,3,3,3,3,2,4,4,5,5,5,5,3,5,4,0,5.0,satisfied +725,44817,Female,Loyal Customer,33,Business travel,Eco Plus,802,4,3,3,3,4,4,4,4,4,3,3,2,4,4,3,7.0,neutral or dissatisfied +726,115610,Male,Loyal Customer,39,Business travel,Business,371,3,5,5,5,2,3,3,3,3,3,3,2,3,1,7,7.0,neutral or dissatisfied +727,60041,Female,disloyal Customer,25,Business travel,Business,997,4,5,4,3,4,4,3,4,4,3,4,4,4,4,41,30.0,satisfied +728,92898,Female,Loyal Customer,42,Business travel,Business,134,4,4,4,4,3,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +729,31018,Female,Loyal Customer,56,Personal Travel,Eco,391,1,3,1,4,1,4,3,4,4,1,4,3,4,1,72,62.0,neutral or dissatisfied +730,81392,Female,disloyal Customer,20,Business travel,Eco,748,5,5,5,4,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +731,111950,Male,Loyal Customer,29,Business travel,Business,3484,1,1,1,1,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +732,80663,Female,Loyal Customer,17,Business travel,Business,821,1,4,4,4,1,1,1,1,3,1,3,4,3,1,0,0.0,neutral or dissatisfied +733,107035,Female,Loyal Customer,40,Business travel,Business,480,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +734,121308,Female,disloyal Customer,18,Business travel,Eco,1009,2,2,2,4,4,2,4,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +735,123342,Female,Loyal Customer,23,Personal Travel,Eco Plus,328,3,1,3,2,3,3,3,3,2,1,2,2,3,3,32,28.0,neutral or dissatisfied +736,32903,Female,Loyal Customer,29,Personal Travel,Eco,101,4,1,4,2,3,4,3,3,1,4,2,4,3,3,0,0.0,neutral or dissatisfied +737,17667,Female,disloyal Customer,19,Business travel,Eco Plus,1008,5,0,5,4,1,5,1,1,1,3,2,2,2,1,0,0.0,satisfied +738,6464,Female,Loyal Customer,44,Business travel,Eco Plus,296,3,2,2,2,5,4,3,2,2,3,2,2,2,2,11,11.0,neutral or dissatisfied +739,101707,Female,Loyal Customer,18,Business travel,Business,1624,5,5,5,5,4,4,4,4,3,5,4,3,4,4,0,0.0,satisfied +740,7978,Female,Loyal Customer,49,Business travel,Business,3616,5,5,2,5,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +741,110803,Male,Loyal Customer,33,Personal Travel,Eco,1105,3,4,3,4,4,3,5,4,4,2,4,4,5,4,0,11.0,neutral or dissatisfied +742,95617,Female,Loyal Customer,55,Business travel,Eco,484,4,1,1,1,2,3,3,4,4,4,4,3,4,3,4,0.0,satisfied +743,60591,Female,Loyal Customer,27,Personal Travel,Eco,1558,2,4,1,2,1,1,1,1,4,3,5,5,4,1,1,0.0,neutral or dissatisfied +744,54418,Female,Loyal Customer,42,Business travel,Business,3632,1,1,3,1,2,5,4,5,5,5,5,5,5,2,0,0.0,satisfied +745,124866,Male,Loyal Customer,18,Business travel,Eco Plus,280,3,4,4,4,3,3,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +746,51574,Female,disloyal Customer,20,Business travel,Eco,451,5,4,5,4,4,5,3,4,4,5,2,2,4,4,0,0.0,satisfied +747,114082,Female,Loyal Customer,80,Business travel,Business,2422,2,2,5,2,4,4,3,4,4,4,4,4,4,4,0,0.0,satisfied +748,35331,Female,Loyal Customer,62,Business travel,Eco,1076,3,5,5,5,3,3,3,2,1,2,2,3,4,3,332,336.0,neutral or dissatisfied +749,70468,Male,Loyal Customer,59,Business travel,Business,2980,5,5,5,5,3,5,5,4,4,4,4,4,4,3,0,29.0,satisfied +750,119099,Male,Loyal Customer,47,Business travel,Business,1107,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +751,110397,Male,disloyal Customer,27,Business travel,Eco,925,3,3,3,3,5,3,5,5,4,5,3,1,4,5,11,11.0,neutral or dissatisfied +752,108193,Male,Loyal Customer,55,Business travel,Business,1624,4,4,4,4,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +753,29278,Male,Loyal Customer,54,Business travel,Business,3995,3,1,1,1,2,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +754,98147,Female,Loyal Customer,52,Business travel,Business,562,3,3,3,3,5,5,4,5,5,4,5,3,5,3,26,21.0,satisfied +755,97689,Female,disloyal Customer,27,Business travel,Eco Plus,491,3,3,3,4,1,3,1,1,4,5,3,3,4,1,15,11.0,neutral or dissatisfied +756,20805,Male,disloyal Customer,50,Business travel,Eco,534,2,3,2,4,5,2,5,5,1,5,4,1,3,5,0,0.0,neutral or dissatisfied +757,30441,Male,Loyal Customer,58,Business travel,Business,3783,5,5,3,5,4,5,4,3,3,3,3,4,3,5,0,13.0,satisfied +758,62128,Female,Loyal Customer,25,Business travel,Business,2454,1,1,5,1,5,5,5,5,4,3,3,5,5,5,0,0.0,satisfied +759,50959,Male,Loyal Customer,70,Personal Travel,Eco,373,3,4,3,3,1,3,1,1,1,4,4,2,4,1,0,0.0,neutral or dissatisfied +760,3920,Male,Loyal Customer,9,Personal Travel,Eco,213,1,5,1,1,5,1,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +761,22989,Female,Loyal Customer,62,Personal Travel,Eco,817,5,1,5,4,4,3,4,2,2,5,2,2,2,3,0,0.0,satisfied +762,111036,Male,disloyal Customer,72,Business travel,Eco,319,3,2,3,3,4,3,4,4,4,3,3,3,3,4,14,4.0,neutral or dissatisfied +763,34805,Male,Loyal Customer,13,Personal Travel,Eco,301,1,4,1,3,4,1,4,4,1,1,4,2,3,4,0,0.0,neutral or dissatisfied +764,68068,Female,Loyal Customer,23,Business travel,Business,813,1,1,4,1,5,5,5,5,3,3,4,4,4,5,0,0.0,satisfied +765,117139,Male,Loyal Customer,29,Personal Travel,Eco,370,3,5,4,2,1,4,1,1,4,2,5,3,3,1,9,0.0,neutral or dissatisfied +766,118651,Female,Loyal Customer,46,Business travel,Eco,368,2,5,5,5,3,4,4,2,2,2,2,3,2,4,2,7.0,neutral or dissatisfied +767,16985,Male,Loyal Customer,40,Business travel,Eco,610,4,4,5,4,4,4,4,4,2,2,4,3,1,4,27,47.0,satisfied +768,85072,Male,Loyal Customer,23,Business travel,Business,3801,3,3,3,3,5,5,5,5,4,5,5,5,5,5,0,0.0,satisfied +769,15670,Male,Loyal Customer,45,Business travel,Eco,617,4,2,2,2,4,4,4,4,5,1,4,3,2,4,0,0.0,satisfied +770,68137,Male,Loyal Customer,54,Business travel,Eco Plus,813,1,1,5,1,1,1,1,1,1,1,3,2,4,1,7,4.0,neutral or dissatisfied +771,123164,Female,Loyal Customer,54,Business travel,Business,468,1,1,1,1,2,1,1,3,3,5,3,2,3,5,1,12.0,satisfied +772,36845,Male,Loyal Customer,35,Personal Travel,Eco,369,5,4,5,2,5,5,4,5,3,1,5,3,5,5,0,0.0,satisfied +773,17451,Male,Loyal Customer,60,Business travel,Eco Plus,351,5,4,4,4,5,5,5,5,3,5,5,1,4,5,0,0.0,satisfied +774,45594,Female,disloyal Customer,62,Business travel,Eco,313,2,0,2,3,3,2,3,3,5,4,2,2,2,3,0,21.0,neutral or dissatisfied +775,123709,Female,Loyal Customer,59,Personal Travel,Eco,214,4,1,0,4,3,4,4,1,1,0,1,2,1,1,0,0.0,neutral or dissatisfied +776,118741,Male,Loyal Customer,54,Personal Travel,Eco,304,3,4,3,1,3,3,3,3,4,2,5,4,5,3,13,6.0,neutral or dissatisfied +777,46265,Male,Loyal Customer,28,Personal Travel,Eco,594,1,4,1,4,4,1,3,4,3,1,2,1,4,4,36,52.0,neutral or dissatisfied +778,103439,Female,Loyal Customer,56,Business travel,Business,393,3,1,1,1,5,4,3,3,3,3,3,1,3,3,14,17.0,neutral or dissatisfied +779,117757,Male,Loyal Customer,21,Business travel,Business,1670,3,2,2,2,3,3,3,3,1,1,3,2,4,3,125,128.0,neutral or dissatisfied +780,23043,Female,Loyal Customer,44,Business travel,Eco,833,5,4,4,4,2,1,2,5,5,5,5,5,5,5,0,0.0,satisfied +781,45009,Female,Loyal Customer,27,Personal Travel,Eco,118,2,4,2,1,5,2,3,5,1,4,1,4,3,5,0,0.0,neutral or dissatisfied +782,10869,Male,Loyal Customer,37,Business travel,Eco,316,2,5,2,5,2,2,2,2,3,4,2,2,2,2,55,48.0,neutral or dissatisfied +783,113642,Male,Loyal Customer,34,Personal Travel,Eco,223,2,5,2,3,3,2,3,3,4,2,4,4,4,3,32,46.0,neutral or dissatisfied +784,36913,Female,disloyal Customer,19,Business travel,Eco,740,3,3,3,3,3,3,3,3,5,3,1,4,5,3,0,0.0,neutral or dissatisfied +785,9209,Female,Loyal Customer,65,Personal Travel,Business,100,2,3,2,1,2,5,1,2,2,2,4,2,2,4,0,0.0,neutral or dissatisfied +786,110354,Female,Loyal Customer,60,Business travel,Business,3207,3,3,3,3,2,5,4,5,5,5,5,4,5,5,102,97.0,satisfied +787,102344,Female,Loyal Customer,54,Business travel,Business,236,2,3,4,3,4,3,3,2,2,2,2,1,2,3,3,0.0,neutral or dissatisfied +788,66245,Female,Loyal Customer,10,Personal Travel,Eco,550,2,4,3,3,4,3,4,4,3,5,4,3,4,4,18,13.0,neutral or dissatisfied +789,2852,Female,Loyal Customer,54,Business travel,Business,491,4,2,2,2,5,3,3,4,4,4,4,3,4,1,13,29.0,neutral or dissatisfied +790,125304,Female,Loyal Customer,17,Business travel,Business,3892,2,2,2,2,2,2,2,2,1,4,3,2,3,2,1,0.0,neutral or dissatisfied +791,94889,Female,Loyal Customer,51,Business travel,Eco,562,5,3,4,4,5,3,2,5,5,5,5,5,5,1,12,11.0,satisfied +792,119911,Female,Loyal Customer,50,Business travel,Business,1009,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +793,129586,Male,Loyal Customer,58,Business travel,Business,2068,2,2,2,2,3,2,2,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +794,58194,Female,Loyal Customer,30,Business travel,Business,3923,3,3,3,3,3,3,3,3,1,4,4,2,3,3,1,0.0,neutral or dissatisfied +795,78323,Male,Loyal Customer,56,Business travel,Business,1547,2,2,2,2,3,4,4,2,2,2,2,4,2,5,34,18.0,satisfied +796,51948,Male,disloyal Customer,30,Business travel,Business,347,3,3,3,3,4,3,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +797,50288,Female,Loyal Customer,47,Business travel,Eco,199,3,4,4,4,3,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +798,9685,Male,disloyal Customer,22,Business travel,Eco,212,1,4,1,4,5,1,5,5,4,1,4,4,4,5,9,11.0,neutral or dissatisfied +799,90835,Male,disloyal Customer,48,Business travel,Business,223,1,1,1,1,5,1,5,5,4,2,4,3,4,5,0,5.0,neutral or dissatisfied +800,29806,Female,disloyal Customer,27,Business travel,Eco,539,2,5,2,3,5,2,5,5,2,5,3,1,5,5,0,0.0,neutral or dissatisfied +801,127821,Male,Loyal Customer,60,Personal Travel,Eco,1262,1,4,1,1,5,1,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +802,100724,Female,Loyal Customer,40,Business travel,Business,3984,2,2,2,2,5,5,4,5,5,5,5,5,5,3,12,4.0,satisfied +803,104066,Male,Loyal Customer,30,Business travel,Eco Plus,1044,4,4,4,4,4,4,4,4,2,3,4,1,3,4,15,12.0,neutral or dissatisfied +804,45221,Male,Loyal Customer,24,Business travel,Business,3090,3,1,1,1,3,3,3,3,1,1,1,5,1,3,10,4.0,neutral or dissatisfied +805,96106,Male,Loyal Customer,66,Personal Travel,Eco,1235,0,5,0,4,4,0,4,4,5,5,3,4,5,4,0,0.0,satisfied +806,5168,Female,Loyal Customer,56,Business travel,Business,383,3,3,3,3,2,2,3,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +807,85301,Female,Loyal Customer,70,Personal Travel,Eco,874,1,2,1,3,1,2,3,2,2,1,3,3,2,4,0,12.0,neutral or dissatisfied +808,27576,Male,Loyal Customer,55,Personal Travel,Eco,697,2,5,2,1,2,2,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +809,10806,Female,Loyal Customer,17,Business travel,Business,312,1,4,4,4,1,1,1,1,4,5,4,4,4,1,29,29.0,neutral or dissatisfied +810,82950,Male,Loyal Customer,46,Business travel,Business,1084,2,1,1,1,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +811,68820,Male,Loyal Customer,24,Business travel,Business,861,1,1,1,1,2,2,2,2,4,2,5,4,5,2,0,0.0,satisfied +812,41932,Female,Loyal Customer,59,Personal Travel,Eco,129,2,4,0,1,3,5,5,2,2,0,2,3,2,4,0,3.0,neutral or dissatisfied +813,94120,Male,Loyal Customer,18,Personal Travel,Business,189,3,4,3,2,3,3,3,3,2,5,4,2,1,3,1,2.0,neutral or dissatisfied +814,19301,Female,Loyal Customer,55,Personal Travel,Eco,299,1,5,3,1,3,3,3,4,4,5,5,3,3,3,136,156.0,neutral or dissatisfied +815,17606,Male,Loyal Customer,46,Business travel,Eco,196,5,2,2,2,5,5,5,5,1,5,3,3,4,5,0,0.0,satisfied +816,17961,Male,Loyal Customer,26,Personal Travel,Eco,460,5,5,5,2,5,5,4,5,4,3,5,5,5,5,0,0.0,satisfied +817,28871,Female,disloyal Customer,22,Business travel,Eco,605,0,0,0,1,4,0,4,4,2,3,5,1,3,4,0,0.0,satisfied +818,56733,Male,Loyal Customer,62,Personal Travel,Eco,937,2,5,2,5,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +819,59118,Male,Loyal Customer,20,Personal Travel,Eco,1846,4,4,4,4,4,4,4,4,3,1,2,2,3,4,40,46.0,neutral or dissatisfied +820,90580,Male,disloyal Customer,28,Business travel,Business,404,0,1,1,2,4,1,4,4,3,2,4,5,4,4,31,20.0,satisfied +821,104013,Female,Loyal Customer,57,Personal Travel,Eco,1334,1,5,1,4,2,5,4,3,3,1,3,5,3,4,3,0.0,neutral or dissatisfied +822,58434,Female,Loyal Customer,9,Personal Travel,Eco,473,1,5,1,3,1,1,1,1,1,5,5,5,2,1,14,5.0,neutral or dissatisfied +823,62768,Female,Loyal Customer,29,Business travel,Business,2486,2,2,2,2,2,2,2,2,3,1,2,2,3,2,0,14.0,neutral or dissatisfied +824,37157,Male,Loyal Customer,54,Business travel,Business,1797,3,3,3,3,5,4,2,4,4,4,4,2,4,4,60,55.0,satisfied +825,43179,Female,Loyal Customer,48,Business travel,Eco,282,4,4,4,4,1,1,2,4,4,4,4,3,4,4,64,69.0,satisfied +826,104829,Female,disloyal Customer,47,Business travel,Business,472,4,4,4,1,3,4,3,3,5,5,5,3,5,3,11,0.0,satisfied +827,53842,Female,Loyal Customer,40,Business travel,Eco,191,4,5,4,4,4,4,4,4,1,5,3,3,3,4,8,0.0,satisfied +828,16606,Female,disloyal Customer,28,Business travel,Eco,1008,3,2,2,3,1,2,1,1,5,3,3,4,2,1,0,0.0,neutral or dissatisfied +829,126600,Male,Loyal Customer,27,Business travel,Business,1337,5,5,1,5,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +830,74144,Male,Loyal Customer,59,Business travel,Business,592,4,4,4,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +831,8920,Male,Loyal Customer,28,Business travel,Eco,661,3,3,1,3,3,3,3,3,1,3,3,3,3,3,35,59.0,neutral or dissatisfied +832,106271,Female,Loyal Customer,41,Business travel,Business,604,2,2,3,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +833,125172,Male,Loyal Customer,51,Personal Travel,Eco,1089,4,5,4,4,2,4,2,2,5,4,5,5,1,2,0,32.0,neutral or dissatisfied +834,62313,Male,Loyal Customer,55,Business travel,Business,3660,3,1,1,1,3,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +835,46105,Male,Loyal Customer,29,Business travel,Business,1623,4,4,4,4,5,5,5,5,4,4,4,4,4,5,0,0.0,satisfied +836,77477,Female,disloyal Customer,35,Business travel,Business,2125,4,4,4,1,2,4,2,2,4,5,5,4,5,2,3,3.0,neutral or dissatisfied +837,59887,Male,Loyal Customer,39,Business travel,Business,1023,2,2,2,2,3,5,4,5,5,5,5,5,5,5,4,0.0,satisfied +838,10298,Female,disloyal Customer,49,Business travel,Business,316,1,1,1,3,4,1,4,4,3,3,4,3,4,4,0,1.0,neutral or dissatisfied +839,122646,Male,Loyal Customer,53,Business travel,Business,3648,2,1,4,4,3,2,2,2,2,2,2,4,2,2,42,25.0,neutral or dissatisfied +840,119398,Male,Loyal Customer,54,Business travel,Business,2436,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +841,8223,Female,Loyal Customer,44,Personal Travel,Eco,402,0,4,0,4,3,4,5,2,2,0,2,4,2,4,0,0.0,satisfied +842,514,Male,Loyal Customer,41,Business travel,Business,134,5,5,5,5,2,4,4,3,3,4,5,4,3,4,0,0.0,satisfied +843,103577,Female,Loyal Customer,35,Personal Travel,Eco,689,1,4,1,2,1,1,1,1,4,4,5,3,4,1,0,1.0,neutral or dissatisfied +844,80697,Male,Loyal Customer,49,Business travel,Business,3732,1,1,1,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +845,129555,Male,Loyal Customer,65,Personal Travel,Eco,2342,1,4,2,1,2,2,2,2,2,5,2,5,4,2,0,1.0,neutral or dissatisfied +846,53107,Female,Loyal Customer,39,Business travel,Business,2065,2,1,1,1,5,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +847,75395,Male,Loyal Customer,17,Business travel,Business,2342,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +848,19580,Male,Loyal Customer,37,Personal Travel,Eco,173,3,4,3,3,3,3,3,3,4,2,3,1,3,3,93,99.0,neutral or dissatisfied +849,77032,Male,Loyal Customer,34,Personal Travel,Eco,368,2,4,2,4,1,2,1,1,2,3,2,5,5,1,0,0.0,neutral or dissatisfied +850,42198,Female,Loyal Customer,49,Business travel,Eco,748,5,1,1,1,2,4,5,4,4,5,4,4,4,5,49,49.0,satisfied +851,6985,Female,Loyal Customer,54,Business travel,Business,1903,3,3,3,3,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +852,89822,Female,disloyal Customer,20,Business travel,Eco,1069,1,1,1,3,2,1,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +853,4380,Female,Loyal Customer,52,Business travel,Business,3894,1,1,1,1,3,1,5,5,5,5,3,1,5,2,0,50.0,satisfied +854,108923,Female,Loyal Customer,44,Personal Travel,Eco,1183,4,5,4,3,2,5,4,5,5,4,2,3,5,5,5,0.0,satisfied +855,76291,Female,disloyal Customer,21,Business travel,Eco,2677,3,3,3,2,3,1,1,1,3,4,3,1,4,1,0,17.0,neutral or dissatisfied +856,87842,Female,Loyal Customer,64,Personal Travel,Eco,214,2,2,2,3,5,3,4,4,4,2,3,1,4,4,81,72.0,neutral or dissatisfied +857,98703,Male,Loyal Customer,49,Personal Travel,Eco,861,1,4,1,4,3,1,3,3,5,3,5,4,4,3,0,44.0,neutral or dissatisfied +858,80641,Male,Loyal Customer,43,Personal Travel,Eco,282,1,2,1,3,1,1,2,1,1,4,4,4,4,1,0,0.0,neutral or dissatisfied +859,107586,Female,Loyal Customer,45,Business travel,Business,423,4,4,4,4,4,4,4,4,4,4,4,4,4,4,1,0.0,neutral or dissatisfied +860,92882,Female,Loyal Customer,57,Business travel,Business,3259,2,5,2,2,4,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +861,45533,Male,Loyal Customer,63,Business travel,Eco,566,5,2,2,2,5,5,5,5,2,4,5,3,1,5,0,0.0,satisfied +862,125911,Male,Loyal Customer,62,Personal Travel,Eco,1013,1,2,1,2,4,1,4,4,4,4,2,1,3,4,0,11.0,neutral or dissatisfied +863,86568,Female,Loyal Customer,61,Business travel,Eco Plus,762,2,5,5,5,1,3,3,2,2,2,2,4,2,4,0,23.0,neutral or dissatisfied +864,118847,Female,disloyal Customer,18,Business travel,Eco Plus,304,1,3,0,4,2,0,2,2,4,5,4,1,3,2,44,58.0,neutral or dissatisfied +865,102099,Female,Loyal Customer,46,Business travel,Business,2961,3,3,3,3,4,4,4,5,3,4,5,4,4,4,416,407.0,satisfied +866,88925,Female,Loyal Customer,43,Business travel,Business,2935,2,2,2,2,5,5,5,4,4,4,4,5,4,3,18,2.0,satisfied +867,89716,Male,Loyal Customer,56,Personal Travel,Eco,1005,2,3,2,3,3,2,3,3,1,4,3,1,3,3,24,35.0,neutral or dissatisfied +868,54873,Female,Loyal Customer,39,Business travel,Business,3207,1,1,1,1,2,3,3,4,4,4,4,2,4,4,3,0.0,satisfied +869,4354,Female,Loyal Customer,50,Business travel,Business,2845,3,1,1,1,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +870,1609,Male,Loyal Customer,42,Business travel,Business,140,4,5,5,5,2,3,3,3,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +871,46669,Female,Loyal Customer,40,Business travel,Eco,251,4,2,2,2,4,4,4,4,1,3,3,3,3,4,0,7.0,satisfied +872,2420,Female,Loyal Customer,41,Personal Travel,Eco,604,5,4,5,2,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +873,86676,Female,disloyal Customer,25,Business travel,Business,952,4,2,4,1,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +874,122412,Male,disloyal Customer,23,Business travel,Eco,1470,5,0,0,4,4,5,2,4,5,3,4,4,4,4,0,2.0,satisfied +875,112547,Male,disloyal Customer,17,Business travel,Business,846,4,4,4,2,2,4,2,2,5,3,5,3,5,2,0,0.0,satisfied +876,81539,Male,Loyal Customer,10,Personal Travel,Eco,1124,1,5,1,2,3,1,3,3,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +877,44355,Male,Loyal Customer,37,Business travel,Eco,596,4,4,4,4,4,5,4,4,3,5,3,2,4,4,0,0.0,satisfied +878,55564,Male,disloyal Customer,20,Business travel,Eco,395,0,0,0,1,2,0,2,2,4,2,5,4,5,2,0,0.0,satisfied +879,81036,Female,Loyal Customer,59,Business travel,Business,1399,4,4,4,4,4,5,4,3,3,3,3,4,3,3,2,3.0,satisfied +880,62565,Female,Loyal Customer,30,Business travel,Business,1846,5,5,2,5,4,4,4,4,5,5,5,4,5,4,14,0.0,satisfied +881,74322,Male,Loyal Customer,36,Business travel,Business,1464,2,2,2,2,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +882,67090,Female,disloyal Customer,29,Business travel,Business,1121,2,2,2,4,2,2,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +883,51430,Female,Loyal Customer,59,Personal Travel,Eco Plus,86,2,3,2,1,4,2,3,1,1,2,1,3,1,4,0,0.0,neutral or dissatisfied +884,99815,Female,Loyal Customer,68,Personal Travel,Business,468,0,2,0,4,5,3,3,4,4,0,4,1,4,2,0,0.0,satisfied +885,3643,Male,Loyal Customer,61,Business travel,Business,1961,1,1,1,1,4,5,4,4,4,4,4,3,4,3,102,97.0,satisfied +886,97188,Female,Loyal Customer,48,Personal Travel,Eco,1129,4,4,4,1,4,4,4,3,3,4,2,5,3,4,0,0.0,neutral or dissatisfied +887,38294,Male,Loyal Customer,25,Business travel,Business,2342,1,3,1,1,4,4,4,3,1,4,2,4,1,4,46,48.0,satisfied +888,96883,Male,Loyal Customer,8,Personal Travel,Eco,781,3,5,3,3,5,3,5,5,5,3,5,5,5,5,1,0.0,neutral or dissatisfied +889,31773,Male,Loyal Customer,65,Personal Travel,Eco,602,2,1,2,4,5,2,5,5,4,4,4,1,4,5,0,0.0,neutral or dissatisfied +890,53367,Male,Loyal Customer,26,Business travel,Business,1452,2,5,5,5,2,2,2,2,2,4,4,2,4,2,0,15.0,neutral or dissatisfied +891,5512,Male,Loyal Customer,53,Business travel,Business,431,4,2,2,2,1,3,4,4,4,4,4,2,4,1,6,11.0,neutral or dissatisfied +892,22172,Female,disloyal Customer,29,Business travel,Eco,773,2,2,2,3,4,2,4,4,1,3,3,3,4,4,4,13.0,neutral or dissatisfied +893,92685,Female,disloyal Customer,30,Business travel,Eco,507,2,4,2,4,4,2,4,4,2,1,3,3,3,4,0,0.0,neutral or dissatisfied +894,81531,Female,Loyal Customer,50,Business travel,Business,2283,1,5,5,5,1,2,3,1,1,2,1,1,1,4,13,5.0,neutral or dissatisfied +895,64202,Female,Loyal Customer,31,Business travel,Business,2436,1,1,3,1,1,1,1,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +896,64306,Female,Loyal Customer,41,Business travel,Business,2223,4,4,5,4,3,5,5,4,4,4,4,3,4,5,10,5.0,satisfied +897,17380,Female,Loyal Customer,44,Business travel,Eco,533,2,1,3,3,5,4,3,2,2,2,2,2,2,2,58,54.0,neutral or dissatisfied +898,33631,Female,Loyal Customer,7,Personal Travel,Eco,399,2,3,2,3,1,2,1,1,5,3,5,1,4,1,0,0.0,neutral or dissatisfied +899,109499,Male,Loyal Customer,59,Business travel,Business,951,3,3,3,3,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +900,94745,Female,Loyal Customer,53,Business travel,Business,192,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +901,126484,Male,Loyal Customer,43,Business travel,Business,1849,4,4,5,4,1,3,4,4,4,4,4,3,4,4,2,0.0,neutral or dissatisfied +902,90246,Male,Loyal Customer,46,Business travel,Business,721,2,5,5,5,4,3,4,2,2,2,2,2,2,3,39,29.0,neutral or dissatisfied +903,109782,Male,Loyal Customer,24,Personal Travel,Business,1092,2,2,2,4,2,2,2,2,4,5,4,4,3,2,0,0.0,neutral or dissatisfied +904,112610,Male,Loyal Customer,39,Business travel,Business,239,3,3,3,3,3,4,2,4,4,4,4,3,4,4,0,0.0,satisfied +905,72338,Male,disloyal Customer,37,Business travel,Business,985,1,1,1,4,5,1,5,5,3,3,5,4,4,5,2,15.0,neutral or dissatisfied +906,93939,Female,Loyal Customer,40,Business travel,Eco,107,3,3,3,3,3,4,3,3,4,4,4,2,4,3,58,43.0,neutral or dissatisfied +907,126750,Male,Loyal Customer,25,Personal Travel,Eco,2521,3,2,3,4,4,3,4,4,1,5,4,3,4,4,0,18.0,neutral or dissatisfied +908,36975,Female,Loyal Customer,28,Business travel,Eco,805,5,5,5,5,5,5,5,5,4,5,2,5,5,5,0,0.0,satisfied +909,3017,Male,Loyal Customer,44,Business travel,Business,922,1,4,4,4,5,2,2,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +910,93973,Female,disloyal Customer,21,Business travel,Business,1218,3,2,3,2,4,3,4,4,3,1,3,2,2,4,57,35.0,neutral or dissatisfied +911,69643,Male,Loyal Customer,55,Business travel,Business,2945,2,2,2,2,1,4,4,2,2,3,2,3,2,2,0,8.0,neutral or dissatisfied +912,123218,Male,Loyal Customer,17,Personal Travel,Eco,328,3,2,3,3,5,3,1,5,4,3,4,1,4,5,0,0.0,neutral or dissatisfied +913,122185,Male,Loyal Customer,49,Business travel,Business,541,4,4,4,4,5,4,5,3,3,4,3,5,3,5,0,0.0,satisfied +914,16656,Male,Loyal Customer,39,Business travel,Eco,488,3,4,4,4,3,3,3,3,1,2,4,3,4,3,3,12.0,neutral or dissatisfied +915,57284,Male,Loyal Customer,38,Personal Travel,Eco,628,4,5,4,5,5,4,5,5,5,3,4,3,4,5,0,0.0,satisfied +916,114246,Male,Loyal Customer,33,Business travel,Business,948,1,1,1,1,4,4,4,4,5,3,5,3,5,4,0,0.0,satisfied +917,84364,Female,Loyal Customer,35,Business travel,Business,606,1,1,1,1,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +918,53261,Male,disloyal Customer,45,Business travel,Business,901,3,3,3,2,4,3,1,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +919,69411,Female,Loyal Customer,70,Business travel,Business,2437,2,3,3,3,1,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +920,38637,Male,Loyal Customer,30,Business travel,Business,2611,3,3,2,3,4,4,4,4,5,3,4,3,4,4,11,0.0,satisfied +921,125026,Female,disloyal Customer,42,Business travel,Eco Plus,184,3,3,3,3,5,3,5,5,1,4,5,4,1,5,0,0.0,neutral or dissatisfied +922,41620,Female,Loyal Customer,34,Business travel,Eco Plus,1464,0,0,0,3,2,0,2,2,5,5,4,4,5,2,3,14.0,satisfied +923,38761,Male,Loyal Customer,24,Business travel,Eco,354,4,4,2,4,4,4,3,4,3,1,1,1,2,4,0,0.0,satisfied +924,3189,Male,Loyal Customer,39,Business travel,Business,185,2,3,3,3,4,3,4,3,3,3,2,2,3,2,105,101.0,neutral or dissatisfied +925,26509,Male,Loyal Customer,48,Personal Travel,Eco,829,3,5,3,4,3,3,3,3,4,4,4,4,4,3,5,11.0,neutral or dissatisfied +926,38521,Male,Loyal Customer,44,Business travel,Eco,2446,2,2,2,2,2,2,2,2,4,4,5,3,4,2,20,0.0,satisfied +927,11753,Male,Loyal Customer,31,Business travel,Eco,395,2,1,1,1,2,2,2,2,3,5,2,3,3,2,5,7.0,neutral or dissatisfied +928,45683,Female,Loyal Customer,37,Business travel,Business,2861,3,3,3,3,1,4,5,4,4,4,4,1,4,5,0,0.0,satisfied +929,23806,Male,Loyal Customer,80,Business travel,Business,3247,1,5,1,1,1,1,5,4,4,4,4,2,4,5,50,37.0,satisfied +930,73308,Male,disloyal Customer,22,Business travel,Eco,1005,5,4,4,1,4,4,5,4,3,3,4,5,5,4,0,0.0,satisfied +931,17747,Male,Loyal Customer,52,Personal Travel,Eco,383,0,5,0,1,1,0,1,1,4,4,5,5,5,1,0,0.0,satisfied +932,46329,Male,Loyal Customer,59,Personal Travel,Eco,420,3,3,5,3,1,5,1,1,2,5,3,3,3,1,5,29.0,neutral or dissatisfied +933,27803,Male,Loyal Customer,69,Business travel,Business,1448,3,3,3,3,2,4,4,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +934,41993,Female,Loyal Customer,44,Business travel,Eco,106,5,4,4,4,5,1,3,5,5,5,5,2,5,1,0,0.0,satisfied +935,20855,Female,Loyal Customer,14,Personal Travel,Eco,357,4,4,4,4,1,4,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +936,42032,Female,Loyal Customer,54,Business travel,Business,3968,3,3,3,3,2,4,1,5,5,5,5,5,5,5,0,0.0,satisfied +937,42506,Female,Loyal Customer,68,Personal Travel,Eco,541,4,3,4,3,4,4,3,5,5,4,5,4,5,2,4,0.0,neutral or dissatisfied +938,36484,Male,disloyal Customer,35,Business travel,Business,1121,4,4,4,4,5,4,5,5,3,5,3,2,3,5,10,16.0,neutral or dissatisfied +939,33321,Male,Loyal Customer,31,Business travel,Eco,2409,5,1,1,1,5,5,5,5,3,5,5,2,2,5,0,0.0,satisfied +940,49440,Female,Loyal Customer,54,Business travel,Eco,308,5,5,5,5,1,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +941,117775,Female,Loyal Customer,47,Business travel,Business,1891,3,3,3,3,2,3,4,4,4,4,4,4,4,5,0,0.0,satisfied +942,98812,Male,Loyal Customer,30,Business travel,Business,763,4,4,4,4,2,2,2,2,5,5,4,5,5,2,15,8.0,satisfied +943,113150,Male,Loyal Customer,40,Business travel,Business,2802,2,2,2,2,2,5,4,4,4,4,4,3,4,4,31,23.0,satisfied +944,101662,Male,Loyal Customer,46,Business travel,Business,2106,3,5,5,5,3,3,3,3,3,3,3,1,3,2,24,0.0,neutral or dissatisfied +945,76362,Female,Loyal Customer,40,Personal Travel,Business,931,2,4,2,4,3,5,5,5,5,2,5,3,5,4,93,101.0,neutral or dissatisfied +946,103160,Male,Loyal Customer,40,Business travel,Business,3799,2,2,5,2,2,4,5,5,5,5,5,3,5,3,81,96.0,satisfied +947,6054,Female,Loyal Customer,29,Personal Travel,Eco,672,3,4,3,3,5,3,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +948,52694,Female,Loyal Customer,53,Business travel,Eco Plus,110,2,3,5,3,4,3,3,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +949,81256,Female,disloyal Customer,17,Business travel,Business,1020,0,0,0,3,4,0,4,4,4,3,5,5,4,4,11,0.0,satisfied +950,115026,Male,Loyal Customer,27,Business travel,Business,358,1,1,3,1,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +951,31424,Female,Loyal Customer,77,Business travel,Business,203,4,3,3,3,5,4,3,2,2,2,4,1,2,4,0,11.0,neutral or dissatisfied +952,36154,Male,Loyal Customer,36,Business travel,Eco Plus,818,2,3,3,3,2,2,2,2,1,1,3,3,3,2,21,37.0,neutral or dissatisfied +953,73038,Male,Loyal Customer,43,Personal Travel,Eco,1096,3,3,3,1,3,3,3,3,5,2,2,1,3,3,68,43.0,neutral or dissatisfied +954,70922,Female,Loyal Customer,68,Business travel,Business,2832,3,3,3,3,3,4,5,3,3,4,3,5,3,3,113,105.0,satisfied +955,6442,Male,Loyal Customer,28,Personal Travel,Eco,296,3,5,3,2,5,3,5,5,3,4,5,3,5,5,17,13.0,neutral or dissatisfied +956,23792,Male,disloyal Customer,25,Business travel,Eco,374,2,1,2,1,4,2,4,4,3,3,1,3,1,4,25,29.0,neutral or dissatisfied +957,62854,Female,Loyal Customer,39,Business travel,Business,2446,2,2,2,2,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +958,125922,Female,Loyal Customer,55,Personal Travel,Eco,993,1,4,1,1,2,4,4,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +959,101735,Male,Loyal Customer,58,Business travel,Business,1590,3,3,3,3,5,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +960,13793,Female,Loyal Customer,18,Business travel,Eco Plus,878,0,5,0,4,4,0,4,4,1,2,3,1,2,4,20,20.0,satisfied +961,45544,Female,Loyal Customer,64,Business travel,Business,166,5,5,5,5,2,4,1,5,5,5,4,5,5,2,0,0.0,satisfied +962,128499,Male,Loyal Customer,7,Personal Travel,Eco,304,4,4,4,4,5,4,5,5,4,4,3,2,2,5,0,0.0,neutral or dissatisfied +963,75319,Male,Loyal Customer,41,Business travel,Business,2556,3,3,3,3,5,5,5,3,3,4,4,5,3,5,0,11.0,satisfied +964,63062,Female,Loyal Customer,56,Personal Travel,Eco,948,3,3,3,3,1,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +965,69088,Male,Loyal Customer,9,Personal Travel,Eco,1389,1,4,1,4,1,1,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +966,56055,Male,Loyal Customer,25,Personal Travel,Eco,2475,3,5,3,2,3,3,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +967,23256,Male,disloyal Customer,24,Business travel,Eco,783,1,1,1,3,4,1,1,4,1,5,3,2,2,4,0,0.0,neutral or dissatisfied +968,2766,Female,Loyal Customer,55,Business travel,Business,764,2,2,2,2,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +969,88472,Female,disloyal Customer,17,Business travel,Eco,406,3,3,3,3,4,3,4,4,2,5,3,1,4,4,40,29.0,neutral or dissatisfied +970,92733,Female,Loyal Customer,55,Business travel,Business,1298,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +971,8997,Male,Loyal Customer,37,Business travel,Business,2214,4,1,1,1,2,3,3,4,4,3,4,1,4,1,28,19.0,neutral or dissatisfied +972,72815,Male,Loyal Customer,25,Business travel,Eco Plus,645,3,5,5,5,3,3,2,3,2,5,4,4,3,3,86,82.0,neutral or dissatisfied +973,37792,Male,Loyal Customer,46,Business travel,Eco Plus,944,5,2,5,2,5,5,5,5,1,1,5,5,5,5,0,0.0,satisfied +974,115023,Male,Loyal Customer,39,Business travel,Business,308,5,5,4,5,3,5,5,4,4,4,4,4,4,4,4,8.0,satisfied +975,127160,Female,Loyal Customer,27,Personal Travel,Eco,651,2,2,2,3,1,2,1,1,1,5,4,2,3,1,124,114.0,neutral or dissatisfied +976,115148,Female,disloyal Customer,21,Business travel,Eco,337,2,1,2,4,2,2,2,4,2,4,3,2,2,2,137,138.0,neutral or dissatisfied +977,43633,Female,Loyal Customer,39,Personal Travel,Eco,119,2,2,0,3,0,3,3,2,2,3,3,3,1,3,187,191.0,neutral or dissatisfied +978,26473,Male,Loyal Customer,64,Personal Travel,Eco,919,3,5,3,3,2,3,2,2,5,1,1,4,3,2,0,0.0,neutral or dissatisfied +979,42952,Female,disloyal Customer,27,Business travel,Eco,259,2,5,3,4,2,3,2,2,1,1,5,4,3,2,0,0.0,neutral or dissatisfied +980,40592,Male,disloyal Customer,37,Business travel,Eco,117,3,1,3,4,5,3,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +981,120510,Female,Loyal Customer,63,Personal Travel,Eco Plus,449,5,3,5,3,2,4,4,2,2,5,2,3,2,1,0,0.0,satisfied +982,125418,Male,disloyal Customer,32,Business travel,Business,735,2,2,2,3,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +983,18427,Female,Loyal Customer,59,Business travel,Business,201,3,3,3,3,3,4,4,3,3,4,5,3,3,3,1,0.0,satisfied +984,45697,Female,Loyal Customer,40,Business travel,Eco Plus,896,2,1,1,1,2,2,2,2,2,5,4,3,3,2,8,10.0,neutral or dissatisfied +985,55250,Male,Loyal Customer,57,Personal Travel,Eco,1009,3,5,3,3,4,3,4,4,3,3,5,4,4,4,26,27.0,neutral or dissatisfied +986,49711,Male,disloyal Customer,25,Business travel,Eco,156,2,5,2,4,1,2,1,1,3,5,1,2,5,1,0,0.0,neutral or dissatisfied +987,41865,Male,Loyal Customer,25,Personal Travel,Eco,483,3,1,3,4,5,3,5,5,4,5,4,5,5,5,5,0.0,neutral or dissatisfied +988,67501,Male,Loyal Customer,60,Personal Travel,Eco Plus,641,3,5,3,1,5,3,5,5,3,2,5,5,5,5,7,0.0,neutral or dissatisfied +989,92116,Male,Loyal Customer,61,Personal Travel,Eco,1532,2,1,3,3,2,3,2,2,2,5,4,1,3,2,0,0.0,neutral or dissatisfied +990,43629,Male,Loyal Customer,15,Personal Travel,Eco,190,2,5,2,5,1,2,1,1,4,4,4,4,5,1,7,0.0,neutral or dissatisfied +991,19680,Female,Loyal Customer,51,Business travel,Eco,409,4,2,5,2,1,2,4,4,4,4,4,3,4,3,12,6.0,satisfied +992,48176,Female,Loyal Customer,23,Business travel,Business,236,3,4,4,4,3,3,3,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +993,107843,Male,Loyal Customer,45,Business travel,Business,2539,4,4,4,4,2,4,4,5,5,5,5,4,5,3,10,3.0,satisfied +994,1878,Male,Loyal Customer,13,Personal Travel,Eco,931,5,5,5,3,4,5,4,4,4,4,5,5,4,4,0,4.0,satisfied +995,76953,Female,disloyal Customer,31,Business travel,Business,1990,2,2,2,2,5,2,5,5,3,2,3,4,4,5,18,6.0,neutral or dissatisfied +996,66370,Male,Loyal Customer,40,Business travel,Business,3298,3,3,3,3,2,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +997,790,Female,Loyal Customer,47,Business travel,Business,482,2,2,2,2,5,4,5,4,4,4,4,5,4,4,9,0.0,satisfied +998,41623,Male,Loyal Customer,15,Personal Travel,Eco Plus,1504,3,3,3,1,2,3,2,2,4,5,1,4,1,2,0,0.0,neutral or dissatisfied +999,40956,Female,disloyal Customer,41,Business travel,Eco,601,1,4,1,3,4,1,4,4,3,1,3,4,2,4,1,0.0,neutral or dissatisfied +1000,79213,Male,Loyal Customer,22,Personal Travel,Eco,1990,2,4,2,4,1,2,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +1001,30364,Male,Loyal Customer,30,Business travel,Business,1945,1,1,1,1,5,5,5,5,3,4,5,4,1,5,36,33.0,satisfied +1002,64612,Male,Loyal Customer,60,Business travel,Business,1688,2,2,3,2,3,4,4,4,4,4,4,3,4,5,32,28.0,satisfied +1003,17057,Male,Loyal Customer,39,Business travel,Business,3905,5,5,5,5,1,2,3,5,5,5,5,1,5,1,0,0.0,satisfied +1004,96444,Male,Loyal Customer,44,Business travel,Business,302,2,2,2,2,4,4,4,5,5,5,5,4,5,4,31,22.0,satisfied +1005,71624,Female,Loyal Customer,49,Business travel,Eco,797,2,5,5,5,2,3,4,2,2,2,2,2,2,3,29,19.0,neutral or dissatisfied +1006,54240,Male,Loyal Customer,35,Business travel,Business,2615,5,5,5,5,2,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +1007,31294,Male,Loyal Customer,40,Personal Travel,Eco Plus,770,1,5,1,4,4,1,4,4,5,3,4,5,5,4,22,17.0,neutral or dissatisfied +1008,118896,Male,Loyal Customer,47,Business travel,Eco,587,1,2,1,1,1,1,1,1,1,3,3,4,4,1,35,18.0,neutral or dissatisfied +1009,53750,Female,Loyal Customer,12,Personal Travel,Eco Plus,1208,1,4,1,3,2,1,2,2,2,3,3,3,3,2,1,0.0,neutral or dissatisfied +1010,32975,Female,Loyal Customer,50,Personal Travel,Eco,163,3,4,3,1,4,4,5,4,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +1011,13179,Male,Loyal Customer,24,Business travel,Business,542,3,3,1,3,5,5,5,5,5,3,4,4,2,5,7,9.0,satisfied +1012,120172,Male,Loyal Customer,52,Business travel,Eco,335,5,5,5,5,5,5,5,5,3,5,4,2,4,5,0,0.0,satisfied +1013,76099,Female,Loyal Customer,14,Personal Travel,Eco,669,1,5,1,1,5,1,5,5,4,5,5,3,5,5,53,41.0,neutral or dissatisfied +1014,50399,Male,Loyal Customer,16,Business travel,Business,2579,2,4,4,4,2,3,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +1015,56284,Male,Loyal Customer,40,Business travel,Business,2227,5,5,5,5,4,4,5,4,4,4,4,5,4,3,15,50.0,satisfied +1016,80295,Male,Loyal Customer,54,Business travel,Eco,746,2,4,4,4,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +1017,111883,Male,Loyal Customer,72,Business travel,Business,3712,4,4,4,4,5,3,4,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +1018,22828,Female,Loyal Customer,22,Business travel,Business,134,3,5,5,5,3,3,3,3,3,2,3,2,3,3,79,70.0,neutral or dissatisfied +1019,81352,Male,Loyal Customer,24,Personal Travel,Eco,1299,2,3,2,4,5,2,5,5,1,1,2,4,3,5,1,0.0,neutral or dissatisfied +1020,3488,Female,Loyal Customer,45,Business travel,Business,1862,2,5,5,5,3,1,2,2,2,2,2,2,2,3,31,30.0,neutral or dissatisfied +1021,15894,Male,Loyal Customer,33,Business travel,Eco,269,4,3,3,3,4,4,4,4,5,2,2,4,3,4,0,0.0,satisfied +1022,51938,Female,Loyal Customer,39,Business travel,Business,936,1,1,1,1,2,4,3,3,3,4,3,5,3,1,17,3.0,satisfied +1023,44254,Male,disloyal Customer,21,Business travel,Eco,118,1,3,1,4,3,1,3,3,2,5,4,1,3,3,0,5.0,neutral or dissatisfied +1024,26778,Male,Loyal Customer,41,Business travel,Eco,1199,3,2,2,2,3,3,3,3,4,1,3,1,4,3,4,0.0,neutral or dissatisfied +1025,49352,Female,disloyal Customer,39,Business travel,Eco,158,2,0,2,5,2,2,2,2,5,3,4,4,1,2,0,0.0,neutral or dissatisfied +1026,94980,Female,disloyal Customer,24,Business travel,Eco,148,2,3,1,4,2,1,2,2,1,5,1,2,2,2,3,8.0,neutral or dissatisfied +1027,23486,Male,Loyal Customer,51,Personal Travel,Eco,576,1,4,1,1,4,1,4,4,4,5,4,4,4,4,17,24.0,neutral or dissatisfied +1028,30993,Female,disloyal Customer,44,Business travel,Eco,391,1,5,2,3,4,2,4,4,5,2,1,1,1,4,0,2.0,neutral or dissatisfied +1029,57676,Male,Loyal Customer,42,Business travel,Business,2711,5,5,3,5,4,5,4,4,4,4,4,4,4,4,5,18.0,satisfied +1030,104952,Female,disloyal Customer,49,Business travel,Business,314,3,3,3,3,5,3,1,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +1031,65054,Male,Loyal Customer,61,Personal Travel,Eco,282,4,5,4,1,5,4,5,5,2,1,4,3,5,5,0,0.0,satisfied +1032,61313,Female,Loyal Customer,59,Business travel,Business,1605,2,2,4,2,5,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +1033,97778,Female,Loyal Customer,43,Business travel,Business,1825,4,1,1,1,4,2,3,4,4,3,4,3,4,1,6,0.0,neutral or dissatisfied +1034,10236,Female,Loyal Customer,48,Business travel,Business,3195,2,1,1,1,3,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +1035,119678,Female,disloyal Customer,27,Business travel,Business,1303,2,2,2,3,5,2,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +1036,5341,Female,Loyal Customer,40,Business travel,Business,785,1,1,1,1,4,5,5,4,3,5,4,5,3,5,247,286.0,satisfied +1037,43504,Male,Loyal Customer,63,Personal Travel,Eco,624,3,5,3,4,2,3,2,2,5,3,3,4,5,2,7,17.0,neutral or dissatisfied +1038,68573,Male,disloyal Customer,16,Business travel,Eco,1616,2,2,2,3,5,2,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +1039,60207,Male,disloyal Customer,25,Business travel,Eco,1546,2,2,2,1,2,2,2,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +1040,67099,Male,Loyal Customer,40,Business travel,Eco,1102,1,3,3,3,1,1,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +1041,33312,Male,disloyal Customer,25,Business travel,Eco,1407,4,4,4,4,5,4,5,5,3,2,4,5,4,5,14,22.0,satisfied +1042,22560,Female,Loyal Customer,47,Personal Travel,Business,300,2,4,3,3,5,5,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +1043,29634,Female,Loyal Customer,36,Business travel,Business,1048,4,1,1,1,5,4,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +1044,119122,Male,Loyal Customer,67,Personal Travel,Eco,1020,2,1,1,2,5,1,5,5,1,3,2,1,3,5,0,0.0,neutral or dissatisfied +1045,115503,Male,Loyal Customer,33,Business travel,Eco,308,1,2,2,2,1,1,1,1,3,5,3,1,3,1,13,12.0,neutral or dissatisfied +1046,82380,Female,Loyal Customer,38,Business travel,Business,2848,3,3,3,3,5,5,4,4,4,4,4,4,4,3,20,1.0,satisfied +1047,48131,Male,Loyal Customer,46,Business travel,Business,2903,0,3,0,4,1,1,2,4,4,5,5,3,4,3,13,0.0,satisfied +1048,124582,Female,Loyal Customer,47,Business travel,Business,500,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +1049,72750,Male,disloyal Customer,26,Business travel,Business,806,4,4,4,5,2,4,2,2,4,2,5,5,4,2,0,0.0,satisfied +1050,123767,Male,Loyal Customer,33,Business travel,Business,2703,2,2,2,2,4,5,4,4,5,4,5,5,5,4,0,0.0,satisfied +1051,126632,Female,Loyal Customer,44,Business travel,Business,602,4,4,4,4,5,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +1052,13247,Female,Loyal Customer,35,Business travel,Eco,468,2,1,1,1,2,2,2,2,2,2,5,4,5,2,0,0.0,satisfied +1053,62234,Male,Loyal Customer,54,Personal Travel,Eco,2454,3,4,2,3,5,2,5,5,4,3,4,1,4,5,0,0.0,neutral or dissatisfied +1054,64146,Male,Loyal Customer,43,Business travel,Business,989,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +1055,109855,Female,disloyal Customer,37,Business travel,Eco,1079,4,4,4,3,1,4,1,1,4,4,3,3,4,1,24,16.0,neutral or dissatisfied +1056,103861,Female,Loyal Customer,16,Personal Travel,Eco,979,3,2,3,3,3,3,3,3,1,2,4,1,3,3,0,25.0,neutral or dissatisfied +1057,60754,Female,Loyal Customer,58,Business travel,Business,1908,2,2,2,2,2,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +1058,98299,Female,Loyal Customer,11,Personal Travel,Eco,1072,3,2,4,3,1,4,1,1,2,3,3,2,4,1,0,0.0,neutral or dissatisfied +1059,38584,Male,Loyal Customer,22,Business travel,Eco Plus,2475,2,5,5,5,2,2,4,2,1,3,3,2,4,2,48,77.0,neutral or dissatisfied +1060,84490,Male,Loyal Customer,35,Personal Travel,Eco,2994,4,4,4,4,4,3,2,2,4,4,3,2,2,2,0,0.0,neutral or dissatisfied +1061,14875,Female,Loyal Customer,71,Business travel,Business,2119,2,2,2,2,5,1,3,4,4,4,4,5,4,4,0,0.0,satisfied +1062,48090,Male,Loyal Customer,44,Business travel,Business,3785,4,4,4,4,3,5,2,5,5,5,3,5,5,2,0,16.0,satisfied +1063,64324,Male,Loyal Customer,50,Business travel,Business,3336,5,5,5,5,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +1064,68561,Female,disloyal Customer,22,Business travel,Business,1616,4,0,4,2,2,4,2,2,5,4,3,3,4,2,0,0.0,satisfied +1065,69472,Female,Loyal Customer,69,Personal Travel,Eco,1096,1,5,1,4,5,4,2,5,5,1,5,4,5,3,0,0.0,neutral or dissatisfied +1066,117618,Male,Loyal Customer,48,Business travel,Business,620,3,1,4,1,3,2,2,3,3,3,3,1,3,3,13,0.0,neutral or dissatisfied +1067,14928,Male,Loyal Customer,29,Personal Travel,Eco Plus,343,4,5,4,2,2,4,2,2,3,4,4,4,4,2,0,0.0,satisfied +1068,8949,Male,Loyal Customer,67,Personal Travel,Eco,328,3,4,3,3,5,3,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +1069,119765,Male,Loyal Customer,7,Personal Travel,Eco Plus,1325,3,5,3,4,2,3,4,2,3,5,4,5,5,2,0,6.0,neutral or dissatisfied +1070,54211,Male,Loyal Customer,29,Business travel,Eco Plus,1400,5,2,2,2,5,5,5,5,4,2,2,5,2,5,0,0.0,satisfied +1071,16797,Male,disloyal Customer,25,Business travel,Eco,1017,3,4,4,5,5,4,5,5,2,5,2,3,2,5,126,,neutral or dissatisfied +1072,39714,Female,Loyal Customer,24,Business travel,Business,2229,0,0,0,2,5,5,5,5,1,4,4,2,3,5,0,1.0,satisfied +1073,61650,Female,Loyal Customer,56,Business travel,Business,1635,2,2,2,2,4,4,4,5,2,5,4,4,3,4,145,122.0,satisfied +1074,66594,Male,Loyal Customer,34,Business travel,Business,761,1,1,1,1,4,4,5,4,4,4,4,5,4,4,10,1.0,satisfied +1075,78968,Male,Loyal Customer,45,Business travel,Business,356,1,1,1,1,5,5,4,4,4,5,4,4,4,4,60,41.0,satisfied +1076,118926,Female,Loyal Customer,42,Business travel,Business,1874,4,4,4,4,4,4,5,2,2,2,2,5,2,5,20,30.0,satisfied +1077,112399,Female,Loyal Customer,47,Business travel,Business,3240,1,1,1,1,2,4,5,4,4,4,4,4,4,3,12,2.0,satisfied +1078,81713,Male,Loyal Customer,23,Business travel,Eco Plus,907,1,1,1,1,1,1,1,1,1,4,4,2,3,1,3,0.0,neutral or dissatisfied +1079,42402,Male,disloyal Customer,18,Business travel,Eco Plus,817,2,0,2,1,5,2,4,5,2,5,1,2,5,5,0,5.0,neutral or dissatisfied +1080,14788,Female,disloyal Customer,27,Business travel,Eco,622,4,0,4,3,5,4,5,5,4,2,3,1,4,5,75,61.0,neutral or dissatisfied +1081,16996,Male,Loyal Customer,23,Business travel,Business,843,3,2,2,2,3,3,3,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +1082,59008,Female,Loyal Customer,24,Business travel,Business,1723,1,1,1,1,5,4,5,5,5,5,5,4,5,5,80,103.0,satisfied +1083,13602,Male,Loyal Customer,48,Business travel,Eco Plus,227,4,3,3,3,4,4,4,4,2,2,1,3,4,4,0,0.0,satisfied +1084,98144,Female,Loyal Customer,33,Business travel,Eco,745,3,3,3,3,3,3,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +1085,27994,Female,Loyal Customer,19,Personal Travel,Eco,1616,4,4,4,3,1,4,4,1,3,4,4,4,4,1,2,0.0,neutral or dissatisfied +1086,116125,Male,Loyal Customer,48,Personal Travel,Eco,342,1,5,1,2,2,1,2,2,3,4,5,5,5,2,4,0.0,neutral or dissatisfied +1087,110235,Male,Loyal Customer,26,Business travel,Business,2401,2,2,2,2,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +1088,104696,Male,Loyal Customer,53,Business travel,Business,159,2,2,4,2,3,5,4,5,5,4,4,4,5,5,15,13.0,satisfied +1089,18662,Male,Loyal Customer,19,Personal Travel,Eco,262,3,4,3,4,1,3,1,1,1,1,2,2,4,1,3,0.0,neutral or dissatisfied +1090,50454,Female,disloyal Customer,18,Business travel,Eco,326,1,0,0,3,3,0,2,3,3,3,5,1,2,3,0,0.0,neutral or dissatisfied +1091,35298,Female,Loyal Customer,61,Business travel,Eco,944,2,2,2,2,5,4,4,3,3,2,3,1,3,3,87,79.0,neutral or dissatisfied +1092,17541,Female,Loyal Customer,19,Personal Travel,Business,970,1,4,0,3,1,0,1,1,4,5,4,3,4,1,12,0.0,neutral or dissatisfied +1093,99655,Female,Loyal Customer,9,Business travel,Business,920,3,3,3,3,3,2,3,3,3,1,3,4,4,3,7,3.0,neutral or dissatisfied +1094,63601,Male,Loyal Customer,29,Business travel,Business,1440,5,5,5,5,4,4,4,4,5,2,5,5,5,4,8,9.0,satisfied +1095,69836,Male,Loyal Customer,38,Business travel,Business,1592,2,4,4,4,3,4,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +1096,57583,Female,disloyal Customer,27,Business travel,Eco,997,3,3,3,3,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +1097,4987,Male,Loyal Customer,48,Business travel,Business,502,3,3,3,3,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +1098,94548,Female,Loyal Customer,55,Business travel,Eco,528,2,1,1,1,2,3,4,2,2,2,2,1,2,1,5,0.0,neutral or dissatisfied +1099,48059,Female,Loyal Customer,26,Personal Travel,Eco,677,4,2,5,3,3,5,3,3,1,1,4,4,4,3,0,5.0,satisfied +1100,14437,Female,disloyal Customer,33,Business travel,Eco,674,1,1,1,3,5,1,5,5,2,4,1,5,2,5,0,0.0,neutral or dissatisfied +1101,79398,Female,Loyal Customer,62,Business travel,Business,3424,3,3,3,3,3,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +1102,48238,Male,Loyal Customer,38,Personal Travel,Eco,391,3,4,3,1,2,3,2,2,5,2,5,3,5,2,68,77.0,neutral or dissatisfied +1103,49494,Female,Loyal Customer,36,Business travel,Business,209,4,4,4,4,4,1,5,5,5,4,4,4,5,2,0,0.0,satisfied +1104,21101,Male,Loyal Customer,39,Business travel,Eco,227,3,5,5,5,3,3,3,3,3,3,3,1,3,3,42,34.0,neutral or dissatisfied +1105,93160,Male,Loyal Customer,27,Personal Travel,Eco,1183,1,5,1,3,5,1,5,5,4,5,3,3,5,5,20,0.0,neutral or dissatisfied +1106,40831,Male,Loyal Customer,33,Business travel,Business,3151,3,2,3,3,5,5,5,5,3,3,4,1,1,5,2,15.0,satisfied +1107,16414,Male,Loyal Customer,47,Business travel,Business,2356,2,2,2,2,3,3,3,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +1108,67575,Male,Loyal Customer,39,Business travel,Business,1235,2,2,2,2,5,4,5,2,2,2,2,3,2,5,8,0.0,satisfied +1109,5675,Female,disloyal Customer,27,Business travel,Business,147,2,2,2,1,2,2,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +1110,83603,Male,Loyal Customer,56,Business travel,Business,409,2,2,2,2,3,4,5,4,4,4,4,4,4,3,18,6.0,satisfied +1111,126503,Male,Loyal Customer,67,Personal Travel,Eco,1788,2,2,2,3,2,2,2,2,3,4,4,1,4,2,0,7.0,neutral or dissatisfied +1112,97633,Male,Loyal Customer,34,Personal Travel,Eco,748,2,2,2,3,3,2,3,3,4,3,4,1,3,3,129,122.0,neutral or dissatisfied +1113,105253,Male,Loyal Customer,43,Business travel,Business,2106,1,1,1,1,3,5,5,4,4,4,4,5,4,4,5,0.0,satisfied +1114,128930,Male,Loyal Customer,51,Business travel,Business,2241,3,3,3,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1115,63692,Female,Loyal Customer,39,Business travel,Business,853,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +1116,10592,Male,Loyal Customer,58,Business travel,Business,2957,5,5,5,5,2,5,4,4,4,4,5,5,4,5,45,44.0,satisfied +1117,65236,Female,disloyal Customer,38,Business travel,Business,190,4,4,4,1,1,4,1,1,4,3,4,5,4,1,0,0.0,satisfied +1118,75594,Female,disloyal Customer,21,Business travel,Eco,337,0,0,0,3,5,0,5,5,2,4,2,2,2,5,0,0.0,satisfied +1119,37492,Male,Loyal Customer,37,Business travel,Business,2376,1,5,5,5,1,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +1120,89014,Female,Loyal Customer,53,Business travel,Business,1919,3,1,1,1,4,3,3,3,3,2,3,4,3,2,100,80.0,neutral or dissatisfied +1121,50921,Male,Loyal Customer,11,Personal Travel,Eco,337,2,4,2,2,5,2,5,5,2,2,5,4,3,5,0,0.0,neutral or dissatisfied +1122,108325,Female,Loyal Customer,46,Business travel,Business,1844,5,5,5,5,4,4,4,5,5,5,5,4,5,5,39,43.0,satisfied +1123,67894,Female,Loyal Customer,46,Personal Travel,Eco,1205,4,1,4,3,4,3,3,1,1,4,1,4,1,2,0,0.0,neutral or dissatisfied +1124,70093,Male,disloyal Customer,26,Business travel,Business,550,3,4,4,2,2,4,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +1125,65907,Male,Loyal Customer,28,Business travel,Business,3935,2,2,2,2,5,5,5,5,5,2,5,4,5,5,0,0.0,satisfied +1126,44188,Female,Loyal Customer,37,Business travel,Business,2979,4,4,4,4,4,4,4,5,5,5,5,1,5,4,0,0.0,satisfied +1127,81300,Male,Loyal Customer,51,Personal Travel,Eco Plus,1020,2,0,2,3,5,2,1,5,4,3,3,3,5,5,52,30.0,neutral or dissatisfied +1128,98286,Male,Loyal Customer,36,Personal Travel,Eco,1136,5,4,5,3,1,5,1,1,4,2,3,3,4,1,0,28.0,satisfied +1129,126924,Female,Loyal Customer,59,Personal Travel,Business,651,4,2,4,3,3,3,3,2,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +1130,649,Male,disloyal Customer,37,Business travel,Business,164,3,2,2,5,4,2,4,4,3,3,4,3,4,4,0,31.0,neutral or dissatisfied +1131,70975,Male,Loyal Customer,43,Business travel,Business,802,4,4,4,4,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +1132,25240,Female,Loyal Customer,14,Personal Travel,Eco,919,2,4,2,2,5,2,5,5,4,4,3,2,5,5,0,0.0,neutral or dissatisfied +1133,122472,Female,Loyal Customer,49,Business travel,Business,3365,4,4,4,4,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +1134,118617,Male,Loyal Customer,25,Business travel,Business,651,2,5,5,5,2,2,2,2,4,1,1,4,2,2,96,80.0,neutral or dissatisfied +1135,95726,Female,Loyal Customer,22,Business travel,Eco,453,2,5,5,5,2,3,1,2,2,3,2,4,3,2,0,23.0,neutral or dissatisfied +1136,2072,Male,Loyal Customer,72,Business travel,Business,2450,3,3,3,3,4,2,2,3,3,3,3,2,3,4,12,0.0,neutral or dissatisfied +1137,74312,Male,Loyal Customer,55,Business travel,Business,3121,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,3.0,satisfied +1138,100888,Female,disloyal Customer,34,Business travel,Business,377,3,3,3,5,4,3,2,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +1139,117017,Female,Loyal Customer,36,Business travel,Business,2993,2,2,2,2,1,3,4,2,2,2,2,3,2,4,9,24.0,neutral or dissatisfied +1140,27978,Male,Loyal Customer,31,Business travel,Eco,2378,2,3,5,3,1,2,2,3,1,4,3,2,4,2,0,12.0,neutral or dissatisfied +1141,70390,Male,Loyal Customer,38,Business travel,Business,1562,4,4,4,4,4,4,5,4,4,4,4,5,4,3,13,8.0,satisfied +1142,43795,Female,disloyal Customer,20,Business travel,Eco,282,3,4,3,4,2,3,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +1143,41892,Female,Loyal Customer,47,Business travel,Business,129,2,2,2,2,2,5,2,4,4,4,4,1,4,1,12,8.0,satisfied +1144,110075,Male,Loyal Customer,76,Business travel,Business,579,5,2,2,2,1,4,3,5,5,4,5,2,5,1,0,0.0,neutral or dissatisfied +1145,20727,Male,Loyal Customer,28,Personal Travel,Eco,707,1,5,1,2,5,1,2,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +1146,49704,Male,Loyal Customer,35,Business travel,Business,3732,4,4,4,4,3,2,4,5,5,5,5,1,5,5,0,1.0,satisfied +1147,81384,Female,Loyal Customer,49,Business travel,Eco,874,2,3,3,3,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +1148,70802,Female,Loyal Customer,15,Personal Travel,Eco Plus,328,2,3,4,1,4,4,4,4,4,5,3,3,5,4,0,0.0,neutral or dissatisfied +1149,117350,Male,Loyal Customer,32,Business travel,Business,296,4,4,4,4,5,5,5,5,4,2,4,4,4,5,0,0.0,satisfied +1150,94917,Male,Loyal Customer,55,Business travel,Business,2132,3,4,2,4,3,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +1151,72231,Male,disloyal Customer,24,Business travel,Business,919,4,2,4,5,1,4,1,1,5,2,4,3,4,1,10,0.0,satisfied +1152,28781,Male,Loyal Customer,8,Business travel,Business,2053,4,4,4,4,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +1153,122659,Female,disloyal Customer,39,Business travel,Business,361,1,1,1,3,1,1,1,1,5,3,4,3,4,1,0,6.0,neutral or dissatisfied +1154,19566,Female,Loyal Customer,22,Business travel,Eco,173,2,4,4,4,2,2,3,2,2,1,4,1,3,2,13,14.0,neutral or dissatisfied +1155,14415,Female,Loyal Customer,42,Business travel,Business,2632,4,4,4,4,1,4,3,4,4,4,4,3,4,2,23,22.0,satisfied +1156,37387,Male,Loyal Customer,45,Business travel,Business,2931,1,1,2,1,4,4,1,5,5,5,5,2,5,2,0,0.0,satisfied +1157,2501,Female,disloyal Customer,24,Business travel,Eco,280,4,5,4,2,4,4,4,4,3,4,5,5,4,4,0,3.0,neutral or dissatisfied +1158,61751,Female,Loyal Customer,15,Personal Travel,Eco,1608,4,5,4,4,2,4,2,2,3,4,4,5,4,2,0,0.0,satisfied +1159,60840,Female,Loyal Customer,53,Business travel,Business,1754,1,1,1,1,5,3,5,5,5,4,5,3,5,3,0,0.0,satisfied +1160,103475,Female,Loyal Customer,56,Business travel,Business,2719,5,5,5,5,5,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +1161,93139,Female,Loyal Customer,29,Business travel,Business,1791,3,3,3,3,5,5,5,5,5,4,5,5,4,5,9,0.0,satisfied +1162,74739,Male,Loyal Customer,8,Personal Travel,Eco,1464,2,4,2,2,2,2,2,2,5,4,3,3,4,2,0,0.0,neutral or dissatisfied +1163,37097,Female,Loyal Customer,41,Business travel,Business,2417,3,3,2,3,2,3,4,4,4,4,4,4,4,4,0,28.0,satisfied +1164,122896,Female,Loyal Customer,48,Business travel,Business,2416,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +1165,118916,Female,Loyal Customer,62,Personal Travel,Eco,570,2,4,2,1,4,4,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +1166,11694,Male,Loyal Customer,44,Business travel,Business,2855,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,12.0,satisfied +1167,127390,Male,Loyal Customer,57,Business travel,Business,868,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +1168,1613,Male,disloyal Customer,62,Business travel,Business,968,2,2,2,3,5,2,5,5,1,3,3,3,3,5,0,1.0,neutral or dissatisfied +1169,96510,Male,Loyal Customer,61,Personal Travel,Eco,436,3,5,3,5,5,3,5,5,4,3,5,3,5,5,28,29.0,neutral or dissatisfied +1170,72817,Female,Loyal Customer,12,Personal Travel,Eco Plus,1045,1,4,1,1,1,1,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +1171,87228,Male,Loyal Customer,50,Business travel,Business,3880,1,1,1,1,3,5,4,4,4,4,4,5,4,4,36,27.0,satisfied +1172,66857,Male,Loyal Customer,11,Personal Travel,Eco,731,1,2,1,3,5,1,5,5,2,5,3,3,3,5,0,1.0,neutral or dissatisfied +1173,16687,Male,Loyal Customer,65,Personal Travel,Eco Plus,605,1,5,1,5,5,1,5,5,4,3,4,3,4,5,14,6.0,neutral or dissatisfied +1174,69974,Male,Loyal Customer,39,Business travel,Business,3637,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +1175,123377,Male,Loyal Customer,69,Personal Travel,Eco,644,2,4,2,2,5,2,5,5,3,5,5,5,5,5,25,17.0,neutral or dissatisfied +1176,9749,Male,Loyal Customer,55,Personal Travel,Eco,908,4,4,4,3,5,4,2,5,5,4,4,1,2,5,3,0.0,satisfied +1177,36878,Male,disloyal Customer,22,Business travel,Business,1182,0,0,0,5,1,0,1,1,1,3,3,1,1,1,0,0.0,satisfied +1178,56188,Female,Loyal Customer,12,Personal Travel,Eco,1569,2,4,2,4,4,2,4,4,1,4,2,3,3,4,0,0.0,neutral or dissatisfied +1179,117387,Female,Loyal Customer,26,Business travel,Eco,912,3,4,3,4,3,3,2,3,1,4,3,3,4,3,0,0.0,neutral or dissatisfied +1180,57805,Female,disloyal Customer,44,Business travel,Eco,1235,3,3,3,4,1,3,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +1181,109462,Male,Loyal Customer,38,Business travel,Business,3048,3,3,2,3,3,4,4,5,5,5,5,3,5,5,8,1.0,satisfied +1182,52980,Male,Loyal Customer,67,Business travel,Business,1208,3,3,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +1183,48052,Male,Loyal Customer,17,Personal Travel,Eco,677,2,5,2,4,5,2,4,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +1184,48042,Male,Loyal Customer,40,Business travel,Eco,896,1,2,2,2,1,1,1,1,2,4,3,1,4,1,36,25.0,neutral or dissatisfied +1185,81618,Female,Loyal Customer,63,Personal Travel,Eco Plus,334,1,3,2,3,5,4,3,1,1,2,4,1,1,2,17,0.0,neutral or dissatisfied +1186,80276,Female,disloyal Customer,22,Business travel,Eco,746,2,1,1,3,5,1,5,5,4,2,5,3,5,5,27,44.0,neutral or dissatisfied +1187,101631,Female,Loyal Customer,26,Personal Travel,Eco,1371,2,5,1,2,5,1,4,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +1188,4280,Male,Loyal Customer,35,Business travel,Eco,502,4,4,3,4,4,4,4,4,1,3,3,1,1,4,0,0.0,satisfied +1189,35632,Female,Loyal Customer,30,Business travel,Eco Plus,1047,4,2,2,2,4,4,4,4,4,2,4,1,1,4,0,0.0,satisfied +1190,54547,Male,Loyal Customer,60,Personal Travel,Eco,925,3,5,3,3,2,3,5,2,5,1,2,2,3,2,8,0.0,neutral or dissatisfied +1191,81291,Female,Loyal Customer,66,Personal Travel,Eco,1020,1,5,1,5,1,1,5,2,2,1,2,3,2,3,7,0.0,neutral or dissatisfied +1192,40654,Male,disloyal Customer,22,Business travel,Eco,599,0,0,0,1,5,0,5,5,3,3,5,3,4,5,6,0.0,satisfied +1193,113570,Female,Loyal Customer,32,Business travel,Business,3699,5,5,5,5,3,4,4,3,4,3,5,3,5,3,1,0.0,satisfied +1194,116585,Male,Loyal Customer,44,Business travel,Business,2745,2,2,2,2,3,5,5,4,4,4,4,3,4,3,98,84.0,satisfied +1195,22904,Male,Loyal Customer,60,Personal Travel,Eco Plus,151,4,4,4,4,3,4,3,3,5,5,5,4,4,3,19,4.0,neutral or dissatisfied +1196,44712,Male,Loyal Customer,26,Personal Travel,Eco,268,5,0,5,1,5,5,5,5,3,3,5,4,5,5,13,0.0,satisfied +1197,70897,Male,Loyal Customer,40,Business travel,Business,1721,4,4,4,4,3,5,4,4,4,4,4,3,4,5,12,9.0,satisfied +1198,98484,Female,disloyal Customer,34,Business travel,Business,402,4,4,4,2,2,4,2,2,4,3,5,3,5,2,2,0.0,neutral or dissatisfied +1199,13787,Male,Loyal Customer,52,Personal Travel,Eco,878,2,3,2,2,5,2,1,5,1,1,1,2,3,5,0,0.0,neutral or dissatisfied +1200,2395,Male,disloyal Customer,21,Business travel,Eco,641,3,0,3,3,1,3,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +1201,72992,Male,disloyal Customer,36,Business travel,Eco,696,3,3,3,4,1,3,4,1,4,1,1,2,2,1,25,24.0,neutral or dissatisfied +1202,46484,Male,Loyal Customer,54,Business travel,Eco,73,4,1,4,4,4,4,4,4,4,4,5,1,1,4,0,0.0,satisfied +1203,100300,Female,disloyal Customer,23,Business travel,Eco,1011,2,2,2,3,3,2,3,3,4,5,2,3,3,3,15,35.0,neutral or dissatisfied +1204,128704,Female,Loyal Customer,25,Business travel,Business,1464,3,3,3,3,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +1205,5183,Male,Loyal Customer,50,Business travel,Business,2977,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,5.0,satisfied +1206,48103,Female,disloyal Customer,42,Business travel,Eco,236,2,5,2,4,4,2,4,4,2,1,3,5,5,4,1,5.0,neutral or dissatisfied +1207,42586,Male,Loyal Customer,34,Business travel,Eco Plus,315,4,4,4,4,4,4,4,4,5,2,3,1,4,4,0,0.0,satisfied +1208,126730,Female,disloyal Customer,26,Business travel,Eco,1165,2,2,2,4,2,2,2,2,3,2,3,1,4,2,63,50.0,neutral or dissatisfied +1209,108384,Male,Loyal Customer,9,Personal Travel,Eco,1844,1,5,1,4,1,1,1,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +1210,6411,Male,Loyal Customer,62,Personal Travel,Eco,240,3,4,3,3,5,3,1,5,1,5,4,3,3,5,10,3.0,neutral or dissatisfied +1211,85645,Female,Loyal Customer,55,Business travel,Business,2804,5,5,5,5,4,4,4,5,5,5,4,3,5,4,0,0.0,satisfied +1212,79909,Male,disloyal Customer,26,Business travel,Eco,1035,3,3,3,2,1,3,1,1,1,3,2,4,3,1,29,13.0,neutral or dissatisfied +1213,34868,Male,Loyal Customer,63,Business travel,Eco,2248,5,2,2,2,5,5,5,5,2,3,4,3,5,5,14,11.0,satisfied +1214,45586,Female,Loyal Customer,39,Business travel,Eco,260,4,5,3,5,4,4,4,4,4,4,1,2,4,4,13,0.0,satisfied +1215,31080,Male,Loyal Customer,56,Business travel,Eco Plus,775,2,2,2,2,2,2,2,2,4,1,4,4,4,2,4,6.0,neutral or dissatisfied +1216,49890,Female,Loyal Customer,43,Business travel,Business,89,0,4,0,3,1,3,5,3,3,3,3,2,3,1,0,0.0,satisfied +1217,87948,Female,Loyal Customer,7,Personal Travel,Business,545,3,3,3,4,2,3,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +1218,46125,Male,Loyal Customer,28,Business travel,Business,2801,4,4,4,4,4,4,4,4,3,2,4,3,2,4,14,38.0,satisfied +1219,116340,Male,Loyal Customer,45,Personal Travel,Eco,308,2,4,2,4,3,2,3,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +1220,53751,Female,Loyal Customer,53,Business travel,Business,2003,5,5,5,5,3,4,5,4,4,4,4,3,4,4,50,21.0,satisfied +1221,106747,Female,Loyal Customer,39,Business travel,Business,3311,1,2,2,2,3,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +1222,113965,Female,disloyal Customer,28,Business travel,Eco,1750,2,2,2,3,2,2,5,2,2,1,3,3,4,2,20,22.0,neutral or dissatisfied +1223,112312,Male,disloyal Customer,20,Business travel,Business,853,5,0,5,1,2,5,2,2,4,4,4,5,4,2,8,0.0,satisfied +1224,30090,Male,Loyal Customer,7,Personal Travel,Eco,399,4,5,4,4,4,4,4,4,4,3,1,1,4,4,0,,neutral or dissatisfied +1225,102102,Female,Loyal Customer,59,Business travel,Business,258,2,2,2,2,2,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +1226,58114,Male,Loyal Customer,40,Personal Travel,Eco,589,1,5,2,1,1,2,1,1,3,5,4,3,5,1,27,12.0,neutral or dissatisfied +1227,38196,Female,Loyal Customer,38,Personal Travel,Eco,1185,3,3,3,3,1,3,1,1,3,2,3,1,3,1,56,54.0,neutral or dissatisfied +1228,45505,Male,Loyal Customer,54,Business travel,Eco Plus,674,3,1,1,1,3,3,3,3,2,3,4,2,3,3,9,7.0,neutral or dissatisfied +1229,15676,Male,Loyal Customer,52,Business travel,Eco,617,4,2,2,2,4,4,4,4,3,2,4,2,4,4,0,0.0,satisfied +1230,53222,Female,Loyal Customer,23,Business travel,Business,2486,2,2,2,2,5,5,5,5,4,1,3,1,2,5,0,1.0,satisfied +1231,11709,Male,Loyal Customer,39,Business travel,Business,2207,1,1,1,1,4,5,5,5,5,5,5,5,5,3,27,46.0,satisfied +1232,126578,Male,Loyal Customer,54,Personal Travel,Eco,1558,1,5,1,1,5,1,5,5,5,2,4,4,4,5,2,12.0,neutral or dissatisfied +1233,108717,Female,Loyal Customer,22,Personal Travel,Eco Plus,321,3,4,3,5,3,3,3,3,4,4,1,5,4,3,63,60.0,neutral or dissatisfied +1234,3603,Male,Loyal Customer,25,Personal Travel,Eco,999,2,5,2,2,2,2,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +1235,14432,Female,Loyal Customer,11,Personal Travel,Business,674,3,5,3,2,5,3,5,5,4,3,4,5,5,5,7,23.0,neutral or dissatisfied +1236,62166,Female,disloyal Customer,62,Business travel,Eco,912,2,2,2,2,2,2,5,2,1,3,2,4,3,2,88,53.0,neutral or dissatisfied +1237,62599,Male,Loyal Customer,38,Business travel,Eco,226,5,5,5,5,5,5,5,5,1,3,2,3,5,5,0,0.0,satisfied +1238,90908,Female,disloyal Customer,16,Business travel,Eco,581,1,1,1,3,2,1,2,2,2,2,3,4,3,2,2,0.0,neutral or dissatisfied +1239,124571,Male,Loyal Customer,60,Business travel,Business,3199,4,4,4,4,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +1240,77718,Female,Loyal Customer,41,Business travel,Eco,874,3,1,1,1,3,3,3,3,1,4,2,4,2,3,2,0.0,neutral or dissatisfied +1241,120043,Male,Loyal Customer,47,Business travel,Business,168,0,4,0,4,2,4,5,3,3,3,3,5,3,4,0,3.0,satisfied +1242,17861,Male,Loyal Customer,40,Business travel,Business,2512,4,4,4,4,4,4,1,5,5,5,5,4,5,4,44,30.0,satisfied +1243,19353,Female,disloyal Customer,37,Business travel,Eco,589,4,0,4,1,5,4,5,5,5,5,5,1,4,5,69,64.0,neutral or dissatisfied +1244,10040,Female,Loyal Customer,60,Business travel,Business,2702,5,5,5,5,2,5,5,5,5,5,5,3,5,5,13,5.0,satisfied +1245,22768,Male,Loyal Customer,36,Business travel,Business,3796,3,3,3,3,1,3,3,4,4,4,4,3,4,1,1,1.0,satisfied +1246,94685,Female,Loyal Customer,27,Business travel,Business,2251,2,2,2,2,5,5,5,5,4,5,5,4,5,5,0,0.0,satisfied +1247,67791,Female,Loyal Customer,40,Business travel,Eco,1242,4,3,3,3,4,3,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +1248,22732,Female,Loyal Customer,45,Business travel,Business,2311,4,4,4,4,4,2,3,5,5,5,5,5,5,3,0,0.0,satisfied +1249,82252,Male,Loyal Customer,48,Business travel,Business,1481,5,2,5,5,4,4,5,4,4,4,4,4,4,5,16,27.0,satisfied +1250,106307,Female,Loyal Customer,31,Business travel,Business,1909,1,1,1,1,5,5,5,5,5,4,5,5,4,5,9,8.0,satisfied +1251,84197,Female,disloyal Customer,25,Business travel,Business,432,3,0,3,4,4,3,4,4,4,2,4,3,4,4,3,5.0,neutral or dissatisfied +1252,32730,Male,Loyal Customer,58,Business travel,Eco,101,4,3,3,3,4,4,4,4,4,4,1,5,3,4,0,0.0,satisfied +1253,68234,Female,Loyal Customer,37,Business travel,Business,432,3,3,3,3,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +1254,117375,Male,Loyal Customer,51,Business travel,Business,1294,3,3,3,3,3,5,5,5,5,5,5,5,5,5,20,19.0,satisfied +1255,107259,Male,Loyal Customer,40,Business travel,Business,1655,5,4,5,5,3,5,4,3,3,4,3,3,3,5,8,1.0,satisfied +1256,31221,Male,Loyal Customer,32,Personal Travel,Eco,628,2,2,2,3,4,2,4,4,4,3,3,4,4,4,20,1.0,neutral or dissatisfied +1257,87975,Male,Loyal Customer,45,Business travel,Business,3246,1,1,1,1,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +1258,99142,Female,Loyal Customer,51,Business travel,Business,3733,2,2,5,2,2,4,5,5,5,5,5,4,5,4,3,2.0,satisfied +1259,88011,Male,Loyal Customer,55,Business travel,Business,3208,4,4,4,4,5,5,5,4,4,4,4,3,4,4,32,32.0,satisfied +1260,88606,Female,Loyal Customer,10,Personal Travel,Eco,271,2,3,2,4,5,2,5,5,1,1,4,2,3,5,46,38.0,neutral or dissatisfied +1261,78053,Male,Loyal Customer,15,Personal Travel,Eco,332,1,4,1,1,3,1,1,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +1262,69423,Female,disloyal Customer,37,Business travel,Eco,696,2,2,2,3,3,2,3,3,3,2,1,3,4,3,0,0.0,neutral or dissatisfied +1263,107108,Male,Loyal Customer,33,Business travel,Business,1806,3,3,3,3,4,4,4,4,3,5,5,4,5,4,41,29.0,satisfied +1264,128133,Female,Loyal Customer,23,Personal Travel,Eco Plus,1587,2,5,2,4,1,2,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +1265,42904,Female,disloyal Customer,25,Business travel,Eco,200,1,0,1,1,5,1,5,5,4,5,3,1,2,5,0,0.0,neutral or dissatisfied +1266,107409,Male,Loyal Customer,48,Business travel,Eco,725,3,2,2,2,3,3,3,3,2,4,3,4,4,3,3,0.0,neutral or dissatisfied +1267,12680,Male,Loyal Customer,45,Business travel,Eco,803,4,3,4,4,4,4,4,4,4,3,3,4,4,4,66,78.0,neutral or dissatisfied +1268,16259,Male,Loyal Customer,33,Business travel,Business,748,5,5,5,5,3,3,3,3,2,2,3,5,2,3,88,73.0,satisfied +1269,5928,Male,Loyal Customer,20,Personal Travel,Eco,108,2,5,2,3,4,2,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +1270,58975,Male,Loyal Customer,45,Business travel,Business,1726,1,1,3,1,4,5,4,5,5,5,5,5,5,4,24,0.0,satisfied +1271,53769,Male,Loyal Customer,39,Personal Travel,Eco,1195,3,4,3,3,2,3,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +1272,761,Male,Loyal Customer,48,Business travel,Business,3447,0,0,0,3,2,4,5,5,5,5,2,4,5,3,0,18.0,satisfied +1273,103941,Female,Loyal Customer,18,Business travel,Business,533,3,4,4,4,3,3,3,3,3,3,3,1,4,3,0,12.0,neutral or dissatisfied +1274,70818,Female,Loyal Customer,26,Personal Travel,Eco,624,4,4,4,1,2,4,2,2,4,4,5,5,5,2,0,0.0,satisfied +1275,106043,Female,Loyal Customer,53,Business travel,Business,452,2,3,3,3,3,4,3,2,2,2,2,3,2,4,24,13.0,neutral or dissatisfied +1276,23641,Female,Loyal Customer,25,Business travel,Eco Plus,911,4,3,3,3,4,4,3,4,1,1,2,2,4,4,0,19.0,satisfied +1277,28450,Male,disloyal Customer,29,Business travel,Eco,1395,3,3,3,4,3,3,3,3,1,3,3,3,2,3,0,0.0,neutral or dissatisfied +1278,41632,Female,Loyal Customer,43,Personal Travel,Eco,438,5,3,5,4,3,3,4,1,1,5,1,2,1,4,0,0.0,satisfied +1279,37388,Female,Loyal Customer,32,Business travel,Business,3880,3,3,3,3,5,5,5,3,2,5,1,5,2,5,146,171.0,satisfied +1280,78571,Female,Loyal Customer,31,Business travel,Business,1977,3,3,3,3,5,5,5,5,4,3,5,4,4,5,3,0.0,satisfied +1281,101927,Female,Loyal Customer,45,Business travel,Business,628,4,4,4,4,2,5,5,4,4,4,4,5,4,3,55,49.0,satisfied +1282,40688,Female,Loyal Customer,45,Business travel,Eco,584,5,5,5,5,4,5,1,5,5,5,5,1,5,2,0,0.0,satisfied +1283,2165,Female,Loyal Customer,48,Business travel,Business,624,3,3,3,3,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +1284,5901,Female,Loyal Customer,61,Business travel,Business,2407,1,1,1,1,5,1,1,3,3,3,1,1,3,1,11,4.0,neutral or dissatisfied +1285,47292,Female,Loyal Customer,24,Business travel,Business,3903,2,2,2,2,4,4,4,4,2,1,1,1,5,4,0,6.0,satisfied +1286,57557,Female,disloyal Customer,31,Business travel,Business,1597,3,3,3,4,4,3,4,4,4,4,3,3,4,4,22,0.0,neutral or dissatisfied +1287,102271,Male,Loyal Customer,49,Business travel,Business,1834,1,1,1,1,2,4,5,5,5,5,5,3,5,4,39,37.0,satisfied +1288,99450,Female,Loyal Customer,25,Business travel,Business,283,5,5,3,5,5,5,5,5,3,4,5,4,4,5,20,16.0,satisfied +1289,69575,Female,Loyal Customer,47,Business travel,Business,3534,3,4,4,4,3,3,3,2,2,3,4,3,1,3,23,0.0,neutral or dissatisfied +1290,56224,Female,Loyal Customer,18,Business travel,Business,1608,1,1,1,1,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +1291,8510,Male,Loyal Customer,37,Business travel,Business,1923,4,4,3,4,4,4,4,4,4,4,4,4,4,3,21,16.0,neutral or dissatisfied +1292,75812,Male,Loyal Customer,45,Business travel,Eco Plus,413,2,5,5,5,2,2,2,2,2,3,3,1,4,2,0,0.0,neutral or dissatisfied +1293,6125,Female,Loyal Customer,38,Business travel,Business,491,1,1,3,1,3,4,4,4,4,4,4,4,4,4,74,65.0,satisfied +1294,5475,Female,Loyal Customer,68,Personal Travel,Eco,265,3,3,0,3,4,3,3,5,5,0,5,4,5,4,0,0.0,neutral or dissatisfied +1295,114113,Male,Loyal Customer,50,Business travel,Business,846,2,2,2,2,2,5,4,3,3,2,3,5,3,3,0,0.0,satisfied +1296,56159,Female,disloyal Customer,14,Business travel,Business,1400,5,4,5,1,3,5,3,3,3,5,4,5,5,3,0,0.0,satisfied +1297,119742,Female,Loyal Customer,35,Personal Travel,Eco,1496,3,1,3,4,3,3,3,3,4,3,3,4,4,3,0,0.0,neutral or dissatisfied +1298,114045,Male,Loyal Customer,47,Business travel,Business,2935,2,2,2,2,2,5,5,3,3,3,3,3,3,3,6,0.0,satisfied +1299,56168,Male,disloyal Customer,25,Business travel,Eco,1569,2,2,2,3,3,2,3,3,1,1,3,2,2,3,72,124.0,neutral or dissatisfied +1300,57258,Male,disloyal Customer,26,Business travel,Business,628,2,2,2,2,1,2,1,1,3,4,5,3,4,1,0,0.0,neutral or dissatisfied +1301,62152,Female,Loyal Customer,72,Business travel,Business,2454,4,3,2,3,5,1,2,4,4,3,4,2,4,2,2,6.0,neutral or dissatisfied +1302,31055,Male,Loyal Customer,38,Business travel,Business,641,3,5,5,5,5,3,2,3,3,3,3,2,3,1,44,54.0,neutral or dissatisfied +1303,8777,Male,Loyal Customer,44,Business travel,Business,552,4,4,4,4,2,5,5,3,3,3,3,4,3,4,5,11.0,satisfied +1304,69746,Female,disloyal Customer,44,Business travel,Business,1085,2,2,2,4,2,2,5,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +1305,118637,Female,disloyal Customer,26,Business travel,Eco,646,1,3,1,4,3,1,3,3,3,5,3,4,4,3,16,20.0,neutral or dissatisfied +1306,21097,Female,disloyal Customer,23,Business travel,Eco,106,0,0,0,2,2,0,2,2,1,5,1,1,5,2,0,0.0,satisfied +1307,64301,Female,Loyal Customer,30,Business travel,Business,1172,3,3,3,3,5,5,5,5,5,4,5,3,5,5,7,0.0,satisfied +1308,28009,Female,Loyal Customer,39,Business travel,Business,763,3,3,3,3,2,1,3,4,4,4,4,5,4,1,0,0.0,satisfied +1309,28711,Male,Loyal Customer,51,Business travel,Business,2717,5,5,5,5,5,5,5,3,2,4,1,5,1,5,0,3.0,satisfied +1310,126953,Female,Loyal Customer,43,Business travel,Business,370,4,4,4,4,5,5,4,2,2,2,2,5,2,4,16,13.0,satisfied +1311,44049,Male,Loyal Customer,66,Personal Travel,Eco,237,4,4,4,1,3,4,3,3,5,3,5,4,4,3,0,1.0,neutral or dissatisfied +1312,67758,Female,Loyal Customer,31,Business travel,Eco,1242,3,5,5,5,3,3,3,3,1,4,4,2,4,3,0,0.0,neutral or dissatisfied +1313,49081,Male,disloyal Customer,42,Business travel,Eco,262,2,0,3,2,2,3,2,2,3,3,1,3,4,2,0,3.0,neutral or dissatisfied +1314,77706,Female,Loyal Customer,22,Business travel,Eco,696,2,5,5,5,2,1,2,2,4,1,3,1,4,2,2,12.0,neutral or dissatisfied +1315,28237,Male,Loyal Customer,41,Business travel,Business,2034,4,4,2,4,5,1,4,4,4,4,4,3,4,2,0,0.0,satisfied +1316,59645,Female,Loyal Customer,21,Business travel,Business,2045,3,5,5,5,3,3,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +1317,87248,Male,Loyal Customer,58,Business travel,Business,3463,1,1,1,1,2,4,4,5,5,5,5,4,5,5,118,109.0,satisfied +1318,20088,Female,Loyal Customer,55,Business travel,Business,2755,5,5,5,5,2,5,5,4,4,4,4,5,4,5,22,23.0,satisfied +1319,69217,Female,Loyal Customer,58,Business travel,Business,2686,3,3,3,3,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +1320,88471,Male,Loyal Customer,39,Business travel,Business,2275,5,5,5,5,3,2,3,4,4,4,4,1,4,2,0,0.0,satisfied +1321,104153,Male,Loyal Customer,38,Business travel,Business,2982,5,5,5,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +1322,24702,Male,Loyal Customer,35,Business travel,Eco,397,2,1,1,1,2,2,2,2,1,4,4,2,3,2,0,6.0,neutral or dissatisfied +1323,19174,Male,Loyal Customer,38,Business travel,Business,2097,3,3,3,3,2,4,2,4,4,4,4,4,4,4,40,27.0,satisfied +1324,118513,Female,Loyal Customer,43,Business travel,Business,3108,2,2,2,2,2,2,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +1325,88757,Female,Loyal Customer,46,Business travel,Business,271,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +1326,1919,Female,Loyal Customer,50,Business travel,Business,2510,1,1,1,1,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +1327,28099,Female,Loyal Customer,39,Business travel,Business,3019,2,2,2,2,5,3,3,5,5,5,5,1,5,4,10,0.0,satisfied +1328,82508,Male,disloyal Customer,26,Business travel,Business,1749,4,4,4,4,4,4,4,4,3,5,3,4,5,4,0,0.0,satisfied +1329,22647,Female,Loyal Customer,60,Business travel,Eco Plus,300,5,5,2,5,5,4,1,3,3,5,3,5,3,1,27,22.0,satisfied +1330,121227,Male,Loyal Customer,37,Business travel,Business,2075,1,1,3,1,4,3,4,4,4,3,4,4,4,3,38,34.0,satisfied +1331,83513,Male,Loyal Customer,19,Personal Travel,Eco,946,1,4,1,4,4,1,4,4,3,3,3,4,3,4,3,0.0,neutral or dissatisfied +1332,120954,Female,disloyal Customer,24,Business travel,Eco,1013,1,1,1,4,2,1,4,2,3,5,3,4,3,2,54,56.0,neutral or dissatisfied +1333,53450,Male,Loyal Customer,22,Business travel,Business,2288,4,4,4,4,2,2,2,4,5,4,2,2,2,2,0,7.0,satisfied +1334,20591,Male,Loyal Customer,54,Business travel,Eco Plus,533,2,2,2,2,2,2,2,2,3,3,4,3,3,2,0,3.0,neutral or dissatisfied +1335,76388,Female,disloyal Customer,26,Business travel,Eco,531,3,5,3,2,4,3,4,4,2,5,3,1,5,4,10,0.0,neutral or dissatisfied +1336,111033,Female,Loyal Customer,39,Business travel,Business,2976,2,2,2,2,5,5,4,4,4,4,4,4,4,4,60,58.0,satisfied +1337,3226,Male,Loyal Customer,58,Business travel,Business,479,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +1338,15268,Female,Loyal Customer,60,Business travel,Eco,501,5,1,2,1,3,1,4,3,3,5,3,1,3,1,0,0.0,satisfied +1339,89816,Male,Loyal Customer,42,Business travel,Business,3215,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +1340,34907,Female,disloyal Customer,24,Business travel,Eco,187,3,4,3,2,3,3,3,3,1,3,4,2,2,3,0,0.0,neutral or dissatisfied +1341,81556,Male,disloyal Customer,40,Business travel,Eco,936,3,3,3,3,4,3,1,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +1342,49334,Male,Loyal Customer,50,Business travel,Eco,372,5,4,4,4,5,5,5,5,5,2,1,5,2,5,0,0.0,satisfied +1343,85780,Female,Loyal Customer,39,Business travel,Business,620,1,1,1,1,5,4,5,5,5,5,5,3,5,4,5,0.0,satisfied +1344,11890,Female,disloyal Customer,24,Business travel,Eco,744,4,4,4,1,2,4,5,2,4,4,4,5,4,2,43,37.0,satisfied +1345,113957,Female,Loyal Customer,46,Business travel,Business,1790,4,4,4,4,4,3,5,5,5,5,5,5,5,4,26,4.0,satisfied +1346,56295,Male,Loyal Customer,67,Personal Travel,Eco,2227,2,5,2,4,1,2,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +1347,99126,Female,Loyal Customer,35,Personal Travel,Eco,419,2,5,2,2,5,2,5,5,3,2,1,1,1,5,43,33.0,neutral or dissatisfied +1348,67172,Male,Loyal Customer,50,Personal Travel,Eco,929,3,4,3,3,1,3,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +1349,75117,Female,Loyal Customer,34,Business travel,Business,1846,4,4,5,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +1350,32544,Male,Loyal Customer,41,Business travel,Eco,163,5,4,4,4,5,5,5,5,2,2,5,4,5,5,0,0.0,satisfied +1351,104741,Female,Loyal Customer,42,Business travel,Business,3515,4,4,4,4,5,5,5,5,5,5,5,5,5,5,15,2.0,satisfied +1352,76294,Male,Loyal Customer,42,Business travel,Business,2182,1,1,1,1,5,3,5,5,5,5,5,5,5,3,8,0.0,satisfied +1353,3478,Female,Loyal Customer,20,Personal Travel,Business,1080,5,4,5,4,4,5,4,4,5,2,5,4,5,4,52,38.0,satisfied +1354,119521,Female,Loyal Customer,58,Business travel,Eco,499,5,5,5,5,4,1,5,5,5,5,5,4,5,5,0,7.0,satisfied +1355,90907,Female,Loyal Customer,29,Business travel,Business,3897,3,4,4,4,3,3,3,3,3,2,3,2,4,3,0,12.0,neutral or dissatisfied +1356,128925,Female,disloyal Customer,32,Business travel,Eco,414,2,1,2,3,3,2,3,3,1,2,4,4,4,3,34,23.0,neutral or dissatisfied +1357,110943,Male,Loyal Customer,7,Personal Travel,Eco,404,4,2,3,4,3,3,3,3,2,3,4,2,3,3,15,0.0,neutral or dissatisfied +1358,129730,Female,Loyal Customer,48,Business travel,Business,3801,4,4,2,4,5,3,2,4,4,4,4,3,4,2,100,94.0,neutral or dissatisfied +1359,31263,Female,disloyal Customer,45,Business travel,Eco,770,3,3,3,3,5,3,5,5,4,1,2,3,5,5,0,0.0,neutral or dissatisfied +1360,59917,Male,Loyal Customer,27,Business travel,Business,2845,3,5,5,5,3,3,3,3,4,1,4,2,4,3,130,115.0,neutral or dissatisfied +1361,6398,Female,Loyal Customer,10,Personal Travel,Eco,296,1,5,1,4,3,1,3,3,5,5,4,5,4,3,0,21.0,neutral or dissatisfied +1362,87138,Male,Loyal Customer,28,Business travel,Eco Plus,594,2,4,4,4,2,2,2,2,4,1,4,4,4,2,5,87.0,neutral or dissatisfied +1363,37914,Female,Loyal Customer,66,Personal Travel,Eco,1023,4,4,4,3,2,5,3,3,3,4,3,1,3,2,1,3.0,neutral or dissatisfied +1364,95718,Male,Loyal Customer,46,Business travel,Business,3404,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +1365,1799,Male,Loyal Customer,59,Business travel,Business,2111,5,5,5,5,3,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +1366,73656,Male,Loyal Customer,52,Business travel,Business,2467,3,5,5,5,3,3,4,4,4,4,3,2,4,1,43,36.0,neutral or dissatisfied +1367,24943,Male,Loyal Customer,33,Business travel,Business,1747,2,2,2,2,2,2,2,2,4,1,5,3,1,2,25,20.0,satisfied +1368,11549,Male,Loyal Customer,57,Business travel,Business,772,2,2,2,2,4,4,4,3,2,4,5,4,5,4,222,221.0,satisfied +1369,82667,Female,Loyal Customer,14,Personal Travel,Eco,120,3,4,3,1,2,3,1,2,1,3,1,1,4,2,0,0.0,neutral or dissatisfied +1370,1097,Male,Loyal Customer,13,Personal Travel,Eco,164,2,5,2,3,3,2,3,3,3,4,5,3,4,3,3,0.0,neutral or dissatisfied +1371,99288,Male,disloyal Customer,57,Personal Travel,Eco,833,1,4,1,1,5,1,5,5,5,2,4,5,5,5,87,75.0,neutral or dissatisfied +1372,82724,Male,Loyal Customer,60,Business travel,Business,2430,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +1373,26258,Female,Loyal Customer,61,Personal Travel,Eco Plus,581,1,4,1,3,2,4,5,3,3,1,1,5,3,3,44,48.0,neutral or dissatisfied +1374,75160,Male,Loyal Customer,58,Business travel,Business,1744,3,3,3,3,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +1375,66685,Male,Loyal Customer,48,Business travel,Business,2434,2,1,1,1,4,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +1376,28777,Male,Loyal Customer,48,Business travel,Business,605,1,1,1,1,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +1377,102597,Female,Loyal Customer,66,Personal Travel,Eco Plus,226,5,5,5,1,4,5,4,4,4,5,4,4,4,3,12,5.0,satisfied +1378,82172,Male,Loyal Customer,57,Personal Travel,Eco,237,2,5,2,1,3,2,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +1379,73259,Male,Loyal Customer,8,Personal Travel,Eco,675,1,2,1,4,1,1,1,1,2,3,4,4,4,1,0,0.0,neutral or dissatisfied +1380,47873,Female,Loyal Customer,31,Business travel,Eco,462,2,2,2,2,2,2,2,2,4,3,3,3,3,2,11,27.0,neutral or dissatisfied +1381,65196,Male,Loyal Customer,25,Personal Travel,Eco,224,3,2,3,3,5,3,5,5,4,5,4,4,4,5,4,4.0,neutral or dissatisfied +1382,25415,Male,Loyal Customer,50,Personal Travel,Eco,990,3,4,3,3,5,3,5,5,3,3,4,4,4,5,2,0.0,neutral or dissatisfied +1383,37302,Female,Loyal Customer,27,Business travel,Eco,1074,1,1,1,1,1,2,1,1,2,2,1,3,3,1,0,0.0,neutral or dissatisfied +1384,96254,Female,Loyal Customer,23,Personal Travel,Eco,687,5,4,5,3,1,5,1,1,5,4,4,5,5,1,0,0.0,satisfied +1385,3029,Male,Loyal Customer,29,Personal Travel,Eco,987,1,5,1,2,4,1,1,4,5,1,2,2,3,4,0,3.0,neutral or dissatisfied +1386,78149,Male,disloyal Customer,26,Business travel,Business,192,3,5,3,4,4,3,4,4,5,2,4,4,4,4,8,8.0,neutral or dissatisfied +1387,120152,Female,Loyal Customer,57,Business travel,Business,2378,4,4,1,4,5,5,5,4,4,4,5,5,4,5,28,40.0,satisfied +1388,128690,Male,Loyal Customer,57,Business travel,Eco Plus,2442,3,1,5,1,3,3,3,2,3,2,4,3,2,3,6,0.0,neutral or dissatisfied +1389,32172,Female,Loyal Customer,46,Business travel,Eco,101,5,3,3,3,1,1,5,5,5,5,5,1,5,5,0,0.0,satisfied +1390,55884,Male,Loyal Customer,58,Business travel,Business,3810,3,3,3,3,5,5,5,5,4,4,4,5,5,5,163,160.0,satisfied +1391,40279,Female,Loyal Customer,29,Personal Travel,Eco,358,4,4,4,4,5,4,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +1392,113444,Male,Loyal Customer,23,Business travel,Business,258,1,3,3,3,1,1,1,1,3,3,4,1,4,1,10,6.0,neutral or dissatisfied +1393,4711,Female,disloyal Customer,21,Business travel,Business,364,2,2,2,4,3,2,3,3,2,1,4,2,3,3,0,8.0,neutral or dissatisfied +1394,38762,Female,Loyal Customer,41,Business travel,Business,1603,5,5,5,5,1,5,2,5,5,5,5,3,5,1,0,0.0,satisfied +1395,8886,Male,Loyal Customer,46,Personal Travel,Eco,622,4,4,4,3,5,4,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +1396,4592,Female,disloyal Customer,26,Business travel,Eco,416,1,4,1,3,4,1,4,4,1,3,2,1,1,4,0,0.0,neutral or dissatisfied +1397,1769,Male,Loyal Customer,40,Business travel,Business,408,4,4,4,4,3,4,5,3,3,4,3,3,3,5,0,2.0,satisfied +1398,84160,Male,Loyal Customer,58,Business travel,Business,1742,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +1399,113068,Female,Loyal Customer,62,Business travel,Eco,543,1,0,0,2,3,2,3,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +1400,30358,Male,Loyal Customer,49,Business travel,Eco,641,5,1,1,1,5,5,5,5,2,1,3,2,3,5,37,34.0,satisfied +1401,79354,Male,Loyal Customer,48,Personal Travel,Eco,1020,3,5,3,4,4,3,4,4,2,4,4,2,5,4,0,0.0,neutral or dissatisfied +1402,61539,Female,Loyal Customer,14,Personal Travel,Eco,2358,1,4,1,5,3,1,3,3,4,4,3,3,5,3,0,0.0,neutral or dissatisfied +1403,3755,Male,Loyal Customer,66,Personal Travel,Eco Plus,544,1,3,1,3,1,1,1,3,1,3,2,1,1,1,205,240.0,neutral or dissatisfied +1404,99310,Male,Loyal Customer,37,Business travel,Eco,448,2,3,5,3,2,2,2,2,2,2,2,1,3,2,0,0.0,neutral or dissatisfied +1405,90659,Male,Loyal Customer,41,Business travel,Business,646,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +1406,127382,Female,Loyal Customer,46,Business travel,Business,868,2,2,2,2,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +1407,46847,Female,disloyal Customer,27,Business travel,Eco,850,1,1,1,4,2,1,2,2,2,2,5,2,1,2,15,0.0,neutral or dissatisfied +1408,124634,Male,Loyal Customer,10,Personal Travel,Eco,1671,2,1,2,4,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +1409,46253,Male,Loyal Customer,64,Personal Travel,Eco,752,2,4,2,4,5,2,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +1410,16122,Female,Loyal Customer,58,Business travel,Eco,725,3,1,1,1,3,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +1411,126727,Female,Loyal Customer,56,Business travel,Business,2521,5,5,5,5,4,3,5,4,4,5,4,3,4,5,0,0.0,satisfied +1412,1754,Female,Loyal Customer,57,Business travel,Business,364,5,4,5,5,4,5,5,5,5,5,5,3,5,4,7,17.0,satisfied +1413,3384,Male,Loyal Customer,41,Business travel,Business,315,2,5,5,5,2,2,2,1,2,3,2,2,2,2,275,248.0,neutral or dissatisfied +1414,22289,Male,disloyal Customer,21,Business travel,Eco,208,1,5,1,3,5,1,5,5,1,1,4,2,4,5,0,0.0,neutral or dissatisfied +1415,98857,Male,Loyal Customer,31,Business travel,Eco,1751,3,5,5,5,3,3,3,3,4,3,2,1,3,3,0,0.0,neutral or dissatisfied +1416,87655,Female,Loyal Customer,59,Business travel,Business,591,5,5,5,5,3,4,5,3,3,3,3,3,3,4,1,5.0,satisfied +1417,124021,Male,Loyal Customer,44,Personal Travel,Eco,184,3,5,3,3,2,3,2,2,5,5,5,5,4,2,0,1.0,neutral or dissatisfied +1418,56195,Female,Loyal Customer,65,Personal Travel,Eco,1569,1,5,1,1,5,5,4,3,3,1,3,4,3,4,0,16.0,neutral or dissatisfied +1419,49827,Female,Loyal Customer,16,Business travel,Eco,262,1,2,2,2,1,1,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +1420,123651,Female,disloyal Customer,22,Business travel,Eco,214,1,1,1,4,4,1,5,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +1421,101143,Female,disloyal Customer,41,Business travel,Business,1235,3,3,3,1,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +1422,38685,Female,Loyal Customer,35,Business travel,Eco Plus,2588,4,3,3,3,4,4,4,4,5,3,4,2,2,4,0,0.0,satisfied +1423,747,Male,Loyal Customer,58,Business travel,Business,1834,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +1424,73934,Female,Loyal Customer,42,Business travel,Eco,2342,2,2,5,2,5,4,4,2,2,2,2,2,2,2,8,0.0,neutral or dissatisfied +1425,83816,Male,Loyal Customer,45,Business travel,Business,425,1,1,1,1,4,4,5,4,4,4,4,3,4,5,2,1.0,satisfied +1426,111415,Male,Loyal Customer,27,Personal Travel,Eco,1671,2,2,2,3,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +1427,21222,Female,Loyal Customer,49,Personal Travel,Eco,192,2,5,2,3,4,4,4,2,2,2,3,5,2,3,0,0.0,neutral or dissatisfied +1428,34485,Female,Loyal Customer,49,Business travel,Eco Plus,266,4,2,2,2,4,3,5,4,4,4,4,3,4,1,8,7.0,satisfied +1429,68436,Female,Loyal Customer,38,Business travel,Business,1045,5,5,5,5,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +1430,24992,Female,Loyal Customer,51,Business travel,Business,2607,5,5,5,5,3,3,3,4,4,4,4,2,4,1,0,0.0,satisfied +1431,111889,Female,Loyal Customer,41,Business travel,Business,1650,1,1,1,1,5,3,4,1,1,2,1,4,1,2,37,44.0,neutral or dissatisfied +1432,32063,Male,disloyal Customer,23,Business travel,Eco,102,3,0,3,1,5,3,5,5,5,2,5,4,4,5,5,5.0,neutral or dissatisfied +1433,85526,Female,Loyal Customer,57,Business travel,Business,1919,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +1434,99328,Male,Loyal Customer,44,Personal Travel,Eco,448,1,5,3,4,4,3,4,4,3,3,4,4,2,4,52,54.0,neutral or dissatisfied +1435,110853,Female,Loyal Customer,56,Business travel,Business,3767,4,4,4,4,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +1436,75309,Female,Loyal Customer,53,Business travel,Business,2504,2,2,2,2,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +1437,33223,Female,disloyal Customer,29,Business travel,Eco Plus,201,2,2,2,1,5,2,4,5,5,4,5,3,3,5,0,0.0,neutral or dissatisfied +1438,84682,Female,disloyal Customer,59,Business travel,Eco,682,3,3,3,1,2,3,2,2,3,5,1,1,2,2,0,4.0,neutral or dissatisfied +1439,117534,Female,Loyal Customer,49,Business travel,Business,1623,1,1,1,1,3,4,4,2,2,2,2,4,2,3,60,52.0,satisfied +1440,86837,Male,disloyal Customer,30,Business travel,Eco,484,2,0,3,5,4,3,4,4,1,1,3,3,5,4,0,0.0,neutral or dissatisfied +1441,88319,Female,Loyal Customer,43,Business travel,Business,2680,1,1,1,1,4,4,4,4,4,4,4,5,4,5,0,1.0,satisfied +1442,45993,Female,disloyal Customer,25,Business travel,Eco,483,4,4,4,4,3,4,3,3,4,2,4,4,3,3,0,5.0,neutral or dissatisfied +1443,44867,Female,Loyal Customer,36,Business travel,Business,3151,4,4,4,4,5,4,4,4,4,4,4,1,4,2,12,7.0,satisfied +1444,123906,Male,Loyal Customer,36,Personal Travel,Eco,603,2,4,2,5,3,2,3,3,5,4,5,4,4,3,0,0.0,neutral or dissatisfied +1445,95175,Male,Loyal Customer,56,Personal Travel,Eco,562,4,4,4,2,5,4,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +1446,50039,Male,Loyal Customer,26,Business travel,Business,308,4,3,3,3,4,4,4,4,3,2,3,1,4,4,0,27.0,neutral or dissatisfied +1447,2537,Female,Loyal Customer,35,Business travel,Business,181,0,4,0,4,2,4,4,4,4,4,4,5,4,3,6,14.0,satisfied +1448,62051,Male,Loyal Customer,51,Personal Travel,Eco,2475,2,3,2,2,1,2,1,1,4,3,4,1,3,1,0,0.0,neutral or dissatisfied +1449,66913,Female,Loyal Customer,29,Business travel,Business,3170,4,4,4,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +1450,67653,Female,Loyal Customer,44,Business travel,Business,2267,3,3,3,3,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +1451,5437,Female,Loyal Customer,38,Business travel,Business,1668,5,4,5,5,3,5,4,5,5,5,5,5,5,3,23,12.0,satisfied +1452,114848,Female,Loyal Customer,46,Business travel,Business,417,5,5,5,5,4,4,5,5,5,5,5,3,5,4,18,19.0,satisfied +1453,32866,Male,Loyal Customer,63,Personal Travel,Eco,163,4,4,4,5,3,4,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +1454,27601,Female,Loyal Customer,50,Personal Travel,Eco,679,2,1,2,4,1,4,3,2,2,2,1,1,2,3,0,0.0,neutral or dissatisfied +1455,850,Female,Loyal Customer,54,Business travel,Business,354,3,5,5,5,2,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +1456,73034,Male,Loyal Customer,17,Personal Travel,Eco,1089,3,5,3,4,2,3,2,2,3,2,1,3,4,2,0,4.0,neutral or dissatisfied +1457,119359,Male,Loyal Customer,53,Personal Travel,Eco,2089,1,1,1,4,5,1,5,5,4,5,2,3,3,5,4,9.0,neutral or dissatisfied +1458,107819,Female,Loyal Customer,53,Business travel,Eco,349,4,3,3,3,1,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +1459,98879,Male,disloyal Customer,37,Business travel,Eco,591,3,3,3,3,1,3,1,1,4,2,4,4,3,1,44,62.0,neutral or dissatisfied +1460,115334,Male,disloyal Customer,52,Business travel,Eco,480,1,2,1,2,3,1,3,3,4,2,2,3,2,3,0,0.0,neutral or dissatisfied +1461,1415,Male,Loyal Customer,28,Personal Travel,Eco Plus,164,1,1,1,3,1,1,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +1462,39685,Female,Loyal Customer,45,Business travel,Eco Plus,534,1,2,2,2,4,3,4,1,1,1,1,1,1,2,0,9.0,neutral or dissatisfied +1463,35737,Male,Loyal Customer,29,Business travel,Business,2153,1,1,4,1,5,5,5,5,4,3,5,5,4,5,25,22.0,satisfied +1464,107533,Female,Loyal Customer,44,Business travel,Business,1521,2,1,2,2,5,4,4,4,4,4,4,5,4,4,19,42.0,satisfied +1465,14244,Female,Loyal Customer,34,Business travel,Business,2974,4,2,4,4,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +1466,120273,Female,disloyal Customer,46,Business travel,Business,1576,4,4,4,4,4,5,5,5,3,4,4,5,4,5,167,139.0,satisfied +1467,73725,Male,disloyal Customer,15,Business travel,Eco,204,5,3,5,3,5,5,5,5,5,3,2,5,2,5,0,0.0,satisfied +1468,53440,Female,Loyal Customer,27,Business travel,Eco,2419,4,2,2,2,4,5,4,4,2,1,3,2,5,4,0,0.0,satisfied +1469,12607,Female,Loyal Customer,21,Personal Travel,Eco,542,2,4,2,4,2,2,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +1470,91384,Female,disloyal Customer,41,Business travel,Business,743,3,3,3,3,4,3,4,4,5,3,4,3,4,4,2,1.0,satisfied +1471,10149,Male,Loyal Customer,59,Personal Travel,Eco,1157,3,5,3,4,3,3,3,3,3,3,3,5,5,3,1,0.0,neutral or dissatisfied +1472,103826,Female,disloyal Customer,27,Business travel,Eco,1056,2,2,2,3,1,2,1,1,1,5,4,2,4,1,24,15.0,neutral or dissatisfied +1473,69047,Male,Loyal Customer,33,Business travel,Business,1389,2,2,2,2,5,5,5,5,4,5,5,4,4,5,0,0.0,satisfied +1474,127135,Male,Loyal Customer,32,Personal Travel,Eco,646,4,2,4,3,1,4,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +1475,54848,Female,disloyal Customer,24,Business travel,Eco,934,4,4,4,2,5,4,5,5,5,2,4,3,5,5,0,0.0,satisfied +1476,6384,Female,disloyal Customer,58,Business travel,Eco,315,4,1,4,2,1,4,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +1477,40509,Female,Loyal Customer,56,Personal Travel,Eco,175,3,1,3,4,3,4,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +1478,88347,Male,Loyal Customer,46,Business travel,Business,1524,1,1,1,1,4,4,4,5,5,5,5,4,5,4,1,0.0,satisfied +1479,56364,Male,Loyal Customer,24,Personal Travel,Eco,200,4,5,4,2,1,4,1,1,5,2,4,4,4,1,0,0.0,satisfied +1480,107766,Female,Loyal Customer,28,Personal Travel,Eco,405,3,5,3,1,3,3,3,3,3,3,4,4,5,3,53,58.0,neutral or dissatisfied +1481,12727,Male,disloyal Customer,16,Business travel,Eco,721,2,2,2,4,3,2,3,3,1,3,3,4,4,3,0,12.0,neutral or dissatisfied +1482,47868,Male,Loyal Customer,56,Business travel,Eco,550,3,2,3,3,2,3,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +1483,12501,Female,disloyal Customer,28,Business travel,Eco Plus,190,3,3,3,4,3,1,1,4,5,3,4,1,1,1,142,129.0,neutral or dissatisfied +1484,108950,Male,disloyal Customer,23,Business travel,Business,542,5,0,5,3,2,0,2,2,5,5,4,5,5,2,24,18.0,satisfied +1485,92388,Male,Loyal Customer,59,Business travel,Business,2139,1,1,1,1,4,5,5,4,4,5,4,3,4,5,0,8.0,satisfied +1486,41423,Male,Loyal Customer,65,Personal Travel,Eco,641,3,4,3,3,1,3,1,1,4,3,4,5,4,1,15,16.0,neutral or dissatisfied +1487,125872,Male,Loyal Customer,34,Business travel,Eco,993,5,5,3,5,5,5,5,5,5,4,2,1,5,5,56,52.0,satisfied +1488,94382,Male,Loyal Customer,53,Business travel,Business,2659,2,2,2,2,5,4,5,5,5,5,4,4,5,3,1,2.0,satisfied +1489,63749,Male,Loyal Customer,51,Personal Travel,Eco,1660,3,5,3,4,2,3,1,2,3,4,4,5,5,2,3,0.0,neutral or dissatisfied +1490,111437,Male,Loyal Customer,51,Business travel,Business,3748,5,5,5,5,3,5,5,4,4,4,4,4,4,3,24,17.0,satisfied +1491,72933,Male,Loyal Customer,58,Business travel,Business,1096,1,1,1,1,2,5,4,4,4,4,4,4,4,4,24,28.0,satisfied +1492,122376,Male,Loyal Customer,37,Business travel,Business,529,4,1,1,1,2,3,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +1493,3527,Male,Loyal Customer,23,Business travel,Eco,557,1,2,4,2,1,1,2,1,4,4,4,3,3,1,0,0.0,neutral or dissatisfied +1494,120914,Male,Loyal Customer,59,Business travel,Business,2352,2,2,2,2,3,4,5,4,4,5,4,5,4,5,21,21.0,satisfied +1495,16543,Male,Loyal Customer,28,Business travel,Business,2150,1,1,1,1,4,4,4,4,5,5,1,4,4,4,0,0.0,satisfied +1496,7242,Male,Loyal Customer,42,Business travel,Eco,139,4,2,2,2,4,4,4,4,2,1,2,5,3,4,0,0.0,satisfied +1497,62653,Female,Loyal Customer,53,Personal Travel,Eco,1781,3,5,2,5,2,5,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +1498,113818,Male,Loyal Customer,17,Personal Travel,Eco Plus,414,3,3,4,1,5,4,5,5,1,1,1,3,2,5,4,2.0,neutral or dissatisfied +1499,23516,Female,disloyal Customer,22,Business travel,Eco,349,1,3,2,3,2,2,3,1,3,3,3,3,4,3,204,197.0,neutral or dissatisfied +1500,80175,Male,disloyal Customer,56,Business travel,Eco,975,2,2,2,4,2,5,5,3,1,3,3,5,5,5,0,0.0,neutral or dissatisfied +1501,127894,Female,Loyal Customer,46,Business travel,Business,1671,1,1,1,1,2,3,4,2,2,2,2,3,2,4,2,0.0,satisfied +1502,101891,Female,Loyal Customer,33,Business travel,Business,2039,1,1,1,1,4,4,4,4,4,4,4,4,4,5,15,0.0,satisfied +1503,53949,Female,Loyal Customer,23,Business travel,Business,3130,3,3,3,3,3,3,3,3,3,5,2,1,2,3,7,0.0,neutral or dissatisfied +1504,21167,Female,Loyal Customer,51,Business travel,Business,2324,5,5,5,5,3,5,4,4,4,4,5,5,4,4,0,38.0,satisfied +1505,60052,Female,Loyal Customer,65,Personal Travel,Eco Plus,997,1,5,2,2,2,4,5,5,5,2,1,5,5,4,7,6.0,neutral or dissatisfied +1506,71429,Male,Loyal Customer,43,Business travel,Business,867,2,2,2,2,4,5,5,4,4,4,4,4,4,3,29,17.0,satisfied +1507,66283,Female,Loyal Customer,39,Business travel,Eco Plus,460,4,3,3,3,4,4,4,4,2,4,1,4,4,4,0,0.0,satisfied +1508,96607,Female,Loyal Customer,45,Business travel,Business,972,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +1509,36951,Female,disloyal Customer,16,Business travel,Eco,901,1,1,1,3,5,1,5,5,3,4,4,2,4,5,0,0.0,neutral or dissatisfied +1510,43327,Female,Loyal Customer,36,Business travel,Eco,347,4,3,3,3,4,4,4,4,1,5,2,5,4,4,4,0.0,satisfied +1511,77910,Male,Loyal Customer,68,Personal Travel,Eco,456,2,3,2,1,2,2,2,2,4,1,4,2,5,2,25,13.0,neutral or dissatisfied +1512,4173,Female,Loyal Customer,23,Personal Travel,Eco,427,2,3,2,4,2,2,2,2,1,2,4,2,4,2,0,0.0,neutral or dissatisfied +1513,29753,Male,disloyal Customer,22,Business travel,Eco,199,3,5,3,5,5,3,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +1514,111942,Male,Loyal Customer,56,Business travel,Business,2057,3,3,2,3,3,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +1515,34323,Female,disloyal Customer,22,Business travel,Eco,2454,2,3,3,4,5,2,5,5,3,4,4,1,4,5,14,28.0,neutral or dissatisfied +1516,104279,Female,Loyal Customer,18,Personal Travel,Eco,1749,2,2,2,3,3,2,3,3,1,5,2,2,3,3,7,0.0,neutral or dissatisfied +1517,59353,Female,Loyal Customer,35,Business travel,Business,2338,5,5,5,5,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +1518,86577,Female,disloyal Customer,29,Business travel,Eco,1269,4,5,5,3,5,5,4,5,2,2,4,3,3,5,26,30.0,neutral or dissatisfied +1519,29642,Male,Loyal Customer,43,Personal Travel,Eco,1448,0,4,0,3,3,0,3,3,3,3,1,3,5,3,0,0.0,satisfied +1520,127522,Female,Loyal Customer,30,Business travel,Business,1506,1,5,1,1,5,5,5,5,4,5,4,4,5,5,31,29.0,satisfied +1521,29336,Female,Loyal Customer,40,Personal Travel,Eco,933,5,4,5,3,1,5,1,1,3,5,5,5,5,1,0,4.0,satisfied +1522,128071,Male,Loyal Customer,28,Business travel,Business,2917,1,1,1,1,5,5,5,3,3,4,4,5,5,5,16,18.0,satisfied +1523,65901,Female,Loyal Customer,32,Business travel,Eco,569,3,1,1,1,3,4,3,3,1,1,3,2,4,3,12,12.0,neutral or dissatisfied +1524,9044,Female,Loyal Customer,56,Business travel,Business,2905,2,2,2,2,5,4,4,4,4,4,5,5,4,5,0,6.0,satisfied +1525,116231,Male,Loyal Customer,20,Personal Travel,Eco,358,3,5,3,4,4,3,2,4,4,1,3,1,5,4,0,0.0,neutral or dissatisfied +1526,48489,Male,Loyal Customer,24,Business travel,Business,833,5,5,2,5,5,5,5,5,3,4,1,5,5,5,34,23.0,satisfied +1527,87487,Female,Loyal Customer,46,Business travel,Business,3983,4,4,4,4,4,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +1528,86240,Female,Loyal Customer,63,Personal Travel,Eco,226,4,5,4,4,2,4,4,3,3,4,3,5,3,5,15,13.0,neutral or dissatisfied +1529,42095,Male,Loyal Customer,28,Business travel,Eco,898,0,0,0,4,5,0,5,5,4,2,1,1,3,5,0,0.0,satisfied +1530,105372,Male,Loyal Customer,39,Business travel,Business,369,3,3,3,3,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +1531,110095,Female,disloyal Customer,23,Business travel,Eco,1072,3,3,3,2,1,3,1,1,5,2,5,3,5,1,0,5.0,neutral or dissatisfied +1532,126644,Female,Loyal Customer,48,Business travel,Eco,602,2,3,3,3,4,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +1533,86887,Female,Loyal Customer,59,Business travel,Business,1708,0,0,0,2,2,5,5,4,4,4,4,3,4,3,34,37.0,satisfied +1534,26308,Male,Loyal Customer,41,Business travel,Eco,2139,4,2,2,2,4,4,4,4,3,1,3,1,5,4,18,8.0,satisfied +1535,15130,Male,Loyal Customer,42,Business travel,Business,1678,5,5,5,5,3,4,4,5,5,5,5,1,5,1,0,0.0,satisfied +1536,87216,Female,Loyal Customer,20,Personal Travel,Eco,946,3,2,3,3,4,3,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +1537,104588,Male,Loyal Customer,67,Business travel,Business,369,2,2,2,2,1,4,3,5,5,5,5,2,5,2,0,0.0,satisfied +1538,117916,Female,Loyal Customer,50,Business travel,Business,3955,2,2,2,2,4,5,5,4,4,4,4,5,4,5,59,52.0,satisfied +1539,8179,Male,Loyal Customer,60,Business travel,Business,1512,3,3,3,3,4,3,2,3,3,3,3,4,3,4,12,1.0,neutral or dissatisfied +1540,76276,Male,Loyal Customer,25,Business travel,Business,1927,2,1,1,1,2,2,2,2,1,2,3,3,4,2,0,4.0,neutral or dissatisfied +1541,128544,Male,Loyal Customer,49,Business travel,Business,1964,0,0,0,3,4,5,4,2,2,2,2,5,2,3,0,0.0,satisfied +1542,42873,Female,Loyal Customer,28,Business travel,Business,3689,2,1,1,1,2,2,2,2,4,4,3,3,3,2,0,1.0,neutral or dissatisfied +1543,63826,Female,Loyal Customer,45,Business travel,Business,1192,3,3,3,3,5,5,4,4,4,4,4,5,4,3,0,2.0,satisfied +1544,20148,Female,disloyal Customer,22,Business travel,Eco,403,1,0,1,4,2,1,5,2,2,1,5,4,4,2,34,32.0,neutral or dissatisfied +1545,63456,Male,Loyal Customer,45,Business travel,Business,337,5,5,2,5,3,5,5,4,4,4,4,5,4,4,99,104.0,satisfied +1546,1193,Male,Loyal Customer,35,Personal Travel,Eco,482,4,4,4,1,5,4,5,5,3,5,4,1,2,5,0,46.0,neutral or dissatisfied +1547,3562,Male,Loyal Customer,42,Business travel,Business,3040,2,3,3,3,1,1,1,2,2,2,2,1,2,4,0,6.0,neutral or dissatisfied +1548,36547,Male,disloyal Customer,31,Business travel,Business,1185,3,4,4,1,3,4,3,3,3,1,3,4,3,3,5,43.0,neutral or dissatisfied +1549,77972,Male,Loyal Customer,44,Business travel,Business,332,3,3,2,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +1550,39634,Male,Loyal Customer,66,Personal Travel,Eco Plus,954,3,4,2,4,3,2,3,3,3,3,4,4,4,3,0,0.0,neutral or dissatisfied +1551,127396,Male,Loyal Customer,42,Business travel,Eco,1009,4,1,1,1,4,4,4,4,4,1,2,3,3,4,12,10.0,neutral or dissatisfied +1552,106999,Male,Loyal Customer,41,Personal Travel,Eco,937,3,5,3,3,4,3,4,4,4,5,5,3,5,4,7,0.0,neutral or dissatisfied +1553,51460,Male,Loyal Customer,8,Personal Travel,Eco Plus,266,1,3,1,2,3,1,3,3,3,1,2,1,2,3,0,0.0,neutral or dissatisfied +1554,41763,Female,Loyal Customer,43,Personal Travel,Eco,491,3,3,3,1,4,2,3,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +1555,123276,Male,Loyal Customer,22,Personal Travel,Eco,468,2,5,2,2,5,2,5,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +1556,89112,Female,Loyal Customer,52,Business travel,Business,1947,4,2,2,2,1,3,3,4,4,4,4,2,4,1,31,12.0,neutral or dissatisfied +1557,25845,Female,Loyal Customer,54,Business travel,Business,2201,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +1558,61393,Male,Loyal Customer,46,Business travel,Business,1699,5,1,3,1,2,3,2,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +1559,17104,Male,Loyal Customer,51,Personal Travel,Eco,416,2,4,2,4,4,2,1,4,4,4,2,4,3,4,0,0.0,neutral or dissatisfied +1560,85863,Male,disloyal Customer,23,Business travel,Eco,920,4,4,4,3,4,4,4,4,5,4,3,5,4,4,9,3.0,satisfied +1561,52230,Female,disloyal Customer,46,Business travel,Eco,370,0,5,0,5,2,0,2,2,4,3,4,4,5,2,0,0.0,satisfied +1562,63636,Female,Loyal Customer,30,Business travel,Eco,602,3,3,3,3,3,3,3,3,3,3,4,1,4,3,0,0.0,neutral or dissatisfied +1563,8124,Female,disloyal Customer,21,Business travel,Eco,335,2,5,2,2,3,2,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +1564,29363,Male,Loyal Customer,50,Business travel,Business,2409,2,2,2,2,4,4,4,1,4,5,5,4,1,4,67,82.0,satisfied +1565,984,Male,Loyal Customer,37,Business travel,Business,2329,3,3,2,3,1,1,5,4,4,5,4,4,4,1,0,0.0,satisfied +1566,18308,Female,Loyal Customer,45,Personal Travel,Business,549,1,5,1,3,1,1,1,5,4,5,4,1,5,1,170,155.0,neutral or dissatisfied +1567,117293,Male,Loyal Customer,60,Business travel,Business,1760,3,3,3,3,4,4,4,4,4,4,4,3,4,3,1,0.0,satisfied +1568,125027,Female,disloyal Customer,24,Business travel,Eco,184,3,3,3,3,1,3,5,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +1569,127739,Female,Loyal Customer,53,Business travel,Business,255,0,0,0,2,5,4,4,3,3,3,3,5,3,5,51,45.0,satisfied +1570,29104,Male,Loyal Customer,48,Personal Travel,Eco,956,3,4,3,1,5,3,5,5,5,4,4,4,4,5,0,5.0,neutral or dissatisfied +1571,6408,Male,Loyal Customer,43,Personal Travel,Eco,315,3,4,4,1,2,4,2,2,1,5,5,4,3,2,0,1.0,neutral or dissatisfied +1572,30558,Male,disloyal Customer,26,Business travel,Business,628,2,2,2,4,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +1573,87346,Female,disloyal Customer,65,Business travel,Business,425,4,4,4,5,4,4,4,4,3,2,4,5,5,4,19,2.0,neutral or dissatisfied +1574,119990,Female,Loyal Customer,62,Personal Travel,Eco Plus,1009,2,3,2,4,3,4,1,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +1575,65797,Male,disloyal Customer,28,Business travel,Business,1389,4,4,4,1,5,4,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +1576,112003,Female,disloyal Customer,51,Business travel,Eco Plus,533,3,3,3,3,5,3,5,5,1,5,4,4,4,5,0,0.0,neutral or dissatisfied +1577,102378,Female,disloyal Customer,43,Business travel,Eco,223,1,0,1,1,5,1,5,5,3,4,5,1,4,5,0,0.0,neutral or dissatisfied +1578,19449,Female,Loyal Customer,43,Business travel,Eco,363,1,5,5,5,4,3,4,2,2,1,2,2,2,4,28,30.0,neutral or dissatisfied +1579,12070,Male,Loyal Customer,20,Personal Travel,Eco,351,5,5,5,5,3,5,3,3,5,3,5,5,5,3,0,0.0,satisfied +1580,15231,Male,Loyal Customer,43,Business travel,Eco,445,2,5,5,5,2,2,2,2,1,4,2,3,3,2,47,50.0,satisfied +1581,88544,Male,Loyal Customer,15,Personal Travel,Eco,270,3,2,5,2,1,5,1,1,3,2,3,4,2,1,7,5.0,neutral or dissatisfied +1582,83549,Male,Loyal Customer,40,Personal Travel,Eco Plus,1121,2,4,2,1,5,2,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +1583,87267,Female,Loyal Customer,41,Business travel,Business,2347,5,5,5,5,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +1584,29010,Male,disloyal Customer,37,Business travel,Business,272,3,3,3,1,4,3,4,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +1585,107641,Male,Loyal Customer,53,Business travel,Business,405,2,2,5,2,3,4,5,5,5,5,5,4,5,5,32,30.0,satisfied +1586,93678,Male,Loyal Customer,26,Personal Travel,Eco,655,1,1,1,3,4,1,1,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +1587,26212,Female,Loyal Customer,38,Business travel,Business,181,1,1,1,1,5,1,1,4,4,4,5,4,4,4,0,0.0,satisfied +1588,9092,Male,Loyal Customer,42,Business travel,Business,3672,1,1,1,1,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +1589,41924,Female,Loyal Customer,58,Business travel,Eco,129,5,3,3,3,3,5,5,5,5,5,5,3,5,5,3,,satisfied +1590,94129,Female,Loyal Customer,42,Business travel,Business,3998,3,3,3,3,4,4,4,5,5,5,5,5,5,3,32,34.0,satisfied +1591,106650,Female,disloyal Customer,25,Business travel,Eco Plus,861,2,2,2,4,3,2,4,3,1,3,4,4,3,3,0,0.0,neutral or dissatisfied +1592,111617,Female,Loyal Customer,42,Business travel,Eco,1014,3,3,3,3,3,2,1,3,3,3,3,4,3,4,43,24.0,neutral or dissatisfied +1593,19025,Female,Loyal Customer,20,Personal Travel,Eco,788,1,4,1,3,2,1,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +1594,32299,Female,Loyal Customer,45,Business travel,Business,2427,1,1,5,1,5,2,1,4,4,5,5,3,4,4,14,14.0,satisfied +1595,1178,Female,Loyal Customer,19,Personal Travel,Eco,482,4,2,4,4,5,4,5,5,1,3,3,4,3,5,8,6.0,neutral or dissatisfied +1596,55267,Male,disloyal Customer,24,Business travel,Eco,709,3,3,3,4,4,3,4,4,5,3,2,5,1,4,0,0.0,neutral or dissatisfied +1597,88983,Female,Loyal Customer,61,Personal Travel,Eco,1340,1,5,1,1,5,4,4,2,2,1,2,3,2,3,104,79.0,neutral or dissatisfied +1598,89605,Female,Loyal Customer,39,Business travel,Business,3863,1,2,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1599,95439,Male,Loyal Customer,49,Business travel,Business,562,5,5,5,5,2,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +1600,12448,Female,Loyal Customer,37,Personal Travel,Eco,190,4,4,4,4,4,1,1,4,3,4,4,1,5,1,258,247.0,neutral or dissatisfied +1601,26858,Female,disloyal Customer,21,Business travel,Eco,224,3,3,3,3,2,3,2,2,3,4,2,4,1,2,0,20.0,neutral or dissatisfied +1602,86312,Female,disloyal Customer,27,Business travel,Eco Plus,356,2,2,2,4,5,2,5,5,4,2,3,3,4,5,0,0.0,neutral or dissatisfied +1603,126217,Female,disloyal Customer,33,Business travel,Eco,328,3,2,3,3,2,3,2,2,1,5,3,3,4,2,6,6.0,neutral or dissatisfied +1604,124793,Male,Loyal Customer,63,Business travel,Eco,280,2,5,5,5,3,2,3,3,2,4,3,1,4,3,0,0.0,neutral or dissatisfied +1605,79,Female,Loyal Customer,70,Personal Travel,Eco,108,5,4,0,3,4,4,4,3,3,0,3,5,3,5,50,41.0,satisfied +1606,120831,Male,disloyal Customer,27,Business travel,Business,920,1,1,1,3,4,1,1,4,5,3,5,5,4,4,0,10.0,neutral or dissatisfied +1607,57679,Female,Loyal Customer,43,Business travel,Business,3537,3,3,1,3,2,5,4,3,3,4,3,5,3,3,33,8.0,satisfied +1608,89648,Male,disloyal Customer,19,Business travel,Eco,1096,3,3,3,3,3,4,4,2,1,3,4,4,2,4,132,102.0,neutral or dissatisfied +1609,114588,Male,Loyal Customer,62,Business travel,Business,2349,3,2,2,2,2,4,4,3,3,3,3,4,3,1,2,0.0,neutral or dissatisfied +1610,123966,Male,Loyal Customer,58,Business travel,Business,2002,3,3,3,3,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1611,121670,Female,Loyal Customer,30,Business travel,Business,511,3,1,1,1,3,3,3,3,1,3,3,2,3,3,28,32.0,neutral or dissatisfied +1612,46690,Male,Loyal Customer,28,Personal Travel,Eco,73,2,2,2,4,3,2,3,3,4,3,4,2,3,3,0,0.0,neutral or dissatisfied +1613,1480,Female,Loyal Customer,42,Business travel,Business,737,4,2,3,2,2,4,4,4,4,3,4,1,4,2,0,3.0,neutral or dissatisfied +1614,77238,Female,Loyal Customer,23,Business travel,Business,1590,2,1,5,5,2,2,2,2,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +1615,64787,Male,disloyal Customer,25,Business travel,Eco,190,1,2,0,4,5,0,5,5,2,4,3,1,3,5,0,0.0,neutral or dissatisfied +1616,117807,Male,Loyal Customer,35,Business travel,Business,2506,5,5,4,5,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +1617,40745,Male,Loyal Customer,43,Business travel,Business,2554,3,3,3,3,3,3,4,4,4,4,4,1,4,2,7,0.0,satisfied +1618,66529,Female,Loyal Customer,45,Personal Travel,Business,733,3,3,2,3,1,4,4,4,4,2,4,4,4,1,30,14.0,neutral or dissatisfied +1619,113901,Male,Loyal Customer,35,Business travel,Business,2295,2,5,5,5,4,2,2,2,2,2,2,1,2,2,24,15.0,neutral or dissatisfied +1620,84032,Female,Loyal Customer,48,Personal Travel,Eco Plus,321,3,3,4,1,4,5,1,3,3,4,3,3,3,2,0,2.0,neutral or dissatisfied +1621,106587,Female,Loyal Customer,8,Personal Travel,Eco,333,4,5,4,2,1,4,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +1622,7191,Female,Loyal Customer,30,Business travel,Eco,135,4,1,1,1,4,4,4,4,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +1623,114205,Female,disloyal Customer,28,Business travel,Business,846,2,2,2,1,2,2,2,2,4,4,5,4,5,2,35,40.0,neutral or dissatisfied +1624,89049,Female,Loyal Customer,43,Business travel,Business,2139,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +1625,69747,Male,Loyal Customer,37,Business travel,Business,1610,2,5,5,5,2,3,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +1626,102108,Female,disloyal Customer,61,Business travel,Business,258,3,3,3,1,4,3,4,4,3,3,5,4,5,4,48,41.0,neutral or dissatisfied +1627,126152,Male,disloyal Customer,45,Business travel,Eco,468,1,3,1,4,1,1,1,1,3,3,3,4,4,1,0,8.0,neutral or dissatisfied +1628,47774,Male,Loyal Customer,64,Business travel,Eco,834,5,5,5,5,5,5,5,5,2,1,5,3,5,5,0,21.0,satisfied +1629,121603,Male,Loyal Customer,18,Personal Travel,Eco,936,3,5,3,3,5,3,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +1630,9293,Male,Loyal Customer,27,Personal Travel,Eco,1201,4,5,4,4,4,4,2,4,2,1,4,4,1,4,15,32.0,neutral or dissatisfied +1631,41133,Male,disloyal Customer,37,Business travel,Business,216,4,4,4,3,2,4,2,2,1,3,4,1,3,2,90,76.0,neutral or dissatisfied +1632,73420,Male,Loyal Customer,38,Business travel,Business,797,1,4,4,4,1,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +1633,80170,Male,Loyal Customer,22,Business travel,Business,2475,1,2,3,2,1,1,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +1634,52243,Female,disloyal Customer,39,Business travel,Business,370,1,1,1,3,1,1,1,1,1,2,3,1,3,1,61,67.0,neutral or dissatisfied +1635,9689,Male,Loyal Customer,45,Business travel,Business,3166,1,1,1,1,2,5,1,5,5,5,5,2,5,3,40,68.0,satisfied +1636,29988,Male,Loyal Customer,43,Business travel,Eco,399,4,5,5,5,4,4,4,4,1,3,3,3,4,4,0,0.0,satisfied +1637,59150,Female,Loyal Customer,54,Business travel,Business,1846,1,1,3,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +1638,106249,Female,Loyal Customer,55,Personal Travel,Eco,1167,1,4,1,1,5,4,5,4,4,1,4,3,4,4,58,39.0,neutral or dissatisfied +1639,14402,Female,Loyal Customer,10,Personal Travel,Eco,789,1,4,1,4,1,1,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +1640,57616,Female,Loyal Customer,49,Business travel,Business,2241,4,4,4,4,2,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +1641,102247,Female,Loyal Customer,41,Business travel,Eco,407,2,3,3,3,3,2,3,3,3,5,3,4,3,3,18,21.0,neutral or dissatisfied +1642,108683,Female,Loyal Customer,31,Business travel,Business,577,4,4,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,satisfied +1643,30154,Male,Loyal Customer,70,Personal Travel,Eco,204,1,3,0,2,4,0,3,4,2,2,2,2,2,4,44,48.0,neutral or dissatisfied +1644,18742,Female,Loyal Customer,42,Business travel,Business,2113,2,2,2,2,1,5,2,5,5,5,5,4,5,5,11,0.0,satisfied +1645,23525,Female,Loyal Customer,38,Business travel,Eco Plus,303,4,1,1,1,4,4,4,4,5,5,5,4,4,4,26,39.0,satisfied +1646,54569,Female,disloyal Customer,26,Business travel,Eco Plus,925,3,3,3,3,1,3,1,1,3,2,4,1,4,1,1,4.0,neutral or dissatisfied +1647,124716,Female,Loyal Customer,49,Personal Travel,Eco,399,2,3,2,2,3,4,3,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +1648,75828,Male,Loyal Customer,52,Business travel,Business,1440,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +1649,100561,Female,Loyal Customer,58,Business travel,Business,2091,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +1650,108934,Male,Loyal Customer,33,Personal Travel,Eco,1183,2,5,1,3,4,1,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +1651,118859,Female,Loyal Customer,36,Personal Travel,Eco Plus,646,1,1,1,3,1,3,3,1,1,3,4,3,3,3,155,138.0,neutral or dissatisfied +1652,37796,Female,disloyal Customer,39,Business travel,Eco Plus,628,2,2,2,3,4,2,4,4,2,2,3,2,3,4,109,100.0,neutral or dissatisfied +1653,107537,Female,Loyal Customer,49,Business travel,Business,1521,5,5,5,5,4,4,4,4,5,5,4,4,5,4,202,207.0,satisfied +1654,107665,Male,Loyal Customer,43,Business travel,Business,251,4,4,5,4,4,5,5,4,4,4,4,4,4,3,8,0.0,satisfied +1655,63689,Female,Loyal Customer,39,Business travel,Business,1696,1,4,4,4,1,1,1,2,1,3,3,1,1,1,951,940.0,neutral or dissatisfied +1656,121840,Male,Loyal Customer,51,Business travel,Eco,366,1,2,2,2,1,1,1,1,4,3,3,3,3,1,8,3.0,neutral or dissatisfied +1657,6399,Male,Loyal Customer,43,Personal Travel,Eco,296,2,5,5,4,4,5,4,4,5,5,4,5,5,4,0,0.0,neutral or dissatisfied +1658,26465,Male,Loyal Customer,42,Personal Travel,Eco,925,2,3,2,3,5,2,5,5,3,3,3,1,4,5,0,8.0,neutral or dissatisfied +1659,69855,Male,Loyal Customer,33,Personal Travel,Eco,1055,1,4,1,4,2,1,1,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +1660,117113,Female,disloyal Customer,16,Business travel,Eco,304,0,0,0,3,3,0,3,3,4,1,5,2,1,3,3,0.0,satisfied +1661,60127,Male,Loyal Customer,40,Business travel,Eco,1050,2,5,5,5,2,3,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +1662,87232,Female,disloyal Customer,25,Business travel,Business,946,2,0,2,1,4,2,4,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +1663,15965,Male,Loyal Customer,23,Personal Travel,Eco,473,1,3,1,3,4,1,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +1664,16941,Female,disloyal Customer,37,Business travel,Eco,420,4,0,4,5,4,4,4,4,2,4,3,2,4,4,3,0.0,neutral or dissatisfied +1665,43733,Female,Loyal Customer,67,Personal Travel,Eco Plus,257,3,2,3,3,4,3,3,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +1666,23499,Female,Loyal Customer,46,Business travel,Eco,303,4,2,2,2,2,1,1,3,3,4,3,2,3,1,26,21.0,neutral or dissatisfied +1667,123327,Female,Loyal Customer,60,Business travel,Eco Plus,107,1,5,5,5,1,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +1668,81544,Male,Loyal Customer,65,Personal Travel,Eco,1124,2,1,2,3,3,2,3,3,2,4,3,2,3,3,0,0.0,neutral or dissatisfied +1669,39344,Female,Loyal Customer,11,Personal Travel,Eco Plus,774,2,5,2,1,4,2,4,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +1670,105561,Male,Loyal Customer,47,Business travel,Business,1528,1,1,5,1,3,5,5,5,5,5,5,3,5,4,20,20.0,satisfied +1671,110434,Male,Loyal Customer,24,Personal Travel,Eco,925,5,5,5,5,5,5,5,5,1,3,5,5,3,5,0,0.0,satisfied +1672,117449,Female,Loyal Customer,51,Business travel,Business,1107,1,3,3,3,2,3,3,1,1,1,1,4,1,4,2,6.0,neutral or dissatisfied +1673,69563,Male,Loyal Customer,62,Business travel,Eco,2586,3,2,2,2,3,3,3,4,2,3,4,3,2,3,15,38.0,neutral or dissatisfied +1674,120496,Male,disloyal Customer,32,Business travel,Eco Plus,449,3,3,3,4,4,3,4,4,3,5,3,3,4,4,0,4.0,neutral or dissatisfied +1675,2229,Female,Loyal Customer,32,Personal Travel,Eco,859,5,4,5,3,3,5,3,3,4,4,4,5,4,3,17,7.0,satisfied +1676,81268,Male,disloyal Customer,23,Business travel,Business,1020,4,5,4,1,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +1677,124508,Male,Loyal Customer,60,Personal Travel,Eco,930,2,4,2,3,3,2,3,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +1678,67335,Male,Loyal Customer,31,Business travel,Business,1471,2,2,2,2,5,5,5,5,4,2,4,3,5,5,0,0.0,satisfied +1679,128390,Female,Loyal Customer,38,Business travel,Business,2492,2,3,3,3,3,4,3,2,2,2,2,3,2,1,43,29.0,neutral or dissatisfied +1680,10870,Female,Loyal Customer,31,Business travel,Eco,191,2,5,5,5,2,2,2,2,4,5,4,1,3,2,24,22.0,neutral or dissatisfied +1681,3714,Female,Loyal Customer,8,Personal Travel,Eco,431,3,2,3,3,3,3,3,3,1,2,4,1,4,3,0,83.0,neutral or dissatisfied +1682,71341,Male,Loyal Customer,58,Personal Travel,Eco,1514,1,3,1,4,5,1,5,5,4,2,4,3,3,5,4,31.0,neutral or dissatisfied +1683,12702,Male,Loyal Customer,47,Business travel,Business,3077,4,4,4,4,3,5,1,4,4,4,4,2,4,1,23,40.0,neutral or dissatisfied +1684,40014,Female,Loyal Customer,50,Business travel,Business,575,5,5,5,5,4,2,1,2,2,2,2,5,2,4,0,0.0,satisfied +1685,39132,Female,Loyal Customer,39,Business travel,Business,3700,4,4,4,4,2,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +1686,67705,Male,Loyal Customer,58,Business travel,Business,1944,3,2,2,2,4,4,3,3,3,3,3,4,3,1,28,34.0,neutral or dissatisfied +1687,56358,Male,Loyal Customer,37,Personal Travel,Eco,200,2,4,0,4,4,0,4,4,1,2,5,1,5,4,60,59.0,neutral or dissatisfied +1688,127955,Male,Loyal Customer,25,Business travel,Eco,1999,3,5,5,5,3,3,3,3,3,1,4,3,4,3,2,21.0,neutral or dissatisfied +1689,96548,Male,Loyal Customer,80,Business travel,Business,1990,2,2,2,2,5,4,5,5,5,5,5,4,5,5,9,0.0,satisfied +1690,25485,Female,disloyal Customer,26,Business travel,Eco,547,4,3,4,2,4,4,4,4,5,5,2,4,3,4,0,0.0,neutral or dissatisfied +1691,59656,Female,Loyal Customer,34,Personal Travel,Eco,965,4,4,5,3,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +1692,53783,Male,Loyal Customer,70,Business travel,Business,140,1,3,3,3,2,2,2,4,4,4,1,1,4,3,0,0.0,neutral or dissatisfied +1693,87694,Male,Loyal Customer,65,Personal Travel,Eco,591,2,5,2,2,4,2,4,4,3,4,4,3,4,4,71,69.0,neutral or dissatisfied +1694,6071,Female,Loyal Customer,30,Personal Travel,Eco,1236,3,5,3,4,3,3,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +1695,109152,Male,Loyal Customer,46,Business travel,Business,655,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +1696,17732,Female,Loyal Customer,37,Business travel,Eco,383,5,3,3,3,5,5,5,5,2,5,4,3,1,5,0,0.0,satisfied +1697,58820,Female,Loyal Customer,50,Personal Travel,Eco,1182,1,3,1,4,2,3,4,3,3,1,3,3,3,2,68,82.0,neutral or dissatisfied +1698,20883,Female,disloyal Customer,26,Business travel,Eco Plus,508,5,5,5,5,4,5,4,4,1,1,4,1,1,4,9,0.0,satisfied +1699,92487,Female,Loyal Customer,40,Business travel,Business,2092,3,1,2,1,1,3,3,3,3,3,3,3,3,2,2,0.0,neutral or dissatisfied +1700,49979,Male,Loyal Customer,34,Business travel,Business,304,1,5,5,5,3,2,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +1701,79922,Female,disloyal Customer,26,Business travel,Eco,1096,3,3,3,3,4,3,4,4,2,2,3,3,4,4,0,0.0,neutral or dissatisfied +1702,129096,Male,disloyal Customer,19,Business travel,Eco,1304,3,3,3,4,3,2,1,2,4,4,4,1,1,1,0,18.0,neutral or dissatisfied +1703,28065,Female,disloyal Customer,20,Business travel,Eco,1372,3,3,3,5,3,3,3,1,3,3,3,3,4,3,3,72.0,neutral or dissatisfied +1704,106832,Female,disloyal Customer,27,Business travel,Business,1733,1,1,1,4,2,1,2,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +1705,14774,Female,Loyal Customer,19,Business travel,Business,2596,4,4,4,4,4,4,4,4,1,4,2,2,5,4,0,4.0,satisfied +1706,11062,Male,Loyal Customer,20,Personal Travel,Eco,216,4,2,4,4,3,4,4,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +1707,56334,Female,Loyal Customer,51,Business travel,Business,3442,2,2,2,2,4,4,5,5,5,5,4,4,5,5,4,0.0,satisfied +1708,108541,Male,Loyal Customer,34,Business travel,Business,511,2,2,2,2,2,4,4,5,5,5,5,4,5,4,12,11.0,satisfied +1709,55971,Female,Loyal Customer,24,Personal Travel,Eco,1620,4,4,4,1,1,4,1,1,5,5,5,5,4,1,0,0.0,satisfied +1710,73607,Male,disloyal Customer,21,Business travel,Eco,204,5,0,5,1,4,5,4,4,5,4,5,4,4,4,0,0.0,satisfied +1711,37255,Male,disloyal Customer,28,Business travel,Eco,828,3,3,3,2,4,3,4,4,1,5,3,1,4,4,19,19.0,neutral or dissatisfied +1712,121300,Female,Loyal Customer,59,Business travel,Business,2877,4,4,4,4,4,4,5,4,4,4,4,3,4,4,44,35.0,satisfied +1713,128586,Male,Loyal Customer,30,Business travel,Business,2552,4,2,2,2,4,4,4,4,2,4,2,4,1,4,0,0.0,neutral or dissatisfied +1714,119627,Male,Loyal Customer,35,Personal Travel,Eco,1927,2,4,1,4,1,5,5,4,3,4,5,5,4,5,190,181.0,neutral or dissatisfied +1715,84558,Male,Loyal Customer,54,Personal Travel,Eco,2399,5,3,5,4,3,5,3,3,3,2,4,2,3,3,0,0.0,satisfied +1716,38708,Male,disloyal Customer,27,Business travel,Eco,2583,3,3,3,3,5,3,5,5,2,4,3,2,3,5,43,48.0,neutral or dissatisfied +1717,89670,Male,disloyal Customer,26,Business travel,Eco,950,3,3,3,3,2,3,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +1718,48483,Female,disloyal Customer,30,Business travel,Eco,844,3,3,3,4,3,3,3,3,3,3,3,2,4,3,4,0.0,neutral or dissatisfied +1719,50705,Male,Loyal Customer,61,Personal Travel,Eco,156,1,4,0,3,2,0,1,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +1720,60000,Male,Loyal Customer,61,Personal Travel,Eco,937,2,3,2,4,1,2,1,1,4,1,1,2,4,1,0,0.0,neutral or dissatisfied +1721,37109,Male,Loyal Customer,35,Business travel,Business,1189,2,2,2,2,2,4,5,5,5,5,5,1,5,5,23,17.0,satisfied +1722,51776,Male,Loyal Customer,48,Personal Travel,Eco,370,4,5,2,1,5,2,5,5,3,4,4,5,5,5,89,78.0,neutral or dissatisfied +1723,100843,Male,Loyal Customer,50,Personal Travel,Eco,711,3,4,3,2,3,3,3,3,3,4,4,5,5,3,0,9.0,neutral or dissatisfied +1724,84133,Female,disloyal Customer,34,Business travel,Eco,782,3,3,3,3,4,3,4,4,1,5,3,2,4,4,0,4.0,neutral or dissatisfied +1725,82240,Female,Loyal Customer,68,Personal Travel,Eco,405,2,3,2,4,5,2,1,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +1726,37252,Female,Loyal Customer,62,Personal Travel,Business,1047,4,5,4,3,3,5,5,5,5,4,3,4,5,4,0,0.0,neutral or dissatisfied +1727,48440,Female,Loyal Customer,39,Business travel,Eco,846,4,3,3,3,4,4,4,4,4,5,3,5,3,4,0,17.0,satisfied +1728,81630,Female,Loyal Customer,48,Business travel,Business,1854,1,1,1,1,4,4,4,2,2,2,2,3,2,4,14,0.0,satisfied +1729,31437,Female,disloyal Customer,54,Business travel,Eco Plus,1007,4,4,4,4,4,4,1,4,4,2,3,1,3,4,0,17.0,neutral or dissatisfied +1730,113762,Male,disloyal Customer,28,Personal Travel,Eco,223,1,4,1,3,4,1,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +1731,90247,Female,Loyal Customer,28,Personal Travel,Eco,1121,1,4,1,4,5,1,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +1732,17500,Male,Loyal Customer,19,Business travel,Business,352,2,2,2,2,5,5,5,5,3,3,2,5,5,5,0,0.0,satisfied +1733,97127,Female,disloyal Customer,60,Business travel,Eco,1211,1,1,1,4,1,1,1,1,1,2,3,4,4,1,16,14.0,neutral or dissatisfied +1734,60284,Male,Loyal Customer,14,Personal Travel,Eco,326,2,4,2,4,2,1,1,3,1,5,4,1,2,1,202,205.0,neutral or dissatisfied +1735,103404,Male,Loyal Customer,34,Business travel,Business,237,3,3,3,3,5,3,3,3,3,3,3,3,3,4,19,13.0,neutral or dissatisfied +1736,60548,Male,Loyal Customer,42,Business travel,Business,862,1,1,1,1,4,4,5,4,4,4,4,3,4,3,11,13.0,satisfied +1737,20442,Female,Loyal Customer,49,Business travel,Eco,177,4,3,3,3,1,4,3,4,4,4,4,4,4,2,7,0.0,satisfied +1738,83427,Male,Loyal Customer,37,Personal Travel,Eco,632,1,5,1,2,2,1,2,2,5,3,5,3,4,2,0,8.0,neutral or dissatisfied +1739,83897,Male,Loyal Customer,43,Business travel,Business,1450,2,5,5,5,1,2,3,2,2,2,2,2,2,1,34,4.0,neutral or dissatisfied +1740,89676,Female,Loyal Customer,18,Business travel,Business,3690,1,3,3,3,1,1,1,1,2,4,3,1,4,1,214,201.0,neutral or dissatisfied +1741,129365,Female,Loyal Customer,48,Business travel,Business,2454,3,3,3,3,2,3,4,5,5,5,5,3,5,5,4,0.0,satisfied +1742,75274,Female,Loyal Customer,33,Personal Travel,Eco,1723,0,1,0,4,1,0,1,1,4,4,4,2,4,1,0,0.0,satisfied +1743,30418,Female,Loyal Customer,20,Personal Travel,Eco Plus,862,1,5,1,5,4,1,1,4,2,1,2,2,3,4,15,27.0,neutral or dissatisfied +1744,17695,Male,Loyal Customer,20,Business travel,Business,2041,1,1,1,1,3,3,3,3,5,1,4,5,3,3,0,1.0,satisfied +1745,93317,Male,Loyal Customer,42,Business travel,Business,3454,3,4,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +1746,78883,Male,Loyal Customer,67,Business travel,Eco Plus,223,1,2,4,2,1,1,1,1,2,1,4,1,4,1,33,49.0,neutral or dissatisfied +1747,61502,Male,disloyal Customer,22,Business travel,Eco,753,5,5,5,1,5,5,5,5,2,2,2,1,5,5,0,0.0,satisfied +1748,71202,Male,Loyal Customer,45,Business travel,Business,1700,3,3,3,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +1749,53579,Female,Loyal Customer,48,Personal Travel,Eco,1195,2,5,2,3,4,4,5,2,2,2,2,5,2,4,9,1.0,neutral or dissatisfied +1750,27173,Male,Loyal Customer,7,Personal Travel,Eco,2677,2,2,3,3,3,1,1,1,3,3,3,1,1,1,0,0.0,neutral or dissatisfied +1751,117933,Male,Loyal Customer,54,Business travel,Business,255,1,1,4,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +1752,27549,Female,Loyal Customer,25,Personal Travel,Eco,679,2,3,2,4,1,2,1,1,3,5,4,2,2,1,33,21.0,neutral or dissatisfied +1753,93552,Female,Loyal Customer,43,Business travel,Business,719,3,3,3,3,4,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +1754,5859,Male,Loyal Customer,40,Personal Travel,Eco,1020,1,0,1,4,5,1,4,5,3,5,4,2,2,5,0,3.0,neutral or dissatisfied +1755,83497,Male,Loyal Customer,46,Business travel,Eco,546,4,2,2,2,4,4,4,5,2,2,2,4,5,4,266,262.0,satisfied +1756,91934,Female,Loyal Customer,50,Business travel,Business,2475,2,2,2,2,5,3,3,2,2,2,2,3,2,2,1,0.0,neutral or dissatisfied +1757,31894,Female,Loyal Customer,33,Personal Travel,Eco,2762,1,0,1,1,2,1,2,2,2,5,4,2,5,2,0,0.0,neutral or dissatisfied +1758,4745,Female,Loyal Customer,38,Personal Travel,Eco,888,3,2,3,3,1,3,1,1,3,1,4,1,3,1,0,0.0,neutral or dissatisfied +1759,96344,Female,Loyal Customer,40,Business travel,Business,1609,1,4,4,4,1,3,3,1,1,1,1,2,1,3,1,21.0,neutral or dissatisfied +1760,118568,Female,Loyal Customer,70,Business travel,Eco,370,2,3,3,3,4,2,2,2,2,2,2,2,2,4,14,20.0,neutral or dissatisfied +1761,1047,Female,disloyal Customer,45,Business travel,Eco,229,2,0,2,2,5,2,5,5,5,1,5,4,2,5,0,0.0,neutral or dissatisfied +1762,88528,Male,Loyal Customer,52,Personal Travel,Eco,404,2,5,2,2,4,2,4,4,1,2,2,5,3,4,0,0.0,neutral or dissatisfied +1763,64317,Female,disloyal Customer,57,Business travel,Business,1192,3,3,3,1,4,3,4,4,4,2,5,5,4,4,0,7.0,neutral or dissatisfied +1764,104260,Male,Loyal Customer,48,Business travel,Business,456,1,1,1,1,3,5,5,4,4,4,4,5,4,3,27,11.0,satisfied +1765,69379,Female,disloyal Customer,49,Business travel,Business,1089,3,3,3,3,5,3,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +1766,6980,Male,Loyal Customer,38,Business travel,Business,2399,3,3,3,3,3,5,5,5,5,5,5,5,5,5,28,25.0,satisfied +1767,43299,Male,Loyal Customer,44,Business travel,Eco,387,5,3,2,3,4,5,4,4,2,3,5,5,1,4,0,0.0,satisfied +1768,13418,Male,Loyal Customer,22,Business travel,Business,2031,1,2,1,1,5,5,5,5,1,4,1,2,1,5,1,16.0,satisfied +1769,94829,Male,Loyal Customer,46,Business travel,Business,341,5,5,5,5,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +1770,36241,Male,Loyal Customer,41,Business travel,Business,612,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +1771,42745,Male,Loyal Customer,38,Personal Travel,Eco Plus,536,2,4,2,5,4,2,1,4,4,5,5,3,5,4,47,29.0,neutral or dissatisfied +1772,14655,Female,disloyal Customer,35,Business travel,Eco,112,3,1,3,2,4,3,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +1773,123726,Female,Loyal Customer,31,Business travel,Business,214,5,5,5,5,5,5,5,5,5,5,5,3,5,5,0,3.0,satisfied +1774,76572,Female,Loyal Customer,49,Business travel,Business,3122,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,10.0,satisfied +1775,86122,Female,disloyal Customer,24,Business travel,Business,226,4,0,4,5,3,4,3,3,3,5,5,4,4,3,17,10.0,satisfied +1776,36387,Male,Loyal Customer,49,Personal Travel,Eco,200,4,2,4,1,4,4,4,4,2,2,1,4,2,4,0,9.0,neutral or dissatisfied +1777,95167,Female,Loyal Customer,33,Personal Travel,Eco,319,3,4,3,3,2,3,1,2,3,5,4,3,4,2,20,13.0,neutral or dissatisfied +1778,103339,Female,Loyal Customer,62,Personal Travel,Eco,1371,1,5,2,2,3,4,5,3,3,2,3,4,3,5,0,9.0,neutral or dissatisfied +1779,26265,Male,Loyal Customer,38,Business travel,Business,2779,3,2,2,2,3,3,2,3,3,4,3,1,3,4,21,15.0,neutral or dissatisfied +1780,43059,Female,Loyal Customer,61,Business travel,Business,2956,4,1,1,1,4,3,3,4,4,4,4,1,4,1,32,16.0,neutral or dissatisfied +1781,71977,Male,Loyal Customer,56,Business travel,Business,1440,3,4,4,4,3,2,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +1782,12911,Female,Loyal Customer,30,Business travel,Business,674,2,3,3,3,2,2,2,2,2,2,3,1,3,2,1,18.0,neutral or dissatisfied +1783,62564,Male,Loyal Customer,42,Business travel,Business,1744,1,1,1,1,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +1784,83367,Female,Loyal Customer,43,Business travel,Business,1124,4,1,1,1,4,4,4,4,4,4,4,1,4,4,65,60.0,neutral or dissatisfied +1785,2220,Male,Loyal Customer,39,Business travel,Business,3098,1,1,1,1,2,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +1786,129419,Male,Loyal Customer,59,Business travel,Business,2863,5,5,5,5,3,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +1787,8440,Male,disloyal Customer,22,Business travel,Business,590,0,0,0,2,2,0,4,2,5,3,5,5,4,2,2,0.0,satisfied +1788,26449,Male,Loyal Customer,28,Business travel,Business,2725,3,3,3,3,5,5,5,5,3,2,1,2,1,5,0,0.0,satisfied +1789,89854,Male,Loyal Customer,49,Business travel,Business,1416,1,1,1,1,3,5,5,4,4,4,4,4,4,3,0,7.0,satisfied +1790,73575,Male,Loyal Customer,42,Business travel,Business,3222,3,3,3,3,4,5,5,3,3,4,4,5,3,5,0,0.0,satisfied +1791,69225,Female,Loyal Customer,59,Business travel,Business,3677,4,4,4,4,4,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +1792,128839,Male,Loyal Customer,51,Personal Travel,Eco,2475,2,4,2,3,2,5,3,5,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +1793,72341,Male,Loyal Customer,58,Business travel,Business,985,4,4,3,4,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +1794,70846,Male,disloyal Customer,25,Business travel,Business,761,3,0,3,5,3,3,1,3,5,2,4,4,4,3,0,0.0,neutral or dissatisfied +1795,115323,Female,Loyal Customer,48,Business travel,Business,3152,2,2,3,2,2,5,5,4,4,4,4,4,4,4,19,16.0,satisfied +1796,32108,Male,disloyal Customer,20,Business travel,Eco,101,2,0,2,5,1,2,1,1,5,5,1,3,2,1,1,11.0,neutral or dissatisfied +1797,111386,Female,Loyal Customer,56,Business travel,Business,773,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +1798,52629,Male,disloyal Customer,34,Business travel,Eco,160,2,0,2,1,4,2,4,4,4,4,4,4,4,4,2,0.0,neutral or dissatisfied +1799,13652,Male,Loyal Customer,44,Business travel,Eco,196,3,5,5,5,3,3,3,3,3,3,2,4,3,3,18,12.0,neutral or dissatisfied +1800,110975,Male,disloyal Customer,24,Business travel,Eco,319,4,0,4,4,3,4,1,3,5,3,4,4,4,3,21,83.0,satisfied +1801,103109,Male,Loyal Customer,38,Personal Travel,Eco,786,5,5,5,1,4,5,4,4,3,3,4,4,4,4,1,0.0,satisfied +1802,29900,Female,Loyal Customer,28,Business travel,Eco,503,2,1,1,1,2,2,2,2,2,5,3,4,3,2,16,19.0,neutral or dissatisfied +1803,101817,Female,Loyal Customer,73,Business travel,Eco,1121,2,2,2,2,2,4,4,2,2,2,2,4,2,4,106,69.0,neutral or dissatisfied +1804,120100,Male,disloyal Customer,42,Business travel,Business,1576,4,4,4,4,5,4,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +1805,52598,Male,Loyal Customer,47,Business travel,Eco,160,3,2,2,2,3,3,3,3,5,4,3,2,3,3,0,0.0,satisfied +1806,44025,Male,Loyal Customer,55,Personal Travel,Eco,802,2,2,2,4,3,2,3,3,2,4,4,4,3,3,63,56.0,neutral or dissatisfied +1807,99078,Male,Loyal Customer,51,Business travel,Business,2343,5,5,2,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +1808,55734,Male,Loyal Customer,40,Business travel,Business,2161,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +1809,48778,Male,disloyal Customer,27,Business travel,Business,109,4,4,4,2,4,4,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +1810,103406,Male,Loyal Customer,33,Business travel,Eco,237,2,5,5,5,2,2,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +1811,135,Male,disloyal Customer,56,Business travel,Business,227,3,3,3,1,2,3,3,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +1812,17432,Male,disloyal Customer,18,Business travel,Eco,376,5,3,5,2,2,5,2,2,1,1,3,5,5,2,0,5.0,satisfied +1813,72234,Male,Loyal Customer,32,Business travel,Business,921,4,4,4,4,4,4,4,4,3,5,1,2,1,4,0,0.0,neutral or dissatisfied +1814,22527,Female,disloyal Customer,18,Business travel,Eco,208,5,0,5,4,2,5,4,2,4,5,3,1,5,2,0,0.0,satisfied +1815,61377,Female,disloyal Customer,43,Business travel,Business,679,3,3,3,3,4,3,4,4,5,2,5,5,4,4,0,4.0,neutral or dissatisfied +1816,17730,Male,Loyal Customer,42,Business travel,Eco,383,3,2,4,4,3,3,3,3,1,2,3,1,3,3,73,,neutral or dissatisfied +1817,2883,Male,Loyal Customer,37,Personal Travel,Eco,475,2,1,2,3,1,2,1,1,4,4,3,1,3,1,55,54.0,neutral or dissatisfied +1818,8286,Female,Loyal Customer,38,Personal Travel,Eco,125,2,2,2,3,5,2,5,5,1,4,3,3,3,5,0,0.0,neutral or dissatisfied +1819,59093,Female,Loyal Customer,27,Personal Travel,Eco,1744,4,5,4,3,4,4,4,4,4,5,5,5,5,4,25,29.0,neutral or dissatisfied +1820,69701,Male,Loyal Customer,42,Business travel,Business,1372,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +1821,32642,Female,Loyal Customer,35,Business travel,Business,1796,1,5,5,5,2,4,4,2,2,2,1,4,2,3,0,3.0,neutral or dissatisfied +1822,31232,Female,Loyal Customer,43,Personal Travel,Business,472,3,5,2,1,2,5,3,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +1823,22147,Male,Loyal Customer,18,Personal Travel,Business,633,3,4,3,4,1,3,5,1,3,2,5,4,5,1,0,0.0,neutral or dissatisfied +1824,13716,Male,Loyal Customer,58,Business travel,Business,2800,5,5,5,5,1,3,2,5,5,5,5,1,5,2,126,114.0,satisfied +1825,61879,Female,Loyal Customer,27,Business travel,Business,2521,5,5,3,5,5,5,5,5,3,4,5,4,4,5,0,11.0,satisfied +1826,26818,Female,Loyal Customer,30,Business travel,Eco,224,5,5,3,5,5,5,5,5,3,3,3,1,5,5,0,0.0,satisfied +1827,94412,Male,disloyal Customer,61,Business travel,Business,248,2,2,2,5,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +1828,10037,Male,Loyal Customer,61,Personal Travel,Eco,630,4,5,4,4,3,4,3,3,4,2,4,5,4,3,40,45.0,neutral or dissatisfied +1829,71261,Female,Loyal Customer,13,Personal Travel,Eco,733,0,1,0,4,5,0,5,5,3,1,4,2,4,5,15,8.0,satisfied +1830,50604,Male,Loyal Customer,63,Personal Travel,Eco,421,3,4,3,4,5,3,5,5,1,4,3,4,3,5,6,0.0,neutral or dissatisfied +1831,28201,Male,Loyal Customer,20,Personal Travel,Eco,834,3,5,3,2,5,3,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +1832,91949,Male,Loyal Customer,67,Personal Travel,Eco,2446,3,4,3,5,3,5,5,3,4,4,4,5,5,5,332,,neutral or dissatisfied +1833,66144,Female,Loyal Customer,27,Personal Travel,Eco,583,3,5,3,2,1,3,1,1,5,3,5,3,5,1,51,55.0,neutral or dissatisfied +1834,59544,Male,Loyal Customer,24,Business travel,Business,787,3,3,3,3,5,5,5,5,3,4,5,4,5,5,58,50.0,satisfied +1835,47994,Female,Loyal Customer,34,Business travel,Eco Plus,846,5,5,5,5,5,5,5,5,2,2,1,3,2,5,107,98.0,satisfied +1836,58675,Male,disloyal Customer,16,Business travel,Eco,622,2,2,2,4,1,2,1,1,2,4,3,2,3,1,31,13.0,neutral or dissatisfied +1837,53208,Female,disloyal Customer,22,Business travel,Eco,589,4,3,4,2,5,4,5,5,4,2,5,4,1,5,0,0.0,neutral or dissatisfied +1838,99837,Female,Loyal Customer,54,Business travel,Business,1975,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +1839,4248,Male,Loyal Customer,55,Personal Travel,Eco,1020,4,3,4,5,3,4,3,3,5,3,4,4,5,3,0,25.0,neutral or dissatisfied +1840,102340,Female,Loyal Customer,46,Business travel,Business,2273,2,5,5,5,1,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +1841,12072,Female,Loyal Customer,12,Personal Travel,Eco,351,2,4,2,5,5,2,5,5,4,4,5,3,4,5,0,0.0,neutral or dissatisfied +1842,21234,Male,Loyal Customer,35,Personal Travel,Eco,192,3,2,3,4,1,3,1,1,1,5,3,2,4,1,25,14.0,neutral or dissatisfied +1843,90079,Female,disloyal Customer,45,Business travel,Business,957,5,5,5,2,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +1844,16105,Female,Loyal Customer,52,Personal Travel,Eco,303,4,5,4,5,2,5,4,2,2,4,2,3,2,5,0,0.0,satisfied +1845,128269,Male,Loyal Customer,47,Business travel,Business,2242,1,0,0,4,3,3,3,3,3,0,5,2,3,4,17,17.0,neutral or dissatisfied +1846,113377,Female,disloyal Customer,33,Business travel,Business,397,2,1,1,2,3,1,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +1847,81225,Female,Loyal Customer,46,Business travel,Business,1426,4,4,4,4,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +1848,4800,Male,Loyal Customer,21,Personal Travel,Eco,438,3,3,3,3,3,3,3,1,5,2,3,3,1,3,71,162.0,neutral or dissatisfied +1849,10021,Male,Loyal Customer,34,Personal Travel,Eco Plus,534,3,2,3,3,3,3,3,3,4,5,4,1,4,3,120,111.0,neutral or dissatisfied +1850,107017,Male,Loyal Customer,38,Business travel,Business,3258,5,5,5,5,5,4,5,5,5,5,5,4,5,4,8,0.0,satisfied +1851,120329,Male,Loyal Customer,55,Personal Travel,Eco,268,2,2,2,4,2,2,5,2,2,5,2,4,3,2,0,20.0,neutral or dissatisfied +1852,70058,Female,Loyal Customer,43,Personal Travel,Eco Plus,583,2,1,2,2,4,3,3,1,1,2,1,3,1,1,14,0.0,neutral or dissatisfied +1853,124034,Male,Loyal Customer,47,Personal Travel,Eco,184,2,3,2,4,3,2,2,3,2,5,3,3,4,3,0,0.0,neutral or dissatisfied +1854,77096,Female,Loyal Customer,52,Business travel,Business,1481,5,5,5,5,5,5,5,4,4,5,4,4,4,3,1,0.0,satisfied +1855,87897,Male,disloyal Customer,34,Business travel,Business,270,2,2,2,3,4,2,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +1856,32248,Male,Loyal Customer,55,Business travel,Business,1734,2,2,2,2,4,5,5,5,5,5,5,1,5,5,0,0.0,satisfied +1857,51042,Male,Loyal Customer,44,Personal Travel,Eco,158,4,2,4,4,1,4,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +1858,16595,Male,Loyal Customer,41,Business travel,Business,3324,1,1,1,1,5,5,4,4,4,4,4,5,4,3,12,19.0,satisfied +1859,113927,Female,Loyal Customer,22,Business travel,Business,1750,4,4,4,4,5,5,5,5,5,4,4,3,5,5,13,0.0,satisfied +1860,21931,Female,disloyal Customer,26,Business travel,Eco,500,2,1,2,3,4,2,5,4,4,3,4,2,3,4,15,5.0,neutral or dissatisfied +1861,94158,Male,Loyal Customer,52,Business travel,Business,3335,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +1862,106282,Female,Loyal Customer,59,Business travel,Business,2244,4,2,2,2,1,2,3,4,4,4,4,4,4,3,3,0.0,neutral or dissatisfied +1863,17356,Male,disloyal Customer,47,Business travel,Eco,163,2,0,2,1,3,2,3,3,1,2,4,1,4,3,15,4.0,neutral or dissatisfied +1864,22146,Female,disloyal Customer,14,Business travel,Business,633,4,4,4,2,2,4,2,2,5,3,5,4,4,2,0,0.0,satisfied +1865,81404,Male,Loyal Customer,52,Personal Travel,Eco Plus,874,3,1,3,3,3,3,1,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +1866,88626,Male,Loyal Customer,64,Personal Travel,Eco,270,3,0,3,3,1,3,1,1,5,2,4,3,5,1,4,0.0,neutral or dissatisfied +1867,75850,Female,Loyal Customer,19,Personal Travel,Eco,1440,4,4,4,2,2,4,2,2,4,3,3,3,4,2,0,19.0,satisfied +1868,64677,Male,disloyal Customer,20,Business travel,Business,551,4,5,4,1,1,4,1,1,3,4,4,4,5,1,0,0.0,satisfied +1869,43608,Male,disloyal Customer,40,Business travel,Eco,297,1,0,1,3,2,1,2,2,5,5,4,5,1,2,0,0.0,neutral or dissatisfied +1870,5652,Male,disloyal Customer,27,Business travel,Business,436,4,4,4,5,2,4,2,2,5,5,4,3,4,2,57,54.0,satisfied +1871,89866,Female,Loyal Customer,50,Business travel,Business,1501,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +1872,96730,Female,Loyal Customer,32,Personal Travel,Eco,813,3,0,2,1,3,2,4,3,5,2,3,5,4,3,0,6.0,neutral or dissatisfied +1873,51619,Male,Loyal Customer,29,Business travel,Business,493,2,3,3,3,2,2,2,2,3,2,3,4,4,2,0,0.0,neutral or dissatisfied +1874,24124,Female,Loyal Customer,28,Personal Travel,Eco,584,3,5,3,4,1,3,2,1,3,4,4,5,4,1,21,11.0,neutral or dissatisfied +1875,60497,Female,Loyal Customer,44,Business travel,Business,2441,2,2,2,2,2,5,1,5,5,5,5,1,5,3,13,0.0,satisfied +1876,92961,Female,disloyal Customer,35,Business travel,Business,1694,2,2,2,3,3,2,3,3,4,4,3,3,5,3,0,0.0,neutral or dissatisfied +1877,100835,Male,Loyal Customer,55,Business travel,Business,1970,4,4,2,4,2,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +1878,59056,Female,Loyal Customer,46,Business travel,Business,1723,2,2,2,2,5,3,3,2,2,2,2,4,2,3,5,0.0,neutral or dissatisfied +1879,55953,Male,Loyal Customer,55,Business travel,Business,1620,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +1880,37189,Male,Loyal Customer,33,Business travel,Eco Plus,1237,4,3,1,3,4,4,4,4,3,4,1,1,4,4,0,0.0,satisfied +1881,9958,Female,disloyal Customer,23,Business travel,Eco,457,4,2,4,4,4,4,4,4,1,4,3,4,1,4,290,285.0,neutral or dissatisfied +1882,91372,Female,Loyal Customer,60,Personal Travel,Eco Plus,270,2,2,5,1,5,2,1,4,4,5,1,1,4,1,0,21.0,neutral or dissatisfied +1883,98079,Male,Loyal Customer,40,Personal Travel,Eco,1449,3,2,3,2,4,3,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +1884,125534,Male,Loyal Customer,39,Business travel,Business,226,4,4,4,4,2,5,4,5,5,4,5,4,5,4,4,5.0,satisfied +1885,77572,Male,disloyal Customer,20,Business travel,Eco,731,3,4,4,4,3,4,3,3,5,5,5,5,5,3,3,0.0,neutral or dissatisfied +1886,100517,Male,Loyal Customer,37,Personal Travel,Eco,580,0,2,0,2,1,0,1,1,3,3,2,3,2,1,0,0.0,satisfied +1887,14011,Female,Loyal Customer,57,Business travel,Business,2054,1,4,3,3,1,4,3,2,2,2,1,4,2,2,0,0.0,neutral or dissatisfied +1888,50259,Female,Loyal Customer,48,Business travel,Business,3973,2,2,2,2,2,3,3,3,3,3,2,2,3,1,0,0.0,neutral or dissatisfied +1889,15825,Female,disloyal Customer,59,Business travel,Business,195,2,2,2,1,4,2,4,4,4,5,5,4,5,4,0,0.0,neutral or dissatisfied +1890,41178,Female,Loyal Customer,28,Personal Travel,Eco,468,2,4,3,1,4,3,4,4,5,5,4,4,4,4,5,0.0,neutral or dissatisfied +1891,15146,Female,disloyal Customer,22,Business travel,Eco,912,1,1,1,3,3,1,3,3,3,5,3,4,4,3,0,0.0,neutral or dissatisfied +1892,125633,Female,Loyal Customer,44,Business travel,Business,899,4,4,4,4,4,4,5,5,5,5,5,3,5,5,30,20.0,satisfied +1893,34173,Female,Loyal Customer,41,Business travel,Business,1189,2,1,1,1,1,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +1894,37357,Female,Loyal Customer,42,Business travel,Business,2201,5,5,5,5,5,2,3,5,5,5,5,1,5,3,101,122.0,satisfied +1895,4620,Male,Loyal Customer,10,Personal Travel,Eco,719,1,5,1,1,1,1,1,1,3,5,4,4,5,1,55,73.0,neutral or dissatisfied +1896,100252,Male,Loyal Customer,51,Business travel,Business,2939,5,5,5,5,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +1897,3076,Male,Loyal Customer,46,Business travel,Business,2504,4,4,4,4,4,4,5,3,3,2,3,4,3,5,0,5.0,satisfied +1898,43752,Male,Loyal Customer,38,Business travel,Business,3995,3,3,4,3,5,5,5,4,4,4,4,1,4,5,0,0.0,satisfied +1899,69683,Male,Loyal Customer,25,Business travel,Business,2580,3,3,3,3,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +1900,85830,Male,Loyal Customer,67,Personal Travel,Eco,666,4,3,3,2,5,3,4,5,2,5,4,5,1,5,14,13.0,neutral or dissatisfied +1901,4602,Male,Loyal Customer,39,Personal Travel,Eco Plus,416,5,1,5,3,3,5,4,3,2,1,4,4,4,3,0,0.0,satisfied +1902,26717,Female,Loyal Customer,69,Personal Travel,Eco,581,1,5,1,2,4,4,4,2,2,1,4,3,2,3,0,0.0,neutral or dissatisfied +1903,20540,Male,Loyal Customer,57,Business travel,Business,533,2,4,4,4,5,2,3,2,2,2,2,2,2,4,29,15.0,neutral or dissatisfied +1904,55404,Male,Loyal Customer,30,Business travel,Business,1290,2,2,2,2,5,5,5,5,5,5,4,4,5,5,0,0.0,satisfied +1905,56042,Male,Loyal Customer,27,Business travel,Eco,2586,3,4,4,4,3,3,3,3,4,2,4,3,1,3,20,6.0,neutral or dissatisfied +1906,109100,Female,Loyal Customer,15,Personal Travel,Eco,781,2,5,2,3,2,2,2,2,3,5,5,3,4,2,0,27.0,neutral or dissatisfied +1907,77276,Female,Loyal Customer,48,Business travel,Business,1931,1,1,1,1,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +1908,32876,Male,Loyal Customer,70,Personal Travel,Eco,101,1,5,1,4,4,1,1,4,4,4,4,4,4,4,0,2.0,neutral or dissatisfied +1909,27398,Female,Loyal Customer,31,Business travel,Business,2289,2,2,2,2,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +1910,25616,Male,disloyal Customer,24,Business travel,Eco,666,4,0,4,2,4,1,1,3,5,3,3,1,4,1,209,194.0,satisfied +1911,45119,Male,Loyal Customer,33,Personal Travel,Eco,157,2,5,2,3,2,2,2,2,3,3,5,5,4,2,5,6.0,neutral or dissatisfied +1912,87881,Male,Loyal Customer,13,Personal Travel,Eco Plus,214,2,3,2,3,1,2,1,1,3,4,4,5,4,1,32,18.0,neutral or dissatisfied +1913,30790,Female,Loyal Customer,58,Personal Travel,Eco,895,3,1,3,3,3,2,3,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +1914,88634,Male,Loyal Customer,49,Personal Travel,Eco,406,2,4,2,1,2,2,2,2,2,4,3,3,4,2,2,0.0,neutral or dissatisfied +1915,89521,Female,Loyal Customer,21,Personal Travel,Business,944,2,1,2,3,1,2,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +1916,56375,Male,Loyal Customer,61,Personal Travel,Eco,200,4,3,4,3,4,4,5,4,1,2,4,1,4,4,0,0.0,neutral or dissatisfied +1917,104954,Male,Loyal Customer,66,Personal Travel,Business,337,4,4,4,1,2,5,4,5,5,4,5,3,5,3,16,1.0,satisfied +1918,89518,Female,Loyal Customer,54,Personal Travel,Business,1069,2,2,2,3,4,4,4,4,4,2,4,3,4,3,12,0.0,neutral or dissatisfied +1919,28943,Male,Loyal Customer,23,Business travel,Eco,978,5,2,2,2,5,4,4,5,1,5,1,1,3,5,0,0.0,satisfied +1920,30202,Male,Loyal Customer,34,Business travel,Eco Plus,95,0,0,0,3,5,0,1,5,4,4,1,3,3,5,0,0.0,satisfied +1921,111474,Male,Loyal Customer,61,Personal Travel,Eco Plus,1024,2,5,2,1,4,2,4,4,5,4,2,5,3,4,0,0.0,neutral or dissatisfied +1922,29335,Female,Loyal Customer,8,Personal Travel,Eco,933,4,5,4,2,1,4,1,1,4,2,4,3,5,1,0,1.0,neutral or dissatisfied +1923,105512,Female,Loyal Customer,36,Business travel,Business,1590,2,2,2,2,5,5,4,3,3,3,3,4,3,4,7,6.0,satisfied +1924,37649,Male,Loyal Customer,25,Personal Travel,Eco,944,3,4,3,1,1,3,1,1,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +1925,91334,Male,Loyal Customer,69,Personal Travel,Eco Plus,404,3,5,3,5,2,3,3,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +1926,59034,Male,Loyal Customer,43,Business travel,Business,1744,4,4,4,4,5,5,4,5,5,4,5,3,5,5,107,97.0,satisfied +1927,98748,Female,Loyal Customer,16,Personal Travel,Eco,1290,2,4,2,2,2,2,2,2,5,2,3,5,5,2,0,0.0,neutral or dissatisfied +1928,111172,Male,Loyal Customer,21,Personal Travel,Business,1506,2,5,2,3,1,2,2,1,4,2,3,5,5,1,32,36.0,neutral or dissatisfied +1929,82372,Male,Loyal Customer,39,Business travel,Eco Plus,453,1,0,0,4,4,0,4,4,2,1,3,4,4,4,0,6.0,neutral or dissatisfied +1930,2670,Male,Loyal Customer,25,Personal Travel,Eco,597,1,4,1,2,1,1,1,1,4,5,4,3,4,1,28,27.0,neutral or dissatisfied +1931,110451,Male,Loyal Customer,28,Personal Travel,Eco,925,3,2,4,4,5,4,5,5,1,5,3,4,3,5,10,0.0,neutral or dissatisfied +1932,71345,Male,Loyal Customer,45,Personal Travel,Eco,1514,1,2,0,3,5,0,5,5,4,1,3,2,4,5,14,0.0,neutral or dissatisfied +1933,125679,Male,Loyal Customer,23,Business travel,Business,759,3,4,4,4,3,3,3,3,3,1,2,3,3,3,0,7.0,neutral or dissatisfied +1934,69275,Female,Loyal Customer,59,Personal Travel,Eco,733,3,4,3,3,4,4,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +1935,114632,Female,disloyal Customer,28,Business travel,Business,447,5,5,5,2,3,5,1,3,5,4,5,5,4,3,42,34.0,satisfied +1936,64946,Female,Loyal Customer,63,Business travel,Business,469,3,1,1,1,2,4,3,3,3,3,3,3,3,2,50,37.0,neutral or dissatisfied +1937,97599,Male,Loyal Customer,42,Business travel,Business,3787,2,2,2,2,3,4,4,2,2,2,2,2,2,3,20,17.0,neutral or dissatisfied +1938,41387,Female,disloyal Customer,14,Business travel,Eco,563,2,4,2,3,1,2,1,1,1,5,3,4,4,1,9,18.0,neutral or dissatisfied +1939,31711,Male,Loyal Customer,58,Personal Travel,Eco,967,3,5,3,3,2,3,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +1940,101242,Female,disloyal Customer,24,Business travel,Eco,805,1,0,0,3,3,1,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +1941,27789,Female,Loyal Customer,70,Business travel,Eco,909,1,3,3,3,4,3,3,1,1,1,1,1,1,1,5,30.0,neutral or dissatisfied +1942,45411,Male,Loyal Customer,40,Business travel,Business,3035,4,4,4,4,4,5,2,3,3,2,3,3,3,4,16,22.0,satisfied +1943,97486,Male,Loyal Customer,41,Business travel,Business,2537,2,4,4,4,3,2,2,2,2,2,2,3,2,4,66,46.0,neutral or dissatisfied +1944,28816,Male,Loyal Customer,24,Business travel,Eco,987,0,3,0,3,1,3,1,1,5,4,2,2,4,1,42,22.0,satisfied +1945,108900,Male,Loyal Customer,46,Business travel,Business,1066,1,1,1,1,2,4,4,4,4,4,4,4,4,4,9,0.0,satisfied +1946,83805,Female,Loyal Customer,54,Business travel,Business,2381,5,5,5,5,4,5,4,4,4,4,4,3,4,3,68,66.0,satisfied +1947,21831,Male,Loyal Customer,35,Personal Travel,Eco,640,1,5,1,2,3,1,3,3,3,5,5,3,5,3,11,16.0,neutral or dissatisfied +1948,58004,Female,Loyal Customer,55,Business travel,Business,2455,5,5,5,5,5,4,5,5,5,5,5,3,5,3,23,13.0,satisfied +1949,126550,Female,Loyal Customer,54,Personal Travel,Eco,644,4,4,4,4,4,5,5,4,4,4,4,5,4,4,22,20.0,neutral or dissatisfied +1950,128502,Male,Loyal Customer,19,Personal Travel,Eco,651,3,0,3,3,1,3,1,1,3,1,4,1,4,1,49,98.0,neutral or dissatisfied +1951,64049,Male,Loyal Customer,55,Business travel,Business,3678,2,2,2,2,4,4,5,4,4,5,4,4,4,3,18,38.0,satisfied +1952,71342,Female,Loyal Customer,69,Personal Travel,Eco,1514,2,5,3,2,3,1,4,5,5,3,4,4,4,4,90,140.0,neutral or dissatisfied +1953,43846,Male,Loyal Customer,42,Business travel,Business,2469,1,1,1,1,2,3,4,4,4,4,5,4,4,5,0,1.0,satisfied +1954,64144,Male,Loyal Customer,44,Business travel,Eco,989,3,2,2,2,3,3,3,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +1955,67178,Female,Loyal Customer,13,Personal Travel,Eco,1017,4,4,4,3,4,4,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +1956,41284,Male,Loyal Customer,36,Business travel,Business,3312,1,5,5,5,1,4,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +1957,113497,Female,Loyal Customer,47,Business travel,Business,3735,2,2,2,2,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +1958,71967,Male,Loyal Customer,63,Business travel,Business,1437,2,2,2,2,4,4,4,2,2,2,2,4,2,1,11,12.0,neutral or dissatisfied +1959,61896,Female,Loyal Customer,7,Personal Travel,Eco Plus,2254,2,4,2,1,1,2,1,1,5,4,4,3,4,1,29,5.0,neutral or dissatisfied +1960,68313,Male,Loyal Customer,47,Business travel,Business,2165,5,5,5,5,3,3,5,4,4,4,4,3,4,4,0,4.0,satisfied +1961,3326,Male,Loyal Customer,49,Business travel,Business,3997,4,4,4,4,5,5,4,5,5,4,5,4,5,5,37,77.0,satisfied +1962,59068,Female,Loyal Customer,40,Business travel,Business,1726,5,5,5,5,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +1963,61979,Female,Loyal Customer,50,Personal Travel,Business,2475,2,4,2,3,2,4,4,4,4,2,4,4,4,4,0,96.0,neutral or dissatisfied +1964,22190,Male,Loyal Customer,56,Business travel,Eco,165,5,3,3,3,5,5,5,5,2,2,3,1,2,5,0,1.0,satisfied +1965,76493,Female,Loyal Customer,60,Business travel,Business,516,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +1966,56067,Female,Loyal Customer,37,Personal Travel,Eco,2586,1,4,1,5,1,5,5,3,2,4,4,5,4,5,0,0.0,neutral or dissatisfied +1967,78592,Female,Loyal Customer,50,Business travel,Business,2454,4,5,4,4,3,4,5,4,4,4,4,4,4,5,2,19.0,satisfied +1968,106430,Male,Loyal Customer,57,Business travel,Business,2778,3,3,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +1969,85058,Male,Loyal Customer,19,Personal Travel,Business,696,2,5,2,2,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +1970,34077,Female,Loyal Customer,22,Business travel,Eco Plus,1674,5,1,1,1,5,4,5,5,4,3,5,4,1,5,4,0.0,satisfied +1971,61612,Female,disloyal Customer,27,Business travel,Business,1346,3,2,2,2,3,2,3,3,3,3,4,3,4,3,0,4.0,neutral or dissatisfied +1972,49734,Female,Loyal Customer,65,Business travel,Eco,308,2,4,4,4,5,4,3,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +1973,12775,Female,Loyal Customer,47,Personal Travel,Eco Plus,851,1,5,0,1,3,5,5,1,1,0,1,5,1,4,10,0.0,neutral or dissatisfied +1974,14565,Male,Loyal Customer,29,Personal Travel,Business,986,3,3,3,3,4,3,1,4,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +1975,74353,Male,Loyal Customer,46,Business travel,Business,1171,3,3,3,3,4,4,4,5,2,4,5,4,5,4,315,299.0,satisfied +1976,39575,Male,Loyal Customer,43,Business travel,Business,965,2,2,2,2,3,4,2,5,5,5,5,5,5,2,0,0.0,satisfied +1977,88633,Female,Loyal Customer,55,Personal Travel,Eco,406,2,5,2,5,4,4,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +1978,28323,Male,Loyal Customer,45,Business travel,Business,1588,2,5,5,5,2,4,3,2,2,2,2,2,2,3,16,2.0,neutral or dissatisfied +1979,37106,Female,Loyal Customer,56,Business travel,Eco,1189,4,1,5,1,2,5,5,4,4,4,4,4,4,1,92,92.0,satisfied +1980,917,Female,Loyal Customer,56,Business travel,Business,3870,3,3,3,3,4,4,4,5,5,5,4,5,5,4,0,0.0,satisfied +1981,11170,Female,Loyal Customer,25,Personal Travel,Eco,201,1,3,1,4,4,1,4,4,2,3,1,4,1,4,67,56.0,neutral or dissatisfied +1982,113249,Male,Loyal Customer,47,Personal Travel,Business,386,2,5,2,4,5,4,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +1983,3983,Male,Loyal Customer,47,Personal Travel,Eco,340,2,5,2,3,1,2,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +1984,56864,Female,Loyal Customer,56,Business travel,Business,2565,1,1,2,1,4,5,5,5,3,5,5,5,3,5,13,0.0,satisfied +1985,120620,Male,Loyal Customer,65,Personal Travel,Business,280,1,3,1,5,3,4,3,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +1986,128134,Male,Loyal Customer,23,Business travel,Business,1587,2,2,2,2,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +1987,64890,Male,Loyal Customer,28,Business travel,Business,3291,1,2,3,3,4,3,1,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +1988,24485,Female,disloyal Customer,29,Business travel,Eco,547,3,3,3,3,1,3,1,1,4,4,4,2,3,1,5,11.0,neutral or dissatisfied +1989,103632,Male,disloyal Customer,36,Business travel,Business,405,1,1,1,2,5,1,3,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +1990,23911,Female,Loyal Customer,33,Business travel,Business,2710,4,5,5,5,3,3,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +1991,5847,Male,Loyal Customer,22,Business travel,Business,1020,4,4,4,4,3,4,3,3,5,3,5,5,4,3,0,0.0,satisfied +1992,95341,Male,Loyal Customer,68,Personal Travel,Eco,319,1,5,1,4,5,1,5,5,2,4,2,2,3,5,0,0.0,neutral or dissatisfied +1993,92042,Male,disloyal Customer,49,Business travel,Business,1522,4,5,5,2,3,4,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +1994,49268,Male,disloyal Customer,39,Business travel,Eco,373,2,5,2,3,5,2,5,5,2,4,2,1,2,5,0,0.0,neutral or dissatisfied +1995,28477,Male,Loyal Customer,25,Personal Travel,Eco,1721,1,5,1,2,5,1,5,5,5,3,3,4,4,5,0,4.0,neutral or dissatisfied +1996,117057,Female,Loyal Customer,41,Business travel,Business,2026,3,3,3,3,5,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +1997,106829,Male,Loyal Customer,46,Personal Travel,Eco Plus,1488,3,4,3,3,1,3,1,1,3,3,5,4,5,1,5,0.0,neutral or dissatisfied +1998,98054,Male,Loyal Customer,39,Personal Travel,Eco,1797,4,2,4,4,2,4,2,2,3,2,2,1,3,2,15,12.0,satisfied +1999,104796,Female,Loyal Customer,65,Business travel,Eco,587,2,4,5,4,1,3,3,2,2,2,2,4,2,4,23,26.0,neutral or dissatisfied +2000,80462,Male,Loyal Customer,47,Business travel,Business,2787,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2001,57504,Male,Loyal Customer,54,Personal Travel,Eco,1075,2,4,2,1,2,2,2,2,4,2,4,3,4,2,21,29.0,neutral or dissatisfied +2002,54505,Male,disloyal Customer,31,Business travel,Eco,925,3,3,3,3,4,3,4,4,3,4,1,4,4,4,0,0.0,neutral or dissatisfied +2003,8921,Male,disloyal Customer,34,Business travel,Eco,661,2,3,2,3,2,3,3,3,1,4,3,3,1,3,302,296.0,neutral or dissatisfied +2004,111738,Male,Loyal Customer,42,Business travel,Business,2209,1,1,1,1,3,4,4,4,4,5,4,4,4,4,4,22.0,satisfied +2005,110902,Female,disloyal Customer,62,Business travel,Eco,404,1,1,0,3,2,0,5,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +2006,51592,Female,disloyal Customer,38,Business travel,Eco,370,1,3,1,4,1,1,1,1,2,5,3,3,3,1,62,78.0,neutral or dissatisfied +2007,103095,Male,Loyal Customer,46,Personal Travel,Eco,687,3,4,3,2,3,3,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +2008,42335,Female,Loyal Customer,59,Personal Travel,Eco,550,2,3,2,5,1,5,4,4,4,2,4,5,4,4,73,70.0,neutral or dissatisfied +2009,18526,Male,disloyal Customer,44,Business travel,Eco,253,3,3,3,1,3,3,3,3,2,3,5,4,5,3,0,0.0,neutral or dissatisfied +2010,51379,Female,Loyal Customer,8,Personal Travel,Eco Plus,110,4,3,4,4,3,4,3,3,1,2,2,1,4,3,0,0.0,neutral or dissatisfied +2011,106850,Male,Loyal Customer,54,Personal Travel,Eco,1733,2,3,2,5,1,2,1,1,5,2,4,3,1,1,28,14.0,neutral or dissatisfied +2012,39478,Male,Loyal Customer,26,Business travel,Business,3376,3,3,3,3,3,3,3,3,4,3,4,4,3,3,56,49.0,neutral or dissatisfied +2013,94305,Female,Loyal Customer,58,Business travel,Business,248,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +2014,59706,Female,Loyal Customer,13,Personal Travel,Eco,861,2,5,3,3,2,3,2,2,3,3,4,3,4,2,0,21.0,neutral or dissatisfied +2015,12883,Female,Loyal Customer,55,Business travel,Eco,809,5,1,1,1,2,1,2,5,5,5,5,5,5,2,0,0.0,satisfied +2016,40410,Female,Loyal Customer,43,Business travel,Business,2920,4,4,3,4,5,2,2,5,5,5,4,1,5,5,0,0.0,satisfied +2017,81230,Female,Loyal Customer,57,Business travel,Business,3967,3,3,3,3,5,5,5,4,4,4,5,5,4,5,0,0.0,satisfied +2018,17844,Male,Loyal Customer,30,Business travel,Eco Plus,505,4,3,3,3,4,4,4,4,4,5,3,5,4,4,0,0.0,satisfied +2019,61987,Female,Loyal Customer,49,Business travel,Business,2475,3,3,3,3,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2020,48586,Female,Loyal Customer,24,Personal Travel,Eco,853,2,4,3,1,3,3,3,3,4,2,4,5,4,3,0,11.0,neutral or dissatisfied +2021,69935,Female,Loyal Customer,59,Business travel,Business,2174,3,3,3,3,3,3,5,4,4,5,4,5,4,5,0,0.0,satisfied +2022,114974,Male,Loyal Customer,44,Business travel,Business,3691,4,4,4,4,4,5,5,4,4,4,4,3,4,3,46,33.0,satisfied +2023,123886,Female,disloyal Customer,37,Business travel,Eco,173,1,3,1,3,4,1,4,4,3,2,1,1,1,4,0,0.0,neutral or dissatisfied +2024,102875,Female,disloyal Customer,25,Business travel,Eco,472,4,0,4,5,3,4,3,3,3,4,3,2,2,3,0,0.0,satisfied +2025,55049,Female,Loyal Customer,53,Business travel,Business,1346,2,2,3,2,5,5,4,4,4,5,4,3,4,3,2,0.0,satisfied +2026,69832,Female,disloyal Customer,21,Business travel,Business,1055,5,5,5,3,5,5,5,5,4,3,4,3,4,5,12,4.0,satisfied +2027,114318,Female,Loyal Customer,64,Personal Travel,Eco,850,3,5,3,2,5,4,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +2028,16546,Female,disloyal Customer,35,Business travel,Eco Plus,1134,1,1,1,5,2,1,2,2,1,4,2,3,2,2,1,5.0,neutral or dissatisfied +2029,55251,Female,Loyal Customer,17,Personal Travel,Eco,1009,4,2,4,2,2,4,5,2,2,3,3,2,2,2,0,0.0,neutral or dissatisfied +2030,56875,Female,disloyal Customer,20,Business travel,Business,2434,5,5,5,2,5,4,4,5,4,4,4,4,5,4,2,0.0,satisfied +2031,105676,Male,Loyal Customer,58,Business travel,Business,3463,1,1,1,1,3,5,5,5,5,5,5,5,5,4,0,5.0,satisfied +2032,14702,Male,Loyal Customer,38,Business travel,Eco,419,3,4,3,4,3,3,3,3,2,2,3,4,4,3,1,0.0,neutral or dissatisfied +2033,40847,Male,Loyal Customer,9,Personal Travel,Eco,574,4,5,4,3,2,4,2,2,5,2,5,5,4,2,0,1.0,satisfied +2034,39059,Female,disloyal Customer,16,Business travel,Eco,784,0,0,0,2,1,0,1,1,5,5,4,4,4,1,0,0.0,satisfied +2035,8658,Male,Loyal Customer,50,Business travel,Business,227,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +2036,43862,Female,Loyal Customer,37,Business travel,Business,2950,0,4,0,2,4,4,4,5,5,5,5,2,5,3,0,0.0,satisfied +2037,109435,Female,Loyal Customer,52,Business travel,Business,1538,4,4,4,4,4,5,5,2,2,2,2,3,2,3,69,48.0,satisfied +2038,25873,Female,disloyal Customer,29,Business travel,Business,907,2,2,2,1,4,2,4,4,3,2,4,4,4,4,93,91.0,neutral or dissatisfied +2039,7979,Male,Loyal Customer,60,Business travel,Business,2845,4,5,4,4,4,5,5,4,4,4,4,3,4,4,46,45.0,satisfied +2040,108078,Male,Loyal Customer,45,Business travel,Business,997,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,12.0,satisfied +2041,123659,Female,disloyal Customer,21,Business travel,Business,214,4,0,4,5,5,4,5,5,4,2,4,5,5,5,0,0.0,satisfied +2042,90036,Male,disloyal Customer,39,Business travel,Business,957,1,0,0,5,3,0,3,3,5,5,4,4,5,3,62,55.0,neutral or dissatisfied +2043,44351,Female,Loyal Customer,52,Business travel,Business,2798,3,3,3,3,5,4,4,5,2,5,5,4,4,4,136,125.0,satisfied +2044,7661,Female,disloyal Customer,40,Business travel,Business,604,3,2,2,3,3,2,3,3,1,2,3,2,4,3,0,0.0,neutral or dissatisfied +2045,27798,Male,disloyal Customer,38,Business travel,Eco,1448,1,1,1,2,4,1,4,4,3,2,2,1,3,4,7,0.0,neutral or dissatisfied +2046,116652,Female,disloyal Customer,26,Business travel,Business,358,3,4,3,1,3,3,3,3,4,2,4,4,5,3,0,0.0,neutral or dissatisfied +2047,92078,Male,Loyal Customer,17,Business travel,Business,1589,3,4,4,4,3,3,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +2048,92099,Female,Loyal Customer,16,Business travel,Business,1535,5,5,5,5,4,4,4,4,5,4,1,2,4,4,0,0.0,satisfied +2049,11082,Male,Loyal Customer,15,Personal Travel,Eco,309,3,4,3,1,3,3,1,3,5,3,4,5,4,3,5,16.0,neutral or dissatisfied +2050,112959,Female,Loyal Customer,62,Personal Travel,Eco,1164,1,4,1,1,4,4,5,4,4,1,4,5,4,5,29,25.0,neutral or dissatisfied +2051,102298,Male,Loyal Customer,35,Business travel,Business,1882,1,1,1,1,3,5,5,4,4,4,5,5,4,4,2,0.0,satisfied +2052,64496,Male,Loyal Customer,52,Business travel,Business,190,1,1,1,1,3,2,3,4,4,4,1,3,4,3,0,0.0,neutral or dissatisfied +2053,68780,Female,disloyal Customer,25,Business travel,Eco,926,2,2,2,3,4,2,4,4,4,3,4,2,3,4,10,6.0,neutral or dissatisfied +2054,121694,Female,Loyal Customer,61,Personal Travel,Eco Plus,328,2,2,2,4,2,3,3,5,5,2,5,2,5,1,8,3.0,neutral or dissatisfied +2055,12841,Female,Loyal Customer,29,Personal Travel,Eco,489,2,3,2,3,3,2,3,3,4,4,3,3,4,3,13,12.0,neutral or dissatisfied +2056,19282,Male,Loyal Customer,79,Business travel,Eco Plus,430,5,2,2,2,5,5,5,5,4,5,3,5,5,5,0,0.0,satisfied +2057,4534,Female,Loyal Customer,8,Personal Travel,Eco,677,3,4,3,1,3,3,3,3,2,1,1,1,5,3,0,0.0,neutral or dissatisfied +2058,128695,Male,disloyal Customer,24,Business travel,Business,1235,5,0,5,4,5,5,4,5,4,2,5,5,5,5,0,0.0,satisfied +2059,119633,Female,disloyal Customer,43,Business travel,Business,1727,2,1,1,4,5,2,3,5,5,5,4,5,5,5,17,47.0,neutral or dissatisfied +2060,58442,Female,Loyal Customer,20,Personal Travel,Eco,733,1,5,1,1,1,1,1,1,5,5,5,1,5,1,0,0.0,neutral or dissatisfied +2061,19037,Female,Loyal Customer,24,Business travel,Eco Plus,788,4,2,1,2,4,4,4,4,5,3,5,3,2,4,0,0.0,satisfied +2062,58669,Female,disloyal Customer,36,Business travel,Business,867,4,4,4,4,4,4,3,4,4,5,5,3,5,4,29,49.0,neutral or dissatisfied +2063,129152,Female,disloyal Customer,26,Business travel,Business,679,3,5,3,4,1,3,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +2064,89332,Female,disloyal Customer,38,Business travel,Business,1587,3,3,3,2,5,3,5,5,3,5,5,4,5,5,0,18.0,neutral or dissatisfied +2065,35046,Male,Loyal Customer,43,Business travel,Business,1746,5,5,5,5,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +2066,102314,Male,disloyal Customer,39,Business travel,Eco,397,3,0,3,3,2,3,2,2,3,3,4,2,4,2,29,22.0,neutral or dissatisfied +2067,30321,Male,Loyal Customer,61,Business travel,Business,3346,4,4,4,4,4,3,1,5,5,5,5,1,5,2,17,25.0,satisfied +2068,108708,Female,Loyal Customer,45,Business travel,Business,425,1,1,1,1,1,2,2,1,1,1,1,2,1,1,28,22.0,neutral or dissatisfied +2069,54119,Female,Loyal Customer,41,Business travel,Eco,1372,5,4,4,4,5,5,5,5,4,2,2,1,2,5,0,0.0,satisfied +2070,74349,Female,Loyal Customer,59,Business travel,Business,1464,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +2071,13770,Male,Loyal Customer,35,Business travel,Eco,925,4,3,3,3,4,4,4,4,4,5,4,4,5,4,34,35.0,satisfied +2072,129765,Male,Loyal Customer,21,Personal Travel,Eco,308,4,3,4,2,3,4,3,3,3,2,4,1,2,3,0,0.0,satisfied +2073,6210,Male,Loyal Customer,38,Business travel,Business,462,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +2074,89387,Male,disloyal Customer,23,Business travel,Eco,134,2,4,2,4,4,2,4,4,1,1,3,3,3,4,15,6.0,neutral or dissatisfied +2075,3223,Female,Loyal Customer,41,Business travel,Business,2901,3,2,2,2,3,2,3,3,3,3,3,4,3,3,0,10.0,neutral or dissatisfied +2076,92002,Male,Loyal Customer,51,Business travel,Business,1532,5,5,5,5,4,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +2077,47806,Male,disloyal Customer,19,Business travel,Eco,315,5,2,5,3,2,5,2,2,1,1,4,3,2,2,0,0.0,satisfied +2078,67708,Female,Loyal Customer,38,Business travel,Business,2944,2,2,2,2,3,5,4,2,2,2,2,5,2,3,4,0.0,satisfied +2079,113954,Male,disloyal Customer,36,Business travel,Business,1706,2,2,2,5,4,2,4,4,4,5,3,3,5,4,0,0.0,neutral or dissatisfied +2080,22053,Female,Loyal Customer,27,Business travel,Business,304,4,4,4,4,5,5,5,5,2,2,3,3,4,5,0,0.0,satisfied +2081,83444,Female,Loyal Customer,55,Business travel,Business,946,3,3,3,3,5,4,4,2,2,2,2,3,2,5,2,0.0,satisfied +2082,1908,Male,disloyal Customer,46,Business travel,Business,383,4,4,4,4,3,4,2,3,5,4,4,5,5,3,25,7.0,satisfied +2083,117675,Male,disloyal Customer,31,Business travel,Business,1814,1,1,1,2,1,1,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +2084,459,Male,Loyal Customer,59,Business travel,Business,134,1,1,1,1,2,4,4,4,4,4,5,3,4,5,0,10.0,satisfied +2085,24804,Male,Loyal Customer,31,Personal Travel,Business,894,4,4,4,2,3,4,1,3,3,2,4,5,4,3,14,11.0,neutral or dissatisfied +2086,87641,Male,Loyal Customer,36,Business travel,Eco,606,2,3,3,3,2,2,2,2,2,3,4,3,3,2,0,0.0,neutral or dissatisfied +2087,61087,Male,Loyal Customer,41,Personal Travel,Eco,1546,3,5,3,2,2,3,2,2,5,5,5,3,5,2,0,0.0,neutral or dissatisfied +2088,89068,Male,disloyal Customer,25,Business travel,Eco,732,5,5,5,3,4,5,4,4,3,2,4,5,4,4,0,0.0,satisfied +2089,88680,Female,Loyal Customer,31,Personal Travel,Eco,444,2,4,2,3,1,2,1,1,4,1,2,3,1,1,0,0.0,neutral or dissatisfied +2090,27794,Female,Loyal Customer,47,Business travel,Business,1448,3,3,3,3,4,2,2,3,3,3,3,5,3,3,2,0.0,satisfied +2091,35815,Male,Loyal Customer,43,Business travel,Business,1677,5,5,5,5,4,2,4,2,2,2,2,1,2,2,0,0.0,satisfied +2092,20977,Male,Loyal Customer,64,Personal Travel,Eco,689,3,3,3,4,1,3,1,1,2,4,3,3,4,1,73,66.0,neutral or dissatisfied +2093,68418,Female,Loyal Customer,53,Personal Travel,Eco,1045,3,5,3,3,4,5,5,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +2094,3668,Male,Loyal Customer,65,Business travel,Eco,431,4,5,5,5,4,4,4,4,4,2,2,4,1,4,70,85.0,neutral or dissatisfied +2095,88597,Male,Loyal Customer,56,Personal Travel,Eco,366,3,4,1,1,4,1,4,4,3,4,5,1,3,4,2,2.0,neutral or dissatisfied +2096,121184,Female,Loyal Customer,62,Personal Travel,Eco,2402,3,3,3,5,3,5,5,2,2,3,1,5,3,5,0,17.0,neutral or dissatisfied +2097,112036,Female,Loyal Customer,58,Business travel,Business,2948,4,4,4,4,2,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +2098,123423,Male,Loyal Customer,64,Personal Travel,Eco,1337,3,5,3,3,4,3,4,4,5,5,4,4,5,4,0,8.0,neutral or dissatisfied +2099,44212,Female,disloyal Customer,38,Business travel,Business,222,1,1,1,5,5,1,3,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +2100,65610,Male,disloyal Customer,35,Business travel,Eco,175,2,0,2,2,4,2,2,4,5,1,2,4,4,4,0,0.0,neutral or dissatisfied +2101,73530,Female,disloyal Customer,39,Business travel,Business,594,3,3,3,4,5,3,5,5,4,2,5,5,5,5,7,5.0,neutral or dissatisfied +2102,63779,Female,disloyal Customer,27,Business travel,Business,1721,2,2,2,2,4,2,4,4,5,2,5,5,4,4,60,47.0,neutral or dissatisfied +2103,52260,Male,Loyal Customer,44,Business travel,Eco,261,5,5,5,5,5,5,5,5,2,1,1,4,5,5,0,0.0,satisfied +2104,13210,Female,Loyal Customer,57,Business travel,Business,2084,3,4,3,4,3,2,3,3,3,2,3,1,3,1,0,2.0,neutral or dissatisfied +2105,31077,Female,Loyal Customer,29,Business travel,Eco Plus,641,0,0,0,3,4,0,4,4,4,3,1,4,5,4,0,0.0,satisfied +2106,34755,Male,Loyal Customer,56,Business travel,Eco,264,2,4,4,4,2,2,2,2,1,4,2,2,3,2,0,0.0,neutral or dissatisfied +2107,60891,Female,disloyal Customer,37,Business travel,Business,420,2,2,2,2,2,2,2,2,3,4,5,4,5,2,14,39.0,neutral or dissatisfied +2108,73502,Female,disloyal Customer,25,Business travel,Business,1197,5,0,5,2,5,3,3,4,5,4,5,3,4,3,154,149.0,satisfied +2109,10327,Female,Loyal Customer,57,Business travel,Business,3582,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +2110,90094,Female,disloyal Customer,23,Business travel,Eco,983,2,2,2,3,2,2,3,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +2111,79416,Male,Loyal Customer,25,Personal Travel,Eco,502,2,2,2,4,3,2,3,3,2,1,4,2,3,3,18,13.0,neutral or dissatisfied +2112,98342,Female,Loyal Customer,29,Business travel,Business,1046,5,5,5,5,5,4,5,5,5,3,4,4,5,5,0,0.0,satisfied +2113,10554,Male,Loyal Customer,45,Business travel,Business,2150,3,3,3,3,2,5,5,3,3,3,3,3,3,5,34,35.0,satisfied +2114,74817,Male,Loyal Customer,12,Personal Travel,Eco Plus,1188,1,5,1,1,2,1,2,2,4,5,3,5,4,2,0,2.0,neutral or dissatisfied +2115,120053,Female,disloyal Customer,32,Business travel,Business,237,3,3,3,3,4,3,2,4,3,2,5,3,4,4,0,43.0,neutral or dissatisfied +2116,69288,Female,Loyal Customer,44,Business travel,Business,2968,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +2117,97200,Male,Loyal Customer,58,Personal Travel,Eco,1211,1,1,0,3,5,0,5,5,3,4,4,3,3,5,9,22.0,neutral or dissatisfied +2118,45203,Female,Loyal Customer,49,Business travel,Business,2496,3,5,2,5,5,1,1,3,3,3,3,4,3,1,44,31.0,neutral or dissatisfied +2119,129132,Female,Loyal Customer,49,Business travel,Business,3618,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +2120,39727,Male,Loyal Customer,34,Business travel,Eco,298,4,2,2,2,4,4,4,4,1,4,4,2,3,4,0,0.0,satisfied +2121,37564,Male,Loyal Customer,37,Business travel,Business,3444,3,3,3,3,3,5,2,4,4,4,4,2,4,4,0,0.0,satisfied +2122,118326,Male,disloyal Customer,25,Business travel,Business,602,1,0,1,4,5,1,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +2123,100389,Male,Loyal Customer,37,Personal Travel,Eco,1073,3,4,4,4,2,4,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +2124,65506,Female,Loyal Customer,27,Personal Travel,Eco Plus,1303,4,5,4,1,2,4,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +2125,74094,Male,disloyal Customer,47,Business travel,Business,769,2,2,2,5,2,2,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +2126,59007,Female,Loyal Customer,59,Business travel,Business,1744,5,5,5,5,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +2127,105632,Male,Loyal Customer,60,Business travel,Business,3301,2,2,2,2,2,4,5,4,4,4,4,3,4,4,19,27.0,satisfied +2128,59032,Male,Loyal Customer,24,Business travel,Business,1726,3,1,1,1,3,2,3,3,1,2,3,1,4,3,2,0.0,neutral or dissatisfied +2129,5418,Male,disloyal Customer,40,Business travel,Business,589,3,3,3,2,2,3,2,2,3,4,5,5,4,2,21,6.0,satisfied +2130,110905,Male,Loyal Customer,22,Business travel,Eco,581,3,3,3,3,3,3,4,3,2,5,3,1,3,3,1,2.0,neutral or dissatisfied +2131,98945,Male,Loyal Customer,44,Business travel,Business,1778,2,2,2,2,2,5,5,4,4,4,4,4,4,5,23,20.0,satisfied +2132,37810,Male,Loyal Customer,32,Personal Travel,Eco Plus,1028,2,2,2,3,4,2,4,4,2,1,3,2,4,4,69,63.0,neutral or dissatisfied +2133,16940,Male,Loyal Customer,45,Business travel,Business,1776,3,2,2,2,3,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +2134,112638,Female,Loyal Customer,31,Personal Travel,Eco Plus,639,4,1,4,4,1,4,1,1,2,2,3,3,3,1,0,7.0,neutral or dissatisfied +2135,112380,Male,Loyal Customer,59,Business travel,Business,3243,3,3,3,3,4,4,4,5,5,5,5,5,5,4,57,44.0,satisfied +2136,102377,Female,disloyal Customer,25,Business travel,Eco,258,3,4,3,3,5,3,2,5,3,2,5,5,1,5,1,5.0,neutral or dissatisfied +2137,125132,Male,Loyal Customer,68,Personal Travel,Eco,361,4,4,4,5,3,4,3,3,5,4,4,5,5,3,0,0.0,satisfied +2138,3099,Female,Loyal Customer,25,Personal Travel,Eco,594,0,2,0,4,2,2,2,2,4,3,3,2,4,2,0,3.0,satisfied +2139,102558,Female,Loyal Customer,8,Personal Travel,Eco,236,1,4,1,4,3,1,3,3,5,5,5,5,5,3,9,14.0,neutral or dissatisfied +2140,126687,Female,Loyal Customer,56,Business travel,Business,2402,4,4,4,4,4,3,4,5,5,5,5,3,5,3,26,0.0,satisfied +2141,42322,Male,Loyal Customer,26,Personal Travel,Eco,817,1,2,1,2,4,1,4,4,2,2,2,4,3,4,0,0.0,neutral or dissatisfied +2142,2990,Male,Loyal Customer,52,Business travel,Business,522,3,3,3,3,5,4,5,5,5,5,5,4,5,3,0,4.0,satisfied +2143,102781,Male,Loyal Customer,60,Business travel,Business,2385,5,5,5,5,5,4,5,4,4,4,4,3,4,4,15,0.0,satisfied +2144,47909,Male,Loyal Customer,56,Business travel,Business,3912,1,1,1,1,5,3,3,4,4,3,1,3,4,1,29,20.0,neutral or dissatisfied +2145,26745,Male,Loyal Customer,54,Personal Travel,Business,859,1,4,1,3,4,5,4,3,3,1,2,3,3,3,0,6.0,neutral or dissatisfied +2146,8699,Male,disloyal Customer,17,Business travel,Business,227,2,1,2,4,1,2,1,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +2147,136,Female,Loyal Customer,43,Business travel,Business,2029,2,2,2,2,2,5,4,4,4,4,4,4,4,4,4,15.0,satisfied +2148,95403,Female,Loyal Customer,39,Personal Travel,Eco,239,4,5,4,3,3,4,3,3,3,4,4,5,4,3,61,57.0,neutral or dissatisfied +2149,14586,Female,disloyal Customer,25,Business travel,Eco,986,2,2,2,4,2,2,2,2,2,4,3,1,4,2,4,10.0,neutral or dissatisfied +2150,118660,Female,disloyal Customer,45,Business travel,Eco,304,3,4,3,4,4,3,2,4,3,4,4,2,4,4,23,21.0,neutral or dissatisfied +2151,26291,Female,disloyal Customer,22,Business travel,Eco,1199,4,4,4,4,4,4,4,4,5,1,2,1,2,4,0,33.0,satisfied +2152,19874,Male,Loyal Customer,16,Business travel,Business,2912,5,5,5,5,5,5,5,5,5,4,5,3,4,5,0,0.0,satisfied +2153,47113,Female,Loyal Customer,70,Business travel,Business,3405,4,4,4,4,2,1,3,2,2,2,2,2,2,2,11,0.0,satisfied +2154,26413,Female,Loyal Customer,30,Business travel,Eco Plus,1249,5,4,4,4,5,5,5,5,2,1,4,2,1,5,1,0.0,satisfied +2155,23807,Male,Loyal Customer,33,Personal Travel,Eco,374,2,4,2,4,4,2,4,4,3,5,4,5,4,4,0,24.0,neutral or dissatisfied +2156,53657,Female,Loyal Customer,32,Business travel,Business,2762,2,2,4,2,3,3,3,3,5,2,4,5,5,3,0,0.0,satisfied +2157,54780,Male,Loyal Customer,52,Personal Travel,Eco Plus,854,2,5,1,3,4,1,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +2158,36903,Female,Loyal Customer,30,Business travel,Eco,2072,3,4,4,4,3,3,3,3,2,1,4,2,4,3,56,79.0,neutral or dissatisfied +2159,30055,Female,disloyal Customer,39,Business travel,Eco,183,3,5,3,2,1,3,1,1,4,1,4,5,1,1,0,0.0,neutral or dissatisfied +2160,93237,Male,Loyal Customer,39,Personal Travel,Eco,1694,3,4,2,4,2,2,5,2,3,1,4,1,1,2,6,3.0,neutral or dissatisfied +2161,34021,Female,Loyal Customer,60,Personal Travel,Eco,1598,2,2,2,4,5,4,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +2162,3052,Female,Loyal Customer,58,Business travel,Business,2529,3,3,3,3,5,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +2163,68626,Male,Loyal Customer,40,Business travel,Business,2433,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2164,77784,Female,Loyal Customer,30,Personal Travel,Eco,696,2,5,2,3,5,2,5,5,4,3,4,4,4,5,4,0.0,neutral or dissatisfied +2165,18571,Female,Loyal Customer,44,Business travel,Business,201,2,2,2,2,1,2,5,5,5,5,5,5,5,4,0,0.0,satisfied +2166,89098,Male,Loyal Customer,42,Business travel,Business,1947,5,5,5,5,5,4,4,5,5,5,5,5,5,4,3,0.0,satisfied +2167,126711,Male,disloyal Customer,46,Business travel,Business,2521,3,3,3,3,5,3,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +2168,72895,Female,Loyal Customer,21,Personal Travel,Business,1096,1,3,1,3,5,1,1,5,2,1,4,1,4,5,31,33.0,neutral or dissatisfied +2169,8306,Female,Loyal Customer,51,Business travel,Business,3596,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +2170,79018,Female,disloyal Customer,33,Business travel,Business,356,2,3,3,2,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +2171,52591,Male,Loyal Customer,37,Business travel,Eco,119,3,5,5,5,3,3,3,3,3,2,4,2,4,3,3,1.0,neutral or dissatisfied +2172,824,Female,Loyal Customer,54,Business travel,Business,2538,0,0,0,1,4,5,4,4,4,4,4,3,4,3,0,1.0,satisfied +2173,42625,Female,Loyal Customer,44,Business travel,Business,2913,2,2,2,2,3,2,5,3,3,4,3,4,3,2,0,0.0,satisfied +2174,104537,Male,Loyal Customer,72,Business travel,Eco,856,4,4,4,4,4,4,4,4,2,3,3,2,4,4,20,3.0,satisfied +2175,45319,Male,disloyal Customer,43,Business travel,Eco,188,3,2,4,4,5,4,5,5,3,4,4,2,3,5,0,0.0,neutral or dissatisfied +2176,116198,Male,Loyal Customer,34,Personal Travel,Eco,417,3,5,3,3,2,3,5,2,5,5,2,4,5,2,0,0.0,neutral or dissatisfied +2177,120322,Female,Loyal Customer,23,Personal Travel,Eco,268,1,3,0,3,2,0,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +2178,89016,Female,Loyal Customer,54,Business travel,Business,1947,1,3,3,3,5,3,2,1,1,1,1,3,1,1,5,0.0,neutral or dissatisfied +2179,97468,Male,Loyal Customer,14,Business travel,Eco,822,2,1,2,1,2,3,2,2,1,4,3,1,4,2,26,13.0,neutral or dissatisfied +2180,117414,Female,Loyal Customer,52,Business travel,Business,1460,1,1,4,1,5,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +2181,26999,Female,Loyal Customer,30,Business travel,Business,1998,3,3,3,3,5,5,5,5,1,2,5,3,5,5,0,0.0,satisfied +2182,60793,Female,Loyal Customer,53,Business travel,Business,1922,4,4,4,4,4,4,4,4,4,4,4,3,4,5,25,44.0,satisfied +2183,81993,Male,Loyal Customer,8,Business travel,Business,1535,1,3,3,3,1,1,1,1,2,2,3,3,3,1,36,6.0,neutral or dissatisfied +2184,90687,Female,Loyal Customer,51,Business travel,Eco,581,3,1,1,1,4,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +2185,80909,Male,disloyal Customer,23,Business travel,Eco,352,4,2,4,3,5,4,5,5,3,3,4,1,4,5,1,10.0,neutral or dissatisfied +2186,121064,Male,Loyal Customer,46,Business travel,Business,3270,5,5,5,5,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +2187,64280,Female,Loyal Customer,44,Business travel,Business,3856,3,3,2,3,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +2188,54795,Female,disloyal Customer,20,Business travel,Eco,775,3,3,3,4,5,3,3,5,3,5,5,2,3,5,0,0.0,neutral or dissatisfied +2189,3126,Female,Loyal Customer,23,Personal Travel,Eco,1013,5,2,5,2,2,5,2,2,1,4,2,4,2,2,0,0.0,satisfied +2190,51715,Male,Loyal Customer,69,Personal Travel,Eco,355,4,4,4,3,3,4,3,3,5,4,4,3,4,3,0,0.0,satisfied +2191,76658,Female,Loyal Customer,63,Personal Travel,Eco,516,1,4,1,4,3,5,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +2192,13735,Female,disloyal Customer,25,Business travel,Eco,441,3,1,3,3,5,3,5,5,2,5,4,3,3,5,21,12.0,neutral or dissatisfied +2193,24230,Female,disloyal Customer,27,Business travel,Eco,302,2,4,2,3,3,2,3,3,3,1,3,2,3,3,17,56.0,neutral or dissatisfied +2194,99923,Male,disloyal Customer,24,Business travel,Eco,764,2,3,3,1,4,3,4,4,5,5,5,3,5,4,3,0.0,neutral or dissatisfied +2195,112342,Female,disloyal Customer,27,Business travel,Business,850,3,3,3,2,1,3,1,1,3,2,5,3,4,1,0,2.0,neutral or dissatisfied +2196,47836,Female,Loyal Customer,37,Business travel,Business,1953,2,2,2,2,4,5,2,2,2,2,2,1,2,4,0,0.0,satisfied +2197,15820,Female,Loyal Customer,26,Business travel,Eco Plus,246,4,4,5,4,4,4,3,4,3,3,2,4,2,4,0,0.0,satisfied +2198,37566,Female,disloyal Customer,39,Business travel,Eco,674,5,5,5,1,3,5,3,3,3,4,3,1,2,3,85,96.0,satisfied +2199,5717,Female,Loyal Customer,65,Personal Travel,Eco,299,3,4,5,4,2,5,4,5,5,5,2,5,5,4,22,28.0,neutral or dissatisfied +2200,4305,Female,disloyal Customer,27,Business travel,Business,502,2,2,2,2,3,2,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +2201,94899,Male,disloyal Customer,80,Business travel,Business,277,4,4,4,5,1,3,2,3,3,4,3,3,3,1,34,33.0,satisfied +2202,56512,Male,Loyal Customer,55,Business travel,Business,937,5,5,5,5,3,5,4,4,4,5,4,3,4,3,18,6.0,satisfied +2203,48281,Female,Loyal Customer,29,Personal Travel,Eco Plus,236,3,2,3,3,3,3,5,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +2204,83967,Male,Loyal Customer,55,Business travel,Business,2917,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,12.0,satisfied +2205,50157,Male,Loyal Customer,33,Business travel,Business,1503,5,2,2,2,5,4,5,5,3,1,2,4,3,5,8,8.0,neutral or dissatisfied +2206,25842,Female,Loyal Customer,28,Business travel,Business,2137,5,5,4,5,4,4,4,4,1,1,5,1,4,4,0,0.0,satisfied +2207,99832,Female,disloyal Customer,43,Business travel,Business,587,3,3,3,4,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +2208,115911,Female,disloyal Customer,55,Business travel,Eco,308,4,4,4,4,1,4,1,1,2,5,3,4,3,1,97,94.0,neutral or dissatisfied +2209,63420,Female,Loyal Customer,49,Personal Travel,Eco,447,4,5,4,2,5,5,5,2,2,4,3,3,2,3,0,0.0,satisfied +2210,101451,Female,Loyal Customer,38,Business travel,Business,345,1,1,1,1,3,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +2211,52512,Male,Loyal Customer,53,Business travel,Business,2475,1,1,1,1,1,5,2,4,4,4,5,4,4,3,0,2.0,satisfied +2212,31017,Male,Loyal Customer,18,Personal Travel,Eco,391,2,5,2,3,4,2,4,4,3,3,5,1,5,4,12,6.0,neutral or dissatisfied +2213,70901,Male,Loyal Customer,24,Business travel,Business,1721,2,2,2,2,2,2,2,2,2,5,2,4,4,2,12,39.0,neutral or dissatisfied +2214,23034,Female,Loyal Customer,40,Personal Travel,Eco,927,3,3,3,1,5,3,5,5,4,3,1,2,4,5,0,0.0,neutral or dissatisfied +2215,24778,Female,disloyal Customer,11,Business travel,Eco,528,1,0,1,4,3,1,1,3,1,5,4,1,5,3,0,0.0,neutral or dissatisfied +2216,95654,Male,Loyal Customer,53,Business travel,Business,2435,3,4,4,4,2,2,3,3,3,3,3,1,3,3,36,37.0,neutral or dissatisfied +2217,101779,Female,Loyal Customer,25,Personal Travel,Business,1521,2,5,2,4,3,2,3,3,3,3,5,3,4,3,23,44.0,neutral or dissatisfied +2218,76095,Male,Loyal Customer,49,Personal Travel,Eco,669,5,4,4,3,5,4,5,5,5,4,5,4,4,5,8,0.0,satisfied +2219,7951,Female,Loyal Customer,47,Business travel,Business,594,3,3,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +2220,40486,Female,Loyal Customer,54,Personal Travel,Eco,461,3,5,3,2,3,3,1,5,5,3,5,3,5,5,0,3.0,neutral or dissatisfied +2221,43640,Male,Loyal Customer,23,Business travel,Business,3130,5,5,5,5,1,2,1,1,4,5,3,2,4,1,35,53.0,satisfied +2222,85829,Female,Loyal Customer,27,Personal Travel,Eco,666,2,4,2,5,2,2,2,2,3,3,4,4,4,2,25,1.0,neutral or dissatisfied +2223,11058,Female,Loyal Customer,16,Personal Travel,Eco,201,2,2,2,3,2,2,2,2,2,2,3,4,4,2,43,34.0,neutral or dissatisfied +2224,88275,Female,Loyal Customer,46,Business travel,Business,594,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +2225,58266,Male,Loyal Customer,54,Business travel,Business,2650,3,3,3,3,5,5,5,3,4,4,4,5,3,5,143,148.0,satisfied +2226,123583,Female,Loyal Customer,43,Personal Travel,Eco,1773,3,2,3,4,5,4,3,3,3,3,3,1,3,3,7,0.0,neutral or dissatisfied +2227,114625,Male,Loyal Customer,44,Business travel,Business,417,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +2228,8652,Male,disloyal Customer,27,Business travel,Business,227,1,2,2,3,5,2,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +2229,121742,Male,Loyal Customer,32,Personal Travel,Eco,1475,2,5,2,3,3,2,1,3,4,4,4,4,5,3,6,0.0,neutral or dissatisfied +2230,123689,Male,disloyal Customer,45,Business travel,Business,214,3,3,3,4,3,3,3,3,2,1,5,1,2,3,8,5.0,neutral or dissatisfied +2231,105423,Female,disloyal Customer,40,Business travel,Business,452,4,4,4,4,3,4,4,3,3,4,4,4,4,3,61,68.0,neutral or dissatisfied +2232,101723,Female,Loyal Customer,37,Business travel,Business,986,4,4,4,4,5,5,4,4,4,4,4,3,4,5,23,4.0,satisfied +2233,25536,Female,Loyal Customer,49,Personal Travel,Eco,516,1,5,1,4,5,5,5,4,4,1,4,4,4,5,12,0.0,neutral or dissatisfied +2234,100392,Female,Loyal Customer,20,Personal Travel,Eco,1092,4,4,4,3,1,4,1,1,4,2,3,2,3,1,6,7.0,neutral or dissatisfied +2235,68388,Female,Loyal Customer,41,Business travel,Business,2956,3,3,3,3,4,5,5,5,5,4,5,4,5,5,0,0.0,satisfied +2236,95098,Male,Loyal Customer,39,Personal Travel,Eco,239,3,4,3,3,4,3,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +2237,122962,Male,disloyal Customer,25,Business travel,Business,468,3,0,3,2,1,3,1,1,5,4,4,4,4,1,15,9.0,neutral or dissatisfied +2238,58961,Male,Loyal Customer,29,Business travel,Business,1723,2,2,2,2,4,4,4,4,5,4,4,4,5,4,2,17.0,satisfied +2239,116956,Male,Loyal Customer,34,Business travel,Business,621,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +2240,109484,Female,disloyal Customer,24,Business travel,Eco,834,1,1,1,4,5,1,5,5,3,3,4,1,3,5,0,0.0,neutral or dissatisfied +2241,76135,Male,Loyal Customer,43,Business travel,Business,689,2,2,2,2,4,5,5,5,5,5,5,3,5,3,13,5.0,satisfied +2242,82101,Male,Loyal Customer,21,Personal Travel,Eco,1276,3,1,3,2,4,3,4,4,1,4,3,4,2,4,4,6.0,neutral or dissatisfied +2243,14052,Male,Loyal Customer,67,Personal Travel,Eco,335,2,3,3,3,2,3,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +2244,104856,Female,Loyal Customer,35,Business travel,Business,327,3,1,1,1,3,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +2245,56116,Female,Loyal Customer,18,Business travel,Business,1400,3,3,3,3,5,5,5,5,5,4,4,5,5,5,0,20.0,satisfied +2246,41304,Female,Loyal Customer,22,Business travel,Business,1624,3,3,4,3,4,5,4,4,4,1,3,5,3,4,0,0.0,satisfied +2247,18506,Male,disloyal Customer,27,Business travel,Eco,201,3,0,3,1,4,3,1,4,3,1,1,5,3,4,18,18.0,neutral or dissatisfied +2248,73821,Male,Loyal Customer,41,Business travel,Business,1754,2,5,2,2,4,5,4,2,2,2,2,3,2,4,5,14.0,satisfied +2249,51188,Male,disloyal Customer,39,Business travel,Eco Plus,373,2,2,2,1,5,2,5,5,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +2250,53044,Female,disloyal Customer,25,Business travel,Eco,1208,3,2,2,3,5,2,5,5,2,3,1,4,3,5,0,0.0,neutral or dissatisfied +2251,15952,Male,Loyal Customer,16,Personal Travel,Eco,528,2,5,2,1,5,2,5,5,3,5,5,3,5,5,0,0.0,neutral or dissatisfied +2252,20885,Female,Loyal Customer,36,Business travel,Eco Plus,134,4,5,3,3,4,4,4,4,3,4,1,2,2,4,0,0.0,satisfied +2253,26533,Female,Loyal Customer,41,Business travel,Eco,990,4,1,1,1,4,4,4,4,2,5,2,1,2,4,12,12.0,neutral or dissatisfied +2254,18713,Female,Loyal Customer,23,Personal Travel,Eco Plus,190,5,2,5,4,1,5,1,1,3,4,3,1,4,1,83,90.0,satisfied +2255,7295,Male,Loyal Customer,35,Personal Travel,Eco,135,3,0,3,4,1,3,1,1,3,4,5,5,5,1,0,16.0,neutral or dissatisfied +2256,3969,Male,Loyal Customer,32,Personal Travel,Eco,764,0,4,0,4,3,0,1,3,3,4,4,4,5,3,0,0.0,satisfied +2257,115625,Female,Loyal Customer,30,Business travel,Business,2142,1,1,1,1,4,4,4,4,4,3,4,5,5,4,19,24.0,satisfied +2258,111662,Male,Loyal Customer,13,Business travel,Business,1864,4,4,4,4,5,5,5,5,4,4,4,4,5,5,10,18.0,satisfied +2259,5811,Female,Loyal Customer,23,Personal Travel,Eco,273,4,3,4,3,3,4,5,3,1,4,4,2,4,3,0,0.0,satisfied +2260,44014,Male,Loyal Customer,57,Personal Travel,Eco,397,3,5,3,2,5,3,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +2261,111289,Male,Loyal Customer,24,Business travel,Business,479,5,5,5,5,4,4,4,4,3,2,5,4,5,4,20,24.0,satisfied +2262,2283,Male,Loyal Customer,50,Business travel,Business,925,1,1,1,1,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +2263,101317,Female,Loyal Customer,51,Business travel,Business,3765,5,5,4,5,4,5,5,5,5,5,5,5,5,3,5,1.0,satisfied +2264,3670,Female,disloyal Customer,34,Business travel,Business,427,3,3,3,2,3,3,3,3,3,5,4,3,5,3,12,0.0,neutral or dissatisfied +2265,88884,Female,disloyal Customer,22,Business travel,Eco,859,3,3,3,2,2,3,2,2,3,4,4,5,4,2,70,64.0,neutral or dissatisfied +2266,105408,Female,Loyal Customer,68,Business travel,Business,369,2,2,2,2,5,5,5,4,4,4,4,4,4,5,8,5.0,satisfied +2267,58571,Female,Loyal Customer,56,Business travel,Business,1806,5,5,5,5,5,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +2268,57965,Male,Loyal Customer,25,Personal Travel,Eco,1911,2,4,2,1,5,2,5,5,5,2,4,3,5,5,40,65.0,neutral or dissatisfied +2269,96792,Male,Loyal Customer,46,Business travel,Business,3840,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,6.0,satisfied +2270,104112,Male,Loyal Customer,34,Personal Travel,Eco,297,2,5,5,1,2,5,2,2,5,2,4,5,5,2,9,0.0,neutral or dissatisfied +2271,120919,Female,Loyal Customer,36,Business travel,Business,2048,2,2,2,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +2272,87383,Female,Loyal Customer,53,Business travel,Business,2651,5,5,5,5,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +2273,62607,Male,Loyal Customer,30,Personal Travel,Eco,1744,4,1,4,3,2,4,2,2,4,5,2,3,4,2,0,0.0,neutral or dissatisfied +2274,126691,Male,Loyal Customer,40,Business travel,Business,2402,5,5,5,5,2,5,5,3,3,3,3,4,3,3,32,11.0,satisfied +2275,10785,Female,Loyal Customer,26,Business travel,Business,2697,4,5,5,5,4,4,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +2276,92166,Female,Loyal Customer,57,Business travel,Business,2079,3,3,3,3,5,3,4,4,4,4,4,5,4,4,0,0.0,satisfied +2277,52077,Male,Loyal Customer,44,Business travel,Eco,438,4,2,2,2,4,4,4,4,3,3,2,5,3,4,0,9.0,satisfied +2278,13074,Male,Loyal Customer,32,Personal Travel,Eco,936,1,2,1,3,4,1,4,4,3,1,3,4,4,4,4,0.0,neutral or dissatisfied +2279,55278,Male,Loyal Customer,52,Business travel,Business,1585,2,3,4,3,3,3,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +2280,62799,Female,Loyal Customer,15,Personal Travel,Eco,2338,0,4,0,3,4,0,3,4,2,3,3,2,3,4,0,5.0,satisfied +2281,3688,Male,Loyal Customer,60,Business travel,Business,2667,2,2,2,2,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +2282,229,Female,Loyal Customer,33,Business travel,Business,213,5,5,5,5,4,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +2283,45704,Female,Loyal Customer,43,Business travel,Eco,852,5,1,1,1,4,4,1,5,5,5,5,3,5,2,13,27.0,satisfied +2284,116869,Male,Loyal Customer,44,Business travel,Business,3764,2,2,2,2,2,4,4,4,4,4,4,3,4,5,56,42.0,satisfied +2285,90372,Male,Loyal Customer,60,Business travel,Business,2438,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +2286,103871,Male,Loyal Customer,7,Personal Travel,Eco,1056,4,4,4,5,1,4,1,1,1,1,1,2,5,1,21,15.0,neutral or dissatisfied +2287,44522,Female,Loyal Customer,20,Business travel,Business,157,4,4,4,4,3,3,4,3,2,4,3,3,4,3,2,14.0,neutral or dissatisfied +2288,79700,Female,Loyal Customer,24,Personal Travel,Eco,762,2,4,2,3,3,2,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +2289,66204,Male,Loyal Customer,78,Business travel,Business,2708,5,5,5,5,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +2290,39557,Female,Loyal Customer,30,Business travel,Business,965,2,2,2,2,4,4,4,4,5,3,3,4,5,4,0,0.0,satisfied +2291,12182,Male,Loyal Customer,52,Business travel,Eco,675,5,1,1,1,5,5,5,5,1,2,5,3,5,5,0,2.0,satisfied +2292,25587,Male,Loyal Customer,52,Business travel,Business,874,2,5,5,5,1,2,2,2,2,2,2,2,2,4,15,21.0,neutral or dissatisfied +2293,76080,Male,Loyal Customer,23,Business travel,Eco,707,2,4,4,4,2,2,1,2,4,1,3,3,4,2,0,0.0,neutral or dissatisfied +2294,6204,Female,Loyal Customer,9,Personal Travel,Eco Plus,501,1,1,1,4,1,1,1,2,4,3,4,1,2,1,80,133.0,neutral or dissatisfied +2295,38737,Female,Loyal Customer,36,Business travel,Eco,387,5,2,2,2,5,5,5,5,3,5,4,1,2,5,0,0.0,satisfied +2296,104277,Male,Loyal Customer,66,Personal Travel,Eco,1749,5,4,5,2,1,5,1,1,4,3,4,3,4,1,2,0.0,satisfied +2297,72642,Female,Loyal Customer,69,Personal Travel,Eco,1121,2,4,2,5,4,5,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +2298,123817,Male,Loyal Customer,43,Business travel,Business,3700,2,3,2,2,5,4,5,4,4,4,4,3,4,5,0,11.0,satisfied +2299,112981,Male,Loyal Customer,36,Personal Travel,Eco Plus,1476,4,5,4,2,4,4,4,4,5,3,3,5,4,4,3,0.0,neutral or dissatisfied +2300,71736,Male,Loyal Customer,59,Business travel,Business,1723,3,5,5,5,4,3,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +2301,77154,Male,Loyal Customer,17,Personal Travel,Eco,1865,1,2,1,2,4,1,4,4,4,1,2,4,2,4,13,5.0,neutral or dissatisfied +2302,70398,Female,Loyal Customer,16,Business travel,Business,1562,4,4,4,4,4,4,4,4,2,5,3,2,3,4,22,16.0,neutral or dissatisfied +2303,13598,Female,Loyal Customer,44,Personal Travel,Eco,227,3,4,3,3,4,4,5,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +2304,44007,Female,Loyal Customer,46,Business travel,Business,2235,2,5,2,5,2,4,4,2,2,2,2,1,2,1,0,1.0,neutral or dissatisfied +2305,121671,Female,disloyal Customer,37,Business travel,Eco,328,3,3,2,4,3,2,3,3,1,2,3,2,4,3,15,7.0,neutral or dissatisfied +2306,115185,Male,Loyal Customer,35,Business travel,Eco,342,3,3,3,3,3,3,3,3,3,2,4,1,3,3,22,28.0,neutral or dissatisfied +2307,52114,Male,Loyal Customer,44,Personal Travel,Eco,351,3,5,2,4,3,2,2,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +2308,101958,Male,Loyal Customer,60,Business travel,Eco,628,4,3,3,3,4,4,4,4,2,1,3,3,4,4,7,0.0,neutral or dissatisfied +2309,107144,Female,disloyal Customer,35,Business travel,Business,668,4,4,4,3,4,4,4,4,3,3,5,4,5,4,82,87.0,neutral or dissatisfied +2310,89485,Male,Loyal Customer,39,Business travel,Business,1931,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,7.0,satisfied +2311,15695,Male,Loyal Customer,24,Business travel,Business,192,3,2,2,2,2,2,3,2,3,1,3,2,4,2,67,64.0,neutral or dissatisfied +2312,62744,Male,Loyal Customer,50,Business travel,Business,2447,2,2,2,2,4,4,4,3,5,5,5,4,5,4,7,13.0,satisfied +2313,82370,Male,Loyal Customer,50,Business travel,Business,3929,3,3,3,3,3,4,5,4,4,4,4,5,4,3,18,5.0,satisfied +2314,51376,Male,Loyal Customer,65,Personal Travel,Eco Plus,109,3,5,0,1,1,0,1,1,2,2,3,1,4,1,1,0.0,neutral or dissatisfied +2315,16238,Female,Loyal Customer,62,Personal Travel,Business,946,2,3,2,3,3,4,3,3,3,2,2,2,3,4,0,0.0,neutral or dissatisfied +2316,66950,Male,Loyal Customer,46,Business travel,Business,985,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +2317,122039,Male,Loyal Customer,46,Business travel,Business,130,0,4,0,3,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +2318,104984,Female,disloyal Customer,27,Business travel,Business,337,3,3,3,3,3,3,3,3,3,5,5,3,4,3,5,1.0,neutral or dissatisfied +2319,21144,Male,Loyal Customer,21,Personal Travel,Eco Plus,227,4,4,0,1,3,0,5,3,5,4,4,3,5,3,0,0.0,satisfied +2320,54121,Male,Loyal Customer,47,Business travel,Business,1569,4,4,4,4,2,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +2321,24314,Female,Loyal Customer,46,Business travel,Eco,479,4,4,4,4,4,4,5,4,4,4,4,3,4,2,0,0.0,satisfied +2322,97154,Female,disloyal Customer,21,Business travel,Eco,990,1,1,1,3,2,1,2,2,2,3,1,4,1,2,3,0.0,neutral or dissatisfied +2323,86955,Male,disloyal Customer,25,Business travel,Business,907,5,4,5,5,3,5,3,3,5,2,5,5,5,3,0,0.0,satisfied +2324,70158,Female,Loyal Customer,64,Personal Travel,Eco,550,1,4,1,5,4,5,4,5,5,1,5,3,5,4,10,0.0,neutral or dissatisfied +2325,40122,Male,Loyal Customer,61,Personal Travel,Eco,200,1,5,0,2,4,0,3,4,3,5,5,4,5,4,8,13.0,neutral or dissatisfied +2326,93363,Male,Loyal Customer,55,Personal Travel,Eco,836,3,5,4,2,4,4,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +2327,71524,Male,Loyal Customer,30,Business travel,Business,2787,2,2,2,2,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +2328,70889,Female,Loyal Customer,23,Personal Travel,Business,1721,2,5,2,5,2,2,5,2,3,5,4,5,4,2,0,4.0,neutral or dissatisfied +2329,107964,Male,disloyal Customer,27,Business travel,Business,825,1,1,1,3,3,1,3,3,5,5,5,3,5,3,2,0.0,neutral or dissatisfied +2330,8867,Male,Loyal Customer,54,Business travel,Business,3183,2,2,2,2,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +2331,32480,Male,Loyal Customer,60,Business travel,Eco,101,4,3,3,3,5,4,5,5,5,2,4,4,2,5,0,0.0,satisfied +2332,117186,Male,Loyal Customer,23,Personal Travel,Eco,370,2,1,1,1,5,1,5,5,1,2,1,1,1,5,7,0.0,neutral or dissatisfied +2333,76611,Female,Loyal Customer,52,Business travel,Business,3739,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,4.0,satisfied +2334,87885,Female,Loyal Customer,11,Personal Travel,Eco Plus,143,0,2,0,4,3,0,3,3,2,1,3,2,4,3,0,0.0,satisfied +2335,53056,Male,Loyal Customer,53,Personal Travel,Eco,1208,2,3,2,4,5,2,5,5,3,2,4,1,4,5,8,13.0,neutral or dissatisfied +2336,81810,Male,Loyal Customer,12,Business travel,Business,1487,2,3,3,3,2,3,2,2,3,4,4,2,3,2,0,16.0,neutral or dissatisfied +2337,24528,Female,Loyal Customer,38,Business travel,Business,492,3,4,4,4,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +2338,40245,Female,disloyal Customer,20,Business travel,Eco,531,2,0,2,2,2,2,1,2,3,1,3,2,4,2,0,0.0,neutral or dissatisfied +2339,60300,Male,Loyal Customer,33,Business travel,Business,406,1,1,1,1,4,4,4,4,3,5,4,3,5,4,0,0.0,satisfied +2340,33125,Male,Loyal Customer,63,Personal Travel,Eco,216,4,2,4,4,4,4,4,4,4,2,4,2,4,4,2,2.0,neutral or dissatisfied +2341,20919,Female,disloyal Customer,22,Business travel,Eco,721,2,2,2,2,3,2,3,3,1,1,1,2,5,3,5,0.0,neutral or dissatisfied +2342,66162,Male,Loyal Customer,55,Business travel,Business,3782,3,1,3,3,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +2343,85989,Female,Loyal Customer,55,Business travel,Business,2271,2,2,2,2,5,5,4,5,5,5,5,4,5,3,1,0.0,satisfied +2344,7690,Male,Loyal Customer,67,Personal Travel,Eco,641,3,4,3,2,4,3,5,4,4,5,5,5,4,4,13,8.0,neutral or dissatisfied +2345,26813,Male,Loyal Customer,42,Business travel,Business,224,3,3,5,3,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +2346,6762,Female,disloyal Customer,26,Business travel,Business,235,4,4,4,1,1,4,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +2347,59351,Female,Loyal Customer,48,Business travel,Business,2447,1,1,1,1,2,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +2348,54265,Male,Loyal Customer,49,Personal Travel,Eco,1222,2,1,2,4,5,2,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +2349,113877,Male,Loyal Customer,68,Personal Travel,Eco,1592,3,5,3,5,3,3,2,3,3,5,5,4,5,3,6,1.0,neutral or dissatisfied +2350,102549,Female,Loyal Customer,23,Personal Travel,Eco,386,4,4,2,2,5,2,5,5,4,4,4,5,5,5,0,1.0,neutral or dissatisfied +2351,96806,Male,Loyal Customer,55,Business travel,Business,2555,4,4,4,4,3,4,4,4,4,4,4,5,4,4,7,11.0,satisfied +2352,1416,Male,Loyal Customer,15,Personal Travel,Eco Plus,312,3,4,3,1,4,3,3,4,3,5,5,4,5,4,5,0.0,neutral or dissatisfied +2353,66140,Male,Loyal Customer,68,Personal Travel,Eco,583,3,4,3,4,3,3,3,3,4,4,5,3,4,3,144,149.0,neutral or dissatisfied +2354,3382,Male,Loyal Customer,34,Business travel,Business,2184,0,0,0,4,3,5,4,2,2,5,5,5,2,4,0,0.0,satisfied +2355,24258,Male,Loyal Customer,15,Personal Travel,Eco,134,1,2,1,4,2,1,2,2,1,5,3,1,3,2,1,0.0,neutral or dissatisfied +2356,20911,Male,Loyal Customer,28,Business travel,Business,689,1,5,1,1,4,4,4,4,2,2,3,4,2,4,0,0.0,satisfied +2357,69881,Female,Loyal Customer,21,Business travel,Business,2248,5,5,5,5,5,5,5,5,4,2,4,4,4,5,14,0.0,satisfied +2358,95132,Female,Loyal Customer,66,Personal Travel,Eco,323,1,4,1,2,3,1,3,2,2,1,2,5,2,2,1,2.0,neutral or dissatisfied +2359,14251,Female,Loyal Customer,33,Business travel,Eco Plus,1027,5,2,2,2,5,5,5,5,5,1,1,2,2,5,0,0.0,satisfied +2360,4892,Female,Loyal Customer,54,Personal Travel,Eco Plus,408,1,5,1,5,5,5,4,5,5,1,1,4,5,4,0,0.0,neutral or dissatisfied +2361,37574,Male,Loyal Customer,46,Business travel,Eco,628,3,2,2,2,3,3,3,3,2,5,4,4,3,3,0,0.0,neutral or dissatisfied +2362,53339,Male,Loyal Customer,29,Business travel,Eco,1452,5,3,3,3,5,5,5,5,4,3,4,3,5,5,2,5.0,satisfied +2363,38239,Male,disloyal Customer,48,Business travel,Eco,1050,3,3,3,1,1,3,1,1,5,3,4,1,3,1,0,0.0,neutral or dissatisfied +2364,63042,Female,Loyal Customer,19,Personal Travel,Eco,967,1,1,2,2,1,2,1,1,3,4,3,4,3,1,26,27.0,neutral or dissatisfied +2365,48625,Male,Loyal Customer,37,Personal Travel,Eco Plus,845,4,5,4,3,3,4,4,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +2366,122496,Female,Loyal Customer,23,Personal Travel,Business,930,2,5,2,4,5,2,5,5,5,4,5,5,4,5,2,1.0,neutral or dissatisfied +2367,110650,Male,disloyal Customer,48,Business travel,Business,1005,3,3,3,1,5,3,5,5,3,5,5,3,4,5,32,41.0,neutral or dissatisfied +2368,10677,Male,Loyal Customer,52,Business travel,Eco,308,1,3,3,3,1,1,1,1,4,4,3,2,3,1,1,2.0,neutral or dissatisfied +2369,101513,Male,disloyal Customer,17,Business travel,Eco,345,5,0,5,4,4,5,4,4,1,4,1,3,1,4,0,0.0,satisfied +2370,68515,Female,disloyal Customer,10,Business travel,Eco,1303,3,3,3,3,4,3,4,4,3,5,3,3,4,4,45,65.0,neutral or dissatisfied +2371,100299,Male,Loyal Customer,44,Business travel,Eco,971,3,5,5,5,3,3,3,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +2372,110522,Female,Loyal Customer,35,Business travel,Business,3252,5,5,5,5,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +2373,78496,Female,Loyal Customer,56,Business travel,Business,2076,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +2374,51881,Female,Loyal Customer,41,Business travel,Business,3738,2,2,2,2,5,4,4,2,2,2,2,3,2,3,46,34.0,neutral or dissatisfied +2375,84226,Female,Loyal Customer,60,Personal Travel,Eco,432,5,2,5,3,5,3,3,1,1,5,1,4,1,3,0,0.0,satisfied +2376,25821,Female,Loyal Customer,31,Personal Travel,Eco,1747,2,0,2,1,1,2,1,1,4,2,5,3,5,1,9,5.0,neutral or dissatisfied +2377,70184,Female,Loyal Customer,40,Business travel,Business,2245,3,3,2,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +2378,20092,Male,Loyal Customer,59,Business travel,Business,3548,3,3,3,3,2,3,3,5,5,5,5,4,5,5,0,0.0,satisfied +2379,126689,Female,disloyal Customer,18,Business travel,Eco,969,1,1,1,3,5,1,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +2380,44681,Male,disloyal Customer,35,Business travel,Eco,67,1,2,1,3,1,1,1,1,4,3,3,3,3,1,49,56.0,neutral or dissatisfied +2381,14352,Male,Loyal Customer,16,Personal Travel,Eco,429,3,5,3,3,1,3,1,1,2,5,2,5,4,1,0,0.0,neutral or dissatisfied +2382,80974,Female,disloyal Customer,38,Business travel,Business,297,3,3,3,5,3,3,2,3,4,4,5,4,5,3,0,0.0,neutral or dissatisfied +2383,68025,Female,Loyal Customer,26,Personal Travel,Eco,304,3,4,3,1,1,3,1,1,4,3,4,4,5,1,7,17.0,neutral or dissatisfied +2384,101973,Male,Loyal Customer,47,Personal Travel,Eco,628,3,4,3,3,1,3,1,1,4,5,5,4,4,1,0,0.0,neutral or dissatisfied +2385,90382,Female,Loyal Customer,43,Business travel,Business,2993,4,4,4,4,5,5,5,4,5,4,5,5,3,5,135,135.0,satisfied +2386,75659,Male,Loyal Customer,43,Personal Travel,Eco,304,2,4,2,4,1,2,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +2387,121166,Male,disloyal Customer,72,Business travel,Eco,902,3,3,3,5,4,3,4,4,1,2,5,1,3,4,0,0.0,neutral or dissatisfied +2388,8219,Female,Loyal Customer,20,Personal Travel,Eco,402,3,5,3,1,4,3,4,4,4,5,5,3,4,4,0,0.0,neutral or dissatisfied +2389,94440,Female,Loyal Customer,48,Business travel,Business,239,3,4,3,3,5,5,4,4,4,4,4,3,4,5,7,1.0,satisfied +2390,21270,Male,Loyal Customer,50,Personal Travel,Business,692,0,4,0,4,3,4,5,2,2,0,2,4,2,5,0,0.0,satisfied +2391,97175,Female,Loyal Customer,9,Personal Travel,Eco,1211,2,0,2,5,5,2,5,5,1,2,2,5,4,5,0,14.0,neutral or dissatisfied +2392,67829,Male,disloyal Customer,39,Business travel,Eco,1038,2,2,2,3,3,2,3,3,2,1,3,3,4,3,0,0.0,neutral or dissatisfied +2393,121752,Male,Loyal Customer,55,Business travel,Business,449,3,3,3,3,2,4,4,5,5,5,5,3,5,4,109,106.0,satisfied +2394,106287,Male,Loyal Customer,13,Personal Travel,Eco,689,3,5,3,3,5,3,5,5,4,2,5,4,5,5,15,6.0,neutral or dissatisfied +2395,68941,Male,Loyal Customer,55,Personal Travel,Eco,646,4,4,4,3,1,4,1,1,4,1,3,4,4,1,0,0.0,neutral or dissatisfied +2396,31911,Female,Loyal Customer,51,Business travel,Business,216,4,4,5,4,5,5,5,4,4,4,5,4,4,3,0,0.0,satisfied +2397,12846,Male,Loyal Customer,18,Personal Travel,Eco,817,1,3,1,3,2,1,2,2,2,2,5,3,3,2,0,0.0,neutral or dissatisfied +2398,7099,Female,Loyal Customer,69,Personal Travel,Eco,273,4,4,4,4,1,3,4,2,2,4,2,2,2,1,12,11.0,neutral or dissatisfied +2399,110298,Male,Loyal Customer,29,Business travel,Business,1948,3,3,3,3,4,4,4,4,4,4,5,3,5,4,85,90.0,satisfied +2400,28563,Female,Loyal Customer,35,Business travel,Eco Plus,2677,5,2,5,2,5,5,5,5,3,3,5,1,3,5,0,0.0,satisfied +2401,25891,Male,disloyal Customer,9,Business travel,Eco,907,3,4,4,3,2,4,2,2,1,2,3,4,2,2,57,68.0,neutral or dissatisfied +2402,12521,Female,Loyal Customer,38,Business travel,Eco,788,5,5,5,5,5,5,5,5,5,5,3,2,1,5,66,92.0,satisfied +2403,63567,Female,disloyal Customer,27,Business travel,Business,969,4,4,4,5,5,4,5,5,5,5,3,3,5,5,0,0.0,satisfied +2404,78357,Female,Loyal Customer,49,Business travel,Business,1927,2,2,1,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +2405,109638,Female,Loyal Customer,54,Business travel,Business,1576,3,3,3,3,2,5,4,5,5,5,5,4,5,3,17,12.0,satisfied +2406,12508,Female,Loyal Customer,38,Personal Travel,Eco Plus,305,1,5,1,3,4,1,4,4,5,5,5,1,4,4,105,111.0,neutral or dissatisfied +2407,3695,Male,Loyal Customer,53,Business travel,Business,431,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +2408,71985,Male,Loyal Customer,59,Personal Travel,Eco,1440,5,5,5,1,4,5,4,4,5,3,5,3,4,4,0,0.0,satisfied +2409,40108,Male,Loyal Customer,47,Business travel,Eco,368,2,2,3,3,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +2410,78461,Male,Loyal Customer,45,Business travel,Business,666,1,2,2,2,5,4,3,1,1,1,1,3,1,3,0,60.0,neutral or dissatisfied +2411,96965,Male,Loyal Customer,33,Business travel,Business,794,3,3,3,3,3,3,3,3,5,2,5,5,5,3,0,0.0,satisfied +2412,54564,Male,Loyal Customer,32,Business travel,Eco Plus,925,4,1,1,1,4,4,4,4,5,3,3,3,4,4,8,0.0,satisfied +2413,25293,Male,Loyal Customer,10,Personal Travel,Eco,321,2,4,5,3,3,5,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +2414,80011,Female,Loyal Customer,11,Personal Travel,Eco,1096,2,2,3,3,1,3,1,1,3,4,3,4,3,1,24,19.0,neutral or dissatisfied +2415,88836,Female,Loyal Customer,60,Personal Travel,Eco Plus,545,3,3,5,2,4,1,3,2,2,5,2,2,2,2,37,33.0,neutral or dissatisfied +2416,64651,Male,disloyal Customer,37,Business travel,Business,551,2,2,2,2,5,2,5,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +2417,39085,Female,Loyal Customer,36,Business travel,Business,3248,5,5,5,5,3,1,4,5,5,5,5,5,5,2,0,12.0,satisfied +2418,23324,Female,disloyal Customer,59,Business travel,Eco,456,2,2,3,3,2,3,2,2,4,5,2,2,3,2,23,40.0,neutral or dissatisfied +2419,53418,Male,disloyal Customer,13,Business travel,Eco,2288,4,4,4,1,4,2,2,4,1,4,3,2,5,2,7,32.0,satisfied +2420,123261,Male,Loyal Customer,20,Personal Travel,Eco,650,3,2,3,3,5,3,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +2421,49901,Female,Loyal Customer,48,Business travel,Eco,250,1,3,3,3,5,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +2422,73262,Male,Loyal Customer,15,Personal Travel,Eco,675,4,4,4,1,4,4,4,4,3,3,4,4,4,4,0,0.0,satisfied +2423,125541,Male,disloyal Customer,40,Business travel,Business,226,4,4,4,2,4,4,4,4,5,2,5,5,4,4,2,12.0,satisfied +2424,47355,Male,Loyal Customer,57,Business travel,Business,2714,2,2,2,2,3,3,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +2425,96129,Male,Loyal Customer,31,Business travel,Business,460,3,3,3,3,5,5,5,5,4,3,4,3,4,5,8,0.0,satisfied +2426,99150,Female,Loyal Customer,52,Business travel,Business,986,1,2,1,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +2427,2002,Male,Loyal Customer,59,Business travel,Business,3926,3,3,4,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +2428,66100,Female,Loyal Customer,40,Personal Travel,Business,583,4,4,4,2,5,5,4,5,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +2429,111166,Female,Loyal Customer,28,Business travel,Eco Plus,1180,2,3,3,3,2,2,2,2,2,5,3,1,4,2,2,0.0,neutral or dissatisfied +2430,38740,Male,Loyal Customer,49,Business travel,Business,1995,2,2,2,2,5,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +2431,62859,Male,Loyal Customer,49,Business travel,Business,2446,3,3,3,3,3,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +2432,422,Male,Loyal Customer,42,Business travel,Business,3957,4,4,4,4,4,5,5,5,5,5,5,4,5,4,7,50.0,satisfied +2433,40103,Male,Loyal Customer,44,Business travel,Eco,368,4,3,4,4,5,4,5,5,5,5,2,1,2,5,0,0.0,satisfied +2434,50481,Female,Loyal Customer,36,Business travel,Eco,110,2,1,1,1,2,2,2,2,3,5,4,4,3,2,6,13.0,neutral or dissatisfied +2435,553,Female,Loyal Customer,57,Business travel,Business,134,5,5,5,5,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +2436,97166,Male,Loyal Customer,69,Personal Travel,Eco,1164,2,5,1,3,4,1,2,4,3,3,4,5,5,4,39,38.0,neutral or dissatisfied +2437,64198,Female,Loyal Customer,55,Business travel,Business,853,4,4,4,4,5,2,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +2438,24365,Male,Loyal Customer,40,Business travel,Eco,669,4,4,4,4,4,4,4,4,5,5,1,3,3,4,5,0.0,satisfied +2439,52499,Male,Loyal Customer,46,Business travel,Business,1810,4,4,3,4,2,5,5,4,4,4,5,5,4,5,0,0.0,satisfied +2440,37996,Male,Loyal Customer,40,Business travel,Eco,1197,4,2,2,2,4,4,4,4,2,2,3,2,1,4,0,6.0,satisfied +2441,36579,Male,disloyal Customer,29,Business travel,Eco,1197,2,2,2,3,2,2,3,2,5,3,3,2,5,2,0,0.0,neutral or dissatisfied +2442,89143,Female,Loyal Customer,25,Business travel,Eco,1947,4,3,3,3,4,4,3,4,5,2,2,3,2,4,2,0.0,satisfied +2443,46424,Male,disloyal Customer,24,Business travel,Eco,649,3,2,3,2,4,3,4,4,2,4,3,1,3,4,19,30.0,neutral or dissatisfied +2444,92135,Female,Loyal Customer,38,Personal Travel,Eco,1535,2,2,2,3,4,2,3,4,3,3,2,2,4,4,14,0.0,neutral or dissatisfied +2445,112395,Male,Loyal Customer,43,Business travel,Business,862,2,2,2,2,5,4,4,5,5,5,5,5,5,5,87,70.0,satisfied +2446,109686,Male,Loyal Customer,39,Personal Travel,Eco,930,1,5,2,2,3,2,4,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +2447,66171,Male,Loyal Customer,42,Business travel,Business,1681,4,4,4,4,4,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +2448,30350,Female,Loyal Customer,52,Business travel,Business,2844,1,1,1,1,5,4,4,3,3,4,3,5,3,5,0,4.0,satisfied +2449,123544,Female,Loyal Customer,29,Business travel,Business,1773,2,2,2,2,4,4,4,4,5,2,4,5,4,4,20,0.0,satisfied +2450,32581,Female,disloyal Customer,24,Business travel,Eco,216,3,4,3,3,3,3,3,3,2,4,4,2,4,3,3,0.0,neutral or dissatisfied +2451,129602,Female,Loyal Customer,45,Business travel,Business,1876,4,4,4,4,5,4,4,5,5,5,5,4,5,3,8,10.0,satisfied +2452,77613,Female,Loyal Customer,50,Business travel,Business,3183,2,4,2,2,5,4,4,3,3,3,3,3,3,4,16,6.0,satisfied +2453,60822,Female,Loyal Customer,19,Personal Travel,Eco,524,3,4,3,3,5,3,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +2454,56133,Female,Loyal Customer,52,Business travel,Business,1400,1,1,3,1,3,5,4,5,5,5,5,5,5,4,28,27.0,satisfied +2455,88535,Female,Loyal Customer,48,Personal Travel,Eco,250,2,4,0,3,5,5,5,1,1,0,1,3,1,4,0,0.0,neutral or dissatisfied +2456,96070,Male,Loyal Customer,69,Personal Travel,Eco,583,3,5,3,4,2,3,2,2,4,4,4,3,5,2,33,34.0,neutral or dissatisfied +2457,71033,Female,Loyal Customer,32,Business travel,Business,2815,3,3,3,3,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +2458,95539,Male,Loyal Customer,50,Personal Travel,Eco Plus,239,3,3,3,2,2,3,2,2,4,3,2,5,2,2,1,6.0,neutral or dissatisfied +2459,70751,Female,Loyal Customer,56,Business travel,Business,733,5,5,5,5,2,4,5,5,5,5,5,4,5,5,4,0.0,satisfied +2460,125833,Female,disloyal Customer,31,Business travel,Eco,1013,3,3,3,4,3,3,3,3,3,3,3,1,4,3,10,8.0,neutral or dissatisfied +2461,89582,Male,Loyal Customer,27,Business travel,Eco,1080,3,2,2,2,3,3,3,3,1,5,3,3,3,3,0,0.0,neutral or dissatisfied +2462,118769,Male,Loyal Customer,7,Personal Travel,Eco,621,4,5,4,1,3,4,1,3,3,2,4,3,5,3,0,0.0,satisfied +2463,12092,Female,Loyal Customer,54,Business travel,Business,1034,3,2,2,2,3,4,4,3,3,3,3,2,3,2,0,16.0,neutral or dissatisfied +2464,129199,Male,Loyal Customer,45,Business travel,Business,2419,4,4,4,4,2,5,4,5,5,5,5,4,5,5,3,0.0,satisfied +2465,49009,Male,Loyal Customer,52,Business travel,Eco,109,4,2,2,2,4,4,4,4,5,1,1,2,1,4,0,2.0,satisfied +2466,59502,Male,Loyal Customer,55,Business travel,Business,1711,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +2467,69113,Male,disloyal Customer,41,Business travel,Business,1598,3,3,3,3,2,3,2,2,3,2,4,3,5,2,3,0.0,neutral or dissatisfied +2468,118856,Male,Loyal Customer,51,Personal Travel,Eco Plus,370,3,4,2,3,5,2,5,5,3,1,4,1,5,5,0,0.0,neutral or dissatisfied +2469,48528,Female,Loyal Customer,39,Business travel,Eco,433,3,5,1,5,3,5,3,3,1,1,1,1,5,3,0,0.0,satisfied +2470,67189,Female,Loyal Customer,41,Personal Travel,Eco,985,2,5,2,3,2,2,2,2,3,5,5,3,4,2,109,101.0,neutral or dissatisfied +2471,29356,Male,Loyal Customer,77,Business travel,Business,2349,3,3,5,3,1,3,5,1,1,2,1,1,1,3,0,10.0,satisfied +2472,72519,Female,Loyal Customer,37,Business travel,Business,2346,4,5,2,5,2,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +2473,70376,Female,Loyal Customer,12,Business travel,Eco Plus,1145,1,1,1,1,1,1,2,1,4,2,3,2,3,1,32,52.0,neutral or dissatisfied +2474,74926,Female,Loyal Customer,33,Business travel,Business,2475,4,2,2,2,2,3,3,4,4,4,4,2,4,4,6,0.0,neutral or dissatisfied +2475,37544,Female,Loyal Customer,42,Business travel,Eco,1097,1,0,0,3,3,3,3,2,2,1,2,3,2,4,0,10.0,neutral or dissatisfied +2476,36778,Male,Loyal Customer,50,Business travel,Business,2611,1,4,4,4,2,1,1,3,5,4,4,1,1,1,121,131.0,neutral or dissatisfied +2477,42217,Male,Loyal Customer,38,Business travel,Eco,784,4,5,5,5,4,4,4,4,2,2,1,5,4,4,0,0.0,satisfied +2478,13751,Female,Loyal Customer,24,Personal Travel,Eco,441,1,4,1,3,5,1,5,5,5,4,4,4,5,5,14,0.0,neutral or dissatisfied +2479,78788,Female,Loyal Customer,47,Business travel,Business,3446,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,3.0,satisfied +2480,127410,Male,Loyal Customer,50,Personal Travel,Eco,1009,1,4,1,1,3,1,2,3,3,5,1,3,3,3,0,6.0,neutral or dissatisfied +2481,106494,Male,Loyal Customer,53,Business travel,Business,495,3,3,3,3,2,5,4,4,4,4,4,4,4,5,2,0.0,satisfied +2482,59954,Female,Loyal Customer,30,Business travel,Business,937,2,4,4,4,2,2,2,2,4,4,4,1,4,2,20,11.0,neutral or dissatisfied +2483,102599,Male,Loyal Customer,40,Personal Travel,Eco Plus,407,2,1,2,3,1,2,2,1,1,4,4,2,3,1,6,7.0,neutral or dissatisfied +2484,25744,Female,Loyal Customer,44,Business travel,Eco,356,5,1,1,1,3,4,1,5,5,5,5,4,5,3,0,0.0,satisfied +2485,29161,Male,Loyal Customer,61,Business travel,Eco Plus,1050,4,2,2,2,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +2486,75367,Female,Loyal Customer,12,Personal Travel,Eco Plus,2504,1,1,1,4,5,1,5,5,4,1,4,1,4,5,53,47.0,neutral or dissatisfied +2487,78779,Male,Loyal Customer,46,Business travel,Business,447,1,1,1,1,4,3,3,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +2488,30523,Male,Loyal Customer,78,Business travel,Eco,464,4,2,1,2,4,4,4,4,3,5,2,3,3,4,26,33.0,neutral or dissatisfied +2489,87970,Male,disloyal Customer,19,Business travel,Business,594,5,1,5,1,1,5,1,1,3,2,5,5,5,1,1,0.0,satisfied +2490,109984,Male,Loyal Customer,46,Business travel,Business,3497,4,4,4,4,5,4,5,5,5,4,5,4,5,5,3,0.0,satisfied +2491,37952,Female,Loyal Customer,17,Personal Travel,Eco Plus,937,3,3,3,4,3,3,3,3,2,4,3,1,3,3,41,55.0,neutral or dissatisfied +2492,91255,Male,Loyal Customer,16,Personal Travel,Eco,406,2,5,2,1,5,2,5,5,3,5,4,3,5,5,1,12.0,neutral or dissatisfied +2493,22140,Female,Loyal Customer,34,Personal Travel,Eco,350,2,1,2,2,3,2,3,3,2,4,2,4,2,3,0,0.0,neutral or dissatisfied +2494,31360,Female,Loyal Customer,24,Business travel,Business,2786,2,2,2,2,4,4,4,4,1,2,2,3,2,4,0,4.0,satisfied +2495,102591,Female,Loyal Customer,46,Business travel,Eco Plus,397,4,2,2,2,2,1,4,3,3,4,3,4,3,5,4,0.0,satisfied +2496,49456,Male,Loyal Customer,53,Business travel,Business,363,1,1,1,1,5,1,4,5,5,5,5,4,5,2,0,1.0,satisfied +2497,29425,Male,Loyal Customer,72,Business travel,Eco Plus,2466,3,1,1,1,3,3,3,2,1,1,2,3,3,3,0,17.0,neutral or dissatisfied +2498,80293,Female,Loyal Customer,41,Business travel,Business,746,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +2499,105097,Male,disloyal Customer,26,Business travel,Business,220,4,0,4,1,5,4,5,5,4,3,5,4,5,5,0,0.0,satisfied +2500,26230,Male,Loyal Customer,40,Personal Travel,Eco,270,4,2,0,4,2,0,2,2,2,5,3,4,4,2,36,27.0,neutral or dissatisfied +2501,26287,Male,Loyal Customer,58,Business travel,Eco Plus,859,2,3,3,3,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +2502,12580,Female,Loyal Customer,24,Business travel,Business,542,5,5,5,5,4,4,4,4,2,3,3,5,3,4,0,0.0,satisfied +2503,23847,Male,Loyal Customer,41,Business travel,Eco,522,2,4,4,4,2,2,2,2,1,1,2,5,2,2,0,0.0,satisfied +2504,69545,Female,disloyal Customer,28,Business travel,Business,2475,2,2,2,4,2,2,2,4,4,3,4,2,3,2,0,0.0,neutral or dissatisfied +2505,117493,Female,disloyal Customer,32,Business travel,Eco,507,2,1,2,3,1,2,1,1,2,1,4,4,4,1,83,59.0,neutral or dissatisfied +2506,84460,Male,Loyal Customer,64,Personal Travel,Eco,290,4,5,4,2,3,4,3,3,5,2,4,5,4,3,0,10.0,satisfied +2507,85694,Male,disloyal Customer,27,Business travel,Business,1547,4,4,4,4,3,4,3,3,5,4,5,3,5,3,21,0.0,satisfied +2508,110536,Female,disloyal Customer,29,Business travel,Business,674,4,4,4,4,5,4,5,5,5,2,5,3,5,5,0,0.0,satisfied +2509,113918,Male,disloyal Customer,22,Business travel,Eco,901,4,4,4,4,2,4,2,2,4,5,5,3,4,2,6,0.0,neutral or dissatisfied +2510,110073,Female,Loyal Customer,40,Business travel,Business,579,3,3,3,3,4,3,3,3,3,4,3,2,3,1,0,17.0,neutral or dissatisfied +2511,44848,Female,Loyal Customer,55,Business travel,Eco Plus,760,2,5,5,5,4,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +2512,91902,Female,Loyal Customer,41,Business travel,Business,2475,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +2513,80129,Male,Loyal Customer,39,Business travel,Business,2475,5,5,5,5,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +2514,90303,Male,Loyal Customer,52,Personal Travel,Eco,879,2,4,3,1,2,3,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +2515,69629,Female,Loyal Customer,47,Business travel,Business,2099,4,2,2,2,3,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +2516,1804,Male,Loyal Customer,59,Business travel,Business,2149,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2517,8654,Male,Loyal Customer,51,Business travel,Business,2572,3,3,3,3,3,5,4,4,4,4,4,3,4,5,6,0.0,satisfied +2518,64749,Male,disloyal Customer,23,Business travel,Eco,551,4,0,4,4,5,4,5,5,5,2,5,3,4,5,0,0.0,satisfied +2519,16700,Female,Loyal Customer,63,Personal Travel,Eco,169,3,5,3,3,3,5,5,1,1,3,1,3,1,5,18,25.0,neutral or dissatisfied +2520,88725,Male,Loyal Customer,27,Personal Travel,Eco,581,3,5,4,2,1,4,1,1,4,2,4,4,5,1,1,0.0,neutral or dissatisfied +2521,67778,Female,disloyal Customer,44,Business travel,Business,1431,2,1,1,5,5,2,5,5,4,5,5,3,4,5,1,10.0,neutral or dissatisfied +2522,42503,Male,Loyal Customer,35,Business travel,Business,495,3,3,3,3,2,2,4,5,5,5,5,1,5,4,17,1.0,satisfied +2523,93558,Female,Loyal Customer,15,Personal Travel,Eco,719,4,4,4,4,4,4,4,4,5,5,5,4,3,4,228,211.0,neutral or dissatisfied +2524,100992,Male,Loyal Customer,45,Business travel,Business,2186,2,2,2,2,5,4,4,4,4,4,4,5,4,4,17,6.0,satisfied +2525,65624,Female,Loyal Customer,18,Personal Travel,Eco,237,3,4,3,3,4,3,4,4,2,1,3,2,1,4,0,0.0,neutral or dissatisfied +2526,94078,Female,Loyal Customer,42,Business travel,Business,2204,1,2,2,2,2,2,1,2,2,2,1,1,2,1,1,0.0,neutral or dissatisfied +2527,753,Female,Loyal Customer,57,Business travel,Business,354,0,0,0,3,3,4,5,3,3,4,4,4,3,3,6,8.0,satisfied +2528,102746,Male,Loyal Customer,26,Business travel,Business,255,2,2,2,2,4,4,4,4,4,5,5,4,5,4,6,10.0,satisfied +2529,83170,Male,Loyal Customer,30,Personal Travel,Eco Plus,957,3,5,3,3,2,3,2,2,3,3,5,4,5,2,26,7.0,neutral or dissatisfied +2530,55729,Male,Loyal Customer,40,Business travel,Business,1969,5,4,5,5,5,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +2531,13307,Female,Loyal Customer,36,Business travel,Business,448,4,4,4,4,2,3,3,4,4,4,4,2,4,1,0,0.0,satisfied +2532,29608,Male,Loyal Customer,18,Business travel,Business,3766,3,4,4,4,3,3,3,3,2,5,3,2,3,3,96,99.0,neutral or dissatisfied +2533,21670,Male,Loyal Customer,31,Business travel,Business,708,4,4,4,4,3,3,3,3,4,2,1,4,3,3,3,0.0,satisfied +2534,105133,Female,Loyal Customer,53,Business travel,Business,289,2,2,5,2,3,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +2535,41784,Male,Loyal Customer,63,Personal Travel,Eco,508,3,4,3,1,5,3,5,5,4,2,4,4,4,5,12,30.0,neutral or dissatisfied +2536,34080,Female,Loyal Customer,49,Business travel,Eco Plus,174,4,3,3,3,4,4,4,4,4,4,4,4,4,2,12,0.0,neutral or dissatisfied +2537,31893,Male,Loyal Customer,51,Personal Travel,Eco,2762,4,4,4,3,4,4,4,4,2,4,3,3,4,4,0,0.0,neutral or dissatisfied +2538,32057,Female,Loyal Customer,31,Business travel,Business,102,1,1,1,1,4,4,4,4,5,2,1,3,4,4,2,5.0,satisfied +2539,64168,Male,Loyal Customer,67,Personal Travel,Eco,989,3,4,3,3,1,3,1,1,5,4,4,4,5,1,24,23.0,neutral or dissatisfied +2540,106370,Male,Loyal Customer,30,Business travel,Business,2486,1,1,1,1,4,4,4,4,4,4,4,5,4,4,101,102.0,satisfied +2541,37410,Male,Loyal Customer,29,Business travel,Eco,828,2,2,3,3,2,2,2,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +2542,36097,Male,Loyal Customer,63,Personal Travel,Eco,399,2,4,2,4,5,2,1,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +2543,28627,Male,Loyal Customer,60,Business travel,Business,2355,4,2,3,2,3,3,3,4,4,4,4,3,4,1,59,5.0,neutral or dissatisfied +2544,40524,Male,Loyal Customer,58,Personal Travel,Eco Plus,188,3,3,3,2,5,3,1,5,2,4,1,4,2,5,0,0.0,neutral or dissatisfied +2545,110697,Female,Loyal Customer,63,Personal Travel,Eco,945,2,2,2,4,4,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +2546,94182,Female,disloyal Customer,24,Business travel,Eco,189,2,5,1,1,5,1,2,5,3,4,4,4,4,5,5,0.0,neutral or dissatisfied +2547,43866,Female,Loyal Customer,72,Business travel,Business,2971,4,4,4,4,3,4,5,4,4,4,3,5,4,5,0,0.0,satisfied +2548,26746,Male,Loyal Customer,45,Business travel,Business,3230,2,2,2,2,3,2,4,5,5,5,5,3,5,2,0,0.0,satisfied +2549,118104,Male,Loyal Customer,52,Business travel,Eco,499,1,3,2,2,2,1,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +2550,96266,Male,Loyal Customer,61,Personal Travel,Eco,546,2,3,2,2,5,2,5,5,2,2,2,2,2,5,21,8.0,neutral or dissatisfied +2551,74919,Male,Loyal Customer,41,Business travel,Business,2475,1,1,1,1,4,4,4,5,5,5,5,4,5,3,50,27.0,satisfied +2552,120703,Male,Loyal Customer,46,Personal Travel,Eco,280,3,4,3,4,5,3,4,5,3,4,3,3,4,5,0,0.0,neutral or dissatisfied +2553,32409,Male,disloyal Customer,36,Business travel,Eco,163,1,4,1,3,4,1,4,4,4,3,5,1,3,4,4,5.0,neutral or dissatisfied +2554,22458,Male,Loyal Customer,50,Personal Travel,Eco,143,4,4,4,4,4,4,4,4,4,4,3,2,4,4,88,83.0,neutral or dissatisfied +2555,99172,Female,Loyal Customer,24,Personal Travel,Eco,1076,2,5,2,3,4,2,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +2556,98815,Female,Loyal Customer,39,Business travel,Business,763,5,5,5,5,5,4,4,4,4,4,4,5,4,5,37,30.0,satisfied +2557,126067,Male,Loyal Customer,31,Business travel,Business,328,3,3,3,3,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +2558,54476,Male,Loyal Customer,30,Business travel,Business,3468,3,5,4,5,3,3,3,3,4,1,4,2,4,3,14,0.0,neutral or dissatisfied +2559,98835,Male,Loyal Customer,65,Personal Travel,Eco,444,1,5,1,3,1,4,4,4,3,5,5,4,4,4,146,143.0,neutral or dissatisfied +2560,98495,Female,Loyal Customer,40,Business travel,Business,402,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +2561,20134,Male,Loyal Customer,25,Personal Travel,Eco,416,3,3,3,4,3,3,3,3,1,1,3,1,3,3,34,16.0,neutral or dissatisfied +2562,4240,Female,Loyal Customer,41,Business travel,Business,3107,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +2563,69987,Female,Loyal Customer,52,Business travel,Business,2134,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +2564,104572,Female,Loyal Customer,43,Business travel,Business,369,2,1,2,2,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +2565,792,Female,Loyal Customer,41,Business travel,Business,158,1,1,3,1,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +2566,125206,Female,Loyal Customer,22,Business travel,Business,251,0,0,0,3,2,2,2,2,1,1,5,3,4,2,0,3.0,satisfied +2567,120869,Female,Loyal Customer,31,Business travel,Business,2523,1,1,1,1,4,4,4,4,4,4,4,4,4,4,5,0.0,satisfied +2568,43870,Female,disloyal Customer,39,Business travel,Eco,114,3,3,3,3,4,3,5,4,3,2,4,4,5,4,6,0.0,neutral or dissatisfied +2569,123464,Male,Loyal Customer,58,Business travel,Business,2296,4,4,4,4,5,5,5,4,3,5,4,5,4,5,9,15.0,satisfied +2570,127741,Female,Loyal Customer,45,Business travel,Business,3784,2,4,4,4,5,4,4,2,2,2,2,4,2,2,0,8.0,neutral or dissatisfied +2571,117908,Female,disloyal Customer,23,Business travel,Business,365,0,4,0,3,1,0,1,1,5,2,4,3,5,1,9,0.0,satisfied +2572,27644,Female,Loyal Customer,35,Personal Travel,Eco Plus,937,2,5,2,2,2,2,2,2,5,5,4,4,5,2,1,3.0,neutral or dissatisfied +2573,35279,Female,Loyal Customer,27,Business travel,Eco,1069,2,5,3,3,2,2,2,3,4,2,2,2,3,2,137,142.0,neutral or dissatisfied +2574,31041,Male,Loyal Customer,28,Business travel,Business,641,2,2,2,2,5,5,5,5,2,3,1,2,5,5,0,0.0,satisfied +2575,79970,Female,Loyal Customer,48,Business travel,Eco,1076,4,1,1,1,4,3,4,4,4,4,4,1,4,4,5,15.0,neutral or dissatisfied +2576,81735,Female,Loyal Customer,58,Business travel,Business,2572,2,2,2,2,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +2577,49333,Female,disloyal Customer,26,Business travel,Eco,308,2,0,2,4,4,2,4,4,3,2,4,5,3,4,4,0.0,neutral or dissatisfied +2578,66496,Male,disloyal Customer,36,Business travel,Eco,447,3,4,4,4,2,4,2,2,1,1,4,4,4,2,70,62.0,neutral or dissatisfied +2579,45361,Male,Loyal Customer,28,Personal Travel,Eco,150,1,4,1,1,1,1,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +2580,516,Male,Loyal Customer,57,Business travel,Business,247,5,5,5,5,4,5,5,3,3,4,3,3,3,4,0,0.0,satisfied +2581,61978,Female,Loyal Customer,63,Personal Travel,Business,2475,4,1,4,3,4,3,2,2,2,4,2,1,2,3,0,0.0,neutral or dissatisfied +2582,5431,Female,Loyal Customer,42,Business travel,Business,265,2,2,5,2,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +2583,76260,Male,Loyal Customer,60,Personal Travel,Eco Plus,1399,5,4,5,3,4,5,4,4,1,3,3,1,4,4,0,0.0,satisfied +2584,124153,Male,disloyal Customer,25,Business travel,Business,1304,0,0,0,3,4,0,3,4,3,3,5,4,4,4,0,0.0,satisfied +2585,16233,Male,Loyal Customer,39,Business travel,Business,2777,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,18.0,satisfied +2586,32817,Male,Loyal Customer,58,Business travel,Eco,102,2,1,3,3,2,2,2,2,4,2,3,1,4,2,0,0.0,neutral or dissatisfied +2587,49759,Male,disloyal Customer,38,Business travel,Eco,109,3,3,3,4,2,3,2,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +2588,84234,Male,Loyal Customer,69,Personal Travel,Eco,432,1,4,1,4,3,1,5,3,2,1,4,2,4,3,1,0.0,neutral or dissatisfied +2589,46783,Male,Loyal Customer,40,Business travel,Business,3101,3,3,3,3,2,5,5,4,4,4,4,3,4,3,58,78.0,satisfied +2590,63355,Female,Loyal Customer,53,Personal Travel,Eco,337,3,5,3,5,4,2,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +2591,84100,Male,Loyal Customer,70,Personal Travel,Eco Plus,932,4,2,4,4,3,4,3,3,1,4,3,4,3,3,18,38.0,neutral or dissatisfied +2592,46727,Male,Loyal Customer,49,Personal Travel,Eco,141,2,4,2,3,4,2,4,4,2,2,3,3,3,4,60,55.0,neutral or dissatisfied +2593,30133,Male,Loyal Customer,70,Personal Travel,Eco,31,2,5,0,4,4,0,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +2594,47539,Male,Loyal Customer,55,Personal Travel,Eco,558,4,4,4,3,2,4,3,2,4,3,5,4,2,2,0,0.0,neutral or dissatisfied +2595,30127,Female,Loyal Customer,48,Personal Travel,Eco,183,4,2,4,4,4,4,3,4,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +2596,63484,Male,Loyal Customer,38,Personal Travel,Eco Plus,337,2,5,2,3,1,2,1,1,5,4,5,5,4,1,0,10.0,neutral or dissatisfied +2597,63054,Female,Loyal Customer,43,Personal Travel,Eco,967,4,2,4,4,3,3,3,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +2598,124973,Male,disloyal Customer,54,Business travel,Eco,184,3,2,2,3,4,2,4,4,3,3,3,1,2,4,0,0.0,neutral or dissatisfied +2599,77103,Male,Loyal Customer,52,Business travel,Eco,1481,3,2,1,2,3,3,3,3,1,1,3,1,4,3,0,0.0,neutral or dissatisfied +2600,48181,Male,Loyal Customer,75,Business travel,Business,192,1,1,1,1,1,2,2,2,2,2,1,3,2,4,54,46.0,neutral or dissatisfied +2601,82258,Female,Loyal Customer,41,Business travel,Business,1481,4,4,4,4,2,5,5,4,4,5,4,4,4,4,4,0.0,satisfied +2602,28358,Female,disloyal Customer,25,Business travel,Eco Plus,867,1,4,2,4,1,2,1,1,2,1,3,3,3,1,0,0.0,neutral or dissatisfied +2603,55828,Male,Loyal Customer,47,Business travel,Business,1416,5,5,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +2604,128637,Female,Loyal Customer,21,Personal Travel,Eco,679,4,4,4,5,5,4,5,5,4,5,5,4,5,5,0,0.0,neutral or dissatisfied +2605,58693,Male,Loyal Customer,41,Personal Travel,Eco,299,3,4,3,5,4,3,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +2606,81156,Male,disloyal Customer,26,Business travel,Business,700,3,3,3,2,5,3,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +2607,75804,Male,Loyal Customer,48,Business travel,Eco Plus,813,1,4,4,4,1,1,1,1,1,3,4,2,3,1,0,0.0,neutral or dissatisfied +2608,37713,Male,Loyal Customer,51,Personal Travel,Eco,972,3,4,3,1,2,3,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +2609,120942,Female,Loyal Customer,58,Business travel,Business,3011,5,5,5,5,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2610,114121,Male,Loyal Customer,37,Personal Travel,Business,850,2,3,2,1,4,1,3,1,1,2,1,3,1,4,3,0.0,neutral or dissatisfied +2611,56047,Male,Loyal Customer,36,Business travel,Business,2050,5,5,5,5,5,5,5,1,3,4,2,5,1,5,24,33.0,satisfied +2612,118405,Male,Loyal Customer,31,Personal Travel,Business,451,2,5,3,4,5,3,5,5,4,1,2,3,5,5,63,68.0,neutral or dissatisfied +2613,103901,Female,Loyal Customer,22,Business travel,Eco Plus,882,3,5,5,5,3,3,2,3,2,4,3,4,3,3,42,46.0,neutral or dissatisfied +2614,99430,Male,Loyal Customer,37,Personal Travel,Eco,337,3,1,2,2,5,2,5,5,4,5,2,1,2,5,115,107.0,neutral or dissatisfied +2615,20539,Male,disloyal Customer,25,Business travel,Eco,565,4,4,4,4,2,4,4,2,2,2,3,3,3,2,34,13.0,neutral or dissatisfied +2616,92959,Male,Loyal Customer,51,Business travel,Business,1694,1,1,1,1,4,5,4,3,3,4,3,3,3,3,32,16.0,satisfied +2617,47133,Male,Loyal Customer,25,Personal Travel,Business,679,3,4,3,3,2,3,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +2618,45394,Male,Loyal Customer,47,Business travel,Eco,1437,5,1,1,1,5,5,5,5,3,1,2,1,1,5,0,0.0,satisfied +2619,6915,Female,Loyal Customer,27,Personal Travel,Eco,265,4,3,4,3,5,4,5,5,1,4,1,2,3,5,0,0.0,neutral or dissatisfied +2620,119734,Male,Loyal Customer,43,Personal Travel,Eco,1303,2,4,2,2,1,2,1,1,3,4,4,3,4,1,1,11.0,neutral or dissatisfied +2621,71526,Male,Loyal Customer,56,Business travel,Business,3954,3,2,5,2,1,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +2622,94972,Male,Loyal Customer,46,Business travel,Business,2138,0,0,0,3,2,5,1,4,4,4,1,1,4,2,0,0.0,satisfied +2623,78435,Male,disloyal Customer,23,Business travel,Business,526,5,5,5,1,5,3,3,5,4,5,4,3,3,3,214,203.0,satisfied +2624,79589,Male,disloyal Customer,27,Business travel,Business,762,4,4,4,4,1,4,1,1,4,2,5,5,4,1,0,0.0,satisfied +2625,22867,Male,Loyal Customer,27,Personal Travel,Eco,147,2,4,2,3,3,2,1,3,4,3,5,3,5,3,0,0.0,neutral or dissatisfied +2626,116452,Female,Loyal Customer,66,Personal Travel,Eco,296,2,4,2,5,5,5,5,4,4,2,5,3,4,5,16,6.0,neutral or dissatisfied +2627,24280,Female,Loyal Customer,62,Personal Travel,Eco,170,2,3,2,1,3,4,2,3,3,2,3,1,3,1,0,0.0,neutral or dissatisfied +2628,99133,Female,Loyal Customer,33,Personal Travel,Eco,237,2,5,2,3,3,2,3,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +2629,108471,Male,Loyal Customer,25,Personal Travel,Eco,1444,4,4,4,4,3,4,5,3,2,2,2,1,4,3,0,7.0,neutral or dissatisfied +2630,127265,Female,Loyal Customer,29,Business travel,Eco,1107,3,4,3,4,3,3,3,3,1,3,3,3,3,3,0,0.0,neutral or dissatisfied +2631,74998,Male,Loyal Customer,15,Personal Travel,Eco,2454,1,2,1,4,3,1,2,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +2632,48024,Female,Loyal Customer,36,Business travel,Eco,1384,4,3,3,3,4,4,4,4,3,3,2,3,4,4,82,72.0,satisfied +2633,8807,Female,Loyal Customer,46,Business travel,Eco,552,3,4,4,4,4,4,4,3,3,3,3,2,3,3,0,10.0,neutral or dissatisfied +2634,101969,Male,disloyal Customer,35,Business travel,Eco,804,1,0,0,1,2,0,2,2,4,2,3,1,5,2,0,1.0,neutral or dissatisfied +2635,82369,Male,Loyal Customer,60,Business travel,Business,3015,3,3,3,3,2,4,5,4,4,4,4,5,4,4,15,33.0,satisfied +2636,109196,Female,Loyal Customer,51,Business travel,Eco,616,2,1,1,1,5,4,4,2,2,2,2,4,2,1,104,94.0,neutral or dissatisfied +2637,4187,Female,Loyal Customer,58,Business travel,Business,431,4,4,4,4,4,4,4,5,5,5,5,5,5,3,26,15.0,satisfied +2638,111757,Male,Loyal Customer,33,Business travel,Business,1436,3,3,3,3,4,4,4,4,4,4,5,3,5,4,12,0.0,satisfied +2639,119421,Female,Loyal Customer,7,Personal Travel,Eco,399,2,5,3,1,3,3,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +2640,19536,Male,Loyal Customer,52,Business travel,Business,2891,5,5,5,5,2,1,2,4,4,4,3,3,4,4,0,0.0,satisfied +2641,28499,Female,Loyal Customer,61,Personal Travel,Business,2715,3,4,3,4,3,4,5,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +2642,74168,Male,Loyal Customer,65,Personal Travel,Eco,721,4,3,4,3,1,4,1,1,2,5,4,4,4,1,0,0.0,neutral or dissatisfied +2643,49709,Female,Loyal Customer,32,Business travel,Business,262,5,5,5,5,5,5,5,5,2,2,1,1,4,5,2,0.0,satisfied +2644,45980,Male,Loyal Customer,46,Business travel,Eco,483,3,2,2,2,3,3,3,3,5,4,4,2,4,3,5,0.0,satisfied +2645,6888,Male,disloyal Customer,40,Business travel,Business,287,3,3,3,4,1,3,1,1,5,4,5,5,5,1,2,0.0,neutral or dissatisfied +2646,126488,Female,disloyal Customer,47,Business travel,Eco,349,3,0,3,1,1,3,1,1,2,2,4,5,2,1,0,0.0,neutral or dissatisfied +2647,64013,Female,Loyal Customer,49,Business travel,Business,3206,3,3,3,3,1,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +2648,123727,Female,Loyal Customer,49,Business travel,Business,1795,2,2,2,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2649,32135,Female,Loyal Customer,30,Business travel,Eco,163,5,4,4,4,5,5,5,5,3,2,5,3,2,5,0,3.0,satisfied +2650,61233,Female,Loyal Customer,45,Business travel,Business,3031,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +2651,17473,Male,Loyal Customer,39,Business travel,Eco,341,5,2,2,2,5,5,5,5,2,1,3,2,5,5,0,0.0,satisfied +2652,86001,Female,Loyal Customer,56,Business travel,Business,447,3,3,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +2653,47737,Female,Loyal Customer,70,Personal Travel,Business,550,3,0,3,3,3,3,5,2,2,3,2,4,2,3,1,0.0,neutral or dissatisfied +2654,20058,Male,Loyal Customer,14,Personal Travel,Eco,738,2,4,2,1,4,2,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +2655,117903,Female,Loyal Customer,33,Business travel,Business,365,2,4,4,4,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +2656,60246,Male,Loyal Customer,19,Personal Travel,Eco,1546,2,4,2,1,2,2,2,2,5,4,3,4,5,2,0,0.0,neutral or dissatisfied +2657,110721,Female,Loyal Customer,42,Business travel,Business,2119,5,4,5,5,5,5,5,4,4,4,4,5,4,3,1,1.0,satisfied +2658,9315,Female,Loyal Customer,59,Business travel,Business,419,2,5,5,5,4,3,3,2,2,2,2,1,2,2,12,4.0,neutral or dissatisfied +2659,93758,Male,Loyal Customer,47,Business travel,Business,3361,5,5,5,5,1,5,5,2,2,2,2,1,2,2,6,6.0,satisfied +2660,31202,Female,Loyal Customer,32,Business travel,Business,2780,4,5,2,5,4,4,4,4,2,1,3,1,3,4,26,26.0,neutral or dissatisfied +2661,54171,Female,disloyal Customer,26,Business travel,Eco,1504,3,3,3,2,4,3,4,4,5,4,3,4,3,4,0,0.0,neutral or dissatisfied +2662,9090,Female,Loyal Customer,68,Personal Travel,Eco,160,2,5,2,3,5,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +2663,10884,Female,Loyal Customer,36,Business travel,Business,2700,2,2,4,2,2,3,4,2,2,2,2,2,2,2,2,0.0,neutral or dissatisfied +2664,55992,Male,Loyal Customer,24,Personal Travel,Business,2586,4,4,4,3,4,5,5,2,2,3,3,5,4,5,12,22.0,neutral or dissatisfied +2665,13487,Male,Loyal Customer,32,Business travel,Business,3660,0,0,0,3,1,1,1,1,1,2,3,1,3,1,60,49.0,satisfied +2666,103823,Male,Loyal Customer,51,Business travel,Eco,1048,3,1,1,1,3,3,3,3,3,1,3,1,3,3,1,0.0,neutral or dissatisfied +2667,114349,Male,Loyal Customer,43,Personal Travel,Eco,819,3,5,3,4,4,3,4,4,4,2,5,4,5,4,54,35.0,neutral or dissatisfied +2668,99896,Male,Loyal Customer,36,Business travel,Business,3874,0,0,0,4,1,5,5,2,2,1,1,5,2,3,5,0.0,satisfied +2669,98831,Female,Loyal Customer,16,Personal Travel,Eco,763,2,5,2,5,5,2,5,5,5,3,5,3,4,5,21,9.0,neutral or dissatisfied +2670,79478,Male,disloyal Customer,34,Business travel,Business,712,3,2,2,2,2,2,2,2,5,2,5,3,5,2,0,9.0,neutral or dissatisfied +2671,548,Female,disloyal Customer,55,Business travel,Business,134,3,3,3,5,3,3,4,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +2672,112555,Male,Loyal Customer,52,Business travel,Business,3000,3,3,3,3,4,5,5,4,4,5,4,4,4,3,15,1.0,satisfied +2673,37339,Female,Loyal Customer,58,Business travel,Eco,1076,3,4,4,4,3,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +2674,123692,Male,Loyal Customer,55,Personal Travel,Eco,214,5,3,5,3,4,5,4,4,1,4,4,4,4,4,0,0.0,satisfied +2675,2412,Male,Loyal Customer,47,Business travel,Eco,204,3,2,2,2,3,3,3,3,2,5,1,4,2,3,0,0.0,neutral or dissatisfied +2676,15982,Female,disloyal Customer,36,Business travel,Eco,780,2,2,2,4,5,2,5,5,4,4,3,1,4,5,7,0.0,neutral or dissatisfied +2677,12595,Female,Loyal Customer,61,Business travel,Business,3451,0,3,0,3,5,3,5,5,5,5,5,3,5,4,4,2.0,satisfied +2678,42761,Male,disloyal Customer,29,Business travel,Eco,493,1,3,1,4,4,1,4,4,3,5,4,5,3,4,0,0.0,neutral or dissatisfied +2679,75759,Male,Loyal Customer,20,Personal Travel,Eco,868,1,5,1,5,2,1,2,2,1,1,4,1,5,2,0,0.0,neutral or dissatisfied +2680,24322,Male,Loyal Customer,43,Business travel,Business,3800,3,3,3,3,2,3,4,4,4,4,4,4,4,3,2,14.0,satisfied +2681,57475,Female,disloyal Customer,24,Business travel,Eco,680,0,0,0,2,2,0,2,2,3,5,5,4,4,2,1,0.0,satisfied +2682,74328,Female,Loyal Customer,58,Business travel,Business,1171,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +2683,90933,Female,Loyal Customer,36,Business travel,Business,3919,2,3,3,3,2,3,3,2,2,2,2,3,2,2,1,1.0,neutral or dissatisfied +2684,13642,Male,Loyal Customer,22,Personal Travel,Eco,835,3,4,3,3,3,3,3,3,3,3,4,5,4,3,9,0.0,neutral or dissatisfied +2685,10439,Female,Loyal Customer,42,Business travel,Business,1546,1,1,1,1,2,4,4,5,5,5,5,3,5,5,0,1.0,satisfied +2686,110869,Male,disloyal Customer,25,Business travel,Business,545,4,0,4,3,1,4,1,1,3,4,5,5,5,1,73,74.0,neutral or dissatisfied +2687,12113,Male,disloyal Customer,18,Business travel,Eco,1034,4,4,4,2,2,4,4,2,2,2,3,4,2,2,1,0.0,neutral or dissatisfied +2688,31201,Female,Loyal Customer,44,Business travel,Business,628,3,1,3,3,3,3,3,2,3,2,3,3,4,3,124,147.0,neutral or dissatisfied +2689,78622,Female,Loyal Customer,22,Business travel,Business,1426,2,5,5,5,2,2,2,2,3,3,2,2,2,2,203,179.0,neutral or dissatisfied +2690,56380,Male,Loyal Customer,41,Business travel,Business,1624,5,5,5,5,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +2691,117782,Male,Loyal Customer,53,Personal Travel,Eco,1912,2,4,2,4,4,2,4,4,3,5,4,4,4,4,9,0.0,neutral or dissatisfied +2692,13141,Female,Loyal Customer,39,Personal Travel,Eco,562,3,5,3,2,2,3,2,2,4,5,5,3,4,2,0,0.0,neutral or dissatisfied +2693,76252,Male,Loyal Customer,13,Personal Travel,Eco,1399,1,5,1,2,1,1,1,1,3,4,3,4,4,1,0,0.0,neutral or dissatisfied +2694,86895,Female,disloyal Customer,22,Business travel,Eco,341,4,0,4,2,2,4,2,2,3,5,5,3,5,2,0,0.0,satisfied +2695,58803,Female,disloyal Customer,29,Personal Travel,Eco,1005,4,5,4,3,4,4,4,4,5,3,4,3,4,4,2,0.0,neutral or dissatisfied +2696,49412,Male,Loyal Customer,53,Business travel,Eco,109,4,2,2,2,4,4,4,4,1,2,3,5,3,4,5,8.0,satisfied +2697,26665,Female,disloyal Customer,34,Business travel,Eco,404,3,3,3,5,3,3,5,3,2,5,1,1,1,3,0,0.0,neutral or dissatisfied +2698,1268,Female,Loyal Customer,60,Personal Travel,Eco,396,3,3,2,4,1,3,3,5,5,2,5,2,5,1,0,0.0,neutral or dissatisfied +2699,109889,Female,Loyal Customer,23,Business travel,Business,3982,2,5,5,5,2,2,2,2,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +2700,69078,Female,Loyal Customer,23,Business travel,Eco,1389,5,1,1,1,5,5,3,5,1,5,1,1,5,5,0,0.0,satisfied +2701,61072,Female,Loyal Customer,50,Business travel,Eco,1709,4,3,3,3,4,3,2,4,4,4,4,4,4,2,3,15.0,neutral or dissatisfied +2702,24119,Female,Loyal Customer,62,Personal Travel,Eco,510,4,5,4,2,3,5,5,3,3,4,3,4,3,5,55,46.0,satisfied +2703,56374,Female,Loyal Customer,26,Personal Travel,Eco,200,3,5,3,1,3,3,2,3,2,4,3,1,3,3,0,0.0,neutral or dissatisfied +2704,102254,Female,Loyal Customer,48,Business travel,Business,1951,3,3,3,3,2,4,5,5,5,5,4,4,5,5,28,25.0,satisfied +2705,54879,Male,Loyal Customer,27,Personal Travel,Eco,862,2,4,3,3,5,3,5,5,4,5,4,3,5,5,22,12.0,neutral or dissatisfied +2706,85648,Female,Loyal Customer,26,Personal Travel,Eco Plus,153,4,5,4,4,3,4,3,3,4,3,4,4,4,3,0,0.0,satisfied +2707,62970,Male,Loyal Customer,50,Business travel,Eco,862,4,5,5,5,4,4,4,4,1,2,4,2,4,4,0,11.0,neutral or dissatisfied +2708,121098,Male,Loyal Customer,44,Personal Travel,Eco,1558,3,5,3,5,4,3,4,4,4,3,5,4,4,4,3,8.0,neutral or dissatisfied +2709,39533,Male,Loyal Customer,38,Business travel,Business,945,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +2710,127897,Female,disloyal Customer,39,Business travel,Business,1671,3,4,4,1,3,4,1,3,3,2,5,5,5,3,10,16.0,neutral or dissatisfied +2711,118508,Female,disloyal Customer,25,Business travel,Business,304,2,4,2,3,3,2,3,3,3,5,5,5,5,3,20,12.0,neutral or dissatisfied +2712,35554,Female,Loyal Customer,45,Personal Travel,Eco,989,1,1,1,4,5,3,4,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +2713,96950,Female,disloyal Customer,25,Business travel,Business,883,3,4,3,3,4,3,4,4,5,5,4,4,5,4,46,34.0,neutral or dissatisfied +2714,128766,Male,Loyal Customer,49,Business travel,Eco,150,5,4,4,4,5,5,5,2,4,2,2,5,4,5,109,135.0,satisfied +2715,16439,Female,Loyal Customer,30,Business travel,Business,1981,4,4,4,4,4,4,4,4,2,4,5,4,3,4,0,0.0,satisfied +2716,76964,Female,Loyal Customer,37,Personal Travel,Eco,1990,4,5,4,4,1,4,4,1,2,1,1,2,1,1,0,0.0,neutral or dissatisfied +2717,23770,Female,Loyal Customer,69,Personal Travel,Business,374,3,1,3,3,5,3,2,3,3,3,3,3,3,4,0,8.0,neutral or dissatisfied +2718,79405,Male,Loyal Customer,47,Business travel,Business,509,3,3,3,3,4,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +2719,71490,Female,Loyal Customer,29,Business travel,Business,3449,5,2,2,2,5,4,5,5,4,4,4,3,3,5,6,19.0,neutral or dissatisfied +2720,24342,Female,disloyal Customer,20,Business travel,Eco,634,4,3,4,2,3,4,1,3,4,4,2,4,2,3,0,0.0,neutral or dissatisfied +2721,103382,Female,Loyal Customer,44,Business travel,Business,237,5,5,5,5,3,4,4,4,4,4,4,5,4,3,14,6.0,satisfied +2722,44834,Female,Loyal Customer,70,Personal Travel,Eco,462,5,5,5,3,1,4,2,5,5,5,5,4,5,2,0,0.0,satisfied +2723,52244,Male,disloyal Customer,21,Business travel,Eco,451,3,3,4,2,4,4,4,4,3,4,4,4,1,4,12,13.0,neutral or dissatisfied +2724,90539,Female,Loyal Customer,33,Business travel,Business,2830,3,3,3,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +2725,7420,Male,Loyal Customer,54,Business travel,Business,552,1,4,3,3,2,4,4,1,1,1,1,2,1,4,7,0.0,neutral or dissatisfied +2726,34646,Female,Loyal Customer,65,Personal Travel,Eco,427,1,0,1,5,3,5,4,4,4,1,1,4,4,4,46,56.0,neutral or dissatisfied +2727,44514,Male,disloyal Customer,26,Business travel,Eco,157,1,3,1,1,4,1,4,4,5,3,4,2,5,4,2,0.0,neutral or dissatisfied +2728,100681,Female,Loyal Customer,24,Business travel,Business,2782,3,3,3,3,3,3,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +2729,43734,Male,disloyal Customer,40,Business travel,Eco,294,4,0,4,1,5,4,5,5,4,4,1,2,2,5,0,6.0,satisfied +2730,89289,Male,Loyal Customer,30,Business travel,Business,453,5,5,5,5,5,5,5,5,3,3,5,5,5,5,25,34.0,satisfied +2731,30286,Female,Loyal Customer,33,Business travel,Business,1476,2,2,2,2,2,4,1,5,5,5,5,2,5,3,0,3.0,satisfied +2732,117572,Female,Loyal Customer,30,Business travel,Business,1020,3,3,3,3,3,3,3,3,1,1,2,1,3,3,1,0.0,neutral or dissatisfied +2733,89766,Female,Loyal Customer,9,Personal Travel,Eco,950,4,1,4,4,2,4,2,2,2,1,2,1,3,2,0,2.0,satisfied +2734,74019,Male,Loyal Customer,53,Business travel,Business,1471,1,1,1,1,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +2735,47198,Male,Loyal Customer,39,Business travel,Eco,279,2,5,1,5,2,2,2,2,2,2,4,1,3,2,16,30.0,neutral or dissatisfied +2736,48932,Female,Loyal Customer,29,Business travel,Business,2781,3,4,3,3,5,5,5,5,3,1,3,5,3,5,0,10.0,satisfied +2737,122000,Male,disloyal Customer,27,Business travel,Business,130,4,4,4,2,5,4,5,5,3,3,5,3,5,5,0,3.0,satisfied +2738,120929,Male,Loyal Customer,47,Business travel,Business,3612,4,4,3,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +2739,52990,Male,Loyal Customer,42,Business travel,Business,1208,1,1,1,1,3,2,2,5,5,4,5,4,5,4,39,37.0,satisfied +2740,112265,Male,disloyal Customer,57,Business travel,Eco,1393,2,2,2,4,3,2,4,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +2741,129876,Male,Loyal Customer,28,Personal Travel,Eco Plus,447,4,4,4,2,4,4,1,4,5,4,4,4,5,4,2,3.0,neutral or dissatisfied +2742,119034,Male,disloyal Customer,48,Business travel,Business,2378,3,3,3,4,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +2743,114004,Male,Loyal Customer,18,Personal Travel,Eco,1855,4,2,4,4,5,4,5,5,1,4,4,1,3,5,0,0.0,neutral or dissatisfied +2744,26897,Male,Loyal Customer,26,Business travel,Business,1770,4,4,4,4,3,3,3,3,4,5,5,3,5,3,0,0.0,satisfied +2745,75972,Female,Loyal Customer,60,Business travel,Business,3637,4,3,4,4,5,5,5,4,4,4,4,4,4,3,0,1.0,satisfied +2746,120058,Female,Loyal Customer,21,Personal Travel,Eco,237,3,4,0,3,4,0,4,4,5,2,4,4,4,4,0,10.0,neutral or dissatisfied +2747,95476,Male,Loyal Customer,40,Business travel,Business,1679,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +2748,110020,Male,Loyal Customer,49,Personal Travel,Eco,1142,3,4,3,3,4,3,4,4,1,5,2,1,4,4,0,0.0,neutral or dissatisfied +2749,92494,Female,Loyal Customer,38,Business travel,Business,3081,4,4,4,4,2,2,1,4,4,4,4,4,4,2,0,0.0,satisfied +2750,3083,Female,Loyal Customer,34,Business travel,Business,1884,3,1,1,1,3,4,3,3,3,3,3,3,3,3,8,0.0,neutral or dissatisfied +2751,7862,Female,disloyal Customer,38,Business travel,Business,948,4,4,4,3,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +2752,66799,Male,Loyal Customer,43,Business travel,Business,1803,1,1,1,1,3,5,4,1,1,2,1,5,1,5,5,0.0,satisfied +2753,69067,Male,disloyal Customer,31,Business travel,Eco,1389,3,3,3,4,5,3,5,5,4,2,4,2,3,5,126,115.0,neutral or dissatisfied +2754,78753,Male,disloyal Customer,20,Business travel,Eco,447,3,1,3,3,2,3,5,2,4,4,3,2,3,2,33,37.0,neutral or dissatisfied +2755,56157,Female,disloyal Customer,46,Business travel,Eco,1400,1,1,1,1,5,1,5,5,4,4,1,1,2,5,0,7.0,neutral or dissatisfied +2756,80486,Male,Loyal Customer,53,Personal Travel,Eco Plus,1299,2,4,2,4,2,2,2,2,4,4,5,3,4,2,0,0.0,neutral or dissatisfied +2757,4891,Female,Loyal Customer,47,Personal Travel,Eco Plus,408,4,5,4,3,4,4,5,4,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +2758,126181,Female,Loyal Customer,51,Business travel,Business,3633,2,5,5,5,2,2,2,2,2,2,2,2,2,2,8,9.0,neutral or dissatisfied +2759,68564,Female,Loyal Customer,54,Business travel,Business,1616,3,3,3,3,3,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +2760,75427,Male,disloyal Customer,17,Business travel,Business,1096,0,5,0,4,4,0,4,4,3,5,5,4,4,4,9,0.0,satisfied +2761,16528,Female,Loyal Customer,41,Business travel,Eco,209,3,4,4,4,4,3,4,4,3,1,3,3,3,4,0,11.0,neutral or dissatisfied +2762,89283,Female,Loyal Customer,38,Business travel,Business,3174,2,2,2,2,2,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +2763,30706,Male,Loyal Customer,59,Business travel,Business,464,4,4,4,4,5,5,5,4,4,4,4,5,4,5,13,7.0,satisfied +2764,106995,Male,Loyal Customer,51,Personal Travel,Eco,937,3,5,2,3,4,2,4,4,4,1,1,5,5,4,89,84.0,neutral or dissatisfied +2765,43104,Female,Loyal Customer,66,Personal Travel,Eco,259,3,4,3,1,1,4,1,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +2766,127747,Female,disloyal Customer,34,Business travel,Eco,601,1,0,1,2,3,1,3,3,2,5,1,1,3,3,20,18.0,neutral or dissatisfied +2767,8071,Male,Loyal Customer,51,Business travel,Business,3530,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +2768,22673,Male,Loyal Customer,50,Business travel,Business,589,4,4,4,4,4,3,3,2,2,3,2,4,2,5,0,0.0,satisfied +2769,100414,Male,Loyal Customer,57,Personal Travel,Eco Plus,1052,2,5,2,3,2,2,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +2770,56078,Male,Loyal Customer,51,Personal Travel,Eco,2586,3,1,3,4,3,1,5,1,5,4,4,5,2,5,6,0.0,neutral or dissatisfied +2771,101772,Female,Loyal Customer,46,Business travel,Business,1521,2,4,4,4,2,3,4,2,2,2,2,4,2,2,4,,neutral or dissatisfied +2772,126216,Male,Loyal Customer,38,Business travel,Business,1764,2,2,2,2,4,5,4,4,4,3,4,5,4,3,11,4.0,satisfied +2773,69390,Female,disloyal Customer,26,Business travel,Business,1096,4,4,4,4,5,4,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +2774,115585,Male,disloyal Customer,61,Business travel,Eco,308,2,2,2,2,5,2,4,5,3,2,2,4,2,5,10,8.0,neutral or dissatisfied +2775,99060,Male,Loyal Customer,50,Business travel,Business,1521,2,2,2,2,5,5,4,4,4,4,4,4,4,4,74,81.0,satisfied +2776,45747,Female,Loyal Customer,69,Personal Travel,Business,391,2,4,2,2,2,3,5,4,4,2,2,3,4,4,0,0.0,neutral or dissatisfied +2777,71433,Male,Loyal Customer,30,Business travel,Business,3493,1,1,1,1,2,2,2,2,5,3,4,4,4,2,0,0.0,satisfied +2778,112966,Male,Loyal Customer,63,Personal Travel,Eco,1642,2,5,2,2,2,2,2,2,3,4,4,3,5,2,125,119.0,neutral or dissatisfied +2779,100357,Male,Loyal Customer,17,Personal Travel,Eco,1033,2,4,2,3,1,2,1,1,5,5,4,3,5,1,0,9.0,neutral or dissatisfied +2780,92444,Male,Loyal Customer,56,Business travel,Business,1892,1,1,1,1,5,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +2781,102974,Male,Loyal Customer,39,Personal Travel,Business,666,2,1,2,2,4,2,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +2782,36767,Female,Loyal Customer,46,Business travel,Business,2704,5,3,5,5,2,2,2,3,4,4,1,2,3,2,3,0.0,satisfied +2783,43454,Male,Loyal Customer,25,Business travel,Eco,679,0,4,0,5,1,0,1,1,3,1,2,1,3,1,10,2.0,satisfied +2784,62215,Male,Loyal Customer,34,Personal Travel,Eco,2565,3,4,3,4,4,3,4,4,3,2,4,3,5,4,16,102.0,neutral or dissatisfied +2785,9137,Male,disloyal Customer,12,Business travel,Eco,826,2,2,2,4,5,2,5,5,2,3,3,2,4,5,69,72.0,neutral or dissatisfied +2786,57691,Male,disloyal Customer,27,Business travel,Business,867,4,4,4,5,5,4,5,5,3,5,4,4,5,5,0,0.0,satisfied +2787,100942,Male,Loyal Customer,42,Business travel,Business,1204,2,2,2,2,2,4,4,4,4,4,4,5,4,3,2,0.0,satisfied +2788,22950,Male,Loyal Customer,35,Business travel,Business,489,3,4,4,4,3,2,2,3,3,3,3,3,3,3,0,1.0,neutral or dissatisfied +2789,21259,Female,Loyal Customer,38,Personal Travel,Eco Plus,153,1,2,1,1,3,1,3,3,1,2,2,2,1,3,14,6.0,neutral or dissatisfied +2790,100598,Male,disloyal Customer,24,Business travel,Eco,718,1,1,1,3,5,1,5,5,4,5,4,4,5,5,28,22.0,neutral or dissatisfied +2791,31662,Male,Loyal Customer,41,Business travel,Eco,967,5,4,4,4,5,5,5,5,5,2,4,5,1,5,11,5.0,satisfied +2792,73481,Female,Loyal Customer,25,Personal Travel,Eco,1197,2,4,2,1,1,2,1,1,3,4,4,3,4,1,18,25.0,neutral or dissatisfied +2793,111835,Male,Loyal Customer,40,Business travel,Business,1605,4,4,4,4,5,5,5,4,3,5,4,5,3,5,138,113.0,satisfied +2794,9105,Male,disloyal Customer,45,Business travel,Business,707,2,2,2,3,2,2,2,4,3,4,4,2,5,2,366,347.0,neutral or dissatisfied +2795,34062,Male,disloyal Customer,26,Business travel,Eco,955,3,3,3,4,1,3,1,1,3,4,3,4,4,1,0,0.0,neutral or dissatisfied +2796,86834,Female,disloyal Customer,23,Business travel,Eco,692,4,4,4,3,4,2,2,4,3,3,4,2,1,2,149,171.0,neutral or dissatisfied +2797,80699,Male,Loyal Customer,47,Personal Travel,Eco,874,2,0,2,3,4,2,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +2798,103508,Male,Loyal Customer,68,Business travel,Business,2585,2,2,2,2,2,3,2,2,2,2,2,1,2,2,6,30.0,neutral or dissatisfied +2799,113759,Male,Loyal Customer,31,Personal Travel,Eco,223,2,0,2,3,1,2,1,1,4,4,4,3,4,1,30,42.0,neutral or dissatisfied +2800,75226,Male,disloyal Customer,23,Business travel,Eco,244,2,1,2,3,4,2,4,4,2,5,3,4,3,4,0,4.0,neutral or dissatisfied +2801,95817,Female,disloyal Customer,22,Business travel,Eco,955,2,2,2,4,3,2,3,3,4,3,5,4,5,3,34,16.0,neutral or dissatisfied +2802,28225,Male,Loyal Customer,46,Personal Travel,Eco Plus,834,4,5,4,4,1,4,1,1,5,2,5,5,5,1,0,1.0,neutral or dissatisfied +2803,22058,Male,Loyal Customer,30,Business travel,Business,1819,3,3,5,3,4,4,4,4,3,4,1,4,2,4,0,0.0,satisfied +2804,117556,Male,Loyal Customer,32,Business travel,Business,3262,3,3,3,3,5,5,5,5,3,4,4,5,4,5,3,0.0,satisfied +2805,92566,Male,Loyal Customer,29,Business travel,Business,2139,5,5,5,5,4,4,4,4,3,5,3,4,4,4,0,0.0,satisfied +2806,10297,Female,Loyal Customer,42,Business travel,Business,429,1,1,5,1,4,4,5,5,5,5,5,4,5,3,18,13.0,satisfied +2807,118349,Female,Loyal Customer,18,Personal Travel,Eco,602,3,2,3,3,3,3,3,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +2808,7414,Female,Loyal Customer,24,Business travel,Business,522,3,2,5,2,3,3,3,3,3,2,3,4,3,3,11,52.0,neutral or dissatisfied +2809,26001,Female,Loyal Customer,46,Business travel,Business,3057,2,2,5,2,3,5,5,5,5,5,5,4,5,3,7,3.0,satisfied +2810,127287,Female,Loyal Customer,46,Personal Travel,Eco,1107,1,4,1,3,3,4,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +2811,15366,Female,Loyal Customer,38,Business travel,Eco,433,2,3,3,3,2,3,2,2,1,4,5,3,1,2,0,0.0,satisfied +2812,125323,Male,disloyal Customer,8,Business travel,Eco,599,2,0,2,2,4,2,4,4,3,2,5,5,5,4,0,0.0,neutral or dissatisfied +2813,58663,Male,Loyal Customer,46,Personal Travel,Eco,867,3,5,3,3,2,3,2,2,2,5,2,2,4,2,0,0.0,neutral or dissatisfied +2814,102184,Male,Loyal Customer,62,Business travel,Eco,258,2,5,5,5,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +2815,38632,Female,Loyal Customer,49,Business travel,Business,2704,2,2,2,2,3,4,1,4,4,4,4,5,4,4,108,90.0,satisfied +2816,27751,Female,Loyal Customer,23,Business travel,Business,1533,4,4,3,4,5,5,5,5,1,4,1,5,4,5,2,13.0,satisfied +2817,33629,Male,Loyal Customer,38,Personal Travel,Eco,474,4,3,4,3,3,4,3,3,3,3,4,5,5,3,12,1.0,satisfied +2818,75071,Female,Loyal Customer,68,Business travel,Business,3033,1,1,4,1,3,2,4,5,5,5,5,1,5,3,0,0.0,satisfied +2819,76075,Female,disloyal Customer,10,Business travel,Eco,669,2,1,1,3,1,1,1,1,1,1,4,4,4,1,0,7.0,neutral or dissatisfied +2820,26315,Female,Loyal Customer,41,Personal Travel,Eco,2139,1,4,1,1,3,1,3,3,3,3,3,5,5,3,0,9.0,neutral or dissatisfied +2821,36756,Male,disloyal Customer,26,Business travel,Business,2611,1,1,1,2,1,4,4,4,4,4,1,4,1,4,2,0.0,neutral or dissatisfied +2822,75650,Male,Loyal Customer,58,Business travel,Business,1659,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,5.0,satisfied +2823,34190,Male,Loyal Customer,13,Personal Travel,Eco,1189,4,2,4,3,4,4,4,4,1,1,3,3,3,4,0,0.0,satisfied +2824,53793,Female,Loyal Customer,42,Business travel,Business,3848,2,2,2,2,5,4,4,4,4,5,4,5,4,1,0,0.0,satisfied +2825,18482,Female,Loyal Customer,41,Business travel,Business,383,5,5,5,5,5,2,4,4,4,4,4,4,4,3,20,16.0,satisfied +2826,60155,Male,Loyal Customer,18,Personal Travel,Eco,1012,3,5,3,3,5,3,5,5,1,2,1,4,5,5,0,1.0,neutral or dissatisfied +2827,115233,Female,disloyal Customer,37,Business travel,Business,446,2,2,2,2,1,2,1,1,3,5,5,5,5,1,3,0.0,neutral or dissatisfied +2828,114767,Female,disloyal Customer,36,Business travel,Eco,372,3,1,4,4,3,4,2,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +2829,14248,Male,Loyal Customer,47,Personal Travel,Eco,1027,2,5,2,4,1,2,1,1,2,2,3,2,5,1,0,0.0,neutral or dissatisfied +2830,94291,Male,Loyal Customer,60,Business travel,Business,3349,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +2831,81030,Female,Loyal Customer,23,Business travel,Business,3553,1,1,1,1,4,4,4,4,5,4,4,4,5,4,9,6.0,satisfied +2832,101271,Female,disloyal Customer,30,Business travel,Business,978,0,0,0,1,4,0,4,4,5,4,4,5,4,4,18,6.0,satisfied +2833,42423,Female,Loyal Customer,32,Personal Travel,Eco Plus,451,2,5,2,4,4,2,4,4,3,4,3,2,5,4,39,37.0,neutral or dissatisfied +2834,84399,Female,Loyal Customer,52,Business travel,Eco,206,4,5,5,5,3,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +2835,23242,Female,Loyal Customer,69,Personal Travel,Eco Plus,549,2,5,3,2,4,4,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +2836,7557,Male,Loyal Customer,8,Personal Travel,Eco,606,3,4,3,3,1,3,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +2837,71485,Male,Loyal Customer,57,Business travel,Business,2670,5,5,5,5,4,4,4,5,3,4,4,4,4,4,135,123.0,satisfied +2838,37703,Female,Loyal Customer,39,Personal Travel,Eco,972,2,4,2,5,3,2,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +2839,35711,Female,Loyal Customer,36,Personal Travel,Eco,2586,1,4,1,1,1,4,4,4,3,4,4,4,4,4,22,21.0,neutral or dissatisfied +2840,22500,Female,Loyal Customer,13,Personal Travel,Eco,143,3,4,3,1,4,3,4,4,3,4,2,2,5,4,0,0.0,neutral or dissatisfied +2841,64705,Female,Loyal Customer,54,Business travel,Business,2974,3,3,3,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +2842,109608,Female,Loyal Customer,46,Business travel,Business,973,4,5,3,5,2,3,4,4,4,3,4,1,4,2,23,27.0,neutral or dissatisfied +2843,26525,Female,Loyal Customer,13,Business travel,Business,3607,3,1,3,3,3,3,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +2844,88688,Male,Loyal Customer,22,Personal Travel,Eco,545,1,5,4,2,3,4,3,3,2,3,5,2,5,3,60,56.0,neutral or dissatisfied +2845,14488,Male,Loyal Customer,68,Personal Travel,Eco,495,2,5,2,1,1,2,1,1,5,5,5,5,4,1,30,27.0,neutral or dissatisfied +2846,9036,Male,Loyal Customer,60,Business travel,Business,3207,4,4,4,4,5,4,4,5,5,5,4,4,5,4,1,12.0,satisfied +2847,35123,Female,Loyal Customer,30,Business travel,Business,2360,3,3,3,3,5,5,5,5,5,5,5,2,1,5,0,0.0,satisfied +2848,61814,Male,Loyal Customer,18,Personal Travel,Eco,1379,4,2,5,3,4,5,5,4,4,1,4,4,4,4,0,0.0,neutral or dissatisfied +2849,82896,Female,Loyal Customer,25,Personal Travel,Eco,594,1,4,1,4,5,1,4,5,2,3,4,2,3,5,65,49.0,neutral or dissatisfied +2850,51699,Female,disloyal Customer,43,Business travel,Eco,237,3,4,3,4,3,4,1,3,5,4,4,1,3,1,134,122.0,neutral or dissatisfied +2851,40797,Female,disloyal Customer,20,Business travel,Eco,558,1,2,2,4,3,2,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +2852,98106,Male,Loyal Customer,59,Business travel,Business,3065,4,4,3,4,3,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +2853,100339,Male,disloyal Customer,25,Business travel,Eco,571,2,0,2,2,2,2,2,2,1,2,5,5,5,2,0,0.0,neutral or dissatisfied +2854,69799,Male,disloyal Customer,25,Business travel,Eco,1055,3,4,4,1,1,4,4,1,3,5,5,3,4,1,11,0.0,neutral or dissatisfied +2855,99803,Male,Loyal Customer,23,Business travel,Business,584,3,3,3,3,4,4,4,4,4,3,3,2,1,4,21,8.0,satisfied +2856,25203,Female,Loyal Customer,54,Business travel,Eco,842,4,3,3,3,4,1,3,4,4,4,4,1,4,2,0,7.0,satisfied +2857,22842,Female,Loyal Customer,12,Personal Travel,Eco,170,3,4,3,3,4,3,4,4,3,3,5,4,4,4,90,86.0,neutral or dissatisfied +2858,1796,Female,disloyal Customer,21,Business travel,Eco,408,4,0,4,1,1,4,1,1,5,2,4,5,4,1,10,24.0,satisfied +2859,115698,Male,Loyal Customer,62,Business travel,Business,3645,1,5,5,5,1,4,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +2860,124092,Male,Loyal Customer,60,Business travel,Business,2708,5,5,5,5,5,5,5,4,4,4,4,4,4,5,47,54.0,satisfied +2861,7200,Female,disloyal Customer,39,Business travel,Eco,116,1,0,2,4,1,2,1,1,1,1,3,1,4,1,0,0.0,neutral or dissatisfied +2862,99573,Male,Loyal Customer,39,Business travel,Business,2863,3,3,5,5,5,4,3,3,3,3,3,2,3,2,0,34.0,neutral or dissatisfied +2863,6257,Male,Loyal Customer,42,Personal Travel,Eco Plus,594,4,5,4,1,2,4,2,2,3,1,3,5,5,2,0,0.0,neutral or dissatisfied +2864,66317,Male,Loyal Customer,13,Personal Travel,Eco,852,3,3,3,3,4,3,4,4,4,1,3,1,2,4,40,38.0,neutral or dissatisfied +2865,34129,Female,Loyal Customer,38,Business travel,Business,2106,5,5,5,5,5,1,3,4,4,4,4,4,4,1,0,12.0,satisfied +2866,64785,Male,Loyal Customer,55,Business travel,Business,2672,2,2,2,2,5,5,4,5,5,5,5,4,5,4,3,0.0,satisfied +2867,128615,Male,Loyal Customer,48,Business travel,Business,1664,2,2,2,2,2,5,4,4,4,4,4,3,4,5,2,0.0,satisfied +2868,21752,Male,Loyal Customer,12,Personal Travel,Eco,563,2,4,2,3,2,2,2,2,4,3,5,5,5,2,0,7.0,neutral or dissatisfied +2869,125642,Male,disloyal Customer,46,Business travel,Business,857,4,4,4,3,3,4,2,3,3,3,4,4,5,3,0,3.0,satisfied +2870,31974,Female,Loyal Customer,57,Business travel,Business,2358,3,4,4,4,4,3,2,2,2,2,3,1,2,4,2,4.0,neutral or dissatisfied +2871,107694,Male,Loyal Customer,57,Business travel,Business,2228,1,1,1,1,4,5,5,5,5,5,5,5,5,4,1,10.0,satisfied +2872,23864,Male,Loyal Customer,54,Personal Travel,Eco,552,3,0,3,5,3,3,1,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +2873,120547,Female,Loyal Customer,52,Business travel,Business,2176,4,4,4,4,4,5,5,5,5,5,5,4,5,5,54,35.0,satisfied +2874,103779,Female,Loyal Customer,42,Business travel,Business,1567,3,3,3,3,5,5,5,3,3,4,4,5,4,5,211,200.0,satisfied +2875,79320,Female,Loyal Customer,43,Business travel,Business,1698,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +2876,39894,Female,Loyal Customer,11,Personal Travel,Eco,272,4,0,4,3,4,4,4,4,4,5,5,4,5,4,4,0.0,satisfied +2877,106103,Male,Loyal Customer,48,Business travel,Business,3485,2,1,1,1,4,3,3,2,2,2,2,1,2,4,12,8.0,neutral or dissatisfied +2878,111695,Female,Loyal Customer,50,Business travel,Business,1910,2,2,2,2,2,5,5,5,5,5,5,5,5,4,25,9.0,satisfied +2879,62275,Female,disloyal Customer,24,Business travel,Eco,236,2,5,3,2,3,3,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +2880,27471,Female,Loyal Customer,45,Business travel,Eco,605,2,3,3,3,1,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +2881,128757,Male,Loyal Customer,31,Business travel,Business,1956,4,4,4,4,4,4,4,4,5,2,5,5,4,4,0,5.0,satisfied +2882,33745,Female,Loyal Customer,36,Business travel,Eco,777,1,1,1,1,1,1,1,3,1,1,1,1,4,1,1,14.0,neutral or dissatisfied +2883,44248,Female,Loyal Customer,23,Business travel,Business,359,2,2,2,2,4,4,4,4,3,5,4,3,2,4,0,0.0,satisfied +2884,34958,Male,Loyal Customer,36,Business travel,Eco Plus,187,4,2,2,2,4,4,4,4,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +2885,104593,Female,Loyal Customer,40,Personal Travel,Eco,369,3,1,3,2,3,3,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +2886,19978,Female,Loyal Customer,28,Business travel,Business,599,4,4,4,4,3,4,3,3,4,5,4,4,4,3,0,0.0,satisfied +2887,10347,Male,Loyal Customer,46,Business travel,Business,2460,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +2888,65914,Female,Loyal Customer,21,Business travel,Business,1939,4,4,4,4,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +2889,95566,Male,Loyal Customer,66,Personal Travel,Eco Plus,192,3,5,3,2,2,3,2,2,5,4,5,5,5,2,25,26.0,neutral or dissatisfied +2890,48505,Female,Loyal Customer,50,Business travel,Eco,737,4,5,5,5,5,3,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +2891,43300,Male,Loyal Customer,40,Business travel,Eco,387,5,4,2,2,5,5,5,5,5,3,5,5,1,5,0,0.0,satisfied +2892,17795,Male,Loyal Customer,32,Business travel,Eco,1075,3,1,1,1,3,3,3,3,1,4,3,4,4,3,0,0.0,neutral or dissatisfied +2893,55958,Male,Loyal Customer,41,Business travel,Business,1620,2,2,2,2,4,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +2894,76871,Female,Loyal Customer,34,Personal Travel,Eco,1927,1,4,1,3,5,1,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +2895,26998,Male,Loyal Customer,42,Business travel,Business,1683,3,3,3,3,5,4,4,3,3,3,3,3,3,3,0,2.0,neutral or dissatisfied +2896,87713,Male,Loyal Customer,10,Personal Travel,Eco,606,1,4,1,3,5,1,1,5,4,2,4,3,4,5,33,28.0,neutral or dissatisfied +2897,44549,Male,Loyal Customer,59,Personal Travel,Eco,157,1,1,1,4,3,1,3,3,2,2,3,1,3,3,0,7.0,neutral or dissatisfied +2898,56742,Male,Loyal Customer,45,Personal Travel,Eco,937,4,4,5,1,5,5,5,5,2,5,4,3,1,5,11,5.0,neutral or dissatisfied +2899,34358,Male,Loyal Customer,29,Business travel,Eco,541,2,3,3,3,2,2,2,2,4,3,4,1,3,2,77,63.0,neutral or dissatisfied +2900,126719,Male,Loyal Customer,45,Business travel,Business,2402,2,2,1,2,4,5,4,4,4,4,4,4,4,3,0,1.0,satisfied +2901,124907,Male,Loyal Customer,45,Business travel,Business,1940,1,1,2,1,2,4,5,5,5,5,5,4,5,4,0,13.0,satisfied +2902,17135,Male,Loyal Customer,32,Personal Travel,Eco,423,2,4,2,4,2,2,2,2,4,5,2,5,2,2,26,39.0,neutral or dissatisfied +2903,37819,Female,Loyal Customer,21,Business travel,Business,2579,2,2,2,2,4,4,4,4,3,4,4,4,4,4,52,52.0,satisfied +2904,101506,Female,disloyal Customer,44,Business travel,Eco,345,3,3,3,4,2,3,2,2,2,4,3,2,4,2,73,82.0,neutral or dissatisfied +2905,80605,Male,Loyal Customer,58,Business travel,Business,1983,5,5,5,5,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +2906,49011,Female,Loyal Customer,42,Business travel,Eco,266,4,3,3,3,2,1,4,4,4,4,4,3,4,3,5,4.0,satisfied +2907,109474,Female,Loyal Customer,27,Business travel,Eco,861,3,3,3,3,3,3,3,2,1,3,4,3,1,3,190,204.0,neutral or dissatisfied +2908,55963,Female,Loyal Customer,59,Business travel,Business,1620,1,1,1,1,5,3,4,5,5,5,5,3,5,5,0,9.0,satisfied +2909,119882,Female,Loyal Customer,60,Personal Travel,Eco,912,3,5,3,4,2,4,5,1,1,3,1,4,1,3,0,3.0,neutral or dissatisfied +2910,42946,Male,Loyal Customer,7,Personal Travel,Business,259,2,5,2,4,1,2,1,1,2,3,3,5,2,1,76,73.0,neutral or dissatisfied +2911,29391,Female,Loyal Customer,26,Business travel,Business,2417,3,1,3,3,4,4,4,4,3,4,5,1,5,4,0,,satisfied +2912,37517,Male,Loyal Customer,66,Business travel,Eco,944,3,3,3,3,3,3,3,3,4,3,3,3,2,3,2,6.0,neutral or dissatisfied +2913,46132,Male,Loyal Customer,29,Business travel,Business,627,4,4,4,4,5,4,5,5,5,5,4,3,2,5,55,84.0,satisfied +2914,25185,Male,Loyal Customer,40,Business travel,Business,577,5,5,1,5,5,5,1,4,4,5,4,5,4,3,2,0.0,satisfied +2915,67238,Female,Loyal Customer,26,Personal Travel,Eco,1121,3,4,3,2,2,3,2,2,3,2,4,5,5,2,45,30.0,neutral or dissatisfied +2916,1243,Male,Loyal Customer,9,Personal Travel,Eco,354,4,5,4,3,1,4,1,1,4,5,5,3,5,1,0,0.0,satisfied +2917,124370,Female,Loyal Customer,59,Business travel,Business,2349,1,1,1,1,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +2918,99527,Male,Loyal Customer,48,Business travel,Business,2060,5,5,5,5,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +2919,29743,Male,Loyal Customer,38,Business travel,Business,3301,4,4,4,4,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +2920,73719,Male,disloyal Customer,34,Business travel,Eco,192,3,0,3,2,1,3,1,1,1,4,5,1,1,1,64,49.0,neutral or dissatisfied +2921,120399,Male,disloyal Customer,35,Business travel,Eco,337,1,4,1,4,3,1,3,3,4,4,3,1,4,3,0,3.0,neutral or dissatisfied +2922,99013,Female,Loyal Customer,45,Personal Travel,Eco Plus,543,4,1,2,3,5,3,4,2,2,2,2,2,2,2,3,0.0,neutral or dissatisfied +2923,42797,Female,Loyal Customer,34,Business travel,Business,2780,2,2,5,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +2924,21729,Female,Loyal Customer,52,Business travel,Eco,563,5,4,2,4,5,2,4,4,4,5,4,4,4,1,0,0.0,satisfied +2925,103725,Male,Loyal Customer,50,Personal Travel,Eco,251,1,5,0,4,5,0,5,5,5,2,2,3,1,5,0,0.0,neutral or dissatisfied +2926,44034,Male,Loyal Customer,56,Business travel,Eco,237,2,5,5,5,2,2,2,2,5,3,4,2,5,2,0,0.0,satisfied +2927,88168,Female,Loyal Customer,49,Business travel,Eco,594,1,4,4,4,3,4,3,1,1,1,1,2,1,4,7,11.0,neutral or dissatisfied +2928,12307,Female,Loyal Customer,45,Business travel,Business,2119,2,2,5,2,3,4,5,4,4,4,3,1,4,4,108,96.0,satisfied +2929,76683,Female,Loyal Customer,26,Personal Travel,Eco,481,1,4,1,4,1,1,1,1,1,1,4,4,5,1,0,8.0,neutral or dissatisfied +2930,111774,Female,Loyal Customer,46,Business travel,Business,1620,5,5,3,5,3,4,5,4,4,5,4,5,4,5,96,84.0,satisfied +2931,40179,Male,disloyal Customer,45,Business travel,Eco,436,1,3,1,3,3,1,5,3,5,4,3,3,3,3,0,0.0,neutral or dissatisfied +2932,59787,Male,Loyal Customer,10,Personal Travel,Eco,895,2,5,2,3,2,2,2,2,5,4,3,2,3,2,26,14.0,neutral or dissatisfied +2933,97211,Male,Loyal Customer,49,Business travel,Business,1390,2,2,2,2,4,4,4,4,5,5,4,4,5,4,184,188.0,satisfied +2934,32332,Female,Loyal Customer,49,Business travel,Business,2290,0,5,0,1,4,1,5,2,2,2,2,2,2,2,20,21.0,satisfied +2935,51887,Male,Loyal Customer,56,Business travel,Eco,507,4,5,5,5,4,4,4,4,3,4,3,2,1,4,0,0.0,satisfied +2936,97819,Male,Loyal Customer,44,Business travel,Business,395,3,3,5,3,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +2937,30722,Male,Loyal Customer,30,Personal Travel,Eco,1123,1,5,1,1,3,1,3,3,3,2,3,5,5,3,0,0.0,neutral or dissatisfied +2938,40372,Female,disloyal Customer,25,Business travel,Eco,1250,2,2,2,2,5,2,5,5,5,1,4,2,5,5,0,6.0,neutral or dissatisfied +2939,2427,Female,Loyal Customer,42,Personal Travel,Eco,604,3,4,3,5,3,5,4,3,3,3,3,2,3,3,27,34.0,neutral or dissatisfied +2940,114130,Female,disloyal Customer,24,Business travel,Business,850,5,3,5,4,3,5,3,3,4,3,5,4,4,3,1,0.0,satisfied +2941,115859,Female,disloyal Customer,18,Business travel,Eco,480,2,0,2,1,3,2,3,3,2,4,5,3,1,3,0,0.0,neutral or dissatisfied +2942,124560,Male,disloyal Customer,24,Business travel,Eco,453,3,5,3,2,4,3,4,4,3,3,5,3,4,4,17,32.0,neutral or dissatisfied +2943,26735,Male,Loyal Customer,48,Business travel,Eco Plus,270,5,3,3,3,5,5,5,5,2,5,5,3,1,5,0,0.0,satisfied +2944,25719,Female,disloyal Customer,59,Business travel,Eco,432,2,0,2,3,3,2,3,3,1,3,5,2,1,3,4,0.0,neutral or dissatisfied +2945,79407,Female,Loyal Customer,22,Business travel,Business,502,3,3,3,3,3,3,3,3,3,2,3,3,3,3,29,14.0,neutral or dissatisfied +2946,114542,Female,Loyal Customer,58,Personal Travel,Business,446,1,5,1,3,4,5,4,1,1,1,4,3,1,4,4,2.0,neutral or dissatisfied +2947,24878,Female,Loyal Customer,40,Business travel,Eco,534,4,2,2,2,4,4,4,4,1,2,4,3,5,4,0,6.0,satisfied +2948,119600,Male,Loyal Customer,31,Business travel,Business,1979,4,1,1,1,4,4,4,4,1,5,2,2,4,4,0,0.0,neutral or dissatisfied +2949,32160,Male,Loyal Customer,36,Business travel,Eco,101,4,3,4,3,4,4,4,4,3,1,5,5,1,4,0,1.0,satisfied +2950,96877,Female,Loyal Customer,55,Personal Travel,Eco,849,1,5,0,4,2,4,4,1,1,0,1,4,1,3,29,37.0,neutral or dissatisfied +2951,42062,Male,Loyal Customer,16,Personal Travel,Eco,106,2,1,2,3,3,2,3,3,3,3,3,4,4,3,0,0.0,neutral or dissatisfied +2952,40395,Male,Loyal Customer,38,Business travel,Business,2494,5,5,5,5,5,4,4,5,5,5,5,5,5,5,8,17.0,satisfied +2953,68956,Male,Loyal Customer,14,Personal Travel,Business,700,3,5,3,5,3,3,3,3,1,5,1,1,5,3,0,14.0,neutral or dissatisfied +2954,14370,Female,Loyal Customer,24,Business travel,Business,3235,3,3,4,3,5,5,5,5,4,1,3,2,1,5,0,0.0,satisfied +2955,118759,Female,Loyal Customer,65,Personal Travel,Eco,368,1,4,1,4,1,1,1,4,4,1,4,3,4,2,21,20.0,neutral or dissatisfied +2956,54262,Male,Loyal Customer,26,Personal Travel,Eco,1222,4,2,4,3,4,4,4,4,4,2,4,2,4,4,1,0.0,neutral or dissatisfied +2957,117535,Female,Loyal Customer,50,Business travel,Business,1586,3,3,3,3,2,5,4,2,2,2,2,3,2,3,6,0.0,satisfied +2958,22680,Female,Loyal Customer,13,Business travel,Business,3878,2,2,2,2,5,5,5,5,5,2,1,4,1,5,115,128.0,satisfied +2959,6944,Female,Loyal Customer,30,Business travel,Business,1793,3,1,1,1,3,3,3,3,2,5,4,1,4,3,7,21.0,neutral or dissatisfied +2960,60446,Male,disloyal Customer,36,Business travel,Business,862,2,2,2,1,2,2,2,2,3,4,4,5,4,2,19,9.0,neutral or dissatisfied +2961,125433,Female,Loyal Customer,55,Personal Travel,Eco,735,3,2,2,1,1,1,2,1,1,2,1,4,1,4,19,17.0,neutral or dissatisfied +2962,103770,Male,Loyal Customer,56,Business travel,Business,1670,3,3,3,3,3,3,3,3,3,4,3,3,2,3,137,162.0,neutral or dissatisfied +2963,104552,Male,Loyal Customer,39,Business travel,Business,3322,3,4,4,4,1,4,3,3,3,3,3,4,3,2,40,40.0,neutral or dissatisfied +2964,70523,Female,Loyal Customer,44,Business travel,Business,1258,4,4,4,4,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +2965,76584,Female,disloyal Customer,34,Business travel,Business,516,4,4,4,4,3,4,5,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +2966,84807,Female,Loyal Customer,39,Business travel,Business,1509,3,3,3,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +2967,37837,Female,Loyal Customer,26,Business travel,Business,937,3,3,3,3,3,3,3,3,5,5,4,5,3,3,0,0.0,satisfied +2968,120502,Male,Loyal Customer,45,Business travel,Business,449,2,2,2,2,5,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +2969,908,Female,disloyal Customer,37,Business travel,Business,270,2,2,2,4,5,2,5,5,3,1,4,3,4,5,0,0.0,neutral or dissatisfied +2970,69961,Female,Loyal Customer,46,Personal Travel,Eco,2174,1,4,1,5,2,4,5,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +2971,63872,Female,Loyal Customer,47,Business travel,Eco,1158,2,3,3,3,2,3,3,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +2972,59591,Female,disloyal Customer,27,Business travel,Business,854,2,2,2,5,4,2,1,4,3,2,4,5,4,4,12,21.0,neutral or dissatisfied +2973,109244,Male,Loyal Customer,38,Personal Travel,Eco,391,4,5,4,3,5,4,5,5,4,2,5,5,4,5,0,0.0,neutral or dissatisfied +2974,92675,Female,Loyal Customer,39,Business travel,Business,3146,3,4,3,3,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +2975,74015,Male,Loyal Customer,23,Business travel,Business,1471,2,2,2,2,2,2,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +2976,122011,Male,Loyal Customer,57,Business travel,Business,83,3,4,4,4,2,3,3,3,3,3,3,4,3,1,5,4.0,neutral or dissatisfied +2977,109772,Male,disloyal Customer,49,Business travel,Business,1092,2,2,2,3,3,2,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +2978,124470,Female,Loyal Customer,14,Personal Travel,Eco,980,3,4,3,5,1,3,1,1,3,4,4,4,5,1,0,0.0,neutral or dissatisfied +2979,97027,Female,disloyal Customer,35,Business travel,Business,883,3,3,3,1,3,3,3,3,5,2,5,5,4,3,0,3.0,neutral or dissatisfied +2980,102915,Male,disloyal Customer,37,Business travel,Business,436,4,4,4,3,3,4,1,3,4,2,4,3,5,3,0,0.0,satisfied +2981,88926,Female,Loyal Customer,31,Personal Travel,Business,1199,1,5,2,1,4,2,4,4,5,5,3,1,1,4,0,0.0,neutral or dissatisfied +2982,652,Female,disloyal Customer,23,Business travel,Eco,229,1,4,0,1,2,0,5,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +2983,89324,Female,Loyal Customer,53,Business travel,Business,1541,2,2,2,2,2,5,5,4,4,5,4,3,4,4,8,5.0,satisfied +2984,122486,Male,Loyal Customer,19,Personal Travel,Eco,808,2,3,2,5,2,2,2,2,2,4,3,4,3,2,0,0.0,neutral or dissatisfied +2985,11060,Female,Loyal Customer,31,Personal Travel,Eco,224,4,2,4,4,5,4,5,5,2,2,3,2,3,5,4,1.0,neutral or dissatisfied +2986,59572,Female,Loyal Customer,53,Business travel,Business,3250,5,5,5,5,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +2987,29766,Female,Loyal Customer,55,Business travel,Business,3537,3,5,5,5,2,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +2988,21749,Female,Loyal Customer,51,Personal Travel,Eco,563,3,5,4,4,1,4,2,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +2989,102324,Female,Loyal Customer,36,Business travel,Business,258,4,4,4,4,4,2,2,4,4,4,4,3,4,2,1,0.0,neutral or dissatisfied +2990,114178,Male,Loyal Customer,41,Business travel,Business,2669,4,4,4,4,3,5,4,5,5,5,5,3,5,5,7,0.0,satisfied +2991,10306,Female,Loyal Customer,56,Business travel,Business,2956,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +2992,47756,Male,Loyal Customer,36,Business travel,Business,817,4,4,4,4,2,1,5,4,4,4,4,2,4,2,0,0.0,satisfied +2993,79350,Female,Loyal Customer,11,Personal Travel,Eco,1020,3,4,3,3,1,3,1,1,3,4,1,2,3,1,13,1.0,neutral or dissatisfied +2994,568,Male,Loyal Customer,40,Business travel,Business,312,2,2,4,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +2995,8136,Female,Loyal Customer,39,Business travel,Business,125,4,4,4,4,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +2996,37355,Male,Loyal Customer,27,Business travel,Business,1005,1,5,1,1,5,4,5,5,3,4,4,3,3,5,0,0.0,satisfied +2997,120608,Female,Loyal Customer,25,Business travel,Eco,453,3,1,2,2,3,3,3,3,1,1,3,1,3,3,0,0.0,neutral or dissatisfied +2998,24130,Male,Loyal Customer,16,Personal Travel,Eco,584,1,5,1,3,1,1,1,1,4,3,5,4,4,1,4,0.0,neutral or dissatisfied +2999,69185,Male,Loyal Customer,50,Personal Travel,Eco,187,5,3,5,4,3,5,3,3,2,1,3,4,3,3,0,0.0,satisfied +3000,9590,Male,Loyal Customer,44,Personal Travel,Eco,288,3,5,3,2,1,3,1,1,4,4,5,5,5,1,0,0.0,neutral or dissatisfied +3001,39210,Female,disloyal Customer,36,Business travel,Business,67,2,2,2,3,1,2,1,1,4,5,5,4,5,1,3,0.0,neutral or dissatisfied +3002,10028,Female,Loyal Customer,42,Business travel,Business,2996,3,3,3,3,2,4,4,4,4,4,4,4,4,5,6,14.0,satisfied +3003,89559,Female,Loyal Customer,28,Business travel,Business,2955,5,5,2,5,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +3004,54013,Male,disloyal Customer,26,Business travel,Business,1091,2,2,2,3,4,2,4,4,5,5,3,2,4,4,0,0.0,neutral or dissatisfied +3005,18782,Male,disloyal Customer,22,Business travel,Eco,448,4,2,4,2,3,4,1,3,5,2,1,1,3,3,35,27.0,satisfied +3006,90853,Female,disloyal Customer,22,Business travel,Business,515,3,4,3,4,1,3,1,1,3,3,3,3,4,1,0,4.0,neutral or dissatisfied +3007,30405,Male,Loyal Customer,41,Personal Travel,Eco,862,2,4,2,4,4,2,4,4,3,5,4,4,5,4,0,3.0,neutral or dissatisfied +3008,14550,Female,Loyal Customer,12,Personal Travel,Eco,368,2,2,2,3,4,2,5,4,3,1,3,3,2,4,0,0.0,neutral or dissatisfied +3009,126567,Male,Loyal Customer,23,Business travel,Business,1558,3,2,1,2,3,3,3,3,1,5,3,1,3,3,82,70.0,neutral or dissatisfied +3010,82004,Female,Loyal Customer,43,Business travel,Eco,1135,5,1,1,1,4,3,1,5,5,5,5,4,5,5,0,1.0,satisfied +3011,105124,Male,Loyal Customer,60,Business travel,Business,2761,3,3,3,3,5,5,4,3,3,4,3,3,3,4,44,41.0,satisfied +3012,47035,Female,Loyal Customer,34,Business travel,Business,351,4,4,4,4,1,4,3,4,4,4,4,2,4,2,0,15.0,satisfied +3013,15601,Female,disloyal Customer,54,Business travel,Eco,229,2,0,2,4,2,1,1,1,5,4,4,1,3,1,131,140.0,neutral or dissatisfied +3014,54834,Male,Loyal Customer,37,Business travel,Business,2844,5,5,5,5,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +3015,68227,Male,Loyal Customer,36,Business travel,Eco,432,1,1,2,1,1,2,1,1,2,2,4,4,4,1,2,6.0,neutral or dissatisfied +3016,10807,Male,Loyal Customer,59,Business travel,Eco,224,2,2,2,2,2,2,2,2,2,5,4,4,3,2,116,128.0,neutral or dissatisfied +3017,124292,Female,Loyal Customer,57,Business travel,Eco,601,3,2,2,2,4,4,4,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +3018,84191,Male,Loyal Customer,48,Business travel,Business,2332,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +3019,20379,Female,Loyal Customer,57,Personal Travel,Eco,287,3,4,3,3,5,4,4,2,2,3,2,1,2,4,17,8.0,neutral or dissatisfied +3020,32720,Female,Loyal Customer,52,Business travel,Eco,163,3,2,2,2,3,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +3021,44016,Female,Loyal Customer,70,Personal Travel,Eco,334,5,4,5,3,4,4,3,2,2,5,2,4,2,1,0,0.0,satisfied +3022,23759,Male,Loyal Customer,9,Personal Travel,Eco,1083,3,3,3,1,2,3,2,2,1,4,3,1,5,2,54,42.0,neutral or dissatisfied +3023,123746,Male,Loyal Customer,14,Personal Travel,Eco,96,5,1,0,4,1,0,1,1,2,2,4,1,3,1,0,0.0,satisfied +3024,107715,Male,Loyal Customer,72,Business travel,Eco,251,1,2,2,2,1,1,1,1,4,3,4,1,4,1,2,0.0,neutral or dissatisfied +3025,109944,Male,Loyal Customer,60,Personal Travel,Eco,1011,1,4,1,3,3,1,3,3,2,4,3,2,3,3,1,0.0,neutral or dissatisfied +3026,126813,Female,Loyal Customer,27,Business travel,Business,2296,2,5,5,5,2,2,2,2,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +3027,3613,Male,Loyal Customer,60,Business travel,Business,3904,5,5,5,5,3,4,5,2,2,2,2,3,2,5,0,0.0,satisfied +3028,36496,Male,Loyal Customer,35,Business travel,Eco,1249,5,1,1,1,5,5,5,5,1,3,1,1,4,5,21,11.0,satisfied +3029,24115,Female,Loyal Customer,35,Business travel,Business,3416,1,3,3,3,3,3,3,1,1,1,1,3,1,1,0,12.0,neutral or dissatisfied +3030,10475,Male,Loyal Customer,46,Business travel,Business,312,3,3,3,3,3,4,5,4,4,4,4,3,4,3,32,29.0,satisfied +3031,22600,Male,Loyal Customer,17,Business travel,Business,1794,4,2,2,2,2,2,4,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +3032,63611,Female,Loyal Customer,59,Business travel,Business,1440,2,2,2,2,2,2,2,4,3,1,1,2,2,2,132,140.0,neutral or dissatisfied +3033,86788,Male,disloyal Customer,28,Business travel,Business,692,4,3,3,2,4,3,3,4,5,4,5,3,4,4,3,0.0,satisfied +3034,77464,Male,disloyal Customer,66,Business travel,Business,507,1,1,1,5,3,1,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +3035,13795,Female,disloyal Customer,62,Business travel,Eco,450,2,3,2,2,3,2,3,3,4,3,1,3,5,3,0,0.0,neutral or dissatisfied +3036,73555,Male,Loyal Customer,58,Business travel,Business,2116,2,2,2,2,3,4,4,4,4,4,5,3,4,4,97,73.0,satisfied +3037,74137,Female,disloyal Customer,14,Business travel,Eco,641,3,4,3,3,1,3,1,1,2,3,3,4,3,1,0,0.0,neutral or dissatisfied +3038,100448,Female,Loyal Customer,14,Personal Travel,Eco,1180,1,4,1,3,1,1,1,1,4,4,5,3,5,1,0,5.0,neutral or dissatisfied +3039,75147,Female,Loyal Customer,58,Business travel,Business,1744,1,1,1,1,4,3,4,5,5,5,5,3,5,4,0,4.0,satisfied +3040,114254,Male,Loyal Customer,25,Business travel,Eco,567,4,4,4,4,4,4,4,4,5,1,2,4,4,4,2,2.0,satisfied +3041,1968,Female,Loyal Customer,17,Personal Travel,Eco,383,4,5,4,3,1,4,4,1,5,2,4,3,4,1,0,32.0,satisfied +3042,50220,Female,Loyal Customer,70,Business travel,Eco,86,1,1,1,1,4,3,2,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +3043,5604,Female,Loyal Customer,52,Business travel,Business,3746,1,1,1,1,4,5,5,4,4,4,4,4,4,5,13,31.0,satisfied +3044,71125,Male,Loyal Customer,22,Business travel,Business,1739,4,4,4,4,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +3045,37678,Male,Loyal Customer,64,Personal Travel,Eco,1028,4,4,4,3,2,4,1,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +3046,66575,Male,disloyal Customer,25,Business travel,Business,624,2,4,2,1,5,2,5,5,4,2,5,3,5,5,12,18.0,neutral or dissatisfied +3047,88055,Male,Loyal Customer,50,Business travel,Business,3166,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +3048,88451,Female,Loyal Customer,27,Business travel,Business,1550,1,5,5,5,1,1,1,1,3,1,3,4,4,1,8,7.0,neutral or dissatisfied +3049,14131,Male,Loyal Customer,46,Business travel,Business,1639,3,4,3,3,2,4,4,2,2,2,2,4,2,1,0,0.0,satisfied +3050,117696,Male,Loyal Customer,26,Personal Travel,Eco,1814,3,5,3,2,4,3,4,4,3,4,5,5,4,4,0,0.0,neutral or dissatisfied +3051,25453,Male,Loyal Customer,36,Personal Travel,Eco,669,2,4,2,4,1,2,1,1,4,3,4,5,4,1,22,32.0,neutral or dissatisfied +3052,85949,Male,Loyal Customer,40,Business travel,Business,447,3,3,4,3,2,4,5,4,4,4,4,5,4,3,1,0.0,satisfied +3053,50339,Female,Loyal Customer,52,Business travel,Business,266,4,4,4,4,1,3,2,5,5,5,5,5,5,5,0,0.0,satisfied +3054,113222,Female,Loyal Customer,64,Business travel,Business,3347,2,1,1,1,3,4,4,2,2,2,2,2,2,1,7,0.0,neutral or dissatisfied +3055,9778,Female,Loyal Customer,68,Personal Travel,Eco,383,3,4,3,2,4,5,5,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +3056,119097,Female,Loyal Customer,27,Business travel,Business,3207,1,4,4,4,1,2,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +3057,116879,Female,Loyal Customer,50,Business travel,Business,2534,2,2,2,2,2,4,5,4,4,4,4,3,4,3,25,26.0,satisfied +3058,69249,Female,Loyal Customer,53,Business travel,Business,1512,2,2,2,2,3,4,5,4,4,4,4,3,4,4,0,1.0,satisfied +3059,96337,Female,disloyal Customer,24,Business travel,Business,1609,0,0,0,2,2,0,2,2,5,5,5,5,4,2,23,0.0,satisfied +3060,126,Male,Loyal Customer,66,Personal Travel,Eco,562,2,5,2,4,5,2,5,5,3,5,2,5,5,5,88,84.0,neutral or dissatisfied +3061,125258,Female,Loyal Customer,80,Business travel,Eco Plus,427,1,3,3,3,3,2,2,1,1,1,1,2,1,2,4,0.0,neutral or dissatisfied +3062,124054,Male,Loyal Customer,44,Business travel,Business,2153,1,1,1,1,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +3063,34962,Male,Loyal Customer,37,Personal Travel,Eco Plus,395,1,4,1,4,4,1,4,4,3,4,4,4,4,4,0,6.0,neutral or dissatisfied +3064,119272,Male,Loyal Customer,47,Business travel,Business,214,0,4,0,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +3065,86170,Male,Loyal Customer,60,Business travel,Business,2503,3,3,3,3,4,5,4,4,4,4,4,3,4,3,6,0.0,satisfied +3066,111026,Male,Loyal Customer,63,Business travel,Eco,268,3,5,5,5,3,3,3,3,1,4,4,1,3,3,8,10.0,neutral or dissatisfied +3067,100673,Male,Loyal Customer,43,Business travel,Business,1962,3,3,3,3,3,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +3068,116754,Male,Loyal Customer,48,Personal Travel,Eco Plus,337,1,4,1,3,3,1,3,3,3,5,4,3,4,3,26,5.0,neutral or dissatisfied +3069,74702,Female,Loyal Customer,60,Personal Travel,Eco,1313,2,4,2,5,2,3,4,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +3070,57898,Male,disloyal Customer,21,Business travel,Eco,305,2,1,3,4,4,3,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +3071,101046,Female,disloyal Customer,20,Business travel,Business,368,5,0,5,4,4,5,4,4,3,2,4,3,4,4,22,23.0,satisfied +3072,23232,Male,Loyal Customer,54,Business travel,Eco,116,2,3,3,3,3,2,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +3073,29327,Male,Loyal Customer,55,Personal Travel,Eco,859,2,5,2,1,3,2,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +3074,22139,Male,Loyal Customer,35,Personal Travel,Eco,566,2,4,2,2,3,2,5,3,3,5,4,4,5,3,0,0.0,neutral or dissatisfied +3075,85626,Male,Loyal Customer,21,Personal Travel,Eco,259,3,2,0,2,1,0,1,1,3,1,1,3,1,1,0,0.0,neutral or dissatisfied +3076,7124,Female,Loyal Customer,56,Personal Travel,Eco Plus,273,2,4,2,3,3,3,3,4,4,2,4,2,4,2,67,63.0,neutral or dissatisfied +3077,98508,Female,Loyal Customer,49,Business travel,Eco,668,3,4,4,4,3,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +3078,98880,Female,disloyal Customer,25,Business travel,Eco,991,1,0,0,2,2,0,2,2,3,5,1,2,2,2,0,0.0,neutral or dissatisfied +3079,119974,Male,Loyal Customer,51,Personal Travel,Eco,868,4,4,4,1,1,4,1,1,4,1,5,3,1,1,0,0.0,neutral or dissatisfied +3080,1281,Female,Loyal Customer,16,Personal Travel,Eco,164,2,5,2,5,5,2,4,5,4,3,5,5,5,5,17,16.0,neutral or dissatisfied +3081,74749,Male,Loyal Customer,63,Personal Travel,Eco,1171,1,5,1,4,4,1,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +3082,24220,Female,Loyal Customer,53,Business travel,Business,302,4,4,4,4,4,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +3083,25784,Male,Loyal Customer,26,Business travel,Business,762,3,3,3,3,5,5,5,5,4,5,4,2,1,5,21,10.0,satisfied +3084,76384,Female,disloyal Customer,21,Business travel,Eco,931,2,2,2,3,3,2,4,3,4,5,3,2,3,3,0,0.0,neutral or dissatisfied +3085,122851,Female,Loyal Customer,55,Business travel,Business,2844,0,0,0,3,4,5,5,4,4,4,4,4,4,5,4,6.0,satisfied +3086,129788,Female,Loyal Customer,34,Personal Travel,Eco,337,3,5,2,1,4,2,4,4,4,4,5,5,4,4,0,5.0,neutral or dissatisfied +3087,66012,Female,Loyal Customer,47,Business travel,Business,2759,4,4,4,4,4,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +3088,28030,Female,Loyal Customer,31,Personal Travel,Eco Plus,763,1,5,1,4,1,1,4,1,1,1,5,1,2,1,0,0.0,neutral or dissatisfied +3089,82550,Female,Loyal Customer,25,Business travel,Business,528,2,2,2,2,3,3,3,3,5,5,4,3,5,3,37,22.0,satisfied +3090,69958,Male,Loyal Customer,43,Personal Travel,Eco,2174,3,4,3,4,5,3,5,5,5,3,4,4,4,5,9,8.0,neutral or dissatisfied +3091,107340,Female,Loyal Customer,39,Business travel,Business,3346,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +3092,21566,Male,disloyal Customer,38,Business travel,Eco Plus,433,3,3,3,4,4,3,3,4,2,5,4,2,1,4,0,0.0,neutral or dissatisfied +3093,81568,Male,Loyal Customer,31,Personal Travel,Eco,936,4,4,4,2,2,4,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +3094,55383,Female,Loyal Customer,59,Personal Travel,Eco,594,3,2,3,3,4,4,4,4,4,3,4,2,4,2,2,0.0,neutral or dissatisfied +3095,128623,Male,disloyal Customer,28,Business travel,Business,679,1,2,2,3,5,2,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +3096,107723,Female,Loyal Customer,35,Business travel,Business,1531,5,5,5,5,5,5,2,4,4,4,4,3,4,1,2,4.0,satisfied +3097,41349,Female,Loyal Customer,47,Business travel,Business,956,4,4,1,4,5,3,1,3,3,3,3,3,3,3,0,0.0,satisfied +3098,13568,Female,Loyal Customer,27,Personal Travel,Eco,106,2,2,2,4,2,2,2,2,4,3,4,4,4,2,0,3.0,neutral or dissatisfied +3099,57329,Female,disloyal Customer,26,Business travel,Business,236,4,0,4,1,3,4,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +3100,32086,Male,Loyal Customer,48,Business travel,Business,216,1,1,1,1,1,5,3,5,5,5,4,5,5,2,0,0.0,satisfied +3101,10938,Male,Loyal Customer,48,Business travel,Eco,312,3,2,2,2,3,3,3,3,1,5,2,2,3,3,0,0.0,neutral or dissatisfied +3102,84347,Female,Loyal Customer,41,Business travel,Business,2208,3,3,3,3,2,5,5,4,4,5,4,4,4,5,0,0.0,satisfied +3103,101224,Female,Loyal Customer,54,Business travel,Business,1235,1,1,1,1,4,5,4,5,5,5,5,5,5,5,34,25.0,satisfied +3104,8493,Female,Loyal Customer,59,Personal Travel,Eco Plus,677,3,5,3,3,4,5,5,1,1,3,1,5,1,5,22,29.0,neutral or dissatisfied +3105,71963,Male,Loyal Customer,19,Business travel,Business,1440,2,5,5,5,2,2,2,2,3,2,3,4,3,2,52,60.0,neutral or dissatisfied +3106,82180,Female,Loyal Customer,41,Personal Travel,Eco Plus,237,1,4,1,2,2,5,5,4,4,1,4,4,4,5,10,4.0,neutral or dissatisfied +3107,17615,Female,Loyal Customer,57,Personal Travel,Business,622,4,4,3,3,4,4,4,1,1,3,3,3,1,4,0,0.0,neutral or dissatisfied +3108,94487,Female,disloyal Customer,26,Business travel,Business,239,4,0,4,1,3,4,3,3,3,4,4,4,5,3,2,0.0,satisfied +3109,90434,Male,Loyal Customer,57,Business travel,Business,646,4,4,4,4,5,4,5,5,5,5,5,5,5,3,13,0.0,satisfied +3110,72808,Female,Loyal Customer,59,Personal Travel,Eco,1045,2,5,2,4,3,5,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +3111,94112,Female,Loyal Customer,38,Personal Travel,Business,239,2,4,2,1,2,5,5,4,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +3112,65364,Male,Loyal Customer,20,Business travel,Eco,432,3,1,1,1,3,3,2,3,1,2,4,1,4,3,113,125.0,neutral or dissatisfied +3113,66158,Female,Loyal Customer,27,Business travel,Business,550,1,1,3,1,3,3,3,3,4,2,4,5,4,3,0,0.0,satisfied +3114,62412,Male,Loyal Customer,7,Personal Travel,Eco Plus,2611,2,4,2,3,5,2,5,5,4,2,3,1,3,5,0,0.0,neutral or dissatisfied +3115,34164,Male,Loyal Customer,26,Business travel,Business,1189,3,1,3,3,3,3,3,3,4,2,2,1,3,3,4,12.0,neutral or dissatisfied +3116,122821,Male,Loyal Customer,39,Personal Travel,Eco,599,3,4,3,3,2,3,2,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +3117,25859,Male,Loyal Customer,61,Personal Travel,Eco,692,1,2,1,4,5,1,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +3118,94011,Female,Loyal Customer,49,Business travel,Business,3724,3,3,3,3,5,4,5,4,4,4,4,5,4,4,7,6.0,satisfied +3119,125116,Male,disloyal Customer,20,Business travel,Eco,361,2,2,2,3,1,2,1,1,2,1,3,4,3,1,15,24.0,neutral or dissatisfied +3120,68999,Male,Loyal Customer,12,Personal Travel,Eco Plus,2422,3,1,3,2,3,4,4,4,1,1,2,4,1,4,4,0.0,neutral or dissatisfied +3121,97408,Male,Loyal Customer,43,Business travel,Business,570,4,4,4,4,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3122,54412,Male,Loyal Customer,67,Business travel,Business,3034,0,0,0,5,5,1,3,3,3,5,5,2,3,1,0,0.0,satisfied +3123,26103,Male,Loyal Customer,64,Personal Travel,Eco,591,3,5,3,5,1,3,1,1,4,5,4,4,4,1,1,0.0,neutral or dissatisfied +3124,35724,Female,Loyal Customer,49,Personal Travel,Eco Plus,2465,0,1,0,4,1,2,4,2,2,0,2,3,2,2,9,0.0,satisfied +3125,81576,Female,Loyal Customer,17,Business travel,Business,3084,5,5,5,5,3,3,3,3,5,3,4,5,4,3,18,3.0,satisfied +3126,4844,Female,Loyal Customer,52,Business travel,Business,408,5,5,1,5,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +3127,125518,Female,Loyal Customer,54,Business travel,Business,2565,0,0,0,3,3,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +3128,54772,Female,Loyal Customer,52,Business travel,Eco Plus,454,3,4,4,4,5,4,4,3,3,3,3,2,3,4,8,10.0,neutral or dissatisfied +3129,24759,Male,disloyal Customer,22,Business travel,Eco,528,4,2,4,3,2,4,2,2,4,4,3,3,4,2,39,26.0,neutral or dissatisfied +3130,71766,Female,disloyal Customer,25,Business travel,Business,1744,1,0,1,1,2,1,5,2,3,5,5,3,4,2,1,0.0,neutral or dissatisfied +3131,109500,Male,disloyal Customer,40,Business travel,Business,861,3,3,3,4,1,3,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +3132,38650,Female,Loyal Customer,55,Business travel,Business,2704,2,1,1,1,5,4,4,2,2,2,2,2,2,1,2,2.0,neutral or dissatisfied +3133,18877,Male,Loyal Customer,53,Business travel,Business,448,3,1,1,1,3,3,3,4,3,3,3,3,3,3,185,176.0,neutral or dissatisfied +3134,2047,Female,Loyal Customer,42,Business travel,Business,3770,5,5,5,5,3,4,5,4,4,4,4,4,4,4,11,4.0,satisfied +3135,106565,Male,disloyal Customer,43,Business travel,Business,1024,5,5,5,5,4,5,4,4,5,3,4,3,4,4,0,3.0,satisfied +3136,55778,Female,Loyal Customer,9,Personal Travel,Eco,646,4,5,4,1,3,4,3,3,5,2,4,1,2,3,0,0.0,satisfied +3137,117429,Female,Loyal Customer,47,Business travel,Business,1460,2,2,2,2,2,4,4,5,5,5,5,5,5,4,2,6.0,satisfied +3138,27007,Male,Loyal Customer,66,Business travel,Business,3852,3,3,3,3,3,3,3,2,2,2,2,4,2,3,0,0.0,satisfied +3139,58439,Female,Loyal Customer,47,Personal Travel,Eco,723,2,1,2,3,3,4,4,3,3,2,2,1,3,4,18,0.0,neutral or dissatisfied +3140,110352,Female,Loyal Customer,57,Business travel,Business,883,3,3,3,3,5,5,4,4,4,4,4,5,4,3,33,21.0,satisfied +3141,123500,Female,Loyal Customer,80,Business travel,Eco,577,2,5,3,5,4,4,4,2,2,2,2,4,2,3,83,46.0,neutral or dissatisfied +3142,46283,Male,Loyal Customer,39,Business travel,Eco Plus,594,3,2,2,2,3,3,3,3,4,3,2,3,1,3,0,0.0,satisfied +3143,51062,Female,Loyal Customer,66,Personal Travel,Eco,109,2,4,2,1,3,2,3,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +3144,14543,Male,Loyal Customer,41,Business travel,Eco,362,4,5,5,5,4,4,4,4,2,1,2,4,3,4,101,99.0,satisfied +3145,40462,Female,disloyal Customer,25,Business travel,Eco,222,2,1,2,2,3,2,5,3,2,2,2,2,2,3,0,5.0,neutral or dissatisfied +3146,31935,Male,Loyal Customer,48,Business travel,Business,101,5,5,3,5,4,5,5,3,3,4,5,3,3,4,0,0.0,satisfied +3147,24886,Male,disloyal Customer,45,Business travel,Eco,397,2,0,2,5,1,2,1,1,4,2,1,1,4,1,8,0.0,neutral or dissatisfied +3148,31480,Female,Loyal Customer,32,Business travel,Business,2001,4,4,4,4,5,5,5,5,2,4,1,4,4,5,2,4.0,satisfied +3149,8362,Female,Loyal Customer,52,Business travel,Business,722,5,5,5,5,3,4,5,4,4,5,4,3,4,5,0,4.0,satisfied +3150,93054,Female,disloyal Customer,38,Business travel,Business,297,2,2,2,1,2,2,2,2,5,4,5,3,5,2,0,1.0,neutral or dissatisfied +3151,38941,Male,Loyal Customer,59,Personal Travel,Eco,320,3,4,3,2,1,3,1,1,1,1,1,3,2,1,0,21.0,neutral or dissatisfied +3152,32367,Male,Loyal Customer,49,Business travel,Business,3943,1,1,1,1,3,5,5,3,3,4,4,5,3,4,6,3.0,satisfied +3153,91857,Male,Loyal Customer,20,Personal Travel,Eco,1797,2,5,2,3,5,2,1,5,1,3,4,1,2,5,0,0.0,neutral or dissatisfied +3154,78786,Male,Loyal Customer,49,Business travel,Business,432,4,4,4,4,4,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +3155,84323,Female,Loyal Customer,41,Business travel,Business,591,3,3,3,3,4,4,4,4,2,5,5,4,5,4,130,141.0,satisfied +3156,31452,Male,Loyal Customer,17,Personal Travel,Business,862,2,5,2,4,1,2,1,1,3,4,4,4,4,1,67,64.0,neutral or dissatisfied +3157,13506,Female,Loyal Customer,39,Business travel,Eco,106,2,3,3,3,2,2,2,2,4,4,3,1,3,2,0,0.0,satisfied +3158,87240,Female,Loyal Customer,49,Business travel,Business,1954,1,1,1,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +3159,107405,Male,disloyal Customer,25,Business travel,Business,523,2,0,2,1,4,2,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +3160,17171,Female,disloyal Customer,16,Business travel,Eco,667,1,5,0,1,1,0,4,1,1,1,4,2,3,1,0,0.0,neutral or dissatisfied +3161,110960,Female,Loyal Customer,35,Business travel,Business,2780,2,5,5,5,3,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +3162,61891,Female,Loyal Customer,50,Business travel,Business,2521,5,5,5,5,3,3,4,5,5,5,5,3,5,3,42,6.0,satisfied +3163,42577,Female,Loyal Customer,37,Business travel,Eco,315,5,3,2,2,5,5,5,5,3,5,5,3,4,5,0,0.0,satisfied +3164,105154,Male,Loyal Customer,23,Business travel,Business,2323,5,5,5,5,4,4,4,4,5,2,2,3,2,4,0,0.0,satisfied +3165,32743,Male,Loyal Customer,36,Business travel,Business,101,3,3,3,3,3,4,3,4,4,5,3,2,4,1,0,0.0,satisfied +3166,93461,Male,Loyal Customer,15,Personal Travel,Eco,723,1,2,1,4,4,1,4,4,4,4,3,1,3,4,58,49.0,neutral or dissatisfied +3167,94054,Male,Loyal Customer,57,Business travel,Business,3166,0,0,0,3,3,5,5,4,4,4,4,4,4,3,66,57.0,satisfied +3168,119402,Male,Loyal Customer,48,Business travel,Business,399,4,5,5,5,5,3,3,4,4,4,4,1,4,3,0,6.0,neutral or dissatisfied +3169,91812,Male,Loyal Customer,63,Personal Travel,Eco,626,3,5,3,3,1,3,1,1,4,4,4,5,4,1,10,15.0,neutral or dissatisfied +3170,122010,Female,Loyal Customer,50,Business travel,Business,130,3,3,3,3,3,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +3171,3491,Female,Loyal Customer,58,Business travel,Business,2282,4,3,3,3,3,3,3,4,4,4,4,4,4,4,20,12.0,neutral or dissatisfied +3172,10077,Female,Loyal Customer,58,Business travel,Business,1961,4,4,4,4,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +3173,76831,Female,Loyal Customer,31,Business travel,Business,1851,1,2,2,2,1,1,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +3174,96496,Female,disloyal Customer,65,Business travel,Eco,302,2,3,2,3,4,2,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +3175,52879,Female,Loyal Customer,72,Business travel,Business,2271,1,1,1,1,1,5,2,4,4,4,4,2,4,1,1,0.0,satisfied +3176,14597,Male,Loyal Customer,54,Personal Travel,Eco,986,3,5,3,3,1,3,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +3177,89490,Female,Loyal Customer,50,Personal Travel,Eco,1931,3,4,3,4,3,4,4,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +3178,51310,Male,disloyal Customer,26,Business travel,Eco Plus,308,4,2,4,3,4,4,4,4,1,5,3,2,2,4,4,0.0,neutral or dissatisfied +3179,70402,Male,Loyal Customer,76,Business travel,Business,2584,1,3,5,3,4,4,4,1,1,1,1,4,1,2,0,1.0,neutral or dissatisfied +3180,97547,Female,Loyal Customer,8,Personal Travel,Eco,675,4,5,4,3,4,3,3,5,4,5,5,3,5,3,154,171.0,neutral or dissatisfied +3181,49086,Male,Loyal Customer,46,Business travel,Business,266,3,2,3,3,3,1,3,5,5,5,5,4,5,5,0,10.0,satisfied +3182,28707,Female,Loyal Customer,37,Personal Travel,Business,2554,4,3,4,5,4,3,3,1,3,3,1,3,2,3,0,6.0,neutral or dissatisfied +3183,100327,Male,Loyal Customer,64,Business travel,Business,2216,1,0,0,4,3,3,4,1,1,0,1,2,1,2,0,0.0,neutral or dissatisfied +3184,11519,Male,Loyal Customer,51,Personal Travel,Eco Plus,429,3,3,3,4,1,3,1,1,2,4,4,1,4,1,17,27.0,neutral or dissatisfied +3185,34167,Female,Loyal Customer,49,Business travel,Business,1189,4,2,2,2,2,3,4,4,4,4,4,3,4,3,8,19.0,neutral or dissatisfied +3186,38247,Male,Loyal Customer,46,Business travel,Business,1998,1,1,1,1,3,4,1,4,4,5,4,5,4,2,0,1.0,satisfied +3187,29869,Male,Loyal Customer,41,Business travel,Business,539,2,2,2,2,5,5,3,4,4,4,4,2,4,2,0,0.0,satisfied +3188,38142,Female,Loyal Customer,20,Personal Travel,Eco,1197,2,4,2,4,1,2,1,1,5,2,5,3,4,1,0,0.0,neutral or dissatisfied +3189,111956,Male,Loyal Customer,60,Business travel,Business,2431,5,5,5,5,3,5,4,4,4,4,4,3,4,3,34,72.0,satisfied +3190,90135,Female,Loyal Customer,19,Business travel,Business,2716,5,5,5,5,5,5,5,5,4,3,4,3,4,5,0,0.0,satisfied +3191,21555,Female,Loyal Customer,43,Business travel,Eco Plus,306,4,1,1,1,4,2,2,4,4,4,4,5,4,3,9,15.0,satisfied +3192,105793,Male,Loyal Customer,65,Personal Travel,Eco,925,1,5,1,2,2,1,3,2,3,5,5,4,4,2,0,0.0,neutral or dissatisfied +3193,6167,Female,disloyal Customer,23,Business travel,Eco,409,1,4,1,2,4,1,4,4,1,2,4,5,5,4,0,0.0,neutral or dissatisfied +3194,66434,Male,Loyal Customer,29,Business travel,Business,3772,5,5,5,5,5,4,5,5,3,3,5,3,4,5,0,,satisfied +3195,101065,Male,Loyal Customer,26,Personal Travel,Eco,368,3,2,3,3,4,3,4,4,2,3,3,3,4,4,3,0.0,neutral or dissatisfied +3196,6431,Female,Loyal Customer,63,Personal Travel,Eco,315,2,5,2,2,4,4,4,3,3,2,5,3,3,3,0,0.0,neutral or dissatisfied +3197,6589,Male,Loyal Customer,58,Personal Travel,Eco,618,1,4,1,2,2,1,2,2,4,4,5,3,5,2,48,,neutral or dissatisfied +3198,78151,Male,Loyal Customer,40,Business travel,Business,259,0,0,0,4,5,4,4,3,3,4,4,5,3,3,15,6.0,satisfied +3199,108781,Female,Loyal Customer,66,Business travel,Business,1629,2,1,1,1,1,2,2,2,2,2,2,1,2,4,23,29.0,neutral or dissatisfied +3200,107511,Male,disloyal Customer,16,Business travel,Eco,838,3,3,3,3,1,3,1,1,3,5,5,4,5,1,65,50.0,neutral or dissatisfied +3201,3286,Male,Loyal Customer,56,Personal Travel,Eco,479,3,1,3,3,2,3,1,2,4,4,3,3,4,2,0,4.0,neutral or dissatisfied +3202,29102,Male,Loyal Customer,48,Personal Travel,Eco,679,1,5,1,5,3,1,3,3,3,4,5,5,5,3,0,8.0,neutral or dissatisfied +3203,105658,Male,Loyal Customer,51,Business travel,Business,919,2,2,2,2,5,5,5,4,4,3,4,4,4,3,13,5.0,satisfied +3204,19723,Female,Loyal Customer,34,Personal Travel,Eco,409,3,4,3,1,4,3,4,4,5,2,3,5,5,4,0,0.0,neutral or dissatisfied +3205,95641,Female,disloyal Customer,18,Business travel,Eco Plus,484,2,2,2,4,2,5,5,2,2,3,3,5,1,5,132,117.0,neutral or dissatisfied +3206,75002,Male,Loyal Customer,39,Business travel,Business,236,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +3207,113651,Female,Loyal Customer,56,Personal Travel,Eco,397,2,5,2,3,5,4,5,2,2,2,2,4,2,3,51,44.0,neutral or dissatisfied +3208,3874,Male,disloyal Customer,37,Business travel,Business,213,4,4,4,4,3,4,3,3,3,3,5,5,4,3,0,45.0,satisfied +3209,58721,Male,Loyal Customer,48,Business travel,Business,2807,2,2,2,2,3,4,3,2,2,2,2,2,2,4,31,16.0,neutral or dissatisfied +3210,117657,Female,Loyal Customer,57,Business travel,Business,1449,2,2,2,2,3,4,5,4,4,4,4,5,4,4,10,0.0,satisfied +3211,58237,Male,Loyal Customer,57,Personal Travel,Eco,925,1,2,1,3,5,1,1,5,2,4,4,3,4,5,6,11.0,neutral or dissatisfied +3212,95688,Male,Loyal Customer,43,Business travel,Business,419,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,2.0,satisfied +3213,39547,Male,Loyal Customer,32,Business travel,Business,3277,2,2,2,2,4,4,4,4,4,3,3,3,2,4,22,2.0,satisfied +3214,121296,Female,Loyal Customer,46,Business travel,Business,2326,2,2,2,2,4,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +3215,74943,Female,disloyal Customer,22,Business travel,Eco,1477,2,2,2,3,5,2,5,5,4,4,2,4,3,5,0,0.0,neutral or dissatisfied +3216,86707,Male,Loyal Customer,46,Business travel,Business,1747,1,1,1,1,4,4,5,4,4,4,4,3,4,5,4,0.0,satisfied +3217,11219,Female,Loyal Customer,68,Personal Travel,Eco,247,3,5,0,1,2,4,5,1,1,0,1,3,1,5,4,7.0,neutral or dissatisfied +3218,93412,Male,disloyal Customer,23,Business travel,Eco,672,1,1,1,3,2,1,2,2,2,2,4,1,4,2,66,59.0,neutral or dissatisfied +3219,36763,Male,disloyal Customer,23,Business travel,Eco,925,3,2,2,4,3,2,2,4,2,3,3,2,3,2,17,10.0,neutral or dissatisfied +3220,111744,Male,Loyal Customer,17,Business travel,Business,2768,1,1,1,1,3,3,3,3,4,4,5,5,5,3,7,4.0,satisfied +3221,34010,Female,disloyal Customer,33,Business travel,Eco,1096,2,2,2,1,4,2,4,4,4,4,5,5,2,4,0,0.0,neutral or dissatisfied +3222,34427,Male,Loyal Customer,25,Business travel,Eco Plus,612,2,5,5,5,2,2,1,2,3,3,3,3,4,2,0,4.0,neutral or dissatisfied +3223,79072,Female,Loyal Customer,43,Business travel,Business,1971,2,5,5,5,4,4,3,2,2,2,2,4,2,1,32,19.0,neutral or dissatisfied +3224,123954,Male,Loyal Customer,11,Personal Travel,Eco Plus,541,1,5,1,1,4,1,4,4,4,4,5,3,5,4,0,1.0,neutral or dissatisfied +3225,61330,Male,Loyal Customer,41,Personal Travel,Eco Plus,967,2,5,2,4,4,2,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +3226,45844,Male,Loyal Customer,41,Personal Travel,Eco,391,1,5,1,5,1,1,1,1,3,1,1,4,2,1,0,0.0,neutral or dissatisfied +3227,85936,Male,disloyal Customer,16,Business travel,Eco,447,1,4,1,4,4,1,3,4,1,2,4,2,4,4,50,29.0,neutral or dissatisfied +3228,9326,Male,Loyal Customer,16,Personal Travel,Eco,419,2,1,4,4,5,4,5,5,4,4,4,4,3,5,12,68.0,neutral or dissatisfied +3229,57518,Female,disloyal Customer,38,Business travel,Business,413,4,4,4,2,4,4,4,4,3,3,4,3,4,4,0,0.0,satisfied +3230,62820,Female,Loyal Customer,48,Personal Travel,Eco,2504,2,4,2,3,3,1,2,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +3231,70411,Male,Loyal Customer,27,Personal Travel,Eco,1562,1,4,2,5,3,2,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +3232,106904,Female,Loyal Customer,57,Business travel,Business,1852,3,3,3,3,4,4,4,5,5,5,5,5,5,3,14,8.0,satisfied +3233,83806,Male,disloyal Customer,26,Business travel,Business,425,4,0,3,3,5,3,5,5,5,5,4,4,4,5,5,0.0,neutral or dissatisfied +3234,29505,Female,Loyal Customer,55,Personal Travel,Eco,1107,3,5,3,2,3,5,5,1,1,3,3,3,1,5,0,9.0,neutral or dissatisfied +3235,43032,Male,Loyal Customer,57,Business travel,Business,3410,4,4,4,4,5,5,2,4,4,4,4,5,4,1,0,0.0,satisfied +3236,53186,Female,Loyal Customer,49,Business travel,Business,3951,2,2,2,2,5,1,4,4,4,4,4,2,4,2,0,0.0,satisfied +3237,2257,Female,Loyal Customer,60,Business travel,Business,630,2,4,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +3238,106434,Male,Loyal Customer,46,Business travel,Business,2665,4,4,4,4,3,4,4,4,4,4,4,3,4,4,17,14.0,satisfied +3239,23466,Female,Loyal Customer,23,Business travel,Eco,488,4,1,1,1,4,4,4,4,5,1,5,3,2,4,22,17.0,satisfied +3240,87393,Male,disloyal Customer,50,Business travel,Eco,425,3,4,4,3,1,4,1,1,2,3,5,2,3,1,0,0.0,neutral or dissatisfied +3241,42042,Male,disloyal Customer,17,Business travel,Eco,106,2,2,2,4,1,2,1,1,2,2,3,2,3,1,109,117.0,neutral or dissatisfied +3242,55075,Male,disloyal Customer,39,Business travel,Eco,1379,2,2,2,4,4,2,4,4,2,3,4,2,4,4,8,0.0,neutral or dissatisfied +3243,88193,Female,disloyal Customer,22,Business travel,Eco,646,4,1,4,4,3,4,3,3,1,2,4,2,4,3,33,20.0,neutral or dissatisfied +3244,89950,Male,Loyal Customer,19,Personal Travel,Eco,1501,1,5,2,3,1,2,1,1,4,3,5,5,5,1,0,0.0,neutral or dissatisfied +3245,97890,Female,Loyal Customer,42,Business travel,Business,612,3,3,3,3,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +3246,5738,Male,Loyal Customer,48,Personal Travel,Eco Plus,234,3,4,3,1,5,3,3,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +3247,84972,Female,Loyal Customer,25,Personal Travel,Eco Plus,547,5,4,5,1,1,5,2,1,3,4,5,5,3,1,2,0.0,satisfied +3248,3743,Female,Loyal Customer,28,Personal Travel,Eco,431,2,5,2,4,1,2,1,1,5,1,2,4,5,1,31,14.0,neutral or dissatisfied +3249,76258,Male,Loyal Customer,49,Business travel,Eco Plus,1399,3,5,2,2,3,3,3,3,1,5,3,2,4,3,1,0.0,neutral or dissatisfied +3250,10027,Female,Loyal Customer,37,Business travel,Business,2323,5,5,5,5,5,4,4,5,5,5,5,3,5,3,25,28.0,satisfied +3251,59421,Male,Loyal Customer,56,Business travel,Business,2367,1,2,1,1,5,5,5,4,4,4,4,3,4,3,13,0.0,satisfied +3252,18032,Male,Loyal Customer,34,Business travel,Business,488,4,4,4,4,1,3,4,4,4,4,4,1,4,5,0,0.0,satisfied +3253,82461,Female,Loyal Customer,40,Personal Travel,Eco,509,3,5,5,1,4,5,3,4,4,2,4,3,4,4,62,124.0,neutral or dissatisfied +3254,62643,Male,Loyal Customer,42,Personal Travel,Eco,1744,2,4,3,4,1,3,1,1,3,3,2,3,3,1,5,3.0,neutral or dissatisfied +3255,589,Male,Loyal Customer,50,Business travel,Business,164,1,1,4,1,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +3256,95589,Female,Loyal Customer,34,Business travel,Business,822,2,2,2,2,5,5,5,5,5,5,5,5,5,5,6,0.0,satisfied +3257,51343,Female,Loyal Customer,55,Business travel,Eco Plus,109,4,3,3,3,4,3,5,4,4,4,4,2,4,5,0,0.0,satisfied +3258,77281,Female,Loyal Customer,60,Business travel,Business,1931,3,3,3,3,3,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +3259,50634,Female,Loyal Customer,9,Personal Travel,Eco,250,2,5,2,4,2,2,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +3260,76262,Female,Loyal Customer,31,Personal Travel,Eco Plus,1175,3,4,3,3,4,3,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +3261,108997,Female,disloyal Customer,27,Business travel,Business,1105,3,3,3,3,3,3,3,3,3,5,4,4,4,3,0,3.0,neutral or dissatisfied +3262,104633,Male,Loyal Customer,14,Personal Travel,Eco,861,1,5,0,3,3,0,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +3263,127702,Male,Loyal Customer,53,Personal Travel,Eco,2133,3,5,2,2,5,2,3,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +3264,60239,Male,Loyal Customer,40,Personal Travel,Eco,1546,3,1,3,2,5,3,5,5,1,2,1,1,2,5,0,0.0,neutral or dissatisfied +3265,68154,Female,Loyal Customer,46,Business travel,Business,603,4,4,4,4,2,5,5,5,5,5,5,3,5,3,26,22.0,satisfied +3266,87689,Male,Loyal Customer,49,Personal Travel,Eco,606,2,5,2,4,4,2,4,4,4,1,2,4,1,4,0,0.0,neutral or dissatisfied +3267,125807,Female,disloyal Customer,20,Business travel,Eco,920,4,4,4,3,5,4,5,5,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +3268,124713,Male,Loyal Customer,36,Personal Travel,Eco,399,3,2,3,4,2,3,4,2,3,5,3,1,4,2,39,46.0,neutral or dissatisfied +3269,9408,Female,disloyal Customer,44,Business travel,Business,1136,4,4,4,5,3,4,3,3,5,5,5,3,5,3,0,6.0,satisfied +3270,22095,Female,Loyal Customer,13,Business travel,Business,3491,3,2,2,2,3,3,3,3,1,1,3,1,3,3,20,26.0,neutral or dissatisfied +3271,40574,Female,disloyal Customer,61,Business travel,Eco,391,2,0,1,5,3,1,3,3,2,2,4,1,3,3,0,0.0,neutral or dissatisfied +3272,76426,Female,Loyal Customer,62,Business travel,Eco,405,2,5,5,5,5,3,3,2,2,2,2,2,2,2,5,7.0,neutral or dissatisfied +3273,30476,Male,Loyal Customer,26,Personal Travel,Eco,428,3,2,3,4,5,3,5,5,3,2,3,2,3,5,56,85.0,neutral or dissatisfied +3274,121865,Female,disloyal Customer,27,Business travel,Eco,337,3,3,4,3,5,4,5,5,4,3,4,1,3,5,0,0.0,neutral or dissatisfied +3275,56879,Male,Loyal Customer,44,Business travel,Business,2454,5,5,5,5,5,4,4,4,4,4,4,5,4,5,41,56.0,satisfied +3276,127934,Male,Loyal Customer,41,Personal Travel,Eco,2300,2,5,2,4,2,2,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +3277,56800,Female,disloyal Customer,42,Business travel,Business,1605,2,2,2,2,1,2,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +3278,53776,Female,Loyal Customer,43,Business travel,Business,3258,3,4,5,5,1,4,4,3,3,3,3,1,3,1,4,0.0,neutral or dissatisfied +3279,89269,Male,disloyal Customer,34,Business travel,Business,453,2,2,2,1,2,2,2,2,5,2,4,4,4,2,2,0.0,neutral or dissatisfied +3280,21696,Male,Loyal Customer,69,Personal Travel,Eco,746,2,3,2,4,1,2,1,1,4,5,4,1,3,1,40,39.0,neutral or dissatisfied +3281,104232,Female,Loyal Customer,18,Personal Travel,Eco Plus,680,1,1,1,3,4,1,4,4,2,2,2,4,3,4,15,0.0,neutral or dissatisfied +3282,56513,Female,Loyal Customer,27,Personal Travel,Business,1023,2,4,2,4,1,2,1,1,3,4,4,5,5,1,51,51.0,neutral or dissatisfied +3283,38117,Female,Loyal Customer,48,Business travel,Business,2748,1,5,5,5,1,4,4,1,1,1,1,2,1,4,77,68.0,neutral or dissatisfied +3284,48214,Female,Loyal Customer,60,Personal Travel,Eco,391,5,3,5,3,5,3,3,1,1,5,1,2,1,1,0,5.0,satisfied +3285,108560,Female,Loyal Customer,21,Personal Travel,Eco,735,4,1,4,3,1,4,1,1,2,1,3,1,3,1,0,0.0,neutral or dissatisfied +3286,91216,Female,Loyal Customer,33,Personal Travel,Eco,406,0,2,0,3,5,0,2,5,3,2,4,3,3,5,0,0.0,satisfied +3287,10331,Female,disloyal Customer,21,Business travel,Business,201,4,4,4,1,4,4,3,4,3,2,4,3,4,4,0,0.0,satisfied +3288,28613,Male,Loyal Customer,27,Business travel,Business,2384,5,5,5,5,4,4,4,4,1,4,3,4,3,4,1,0.0,satisfied +3289,20206,Female,Loyal Customer,49,Business travel,Business,179,2,1,1,1,2,4,4,2,2,2,2,3,2,3,3,0.0,neutral or dissatisfied +3290,119773,Female,Loyal Customer,59,Business travel,Business,1569,2,2,1,1,3,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +3291,3062,Female,Loyal Customer,13,Personal Travel,Eco,340,2,2,2,3,4,2,3,4,3,1,4,1,3,4,9,25.0,neutral or dissatisfied +3292,30122,Female,Loyal Customer,67,Personal Travel,Eco,261,2,5,2,4,5,2,1,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +3293,80495,Male,Loyal Customer,34,Business travel,Business,1749,1,1,1,1,5,3,5,4,4,4,4,4,4,3,84,80.0,satisfied +3294,26671,Female,Loyal Customer,13,Personal Travel,Eco,515,3,3,3,4,3,3,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +3295,731,Female,disloyal Customer,22,Business travel,Business,164,1,2,1,3,4,1,4,4,1,1,3,2,3,4,3,0.0,neutral or dissatisfied +3296,118443,Male,Loyal Customer,42,Business travel,Business,1847,3,3,3,3,4,4,4,5,5,5,5,4,5,3,11,3.0,satisfied +3297,74840,Female,Loyal Customer,41,Personal Travel,Eco,1797,4,5,4,3,5,4,4,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +3298,38635,Female,Loyal Customer,55,Business travel,Business,2704,4,4,4,4,5,5,5,4,4,4,4,3,4,1,0,0.0,satisfied +3299,100330,Male,Loyal Customer,28,Business travel,Business,3486,4,4,4,4,4,3,4,4,4,3,3,4,4,4,22,12.0,neutral or dissatisfied +3300,23823,Female,Loyal Customer,65,Personal Travel,Eco,438,2,4,2,3,5,4,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +3301,18982,Female,Loyal Customer,26,Business travel,Business,451,3,1,4,1,3,3,3,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +3302,56654,Male,disloyal Customer,18,Business travel,Eco,937,4,4,4,5,2,4,1,2,1,3,3,4,4,2,0,0.0,satisfied +3303,84185,Male,Loyal Customer,47,Business travel,Business,3675,2,4,4,4,3,4,4,2,2,2,2,2,2,2,56,83.0,neutral or dissatisfied +3304,89420,Male,disloyal Customer,25,Business travel,Eco,151,4,2,4,3,1,4,1,1,1,1,3,4,3,1,0,11.0,neutral or dissatisfied +3305,95246,Male,Loyal Customer,52,Personal Travel,Eco,323,2,1,2,2,2,2,2,2,4,2,2,1,3,2,1,0.0,neutral or dissatisfied +3306,22249,Female,Loyal Customer,42,Business travel,Business,3694,3,4,3,3,5,2,1,5,5,5,5,3,5,5,0,0.0,satisfied +3307,99571,Male,Loyal Customer,45,Business travel,Business,3146,5,5,4,5,5,4,4,4,4,4,4,3,4,4,0,4.0,satisfied +3308,121789,Male,Loyal Customer,45,Business travel,Business,449,4,4,2,4,2,4,4,4,4,4,4,5,4,5,3,0.0,satisfied +3309,99695,Male,Loyal Customer,52,Personal Travel,Eco,442,3,3,3,4,5,3,5,5,2,1,4,2,4,5,2,5.0,neutral or dissatisfied +3310,47115,Female,Loyal Customer,39,Business travel,Business,384,5,5,3,5,4,4,1,4,4,4,4,1,4,4,0,0.0,satisfied +3311,21283,Male,Loyal Customer,27,Business travel,Business,620,3,3,3,3,5,5,5,5,1,1,3,4,2,5,7,0.0,satisfied +3312,98944,Male,Loyal Customer,52,Business travel,Eco,479,2,5,5,5,2,2,2,2,1,4,4,4,4,2,0,0.0,neutral or dissatisfied +3313,15187,Male,Loyal Customer,44,Business travel,Eco,544,4,2,3,2,5,4,5,5,5,1,4,2,4,5,42,11.0,satisfied +3314,21680,Female,Loyal Customer,48,Business travel,Eco,746,3,5,5,5,3,3,3,3,3,3,3,2,3,1,49,95.0,neutral or dissatisfied +3315,114299,Female,Loyal Customer,41,Personal Travel,Eco,948,2,3,2,3,5,2,5,5,1,2,4,3,4,5,49,52.0,neutral or dissatisfied +3316,79842,Male,disloyal Customer,36,Business travel,Business,950,3,3,3,5,5,3,5,5,3,5,5,5,4,5,0,10.0,neutral or dissatisfied +3317,108494,Female,Loyal Customer,50,Business travel,Business,1961,2,2,2,2,2,5,4,4,4,4,4,4,4,5,15,4.0,satisfied +3318,105972,Female,Loyal Customer,59,Business travel,Business,829,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +3319,92162,Female,Loyal Customer,60,Business travel,Business,1979,1,1,1,1,5,3,4,5,5,5,5,3,5,5,6,0.0,satisfied +3320,117192,Male,Loyal Customer,29,Personal Travel,Eco,646,2,2,2,4,3,2,3,3,2,1,4,3,4,3,17,3.0,neutral or dissatisfied +3321,11328,Male,Loyal Customer,46,Personal Travel,Eco,517,3,4,3,3,3,3,3,3,3,3,4,5,5,3,41,36.0,neutral or dissatisfied +3322,15241,Male,Loyal Customer,27,Personal Travel,Eco,416,4,3,4,2,5,4,5,5,2,3,3,4,3,5,0,0.0,satisfied +3323,42106,Male,Loyal Customer,33,Business travel,Business,2251,1,1,1,1,4,5,4,4,1,5,3,4,4,4,0,0.0,satisfied +3324,31179,Male,Loyal Customer,57,Business travel,Eco,1620,4,4,4,4,4,4,4,4,3,1,2,2,3,4,0,26.0,neutral or dissatisfied +3325,21355,Male,Loyal Customer,15,Personal Travel,Eco,674,2,4,2,4,2,4,3,5,2,4,5,3,5,3,352,344.0,neutral or dissatisfied +3326,43298,Female,disloyal Customer,41,Business travel,Business,358,3,3,3,3,4,3,2,4,3,1,3,2,1,4,0,5.0,neutral or dissatisfied +3327,94979,Male,Loyal Customer,20,Business travel,Business,2916,1,4,4,4,1,1,1,1,4,4,4,2,3,1,14,7.0,neutral or dissatisfied +3328,54104,Female,Loyal Customer,34,Personal Travel,Eco Plus,1416,2,3,2,2,2,2,2,2,2,2,2,2,4,2,29,11.0,neutral or dissatisfied +3329,109962,Male,Loyal Customer,21,Personal Travel,Eco,1073,4,5,4,4,4,4,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +3330,5914,Male,Loyal Customer,36,Personal Travel,Eco,67,4,4,4,3,3,4,3,3,3,5,5,4,4,3,0,0.0,satisfied +3331,64555,Male,Loyal Customer,53,Business travel,Business,247,5,5,5,5,3,5,5,5,5,5,5,4,5,5,0,2.0,satisfied +3332,47398,Female,Loyal Customer,23,Business travel,Eco,584,3,1,1,1,3,3,4,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +3333,17838,Female,Loyal Customer,51,Personal Travel,Eco Plus,1214,4,4,4,4,4,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +3334,8505,Female,Loyal Customer,48,Business travel,Business,3628,5,5,5,5,3,4,5,5,5,5,5,3,5,5,2,0.0,satisfied +3335,30669,Male,Loyal Customer,41,Personal Travel,Eco Plus,533,3,4,3,3,4,3,4,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +3336,15111,Male,Loyal Customer,57,Business travel,Eco,912,5,5,4,4,5,5,5,5,4,5,4,3,2,5,0,0.0,satisfied +3337,58928,Male,Loyal Customer,16,Personal Travel,Eco,888,4,4,4,4,2,4,4,2,5,5,4,5,4,2,0,0.0,satisfied +3338,64926,Male,disloyal Customer,17,Business travel,Eco,247,3,4,3,3,2,3,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +3339,21043,Male,Loyal Customer,53,Business travel,Business,2228,0,0,0,2,4,3,5,5,5,5,5,1,5,4,0,0.0,satisfied +3340,128495,Male,Loyal Customer,16,Personal Travel,Eco,325,1,4,1,5,4,1,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +3341,302,Male,Loyal Customer,52,Business travel,Business,821,5,5,4,5,5,5,5,5,5,5,5,3,5,4,18,18.0,satisfied +3342,80508,Male,Loyal Customer,52,Business travel,Business,1749,4,4,4,4,2,2,3,4,4,4,4,1,4,2,0,2.0,neutral or dissatisfied +3343,2707,Female,Loyal Customer,14,Personal Travel,Eco,562,1,5,1,1,1,1,1,1,3,2,4,4,4,1,50,48.0,neutral or dissatisfied +3344,37738,Female,Loyal Customer,8,Personal Travel,Eco,1053,2,4,2,4,5,2,5,5,4,3,4,3,5,5,0,4.0,neutral or dissatisfied +3345,68711,Female,Loyal Customer,42,Personal Travel,Eco,237,2,1,2,2,1,3,2,2,2,2,3,3,2,2,0,0.0,neutral or dissatisfied +3346,98547,Female,Loyal Customer,51,Personal Travel,Eco Plus,402,1,5,1,4,2,4,4,3,3,1,3,3,3,3,9,22.0,neutral or dissatisfied +3347,45194,Male,disloyal Customer,36,Business travel,Eco,1037,3,3,3,3,4,3,4,4,5,1,2,2,3,4,0,0.0,neutral or dissatisfied +3348,91576,Female,Loyal Customer,40,Business travel,Eco,723,2,5,5,5,2,2,2,2,1,4,4,3,3,2,0,0.0,neutral or dissatisfied +3349,128066,Male,Loyal Customer,7,Personal Travel,Business,2860,3,1,3,3,3,1,4,2,1,4,3,4,1,4,0,0.0,neutral or dissatisfied +3350,84962,Female,Loyal Customer,60,Personal Travel,Eco Plus,534,2,4,2,2,4,5,4,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +3351,106139,Female,disloyal Customer,19,Business travel,Eco,302,4,0,4,3,4,4,4,4,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +3352,79238,Male,Loyal Customer,46,Business travel,Business,1598,3,3,3,3,4,3,4,2,2,2,2,5,2,4,20,33.0,satisfied +3353,62779,Male,Loyal Customer,34,Business travel,Eco,2399,2,2,2,2,2,2,2,2,3,4,4,3,3,2,84,76.0,neutral or dissatisfied +3354,92689,Female,Loyal Customer,35,Personal Travel,Eco,507,4,5,4,1,1,4,3,1,5,4,4,5,5,1,0,0.0,satisfied +3355,308,Female,Loyal Customer,56,Business travel,Business,853,3,3,1,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +3356,126312,Male,Loyal Customer,30,Personal Travel,Eco,590,4,5,4,1,2,4,2,2,1,2,3,4,5,2,0,0.0,neutral or dissatisfied +3357,14968,Male,Loyal Customer,38,Business travel,Eco,1020,4,2,2,2,4,4,4,4,5,2,4,5,5,4,0,4.0,satisfied +3358,42594,Male,Loyal Customer,48,Personal Travel,Eco,1201,3,5,3,3,4,3,4,4,4,5,2,2,5,4,0,0.0,neutral or dissatisfied +3359,103733,Female,Loyal Customer,28,Personal Travel,Eco,251,1,5,1,5,5,1,3,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +3360,16773,Female,Loyal Customer,40,Business travel,Business,569,2,2,2,2,3,2,2,5,5,5,5,4,5,3,0,0.0,satisfied +3361,9465,Male,Loyal Customer,19,Personal Travel,Eco,288,1,4,1,4,5,1,5,5,2,2,3,3,4,5,1,0.0,neutral or dissatisfied +3362,121617,Male,Loyal Customer,53,Personal Travel,Eco,1095,2,1,2,4,4,2,4,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +3363,3844,Male,Loyal Customer,22,Personal Travel,Eco,650,2,2,2,4,4,2,5,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +3364,81019,Male,Loyal Customer,31,Business travel,Business,1399,1,5,5,5,1,1,1,1,3,4,4,1,4,1,6,8.0,neutral or dissatisfied +3365,74542,Male,Loyal Customer,29,Business travel,Business,1171,1,1,4,1,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +3366,105662,Male,Loyal Customer,40,Business travel,Business,787,1,5,1,1,3,5,4,4,4,4,4,5,4,4,68,74.0,satisfied +3367,69025,Female,Loyal Customer,51,Business travel,Business,1389,4,4,4,4,3,4,4,4,4,4,4,5,4,4,11,1.0,satisfied +3368,62878,Female,Loyal Customer,45,Personal Travel,Eco,2218,4,2,5,3,3,3,2,3,3,5,3,4,3,3,28,20.0,neutral or dissatisfied +3369,89753,Female,Loyal Customer,21,Personal Travel,Eco,1080,4,4,4,3,3,4,3,3,4,2,3,2,4,3,0,0.0,satisfied +3370,20530,Female,Loyal Customer,42,Business travel,Eco,533,4,5,3,5,4,5,3,3,3,4,3,1,3,2,0,0.0,satisfied +3371,85758,Male,Loyal Customer,54,Business travel,Business,666,2,1,2,2,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +3372,126306,Female,Loyal Customer,21,Personal Travel,Eco,328,4,4,4,3,3,4,3,3,4,5,4,1,4,3,5,3.0,neutral or dissatisfied +3373,106989,Female,Loyal Customer,29,Personal Travel,Eco,937,3,3,3,3,1,3,2,1,1,3,4,1,3,1,30,24.0,neutral or dissatisfied +3374,96402,Female,Loyal Customer,42,Business travel,Eco,942,3,1,1,1,2,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +3375,63640,Female,Loyal Customer,52,Personal Travel,Eco,602,4,1,4,3,2,4,4,5,5,4,5,3,5,1,0,0.0,satisfied +3376,42057,Male,Loyal Customer,33,Personal Travel,Eco,116,4,3,4,3,4,4,4,4,2,4,3,2,4,4,0,0.0,neutral or dissatisfied +3377,60272,Female,Loyal Customer,40,Business travel,Business,2446,4,4,4,4,4,4,4,5,5,4,5,4,3,4,18,29.0,satisfied +3378,27434,Male,Loyal Customer,57,Business travel,Eco,954,3,3,5,3,3,3,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +3379,87475,Female,Loyal Customer,59,Business travel,Business,2886,5,5,5,5,3,5,5,5,5,5,5,4,5,4,34,39.0,satisfied +3380,58648,Male,Loyal Customer,46,Business travel,Eco,467,2,5,5,5,2,2,2,2,1,1,4,2,4,2,40,24.0,neutral or dissatisfied +3381,42517,Female,Loyal Customer,60,Personal Travel,Eco,1384,2,5,2,4,4,4,1,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +3382,3401,Female,Loyal Customer,21,Business travel,Business,3365,2,2,2,2,4,4,4,4,4,5,2,3,1,4,0,0.0,satisfied +3383,60114,Female,disloyal Customer,22,Business travel,Business,1005,4,0,4,1,5,4,4,5,4,3,5,5,5,5,0,0.0,satisfied +3384,77916,Female,Loyal Customer,45,Business travel,Business,2210,1,1,1,1,5,4,5,5,5,5,4,4,5,3,22,27.0,satisfied +3385,15608,Male,Loyal Customer,33,Business travel,Business,283,3,4,4,4,3,2,3,3,4,1,4,4,4,3,51,56.0,neutral or dissatisfied +3386,61023,Male,Loyal Customer,49,Personal Travel,Eco,3365,3,3,3,4,3,5,5,3,4,4,4,5,4,5,12,80.0,neutral or dissatisfied +3387,41512,Male,Loyal Customer,18,Business travel,Eco,1482,3,5,3,3,3,4,4,3,1,4,1,5,5,3,16,20.0,satisfied +3388,4610,Female,Loyal Customer,58,Business travel,Eco,719,3,5,5,5,2,3,3,4,4,3,4,4,4,3,6,1.0,neutral or dissatisfied +3389,28383,Male,Loyal Customer,73,Business travel,Business,3686,1,4,4,4,3,4,3,1,1,1,1,1,1,1,0,3.0,neutral or dissatisfied +3390,70632,Female,Loyal Customer,56,Personal Travel,Eco,1217,4,5,4,4,4,5,4,5,5,4,5,5,5,5,0,0.0,neutral or dissatisfied +3391,93472,Female,Loyal Customer,58,Business travel,Eco Plus,697,1,4,4,4,5,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +3392,53907,Female,Loyal Customer,53,Personal Travel,Eco,191,3,5,3,1,4,4,4,1,1,3,1,4,1,5,57,53.0,neutral or dissatisfied +3393,95786,Female,Loyal Customer,49,Personal Travel,Eco,237,2,4,2,4,2,4,5,1,1,2,1,5,1,5,9,3.0,neutral or dissatisfied +3394,100961,Male,Loyal Customer,44,Personal Travel,Eco,1142,3,4,3,5,3,3,3,3,4,3,3,5,4,3,0,62.0,neutral or dissatisfied +3395,51828,Male,Loyal Customer,44,Business travel,Eco Plus,370,2,3,3,3,3,2,3,3,1,5,1,4,4,3,0,0.0,satisfied +3396,37710,Female,Loyal Customer,43,Personal Travel,Eco,972,1,5,1,3,5,4,4,2,2,1,2,5,2,4,3,0.0,neutral or dissatisfied +3397,105240,Male,Loyal Customer,32,Personal Travel,Eco,377,3,5,3,4,3,3,3,3,5,4,4,4,4,3,51,35.0,neutral or dissatisfied +3398,85790,Male,Loyal Customer,72,Business travel,Business,1778,1,1,4,1,3,5,5,2,2,3,2,5,2,3,0,0.0,satisfied +3399,64356,Female,disloyal Customer,23,Business travel,Eco,758,2,2,2,2,4,2,4,4,4,3,1,5,4,4,0,0.0,neutral or dissatisfied +3400,40206,Male,Loyal Customer,30,Business travel,Eco,436,5,2,3,2,5,5,5,5,2,1,5,3,4,5,0,0.0,satisfied +3401,38514,Female,Loyal Customer,40,Business travel,Eco,2475,4,2,2,2,4,4,4,4,4,4,5,3,5,4,12,25.0,satisfied +3402,66816,Female,disloyal Customer,35,Business travel,Business,731,3,3,3,4,4,3,4,4,5,3,5,5,5,4,0,39.0,neutral or dissatisfied +3403,26211,Male,disloyal Customer,23,Business travel,Eco,404,5,2,5,1,5,5,2,5,2,1,5,3,2,5,0,0.0,satisfied +3404,120075,Male,disloyal Customer,42,Business travel,Business,683,1,1,1,4,4,1,4,4,5,3,5,3,4,4,0,40.0,neutral or dissatisfied +3405,69456,Male,Loyal Customer,17,Personal Travel,Eco,1096,4,2,4,3,4,4,4,4,2,5,2,1,3,4,60,81.0,neutral or dissatisfied +3406,65869,Male,Loyal Customer,43,Personal Travel,Eco,1389,3,4,3,4,3,3,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +3407,10162,Male,disloyal Customer,27,Business travel,Business,224,5,5,5,4,2,5,2,2,5,2,5,5,5,2,0,0.0,satisfied +3408,125470,Female,Loyal Customer,40,Personal Travel,Eco,2845,3,1,3,4,5,3,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +3409,102308,Female,Loyal Customer,74,Business travel,Business,236,4,3,3,3,4,3,3,4,4,4,4,1,4,3,0,1.0,neutral or dissatisfied +3410,114319,Male,Loyal Customer,47,Personal Travel,Eco,846,3,5,2,1,5,2,1,5,3,3,5,4,5,5,0,0.0,neutral or dissatisfied +3411,56523,Female,disloyal Customer,45,Business travel,Business,1023,2,2,2,3,3,2,4,3,3,2,4,4,5,3,8,7.0,neutral or dissatisfied +3412,108416,Female,Loyal Customer,31,Business travel,Business,1440,5,5,5,5,4,4,4,4,4,5,4,3,4,4,4,12.0,satisfied +3413,76709,Male,Loyal Customer,49,Personal Travel,Eco,357,3,1,3,3,4,3,5,4,4,5,2,3,2,4,0,0.0,neutral or dissatisfied +3414,16674,Female,Loyal Customer,66,Personal Travel,Eco,605,4,4,5,2,4,4,4,2,2,5,2,5,2,3,28,48.0,neutral or dissatisfied +3415,12112,Male,Loyal Customer,39,Business travel,Business,3399,3,4,5,4,1,3,2,3,3,3,3,1,3,2,0,19.0,neutral or dissatisfied +3416,40159,Female,Loyal Customer,51,Personal Travel,Business,387,3,5,3,4,5,5,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +3417,61867,Female,Loyal Customer,60,Business travel,Business,2521,3,3,3,3,4,5,5,5,5,5,5,3,5,4,46,21.0,satisfied +3418,71379,Male,Loyal Customer,32,Business travel,Eco,258,5,2,2,2,5,4,5,5,4,1,3,2,4,5,0,0.0,neutral or dissatisfied +3419,11681,Female,disloyal Customer,25,Business travel,Business,395,4,0,4,4,2,4,2,2,5,5,5,3,5,2,4,0.0,satisfied +3420,110900,Male,disloyal Customer,24,Business travel,Eco,545,3,3,3,3,5,3,5,5,1,3,3,3,4,5,0,9.0,neutral or dissatisfied +3421,27800,Male,disloyal Customer,29,Business travel,Eco,1533,1,1,1,3,5,1,5,5,3,3,3,1,3,5,4,0.0,neutral or dissatisfied +3422,90883,Female,Loyal Customer,45,Business travel,Business,1946,4,4,4,4,4,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +3423,61626,Male,Loyal Customer,44,Business travel,Business,1635,5,5,5,5,3,3,5,5,5,5,5,4,5,5,23,5.0,satisfied +3424,4957,Female,Loyal Customer,42,Business travel,Business,2712,4,5,4,4,4,5,5,4,4,3,4,4,4,3,0,0.0,satisfied +3425,13157,Male,Loyal Customer,45,Personal Travel,Eco,427,3,5,4,4,2,4,2,2,1,4,2,3,3,2,5,11.0,neutral or dissatisfied +3426,95716,Female,Loyal Customer,37,Business travel,Eco,419,2,5,1,5,2,2,2,2,2,1,1,1,2,2,53,43.0,neutral or dissatisfied +3427,62083,Male,Loyal Customer,39,Business travel,Business,2475,2,2,2,2,4,5,4,5,5,5,5,3,5,4,107,89.0,satisfied +3428,3699,Female,Loyal Customer,36,Business travel,Business,1840,2,2,2,2,4,5,5,2,5,1,5,5,4,5,166,,satisfied +3429,128190,Female,Loyal Customer,23,Personal Travel,Eco Plus,1849,5,4,5,4,2,4,2,2,1,3,5,5,5,2,0,19.0,satisfied +3430,16360,Male,Loyal Customer,48,Business travel,Eco,319,5,4,4,4,5,5,5,5,2,4,3,1,2,5,35,31.0,satisfied +3431,126716,Male,Loyal Customer,39,Business travel,Business,2402,4,4,4,4,3,5,5,4,4,4,4,5,4,5,17,0.0,satisfied +3432,125203,Female,Loyal Customer,61,Business travel,Business,3504,5,2,5,5,1,3,1,5,5,5,5,2,5,1,0,8.0,satisfied +3433,99313,Male,Loyal Customer,23,Business travel,Business,448,3,4,4,4,3,3,3,3,4,3,3,4,3,3,64,74.0,neutral or dissatisfied +3434,39857,Female,disloyal Customer,48,Business travel,Eco,184,0,0,0,3,3,0,3,3,1,4,4,2,5,3,0,0.0,satisfied +3435,67161,Male,Loyal Customer,36,Business travel,Eco,529,2,4,4,4,2,3,2,2,1,2,4,1,3,2,30,27.0,neutral or dissatisfied +3436,73527,Male,disloyal Customer,51,Business travel,Eco,594,4,1,4,4,5,4,5,5,1,3,3,3,3,5,0,26.0,neutral or dissatisfied +3437,29456,Female,Loyal Customer,14,Personal Travel,Eco,421,1,2,1,3,4,1,3,4,2,5,3,3,3,4,72,81.0,neutral or dissatisfied +3438,76146,Female,Loyal Customer,12,Business travel,Business,3674,4,4,4,4,5,5,5,5,5,5,4,4,4,5,0,0.0,satisfied +3439,51289,Male,Loyal Customer,79,Business travel,Eco Plus,209,2,2,4,2,2,2,2,2,1,2,3,1,3,2,18,22.0,neutral or dissatisfied +3440,72337,Female,disloyal Customer,20,Business travel,Eco,918,4,3,3,3,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +3441,23434,Female,disloyal Customer,22,Business travel,Business,516,4,0,4,1,3,4,3,3,4,1,2,1,1,3,21,27.0,satisfied +3442,1992,Male,Loyal Customer,47,Personal Travel,Eco,285,2,4,3,1,5,3,4,5,4,2,5,3,2,5,7,9.0,neutral or dissatisfied +3443,101904,Female,disloyal Customer,16,Business travel,Eco,2039,1,1,1,3,4,1,4,4,4,4,3,3,4,4,4,0.0,neutral or dissatisfied +3444,113527,Male,Loyal Customer,61,Business travel,Business,1861,2,5,2,2,3,4,3,2,2,2,2,3,2,1,32,52.0,neutral or dissatisfied +3445,119409,Female,Loyal Customer,56,Business travel,Business,3167,4,4,4,4,2,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +3446,71710,Male,Loyal Customer,31,Personal Travel,Eco Plus,1005,3,4,3,2,5,3,2,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +3447,80574,Male,Loyal Customer,50,Business travel,Business,1747,1,5,5,5,4,1,3,1,1,1,1,1,1,4,1,0.0,neutral or dissatisfied +3448,96996,Male,Loyal Customer,65,Personal Travel,Eco,883,1,2,1,2,3,1,1,3,2,5,3,4,3,3,5,4.0,neutral or dissatisfied +3449,40614,Female,Loyal Customer,8,Personal Travel,Eco,391,3,5,3,3,2,3,4,2,4,4,4,5,5,2,12,44.0,neutral or dissatisfied +3450,113319,Male,Loyal Customer,49,Business travel,Business,3002,5,5,5,5,3,4,4,4,4,4,5,3,4,5,2,0.0,satisfied +3451,870,Male,Loyal Customer,44,Business travel,Business,2184,3,2,2,2,1,3,2,4,4,3,3,2,4,1,39,42.0,neutral or dissatisfied +3452,41049,Female,Loyal Customer,59,Personal Travel,Eco,1087,2,4,2,3,1,1,1,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +3453,95376,Female,Loyal Customer,29,Personal Travel,Eco,248,3,5,3,4,5,3,2,5,3,2,4,5,4,5,10,12.0,neutral or dissatisfied +3454,11011,Male,Loyal Customer,42,Business travel,Business,3198,5,5,5,5,4,2,1,5,5,5,5,1,5,1,1,0.0,satisfied +3455,53188,Male,Loyal Customer,41,Business travel,Business,2021,2,2,2,2,3,5,3,4,4,4,4,4,4,3,0,24.0,satisfied +3456,101389,Female,disloyal Customer,21,Business travel,Eco,486,1,5,1,4,1,1,1,1,4,4,4,5,4,1,49,35.0,neutral or dissatisfied +3457,123063,Female,Loyal Customer,41,Business travel,Business,590,3,2,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +3458,4995,Female,Loyal Customer,27,Business travel,Business,502,2,1,1,1,2,2,2,2,3,2,3,2,3,2,13,53.0,neutral or dissatisfied +3459,111954,Female,Loyal Customer,41,Business travel,Business,770,4,4,4,4,3,4,5,4,4,4,4,3,4,3,23,4.0,satisfied +3460,85129,Female,Loyal Customer,57,Business travel,Business,813,4,4,4,4,5,5,5,4,4,4,4,4,4,5,8,0.0,satisfied +3461,68131,Female,Loyal Customer,56,Personal Travel,Eco,813,2,2,2,3,5,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +3462,7303,Male,Loyal Customer,38,Business travel,Business,3548,2,2,2,2,4,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +3463,94257,Female,Loyal Customer,50,Business travel,Business,2504,0,4,0,1,5,4,5,5,5,5,5,3,5,4,14,11.0,satisfied +3464,121251,Female,Loyal Customer,35,Business travel,Business,1814,2,1,1,1,5,3,3,2,2,2,2,4,2,4,0,7.0,neutral or dissatisfied +3465,124821,Female,disloyal Customer,23,Business travel,Eco,280,0,3,0,3,2,0,2,2,2,1,5,1,3,2,22,15.0,satisfied +3466,49978,Female,Loyal Customer,54,Business travel,Eco,308,2,4,4,4,3,4,4,2,2,2,2,4,2,2,0,1.0,neutral or dissatisfied +3467,86419,Male,Loyal Customer,59,Business travel,Business,762,2,2,2,2,5,5,5,5,5,5,5,5,5,4,22,1.0,satisfied +3468,68089,Male,Loyal Customer,52,Business travel,Eco,868,2,4,4,4,2,2,2,1,2,3,3,2,4,2,156,142.0,neutral or dissatisfied +3469,114437,Female,Loyal Customer,40,Business travel,Business,325,0,0,0,4,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +3470,114041,Male,Loyal Customer,59,Business travel,Business,511,4,4,4,4,2,5,5,5,5,5,5,3,5,3,1,0.0,satisfied +3471,46750,Male,Loyal Customer,9,Personal Travel,Eco,125,4,3,0,3,3,0,3,3,3,5,4,4,4,3,0,0.0,satisfied +3472,96582,Male,disloyal Customer,33,Business travel,Business,333,2,2,2,4,2,2,2,2,4,5,4,5,4,2,115,102.0,neutral or dissatisfied +3473,64816,Female,disloyal Customer,20,Business travel,Eco,282,5,0,5,1,3,5,3,3,4,2,5,4,4,3,0,0.0,satisfied +3474,109933,Female,Loyal Customer,17,Personal Travel,Eco,1053,4,5,3,1,4,3,4,4,4,5,5,3,5,4,20,24.0,neutral or dissatisfied +3475,89995,Male,Loyal Customer,56,Business travel,Business,2138,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +3476,94083,Male,disloyal Customer,20,Business travel,Eco,192,3,1,2,3,5,2,5,5,1,3,3,2,3,5,55,46.0,neutral or dissatisfied +3477,81907,Female,Loyal Customer,48,Personal Travel,Eco,680,1,5,1,5,4,5,4,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +3478,111623,Female,Loyal Customer,40,Personal Travel,Eco,1014,2,5,1,4,4,1,4,4,2,1,4,3,3,4,15,34.0,neutral or dissatisfied +3479,49238,Male,disloyal Customer,36,Business travel,Eco,308,2,0,2,3,1,2,1,1,4,2,3,2,4,1,0,22.0,neutral or dissatisfied +3480,7738,Male,disloyal Customer,25,Business travel,Business,489,4,4,4,4,2,4,2,2,5,2,4,5,4,2,0,0.0,satisfied +3481,72122,Female,Loyal Customer,50,Business travel,Business,2630,5,5,5,5,2,4,5,4,4,4,4,4,4,5,0,5.0,satisfied +3482,7928,Male,Loyal Customer,28,Business travel,Business,3773,5,5,5,5,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +3483,20779,Male,disloyal Customer,34,Business travel,Eco,515,2,4,2,2,1,2,1,1,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +3484,77080,Male,Loyal Customer,28,Personal Travel,Eco,991,2,3,2,5,5,2,2,5,4,2,4,2,3,5,13,0.0,neutral or dissatisfied +3485,63250,Male,Loyal Customer,42,Business travel,Business,3908,2,2,2,2,3,5,4,5,5,5,5,3,5,3,11,8.0,satisfied +3486,63900,Female,Loyal Customer,39,Business travel,Business,3180,1,1,1,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +3487,102292,Male,Loyal Customer,37,Business travel,Eco,407,3,2,2,2,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +3488,12890,Female,Loyal Customer,58,Business travel,Business,927,5,5,5,5,1,1,5,5,5,5,5,2,5,4,13,,satisfied +3489,1405,Male,Loyal Customer,57,Personal Travel,Eco Plus,270,2,2,2,3,3,2,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +3490,46830,Male,Loyal Customer,52,Business travel,Eco,776,4,3,3,3,4,4,4,5,4,2,3,4,3,4,157,134.0,satisfied +3491,79225,Male,Loyal Customer,11,Business travel,Eco Plus,1990,2,2,2,2,2,2,1,2,1,4,4,3,4,2,0,0.0,neutral or dissatisfied +3492,65354,Male,Loyal Customer,31,Business travel,Eco,631,2,2,2,2,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +3493,64022,Male,Loyal Customer,23,Business travel,Business,919,1,1,1,1,4,3,4,4,3,3,5,5,4,4,0,0.0,satisfied +3494,126097,Male,Loyal Customer,34,Business travel,Business,2479,3,4,4,4,5,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +3495,18530,Male,Loyal Customer,46,Business travel,Eco,253,2,1,1,1,2,2,2,2,1,5,2,1,1,2,0,0.0,neutral or dissatisfied +3496,68496,Male,Loyal Customer,45,Personal Travel,Eco,1067,4,4,4,1,3,4,3,3,4,4,5,3,5,3,0,0.0,satisfied +3497,102695,Female,disloyal Customer,16,Business travel,Eco,255,4,2,4,4,3,4,4,3,2,4,4,3,4,3,33,21.0,neutral or dissatisfied +3498,56481,Female,Loyal Customer,43,Business travel,Eco,3463,4,2,2,2,4,4,4,3,3,4,3,4,1,4,24,53.0,neutral or dissatisfied +3499,5118,Male,Loyal Customer,9,Personal Travel,Eco,303,2,4,2,2,1,2,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +3500,103329,Female,Loyal Customer,62,Personal Travel,Eco,1371,4,4,4,3,4,5,4,4,4,4,4,3,4,4,67,56.0,neutral or dissatisfied +3501,134,Female,Loyal Customer,33,Business travel,Business,227,1,1,1,1,5,4,5,5,5,5,5,4,5,5,56,57.0,satisfied +3502,86960,Female,Loyal Customer,47,Business travel,Business,3951,1,1,1,1,2,5,5,2,2,3,2,4,2,4,4,0.0,satisfied +3503,65451,Female,disloyal Customer,24,Business travel,Business,1303,5,2,5,3,3,5,3,3,4,3,5,3,4,3,29,25.0,satisfied +3504,104312,Male,Loyal Customer,8,Personal Travel,Business,452,1,5,1,2,4,1,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +3505,44818,Female,Loyal Customer,28,Business travel,Eco,491,2,5,5,5,2,2,2,2,4,5,3,1,3,2,1,5.0,neutral or dissatisfied +3506,110396,Female,Loyal Customer,23,Business travel,Business,925,4,4,4,4,5,5,5,5,5,3,5,3,4,5,0,0.0,satisfied +3507,52048,Male,Loyal Customer,48,Business travel,Business,2937,3,4,3,4,3,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +3508,114488,Male,Loyal Customer,54,Business travel,Business,2682,2,3,3,3,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +3509,49212,Female,Loyal Customer,58,Business travel,Business,1621,1,1,1,1,4,3,3,5,5,5,5,5,5,5,108,100.0,satisfied +3510,25477,Male,Loyal Customer,57,Business travel,Business,2493,1,1,1,1,3,4,4,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +3511,91871,Female,Loyal Customer,9,Personal Travel,Eco,2239,1,5,1,1,1,1,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +3512,109917,Male,Loyal Customer,29,Personal Travel,Eco,971,3,4,3,2,1,3,1,1,5,2,4,4,5,1,20,0.0,neutral or dissatisfied +3513,89130,Male,Loyal Customer,26,Business travel,Business,2139,1,3,3,3,1,1,1,1,2,4,3,4,3,1,0,0.0,neutral or dissatisfied +3514,47469,Female,Loyal Customer,8,Personal Travel,Eco,541,1,5,1,2,5,1,4,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +3515,68929,Female,disloyal Customer,26,Business travel,Business,646,3,4,3,3,2,3,1,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +3516,62089,Male,Loyal Customer,20,Personal Travel,Eco Plus,2475,4,1,4,4,4,4,2,4,2,4,3,2,3,4,31,,neutral or dissatisfied +3517,10320,Female,disloyal Customer,18,Business travel,Eco,667,3,4,3,5,2,3,2,2,4,2,5,5,4,2,75,66.0,neutral or dissatisfied +3518,39196,Male,disloyal Customer,39,Business travel,Eco,318,2,1,3,3,5,3,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +3519,78431,Female,Loyal Customer,61,Personal Travel,Business,526,3,3,3,3,2,2,3,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +3520,37672,Female,Loyal Customer,9,Personal Travel,Eco,1074,2,2,2,3,5,2,5,5,4,5,3,1,4,5,0,0.0,neutral or dissatisfied +3521,21065,Male,Loyal Customer,47,Business travel,Eco,227,4,1,5,1,4,4,4,2,3,3,3,4,4,4,140,122.0,neutral or dissatisfied +3522,95766,Male,Loyal Customer,15,Personal Travel,Eco,419,2,3,2,3,3,2,3,3,3,4,2,3,2,3,0,0.0,neutral or dissatisfied +3523,108675,Male,disloyal Customer,23,Business travel,Business,577,5,0,5,1,4,5,4,4,4,2,5,5,4,4,80,72.0,satisfied +3524,27974,Female,Loyal Customer,51,Business travel,Business,2378,1,1,1,1,4,5,5,5,2,4,2,5,1,5,11,20.0,satisfied +3525,5196,Female,Loyal Customer,49,Business travel,Business,2788,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +3526,83114,Female,Loyal Customer,62,Personal Travel,Eco,1084,1,4,1,1,4,5,5,1,1,1,1,5,1,4,10,15.0,neutral or dissatisfied +3527,21592,Male,Loyal Customer,46,Business travel,Eco,780,4,2,2,2,4,4,4,4,4,2,1,4,2,4,79,77.0,satisfied +3528,85575,Female,Loyal Customer,30,Business travel,Business,2927,2,3,3,3,2,2,2,2,4,5,1,4,2,2,2,8.0,neutral or dissatisfied +3529,100229,Male,Loyal Customer,61,Business travel,Business,971,2,2,2,2,3,3,3,2,2,2,2,4,2,3,103,88.0,neutral or dissatisfied +3530,89078,Female,Loyal Customer,39,Business travel,Business,2139,3,3,3,3,3,5,5,4,4,4,4,4,4,3,44,46.0,satisfied +3531,99392,Male,Loyal Customer,52,Business travel,Business,2770,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +3532,100664,Male,Loyal Customer,39,Business travel,Business,677,5,5,5,5,3,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +3533,115892,Female,Loyal Customer,49,Business travel,Business,446,5,5,5,5,2,4,4,4,4,4,4,3,4,5,5,4.0,satisfied +3534,93533,Female,Loyal Customer,57,Personal Travel,Eco,1315,3,5,3,3,3,5,5,2,2,3,4,4,2,5,10,3.0,neutral or dissatisfied +3535,59937,Female,Loyal Customer,51,Business travel,Business,1065,2,2,2,2,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +3536,37961,Male,Loyal Customer,63,Business travel,Business,1531,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +3537,31045,Female,Loyal Customer,29,Business travel,Business,641,2,3,3,3,2,2,2,2,4,2,3,3,4,2,0,2.0,neutral or dissatisfied +3538,34766,Female,disloyal Customer,21,Business travel,Eco,264,3,0,3,1,5,3,3,5,2,5,2,3,5,5,0,0.0,neutral or dissatisfied +3539,9725,Female,Loyal Customer,45,Business travel,Business,3512,5,5,5,5,5,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +3540,97033,Male,Loyal Customer,45,Business travel,Business,1497,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,2.0,satisfied +3541,95715,Female,Loyal Customer,37,Business travel,Business,3376,4,4,4,4,3,4,5,4,4,4,4,3,4,4,115,103.0,satisfied +3542,82360,Male,Loyal Customer,64,Personal Travel,Eco,453,3,3,3,4,1,3,1,1,1,2,3,4,3,1,0,0.0,neutral or dissatisfied +3543,57529,Male,disloyal Customer,24,Business travel,Eco,413,4,0,3,5,2,3,2,2,4,5,4,5,4,2,3,2.0,satisfied +3544,17715,Female,Loyal Customer,45,Personal Travel,Business,456,4,4,4,4,5,3,3,1,1,4,3,2,1,2,0,0.0,neutral or dissatisfied +3545,15827,Female,Loyal Customer,52,Business travel,Business,195,2,3,4,3,4,3,3,4,4,4,2,1,4,3,0,0.0,neutral or dissatisfied +3546,104560,Male,Loyal Customer,62,Business travel,Business,369,2,2,2,2,2,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +3547,128248,Male,Loyal Customer,51,Business travel,Business,338,4,4,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +3548,6247,Male,Loyal Customer,10,Personal Travel,Eco,413,1,4,1,3,4,1,4,4,2,2,3,5,3,4,50,42.0,neutral or dissatisfied +3549,19116,Female,Loyal Customer,42,Business travel,Business,265,5,5,5,5,1,5,1,5,5,5,5,4,5,2,0,0.0,satisfied +3550,57731,Male,Loyal Customer,42,Business travel,Business,1754,4,4,4,4,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +3551,49989,Male,Loyal Customer,47,Business travel,Eco,77,2,2,2,2,3,2,3,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +3552,26101,Female,Loyal Customer,53,Personal Travel,Eco,591,3,5,2,3,2,5,5,5,5,2,5,4,5,5,10,0.0,neutral or dissatisfied +3553,6977,Male,Loyal Customer,33,Business travel,Business,3845,1,3,3,3,1,1,1,1,1,5,3,1,4,1,0,0.0,neutral or dissatisfied +3554,104362,Male,disloyal Customer,20,Business travel,Eco,228,4,0,4,3,2,4,1,2,3,3,5,4,5,2,14,2.0,neutral or dissatisfied +3555,14538,Female,Loyal Customer,61,Business travel,Eco,310,4,5,4,4,4,4,4,4,4,4,4,2,4,2,37,21.0,neutral or dissatisfied +3556,102194,Male,Loyal Customer,44,Business travel,Eco,258,1,4,4,4,1,1,1,1,2,5,4,3,4,1,0,0.0,neutral or dissatisfied +3557,52222,Female,Loyal Customer,44,Business travel,Eco,598,4,5,5,5,2,4,1,5,5,4,5,3,5,5,17,,satisfied +3558,15281,Male,Loyal Customer,49,Personal Travel,Eco,500,2,3,2,5,2,2,2,2,3,2,4,4,2,2,0,0.0,neutral or dissatisfied +3559,9717,Male,Loyal Customer,38,Personal Travel,Eco,212,3,5,3,3,2,3,2,2,4,1,5,2,5,2,4,2.0,neutral or dissatisfied +3560,62583,Male,Loyal Customer,36,Business travel,Business,1846,4,4,4,4,4,3,5,3,3,3,3,5,3,4,20,5.0,satisfied +3561,89454,Male,Loyal Customer,56,Personal Travel,Eco,134,3,5,3,4,3,3,4,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +3562,9626,Male,Loyal Customer,17,Business travel,Eco Plus,228,0,5,0,3,5,0,5,5,5,1,1,5,1,5,0,0.0,satisfied +3563,29416,Male,Loyal Customer,31,Business travel,Eco Plus,2676,5,5,5,5,5,5,5,4,4,4,2,5,4,5,0,24.0,satisfied +3564,47326,Female,Loyal Customer,35,Business travel,Eco,590,4,1,1,1,4,4,4,4,3,2,2,5,4,4,33,15.0,satisfied +3565,96627,Female,Loyal Customer,47,Business travel,Business,1691,1,1,1,1,2,4,4,1,1,1,1,4,1,3,25,19.0,neutral or dissatisfied +3566,2844,Male,Loyal Customer,59,Business travel,Business,491,1,1,1,1,4,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +3567,90991,Male,Loyal Customer,40,Business travel,Business,406,3,3,3,3,5,4,4,3,3,3,3,4,3,4,0,25.0,neutral or dissatisfied +3568,35130,Male,Loyal Customer,38,Business travel,Eco,1069,4,5,2,2,4,5,4,4,5,3,4,1,3,4,29,44.0,satisfied +3569,60304,Male,disloyal Customer,40,Business travel,Eco,406,4,2,4,3,4,4,4,4,1,5,3,4,2,4,1,5.0,neutral or dissatisfied +3570,85676,Male,Loyal Customer,14,Personal Travel,Eco,903,3,5,3,3,3,3,3,3,5,4,4,5,5,3,0,21.0,neutral or dissatisfied +3571,6381,Female,disloyal Customer,25,Business travel,Eco,240,3,2,3,2,2,3,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +3572,50104,Male,Loyal Customer,36,Business travel,Business,77,4,4,4,4,3,5,4,4,4,5,3,1,4,4,0,0.0,satisfied +3573,12304,Female,disloyal Customer,20,Business travel,Eco,192,2,0,2,4,3,2,3,3,1,3,1,3,5,3,27,21.0,neutral or dissatisfied +3574,40269,Male,Loyal Customer,50,Personal Travel,Eco,387,3,1,3,2,3,3,3,3,2,2,2,2,1,3,0,12.0,neutral or dissatisfied +3575,80436,Male,Loyal Customer,11,Personal Travel,Eco,2248,3,5,3,1,2,3,2,2,4,3,5,3,5,2,31,25.0,neutral or dissatisfied +3576,10624,Female,Loyal Customer,53,Business travel,Business,229,2,1,3,1,4,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +3577,17447,Male,Loyal Customer,45,Business travel,Eco Plus,376,4,2,2,2,4,4,4,4,3,4,2,5,4,4,0,4.0,satisfied +3578,17212,Female,Loyal Customer,31,Business travel,Business,3451,3,3,3,3,5,5,5,5,3,5,1,2,1,5,0,0.0,satisfied +3579,53606,Male,Loyal Customer,25,Business travel,Business,1874,5,5,5,5,5,5,5,5,4,3,5,2,2,5,14,43.0,satisfied +3580,32838,Female,Loyal Customer,66,Personal Travel,Eco,216,0,0,0,3,2,5,5,5,5,0,5,5,5,3,17,15.0,satisfied +3581,4861,Male,Loyal Customer,36,Personal Travel,Eco,408,3,4,5,1,4,5,4,4,5,4,4,5,4,4,0,6.0,neutral or dissatisfied +3582,21079,Female,Loyal Customer,33,Business travel,Eco,227,4,5,5,5,4,4,4,4,3,2,4,3,2,4,0,0.0,satisfied +3583,123045,Male,Loyal Customer,41,Business travel,Business,3494,3,3,3,3,2,5,5,5,5,5,5,5,5,3,86,94.0,satisfied +3584,39443,Male,disloyal Customer,41,Business travel,Eco,129,5,5,5,5,1,5,1,1,5,4,4,5,2,1,0,0.0,satisfied +3585,11207,Female,Loyal Customer,24,Personal Travel,Eco,247,2,4,2,4,3,2,3,3,4,5,4,4,5,3,5,52.0,neutral or dissatisfied +3586,89117,Female,disloyal Customer,49,Business travel,Eco,711,1,1,1,3,4,1,4,4,3,1,4,4,4,4,0,2.0,neutral or dissatisfied +3587,94030,Male,Loyal Customer,52,Business travel,Business,189,4,4,4,4,5,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +3588,28370,Female,Loyal Customer,34,Business travel,Business,763,3,3,3,3,3,5,2,5,5,5,5,2,5,1,0,0.0,satisfied +3589,56215,Female,Loyal Customer,45,Business travel,Business,1585,5,5,5,5,3,5,5,2,2,2,2,4,2,5,26,9.0,satisfied +3590,3153,Male,Loyal Customer,57,Personal Travel,Eco,140,1,3,1,3,5,1,5,5,3,5,3,2,5,5,0,0.0,neutral or dissatisfied +3591,82086,Male,Loyal Customer,42,Business travel,Business,1276,1,1,5,1,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +3592,21381,Female,Loyal Customer,12,Personal Travel,Eco,554,4,4,4,4,5,4,5,5,4,4,5,5,5,5,0,0.0,satisfied +3593,40424,Female,Loyal Customer,45,Business travel,Eco,461,5,3,3,3,2,2,3,5,5,5,5,5,5,4,0,6.0,satisfied +3594,23301,Female,Loyal Customer,39,Business travel,Business,1548,3,3,3,3,3,5,2,5,5,5,5,2,5,3,9,0.0,satisfied +3595,59368,Female,disloyal Customer,35,Business travel,Business,2556,2,2,2,1,1,2,1,1,5,3,3,3,4,1,0,0.0,neutral or dissatisfied +3596,74387,Male,Loyal Customer,25,Business travel,Business,3243,3,3,3,3,5,5,5,5,4,2,4,4,5,5,0,0.0,satisfied +3597,24057,Male,Loyal Customer,31,Personal Travel,Eco,595,2,5,2,1,4,2,4,4,1,1,2,2,5,4,0,0.0,neutral or dissatisfied +3598,81207,Male,Loyal Customer,50,Business travel,Business,1426,4,2,4,4,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +3599,109443,Male,Loyal Customer,50,Business travel,Business,1656,2,2,4,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +3600,90796,Female,disloyal Customer,38,Business travel,Business,270,5,5,5,3,2,5,2,2,5,3,4,3,5,2,0,0.0,satisfied +3601,103176,Male,Loyal Customer,45,Personal Travel,Eco,272,3,3,3,4,3,3,3,3,3,5,4,2,4,3,32,27.0,neutral or dissatisfied +3602,85881,Male,Loyal Customer,48,Business travel,Business,2172,1,4,3,4,5,1,1,1,1,2,1,1,1,4,3,20.0,neutral or dissatisfied +3603,6799,Male,Loyal Customer,28,Business travel,Business,235,4,4,4,4,4,4,4,4,3,3,4,3,4,4,6,3.0,satisfied +3604,75892,Female,Loyal Customer,55,Business travel,Business,603,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +3605,87094,Male,disloyal Customer,25,Business travel,Eco,640,2,4,2,4,2,2,2,2,2,3,4,1,4,2,106,107.0,neutral or dissatisfied +3606,68040,Female,Loyal Customer,47,Business travel,Business,3173,1,1,1,1,2,5,4,4,4,4,4,5,4,3,87,111.0,satisfied +3607,114578,Male,Loyal Customer,51,Business travel,Business,296,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +3608,75618,Female,Loyal Customer,52,Personal Travel,Eco,337,3,4,3,1,2,4,4,2,2,3,2,2,2,5,0,7.0,neutral or dissatisfied +3609,70147,Male,Loyal Customer,56,Personal Travel,Eco,550,3,5,3,2,5,3,5,5,2,1,4,1,1,5,0,0.0,neutral or dissatisfied +3610,56214,Female,Loyal Customer,53,Business travel,Business,1608,2,2,2,2,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +3611,51500,Male,Loyal Customer,19,Personal Travel,Business,237,2,5,2,1,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +3612,104174,Male,Loyal Customer,31,Business travel,Business,349,1,5,5,5,1,1,1,1,2,5,4,2,3,1,37,23.0,neutral or dissatisfied +3613,57652,Female,disloyal Customer,37,Business travel,Eco,200,2,2,2,3,4,2,4,4,4,4,3,3,4,4,77,75.0,neutral or dissatisfied +3614,66097,Female,Loyal Customer,80,Business travel,Eco Plus,655,4,3,3,3,1,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +3615,73301,Female,Loyal Customer,46,Business travel,Business,3586,4,4,4,4,3,4,5,4,4,4,4,5,4,5,5,10.0,satisfied +3616,50765,Female,Loyal Customer,11,Personal Travel,Eco,373,2,4,2,3,4,2,4,4,4,1,3,4,4,4,8,3.0,neutral or dissatisfied +3617,103000,Female,Loyal Customer,40,Business travel,Business,3742,2,2,2,2,4,5,4,3,3,3,3,3,3,3,43,33.0,satisfied +3618,96192,Male,Loyal Customer,51,Business travel,Business,2097,4,4,4,4,3,4,4,5,5,5,5,4,5,4,0,4.0,satisfied +3619,16005,Female,Loyal Customer,29,Business travel,Business,3014,1,3,3,3,1,1,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +3620,89232,Male,Loyal Customer,44,Business travel,Business,2139,1,1,1,1,4,3,5,4,4,5,4,5,4,4,57,52.0,satisfied +3621,57603,Male,disloyal Customer,52,Business travel,Business,563,1,1,1,3,2,1,2,2,3,4,4,5,4,2,0,0.0,neutral or dissatisfied +3622,47606,Female,Loyal Customer,48,Business travel,Eco,1211,5,4,3,4,3,1,3,5,5,5,5,2,5,4,4,0.0,satisfied +3623,129167,Male,Loyal Customer,38,Personal Travel,Eco,679,3,4,3,3,4,3,1,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +3624,50373,Female,disloyal Customer,38,Business travel,Eco,209,1,0,1,4,4,1,4,4,3,3,2,4,1,4,13,33.0,neutral or dissatisfied +3625,75051,Female,disloyal Customer,26,Business travel,Eco,1457,2,2,2,3,3,2,3,3,2,5,3,1,3,3,0,20.0,neutral or dissatisfied +3626,121659,Female,Loyal Customer,59,Business travel,Business,328,3,3,3,3,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +3627,114020,Female,Loyal Customer,33,Personal Travel,Eco,1844,0,5,0,4,2,0,2,2,3,5,4,4,5,2,1,4.0,satisfied +3628,5388,Male,Loyal Customer,33,Personal Travel,Eco,785,3,3,3,3,5,3,5,5,3,2,3,4,4,5,1,10.0,neutral or dissatisfied +3629,116891,Female,Loyal Customer,58,Business travel,Business,2512,3,3,3,3,2,4,4,3,3,3,3,5,3,3,2,0.0,satisfied +3630,22206,Male,Loyal Customer,12,Personal Travel,Eco,633,3,4,3,4,3,1,1,5,2,4,4,1,4,1,142,133.0,neutral or dissatisfied +3631,119126,Female,disloyal Customer,20,Business travel,Eco Plus,1020,3,3,3,4,1,3,1,1,2,2,3,3,5,1,0,0.0,neutral or dissatisfied +3632,75058,Female,Loyal Customer,47,Business travel,Business,1592,1,1,1,1,2,3,5,5,5,5,5,4,5,5,0,0.0,satisfied +3633,122265,Female,Loyal Customer,67,Personal Travel,Eco,544,3,3,3,3,1,5,5,1,1,3,1,3,1,3,86,68.0,neutral or dissatisfied +3634,80450,Male,disloyal Customer,26,Business travel,Business,1299,4,4,4,4,5,4,2,5,3,1,4,2,4,5,0,0.0,neutral or dissatisfied +3635,2417,Male,Loyal Customer,38,Personal Travel,Eco,641,2,3,2,3,1,2,1,1,3,4,2,4,2,1,0,0.0,neutral or dissatisfied +3636,93938,Female,Loyal Customer,40,Business travel,Business,1932,2,2,4,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +3637,80616,Female,disloyal Customer,24,Business travel,Eco,236,5,4,5,4,2,5,2,2,5,3,4,4,4,2,0,0.0,satisfied +3638,27547,Male,Loyal Customer,52,Personal Travel,Eco,978,3,4,3,4,3,3,3,3,5,4,5,4,4,3,20,12.0,neutral or dissatisfied +3639,118585,Male,Loyal Customer,58,Business travel,Business,651,4,3,4,4,4,5,5,5,5,4,5,5,5,4,83,94.0,satisfied +3640,70918,Female,disloyal Customer,22,Business travel,Eco,612,2,5,2,1,5,2,5,5,3,5,5,4,4,5,14,15.0,neutral or dissatisfied +3641,54926,Male,Loyal Customer,28,Business travel,Eco Plus,794,2,5,5,5,2,2,2,2,5,4,3,2,1,2,151,147.0,neutral or dissatisfied +3642,10397,Male,disloyal Customer,23,Business travel,Eco,166,5,0,5,2,5,5,4,5,3,2,4,4,5,5,0,0.0,satisfied +3643,30665,Female,Loyal Customer,38,Business travel,Eco Plus,533,5,5,5,5,5,5,5,5,2,1,1,2,2,5,0,0.0,satisfied +3644,66808,Female,Loyal Customer,50,Business travel,Business,2446,5,2,5,5,3,5,4,5,5,5,5,5,5,4,0,1.0,satisfied +3645,59263,Male,Loyal Customer,44,Business travel,Business,4963,5,5,5,5,4,4,4,3,3,4,4,4,5,4,0,0.0,satisfied +3646,76046,Male,Loyal Customer,50,Business travel,Business,669,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +3647,106211,Male,Loyal Customer,39,Business travel,Business,471,1,1,1,1,4,5,5,3,3,3,3,4,3,3,25,15.0,satisfied +3648,69626,Female,Loyal Customer,50,Personal Travel,Eco Plus,2446,2,5,2,2,2,3,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +3649,9480,Male,Loyal Customer,54,Business travel,Business,224,3,3,3,3,5,4,4,5,5,5,5,4,5,5,16,15.0,satisfied +3650,14026,Female,disloyal Customer,45,Business travel,Eco,1117,2,2,2,3,5,2,5,5,1,1,3,4,1,5,73,98.0,neutral or dissatisfied +3651,93197,Female,Loyal Customer,27,Business travel,Business,3433,4,4,4,4,4,4,4,4,1,1,1,2,2,4,40,49.0,neutral or dissatisfied +3652,40836,Female,Loyal Customer,22,Business travel,Business,1538,2,4,2,2,3,3,3,3,1,1,3,1,1,3,0,0.0,satisfied +3653,56024,Female,Loyal Customer,36,Business travel,Business,2586,3,1,1,1,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +3654,13669,Male,Loyal Customer,36,Business travel,Business,3446,4,4,4,4,2,4,3,4,4,4,4,3,4,4,46,46.0,satisfied +3655,52375,Female,Loyal Customer,59,Personal Travel,Eco,598,2,0,2,2,3,4,4,2,2,2,4,4,2,3,0,0.0,neutral or dissatisfied +3656,20419,Male,disloyal Customer,49,Business travel,Eco,299,3,4,3,4,3,3,2,3,1,2,3,4,3,3,9,0.0,neutral or dissatisfied +3657,81650,Male,Loyal Customer,37,Business travel,Business,907,2,2,2,2,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +3658,56290,Male,Loyal Customer,26,Business travel,Business,2227,2,5,5,5,2,2,2,2,1,5,1,4,2,2,17,15.0,neutral or dissatisfied +3659,55101,Male,disloyal Customer,23,Business travel,Eco,979,2,2,2,3,4,2,4,4,4,3,4,4,3,4,6,9.0,neutral or dissatisfied +3660,32990,Male,Loyal Customer,56,Personal Travel,Eco,101,2,1,0,4,3,0,1,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +3661,55478,Female,Loyal Customer,35,Business travel,Eco Plus,1825,1,5,5,5,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +3662,13218,Male,Loyal Customer,34,Business travel,Business,3836,3,2,5,5,3,3,3,2,1,4,4,3,3,3,188,184.0,neutral or dissatisfied +3663,33758,Male,Loyal Customer,71,Business travel,Business,1816,4,4,4,4,2,4,4,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +3664,121073,Female,disloyal Customer,30,Business travel,Eco Plus,861,3,3,3,3,5,3,5,5,1,3,3,3,3,5,54,70.0,neutral or dissatisfied +3665,44667,Male,Loyal Customer,48,Business travel,Business,2397,0,4,0,4,4,3,3,3,3,3,3,5,3,2,7,4.0,satisfied +3666,108520,Male,Loyal Customer,20,Personal Travel,Eco,519,2,4,4,1,3,4,3,3,3,5,4,3,5,3,3,0.0,neutral or dissatisfied +3667,111355,Female,Loyal Customer,28,Personal Travel,Eco,777,3,5,3,4,2,3,1,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +3668,75431,Male,Loyal Customer,50,Business travel,Business,2342,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +3669,25581,Female,Loyal Customer,23,Business travel,Eco,874,2,2,2,2,2,2,3,2,4,2,4,2,4,2,0,5.0,neutral or dissatisfied +3670,102366,Male,Loyal Customer,37,Business travel,Business,407,1,1,1,1,1,2,2,1,1,1,1,2,1,3,60,58.0,neutral or dissatisfied +3671,126888,Male,Loyal Customer,56,Personal Travel,Eco,2125,3,1,3,2,3,3,3,3,1,5,2,3,2,3,0,2.0,neutral or dissatisfied +3672,54829,Male,Loyal Customer,33,Business travel,Business,1684,2,1,2,2,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +3673,9944,Female,Loyal Customer,36,Business travel,Business,3892,4,1,1,1,2,3,3,4,4,4,4,2,4,2,38,38.0,neutral or dissatisfied +3674,29243,Male,disloyal Customer,21,Business travel,Eco,569,0,4,0,4,2,0,2,2,5,4,2,3,4,2,1,11.0,satisfied +3675,12594,Female,disloyal Customer,12,Business travel,Eco,542,3,1,3,3,1,3,1,1,3,4,3,2,3,1,25,7.0,neutral or dissatisfied +3676,121711,Female,Loyal Customer,62,Personal Travel,Eco,683,4,5,5,1,5,5,4,2,2,5,2,5,2,4,0,0.0,neutral or dissatisfied +3677,74598,Female,Loyal Customer,35,Business travel,Business,2005,2,2,2,2,5,3,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +3678,128606,Male,Loyal Customer,57,Business travel,Business,3456,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,6.0,satisfied +3679,52130,Female,Loyal Customer,60,Business travel,Business,370,5,5,3,5,4,5,5,4,4,4,4,5,4,3,16,21.0,satisfied +3680,33630,Female,Loyal Customer,11,Personal Travel,Eco,399,5,5,5,3,4,5,4,4,4,5,5,4,1,4,0,0.0,satisfied +3681,55612,Male,Loyal Customer,39,Personal Travel,Eco,404,2,3,2,5,2,2,2,2,5,2,5,1,1,2,39,16.0,neutral or dissatisfied +3682,25583,Male,Loyal Customer,56,Business travel,Business,696,3,5,5,5,5,4,4,3,3,3,3,3,3,2,0,5.0,neutral or dissatisfied +3683,3370,Female,Loyal Customer,35,Business travel,Eco,315,2,5,5,5,2,2,2,2,2,3,1,4,2,2,0,8.0,neutral or dissatisfied +3684,124428,Female,Loyal Customer,13,Personal Travel,Eco,1262,2,2,2,4,5,2,4,5,4,3,2,3,4,5,0,26.0,neutral or dissatisfied +3685,63849,Female,Loyal Customer,37,Business travel,Business,2013,2,5,5,5,1,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +3686,25907,Female,Loyal Customer,63,Personal Travel,Eco Plus,907,3,1,3,2,5,3,2,5,5,3,3,2,5,4,0,0.0,neutral or dissatisfied +3687,61711,Male,Loyal Customer,39,Business travel,Business,1346,3,3,3,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +3688,39742,Female,Loyal Customer,37,Personal Travel,Eco,162,2,4,2,4,4,2,5,4,3,3,4,5,5,4,22,49.0,neutral or dissatisfied +3689,9581,Female,Loyal Customer,65,Business travel,Business,3259,2,2,2,2,1,2,2,2,2,2,2,2,2,1,88,119.0,neutral or dissatisfied +3690,111818,Female,Loyal Customer,52,Business travel,Eco Plus,349,2,1,1,1,4,4,3,2,2,2,2,3,2,2,2,0.0,neutral or dissatisfied +3691,97311,Male,disloyal Customer,32,Business travel,Business,872,4,4,4,1,4,4,5,4,4,4,5,5,4,4,7,10.0,neutral or dissatisfied +3692,47713,Female,Loyal Customer,48,Personal Travel,Eco Plus,1428,1,5,1,2,4,5,5,2,2,1,4,5,2,4,0,0.0,neutral or dissatisfied +3693,77540,Female,Loyal Customer,52,Business travel,Business,2442,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +3694,101086,Female,Loyal Customer,49,Business travel,Business,1797,2,2,2,2,3,4,4,3,3,4,3,5,3,4,6,0.0,satisfied +3695,4553,Male,Loyal Customer,56,Business travel,Business,3451,1,1,1,1,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +3696,31953,Female,disloyal Customer,23,Business travel,Eco,163,1,0,1,2,4,1,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +3697,128854,Male,Loyal Customer,49,Personal Travel,Eco,2475,2,4,2,1,2,2,2,4,2,5,5,2,3,2,0,0.0,neutral or dissatisfied +3698,99908,Male,Loyal Customer,41,Business travel,Business,1428,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,12.0,satisfied +3699,129341,Female,Loyal Customer,13,Personal Travel,Eco,2586,0,1,0,2,4,0,4,4,4,4,1,3,1,4,5,0.0,satisfied +3700,28745,Male,Loyal Customer,30,Business travel,Eco,1024,5,3,3,3,5,5,5,5,4,5,5,4,4,5,0,0.0,satisfied +3701,38334,Male,Loyal Customer,24,Business travel,Business,2716,2,2,2,2,5,5,5,5,5,2,1,3,4,5,25,40.0,satisfied +3702,23128,Female,Loyal Customer,53,Business travel,Business,223,5,5,5,5,5,5,5,4,4,4,3,4,4,2,0,0.0,satisfied +3703,121663,Female,Loyal Customer,59,Business travel,Eco,328,3,3,5,3,2,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +3704,55432,Female,disloyal Customer,42,Business travel,Eco,938,2,3,3,4,1,2,2,1,4,5,3,3,4,1,0,2.0,neutral or dissatisfied +3705,122668,Male,Loyal Customer,37,Business travel,Business,3867,1,1,1,1,2,4,4,5,5,5,5,4,5,4,7,6.0,satisfied +3706,18215,Female,Loyal Customer,28,Business travel,Business,137,2,1,1,1,2,2,2,2,3,5,3,2,3,2,0,10.0,neutral or dissatisfied +3707,120606,Female,disloyal Customer,24,Business travel,Business,453,4,0,4,4,4,4,4,4,5,4,4,4,5,4,0,4.0,satisfied +3708,69,Male,Loyal Customer,52,Business travel,Business,212,3,1,3,1,4,3,3,1,1,1,3,4,1,4,0,67.0,neutral or dissatisfied +3709,73690,Female,Loyal Customer,38,Business travel,Business,192,2,5,5,5,2,3,4,2,2,2,2,1,2,4,0,3.0,neutral or dissatisfied +3710,46136,Male,disloyal Customer,23,Business travel,Eco,604,2,2,2,4,4,2,4,4,4,5,4,3,3,4,0,12.0,neutral or dissatisfied +3711,28026,Male,Loyal Customer,48,Personal Travel,Eco,763,3,5,3,3,1,3,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +3712,64813,Male,Loyal Customer,31,Business travel,Eco,247,2,3,3,3,2,2,2,2,4,5,2,3,2,2,14,10.0,neutral or dissatisfied +3713,15406,Female,Loyal Customer,59,Business travel,Business,164,0,5,0,5,4,5,3,5,5,5,5,1,5,1,81,,satisfied +3714,2867,Male,Loyal Customer,37,Business travel,Business,3640,2,5,5,5,3,2,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +3715,95840,Male,disloyal Customer,25,Business travel,Business,580,0,4,0,1,4,4,4,4,3,4,4,4,4,4,9,4.0,satisfied +3716,63234,Male,Loyal Customer,59,Business travel,Business,447,5,5,5,5,3,4,5,2,2,2,2,3,2,3,0,7.0,satisfied +3717,106563,Female,Loyal Customer,46,Business travel,Business,3541,2,2,1,2,2,5,4,4,4,4,4,4,4,3,0,3.0,satisfied +3718,118303,Female,Loyal Customer,26,Business travel,Eco,602,2,4,4,4,2,3,1,2,2,2,2,2,3,2,3,0.0,neutral or dissatisfied +3719,122863,Female,Loyal Customer,47,Business travel,Eco,226,2,3,3,3,1,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +3720,84013,Male,Loyal Customer,58,Personal Travel,Eco,321,4,5,4,5,4,4,3,4,4,2,5,1,2,4,0,0.0,neutral or dissatisfied +3721,98536,Female,Loyal Customer,62,Personal Travel,Eco,668,2,4,1,5,5,4,4,3,3,1,3,3,3,3,2,0.0,neutral or dissatisfied +3722,49498,Male,Loyal Customer,39,Business travel,Eco,89,2,2,2,2,2,2,2,2,4,1,4,2,3,2,6,7.0,satisfied +3723,22949,Female,Loyal Customer,25,Business travel,Eco,528,3,5,2,5,3,4,5,3,2,3,1,4,5,3,2,0.0,satisfied +3724,58782,Female,Loyal Customer,25,Business travel,Eco,1120,1,4,4,4,1,1,4,1,2,1,3,4,3,1,0,0.0,neutral or dissatisfied +3725,44902,Female,Loyal Customer,33,Personal Travel,Eco,536,0,4,0,4,5,0,5,5,4,3,4,3,3,5,2,4.0,satisfied +3726,104573,Male,Loyal Customer,53,Business travel,Business,369,3,3,3,3,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +3727,52994,Female,Loyal Customer,41,Business travel,Business,1208,2,2,2,2,5,1,2,2,2,2,2,5,2,5,0,0.0,satisfied +3728,122160,Male,Loyal Customer,55,Business travel,Business,541,4,4,4,4,4,4,4,4,4,4,4,3,4,4,30,79.0,satisfied +3729,85753,Female,disloyal Customer,43,Business travel,Business,666,5,5,5,3,5,5,5,5,3,5,4,4,5,5,0,4.0,satisfied +3730,49629,Male,Loyal Customer,43,Business travel,Eco,262,2,4,3,4,2,2,2,2,4,2,3,4,2,2,51,61.0,neutral or dissatisfied +3731,119292,Male,disloyal Customer,49,Business travel,Business,214,1,1,1,2,5,1,5,5,3,4,5,3,5,5,0,0.0,neutral or dissatisfied +3732,100701,Female,Loyal Customer,35,Personal Travel,Eco,677,4,2,4,4,5,4,5,5,1,3,4,4,3,5,0,0.0,neutral or dissatisfied +3733,94455,Female,Loyal Customer,43,Business travel,Business,239,1,1,1,1,3,5,4,5,5,5,5,4,5,5,11,10.0,satisfied +3734,34588,Female,disloyal Customer,20,Business travel,Eco,1031,4,4,4,5,5,4,5,5,2,4,1,3,5,5,0,0.0,neutral or dissatisfied +3735,36079,Male,Loyal Customer,8,Personal Travel,Eco,474,2,5,2,3,4,2,4,4,3,5,4,1,2,4,0,0.0,neutral or dissatisfied +3736,69202,Female,Loyal Customer,50,Business travel,Business,733,3,2,2,2,4,3,3,3,3,3,3,2,3,4,76,70.0,neutral or dissatisfied +3737,121760,Female,Loyal Customer,33,Personal Travel,Business,337,3,5,3,4,2,5,5,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +3738,112783,Male,Loyal Customer,57,Personal Travel,Eco,590,3,5,4,2,3,4,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +3739,97115,Male,Loyal Customer,55,Business travel,Business,715,5,5,4,5,4,5,4,5,5,4,5,3,5,4,17,18.0,satisfied +3740,34023,Female,Loyal Customer,55,Personal Travel,Eco,1576,2,4,2,5,5,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +3741,44338,Male,Loyal Customer,29,Personal Travel,Eco,230,4,5,4,3,2,4,2,2,4,4,5,3,5,2,0,0.0,satisfied +3742,79798,Male,Loyal Customer,52,Business travel,Business,1010,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +3743,13573,Male,Loyal Customer,53,Personal Travel,Eco,152,2,4,0,1,5,0,2,5,5,3,4,4,5,5,0,3.0,neutral or dissatisfied +3744,101576,Female,Loyal Customer,58,Business travel,Business,3383,4,4,4,4,5,4,5,5,5,5,5,4,5,3,57,41.0,satisfied +3745,78790,Female,disloyal Customer,24,Business travel,Eco,432,5,0,5,1,2,5,2,2,1,3,5,1,1,2,7,0.0,satisfied +3746,72974,Female,Loyal Customer,41,Business travel,Business,944,3,5,2,5,4,4,4,3,3,3,3,4,3,1,17,10.0,neutral or dissatisfied +3747,12034,Female,Loyal Customer,72,Business travel,Eco,376,4,5,5,5,5,4,3,4,4,4,4,4,4,3,0,16.0,neutral or dissatisfied +3748,15413,Female,Loyal Customer,38,Business travel,Business,399,1,3,3,3,5,4,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +3749,107760,Male,Loyal Customer,59,Personal Travel,Eco,405,3,5,3,3,1,3,1,1,3,5,4,4,1,1,8,7.0,neutral or dissatisfied +3750,6725,Female,Loyal Customer,68,Personal Travel,Eco Plus,403,2,4,2,3,4,5,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +3751,36000,Female,Loyal Customer,46,Business travel,Business,1956,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +3752,71457,Male,Loyal Customer,52,Business travel,Business,2957,4,4,4,4,4,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +3753,119459,Female,Loyal Customer,42,Personal Travel,Business,814,3,1,2,3,5,3,4,2,2,2,4,2,2,2,0,0.0,neutral or dissatisfied +3754,17200,Male,Loyal Customer,44,Business travel,Eco,694,5,5,1,5,5,5,5,5,2,5,1,1,3,5,0,0.0,satisfied +3755,35490,Female,Loyal Customer,40,Personal Travel,Eco,1028,1,2,2,3,4,2,4,4,4,4,2,1,2,4,72,55.0,neutral or dissatisfied +3756,5383,Female,Loyal Customer,43,Personal Travel,Eco,812,3,4,4,4,1,5,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +3757,4969,Female,Loyal Customer,70,Business travel,Eco Plus,931,1,3,3,3,2,3,2,1,1,1,1,3,1,2,17,13.0,neutral or dissatisfied +3758,121487,Male,Loyal Customer,52,Personal Travel,Eco,331,3,4,3,3,3,3,3,3,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +3759,116758,Male,Loyal Customer,7,Personal Travel,Eco Plus,417,3,4,3,3,4,3,4,4,3,5,4,4,4,4,8,6.0,neutral or dissatisfied +3760,13703,Female,Loyal Customer,36,Personal Travel,Eco,483,2,1,2,4,5,2,5,5,3,5,4,1,3,5,0,0.0,neutral or dissatisfied +3761,32498,Female,Loyal Customer,44,Business travel,Business,3211,1,1,1,1,4,3,2,4,4,4,1,1,4,2,0,0.0,neutral or dissatisfied +3762,57796,Female,disloyal Customer,24,Business travel,Business,1235,5,4,5,4,2,4,2,2,4,5,4,4,4,2,0,0.0,satisfied +3763,129194,Male,Loyal Customer,43,Business travel,Business,2288,5,5,5,5,4,5,5,4,4,4,4,5,4,5,21,0.0,satisfied +3764,4616,Female,Loyal Customer,60,Personal Travel,Eco,719,2,3,2,4,5,3,1,2,2,2,2,2,2,5,0,0.0,neutral or dissatisfied +3765,28192,Female,Loyal Customer,26,Personal Travel,Eco,550,2,5,2,4,1,2,1,1,4,2,5,4,4,1,0,0.0,neutral or dissatisfied +3766,109801,Female,Loyal Customer,55,Business travel,Business,1073,5,5,5,5,4,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +3767,72590,Female,Loyal Customer,66,Personal Travel,Eco,985,5,4,5,1,5,4,4,5,2,5,5,4,3,4,131,143.0,satisfied +3768,122579,Male,Loyal Customer,53,Business travel,Business,1679,3,3,3,3,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3769,67022,Male,Loyal Customer,46,Business travel,Business,3471,3,5,5,5,1,4,4,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +3770,11089,Male,Loyal Customer,25,Personal Travel,Eco,201,1,4,1,4,1,1,1,1,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +3771,81123,Male,Loyal Customer,64,Personal Travel,Eco,991,3,2,3,3,2,3,2,2,1,3,4,2,3,2,0,4.0,neutral or dissatisfied +3772,3022,Male,Loyal Customer,49,Personal Travel,Eco,922,5,5,5,2,4,5,3,4,3,2,5,3,5,4,20,13.0,satisfied +3773,88894,Male,Loyal Customer,53,Business travel,Business,859,2,2,2,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +3774,66406,Female,Loyal Customer,49,Business travel,Business,1562,3,4,5,4,4,4,3,3,3,3,3,4,3,3,6,5.0,neutral or dissatisfied +3775,6097,Female,Loyal Customer,11,Personal Travel,Eco Plus,630,3,5,3,5,4,3,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +3776,10438,Female,Loyal Customer,47,Business travel,Business,1717,5,5,5,5,2,4,5,4,4,4,4,3,4,5,10,4.0,satisfied +3777,83550,Male,Loyal Customer,57,Business travel,Business,1865,2,4,4,4,5,2,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +3778,58999,Female,Loyal Customer,40,Business travel,Business,1652,1,1,2,1,3,4,5,4,4,4,4,4,4,4,0,1.0,satisfied +3779,56199,Male,Loyal Customer,63,Personal Travel,Eco,1400,1,4,1,4,5,1,5,5,5,3,3,5,5,5,49,41.0,neutral or dissatisfied +3780,53794,Female,disloyal Customer,22,Business travel,Business,191,4,0,4,3,4,4,4,4,1,5,4,1,5,4,0,0.0,satisfied +3781,128363,Female,disloyal Customer,27,Business travel,Business,304,4,4,4,4,1,4,1,1,3,5,4,5,4,1,58,60.0,satisfied +3782,105801,Female,Loyal Customer,9,Personal Travel,Eco,787,1,4,1,1,4,1,4,4,3,3,5,5,5,4,14,17.0,neutral or dissatisfied +3783,94642,Female,Loyal Customer,19,Business travel,Business,248,1,1,1,1,1,1,1,1,4,3,3,3,3,1,3,12.0,neutral or dissatisfied +3784,47926,Male,Loyal Customer,59,Personal Travel,Eco,451,3,5,3,3,2,3,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +3785,64807,Female,disloyal Customer,23,Business travel,Business,224,5,4,5,3,3,5,3,3,3,5,4,5,4,3,9,21.0,satisfied +3786,128863,Female,Loyal Customer,56,Business travel,Business,2454,1,1,1,1,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +3787,18929,Female,Loyal Customer,9,Personal Travel,Eco,551,4,4,4,2,3,4,3,3,2,5,4,4,5,3,5,18.0,neutral or dissatisfied +3788,103918,Female,Loyal Customer,49,Business travel,Business,3105,5,5,2,5,4,5,4,5,5,5,5,5,5,4,24,24.0,satisfied +3789,2971,Male,disloyal Customer,13,Business travel,Business,737,5,0,5,3,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +3790,59289,Female,Loyal Customer,52,Business travel,Business,2338,4,4,4,4,5,5,5,4,4,4,4,4,4,5,3,0.0,satisfied +3791,86041,Male,Loyal Customer,34,Personal Travel,Eco,432,3,4,3,3,2,3,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +3792,79502,Female,Loyal Customer,48,Business travel,Business,712,2,2,2,2,4,4,5,4,4,4,4,5,4,5,1,10.0,satisfied +3793,21168,Male,Loyal Customer,48,Business travel,Business,2578,2,1,1,1,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +3794,11102,Female,Loyal Customer,8,Personal Travel,Eco,316,3,5,3,1,4,3,3,4,1,2,5,4,1,4,0,0.0,neutral or dissatisfied +3795,72042,Female,Loyal Customer,45,Personal Travel,Eco,4243,1,5,1,1,1,3,3,1,2,3,3,3,2,3,6,0.0,neutral or dissatisfied +3796,127228,Male,Loyal Customer,58,Business travel,Business,1460,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +3797,113128,Female,Loyal Customer,70,Business travel,Eco Plus,479,3,2,2,2,4,3,3,3,3,3,3,4,3,3,16,10.0,neutral or dissatisfied +3798,107967,Female,Loyal Customer,37,Business travel,Business,825,1,1,1,1,3,4,4,3,3,4,3,3,3,3,8,0.0,satisfied +3799,101021,Female,Loyal Customer,51,Personal Travel,Eco,867,3,4,2,3,3,4,5,2,2,2,2,5,2,4,1,7.0,neutral or dissatisfied +3800,20443,Male,disloyal Customer,21,Business travel,Eco,177,4,4,4,3,1,4,1,1,1,4,4,2,2,1,0,0.0,satisfied +3801,96534,Male,Loyal Customer,51,Personal Travel,Eco,302,1,5,1,5,4,1,4,4,5,4,4,4,4,4,36,41.0,neutral or dissatisfied +3802,74469,Female,Loyal Customer,53,Business travel,Business,2772,2,2,2,2,4,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +3803,26573,Female,Loyal Customer,36,Business travel,Eco,581,4,5,5,5,4,4,4,4,1,3,2,5,2,4,52,70.0,satisfied +3804,8911,Male,Loyal Customer,15,Personal Travel,Eco,510,2,4,2,3,2,2,3,2,3,5,4,4,4,2,29,26.0,neutral or dissatisfied +3805,77487,Male,disloyal Customer,23,Business travel,Business,1195,5,0,5,1,4,5,4,4,3,4,4,3,5,4,19,93.0,satisfied +3806,97935,Female,Loyal Customer,49,Business travel,Business,2788,3,5,5,5,5,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +3807,37419,Male,Loyal Customer,45,Business travel,Business,3356,1,1,1,1,1,4,4,5,5,5,5,2,5,1,0,1.0,satisfied +3808,27388,Female,Loyal Customer,28,Business travel,Business,679,2,2,2,2,5,5,5,5,1,3,2,2,4,5,5,0.0,satisfied +3809,69710,Female,Loyal Customer,10,Business travel,Business,1372,4,4,4,4,4,4,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +3810,63366,Female,Loyal Customer,12,Personal Travel,Eco,372,1,0,1,3,5,1,2,5,3,3,5,4,5,5,0,0.0,neutral or dissatisfied +3811,100053,Female,Loyal Customer,27,Personal Travel,Eco,281,2,4,2,2,2,2,2,2,3,4,4,5,4,2,25,19.0,neutral or dissatisfied +3812,44100,Female,Loyal Customer,35,Business travel,Eco,408,3,4,4,4,3,3,3,3,1,5,3,2,2,3,47,52.0,neutral or dissatisfied +3813,5322,Female,Loyal Customer,68,Personal Travel,Eco Plus,383,2,5,2,3,5,4,3,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +3814,58911,Female,Loyal Customer,45,Personal Travel,Eco,888,3,3,3,2,5,2,2,4,4,3,2,2,4,2,0,0.0,neutral or dissatisfied +3815,48616,Female,Loyal Customer,25,Business travel,Eco Plus,850,4,1,2,1,4,4,5,4,3,3,1,4,2,4,0,0.0,satisfied +3816,76407,Male,Loyal Customer,21,Personal Travel,Business,405,2,5,2,3,1,2,3,1,2,4,3,1,3,1,0,0.0,neutral or dissatisfied +3817,53398,Male,Loyal Customer,54,Business travel,Business,2288,4,4,4,4,2,4,4,3,3,4,3,4,3,3,121,94.0,satisfied +3818,101601,Female,Loyal Customer,55,Business travel,Business,1139,3,1,3,3,4,4,5,5,5,5,5,3,5,4,15,3.0,satisfied +3819,110635,Female,Loyal Customer,61,Business travel,Eco Plus,327,4,3,1,3,1,4,3,4,4,4,4,3,4,1,3,0.0,satisfied +3820,122425,Male,disloyal Customer,25,Business travel,Eco,961,2,2,2,3,2,2,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +3821,58088,Female,disloyal Customer,28,Business travel,Business,589,4,4,4,3,3,4,3,3,4,5,4,3,5,3,10,0.0,satisfied +3822,36562,Female,disloyal Customer,35,Business travel,Eco,1010,3,3,3,2,5,3,5,5,4,3,2,5,4,5,0,17.0,neutral or dissatisfied +3823,49101,Female,Loyal Customer,45,Business travel,Eco,373,4,3,5,3,4,2,5,4,4,4,4,2,4,4,36,21.0,satisfied +3824,83667,Male,Loyal Customer,27,Business travel,Business,2718,3,2,2,2,3,3,3,3,3,2,3,2,3,3,69,77.0,neutral or dissatisfied +3825,89547,Male,disloyal Customer,27,Business travel,Business,1005,2,2,2,4,1,2,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +3826,12692,Male,Loyal Customer,56,Business travel,Eco,689,5,2,2,2,5,5,5,5,5,3,2,5,4,5,0,18.0,satisfied +3827,88415,Male,Loyal Customer,49,Business travel,Eco,581,2,2,2,2,2,2,2,2,4,3,3,1,2,2,0,0.0,neutral or dissatisfied +3828,101050,Female,Loyal Customer,57,Business travel,Business,2001,3,3,4,3,4,4,5,4,4,4,4,3,4,5,9,0.0,satisfied +3829,75389,Female,Loyal Customer,48,Business travel,Business,2585,1,1,3,1,5,5,5,2,2,2,2,3,2,4,0,0.0,satisfied +3830,95745,Male,disloyal Customer,16,Business travel,Eco,181,2,3,2,4,5,2,5,5,3,5,4,1,4,5,9,2.0,neutral or dissatisfied +3831,115220,Female,Loyal Customer,48,Business travel,Business,296,1,1,3,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +3832,109036,Female,Loyal Customer,61,Business travel,Business,2642,3,1,1,1,1,3,3,3,3,3,3,2,3,1,9,0.0,neutral or dissatisfied +3833,128475,Female,Loyal Customer,10,Personal Travel,Eco,647,2,2,2,3,2,2,2,2,4,5,3,2,3,2,10,2.0,neutral or dissatisfied +3834,71709,Female,Loyal Customer,50,Personal Travel,Eco Plus,1197,2,4,2,5,3,5,4,3,3,2,3,3,3,3,3,0.0,neutral or dissatisfied +3835,34593,Female,Loyal Customer,52,Business travel,Eco,1598,2,5,5,5,2,3,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +3836,105613,Male,disloyal Customer,36,Business travel,Business,787,2,2,2,5,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +3837,2839,Male,Loyal Customer,40,Business travel,Business,409,1,1,1,1,2,2,3,1,1,1,1,2,1,4,0,2.0,neutral or dissatisfied +3838,111080,Female,Loyal Customer,57,Personal Travel,Eco,197,3,4,3,3,5,5,5,5,5,3,5,4,5,4,26,15.0,neutral or dissatisfied +3839,19516,Female,Loyal Customer,22,Business travel,Eco Plus,566,3,3,3,3,3,3,2,3,4,3,4,3,3,3,5,3.0,neutral or dissatisfied +3840,37766,Female,Loyal Customer,47,Business travel,Eco Plus,1076,5,1,1,1,2,1,2,5,5,5,5,5,5,4,50,66.0,satisfied +3841,245,Female,Loyal Customer,29,Business travel,Business,2903,3,2,2,2,3,3,3,3,3,5,3,4,3,3,17,25.0,neutral or dissatisfied +3842,125467,Male,disloyal Customer,25,Business travel,Eco,1417,2,1,1,1,2,2,2,2,3,3,2,5,1,2,0,0.0,neutral or dissatisfied +3843,84967,Male,Loyal Customer,10,Personal Travel,Eco Plus,547,3,3,3,4,2,3,5,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +3844,44234,Male,Loyal Customer,54,Business travel,Business,2616,1,1,5,1,2,1,5,5,5,5,3,4,5,4,0,6.0,satisfied +3845,8756,Male,Loyal Customer,23,Business travel,Business,1698,3,4,4,4,3,3,3,3,2,1,4,4,3,3,25,23.0,neutral or dissatisfied +3846,124363,Male,Loyal Customer,56,Business travel,Business,2803,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +3847,14670,Female,disloyal Customer,24,Business travel,Eco,430,2,0,2,3,5,2,5,5,4,3,5,3,4,5,0,0.0,neutral or dissatisfied +3848,110229,Female,Loyal Customer,33,Business travel,Business,2300,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,6.0,satisfied +3849,43037,Male,Loyal Customer,42,Business travel,Business,391,2,1,1,1,1,2,3,2,2,2,2,2,2,4,10,0.0,neutral or dissatisfied +3850,13681,Male,Loyal Customer,52,Business travel,Business,954,3,3,3,3,5,4,2,4,4,4,4,5,4,3,9,13.0,satisfied +3851,23227,Female,Loyal Customer,53,Business travel,Business,116,0,3,0,4,1,3,4,2,2,2,2,3,2,5,2,0.0,satisfied +3852,118055,Male,Loyal Customer,33,Business travel,Business,1262,3,5,5,5,3,3,3,3,2,4,4,1,3,3,58,41.0,neutral or dissatisfied +3853,54405,Female,Loyal Customer,39,Business travel,Business,305,1,3,3,3,3,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +3854,62038,Male,disloyal Customer,11,Business travel,Eco,1117,3,3,3,4,3,3,5,3,4,1,4,2,4,3,11,18.0,neutral or dissatisfied +3855,2696,Male,Loyal Customer,40,Business travel,Business,562,4,4,4,4,5,4,5,5,5,5,5,5,5,5,10,0.0,satisfied +3856,60951,Female,disloyal Customer,26,Business travel,Eco,888,1,2,2,4,1,2,2,1,1,2,3,3,3,1,24,6.0,neutral or dissatisfied +3857,2267,Male,Loyal Customer,59,Business travel,Business,925,5,5,5,5,5,5,4,3,3,4,3,4,3,5,67,57.0,satisfied +3858,56883,Male,Loyal Customer,53,Business travel,Business,2454,4,4,2,4,5,4,5,5,5,5,5,3,5,3,1,0.0,satisfied +3859,40447,Male,Loyal Customer,44,Business travel,Business,222,2,2,3,2,5,4,5,4,4,4,5,5,4,1,0,0.0,satisfied +3860,91718,Female,Loyal Customer,38,Business travel,Business,2089,4,4,4,4,4,5,4,3,3,4,3,5,3,4,0,1.0,satisfied +3861,86124,Male,disloyal Customer,24,Business travel,Business,331,5,5,5,4,2,5,3,2,4,3,5,4,5,2,2,4.0,satisfied +3862,23356,Male,Loyal Customer,52,Personal Travel,Eco Plus,979,1,5,1,2,3,1,3,3,5,5,4,4,5,3,67,48.0,neutral or dissatisfied +3863,128855,Male,Loyal Customer,14,Personal Travel,Eco,2475,4,4,3,5,3,5,5,3,3,5,5,5,3,5,15,24.0,neutral or dissatisfied +3864,115595,Male,Loyal Customer,43,Business travel,Business,2533,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +3865,69730,Female,Loyal Customer,48,Personal Travel,Eco,1372,1,4,1,4,3,2,3,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +3866,128678,Male,Loyal Customer,30,Business travel,Business,2288,3,3,3,3,5,5,5,5,3,4,5,5,4,5,17,0.0,satisfied +3867,86658,Female,Loyal Customer,70,Personal Travel,Eco,746,2,4,2,4,4,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +3868,121360,Male,Loyal Customer,56,Business travel,Business,1670,5,5,5,5,3,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +3869,54056,Male,Loyal Customer,52,Business travel,Business,1416,2,2,2,2,1,1,1,4,4,4,4,2,4,4,0,0.0,satisfied +3870,19032,Male,Loyal Customer,22,Personal Travel,Eco,871,1,5,0,3,4,0,4,4,2,4,3,2,5,4,0,2.0,neutral or dissatisfied +3871,32546,Male,Loyal Customer,62,Business travel,Business,2276,2,2,4,2,3,1,2,5,5,5,4,2,5,2,0,0.0,satisfied +3872,18779,Female,Loyal Customer,46,Business travel,Eco,551,4,1,1,1,1,3,2,5,5,4,5,1,5,3,43,31.0,satisfied +3873,123450,Male,Loyal Customer,47,Business travel,Business,2125,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +3874,83912,Female,Loyal Customer,42,Business travel,Business,2543,2,5,5,5,1,3,4,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +3875,97688,Female,disloyal Customer,66,Business travel,Business,491,2,2,2,4,2,2,5,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +3876,34066,Female,Loyal Customer,40,Personal Travel,Eco,1674,3,1,3,4,3,3,3,3,1,4,4,1,3,3,20,0.0,neutral or dissatisfied +3877,67813,Female,Loyal Customer,58,Business travel,Business,2294,1,1,1,1,5,2,1,5,5,5,5,2,5,2,0,0.0,satisfied +3878,66888,Female,Loyal Customer,55,Business travel,Business,2114,2,5,5,5,4,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +3879,32823,Male,disloyal Customer,22,Business travel,Eco,216,1,0,0,2,3,0,3,3,4,4,5,3,3,3,0,3.0,neutral or dissatisfied +3880,7957,Female,Loyal Customer,25,Business travel,Business,2721,2,2,2,2,3,4,3,3,3,2,4,3,4,3,0,0.0,satisfied +3881,10533,Male,Loyal Customer,39,Business travel,Business,429,3,3,3,3,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +3882,114087,Male,Loyal Customer,12,Personal Travel,Eco,1947,0,4,0,5,1,0,1,1,5,3,5,4,5,1,25,18.0,satisfied +3883,113116,Female,Loyal Customer,44,Personal Travel,Eco,479,3,4,3,3,5,3,3,2,2,3,2,3,2,1,26,22.0,neutral or dissatisfied +3884,103980,Female,Loyal Customer,40,Business travel,Business,1334,5,5,5,5,3,4,4,5,5,5,5,5,5,4,2,0.0,satisfied +3885,126195,Female,disloyal Customer,26,Business travel,Eco,631,4,2,4,3,5,4,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +3886,90521,Female,Loyal Customer,42,Business travel,Business,406,4,4,4,4,3,4,5,5,5,5,5,4,5,4,3,0.0,satisfied +3887,33406,Male,disloyal Customer,35,Business travel,Eco,851,1,1,1,5,1,4,4,4,2,4,5,4,1,4,0,18.0,neutral or dissatisfied +3888,46872,Male,disloyal Customer,27,Business travel,Eco,844,3,3,3,4,4,3,1,4,1,2,3,2,4,4,10,22.0,neutral or dissatisfied +3889,12398,Male,Loyal Customer,22,Business travel,Business,2840,4,5,5,5,1,1,4,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +3890,28193,Female,Loyal Customer,7,Personal Travel,Eco,834,3,3,3,1,1,3,1,1,4,3,2,1,1,1,0,0.0,neutral or dissatisfied +3891,128049,Male,Loyal Customer,54,Business travel,Business,735,3,3,3,3,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +3892,104568,Male,disloyal Customer,24,Business travel,Eco,369,2,4,2,2,3,2,3,3,4,5,5,3,5,3,11,10.0,neutral or dissatisfied +3893,44953,Female,Loyal Customer,46,Personal Travel,Eco,397,3,3,3,1,2,1,4,1,1,3,1,1,1,4,34,47.0,neutral or dissatisfied +3894,49666,Female,disloyal Customer,40,Business travel,Business,109,3,3,3,2,3,3,4,3,4,2,5,1,3,3,56,54.0,neutral or dissatisfied +3895,42037,Male,Loyal Customer,32,Business travel,Business,116,1,2,2,2,2,2,1,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +3896,99360,Male,Loyal Customer,48,Business travel,Business,409,4,4,4,4,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +3897,49476,Male,Loyal Customer,59,Business travel,Eco,109,4,3,4,4,4,4,4,4,2,1,4,2,1,4,5,0.0,satisfied +3898,109021,Female,Loyal Customer,50,Business travel,Business,1609,4,4,4,4,4,5,5,2,2,2,2,3,2,4,14,10.0,satisfied +3899,52439,Female,Loyal Customer,27,Personal Travel,Eco,598,4,0,4,4,3,4,3,3,4,2,5,5,5,3,0,0.0,neutral or dissatisfied +3900,107785,Male,Loyal Customer,50,Business travel,Business,666,5,5,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +3901,82392,Female,Loyal Customer,48,Business travel,Business,1808,4,4,5,4,2,5,4,4,4,4,4,5,4,3,0,1.0,satisfied +3902,84404,Male,Loyal Customer,15,Business travel,Business,606,2,5,5,5,2,2,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +3903,84622,Male,disloyal Customer,18,Business travel,Eco,669,3,4,3,3,5,3,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +3904,71664,Male,Loyal Customer,62,Personal Travel,Eco,1120,1,4,1,5,2,1,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +3905,49558,Female,Loyal Customer,47,Business travel,Business,308,5,5,5,5,2,1,3,5,5,5,5,2,5,1,0,0.0,satisfied +3906,48345,Female,disloyal Customer,33,Business travel,Eco,587,4,0,4,4,3,4,3,3,4,3,5,4,5,3,0,,neutral or dissatisfied +3907,99781,Male,Loyal Customer,45,Business travel,Business,584,1,1,1,1,3,5,4,5,5,5,5,5,5,4,100,121.0,satisfied +3908,58303,Male,Loyal Customer,57,Business travel,Business,1739,4,4,4,4,5,3,4,4,4,4,4,4,4,5,6,0.0,satisfied +3909,88778,Female,Loyal Customer,32,Business travel,Business,270,4,4,2,4,5,5,5,5,5,2,4,4,4,5,0,0.0,satisfied +3910,26486,Female,Loyal Customer,13,Personal Travel,Eco Plus,842,3,5,3,2,2,3,2,2,4,1,2,3,2,2,0,0.0,neutral or dissatisfied +3911,29816,Female,Loyal Customer,38,Business travel,Eco,31,4,2,2,2,4,4,4,4,4,4,3,5,2,4,0,0.0,satisfied +3912,48742,Male,disloyal Customer,23,Business travel,Business,209,4,4,4,3,2,4,2,2,3,2,3,3,4,2,13,0.0,neutral or dissatisfied +3913,74809,Male,Loyal Customer,33,Business travel,Eco Plus,1431,5,4,3,4,5,5,5,5,3,3,2,4,4,5,34,51.0,satisfied +3914,95096,Male,Loyal Customer,65,Personal Travel,Eco,248,3,5,3,2,4,3,4,4,4,3,5,5,4,4,14,28.0,neutral or dissatisfied +3915,75719,Female,disloyal Customer,21,Business travel,Eco,813,5,5,5,1,2,5,4,2,3,5,4,3,5,2,0,0.0,satisfied +3916,77142,Female,Loyal Customer,58,Business travel,Business,1865,5,5,5,5,5,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +3917,3146,Male,Loyal Customer,40,Business travel,Business,140,1,1,1,1,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3918,114585,Female,disloyal Customer,45,Business travel,Business,446,2,2,2,1,4,2,4,4,3,2,5,5,5,4,0,0.0,satisfied +3919,54334,Female,Loyal Customer,8,Personal Travel,Eco,1597,2,5,2,4,1,2,1,1,3,3,4,5,4,1,4,0.0,neutral or dissatisfied +3920,89808,Female,Loyal Customer,52,Business travel,Business,1688,2,4,2,2,2,4,5,4,4,4,4,4,4,5,22,13.0,satisfied +3921,48235,Male,Loyal Customer,32,Personal Travel,Eco,259,5,3,5,5,2,5,1,2,5,4,5,3,5,2,0,0.0,satisfied +3922,84004,Female,Loyal Customer,13,Personal Travel,Eco,373,2,3,2,3,5,2,5,5,3,3,5,3,2,5,0,4.0,neutral or dissatisfied +3923,59561,Female,disloyal Customer,24,Business travel,Eco,787,2,2,2,2,1,2,1,1,4,2,5,3,5,1,6,0.0,neutral or dissatisfied +3924,128126,Female,Loyal Customer,54,Personal Travel,Eco,1587,2,5,2,5,2,5,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +3925,114332,Female,Loyal Customer,69,Personal Travel,Eco,862,4,4,4,2,2,4,4,4,4,4,4,5,4,5,8,9.0,neutral or dissatisfied +3926,70149,Female,Loyal Customer,7,Personal Travel,Eco,550,4,4,4,3,1,4,1,1,2,5,2,1,4,1,4,4.0,neutral or dissatisfied +3927,88151,Male,Loyal Customer,54,Business travel,Business,2703,1,1,4,1,3,5,5,5,5,5,5,5,5,4,19,5.0,satisfied +3928,114784,Female,Loyal Customer,59,Business travel,Business,1503,2,5,2,2,4,4,5,5,5,5,5,5,5,5,10,0.0,satisfied +3929,25823,Female,Loyal Customer,22,Business travel,Eco Plus,1747,4,5,5,5,4,4,5,4,5,3,1,4,1,4,4,7.0,satisfied +3930,10585,Female,disloyal Customer,23,Business travel,Eco,458,2,4,2,5,2,2,2,2,3,4,4,5,5,2,26,30.0,neutral or dissatisfied +3931,6797,Male,Loyal Customer,36,Business travel,Business,223,1,3,1,1,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3932,74743,Male,Loyal Customer,46,Personal Travel,Eco,1171,3,4,4,4,4,4,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +3933,38213,Female,Loyal Customer,23,Business travel,Eco Plus,1197,4,5,5,5,4,4,5,4,3,2,1,5,2,4,0,0.0,satisfied +3934,40194,Male,disloyal Customer,24,Business travel,Eco,387,4,0,4,3,5,4,2,5,5,2,5,1,5,5,0,0.0,neutral or dissatisfied +3935,66085,Female,Loyal Customer,41,Personal Travel,Eco,1055,2,4,2,3,5,2,5,5,5,2,5,4,5,5,9,9.0,neutral or dissatisfied +3936,12489,Female,Loyal Customer,49,Business travel,Eco Plus,190,5,3,3,3,4,5,1,5,5,5,5,5,5,4,0,0.0,satisfied +3937,1205,Female,Loyal Customer,54,Personal Travel,Eco,312,2,4,4,3,5,5,5,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +3938,15442,Female,Loyal Customer,59,Business travel,Eco,331,4,4,4,4,2,2,3,5,5,4,5,1,5,4,0,1.0,neutral or dissatisfied +3939,45670,Male,Loyal Customer,32,Personal Travel,Eco Plus,313,3,4,2,3,3,2,1,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +3940,2069,Male,Loyal Customer,40,Business travel,Business,2502,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +3941,30998,Male,Loyal Customer,42,Business travel,Business,391,5,5,5,5,3,3,3,4,4,4,4,4,4,4,29,60.0,satisfied +3942,107705,Male,disloyal Customer,21,Business travel,Eco,405,2,3,2,3,4,2,4,4,4,2,3,4,2,4,13,3.0,neutral or dissatisfied +3943,5059,Female,Loyal Customer,52,Business travel,Business,3394,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,25.0,satisfied +3944,41307,Male,Loyal Customer,27,Business travel,Eco,802,3,5,2,5,3,4,3,3,2,1,4,2,4,3,0,8.0,satisfied +3945,101057,Female,Loyal Customer,54,Business travel,Eco,368,2,3,3,3,1,3,4,2,2,2,2,2,2,2,23,9.0,neutral or dissatisfied +3946,101241,Male,Loyal Customer,48,Business travel,Eco,1587,3,3,3,3,3,3,3,3,2,1,3,3,4,3,21,11.0,neutral or dissatisfied +3947,88689,Male,Loyal Customer,33,Personal Travel,Eco,594,3,4,3,3,3,3,3,3,4,3,4,1,3,3,87,69.0,neutral or dissatisfied +3948,110657,Male,Loyal Customer,52,Business travel,Business,3000,2,2,2,2,5,5,4,4,4,4,4,4,4,3,4,0.0,satisfied +3949,34777,Female,Loyal Customer,43,Personal Travel,Eco,209,3,3,3,3,3,3,4,5,5,3,5,3,5,2,40,42.0,neutral or dissatisfied +3950,104813,Male,Loyal Customer,69,Personal Travel,Eco,587,1,5,1,2,3,1,3,3,3,2,5,5,5,3,48,41.0,neutral or dissatisfied +3951,69775,Female,Loyal Customer,50,Business travel,Eco,2454,4,4,4,4,4,4,4,2,5,3,4,4,4,4,0,13.0,neutral or dissatisfied +3952,29989,Female,Loyal Customer,22,Business travel,Business,183,2,2,2,2,5,5,3,5,3,2,4,4,5,5,0,1.0,satisfied +3953,59265,Male,Loyal Customer,44,Business travel,Business,4963,5,5,5,5,5,4,4,3,2,3,4,4,4,4,0,0.0,satisfied +3954,105677,Female,disloyal Customer,44,Business travel,Eco,663,2,4,2,3,2,2,2,2,2,5,3,1,3,2,15,9.0,neutral or dissatisfied +3955,91275,Female,disloyal Customer,51,Business travel,Business,545,2,1,1,4,3,2,3,3,3,2,4,4,4,3,2,0.0,neutral or dissatisfied +3956,119125,Female,disloyal Customer,15,Business travel,Eco,1107,5,5,5,2,4,5,4,4,3,5,5,5,4,4,0,0.0,satisfied +3957,114950,Male,Loyal Customer,41,Business travel,Business,404,3,3,3,3,2,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +3958,1099,Male,Loyal Customer,52,Personal Travel,Eco,134,2,3,2,3,2,2,4,2,4,5,3,2,3,2,0,0.0,neutral or dissatisfied +3959,125778,Female,Loyal Customer,28,Business travel,Business,2637,1,1,1,1,5,5,5,5,4,4,4,5,4,5,14,61.0,satisfied +3960,100511,Female,disloyal Customer,18,Business travel,Eco,580,2,4,2,3,2,2,2,2,2,2,3,4,4,2,38,30.0,neutral or dissatisfied +3961,116023,Male,Loyal Customer,45,Personal Travel,Eco,337,3,3,3,3,4,3,4,4,5,5,1,3,3,4,0,0.0,neutral or dissatisfied +3962,90269,Female,Loyal Customer,30,Business travel,Business,2610,4,4,3,4,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +3963,51216,Female,Loyal Customer,55,Business travel,Eco Plus,153,4,2,2,2,3,5,5,4,4,4,4,4,4,5,26,18.0,satisfied +3964,44776,Male,disloyal Customer,50,Business travel,Eco,1250,4,4,4,3,2,4,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +3965,129376,Female,disloyal Customer,27,Business travel,Business,2454,3,3,3,3,2,3,2,2,4,5,3,3,5,2,0,0.0,neutral or dissatisfied +3966,81747,Male,Loyal Customer,43,Business travel,Business,1487,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +3967,91624,Female,Loyal Customer,42,Business travel,Eco,1312,4,5,5,5,2,2,2,4,4,4,4,3,4,1,100,87.0,neutral or dissatisfied +3968,52409,Female,Loyal Customer,8,Personal Travel,Eco,370,2,4,2,2,3,2,3,3,2,5,4,4,2,3,0,0.0,neutral or dissatisfied +3969,43944,Female,disloyal Customer,38,Business travel,Business,473,3,3,3,3,3,3,3,3,2,5,4,1,4,3,0,6.0,neutral or dissatisfied +3970,62821,Female,Loyal Customer,23,Personal Travel,Eco,2556,2,3,2,3,2,2,2,4,1,3,3,2,3,2,3,14.0,neutral or dissatisfied +3971,19099,Male,Loyal Customer,35,Business travel,Eco,287,5,4,4,4,5,5,5,5,2,5,1,4,5,5,0,0.0,satisfied +3972,53707,Female,Loyal Customer,41,Business travel,Eco,1190,4,1,1,1,3,4,3,3,1,4,1,5,3,3,0,0.0,satisfied +3973,73593,Male,Loyal Customer,34,Business travel,Business,3792,5,5,5,5,3,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +3974,88234,Female,disloyal Customer,38,Business travel,Eco,223,4,2,4,4,2,4,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +3975,16826,Male,Loyal Customer,32,Personal Travel,Eco,645,1,5,1,3,3,1,3,3,4,5,4,3,1,3,0,18.0,neutral or dissatisfied +3976,69193,Male,Loyal Customer,54,Business travel,Business,3563,4,4,4,4,5,4,4,4,4,4,5,5,4,5,103,101.0,satisfied +3977,36890,Male,Loyal Customer,28,Business travel,Eco Plus,1182,0,0,0,2,3,0,3,3,3,5,2,5,4,3,31,20.0,satisfied +3978,28843,Male,Loyal Customer,43,Business travel,Eco,954,3,4,4,4,3,3,3,3,4,2,2,4,3,3,0,0.0,satisfied +3979,108279,Female,Loyal Customer,57,Personal Travel,Eco,895,2,5,2,3,4,5,5,4,4,2,4,4,4,4,36,15.0,neutral or dissatisfied +3980,118893,Female,disloyal Customer,26,Business travel,Business,587,5,5,5,1,5,5,5,5,5,5,4,5,3,5,130,135.0,satisfied +3981,96409,Male,Loyal Customer,15,Personal Travel,Eco,1407,5,3,5,3,1,5,1,1,5,5,3,5,2,1,0,0.0,satisfied +3982,15094,Male,Loyal Customer,68,Personal Travel,Eco,239,4,1,4,4,3,4,3,3,4,4,4,2,3,3,0,0.0,satisfied +3983,107297,Female,Loyal Customer,20,Personal Travel,Eco,307,3,2,3,4,1,3,1,1,3,1,4,4,3,1,16,14.0,neutral or dissatisfied +3984,25654,Male,Loyal Customer,38,Personal Travel,Eco Plus,526,3,2,5,3,1,5,1,1,4,4,3,2,3,1,0,0.0,neutral or dissatisfied +3985,87194,Female,Loyal Customer,22,Business travel,Business,3055,3,5,5,5,3,3,3,3,2,3,3,4,4,3,40,18.0,neutral or dissatisfied +3986,85187,Female,disloyal Customer,25,Business travel,Eco,696,4,4,4,4,3,4,3,3,2,2,4,1,4,3,0,0.0,neutral or dissatisfied +3987,21306,Female,Loyal Customer,23,Personal Travel,Eco,526,4,5,4,3,4,4,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +3988,32502,Female,Loyal Customer,64,Business travel,Eco,163,5,3,3,3,5,4,5,5,5,5,5,2,5,5,0,0.0,satisfied +3989,125253,Female,Loyal Customer,13,Personal Travel,Eco,427,4,1,4,1,1,4,1,1,4,4,1,4,1,1,0,0.0,neutral or dissatisfied +3990,78129,Male,Loyal Customer,39,Personal Travel,Eco,196,4,2,4,4,2,4,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +3991,102160,Male,Loyal Customer,19,Business travel,Business,3076,5,5,5,5,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +3992,116912,Male,disloyal Customer,24,Business travel,Eco,370,4,0,4,3,2,4,2,2,4,5,4,3,4,2,74,68.0,satisfied +3993,121468,Male,Loyal Customer,47,Personal Travel,Eco,331,3,4,3,3,5,3,5,5,3,4,4,5,5,5,0,3.0,neutral or dissatisfied +3994,52121,Female,Loyal Customer,14,Business travel,Eco Plus,639,2,1,5,1,2,2,3,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +3995,26445,Male,Loyal Customer,40,Business travel,Business,919,3,3,3,3,1,4,3,4,4,4,4,1,4,1,5,0.0,satisfied +3996,125814,Male,disloyal Customer,39,Business travel,Business,992,4,4,4,1,3,4,3,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +3997,126560,Female,Loyal Customer,44,Business travel,Business,1558,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +3998,105530,Female,disloyal Customer,10,Business travel,Eco,611,5,0,5,3,1,0,1,1,3,4,5,4,4,1,0,0.0,satisfied +3999,127728,Male,Loyal Customer,57,Business travel,Business,255,4,4,4,4,2,5,5,5,5,5,5,3,5,5,66,54.0,satisfied +4000,67124,Female,Loyal Customer,25,Business travel,Business,2603,1,5,5,5,1,1,1,1,4,4,1,3,1,1,32,36.0,neutral or dissatisfied +4001,100012,Female,Loyal Customer,71,Business travel,Business,3887,1,2,2,2,3,3,2,1,1,2,1,2,1,3,5,0.0,neutral or dissatisfied +4002,100562,Male,disloyal Customer,85,Business travel,Business,486,3,4,4,4,3,3,3,4,5,4,4,3,4,3,8,1.0,neutral or dissatisfied +4003,110778,Female,Loyal Customer,59,Business travel,Business,990,2,4,4,4,3,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +4004,92656,Female,Loyal Customer,9,Personal Travel,Eco,453,4,4,4,3,3,4,3,3,1,1,4,3,5,3,0,0.0,neutral or dissatisfied +4005,80415,Male,Loyal Customer,38,Business travel,Business,2248,3,4,3,3,2,4,5,4,4,4,4,4,4,3,8,25.0,satisfied +4006,47924,Female,Loyal Customer,7,Personal Travel,Eco,834,3,5,3,4,2,3,4,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +4007,10844,Male,Loyal Customer,39,Business travel,Business,3927,1,5,5,5,3,4,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +4008,38648,Male,disloyal Customer,27,Business travel,Eco,1460,2,2,2,4,4,2,4,4,5,3,5,2,3,4,0,0.0,neutral or dissatisfied +4009,45289,Male,Loyal Customer,42,Business travel,Business,150,5,5,5,5,4,4,1,4,4,4,4,3,4,3,0,0.0,satisfied +4010,42532,Male,Loyal Customer,60,Business travel,Eco,368,5,1,3,1,4,5,4,4,5,1,5,3,1,4,0,0.0,satisfied +4011,39697,Male,Loyal Customer,54,Business travel,Business,3780,4,4,4,4,4,5,4,4,4,4,4,4,4,4,73,60.0,satisfied +4012,113474,Male,Loyal Customer,54,Business travel,Business,407,5,1,5,5,3,5,4,4,4,4,4,3,4,5,6,5.0,satisfied +4013,79543,Female,Loyal Customer,43,Business travel,Business,762,4,4,4,4,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +4014,4656,Female,disloyal Customer,24,Business travel,Business,364,4,0,4,3,2,4,2,2,5,2,4,5,5,2,0,0.0,satisfied +4015,107536,Female,Loyal Customer,56,Business travel,Business,1521,2,2,4,2,4,5,4,4,4,4,4,3,4,4,29,22.0,satisfied +4016,27075,Female,Loyal Customer,18,Personal Travel,Eco Plus,1399,2,3,2,4,1,2,1,1,4,3,1,5,4,1,0,0.0,neutral or dissatisfied +4017,80080,Male,Loyal Customer,43,Business travel,Business,2129,4,4,2,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +4018,127190,Female,disloyal Customer,30,Business travel,Business,647,2,2,2,4,4,2,5,4,3,5,5,4,5,4,4,0.0,neutral or dissatisfied +4019,57573,Female,Loyal Customer,16,Business travel,Eco,1597,1,2,2,2,1,1,2,1,4,2,2,3,4,1,12,21.0,neutral or dissatisfied +4020,47362,Male,Loyal Customer,59,Business travel,Eco,599,3,2,2,2,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +4021,40489,Female,Loyal Customer,35,Personal Travel,Eco,222,2,4,2,2,2,2,3,2,1,1,3,1,3,2,0,0.0,neutral or dissatisfied +4022,35057,Female,Loyal Customer,60,Business travel,Business,1076,2,2,5,2,2,5,5,5,5,5,5,5,5,4,88,51.0,satisfied +4023,40406,Female,Loyal Customer,45,Business travel,Eco,222,5,4,4,4,5,3,4,5,5,5,5,1,5,2,0,,satisfied +4024,70257,Female,Loyal Customer,22,Personal Travel,Eco,1592,1,5,1,5,4,1,4,4,3,5,3,5,5,4,2,0.0,neutral or dissatisfied +4025,119481,Female,Loyal Customer,44,Business travel,Business,3098,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +4026,126965,Female,Loyal Customer,54,Business travel,Business,2102,4,3,4,4,5,5,4,2,2,2,2,4,2,3,0,0.0,satisfied +4027,51879,Female,Loyal Customer,41,Business travel,Business,3068,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +4028,114756,Male,disloyal Customer,39,Business travel,Business,342,2,2,2,5,1,2,1,1,3,3,4,4,4,1,0,0.0,neutral or dissatisfied +4029,73331,Male,Loyal Customer,26,Business travel,Business,1687,2,2,2,2,4,4,4,4,4,4,5,4,5,4,0,0.0,satisfied +4030,115327,Male,disloyal Customer,27,Business travel,Business,296,4,4,4,1,4,4,4,4,5,4,4,5,4,4,17,30.0,satisfied +4031,46681,Male,Loyal Customer,9,Personal Travel,Eco,125,3,2,3,2,4,3,4,4,2,2,3,2,2,4,10,17.0,neutral or dissatisfied +4032,57419,Male,Loyal Customer,68,Personal Travel,Eco,455,2,4,2,3,5,2,5,5,4,5,4,3,4,5,0,0.0,neutral or dissatisfied +4033,81348,Female,disloyal Customer,30,Business travel,Eco,1299,1,1,1,4,4,1,4,4,2,3,1,1,2,4,0,0.0,neutral or dissatisfied +4034,99231,Female,Loyal Customer,51,Business travel,Business,1541,2,5,5,5,5,3,3,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +4035,60554,Female,Loyal Customer,60,Business travel,Eco Plus,641,3,5,5,5,3,3,3,3,2,4,3,3,4,3,132,121.0,neutral or dissatisfied +4036,99770,Male,Loyal Customer,62,Business travel,Eco Plus,255,2,5,5,5,2,2,2,2,2,2,3,1,2,2,8,6.0,neutral or dissatisfied +4037,87783,Male,Loyal Customer,41,Business travel,Business,214,1,1,5,1,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +4038,28359,Male,Loyal Customer,64,Business travel,Eco Plus,867,4,3,3,3,4,4,4,4,4,1,3,2,4,4,0,0.0,neutral or dissatisfied +4039,2749,Female,Loyal Customer,42,Business travel,Eco,695,4,2,2,2,2,4,3,4,4,4,4,2,4,1,0,18.0,neutral or dissatisfied +4040,75866,Male,Loyal Customer,68,Personal Travel,Eco Plus,1437,5,5,5,2,4,5,4,4,5,4,4,5,4,4,0,0.0,satisfied +4041,111759,Female,disloyal Customer,21,Business travel,Eco,938,2,2,2,3,4,2,1,4,3,2,3,2,4,4,25,18.0,neutral or dissatisfied +4042,33469,Female,Loyal Customer,13,Personal Travel,Eco Plus,2556,2,2,2,4,1,2,1,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +4043,68943,Male,Loyal Customer,34,Personal Travel,Eco,646,4,2,4,1,5,4,5,5,1,1,1,1,2,5,0,0.0,neutral or dissatisfied +4044,19043,Male,Loyal Customer,32,Business travel,Business,3990,5,5,5,5,4,4,4,4,2,4,1,5,4,4,30,28.0,satisfied +4045,71193,Male,Loyal Customer,46,Business travel,Business,2586,2,2,2,2,3,4,5,4,4,4,4,5,4,4,38,33.0,satisfied +4046,39321,Male,Loyal Customer,31,Personal Travel,Eco,212,2,1,2,1,5,2,1,5,3,5,2,1,2,5,0,0.0,neutral or dissatisfied +4047,23096,Male,Loyal Customer,24,Business travel,Business,240,0,0,0,1,1,1,1,1,3,5,5,3,4,1,23,25.0,satisfied +4048,72072,Male,disloyal Customer,27,Business travel,Business,2486,1,1,1,1,1,1,5,1,3,3,5,5,4,1,19,0.0,neutral or dissatisfied +4049,8078,Male,disloyal Customer,23,Business travel,Business,530,4,0,4,3,5,4,5,5,3,2,5,5,5,5,0,0.0,satisfied +4050,10774,Male,Loyal Customer,45,Business travel,Business,1677,0,5,0,2,5,5,4,1,1,1,1,4,1,4,0,0.0,satisfied +4051,117658,Female,Loyal Customer,54,Business travel,Business,1449,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +4052,79303,Female,Loyal Customer,24,Business travel,Business,2248,2,2,2,2,2,2,2,2,5,2,3,5,4,2,0,0.0,satisfied +4053,8771,Male,Loyal Customer,55,Personal Travel,Business,522,4,5,4,3,2,4,4,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +4054,110115,Female,Loyal Customer,50,Business travel,Business,3816,5,5,5,5,5,4,4,4,4,4,4,3,4,4,3,4.0,satisfied +4055,107006,Male,Loyal Customer,47,Business travel,Business,937,3,3,3,3,4,4,5,4,4,4,4,3,4,5,1,0.0,satisfied +4056,103565,Female,Loyal Customer,48,Business travel,Business,2914,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +4057,1290,Male,Loyal Customer,45,Personal Travel,Eco,102,3,4,0,4,4,0,4,4,5,4,1,2,2,4,0,0.0,neutral or dissatisfied +4058,118062,Male,Loyal Customer,51,Personal Travel,Eco,1044,4,4,3,3,2,3,2,2,5,3,2,2,4,2,0,0.0,neutral or dissatisfied +4059,127213,Male,Loyal Customer,31,Personal Travel,Eco Plus,370,1,4,1,2,4,1,4,4,4,2,4,5,5,4,3,6.0,neutral or dissatisfied +4060,106335,Male,Loyal Customer,48,Personal Travel,Eco,825,2,5,2,4,1,2,1,1,4,4,5,5,4,1,0,6.0,neutral or dissatisfied +4061,64840,Female,disloyal Customer,27,Business travel,Business,247,4,4,4,3,2,4,2,2,3,2,4,4,5,2,0,0.0,satisfied +4062,46468,Female,disloyal Customer,19,Business travel,Eco,125,1,2,1,3,2,1,5,2,4,5,3,1,4,2,29,26.0,neutral or dissatisfied +4063,54117,Male,Loyal Customer,50,Business travel,Business,1400,1,1,1,1,4,3,2,4,4,4,4,2,4,4,8,0.0,satisfied +4064,56110,Male,Loyal Customer,67,Personal Travel,Eco,2402,1,4,1,1,1,5,5,1,1,5,2,5,3,5,0,1.0,neutral or dissatisfied +4065,22302,Male,Loyal Customer,39,Business travel,Business,238,0,0,0,3,1,2,4,3,3,4,4,2,3,3,0,9.0,satisfied +4066,36824,Female,Loyal Customer,39,Business travel,Business,369,2,2,2,2,3,1,2,2,2,2,2,2,2,3,0,0.0,satisfied +4067,105745,Male,Loyal Customer,16,Business travel,Business,3335,2,1,1,1,2,2,2,2,4,1,3,3,4,2,0,4.0,neutral or dissatisfied +4068,13896,Male,Loyal Customer,41,Business travel,Business,153,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +4069,102615,Female,Loyal Customer,43,Business travel,Business,1294,2,2,5,2,5,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +4070,83547,Female,Loyal Customer,42,Business travel,Business,3270,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +4071,104845,Female,Loyal Customer,16,Personal Travel,Eco,472,3,5,3,1,3,2,1,3,5,5,4,1,5,1,145,136.0,neutral or dissatisfied +4072,50545,Female,Loyal Customer,26,Personal Travel,Eco,209,3,3,3,2,4,3,4,4,1,4,4,1,5,4,6,15.0,neutral or dissatisfied +4073,3698,Male,disloyal Customer,39,Business travel,Eco,431,1,3,1,4,4,1,4,4,1,4,3,1,3,4,0,0.0,neutral or dissatisfied +4074,74296,Male,Loyal Customer,69,Personal Travel,Eco,2288,4,2,4,3,5,4,5,5,4,2,2,4,2,5,0,0.0,neutral or dissatisfied +4075,36473,Female,disloyal Customer,45,Business travel,Business,1249,1,1,1,5,2,1,2,2,5,5,5,3,4,2,0,17.0,neutral or dissatisfied +4076,77257,Female,Loyal Customer,60,Personal Travel,Eco,1590,4,4,4,1,5,5,4,2,2,4,2,5,2,5,5,5.0,satisfied +4077,69146,Male,Loyal Customer,62,Personal Travel,Eco,2248,3,5,3,3,3,2,5,3,4,4,5,5,4,5,0,38.0,neutral or dissatisfied +4078,59516,Female,Loyal Customer,51,Business travel,Business,387,2,2,3,2,2,4,4,4,4,4,4,3,4,4,7,0.0,satisfied +4079,4922,Male,Loyal Customer,63,Personal Travel,Eco,1020,3,4,3,3,1,3,1,1,1,4,4,1,4,1,22,36.0,neutral or dissatisfied +4080,97843,Female,Loyal Customer,35,Personal Travel,Eco,395,4,4,4,2,4,4,4,4,5,2,4,3,4,4,0,18.0,neutral or dissatisfied +4081,30439,Female,Loyal Customer,53,Business travel,Eco Plus,851,1,3,3,3,5,3,4,2,2,1,2,3,2,4,17,9.0,neutral or dissatisfied +4082,112751,Female,disloyal Customer,22,Business travel,Eco,590,4,0,5,3,1,5,1,1,4,2,4,4,4,1,0,0.0,satisfied +4083,129712,Male,disloyal Customer,26,Business travel,Business,308,3,4,3,1,4,3,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +4084,8719,Female,disloyal Customer,22,Personal Travel,Eco,280,2,5,5,2,2,5,1,2,4,5,2,4,2,2,0,0.0,neutral or dissatisfied +4085,48179,Female,Loyal Customer,48,Business travel,Business,236,2,2,2,2,1,1,5,4,4,4,4,1,4,1,0,0.0,satisfied +4086,65115,Male,Loyal Customer,45,Personal Travel,Eco,224,1,5,1,3,3,1,3,3,3,3,5,4,4,3,9,11.0,neutral or dissatisfied +4087,33527,Female,Loyal Customer,32,Business travel,Business,1850,1,1,1,1,5,4,5,5,2,2,5,5,1,5,0,0.0,satisfied +4088,6615,Female,Loyal Customer,47,Business travel,Business,1763,4,4,2,4,5,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +4089,97839,Male,Loyal Customer,36,Personal Travel,Eco,480,3,0,3,4,3,5,5,3,5,4,5,5,3,5,166,148.0,neutral or dissatisfied +4090,72789,Male,Loyal Customer,40,Business travel,Eco,645,4,4,4,4,4,4,4,4,2,4,3,3,4,4,0,0.0,neutral or dissatisfied +4091,45339,Male,disloyal Customer,25,Business travel,Business,222,2,0,2,5,4,2,4,4,1,3,3,5,3,4,0,0.0,neutral or dissatisfied +4092,99703,Male,Loyal Customer,52,Business travel,Business,2026,3,3,3,3,5,5,5,4,4,4,4,3,4,4,42,42.0,satisfied +4093,81494,Female,Loyal Customer,15,Personal Travel,Eco,528,2,2,2,3,3,2,3,3,4,4,4,4,4,3,1,0.0,neutral or dissatisfied +4094,42674,Male,Loyal Customer,23,Business travel,Business,2270,3,4,4,4,3,3,3,3,1,4,3,3,2,3,0,0.0,neutral or dissatisfied +4095,110694,Female,Loyal Customer,65,Personal Travel,Eco,829,2,4,2,2,2,5,4,3,3,2,5,5,3,3,0,0.0,neutral or dissatisfied +4096,8992,Male,Loyal Customer,72,Business travel,Business,228,0,0,0,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +4097,45124,Male,Loyal Customer,46,Personal Travel,Eco,157,2,4,2,1,3,2,3,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +4098,693,Female,Loyal Customer,40,Business travel,Business,3625,1,1,2,1,3,4,4,5,5,5,5,3,5,3,0,1.0,satisfied +4099,114255,Female,Loyal Customer,54,Business travel,Eco,567,4,4,4,4,2,1,1,4,4,4,4,5,4,4,0,0.0,satisfied +4100,116291,Male,Loyal Customer,11,Personal Travel,Eco,337,2,2,3,3,5,3,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +4101,40174,Male,Loyal Customer,43,Business travel,Business,2934,4,4,4,4,5,2,5,4,4,4,4,4,4,5,0,13.0,satisfied +4102,97846,Female,Loyal Customer,40,Personal Travel,Eco,395,2,4,2,3,4,2,4,4,1,4,2,5,2,4,3,13.0,neutral or dissatisfied +4103,38198,Female,Loyal Customer,28,Business travel,Eco Plus,1091,5,2,2,2,5,5,5,5,3,4,5,4,3,5,0,0.0,satisfied +4104,23273,Male,disloyal Customer,22,Business travel,Eco,359,2,3,2,3,4,2,4,4,3,1,3,1,4,4,0,0.0,neutral or dissatisfied +4105,119395,Female,disloyal Customer,33,Business travel,Eco,399,2,1,2,3,2,2,4,2,1,1,3,3,4,2,3,0.0,neutral or dissatisfied +4106,94866,Female,disloyal Customer,44,Business travel,Eco,239,3,4,3,4,3,3,3,3,2,2,3,1,4,3,105,98.0,neutral or dissatisfied +4107,78708,Male,Loyal Customer,45,Business travel,Business,2126,0,5,0,2,3,5,5,5,5,5,5,5,5,3,111,105.0,satisfied +4108,4322,Male,Loyal Customer,60,Business travel,Business,189,2,5,5,5,2,1,2,2,2,2,2,2,2,4,34,11.0,neutral or dissatisfied +4109,76311,Male,disloyal Customer,23,Business travel,Business,1187,4,0,4,1,4,4,4,4,5,5,5,4,5,4,2,3.0,satisfied +4110,76933,Female,Loyal Customer,42,Personal Travel,Eco,1727,2,3,2,2,5,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +4111,112123,Female,disloyal Customer,31,Business travel,Eco,977,2,2,2,4,2,2,2,2,1,5,4,2,4,2,55,41.0,neutral or dissatisfied +4112,99079,Male,Loyal Customer,47,Business travel,Business,2794,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +4113,113863,Male,Loyal Customer,50,Business travel,Eco,992,4,3,3,3,4,4,4,4,5,2,2,3,2,4,0,0.0,satisfied +4114,69029,Female,Loyal Customer,54,Business travel,Business,1389,3,3,5,3,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +4115,9993,Male,Loyal Customer,12,Personal Travel,Eco,508,3,5,3,3,2,3,2,2,5,2,4,4,4,2,23,20.0,neutral or dissatisfied +4116,91808,Female,Loyal Customer,54,Personal Travel,Eco,590,2,5,2,2,2,4,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +4117,108664,Male,disloyal Customer,37,Business travel,Business,484,2,2,2,4,2,2,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +4118,93812,Male,Loyal Customer,39,Business travel,Business,391,4,4,4,4,4,5,5,4,4,4,4,4,4,3,14,4.0,satisfied +4119,51415,Male,Loyal Customer,34,Personal Travel,Eco Plus,209,3,2,0,3,3,0,3,3,1,1,2,3,2,3,5,7.0,neutral or dissatisfied +4120,39299,Male,Loyal Customer,8,Personal Travel,Eco,67,1,5,1,2,2,1,2,2,4,4,4,3,5,2,23,38.0,neutral or dissatisfied +4121,57467,Male,Loyal Customer,65,Personal Travel,Eco,334,2,4,2,3,4,2,4,4,4,2,4,3,4,4,23,9.0,neutral or dissatisfied +4122,50266,Female,Loyal Customer,36,Business travel,Business,2615,4,3,3,3,4,3,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +4123,83172,Female,Loyal Customer,35,Business travel,Eco Plus,1127,2,4,5,4,2,2,2,2,1,4,2,4,1,2,0,0.0,neutral or dissatisfied +4124,41986,Female,Loyal Customer,40,Business travel,Business,116,3,2,2,2,5,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +4125,87037,Female,disloyal Customer,22,Business travel,Business,594,4,3,4,1,3,4,3,3,4,5,4,3,4,3,27,34.0,satisfied +4126,100787,Male,Loyal Customer,12,Personal Travel,Eco,1411,1,5,1,1,4,1,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +4127,13645,Male,Loyal Customer,61,Business travel,Business,196,0,5,0,5,5,1,2,5,5,5,5,1,5,1,3,0.0,satisfied +4128,106014,Female,Loyal Customer,42,Business travel,Business,1999,5,5,5,5,2,5,4,5,5,5,5,5,5,5,7,1.0,satisfied +4129,121625,Female,Loyal Customer,55,Personal Travel,Eco,912,3,4,3,1,3,5,5,2,2,3,1,5,2,3,15,4.0,neutral or dissatisfied +4130,53675,Female,Loyal Customer,25,Business travel,Business,3966,3,3,3,3,2,2,2,2,4,5,4,1,5,2,12,3.0,satisfied +4131,46798,Female,Loyal Customer,26,Personal Travel,Business,845,4,4,4,2,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +4132,70369,Female,disloyal Customer,57,Business travel,Eco,1145,2,2,2,3,3,2,3,3,3,2,3,2,4,3,0,0.0,neutral or dissatisfied +4133,53524,Female,Loyal Customer,23,Personal Travel,Eco,2288,1,5,1,2,1,2,2,3,4,1,2,2,4,2,196,178.0,neutral or dissatisfied +4134,109228,Female,Loyal Customer,57,Personal Travel,Eco,684,4,4,4,3,5,4,5,4,4,4,4,4,4,3,41,30.0,neutral or dissatisfied +4135,26059,Female,Loyal Customer,47,Personal Travel,Eco,432,3,5,3,3,5,5,5,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +4136,31333,Male,Loyal Customer,24,Business travel,Eco,1062,0,5,0,3,2,0,2,2,2,2,3,2,1,2,87,101.0,satisfied +4137,82983,Male,Loyal Customer,53,Business travel,Business,1127,5,5,3,5,3,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +4138,48445,Female,Loyal Customer,54,Business travel,Eco,850,3,2,2,2,4,1,1,4,4,3,4,4,4,4,65,55.0,satisfied +4139,101829,Female,Loyal Customer,21,Personal Travel,Eco,1521,3,5,3,3,5,3,5,5,4,4,4,3,5,5,3,0.0,neutral or dissatisfied +4140,86096,Female,Loyal Customer,59,Business travel,Business,3611,5,3,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +4141,102147,Male,Loyal Customer,55,Business travel,Business,2056,3,3,3,3,5,4,5,4,4,4,4,5,4,4,9,0.0,satisfied +4142,14045,Female,Loyal Customer,36,Business travel,Business,3270,2,4,4,4,5,4,3,2,2,2,2,3,2,1,44,43.0,neutral or dissatisfied +4143,8745,Male,Loyal Customer,51,Personal Travel,Eco Plus,181,2,5,2,2,5,2,2,5,1,1,4,4,5,5,0,11.0,neutral or dissatisfied +4144,24687,Male,Loyal Customer,40,Business travel,Business,2562,4,4,4,4,4,3,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +4145,101364,Female,disloyal Customer,27,Business travel,Eco,1986,2,2,2,3,3,2,2,3,2,2,3,4,3,3,69,43.0,neutral or dissatisfied +4146,30894,Male,Loyal Customer,69,Personal Travel,Eco,973,1,5,1,3,4,1,4,4,4,5,5,3,5,4,40,58.0,neutral or dissatisfied +4147,7513,Female,Loyal Customer,47,Business travel,Business,2467,2,2,2,2,3,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +4148,126366,Male,Loyal Customer,16,Personal Travel,Eco,631,2,5,2,4,3,2,2,3,4,2,5,5,4,3,0,3.0,neutral or dissatisfied +4149,58044,Female,disloyal Customer,36,Business travel,Business,642,1,1,1,4,1,1,1,1,3,3,5,3,4,1,0,0.0,neutral or dissatisfied +4150,69651,Female,Loyal Customer,30,Business travel,Business,569,2,1,2,2,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +4151,92784,Male,Loyal Customer,62,Personal Travel,Eco,1671,3,4,3,4,1,3,3,1,3,1,4,1,3,1,12,2.0,neutral or dissatisfied +4152,119083,Female,Loyal Customer,57,Business travel,Business,1788,3,3,2,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +4153,17001,Male,Loyal Customer,24,Business travel,Business,2762,3,3,3,3,3,3,3,3,5,1,1,3,3,3,10,5.0,satisfied +4154,110304,Male,Loyal Customer,34,Business travel,Business,3248,2,2,2,2,2,5,5,4,4,4,4,3,4,5,18,0.0,satisfied +4155,27093,Male,Loyal Customer,24,Business travel,Business,1721,1,1,1,1,5,5,5,5,3,2,4,2,5,5,0,0.0,satisfied +4156,197,Male,Loyal Customer,56,Business travel,Business,2136,4,2,4,4,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +4157,112921,Female,disloyal Customer,16,Business travel,Eco,1313,3,3,3,5,2,3,2,2,4,1,5,1,2,2,0,0.0,neutral or dissatisfied +4158,31791,Male,Loyal Customer,41,Business travel,Eco,2677,4,2,2,2,4,4,4,3,2,3,5,4,4,4,0,0.0,satisfied +4159,65357,Male,Loyal Customer,47,Business travel,Business,3250,3,2,3,3,2,5,4,3,3,4,3,4,3,3,18,8.0,satisfied +4160,55683,Female,Loyal Customer,72,Business travel,Business,3408,3,3,3,3,4,5,4,5,5,5,5,5,5,5,6,0.0,satisfied +4161,38359,Female,Loyal Customer,30,Business travel,Business,1616,1,1,1,1,4,4,4,4,3,4,1,2,4,4,0,0.0,satisfied +4162,111347,Female,Loyal Customer,53,Business travel,Business,777,4,2,4,4,4,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +4163,45783,Male,Loyal Customer,29,Business travel,Business,2805,3,3,3,3,4,4,4,4,4,2,4,5,1,4,0,0.0,satisfied +4164,9895,Male,disloyal Customer,38,Business travel,Business,515,2,2,2,5,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +4165,13640,Female,Loyal Customer,24,Business travel,Business,2662,2,2,2,2,2,2,2,3,1,3,3,2,4,2,151,131.0,neutral or dissatisfied +4166,18512,Male,Loyal Customer,61,Business travel,Business,383,2,3,3,3,4,4,3,2,2,2,2,1,2,4,7,0.0,neutral or dissatisfied +4167,28462,Male,Loyal Customer,61,Personal Travel,Eco,2588,2,4,3,5,3,3,5,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +4168,30172,Female,Loyal Customer,49,Personal Travel,Eco,548,4,1,4,3,3,3,3,2,2,4,2,4,2,2,0,0.0,neutral or dissatisfied +4169,104641,Female,Loyal Customer,43,Business travel,Business,1754,4,4,4,4,2,5,4,3,3,4,3,5,3,5,0,28.0,satisfied +4170,115358,Male,Loyal Customer,23,Business travel,Business,3145,1,3,3,3,1,1,1,1,2,1,4,4,4,1,0,0.0,neutral or dissatisfied +4171,67557,Female,Loyal Customer,40,Business travel,Business,3444,1,1,1,1,2,5,5,4,4,4,4,5,4,3,32,21.0,satisfied +4172,122665,Female,Loyal Customer,49,Business travel,Business,361,2,3,3,3,2,3,3,2,2,2,2,1,2,2,6,0.0,neutral or dissatisfied +4173,66228,Female,Loyal Customer,31,Business travel,Business,550,2,3,3,3,2,2,2,2,1,3,3,3,4,2,0,0.0,neutral or dissatisfied +4174,14685,Male,Loyal Customer,45,Business travel,Business,479,5,5,5,5,4,2,1,5,5,5,5,1,5,1,37,13.0,satisfied +4175,3963,Female,Loyal Customer,40,Personal Travel,Eco,764,2,4,2,4,1,2,1,1,4,4,5,4,5,1,0,13.0,neutral or dissatisfied +4176,127957,Male,disloyal Customer,9,Business travel,Eco,855,4,3,3,3,1,4,1,1,2,3,3,4,3,1,1,0.0,neutral or dissatisfied +4177,11537,Male,Loyal Customer,46,Business travel,Business,3088,5,5,5,5,4,4,5,5,5,5,5,3,5,4,59,58.0,satisfied +4178,36359,Female,disloyal Customer,27,Business travel,Eco,200,4,2,5,5,4,5,4,4,1,1,5,1,1,4,80,90.0,satisfied +4179,109818,Female,Loyal Customer,51,Business travel,Business,1011,5,2,5,5,5,4,5,4,4,4,4,3,4,5,8,3.0,satisfied +4180,62651,Female,Loyal Customer,18,Personal Travel,Eco,1744,2,5,2,3,1,2,3,1,1,1,4,3,2,1,0,0.0,neutral or dissatisfied +4181,42111,Female,disloyal Customer,23,Business travel,Eco,964,4,3,3,4,3,3,3,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +4182,82579,Female,Loyal Customer,31,Business travel,Business,528,2,5,5,5,2,2,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +4183,84952,Male,Loyal Customer,43,Business travel,Business,2214,5,5,5,5,3,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +4184,111486,Female,Loyal Customer,15,Personal Travel,Eco,1452,4,3,4,4,4,4,4,4,3,1,3,3,4,4,0,0.0,satisfied +4185,85611,Female,Loyal Customer,23,Personal Travel,Eco,153,1,5,1,2,5,1,5,5,5,3,5,3,5,5,17,16.0,neutral or dissatisfied +4186,60189,Male,Loyal Customer,40,Business travel,Business,1577,1,1,5,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +4187,8082,Female,Loyal Customer,39,Business travel,Business,530,1,0,0,4,1,3,3,4,4,0,4,3,4,1,43,40.0,neutral or dissatisfied +4188,25684,Male,Loyal Customer,48,Business travel,Business,528,1,1,1,1,2,4,5,2,2,2,2,5,2,4,6,0.0,satisfied +4189,105327,Male,disloyal Customer,26,Business travel,Business,528,5,5,5,2,5,5,5,5,5,2,4,5,4,5,0,0.0,satisfied +4190,58588,Female,disloyal Customer,32,Business travel,Business,334,2,3,3,4,1,3,1,1,4,2,4,4,4,1,23,18.0,neutral or dissatisfied +4191,37927,Female,Loyal Customer,47,Personal Travel,Eco,937,3,4,3,1,1,1,3,3,3,3,3,4,3,2,8,7.0,neutral or dissatisfied +4192,25938,Male,Loyal Customer,8,Personal Travel,Eco,594,2,1,2,3,2,2,2,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +4193,61865,Female,disloyal Customer,27,Business travel,Business,1379,2,2,2,2,2,2,2,2,4,2,5,3,5,2,3,2.0,neutral or dissatisfied +4194,81562,Male,Loyal Customer,43,Business travel,Business,936,1,4,4,4,2,4,4,1,1,2,1,1,1,2,18,5.0,neutral or dissatisfied +4195,79979,Female,Loyal Customer,53,Personal Travel,Eco,1069,3,2,3,2,1,1,2,5,5,3,5,1,5,1,0,0.0,neutral or dissatisfied +4196,109539,Female,Loyal Customer,43,Personal Travel,Eco,873,2,4,2,3,4,3,4,4,4,2,4,5,4,5,10,1.0,neutral or dissatisfied +4197,18706,Female,disloyal Customer,25,Business travel,Eco Plus,190,2,4,2,1,4,2,5,4,3,1,2,4,3,4,0,0.0,neutral or dissatisfied +4198,77152,Female,Loyal Customer,47,Personal Travel,Eco,1865,3,3,3,2,5,5,5,1,1,3,1,2,1,3,0,0.0,neutral or dissatisfied +4199,112780,Female,Loyal Customer,59,Personal Travel,Eco,588,3,4,3,2,3,5,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +4200,98049,Female,Loyal Customer,17,Business travel,Business,1797,4,4,4,4,5,5,5,5,3,3,4,4,4,5,21,4.0,satisfied +4201,6575,Female,disloyal Customer,16,Business travel,Eco,607,5,2,5,3,2,5,2,2,3,5,4,5,5,2,0,0.0,satisfied +4202,112228,Female,Loyal Customer,57,Personal Travel,Eco,1199,1,4,1,4,4,3,3,1,1,1,1,2,1,4,108,110.0,neutral or dissatisfied +4203,93132,Female,Loyal Customer,43,Business travel,Business,1993,4,4,4,4,3,5,5,5,5,5,5,4,5,5,1,30.0,satisfied +4204,4762,Female,Loyal Customer,59,Business travel,Business,315,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +4205,51380,Female,Loyal Customer,39,Personal Travel,Eco Plus,447,3,4,3,5,4,3,4,4,5,2,5,5,5,4,68,120.0,neutral or dissatisfied +4206,88484,Male,disloyal Customer,21,Business travel,Eco,115,3,0,3,2,3,3,2,3,2,1,2,1,5,3,0,0.0,neutral or dissatisfied +4207,15000,Female,Loyal Customer,67,Business travel,Business,3230,2,2,2,2,2,4,3,5,5,5,5,4,5,4,0,0.0,satisfied +4208,100466,Female,Loyal Customer,37,Business travel,Business,2593,5,5,5,5,3,5,5,4,4,4,4,5,4,3,48,46.0,satisfied +4209,98297,Female,Loyal Customer,56,Personal Travel,Eco,1188,4,4,4,1,2,5,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +4210,129767,Female,Loyal Customer,9,Personal Travel,Eco,337,5,4,4,4,5,4,5,5,2,4,3,1,3,5,6,7.0,satisfied +4211,92955,Female,Loyal Customer,47,Business travel,Eco Plus,134,3,3,3,3,4,2,3,3,3,3,3,3,3,2,13,7.0,neutral or dissatisfied +4212,14156,Male,Loyal Customer,37,Business travel,Business,620,5,5,3,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +4213,70978,Male,Loyal Customer,20,Business travel,Business,2777,4,4,4,4,4,4,4,4,4,4,4,4,5,4,0,0.0,satisfied +4214,28550,Male,Loyal Customer,15,Personal Travel,Eco,2701,2,2,2,3,3,2,3,3,3,3,4,3,3,3,0,0.0,neutral or dissatisfied +4215,11954,Female,Loyal Customer,69,Personal Travel,Eco,781,2,5,2,4,3,4,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +4216,36676,Female,Loyal Customer,18,Personal Travel,Eco,1121,4,5,4,1,2,4,2,2,5,3,4,4,4,2,26,7.0,neutral or dissatisfied +4217,82203,Female,disloyal Customer,26,Business travel,Business,405,4,5,5,1,2,5,2,2,5,2,4,4,4,2,23,23.0,satisfied +4218,1249,Male,Loyal Customer,11,Personal Travel,Eco,282,2,1,2,3,4,2,4,4,4,1,4,4,4,4,10,12.0,neutral or dissatisfied +4219,89947,Female,Loyal Customer,34,Personal Travel,Eco,1416,2,2,3,3,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +4220,93387,Female,Loyal Customer,19,Business travel,Business,3791,5,5,5,5,5,4,5,5,5,3,4,4,4,5,10,1.0,satisfied +4221,66544,Male,Loyal Customer,61,Business travel,Business,328,3,1,1,1,5,2,3,3,3,3,3,2,3,2,91,88.0,neutral or dissatisfied +4222,129652,Male,Loyal Customer,50,Business travel,Business,1967,5,5,3,5,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4223,104772,Male,Loyal Customer,37,Business travel,Eco Plus,1246,1,2,3,2,1,1,1,1,2,5,4,4,4,1,0,6.0,neutral or dissatisfied +4224,81665,Female,disloyal Customer,30,Business travel,Eco,907,2,2,2,4,1,2,1,1,4,3,3,3,3,1,16,13.0,neutral or dissatisfied +4225,25274,Male,Loyal Customer,38,Business travel,Business,3387,2,1,1,1,2,3,4,2,2,2,2,3,2,4,0,11.0,neutral or dissatisfied +4226,68672,Male,Loyal Customer,74,Business travel,Business,2317,4,5,5,5,4,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +4227,73880,Female,disloyal Customer,22,Business travel,Eco,1213,4,5,5,3,5,5,5,5,4,5,5,3,5,5,7,0.0,satisfied +4228,123409,Male,Loyal Customer,53,Business travel,Business,1337,1,1,1,1,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +4229,29357,Female,Loyal Customer,54,Business travel,Eco,2409,5,4,4,4,5,5,4,5,5,5,5,4,5,5,23,21.0,satisfied +4230,80788,Male,Loyal Customer,33,Business travel,Business,484,4,4,4,4,4,4,4,4,3,5,5,4,5,4,2,0.0,satisfied +4231,50506,Female,Loyal Customer,44,Personal Travel,Eco,337,3,5,3,3,5,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +4232,66733,Male,Loyal Customer,44,Personal Travel,Eco,802,1,3,1,3,1,1,1,1,3,2,3,1,4,1,0,0.0,neutral or dissatisfied +4233,16108,Male,Loyal Customer,49,Business travel,Business,725,5,5,5,5,3,5,4,4,4,4,4,4,4,5,80,74.0,satisfied +4234,42107,Male,Loyal Customer,29,Business travel,Business,991,4,5,3,3,4,4,4,4,2,5,4,4,3,4,0,0.0,neutral or dissatisfied +4235,41169,Female,Loyal Customer,37,Business travel,Eco Plus,191,5,4,4,4,5,5,5,5,4,2,1,5,4,5,4,3.0,satisfied +4236,76765,Female,Loyal Customer,39,Business travel,Business,546,5,5,5,5,2,4,4,4,4,4,4,3,4,5,20,16.0,satisfied +4237,34808,Male,Loyal Customer,13,Personal Travel,Eco,301,1,5,3,3,5,3,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +4238,87027,Female,Loyal Customer,63,Personal Travel,Business,645,3,4,3,3,5,4,5,1,1,3,1,4,1,3,4,8.0,neutral or dissatisfied +4239,122917,Female,Loyal Customer,13,Personal Travel,Business,468,4,5,2,2,4,2,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +4240,110468,Female,Loyal Customer,9,Personal Travel,Eco,919,2,2,2,2,2,2,4,2,1,4,1,4,2,2,52,45.0,neutral or dissatisfied +4241,79252,Female,Loyal Customer,45,Business travel,Business,1598,2,2,2,2,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +4242,16408,Female,Loyal Customer,7,Personal Travel,Eco,533,1,5,1,1,3,1,3,3,5,4,5,3,5,3,7,3.0,neutral or dissatisfied +4243,63608,Male,Loyal Customer,49,Business travel,Business,1440,2,5,5,5,2,3,3,2,2,2,2,4,2,1,14,5.0,neutral or dissatisfied +4244,45118,Female,Loyal Customer,69,Personal Travel,Eco,157,1,5,1,2,3,5,5,3,3,1,3,5,3,4,4,8.0,neutral or dissatisfied +4245,59096,Female,Loyal Customer,37,Personal Travel,Eco,1726,4,1,4,3,2,4,2,2,3,4,4,2,3,2,0,0.0,neutral or dissatisfied +4246,73580,Male,Loyal Customer,51,Business travel,Business,3319,0,5,0,2,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +4247,57341,Male,disloyal Customer,16,Business travel,Business,414,5,0,5,5,1,5,1,1,4,5,4,5,4,1,0,0.0,satisfied +4248,54920,Female,Loyal Customer,7,Personal Travel,Eco Plus,862,3,4,3,3,1,3,1,1,4,4,4,4,5,1,21,29.0,neutral or dissatisfied +4249,116941,Female,Loyal Customer,54,Business travel,Business,2877,4,4,4,4,3,4,5,3,3,3,3,5,3,3,3,1.0,satisfied +4250,109498,Female,Loyal Customer,25,Business travel,Business,2630,2,2,1,2,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +4251,3036,Male,disloyal Customer,28,Business travel,Business,489,2,2,2,5,2,2,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +4252,102776,Male,Loyal Customer,26,Business travel,Eco,1099,4,3,3,3,4,4,2,4,4,4,3,4,3,4,63,59.0,neutral or dissatisfied +4253,118194,Female,disloyal Customer,79,Business travel,Eco,1044,2,1,1,3,2,1,5,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +4254,119994,Female,Loyal Customer,49,Business travel,Business,2833,3,5,5,5,2,4,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +4255,88731,Male,Loyal Customer,7,Personal Travel,Eco,406,4,4,4,2,4,4,1,4,3,4,4,4,4,4,0,9.0,neutral or dissatisfied +4256,66473,Male,disloyal Customer,37,Business travel,Business,447,3,3,3,2,1,3,1,1,1,5,2,3,2,1,0,0.0,neutral or dissatisfied +4257,96231,Female,Loyal Customer,26,Business travel,Eco,546,1,5,5,5,1,1,1,1,2,3,3,4,3,1,17,11.0,neutral or dissatisfied +4258,47437,Male,Loyal Customer,41,Business travel,Eco,588,5,2,2,2,5,5,5,5,3,5,5,5,2,5,4,0.0,satisfied +4259,54087,Male,Loyal Customer,48,Personal Travel,Eco,1416,2,4,2,5,2,2,2,5,5,5,5,2,5,2,161,147.0,neutral or dissatisfied +4260,9158,Female,Loyal Customer,56,Business travel,Eco,946,1,5,5,5,2,4,4,1,1,1,1,1,1,3,73,46.0,neutral or dissatisfied +4261,103246,Male,Loyal Customer,53,Business travel,Business,2173,3,3,3,3,4,5,5,4,4,4,4,4,4,4,32,31.0,satisfied +4262,100375,Male,Loyal Customer,36,Personal Travel,Eco,971,2,4,2,3,3,2,3,3,5,3,5,5,5,3,0,4.0,neutral or dissatisfied +4263,15603,Male,Loyal Customer,38,Business travel,Business,3386,4,4,4,4,4,2,5,5,5,5,5,1,5,3,0,0.0,satisfied +4264,65526,Female,Loyal Customer,21,Personal Travel,Eco,1616,2,4,1,3,1,1,5,1,3,5,3,4,5,1,60,67.0,neutral or dissatisfied +4265,106039,Female,disloyal Customer,40,Business travel,Business,452,4,4,4,4,3,4,3,3,3,3,4,5,4,3,5,0.0,satisfied +4266,84437,Male,Loyal Customer,29,Business travel,Business,2500,1,1,1,1,5,5,5,5,3,3,5,3,5,5,4,2.0,satisfied +4267,76261,Female,Loyal Customer,43,Personal Travel,Eco Plus,1399,2,5,2,3,3,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +4268,68504,Male,Loyal Customer,64,Personal Travel,Eco,1303,4,5,5,1,1,5,1,1,3,4,5,3,5,1,18,6.0,neutral or dissatisfied +4269,85759,Male,Loyal Customer,40,Business travel,Business,2548,5,5,5,5,5,4,5,3,3,2,3,3,3,5,79,62.0,satisfied +4270,102388,Male,Loyal Customer,49,Business travel,Business,391,1,1,1,1,5,5,3,3,3,3,3,5,3,1,50,57.0,satisfied +4271,121331,Female,disloyal Customer,39,Business travel,Business,1009,1,1,1,4,1,1,1,1,2,2,3,2,3,1,0,1.0,neutral or dissatisfied +4272,51783,Male,Loyal Customer,9,Personal Travel,Eco,237,4,5,0,4,4,0,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +4273,128343,Male,Loyal Customer,48,Business travel,Business,647,4,4,4,4,4,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +4274,85433,Female,disloyal Customer,20,Business travel,Eco,214,1,0,0,4,1,0,1,1,4,4,4,5,5,1,34,27.0,neutral or dissatisfied +4275,21123,Male,Loyal Customer,60,Personal Travel,Eco,227,5,5,5,3,1,5,1,1,5,2,5,4,5,1,0,0.0,satisfied +4276,112585,Female,Loyal Customer,15,Business travel,Business,602,3,3,3,3,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +4277,113932,Female,disloyal Customer,30,Business travel,Business,1855,3,3,3,5,4,3,5,4,3,3,3,3,4,4,3,1.0,neutral or dissatisfied +4278,117116,Male,Loyal Customer,71,Business travel,Business,3571,1,1,1,1,4,2,5,5,5,5,5,5,5,5,0,0.0,satisfied +4279,60388,Female,Loyal Customer,33,Business travel,Business,1452,4,4,4,4,4,4,3,4,4,4,4,3,4,2,100,109.0,neutral or dissatisfied +4280,84819,Female,disloyal Customer,36,Business travel,Business,547,1,1,1,3,2,1,2,2,4,3,5,4,4,2,0,0.0,neutral or dissatisfied +4281,108712,Female,Loyal Customer,56,Business travel,Business,2383,3,3,3,3,4,4,4,5,5,5,5,3,5,4,3,8.0,satisfied +4282,82275,Female,Loyal Customer,39,Business travel,Eco,1481,2,2,2,2,2,2,2,2,2,3,4,2,3,2,3,6.0,neutral or dissatisfied +4283,15618,Male,Loyal Customer,45,Personal Travel,Eco,228,4,3,4,3,2,4,2,2,3,4,4,3,3,2,0,0.0,neutral or dissatisfied +4284,46832,Female,disloyal Customer,52,Business travel,Eco,776,2,3,3,3,1,3,1,1,5,4,3,3,2,1,3,0.0,neutral or dissatisfied +4285,89524,Male,Loyal Customer,64,Personal Travel,Business,950,5,5,5,2,3,4,5,1,1,5,1,4,1,1,3,0.0,satisfied +4286,115029,Male,disloyal Customer,23,Business travel,Eco,447,1,5,1,1,5,1,5,5,5,4,4,3,4,5,0,0.0,neutral or dissatisfied +4287,77536,Male,Loyal Customer,22,Business travel,Business,986,1,1,1,1,3,3,3,3,3,5,5,5,5,3,0,4.0,satisfied +4288,28016,Male,Loyal Customer,60,Business travel,Eco,763,2,2,2,2,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +4289,21118,Female,Loyal Customer,21,Personal Travel,Eco,106,0,5,0,2,4,0,4,4,3,4,4,5,4,4,0,11.0,satisfied +4290,76858,Female,Loyal Customer,22,Personal Travel,Eco,1195,4,2,4,3,4,4,4,4,2,3,2,3,4,4,0,8.0,neutral or dissatisfied +4291,38842,Male,Loyal Customer,22,Business travel,Eco Plus,387,5,1,1,1,5,5,3,5,2,4,5,2,3,5,0,0.0,satisfied +4292,40771,Male,Loyal Customer,33,Business travel,Business,584,4,4,4,4,5,5,5,5,4,2,3,4,1,5,0,0.0,satisfied +4293,115002,Male,Loyal Customer,29,Business travel,Business,3223,2,2,2,2,5,5,5,5,3,3,4,4,5,5,0,0.0,satisfied +4294,111314,Female,disloyal Customer,22,Business travel,Eco,283,3,0,3,1,1,3,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +4295,87846,Male,Loyal Customer,61,Personal Travel,Eco,214,1,3,1,4,4,1,4,4,5,4,3,3,4,4,0,0.0,neutral or dissatisfied +4296,66038,Female,Loyal Customer,52,Business travel,Business,1345,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +4297,111907,Female,Loyal Customer,50,Business travel,Business,628,4,4,5,4,2,5,5,4,4,4,4,3,4,3,9,17.0,satisfied +4298,4508,Female,Loyal Customer,27,Personal Travel,Eco,551,3,4,3,3,2,3,2,2,1,5,4,1,4,2,0,0.0,neutral or dissatisfied +4299,104707,Female,Loyal Customer,19,Business travel,Eco Plus,159,3,4,4,4,3,3,3,3,3,5,4,4,3,3,0,0.0,neutral or dissatisfied +4300,30104,Female,Loyal Customer,7,Personal Travel,Eco,261,3,1,3,2,2,3,2,2,1,1,2,2,3,2,0,0.0,neutral or dissatisfied +4301,86775,Female,Loyal Customer,44,Business travel,Business,484,1,0,0,4,1,4,3,2,2,0,2,2,2,2,0,0.0,neutral or dissatisfied +4302,28861,Female,Loyal Customer,48,Business travel,Business,1050,1,1,1,1,5,4,2,3,3,2,3,1,3,2,0,0.0,satisfied +4303,52653,Female,Loyal Customer,14,Personal Travel,Eco,160,1,5,1,3,4,1,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +4304,5957,Male,Loyal Customer,41,Business travel,Business,2937,4,4,4,4,1,4,3,4,4,4,4,2,4,2,42,37.0,neutral or dissatisfied +4305,39195,Female,Loyal Customer,45,Business travel,Eco,318,3,3,3,3,3,3,4,3,3,3,3,4,3,3,62,55.0,neutral or dissatisfied +4306,60468,Male,Loyal Customer,33,Business travel,Business,862,3,3,3,3,2,2,2,2,3,4,4,3,5,2,3,0.0,satisfied +4307,123433,Male,disloyal Customer,12,Personal Travel,Business,2125,3,4,3,3,5,3,5,5,1,1,3,3,4,5,87,84.0,neutral or dissatisfied +4308,39676,Male,disloyal Customer,36,Business travel,Eco,717,1,1,1,4,1,1,2,1,2,1,4,2,3,1,0,8.0,neutral or dissatisfied +4309,5482,Female,Loyal Customer,59,Business travel,Business,910,1,1,1,1,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +4310,90208,Male,Loyal Customer,69,Personal Travel,Eco,1084,2,3,2,3,2,2,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +4311,43910,Male,Loyal Customer,68,Personal Travel,Eco,199,5,5,5,4,5,5,1,5,3,4,4,4,4,5,0,0.0,satisfied +4312,90029,Female,disloyal Customer,14,Business travel,Business,1145,0,0,0,5,2,0,2,2,5,4,5,4,4,2,18,19.0,satisfied +4313,120049,Male,disloyal Customer,22,Business travel,Business,356,4,0,3,5,5,3,5,5,5,4,5,4,4,5,0,2.0,satisfied +4314,39092,Male,Loyal Customer,28,Business travel,Eco,984,5,1,1,1,5,5,5,5,4,3,4,1,4,5,5,0.0,satisfied +4315,38568,Female,Loyal Customer,18,Personal Travel,Eco,2465,2,4,2,5,1,2,1,1,3,3,5,5,5,1,0,2.0,neutral or dissatisfied +4316,99422,Female,Loyal Customer,57,Personal Travel,Eco,337,1,4,5,2,4,5,5,4,4,5,4,5,4,3,72,70.0,neutral or dissatisfied +4317,115858,Female,disloyal Customer,50,Business travel,Eco,480,2,0,2,4,4,2,4,4,1,3,1,1,5,4,1,0.0,neutral or dissatisfied +4318,119908,Male,Loyal Customer,31,Personal Travel,Eco Plus,912,3,5,3,1,3,3,3,3,3,2,1,1,3,3,0,0.0,neutral or dissatisfied +4319,55481,Female,Loyal Customer,40,Business travel,Business,2434,1,1,1,1,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +4320,82231,Male,Loyal Customer,39,Business travel,Business,3987,3,1,1,1,3,3,3,4,2,1,1,3,1,3,144,158.0,neutral or dissatisfied +4321,56503,Female,disloyal Customer,23,Business travel,Business,997,0,0,0,4,3,0,3,3,4,3,4,4,4,3,3,42.0,satisfied +4322,129119,Female,disloyal Customer,26,Business travel,Business,954,3,3,3,4,5,3,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +4323,95676,Female,Loyal Customer,52,Business travel,Business,237,5,5,5,5,3,5,5,5,5,5,5,3,5,5,41,53.0,satisfied +4324,80473,Male,Loyal Customer,34,Personal Travel,Eco,1299,4,4,4,5,1,4,1,1,5,2,3,4,4,1,0,0.0,satisfied +4325,80205,Male,Loyal Customer,43,Business travel,Eco Plus,2586,1,5,5,5,1,1,1,2,2,4,3,1,2,1,7,18.0,neutral or dissatisfied +4326,128845,Female,Loyal Customer,9,Personal Travel,Eco,2475,4,2,4,3,4,5,5,1,5,2,3,5,3,5,0,0.0,neutral or dissatisfied +4327,62278,Female,Loyal Customer,43,Business travel,Business,3596,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +4328,4712,Male,Loyal Customer,66,Business travel,Eco Plus,364,5,5,5,5,5,5,5,5,4,2,1,1,1,5,0,0.0,satisfied +4329,116809,Male,Loyal Customer,37,Business travel,Eco Plus,417,2,5,5,5,2,2,2,2,3,4,3,4,4,2,7,14.0,neutral or dissatisfied +4330,69497,Female,Loyal Customer,29,Personal Travel,Eco Plus,1096,3,3,3,3,5,3,5,5,3,2,3,2,4,5,0,0.0,neutral or dissatisfied +4331,29272,Female,disloyal Customer,33,Business travel,Eco,550,3,4,3,4,1,3,1,1,5,1,1,2,2,1,0,0.0,neutral or dissatisfied +4332,54054,Female,disloyal Customer,31,Business travel,Eco,1416,4,4,4,3,1,4,1,1,2,3,1,2,3,1,2,0.0,neutral or dissatisfied +4333,62104,Female,Loyal Customer,7,Personal Travel,Business,2454,3,4,3,5,5,3,5,5,4,4,4,5,1,5,2,0.0,neutral or dissatisfied +4334,67484,Male,Loyal Customer,22,Personal Travel,Eco,641,2,3,2,3,5,2,4,5,3,1,3,4,2,5,5,0.0,neutral or dissatisfied +4335,2988,Male,disloyal Customer,34,Business travel,Business,862,3,3,3,2,5,3,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +4336,122225,Female,disloyal Customer,12,Business travel,Eco,573,4,0,4,2,4,4,2,4,5,4,5,5,5,4,20,5.0,neutral or dissatisfied +4337,51470,Male,Loyal Customer,60,Business travel,Eco Plus,250,3,2,2,2,3,3,3,3,2,3,4,2,2,3,0,0.0,satisfied +4338,117502,Male,Loyal Customer,23,Personal Travel,Eco,507,1,5,1,4,1,1,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +4339,116518,Female,Loyal Customer,38,Personal Travel,Eco,371,5,1,5,3,5,5,5,5,4,4,1,3,3,5,0,0.0,satisfied +4340,89380,Female,Loyal Customer,59,Business travel,Business,151,4,4,4,4,3,5,5,5,5,5,4,4,5,3,0,0.0,satisfied +4341,95262,Female,Loyal Customer,55,Personal Travel,Eco,239,1,4,1,3,2,4,4,3,3,1,3,2,3,1,31,11.0,neutral or dissatisfied +4342,86602,Female,disloyal Customer,36,Business travel,Business,746,2,2,2,4,4,2,4,4,5,5,5,5,5,4,16,0.0,neutral or dissatisfied +4343,63462,Female,disloyal Customer,58,Business travel,Eco Plus,337,4,3,3,2,3,4,3,3,2,3,3,4,3,3,0,0.0,neutral or dissatisfied +4344,69839,Male,Loyal Customer,65,Business travel,Business,655,5,5,5,5,3,2,3,4,4,4,4,4,4,1,0,0.0,satisfied +4345,28130,Male,Loyal Customer,54,Business travel,Eco,550,3,2,2,2,3,3,3,3,4,5,3,4,2,3,0,0.0,neutral or dissatisfied +4346,95110,Female,Loyal Customer,47,Personal Travel,Eco,239,2,4,2,2,3,4,4,5,5,2,5,4,5,3,0,13.0,neutral or dissatisfied +4347,103811,Female,Loyal Customer,48,Business travel,Business,3161,2,2,2,2,2,4,4,4,4,4,4,4,4,5,16,0.0,satisfied +4348,7871,Female,Loyal Customer,55,Business travel,Business,948,4,4,4,4,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +4349,43544,Female,Loyal Customer,22,Business travel,Business,3641,2,3,3,3,2,1,2,2,1,1,4,4,3,2,0,13.0,neutral or dissatisfied +4350,96191,Male,Loyal Customer,50,Business travel,Business,3563,2,2,2,2,5,5,5,5,5,5,5,4,5,5,79,68.0,satisfied +4351,15851,Female,Loyal Customer,29,Business travel,Business,783,4,4,5,4,5,5,5,5,4,1,2,2,5,5,0,0.0,satisfied +4352,110783,Male,Loyal Customer,25,Business travel,Business,3491,2,5,5,5,2,2,2,2,4,3,3,4,4,2,90,72.0,neutral or dissatisfied +4353,4832,Female,Loyal Customer,42,Business travel,Business,500,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,1.0,satisfied +4354,9282,Male,Loyal Customer,45,Business travel,Eco,1201,1,2,2,2,1,1,1,1,4,2,3,1,4,1,0,0.0,neutral or dissatisfied +4355,8620,Male,Loyal Customer,50,Business travel,Business,280,2,2,2,2,2,4,4,4,4,4,4,4,4,3,9,21.0,satisfied +4356,7087,Female,Loyal Customer,52,Business travel,Business,2258,1,1,4,4,2,3,3,1,1,1,1,4,1,4,50,48.0,neutral or dissatisfied +4357,23640,Male,Loyal Customer,47,Personal Travel,Eco,793,1,4,1,1,5,1,3,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +4358,124559,Male,Loyal Customer,56,Business travel,Business,3118,2,2,2,2,4,5,5,4,4,4,4,3,4,4,5,0.0,satisfied +4359,12195,Male,Loyal Customer,51,Personal Travel,Eco Plus,1075,1,2,1,2,4,1,4,4,3,1,2,3,2,4,17,0.0,neutral or dissatisfied +4360,32006,Male,Loyal Customer,33,Personal Travel,Business,101,3,2,0,2,5,0,5,5,3,4,2,1,3,5,0,0.0,neutral or dissatisfied +4361,74445,Male,Loyal Customer,50,Business travel,Business,3091,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4362,12126,Male,Loyal Customer,49,Business travel,Eco Plus,852,5,2,2,2,5,5,5,5,4,2,2,3,1,5,0,2.0,satisfied +4363,8713,Male,Loyal Customer,62,Personal Travel,Eco,280,4,4,2,2,1,2,1,1,4,3,4,5,4,1,0,9.0,neutral or dissatisfied +4364,103539,Male,Loyal Customer,52,Business travel,Business,2439,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +4365,103897,Male,Loyal Customer,33,Business travel,Eco Plus,869,2,5,4,5,2,2,2,2,1,2,3,2,3,2,40,28.0,neutral or dissatisfied +4366,77043,Male,Loyal Customer,47,Business travel,Business,3829,1,1,1,1,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +4367,103532,Male,Loyal Customer,51,Business travel,Business,738,1,4,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +4368,81611,Male,Loyal Customer,43,Personal Travel,Eco,334,1,5,1,1,1,2,2,4,4,5,5,2,5,2,168,179.0,neutral or dissatisfied +4369,38525,Male,Loyal Customer,48,Business travel,Eco,2465,4,4,4,4,4,4,4,4,5,2,5,2,4,4,0,0.0,satisfied +4370,107026,Male,Loyal Customer,43,Business travel,Business,3001,4,4,5,4,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +4371,70413,Male,Loyal Customer,52,Personal Travel,Eco,1562,3,5,3,2,2,3,5,2,4,5,5,3,5,2,0,11.0,neutral or dissatisfied +4372,95079,Female,Loyal Customer,13,Personal Travel,Eco,319,2,2,2,4,5,2,5,5,1,5,4,2,3,5,0,0.0,neutral or dissatisfied +4373,60158,Male,Loyal Customer,46,Personal Travel,Eco,1182,1,4,1,4,1,1,1,1,4,1,4,3,3,1,2,0.0,neutral or dissatisfied +4374,44130,Female,Loyal Customer,30,Business travel,Business,198,4,4,4,4,5,5,5,5,3,5,5,4,3,5,0,0.0,satisfied +4375,4876,Male,Loyal Customer,52,Personal Travel,Eco,408,4,5,2,1,3,2,3,3,3,1,2,4,5,3,0,0.0,satisfied +4376,19796,Male,Loyal Customer,48,Personal Travel,Eco,667,3,2,4,2,5,4,5,5,4,4,3,4,3,5,0,0.0,neutral or dissatisfied +4377,26061,Male,Loyal Customer,74,Business travel,Eco Plus,432,3,2,3,2,3,3,3,3,1,4,4,1,4,3,13,12.0,neutral or dissatisfied +4378,127250,Female,Loyal Customer,52,Business travel,Business,3557,5,5,5,5,2,5,5,4,4,4,4,3,4,3,5,2.0,satisfied +4379,101247,Female,Loyal Customer,39,Business travel,Business,1587,3,3,3,3,5,3,5,5,5,5,5,3,5,5,0,0.0,satisfied +4380,56139,Male,Loyal Customer,45,Business travel,Business,1400,4,4,4,4,3,4,4,5,5,5,5,5,5,3,0,4.0,satisfied +4381,79990,Male,Loyal Customer,20,Personal Travel,Eco,950,2,1,2,4,1,2,4,1,2,4,2,3,3,1,0,0.0,neutral or dissatisfied +4382,29246,Male,disloyal Customer,37,Business travel,Eco,859,3,3,3,3,4,3,4,4,3,5,1,4,2,4,0,3.0,neutral or dissatisfied +4383,19188,Female,disloyal Customer,34,Business travel,Eco,542,1,0,2,3,4,2,4,4,5,4,2,2,4,4,2,9.0,neutral or dissatisfied +4384,98715,Male,Loyal Customer,33,Business travel,Eco Plus,834,2,3,3,3,2,2,2,2,3,1,2,1,3,2,0,4.0,neutral or dissatisfied +4385,38333,Female,Loyal Customer,41,Business travel,Business,1050,4,4,4,4,2,1,3,5,5,5,5,3,5,5,0,0.0,satisfied +4386,122679,Male,Loyal Customer,49,Business travel,Eco,361,1,4,4,4,1,1,1,1,4,1,2,3,2,1,0,0.0,neutral or dissatisfied +4387,57822,Male,Loyal Customer,40,Business travel,Eco,622,3,3,3,3,3,3,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +4388,116078,Male,Loyal Customer,42,Personal Travel,Eco,446,3,5,3,1,3,3,3,3,5,5,4,3,5,3,19,18.0,neutral or dissatisfied +4389,16341,Male,Loyal Customer,33,Business travel,Eco Plus,628,5,5,5,5,5,5,5,5,4,5,5,2,1,5,0,0.0,satisfied +4390,16585,Female,Loyal Customer,36,Personal Travel,Eco,1092,3,1,3,1,1,3,2,1,4,4,1,2,2,1,35,32.0,neutral or dissatisfied +4391,9866,Female,Loyal Customer,60,Business travel,Business,3724,5,5,5,5,3,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +4392,72388,Male,Loyal Customer,42,Business travel,Business,985,3,3,3,3,4,4,4,3,3,3,3,5,3,4,11,0.0,satisfied +4393,95352,Female,Loyal Customer,49,Personal Travel,Eco,277,3,4,3,3,1,4,3,2,2,3,2,2,2,4,0,0.0,neutral or dissatisfied +4394,64418,Male,Loyal Customer,23,Personal Travel,Business,989,3,4,3,1,1,3,1,1,4,2,5,5,5,1,23,10.0,neutral or dissatisfied +4395,94233,Male,disloyal Customer,37,Business travel,Business,189,3,3,3,4,2,3,2,2,4,4,4,5,4,2,16,4.0,neutral or dissatisfied +4396,10974,Female,disloyal Customer,42,Business travel,Eco,224,2,0,1,2,2,1,2,2,1,5,5,4,1,2,2,4.0,neutral or dissatisfied +4397,122670,Female,Loyal Customer,44,Business travel,Business,361,5,5,5,5,4,4,5,4,4,4,4,4,4,4,22,17.0,satisfied +4398,5762,Male,Loyal Customer,42,Personal Travel,Eco,859,1,4,1,4,3,1,4,3,1,3,3,3,4,3,15,0.0,neutral or dissatisfied +4399,116017,Female,Loyal Customer,65,Personal Travel,Eco,417,2,2,2,1,3,1,2,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +4400,128882,Female,Loyal Customer,25,Business travel,Business,2454,3,2,2,2,3,3,3,1,3,4,3,3,4,3,39,16.0,neutral or dissatisfied +4401,38308,Female,Loyal Customer,36,Personal Travel,Eco,2583,2,1,2,3,2,5,2,3,3,2,4,2,2,2,0,23.0,neutral or dissatisfied +4402,84789,Female,disloyal Customer,38,Business travel,Business,547,4,5,5,1,4,5,4,4,5,5,5,3,5,4,7,0.0,satisfied +4403,65899,Female,disloyal Customer,23,Business travel,Business,569,5,5,5,3,5,5,5,5,3,2,5,4,5,5,0,16.0,satisfied +4404,5448,Male,Loyal Customer,24,Business travel,Business,1809,3,3,3,3,3,3,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +4405,94369,Female,Loyal Customer,39,Business travel,Business,3609,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,1.0,satisfied +4406,118344,Male,Loyal Customer,27,Personal Travel,Eco,639,1,5,1,3,3,1,3,3,4,3,4,4,4,3,0,24.0,neutral or dissatisfied +4407,58164,Female,Loyal Customer,41,Business travel,Business,2092,2,2,2,2,4,4,4,4,4,4,4,5,4,4,13,12.0,satisfied +4408,25554,Male,Loyal Customer,53,Personal Travel,Eco Plus,481,2,4,2,4,1,2,1,1,1,4,4,1,4,1,0,0.0,neutral or dissatisfied +4409,93296,Female,Loyal Customer,29,Business travel,Eco Plus,867,1,3,3,3,1,1,1,1,1,1,3,1,3,1,0,0.0,neutral or dissatisfied +4410,105224,Female,disloyal Customer,22,Business travel,Eco,377,3,4,3,3,3,3,3,3,3,4,4,3,5,3,89,69.0,neutral or dissatisfied +4411,114110,Male,Loyal Customer,47,Business travel,Business,3871,1,1,1,1,2,4,4,4,4,4,4,4,4,4,14,7.0,satisfied +4412,26521,Male,Loyal Customer,40,Business travel,Business,3151,5,5,5,5,5,1,1,4,4,5,4,5,4,4,33,21.0,satisfied +4413,64448,Male,Loyal Customer,22,Business travel,Business,989,2,4,4,4,2,2,2,2,3,1,3,1,4,2,1,6.0,neutral or dissatisfied +4414,111171,Female,Loyal Customer,42,Business travel,Business,1506,2,3,3,3,2,4,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +4415,14592,Male,Loyal Customer,10,Personal Travel,Eco,1021,2,5,2,5,4,2,4,4,2,2,1,1,5,4,37,25.0,neutral or dissatisfied +4416,46664,Female,Loyal Customer,52,Business travel,Business,2686,5,3,5,5,4,1,2,5,5,4,5,5,5,1,0,0.0,satisfied +4417,34573,Male,Loyal Customer,52,Business travel,Eco,1598,2,5,2,5,1,2,1,1,5,1,4,4,4,1,0,0.0,satisfied +4418,65764,Female,Loyal Customer,20,Personal Travel,Eco,936,3,3,3,3,1,3,3,1,2,3,3,3,3,1,1,14.0,neutral or dissatisfied +4419,62156,Female,Loyal Customer,45,Business travel,Business,2565,1,1,3,1,4,4,5,5,5,5,5,4,5,4,11,2.0,satisfied +4420,128543,Female,Loyal Customer,22,Business travel,Business,651,3,3,3,3,4,4,4,4,3,2,4,5,4,4,2,0.0,satisfied +4421,72672,Female,Loyal Customer,52,Personal Travel,Eco,1121,3,1,3,2,5,2,2,1,1,3,1,3,1,2,0,0.0,neutral or dissatisfied +4422,73330,Female,Loyal Customer,64,Business travel,Eco,1182,2,4,4,4,2,3,3,1,1,2,1,2,1,2,94,86.0,neutral or dissatisfied +4423,47272,Male,disloyal Customer,35,Business travel,Eco,588,3,4,3,1,4,3,4,4,5,3,1,2,1,4,0,3.0,neutral or dissatisfied +4424,112255,Male,Loyal Customer,44,Business travel,Business,1546,2,2,2,2,3,5,4,4,4,4,4,5,4,4,84,83.0,satisfied +4425,66301,Female,Loyal Customer,45,Business travel,Business,852,1,1,1,1,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +4426,115948,Female,Loyal Customer,17,Personal Travel,Eco,371,3,0,3,3,4,3,4,4,5,2,4,3,4,4,18,11.0,neutral or dissatisfied +4427,73537,Male,disloyal Customer,21,Business travel,Business,594,5,0,5,2,5,5,5,5,5,3,5,4,4,5,0,0.0,satisfied +4428,121852,Female,Loyal Customer,41,Business travel,Eco,449,1,3,3,3,1,1,1,1,1,1,3,4,3,1,16,10.0,neutral or dissatisfied +4429,115414,Female,disloyal Customer,44,Business travel,Business,447,5,0,0,1,1,5,1,1,5,4,4,4,4,1,8,15.0,satisfied +4430,9363,Male,Loyal Customer,52,Business travel,Business,384,3,5,4,4,4,4,3,3,3,3,3,3,3,4,15,12.0,neutral or dissatisfied +4431,15684,Male,Loyal Customer,17,Business travel,Eco Plus,641,3,1,1,1,3,3,4,3,1,3,4,3,4,3,47,33.0,neutral or dissatisfied +4432,35845,Female,disloyal Customer,42,Business travel,Eco,1065,1,1,1,2,2,1,2,2,1,4,4,3,4,2,0,4.0,neutral or dissatisfied +4433,119016,Male,Loyal Customer,48,Business travel,Business,1460,3,3,3,3,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +4434,127548,Female,Loyal Customer,65,Personal Travel,Eco,1009,2,5,2,2,4,4,4,3,3,2,3,4,3,4,0,14.0,neutral or dissatisfied +4435,49178,Male,Loyal Customer,58,Business travel,Eco,304,3,3,3,3,3,3,3,3,3,2,4,4,4,3,0,0.0,satisfied +4436,41564,Male,disloyal Customer,21,Business travel,Eco,811,2,2,2,2,4,2,4,4,4,4,1,3,2,4,30,30.0,neutral or dissatisfied +4437,82657,Female,disloyal Customer,34,Business travel,Eco,120,2,1,2,4,2,5,3,3,2,4,3,3,1,3,141,141.0,neutral or dissatisfied +4438,86546,Male,Loyal Customer,44,Business travel,Business,1578,4,4,3,4,5,4,5,5,5,5,5,4,5,5,57,47.0,satisfied +4439,61472,Female,Loyal Customer,38,Business travel,Business,2253,5,5,5,5,4,4,5,5,5,5,5,5,5,3,44,38.0,satisfied +4440,5560,Male,Loyal Customer,50,Business travel,Business,2203,3,5,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +4441,36730,Female,Loyal Customer,68,Personal Travel,Eco Plus,1211,4,2,4,3,1,2,4,3,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +4442,58933,Male,Loyal Customer,44,Personal Travel,Eco,888,3,4,3,4,3,3,3,3,5,3,5,5,5,3,12,14.0,neutral or dissatisfied +4443,90149,Female,Loyal Customer,37,Business travel,Business,3644,4,4,4,4,2,5,5,4,4,4,4,4,4,4,0,12.0,satisfied +4444,92294,Female,Loyal Customer,54,Business travel,Business,1814,4,4,4,4,5,4,5,5,5,5,5,5,5,4,11,0.0,satisfied +4445,114568,Female,Loyal Customer,65,Personal Travel,Business,362,1,4,1,2,3,5,4,5,5,1,5,4,5,4,20,6.0,neutral or dissatisfied +4446,46275,Female,Loyal Customer,7,Personal Travel,Eco,594,1,5,1,2,1,1,1,1,2,4,1,1,5,1,0,0.0,neutral or dissatisfied +4447,62616,Female,Loyal Customer,45,Personal Travel,Eco,1744,3,2,3,4,1,2,4,2,2,3,2,4,2,2,0,0.0,neutral or dissatisfied +4448,38097,Male,Loyal Customer,29,Business travel,Eco,1237,1,4,2,4,1,1,1,1,1,3,4,4,3,1,19,10.0,neutral or dissatisfied +4449,67677,Female,Loyal Customer,43,Business travel,Business,2946,1,1,1,1,4,5,4,3,3,3,3,4,3,5,0,2.0,satisfied +4450,81186,Male,disloyal Customer,54,Business travel,Eco,580,3,0,3,1,3,3,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +4451,98026,Female,disloyal Customer,22,Business travel,Eco,1014,3,2,2,2,3,2,3,3,4,4,3,3,2,3,94,111.0,neutral or dissatisfied +4452,23244,Male,Loyal Customer,56,Business travel,Business,3831,3,2,2,2,4,1,1,3,3,3,3,3,3,3,6,7.0,neutral or dissatisfied +4453,80712,Female,Loyal Customer,33,Business travel,Business,920,3,3,5,3,2,5,4,1,1,2,1,3,1,3,0,5.0,satisfied +4454,70783,Male,Loyal Customer,46,Business travel,Business,3866,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +4455,87361,Male,Loyal Customer,50,Business travel,Business,425,4,4,4,4,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +4456,57182,Male,Loyal Customer,52,Personal Travel,Eco,2227,3,4,3,5,3,3,3,3,4,2,5,4,5,3,44,42.0,neutral or dissatisfied +4457,22535,Male,Loyal Customer,66,Personal Travel,Eco Plus,143,1,5,1,2,1,1,1,1,5,3,3,2,2,1,71,54.0,neutral or dissatisfied +4458,75538,Female,Loyal Customer,50,Business travel,Business,337,0,0,0,1,2,5,4,2,2,2,2,5,2,5,22,52.0,satisfied +4459,2180,Female,Loyal Customer,27,Business travel,Eco,685,1,3,3,3,1,1,1,1,2,1,3,2,4,1,12,31.0,neutral or dissatisfied +4460,37778,Male,Loyal Customer,45,Business travel,Eco Plus,1035,5,2,2,2,5,5,5,2,2,3,4,5,4,5,197,174.0,satisfied +4461,99279,Female,Loyal Customer,16,Business travel,Eco,935,3,2,2,2,3,2,3,3,1,3,4,4,4,3,34,29.0,neutral or dissatisfied +4462,655,Male,Loyal Customer,47,Business travel,Business,2556,0,5,0,3,4,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +4463,15838,Male,disloyal Customer,48,Business travel,Business,1107,1,1,1,3,1,1,2,4,2,4,4,2,5,2,255,236.0,neutral or dissatisfied +4464,65684,Male,Loyal Customer,15,Personal Travel,Eco,1021,1,2,1,3,2,1,1,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +4465,75070,Male,Loyal Customer,45,Business travel,Business,2611,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +4466,8061,Male,Loyal Customer,80,Business travel,Eco,402,3,2,2,2,3,3,3,3,4,4,3,4,2,3,71,69.0,neutral or dissatisfied +4467,79545,Male,Loyal Customer,39,Business travel,Business,762,4,2,4,4,5,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +4468,80037,Female,Loyal Customer,18,Personal Travel,Eco,1035,3,4,3,5,3,4,4,4,5,4,5,4,5,4,113,144.0,neutral or dissatisfied +4469,107874,Female,Loyal Customer,70,Personal Travel,Eco,228,2,4,2,3,3,4,3,4,4,2,4,5,4,4,123,107.0,neutral or dissatisfied +4470,4619,Female,Loyal Customer,37,Personal Travel,Eco,719,1,4,1,1,3,1,3,3,5,2,5,3,4,3,14,0.0,neutral or dissatisfied +4471,123637,Male,Loyal Customer,33,Business travel,Business,1899,3,2,3,3,4,4,5,4,5,2,5,5,4,4,0,0.0,satisfied +4472,6414,Female,Loyal Customer,59,Personal Travel,Eco,296,2,5,2,1,2,4,4,5,5,2,5,5,5,3,12,16.0,neutral or dissatisfied +4473,40054,Male,Loyal Customer,62,Personal Travel,Eco,926,4,5,3,1,5,3,1,5,4,3,5,4,4,5,48,82.0,neutral or dissatisfied +4474,122042,Male,Loyal Customer,60,Business travel,Business,2226,0,5,0,2,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +4475,61729,Male,Loyal Customer,37,Business travel,Eco,1009,4,4,1,1,4,4,4,4,3,3,5,2,4,4,19,0.0,satisfied +4476,122574,Female,Loyal Customer,21,Personal Travel,Business,728,1,4,1,4,3,1,3,3,4,4,3,1,4,3,0,0.0,neutral or dissatisfied +4477,85628,Female,Loyal Customer,61,Personal Travel,Eco,192,1,5,1,2,3,4,5,2,2,1,2,5,2,3,2,1.0,neutral or dissatisfied +4478,29419,Male,Loyal Customer,55,Business travel,Eco Plus,2417,3,1,2,1,3,3,3,1,2,1,3,3,2,3,0,4.0,neutral or dissatisfied +4479,9082,Male,Loyal Customer,36,Personal Travel,Eco,212,4,5,4,3,5,4,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +4480,121522,Female,Loyal Customer,44,Business travel,Business,3069,2,2,2,2,2,5,5,4,4,4,4,4,4,5,29,40.0,satisfied +4481,74274,Male,Loyal Customer,47,Business travel,Business,2288,5,5,5,5,5,5,5,4,4,5,4,5,4,3,86,65.0,satisfied +4482,24374,Female,disloyal Customer,29,Business travel,Eco,669,5,5,5,2,4,5,4,4,2,3,5,5,5,4,0,0.0,satisfied +4483,29053,Male,Loyal Customer,28,Personal Travel,Eco,937,1,2,1,3,5,1,5,5,4,4,4,1,4,5,8,0.0,neutral or dissatisfied +4484,35526,Male,Loyal Customer,42,Personal Travel,Eco,1056,4,5,4,3,4,4,4,4,4,1,3,4,1,4,16,27.0,neutral or dissatisfied +4485,85382,Female,Loyal Customer,35,Business travel,Business,152,1,2,2,2,3,2,1,4,4,4,1,1,4,2,0,19.0,neutral or dissatisfied +4486,102304,Female,Loyal Customer,55,Business travel,Business,407,3,3,4,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +4487,67725,Female,Loyal Customer,25,Business travel,Business,2273,2,3,3,3,2,2,2,2,4,1,4,4,3,2,34,37.0,neutral or dissatisfied +4488,95290,Female,Loyal Customer,18,Personal Travel,Eco,192,3,4,3,1,3,3,3,3,5,3,5,3,4,3,87,86.0,neutral or dissatisfied +4489,44996,Male,Loyal Customer,44,Business travel,Eco,359,1,4,2,4,1,1,1,1,1,2,2,2,3,1,0,0.0,neutral or dissatisfied +4490,68864,Female,Loyal Customer,45,Business travel,Business,2346,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +4491,125776,Male,Loyal Customer,43,Business travel,Business,1013,1,1,1,1,2,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +4492,79788,Female,Loyal Customer,48,Business travel,Business,1035,1,1,1,1,5,4,5,5,5,5,5,5,5,4,2,21.0,satisfied +4493,125227,Female,Loyal Customer,56,Business travel,Business,651,2,2,2,2,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +4494,90324,Male,Loyal Customer,40,Business travel,Business,250,3,3,5,3,5,5,5,4,4,4,4,4,4,3,5,25.0,satisfied +4495,107403,Male,Loyal Customer,27,Business travel,Business,725,3,3,3,3,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +4496,52240,Female,Loyal Customer,44,Business travel,Business,751,3,2,2,2,3,2,3,3,3,3,3,4,3,3,13,18.0,neutral or dissatisfied +4497,68897,Male,Loyal Customer,33,Business travel,Business,1680,2,4,4,4,2,2,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +4498,27738,Female,Loyal Customer,27,Business travel,Business,3772,1,1,1,1,4,4,4,4,3,5,5,1,3,4,42,54.0,satisfied +4499,72978,Female,disloyal Customer,29,Business travel,Eco,1096,1,1,1,4,5,1,5,5,3,1,4,1,4,5,58,36.0,neutral or dissatisfied +4500,34414,Female,Loyal Customer,22,Personal Travel,Eco,612,3,4,3,3,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +4501,22426,Male,Loyal Customer,38,Personal Travel,Eco,238,2,4,2,2,5,2,5,5,3,5,5,5,5,5,0,15.0,neutral or dissatisfied +4502,78330,Female,Loyal Customer,58,Business travel,Business,1547,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +4503,84446,Female,Loyal Customer,56,Business travel,Business,3184,3,1,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +4504,112591,Male,disloyal Customer,18,Business travel,Eco,602,5,2,5,3,3,5,3,3,3,2,4,5,5,3,0,0.0,satisfied +4505,21348,Female,Loyal Customer,34,Business travel,Business,3187,1,2,2,2,5,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +4506,101670,Male,Loyal Customer,26,Personal Travel,Eco,2106,3,2,3,4,3,3,3,3,1,3,3,1,3,3,101,94.0,neutral or dissatisfied +4507,97346,Male,Loyal Customer,54,Business travel,Business,872,1,2,2,2,4,3,3,1,1,1,1,3,1,3,2,0.0,neutral or dissatisfied +4508,118600,Female,Loyal Customer,58,Business travel,Business,2663,3,3,3,3,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +4509,41075,Female,Loyal Customer,34,Business travel,Business,216,4,3,4,4,5,2,1,5,5,5,5,2,5,2,0,2.0,satisfied +4510,22098,Male,Loyal Customer,37,Personal Travel,Eco,782,3,5,3,1,2,3,2,2,4,5,5,4,4,2,3,1.0,neutral or dissatisfied +4511,113719,Female,Loyal Customer,31,Personal Travel,Eco,236,4,4,4,2,4,4,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +4512,59295,Female,Loyal Customer,40,Personal Travel,Business,2399,3,5,3,4,4,3,4,4,4,3,2,3,4,5,7,0.0,neutral or dissatisfied +4513,29712,Female,Loyal Customer,46,Business travel,Business,2304,3,3,3,3,2,5,2,5,5,5,5,4,5,2,0,0.0,satisfied +4514,100637,Female,Loyal Customer,31,Business travel,Eco,349,3,2,2,2,3,3,3,3,2,1,1,3,2,3,0,9.0,neutral or dissatisfied +4515,18784,Male,Loyal Customer,50,Business travel,Business,3468,5,5,5,5,5,2,2,4,4,4,4,5,4,4,2,0.0,satisfied +4516,15719,Female,Loyal Customer,52,Business travel,Eco,419,4,4,4,4,4,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +4517,66181,Male,Loyal Customer,54,Business travel,Business,3954,4,4,5,4,4,4,4,5,5,5,5,5,5,3,11,15.0,satisfied +4518,25920,Male,Loyal Customer,29,Business travel,Business,594,5,5,5,5,4,4,4,4,2,5,5,3,4,4,0,0.0,satisfied +4519,128914,Female,Loyal Customer,51,Personal Travel,Eco,2248,2,5,1,3,2,4,5,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +4520,101331,Female,disloyal Customer,31,Business travel,Business,1771,3,3,3,3,3,3,3,3,4,4,5,4,4,3,15,0.0,neutral or dissatisfied +4521,110774,Male,Loyal Customer,56,Business travel,Business,1166,4,4,4,4,2,4,4,4,4,4,4,3,4,5,5,1.0,satisfied +4522,66221,Male,Loyal Customer,33,Business travel,Business,1589,3,2,2,2,3,3,3,3,3,4,4,2,4,3,0,0.0,neutral or dissatisfied +4523,3142,Male,Loyal Customer,41,Business travel,Eco,140,4,3,3,3,4,4,4,4,1,1,3,3,4,4,0,0.0,neutral or dissatisfied +4524,93107,Male,Loyal Customer,49,Business travel,Business,1655,2,2,1,2,3,5,4,2,2,2,2,3,2,3,1,4.0,satisfied +4525,84776,Female,Loyal Customer,27,Business travel,Business,1703,5,5,5,5,5,5,5,5,3,5,4,5,4,5,10,0.0,satisfied +4526,83143,Female,Loyal Customer,30,Personal Travel,Eco,957,1,2,2,3,3,2,3,3,4,3,4,2,4,3,0,9.0,neutral or dissatisfied +4527,23519,Male,Loyal Customer,32,Personal Travel,Eco,349,1,4,5,3,2,5,2,2,4,3,5,3,5,2,3,0.0,neutral or dissatisfied +4528,24063,Male,Loyal Customer,41,Business travel,Eco Plus,562,4,5,5,5,4,4,4,4,2,3,5,1,2,4,62,46.0,satisfied +4529,125623,Female,Loyal Customer,54,Business travel,Business,2399,4,4,2,4,4,5,4,5,5,5,5,4,5,3,21,19.0,satisfied +4530,49920,Male,disloyal Customer,54,Business travel,Eco,77,4,0,4,1,5,4,5,5,5,4,5,2,5,5,0,0.0,neutral or dissatisfied +4531,48070,Male,Loyal Customer,51,Business travel,Business,259,1,1,1,1,1,4,4,1,1,1,1,3,1,2,11,10.0,neutral or dissatisfied +4532,113430,Female,Loyal Customer,45,Business travel,Business,3631,0,5,0,1,4,4,5,4,4,5,5,5,4,5,10,1.0,satisfied +4533,87178,Female,disloyal Customer,32,Business travel,Eco,946,3,4,4,4,3,4,3,3,2,4,4,4,3,3,0,0.0,neutral or dissatisfied +4534,67170,Male,Loyal Customer,56,Personal Travel,Eco,964,1,4,1,5,4,1,4,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +4535,126943,Female,Loyal Customer,25,Business travel,Business,338,4,4,4,4,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +4536,33379,Male,Loyal Customer,22,Personal Travel,Eco,2355,3,2,3,4,4,3,4,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +4537,79672,Male,Loyal Customer,9,Personal Travel,Eco,762,5,4,5,3,2,5,2,2,4,2,4,5,5,2,0,0.0,satisfied +4538,65033,Female,Loyal Customer,15,Personal Travel,Eco,469,2,4,2,2,5,2,4,5,4,2,5,5,4,5,17,14.0,neutral or dissatisfied +4539,82737,Female,Loyal Customer,47,Business travel,Business,2007,3,3,3,3,5,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +4540,6161,Male,Loyal Customer,66,Business travel,Eco,409,4,1,1,1,4,4,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +4541,23682,Female,Loyal Customer,41,Business travel,Eco,251,5,2,5,2,5,5,5,5,3,3,3,1,5,5,23,19.0,satisfied +4542,11590,Male,Loyal Customer,33,Business travel,Business,468,1,5,5,5,1,1,1,1,1,1,4,3,3,1,0,0.0,neutral or dissatisfied +4543,83480,Male,Loyal Customer,30,Business travel,Eco,946,4,1,3,3,4,4,4,4,1,1,4,2,4,4,1,0.0,neutral or dissatisfied +4544,125249,Male,Loyal Customer,23,Business travel,Eco,427,2,5,5,5,2,2,3,2,3,2,3,2,4,2,0,0.0,neutral or dissatisfied +4545,87384,Male,Loyal Customer,30,Business travel,Business,3263,2,5,5,5,2,2,2,2,2,2,2,3,2,2,50,41.0,neutral or dissatisfied +4546,10588,Male,disloyal Customer,39,Business travel,Business,74,4,4,4,1,5,4,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +4547,110977,Male,disloyal Customer,55,Business travel,Business,197,3,2,2,1,1,3,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +4548,10337,Female,Loyal Customer,30,Business travel,Business,2822,1,1,1,1,4,4,4,4,3,5,5,4,5,4,18,17.0,satisfied +4549,107152,Female,disloyal Customer,37,Business travel,Business,402,1,1,1,1,4,1,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +4550,45931,Female,Loyal Customer,16,Personal Travel,Eco,809,2,4,2,3,4,2,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +4551,13357,Male,Loyal Customer,15,Business travel,Business,1619,1,4,5,4,1,1,1,1,3,4,3,2,3,1,90,94.0,neutral or dissatisfied +4552,71550,Female,Loyal Customer,44,Business travel,Business,3417,1,1,1,1,3,5,4,3,3,4,3,3,3,3,7,22.0,satisfied +4553,55209,Male,Loyal Customer,39,Business travel,Business,2873,1,1,1,1,3,4,5,5,5,5,5,3,5,5,8,17.0,satisfied +4554,87863,Female,Loyal Customer,49,Personal Travel,Eco,143,2,3,2,5,3,5,1,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +4555,45617,Male,disloyal Customer,44,Business travel,Eco,391,2,0,2,4,3,2,3,3,4,3,3,3,4,3,13,2.0,neutral or dissatisfied +4556,73336,Female,disloyal Customer,62,Business travel,Business,1005,5,5,5,1,5,5,5,5,3,2,4,4,5,5,74,68.0,satisfied +4557,127859,Female,Loyal Customer,41,Business travel,Business,1276,3,3,3,3,4,4,4,5,5,5,5,5,5,5,64,47.0,satisfied +4558,40902,Female,Loyal Customer,21,Personal Travel,Eco,599,1,3,1,4,4,1,1,4,4,5,3,1,3,4,18,43.0,neutral or dissatisfied +4559,16681,Male,Loyal Customer,24,Business travel,Eco Plus,488,5,5,5,5,5,5,4,5,3,3,3,1,3,5,0,0.0,satisfied +4560,94606,Male,Loyal Customer,39,Business travel,Business,2690,1,4,1,4,3,3,3,1,1,1,1,2,1,3,20,21.0,neutral or dissatisfied +4561,104961,Male,disloyal Customer,25,Business travel,Business,337,0,1,0,5,4,0,2,4,3,3,4,5,5,4,1,5.0,satisfied +4562,1522,Male,Loyal Customer,57,Business travel,Business,3896,5,5,5,5,3,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +4563,772,Female,Loyal Customer,73,Business travel,Business,134,3,3,3,3,2,4,4,2,2,2,3,4,2,3,0,0.0,neutral or dissatisfied +4564,81361,Female,disloyal Customer,10,Business travel,Eco,1299,4,4,4,4,5,4,5,5,3,3,4,5,5,5,0,0.0,satisfied +4565,16147,Male,Loyal Customer,31,Business travel,Business,199,0,5,0,3,3,3,3,3,1,2,2,4,5,3,38,34.0,satisfied +4566,47755,Male,Loyal Customer,49,Business travel,Business,3945,4,4,4,4,5,5,5,2,4,5,1,5,2,5,157,138.0,satisfied +4567,37300,Female,Loyal Customer,58,Business travel,Eco,944,4,2,5,2,2,4,2,4,4,4,4,4,4,2,23,0.0,satisfied +4568,70384,Female,Loyal Customer,39,Business travel,Business,1562,4,4,4,4,4,4,4,4,4,5,4,3,4,3,0,19.0,satisfied +4569,102747,Male,Loyal Customer,34,Business travel,Business,255,3,1,3,3,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +4570,96009,Male,Loyal Customer,26,Business travel,Business,775,2,2,2,2,5,5,5,5,5,3,4,5,4,5,2,18.0,satisfied +4571,71432,Male,disloyal Customer,35,Business travel,Business,867,2,2,2,4,3,2,2,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +4572,95046,Male,Loyal Customer,65,Personal Travel,Eco,239,2,4,2,4,4,2,4,4,5,4,5,5,4,4,0,0.0,neutral or dissatisfied +4573,61982,Female,Loyal Customer,65,Personal Travel,Business,2586,2,5,2,4,5,5,5,4,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +4574,118503,Female,disloyal Customer,26,Business travel,Business,646,4,4,4,2,2,4,2,2,5,4,4,4,4,2,24,17.0,satisfied +4575,8989,Female,Loyal Customer,43,Personal Travel,Eco,799,3,2,2,3,2,3,4,3,3,2,3,3,3,4,56,70.0,neutral or dissatisfied +4576,106487,Female,Loyal Customer,33,Personal Travel,Business,495,2,4,2,3,2,4,5,4,4,2,4,5,4,5,60,44.0,neutral or dissatisfied +4577,5751,Male,Loyal Customer,32,Business travel,Business,2306,4,4,4,4,2,2,2,2,5,4,4,5,5,2,0,0.0,satisfied +4578,6626,Male,Loyal Customer,48,Business travel,Eco,719,1,1,1,1,1,1,1,1,3,3,3,2,4,1,0,0.0,neutral or dissatisfied +4579,11855,Female,Loyal Customer,29,Business travel,Business,2278,2,3,2,2,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +4580,120101,Male,Loyal Customer,39,Business travel,Business,1576,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,,satisfied +4581,2741,Male,disloyal Customer,39,Business travel,Business,772,3,3,3,3,3,3,3,3,1,2,3,4,3,3,0,0.0,neutral or dissatisfied +4582,40352,Female,Loyal Customer,37,Business travel,Business,1028,2,2,2,2,5,5,4,5,5,5,5,1,5,3,113,101.0,satisfied +4583,65228,Female,Loyal Customer,36,Business travel,Business,2556,3,3,3,3,2,5,5,4,4,4,4,5,4,5,78,75.0,satisfied +4584,88934,Female,Loyal Customer,28,Business travel,Business,1928,5,5,3,5,4,4,4,4,5,5,5,3,5,4,0,0.0,satisfied +4585,38593,Male,Loyal Customer,45,Business travel,Eco,231,2,1,3,1,2,2,2,2,3,2,3,4,5,2,2,0.0,satisfied +4586,4565,Female,Loyal Customer,32,Personal Travel,Eco,561,4,4,4,4,3,4,3,3,4,5,5,5,5,3,27,8.0,neutral or dissatisfied +4587,41675,Female,disloyal Customer,20,Business travel,Eco,843,5,5,5,1,4,5,4,4,5,3,5,5,2,4,0,0.0,satisfied +4588,70048,Male,Loyal Customer,64,Personal Travel,Eco,583,3,5,3,1,2,3,5,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +4589,7079,Male,Loyal Customer,42,Business travel,Business,2667,0,5,0,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +4590,71503,Female,Loyal Customer,54,Business travel,Business,3270,5,5,5,5,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +4591,14546,Female,Loyal Customer,29,Personal Travel,Eco,362,1,4,1,1,3,1,3,3,4,4,4,4,4,3,16,9.0,neutral or dissatisfied +4592,7032,Female,Loyal Customer,8,Personal Travel,Eco,299,1,4,1,1,3,1,4,3,4,4,4,5,4,3,4,6.0,neutral or dissatisfied +4593,99709,Male,Loyal Customer,57,Business travel,Business,1592,3,3,3,3,2,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +4594,45664,Female,Loyal Customer,47,Personal Travel,Eco Plus,260,4,1,4,4,5,4,3,4,4,4,4,3,4,3,0,9.0,satisfied +4595,62167,Female,Loyal Customer,59,Business travel,Business,2454,3,3,3,3,1,3,3,3,3,3,3,1,3,4,22,6.0,neutral or dissatisfied +4596,66567,Male,Loyal Customer,54,Personal Travel,Business,624,1,4,1,3,1,1,5,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +4597,5422,Male,Loyal Customer,52,Personal Travel,Eco,589,3,4,3,1,4,3,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +4598,96708,Male,Loyal Customer,19,Business travel,Business,2971,2,2,2,2,4,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +4599,85314,Male,Loyal Customer,30,Personal Travel,Eco,731,1,3,1,3,5,1,5,5,2,2,3,1,2,5,0,0.0,neutral or dissatisfied +4600,22770,Female,disloyal Customer,30,Business travel,Eco,170,4,0,4,3,2,4,2,2,1,5,3,3,2,2,0,0.0,satisfied +4601,90510,Male,Loyal Customer,46,Business travel,Business,2589,3,3,3,3,3,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +4602,92954,Female,Loyal Customer,55,Business travel,Business,1904,3,3,3,3,2,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +4603,118204,Male,Loyal Customer,16,Personal Travel,Eco,1444,1,1,1,3,3,1,1,3,1,3,3,1,3,3,15,0.0,neutral or dissatisfied +4604,19548,Female,Loyal Customer,48,Business travel,Business,2273,0,5,0,2,2,3,1,5,5,5,5,4,5,3,22,20.0,satisfied +4605,82057,Female,Loyal Customer,29,Personal Travel,Eco Plus,1532,2,5,2,3,3,2,3,3,4,3,3,5,5,3,0,0.0,neutral or dissatisfied +4606,63402,Female,Loyal Customer,29,Personal Travel,Eco,447,2,3,2,3,4,2,4,4,1,2,4,3,3,4,0,8.0,neutral or dissatisfied +4607,99211,Female,disloyal Customer,39,Business travel,Business,495,3,2,2,4,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +4608,108826,Male,Loyal Customer,49,Business travel,Business,2201,5,5,5,5,3,4,4,4,4,4,4,3,4,5,11,13.0,satisfied +4609,80785,Male,Loyal Customer,45,Business travel,Business,692,4,4,2,4,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +4610,85029,Female,Loyal Customer,27,Personal Travel,Eco,1590,2,4,2,2,5,2,5,5,5,5,5,3,5,5,3,14.0,neutral or dissatisfied +4611,28741,Male,Loyal Customer,34,Business travel,Business,1024,2,2,2,2,4,4,5,4,4,4,4,4,4,1,0,0.0,satisfied +4612,69937,Female,disloyal Customer,36,Business travel,Business,2174,1,1,1,1,5,1,5,5,4,5,3,5,5,5,0,0.0,neutral or dissatisfied +4613,14201,Male,Loyal Customer,27,Business travel,Eco,620,0,0,0,1,2,5,1,2,2,2,2,1,2,2,0,1.0,satisfied +4614,89412,Female,Loyal Customer,43,Business travel,Business,3737,4,3,3,3,2,3,4,3,3,3,4,2,3,3,43,35.0,neutral or dissatisfied +4615,122226,Male,disloyal Customer,10,Business travel,Eco,646,5,0,5,1,2,5,2,2,4,2,4,4,4,2,0,0.0,satisfied +4616,95895,Male,Loyal Customer,28,Personal Travel,Eco,580,3,4,3,4,3,3,3,3,1,4,4,2,3,3,56,49.0,neutral or dissatisfied +4617,5124,Female,Loyal Customer,55,Business travel,Business,3048,4,4,4,4,3,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +4618,15890,Female,Loyal Customer,17,Personal Travel,Eco,296,2,4,2,4,5,2,5,5,3,4,5,3,5,5,50,36.0,neutral or dissatisfied +4619,6387,Female,Loyal Customer,36,Business travel,Business,3937,4,5,5,5,5,4,3,4,4,4,4,3,4,3,10,5.0,neutral or dissatisfied +4620,31856,Male,Loyal Customer,33,Personal Travel,Eco,2640,4,4,4,4,3,4,3,3,1,4,5,5,4,3,1,0.0,satisfied +4621,123415,Male,Loyal Customer,53,Business travel,Business,937,4,4,4,4,5,2,4,5,5,4,5,4,5,3,8,0.0,satisfied +4622,105067,Female,disloyal Customer,21,Business travel,Eco,277,2,3,3,4,3,3,3,3,1,4,4,1,4,3,85,86.0,neutral or dissatisfied +4623,560,Female,Loyal Customer,32,Business travel,Business,2560,4,4,4,4,5,5,4,5,3,2,4,5,5,5,25,17.0,satisfied +4624,114990,Female,disloyal Customer,24,Business travel,Eco,296,4,0,4,3,2,4,2,2,4,2,4,3,5,2,0,0.0,satisfied +4625,94076,Male,Loyal Customer,23,Business travel,Business,562,3,4,4,4,3,3,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +4626,95585,Female,disloyal Customer,25,Business travel,Eco,822,2,3,3,4,5,3,5,5,2,2,4,1,3,5,0,0.0,neutral or dissatisfied +4627,123025,Male,disloyal Customer,37,Business travel,Business,650,1,1,1,5,4,1,4,4,4,5,4,4,4,4,2,3.0,neutral or dissatisfied +4628,38034,Male,Loyal Customer,49,Business travel,Business,3213,4,4,4,4,5,5,2,4,4,5,4,2,4,1,81,58.0,satisfied +4629,108200,Male,Loyal Customer,7,Personal Travel,Eco Plus,990,3,5,3,4,5,3,5,5,3,4,4,5,4,5,11,0.0,neutral or dissatisfied +4630,68493,Male,Loyal Customer,14,Personal Travel,Eco,1303,2,1,2,3,3,2,3,3,4,3,2,2,3,3,1,0.0,neutral or dissatisfied +4631,34002,Male,Loyal Customer,12,Business travel,Business,1576,4,1,1,1,4,4,4,4,1,4,3,4,4,4,0,20.0,neutral or dissatisfied +4632,115926,Female,Loyal Customer,37,Business travel,Business,3095,4,2,2,2,2,3,4,4,4,4,4,1,4,2,53,55.0,neutral or dissatisfied +4633,97405,Male,Loyal Customer,59,Business travel,Business,570,2,2,2,2,3,5,4,2,2,2,2,4,2,3,29,17.0,satisfied +4634,34329,Male,Loyal Customer,16,Business travel,Business,846,5,5,5,5,5,5,5,5,4,1,4,2,2,5,0,6.0,satisfied +4635,123957,Female,Loyal Customer,40,Personal Travel,Eco Plus,544,1,3,5,3,2,5,2,2,3,4,3,4,4,2,0,0.0,neutral or dissatisfied +4636,43267,Male,Loyal Customer,40,Business travel,Business,1769,4,4,4,4,1,5,1,4,4,4,4,4,4,3,0,0.0,satisfied +4637,11984,Male,disloyal Customer,16,Business travel,Eco,643,2,1,2,3,4,2,4,4,1,5,4,4,4,4,20,10.0,neutral or dissatisfied +4638,92003,Female,Loyal Customer,54,Business travel,Business,1535,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +4639,95206,Female,Loyal Customer,18,Personal Travel,Eco,239,1,3,1,3,3,1,2,3,3,1,5,3,3,3,30,19.0,neutral or dissatisfied +4640,78535,Female,Loyal Customer,9,Personal Travel,Eco,666,5,1,5,3,2,5,2,2,1,2,3,4,3,2,1,5.0,satisfied +4641,4673,Male,disloyal Customer,20,Business travel,Business,364,2,4,2,4,4,2,3,4,3,3,4,4,3,4,31,22.0,neutral or dissatisfied +4642,15480,Male,Loyal Customer,29,Personal Travel,Eco,377,0,4,0,2,4,0,4,4,4,2,5,4,5,4,0,0.0,satisfied +4643,120495,Male,Loyal Customer,42,Business travel,Business,3976,3,3,3,3,3,4,4,3,3,3,3,5,3,4,15,4.0,satisfied +4644,32948,Male,Loyal Customer,8,Personal Travel,Eco,101,3,5,3,2,5,3,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +4645,69585,Male,Loyal Customer,23,Personal Travel,Eco,2475,1,0,2,3,2,2,2,4,1,3,5,2,4,2,0,0.0,neutral or dissatisfied +4646,115051,Female,disloyal Customer,58,Business travel,Business,404,2,2,2,1,1,2,2,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +4647,107309,Female,Loyal Customer,52,Personal Travel,Eco,283,3,5,3,4,5,5,5,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +4648,70106,Female,disloyal Customer,22,Business travel,Business,550,5,0,5,3,3,5,3,3,3,3,4,3,4,3,0,2.0,satisfied +4649,94799,Male,Loyal Customer,63,Business travel,Eco,239,2,4,4,4,2,2,2,2,4,5,3,4,2,2,5,2.0,neutral or dissatisfied +4650,78648,Female,Loyal Customer,51,Business travel,Business,2967,5,5,5,5,1,5,5,3,3,3,3,2,3,3,0,0.0,satisfied +4651,85276,Male,Loyal Customer,70,Personal Travel,Eco,689,2,4,2,5,1,2,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +4652,105004,Female,Loyal Customer,56,Personal Travel,Business,255,2,3,2,2,1,4,4,3,3,2,3,4,3,3,16,13.0,neutral or dissatisfied +4653,37356,Female,Loyal Customer,28,Business travel,Eco,1035,5,2,2,2,5,5,5,5,5,2,4,2,1,5,49,59.0,satisfied +4654,100901,Female,disloyal Customer,21,Business travel,Eco,377,4,0,3,3,5,3,5,5,5,5,4,5,1,5,34,29.0,neutral or dissatisfied +4655,126163,Male,Loyal Customer,56,Business travel,Business,3128,4,4,3,4,3,5,4,5,5,4,5,4,5,3,0,2.0,satisfied +4656,85576,Female,Loyal Customer,47,Business travel,Eco,259,3,1,1,1,4,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +4657,78681,Male,Loyal Customer,43,Business travel,Business,3385,1,1,1,1,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +4658,5815,Male,Loyal Customer,44,Personal Travel,Eco,157,2,5,2,2,1,2,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +4659,5084,Female,disloyal Customer,25,Business travel,Eco,137,1,1,1,4,5,1,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +4660,1859,Female,Loyal Customer,44,Business travel,Business,2961,4,4,4,4,5,4,5,4,4,4,4,3,4,5,0,6.0,satisfied +4661,24079,Male,disloyal Customer,46,Personal Travel,Eco,866,2,4,2,3,2,2,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +4662,30702,Female,Loyal Customer,25,Personal Travel,Eco,680,1,5,1,2,1,1,2,1,3,3,4,5,5,1,14,8.0,neutral or dissatisfied +4663,97706,Female,Loyal Customer,55,Personal Travel,Eco,456,4,5,4,2,4,4,4,3,3,4,3,5,3,3,8,0.0,neutral or dissatisfied +4664,16633,Male,Loyal Customer,25,Business travel,Eco,488,5,3,3,3,5,5,4,5,2,3,1,4,5,5,19,8.0,satisfied +4665,6114,Male,Loyal Customer,40,Business travel,Business,2505,3,3,3,3,5,4,5,3,3,4,3,5,3,3,29,31.0,satisfied +4666,45896,Male,disloyal Customer,40,Business travel,Eco,563,4,5,5,4,1,5,1,1,1,3,3,3,3,1,55,69.0,satisfied +4667,30005,Female,Loyal Customer,66,Business travel,Business,3969,3,4,4,4,1,3,3,0,0,1,3,3,0,2,0,0.0,neutral or dissatisfied +4668,52839,Male,Loyal Customer,32,Business travel,Business,1721,5,5,5,5,5,5,5,5,1,3,5,3,4,5,0,0.0,satisfied +4669,51634,Female,disloyal Customer,32,Business travel,Eco,370,3,4,3,3,4,3,4,4,3,4,2,5,3,4,2,0.0,neutral or dissatisfied +4670,36470,Male,Loyal Customer,51,Business travel,Business,901,2,2,2,2,5,4,5,5,5,5,5,2,5,3,26,20.0,satisfied +4671,79815,Male,Loyal Customer,43,Business travel,Business,1076,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +4672,10352,Female,Loyal Customer,51,Business travel,Business,316,0,0,0,5,2,4,4,3,3,3,3,4,3,5,89,83.0,satisfied +4673,34009,Male,disloyal Customer,35,Business travel,Eco,866,3,3,3,3,4,3,4,4,4,1,2,4,2,4,0,0.0,neutral or dissatisfied +4674,56920,Male,Loyal Customer,29,Business travel,Business,2565,3,5,5,5,3,3,3,4,2,3,3,3,1,3,13,0.0,neutral or dissatisfied +4675,12630,Male,disloyal Customer,24,Business travel,Eco,844,0,0,0,1,1,0,1,1,3,4,2,5,2,1,0,0.0,satisfied +4676,55352,Female,Loyal Customer,22,Business travel,Business,678,5,5,5,5,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +4677,93712,Female,Loyal Customer,23,Personal Travel,Eco,689,3,5,3,2,1,3,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +4678,116946,Male,Loyal Customer,48,Business travel,Business,1618,1,1,1,1,4,5,5,4,4,4,4,5,4,5,14,9.0,satisfied +4679,106724,Female,Loyal Customer,39,Business travel,Business,3654,1,1,1,1,5,4,5,4,4,4,4,4,4,4,23,21.0,satisfied +4680,30165,Male,Loyal Customer,18,Personal Travel,Eco,82,4,1,4,4,4,4,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +4681,80328,Male,Loyal Customer,10,Personal Travel,Eco,746,2,5,2,4,2,4,4,5,5,4,4,4,3,4,199,185.0,neutral or dissatisfied +4682,50169,Male,Loyal Customer,39,Business travel,Business,2024,4,4,4,4,5,3,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +4683,79648,Male,Loyal Customer,67,Business travel,Eco,360,3,5,5,5,3,3,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +4684,64420,Female,Loyal Customer,42,Personal Travel,Business,989,2,4,2,4,5,4,4,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +4685,90821,Female,disloyal Customer,22,Business travel,Eco,581,4,0,4,3,2,4,2,2,4,5,5,3,4,2,0,0.0,satisfied +4686,81139,Female,Loyal Customer,47,Business travel,Business,1631,5,5,5,5,3,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +4687,72257,Female,Loyal Customer,41,Business travel,Business,3149,2,3,3,3,3,2,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +4688,129519,Female,disloyal Customer,26,Business travel,Business,2583,1,3,1,4,3,1,2,3,1,1,2,1,4,3,0,1.0,neutral or dissatisfied +4689,82003,Male,Loyal Customer,53,Business travel,Business,1589,4,4,4,4,1,1,2,4,4,4,4,2,4,1,10,0.0,neutral or dissatisfied +4690,44471,Female,Loyal Customer,51,Personal Travel,Eco,196,1,5,1,3,2,5,5,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +4691,119562,Female,Loyal Customer,49,Personal Travel,Eco,759,1,4,1,1,2,4,4,1,1,1,5,5,1,5,0,0.0,neutral or dissatisfied +4692,25543,Male,Loyal Customer,28,Personal Travel,Eco,547,3,4,3,4,5,3,2,5,2,5,4,1,3,5,3,3.0,neutral or dissatisfied +4693,23019,Female,Loyal Customer,28,Business travel,Eco Plus,528,0,0,0,1,2,0,2,2,2,2,5,1,1,2,0,0.0,satisfied +4694,9882,Male,Loyal Customer,27,Business travel,Business,2402,4,4,3,4,5,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +4695,22072,Female,Loyal Customer,39,Personal Travel,Eco,304,5,5,5,1,2,5,2,2,4,3,4,4,5,2,0,0.0,satisfied +4696,116977,Male,disloyal Customer,24,Business travel,Business,338,0,5,0,5,3,0,3,3,5,3,5,4,4,3,22,46.0,satisfied +4697,29612,Female,Loyal Customer,41,Business travel,Eco,1448,3,2,2,2,3,3,3,3,2,3,4,1,3,3,0,0.0,neutral or dissatisfied +4698,121878,Female,Loyal Customer,35,Business travel,Business,366,2,2,2,2,3,3,3,5,5,5,5,1,5,1,0,0.0,satisfied +4699,52376,Male,Loyal Customer,47,Personal Travel,Eco,651,2,5,3,1,5,3,5,5,5,4,1,4,3,5,0,0.0,neutral or dissatisfied +4700,22772,Female,Loyal Customer,33,Business travel,Eco,134,4,1,4,1,4,4,4,4,1,5,2,2,4,4,0,14.0,satisfied +4701,72431,Female,disloyal Customer,27,Business travel,Business,1121,2,1,1,1,3,1,3,3,5,5,5,4,4,3,1,0.0,neutral or dissatisfied +4702,19832,Female,Loyal Customer,31,Personal Travel,Eco,594,2,3,2,3,1,2,1,1,1,4,3,5,4,1,72,54.0,neutral or dissatisfied +4703,35009,Male,Loyal Customer,24,Business travel,Eco Plus,1182,4,1,5,1,4,4,5,4,5,1,5,4,3,4,0,0.0,satisfied +4704,94910,Male,Loyal Customer,61,Business travel,Business,277,1,1,1,1,2,5,1,5,5,5,5,3,5,5,0,1.0,satisfied +4705,75842,Female,Loyal Customer,59,Business travel,Business,1440,1,1,4,1,4,5,5,4,4,4,4,4,4,4,51,29.0,satisfied +4706,119542,Female,Loyal Customer,44,Personal Travel,Eco,899,2,5,2,4,2,5,5,4,4,2,4,3,4,3,1,11.0,neutral or dissatisfied +4707,99642,Female,Loyal Customer,29,Business travel,Business,1670,4,4,4,4,4,4,4,4,5,3,4,3,4,4,0,10.0,satisfied +4708,92143,Male,Loyal Customer,52,Business travel,Eco Plus,1532,2,3,4,3,2,2,2,2,3,4,3,1,4,2,0,0.0,neutral or dissatisfied +4709,10416,Male,Loyal Customer,37,Business travel,Business,3540,2,2,2,2,3,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +4710,20269,Female,Loyal Customer,41,Business travel,Business,3820,1,1,1,1,1,3,3,5,5,5,3,5,5,3,108,109.0,satisfied +4711,18091,Male,Loyal Customer,44,Business travel,Eco Plus,488,2,3,3,3,2,2,2,2,4,4,1,2,4,2,0,0.0,satisfied +4712,57468,Female,Loyal Customer,73,Business travel,Eco Plus,334,2,2,2,2,1,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +4713,19280,Male,Loyal Customer,11,Personal Travel,Eco,430,2,5,2,1,5,2,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +4714,49364,Male,Loyal Customer,51,Business travel,Business,1592,0,5,0,2,3,3,3,2,2,2,2,3,2,1,0,0.0,satisfied +4715,29468,Female,disloyal Customer,22,Business travel,Business,1216,5,0,5,3,3,5,5,3,4,5,5,5,5,3,0,0.0,satisfied +4716,85480,Female,Loyal Customer,51,Personal Travel,Eco,227,5,5,5,2,4,4,5,4,4,5,4,4,4,5,37,18.0,satisfied +4717,114721,Female,Loyal Customer,50,Business travel,Business,2133,1,1,3,1,2,5,5,5,5,5,5,5,5,5,1,0.0,satisfied +4718,106021,Female,Loyal Customer,46,Business travel,Business,682,4,4,4,4,4,4,5,5,5,5,5,3,5,5,3,2.0,satisfied +4719,71835,Male,Loyal Customer,25,Business travel,Business,1744,3,1,3,3,3,3,3,3,1,2,4,2,3,3,39,26.0,neutral or dissatisfied +4720,29135,Female,Loyal Customer,59,Personal Travel,Eco,987,1,4,1,1,5,4,5,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +4721,28480,Female,Loyal Customer,29,Business travel,Eco Plus,1721,3,5,5,5,3,3,3,3,3,5,4,4,3,3,24,15.0,neutral or dissatisfied +4722,111393,Female,Loyal Customer,33,Personal Travel,Eco,1180,3,5,4,3,5,4,5,5,3,5,4,3,4,5,6,0.0,neutral or dissatisfied +4723,123764,Female,Loyal Customer,30,Business travel,Business,546,2,2,2,2,4,5,4,4,5,2,4,4,4,4,0,0.0,satisfied +4724,55497,Male,Loyal Customer,43,Business travel,Eco,239,4,3,3,3,4,4,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +4725,52760,Male,Loyal Customer,32,Business travel,Business,1874,3,3,3,3,4,4,4,4,1,3,4,4,3,4,0,4.0,satisfied +4726,8846,Male,Loyal Customer,30,Business travel,Business,1371,5,5,5,5,5,5,5,5,3,2,4,3,4,5,47,54.0,satisfied +4727,78943,Female,Loyal Customer,13,Business travel,Business,500,2,2,2,2,5,4,5,5,4,3,5,4,4,5,0,0.0,satisfied +4728,46274,Female,Loyal Customer,36,Personal Travel,Eco,594,3,1,3,4,1,3,1,1,1,5,3,1,3,1,86,106.0,neutral or dissatisfied +4729,59378,Female,disloyal Customer,72,Business travel,Eco,899,2,2,2,3,3,2,5,3,2,4,3,1,3,3,45,4.0,neutral or dissatisfied +4730,99354,Female,Loyal Customer,59,Personal Travel,Eco,1771,3,4,3,3,2,4,3,4,4,3,4,4,4,1,9,0.0,neutral or dissatisfied +4731,125750,Female,Loyal Customer,28,Personal Travel,Business,993,4,4,4,3,2,4,2,2,2,1,3,2,3,2,0,0.0,neutral or dissatisfied +4732,50148,Male,disloyal Customer,26,Business travel,Eco,190,2,1,1,3,4,1,4,4,2,2,4,3,4,4,32,45.0,neutral or dissatisfied +4733,109803,Male,Loyal Customer,52,Business travel,Business,1073,2,2,2,2,5,4,5,2,2,2,2,4,2,5,13,18.0,satisfied +4734,43081,Female,Loyal Customer,44,Personal Travel,Eco,259,5,1,5,3,3,3,4,5,5,5,5,2,5,3,0,0.0,satisfied +4735,78969,Male,Loyal Customer,27,Business travel,Business,356,1,1,1,1,5,5,5,5,5,5,4,5,5,5,1,38.0,satisfied +4736,13329,Female,disloyal Customer,39,Business travel,Business,748,4,3,3,4,2,3,2,2,3,2,4,1,3,2,0,0.0,neutral or dissatisfied +4737,64925,Female,Loyal Customer,42,Business travel,Business,3236,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +4738,88520,Female,Loyal Customer,39,Personal Travel,Eco,240,3,4,3,3,5,3,3,5,3,5,4,5,4,5,0,0.0,neutral or dissatisfied +4739,101158,Female,Loyal Customer,59,Business travel,Eco,1235,3,5,5,5,5,2,1,3,3,3,3,2,3,2,20,11.0,neutral or dissatisfied +4740,75632,Male,Loyal Customer,69,Personal Travel,Eco Plus,337,1,4,1,3,3,1,1,3,5,4,5,4,5,3,0,8.0,neutral or dissatisfied +4741,2877,Male,Loyal Customer,70,Personal Travel,Eco,475,3,3,5,2,5,1,1,4,3,5,4,1,2,1,166,172.0,neutral or dissatisfied +4742,53632,Male,Loyal Customer,21,Personal Travel,Eco,1874,2,1,2,1,3,2,3,3,2,2,2,1,1,3,35,14.0,neutral or dissatisfied +4743,83704,Female,Loyal Customer,52,Personal Travel,Eco,577,3,1,2,2,5,1,1,5,5,2,4,3,5,2,13,1.0,neutral or dissatisfied +4744,60387,Male,Loyal Customer,56,Business travel,Business,1452,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +4745,111762,Male,Loyal Customer,50,Personal Travel,Eco,1436,3,4,3,3,4,3,4,4,4,5,4,2,4,4,0,1.0,neutral or dissatisfied +4746,6598,Female,Loyal Customer,34,Personal Travel,Eco,473,3,1,3,3,3,3,3,3,1,2,3,4,3,3,17,8.0,neutral or dissatisfied +4747,84621,Female,disloyal Customer,79,Business travel,Eco,269,2,2,2,4,5,2,3,5,2,3,3,1,4,5,0,0.0,neutral or dissatisfied +4748,5687,Female,Loyal Customer,41,Business travel,Eco,196,3,1,1,1,3,3,3,3,3,5,3,3,4,3,6,11.0,neutral or dissatisfied +4749,62706,Female,disloyal Customer,27,Business travel,Eco,2399,3,3,3,4,3,3,3,2,2,4,3,3,4,3,50,71.0,neutral or dissatisfied +4750,115546,Male,Loyal Customer,64,Business travel,Business,2665,2,3,3,3,5,3,4,2,2,2,2,1,2,1,15,11.0,neutral or dissatisfied +4751,111342,Female,Loyal Customer,12,Personal Travel,Eco Plus,283,1,5,1,2,3,1,3,3,5,2,4,3,5,3,79,71.0,neutral or dissatisfied +4752,52796,Female,Loyal Customer,52,Personal Travel,Eco,1874,4,3,4,4,2,1,3,4,4,4,4,3,4,4,1,0.0,neutral or dissatisfied +4753,121261,Female,Loyal Customer,10,Personal Travel,Eco,2075,2,3,1,3,5,1,5,5,4,4,3,5,3,5,18,1.0,neutral or dissatisfied +4754,129508,Female,Loyal Customer,30,Business travel,Business,1744,1,4,4,4,1,1,1,1,3,3,2,3,2,1,0,0.0,neutral or dissatisfied +4755,5623,Female,Loyal Customer,70,Personal Travel,Eco,624,2,5,2,5,2,1,3,2,2,2,4,3,2,2,0,0.0,neutral or dissatisfied +4756,33667,Male,Loyal Customer,15,Personal Travel,Eco Plus,474,1,3,1,3,4,1,4,4,4,5,3,2,3,4,34,50.0,neutral or dissatisfied +4757,87972,Male,Loyal Customer,28,Business travel,Business,1749,3,4,3,3,4,4,4,4,4,2,5,3,5,4,15,8.0,satisfied +4758,94851,Female,Loyal Customer,53,Business travel,Business,2249,0,5,0,5,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +4759,69315,Male,disloyal Customer,26,Business travel,Business,944,3,3,3,2,5,3,5,5,3,2,4,3,5,5,0,6.0,neutral or dissatisfied +4760,53532,Female,Loyal Customer,49,Business travel,Eco Plus,2419,4,4,4,4,5,3,1,4,4,4,4,5,4,3,0,0.0,satisfied +4761,364,Female,disloyal Customer,33,Business travel,Business,113,3,3,3,5,5,3,5,5,4,5,5,3,4,5,0,0.0,neutral or dissatisfied +4762,47112,Male,Loyal Customer,40,Business travel,Business,784,4,4,4,4,1,2,3,4,4,4,4,3,4,5,0,0.0,satisfied +4763,740,Male,Loyal Customer,32,Business travel,Business,270,2,2,2,2,4,4,4,4,5,2,5,3,5,4,0,0.0,satisfied +4764,106255,Female,disloyal Customer,23,Business travel,Business,1500,5,3,5,4,4,5,4,4,5,5,5,5,5,4,17,22.0,satisfied +4765,127560,Female,Loyal Customer,28,Business travel,Business,1670,2,2,2,2,5,5,5,5,4,5,3,5,4,5,0,0.0,satisfied +4766,126780,Female,Loyal Customer,50,Business travel,Business,2125,3,2,2,2,2,3,4,3,3,3,3,1,3,4,16,12.0,neutral or dissatisfied +4767,12305,Female,Loyal Customer,31,Business travel,Business,3033,0,3,0,5,3,3,3,3,4,3,3,3,2,3,19,16.0,satisfied +4768,24837,Female,Loyal Customer,60,Personal Travel,Eco,861,2,5,2,2,5,4,5,5,5,2,5,4,5,3,101,99.0,neutral or dissatisfied +4769,69237,Male,Loyal Customer,25,Business travel,Business,3547,2,3,1,3,2,2,2,2,1,2,2,3,2,2,0,0.0,neutral or dissatisfied +4770,40030,Male,Loyal Customer,30,Personal Travel,Eco,618,1,5,1,3,4,1,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +4771,99624,Male,disloyal Customer,24,Business travel,Eco,1154,4,4,4,4,3,4,3,3,3,5,3,1,3,3,0,0.0,neutral or dissatisfied +4772,31528,Male,Loyal Customer,63,Personal Travel,Eco,967,1,5,1,3,2,1,1,2,3,3,4,3,5,2,9,0.0,neutral or dissatisfied +4773,10972,Female,disloyal Customer,44,Business travel,Eco,458,4,0,5,2,3,5,3,3,4,2,3,2,4,3,75,79.0,neutral or dissatisfied +4774,52524,Female,Loyal Customer,26,Business travel,Business,110,2,2,2,2,5,5,3,5,2,4,4,4,1,5,0,0.0,satisfied +4775,2458,Female,disloyal Customer,30,Business travel,Business,773,3,3,3,1,3,3,1,3,4,2,4,4,4,3,0,29.0,neutral or dissatisfied +4776,45422,Male,Loyal Customer,15,Business travel,Business,649,3,4,5,4,3,3,3,3,1,2,4,2,4,3,92,118.0,neutral or dissatisfied +4777,56763,Female,disloyal Customer,39,Business travel,Business,997,3,3,3,3,2,3,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +4778,2136,Female,Loyal Customer,38,Personal Travel,Eco,404,1,4,1,2,4,1,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +4779,60777,Male,Loyal Customer,20,Personal Travel,Eco,628,3,5,3,1,3,4,4,4,3,3,3,4,1,4,157,185.0,neutral or dissatisfied +4780,114594,Male,Loyal Customer,40,Business travel,Business,447,1,5,1,1,2,5,4,4,4,4,4,3,4,5,1,0.0,satisfied +4781,113809,Female,Loyal Customer,57,Business travel,Eco Plus,397,3,5,5,5,1,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +4782,83541,Female,Loyal Customer,37,Business travel,Business,1121,1,1,1,1,3,4,4,3,3,3,3,5,3,4,0,1.0,satisfied +4783,16281,Female,Loyal Customer,62,Personal Travel,Eco,946,3,3,3,4,5,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +4784,82398,Female,Loyal Customer,13,Business travel,Business,1578,3,5,5,5,3,3,3,3,4,3,3,4,3,3,27,114.0,neutral or dissatisfied +4785,77810,Male,Loyal Customer,10,Personal Travel,Eco,696,1,5,1,3,5,1,4,5,5,2,5,4,4,5,0,0.0,neutral or dissatisfied +4786,53152,Male,Loyal Customer,61,Business travel,Eco,955,4,3,3,3,4,4,4,4,3,3,2,5,4,4,0,0.0,satisfied +4787,79630,Female,Loyal Customer,66,Business travel,Business,3994,3,5,5,5,5,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +4788,107435,Female,Loyal Customer,69,Personal Travel,Eco,717,2,4,2,5,3,4,5,4,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +4789,37641,Male,Loyal Customer,20,Personal Travel,Eco,1028,2,4,2,3,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +4790,47335,Male,disloyal Customer,26,Business travel,Eco,501,2,4,2,1,2,2,3,2,5,5,1,3,3,2,12,1.0,neutral or dissatisfied +4791,102706,Female,disloyal Customer,21,Business travel,Business,255,3,4,4,4,3,4,1,3,4,3,4,4,4,3,14,6.0,neutral or dissatisfied +4792,95588,Male,disloyal Customer,15,Business travel,Eco,756,2,2,2,3,1,2,1,1,3,3,4,3,5,1,5,1.0,neutral or dissatisfied +4793,23747,Male,Loyal Customer,30,Business travel,Business,3658,1,1,5,1,4,4,4,4,4,1,4,1,5,4,57,39.0,satisfied +4794,121062,Male,Loyal Customer,19,Personal Travel,Eco,861,1,5,1,3,4,1,4,4,3,2,4,4,4,4,14,1.0,neutral or dissatisfied +4795,22788,Female,disloyal Customer,59,Business travel,Eco,170,2,0,2,3,5,2,5,5,1,3,4,3,3,5,63,84.0,neutral or dissatisfied +4796,30268,Female,disloyal Customer,24,Business travel,Eco,1024,2,2,2,4,5,2,5,5,1,3,4,4,3,5,0,11.0,neutral or dissatisfied +4797,47465,Male,Loyal Customer,24,Personal Travel,Eco,599,5,0,5,1,5,5,5,5,2,4,3,2,2,5,12,0.0,satisfied +4798,3586,Female,Loyal Customer,50,Business travel,Business,1534,2,2,2,2,2,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +4799,83755,Female,Loyal Customer,60,Personal Travel,Eco,1183,3,5,2,2,5,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +4800,34246,Male,disloyal Customer,41,Business travel,Business,1666,2,2,2,2,3,2,3,3,1,3,3,3,3,3,18,50.0,neutral or dissatisfied +4801,82115,Male,Loyal Customer,67,Personal Travel,Eco,1276,2,4,2,1,1,2,1,1,5,5,4,5,5,1,24,11.0,neutral or dissatisfied +4802,126422,Female,disloyal Customer,52,Business travel,Eco Plus,590,2,1,1,4,3,2,1,3,3,2,3,3,3,3,49,68.0,neutral or dissatisfied +4803,109412,Female,Loyal Customer,54,Business travel,Business,2284,4,4,4,4,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +4804,34838,Female,Loyal Customer,10,Personal Travel,Eco Plus,264,4,4,0,4,1,0,2,1,2,1,4,3,4,1,0,0.0,satisfied +4805,127065,Male,Loyal Customer,57,Business travel,Business,3496,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +4806,21677,Male,Loyal Customer,38,Business travel,Business,746,1,1,1,1,1,2,3,5,5,5,5,1,5,5,22,1.0,satisfied +4807,49899,Male,disloyal Customer,50,Business travel,Eco,109,2,0,2,3,5,2,1,5,5,5,2,1,1,5,0,1.0,neutral or dissatisfied +4808,35200,Male,disloyal Customer,26,Business travel,Eco,828,1,1,1,3,4,1,4,4,4,4,4,2,5,4,0,25.0,neutral or dissatisfied +4809,77449,Female,Loyal Customer,44,Business travel,Business,1634,1,1,1,1,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +4810,14459,Male,Loyal Customer,51,Business travel,Eco,361,5,4,4,4,5,5,5,5,5,1,1,3,1,5,13,0.0,satisfied +4811,16513,Male,Loyal Customer,64,Business travel,Eco Plus,143,4,4,4,4,4,4,4,4,2,4,1,2,5,4,0,0.0,satisfied +4812,39531,Male,disloyal Customer,62,Business travel,Business,954,4,4,4,3,1,4,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +4813,44613,Male,Loyal Customer,45,Personal Travel,Eco,508,2,4,2,3,1,2,1,1,3,4,4,3,5,1,0,8.0,neutral or dissatisfied +4814,3078,Female,Loyal Customer,46,Business travel,Business,413,3,4,5,5,1,3,3,3,3,2,3,2,3,4,33,43.0,neutral or dissatisfied +4815,68551,Male,Loyal Customer,27,Personal Travel,Eco Plus,1013,2,2,2,4,3,2,3,3,3,4,3,1,3,3,0,7.0,neutral or dissatisfied +4816,100152,Female,Loyal Customer,29,Business travel,Business,3086,3,4,4,4,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +4817,6069,Female,Loyal Customer,30,Personal Travel,Eco,691,2,1,2,3,2,2,5,2,3,3,3,4,2,2,21,38.0,neutral or dissatisfied +4818,111273,Female,Loyal Customer,60,Business travel,Business,1817,2,2,4,2,4,4,4,2,2,2,2,3,2,5,6,2.0,satisfied +4819,51524,Male,Loyal Customer,53,Business travel,Business,237,5,5,5,5,5,5,2,4,4,4,4,2,4,3,0,0.0,satisfied +4820,8471,Male,Loyal Customer,36,Personal Travel,Business,1187,3,5,4,5,3,4,5,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +4821,7984,Female,Loyal Customer,46,Business travel,Business,3621,5,5,5,5,2,5,5,5,5,5,5,3,5,4,17,11.0,satisfied +4822,89087,Female,disloyal Customer,13,Business travel,Eco,1892,2,3,3,4,3,2,3,3,2,2,3,3,3,3,2,0.0,neutral or dissatisfied +4823,121587,Female,disloyal Customer,22,Business travel,Business,536,0,0,0,3,1,0,1,1,3,1,2,4,1,1,3,0.0,satisfied +4824,81018,Male,disloyal Customer,21,Business travel,Business,1399,1,1,1,3,3,1,3,3,3,1,2,1,3,3,11,12.0,neutral or dissatisfied +4825,17254,Female,Loyal Customer,51,Business travel,Business,472,2,2,2,2,3,4,1,4,4,5,4,5,4,2,42,49.0,satisfied +4826,68007,Male,Loyal Customer,59,Business travel,Business,2286,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +4827,21396,Female,disloyal Customer,23,Business travel,Eco,164,0,3,0,2,5,0,5,5,5,3,2,4,2,5,0,0.0,satisfied +4828,66008,Male,Loyal Customer,52,Business travel,Business,1055,5,5,5,5,4,5,4,3,3,2,3,4,3,5,43,37.0,satisfied +4829,5234,Female,Loyal Customer,39,Business travel,Business,295,1,1,1,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +4830,62661,Female,Loyal Customer,64,Business travel,Eco Plus,1744,1,2,2,2,3,3,4,1,1,1,1,3,1,3,0,9.0,neutral or dissatisfied +4831,3433,Male,Loyal Customer,7,Personal Travel,Eco,296,1,1,1,4,1,1,1,1,3,4,3,2,4,1,0,0.0,neutral or dissatisfied +4832,116311,Female,Loyal Customer,70,Personal Travel,Eco,447,1,4,2,2,1,4,2,5,5,2,5,1,5,1,13,10.0,neutral or dissatisfied +4833,122165,Male,Loyal Customer,55,Business travel,Business,544,4,4,4,4,2,4,5,5,5,4,5,5,5,4,42,39.0,satisfied +4834,97401,Male,disloyal Customer,23,Business travel,Eco,587,2,5,3,1,4,3,4,4,4,4,4,4,4,4,35,26.0,neutral or dissatisfied +4835,58346,Female,Loyal Customer,49,Personal Travel,Eco,315,4,1,4,4,4,4,4,5,5,4,5,1,5,4,108,103.0,neutral or dissatisfied +4836,71750,Female,Loyal Customer,41,Business travel,Business,1723,1,1,2,1,5,4,5,5,5,4,5,5,5,5,46,74.0,satisfied +4837,52840,Female,Loyal Customer,17,Business travel,Business,1721,1,1,1,1,3,3,3,3,1,5,4,3,5,3,0,0.0,satisfied +4838,101319,Female,Loyal Customer,41,Business travel,Eco,1076,3,3,3,3,3,3,3,3,4,1,2,3,2,3,78,68.0,neutral or dissatisfied +4839,23913,Female,disloyal Customer,26,Business travel,Eco,589,1,0,1,3,5,1,5,5,2,2,1,5,3,5,0,0.0,neutral or dissatisfied +4840,91074,Female,Loyal Customer,65,Personal Travel,Eco,545,2,2,2,3,4,3,3,2,2,2,5,3,2,3,0,0.0,neutral or dissatisfied +4841,2767,Female,disloyal Customer,36,Business travel,Business,764,2,2,2,3,2,2,2,2,5,2,4,4,5,2,0,15.0,neutral or dissatisfied +4842,58792,Male,disloyal Customer,25,Business travel,Eco,1012,3,3,3,2,4,3,4,4,3,3,3,3,2,4,0,0.0,neutral or dissatisfied +4843,120990,Male,Loyal Customer,46,Business travel,Business,993,2,5,5,5,1,3,3,2,2,2,2,2,2,3,0,5.0,neutral or dissatisfied +4844,128973,Male,Loyal Customer,13,Personal Travel,Eco,236,2,4,2,3,5,2,5,5,1,2,1,1,1,5,3,7.0,neutral or dissatisfied +4845,72943,Female,Loyal Customer,49,Business travel,Business,2493,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +4846,60079,Male,Loyal Customer,23,Business travel,Business,1528,1,1,1,1,4,4,4,4,3,2,4,5,5,4,0,0.0,satisfied +4847,118453,Male,Loyal Customer,57,Business travel,Business,2503,1,1,1,1,4,5,4,4,4,4,4,5,4,5,19,18.0,satisfied +4848,88640,Male,Loyal Customer,44,Personal Travel,Eco,404,3,5,5,3,4,5,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +4849,44022,Male,disloyal Customer,27,Business travel,Eco,680,3,3,3,2,5,3,5,5,5,5,5,1,2,5,7,0.0,neutral or dissatisfied +4850,90093,Female,disloyal Customer,62,Business travel,Eco,983,3,3,3,4,3,3,3,3,3,3,4,1,3,3,5,0.0,neutral or dissatisfied +4851,13604,Female,disloyal Customer,29,Business travel,Eco Plus,214,2,2,2,3,3,2,5,3,1,4,4,2,3,3,0,0.0,neutral or dissatisfied +4852,103430,Male,Loyal Customer,30,Personal Travel,Eco,237,1,4,1,1,2,1,2,2,4,5,4,3,5,2,7,2.0,neutral or dissatisfied +4853,16692,Male,Loyal Customer,71,Business travel,Eco,200,5,3,5,3,5,5,5,5,1,5,2,3,5,5,0,0.0,satisfied +4854,107098,Male,Loyal Customer,11,Personal Travel,Eco,745,3,5,3,1,4,3,4,4,5,4,5,4,5,4,15,11.0,neutral or dissatisfied +4855,4314,Female,Loyal Customer,61,Business travel,Eco,184,2,4,4,4,1,4,4,2,2,2,2,3,2,1,0,26.0,neutral or dissatisfied +4856,2983,Male,Loyal Customer,46,Personal Travel,Eco,462,4,4,4,3,3,4,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +4857,107801,Female,disloyal Customer,40,Business travel,Business,349,2,2,2,1,5,2,5,5,5,4,5,3,4,5,15,7.0,neutral or dissatisfied +4858,112007,Female,disloyal Customer,65,Business travel,Eco Plus,133,2,2,2,3,4,2,5,4,3,4,3,2,3,4,14,15.0,neutral or dissatisfied +4859,18736,Female,Loyal Customer,32,Business travel,Eco,1167,4,2,2,2,4,4,4,5,3,2,1,4,1,4,136,150.0,satisfied +4860,67045,Female,Loyal Customer,35,Business travel,Business,1121,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +4861,107311,Male,Loyal Customer,13,Personal Travel,Eco,283,2,1,2,3,3,2,5,3,1,5,4,4,4,3,52,37.0,neutral or dissatisfied +4862,107521,Female,Loyal Customer,56,Personal Travel,Eco,838,2,5,2,2,5,5,5,2,2,2,2,3,2,4,30,23.0,neutral or dissatisfied +4863,126031,Male,Loyal Customer,37,Business travel,Business,600,2,2,2,2,2,5,5,5,5,5,5,5,5,3,48,40.0,satisfied +4864,92963,Female,disloyal Customer,19,Business travel,Eco,711,2,2,2,4,5,2,5,5,2,2,4,4,4,5,30,34.0,neutral or dissatisfied +4865,97426,Female,Loyal Customer,62,Personal Travel,Eco,570,2,2,1,3,2,2,3,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +4866,104148,Male,Loyal Customer,41,Business travel,Business,3312,2,2,2,2,5,5,5,5,5,5,5,5,5,5,6,1.0,satisfied +4867,38683,Male,Loyal Customer,22,Business travel,Eco Plus,2611,4,4,4,4,4,4,5,4,5,4,4,4,3,4,0,0.0,satisfied +4868,112898,Male,disloyal Customer,35,Business travel,Business,1129,2,2,2,2,2,2,2,2,4,1,3,3,3,2,23,16.0,neutral or dissatisfied +4869,115969,Female,Loyal Customer,64,Personal Travel,Eco,373,4,0,4,2,4,4,4,1,1,4,1,3,1,5,0,0.0,neutral or dissatisfied +4870,17054,Male,Loyal Customer,37,Business travel,Business,3346,3,3,5,3,4,5,2,5,5,5,5,1,5,4,0,0.0,satisfied +4871,84996,Male,disloyal Customer,29,Business travel,Business,1590,4,4,4,5,4,4,3,4,4,4,4,5,4,4,36,23.0,satisfied +4872,70086,Female,disloyal Customer,23,Business travel,Business,460,4,2,4,4,4,1,1,4,4,5,4,1,5,1,381,374.0,satisfied +4873,127427,Female,Loyal Customer,29,Personal Travel,Eco,868,1,3,1,4,2,1,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +4874,50995,Male,Loyal Customer,11,Personal Travel,Eco,110,2,2,2,3,2,2,2,2,2,4,4,3,4,2,70,64.0,neutral or dissatisfied +4875,41980,Male,Loyal Customer,34,Personal Travel,Eco,618,2,5,2,1,1,2,1,1,3,5,4,5,5,1,0,1.0,neutral or dissatisfied +4876,94531,Female,Loyal Customer,38,Business travel,Eco,323,3,1,1,1,3,4,3,3,1,3,4,2,4,3,27,27.0,neutral or dissatisfied +4877,66998,Male,Loyal Customer,60,Business travel,Business,1119,4,4,4,4,3,4,4,4,4,4,4,5,4,5,0,39.0,satisfied +4878,104326,Female,Loyal Customer,41,Business travel,Eco,452,1,5,2,2,1,1,1,1,1,1,4,1,3,1,27,35.0,neutral or dissatisfied +4879,97398,Female,Loyal Customer,10,Personal Travel,Eco Plus,872,2,2,2,2,5,2,1,5,3,4,4,3,4,5,0,0.0,neutral or dissatisfied +4880,122390,Female,Loyal Customer,27,Personal Travel,Eco,529,4,1,4,4,2,4,3,2,1,1,3,2,4,2,10,7.0,neutral or dissatisfied +4881,70313,Female,Loyal Customer,10,Personal Travel,Eco Plus,334,1,4,1,3,1,1,1,1,4,2,5,5,4,1,11,19.0,neutral or dissatisfied +4882,50607,Female,Loyal Customer,17,Personal Travel,Eco,156,2,5,2,3,2,2,2,2,5,5,5,3,4,2,0,0.0,neutral or dissatisfied +4883,29675,Male,Loyal Customer,32,Business travel,Eco Plus,909,4,2,2,2,4,4,4,4,5,1,5,5,3,4,0,0.0,satisfied +4884,43980,Male,Loyal Customer,53,Business travel,Eco,411,4,5,5,5,4,4,4,4,2,1,2,1,2,4,0,0.0,satisfied +4885,8032,Male,disloyal Customer,22,Business travel,Business,530,5,3,5,5,4,5,5,4,3,3,5,3,4,4,0,0.0,satisfied +4886,47072,Female,Loyal Customer,49,Personal Travel,Eco,351,1,4,1,4,2,4,3,5,5,1,5,3,5,3,0,0.0,neutral or dissatisfied +4887,93814,Female,Loyal Customer,49,Business travel,Business,391,4,4,4,4,2,5,5,4,4,4,4,5,4,4,62,84.0,satisfied +4888,111209,Female,Loyal Customer,35,Business travel,Eco,1506,1,0,0,3,0,3,3,3,2,2,3,3,2,3,90,135.0,neutral or dissatisfied +4889,122943,Female,disloyal Customer,50,Business travel,Business,590,5,0,0,4,3,5,5,3,4,2,4,5,4,3,0,0.0,satisfied +4890,75315,Female,Loyal Customer,36,Business travel,Business,2556,4,4,5,4,4,3,3,4,5,3,5,3,5,3,0,3.0,satisfied +4891,121072,Male,Loyal Customer,30,Business travel,Business,3218,4,4,4,4,2,2,2,2,3,4,5,3,5,2,0,0.0,satisfied +4892,40169,Male,Loyal Customer,46,Business travel,Eco,531,4,2,2,2,3,4,3,3,4,2,4,5,1,3,0,0.0,satisfied +4893,98502,Male,Loyal Customer,53,Business travel,Business,402,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +4894,128510,Female,Loyal Customer,15,Personal Travel,Eco,646,1,1,1,4,4,1,4,4,4,5,4,4,4,4,1,0.0,neutral or dissatisfied +4895,104243,Female,Loyal Customer,48,Business travel,Business,1741,2,2,2,2,5,5,5,5,5,5,5,4,5,4,14,48.0,satisfied +4896,94481,Female,Loyal Customer,48,Business travel,Business,239,0,1,1,4,5,5,5,3,3,3,3,3,3,5,30,28.0,satisfied +4897,4836,Male,Loyal Customer,58,Business travel,Business,3748,5,5,5,5,2,4,4,5,5,5,5,3,5,4,0,9.0,satisfied +4898,23914,Female,disloyal Customer,43,Business travel,Eco,189,4,3,5,3,1,5,1,1,3,5,3,3,4,1,12,20.0,neutral or dissatisfied +4899,35270,Female,Loyal Customer,45,Business travel,Eco,1005,2,1,3,3,3,3,3,2,2,2,2,2,2,1,57,67.0,neutral or dissatisfied +4900,33697,Male,Loyal Customer,49,Business travel,Business,759,2,2,2,2,2,2,1,4,4,4,4,1,4,4,0,0.0,satisfied +4901,111351,Male,disloyal Customer,36,Business travel,Business,777,1,1,1,1,1,1,1,1,5,5,5,3,4,1,1,0.0,neutral or dissatisfied +4902,21080,Female,disloyal Customer,63,Business travel,Eco,106,3,1,3,3,4,3,4,4,2,2,4,2,3,4,0,0.0,neutral or dissatisfied +4903,101337,Female,Loyal Customer,46,Personal Travel,Eco,1771,4,4,4,3,3,4,4,3,3,4,3,2,3,3,2,9.0,neutral or dissatisfied +4904,32570,Male,Loyal Customer,30,Business travel,Business,2172,4,4,4,4,5,5,5,5,5,4,2,5,1,5,0,0.0,satisfied +4905,101571,Female,Loyal Customer,70,Personal Travel,Eco Plus,345,2,5,2,2,2,4,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +4906,104170,Male,Loyal Customer,59,Business travel,Business,349,5,5,5,5,4,4,5,4,4,5,4,5,4,5,12,0.0,satisfied +4907,124637,Female,disloyal Customer,25,Business travel,Eco Plus,1671,4,2,4,3,4,4,3,4,4,3,2,4,4,4,0,9.0,neutral or dissatisfied +4908,27886,Female,Loyal Customer,13,Business travel,Eco,2329,5,5,5,5,5,5,4,5,5,1,5,4,2,5,0,0.0,satisfied +4909,73962,Female,Loyal Customer,66,Personal Travel,Eco,2585,3,5,3,3,3,2,3,2,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +4910,73511,Female,Loyal Customer,43,Business travel,Eco Plus,1197,3,1,3,1,5,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +4911,105519,Female,Loyal Customer,37,Business travel,Business,611,3,3,3,3,5,5,5,4,4,5,4,3,4,4,9,0.0,satisfied +4912,90504,Male,Loyal Customer,30,Business travel,Business,2667,1,1,1,1,4,4,4,4,5,5,5,5,5,4,11,0.0,satisfied +4913,38161,Female,Loyal Customer,33,Personal Travel,Eco,1197,4,4,5,5,3,5,4,3,3,3,5,5,4,3,38,20.0,neutral or dissatisfied +4914,105963,Female,Loyal Customer,39,Business travel,Eco,2329,4,3,3,3,4,4,4,4,3,2,3,4,3,4,18,34.0,neutral or dissatisfied +4915,26226,Female,Loyal Customer,22,Personal Travel,Eco,515,5,4,5,5,2,5,2,2,5,4,5,5,4,2,14,3.0,satisfied +4916,47567,Female,Loyal Customer,19,Personal Travel,Eco Plus,588,3,4,3,1,5,3,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +4917,103986,Female,Loyal Customer,20,Business travel,Business,1363,3,3,3,3,4,4,4,4,4,5,4,4,5,4,44,46.0,satisfied +4918,119373,Female,Loyal Customer,60,Business travel,Business,3014,4,4,4,4,3,5,5,5,5,5,5,5,5,5,12,5.0,satisfied +4919,67838,Female,Loyal Customer,38,Personal Travel,Eco,1313,4,5,4,2,2,4,2,2,3,2,4,3,5,2,12,32.0,satisfied +4920,113964,Female,Loyal Customer,55,Business travel,Business,1750,1,1,1,1,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +4921,41290,Male,Loyal Customer,38,Business travel,Eco Plus,542,4,4,4,4,4,5,4,4,2,2,1,1,1,4,45,34.0,satisfied +4922,68257,Female,Loyal Customer,9,Personal Travel,Eco,631,3,2,3,3,3,3,3,3,1,5,4,3,3,3,17,0.0,neutral or dissatisfied +4923,93068,Male,Loyal Customer,53,Personal Travel,Eco,297,3,5,3,4,3,3,3,3,4,5,5,3,4,3,36,28.0,neutral or dissatisfied +4924,5894,Male,Loyal Customer,54,Business travel,Business,3295,1,1,1,1,5,4,4,5,5,5,5,5,5,5,0,1.0,satisfied +4925,42835,Male,Loyal Customer,55,Business travel,Business,2742,0,0,0,4,4,2,3,2,2,2,2,4,2,3,30,13.0,satisfied +4926,97617,Female,Loyal Customer,38,Business travel,Business,3031,4,5,5,5,4,4,4,4,4,4,4,3,4,1,0,2.0,neutral or dissatisfied +4927,56867,Male,disloyal Customer,29,Business travel,Eco,2454,1,1,1,3,1,4,4,4,4,3,3,4,1,4,51,57.0,neutral or dissatisfied +4928,112191,Female,Loyal Customer,41,Business travel,Business,895,3,5,3,3,3,4,4,4,4,4,4,5,4,4,16,19.0,satisfied +4929,7072,Female,Loyal Customer,39,Business travel,Business,157,5,5,3,5,4,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +4930,6221,Male,disloyal Customer,33,Business travel,Business,594,2,2,2,1,3,2,4,3,4,4,5,4,5,3,37,26.0,neutral or dissatisfied +4931,20590,Male,disloyal Customer,36,Business travel,Eco Plus,533,2,2,2,3,2,2,2,2,2,5,4,4,4,2,36,35.0,neutral or dissatisfied +4932,95466,Female,Loyal Customer,43,Business travel,Business,319,0,0,0,4,2,4,5,1,1,1,1,3,1,5,0,0.0,satisfied +4933,14688,Male,disloyal Customer,25,Business travel,Eco,479,4,4,4,1,2,4,2,2,3,4,5,4,2,2,0,0.0,neutral or dissatisfied +4934,52464,Male,Loyal Customer,17,Business travel,Eco Plus,370,3,3,3,3,3,3,4,3,1,2,3,4,3,3,12,14.0,neutral or dissatisfied +4935,31600,Male,Loyal Customer,34,Personal Travel,Eco,602,4,4,4,3,4,5,5,5,4,5,4,5,5,5,130,140.0,neutral or dissatisfied +4936,36264,Male,Loyal Customer,52,Business travel,Business,3599,1,1,1,1,2,3,3,1,1,1,1,1,1,3,82,100.0,neutral or dissatisfied +4937,62664,Female,Loyal Customer,46,Business travel,Business,1744,2,2,2,2,4,3,4,3,3,3,3,3,3,3,43,57.0,satisfied +4938,108791,Female,Loyal Customer,28,Business travel,Business,1887,1,1,1,1,5,5,5,5,3,3,1,5,2,5,0,0.0,satisfied +4939,50515,Female,Loyal Customer,18,Personal Travel,Eco,250,1,5,1,4,2,1,2,2,3,2,4,4,5,2,0,7.0,neutral or dissatisfied +4940,26087,Female,Loyal Customer,29,Business travel,Business,2511,5,5,5,5,4,4,4,4,2,5,2,2,4,4,0,0.0,satisfied +4941,120523,Female,Loyal Customer,45,Business travel,Business,3189,5,5,5,5,5,5,5,5,5,5,4,3,5,5,104,102.0,satisfied +4942,120353,Male,Loyal Customer,32,Business travel,Business,413,5,5,3,5,4,4,4,4,4,2,5,5,5,4,0,15.0,satisfied +4943,55652,Male,Loyal Customer,53,Business travel,Business,1641,0,0,0,4,2,5,4,5,5,5,3,4,5,3,0,16.0,satisfied +4944,79211,Male,Loyal Customer,51,Business travel,Business,490,5,5,5,5,3,4,5,4,4,4,4,2,4,4,0,0.0,satisfied +4945,55122,Female,Loyal Customer,42,Personal Travel,Eco,1346,4,5,3,2,5,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +4946,82412,Female,Loyal Customer,50,Business travel,Business,502,1,1,1,1,3,5,5,5,5,5,5,3,5,5,66,54.0,satisfied +4947,62289,Male,Loyal Customer,66,Business travel,Eco,414,3,5,5,5,3,3,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +4948,123698,Male,Loyal Customer,34,Personal Travel,Eco,214,2,4,2,3,4,2,4,4,1,5,4,1,4,4,0,26.0,neutral or dissatisfied +4949,110958,Female,Loyal Customer,46,Business travel,Business,197,1,4,4,4,3,3,3,3,3,3,1,3,3,4,8,29.0,neutral or dissatisfied +4950,29946,Male,disloyal Customer,22,Business travel,Eco,571,3,1,3,1,1,3,1,1,2,2,2,3,2,1,35,91.0,neutral or dissatisfied +4951,92177,Female,disloyal Customer,29,Business travel,Business,2079,1,1,1,4,5,1,5,5,5,2,4,5,5,5,0,1.0,neutral or dissatisfied +4952,53977,Male,Loyal Customer,59,Personal Travel,Eco,1325,1,4,1,4,4,1,4,4,3,2,3,5,4,4,0,0.0,neutral or dissatisfied +4953,46447,Male,Loyal Customer,50,Business travel,Eco Plus,1199,2,5,5,5,2,2,2,2,3,5,3,3,3,2,84,66.0,neutral or dissatisfied +4954,104379,Female,Loyal Customer,43,Business travel,Business,228,3,5,5,5,2,2,3,3,3,3,3,4,3,3,7,4.0,neutral or dissatisfied +4955,25692,Male,Loyal Customer,59,Business travel,Business,432,5,5,5,5,3,4,2,5,5,5,5,2,5,5,78,55.0,satisfied +4956,38315,Female,Loyal Customer,29,Business travel,Eco,1666,5,3,3,3,5,5,5,5,3,2,4,5,3,5,0,18.0,satisfied +4957,53815,Male,Loyal Customer,48,Business travel,Eco,191,5,1,1,1,5,5,5,5,3,2,5,2,3,5,0,0.0,satisfied +4958,18925,Male,Loyal Customer,58,Personal Travel,Eco,503,2,4,2,5,4,2,5,4,5,2,4,5,4,4,3,0.0,neutral or dissatisfied +4959,55930,Male,Loyal Customer,69,Personal Travel,Eco,723,3,1,3,4,4,3,4,4,3,4,3,1,4,4,0,0.0,neutral or dissatisfied +4960,50215,Female,Loyal Customer,33,Business travel,Eco,77,1,5,5,5,1,1,1,1,3,3,4,2,3,1,25,20.0,neutral or dissatisfied +4961,104659,Female,Loyal Customer,43,Business travel,Business,1650,2,2,2,2,4,4,4,4,4,4,4,5,4,3,45,42.0,satisfied +4962,54404,Female,Loyal Customer,42,Business travel,Eco,305,4,1,2,1,3,2,5,4,4,4,4,3,4,3,4,0.0,satisfied +4963,70244,Male,disloyal Customer,31,Business travel,Eco,1282,1,0,0,3,5,1,1,5,4,1,3,1,4,5,13,0.0,neutral or dissatisfied +4964,87909,Male,Loyal Customer,46,Business travel,Business,2096,5,5,5,5,4,5,4,4,4,4,4,3,4,4,4,0.0,satisfied +4965,52937,Female,Loyal Customer,27,Personal Travel,Eco,679,3,5,3,1,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +4966,63457,Male,Loyal Customer,55,Business travel,Business,447,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +4967,122722,Male,disloyal Customer,45,Business travel,Business,651,1,1,1,3,3,1,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +4968,24316,Male,Loyal Customer,33,Business travel,Business,3648,1,5,5,5,1,1,1,1,3,2,3,3,3,1,117,108.0,neutral or dissatisfied +4969,113341,Female,disloyal Customer,23,Business travel,Eco,258,4,5,4,4,4,2,2,3,3,4,5,2,3,2,111,140.0,neutral or dissatisfied +4970,2302,Female,Loyal Customer,63,Business travel,Business,691,4,4,4,4,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +4971,20080,Male,Loyal Customer,60,Business travel,Eco Plus,738,3,1,1,1,3,3,3,3,4,1,4,1,3,3,44,36.0,neutral or dissatisfied +4972,123011,Female,Loyal Customer,52,Business travel,Business,650,5,5,5,5,3,4,5,4,4,4,4,5,4,5,64,64.0,satisfied +4973,113603,Female,disloyal Customer,25,Business travel,Eco,407,3,4,3,1,4,3,4,4,5,3,2,4,2,4,0,0.0,neutral or dissatisfied +4974,115392,Female,Loyal Customer,68,Business travel,Business,3043,2,2,2,2,5,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +4975,126589,Female,Loyal Customer,59,Business travel,Business,1337,5,5,5,5,3,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +4976,97261,Female,Loyal Customer,53,Personal Travel,Eco,296,4,4,4,3,1,3,3,2,2,4,2,2,2,1,0,0.0,satisfied +4977,26217,Female,Loyal Customer,24,Personal Travel,Eco,270,4,0,5,1,2,5,2,2,5,5,4,4,4,2,44,41.0,neutral or dissatisfied +4978,26418,Female,Loyal Customer,58,Personal Travel,Business,787,2,1,2,4,5,4,3,4,4,2,4,3,4,4,7,31.0,neutral or dissatisfied +4979,49702,Male,Loyal Customer,40,Business travel,Eco,363,4,5,5,5,4,4,4,4,1,5,3,4,4,4,0,0.0,neutral or dissatisfied +4980,85639,Male,Loyal Customer,43,Personal Travel,Eco,259,1,5,1,2,2,1,5,2,1,3,5,1,3,2,1,0.0,neutral or dissatisfied +4981,103477,Male,Loyal Customer,60,Business travel,Business,440,4,4,4,4,4,5,4,4,4,4,4,4,4,4,17,0.0,satisfied +4982,24618,Female,disloyal Customer,35,Business travel,Eco,666,2,4,3,3,5,3,3,5,2,2,4,1,4,5,0,26.0,neutral or dissatisfied +4983,53866,Female,Loyal Customer,34,Business travel,Business,191,2,3,3,3,5,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +4984,41599,Female,Loyal Customer,60,Personal Travel,Eco,1504,3,3,3,3,5,4,3,1,1,3,1,2,1,2,28,25.0,neutral or dissatisfied +4985,117296,Female,disloyal Customer,37,Business travel,Business,304,4,4,4,4,3,4,3,3,4,4,4,4,4,3,0,0.0,satisfied +4986,4049,Female,Loyal Customer,13,Personal Travel,Eco,479,3,4,3,3,4,3,4,4,1,4,3,2,4,4,0,0.0,neutral or dissatisfied +4987,1282,Female,Loyal Customer,11,Personal Travel,Eco,247,1,1,1,2,2,1,2,2,3,5,3,4,3,2,0,12.0,neutral or dissatisfied +4988,101138,Female,Loyal Customer,62,Business travel,Business,1235,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +4989,115279,Female,Loyal Customer,31,Business travel,Business,3702,4,5,4,4,4,4,4,4,2,3,1,1,2,4,71,69.0,neutral or dissatisfied +4990,69537,Female,Loyal Customer,52,Business travel,Business,2586,3,3,3,3,4,4,4,3,3,4,5,4,4,4,0,0.0,satisfied +4991,21324,Female,Loyal Customer,45,Business travel,Business,3067,4,4,4,4,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +4992,62792,Female,Loyal Customer,52,Personal Travel,Eco,2449,3,3,2,1,2,3,3,5,2,5,4,3,2,3,2,6.0,neutral or dissatisfied +4993,125665,Female,disloyal Customer,25,Business travel,Eco,759,3,4,4,4,4,4,4,4,3,1,3,1,3,4,0,0.0,neutral or dissatisfied +4994,86672,Female,Loyal Customer,41,Personal Travel,Eco Plus,746,3,5,3,4,5,3,3,3,3,3,3,5,3,4,4,28.0,neutral or dissatisfied +4995,52046,Male,Loyal Customer,53,Business travel,Business,3095,3,3,3,3,4,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +4996,46605,Male,disloyal Customer,21,Business travel,Eco,125,4,0,4,4,5,4,5,5,3,4,4,1,1,5,58,60.0,satisfied +4997,24174,Male,Loyal Customer,59,Business travel,Eco,302,4,3,3,3,4,4,4,4,5,2,4,1,2,4,0,0.0,satisfied +4998,105290,Male,disloyal Customer,25,Business travel,Business,738,1,4,2,4,3,2,1,3,5,5,5,4,5,3,86,71.0,neutral or dissatisfied +4999,129185,Female,Loyal Customer,45,Business travel,Business,2288,4,4,4,4,4,3,4,5,5,4,5,3,5,3,0,11.0,satisfied +5000,1006,Male,Loyal Customer,57,Business travel,Business,2116,4,2,4,4,3,1,2,5,5,4,4,1,5,1,0,0.0,satisfied +5001,26440,Male,disloyal Customer,24,Business travel,Eco,925,5,5,5,2,3,5,3,3,1,3,1,2,1,3,0,0.0,satisfied +5002,4232,Male,disloyal Customer,35,Business travel,Business,1020,3,3,3,3,5,3,5,5,5,2,4,5,4,5,1,0.0,neutral or dissatisfied +5003,26916,Female,Loyal Customer,35,Business travel,Business,1770,2,2,2,2,3,3,4,5,5,5,5,1,5,4,0,0.0,satisfied +5004,123277,Female,Loyal Customer,45,Personal Travel,Eco,600,2,2,2,2,2,4,5,5,5,2,5,5,5,3,0,4.0,neutral or dissatisfied +5005,5796,Female,Loyal Customer,43,Business travel,Business,1726,4,4,4,4,2,5,4,4,4,4,4,4,4,3,1,6.0,satisfied +5006,44747,Male,disloyal Customer,24,Business travel,Eco,717,0,0,0,4,4,0,3,4,5,3,2,3,5,4,0,5.0,satisfied +5007,14673,Male,Loyal Customer,50,Business travel,Business,416,3,3,3,3,1,5,2,5,5,5,5,2,5,4,0,0.0,satisfied +5008,54866,Male,Loyal Customer,39,Business travel,Business,862,3,3,3,3,3,2,3,3,3,3,3,4,3,3,6,0.0,neutral or dissatisfied +5009,101982,Male,Loyal Customer,45,Personal Travel,Eco,628,1,1,1,3,5,1,5,5,4,1,3,4,4,5,0,0.0,neutral or dissatisfied +5010,78232,Male,Loyal Customer,60,Personal Travel,Eco,259,2,1,2,3,5,2,5,5,4,4,3,1,4,5,0,0.0,neutral or dissatisfied +5011,81187,Male,Loyal Customer,61,Business travel,Business,3121,2,1,2,2,3,5,4,5,5,5,5,1,5,4,0,0.0,satisfied +5012,90119,Female,Loyal Customer,15,Business travel,Eco,1022,3,3,3,3,3,3,4,3,4,2,3,2,3,3,0,0.0,neutral or dissatisfied +5013,54756,Female,Loyal Customer,48,Business travel,Eco Plus,964,3,1,1,1,2,3,3,2,2,3,2,3,2,3,34,19.0,satisfied +5014,47561,Female,Loyal Customer,67,Personal Travel,Eco Plus,590,1,5,1,5,5,5,4,3,3,1,3,5,3,3,0,0.0,neutral or dissatisfied +5015,16264,Male,Loyal Customer,21,Business travel,Business,946,3,4,4,4,3,2,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +5016,9606,Male,Loyal Customer,69,Personal Travel,Eco,228,3,4,3,5,2,3,2,2,4,4,4,4,4,2,5,5.0,neutral or dissatisfied +5017,117473,Female,disloyal Customer,28,Business travel,Business,507,4,4,4,3,4,4,5,4,4,5,4,5,5,4,0,0.0,satisfied +5018,63487,Male,Loyal Customer,44,Business travel,Business,2691,1,1,3,1,2,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +5019,38063,Female,Loyal Customer,34,Business travel,Business,1185,3,2,2,2,4,3,4,3,3,3,3,4,3,1,11,0.0,neutral or dissatisfied +5020,112861,Male,disloyal Customer,25,Business travel,Eco,1313,1,1,1,1,5,1,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +5021,35898,Female,Loyal Customer,40,Business travel,Eco Plus,1065,4,2,2,2,4,4,4,4,4,2,2,2,1,4,63,66.0,satisfied +5022,90446,Male,Loyal Customer,58,Business travel,Business,3491,3,3,3,3,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +5023,23613,Female,Loyal Customer,32,Personal Travel,Eco Plus,692,3,5,3,2,3,3,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +5024,109663,Male,Loyal Customer,50,Business travel,Eco,802,2,2,2,2,2,2,2,2,2,2,4,2,3,2,0,2.0,neutral or dissatisfied +5025,18957,Female,Loyal Customer,42,Business travel,Eco Plus,448,5,5,4,5,5,4,2,5,5,5,5,4,5,4,7,1.0,satisfied +5026,122795,Female,Loyal Customer,16,Business travel,Business,599,5,5,4,5,3,3,3,3,5,4,5,4,5,3,0,3.0,satisfied +5027,17484,Male,Loyal Customer,37,Business travel,Eco,352,4,1,5,1,4,4,4,4,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +5028,96236,Male,Loyal Customer,76,Business travel,Eco,460,1,1,4,4,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +5029,48967,Male,Loyal Customer,38,Business travel,Eco,86,3,3,3,3,3,3,3,3,1,5,5,3,2,3,4,2.0,satisfied +5030,19451,Female,disloyal Customer,32,Business travel,Eco,231,4,4,3,3,4,3,4,4,3,2,1,3,4,4,0,0.0,neutral or dissatisfied +5031,110091,Male,disloyal Customer,21,Business travel,Business,882,5,0,5,4,4,5,1,4,3,4,5,4,5,4,1,11.0,satisfied +5032,95955,Male,Loyal Customer,53,Business travel,Business,1999,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +5033,1974,Male,Loyal Customer,31,Personal Travel,Eco,293,5,4,5,4,5,5,5,5,4,5,3,2,4,5,5,0.0,satisfied +5034,98225,Male,Loyal Customer,56,Personal Travel,Eco Plus,842,2,3,2,5,3,2,3,3,1,5,5,5,5,3,16,9.0,neutral or dissatisfied +5035,47827,Male,Loyal Customer,55,Business travel,Eco,834,5,1,1,1,5,4,4,2,4,2,4,4,4,4,156,142.0,satisfied +5036,21943,Male,Loyal Customer,68,Business travel,Business,1831,2,2,2,2,3,1,2,4,4,4,4,1,4,1,0,0.0,satisfied +5037,15973,Male,Loyal Customer,57,Personal Travel,Eco Plus,738,3,4,3,1,2,3,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +5038,42666,Female,Loyal Customer,38,Business travel,Business,1705,4,4,2,4,1,4,1,5,5,5,5,1,5,4,0,0.0,satisfied +5039,11755,Female,Loyal Customer,47,Business travel,Eco,429,5,3,2,3,4,5,3,5,5,5,5,4,5,2,30,22.0,satisfied +5040,58519,Male,Loyal Customer,49,Personal Travel,Eco,719,3,2,3,3,1,3,1,1,3,3,4,1,3,1,4,0.0,neutral or dissatisfied +5041,50207,Male,Loyal Customer,28,Business travel,Eco,86,1,3,3,3,1,1,1,1,2,5,4,2,4,1,0,0.0,neutral or dissatisfied +5042,68358,Male,disloyal Customer,23,Business travel,Eco,1322,4,4,4,3,1,4,1,1,3,4,3,3,4,1,34,38.0,satisfied +5043,66579,Female,disloyal Customer,22,Business travel,Eco,761,1,1,1,3,1,1,1,1,1,3,3,2,2,1,7,0.0,neutral or dissatisfied +5044,16850,Male,disloyal Customer,39,Business travel,Business,708,3,3,3,3,1,3,5,1,4,5,2,1,3,1,90,122.0,neutral or dissatisfied +5045,44735,Female,disloyal Customer,39,Business travel,Eco Plus,67,2,2,2,3,4,2,5,4,5,2,2,1,2,4,0,0.0,neutral or dissatisfied +5046,91337,Female,Loyal Customer,53,Personal Travel,Eco Plus,240,3,4,0,1,4,4,4,4,4,0,4,4,4,4,0,0.0,neutral or dissatisfied +5047,87394,Male,Loyal Customer,63,Business travel,Business,2464,1,1,1,1,1,3,4,5,5,5,5,4,5,1,10,14.0,satisfied +5048,38148,Male,Loyal Customer,65,Personal Travel,Eco,1121,3,5,3,1,1,3,1,1,4,3,4,4,4,1,1,0.0,neutral or dissatisfied +5049,47364,Male,disloyal Customer,20,Business travel,Eco,574,2,2,2,4,5,2,5,5,3,2,4,2,3,5,0,3.0,neutral or dissatisfied +5050,93738,Male,Loyal Customer,31,Business travel,Business,368,2,2,2,2,4,4,4,4,5,3,5,5,4,4,0,4.0,satisfied +5051,49418,Male,Loyal Customer,40,Business travel,Business,3441,4,4,4,4,5,3,4,5,5,5,4,5,5,4,0,0.0,satisfied +5052,89903,Male,Loyal Customer,42,Business travel,Business,3550,3,3,3,3,2,5,4,3,3,3,3,3,3,3,20,1.0,satisfied +5053,90,Male,Loyal Customer,41,Business travel,Business,2865,2,2,4,2,3,4,4,5,5,5,5,4,5,3,72,78.0,satisfied +5054,81554,Female,Loyal Customer,50,Business travel,Business,936,1,1,1,1,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +5055,45968,Female,Loyal Customer,27,Business travel,Business,1601,5,5,5,5,5,5,5,5,4,3,1,4,5,5,0,13.0,satisfied +5056,16483,Male,Loyal Customer,57,Business travel,Business,2355,1,4,4,4,2,3,2,1,1,1,1,1,1,1,79,75.0,neutral or dissatisfied +5057,36025,Male,Loyal Customer,51,Business travel,Eco,399,4,5,5,5,4,4,4,4,1,5,5,4,2,4,13,5.0,satisfied +5058,55766,Female,Loyal Customer,44,Business travel,Business,224,3,3,3,3,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +5059,9040,Male,Loyal Customer,41,Business travel,Business,3382,1,1,5,1,4,4,3,2,2,3,1,1,2,1,43,37.0,neutral or dissatisfied +5060,125350,Male,Loyal Customer,51,Business travel,Business,2293,1,1,3,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +5061,80426,Male,disloyal Customer,22,Business travel,Eco,2248,1,0,0,1,5,1,5,5,5,5,3,5,4,5,1,0.0,neutral or dissatisfied +5062,100885,Female,Loyal Customer,51,Business travel,Business,377,3,3,3,3,4,5,5,2,2,2,2,5,2,4,0,0.0,satisfied +5063,78495,Male,Loyal Customer,59,Business travel,Eco,666,2,5,5,5,2,2,2,2,3,2,4,2,4,2,0,0.0,neutral or dissatisfied +5064,17540,Female,Loyal Customer,20,Business travel,Business,908,3,3,3,3,4,4,4,4,4,5,5,3,5,4,49,33.0,satisfied +5065,83455,Male,Loyal Customer,60,Business travel,Business,946,1,1,1,1,3,4,4,4,4,4,4,3,4,3,0,17.0,satisfied +5066,34929,Female,Loyal Customer,68,Personal Travel,Eco,187,1,3,1,3,4,4,3,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +5067,35918,Female,Loyal Customer,63,Personal Travel,Eco,2248,3,4,3,4,3,5,4,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +5068,127165,Male,Loyal Customer,63,Personal Travel,Eco,370,4,0,3,3,4,3,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +5069,918,Male,Loyal Customer,32,Business travel,Business,2702,4,5,4,5,4,4,4,4,2,4,4,3,3,4,1,2.0,neutral or dissatisfied +5070,3265,Female,disloyal Customer,30,Business travel,Eco,479,4,2,4,3,2,4,2,2,1,1,3,4,3,2,15,0.0,neutral or dissatisfied +5071,100449,Male,Loyal Customer,7,Personal Travel,Eco,1180,3,4,3,1,3,3,5,3,3,4,3,3,4,3,38,53.0,neutral or dissatisfied +5072,36026,Male,disloyal Customer,36,Business travel,Eco,399,1,3,1,4,5,1,5,5,1,1,5,1,2,5,0,1.0,neutral or dissatisfied +5073,111924,Female,Loyal Customer,68,Personal Travel,Eco,472,3,1,3,4,4,3,3,1,1,3,3,3,1,3,1,0.0,neutral or dissatisfied +5074,76506,Male,Loyal Customer,31,Business travel,Business,2008,2,4,2,4,2,2,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +5075,630,Male,Loyal Customer,40,Business travel,Business,134,3,3,3,3,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +5076,90022,Male,disloyal Customer,18,Business travel,Eco,957,4,4,4,5,2,4,1,2,4,2,4,5,5,2,0,0.0,satisfied +5077,26950,Female,Loyal Customer,27,Business travel,Eco Plus,2402,5,1,5,1,5,5,5,5,2,3,5,1,4,5,0,0.0,satisfied +5078,127597,Female,Loyal Customer,42,Business travel,Business,1773,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,5.0,satisfied +5079,104190,Female,Loyal Customer,15,Personal Travel,Eco Plus,349,2,5,2,3,2,2,2,2,3,5,5,4,4,2,60,75.0,neutral or dissatisfied +5080,37465,Female,Loyal Customer,39,Business travel,Business,1076,2,2,2,2,3,3,2,4,4,4,4,5,4,2,0,0.0,satisfied +5081,8250,Male,Loyal Customer,39,Personal Travel,Eco,125,4,3,4,3,5,4,5,5,4,5,1,3,4,5,0,0.0,neutral or dissatisfied +5082,69679,Male,Loyal Customer,34,Personal Travel,Eco,569,3,4,3,4,1,3,5,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +5083,680,Male,Loyal Customer,46,Business travel,Business,3259,4,4,3,4,3,5,5,4,4,4,4,4,4,5,46,60.0,satisfied +5084,46679,Female,Loyal Customer,16,Personal Travel,Eco,125,4,3,4,4,1,4,1,1,3,2,4,2,4,1,55,54.0,neutral or dissatisfied +5085,14404,Male,Loyal Customer,42,Business travel,Eco Plus,789,5,5,2,5,5,5,5,4,1,1,5,5,1,5,151,127.0,satisfied +5086,46560,Female,Loyal Customer,47,Business travel,Business,2232,4,4,4,4,3,2,4,4,4,4,3,4,4,3,63,60.0,satisfied +5087,5325,Male,Loyal Customer,53,Business travel,Business,812,2,2,2,2,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +5088,52081,Female,Loyal Customer,62,Business travel,Business,2648,5,5,5,5,3,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +5089,6183,Male,Loyal Customer,38,Personal Travel,Eco,491,2,5,2,5,3,2,5,3,4,5,5,4,4,3,59,65.0,neutral or dissatisfied +5090,37074,Male,Loyal Customer,22,Personal Travel,Eco,1072,5,4,5,4,2,5,2,2,3,5,5,5,5,2,2,0.0,satisfied +5091,111933,Male,Loyal Customer,7,Personal Travel,Business,533,2,4,2,2,1,2,4,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +5092,85660,Male,Loyal Customer,45,Business travel,Business,2462,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +5093,76622,Male,Loyal Customer,49,Business travel,Business,2735,0,5,0,5,4,1,2,1,1,1,1,5,1,5,0,0.0,satisfied +5094,107055,Male,disloyal Customer,25,Business travel,Eco,395,2,2,2,3,4,2,4,4,4,3,4,3,3,4,45,64.0,neutral or dissatisfied +5095,95443,Male,Loyal Customer,38,Business travel,Business,239,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +5096,105766,Female,Loyal Customer,75,Business travel,Business,3680,4,4,4,4,2,1,2,4,4,4,4,5,4,5,0,0.0,satisfied +5097,56218,Male,Loyal Customer,40,Business travel,Business,1608,5,5,5,5,3,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +5098,39348,Male,disloyal Customer,30,Business travel,Business,896,3,3,3,3,2,3,2,2,4,2,5,4,4,2,0,3.0,neutral or dissatisfied +5099,4450,Female,disloyal Customer,22,Business travel,Eco,762,5,5,5,2,2,5,2,2,4,2,4,3,5,2,0,26.0,satisfied +5100,2285,Male,Loyal Customer,51,Business travel,Business,3839,3,3,3,3,5,5,4,2,2,2,2,5,2,4,0,0.0,satisfied +5101,76371,Female,disloyal Customer,25,Business travel,Business,931,4,5,4,3,1,4,1,1,4,3,4,3,5,1,14,15.0,neutral or dissatisfied +5102,6395,Male,Loyal Customer,61,Business travel,Eco,213,5,4,4,4,5,5,5,5,1,4,4,2,3,5,0,0.0,satisfied +5103,80119,Male,disloyal Customer,26,Business travel,Business,2475,4,4,4,3,4,2,2,5,3,3,4,2,5,2,8,15.0,neutral or dissatisfied +5104,7642,Female,Loyal Customer,43,Business travel,Business,767,2,2,2,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +5105,104674,Female,Loyal Customer,14,Personal Travel,Eco,641,4,4,4,3,4,4,4,4,3,3,4,4,5,4,0,15.0,neutral or dissatisfied +5106,9061,Male,Loyal Customer,60,Business travel,Eco,212,2,4,4,4,2,2,2,2,3,2,3,3,2,2,12,15.0,neutral or dissatisfied +5107,97347,Male,Loyal Customer,45,Business travel,Eco,347,4,3,3,3,4,4,4,4,4,1,4,4,5,4,0,0.0,satisfied +5108,57085,Male,Loyal Customer,52,Personal Travel,Business,1222,3,2,3,3,2,3,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +5109,50042,Male,disloyal Customer,27,Business travel,Eco,207,2,0,2,1,4,2,1,4,1,5,2,1,4,4,0,0.0,neutral or dissatisfied +5110,15446,Female,Loyal Customer,43,Business travel,Business,164,1,3,3,3,2,2,1,4,4,3,1,4,4,2,0,0.0,neutral or dissatisfied +5111,90646,Male,Loyal Customer,47,Business travel,Business,581,1,1,1,1,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +5112,48606,Female,Loyal Customer,43,Personal Travel,Eco,833,2,4,2,1,5,4,4,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +5113,92555,Female,Loyal Customer,25,Personal Travel,Eco,1947,3,5,3,3,3,3,3,3,3,5,3,3,4,3,6,10.0,neutral or dissatisfied +5114,103785,Male,Loyal Customer,54,Business travel,Business,2806,2,2,2,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +5115,22004,Male,Loyal Customer,58,Personal Travel,Eco,448,4,4,4,4,4,1,3,5,3,5,4,3,4,3,146,125.0,neutral or dissatisfied +5116,115842,Male,disloyal Customer,16,Business travel,Eco,362,1,1,1,3,3,1,3,3,1,1,4,2,3,3,21,16.0,neutral or dissatisfied +5117,17296,Male,Loyal Customer,47,Business travel,Business,438,3,2,5,5,1,3,3,3,3,3,3,3,3,2,0,15.0,neutral or dissatisfied +5118,62057,Female,Loyal Customer,33,Personal Travel,Eco,2475,3,5,4,3,3,4,3,3,5,2,5,3,4,3,12,9.0,neutral or dissatisfied +5119,63333,Female,disloyal Customer,23,Business travel,Eco,372,2,3,2,4,2,2,1,2,3,4,3,3,3,2,0,11.0,neutral or dissatisfied +5120,14658,Female,Loyal Customer,54,Personal Travel,Eco,162,3,4,3,4,3,5,4,3,3,3,3,3,3,4,19,8.0,neutral or dissatisfied +5121,48097,Female,Loyal Customer,51,Business travel,Business,192,0,5,0,4,5,2,3,5,5,3,3,4,5,2,60,54.0,satisfied +5122,5215,Male,Loyal Customer,59,Business travel,Business,351,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +5123,41557,Male,Loyal Customer,58,Business travel,Eco,1504,2,2,2,2,2,2,2,2,1,1,4,1,4,2,27,42.0,neutral or dissatisfied +5124,8883,Male,disloyal Customer,73,Business travel,Business,222,2,2,2,4,1,2,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +5125,13043,Female,Loyal Customer,65,Personal Travel,Eco,304,3,5,3,2,3,5,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +5126,97597,Male,Loyal Customer,41,Business travel,Business,442,5,5,5,5,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +5127,73729,Female,Loyal Customer,63,Personal Travel,Eco,192,2,5,2,3,3,4,5,3,3,2,3,4,3,3,23,25.0,neutral or dissatisfied +5128,48146,Male,Loyal Customer,50,Business travel,Business,192,3,4,4,4,4,4,4,2,2,2,3,2,2,1,0,0.0,neutral or dissatisfied +5129,80480,Male,Loyal Customer,59,Personal Travel,Eco,1299,1,4,1,1,4,1,4,4,3,4,4,3,5,4,0,4.0,neutral or dissatisfied +5130,28747,Female,disloyal Customer,8,Business travel,Eco,1024,4,4,4,3,5,4,3,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +5131,111879,Male,Loyal Customer,37,Business travel,Business,3022,1,1,5,1,5,4,4,3,3,4,3,4,3,3,0,2.0,satisfied +5132,79184,Male,Loyal Customer,42,Personal Travel,Eco,2422,3,4,3,1,3,4,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +5133,64927,Male,disloyal Customer,25,Business travel,Business,282,4,1,4,3,4,4,4,4,2,1,4,3,3,4,0,0.0,neutral or dissatisfied +5134,67804,Female,disloyal Customer,25,Business travel,Eco,1235,2,2,2,3,2,2,2,2,3,1,5,5,5,2,3,1.0,neutral or dissatisfied +5135,28153,Female,disloyal Customer,17,Business travel,Eco,933,1,1,1,4,3,1,3,3,1,5,2,1,1,3,0,0.0,neutral or dissatisfied +5136,54100,Female,Loyal Customer,38,Business travel,Eco Plus,1416,5,3,3,3,5,5,5,5,2,4,2,5,4,5,7,3.0,satisfied +5137,92138,Female,Loyal Customer,10,Personal Travel,Eco,1532,3,4,3,1,4,3,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +5138,125650,Female,Loyal Customer,60,Business travel,Business,814,2,2,4,2,5,5,4,5,5,5,5,3,5,3,4,0.0,satisfied +5139,103757,Female,disloyal Customer,51,Business travel,Business,484,1,1,1,1,4,1,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +5140,101511,Male,Loyal Customer,52,Business travel,Eco,345,4,4,4,4,4,4,4,4,5,3,4,1,3,4,51,48.0,satisfied +5141,3593,Male,disloyal Customer,11,Business travel,Eco,999,2,2,2,1,4,2,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +5142,50187,Male,Loyal Customer,47,Business travel,Business,3572,1,1,1,1,5,4,5,4,4,5,3,4,4,1,0,0.0,satisfied +5143,10572,Male,disloyal Customer,22,Business travel,Eco,201,2,4,2,4,5,2,5,5,4,5,4,5,4,5,45,45.0,neutral or dissatisfied +5144,18624,Female,Loyal Customer,64,Personal Travel,Eco,285,1,3,1,1,4,3,5,4,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +5145,37655,Female,Loyal Customer,36,Personal Travel,Eco,1035,3,4,3,2,1,3,1,1,5,5,4,4,4,1,18,3.0,neutral or dissatisfied +5146,120953,Female,Loyal Customer,31,Business travel,Business,2146,3,5,4,5,3,3,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +5147,31861,Male,Loyal Customer,31,Business travel,Eco,2599,0,0,0,5,3,0,3,3,5,1,5,2,5,3,0,0.0,satisfied +5148,23396,Male,disloyal Customer,43,Business travel,Eco,300,1,4,1,3,2,1,2,2,2,2,4,4,4,2,0,20.0,neutral or dissatisfied +5149,77654,Male,Loyal Customer,35,Business travel,Eco,813,4,3,4,4,4,4,4,4,4,1,2,3,2,4,0,0.0,neutral or dissatisfied +5150,64691,Female,Loyal Customer,43,Business travel,Business,247,2,2,2,2,4,5,4,4,4,4,4,4,4,4,58,67.0,satisfied +5151,85061,Male,Loyal Customer,48,Business travel,Business,3666,4,4,4,4,4,5,4,5,5,5,5,3,5,3,7,2.0,satisfied +5152,111156,Female,Loyal Customer,29,Personal Travel,Eco,1050,5,5,5,4,4,5,4,4,4,5,4,3,5,4,2,0.0,satisfied +5153,12507,Male,Loyal Customer,47,Personal Travel,Eco Plus,201,2,2,2,3,1,2,1,1,1,1,4,3,4,1,0,0.0,neutral or dissatisfied +5154,67292,Female,Loyal Customer,50,Business travel,Business,2041,5,5,5,5,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +5155,129173,Female,Loyal Customer,8,Personal Travel,Eco,954,2,5,3,3,3,3,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +5156,70084,Male,Loyal Customer,53,Business travel,Business,2390,4,4,4,4,2,4,4,5,5,5,5,4,5,5,0,30.0,satisfied +5157,22866,Male,Loyal Customer,49,Personal Travel,Eco,147,1,4,0,2,5,0,5,5,5,1,3,2,2,5,14,2.0,neutral or dissatisfied +5158,126169,Male,disloyal Customer,37,Business travel,Business,507,4,4,4,4,5,4,5,5,5,2,4,5,5,5,0,0.0,satisfied +5159,26455,Female,Loyal Customer,25,Business travel,Eco,925,4,4,4,4,4,4,1,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +5160,22511,Male,disloyal Customer,38,Business travel,Eco Plus,83,1,2,2,4,5,2,5,5,1,4,5,5,1,5,5,11.0,neutral or dissatisfied +5161,63312,Male,Loyal Customer,67,Business travel,Business,3803,3,5,5,5,4,2,2,3,3,3,3,3,3,2,92,91.0,neutral or dissatisfied +5162,26600,Female,disloyal Customer,27,Business travel,Eco,406,2,3,2,3,4,2,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +5163,13722,Male,disloyal Customer,38,Business travel,Eco,441,3,4,3,3,3,3,3,3,3,3,3,3,3,3,100,104.0,neutral or dissatisfied +5164,7581,Male,Loyal Customer,57,Business travel,Business,3216,5,1,5,5,4,5,4,4,4,4,4,3,4,4,2,4.0,satisfied +5165,5270,Female,Loyal Customer,32,Personal Travel,Eco,351,3,4,3,4,4,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +5166,55539,Male,Loyal Customer,42,Business travel,Business,550,4,5,5,5,5,4,4,4,4,4,4,3,4,2,18,10.0,neutral or dissatisfied +5167,74371,Female,disloyal Customer,24,Business travel,Business,1464,4,0,4,4,2,4,2,2,3,5,4,3,4,2,0,0.0,satisfied +5168,110312,Male,Loyal Customer,49,Business travel,Business,842,5,5,5,5,2,4,5,4,4,4,4,4,4,4,56,64.0,satisfied +5169,73223,Female,Loyal Customer,31,Business travel,Business,2589,5,5,5,5,3,3,3,3,5,3,4,5,4,3,0,28.0,satisfied +5170,3380,Female,Loyal Customer,18,Business travel,Business,296,1,5,5,5,1,1,1,1,4,5,3,1,4,1,0,42.0,neutral or dissatisfied +5171,96827,Male,Loyal Customer,56,Business travel,Business,2784,4,4,4,4,5,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +5172,89263,Female,Loyal Customer,33,Business travel,Business,453,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +5173,57977,Male,Loyal Customer,18,Personal Travel,Eco,420,3,5,3,2,5,3,5,5,4,5,3,3,2,5,0,2.0,neutral or dissatisfied +5174,88699,Male,Loyal Customer,48,Personal Travel,Eco,240,4,2,4,3,2,4,4,2,1,3,2,3,3,2,0,0.0,neutral or dissatisfied +5175,2868,Female,disloyal Customer,25,Business travel,Eco,475,2,3,2,3,3,2,4,3,1,2,3,3,3,3,37,28.0,neutral or dissatisfied +5176,44897,Male,disloyal Customer,25,Business travel,Eco,136,2,0,3,1,3,3,3,3,3,3,4,2,5,3,0,7.0,neutral or dissatisfied +5177,29029,Male,Loyal Customer,57,Business travel,Eco,297,2,5,5,5,3,2,3,3,2,5,4,1,3,3,0,0.0,neutral or dissatisfied +5178,44181,Female,Loyal Customer,61,Business travel,Business,231,0,0,0,5,1,1,1,5,5,5,5,2,5,2,3,14.0,satisfied +5179,120008,Female,Loyal Customer,45,Business travel,Business,2616,3,3,3,3,2,4,4,3,3,3,3,1,3,3,29,17.0,neutral or dissatisfied +5180,113385,Male,Loyal Customer,59,Business travel,Business,2824,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +5181,433,Male,Loyal Customer,63,Personal Travel,Business,102,4,4,4,3,3,3,5,2,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +5182,93245,Male,Loyal Customer,48,Business travel,Business,689,3,5,2,5,2,3,3,3,3,3,3,4,3,2,53,35.0,neutral or dissatisfied +5183,85553,Female,Loyal Customer,53,Business travel,Business,2853,3,3,5,3,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +5184,35530,Female,Loyal Customer,23,Personal Travel,Eco,1144,3,5,3,3,5,3,5,5,2,4,4,4,2,5,0,15.0,neutral or dissatisfied +5185,12536,Female,Loyal Customer,36,Business travel,Business,1625,2,1,1,1,2,2,3,2,2,1,2,1,2,4,0,0.0,neutral or dissatisfied +5186,64064,Male,Loyal Customer,35,Business travel,Business,2254,3,3,3,3,1,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +5187,64863,Male,disloyal Customer,26,Business travel,Business,469,0,0,0,3,1,0,1,1,3,2,4,5,5,1,0,0.0,satisfied +5188,868,Male,Loyal Customer,57,Business travel,Business,113,4,2,2,2,2,3,4,1,1,1,4,1,1,1,0,0.0,neutral or dissatisfied +5189,74486,Male,disloyal Customer,26,Business travel,Business,1205,4,4,4,2,1,4,1,1,4,4,5,4,5,1,0,0.0,satisfied +5190,119321,Female,Loyal Customer,48,Personal Travel,Eco,214,3,0,3,5,2,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +5191,34297,Female,Loyal Customer,9,Personal Travel,Eco,280,2,4,2,2,2,2,2,2,4,3,5,5,2,2,0,0.0,neutral or dissatisfied +5192,105093,Female,Loyal Customer,53,Business travel,Business,1770,0,0,0,1,4,5,5,2,2,2,2,5,2,4,3,0.0,satisfied +5193,128534,Male,Loyal Customer,29,Personal Travel,Eco,651,2,5,2,2,1,2,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +5194,284,Female,disloyal Customer,17,Business travel,Eco,802,4,4,4,5,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +5195,69016,Female,Loyal Customer,43,Business travel,Business,1389,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5196,65011,Female,disloyal Customer,30,Business travel,Eco,190,1,4,1,4,4,1,4,4,4,5,1,5,4,4,0,0.0,neutral or dissatisfied +5197,36575,Female,Loyal Customer,47,Business travel,Eco,1237,4,5,5,5,2,2,2,4,4,4,4,1,4,1,0,0.0,satisfied +5198,50165,Male,Loyal Customer,33,Business travel,Business,2654,1,1,1,1,5,5,5,5,4,1,2,1,2,5,0,0.0,satisfied +5199,118414,Male,Loyal Customer,35,Business travel,Business,2422,5,5,5,5,2,5,4,5,5,5,5,5,5,5,29,23.0,satisfied +5200,63587,Female,disloyal Customer,27,Business travel,Business,1280,4,4,4,4,4,4,4,4,5,4,3,5,4,4,21,4.0,satisfied +5201,98419,Female,Loyal Customer,28,Business travel,Business,1910,4,4,4,4,3,4,3,3,5,3,3,5,5,3,109,69.0,satisfied +5202,63926,Female,Loyal Customer,41,Personal Travel,Eco,1172,3,5,3,2,1,3,1,1,4,4,3,4,4,1,0,6.0,neutral or dissatisfied +5203,57686,Female,Loyal Customer,60,Business travel,Business,2130,5,5,5,5,4,5,5,4,4,4,4,5,4,3,1,1.0,satisfied +5204,16126,Female,Loyal Customer,31,Personal Travel,Eco,725,5,4,5,1,2,5,2,2,4,3,3,5,2,2,0,0.0,satisfied +5205,70382,Male,Loyal Customer,44,Personal Travel,Business,1562,3,5,3,4,4,4,4,2,2,3,2,3,2,3,4,17.0,neutral or dissatisfied +5206,126247,Male,Loyal Customer,38,Business travel,Business,3890,1,1,1,1,2,1,4,4,4,4,4,1,4,1,0,0.0,satisfied +5207,44169,Male,Loyal Customer,60,Business travel,Business,2386,0,5,0,1,5,5,4,5,5,4,4,4,5,5,0,0.0,satisfied +5208,74952,Female,Loyal Customer,21,Business travel,Eco,2475,3,4,4,4,3,3,1,3,2,1,2,1,3,3,0,0.0,neutral or dissatisfied +5209,72455,Male,Loyal Customer,43,Business travel,Business,3331,1,3,1,1,3,5,4,4,4,4,4,4,4,3,7,22.0,satisfied +5210,41408,Male,Loyal Customer,61,Personal Travel,Eco,563,2,4,1,4,2,1,5,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +5211,74723,Female,Loyal Customer,61,Personal Travel,Eco,1438,2,4,2,1,3,5,5,4,4,2,4,5,4,4,0,9.0,neutral or dissatisfied +5212,19237,Male,disloyal Customer,15,Business travel,Eco,782,3,3,3,2,3,3,4,3,2,4,2,2,5,3,0,0.0,neutral or dissatisfied +5213,55182,Female,Loyal Customer,43,Business travel,Business,1635,5,5,5,5,2,4,5,5,5,5,5,5,5,3,5,0.0,satisfied +5214,43344,Male,disloyal Customer,24,Business travel,Eco,531,3,0,3,4,4,3,4,4,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +5215,104286,Male,Loyal Customer,49,Business travel,Business,1897,1,1,4,1,2,2,2,3,4,5,5,2,5,2,254,,satisfied +5216,119667,Female,Loyal Customer,62,Personal Travel,Eco,507,3,4,3,3,5,4,4,3,3,3,3,3,3,2,9,1.0,neutral or dissatisfied +5217,101029,Male,Loyal Customer,57,Personal Travel,Eco,867,2,0,2,4,3,2,3,3,3,4,4,3,5,3,78,91.0,neutral or dissatisfied +5218,106062,Female,Loyal Customer,55,Business travel,Business,302,0,0,0,1,2,4,4,1,1,1,1,4,1,3,0,2.0,satisfied +5219,33870,Male,Loyal Customer,40,Business travel,Business,2937,5,5,5,5,3,5,4,4,4,4,4,5,4,4,0,7.0,satisfied +5220,74608,Female,Loyal Customer,59,Business travel,Business,1574,4,4,4,4,4,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +5221,48160,Male,Loyal Customer,32,Business travel,Eco,236,0,0,0,2,3,0,3,3,4,1,3,1,4,3,45,51.0,satisfied +5222,61529,Female,Loyal Customer,46,Personal Travel,Eco,2288,3,2,3,4,2,4,3,5,5,3,5,3,5,4,0,0.0,neutral or dissatisfied +5223,27303,Male,Loyal Customer,46,Business travel,Business,956,4,4,4,4,2,4,3,3,3,4,3,2,3,1,0,0.0,satisfied +5224,28610,Male,Loyal Customer,33,Business travel,Business,2466,3,3,3,3,4,4,4,3,2,4,5,4,2,4,163,158.0,satisfied +5225,6209,Female,disloyal Customer,22,Business travel,Eco,462,1,0,1,2,5,1,2,5,3,4,4,3,5,5,0,0.0,neutral or dissatisfied +5226,50500,Male,Loyal Customer,46,Personal Travel,Eco,373,3,4,3,3,4,3,4,4,5,4,1,3,1,4,0,0.0,neutral or dissatisfied +5227,48922,Male,Loyal Customer,38,Business travel,Business,86,4,4,4,4,1,3,4,5,5,5,5,2,5,4,0,1.0,satisfied +5228,7685,Male,disloyal Customer,21,Business travel,Eco,204,4,1,4,2,5,4,5,5,1,2,4,2,1,5,0,0.0,satisfied +5229,120802,Male,Loyal Customer,51,Business travel,Business,2357,3,3,3,3,2,2,2,4,2,4,4,2,4,2,139,135.0,satisfied +5230,5336,Female,Loyal Customer,52,Business travel,Business,812,2,2,2,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +5231,70071,Male,Loyal Customer,42,Personal Travel,Business,460,4,5,4,5,3,4,4,3,3,4,3,4,3,3,7,0.0,neutral or dissatisfied +5232,66235,Male,Loyal Customer,36,Business travel,Business,2836,3,3,3,3,2,5,3,5,5,5,5,4,5,4,1,6.0,satisfied +5233,118390,Female,Loyal Customer,42,Business travel,Business,651,1,5,5,5,3,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +5234,76184,Male,disloyal Customer,34,Business travel,Business,2422,3,3,3,4,5,3,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +5235,68452,Male,disloyal Customer,43,Business travel,Business,1067,5,5,5,2,3,5,3,3,4,2,5,5,5,3,0,0.0,satisfied +5236,126882,Female,Loyal Customer,51,Personal Travel,Eco,2125,3,5,3,4,3,1,1,3,3,3,4,2,3,2,0,0.0,neutral or dissatisfied +5237,96575,Female,Loyal Customer,15,Personal Travel,Eco,333,3,4,3,1,4,3,5,4,4,3,4,4,4,4,3,0.0,neutral or dissatisfied +5238,62096,Male,Loyal Customer,40,Business travel,Business,2565,3,3,3,3,4,4,4,4,4,4,4,5,4,3,61,50.0,satisfied +5239,8828,Male,Loyal Customer,34,Personal Travel,Eco,522,3,4,3,3,3,3,4,3,5,3,5,4,4,3,0,12.0,neutral or dissatisfied +5240,123190,Male,Loyal Customer,70,Personal Travel,Eco,650,3,3,3,4,4,3,4,4,2,5,4,4,4,4,9,0.0,neutral or dissatisfied +5241,114396,Female,Loyal Customer,47,Business travel,Business,333,0,0,0,2,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +5242,18299,Male,Loyal Customer,37,Personal Travel,Eco,640,4,4,4,4,3,4,3,3,5,5,5,5,5,3,3,0.0,satisfied +5243,61737,Female,disloyal Customer,26,Business travel,Eco,1379,3,2,2,4,5,3,5,5,3,4,3,3,4,5,2,0.0,neutral or dissatisfied +5244,126284,Male,Loyal Customer,64,Personal Travel,Eco,507,3,5,3,1,3,1,1,5,4,4,5,1,3,1,153,144.0,neutral or dissatisfied +5245,2249,Female,Loyal Customer,43,Business travel,Business,2997,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,18.0,satisfied +5246,124360,Female,Loyal Customer,22,Business travel,Business,2498,4,4,4,4,5,5,5,5,4,2,4,3,5,5,0,0.0,satisfied +5247,23299,Female,Loyal Customer,35,Business travel,Eco,927,4,3,3,3,4,4,4,4,3,1,5,1,4,4,0,10.0,satisfied +5248,97848,Male,Loyal Customer,34,Personal Travel,Eco,395,2,5,2,3,3,2,3,3,3,5,2,5,2,3,0,0.0,neutral or dissatisfied +5249,126476,Male,Loyal Customer,56,Business travel,Business,1849,1,1,1,1,5,4,4,4,4,4,4,3,4,5,128,123.0,satisfied +5250,49749,Male,Loyal Customer,35,Business travel,Business,3715,3,3,4,3,3,3,3,3,4,4,3,3,1,3,163,164.0,neutral or dissatisfied +5251,110704,Male,Loyal Customer,57,Business travel,Eco Plus,429,4,2,2,2,4,4,4,4,4,4,2,3,4,4,2,0.0,satisfied +5252,82015,Male,Loyal Customer,53,Business travel,Eco,1189,4,2,2,2,4,4,4,4,1,2,3,3,3,4,0,13.0,neutral or dissatisfied +5253,94426,Female,Loyal Customer,78,Business travel,Eco,192,1,4,2,2,1,3,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +5254,125491,Female,Loyal Customer,28,Personal Travel,Eco Plus,2845,4,1,4,4,1,4,1,1,4,5,3,4,4,1,0,0.0,neutral or dissatisfied +5255,51543,Male,Loyal Customer,58,Business travel,Eco,455,5,3,3,3,3,5,3,3,5,5,5,4,2,3,0,0.0,satisfied +5256,23368,Female,Loyal Customer,43,Business travel,Business,3647,4,4,2,2,2,3,4,4,4,4,4,3,4,2,4,17.0,neutral or dissatisfied +5257,37119,Male,Loyal Customer,35,Business travel,Eco,1179,4,5,5,5,4,4,4,4,2,4,5,5,1,4,9,0.0,satisfied +5258,13281,Female,Loyal Customer,68,Personal Travel,Eco,657,2,2,2,2,3,2,2,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +5259,22286,Male,Loyal Customer,32,Business travel,Business,143,2,4,2,2,5,5,4,5,3,5,4,4,3,5,0,0.0,satisfied +5260,21625,Female,Loyal Customer,35,Business travel,Business,3272,3,3,1,3,4,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +5261,45511,Male,Loyal Customer,19,Personal Travel,Eco,774,5,2,5,3,1,5,1,1,3,3,3,2,3,1,0,0.0,satisfied +5262,3331,Female,disloyal Customer,39,Business travel,Business,213,4,4,4,1,4,4,4,4,3,2,4,4,4,4,4,17.0,satisfied +5263,52256,Male,Loyal Customer,40,Business travel,Business,3801,2,4,4,4,2,4,4,2,2,2,2,4,2,4,61,82.0,neutral or dissatisfied +5264,80362,Male,Loyal Customer,35,Business travel,Business,368,1,1,1,1,4,5,5,4,4,4,4,5,4,3,3,0.0,satisfied +5265,123834,Male,Loyal Customer,29,Business travel,Business,541,2,1,2,2,2,2,2,2,5,3,4,5,4,2,0,0.0,satisfied +5266,128352,Male,Loyal Customer,58,Business travel,Business,3423,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +5267,37684,Female,Loyal Customer,54,Personal Travel,Eco,1053,2,5,2,2,4,5,5,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +5268,6229,Male,Loyal Customer,60,Business travel,Eco,594,2,4,4,4,2,2,2,2,4,4,3,1,3,2,36,36.0,neutral or dissatisfied +5269,95275,Male,Loyal Customer,26,Personal Travel,Eco,148,1,2,1,4,5,1,1,5,4,2,4,3,4,5,16,0.0,neutral or dissatisfied +5270,99103,Male,Loyal Customer,40,Business travel,Business,237,2,1,2,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +5271,86458,Male,disloyal Customer,40,Business travel,Eco,712,1,1,1,3,3,1,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +5272,76347,Male,Loyal Customer,56,Business travel,Business,1851,1,1,5,1,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +5273,54284,Male,Loyal Customer,25,Personal Travel,Business,1075,3,5,2,3,5,2,5,5,4,5,4,5,5,5,0,3.0,neutral or dissatisfied +5274,46774,Female,Loyal Customer,60,Personal Travel,Eco Plus,196,2,4,2,2,4,4,5,3,3,2,3,3,3,4,39,33.0,neutral or dissatisfied +5275,36559,Male,Loyal Customer,38,Business travel,Business,1185,4,4,4,4,2,3,4,5,5,5,5,1,5,2,21,36.0,satisfied +5276,109302,Male,Loyal Customer,27,Business travel,Business,1136,3,2,3,3,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +5277,54817,Female,Loyal Customer,36,Business travel,Business,862,4,4,4,4,5,5,3,4,4,5,4,1,4,4,0,0.0,satisfied +5278,57998,Male,disloyal Customer,9,Business travel,Eco,1375,2,2,2,3,1,2,1,1,2,2,2,1,3,1,0,19.0,neutral or dissatisfied +5279,57682,Male,Loyal Customer,48,Business travel,Business,2880,4,4,5,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +5280,102422,Female,Loyal Customer,68,Personal Travel,Eco,397,3,5,2,3,3,4,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +5281,19543,Female,Loyal Customer,20,Business travel,Business,212,5,5,5,5,5,5,3,5,4,4,4,1,1,5,72,64.0,satisfied +5282,21737,Male,Loyal Customer,53,Business travel,Eco,563,2,4,4,4,2,2,2,2,5,4,4,5,4,2,0,0.0,satisfied +5283,84661,Male,disloyal Customer,28,Business travel,Business,1177,0,0,0,2,4,0,4,4,3,2,4,3,5,4,35,16.0,satisfied +5284,106548,Female,Loyal Customer,57,Business travel,Eco,727,2,3,3,3,3,3,3,2,2,2,2,1,2,2,3,0.0,neutral or dissatisfied +5285,25040,Male,Loyal Customer,70,Business travel,Eco Plus,907,3,2,2,2,3,3,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +5286,72464,Male,Loyal Customer,50,Business travel,Business,2034,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +5287,91679,Male,Loyal Customer,57,Business travel,Business,3653,4,4,5,4,4,5,5,2,2,2,2,4,2,3,124,116.0,satisfied +5288,107939,Male,Loyal Customer,70,Personal Travel,Eco,611,4,3,5,3,2,5,1,2,1,1,4,5,2,2,3,3.0,neutral or dissatisfied +5289,85226,Female,disloyal Customer,16,Business travel,Eco,874,2,2,2,3,1,2,3,1,3,4,4,2,4,1,13,0.0,neutral or dissatisfied +5290,108815,Female,Loyal Customer,44,Business travel,Business,3790,5,5,5,5,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +5291,73274,Male,Loyal Customer,8,Business travel,Business,2660,3,2,2,2,3,3,3,3,1,3,4,3,3,3,1,3.0,neutral or dissatisfied +5292,109147,Female,disloyal Customer,20,Business travel,Eco,483,0,0,1,1,5,1,5,5,3,4,4,4,4,5,12,17.0,satisfied +5293,115983,Female,Loyal Customer,29,Personal Travel,Eco,404,1,3,1,2,2,1,2,2,1,4,3,4,2,2,0,0.0,neutral or dissatisfied +5294,1375,Male,Loyal Customer,47,Business travel,Business,140,2,4,4,4,3,2,3,3,3,4,2,2,3,4,0,9.0,neutral or dissatisfied +5295,10545,Female,disloyal Customer,18,Business travel,Business,667,5,5,5,1,1,5,1,1,4,4,5,4,4,1,10,6.0,satisfied +5296,53149,Male,Loyal Customer,57,Personal Travel,Eco Plus,413,1,4,1,3,3,1,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +5297,47371,Male,Loyal Customer,51,Business travel,Business,599,3,2,2,2,2,3,3,3,3,3,3,4,3,3,35,30.0,neutral or dissatisfied +5298,19243,Male,Loyal Customer,48,Personal Travel,Eco,782,4,5,4,3,5,4,5,5,4,5,5,4,4,5,0,0.0,satisfied +5299,56681,Male,Loyal Customer,38,Personal Travel,Eco,1068,2,5,1,1,2,1,2,2,5,2,5,3,4,2,1,0.0,neutral or dissatisfied +5300,82073,Female,disloyal Customer,27,Business travel,Business,1276,0,0,0,3,2,0,3,2,3,4,4,5,5,2,1,0.0,satisfied +5301,75379,Female,Loyal Customer,28,Business travel,Business,2218,3,3,3,3,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +5302,98114,Female,disloyal Customer,23,Business travel,Eco,426,2,0,3,1,4,3,4,4,5,4,4,3,4,4,14,8.0,neutral or dissatisfied +5303,91740,Female,Loyal Customer,31,Business travel,Business,3709,5,5,5,5,2,2,2,2,4,4,4,4,4,2,16,19.0,satisfied +5304,11136,Female,Loyal Customer,53,Personal Travel,Eco,224,3,4,3,5,1,2,4,2,2,3,1,2,2,3,0,11.0,neutral or dissatisfied +5305,60066,Female,disloyal Customer,35,Business travel,Business,1005,2,2,2,3,2,2,2,2,2,1,4,3,4,2,35,14.0,neutral or dissatisfied +5306,56384,Male,Loyal Customer,40,Personal Travel,Eco Plus,200,5,2,0,4,1,0,1,1,4,5,3,3,3,1,0,0.0,satisfied +5307,76779,Male,disloyal Customer,11,Business travel,Eco,689,4,4,4,4,2,4,2,2,4,2,3,4,3,2,0,7.0,neutral or dissatisfied +5308,27692,Male,Loyal Customer,60,Personal Travel,Eco,1107,3,0,3,4,5,3,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +5309,118023,Female,Loyal Customer,24,Personal Travel,Business,1262,2,4,2,5,2,2,3,2,3,5,3,5,4,2,10,0.0,neutral or dissatisfied +5310,16018,Female,Loyal Customer,43,Personal Travel,Eco,780,1,5,1,5,5,4,4,1,1,1,1,3,1,4,15,5.0,neutral or dissatisfied +5311,83901,Male,Loyal Customer,40,Business travel,Business,1678,1,1,1,1,4,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +5312,103154,Female,disloyal Customer,37,Business travel,Business,491,5,4,4,4,3,4,3,3,5,4,4,5,5,3,17,25.0,satisfied +5313,101370,Female,Loyal Customer,30,Personal Travel,Eco,1986,2,2,2,3,2,2,2,2,4,1,2,2,2,2,2,0.0,neutral or dissatisfied +5314,39283,Male,Loyal Customer,46,Business travel,Business,1650,3,5,5,5,3,4,3,3,3,3,3,4,3,3,21,9.0,neutral or dissatisfied +5315,75600,Male,Loyal Customer,27,Personal Travel,Eco,337,1,4,1,4,1,1,1,1,4,5,4,3,4,1,7,6.0,neutral or dissatisfied +5316,13839,Female,Loyal Customer,31,Personal Travel,Eco,628,2,4,2,4,4,2,4,4,4,3,5,3,5,4,8,16.0,neutral or dissatisfied +5317,128345,Female,Loyal Customer,35,Business travel,Business,3503,4,4,4,4,2,4,5,5,5,5,5,4,5,4,0,2.0,satisfied +5318,129446,Male,Loyal Customer,49,Personal Travel,Eco,236,5,1,0,2,1,0,1,1,1,3,2,3,2,1,2,0.0,satisfied +5319,41154,Female,Loyal Customer,27,Personal Travel,Eco,295,1,4,1,5,3,1,3,3,4,5,5,3,4,3,1,0.0,neutral or dissatisfied +5320,47466,Female,Loyal Customer,38,Personal Travel,Eco,558,2,5,2,1,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +5321,73468,Male,Loyal Customer,57,Personal Travel,Eco,1005,1,4,1,2,5,1,5,5,5,5,5,3,5,5,4,0.0,neutral or dissatisfied +5322,38809,Male,Loyal Customer,30,Personal Travel,Eco,354,4,3,4,2,5,4,5,5,4,4,2,3,3,5,0,1.0,neutral or dissatisfied +5323,84297,Male,Loyal Customer,50,Business travel,Business,235,0,0,0,1,5,5,5,2,2,2,2,4,2,5,8,13.0,satisfied +5324,17411,Female,Loyal Customer,60,Business travel,Eco,351,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +5325,129215,Female,Loyal Customer,54,Business travel,Business,2414,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +5326,100705,Male,Loyal Customer,45,Business travel,Business,2610,4,4,4,4,4,4,4,1,1,2,1,4,1,4,0,0.0,satisfied +5327,35266,Female,Loyal Customer,25,Business travel,Business,3056,3,5,5,5,3,3,3,3,3,4,3,2,4,3,15,47.0,neutral or dissatisfied +5328,91976,Male,Loyal Customer,53,Business travel,Business,2475,1,1,1,1,4,3,4,3,3,4,3,5,3,3,4,0.0,satisfied +5329,67600,Female,Loyal Customer,51,Business travel,Business,2548,5,5,5,5,2,4,4,4,4,4,4,5,4,5,62,43.0,satisfied +5330,1327,Female,Loyal Customer,59,Business travel,Business,3994,0,4,0,5,2,2,3,5,4,5,5,3,3,3,146,142.0,satisfied +5331,127565,Female,Loyal Customer,35,Business travel,Business,1670,1,1,1,1,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +5332,62280,Male,Loyal Customer,53,Business travel,Business,1624,5,5,5,5,4,4,5,5,5,5,5,5,5,3,55,45.0,satisfied +5333,124209,Male,disloyal Customer,25,Business travel,Eco,1319,5,5,5,2,5,5,5,5,3,4,2,5,1,5,3,0.0,satisfied +5334,20737,Male,Loyal Customer,34,Business travel,Eco,363,5,1,1,1,5,5,5,5,1,3,1,3,4,5,64,90.0,satisfied +5335,1533,Female,Loyal Customer,46,Business travel,Business,2016,4,1,1,1,3,4,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +5336,69586,Male,Loyal Customer,12,Personal Travel,Eco,2475,3,4,3,1,3,5,4,3,3,4,4,4,4,4,15,61.0,neutral or dissatisfied +5337,37993,Female,Loyal Customer,28,Business travel,Business,3308,2,2,2,2,4,4,4,4,4,3,5,5,4,4,0,0.0,satisfied +5338,108801,Female,Loyal Customer,57,Personal Travel,Eco,406,3,2,3,4,4,4,4,5,5,3,5,1,5,4,10,0.0,neutral or dissatisfied +5339,107154,Male,disloyal Customer,39,Business travel,Business,402,1,1,1,3,3,1,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +5340,31755,Male,disloyal Customer,37,Business travel,Business,602,2,2,2,3,1,2,1,1,3,2,5,3,5,1,51,42.0,neutral or dissatisfied +5341,51258,Female,Loyal Customer,38,Business travel,Eco Plus,266,4,5,5,5,4,4,4,4,3,4,5,4,5,4,0,9.0,satisfied +5342,124527,Male,Loyal Customer,42,Business travel,Business,1276,5,5,5,5,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +5343,28313,Female,Loyal Customer,21,Business travel,Business,867,4,5,2,5,4,3,4,4,4,3,2,1,2,4,0,3.0,neutral or dissatisfied +5344,73244,Male,Loyal Customer,36,Business travel,Business,3615,4,4,2,4,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +5345,54438,Male,Loyal Customer,41,Business travel,Eco Plus,305,5,4,4,4,5,5,5,5,2,5,4,3,4,5,2,0.0,satisfied +5346,108111,Male,Loyal Customer,31,Business travel,Business,1105,4,4,4,4,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +5347,23718,Male,Loyal Customer,57,Personal Travel,Eco,212,3,0,3,5,2,3,2,2,5,3,4,4,5,2,0,1.0,neutral or dissatisfied +5348,7231,Female,Loyal Customer,43,Business travel,Eco,135,3,5,5,5,4,4,4,3,3,3,3,3,3,1,42,55.0,neutral or dissatisfied +5349,55776,Male,Loyal Customer,54,Business travel,Business,599,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +5350,36043,Male,Loyal Customer,46,Business travel,Eco,413,5,4,4,4,5,5,5,5,1,5,3,4,3,5,0,0.0,satisfied +5351,3481,Female,Loyal Customer,47,Business travel,Business,3880,5,5,5,5,3,4,5,5,5,4,5,5,5,4,9,0.0,satisfied +5352,59720,Male,Loyal Customer,60,Business travel,Eco Plus,861,3,4,4,4,3,3,3,3,1,3,4,3,2,3,225,207.0,neutral or dissatisfied +5353,63071,Male,Loyal Customer,25,Personal Travel,Eco,948,1,4,1,3,5,1,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +5354,113327,Male,Loyal Customer,60,Business travel,Business,397,2,2,2,2,2,5,5,3,3,3,3,3,3,4,20,22.0,satisfied +5355,36958,Female,Loyal Customer,39,Business travel,Business,2058,1,1,1,1,3,5,3,4,4,4,4,4,4,1,0,0.0,satisfied +5356,44618,Female,Loyal Customer,35,Business travel,Eco Plus,566,1,3,3,3,1,1,1,1,4,2,3,1,4,1,90,78.0,neutral or dissatisfied +5357,6149,Male,disloyal Customer,35,Business travel,Business,409,2,2,2,5,4,2,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +5358,12872,Female,Loyal Customer,31,Business travel,Business,3927,1,1,1,1,5,5,5,5,2,2,2,4,3,5,0,0.0,satisfied +5359,93088,Male,Loyal Customer,40,Personal Travel,Eco,860,1,4,1,1,2,1,2,2,4,3,4,4,4,2,1,0.0,neutral or dissatisfied +5360,107950,Male,disloyal Customer,12,Business travel,Business,611,5,5,5,1,5,5,5,4,5,5,5,5,5,5,223,243.0,satisfied +5361,81636,Female,Loyal Customer,60,Business travel,Business,907,2,3,3,3,4,3,3,2,2,1,2,1,2,4,9,13.0,neutral or dissatisfied +5362,25707,Male,Loyal Customer,45,Business travel,Eco,432,3,3,3,3,3,3,3,3,1,1,3,3,4,3,0,0.0,satisfied +5363,75690,Male,Loyal Customer,54,Business travel,Business,2409,1,1,1,1,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +5364,85286,Male,Loyal Customer,16,Personal Travel,Eco,696,3,4,3,1,1,3,1,1,3,5,5,3,5,1,0,11.0,neutral or dissatisfied +5365,21516,Female,Loyal Customer,34,Personal Travel,Eco,164,2,5,2,3,1,2,1,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +5366,11613,Female,Loyal Customer,47,Personal Travel,Eco,657,4,2,4,3,5,3,4,2,2,4,2,4,2,1,10,0.0,neutral or dissatisfied +5367,51427,Male,Loyal Customer,67,Personal Travel,Eco Plus,134,2,5,2,2,1,2,1,1,4,5,2,3,4,1,0,0.0,neutral or dissatisfied +5368,73267,Female,Loyal Customer,43,Business travel,Business,3815,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +5369,16167,Female,Loyal Customer,55,Business travel,Business,3071,1,4,4,4,2,3,3,2,2,2,1,3,2,2,0,4.0,neutral or dissatisfied +5370,43264,Female,Loyal Customer,43,Business travel,Eco,436,5,4,4,4,2,4,2,5,5,5,5,3,5,5,0,0.0,satisfied +5371,81888,Female,Loyal Customer,52,Business travel,Business,2922,1,1,1,1,4,5,4,4,4,4,4,4,4,4,63,58.0,satisfied +5372,120256,Female,Loyal Customer,35,Personal Travel,Eco Plus,1325,2,5,2,1,1,2,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +5373,93609,Male,disloyal Customer,29,Business travel,Eco,577,3,3,3,3,1,3,1,1,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +5374,60170,Female,Loyal Customer,17,Personal Travel,Eco,1050,2,4,2,3,2,2,2,2,1,4,5,1,3,2,2,50.0,neutral or dissatisfied +5375,124378,Male,Loyal Customer,35,Business travel,Eco,808,5,3,3,3,5,5,5,5,2,2,4,5,2,5,0,0.0,satisfied +5376,66347,Female,Loyal Customer,40,Business travel,Business,3215,5,4,5,5,2,4,5,4,4,4,4,3,4,5,21,18.0,satisfied +5377,16580,Female,Loyal Customer,62,Business travel,Eco,472,5,5,5,5,2,1,4,5,5,5,5,1,5,4,48,29.0,satisfied +5378,7238,Female,disloyal Customer,47,Business travel,Eco,139,4,4,4,2,4,4,4,4,4,2,4,3,1,4,0,0.0,satisfied +5379,122304,Female,Loyal Customer,22,Personal Travel,Eco,573,2,5,2,3,4,2,4,4,4,3,5,5,5,4,0,7.0,neutral or dissatisfied +5380,34306,Female,Loyal Customer,37,Personal Travel,Eco,280,2,4,2,3,3,2,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +5381,47090,Male,Loyal Customer,70,Personal Travel,Eco,602,1,5,1,1,2,1,2,2,5,2,4,4,4,2,82,68.0,neutral or dissatisfied +5382,53001,Female,Loyal Customer,31,Business travel,Eco,1208,4,3,3,3,4,4,4,4,1,3,1,5,2,4,16,21.0,satisfied +5383,97404,Male,Loyal Customer,55,Business travel,Business,2254,4,4,5,4,3,5,4,4,4,4,4,4,4,3,22,8.0,satisfied +5384,56487,Female,Loyal Customer,59,Business travel,Business,3771,3,3,3,3,5,4,5,5,5,5,5,4,5,5,6,0.0,satisfied +5385,27447,Female,disloyal Customer,21,Business travel,Eco,937,2,2,2,3,3,2,1,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +5386,47615,Male,Loyal Customer,29,Business travel,Business,1482,2,2,2,2,5,5,5,5,4,3,4,5,5,5,120,116.0,satisfied +5387,107776,Male,Loyal Customer,58,Business travel,Eco Plus,251,4,5,5,5,5,4,5,5,2,2,4,1,4,5,59,56.0,neutral or dissatisfied +5388,8359,Male,Loyal Customer,32,Personal Travel,Business,701,1,4,1,2,2,1,2,2,1,1,2,4,1,2,0,0.0,neutral or dissatisfied +5389,48884,Male,disloyal Customer,22,Business travel,Eco,421,4,0,4,4,2,4,2,2,2,4,3,1,1,2,81,79.0,neutral or dissatisfied +5390,105864,Male,Loyal Customer,36,Business travel,Eco Plus,387,4,2,2,2,4,4,4,4,5,4,3,4,1,4,0,0.0,satisfied +5391,109449,Male,Loyal Customer,54,Business travel,Business,1711,3,3,3,3,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +5392,121400,Female,disloyal Customer,36,Business travel,Business,331,2,2,2,1,3,2,3,3,5,3,4,3,5,3,0,0.0,neutral or dissatisfied +5393,62521,Female,Loyal Customer,33,Business travel,Business,1744,1,2,2,2,2,3,4,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +5394,124751,Female,Loyal Customer,45,Personal Travel,Business,280,3,0,3,3,3,4,4,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +5395,30516,Male,Loyal Customer,42,Business travel,Business,3358,3,3,1,3,2,5,4,5,5,5,5,4,5,4,23,36.0,satisfied +5396,55674,Male,Loyal Customer,51,Business travel,Business,2692,5,5,5,5,2,5,4,3,3,3,3,3,3,3,28,22.0,satisfied +5397,63788,Male,Loyal Customer,32,Business travel,Eco,1721,5,4,4,4,5,5,5,5,5,2,2,3,4,5,0,0.0,satisfied +5398,66743,Male,Loyal Customer,7,Personal Travel,Eco,802,1,4,1,4,5,1,5,5,2,4,3,1,4,5,0,0.0,neutral or dissatisfied +5399,129589,Female,Loyal Customer,75,Business travel,Business,308,0,0,0,4,5,4,5,3,3,3,5,5,3,3,0,0.0,satisfied +5400,105576,Male,disloyal Customer,12,Business travel,Eco,577,3,4,3,3,2,3,2,2,4,4,4,2,4,2,18,7.0,neutral or dissatisfied +5401,9341,Female,Loyal Customer,39,Business travel,Business,2142,2,2,2,2,5,5,4,5,5,5,5,3,5,3,83,78.0,satisfied +5402,43880,Male,Loyal Customer,39,Business travel,Eco,144,4,2,2,2,4,4,4,4,2,1,2,3,1,4,0,0.0,satisfied +5403,40529,Female,Loyal Customer,46,Business travel,Business,391,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +5404,95791,Male,Loyal Customer,55,Business travel,Business,3769,5,5,5,5,3,4,5,4,4,4,5,5,4,4,15,14.0,satisfied +5405,62885,Male,Loyal Customer,28,Personal Travel,Eco Plus,2218,4,2,4,4,1,4,1,1,3,3,4,2,4,1,0,0.0,neutral or dissatisfied +5406,42103,Female,Loyal Customer,28,Business travel,Business,1910,1,1,1,1,4,4,4,4,1,1,3,4,5,4,30,28.0,satisfied +5407,27932,Male,Loyal Customer,30,Business travel,Business,1770,4,4,4,4,2,2,2,2,2,2,4,3,3,2,0,0.0,satisfied +5408,121476,Male,Loyal Customer,48,Personal Travel,Eco,331,3,4,3,1,1,3,1,1,5,5,1,4,2,1,0,0.0,neutral or dissatisfied +5409,31565,Male,disloyal Customer,20,Business travel,Eco,853,1,1,1,4,5,1,5,5,3,5,3,4,4,5,8,4.0,neutral or dissatisfied +5410,42112,Female,Loyal Customer,26,Business travel,Business,2255,2,2,3,2,2,2,2,2,4,5,1,4,2,2,0,33.0,neutral or dissatisfied +5411,98323,Female,Loyal Customer,57,Personal Travel,Eco Plus,1547,1,4,1,1,4,4,5,2,2,1,2,5,2,5,3,2.0,neutral or dissatisfied +5412,14121,Female,Loyal Customer,70,Personal Travel,Business,654,4,2,5,4,2,3,3,1,1,5,1,3,1,3,0,0.0,neutral or dissatisfied +5413,68992,Male,Loyal Customer,47,Business travel,Business,2422,1,2,2,2,1,1,1,4,5,3,3,1,3,1,86,104.0,neutral or dissatisfied +5414,37906,Male,disloyal Customer,21,Business travel,Business,1065,3,4,3,4,5,3,5,5,4,1,4,1,3,5,0,0.0,neutral or dissatisfied +5415,35663,Female,Loyal Customer,44,Business travel,Eco,2475,4,3,3,3,2,4,3,4,4,4,4,2,4,2,13,0.0,neutral or dissatisfied +5416,92886,Female,disloyal Customer,43,Business travel,Eco,134,3,1,3,4,1,3,1,1,4,4,3,4,4,1,7,18.0,neutral or dissatisfied +5417,18047,Female,Loyal Customer,39,Business travel,Business,3361,5,5,5,5,1,5,2,3,3,3,3,4,3,5,0,25.0,satisfied +5418,98720,Male,Loyal Customer,66,Personal Travel,Eco Plus,951,3,2,3,3,4,3,4,4,3,4,3,4,2,4,0,0.0,neutral or dissatisfied +5419,18926,Female,Loyal Customer,64,Personal Travel,Eco,448,3,4,3,3,5,5,5,5,5,3,5,4,5,4,0,11.0,neutral or dissatisfied +5420,108473,Female,Loyal Customer,44,Personal Travel,Eco,1444,3,3,3,4,4,1,2,3,3,3,3,5,3,5,15,24.0,neutral or dissatisfied +5421,121236,Female,disloyal Customer,34,Business travel,Business,2075,2,2,2,4,2,2,2,2,3,3,5,4,5,2,0,7.0,neutral or dissatisfied +5422,83699,Male,Loyal Customer,59,Personal Travel,Eco,577,4,2,4,2,3,4,3,3,3,1,2,3,3,3,0,0.0,neutral or dissatisfied +5423,63656,Female,Loyal Customer,58,Business travel,Business,2846,3,3,3,3,5,5,5,4,3,3,4,5,5,5,0,0.0,satisfied +5424,103391,Male,Loyal Customer,40,Business travel,Business,3106,4,4,4,4,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +5425,70734,Female,Loyal Customer,7,Personal Travel,Eco,675,2,5,2,2,5,2,5,5,5,5,5,3,4,5,0,10.0,neutral or dissatisfied +5426,38540,Male,disloyal Customer,40,Business travel,Eco,2586,3,3,3,3,1,3,1,1,4,1,4,1,4,1,1,0.0,neutral or dissatisfied +5427,54563,Female,disloyal Customer,31,Business travel,Eco Plus,925,1,1,1,3,2,1,2,2,4,2,2,2,2,2,46,23.0,neutral or dissatisfied +5428,81226,Female,Loyal Customer,32,Business travel,Eco Plus,1426,5,2,3,3,5,5,5,5,2,3,5,1,1,5,25,60.0,satisfied +5429,53345,Female,Loyal Customer,24,Business travel,Business,1452,5,5,1,5,3,3,3,3,4,4,3,1,2,3,0,0.0,satisfied +5430,126615,Female,Loyal Customer,51,Personal Travel,Eco,1337,2,5,2,1,5,4,5,2,2,2,2,4,2,3,10,0.0,neutral or dissatisfied +5431,59470,Female,Loyal Customer,45,Business travel,Business,758,4,4,4,4,4,5,5,5,5,5,5,3,5,4,0,3.0,satisfied +5432,6520,Female,Loyal Customer,37,Business travel,Business,199,1,5,5,5,1,1,1,3,1,3,4,1,3,1,63,137.0,neutral or dissatisfied +5433,123075,Male,disloyal Customer,15,Business travel,Eco,631,2,5,1,2,2,1,2,2,4,2,4,4,4,2,4,0.0,neutral or dissatisfied +5434,128336,Male,Loyal Customer,40,Business travel,Business,3275,3,3,3,3,4,4,4,4,4,4,4,3,4,4,50,64.0,satisfied +5435,122302,Female,Loyal Customer,27,Personal Travel,Eco,603,1,5,1,2,3,1,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +5436,48930,Female,Loyal Customer,38,Business travel,Business,3357,1,1,1,1,1,1,4,5,5,5,5,5,5,4,0,0.0,satisfied +5437,83773,Female,Loyal Customer,68,Personal Travel,Eco,926,1,4,1,4,1,4,3,3,3,1,3,2,3,1,26,31.0,neutral or dissatisfied +5438,81495,Male,Loyal Customer,53,Personal Travel,Eco,528,1,5,1,2,3,1,3,3,3,2,5,3,5,3,0,3.0,neutral or dissatisfied +5439,48428,Male,Loyal Customer,44,Business travel,Eco,833,2,1,1,1,2,2,2,2,2,5,2,4,1,2,0,12.0,satisfied +5440,128889,Female,Loyal Customer,40,Business travel,Business,2454,5,5,5,5,4,4,4,5,4,5,4,4,5,4,0,0.0,satisfied +5441,45256,Male,Loyal Customer,50,Business travel,Business,584,1,1,1,1,2,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +5442,104221,Male,disloyal Customer,37,Business travel,Eco,680,4,3,3,3,5,3,5,5,2,1,3,1,4,5,0,0.0,neutral or dissatisfied +5443,116154,Male,Loyal Customer,64,Personal Travel,Eco,446,4,5,4,4,1,4,2,1,3,3,5,3,4,1,32,29.0,neutral or dissatisfied +5444,38553,Male,Loyal Customer,57,Personal Travel,Eco,2475,3,4,3,1,1,3,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +5445,9314,Male,Loyal Customer,16,Business travel,Business,419,5,5,5,5,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +5446,63308,Male,Loyal Customer,52,Business travel,Business,2657,1,1,5,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +5447,87105,Male,Loyal Customer,59,Personal Travel,Eco,645,2,2,2,3,1,2,1,1,2,3,2,2,3,1,0,0.0,neutral or dissatisfied +5448,58914,Female,Loyal Customer,51,Personal Travel,Eco,888,4,4,5,4,1,3,3,3,3,5,3,2,3,3,0,7.0,neutral or dissatisfied +5449,13302,Female,Loyal Customer,49,Personal Travel,Eco Plus,657,1,5,1,3,2,4,4,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +5450,117105,Female,disloyal Customer,39,Business travel,Eco,251,3,1,3,3,2,3,2,2,1,3,3,4,3,2,108,97.0,neutral or dissatisfied +5451,81202,Female,Loyal Customer,51,Business travel,Business,1426,4,4,4,4,3,4,5,3,3,3,3,4,3,5,0,9.0,satisfied +5452,77331,Female,disloyal Customer,30,Business travel,Business,590,1,1,1,3,2,1,4,2,3,2,4,4,5,2,4,0.0,neutral or dissatisfied +5453,70318,Male,Loyal Customer,63,Business travel,Eco,1501,2,5,5,5,2,2,2,2,1,5,2,2,3,2,0,0.0,neutral or dissatisfied +5454,25593,Female,Loyal Customer,9,Personal Travel,Eco,696,1,4,1,2,2,1,2,2,5,5,4,5,5,2,11,23.0,neutral or dissatisfied +5455,73131,Female,Loyal Customer,51,Business travel,Business,1068,5,5,5,5,5,5,5,3,3,3,3,5,3,3,19,37.0,satisfied +5456,11609,Male,Loyal Customer,57,Personal Travel,Eco,657,3,4,3,4,2,3,2,2,3,4,2,5,3,2,24,25.0,neutral or dissatisfied +5457,14924,Male,Loyal Customer,43,Business travel,Eco Plus,296,4,4,4,4,4,4,4,4,5,3,2,2,5,4,1,0.0,satisfied +5458,28233,Male,Loyal Customer,26,Business travel,Business,1009,3,1,1,1,3,3,3,3,1,1,4,3,3,3,0,0.0,neutral or dissatisfied +5459,126134,Male,Loyal Customer,36,Business travel,Business,3981,3,3,5,3,3,4,4,4,4,4,4,5,4,5,0,9.0,satisfied +5460,101124,Female,Loyal Customer,41,Business travel,Business,1069,2,2,2,2,2,4,4,5,5,5,5,3,5,3,6,0.0,satisfied +5461,75860,Female,Loyal Customer,62,Personal Travel,Eco,1440,3,4,3,1,3,5,4,4,4,3,4,3,4,5,27,16.0,neutral or dissatisfied +5462,128986,Male,disloyal Customer,8,Personal Travel,Eco,236,1,5,1,4,1,1,1,1,5,3,4,4,5,1,0,0.0,neutral or dissatisfied +5463,91322,Female,Loyal Customer,16,Business travel,Eco Plus,515,2,1,5,1,2,2,2,2,1,5,4,2,4,2,8,4.0,neutral or dissatisfied +5464,73768,Male,Loyal Customer,59,Personal Travel,Eco,192,5,5,5,3,5,5,5,5,5,4,4,3,5,5,4,0.0,satisfied +5465,5254,Male,Loyal Customer,39,Business travel,Business,2513,1,1,1,1,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +5466,39524,Male,Loyal Customer,53,Personal Travel,Eco,852,2,4,2,1,1,2,1,1,3,4,4,3,5,1,0,0.0,neutral or dissatisfied +5467,1981,Male,Loyal Customer,51,Personal Travel,Eco,383,2,4,5,4,1,5,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +5468,12907,Female,Loyal Customer,30,Business travel,Business,2045,2,2,2,2,5,5,5,5,5,1,1,4,2,5,0,0.0,satisfied +5469,17233,Male,Loyal Customer,43,Business travel,Eco,1092,3,5,5,5,3,3,3,3,3,5,3,1,4,3,0,0.0,neutral or dissatisfied +5470,53036,Male,Loyal Customer,55,Business travel,Business,1190,1,1,1,1,3,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +5471,46742,Female,Loyal Customer,47,Personal Travel,Eco,73,2,1,2,3,3,2,2,5,5,2,5,2,5,2,64,79.0,neutral or dissatisfied +5472,66367,Male,Loyal Customer,41,Personal Travel,Eco,986,4,5,4,4,4,4,4,4,5,2,4,3,5,4,9,1.0,neutral or dissatisfied +5473,12022,Female,Loyal Customer,55,Business travel,Eco,376,2,1,1,1,2,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +5474,13543,Female,Loyal Customer,41,Business travel,Business,1993,3,3,5,5,3,2,3,3,3,3,3,2,3,4,0,17.0,neutral or dissatisfied +5475,115153,Female,Loyal Customer,49,Business travel,Business,3507,4,4,4,4,4,5,5,5,5,5,5,4,5,3,1,0.0,satisfied +5476,101265,Female,Loyal Customer,40,Business travel,Business,3918,1,0,0,3,5,3,3,3,3,0,3,1,3,4,0,0.0,neutral or dissatisfied +5477,20045,Female,disloyal Customer,22,Business travel,Eco,738,3,3,3,3,3,3,3,3,3,4,2,2,2,3,46,41.0,neutral or dissatisfied +5478,118118,Male,Loyal Customer,65,Personal Travel,Eco,1300,1,4,1,1,4,1,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +5479,91989,Female,Loyal Customer,36,Business travel,Business,236,1,1,1,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +5480,71465,Female,Loyal Customer,36,Personal Travel,Eco,867,4,5,4,1,5,4,5,5,4,4,4,4,5,5,30,18.0,neutral or dissatisfied +5481,6893,Female,Loyal Customer,41,Business travel,Business,1999,3,3,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5482,2513,Male,Loyal Customer,58,Business travel,Business,2073,2,2,2,2,3,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +5483,75374,Female,Loyal Customer,59,Personal Travel,Business,2218,1,3,1,4,4,4,3,1,1,1,1,2,1,1,2,0.0,neutral or dissatisfied +5484,42056,Male,Loyal Customer,28,Personal Travel,Eco,241,1,5,1,1,1,1,1,1,5,2,4,3,5,1,6,1.0,neutral or dissatisfied +5485,8524,Male,Loyal Customer,65,Personal Travel,Eco,862,2,4,2,1,1,2,5,1,5,4,5,5,4,1,0,4.0,neutral or dissatisfied +5486,91052,Female,Loyal Customer,64,Personal Travel,Eco,515,1,5,1,3,3,5,4,4,4,1,4,3,4,3,0,3.0,neutral or dissatisfied +5487,127890,Male,Loyal Customer,60,Business travel,Business,1671,1,1,4,1,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +5488,32436,Male,disloyal Customer,40,Business travel,Eco,101,1,1,1,3,4,1,3,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +5489,82089,Female,Loyal Customer,66,Business travel,Eco,1276,3,4,3,3,3,3,2,3,3,3,3,4,3,4,54,41.0,neutral or dissatisfied +5490,63130,Female,Loyal Customer,47,Business travel,Business,2994,4,3,3,3,5,4,3,4,4,4,4,1,4,1,13,13.0,neutral or dissatisfied +5491,109311,Female,disloyal Customer,24,Business travel,Eco,1072,2,2,2,4,3,2,3,3,3,5,4,3,3,3,105,84.0,neutral or dissatisfied +5492,21165,Male,disloyal Customer,57,Business travel,Business,192,5,5,5,4,5,5,5,5,5,4,5,4,5,5,0,5.0,satisfied +5493,77033,Male,Loyal Customer,9,Personal Travel,Eco,422,2,2,2,4,3,2,3,3,3,1,4,1,4,3,5,6.0,neutral or dissatisfied +5494,73882,Female,Loyal Customer,35,Business travel,Business,2342,4,4,4,4,3,3,5,1,1,2,1,3,1,3,0,0.0,satisfied +5495,20785,Male,Loyal Customer,49,Business travel,Business,534,3,3,3,3,2,5,2,4,4,4,4,2,4,2,3,0.0,satisfied +5496,121981,Male,Loyal Customer,38,Business travel,Business,130,2,2,2,2,3,5,5,5,5,4,4,3,5,5,0,0.0,satisfied +5497,34530,Female,Loyal Customer,40,Business travel,Eco,636,5,5,5,5,5,5,5,5,3,3,2,1,1,5,38,48.0,satisfied +5498,99185,Male,Loyal Customer,12,Personal Travel,Eco,351,2,1,2,2,2,2,2,2,2,2,3,1,2,2,0,0.0,neutral or dissatisfied +5499,115826,Male,disloyal Customer,22,Business travel,Eco,417,2,1,2,3,1,2,1,1,3,5,4,3,4,1,36,31.0,neutral or dissatisfied +5500,12582,Male,Loyal Customer,60,Business travel,Business,1723,1,1,1,1,1,2,4,5,5,5,5,3,5,1,0,0.0,satisfied +5501,117071,Female,disloyal Customer,26,Business travel,Eco,451,2,3,2,4,5,2,5,5,1,2,3,4,3,5,3,0.0,neutral or dissatisfied +5502,30628,Female,disloyal Customer,38,Business travel,Eco,533,4,3,4,2,5,4,5,5,1,5,1,3,2,5,16,12.0,satisfied +5503,86258,Female,Loyal Customer,35,Personal Travel,Eco,356,3,5,3,3,3,3,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +5504,63438,Female,Loyal Customer,51,Personal Travel,Eco,337,2,2,2,4,2,4,4,5,5,2,5,1,5,3,9,0.0,neutral or dissatisfied +5505,32524,Female,Loyal Customer,31,Business travel,Business,3428,0,4,0,1,2,2,2,2,3,3,1,1,5,2,0,0.0,satisfied +5506,28612,Male,Loyal Customer,38,Business travel,Business,2409,5,5,5,5,2,3,3,4,4,4,4,2,4,4,0,0.0,satisfied +5507,40232,Male,disloyal Customer,39,Business travel,Eco,387,2,0,2,4,3,2,3,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +5508,62385,Female,Loyal Customer,59,Business travel,Business,2704,2,2,2,2,5,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +5509,91714,Male,Loyal Customer,49,Business travel,Business,590,5,5,2,5,4,5,5,2,2,2,2,5,2,4,46,40.0,satisfied +5510,3339,Female,Loyal Customer,49,Business travel,Business,3844,1,1,1,1,5,5,5,4,4,4,4,4,4,4,86,80.0,satisfied +5511,50102,Female,Loyal Customer,50,Business travel,Business,3397,4,5,5,5,3,4,4,3,2,3,4,4,2,4,161,173.0,neutral or dissatisfied +5512,44442,Male,Loyal Customer,43,Business travel,Eco,420,4,1,1,1,4,4,4,4,1,4,2,3,4,4,5,29.0,satisfied +5513,43812,Male,Loyal Customer,41,Business travel,Business,114,4,4,4,4,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +5514,122684,Male,Loyal Customer,53,Business travel,Business,3057,1,1,1,1,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +5515,14898,Female,disloyal Customer,38,Business travel,Eco,240,3,3,3,4,1,3,1,1,3,4,4,3,4,1,5,2.0,neutral or dissatisfied +5516,97845,Male,Loyal Customer,43,Personal Travel,Eco,395,3,3,3,3,1,3,1,1,5,3,3,3,3,1,1,0.0,neutral or dissatisfied +5517,95473,Female,Loyal Customer,72,Business travel,Eco Plus,319,2,1,1,1,3,3,3,2,2,2,2,3,2,1,52,43.0,neutral or dissatisfied +5518,125698,Male,Loyal Customer,29,Personal Travel,Eco,814,4,2,4,3,3,4,3,3,1,3,2,3,4,3,0,0.0,neutral or dissatisfied +5519,104878,Female,Loyal Customer,70,Personal Travel,Eco,327,2,0,2,3,5,4,5,5,5,2,5,5,5,5,59,57.0,neutral or dissatisfied +5520,92447,Male,Loyal Customer,41,Business travel,Eco,1892,3,4,5,4,2,3,2,2,3,1,4,1,4,2,0,0.0,neutral or dissatisfied +5521,41600,Female,Loyal Customer,41,Personal Travel,Eco,1504,2,1,2,3,5,2,5,5,1,3,2,1,3,5,0,0.0,neutral or dissatisfied +5522,30216,Female,Loyal Customer,43,Personal Travel,Eco Plus,261,2,3,2,2,3,3,4,5,5,2,5,1,5,2,1,5.0,neutral or dissatisfied +5523,89543,Female,Loyal Customer,25,Business travel,Business,2073,2,2,2,2,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +5524,58985,Male,Loyal Customer,17,Business travel,Business,1723,4,4,4,4,3,3,3,3,5,5,3,4,4,3,2,3.0,satisfied +5525,67123,Male,Loyal Customer,52,Business travel,Business,3176,3,3,3,3,2,4,5,5,5,4,5,5,5,4,6,0.0,satisfied +5526,46127,Female,Loyal Customer,45,Business travel,Business,604,4,4,4,4,5,5,3,4,4,4,4,1,4,5,0,0.0,satisfied +5527,106336,Male,disloyal Customer,22,Business travel,Business,825,0,4,0,5,3,0,3,3,4,2,4,4,5,3,0,0.0,satisfied +5528,116344,Male,Loyal Customer,64,Personal Travel,Eco,358,3,4,3,5,5,3,5,5,5,4,4,4,5,5,1,0.0,neutral or dissatisfied +5529,119208,Male,Loyal Customer,59,Business travel,Business,290,2,2,2,2,5,5,5,5,5,5,5,2,5,3,2,7.0,satisfied +5530,117098,Male,Loyal Customer,38,Business travel,Eco,251,5,4,4,4,5,5,5,5,3,2,2,4,1,5,0,0.0,satisfied +5531,77802,Female,Loyal Customer,18,Personal Travel,Eco,689,3,2,4,3,4,4,4,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +5532,48995,Male,Loyal Customer,68,Business travel,Eco,156,3,2,2,2,3,3,3,3,2,5,2,5,4,3,0,0.0,satisfied +5533,38155,Male,Loyal Customer,59,Personal Travel,Eco,1211,1,0,1,3,4,1,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +5534,14477,Female,Loyal Customer,59,Business travel,Business,541,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,18.0,satisfied +5535,112494,Female,Loyal Customer,53,Personal Travel,Eco,957,3,4,3,3,4,4,5,5,5,3,5,3,5,3,0,13.0,neutral or dissatisfied +5536,61924,Female,Loyal Customer,50,Personal Travel,Eco,550,4,3,4,3,5,4,4,2,2,4,2,4,2,4,1,3.0,neutral or dissatisfied +5537,59879,Male,Loyal Customer,52,Business travel,Business,1985,5,5,4,5,3,5,4,4,4,4,4,5,4,3,1,0.0,satisfied +5538,20839,Female,Loyal Customer,27,Business travel,Business,1938,5,5,5,5,5,5,5,5,1,5,4,1,1,5,0,0.0,satisfied +5539,96160,Female,Loyal Customer,32,Business travel,Business,3147,4,1,4,4,4,4,4,4,5,4,5,4,4,4,7,9.0,satisfied +5540,92101,Male,Loyal Customer,50,Business travel,Eco,1132,4,4,3,3,4,4,4,2,5,1,1,4,4,4,284,286.0,neutral or dissatisfied +5541,38627,Female,Loyal Customer,30,Business travel,Business,2611,5,5,5,5,3,3,3,3,1,3,3,1,5,3,15,0.0,satisfied +5542,126608,Male,Loyal Customer,49,Personal Travel,Eco,1337,0,2,0,4,2,0,4,2,4,1,4,3,4,2,0,15.0,satisfied +5543,93740,Female,disloyal Customer,21,Business travel,Eco,368,3,5,3,4,3,2,2,3,4,4,5,2,3,2,251,253.0,neutral or dissatisfied +5544,84846,Female,Loyal Customer,39,Business travel,Eco,516,2,4,3,4,2,2,2,2,3,3,3,4,4,2,62,51.0,neutral or dissatisfied +5545,79971,Female,Loyal Customer,63,Business travel,Eco,696,2,5,5,5,5,4,3,2,2,2,2,4,2,3,59,32.0,neutral or dissatisfied +5546,45981,Male,disloyal Customer,34,Business travel,Eco,483,3,5,3,3,3,3,3,3,4,5,2,3,3,3,0,0.0,neutral or dissatisfied +5547,70353,Female,disloyal Customer,36,Business travel,Eco Plus,986,2,2,2,4,5,2,5,5,4,5,4,1,4,5,0,7.0,neutral or dissatisfied +5548,14671,Male,Loyal Customer,55,Business travel,Business,3584,2,2,2,2,5,1,1,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +5549,92358,Male,disloyal Customer,30,Business travel,Business,1096,0,0,0,1,1,0,1,1,4,5,5,5,4,1,3,0.0,satisfied +5550,77314,Female,Loyal Customer,22,Business travel,Business,2880,2,2,2,2,5,5,5,5,5,5,4,4,4,5,0,0.0,satisfied +5551,94049,Male,Loyal Customer,46,Business travel,Business,1766,4,4,4,4,4,4,4,5,5,5,5,4,5,5,56,53.0,satisfied +5552,38144,Female,Loyal Customer,61,Personal Travel,Eco,1249,3,5,3,1,2,3,4,3,3,3,3,4,3,4,9,3.0,neutral or dissatisfied +5553,52035,Female,disloyal Customer,27,Business travel,Eco Plus,328,5,5,5,2,3,5,3,3,3,4,3,1,4,3,0,0.0,satisfied +5554,97476,Male,disloyal Customer,24,Business travel,Eco,756,5,5,5,4,3,5,5,3,4,5,5,4,4,3,7,2.0,satisfied +5555,73356,Male,Loyal Customer,31,Business travel,Business,3025,4,1,4,4,1,2,1,1,3,4,5,4,5,1,41,31.0,satisfied +5556,75911,Male,Loyal Customer,15,Personal Travel,Eco,597,3,3,4,4,2,4,2,2,1,1,4,4,3,2,0,0.0,neutral or dissatisfied +5557,85317,Male,Loyal Customer,19,Personal Travel,Eco,731,3,4,3,3,3,3,3,3,4,4,4,2,3,3,0,0.0,neutral or dissatisfied +5558,103140,Female,Loyal Customer,56,Personal Travel,Eco Plus,546,2,4,2,5,3,5,4,3,3,2,4,3,3,1,0,5.0,neutral or dissatisfied +5559,93955,Female,Loyal Customer,51,Business travel,Business,2404,1,1,1,1,2,5,4,4,4,4,4,3,4,4,41,39.0,satisfied +5560,100509,Male,disloyal Customer,34,Business travel,Eco,580,3,3,3,3,3,3,3,3,3,5,4,1,4,3,1,0.0,neutral or dissatisfied +5561,20142,Male,Loyal Customer,51,Business travel,Business,2478,5,5,3,5,4,4,2,4,4,4,4,3,4,3,12,5.0,satisfied +5562,15546,Female,disloyal Customer,23,Business travel,Business,296,5,0,5,2,4,5,4,4,5,3,4,5,4,4,0,0.0,satisfied +5563,27180,Male,Loyal Customer,13,Personal Travel,Eco,2640,2,4,2,5,2,4,4,5,4,4,4,4,3,4,5,0.0,neutral or dissatisfied +5564,14824,Male,Loyal Customer,50,Personal Travel,Business,314,1,4,1,2,4,4,5,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +5565,61295,Female,Loyal Customer,48,Personal Travel,Eco,967,1,5,1,3,3,4,5,2,2,1,2,3,2,5,52,61.0,neutral or dissatisfied +5566,28491,Female,disloyal Customer,9,Business travel,Eco,1050,2,3,3,4,2,4,4,4,5,3,4,4,2,4,0,12.0,neutral or dissatisfied +5567,22006,Female,Loyal Customer,70,Personal Travel,Eco,503,2,5,2,3,3,4,4,4,4,2,5,3,4,5,0,5.0,neutral or dissatisfied +5568,54516,Female,disloyal Customer,56,Business travel,Eco,525,3,0,2,1,3,2,3,3,2,3,4,4,3,3,0,0.0,neutral or dissatisfied +5569,94974,Male,Loyal Customer,38,Business travel,Business,1624,4,2,2,2,4,3,3,3,3,3,4,1,3,4,7,6.0,neutral or dissatisfied +5570,35146,Female,Loyal Customer,40,Business travel,Eco,828,5,1,1,1,5,5,5,5,5,1,4,2,2,5,0,12.0,satisfied +5571,70228,Female,Loyal Customer,66,Personal Travel,Eco,1068,2,5,2,4,3,5,5,4,4,2,1,4,4,4,0,0.0,neutral or dissatisfied +5572,48209,Female,Loyal Customer,56,Business travel,Eco,236,1,3,3,3,4,3,3,2,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +5573,23150,Female,Loyal Customer,48,Business travel,Eco,223,4,4,4,4,5,4,2,4,4,4,4,3,4,1,0,0.0,satisfied +5574,103944,Male,Loyal Customer,32,Business travel,Business,770,1,1,2,1,1,1,1,1,3,2,4,4,3,1,113,112.0,neutral or dissatisfied +5575,117033,Female,disloyal Customer,21,Business travel,Business,651,3,4,3,3,2,3,2,2,1,3,4,1,3,2,2,1.0,neutral or dissatisfied +5576,59660,Male,Loyal Customer,8,Personal Travel,Eco,861,2,4,2,3,4,2,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +5577,84532,Female,Loyal Customer,21,Business travel,Business,2486,4,4,4,4,3,4,3,3,5,4,3,4,4,3,0,0.0,satisfied +5578,95315,Male,Loyal Customer,29,Personal Travel,Eco,341,4,5,4,4,2,4,2,2,4,4,4,5,4,2,0,0.0,satisfied +5579,89145,Male,disloyal Customer,20,Business travel,Eco,639,1,2,1,3,4,1,4,4,4,1,3,4,4,4,0,0.0,neutral or dissatisfied +5580,73498,Male,Loyal Customer,39,Business travel,Business,3661,4,5,4,4,4,5,4,4,4,4,4,5,4,3,6,7.0,satisfied +5581,112993,Female,Loyal Customer,48,Business travel,Business,1797,1,1,1,1,4,3,4,4,4,4,4,3,4,5,24,27.0,satisfied +5582,49913,Female,disloyal Customer,57,Business travel,Eco,262,3,3,3,2,5,3,4,5,1,5,2,2,2,5,0,0.0,neutral or dissatisfied +5583,115219,Female,Loyal Customer,54,Business travel,Business,325,0,0,0,3,4,4,5,5,5,5,5,4,5,4,0,5.0,satisfied +5584,32849,Male,Loyal Customer,59,Personal Travel,Eco,216,3,1,3,2,1,3,1,1,2,2,1,4,2,1,0,0.0,neutral or dissatisfied +5585,2361,Male,Loyal Customer,29,Business travel,Business,3916,3,3,3,3,4,4,4,4,4,2,4,3,5,4,8,3.0,satisfied +5586,116694,Female,disloyal Customer,37,Business travel,Business,446,1,1,1,4,3,1,3,3,5,4,4,3,4,3,1,0.0,neutral or dissatisfied +5587,14312,Male,Loyal Customer,59,Business travel,Eco,429,2,4,4,4,2,2,2,2,3,3,4,1,3,2,0,0.0,neutral or dissatisfied +5588,80935,Male,Loyal Customer,22,Personal Travel,Eco,341,1,1,1,3,5,1,5,5,1,2,3,4,3,5,0,0.0,neutral or dissatisfied +5589,72751,Male,Loyal Customer,47,Business travel,Business,1850,3,3,3,3,4,4,5,2,2,2,2,3,2,4,0,1.0,satisfied +5590,101084,Male,Loyal Customer,56,Personal Travel,Business,795,2,5,2,1,2,5,5,5,5,2,5,5,5,4,19,10.0,neutral or dissatisfied +5591,55879,Male,disloyal Customer,29,Business travel,Business,733,5,5,5,1,2,5,4,2,3,4,5,5,5,2,24,17.0,satisfied +5592,31582,Male,disloyal Customer,23,Business travel,Eco,602,1,0,1,3,4,1,2,4,5,3,1,4,4,4,0,0.0,neutral or dissatisfied +5593,101069,Male,Loyal Customer,49,Business travel,Business,1908,3,3,3,3,3,5,5,3,3,4,3,5,3,3,14,5.0,satisfied +5594,5439,Female,Loyal Customer,43,Business travel,Business,265,4,4,4,4,4,4,5,4,4,4,4,5,4,3,0,17.0,satisfied +5595,92943,Female,Loyal Customer,10,Personal Travel,Eco,134,1,4,1,2,2,1,2,2,4,5,5,5,4,2,22,50.0,neutral or dissatisfied +5596,107504,Male,Loyal Customer,58,Personal Travel,Eco,711,1,1,0,3,2,0,2,2,4,2,2,3,3,2,66,87.0,neutral or dissatisfied +5597,95785,Male,Loyal Customer,68,Personal Travel,Eco,419,2,4,2,2,1,2,1,1,4,2,3,4,1,1,2,3.0,neutral or dissatisfied +5598,1144,Male,Loyal Customer,60,Personal Travel,Eco,158,3,4,3,1,5,3,2,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +5599,13984,Male,Loyal Customer,43,Business travel,Business,3742,1,1,1,1,1,3,5,3,3,4,3,5,3,4,0,0.0,satisfied +5600,40555,Female,Loyal Customer,54,Business travel,Eco,517,4,1,1,1,4,3,3,4,4,4,4,2,4,2,57,48.0,satisfied +5601,32707,Female,Loyal Customer,43,Business travel,Business,2115,4,4,4,4,2,2,4,5,5,5,5,4,5,1,0,0.0,satisfied +5602,77292,Male,disloyal Customer,45,Business travel,Business,391,2,2,2,3,2,2,1,2,5,2,4,3,5,2,77,77.0,neutral or dissatisfied +5603,125455,Female,Loyal Customer,41,Business travel,Business,2917,3,3,4,3,2,4,5,5,5,5,5,4,5,4,5,0.0,satisfied +5604,77809,Male,Loyal Customer,45,Personal Travel,Eco,689,1,5,1,5,2,1,2,2,3,2,5,5,4,2,0,1.0,neutral or dissatisfied +5605,96848,Male,Loyal Customer,69,Business travel,Business,3227,4,3,2,2,1,4,4,4,4,4,4,4,4,2,3,0.0,neutral or dissatisfied +5606,105,Female,Loyal Customer,55,Business travel,Business,2639,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +5607,120198,Male,Loyal Customer,51,Business travel,Business,1303,4,4,4,4,3,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +5608,37499,Female,Loyal Customer,25,Business travel,Business,3996,4,3,3,3,4,4,4,4,1,3,3,2,4,4,0,0.0,neutral or dissatisfied +5609,122103,Male,Loyal Customer,28,Personal Travel,Eco,130,2,5,2,3,4,2,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +5610,55908,Female,Loyal Customer,31,Business travel,Eco,473,4,3,3,3,4,4,4,4,3,2,2,1,4,4,0,0.0,satisfied +5611,52218,Female,Loyal Customer,37,Business travel,Eco,493,5,3,2,2,5,5,5,5,3,5,1,2,4,5,0,0.0,satisfied +5612,25876,Female,Loyal Customer,51,Business travel,Business,2059,4,4,4,4,3,3,5,3,3,4,3,5,3,5,0,9.0,satisfied +5613,42724,Male,Loyal Customer,57,Personal Travel,Eco,1042,2,5,2,1,5,2,2,5,2,1,3,2,4,5,37,50.0,neutral or dissatisfied +5614,116942,Male,disloyal Customer,29,Business travel,Eco,646,3,3,3,3,1,3,1,1,4,1,3,3,3,1,56,52.0,neutral or dissatisfied +5615,87063,Female,Loyal Customer,53,Business travel,Business,594,2,2,2,2,3,4,4,4,4,4,4,5,4,4,88,84.0,satisfied +5616,46579,Male,Loyal Customer,28,Business travel,Business,141,1,4,4,4,4,4,1,4,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +5617,102258,Female,disloyal Customer,23,Business travel,Eco,226,2,2,2,2,5,2,5,5,3,4,2,3,3,5,0,0.0,neutral or dissatisfied +5618,128429,Male,disloyal Customer,61,Business travel,Eco,304,2,1,2,3,3,2,3,3,2,5,3,3,4,3,2,0.0,neutral or dissatisfied +5619,118900,Female,disloyal Customer,18,Business travel,Eco,570,5,4,5,3,2,5,1,2,3,2,4,5,4,2,1,1.0,satisfied +5620,57866,Male,Loyal Customer,44,Personal Travel,Eco,955,2,5,2,5,2,2,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +5621,102049,Female,Loyal Customer,44,Business travel,Business,2600,1,4,4,4,1,4,4,3,3,3,1,1,3,2,8,11.0,neutral or dissatisfied +5622,84525,Male,disloyal Customer,19,Business travel,Eco,2615,5,5,5,1,1,5,1,1,4,5,4,4,5,1,0,0.0,satisfied +5623,116937,Female,Loyal Customer,31,Business travel,Business,1705,4,4,4,4,4,4,4,4,5,5,4,4,5,4,21,31.0,satisfied +5624,3985,Male,Loyal Customer,50,Business travel,Business,479,4,4,4,4,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +5625,75423,Female,Loyal Customer,36,Business travel,Business,2330,2,4,4,4,2,2,2,2,2,2,2,2,2,3,2,0.0,neutral or dissatisfied +5626,9589,Female,disloyal Customer,30,Business travel,Eco,292,1,1,1,3,5,1,4,5,4,1,3,4,4,5,0,0.0,neutral or dissatisfied +5627,25621,Female,disloyal Customer,50,Business travel,Eco,526,4,2,4,3,5,4,5,5,4,2,2,2,3,5,1,0.0,neutral or dissatisfied +5628,105016,Female,disloyal Customer,30,Business travel,Eco,255,2,4,2,4,3,2,3,3,1,2,4,4,4,3,3,0.0,neutral or dissatisfied +5629,29978,Female,disloyal Customer,20,Business travel,Eco,261,3,1,3,4,2,3,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +5630,14247,Male,Loyal Customer,14,Personal Travel,Eco,1027,2,4,2,3,3,2,3,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +5631,8190,Female,Loyal Customer,50,Business travel,Business,3359,1,1,1,1,4,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +5632,57953,Female,Loyal Customer,49,Business travel,Eco,1062,3,2,2,2,2,3,3,3,3,3,3,4,3,2,48,34.0,neutral or dissatisfied +5633,75134,Male,Loyal Customer,39,Business travel,Business,1726,5,5,1,5,3,4,4,5,5,5,5,4,5,4,4,0.0,satisfied +5634,106860,Male,Loyal Customer,25,Business travel,Business,1993,1,1,1,1,5,5,5,5,5,4,4,3,5,5,9,1.0,satisfied +5635,22351,Male,disloyal Customer,21,Business travel,Eco,83,2,2,2,2,4,2,4,4,1,3,2,1,1,4,8,5.0,neutral or dissatisfied +5636,99276,Female,disloyal Customer,27,Business travel,Eco,935,3,3,3,4,5,3,4,5,3,4,4,1,3,5,7,0.0,neutral or dissatisfied +5637,33937,Female,Loyal Customer,43,Business travel,Eco,1072,2,2,2,2,5,3,4,2,2,2,2,3,2,1,0,3.0,neutral or dissatisfied +5638,34508,Male,Loyal Customer,41,Business travel,Eco,1428,4,2,2,2,4,4,4,4,4,3,1,4,4,4,0,0.0,satisfied +5639,21193,Female,Loyal Customer,33,Business travel,Eco,192,4,2,2,2,4,4,4,1,5,5,5,4,5,4,293,306.0,satisfied +5640,79177,Female,Loyal Customer,58,Business travel,Business,2422,5,5,5,5,5,5,5,4,3,4,5,5,4,5,0,2.0,satisfied +5641,3795,Male,Loyal Customer,40,Business travel,Business,2679,1,1,1,1,5,4,5,4,4,4,4,5,4,3,0,4.0,satisfied +5642,75698,Male,Loyal Customer,38,Business travel,Business,868,4,2,2,2,2,3,4,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +5643,106458,Male,Loyal Customer,56,Personal Travel,Eco,1670,3,1,3,2,1,3,1,1,3,1,3,1,2,1,3,22.0,neutral or dissatisfied +5644,30801,Female,disloyal Customer,25,Business travel,Eco Plus,701,4,3,4,3,2,4,2,2,1,1,3,4,3,2,0,0.0,satisfied +5645,68514,Male,Loyal Customer,20,Personal Travel,Eco Plus,1067,2,4,2,2,3,2,3,3,3,3,4,4,4,3,0,1.0,neutral or dissatisfied +5646,60590,Male,Loyal Customer,49,Personal Travel,Eco,1290,3,4,3,2,4,3,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +5647,37902,Female,Loyal Customer,58,Business travel,Business,2609,3,4,4,4,2,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +5648,53212,Female,Loyal Customer,44,Business travel,Eco,612,2,5,5,5,2,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +5649,75535,Female,Loyal Customer,12,Personal Travel,Business,337,3,4,3,1,5,3,5,5,4,3,4,4,5,5,0,0.0,neutral or dissatisfied +5650,91590,Male,Loyal Customer,60,Business travel,Business,3737,3,3,3,3,5,5,4,4,4,4,4,3,4,4,12,1.0,satisfied +5651,119643,Female,disloyal Customer,29,Business travel,Business,507,5,5,5,2,3,5,1,3,4,2,5,3,4,3,0,0.0,satisfied +5652,81137,Female,Loyal Customer,57,Business travel,Business,3114,3,3,3,3,4,4,4,5,5,5,5,5,5,5,2,0.0,satisfied +5653,32277,Male,Loyal Customer,61,Business travel,Business,3045,3,3,3,3,4,3,1,5,5,5,5,3,5,4,0,0.0,satisfied +5654,20367,Female,Loyal Customer,11,Personal Travel,Eco,287,1,5,5,2,1,5,1,1,3,4,5,5,4,1,30,15.0,neutral or dissatisfied +5655,81751,Female,Loyal Customer,43,Business travel,Business,1310,1,1,1,1,3,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +5656,75451,Female,Loyal Customer,31,Business travel,Business,2342,1,1,1,1,5,5,5,5,3,3,2,3,3,5,85,97.0,satisfied +5657,17112,Male,Loyal Customer,25,Personal Travel,Eco,466,0,4,0,2,2,0,2,2,5,3,4,5,5,2,0,0.0,satisfied +5658,17635,Male,Loyal Customer,40,Business travel,Eco,783,5,4,4,4,5,5,5,5,5,5,3,2,5,5,26,6.0,satisfied +5659,20505,Male,Loyal Customer,38,Personal Travel,Eco,139,3,5,3,4,5,3,3,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +5660,69964,Female,disloyal Customer,22,Business travel,Eco,236,1,4,1,2,2,1,2,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +5661,25383,Female,Loyal Customer,25,Personal Travel,Eco,591,3,4,3,2,2,3,2,2,5,5,4,5,5,2,19,14.0,neutral or dissatisfied +5662,10158,Female,Loyal Customer,51,Business travel,Eco,1195,2,5,4,4,4,4,4,2,2,2,2,2,2,1,75,85.0,neutral or dissatisfied +5663,50601,Male,Loyal Customer,43,Personal Travel,Eco,304,2,5,2,5,5,2,1,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +5664,94443,Female,Loyal Customer,49,Business travel,Business,189,0,4,0,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +5665,42151,Male,Loyal Customer,19,Personal Travel,Business,726,2,1,2,4,5,2,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +5666,78024,Male,Loyal Customer,50,Business travel,Business,2168,1,3,3,3,2,4,4,2,2,2,1,4,2,2,0,7.0,neutral or dissatisfied +5667,90243,Female,Loyal Customer,42,Business travel,Business,2433,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +5668,123382,Male,Loyal Customer,35,Personal Travel,Eco Plus,644,4,5,4,4,1,4,1,1,5,2,4,3,4,1,0,0.0,neutral or dissatisfied +5669,52042,Female,Loyal Customer,46,Business travel,Business,2826,2,5,2,2,4,5,5,5,5,4,5,4,5,5,0,6.0,satisfied +5670,88023,Male,disloyal Customer,27,Business travel,Business,404,0,0,0,2,5,0,3,5,4,2,4,4,5,5,62,53.0,satisfied +5671,27753,Male,disloyal Customer,25,Business travel,Eco,680,4,4,4,3,4,4,4,4,2,1,2,2,3,4,0,8.0,satisfied +5672,85160,Female,disloyal Customer,36,Business travel,Business,731,3,3,3,1,5,3,5,5,4,5,5,5,4,5,9,4.0,neutral or dissatisfied +5673,76192,Male,Loyal Customer,47,Business travel,Business,2422,4,5,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +5674,94224,Female,Loyal Customer,45,Business travel,Business,2422,0,5,0,4,2,4,4,5,5,3,3,5,5,4,14,13.0,satisfied +5675,61694,Male,disloyal Customer,37,Business travel,Business,1608,3,3,3,5,4,3,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +5676,112125,Female,Loyal Customer,45,Business travel,Business,2565,4,4,5,4,4,2,3,4,4,4,4,1,4,1,86,73.0,neutral or dissatisfied +5677,119251,Male,Loyal Customer,53,Business travel,Business,3904,3,3,3,3,2,4,4,5,5,5,4,5,5,4,0,2.0,satisfied +5678,118547,Male,Loyal Customer,42,Business travel,Business,304,2,2,2,2,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +5679,120482,Male,Loyal Customer,19,Personal Travel,Eco,449,2,4,2,3,1,2,1,1,5,3,4,4,4,1,4,39.0,neutral or dissatisfied +5680,124684,Female,disloyal Customer,33,Business travel,Eco,399,2,1,2,3,4,2,4,4,1,5,3,2,3,4,0,5.0,neutral or dissatisfied +5681,49660,Male,Loyal Customer,55,Business travel,Business,2926,3,5,5,5,3,3,4,1,1,1,3,3,1,3,1,0.0,neutral or dissatisfied +5682,59980,Male,Loyal Customer,59,Personal Travel,Eco,1068,4,1,4,3,1,4,1,1,3,4,4,2,4,1,5,0.0,neutral or dissatisfied +5683,19472,Male,Loyal Customer,41,Business travel,Eco,84,1,5,5,5,1,1,1,1,1,3,2,1,3,1,149,133.0,neutral or dissatisfied +5684,71179,Male,Loyal Customer,57,Business travel,Business,1722,4,4,4,4,4,5,4,5,5,5,5,3,5,3,18,0.0,satisfied +5685,103812,Male,Loyal Customer,60,Business travel,Business,2303,1,1,1,1,2,2,2,3,5,4,4,2,5,2,298,292.0,satisfied +5686,102022,Female,Loyal Customer,46,Business travel,Business,236,3,3,3,3,4,4,4,4,4,4,4,4,4,5,33,44.0,satisfied +5687,112426,Female,disloyal Customer,14,Business travel,Eco,846,3,3,3,3,4,3,4,4,2,5,4,2,3,4,21,12.0,neutral or dissatisfied +5688,2456,Female,Loyal Customer,48,Business travel,Business,722,1,1,1,1,5,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +5689,52274,Female,Loyal Customer,43,Business travel,Eco,370,2,2,2,2,1,3,3,3,3,2,3,2,3,4,10,15.0,neutral or dissatisfied +5690,27989,Male,Loyal Customer,50,Business travel,Business,1616,5,5,5,5,5,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +5691,50444,Male,Loyal Customer,32,Business travel,Business,2072,2,1,1,1,2,3,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +5692,93635,Female,Loyal Customer,50,Personal Travel,Eco,577,2,4,2,3,2,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +5693,41357,Male,Loyal Customer,34,Personal Travel,Business,563,3,5,3,1,2,4,4,2,2,3,2,3,2,4,0,6.0,neutral or dissatisfied +5694,65557,Male,Loyal Customer,40,Business travel,Business,1791,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +5695,14180,Female,Loyal Customer,50,Business travel,Business,692,4,5,5,5,4,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +5696,62803,Male,Loyal Customer,32,Personal Travel,Eco,2367,1,1,2,3,3,2,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +5697,122658,Female,Loyal Customer,44,Business travel,Business,361,3,1,3,3,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +5698,39325,Female,Loyal Customer,33,Business travel,Eco Plus,67,5,3,3,3,5,5,5,5,5,5,3,4,5,5,42,41.0,satisfied +5699,95462,Female,Loyal Customer,59,Business travel,Business,677,2,2,5,2,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +5700,104091,Female,Loyal Customer,37,Business travel,Business,2242,3,2,2,2,3,3,3,3,3,3,3,2,3,1,1,0.0,neutral or dissatisfied +5701,75314,Male,Loyal Customer,40,Business travel,Business,2615,4,4,4,4,5,5,5,3,3,5,5,5,4,5,0,0.0,satisfied +5702,37967,Female,Loyal Customer,39,Business travel,Business,1249,3,3,3,3,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +5703,123099,Male,Loyal Customer,45,Business travel,Business,600,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,3.0,satisfied +5704,29511,Male,Loyal Customer,42,Business travel,Eco Plus,1216,4,4,4,4,4,4,4,4,2,4,5,3,1,4,0,1.0,satisfied +5705,19507,Male,disloyal Customer,29,Business travel,Eco,508,2,3,2,4,2,3,3,2,4,4,4,3,3,3,213,197.0,neutral or dissatisfied +5706,42270,Male,Loyal Customer,31,Business travel,Eco,329,3,5,5,5,3,3,3,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +5707,40442,Male,Loyal Customer,53,Business travel,Eco,461,4,2,2,2,4,4,4,4,1,5,4,2,5,4,0,0.0,satisfied +5708,94931,Female,Loyal Customer,41,Business travel,Business,1934,5,5,1,5,5,3,3,4,4,4,5,1,4,4,41,25.0,satisfied +5709,58147,Female,Loyal Customer,57,Business travel,Business,925,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +5710,125708,Male,Loyal Customer,14,Personal Travel,Eco,857,2,4,2,3,5,2,5,5,2,1,5,5,2,5,1,0.0,neutral or dissatisfied +5711,20572,Female,Loyal Customer,44,Business travel,Eco,165,4,2,4,4,5,5,5,4,4,4,4,4,4,2,6,0.0,satisfied +5712,101729,Male,Loyal Customer,36,Personal Travel,Eco,1216,3,1,3,3,5,3,5,5,1,5,4,4,4,5,21,0.0,neutral or dissatisfied +5713,95054,Male,Loyal Customer,23,Personal Travel,Eco,323,3,5,3,3,4,3,4,4,3,5,2,1,5,4,0,0.0,neutral or dissatisfied +5714,30857,Male,Loyal Customer,68,Personal Travel,Business,1546,2,5,2,3,4,5,5,2,2,2,2,4,2,4,0,9.0,neutral or dissatisfied +5715,51851,Female,disloyal Customer,30,Business travel,Eco Plus,651,1,1,1,3,4,1,4,4,2,4,4,2,4,4,33,16.0,neutral or dissatisfied +5716,105722,Male,disloyal Customer,40,Business travel,Eco,925,3,3,3,4,5,3,5,5,4,2,4,1,4,5,23,22.0,neutral or dissatisfied +5717,62916,Female,disloyal Customer,36,Business travel,Business,862,3,3,3,2,5,3,5,5,5,5,4,3,4,5,56,52.0,neutral or dissatisfied +5718,97351,Female,Loyal Customer,38,Business travel,Business,2831,2,2,2,2,5,4,4,4,4,4,4,3,4,2,3,5.0,satisfied +5719,48350,Male,disloyal Customer,24,Business travel,Eco,587,5,0,5,1,2,5,2,2,5,3,5,3,5,2,46,46.0,satisfied +5720,18216,Female,Loyal Customer,43,Business travel,Business,3484,3,3,3,3,1,2,4,3,3,4,3,5,3,2,3,6.0,satisfied +5721,32837,Male,Loyal Customer,60,Personal Travel,Eco,101,0,4,0,5,2,0,2,2,4,2,4,5,5,2,0,0.0,satisfied +5722,84803,Female,Loyal Customer,57,Business travel,Business,2227,2,2,1,2,4,4,4,5,4,4,5,4,3,4,184,167.0,satisfied +5723,16559,Male,Loyal Customer,65,Business travel,Business,1974,5,5,5,5,3,3,5,5,5,5,5,3,5,4,0,0.0,satisfied +5724,66696,Female,Loyal Customer,59,Business travel,Business,802,3,3,3,3,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +5725,118370,Male,Loyal Customer,30,Personal Travel,Eco Plus,602,3,3,3,2,5,3,5,5,4,4,5,5,5,5,27,21.0,neutral or dissatisfied +5726,1857,Female,Loyal Customer,44,Business travel,Business,3798,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +5727,66726,Male,Loyal Customer,11,Personal Travel,Eco,978,2,4,3,1,5,3,1,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +5728,119877,Female,Loyal Customer,44,Personal Travel,Eco,936,1,5,1,2,4,4,5,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +5729,47421,Male,disloyal Customer,28,Business travel,Eco,501,2,0,2,3,1,2,1,1,5,5,5,1,4,1,0,0.0,neutral or dissatisfied +5730,28521,Female,Loyal Customer,35,Business travel,Business,2677,3,3,3,3,5,4,3,5,5,5,5,1,5,5,0,0.0,satisfied +5731,102218,Male,Loyal Customer,59,Business travel,Business,1676,2,1,1,1,2,3,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +5732,114096,Male,Loyal Customer,33,Personal Travel,Eco,2139,5,4,5,5,4,5,4,4,5,2,4,3,5,4,0,0.0,satisfied +5733,7859,Male,disloyal Customer,24,Business travel,Business,910,4,2,4,2,4,4,2,4,4,5,4,4,4,4,0,19.0,satisfied +5734,80172,Male,disloyal Customer,23,Business travel,Eco,2475,3,3,3,4,3,4,4,2,1,4,4,4,1,4,312,312.0,neutral or dissatisfied +5735,16242,Female,disloyal Customer,32,Business travel,Eco,748,4,4,4,1,2,4,2,2,5,4,3,3,3,2,0,0.0,neutral or dissatisfied +5736,30299,Male,Loyal Customer,12,Business travel,Eco,1476,5,2,2,2,5,5,5,5,2,4,3,4,3,5,0,0.0,satisfied +5737,29528,Male,Loyal Customer,34,Personal Travel,Eco,1009,4,3,4,2,3,4,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +5738,104421,Male,disloyal Customer,41,Business travel,Business,1147,5,5,5,3,4,5,4,4,5,3,4,5,5,4,7,6.0,satisfied +5739,107548,Female,Loyal Customer,50,Business travel,Business,1521,2,5,5,5,4,2,3,2,2,2,2,2,2,4,17,0.0,neutral or dissatisfied +5740,82600,Female,Loyal Customer,41,Business travel,Business,2199,3,5,3,5,4,2,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +5741,84476,Female,Loyal Customer,60,Personal Travel,Eco,1142,1,5,1,2,3,3,5,2,2,1,3,1,2,2,0,0.0,neutral or dissatisfied +5742,1458,Female,disloyal Customer,32,Business travel,Business,695,4,4,4,3,5,4,5,5,1,5,4,3,3,5,34,30.0,neutral or dissatisfied +5743,34201,Male,Loyal Customer,21,Personal Travel,Eco,1129,1,4,1,3,1,1,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +5744,128088,Male,Loyal Customer,28,Business travel,Eco,2917,2,2,2,2,2,2,2,2,5,4,4,2,1,2,1,44.0,neutral or dissatisfied +5745,23204,Female,Loyal Customer,46,Personal Travel,Eco Plus,300,1,4,1,4,3,4,3,4,4,1,4,4,4,1,4,0.0,neutral or dissatisfied +5746,30004,Female,Loyal Customer,32,Business travel,Business,3212,1,2,2,2,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +5747,41410,Female,Loyal Customer,31,Personal Travel,Eco,563,0,5,0,3,4,0,4,4,5,2,4,3,5,4,0,17.0,satisfied +5748,98073,Female,Loyal Customer,65,Business travel,Eco,1449,1,5,5,5,4,3,4,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +5749,124597,Female,Loyal Customer,40,Personal Travel,Eco,500,2,4,2,2,5,2,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +5750,67023,Female,Loyal Customer,56,Business travel,Business,2148,4,4,5,4,2,5,5,3,3,4,3,5,3,5,0,0.0,satisfied +5751,24454,Male,Loyal Customer,37,Business travel,Business,2974,3,3,3,3,1,2,1,4,4,4,4,3,4,4,0,0.0,satisfied +5752,73559,Male,Loyal Customer,38,Business travel,Business,1994,0,5,0,3,4,5,4,1,1,1,1,4,1,4,1,0.0,satisfied +5753,117582,Female,Loyal Customer,55,Business travel,Business,2985,2,2,2,2,4,4,4,5,5,5,5,4,5,4,36,31.0,satisfied +5754,99158,Male,Loyal Customer,33,Business travel,Eco,986,1,2,2,2,1,1,1,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +5755,66257,Female,Loyal Customer,10,Personal Travel,Eco,550,3,4,3,3,1,3,1,1,4,5,4,2,4,1,24,17.0,neutral or dissatisfied +5756,69196,Female,Loyal Customer,35,Personal Travel,Eco Plus,187,1,4,0,3,3,0,3,3,5,3,5,4,5,3,0,3.0,neutral or dissatisfied +5757,12279,Male,disloyal Customer,21,Business travel,Eco,253,3,3,3,4,4,3,5,4,3,2,3,3,4,4,0,0.0,neutral or dissatisfied +5758,87667,Female,Loyal Customer,53,Business travel,Business,2297,1,4,2,4,2,4,3,1,1,1,1,4,1,1,0,13.0,neutral or dissatisfied +5759,46333,Female,Loyal Customer,22,Business travel,Business,692,2,2,2,2,5,5,5,5,3,2,2,2,4,5,0,26.0,satisfied +5760,51838,Male,Loyal Customer,11,Personal Travel,Eco Plus,509,3,4,3,5,5,3,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +5761,9150,Male,Loyal Customer,21,Personal Travel,Eco,227,4,4,0,3,3,0,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +5762,25810,Male,disloyal Customer,9,Business travel,Eco,1747,3,3,3,4,1,3,1,1,3,4,4,1,3,1,8,0.0,neutral or dissatisfied +5763,69092,Female,Loyal Customer,38,Personal Travel,Eco,1389,2,4,1,3,3,1,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +5764,60240,Female,Loyal Customer,55,Personal Travel,Eco,1506,2,5,2,5,3,4,5,3,3,2,3,5,3,3,8,15.0,neutral or dissatisfied +5765,27975,Female,Loyal Customer,30,Business travel,Business,2378,3,3,2,3,5,5,5,3,2,4,1,5,2,5,0,0.0,satisfied +5766,85193,Male,disloyal Customer,26,Business travel,Business,874,3,3,3,3,3,3,5,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +5767,12232,Male,disloyal Customer,22,Business travel,Eco,192,2,3,2,1,4,2,5,4,5,4,5,4,5,4,0,6.0,neutral or dissatisfied +5768,20291,Male,Loyal Customer,11,Personal Travel,Eco,137,1,4,0,3,2,0,2,2,1,2,2,4,2,2,0,0.0,neutral or dissatisfied +5769,14907,Female,Loyal Customer,62,Personal Travel,Eco,315,4,5,3,2,3,5,5,2,2,3,2,5,2,5,15,24.0,neutral or dissatisfied +5770,80655,Male,Loyal Customer,25,Business travel,Business,821,5,5,5,5,2,2,2,2,4,2,4,3,5,2,16,15.0,satisfied +5771,55996,Male,disloyal Customer,22,Business travel,Eco,2586,4,4,4,1,4,5,5,3,5,5,4,5,3,5,177,225.0,satisfied +5772,36962,Female,Loyal Customer,39,Business travel,Eco,814,5,1,1,1,5,5,5,3,4,5,1,5,2,5,396,381.0,satisfied +5773,66737,Male,Loyal Customer,43,Personal Travel,Eco,802,0,4,0,3,2,0,4,2,4,5,3,3,4,2,0,0.0,satisfied +5774,129042,Male,disloyal Customer,31,Business travel,Eco,1744,2,2,2,2,2,2,2,4,3,2,3,2,4,2,148,143.0,neutral or dissatisfied +5775,66937,Female,Loyal Customer,41,Business travel,Business,929,2,2,2,2,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +5776,98737,Female,Loyal Customer,52,Business travel,Eco,1558,4,3,3,3,1,4,4,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +5777,2540,Female,Loyal Customer,44,Business travel,Business,2014,0,0,0,4,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +5778,117351,Female,disloyal Customer,22,Business travel,Eco,296,3,4,4,4,4,4,4,4,4,4,3,3,4,4,63,71.0,neutral or dissatisfied +5779,28925,Female,Loyal Customer,27,Business travel,Business,954,1,1,1,1,4,4,4,4,4,5,4,2,5,4,0,0.0,satisfied +5780,1678,Male,Loyal Customer,30,Business travel,Business,2475,2,3,3,3,2,2,2,2,4,1,3,4,4,2,40,35.0,neutral or dissatisfied +5781,74980,Male,Loyal Customer,63,Personal Travel,Eco,2475,1,1,2,3,3,2,3,3,4,2,4,2,3,3,20,0.0,neutral or dissatisfied +5782,56426,Female,Loyal Customer,34,Business travel,Business,719,1,2,2,2,2,3,4,1,1,1,1,3,1,3,0,1.0,neutral or dissatisfied +5783,69655,Female,Loyal Customer,41,Business travel,Business,2729,2,2,2,2,3,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +5784,29554,Female,disloyal Customer,25,Business travel,Eco,933,2,2,2,2,4,2,4,4,3,2,2,3,2,4,0,0.0,neutral or dissatisfied +5785,57825,Female,Loyal Customer,15,Personal Travel,Eco,622,3,5,4,3,5,4,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +5786,2642,Male,Loyal Customer,31,Business travel,Business,597,1,1,1,1,3,3,3,3,4,2,5,5,4,3,10,2.0,satisfied +5787,30936,Male,disloyal Customer,38,Business travel,Eco,1024,2,2,2,3,4,2,4,4,3,3,5,3,5,4,23,19.0,neutral or dissatisfied +5788,107682,Male,disloyal Customer,25,Business travel,Business,251,2,0,2,3,2,2,2,2,4,2,4,5,4,2,3,0.0,neutral or dissatisfied +5789,8715,Female,Loyal Customer,23,Personal Travel,Eco,227,2,4,0,3,1,0,1,1,4,2,4,4,4,1,9,16.0,neutral or dissatisfied +5790,66694,Female,Loyal Customer,37,Business travel,Business,978,4,2,2,2,3,2,2,4,4,4,4,2,4,2,31,16.0,neutral or dissatisfied +5791,109011,Female,Loyal Customer,56,Business travel,Business,781,2,2,2,2,3,5,4,4,4,4,4,5,4,4,12,13.0,satisfied +5792,31696,Female,disloyal Customer,44,Business travel,Eco,462,3,4,4,4,3,4,4,3,3,2,3,2,3,3,105,85.0,neutral or dissatisfied +5793,64051,Male,Loyal Customer,47,Business travel,Business,1651,2,2,2,2,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +5794,125754,Male,Loyal Customer,37,Business travel,Business,2128,2,2,2,2,5,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +5795,100529,Female,Loyal Customer,63,Personal Travel,Eco,580,2,4,2,1,2,1,3,5,5,4,5,3,4,3,217,209.0,neutral or dissatisfied +5796,70289,Male,disloyal Customer,24,Business travel,Eco,452,4,3,4,3,4,4,4,4,5,3,1,1,4,4,0,0.0,satisfied +5797,70512,Female,Loyal Customer,21,Personal Travel,Eco,867,3,4,3,2,1,3,1,1,3,3,4,3,5,1,0,0.0,neutral or dissatisfied +5798,116720,Female,Loyal Customer,34,Business travel,Eco Plus,337,3,5,5,5,3,3,3,3,4,4,4,2,3,3,1,0.0,neutral or dissatisfied +5799,127183,Female,disloyal Customer,48,Business travel,Eco Plus,646,2,1,1,3,4,2,4,4,2,3,3,1,3,4,0,0.0,neutral or dissatisfied +5800,6232,Male,disloyal Customer,22,Business travel,Business,594,0,4,0,4,3,0,3,3,4,3,5,4,4,3,0,0.0,satisfied +5801,82844,Male,Loyal Customer,37,Business travel,Business,3033,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,7.0,satisfied +5802,51271,Female,disloyal Customer,41,Business travel,Business,89,3,3,3,5,1,3,1,1,4,5,2,4,3,1,0,0.0,neutral or dissatisfied +5803,53076,Female,Loyal Customer,27,Business travel,Eco Plus,1208,2,4,4,4,2,2,2,2,1,1,4,4,3,2,3,17.0,neutral or dissatisfied +5804,6618,Male,Loyal Customer,34,Personal Travel,Eco Plus,607,3,4,3,1,5,3,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +5805,36806,Female,Loyal Customer,58,Personal Travel,Eco Plus,2611,2,1,2,4,2,3,3,2,5,3,3,3,1,3,0,0.0,neutral or dissatisfied +5806,72306,Male,Loyal Customer,31,Personal Travel,Eco,919,3,2,3,4,5,3,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +5807,86125,Female,Loyal Customer,52,Business travel,Business,226,4,4,3,4,2,5,4,5,5,5,5,3,5,3,16,1.0,satisfied +5808,3473,Male,Loyal Customer,49,Business travel,Business,3472,4,3,3,3,4,3,4,4,4,4,4,4,4,4,0,1.0,neutral or dissatisfied +5809,52037,Female,Loyal Customer,35,Business travel,Eco Plus,328,4,2,4,4,4,4,4,4,2,4,1,2,5,4,0,0.0,satisfied +5810,28830,Female,Loyal Customer,27,Business travel,Eco,679,4,1,1,1,4,5,4,4,1,5,3,3,3,4,0,0.0,satisfied +5811,47456,Female,Loyal Customer,32,Personal Travel,Eco,590,3,4,3,1,5,3,5,5,3,2,5,5,5,5,2,0.0,neutral or dissatisfied +5812,114154,Male,Loyal Customer,43,Business travel,Business,2540,3,3,3,3,2,4,5,4,4,4,4,4,4,5,114,106.0,satisfied +5813,46868,Male,disloyal Customer,42,Business travel,Eco,737,4,4,4,1,2,4,5,2,3,3,1,3,5,2,77,69.0,satisfied +5814,52083,Female,Loyal Customer,31,Business travel,Eco,438,5,3,4,3,5,5,5,5,3,1,1,1,5,5,0,1.0,satisfied +5815,106511,Female,Loyal Customer,58,Business travel,Business,2113,5,5,5,5,4,5,4,4,4,4,4,4,4,3,28,22.0,satisfied +5816,36483,Male,Loyal Customer,55,Business travel,Business,1237,5,5,5,5,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +5817,86740,Female,Loyal Customer,39,Business travel,Business,3662,1,1,1,1,2,5,5,2,2,2,2,4,2,3,20,37.0,satisfied +5818,92877,Female,Loyal Customer,54,Business travel,Business,302,2,3,3,3,3,4,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +5819,126246,Male,Loyal Customer,61,Business travel,Eco,200,5,1,1,1,4,5,4,4,2,2,2,4,2,4,0,0.0,satisfied +5820,113125,Male,Loyal Customer,40,Business travel,Business,3969,4,4,4,4,2,5,4,4,4,4,4,4,4,5,9,7.0,satisfied +5821,78922,Female,Loyal Customer,47,Business travel,Business,501,1,1,1,1,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +5822,127647,Male,Loyal Customer,35,Personal Travel,Eco,1773,1,2,1,3,4,1,2,4,2,2,3,4,4,4,0,35.0,neutral or dissatisfied +5823,12223,Male,Loyal Customer,65,Personal Travel,Business,190,3,4,3,3,2,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +5824,87375,Male,Loyal Customer,39,Business travel,Business,3974,2,2,2,2,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +5825,36514,Male,Loyal Customer,24,Business travel,Business,1010,5,5,5,5,5,5,5,5,5,5,5,2,3,5,1,0.0,satisfied +5826,91148,Female,Loyal Customer,52,Personal Travel,Eco,250,3,5,3,5,4,4,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +5827,84526,Male,Loyal Customer,45,Business travel,Business,2486,5,5,5,5,5,5,4,5,5,5,5,5,5,5,34,19.0,satisfied +5828,16498,Female,Loyal Customer,33,Business travel,Business,246,5,5,5,5,2,4,2,4,4,5,4,3,4,3,34,42.0,satisfied +5829,803,Female,Loyal Customer,42,Business travel,Business,3761,3,1,1,1,3,4,3,3,3,3,3,4,3,4,5,12.0,neutral or dissatisfied +5830,56331,Male,Loyal Customer,56,Business travel,Business,2907,5,5,5,5,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +5831,73928,Male,Loyal Customer,55,Business travel,Business,2342,1,4,4,4,2,2,2,1,1,1,1,2,1,4,1,0.0,neutral or dissatisfied +5832,48451,Male,disloyal Customer,24,Business travel,Eco,763,4,4,4,3,1,4,1,1,1,4,1,3,3,1,0,0.0,satisfied +5833,92916,Female,Loyal Customer,74,Business travel,Eco,151,1,0,0,3,2,3,4,5,5,1,5,4,5,2,15,3.0,neutral or dissatisfied +5834,71575,Female,disloyal Customer,28,Business travel,Business,1197,4,4,4,3,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +5835,80795,Female,Loyal Customer,56,Business travel,Business,2301,5,5,5,5,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +5836,33824,Female,Loyal Customer,47,Business travel,Eco Plus,1521,4,2,2,2,1,4,4,4,4,4,4,4,4,1,0,5.0,satisfied +5837,124323,Female,Loyal Customer,7,Personal Travel,Eco,255,2,4,2,1,1,2,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +5838,12079,Male,Loyal Customer,39,Business travel,Eco Plus,376,3,2,1,2,3,3,3,3,4,3,3,3,2,3,1,0.0,neutral or dissatisfied +5839,13207,Female,Loyal Customer,46,Business travel,Business,3077,1,1,1,1,2,5,5,4,4,3,4,4,4,5,0,0.0,satisfied +5840,100439,Male,Loyal Customer,50,Business travel,Eco Plus,1912,1,4,4,4,1,1,1,1,2,2,4,1,4,1,5,37.0,neutral or dissatisfied +5841,72383,Male,disloyal Customer,22,Business travel,Eco,1119,3,3,3,3,4,3,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +5842,29656,Male,Loyal Customer,36,Personal Travel,Eco,1533,0,2,0,4,2,0,2,2,2,2,2,4,4,2,0,0.0,satisfied +5843,44096,Female,disloyal Customer,22,Business travel,Eco,408,4,5,4,2,2,4,2,2,5,1,4,3,5,2,10,11.0,neutral or dissatisfied +5844,65500,Male,Loyal Customer,53,Business travel,Business,1303,5,3,5,5,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +5845,96256,Male,Loyal Customer,63,Personal Travel,Eco,460,1,1,1,4,1,1,1,1,4,4,3,1,4,1,1,0.0,neutral or dissatisfied +5846,43755,Male,Loyal Customer,22,Business travel,Business,2446,5,5,5,5,5,5,5,5,4,1,1,1,2,5,0,0.0,satisfied +5847,91822,Male,Loyal Customer,52,Business travel,Business,590,3,3,3,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +5848,124399,Male,Loyal Customer,60,Personal Travel,Eco Plus,808,2,5,2,3,4,2,4,4,1,1,1,1,5,4,3,0.0,neutral or dissatisfied +5849,93779,Female,disloyal Customer,24,Business travel,Eco,1249,3,3,3,4,3,3,2,3,1,1,4,4,3,3,0,0.0,neutral or dissatisfied +5850,9635,Female,Loyal Customer,36,Business travel,Business,199,5,5,5,5,5,4,4,4,4,4,4,3,4,4,0,8.0,satisfied +5851,123315,Female,Loyal Customer,23,Business travel,Eco Plus,468,1,1,2,1,1,1,3,1,2,2,4,2,3,1,16,12.0,neutral or dissatisfied +5852,111694,Female,Loyal Customer,43,Business travel,Business,495,4,4,4,4,5,5,4,3,3,3,3,5,3,5,11,10.0,satisfied +5853,86552,Male,Loyal Customer,57,Business travel,Business,3107,3,4,3,3,5,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +5854,71619,Female,disloyal Customer,22,Business travel,Eco,1182,1,1,1,4,2,1,2,2,4,3,4,3,4,2,5,6.0,neutral or dissatisfied +5855,75359,Female,Loyal Customer,46,Business travel,Business,2504,4,4,4,4,5,5,5,3,2,4,4,5,4,5,0,14.0,satisfied +5856,102495,Female,Loyal Customer,12,Personal Travel,Eco,226,2,4,2,4,2,2,2,2,3,3,5,5,5,2,19,11.0,neutral or dissatisfied +5857,81972,Male,Loyal Customer,47,Business travel,Business,1535,4,4,4,4,2,4,5,4,4,4,4,5,4,4,5,0.0,satisfied +5858,121809,Female,Loyal Customer,50,Business travel,Business,449,5,5,5,5,4,5,4,4,4,4,4,5,4,5,93,79.0,satisfied +5859,86206,Female,Loyal Customer,54,Business travel,Business,1573,3,3,3,3,4,3,3,3,3,3,3,2,3,3,34,10.0,neutral or dissatisfied +5860,101538,Male,Loyal Customer,51,Personal Travel,Eco,345,4,4,4,4,5,4,5,5,5,3,4,5,5,5,6,0.0,neutral or dissatisfied +5861,122603,Female,disloyal Customer,26,Business travel,Eco,728,3,3,3,3,5,3,5,5,4,5,3,4,4,5,29,30.0,neutral or dissatisfied +5862,20420,Female,Loyal Customer,62,Business travel,Eco,299,3,1,1,1,1,3,4,3,3,3,3,4,3,2,6,0.0,neutral or dissatisfied +5863,85154,Male,Loyal Customer,50,Business travel,Business,2728,3,3,3,3,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +5864,175,Male,disloyal Customer,36,Business travel,Business,227,2,2,2,3,5,2,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +5865,89864,Male,Loyal Customer,41,Business travel,Business,2104,3,3,5,3,2,5,4,5,5,5,5,4,5,5,79,79.0,satisfied +5866,46146,Female,Loyal Customer,40,Business travel,Eco,516,4,4,4,4,4,4,4,4,3,1,3,2,3,4,29,34.0,neutral or dissatisfied +5867,129334,Male,Loyal Customer,37,Business travel,Business,2475,1,1,1,1,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +5868,5944,Female,Loyal Customer,42,Business travel,Business,2267,4,4,4,4,3,4,5,4,4,4,4,4,4,5,7,4.0,satisfied +5869,76126,Female,Loyal Customer,29,Business travel,Business,689,1,1,1,1,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +5870,93892,Male,disloyal Customer,18,Business travel,Eco,590,1,4,1,3,1,1,1,1,3,1,3,4,4,1,40,43.0,neutral or dissatisfied +5871,44577,Female,Loyal Customer,70,Business travel,Business,2625,0,4,0,2,5,4,5,4,4,5,5,2,4,4,0,6.0,satisfied +5872,50470,Male,Loyal Customer,33,Business travel,Business,2076,0,5,0,1,4,4,4,4,1,3,5,5,3,4,0,0.0,satisfied +5873,25041,Female,Loyal Customer,54,Business travel,Eco Plus,907,4,1,1,1,4,3,2,4,4,4,4,1,4,4,42,40.0,neutral or dissatisfied +5874,114876,Female,Loyal Customer,34,Business travel,Business,1782,3,3,4,3,5,4,5,4,4,4,4,3,4,3,28,16.0,satisfied +5875,92470,Female,Loyal Customer,48,Business travel,Eco,1892,4,2,2,2,2,3,3,4,4,4,4,2,4,3,4,17.0,neutral or dissatisfied +5876,88927,Male,Loyal Customer,46,Business travel,Business,3098,1,1,4,1,3,5,5,3,3,4,3,4,3,4,3,0.0,satisfied +5877,20485,Female,Loyal Customer,42,Business travel,Eco,139,4,3,3,3,3,4,5,3,3,4,3,3,3,2,55,75.0,satisfied +5878,13186,Male,disloyal Customer,36,Business travel,Eco,542,2,0,2,2,2,3,3,3,5,3,2,3,1,3,202,184.0,neutral or dissatisfied +5879,66837,Female,Loyal Customer,47,Business travel,Business,731,3,5,5,5,2,4,3,3,3,3,3,2,3,2,16,0.0,neutral or dissatisfied +5880,14078,Female,Loyal Customer,42,Business travel,Eco,425,3,5,5,5,2,2,3,4,4,3,4,2,4,2,3,0.0,neutral or dissatisfied +5881,95788,Male,Loyal Customer,28,Personal Travel,Eco,181,2,4,2,5,3,2,4,3,5,3,4,3,1,3,16,16.0,neutral or dissatisfied +5882,123731,Male,Loyal Customer,24,Personal Travel,Eco Plus,214,2,3,2,3,4,2,4,4,4,3,4,4,3,4,0,6.0,neutral or dissatisfied +5883,35017,Female,Loyal Customer,27,Business travel,Business,2559,3,3,3,3,3,3,3,3,4,5,2,3,2,3,0,15.0,neutral or dissatisfied +5884,85659,Female,Loyal Customer,18,Personal Travel,Business,903,2,4,2,4,5,2,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +5885,79888,Male,Loyal Customer,47,Business travel,Eco,1089,2,5,5,5,2,2,2,2,2,2,2,1,3,2,8,0.0,neutral or dissatisfied +5886,5464,Male,Loyal Customer,41,Personal Travel,Eco,287,1,2,3,4,5,3,4,5,1,3,4,4,4,5,52,48.0,neutral or dissatisfied +5887,39738,Male,Loyal Customer,36,Personal Travel,Eco,320,3,5,1,3,3,1,3,3,5,5,2,2,5,3,0,9.0,neutral or dissatisfied +5888,44641,Female,disloyal Customer,29,Business travel,Eco,67,5,5,5,1,5,5,5,5,4,2,2,4,3,5,76,66.0,satisfied +5889,99970,Male,Loyal Customer,66,Personal Travel,Eco,888,1,5,1,4,3,1,3,3,5,3,5,5,4,3,1,0.0,neutral or dissatisfied +5890,2144,Female,Loyal Customer,18,Personal Travel,Eco Plus,431,3,5,3,1,2,3,4,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +5891,37406,Female,Loyal Customer,38,Business travel,Business,3828,4,4,4,4,2,4,2,5,5,5,5,1,5,1,0,0.0,satisfied +5892,114867,Female,Loyal Customer,41,Business travel,Business,3941,1,1,1,1,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +5893,38065,Male,Loyal Customer,48,Business travel,Business,3783,2,2,2,2,1,3,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +5894,93638,Female,Loyal Customer,19,Personal Travel,Eco,577,1,4,1,1,3,1,2,3,4,4,4,3,5,3,4,2.0,neutral or dissatisfied +5895,15898,Male,Loyal Customer,51,Business travel,Eco,378,2,3,3,3,2,2,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +5896,30635,Female,Loyal Customer,51,Business travel,Business,3866,2,2,2,2,3,4,4,4,4,4,4,5,4,2,0,0.0,satisfied +5897,40180,Female,disloyal Customer,43,Business travel,Eco,531,4,0,4,1,4,4,4,4,2,2,2,4,5,4,0,4.0,neutral or dissatisfied +5898,16991,Male,Loyal Customer,31,Business travel,Business,843,2,2,2,2,5,5,5,5,4,5,5,4,5,5,2,0.0,satisfied +5899,42312,Male,Loyal Customer,16,Personal Travel,Eco,838,4,4,4,3,3,4,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +5900,95176,Female,Loyal Customer,59,Personal Travel,Eco,248,2,4,2,2,5,5,4,2,2,2,2,5,2,3,16,5.0,neutral or dissatisfied +5901,116909,Male,Loyal Customer,44,Business travel,Business,338,5,5,5,5,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +5902,58744,Male,Loyal Customer,50,Business travel,Business,1537,3,3,3,3,3,5,4,4,4,4,4,3,4,3,10,11.0,satisfied +5903,41174,Female,Loyal Customer,57,Business travel,Eco Plus,429,2,2,2,2,2,3,4,2,2,2,2,2,2,4,21,18.0,neutral or dissatisfied +5904,126222,Female,Loyal Customer,51,Business travel,Eco,650,4,3,3,3,1,4,4,4,4,4,4,1,4,2,0,4.0,neutral or dissatisfied +5905,3566,Female,disloyal Customer,26,Business travel,Eco,227,2,0,2,1,4,2,4,4,3,4,1,1,4,4,0,11.0,neutral or dissatisfied +5906,63167,Male,Loyal Customer,42,Business travel,Business,337,0,0,0,3,5,4,5,3,3,1,1,3,3,4,99,99.0,satisfied +5907,10319,Male,Loyal Customer,46,Business travel,Business,140,0,4,0,1,4,4,5,1,1,1,1,3,1,5,19,11.0,satisfied +5908,101081,Male,Loyal Customer,13,Personal Travel,Business,1069,3,4,3,3,4,3,4,4,3,3,5,3,5,4,30,37.0,neutral or dissatisfied +5909,41115,Female,Loyal Customer,62,Business travel,Business,224,4,4,4,4,5,3,4,5,5,5,5,2,5,1,68,55.0,satisfied +5910,124449,Female,disloyal Customer,38,Business travel,Business,980,2,2,2,5,3,2,3,3,5,5,5,4,5,3,22,18.0,neutral or dissatisfied +5911,49602,Male,Loyal Customer,51,Business travel,Business,308,1,1,1,1,5,2,2,4,4,4,4,2,4,2,0,0.0,satisfied +5912,66077,Male,Loyal Customer,27,Personal Travel,Eco,1055,2,5,1,3,1,1,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +5913,8549,Male,disloyal Customer,27,Business travel,Business,109,4,4,4,4,3,4,3,3,5,3,4,4,4,3,58,38.0,satisfied +5914,64222,Female,disloyal Customer,42,Business travel,Business,1660,3,3,3,5,1,3,1,1,4,5,4,5,4,1,0,9.0,neutral or dissatisfied +5915,8840,Male,Loyal Customer,55,Personal Travel,Eco Plus,522,2,5,2,5,4,2,4,4,2,2,1,1,4,4,0,0.0,neutral or dissatisfied +5916,78348,Male,Loyal Customer,53,Personal Travel,Eco,1547,3,4,3,4,4,3,4,4,1,2,4,4,3,4,0,0.0,neutral or dissatisfied +5917,101407,Female,Loyal Customer,16,Personal Travel,Eco,486,2,0,2,5,4,2,4,4,4,5,5,5,5,4,12,7.0,neutral or dissatisfied +5918,7346,Female,Loyal Customer,70,Personal Travel,Eco,606,4,3,4,2,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +5919,96080,Male,Loyal Customer,68,Personal Travel,Eco,795,1,5,0,3,3,0,3,3,5,2,5,3,5,3,15,20.0,neutral or dissatisfied +5920,47423,Male,Loyal Customer,68,Business travel,Business,1678,0,3,0,4,3,1,5,4,4,4,4,1,4,4,0,0.0,satisfied +5921,59361,Male,Loyal Customer,58,Business travel,Business,2615,2,4,2,2,1,2,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +5922,3561,Female,Loyal Customer,41,Business travel,Eco,227,1,3,3,3,1,1,1,4,4,3,4,1,2,1,132,133.0,neutral or dissatisfied +5923,50645,Female,Loyal Customer,45,Personal Travel,Eco,250,2,4,0,4,3,4,5,2,2,0,4,3,2,4,2,0.0,neutral or dissatisfied +5924,57560,Male,Loyal Customer,28,Business travel,Business,1597,1,1,1,1,4,4,4,4,4,4,5,4,5,4,94,80.0,satisfied +5925,64952,Male,Loyal Customer,44,Business travel,Business,224,3,3,3,3,2,4,4,5,5,4,5,5,5,5,0,2.0,satisfied +5926,83826,Male,Loyal Customer,44,Business travel,Eco,425,2,5,3,5,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +5927,91612,Male,disloyal Customer,27,Business travel,Business,1199,0,0,0,1,4,0,4,4,5,3,5,3,5,4,0,17.0,satisfied +5928,89836,Female,disloyal Customer,30,Business travel,Business,2039,1,1,1,1,2,1,2,2,4,4,3,4,4,2,14,8.0,neutral or dissatisfied +5929,82690,Male,Loyal Customer,29,Business travel,Business,2457,4,4,4,4,3,3,3,3,5,2,5,3,5,3,0,0.0,satisfied +5930,105740,Female,disloyal Customer,20,Business travel,Eco,925,3,3,3,2,5,3,5,5,2,1,3,2,3,5,32,15.0,neutral or dissatisfied +5931,7090,Male,disloyal Customer,20,Business travel,Eco,273,1,1,1,3,5,1,5,5,2,2,3,1,3,5,2,0.0,neutral or dissatisfied +5932,60654,Male,disloyal Customer,23,Business travel,Eco,1620,1,1,1,2,5,1,5,5,4,1,1,4,1,5,110,105.0,neutral or dissatisfied +5933,115761,Male,Loyal Customer,47,Business travel,Eco,325,1,4,4,4,1,1,1,1,1,2,3,2,3,1,1,0.0,neutral or dissatisfied +5934,75020,Female,disloyal Customer,37,Business travel,Business,236,1,1,1,1,1,1,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +5935,96222,Female,Loyal Customer,57,Business travel,Eco,546,3,3,3,3,1,2,3,3,3,3,3,2,3,2,8,0.0,neutral or dissatisfied +5936,30347,Female,Loyal Customer,28,Personal Travel,Eco Plus,391,2,5,2,4,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +5937,68316,Male,Loyal Customer,41,Business travel,Business,2165,2,5,2,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +5938,8186,Male,disloyal Customer,22,Business travel,Eco,335,4,2,3,3,3,3,3,3,2,1,3,4,2,3,0,0.0,neutral or dissatisfied +5939,23451,Female,Loyal Customer,54,Business travel,Eco,576,4,5,5,5,1,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +5940,110017,Male,disloyal Customer,25,Business travel,Eco,742,2,2,2,4,3,2,3,3,3,2,2,4,3,3,4,0.0,neutral or dissatisfied +5941,80781,Female,Loyal Customer,69,Personal Travel,Business,692,2,4,2,3,5,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +5942,37163,Male,Loyal Customer,62,Personal Travel,Eco,1046,1,5,1,3,3,1,1,3,5,3,5,4,5,3,14,9.0,neutral or dissatisfied +5943,70927,Female,disloyal Customer,20,Business travel,Eco,612,2,0,3,3,1,3,1,1,5,5,4,4,5,1,0,0.0,neutral or dissatisfied +5944,6723,Male,disloyal Customer,23,Business travel,Business,403,0,0,0,2,3,0,3,3,3,2,5,4,4,3,0,8.0,satisfied +5945,85798,Male,Loyal Customer,46,Business travel,Business,1792,4,4,4,4,1,3,1,5,5,5,5,2,5,3,6,0.0,satisfied +5946,73361,Male,Loyal Customer,39,Business travel,Business,3222,4,4,4,4,5,4,5,4,4,4,4,4,4,4,6,9.0,satisfied +5947,56810,Female,disloyal Customer,23,Business travel,Eco,1605,3,3,3,3,2,3,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +5948,85508,Male,Loyal Customer,43,Personal Travel,Eco,332,2,1,2,2,4,2,4,4,3,2,3,2,2,4,30,42.0,neutral or dissatisfied +5949,15508,Female,Loyal Customer,35,Personal Travel,Eco,164,1,5,1,1,3,1,4,3,5,3,5,5,5,3,3,0.0,neutral or dissatisfied +5950,119010,Female,Loyal Customer,27,Personal Travel,Eco,459,1,5,1,2,2,1,4,2,5,3,5,5,4,2,6,1.0,neutral or dissatisfied +5951,42563,Male,Loyal Customer,42,Business travel,Business,95,2,1,1,1,5,4,3,4,4,4,2,4,4,4,25,6.0,neutral or dissatisfied +5952,83119,Female,Loyal Customer,29,Personal Travel,Eco,957,1,1,1,3,3,1,3,3,2,5,4,3,4,3,0,0.0,neutral or dissatisfied +5953,13607,Female,Loyal Customer,52,Business travel,Eco Plus,106,2,5,5,5,1,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +5954,3711,Male,Loyal Customer,9,Personal Travel,Eco,427,1,0,1,1,4,1,4,4,4,5,1,5,1,4,0,,neutral or dissatisfied +5955,125919,Male,Loyal Customer,40,Personal Travel,Eco,992,3,4,3,1,3,3,3,3,4,3,4,3,4,3,59,41.0,neutral or dissatisfied +5956,127083,Male,Loyal Customer,54,Business travel,Eco,651,3,4,3,4,3,3,3,3,3,3,4,1,3,3,2,13.0,neutral or dissatisfied +5957,60491,Female,Loyal Customer,55,Business travel,Business,1974,4,4,3,4,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +5958,30435,Female,Loyal Customer,47,Personal Travel,Eco,483,2,5,2,3,1,3,5,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +5959,40694,Female,Loyal Customer,36,Business travel,Eco,599,4,3,3,3,4,4,4,4,4,1,2,1,1,4,0,0.0,satisfied +5960,56629,Male,Loyal Customer,35,Business travel,Eco,997,1,3,3,3,1,1,1,1,3,3,4,1,4,1,27,22.0,neutral or dissatisfied +5961,114467,Female,Loyal Customer,39,Business travel,Business,3398,2,1,4,1,4,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +5962,33079,Male,Loyal Customer,49,Personal Travel,Eco,163,4,4,4,4,3,4,5,3,5,5,4,3,5,3,0,0.0,satisfied +5963,81801,Female,disloyal Customer,25,Business travel,Eco,1310,3,3,3,3,1,3,1,1,1,4,3,2,3,1,10,0.0,neutral or dissatisfied +5964,80228,Female,Loyal Customer,49,Personal Travel,Eco,2153,2,4,2,3,3,5,5,2,2,2,3,4,2,3,2,0.0,neutral or dissatisfied +5965,75,Female,disloyal Customer,23,Business travel,Eco,108,2,5,1,2,2,1,2,2,4,2,4,5,2,2,0,0.0,neutral or dissatisfied +5966,87119,Male,Loyal Customer,62,Personal Travel,Eco,594,4,2,4,3,4,4,4,4,4,1,3,1,4,4,105,92.0,neutral or dissatisfied +5967,27725,Male,Loyal Customer,53,Business travel,Business,1448,4,4,4,4,1,5,4,3,3,3,3,5,3,3,2,0.0,satisfied +5968,101751,Female,Loyal Customer,48,Business travel,Business,1590,2,2,2,2,3,3,4,3,3,3,3,4,3,4,0,0.0,satisfied +5969,37936,Male,Loyal Customer,57,Personal Travel,Eco,1065,1,4,1,1,4,1,4,4,4,3,4,5,5,4,42,23.0,neutral or dissatisfied +5970,11698,Female,Loyal Customer,53,Business travel,Business,395,4,4,4,4,3,3,3,5,4,4,4,3,4,3,187,217.0,satisfied +5971,11061,Female,Loyal Customer,48,Personal Travel,Eco,312,4,2,4,3,2,4,4,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +5972,49969,Female,disloyal Customer,80,Business travel,Business,209,4,4,4,4,5,3,4,1,1,4,1,4,1,4,5,2.0,neutral or dissatisfied +5973,30036,Male,Loyal Customer,61,Business travel,Eco,148,4,1,1,1,4,4,4,4,1,3,1,4,3,4,0,4.0,satisfied +5974,74330,Female,disloyal Customer,41,Business travel,Business,1242,4,4,4,3,2,4,2,2,3,2,5,5,5,2,0,0.0,satisfied +5975,47412,Female,disloyal Customer,24,Business travel,Eco,588,3,1,2,3,5,2,3,5,4,3,2,3,3,5,0,0.0,neutral or dissatisfied +5976,53351,Male,disloyal Customer,46,Business travel,Eco,908,4,4,4,3,3,4,3,3,5,4,5,2,5,3,37,46.0,neutral or dissatisfied +5977,1926,Female,Loyal Customer,36,Business travel,Business,3166,0,0,0,5,2,5,4,1,1,1,1,3,1,3,0,7.0,satisfied +5978,91516,Female,Loyal Customer,66,Personal Travel,Eco,1626,3,4,3,3,2,3,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +5979,37610,Female,Loyal Customer,38,Personal Travel,Eco,1005,3,4,3,3,2,3,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +5980,67822,Male,Loyal Customer,40,Business travel,Eco,1438,3,2,2,2,3,3,3,3,4,1,4,3,3,3,17,48.0,neutral or dissatisfied +5981,83131,Male,Loyal Customer,41,Personal Travel,Eco,957,4,5,5,2,4,5,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +5982,75598,Female,Loyal Customer,30,Personal Travel,Eco,337,3,4,3,3,5,3,5,5,3,3,5,4,4,5,34,15.0,neutral or dissatisfied +5983,37040,Male,Loyal Customer,50,Business travel,Eco,994,3,2,3,3,3,3,3,3,1,1,4,3,4,3,13,7.0,neutral or dissatisfied +5984,32633,Female,Loyal Customer,32,Business travel,Eco,163,4,1,1,1,4,4,4,4,1,1,3,2,2,4,0,0.0,satisfied +5985,113281,Female,Loyal Customer,34,Business travel,Business,197,4,4,5,4,2,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +5986,62548,Male,Loyal Customer,41,Business travel,Business,1846,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +5987,105361,Female,Loyal Customer,52,Personal Travel,Eco Plus,452,2,5,2,3,4,1,1,5,5,2,5,2,5,5,4,0.0,neutral or dissatisfied +5988,83703,Male,Loyal Customer,70,Personal Travel,Eco,577,2,4,2,4,4,2,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +5989,11503,Female,Loyal Customer,24,Personal Travel,Eco Plus,166,3,5,3,3,1,3,1,1,3,3,5,5,5,1,5,4.0,neutral or dissatisfied +5990,5397,Male,Loyal Customer,37,Personal Travel,Eco,812,3,1,3,4,5,3,2,5,2,1,3,1,3,5,27,38.0,neutral or dissatisfied +5991,80532,Male,Loyal Customer,48,Business travel,Business,1678,2,2,1,1,2,2,2,2,2,2,2,1,2,1,88,85.0,neutral or dissatisfied +5992,8446,Female,Loyal Customer,69,Personal Travel,Eco Plus,590,3,4,3,2,5,4,5,3,3,3,1,3,3,4,0,0.0,neutral or dissatisfied +5993,46892,Male,Loyal Customer,36,Business travel,Eco,964,4,1,3,1,4,3,4,4,4,3,3,2,3,4,0,5.0,neutral or dissatisfied +5994,57744,Female,Loyal Customer,17,Personal Travel,Business,2611,4,5,4,1,4,1,1,4,3,5,5,1,3,1,0,0.0,neutral or dissatisfied +5995,127185,Male,disloyal Customer,58,Business travel,Business,370,4,4,4,3,5,4,5,5,5,2,5,5,4,5,4,6.0,neutral or dissatisfied +5996,44415,Male,Loyal Customer,66,Business travel,Eco Plus,323,4,4,4,4,5,4,5,5,2,5,4,2,3,5,0,6.0,satisfied +5997,21567,Female,Loyal Customer,61,Business travel,Eco Plus,399,2,4,5,4,3,3,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +5998,62282,Female,disloyal Customer,61,Business travel,Business,414,4,4,4,1,1,4,1,1,4,4,5,4,5,1,6,18.0,satisfied +5999,21284,Female,Loyal Customer,59,Business travel,Eco,692,5,2,3,3,1,5,1,4,4,5,4,3,4,5,0,0.0,satisfied +6000,32626,Male,Loyal Customer,67,Business travel,Eco,101,3,5,3,3,3,3,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +6001,32098,Female,Loyal Customer,26,Business travel,Business,163,5,5,4,5,5,5,3,5,2,3,5,3,5,5,0,0.0,satisfied +6002,119864,Female,Loyal Customer,28,Personal Travel,Eco,936,4,4,4,3,5,4,2,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +6003,68084,Female,Loyal Customer,27,Business travel,Business,1624,5,5,5,5,3,3,3,3,3,4,4,3,5,3,35,27.0,satisfied +6004,47293,Male,Loyal Customer,42,Business travel,Business,2590,5,5,5,5,1,1,4,3,3,4,3,2,3,3,0,0.0,satisfied +6005,1124,Male,Loyal Customer,23,Personal Travel,Eco,158,4,5,4,1,4,4,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +6006,37203,Male,Loyal Customer,62,Personal Travel,Eco Plus,1237,3,4,3,3,1,3,1,1,3,2,4,3,5,1,0,3.0,neutral or dissatisfied +6007,55543,Male,disloyal Customer,39,Business travel,Eco,550,2,4,2,3,2,2,2,2,4,5,3,4,4,2,75,57.0,neutral or dissatisfied +6008,75898,Female,Loyal Customer,40,Business travel,Business,3456,1,4,4,4,3,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +6009,90724,Female,Loyal Customer,40,Business travel,Business,404,5,5,5,5,2,4,5,3,3,3,3,3,3,3,9,0.0,satisfied +6010,61238,Female,Loyal Customer,37,Business travel,Eco,509,4,2,2,2,4,4,4,4,4,2,2,4,5,4,0,0.0,satisfied +6011,86550,Female,Loyal Customer,30,Business travel,Eco Plus,760,4,1,1,1,4,3,4,4,2,4,4,2,3,4,8,12.0,neutral or dissatisfied +6012,19865,Female,Loyal Customer,12,Personal Travel,Eco,693,4,5,4,2,2,4,2,2,3,2,4,4,4,2,18,65.0,neutral or dissatisfied +6013,48105,Male,Loyal Customer,55,Business travel,Business,259,3,3,4,3,2,3,5,5,5,5,5,1,5,2,0,0.0,satisfied +6014,85405,Female,Loyal Customer,45,Business travel,Business,2761,3,3,3,3,4,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +6015,78492,Male,Loyal Customer,43,Business travel,Eco,526,2,3,3,3,2,2,2,2,4,5,3,1,3,2,14,8.0,neutral or dissatisfied +6016,3857,Female,Loyal Customer,11,Personal Travel,Eco Plus,650,2,1,2,2,3,2,3,3,4,1,2,4,1,3,0,0.0,neutral or dissatisfied +6017,8042,Female,disloyal Customer,21,Business travel,Eco,335,4,4,4,3,5,4,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +6018,108669,Male,disloyal Customer,22,Business travel,Eco,484,3,1,3,4,3,2,2,4,3,4,3,2,2,2,243,224.0,neutral or dissatisfied +6019,73763,Female,Loyal Customer,38,Personal Travel,Eco,204,2,5,2,3,5,2,5,5,2,4,5,4,1,5,69,82.0,neutral or dissatisfied +6020,14954,Male,Loyal Customer,7,Personal Travel,Eco,528,3,5,3,1,1,3,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +6021,102964,Female,disloyal Customer,22,Business travel,Eco,546,4,0,4,5,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +6022,20049,Male,Loyal Customer,48,Business travel,Eco,738,2,1,1,1,2,2,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +6023,68571,Female,Loyal Customer,48,Business travel,Eco,1616,2,3,3,3,4,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +6024,20962,Male,Loyal Customer,40,Business travel,Eco,689,1,3,3,3,1,1,1,1,3,3,4,4,3,1,0,0.0,neutral or dissatisfied +6025,100383,Female,Loyal Customer,17,Personal Travel,Eco,1052,1,4,0,1,2,0,2,2,3,4,5,5,5,2,0,4.0,neutral or dissatisfied +6026,46616,Female,Loyal Customer,33,Business travel,Eco,125,5,3,3,3,5,4,5,5,3,4,4,3,4,5,25,16.0,neutral or dissatisfied +6027,4038,Female,disloyal Customer,16,Business travel,Eco,479,3,4,3,3,3,5,4,4,5,4,3,4,2,4,123,149.0,neutral or dissatisfied +6028,115027,Male,Loyal Customer,36,Business travel,Business,2989,1,1,1,1,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +6029,91433,Male,Loyal Customer,18,Personal Travel,Eco,549,3,0,3,3,5,3,5,5,3,4,5,1,5,5,0,2.0,neutral or dissatisfied +6030,73842,Female,Loyal Customer,54,Business travel,Business,1709,1,1,1,1,4,3,4,4,4,4,4,5,4,5,9,10.0,satisfied +6031,68668,Male,Loyal Customer,58,Business travel,Business,3897,2,3,3,3,4,4,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +6032,61363,Female,Loyal Customer,11,Personal Travel,Eco,2405,2,2,2,3,2,2,2,2,3,5,4,2,3,2,3,0.0,neutral or dissatisfied +6033,13988,Male,disloyal Customer,21,Business travel,Eco,541,2,0,2,1,4,2,4,4,5,5,4,2,4,4,0,0.0,neutral or dissatisfied +6034,78490,Female,disloyal Customer,8,Business travel,Eco,666,1,1,1,3,3,1,3,3,1,1,3,4,4,3,112,126.0,neutral or dissatisfied +6035,40667,Female,Loyal Customer,62,Business travel,Business,590,4,5,5,5,3,2,3,4,4,4,4,2,4,4,36,44.0,neutral or dissatisfied +6036,64024,Male,Loyal Customer,31,Business travel,Business,2393,3,3,3,3,5,5,5,5,5,3,5,3,4,5,0,0.0,satisfied +6037,29725,Female,Loyal Customer,66,Personal Travel,Eco,2777,3,3,4,3,4,1,2,4,3,3,4,2,1,2,52,68.0,neutral or dissatisfied +6038,38784,Male,disloyal Customer,25,Business travel,Business,354,4,0,4,2,5,4,5,5,4,1,3,4,1,5,0,0.0,satisfied +6039,91351,Female,Loyal Customer,58,Personal Travel,Eco Plus,545,4,3,4,1,4,3,5,1,1,4,1,4,1,1,0,40.0,neutral or dissatisfied +6040,28877,Female,Loyal Customer,48,Business travel,Business,956,4,4,4,4,1,2,3,5,5,5,5,4,5,4,7,0.0,satisfied +6041,104670,Male,Loyal Customer,8,Personal Travel,Eco,641,1,4,1,1,2,1,2,2,4,2,4,3,4,2,18,5.0,neutral or dissatisfied +6042,70488,Male,Loyal Customer,39,Business travel,Business,2647,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,5.0,satisfied +6043,104832,Male,Loyal Customer,43,Business travel,Business,426,5,5,5,5,5,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +6044,119329,Male,Loyal Customer,18,Personal Travel,Eco,214,3,3,3,3,2,3,2,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +6045,96899,Female,Loyal Customer,55,Personal Travel,Eco,488,2,4,4,3,1,2,4,3,3,4,3,1,3,4,0,0.0,neutral or dissatisfied +6046,123483,Male,disloyal Customer,29,Business travel,Eco,2296,2,2,2,3,3,2,4,3,2,4,4,2,4,3,0,2.0,neutral or dissatisfied +6047,69573,Female,disloyal Customer,29,Business travel,Eco,1132,3,3,3,5,5,3,5,5,1,1,4,2,1,5,2,0.0,neutral or dissatisfied +6048,4006,Male,disloyal Customer,58,Business travel,Business,425,4,4,4,5,2,4,2,2,3,5,4,4,4,2,0,13.0,satisfied +6049,101127,Male,disloyal Customer,21,Business travel,Eco,1235,5,5,5,1,4,5,4,4,4,3,4,3,5,4,0,0.0,satisfied +6050,70210,Female,Loyal Customer,54,Personal Travel,Eco,258,2,4,0,3,5,2,2,5,5,0,5,1,5,2,7,0.0,neutral or dissatisfied +6051,98127,Female,Loyal Customer,17,Personal Travel,Eco,472,1,3,1,1,1,1,1,1,2,2,1,4,2,1,0,0.0,neutral or dissatisfied +6052,28859,Female,disloyal Customer,22,Business travel,Eco,679,3,3,3,3,4,3,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +6053,61909,Female,Loyal Customer,53,Business travel,Business,2329,3,3,3,3,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +6054,105608,Male,disloyal Customer,26,Business travel,Business,519,2,2,2,2,3,2,3,3,3,3,5,4,4,3,29,23.0,neutral or dissatisfied +6055,46463,Female,Loyal Customer,54,Business travel,Business,141,4,3,4,4,5,5,4,5,5,5,4,3,5,3,0,0.0,satisfied +6056,56275,Male,Loyal Customer,32,Business travel,Business,2227,4,2,2,2,4,4,4,4,3,2,4,3,3,4,17,0.0,neutral or dissatisfied +6057,113906,Male,Loyal Customer,17,Personal Travel,Eco,2295,2,3,2,3,4,2,4,4,2,3,2,4,2,4,3,0.0,neutral or dissatisfied +6058,110627,Male,Loyal Customer,19,Personal Travel,Eco,719,3,4,3,3,1,3,1,1,1,5,2,2,1,1,0,0.0,neutral or dissatisfied +6059,64824,Male,Loyal Customer,44,Business travel,Business,247,1,1,4,1,1,3,4,1,1,1,1,3,1,3,19,20.0,neutral or dissatisfied +6060,10905,Male,disloyal Customer,22,Business travel,Eco,201,3,3,3,2,4,3,4,4,4,3,2,2,3,4,0,0.0,neutral or dissatisfied +6061,16402,Male,Loyal Customer,68,Personal Travel,Eco,533,1,5,1,3,4,1,4,4,3,4,5,4,5,4,7,5.0,neutral or dissatisfied +6062,12724,Male,disloyal Customer,34,Business travel,Eco,721,4,4,4,4,3,4,3,3,1,5,5,4,3,3,17,16.0,neutral or dissatisfied +6063,126703,Male,Loyal Customer,43,Business travel,Business,2402,2,2,2,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +6064,66784,Male,disloyal Customer,26,Business travel,Business,3711,3,3,3,2,3,3,3,1,2,1,3,3,4,3,0,43.0,neutral or dissatisfied +6065,34681,Female,Loyal Customer,48,Business travel,Business,2582,0,0,0,3,1,1,2,4,4,4,4,5,4,1,0,0.0,satisfied +6066,39029,Male,Loyal Customer,60,Personal Travel,Eco,406,4,4,4,4,1,4,1,1,5,3,5,4,4,1,0,0.0,satisfied +6067,79685,Male,Loyal Customer,45,Personal Travel,Eco,749,2,4,2,2,1,2,1,1,5,2,5,5,5,1,23,5.0,neutral or dissatisfied +6068,15877,Male,disloyal Customer,22,Business travel,Eco,332,1,4,1,2,5,1,5,5,4,1,1,5,4,5,0,0.0,neutral or dissatisfied +6069,65281,Female,Loyal Customer,68,Personal Travel,Eco Plus,469,3,4,3,5,3,4,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +6070,10913,Female,Loyal Customer,44,Business travel,Business,1768,4,2,2,2,4,4,4,2,2,2,4,2,2,1,0,0.0,neutral or dissatisfied +6071,2336,Male,Loyal Customer,51,Personal Travel,Eco,630,2,3,2,2,1,2,1,1,2,3,2,1,2,1,16,13.0,neutral or dissatisfied +6072,557,Female,Loyal Customer,31,Business travel,Business,3594,3,3,3,3,4,4,5,4,5,3,5,3,4,4,15,23.0,satisfied +6073,126985,Female,Loyal Customer,32,Business travel,Business,3785,1,4,4,4,1,1,1,1,2,3,3,3,4,1,0,0.0,neutral or dissatisfied +6074,106616,Male,Loyal Customer,29,Business travel,Business,1216,1,5,4,5,1,2,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +6075,76215,Male,Loyal Customer,43,Business travel,Business,1399,5,5,5,5,5,5,5,5,5,5,5,5,5,3,4,32.0,satisfied +6076,43444,Male,disloyal Customer,22,Business travel,Eco,524,3,0,3,4,5,3,5,5,2,5,3,3,5,5,8,10.0,neutral or dissatisfied +6077,64335,Male,Loyal Customer,31,Business travel,Business,3531,2,4,4,4,2,2,2,2,1,1,3,3,3,2,44,30.0,neutral or dissatisfied +6078,31918,Female,Loyal Customer,55,Business travel,Business,3329,4,4,4,4,3,4,5,4,4,4,5,4,4,3,2,0.0,satisfied +6079,93373,Female,Loyal Customer,47,Business travel,Business,2390,5,5,5,5,2,4,4,5,5,5,5,5,5,4,5,0.0,satisfied +6080,111375,Male,disloyal Customer,26,Business travel,Eco,1050,3,3,3,3,1,3,1,1,4,3,3,2,2,1,0,0.0,neutral or dissatisfied +6081,60191,Male,Loyal Customer,19,Personal Travel,Eco Plus,1012,3,1,3,4,2,3,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +6082,74365,Female,Loyal Customer,40,Business travel,Business,2060,1,1,1,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +6083,127339,Male,disloyal Customer,22,Business travel,Eco,507,2,1,2,2,4,2,4,4,3,5,3,4,2,4,7,5.0,neutral or dissatisfied +6084,57133,Male,Loyal Customer,20,Personal Travel,Eco,1222,3,3,3,3,4,3,4,4,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +6085,28385,Male,Loyal Customer,15,Personal Travel,Eco,763,1,4,1,2,5,1,5,5,2,5,4,2,3,5,0,3.0,neutral or dissatisfied +6086,61048,Female,Loyal Customer,38,Business travel,Business,1546,1,1,1,1,5,4,5,4,4,4,4,4,4,3,7,16.0,satisfied +6087,11496,Female,Loyal Customer,44,Personal Travel,Eco Plus,667,4,4,5,3,5,4,5,3,3,5,3,3,3,3,7,0.0,neutral or dissatisfied +6088,103791,Male,Loyal Customer,23,Business travel,Business,1516,5,5,3,5,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +6089,123211,Female,Loyal Customer,63,Personal Travel,Eco,600,1,1,1,3,1,3,2,3,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +6090,26243,Female,Loyal Customer,43,Personal Travel,Eco,270,1,3,0,4,3,3,3,2,2,0,1,3,2,4,0,0.0,neutral or dissatisfied +6091,85769,Male,Loyal Customer,58,Business travel,Business,666,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +6092,109390,Female,Loyal Customer,10,Personal Travel,Eco,1189,2,4,2,3,5,2,5,5,3,3,3,4,5,5,14,5.0,neutral or dissatisfied +6093,63448,Male,Loyal Customer,69,Personal Travel,Eco,337,1,4,1,4,4,1,4,4,2,4,3,2,4,4,8,17.0,neutral or dissatisfied +6094,3216,Male,disloyal Customer,48,Business travel,Business,1187,1,1,1,1,2,1,3,2,5,5,4,4,4,2,0,0.0,neutral or dissatisfied +6095,5829,Female,Loyal Customer,50,Personal Travel,Eco,177,3,1,3,4,3,4,4,1,1,3,1,1,1,4,18,33.0,neutral or dissatisfied +6096,128264,Female,Loyal Customer,46,Business travel,Business,3557,1,1,1,1,3,5,4,4,4,4,4,3,4,4,4,0.0,satisfied +6097,6579,Female,Loyal Customer,54,Business travel,Business,607,5,5,5,5,5,4,4,4,4,4,4,3,4,4,2,0.0,satisfied +6098,117990,Female,Loyal Customer,33,Business travel,Business,3845,0,0,0,1,2,5,5,1,1,1,1,5,1,3,27,38.0,satisfied +6099,14299,Female,Loyal Customer,42,Business travel,Business,3923,1,1,1,1,4,3,3,2,2,2,2,3,2,1,0,1.0,satisfied +6100,111704,Male,Loyal Customer,39,Business travel,Business,3311,5,5,5,5,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +6101,38311,Female,disloyal Customer,24,Business travel,Eco,1312,3,3,3,4,3,1,1,2,4,2,4,1,4,1,145,147.0,neutral or dissatisfied +6102,83226,Male,Loyal Customer,60,Business travel,Business,1956,1,1,1,1,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +6103,121700,Male,Loyal Customer,46,Business travel,Business,2883,2,2,2,2,5,5,5,5,5,5,5,5,5,4,7,29.0,satisfied +6104,101655,Female,Loyal Customer,33,Business travel,Eco Plus,1749,2,3,3,3,2,2,2,2,3,2,4,2,4,2,47,32.0,neutral or dissatisfied +6105,98923,Male,Loyal Customer,54,Business travel,Business,479,4,4,4,4,2,5,5,4,4,4,4,5,4,5,26,20.0,satisfied +6106,85407,Male,disloyal Customer,20,Business travel,Eco,152,4,0,4,5,2,4,2,2,4,5,4,3,5,2,0,0.0,satisfied +6107,112764,Female,Loyal Customer,59,Business travel,Business,3812,4,4,4,4,5,4,4,4,4,4,4,3,4,5,84,72.0,satisfied +6108,121295,Male,Loyal Customer,44,Business travel,Business,2067,3,3,3,3,5,4,4,2,2,2,2,5,2,5,0,6.0,satisfied +6109,14883,Male,Loyal Customer,51,Business travel,Business,2298,2,4,5,5,3,4,3,2,2,2,2,2,2,2,0,25.0,neutral or dissatisfied +6110,16490,Female,Loyal Customer,56,Business travel,Business,3207,1,2,2,2,1,1,1,2,2,4,4,1,1,1,162,165.0,neutral or dissatisfied +6111,103054,Male,Loyal Customer,30,Business travel,Business,546,4,4,4,4,4,4,4,4,1,5,3,3,4,4,0,0.0,neutral or dissatisfied +6112,81880,Female,Loyal Customer,58,Business travel,Business,1731,4,4,4,4,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +6113,75551,Male,Loyal Customer,29,Business travel,Business,3075,0,0,0,4,3,3,3,3,5,4,5,5,5,3,0,0.0,satisfied +6114,35295,Male,Loyal Customer,45,Business travel,Eco,1102,4,3,4,3,4,4,4,4,5,1,1,4,5,4,3,4.0,satisfied +6115,75549,Male,Loyal Customer,37,Business travel,Business,2244,1,1,2,1,4,4,5,4,4,4,4,3,4,4,1,5.0,satisfied +6116,80892,Female,Loyal Customer,46,Personal Travel,Eco Plus,692,1,5,0,4,5,5,4,1,1,0,1,5,1,5,0,0.0,neutral or dissatisfied +6117,96366,Male,disloyal Customer,24,Business travel,Eco,1246,1,1,1,3,4,1,4,4,4,4,5,4,5,4,81,74.0,neutral or dissatisfied +6118,106524,Male,Loyal Customer,64,Personal Travel,Eco,271,3,0,2,3,4,2,4,4,3,5,3,4,4,4,0,0.0,neutral or dissatisfied +6119,105636,Female,Loyal Customer,46,Business travel,Business,1661,4,4,3,4,3,5,5,5,5,4,5,3,5,4,26,0.0,satisfied +6120,53688,Female,Loyal Customer,37,Business travel,Business,1866,2,2,2,2,2,1,1,4,4,4,4,2,4,1,7,0.0,satisfied +6121,37325,Male,Loyal Customer,45,Business travel,Eco,944,4,2,2,2,4,4,4,4,1,3,3,5,5,4,0,10.0,satisfied +6122,72879,Female,Loyal Customer,44,Business travel,Business,1096,4,4,4,4,5,5,4,4,4,4,4,5,4,3,51,47.0,satisfied +6123,85076,Female,Loyal Customer,41,Business travel,Business,731,4,4,2,4,3,4,5,5,5,4,5,4,5,4,6,16.0,satisfied +6124,116086,Male,Loyal Customer,30,Personal Travel,Eco,372,3,4,3,4,1,3,1,1,1,5,2,1,3,1,0,0.0,neutral or dissatisfied +6125,80492,Male,Loyal Customer,51,Business travel,Business,1749,2,2,2,2,5,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +6126,46445,Male,Loyal Customer,53,Personal Travel,Eco,1304,1,5,1,1,4,1,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +6127,30880,Male,Loyal Customer,35,Personal Travel,Eco,1546,3,3,3,3,3,3,3,3,4,3,4,1,4,3,42,37.0,neutral or dissatisfied +6128,107315,Female,Loyal Customer,46,Personal Travel,Eco,307,4,3,4,3,5,3,5,1,1,4,1,2,1,2,0,0.0,neutral or dissatisfied +6129,103877,Male,Loyal Customer,40,Personal Travel,Eco,882,1,5,1,5,2,1,5,2,4,5,2,5,2,2,33,21.0,neutral or dissatisfied +6130,46829,Male,disloyal Customer,32,Business travel,Eco,848,2,1,1,2,1,1,1,1,5,2,1,5,4,1,0,0.0,neutral or dissatisfied +6131,31930,Male,Loyal Customer,55,Business travel,Business,3268,1,1,5,1,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +6132,11160,Male,Loyal Customer,53,Personal Travel,Eco,113,3,4,3,5,3,1,3,3,1,2,1,3,3,3,162,186.0,neutral or dissatisfied +6133,83716,Female,Loyal Customer,17,Business travel,Eco Plus,577,3,4,4,4,3,3,2,3,4,2,3,4,3,3,10,4.0,neutral or dissatisfied +6134,124265,Female,Loyal Customer,54,Business travel,Business,3871,3,4,4,4,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +6135,71089,Male,Loyal Customer,54,Personal Travel,Eco,802,2,4,2,1,4,2,4,4,5,3,1,1,4,4,4,12.0,neutral or dissatisfied +6136,47545,Female,disloyal Customer,21,Business travel,Eco,588,0,0,0,2,3,0,3,3,3,4,1,2,5,3,0,0.0,satisfied +6137,107737,Female,Loyal Customer,32,Personal Travel,Eco,251,2,2,2,3,5,2,5,5,2,4,4,1,4,5,27,29.0,neutral or dissatisfied +6138,46546,Female,Loyal Customer,53,Business travel,Business,2299,5,5,5,5,4,2,1,4,4,4,4,1,4,4,8,5.0,satisfied +6139,39679,Female,Loyal Customer,57,Personal Travel,Eco,612,1,4,0,1,4,5,5,2,2,0,2,3,2,3,0,1.0,neutral or dissatisfied +6140,54459,Male,Loyal Customer,27,Business travel,Business,925,2,2,2,2,5,5,5,5,4,3,3,5,2,5,0,0.0,satisfied +6141,114571,Female,Loyal Customer,14,Personal Travel,Business,373,3,1,0,3,2,0,5,2,3,1,4,2,3,2,0,0.0,neutral or dissatisfied +6142,12438,Male,Loyal Customer,9,Personal Travel,Eco,192,1,5,1,4,3,1,3,3,4,5,5,4,5,3,22,26.0,neutral or dissatisfied +6143,47091,Male,Loyal Customer,13,Personal Travel,Eco,639,4,3,3,2,2,3,2,2,2,4,2,2,3,2,60,55.0,neutral or dissatisfied +6144,68203,Male,Loyal Customer,70,Personal Travel,Business,631,1,2,1,3,4,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +6145,15636,Male,Loyal Customer,40,Business travel,Eco Plus,228,4,2,2,2,4,4,4,4,3,2,3,5,4,4,0,0.0,satisfied +6146,103006,Female,Loyal Customer,46,Business travel,Business,3030,1,1,1,1,5,4,4,5,5,5,5,4,5,4,20,8.0,satisfied +6147,57787,Female,Loyal Customer,53,Personal Travel,Eco,2611,2,5,2,4,2,3,3,2,4,3,3,3,2,3,7,0.0,neutral or dissatisfied +6148,88550,Female,Loyal Customer,58,Personal Travel,Eco,594,1,2,1,4,1,4,4,1,1,1,1,4,1,3,7,0.0,neutral or dissatisfied +6149,88944,Female,disloyal Customer,25,Business travel,Business,1199,3,4,3,3,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +6150,112396,Male,Loyal Customer,49,Business travel,Business,850,5,5,5,5,5,4,4,2,2,3,2,5,2,3,0,0.0,satisfied +6151,72767,Male,Loyal Customer,41,Business travel,Business,1045,3,3,3,3,4,5,5,5,5,5,5,4,5,3,61,65.0,satisfied +6152,31604,Female,Loyal Customer,46,Personal Travel,Eco,602,4,4,4,1,3,5,5,1,1,4,1,3,1,5,2,0.0,neutral or dissatisfied +6153,1622,Female,Loyal Customer,45,Business travel,Business,999,5,5,5,5,3,5,5,4,4,4,4,3,4,3,38,41.0,satisfied +6154,112739,Female,Loyal Customer,59,Business travel,Business,723,5,5,5,5,2,5,4,4,4,4,4,3,4,4,7,0.0,satisfied +6155,61128,Female,disloyal Customer,23,Business travel,Eco,967,4,4,4,3,3,4,3,3,4,5,4,4,5,3,2,0.0,satisfied +6156,106309,Female,Loyal Customer,41,Business travel,Business,998,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,3.0,satisfied +6157,23758,Male,Loyal Customer,17,Personal Travel,Eco,1048,1,4,1,3,5,1,2,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +6158,5197,Female,disloyal Customer,36,Business travel,Business,383,3,3,3,1,5,3,5,5,3,5,5,3,5,5,14,34.0,neutral or dissatisfied +6159,94285,Male,Loyal Customer,38,Business travel,Business,239,0,0,0,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +6160,67046,Male,Loyal Customer,44,Business travel,Business,3249,5,5,4,5,5,4,4,4,4,5,4,3,4,5,2,0.0,satisfied +6161,125857,Male,Loyal Customer,48,Business travel,Eco,1013,2,5,5,5,2,2,2,2,1,2,3,4,4,2,30,57.0,neutral or dissatisfied +6162,7216,Male,Loyal Customer,41,Business travel,Business,130,3,4,4,4,5,4,3,2,2,1,3,3,2,2,0,0.0,neutral or dissatisfied +6163,70234,Female,Loyal Customer,43,Business travel,Business,1068,1,1,1,1,3,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +6164,97022,Male,Loyal Customer,48,Business travel,Business,1645,2,2,2,2,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6165,50476,Male,disloyal Customer,28,Business travel,Eco,156,4,1,4,2,1,4,1,1,5,5,1,1,2,1,1,0.0,satisfied +6166,88084,Female,Loyal Customer,54,Business travel,Business,3743,2,2,2,2,2,4,4,3,3,4,3,5,3,4,0,1.0,satisfied +6167,49719,Male,Loyal Customer,39,Business travel,Business,3031,1,0,0,3,3,2,3,4,4,0,1,4,4,4,18,62.0,neutral or dissatisfied +6168,80046,Female,Loyal Customer,63,Personal Travel,Eco,1035,4,4,4,3,5,4,4,3,3,4,4,3,3,3,0,7.0,neutral or dissatisfied +6169,109666,Male,Loyal Customer,46,Business travel,Eco,973,3,2,2,2,3,3,3,3,3,4,4,4,4,3,83,73.0,neutral or dissatisfied +6170,121127,Female,Loyal Customer,43,Business travel,Business,2521,2,2,2,2,4,4,4,3,2,4,5,4,3,4,11,25.0,satisfied +6171,129514,Male,Loyal Customer,23,Personal Travel,Eco,1744,4,1,4,3,4,4,4,4,2,2,2,4,2,4,0,9.0,neutral or dissatisfied +6172,38511,Male,Loyal Customer,45,Business travel,Business,2521,4,4,4,4,5,4,2,4,4,5,4,3,4,3,118,98.0,satisfied +6173,39351,Male,Loyal Customer,13,Personal Travel,Business,896,2,4,2,3,2,5,5,3,3,5,4,5,5,5,197,182.0,neutral or dissatisfied +6174,18613,Male,Loyal Customer,38,Personal Travel,Eco,190,2,5,2,5,1,2,1,1,4,1,3,1,1,1,0,1.0,neutral or dissatisfied +6175,44437,Male,disloyal Customer,43,Business travel,Eco,588,4,0,4,3,4,4,4,4,1,4,5,2,1,4,0,0.0,neutral or dissatisfied +6176,47790,Female,Loyal Customer,43,Business travel,Business,2512,2,4,4,4,4,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +6177,31697,Male,disloyal Customer,35,Business travel,Eco,862,2,2,2,2,1,2,1,1,2,3,1,1,2,1,0,0.0,neutral or dissatisfied +6178,36779,Female,Loyal Customer,39,Business travel,Business,2588,1,5,5,5,1,1,1,2,1,4,3,1,2,1,0,0.0,neutral or dissatisfied +6179,102244,Male,Loyal Customer,51,Business travel,Business,223,5,5,5,5,4,4,4,5,5,4,4,4,5,5,8,4.0,satisfied +6180,116221,Female,Loyal Customer,52,Personal Travel,Eco,325,1,5,1,4,2,3,2,2,2,1,2,1,2,2,63,56.0,neutral or dissatisfied +6181,112539,Female,Loyal Customer,22,Personal Travel,Eco,853,2,5,2,4,4,2,4,4,3,5,4,3,4,4,1,7.0,neutral or dissatisfied +6182,42087,Male,Loyal Customer,35,Personal Travel,Eco,344,3,1,3,2,5,3,5,5,1,1,2,1,1,5,0,0.0,neutral or dissatisfied +6183,15224,Female,Loyal Customer,27,Business travel,Business,3153,2,2,2,2,5,5,5,5,4,1,2,5,5,5,99,77.0,satisfied +6184,14341,Female,Loyal Customer,25,Personal Travel,Eco,395,4,4,4,2,2,4,2,2,3,2,2,4,5,2,0,0.0,neutral or dissatisfied +6185,118679,Female,Loyal Customer,56,Business travel,Business,368,2,5,5,5,5,3,3,2,2,2,2,2,2,2,35,36.0,neutral or dissatisfied +6186,22212,Female,Loyal Customer,33,Personal Travel,Eco,565,2,5,2,2,4,2,4,4,3,4,4,4,5,4,49,45.0,neutral or dissatisfied +6187,125386,Male,disloyal Customer,21,Business travel,Eco,1440,5,4,4,1,3,5,3,3,5,3,4,5,4,3,0,0.0,satisfied +6188,127661,Male,disloyal Customer,24,Business travel,Business,776,4,0,4,3,1,4,1,1,5,4,4,3,5,1,0,0.0,satisfied +6189,111077,Female,Loyal Customer,68,Personal Travel,Eco,197,1,3,1,3,1,2,2,4,4,1,2,3,4,4,10,0.0,neutral or dissatisfied +6190,59763,Female,disloyal Customer,25,Business travel,Business,895,4,0,4,2,1,4,3,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +6191,70724,Female,Loyal Customer,23,Business travel,Business,2895,2,4,5,5,2,2,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +6192,55336,Male,Loyal Customer,31,Personal Travel,Eco,1117,2,3,2,3,1,2,1,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +6193,14547,Male,Loyal Customer,43,Personal Travel,Eco,362,2,5,5,3,2,5,4,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +6194,85443,Male,Loyal Customer,39,Business travel,Business,1845,4,2,4,4,5,4,4,5,5,4,4,5,5,5,0,0.0,satisfied +6195,76601,Female,disloyal Customer,50,Business travel,Eco,547,3,2,3,2,4,3,4,4,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +6196,78671,Female,Loyal Customer,47,Business travel,Business,3681,2,2,2,2,4,5,4,5,5,5,5,3,5,4,0,11.0,satisfied +6197,81740,Male,disloyal Customer,27,Business travel,Business,1501,4,4,4,3,2,4,2,2,5,4,4,3,4,2,0,0.0,satisfied +6198,90353,Female,Loyal Customer,54,Business travel,Business,3933,1,1,4,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +6199,11688,Female,Loyal Customer,28,Business travel,Business,429,3,3,2,3,5,5,5,5,4,2,5,5,5,5,2,0.0,satisfied +6200,123247,Female,Loyal Customer,36,Personal Travel,Eco,468,1,4,1,3,5,1,1,5,1,1,4,3,4,5,0,0.0,neutral or dissatisfied +6201,109571,Female,Loyal Customer,36,Personal Travel,Eco,951,2,4,2,4,2,1,5,1,2,5,5,5,4,5,222,223.0,neutral or dissatisfied +6202,72652,Female,Loyal Customer,8,Personal Travel,Eco,985,3,5,3,4,1,3,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +6203,29744,Female,disloyal Customer,64,Business travel,Business,261,3,4,4,4,2,3,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +6204,66814,Female,Loyal Customer,29,Business travel,Business,731,2,2,2,2,4,4,4,4,5,3,5,4,5,4,0,0.0,satisfied +6205,17027,Male,Loyal Customer,24,Personal Travel,Eco,781,3,5,3,3,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +6206,51120,Female,Loyal Customer,18,Personal Travel,Eco,326,3,1,3,3,2,3,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +6207,59764,Female,disloyal Customer,23,Business travel,Eco,927,3,3,3,3,1,3,1,1,5,5,5,5,4,1,22,8.0,neutral or dissatisfied +6208,14743,Male,Loyal Customer,49,Business travel,Business,2024,1,1,1,1,3,4,1,5,5,5,5,1,5,2,5,0.0,satisfied +6209,107497,Male,Loyal Customer,28,Business travel,Business,3832,4,4,4,4,4,4,4,4,4,4,3,2,3,4,60,40.0,neutral or dissatisfied +6210,44542,Female,Loyal Customer,15,Personal Travel,Eco,157,3,4,0,3,4,0,4,4,2,2,4,3,4,4,0,0.0,neutral or dissatisfied +6211,77528,Female,Loyal Customer,9,Business travel,Business,2890,3,3,5,3,4,4,4,4,3,5,5,3,4,4,0,3.0,satisfied +6212,24676,Female,disloyal Customer,26,Business travel,Eco,761,3,3,3,3,5,3,1,5,3,1,3,1,3,5,50,69.0,neutral or dissatisfied +6213,97795,Male,Loyal Customer,28,Personal Travel,Eco,471,2,5,2,4,2,2,2,2,5,2,4,4,4,2,21,28.0,neutral or dissatisfied +6214,22786,Male,Loyal Customer,40,Business travel,Business,147,5,5,5,5,1,4,2,4,4,4,5,3,4,3,4,0.0,satisfied +6215,81290,Female,Loyal Customer,33,Personal Travel,Eco,1020,2,5,2,1,2,2,2,2,4,5,3,5,3,2,1,0.0,neutral or dissatisfied +6216,6123,Male,disloyal Customer,39,Business travel,Business,491,4,4,4,4,2,4,2,2,4,2,5,4,4,2,0,0.0,satisfied +6217,32413,Female,disloyal Customer,22,Business travel,Eco,101,3,3,3,1,5,3,2,5,3,5,5,3,1,5,0,8.0,neutral or dissatisfied +6218,23745,Female,disloyal Customer,19,Business travel,Eco,1048,5,5,5,1,4,5,4,4,3,1,4,2,5,4,0,0.0,satisfied +6219,58166,Female,Loyal Customer,46,Business travel,Business,1642,1,1,1,1,5,5,4,4,4,4,4,4,4,5,96,86.0,satisfied +6220,111689,Male,Loyal Customer,43,Business travel,Business,1863,3,3,3,3,3,4,4,5,5,4,5,3,5,3,51,42.0,satisfied +6221,62146,Female,Loyal Customer,47,Business travel,Business,2454,3,3,3,3,5,5,4,5,5,5,5,5,5,5,4,0.0,satisfied +6222,85254,Female,Loyal Customer,35,Personal Travel,Eco,874,2,2,2,4,4,2,4,4,4,4,4,1,3,4,0,0.0,neutral or dissatisfied +6223,80053,Male,Loyal Customer,12,Personal Travel,Eco,950,2,0,2,3,2,2,2,2,1,5,5,3,1,2,0,0.0,neutral or dissatisfied +6224,53245,Male,Loyal Customer,54,Business travel,Eco Plus,612,5,3,3,3,5,5,5,5,2,1,5,1,5,5,0,4.0,satisfied +6225,15040,Female,Loyal Customer,24,Business travel,Business,488,4,4,4,4,2,2,2,5,3,1,1,2,2,2,161,163.0,satisfied +6226,48661,Male,Loyal Customer,40,Business travel,Business,1683,0,4,0,4,2,4,5,5,5,5,5,3,5,5,0,9.0,satisfied +6227,106229,Female,Loyal Customer,15,Personal Travel,Eco,471,2,3,2,3,1,2,1,1,4,3,3,2,3,1,78,71.0,neutral or dissatisfied +6228,122308,Male,Loyal Customer,70,Personal Travel,Eco,541,3,5,3,3,2,3,1,2,2,2,5,2,5,2,0,0.0,neutral or dissatisfied +6229,27669,Male,disloyal Customer,25,Business travel,Eco,1107,5,5,5,5,5,5,5,5,2,1,3,2,3,5,3,0.0,satisfied +6230,112103,Male,Loyal Customer,16,Personal Travel,Eco,1062,4,4,4,3,2,4,2,2,4,5,4,5,4,2,1,0.0,satisfied +6231,38249,Male,disloyal Customer,25,Business travel,Business,1173,4,4,4,3,4,4,4,4,4,5,3,1,3,4,5,0.0,neutral or dissatisfied +6232,93340,Male,Loyal Customer,24,Business travel,Business,3328,5,5,5,5,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +6233,112355,Male,Loyal Customer,46,Business travel,Business,2102,5,5,5,5,5,5,4,5,5,5,5,4,5,4,64,47.0,satisfied +6234,113094,Male,disloyal Customer,20,Business travel,Eco,479,3,0,3,2,3,3,3,3,4,3,2,1,1,3,48,29.0,neutral or dissatisfied +6235,53487,Male,Loyal Customer,59,Business travel,Eco,919,1,2,3,2,1,1,1,1,2,3,4,3,3,1,65,59.0,neutral or dissatisfied +6236,122879,Male,Loyal Customer,24,Personal Travel,Eco,226,1,5,0,2,1,0,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +6237,128978,Male,Loyal Customer,49,Personal Travel,Eco,414,2,5,2,2,1,2,1,1,5,2,3,1,2,1,0,0.0,neutral or dissatisfied +6238,32105,Female,Loyal Customer,56,Business travel,Business,163,0,3,0,3,2,5,2,5,5,5,5,4,5,5,0,0.0,satisfied +6239,100848,Female,Loyal Customer,49,Personal Travel,Eco,711,4,5,4,4,2,5,4,4,4,4,2,1,4,1,52,36.0,neutral or dissatisfied +6240,37926,Female,Loyal Customer,60,Personal Travel,Eco,1068,3,4,3,2,3,4,5,3,3,3,3,4,3,5,16,0.0,neutral or dissatisfied +6241,127481,Male,Loyal Customer,48,Business travel,Eco,2075,2,4,4,4,2,2,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +6242,62410,Female,disloyal Customer,49,Business travel,Business,2704,3,2,2,4,5,3,5,5,3,4,5,5,5,5,5,0.0,neutral or dissatisfied +6243,20225,Female,Loyal Customer,36,Business travel,Eco,228,5,4,4,4,5,5,5,5,5,4,1,1,1,5,16,0.0,satisfied +6244,4787,Male,Loyal Customer,15,Personal Travel,Eco,403,0,4,0,1,5,0,5,5,3,3,4,5,4,5,0,0.0,satisfied +6245,45818,Male,Loyal Customer,41,Personal Travel,Eco,411,4,5,4,3,1,4,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +6246,109930,Male,Loyal Customer,62,Personal Travel,Eco,1092,2,1,2,4,3,2,3,3,2,2,4,2,4,3,20,22.0,neutral or dissatisfied +6247,21128,Male,Loyal Customer,28,Personal Travel,Eco,227,3,5,0,3,2,0,1,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +6248,68805,Male,Loyal Customer,51,Personal Travel,Eco,861,3,2,4,4,3,4,3,3,4,4,4,1,3,3,0,12.0,neutral or dissatisfied +6249,75704,Female,Loyal Customer,45,Business travel,Business,868,4,4,4,4,5,5,5,4,4,4,4,5,4,3,1,3.0,satisfied +6250,122678,Male,Loyal Customer,66,Business travel,Business,361,2,2,2,2,2,3,4,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +6251,10288,Male,Loyal Customer,55,Business travel,Business,2910,1,1,1,1,4,5,5,4,4,4,4,5,4,4,0,1.0,satisfied +6252,17259,Female,Loyal Customer,38,Personal Travel,Eco,872,2,1,2,4,1,2,5,1,2,1,4,1,3,1,52,40.0,neutral or dissatisfied +6253,116643,Female,disloyal Customer,22,Business travel,Business,373,5,0,5,3,5,5,5,5,3,5,5,3,5,5,0,0.0,satisfied +6254,4479,Male,disloyal Customer,23,Business travel,Business,1147,5,0,5,1,2,5,2,2,5,2,5,4,4,2,0,0.0,satisfied +6255,73764,Male,Loyal Customer,68,Personal Travel,Eco,192,4,1,4,4,4,4,4,4,3,4,4,4,4,4,0,1.0,neutral or dissatisfied +6256,103245,Female,Loyal Customer,47,Business travel,Eco Plus,409,3,3,3,3,5,3,1,3,3,3,3,1,3,5,15,5.0,satisfied +6257,32744,Female,disloyal Customer,27,Business travel,Eco,216,3,2,3,3,2,3,2,2,1,2,4,4,3,2,0,0.0,neutral or dissatisfied +6258,37545,Female,disloyal Customer,23,Business travel,Eco,1076,2,2,2,4,5,2,5,5,2,2,3,3,4,5,0,0.0,neutral or dissatisfied +6259,112163,Male,Loyal Customer,34,Business travel,Business,895,5,5,5,5,4,4,2,4,4,4,4,4,4,1,10,2.0,satisfied +6260,127418,Male,Loyal Customer,11,Personal Travel,Eco,868,2,3,3,1,5,3,5,5,3,1,5,5,5,5,5,16.0,neutral or dissatisfied +6261,94047,Male,disloyal Customer,39,Business travel,Business,233,5,5,5,1,4,5,4,4,4,2,4,4,5,4,0,0.0,satisfied +6262,41000,Male,Loyal Customer,31,Business travel,Business,1201,3,3,3,3,4,4,4,4,2,4,1,3,5,4,0,9.0,satisfied +6263,2552,Male,Loyal Customer,53,Business travel,Business,2118,1,4,4,4,1,3,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +6264,91650,Female,Loyal Customer,65,Personal Travel,Eco,1312,4,4,4,2,4,4,4,5,5,4,5,3,5,4,58,51.0,neutral or dissatisfied +6265,96094,Female,Loyal Customer,46,Personal Travel,Eco,583,3,5,3,1,3,5,5,4,4,3,4,5,4,4,31,27.0,neutral or dissatisfied +6266,50966,Male,Loyal Customer,47,Personal Travel,Eco,308,4,5,4,3,3,4,3,3,3,3,4,3,4,3,0,0.0,satisfied +6267,7433,Female,Loyal Customer,12,Personal Travel,Eco,552,2,5,2,3,3,2,3,3,5,4,5,3,5,3,0,7.0,neutral or dissatisfied +6268,122887,Male,disloyal Customer,49,Business travel,Business,226,5,5,5,3,4,5,4,4,5,5,4,4,4,4,5,0.0,satisfied +6269,125863,Female,disloyal Customer,21,Business travel,Eco,992,2,2,2,3,1,2,1,1,3,4,5,3,5,1,0,0.0,neutral or dissatisfied +6270,111852,Female,disloyal Customer,26,Business travel,Eco,628,3,3,3,4,2,3,2,2,2,2,3,1,3,2,5,19.0,neutral or dissatisfied +6271,51101,Male,Loyal Customer,16,Personal Travel,Eco,308,3,4,3,3,2,3,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +6272,101621,Male,Loyal Customer,13,Personal Travel,Eco,1139,3,4,3,1,3,3,3,3,3,3,4,4,4,3,8,0.0,neutral or dissatisfied +6273,70615,Male,Loyal Customer,49,Business travel,Business,3249,5,5,5,5,2,4,4,4,4,4,4,4,4,4,0,4.0,satisfied +6274,41915,Female,Loyal Customer,52,Business travel,Business,1637,4,4,4,4,3,3,2,5,5,5,5,5,5,3,0,4.0,satisfied +6275,3577,Male,Loyal Customer,58,Business travel,Business,227,0,0,0,1,3,5,5,3,3,4,4,5,3,3,0,5.0,satisfied +6276,104457,Male,Loyal Customer,34,Business travel,Business,1123,5,5,5,5,5,4,5,4,4,4,4,5,4,5,28,5.0,satisfied +6277,91008,Male,Loyal Customer,50,Personal Travel,Eco,581,4,2,4,2,5,4,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +6278,11846,Female,Loyal Customer,42,Business travel,Business,912,2,2,3,2,3,4,5,3,3,2,3,4,3,4,15,17.0,satisfied +6279,10097,Male,Loyal Customer,35,Business travel,Business,3151,3,3,3,3,3,3,3,2,4,4,3,3,1,3,384,401.0,neutral or dissatisfied +6280,14972,Female,Loyal Customer,31,Business travel,Eco,927,4,5,2,5,4,4,4,4,3,1,2,3,5,4,0,0.0,satisfied +6281,23827,Male,Loyal Customer,21,Personal Travel,Eco Plus,304,3,3,3,1,1,3,1,1,2,1,5,2,5,1,1,0.0,neutral or dissatisfied +6282,45897,Female,Loyal Customer,45,Business travel,Eco,563,4,1,1,1,1,2,5,5,5,4,5,1,5,2,10,0.0,satisfied +6283,121077,Male,disloyal Customer,38,Business travel,Eco Plus,613,1,1,1,2,1,1,1,1,2,3,5,2,3,1,0,0.0,neutral or dissatisfied +6284,64171,Male,Loyal Customer,70,Personal Travel,Eco,989,2,5,2,3,4,2,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +6285,78088,Female,Loyal Customer,17,Personal Travel,Eco Plus,152,3,5,3,4,5,3,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +6286,100754,Female,Loyal Customer,22,Personal Travel,Eco,328,4,5,3,1,2,3,2,2,4,2,3,2,2,2,0,0.0,neutral or dissatisfied +6287,54942,Female,Loyal Customer,59,Business travel,Business,3707,2,2,2,2,5,3,4,2,2,2,2,3,2,2,6,3.0,neutral or dissatisfied +6288,39633,Male,Loyal Customer,20,Business travel,Eco Plus,620,5,1,3,1,5,5,5,5,1,4,3,3,2,5,0,0.0,satisfied +6289,45848,Male,Loyal Customer,70,Personal Travel,Eco,216,1,3,1,3,5,1,5,5,4,2,4,4,3,5,0,22.0,neutral or dissatisfied +6290,98295,Male,Loyal Customer,14,Personal Travel,Eco,1136,2,1,2,4,4,2,4,4,3,1,2,4,4,4,1,2.0,neutral or dissatisfied +6291,15562,Male,Loyal Customer,55,Business travel,Business,1846,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +6292,17776,Male,disloyal Customer,23,Business travel,Business,1075,5,0,5,5,5,5,3,5,3,4,2,3,4,5,0,0.0,satisfied +6293,42854,Female,Loyal Customer,49,Personal Travel,Eco,328,1,1,3,2,2,4,5,3,3,3,3,5,3,5,9,16.0,neutral or dissatisfied +6294,552,Female,Loyal Customer,60,Business travel,Business,89,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +6295,4831,Female,Loyal Customer,51,Business travel,Business,2544,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +6296,117958,Male,Loyal Customer,46,Business travel,Business,365,2,3,3,3,5,3,4,2,2,2,2,4,2,2,40,31.0,neutral or dissatisfied +6297,114655,Female,Loyal Customer,53,Business travel,Business,480,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +6298,35242,Female,disloyal Customer,19,Business travel,Eco,1028,3,3,3,2,4,3,4,4,4,4,2,2,1,4,0,0.0,neutral or dissatisfied +6299,25513,Female,disloyal Customer,30,Business travel,Eco,516,2,5,3,4,1,3,1,1,3,5,3,1,2,1,6,1.0,neutral or dissatisfied +6300,75992,Female,Loyal Customer,51,Personal Travel,Eco,297,2,4,2,4,4,4,5,5,5,2,5,3,5,5,0,1.0,neutral or dissatisfied +6301,103805,Male,Loyal Customer,27,Business travel,Business,1242,5,5,5,5,4,4,4,4,5,3,5,3,5,4,27,22.0,satisfied +6302,92753,Female,Loyal Customer,9,Personal Travel,Eco,1276,0,2,0,3,3,0,3,3,1,1,2,3,3,3,0,0.0,satisfied +6303,46939,Male,Loyal Customer,60,Personal Travel,Eco,846,3,4,3,4,1,3,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +6304,20235,Male,Loyal Customer,50,Business travel,Eco,228,4,1,3,1,4,4,4,4,2,1,4,5,2,4,0,0.0,satisfied +6305,63156,Female,Loyal Customer,58,Business travel,Business,447,1,1,1,1,5,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +6306,57230,Female,Loyal Customer,60,Personal Travel,Eco,1514,1,4,1,3,4,5,5,5,5,1,5,5,5,4,0,0.0,neutral or dissatisfied +6307,101238,Male,disloyal Customer,46,Business travel,Business,1587,1,0,0,3,2,1,4,2,3,2,4,4,5,2,87,92.0,neutral or dissatisfied +6308,80210,Female,Loyal Customer,60,Personal Travel,Eco Plus,2475,1,1,1,3,1,5,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +6309,103611,Female,Loyal Customer,31,Personal Travel,Business,405,1,5,1,4,1,1,1,1,3,2,5,4,4,1,5,0.0,neutral or dissatisfied +6310,105208,Female,disloyal Customer,27,Business travel,Business,1040,4,4,4,1,4,4,4,4,5,3,5,4,5,4,1,0.0,satisfied +6311,74224,Female,Loyal Customer,49,Personal Travel,Eco,1746,2,0,2,3,5,5,5,2,2,2,2,4,2,5,0,3.0,neutral or dissatisfied +6312,23005,Female,Loyal Customer,48,Personal Travel,Eco,641,3,4,3,4,4,5,5,2,2,3,1,5,2,3,0,0.0,neutral or dissatisfied +6313,10653,Male,disloyal Customer,25,Business travel,Business,201,3,0,3,4,2,3,2,2,5,2,4,4,5,2,7,2.0,neutral or dissatisfied +6314,123363,Male,Loyal Customer,45,Business travel,Business,2659,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +6315,89908,Female,Loyal Customer,39,Business travel,Eco,1501,2,5,5,5,2,2,2,2,2,3,3,1,4,2,3,8.0,neutral or dissatisfied +6316,20776,Female,disloyal Customer,22,Business travel,Eco,457,4,4,4,4,3,4,3,3,2,4,4,4,5,3,0,0.0,satisfied +6317,14887,Female,disloyal Customer,34,Business travel,Eco,315,2,1,2,3,5,2,5,5,1,1,3,1,3,5,0,0.0,neutral or dissatisfied +6318,91495,Male,disloyal Customer,46,Business travel,Business,391,2,1,1,5,3,2,2,3,5,3,4,3,4,3,62,96.0,neutral or dissatisfied +6319,24703,Male,Loyal Customer,51,Business travel,Business,1963,5,5,5,5,3,3,2,4,4,4,4,2,4,5,8,8.0,satisfied +6320,3570,Female,Loyal Customer,26,Personal Travel,Eco,227,5,5,5,2,1,5,1,1,3,2,5,4,5,1,0,0.0,satisfied +6321,114375,Female,Loyal Customer,37,Business travel,Eco Plus,548,4,4,4,4,4,4,4,4,1,1,4,3,3,4,0,0.0,neutral or dissatisfied +6322,103513,Male,Loyal Customer,19,Personal Travel,Eco,1256,4,5,4,3,1,4,1,1,4,5,3,4,5,1,0,3.0,neutral or dissatisfied +6323,7943,Female,Loyal Customer,48,Business travel,Business,3791,3,1,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +6324,104022,Female,disloyal Customer,48,Business travel,Business,1262,2,2,2,4,3,2,3,3,3,3,4,4,5,3,7,27.0,neutral or dissatisfied +6325,578,Male,Loyal Customer,37,Business travel,Business,309,4,4,4,4,4,5,5,4,4,4,4,3,4,3,40,35.0,satisfied +6326,43334,Male,Loyal Customer,49,Business travel,Business,358,2,2,2,2,4,4,2,4,4,4,4,1,4,5,6,0.0,satisfied +6327,32617,Male,disloyal Customer,25,Business travel,Business,216,2,2,2,4,4,2,3,4,2,1,3,3,3,4,3,11.0,neutral or dissatisfied +6328,61272,Female,Loyal Customer,26,Personal Travel,Eco,967,2,4,2,4,2,2,2,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +6329,62773,Female,Loyal Customer,8,Business travel,Business,2486,1,2,3,2,1,1,1,4,4,4,4,1,2,1,0,12.0,neutral or dissatisfied +6330,117845,Female,Loyal Customer,27,Business travel,Business,2133,5,5,5,5,5,5,5,5,3,3,3,3,5,5,12,4.0,satisfied +6331,88226,Female,Loyal Customer,42,Business travel,Business,3135,0,0,0,4,5,5,5,4,4,4,4,5,4,4,31,21.0,satisfied +6332,50979,Male,Loyal Customer,64,Personal Travel,Eco,266,2,0,2,5,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +6333,73714,Male,Loyal Customer,46,Business travel,Business,204,1,1,4,1,1,1,3,4,4,4,3,1,4,1,0,0.0,satisfied +6334,26974,Male,Loyal Customer,42,Business travel,Business,954,2,2,2,2,4,2,1,4,4,4,4,4,4,1,0,0.0,satisfied +6335,21114,Female,Loyal Customer,59,Personal Travel,Eco,152,1,4,1,1,5,4,5,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +6336,98081,Male,Loyal Customer,26,Business travel,Business,845,2,2,2,2,5,5,5,5,3,2,5,5,4,5,0,0.0,satisfied +6337,83130,Male,Loyal Customer,11,Personal Travel,Eco,1127,4,5,4,1,5,4,5,5,3,5,4,4,4,5,42,57.0,neutral or dissatisfied +6338,129290,Female,Loyal Customer,41,Business travel,Eco,150,5,1,1,1,5,5,5,5,2,2,4,4,5,5,0,0.0,satisfied +6339,124426,Female,Loyal Customer,34,Personal Travel,Eco,1262,3,4,3,2,1,3,2,1,3,4,4,5,4,1,0,0.0,neutral or dissatisfied +6340,51707,Male,disloyal Customer,16,Business travel,Eco,751,2,2,2,4,1,2,1,1,1,3,4,1,3,1,126,120.0,neutral or dissatisfied +6341,111384,Female,disloyal Customer,29,Business travel,Eco,1050,1,1,1,3,1,1,5,1,1,1,3,2,3,1,35,28.0,neutral or dissatisfied +6342,5558,Male,Loyal Customer,59,Business travel,Business,588,5,5,5,5,3,5,4,4,4,4,4,3,4,3,33,83.0,satisfied +6343,43309,Female,Loyal Customer,61,Business travel,Business,347,1,5,5,5,5,3,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +6344,75094,Female,Loyal Customer,35,Business travel,Business,1744,4,4,4,4,3,3,5,4,4,4,4,4,4,5,0,0.0,satisfied +6345,121708,Male,Loyal Customer,53,Business travel,Business,2719,1,1,1,1,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +6346,38573,Female,Loyal Customer,10,Personal Travel,Eco,2569,1,5,1,5,5,1,5,5,3,1,1,1,4,5,0,0.0,neutral or dissatisfied +6347,19656,Female,Loyal Customer,67,Personal Travel,Eco,763,1,2,1,4,3,4,3,2,2,1,2,4,2,1,15,3.0,neutral or dissatisfied +6348,10388,Female,Loyal Customer,49,Business travel,Business,3822,4,4,4,4,3,5,5,5,5,5,5,5,5,4,0,11.0,satisfied +6349,86607,Male,Loyal Customer,40,Business travel,Business,2330,1,1,1,1,3,4,4,5,5,5,5,3,5,3,3,3.0,satisfied +6350,30460,Female,Loyal Customer,60,Personal Travel,Eco,991,3,4,3,3,5,4,4,2,2,3,2,3,2,3,78,68.0,neutral or dissatisfied +6351,85260,Female,Loyal Customer,8,Personal Travel,Eco,696,3,4,3,1,1,3,1,1,5,4,4,5,4,1,17,15.0,neutral or dissatisfied +6352,82861,Male,disloyal Customer,23,Business travel,Eco,594,4,0,4,4,4,1,1,5,3,5,5,1,5,1,167,159.0,satisfied +6353,102836,Male,Loyal Customer,58,Business travel,Business,423,5,5,3,5,2,4,5,5,5,5,5,4,5,3,57,48.0,satisfied +6354,8983,Female,Loyal Customer,56,Personal Travel,Eco,725,1,2,1,3,3,4,4,5,5,1,4,3,5,4,0,0.0,neutral or dissatisfied +6355,99509,Male,Loyal Customer,53,Personal Travel,Eco,283,4,4,4,1,5,4,5,5,3,2,4,3,4,5,0,6.0,neutral or dissatisfied +6356,81631,Male,disloyal Customer,35,Business travel,Business,907,2,2,2,2,2,2,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +6357,124258,Female,Loyal Customer,55,Business travel,Eco Plus,1916,2,5,2,2,5,3,4,2,2,2,2,3,2,3,1,0.0,neutral or dissatisfied +6358,64547,Female,Loyal Customer,40,Business travel,Business,3953,1,1,3,1,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6359,13854,Female,Loyal Customer,31,Personal Travel,Eco,583,2,4,2,2,5,2,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +6360,58716,Female,Loyal Customer,59,Personal Travel,Eco,606,2,2,3,3,5,3,2,1,1,3,1,1,1,2,76,59.0,neutral or dissatisfied +6361,3716,Female,Loyal Customer,24,Personal Travel,Eco,431,5,4,5,1,1,5,1,1,5,4,4,4,4,1,0,0.0,satisfied +6362,47234,Female,Loyal Customer,68,Personal Travel,Eco Plus,965,1,4,1,1,5,5,4,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +6363,74685,Female,Loyal Customer,8,Personal Travel,Eco,1464,1,4,1,3,2,1,2,2,3,3,5,5,5,2,0,5.0,neutral or dissatisfied +6364,99660,Female,Loyal Customer,22,Business travel,Eco,650,4,4,4,4,4,4,4,4,5,5,2,1,5,4,0,0.0,satisfied +6365,53506,Male,Loyal Customer,8,Personal Travel,Eco,2419,4,4,4,4,4,5,5,3,4,4,5,5,5,5,26,24.0,neutral or dissatisfied +6366,63398,Male,Loyal Customer,33,Personal Travel,Eco,337,1,3,1,1,2,1,2,2,2,4,1,1,2,2,0,0.0,neutral or dissatisfied +6367,104015,Male,Loyal Customer,22,Business travel,Business,1363,4,4,4,4,3,3,3,3,4,3,4,3,4,3,0,0.0,satisfied +6368,97784,Female,Loyal Customer,43,Business travel,Business,1917,4,4,5,4,2,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +6369,118598,Female,Loyal Customer,48,Business travel,Business,3266,2,2,2,2,3,4,5,4,4,4,4,5,4,5,2,3.0,satisfied +6370,124185,Male,Loyal Customer,38,Personal Travel,Eco Plus,2089,3,4,4,4,5,4,5,5,1,2,3,4,4,5,2,0.0,neutral or dissatisfied +6371,66172,Male,Loyal Customer,52,Business travel,Business,550,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +6372,52536,Female,Loyal Customer,54,Business travel,Business,110,3,3,3,3,5,4,4,5,5,5,4,4,5,4,0,0.0,satisfied +6373,93672,Female,disloyal Customer,23,Business travel,Eco,542,2,5,2,4,4,2,4,4,4,5,4,5,2,4,1,0.0,neutral or dissatisfied +6374,97338,Male,Loyal Customer,64,Business travel,Business,843,3,5,5,5,4,3,2,3,3,3,3,2,3,2,68,61.0,neutral or dissatisfied +6375,102857,Female,disloyal Customer,69,Business travel,Business,423,4,4,4,3,1,4,1,1,4,5,4,4,5,1,36,28.0,neutral or dissatisfied +6376,40778,Male,Loyal Customer,54,Business travel,Business,3437,3,2,2,2,5,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +6377,98377,Male,Loyal Customer,50,Business travel,Business,1046,3,3,3,3,4,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +6378,95815,Female,disloyal Customer,37,Business travel,Business,1428,2,2,2,3,1,2,1,1,4,4,4,5,4,1,85,,neutral or dissatisfied +6379,64443,Female,Loyal Customer,40,Business travel,Business,3276,5,1,5,5,2,4,4,4,4,4,4,3,4,3,2,0.0,satisfied +6380,19410,Female,Loyal Customer,15,Personal Travel,Business,645,3,5,4,2,4,4,4,4,1,2,5,2,4,4,0,0.0,neutral or dissatisfied +6381,25329,Female,Loyal Customer,41,Business travel,Eco,829,4,1,1,1,4,4,4,4,3,3,5,5,3,4,0,0.0,satisfied +6382,28912,Female,Loyal Customer,43,Business travel,Business,2877,5,5,5,5,5,5,2,4,4,4,4,4,4,5,0,0.0,satisfied +6383,58455,Female,Loyal Customer,53,Personal Travel,Eco,733,1,2,1,3,4,4,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +6384,71782,Female,Loyal Customer,54,Business travel,Business,1723,4,4,4,4,4,4,5,5,5,4,5,4,5,4,18,10.0,satisfied +6385,39729,Male,disloyal Customer,38,Business travel,Eco,320,3,4,3,3,5,3,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +6386,31410,Female,disloyal Customer,22,Business travel,Eco,1306,4,4,4,1,5,4,5,5,4,4,1,3,4,5,0,13.0,satisfied +6387,20930,Female,Loyal Customer,23,Business travel,Business,721,2,2,2,2,5,5,5,5,5,4,3,4,2,5,0,0.0,satisfied +6388,108085,Male,Loyal Customer,47,Business travel,Business,2430,5,5,5,5,2,5,4,3,3,3,3,5,3,5,22,11.0,satisfied +6389,56921,Male,Loyal Customer,59,Business travel,Business,2565,2,2,2,2,4,4,4,3,4,4,5,4,4,4,9,0.0,satisfied +6390,114231,Male,Loyal Customer,35,Business travel,Business,909,2,3,3,3,1,2,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +6391,116868,Male,Loyal Customer,60,Business travel,Business,647,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +6392,125182,Male,Loyal Customer,61,Business travel,Business,651,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,5.0,satisfied +6393,43023,Female,Loyal Customer,71,Business travel,Eco,192,1,0,0,2,3,2,1,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +6394,21184,Female,Loyal Customer,27,Business travel,Business,2134,4,4,4,4,5,5,5,5,5,2,5,4,2,5,51,40.0,satisfied +6395,81931,Female,Loyal Customer,16,Personal Travel,Business,1532,2,5,2,2,2,2,3,2,3,5,5,4,5,2,10,0.0,neutral or dissatisfied +6396,83714,Female,disloyal Customer,23,Business travel,Eco,577,0,0,1,4,2,1,5,2,5,3,5,3,5,2,0,0.0,satisfied +6397,116971,Female,Loyal Customer,60,Business travel,Business,338,2,2,2,2,4,4,5,5,5,5,5,5,5,4,35,28.0,satisfied +6398,49094,Male,Loyal Customer,30,Business travel,Business,1862,2,2,5,2,4,4,5,4,4,5,5,1,5,4,0,0.0,satisfied +6399,129801,Female,Loyal Customer,62,Personal Travel,Eco,447,2,4,2,3,5,5,5,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +6400,48638,Male,Loyal Customer,60,Business travel,Business,3128,5,5,5,5,4,5,5,5,5,5,5,4,5,4,19,30.0,satisfied +6401,78268,Male,Loyal Customer,49,Personal Travel,Eco,903,3,1,3,4,5,3,5,5,1,1,3,3,3,5,0,0.0,neutral or dissatisfied +6402,120054,Female,disloyal Customer,26,Business travel,Business,237,3,5,3,3,1,3,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +6403,83256,Male,disloyal Customer,11,Business travel,Eco,731,2,2,2,3,2,2,3,2,3,4,2,4,3,2,49,49.0,neutral or dissatisfied +6404,44683,Male,Loyal Customer,45,Business travel,Business,67,3,5,5,5,3,4,4,3,3,3,3,1,3,1,53,56.0,neutral or dissatisfied +6405,13554,Female,disloyal Customer,29,Business travel,Eco,106,2,0,2,2,5,2,5,5,3,4,1,3,4,5,0,0.0,neutral or dissatisfied +6406,67120,Female,Loyal Customer,52,Business travel,Eco,985,4,4,4,4,4,4,4,3,5,4,3,4,1,4,294,280.0,neutral or dissatisfied +6407,120870,Female,Loyal Customer,46,Business travel,Business,1013,2,2,3,2,5,5,5,4,4,4,5,5,5,5,76,181.0,satisfied +6408,27730,Female,Loyal Customer,47,Business travel,Eco,1448,5,1,3,1,2,2,5,5,5,5,5,2,5,2,0,0.0,satisfied +6409,93637,Female,Loyal Customer,43,Personal Travel,Eco,704,2,4,2,3,2,5,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +6410,91343,Female,Loyal Customer,10,Personal Travel,Eco Plus,515,4,2,4,3,4,4,4,4,4,3,4,4,3,4,11,0.0,neutral or dissatisfied +6411,95106,Female,Loyal Customer,66,Personal Travel,Eco,496,1,2,1,4,1,5,2,3,4,4,4,2,3,2,148,138.0,neutral or dissatisfied +6412,11878,Female,Loyal Customer,47,Personal Travel,Eco,1042,3,5,3,4,4,4,4,2,2,3,2,5,2,3,20,17.0,neutral or dissatisfied +6413,68934,Female,Loyal Customer,56,Business travel,Business,646,2,3,3,3,1,4,4,2,2,2,2,2,2,1,0,8.0,neutral or dissatisfied +6414,43875,Female,Loyal Customer,31,Business travel,Business,199,3,3,3,3,5,5,5,5,1,2,5,1,4,5,0,0.0,satisfied +6415,78271,Male,disloyal Customer,11,Business travel,Eco,903,1,0,0,4,1,0,1,1,3,3,4,3,4,1,1,0.0,neutral or dissatisfied +6416,78112,Female,Loyal Customer,8,Business travel,Business,1619,2,2,2,2,4,4,4,4,4,5,4,5,4,4,0,4.0,satisfied +6417,120255,Male,Loyal Customer,63,Personal Travel,Eco Plus,1303,2,5,2,1,3,2,3,3,5,3,5,4,4,3,52,35.0,neutral or dissatisfied +6418,106950,Male,Loyal Customer,59,Business travel,Business,937,1,1,5,1,3,5,5,4,4,4,4,3,4,5,6,0.0,satisfied +6419,42376,Female,Loyal Customer,44,Personal Travel,Eco,550,1,2,1,4,4,3,3,4,4,1,4,3,4,2,51,,neutral or dissatisfied +6420,81778,Male,Loyal Customer,37,Business travel,Business,1780,1,1,1,1,3,4,4,3,3,4,3,4,3,4,10,14.0,satisfied +6421,35272,Female,Loyal Customer,36,Business travel,Business,3862,5,5,3,5,5,1,2,5,5,5,5,4,5,2,0,0.0,satisfied +6422,122022,Female,Loyal Customer,24,Business travel,Business,130,0,5,0,3,1,1,1,1,3,2,4,4,5,1,32,25.0,satisfied +6423,108265,Male,Loyal Customer,49,Business travel,Eco,495,4,3,3,3,4,4,4,4,1,3,2,4,5,4,10,0.0,satisfied +6424,79482,Female,Loyal Customer,52,Business travel,Business,760,2,3,3,3,1,4,4,2,2,2,2,1,2,2,0,19.0,neutral or dissatisfied +6425,120138,Female,Loyal Customer,36,Business travel,Business,1475,4,4,4,4,4,4,5,5,5,5,5,3,5,5,23,12.0,satisfied +6426,59396,Female,Loyal Customer,66,Personal Travel,Eco,2556,1,1,1,3,1,4,3,4,4,1,1,2,4,1,65,56.0,neutral or dissatisfied +6427,40780,Male,Loyal Customer,27,Business travel,Eco,590,0,1,1,1,5,1,5,5,3,1,3,5,3,5,0,0.0,satisfied +6428,108806,Female,Loyal Customer,9,Personal Travel,Eco,406,2,4,2,3,1,2,1,1,1,2,3,2,4,1,2,0.0,neutral or dissatisfied +6429,68693,Female,Loyal Customer,38,Personal Travel,Eco,237,3,4,3,5,5,3,5,5,5,5,5,5,5,5,38,47.0,neutral or dissatisfied +6430,45836,Female,Loyal Customer,17,Personal Travel,Eco,411,4,4,4,1,1,4,1,1,2,3,2,3,4,1,0,0.0,satisfied +6431,120195,Female,disloyal Customer,25,Business travel,Business,1325,4,0,4,2,2,4,2,2,4,5,5,5,4,2,5,0.0,satisfied +6432,127592,Female,Loyal Customer,36,Business travel,Business,1773,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +6433,96098,Male,Loyal Customer,18,Personal Travel,Eco,795,2,4,2,3,1,2,1,1,5,2,4,4,4,1,0,2.0,neutral or dissatisfied +6434,64190,Male,Loyal Customer,46,Business travel,Business,453,2,1,1,1,3,4,3,2,2,2,2,3,2,3,16,12.0,neutral or dissatisfied +6435,109654,Female,Loyal Customer,32,Business travel,Eco,829,3,2,2,2,3,3,3,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +6436,118712,Male,Loyal Customer,20,Personal Travel,Eco,369,3,5,3,1,3,3,3,3,3,3,2,4,4,3,0,0.0,neutral or dissatisfied +6437,80025,Female,Loyal Customer,47,Personal Travel,Eco,1076,2,5,2,1,5,5,4,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +6438,21951,Female,disloyal Customer,27,Business travel,Eco,500,3,3,3,3,5,3,5,5,4,3,3,1,4,5,0,13.0,neutral or dissatisfied +6439,103568,Female,Loyal Customer,23,Business travel,Business,3656,3,3,3,3,4,4,4,4,3,4,5,3,4,4,14,0.0,satisfied +6440,3019,Female,Loyal Customer,56,Business travel,Business,3639,3,4,4,4,4,3,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +6441,116013,Female,Loyal Customer,45,Personal Travel,Eco,337,3,1,3,2,4,2,2,4,4,3,4,1,4,1,4,0.0,neutral or dissatisfied +6442,24389,Male,Loyal Customer,63,Personal Travel,Eco,669,4,4,4,2,2,4,2,2,4,3,5,5,4,2,2,5.0,satisfied +6443,29864,Female,disloyal Customer,23,Business travel,Eco,213,3,4,4,2,5,4,5,5,2,5,4,4,3,5,0,0.0,neutral or dissatisfied +6444,48682,Female,disloyal Customer,22,Business travel,Eco,56,1,5,1,3,5,1,5,5,3,5,5,4,4,5,0,16.0,neutral or dissatisfied +6445,109268,Male,Loyal Customer,55,Personal Travel,Eco Plus,616,3,5,3,4,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +6446,47690,Female,Loyal Customer,62,Personal Travel,Eco,715,4,2,4,4,3,4,4,1,1,4,1,2,1,4,0,6.0,neutral or dissatisfied +6447,50748,Male,Loyal Customer,26,Personal Travel,Eco,156,4,5,4,3,5,4,2,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +6448,94402,Female,Loyal Customer,62,Business travel,Business,2793,0,0,0,4,3,4,4,4,4,4,4,4,4,3,2,0.0,satisfied +6449,115908,Male,Loyal Customer,48,Business travel,Eco,296,4,3,3,3,4,4,4,4,5,1,2,3,5,4,0,0.0,satisfied +6450,104498,Male,Loyal Customer,49,Business travel,Business,1609,2,2,2,2,2,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +6451,33968,Female,disloyal Customer,24,Business travel,Eco,1244,3,3,3,1,3,3,3,3,4,1,5,3,5,3,0,0.0,neutral or dissatisfied +6452,90868,Female,disloyal Customer,38,Business travel,Business,406,5,5,5,3,3,5,3,3,5,4,5,4,5,3,0,0.0,satisfied +6453,46374,Male,Loyal Customer,45,Business travel,Eco,1081,4,1,1,1,4,4,4,4,3,4,2,5,5,4,0,0.0,satisfied +6454,25275,Male,Loyal Customer,36,Personal Travel,Eco,425,4,3,4,4,3,4,2,3,1,2,3,2,4,3,5,4.0,neutral or dissatisfied +6455,125369,Female,Loyal Customer,54,Personal Travel,Eco,599,2,2,2,2,4,3,2,4,4,2,2,3,4,2,0,0.0,neutral or dissatisfied +6456,36871,Female,Loyal Customer,13,Personal Travel,Eco,273,3,2,3,3,2,3,4,2,2,4,4,3,3,2,0,0.0,neutral or dissatisfied +6457,103316,Female,Loyal Customer,56,Business travel,Business,1371,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,1.0,satisfied +6458,95860,Male,Loyal Customer,34,Business travel,Business,580,4,4,4,4,4,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +6459,20744,Male,Loyal Customer,33,Business travel,Business,363,1,1,1,1,5,5,5,5,2,2,3,3,5,5,0,0.0,satisfied +6460,101526,Male,Loyal Customer,19,Personal Travel,Eco,345,4,3,4,4,4,4,4,4,4,2,1,4,3,4,4,0.0,neutral or dissatisfied +6461,80041,Male,disloyal Customer,65,Personal Travel,Eco,1076,2,4,2,1,4,2,4,4,3,3,4,4,4,4,8,19.0,neutral or dissatisfied +6462,32922,Male,Loyal Customer,36,Personal Travel,Eco,163,3,1,3,3,1,3,1,1,4,4,2,4,3,1,0,0.0,neutral or dissatisfied +6463,35054,Male,Loyal Customer,21,Business travel,Business,3699,4,4,4,4,4,4,4,3,2,4,4,4,5,4,170,158.0,satisfied +6464,89992,Female,Loyal Customer,44,Business travel,Business,1084,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,4.0,satisfied +6465,10563,Male,Loyal Customer,47,Business travel,Business,74,2,2,2,2,2,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +6466,92411,Female,Loyal Customer,33,Business travel,Business,1919,3,5,5,5,1,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +6467,8601,Female,Loyal Customer,33,Business travel,Business,109,3,3,3,3,2,5,5,4,4,4,5,3,4,5,5,2.0,satisfied +6468,18874,Female,Loyal Customer,26,Business travel,Business,500,4,4,4,4,4,4,4,4,1,5,3,2,1,4,0,0.0,satisfied +6469,111767,Female,Loyal Customer,43,Business travel,Business,1620,1,2,2,2,2,1,2,1,1,2,1,1,1,4,39,19.0,neutral or dissatisfied +6470,34189,Male,Loyal Customer,68,Personal Travel,Eco,1046,2,1,2,4,5,2,5,5,2,4,4,2,4,5,3,0.0,neutral or dissatisfied +6471,114690,Female,disloyal Customer,23,Business travel,Eco,447,3,4,3,3,1,3,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +6472,19931,Male,Loyal Customer,43,Personal Travel,Eco,240,3,5,0,3,1,0,1,1,4,4,4,4,4,1,31,28.0,neutral or dissatisfied +6473,36925,Male,Loyal Customer,41,Business travel,Business,3522,1,1,1,1,1,5,2,4,4,4,4,3,4,1,0,0.0,satisfied +6474,26407,Male,Loyal Customer,44,Business travel,Eco Plus,957,5,2,2,2,5,5,5,5,1,3,2,2,3,5,3,0.0,satisfied +6475,117338,Male,disloyal Customer,23,Business travel,Eco,296,1,0,2,2,2,2,2,2,4,2,4,3,5,2,0,0.0,neutral or dissatisfied +6476,49402,Male,Loyal Customer,42,Business travel,Business,3985,3,3,5,3,1,2,4,5,5,5,4,3,5,2,12,8.0,satisfied +6477,83393,Male,Loyal Customer,48,Business travel,Business,1697,3,3,3,3,2,5,4,4,4,5,4,5,4,3,6,0.0,satisfied +6478,51387,Female,Loyal Customer,48,Personal Travel,Eco Plus,262,5,4,0,4,1,4,5,4,4,0,2,5,4,1,0,0.0,satisfied +6479,83965,Male,Loyal Customer,55,Business travel,Business,2145,1,1,3,1,2,5,5,1,1,2,1,3,1,3,1,15.0,satisfied +6480,88752,Male,Loyal Customer,11,Personal Travel,Eco,366,2,5,3,2,1,3,1,1,1,2,2,2,2,1,0,0.0,neutral or dissatisfied +6481,56453,Female,Loyal Customer,63,Personal Travel,Eco,719,1,4,1,2,4,4,5,5,5,1,4,4,5,5,0,0.0,neutral or dissatisfied +6482,102553,Female,Loyal Customer,68,Personal Travel,Eco,223,2,5,2,2,2,5,5,5,5,2,5,5,5,3,18,7.0,neutral or dissatisfied +6483,116818,Male,Loyal Customer,49,Business travel,Business,646,4,2,4,4,3,4,5,4,4,4,4,4,4,4,4,0.0,satisfied +6484,7851,Male,Loyal Customer,40,Business travel,Eco,1005,2,3,3,3,2,2,2,2,2,2,4,1,3,2,10,10.0,neutral or dissatisfied +6485,93813,Male,Loyal Customer,48,Business travel,Business,391,4,4,4,4,4,5,4,5,5,5,5,5,5,4,3,0.0,satisfied +6486,109217,Male,Loyal Customer,30,Business travel,Eco,616,5,1,1,1,5,5,5,5,3,5,2,2,4,5,0,0.0,satisfied +6487,68685,Male,disloyal Customer,36,Business travel,Eco,237,3,0,3,2,1,3,1,1,4,2,1,2,1,1,0,0.0,neutral or dissatisfied +6488,56987,Female,Loyal Customer,37,Personal Travel,Eco,2565,2,2,2,4,2,4,3,3,3,2,4,3,3,3,0,3.0,neutral or dissatisfied +6489,111318,Male,Loyal Customer,33,Business travel,Business,283,4,1,1,1,4,4,4,4,1,1,3,4,4,4,19,35.0,neutral or dissatisfied +6490,113507,Male,Loyal Customer,75,Business travel,Business,2576,4,5,5,5,4,2,3,4,4,4,4,4,4,3,5,4.0,neutral or dissatisfied +6491,54616,Male,disloyal Customer,42,Business travel,Eco,854,1,1,1,2,4,1,4,4,1,1,4,1,5,4,0,0.0,neutral or dissatisfied +6492,99140,Female,Loyal Customer,55,Business travel,Business,1565,4,4,1,4,2,5,4,4,4,5,4,3,4,3,3,0.0,satisfied +6493,112427,Female,Loyal Customer,51,Business travel,Business,957,2,2,2,2,4,5,4,4,4,4,4,4,4,5,50,39.0,satisfied +6494,9599,Female,Loyal Customer,23,Personal Travel,Eco,229,3,5,3,2,1,3,1,1,5,5,4,5,4,1,3,0.0,neutral or dissatisfied +6495,37418,Female,Loyal Customer,40,Business travel,Eco,1035,1,5,5,5,1,1,1,1,4,4,4,2,3,1,0,0.0,neutral or dissatisfied +6496,18906,Male,Loyal Customer,30,Personal Travel,Eco,503,4,3,4,3,3,4,3,3,4,1,3,4,2,3,0,0.0,neutral or dissatisfied +6497,70278,Male,Loyal Customer,45,Business travel,Business,852,3,3,3,3,5,5,5,4,4,4,4,5,4,3,0,3.0,satisfied +6498,88172,Male,disloyal Customer,20,Business travel,Eco,270,1,0,0,4,5,0,5,5,4,2,5,4,5,5,0,0.0,neutral or dissatisfied +6499,16728,Female,Loyal Customer,58,Business travel,Eco,1167,4,4,4,4,4,4,4,5,4,2,3,4,4,4,244,261.0,satisfied +6500,112681,Female,Loyal Customer,52,Business travel,Business,723,5,5,5,5,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +6501,2067,Male,Loyal Customer,56,Business travel,Business,1593,4,5,4,4,4,4,5,3,3,4,3,3,3,3,17,3.0,satisfied +6502,127982,Male,Loyal Customer,60,Business travel,Business,2329,5,5,5,5,5,5,2,5,5,5,5,1,5,4,0,17.0,satisfied +6503,120763,Female,disloyal Customer,20,Business travel,Eco,678,3,3,3,5,4,3,5,4,4,4,5,5,5,4,0,0.0,neutral or dissatisfied +6504,60074,Male,Loyal Customer,25,Business travel,Business,1012,4,4,4,4,3,3,3,3,3,4,5,5,4,3,4,0.0,satisfied +6505,101783,Female,Loyal Customer,31,Business travel,Business,1521,1,1,1,1,5,5,5,5,5,5,5,4,5,5,52,43.0,satisfied +6506,34893,Male,Loyal Customer,40,Personal Travel,Business,187,1,5,1,3,4,5,5,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +6507,71404,Female,Loyal Customer,40,Business travel,Business,1533,4,4,4,4,2,5,4,4,4,4,4,4,4,3,50,46.0,satisfied +6508,129267,Female,Loyal Customer,59,Business travel,Eco,2521,2,2,4,4,5,2,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +6509,57424,Female,disloyal Customer,20,Business travel,Business,533,4,5,3,5,4,3,4,4,3,2,5,5,5,4,21,8.0,satisfied +6510,14079,Male,disloyal Customer,27,Business travel,Eco,371,1,0,1,2,3,1,3,3,1,2,1,5,4,3,0,0.0,neutral or dissatisfied +6511,94557,Female,Loyal Customer,42,Business travel,Business,2726,1,1,5,1,2,4,4,5,5,5,5,3,5,5,3,0.0,satisfied +6512,5857,Male,Loyal Customer,31,Personal Travel,Eco,1020,4,0,4,4,4,4,4,4,3,5,2,2,4,4,0,0.0,satisfied +6513,78678,Female,Loyal Customer,32,Business travel,Business,2805,4,4,4,4,5,4,5,5,4,4,4,3,5,5,0,0.0,satisfied +6514,87402,Female,Loyal Customer,50,Personal Travel,Eco,425,2,0,4,4,5,5,5,5,5,4,5,2,5,5,48,33.0,neutral or dissatisfied +6515,45638,Male,Loyal Customer,16,Personal Travel,Eco,230,2,4,0,3,4,0,4,4,5,3,5,5,5,4,2,0.0,neutral or dissatisfied +6516,102121,Female,disloyal Customer,20,Business travel,Business,236,0,0,0,3,1,0,1,1,4,3,4,4,5,1,6,0.0,satisfied +6517,45282,Female,Loyal Customer,36,Business travel,Eco,188,4,4,4,4,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +6518,4958,Male,disloyal Customer,26,Business travel,Business,931,0,0,0,3,2,0,2,2,3,2,4,4,5,2,0,0.0,satisfied +6519,128585,Male,Loyal Customer,47,Business travel,Business,2552,4,4,4,4,5,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +6520,16904,Female,Loyal Customer,20,Personal Travel,Eco,746,2,4,1,4,4,1,4,4,4,5,4,3,4,4,79,78.0,neutral or dissatisfied +6521,74720,Male,Loyal Customer,53,Personal Travel,Eco,1464,3,5,3,2,5,3,5,5,4,2,3,5,5,5,31,33.0,neutral or dissatisfied +6522,111613,Female,Loyal Customer,44,Business travel,Business,1014,2,2,2,2,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +6523,54064,Male,Loyal Customer,30,Business travel,Business,1416,4,4,4,4,5,5,5,5,1,2,1,4,2,5,0,0.0,satisfied +6524,17959,Male,Loyal Customer,48,Business travel,Eco,500,3,2,2,2,3,3,3,3,4,5,2,5,2,3,0,0.0,satisfied +6525,128057,Female,Loyal Customer,55,Personal Travel,Eco Plus,735,3,4,3,3,3,3,1,2,2,3,1,1,2,2,6,0.0,neutral or dissatisfied +6526,33382,Female,Loyal Customer,47,Personal Travel,Eco,2556,2,5,2,3,4,5,1,5,5,2,5,1,5,2,0,0.0,neutral or dissatisfied +6527,110110,Female,disloyal Customer,46,Business travel,Business,1056,1,0,0,2,2,1,2,2,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +6528,124386,Female,Loyal Customer,63,Personal Travel,Eco,575,4,4,4,1,2,4,4,3,3,4,2,5,3,4,0,1.0,neutral or dissatisfied +6529,123990,Male,Loyal Customer,58,Business travel,Business,184,3,3,4,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +6530,113522,Male,Loyal Customer,43,Business travel,Business,407,2,2,2,2,5,4,4,5,5,5,5,3,5,5,5,0.0,satisfied +6531,35364,Female,disloyal Customer,49,Business travel,Eco,944,1,1,1,3,1,1,1,1,4,2,3,2,3,1,53,13.0,neutral or dissatisfied +6532,124452,Male,disloyal Customer,24,Business travel,Eco,980,2,2,2,2,3,2,4,3,5,4,4,3,4,3,3,39.0,neutral or dissatisfied +6533,73558,Male,Loyal Customer,31,Business travel,Business,204,0,5,0,3,5,4,4,5,5,5,4,4,4,5,21,7.0,satisfied +6534,13878,Male,disloyal Customer,23,Business travel,Eco,667,4,1,5,2,4,5,4,4,4,2,3,1,3,4,0,1.0,neutral or dissatisfied +6535,91154,Male,Loyal Customer,12,Personal Travel,Eco,271,4,0,4,4,3,4,3,3,4,2,2,1,4,3,40,33.0,neutral or dissatisfied +6536,15326,Male,Loyal Customer,35,Business travel,Eco,599,1,4,4,4,1,1,1,1,3,3,3,2,2,1,0,0.0,neutral or dissatisfied +6537,115452,Female,Loyal Customer,20,Business travel,Business,325,1,1,1,1,1,1,1,1,1,2,4,1,3,1,0,0.0,neutral or dissatisfied +6538,50083,Male,Loyal Customer,71,Business travel,Eco,262,1,5,5,5,2,1,2,2,4,5,1,2,1,2,0,5.0,neutral or dissatisfied +6539,99717,Male,Loyal Customer,45,Business travel,Business,255,5,5,5,5,3,5,4,3,3,4,3,4,3,3,62,64.0,satisfied +6540,27695,Female,Loyal Customer,45,Personal Travel,Eco,1107,4,0,3,2,5,5,4,4,4,3,4,4,4,4,0,0.0,satisfied +6541,48514,Male,Loyal Customer,54,Business travel,Eco,776,1,3,3,3,1,1,1,1,4,2,3,3,4,1,11,38.0,neutral or dissatisfied +6542,57134,Female,Loyal Customer,29,Personal Travel,Eco,1222,2,5,2,3,3,2,3,3,1,2,2,1,1,3,3,0.0,neutral or dissatisfied +6543,33128,Male,Loyal Customer,38,Personal Travel,Eco,102,1,5,0,3,2,0,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +6544,97323,Female,Loyal Customer,47,Business travel,Business,843,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +6545,89320,Female,Loyal Customer,60,Business travel,Business,1587,1,1,1,1,2,3,4,4,4,5,4,3,4,3,0,0.0,satisfied +6546,82205,Male,disloyal Customer,38,Business travel,Business,405,2,2,2,1,1,2,1,1,5,4,5,5,4,1,0,0.0,satisfied +6547,61771,Male,Loyal Customer,33,Personal Travel,Eco,1303,1,4,1,5,4,1,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +6548,42530,Male,Loyal Customer,46,Personal Travel,Eco Plus,328,0,2,0,2,4,0,4,4,2,5,3,2,2,4,0,0.0,satisfied +6549,112136,Female,disloyal Customer,35,Business travel,Business,895,2,2,2,1,4,2,5,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +6550,16193,Male,disloyal Customer,25,Business travel,Business,277,4,0,4,2,3,4,3,3,5,2,1,1,2,3,25,55.0,satisfied +6551,45955,Female,Loyal Customer,44,Business travel,Eco Plus,563,5,3,3,3,5,4,3,5,5,5,5,2,5,5,0,0.0,satisfied +6552,53768,Male,Loyal Customer,16,Personal Travel,Eco,1195,4,4,4,3,2,4,2,2,3,2,5,5,5,2,3,0.0,neutral or dissatisfied +6553,101439,Male,Loyal Customer,40,Business travel,Business,345,3,3,3,3,3,4,5,5,5,4,5,5,5,3,0,5.0,satisfied +6554,105950,Male,disloyal Customer,34,Business travel,Business,2295,2,2,2,4,1,2,1,1,4,4,3,5,5,1,9,0.0,neutral or dissatisfied +6555,3713,Male,Loyal Customer,47,Personal Travel,Eco,431,3,5,3,2,3,3,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +6556,39149,Male,Loyal Customer,47,Personal Travel,Eco,190,1,4,1,3,5,1,5,5,4,2,5,3,4,5,1,,neutral or dissatisfied +6557,27297,Male,Loyal Customer,26,Business travel,Eco,1050,4,2,4,2,4,4,3,4,1,4,4,5,1,4,0,0.0,satisfied +6558,100380,Female,Loyal Customer,39,Personal Travel,Eco,1011,1,3,1,3,2,1,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +6559,57087,Male,Loyal Customer,58,Business travel,Business,3534,1,4,1,1,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +6560,108821,Female,Loyal Customer,48,Business travel,Business,1199,1,4,4,4,2,3,4,1,1,1,1,1,1,1,0,4.0,neutral or dissatisfied +6561,127008,Female,Loyal Customer,33,Business travel,Business,2030,4,4,4,4,1,3,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +6562,44061,Male,Loyal Customer,26,Personal Travel,Business,456,1,4,1,5,3,1,3,3,3,3,5,3,4,3,0,3.0,neutral or dissatisfied +6563,128488,Female,Loyal Customer,62,Personal Travel,Eco,370,2,5,2,5,1,1,1,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +6564,129670,Female,disloyal Customer,23,Business travel,Eco,447,3,0,3,3,4,3,4,4,3,5,5,3,4,4,57,61.0,neutral or dissatisfied +6565,120988,Female,Loyal Customer,12,Business travel,Business,1502,1,1,2,1,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +6566,53071,Male,Loyal Customer,12,Personal Travel,Eco,1208,2,1,2,2,2,2,2,2,4,5,3,4,2,2,3,6.0,neutral or dissatisfied +6567,114745,Female,Loyal Customer,46,Business travel,Business,1573,5,5,5,5,5,5,5,5,5,5,5,3,5,3,73,64.0,satisfied +6568,50361,Male,Loyal Customer,18,Business travel,Business,190,4,4,4,4,4,4,5,4,4,2,4,2,1,4,0,2.0,satisfied +6569,38342,Female,Loyal Customer,42,Business travel,Business,1612,4,4,4,4,3,5,5,5,5,5,5,4,5,4,4,0.0,satisfied +6570,54128,Female,disloyal Customer,29,Business travel,Eco,1400,1,0,0,4,3,1,3,3,2,4,2,1,5,3,1,0.0,neutral or dissatisfied +6571,14911,Male,Loyal Customer,8,Personal Travel,Eco,240,0,5,0,2,5,0,3,5,3,5,4,3,5,5,0,0.0,satisfied +6572,52258,Male,Loyal Customer,30,Business travel,Business,370,4,4,4,4,4,4,4,4,3,3,5,4,1,4,0,11.0,satisfied +6573,56039,Female,Loyal Customer,43,Business travel,Eco,2586,3,5,1,5,3,4,4,2,4,2,2,4,2,4,31,33.0,neutral or dissatisfied +6574,58987,Male,disloyal Customer,48,Business travel,Business,1744,5,5,5,2,5,5,5,5,5,2,4,4,5,5,5,29.0,satisfied +6575,19215,Female,Loyal Customer,55,Business travel,Business,459,5,4,4,4,3,1,1,5,5,4,5,4,5,3,118,115.0,neutral or dissatisfied +6576,104926,Male,Loyal Customer,28,Business travel,Business,210,5,5,5,5,4,4,4,4,5,5,5,3,3,4,98,102.0,satisfied +6577,120971,Female,Loyal Customer,55,Business travel,Business,992,1,1,3,1,2,4,4,4,4,4,4,3,4,4,1,5.0,satisfied +6578,111630,Male,Loyal Customer,59,Personal Travel,Eco Plus,1014,2,4,2,4,1,2,1,1,4,4,1,3,2,1,46,48.0,neutral or dissatisfied +6579,17518,Male,Loyal Customer,61,Personal Travel,Eco,241,4,5,4,4,3,4,3,3,3,2,4,4,5,3,0,2.0,satisfied +6580,37409,Male,disloyal Customer,26,Business travel,Eco,944,4,4,4,2,4,4,4,4,4,2,5,3,3,4,0,0.0,neutral or dissatisfied +6581,38064,Female,Loyal Customer,24,Business travel,Eco,1237,5,1,1,1,5,5,4,5,2,4,4,4,5,5,21,5.0,satisfied +6582,111597,Female,disloyal Customer,29,Business travel,Business,883,5,5,5,1,1,5,1,1,3,3,4,3,4,1,4,5.0,satisfied +6583,18230,Male,Loyal Customer,37,Business travel,Business,346,1,2,2,2,3,3,4,1,1,1,1,1,1,4,55,42.0,neutral or dissatisfied +6584,84382,Male,Loyal Customer,30,Business travel,Business,606,3,5,5,5,3,4,3,3,4,5,4,1,4,3,0,4.0,neutral or dissatisfied +6585,122420,Male,Loyal Customer,30,Business travel,Business,1916,4,4,5,4,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +6586,78970,Male,disloyal Customer,24,Business travel,Eco,226,3,0,3,5,3,3,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +6587,61560,Female,Loyal Customer,32,Business travel,Eco Plus,2442,2,3,3,3,2,2,2,2,4,1,1,1,2,2,30,8.0,neutral or dissatisfied +6588,106088,Female,Loyal Customer,30,Business travel,Business,302,0,0,0,2,4,4,4,4,3,4,4,4,5,4,20,21.0,satisfied +6589,105066,Male,Loyal Customer,47,Business travel,Business,2055,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,10.0,satisfied +6590,54888,Male,Loyal Customer,69,Personal Travel,Eco,641,4,5,3,3,3,3,5,3,3,3,5,5,5,3,2,0.0,neutral or dissatisfied +6591,2651,Male,Loyal Customer,39,Business travel,Business,3641,4,4,2,4,4,5,4,4,4,4,4,3,4,4,14,11.0,satisfied +6592,129013,Female,Loyal Customer,24,Business travel,Business,2704,4,1,1,1,3,4,4,1,2,3,4,4,4,4,2,12.0,neutral or dissatisfied +6593,29813,Female,Loyal Customer,34,Business travel,Business,373,5,5,2,5,1,1,2,4,4,4,4,3,4,5,0,6.0,satisfied +6594,65644,Female,Loyal Customer,34,Business travel,Business,926,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +6595,127349,Male,Loyal Customer,35,Business travel,Eco,507,1,3,3,3,1,1,1,1,1,2,3,1,3,1,0,0.0,neutral or dissatisfied +6596,110488,Female,Loyal Customer,20,Personal Travel,Eco,842,3,5,3,3,1,3,3,1,5,2,2,2,3,1,11,6.0,neutral or dissatisfied +6597,50685,Male,Loyal Customer,15,Personal Travel,Eco,304,3,4,3,3,5,3,2,5,5,3,4,3,5,5,23,18.0,neutral or dissatisfied +6598,13248,Male,disloyal Customer,24,Business travel,Eco,468,2,2,2,3,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +6599,36365,Male,disloyal Customer,23,Business travel,Eco,200,4,0,4,3,4,4,4,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +6600,112817,Female,disloyal Customer,46,Business travel,Business,1211,3,3,3,3,3,3,3,3,4,5,5,3,4,3,9,0.0,neutral or dissatisfied +6601,124364,Male,Loyal Customer,10,Business travel,Business,575,1,1,1,1,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +6602,38194,Male,Loyal Customer,67,Personal Travel,Eco,1249,1,4,1,3,3,1,3,3,5,3,4,4,5,3,10,3.0,neutral or dissatisfied +6603,2882,Female,Loyal Customer,7,Personal Travel,Eco,409,2,3,2,2,4,2,2,4,1,1,3,4,3,4,0,9.0,neutral or dissatisfied +6604,17945,Female,Loyal Customer,49,Personal Travel,Eco,214,4,2,4,2,2,2,3,4,4,4,4,3,4,1,43,68.0,neutral or dissatisfied +6605,53015,Female,disloyal Customer,41,Business travel,Eco,1190,3,3,3,1,4,3,4,4,2,2,2,2,2,4,22,36.0,neutral or dissatisfied +6606,4195,Female,Loyal Customer,50,Business travel,Business,544,5,5,5,5,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +6607,3170,Female,disloyal Customer,21,Business travel,Eco,585,5,2,5,2,4,5,4,4,5,5,4,3,4,4,9,51.0,satisfied +6608,116990,Male,Loyal Customer,34,Business travel,Business,338,4,4,4,4,2,4,5,4,4,4,4,3,4,3,19,13.0,satisfied +6609,52289,Female,disloyal Customer,40,Business travel,Business,370,4,4,4,3,4,4,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +6610,95287,Female,Loyal Customer,66,Personal Travel,Eco,562,4,4,4,2,2,4,4,5,5,4,5,4,5,3,88,83.0,neutral or dissatisfied +6611,124718,Male,Loyal Customer,25,Personal Travel,Eco,399,1,2,1,2,3,1,2,3,3,5,2,4,2,3,22,16.0,neutral or dissatisfied +6612,123049,Male,disloyal Customer,23,Business travel,Eco,468,2,5,2,2,2,2,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +6613,109761,Male,Loyal Customer,56,Business travel,Business,2345,3,3,5,3,3,5,5,5,5,5,5,3,5,4,77,80.0,satisfied +6614,49795,Female,disloyal Customer,22,Business travel,Eco,266,3,0,3,3,4,3,5,4,3,3,2,3,5,4,0,0.0,neutral or dissatisfied +6615,33890,Male,Loyal Customer,31,Business travel,Business,1226,3,4,4,4,3,3,3,3,3,3,4,1,4,3,127,123.0,neutral or dissatisfied +6616,36230,Male,Loyal Customer,43,Personal Travel,Eco,280,2,3,2,4,1,2,1,1,5,4,4,4,1,1,0,0.0,neutral or dissatisfied +6617,46925,Male,Loyal Customer,43,Business travel,Business,2941,1,1,1,1,2,2,1,5,5,5,5,3,5,3,41,46.0,satisfied +6618,10593,Female,Loyal Customer,43,Business travel,Business,2862,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +6619,74609,Female,Loyal Customer,28,Business travel,Business,1242,5,5,5,5,4,4,4,4,5,4,4,4,4,4,15,2.0,satisfied +6620,16484,Male,Loyal Customer,71,Business travel,Business,3230,5,5,5,5,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +6621,63334,Male,disloyal Customer,43,Business travel,Eco,337,1,3,1,4,2,1,2,2,3,4,4,4,3,2,8,10.0,neutral or dissatisfied +6622,50043,Male,Loyal Customer,46,Business travel,Eco,89,5,1,1,1,5,5,5,5,1,1,2,3,5,5,0,0.0,satisfied +6623,112665,Female,Loyal Customer,42,Business travel,Business,1865,1,1,1,1,3,4,5,4,4,4,4,4,4,4,37,21.0,satisfied +6624,72047,Female,Loyal Customer,20,Personal Travel,Business,2556,3,4,3,2,4,3,4,4,1,1,4,1,5,4,15,2.0,neutral or dissatisfied +6625,64801,Female,disloyal Customer,24,Business travel,Eco,551,4,4,4,4,4,4,4,4,1,5,3,2,3,4,0,0.0,neutral or dissatisfied +6626,1947,Female,Loyal Customer,61,Business travel,Eco,383,3,3,2,3,1,4,4,3,3,3,3,3,3,2,5,14.0,neutral or dissatisfied +6627,88686,Female,Loyal Customer,20,Personal Travel,Eco,515,2,5,2,4,5,2,5,5,4,4,5,5,5,5,0,13.0,neutral or dissatisfied +6628,77799,Female,Loyal Customer,52,Personal Travel,Eco,731,1,5,1,2,4,3,4,4,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +6629,86525,Female,Loyal Customer,39,Personal Travel,Eco,712,2,5,1,2,4,1,4,4,2,2,4,4,5,4,0,0.0,neutral or dissatisfied +6630,26395,Male,Loyal Customer,50,Business travel,Eco,957,1,5,5,5,1,1,1,1,3,5,3,4,2,1,0,0.0,neutral or dissatisfied +6631,31535,Female,Loyal Customer,41,Personal Travel,Eco,853,1,5,1,4,2,1,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +6632,96406,Male,Loyal Customer,7,Personal Travel,Eco,1246,3,4,3,2,3,3,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +6633,58035,Male,disloyal Customer,24,Business travel,Business,612,4,0,5,5,1,5,1,1,3,2,4,3,4,1,0,0.0,satisfied +6634,59105,Male,Loyal Customer,10,Personal Travel,Eco,1726,4,1,4,3,3,4,3,3,1,5,4,2,4,3,0,0.0,neutral or dissatisfied +6635,88232,Female,Loyal Customer,69,Business travel,Business,581,2,5,5,5,4,4,4,2,2,2,2,1,2,1,4,4.0,neutral or dissatisfied +6636,14537,Female,disloyal Customer,37,Business travel,Eco,368,1,1,1,3,2,1,2,2,2,4,4,2,3,2,22,12.0,neutral or dissatisfied +6637,85888,Female,Loyal Customer,53,Personal Travel,Eco,2172,3,5,4,3,4,5,5,5,5,4,5,4,5,3,1,9.0,neutral or dissatisfied +6638,3197,Male,Loyal Customer,65,Personal Travel,Eco,585,2,5,2,2,2,2,5,2,4,2,5,3,4,2,0,10.0,neutral or dissatisfied +6639,86397,Female,Loyal Customer,57,Business travel,Eco,762,1,2,2,2,2,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +6640,112074,Male,Loyal Customer,52,Business travel,Business,1491,4,4,4,4,4,5,4,4,4,5,4,3,4,3,10,0.0,satisfied +6641,47880,Female,Loyal Customer,37,Business travel,Business,2930,1,3,3,3,1,2,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +6642,46599,Male,disloyal Customer,24,Business travel,Eco,141,1,0,1,3,4,1,4,4,3,3,1,1,3,4,2,0.0,neutral or dissatisfied +6643,47850,Female,disloyal Customer,22,Business travel,Eco,329,3,0,3,3,5,3,5,5,3,5,4,3,4,5,38,42.0,neutral or dissatisfied +6644,27797,Male,Loyal Customer,60,Business travel,Eco,680,4,3,3,3,4,4,4,4,3,4,3,4,4,4,0,0.0,neutral or dissatisfied +6645,103825,Female,disloyal Customer,17,Business travel,Business,882,0,5,0,4,2,5,2,2,4,2,4,5,4,2,0,0.0,satisfied +6646,88766,Female,Loyal Customer,60,Business travel,Business,515,2,2,2,2,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6647,63353,Male,Loyal Customer,33,Personal Travel,Eco,337,5,2,5,4,4,5,4,4,3,1,3,4,4,4,0,0.0,satisfied +6648,124606,Male,disloyal Customer,20,Business travel,Business,1671,2,2,2,1,5,2,5,5,1,1,1,1,2,5,0,28.0,neutral or dissatisfied +6649,81128,Female,Loyal Customer,57,Personal Travel,Eco,991,4,2,4,4,2,4,3,5,5,4,5,2,5,2,4,0.0,neutral or dissatisfied +6650,127831,Male,Loyal Customer,38,Personal Travel,Eco,1044,2,5,2,2,3,2,3,3,4,4,4,4,5,3,0,8.0,neutral or dissatisfied +6651,21275,Male,Loyal Customer,26,Business travel,Business,3568,3,5,3,3,5,5,5,5,4,5,3,5,4,5,0,0.0,satisfied +6652,53565,Male,Loyal Customer,25,Business travel,Business,1195,2,2,3,2,5,5,5,5,2,3,5,1,1,5,0,0.0,satisfied +6653,47129,Female,Loyal Customer,54,Business travel,Business,3668,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +6654,101159,Male,Loyal Customer,65,Business travel,Business,1235,2,2,2,2,3,2,3,2,2,2,2,4,2,2,10,0.0,neutral or dissatisfied +6655,64036,Female,disloyal Customer,29,Business travel,Business,919,5,5,5,3,2,5,2,2,4,3,4,5,4,2,0,10.0,satisfied +6656,25297,Male,Loyal Customer,54,Business travel,Business,2516,2,2,2,2,5,5,5,2,2,2,2,4,2,4,0,9.0,satisfied +6657,66263,Female,Loyal Customer,52,Personal Travel,Eco,550,2,3,2,3,1,1,4,2,2,2,2,5,2,1,0,0.0,neutral or dissatisfied +6658,12648,Female,Loyal Customer,34,Personal Travel,Eco,844,3,4,3,1,4,3,4,4,5,4,4,4,5,4,40,105.0,neutral or dissatisfied +6659,66423,Male,Loyal Customer,7,Personal Travel,Eco,1562,3,5,2,4,2,2,3,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +6660,90263,Male,disloyal Customer,26,Business travel,Business,932,2,1,1,4,3,1,3,3,5,5,4,5,5,3,40,26.0,neutral or dissatisfied +6661,61910,Female,disloyal Customer,25,Business travel,Business,550,4,5,5,4,1,5,2,1,5,2,4,4,5,1,0,6.0,satisfied +6662,83454,Female,Loyal Customer,46,Business travel,Business,2389,4,4,2,4,5,5,4,3,3,3,3,4,3,5,93,94.0,satisfied +6663,123526,Female,disloyal Customer,21,Business travel,Eco,2296,3,3,3,4,5,3,5,5,5,3,4,3,4,5,5,0.0,neutral or dissatisfied +6664,77008,Female,Loyal Customer,58,Business travel,Business,2598,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +6665,98965,Female,Loyal Customer,40,Business travel,Business,479,3,3,1,3,5,3,5,5,5,5,5,5,5,2,0,0.0,satisfied +6666,119431,Male,Loyal Customer,32,Personal Travel,Eco,399,5,4,5,4,5,5,5,5,3,5,1,4,3,5,0,0.0,satisfied +6667,40200,Female,disloyal Customer,23,Business travel,Eco,531,1,5,1,1,2,1,2,2,3,1,5,4,3,2,0,2.0,neutral or dissatisfied +6668,14823,Male,Loyal Customer,36,Business travel,Business,1832,5,5,5,5,2,4,4,5,5,5,5,4,5,5,1,2.0,satisfied +6669,88192,Female,disloyal Customer,62,Business travel,Business,404,4,4,4,2,4,4,4,4,5,5,4,4,4,4,7,3.0,satisfied +6670,70754,Female,Loyal Customer,38,Business travel,Business,2427,1,1,1,1,4,4,5,4,4,4,4,4,4,4,1,0.0,satisfied +6671,104968,Female,Loyal Customer,38,Business travel,Business,3934,5,5,5,5,3,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +6672,125943,Male,Loyal Customer,34,Personal Travel,Eco,920,3,5,3,4,2,3,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +6673,2665,Female,Loyal Customer,59,Business travel,Business,1887,2,2,2,2,5,5,4,5,5,5,5,4,5,4,11,16.0,satisfied +6674,55435,Male,Loyal Customer,25,Business travel,Eco,2521,1,5,5,5,1,1,1,2,3,3,3,1,2,1,0,4.0,neutral or dissatisfied +6675,49655,Female,Loyal Customer,38,Business travel,Eco,199,4,5,4,5,4,4,4,4,3,2,5,1,5,4,0,25.0,satisfied +6676,108425,Female,Loyal Customer,27,Business travel,Business,1444,2,2,2,2,4,5,4,4,4,3,4,3,4,4,0,0.0,satisfied +6677,125210,Female,Loyal Customer,32,Business travel,Business,651,2,4,3,4,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +6678,56893,Female,disloyal Customer,54,Business travel,Eco,901,4,4,4,3,4,5,5,2,4,2,2,5,1,5,49,38.0,neutral or dissatisfied +6679,99146,Female,Loyal Customer,36,Business travel,Eco Plus,453,1,2,2,2,1,1,1,1,3,2,3,2,4,1,0,1.0,neutral or dissatisfied +6680,101815,Male,disloyal Customer,49,Business travel,Eco,1521,3,3,3,3,3,3,3,3,4,4,3,1,3,3,1,0.0,neutral or dissatisfied +6681,71573,Female,Loyal Customer,57,Business travel,Business,1197,1,1,1,1,5,4,4,3,3,3,3,4,3,3,23,24.0,satisfied +6682,32176,Male,Loyal Customer,55,Business travel,Eco,102,4,5,5,5,5,4,5,5,4,5,4,4,2,5,0,0.0,satisfied +6683,15986,Male,disloyal Customer,38,Business travel,Eco,780,2,2,2,4,3,2,3,3,1,1,5,4,1,3,0,10.0,neutral or dissatisfied +6684,45046,Female,disloyal Customer,22,Business travel,Eco,342,4,0,5,1,3,5,3,3,4,4,4,5,5,3,0,0.0,satisfied +6685,62056,Female,Loyal Customer,27,Personal Travel,Eco,2475,1,0,1,3,4,1,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +6686,77568,Female,Loyal Customer,57,Business travel,Business,2690,5,1,5,5,4,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +6687,117606,Male,Loyal Customer,36,Business travel,Business,872,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +6688,124113,Female,Loyal Customer,58,Business travel,Eco,529,3,3,2,3,3,4,3,3,3,3,3,2,3,1,73,83.0,neutral or dissatisfied +6689,64095,Female,Loyal Customer,48,Personal Travel,Eco,919,1,2,1,3,3,3,4,1,1,1,1,3,1,2,0,7.0,neutral or dissatisfied +6690,1284,Female,Loyal Customer,40,Personal Travel,Eco,164,2,5,2,4,5,2,5,5,4,4,5,2,3,5,9,11.0,neutral or dissatisfied +6691,116617,Female,Loyal Customer,47,Business travel,Business,362,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +6692,84414,Female,Loyal Customer,63,Personal Travel,Eco,591,2,4,2,3,2,4,5,2,2,2,5,4,2,4,0,0.0,neutral or dissatisfied +6693,26471,Female,Loyal Customer,51,Personal Travel,Eco,925,4,2,3,3,3,2,2,1,1,3,1,3,1,3,5,17.0,neutral or dissatisfied +6694,106536,Male,Loyal Customer,54,Business travel,Business,3414,3,3,3,3,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +6695,69865,Female,Loyal Customer,64,Personal Travel,Eco,1055,1,4,1,4,2,4,4,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +6696,85864,Male,Loyal Customer,58,Business travel,Business,672,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,4.0,satisfied +6697,52870,Male,Loyal Customer,44,Business travel,Business,2859,1,1,1,1,5,2,1,4,4,4,4,2,4,5,12,23.0,satisfied +6698,74779,Male,disloyal Customer,29,Business travel,Business,1171,0,0,0,4,3,0,3,3,3,4,5,3,4,3,0,0.0,satisfied +6699,40631,Male,Loyal Customer,47,Personal Travel,Eco,391,3,5,3,3,1,3,1,1,1,4,4,5,3,1,11,28.0,neutral or dissatisfied +6700,55468,Male,disloyal Customer,24,Business travel,Eco,1825,3,3,3,3,3,3,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +6701,838,Female,disloyal Customer,35,Business travel,Business,89,4,5,5,3,3,5,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +6702,66371,Male,Loyal Customer,57,Business travel,Business,3559,1,1,1,1,5,4,4,3,3,2,3,4,3,3,5,0.0,satisfied +6703,114071,Female,Loyal Customer,31,Business travel,Eco,1892,2,2,2,2,2,1,2,2,2,4,3,2,4,2,0,0.0,neutral or dissatisfied +6704,61079,Male,Loyal Customer,46,Business travel,Eco,1146,4,3,3,3,4,4,4,4,3,4,4,1,4,4,130,121.0,satisfied +6705,116307,Female,Loyal Customer,50,Personal Travel,Eco,337,4,1,2,3,2,3,3,3,3,2,3,1,3,2,0,0.0,satisfied +6706,83580,Male,Loyal Customer,53,Business travel,Business,2064,5,5,5,5,2,2,1,5,5,5,5,3,5,1,0,0.0,satisfied +6707,88639,Male,Loyal Customer,27,Personal Travel,Eco,271,2,1,2,3,2,2,2,2,1,4,4,1,3,2,39,25.0,neutral or dissatisfied +6708,10045,Female,Loyal Customer,42,Business travel,Business,326,3,3,4,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +6709,43439,Female,Loyal Customer,60,Business travel,Business,279,4,4,1,4,2,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +6710,48647,Female,Loyal Customer,41,Business travel,Business,2863,5,5,5,5,5,4,4,4,4,4,4,4,4,3,0,4.0,satisfied +6711,49636,Female,Loyal Customer,64,Business travel,Business,2749,3,3,3,3,2,2,3,3,3,3,3,3,3,2,11,6.0,neutral or dissatisfied +6712,14521,Female,Loyal Customer,55,Business travel,Business,368,4,4,4,4,4,4,4,3,1,5,5,4,2,4,178,174.0,satisfied +6713,3335,Female,Loyal Customer,39,Business travel,Business,240,2,2,2,2,2,5,5,5,5,5,5,4,5,4,21,25.0,satisfied +6714,4197,Female,Loyal Customer,16,Personal Travel,Eco Plus,544,3,2,3,3,2,3,2,2,3,5,4,3,3,2,0,8.0,neutral or dissatisfied +6715,9278,Female,Loyal Customer,56,Business travel,Business,3272,3,3,3,3,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +6716,31683,Female,Loyal Customer,22,Business travel,Business,776,3,1,1,1,3,3,3,3,1,2,4,3,3,3,7,10.0,neutral or dissatisfied +6717,47490,Female,Loyal Customer,13,Personal Travel,Eco,599,2,3,3,4,4,3,4,4,1,3,3,2,3,4,0,0.0,neutral or dissatisfied +6718,101882,Female,Loyal Customer,57,Business travel,Business,2039,5,5,5,5,4,5,5,4,4,4,4,4,4,4,20,0.0,satisfied +6719,958,Male,Loyal Customer,56,Business travel,Business,1636,3,3,3,3,5,4,3,2,2,2,3,4,2,2,0,0.0,neutral or dissatisfied +6720,43899,Female,Loyal Customer,38,Personal Travel,Eco,199,5,5,0,2,1,0,1,1,3,3,4,1,3,1,0,16.0,satisfied +6721,123780,Female,Loyal Customer,22,Business travel,Business,3570,5,5,5,5,4,4,4,4,4,3,5,5,5,4,2,34.0,satisfied +6722,37752,Female,Loyal Customer,48,Business travel,Eco Plus,950,4,1,1,1,5,5,3,4,4,4,4,5,4,2,26,19.0,satisfied +6723,56409,Male,Loyal Customer,40,Business travel,Business,3250,3,3,2,3,3,5,5,1,1,2,1,5,1,5,0,12.0,satisfied +6724,20655,Female,Loyal Customer,31,Business travel,Business,522,1,1,1,1,5,5,5,5,5,4,3,5,2,5,29,29.0,satisfied +6725,17942,Male,Loyal Customer,54,Personal Travel,Eco,95,2,3,2,3,2,2,2,2,5,3,1,2,3,2,0,28.0,neutral or dissatisfied +6726,117468,Male,Loyal Customer,65,Personal Travel,Business,507,5,5,5,1,5,5,4,2,2,5,2,3,2,3,7,1.0,satisfied +6727,56277,Male,Loyal Customer,45,Business travel,Business,2227,2,2,2,2,3,3,5,5,5,4,5,4,5,5,0,0.0,satisfied +6728,63022,Male,disloyal Customer,24,Business travel,Eco,862,3,3,3,3,4,3,1,4,1,1,3,4,4,4,22,11.0,neutral or dissatisfied +6729,90443,Female,Loyal Customer,58,Business travel,Business,3323,3,3,3,3,5,4,4,5,5,5,5,3,5,4,51,45.0,satisfied +6730,85560,Female,Loyal Customer,50,Business travel,Business,2755,2,2,4,2,5,4,4,4,4,4,4,5,4,4,39,34.0,satisfied +6731,87871,Male,Loyal Customer,57,Business travel,Business,3739,4,4,4,4,3,4,5,4,4,4,5,3,4,3,0,7.0,satisfied +6732,34896,Female,Loyal Customer,41,Business travel,Eco,395,4,1,1,1,4,4,4,4,1,1,1,4,4,4,0,0.0,satisfied +6733,121387,Male,Loyal Customer,14,Personal Travel,Eco,2279,2,4,2,4,2,2,2,2,4,2,5,3,5,2,0,5.0,neutral or dissatisfied +6734,52913,Male,Loyal Customer,43,Business travel,Eco,679,5,3,3,3,5,5,5,5,5,4,2,4,3,5,12,0.0,satisfied +6735,97283,Male,Loyal Customer,28,Personal Travel,Business,843,2,5,1,4,5,1,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +6736,16426,Male,Loyal Customer,51,Business travel,Business,3948,3,5,3,3,3,5,5,4,4,4,4,1,4,4,99,97.0,satisfied +6737,58552,Female,Loyal Customer,52,Personal Travel,Eco,1514,1,4,1,3,3,3,5,1,1,1,1,4,1,5,0,0.0,neutral or dissatisfied +6738,62494,Female,Loyal Customer,22,Business travel,Business,1846,4,5,4,4,3,4,3,3,5,5,5,4,5,3,0,0.0,satisfied +6739,61054,Male,Loyal Customer,30,Business travel,Business,1546,4,4,4,4,4,4,4,4,4,4,5,3,5,4,0,0.0,satisfied +6740,10182,Male,Loyal Customer,34,Business travel,Business,3471,2,2,2,2,5,5,5,5,5,5,5,3,5,4,53,43.0,satisfied +6741,105647,Female,Loyal Customer,48,Business travel,Business,787,4,4,4,4,3,5,5,4,4,4,4,4,4,4,21,13.0,satisfied +6742,69289,Male,Loyal Customer,44,Business travel,Business,3677,2,2,2,2,5,5,5,5,5,5,5,5,5,3,95,76.0,satisfied +6743,93547,Female,Loyal Customer,44,Personal Travel,Eco,585,3,4,3,2,5,4,5,5,5,3,5,4,5,4,8,0.0,neutral or dissatisfied +6744,10700,Male,Loyal Customer,49,Business travel,Business,247,3,3,3,3,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6745,24592,Female,Loyal Customer,34,Business travel,Eco,526,5,4,4,4,5,5,5,5,1,4,5,2,3,5,0,0.0,satisfied +6746,48885,Female,disloyal Customer,21,Business travel,Business,363,5,3,5,4,1,5,1,1,2,1,5,3,3,1,0,0.0,satisfied +6747,42701,Male,Loyal Customer,41,Personal Travel,Eco,516,3,1,3,2,2,3,2,2,2,1,3,1,2,2,0,0.0,neutral or dissatisfied +6748,57755,Female,Loyal Customer,49,Business travel,Business,2704,5,5,5,5,4,3,3,3,4,3,5,3,4,3,35,63.0,satisfied +6749,120388,Male,Loyal Customer,40,Business travel,Business,449,2,2,2,2,3,5,5,4,4,4,4,5,4,4,1,16.0,satisfied +6750,40510,Female,Loyal Customer,66,Personal Travel,Eco,188,1,3,1,2,1,3,3,5,5,1,5,3,5,2,0,0.0,neutral or dissatisfied +6751,47239,Male,Loyal Customer,59,Personal Travel,Eco Plus,908,1,3,1,2,1,1,1,1,1,1,4,3,4,1,36,26.0,neutral or dissatisfied +6752,85361,Male,Loyal Customer,30,Personal Travel,Eco Plus,813,2,3,3,3,4,3,4,4,4,1,1,2,2,4,11,0.0,neutral or dissatisfied +6753,9645,Female,Loyal Customer,54,Business travel,Business,3091,0,5,0,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +6754,38184,Male,Loyal Customer,44,Personal Travel,Eco,1185,1,4,1,3,4,1,4,4,3,2,3,3,4,4,105,83.0,neutral or dissatisfied +6755,7173,Male,Loyal Customer,45,Business travel,Business,2933,0,5,0,4,4,5,5,2,2,2,2,5,2,3,0,1.0,satisfied +6756,97726,Male,Loyal Customer,54,Business travel,Business,2205,3,3,3,3,3,5,4,4,4,5,4,5,4,5,0,0.0,satisfied +6757,79408,Female,Loyal Customer,58,Business travel,Business,102,4,4,4,4,5,1,3,5,5,5,4,1,5,5,19,5.0,satisfied +6758,81515,Male,Loyal Customer,27,Business travel,Business,1124,2,2,2,2,5,5,5,5,3,3,4,5,4,5,0,0.0,satisfied +6759,18496,Female,Loyal Customer,19,Business travel,Eco,305,1,5,5,5,1,1,1,1,1,3,3,4,2,1,0,0.0,neutral or dissatisfied +6760,26613,Female,Loyal Customer,50,Business travel,Business,3053,2,2,2,2,3,4,3,5,5,5,5,4,5,4,0,0.0,satisfied +6761,32527,Female,Loyal Customer,39,Business travel,Business,3062,1,2,2,2,2,3,3,1,1,1,1,4,1,3,0,1.0,neutral or dissatisfied +6762,14154,Female,Loyal Customer,50,Business travel,Eco Plus,654,4,2,2,2,5,2,4,4,4,4,4,5,4,1,4,29.0,satisfied +6763,127547,Male,Loyal Customer,35,Business travel,Business,2432,2,1,1,1,4,3,4,2,2,2,2,1,2,3,0,4.0,neutral or dissatisfied +6764,16456,Female,Loyal Customer,29,Personal Travel,Eco,529,2,4,2,4,4,2,4,4,4,5,5,4,5,4,8,11.0,neutral or dissatisfied +6765,101456,Male,Loyal Customer,19,Business travel,Business,2195,5,5,5,5,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +6766,7493,Female,Loyal Customer,47,Business travel,Business,1992,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +6767,69303,Male,disloyal Customer,26,Business travel,Business,944,5,5,5,5,4,5,3,4,5,3,5,4,5,4,0,26.0,satisfied +6768,27143,Female,Loyal Customer,40,Business travel,Business,2640,3,1,2,2,3,3,3,1,2,3,4,3,1,3,0,4.0,neutral or dissatisfied +6769,89943,Male,Loyal Customer,11,Personal Travel,Eco,1306,4,5,4,3,1,4,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +6770,104131,Male,Loyal Customer,33,Business travel,Business,3423,2,3,3,3,2,2,2,2,2,2,4,4,4,2,9,0.0,neutral or dissatisfied +6771,64359,Female,disloyal Customer,35,Business travel,Eco,1192,4,4,4,3,3,4,3,3,1,3,2,4,1,3,54,43.0,neutral or dissatisfied +6772,117101,Male,Loyal Customer,48,Business travel,Eco,304,4,3,3,3,4,4,4,4,3,2,1,3,2,4,10,13.0,satisfied +6773,7207,Male,Loyal Customer,50,Business travel,Business,1855,4,4,4,4,3,5,4,5,5,5,4,4,5,3,79,95.0,satisfied +6774,44868,Male,Loyal Customer,48,Business travel,Eco,315,2,1,1,1,2,2,2,2,5,1,2,4,4,2,0,42.0,satisfied +6775,64159,Female,Loyal Customer,36,Business travel,Business,589,4,4,4,4,5,2,1,4,4,4,4,2,4,3,0,0.0,satisfied +6776,82810,Female,Loyal Customer,36,Business travel,Business,3841,4,4,4,4,3,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +6777,96583,Female,Loyal Customer,51,Personal Travel,Eco Plus,333,3,4,3,3,4,4,5,1,1,3,4,5,1,5,0,0.0,neutral or dissatisfied +6778,122050,Female,Loyal Customer,33,Business travel,Business,3069,2,2,2,2,5,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +6779,27917,Male,Loyal Customer,50,Business travel,Business,3127,4,5,5,5,1,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +6780,74496,Male,Loyal Customer,36,Business travel,Business,1171,5,5,4,5,5,4,4,2,2,2,2,4,2,5,7,0.0,satisfied +6781,19385,Male,disloyal Customer,30,Business travel,Eco,844,1,1,1,3,3,1,3,3,3,3,4,4,4,3,19,21.0,neutral or dissatisfied +6782,37048,Male,Loyal Customer,37,Personal Travel,Eco,1105,2,4,2,2,2,2,2,2,5,2,1,2,2,2,4,10.0,neutral or dissatisfied +6783,42771,Male,Loyal Customer,40,Personal Travel,Eco,493,2,5,2,3,3,2,1,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +6784,104629,Male,Loyal Customer,55,Business travel,Eco,861,1,1,1,1,2,1,2,2,3,3,4,4,3,2,0,0.0,neutral or dissatisfied +6785,75121,Female,Loyal Customer,48,Business travel,Business,1652,4,4,4,4,4,5,4,3,3,3,3,3,3,5,8,0.0,satisfied +6786,120719,Female,Loyal Customer,55,Business travel,Business,90,3,3,3,3,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +6787,34453,Male,Loyal Customer,16,Personal Travel,Eco,228,4,5,4,3,4,4,3,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +6788,41827,Male,Loyal Customer,57,Personal Travel,Eco,257,2,4,2,3,1,2,1,1,4,5,1,5,2,1,0,0.0,neutral or dissatisfied +6789,38914,Male,disloyal Customer,39,Business travel,Eco,162,2,0,2,1,4,2,3,4,1,2,4,1,5,4,0,0.0,neutral or dissatisfied +6790,35683,Female,Loyal Customer,24,Business travel,Business,2586,2,3,3,3,2,2,2,2,5,2,4,2,1,2,0,8.0,neutral or dissatisfied +6791,2908,Male,Loyal Customer,39,Personal Travel,Eco,409,1,4,4,3,3,4,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +6792,11302,Male,Loyal Customer,62,Personal Travel,Eco,396,2,4,2,5,5,2,5,5,5,2,5,4,4,5,0,2.0,neutral or dissatisfied +6793,82428,Female,Loyal Customer,59,Business travel,Business,3810,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +6794,36807,Female,Loyal Customer,50,Personal Travel,Business,2300,2,4,2,1,5,5,4,5,5,2,5,5,5,3,2,0.0,neutral or dissatisfied +6795,76269,Female,Loyal Customer,47,Business travel,Business,1927,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +6796,58496,Male,Loyal Customer,32,Business travel,Business,1660,4,2,2,2,4,4,4,4,3,5,2,1,2,4,24,40.0,neutral or dissatisfied +6797,128144,Female,Loyal Customer,55,Business travel,Business,1849,3,3,3,3,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +6798,83590,Female,Loyal Customer,40,Business travel,Business,2786,3,3,2,3,2,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +6799,94198,Male,Loyal Customer,44,Business travel,Business,528,2,2,1,2,2,5,4,3,3,3,3,4,3,3,121,128.0,satisfied +6800,110963,Female,Loyal Customer,48,Business travel,Business,2745,2,5,5,5,2,4,4,3,3,3,2,3,3,3,7,10.0,neutral or dissatisfied +6801,124660,Female,Loyal Customer,38,Business travel,Business,2489,2,2,2,2,2,4,5,5,5,5,5,5,5,5,6,13.0,satisfied +6802,21950,Male,Loyal Customer,16,Business travel,Business,551,3,1,4,1,3,3,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +6803,81672,Female,Loyal Customer,56,Business travel,Business,3524,4,4,4,4,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +6804,93642,Female,disloyal Customer,40,Business travel,Business,704,4,4,4,3,5,4,1,5,3,4,4,4,5,5,3,9.0,satisfied +6805,101756,Female,Loyal Customer,50,Personal Travel,Eco,1590,3,2,3,4,4,3,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +6806,83591,Male,Loyal Customer,65,Personal Travel,Eco Plus,936,4,5,4,5,1,4,1,1,5,2,4,4,4,1,4,0.0,neutral or dissatisfied +6807,46024,Male,Loyal Customer,43,Business travel,Business,2607,3,3,4,3,4,5,5,4,4,4,4,5,4,3,83,100.0,satisfied +6808,44055,Female,Loyal Customer,21,Business travel,Eco Plus,296,0,4,0,2,5,0,5,5,2,1,1,3,3,5,0,0.0,satisfied +6809,84300,Female,Loyal Customer,35,Business travel,Business,2399,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +6810,85464,Female,Loyal Customer,28,Business travel,Business,332,5,5,5,5,4,4,4,4,3,5,5,5,5,4,6,0.0,satisfied +6811,64781,Female,disloyal Customer,27,Business travel,Business,469,4,4,4,5,5,4,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +6812,62546,Female,Loyal Customer,49,Business travel,Business,1846,1,1,1,1,2,5,4,4,4,4,4,3,4,5,91,61.0,satisfied +6813,13908,Male,Loyal Customer,36,Business travel,Eco,192,5,4,4,4,5,5,5,5,2,3,3,3,5,5,0,0.0,satisfied +6814,64811,Female,Loyal Customer,43,Business travel,Business,224,5,5,5,5,5,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +6815,126784,Male,disloyal Customer,27,Business travel,Business,2125,2,2,2,4,3,2,5,3,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +6816,81596,Male,Loyal Customer,55,Business travel,Business,349,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +6817,15162,Female,Loyal Customer,39,Business travel,Eco Plus,912,3,4,2,2,3,3,3,3,1,3,4,2,4,3,0,7.0,neutral or dissatisfied +6818,118766,Male,Loyal Customer,17,Personal Travel,Eco,370,4,1,1,2,3,1,3,3,4,5,3,4,2,3,46,44.0,neutral or dissatisfied +6819,102768,Female,Loyal Customer,50,Personal Travel,Eco,1618,1,4,1,3,4,5,5,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +6820,50219,Male,Loyal Customer,53,Business travel,Eco,78,3,2,2,2,3,3,3,3,2,3,4,4,4,3,0,0.0,neutral or dissatisfied +6821,129651,Female,disloyal Customer,38,Business travel,Business,447,2,2,2,5,5,2,2,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +6822,30152,Female,Loyal Customer,49,Personal Travel,Eco,204,3,5,3,1,2,2,4,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +6823,61730,Female,Loyal Customer,47,Business travel,Eco,1635,4,4,4,4,4,4,2,3,3,4,3,4,3,1,0,11.0,satisfied +6824,17318,Male,Loyal Customer,13,Personal Travel,Eco,403,2,5,4,3,1,4,1,1,5,5,4,3,4,1,0,16.0,neutral or dissatisfied +6825,42307,Female,Loyal Customer,12,Personal Travel,Eco,550,1,3,1,3,2,1,2,2,4,4,2,3,4,2,7,14.0,neutral or dissatisfied +6826,38622,Female,Loyal Customer,41,Business travel,Business,1111,1,1,1,1,2,5,4,2,2,2,2,5,2,4,108,100.0,satisfied +6827,119938,Female,disloyal Customer,20,Business travel,Eco,868,2,2,2,3,4,2,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +6828,99990,Male,disloyal Customer,21,Business travel,Eco,277,3,4,3,5,5,3,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +6829,907,Male,disloyal Customer,18,Business travel,Eco,134,3,5,3,2,4,3,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +6830,60394,Male,Loyal Customer,50,Business travel,Eco,1452,4,5,5,5,4,4,4,4,3,5,4,2,5,4,13,1.0,satisfied +6831,96724,Male,Loyal Customer,10,Personal Travel,Eco,696,4,5,4,4,1,4,1,1,3,5,4,4,4,1,12,6.0,neutral or dissatisfied +6832,6350,Male,Loyal Customer,55,Business travel,Business,240,1,1,1,1,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +6833,105681,Female,Loyal Customer,38,Business travel,Business,663,4,4,4,4,5,5,5,4,4,5,4,3,4,4,32,51.0,satisfied +6834,55225,Male,Loyal Customer,44,Business travel,Business,3422,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +6835,75979,Male,Loyal Customer,37,Business travel,Business,3101,4,5,5,5,1,3,3,4,4,4,4,2,4,1,2,23.0,neutral or dissatisfied +6836,81168,Male,Loyal Customer,46,Personal Travel,Eco,196,2,5,2,3,2,2,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +6837,99944,Male,Loyal Customer,41,Business travel,Business,1986,4,4,4,4,3,4,4,4,4,4,4,3,4,5,0,3.0,satisfied +6838,37221,Male,Loyal Customer,58,Business travel,Business,2340,1,0,0,4,5,4,3,3,3,0,3,2,3,3,0,0.0,neutral or dissatisfied +6839,36613,Male,disloyal Customer,29,Business travel,Eco,1220,2,2,2,2,3,2,3,3,4,2,2,4,2,3,0,0.0,neutral or dissatisfied +6840,104252,Female,Loyal Customer,59,Personal Travel,Eco,1276,2,5,2,1,4,5,1,3,3,2,3,4,3,2,24,0.0,neutral or dissatisfied +6841,59453,Male,Loyal Customer,50,Business travel,Business,811,3,3,3,3,4,5,4,4,4,4,4,4,4,5,3,20.0,satisfied +6842,4003,Female,Loyal Customer,59,Business travel,Business,419,5,5,5,5,5,5,4,5,5,5,5,4,5,3,49,90.0,satisfied +6843,80137,Female,disloyal Customer,22,Business travel,Eco,1449,4,4,4,3,4,1,1,5,4,4,4,1,3,1,9,12.0,satisfied +6844,21522,Male,Loyal Customer,38,Personal Travel,Eco,377,3,4,3,3,3,3,3,3,5,3,5,4,5,3,35,28.0,neutral or dissatisfied +6845,64868,Male,disloyal Customer,23,Business travel,Eco,247,2,1,2,3,4,2,4,4,3,4,2,4,2,4,0,0.0,neutral or dissatisfied +6846,3851,Female,Loyal Customer,11,Personal Travel,Eco,650,3,1,3,4,3,3,3,3,1,5,4,4,3,3,2,4.0,neutral or dissatisfied +6847,24868,Female,disloyal Customer,22,Business travel,Eco,356,2,4,2,3,4,2,1,4,2,4,3,3,3,4,0,0.0,neutral or dissatisfied +6848,69860,Female,Loyal Customer,54,Personal Travel,Eco,1055,2,1,2,4,3,3,3,5,5,2,5,1,5,3,0,0.0,neutral or dissatisfied +6849,104758,Male,Loyal Customer,9,Personal Travel,Eco,1342,4,5,4,5,2,4,2,2,3,3,3,3,5,2,8,28.0,neutral or dissatisfied +6850,128934,Female,Loyal Customer,33,Business travel,Business,2486,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,5.0,satisfied +6851,2465,Female,Loyal Customer,41,Business travel,Business,322,1,2,2,2,5,3,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +6852,26357,Male,Loyal Customer,47,Business travel,Eco,991,4,5,5,5,4,4,4,4,3,2,1,3,2,4,0,0.0,satisfied +6853,10269,Male,Loyal Customer,27,Personal Travel,Business,74,2,4,2,4,5,2,5,5,2,4,3,1,1,5,1,1.0,neutral or dissatisfied +6854,64336,Male,Loyal Customer,59,Business travel,Business,3092,2,4,4,4,2,1,2,2,2,2,2,2,2,1,34,32.0,neutral or dissatisfied +6855,40857,Male,Loyal Customer,30,Personal Travel,Eco,541,3,4,3,2,4,3,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +6856,23282,Male,disloyal Customer,19,Business travel,Eco,809,2,2,2,5,3,2,3,3,1,2,3,3,5,3,0,0.0,neutral or dissatisfied +6857,29778,Female,Loyal Customer,43,Personal Travel,Business,725,1,3,1,3,4,4,2,1,1,1,1,5,1,4,3,8.0,neutral or dissatisfied +6858,92849,Male,Loyal Customer,55,Business travel,Business,1587,5,5,5,5,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +6859,1942,Female,Loyal Customer,53,Business travel,Eco,383,4,4,4,4,1,3,3,5,5,4,5,4,5,4,4,1.0,neutral or dissatisfied +6860,9426,Male,Loyal Customer,55,Business travel,Business,288,5,5,5,5,2,4,4,5,5,5,5,4,5,3,2,0.0,satisfied +6861,96439,Male,Loyal Customer,49,Business travel,Business,3295,3,3,3,3,2,5,5,4,4,4,4,5,4,5,32,26.0,satisfied +6862,4862,Female,Loyal Customer,43,Personal Travel,Eco,408,1,2,1,3,3,4,3,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +6863,24947,Female,Loyal Customer,27,Business travel,Business,1747,5,5,5,5,5,4,5,5,5,2,3,1,5,5,14,0.0,satisfied +6864,116266,Female,Loyal Customer,53,Personal Travel,Eco,447,4,5,4,2,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +6865,61739,Female,disloyal Customer,35,Business travel,Eco,1346,3,3,3,4,4,3,3,4,4,4,5,1,5,4,0,0.0,neutral or dissatisfied +6866,91055,Female,Loyal Customer,50,Personal Travel,Eco,406,1,1,1,3,3,3,3,3,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +6867,121697,Female,Loyal Customer,56,Business travel,Business,3085,2,2,2,2,4,4,4,5,5,5,4,3,5,3,0,2.0,satisfied +6868,102559,Female,Loyal Customer,38,Business travel,Business,3611,2,2,2,2,5,5,5,5,5,5,5,3,5,5,2,0.0,satisfied +6869,100621,Male,Loyal Customer,11,Personal Travel,Eco,1121,2,4,2,4,4,2,5,4,3,5,4,5,4,4,1,8.0,neutral or dissatisfied +6870,17036,Male,Loyal Customer,22,Personal Travel,Eco Plus,781,2,5,2,1,3,2,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +6871,26696,Female,Loyal Customer,46,Personal Travel,Eco,406,1,4,2,1,2,4,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +6872,211,Male,disloyal Customer,22,Business travel,Eco,213,5,0,5,1,3,5,3,3,4,4,5,1,3,3,1,4.0,satisfied +6873,113770,Female,Loyal Customer,9,Personal Travel,Eco,226,1,4,1,3,1,1,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +6874,19307,Female,Loyal Customer,15,Personal Travel,Eco,299,3,4,3,4,3,3,5,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +6875,52424,Female,Loyal Customer,45,Personal Travel,Eco,493,1,5,1,2,2,5,5,2,2,1,2,4,2,3,10,12.0,neutral or dissatisfied +6876,16824,Female,Loyal Customer,57,Personal Travel,Eco,645,3,5,3,4,4,4,5,4,4,3,4,3,4,3,12,18.0,neutral or dissatisfied +6877,22071,Female,Loyal Customer,62,Personal Travel,Eco,304,4,4,4,4,2,5,4,2,2,4,2,4,2,5,0,0.0,neutral or dissatisfied +6878,127871,Male,Loyal Customer,36,Business travel,Business,2283,3,2,2,2,4,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +6879,15793,Female,Loyal Customer,56,Business travel,Business,3157,0,0,0,3,5,1,5,5,5,5,5,3,5,5,21,3.0,satisfied +6880,34059,Female,Loyal Customer,55,Business travel,Eco,1674,4,4,4,4,2,3,2,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +6881,62815,Female,Loyal Customer,39,Personal Travel,Eco,2486,2,2,2,3,2,3,3,1,3,3,3,3,2,3,0,12.0,neutral or dissatisfied +6882,81289,Male,Loyal Customer,62,Personal Travel,Eco,1020,3,2,3,3,4,3,4,4,4,5,3,4,4,4,0,32.0,neutral or dissatisfied +6883,63848,Male,disloyal Customer,37,Business travel,Business,1192,2,2,2,3,2,2,2,2,5,5,4,5,5,2,0,0.0,neutral or dissatisfied +6884,10073,Male,Loyal Customer,69,Personal Travel,Eco,441,3,3,3,1,1,3,1,1,5,1,3,2,5,1,24,17.0,neutral or dissatisfied +6885,35974,Male,Loyal Customer,58,Business travel,Eco Plus,231,4,3,4,3,4,4,4,4,3,4,4,1,3,4,0,1.0,satisfied +6886,24070,Male,Loyal Customer,45,Personal Travel,Business,866,1,5,1,4,2,5,4,3,3,1,3,3,3,5,0,0.0,neutral or dissatisfied +6887,3208,Male,Loyal Customer,50,Personal Travel,Eco,693,3,4,3,3,2,3,3,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +6888,10164,Female,Loyal Customer,52,Business travel,Business,429,4,4,4,4,4,4,5,4,4,4,4,4,4,4,6,3.0,satisfied +6889,21538,Male,Loyal Customer,57,Personal Travel,Eco,377,2,4,2,4,3,2,3,3,3,2,5,3,5,3,0,0.0,neutral or dissatisfied +6890,96705,Female,Loyal Customer,43,Business travel,Business,813,1,3,3,3,4,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +6891,74746,Female,Loyal Customer,12,Personal Travel,Eco,1431,3,4,3,3,4,3,4,4,4,2,4,3,4,4,75,71.0,neutral or dissatisfied +6892,75166,Male,disloyal Customer,35,Business travel,Business,1744,3,3,3,2,5,3,5,5,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +6893,106227,Male,Loyal Customer,63,Personal Travel,Eco,471,2,2,2,3,5,2,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +6894,57752,Female,Loyal Customer,33,Business travel,Business,2704,4,4,4,4,3,2,2,3,4,4,5,2,5,2,0,0.0,satisfied +6895,110888,Male,Loyal Customer,48,Business travel,Business,3932,5,5,5,5,2,4,5,4,4,4,4,5,4,4,5,3.0,satisfied +6896,8844,Male,Loyal Customer,41,Business travel,Business,1371,3,5,5,5,2,4,4,3,3,3,3,3,3,1,31,60.0,neutral or dissatisfied +6897,52479,Female,Loyal Customer,35,Personal Travel,Eco Plus,651,3,4,3,2,2,3,2,2,1,2,2,5,3,2,65,76.0,neutral or dissatisfied +6898,43947,Male,Loyal Customer,55,Business travel,Eco,408,2,3,3,3,3,2,3,3,2,1,3,3,4,3,0,0.0,satisfied +6899,103879,Male,Loyal Customer,61,Personal Travel,Eco,869,1,2,1,4,3,1,3,3,4,2,3,3,4,3,18,8.0,neutral or dissatisfied +6900,86063,Female,Loyal Customer,38,Business travel,Eco Plus,554,2,5,2,5,2,2,2,2,2,2,3,4,3,2,21,27.0,neutral or dissatisfied +6901,125759,Female,Loyal Customer,65,Business travel,Business,2943,3,3,3,3,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +6902,112006,Male,Loyal Customer,29,Business travel,Business,770,1,1,2,1,5,5,5,5,4,3,5,3,5,5,0,0.0,satisfied +6903,96014,Male,Loyal Customer,25,Business travel,Business,1865,5,5,5,5,5,5,5,5,5,5,4,3,4,5,12,0.0,satisfied +6904,50864,Male,Loyal Customer,40,Personal Travel,Eco,109,2,5,0,1,3,0,3,3,5,5,1,3,3,3,0,0.0,neutral or dissatisfied +6905,26396,Female,Loyal Customer,36,Business travel,Eco,957,3,5,5,5,3,2,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +6906,93695,Female,Loyal Customer,34,Business travel,Business,1452,1,2,2,2,5,3,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +6907,28985,Female,disloyal Customer,31,Business travel,Eco,1050,1,0,0,3,5,0,5,5,5,2,2,2,4,5,0,0.0,neutral or dissatisfied +6908,49488,Male,disloyal Customer,39,Business travel,Eco,156,2,5,2,1,5,2,5,5,3,1,1,3,1,5,0,0.0,neutral or dissatisfied +6909,80526,Male,Loyal Customer,40,Business travel,Business,2381,3,3,3,3,5,4,5,4,4,4,4,4,4,4,24,18.0,satisfied +6910,79568,Female,Loyal Customer,38,Business travel,Business,2243,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +6911,28525,Female,disloyal Customer,26,Business travel,Eco,1368,1,1,1,2,3,1,3,3,3,4,3,4,2,3,19,0.0,neutral or dissatisfied +6912,46151,Male,disloyal Customer,30,Business travel,Eco,604,2,5,2,4,2,2,2,2,3,5,2,1,1,2,2,0.0,neutral or dissatisfied +6913,75209,Male,Loyal Customer,27,Business travel,Business,1744,2,1,1,1,2,2,2,2,2,3,3,3,4,2,66,67.0,neutral or dissatisfied +6914,42235,Female,disloyal Customer,22,Business travel,Eco,329,3,1,3,2,5,3,1,5,1,4,2,4,3,5,15,0.0,neutral or dissatisfied +6915,60952,Female,Loyal Customer,30,Business travel,Business,888,2,4,4,4,2,2,2,2,1,1,3,2,2,2,0,0.0,neutral or dissatisfied +6916,7108,Female,Loyal Customer,46,Personal Travel,Eco,157,3,4,3,4,4,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +6917,1305,Female,Loyal Customer,62,Business travel,Business,2622,0,4,0,3,5,4,5,1,1,1,1,3,1,5,56,44.0,satisfied +6918,45651,Female,Loyal Customer,19,Personal Travel,Eco,260,5,3,5,3,1,5,1,1,3,3,2,4,2,1,0,1.0,satisfied +6919,127326,Female,Loyal Customer,44,Business travel,Business,2698,4,4,2,4,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +6920,51708,Female,Loyal Customer,64,Business travel,Business,2719,1,1,1,1,3,2,4,3,3,4,5,4,3,2,0,0.0,satisfied +6921,105979,Male,Loyal Customer,62,Personal Travel,Eco,2295,1,4,1,3,1,3,3,3,4,1,2,3,2,3,0,0.0,neutral or dissatisfied +6922,92385,Female,disloyal Customer,26,Business travel,Business,1489,0,0,0,2,3,0,3,3,3,2,4,3,5,3,3,0.0,satisfied +6923,48085,Female,Loyal Customer,43,Business travel,Business,2564,4,4,4,4,4,4,2,5,5,5,3,1,5,5,0,0.0,satisfied +6924,65937,Male,Loyal Customer,23,Business travel,Business,3718,4,4,4,4,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +6925,13999,Male,Loyal Customer,46,Business travel,Eco,160,4,5,5,5,4,4,4,4,1,2,4,3,4,4,0,0.0,neutral or dissatisfied +6926,45274,Female,Loyal Customer,21,Personal Travel,Business,222,2,3,2,3,5,2,1,5,1,1,4,1,3,5,12,0.0,neutral or dissatisfied +6927,21236,Female,Loyal Customer,64,Personal Travel,Eco,317,3,3,3,4,4,2,2,3,3,3,3,2,3,1,72,90.0,neutral or dissatisfied +6928,78815,Female,Loyal Customer,14,Personal Travel,Eco,447,2,5,1,4,2,1,2,2,5,5,2,4,1,2,0,0.0,neutral or dissatisfied +6929,96205,Female,Loyal Customer,44,Business travel,Eco,687,4,3,3,3,2,3,3,4,4,4,4,4,4,1,16,8.0,neutral or dissatisfied +6930,39666,Male,Loyal Customer,32,Business travel,Business,476,3,3,3,3,5,5,5,5,1,2,2,2,3,5,123,115.0,satisfied +6931,70487,Female,disloyal Customer,25,Business travel,Eco,867,2,2,2,4,4,2,4,4,4,1,3,3,3,4,2,14.0,neutral or dissatisfied +6932,94213,Male,disloyal Customer,22,Business travel,Eco,239,4,0,4,3,5,4,5,5,3,2,4,5,5,5,0,5.0,satisfied +6933,15627,Female,Loyal Customer,38,Personal Travel,Eco,229,4,4,4,3,4,4,4,4,4,5,5,4,4,4,0,4.0,neutral or dissatisfied +6934,2342,Male,disloyal Customer,28,Business travel,Eco Plus,925,4,4,4,3,3,4,3,3,3,4,4,3,4,3,0,24.0,neutral or dissatisfied +6935,108328,Male,disloyal Customer,28,Business travel,Business,1750,3,4,4,4,1,4,1,1,5,3,5,4,5,1,23,26.0,neutral or dissatisfied +6936,115833,Male,disloyal Customer,39,Business travel,Eco,325,1,0,0,3,5,0,5,5,1,1,2,4,5,5,1,0.0,neutral or dissatisfied +6937,24366,Male,Loyal Customer,52,Business travel,Eco,669,4,1,1,1,4,4,4,4,3,1,4,3,4,4,0,26.0,satisfied +6938,78418,Female,disloyal Customer,26,Business travel,Eco,453,2,0,2,1,2,2,2,2,1,3,2,2,1,2,5,1.0,neutral or dissatisfied +6939,63754,Male,disloyal Customer,37,Business travel,Business,1660,2,2,2,3,2,2,2,2,3,4,4,4,4,2,3,7.0,neutral or dissatisfied +6940,103803,Female,Loyal Customer,51,Business travel,Business,869,2,2,2,2,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +6941,46799,Male,Loyal Customer,63,Personal Travel,Business,964,4,5,4,2,5,4,5,5,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +6942,65261,Female,Loyal Customer,51,Business travel,Business,551,3,1,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +6943,79728,Male,Loyal Customer,44,Personal Travel,Eco,760,3,1,3,3,2,3,2,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +6944,92072,Female,Loyal Customer,40,Business travel,Business,1589,4,4,4,4,5,5,5,4,4,4,4,5,4,3,66,53.0,satisfied +6945,50697,Female,Loyal Customer,17,Personal Travel,Eco,266,2,0,2,1,4,2,3,4,3,2,4,5,4,4,0,0.0,neutral or dissatisfied +6946,18729,Female,Loyal Customer,48,Business travel,Business,917,1,1,1,1,5,1,3,4,4,4,4,1,4,5,0,0.0,satisfied +6947,49934,Male,Loyal Customer,39,Business travel,Eco,308,5,2,2,2,5,5,5,5,4,3,4,3,2,5,0,2.0,satisfied +6948,110087,Male,Loyal Customer,23,Business travel,Eco,1056,3,5,5,5,3,3,1,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +6949,64070,Female,Loyal Customer,38,Business travel,Business,3828,3,3,3,3,5,4,5,5,5,5,5,2,5,5,0,3.0,satisfied +6950,64915,Male,Loyal Customer,46,Business travel,Business,2288,2,4,4,4,2,3,3,2,2,2,2,2,2,1,76,67.0,neutral or dissatisfied +6951,27131,Male,Loyal Customer,54,Business travel,Eco,2681,4,3,3,3,4,4,4,5,3,4,5,4,3,4,0,0.0,satisfied +6952,57572,Male,Loyal Customer,40,Business travel,Business,1597,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +6953,102429,Male,Loyal Customer,22,Personal Travel,Eco,414,2,4,2,4,1,2,1,1,1,1,4,5,2,1,0,0.0,neutral or dissatisfied +6954,87432,Male,Loyal Customer,69,Personal Travel,Eco Plus,425,4,0,4,5,3,4,3,3,5,3,3,1,1,3,0,0.0,neutral or dissatisfied +6955,76402,Male,Loyal Customer,47,Business travel,Business,2674,3,3,3,3,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +6956,2049,Male,disloyal Customer,42,Business travel,Business,785,3,3,3,2,2,3,4,2,3,5,4,4,5,2,15,9.0,neutral or dissatisfied +6957,52715,Female,Loyal Customer,30,Business travel,Eco Plus,1162,5,1,4,1,5,5,5,5,5,5,4,1,4,5,30,13.0,satisfied +6958,70235,Male,Loyal Customer,34,Business travel,Eco Plus,1068,5,1,1,1,5,5,5,5,2,2,5,1,1,5,4,0.0,satisfied +6959,66604,Female,Loyal Customer,20,Personal Travel,Eco,761,2,4,2,2,3,2,2,3,3,4,4,1,5,3,0,0.0,neutral or dissatisfied +6960,2082,Female,Loyal Customer,40,Personal Travel,Eco,812,3,2,3,3,5,3,5,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +6961,63115,Male,Loyal Customer,47,Business travel,Business,2756,3,3,3,3,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +6962,105292,Female,Loyal Customer,41,Business travel,Business,2097,4,4,4,4,2,4,4,4,4,4,4,3,4,5,29,21.0,satisfied +6963,75422,Male,Loyal Customer,42,Business travel,Business,2342,5,5,5,5,4,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +6964,126863,Female,Loyal Customer,58,Personal Travel,Eco,2125,3,2,3,3,4,3,3,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +6965,36151,Male,Loyal Customer,65,Personal Travel,Eco,818,1,5,1,2,3,1,3,3,3,2,5,1,1,3,0,0.0,neutral or dissatisfied +6966,48029,Female,disloyal Customer,16,Business travel,Eco,1187,3,3,3,4,1,3,1,1,3,1,4,3,3,1,13,22.0,neutral or dissatisfied +6967,68196,Female,Loyal Customer,31,Business travel,Business,3041,3,3,3,3,4,4,4,4,3,4,5,5,4,4,8,0.0,satisfied +6968,107401,Female,Loyal Customer,15,Business travel,Business,3082,2,3,5,3,2,2,2,2,4,4,4,4,3,2,53,52.0,neutral or dissatisfied +6969,2797,Male,Loyal Customer,60,Personal Travel,Eco,765,2,5,3,4,1,3,1,1,5,4,4,4,4,1,17,10.0,neutral or dissatisfied +6970,83634,Male,disloyal Customer,23,Business travel,Eco,577,0,4,0,4,2,0,2,2,5,2,4,5,5,2,0,0.0,satisfied +6971,22727,Male,Loyal Customer,60,Personal Travel,Business,170,2,5,0,2,2,5,4,4,4,0,4,4,4,3,14,8.0,neutral or dissatisfied +6972,125767,Female,disloyal Customer,37,Business travel,Business,920,5,5,5,3,1,5,1,1,4,3,5,3,5,1,1,0.0,satisfied +6973,48374,Female,Loyal Customer,17,Personal Travel,Eco,587,2,4,2,1,2,2,1,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +6974,42117,Male,Loyal Customer,49,Business travel,Business,3331,2,4,4,4,3,4,3,2,2,2,2,4,2,4,41,47.0,neutral or dissatisfied +6975,110508,Male,disloyal Customer,37,Business travel,Eco Plus,442,3,3,3,3,5,3,5,5,1,3,4,1,3,5,0,0.0,neutral or dissatisfied +6976,4579,Female,Loyal Customer,51,Business travel,Business,1917,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,11.0,satisfied +6977,118164,Female,disloyal Customer,21,Business travel,Eco,1165,4,4,4,1,2,4,2,2,3,2,4,4,5,2,2,0.0,satisfied +6978,1166,Female,Loyal Customer,31,Personal Travel,Eco,89,5,2,0,3,3,0,3,3,3,4,3,2,3,3,1,0.0,satisfied +6979,19227,Male,Loyal Customer,44,Personal Travel,Eco,459,5,5,5,4,2,5,3,2,3,4,4,4,4,2,0,0.0,satisfied +6980,97080,Female,disloyal Customer,24,Business travel,Business,1476,4,3,4,2,3,4,3,3,3,4,5,3,4,3,13,16.0,satisfied +6981,50239,Female,Loyal Customer,58,Business travel,Business,2243,3,1,2,1,4,2,3,2,2,2,3,4,2,4,0,0.0,neutral or dissatisfied +6982,83595,Female,Loyal Customer,38,Business travel,Business,3758,3,2,3,3,5,4,5,5,5,5,5,3,5,5,29,34.0,satisfied +6983,4920,Female,Loyal Customer,67,Personal Travel,Eco,1020,3,4,3,4,4,5,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +6984,36802,Male,Loyal Customer,69,Personal Travel,Eco,2704,1,4,1,2,1,2,2,3,3,3,5,2,3,2,167,133.0,neutral or dissatisfied +6985,6053,Female,Loyal Customer,50,Personal Travel,Eco,925,3,5,3,1,3,5,5,5,5,3,3,5,5,3,0,19.0,neutral or dissatisfied +6986,83578,Male,disloyal Customer,30,Business travel,Eco,936,1,1,1,2,4,1,4,4,1,4,3,2,2,4,0,0.0,neutral or dissatisfied +6987,113075,Male,Loyal Customer,28,Business travel,Business,1941,2,1,1,1,2,1,2,2,4,4,4,4,4,2,9,12.0,neutral or dissatisfied +6988,19936,Female,Loyal Customer,65,Personal Travel,Eco,315,3,4,2,3,2,4,3,5,5,2,5,4,5,1,5,6.0,neutral or dissatisfied +6989,87022,Female,Loyal Customer,31,Business travel,Business,2240,1,1,1,1,5,5,5,5,5,3,4,4,4,5,0,0.0,satisfied +6990,118803,Male,Loyal Customer,42,Personal Travel,Eco,621,2,4,2,3,4,2,4,4,3,5,3,1,3,4,9,0.0,neutral or dissatisfied +6991,11118,Male,Loyal Customer,15,Personal Travel,Eco,216,1,5,0,3,5,0,5,5,4,3,5,2,1,5,79,82.0,neutral or dissatisfied +6992,62560,Female,disloyal Customer,31,Business travel,Business,1846,3,3,3,4,5,3,1,5,4,4,3,3,5,5,0,0.0,neutral or dissatisfied +6993,122187,Female,Loyal Customer,46,Business travel,Business,2070,2,2,4,2,5,5,5,4,4,4,4,4,4,5,0,3.0,satisfied +6994,47084,Female,Loyal Customer,35,Personal Travel,Eco,602,3,1,3,3,5,3,5,5,3,3,3,4,4,5,0,0.0,neutral or dissatisfied +6995,40058,Female,Loyal Customer,41,Business travel,Eco Plus,866,3,2,2,2,3,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +6996,33026,Female,Loyal Customer,27,Personal Travel,Eco,101,4,5,4,1,3,4,3,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +6997,121419,Female,disloyal Customer,45,Business travel,Business,331,2,2,2,2,4,2,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +6998,74562,Male,Loyal Customer,34,Business travel,Business,3768,3,2,2,2,3,3,2,3,3,2,3,1,3,4,0,2.0,neutral or dissatisfied +6999,300,Female,disloyal Customer,24,Business travel,Business,590,4,1,4,4,3,4,3,3,3,2,4,4,5,3,0,0.0,satisfied +7000,95737,Female,disloyal Customer,33,Business travel,Business,181,2,2,2,4,1,2,1,1,3,3,5,3,4,1,7,5.0,neutral or dissatisfied +7001,108353,Male,Loyal Customer,54,Business travel,Eco,290,5,4,4,4,5,5,5,5,1,3,2,3,3,5,4,0.0,satisfied +7002,115735,Male,Loyal Customer,44,Business travel,Business,373,2,4,4,4,3,4,4,2,2,2,2,4,2,1,33,29.0,neutral or dissatisfied +7003,102990,Female,Loyal Customer,53,Business travel,Business,786,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +7004,36898,Female,Loyal Customer,66,Personal Travel,Eco,1368,4,5,4,2,2,4,4,3,3,4,3,4,3,3,3,0.0,neutral or dissatisfied +7005,23987,Female,Loyal Customer,45,Business travel,Business,2976,4,4,4,4,4,2,1,3,3,3,3,5,3,5,0,0.0,satisfied +7006,99762,Female,Loyal Customer,18,Personal Travel,Eco,255,3,3,3,4,2,3,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +7007,68870,Female,disloyal Customer,43,Business travel,Eco,1061,2,2,2,4,4,2,4,4,1,4,3,1,3,4,0,0.0,neutral or dissatisfied +7008,109460,Female,Loyal Customer,40,Business travel,Business,1514,1,1,1,1,4,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +7009,38468,Male,Loyal Customer,15,Business travel,Business,3077,3,4,4,4,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +7010,75819,Female,Loyal Customer,7,Personal Travel,Eco Plus,868,3,1,3,1,3,3,2,3,1,3,1,3,1,3,2,0.0,neutral or dissatisfied +7011,4651,Male,Loyal Customer,48,Business travel,Business,3818,3,1,1,1,3,4,3,3,3,2,3,4,3,3,0,15.0,neutral or dissatisfied +7012,50048,Female,Loyal Customer,43,Business travel,Eco,109,3,2,4,4,5,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +7013,111423,Female,disloyal Customer,26,Business travel,Business,896,0,0,0,3,1,0,1,1,5,3,5,5,4,1,0,0.0,satisfied +7014,20048,Female,Loyal Customer,36,Business travel,Eco,607,4,4,4,4,4,3,4,4,5,2,2,1,4,4,0,0.0,satisfied +7015,60571,Female,Loyal Customer,55,Business travel,Business,1558,5,5,5,5,3,4,4,5,5,5,5,4,5,4,30,5.0,satisfied +7016,104102,Male,disloyal Customer,39,Business travel,Eco,297,3,0,4,3,4,4,4,4,2,1,4,4,4,4,0,0.0,neutral or dissatisfied +7017,84009,Male,Loyal Customer,64,Personal Travel,Eco,373,1,4,1,1,2,1,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +7018,41938,Female,Loyal Customer,41,Personal Travel,Eco,129,3,4,3,3,2,3,2,2,2,5,4,2,4,2,0,2.0,neutral or dissatisfied +7019,14827,Male,Loyal Customer,10,Personal Travel,Eco,314,1,4,1,4,2,1,2,2,2,1,3,1,4,2,43,33.0,neutral or dissatisfied +7020,66571,Male,disloyal Customer,23,Business travel,Eco,624,2,5,2,5,5,2,3,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +7021,35901,Female,Loyal Customer,41,Personal Travel,Eco Plus,1065,4,5,4,2,3,4,5,5,5,4,5,5,5,3,2,42.0,neutral or dissatisfied +7022,67852,Male,Loyal Customer,32,Personal Travel,Eco,1438,3,4,3,1,2,3,2,2,4,4,3,3,5,2,0,0.0,neutral or dissatisfied +7023,10538,Male,Loyal Customer,60,Business travel,Business,3786,1,1,1,1,4,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +7024,71948,Female,Loyal Customer,43,Business travel,Business,1437,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +7025,116745,Female,Loyal Customer,39,Personal Travel,Eco Plus,308,3,4,3,4,5,3,5,5,1,5,4,5,5,5,10,8.0,neutral or dissatisfied +7026,73517,Female,Loyal Customer,45,Business travel,Business,2793,3,3,3,3,3,5,5,4,4,4,4,4,4,4,38,33.0,satisfied +7027,52843,Male,Loyal Customer,22,Personal Travel,Eco,1721,4,5,4,2,2,4,2,2,5,2,5,3,4,2,8,1.0,satisfied +7028,79274,Male,Loyal Customer,26,Personal Travel,Eco,2454,3,2,3,1,3,5,5,1,4,1,1,5,2,5,0,0.0,neutral or dissatisfied +7029,66103,Female,Loyal Customer,56,Business travel,Business,2607,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +7030,81979,Male,Loyal Customer,45,Business travel,Business,1532,3,3,2,3,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +7031,15202,Female,disloyal Customer,15,Business travel,Eco,544,4,0,4,3,5,4,5,5,3,4,2,1,4,5,58,,neutral or dissatisfied +7032,8576,Female,disloyal Customer,26,Business travel,Eco,109,2,1,2,3,5,2,4,5,2,5,3,4,3,5,0,0.0,neutral or dissatisfied +7033,52850,Female,Loyal Customer,24,Personal Travel,Eco,1721,3,4,3,2,4,3,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +7034,97034,Female,Loyal Customer,34,Business travel,Business,1390,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +7035,83244,Female,Loyal Customer,51,Business travel,Business,1979,1,1,1,1,5,4,5,4,4,4,4,5,4,4,8,9.0,satisfied +7036,100064,Male,Loyal Customer,51,Personal Travel,Eco,220,2,5,2,3,4,2,4,4,3,5,5,4,5,4,31,30.0,neutral or dissatisfied +7037,117313,Female,Loyal Customer,22,Personal Travel,Eco Plus,646,3,1,3,3,5,3,5,5,4,2,4,2,4,5,11,12.0,neutral or dissatisfied +7038,94427,Male,Loyal Customer,48,Business travel,Business,2605,0,0,0,5,2,5,5,2,2,3,3,5,2,5,0,0.0,satisfied +7039,117899,Female,Loyal Customer,46,Business travel,Business,255,0,0,0,3,4,5,4,2,2,1,1,5,2,5,0,4.0,satisfied +7040,5834,Male,Loyal Customer,56,Business travel,Business,177,5,5,5,5,5,4,5,4,4,4,5,3,4,5,1,3.0,satisfied +7041,110797,Male,Loyal Customer,29,Personal Travel,Eco,997,1,2,1,3,2,1,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +7042,19051,Female,Loyal Customer,64,Business travel,Eco Plus,304,4,2,2,2,5,1,2,4,4,4,4,4,4,2,0,0.0,satisfied +7043,33756,Male,Loyal Customer,31,Business travel,Business,266,0,0,0,2,4,4,3,4,4,2,2,2,5,4,0,0.0,satisfied +7044,75813,Female,Loyal Customer,48,Personal Travel,Eco Plus,813,2,4,2,4,1,3,4,3,3,2,3,4,3,4,9,9.0,neutral or dissatisfied +7045,47792,Male,disloyal Customer,28,Business travel,Eco,817,3,3,3,4,5,3,5,5,3,2,2,2,5,5,0,6.0,neutral or dissatisfied +7046,83016,Male,Loyal Customer,46,Business travel,Business,2640,1,1,1,1,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +7047,57683,Male,Loyal Customer,56,Business travel,Business,3550,5,5,4,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +7048,22447,Male,Loyal Customer,35,Personal Travel,Eco,143,3,3,3,2,3,3,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +7049,27656,Male,Loyal Customer,45,Personal Travel,Business,1216,0,2,0,3,4,3,3,1,1,0,1,4,1,1,20,15.0,satisfied +7050,21553,Male,Loyal Customer,48,Business travel,Eco Plus,164,4,1,1,1,4,4,4,4,4,4,5,3,2,4,0,0.0,satisfied +7051,94663,Male,Loyal Customer,34,Business travel,Business,3849,1,2,5,2,1,4,3,1,1,1,1,3,1,2,2,0.0,neutral or dissatisfied +7052,117315,Male,Loyal Customer,38,Personal Travel,Eco Plus,368,2,3,3,3,2,3,4,2,3,4,4,4,4,2,66,54.0,neutral or dissatisfied +7053,85843,Female,Loyal Customer,37,Personal Travel,Eco,666,4,1,4,2,5,4,5,5,4,1,2,1,2,5,0,0.0,neutral or dissatisfied +7054,62417,Female,Loyal Customer,39,Business travel,Business,2457,2,3,3,3,4,3,3,2,2,2,2,4,2,1,8,0.0,neutral or dissatisfied +7055,123101,Male,Loyal Customer,50,Business travel,Eco,650,2,4,5,5,2,2,2,2,2,2,3,4,3,2,11,13.0,neutral or dissatisfied +7056,8333,Female,disloyal Customer,30,Business travel,Eco,661,4,1,4,3,5,4,1,5,4,1,3,1,4,5,0,7.0,neutral or dissatisfied +7057,90630,Female,Loyal Customer,25,Business travel,Business,581,1,5,5,5,1,2,1,1,3,4,4,2,4,1,1,0.0,neutral or dissatisfied +7058,61927,Female,Loyal Customer,34,Personal Travel,Eco,550,4,0,4,1,3,4,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +7059,115081,Male,disloyal Customer,43,Business travel,Business,358,2,2,2,3,5,2,5,5,1,5,4,3,3,5,0,0.0,neutral or dissatisfied +7060,53954,Male,Loyal Customer,44,Business travel,Business,1325,5,5,5,5,3,1,2,1,1,2,1,3,1,2,0,0.0,satisfied +7061,62279,Female,disloyal Customer,23,Business travel,Business,414,0,0,0,5,4,0,4,4,5,4,5,5,4,4,27,25.0,satisfied +7062,34782,Female,Loyal Customer,67,Personal Travel,Eco,209,1,3,1,4,3,1,4,1,1,1,1,2,1,5,0,0.0,neutral or dissatisfied +7063,88016,Male,Loyal Customer,39,Business travel,Business,270,0,0,0,4,3,4,5,5,5,5,5,3,5,3,1,12.0,satisfied +7064,77471,Male,Loyal Customer,35,Personal Travel,Eco,507,1,4,1,3,5,1,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +7065,56167,Male,disloyal Customer,29,Business travel,Eco,1400,4,4,4,3,2,4,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +7066,96039,Male,Loyal Customer,42,Business travel,Eco,1069,2,2,2,2,2,2,2,2,4,3,2,2,2,2,0,0.0,neutral or dissatisfied +7067,90710,Female,Loyal Customer,23,Business travel,Business,3795,3,5,5,5,3,3,3,3,3,5,2,3,2,3,0,2.0,neutral or dissatisfied +7068,58167,Male,disloyal Customer,30,Business travel,Business,925,0,0,0,3,4,0,4,4,4,2,5,4,5,4,25,7.0,satisfied +7069,125161,Female,Loyal Customer,39,Business travel,Business,2661,4,3,3,3,1,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +7070,99263,Female,Loyal Customer,42,Business travel,Business,833,1,1,1,1,3,4,5,4,4,4,4,3,4,3,1,0.0,satisfied +7071,4318,Male,disloyal Customer,20,Business travel,Business,589,0,4,0,4,4,0,4,4,4,3,4,4,4,4,0,0.0,satisfied +7072,21434,Female,disloyal Customer,24,Business travel,Eco,433,5,0,5,1,5,5,2,5,1,5,3,5,4,5,81,71.0,satisfied +7073,4678,Male,Loyal Customer,66,Business travel,Eco,364,2,5,5,5,2,2,2,2,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +7074,32786,Female,disloyal Customer,20,Business travel,Eco,101,2,0,2,5,2,2,2,2,5,4,3,3,5,2,0,0.0,neutral or dissatisfied +7075,48347,Female,Loyal Customer,57,Business travel,Eco,522,4,3,3,3,5,3,2,4,4,4,4,5,4,3,0,0.0,satisfied +7076,39219,Female,Loyal Customer,45,Business travel,Business,2656,1,1,2,1,1,3,2,5,5,5,5,5,5,5,2,0.0,satisfied +7077,11468,Male,Loyal Customer,26,Business travel,Eco Plus,247,1,5,5,5,1,1,2,1,2,1,4,4,4,1,0,8.0,neutral or dissatisfied +7078,119853,Female,Loyal Customer,34,Business travel,Business,3937,3,3,3,3,1,4,1,5,5,5,5,2,5,2,0,0.0,satisfied +7079,32699,Male,Loyal Customer,38,Business travel,Eco,216,3,2,2,2,3,3,3,3,4,2,3,3,4,3,0,0.0,neutral or dissatisfied +7080,117975,Male,Loyal Customer,28,Personal Travel,Eco,255,4,5,0,4,5,0,5,5,1,3,3,5,5,5,29,42.0,neutral or dissatisfied +7081,7927,Female,Loyal Customer,8,Personal Travel,Eco Plus,1020,1,0,0,2,4,0,1,4,3,5,5,3,5,4,0,0.0,neutral or dissatisfied +7082,82448,Male,Loyal Customer,52,Business travel,Business,502,1,1,1,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +7083,44545,Male,Loyal Customer,19,Personal Travel,Eco,157,2,5,2,1,1,2,1,1,3,3,4,5,5,1,0,0.0,neutral or dissatisfied +7084,17884,Male,Loyal Customer,7,Personal Travel,Eco,425,3,2,3,4,1,3,1,1,3,3,2,3,3,1,5,51.0,neutral or dissatisfied +7085,23357,Female,Loyal Customer,53,Personal Travel,Eco Plus,563,4,1,4,3,1,4,4,4,4,4,4,2,4,3,0,0.0,satisfied +7086,67301,Male,Loyal Customer,53,Business travel,Business,964,5,5,5,5,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +7087,89594,Female,disloyal Customer,22,Business travel,Business,1035,5,4,5,1,5,5,2,5,5,2,5,4,4,5,0,,satisfied +7088,55775,Female,Loyal Customer,30,Business travel,Eco,646,3,2,2,2,3,3,3,3,4,4,3,1,2,3,0,0.0,neutral or dissatisfied +7089,29807,Male,Loyal Customer,35,Business travel,Business,3483,3,3,3,3,4,2,2,4,4,4,4,5,4,4,0,5.0,satisfied +7090,1881,Female,Loyal Customer,20,Personal Travel,Eco,931,3,4,3,1,5,3,4,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +7091,42398,Female,Loyal Customer,29,Business travel,Eco Plus,834,2,2,2,2,2,2,2,2,3,5,4,4,4,2,23,28.0,neutral or dissatisfied +7092,121095,Female,Loyal Customer,31,Personal Travel,Eco,1558,1,5,1,4,3,1,3,3,4,4,4,4,5,3,25,43.0,neutral or dissatisfied +7093,79368,Female,Loyal Customer,45,Business travel,Business,502,4,4,4,4,5,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +7094,76554,Female,Loyal Customer,39,Business travel,Business,1554,3,5,5,5,5,2,1,3,3,2,3,2,3,4,0,15.0,neutral or dissatisfied +7095,107196,Female,Loyal Customer,19,Personal Travel,Eco,668,3,5,3,4,2,3,2,2,3,3,4,4,4,2,0,0.0,neutral or dissatisfied +7096,109646,Female,Loyal Customer,47,Business travel,Business,973,1,1,1,1,4,4,4,2,2,3,2,3,2,4,0,8.0,satisfied +7097,6245,Female,Loyal Customer,65,Personal Travel,Eco,594,2,5,2,3,1,2,2,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +7098,66025,Male,disloyal Customer,24,Business travel,Eco,1055,2,2,2,3,2,2,2,2,3,5,4,1,4,2,64,63.0,neutral or dissatisfied +7099,95231,Female,Loyal Customer,70,Personal Travel,Eco,528,2,4,2,2,2,5,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +7100,95472,Male,Loyal Customer,58,Business travel,Business,2059,2,2,2,2,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +7101,62333,Female,Loyal Customer,59,Personal Travel,Eco,236,3,5,3,1,4,4,3,3,3,3,5,4,3,2,0,0.0,neutral or dissatisfied +7102,20222,Male,disloyal Customer,37,Business travel,Business,228,5,5,5,2,4,5,4,4,2,2,5,1,4,4,0,0.0,satisfied +7103,51262,Female,Loyal Customer,34,Business travel,Eco Plus,110,5,4,1,4,5,5,5,5,2,1,5,3,5,5,28,19.0,satisfied +7104,104026,Female,Loyal Customer,58,Business travel,Business,3028,4,4,4,4,4,5,5,4,4,4,4,4,4,3,14,0.0,satisfied +7105,73317,Female,Loyal Customer,43,Business travel,Business,1197,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7106,2317,Female,Loyal Customer,70,Personal Travel,Eco,691,4,2,4,3,3,3,3,4,4,4,4,3,4,1,16,13.0,neutral or dissatisfied +7107,98849,Male,Loyal Customer,21,Personal Travel,Eco Plus,1482,4,5,3,3,1,3,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +7108,122797,Female,disloyal Customer,24,Business travel,Eco,599,3,0,3,3,1,3,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +7109,114707,Female,Loyal Customer,41,Business travel,Business,446,5,5,5,5,5,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +7110,87399,Female,Loyal Customer,60,Personal Travel,Eco,425,2,0,2,5,2,4,5,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +7111,88647,Female,Loyal Customer,19,Personal Travel,Eco,240,3,5,3,1,2,3,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +7112,92075,Female,Loyal Customer,44,Business travel,Business,1522,2,2,2,2,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +7113,23194,Female,Loyal Customer,37,Business travel,Eco Plus,250,5,4,4,4,5,5,5,5,1,3,4,4,2,5,0,0.0,satisfied +7114,99892,Male,disloyal Customer,24,Business travel,Eco,738,3,3,3,3,3,3,3,3,1,1,2,3,3,3,0,0.0,neutral or dissatisfied +7115,35013,Male,disloyal Customer,28,Business travel,Eco,740,4,4,4,4,1,4,1,1,2,1,5,4,4,1,10,54.0,satisfied +7116,35836,Female,disloyal Customer,43,Business travel,Eco,1023,2,2,2,4,2,2,2,2,2,2,4,4,4,2,63,106.0,neutral or dissatisfied +7117,41345,Male,disloyal Customer,48,Business travel,Business,956,3,3,3,3,5,3,5,5,2,4,3,2,4,5,89,102.0,neutral or dissatisfied +7118,10569,Male,Loyal Customer,48,Business travel,Eco,301,3,1,3,3,3,3,3,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +7119,123044,Male,Loyal Customer,37,Business travel,Business,3385,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +7120,56509,Male,Loyal Customer,44,Business travel,Business,2880,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +7121,54682,Male,disloyal Customer,18,Business travel,Eco,956,2,2,2,4,5,2,5,5,3,1,4,3,4,5,1,0.0,neutral or dissatisfied +7122,49864,Male,Loyal Customer,37,Business travel,Business,1577,2,2,2,2,2,1,5,4,4,4,4,3,4,2,0,0.0,satisfied +7123,97827,Female,Loyal Customer,25,Business travel,Business,3425,3,4,4,4,3,3,3,3,4,2,4,3,4,3,66,76.0,neutral or dissatisfied +7124,9863,Male,Loyal Customer,17,Personal Travel,Eco,717,3,5,3,1,3,3,3,4,3,5,4,3,5,3,131,122.0,neutral or dissatisfied +7125,79143,Female,Loyal Customer,41,Personal Travel,Eco Plus,226,2,5,2,2,5,5,4,2,2,2,2,4,2,5,52,42.0,neutral or dissatisfied +7126,16049,Male,Loyal Customer,34,Business travel,Business,3871,5,5,5,5,2,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +7127,70605,Male,Loyal Customer,59,Personal Travel,Eco,2611,2,1,2,1,2,1,1,3,1,1,1,1,3,1,0,0.0,neutral or dissatisfied +7128,54628,Female,Loyal Customer,34,Business travel,Business,2852,5,5,5,5,5,2,1,5,5,5,5,3,5,2,0,0.0,satisfied +7129,38248,Male,Loyal Customer,36,Business travel,Eco,1050,1,3,3,3,1,1,1,1,4,4,2,2,2,1,0,0.0,neutral or dissatisfied +7130,26687,Female,Loyal Customer,68,Personal Travel,Eco,515,3,5,3,1,2,4,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +7131,17096,Female,Loyal Customer,30,Business travel,Business,1604,3,3,3,3,4,4,4,4,1,1,2,4,5,4,0,0.0,satisfied +7132,28132,Male,disloyal Customer,27,Business travel,Eco,550,3,3,3,3,2,3,2,2,4,2,1,2,5,2,0,0.0,neutral or dissatisfied +7133,52045,Male,disloyal Customer,20,Business travel,Business,639,0,0,0,3,5,0,2,5,4,4,5,5,4,5,25,31.0,satisfied +7134,42125,Female,Loyal Customer,16,Personal Travel,Eco,964,3,4,3,3,1,3,1,1,4,4,4,3,5,1,0,6.0,neutral or dissatisfied +7135,124314,Female,Loyal Customer,34,Business travel,Business,2200,2,2,2,2,1,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +7136,18131,Female,disloyal Customer,26,Business travel,Eco,120,4,4,4,4,3,4,3,3,2,2,1,2,2,3,0,0.0,neutral or dissatisfied +7137,100140,Female,Loyal Customer,41,Business travel,Business,523,3,3,3,3,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +7138,24409,Female,Loyal Customer,32,Business travel,Business,3267,2,2,2,2,5,5,5,5,4,4,1,2,1,5,0,0.0,satisfied +7139,29613,Female,Loyal Customer,31,Business travel,Business,1448,3,5,5,5,3,3,3,3,4,2,2,4,2,3,32,30.0,neutral or dissatisfied +7140,100379,Female,Loyal Customer,56,Personal Travel,Eco,1092,1,4,1,4,3,4,3,4,4,1,4,5,4,4,43,58.0,neutral or dissatisfied +7141,34913,Female,Loyal Customer,39,Business travel,Eco,187,5,1,1,1,5,5,5,5,3,4,5,1,5,5,0,0.0,satisfied +7142,44703,Female,Loyal Customer,14,Personal Travel,Eco,67,5,5,5,4,4,5,4,4,1,3,2,5,2,4,0,0.0,satisfied +7143,48401,Female,Loyal Customer,23,Business travel,Eco Plus,522,3,4,4,4,3,3,2,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +7144,128230,Female,Loyal Customer,62,Personal Travel,Eco,602,1,3,1,3,3,2,2,4,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +7145,119828,Male,Loyal Customer,25,Business travel,Business,3867,3,4,5,4,3,3,3,3,4,4,3,2,2,3,34,16.0,neutral or dissatisfied +7146,4779,Female,Loyal Customer,44,Business travel,Business,2825,1,1,1,1,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +7147,13326,Female,Loyal Customer,23,Personal Travel,Business,748,3,5,3,2,5,3,5,5,4,2,4,4,4,5,36,33.0,neutral or dissatisfied +7148,13344,Male,Loyal Customer,25,Business travel,Eco,748,4,3,3,3,4,4,5,4,2,2,5,2,5,4,0,0.0,satisfied +7149,34555,Female,Loyal Customer,38,Business travel,Eco,1598,2,3,3,3,2,3,2,2,4,4,5,3,2,2,0,0.0,satisfied +7150,13034,Female,Loyal Customer,68,Personal Travel,Eco,304,3,4,3,3,2,4,4,2,2,3,4,5,2,3,16,56.0,neutral or dissatisfied +7151,662,Female,Loyal Customer,48,Business travel,Business,102,4,3,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +7152,33042,Female,Loyal Customer,41,Personal Travel,Eco,101,1,4,1,3,4,1,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +7153,91689,Male,Loyal Customer,15,Personal Travel,Business,588,3,4,3,4,1,3,1,1,3,4,5,5,5,1,13,21.0,neutral or dissatisfied +7154,19046,Female,Loyal Customer,31,Business travel,Business,2526,5,5,5,5,5,5,5,3,2,3,5,5,5,5,182,185.0,satisfied +7155,13400,Female,Loyal Customer,65,Personal Travel,Eco,505,3,4,3,1,3,5,5,2,2,3,2,3,2,3,59,49.0,neutral or dissatisfied +7156,107777,Female,Loyal Customer,69,Business travel,Eco Plus,405,3,2,2,2,5,4,3,2,2,3,2,3,2,2,14,12.0,neutral or dissatisfied +7157,33343,Female,Loyal Customer,42,Business travel,Eco,2399,5,2,2,2,4,4,3,5,5,5,5,3,5,1,2,0.0,satisfied +7158,6770,Male,disloyal Customer,26,Business travel,Business,235,5,0,5,1,2,5,2,2,5,4,5,3,4,2,25,23.0,satisfied +7159,59365,Female,disloyal Customer,24,Business travel,Eco,1407,2,2,2,4,1,2,1,1,4,5,2,3,3,1,5,0.0,neutral or dissatisfied +7160,66688,Male,Loyal Customer,30,Business travel,Business,3427,3,5,5,5,3,3,3,4,4,4,4,3,2,3,151,147.0,neutral or dissatisfied +7161,18909,Female,Loyal Customer,49,Personal Travel,Eco,448,1,5,2,2,4,4,1,2,2,2,3,4,2,2,64,60.0,neutral or dissatisfied +7162,95293,Male,Loyal Customer,34,Personal Travel,Eco,239,1,4,1,2,2,1,2,2,5,4,5,3,5,2,17,8.0,neutral or dissatisfied +7163,87514,Female,Loyal Customer,17,Personal Travel,Eco,373,4,5,4,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +7164,16063,Male,disloyal Customer,42,Business travel,Eco,744,2,2,2,4,4,2,4,4,5,4,2,3,2,4,0,0.0,neutral or dissatisfied +7165,1336,Female,disloyal Customer,23,Business travel,Eco,134,3,4,3,3,1,3,1,1,4,4,5,3,4,1,0,1.0,neutral or dissatisfied +7166,13222,Female,Loyal Customer,26,Business travel,Business,1683,4,4,4,4,3,3,3,3,3,2,2,5,3,3,42,28.0,satisfied +7167,44395,Female,Loyal Customer,45,Business travel,Eco,265,4,1,2,1,4,1,1,4,4,4,4,5,4,3,5,0.0,satisfied +7168,128734,Male,Loyal Customer,30,Business travel,Business,1464,4,4,4,4,5,5,5,5,5,5,4,3,5,5,0,0.0,satisfied +7169,23845,Male,disloyal Customer,52,Business travel,Business,552,1,1,1,4,5,1,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +7170,116183,Female,Loyal Customer,55,Personal Travel,Eco,480,3,4,3,4,1,3,4,1,1,3,3,1,1,1,8,0.0,neutral or dissatisfied +7171,42097,Female,Loyal Customer,31,Business travel,Business,996,1,1,1,1,2,2,2,2,5,3,2,1,2,2,0,0.0,satisfied +7172,118646,Female,Loyal Customer,50,Business travel,Business,368,1,1,1,1,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +7173,124372,Male,Loyal Customer,36,Business travel,Business,808,1,1,1,1,4,4,5,5,5,4,5,3,5,3,0,0.0,satisfied +7174,103510,Female,Loyal Customer,50,Business travel,Eco,1047,3,3,3,3,2,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +7175,109618,Female,Loyal Customer,17,Business travel,Business,808,4,4,4,4,4,4,4,3,5,4,5,4,3,4,224,221.0,satisfied +7176,39130,Female,Loyal Customer,61,Business travel,Business,228,4,5,5,5,4,4,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +7177,18155,Female,Loyal Customer,27,Business travel,Business,1669,4,4,4,4,5,4,5,5,3,4,5,4,5,5,0,0.0,satisfied +7178,3507,Female,disloyal Customer,23,Business travel,Business,968,4,0,5,3,2,5,2,2,5,5,5,4,4,2,26,29.0,satisfied +7179,46627,Female,disloyal Customer,24,Business travel,Eco,125,2,2,2,3,2,2,2,2,4,1,3,1,2,2,0,0.0,neutral or dissatisfied +7180,22051,Male,Loyal Customer,35,Business travel,Eco,304,5,2,4,2,5,5,5,5,2,2,2,3,5,5,0,0.0,satisfied +7181,102145,Male,disloyal Customer,21,Business travel,Eco,488,4,4,4,1,1,4,1,1,4,5,4,3,4,1,0,0.0,satisfied +7182,104902,Female,Loyal Customer,52,Business travel,Business,1565,5,5,5,5,3,5,4,4,4,4,4,4,4,5,0,1.0,satisfied +7183,50510,Male,Loyal Customer,8,Personal Travel,Eco,109,3,5,3,1,1,3,3,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +7184,44041,Male,Loyal Customer,45,Business travel,Eco,287,1,4,3,3,1,1,1,1,2,4,3,4,4,1,0,0.0,neutral or dissatisfied +7185,46470,Female,disloyal Customer,20,Business travel,Eco,73,2,4,2,4,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +7186,112948,Female,Loyal Customer,18,Personal Travel,Eco,1242,2,5,2,3,4,2,5,4,5,5,3,4,2,4,14,0.0,neutral or dissatisfied +7187,10513,Male,Loyal Customer,60,Business travel,Business,140,4,4,5,4,5,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +7188,49170,Male,Loyal Customer,32,Business travel,Business,337,5,5,5,5,3,4,3,3,3,3,5,5,5,3,0,11.0,satisfied +7189,101529,Male,Loyal Customer,44,Personal Travel,Eco,345,3,2,3,2,3,3,3,3,1,4,1,1,1,3,0,0.0,neutral or dissatisfied +7190,125994,Male,Loyal Customer,69,Personal Travel,Business,631,3,5,4,5,3,5,5,2,2,4,5,4,2,3,3,0.0,neutral or dissatisfied +7191,126906,Female,Loyal Customer,51,Business travel,Business,2045,3,3,3,3,2,4,5,5,5,5,5,3,5,5,8,11.0,satisfied +7192,14686,Male,disloyal Customer,35,Business travel,Eco,419,2,3,2,3,2,3,3,2,4,4,4,3,4,3,162,131.0,neutral or dissatisfied +7193,46430,Female,Loyal Customer,16,Personal Travel,Eco,649,2,3,2,4,5,2,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +7194,106863,Female,Loyal Customer,53,Business travel,Business,3044,1,1,1,1,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +7195,22936,Male,Loyal Customer,40,Business travel,Eco,817,4,3,3,3,4,4,4,4,2,4,1,2,4,4,19,5.0,satisfied +7196,85353,Male,Loyal Customer,69,Business travel,Eco Plus,696,2,2,2,2,2,2,2,2,1,5,3,4,4,2,0,0.0,neutral or dissatisfied +7197,20502,Female,Loyal Customer,25,Personal Travel,Eco,139,2,4,2,3,5,2,5,5,3,4,4,4,4,5,9,22.0,neutral or dissatisfied +7198,80363,Female,disloyal Customer,38,Business travel,Eco,368,2,3,2,2,5,2,5,5,1,4,3,3,2,5,4,0.0,neutral or dissatisfied +7199,17778,Female,Loyal Customer,50,Business travel,Eco,1214,4,5,5,5,4,4,4,3,3,4,3,4,5,4,148,129.0,satisfied +7200,12357,Female,Loyal Customer,35,Business travel,Eco,305,3,1,1,1,3,3,3,3,1,5,3,4,3,3,0,0.0,neutral or dissatisfied +7201,126259,Female,disloyal Customer,27,Business travel,Eco,600,1,2,1,3,1,2,2,3,3,4,3,2,3,2,244,235.0,neutral or dissatisfied +7202,89783,Male,Loyal Customer,41,Personal Travel,Eco,1080,3,4,3,3,3,2,2,4,2,4,5,2,5,2,149,149.0,neutral or dissatisfied +7203,28418,Female,Loyal Customer,27,Business travel,Business,1399,4,4,4,4,5,5,5,5,1,4,4,4,3,5,0,0.0,satisfied +7204,124503,Male,Loyal Customer,46,Business travel,Eco,930,4,5,4,4,5,4,5,5,3,2,4,3,4,5,1,0.0,neutral or dissatisfied +7205,85116,Female,Loyal Customer,60,Business travel,Business,813,2,2,2,2,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +7206,92125,Male,Loyal Customer,21,Personal Travel,Eco,1589,3,5,3,3,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +7207,82312,Male,Loyal Customer,53,Business travel,Business,1855,3,3,4,3,5,4,5,2,2,2,2,5,2,3,22,8.0,satisfied +7208,25608,Male,Loyal Customer,47,Business travel,Eco,666,4,3,3,3,4,4,4,4,5,5,2,4,2,4,6,2.0,satisfied +7209,46226,Male,Loyal Customer,46,Business travel,Eco,594,4,3,5,5,4,4,4,4,2,5,1,2,3,4,55,49.0,satisfied +7210,78778,Male,Loyal Customer,59,Business travel,Business,1730,3,3,3,3,3,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +7211,59247,Female,Loyal Customer,57,Business travel,Business,3801,5,5,5,5,5,5,5,3,3,4,5,5,4,5,75,95.0,satisfied +7212,78055,Male,Loyal Customer,47,Personal Travel,Eco,332,2,5,2,3,2,2,2,2,1,3,4,1,4,2,39,23.0,neutral or dissatisfied +7213,107092,Male,Loyal Customer,60,Business travel,Eco,562,2,4,4,4,2,2,2,2,1,1,2,4,2,2,38,32.0,neutral or dissatisfied +7214,99331,Female,Loyal Customer,24,Personal Travel,Eco,448,3,5,5,3,2,5,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +7215,5662,Male,Loyal Customer,53,Business travel,Business,2072,5,5,5,5,4,4,4,3,3,4,3,4,3,4,9,15.0,satisfied +7216,25897,Female,Loyal Customer,57,Personal Travel,Eco,907,3,5,3,1,5,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +7217,33689,Male,Loyal Customer,58,Business travel,Business,1533,5,5,5,5,1,1,3,5,5,5,5,3,5,1,0,0.0,satisfied +7218,44344,Male,Loyal Customer,11,Personal Travel,Eco Plus,230,3,4,0,4,4,0,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +7219,55994,Male,Loyal Customer,52,Business travel,Business,2586,5,1,5,5,5,5,5,3,2,5,5,5,4,5,112,124.0,satisfied +7220,62103,Male,Loyal Customer,7,Personal Travel,Business,2565,5,4,5,4,5,5,5,5,3,4,4,1,4,5,0,0.0,satisfied +7221,93565,Female,Loyal Customer,33,Business travel,Business,159,3,3,3,3,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +7222,37645,Female,Loyal Customer,10,Personal Travel,Eco,1144,3,5,3,4,2,3,2,2,4,3,5,3,5,2,16,0.0,neutral or dissatisfied +7223,14444,Female,Loyal Customer,40,Business travel,Business,674,1,3,1,1,4,4,3,5,5,5,5,5,5,5,0,0.0,satisfied +7224,58103,Male,Loyal Customer,49,Personal Travel,Eco,589,4,3,4,3,3,4,3,3,2,1,4,2,1,3,1,0.0,satisfied +7225,42965,Female,Loyal Customer,54,Business travel,Business,3732,2,2,2,2,5,4,3,5,5,5,5,4,5,1,0,0.0,satisfied +7226,34606,Female,Loyal Customer,29,Personal Travel,Eco,1598,1,4,1,3,5,1,2,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +7227,101519,Female,Loyal Customer,25,Personal Travel,Eco,345,1,4,1,4,4,1,4,4,4,1,4,1,3,4,0,0.0,neutral or dissatisfied +7228,23724,Female,disloyal Customer,27,Business travel,Eco Plus,196,2,3,3,4,4,3,2,4,2,1,4,4,3,4,0,0.0,neutral or dissatisfied +7229,18147,Female,Loyal Customer,66,Personal Travel,Business,306,4,4,3,3,2,3,4,5,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +7230,79140,Female,Loyal Customer,23,Business travel,Eco Plus,356,1,2,3,3,1,1,4,1,4,5,4,3,3,1,0,9.0,neutral or dissatisfied +7231,79998,Female,Loyal Customer,67,Personal Travel,Eco,1010,2,4,2,3,5,5,4,2,2,2,4,4,2,2,0,4.0,neutral or dissatisfied +7232,3618,Male,disloyal Customer,39,Business travel,Business,427,4,4,4,3,2,4,4,2,5,4,5,4,4,2,20,26.0,neutral or dissatisfied +7233,61459,Male,Loyal Customer,28,Business travel,Business,2419,5,5,3,5,4,4,4,4,3,3,4,4,4,4,8,0.0,satisfied +7234,33350,Female,Loyal Customer,16,Business travel,Business,2614,5,5,5,5,4,4,4,4,5,2,4,2,3,4,0,0.0,satisfied +7235,40448,Female,disloyal Customer,38,Business travel,Eco,150,2,0,3,1,3,3,3,3,3,1,4,3,5,3,0,0.0,neutral or dissatisfied +7236,8539,Male,Loyal Customer,59,Business travel,Business,3418,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +7237,33502,Female,Loyal Customer,30,Business travel,Business,965,2,2,5,2,3,3,3,3,1,4,5,1,5,3,17,23.0,satisfied +7238,108844,Male,disloyal Customer,42,Business travel,Business,2139,2,1,1,3,2,2,3,2,5,5,5,5,4,2,0,5.0,neutral or dissatisfied +7239,7285,Male,Loyal Customer,10,Personal Travel,Eco,135,3,4,0,4,0,4,4,4,3,4,5,4,5,4,489,491.0,neutral or dissatisfied +7240,39456,Male,Loyal Customer,49,Personal Travel,Eco,129,3,2,3,3,3,3,3,3,4,5,2,2,3,3,0,10.0,neutral or dissatisfied +7241,100255,Female,Loyal Customer,45,Business travel,Business,1708,5,5,5,5,3,4,4,4,4,4,4,5,4,3,5,0.0,satisfied +7242,15054,Female,Loyal Customer,56,Business travel,Eco,176,5,3,3,3,1,3,3,5,5,5,5,1,5,3,0,0.0,satisfied +7243,36768,Male,Loyal Customer,44,Business travel,Business,2704,2,2,2,2,1,2,2,1,1,3,3,2,5,2,0,1.0,neutral or dissatisfied +7244,11233,Female,Loyal Customer,69,Personal Travel,Eco,163,0,4,0,3,1,2,3,2,2,0,2,1,2,4,2,0.0,satisfied +7245,114408,Male,disloyal Customer,40,Business travel,Business,337,5,0,0,3,2,0,2,2,5,2,5,3,5,2,8,8.0,satisfied +7246,20520,Male,disloyal Customer,27,Business travel,Business,133,5,5,5,2,2,0,2,2,3,4,5,3,4,2,0,0.0,satisfied +7247,49445,Female,Loyal Customer,35,Business travel,Business,2584,1,1,1,1,3,3,3,5,5,5,5,2,5,2,27,28.0,satisfied +7248,26113,Female,disloyal Customer,27,Business travel,Business,545,4,4,4,3,3,4,3,3,4,3,5,5,4,3,8,0.0,satisfied +7249,30985,Male,Loyal Customer,50,Personal Travel,Eco,1476,3,1,3,4,5,3,5,5,3,4,4,1,4,5,0,2.0,neutral or dissatisfied +7250,61002,Female,Loyal Customer,23,Business travel,Business,2211,4,5,5,5,4,4,4,4,1,5,3,4,3,4,38,31.0,neutral or dissatisfied +7251,101867,Female,Loyal Customer,18,Business travel,Eco,1747,0,5,5,5,0,1,4,0,4,3,4,2,4,0,86,59.0,neutral or dissatisfied +7252,22214,Female,Loyal Customer,57,Personal Travel,Eco,633,1,5,1,1,5,5,4,2,2,1,3,4,2,4,4,0.0,neutral or dissatisfied +7253,75543,Female,disloyal Customer,24,Business travel,Business,337,5,0,4,3,5,4,5,5,3,2,5,3,4,5,0,0.0,satisfied +7254,29622,Male,Loyal Customer,9,Business travel,Business,1448,1,1,1,1,5,5,5,5,1,4,5,1,3,5,0,0.0,satisfied +7255,101739,Female,Loyal Customer,52,Business travel,Business,1590,3,3,3,3,2,5,5,5,5,5,5,4,5,5,0,11.0,satisfied +7256,36023,Male,Loyal Customer,31,Business travel,Business,2653,2,5,5,5,2,2,2,2,3,1,4,1,4,2,0,0.0,neutral or dissatisfied +7257,122533,Female,Loyal Customer,25,Business travel,Business,500,5,5,4,5,5,5,5,5,4,5,5,3,5,5,0,0.0,satisfied +7258,24962,Female,Loyal Customer,53,Business travel,Eco,226,5,3,3,3,4,1,4,5,5,5,5,3,5,5,8,0.0,satisfied +7259,33538,Female,Loyal Customer,47,Business travel,Business,474,2,1,2,2,5,5,4,3,3,4,3,5,3,5,0,12.0,satisfied +7260,1492,Male,Loyal Customer,26,Business travel,Business,2891,5,5,5,5,5,4,5,5,4,2,4,5,5,5,4,0.0,satisfied +7261,38068,Male,Loyal Customer,31,Business travel,Business,2824,1,1,4,1,5,5,5,5,2,1,3,3,5,5,7,0.0,satisfied +7262,107592,Male,disloyal Customer,39,Business travel,Business,423,3,3,3,3,3,3,4,3,4,4,5,3,4,3,1,0.0,neutral or dissatisfied +7263,44906,Male,Loyal Customer,22,Business travel,Business,3174,3,3,3,3,4,4,4,4,1,5,5,5,5,4,0,30.0,satisfied +7264,125677,Male,Loyal Customer,29,Business travel,Business,759,1,2,2,2,1,1,1,1,1,1,3,3,3,1,1,0.0,neutral or dissatisfied +7265,73272,Female,Loyal Customer,56,Business travel,Business,1182,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +7266,89039,Female,Loyal Customer,46,Business travel,Business,1892,3,3,3,3,5,3,4,5,5,5,5,4,5,3,14,3.0,satisfied +7267,62796,Female,Loyal Customer,61,Personal Travel,Eco,2615,3,4,3,1,3,3,3,5,2,4,5,3,5,3,0,14.0,neutral or dissatisfied +7268,96535,Female,Loyal Customer,7,Personal Travel,Eco,436,2,4,2,4,1,2,1,1,1,4,3,1,4,1,0,0.0,neutral or dissatisfied +7269,89020,Male,Loyal Customer,60,Business travel,Business,2139,4,1,1,1,2,2,3,4,4,4,4,2,4,2,3,0.0,neutral or dissatisfied +7270,43141,Female,Loyal Customer,27,Personal Travel,Eco Plus,192,3,4,3,3,1,3,1,1,3,5,5,4,4,1,0,0.0,neutral or dissatisfied +7271,55838,Male,disloyal Customer,41,Business travel,Eco,1396,2,2,2,3,3,2,2,3,4,5,3,2,4,3,20,1.0,neutral or dissatisfied +7272,15755,Female,Loyal Customer,42,Business travel,Business,1990,5,5,4,5,5,1,5,2,2,2,2,5,2,4,0,0.0,satisfied +7273,56353,Male,Loyal Customer,40,Personal Travel,Eco,200,3,4,3,2,1,3,1,1,3,3,1,4,5,1,0,0.0,neutral or dissatisfied +7274,81716,Male,Loyal Customer,44,Business travel,Business,2853,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +7275,104209,Male,Loyal Customer,58,Business travel,Business,3171,3,3,3,3,2,5,4,5,5,5,5,4,5,3,64,63.0,satisfied +7276,102136,Female,Loyal Customer,40,Business travel,Business,1788,5,5,5,5,4,4,4,5,5,5,5,5,5,5,84,92.0,satisfied +7277,26235,Male,Loyal Customer,55,Personal Travel,Eco,404,3,4,3,3,2,3,2,2,3,2,4,5,4,2,0,13.0,neutral or dissatisfied +7278,32587,Female,disloyal Customer,43,Business travel,Eco,163,2,0,2,4,4,2,4,4,4,3,2,4,5,4,0,3.0,neutral or dissatisfied +7279,124687,Female,Loyal Customer,45,Business travel,Business,1750,2,4,4,4,2,2,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +7280,18516,Female,Loyal Customer,26,Business travel,Eco,190,0,5,0,3,2,0,2,2,1,4,4,2,3,2,0,0.0,satisfied +7281,9952,Male,Loyal Customer,11,Business travel,Business,2040,5,5,5,5,5,5,5,5,3,4,5,3,4,5,0,0.0,satisfied +7282,78427,Male,Loyal Customer,59,Business travel,Business,2349,5,5,5,5,3,5,4,5,5,5,5,5,5,3,47,77.0,satisfied +7283,66681,Female,Loyal Customer,26,Business travel,Business,802,4,5,5,5,4,4,4,4,4,5,4,2,3,4,1,0.0,neutral or dissatisfied +7284,68210,Male,Loyal Customer,47,Business travel,Business,3421,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,1.0,satisfied +7285,108037,Female,Loyal Customer,16,Personal Travel,Eco,306,3,5,3,2,2,3,2,2,4,5,5,3,5,2,9,5.0,neutral or dissatisfied +7286,77270,Male,Loyal Customer,14,Personal Travel,Eco Plus,1590,2,5,2,5,2,2,1,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +7287,108056,Female,Loyal Customer,30,Personal Travel,Eco,591,1,4,1,2,1,4,5,4,4,4,4,5,4,5,158,166.0,neutral or dissatisfied +7288,25407,Male,Loyal Customer,47,Business travel,Business,2578,5,5,1,5,1,2,3,5,5,5,5,5,5,1,0,0.0,satisfied +7289,82133,Male,Loyal Customer,59,Business travel,Business,1517,3,3,3,3,5,5,5,4,4,4,4,3,4,3,0,6.0,satisfied +7290,85827,Male,Loyal Customer,19,Personal Travel,Eco,666,4,4,4,4,3,4,2,3,1,4,5,4,1,3,16,32.0,neutral or dissatisfied +7291,124764,Male,Loyal Customer,52,Business travel,Business,3908,0,0,0,1,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +7292,77463,Female,Loyal Customer,30,Business travel,Business,2306,4,3,3,3,4,4,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +7293,51980,Female,Loyal Customer,34,Personal Travel,Eco,347,2,5,2,4,5,2,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +7294,51060,Female,Loyal Customer,20,Personal Travel,Eco,158,2,4,2,3,3,2,3,3,4,4,4,4,4,3,67,71.0,neutral or dissatisfied +7295,1469,Female,Loyal Customer,69,Personal Travel,Eco,695,3,4,3,4,4,3,4,2,2,3,2,2,2,2,11,11.0,neutral or dissatisfied +7296,90307,Male,Loyal Customer,62,Personal Travel,Eco,879,3,4,3,3,1,3,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +7297,88939,Male,Loyal Customer,35,Business travel,Business,1697,5,5,5,5,3,5,5,4,4,4,4,5,4,4,12,18.0,satisfied +7298,118367,Female,Loyal Customer,52,Business travel,Eco Plus,602,1,5,5,5,5,3,3,1,1,1,1,2,1,3,37,29.0,neutral or dissatisfied +7299,124935,Female,Loyal Customer,56,Personal Travel,Eco,728,2,1,2,4,2,2,3,4,4,3,3,3,2,3,118,166.0,neutral or dissatisfied +7300,17564,Female,Loyal Customer,29,Business travel,Business,1034,2,2,2,2,4,4,4,4,5,5,2,4,1,4,0,0.0,satisfied +7301,27316,Female,Loyal Customer,24,Business travel,Business,671,5,5,5,5,5,5,5,5,5,5,2,2,2,5,0,0.0,satisfied +7302,42136,Male,Loyal Customer,43,Business travel,Business,2115,5,5,5,5,2,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +7303,111204,Female,disloyal Customer,50,Business travel,Business,1506,2,2,2,1,4,2,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +7304,34071,Female,Loyal Customer,37,Personal Travel,Eco,1674,1,4,1,3,4,1,1,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +7305,127363,Male,Loyal Customer,27,Business travel,Business,2783,4,4,4,4,5,5,5,5,4,2,5,4,5,5,0,2.0,satisfied +7306,118583,Male,Loyal Customer,57,Business travel,Business,370,3,5,4,4,4,3,3,3,3,3,3,4,3,4,25,25.0,neutral or dissatisfied +7307,112693,Female,Loyal Customer,27,Business travel,Business,671,3,5,5,5,3,3,3,3,2,5,2,2,2,3,3,0.0,neutral or dissatisfied +7308,118515,Male,Loyal Customer,39,Business travel,Business,370,5,5,5,5,5,4,5,5,5,5,5,5,5,3,40,35.0,satisfied +7309,52273,Male,disloyal Customer,49,Business travel,Eco,261,4,3,4,5,1,4,1,1,3,5,1,2,5,1,0,0.0,satisfied +7310,8533,Female,Loyal Customer,22,Personal Travel,Eco Plus,862,4,4,5,3,5,5,5,5,4,5,4,4,5,5,7,6.0,neutral or dissatisfied +7311,38123,Female,disloyal Customer,29,Business travel,Eco,1185,2,2,2,4,3,2,5,3,1,4,3,2,3,3,5,0.0,neutral or dissatisfied +7312,65251,Male,disloyal Customer,40,Business travel,Business,190,4,4,4,2,1,4,1,1,4,3,5,5,5,1,105,102.0,satisfied +7313,31245,Female,Loyal Customer,41,Personal Travel,Eco,472,1,5,1,1,3,1,3,3,5,3,1,1,2,3,7,37.0,neutral or dissatisfied +7314,3515,Male,Loyal Customer,54,Business travel,Business,1552,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,8.0,satisfied +7315,98645,Male,disloyal Customer,21,Business travel,Eco,861,2,2,2,4,4,2,1,4,1,5,3,1,3,4,15,0.0,neutral or dissatisfied +7316,56336,Female,disloyal Customer,35,Business travel,Business,200,3,3,3,2,5,3,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +7317,22316,Female,Loyal Customer,33,Business travel,Eco,238,5,1,1,1,5,5,5,5,2,2,2,3,5,5,0,3.0,satisfied +7318,123941,Male,Loyal Customer,65,Personal Travel,Eco,541,4,4,5,3,2,5,5,2,3,3,4,3,5,2,4,12.0,neutral or dissatisfied +7319,129326,Female,Loyal Customer,39,Business travel,Business,2586,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +7320,2802,Male,Loyal Customer,70,Personal Travel,Eco,764,3,4,3,3,1,3,3,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +7321,88981,Female,Loyal Customer,32,Personal Travel,Eco,1184,3,4,3,3,1,3,1,1,4,3,4,4,5,1,0,0.0,neutral or dissatisfied +7322,9496,Male,Loyal Customer,60,Business travel,Business,239,4,4,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +7323,5522,Male,disloyal Customer,26,Business travel,Business,404,4,0,4,3,2,4,2,2,5,5,5,4,5,2,0,0.0,satisfied +7324,83577,Female,Loyal Customer,44,Business travel,Business,1757,2,3,3,3,5,3,2,2,2,2,2,4,2,1,5,25.0,neutral or dissatisfied +7325,43992,Male,disloyal Customer,34,Business travel,Eco,334,1,3,1,1,3,1,3,3,3,1,5,1,5,3,0,14.0,neutral or dissatisfied +7326,346,Male,Loyal Customer,68,Personal Travel,Eco,853,1,2,1,4,4,1,4,4,1,2,3,3,4,4,27,36.0,neutral or dissatisfied +7327,42438,Male,Loyal Customer,66,Personal Travel,Eco,1119,2,2,1,3,4,1,4,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +7328,68635,Female,disloyal Customer,59,Business travel,Business,237,4,4,4,3,3,4,2,3,4,4,4,3,5,3,0,0.0,satisfied +7329,20086,Female,disloyal Customer,35,Business travel,Eco,843,2,2,2,3,5,2,5,5,3,3,4,1,3,5,0,0.0,neutral or dissatisfied +7330,105226,Male,disloyal Customer,41,Business travel,Business,377,1,1,1,3,1,1,1,1,5,5,5,5,5,1,17,10.0,neutral or dissatisfied +7331,34452,Male,Loyal Customer,11,Personal Travel,Eco,228,5,5,0,1,5,0,5,5,4,2,4,3,5,5,0,0.0,satisfied +7332,123182,Female,Loyal Customer,37,Personal Travel,Eco,631,5,2,5,4,2,5,2,2,1,2,4,4,3,2,0,0.0,satisfied +7333,32334,Female,Loyal Customer,53,Business travel,Business,3210,4,4,4,4,1,3,5,4,4,4,5,1,4,1,18,15.0,satisfied +7334,69807,Female,Loyal Customer,55,Business travel,Business,3787,5,5,5,5,4,5,5,4,4,4,4,5,4,4,4,2.0,satisfied +7335,24883,Female,Loyal Customer,49,Business travel,Business,397,4,5,4,4,3,4,4,5,5,5,5,3,5,3,22,13.0,satisfied +7336,18797,Male,Loyal Customer,44,Business travel,Business,3933,3,3,3,3,5,2,3,5,5,5,5,4,5,1,0,1.0,satisfied +7337,13398,Male,Loyal Customer,17,Personal Travel,Eco,505,3,4,3,3,1,3,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +7338,65795,Female,Loyal Customer,40,Business travel,Business,1389,2,2,2,2,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7339,53140,Female,Loyal Customer,46,Business travel,Eco,413,2,1,1,1,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +7340,1686,Male,Loyal Customer,57,Business travel,Business,2544,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +7341,55624,Female,Loyal Customer,48,Business travel,Business,1824,2,2,2,2,2,3,5,5,5,5,5,3,5,4,8,37.0,satisfied +7342,96466,Female,disloyal Customer,16,Business travel,Eco,436,2,1,2,3,3,2,3,3,2,4,4,1,3,3,19,19.0,neutral or dissatisfied +7343,19314,Male,Loyal Customer,24,Business travel,Business,694,3,3,3,3,3,3,3,3,2,5,4,4,3,3,12,5.0,satisfied +7344,66069,Male,Loyal Customer,60,Personal Travel,Eco,1055,2,4,2,1,1,2,1,1,3,5,4,3,4,1,0,2.0,neutral or dissatisfied +7345,72907,Female,Loyal Customer,59,Business travel,Business,1096,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +7346,61391,Female,disloyal Customer,30,Business travel,Business,679,4,4,4,2,1,4,1,1,3,3,4,5,4,1,0,2.0,neutral or dissatisfied +7347,64214,Female,Loyal Customer,36,Business travel,Business,1660,3,3,3,3,5,4,5,4,4,4,4,5,4,5,33,45.0,satisfied +7348,69777,Female,Loyal Customer,25,Business travel,Business,2454,1,1,5,1,4,5,5,4,3,5,5,5,5,5,103,99.0,satisfied +7349,72915,Male,Loyal Customer,47,Business travel,Business,1089,2,2,2,2,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +7350,98486,Female,disloyal Customer,22,Business travel,Business,668,0,4,0,5,5,0,5,5,4,4,4,3,5,5,6,9.0,satisfied +7351,37152,Male,disloyal Customer,46,Business travel,Business,1189,3,3,3,3,3,3,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +7352,49031,Female,disloyal Customer,26,Business travel,Eco,134,3,3,3,1,3,3,3,3,1,4,2,3,3,3,0,0.0,neutral or dissatisfied +7353,96935,Male,disloyal Customer,35,Business travel,Eco Plus,781,3,3,3,3,4,3,4,4,2,1,2,1,2,4,49,53.0,neutral or dissatisfied +7354,87013,Male,Loyal Customer,47,Business travel,Business,907,4,3,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +7355,57033,Female,Loyal Customer,53,Business travel,Business,2565,4,4,4,4,5,5,5,3,4,5,4,5,3,5,12,34.0,satisfied +7356,83506,Female,Loyal Customer,58,Personal Travel,Eco,946,1,2,1,3,1,3,3,1,1,1,1,1,1,2,0,14.0,neutral or dissatisfied +7357,97037,Female,disloyal Customer,26,Business travel,Business,1476,2,2,2,3,3,2,4,3,4,1,3,2,4,3,0,6.0,neutral or dissatisfied +7358,51272,Male,Loyal Customer,27,Business travel,Eco Plus,86,4,3,3,3,4,4,4,4,4,1,4,1,3,4,68,74.0,neutral or dissatisfied +7359,120872,Male,Loyal Customer,57,Business travel,Business,2639,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7360,101925,Male,Loyal Customer,34,Business travel,Business,628,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +7361,104991,Female,Loyal Customer,25,Personal Travel,Eco,337,5,2,5,2,3,5,4,3,2,5,2,1,3,3,0,0.0,satisfied +7362,18437,Male,disloyal Customer,24,Business travel,Business,192,5,2,5,2,1,2,1,1,3,2,4,3,4,1,2,0.0,satisfied +7363,92188,Male,disloyal Customer,14,Business travel,Eco,920,3,3,3,4,4,3,4,4,3,5,2,2,4,4,0,0.0,neutral or dissatisfied +7364,79045,Male,Loyal Customer,55,Business travel,Business,2797,0,5,0,3,2,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +7365,45680,Male,Loyal Customer,46,Business travel,Business,2821,2,2,2,2,1,4,2,4,4,4,4,1,4,3,0,0.0,satisfied +7366,53461,Male,disloyal Customer,35,Business travel,Eco,811,3,3,3,3,3,1,1,3,3,4,3,1,1,1,0,0.0,neutral or dissatisfied +7367,54490,Female,Loyal Customer,26,Business travel,Business,925,4,4,4,4,5,5,5,5,3,4,3,4,4,5,0,0.0,satisfied +7368,52058,Male,Loyal Customer,26,Business travel,Business,2949,3,3,4,3,4,4,4,4,1,4,2,3,1,4,29,36.0,satisfied +7369,79917,Female,disloyal Customer,29,Business travel,Eco,1096,3,3,3,3,3,5,5,4,3,3,4,5,3,5,137,117.0,neutral or dissatisfied +7370,76734,Male,Loyal Customer,44,Personal Travel,Eco Plus,534,2,5,4,5,3,4,3,3,3,5,4,4,4,3,8,0.0,neutral or dissatisfied +7371,59106,Male,Loyal Customer,57,Personal Travel,Eco,1846,3,4,3,1,1,3,1,1,3,5,4,4,5,1,18,23.0,neutral or dissatisfied +7372,109970,Female,Loyal Customer,61,Personal Travel,Eco,1052,3,4,3,2,2,4,5,2,2,3,4,4,2,3,76,59.0,neutral or dissatisfied +7373,14109,Male,Loyal Customer,29,Personal Travel,Eco,425,1,0,1,1,5,1,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +7374,9942,Female,Loyal Customer,21,Business travel,Business,534,3,3,4,3,3,3,3,3,2,3,3,4,2,3,29,23.0,neutral or dissatisfied +7375,96131,Male,disloyal Customer,27,Business travel,Business,460,4,4,4,4,5,4,5,5,5,2,5,4,4,5,3,0.0,satisfied +7376,80302,Male,Loyal Customer,26,Business travel,Business,2870,3,3,3,3,3,3,3,3,3,2,3,1,4,3,27,29.0,neutral or dissatisfied +7377,23333,Male,Loyal Customer,57,Personal Travel,Eco,563,2,4,2,5,2,1,1,5,4,4,5,1,5,1,207,224.0,neutral or dissatisfied +7378,50928,Female,Loyal Customer,64,Personal Travel,Eco,86,3,4,3,4,3,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +7379,94711,Male,Loyal Customer,43,Business travel,Business,293,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +7380,58125,Male,Loyal Customer,50,Personal Travel,Eco,589,3,4,3,3,5,3,5,5,3,2,4,5,5,5,6,13.0,neutral or dissatisfied +7381,112658,Female,Loyal Customer,40,Personal Travel,Business,723,4,3,4,4,5,1,5,1,1,4,1,2,1,3,14,0.0,neutral or dissatisfied +7382,91032,Male,Loyal Customer,38,Personal Travel,Eco,406,2,1,2,2,2,2,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +7383,95640,Male,Loyal Customer,52,Business travel,Business,2538,5,5,5,5,5,5,5,5,5,5,5,4,5,4,14,10.0,satisfied +7384,6639,Male,Loyal Customer,43,Business travel,Business,416,3,3,3,3,2,5,4,5,5,5,5,3,5,3,50,56.0,satisfied +7385,106769,Female,Loyal Customer,56,Personal Travel,Eco,837,3,1,3,3,4,4,3,5,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +7386,116552,Male,Loyal Customer,34,Personal Travel,Eco,337,3,4,5,3,3,5,3,3,1,2,4,1,4,3,10,21.0,neutral or dissatisfied +7387,94747,Female,Loyal Customer,30,Business travel,Business,2382,4,5,5,5,3,3,4,3,2,3,3,3,4,3,0,4.0,neutral or dissatisfied +7388,124767,Female,Loyal Customer,54,Business travel,Business,280,4,4,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +7389,61099,Male,Loyal Customer,20,Personal Travel,Eco,1506,1,3,1,3,3,1,2,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +7390,4851,Male,disloyal Customer,61,Business travel,Business,408,5,5,5,3,2,5,4,2,3,4,4,3,4,2,0,0.0,satisfied +7391,76297,Female,Loyal Customer,40,Business travel,Business,2182,1,1,1,1,5,5,5,4,4,4,4,3,4,5,8,0.0,satisfied +7392,78946,Female,Loyal Customer,11,Business travel,Business,3063,3,3,3,3,4,4,4,4,3,5,4,5,5,4,0,0.0,satisfied +7393,59420,Female,Loyal Customer,48,Business travel,Business,2399,3,3,3,3,4,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +7394,24370,Female,Loyal Customer,42,Business travel,Eco,669,4,5,5,5,1,4,5,4,4,4,4,4,4,2,1,17.0,satisfied +7395,80150,Male,disloyal Customer,42,Business travel,Eco,2475,3,3,3,3,3,5,5,1,4,1,3,5,3,5,1,0.0,neutral or dissatisfied +7396,94154,Female,Loyal Customer,59,Business travel,Business,148,2,2,2,2,5,5,5,4,4,4,5,3,4,4,0,0.0,satisfied +7397,61703,Female,Loyal Customer,44,Business travel,Business,1464,1,1,1,1,4,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +7398,26063,Female,disloyal Customer,51,Business travel,Business,591,1,1,1,1,3,1,3,3,3,5,4,5,5,3,3,0.0,neutral or dissatisfied +7399,112305,Female,Loyal Customer,52,Business travel,Business,2245,5,5,5,5,5,4,5,4,4,4,4,3,4,5,8,9.0,satisfied +7400,27462,Male,disloyal Customer,30,Business travel,Eco,987,3,3,3,3,1,3,2,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +7401,114647,Male,Loyal Customer,58,Business travel,Business,2751,1,1,1,1,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +7402,92056,Male,Loyal Customer,56,Business travel,Business,1589,5,5,5,5,4,1,3,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +7403,72043,Male,Loyal Customer,30,Business travel,Business,2556,1,1,1,1,4,4,4,4,5,4,4,5,4,4,25,38.0,satisfied +7404,84440,Female,Loyal Customer,47,Business travel,Business,1574,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +7405,36911,Female,Loyal Customer,50,Business travel,Business,2001,4,3,4,4,5,3,2,4,4,4,4,5,4,2,27,50.0,satisfied +7406,124296,Male,Loyal Customer,56,Business travel,Business,255,3,4,4,4,3,4,4,3,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +7407,29651,Male,Loyal Customer,59,Personal Travel,Eco,1448,3,1,3,3,5,3,5,5,2,5,1,2,3,5,0,0.0,neutral or dissatisfied +7408,120223,Male,Loyal Customer,39,Business travel,Business,1729,2,1,2,2,4,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +7409,34285,Male,disloyal Customer,40,Business travel,Business,280,2,2,2,4,3,2,2,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +7410,116387,Female,Loyal Customer,33,Personal Travel,Eco,417,1,4,1,4,1,1,1,1,2,5,3,2,3,1,41,44.0,neutral or dissatisfied +7411,118362,Male,disloyal Customer,23,Business travel,Business,602,0,4,0,1,4,0,4,4,3,2,4,4,5,4,0,3.0,satisfied +7412,15808,Female,Loyal Customer,70,Personal Travel,Eco,282,1,5,1,5,5,1,4,2,2,1,2,4,2,1,3,0.0,neutral or dissatisfied +7413,80599,Female,Loyal Customer,42,Personal Travel,Eco Plus,1747,4,4,4,4,1,4,3,1,1,4,3,3,1,2,0,0.0,neutral or dissatisfied +7414,86368,Female,Loyal Customer,53,Business travel,Business,760,5,5,5,5,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +7415,62303,Male,Loyal Customer,58,Business travel,Business,236,4,4,4,4,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +7416,75292,Male,Loyal Customer,36,Business travel,Eco Plus,329,5,4,4,4,5,5,5,5,1,5,4,1,2,5,0,1.0,satisfied +7417,48364,Female,Loyal Customer,72,Business travel,Business,522,1,0,0,4,1,4,3,3,3,0,1,3,3,3,0,0.0,neutral or dissatisfied +7418,49675,Male,Loyal Customer,55,Business travel,Business,373,4,4,4,4,2,4,4,4,4,4,4,1,4,4,9,10.0,satisfied +7419,59478,Male,disloyal Customer,30,Business travel,Business,758,1,1,1,2,3,1,3,3,3,5,4,4,4,3,10,0.0,neutral or dissatisfied +7420,84268,Male,Loyal Customer,52,Business travel,Business,3362,0,1,1,2,4,4,4,1,1,1,5,4,1,4,0,0.0,satisfied +7421,55836,Male,Loyal Customer,38,Business travel,Eco,1416,2,4,4,4,2,2,2,2,3,2,2,4,2,2,5,0.0,neutral or dissatisfied +7422,12851,Female,Loyal Customer,21,Personal Travel,Eco,817,1,4,0,4,4,0,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +7423,57675,Female,Loyal Customer,18,Personal Travel,Business,867,2,1,2,4,4,2,4,4,4,5,3,4,4,4,1,6.0,neutral or dissatisfied +7424,113374,Male,Loyal Customer,55,Business travel,Business,226,2,2,2,2,5,4,4,5,5,5,5,3,5,5,45,48.0,satisfied +7425,123708,Male,Loyal Customer,25,Personal Travel,Eco,214,3,0,0,1,1,0,1,1,5,2,4,3,1,1,0,0.0,neutral or dissatisfied +7426,11664,Female,disloyal Customer,23,Business travel,Eco,1117,3,3,3,2,2,3,2,2,5,5,5,5,4,2,26,21.0,neutral or dissatisfied +7427,73588,Female,Loyal Customer,56,Business travel,Business,192,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +7428,85295,Male,Loyal Customer,48,Personal Travel,Eco,874,3,1,3,3,1,3,1,1,1,5,4,3,3,1,14,7.0,neutral or dissatisfied +7429,14265,Male,Loyal Customer,35,Business travel,Eco,429,4,4,4,4,4,4,4,4,2,5,5,1,1,4,0,0.0,satisfied +7430,64885,Male,Loyal Customer,32,Business travel,Eco,247,1,4,4,4,1,1,1,1,2,4,2,4,3,1,0,2.0,neutral or dissatisfied +7431,5148,Male,disloyal Customer,25,Business travel,Business,622,2,0,2,1,2,2,2,2,4,2,5,5,4,2,8,8.0,neutral or dissatisfied +7432,108412,Female,disloyal Customer,27,Business travel,Business,1444,4,4,4,2,4,4,4,4,3,4,5,3,4,4,83,61.0,satisfied +7433,31664,Male,Loyal Customer,29,Business travel,Business,3127,2,3,3,3,2,2,2,2,4,3,2,2,3,2,0,2.0,neutral or dissatisfied +7434,108553,Female,Loyal Customer,29,Personal Travel,Business,735,1,4,1,1,2,1,2,2,4,5,4,4,4,2,1,0.0,neutral or dissatisfied +7435,90759,Female,disloyal Customer,27,Business travel,Eco,270,2,1,2,2,2,2,2,2,2,1,2,4,2,2,0,9.0,neutral or dissatisfied +7436,28951,Male,Loyal Customer,49,Business travel,Eco,697,2,5,5,5,2,2,2,2,5,5,4,4,3,2,0,0.0,satisfied +7437,40560,Female,disloyal Customer,32,Business travel,Eco,391,3,4,3,3,2,3,5,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +7438,80800,Female,Loyal Customer,43,Business travel,Business,2602,1,1,1,1,2,4,4,4,4,4,4,3,4,4,5,1.0,satisfied +7439,120848,Male,Loyal Customer,57,Business travel,Business,992,2,2,2,2,1,3,4,2,2,2,2,4,2,3,13,41.0,neutral or dissatisfied +7440,94543,Female,disloyal Customer,43,Business travel,Business,192,3,3,3,4,1,3,1,1,5,5,5,3,4,1,38,62.0,neutral or dissatisfied +7441,67495,Male,Loyal Customer,47,Business travel,Eco Plus,592,3,3,3,3,3,3,3,3,3,4,3,2,3,3,0,0.0,neutral or dissatisfied +7442,28392,Male,Loyal Customer,14,Personal Travel,Eco,763,4,5,4,2,2,4,2,2,3,5,1,2,5,2,0,0.0,satisfied +7443,91403,Female,Loyal Customer,19,Personal Travel,Eco,2218,4,1,4,4,4,4,4,4,3,5,3,1,4,4,0,5.0,satisfied +7444,50238,Male,Loyal Customer,70,Business travel,Business,1721,1,5,5,5,3,2,2,2,2,2,1,2,2,2,35,39.0,neutral or dissatisfied +7445,78847,Female,Loyal Customer,47,Business travel,Business,2957,3,3,5,3,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +7446,79806,Male,Loyal Customer,36,Business travel,Business,2304,1,1,4,1,5,5,5,3,2,5,4,5,5,5,202,182.0,satisfied +7447,103551,Female,Loyal Customer,34,Personal Travel,Eco,738,4,5,4,1,3,4,3,3,4,5,4,4,5,3,58,52.0,neutral or dissatisfied +7448,32919,Male,Loyal Customer,58,Personal Travel,Eco,102,2,2,2,4,2,2,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +7449,86024,Male,Loyal Customer,45,Business travel,Eco,447,2,4,4,4,2,2,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +7450,56944,Male,Loyal Customer,29,Business travel,Eco,2454,2,3,3,3,2,2,2,1,2,2,3,2,1,2,0,0.0,neutral or dissatisfied +7451,85311,Male,Loyal Customer,34,Personal Travel,Eco,874,1,2,1,3,4,1,4,4,1,4,3,2,3,4,1,0.0,neutral or dissatisfied +7452,6085,Female,disloyal Customer,27,Business travel,Eco Plus,672,3,3,3,4,1,3,3,1,3,2,4,3,3,1,5,40.0,neutral or dissatisfied +7453,65572,Female,disloyal Customer,54,Business travel,Business,237,4,4,4,4,4,4,4,4,3,3,5,4,4,4,2,0.0,neutral or dissatisfied +7454,60687,Male,Loyal Customer,33,Personal Travel,Business,1605,2,5,2,4,4,2,2,4,3,5,5,4,4,4,92,70.0,neutral or dissatisfied +7455,31109,Male,disloyal Customer,28,Business travel,Eco,483,2,2,2,3,4,2,4,4,2,4,4,1,4,4,24,29.0,neutral or dissatisfied +7456,34087,Female,disloyal Customer,24,Business travel,Eco,1173,4,4,4,2,4,4,4,4,3,3,4,5,2,4,0,0.0,satisfied +7457,82287,Female,Loyal Customer,16,Personal Travel,Eco,1481,1,3,2,4,2,2,2,2,4,3,3,4,4,2,36,32.0,neutral or dissatisfied +7458,101289,Male,Loyal Customer,39,Business travel,Business,444,4,3,4,4,5,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +7459,28732,Male,Loyal Customer,26,Business travel,Business,2149,1,1,1,1,5,5,5,5,2,2,4,4,5,5,0,0.0,satisfied +7460,126988,Female,Loyal Customer,45,Business travel,Business,647,2,2,2,2,5,5,4,5,5,5,5,3,5,5,16,11.0,satisfied +7461,25963,Male,Loyal Customer,55,Business travel,Business,946,4,4,4,4,5,2,4,5,5,5,5,3,5,1,2,0.0,satisfied +7462,99339,Female,disloyal Customer,30,Business travel,Business,1771,2,2,2,4,1,2,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +7463,124383,Male,Loyal Customer,27,Personal Travel,Eco,575,1,5,1,1,2,1,2,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +7464,5178,Female,Loyal Customer,37,Business travel,Business,293,0,0,0,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +7465,47556,Male,Loyal Customer,27,Business travel,Eco Plus,584,0,0,0,2,5,0,4,5,1,5,2,4,3,5,0,0.0,satisfied +7466,119901,Male,Loyal Customer,36,Business travel,Eco Plus,912,4,1,1,1,4,4,4,3,4,4,4,4,4,4,404,413.0,neutral or dissatisfied +7467,114965,Female,disloyal Customer,28,Business travel,Business,404,5,5,5,3,4,5,4,4,4,5,5,5,5,4,0,0.0,satisfied +7468,128409,Female,disloyal Customer,30,Business travel,Eco,647,3,4,3,4,1,3,1,1,3,2,4,4,3,1,9,14.0,neutral or dissatisfied +7469,22243,Male,disloyal Customer,25,Business travel,Business,143,2,1,2,2,3,2,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +7470,107387,Male,Loyal Customer,35,Business travel,Business,717,4,4,4,4,4,4,4,2,2,2,2,5,2,5,36,38.0,satisfied +7471,70537,Female,Loyal Customer,43,Business travel,Business,2539,1,1,1,1,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7472,119660,Male,Loyal Customer,41,Business travel,Business,107,4,4,4,4,3,4,4,3,3,3,4,1,3,1,3,2.0,neutral or dissatisfied +7473,71798,Female,disloyal Customer,24,Business travel,Eco,1301,4,3,3,2,4,4,4,4,4,3,4,4,5,4,1,0.0,satisfied +7474,39292,Female,Loyal Customer,58,Personal Travel,Eco,67,1,3,1,4,1,3,3,4,4,1,2,2,4,2,49,69.0,neutral or dissatisfied +7475,27986,Female,Loyal Customer,66,Personal Travel,Eco,2350,2,4,2,4,3,1,3,2,2,2,2,1,2,5,0,0.0,neutral or dissatisfied +7476,45694,Male,Loyal Customer,33,Personal Travel,Eco,896,2,4,2,3,4,2,4,4,3,5,5,4,5,4,5,16.0,neutral or dissatisfied +7477,118230,Female,Loyal Customer,30,Business travel,Business,1587,3,3,3,3,5,5,5,5,4,4,5,3,5,5,0,0.0,satisfied +7478,12351,Female,Loyal Customer,19,Business travel,Eco,190,5,1,1,1,5,5,4,5,4,4,3,5,1,5,0,0.0,satisfied +7479,128,Male,Loyal Customer,65,Personal Travel,Eco,562,2,1,2,4,4,2,4,4,1,1,4,1,3,4,7,15.0,neutral or dissatisfied +7480,4634,Male,Loyal Customer,49,Business travel,Eco,327,2,3,3,3,2,2,2,2,4,2,4,2,4,2,29,45.0,neutral or dissatisfied +7481,128905,Female,Loyal Customer,24,Personal Travel,Eco Plus,2454,2,1,2,4,2,4,4,4,2,3,3,4,2,4,31,14.0,neutral or dissatisfied +7482,65004,Male,Loyal Customer,35,Business travel,Eco,224,2,1,1,1,2,2,2,2,3,4,3,5,5,2,4,0.0,satisfied +7483,27747,Male,Loyal Customer,34,Business travel,Business,1448,1,1,1,1,5,4,4,4,4,4,4,3,4,2,17,0.0,satisfied +7484,26741,Female,Loyal Customer,44,Business travel,Eco Plus,515,4,4,3,4,1,1,3,4,4,4,4,4,4,5,0,0.0,satisfied +7485,32072,Male,Loyal Customer,37,Business travel,Business,163,4,4,4,4,4,2,1,4,4,4,3,5,4,1,0,0.0,satisfied +7486,81080,Male,disloyal Customer,40,Business travel,Business,931,3,3,3,5,1,3,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +7487,46573,Male,Loyal Customer,62,Business travel,Business,2239,1,1,1,1,4,3,2,5,5,5,5,1,5,4,3,3.0,satisfied +7488,14731,Male,Loyal Customer,17,Business travel,Business,1642,2,2,2,2,5,5,5,5,5,2,4,3,4,5,43,20.0,satisfied +7489,46345,Female,Loyal Customer,33,Personal Travel,Eco,589,3,2,4,3,3,4,3,3,4,5,3,1,2,3,28,29.0,neutral or dissatisfied +7490,104383,Male,Loyal Customer,28,Personal Travel,Eco,228,2,4,2,3,1,2,1,1,5,3,5,3,4,1,37,38.0,neutral or dissatisfied +7491,100168,Female,Loyal Customer,55,Personal Travel,Eco,725,2,2,2,4,4,3,3,3,3,2,3,4,3,2,40,21.0,neutral or dissatisfied +7492,63015,Female,disloyal Customer,30,Business travel,Eco,948,3,2,2,4,5,2,5,5,2,4,3,2,4,5,0,0.0,neutral or dissatisfied +7493,98451,Female,Loyal Customer,41,Business travel,Business,1954,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +7494,56468,Female,Loyal Customer,33,Business travel,Eco Plus,719,2,2,2,2,2,2,2,2,4,3,4,2,4,2,15,8.0,neutral or dissatisfied +7495,75610,Male,Loyal Customer,25,Personal Travel,Eco,337,2,5,2,1,5,2,3,5,5,4,4,5,4,5,0,4.0,neutral or dissatisfied +7496,25764,Female,Loyal Customer,11,Personal Travel,Eco,356,3,5,3,4,3,3,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +7497,96386,Female,Loyal Customer,59,Business travel,Business,1407,3,4,4,4,5,2,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +7498,19257,Female,Loyal Customer,38,Business travel,Business,802,1,1,1,1,2,4,3,2,2,2,2,5,2,4,12,5.0,satisfied +7499,119847,Male,Loyal Customer,31,Business travel,Business,2894,4,5,4,4,4,4,4,4,4,3,3,2,3,4,0,0.0,neutral or dissatisfied +7500,31494,Female,Loyal Customer,42,Business travel,Business,2914,1,1,2,1,1,5,4,4,4,4,4,4,4,5,112,126.0,satisfied +7501,26574,Male,disloyal Customer,20,Business travel,Eco,404,2,0,2,4,3,2,3,3,1,1,4,2,5,3,1,0.0,neutral or dissatisfied +7502,91654,Male,disloyal Customer,9,Personal Travel,Eco,1199,3,4,2,2,2,2,2,2,5,2,4,3,1,2,0,0.0,neutral or dissatisfied +7503,25145,Male,Loyal Customer,36,Business travel,Eco,406,4,1,1,1,4,4,4,4,3,3,2,3,5,4,0,0.0,satisfied +7504,56053,Male,Loyal Customer,64,Business travel,Eco,975,3,5,5,5,3,3,3,2,2,4,4,3,4,3,40,12.0,neutral or dissatisfied +7505,80652,Female,disloyal Customer,24,Business travel,Eco,821,3,3,3,1,5,3,4,5,5,3,5,3,4,5,0,0.0,neutral or dissatisfied +7506,126260,Female,disloyal Customer,37,Business travel,Eco,200,3,4,3,4,1,3,1,1,2,3,3,3,4,1,40,44.0,neutral or dissatisfied +7507,68231,Female,Loyal Customer,46,Business travel,Eco,631,1,5,5,5,5,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +7508,59193,Male,Loyal Customer,52,Business travel,Business,1440,4,4,4,4,5,4,5,2,2,2,2,4,2,4,15,0.0,satisfied +7509,57279,Male,Loyal Customer,57,Personal Travel,Eco,628,2,5,2,3,1,2,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +7510,95798,Male,Loyal Customer,14,Personal Travel,Eco Plus,419,3,1,3,1,1,3,1,1,1,5,2,3,2,1,10,0.0,neutral or dissatisfied +7511,101964,Female,Loyal Customer,43,Business travel,Business,2022,2,1,4,1,1,4,4,2,2,2,2,3,2,4,1,0.0,neutral or dissatisfied +7512,18831,Female,Loyal Customer,44,Business travel,Business,503,1,1,5,1,4,2,2,5,5,4,5,3,5,2,0,0.0,satisfied +7513,92684,Male,Loyal Customer,36,Business travel,Business,507,4,5,5,5,4,4,3,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +7514,14735,Female,Loyal Customer,20,Personal Travel,Business,404,2,3,2,3,4,2,4,4,5,1,2,1,3,4,4,4.0,neutral or dissatisfied +7515,22314,Female,Loyal Customer,21,Business travel,Eco,208,2,1,1,1,2,2,3,2,4,1,4,4,4,2,14,13.0,neutral or dissatisfied +7516,20480,Female,Loyal Customer,51,Business travel,Business,1654,0,5,0,3,1,2,3,4,4,4,4,4,4,2,0,0.0,satisfied +7517,50255,Female,Loyal Customer,35,Business travel,Business,109,2,3,3,3,3,3,2,3,3,3,2,4,3,4,0,0.0,neutral or dissatisfied +7518,38591,Male,Loyal Customer,54,Business travel,Business,1846,3,5,5,5,5,2,2,3,3,3,3,2,3,1,81,82.0,neutral or dissatisfied +7519,19896,Female,Loyal Customer,26,Business travel,Business,315,2,2,2,2,5,5,5,5,4,2,4,4,4,5,0,0.0,satisfied +7520,4069,Female,Loyal Customer,50,Business travel,Business,1600,4,4,4,4,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +7521,1576,Male,disloyal Customer,33,Business travel,Business,140,3,3,3,2,3,3,3,3,4,4,5,4,4,3,0,0.0,neutral or dissatisfied +7522,126961,Male,Loyal Customer,33,Business travel,Business,2820,2,2,2,2,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +7523,59603,Male,Loyal Customer,43,Business travel,Business,3004,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +7524,114446,Male,disloyal Customer,18,Business travel,Business,325,5,3,5,1,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +7525,96545,Female,Loyal Customer,16,Personal Travel,Eco,436,5,5,5,2,4,5,4,4,3,5,4,3,5,4,0,0.0,satisfied +7526,127113,Male,Loyal Customer,23,Personal Travel,Eco,370,1,5,1,2,4,1,4,4,5,2,4,1,4,4,0,9.0,neutral or dissatisfied +7527,24784,Female,Loyal Customer,48,Personal Travel,Eco,432,3,4,3,4,3,4,5,4,4,3,4,4,4,3,0,21.0,neutral or dissatisfied +7528,24723,Female,Loyal Customer,48,Business travel,Business,1773,1,2,2,2,1,2,3,1,1,1,1,3,1,3,0,14.0,neutral or dissatisfied +7529,9514,Male,Loyal Customer,51,Personal Travel,Eco Plus,322,1,4,1,3,1,1,1,1,1,1,3,4,3,1,4,0.0,neutral or dissatisfied +7530,40363,Female,Loyal Customer,50,Business travel,Business,3805,4,4,4,4,1,2,5,4,4,4,4,2,4,3,0,0.0,satisfied +7531,23959,Male,disloyal Customer,44,Business travel,Eco Plus,536,4,4,4,4,3,4,2,3,2,2,4,1,3,3,3,2.0,neutral or dissatisfied +7532,41648,Female,Loyal Customer,67,Business travel,Eco,347,3,2,2,2,4,3,2,3,3,3,3,2,3,3,0,1.0,satisfied +7533,78333,Female,Loyal Customer,24,Business travel,Business,1547,2,2,2,2,4,4,4,4,3,5,4,4,5,4,0,5.0,satisfied +7534,28139,Female,Loyal Customer,62,Business travel,Eco,933,2,5,5,5,2,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +7535,80036,Male,Loyal Customer,21,Personal Travel,Eco,1069,3,5,3,4,4,3,4,4,5,3,4,4,5,4,17,6.0,neutral or dissatisfied +7536,120019,Female,Loyal Customer,44,Personal Travel,Eco,511,1,5,3,2,2,5,5,1,1,3,3,3,1,3,33,25.0,neutral or dissatisfied +7537,67846,Female,Loyal Customer,50,Personal Travel,Eco,1171,2,5,2,3,3,5,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +7538,113638,Female,Loyal Customer,37,Personal Travel,Eco,236,2,4,2,1,1,2,1,1,3,3,4,3,5,1,18,0.0,neutral or dissatisfied +7539,4868,Male,Loyal Customer,54,Personal Travel,Eco,408,3,5,5,3,1,5,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +7540,84982,Male,Loyal Customer,52,Business travel,Business,1590,4,4,4,4,3,5,4,4,4,4,4,5,4,3,15,7.0,satisfied +7541,52012,Male,Loyal Customer,36,Business travel,Eco,328,5,5,5,5,5,5,5,5,4,3,2,2,3,5,0,0.0,satisfied +7542,104212,Male,Loyal Customer,16,Business travel,Eco,680,5,3,3,3,5,4,2,5,3,2,4,3,3,5,22,18.0,neutral or dissatisfied +7543,71367,Female,Loyal Customer,43,Business travel,Business,3945,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +7544,116303,Female,Loyal Customer,20,Personal Travel,Eco,447,1,4,1,3,2,1,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +7545,88371,Male,Loyal Customer,54,Business travel,Business,3410,3,3,3,3,3,4,4,3,3,3,3,4,3,2,20,18.0,neutral or dissatisfied +7546,121851,Male,Loyal Customer,50,Business travel,Business,2745,1,1,1,1,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +7547,32694,Female,Loyal Customer,85,Business travel,Business,101,4,3,3,3,2,4,3,1,3,3,3,3,2,3,0,0.0,neutral or dissatisfied +7548,16646,Male,Loyal Customer,34,Business travel,Business,488,3,4,4,4,5,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +7549,120149,Female,Loyal Customer,28,Personal Travel,Eco,1475,5,5,5,3,3,5,3,3,5,2,3,4,4,3,0,0.0,satisfied +7550,115699,Male,disloyal Customer,10,Business travel,Eco,480,1,1,1,3,4,1,5,4,2,3,3,2,4,4,3,0.0,neutral or dissatisfied +7551,62856,Female,Loyal Customer,41,Business travel,Business,2446,3,3,4,3,5,4,4,2,2,2,2,4,2,3,14,8.0,satisfied +7552,92085,Female,disloyal Customer,43,Business travel,Eco,1080,2,2,2,3,3,2,3,3,1,1,3,4,3,3,0,0.0,neutral or dissatisfied +7553,38260,Male,Loyal Customer,49,Business travel,Eco,1050,2,5,4,4,2,2,2,2,1,2,4,3,3,2,0,17.0,neutral or dissatisfied +7554,71759,Female,Loyal Customer,53,Business travel,Business,1744,1,1,1,1,3,4,5,5,5,5,5,3,5,4,34,33.0,satisfied +7555,43351,Female,disloyal Customer,30,Business travel,Eco,347,3,0,3,2,4,3,4,4,4,1,3,2,2,4,0,0.0,neutral or dissatisfied +7556,116826,Male,Loyal Customer,45,Business travel,Business,1789,5,5,5,5,2,5,5,5,5,5,5,3,5,4,6,0.0,satisfied +7557,18115,Female,disloyal Customer,18,Business travel,Eco,629,1,0,1,1,3,1,3,3,2,1,5,4,1,3,0,0.0,neutral or dissatisfied +7558,19873,Female,disloyal Customer,45,Business travel,Business,315,4,4,4,2,3,4,3,3,4,4,4,4,5,3,0,0.0,satisfied +7559,19657,Female,Loyal Customer,23,Personal Travel,Eco,763,2,4,2,3,2,2,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +7560,70452,Male,Loyal Customer,41,Business travel,Business,3753,5,5,5,5,4,5,4,5,5,4,5,5,5,3,7,4.0,satisfied +7561,57225,Female,Loyal Customer,29,Personal Travel,Eco,1514,2,4,2,5,3,2,3,3,3,5,5,1,4,3,0,0.0,neutral or dissatisfied +7562,69051,Female,Loyal Customer,56,Business travel,Business,1389,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +7563,44592,Male,Loyal Customer,58,Personal Travel,Eco,157,3,5,3,5,1,3,1,1,3,3,4,4,5,1,10,32.0,neutral or dissatisfied +7564,30147,Female,Loyal Customer,61,Personal Travel,Eco,95,1,4,1,2,5,1,3,2,2,1,2,2,2,5,0,0.0,neutral or dissatisfied +7565,5802,Female,Loyal Customer,61,Business travel,Business,2300,2,1,1,1,3,2,2,3,3,3,2,4,3,1,0,11.0,neutral or dissatisfied +7566,55501,Female,Loyal Customer,49,Personal Travel,Eco,1739,2,4,1,5,5,5,5,2,2,1,2,5,2,5,4,0.0,neutral or dissatisfied +7567,24678,Male,Loyal Customer,41,Business travel,Business,3169,1,1,1,1,5,2,1,4,4,4,4,5,4,3,0,0.0,satisfied +7568,97952,Female,Loyal Customer,54,Business travel,Business,612,3,3,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +7569,14095,Female,disloyal Customer,24,Business travel,Business,371,5,3,5,5,1,5,1,1,2,5,4,4,1,1,0,0.0,satisfied +7570,37260,Male,Loyal Customer,43,Business travel,Business,1028,2,2,2,2,5,3,2,5,5,5,5,1,5,3,0,0.0,satisfied +7571,117196,Male,Loyal Customer,20,Personal Travel,Eco,647,3,4,3,4,1,3,4,1,1,1,3,3,4,1,19,11.0,neutral or dissatisfied +7572,70085,Male,Loyal Customer,54,Business travel,Business,2931,3,3,3,3,5,4,4,4,4,4,4,4,4,4,0,7.0,satisfied +7573,17512,Male,disloyal Customer,21,Business travel,Eco,241,3,2,3,4,5,3,5,5,1,3,3,3,4,5,0,11.0,neutral or dissatisfied +7574,125144,Female,Loyal Customer,23,Business travel,Business,1999,4,4,4,4,5,5,5,5,5,2,5,4,4,5,1,4.0,satisfied +7575,48969,Male,Loyal Customer,44,Business travel,Eco,89,4,2,2,2,4,4,4,4,1,2,5,3,2,4,0,15.0,satisfied +7576,124956,Female,Loyal Customer,58,Business travel,Business,2564,4,4,4,4,2,4,5,5,5,5,4,5,5,3,0,0.0,satisfied +7577,23111,Male,Loyal Customer,24,Business travel,Eco,300,3,3,3,3,3,3,1,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +7578,107111,Female,Loyal Customer,51,Business travel,Eco,842,2,2,4,4,5,4,3,2,2,2,2,1,2,2,2,3.0,neutral or dissatisfied +7579,103231,Male,Loyal Customer,35,Business travel,Eco Plus,351,3,3,3,3,2,3,3,4,3,2,3,3,2,3,138,133.0,neutral or dissatisfied +7580,125788,Female,Loyal Customer,58,Business travel,Business,1752,2,2,4,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +7581,106785,Male,Loyal Customer,64,Personal Travel,Eco Plus,837,1,4,1,3,4,1,4,4,4,2,4,4,5,4,15,9.0,neutral or dissatisfied +7582,13923,Female,Loyal Customer,43,Business travel,Eco,317,4,2,2,2,2,3,1,4,4,4,4,5,4,5,0,4.0,satisfied +7583,13910,Male,Loyal Customer,61,Business travel,Business,1803,2,2,2,2,4,3,1,5,5,5,5,5,5,5,0,0.0,satisfied +7584,13417,Male,disloyal Customer,30,Business travel,Eco,409,3,4,3,1,5,3,5,5,4,3,3,5,2,5,19,17.0,neutral or dissatisfied +7585,35313,Female,disloyal Customer,26,Business travel,Eco,1005,2,2,2,1,2,2,3,2,4,2,1,2,1,2,4,0.0,neutral or dissatisfied +7586,101418,Female,disloyal Customer,22,Business travel,Eco Plus,486,1,1,0,3,4,0,3,4,4,5,4,1,4,4,6,0.0,neutral or dissatisfied +7587,77474,Female,Loyal Customer,26,Personal Travel,Eco,507,3,4,3,3,5,3,3,5,3,5,4,1,4,5,2,0.0,neutral or dissatisfied +7588,124036,Male,Loyal Customer,18,Personal Travel,Eco,184,3,5,3,1,3,3,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +7589,59014,Female,Loyal Customer,24,Business travel,Business,1846,2,2,2,2,4,4,4,4,5,2,5,5,5,4,23,4.0,satisfied +7590,29738,Male,Loyal Customer,60,Business travel,Business,123,3,3,3,3,2,4,5,5,5,5,4,3,5,3,0,0.0,satisfied +7591,19596,Female,Loyal Customer,56,Personal Travel,Eco,160,3,2,0,3,3,3,3,2,2,0,2,2,2,1,19,17.0,neutral or dissatisfied +7592,54766,Female,Loyal Customer,72,Business travel,Eco Plus,787,2,5,3,3,4,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +7593,68944,Female,Loyal Customer,50,Personal Travel,Eco,646,4,1,4,3,1,4,4,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +7594,64454,Female,Loyal Customer,53,Personal Travel,Eco,989,3,3,3,4,4,3,3,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +7595,114691,Male,Loyal Customer,60,Business travel,Business,308,4,4,4,4,4,4,5,5,5,5,5,4,5,3,51,48.0,satisfied +7596,109170,Male,disloyal Customer,22,Business travel,Business,391,4,4,4,3,5,4,5,5,4,2,5,4,4,5,19,7.0,satisfied +7597,28760,Male,Loyal Customer,25,Personal Travel,Eco,1024,2,4,2,1,1,2,1,1,3,3,5,5,5,1,0,0.0,neutral or dissatisfied +7598,64827,Female,Loyal Customer,30,Business travel,Business,551,2,2,3,3,2,2,2,2,1,1,3,3,3,2,24,11.0,neutral or dissatisfied +7599,65786,Male,Loyal Customer,52,Business travel,Business,1389,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +7600,27771,Female,disloyal Customer,20,Business travel,Eco,1284,2,2,2,1,4,2,4,4,1,1,3,1,3,4,7,0.0,neutral or dissatisfied +7601,110105,Female,disloyal Customer,37,Business travel,Business,882,3,3,3,3,5,3,5,5,3,5,4,4,4,5,0,0.0,satisfied +7602,92445,Male,Loyal Customer,39,Business travel,Business,2139,1,5,1,1,5,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +7603,128195,Female,Loyal Customer,63,Personal Travel,Eco Plus,1972,2,0,2,3,2,5,4,1,1,2,5,5,1,5,0,0.0,neutral or dissatisfied +7604,88159,Female,Loyal Customer,55,Business travel,Business,2011,3,3,4,3,4,4,5,4,4,4,4,3,4,4,0,1.0,satisfied +7605,114204,Male,Loyal Customer,49,Business travel,Business,1585,5,5,5,5,5,5,5,2,2,2,2,5,2,4,8,3.0,satisfied +7606,29090,Male,Loyal Customer,68,Personal Travel,Eco,605,2,4,2,4,2,2,2,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +7607,73155,Female,Loyal Customer,49,Personal Travel,Eco,1501,3,4,3,2,2,3,4,1,1,3,1,5,1,4,4,0.0,neutral or dissatisfied +7608,64778,Male,Loyal Customer,38,Business travel,Business,282,0,0,0,3,3,4,5,1,1,1,1,4,1,4,0,0.0,satisfied +7609,114502,Female,disloyal Customer,33,Business travel,Business,373,1,1,1,3,2,1,2,2,4,1,4,3,4,2,26,28.0,neutral or dissatisfied +7610,43634,Male,Loyal Customer,42,Personal Travel,Eco Plus,252,1,5,1,3,2,1,2,2,1,2,4,4,4,2,0,0.0,neutral or dissatisfied +7611,121698,Male,disloyal Customer,30,Business travel,Business,683,2,2,2,2,2,2,2,2,3,4,4,3,5,2,0,0.0,neutral or dissatisfied +7612,111262,Male,Loyal Customer,51,Business travel,Business,459,4,4,4,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +7613,57714,Female,Loyal Customer,39,Business travel,Business,2178,5,5,5,5,4,5,5,4,4,4,4,3,4,3,31,26.0,satisfied +7614,111806,Female,Loyal Customer,51,Business travel,Business,3034,3,3,3,3,2,1,5,5,5,5,5,5,5,5,70,70.0,satisfied +7615,114885,Male,Loyal Customer,22,Business travel,Business,2865,3,5,4,5,3,3,3,3,3,5,4,4,3,3,10,3.0,neutral or dissatisfied +7616,126016,Male,Loyal Customer,55,Business travel,Business,3626,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,8.0,satisfied +7617,113179,Male,Loyal Customer,43,Personal Travel,Eco,628,2,4,3,5,2,3,2,2,5,3,5,3,5,2,77,67.0,neutral or dissatisfied +7618,62907,Male,Loyal Customer,16,Personal Travel,Business,862,2,4,2,1,4,2,4,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +7619,38475,Male,disloyal Customer,35,Business travel,Eco,846,1,2,2,3,5,2,5,5,3,3,4,2,4,5,27,27.0,neutral or dissatisfied +7620,35443,Male,Loyal Customer,50,Personal Travel,Eco,1028,5,5,5,4,5,5,5,5,5,2,5,3,5,5,16,0.0,satisfied +7621,17711,Male,Loyal Customer,9,Personal Travel,Eco,237,3,4,0,1,2,0,3,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +7622,79702,Male,Loyal Customer,29,Personal Travel,Eco,853,2,4,2,3,3,2,3,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +7623,269,Female,Loyal Customer,55,Business travel,Business,802,5,5,5,5,5,4,4,5,5,5,5,4,4,4,165,167.0,satisfied +7624,36458,Female,Loyal Customer,46,Personal Travel,Eco,867,4,4,4,2,2,5,5,3,3,4,3,4,3,3,0,0.0,satisfied +7625,115844,Female,Loyal Customer,59,Business travel,Eco,417,2,3,3,3,5,4,4,2,2,2,2,4,2,2,0,4.0,neutral or dissatisfied +7626,31236,Female,Loyal Customer,51,Business travel,Business,2870,1,2,2,2,1,3,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +7627,52134,Male,Loyal Customer,57,Business travel,Business,3430,3,3,3,3,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +7628,43895,Female,Loyal Customer,85,Business travel,Business,2971,1,3,1,1,5,3,5,5,5,5,1,5,5,5,0,0.0,satisfied +7629,53529,Male,Loyal Customer,52,Business travel,Eco Plus,2358,5,2,2,2,5,5,5,5,2,3,5,2,1,5,0,0.0,satisfied +7630,44544,Male,Loyal Customer,69,Personal Travel,Eco,157,3,1,3,3,4,3,3,4,1,2,2,2,2,4,0,1.0,neutral or dissatisfied +7631,51419,Male,Loyal Customer,59,Personal Travel,Eco Plus,262,1,3,1,4,2,1,2,2,1,3,3,3,3,2,87,104.0,neutral or dissatisfied +7632,26866,Male,Loyal Customer,40,Business travel,Business,2329,5,5,5,5,4,4,3,4,4,5,4,5,4,3,0,0.0,satisfied +7633,37705,Male,Loyal Customer,61,Personal Travel,Eco,944,3,4,3,3,4,3,5,4,3,3,1,1,2,4,0,0.0,neutral or dissatisfied +7634,73536,Male,Loyal Customer,59,Business travel,Business,2415,3,3,3,3,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +7635,48943,Female,Loyal Customer,38,Business travel,Business,2290,5,5,5,5,1,5,3,5,5,5,5,4,5,5,0,0.0,satisfied +7636,91220,Male,Loyal Customer,64,Personal Travel,Eco,444,2,2,2,3,3,2,3,3,1,4,3,2,3,3,0,0.0,neutral or dissatisfied +7637,44658,Female,disloyal Customer,35,Business travel,Eco,67,3,1,3,3,1,3,1,1,2,5,3,2,4,1,4,7.0,neutral or dissatisfied +7638,107206,Male,Loyal Customer,63,Personal Travel,Eco,402,1,4,5,2,3,5,3,3,5,5,5,5,5,3,2,0.0,neutral or dissatisfied +7639,7884,Female,Loyal Customer,41,Business travel,Eco,510,5,4,4,4,5,5,5,5,2,3,5,3,3,5,0,0.0,satisfied +7640,39900,Female,disloyal Customer,36,Business travel,Eco Plus,221,3,3,3,3,3,3,3,3,1,5,1,5,3,3,0,0.0,neutral or dissatisfied +7641,62702,Male,Loyal Customer,32,Business travel,Business,2399,3,3,3,3,5,5,5,5,3,2,3,4,5,5,0,0.0,satisfied +7642,2738,Male,Loyal Customer,42,Business travel,Business,772,1,1,1,1,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7643,128322,Male,disloyal Customer,33,Business travel,Business,370,2,2,2,4,3,2,3,3,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +7644,110861,Male,Loyal Customer,39,Business travel,Business,406,3,3,4,3,2,5,5,5,5,5,5,3,5,3,13,13.0,satisfied +7645,60835,Male,Loyal Customer,36,Business travel,Business,1754,3,4,4,4,5,2,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +7646,47190,Male,disloyal Customer,20,Business travel,Eco,620,3,1,2,3,3,2,5,3,4,5,3,3,2,3,0,9.0,neutral or dissatisfied +7647,68181,Male,Loyal Customer,22,Personal Travel,Eco,597,1,3,1,3,4,1,4,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +7648,90954,Male,Loyal Customer,49,Business travel,Business,194,1,1,1,1,5,5,1,5,5,5,3,1,5,3,32,32.0,satisfied +7649,17588,Male,Loyal Customer,48,Business travel,Eco Plus,1034,4,5,1,5,4,4,4,4,4,5,1,2,1,4,1,9.0,satisfied +7650,99980,Male,Loyal Customer,43,Business travel,Business,2597,1,3,3,3,2,3,3,2,2,2,1,1,2,2,2,5.0,neutral or dissatisfied +7651,89937,Female,Loyal Customer,63,Personal Travel,Eco,1306,2,4,2,3,5,5,4,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +7652,120419,Male,Loyal Customer,54,Business travel,Business,3002,4,4,4,4,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +7653,62062,Male,Loyal Customer,55,Personal Travel,Eco,2586,3,5,3,3,5,3,5,5,5,3,5,3,2,5,40,15.0,neutral or dissatisfied +7654,15880,Female,Loyal Customer,28,Personal Travel,Eco,332,3,4,3,4,3,3,1,3,2,2,4,2,4,3,97,123.0,neutral or dissatisfied +7655,29726,Female,Loyal Customer,47,Personal Travel,Eco,2777,2,1,2,1,2,3,2,2,1,2,2,2,3,2,0,0.0,neutral or dissatisfied +7656,84186,Male,disloyal Customer,18,Business travel,Eco,432,2,4,2,3,2,2,2,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +7657,93906,Male,Loyal Customer,66,Business travel,Eco Plus,590,3,3,3,3,3,3,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +7658,28165,Female,disloyal Customer,37,Business travel,Eco,169,1,0,1,1,3,1,3,3,4,2,4,3,2,3,0,0.0,neutral or dissatisfied +7659,113866,Female,disloyal Customer,44,Business travel,Eco,934,4,4,4,1,5,4,2,5,2,4,1,4,1,5,23,21.0,neutral or dissatisfied +7660,49339,Male,disloyal Customer,39,Business travel,Eco,262,5,1,5,2,2,5,2,2,2,5,3,3,3,2,0,0.0,satisfied +7661,84716,Female,Loyal Customer,49,Personal Travel,Business,481,2,4,2,1,4,1,5,5,5,2,5,2,5,2,0,0.0,neutral or dissatisfied +7662,12391,Male,disloyal Customer,36,Business travel,Eco,253,2,3,2,3,2,2,2,2,4,5,4,4,4,2,41,28.0,neutral or dissatisfied +7663,38664,Female,Loyal Customer,20,Personal Travel,Eco,2611,1,4,1,4,3,1,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +7664,35254,Male,Loyal Customer,57,Business travel,Business,944,5,5,5,5,3,5,4,4,4,4,4,3,4,2,4,0.0,satisfied +7665,126611,Male,Loyal Customer,9,Personal Travel,Eco,1337,3,5,3,5,1,3,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +7666,120066,Female,disloyal Customer,24,Business travel,Business,683,5,4,5,3,1,5,1,1,5,5,4,4,5,1,4,0.0,satisfied +7667,83771,Male,Loyal Customer,59,Personal Travel,Eco,926,1,5,1,1,2,1,2,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +7668,57968,Female,Loyal Customer,38,Personal Travel,Eco,1911,1,4,1,4,5,1,1,5,5,3,3,5,5,5,25,14.0,neutral or dissatisfied +7669,13053,Male,Loyal Customer,50,Personal Travel,Eco Plus,374,3,3,3,4,1,3,1,1,2,3,4,3,4,1,0,2.0,neutral or dissatisfied +7670,83178,Female,Loyal Customer,23,Business travel,Business,549,5,5,5,5,4,4,4,4,3,3,5,3,4,4,0,0.0,satisfied +7671,99874,Female,Loyal Customer,59,Business travel,Business,1436,3,3,3,3,2,4,5,5,5,5,5,4,5,4,14,28.0,satisfied +7672,26461,Male,Loyal Customer,10,Personal Travel,Eco,925,4,5,4,3,4,4,4,4,2,1,3,4,3,4,9,0.0,neutral or dissatisfied +7673,123239,Female,Loyal Customer,65,Personal Travel,Eco,631,3,4,3,3,3,3,3,5,5,3,5,1,5,2,0,10.0,neutral or dissatisfied +7674,20492,Male,Loyal Customer,37,Business travel,Business,1856,2,5,5,5,3,4,4,2,2,2,2,3,2,4,91,83.0,neutral or dissatisfied +7675,8896,Female,disloyal Customer,23,Business travel,Eco,539,2,2,3,3,1,3,5,1,1,4,4,2,3,1,0,0.0,neutral or dissatisfied +7676,120084,Male,Loyal Customer,51,Personal Travel,Eco,683,1,4,2,4,5,2,5,5,3,2,3,2,1,5,5,8.0,neutral or dissatisfied +7677,115077,Female,Loyal Customer,54,Business travel,Business,1962,5,4,5,5,3,4,4,4,4,4,4,3,4,5,48,47.0,satisfied +7678,56058,Male,Loyal Customer,20,Personal Travel,Eco,2475,3,4,3,4,3,4,4,4,3,5,4,4,3,4,0,0.0,neutral or dissatisfied +7679,18208,Male,Loyal Customer,30,Business travel,Business,179,3,3,3,3,5,4,4,5,1,3,3,4,3,5,0,18.0,satisfied +7680,104880,Male,Loyal Customer,68,Personal Travel,Eco,327,2,5,4,1,3,4,3,3,3,3,5,3,4,3,47,47.0,neutral or dissatisfied +7681,62479,Male,Loyal Customer,44,Business travel,Business,1846,2,2,2,2,3,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +7682,67460,Male,Loyal Customer,22,Personal Travel,Eco,641,1,5,1,3,2,1,2,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +7683,34677,Male,Loyal Customer,30,Business travel,Business,2525,0,0,0,2,4,4,4,4,5,3,3,5,5,4,14,22.0,satisfied +7684,68245,Female,Loyal Customer,38,Business travel,Eco,231,4,5,5,5,4,4,4,4,4,3,1,1,3,4,0,0.0,satisfied +7685,64308,Male,Loyal Customer,48,Business travel,Business,2968,1,3,3,3,3,2,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +7686,56940,Male,disloyal Customer,39,Business travel,Eco,1322,3,3,3,3,3,5,5,2,2,4,3,5,3,5,0,0.0,neutral or dissatisfied +7687,23926,Male,Loyal Customer,37,Personal Travel,Eco,589,2,4,2,4,4,2,4,4,1,4,4,3,2,4,0,0.0,neutral or dissatisfied +7688,105418,Male,disloyal Customer,42,Business travel,Business,452,2,2,2,3,3,2,3,3,5,3,5,3,4,3,14,9.0,neutral or dissatisfied +7689,101999,Female,Loyal Customer,47,Personal Travel,Eco,628,2,4,2,2,2,5,1,5,5,2,2,5,5,5,0,0.0,neutral or dissatisfied +7690,84334,Female,Loyal Customer,37,Business travel,Business,2075,3,3,3,3,2,4,5,5,5,5,5,5,5,4,26,13.0,satisfied +7691,11282,Female,Loyal Customer,67,Personal Travel,Eco,74,3,1,3,4,4,3,3,4,4,3,4,1,4,3,0,0.0,neutral or dissatisfied +7692,126671,Female,Loyal Customer,29,Business travel,Business,2276,3,3,1,3,5,5,5,5,3,3,5,3,4,5,35,14.0,satisfied +7693,20902,Male,Loyal Customer,51,Business travel,Business,3345,2,2,3,2,4,4,4,3,3,4,3,3,3,3,22,0.0,satisfied +7694,5260,Female,disloyal Customer,22,Business travel,Eco,295,2,1,2,2,4,2,4,4,4,3,3,3,2,4,0,0.0,neutral or dissatisfied +7695,4916,Male,Loyal Customer,30,Business travel,Business,1020,4,2,2,2,4,4,4,4,4,4,3,2,3,4,9,2.0,neutral or dissatisfied +7696,77640,Female,disloyal Customer,21,Business travel,Eco,731,3,3,3,3,5,3,4,5,2,2,3,3,3,5,0,0.0,neutral or dissatisfied +7697,127782,Female,Loyal Customer,53,Business travel,Business,1037,2,4,4,4,4,2,2,2,2,2,2,3,2,2,0,9.0,neutral or dissatisfied +7698,13851,Male,disloyal Customer,26,Business travel,Eco,583,5,3,5,1,4,5,4,4,1,3,1,3,3,4,0,0.0,satisfied +7699,123729,Female,Loyal Customer,59,Personal Travel,Eco Plus,214,3,3,3,3,1,4,2,4,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +7700,116150,Male,Loyal Customer,9,Personal Travel,Eco,342,3,3,3,3,2,3,2,2,2,3,2,3,3,2,0,0.0,neutral or dissatisfied +7701,89867,Female,Loyal Customer,32,Business travel,Business,1310,1,1,1,1,3,3,3,3,4,2,5,4,5,3,0,0.0,satisfied +7702,6145,Male,disloyal Customer,21,Business travel,Business,491,4,4,4,1,2,4,4,2,5,2,4,3,5,2,0,0.0,satisfied +7703,51333,Female,Loyal Customer,43,Business travel,Eco Plus,156,4,4,1,4,3,5,2,3,3,4,3,5,3,2,0,0.0,satisfied +7704,25560,Male,Loyal Customer,18,Business travel,Business,3594,4,4,4,4,4,4,4,4,1,3,1,5,1,4,7,12.0,satisfied +7705,37577,Female,Loyal Customer,75,Business travel,Eco,635,3,5,5,5,1,4,4,3,3,3,3,4,3,3,21,6.0,neutral or dissatisfied +7706,122446,Female,disloyal Customer,25,Business travel,Business,808,2,5,2,3,3,2,5,3,4,2,4,3,5,3,2,0.0,neutral or dissatisfied +7707,83237,Female,Loyal Customer,43,Business travel,Business,1956,4,4,4,4,3,3,4,4,4,4,4,5,4,4,0,3.0,satisfied +7708,126268,Male,disloyal Customer,17,Business travel,Eco,468,2,0,2,4,5,2,5,5,1,5,5,4,5,5,1,0.0,neutral or dissatisfied +7709,50677,Female,Loyal Customer,44,Personal Travel,Eco,78,3,4,3,3,4,5,5,3,3,3,3,4,3,5,18,11.0,neutral or dissatisfied +7710,129820,Female,Loyal Customer,35,Personal Travel,Eco,337,4,5,4,1,3,4,3,3,1,3,2,5,1,3,2,0.0,satisfied +7711,64829,Male,Loyal Customer,40,Business travel,Business,247,0,0,0,4,2,4,4,4,4,1,1,5,4,3,0,0.0,satisfied +7712,87517,Female,Loyal Customer,15,Personal Travel,Eco,373,2,1,2,3,5,2,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +7713,120885,Female,Loyal Customer,49,Business travel,Business,920,2,2,2,2,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +7714,13619,Female,Loyal Customer,40,Business travel,Eco,1162,5,1,1,1,5,5,5,5,4,4,3,4,5,5,32,31.0,satisfied +7715,11279,Male,Loyal Customer,69,Personal Travel,Eco,312,4,4,2,4,2,2,2,2,3,3,4,5,4,2,11,15.0,neutral or dissatisfied +7716,94453,Male,Loyal Customer,51,Business travel,Business,562,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,3.0,satisfied +7717,123556,Male,disloyal Customer,30,Business travel,Business,1773,4,3,3,1,2,3,2,2,4,2,3,3,4,2,7,15.0,neutral or dissatisfied +7718,43246,Female,Loyal Customer,48,Personal Travel,Business,347,1,1,1,4,5,3,3,2,2,1,2,1,2,3,0,0.0,neutral or dissatisfied +7719,1381,Male,disloyal Customer,26,Business travel,Eco Plus,89,3,2,3,4,2,3,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +7720,17222,Female,Loyal Customer,22,Business travel,Eco,872,5,3,5,3,5,4,4,5,5,3,3,2,3,5,72,52.0,satisfied +7721,90108,Male,Loyal Customer,45,Business travel,Business,1127,5,5,5,5,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +7722,26394,Female,disloyal Customer,46,Business travel,Eco,957,4,4,4,4,5,4,5,5,4,2,2,5,5,5,0,0.0,neutral or dissatisfied +7723,16300,Female,Loyal Customer,56,Personal Travel,Eco Plus,748,3,5,3,1,4,5,5,5,5,3,5,3,5,4,2,0.0,neutral or dissatisfied +7724,80059,Female,Loyal Customer,59,Personal Travel,Eco,1089,5,2,5,4,2,4,4,2,2,2,2,4,2,3,0,0.0,satisfied +7725,44251,Female,disloyal Customer,32,Business travel,Eco,222,3,2,3,2,2,3,2,2,1,5,2,4,1,2,0,0.0,neutral or dissatisfied +7726,26363,Female,disloyal Customer,28,Business travel,Eco,894,3,2,2,5,1,2,1,1,3,3,2,5,3,1,3,2.0,neutral or dissatisfied +7727,99292,Female,disloyal Customer,21,Business travel,Business,935,4,0,4,1,1,4,1,1,5,4,4,5,5,1,7,0.0,satisfied +7728,46889,Male,Loyal Customer,26,Business travel,Business,1941,2,4,4,4,2,2,2,2,4,4,4,1,4,2,0,2.0,neutral or dissatisfied +7729,123034,Male,Loyal Customer,43,Business travel,Business,3237,1,1,1,1,5,5,5,5,5,5,5,3,5,4,11,13.0,satisfied +7730,118565,Male,Loyal Customer,39,Business travel,Business,621,2,2,2,2,3,5,4,5,5,5,5,3,5,5,23,26.0,satisfied +7731,121342,Male,Loyal Customer,51,Business travel,Business,3876,0,0,0,3,2,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +7732,36930,Male,Loyal Customer,45,Business travel,Eco,867,4,2,2,2,4,4,4,4,3,1,4,3,4,4,0,14.0,satisfied +7733,1985,Male,Loyal Customer,23,Personal Travel,Eco,383,2,4,2,2,5,2,1,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +7734,23347,Male,Loyal Customer,54,Business travel,Eco Plus,809,5,4,4,4,5,5,5,5,5,3,2,3,2,5,9,2.0,satisfied +7735,59770,Female,disloyal Customer,19,Business travel,Eco,895,1,1,1,3,4,1,4,4,4,1,3,2,3,4,44,28.0,neutral or dissatisfied +7736,40901,Female,Loyal Customer,19,Personal Travel,Eco,501,2,4,2,3,3,2,4,3,5,4,4,3,5,3,110,91.0,neutral or dissatisfied +7737,108556,Male,disloyal Customer,24,Business travel,Business,735,5,5,5,5,3,5,3,3,3,4,4,3,4,3,0,0.0,satisfied +7738,48720,Male,Loyal Customer,58,Business travel,Business,337,1,1,1,1,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +7739,52846,Male,Loyal Customer,64,Personal Travel,Eco,1721,4,4,3,5,3,3,3,3,3,2,4,5,5,3,0,0.0,satisfied +7740,8116,Female,Loyal Customer,53,Business travel,Business,3982,2,2,2,2,4,4,5,4,4,4,4,3,4,3,0,13.0,satisfied +7741,127240,Male,Loyal Customer,68,Personal Travel,Eco Plus,1460,2,5,3,4,1,3,1,1,3,3,3,4,4,1,0,3.0,neutral or dissatisfied +7742,12905,Male,Loyal Customer,35,Business travel,Eco,359,1,1,1,1,1,2,1,1,2,5,4,2,4,1,0,0.0,neutral or dissatisfied +7743,62218,Female,Loyal Customer,12,Personal Travel,Eco,2454,2,2,2,3,2,2,1,2,2,2,3,3,3,2,0,0.0,neutral or dissatisfied +7744,80097,Female,disloyal Customer,22,Business travel,Eco,859,1,1,1,3,2,1,3,2,4,2,4,4,4,2,0,8.0,neutral or dissatisfied +7745,88262,Male,Loyal Customer,54,Business travel,Business,3344,4,4,4,4,2,4,5,4,4,4,4,4,4,4,26,22.0,satisfied +7746,97672,Male,disloyal Customer,24,Business travel,Business,272,4,1,4,3,4,3,3,4,3,2,3,3,2,3,232,235.0,neutral or dissatisfied +7747,39796,Male,Loyal Customer,62,Personal Travel,Business,272,3,1,3,3,1,4,4,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +7748,70047,Male,Loyal Customer,33,Personal Travel,Eco,583,1,5,1,1,3,1,3,3,3,2,5,4,4,3,1,17.0,neutral or dissatisfied +7749,87058,Male,Loyal Customer,24,Business travel,Business,2271,1,1,1,1,5,5,5,4,4,4,5,5,4,5,197,183.0,satisfied +7750,39840,Male,disloyal Customer,57,Business travel,Business,272,4,3,3,1,5,4,5,5,4,2,1,5,2,5,0,0.0,satisfied +7751,83104,Male,Loyal Customer,28,Personal Travel,Eco,1086,4,5,4,3,5,4,5,5,4,3,5,5,5,5,0,5.0,neutral or dissatisfied +7752,9586,Male,Loyal Customer,36,Business travel,Business,296,4,5,5,5,4,4,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +7753,77366,Female,Loyal Customer,46,Business travel,Business,599,2,4,4,4,1,4,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +7754,114325,Male,Loyal Customer,58,Personal Travel,Eco,948,4,2,4,4,2,4,2,2,4,2,2,1,3,2,0,0.0,neutral or dissatisfied +7755,69877,Male,Loyal Customer,56,Business travel,Business,2248,3,3,3,3,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +7756,34635,Female,disloyal Customer,34,Business travel,Eco,541,3,2,3,3,4,3,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +7757,24402,Male,Loyal Customer,70,Personal Travel,Business,634,3,4,3,1,5,4,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +7758,56553,Male,Loyal Customer,44,Business travel,Business,2431,4,4,4,4,4,4,5,2,2,2,2,3,2,4,0,1.0,satisfied +7759,47683,Female,Loyal Customer,24,Personal Travel,Eco,715,3,2,4,2,3,4,3,3,4,2,1,3,2,3,0,0.0,neutral or dissatisfied +7760,6138,Male,Loyal Customer,56,Business travel,Business,3342,3,3,3,3,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +7761,77772,Female,Loyal Customer,7,Personal Travel,Eco,731,1,4,1,2,3,1,3,3,2,1,4,2,1,3,0,0.0,neutral or dissatisfied +7762,79253,Female,Loyal Customer,47,Business travel,Eco,1598,1,3,3,3,2,4,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +7763,18251,Female,Loyal Customer,52,Personal Travel,Eco,179,4,2,0,4,3,4,4,1,1,0,1,3,1,2,0,8.0,neutral or dissatisfied +7764,60819,Male,Loyal Customer,33,Personal Travel,Eco,524,1,4,1,4,4,1,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +7765,66589,Male,Loyal Customer,58,Business travel,Business,761,4,1,1,1,3,3,3,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +7766,34416,Male,Loyal Customer,30,Personal Travel,Eco,728,3,5,3,1,4,3,1,4,1,3,2,1,4,4,0,0.0,neutral or dissatisfied +7767,125573,Female,Loyal Customer,11,Personal Travel,Eco,226,1,1,1,3,2,1,2,2,4,5,3,2,4,2,0,0.0,neutral or dissatisfied +7768,97829,Female,disloyal Customer,24,Business travel,Eco,395,2,4,2,3,2,2,2,2,4,5,4,1,4,2,7,16.0,neutral or dissatisfied +7769,69825,Female,Loyal Customer,40,Business travel,Eco,1055,1,2,2,2,1,1,1,4,5,3,3,1,4,1,189,171.0,neutral or dissatisfied +7770,82050,Male,Loyal Customer,56,Business travel,Business,1535,5,5,5,5,2,5,5,5,5,4,5,5,5,5,37,53.0,satisfied +7771,7783,Male,Loyal Customer,52,Business travel,Business,650,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,12.0,satisfied +7772,84242,Male,Loyal Customer,27,Personal Travel,Eco Plus,432,3,1,3,1,3,3,2,3,4,5,1,3,1,3,0,0.0,neutral or dissatisfied +7773,57858,Female,Loyal Customer,29,Personal Travel,Eco,2457,1,5,2,2,2,3,3,5,2,5,4,3,3,3,2,33.0,neutral or dissatisfied +7774,117082,Female,Loyal Customer,41,Business travel,Business,304,3,3,3,3,4,5,5,5,5,5,5,3,5,5,1,3.0,satisfied +7775,91593,Male,Loyal Customer,57,Business travel,Business,1545,2,1,1,1,2,2,2,1,3,4,4,2,4,2,178,198.0,neutral or dissatisfied +7776,84600,Female,disloyal Customer,23,Business travel,Eco,669,3,2,3,4,5,3,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +7777,44666,Male,Loyal Customer,56,Business travel,Eco,173,3,1,1,1,3,3,3,3,4,4,4,5,5,3,0,0.0,satisfied +7778,124440,Female,Loyal Customer,11,Personal Travel,Eco Plus,1262,2,5,2,4,5,2,5,5,5,5,3,3,4,5,0,0.0,neutral or dissatisfied +7779,103987,Female,Loyal Customer,60,Business travel,Business,1334,5,5,5,5,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +7780,88255,Male,Loyal Customer,30,Business travel,Business,594,1,1,1,1,4,4,4,4,5,2,4,3,4,4,8,3.0,satisfied +7781,68667,Male,disloyal Customer,24,Business travel,Eco,175,2,3,2,2,4,2,4,4,3,4,2,3,3,4,0,0.0,neutral or dissatisfied +7782,87920,Female,disloyal Customer,57,Business travel,Business,240,4,4,4,3,5,4,2,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +7783,64919,Female,Loyal Customer,49,Business travel,Business,247,2,2,2,2,3,5,5,5,5,5,5,3,5,5,8,0.0,satisfied +7784,45050,Female,disloyal Customer,34,Business travel,Eco,265,3,0,3,1,2,3,2,2,5,3,5,2,3,2,0,0.0,neutral or dissatisfied +7785,27271,Female,Loyal Customer,45,Business travel,Business,3823,4,4,4,4,5,4,5,5,5,5,5,4,5,4,108,102.0,satisfied +7786,119557,Male,Loyal Customer,68,Personal Travel,Eco,759,4,5,4,1,4,4,4,4,3,2,5,3,4,4,0,19.0,neutral or dissatisfied +7787,119913,Female,Loyal Customer,33,Business travel,Business,3296,5,5,5,5,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7788,92840,Female,Loyal Customer,32,Personal Travel,Eco,1541,3,5,3,2,5,3,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +7789,51575,Female,Loyal Customer,39,Business travel,Eco,370,4,2,2,2,4,4,4,4,2,3,3,4,3,4,15,12.0,neutral or dissatisfied +7790,42613,Female,disloyal Customer,22,Business travel,Eco,223,2,3,2,1,3,2,3,3,2,2,2,5,1,3,0,4.0,neutral or dissatisfied +7791,81663,Male,Loyal Customer,38,Business travel,Eco,907,1,5,5,5,1,1,1,1,4,3,3,1,3,1,0,6.0,neutral or dissatisfied +7792,59694,Female,Loyal Customer,32,Personal Travel,Eco,787,2,4,2,2,1,2,1,1,3,2,4,5,4,1,121,111.0,neutral or dissatisfied +7793,54163,Female,Loyal Customer,67,Business travel,Business,1400,4,3,4,3,2,3,3,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +7794,55132,Male,disloyal Customer,49,Personal Travel,Eco,1379,4,4,4,3,4,4,4,4,3,4,3,3,4,4,2,0.0,satisfied +7795,97399,Female,disloyal Customer,27,Business travel,Business,587,4,4,4,4,4,4,3,4,5,4,5,3,4,4,34,35.0,neutral or dissatisfied +7796,65807,Female,disloyal Customer,41,Business travel,Business,1389,1,1,1,3,4,1,4,4,4,3,5,3,4,4,7,4.0,neutral or dissatisfied +7797,45924,Male,disloyal Customer,36,Business travel,Eco,513,2,0,2,5,2,2,2,2,4,1,3,5,1,2,0,0.0,neutral or dissatisfied +7798,77509,Male,disloyal Customer,28,Business travel,Business,1587,4,5,5,2,4,5,1,4,3,5,4,3,5,4,0,0.0,satisfied +7799,105184,Female,Loyal Customer,9,Personal Travel,Eco,281,4,2,4,4,5,4,5,5,3,3,3,2,3,5,18,19.0,neutral or dissatisfied +7800,101668,Female,Loyal Customer,50,Personal Travel,Eco,2106,4,1,5,2,4,3,3,3,3,5,3,4,3,3,15,0.0,satisfied +7801,58098,Female,Loyal Customer,47,Business travel,Eco,589,3,1,1,1,4,4,4,3,3,3,3,1,3,2,10,4.0,neutral or dissatisfied +7802,30978,Female,Loyal Customer,40,Business travel,Eco,1476,2,1,1,1,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +7803,95969,Female,Loyal Customer,60,Business travel,Business,3204,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +7804,21724,Female,Loyal Customer,59,Business travel,Business,563,5,5,5,5,4,5,4,5,5,5,5,5,5,3,22,11.0,satisfied +7805,74643,Female,Loyal Customer,42,Business travel,Eco,788,5,5,5,5,4,5,1,5,5,5,5,1,5,1,3,0.0,satisfied +7806,50968,Male,Loyal Customer,34,Personal Travel,Eco,78,1,5,1,4,2,1,2,2,3,4,4,3,4,2,0,3.0,neutral or dissatisfied +7807,44410,Female,Loyal Customer,56,Personal Travel,Eco,323,0,5,0,3,5,1,4,5,5,0,5,3,5,1,0,3.0,satisfied +7808,81860,Male,Loyal Customer,44,Business travel,Eco Plus,1306,4,2,2,2,3,4,3,3,1,5,2,4,2,3,9,0.0,neutral or dissatisfied +7809,56408,Male,disloyal Customer,23,Business travel,Business,719,0,0,0,3,2,0,5,2,5,5,4,3,5,2,10,21.0,satisfied +7810,95952,Female,disloyal Customer,27,Business travel,Business,1235,4,4,4,2,3,4,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +7811,25414,Male,Loyal Customer,41,Personal Travel,Eco,990,1,5,2,4,1,2,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +7812,54148,Female,Loyal Customer,29,Business travel,Business,1400,3,2,2,2,3,3,3,3,1,1,3,2,3,3,62,36.0,neutral or dissatisfied +7813,73449,Male,Loyal Customer,47,Personal Travel,Eco,1197,4,4,3,1,5,3,5,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +7814,39799,Male,Loyal Customer,35,Business travel,Eco,184,4,1,1,1,4,4,4,4,1,2,5,2,3,4,0,0.0,satisfied +7815,17066,Female,Loyal Customer,56,Business travel,Business,3137,3,3,3,3,5,1,1,5,5,5,5,4,5,4,71,65.0,satisfied +7816,110674,Male,Loyal Customer,43,Business travel,Business,945,2,2,2,2,2,2,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +7817,74573,Male,Loyal Customer,22,Business travel,Business,1235,5,5,5,5,3,3,3,3,3,5,5,3,5,3,3,0.0,satisfied +7818,120089,Female,Loyal Customer,55,Business travel,Business,1679,3,3,3,3,3,4,5,4,4,4,4,4,4,3,0,3.0,satisfied +7819,25394,Female,disloyal Customer,39,Business travel,Business,990,4,4,4,2,3,4,3,3,4,1,1,3,1,3,7,0.0,neutral or dissatisfied +7820,42682,Male,Loyal Customer,58,Business travel,Eco,516,3,2,2,2,3,3,3,3,3,1,4,2,2,3,0,0.0,satisfied +7821,26666,Female,Loyal Customer,37,Business travel,Business,115,3,3,3,3,5,1,1,5,5,5,4,4,5,5,0,0.0,satisfied +7822,84603,Female,Loyal Customer,50,Business travel,Business,669,4,4,4,4,2,4,5,5,5,5,5,5,5,4,24,18.0,satisfied +7823,81199,Male,Loyal Customer,20,Business travel,Business,1426,2,2,2,2,5,5,5,5,4,5,5,5,4,5,6,4.0,satisfied +7824,78649,Male,Loyal Customer,40,Business travel,Business,2427,1,1,1,1,2,5,5,5,5,5,5,1,5,5,0,0.0,satisfied +7825,63909,Male,disloyal Customer,35,Business travel,Business,1172,3,3,3,3,5,3,2,5,3,5,3,4,4,5,0,6.0,neutral or dissatisfied +7826,99647,Female,Loyal Customer,29,Business travel,Business,1670,4,2,2,2,4,4,4,4,4,3,1,4,2,4,65,37.0,neutral or dissatisfied +7827,34861,Female,Loyal Customer,58,Business travel,Business,2248,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +7828,15879,Female,Loyal Customer,30,Personal Travel,Eco,332,4,4,4,4,2,4,2,2,4,2,5,3,4,2,0,0.0,satisfied +7829,100038,Female,disloyal Customer,39,Business travel,Eco,277,3,2,3,4,2,3,1,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +7830,2422,Female,Loyal Customer,13,Personal Travel,Eco,641,3,4,3,1,3,3,3,3,5,5,4,4,4,3,18,18.0,neutral or dissatisfied +7831,18832,Male,Loyal Customer,35,Business travel,Eco,503,3,5,5,5,3,3,3,3,3,5,4,3,4,3,3,0.0,neutral or dissatisfied +7832,95221,Male,Loyal Customer,41,Personal Travel,Eco,187,3,5,0,2,5,0,5,5,4,2,5,3,4,5,14,18.0,neutral or dissatisfied +7833,40484,Female,Loyal Customer,65,Personal Travel,Eco,175,2,5,0,4,3,4,5,1,1,0,1,3,1,5,62,71.0,neutral or dissatisfied +7834,65587,Female,disloyal Customer,20,Business travel,Eco,175,2,0,2,1,2,2,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +7835,42756,Female,disloyal Customer,37,Business travel,Business,493,3,3,3,4,1,3,1,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +7836,33921,Male,Loyal Customer,38,Personal Travel,Business,818,3,1,3,3,3,4,4,5,5,3,5,3,5,3,17,8.0,neutral or dissatisfied +7837,18328,Female,disloyal Customer,23,Business travel,Business,554,4,0,4,5,2,4,2,2,2,5,3,3,1,2,0,7.0,satisfied +7838,10282,Male,Loyal Customer,60,Business travel,Business,1919,3,3,3,3,2,5,5,5,5,4,5,5,5,3,42,37.0,satisfied +7839,19113,Female,Loyal Customer,25,Business travel,Eco,287,4,5,5,5,4,4,3,4,3,4,4,2,4,4,0,0.0,satisfied +7840,111802,Male,disloyal Customer,37,Business travel,Business,349,4,4,4,3,3,4,3,3,1,1,2,4,2,3,108,105.0,neutral or dissatisfied +7841,65438,Female,Loyal Customer,40,Personal Travel,Eco Plus,2165,3,4,3,5,1,3,1,1,3,2,5,3,5,1,5,0.0,neutral or dissatisfied +7842,107000,Male,Loyal Customer,24,Personal Travel,Eco,1036,3,4,3,2,4,3,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +7843,81639,Male,disloyal Customer,17,Business travel,Eco,907,2,2,2,3,4,2,4,4,4,3,4,1,3,4,0,0.0,neutral or dissatisfied +7844,66288,Female,Loyal Customer,9,Personal Travel,Eco Plus,550,1,2,1,2,1,1,1,1,2,3,2,1,2,1,0,0.0,neutral or dissatisfied +7845,2922,Female,Loyal Customer,41,Business travel,Business,806,5,5,5,5,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +7846,27686,Female,Loyal Customer,40,Business travel,Business,1107,2,5,5,5,4,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +7847,19810,Female,Loyal Customer,27,Business travel,Business,3322,5,5,5,5,4,4,4,4,1,4,4,1,3,4,54,61.0,satisfied +7848,77311,Male,Loyal Customer,50,Business travel,Business,626,2,2,2,2,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +7849,71773,Female,Loyal Customer,56,Business travel,Business,1744,2,2,2,2,5,3,5,4,4,4,4,3,4,3,28,34.0,satisfied +7850,28608,Female,Loyal Customer,34,Business travel,Business,2541,4,4,4,4,3,4,2,5,5,5,5,2,5,2,0,0.0,satisfied +7851,31874,Female,Loyal Customer,33,Business travel,Business,4983,1,1,1,1,4,4,4,4,1,4,5,4,3,4,0,0.0,satisfied +7852,43067,Female,Loyal Customer,33,Business travel,Business,236,4,4,4,4,4,2,5,5,5,5,5,5,5,3,49,49.0,satisfied +7853,7390,Male,Loyal Customer,42,Business travel,Business,3419,1,1,1,1,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +7854,11809,Male,Loyal Customer,68,Personal Travel,Eco Plus,429,1,4,2,1,1,2,1,1,1,1,3,5,1,1,4,0.0,neutral or dissatisfied +7855,58320,Male,Loyal Customer,29,Business travel,Eco,1739,1,0,0,3,1,0,1,1,1,1,3,4,4,1,3,12.0,neutral or dissatisfied +7856,11238,Male,Loyal Customer,48,Personal Travel,Eco,482,1,2,5,3,2,5,2,2,4,5,3,3,4,2,0,3.0,neutral or dissatisfied +7857,55777,Female,Loyal Customer,54,Business travel,Eco,646,3,5,3,5,5,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +7858,116339,Male,Loyal Customer,52,Personal Travel,Eco,480,2,2,2,3,2,2,2,2,3,4,4,4,4,2,50,47.0,neutral or dissatisfied +7859,108922,Female,Loyal Customer,57,Personal Travel,Eco,1243,2,5,2,2,2,4,4,1,1,2,1,5,1,3,29,22.0,neutral or dissatisfied +7860,98852,Male,Loyal Customer,52,Business travel,Business,1751,5,1,5,5,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +7861,69210,Female,disloyal Customer,25,Business travel,Business,733,2,4,3,2,1,3,5,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +7862,43384,Female,Loyal Customer,16,Personal Travel,Eco,387,2,4,2,2,4,2,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +7863,119461,Male,Loyal Customer,60,Business travel,Business,2085,5,5,5,5,3,5,4,4,4,4,4,3,4,4,7,0.0,satisfied +7864,126742,Female,disloyal Customer,35,Business travel,Eco,2370,3,3,3,3,2,3,2,2,3,5,1,1,1,2,2,0.0,neutral or dissatisfied +7865,108029,Female,Loyal Customer,46,Business travel,Business,3345,0,1,1,3,2,5,4,3,3,3,4,3,3,4,0,0.0,satisfied +7866,33515,Female,Loyal Customer,46,Business travel,Eco,1554,5,2,5,2,2,2,5,5,5,5,5,2,5,1,0,0.0,satisfied +7867,20782,Female,disloyal Customer,27,Business travel,Eco,457,2,4,1,2,4,1,4,4,1,2,2,2,1,4,29,32.0,neutral or dissatisfied +7868,72531,Female,Loyal Customer,35,Business travel,Business,3836,2,4,4,4,4,3,3,2,2,2,2,1,2,4,1,0.0,neutral or dissatisfied +7869,41771,Male,Loyal Customer,18,Personal Travel,Eco,872,1,5,1,4,3,1,3,3,3,2,4,3,4,3,0,4.0,neutral or dissatisfied +7870,65042,Male,Loyal Customer,18,Personal Travel,Eco,247,2,4,2,1,1,2,1,1,5,4,5,4,4,1,4,0.0,neutral or dissatisfied +7871,62349,Female,Loyal Customer,54,Business travel,Business,1735,4,4,4,4,4,5,5,4,4,4,4,4,4,3,73,44.0,satisfied +7872,88905,Male,Loyal Customer,34,Personal Travel,Eco,859,4,4,4,2,1,4,1,1,4,4,5,5,4,1,0,0.0,satisfied +7873,123324,Female,Loyal Customer,44,Business travel,Business,3822,4,2,2,2,3,3,4,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +7874,64553,Female,disloyal Customer,25,Business travel,Business,190,2,0,2,3,2,2,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +7875,26708,Female,Loyal Customer,37,Personal Travel,Eco,515,2,1,2,4,1,2,1,1,4,5,3,3,3,1,47,44.0,neutral or dissatisfied +7876,3396,Female,disloyal Customer,68,Business travel,Business,240,2,2,2,2,3,2,4,3,2,1,2,2,2,3,0,2.0,neutral or dissatisfied +7877,24612,Female,Loyal Customer,17,Business travel,Business,666,3,3,3,3,3,3,3,3,1,5,3,1,4,3,45,44.0,neutral or dissatisfied +7878,83955,Female,Loyal Customer,38,Business travel,Business,2949,2,2,4,2,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +7879,10583,Male,Loyal Customer,30,Business travel,Business,2175,4,4,4,4,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +7880,17981,Female,Loyal Customer,45,Business travel,Business,2212,2,4,3,4,5,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +7881,96857,Female,disloyal Customer,14,Business travel,Eco,781,3,3,3,4,3,3,4,3,4,3,3,3,3,3,0,11.0,neutral or dissatisfied +7882,2437,Female,Loyal Customer,37,Personal Travel,Eco,641,4,4,3,2,2,3,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +7883,16007,Female,Loyal Customer,25,Business travel,Business,780,2,3,3,3,2,2,2,2,2,4,3,2,1,2,115,232.0,neutral or dissatisfied +7884,15097,Male,Loyal Customer,40,Personal Travel,Eco,239,4,5,4,3,1,4,1,1,5,2,4,4,5,1,3,0.0,satisfied +7885,107628,Male,Loyal Customer,61,Personal Travel,Eco,423,5,4,5,1,4,5,3,4,3,2,3,5,2,4,0,0.0,satisfied +7886,51742,Female,Loyal Customer,53,Personal Travel,Eco,451,5,4,5,3,5,4,4,4,4,5,4,5,4,5,0,0.0,satisfied +7887,16579,Male,Loyal Customer,76,Business travel,Business,2441,3,3,3,3,4,1,4,5,5,4,5,2,5,4,0,0.0,satisfied +7888,129536,Female,Loyal Customer,26,Business travel,Business,2342,2,4,4,4,2,2,2,2,2,4,4,4,4,2,16,6.0,neutral or dissatisfied +7889,120801,Female,disloyal Customer,30,Business travel,Eco,666,1,2,1,3,4,1,5,4,1,4,4,4,3,4,1,0.0,neutral or dissatisfied +7890,93801,Male,Loyal Customer,54,Business travel,Business,859,3,1,1,1,4,1,1,3,3,4,3,2,3,1,2,0.0,neutral or dissatisfied +7891,47856,Female,Loyal Customer,53,Business travel,Business,838,1,1,1,1,3,3,4,4,4,4,4,3,4,1,0,0.0,satisfied +7892,835,Male,Loyal Customer,34,Business travel,Business,354,2,2,2,2,1,3,3,2,2,2,2,1,2,4,31,29.0,neutral or dissatisfied +7893,52163,Male,Loyal Customer,54,Business travel,Business,3477,5,2,5,5,5,5,3,5,5,5,5,2,5,2,10,43.0,satisfied +7894,125596,Female,disloyal Customer,24,Business travel,Eco,1587,5,5,5,3,1,5,1,1,4,3,3,4,4,1,0,6.0,satisfied +7895,62007,Male,disloyal Customer,42,Business travel,Business,720,4,4,4,1,4,4,4,4,3,4,5,5,4,4,0,10.0,satisfied +7896,51521,Female,Loyal Customer,37,Business travel,Eco,509,4,4,4,4,4,4,4,4,5,2,1,1,1,4,0,0.0,satisfied +7897,76942,Female,Loyal Customer,39,Business travel,Business,1990,1,1,4,1,4,3,5,3,3,4,3,4,3,3,0,11.0,satisfied +7898,10985,Male,Loyal Customer,36,Business travel,Business,74,1,2,3,2,1,4,3,2,2,2,1,4,2,3,55,52.0,neutral or dissatisfied +7899,25298,Male,Loyal Customer,56,Business travel,Business,432,2,2,2,2,4,5,5,4,4,4,4,3,4,4,32,27.0,satisfied +7900,95295,Male,Loyal Customer,32,Personal Travel,Eco,248,2,5,2,2,2,2,1,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +7901,60569,Female,disloyal Customer,45,Business travel,Business,1290,1,2,2,3,1,1,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +7902,22606,Male,Loyal Customer,57,Business travel,Business,250,3,2,2,2,5,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +7903,111600,Female,Loyal Customer,59,Business travel,Eco Plus,359,3,5,5,5,3,4,3,3,3,3,3,3,3,1,5,0.0,neutral or dissatisfied +7904,72623,Female,Loyal Customer,18,Personal Travel,Eco,918,1,5,1,3,1,1,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +7905,75528,Male,Loyal Customer,65,Business travel,Business,337,3,1,1,1,3,3,3,3,3,3,3,3,3,3,13,2.0,neutral or dissatisfied +7906,127521,Male,disloyal Customer,17,Business travel,Business,1009,5,4,5,3,1,5,1,1,4,4,5,5,4,1,41,37.0,satisfied +7907,28649,Female,Loyal Customer,33,Personal Travel,Eco,2541,2,4,2,2,4,2,4,4,4,4,4,4,4,4,17,0.0,neutral or dissatisfied +7908,50278,Male,disloyal Customer,30,Business travel,Eco,110,3,3,3,3,4,3,4,4,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +7909,83534,Female,Loyal Customer,51,Business travel,Business,1121,3,3,3,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +7910,30135,Male,Loyal Customer,24,Personal Travel,Eco,399,1,5,1,4,5,1,4,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +7911,109765,Male,Loyal Customer,14,Business travel,Business,1165,5,5,5,5,4,4,4,4,3,4,4,5,4,4,8,6.0,satisfied +7912,109432,Male,Loyal Customer,47,Business travel,Business,3295,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +7913,70882,Female,Loyal Customer,58,Personal Travel,Eco,1814,3,4,3,1,5,5,4,4,4,3,2,3,4,4,0,0.0,neutral or dissatisfied +7914,84373,Male,disloyal Customer,23,Business travel,Eco,591,3,0,4,2,4,4,4,4,3,2,4,3,4,4,4,0.0,neutral or dissatisfied +7915,116774,Male,Loyal Customer,51,Personal Travel,Eco Plus,480,2,4,2,4,5,2,5,5,4,3,4,1,4,5,12,6.0,neutral or dissatisfied +7916,106867,Male,Loyal Customer,17,Business travel,Eco,577,2,2,2,2,2,2,4,2,3,5,3,4,3,2,114,90.0,neutral or dissatisfied +7917,107411,Male,Loyal Customer,54,Business travel,Eco,468,3,5,5,5,3,3,3,3,2,4,4,1,4,3,12,4.0,neutral or dissatisfied +7918,701,Male,disloyal Customer,18,Business travel,Eco,270,2,4,2,3,1,2,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +7919,61726,Female,disloyal Customer,24,Business travel,Eco,1379,3,3,3,3,3,3,3,3,2,4,5,3,4,3,10,2.0,neutral or dissatisfied +7920,78188,Male,Loyal Customer,49,Business travel,Business,3833,5,5,5,5,4,4,4,4,4,4,4,5,4,5,0,25.0,satisfied +7921,105721,Male,Loyal Customer,61,Business travel,Business,925,2,3,1,3,5,3,2,2,2,2,2,1,2,4,0,27.0,neutral or dissatisfied +7922,53724,Male,Loyal Customer,49,Personal Travel,Eco,1297,3,3,3,3,5,3,5,5,3,5,3,1,4,5,11,13.0,neutral or dissatisfied +7923,105069,Male,Loyal Customer,23,Personal Travel,Business,220,3,3,3,4,3,3,4,3,1,4,1,2,3,3,34,21.0,neutral or dissatisfied +7924,11107,Female,Loyal Customer,37,Personal Travel,Eco,667,3,4,3,2,2,3,2,2,5,4,5,4,5,2,0,10.0,neutral or dissatisfied +7925,105481,Male,Loyal Customer,28,Business travel,Business,1794,2,2,2,2,4,4,4,4,4,2,4,3,5,4,19,16.0,satisfied +7926,15980,Female,Loyal Customer,10,Personal Travel,Business,780,1,2,1,2,1,5,5,1,1,1,1,5,2,5,265,265.0,neutral or dissatisfied +7927,98946,Female,Loyal Customer,44,Business travel,Business,569,1,1,1,1,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +7928,54707,Female,Loyal Customer,57,Business travel,Business,2201,2,2,3,2,1,2,5,4,4,5,4,2,4,4,10,1.0,satisfied +7929,12138,Male,Loyal Customer,34,Business travel,Business,2579,1,5,5,5,5,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +7930,1879,Female,Loyal Customer,34,Personal Travel,Eco,931,3,5,3,5,5,3,5,5,4,4,5,4,4,5,40,83.0,neutral or dissatisfied +7931,71883,Male,Loyal Customer,28,Personal Travel,Eco,1744,3,4,3,4,4,3,4,4,3,3,3,3,5,4,87,74.0,neutral or dissatisfied +7932,112327,Male,Loyal Customer,42,Business travel,Business,1760,3,1,2,1,4,4,4,3,3,3,3,3,3,2,43,24.0,neutral or dissatisfied +7933,79622,Male,disloyal Customer,34,Business travel,Eco,762,1,0,0,3,4,0,4,4,1,3,2,3,2,4,0,4.0,neutral or dissatisfied +7934,126986,Female,Loyal Customer,25,Business travel,Business,651,1,1,3,1,2,3,2,2,5,3,4,3,5,2,0,0.0,satisfied +7935,22359,Female,Loyal Customer,44,Business travel,Business,3220,2,3,4,3,4,4,4,4,4,3,2,4,4,1,0,0.0,neutral or dissatisfied +7936,1053,Female,Loyal Customer,20,Personal Travel,Eco,164,5,4,5,2,1,5,1,1,5,3,5,4,5,1,0,0.0,satisfied +7937,58626,Male,Loyal Customer,60,Business travel,Business,2449,3,1,1,1,5,3,4,3,3,3,3,4,3,2,13,1.0,neutral or dissatisfied +7938,55015,Male,Loyal Customer,38,Business travel,Business,2272,4,4,4,4,2,5,5,4,4,4,4,4,4,5,26,26.0,satisfied +7939,79153,Male,Loyal Customer,26,Personal Travel,Eco Plus,226,3,4,3,5,5,3,5,5,4,5,5,4,4,5,6,2.0,neutral or dissatisfied +7940,124356,Female,Loyal Customer,30,Business travel,Business,2046,4,4,2,4,4,5,4,4,3,3,5,5,4,4,0,33.0,satisfied +7941,120061,Male,disloyal Customer,43,Business travel,Business,683,2,2,2,4,1,2,4,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +7942,1535,Male,Loyal Customer,34,Business travel,Business,922,1,1,1,1,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +7943,5343,Male,Loyal Customer,58,Business travel,Business,1721,4,3,4,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +7944,69018,Male,disloyal Customer,22,Business travel,Eco,1389,2,2,2,5,5,2,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +7945,47877,Female,Loyal Customer,38,Business travel,Eco,846,3,1,1,1,3,3,3,3,3,5,2,4,3,3,0,0.0,neutral or dissatisfied +7946,61919,Male,Loyal Customer,27,Business travel,Business,3363,1,1,1,1,4,4,4,4,5,4,5,5,4,4,0,2.0,satisfied +7947,121797,Male,disloyal Customer,26,Business travel,Business,366,2,0,2,3,4,2,4,4,4,2,5,3,5,4,12,1.0,neutral or dissatisfied +7948,111082,Male,Loyal Customer,60,Personal Travel,Eco,197,3,4,3,5,3,3,1,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +7949,97775,Male,Loyal Customer,46,Business travel,Business,471,1,1,1,1,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +7950,117501,Male,Loyal Customer,38,Personal Travel,Eco,507,3,3,3,4,1,3,1,1,2,2,3,2,3,1,0,0.0,neutral or dissatisfied +7951,102096,Male,disloyal Customer,34,Business travel,Business,258,4,4,4,1,1,4,1,1,3,4,5,4,4,1,82,84.0,neutral or dissatisfied +7952,25362,Male,Loyal Customer,25,Business travel,Business,1975,1,1,1,1,5,5,5,5,2,1,4,3,3,5,0,0.0,satisfied +7953,19786,Male,Loyal Customer,56,Business travel,Eco,667,1,3,1,3,1,1,1,1,1,3,3,4,2,1,39,35.0,neutral or dissatisfied +7954,62999,Female,Loyal Customer,35,Business travel,Business,853,2,5,5,5,2,4,4,2,2,2,2,4,2,3,0,18.0,neutral or dissatisfied +7955,28263,Female,Loyal Customer,16,Personal Travel,Eco,1542,5,4,5,4,1,5,1,1,3,3,4,4,5,1,0,0.0,satisfied +7956,45632,Female,Loyal Customer,51,Business travel,Business,113,1,3,3,3,1,3,3,2,2,3,1,2,2,3,0,22.0,neutral or dissatisfied +7957,117860,Female,Loyal Customer,39,Business travel,Business,1875,4,4,4,4,2,3,3,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +7958,97979,Male,Loyal Customer,67,Personal Travel,Eco,612,3,4,3,2,2,3,2,2,5,4,3,1,1,2,2,2.0,neutral or dissatisfied +7959,90279,Male,Loyal Customer,27,Business travel,Business,3970,2,3,3,3,2,1,2,2,4,1,2,4,2,2,8,11.0,neutral or dissatisfied +7960,112146,Male,Loyal Customer,49,Business travel,Eco,895,2,1,1,1,3,2,3,3,3,2,2,1,3,3,9,0.0,neutral or dissatisfied +7961,79864,Male,Loyal Customer,36,Business travel,Business,3430,1,1,1,1,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +7962,110544,Female,Loyal Customer,52,Business travel,Business,2553,2,4,4,4,5,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +7963,106411,Male,Loyal Customer,28,Personal Travel,Eco,551,2,3,2,2,3,2,3,3,3,2,2,5,1,3,0,0.0,neutral or dissatisfied +7964,29163,Female,Loyal Customer,16,Business travel,Eco Plus,978,0,4,0,2,3,0,3,3,1,1,1,1,5,3,0,10.0,satisfied +7965,102480,Female,Loyal Customer,46,Personal Travel,Eco,397,4,4,4,2,4,5,5,4,5,4,5,5,4,5,175,169.0,neutral or dissatisfied +7966,109601,Female,Loyal Customer,18,Personal Travel,Eco Plus,861,3,4,3,2,4,3,2,4,5,3,3,3,4,4,21,12.0,neutral or dissatisfied +7967,53482,Female,Loyal Customer,39,Business travel,Business,3574,2,1,4,1,5,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +7968,33666,Female,Loyal Customer,62,Business travel,Eco Plus,399,3,5,5,5,3,2,3,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +7969,9978,Female,Loyal Customer,19,Personal Travel,Eco,515,4,4,4,3,4,4,4,4,5,3,4,3,5,4,15,0.0,neutral or dissatisfied +7970,103340,Female,Loyal Customer,27,Personal Travel,Eco,1139,3,5,4,1,5,4,4,5,3,2,3,4,5,5,0,5.0,neutral or dissatisfied +7971,52189,Male,disloyal Customer,40,Business travel,Eco,261,2,0,2,4,5,2,5,5,4,3,5,4,5,5,0,0.0,neutral or dissatisfied +7972,18651,Male,Loyal Customer,23,Personal Travel,Eco,253,1,3,0,4,4,0,4,4,4,5,4,3,4,4,108,117.0,neutral or dissatisfied +7973,37604,Male,Loyal Customer,39,Personal Travel,Eco,1028,3,5,3,2,4,3,5,4,3,2,5,4,4,4,49,34.0,neutral or dissatisfied +7974,112411,Female,Loyal Customer,40,Business travel,Business,1643,5,5,5,5,3,5,4,4,4,4,4,5,4,3,23,15.0,satisfied +7975,100733,Male,Loyal Customer,33,Business travel,Eco,328,4,4,1,4,4,4,4,4,2,1,3,4,3,4,40,38.0,neutral or dissatisfied +7976,94370,Female,Loyal Customer,51,Business travel,Business,293,0,0,0,2,4,4,5,4,4,4,4,5,4,4,57,31.0,satisfied +7977,5930,Male,Loyal Customer,26,Personal Travel,Eco,173,2,4,2,3,5,2,5,5,4,4,2,3,1,5,0,0.0,neutral or dissatisfied +7978,126374,Female,Loyal Customer,31,Personal Travel,Eco,507,3,4,1,5,5,1,5,5,2,2,4,3,5,5,0,0.0,neutral or dissatisfied +7979,47871,Female,Loyal Customer,66,Business travel,Eco,834,2,4,4,4,5,3,4,3,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +7980,81967,Female,Loyal Customer,44,Business travel,Business,1522,2,3,5,3,4,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +7981,30939,Female,disloyal Customer,24,Business travel,Eco,1024,1,1,1,4,1,1,1,1,2,5,4,1,4,1,22,43.0,neutral or dissatisfied +7982,83564,Male,Loyal Customer,65,Personal Travel,Business,936,4,1,4,4,4,4,4,2,2,4,4,4,2,2,0,0.0,satisfied +7983,123649,Female,Loyal Customer,48,Business travel,Business,214,4,4,4,4,2,5,5,5,5,5,5,3,5,3,0,3.0,satisfied +7984,36822,Female,Loyal Customer,33,Business travel,Business,2797,2,2,2,2,1,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +7985,25465,Male,Loyal Customer,28,Business travel,Business,1609,3,3,3,3,5,5,5,5,3,4,5,5,4,5,0,0.0,satisfied +7986,116424,Male,Loyal Customer,52,Personal Travel,Eco,372,3,2,3,4,5,3,5,5,3,3,4,2,3,5,0,0.0,neutral or dissatisfied +7987,18050,Female,disloyal Customer,34,Business travel,Eco,488,2,1,2,4,3,2,5,3,2,3,4,4,4,3,0,0.0,neutral or dissatisfied +7988,10664,Male,disloyal Customer,24,Business travel,Eco,482,4,3,4,2,2,4,2,2,4,3,4,4,4,2,0,0.0,satisfied +7989,84571,Female,Loyal Customer,54,Business travel,Business,2486,3,3,3,3,4,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +7990,123117,Female,Loyal Customer,39,Business travel,Business,468,1,1,1,1,3,4,5,2,2,2,2,5,2,3,2,18.0,satisfied +7991,123883,Male,disloyal Customer,42,Business travel,Eco,144,3,5,3,1,4,3,4,4,4,1,5,1,1,4,0,0.0,neutral or dissatisfied +7992,46898,Male,Loyal Customer,56,Business travel,Business,3194,2,2,5,2,3,4,3,2,2,2,2,2,2,2,0,8.0,neutral or dissatisfied +7993,10051,Female,Loyal Customer,51,Business travel,Eco,326,3,1,1,1,5,3,3,3,3,3,3,4,3,3,55,44.0,neutral or dissatisfied +7994,106549,Female,Loyal Customer,30,Business travel,Business,719,1,1,1,1,4,4,4,4,5,4,5,2,2,4,15,11.0,satisfied +7995,72112,Female,Loyal Customer,76,Business travel,Business,2014,1,1,1,1,5,4,3,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +7996,110405,Male,Loyal Customer,59,Business travel,Business,2078,1,5,3,5,1,2,2,1,1,1,1,2,1,1,17,8.0,neutral or dissatisfied +7997,122416,Female,Loyal Customer,46,Business travel,Business,1916,2,2,2,2,2,3,4,4,4,5,4,4,4,5,0,0.0,satisfied +7998,70549,Female,Loyal Customer,30,Business travel,Business,1541,4,4,4,4,3,4,3,3,3,2,5,3,4,3,55,50.0,satisfied +7999,89152,Female,disloyal Customer,29,Business travel,Eco,908,4,4,4,3,3,4,3,3,1,2,1,5,3,3,3,0.0,satisfied +8000,30883,Male,Loyal Customer,38,Personal Travel,Eco,1546,2,5,3,3,1,3,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +8001,116825,Male,Loyal Customer,45,Business travel,Business,647,5,5,5,5,4,5,4,2,2,3,2,4,2,5,0,0.0,satisfied +8002,28597,Female,Loyal Customer,44,Business travel,Business,2614,5,5,5,5,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +8003,30150,Male,Loyal Customer,14,Personal Travel,Eco,82,3,2,3,3,4,3,4,4,4,5,4,1,3,4,7,0.0,neutral or dissatisfied +8004,128969,Male,Loyal Customer,50,Personal Travel,Eco,414,2,5,2,2,5,2,1,5,3,1,3,5,1,5,0,0.0,neutral or dissatisfied +8005,80975,Male,Loyal Customer,40,Business travel,Business,3472,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +8006,16042,Female,Loyal Customer,64,Personal Travel,Eco Plus,780,3,5,3,2,4,2,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +8007,4511,Male,Loyal Customer,36,Personal Travel,Eco,551,2,5,2,1,4,2,4,4,2,2,5,3,3,4,0,8.0,neutral or dissatisfied +8008,100661,Female,Loyal Customer,54,Business travel,Business,889,4,4,4,4,3,5,5,5,5,5,5,3,5,5,3,1.0,satisfied +8009,27526,Female,Loyal Customer,10,Personal Travel,Eco,956,2,4,2,4,4,2,1,4,4,5,5,3,5,4,0,0.0,neutral or dissatisfied +8010,33593,Male,Loyal Customer,44,Business travel,Eco,413,4,2,2,2,4,4,4,4,5,3,5,1,5,4,7,8.0,satisfied +8011,75022,Female,Loyal Customer,45,Business travel,Eco,236,3,1,4,4,2,4,4,3,3,3,3,4,3,1,0,19.0,neutral or dissatisfied +8012,38757,Female,disloyal Customer,27,Business travel,Eco,354,1,0,0,1,4,0,3,4,5,3,4,1,4,4,0,0.0,neutral or dissatisfied +8013,57783,Female,Loyal Customer,35,Personal Travel,Eco,2704,2,1,2,3,2,1,1,1,2,3,3,1,1,1,2,0.0,neutral or dissatisfied +8014,129372,Male,Loyal Customer,53,Business travel,Business,2454,2,2,2,2,2,5,5,5,5,5,5,5,5,4,1,0.0,satisfied +8015,126787,Female,Loyal Customer,60,Business travel,Business,2296,3,3,3,3,5,5,5,3,3,4,3,4,3,3,6,0.0,satisfied +8016,104125,Male,Loyal Customer,44,Business travel,Business,3322,4,4,4,4,2,4,4,3,3,3,3,5,3,5,7,0.0,satisfied +8017,101248,Male,Loyal Customer,67,Business travel,Eco Plus,1587,3,5,5,5,2,3,2,2,2,2,3,4,4,2,0,0.0,neutral or dissatisfied +8018,29235,Female,Loyal Customer,16,Business travel,Eco,834,5,5,5,5,5,5,4,5,5,3,4,3,2,5,0,0.0,satisfied +8019,37898,Male,Loyal Customer,43,Business travel,Business,2096,2,2,2,2,4,2,5,5,5,5,5,3,5,3,5,0.0,satisfied +8020,18466,Female,Loyal Customer,38,Business travel,Business,3437,5,5,5,5,3,4,2,5,5,5,5,5,5,4,0,0.0,satisfied +8021,72821,Female,Loyal Customer,43,Business travel,Business,1013,1,1,1,1,5,4,4,4,4,5,4,5,4,3,10,0.0,satisfied +8022,128899,Female,Loyal Customer,66,Personal Travel,Eco,2454,4,2,4,3,2,2,2,1,1,4,1,1,1,3,2,0.0,neutral or dissatisfied +8023,58403,Male,Loyal Customer,24,Business travel,Business,3996,2,2,2,2,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +8024,6366,Male,Loyal Customer,53,Business travel,Business,315,3,4,4,4,5,2,2,3,3,2,3,3,3,3,7,15.0,neutral or dissatisfied +8025,1285,Male,Loyal Customer,25,Personal Travel,Eco,134,1,4,1,3,1,1,2,1,4,1,4,1,4,1,0,2.0,neutral or dissatisfied +8026,116257,Female,Loyal Customer,43,Personal Travel,Eco,390,2,5,2,1,2,5,5,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +8027,84137,Male,Loyal Customer,13,Personal Travel,Eco,782,4,4,4,4,2,4,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +8028,92664,Female,Loyal Customer,10,Personal Travel,Eco Plus,453,5,5,5,5,1,5,1,1,3,5,5,4,4,1,0,0.0,satisfied +8029,26364,Female,Loyal Customer,46,Business travel,Eco,861,5,1,1,1,2,5,2,5,5,5,5,4,5,3,19,33.0,satisfied +8030,116571,Male,Loyal Customer,44,Business travel,Business,371,3,3,3,3,4,4,5,3,3,2,3,4,3,5,40,39.0,satisfied +8031,80553,Male,Loyal Customer,45,Business travel,Business,1747,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +8032,16657,Female,disloyal Customer,25,Business travel,Eco,605,4,4,4,3,2,4,2,2,3,3,3,3,4,2,12,16.0,neutral or dissatisfied +8033,127348,Male,Loyal Customer,68,Business travel,Eco,107,5,1,1,1,5,5,5,5,1,1,4,3,1,5,10,7.0,satisfied +8034,104434,Female,Loyal Customer,23,Personal Travel,Eco,1011,5,4,5,3,1,5,1,1,5,2,2,2,3,1,0,0.0,satisfied +8035,66577,Female,Loyal Customer,48,Personal Travel,Eco,624,3,3,3,3,2,4,4,5,5,3,5,2,5,4,4,12.0,neutral or dissatisfied +8036,45796,Male,Loyal Customer,52,Business travel,Business,391,4,4,5,4,4,4,3,4,4,4,4,2,4,4,3,6.0,neutral or dissatisfied +8037,65746,Female,Loyal Customer,13,Personal Travel,Eco,1061,1,5,1,5,5,1,5,5,4,4,4,3,5,5,10,0.0,neutral or dissatisfied +8038,6150,Male,disloyal Customer,26,Business travel,Eco,409,3,4,2,3,4,2,4,4,4,4,3,4,4,4,40,33.0,neutral or dissatisfied +8039,101800,Female,Loyal Customer,37,Business travel,Business,1521,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +8040,76208,Female,Loyal Customer,31,Business travel,Business,2422,4,4,1,4,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +8041,52378,Male,Loyal Customer,14,Personal Travel,Eco,370,1,2,1,2,2,1,2,2,2,4,3,3,3,2,0,0.0,neutral or dissatisfied +8042,24700,Male,Loyal Customer,46,Business travel,Eco,397,4,1,1,1,4,4,4,4,1,3,5,1,3,4,0,0.0,satisfied +8043,70668,Female,Loyal Customer,54,Business travel,Business,447,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +8044,46597,Female,Loyal Customer,25,Business travel,Business,1534,4,3,4,4,4,3,4,4,3,1,4,4,3,4,52,48.0,neutral or dissatisfied +8045,91333,Female,Loyal Customer,37,Personal Travel,Eco Plus,223,3,4,3,1,4,3,4,4,4,4,4,4,5,4,1,12.0,neutral or dissatisfied +8046,37182,Male,Loyal Customer,63,Personal Travel,Eco,1129,3,5,3,3,4,3,4,4,4,4,3,3,4,4,58,47.0,neutral or dissatisfied +8047,58486,Female,Loyal Customer,59,Business travel,Business,719,1,1,1,1,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +8048,29517,Male,Loyal Customer,18,Personal Travel,Business,1009,2,3,2,4,4,2,4,4,2,2,1,5,5,4,0,0.0,neutral or dissatisfied +8049,5681,Male,Loyal Customer,39,Business travel,Business,3928,0,5,0,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +8050,114695,Male,Loyal Customer,48,Business travel,Business,2189,1,1,5,1,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +8051,41104,Male,Loyal Customer,39,Business travel,Eco,140,5,2,4,2,5,5,5,5,1,5,5,4,5,5,0,0.0,satisfied +8052,13091,Male,Loyal Customer,59,Business travel,Eco,595,4,2,2,2,4,4,4,4,3,3,2,1,4,4,58,48.0,satisfied +8053,68297,Male,Loyal Customer,24,Business travel,Business,1797,1,1,1,1,4,4,4,4,3,3,3,3,4,4,0,2.0,satisfied +8054,88514,Male,Loyal Customer,50,Personal Travel,Eco,545,2,3,2,3,1,2,1,1,4,3,3,2,3,1,0,0.0,neutral or dissatisfied +8055,32739,Female,Loyal Customer,58,Business travel,Eco,101,1,2,2,2,5,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +8056,41046,Male,Loyal Customer,54,Personal Travel,Eco,989,3,2,3,3,1,3,1,1,2,3,4,4,3,1,0,34.0,neutral or dissatisfied +8057,48493,Female,Loyal Customer,25,Business travel,Business,1838,2,2,2,2,4,4,4,4,3,4,2,2,1,4,14,0.0,satisfied +8058,563,Female,Loyal Customer,29,Business travel,Business,1588,1,1,1,1,1,1,1,1,2,5,3,2,3,1,0,0.0,neutral or dissatisfied +8059,19753,Male,Loyal Customer,35,Business travel,Business,462,1,1,1,1,3,3,5,5,5,5,5,5,5,3,32,20.0,satisfied +8060,1061,Female,Loyal Customer,67,Personal Travel,Eco,158,3,5,3,2,5,1,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +8061,114021,Female,Loyal Customer,34,Personal Travel,Eco,1844,3,4,3,2,1,3,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +8062,94521,Male,Loyal Customer,44,Business travel,Business,1526,5,5,5,5,2,5,4,4,4,4,4,4,4,3,23,6.0,satisfied +8063,38838,Male,Loyal Customer,32,Business travel,Eco Plus,387,4,2,2,2,4,4,4,4,3,2,3,1,4,4,0,1.0,satisfied +8064,110670,Female,Loyal Customer,40,Business travel,Business,3952,2,4,4,4,5,3,3,2,2,2,2,3,2,1,17,8.0,neutral or dissatisfied +8065,92984,Male,Loyal Customer,39,Business travel,Business,2775,5,5,5,5,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +8066,3838,Female,Loyal Customer,53,Personal Travel,Eco,650,3,5,3,4,2,5,4,5,5,3,5,3,5,2,0,5.0,neutral or dissatisfied +8067,96150,Male,Loyal Customer,54,Business travel,Business,3994,5,4,5,5,2,5,4,3,3,2,3,4,3,4,0,1.0,satisfied +8068,117772,Male,Loyal Customer,42,Business travel,Business,1891,1,1,1,1,2,3,4,5,5,5,5,4,5,5,36,22.0,satisfied +8069,112684,Male,Loyal Customer,39,Business travel,Business,3762,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,2.0,satisfied +8070,76202,Male,Loyal Customer,54,Personal Travel,Eco,2422,4,4,4,3,4,4,4,4,4,3,4,4,5,4,0,0.0,satisfied +8071,19096,Male,Loyal Customer,31,Personal Travel,Business,323,4,1,1,3,2,1,5,2,2,3,3,4,3,2,0,4.0,satisfied +8072,86401,Female,Loyal Customer,57,Business travel,Business,712,2,2,2,2,5,4,5,4,4,4,4,5,4,5,11,0.0,satisfied +8073,22047,Female,Loyal Customer,33,Personal Travel,Business,304,1,4,1,4,4,4,3,3,3,1,3,2,3,4,5,0.0,neutral or dissatisfied +8074,68183,Female,Loyal Customer,35,Personal Travel,Eco,603,3,4,3,4,2,3,2,2,2,2,2,3,2,2,79,97.0,neutral or dissatisfied +8075,36576,Female,Loyal Customer,48,Business travel,Business,3287,1,2,2,2,1,3,2,1,1,2,1,2,1,3,0,12.0,neutral or dissatisfied +8076,94958,Male,Loyal Customer,34,Business travel,Eco,192,1,4,4,4,1,1,1,1,4,4,4,1,4,1,15,12.0,neutral or dissatisfied +8077,7993,Female,Loyal Customer,60,Business travel,Business,402,4,4,4,4,4,4,5,4,4,3,4,5,4,3,4,0.0,satisfied +8078,80910,Male,Loyal Customer,50,Business travel,Business,352,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +8079,97493,Female,Loyal Customer,9,Personal Travel,Eco,822,4,5,4,1,1,4,1,1,5,3,5,5,5,1,4,9.0,neutral or dissatisfied +8080,53841,Female,Loyal Customer,45,Business travel,Eco,191,1,1,1,1,3,3,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +8081,32342,Female,Loyal Customer,48,Business travel,Eco,101,5,1,1,1,3,5,5,4,4,5,4,3,4,2,0,0.0,satisfied +8082,100469,Male,Loyal Customer,52,Business travel,Business,580,3,3,3,3,3,4,4,5,5,5,5,5,5,4,127,122.0,satisfied +8083,1292,Female,Loyal Customer,21,Personal Travel,Eco,102,2,4,2,2,2,2,2,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +8084,88618,Male,Loyal Customer,47,Personal Travel,Eco,404,1,1,1,1,4,1,4,4,4,3,2,2,2,4,0,0.0,neutral or dissatisfied +8085,51252,Male,Loyal Customer,39,Business travel,Eco Plus,421,2,1,1,1,2,3,2,2,5,5,2,5,5,2,39,52.0,satisfied +8086,71311,Female,Loyal Customer,31,Business travel,Business,1514,3,3,1,3,5,5,5,5,3,4,4,4,4,5,0,12.0,satisfied +8087,20999,Male,Loyal Customer,34,Business travel,Eco Plus,689,4,4,4,4,4,5,4,4,1,3,3,1,3,4,0,0.0,satisfied +8088,52607,Female,Loyal Customer,43,Business travel,Business,3713,2,2,2,2,5,3,2,2,2,2,2,2,2,1,58,49.0,neutral or dissatisfied +8089,114491,Male,Loyal Customer,48,Business travel,Business,362,1,1,1,1,4,4,4,1,1,1,1,3,1,4,37,30.0,neutral or dissatisfied +8090,84538,Male,disloyal Customer,8,Business travel,Eco,1319,2,2,2,4,1,2,1,1,1,3,3,3,3,1,0,0.0,neutral or dissatisfied +8091,2967,Female,Loyal Customer,44,Personal Travel,Eco,737,3,1,3,3,1,2,3,3,3,3,3,2,3,3,7,17.0,neutral or dissatisfied +8092,77678,Male,Loyal Customer,55,Business travel,Business,1836,3,3,3,3,4,5,5,5,5,5,5,4,5,3,15,0.0,satisfied +8093,59484,Male,Loyal Customer,66,Business travel,Business,758,2,5,5,5,1,3,3,2,2,2,2,2,2,1,45,33.0,neutral or dissatisfied +8094,18361,Male,Loyal Customer,34,Business travel,Eco,169,0,0,0,2,4,0,4,4,4,3,1,4,4,4,0,0.0,satisfied +8095,4077,Male,disloyal Customer,23,Business travel,Eco,431,4,5,4,5,3,4,3,3,3,4,5,5,5,3,0,0.0,neutral or dissatisfied +8096,86376,Male,Loyal Customer,38,Business travel,Eco,760,3,5,5,5,3,3,3,3,2,2,1,3,1,3,74,64.0,neutral or dissatisfied +8097,120151,Female,disloyal Customer,29,Business travel,Business,2378,2,2,2,1,2,4,3,4,2,4,4,3,3,3,24,25.0,neutral or dissatisfied +8098,49950,Female,disloyal Customer,21,Business travel,Eco,250,2,3,2,2,5,2,5,5,4,2,5,3,2,5,2,0.0,neutral or dissatisfied +8099,107506,Male,Loyal Customer,53,Personal Travel,Eco,711,2,4,2,1,3,2,1,3,5,4,4,1,4,3,0,0.0,neutral or dissatisfied +8100,44236,Female,Loyal Customer,37,Business travel,Business,3532,2,1,1,1,4,3,2,2,2,2,2,2,2,2,0,20.0,neutral or dissatisfied +8101,68688,Male,Loyal Customer,13,Personal Travel,Eco,175,3,5,3,2,3,3,3,3,4,3,4,5,4,3,12,5.0,neutral or dissatisfied +8102,83735,Male,Loyal Customer,60,Business travel,Business,1183,2,1,1,1,3,4,3,2,2,2,2,3,2,3,3,28.0,neutral or dissatisfied +8103,74140,Female,disloyal Customer,48,Business travel,Eco,678,2,2,2,4,3,2,3,3,4,2,4,1,3,3,0,10.0,neutral or dissatisfied +8104,15213,Male,Loyal Customer,37,Business travel,Eco,529,5,5,5,5,5,5,5,1,5,1,4,5,1,5,134,123.0,satisfied +8105,62009,Male,Loyal Customer,55,Business travel,Eco,2586,3,4,4,4,3,3,3,3,4,4,1,1,3,3,0,0.0,neutral or dissatisfied +8106,79053,Male,Loyal Customer,39,Business travel,Eco,356,3,1,1,1,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +8107,2856,Female,Loyal Customer,51,Business travel,Eco,475,3,5,5,5,1,3,3,3,3,3,3,4,3,1,41,72.0,neutral or dissatisfied +8108,125849,Female,Loyal Customer,19,Business travel,Business,1013,4,4,4,4,4,4,4,4,4,2,4,5,4,4,0,0.0,satisfied +8109,109379,Male,disloyal Customer,17,Business travel,Eco,1189,4,5,5,4,5,5,5,5,2,5,4,2,4,5,16,8.0,neutral or dissatisfied +8110,25023,Male,Loyal Customer,58,Business travel,Business,2483,4,4,4,4,5,3,3,4,4,5,4,2,4,1,21,1.0,satisfied +8111,78048,Male,Loyal Customer,68,Personal Travel,Eco,227,4,2,4,3,3,4,3,3,2,1,4,2,4,3,5,0.0,neutral or dissatisfied +8112,118483,Female,Loyal Customer,25,Business travel,Business,646,1,1,1,1,4,4,4,4,4,3,5,4,4,4,77,76.0,satisfied +8113,17416,Female,Loyal Customer,43,Business travel,Business,2686,5,5,5,5,1,2,3,5,5,5,5,5,5,1,0,0.0,satisfied +8114,25091,Female,Loyal Customer,34,Business travel,Business,369,1,4,1,1,2,1,4,4,4,4,4,3,4,1,0,0.0,satisfied +8115,9296,Female,Loyal Customer,63,Business travel,Business,2249,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,6.0,satisfied +8116,77070,Female,Loyal Customer,39,Business travel,Business,991,4,2,4,4,2,3,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +8117,24440,Female,Loyal Customer,28,Business travel,Business,3491,3,3,2,3,5,5,5,5,5,4,4,3,5,5,6,0.0,satisfied +8118,113078,Male,Loyal Customer,62,Business travel,Eco,569,1,0,0,3,4,1,4,4,4,5,3,1,3,4,0,0.0,neutral or dissatisfied +8119,88465,Male,Loyal Customer,41,Business travel,Eco,145,5,5,5,5,5,5,5,5,1,4,4,5,2,5,0,0.0,satisfied +8120,7543,Male,Loyal Customer,66,Personal Travel,Eco,762,2,3,2,4,1,2,1,1,3,5,4,2,3,1,54,24.0,neutral or dissatisfied +8121,94783,Male,Loyal Customer,47,Business travel,Business,189,0,4,0,3,5,4,4,2,2,2,2,5,2,3,0,0.0,satisfied +8122,8449,Male,disloyal Customer,21,Business travel,Business,1379,5,0,5,5,3,0,3,3,4,3,4,5,5,3,28,28.0,satisfied +8123,126497,Male,Loyal Customer,25,Personal Travel,Eco,1849,4,4,4,5,5,4,5,5,5,5,1,1,3,5,0,0.0,neutral or dissatisfied +8124,57891,Female,Loyal Customer,76,Business travel,Business,305,4,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +8125,124995,Female,disloyal Customer,22,Business travel,Eco,184,4,2,4,4,5,4,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +8126,73496,Male,Loyal Customer,64,Personal Travel,Eco,1182,2,5,2,4,4,2,4,4,3,3,4,4,4,4,0,2.0,neutral or dissatisfied +8127,98501,Male,disloyal Customer,41,Business travel,Business,402,5,5,5,3,2,5,2,2,3,4,4,5,4,2,76,95.0,satisfied +8128,103169,Female,disloyal Customer,30,Business travel,Eco,491,3,5,3,4,2,3,2,2,2,2,1,4,4,2,15,10.0,neutral or dissatisfied +8129,96064,Female,Loyal Customer,9,Personal Travel,Eco,1235,2,4,2,3,5,2,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +8130,11275,Male,Loyal Customer,24,Personal Travel,Eco,216,2,3,0,1,3,0,3,3,3,1,1,3,2,3,0,0.0,neutral or dissatisfied +8131,66102,Male,Loyal Customer,53,Business travel,Business,1739,3,3,3,3,5,5,4,3,3,4,3,5,3,3,0,0.0,satisfied +8132,41252,Female,Loyal Customer,16,Business travel,Eco,852,5,4,4,4,5,4,4,5,5,1,1,1,4,5,0,4.0,satisfied +8133,56953,Female,Loyal Customer,11,Business travel,Business,2565,2,3,3,3,2,2,2,4,5,3,3,2,1,2,6,6.0,neutral or dissatisfied +8134,59142,Female,Loyal Customer,14,Personal Travel,Eco,1744,3,2,3,3,3,3,4,3,2,3,2,4,3,3,0,0.0,neutral or dissatisfied +8135,102222,Male,Loyal Customer,58,Business travel,Business,2811,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +8136,35050,Female,Loyal Customer,52,Business travel,Business,2973,5,5,5,5,3,5,4,4,4,4,4,4,4,5,5,18.0,satisfied +8137,91564,Male,Loyal Customer,61,Personal Travel,Eco,680,3,5,3,4,5,3,5,5,3,5,2,4,3,5,14,9.0,neutral or dissatisfied +8138,88138,Male,Loyal Customer,60,Business travel,Business,581,2,2,2,2,5,5,5,4,4,4,4,3,4,4,14,17.0,satisfied +8139,86532,Female,Loyal Customer,37,Personal Travel,Eco,762,3,4,3,5,3,3,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +8140,98280,Male,Loyal Customer,15,Business travel,Eco,1188,3,1,1,1,3,3,2,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +8141,79879,Male,disloyal Customer,13,Business travel,Business,1096,4,5,4,4,4,4,4,4,5,2,5,4,4,4,0,5.0,satisfied +8142,19707,Male,disloyal Customer,36,Business travel,Eco,409,1,2,0,4,2,0,2,2,1,1,3,4,4,2,0,0.0,neutral or dissatisfied +8143,79791,Male,Loyal Customer,31,Business travel,Business,1886,4,4,4,4,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +8144,18804,Female,Loyal Customer,24,Business travel,Eco,448,5,5,5,5,5,5,5,5,2,1,2,5,2,5,6,0.0,satisfied +8145,39028,Male,Loyal Customer,65,Personal Travel,Eco,406,1,1,1,4,1,1,1,1,1,2,4,3,3,1,15,0.0,neutral or dissatisfied +8146,94419,Female,Loyal Customer,30,Business travel,Eco,248,1,4,4,4,1,1,1,1,3,1,3,1,4,1,0,1.0,neutral or dissatisfied +8147,61588,Male,Loyal Customer,30,Personal Travel,Business,1609,2,5,2,5,3,2,3,3,3,4,4,5,5,3,4,0.0,neutral or dissatisfied +8148,84632,Male,Loyal Customer,30,Personal Travel,Eco,707,4,4,4,4,5,4,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +8149,20901,Female,Loyal Customer,49,Business travel,Business,689,2,2,2,2,2,2,2,2,4,2,3,2,3,2,138,128.0,neutral or dissatisfied +8150,11617,Male,Loyal Customer,47,Personal Travel,Eco,468,3,3,3,4,2,3,2,2,1,2,4,1,3,2,0,5.0,neutral or dissatisfied +8151,22845,Male,Loyal Customer,30,Personal Travel,Eco,147,4,1,4,2,2,4,2,2,2,2,2,4,2,2,6,4.0,satisfied +8152,98571,Female,Loyal Customer,45,Business travel,Business,3560,1,1,1,1,5,5,4,5,5,5,5,5,5,4,6,0.0,satisfied +8153,59338,Female,Loyal Customer,58,Business travel,Business,2449,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +8154,113857,Female,disloyal Customer,22,Business travel,Eco,1363,4,4,4,2,1,4,1,1,5,3,4,4,4,1,0,3.0,satisfied +8155,196,Male,disloyal Customer,23,Business travel,Eco,213,5,5,5,4,1,5,1,1,3,5,4,3,4,1,21,31.0,satisfied +8156,62432,Male,Loyal Customer,11,Personal Travel,Eco,1911,1,4,1,3,4,1,4,4,4,2,5,3,4,4,26,17.0,neutral or dissatisfied +8157,80360,Female,Loyal Customer,26,Business travel,Business,368,2,2,4,2,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +8158,59126,Female,Loyal Customer,49,Personal Travel,Eco,1723,3,4,3,3,2,3,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +8159,67041,Female,Loyal Customer,46,Business travel,Business,3028,1,1,1,1,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +8160,115011,Male,Loyal Customer,53,Business travel,Business,1998,2,2,2,2,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +8161,54971,Female,Loyal Customer,26,Business travel,Business,1635,2,2,2,2,3,4,3,3,4,5,4,4,4,3,13,20.0,satisfied +8162,119786,Female,disloyal Customer,27,Business travel,Business,912,4,4,4,4,1,4,1,1,3,2,4,5,5,1,0,0.0,satisfied +8163,7140,Male,Loyal Customer,34,Business travel,Business,2599,4,4,5,4,3,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +8164,5890,Female,Loyal Customer,54,Business travel,Business,2503,1,1,1,1,4,4,4,4,4,4,5,4,4,5,5,10.0,satisfied +8165,59670,Female,Loyal Customer,46,Personal Travel,Eco,854,1,5,1,3,3,5,5,5,5,1,1,3,5,5,10,16.0,neutral or dissatisfied +8166,22997,Male,Loyal Customer,24,Personal Travel,Eco,489,4,5,4,5,3,4,3,3,5,3,2,2,4,3,0,0.0,neutral or dissatisfied +8167,92947,Female,Loyal Customer,12,Personal Travel,Eco,151,3,5,0,1,1,0,1,1,4,5,4,5,5,1,0,7.0,neutral or dissatisfied +8168,7153,Male,Loyal Customer,58,Business travel,Business,135,1,1,1,1,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +8169,107072,Female,Loyal Customer,11,Personal Travel,Eco,395,3,5,5,3,3,5,3,3,5,4,4,3,5,3,0,1.0,neutral or dissatisfied +8170,67184,Male,Loyal Customer,49,Personal Travel,Eco,929,2,1,3,3,2,3,2,2,4,2,4,3,4,2,27,18.0,neutral or dissatisfied +8171,47307,Male,Loyal Customer,42,Business travel,Eco,558,4,3,3,3,4,4,4,4,1,1,5,1,5,4,0,0.0,satisfied +8172,124898,Female,Loyal Customer,45,Business travel,Business,728,2,2,5,2,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +8173,31783,Female,Loyal Customer,31,Personal Travel,Eco,602,2,1,2,4,3,2,3,3,2,3,4,4,3,3,0,0.0,neutral or dissatisfied +8174,66692,Male,Loyal Customer,56,Business travel,Business,2297,5,5,5,5,3,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +8175,109549,Female,Loyal Customer,31,Personal Travel,Eco,951,3,4,3,1,4,3,4,4,1,1,4,4,2,4,3,3.0,neutral or dissatisfied +8176,101811,Male,Loyal Customer,35,Business travel,Eco,1521,2,5,5,5,2,2,2,2,3,5,1,2,1,2,0,0.0,neutral or dissatisfied +8177,116325,Male,Loyal Customer,43,Personal Travel,Eco,371,4,0,2,1,1,2,1,1,2,3,5,5,4,1,5,0.0,satisfied +8178,30402,Female,Loyal Customer,60,Personal Travel,Eco,775,1,5,1,3,2,5,5,2,2,1,2,3,2,3,6,9.0,neutral or dissatisfied +8179,29916,Male,Loyal Customer,34,Business travel,Business,399,4,4,3,3,1,4,3,4,4,4,4,4,4,1,76,82.0,neutral or dissatisfied +8180,16784,Male,Loyal Customer,66,Personal Travel,Eco,642,4,2,4,3,1,4,1,1,4,3,3,4,4,1,5,0.0,neutral or dissatisfied +8181,62322,Male,Loyal Customer,64,Personal Travel,Eco,236,3,5,3,3,3,2,2,4,3,5,4,2,3,2,179,189.0,neutral or dissatisfied +8182,77597,Male,Loyal Customer,35,Business travel,Business,731,3,3,3,3,5,4,5,5,5,5,5,5,5,4,10,0.0,satisfied +8183,43035,Female,Loyal Customer,48,Business travel,Business,192,3,2,2,2,4,4,4,1,1,1,3,2,1,4,0,0.0,neutral or dissatisfied +8184,89763,Male,Loyal Customer,39,Personal Travel,Eco,944,3,4,3,4,3,3,3,3,3,4,3,2,4,3,0,0.0,neutral or dissatisfied +8185,109976,Male,Loyal Customer,25,Personal Travel,Eco,971,5,5,5,3,3,5,3,3,3,2,5,4,4,3,0,0.0,satisfied +8186,88889,Female,disloyal Customer,22,Business travel,Eco,859,1,1,1,4,1,1,1,1,3,1,3,3,4,1,74,64.0,neutral or dissatisfied +8187,95573,Female,Loyal Customer,23,Business travel,Eco Plus,441,2,3,3,3,2,2,1,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +8188,114075,Male,Loyal Customer,70,Business travel,Business,1892,3,2,2,2,5,2,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +8189,50642,Female,Loyal Customer,37,Personal Travel,Eco,373,3,0,5,5,5,5,5,5,5,2,5,5,5,5,0,8.0,neutral or dissatisfied +8190,48441,Female,Loyal Customer,19,Business travel,Business,1773,5,5,5,5,4,4,4,4,5,1,1,5,3,4,5,0.0,satisfied +8191,52068,Female,Loyal Customer,38,Business travel,Eco,351,4,2,2,2,4,5,4,4,3,4,5,5,1,4,0,0.0,satisfied +8192,45710,Male,Loyal Customer,36,Business travel,Business,3920,4,4,2,4,4,5,4,5,5,5,5,4,5,3,5,8.0,satisfied +8193,114870,Female,Loyal Customer,43,Business travel,Business,325,5,5,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +8194,111328,Female,Loyal Customer,42,Business travel,Eco,283,2,4,4,4,3,4,4,2,2,2,2,4,2,1,17,14.0,neutral or dissatisfied +8195,23958,Male,Loyal Customer,8,Personal Travel,Eco,936,3,4,3,2,5,3,5,5,5,3,5,4,5,5,0,,neutral or dissatisfied +8196,16890,Male,Loyal Customer,34,Business travel,Business,3444,2,5,1,5,3,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +8197,18406,Female,Loyal Customer,30,Business travel,Business,284,4,3,3,3,4,3,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +8198,3972,Male,Loyal Customer,27,Business travel,Eco Plus,764,1,4,4,4,1,2,1,1,2,3,3,2,3,1,0,60.0,neutral or dissatisfied +8199,51312,Male,Loyal Customer,59,Business travel,Eco Plus,158,2,5,5,5,2,2,2,2,4,3,3,2,2,2,447,438.0,neutral or dissatisfied +8200,118331,Male,Loyal Customer,42,Business travel,Business,602,3,2,3,3,4,4,5,4,4,4,4,3,4,4,79,68.0,satisfied +8201,46981,Female,Loyal Customer,61,Personal Travel,Eco,737,2,1,2,2,2,3,3,1,1,2,5,4,1,1,60,69.0,neutral or dissatisfied +8202,34686,Female,disloyal Customer,25,Business travel,Eco,301,1,0,0,2,3,0,3,3,3,5,2,5,1,3,50,44.0,neutral or dissatisfied +8203,39239,Male,disloyal Customer,38,Business travel,Eco,108,2,0,2,3,4,2,4,4,5,2,1,5,2,4,0,41.0,neutral or dissatisfied +8204,27827,Male,Loyal Customer,48,Business travel,Eco,509,2,1,1,1,2,2,2,2,4,3,3,3,4,2,0,11.0,neutral or dissatisfied +8205,67190,Male,Loyal Customer,58,Personal Travel,Eco,985,3,1,3,4,5,3,2,5,4,2,4,1,4,5,0,1.0,neutral or dissatisfied +8206,85189,Male,Loyal Customer,52,Business travel,Business,2251,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,3.0,satisfied +8207,52932,Female,Loyal Customer,14,Personal Travel,Eco,679,1,4,1,3,3,1,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +8208,76171,Male,Loyal Customer,58,Personal Travel,Eco,546,4,2,4,3,1,4,1,1,3,3,2,4,3,1,0,0.0,neutral or dissatisfied +8209,117519,Male,disloyal Customer,22,Business travel,Eco,872,0,0,0,3,2,0,4,2,5,3,4,5,5,2,0,0.0,satisfied +8210,13094,Female,Loyal Customer,55,Business travel,Business,3741,1,1,1,1,1,2,2,4,4,4,4,3,4,3,0,0.0,satisfied +8211,19899,Female,Loyal Customer,40,Business travel,Eco,296,3,2,2,2,3,4,3,3,3,3,3,4,3,3,5,10.0,satisfied +8212,127060,Female,disloyal Customer,25,Business travel,Eco,338,3,3,3,4,1,3,1,1,2,2,3,1,3,1,73,55.0,neutral or dissatisfied +8213,73608,Male,Loyal Customer,62,Business travel,Business,2279,2,2,2,2,3,5,5,4,4,5,5,3,4,4,0,0.0,satisfied +8214,96929,Female,Loyal Customer,9,Personal Travel,Eco Plus,1041,4,4,4,3,5,4,5,5,3,2,5,5,4,5,0,1.0,neutral or dissatisfied +8215,32245,Female,Loyal Customer,31,Business travel,Business,101,1,1,5,1,4,4,5,4,4,4,5,5,1,4,0,0.0,satisfied +8216,52940,Male,Loyal Customer,63,Business travel,Eco Plus,679,2,2,2,2,1,2,1,1,4,2,2,3,2,1,0,0.0,satisfied +8217,25319,Male,Loyal Customer,62,Personal Travel,Eco,432,2,3,2,4,4,2,4,4,3,4,5,3,4,4,0,,neutral or dissatisfied +8218,114800,Male,Loyal Customer,32,Business travel,Business,2205,2,2,2,2,4,5,4,4,4,3,5,5,5,4,50,51.0,satisfied +8219,13112,Female,Loyal Customer,26,Business travel,Business,427,4,4,4,4,4,4,4,4,3,5,5,5,5,4,4,18.0,satisfied +8220,96509,Male,Loyal Customer,29,Personal Travel,Eco,436,4,4,4,4,4,4,4,4,1,2,1,5,2,4,5,13.0,neutral or dissatisfied +8221,47083,Female,Loyal Customer,24,Personal Travel,Eco,351,4,5,4,5,4,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +8222,41405,Female,Loyal Customer,29,Business travel,Business,2222,2,2,2,2,2,2,2,2,2,3,4,4,3,2,13,21.0,neutral or dissatisfied +8223,26452,Female,Loyal Customer,57,Business travel,Eco,787,5,3,2,2,5,2,5,5,5,5,5,2,5,1,0,0.0,satisfied +8224,111203,Male,Loyal Customer,44,Business travel,Business,1506,5,5,5,5,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +8225,75792,Male,Loyal Customer,51,Personal Travel,Eco,813,3,2,3,3,2,3,2,2,2,5,2,1,4,2,17,7.0,neutral or dissatisfied +8226,33061,Female,Loyal Customer,68,Personal Travel,Eco,84,2,5,2,3,2,4,4,1,1,2,1,5,1,5,0,0.0,neutral or dissatisfied +8227,125799,Female,disloyal Customer,26,Business travel,Eco,993,4,4,4,3,5,4,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +8228,92616,Female,Loyal Customer,60,Personal Travel,Business,453,3,5,4,3,5,5,4,1,1,4,1,4,1,3,9,5.0,neutral or dissatisfied +8229,113414,Male,Loyal Customer,35,Business travel,Business,3610,1,5,5,5,3,4,4,1,1,2,1,1,1,4,0,3.0,neutral or dissatisfied +8230,87343,Male,Loyal Customer,57,Business travel,Business,1869,3,3,3,3,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +8231,12497,Female,Loyal Customer,36,Business travel,Eco Plus,190,4,5,3,3,4,3,4,4,1,2,2,1,2,4,0,0.0,neutral or dissatisfied +8232,111478,Male,Loyal Customer,57,Business travel,Business,1452,5,5,5,5,4,5,4,4,4,4,4,3,4,4,60,54.0,satisfied +8233,114775,Male,Loyal Customer,58,Business travel,Business,2004,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +8234,92903,Female,Loyal Customer,42,Business travel,Business,3800,3,3,3,3,5,4,4,4,4,4,4,5,4,5,1,3.0,satisfied +8235,84375,Female,disloyal Customer,43,Business travel,Eco,606,3,1,3,2,4,3,4,4,4,1,2,4,3,4,0,0.0,neutral or dissatisfied +8236,19593,Male,Loyal Customer,24,Personal Travel,Eco,160,2,4,0,2,4,0,4,4,3,2,5,3,4,4,45,69.0,neutral or dissatisfied +8237,85447,Female,Loyal Customer,45,Business travel,Business,214,1,1,1,1,5,5,5,5,5,5,5,5,5,4,13,11.0,satisfied +8238,119323,Female,Loyal Customer,54,Personal Travel,Eco,214,3,0,3,2,2,3,3,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +8239,23162,Female,Loyal Customer,61,Personal Travel,Eco,300,4,4,4,3,4,4,5,5,5,4,5,5,5,5,52,34.0,neutral or dissatisfied +8240,111746,Female,Loyal Customer,40,Business travel,Business,754,4,4,4,4,5,3,2,5,5,5,5,1,5,1,2,4.0,satisfied +8241,35339,Male,Loyal Customer,12,Business travel,Business,2948,3,1,1,1,3,3,3,3,1,5,3,4,4,3,31,36.0,neutral or dissatisfied +8242,99604,Male,Loyal Customer,41,Business travel,Business,3468,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +8243,10358,Female,Loyal Customer,50,Business travel,Business,3303,3,3,3,3,2,5,4,3,3,4,3,4,3,5,97,116.0,satisfied +8244,42420,Female,Loyal Customer,53,Personal Travel,Eco Plus,315,3,2,3,2,2,3,2,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +8245,97740,Female,Loyal Customer,27,Business travel,Business,2690,5,5,5,5,5,4,5,5,5,3,5,3,4,5,49,34.0,satisfied +8246,37186,Female,Loyal Customer,45,Personal Travel,Eco,1189,3,4,3,3,5,4,4,3,3,3,3,4,3,3,13,9.0,neutral or dissatisfied +8247,97513,Female,Loyal Customer,44,Business travel,Business,2854,1,1,1,1,5,4,5,4,4,4,4,4,4,3,27,5.0,satisfied +8248,31542,Male,Loyal Customer,15,Personal Travel,Eco,862,1,4,1,3,3,1,3,3,5,2,5,4,4,3,3,45.0,neutral or dissatisfied +8249,37100,Male,Loyal Customer,29,Business travel,Eco,1179,4,5,5,5,4,4,4,4,4,2,5,3,1,4,0,0.0,satisfied +8250,128255,Female,disloyal Customer,20,Business travel,Business,304,5,0,5,2,1,5,1,1,4,4,5,3,5,1,0,0.0,satisfied +8251,35378,Female,Loyal Customer,72,Business travel,Eco,1056,3,1,5,1,3,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +8252,127561,Female,Loyal Customer,41,Business travel,Business,1670,2,2,2,2,2,3,4,4,4,4,4,4,4,4,0,14.0,satisfied +8253,1076,Female,Loyal Customer,53,Personal Travel,Eco,247,5,4,0,4,1,1,2,1,1,0,1,5,1,1,26,21.0,satisfied +8254,128424,Female,Loyal Customer,57,Business travel,Eco,370,2,1,1,1,3,4,4,2,2,2,2,3,2,1,1,8.0,neutral or dissatisfied +8255,96602,Male,Loyal Customer,36,Personal Travel,Business,1036,4,1,4,4,2,3,3,1,1,4,1,4,1,4,15,6.0,neutral or dissatisfied +8256,61150,Male,Loyal Customer,20,Business travel,Business,3436,1,5,5,5,1,1,1,1,1,5,4,2,4,1,111,99.0,neutral or dissatisfied +8257,94330,Male,Loyal Customer,48,Business travel,Business,277,4,4,4,4,4,4,5,5,5,5,5,5,5,3,3,0.0,satisfied +8258,47573,Male,Loyal Customer,49,Business travel,Business,1482,3,3,3,3,3,4,4,4,4,5,4,3,4,4,35,35.0,satisfied +8259,83652,Female,Loyal Customer,39,Business travel,Business,577,5,5,5,5,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +8260,78,Male,Loyal Customer,58,Personal Travel,Eco,173,4,4,4,3,2,4,2,2,4,3,4,1,5,2,0,4.0,satisfied +8261,6787,Male,Loyal Customer,69,Business travel,Eco,223,2,5,5,5,2,2,2,2,2,3,3,4,2,2,0,6.0,neutral or dissatisfied +8262,63655,Female,disloyal Customer,14,Business travel,Eco,796,3,2,2,3,3,3,3,3,1,5,3,4,4,3,0,0.0,neutral or dissatisfied +8263,30212,Female,Loyal Customer,27,Personal Travel,Eco Plus,31,3,5,3,5,4,3,1,4,5,5,4,3,5,4,8,15.0,neutral or dissatisfied +8264,109122,Male,Loyal Customer,41,Personal Travel,Eco Plus,781,1,5,1,1,3,1,3,3,3,3,5,3,5,3,5,0.0,neutral or dissatisfied +8265,41194,Female,Loyal Customer,56,Business travel,Eco,1091,5,4,4,4,2,4,5,5,5,5,5,4,5,1,3,0.0,satisfied +8266,126801,Male,Loyal Customer,31,Business travel,Business,2125,2,2,2,2,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +8267,53328,Female,disloyal Customer,40,Business travel,Business,758,3,3,3,3,4,3,4,4,1,2,1,1,5,4,0,0.0,satisfied +8268,5188,Female,Loyal Customer,51,Business travel,Business,2355,1,1,1,1,3,4,5,5,5,5,5,4,5,5,12,12.0,satisfied +8269,107495,Male,Loyal Customer,25,Business travel,Eco,711,2,5,5,5,2,2,2,2,1,3,4,4,4,2,0,0.0,neutral or dissatisfied +8270,99615,Male,Loyal Customer,39,Business travel,Business,1154,4,4,4,4,5,4,5,2,2,2,2,3,2,5,24,34.0,satisfied +8271,6226,Male,disloyal Customer,26,Business travel,Business,594,5,5,5,2,3,5,3,3,3,4,5,5,5,3,0,0.0,satisfied +8272,119320,Female,Loyal Customer,70,Personal Travel,Eco,214,2,1,2,2,3,3,3,4,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +8273,28057,Male,disloyal Customer,17,Business travel,Eco,2603,4,4,4,3,4,1,1,5,3,3,3,1,3,1,2,0.0,neutral or dissatisfied +8274,70070,Female,Loyal Customer,38,Personal Travel,Business,460,3,5,3,4,3,5,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +8275,26317,Female,Loyal Customer,41,Personal Travel,Eco Plus,2139,2,5,2,3,5,5,5,5,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +8276,49857,Male,Loyal Customer,41,Business travel,Business,326,1,1,1,1,5,3,5,4,4,4,4,2,4,4,32,22.0,satisfied +8277,129823,Male,Loyal Customer,35,Personal Travel,Eco,337,2,5,2,5,2,2,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +8278,106140,Male,Loyal Customer,43,Business travel,Eco,436,3,5,5,5,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +8279,75111,Female,disloyal Customer,29,Business travel,Business,1744,3,3,3,4,2,3,2,2,5,5,3,3,4,2,4,0.0,neutral or dissatisfied +8280,51266,Female,Loyal Customer,46,Business travel,Eco Plus,372,3,2,2,2,4,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +8281,83044,Male,Loyal Customer,40,Business travel,Eco,1127,3,1,1,1,3,4,3,3,2,4,3,3,3,3,0,11.0,neutral or dissatisfied +8282,18309,Male,Loyal Customer,36,Business travel,Business,3649,5,5,5,5,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +8283,19368,Male,Loyal Customer,42,Business travel,Eco,476,4,4,4,4,4,4,4,4,3,5,2,4,1,4,0,0.0,satisfied +8284,90182,Female,Loyal Customer,29,Personal Travel,Eco,983,1,2,1,3,1,1,1,1,1,3,3,4,4,1,0,0.0,neutral or dissatisfied +8285,32271,Female,Loyal Customer,37,Business travel,Eco,201,2,4,4,4,2,2,2,2,3,5,3,2,2,2,3,7.0,neutral or dissatisfied +8286,80416,Male,Loyal Customer,43,Business travel,Business,2248,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +8287,32510,Female,Loyal Customer,38,Business travel,Business,1892,4,5,4,4,2,1,5,5,5,5,5,2,5,2,0,0.0,satisfied +8288,61482,Female,Loyal Customer,25,Business travel,Business,2358,1,1,1,1,5,4,5,5,5,4,3,4,4,5,107,105.0,satisfied +8289,44046,Female,Loyal Customer,51,Personal Travel,Eco,296,4,5,4,1,4,4,4,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +8290,39049,Male,Loyal Customer,31,Business travel,Eco Plus,230,0,0,0,4,3,0,3,3,2,5,2,2,4,3,0,0.0,satisfied +8291,46571,Female,Loyal Customer,38,Business travel,Eco,125,5,2,2,2,5,5,5,5,5,5,1,2,1,5,108,110.0,satisfied +8292,83469,Male,Loyal Customer,49,Business travel,Business,3921,2,2,2,2,5,5,5,4,3,5,4,5,5,5,234,278.0,satisfied +8293,99491,Male,Loyal Customer,67,Personal Travel,Eco,307,4,4,4,1,1,4,1,1,3,4,3,3,4,1,3,0.0,neutral or dissatisfied +8294,112630,Male,Loyal Customer,56,Business travel,Business,3547,3,3,3,3,3,4,4,5,5,5,5,5,5,4,5,3.0,satisfied +8295,127308,Female,Loyal Customer,50,Business travel,Business,1979,1,1,1,1,2,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +8296,112700,Female,Loyal Customer,27,Business travel,Business,723,4,4,4,4,4,4,4,4,3,3,4,2,4,4,0,0.0,neutral or dissatisfied +8297,4263,Male,disloyal Customer,27,Business travel,Eco,502,1,4,1,4,5,1,5,5,3,5,3,4,3,5,12,14.0,neutral or dissatisfied +8298,59185,Female,Loyal Customer,47,Business travel,Business,2290,5,5,5,5,5,4,5,4,4,4,4,4,4,3,13,0.0,satisfied +8299,37324,Female,disloyal Customer,64,Business travel,Eco,1028,5,5,5,2,1,5,1,1,5,2,2,3,1,1,1,0.0,satisfied +8300,86282,Male,Loyal Customer,68,Personal Travel,Eco,356,2,3,2,2,1,2,5,1,4,5,3,1,2,1,0,0.0,neutral or dissatisfied +8301,42126,Male,Loyal Customer,41,Personal Travel,Eco,898,4,5,3,5,3,3,3,3,2,1,4,1,4,3,0,0.0,satisfied +8302,8509,Male,Loyal Customer,31,Business travel,Business,862,2,5,5,5,2,2,2,2,3,3,4,4,3,2,88,79.0,neutral or dissatisfied +8303,126424,Female,disloyal Customer,44,Business travel,Eco Plus,328,3,2,2,4,4,3,4,4,4,1,3,2,4,4,14,17.0,neutral or dissatisfied +8304,26456,Male,Loyal Customer,29,Business travel,Business,2771,4,2,2,2,4,4,4,4,1,1,3,2,3,4,9,0.0,neutral or dissatisfied +8305,45645,Male,Loyal Customer,34,Personal Travel,Eco,230,2,4,2,3,4,2,4,4,5,5,4,4,5,4,0,6.0,neutral or dissatisfied +8306,39683,Female,Loyal Customer,53,Personal Travel,Eco Plus,612,4,3,5,3,4,3,3,3,3,5,3,1,3,4,1,0.0,neutral or dissatisfied +8307,9955,Male,Loyal Customer,22,Business travel,Business,1690,1,1,1,1,1,1,1,1,4,3,2,1,3,1,6,0.0,neutral or dissatisfied +8308,69147,Female,Loyal Customer,25,Personal Travel,Eco,2248,2,5,2,2,4,2,4,4,4,5,3,5,5,4,0,0.0,neutral or dissatisfied +8309,113065,Male,Loyal Customer,56,Business travel,Business,543,3,3,5,3,4,4,3,3,3,3,3,1,3,2,80,71.0,neutral or dissatisfied +8310,68722,Male,Loyal Customer,49,Business travel,Business,1794,2,2,2,2,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +8311,124125,Female,Loyal Customer,51,Business travel,Business,2145,1,1,1,1,3,4,3,5,5,5,3,1,5,2,10,1.0,satisfied +8312,9798,Male,Loyal Customer,33,Personal Travel,Eco Plus,383,3,4,3,4,3,3,3,3,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +8313,29252,Female,disloyal Customer,29,Business travel,Eco,859,3,2,2,3,1,2,1,1,2,5,4,4,4,1,1,0.0,neutral or dissatisfied +8314,4676,Female,disloyal Customer,36,Business travel,Eco,364,2,0,2,2,3,2,5,3,5,1,2,2,2,3,0,2.0,neutral or dissatisfied +8315,54633,Male,Loyal Customer,55,Business travel,Eco,965,3,3,4,3,3,3,3,3,2,2,4,2,4,3,0,0.0,neutral or dissatisfied +8316,101098,Female,Loyal Customer,36,Business travel,Business,758,2,2,1,2,5,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +8317,24887,Female,Loyal Customer,56,Business travel,Business,3193,4,4,4,4,3,3,4,4,4,4,4,1,4,4,2,0.0,satisfied +8318,117521,Female,Loyal Customer,56,Business travel,Business,2835,2,2,2,2,4,5,5,3,3,3,3,4,3,3,2,0.0,satisfied +8319,50523,Female,Loyal Customer,49,Personal Travel,Eco,308,2,5,2,2,2,5,5,3,3,2,3,4,3,3,3,0.0,neutral or dissatisfied +8320,1560,Female,Loyal Customer,52,Business travel,Business,3463,1,1,1,1,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +8321,324,Male,disloyal Customer,21,Business travel,Business,821,4,0,4,2,5,4,5,5,5,3,4,4,4,5,0,3.0,satisfied +8322,127069,Female,Loyal Customer,64,Business travel,Business,2290,3,5,3,3,3,3,3,3,3,3,3,3,3,4,20,19.0,neutral or dissatisfied +8323,58666,Male,Loyal Customer,23,Business travel,Eco Plus,867,4,1,1,1,4,4,3,4,3,1,3,4,3,4,16,3.0,neutral or dissatisfied +8324,5401,Female,Loyal Customer,64,Personal Travel,Eco,812,3,3,3,3,3,1,3,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +8325,123179,Male,disloyal Customer,38,Business travel,Eco,250,1,2,1,4,1,1,3,1,4,1,4,3,3,1,100,95.0,neutral or dissatisfied +8326,43848,Female,Loyal Customer,41,Business travel,Eco,174,4,4,4,4,4,4,4,4,3,4,4,1,3,4,0,0.0,satisfied +8327,72905,Female,Loyal Customer,33,Business travel,Business,1035,2,2,3,2,4,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +8328,10044,Female,Loyal Customer,33,Business travel,Business,3493,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +8329,44889,Male,Loyal Customer,39,Business travel,Business,536,4,4,4,4,3,1,3,4,4,4,4,4,4,4,2,3.0,satisfied +8330,80957,Male,Loyal Customer,63,Business travel,Business,3182,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +8331,34180,Female,disloyal Customer,24,Business travel,Eco,1237,5,5,5,1,1,5,1,1,4,5,5,4,5,1,0,0.0,satisfied +8332,96120,Male,Loyal Customer,15,Business travel,Business,1848,5,5,5,5,5,5,5,5,5,2,4,3,5,5,68,63.0,satisfied +8333,62978,Female,disloyal Customer,48,Business travel,Eco,909,2,2,2,3,2,2,2,2,3,4,3,1,4,2,48,29.0,neutral or dissatisfied +8334,18419,Male,Loyal Customer,16,Personal Travel,Eco,750,4,4,4,3,4,5,5,4,5,5,4,5,5,5,201,199.0,neutral or dissatisfied +8335,65946,Male,Loyal Customer,60,Business travel,Business,1372,1,1,1,1,2,4,4,2,2,2,2,4,2,5,81,93.0,satisfied +8336,1199,Female,Loyal Customer,56,Personal Travel,Eco,270,2,0,2,1,2,5,5,5,5,2,5,3,5,4,11,0.0,neutral or dissatisfied +8337,39783,Female,Loyal Customer,38,Business travel,Eco Plus,521,4,4,4,4,4,4,4,4,3,1,2,2,2,4,0,12.0,satisfied +8338,121777,Female,Loyal Customer,46,Business travel,Business,449,4,4,4,4,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +8339,76424,Male,disloyal Customer,23,Business travel,Eco,405,1,2,0,4,1,0,1,1,2,1,3,1,3,1,4,0.0,neutral or dissatisfied +8340,90156,Male,Loyal Customer,69,Business travel,Business,583,4,2,4,4,3,3,5,4,4,4,4,4,4,2,0,0.0,satisfied +8341,55071,Male,Loyal Customer,55,Business travel,Eco,1635,2,1,1,1,2,2,2,2,1,5,2,4,1,2,0,0.0,neutral or dissatisfied +8342,80917,Female,Loyal Customer,55,Business travel,Business,341,1,1,1,1,3,5,4,5,5,5,5,5,5,4,9,26.0,satisfied +8343,31968,Female,Loyal Customer,39,Business travel,Business,3203,3,1,3,1,3,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +8344,47163,Male,Loyal Customer,37,Business travel,Eco,954,3,5,5,5,3,3,3,3,2,3,4,3,4,3,0,5.0,neutral or dissatisfied +8345,73739,Female,Loyal Customer,31,Personal Travel,Eco,192,2,5,2,3,1,2,3,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +8346,118216,Male,Loyal Customer,20,Business travel,Business,735,3,3,3,3,3,4,3,3,5,4,5,4,4,3,110,120.0,satisfied +8347,53819,Female,Loyal Customer,33,Business travel,Business,3269,5,5,5,5,4,2,1,4,4,4,3,1,4,2,53,47.0,satisfied +8348,78502,Female,disloyal Customer,30,Business travel,Eco,666,4,1,4,4,1,4,4,1,1,4,3,4,4,1,51,35.0,neutral or dissatisfied +8349,110074,Female,Loyal Customer,49,Business travel,Business,3812,2,2,2,2,2,5,5,4,4,4,4,4,4,3,12,3.0,satisfied +8350,87220,Male,Loyal Customer,50,Personal Travel,Eco,946,3,4,3,3,4,3,2,4,3,5,3,1,3,4,0,0.0,neutral or dissatisfied +8351,22290,Female,Loyal Customer,43,Business travel,Eco,145,2,1,1,1,3,1,5,2,2,2,2,3,2,4,0,0.0,satisfied +8352,94307,Male,Loyal Customer,50,Business travel,Business,562,4,4,4,4,2,4,5,4,4,4,4,3,4,3,29,22.0,satisfied +8353,108145,Female,disloyal Customer,35,Business travel,Eco,1166,3,3,3,4,5,3,1,5,4,1,3,3,3,5,17,6.0,neutral or dissatisfied +8354,112870,Male,Loyal Customer,48,Business travel,Business,715,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +8355,70165,Male,Loyal Customer,30,Personal Travel,Eco,550,1,4,1,3,1,1,1,1,2,4,4,3,4,1,0,0.0,neutral or dissatisfied +8356,66828,Male,disloyal Customer,39,Business travel,Business,731,2,2,2,3,4,2,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +8357,11029,Male,Loyal Customer,33,Business travel,Business,201,2,2,2,2,5,5,3,5,2,5,5,5,1,5,0,0.0,satisfied +8358,21955,Male,disloyal Customer,23,Business travel,Eco,551,2,0,2,4,5,2,5,5,4,1,2,1,2,5,0,0.0,neutral or dissatisfied +8359,21702,Female,Loyal Customer,13,Personal Travel,Eco,708,3,4,3,3,3,3,3,3,5,3,4,5,4,3,13,0.0,neutral or dissatisfied +8360,23653,Male,Loyal Customer,37,Business travel,Business,3860,1,1,4,1,4,4,2,3,3,4,3,3,3,2,0,0.0,satisfied +8361,105888,Female,disloyal Customer,27,Business travel,Business,283,0,0,0,4,3,0,3,3,3,3,5,5,4,3,51,38.0,satisfied +8362,116119,Male,Loyal Customer,47,Personal Travel,Eco,447,5,5,5,3,5,5,5,5,4,5,5,3,4,5,11,0.0,satisfied +8363,100021,Male,Loyal Customer,32,Business travel,Business,277,2,4,4,4,2,2,2,4,4,3,4,2,3,2,360,388.0,neutral or dissatisfied +8364,76879,Male,Loyal Customer,48,Business travel,Business,630,1,1,5,1,2,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +8365,39589,Female,Loyal Customer,49,Business travel,Business,945,4,3,3,3,1,4,3,4,4,4,4,3,4,2,0,6.0,neutral or dissatisfied +8366,14854,Female,Loyal Customer,54,Business travel,Business,315,4,4,4,4,2,1,3,4,4,4,4,1,4,2,0,0.0,satisfied +8367,106914,Male,Loyal Customer,57,Business travel,Business,1259,1,1,1,1,2,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +8368,19758,Female,Loyal Customer,57,Business travel,Business,462,2,2,2,2,5,5,3,5,5,5,5,2,5,5,0,0.0,satisfied +8369,115298,Female,Loyal Customer,67,Business travel,Eco,325,2,1,1,1,3,3,4,2,2,2,2,3,2,4,74,72.0,neutral or dissatisfied +8370,84992,Male,disloyal Customer,40,Business travel,Business,1590,1,2,2,1,4,2,4,4,3,4,4,4,5,4,1,5.0,neutral or dissatisfied +8371,19553,Male,Loyal Customer,43,Business travel,Eco,160,2,3,3,3,1,2,1,1,1,1,4,4,4,1,123,129.0,neutral or dissatisfied +8372,25768,Male,disloyal Customer,39,Business travel,Business,762,2,2,2,2,1,2,1,1,3,3,5,5,4,1,0,0.0,neutral or dissatisfied +8373,50678,Male,disloyal Customer,42,Personal Travel,Eco,134,4,1,4,3,4,4,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +8374,32896,Male,Loyal Customer,11,Personal Travel,Eco,101,3,4,0,2,5,0,1,5,3,5,5,2,4,5,0,0.0,neutral or dissatisfied +8375,105033,Male,disloyal Customer,36,Business travel,Business,361,1,2,2,4,2,2,2,2,1,2,4,1,3,2,33,13.0,neutral or dissatisfied +8376,38720,Female,Loyal Customer,38,Business travel,Business,3850,1,1,1,1,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +8377,34798,Female,Loyal Customer,39,Personal Travel,Eco,209,4,3,4,4,2,4,2,2,5,3,3,1,5,2,0,0.0,satisfied +8378,51051,Male,Loyal Customer,16,Personal Travel,Eco,78,2,5,0,2,4,0,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +8379,99274,Male,Loyal Customer,41,Business travel,Business,833,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +8380,35736,Male,disloyal Customer,42,Business travel,Business,2153,1,1,1,4,4,1,4,4,4,5,5,4,5,4,71,71.0,neutral or dissatisfied +8381,78895,Female,Loyal Customer,57,Business travel,Business,1823,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +8382,24939,Female,Loyal Customer,22,Business travel,Eco Plus,2106,5,1,1,1,5,4,4,5,4,4,3,4,5,5,4,0.0,satisfied +8383,105196,Male,Loyal Customer,54,Business travel,Eco Plus,281,2,5,5,5,2,2,2,2,2,1,4,3,3,2,34,23.0,neutral or dissatisfied +8384,7223,Male,Loyal Customer,61,Business travel,Business,135,4,3,5,3,2,3,3,1,1,1,4,3,1,4,0,0.0,neutral or dissatisfied +8385,79996,Female,Loyal Customer,11,Personal Travel,Eco,1010,3,5,3,5,2,3,2,2,4,1,1,4,3,2,0,13.0,neutral or dissatisfied +8386,105872,Male,Loyal Customer,50,Personal Travel,Eco Plus,787,3,1,2,3,5,2,5,5,2,4,4,3,4,5,4,13.0,neutral or dissatisfied +8387,57487,Female,Loyal Customer,50,Business travel,Business,1589,2,2,2,2,5,4,4,3,3,3,3,3,3,5,5,0.0,satisfied +8388,95764,Female,Loyal Customer,23,Personal Travel,Eco,237,3,4,0,3,1,0,1,1,4,5,4,3,4,1,49,36.0,neutral or dissatisfied +8389,37804,Female,Loyal Customer,47,Personal Travel,Eco Plus,1028,4,2,4,3,2,4,4,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +8390,19781,Female,Loyal Customer,51,Business travel,Eco,667,5,4,5,4,4,1,3,5,5,5,5,3,5,3,0,19.0,satisfied +8391,79735,Female,Loyal Customer,42,Business travel,Eco Plus,762,3,3,3,3,4,3,3,3,3,3,3,4,3,2,3,8.0,neutral or dissatisfied +8392,17969,Female,Loyal Customer,70,Personal Travel,Eco,460,1,2,1,4,4,3,3,5,5,1,5,2,5,2,0,0.0,neutral or dissatisfied +8393,72812,Male,Loyal Customer,20,Business travel,Eco Plus,1045,2,2,2,2,2,1,2,2,4,5,4,1,4,2,14,2.0,neutral or dissatisfied +8394,59864,Female,Loyal Customer,18,Business travel,Eco,937,1,3,4,3,1,1,1,1,4,3,4,3,3,1,3,0.0,neutral or dissatisfied +8395,124149,Male,Loyal Customer,20,Personal Travel,Business,2133,3,3,3,3,2,3,2,2,1,3,4,2,4,2,12,2.0,neutral or dissatisfied +8396,123785,Female,Loyal Customer,29,Business travel,Business,541,3,3,3,3,3,3,3,3,5,4,5,4,5,3,4,0.0,satisfied +8397,57531,Male,Loyal Customer,39,Business travel,Eco,413,2,5,5,5,2,2,2,2,3,5,3,4,3,2,10,6.0,neutral or dissatisfied +8398,47039,Female,disloyal Customer,42,Business travel,Eco,351,2,0,2,5,2,2,2,2,3,4,2,2,5,2,0,0.0,neutral or dissatisfied +8399,73453,Female,Loyal Customer,7,Personal Travel,Eco,1012,3,5,3,3,5,3,2,5,2,3,3,5,1,5,26,45.0,neutral or dissatisfied +8400,25423,Male,disloyal Customer,35,Business travel,Business,669,3,3,3,3,2,3,2,2,4,5,5,5,4,2,7,12.0,neutral or dissatisfied +8401,124348,Male,Loyal Customer,53,Business travel,Business,3078,4,4,4,4,4,3,3,4,4,4,4,4,4,2,62,60.0,neutral or dissatisfied +8402,105977,Female,Loyal Customer,24,Personal Travel,Eco,2329,4,2,3,3,3,3,3,3,2,4,4,2,4,3,39,6.0,neutral or dissatisfied +8403,10930,Female,disloyal Customer,22,Business travel,Eco,247,2,4,2,2,3,2,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +8404,2655,Female,disloyal Customer,25,Business travel,Business,539,3,0,3,2,3,3,4,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +8405,125928,Female,Loyal Customer,47,Personal Travel,Eco,1013,3,4,3,5,1,4,2,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +8406,4149,Male,Loyal Customer,39,Business travel,Business,2413,4,5,5,5,5,2,3,4,4,4,4,4,4,4,0,20.0,neutral or dissatisfied +8407,28185,Female,Loyal Customer,59,Personal Travel,Eco,873,4,1,4,3,3,4,3,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +8408,19345,Female,Loyal Customer,54,Personal Travel,Eco Plus,743,2,5,2,2,3,4,4,5,5,2,5,5,5,5,17,13.0,neutral or dissatisfied +8409,92032,Female,disloyal Customer,39,Business travel,Business,1535,5,5,5,1,1,5,1,1,3,3,5,4,5,1,7,0.0,satisfied +8410,26630,Male,disloyal Customer,23,Business travel,Eco,581,4,2,4,3,2,4,1,2,1,1,2,2,3,2,9,0.0,neutral or dissatisfied +8411,105389,Male,Loyal Customer,24,Personal Travel,Eco,369,2,2,2,4,3,2,3,3,1,1,3,4,4,3,0,0.0,neutral or dissatisfied +8412,96147,Male,Loyal Customer,47,Business travel,Eco,460,1,2,2,2,1,1,1,1,2,5,3,4,3,1,46,40.0,neutral or dissatisfied +8413,1813,Male,Loyal Customer,25,Business travel,Business,500,2,2,2,2,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +8414,5472,Male,Loyal Customer,24,Personal Travel,Eco,265,1,3,1,4,5,1,5,5,2,2,3,2,4,5,0,9.0,neutral or dissatisfied +8415,13701,Female,Loyal Customer,68,Personal Travel,Eco,483,2,3,2,3,2,3,3,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +8416,33957,Female,Loyal Customer,59,Business travel,Business,1554,2,4,4,4,2,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +8417,118159,Female,disloyal Customer,25,Business travel,Business,1444,5,0,5,1,3,5,3,3,3,3,4,5,4,3,18,3.0,satisfied +8418,102408,Female,Loyal Customer,34,Personal Travel,Eco,391,2,5,2,1,4,2,1,4,3,4,4,4,4,4,14,5.0,neutral or dissatisfied +8419,6118,Female,Loyal Customer,39,Business travel,Business,3817,5,5,3,5,2,5,5,4,4,4,4,3,4,4,0,3.0,satisfied +8420,29280,Female,Loyal Customer,25,Business travel,Business,859,1,2,2,2,1,1,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +8421,81930,Male,Loyal Customer,51,Personal Travel,Business,1535,1,1,1,2,1,2,3,4,4,1,3,1,4,2,5,0.0,neutral or dissatisfied +8422,73891,Female,disloyal Customer,30,Business travel,Business,1062,4,4,4,1,1,4,1,1,5,3,4,5,4,1,0,7.0,satisfied +8423,67665,Male,disloyal Customer,18,Business travel,Eco,1464,4,4,4,2,2,4,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +8424,126133,Male,Loyal Customer,51,Business travel,Business,3507,4,4,4,4,3,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +8425,39450,Male,Loyal Customer,17,Personal Travel,Eco,129,2,4,2,5,2,2,2,2,3,4,4,1,3,2,19,29.0,neutral or dissatisfied +8426,34241,Female,Loyal Customer,14,Personal Travel,Eco Plus,1237,3,4,3,2,4,3,3,4,4,4,4,3,4,4,9,1.0,neutral or dissatisfied +8427,70946,Male,Loyal Customer,30,Personal Travel,Eco,612,4,4,4,3,5,4,5,5,4,5,4,4,5,5,47,42.0,satisfied +8428,113775,Male,Loyal Customer,22,Personal Travel,Eco,223,2,5,2,4,3,2,3,3,4,2,4,5,5,3,0,2.0,neutral or dissatisfied +8429,66666,Male,Loyal Customer,34,Business travel,Business,1636,5,5,5,5,5,5,4,4,4,4,4,3,4,4,24,11.0,satisfied +8430,82447,Female,Loyal Customer,36,Business travel,Eco,509,3,4,4,4,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +8431,32203,Female,Loyal Customer,37,Business travel,Eco,163,4,5,5,5,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +8432,118129,Male,disloyal Customer,28,Business travel,Business,1488,3,3,3,4,5,3,5,5,4,4,4,5,5,5,42,28.0,neutral or dissatisfied +8433,63997,Female,disloyal Customer,27,Business travel,Eco,612,3,4,3,4,1,3,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +8434,46270,Female,Loyal Customer,60,Personal Travel,Eco,679,2,4,2,1,2,5,4,3,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +8435,52740,Male,disloyal Customer,29,Business travel,Eco,1310,1,1,1,3,4,1,4,4,4,5,3,1,3,4,0,0.0,neutral or dissatisfied +8436,23538,Male,Loyal Customer,53,Personal Travel,Eco,423,5,2,5,3,4,5,4,4,1,5,3,1,4,4,2,1.0,satisfied +8437,110055,Female,Loyal Customer,66,Personal Travel,Eco,2173,1,2,1,3,4,3,2,4,4,1,4,3,4,4,36,19.0,neutral or dissatisfied +8438,21189,Female,Loyal Customer,63,Business travel,Business,153,1,1,1,1,4,1,4,1,3,2,3,4,3,4,147,142.0,neutral or dissatisfied +8439,74823,Male,Loyal Customer,30,Personal Travel,Eco Plus,1205,5,2,5,3,4,5,4,4,2,4,3,4,4,4,0,0.0,satisfied +8440,61601,Male,Loyal Customer,43,Business travel,Business,1346,1,1,1,1,5,4,5,2,2,2,2,4,2,5,0,7.0,satisfied +8441,1056,Female,Loyal Customer,38,Personal Travel,Eco,158,5,4,5,3,2,5,2,2,3,2,4,3,5,2,0,0.0,satisfied +8442,124667,Male,Loyal Customer,39,Business travel,Business,399,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +8443,15548,Female,Loyal Customer,40,Business travel,Business,3826,0,0,0,3,4,5,5,3,3,3,5,5,3,5,97,106.0,satisfied +8444,121323,Male,Loyal Customer,29,Personal Travel,Eco,1009,2,3,2,4,5,2,5,5,3,4,4,2,4,5,0,0.0,neutral or dissatisfied +8445,15059,Female,Loyal Customer,29,Personal Travel,Eco,488,2,4,2,3,1,2,1,1,3,3,2,1,4,1,28,42.0,neutral or dissatisfied +8446,95204,Male,Loyal Customer,25,Personal Travel,Eco,239,2,5,2,5,4,2,4,4,2,1,1,5,3,4,0,0.0,neutral or dissatisfied +8447,31607,Male,Loyal Customer,29,Personal Travel,Eco,602,3,5,3,4,5,3,5,5,3,3,5,3,4,5,0,0.0,neutral or dissatisfied +8448,21860,Male,disloyal Customer,45,Business travel,Eco,448,2,4,2,1,3,2,3,3,5,3,3,3,4,3,1,0.0,neutral or dissatisfied +8449,13901,Male,Loyal Customer,46,Business travel,Business,3821,0,3,0,4,1,2,2,3,3,3,3,4,3,1,0,0.0,satisfied +8450,107015,Female,Loyal Customer,47,Personal Travel,Eco Plus,937,3,5,4,2,2,4,4,5,5,4,4,5,5,3,1,0.0,neutral or dissatisfied +8451,125085,Female,Loyal Customer,58,Business travel,Business,361,3,4,3,3,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +8452,58729,Male,disloyal Customer,24,Business travel,Eco,1050,2,2,2,3,1,2,1,1,4,4,4,4,5,1,1,4.0,neutral or dissatisfied +8453,21834,Female,Loyal Customer,33,Personal Travel,Eco,640,2,5,2,4,2,2,1,2,3,4,4,5,5,2,100,87.0,neutral or dissatisfied +8454,109841,Male,disloyal Customer,24,Business travel,Eco,1073,4,4,4,2,1,4,1,1,3,4,4,3,4,1,2,0.0,satisfied +8455,16294,Male,Loyal Customer,55,Personal Travel,Eco,631,4,4,4,4,3,4,5,3,5,1,3,5,4,3,0,0.0,neutral or dissatisfied +8456,109305,Female,Loyal Customer,41,Business travel,Business,2783,4,3,3,3,5,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +8457,17294,Female,Loyal Customer,53,Business travel,Business,403,4,4,4,4,2,1,1,5,5,5,5,4,5,2,0,0.0,satisfied +8458,98392,Male,Loyal Customer,62,Personal Travel,Business,462,3,4,4,3,5,4,5,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +8459,27842,Female,Loyal Customer,17,Personal Travel,Eco,1448,4,2,4,4,2,4,2,2,1,5,3,1,4,2,6,0.0,neutral or dissatisfied +8460,105487,Male,disloyal Customer,25,Business travel,Business,516,3,0,3,4,5,3,5,5,5,4,5,3,5,5,44,49.0,neutral or dissatisfied +8461,46969,Female,Loyal Customer,69,Personal Travel,Eco,909,3,5,3,3,5,5,5,5,5,3,5,3,5,1,4,25.0,neutral or dissatisfied +8462,83776,Male,Loyal Customer,56,Business travel,Business,3175,2,2,2,2,5,5,4,5,5,5,5,3,5,3,3,6.0,satisfied +8463,73708,Male,Loyal Customer,54,Business travel,Business,192,3,4,4,4,3,3,3,1,1,1,3,2,1,2,13,12.0,neutral or dissatisfied +8464,114851,Male,Loyal Customer,45,Business travel,Business,2689,4,4,4,4,5,4,4,4,2,4,4,4,3,4,252,231.0,satisfied +8465,3525,Female,Loyal Customer,31,Business travel,Business,557,1,1,1,1,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +8466,84407,Female,Loyal Customer,54,Personal Travel,Eco,606,3,1,3,2,2,2,3,1,1,3,1,4,1,2,0,1.0,neutral or dissatisfied +8467,62676,Female,Loyal Customer,43,Personal Travel,Eco Plus,1726,2,1,2,3,3,3,3,5,5,2,5,4,5,3,26,24.0,neutral or dissatisfied +8468,23048,Male,Loyal Customer,58,Business travel,Business,3848,1,1,1,1,2,4,5,5,5,5,5,4,5,5,35,23.0,satisfied +8469,988,Male,disloyal Customer,25,Business travel,Eco,102,3,3,3,2,4,3,4,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +8470,12392,Female,Loyal Customer,58,Business travel,Business,1640,4,4,4,4,4,2,4,5,5,4,4,4,5,5,23,25.0,satisfied +8471,88145,Male,Loyal Customer,53,Business travel,Business,270,1,1,1,1,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +8472,74714,Female,Loyal Customer,18,Personal Travel,Eco,1313,3,2,3,3,4,3,3,4,3,3,4,3,3,4,0,0.0,neutral or dissatisfied +8473,95487,Female,Loyal Customer,49,Business travel,Business,562,3,3,3,3,5,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +8474,113490,Female,Loyal Customer,61,Business travel,Business,3167,4,2,5,2,4,4,4,3,3,3,4,3,3,4,9,0.0,neutral or dissatisfied +8475,91750,Male,Loyal Customer,58,Business travel,Business,626,4,4,4,4,4,5,4,2,2,3,2,5,2,5,26,23.0,satisfied +8476,96314,Female,Loyal Customer,68,Personal Travel,Eco Plus,687,2,5,2,2,2,4,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +8477,105242,Female,Loyal Customer,40,Personal Travel,Eco,377,3,5,3,4,3,3,1,3,5,5,4,4,4,3,4,0.0,neutral or dissatisfied +8478,71539,Male,Loyal Customer,58,Business travel,Business,1005,2,2,2,2,5,4,5,5,5,5,5,3,5,3,7,0.0,satisfied +8479,59217,Male,Loyal Customer,20,Personal Travel,Eco,1440,3,5,3,1,2,3,2,2,4,2,3,3,5,2,3,0.0,neutral or dissatisfied +8480,92014,Male,Loyal Customer,53,Business travel,Business,1535,3,3,3,3,4,5,4,4,4,4,4,4,4,5,12,3.0,satisfied +8481,73416,Male,Loyal Customer,58,Business travel,Business,797,2,5,5,5,3,1,1,2,2,2,2,4,2,1,2,10.0,neutral or dissatisfied +8482,95257,Male,Loyal Customer,22,Personal Travel,Eco,148,2,1,2,3,1,2,1,1,1,5,3,2,3,1,7,0.0,neutral or dissatisfied +8483,21435,Female,Loyal Customer,36,Business travel,Eco,331,3,2,4,2,3,3,3,3,4,2,3,1,3,3,0,0.0,neutral or dissatisfied +8484,2240,Male,disloyal Customer,62,Business travel,Business,1041,4,5,5,5,4,4,2,4,4,3,4,3,4,4,6,13.0,satisfied +8485,53145,Male,Loyal Customer,56,Personal Travel,Eco,413,4,5,5,1,4,5,4,4,5,2,4,5,4,4,0,0.0,neutral or dissatisfied +8486,45918,Male,disloyal Customer,37,Business travel,Eco,409,2,3,2,1,4,2,4,4,2,2,5,2,1,4,0,3.0,neutral or dissatisfied +8487,76081,Male,Loyal Customer,26,Business travel,Eco,707,3,1,3,3,3,3,4,3,1,2,3,1,4,3,0,0.0,neutral or dissatisfied +8488,26185,Female,Loyal Customer,51,Business travel,Eco,515,2,1,1,1,4,4,4,2,2,2,2,4,2,3,107,103.0,neutral or dissatisfied +8489,22686,Female,Loyal Customer,38,Business travel,Eco,589,3,3,3,3,3,3,3,3,3,2,3,3,4,3,163,222.0,satisfied +8490,115933,Male,Loyal Customer,28,Business travel,Business,337,4,4,4,4,4,4,4,4,3,5,3,2,4,4,0,0.0,satisfied +8491,1805,Female,Loyal Customer,28,Business travel,Business,500,1,1,1,1,5,5,5,5,4,4,4,3,4,5,0,0.0,satisfied +8492,29993,Female,Loyal Customer,63,Business travel,Business,95,1,1,1,1,1,4,3,3,3,3,1,4,3,4,14,11.0,neutral or dissatisfied +8493,40342,Male,disloyal Customer,29,Business travel,Eco,920,4,4,4,3,3,4,3,3,3,1,3,1,3,3,23,16.0,satisfied +8494,37773,Female,Loyal Customer,38,Business travel,Eco Plus,1074,4,3,3,3,4,4,4,4,1,3,3,2,5,4,10,10.0,satisfied +8495,32270,Male,disloyal Customer,21,Business travel,Eco,102,2,5,3,4,5,3,5,5,3,2,5,2,5,5,5,2.0,neutral or dissatisfied +8496,115477,Female,disloyal Customer,27,Business travel,Business,362,1,1,1,1,1,1,1,1,4,2,5,5,5,1,2,1.0,neutral or dissatisfied +8497,24294,Female,Loyal Customer,38,Business travel,Eco Plus,302,2,2,2,2,2,2,2,2,1,4,4,3,3,2,0,6.0,neutral or dissatisfied +8498,115379,Female,Loyal Customer,56,Business travel,Business,480,2,2,2,2,5,5,5,1,1,2,1,5,1,3,0,0.0,satisfied +8499,93233,Male,disloyal Customer,21,Business travel,Business,1694,5,0,5,4,2,5,2,2,3,3,5,3,4,2,0,0.0,satisfied +8500,57338,Female,disloyal Customer,42,Business travel,Eco,414,3,2,3,4,3,3,3,3,3,2,3,3,4,3,8,0.0,neutral or dissatisfied +8501,102309,Female,Loyal Customer,48,Business travel,Business,3461,0,0,0,1,5,5,5,4,4,4,4,5,4,3,9,19.0,satisfied +8502,114877,Female,Loyal Customer,56,Business travel,Business,3567,2,2,2,2,5,5,5,4,4,4,4,3,4,3,6,5.0,satisfied +8503,82753,Male,Loyal Customer,44,Business travel,Business,409,2,2,2,2,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +8504,51815,Female,disloyal Customer,25,Business travel,Eco Plus,598,3,0,3,3,3,3,3,3,5,5,1,2,3,3,8,7.0,neutral or dissatisfied +8505,4881,Male,Loyal Customer,8,Personal Travel,Eco,408,1,3,1,4,5,1,5,5,2,2,4,3,3,5,0,0.0,neutral or dissatisfied +8506,26653,Female,Loyal Customer,44,Business travel,Eco,270,4,5,5,5,3,4,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +8507,114814,Female,Loyal Customer,56,Business travel,Business,3397,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +8508,93700,Female,Loyal Customer,48,Business travel,Eco Plus,1452,1,5,5,5,3,3,3,2,2,1,2,1,2,4,1,17.0,neutral or dissatisfied +8509,83167,Female,Loyal Customer,60,Personal Travel,Eco Plus,957,1,5,0,3,3,5,5,5,5,0,5,4,5,4,24,42.0,neutral or dissatisfied +8510,102376,Female,Loyal Customer,19,Business travel,Eco,223,5,1,1,1,5,5,3,5,2,1,3,2,1,5,54,50.0,satisfied +8511,95450,Female,disloyal Customer,26,Business travel,Eco Plus,458,2,2,2,4,3,2,3,3,4,1,3,3,3,3,41,48.0,neutral or dissatisfied +8512,53679,Male,Loyal Customer,33,Business travel,Business,1208,2,3,3,3,2,2,2,2,3,5,3,1,4,2,30,10.0,neutral or dissatisfied +8513,117282,Female,Loyal Customer,40,Business travel,Business,3738,0,1,1,2,4,4,5,4,4,4,4,3,4,5,1,0.0,satisfied +8514,91760,Male,Loyal Customer,48,Business travel,Business,588,3,2,2,2,5,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +8515,60914,Female,Loyal Customer,34,Business travel,Business,888,3,3,3,3,4,5,5,3,3,3,3,4,3,4,26,10.0,satisfied +8516,93392,Male,Loyal Customer,40,Business travel,Business,671,4,4,4,4,4,4,5,5,5,4,5,3,5,5,28,19.0,satisfied +8517,72884,Female,Loyal Customer,12,Business travel,Business,2108,5,5,5,5,4,4,4,4,5,5,5,5,5,4,0,0.0,satisfied +8518,31198,Female,Loyal Customer,60,Business travel,Eco,628,4,2,2,2,5,2,3,4,4,4,4,4,4,5,0,0.0,satisfied +8519,74236,Female,Loyal Customer,38,Personal Travel,Eco,888,3,3,3,3,1,3,1,1,4,2,2,1,5,1,4,6.0,neutral or dissatisfied +8520,33744,Female,Loyal Customer,40,Business travel,Eco,2277,5,3,3,3,5,5,5,5,1,3,5,3,3,5,0,5.0,satisfied +8521,79632,Male,Loyal Customer,44,Business travel,Eco,762,2,5,4,5,2,2,2,2,1,4,3,3,4,2,0,0.0,neutral or dissatisfied +8522,52528,Male,Loyal Customer,52,Business travel,Business,160,1,1,1,1,5,4,3,5,5,5,3,3,5,2,0,0.0,satisfied +8523,26747,Female,disloyal Customer,29,Business travel,Eco,859,1,1,1,2,1,1,1,1,3,2,2,4,2,1,0,10.0,neutral or dissatisfied +8524,99487,Male,Loyal Customer,29,Personal Travel,Eco,283,1,5,1,2,1,1,1,1,3,3,3,5,4,1,7,11.0,neutral or dissatisfied +8525,30290,Male,Loyal Customer,39,Business travel,Business,1533,4,4,4,4,3,2,3,3,3,4,3,5,3,1,0,2.0,satisfied +8526,20203,Female,disloyal Customer,38,Business travel,Business,137,1,1,1,1,4,1,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +8527,84633,Female,Loyal Customer,45,Personal Travel,Eco,669,3,4,3,2,4,4,4,5,5,3,5,4,5,4,30,24.0,neutral or dissatisfied +8528,53294,Female,Loyal Customer,33,Business travel,Business,758,1,3,3,3,5,3,3,1,1,1,1,1,1,2,0,1.0,neutral or dissatisfied +8529,13692,Female,Loyal Customer,27,Business travel,Business,1872,3,3,3,3,2,2,2,2,5,4,1,4,3,2,0,0.0,satisfied +8530,111894,Female,Loyal Customer,16,Personal Travel,Eco,628,2,5,3,1,1,3,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +8531,31476,Female,Loyal Customer,39,Business travel,Business,846,2,2,3,2,1,4,1,5,5,5,5,1,5,1,0,0.0,satisfied +8532,79537,Male,disloyal Customer,24,Business travel,Eco,762,4,5,5,4,4,5,4,4,5,5,5,4,4,4,0,0.0,satisfied +8533,120247,Female,Loyal Customer,53,Personal Travel,Eco,1303,4,3,4,4,5,4,3,2,2,4,2,1,2,2,0,15.0,neutral or dissatisfied +8534,87021,Male,Loyal Customer,59,Business travel,Business,594,2,1,2,2,4,4,4,4,4,4,4,4,4,3,8,21.0,satisfied +8535,110097,Male,Loyal Customer,37,Business travel,Business,1048,1,5,5,5,1,4,4,1,1,2,1,3,1,4,41,59.0,neutral or dissatisfied +8536,121756,Female,Loyal Customer,55,Business travel,Business,337,5,5,2,5,2,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +8537,48708,Male,Loyal Customer,35,Business travel,Business,421,2,2,2,2,3,5,5,2,2,2,2,4,2,5,14,14.0,satisfied +8538,46061,Female,Loyal Customer,59,Business travel,Eco Plus,996,1,1,1,1,3,3,4,1,1,1,1,1,1,4,3,0.0,neutral or dissatisfied +8539,100296,Male,Loyal Customer,17,Business travel,Business,3674,4,4,4,4,4,4,4,4,4,4,4,5,5,4,0,0.0,satisfied +8540,73621,Female,Loyal Customer,43,Business travel,Business,204,1,1,1,1,3,5,5,4,4,4,4,3,4,3,12,7.0,satisfied +8541,46230,Male,Loyal Customer,35,Business travel,Business,2116,1,1,1,1,5,3,2,3,3,4,3,5,3,5,0,0.0,satisfied +8542,66803,Female,disloyal Customer,25,Business travel,Business,731,3,0,3,2,3,3,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +8543,58428,Male,Loyal Customer,52,Business travel,Business,3562,3,1,4,1,4,3,3,3,3,3,3,3,3,3,5,10.0,neutral or dissatisfied +8544,19940,Female,Loyal Customer,22,Personal Travel,Eco,315,2,4,2,2,4,2,4,4,5,2,5,4,1,4,1,81.0,neutral or dissatisfied +8545,22102,Male,Loyal Customer,52,Business travel,Business,694,5,5,4,5,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +8546,67256,Male,Loyal Customer,37,Personal Travel,Eco,1119,3,4,4,2,3,4,3,3,4,4,5,5,5,3,0,16.0,neutral or dissatisfied +8547,23185,Female,Loyal Customer,52,Personal Travel,Eco,646,3,5,3,4,2,3,1,2,2,3,2,5,2,2,0,0.0,neutral or dissatisfied +8548,113726,Female,Loyal Customer,23,Personal Travel,Eco,258,2,4,2,3,1,2,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +8549,108793,Female,Loyal Customer,30,Business travel,Business,2264,4,4,4,4,4,4,4,4,5,3,1,3,5,4,0,0.0,satisfied +8550,19416,Male,Loyal Customer,26,Business travel,Eco,645,5,2,2,2,5,5,5,5,1,3,4,5,2,5,11,,satisfied +8551,100254,Male,Loyal Customer,59,Business travel,Business,2174,5,5,5,5,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +8552,91769,Female,Loyal Customer,54,Business travel,Business,3040,0,0,0,4,4,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +8553,24598,Male,Loyal Customer,42,Business travel,Eco,526,4,1,1,1,4,4,4,4,3,1,1,5,1,4,0,0.0,satisfied +8554,67764,Female,Loyal Customer,39,Business travel,Business,2590,1,1,3,1,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +8555,96484,Male,disloyal Customer,36,Business travel,Business,302,3,3,3,2,5,3,2,5,5,2,5,5,4,5,0,0.0,neutral or dissatisfied +8556,98907,Male,Loyal Customer,39,Business travel,Business,543,1,2,1,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +8557,26499,Female,Loyal Customer,33,Business travel,Business,829,3,3,3,3,3,1,2,4,4,4,4,1,4,5,10,2.0,satisfied +8558,85732,Male,Loyal Customer,67,Business travel,Business,1739,2,2,2,2,5,5,4,5,5,5,5,4,5,3,23,20.0,satisfied +8559,74954,Female,Loyal Customer,58,Business travel,Eco,975,4,1,1,1,2,2,4,4,4,4,4,5,4,1,0,0.0,satisfied +8560,128484,Female,Loyal Customer,30,Personal Travel,Eco,651,1,5,1,2,4,1,4,4,5,5,4,2,1,4,0,10.0,neutral or dissatisfied +8561,96734,Male,Loyal Customer,59,Personal Travel,Eco,696,5,4,5,2,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +8562,43283,Male,Loyal Customer,38,Business travel,Eco,531,5,1,1,1,5,5,5,5,2,2,1,2,3,5,0,0.0,satisfied +8563,83023,Male,Loyal Customer,42,Business travel,Business,2317,2,2,2,2,3,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +8564,112540,Female,Loyal Customer,30,Business travel,Business,862,2,2,2,2,5,5,5,5,5,2,4,4,5,5,7,36.0,satisfied +8565,58421,Female,Loyal Customer,31,Business travel,Business,1773,1,3,4,3,1,1,1,1,3,3,2,2,2,1,52,48.0,neutral or dissatisfied +8566,88693,Female,Loyal Customer,26,Personal Travel,Eco,515,1,4,1,3,5,1,4,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +8567,57967,Female,Loyal Customer,49,Personal Travel,Eco,1911,1,4,1,3,1,5,5,5,5,1,5,1,5,4,0,0.0,neutral or dissatisfied +8568,80973,Female,Loyal Customer,42,Business travel,Business,297,0,0,0,2,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +8569,125860,Female,Loyal Customer,54,Business travel,Business,3074,4,3,3,3,1,4,4,4,4,3,4,4,4,2,34,60.0,neutral or dissatisfied +8570,96412,Female,Loyal Customer,28,Personal Travel,Eco,1342,4,2,4,4,4,4,4,4,2,5,2,3,4,4,2,0.0,neutral or dissatisfied +8571,83421,Female,Loyal Customer,55,Personal Travel,Eco,632,3,3,3,4,1,4,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +8572,993,Male,disloyal Customer,22,Business travel,Eco,113,4,0,4,1,3,4,3,3,4,4,1,3,2,3,5,0.0,satisfied +8573,74658,Male,Loyal Customer,11,Personal Travel,Eco,1205,3,5,3,3,2,3,2,2,4,3,2,3,3,2,0,5.0,neutral or dissatisfied +8574,113059,Male,disloyal Customer,50,Business travel,Business,569,5,5,5,3,2,5,2,2,5,2,5,5,4,2,0,0.0,satisfied +8575,52888,Female,Loyal Customer,31,Personal Travel,Eco,836,0,4,0,2,5,0,5,5,3,5,4,4,5,5,0,0.0,satisfied +8576,73057,Female,Loyal Customer,8,Business travel,Business,1988,4,4,3,4,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +8577,21011,Male,Loyal Customer,45,Business travel,Business,227,0,0,0,2,4,4,5,4,4,4,4,4,4,3,0,4.0,satisfied +8578,106212,Female,Loyal Customer,43,Business travel,Business,1844,2,5,5,5,4,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +8579,124632,Male,Loyal Customer,45,Personal Travel,Eco,1671,4,1,4,4,1,4,1,1,3,4,3,2,3,1,0,0.0,neutral or dissatisfied +8580,88911,Male,Loyal Customer,33,Personal Travel,Eco,859,4,2,4,4,4,4,4,4,1,3,4,2,3,4,0,0.0,satisfied +8581,46880,Male,Loyal Customer,59,Business travel,Business,948,5,5,5,5,5,3,1,5,5,5,5,1,5,5,47,55.0,satisfied +8582,71308,Male,Loyal Customer,31,Business travel,Business,1514,2,2,2,2,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +8583,95449,Female,disloyal Customer,27,Business travel,Business,189,5,5,5,1,3,5,3,3,5,2,5,4,5,3,23,20.0,satisfied +8584,15745,Male,Loyal Customer,44,Business travel,Business,544,5,5,5,5,4,5,1,4,4,4,4,4,4,5,0,0.0,satisfied +8585,80825,Female,disloyal Customer,33,Business travel,Business,692,3,3,3,4,1,3,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +8586,51710,Female,Loyal Customer,16,Business travel,Business,2879,3,3,1,3,3,3,3,3,3,5,1,3,4,3,0,0.0,satisfied +8587,21004,Male,Loyal Customer,25,Business travel,Eco Plus,721,3,2,2,2,3,3,2,3,1,1,3,2,3,3,0,0.0,neutral or dissatisfied +8588,29949,Female,Loyal Customer,56,Business travel,Business,183,0,3,0,5,2,3,2,2,2,2,2,5,2,1,22,34.0,satisfied +8589,69637,Female,Loyal Customer,36,Business travel,Business,2120,3,3,3,3,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +8590,73307,Male,Loyal Customer,50,Business travel,Business,2762,2,2,2,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +8591,18730,Female,Loyal Customer,52,Business travel,Business,1167,4,4,4,4,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +8592,59951,Male,Loyal Customer,46,Business travel,Business,3077,5,5,5,5,4,4,5,4,4,4,4,5,4,5,2,0.0,satisfied +8593,22240,Male,Loyal Customer,52,Business travel,Business,3442,1,1,1,1,5,4,4,3,3,3,1,4,3,2,34,31.0,neutral or dissatisfied +8594,84904,Female,Loyal Customer,40,Personal Travel,Eco,534,4,5,4,3,2,4,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +8595,31050,Female,Loyal Customer,55,Business travel,Business,862,2,4,4,4,3,2,2,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +8596,38801,Female,Loyal Customer,67,Personal Travel,Eco,354,3,4,3,1,5,4,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +8597,30842,Male,Loyal Customer,30,Business travel,Eco Plus,1211,2,2,2,2,2,2,2,2,1,1,4,3,3,2,20,13.0,neutral or dissatisfied +8598,29156,Female,Loyal Customer,35,Business travel,Eco Plus,605,5,1,1,1,5,5,5,5,1,3,1,5,4,5,0,0.0,satisfied +8599,63279,Female,Loyal Customer,38,Business travel,Business,337,5,5,5,5,5,5,5,5,5,5,5,4,5,5,2,0.0,satisfied +8600,348,Male,Loyal Customer,56,Personal Travel,Eco,853,3,4,3,1,1,3,1,1,3,4,5,3,4,1,0,0.0,neutral or dissatisfied +8601,52599,Female,Loyal Customer,72,Business travel,Business,1793,2,2,2,2,1,1,2,1,1,1,2,2,1,4,0,51.0,neutral or dissatisfied +8602,96384,Female,disloyal Customer,24,Business travel,Business,1407,3,3,3,3,2,3,2,2,3,4,3,1,3,2,1,3.0,neutral or dissatisfied +8603,105797,Male,Loyal Customer,13,Personal Travel,Eco,925,2,5,2,1,3,2,3,3,4,2,4,5,5,3,95,91.0,neutral or dissatisfied +8604,42058,Female,Loyal Customer,39,Personal Travel,Eco,106,3,5,0,1,3,0,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +8605,33237,Female,Loyal Customer,36,Business travel,Eco Plus,102,5,5,4,4,5,5,5,5,2,2,4,5,4,5,0,0.0,satisfied +8606,63524,Female,Loyal Customer,29,Business travel,Business,1009,3,3,3,3,4,4,4,4,3,3,4,4,5,4,0,0.0,satisfied +8607,38327,Male,Loyal Customer,42,Business travel,Eco,1133,4,2,2,2,4,4,4,4,2,2,4,1,4,4,7,22.0,satisfied +8608,11947,Female,Loyal Customer,30,Business travel,Business,781,1,0,0,4,3,0,1,3,3,5,3,2,3,3,0,0.0,neutral or dissatisfied +8609,70469,Male,disloyal Customer,27,Business travel,Business,867,3,3,3,4,2,3,2,2,5,3,4,5,4,2,0,1.0,neutral or dissatisfied +8610,95966,Male,Loyal Customer,58,Business travel,Business,2645,5,5,5,5,2,4,5,3,3,3,3,4,3,5,46,40.0,satisfied +8611,31726,Female,Loyal Customer,48,Personal Travel,Eco,846,3,5,3,1,4,4,5,1,1,3,1,3,1,3,0,0.0,neutral or dissatisfied +8612,100308,Male,Loyal Customer,48,Business travel,Business,2659,1,1,1,1,5,5,5,2,2,2,2,3,2,5,1,0.0,satisfied +8613,45202,Female,Loyal Customer,56,Business travel,Business,3398,3,3,3,3,5,5,4,5,5,5,5,3,5,5,15,7.0,satisfied +8614,59634,Female,Loyal Customer,17,Business travel,Business,3633,2,5,5,5,2,2,2,2,4,1,3,3,4,2,12,0.0,neutral or dissatisfied +8615,82371,Female,disloyal Customer,27,Business travel,Eco Plus,453,3,3,3,3,5,3,5,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +8616,66486,Male,disloyal Customer,40,Business travel,Business,447,3,3,3,4,5,3,5,5,3,2,5,4,5,5,1,0.0,neutral or dissatisfied +8617,118953,Female,Loyal Customer,44,Business travel,Business,3384,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +8618,44768,Male,Loyal Customer,27,Business travel,Eco,1250,5,2,2,2,5,4,5,5,2,5,5,1,1,5,0,0.0,satisfied +8619,116326,Male,Loyal Customer,14,Personal Travel,Eco,337,1,5,1,5,1,2,2,3,3,4,5,2,5,2,117,132.0,neutral or dissatisfied +8620,116252,Female,Loyal Customer,59,Personal Travel,Eco,342,2,5,2,4,2,4,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +8621,35377,Female,disloyal Customer,27,Business travel,Eco,972,3,3,3,3,5,3,5,5,2,1,4,1,1,5,0,0.0,neutral or dissatisfied +8622,101067,Female,Loyal Customer,11,Personal Travel,Eco,368,2,3,2,2,2,2,2,2,1,5,3,3,4,2,1,0.0,neutral or dissatisfied +8623,14920,Female,Loyal Customer,51,Personal Travel,Eco,240,4,4,4,2,2,1,5,2,2,4,5,2,2,3,0,0.0,neutral or dissatisfied +8624,99533,Male,Loyal Customer,35,Personal Travel,Business,802,4,5,4,3,2,4,5,3,3,4,3,3,3,5,0,1.0,neutral or dissatisfied +8625,23765,Male,disloyal Customer,41,Business travel,Business,374,4,4,4,3,3,4,3,3,4,5,4,3,5,3,31,31.0,satisfied +8626,113631,Female,Loyal Customer,28,Personal Travel,Eco,258,0,2,0,4,4,0,4,4,3,1,4,3,3,4,1,0.0,satisfied +8627,27878,Male,Loyal Customer,17,Business travel,Eco Plus,680,4,1,1,1,4,4,3,4,2,1,3,4,3,4,15,8.0,neutral or dissatisfied +8628,67834,Male,Loyal Customer,55,Business travel,Business,3020,3,3,3,3,2,5,5,4,4,5,4,5,4,2,0,0.0,satisfied +8629,11318,Female,Loyal Customer,54,Personal Travel,Eco,247,2,5,2,2,4,4,5,2,2,2,2,3,2,3,14,7.0,neutral or dissatisfied +8630,102571,Female,Loyal Customer,34,Business travel,Business,2418,3,3,3,3,2,5,4,2,2,2,2,5,2,5,6,10.0,satisfied +8631,5789,Female,Loyal Customer,54,Business travel,Business,3115,4,4,4,4,3,4,5,4,4,4,5,3,4,3,4,28.0,satisfied +8632,77439,Female,Loyal Customer,60,Business travel,Eco Plus,199,3,2,2,2,2,4,3,3,3,3,3,1,3,2,35,16.0,neutral or dissatisfied +8633,3349,Male,disloyal Customer,24,Business travel,Business,240,4,0,3,5,5,3,5,5,3,5,4,4,5,5,0,0.0,satisfied +8634,104011,Male,Loyal Customer,45,Personal Travel,Eco,1363,2,4,2,3,1,2,1,1,2,2,4,1,3,1,3,11.0,neutral or dissatisfied +8635,50142,Male,Loyal Customer,56,Business travel,Business,1644,0,0,0,1,3,5,2,3,3,3,3,3,3,1,0,0.0,satisfied +8636,86233,Female,Loyal Customer,41,Personal Travel,Eco,306,0,2,0,3,5,0,5,5,2,5,4,1,4,5,0,0.0,satisfied +8637,78146,Male,Loyal Customer,48,Business travel,Business,3617,2,2,2,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +8638,20316,Male,disloyal Customer,21,Business travel,Eco,837,2,2,2,5,5,2,5,5,1,5,3,1,4,5,30,55.0,neutral or dissatisfied +8639,100341,Female,disloyal Customer,36,Business travel,Eco,571,2,0,2,2,3,2,3,3,4,2,4,2,2,3,0,0.0,neutral or dissatisfied +8640,5990,Female,Loyal Customer,59,Business travel,Business,3747,3,4,3,3,3,5,5,4,4,4,4,5,4,4,59,47.0,satisfied +8641,40347,Male,Loyal Customer,20,Business travel,Business,1428,2,2,2,2,4,4,4,4,2,5,1,2,1,4,0,3.0,satisfied +8642,34999,Female,disloyal Customer,25,Business travel,Eco,1182,2,1,1,3,1,2,2,1,3,2,2,2,2,2,198,271.0,neutral or dissatisfied +8643,9217,Female,Loyal Customer,52,Business travel,Business,177,3,3,5,3,2,5,4,4,4,4,5,5,4,4,116,119.0,satisfied +8644,48940,Male,Loyal Customer,37,Business travel,Business,3856,0,0,0,2,1,2,5,3,3,3,4,2,3,5,0,7.0,satisfied +8645,15175,Male,Loyal Customer,43,Business travel,Eco,416,5,5,2,2,5,5,5,5,4,2,1,5,3,5,0,0.0,satisfied +8646,86238,Male,Loyal Customer,39,Personal Travel,Eco,356,2,4,2,3,5,2,1,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +8647,75710,Female,Loyal Customer,59,Business travel,Business,813,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +8648,21480,Female,Loyal Customer,38,Business travel,Eco,331,2,1,2,1,2,2,2,2,4,5,3,1,2,2,65,50.0,neutral or dissatisfied +8649,70062,Male,Loyal Customer,43,Business travel,Business,460,2,2,2,2,5,5,4,4,4,4,4,5,4,4,18,15.0,satisfied +8650,95959,Female,Loyal Customer,66,Business travel,Business,3389,5,5,5,5,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +8651,6934,Male,Loyal Customer,52,Business travel,Business,1985,1,1,1,1,2,4,4,5,5,5,5,3,5,3,10,3.0,satisfied +8652,108089,Male,Loyal Customer,47,Business travel,Business,3763,2,3,2,2,5,5,5,5,5,5,5,5,5,5,49,48.0,satisfied +8653,115289,Male,Loyal Customer,38,Business travel,Business,337,3,3,3,3,4,4,3,3,3,3,3,4,3,1,58,60.0,neutral or dissatisfied +8654,44981,Male,disloyal Customer,42,Business travel,Business,359,3,3,3,5,2,3,2,2,3,5,5,1,3,2,0,0.0,neutral or dissatisfied +8655,60858,Male,Loyal Customer,39,Personal Travel,Business,1491,3,2,3,4,2,4,4,4,4,3,4,2,4,2,12,36.0,neutral or dissatisfied +8656,104050,Female,Loyal Customer,36,Personal Travel,Eco,1044,1,4,1,1,1,1,2,1,2,5,1,1,3,1,4,0.0,neutral or dissatisfied +8657,52357,Female,Loyal Customer,63,Personal Travel,Eco,370,2,3,2,1,1,4,2,4,4,2,4,4,4,4,1,0.0,neutral or dissatisfied +8658,114453,Female,Loyal Customer,51,Business travel,Business,342,4,4,4,4,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +8659,86145,Male,Loyal Customer,40,Business travel,Business,356,3,3,2,3,5,5,4,5,5,5,5,5,5,3,26,3.0,satisfied +8660,47481,Male,Loyal Customer,37,Personal Travel,Eco,590,2,5,2,3,2,2,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +8661,44993,Male,Loyal Customer,60,Business travel,Business,1851,3,3,3,3,2,5,3,5,5,5,5,2,5,2,0,0.0,satisfied +8662,12599,Female,Loyal Customer,10,Personal Travel,Eco,542,3,4,1,5,5,1,5,5,5,2,2,1,4,5,0,0.0,neutral or dissatisfied +8663,122340,Female,Loyal Customer,47,Business travel,Business,2417,5,5,5,5,4,4,4,4,4,4,4,4,4,3,4,7.0,satisfied +8664,2689,Female,disloyal Customer,25,Business travel,Business,562,4,0,4,3,5,4,5,5,3,5,5,3,5,5,21,75.0,neutral or dissatisfied +8665,128416,Male,Loyal Customer,49,Business travel,Business,370,1,5,2,2,3,4,3,1,1,1,1,4,1,3,7,6.0,neutral or dissatisfied +8666,4512,Male,Loyal Customer,20,Personal Travel,Eco,551,3,4,3,5,5,3,5,5,5,3,2,1,4,5,0,3.0,neutral or dissatisfied +8667,81066,Female,disloyal Customer,37,Business travel,Business,931,2,2,2,3,3,2,3,3,2,5,2,2,3,3,0,0.0,neutral or dissatisfied +8668,52138,Male,Loyal Customer,38,Business travel,Business,2990,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +8669,71421,Female,disloyal Customer,40,Business travel,Business,867,2,2,2,3,4,2,4,4,1,2,3,3,3,4,0,0.0,neutral or dissatisfied +8670,121488,Female,Loyal Customer,51,Personal Travel,Eco,331,2,5,2,4,3,4,4,1,1,2,1,3,1,4,0,11.0,neutral or dissatisfied +8671,47477,Male,Loyal Customer,13,Personal Travel,Eco,626,0,1,0,3,4,0,3,4,4,2,3,2,2,4,0,0.0,satisfied +8672,72251,Female,disloyal Customer,25,Business travel,Business,919,3,5,3,2,5,3,5,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +8673,112985,Male,disloyal Customer,39,Business travel,Business,1751,1,1,1,3,4,1,4,4,5,3,5,4,4,4,7,11.0,neutral or dissatisfied +8674,35316,Male,disloyal Customer,14,Business travel,Eco,1028,3,3,3,4,5,3,1,5,1,2,4,2,4,5,70,71.0,neutral or dissatisfied +8675,15048,Male,Loyal Customer,41,Business travel,Eco,604,1,3,3,3,1,1,1,1,3,5,4,4,3,1,25,20.0,neutral or dissatisfied +8676,38283,Female,Loyal Customer,25,Personal Travel,Eco,1050,2,5,2,3,3,2,3,3,3,5,5,5,5,3,3,1.0,neutral or dissatisfied +8677,66026,Female,Loyal Customer,16,Business travel,Business,1345,4,4,4,4,5,5,5,5,4,3,4,4,4,5,11,0.0,satisfied +8678,60659,Male,Loyal Customer,30,Personal Travel,Eco,1620,4,4,4,1,4,4,3,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +8679,72645,Male,Loyal Customer,55,Personal Travel,Eco,985,2,5,2,1,3,2,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +8680,85589,Male,disloyal Customer,37,Business travel,Eco,259,1,1,2,3,1,2,1,1,2,1,4,4,4,1,21,6.0,neutral or dissatisfied +8681,117366,Female,Loyal Customer,41,Personal Travel,Eco,296,2,3,2,4,1,2,1,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +8682,79706,Male,Loyal Customer,40,Personal Travel,Eco,749,2,3,2,1,4,2,4,4,5,3,3,5,4,4,0,8.0,neutral or dissatisfied +8683,127673,Male,disloyal Customer,20,Business travel,Eco,653,3,5,4,4,3,4,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +8684,25657,Female,Loyal Customer,27,Business travel,Business,2672,4,4,4,4,5,5,5,5,3,1,1,1,3,5,6,1.0,satisfied +8685,35404,Male,disloyal Customer,39,Business travel,Eco,641,2,0,2,5,1,2,3,1,2,4,4,4,1,1,0,5.0,neutral or dissatisfied +8686,60400,Female,Loyal Customer,45,Personal Travel,Eco,1452,1,3,1,2,2,4,2,3,3,1,3,5,3,4,64,42.0,neutral or dissatisfied +8687,97514,Male,Loyal Customer,45,Business travel,Eco,439,2,1,1,1,1,2,1,1,1,5,4,2,4,1,98,106.0,neutral or dissatisfied +8688,19594,Male,Loyal Customer,15,Personal Travel,Eco,160,2,1,2,3,5,2,5,5,1,4,4,1,4,5,0,0.0,neutral or dissatisfied +8689,27337,Female,Loyal Customer,37,Business travel,Eco,978,5,4,4,4,5,5,5,5,4,1,1,3,4,5,0,0.0,satisfied +8690,31143,Male,Loyal Customer,8,Personal Travel,Eco Plus,991,3,4,3,4,2,3,2,2,4,4,4,3,4,2,4,18.0,neutral or dissatisfied +8691,17645,Female,Loyal Customer,33,Business travel,Business,3988,2,2,2,2,3,1,2,4,4,4,4,3,4,4,48,31.0,satisfied +8692,70994,Male,disloyal Customer,26,Business travel,Business,802,1,1,1,4,1,1,1,1,5,2,5,5,4,1,90,89.0,neutral or dissatisfied +8693,34914,Female,Loyal Customer,33,Business travel,Business,395,2,2,2,2,4,3,4,4,4,4,4,2,4,4,0,0.0,satisfied +8694,52947,Female,Loyal Customer,34,Business travel,Business,1448,2,2,2,2,3,2,4,4,4,4,4,5,4,2,0,0.0,satisfied +8695,109489,Male,Loyal Customer,49,Business travel,Business,920,1,1,1,1,2,5,5,5,5,5,5,5,5,3,39,33.0,satisfied +8696,372,Male,Loyal Customer,50,Business travel,Business,3579,1,1,1,1,4,4,4,4,4,5,4,5,4,5,25,22.0,satisfied +8697,95455,Male,Loyal Customer,57,Business travel,Business,239,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +8698,56241,Male,Loyal Customer,11,Business travel,Business,2434,1,1,2,1,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +8699,33044,Male,Loyal Customer,40,Personal Travel,Eco,102,4,5,4,4,3,4,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +8700,20368,Female,Loyal Customer,22,Personal Travel,Eco,323,1,2,1,4,5,1,5,5,3,3,3,2,3,5,11,11.0,neutral or dissatisfied +8701,60102,Male,Loyal Customer,50,Business travel,Business,3161,2,2,2,2,3,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +8702,36864,Male,Loyal Customer,19,Business travel,Business,273,4,4,4,4,4,4,4,4,1,1,3,2,5,4,0,0.0,satisfied +8703,111964,Female,disloyal Customer,23,Business travel,Eco,533,1,2,1,4,5,1,4,5,1,3,4,3,3,5,44,36.0,neutral or dissatisfied +8704,6434,Female,Loyal Customer,37,Personal Travel,Eco,315,4,5,2,5,4,2,4,4,3,4,4,3,5,4,48,42.0,neutral or dissatisfied +8705,78811,Male,Loyal Customer,19,Personal Travel,Eco,447,2,2,3,3,3,3,5,3,4,1,4,1,3,3,0,0.0,neutral or dissatisfied +8706,66518,Male,Loyal Customer,57,Personal Travel,Eco,447,2,4,2,3,4,2,4,4,5,4,4,4,4,4,0,0.0,neutral or dissatisfied +8707,80065,Male,Loyal Customer,33,Personal Travel,Eco,1096,1,0,1,3,5,1,5,5,5,2,5,5,4,5,122,112.0,neutral or dissatisfied +8708,45161,Female,Loyal Customer,37,Business travel,Business,1632,4,4,5,4,4,3,1,4,4,4,4,3,4,1,0,0.0,satisfied +8709,15872,Female,Loyal Customer,46,Business travel,Business,1909,4,2,2,2,2,4,4,4,4,3,4,2,4,4,24,11.0,neutral or dissatisfied +8710,120533,Female,Loyal Customer,12,Personal Travel,Eco Plus,96,3,2,3,4,1,3,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +8711,61645,Male,Loyal Customer,51,Business travel,Business,1464,5,2,5,5,4,5,4,4,4,4,4,3,4,3,6,0.0,satisfied +8712,81549,Female,Loyal Customer,30,Personal Travel,Eco Plus,1124,2,5,2,3,2,2,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +8713,83950,Male,disloyal Customer,23,Business travel,Eco,373,3,4,3,4,1,3,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +8714,62995,Female,Loyal Customer,24,Business travel,Business,2489,2,3,3,3,2,2,2,2,2,5,2,3,2,2,16,9.0,neutral or dissatisfied +8715,41151,Female,Loyal Customer,8,Personal Travel,Eco,140,4,0,4,1,1,4,1,1,5,3,5,5,5,1,0,6.0,neutral or dissatisfied +8716,118922,Male,Loyal Customer,46,Personal Travel,Eco,587,2,4,2,3,4,2,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +8717,46797,Female,Loyal Customer,31,Personal Travel,Business,850,1,5,1,5,4,1,4,4,3,2,4,4,4,4,36,34.0,neutral or dissatisfied +8718,21620,Female,Loyal Customer,23,Business travel,Business,3702,2,1,1,1,2,3,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +8719,15058,Male,Loyal Customer,18,Personal Travel,Eco,576,1,5,1,2,2,1,4,2,2,1,3,3,1,2,0,0.0,neutral or dissatisfied +8720,98805,Female,Loyal Customer,16,Personal Travel,Business,444,2,4,2,3,2,2,2,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +8721,33265,Male,Loyal Customer,52,Personal Travel,Eco Plus,102,3,3,3,1,2,3,2,2,2,5,1,5,5,2,0,0.0,neutral or dissatisfied +8722,120738,Female,Loyal Customer,57,Personal Travel,Eco,1089,1,4,1,3,3,4,4,3,3,1,3,4,3,3,0,1.0,neutral or dissatisfied +8723,6646,Female,Loyal Customer,36,Business travel,Business,416,3,3,3,3,2,3,3,5,5,5,5,2,5,2,1,0.0,satisfied +8724,49487,Female,disloyal Customer,20,Business travel,Eco,262,3,2,3,4,4,3,2,4,3,2,3,2,3,4,15,38.0,neutral or dissatisfied +8725,111580,Female,Loyal Customer,70,Personal Travel,Eco,359,4,4,4,4,2,5,4,1,1,4,1,3,1,4,1,2.0,satisfied +8726,63264,Male,Loyal Customer,32,Business travel,Business,337,2,2,2,2,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +8727,108536,Male,Loyal Customer,44,Personal Travel,Eco Plus,649,3,1,3,4,5,3,5,5,1,2,4,1,3,5,0,0.0,neutral or dissatisfied +8728,86588,Female,Loyal Customer,35,Personal Travel,Eco,1269,2,5,2,3,2,2,2,2,5,5,3,4,4,2,31,7.0,neutral or dissatisfied +8729,104461,Male,Loyal Customer,52,Business travel,Eco,1123,2,2,2,2,2,2,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +8730,126498,Female,Loyal Customer,57,Personal Travel,Eco,1849,3,3,3,4,3,1,3,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +8731,104237,Female,disloyal Customer,38,Business travel,Business,1276,1,1,1,4,5,1,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +8732,58292,Male,Loyal Customer,65,Personal Travel,Eco,594,2,3,2,1,4,2,4,4,2,5,4,2,4,4,6,0.0,neutral or dissatisfied +8733,90989,Female,disloyal Customer,20,Business travel,Eco,404,2,2,2,3,3,2,3,3,1,2,4,4,3,3,14,21.0,neutral or dissatisfied +8734,16631,Female,Loyal Customer,45,Business travel,Business,3515,4,1,1,1,3,3,4,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +8735,2918,Female,disloyal Customer,25,Business travel,Business,806,4,5,4,2,4,4,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +8736,91430,Female,Loyal Customer,33,Personal Travel,Eco,549,5,5,5,3,4,5,4,4,4,5,4,5,5,4,0,0.0,satisfied +8737,33140,Female,Loyal Customer,21,Personal Travel,Eco,101,3,5,3,4,5,3,4,5,4,4,5,4,4,5,0,2.0,neutral or dissatisfied +8738,83316,Female,disloyal Customer,49,Business travel,Eco,1469,4,4,4,4,5,4,5,5,3,1,4,3,3,5,0,46.0,neutral or dissatisfied +8739,76230,Female,disloyal Customer,57,Business travel,Business,1175,5,5,5,1,1,5,3,1,4,3,4,5,4,1,0,0.0,satisfied +8740,7671,Female,Loyal Customer,16,Business travel,Business,3297,2,4,2,2,5,5,5,5,3,4,4,5,5,5,0,5.0,satisfied +8741,89722,Male,Loyal Customer,17,Personal Travel,Eco,950,4,2,4,3,1,4,1,1,3,5,3,2,3,1,107,91.0,neutral or dissatisfied +8742,15812,Male,Loyal Customer,62,Personal Travel,Eco,195,3,5,0,3,0,3,2,4,5,1,2,2,3,2,125,141.0,neutral or dissatisfied +8743,81814,Male,Loyal Customer,53,Business travel,Business,1501,5,5,5,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +8744,96943,Female,Loyal Customer,41,Business travel,Business,775,2,2,2,2,3,4,5,3,3,3,3,5,3,3,3,10.0,satisfied +8745,67050,Female,disloyal Customer,30,Business travel,Eco,985,2,2,2,3,2,2,2,2,1,3,3,3,3,2,65,59.0,neutral or dissatisfied +8746,117829,Female,Loyal Customer,23,Personal Travel,Eco,328,1,1,1,3,5,1,5,5,4,5,3,1,3,5,3,0.0,neutral or dissatisfied +8747,60403,Female,Loyal Customer,33,Personal Travel,Eco,1476,3,4,3,2,5,3,1,5,1,3,4,5,4,5,0,8.0,neutral or dissatisfied +8748,97145,Female,disloyal Customer,29,Business travel,Eco,715,3,3,3,4,1,3,1,1,1,1,4,3,4,1,12,12.0,neutral or dissatisfied +8749,13406,Female,Loyal Customer,57,Business travel,Business,2248,3,3,3,3,3,3,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +8750,69752,Male,Loyal Customer,44,Personal Travel,Eco,1085,1,4,1,3,3,1,3,3,5,2,5,3,4,3,4,24.0,neutral or dissatisfied +8751,86079,Female,disloyal Customer,42,Business travel,Business,306,3,3,3,3,1,3,1,1,4,3,5,3,5,1,3,0.0,neutral or dissatisfied +8752,73439,Male,Loyal Customer,36,Personal Travel,Eco,1144,1,4,1,3,5,1,3,5,5,2,4,1,5,5,0,0.0,neutral or dissatisfied +8753,115352,Male,Loyal Customer,47,Business travel,Business,3382,2,2,2,2,3,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +8754,32111,Female,Loyal Customer,41,Business travel,Business,3170,4,4,4,4,3,3,4,4,4,4,4,3,4,2,0,1.0,satisfied +8755,125493,Male,Loyal Customer,29,Personal Travel,Eco Plus,2979,2,2,2,4,2,5,5,3,2,3,4,5,4,5,0,0.0,neutral or dissatisfied +8756,96789,Male,Loyal Customer,31,Business travel,Business,781,1,1,1,1,5,5,5,5,4,2,5,3,4,5,13,8.0,satisfied +8757,60573,Male,Loyal Customer,50,Business travel,Business,1558,5,5,4,5,2,5,5,4,4,4,4,3,4,5,1,0.0,satisfied +8758,45739,Male,Loyal Customer,56,Business travel,Business,1523,1,1,5,1,3,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +8759,7361,Female,Loyal Customer,57,Business travel,Business,2051,1,1,1,1,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +8760,34591,Male,Loyal Customer,43,Business travel,Eco,1617,4,5,5,5,4,4,4,4,4,2,5,3,5,4,0,0.0,satisfied +8761,14871,Male,disloyal Customer,28,Business travel,Eco,315,5,0,5,2,1,5,1,1,3,1,3,4,3,1,3,0.0,satisfied +8762,100960,Female,Loyal Customer,47,Personal Travel,Eco,1142,3,5,4,1,5,5,3,5,5,4,5,4,5,5,0,5.0,neutral or dissatisfied +8763,96052,Female,Loyal Customer,30,Business travel,Business,3038,3,4,1,4,3,3,3,3,3,2,3,1,4,3,0,0.0,neutral or dissatisfied +8764,122069,Female,Loyal Customer,57,Business travel,Business,130,1,1,4,1,2,1,2,5,5,5,5,4,5,2,0,22.0,satisfied +8765,81651,Male,disloyal Customer,24,Business travel,Eco,907,4,4,4,4,1,4,1,1,3,5,5,4,4,1,9,9.0,satisfied +8766,71505,Female,Loyal Customer,41,Business travel,Business,3220,5,5,5,5,2,5,4,2,2,2,2,4,2,3,86,89.0,satisfied +8767,122167,Male,Loyal Customer,46,Business travel,Business,541,4,4,4,4,4,4,5,4,4,4,4,4,4,4,47,70.0,satisfied +8768,95935,Female,Loyal Customer,21,Personal Travel,Eco,1504,3,4,3,2,2,3,2,2,5,3,5,5,4,2,0,0.0,neutral or dissatisfied +8769,50302,Female,Loyal Customer,64,Business travel,Business,89,1,5,5,5,2,3,2,3,3,3,1,4,3,1,0,0.0,neutral or dissatisfied +8770,103984,Female,Loyal Customer,42,Business travel,Business,1592,3,3,3,3,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +8771,28399,Female,Loyal Customer,49,Business travel,Business,1489,3,5,1,5,5,4,4,3,3,3,3,4,3,3,0,8.0,neutral or dissatisfied +8772,66812,Female,disloyal Customer,30,Business travel,Eco,731,1,1,1,1,1,1,1,1,1,5,1,1,2,1,5,0.0,neutral or dissatisfied +8773,3797,Female,Loyal Customer,16,Personal Travel,Eco Plus,599,4,2,4,3,2,4,1,2,1,2,3,3,4,2,0,12.0,neutral or dissatisfied +8774,101106,Female,disloyal Customer,25,Business travel,Business,795,1,0,1,2,4,1,4,4,5,4,5,5,4,4,14,10.0,neutral or dissatisfied +8775,38977,Male,Loyal Customer,27,Business travel,Eco,313,4,1,1,1,4,4,4,4,3,4,4,4,1,4,2,0.0,satisfied +8776,84540,Female,Loyal Customer,45,Business travel,Business,2392,5,5,5,5,1,3,3,4,4,4,4,4,4,4,12,0.0,satisfied +8777,42954,Male,Loyal Customer,59,Business travel,Eco,236,4,2,2,2,5,4,5,5,5,2,4,1,2,5,0,0.0,satisfied +8778,110113,Female,Loyal Customer,43,Business travel,Business,1990,2,2,5,2,5,4,5,2,2,2,2,3,2,3,30,30.0,satisfied +8779,1814,Female,Loyal Customer,71,Business travel,Eco,500,3,4,4,4,4,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +8780,86276,Female,Loyal Customer,28,Personal Travel,Eco,164,2,5,2,1,4,2,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +8781,124663,Male,Loyal Customer,49,Business travel,Business,399,2,2,2,2,4,5,5,5,5,4,5,5,5,5,0,9.0,satisfied +8782,71370,Male,disloyal Customer,42,Business travel,Business,258,5,5,5,1,3,5,3,3,4,4,5,4,4,3,7,0.0,satisfied +8783,81878,Male,Loyal Customer,41,Personal Travel,Business,680,3,5,3,2,3,5,5,5,5,3,5,5,5,4,7,17.0,neutral or dissatisfied +8784,120519,Female,Loyal Customer,38,Business travel,Business,3687,4,4,4,4,5,5,5,5,5,5,4,4,5,5,24,16.0,satisfied +8785,99129,Female,Loyal Customer,35,Personal Travel,Eco,453,2,4,2,5,2,5,5,5,2,4,5,5,4,5,139,138.0,neutral or dissatisfied +8786,122807,Male,Loyal Customer,13,Personal Travel,Eco,599,3,3,3,4,2,3,2,2,1,5,4,3,1,2,8,0.0,neutral or dissatisfied +8787,85491,Male,Loyal Customer,46,Personal Travel,Eco,214,3,3,0,4,2,0,2,2,2,1,4,1,3,2,0,0.0,neutral or dissatisfied +8788,1008,Male,Loyal Customer,33,Business travel,Eco,140,0,0,0,1,4,3,4,4,3,2,5,4,1,4,0,14.0,satisfied +8789,107345,Male,disloyal Customer,39,Business travel,Business,632,4,4,4,3,2,4,2,2,3,5,4,3,4,2,23,10.0,satisfied +8790,65279,Male,Loyal Customer,16,Personal Travel,Eco Plus,551,4,3,4,2,1,4,1,1,4,5,4,2,5,1,0,0.0,neutral or dissatisfied +8791,1033,Male,disloyal Customer,18,Business travel,Eco,309,3,3,3,2,5,3,5,5,1,1,5,3,1,5,1,0.0,neutral or dissatisfied +8792,91765,Male,disloyal Customer,28,Business travel,Business,626,3,3,3,4,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +8793,100492,Female,disloyal Customer,24,Business travel,Eco,580,3,1,2,3,4,2,4,4,1,5,2,4,3,4,5,3.0,neutral or dissatisfied +8794,71695,Male,Loyal Customer,38,Personal Travel,Eco,1005,1,5,1,4,1,1,1,1,5,5,4,3,5,1,0,0.0,neutral or dissatisfied +8795,73495,Male,Loyal Customer,56,Personal Travel,Eco,1005,2,4,2,2,5,2,5,5,3,4,5,5,5,5,10,7.0,neutral or dissatisfied +8796,18811,Female,Loyal Customer,15,Business travel,Business,3791,3,3,2,3,5,5,5,5,1,5,3,5,4,5,69,66.0,satisfied +8797,41157,Male,Loyal Customer,46,Personal Travel,Eco,667,2,1,2,3,1,2,4,1,4,5,4,1,3,1,5,1.0,neutral or dissatisfied +8798,38044,Male,Loyal Customer,58,Business travel,Business,1220,5,5,5,5,1,2,3,4,4,4,4,5,4,2,0,0.0,satisfied +8799,8305,Female,disloyal Customer,37,Business travel,Business,125,5,5,5,2,5,5,2,5,4,5,4,3,5,5,0,0.0,satisfied +8800,101201,Female,Loyal Customer,65,Personal Travel,Eco,1069,2,5,2,1,2,5,4,3,3,2,3,3,3,3,109,104.0,neutral or dissatisfied +8801,57717,Male,Loyal Customer,55,Business travel,Business,1754,2,4,4,4,4,3,3,2,2,2,2,1,2,1,13,12.0,neutral or dissatisfied +8802,55025,Female,Loyal Customer,54,Business travel,Business,1379,3,1,1,1,4,4,4,3,3,3,3,1,3,3,29,25.0,neutral or dissatisfied +8803,102431,Male,Loyal Customer,57,Personal Travel,Eco,223,3,5,0,3,2,0,2,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +8804,112382,Female,Loyal Customer,30,Business travel,Business,3364,3,3,3,3,5,5,5,5,5,2,4,5,5,5,42,28.0,satisfied +8805,129087,Male,Loyal Customer,36,Business travel,Business,2342,3,3,3,3,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +8806,104077,Female,Loyal Customer,49,Personal Travel,Eco,359,3,4,3,2,3,5,4,3,3,3,1,4,3,3,5,2.0,neutral or dissatisfied +8807,75269,Female,Loyal Customer,47,Personal Travel,Eco,1652,2,5,2,1,3,3,4,3,3,2,3,3,3,5,5,0.0,neutral or dissatisfied +8808,62211,Female,Loyal Customer,15,Personal Travel,Eco,2565,3,4,3,2,2,3,4,2,2,2,3,2,5,2,2,0.0,neutral or dissatisfied +8809,72343,Male,disloyal Customer,29,Business travel,Business,1121,2,2,2,4,5,2,1,5,1,2,4,4,4,5,15,10.0,neutral or dissatisfied +8810,2443,Male,Loyal Customer,58,Business travel,Business,2108,5,5,5,5,2,4,5,5,5,5,5,3,5,3,5,1.0,satisfied +8811,54398,Female,Loyal Customer,49,Business travel,Eco,305,2,3,2,3,3,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +8812,74354,Female,Loyal Customer,51,Business travel,Business,1235,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +8813,116924,Male,Loyal Customer,39,Business travel,Business,2780,3,3,3,3,5,4,5,4,4,4,4,5,4,4,2,0.0,satisfied +8814,69170,Female,Loyal Customer,36,Business travel,Business,187,0,5,0,4,3,5,5,3,3,5,5,4,3,3,0,12.0,satisfied +8815,125010,Male,Loyal Customer,70,Personal Travel,Eco,184,4,5,4,5,1,4,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +8816,28453,Female,disloyal Customer,54,Business travel,Eco Plus,2537,3,3,3,4,3,3,3,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +8817,56724,Male,Loyal Customer,51,Personal Travel,Eco,997,2,3,2,4,1,2,1,1,4,4,4,3,4,1,63,43.0,neutral or dissatisfied +8818,42815,Female,Loyal Customer,27,Personal Travel,Eco,896,2,5,1,5,1,1,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +8819,120398,Male,Loyal Customer,36,Business travel,Business,3860,2,5,5,5,3,4,4,2,2,2,2,1,2,2,0,39.0,neutral or dissatisfied +8820,103223,Female,Loyal Customer,19,Business travel,Business,351,2,4,4,4,2,2,2,2,3,1,3,1,4,2,39,35.0,neutral or dissatisfied +8821,64737,Male,Loyal Customer,45,Business travel,Business,2828,0,5,0,1,5,4,5,4,4,2,2,5,4,4,0,0.0,satisfied +8822,77127,Female,Loyal Customer,47,Business travel,Business,1481,4,4,4,4,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +8823,40818,Male,Loyal Customer,31,Business travel,Business,2097,2,3,3,3,2,2,2,2,4,4,3,4,3,2,0,0.0,neutral or dissatisfied +8824,12446,Female,Loyal Customer,54,Personal Travel,Eco,201,2,4,2,1,1,1,3,3,3,2,3,2,3,1,4,13.0,neutral or dissatisfied +8825,68150,Male,Loyal Customer,48,Business travel,Business,603,3,3,3,3,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +8826,102241,Female,Loyal Customer,34,Business travel,Business,1591,1,1,1,1,2,5,4,4,4,4,4,5,4,3,29,25.0,satisfied +8827,67914,Male,Loyal Customer,54,Personal Travel,Eco,1205,2,4,2,3,2,2,2,2,2,5,4,3,4,2,18,20.0,neutral or dissatisfied +8828,15836,Male,Loyal Customer,16,Personal Travel,Eco,1148,1,5,1,1,5,1,5,5,3,4,5,4,5,5,0,0.0,neutral or dissatisfied +8829,66194,Male,disloyal Customer,22,Business travel,Eco,550,4,0,3,4,2,3,2,2,4,5,5,5,5,2,0,0.0,satisfied +8830,70337,Male,Loyal Customer,32,Business travel,Eco,986,2,1,1,1,2,2,2,2,3,2,4,4,4,2,99,111.0,neutral or dissatisfied +8831,37959,Male,Loyal Customer,25,Business travel,Business,1211,3,3,3,3,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +8832,127644,Female,Loyal Customer,30,Personal Travel,Eco,1773,2,5,3,3,5,3,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +8833,27475,Female,disloyal Customer,8,Business travel,Eco,954,1,1,1,3,4,1,4,4,4,3,4,2,3,4,3,12.0,neutral or dissatisfied +8834,104747,Male,disloyal Customer,37,Business travel,Eco,846,3,3,3,1,2,3,2,2,4,5,4,4,2,2,46,91.0,neutral or dissatisfied +8835,116603,Male,Loyal Customer,41,Business travel,Business,2112,4,4,4,4,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +8836,120573,Female,Loyal Customer,42,Business travel,Business,2176,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +8837,23197,Male,Loyal Customer,45,Business travel,Eco Plus,223,3,3,3,3,3,3,3,3,1,2,2,5,5,3,0,0.0,satisfied +8838,58715,Male,disloyal Customer,23,Business travel,Eco,606,1,4,1,4,2,1,2,2,4,5,4,1,4,2,21,13.0,neutral or dissatisfied +8839,98400,Male,Loyal Customer,27,Business travel,Business,3641,2,1,1,1,2,2,2,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +8840,45872,Male,Loyal Customer,41,Business travel,Eco,641,2,3,3,3,2,2,2,2,1,5,5,4,5,2,47,39.0,satisfied +8841,67419,Male,Loyal Customer,29,Business travel,Business,2013,2,2,2,2,2,2,2,2,1,4,3,3,3,2,0,0.0,neutral or dissatisfied +8842,100164,Male,disloyal Customer,18,Business travel,Eco,468,3,3,3,3,4,3,4,4,1,4,3,4,3,4,44,96.0,neutral or dissatisfied +8843,49017,Female,Loyal Customer,56,Business travel,Business,2640,0,0,0,3,2,4,1,1,1,1,1,3,1,4,10,1.0,satisfied +8844,51016,Female,Loyal Customer,69,Personal Travel,Eco,190,3,4,3,1,3,5,5,4,4,3,2,3,4,5,0,0.0,neutral or dissatisfied +8845,78026,Male,Loyal Customer,37,Business travel,Eco,332,3,5,5,5,3,5,3,3,1,4,5,2,2,3,0,0.0,satisfied +8846,67366,Male,Loyal Customer,49,Business travel,Business,641,1,1,1,1,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +8847,104084,Male,Loyal Customer,53,Personal Travel,Eco,666,3,3,3,4,4,3,4,4,1,2,3,1,3,4,2,0.0,neutral or dissatisfied +8848,23264,Female,Loyal Customer,34,Business travel,Business,2205,2,2,2,2,3,1,2,4,4,4,4,4,4,3,1,0.0,satisfied +8849,9601,Male,Loyal Customer,40,Personal Travel,Eco,296,5,5,5,4,3,5,3,3,3,2,5,4,4,3,0,0.0,satisfied +8850,1988,Male,Loyal Customer,13,Personal Travel,Eco,383,3,2,3,3,4,3,4,4,1,4,2,1,2,4,0,0.0,neutral or dissatisfied +8851,34738,Male,disloyal Customer,48,Business travel,Eco,301,2,1,3,3,2,3,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +8852,26805,Female,disloyal Customer,21,Business travel,Eco,796,0,0,0,1,4,0,4,4,3,5,2,2,1,4,0,0.0,satisfied +8853,109883,Male,Loyal Customer,11,Business travel,Business,1943,4,4,4,4,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +8854,62665,Female,disloyal Customer,48,Business travel,Business,1846,1,1,1,3,5,1,5,5,4,3,3,3,4,5,48,46.0,neutral or dissatisfied +8855,70945,Female,Loyal Customer,40,Personal Travel,Eco,612,3,5,3,2,3,3,2,3,5,2,4,3,5,3,0,2.0,neutral or dissatisfied +8856,74474,Female,disloyal Customer,25,Business travel,Eco,1242,2,2,2,3,4,2,4,4,2,3,4,1,4,4,0,0.0,neutral or dissatisfied +8857,79387,Male,Loyal Customer,56,Business travel,Business,3705,1,1,1,1,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +8858,35245,Female,Loyal Customer,45,Business travel,Eco,944,2,3,3,3,1,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +8859,77925,Male,Loyal Customer,55,Personal Travel,Business,214,4,4,4,3,4,4,4,1,1,4,1,3,1,3,0,14.0,neutral or dissatisfied +8860,55274,Male,disloyal Customer,22,Business travel,Business,1839,5,5,5,1,4,5,4,4,5,5,4,4,5,4,20,12.0,satisfied +8861,7113,Female,Loyal Customer,58,Personal Travel,Eco,273,3,5,3,3,1,4,2,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +8862,556,Male,Loyal Customer,39,Business travel,Business,2398,5,5,5,5,4,5,5,4,4,4,4,5,4,4,0,4.0,satisfied +8863,21470,Male,disloyal Customer,77,Business travel,Eco,399,5,0,5,4,1,5,1,1,4,1,3,1,5,1,0,0.0,satisfied +8864,125611,Female,Loyal Customer,59,Business travel,Business,2001,4,4,5,4,2,5,5,5,5,5,5,4,5,4,6,16.0,satisfied +8865,107580,Male,Loyal Customer,37,Business travel,Business,1521,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,67.0,satisfied +8866,40800,Female,Loyal Customer,43,Business travel,Business,626,5,5,4,5,2,4,5,5,5,5,5,1,5,3,66,43.0,satisfied +8867,122698,Female,Loyal Customer,41,Personal Travel,Eco,361,3,4,3,4,1,3,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +8868,9257,Male,Loyal Customer,12,Personal Travel,Eco,157,0,5,0,3,1,0,1,1,5,3,4,5,5,1,0,0.0,satisfied +8869,32799,Female,disloyal Customer,23,Business travel,Business,102,2,1,2,3,2,2,2,2,3,3,4,4,3,2,0,9.0,neutral or dissatisfied +8870,115093,Female,Loyal Customer,43,Business travel,Business,337,2,2,2,2,3,4,5,4,4,4,4,4,4,3,0,8.0,satisfied +8871,122430,Female,disloyal Customer,24,Business travel,Eco,416,5,0,5,1,5,5,5,5,2,4,5,2,2,5,0,0.0,satisfied +8872,112488,Female,Loyal Customer,53,Personal Travel,Eco,909,5,3,5,4,1,4,3,1,1,5,1,4,1,3,1,0.0,satisfied +8873,107900,Male,Loyal Customer,41,Business travel,Business,3872,1,1,1,1,2,5,5,3,3,4,3,4,3,5,9,0.0,satisfied +8874,124315,Female,Loyal Customer,41,Personal Travel,Eco,601,3,1,3,3,3,3,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +8875,116080,Female,Loyal Customer,33,Personal Travel,Eco,296,1,4,1,3,5,1,5,5,3,4,4,3,5,5,20,19.0,neutral or dissatisfied +8876,111145,Male,Loyal Customer,45,Business travel,Eco,650,2,4,3,4,2,2,2,2,2,4,5,3,2,2,0,0.0,satisfied +8877,9609,Female,Loyal Customer,30,Personal Travel,Eco,229,1,1,1,3,2,1,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +8878,55967,Male,Loyal Customer,42,Business travel,Eco,1620,3,4,4,4,2,3,2,2,1,2,3,4,2,2,0,0.0,neutral or dissatisfied +8879,110838,Female,Loyal Customer,33,Personal Travel,Eco Plus,1166,4,5,4,3,4,4,4,4,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +8880,29689,Male,disloyal Customer,24,Business travel,Eco,717,3,3,3,4,3,3,2,3,1,2,3,1,2,3,0,0.0,neutral or dissatisfied +8881,91157,Male,Loyal Customer,11,Personal Travel,Eco,404,2,5,2,5,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +8882,9088,Female,Loyal Customer,30,Personal Travel,Eco,160,3,3,3,4,5,3,1,5,2,5,4,1,4,5,34,22.0,neutral or dissatisfied +8883,7241,Male,Loyal Customer,37,Business travel,Business,3480,3,2,2,2,1,3,4,2,2,2,3,1,2,1,34,33.0,neutral or dissatisfied +8884,73258,Female,Loyal Customer,7,Personal Travel,Eco,675,2,4,2,3,5,2,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +8885,90803,Female,Loyal Customer,29,Business travel,Business,2100,2,5,5,5,2,2,2,2,2,5,3,1,3,2,0,5.0,neutral or dissatisfied +8886,120995,Female,Loyal Customer,37,Business travel,Business,1013,3,3,3,3,1,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +8887,51006,Male,Loyal Customer,49,Personal Travel,Eco,190,4,4,0,4,5,0,5,5,2,2,3,4,4,5,0,0.0,neutral or dissatisfied +8888,96961,Female,disloyal Customer,28,Business travel,Business,775,1,1,1,3,3,1,3,3,3,4,4,3,4,3,59,64.0,neutral or dissatisfied +8889,36298,Female,Loyal Customer,36,Business travel,Business,187,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,23.0,satisfied +8890,62197,Male,Loyal Customer,38,Personal Travel,Eco,2454,4,1,4,4,4,4,4,4,1,1,4,4,4,4,0,0.0,satisfied +8891,90340,Male,Loyal Customer,54,Business travel,Business,3850,5,3,5,5,4,4,4,4,3,4,4,4,5,4,333,325.0,satisfied +8892,80897,Male,Loyal Customer,45,Personal Travel,Eco Plus,692,2,1,2,4,1,2,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +8893,53992,Male,Loyal Customer,41,Business travel,Eco,1825,4,3,3,3,4,4,4,4,1,3,4,5,1,4,1,0.0,satisfied +8894,47819,Female,disloyal Customer,38,Business travel,Eco,817,3,3,3,4,4,3,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +8895,44209,Female,Loyal Customer,54,Personal Travel,Eco Plus,157,3,4,3,4,3,4,5,2,2,3,2,3,2,4,42,40.0,neutral or dissatisfied +8896,105346,Male,Loyal Customer,63,Personal Travel,Eco,409,0,5,0,1,4,0,4,4,4,4,4,4,4,4,0,0.0,satisfied +8897,20558,Male,Loyal Customer,37,Business travel,Eco,606,3,5,5,5,3,3,3,3,3,1,2,3,3,3,0,0.0,neutral or dissatisfied +8898,9908,Male,disloyal Customer,37,Business travel,Business,515,2,2,2,2,5,2,4,5,5,2,5,5,5,5,18,43.0,neutral or dissatisfied +8899,54341,Male,Loyal Customer,62,Personal Travel,Eco,1597,4,5,4,3,4,4,2,4,4,2,4,3,4,4,2,0.0,neutral or dissatisfied +8900,55547,Male,Loyal Customer,38,Business travel,Business,2239,1,1,1,1,4,2,1,4,4,4,3,5,4,4,0,5.0,satisfied +8901,46330,Male,Loyal Customer,65,Personal Travel,Eco,420,4,3,4,4,4,4,3,4,2,1,3,1,4,4,0,0.0,neutral or dissatisfied +8902,98060,Male,Loyal Customer,52,Business travel,Business,1449,1,1,1,1,3,5,5,2,2,3,2,5,2,4,8,0.0,satisfied +8903,39005,Female,Loyal Customer,43,Business travel,Business,406,1,0,0,3,1,3,4,3,3,0,3,2,3,1,0,2.0,neutral or dissatisfied +8904,129,Male,Loyal Customer,67,Personal Travel,Eco,562,4,2,4,4,2,4,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +8905,111012,Male,Loyal Customer,60,Business travel,Business,197,5,5,5,5,4,5,4,4,4,4,5,5,4,4,26,9.0,satisfied +8906,72806,Male,Loyal Customer,51,Personal Travel,Eco,1045,1,4,1,2,1,1,1,1,2,1,5,4,3,1,0,0.0,neutral or dissatisfied +8907,76669,Female,Loyal Customer,63,Personal Travel,Eco,516,2,5,2,3,2,5,3,5,5,2,5,4,5,1,0,0.0,neutral or dissatisfied +8908,25378,Male,Loyal Customer,43,Business travel,Business,2799,3,1,2,1,4,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +8909,12959,Male,Loyal Customer,41,Business travel,Eco Plus,674,4,2,2,2,4,4,4,4,1,3,4,2,5,4,12,5.0,satisfied +8910,4445,Male,Loyal Customer,19,Personal Travel,Eco,762,3,4,3,3,5,3,5,5,5,3,5,3,4,5,17,12.0,neutral or dissatisfied +8911,77696,Female,Loyal Customer,50,Business travel,Business,3359,4,4,3,4,4,4,4,5,5,5,5,3,5,3,12,8.0,satisfied +8912,95749,Male,Loyal Customer,40,Business travel,Eco,237,4,1,1,1,4,4,4,4,1,5,2,4,1,4,0,0.0,neutral or dissatisfied +8913,24905,Female,Loyal Customer,28,Business travel,Eco,762,0,0,0,4,1,0,1,1,3,4,4,5,1,1,0,0.0,satisfied +8914,11046,Male,Loyal Customer,7,Personal Travel,Eco,312,3,4,3,2,5,3,5,5,3,5,4,3,5,5,96,91.0,neutral or dissatisfied +8915,24548,Male,disloyal Customer,18,Business travel,Eco,874,2,2,2,3,1,2,1,1,5,2,2,4,4,1,27,32.0,neutral or dissatisfied +8916,56949,Female,Loyal Customer,44,Business travel,Business,2565,2,2,3,2,5,5,5,3,4,4,5,5,4,5,0,5.0,satisfied +8917,104677,Male,Loyal Customer,54,Business travel,Business,641,5,5,5,5,5,5,5,3,5,4,5,5,4,5,141,190.0,satisfied +8918,71243,Male,disloyal Customer,30,Business travel,Business,733,2,2,2,4,3,2,3,3,4,3,4,5,4,3,81,61.0,neutral or dissatisfied +8919,8545,Male,disloyal Customer,22,Business travel,Business,109,4,0,4,2,5,4,5,5,4,5,5,4,5,5,3,7.0,satisfied +8920,124225,Female,Loyal Customer,57,Business travel,Business,1916,3,3,3,3,4,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +8921,36152,Female,Loyal Customer,48,Personal Travel,Eco,818,3,3,3,2,2,5,4,1,1,3,1,1,1,4,0,16.0,neutral or dissatisfied +8922,104727,Male,disloyal Customer,25,Business travel,Eco,1407,3,3,3,3,4,3,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +8923,109176,Female,Loyal Customer,67,Business travel,Eco,793,1,2,2,2,2,3,4,2,2,1,2,4,2,1,58,47.0,neutral or dissatisfied +8924,76452,Male,disloyal Customer,39,Business travel,Business,481,1,1,1,4,3,1,3,3,4,4,4,3,5,3,7,16.0,neutral or dissatisfied +8925,99287,Female,Loyal Customer,54,Personal Travel,Eco,833,3,5,4,1,5,4,4,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +8926,90530,Male,disloyal Customer,25,Business travel,Business,594,4,0,3,2,4,3,5,4,3,5,4,3,4,4,0,0.0,satisfied +8927,124354,Female,disloyal Customer,21,Business travel,Eco,808,1,2,2,4,2,2,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +8928,33316,Female,Loyal Customer,60,Personal Travel,Business,2349,2,1,2,3,3,4,4,2,2,2,3,3,2,3,0,0.0,neutral or dissatisfied +8929,112830,Female,Loyal Customer,29,Business travel,Business,3121,1,5,5,5,1,1,1,1,3,5,4,2,3,1,0,0.0,neutral or dissatisfied +8930,23487,Male,disloyal Customer,22,Business travel,Eco,516,2,0,2,1,1,2,1,1,5,5,1,2,1,1,37,31.0,neutral or dissatisfied +8931,61032,Male,Loyal Customer,49,Business travel,Business,1546,2,2,2,2,5,4,4,5,2,5,5,4,5,4,266,281.0,satisfied +8932,37137,Male,Loyal Customer,50,Business travel,Eco,1189,2,2,2,2,2,2,2,1,3,4,3,2,3,2,186,201.0,neutral or dissatisfied +8933,21247,Male,Loyal Customer,22,Business travel,Eco Plus,317,3,3,3,3,3,3,1,3,1,3,3,3,2,3,70,71.0,neutral or dissatisfied +8934,94312,Male,Loyal Customer,56,Business travel,Business,248,2,2,2,2,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +8935,42252,Female,Loyal Customer,52,Business travel,Business,329,1,3,3,3,2,3,3,1,1,2,1,1,1,1,2,0.0,neutral or dissatisfied +8936,23828,Female,Loyal Customer,60,Personal Travel,Eco Plus,438,2,4,2,3,2,4,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +8937,103936,Male,Loyal Customer,57,Business travel,Business,2184,1,1,1,1,3,4,4,5,5,5,5,4,5,4,41,41.0,satisfied +8938,56128,Female,Loyal Customer,51,Business travel,Business,1400,5,5,4,5,4,5,5,4,4,5,4,3,4,5,18,35.0,satisfied +8939,75824,Male,disloyal Customer,46,Business travel,Business,1440,3,4,4,2,4,3,4,4,4,3,5,5,4,4,41,36.0,neutral or dissatisfied +8940,59673,Female,Loyal Customer,70,Personal Travel,Eco,787,3,3,3,5,2,1,3,4,4,3,4,4,4,4,2,0.0,neutral or dissatisfied +8941,73531,Female,Loyal Customer,31,Business travel,Business,594,5,5,5,5,3,3,3,3,4,5,5,4,5,3,1,0.0,satisfied +8942,31665,Female,Loyal Customer,21,Business travel,Business,3135,3,1,1,1,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +8943,112114,Female,Loyal Customer,55,Personal Travel,Eco,1024,3,4,3,2,2,4,4,2,2,3,2,4,2,5,13,4.0,neutral or dissatisfied +8944,126655,Female,Loyal Customer,57,Personal Travel,Eco,602,1,5,1,1,1,1,2,2,2,1,2,1,2,3,17,22.0,neutral or dissatisfied +8945,92035,Female,Loyal Customer,28,Business travel,Business,1535,3,3,5,3,4,4,4,4,5,5,4,5,5,4,0,0.0,satisfied +8946,123397,Female,Loyal Customer,57,Business travel,Business,1337,2,2,2,2,5,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +8947,41394,Female,Loyal Customer,65,Business travel,Business,2592,5,5,5,5,5,3,5,4,4,4,4,4,4,2,0,0.0,satisfied +8948,81053,Male,Loyal Customer,13,Personal Travel,Eco,1175,1,3,0,4,4,0,4,4,4,2,2,4,3,4,0,0.0,neutral or dissatisfied +8949,53372,Male,Loyal Customer,39,Business travel,Business,1452,3,1,1,1,2,3,4,3,3,3,3,2,3,4,13,0.0,neutral or dissatisfied +8950,116526,Male,Loyal Customer,60,Personal Travel,Eco,358,3,4,5,2,1,5,1,1,5,4,4,5,4,1,57,43.0,neutral or dissatisfied +8951,60975,Female,Loyal Customer,23,Personal Travel,Eco,888,2,4,2,5,3,2,3,3,3,3,4,4,5,3,59,56.0,neutral or dissatisfied +8952,50234,Male,Loyal Customer,62,Business travel,Business,363,4,5,5,5,3,4,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +8953,37116,Male,Loyal Customer,47,Business travel,Eco,1046,5,2,2,2,5,5,5,5,4,2,5,5,4,5,36,31.0,satisfied +8954,63351,Male,Loyal Customer,25,Personal Travel,Eco,337,5,5,5,3,3,5,3,3,3,4,5,4,4,3,0,0.0,satisfied +8955,123037,Female,disloyal Customer,43,Business travel,Business,650,4,4,4,1,5,4,5,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +8956,34837,Female,disloyal Customer,16,Business travel,Eco Plus,264,3,5,2,1,1,2,1,1,2,2,5,2,4,1,0,0.0,neutral or dissatisfied +8957,107997,Female,Loyal Customer,37,Business travel,Business,3985,0,0,0,3,5,2,4,4,4,4,4,1,4,3,0,0.0,satisfied +8958,24660,Female,disloyal Customer,21,Business travel,Eco,873,2,2,2,3,3,2,1,3,3,5,2,1,3,3,7,0.0,neutral or dissatisfied +8959,31919,Female,Loyal Customer,51,Business travel,Business,102,0,4,0,1,5,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +8960,36988,Male,Loyal Customer,33,Business travel,Business,2330,3,3,5,3,3,2,3,3,1,4,4,1,4,3,66,55.0,neutral or dissatisfied +8961,125710,Male,Loyal Customer,57,Personal Travel,Eco,814,4,5,4,1,4,4,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +8962,64838,Female,disloyal Customer,37,Business travel,Eco,190,2,3,2,3,1,2,1,1,1,3,4,2,3,1,77,67.0,neutral or dissatisfied +8963,58884,Male,Loyal Customer,43,Business travel,Business,888,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +8964,76722,Female,disloyal Customer,39,Business travel,Business,547,1,1,1,3,3,1,3,3,1,3,4,3,3,3,1,0.0,neutral or dissatisfied +8965,103839,Female,Loyal Customer,25,Business travel,Business,979,4,1,3,1,4,4,4,4,3,4,3,4,3,4,15,8.0,neutral or dissatisfied +8966,29260,Male,Loyal Customer,44,Business travel,Business,834,2,2,2,2,3,3,3,4,4,4,4,2,4,5,0,4.0,satisfied +8967,15763,Female,Loyal Customer,62,Business travel,Business,292,2,2,2,2,4,1,2,5,5,5,5,3,5,4,0,0.0,satisfied +8968,58526,Female,Loyal Customer,59,Personal Travel,Eco,719,3,5,3,3,4,4,5,2,2,3,2,4,2,5,0,11.0,neutral or dissatisfied +8969,51873,Male,disloyal Customer,25,Business travel,Eco,771,3,3,3,2,2,3,1,2,5,2,2,5,4,2,0,0.0,neutral or dissatisfied +8970,128104,Female,Loyal Customer,12,Personal Travel,Business,1587,3,4,3,4,1,3,1,1,3,5,3,5,5,1,3,0.0,neutral or dissatisfied +8971,73413,Male,disloyal Customer,79,Business travel,Eco,797,2,2,2,4,2,2,4,2,2,1,3,5,1,2,0,0.0,neutral or dissatisfied +8972,23506,Male,Loyal Customer,43,Business travel,Business,2116,1,1,1,1,2,4,5,5,5,5,5,4,5,1,0,0.0,satisfied +8973,91548,Male,disloyal Customer,38,Business travel,Business,280,3,3,3,3,4,3,4,4,1,2,3,2,3,4,0,17.0,neutral or dissatisfied +8974,129423,Female,Loyal Customer,46,Business travel,Business,2357,3,3,3,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +8975,29875,Female,Loyal Customer,32,Business travel,Business,2486,2,1,1,1,2,2,2,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +8976,81882,Female,Loyal Customer,15,Business travel,Business,1661,4,4,4,4,5,5,5,5,4,4,5,4,5,5,5,5.0,satisfied +8977,49937,Male,disloyal Customer,25,Business travel,Eco,110,2,3,2,3,4,2,4,4,2,2,2,1,2,4,4,29.0,neutral or dissatisfied +8978,42069,Male,Loyal Customer,26,Personal Travel,Eco,116,3,2,3,3,4,3,4,4,3,3,3,1,4,4,98,97.0,neutral or dissatisfied +8979,8418,Male,Loyal Customer,35,Business travel,Eco,862,1,4,4,4,1,1,1,1,2,3,3,3,2,1,1,0.0,neutral or dissatisfied +8980,44389,Female,disloyal Customer,38,Business travel,Eco,342,4,1,4,3,2,4,4,2,4,2,4,1,3,2,0,1.0,satisfied +8981,42290,Female,Loyal Customer,38,Business travel,Business,2050,1,1,1,1,3,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +8982,60629,Male,Loyal Customer,51,Business travel,Business,1620,4,4,4,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +8983,104997,Male,Loyal Customer,43,Personal Travel,Eco,406,2,5,2,4,4,2,2,4,2,1,2,3,4,4,0,0.0,neutral or dissatisfied +8984,5625,Female,Loyal Customer,36,Personal Travel,Eco,624,4,5,4,3,1,4,1,1,5,2,1,5,4,1,0,0.0,satisfied +8985,42711,Female,disloyal Customer,24,Business travel,Eco Plus,627,1,0,1,4,4,1,4,4,2,1,4,3,4,4,0,,neutral or dissatisfied +8986,114420,Male,Loyal Customer,59,Business travel,Business,417,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +8987,119578,Female,Loyal Customer,51,Business travel,Business,2552,4,4,4,4,2,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +8988,31154,Female,Loyal Customer,40,Business travel,Business,495,4,4,4,4,1,5,1,2,2,2,2,5,2,2,70,75.0,satisfied +8989,41832,Male,disloyal Customer,45,Business travel,Eco,462,5,0,5,4,3,0,3,3,5,1,1,3,5,3,0,36.0,satisfied +8990,80133,Male,disloyal Customer,35,Business travel,Business,2586,1,1,1,2,1,5,5,5,2,4,5,5,3,5,33,22.0,neutral or dissatisfied +8991,2160,Male,disloyal Customer,22,Business travel,Business,624,0,0,0,2,3,0,3,3,5,2,4,5,5,3,81,94.0,satisfied +8992,63994,Male,Loyal Customer,12,Business travel,Eco,612,2,3,3,3,2,2,1,2,4,3,2,2,3,2,9,3.0,neutral or dissatisfied +8993,59902,Male,Loyal Customer,19,Business travel,Business,2905,4,4,4,4,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +8994,78912,Female,disloyal Customer,52,Business travel,Business,930,2,2,2,3,2,2,2,2,5,4,4,3,5,2,0,0.0,satisfied +8995,73403,Female,disloyal Customer,27,Business travel,Business,1005,2,2,2,5,3,2,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +8996,31040,Male,Loyal Customer,33,Business travel,Business,2764,4,4,4,4,5,5,5,5,5,1,1,3,5,5,6,0.0,satisfied +8997,10291,Female,disloyal Customer,58,Business travel,Business,316,3,4,4,1,3,3,3,3,3,4,4,3,4,3,0,0.0,satisfied +8998,55582,Male,Loyal Customer,63,Personal Travel,Eco,1091,3,5,3,3,1,3,2,1,5,5,5,4,3,1,21,7.0,neutral or dissatisfied +8999,60225,Male,Loyal Customer,25,Business travel,Business,1546,3,3,3,3,3,3,3,3,1,3,4,1,4,3,0,0.0,neutral or dissatisfied +9000,107274,Male,Loyal Customer,31,Business travel,Business,3716,2,1,2,2,4,4,4,4,3,4,4,4,4,4,13,4.0,satisfied +9001,43192,Female,Loyal Customer,27,Business travel,Eco,651,4,2,3,2,4,4,4,4,4,5,4,2,3,4,0,0.0,satisfied +9002,107524,Female,Loyal Customer,54,Personal Travel,Eco,838,2,4,2,1,2,5,4,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +9003,99916,Male,Loyal Customer,31,Personal Travel,Eco,1428,2,4,2,3,1,2,1,1,4,4,5,3,5,1,0,17.0,neutral or dissatisfied +9004,32347,Female,disloyal Customer,20,Business travel,Eco,101,0,4,0,4,2,0,1,2,5,5,3,1,5,2,4,9.0,satisfied +9005,56627,Female,disloyal Customer,36,Business travel,Business,1065,3,4,4,3,2,4,1,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +9006,87152,Male,disloyal Customer,26,Business travel,Business,946,4,4,4,1,2,4,2,2,3,4,5,5,4,2,0,0.0,satisfied +9007,58110,Male,Loyal Customer,18,Personal Travel,Eco,612,1,4,1,3,1,1,1,1,4,3,5,3,4,1,15,3.0,neutral or dissatisfied +9008,4253,Male,Loyal Customer,41,Business travel,Eco Plus,1020,2,4,4,4,2,2,2,2,1,3,3,2,3,2,0,14.0,neutral or dissatisfied +9009,61935,Male,Loyal Customer,39,Business travel,Business,2584,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +9010,28551,Male,Loyal Customer,33,Personal Travel,Eco,2677,1,2,2,3,4,2,4,4,1,4,4,2,3,4,0,0.0,neutral or dissatisfied +9011,82789,Male,Loyal Customer,60,Personal Travel,Eco,231,2,4,2,4,3,2,3,3,3,4,3,2,3,3,23,11.0,neutral or dissatisfied +9012,82136,Male,disloyal Customer,24,Business travel,Eco,237,4,1,4,4,3,4,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +9013,85005,Female,disloyal Customer,27,Business travel,Eco,1364,3,3,3,3,1,3,1,1,4,1,3,3,4,1,4,0.0,neutral or dissatisfied +9014,63126,Female,Loyal Customer,46,Business travel,Business,337,3,3,2,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +9015,115622,Female,Loyal Customer,53,Business travel,Business,3693,1,1,1,1,1,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +9016,112121,Male,Loyal Customer,51,Business travel,Business,977,4,4,4,4,2,4,4,4,4,4,4,3,4,4,13,5.0,satisfied +9017,119788,Female,Loyal Customer,32,Business travel,Business,912,4,4,4,4,4,4,4,4,3,4,4,4,5,4,0,0.0,satisfied +9018,21563,Female,Loyal Customer,59,Business travel,Eco Plus,164,5,4,4,4,5,2,3,4,4,5,4,3,4,5,0,0.0,satisfied +9019,43882,Female,disloyal Customer,24,Business travel,Eco,144,4,4,4,4,4,4,4,4,1,3,4,2,4,4,0,24.0,neutral or dissatisfied +9020,98961,Female,disloyal Customer,22,Business travel,Eco,479,2,1,3,3,3,3,3,3,2,1,3,4,3,3,22,20.0,neutral or dissatisfied +9021,108482,Female,disloyal Customer,15,Business travel,Eco,570,2,0,2,4,3,2,3,3,3,2,3,2,3,3,3,12.0,neutral or dissatisfied +9022,108115,Male,Loyal Customer,46,Business travel,Business,2139,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9023,2873,Male,Loyal Customer,68,Personal Travel,Eco,475,4,5,4,3,4,4,4,4,1,3,5,4,4,4,0,20.0,neutral or dissatisfied +9024,118972,Female,Loyal Customer,65,Personal Travel,Eco,570,0,4,1,2,2,5,5,2,2,1,2,3,2,4,0,0.0,satisfied +9025,17740,Female,Loyal Customer,23,Business travel,Business,383,2,3,3,3,2,2,2,2,4,5,3,3,3,2,0,0.0,neutral or dissatisfied +9026,119613,Female,Loyal Customer,45,Business travel,Business,1979,2,2,2,2,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +9027,49283,Male,disloyal Customer,37,Business travel,Eco,337,3,0,3,3,2,3,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +9028,89436,Male,Loyal Customer,50,Personal Travel,Eco,151,2,5,2,3,5,2,5,5,3,5,4,3,5,5,1,0.0,neutral or dissatisfied +9029,7162,Male,Loyal Customer,49,Business travel,Business,2890,1,1,1,1,3,5,5,5,5,5,4,5,5,3,68,81.0,satisfied +9030,26547,Female,Loyal Customer,53,Personal Travel,Eco,990,3,5,3,3,3,5,4,5,5,3,2,3,5,5,0,0.0,neutral or dissatisfied +9031,42251,Male,disloyal Customer,48,Business travel,Eco,838,2,2,2,4,5,2,5,5,3,2,3,3,3,5,25,25.0,neutral or dissatisfied +9032,43502,Male,Loyal Customer,37,Personal Travel,Eco,679,2,5,2,2,2,4,4,4,5,5,4,4,3,4,174,161.0,neutral or dissatisfied +9033,49549,Female,Loyal Customer,43,Business travel,Business,373,1,1,1,1,5,3,3,4,4,4,4,1,4,4,0,0.0,satisfied +9034,43930,Male,Loyal Customer,54,Personal Travel,Eco,255,2,5,2,2,1,2,2,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +9035,47685,Male,Loyal Customer,46,Personal Travel,Eco,1211,2,1,1,3,1,1,1,1,1,5,4,3,4,1,46,38.0,neutral or dissatisfied +9036,122869,Male,Loyal Customer,30,Business travel,Business,2015,1,1,3,1,4,4,4,4,3,1,4,5,2,4,55,33.0,satisfied +9037,43637,Female,Loyal Customer,36,Business travel,Business,1676,4,4,4,4,3,4,5,5,5,5,5,4,5,3,0,5.0,satisfied +9038,99759,Female,Loyal Customer,64,Personal Travel,Eco,255,2,3,2,3,5,2,2,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +9039,40908,Male,Loyal Customer,44,Personal Travel,Eco,541,4,5,4,3,1,4,1,1,2,4,5,5,2,1,8,0.0,neutral or dissatisfied +9040,80786,Male,Loyal Customer,40,Business travel,Business,3070,2,2,2,2,2,5,4,4,4,4,4,3,4,5,4,0.0,satisfied +9041,45975,Female,Loyal Customer,21,Personal Travel,Business,483,1,0,1,1,1,1,1,1,3,5,4,4,4,1,0,12.0,neutral or dissatisfied +9042,57359,Female,Loyal Customer,64,Personal Travel,Eco,236,3,5,3,2,5,4,5,4,4,3,4,5,4,5,53,48.0,neutral or dissatisfied +9043,23815,Male,Loyal Customer,39,Personal Travel,Eco,374,1,5,1,3,3,1,3,3,5,5,2,4,2,3,0,0.0,neutral or dissatisfied +9044,74971,Female,Loyal Customer,43,Personal Travel,Eco,2446,2,4,1,3,2,3,3,4,4,1,4,3,4,4,0,0.0,neutral or dissatisfied +9045,34988,Female,Loyal Customer,19,Personal Travel,Eco Plus,273,3,2,3,3,1,3,1,1,1,2,2,2,3,1,0,0.0,neutral or dissatisfied +9046,25806,Male,Loyal Customer,44,Business travel,Eco Plus,762,4,3,3,3,4,4,4,4,1,5,4,2,4,4,32,53.0,satisfied +9047,89609,Female,Loyal Customer,37,Business travel,Business,1089,5,5,5,5,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +9048,53288,Female,disloyal Customer,25,Business travel,Eco,811,3,3,3,3,4,3,4,4,1,2,1,4,2,4,9,0.0,neutral or dissatisfied +9049,29600,Male,Loyal Customer,69,Business travel,Eco,1533,3,3,3,3,3,3,3,3,4,1,4,4,3,3,0,14.0,neutral or dissatisfied +9050,128874,Male,disloyal Customer,38,Business travel,Business,2454,3,4,4,1,4,2,2,5,5,5,5,2,3,2,0,0.0,neutral or dissatisfied +9051,100386,Male,Loyal Customer,66,Personal Travel,Eco,1034,3,4,2,2,2,2,2,2,4,2,5,3,5,2,22,9.0,neutral or dissatisfied +9052,35424,Female,Loyal Customer,61,Personal Travel,Eco,1041,0,4,0,3,4,4,4,4,4,0,4,5,4,3,0,0.0,satisfied +9053,29727,Female,Loyal Customer,34,Business travel,Eco Plus,2797,3,1,1,1,4,3,3,5,2,4,2,3,3,3,37,29.0,satisfied +9054,26138,Male,Loyal Customer,23,Business travel,Business,1907,3,3,3,3,4,4,4,4,1,3,2,3,1,4,0,0.0,satisfied +9055,129058,Female,Loyal Customer,61,Personal Travel,Eco,1846,0,3,0,4,1,3,3,4,4,0,3,2,4,3,0,0.0,satisfied +9056,79178,Male,Loyal Customer,46,Business travel,Business,2422,4,4,3,4,2,4,4,4,4,4,4,5,4,5,26,18.0,satisfied +9057,100944,Female,Loyal Customer,52,Business travel,Business,1204,4,4,4,4,5,4,4,4,4,4,4,4,4,3,10,28.0,satisfied +9058,18597,Female,disloyal Customer,29,Business travel,Eco,305,2,4,2,4,5,2,5,5,2,4,3,2,3,5,39,30.0,neutral or dissatisfied +9059,56948,Female,Loyal Customer,27,Business travel,Business,2454,4,2,2,2,4,4,4,3,2,3,2,4,3,4,0,0.0,neutral or dissatisfied +9060,5524,Male,disloyal Customer,20,Business travel,Eco,431,2,0,1,3,2,1,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +9061,127152,Female,Loyal Customer,53,Personal Travel,Eco,646,1,4,1,2,5,2,1,4,4,1,4,5,4,2,0,0.0,neutral or dissatisfied +9062,128074,Female,Loyal Customer,56,Business travel,Business,2917,1,1,1,1,5,5,5,5,2,5,5,5,5,5,54,45.0,satisfied +9063,110327,Female,Loyal Customer,40,Business travel,Business,925,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +9064,4137,Female,disloyal Customer,23,Business travel,Eco,544,1,4,1,3,3,1,3,3,3,4,3,1,3,3,0,7.0,neutral or dissatisfied +9065,109974,Male,Loyal Customer,18,Personal Travel,Eco,1204,2,3,2,3,4,2,4,4,4,4,1,3,1,4,62,49.0,neutral or dissatisfied +9066,24932,Male,Loyal Customer,50,Personal Travel,Eco,762,2,4,2,4,1,2,1,1,4,2,5,5,4,1,14,18.0,neutral or dissatisfied +9067,51803,Female,Loyal Customer,29,Personal Travel,Eco,370,4,3,4,2,4,4,4,4,3,4,4,3,2,4,0,0.0,neutral or dissatisfied +9068,76065,Male,Loyal Customer,13,Business travel,Business,1769,1,1,1,1,4,4,4,4,4,5,5,4,4,4,22,66.0,satisfied +9069,86720,Male,Loyal Customer,79,Business travel,Eco,247,4,1,1,1,5,4,5,5,4,3,4,3,5,5,0,0.0,satisfied +9070,57511,Male,Loyal Customer,55,Business travel,Business,2729,0,5,0,5,5,2,4,1,1,1,1,4,1,4,0,6.0,satisfied +9071,26393,Male,Loyal Customer,48,Business travel,Business,3493,5,1,5,5,2,3,5,5,5,5,5,5,5,5,0,0.0,satisfied +9072,123274,Male,Loyal Customer,15,Personal Travel,Eco,328,1,5,4,3,1,4,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +9073,20708,Female,Loyal Customer,8,Business travel,Eco Plus,779,4,5,5,5,4,1,4,2,2,3,3,4,2,4,244,259.0,neutral or dissatisfied +9074,121466,Female,Loyal Customer,15,Personal Travel,Eco,331,3,4,3,5,4,3,4,4,3,1,2,2,3,4,4,16.0,neutral or dissatisfied +9075,93996,Female,Loyal Customer,53,Business travel,Business,3935,0,0,0,3,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +9076,47448,Female,disloyal Customer,35,Business travel,Eco,590,1,2,1,3,3,1,3,3,3,2,4,4,3,3,24,43.0,neutral or dissatisfied +9077,23733,Female,Loyal Customer,55,Business travel,Eco,771,1,4,4,4,3,3,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +9078,57014,Female,Loyal Customer,24,Personal Travel,Eco,2565,2,5,2,2,2,4,2,5,5,3,2,2,5,2,4,0.0,neutral or dissatisfied +9079,89555,Female,Loyal Customer,38,Business travel,Business,1010,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +9080,113256,Female,Loyal Customer,42,Business travel,Business,2977,2,2,2,2,4,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +9081,70795,Female,Loyal Customer,56,Business travel,Business,328,2,2,4,2,2,5,5,5,5,5,5,1,5,5,0,0.0,satisfied +9082,82127,Male,Loyal Customer,33,Business travel,Business,2519,4,4,4,4,4,4,4,3,5,1,2,4,4,4,0,4.0,satisfied +9083,123070,Female,Loyal Customer,50,Business travel,Business,2657,2,2,2,2,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +9084,14510,Male,Loyal Customer,60,Personal Travel,Eco,328,0,2,0,3,1,0,1,1,1,5,3,2,3,1,0,0.0,satisfied +9085,8717,Male,Loyal Customer,55,Personal Travel,Eco,280,3,4,3,4,3,3,3,3,3,4,3,1,3,3,52,63.0,neutral or dissatisfied +9086,92207,Male,Loyal Customer,48,Personal Travel,Eco,1956,3,4,3,3,3,3,3,3,4,4,3,4,4,3,0,0.0,neutral or dissatisfied +9087,128957,Male,Loyal Customer,52,Business travel,Business,414,5,5,5,5,3,5,5,5,5,4,5,5,5,3,2,0.0,satisfied +9088,17381,Male,disloyal Customer,20,Business travel,Eco,637,4,0,4,2,4,4,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +9089,16400,Male,Loyal Customer,61,Personal Travel,Eco,533,1,5,1,3,2,1,1,2,4,4,4,5,4,2,34,29.0,neutral or dissatisfied +9090,68448,Female,disloyal Customer,49,Business travel,Business,1067,1,0,0,2,4,1,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +9091,87992,Female,Loyal Customer,57,Business travel,Business,646,4,4,4,4,2,4,4,4,4,4,4,3,4,5,0,2.0,satisfied +9092,16922,Male,Loyal Customer,66,Personal Travel,Business,820,3,5,3,2,1,1,3,3,3,3,3,5,3,1,40,77.0,neutral or dissatisfied +9093,82465,Female,Loyal Customer,55,Personal Travel,Eco,502,4,5,4,3,3,5,5,5,5,4,5,4,5,4,0,22.0,neutral or dissatisfied +9094,83279,Female,Loyal Customer,50,Personal Travel,Eco,1979,2,4,2,4,5,5,3,4,4,2,4,4,4,2,8,48.0,neutral or dissatisfied +9095,49083,Male,disloyal Customer,57,Business travel,Eco,250,3,5,3,3,5,3,5,5,2,4,3,3,5,5,0,0.0,neutral or dissatisfied +9096,29223,Male,Loyal Customer,44,Business travel,Business,434,4,5,5,5,3,3,4,4,4,4,4,4,4,2,9,2.0,neutral or dissatisfied +9097,128167,Female,disloyal Customer,22,Business travel,Eco,928,3,3,3,3,1,3,1,1,4,5,4,4,5,1,12,0.0,satisfied +9098,2942,Female,disloyal Customer,24,Business travel,Business,737,5,4,5,3,5,5,4,5,3,3,5,3,5,5,22,43.0,satisfied +9099,22631,Female,Loyal Customer,38,Personal Travel,Eco,300,3,3,1,4,2,1,3,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +9100,17413,Female,disloyal Customer,41,Business travel,Business,351,2,2,2,2,1,2,1,1,3,4,5,5,1,1,10,0.0,satisfied +9101,104964,Male,Loyal Customer,41,Business travel,Business,3108,3,3,3,3,2,4,5,4,4,4,4,3,4,5,17,22.0,satisfied +9102,80511,Male,Loyal Customer,15,Personal Travel,Eco,1749,3,3,3,3,3,3,4,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +9103,114330,Female,Loyal Customer,70,Personal Travel,Eco,862,3,4,3,5,3,2,1,1,1,3,2,1,1,5,0,0.0,neutral or dissatisfied +9104,114693,Male,disloyal Customer,26,Business travel,Business,373,5,0,5,2,2,5,2,2,4,5,5,3,5,2,48,48.0,satisfied +9105,40662,Male,Loyal Customer,35,Business travel,Business,590,3,3,3,3,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +9106,70374,Female,Loyal Customer,49,Personal Travel,Eco,1145,2,5,2,2,4,3,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +9107,129814,Male,Loyal Customer,49,Personal Travel,Eco,337,2,2,2,3,3,2,3,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +9108,71069,Female,Loyal Customer,25,Personal Travel,Eco,978,1,5,1,2,1,1,1,1,5,3,4,5,4,1,0,0.0,neutral or dissatisfied +9109,2713,Male,Loyal Customer,32,Personal Travel,Eco,562,3,3,3,1,1,3,4,1,3,5,1,1,5,1,0,0.0,neutral or dissatisfied +9110,110021,Female,Loyal Customer,66,Personal Travel,Eco,1204,4,1,4,3,3,4,3,4,4,4,4,4,4,3,56,38.0,neutral or dissatisfied +9111,121551,Female,Loyal Customer,43,Business travel,Business,1764,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +9112,125402,Male,Loyal Customer,43,Personal Travel,Eco,1440,3,4,3,4,3,3,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +9113,29435,Female,Loyal Customer,38,Business travel,Business,421,3,4,3,3,2,5,5,4,4,5,4,3,4,3,0,6.0,satisfied +9114,31101,Female,Loyal Customer,11,Personal Travel,Eco,1014,4,4,4,4,3,4,1,3,3,3,2,2,4,3,0,0.0,neutral or dissatisfied +9115,118586,Male,Loyal Customer,51,Business travel,Eco,621,4,1,2,2,4,4,4,4,1,4,3,1,3,4,17,10.0,neutral or dissatisfied +9116,23804,Male,disloyal Customer,44,Business travel,Eco,304,1,2,1,4,5,1,5,5,4,3,4,1,3,5,34,36.0,neutral or dissatisfied +9117,97288,Male,disloyal Customer,27,Business travel,Business,843,3,3,3,3,1,3,1,1,5,5,5,3,5,1,17,14.0,neutral or dissatisfied +9118,56683,Female,Loyal Customer,57,Personal Travel,Eco,937,1,5,1,1,5,5,4,4,4,1,5,4,4,5,3,0.0,neutral or dissatisfied +9119,39243,Female,Loyal Customer,39,Business travel,Eco,160,4,3,3,3,4,4,4,4,3,4,2,5,4,4,0,0.0,satisfied +9120,6460,Male,Loyal Customer,41,Business travel,Eco Plus,213,4,3,4,3,4,4,4,4,2,5,4,2,3,4,21,19.0,neutral or dissatisfied +9121,58300,Male,Loyal Customer,13,Personal Travel,Eco Plus,678,2,5,2,4,5,2,1,5,3,3,5,3,4,5,10,16.0,neutral or dissatisfied +9122,118260,Female,Loyal Customer,12,Personal Travel,Eco,1972,3,1,3,4,3,3,3,3,2,1,3,3,3,3,39,28.0,neutral or dissatisfied +9123,73841,Female,Loyal Customer,28,Business travel,Business,1709,2,2,2,2,4,4,4,4,3,2,5,5,5,4,3,0.0,satisfied +9124,18276,Male,Loyal Customer,40,Business travel,Eco Plus,137,4,1,1,1,4,4,4,4,4,4,3,5,5,4,56,39.0,satisfied +9125,126301,Male,Loyal Customer,40,Personal Travel,Eco,328,2,0,2,1,2,2,2,2,3,5,4,4,5,2,1,8.0,neutral or dissatisfied +9126,31120,Female,Loyal Customer,27,Business travel,Eco,991,3,5,5,5,3,4,3,3,1,2,1,5,1,3,75,59.0,satisfied +9127,56973,Female,Loyal Customer,25,Personal Travel,Eco,2565,2,4,2,1,2,3,3,2,5,1,4,3,2,3,96,98.0,neutral or dissatisfied +9128,92736,Male,Loyal Customer,42,Business travel,Business,1276,3,1,1,1,5,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +9129,5878,Male,Loyal Customer,42,Business travel,Business,1757,3,3,3,3,4,4,4,3,2,5,5,4,3,4,237,303.0,satisfied +9130,11285,Male,Loyal Customer,29,Personal Travel,Eco,270,2,0,2,1,3,2,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +9131,122636,Female,Loyal Customer,32,Business travel,Business,3756,2,2,3,2,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +9132,94800,Female,Loyal Customer,29,Business travel,Business,2335,3,4,4,4,3,3,3,3,1,3,4,2,3,3,4,6.0,neutral or dissatisfied +9133,9419,Male,disloyal Customer,28,Business travel,Business,362,5,5,5,3,5,5,5,5,5,2,5,3,4,5,0,0.0,satisfied +9134,70233,Male,Loyal Customer,43,Business travel,Business,1068,2,2,2,2,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9135,122587,Female,Loyal Customer,39,Business travel,Business,3795,1,1,2,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +9136,38817,Male,Loyal Customer,26,Personal Travel,Eco,353,1,5,1,1,3,1,3,3,1,2,1,4,3,3,0,0.0,neutral or dissatisfied +9137,119486,Female,Loyal Customer,23,Business travel,Eco,814,3,5,4,4,3,3,4,3,3,4,3,4,4,3,34,24.0,neutral or dissatisfied +9138,65023,Male,Loyal Customer,70,Personal Travel,Eco,190,3,3,3,3,5,3,1,5,3,2,2,4,2,5,12,4.0,neutral or dissatisfied +9139,11633,Female,disloyal Customer,26,Business travel,Business,835,3,3,3,4,3,3,3,3,4,3,4,4,5,3,1,0.0,neutral or dissatisfied +9140,88840,Male,Loyal Customer,44,Personal Travel,Eco Plus,404,4,4,4,3,3,4,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +9141,35471,Female,Loyal Customer,33,Personal Travel,Eco,1069,2,5,3,1,5,3,2,5,3,4,4,4,4,5,26,50.0,neutral or dissatisfied +9142,97123,Female,disloyal Customer,25,Business travel,Eco,1242,3,3,3,4,5,3,5,5,2,5,4,1,3,5,51,44.0,neutral or dissatisfied +9143,15424,Male,disloyal Customer,22,Business travel,Eco,377,2,0,2,3,5,2,5,5,2,2,3,1,3,5,6,10.0,neutral or dissatisfied +9144,271,Male,disloyal Customer,35,Business travel,Business,802,2,1,1,3,4,1,4,4,4,2,3,3,4,4,0,2.0,neutral or dissatisfied +9145,3859,Female,Loyal Customer,31,Personal Travel,Eco Plus,650,1,3,1,4,2,1,2,2,4,1,1,1,4,2,0,0.0,neutral or dissatisfied +9146,29480,Male,Loyal Customer,20,Business travel,Business,1107,1,1,1,1,3,3,3,3,5,4,1,1,2,3,0,0.0,satisfied +9147,124537,Female,Loyal Customer,53,Business travel,Business,1276,3,3,3,3,5,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +9148,64924,Male,Loyal Customer,48,Business travel,Eco,469,2,4,4,4,2,2,2,2,4,2,2,4,3,2,0,0.0,neutral or dissatisfied +9149,127706,Female,Loyal Customer,60,Business travel,Business,2315,2,2,2,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +9150,88645,Female,Loyal Customer,63,Personal Travel,Eco,594,4,4,4,3,3,2,2,3,3,4,3,5,3,5,0,0.0,satisfied +9151,94909,Female,Loyal Customer,36,Business travel,Eco,239,3,2,2,2,3,3,3,3,3,5,4,4,3,3,5,1.0,satisfied +9152,89945,Male,Loyal Customer,54,Personal Travel,Eco,1501,1,4,1,2,3,1,3,3,3,4,5,4,5,3,0,1.0,neutral or dissatisfied +9153,32233,Male,Loyal Customer,51,Business travel,Business,3188,2,2,2,2,2,3,5,4,4,4,5,4,4,5,0,0.0,satisfied +9154,94164,Female,Loyal Customer,50,Business travel,Business,3705,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +9155,596,Female,Loyal Customer,44,Business travel,Business,89,1,1,1,1,2,4,5,4,4,4,4,4,4,5,25,23.0,satisfied +9156,118125,Male,Loyal Customer,65,Personal Travel,Eco,1506,1,4,1,4,2,1,2,2,4,2,3,1,3,2,19,4.0,neutral or dissatisfied +9157,66335,Male,disloyal Customer,54,Business travel,Business,986,1,1,1,3,1,1,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +9158,8128,Male,Loyal Customer,32,Business travel,Business,3952,0,0,0,4,1,1,1,1,5,3,5,3,5,1,0,0.0,satisfied +9159,94090,Female,Loyal Customer,39,Personal Travel,Business,239,1,5,1,1,4,5,5,3,3,1,5,4,3,4,0,0.0,neutral or dissatisfied +9160,3992,Female,Loyal Customer,50,Business travel,Business,479,4,4,4,4,4,5,4,5,5,5,5,4,5,3,0,10.0,satisfied +9161,129017,Female,disloyal Customer,25,Business travel,Eco,752,1,1,1,3,1,1,1,2,5,4,3,1,2,1,1,0.0,neutral or dissatisfied +9162,88029,Male,Loyal Customer,59,Business travel,Business,2170,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +9163,22026,Male,Loyal Customer,33,Business travel,Eco Plus,448,5,1,1,1,5,5,5,5,5,4,2,1,1,5,0,0.0,satisfied +9164,2468,Female,Loyal Customer,58,Personal Travel,Eco,773,1,2,1,3,4,4,4,1,1,1,1,3,1,4,5,0.0,neutral or dissatisfied +9165,90114,Male,Loyal Customer,24,Business travel,Business,3990,1,1,4,1,3,4,3,3,3,2,5,5,5,3,0,0.0,satisfied +9166,128257,Female,Loyal Customer,32,Business travel,Business,325,2,2,2,2,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +9167,125749,Female,Loyal Customer,70,Personal Travel,Business,861,4,5,4,4,5,5,5,5,5,4,5,4,5,5,0,33.0,neutral or dissatisfied +9168,71597,Female,Loyal Customer,43,Business travel,Business,2730,4,5,5,5,1,4,3,4,4,4,4,2,4,2,0,6.0,neutral or dissatisfied +9169,42116,Male,Loyal Customer,50,Business travel,Eco,898,1,1,2,1,1,1,1,1,1,2,4,1,4,1,0,0.0,neutral or dissatisfied +9170,8918,Male,disloyal Customer,24,Business travel,Eco,661,4,0,3,4,4,3,4,4,4,2,5,4,4,4,0,0.0,neutral or dissatisfied +9171,43863,Male,Loyal Customer,38,Business travel,Business,1766,0,5,0,4,5,4,2,3,3,3,3,5,3,2,0,0.0,satisfied +9172,66004,Male,Loyal Customer,42,Business travel,Business,2211,2,2,2,2,4,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +9173,73030,Male,Loyal Customer,37,Personal Travel,Eco,1096,2,1,2,1,2,2,1,2,1,1,1,3,2,2,0,0.0,neutral or dissatisfied +9174,120773,Female,disloyal Customer,30,Business travel,Eco,678,2,2,2,4,1,2,1,1,1,3,3,4,3,1,5,22.0,neutral or dissatisfied +9175,35517,Female,Loyal Customer,38,Personal Travel,Eco,1144,4,5,5,1,3,5,3,3,5,4,3,4,4,3,0,0.0,neutral or dissatisfied +9176,49647,Male,Loyal Customer,61,Business travel,Eco,337,5,3,3,3,5,5,5,5,4,1,3,5,5,5,23,20.0,satisfied +9177,125762,Male,Loyal Customer,51,Business travel,Business,920,1,1,2,1,3,3,3,4,4,4,4,3,5,3,199,197.0,satisfied +9178,2904,Female,Loyal Customer,45,Personal Travel,Eco,491,2,5,2,5,4,4,4,2,2,2,2,4,2,5,95,104.0,neutral or dissatisfied +9179,124382,Male,Loyal Customer,55,Personal Travel,Eco,808,0,3,0,1,4,0,4,4,3,1,3,3,3,4,0,0.0,satisfied +9180,123280,Female,Loyal Customer,52,Personal Travel,Eco,328,3,2,3,3,1,3,3,3,3,3,3,4,3,3,21,11.0,neutral or dissatisfied +9181,75122,Male,disloyal Customer,43,Business travel,Business,1744,3,3,3,3,2,3,1,2,3,2,4,4,4,2,0,0.0,satisfied +9182,65249,Female,disloyal Customer,37,Business travel,Eco Plus,190,2,2,2,3,3,2,3,3,3,3,4,4,3,3,0,0.0,neutral or dissatisfied +9183,17771,Female,Loyal Customer,47,Business travel,Eco,1075,4,5,5,5,1,3,1,4,4,4,4,3,4,3,0,0.0,satisfied +9184,43265,Female,Loyal Customer,42,Business travel,Eco,436,2,4,4,4,1,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +9185,82531,Female,Loyal Customer,51,Business travel,Business,440,1,5,5,5,3,4,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +9186,66066,Male,Loyal Customer,9,Personal Travel,Eco,1055,2,5,2,4,2,2,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +9187,125546,Female,Loyal Customer,59,Business travel,Business,226,0,0,0,5,2,5,5,5,5,5,5,4,5,4,16,10.0,satisfied +9188,118512,Male,disloyal Customer,25,Business travel,Business,304,3,0,3,2,2,3,2,2,3,4,5,5,4,2,38,23.0,neutral or dissatisfied +9189,93951,Male,Loyal Customer,30,Personal Travel,Eco,507,4,5,4,2,5,4,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +9190,88734,Male,Loyal Customer,49,Personal Travel,Eco,515,3,3,3,4,4,3,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +9191,13889,Female,Loyal Customer,7,Personal Travel,Eco,578,5,4,5,1,5,5,5,5,3,3,4,4,4,5,7,0.0,satisfied +9192,33272,Female,Loyal Customer,32,Personal Travel,Eco Plus,101,3,4,3,5,2,3,2,2,4,3,2,4,2,2,0,1.0,neutral or dissatisfied +9193,484,Male,Loyal Customer,45,Business travel,Business,1528,0,0,0,3,2,4,4,3,3,3,3,3,3,5,5,1.0,satisfied +9194,64133,Female,Loyal Customer,42,Business travel,Business,2200,2,2,5,2,4,5,4,5,5,5,5,5,5,5,20,0.0,satisfied +9195,32664,Male,Loyal Customer,41,Business travel,Eco,163,5,1,3,1,5,5,5,5,1,5,2,5,1,5,0,0.0,satisfied +9196,73059,Female,Loyal Customer,44,Business travel,Eco Plus,696,5,1,1,1,4,5,5,5,5,5,5,5,5,3,9,0.0,satisfied +9197,84919,Male,Loyal Customer,20,Personal Travel,Eco,547,3,1,3,3,5,3,5,5,2,1,3,3,4,5,0,0.0,neutral or dissatisfied +9198,67206,Male,Loyal Customer,17,Personal Travel,Eco,985,2,5,2,3,3,2,5,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +9199,85461,Female,Loyal Customer,35,Business travel,Business,214,1,5,5,5,3,3,2,1,1,1,1,1,1,3,6,4.0,neutral or dissatisfied +9200,108650,Female,Loyal Customer,42,Business travel,Business,1747,4,4,4,4,5,5,5,5,5,5,5,3,5,5,13,39.0,satisfied +9201,15447,Female,Loyal Customer,32,Business travel,Eco,164,3,1,1,1,3,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +9202,1486,Male,disloyal Customer,22,Business travel,Business,737,5,0,5,4,2,5,1,2,3,4,5,4,5,2,0,0.0,satisfied +9203,93490,Female,Loyal Customer,40,Business travel,Business,1613,3,3,3,3,2,5,5,5,5,5,5,4,5,5,15,4.0,satisfied +9204,123470,Male,disloyal Customer,23,Business travel,Eco,919,1,1,1,5,2,1,2,2,4,3,3,4,4,2,2,0.0,neutral or dissatisfied +9205,100264,Male,Loyal Customer,27,Business travel,Business,2006,5,5,5,5,5,5,5,5,5,2,4,4,5,5,12,29.0,satisfied +9206,61236,Female,Loyal Customer,37,Business travel,Business,2413,2,1,1,1,3,4,3,2,2,2,2,2,2,4,18,7.0,neutral or dissatisfied +9207,76257,Male,Loyal Customer,39,Business travel,Eco Plus,1399,1,3,3,3,1,1,1,1,2,3,3,2,4,1,0,2.0,neutral or dissatisfied +9208,45779,Female,Loyal Customer,49,Business travel,Business,2094,5,5,3,5,3,1,2,5,5,5,5,2,5,2,0,0.0,satisfied +9209,83530,Male,Loyal Customer,53,Personal Travel,Eco Plus,946,1,1,1,2,2,1,4,2,2,5,2,4,3,2,0,0.0,neutral or dissatisfied +9210,79856,Male,Loyal Customer,53,Business travel,Business,1715,5,5,2,5,3,5,4,5,5,5,5,4,5,4,0,14.0,satisfied +9211,15583,Female,disloyal Customer,24,Business travel,Eco,229,2,4,1,4,5,1,5,5,1,2,3,5,3,5,0,0.0,neutral or dissatisfied +9212,89587,Female,Loyal Customer,42,Business travel,Business,1069,2,2,2,2,2,5,5,2,2,2,2,4,2,4,124,117.0,satisfied +9213,92081,Female,disloyal Customer,62,Business travel,Eco,1589,3,3,3,3,3,3,3,3,3,2,3,3,4,3,0,0.0,neutral or dissatisfied +9214,38171,Female,Loyal Customer,28,Personal Travel,Eco,1237,2,4,2,5,3,2,3,3,3,2,4,5,4,3,32,10.0,neutral or dissatisfied +9215,108999,Male,Loyal Customer,60,Business travel,Business,3180,2,2,4,2,4,5,4,4,4,4,4,4,4,5,39,35.0,satisfied +9216,2842,Female,Loyal Customer,44,Business travel,Business,2646,1,1,1,1,4,5,5,4,4,5,4,3,4,4,3,5.0,satisfied +9217,32583,Male,Loyal Customer,31,Business travel,Eco,101,3,5,3,3,3,3,3,3,4,5,3,4,4,3,0,0.0,neutral or dissatisfied +9218,46019,Female,disloyal Customer,18,Business travel,Eco,898,5,5,5,4,1,5,1,1,2,3,2,3,5,1,14,8.0,satisfied +9219,106935,Male,disloyal Customer,10,Business travel,Eco,1036,3,2,2,4,4,2,4,4,1,2,4,4,3,4,29,27.0,neutral or dissatisfied +9220,4917,Female,Loyal Customer,54,Business travel,Business,3353,2,1,1,1,5,1,2,2,2,2,2,1,2,4,0,33.0,neutral or dissatisfied +9221,117428,Male,Loyal Customer,8,Personal Travel,Eco,1460,4,5,4,4,2,4,2,2,4,4,4,3,5,2,39,29.0,neutral or dissatisfied +9222,30793,Female,disloyal Customer,24,Business travel,Eco Plus,895,2,1,2,4,2,2,2,2,4,3,3,1,3,2,95,90.0,neutral or dissatisfied +9223,38276,Male,Loyal Customer,58,Personal Travel,Eco,1133,3,4,3,2,3,3,3,3,3,5,3,3,4,3,14,15.0,neutral or dissatisfied +9224,31464,Male,Loyal Customer,41,Business travel,Eco,776,4,4,2,4,4,4,4,4,5,1,3,3,1,4,14,19.0,satisfied +9225,90127,Male,Loyal Customer,42,Business travel,Eco,1145,2,1,1,1,3,2,3,3,2,4,3,4,4,3,0,0.0,neutral or dissatisfied +9226,74098,Male,Loyal Customer,49,Business travel,Business,2547,5,5,5,5,4,5,5,3,3,4,3,4,3,4,29,19.0,satisfied +9227,2418,Male,Loyal Customer,17,Personal Travel,Eco,604,1,5,1,4,5,1,5,5,5,5,4,5,5,5,9,10.0,neutral or dissatisfied +9228,11079,Female,Loyal Customer,27,Personal Travel,Eco,74,0,4,0,5,2,0,2,2,4,4,5,5,4,2,0,0.0,satisfied +9229,87557,Male,disloyal Customer,59,Business travel,Eco,432,2,2,2,3,3,2,4,3,4,3,4,2,3,3,14,22.0,neutral or dissatisfied +9230,119775,Male,Loyal Customer,32,Business travel,Business,936,1,1,1,1,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +9231,129260,Male,Loyal Customer,55,Business travel,Business,1235,5,5,5,5,4,4,4,1,1,2,1,3,1,5,0,0.0,satisfied +9232,76893,Female,disloyal Customer,49,Business travel,Eco,630,2,3,2,4,5,2,5,5,4,3,4,4,3,5,0,1.0,neutral or dissatisfied +9233,98238,Female,disloyal Customer,38,Business travel,Business,1072,4,4,4,3,2,4,2,2,5,4,4,3,4,2,7,19.0,satisfied +9234,28079,Male,Loyal Customer,30,Personal Travel,Eco Plus,2603,2,4,2,1,2,3,1,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +9235,25952,Female,Loyal Customer,42,Business travel,Business,3553,2,2,2,2,2,2,2,5,5,5,5,2,5,3,8,0.0,satisfied +9236,107074,Male,Loyal Customer,23,Personal Travel,Eco,395,1,5,1,2,1,1,1,1,1,1,2,2,3,1,0,0.0,neutral or dissatisfied +9237,3088,Female,Loyal Customer,44,Business travel,Business,594,3,3,3,3,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +9238,54251,Female,Loyal Customer,34,Business travel,Business,1595,3,3,3,3,3,3,3,2,2,2,2,1,2,3,3,0.0,satisfied +9239,59908,Male,Loyal Customer,53,Business travel,Business,2639,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +9240,122122,Male,Loyal Customer,51,Business travel,Eco Plus,130,1,5,5,5,1,1,1,1,3,4,3,4,3,1,0,0.0,neutral or dissatisfied +9241,87538,Female,Loyal Customer,56,Personal Travel,Eco Plus,321,2,3,2,2,2,5,5,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +9242,1611,Female,Loyal Customer,49,Business travel,Business,968,2,2,4,2,3,5,5,5,5,5,5,5,5,3,13,6.0,satisfied +9243,112862,Female,Loyal Customer,49,Business travel,Business,2084,5,5,5,5,3,4,5,2,2,2,2,5,2,3,25,19.0,satisfied +9244,89297,Female,Loyal Customer,7,Personal Travel,Eco,453,4,4,2,1,2,2,4,3,4,4,5,4,4,4,161,154.0,satisfied +9245,18442,Female,Loyal Customer,43,Business travel,Business,1510,2,5,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +9246,48898,Female,Loyal Customer,39,Business travel,Business,89,3,3,3,3,3,3,5,5,5,4,3,3,5,5,93,81.0,satisfied +9247,121478,Male,Loyal Customer,31,Personal Travel,Eco,331,3,3,3,2,5,3,5,5,5,1,1,5,5,5,0,0.0,neutral or dissatisfied +9248,59309,Male,Loyal Customer,44,Business travel,Business,2338,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +9249,112885,Female,Loyal Customer,21,Business travel,Business,715,3,3,3,3,3,3,3,3,1,3,3,2,3,3,24,18.0,neutral or dissatisfied +9250,48551,Male,Loyal Customer,24,Personal Travel,Eco,853,3,4,2,3,1,2,1,1,3,4,4,5,4,1,0,5.0,neutral or dissatisfied +9251,22311,Male,Loyal Customer,41,Business travel,Business,2902,4,4,4,4,2,5,3,4,4,4,5,4,4,2,6,0.0,satisfied +9252,20014,Female,Loyal Customer,34,Personal Travel,Eco,599,3,4,3,4,4,3,4,4,4,2,4,1,3,4,0,0.0,neutral or dissatisfied +9253,108687,Male,disloyal Customer,21,Business travel,Eco,577,3,5,3,2,3,3,3,3,4,3,5,4,4,3,6,0.0,neutral or dissatisfied +9254,53703,Female,Loyal Customer,50,Business travel,Business,2842,2,3,3,3,5,2,3,2,2,2,2,1,2,1,3,0.0,neutral or dissatisfied +9255,111011,Female,disloyal Customer,33,Business travel,Business,197,1,1,1,3,3,1,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +9256,27071,Male,Loyal Customer,12,Personal Travel,Eco,1399,2,4,2,4,2,2,2,2,3,2,5,5,5,2,0,0.0,neutral or dissatisfied +9257,48563,Male,Loyal Customer,48,Personal Travel,Eco,737,1,5,1,3,3,1,3,3,4,3,4,4,5,3,15,26.0,neutral or dissatisfied +9258,77024,Male,Loyal Customer,41,Business travel,Business,368,4,4,4,4,4,1,5,5,5,5,5,3,5,5,3,0.0,satisfied +9259,8384,Male,Loyal Customer,46,Personal Travel,Eco,773,1,4,1,3,2,1,2,2,2,1,4,2,4,2,36,48.0,neutral or dissatisfied +9260,57853,Female,Loyal Customer,23,Business travel,Business,2329,1,0,0,4,0,2,2,3,2,3,3,2,2,2,15,18.0,neutral or dissatisfied +9261,19770,Male,Loyal Customer,31,Business travel,Business,3863,2,3,3,3,2,2,2,2,2,1,3,1,4,2,110,104.0,neutral or dissatisfied +9262,90689,Female,Loyal Customer,37,Business travel,Business,1834,1,1,1,1,3,5,5,4,4,5,4,4,4,4,1,0.0,satisfied +9263,6295,Female,Loyal Customer,60,Business travel,Business,693,3,3,2,3,4,5,4,4,4,4,4,3,4,4,29,24.0,satisfied +9264,32541,Male,disloyal Customer,25,Business travel,Eco,163,4,0,4,5,4,4,4,4,5,2,4,3,2,4,0,3.0,satisfied +9265,114539,Male,Loyal Customer,38,Personal Travel,Business,446,4,5,4,2,2,4,4,3,3,4,3,5,3,5,36,48.0,neutral or dissatisfied +9266,49871,Female,disloyal Customer,16,Business travel,Eco,326,0,2,0,1,5,0,5,5,1,2,4,1,4,5,0,0.0,satisfied +9267,34867,Female,disloyal Customer,40,Business travel,Business,1295,4,4,4,3,3,4,3,3,1,4,4,4,2,3,0,0.0,satisfied +9268,64797,Female,Loyal Customer,33,Business travel,Business,2102,5,5,5,5,3,4,4,5,5,5,5,5,5,4,37,27.0,satisfied +9269,123018,Male,disloyal Customer,23,Business travel,Eco,631,2,0,2,3,5,2,5,5,3,5,4,3,5,5,0,6.0,neutral or dissatisfied +9270,121975,Female,Loyal Customer,51,Business travel,Business,185,3,3,3,3,2,5,4,3,3,4,5,3,3,3,0,0.0,satisfied +9271,108481,Male,Loyal Customer,49,Business travel,Business,570,2,2,2,2,2,5,5,5,5,5,5,3,5,3,34,27.0,satisfied +9272,87925,Male,Loyal Customer,47,Business travel,Business,1619,1,1,1,1,4,4,4,4,4,4,4,3,4,5,17,24.0,satisfied +9273,127400,Male,disloyal Customer,27,Business travel,Eco,872,4,4,4,4,3,4,3,3,1,5,4,4,3,3,0,0.0,neutral or dissatisfied +9274,23740,Male,Loyal Customer,29,Business travel,Business,3884,4,4,4,4,5,5,5,5,2,2,1,4,2,5,0,0.0,satisfied +9275,108495,Female,Loyal Customer,57,Business travel,Business,1779,5,5,5,5,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +9276,117562,Male,Loyal Customer,46,Business travel,Business,3787,1,1,1,1,4,4,5,5,5,5,5,4,5,5,20,9.0,satisfied +9277,67833,Female,Loyal Customer,33,Business travel,Business,1235,3,1,1,1,2,4,4,3,3,3,3,3,3,4,17,6.0,neutral or dissatisfied +9278,68083,Female,Loyal Customer,32,Business travel,Business,2085,1,4,4,4,1,1,1,1,4,1,2,3,2,1,9,6.0,neutral or dissatisfied +9279,124493,Male,disloyal Customer,29,Business travel,Business,930,4,4,4,3,4,4,5,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +9280,124089,Male,Loyal Customer,60,Business travel,Business,3363,4,4,4,4,5,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +9281,88296,Male,Loyal Customer,44,Business travel,Business,2254,1,1,5,1,2,4,4,4,4,5,4,5,4,3,0,4.0,satisfied +9282,36914,Female,Loyal Customer,45,Business travel,Eco,740,5,1,1,1,3,1,4,5,5,5,5,2,5,1,0,0.0,satisfied +9283,108846,Male,Loyal Customer,48,Business travel,Business,1947,2,2,2,2,2,5,5,3,3,3,3,5,3,4,14,11.0,satisfied +9284,107693,Female,Loyal Customer,30,Business travel,Business,2453,1,1,5,1,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +9285,56552,Female,disloyal Customer,25,Business travel,Business,1023,5,5,5,4,2,5,1,2,3,3,4,4,4,2,14,19.0,satisfied +9286,81073,Female,Loyal Customer,39,Business travel,Business,931,3,3,3,3,3,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +9287,41024,Female,Loyal Customer,45,Business travel,Eco,989,4,5,5,5,3,2,1,4,4,4,4,3,4,4,0,21.0,satisfied +9288,5156,Female,Loyal Customer,67,Personal Travel,Eco,622,1,4,1,1,4,5,5,3,3,1,3,5,3,3,0,33.0,neutral or dissatisfied +9289,53495,Male,Loyal Customer,65,Personal Travel,Eco,2419,3,4,3,3,3,5,5,5,4,4,4,5,3,5,4,0.0,neutral or dissatisfied +9290,111922,Female,Loyal Customer,55,Business travel,Business,2131,5,5,1,5,2,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +9291,5069,Male,Loyal Customer,64,Business travel,Eco,223,1,3,3,3,2,1,2,2,4,5,3,2,4,2,6,0.0,neutral or dissatisfied +9292,65689,Female,Loyal Customer,51,Personal Travel,Eco Plus,926,2,5,2,2,2,3,5,5,5,2,5,3,5,3,47,34.0,neutral or dissatisfied +9293,25805,Female,Loyal Customer,37,Personal Travel,Eco,762,2,4,2,3,4,2,4,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +9294,127278,Female,Loyal Customer,24,Personal Travel,Eco,1107,3,5,4,3,3,4,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +9295,32010,Female,Loyal Customer,14,Personal Travel,Business,102,2,3,2,4,2,2,2,2,1,2,4,1,4,2,1,3.0,neutral or dissatisfied +9296,45231,Female,disloyal Customer,26,Business travel,Eco,911,2,2,2,4,4,2,4,4,4,4,3,1,4,4,59,46.0,neutral or dissatisfied +9297,21083,Male,disloyal Customer,61,Business travel,Business,227,1,1,1,4,4,1,4,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +9298,3408,Male,Loyal Customer,47,Personal Travel,Eco,213,1,2,1,1,3,1,2,3,5,3,5,4,5,3,0,4.0,neutral or dissatisfied +9299,111374,Male,disloyal Customer,39,Business travel,Eco,1050,3,3,3,2,2,3,3,2,3,5,2,2,3,2,21,16.0,neutral or dissatisfied +9300,109078,Male,Loyal Customer,44,Personal Travel,Eco,972,3,5,3,3,2,3,2,2,4,3,5,4,5,2,11,41.0,neutral or dissatisfied +9301,67080,Male,Loyal Customer,59,Business travel,Eco,929,3,1,1,1,3,3,3,3,4,3,4,1,4,3,41,81.0,neutral or dissatisfied +9302,53059,Male,Loyal Customer,59,Personal Travel,Eco,1208,1,1,1,4,5,1,5,5,1,1,3,1,4,5,0,0.0,neutral or dissatisfied +9303,128054,Female,Loyal Customer,63,Personal Travel,Eco,735,1,1,1,4,5,4,3,1,1,1,1,4,1,1,11,8.0,neutral or dissatisfied +9304,85612,Female,Loyal Customer,31,Personal Travel,Eco,259,3,4,3,2,1,3,1,1,1,1,4,1,3,1,0,0.0,neutral or dissatisfied +9305,95657,Female,Loyal Customer,59,Personal Travel,Eco,845,3,4,4,4,5,4,4,2,2,4,2,3,2,4,0,0.0,neutral or dissatisfied +9306,25909,Female,Loyal Customer,26,Business travel,Business,3808,3,3,5,3,4,4,4,4,4,2,4,3,5,4,27,28.0,satisfied +9307,35546,Male,Loyal Customer,29,Personal Travel,Eco,1035,1,4,1,3,5,1,5,5,4,2,5,5,4,5,7,0.0,neutral or dissatisfied +9308,16090,Female,Loyal Customer,34,Business travel,Business,2231,1,4,4,4,4,3,4,1,1,1,1,3,1,3,0,3.0,neutral or dissatisfied +9309,99186,Male,Loyal Customer,46,Personal Travel,Eco,351,3,4,3,3,3,3,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +9310,11486,Female,Loyal Customer,40,Personal Travel,Eco Plus,247,2,4,2,1,1,2,1,1,5,3,4,5,4,1,20,22.0,neutral or dissatisfied +9311,113158,Male,Loyal Customer,45,Business travel,Eco,677,3,5,4,5,3,3,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +9312,68146,Male,Loyal Customer,44,Business travel,Business,2670,1,1,1,1,4,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +9313,62250,Male,Loyal Customer,55,Personal Travel,Eco,2425,2,4,2,1,5,2,5,5,3,5,3,4,4,5,0,0.0,neutral or dissatisfied +9314,114672,Female,disloyal Customer,22,Business travel,Eco,342,4,5,4,3,5,4,5,5,3,5,4,4,5,5,2,0.0,satisfied +9315,10620,Female,Loyal Customer,45,Business travel,Eco,74,1,3,3,3,3,4,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +9316,106981,Male,Loyal Customer,51,Personal Travel,Eco,1036,4,3,4,2,4,4,4,4,2,1,2,3,2,4,16,1.0,satisfied +9317,69512,Male,disloyal Customer,26,Business travel,Business,2586,5,5,5,1,5,5,2,3,2,4,5,2,3,2,7,39.0,satisfied +9318,29188,Female,Loyal Customer,33,Personal Travel,Eco Plus,954,3,1,3,4,4,3,4,4,3,5,3,1,4,4,0,3.0,neutral or dissatisfied +9319,22154,Male,Loyal Customer,55,Business travel,Eco,533,4,2,2,2,4,4,4,4,5,2,1,5,5,4,17,5.0,satisfied +9320,43280,Male,disloyal Customer,20,Business travel,Eco,463,4,2,4,4,3,4,2,3,2,1,4,3,4,3,0,0.0,neutral or dissatisfied +9321,105731,Male,disloyal Customer,29,Business travel,Eco,919,3,3,3,3,2,3,2,2,3,5,2,4,3,2,45,25.0,neutral or dissatisfied +9322,26614,Female,Loyal Customer,28,Business travel,Business,1529,4,4,4,4,4,5,4,4,5,3,2,2,2,4,1,0.0,satisfied +9323,63163,Male,Loyal Customer,45,Business travel,Business,3309,1,1,1,1,4,5,5,5,5,4,5,3,5,4,4,0.0,satisfied +9324,106431,Female,Loyal Customer,43,Business travel,Business,3364,4,4,5,4,4,5,5,4,4,4,4,4,4,4,7,0.0,satisfied +9325,96504,Male,Loyal Customer,53,Business travel,Eco,444,2,5,2,5,2,2,2,2,2,2,3,1,4,2,0,0.0,neutral or dissatisfied +9326,112559,Male,Loyal Customer,66,Personal Travel,Eco Plus,948,2,2,2,4,5,2,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +9327,68587,Male,Loyal Customer,52,Personal Travel,Eco,1616,1,5,1,4,5,1,5,5,4,2,4,3,4,5,39,20.0,neutral or dissatisfied +9328,71293,Male,Loyal Customer,45,Personal Travel,Eco Plus,733,3,4,3,2,3,3,5,3,3,2,2,3,5,3,84,86.0,neutral or dissatisfied +9329,21552,Female,Loyal Customer,23,Personal Travel,Eco,164,2,2,0,3,4,0,4,4,1,2,4,2,4,4,0,0.0,neutral or dissatisfied +9330,119045,Female,disloyal Customer,27,Business travel,Business,2279,5,5,5,5,5,5,5,5,4,5,4,4,4,5,0,0.0,satisfied +9331,4583,Male,Loyal Customer,46,Business travel,Eco,416,3,2,5,5,4,3,4,4,1,1,2,1,1,4,19,17.0,neutral or dissatisfied +9332,21968,Male,disloyal Customer,25,Business travel,Eco,448,2,5,2,1,4,2,4,4,4,1,3,4,4,4,87,83.0,neutral or dissatisfied +9333,4367,Male,Loyal Customer,44,Business travel,Business,2974,3,1,1,1,2,4,4,3,3,3,3,1,3,2,47,41.0,neutral or dissatisfied +9334,113028,Female,disloyal Customer,25,Business travel,Business,543,3,0,3,5,4,3,4,4,3,3,5,4,4,4,51,41.0,neutral or dissatisfied +9335,71964,Female,Loyal Customer,46,Business travel,Business,1440,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +9336,68970,Female,disloyal Customer,25,Business travel,Business,700,3,4,3,2,2,3,5,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +9337,109978,Male,Loyal Customer,23,Personal Travel,Eco,1092,2,1,1,2,1,1,1,1,3,1,2,3,2,1,4,0.0,neutral or dissatisfied +9338,67167,Male,Loyal Customer,46,Personal Travel,Eco,964,3,4,3,4,3,3,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +9339,86516,Female,Loyal Customer,23,Personal Travel,Eco,762,3,5,3,3,3,3,3,3,4,5,5,5,4,3,0,0.0,neutral or dissatisfied +9340,125219,Male,Loyal Customer,70,Personal Travel,Eco,651,4,5,4,5,1,4,2,1,5,1,3,4,2,1,7,6.0,neutral or dissatisfied +9341,39256,Female,Loyal Customer,70,Business travel,Eco,268,3,4,4,4,2,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +9342,34691,Male,Loyal Customer,24,Business travel,Business,301,5,5,5,5,4,4,4,4,4,3,2,1,2,4,125,112.0,satisfied +9343,84546,Female,Loyal Customer,49,Personal Travel,Eco,2486,4,3,4,3,3,4,3,5,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +9344,108689,Female,Loyal Customer,28,Business travel,Business,2253,3,1,1,1,3,3,3,3,4,2,3,2,4,3,2,0.0,neutral or dissatisfied +9345,108470,Female,Loyal Customer,61,Personal Travel,Eco,1444,2,4,2,2,5,5,4,1,1,2,1,5,1,5,31,9.0,neutral or dissatisfied +9346,60690,Female,Loyal Customer,49,Business travel,Business,1605,4,4,4,4,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +9347,17095,Male,Loyal Customer,17,Business travel,Business,3088,5,5,5,5,5,5,5,5,2,1,1,2,2,5,0,0.0,satisfied +9348,81991,Male,Loyal Customer,57,Business travel,Business,1589,3,3,4,3,3,3,5,3,3,3,3,5,3,3,0,0.0,satisfied +9349,50519,Female,Loyal Customer,34,Personal Travel,Eco,78,2,5,2,2,4,2,4,4,4,4,5,4,4,4,127,125.0,neutral or dissatisfied +9350,2477,Female,Loyal Customer,32,Personal Travel,Eco Plus,701,1,1,1,3,2,1,2,2,4,3,4,3,3,2,12,8.0,neutral or dissatisfied +9351,851,Male,Loyal Customer,39,Business travel,Business,309,2,4,4,4,2,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +9352,90015,Male,disloyal Customer,18,Business travel,Eco,983,4,4,4,3,5,4,5,5,4,4,5,3,4,5,0,0.0,satisfied +9353,58618,Female,Loyal Customer,54,Business travel,Business,235,3,3,3,3,5,3,1,4,4,4,4,5,4,1,1,0.0,satisfied +9354,70322,Female,Loyal Customer,52,Business travel,Business,3002,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +9355,51399,Male,Loyal Customer,44,Personal Travel,Eco Plus,209,4,3,4,4,3,4,3,3,2,4,4,2,3,3,0,0.0,neutral or dissatisfied +9356,63950,Male,Loyal Customer,45,Personal Travel,Eco,1192,2,5,2,4,2,2,2,2,4,5,4,3,4,2,1,36.0,neutral or dissatisfied +9357,129715,Female,Loyal Customer,41,Business travel,Business,337,3,3,3,3,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +9358,12615,Female,Loyal Customer,45,Business travel,Business,1843,2,1,1,1,5,2,2,2,2,2,2,1,2,1,75,65.0,neutral or dissatisfied +9359,122954,Female,Loyal Customer,12,Business travel,Business,650,5,5,5,5,2,2,2,2,5,2,4,3,4,2,13,24.0,satisfied +9360,21658,Male,Loyal Customer,22,Business travel,Business,746,2,2,2,2,4,4,4,4,2,4,4,4,5,4,1,2.0,satisfied +9361,21814,Male,Loyal Customer,13,Personal Travel,Eco,341,3,5,3,4,3,3,3,3,5,2,5,2,3,3,10,0.0,neutral or dissatisfied +9362,35341,Female,Loyal Customer,25,Business travel,Business,3559,4,4,4,4,5,5,5,5,3,1,4,3,5,5,0,0.0,satisfied +9363,78855,Female,Loyal Customer,39,Personal Travel,Eco Plus,432,3,4,3,3,2,3,2,2,5,5,5,4,4,2,0,0.0,neutral or dissatisfied +9364,127757,Female,Loyal Customer,65,Personal Travel,Eco,255,2,1,2,4,3,3,3,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +9365,65922,Male,Loyal Customer,47,Personal Travel,Eco,569,2,5,2,2,5,2,5,5,4,4,4,3,4,5,0,4.0,neutral or dissatisfied +9366,114308,Male,Loyal Customer,59,Personal Travel,Eco,909,3,4,3,4,3,3,3,3,1,5,3,1,5,3,0,0.0,neutral or dissatisfied +9367,30955,Male,Loyal Customer,43,Business travel,Business,624,2,5,5,5,3,3,3,2,2,2,2,3,2,2,12,38.0,neutral or dissatisfied +9368,69609,Female,Loyal Customer,51,Personal Travel,Eco,2446,3,4,3,1,3,4,4,3,4,5,4,4,4,4,0,25.0,neutral or dissatisfied +9369,110920,Male,Loyal Customer,10,Personal Travel,Eco,581,3,1,3,3,1,3,1,1,3,2,3,4,4,1,5,0.0,neutral or dissatisfied +9370,21845,Male,Loyal Customer,58,Business travel,Business,551,2,5,3,5,3,3,3,2,2,2,2,2,2,2,34,31.0,neutral or dissatisfied +9371,60010,Female,Loyal Customer,66,Personal Travel,Eco,937,2,3,2,3,1,3,3,2,2,2,2,1,2,4,6,0.0,neutral or dissatisfied +9372,24667,Female,disloyal Customer,27,Business travel,Eco Plus,834,1,2,2,3,5,2,5,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +9373,32033,Male,Loyal Customer,43,Business travel,Eco,102,5,5,5,5,5,5,5,5,4,5,2,5,4,5,0,0.0,satisfied +9374,21779,Female,Loyal Customer,35,Business travel,Business,241,3,3,3,3,4,4,5,5,5,5,5,3,5,1,48,41.0,satisfied +9375,93311,Male,Loyal Customer,37,Personal Travel,Eco,1733,3,4,3,1,5,3,5,5,5,4,4,3,3,5,0,0.0,neutral or dissatisfied +9376,8967,Female,Loyal Customer,42,Business travel,Business,3943,5,5,5,5,3,5,5,3,3,3,3,4,3,4,20,43.0,satisfied +9377,39231,Male,Loyal Customer,25,Business travel,Business,268,0,0,0,1,2,2,2,2,2,3,3,5,1,2,0,0.0,satisfied +9378,92387,Female,Loyal Customer,49,Business travel,Business,1892,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +9379,33236,Male,Loyal Customer,54,Business travel,Eco Plus,201,2,3,3,3,2,2,2,2,3,5,3,2,3,2,0,10.0,neutral or dissatisfied +9380,98785,Male,Loyal Customer,28,Business travel,Eco,630,2,4,4,4,2,2,2,2,3,5,4,1,3,2,20,8.0,neutral or dissatisfied +9381,72950,Male,Loyal Customer,45,Business travel,Eco,1089,3,3,3,3,3,3,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +9382,17883,Male,Loyal Customer,16,Personal Travel,Eco,371,2,4,3,1,3,3,3,3,3,3,3,3,5,3,6,0.0,neutral or dissatisfied +9383,71994,Female,Loyal Customer,46,Personal Travel,Eco,1440,3,4,3,4,2,4,3,3,3,3,3,1,3,3,0,9.0,neutral or dissatisfied +9384,116279,Male,Loyal Customer,46,Personal Travel,Eco,337,2,3,2,4,3,2,3,3,5,4,5,1,2,3,0,0.0,neutral or dissatisfied +9385,104048,Male,Loyal Customer,41,Personal Travel,Eco,1262,2,5,2,4,2,2,2,2,4,5,4,5,4,2,8,3.0,neutral or dissatisfied +9386,67901,Male,Loyal Customer,65,Personal Travel,Eco,1235,4,5,4,1,5,4,5,5,5,5,5,5,4,5,0,0.0,satisfied +9387,39856,Male,Loyal Customer,44,Business travel,Business,3597,3,5,5,5,1,4,4,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +9388,8985,Female,Loyal Customer,58,Personal Travel,Eco,725,2,1,2,2,1,2,2,3,3,2,3,4,3,4,0,0.0,neutral or dissatisfied +9389,85178,Female,Loyal Customer,39,Business travel,Business,2523,5,4,5,5,3,4,4,5,5,5,5,4,5,4,0,2.0,satisfied +9390,64656,Female,disloyal Customer,37,Business travel,Business,282,3,3,3,3,5,3,5,5,4,3,5,5,4,5,64,65.0,satisfied +9391,50608,Male,Loyal Customer,32,Personal Travel,Eco,207,3,3,3,3,2,3,2,2,2,2,4,1,4,2,17,13.0,neutral or dissatisfied +9392,80554,Female,Loyal Customer,41,Business travel,Business,1747,5,5,3,5,3,4,4,3,3,4,3,5,3,5,17,0.0,satisfied +9393,117250,Female,Loyal Customer,46,Personal Travel,Eco,338,3,5,5,4,4,4,4,4,4,5,4,4,4,3,49,24.0,neutral or dissatisfied +9394,125973,Male,Loyal Customer,42,Business travel,Business,600,4,4,2,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +9395,8527,Female,Loyal Customer,41,Personal Travel,Eco,862,3,4,3,1,2,3,2,2,5,3,4,5,4,2,7,12.0,neutral or dissatisfied +9396,68509,Male,Loyal Customer,54,Business travel,Business,1067,2,2,2,2,3,5,4,5,5,5,5,3,5,4,3,12.0,satisfied +9397,82346,Male,Loyal Customer,51,Business travel,Business,1570,5,5,5,5,4,5,4,4,4,4,4,4,4,3,120,111.0,satisfied +9398,72604,Male,Loyal Customer,33,Personal Travel,Eco,929,5,4,5,3,3,5,3,3,4,2,4,4,5,3,0,2.0,satisfied +9399,114331,Female,Loyal Customer,11,Personal Travel,Eco,948,4,0,4,1,3,4,3,3,5,2,4,5,5,3,11,5.0,neutral or dissatisfied +9400,55586,Female,Loyal Customer,57,Personal Travel,Eco,1091,1,5,1,4,2,2,3,5,5,1,5,2,5,2,34,24.0,neutral or dissatisfied +9401,108751,Female,Loyal Customer,34,Business travel,Business,1582,4,4,4,4,3,4,4,5,5,5,5,3,5,4,12,31.0,satisfied +9402,115977,Male,Loyal Customer,68,Personal Travel,Eco,404,2,4,2,3,5,2,1,5,3,2,5,4,5,5,1,0.0,neutral or dissatisfied +9403,3497,Female,Loyal Customer,26,Personal Travel,Eco,1080,4,4,4,5,4,4,4,4,3,5,5,5,4,4,5,7.0,neutral or dissatisfied +9404,2383,Female,Loyal Customer,39,Business travel,Business,604,3,3,3,3,4,5,5,4,4,4,4,3,4,5,31,41.0,satisfied +9405,45214,Female,Loyal Customer,33,Business travel,Business,1512,3,3,5,3,1,2,1,2,2,2,2,1,2,1,0,0.0,satisfied +9406,6545,Male,disloyal Customer,23,Business travel,Business,473,4,0,4,4,5,4,5,5,3,5,5,5,5,5,0,0.0,satisfied +9407,46945,Female,Loyal Customer,20,Personal Travel,Eco,916,0,5,0,4,3,0,1,3,5,3,4,3,2,3,0,0.0,satisfied +9408,38955,Female,disloyal Customer,26,Business travel,Eco,1265,4,4,4,2,3,4,3,3,4,3,4,1,3,3,5,13.0,satisfied +9409,71274,Female,Loyal Customer,66,Personal Travel,Eco,733,4,2,4,3,3,2,3,5,5,4,5,2,5,4,23,10.0,neutral or dissatisfied +9410,113157,Male,Loyal Customer,67,Business travel,Business,677,4,1,4,4,3,5,4,5,5,5,5,5,5,4,7,0.0,satisfied +9411,120033,Female,Loyal Customer,63,Personal Travel,Eco Plus,511,5,5,5,5,3,4,5,3,3,5,3,4,3,4,9,0.0,satisfied +9412,100643,Female,Loyal Customer,25,Personal Travel,Eco,349,3,5,1,5,3,1,3,3,5,4,2,4,1,3,0,25.0,neutral or dissatisfied +9413,24291,Male,Loyal Customer,52,Personal Travel,Eco,302,2,5,2,5,5,2,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +9414,65329,Female,Loyal Customer,55,Business travel,Business,631,2,2,5,2,2,5,4,2,2,2,2,4,2,5,0,0.0,satisfied +9415,4757,Male,Loyal Customer,57,Personal Travel,Business,403,2,2,2,3,2,3,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +9416,73395,Male,Loyal Customer,32,Business travel,Business,1182,1,0,0,3,5,0,4,5,3,3,4,1,4,5,0,0.0,neutral or dissatisfied +9417,20275,Female,Loyal Customer,67,Personal Travel,Eco,235,2,1,2,3,1,2,2,3,3,2,5,3,3,4,34,15.0,neutral or dissatisfied +9418,56126,Female,disloyal Customer,26,Business travel,Business,1400,4,4,4,1,3,4,3,3,4,3,4,3,4,3,38,31.0,satisfied +9419,9591,Female,Loyal Customer,63,Personal Travel,Eco,292,4,5,4,2,2,5,4,2,2,4,2,4,2,5,0,0.0,satisfied +9420,8998,Male,Loyal Customer,60,Personal Travel,Eco,297,3,2,3,3,4,3,4,4,4,1,4,1,4,4,1,0.0,neutral or dissatisfied +9421,106665,Male,Loyal Customer,52,Personal Travel,Eco,1590,2,4,2,2,3,2,3,3,5,2,5,4,4,3,0,11.0,neutral or dissatisfied +9422,5646,Male,Loyal Customer,57,Personal Travel,Business,147,3,5,3,5,4,5,4,2,2,3,2,2,2,1,14,7.0,neutral or dissatisfied +9423,25592,Female,Loyal Customer,49,Personal Travel,Eco,696,2,5,2,4,4,2,4,5,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +9424,96558,Female,Loyal Customer,11,Personal Travel,Eco Plus,302,4,5,4,3,5,4,5,5,5,5,5,3,5,5,42,36.0,neutral or dissatisfied +9425,50447,Female,Loyal Customer,76,Business travel,Business,3689,0,4,0,2,3,2,5,1,1,3,3,1,1,3,0,0.0,satisfied +9426,128847,Male,Loyal Customer,64,Personal Travel,Eco,2586,3,5,3,4,3,2,2,5,5,4,4,2,5,2,11,5.0,neutral or dissatisfied +9427,104052,Female,Loyal Customer,8,Personal Travel,Eco,1044,2,2,2,4,4,2,4,4,4,2,3,3,3,4,32,19.0,neutral or dissatisfied +9428,33862,Female,Loyal Customer,36,Personal Travel,Eco,1698,3,2,2,3,3,2,3,3,4,5,2,2,2,3,0,0.0,neutral or dissatisfied +9429,87466,Male,Loyal Customer,54,Business travel,Business,2607,5,5,5,5,2,5,5,5,5,5,5,3,5,3,5,8.0,satisfied +9430,85796,Male,Loyal Customer,50,Business travel,Business,126,0,4,0,2,5,3,3,4,4,4,4,5,4,4,2,0.0,satisfied +9431,29196,Female,Loyal Customer,27,Personal Travel,Eco Plus,937,2,5,2,2,2,2,2,2,5,3,4,4,4,2,6,0.0,neutral or dissatisfied +9432,93655,Female,Loyal Customer,46,Business travel,Eco Plus,547,2,2,2,2,2,4,4,2,2,2,2,1,2,1,3,0.0,neutral or dissatisfied +9433,24301,Male,Loyal Customer,41,Business travel,Eco Plus,147,5,5,5,5,5,5,5,4,4,2,2,5,5,5,89,134.0,satisfied +9434,22861,Male,Loyal Customer,12,Personal Travel,Eco,147,2,4,2,4,2,2,2,2,3,4,5,4,4,2,4,0.0,neutral or dissatisfied +9435,112798,Female,Loyal Customer,43,Business travel,Business,3719,4,4,4,4,5,4,5,3,3,3,3,4,3,5,6,0.0,satisfied +9436,16037,Female,Loyal Customer,51,Business travel,Eco Plus,780,5,1,1,1,5,5,5,1,2,4,5,5,4,5,228,212.0,satisfied +9437,98672,Female,Loyal Customer,36,Personal Travel,Eco,834,1,1,1,3,2,1,2,2,3,5,4,1,3,2,45,46.0,neutral or dissatisfied +9438,30256,Female,Loyal Customer,35,Business travel,Eco,1024,4,2,2,2,4,4,4,4,3,1,2,5,1,4,31,17.0,satisfied +9439,110534,Female,Loyal Customer,48,Business travel,Business,3074,4,4,4,4,3,5,4,4,4,4,4,5,4,5,8,0.0,satisfied +9440,7646,Male,Loyal Customer,49,Business travel,Business,2032,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,8.0,satisfied +9441,119701,Male,Loyal Customer,30,Business travel,Business,3919,3,3,3,3,3,3,3,3,5,3,5,3,5,3,0,0.0,satisfied +9442,101473,Male,Loyal Customer,28,Business travel,Business,2788,2,2,2,2,2,2,2,2,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +9443,28778,Male,Loyal Customer,50,Business travel,Business,679,5,5,5,5,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +9444,17675,Male,Loyal Customer,32,Personal Travel,Eco,282,3,2,3,3,1,3,1,1,4,5,3,4,3,1,0,5.0,neutral or dissatisfied +9445,86433,Male,Loyal Customer,57,Business travel,Business,762,2,2,2,2,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +9446,88124,Female,Loyal Customer,50,Business travel,Business,3953,0,1,1,2,3,4,4,4,4,3,3,3,4,3,0,0.0,satisfied +9447,75237,Female,Loyal Customer,47,Personal Travel,Eco,1744,1,1,1,3,4,2,2,3,3,1,5,1,3,1,24,37.0,neutral or dissatisfied +9448,24657,Female,disloyal Customer,28,Business travel,Eco,873,3,3,3,3,4,3,4,4,3,5,5,1,4,4,0,0.0,neutral or dissatisfied +9449,44509,Female,Loyal Customer,32,Business travel,Business,2045,4,4,4,4,4,5,4,4,4,3,4,5,4,4,11,8.0,satisfied +9450,115000,Male,Loyal Customer,50,Business travel,Business,2097,5,5,3,5,4,4,4,4,4,4,4,5,4,5,53,46.0,satisfied +9451,14242,Female,Loyal Customer,22,Business travel,Business,2331,2,2,2,2,4,4,4,4,5,4,1,3,2,4,82,73.0,satisfied +9452,126242,Male,Loyal Customer,69,Business travel,Business,3044,4,4,3,4,3,4,3,1,1,1,4,2,1,3,0,0.0,neutral or dissatisfied +9453,12015,Male,Loyal Customer,7,Personal Travel,Business,376,3,5,3,1,2,3,3,2,4,5,5,5,5,2,57,54.0,neutral or dissatisfied +9454,124840,Female,Loyal Customer,21,Personal Travel,Eco,280,3,4,3,3,1,3,1,1,5,3,4,5,5,1,0,0.0,neutral or dissatisfied +9455,31346,Male,Loyal Customer,29,Business travel,Eco,1069,5,4,4,4,5,5,5,5,1,1,2,1,3,5,8,10.0,satisfied +9456,50269,Female,Loyal Customer,54,Business travel,Business,2403,2,4,4,4,1,4,4,3,3,3,2,1,3,3,0,1.0,neutral or dissatisfied +9457,84328,Female,Loyal Customer,30,Business travel,Business,3498,3,5,5,5,3,3,3,3,4,1,4,2,4,3,0,0.0,neutral or dissatisfied +9458,33855,Male,Loyal Customer,15,Personal Travel,Eco,1609,2,5,2,3,4,2,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +9459,83837,Female,Loyal Customer,78,Business travel,Business,425,2,1,1,1,4,4,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +9460,122033,Male,Loyal Customer,42,Business travel,Business,130,0,5,0,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +9461,32722,Male,Loyal Customer,40,Business travel,Business,3223,0,5,0,4,3,2,5,3,3,3,3,1,3,1,0,0.0,satisfied +9462,104063,Female,Loyal Customer,26,Personal Travel,Eco,1044,1,5,1,5,3,1,3,3,5,5,3,2,3,3,20,0.0,neutral or dissatisfied +9463,26298,Female,disloyal Customer,29,Business travel,Eco,1199,3,4,4,4,3,4,1,3,3,5,4,2,3,3,17,35.0,neutral or dissatisfied +9464,67400,Male,disloyal Customer,30,Business travel,Business,678,2,2,2,3,2,2,2,2,4,2,5,3,5,2,48,43.0,neutral or dissatisfied +9465,39192,Male,Loyal Customer,25,Business travel,Business,1769,2,2,2,2,5,5,5,5,3,1,4,5,2,5,0,0.0,satisfied +9466,35692,Male,disloyal Customer,27,Business travel,Eco,1210,2,2,2,3,2,5,2,2,3,3,3,2,2,2,31,16.0,neutral or dissatisfied +9467,119964,Male,Loyal Customer,50,Personal Travel,Eco,868,3,5,3,4,2,3,2,2,2,3,1,3,1,2,0,3.0,neutral or dissatisfied +9468,66753,Female,Loyal Customer,53,Personal Travel,Eco,802,3,5,3,3,2,2,5,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +9469,28101,Female,disloyal Customer,25,Business travel,Eco,933,3,3,3,3,4,3,4,4,5,1,1,2,1,4,0,0.0,neutral or dissatisfied +9470,42957,Female,Loyal Customer,51,Business travel,Eco,192,4,1,1,1,2,5,1,4,4,4,4,5,4,3,0,0.0,satisfied +9471,120248,Female,Loyal Customer,14,Personal Travel,Eco,1303,2,4,2,3,1,2,1,1,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +9472,71103,Male,Loyal Customer,36,Personal Travel,Eco Plus,802,4,3,4,3,2,4,4,2,4,4,3,2,4,2,15,14.0,neutral or dissatisfied +9473,101591,Male,Loyal Customer,42,Business travel,Business,1371,3,3,1,3,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +9474,42160,Female,Loyal Customer,58,Business travel,Eco,329,4,2,2,2,4,4,4,4,1,4,1,4,2,4,211,221.0,satisfied +9475,76083,Female,Loyal Customer,62,Business travel,Eco,269,5,1,1,1,4,5,1,5,5,5,5,2,5,3,0,0.0,satisfied +9476,113617,Male,Loyal Customer,48,Personal Travel,Eco,258,3,3,3,2,3,3,3,3,1,3,3,4,2,3,0,0.0,neutral or dissatisfied +9477,18798,Female,Loyal Customer,51,Business travel,Eco,448,3,4,4,4,5,2,5,3,3,3,3,4,3,1,0,0.0,satisfied +9478,72100,Male,Loyal Customer,37,Personal Travel,Eco,2486,3,1,3,2,4,3,4,4,2,3,2,3,2,4,11,0.0,neutral or dissatisfied +9479,104442,Male,Loyal Customer,40,Personal Travel,Eco,1011,2,2,2,2,3,2,3,3,4,2,3,3,2,3,0,0.0,neutral or dissatisfied +9480,16953,Female,Loyal Customer,41,Business travel,Business,116,2,2,2,2,3,1,5,5,5,5,4,4,5,1,0,0.0,satisfied +9481,22539,Female,Loyal Customer,58,Personal Travel,Eco Plus,208,4,3,4,2,2,4,2,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +9482,89349,Female,disloyal Customer,39,Business travel,Eco,1187,2,2,2,3,1,2,1,1,1,4,3,2,4,1,0,0.0,neutral or dissatisfied +9483,78287,Female,Loyal Customer,25,Business travel,Business,1598,3,3,3,3,5,5,5,5,4,5,3,3,4,5,0,0.0,satisfied +9484,18209,Male,Loyal Customer,43,Business travel,Business,2743,3,3,3,3,5,1,1,4,4,4,4,1,4,5,9,59.0,satisfied +9485,4654,Female,Loyal Customer,43,Business travel,Business,3078,0,0,0,2,5,5,5,4,4,3,3,3,4,5,0,0.0,satisfied +9486,87169,Female,Loyal Customer,47,Business travel,Business,3395,2,2,3,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +9487,43933,Female,Loyal Customer,37,Business travel,Eco Plus,255,5,3,3,3,5,5,5,5,4,5,4,3,1,5,0,0.0,satisfied +9488,117613,Male,disloyal Customer,22,Business travel,Eco,472,1,3,1,4,2,1,4,2,2,2,4,2,4,2,2,0.0,neutral or dissatisfied +9489,79823,Male,disloyal Customer,35,Business travel,Business,1096,2,2,2,2,5,2,2,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +9490,102829,Male,disloyal Customer,39,Business travel,Business,423,4,4,4,1,2,4,2,2,3,5,4,4,4,2,7,0.0,satisfied +9491,49323,Male,Loyal Customer,46,Business travel,Business,1512,1,1,1,1,1,4,1,5,5,5,5,4,5,4,0,56.0,satisfied +9492,47498,Female,Loyal Customer,68,Personal Travel,Eco,558,1,5,1,4,5,4,5,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +9493,70896,Male,Loyal Customer,46,Business travel,Business,1721,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +9494,74506,Female,disloyal Customer,29,Business travel,Eco,1235,3,3,3,4,1,3,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +9495,95524,Male,Loyal Customer,23,Personal Travel,Eco Plus,293,5,5,5,1,3,5,1,3,1,1,3,3,3,3,0,0.0,satisfied +9496,79265,Male,Loyal Customer,70,Personal Travel,Eco,1598,4,2,5,4,2,5,2,2,2,1,3,1,3,2,0,19.0,neutral or dissatisfied +9497,1797,Male,disloyal Customer,44,Business travel,Business,408,3,3,3,3,1,3,1,1,5,5,4,3,5,1,80,121.0,neutral or dissatisfied +9498,12611,Male,Loyal Customer,39,Business travel,Eco Plus,142,3,5,2,2,3,3,3,3,2,2,4,3,4,3,27,18.0,neutral or dissatisfied +9499,100335,Male,Loyal Customer,33,Business travel,Business,1130,2,2,2,2,4,4,4,4,2,5,3,5,4,4,14,2.0,satisfied +9500,85821,Male,Loyal Customer,29,Personal Travel,Eco,666,3,3,3,3,3,3,3,3,3,5,2,1,2,3,0,21.0,neutral or dissatisfied +9501,117046,Female,Loyal Customer,29,Business travel,Business,646,1,2,2,2,1,1,1,1,1,5,4,4,4,1,124,131.0,neutral or dissatisfied +9502,92712,Male,Loyal Customer,21,Personal Travel,Eco Plus,2153,4,4,3,4,5,3,5,5,5,3,4,4,5,5,1,0.0,neutral or dissatisfied +9503,65009,Male,Loyal Customer,35,Business travel,Eco,247,4,3,3,3,4,4,4,4,3,2,1,1,3,4,0,0.0,satisfied +9504,101912,Male,Loyal Customer,21,Personal Travel,Eco,1984,2,2,2,4,3,2,1,3,1,3,3,1,4,3,33,6.0,neutral or dissatisfied +9505,82874,Female,Loyal Customer,26,Business travel,Business,2971,1,1,1,1,4,4,4,4,3,5,5,4,5,4,4,0.0,satisfied +9506,95533,Male,Loyal Customer,29,Personal Travel,Eco Plus,677,2,1,2,3,1,2,1,1,4,4,4,4,4,1,15,5.0,neutral or dissatisfied +9507,24507,Female,Loyal Customer,28,Personal Travel,Eco,516,1,1,1,3,2,1,5,2,4,3,2,1,2,2,0,0.0,neutral or dissatisfied +9508,126684,Male,Loyal Customer,54,Business travel,Business,2402,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +9509,65645,Female,disloyal Customer,20,Business travel,Eco,926,4,4,4,3,3,4,3,3,1,5,3,3,3,3,20,0.0,neutral or dissatisfied +9510,93521,Female,Loyal Customer,56,Business travel,Business,3565,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,9.0,satisfied +9511,75084,Female,disloyal Customer,30,Business travel,Business,1814,2,2,2,2,2,2,2,2,4,5,4,5,4,2,7,0.0,neutral or dissatisfied +9512,39577,Male,Loyal Customer,61,Business travel,Business,2178,1,3,3,3,4,1,2,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +9513,82504,Female,Loyal Customer,52,Personal Travel,Business,1749,3,2,2,4,1,3,3,4,4,2,3,4,4,1,18,44.0,neutral or dissatisfied +9514,36343,Male,Loyal Customer,29,Personal Travel,Eco,395,4,3,4,3,1,4,1,1,3,4,1,1,3,1,42,82.0,neutral or dissatisfied +9515,77229,Female,disloyal Customer,23,Business travel,Eco,1590,4,4,4,4,2,4,2,2,4,3,4,5,5,2,4,0.0,satisfied +9516,129798,Female,Loyal Customer,43,Personal Travel,Eco,308,2,4,2,2,3,5,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +9517,35753,Female,Loyal Customer,35,Business travel,Eco,1608,4,1,1,1,4,4,4,4,2,4,5,3,3,4,0,0.0,satisfied +9518,85698,Female,Loyal Customer,31,Business travel,Business,1547,2,1,1,1,2,2,2,2,3,3,2,2,3,2,5,0.0,neutral or dissatisfied +9519,1839,Male,Loyal Customer,39,Personal Travel,Eco,408,2,4,4,5,3,4,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +9520,83035,Male,Loyal Customer,40,Business travel,Business,1084,4,4,1,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +9521,13362,Male,Loyal Customer,32,Personal Travel,Eco,748,2,5,2,3,3,2,3,3,2,5,1,2,2,3,0,0.0,neutral or dissatisfied +9522,122731,Male,Loyal Customer,21,Business travel,Business,2915,3,3,3,3,3,4,3,3,4,3,4,3,5,3,0,0.0,satisfied +9523,106932,Male,disloyal Customer,24,Business travel,Eco,937,5,5,5,3,2,5,2,2,4,5,5,3,4,2,89,75.0,satisfied +9524,73392,Female,disloyal Customer,20,Business travel,Business,1005,4,4,4,3,1,4,1,1,4,2,5,4,4,1,0,0.0,satisfied +9525,109966,Female,Loyal Customer,22,Personal Travel,Eco,1011,2,2,3,4,1,3,5,1,4,3,4,3,4,1,3,0.0,neutral or dissatisfied +9526,90474,Male,Loyal Customer,40,Business travel,Business,270,3,3,3,3,3,3,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +9527,84274,Female,Loyal Customer,49,Business travel,Business,334,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +9528,63486,Female,disloyal Customer,23,Business travel,Eco,337,4,5,4,3,1,4,1,1,3,3,4,5,5,1,0,0.0,satisfied +9529,72722,Male,Loyal Customer,48,Business travel,Eco Plus,964,4,3,3,3,4,4,4,4,3,5,1,1,2,4,0,3.0,neutral or dissatisfied +9530,102780,Female,disloyal Customer,27,Business travel,Eco,1099,1,1,1,4,3,1,3,3,1,3,4,4,3,3,6,8.0,neutral or dissatisfied +9531,2187,Male,Loyal Customer,76,Business travel,Business,2282,3,2,3,3,1,4,5,4,4,4,4,2,4,4,56,42.0,satisfied +9532,26327,Female,disloyal Customer,28,Business travel,Business,834,4,4,4,5,1,4,1,1,5,5,4,3,4,1,0,0.0,satisfied +9533,21322,Female,disloyal Customer,34,Business travel,Business,761,1,1,1,5,4,1,1,4,4,4,5,5,4,4,24,22.0,neutral or dissatisfied +9534,72364,Female,Loyal Customer,57,Business travel,Business,2066,5,5,5,5,5,4,4,2,2,2,2,3,2,5,82,88.0,satisfied +9535,45614,Male,disloyal Customer,24,Business travel,Eco,313,3,4,4,4,3,4,4,3,2,3,4,1,3,3,58,48.0,neutral or dissatisfied +9536,97553,Male,Loyal Customer,39,Business travel,Eco Plus,462,5,4,4,4,5,5,5,5,1,5,1,4,4,5,0,0.0,satisfied +9537,124040,Female,Loyal Customer,50,Business travel,Business,1849,0,5,0,3,4,5,5,4,4,1,1,3,4,3,0,0.0,satisfied +9538,67166,Female,Loyal Customer,20,Personal Travel,Eco,1121,4,5,4,5,3,4,3,3,3,4,4,3,4,3,0,0.0,satisfied +9539,9517,Female,Loyal Customer,26,Business travel,Business,2605,5,5,4,5,5,5,5,5,5,5,5,5,4,5,19,60.0,satisfied +9540,122100,Female,Loyal Customer,15,Personal Travel,Eco,185,3,4,0,4,2,0,2,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +9541,53415,Male,Loyal Customer,49,Business travel,Eco,2358,4,3,3,3,4,4,4,4,3,5,4,4,2,4,7,0.0,satisfied +9542,51106,Female,Loyal Customer,53,Personal Travel,Eco,109,4,4,0,5,2,5,4,5,5,0,2,4,5,5,0,0.0,neutral or dissatisfied +9543,106618,Male,Loyal Customer,53,Business travel,Business,2858,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +9544,34759,Female,Loyal Customer,70,Business travel,Business,301,1,1,4,1,4,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +9545,114535,Female,Loyal Customer,55,Personal Travel,Business,447,2,5,2,3,3,2,2,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +9546,328,Male,Loyal Customer,56,Business travel,Business,3344,2,2,1,2,2,5,5,4,4,4,4,5,4,3,16,4.0,satisfied +9547,19487,Female,Loyal Customer,28,Personal Travel,Eco,84,4,4,0,1,2,0,2,2,3,2,4,5,4,2,22,10.0,neutral or dissatisfied +9548,38729,Female,Loyal Customer,29,Personal Travel,Business,354,3,3,3,3,5,3,5,5,2,2,2,5,5,5,0,0.0,neutral or dissatisfied +9549,71635,Male,Loyal Customer,44,Personal Travel,Eco,1012,3,5,3,3,5,3,5,5,3,4,4,4,1,5,53,102.0,neutral or dissatisfied +9550,45874,Male,Loyal Customer,27,Business travel,Business,3892,1,1,1,1,5,5,5,5,4,5,3,5,5,5,75,69.0,satisfied +9551,48822,Male,Loyal Customer,28,Personal Travel,Business,308,3,5,3,1,1,3,1,1,3,5,4,4,4,1,31,42.0,neutral or dissatisfied +9552,40118,Male,disloyal Customer,23,Business travel,Eco,422,2,1,3,3,4,3,4,4,3,5,3,2,3,4,0,0.0,neutral or dissatisfied +9553,119467,Female,disloyal Customer,45,Business travel,Business,759,3,3,3,5,5,3,5,5,5,5,4,3,5,5,53,49.0,neutral or dissatisfied +9554,33293,Female,Loyal Customer,30,Personal Travel,Eco Plus,101,3,1,3,3,3,3,4,3,2,5,3,1,2,3,5,10.0,neutral or dissatisfied +9555,17681,Female,Loyal Customer,43,Business travel,Business,1039,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +9556,93379,Female,Loyal Customer,18,Personal Travel,Business,672,5,5,5,1,3,5,3,3,5,5,4,5,5,3,0,13.0,satisfied +9557,43528,Female,disloyal Customer,22,Business travel,Eco,807,4,4,4,3,4,4,4,4,3,5,3,2,3,4,0,0.0,neutral or dissatisfied +9558,95059,Female,Loyal Customer,25,Personal Travel,Eco,323,1,2,0,2,2,0,2,2,1,3,3,2,3,2,76,70.0,neutral or dissatisfied +9559,75890,Male,Loyal Customer,60,Business travel,Business,1999,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +9560,82913,Male,Loyal Customer,48,Personal Travel,Eco,645,2,4,2,2,3,2,3,3,5,5,4,5,5,3,98,94.0,neutral or dissatisfied +9561,102055,Female,Loyal Customer,51,Personal Travel,Business,397,5,2,5,4,4,3,3,2,2,5,2,2,2,2,87,83.0,satisfied +9562,88774,Male,Loyal Customer,69,Business travel,Business,404,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +9563,41654,Female,Loyal Customer,44,Business travel,Business,1811,0,0,0,2,1,4,3,5,5,5,5,1,5,5,0,0.0,satisfied +9564,37305,Female,Loyal Customer,48,Business travel,Business,2835,4,4,4,4,4,4,4,4,4,4,4,1,4,5,10,1.0,satisfied +9565,93432,Female,Loyal Customer,52,Business travel,Eco,671,3,2,2,2,3,4,3,3,3,3,3,4,3,3,17,17.0,neutral or dissatisfied +9566,93111,Male,Loyal Customer,9,Personal Travel,Eco,903,5,2,5,4,1,5,1,1,3,3,4,2,3,1,2,0.0,satisfied +9567,14680,Male,disloyal Customer,35,Business travel,Business,419,2,2,2,4,2,2,2,2,4,5,5,3,5,2,60,26.0,neutral or dissatisfied +9568,13227,Female,disloyal Customer,49,Business travel,Eco,657,2,3,2,2,5,2,5,5,1,2,5,1,5,5,0,0.0,neutral or dissatisfied +9569,47786,Male,Loyal Customer,27,Business travel,Business,3374,4,4,4,4,4,4,4,4,4,5,5,1,5,4,0,0.0,satisfied +9570,18172,Female,disloyal Customer,25,Business travel,Eco,363,2,3,2,2,1,2,5,1,5,5,3,3,5,1,0,0.0,neutral or dissatisfied +9571,28209,Female,Loyal Customer,19,Personal Travel,Eco,834,4,5,4,1,4,4,4,4,4,3,5,4,5,4,1,0.0,satisfied +9572,37893,Male,Loyal Customer,41,Business travel,Eco,937,2,3,5,3,2,2,2,2,3,4,2,1,3,2,0,0.0,neutral or dissatisfied +9573,34534,Male,Loyal Customer,59,Business travel,Eco,636,1,3,3,3,1,1,1,1,4,4,3,4,2,1,0,17.0,neutral or dissatisfied +9574,30748,Male,disloyal Customer,24,Business travel,Eco,577,4,0,3,1,1,3,1,1,2,1,2,3,5,1,39,31.0,neutral or dissatisfied +9575,38589,Female,Loyal Customer,70,Personal Travel,Eco Plus,2475,2,3,2,3,2,4,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +9576,79925,Male,Loyal Customer,21,Business travel,Business,950,3,2,2,2,3,3,3,3,1,5,3,3,4,3,0,0.0,neutral or dissatisfied +9577,45746,Female,Loyal Customer,66,Personal Travel,Business,391,3,3,3,4,2,3,3,5,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +9578,102209,Male,Loyal Customer,37,Business travel,Business,386,4,4,4,4,2,4,4,5,5,5,5,3,5,5,28,18.0,satisfied +9579,8938,Male,Loyal Customer,50,Business travel,Business,1884,5,5,5,5,3,5,4,4,4,4,4,5,4,5,0,7.0,satisfied +9580,71918,Male,Loyal Customer,64,Personal Travel,Eco,1723,2,5,2,3,5,2,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +9581,45777,Male,Loyal Customer,40,Business travel,Business,391,2,2,2,2,5,1,5,5,5,5,5,2,5,5,0,2.0,satisfied +9582,97898,Male,Loyal Customer,51,Business travel,Business,3517,4,2,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +9583,90438,Female,Loyal Customer,49,Business travel,Business,1940,4,4,4,4,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +9584,75485,Female,Loyal Customer,69,Personal Travel,Eco,2585,3,1,3,4,2,3,4,1,1,3,1,4,1,1,0,0.0,neutral or dissatisfied +9585,51738,Female,Loyal Customer,58,Personal Travel,Eco,370,3,1,3,3,2,3,3,1,1,3,1,3,1,2,0,1.0,neutral or dissatisfied +9586,39722,Female,Loyal Customer,34,Business travel,Business,320,5,5,5,5,5,1,4,5,5,5,5,4,5,2,0,2.0,satisfied +9587,67663,Female,Loyal Customer,43,Business travel,Business,1242,3,3,1,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +9588,124939,Female,Loyal Customer,46,Personal Travel,Eco,728,3,1,4,2,2,2,2,3,3,4,1,1,3,1,0,0.0,neutral or dissatisfied +9589,124366,Male,disloyal Customer,42,Business travel,Eco,808,1,1,1,4,1,1,1,1,3,4,3,2,3,1,27,25.0,neutral or dissatisfied +9590,43975,Male,Loyal Customer,45,Business travel,Business,411,4,2,2,2,3,4,3,4,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +9591,1520,Female,Loyal Customer,53,Business travel,Business,922,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +9592,71959,Female,Loyal Customer,49,Business travel,Business,1440,4,4,4,4,3,4,4,5,5,5,5,5,5,4,3,4.0,satisfied +9593,107924,Female,disloyal Customer,25,Business travel,Business,611,5,5,5,4,5,5,1,5,5,4,4,4,5,5,72,96.0,satisfied +9594,48852,Male,Loyal Customer,56,Personal Travel,Business,262,4,4,4,1,4,4,2,1,1,4,1,3,1,3,0,0.0,neutral or dissatisfied +9595,5934,Male,Loyal Customer,53,Personal Travel,Eco,173,1,4,1,2,4,1,4,4,5,5,4,3,4,4,4,8.0,neutral or dissatisfied +9596,68453,Female,Loyal Customer,50,Business travel,Business,1303,1,1,1,1,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +9597,80330,Female,disloyal Customer,55,Personal Travel,Eco,746,5,2,5,4,1,5,5,1,1,1,3,3,4,1,0,0.0,satisfied +9598,83643,Male,disloyal Customer,26,Business travel,Business,577,2,2,2,2,3,2,5,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +9599,56153,Male,Loyal Customer,56,Business travel,Business,1400,2,2,5,2,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +9600,61280,Male,Loyal Customer,39,Personal Travel,Eco,967,1,4,1,2,5,1,5,5,3,4,4,3,4,5,24,4.0,neutral or dissatisfied +9601,101943,Female,Loyal Customer,39,Business travel,Business,3799,2,2,2,2,3,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +9602,93181,Female,Loyal Customer,47,Personal Travel,Eco,1075,3,5,3,3,2,3,1,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +9603,119941,Female,Loyal Customer,26,Business travel,Business,1930,1,1,1,1,4,4,4,4,5,5,5,3,4,4,0,0.0,satisfied +9604,81425,Female,disloyal Customer,45,Business travel,Business,393,4,4,4,4,2,4,2,2,4,2,4,4,4,2,0,0.0,satisfied +9605,117128,Female,Loyal Customer,22,Personal Travel,Eco,304,0,3,0,3,5,0,5,5,4,2,3,2,4,5,0,0.0,satisfied +9606,32648,Female,disloyal Customer,23,Business travel,Eco,163,4,4,3,4,1,3,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +9607,70277,Male,Loyal Customer,55,Business travel,Business,3117,4,4,4,4,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +9608,42518,Female,Loyal Customer,35,Personal Travel,Eco,1187,3,5,3,3,5,3,5,5,4,5,5,5,4,5,102,92.0,neutral or dissatisfied +9609,71158,Male,disloyal Customer,27,Business travel,Eco,246,3,0,3,4,4,3,4,4,1,1,4,3,2,4,0,12.0,neutral or dissatisfied +9610,58111,Female,Loyal Customer,8,Personal Travel,Eco,612,2,5,2,4,5,2,5,5,3,2,5,4,5,5,1,7.0,neutral or dissatisfied +9611,118441,Male,Loyal Customer,36,Business travel,Business,370,3,3,3,3,5,5,5,4,4,5,4,5,4,4,0,0.0,satisfied +9612,24805,Female,Loyal Customer,17,Personal Travel,Business,894,3,4,3,5,2,3,2,2,4,3,5,5,4,2,40,35.0,neutral or dissatisfied +9613,89689,Female,disloyal Customer,47,Business travel,Eco,550,2,0,2,5,3,2,3,3,1,4,1,4,2,3,6,0.0,neutral or dissatisfied +9614,65918,Female,disloyal Customer,24,Business travel,Eco,569,1,4,1,3,1,1,1,1,2,4,4,3,3,1,0,0.0,neutral or dissatisfied +9615,43227,Female,disloyal Customer,22,Business travel,Eco Plus,423,5,0,5,2,3,5,3,3,3,3,2,4,4,3,20,17.0,satisfied +9616,112264,Female,disloyal Customer,28,Business travel,Eco,1506,3,3,3,3,1,3,1,1,3,3,3,3,3,1,22,3.0,neutral or dissatisfied +9617,75706,Male,disloyal Customer,21,Business travel,Eco,813,5,5,5,1,2,5,2,2,4,2,4,3,4,2,0,0.0,satisfied +9618,21389,Male,Loyal Customer,27,Business travel,Eco,306,4,3,3,3,4,5,4,4,1,2,2,5,4,4,0,0.0,satisfied +9619,100526,Female,Loyal Customer,41,Personal Travel,Eco,759,4,5,4,4,4,4,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +9620,91011,Male,Loyal Customer,52,Personal Travel,Eco,515,2,5,2,4,3,2,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +9621,117510,Female,Loyal Customer,25,Personal Travel,Eco,507,4,2,2,2,4,2,4,4,1,3,2,4,2,4,0,0.0,satisfied +9622,67676,Female,Loyal Customer,55,Business travel,Business,1438,2,3,2,2,3,5,5,3,3,3,3,3,3,3,28,40.0,satisfied +9623,92578,Male,Loyal Customer,42,Personal Travel,Eco Plus,2139,2,1,2,2,2,2,2,2,4,5,1,2,3,2,0,0.0,neutral or dissatisfied +9624,36659,Female,Loyal Customer,33,Personal Travel,Eco,1237,2,4,2,3,5,2,3,5,5,3,4,4,4,5,3,0.0,neutral or dissatisfied +9625,28996,Female,disloyal Customer,47,Business travel,Eco,978,3,4,4,4,2,4,2,2,2,2,4,3,3,2,0,0.0,neutral or dissatisfied +9626,76272,Female,disloyal Customer,15,Business travel,Eco,823,3,3,3,3,1,3,1,1,5,4,3,3,5,1,23,2.0,neutral or dissatisfied +9627,4973,Male,Loyal Customer,60,Business travel,Business,3479,2,2,2,2,5,5,5,3,3,3,3,4,3,3,55,72.0,satisfied +9628,88938,Female,Loyal Customer,28,Business travel,Business,2270,3,3,3,3,4,4,4,4,5,2,5,3,4,4,0,0.0,satisfied +9629,16139,Female,Loyal Customer,48,Business travel,Business,212,3,3,3,3,2,4,4,4,4,4,5,3,4,5,49,51.0,satisfied +9630,123635,Female,Loyal Customer,49,Business travel,Business,214,2,2,2,2,5,5,4,4,4,4,4,4,4,3,42,42.0,satisfied +9631,23077,Female,Loyal Customer,68,Personal Travel,Eco,1174,2,3,2,4,5,2,4,5,5,2,5,4,5,4,40,24.0,neutral or dissatisfied +9632,84261,Male,Loyal Customer,47,Business travel,Business,1582,3,3,3,3,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +9633,25867,Male,Loyal Customer,39,Business travel,Eco Plus,484,1,1,5,5,1,1,1,1,2,5,3,3,4,1,0,0.0,neutral or dissatisfied +9634,81627,Male,Loyal Customer,50,Personal Travel,Eco,1142,0,4,0,3,3,0,3,3,2,4,2,1,3,3,0,0.0,satisfied +9635,64802,Female,Loyal Customer,41,Business travel,Business,2724,0,5,0,4,3,4,4,5,5,5,5,5,5,5,0,2.0,satisfied +9636,30546,Female,Loyal Customer,42,Business travel,Business,896,3,3,3,3,3,3,4,5,5,5,5,4,5,2,8,8.0,satisfied +9637,90602,Female,Loyal Customer,39,Business travel,Business,581,4,4,4,4,2,4,5,4,4,4,4,5,4,4,3,19.0,satisfied +9638,40399,Female,disloyal Customer,39,Business travel,Business,150,1,1,1,3,1,1,1,1,1,3,3,1,2,1,0,22.0,neutral or dissatisfied +9639,109175,Male,disloyal Customer,21,Business travel,Eco,793,2,2,2,1,5,2,5,5,4,5,4,5,4,5,14,0.0,neutral or dissatisfied +9640,81683,Male,Loyal Customer,54,Business travel,Eco,907,1,5,5,5,1,1,1,1,3,4,2,3,3,1,49,95.0,neutral or dissatisfied +9641,105661,Male,Loyal Customer,56,Business travel,Business,3290,1,1,1,1,2,4,5,5,5,5,5,3,5,3,4,0.0,satisfied +9642,33955,Female,disloyal Customer,31,Business travel,Eco,1554,3,4,4,2,1,3,1,1,2,2,3,5,5,1,0,0.0,neutral or dissatisfied +9643,112865,Male,disloyal Customer,26,Business travel,Business,1390,4,4,4,2,2,4,2,2,5,4,5,3,5,2,11,3.0,satisfied +9644,113894,Female,disloyal Customer,27,Business travel,Business,2295,3,3,3,3,5,3,3,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +9645,59767,Male,disloyal Customer,29,Business travel,Eco,895,3,3,3,4,5,3,5,5,3,1,4,4,3,5,28,24.0,neutral or dissatisfied +9646,8342,Female,Loyal Customer,20,Personal Travel,Eco,661,2,1,2,3,3,2,3,3,4,1,3,1,4,3,48,36.0,neutral or dissatisfied +9647,56293,Female,Loyal Customer,37,Personal Travel,Eco,2227,3,5,3,2,4,3,4,4,3,5,4,5,5,4,0,0.0,neutral or dissatisfied +9648,24829,Male,Loyal Customer,43,Business travel,Eco,828,3,4,4,4,3,3,3,3,1,5,4,3,3,3,0,4.0,neutral or dissatisfied +9649,103819,Male,Loyal Customer,32,Business travel,Business,2904,5,5,5,5,4,4,4,4,4,2,5,5,5,4,18,0.0,satisfied +9650,118510,Female,Loyal Customer,50,Business travel,Business,370,3,3,3,3,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +9651,75756,Male,Loyal Customer,23,Business travel,Eco,868,0,3,0,2,5,0,5,5,1,3,5,5,5,5,0,2.0,satisfied +9652,69083,Female,Loyal Customer,52,Personal Travel,Eco,1389,2,5,2,3,3,4,4,3,3,2,4,3,3,5,5,0.0,neutral or dissatisfied +9653,70601,Male,Loyal Customer,54,Business travel,Business,3273,4,4,4,4,5,5,5,4,3,5,3,5,3,5,56,71.0,satisfied +9654,101600,Male,Loyal Customer,47,Business travel,Business,1371,5,5,2,5,5,5,4,4,4,4,4,4,4,4,2,0.0,satisfied +9655,71805,Male,Loyal Customer,39,Business travel,Business,1726,2,2,2,2,5,5,5,4,4,4,4,5,4,3,2,0.0,satisfied +9656,75563,Female,Loyal Customer,36,Business travel,Eco,337,2,2,2,2,2,2,2,2,2,1,4,4,3,2,0,18.0,neutral or dissatisfied +9657,14111,Female,Loyal Customer,37,Business travel,Eco Plus,201,4,2,2,2,4,4,4,4,1,5,2,1,5,4,0,0.0,satisfied +9658,108963,Male,Loyal Customer,58,Business travel,Eco,542,4,3,3,3,4,4,4,4,3,2,4,1,4,4,0,0.0,neutral or dissatisfied +9659,66192,Female,Loyal Customer,60,Business travel,Business,3622,5,1,5,5,3,5,4,4,4,4,4,4,4,5,90,104.0,satisfied +9660,94423,Female,Loyal Customer,29,Business travel,Business,2363,1,1,5,1,5,5,5,5,3,2,5,5,5,5,0,0.0,satisfied +9661,28757,Male,disloyal Customer,38,Business travel,Eco,624,2,1,2,3,4,2,1,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +9662,73546,Female,Loyal Customer,41,Personal Travel,Eco,594,3,4,3,4,2,3,2,2,1,1,1,1,5,2,25,22.0,neutral or dissatisfied +9663,87886,Female,Loyal Customer,44,Business travel,Eco Plus,214,2,4,4,4,4,4,4,2,2,2,2,2,2,2,0,6.0,neutral or dissatisfied +9664,30513,Male,Loyal Customer,51,Business travel,Eco,377,5,1,1,1,5,5,5,5,5,3,5,4,5,5,1,0.0,satisfied +9665,118429,Male,Loyal Customer,51,Business travel,Business,370,2,4,2,2,3,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +9666,108162,Female,Loyal Customer,19,Personal Travel,Eco,1166,3,5,3,5,3,3,3,3,5,4,5,3,4,3,13,7.0,neutral or dissatisfied +9667,97680,Male,Loyal Customer,54,Personal Travel,Eco,491,3,5,3,3,2,3,5,2,3,2,4,4,5,2,0,3.0,neutral or dissatisfied +9668,32659,Male,Loyal Customer,38,Business travel,Business,101,3,5,5,5,2,3,3,2,2,2,3,3,2,1,6,12.0,neutral or dissatisfied +9669,30958,Female,Loyal Customer,35,Personal Travel,Eco,836,4,5,4,2,3,4,3,3,5,3,5,4,5,3,11,33.0,neutral or dissatisfied +9670,28534,Female,disloyal Customer,29,Business travel,Eco,1035,3,3,3,2,4,3,4,4,1,3,5,1,1,4,0,0.0,neutral or dissatisfied +9671,119138,Female,Loyal Customer,31,Business travel,Business,2062,3,3,5,3,5,5,5,5,5,5,5,4,5,5,0,35.0,satisfied +9672,5653,Male,Loyal Customer,54,Business travel,Business,3109,0,0,0,1,2,5,5,1,1,1,1,3,1,4,0,0.0,satisfied +9673,49341,Male,Loyal Customer,52,Business travel,Business,3201,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +9674,126291,Male,Loyal Customer,63,Personal Travel,Eco,631,4,5,4,4,4,4,4,4,2,3,4,2,5,4,20,13.0,neutral or dissatisfied +9675,88683,Female,Loyal Customer,62,Personal Travel,Eco,581,1,4,2,4,5,5,5,4,4,2,4,3,4,3,2,15.0,neutral or dissatisfied +9676,50033,Female,Loyal Customer,66,Business travel,Eco,262,3,4,4,4,2,3,3,4,4,3,4,2,4,4,21,8.0,neutral or dissatisfied +9677,80038,Male,Loyal Customer,25,Personal Travel,Eco,950,3,2,3,3,3,3,3,3,1,2,4,2,3,3,0,4.0,neutral or dissatisfied +9678,109511,Female,Loyal Customer,48,Business travel,Business,3252,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +9679,25503,Female,Loyal Customer,41,Business travel,Eco,481,4,4,4,4,3,4,3,3,2,5,2,2,2,3,0,0.0,neutral or dissatisfied +9680,58254,Female,Loyal Customer,43,Business travel,Business,2072,5,5,5,5,2,4,4,4,4,4,4,5,4,3,2,0.0,satisfied +9681,13067,Female,Loyal Customer,47,Business travel,Business,2999,4,4,4,4,4,5,4,4,4,4,4,3,4,4,18,28.0,satisfied +9682,87019,Male,Loyal Customer,27,Business travel,Eco Plus,907,3,3,3,3,3,3,3,3,4,5,4,4,3,3,0,0.0,neutral or dissatisfied +9683,82030,Female,Loyal Customer,34,Personal Travel,Eco,1535,2,5,2,5,1,2,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +9684,69613,Female,Loyal Customer,7,Personal Travel,Eco,2475,1,4,1,3,1,5,5,2,1,4,3,5,2,5,0,0.0,neutral or dissatisfied +9685,13781,Female,Loyal Customer,44,Business travel,Eco,925,4,4,4,4,4,3,2,4,4,4,4,3,4,2,0,0.0,satisfied +9686,94534,Male,Loyal Customer,40,Business travel,Business,3084,1,1,1,1,4,4,5,4,4,4,4,3,4,3,71,67.0,satisfied +9687,12850,Female,Loyal Customer,48,Personal Travel,Eco,817,2,2,2,4,5,4,4,2,2,2,2,3,2,1,2,0.0,neutral or dissatisfied +9688,117736,Female,Loyal Customer,31,Business travel,Business,833,4,4,3,4,4,4,4,4,1,5,3,2,4,4,11,0.0,neutral or dissatisfied +9689,115884,Female,Loyal Customer,16,Business travel,Business,373,3,2,2,2,3,3,3,3,3,1,4,4,4,3,14,6.0,neutral or dissatisfied +9690,19064,Female,Loyal Customer,53,Business travel,Business,3338,4,4,4,4,3,1,4,4,4,4,4,3,4,4,33,34.0,satisfied +9691,74920,Female,Loyal Customer,46,Business travel,Business,2586,1,1,1,1,5,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +9692,30220,Female,Loyal Customer,42,Business travel,Eco,406,4,2,2,2,5,4,2,4,4,4,4,5,4,5,7,46.0,satisfied +9693,74508,Male,Loyal Customer,34,Business travel,Business,3436,2,2,2,2,5,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +9694,91521,Female,Loyal Customer,47,Personal Travel,Eco,1626,2,3,2,2,3,3,1,3,3,2,5,1,3,4,0,0.0,neutral or dissatisfied +9695,52922,Female,disloyal Customer,14,Business travel,Eco,679,1,1,1,3,5,1,5,5,3,3,3,1,4,5,0,0.0,neutral or dissatisfied +9696,39975,Male,Loyal Customer,16,Business travel,Business,1404,1,5,5,5,1,1,1,1,4,2,2,2,2,1,0,10.0,neutral or dissatisfied +9697,44154,Female,Loyal Customer,43,Personal Travel,Eco Plus,120,1,3,0,4,3,3,3,1,1,0,1,3,1,1,28,18.0,neutral or dissatisfied +9698,110810,Male,Loyal Customer,40,Personal Travel,Eco,997,1,4,1,3,3,1,3,3,4,3,5,3,5,3,0,18.0,neutral or dissatisfied +9699,25373,Female,disloyal Customer,36,Business travel,Eco,591,1,1,1,3,2,1,2,2,4,5,3,3,2,2,18,14.0,neutral or dissatisfied +9700,18855,Female,Loyal Customer,53,Business travel,Business,551,1,1,1,1,3,3,4,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +9701,116313,Female,Loyal Customer,65,Personal Travel,Eco,390,3,1,3,4,5,4,3,4,4,3,4,4,4,2,2,0.0,neutral or dissatisfied +9702,9868,Female,Loyal Customer,40,Business travel,Eco Plus,717,1,2,2,2,1,2,1,1,1,3,3,3,4,1,0,17.0,neutral or dissatisfied +9703,80916,Male,Loyal Customer,51,Business travel,Business,341,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +9704,87167,Female,disloyal Customer,24,Business travel,Eco,946,2,2,2,3,4,2,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +9705,49452,Male,Loyal Customer,49,Business travel,Business,207,5,5,5,5,3,3,5,4,4,4,5,5,4,5,0,0.0,satisfied +9706,104676,Female,Loyal Customer,56,Business travel,Business,641,2,2,2,2,2,5,5,5,5,5,5,3,5,4,52,33.0,satisfied +9707,109455,Female,disloyal Customer,22,Business travel,Business,834,0,0,0,5,5,0,5,5,5,3,4,3,4,5,10,1.0,satisfied +9708,31303,Female,Loyal Customer,58,Business travel,Eco,680,4,2,2,2,3,4,5,4,4,4,4,2,4,5,10,20.0,satisfied +9709,48916,Male,disloyal Customer,26,Business travel,Eco,89,2,4,2,3,3,2,3,3,5,5,4,3,2,3,11,17.0,neutral or dissatisfied +9710,98387,Male,Loyal Customer,44,Business travel,Business,2649,3,5,5,5,2,4,4,3,3,3,3,2,3,3,0,3.0,neutral or dissatisfied +9711,29043,Male,Loyal Customer,7,Personal Travel,Eco,1050,4,1,4,4,3,4,3,3,2,4,3,4,4,3,0,0.0,satisfied +9712,43945,Female,Loyal Customer,42,Business travel,Business,473,2,2,2,2,1,1,1,4,4,4,4,2,4,3,0,0.0,satisfied +9713,50744,Male,Loyal Customer,35,Personal Travel,Eco,109,1,1,1,3,2,1,2,2,2,4,3,3,2,2,0,0.0,neutral or dissatisfied +9714,76356,Male,Loyal Customer,64,Personal Travel,Eco,1851,1,5,1,3,3,1,3,3,4,2,4,4,2,3,0,2.0,neutral or dissatisfied +9715,116027,Male,Loyal Customer,64,Personal Travel,Eco,325,2,4,2,1,5,2,4,5,4,1,5,3,5,5,0,0.0,neutral or dissatisfied +9716,24930,Female,Loyal Customer,27,Personal Travel,Eco,762,1,4,1,5,1,1,1,1,5,2,5,4,5,1,14,20.0,neutral or dissatisfied +9717,27955,Female,disloyal Customer,23,Business travel,Eco,970,2,2,2,2,3,2,3,3,4,3,4,3,1,3,0,0.0,neutral or dissatisfied +9718,95668,Male,disloyal Customer,25,Business travel,Business,1131,5,0,5,2,5,5,5,5,3,3,5,3,5,5,17,5.0,satisfied +9719,107275,Female,Loyal Customer,59,Business travel,Business,283,2,4,4,4,2,3,3,2,2,2,2,2,2,3,45,42.0,neutral or dissatisfied +9720,33574,Female,Loyal Customer,53,Business travel,Eco,399,2,1,1,1,3,4,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +9721,76543,Female,Loyal Customer,29,Business travel,Business,2280,3,3,3,3,3,3,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +9722,127409,Male,Loyal Customer,20,Personal Travel,Eco,1009,3,5,3,5,3,3,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +9723,3006,Female,Loyal Customer,43,Business travel,Business,987,1,1,1,1,2,5,5,5,5,5,5,4,5,5,11,17.0,satisfied +9724,12572,Male,Loyal Customer,58,Personal Travel,Eco Plus,788,2,4,2,3,4,2,4,4,2,3,4,3,3,4,19,17.0,neutral or dissatisfied +9725,43616,Male,Loyal Customer,60,Business travel,Eco,190,4,2,2,2,4,4,4,4,5,2,3,3,1,4,0,0.0,satisfied +9726,20557,Female,Loyal Customer,23,Business travel,Eco,533,3,4,2,4,3,3,3,3,2,4,4,4,3,3,0,7.0,neutral or dissatisfied +9727,64189,Male,Loyal Customer,53,Business travel,Business,2839,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +9728,73256,Female,Loyal Customer,38,Business travel,Business,3382,2,1,1,1,3,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +9729,120614,Female,disloyal Customer,19,Business travel,Eco,453,3,4,3,3,2,3,2,2,1,1,4,4,3,2,32,14.0,neutral or dissatisfied +9730,101016,Male,Loyal Customer,53,Business travel,Business,3149,1,1,1,1,3,5,4,1,1,2,1,3,1,4,11,3.0,satisfied +9731,63131,Male,Loyal Customer,48,Business travel,Business,2628,2,2,2,2,4,3,3,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +9732,29667,Male,Loyal Customer,29,Personal Travel,Eco,1448,2,3,2,1,1,2,1,1,1,3,1,1,4,1,0,0.0,neutral or dissatisfied +9733,82860,Female,disloyal Customer,20,Business travel,Eco,594,0,0,0,3,4,0,4,4,4,2,4,3,5,4,5,0.0,satisfied +9734,20353,Female,disloyal Customer,39,Business travel,Business,265,1,1,1,4,1,1,1,1,1,2,3,3,3,1,0,7.0,neutral or dissatisfied +9735,129605,Male,disloyal Customer,24,Business travel,Business,337,4,0,4,2,4,4,4,4,5,3,5,4,4,4,27,32.0,satisfied +9736,100648,Female,disloyal Customer,26,Business travel,Business,349,5,5,4,2,2,4,2,2,4,5,5,4,4,2,0,17.0,satisfied +9737,57685,Male,Loyal Customer,26,Business travel,Business,867,2,2,2,2,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +9738,13563,Male,Loyal Customer,33,Personal Travel,Eco,152,5,4,5,3,2,5,2,2,4,4,5,5,4,2,0,0.0,satisfied +9739,9912,Female,Loyal Customer,55,Business travel,Business,3921,4,4,2,4,5,4,4,3,3,4,3,5,3,5,60,53.0,satisfied +9740,102589,Female,Loyal Customer,39,Business travel,Eco Plus,223,1,5,5,5,1,1,1,1,4,2,3,2,3,1,35,31.0,neutral or dissatisfied +9741,98460,Female,Loyal Customer,56,Business travel,Business,2153,2,2,2,2,3,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +9742,70872,Male,Loyal Customer,16,Personal Travel,Eco,761,1,4,1,3,2,1,2,2,4,2,4,4,4,2,3,0.0,neutral or dissatisfied +9743,105568,Male,Loyal Customer,39,Business travel,Business,1774,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +9744,27527,Male,Loyal Customer,69,Personal Travel,Eco,954,2,5,2,1,1,2,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +9745,65599,Male,Loyal Customer,38,Business travel,Eco,175,2,5,5,5,2,2,2,2,1,3,4,1,4,2,30,34.0,neutral or dissatisfied +9746,72694,Male,Loyal Customer,58,Personal Travel,Eco,985,4,4,5,4,1,5,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +9747,80009,Male,Loyal Customer,65,Personal Travel,Eco,1010,4,4,4,4,4,4,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +9748,113304,Female,Loyal Customer,32,Business travel,Business,2655,1,0,0,3,3,0,3,3,4,5,4,4,3,3,58,52.0,neutral or dissatisfied +9749,21408,Male,Loyal Customer,37,Business travel,Eco,306,4,2,2,2,4,4,4,4,2,4,1,5,3,4,38,21.0,satisfied +9750,16335,Male,Loyal Customer,63,Personal Travel,Eco,628,2,4,2,1,5,2,2,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +9751,23886,Male,Loyal Customer,48,Business travel,Business,2013,5,5,5,5,1,2,3,5,5,5,5,5,5,2,54,32.0,satisfied +9752,68202,Female,Loyal Customer,44,Personal Travel,Business,432,3,2,3,3,3,4,4,1,1,3,1,4,1,1,50,38.0,neutral or dissatisfied +9753,98509,Male,disloyal Customer,21,Business travel,Eco,402,2,1,2,3,2,5,3,1,2,2,3,3,1,3,86,209.0,neutral or dissatisfied +9754,54180,Male,disloyal Customer,26,Business travel,Eco,1000,1,1,1,3,1,1,2,1,2,2,3,3,4,1,0,0.0,neutral or dissatisfied +9755,82722,Male,Loyal Customer,34,Personal Travel,Eco,632,2,4,2,3,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +9756,45523,Female,Loyal Customer,20,Personal Travel,Eco,689,3,4,3,4,5,3,1,5,5,4,4,3,5,5,0,0.0,neutral or dissatisfied +9757,66049,Male,Loyal Customer,32,Business travel,Eco,1055,3,5,2,5,3,2,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +9758,42616,Female,Loyal Customer,59,Business travel,Business,2121,3,3,3,3,3,5,3,4,4,5,4,5,4,3,0,0.0,satisfied +9759,8057,Male,Loyal Customer,49,Business travel,Business,2771,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +9760,24680,Female,disloyal Customer,45,Business travel,Eco,761,1,2,2,5,5,2,5,5,1,5,4,1,4,5,0,8.0,neutral or dissatisfied +9761,103037,Female,Loyal Customer,34,Business travel,Business,3402,1,1,3,1,4,2,3,1,1,1,1,3,1,4,66,67.0,neutral or dissatisfied +9762,101740,Male,Loyal Customer,57,Business travel,Business,1590,1,1,5,1,4,5,4,2,2,3,2,4,2,5,9,0.0,satisfied +9763,35107,Female,Loyal Customer,49,Business travel,Eco,1028,4,5,5,5,4,4,5,4,4,4,4,2,4,1,0,0.0,satisfied +9764,79113,Female,Loyal Customer,60,Personal Travel,Eco,356,3,5,3,5,5,5,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +9765,3089,Male,Loyal Customer,30,Business travel,Business,413,4,4,4,4,4,4,4,4,3,4,5,5,5,4,0,0.0,satisfied +9766,82716,Male,Loyal Customer,50,Personal Travel,Eco,632,3,4,4,3,4,4,4,4,3,3,5,3,4,4,5,0.0,neutral or dissatisfied +9767,69859,Female,Loyal Customer,20,Personal Travel,Eco,1055,3,4,3,5,4,3,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +9768,100376,Female,Loyal Customer,47,Personal Travel,Eco,1052,4,4,4,3,4,5,5,3,3,4,3,3,3,4,20,34.0,neutral or dissatisfied +9769,58502,Male,Loyal Customer,59,Business travel,Business,719,4,4,4,4,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +9770,8720,Male,Loyal Customer,66,Personal Travel,Eco,280,3,4,3,5,2,3,2,2,4,2,4,4,4,2,10,33.0,neutral or dissatisfied +9771,17103,Male,Loyal Customer,28,Personal Travel,Eco,466,3,5,3,5,1,3,1,1,4,4,4,4,4,1,56,75.0,neutral or dissatisfied +9772,93660,Male,disloyal Customer,33,Business travel,Business,667,3,3,3,2,2,3,2,2,3,2,4,5,5,2,37,31.0,neutral or dissatisfied +9773,10176,Male,Loyal Customer,55,Business travel,Business,3280,0,0,0,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +9774,30721,Male,Loyal Customer,9,Personal Travel,Eco,1123,3,5,3,4,5,3,5,5,4,3,3,5,5,5,0,7.0,neutral or dissatisfied +9775,90294,Male,Loyal Customer,34,Business travel,Business,1761,5,5,5,5,3,5,2,4,4,5,4,4,4,2,7,5.0,satisfied +9776,38698,Female,disloyal Customer,22,Business travel,Eco,1224,2,2,2,4,1,2,1,1,4,4,3,2,1,1,4,0.0,neutral or dissatisfied +9777,50720,Male,Loyal Customer,48,Personal Travel,Eco,250,4,5,4,4,4,4,4,4,4,3,5,3,4,4,0,5.0,neutral or dissatisfied +9778,55863,Female,Loyal Customer,63,Personal Travel,Eco,419,1,5,1,2,4,1,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +9779,92136,Male,Loyal Customer,48,Personal Travel,Eco,1522,1,1,1,3,2,1,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +9780,87907,Female,Loyal Customer,47,Business travel,Business,2351,4,4,4,4,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +9781,34658,Male,disloyal Customer,40,Business travel,Business,301,2,1,1,2,1,1,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +9782,41971,Male,Loyal Customer,57,Personal Travel,Eco,525,3,2,3,3,3,3,5,3,2,2,2,2,3,3,11,3.0,neutral or dissatisfied +9783,14729,Male,Loyal Customer,36,Personal Travel,Eco Plus,479,3,1,3,2,2,3,2,2,4,5,2,3,2,2,8,0.0,neutral or dissatisfied +9784,124243,Male,Loyal Customer,35,Business travel,Eco,1916,5,5,5,5,5,5,5,5,2,3,1,1,1,5,0,0.0,satisfied +9785,737,Female,Loyal Customer,46,Business travel,Business,3717,3,3,3,3,3,5,5,4,4,4,5,5,4,3,0,6.0,satisfied +9786,37688,Male,Loyal Customer,54,Personal Travel,Eco,1056,2,5,2,1,4,2,4,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +9787,51986,Female,Loyal Customer,34,Business travel,Eco Plus,347,5,3,3,3,5,5,5,5,3,3,2,5,1,5,0,0.0,satisfied +9788,12362,Male,Loyal Customer,45,Business travel,Eco,253,2,4,4,4,2,2,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +9789,95360,Male,Loyal Customer,45,Personal Travel,Eco,293,2,4,2,4,3,2,3,3,4,4,4,3,4,3,8,3.0,neutral or dissatisfied +9790,1621,Male,disloyal Customer,25,Business travel,Eco,999,3,3,3,4,4,3,4,4,3,3,5,5,4,4,13,0.0,neutral or dissatisfied +9791,90330,Female,Loyal Customer,50,Business travel,Business,3262,2,2,2,2,3,4,5,4,4,4,4,4,4,4,9,2.0,satisfied +9792,65875,Male,Loyal Customer,27,Personal Travel,Eco,1389,5,5,4,1,3,4,3,3,3,5,5,4,5,3,0,0.0,satisfied +9793,70126,Female,Loyal Customer,54,Business travel,Business,2785,4,4,5,4,4,5,5,5,5,5,5,5,5,3,0,4.0,satisfied +9794,17092,Male,Loyal Customer,23,Business travel,Business,3386,2,5,5,5,2,2,2,1,2,4,4,2,1,2,164,157.0,neutral or dissatisfied +9795,109236,Male,Loyal Customer,66,Personal Travel,Eco,722,3,5,3,1,4,3,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +9796,59281,Male,Loyal Customer,48,Business travel,Business,3365,1,1,1,1,5,4,4,5,3,5,4,4,5,4,4,0.0,satisfied +9797,124179,Male,Loyal Customer,43,Business travel,Business,2089,1,1,1,1,3,3,4,4,4,4,4,5,4,4,0,0.0,satisfied +9798,60331,Male,Loyal Customer,38,Business travel,Business,3422,2,5,5,5,4,3,4,2,2,2,2,2,2,2,0,10.0,neutral or dissatisfied +9799,53827,Female,Loyal Customer,61,Business travel,Eco,191,1,3,3,3,5,3,4,1,1,1,1,3,1,2,0,1.0,neutral or dissatisfied +9800,39824,Female,disloyal Customer,24,Business travel,Eco,272,2,1,2,3,4,2,4,4,3,2,3,2,4,4,0,0.0,neutral or dissatisfied +9801,8986,Female,disloyal Customer,59,Personal Travel,Eco,799,2,3,3,3,4,3,4,4,5,1,3,3,4,4,0,0.0,neutral or dissatisfied +9802,96542,Male,Loyal Customer,14,Personal Travel,Eco,302,1,5,1,1,5,1,4,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +9803,9858,Male,Loyal Customer,60,Personal Travel,Eco,531,3,4,3,4,4,3,4,4,4,2,4,5,4,4,24,31.0,neutral or dissatisfied +9804,31161,Male,Loyal Customer,67,Business travel,Business,3545,2,5,5,5,5,3,2,2,2,2,2,2,2,2,27,18.0,neutral or dissatisfied +9805,56853,Male,Loyal Customer,68,Personal Travel,Business,2454,1,3,1,1,1,4,4,5,4,4,2,4,1,4,4,61.0,neutral or dissatisfied +9806,109619,Female,Loyal Customer,44,Business travel,Business,3881,2,2,2,2,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +9807,46271,Male,Loyal Customer,26,Personal Travel,Eco,752,3,5,3,2,3,3,3,3,5,3,5,3,5,3,28,39.0,neutral or dissatisfied +9808,107020,Female,Loyal Customer,55,Business travel,Business,2250,2,2,2,2,2,2,2,3,1,4,3,2,2,2,131,120.0,neutral or dissatisfied +9809,13017,Male,Loyal Customer,49,Business travel,Business,374,3,5,5,5,2,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +9810,12575,Male,Loyal Customer,8,Personal Travel,Business,542,3,2,3,3,5,3,5,5,1,4,3,2,4,5,0,0.0,neutral or dissatisfied +9811,50538,Male,Loyal Customer,67,Personal Travel,Eco,156,1,4,1,3,4,1,4,4,3,5,4,5,4,4,3,0.0,neutral or dissatisfied +9812,125626,Female,Loyal Customer,42,Business travel,Business,3038,2,2,2,2,5,5,5,5,5,5,5,4,5,3,0,24.0,satisfied +9813,80679,Female,disloyal Customer,70,Business travel,Eco Plus,821,2,2,2,4,3,2,3,3,3,1,3,2,4,3,6,0.0,neutral or dissatisfied +9814,38721,Female,Loyal Customer,59,Business travel,Business,1915,3,4,4,4,3,3,3,3,3,3,3,4,3,4,0,18.0,neutral or dissatisfied +9815,117117,Female,disloyal Customer,29,Business travel,Eco,338,4,1,4,3,1,4,1,1,1,2,3,3,3,1,13,7.0,neutral or dissatisfied +9816,65724,Female,Loyal Customer,52,Business travel,Business,3404,2,4,4,4,2,2,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +9817,109148,Male,disloyal Customer,24,Business travel,Eco,483,1,5,1,2,4,1,4,4,5,5,4,5,4,4,76,73.0,neutral or dissatisfied +9818,68998,Female,Loyal Customer,70,Personal Travel,Eco,2422,4,4,4,3,4,4,4,5,2,4,4,4,4,4,40,36.0,neutral or dissatisfied +9819,123318,Female,Loyal Customer,22,Business travel,Eco Plus,468,1,2,2,2,1,1,3,1,4,3,3,4,4,1,12,20.0,neutral or dissatisfied +9820,58104,Male,Loyal Customer,48,Personal Travel,Eco,589,3,5,3,5,4,3,4,4,3,2,4,5,5,4,3,0.0,neutral or dissatisfied +9821,68767,Female,Loyal Customer,25,Business travel,Business,2685,3,4,4,4,3,3,3,3,1,1,3,3,2,3,16,53.0,neutral or dissatisfied +9822,124491,Male,Loyal Customer,39,Business travel,Business,2803,5,5,4,5,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +9823,95621,Female,Loyal Customer,43,Personal Travel,Eco,670,3,4,3,3,2,5,5,3,3,3,2,3,3,3,7,0.0,neutral or dissatisfied +9824,69830,Female,Loyal Customer,57,Business travel,Business,1055,2,2,2,2,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +9825,13615,Female,Loyal Customer,39,Personal Travel,Eco Plus,227,2,4,2,1,5,2,5,5,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +9826,50081,Female,Loyal Customer,31,Business travel,Business,2331,2,2,2,2,5,5,5,5,3,1,5,3,5,5,1,8.0,satisfied +9827,22813,Male,Loyal Customer,45,Business travel,Eco,302,4,5,5,5,4,4,4,4,2,1,4,2,3,4,0,0.0,satisfied +9828,61589,Female,Loyal Customer,58,Business travel,Business,1635,4,4,5,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +9829,92005,Female,Loyal Customer,48,Business travel,Business,1532,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +9830,2892,Male,Loyal Customer,45,Personal Travel,Eco,491,1,2,1,3,5,1,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +9831,119410,Male,Loyal Customer,40,Business travel,Eco,399,2,3,3,3,2,2,2,2,1,5,2,3,2,2,0,0.0,neutral or dissatisfied +9832,68161,Male,Loyal Customer,23,Business travel,Eco,603,2,2,2,2,2,2,4,2,1,5,4,1,4,2,0,0.0,neutral or dissatisfied +9833,20431,Female,Loyal Customer,21,Personal Travel,Eco,299,4,5,4,3,4,4,4,4,4,5,5,4,4,4,0,0.0,satisfied +9834,42844,Female,Loyal Customer,46,Business travel,Eco,328,4,1,5,5,3,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +9835,35658,Female,Loyal Customer,62,Business travel,Eco,2586,4,5,5,5,4,4,4,3,2,3,1,4,2,4,0,21.0,satisfied +9836,96540,Male,Loyal Customer,11,Personal Travel,Eco,302,2,4,2,3,4,2,4,4,3,3,4,3,4,4,0,0.0,neutral or dissatisfied +9837,96473,Female,disloyal Customer,25,Business travel,Business,302,2,0,2,4,1,2,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +9838,119513,Male,disloyal Customer,22,Business travel,Business,814,4,0,4,1,1,4,1,1,5,3,5,4,5,1,0,0.0,satisfied +9839,41585,Female,Loyal Customer,42,Personal Travel,Eco,1482,2,3,2,4,4,1,3,4,4,2,3,1,4,3,0,2.0,neutral or dissatisfied +9840,110406,Male,Loyal Customer,63,Business travel,Eco,787,1,5,5,5,1,1,1,1,2,2,3,1,2,1,0,0.0,neutral or dissatisfied +9841,42931,Female,disloyal Customer,26,Business travel,Business,236,1,5,1,4,2,1,2,2,5,3,4,4,4,2,12,5.0,neutral or dissatisfied +9842,96032,Male,Loyal Customer,45,Business travel,Eco,1235,1,1,1,1,1,1,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +9843,13981,Female,Loyal Customer,48,Business travel,Business,372,5,5,5,5,4,4,5,4,4,4,4,3,4,3,56,56.0,satisfied +9844,79870,Male,Loyal Customer,45,Business travel,Business,1096,4,4,4,4,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +9845,82338,Female,Loyal Customer,25,Personal Travel,Business,453,1,4,1,4,4,1,4,4,4,2,4,4,3,4,0,0.0,neutral or dissatisfied +9846,122601,Female,disloyal Customer,45,Business travel,Business,728,4,4,4,5,5,4,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +9847,46035,Male,Loyal Customer,27,Business travel,Eco,898,4,1,1,1,4,4,4,4,4,1,1,4,3,4,0,0.0,satisfied +9848,54643,Male,Loyal Customer,48,Business travel,Eco,964,5,5,5,5,5,5,5,5,2,5,1,2,1,5,0,0.0,satisfied +9849,110256,Male,disloyal Customer,22,Business travel,Eco,925,0,1,1,2,2,1,2,2,5,4,5,3,5,2,0,8.0,satisfied +9850,113580,Female,disloyal Customer,38,Business travel,Eco,226,0,2,0,1,4,0,4,4,5,1,5,4,4,4,0,0.0,satisfied +9851,100726,Male,disloyal Customer,27,Business travel,Eco,328,3,4,3,4,3,3,3,3,3,3,4,4,4,3,0,1.0,neutral or dissatisfied +9852,65697,Male,Loyal Customer,42,Personal Travel,Business,1061,5,4,5,3,4,4,4,1,1,5,1,4,1,4,0,0.0,satisfied +9853,59259,Male,Loyal Customer,27,Business travel,Business,3904,3,3,3,3,2,2,2,4,4,3,5,2,4,2,42,13.0,satisfied +9854,72566,Female,disloyal Customer,28,Business travel,Eco,1119,1,1,1,4,2,1,4,2,1,3,3,2,4,2,14,24.0,neutral or dissatisfied +9855,19807,Female,Loyal Customer,55,Business travel,Eco,654,4,1,1,1,1,2,5,4,4,4,4,2,4,5,2,8.0,satisfied +9856,114316,Female,Loyal Customer,55,Personal Travel,Eco,862,3,4,3,1,1,2,3,3,3,3,3,1,3,4,23,8.0,neutral or dissatisfied +9857,72936,Male,disloyal Customer,23,Business travel,Eco,1096,2,2,2,2,1,2,4,1,3,3,4,4,4,1,2,0.0,neutral or dissatisfied +9858,91117,Male,Loyal Customer,33,Personal Travel,Eco,404,2,4,2,2,4,2,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +9859,86263,Female,Loyal Customer,15,Personal Travel,Eco,356,2,1,2,3,2,4,4,3,4,4,4,4,3,4,254,239.0,neutral or dissatisfied +9860,52702,Male,Loyal Customer,34,Business travel,Business,2708,3,5,3,5,1,2,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +9861,11801,Male,disloyal Customer,27,Business travel,Eco Plus,429,4,4,4,5,5,4,5,5,1,1,2,3,2,5,0,0.0,neutral or dissatisfied +9862,108745,Male,Loyal Customer,33,Personal Travel,Business,404,2,4,2,4,1,2,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +9863,129739,Female,Loyal Customer,72,Business travel,Business,2943,0,0,0,1,5,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +9864,66745,Male,Loyal Customer,49,Personal Travel,Eco,802,0,1,0,4,2,0,2,2,3,5,4,3,4,2,1,0.0,satisfied +9865,27991,Male,Loyal Customer,42,Business travel,Business,1616,2,3,3,3,5,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +9866,60354,Female,Loyal Customer,61,Personal Travel,Eco Plus,1024,3,4,4,2,4,5,4,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +9867,21143,Male,Loyal Customer,18,Business travel,Eco Plus,106,1,3,2,3,1,2,4,1,1,3,3,3,4,1,33,25.0,neutral or dissatisfied +9868,89878,Male,Loyal Customer,24,Business travel,Business,1306,5,5,5,5,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +9869,48772,Male,Loyal Customer,49,Business travel,Business,3257,2,1,1,1,4,3,3,2,2,2,2,2,2,3,8,24.0,neutral or dissatisfied +9870,38108,Male,Loyal Customer,29,Business travel,Business,1615,3,3,3,3,3,3,3,3,3,2,5,2,2,3,0,0.0,satisfied +9871,51615,Male,disloyal Customer,34,Business travel,Eco,370,3,0,4,3,3,4,3,3,4,5,1,1,5,3,0,0.0,neutral or dissatisfied +9872,21034,Female,Loyal Customer,44,Business travel,Business,152,4,4,4,4,4,2,4,4,4,4,4,1,4,1,0,0.0,satisfied +9873,49698,Male,disloyal Customer,27,Business travel,Eco,86,3,5,3,3,5,3,5,5,5,1,5,5,5,5,0,0.0,neutral or dissatisfied +9874,129228,Male,Loyal Customer,46,Business travel,Business,3356,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +9875,121492,Female,Loyal Customer,40,Business travel,Business,3855,0,0,0,1,4,5,5,1,1,1,1,3,1,3,3,6.0,satisfied +9876,77388,Male,Loyal Customer,37,Business travel,Business,190,4,4,4,4,4,1,1,4,4,4,4,4,4,1,0,0.0,satisfied +9877,61372,Female,Loyal Customer,46,Business travel,Business,679,5,5,2,5,4,5,5,4,4,4,4,3,4,3,15,16.0,satisfied +9878,128710,Male,Loyal Customer,30,Business travel,Business,1464,3,5,4,5,3,3,3,3,2,5,4,4,3,3,0,0.0,neutral or dissatisfied +9879,11330,Male,Loyal Customer,8,Personal Travel,Eco,517,1,2,1,4,3,1,3,3,2,3,3,3,4,3,27,19.0,neutral or dissatisfied +9880,81936,Male,Loyal Customer,41,Business travel,Business,1589,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +9881,41234,Male,Loyal Customer,36,Personal Travel,Eco,744,1,4,1,1,5,1,5,5,3,2,5,5,4,5,14,8.0,neutral or dissatisfied +9882,106851,Female,Loyal Customer,13,Personal Travel,Eco,1733,3,4,4,3,1,4,1,1,5,2,4,5,5,1,9,12.0,neutral or dissatisfied +9883,10579,Female,Loyal Customer,46,Business travel,Business,3584,1,1,1,1,4,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +9884,89056,Female,disloyal Customer,37,Business travel,Business,1947,1,1,1,3,1,1,1,1,3,4,4,3,4,1,0,7.0,neutral or dissatisfied +9885,56689,Female,Loyal Customer,57,Personal Travel,Eco,1068,2,2,2,1,4,2,1,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +9886,70696,Male,Loyal Customer,51,Business travel,Eco Plus,447,3,2,5,2,3,3,3,3,4,1,2,5,3,3,0,1.0,satisfied +9887,96433,Female,Loyal Customer,49,Business travel,Business,2956,2,2,2,2,2,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +9888,41312,Female,Loyal Customer,24,Business travel,Business,802,3,2,3,3,3,3,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +9889,9984,Male,Loyal Customer,12,Personal Travel,Eco,508,2,5,2,4,2,2,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +9890,78723,Female,Loyal Customer,42,Business travel,Business,3502,1,1,1,1,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +9891,58660,Male,Loyal Customer,59,Personal Travel,Eco,867,3,3,3,2,3,3,3,3,1,5,4,4,1,3,16,41.0,neutral or dissatisfied +9892,74429,Male,Loyal Customer,49,Business travel,Business,1438,1,1,1,1,5,4,4,2,2,2,2,5,2,5,0,0.0,satisfied +9893,53893,Female,disloyal Customer,69,Personal Travel,Eco,191,3,4,3,4,4,3,4,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +9894,22459,Female,Loyal Customer,38,Personal Travel,Eco,143,4,1,4,2,5,4,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +9895,59194,Male,Loyal Customer,53,Business travel,Business,1440,1,1,1,1,2,4,5,4,4,4,4,5,4,4,40,33.0,satisfied +9896,20280,Female,Loyal Customer,56,Personal Travel,Eco,235,2,5,2,1,3,5,2,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +9897,85839,Female,Loyal Customer,10,Personal Travel,Eco,526,3,4,3,4,1,3,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +9898,43126,Female,Loyal Customer,28,Business travel,Eco Plus,236,0,0,0,3,3,3,3,3,3,4,2,1,1,3,0,0.0,satisfied +9899,58387,Male,disloyal Customer,25,Business travel,Business,733,5,0,5,5,2,5,4,2,3,3,4,4,5,2,14,6.0,satisfied +9900,79877,Male,disloyal Customer,25,Business travel,Eco,1096,3,4,4,3,3,4,5,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +9901,13673,Female,Loyal Customer,10,Personal Travel,Eco,462,3,1,3,2,3,5,5,1,4,2,3,5,1,5,170,162.0,neutral or dissatisfied +9902,56176,Female,disloyal Customer,22,Business travel,Eco,1400,2,2,2,2,4,2,4,4,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +9903,91048,Female,Loyal Customer,58,Personal Travel,Eco,594,3,2,3,3,5,3,4,1,1,3,1,1,1,1,1,0.0,neutral or dissatisfied +9904,127489,Female,Loyal Customer,21,Personal Travel,Eco,2075,2,5,2,3,4,2,4,4,1,4,5,2,3,4,0,0.0,neutral or dissatisfied +9905,91962,Male,Loyal Customer,16,Personal Travel,Eco,2586,3,2,3,3,5,3,5,5,3,3,2,1,2,5,0,0.0,neutral or dissatisfied +9906,21974,Female,Loyal Customer,66,Personal Travel,Eco,500,2,5,2,4,2,5,4,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +9907,41907,Male,Loyal Customer,48,Business travel,Business,129,0,4,0,1,3,3,4,2,2,2,2,2,2,4,0,1.0,satisfied +9908,127227,Male,Loyal Customer,56,Business travel,Eco,1460,2,5,5,5,3,2,3,3,2,5,4,2,3,3,0,0.0,neutral or dissatisfied +9909,101840,Female,Loyal Customer,45,Business travel,Eco Plus,1521,2,3,3,3,1,2,3,2,2,2,2,3,2,3,0,7.0,neutral or dissatisfied +9910,32116,Male,disloyal Customer,21,Business travel,Eco,101,1,3,1,4,4,1,4,4,4,3,2,4,3,4,0,0.0,neutral or dissatisfied +9911,11172,Male,Loyal Customer,69,Personal Travel,Eco,201,3,3,0,4,2,0,2,2,2,2,1,2,3,2,0,0.0,neutral or dissatisfied +9912,65006,Male,disloyal Customer,72,Business travel,Eco,190,4,0,4,1,2,4,2,2,3,4,4,2,3,2,0,0.0,satisfied +9913,26080,Female,Loyal Customer,40,Business travel,Eco,591,5,1,1,1,5,5,5,5,1,3,4,3,1,5,3,11.0,satisfied +9914,49079,Male,disloyal Customer,25,Business travel,Eco,308,4,5,4,3,3,4,5,3,3,3,1,3,3,3,6,2.0,neutral or dissatisfied +9915,83342,Male,Loyal Customer,35,Business travel,Business,187,2,5,5,5,4,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +9916,50572,Female,Loyal Customer,25,Personal Travel,Eco,109,0,3,0,4,5,0,5,5,4,2,1,2,5,5,0,0.0,satisfied +9917,85310,Female,Loyal Customer,12,Personal Travel,Eco,731,4,1,4,3,3,4,3,3,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +9918,5363,Female,Loyal Customer,40,Business travel,Business,3313,5,5,5,5,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +9919,101820,Male,Loyal Customer,66,Business travel,Business,1121,3,1,1,1,1,3,3,3,3,3,3,3,3,1,27,9.0,neutral or dissatisfied +9920,7317,Male,Loyal Customer,40,Personal Travel,Eco Plus,130,1,4,1,2,2,1,2,2,4,3,3,3,5,2,1,9.0,neutral or dissatisfied +9921,96293,Male,Loyal Customer,15,Personal Travel,Eco,546,2,5,3,4,1,3,1,1,5,3,4,4,1,1,13,9.0,neutral or dissatisfied +9922,69965,Female,Loyal Customer,50,Business travel,Business,2770,1,4,1,1,3,5,4,4,4,4,4,4,4,4,47,42.0,satisfied +9923,101014,Male,disloyal Customer,23,Business travel,Eco,806,1,2,2,2,2,2,2,2,2,1,2,4,3,2,7,0.0,neutral or dissatisfied +9924,115432,Male,Loyal Customer,38,Business travel,Business,3834,4,4,4,4,5,5,4,4,4,4,4,4,4,4,16,13.0,satisfied +9925,20915,Female,Loyal Customer,30,Business travel,Business,3639,5,5,5,5,2,2,2,2,2,2,2,5,5,2,0,0.0,satisfied +9926,122487,Female,Loyal Customer,61,Personal Travel,Eco,575,1,4,1,2,2,4,5,5,5,1,1,5,5,4,23,16.0,neutral or dissatisfied +9927,64734,Male,Loyal Customer,78,Business travel,Business,2703,3,4,4,4,1,4,4,3,3,3,3,2,3,3,5,0.0,neutral or dissatisfied +9928,96712,Female,Loyal Customer,51,Business travel,Eco,696,4,2,2,2,2,3,3,3,3,4,3,4,3,1,11,0.0,neutral or dissatisfied +9929,116041,Male,Loyal Customer,69,Personal Travel,Eco,373,2,0,2,1,3,2,3,3,3,2,5,4,4,3,57,48.0,neutral or dissatisfied +9930,119114,Male,Loyal Customer,43,Personal Travel,Eco,1107,4,0,5,5,2,5,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +9931,57136,Male,Loyal Customer,49,Personal Travel,Eco,1222,2,4,2,4,5,2,3,5,2,1,3,1,4,5,0,0.0,neutral or dissatisfied +9932,16948,Female,Loyal Customer,41,Business travel,Eco Plus,820,2,4,4,4,4,2,1,2,2,2,2,1,2,4,0,0.0,satisfied +9933,103433,Female,Loyal Customer,35,Personal Travel,Eco,237,3,5,0,4,5,0,5,5,3,2,5,4,4,5,14,14.0,neutral or dissatisfied +9934,75969,Male,Loyal Customer,33,Business travel,Eco,297,2,4,2,4,2,2,2,2,2,3,3,3,3,2,8,44.0,neutral or dissatisfied +9935,111725,Female,disloyal Customer,28,Business travel,Business,541,2,2,2,3,2,4,4,4,3,4,5,4,4,4,138,113.0,neutral or dissatisfied +9936,73026,Female,Loyal Customer,48,Personal Travel,Eco,944,4,3,5,2,2,3,3,3,3,5,2,5,3,3,0,0.0,neutral or dissatisfied +9937,15727,Female,Loyal Customer,7,Personal Travel,Eco,192,3,4,3,2,2,3,2,2,5,2,4,4,5,2,4,0.0,neutral or dissatisfied +9938,26329,Male,Loyal Customer,22,Personal Travel,Business,873,2,1,2,3,3,2,3,3,3,3,4,2,3,3,3,0.0,neutral or dissatisfied +9939,58984,Male,Loyal Customer,45,Business travel,Business,1846,2,2,2,2,3,3,5,4,4,4,4,4,4,3,1,0.0,satisfied +9940,37384,Female,Loyal Customer,33,Business travel,Business,3737,3,3,3,3,3,3,2,5,5,5,5,2,5,1,0,0.0,satisfied +9941,104941,Female,Loyal Customer,28,Business travel,Business,1541,1,1,1,1,4,4,4,4,3,3,4,3,5,4,9,3.0,satisfied +9942,19524,Female,disloyal Customer,25,Business travel,Business,160,3,5,4,3,2,4,3,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +9943,116335,Male,Loyal Customer,46,Personal Travel,Eco,446,3,3,4,1,2,4,2,2,3,4,3,5,2,2,81,72.0,neutral or dissatisfied +9944,74139,Female,Loyal Customer,51,Business travel,Business,1975,1,1,1,1,4,1,2,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +9945,40989,Male,Loyal Customer,67,Business travel,Business,3463,5,5,5,5,4,3,5,4,4,4,4,5,4,2,24,28.0,satisfied +9946,72408,Male,disloyal Customer,29,Business travel,Business,985,3,3,3,3,4,3,4,4,5,3,5,5,5,4,2,0.0,neutral or dissatisfied +9947,62791,Female,Loyal Customer,63,Personal Travel,Eco,2338,5,2,5,4,5,3,3,5,5,5,5,3,5,4,11,0.0,satisfied +9948,40086,Male,Loyal Customer,20,Business travel,Eco Plus,493,2,4,4,4,2,2,1,2,4,4,2,3,2,2,0,0.0,neutral or dissatisfied +9949,107544,Female,Loyal Customer,57,Business travel,Business,1521,1,1,3,1,2,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +9950,82681,Male,disloyal Customer,49,Business travel,Business,632,1,1,1,2,4,1,4,4,5,4,4,4,5,4,0,0.0,neutral or dissatisfied +9951,48469,Male,Loyal Customer,48,Business travel,Business,3495,2,2,3,2,5,1,3,5,5,5,5,3,5,5,0,0.0,satisfied +9952,110489,Male,Loyal Customer,33,Personal Travel,Eco,925,3,5,3,2,3,3,3,3,3,4,5,4,5,3,0,16.0,neutral or dissatisfied +9953,80921,Female,Loyal Customer,60,Business travel,Business,2645,5,5,5,5,2,5,5,4,4,4,4,5,4,4,0,1.0,satisfied +9954,121920,Female,Loyal Customer,70,Personal Travel,Eco,449,1,4,3,2,2,4,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +9955,101582,Female,Loyal Customer,49,Business travel,Business,1099,4,4,4,4,2,4,4,2,2,2,2,4,2,4,102,101.0,satisfied +9956,9954,Female,disloyal Customer,38,Business travel,Business,357,2,3,3,4,2,3,2,2,3,3,5,3,4,2,0,0.0,neutral or dissatisfied +9957,57493,Male,Loyal Customer,42,Business travel,Business,1868,2,2,2,2,4,4,4,4,4,4,4,3,4,5,7,0.0,satisfied +9958,69499,Female,Loyal Customer,42,Personal Travel,Eco Plus,1096,3,2,3,2,1,1,2,3,3,3,3,1,3,1,0,2.0,neutral or dissatisfied +9959,121283,Female,Loyal Customer,18,Personal Travel,Eco Plus,2075,2,3,2,3,5,2,1,5,2,2,3,3,3,5,0,10.0,neutral or dissatisfied +9960,129037,Male,Loyal Customer,69,Personal Travel,Business,1744,2,2,2,4,1,2,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +9961,12764,Female,Loyal Customer,61,Personal Travel,Eco,851,2,4,2,3,4,4,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +9962,7109,Male,Loyal Customer,65,Personal Travel,Eco,157,3,5,3,5,3,3,3,3,4,5,4,4,4,3,0,5.0,neutral or dissatisfied +9963,63767,Male,Loyal Customer,35,Business travel,Business,1721,2,2,2,2,5,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +9964,50757,Male,Loyal Customer,14,Personal Travel,Eco,158,2,4,2,1,2,2,2,2,3,2,4,1,5,2,0,4.0,neutral or dissatisfied +9965,122978,Male,Loyal Customer,60,Business travel,Business,3517,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +9966,86412,Female,disloyal Customer,26,Business travel,Business,853,0,0,0,2,2,2,2,2,4,5,4,5,5,2,0,0.0,satisfied +9967,42224,Male,Loyal Customer,36,Business travel,Eco,550,4,4,4,4,4,4,4,4,2,5,1,2,2,4,0,0.0,satisfied +9968,57371,Female,Loyal Customer,33,Personal Travel,Eco,236,1,1,1,1,1,1,2,1,2,4,1,2,2,1,0,0.0,neutral or dissatisfied +9969,70847,Female,Loyal Customer,23,Business travel,Business,2505,2,5,5,5,2,2,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +9970,5732,Male,Loyal Customer,23,Personal Travel,Eco Plus,234,4,5,4,3,1,4,1,1,5,3,3,1,2,1,1,20.0,neutral or dissatisfied +9971,82029,Male,Loyal Customer,57,Personal Travel,Eco,1454,3,4,3,1,2,3,1,2,4,4,4,3,5,2,0,0.0,neutral or dissatisfied +9972,7720,Female,Loyal Customer,59,Business travel,Business,3490,2,2,2,2,4,4,4,5,5,5,5,3,5,3,0,3.0,satisfied +9973,54558,Male,Loyal Customer,50,Personal Travel,Eco,925,0,5,0,5,2,0,2,2,5,4,4,4,5,2,0,0.0,satisfied +9974,35219,Female,Loyal Customer,23,Business travel,Business,1005,2,2,2,2,5,5,5,5,4,3,3,4,3,5,0,19.0,satisfied +9975,34839,Female,Loyal Customer,24,Personal Travel,Eco Plus,264,2,5,2,2,2,2,2,2,4,2,1,5,2,2,15,9.0,neutral or dissatisfied +9976,7850,Female,disloyal Customer,30,Business travel,Eco,1005,2,2,2,2,2,2,2,2,1,5,2,4,3,2,0,0.0,neutral or dissatisfied +9977,15066,Female,Loyal Customer,52,Personal Travel,Eco,576,4,4,4,3,5,4,5,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +9978,44116,Male,Loyal Customer,35,Personal Travel,Business,74,2,5,0,2,2,4,4,3,3,0,2,4,3,3,12,36.0,neutral or dissatisfied +9979,69141,Female,Loyal Customer,58,Business travel,Business,2248,3,3,3,3,4,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +9980,120390,Female,Loyal Customer,43,Business travel,Business,366,1,1,1,1,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +9981,84076,Male,Loyal Customer,40,Business travel,Eco,773,3,3,3,3,3,3,3,1,4,3,4,3,2,3,137,131.0,neutral or dissatisfied +9982,81864,Female,Loyal Customer,62,Personal Travel,Eco Plus,1310,3,4,3,4,5,5,4,3,3,3,3,5,3,5,62,44.0,neutral or dissatisfied +9983,27494,Female,Loyal Customer,52,Business travel,Eco,578,5,4,4,4,4,4,3,5,5,5,5,1,5,3,0,1.0,satisfied +9984,108150,Female,Loyal Customer,45,Personal Travel,Eco,997,2,3,3,2,2,5,4,4,4,3,4,1,4,5,6,12.0,neutral or dissatisfied +9985,48161,Male,Loyal Customer,18,Business travel,Business,391,2,2,2,2,4,4,4,4,4,2,4,2,1,4,0,0.0,satisfied +9986,7710,Female,Loyal Customer,52,Business travel,Eco Plus,604,3,1,1,1,2,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +9987,8725,Female,Loyal Customer,9,Personal Travel,Eco,227,2,1,2,3,4,2,4,4,1,4,3,3,2,4,13,34.0,neutral or dissatisfied +9988,129621,Male,Loyal Customer,39,Business travel,Business,337,1,1,1,1,5,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +9989,110195,Female,disloyal Customer,26,Business travel,Business,869,3,3,3,5,1,3,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +9990,60343,Female,Loyal Customer,20,Business travel,Business,2585,2,2,2,2,2,2,2,2,1,1,3,4,3,2,0,0.0,neutral or dissatisfied +9991,114447,Male,Loyal Customer,41,Business travel,Business,1787,3,3,3,3,3,4,4,4,4,4,4,5,4,5,7,1.0,satisfied +9992,13425,Male,Loyal Customer,40,Business travel,Business,1670,4,3,3,3,5,3,3,4,4,4,4,4,4,3,0,12.0,neutral or dissatisfied +9993,51588,Male,disloyal Customer,44,Business travel,Eco,370,2,4,2,5,4,2,4,4,5,5,4,2,5,4,0,0.0,neutral or dissatisfied +9994,14970,Female,Loyal Customer,42,Business travel,Eco,927,5,3,3,3,4,3,2,5,5,5,5,1,5,4,48,84.0,satisfied +9995,53434,Female,Loyal Customer,20,Business travel,Business,2288,4,4,4,4,5,4,5,5,3,5,5,2,2,5,0,0.0,satisfied +9996,55197,Female,Loyal Customer,19,Personal Travel,Eco Plus,1635,2,5,2,3,1,2,1,1,5,2,3,5,5,1,0,27.0,neutral or dissatisfied +9997,42997,Female,Loyal Customer,52,Business travel,Business,192,1,1,1,1,3,1,3,2,5,3,4,3,3,3,131,120.0,neutral or dissatisfied +9998,27031,Male,Loyal Customer,46,Business travel,Eco Plus,867,3,4,4,4,3,3,3,3,4,2,4,5,5,3,6,9.0,satisfied +9999,75613,Male,Loyal Customer,67,Personal Travel,Eco,337,2,4,2,3,1,2,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +10000,75917,Female,Loyal Customer,56,Business travel,Business,3189,4,4,4,4,2,4,4,5,5,5,5,3,5,3,42,37.0,satisfied +10001,4145,Male,disloyal Customer,44,Business travel,Eco,427,3,3,3,3,4,3,4,4,2,1,3,4,3,4,32,36.0,neutral or dissatisfied +10002,88212,Male,Loyal Customer,39,Business travel,Business,581,1,1,1,1,2,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +10003,74832,Female,Loyal Customer,40,Business travel,Business,1797,5,5,5,5,2,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +10004,127419,Female,Loyal Customer,36,Personal Travel,Eco,868,3,1,3,3,2,3,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +10005,87262,Female,Loyal Customer,35,Business travel,Eco,577,3,3,3,3,3,3,3,3,2,2,3,4,4,3,26,12.0,neutral or dissatisfied +10006,37769,Female,Loyal Customer,25,Business travel,Eco Plus,1056,4,4,4,4,4,4,4,4,1,5,5,3,3,4,0,0.0,satisfied +10007,106736,Female,Loyal Customer,59,Business travel,Business,829,5,5,5,5,5,4,5,5,5,5,5,4,5,3,34,26.0,satisfied +10008,91736,Male,Loyal Customer,9,Business travel,Business,590,4,1,1,1,4,4,4,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +10009,97258,Female,Loyal Customer,57,Personal Travel,Eco,296,5,4,5,3,5,5,5,4,4,5,4,3,4,3,1,2.0,satisfied +10010,93246,Female,Loyal Customer,65,Personal Travel,Eco,689,3,4,3,1,3,5,5,4,4,3,4,4,4,3,20,10.0,neutral or dissatisfied +10011,60681,Female,Loyal Customer,45,Business travel,Business,1605,1,1,1,1,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +10012,32122,Female,Loyal Customer,33,Business travel,Business,2204,4,4,4,4,3,2,5,5,5,5,5,3,5,2,0,0.0,satisfied +10013,104744,Male,disloyal Customer,28,Business travel,Eco,1342,3,3,3,4,2,3,2,2,2,2,4,2,4,2,110,83.0,neutral or dissatisfied +10014,123668,Male,disloyal Customer,38,Business travel,Business,214,3,3,3,1,3,3,3,3,5,2,5,3,5,3,10,32.0,neutral or dissatisfied +10015,35642,Female,Loyal Customer,46,Business travel,Business,2521,3,4,4,4,3,3,3,4,5,3,2,3,1,3,0,36.0,neutral or dissatisfied +10016,31917,Male,disloyal Customer,22,Business travel,Eco,163,1,4,1,3,4,1,5,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +10017,47857,Male,Loyal Customer,60,Business travel,Eco,726,5,2,1,2,5,5,5,5,3,1,4,5,3,5,0,0.0,satisfied +10018,1487,Female,Loyal Customer,66,Business travel,Business,2124,4,4,4,4,2,4,4,5,5,5,5,4,5,3,0,3.0,satisfied +10019,126367,Male,Loyal Customer,62,Personal Travel,Eco,328,3,2,3,4,3,3,2,3,4,2,3,4,3,3,0,11.0,neutral or dissatisfied +10020,17668,Male,disloyal Customer,58,Business travel,Business,282,3,3,3,5,5,3,5,5,3,2,5,5,5,5,29,15.0,neutral or dissatisfied +10021,84527,Male,Loyal Customer,51,Business travel,Business,2486,1,1,1,1,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +10022,10353,Female,Loyal Customer,30,Business travel,Business,216,3,3,3,3,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +10023,115489,Female,Loyal Customer,53,Business travel,Business,2419,4,5,5,5,4,3,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +10024,101061,Male,Loyal Customer,45,Business travel,Business,1631,2,2,5,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +10025,126624,Male,Loyal Customer,33,Business travel,Business,3623,4,4,4,4,5,5,5,5,5,2,4,3,5,5,0,0.0,satisfied +10026,56816,Female,Loyal Customer,29,Business travel,Business,1605,5,5,5,5,4,4,4,4,4,5,5,5,4,4,4,0.0,satisfied +10027,56907,Female,Loyal Customer,42,Business travel,Business,2454,1,1,2,1,5,5,5,4,3,3,5,5,5,5,8,0.0,satisfied +10028,16454,Male,Loyal Customer,38,Personal Travel,Eco,529,2,3,3,4,5,3,3,5,1,1,4,3,5,5,0,0.0,neutral or dissatisfied +10029,98191,Male,Loyal Customer,33,Business travel,Business,327,3,1,3,3,3,3,3,3,3,3,3,2,4,3,40,26.0,neutral or dissatisfied +10030,47513,Male,Loyal Customer,22,Personal Travel,Eco,558,4,3,4,4,4,4,4,4,2,4,4,1,4,4,0,9.0,neutral or dissatisfied +10031,61657,Female,disloyal Customer,26,Business travel,Business,1379,2,5,2,3,4,2,4,4,4,2,4,5,5,4,0,0.0,neutral or dissatisfied +10032,107070,Female,Loyal Customer,28,Personal Travel,Eco,395,1,1,1,4,5,1,5,5,2,1,3,3,4,5,3,0.0,neutral or dissatisfied +10033,96882,Male,Loyal Customer,56,Personal Travel,Eco,994,3,5,3,3,1,3,1,1,5,3,3,1,2,1,9,0.0,neutral or dissatisfied +10034,120713,Male,Loyal Customer,41,Business travel,Eco Plus,280,2,1,4,1,3,2,3,3,4,5,4,4,4,3,17,6.0,neutral or dissatisfied +10035,43177,Male,Loyal Customer,63,Business travel,Eco,282,5,4,4,4,5,5,5,5,5,2,5,3,2,5,0,13.0,satisfied +10036,92968,Male,Loyal Customer,15,Personal Travel,Eco,1694,3,5,3,2,2,3,2,2,5,1,3,2,3,2,0,0.0,neutral or dissatisfied +10037,103474,Female,disloyal Customer,28,Business travel,Business,440,3,3,3,2,1,3,1,1,5,4,5,5,4,1,59,41.0,neutral or dissatisfied +10038,98479,Male,Loyal Customer,52,Business travel,Business,1900,3,2,5,2,3,4,3,3,3,3,3,4,3,2,0,5.0,neutral or dissatisfied +10039,112777,Female,Loyal Customer,36,Personal Travel,Eco,590,4,5,4,2,5,4,5,5,5,5,5,5,5,5,0,0.0,neutral or dissatisfied +10040,100150,Female,disloyal Customer,22,Business travel,Eco,725,4,4,4,4,5,4,5,5,1,5,4,4,3,5,0,0.0,neutral or dissatisfied +10041,120716,Male,Loyal Customer,40,Business travel,Business,90,2,2,2,2,3,5,4,5,5,5,4,4,5,5,0,0.0,satisfied +10042,129002,Male,Loyal Customer,26,Business travel,Business,2611,2,2,2,2,4,5,5,3,4,3,4,5,5,5,0,0.0,satisfied +10043,72253,Female,Loyal Customer,54,Business travel,Business,2592,5,5,5,5,5,4,5,5,5,5,5,3,5,3,8,6.0,satisfied +10044,24078,Male,Loyal Customer,42,Personal Travel,Eco,866,3,2,3,4,5,3,3,5,3,4,4,1,4,5,0,0.0,neutral or dissatisfied +10045,33345,Female,Loyal Customer,57,Business travel,Business,2614,1,1,1,1,4,5,3,5,5,5,5,5,5,1,0,0.0,satisfied +10046,70459,Male,Loyal Customer,60,Business travel,Business,3858,3,3,4,3,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +10047,5819,Male,Loyal Customer,25,Personal Travel,Eco,177,3,5,3,3,5,3,5,5,3,4,5,4,5,5,71,76.0,neutral or dissatisfied +10048,105668,Female,Loyal Customer,55,Business travel,Eco,787,2,1,1,1,4,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +10049,7594,Male,Loyal Customer,57,Business travel,Business,1905,3,3,2,3,3,4,5,2,2,2,2,4,2,3,1,2.0,satisfied +10050,43403,Female,Loyal Customer,13,Personal Travel,Eco,463,4,3,4,3,2,4,3,2,5,5,3,1,3,2,0,0.0,satisfied +10051,128393,Female,Loyal Customer,30,Business travel,Business,2979,2,4,4,4,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +10052,57756,Male,Loyal Customer,29,Business travel,Business,2704,2,2,3,2,4,4,4,5,3,4,4,4,3,4,2,9.0,satisfied +10053,117824,Male,Loyal Customer,34,Personal Travel,Eco,328,4,0,4,3,4,4,4,4,5,5,3,4,4,4,0,2.0,neutral or dissatisfied +10054,10219,Male,Loyal Customer,35,Business travel,Business,2549,1,1,1,1,4,4,5,4,4,4,4,4,4,4,3,0.0,satisfied +10055,96840,Male,Loyal Customer,41,Business travel,Business,571,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +10056,61646,Male,Loyal Customer,48,Business travel,Business,1379,3,3,3,3,3,5,5,4,4,3,4,3,4,3,0,0.0,satisfied +10057,74599,Female,disloyal Customer,12,Business travel,Eco,1171,4,4,4,3,2,4,2,2,2,4,3,3,4,2,0,0.0,neutral or dissatisfied +10058,126293,Female,Loyal Customer,61,Personal Travel,Eco,631,3,4,3,2,5,5,4,4,4,3,4,4,4,3,0,6.0,neutral or dissatisfied +10059,49963,Female,Loyal Customer,65,Business travel,Eco,109,1,2,2,2,2,3,3,1,1,1,1,3,1,3,2,6.0,neutral or dissatisfied +10060,126427,Female,Loyal Customer,12,Business travel,Eco Plus,650,3,5,5,5,3,3,1,3,3,5,4,2,4,3,0,12.0,neutral or dissatisfied +10061,97183,Female,Loyal Customer,21,Personal Travel,Eco,1642,2,4,3,2,2,3,4,2,5,5,5,3,5,2,102,77.0,neutral or dissatisfied +10062,81871,Male,Loyal Customer,44,Business travel,Business,1050,3,5,3,3,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +10063,89573,Female,disloyal Customer,25,Business travel,Business,950,1,5,1,2,5,1,5,5,5,2,4,5,4,5,2,0.0,neutral or dissatisfied +10064,2747,Female,disloyal Customer,29,Business travel,Eco,772,1,1,1,4,5,1,5,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +10065,54791,Female,Loyal Customer,25,Personal Travel,Business,862,1,5,1,1,3,1,3,3,3,4,5,4,4,3,7,0.0,neutral or dissatisfied +10066,66836,Female,Loyal Customer,60,Business travel,Business,2758,2,2,2,2,1,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +10067,109755,Female,Loyal Customer,52,Business travel,Business,3333,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +10068,1934,Female,Loyal Customer,49,Business travel,Business,2454,1,5,5,5,5,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +10069,95677,Male,Loyal Customer,45,Business travel,Business,1750,0,0,0,1,5,4,5,4,4,1,1,3,4,3,23,23.0,satisfied +10070,46697,Male,Loyal Customer,42,Personal Travel,Eco,73,1,3,1,1,3,1,2,3,4,4,5,2,5,3,0,0.0,neutral or dissatisfied +10071,50994,Female,Loyal Customer,17,Personal Travel,Eco,262,1,5,1,3,2,1,2,2,2,4,5,2,3,2,7,14.0,neutral or dissatisfied +10072,6062,Female,Loyal Customer,45,Personal Travel,Eco,630,1,4,1,1,1,5,5,3,4,4,5,5,5,5,794,795.0,neutral or dissatisfied +10073,83067,Female,Loyal Customer,54,Business travel,Business,1086,3,2,2,2,1,2,2,3,3,3,3,1,3,2,2,6.0,neutral or dissatisfied +10074,35305,Female,Loyal Customer,59,Business travel,Eco,1035,4,2,2,2,1,5,4,4,4,4,4,1,4,5,0,0.0,satisfied +10075,25673,Male,Loyal Customer,45,Personal Travel,Eco,761,1,4,1,4,1,1,5,1,4,3,4,3,4,1,7,3.0,neutral or dissatisfied +10076,13996,Male,Loyal Customer,60,Business travel,Eco,160,2,5,5,5,2,2,2,2,1,1,3,2,4,2,0,0.0,neutral or dissatisfied +10077,22939,Male,Loyal Customer,45,Business travel,Business,2609,4,4,4,4,5,5,5,5,5,5,5,1,5,3,0,0.0,satisfied +10078,102176,Female,disloyal Customer,36,Business travel,Business,236,2,2,2,3,4,2,4,4,5,3,4,3,5,4,0,1.0,neutral or dissatisfied +10079,71051,Male,Loyal Customer,51,Business travel,Business,578,3,3,2,3,2,2,1,3,3,3,3,1,3,2,18,29.0,neutral or dissatisfied +10080,3193,Male,Loyal Customer,42,Business travel,Business,3441,2,2,2,2,5,4,5,5,2,2,2,5,1,5,110,144.0,satisfied +10081,115726,Male,disloyal Customer,58,Business travel,Eco,390,2,2,2,4,2,2,4,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +10082,2365,Female,Loyal Customer,31,Business travel,Eco,925,2,4,4,4,2,2,2,2,3,5,4,3,4,2,29,44.0,neutral or dissatisfied +10083,89233,Male,Loyal Customer,37,Business travel,Business,2139,5,5,5,5,2,4,5,4,4,4,4,4,4,4,5,0.0,satisfied +10084,79682,Male,Loyal Customer,49,Personal Travel,Eco,762,4,4,4,5,2,4,2,2,3,3,5,4,5,2,56,48.0,neutral or dissatisfied +10085,101911,Female,Loyal Customer,56,Personal Travel,Eco,2039,1,2,1,4,4,4,4,1,1,1,1,4,1,3,7,3.0,neutral or dissatisfied +10086,73017,Male,Loyal Customer,54,Personal Travel,Eco,1096,1,2,1,4,1,1,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +10087,23353,Female,disloyal Customer,30,Business travel,Eco Plus,794,1,1,1,3,1,1,4,1,3,1,3,4,4,1,0,0.0,neutral or dissatisfied +10088,29926,Male,Loyal Customer,30,Business travel,Business,261,0,0,0,1,4,1,1,4,3,2,5,1,3,4,0,0.0,satisfied +10089,120896,Male,Loyal Customer,51,Business travel,Business,1546,1,1,1,1,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +10090,46547,Male,Loyal Customer,35,Business travel,Business,3915,4,4,4,4,5,1,4,4,4,4,4,4,4,1,4,0.0,satisfied +10091,3163,Male,Loyal Customer,64,Personal Travel,Business,693,0,5,0,3,3,5,4,1,1,0,2,4,1,3,0,0.0,satisfied +10092,65378,Female,Loyal Customer,48,Business travel,Business,1892,2,2,2,2,2,3,2,4,4,4,4,1,4,4,4,6.0,satisfied +10093,16600,Male,Loyal Customer,20,Business travel,Business,1626,5,5,5,5,5,5,5,5,1,4,4,4,2,5,0,1.0,satisfied +10094,109263,Male,Loyal Customer,52,Personal Travel,Eco Plus,612,3,3,3,1,4,3,4,4,4,4,5,5,3,4,0,0.0,neutral or dissatisfied +10095,101261,Male,disloyal Customer,28,Business travel,Business,968,4,5,5,4,5,1,1,5,2,4,5,1,5,1,129,135.0,satisfied +10096,69907,Female,disloyal Customer,39,Business travel,Business,1671,2,2,2,1,2,2,2,2,3,3,3,4,4,2,0,0.0,neutral or dissatisfied +10097,2017,Female,Loyal Customer,52,Business travel,Business,733,3,1,3,3,5,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +10098,18182,Male,Loyal Customer,51,Business travel,Eco,346,5,5,5,5,5,5,5,5,5,2,4,5,4,5,13,44.0,satisfied +10099,98550,Male,Loyal Customer,57,Business travel,Eco Plus,668,3,2,2,2,3,3,3,3,1,3,4,3,3,3,17,10.0,neutral or dissatisfied +10100,5091,Female,Loyal Customer,33,Business travel,Business,2594,3,3,3,3,3,4,1,5,5,5,3,5,5,1,0,2.0,satisfied +10101,39639,Female,Loyal Customer,29,Personal Travel,Eco Plus,679,1,4,1,1,5,1,5,5,5,2,4,3,5,5,0,0.0,neutral or dissatisfied +10102,25720,Female,Loyal Customer,38,Business travel,Business,3467,4,5,5,5,1,3,4,2,2,2,4,4,2,3,0,0.0,neutral or dissatisfied +10103,77214,Female,Loyal Customer,61,Personal Travel,Business,1590,3,4,3,4,5,4,5,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +10104,31819,Female,Loyal Customer,55,Business travel,Business,2762,3,3,3,3,5,5,5,3,4,4,4,5,4,5,0,0.0,satisfied +10105,79104,Male,Loyal Customer,34,Personal Travel,Eco,226,3,4,3,2,1,3,1,1,5,3,3,5,1,1,6,0.0,neutral or dissatisfied +10106,70130,Male,Loyal Customer,59,Business travel,Eco,150,4,4,4,4,4,4,4,4,4,2,5,4,1,4,0,0.0,satisfied +10107,100213,Female,Loyal Customer,48,Business travel,Business,3200,2,2,5,2,4,4,5,4,4,4,4,5,4,4,0,1.0,satisfied +10108,64208,Female,Loyal Customer,45,Business travel,Business,853,2,5,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10109,101294,Male,Loyal Customer,48,Personal Travel,Eco,763,3,5,3,3,1,3,1,1,3,2,4,4,4,1,0,0.0,neutral or dissatisfied +10110,11452,Male,Loyal Customer,52,Business travel,Business,312,2,2,2,2,4,4,4,5,5,5,5,5,5,3,10,13.0,satisfied +10111,82951,Male,Loyal Customer,54,Business travel,Business,957,2,2,2,2,2,4,5,5,5,5,5,3,5,4,5,10.0,satisfied +10112,46413,Male,Loyal Customer,38,Business travel,Eco,649,4,2,2,2,4,4,4,4,1,4,1,4,3,4,23,24.0,satisfied +10113,89593,Male,Loyal Customer,44,Business travel,Business,1983,1,1,1,1,4,5,4,3,3,2,3,3,3,3,0,0.0,satisfied +10114,2659,Female,Loyal Customer,54,Business travel,Business,539,2,2,2,2,3,5,4,2,2,2,2,5,2,4,1,0.0,satisfied +10115,41480,Female,disloyal Customer,39,Business travel,Business,715,5,5,5,1,4,5,4,4,5,3,1,2,1,4,0,0.0,satisfied +10116,114696,Female,Loyal Customer,33,Business travel,Business,337,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,7.0,satisfied +10117,43988,Female,Loyal Customer,39,Business travel,Business,3013,0,0,0,2,4,5,2,3,3,1,1,4,3,5,52,52.0,satisfied +10118,114248,Female,disloyal Customer,29,Business travel,Eco,853,2,2,2,3,1,2,1,1,2,4,3,1,4,1,38,32.0,neutral or dissatisfied +10119,110227,Female,Loyal Customer,15,Business travel,Business,1041,2,2,2,2,5,5,5,5,5,5,4,3,4,5,28,32.0,satisfied +10120,38102,Male,disloyal Customer,71,Business travel,Business,1121,3,3,3,3,1,3,1,1,4,2,4,4,3,1,18,4.0,neutral or dissatisfied +10121,111294,Male,disloyal Customer,43,Business travel,Business,2297,1,1,1,1,2,1,2,2,4,5,3,4,4,2,8,0.0,neutral or dissatisfied +10122,18065,Female,disloyal Customer,56,Business travel,Eco,205,4,4,4,4,5,4,5,5,1,2,1,4,5,5,0,0.0,satisfied +10123,83801,Female,Loyal Customer,53,Business travel,Business,1805,1,1,4,1,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +10124,1043,Male,Loyal Customer,39,Business travel,Eco,247,5,2,5,2,5,5,5,5,4,5,5,2,2,5,0,0.0,satisfied +10125,46717,Female,Loyal Customer,55,Personal Travel,Eco,73,3,5,3,1,3,2,1,1,1,3,1,4,1,5,1,0.0,neutral or dissatisfied +10126,116903,Male,Loyal Customer,47,Business travel,Business,3776,2,2,2,2,5,5,5,5,5,5,5,3,5,5,16,8.0,satisfied +10127,121602,Male,Loyal Customer,39,Personal Travel,Eco,912,3,5,3,1,3,3,3,3,5,3,4,3,4,3,0,0.0,neutral or dissatisfied +10128,20501,Female,Loyal Customer,50,Personal Travel,Eco,139,4,0,4,1,3,5,5,4,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +10129,11598,Female,Loyal Customer,17,Business travel,Business,468,2,5,2,5,2,1,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +10130,113037,Female,Loyal Customer,36,Business travel,Business,1621,5,5,5,5,2,4,5,5,5,5,5,5,5,4,37,18.0,satisfied +10131,18162,Male,Loyal Customer,58,Personal Travel,Eco,430,3,1,5,4,2,5,2,2,4,3,4,1,4,2,0,6.0,neutral or dissatisfied +10132,10240,Female,Loyal Customer,19,Personal Travel,Business,667,5,5,5,4,5,5,5,5,5,3,4,5,5,5,14,0.0,satisfied +10133,49198,Female,Loyal Customer,47,Business travel,Business,2052,3,3,3,3,5,4,4,4,4,4,5,5,4,4,5,0.0,satisfied +10134,4036,Female,Loyal Customer,48,Business travel,Business,2029,3,3,3,3,4,2,1,5,5,5,5,2,5,5,0,0.0,satisfied +10135,65112,Male,Loyal Customer,38,Personal Travel,Eco,224,2,5,2,4,4,2,4,4,3,4,5,4,5,4,0,0.0,neutral or dissatisfied +10136,14966,Male,Loyal Customer,43,Business travel,Business,3709,1,1,2,1,4,1,5,3,3,3,3,3,3,3,19,4.0,satisfied +10137,83442,Male,Loyal Customer,32,Personal Travel,Eco Plus,632,3,4,3,3,3,3,3,3,4,2,3,4,4,3,0,15.0,neutral or dissatisfied +10138,34468,Female,Loyal Customer,49,Business travel,Business,1982,5,5,5,5,1,3,1,5,5,5,5,3,5,4,17,5.0,satisfied +10139,23865,Male,Loyal Customer,50,Personal Travel,Eco,552,1,4,1,2,5,1,5,5,4,3,4,4,4,5,24,45.0,neutral or dissatisfied +10140,93079,Female,Loyal Customer,54,Business travel,Business,2804,5,5,5,5,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +10141,112604,Male,Loyal Customer,57,Business travel,Eco,602,2,3,3,3,2,2,2,2,3,1,4,2,3,2,13,0.0,neutral or dissatisfied +10142,97855,Female,Loyal Customer,46,Business travel,Business,1931,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +10143,78702,Male,Loyal Customer,36,Business travel,Business,2891,2,4,2,2,4,4,5,4,4,4,4,5,4,4,13,0.0,satisfied +10144,126516,Female,Loyal Customer,45,Business travel,Eco,313,3,3,3,3,4,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +10145,60444,Male,disloyal Customer,40,Business travel,Business,641,3,3,3,4,2,3,2,2,3,4,4,4,5,2,25,14.0,neutral or dissatisfied +10146,102529,Male,Loyal Customer,47,Personal Travel,Eco,407,1,5,2,3,3,2,3,3,5,4,1,2,3,3,0,0.0,neutral or dissatisfied +10147,125632,Female,Loyal Customer,57,Business travel,Business,2015,4,4,4,4,5,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +10148,67640,Male,Loyal Customer,57,Business travel,Business,1464,4,4,4,4,2,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +10149,95975,Female,disloyal Customer,47,Business travel,Eco,1090,4,4,4,3,5,4,5,5,4,5,4,4,3,5,0,0.0,neutral or dissatisfied +10150,86935,Male,Loyal Customer,51,Personal Travel,Eco Plus,352,2,5,2,3,2,2,2,2,3,5,4,4,5,2,3,3.0,neutral or dissatisfied +10151,2679,Female,Loyal Customer,64,Personal Travel,Eco,622,3,3,3,5,3,3,4,1,1,3,1,2,1,5,109,,neutral or dissatisfied +10152,33441,Female,Loyal Customer,57,Personal Travel,Eco,2355,4,4,4,1,4,3,2,4,4,3,5,2,4,2,0,11.0,neutral or dissatisfied +10153,14240,Male,disloyal Customer,28,Business travel,Eco,1027,4,4,4,2,3,4,3,3,2,3,3,3,1,3,0,0.0,neutral or dissatisfied +10154,74065,Male,Loyal Customer,51,Business travel,Business,641,1,1,1,1,3,4,4,5,5,5,5,5,5,4,35,20.0,satisfied +10155,88602,Female,Loyal Customer,18,Personal Travel,Eco,240,2,5,2,3,3,2,1,3,3,3,4,5,5,3,32,27.0,neutral or dissatisfied +10156,67955,Male,Loyal Customer,23,Business travel,Business,1464,3,3,3,3,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +10157,22073,Female,Loyal Customer,42,Personal Travel,Eco,304,3,4,3,5,3,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +10158,77732,Male,Loyal Customer,47,Business travel,Business,3105,1,5,5,5,2,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +10159,88673,Male,Loyal Customer,64,Personal Travel,Eco,594,1,3,1,5,2,1,2,2,5,5,4,2,2,2,24,18.0,neutral or dissatisfied +10160,127569,Male,disloyal Customer,20,Business travel,Eco,1178,3,3,3,4,5,3,5,5,2,4,4,2,4,5,0,0.0,satisfied +10161,67281,Male,Loyal Customer,30,Personal Travel,Eco,1119,3,4,3,4,2,3,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +10162,77253,Female,Loyal Customer,23,Personal Travel,Eco,1590,4,5,4,3,3,4,3,3,5,3,4,5,4,3,0,0.0,neutral or dissatisfied +10163,97425,Female,Loyal Customer,43,Personal Travel,Eco,587,1,1,2,4,4,4,3,2,2,2,2,1,2,2,2,0.0,neutral or dissatisfied +10164,87766,Female,disloyal Customer,24,Business travel,Business,214,5,0,5,4,3,5,3,3,5,2,4,4,4,3,0,0.0,satisfied +10165,118265,Female,Loyal Customer,48,Business travel,Eco Plus,1972,3,2,4,4,4,2,3,3,3,3,3,3,3,2,59,58.0,neutral or dissatisfied +10166,48874,Male,Loyal Customer,34,Business travel,Business,109,5,5,5,5,4,2,5,4,4,4,4,3,4,3,0,0.0,satisfied +10167,108135,Male,Loyal Customer,19,Business travel,Eco,1166,3,4,4,4,3,3,1,3,3,5,4,2,4,3,15,1.0,neutral or dissatisfied +10168,10782,Male,Loyal Customer,44,Business travel,Business,1778,5,5,5,5,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +10169,14305,Female,Loyal Customer,45,Business travel,Eco,175,3,4,4,4,3,2,3,3,3,3,3,4,3,1,25,6.0,neutral or dissatisfied +10170,97194,Male,Loyal Customer,39,Personal Travel,Eco,1497,4,4,3,2,1,3,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +10171,30322,Female,Loyal Customer,55,Business travel,Eco,391,3,2,2,2,4,2,3,3,3,3,3,2,3,1,0,3.0,satisfied +10172,26577,Male,disloyal Customer,23,Business travel,Eco,515,2,4,2,1,1,2,1,1,4,4,3,3,5,1,0,0.0,neutral or dissatisfied +10173,28351,Female,Loyal Customer,17,Personal Travel,Eco,867,4,3,4,2,4,4,4,4,4,3,5,4,2,4,0,0.0,neutral or dissatisfied +10174,30487,Female,Loyal Customer,48,Business travel,Business,516,2,3,3,3,2,4,4,2,2,2,2,1,2,2,11,23.0,neutral or dissatisfied +10175,67445,Female,Loyal Customer,34,Personal Travel,Eco,769,3,5,3,3,5,3,2,5,3,4,5,4,4,5,10,14.0,neutral or dissatisfied +10176,7996,Male,Loyal Customer,47,Business travel,Business,3306,1,5,5,5,3,3,3,3,3,3,1,1,3,4,0,0.0,neutral or dissatisfied +10177,129229,Female,Loyal Customer,53,Business travel,Business,1504,5,5,3,5,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +10178,45250,Female,Loyal Customer,52,Personal Travel,Eco Plus,1013,1,4,1,1,2,2,3,2,2,1,2,5,2,5,5,0.0,neutral or dissatisfied +10179,98767,Female,Loyal Customer,17,Personal Travel,Eco,2075,2,4,2,5,1,2,1,1,3,2,3,4,4,1,0,4.0,neutral or dissatisfied +10180,69531,Female,Loyal Customer,47,Business travel,Business,2475,5,5,5,5,4,4,4,3,4,4,4,4,3,4,0,0.0,satisfied +10181,99630,Male,Loyal Customer,18,Personal Travel,Eco,1085,4,5,4,5,4,4,3,4,3,3,4,3,4,4,0,0.0,satisfied +10182,39218,Male,Loyal Customer,32,Business travel,Business,2558,0,4,0,1,5,5,5,5,5,4,1,1,3,5,0,6.0,satisfied +10183,22572,Male,Loyal Customer,38,Business travel,Business,1833,2,2,2,2,5,3,5,4,4,4,4,3,4,2,4,0.0,satisfied +10184,110743,Female,Loyal Customer,40,Business travel,Business,3567,2,2,2,2,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +10185,1548,Male,Loyal Customer,38,Personal Travel,Eco,862,4,4,4,3,3,4,3,3,1,2,5,5,4,3,0,0.0,satisfied +10186,126235,Female,disloyal Customer,25,Business travel,Eco,328,4,0,4,3,5,4,5,5,2,3,2,5,1,5,0,0.0,neutral or dissatisfied +10187,2530,Female,Loyal Customer,39,Business travel,Business,2713,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +10188,101447,Female,disloyal Customer,44,Business travel,Business,345,2,2,2,4,2,2,1,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +10189,124500,Female,Loyal Customer,36,Business travel,Business,3062,1,1,4,1,3,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +10190,89963,Female,Loyal Customer,28,Personal Travel,Eco,1310,1,4,1,3,1,1,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +10191,7705,Male,Loyal Customer,30,Personal Travel,Eco,604,2,4,2,1,2,2,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +10192,112009,Female,Loyal Customer,21,Personal Travel,Eco Plus,533,2,5,2,3,5,2,5,5,5,4,5,4,5,5,39,43.0,neutral or dissatisfied +10193,20593,Male,Loyal Customer,47,Business travel,Eco Plus,565,5,4,5,4,5,5,5,5,3,1,2,1,3,5,0,0.0,satisfied +10194,77827,Male,Loyal Customer,21,Personal Travel,Eco,813,3,0,3,3,1,3,5,1,1,5,1,5,1,1,91,80.0,neutral or dissatisfied +10195,32854,Female,Loyal Customer,44,Personal Travel,Eco,216,4,3,4,3,1,3,2,5,5,4,5,3,5,3,0,2.0,satisfied +10196,111024,Male,Loyal Customer,30,Business travel,Business,3046,2,3,3,3,2,2,2,2,3,2,3,2,3,2,48,38.0,neutral or dissatisfied +10197,60503,Male,Loyal Customer,45,Personal Travel,Eco,862,4,4,5,4,3,5,3,3,3,4,5,4,5,3,8,12.0,satisfied +10198,33829,Male,disloyal Customer,22,Business travel,Eco,722,4,4,4,5,2,4,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +10199,61893,Female,Loyal Customer,43,Business travel,Business,2521,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +10200,112924,Male,Loyal Customer,8,Personal Travel,Eco,1129,0,5,0,3,2,0,2,2,3,2,4,3,4,2,4,2.0,satisfied +10201,93713,Male,Loyal Customer,30,Personal Travel,Eco,689,1,2,1,3,3,1,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +10202,88987,Female,Loyal Customer,61,Personal Travel,Eco,1199,1,3,1,3,5,4,4,4,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +10203,35022,Male,Loyal Customer,55,Personal Travel,Eco,740,3,5,3,2,4,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +10204,58192,Male,Loyal Customer,62,Business travel,Business,2741,1,1,1,1,3,5,4,4,4,4,4,5,4,3,16,0.0,satisfied +10205,2177,Male,Loyal Customer,40,Business travel,Eco,685,4,5,3,5,4,4,4,4,4,3,4,3,4,4,0,13.0,neutral or dissatisfied +10206,10302,Male,Loyal Customer,58,Business travel,Business,216,3,3,3,3,4,4,5,4,4,4,5,5,4,5,11,0.0,satisfied +10207,29611,Female,Loyal Customer,29,Business travel,Business,3058,4,1,4,4,4,4,4,4,5,5,1,4,2,4,0,0.0,satisfied +10208,43771,Male,disloyal Customer,24,Business travel,Eco,481,3,3,4,3,2,4,2,2,4,3,4,2,3,2,10,0.0,neutral or dissatisfied +10209,50192,Female,disloyal Customer,40,Business travel,Business,156,3,3,3,3,3,3,3,3,3,3,5,4,5,3,8,2.0,neutral or dissatisfied +10210,81645,Female,Loyal Customer,33,Business travel,Business,2760,4,4,4,4,2,4,5,3,3,2,3,5,3,5,0,0.0,satisfied +10211,82343,Female,Loyal Customer,56,Business travel,Business,453,5,5,5,5,4,5,4,2,2,2,2,4,2,4,0,34.0,satisfied +10212,65168,Female,Loyal Customer,57,Personal Travel,Eco,224,5,2,0,2,1,2,3,5,5,0,5,3,5,4,0,0.0,satisfied +10213,27990,Male,Loyal Customer,22,Business travel,Eco,1616,4,2,2,2,4,4,3,4,1,2,5,3,3,4,0,0.0,satisfied +10214,83133,Male,Loyal Customer,41,Personal Travel,Eco,1084,2,5,2,2,3,2,3,3,3,2,4,3,5,3,0,18.0,neutral or dissatisfied +10215,86794,Female,Loyal Customer,47,Business travel,Business,692,4,4,4,4,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +10216,95926,Male,disloyal Customer,13,Business travel,Eco,1031,4,4,4,3,1,4,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +10217,42700,Female,Loyal Customer,24,Personal Travel,Eco,516,1,4,4,1,5,4,5,5,5,5,4,3,4,5,0,0.0,neutral or dissatisfied +10218,92113,Male,Loyal Customer,62,Personal Travel,Eco,1535,3,5,2,2,3,2,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +10219,76735,Female,Loyal Customer,34,Personal Travel,Eco Plus,534,3,4,3,2,2,3,2,2,5,3,5,5,5,2,12,0.0,neutral or dissatisfied +10220,89815,Male,Loyal Customer,53,Business travel,Eco Plus,944,2,2,2,2,2,2,2,2,4,3,3,1,4,2,9,10.0,neutral or dissatisfied +10221,123529,Female,Loyal Customer,56,Business travel,Business,2296,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +10222,115354,Female,Loyal Customer,25,Business travel,Business,296,2,5,5,5,2,2,2,2,4,3,4,2,3,2,21,14.0,neutral or dissatisfied +10223,57018,Female,Loyal Customer,11,Personal Travel,Eco,2565,2,1,1,3,5,1,5,5,4,2,3,2,2,5,0,0.0,neutral or dissatisfied +10224,71092,Male,Loyal Customer,31,Business travel,Eco Plus,802,2,5,5,5,2,2,2,2,2,5,3,2,4,2,0,0.0,neutral or dissatisfied +10225,117667,Female,Loyal Customer,28,Personal Travel,Eco,1449,2,5,2,2,2,2,2,2,3,1,4,5,3,2,42,56.0,neutral or dissatisfied +10226,47240,Female,Loyal Customer,62,Personal Travel,Eco Plus,748,1,4,1,1,3,5,5,3,3,1,3,2,3,3,0,0.0,neutral or dissatisfied +10227,31634,Female,Loyal Customer,30,Business travel,Business,3325,2,2,2,2,5,4,5,5,5,1,1,4,3,5,2,9.0,satisfied +10228,88741,Male,Loyal Customer,35,Personal Travel,Eco,404,2,4,2,3,1,2,1,1,3,4,5,5,5,1,0,4.0,neutral or dissatisfied +10229,69712,Female,Loyal Customer,66,Business travel,Business,1372,2,2,2,2,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +10230,69871,Female,Loyal Customer,62,Personal Travel,Eco Plus,1055,2,4,2,3,3,5,5,3,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +10231,6346,Female,Loyal Customer,31,Business travel,Business,2118,1,3,3,3,1,2,1,1,4,2,4,1,3,1,0,51.0,neutral or dissatisfied +10232,84272,Female,Loyal Customer,27,Business travel,Business,334,5,5,5,5,5,5,5,5,5,4,4,4,4,5,0,0.0,satisfied +10233,129144,Female,Loyal Customer,29,Business travel,Business,1559,4,4,4,4,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +10234,44466,Male,disloyal Customer,40,Business travel,Eco,196,2,0,2,4,2,2,2,2,2,4,1,5,4,2,0,0.0,neutral or dissatisfied +10235,34742,Female,Loyal Customer,32,Business travel,Eco,209,5,2,2,2,5,4,5,5,1,3,4,3,5,5,0,0.0,satisfied +10236,20670,Male,Loyal Customer,51,Business travel,Business,3504,1,1,1,1,1,4,3,1,1,1,1,4,1,1,0,7.0,neutral or dissatisfied +10237,75187,Female,Loyal Customer,26,Business travel,Business,1846,1,1,5,1,4,4,4,4,3,5,4,3,5,4,0,0.0,satisfied +10238,39485,Female,disloyal Customer,41,Business travel,Business,467,3,2,2,1,1,4,1,1,1,1,4,1,5,1,6,0.0,neutral or dissatisfied +10239,6094,Female,Loyal Customer,51,Personal Travel,Eco Plus,693,4,1,4,4,2,3,4,5,5,4,5,2,5,3,0,0.0,neutral or dissatisfied +10240,103860,Female,Loyal Customer,33,Personal Travel,Eco,882,5,5,5,4,4,5,5,4,4,1,5,5,3,4,0,6.0,satisfied +10241,82341,Female,Loyal Customer,39,Business travel,Business,453,4,4,4,4,3,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +10242,49597,Male,Loyal Customer,57,Business travel,Business,3815,3,3,3,3,3,4,5,4,4,4,3,1,4,2,0,5.0,satisfied +10243,19364,Male,Loyal Customer,45,Business travel,Business,3908,2,4,2,2,5,4,5,5,5,5,5,4,5,4,15,8.0,satisfied +10244,95811,Female,Loyal Customer,20,Personal Travel,Eco,1050,1,4,1,2,3,1,3,3,3,3,5,4,4,3,0,,neutral or dissatisfied +10245,69784,Female,disloyal Customer,27,Business travel,Business,1345,5,5,5,3,3,5,3,3,3,5,4,5,5,3,0,0.0,satisfied +10246,95636,Female,Loyal Customer,57,Personal Travel,Eco,670,1,5,1,4,3,4,5,5,5,1,5,5,5,5,55,62.0,neutral or dissatisfied +10247,50263,Female,Loyal Customer,30,Business travel,Business,209,2,3,3,3,3,2,2,3,3,5,4,3,3,3,43,43.0,neutral or dissatisfied +10248,122841,Female,Loyal Customer,59,Business travel,Business,2078,3,3,3,3,4,5,4,5,5,5,5,3,5,4,11,16.0,satisfied +10249,36985,Female,disloyal Customer,20,Business travel,Eco,899,2,2,2,3,5,2,2,5,2,2,4,2,3,5,107,99.0,neutral or dissatisfied +10250,44403,Male,Loyal Customer,12,Personal Travel,Eco,323,1,5,1,5,4,1,4,4,3,4,5,1,1,4,0,0.0,neutral or dissatisfied +10251,97735,Male,Loyal Customer,48,Business travel,Business,3633,5,5,5,5,4,4,4,5,5,5,5,4,5,5,36,28.0,satisfied +10252,101112,Female,Loyal Customer,53,Business travel,Business,583,1,1,1,1,2,5,4,4,4,4,4,4,4,3,8,0.0,satisfied +10253,68965,Female,Loyal Customer,60,Business travel,Business,1751,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,5.0,satisfied +10254,98688,Female,Loyal Customer,68,Personal Travel,Eco,966,1,5,1,1,5,5,5,5,5,1,5,4,5,4,34,36.0,neutral or dissatisfied +10255,66588,Female,disloyal Customer,26,Business travel,Business,761,5,5,5,5,1,5,1,1,5,3,5,4,4,1,7,1.0,satisfied +10256,46818,Male,Loyal Customer,54,Business travel,Eco,916,5,5,5,5,5,5,5,5,5,1,5,2,1,5,5,0.0,satisfied +10257,87635,Male,Loyal Customer,37,Business travel,Business,3856,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +10258,60638,Female,Loyal Customer,59,Business travel,Business,1620,3,3,3,3,2,4,5,4,4,4,4,4,4,5,50,43.0,satisfied +10259,92863,Female,Loyal Customer,48,Business travel,Business,2519,3,3,3,3,3,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +10260,4731,Male,Loyal Customer,58,Business travel,Business,888,2,2,2,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10261,18549,Female,Loyal Customer,36,Business travel,Business,1891,0,3,0,1,3,4,5,4,4,5,5,4,4,2,0,5.0,satisfied +10262,97646,Female,Loyal Customer,50,Business travel,Eco,1587,3,3,3,3,5,3,4,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +10263,115526,Male,Loyal Customer,54,Business travel,Eco,296,3,1,1,1,3,3,3,3,3,2,3,2,2,3,43,38.0,neutral or dissatisfied +10264,36926,Female,Loyal Customer,37,Business travel,Eco,867,4,5,5,5,4,4,4,4,1,1,3,3,4,4,3,0.0,satisfied +10265,75493,Male,Loyal Customer,39,Business travel,Business,2585,1,2,1,1,3,3,5,4,4,4,4,3,4,3,3,0.0,satisfied +10266,66970,Female,Loyal Customer,42,Business travel,Business,1924,5,5,5,5,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +10267,92158,Male,Loyal Customer,38,Personal Travel,Eco Plus,1535,3,4,3,1,1,3,1,1,4,3,3,3,4,1,11,24.0,neutral or dissatisfied +10268,37878,Female,Loyal Customer,35,Business travel,Eco,937,4,1,1,1,4,4,4,4,4,2,4,5,2,4,0,0.0,satisfied +10269,95769,Male,Loyal Customer,33,Personal Travel,Eco,237,2,5,2,3,5,2,5,5,4,4,4,4,4,5,16,9.0,neutral or dissatisfied +10270,106937,Female,Loyal Customer,53,Business travel,Business,3754,2,4,4,4,4,2,2,2,2,2,2,1,2,4,1,19.0,neutral or dissatisfied +10271,73767,Male,Loyal Customer,25,Personal Travel,Eco,192,4,5,4,2,3,4,3,3,3,4,4,3,4,3,26,12.0,neutral or dissatisfied +10272,120854,Male,Loyal Customer,31,Personal Travel,Business,1013,2,1,2,3,1,2,1,1,4,4,3,2,2,1,0,0.0,neutral or dissatisfied +10273,52147,Female,disloyal Customer,37,Business travel,Business,370,2,2,2,3,4,2,4,4,2,4,3,4,4,4,0,2.0,neutral or dissatisfied +10274,98864,Female,Loyal Customer,42,Personal Travel,Eco,1751,1,2,1,2,4,3,2,5,5,1,5,3,5,4,84,78.0,neutral or dissatisfied +10275,81519,Female,Loyal Customer,41,Business travel,Business,3959,2,2,2,2,2,4,4,5,5,5,5,5,5,3,60,70.0,satisfied +10276,46466,Male,Loyal Customer,55,Business travel,Business,2948,4,4,4,4,2,4,4,4,4,4,5,5,4,5,0,0.0,satisfied +10277,58559,Female,Loyal Customer,21,Personal Travel,Eco,1514,1,4,1,3,4,1,4,4,5,4,3,5,4,4,35,22.0,neutral or dissatisfied +10278,27463,Male,disloyal Customer,25,Business travel,Eco,1050,2,2,2,3,4,2,4,4,2,5,4,3,3,4,44,43.0,neutral or dissatisfied +10279,106304,Male,Loyal Customer,45,Business travel,Business,1734,3,3,3,3,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +10280,33671,Female,Loyal Customer,57,Personal Travel,Eco Plus,474,4,2,4,4,5,4,3,1,1,4,1,4,1,2,6,0.0,neutral or dissatisfied +10281,114740,Male,disloyal Customer,39,Business travel,Business,337,2,1,1,1,2,1,2,2,3,4,5,5,5,2,78,90.0,neutral or dissatisfied +10282,49797,Male,Loyal Customer,64,Business travel,Eco,109,1,2,2,2,1,1,1,1,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +10283,15107,Male,Loyal Customer,60,Personal Travel,Eco,224,4,4,0,5,4,0,4,4,5,3,4,3,4,4,21,11.0,neutral or dissatisfied +10284,45294,Female,Loyal Customer,35,Business travel,Business,1993,4,4,4,4,4,4,3,1,4,3,4,3,4,3,136,184.0,satisfied +10285,13572,Female,Loyal Customer,44,Personal Travel,Eco,152,3,5,3,3,3,5,5,1,1,3,1,3,1,4,35,35.0,neutral or dissatisfied +10286,64148,Male,Loyal Customer,45,Business travel,Business,989,1,1,4,1,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +10287,27410,Male,Loyal Customer,54,Business travel,Business,954,3,4,4,4,3,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +10288,80373,Male,disloyal Customer,18,Business travel,Business,368,3,0,3,4,4,3,4,4,4,5,4,4,3,4,0,0.0,neutral or dissatisfied +10289,4440,Male,Loyal Customer,22,Personal Travel,Eco,762,1,4,1,3,4,1,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +10290,5323,Female,Loyal Customer,14,Personal Travel,Eco Plus,351,3,5,3,1,3,3,4,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +10291,37427,Female,disloyal Customer,16,Business travel,Eco,1097,1,1,1,2,2,1,5,2,4,5,3,4,2,2,0,0.0,neutral or dissatisfied +10292,43255,Male,disloyal Customer,38,Business travel,Eco,387,3,5,3,3,5,3,1,5,4,1,4,5,5,5,0,0.0,neutral or dissatisfied +10293,103431,Female,Loyal Customer,67,Personal Travel,Eco,237,2,5,2,3,2,4,5,5,5,2,5,3,5,3,12,4.0,neutral or dissatisfied +10294,110893,Male,Loyal Customer,60,Business travel,Business,2223,3,3,3,3,4,4,4,4,4,4,4,3,4,5,1,0.0,satisfied +10295,68306,Female,Loyal Customer,69,Personal Travel,Eco,1797,3,5,4,2,5,5,4,2,2,4,4,4,2,5,0,0.0,neutral or dissatisfied +10296,124079,Male,Loyal Customer,27,Personal Travel,Eco,80,1,1,0,1,5,0,2,5,2,1,1,1,1,5,9,17.0,neutral or dissatisfied +10297,15026,Male,disloyal Customer,21,Business travel,Eco,576,2,5,2,3,2,5,5,4,4,5,5,5,4,5,200,208.0,neutral or dissatisfied +10298,371,Male,Loyal Customer,50,Business travel,Business,482,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,3.0,satisfied +10299,103907,Male,disloyal Customer,37,Business travel,Business,770,1,1,1,3,4,1,4,4,4,1,2,3,2,4,14,17.0,neutral or dissatisfied +10300,39014,Male,Loyal Customer,36,Business travel,Business,230,3,5,5,5,5,1,1,3,3,2,3,3,3,4,20,14.0,neutral or dissatisfied +10301,18122,Female,Loyal Customer,44,Business travel,Business,120,0,3,0,2,4,1,3,4,4,4,4,5,4,3,0,0.0,satisfied +10302,65758,Female,Loyal Customer,39,Personal Travel,Eco,936,3,4,3,2,4,3,4,4,4,4,5,5,5,4,1,0.0,neutral or dissatisfied +10303,100047,Male,Loyal Customer,45,Personal Travel,Eco,289,0,4,0,3,4,0,4,4,4,3,4,4,5,4,0,0.0,satisfied +10304,122461,Male,Loyal Customer,53,Business travel,Business,808,5,5,5,5,2,4,5,5,5,5,5,5,5,4,5,12.0,satisfied +10305,98115,Male,Loyal Customer,52,Business travel,Business,472,4,4,4,4,4,5,4,5,5,5,5,4,5,5,48,36.0,satisfied +10306,42721,Male,Loyal Customer,29,Personal Travel,Eco,912,2,5,2,3,4,2,2,4,3,4,4,5,5,4,5,0.0,neutral or dissatisfied +10307,63897,Female,Loyal Customer,22,Business travel,Business,1212,3,3,3,3,3,3,3,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +10308,119689,Male,disloyal Customer,39,Business travel,Business,1303,5,5,5,3,5,5,5,5,3,2,4,3,5,5,0,0.0,satisfied +10309,70035,Male,disloyal Customer,25,Business travel,Business,583,3,0,3,1,4,3,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +10310,89999,Female,Loyal Customer,41,Business travel,Business,1127,2,3,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +10311,119621,Male,Loyal Customer,58,Business travel,Eco,335,1,1,1,1,1,1,1,1,2,4,2,2,2,1,0,0.0,neutral or dissatisfied +10312,77786,Male,Loyal Customer,39,Personal Travel,Eco,731,2,2,2,4,3,2,3,3,2,5,3,3,3,3,4,0.0,neutral or dissatisfied +10313,32404,Female,Loyal Customer,49,Business travel,Eco,163,4,3,3,3,5,2,4,4,4,4,4,1,4,1,0,0.0,satisfied +10314,19022,Male,Loyal Customer,53,Personal Travel,Eco,788,1,4,1,2,1,1,1,1,5,2,4,4,5,1,0,13.0,neutral or dissatisfied +10315,34119,Female,Loyal Customer,18,Business travel,Eco,1046,0,3,0,4,4,0,5,4,4,5,5,4,1,4,0,0.0,satisfied +10316,49477,Female,Loyal Customer,31,Business travel,Eco,110,0,0,0,1,2,0,2,2,2,1,4,4,4,2,0,7.0,satisfied +10317,125246,Female,disloyal Customer,23,Business travel,Eco,427,4,0,4,4,3,4,5,3,5,4,4,4,4,3,0,5.0,satisfied +10318,36572,Male,Loyal Customer,55,Business travel,Eco,1121,5,1,1,1,5,5,5,5,1,4,4,4,5,5,105,95.0,satisfied +10319,43303,Female,Loyal Customer,38,Business travel,Eco,358,5,3,3,3,5,5,5,5,3,3,4,4,1,5,0,0.0,satisfied +10320,14237,Male,Loyal Customer,76,Business travel,Business,890,3,3,3,3,4,5,3,5,5,4,5,5,5,3,0,0.0,satisfied +10321,12754,Female,Loyal Customer,9,Personal Travel,Eco,721,4,4,4,2,1,4,2,1,5,5,2,5,3,1,0,0.0,neutral or dissatisfied +10322,110440,Female,Loyal Customer,59,Personal Travel,Eco,787,4,4,4,3,5,5,4,5,5,4,5,5,5,5,11,0.0,satisfied +10323,83585,Male,Loyal Customer,33,Personal Travel,Eco,936,2,3,2,3,5,2,1,5,2,2,3,4,2,5,1,25.0,neutral or dissatisfied +10324,33736,Female,Loyal Customer,68,Personal Travel,Eco,667,0,4,0,2,5,5,4,2,2,0,3,3,2,3,0,0.0,satisfied +10325,79469,Male,Loyal Customer,68,Personal Travel,Eco,1183,1,5,1,1,3,1,3,3,5,4,4,3,5,3,37,80.0,neutral or dissatisfied +10326,113117,Male,Loyal Customer,9,Personal Travel,Eco,569,3,4,3,1,4,3,4,4,3,2,4,5,5,4,0,0.0,neutral or dissatisfied +10327,76580,Male,Loyal Customer,36,Business travel,Eco,547,2,3,3,3,2,2,2,2,3,4,4,1,4,2,1,0.0,neutral or dissatisfied +10328,67439,Female,Loyal Customer,36,Business travel,Eco,241,2,1,1,1,2,3,2,2,1,4,3,1,3,2,31,15.0,neutral or dissatisfied +10329,104522,Female,Loyal Customer,37,Business travel,Business,3144,1,1,1,1,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +10330,115087,Female,Loyal Customer,39,Business travel,Business,2158,3,3,3,3,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10331,127513,Male,Loyal Customer,44,Business travel,Business,1814,4,4,3,4,4,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +10332,10431,Male,Loyal Customer,48,Business travel,Business,316,3,3,3,3,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +10333,25956,Female,Loyal Customer,23,Business travel,Eco,946,5,4,4,4,5,5,3,5,1,2,1,3,4,5,30,25.0,satisfied +10334,19136,Female,disloyal Customer,58,Business travel,Eco Plus,265,2,3,3,3,3,2,3,3,4,5,2,4,3,3,0,3.0,neutral or dissatisfied +10335,107238,Male,Loyal Customer,25,Business travel,Business,283,0,0,0,1,3,3,3,3,5,3,4,5,5,3,16,22.0,satisfied +10336,99549,Male,disloyal Customer,21,Business travel,Business,802,4,4,4,3,3,4,3,3,4,2,4,5,4,3,122,105.0,satisfied +10337,96310,Female,Loyal Customer,43,Business travel,Business,2290,3,3,3,3,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +10338,20738,Female,Loyal Customer,40,Business travel,Eco,363,5,2,2,2,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +10339,19624,Female,Loyal Customer,56,Business travel,Business,1669,0,0,0,4,3,5,5,3,3,3,3,3,3,4,82,78.0,satisfied +10340,110822,Female,Loyal Customer,42,Personal Travel,Eco,997,2,4,2,3,4,4,4,4,4,2,4,4,4,4,4,19.0,neutral or dissatisfied +10341,129324,Female,Loyal Customer,68,Business travel,Eco,2475,1,4,2,4,5,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +10342,116819,Male,disloyal Customer,21,Business travel,Business,370,0,0,0,1,5,0,5,5,3,4,5,5,4,5,1,0.0,satisfied +10343,60577,Female,disloyal Customer,38,Business travel,Eco,1290,2,2,2,2,4,2,4,4,3,1,2,4,2,4,1,0.0,neutral or dissatisfied +10344,3066,Male,Loyal Customer,37,Personal Travel,Business,594,2,3,3,3,2,3,4,5,5,3,5,1,5,1,0,11.0,neutral or dissatisfied +10345,36394,Female,Loyal Customer,47,Business travel,Business,2381,1,2,2,2,2,2,4,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +10346,78078,Female,Loyal Customer,46,Business travel,Business,1574,2,2,2,2,3,4,4,4,4,4,5,4,4,5,30,38.0,satisfied +10347,50299,Female,disloyal Customer,22,Business travel,Business,134,1,4,1,3,1,1,1,1,2,2,4,4,4,1,0,5.0,neutral or dissatisfied +10348,81800,Male,Loyal Customer,57,Business travel,Business,1310,2,2,2,2,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10349,16493,Male,Loyal Customer,36,Business travel,Business,2162,3,5,4,5,3,3,4,1,1,1,3,1,1,3,14,1.0,neutral or dissatisfied +10350,95048,Female,Loyal Customer,47,Personal Travel,Eco,239,2,5,2,4,1,2,5,5,5,2,3,5,5,3,0,4.0,neutral or dissatisfied +10351,93697,Male,Loyal Customer,8,Personal Travel,Eco,1452,4,4,4,4,4,4,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +10352,87717,Male,Loyal Customer,41,Business travel,Business,1523,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +10353,21300,Female,Loyal Customer,70,Personal Travel,Eco,526,2,4,2,1,3,4,5,5,5,2,5,3,5,4,9,0.0,neutral or dissatisfied +10354,111247,Male,disloyal Customer,28,Business travel,Business,1849,1,1,1,3,2,1,2,2,4,3,3,5,4,2,13,9.0,neutral or dissatisfied +10355,23920,Female,Loyal Customer,68,Personal Travel,Eco,579,2,1,2,3,4,4,3,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +10356,14002,Female,Loyal Customer,25,Personal Travel,Eco,160,3,5,3,2,1,3,1,1,5,4,5,4,4,1,0,6.0,neutral or dissatisfied +10357,29227,Female,Loyal Customer,58,Business travel,Eco,550,5,2,2,2,3,5,1,5,5,5,5,2,5,2,0,0.0,satisfied +10358,78212,Female,Loyal Customer,43,Personal Travel,Eco,259,3,1,3,3,4,3,2,3,3,3,3,4,3,1,5,4.0,neutral or dissatisfied +10359,99926,Female,Loyal Customer,35,Business travel,Business,764,4,4,4,4,5,5,4,2,2,2,2,3,2,3,0,27.0,satisfied +10360,124631,Male,Loyal Customer,46,Personal Travel,Eco,1671,1,5,1,3,2,1,2,2,5,4,2,4,3,2,0,0.0,neutral or dissatisfied +10361,88370,Male,Loyal Customer,50,Business travel,Business,2179,1,1,1,1,5,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +10362,97892,Male,Loyal Customer,31,Business travel,Business,612,5,5,5,5,3,3,3,3,4,3,5,4,5,3,0,0.0,satisfied +10363,29182,Female,disloyal Customer,23,Business travel,Eco Plus,697,4,0,4,4,2,4,4,2,2,5,1,5,5,2,0,0.0,satisfied +10364,85647,Female,Loyal Customer,35,Business travel,Eco Plus,259,1,4,3,4,1,1,1,1,4,3,3,4,3,1,9,8.0,neutral or dissatisfied +10365,82785,Male,disloyal Customer,57,Business travel,Business,231,1,1,1,3,3,1,3,3,2,3,3,3,3,3,37,31.0,neutral or dissatisfied +10366,35375,Male,Loyal Customer,38,Business travel,Business,2762,2,3,3,3,4,3,4,2,2,2,2,1,2,2,16,25.0,neutral or dissatisfied +10367,54503,Female,disloyal Customer,52,Business travel,Eco,802,2,2,2,3,5,2,5,5,3,1,5,3,1,5,0,0.0,neutral or dissatisfied +10368,84154,Male,Loyal Customer,20,Personal Travel,Eco,1355,3,4,3,4,1,3,1,1,2,3,3,4,3,1,57,45.0,neutral or dissatisfied +10369,32559,Female,Loyal Customer,43,Business travel,Eco,102,4,1,4,1,5,2,3,4,4,4,4,1,4,5,2,1.0,satisfied +10370,113609,Male,Loyal Customer,57,Personal Travel,Eco,236,2,5,2,3,3,2,1,3,1,2,2,2,4,3,1,0.0,neutral or dissatisfied +10371,39043,Male,Loyal Customer,57,Personal Travel,Eco,391,3,5,3,4,5,3,1,5,5,5,5,3,4,5,0,0.0,neutral or dissatisfied +10372,115175,Male,Loyal Customer,58,Business travel,Business,2814,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +10373,37815,Female,Loyal Customer,45,Personal Travel,Eco Plus,1053,2,4,2,3,4,5,5,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +10374,1807,Male,Loyal Customer,55,Business travel,Business,2113,4,4,4,4,4,3,2,4,4,4,4,1,4,3,0,3.0,neutral or dissatisfied +10375,105244,Male,Loyal Customer,37,Business travel,Eco Plus,377,3,4,4,4,3,3,3,3,4,1,4,1,4,3,32,13.0,neutral or dissatisfied +10376,18845,Male,Loyal Customer,51,Business travel,Business,1945,1,1,1,1,4,3,2,3,3,3,3,5,3,3,0,0.0,satisfied +10377,31177,Female,Loyal Customer,49,Business travel,Business,1620,5,5,5,5,4,3,2,4,4,4,4,3,4,3,0,24.0,satisfied +10378,119224,Female,Loyal Customer,7,Personal Travel,Eco,331,4,3,4,3,2,4,2,2,3,5,3,1,2,2,0,0.0,neutral or dissatisfied +10379,77942,Male,Loyal Customer,50,Business travel,Business,1947,3,3,3,3,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +10380,112956,Female,Loyal Customer,65,Personal Travel,Eco,1390,3,3,3,3,3,4,4,1,1,3,1,2,1,4,0,0.0,neutral or dissatisfied +10381,104663,Female,Loyal Customer,31,Business travel,Business,641,5,5,5,5,4,5,4,4,3,2,5,5,5,4,2,1.0,satisfied +10382,25964,Female,disloyal Customer,40,Business travel,Business,546,2,2,2,1,2,2,2,2,4,1,2,5,2,2,0,10.0,neutral or dissatisfied +10383,20417,Male,Loyal Customer,47,Business travel,Business,2095,1,1,1,1,5,3,3,1,1,1,1,4,1,4,5,0.0,neutral or dissatisfied +10384,122343,Male,Loyal Customer,50,Business travel,Business,3189,2,2,2,2,2,4,5,5,5,5,5,3,5,3,59,34.0,satisfied +10385,43489,Male,disloyal Customer,36,Business travel,Business,279,2,2,2,3,2,2,2,2,2,5,3,1,4,2,0,0.0,neutral or dissatisfied +10386,108340,Male,Loyal Customer,33,Business travel,Business,1838,4,4,4,4,3,3,3,3,4,2,5,3,5,3,11,0.0,satisfied +10387,67924,Male,Loyal Customer,26,Personal Travel,Eco,1235,3,4,4,2,5,4,1,5,4,2,5,3,5,5,0,12.0,neutral or dissatisfied +10388,82611,Female,Loyal Customer,16,Business travel,Business,528,4,4,4,4,4,4,4,4,1,3,4,2,4,4,1,0.0,satisfied +10389,52176,Male,disloyal Customer,38,Business travel,Eco,237,1,3,1,4,2,1,2,2,5,5,5,2,2,2,0,0.0,neutral or dissatisfied +10390,47680,Male,Loyal Customer,68,Personal Travel,Eco,1464,4,4,3,3,1,3,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +10391,16747,Male,Loyal Customer,35,Business travel,Business,569,3,3,3,3,1,2,3,4,4,4,4,5,4,4,90,94.0,satisfied +10392,80488,Male,Loyal Customer,18,Personal Travel,Eco Plus,1299,2,2,2,4,5,2,3,5,2,4,4,2,4,5,1,0.0,neutral or dissatisfied +10393,3498,Female,Loyal Customer,14,Personal Travel,Eco,990,3,5,3,4,3,3,3,3,3,4,5,4,4,3,8,7.0,neutral or dissatisfied +10394,81606,Male,disloyal Customer,16,Business travel,Eco,334,3,4,3,4,3,3,2,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +10395,121246,Male,Loyal Customer,30,Business travel,Business,2075,2,2,2,2,2,2,2,2,2,3,3,2,2,2,161,124.0,neutral or dissatisfied +10396,63621,Female,Loyal Customer,49,Personal Travel,Eco,1440,1,5,1,1,5,4,5,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +10397,117518,Female,Loyal Customer,42,Business travel,Business,872,1,1,1,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +10398,112819,Female,disloyal Customer,44,Business travel,Business,1164,4,4,4,5,3,4,3,3,3,2,5,5,5,3,10,0.0,neutral or dissatisfied +10399,104970,Male,Loyal Customer,41,Business travel,Business,3019,3,3,3,3,5,5,5,4,4,4,4,4,4,3,23,9.0,satisfied +10400,70129,Male,Loyal Customer,36,Business travel,Business,1886,3,2,4,2,4,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +10401,93895,Female,Loyal Customer,43,Personal Travel,Eco,590,1,4,1,4,3,3,3,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +10402,15497,Male,Loyal Customer,51,Personal Travel,Eco,164,5,4,5,3,1,5,1,1,3,2,5,5,5,1,0,11.0,satisfied +10403,8021,Female,Loyal Customer,34,Business travel,Business,2487,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +10404,108241,Female,Loyal Customer,56,Business travel,Business,1682,1,1,4,1,5,5,5,5,5,5,5,4,5,5,10,5.0,satisfied +10405,105943,Female,Loyal Customer,42,Personal Travel,Eco Plus,1491,2,1,2,1,1,2,1,2,2,2,2,3,2,3,6,0.0,neutral or dissatisfied +10406,66096,Male,Loyal Customer,69,Personal Travel,Eco Plus,1055,2,5,2,3,2,2,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +10407,95843,Male,Loyal Customer,56,Business travel,Business,759,3,3,3,3,3,4,4,4,4,4,4,4,4,3,10,0.0,satisfied +10408,129281,Male,disloyal Customer,33,Business travel,Business,550,2,2,2,2,3,2,3,3,4,5,4,3,4,3,0,8.0,neutral or dissatisfied +10409,47301,Male,Loyal Customer,34,Business travel,Business,1512,4,4,4,4,4,3,3,5,5,5,5,2,5,2,0,0.0,satisfied +10410,96927,Male,Loyal Customer,50,Business travel,Business,2937,1,1,5,1,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10411,116699,Female,disloyal Customer,20,Business travel,Eco Plus,337,2,1,2,3,2,2,2,2,1,2,2,1,2,2,14,32.0,neutral or dissatisfied +10412,78034,Female,Loyal Customer,70,Personal Travel,Eco,332,2,5,2,3,3,5,4,4,4,2,4,5,4,4,0,0.0,neutral or dissatisfied +10413,28862,Male,Loyal Customer,53,Business travel,Eco,956,4,4,3,4,4,4,4,4,4,2,1,1,2,4,0,0.0,satisfied +10414,59197,Female,Loyal Customer,42,Business travel,Business,1440,5,5,5,5,2,5,4,5,5,4,5,4,5,5,7,0.0,satisfied +10415,29381,Female,Loyal Customer,26,Business travel,Business,2355,5,5,5,5,4,4,4,4,1,4,3,4,4,4,0,0.0,satisfied +10416,77345,Female,Loyal Customer,53,Business travel,Business,588,1,1,5,1,4,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +10417,5634,Female,Loyal Customer,35,Personal Travel,Eco Plus,685,3,3,3,4,5,3,4,5,3,4,3,2,3,5,0,10.0,neutral or dissatisfied +10418,30849,Male,Loyal Customer,25,Business travel,Business,973,1,1,1,1,3,4,3,3,5,4,2,3,2,3,12,0.0,satisfied +10419,32159,Female,Loyal Customer,36,Business travel,Business,2198,5,5,5,5,1,2,4,4,4,4,5,4,4,5,3,3.0,satisfied +10420,77003,Female,Loyal Customer,54,Business travel,Eco,368,2,5,5,5,1,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +10421,48473,Male,Loyal Customer,45,Business travel,Business,3439,1,4,4,4,3,3,4,1,1,1,1,4,1,2,3,2.0,neutral or dissatisfied +10422,58957,Male,Loyal Customer,46,Business travel,Business,1723,4,4,4,4,5,3,5,4,4,4,4,5,4,4,0,0.0,satisfied +10423,18633,Female,Loyal Customer,48,Personal Travel,Eco,190,3,5,0,1,3,4,4,1,1,0,1,3,1,4,0,6.0,neutral or dissatisfied +10424,78925,Male,Loyal Customer,43,Business travel,Business,3587,4,4,4,4,4,4,5,4,4,4,4,3,4,4,2,2.0,satisfied +10425,584,Male,disloyal Customer,25,Business travel,Business,282,1,1,1,3,2,1,2,2,3,1,4,1,4,2,0,1.0,neutral or dissatisfied +10426,28683,Female,Loyal Customer,48,Personal Travel,Eco,2777,4,3,4,4,4,4,3,3,3,4,3,3,3,2,0,0.0,satisfied +10427,118946,Female,Loyal Customer,46,Business travel,Business,3388,4,4,4,4,4,4,5,4,4,4,4,3,4,4,129,117.0,satisfied +10428,51238,Male,Loyal Customer,47,Business travel,Eco Plus,209,3,5,5,5,3,3,3,3,1,1,1,3,2,3,34,20.0,satisfied +10429,93759,Female,disloyal Customer,20,Business travel,Eco,368,1,2,1,3,2,1,2,2,4,4,3,4,4,2,16,6.0,neutral or dissatisfied +10430,92489,Male,Loyal Customer,28,Business travel,Business,2139,2,1,3,1,2,2,2,2,1,3,3,4,4,2,11,28.0,neutral or dissatisfied +10431,99282,Male,Loyal Customer,44,Business travel,Eco,935,3,4,1,4,3,3,3,3,2,4,4,4,4,3,0,1.0,neutral or dissatisfied +10432,31192,Male,Loyal Customer,47,Business travel,Business,1864,1,1,1,1,3,4,3,4,4,4,4,4,4,3,0,5.0,satisfied +10433,113153,Male,disloyal Customer,24,Business travel,Eco,677,1,1,1,4,4,1,4,4,5,2,4,3,5,4,7,0.0,neutral or dissatisfied +10434,94204,Male,Loyal Customer,56,Business travel,Business,2100,0,5,0,4,4,5,5,4,4,4,4,5,4,3,3,0.0,satisfied +10435,100842,Male,Loyal Customer,63,Business travel,Business,3570,1,4,4,4,5,3,3,1,1,1,1,1,1,1,121,94.0,neutral or dissatisfied +10436,55943,Male,Loyal Customer,54,Business travel,Business,1620,5,5,5,5,2,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +10437,88580,Male,Loyal Customer,29,Personal Travel,Eco,223,2,5,2,5,1,2,1,1,3,3,5,4,4,1,26,31.0,neutral or dissatisfied +10438,64608,Female,disloyal Customer,54,Business travel,Business,190,4,5,5,4,4,4,4,4,5,3,5,5,4,4,0,0.0,satisfied +10439,88369,Male,disloyal Customer,58,Business travel,Eco,442,1,1,1,4,4,1,4,4,2,5,4,1,4,4,44,43.0,neutral or dissatisfied +10440,74489,Female,Loyal Customer,40,Business travel,Business,1235,3,3,3,3,5,4,5,5,5,5,5,4,5,4,0,2.0,satisfied +10441,108855,Female,disloyal Customer,25,Business travel,Business,2139,3,5,3,4,3,3,3,3,4,2,5,5,4,3,11,0.0,neutral or dissatisfied +10442,66542,Male,Loyal Customer,60,Business travel,Business,2165,0,0,0,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +10443,102522,Female,Loyal Customer,14,Personal Travel,Eco,236,2,5,2,5,4,2,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +10444,116166,Male,Loyal Customer,21,Personal Travel,Eco,390,2,4,2,2,3,2,3,3,3,5,5,3,4,3,44,42.0,neutral or dissatisfied +10445,81179,Male,Loyal Customer,39,Business travel,Business,726,2,2,2,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +10446,117503,Female,Loyal Customer,69,Personal Travel,Eco,507,2,4,2,2,4,5,5,4,4,2,1,4,4,5,0,0.0,neutral or dissatisfied +10447,80515,Female,Loyal Customer,64,Personal Travel,Eco,1749,3,4,3,4,3,2,2,4,1,3,4,2,3,2,182,197.0,neutral or dissatisfied +10448,64841,Male,Loyal Customer,58,Business travel,Business,1505,2,2,2,2,3,4,4,5,5,5,5,4,5,4,16,15.0,satisfied +10449,78590,Male,Loyal Customer,39,Business travel,Business,2081,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +10450,615,Female,Loyal Customer,39,Business travel,Business,2145,0,4,0,2,4,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +10451,112434,Male,disloyal Customer,20,Business travel,Eco,853,2,2,2,3,3,2,3,3,5,5,4,5,4,3,0,0.0,neutral or dissatisfied +10452,127000,Male,disloyal Customer,17,Business travel,Business,338,0,2,0,5,5,0,5,5,3,2,5,3,5,5,0,0.0,satisfied +10453,33150,Female,Loyal Customer,49,Personal Travel,Eco,101,4,2,4,4,5,4,4,1,1,4,1,4,1,4,0,0.0,satisfied +10454,102594,Female,disloyal Customer,42,Business travel,Eco Plus,223,1,1,1,1,3,1,3,3,5,5,1,5,4,3,32,21.0,neutral or dissatisfied +10455,112672,Female,Loyal Customer,41,Business travel,Business,605,3,3,3,3,2,5,5,4,4,5,4,3,4,5,11,0.0,satisfied +10456,79271,Female,disloyal Customer,27,Business travel,Business,1101,0,0,0,4,0,1,1,3,3,4,5,1,4,1,0,2.0,satisfied +10457,22234,Female,Loyal Customer,27,Business travel,Business,3076,4,4,4,4,5,5,5,5,5,2,5,3,5,5,68,67.0,satisfied +10458,80654,Female,disloyal Customer,29,Business travel,Business,821,5,5,5,4,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +10459,28251,Female,Loyal Customer,54,Business travel,Eco,1542,4,3,3,3,2,1,2,4,4,4,4,1,4,1,14,45.0,satisfied +10460,97572,Male,disloyal Customer,23,Business travel,Eco,448,3,4,3,4,2,3,2,2,4,1,3,1,4,2,78,70.0,neutral or dissatisfied +10461,66075,Male,Loyal Customer,37,Personal Travel,Eco,1055,1,5,1,4,1,1,1,1,3,2,5,3,4,1,21,21.0,neutral or dissatisfied +10462,57381,Male,Loyal Customer,43,Personal Travel,Eco Plus,414,4,3,4,2,5,4,5,5,1,4,5,5,4,5,0,0.0,neutral or dissatisfied +10463,87757,Male,disloyal Customer,21,Business travel,Eco,214,4,0,4,2,5,4,5,5,4,3,5,5,4,5,2,8.0,satisfied +10464,69213,Male,Loyal Customer,51,Business travel,Business,733,1,1,1,1,5,5,5,5,5,5,5,4,5,5,7,0.0,satisfied +10465,51551,Male,Loyal Customer,24,Business travel,Eco,651,5,4,4,4,5,5,4,5,5,4,2,5,4,5,40,23.0,satisfied +10466,99216,Female,Loyal Customer,28,Business travel,Business,495,1,1,1,1,5,4,5,5,5,5,4,4,5,5,5,4.0,satisfied +10467,25865,Female,disloyal Customer,44,Business travel,Eco Plus,692,1,1,1,4,2,1,2,2,5,2,4,1,4,2,8,0.0,neutral or dissatisfied +10468,102890,Female,disloyal Customer,29,Business travel,Business,1037,4,4,4,3,1,4,1,1,4,5,4,4,4,1,0,0.0,satisfied +10469,67473,Female,Loyal Customer,38,Personal Travel,Eco,592,3,2,3,3,4,3,4,4,4,4,4,2,3,4,0,0.0,neutral or dissatisfied +10470,85567,Female,Loyal Customer,30,Business travel,Business,3560,0,0,0,4,3,3,3,3,3,5,4,4,4,3,1,0.0,satisfied +10471,8185,Female,disloyal Customer,58,Business travel,Eco,402,3,1,3,2,4,3,4,4,3,2,2,1,3,4,0,0.0,neutral or dissatisfied +10472,5974,Female,Loyal Customer,35,Personal Travel,Business,1041,3,5,3,3,2,5,4,2,2,3,2,5,2,5,22,11.0,neutral or dissatisfied +10473,98206,Female,Loyal Customer,39,Personal Travel,Eco,327,4,0,4,3,5,4,5,5,3,4,5,5,5,5,0,20.0,neutral or dissatisfied +10474,16903,Female,Loyal Customer,40,Personal Travel,Eco,746,2,4,2,4,5,2,5,5,4,5,4,4,4,5,14,54.0,neutral or dissatisfied +10475,12729,Male,Loyal Customer,40,Personal Travel,Eco,721,5,1,5,3,3,5,3,3,4,2,4,2,4,3,8,0.0,satisfied +10476,104222,Female,Loyal Customer,48,Business travel,Eco,680,3,1,1,1,1,4,4,3,3,3,3,1,3,2,37,12.0,neutral or dissatisfied +10477,32408,Female,Loyal Customer,46,Business travel,Eco,163,5,3,3,3,2,3,4,5,5,5,5,4,5,1,0,0.0,satisfied +10478,51093,Male,Loyal Customer,12,Personal Travel,Eco,86,2,2,2,4,2,2,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +10479,71816,Female,Loyal Customer,28,Business travel,Business,1723,2,2,2,2,5,5,5,5,5,5,3,3,5,5,0,0.0,satisfied +10480,125047,Male,Loyal Customer,44,Personal Travel,Eco,2300,3,4,3,1,1,3,1,1,5,2,4,5,5,1,4,0.0,neutral or dissatisfied +10481,47273,Female,Loyal Customer,44,Business travel,Eco,574,5,5,5,5,5,5,4,5,5,5,5,3,5,2,0,0.0,satisfied +10482,117632,Female,Loyal Customer,12,Personal Travel,Eco,843,3,1,3,3,4,3,4,4,4,3,4,2,3,4,1,0.0,neutral or dissatisfied +10483,41921,Female,disloyal Customer,36,Business travel,Eco,129,3,3,3,3,3,3,3,3,2,2,2,3,4,3,0,3.0,neutral or dissatisfied +10484,123870,Male,Loyal Customer,40,Business travel,Business,2212,2,5,5,5,4,2,3,2,2,2,2,1,2,4,0,8.0,neutral or dissatisfied +10485,127043,Female,disloyal Customer,28,Business travel,Eco,646,3,3,3,3,3,3,5,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +10486,19647,Male,Loyal Customer,50,Personal Travel,Eco Plus,642,4,3,5,2,4,5,4,4,4,1,1,1,5,4,0,0.0,neutral or dissatisfied +10487,94863,Male,Loyal Customer,33,Business travel,Business,441,1,5,1,1,4,4,4,4,3,4,5,4,5,4,0,2.0,satisfied +10488,121934,Male,Loyal Customer,60,Personal Travel,Eco Plus,337,1,3,1,3,3,1,3,3,1,4,2,2,1,3,0,0.0,neutral or dissatisfied +10489,66775,Female,disloyal Customer,8,Business travel,Eco Plus,802,3,2,3,4,3,3,3,3,1,3,3,2,3,3,45,38.0,neutral or dissatisfied +10490,121129,Male,Loyal Customer,36,Business travel,Business,2402,1,1,1,1,2,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +10491,6761,Male,Loyal Customer,57,Business travel,Business,2796,4,4,4,4,5,4,5,5,5,5,5,3,5,3,3,33.0,satisfied +10492,1390,Male,Loyal Customer,34,Personal Travel,Eco Plus,164,3,4,3,3,1,3,1,1,3,5,4,5,4,1,0,0.0,neutral or dissatisfied +10493,127541,Female,disloyal Customer,8,Business travel,Eco,1009,2,2,2,4,5,2,5,5,4,3,4,2,3,5,0,0.0,neutral or dissatisfied +10494,96224,Male,Loyal Customer,33,Business travel,Eco,460,2,4,4,4,2,2,2,2,3,5,4,2,4,2,36,27.0,neutral or dissatisfied +10495,122870,Female,Loyal Customer,10,Personal Travel,Eco,226,0,4,0,1,5,0,5,5,3,2,4,4,4,5,0,0.0,satisfied +10496,5400,Female,Loyal Customer,23,Personal Travel,Eco,812,3,1,2,3,4,2,4,4,3,2,3,2,3,4,31,24.0,neutral or dissatisfied +10497,78768,Female,Loyal Customer,44,Business travel,Business,1681,3,4,2,2,1,4,4,3,3,2,3,2,3,3,0,9.0,neutral or dissatisfied +10498,7168,Female,Loyal Customer,37,Business travel,Business,3498,0,5,0,4,2,4,4,1,1,1,1,3,1,5,35,33.0,satisfied +10499,46761,Female,Loyal Customer,43,Business travel,Eco Plus,73,4,4,4,4,4,3,2,4,4,4,4,3,4,2,0,0.0,satisfied +10500,66923,Male,Loyal Customer,58,Business travel,Business,2393,1,1,3,1,5,5,5,3,3,4,3,4,3,4,40,29.0,satisfied +10501,110241,Female,Loyal Customer,58,Business travel,Business,1011,2,2,2,2,4,5,5,5,5,5,5,4,5,5,2,0.0,satisfied +10502,79430,Male,Loyal Customer,37,Personal Travel,Eco,502,1,3,1,1,2,1,2,2,1,2,3,1,4,2,18,0.0,neutral or dissatisfied +10503,5948,Female,Loyal Customer,28,Personal Travel,Eco,612,2,4,2,2,2,2,2,2,4,5,5,5,4,2,14,2.0,neutral or dissatisfied +10504,85288,Male,Loyal Customer,57,Personal Travel,Eco,813,4,1,4,4,5,4,5,5,4,1,3,3,3,5,24,1.0,neutral or dissatisfied +10505,50896,Male,Loyal Customer,33,Personal Travel,Eco,337,1,4,4,3,3,4,3,3,5,5,5,4,4,3,34,30.0,neutral or dissatisfied +10506,80927,Female,disloyal Customer,17,Business travel,Eco,341,3,4,3,4,2,3,2,2,1,3,3,1,4,2,0,0.0,neutral or dissatisfied +10507,63198,Female,Loyal Customer,52,Business travel,Business,337,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +10508,73569,Female,Loyal Customer,45,Business travel,Business,2586,2,2,2,2,4,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +10509,58189,Male,disloyal Customer,9,Business travel,Eco,925,3,3,3,1,4,3,4,4,4,2,5,3,5,4,6,0.0,neutral or dissatisfied +10510,8891,Male,Loyal Customer,38,Personal Travel,Eco,622,2,4,2,4,3,2,5,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +10511,24901,Male,Loyal Customer,59,Business travel,Business,2898,2,2,2,2,1,4,3,2,2,2,2,2,2,1,0,12.0,neutral or dissatisfied +10512,36539,Male,Loyal Customer,29,Business travel,Eco,1091,5,1,1,1,5,5,5,5,2,5,4,2,2,5,0,12.0,satisfied +10513,114170,Male,Loyal Customer,50,Business travel,Business,862,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +10514,113479,Male,Loyal Customer,43,Business travel,Business,386,1,2,2,2,1,2,3,1,1,1,1,2,1,4,38,29.0,neutral or dissatisfied +10515,79285,Male,Loyal Customer,43,Business travel,Business,2248,5,5,5,5,4,4,4,5,3,5,5,4,4,4,0,0.0,satisfied +10516,30131,Male,Loyal Customer,20,Personal Travel,Eco,95,3,4,3,3,4,3,4,4,2,4,2,1,2,4,0,0.0,neutral or dissatisfied +10517,72611,Female,Loyal Customer,53,Personal Travel,Eco,918,1,1,1,3,2,4,4,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +10518,112254,Male,Loyal Customer,55,Business travel,Business,1703,2,2,2,2,1,1,3,2,2,1,2,3,2,3,15,19.0,neutral or dissatisfied +10519,41269,Female,Loyal Customer,31,Personal Travel,Eco,305,5,1,5,3,5,5,5,5,3,1,3,3,4,5,0,0.0,satisfied +10520,121912,Female,Loyal Customer,47,Personal Travel,Eco,449,3,4,3,2,3,5,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +10521,16801,Female,disloyal Customer,25,Business travel,Business,645,1,1,1,4,3,1,2,3,3,3,4,1,3,3,38,40.0,neutral or dissatisfied +10522,121531,Female,Loyal Customer,30,Business travel,Business,2747,2,2,2,2,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +10523,75523,Female,Loyal Customer,35,Business travel,Business,337,2,2,3,2,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +10524,47577,Female,Loyal Customer,45,Business travel,Business,1464,1,1,1,1,4,5,5,5,5,5,5,4,5,4,56,31.0,satisfied +10525,93836,Male,Loyal Customer,33,Business travel,Business,391,3,3,3,3,3,3,3,3,2,4,3,2,4,3,18,3.0,neutral or dissatisfied +10526,90814,Female,disloyal Customer,9,Business travel,Eco,545,2,2,2,3,1,2,1,1,4,3,4,4,4,1,0,3.0,neutral or dissatisfied +10527,22043,Male,Loyal Customer,57,Business travel,Eco Plus,448,1,5,5,5,1,1,1,1,1,2,3,2,2,1,11,10.0,neutral or dissatisfied +10528,68345,Female,Loyal Customer,36,Business travel,Eco,1598,1,2,2,2,1,1,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +10529,22262,Female,disloyal Customer,43,Business travel,Eco,143,3,5,3,2,2,3,2,2,3,5,2,2,3,2,70,60.0,neutral or dissatisfied +10530,54331,Male,Loyal Customer,26,Personal Travel,Eco,1597,4,4,5,3,4,5,4,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +10531,68469,Female,disloyal Customer,45,Business travel,Business,1067,4,4,4,1,1,4,1,1,4,5,5,3,5,1,0,0.0,satisfied +10532,49177,Female,Loyal Customer,44,Business travel,Business,3285,0,0,0,1,3,1,3,3,3,3,3,3,3,1,0,0.0,satisfied +10533,37113,Female,disloyal Customer,27,Business travel,Eco,1189,2,2,2,4,4,2,4,4,5,5,1,4,4,4,0,0.0,neutral or dissatisfied +10534,92995,Female,Loyal Customer,46,Personal Travel,Eco,738,2,5,2,5,5,5,5,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +10535,59399,Male,Loyal Customer,58,Personal Travel,Eco,2486,1,2,1,3,5,1,5,5,2,4,3,3,3,5,0,0.0,neutral or dissatisfied +10536,20156,Male,Loyal Customer,29,Business travel,Business,403,1,1,1,1,5,5,5,5,3,1,3,2,4,5,21,4.0,satisfied +10537,86828,Male,disloyal Customer,24,Business travel,Eco,692,3,3,3,4,3,3,3,3,4,1,4,2,3,3,72,77.0,neutral or dissatisfied +10538,110152,Female,Loyal Customer,36,Business travel,Business,2465,1,1,1,1,2,5,1,2,2,2,2,4,2,5,0,0.0,satisfied +10539,31568,Female,disloyal Customer,43,Business travel,Eco Plus,453,5,5,5,1,4,5,4,4,2,3,3,5,4,4,0,0.0,satisfied +10540,69136,Female,Loyal Customer,57,Business travel,Business,2248,4,3,4,4,5,4,4,3,3,3,3,5,3,5,18,7.0,satisfied +10541,4435,Male,Loyal Customer,32,Business travel,Business,2877,5,5,5,5,4,4,4,4,3,3,2,2,3,4,0,0.0,satisfied +10542,102715,Female,Loyal Customer,61,Personal Travel,Eco,365,3,5,3,5,5,5,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +10543,100803,Female,Loyal Customer,69,Personal Travel,Eco,748,3,5,4,3,1,4,1,5,5,4,5,3,5,1,0,0.0,neutral or dissatisfied +10544,75000,Male,Loyal Customer,62,Personal Travel,Eco Plus,2454,1,5,1,3,4,1,4,4,5,4,3,4,4,4,50,92.0,neutral or dissatisfied +10545,45525,Female,Loyal Customer,8,Personal Travel,Eco,689,0,4,0,3,1,4,1,1,3,2,5,3,5,1,0,1.0,satisfied +10546,3255,Female,Loyal Customer,56,Business travel,Business,419,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +10547,37532,Female,Loyal Customer,33,Business travel,Business,2739,2,2,2,2,2,4,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +10548,64037,Female,disloyal Customer,25,Business travel,Business,921,1,0,1,1,1,1,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +10549,119795,Male,disloyal Customer,13,Business travel,Eco,936,2,2,2,4,2,2,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +10550,11278,Female,Loyal Customer,48,Personal Travel,Eco,201,5,1,5,3,4,3,3,2,2,5,4,3,2,4,0,0.0,satisfied +10551,99726,Male,Loyal Customer,50,Business travel,Business,255,2,2,2,2,3,5,4,4,4,4,4,4,4,3,21,14.0,satisfied +10552,99608,Female,Loyal Customer,30,Business travel,Eco Plus,829,3,2,2,2,3,3,3,3,2,1,3,4,3,3,0,0.0,neutral or dissatisfied +10553,1847,Male,Loyal Customer,24,Personal Travel,Eco,500,1,5,1,2,4,1,4,4,5,2,4,4,4,4,0,0.0,neutral or dissatisfied +10554,55956,Female,Loyal Customer,53,Business travel,Business,1620,2,2,2,2,5,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +10555,56666,Male,Loyal Customer,51,Personal Travel,Eco,937,0,3,0,2,3,0,3,3,3,3,2,2,2,3,29,13.0,satisfied +10556,68273,Male,Loyal Customer,56,Business travel,Business,3219,1,1,1,1,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +10557,73375,Female,disloyal Customer,26,Business travel,Eco,1144,3,3,3,3,1,3,1,1,2,1,3,2,3,1,7,16.0,neutral or dissatisfied +10558,30416,Female,Loyal Customer,31,Business travel,Eco Plus,862,5,1,1,1,5,5,5,5,3,5,1,3,3,5,0,9.0,satisfied +10559,62701,Male,Loyal Customer,54,Business travel,Business,2556,2,2,2,2,4,4,4,3,5,4,5,4,5,4,8,39.0,satisfied +10560,19111,Female,Loyal Customer,37,Business travel,Eco,323,2,3,3,3,2,2,2,2,2,3,4,3,5,2,0,0.0,satisfied +10561,91898,Female,Loyal Customer,56,Business travel,Business,2586,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,1.0,satisfied +10562,109759,Female,Loyal Customer,18,Personal Travel,Eco Plus,587,1,4,1,1,5,1,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +10563,69762,Male,Loyal Customer,41,Personal Travel,Eco,1085,3,4,3,1,4,3,4,4,3,2,5,3,4,4,0,55.0,neutral or dissatisfied +10564,127879,Female,Loyal Customer,11,Personal Travel,Eco,1276,2,5,1,2,4,1,4,4,3,2,5,4,5,4,6,11.0,neutral or dissatisfied +10565,50497,Female,Loyal Customer,42,Personal Travel,Eco,77,5,4,5,4,5,4,5,1,1,5,1,5,1,4,0,0.0,satisfied +10566,41825,Male,Loyal Customer,69,Personal Travel,Eco,489,1,2,1,3,3,1,3,3,2,3,4,4,4,3,0,3.0,neutral or dissatisfied +10567,115239,Female,Loyal Customer,50,Business travel,Business,3267,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +10568,82628,Female,Loyal Customer,50,Personal Travel,Eco,528,3,1,3,3,5,3,4,1,1,3,1,1,1,4,0,0.0,neutral or dissatisfied +10569,21472,Male,Loyal Customer,61,Business travel,Business,3237,2,2,2,2,2,2,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +10570,93106,Male,Loyal Customer,47,Business travel,Eco Plus,641,4,4,4,4,4,4,4,4,5,3,4,4,2,4,168,163.0,neutral or dissatisfied +10571,57579,Female,Loyal Customer,52,Business travel,Business,1597,3,3,3,3,3,4,4,3,3,4,3,3,3,4,5,0.0,satisfied +10572,8900,Female,Loyal Customer,53,Personal Travel,Eco Plus,622,1,4,1,1,3,5,4,3,3,1,3,3,3,3,36,61.0,neutral or dissatisfied +10573,56645,Male,Loyal Customer,36,Business travel,Business,597,2,3,3,3,3,2,1,2,2,2,2,4,2,3,15,40.0,neutral or dissatisfied +10574,54624,Male,Loyal Customer,32,Business travel,Eco,861,4,3,3,3,4,4,4,4,2,5,1,1,5,4,0,0.0,satisfied +10575,41428,Male,Loyal Customer,8,Personal Travel,Eco,809,3,4,3,3,2,3,2,2,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +10576,110901,Male,Loyal Customer,76,Business travel,Eco,404,3,4,4,4,3,3,3,3,1,4,2,2,2,3,6,4.0,neutral or dissatisfied +10577,125853,Female,disloyal Customer,10,Business travel,Eco,920,3,3,3,3,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +10578,64223,Male,Loyal Customer,53,Business travel,Business,1660,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +10579,115924,Male,Loyal Customer,47,Business travel,Eco,337,5,4,4,4,5,5,5,5,4,2,1,5,3,5,24,21.0,satisfied +10580,47099,Female,Loyal Customer,45,Personal Travel,Eco,438,3,5,3,1,5,4,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +10581,55477,Male,Loyal Customer,47,Business travel,Business,1825,5,5,1,5,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +10582,62726,Female,Loyal Customer,54,Business travel,Business,2504,1,2,1,1,5,5,5,3,4,3,4,5,5,5,5,12.0,satisfied +10583,39386,Male,Loyal Customer,23,Business travel,Business,546,3,3,3,3,4,4,4,4,2,5,4,1,2,4,0,0.0,satisfied +10584,12591,Male,Loyal Customer,23,Business travel,Business,542,3,3,3,3,3,3,3,3,1,2,3,2,3,3,33,39.0,neutral or dissatisfied +10585,5866,Male,Loyal Customer,33,Business travel,Business,1822,2,2,2,2,5,4,5,5,4,3,4,5,5,5,0,0.0,satisfied +10586,80829,Male,Loyal Customer,62,Business travel,Eco,692,1,1,1,1,1,1,1,1,1,5,4,3,4,1,0,0.0,neutral or dissatisfied +10587,19512,Female,Loyal Customer,21,Personal Travel,Eco,566,1,4,1,4,4,1,2,4,3,4,4,4,4,4,1,9.0,neutral or dissatisfied +10588,21777,Female,Loyal Customer,47,Business travel,Business,241,0,0,0,4,5,5,5,4,4,4,4,5,4,3,19,7.0,satisfied +10589,79187,Male,Loyal Customer,12,Personal Travel,Eco Plus,2422,2,5,2,4,2,3,3,4,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +10590,24183,Male,disloyal Customer,57,Business travel,Eco,147,4,0,4,1,3,4,3,3,4,5,2,4,5,3,23,45.0,neutral or dissatisfied +10591,2063,Female,Loyal Customer,44,Business travel,Business,2610,1,2,2,2,5,4,3,1,1,2,1,2,1,1,0,4.0,neutral or dissatisfied +10592,118366,Female,Loyal Customer,27,Business travel,Eco Plus,602,1,4,4,4,1,1,1,1,3,3,1,4,1,1,5,0.0,neutral or dissatisfied +10593,74304,Male,Loyal Customer,54,Business travel,Business,2876,4,4,4,4,5,4,4,5,5,5,5,4,5,4,2,1.0,satisfied +10594,25610,Female,disloyal Customer,26,Business travel,Eco,666,3,0,3,4,4,3,4,4,2,2,2,1,3,4,0,0.0,neutral or dissatisfied +10595,110685,Female,Loyal Customer,67,Personal Travel,Eco,945,4,2,4,3,1,2,2,4,4,4,4,4,4,4,0,2.0,satisfied +10596,127800,Female,Loyal Customer,59,Business travel,Eco,1044,3,4,4,4,4,3,3,3,3,3,3,4,3,4,0,5.0,neutral or dissatisfied +10597,88225,Male,Loyal Customer,40,Business travel,Business,3320,4,4,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +10598,1903,Female,Loyal Customer,39,Business travel,Business,351,2,2,2,2,4,5,4,4,4,5,4,4,4,3,0,0.0,satisfied +10599,2940,Male,Loyal Customer,29,Personal Travel,Business,737,3,2,3,3,2,3,2,2,3,2,4,2,3,2,0,0.0,neutral or dissatisfied +10600,104635,Male,Loyal Customer,53,Personal Travel,Eco,861,2,5,2,3,2,2,2,2,5,2,5,4,4,2,0,0.0,neutral or dissatisfied +10601,80375,Male,Loyal Customer,40,Business travel,Business,1868,4,5,3,3,4,3,2,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +10602,116074,Female,Loyal Customer,28,Personal Travel,Eco,358,3,4,3,4,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +10603,41485,Male,Loyal Customer,45,Business travel,Eco,1464,4,4,4,4,4,4,4,4,2,1,4,5,2,4,67,52.0,satisfied +10604,46135,Female,Loyal Customer,25,Business travel,Eco,627,5,3,3,3,5,5,5,5,5,4,1,5,1,5,0,29.0,satisfied +10605,43243,Male,Loyal Customer,42,Business travel,Business,3739,1,1,1,1,4,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +10606,9366,Male,Loyal Customer,67,Business travel,Eco,401,1,5,5,5,1,1,1,1,4,3,3,1,2,1,0,0.0,neutral or dissatisfied +10607,93455,Female,Loyal Customer,61,Personal Travel,Eco,672,3,2,3,3,1,4,4,1,1,3,1,2,1,1,75,60.0,neutral or dissatisfied +10608,51713,Female,Loyal Customer,33,Business travel,Eco,237,3,3,3,3,5,5,5,5,5,4,1,5,4,5,0,0.0,satisfied +10609,47762,Male,Loyal Customer,49,Business travel,Eco,838,4,5,5,5,5,4,5,5,5,5,3,3,3,5,0,3.0,satisfied +10610,65411,Male,Loyal Customer,31,Business travel,Business,631,1,1,1,1,5,4,5,5,4,2,4,4,4,5,1,0.0,satisfied +10611,58958,Male,Loyal Customer,40,Business travel,Business,1846,1,1,1,1,4,4,5,5,5,5,5,3,5,5,27,13.0,satisfied +10612,116785,Female,Loyal Customer,59,Personal Travel,Eco Plus,447,2,2,2,2,2,3,3,5,5,2,5,2,5,3,6,9.0,neutral or dissatisfied +10613,65723,Female,disloyal Customer,15,Business travel,Eco,1061,2,2,2,3,1,2,1,1,4,3,3,4,3,1,0,0.0,neutral or dissatisfied +10614,78597,Male,disloyal Customer,25,Business travel,Eco,958,3,3,3,2,4,3,4,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +10615,32857,Male,Loyal Customer,18,Personal Travel,Eco,102,2,5,2,4,5,2,5,5,2,3,4,2,4,5,0,0.0,neutral or dissatisfied +10616,76586,Female,Loyal Customer,39,Business travel,Eco,481,4,1,1,1,4,4,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +10617,33273,Female,Loyal Customer,68,Personal Travel,Eco Plus,102,1,5,1,4,4,5,1,5,5,1,4,2,5,2,0,0.0,neutral or dissatisfied +10618,108522,Male,Loyal Customer,37,Personal Travel,Eco Plus,519,2,4,2,3,3,2,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +10619,60492,Male,disloyal Customer,25,Business travel,Business,862,1,5,1,1,3,1,3,3,3,4,5,3,4,3,0,0.0,neutral or dissatisfied +10620,93591,Male,Loyal Customer,32,Personal Travel,Eco,159,3,4,3,2,4,3,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +10621,99545,Male,disloyal Customer,24,Business travel,Eco,802,5,5,5,3,1,5,1,1,3,2,4,4,5,1,0,0.0,satisfied +10622,44806,Female,Loyal Customer,16,Business travel,Business,1847,1,1,1,1,5,5,5,5,3,3,1,4,5,5,19,14.0,satisfied +10623,1365,Female,Loyal Customer,60,Business travel,Business,158,1,1,1,1,3,5,4,4,4,4,5,4,4,3,0,0.0,satisfied +10624,102077,Female,Loyal Customer,55,Business travel,Business,1924,0,5,0,2,5,4,4,3,3,3,3,3,3,5,6,7.0,satisfied +10625,53955,Female,disloyal Customer,8,Business travel,Eco,1325,2,2,2,3,4,2,4,4,2,3,3,3,3,4,100,76.0,neutral or dissatisfied +10626,112276,Female,Loyal Customer,21,Personal Travel,Eco,1703,3,5,3,2,1,3,1,1,4,4,5,5,2,1,42,26.0,neutral or dissatisfied +10627,14036,Female,Loyal Customer,18,Personal Travel,Eco,1117,3,5,3,3,1,3,1,1,5,4,5,5,5,1,0,0.0,neutral or dissatisfied +10628,20318,Male,disloyal Customer,58,Business travel,Business,265,2,2,2,4,4,2,4,4,5,4,5,5,4,4,80,74.0,neutral or dissatisfied +10629,56929,Female,Loyal Customer,49,Business travel,Business,2454,2,2,2,2,2,2,2,5,3,5,5,2,3,2,15,79.0,satisfied +10630,52067,Male,Loyal Customer,28,Business travel,Business,2591,4,4,2,4,4,4,4,4,5,1,3,2,5,4,0,0.0,satisfied +10631,99497,Male,Loyal Customer,15,Personal Travel,Eco,283,2,4,2,4,3,2,2,3,4,3,5,4,5,3,7,12.0,neutral or dissatisfied +10632,12149,Female,Loyal Customer,43,Business travel,Eco,1042,5,2,2,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +10633,49579,Male,Loyal Customer,47,Business travel,Eco,337,4,4,4,4,4,4,4,4,1,1,1,2,3,4,0,2.0,satisfied +10634,7891,Female,Loyal Customer,49,Personal Travel,Eco,948,2,2,2,3,4,3,5,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +10635,110759,Female,disloyal Customer,41,Business travel,Business,1166,2,2,2,2,1,2,1,1,5,5,4,4,5,1,0,0.0,satisfied +10636,26081,Male,Loyal Customer,52,Business travel,Business,591,1,1,1,1,1,3,1,5,5,5,5,4,5,1,0,0.0,satisfied +10637,56280,Male,disloyal Customer,43,Business travel,Eco,1475,2,2,2,3,2,2,2,2,2,1,2,1,3,2,0,0.0,neutral or dissatisfied +10638,20250,Female,disloyal Customer,26,Business travel,Eco,346,5,0,5,2,2,5,4,2,5,3,3,4,1,2,0,0.0,satisfied +10639,50517,Female,Loyal Customer,43,Personal Travel,Eco,209,2,5,2,1,2,3,3,1,1,2,1,5,1,4,12,6.0,neutral or dissatisfied +10640,45029,Female,disloyal Customer,25,Business travel,Eco,867,1,1,1,3,3,1,3,3,4,1,3,4,4,3,4,22.0,neutral or dissatisfied +10641,16645,Female,disloyal Customer,37,Business travel,Eco,488,2,1,2,3,4,2,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +10642,50355,Female,disloyal Customer,24,Business travel,Eco,86,5,0,5,4,3,5,4,3,4,2,5,3,3,3,0,0.0,satisfied +10643,93339,Male,Loyal Customer,34,Business travel,Business,3687,3,3,3,3,5,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +10644,93982,Male,Loyal Customer,11,Business travel,Business,1218,2,4,4,4,2,2,2,2,2,3,4,1,3,2,0,2.0,neutral or dissatisfied +10645,57146,Male,Loyal Customer,36,Personal Travel,Eco Plus,1222,2,1,3,4,4,3,4,4,1,1,3,3,3,4,2,0.0,neutral or dissatisfied +10646,67139,Male,disloyal Customer,24,Business travel,Eco,1102,3,3,3,3,4,3,1,4,1,1,3,3,3,4,0,0.0,neutral or dissatisfied +10647,86131,Female,Loyal Customer,39,Business travel,Business,356,1,1,1,1,2,5,5,2,2,2,2,4,2,3,0,0.0,satisfied +10648,74042,Female,disloyal Customer,25,Business travel,Business,1194,0,0,0,3,1,0,1,1,5,4,5,5,5,1,0,0.0,satisfied +10649,27278,Male,Loyal Customer,27,Personal Travel,Business,1050,2,4,2,1,2,2,2,2,5,5,5,3,4,2,0,2.0,neutral or dissatisfied +10650,106975,Female,Loyal Customer,76,Business travel,Business,1934,3,4,3,3,3,1,2,3,3,3,3,5,3,5,10,7.0,satisfied +10651,4549,Male,Loyal Customer,52,Business travel,Business,2708,5,5,5,5,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +10652,25545,Male,Loyal Customer,19,Business travel,Eco Plus,516,5,4,4,4,5,5,4,5,2,1,2,5,4,5,8,0.0,satisfied +10653,127988,Male,Loyal Customer,17,Personal Travel,Eco,1149,3,1,2,3,2,2,2,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +10654,36981,Female,Loyal Customer,26,Business travel,Business,3828,2,2,2,2,4,5,4,4,5,5,4,2,4,4,0,0.0,satisfied +10655,8365,Male,Loyal Customer,59,Business travel,Business,2963,4,4,4,4,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +10656,91448,Male,Loyal Customer,32,Business travel,Business,2825,3,3,3,3,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +10657,126385,Male,Loyal Customer,67,Personal Travel,Eco,650,4,2,5,3,1,5,1,1,3,5,3,3,2,1,0,0.0,satisfied +10658,118655,Female,disloyal Customer,23,Business travel,Eco,651,3,1,3,2,3,2,2,4,1,2,2,2,1,2,217,218.0,neutral or dissatisfied +10659,103920,Male,Loyal Customer,60,Business travel,Business,2302,1,1,1,1,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +10660,5237,Female,disloyal Customer,27,Business travel,Business,293,2,2,2,4,3,2,3,3,5,5,4,4,5,3,5,4.0,neutral or dissatisfied +10661,16340,Female,Loyal Customer,40,Business travel,Eco Plus,594,4,3,3,3,4,4,4,4,3,2,1,3,1,4,0,17.0,satisfied +10662,34830,Male,Loyal Customer,55,Business travel,Eco Plus,264,2,2,2,2,2,2,2,2,4,3,2,2,5,2,0,0.0,satisfied +10663,90003,Male,disloyal Customer,30,Business travel,Business,1084,2,2,2,4,1,2,1,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +10664,115715,Male,Loyal Customer,40,Business travel,Eco,404,2,4,4,4,2,2,2,2,2,4,3,2,4,2,40,34.0,neutral or dissatisfied +10665,115038,Male,Loyal Customer,66,Business travel,Business,2724,0,0,0,2,5,4,4,4,4,4,5,3,4,5,0,0.0,satisfied +10666,11962,Male,Loyal Customer,52,Business travel,Business,1940,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10667,6936,Female,Loyal Customer,53,Business travel,Business,588,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,3.0,satisfied +10668,65417,Female,Loyal Customer,67,Personal Travel,Eco Plus,631,3,4,3,2,5,5,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +10669,6527,Female,Loyal Customer,21,Personal Travel,Eco,599,4,3,4,3,4,4,4,4,5,1,5,4,4,4,0,0.0,satisfied +10670,7964,Female,Loyal Customer,44,Personal Travel,Eco,594,3,5,3,5,1,3,4,4,4,3,4,2,4,5,0,0.0,neutral or dissatisfied +10671,104200,Female,disloyal Customer,23,Business travel,Eco,1016,2,3,3,4,4,3,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +10672,70518,Male,Loyal Customer,53,Business travel,Business,3486,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +10673,42855,Male,Loyal Customer,60,Personal Travel,Eco,328,3,0,3,3,2,3,2,2,4,3,5,4,5,2,0,0.0,neutral or dissatisfied +10674,9407,Female,disloyal Customer,25,Business travel,Eco,1027,3,4,4,4,2,4,3,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +10675,17532,Male,Loyal Customer,46,Business travel,Business,1857,3,3,3,3,3,3,2,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +10676,124691,Female,Loyal Customer,62,Business travel,Eco,399,2,5,5,5,4,3,2,2,2,2,2,3,2,4,16,50.0,neutral or dissatisfied +10677,108949,Male,disloyal Customer,24,Business travel,Business,542,5,0,5,2,5,5,5,5,3,5,4,3,5,5,99,89.0,satisfied +10678,2666,Female,disloyal Customer,38,Business travel,Business,597,5,5,5,5,5,5,5,5,5,4,4,4,5,5,0,0.0,satisfied +10679,48125,Female,Loyal Customer,55,Business travel,Business,2759,4,4,4,4,2,3,2,4,4,4,4,5,4,4,0,0.0,satisfied +10680,36794,Female,Loyal Customer,47,Personal Travel,Eco,2704,3,5,3,3,3,3,2,4,5,4,4,2,3,2,138,153.0,neutral or dissatisfied +10681,99937,Male,Loyal Customer,31,Business travel,Eco Plus,764,2,4,1,4,2,2,2,2,1,2,3,1,4,2,74,50.0,neutral or dissatisfied +10682,25973,Male,Loyal Customer,47,Personal Travel,Eco,946,1,2,1,2,2,1,2,2,2,5,2,3,3,2,0,0.0,neutral or dissatisfied +10683,4970,Male,Loyal Customer,40,Business travel,Eco Plus,931,3,4,1,1,3,3,3,3,2,5,3,2,3,3,3,6.0,neutral or dissatisfied +10684,91313,Female,Loyal Customer,49,Business travel,Business,270,0,0,0,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +10685,44295,Female,Loyal Customer,25,Business travel,Business,563,3,5,5,5,3,3,3,3,1,5,3,1,3,3,0,0.0,neutral or dissatisfied +10686,122287,Female,Loyal Customer,57,Personal Travel,Eco,544,3,3,3,4,3,1,5,5,5,3,5,2,5,1,0,6.0,neutral or dissatisfied +10687,12181,Female,disloyal Customer,25,Business travel,Eco,675,3,3,3,3,4,3,4,4,1,1,4,1,4,4,33,14.0,neutral or dissatisfied +10688,4353,Male,Loyal Customer,41,Business travel,Business,1884,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,15.0,satisfied +10689,93676,Male,Loyal Customer,20,Personal Travel,Eco,655,3,0,3,3,3,3,1,3,4,2,3,5,1,3,0,0.0,neutral or dissatisfied +10690,123264,Male,Loyal Customer,46,Personal Travel,Eco,328,1,5,1,3,3,1,1,3,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +10691,72248,Male,Loyal Customer,21,Business travel,Business,919,3,3,3,3,3,3,3,3,3,4,5,5,5,3,0,0.0,satisfied +10692,10898,Female,Loyal Customer,37,Business travel,Business,2604,4,4,4,4,1,4,3,2,2,2,4,3,2,2,0,0.0,neutral or dissatisfied +10693,35536,Male,Loyal Customer,30,Personal Travel,Eco,1080,2,4,2,1,2,2,2,2,5,3,5,3,5,2,4,0.0,neutral or dissatisfied +10694,23422,Male,Loyal Customer,59,Personal Travel,Eco Plus,541,4,4,3,3,5,3,5,5,5,2,4,5,5,5,29,19.0,neutral or dissatisfied +10695,15721,Male,Loyal Customer,38,Business travel,Eco,419,3,4,4,4,3,3,3,3,4,5,4,2,4,3,85,89.0,neutral or dissatisfied +10696,55124,Female,Loyal Customer,41,Personal Travel,Eco,1635,4,3,4,4,5,4,5,5,2,1,4,5,3,5,0,20.0,neutral or dissatisfied +10697,15423,Female,disloyal Customer,21,Business travel,Eco,377,2,4,2,3,5,2,5,5,5,2,1,1,2,5,0,0.0,neutral or dissatisfied +10698,58622,Male,Loyal Customer,47,Business travel,Eco Plus,137,1,2,2,2,1,1,1,1,3,3,3,2,3,1,55,43.0,neutral or dissatisfied +10699,68121,Female,Loyal Customer,19,Personal Travel,Eco,868,4,2,4,3,4,4,4,4,4,4,4,2,4,4,0,0.0,satisfied +10700,57372,Female,Loyal Customer,50,Personal Travel,Eco,414,2,4,2,2,3,3,3,1,1,2,1,3,1,3,1,0.0,neutral or dissatisfied +10701,120041,Male,Loyal Customer,47,Business travel,Eco,168,3,1,1,1,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +10702,23800,Female,Loyal Customer,80,Business travel,Business,2672,2,3,3,3,1,3,3,2,2,2,2,1,2,1,44,123.0,neutral or dissatisfied +10703,74948,Female,Loyal Customer,26,Business travel,Business,2586,2,2,5,2,4,4,4,4,3,2,3,3,5,4,10,0.0,satisfied +10704,36598,Female,disloyal Customer,29,Business travel,Eco,1197,1,1,1,1,3,1,3,3,3,5,5,2,3,3,0,0.0,neutral or dissatisfied +10705,70890,Male,Loyal Customer,33,Personal Travel,Business,1721,3,5,3,2,3,3,3,4,4,4,5,3,3,3,182,160.0,neutral or dissatisfied +10706,53600,Female,Loyal Customer,15,Personal Travel,Eco,3801,4,5,4,1,4,4,4,3,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +10707,49302,Male,Loyal Customer,37,Business travel,Business,78,0,4,1,2,2,4,4,4,4,4,4,1,4,2,0,0.0,satisfied +10708,2334,Female,Loyal Customer,47,Personal Travel,Eco,690,1,4,1,5,2,5,5,2,2,1,2,4,2,5,25,24.0,neutral or dissatisfied +10709,39580,Female,Loyal Customer,47,Business travel,Eco,908,3,4,4,4,3,2,1,3,3,3,3,5,3,1,0,0.0,satisfied +10710,1514,Female,Loyal Customer,46,Business travel,Business,3336,3,3,3,3,4,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +10711,116703,Female,disloyal Customer,36,Business travel,Eco Plus,337,2,2,2,4,3,2,3,3,3,2,4,2,3,3,0,0.0,neutral or dissatisfied +10712,20701,Male,Loyal Customer,80,Business travel,Business,2494,4,5,1,1,2,3,4,4,4,4,4,4,4,3,28,29.0,neutral or dissatisfied +10713,2222,Male,disloyal Customer,24,Business travel,Eco,859,2,2,2,3,3,2,3,3,2,4,3,3,4,3,0,2.0,neutral or dissatisfied +10714,41829,Female,Loyal Customer,26,Business travel,Eco Plus,489,5,4,4,4,5,5,4,5,4,2,2,2,3,5,57,44.0,satisfied +10715,72665,Female,Loyal Customer,7,Personal Travel,Eco,1119,2,4,2,4,3,2,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +10716,113535,Male,disloyal Customer,25,Business travel,Business,258,4,0,5,3,4,5,4,4,3,4,5,5,4,4,1,0.0,satisfied +10717,70463,Female,Loyal Customer,60,Business travel,Business,3255,4,4,4,4,3,5,5,4,4,4,4,4,4,3,19,27.0,satisfied +10718,83915,Female,disloyal Customer,52,Business travel,Eco Plus,752,4,4,4,4,4,4,4,4,3,1,4,1,3,4,36,21.0,neutral or dissatisfied +10719,32867,Female,Loyal Customer,42,Personal Travel,Eco,101,4,5,4,2,4,4,4,5,5,4,1,3,5,3,2,4.0,satisfied +10720,78470,Female,Loyal Customer,52,Business travel,Business,526,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +10721,120888,Female,disloyal Customer,23,Business travel,Business,992,4,1,4,3,1,4,1,1,1,5,4,3,4,1,0,0.0,neutral or dissatisfied +10722,2004,Female,disloyal Customer,38,Business travel,Business,351,5,5,5,4,3,5,3,3,5,3,5,3,5,3,0,0.0,satisfied +10723,75768,Female,Loyal Customer,53,Personal Travel,Eco,868,4,1,4,2,4,2,2,4,4,4,4,2,4,4,0,6.0,neutral or dissatisfied +10724,43749,Male,disloyal Customer,20,Business travel,Eco,546,1,0,1,1,1,1,1,1,2,5,1,4,4,1,0,0.0,neutral or dissatisfied +10725,52364,Male,Loyal Customer,65,Personal Travel,Eco,261,1,4,0,4,5,0,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +10726,60131,Female,Loyal Customer,33,Business travel,Business,1144,5,5,5,5,5,5,4,4,4,4,4,4,4,4,12,0.0,satisfied +10727,33242,Female,disloyal Customer,24,Business travel,Eco,101,3,2,3,3,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +10728,92742,Male,Loyal Customer,39,Personal Travel,Eco,1276,0,5,0,1,4,0,4,4,5,2,5,4,4,4,68,63.0,satisfied +10729,113402,Male,disloyal Customer,41,Business travel,Business,386,1,1,1,5,3,1,3,3,3,5,5,3,4,3,0,4.0,neutral or dissatisfied +10730,44120,Male,Loyal Customer,37,Business travel,Eco,198,5,5,5,5,5,5,5,5,2,3,1,5,3,5,0,0.0,satisfied +10731,51334,Female,Loyal Customer,23,Business travel,Eco Plus,337,2,5,5,5,2,2,2,2,2,3,4,2,4,2,1,3.0,neutral or dissatisfied +10732,52914,Male,Loyal Customer,48,Business travel,Business,3940,3,3,3,3,1,1,2,5,5,5,5,3,5,4,20,0.0,satisfied +10733,41647,Female,Loyal Customer,35,Business travel,Business,2849,3,3,3,3,3,3,1,5,5,5,5,5,5,4,98,90.0,satisfied +10734,19703,Male,Loyal Customer,39,Business travel,Business,475,2,4,5,4,3,4,4,2,2,2,2,3,2,2,52,55.0,neutral or dissatisfied +10735,4714,Female,Loyal Customer,61,Personal Travel,Eco Plus,364,2,4,2,4,3,4,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +10736,56915,Male,Loyal Customer,25,Business travel,Business,2454,2,4,4,4,2,2,2,4,4,3,4,2,1,2,29,23.0,neutral or dissatisfied +10737,22131,Female,Loyal Customer,22,Business travel,Business,566,2,2,2,2,5,5,5,5,4,3,1,4,3,5,0,0.0,satisfied +10738,126729,Male,disloyal Customer,22,Business travel,Eco,1127,3,3,3,4,4,3,2,4,4,1,3,3,4,4,0,0.0,neutral or dissatisfied +10739,119891,Female,Loyal Customer,13,Personal Travel,Eco,936,2,1,2,4,4,2,4,4,1,1,3,4,3,4,33,19.0,neutral or dissatisfied +10740,105130,Female,Loyal Customer,60,Business travel,Business,2990,0,0,0,2,5,4,5,5,5,4,4,3,5,3,0,0.0,satisfied +10741,10768,Female,Loyal Customer,45,Business travel,Business,3449,1,1,1,1,2,5,5,4,4,4,5,5,4,3,2,0.0,satisfied +10742,96538,Female,Loyal Customer,35,Personal Travel,Eco,436,2,2,5,3,4,5,4,4,4,1,2,4,3,4,0,0.0,neutral or dissatisfied +10743,8387,Male,Loyal Customer,44,Business travel,Business,2745,4,4,3,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +10744,6748,Female,Loyal Customer,47,Personal Travel,Business,235,3,5,3,3,3,4,5,4,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +10745,127609,Female,Loyal Customer,42,Business travel,Business,1773,3,3,3,3,4,3,5,4,4,4,4,5,4,3,0,0.0,satisfied +10746,113308,Female,Loyal Customer,57,Business travel,Business,2849,5,5,5,5,2,5,5,4,4,4,5,3,4,3,5,10.0,satisfied +10747,65480,Female,Loyal Customer,45,Business travel,Business,903,3,5,5,5,4,4,3,3,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +10748,31558,Male,Loyal Customer,53,Personal Travel,Eco,853,1,5,1,4,4,1,4,4,4,4,5,4,4,4,0,0.0,neutral or dissatisfied +10749,46228,Female,disloyal Customer,29,Business travel,Eco,679,2,2,2,3,2,2,4,2,5,5,1,1,1,2,3,9.0,neutral or dissatisfied +10750,68721,Female,disloyal Customer,38,Business travel,Business,237,4,4,4,2,3,4,3,3,5,2,4,5,4,3,24,14.0,satisfied +10751,28700,Female,Loyal Customer,50,Business travel,Eco,2172,5,4,5,4,2,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +10752,125769,Female,disloyal Customer,52,Business travel,Business,993,2,2,2,2,3,2,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +10753,90300,Female,Loyal Customer,57,Personal Travel,Eco,932,1,5,1,3,3,4,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +10754,124521,Male,Loyal Customer,55,Business travel,Business,1276,2,2,2,2,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +10755,20185,Female,Loyal Customer,51,Business travel,Eco Plus,403,5,4,4,4,3,3,3,5,5,5,5,2,5,4,69,79.0,satisfied +10756,95536,Male,Loyal Customer,47,Personal Travel,Eco Plus,319,4,1,4,3,4,4,4,4,3,4,3,1,4,4,0,2.0,satisfied +10757,15199,Female,Loyal Customer,44,Personal Travel,Eco,461,2,4,2,4,4,4,3,5,5,2,5,2,5,2,0,0.0,neutral or dissatisfied +10758,127147,Male,Loyal Customer,41,Personal Travel,Eco,647,2,1,3,2,4,3,2,4,3,2,2,2,3,4,3,0.0,neutral or dissatisfied +10759,74780,Female,disloyal Customer,25,Business travel,Business,1242,3,0,3,3,5,3,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +10760,65913,Male,disloyal Customer,27,Business travel,Eco,569,4,2,4,4,5,4,5,5,4,3,4,4,3,5,2,7.0,neutral or dissatisfied +10761,109135,Female,Loyal Customer,50,Business travel,Business,483,3,3,3,3,5,5,5,4,4,4,4,3,4,3,4,3.0,satisfied +10762,89725,Female,Loyal Customer,58,Personal Travel,Eco,950,3,3,3,4,4,3,1,5,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +10763,97631,Male,Loyal Customer,27,Business travel,Eco,748,1,3,3,3,1,2,1,1,2,2,4,4,3,1,65,46.0,neutral or dissatisfied +10764,39417,Male,Loyal Customer,28,Personal Travel,Business,129,4,2,4,4,5,4,5,5,4,5,3,1,3,5,3,8.0,neutral or dissatisfied +10765,119163,Female,disloyal Customer,23,Business travel,Eco,331,5,0,5,2,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +10766,122351,Male,Loyal Customer,55,Business travel,Business,3128,4,4,4,4,5,4,5,5,5,5,5,4,5,3,23,4.0,satisfied +10767,29548,Male,Loyal Customer,38,Business travel,Business,1448,3,3,3,3,1,3,1,4,4,4,4,4,4,5,0,22.0,satisfied +10768,47418,Male,Loyal Customer,24,Business travel,Business,588,1,4,4,4,1,1,1,1,1,1,1,1,1,1,0,3.0,neutral or dissatisfied +10769,16905,Female,Loyal Customer,52,Personal Travel,Eco,746,4,4,4,2,3,5,4,5,5,4,5,4,5,4,108,105.0,neutral or dissatisfied +10770,71208,Female,Loyal Customer,48,Business travel,Business,733,5,5,5,5,5,5,5,4,4,4,4,5,4,3,54,36.0,satisfied +10771,35814,Male,Loyal Customer,30,Business travel,Business,2919,5,5,5,5,3,4,3,3,3,1,4,1,3,3,0,30.0,satisfied +10772,43353,Female,disloyal Customer,25,Business travel,Eco,358,2,0,2,1,2,2,2,2,3,5,4,2,4,2,0,0.0,neutral or dissatisfied +10773,10493,Female,Loyal Customer,40,Business travel,Business,140,5,5,5,5,3,4,4,4,4,4,5,4,4,3,0,0.0,satisfied +10774,26886,Female,Loyal Customer,36,Business travel,Business,2702,5,5,5,5,2,3,1,4,4,4,4,4,4,1,0,0.0,satisfied +10775,54384,Male,disloyal Customer,39,Business travel,Eco,305,2,0,2,1,3,2,3,3,2,3,4,1,1,3,2,0.0,neutral or dissatisfied +10776,114777,Male,Loyal Customer,73,Business travel,Business,1973,1,1,1,1,4,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +10777,8181,Female,Loyal Customer,30,Business travel,Business,402,2,2,2,2,2,2,2,2,3,4,2,4,3,2,0,0.0,neutral or dissatisfied +10778,61503,Female,Loyal Customer,51,Business travel,Eco,942,4,2,2,2,5,4,3,4,4,4,4,4,4,4,44,32.0,neutral or dissatisfied +10779,98207,Male,Loyal Customer,59,Personal Travel,Eco,327,1,0,5,3,5,5,5,5,2,2,2,3,1,5,0,0.0,neutral or dissatisfied +10780,16121,Male,Loyal Customer,38,Business travel,Eco,725,2,4,4,4,2,2,2,2,1,1,4,1,4,2,35,30.0,neutral or dissatisfied +10781,78919,Male,Loyal Customer,50,Business travel,Business,2540,1,1,1,1,5,5,5,5,4,5,5,5,4,5,139,115.0,satisfied +10782,61309,Male,Loyal Customer,27,Business travel,Business,909,1,1,1,1,2,2,2,2,5,4,4,3,4,2,10,6.0,satisfied +10783,6297,Female,Loyal Customer,25,Business travel,Eco Plus,693,2,4,4,4,2,1,2,1,4,2,3,2,4,2,32,155.0,neutral or dissatisfied +10784,102020,Male,Loyal Customer,41,Business travel,Business,223,3,3,3,3,4,5,5,5,5,5,4,3,5,5,1,0.0,satisfied +10785,23309,Female,Loyal Customer,27,Business travel,Eco,563,5,2,2,2,5,5,5,5,2,1,3,3,5,5,2,0.0,satisfied +10786,36120,Female,Loyal Customer,34,Business travel,Business,1609,5,5,5,5,1,3,4,5,5,5,5,4,5,4,0,2.0,satisfied +10787,47967,Female,Loyal Customer,14,Personal Travel,Eco,329,1,4,1,3,5,1,3,5,1,1,3,3,3,5,29,34.0,neutral or dissatisfied +10788,88523,Male,Loyal Customer,29,Personal Travel,Eco,240,5,5,0,1,2,0,2,2,3,4,5,4,4,2,3,0.0,satisfied +10789,110362,Male,Loyal Customer,43,Business travel,Business,842,3,3,3,3,5,4,5,5,5,5,5,4,5,4,29,23.0,satisfied +10790,35289,Female,Loyal Customer,26,Business travel,Business,2169,1,1,1,1,4,4,4,4,1,4,4,3,3,4,0,0.0,satisfied +10791,5421,Male,Loyal Customer,30,Personal Travel,Eco,589,1,5,1,3,3,1,3,3,4,5,5,4,4,3,8,1.0,neutral or dissatisfied +10792,62973,Female,Loyal Customer,32,Business travel,Business,2273,1,2,2,2,1,1,1,1,4,2,3,1,3,1,0,0.0,neutral or dissatisfied +10793,63774,Male,Loyal Customer,47,Business travel,Business,1721,3,3,3,3,3,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +10794,67522,Male,Loyal Customer,45,Business travel,Business,1464,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +10795,114992,Female,disloyal Customer,23,Business travel,Business,333,4,2,4,5,2,4,2,2,4,3,5,3,4,2,15,8.0,satisfied +10796,69152,Female,Loyal Customer,55,Business travel,Business,2248,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +10797,81478,Male,Loyal Customer,12,Business travel,Eco,528,4,3,3,3,4,4,3,4,4,4,4,2,4,4,0,19.0,neutral or dissatisfied +10798,129447,Female,Loyal Customer,66,Personal Travel,Eco,414,3,5,3,3,3,1,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +10799,105909,Female,Loyal Customer,51,Business travel,Eco,283,4,4,4,4,2,3,3,4,4,4,4,4,4,3,36,29.0,satisfied +10800,97253,Male,Loyal Customer,68,Business travel,Eco,296,3,1,5,5,3,3,3,3,1,4,4,3,3,3,0,0.0,neutral or dissatisfied +10801,4976,Male,Loyal Customer,46,Business travel,Business,502,3,1,5,1,4,3,4,3,3,3,3,4,3,1,0,19.0,neutral or dissatisfied +10802,3424,Male,Loyal Customer,36,Personal Travel,Eco,315,4,2,4,4,1,4,1,1,1,2,3,3,3,1,0,0.0,neutral or dissatisfied +10803,15324,Female,Loyal Customer,44,Business travel,Eco,599,2,3,2,3,1,3,3,3,3,2,3,2,3,3,0,0.0,neutral or dissatisfied +10804,112290,Female,Loyal Customer,40,Business travel,Business,1703,4,4,4,4,4,3,5,5,5,5,5,5,5,5,14,13.0,satisfied +10805,127627,Male,Loyal Customer,54,Business travel,Business,1773,3,4,4,4,4,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +10806,91571,Male,disloyal Customer,26,Business travel,Business,1123,5,5,5,2,3,5,3,3,5,3,5,4,4,3,0,0.0,satisfied +10807,2570,Female,Loyal Customer,65,Business travel,Business,2679,2,4,4,4,2,2,2,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +10808,10248,Male,Loyal Customer,58,Personal Travel,Business,295,3,5,3,2,3,4,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +10809,87505,Male,Loyal Customer,11,Personal Travel,Eco,373,2,4,2,3,5,2,4,5,5,4,5,5,2,5,15,10.0,neutral or dissatisfied +10810,21022,Male,Loyal Customer,47,Business travel,Eco,227,5,3,3,3,5,5,5,5,2,4,5,2,2,5,0,0.0,satisfied +10811,15476,Male,Loyal Customer,16,Personal Travel,Eco,331,3,2,3,3,2,3,1,2,2,5,3,4,3,2,0,0.0,neutral or dissatisfied +10812,112676,Male,Loyal Customer,46,Business travel,Eco,671,1,4,4,4,1,1,1,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +10813,122460,Female,Loyal Customer,53,Business travel,Business,575,2,2,2,2,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +10814,15832,Female,Loyal Customer,49,Business travel,Business,2450,3,5,5,5,1,4,4,1,1,1,3,3,1,2,1,0.0,neutral or dissatisfied +10815,8870,Female,Loyal Customer,22,Business travel,Eco,622,3,3,3,3,3,3,2,3,2,2,3,2,4,3,0,5.0,neutral or dissatisfied +10816,124676,Male,Loyal Customer,43,Business travel,Business,1936,4,5,4,4,3,5,5,5,5,5,5,4,5,3,0,8.0,satisfied +10817,31287,Female,Loyal Customer,22,Personal Travel,Eco,533,4,5,4,3,2,4,2,2,5,4,4,4,5,2,0,1.0,neutral or dissatisfied +10818,98606,Male,Loyal Customer,37,Business travel,Business,3549,3,3,3,3,5,5,5,5,5,5,5,5,5,5,169,184.0,satisfied +10819,93405,Female,disloyal Customer,26,Business travel,Business,723,4,4,4,4,3,4,3,3,5,4,5,3,4,3,35,42.0,satisfied +10820,115680,Male,Loyal Customer,47,Business travel,Eco,446,3,1,1,1,3,3,3,3,4,5,3,3,4,3,96,91.0,neutral or dissatisfied +10821,65762,Male,Loyal Customer,57,Personal Travel,Eco,1061,1,1,1,2,1,1,2,1,2,4,1,4,1,1,0,0.0,neutral or dissatisfied +10822,103478,Male,Loyal Customer,47,Business travel,Business,2910,5,5,5,5,3,4,4,2,2,2,2,3,2,5,13,0.0,satisfied +10823,36939,Female,disloyal Customer,28,Business travel,Eco,718,2,2,2,4,5,2,4,5,5,2,2,3,1,5,42,30.0,neutral or dissatisfied +10824,47408,Female,Loyal Customer,28,Business travel,Business,2700,4,5,5,5,4,4,4,2,3,3,3,4,3,4,136,163.0,neutral or dissatisfied +10825,128128,Male,Loyal Customer,22,Personal Travel,Eco,1587,2,4,2,2,3,2,3,3,3,2,3,4,5,3,0,0.0,neutral or dissatisfied +10826,42297,Female,Loyal Customer,33,Personal Travel,Eco,451,4,3,4,3,5,4,5,5,4,2,3,4,3,5,0,0.0,satisfied +10827,128570,Female,Loyal Customer,51,Business travel,Business,110,2,2,2,2,5,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +10828,6321,Male,Loyal Customer,44,Business travel,Business,296,3,3,5,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +10829,100989,Male,Loyal Customer,52,Business travel,Business,806,4,4,4,4,2,5,5,5,5,5,5,4,5,4,1,0.0,satisfied +10830,69522,Male,Loyal Customer,26,Business travel,Business,2475,4,4,4,4,2,2,2,5,4,5,5,2,5,2,0,0.0,satisfied +10831,128161,Male,Loyal Customer,54,Business travel,Business,1849,1,1,1,1,2,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +10832,35968,Female,Loyal Customer,7,Personal Travel,Eco,231,1,5,1,1,4,1,2,4,5,4,5,3,3,4,0,0.0,neutral or dissatisfied +10833,64650,Female,Loyal Customer,35,Business travel,Business,3835,5,5,5,5,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +10834,85404,Male,Loyal Customer,46,Business travel,Business,3479,3,3,5,3,2,4,5,4,4,4,5,3,4,5,37,46.0,satisfied +10835,64481,Male,Loyal Customer,34,Business travel,Business,190,3,3,3,3,5,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +10836,88372,Female,Loyal Customer,36,Business travel,Business,1528,1,2,2,2,5,4,3,1,1,2,1,4,1,1,1,8.0,neutral or dissatisfied +10837,117787,Male,Loyal Customer,42,Business travel,Business,328,4,4,4,4,4,4,4,5,5,5,5,4,5,5,24,15.0,satisfied +10838,47798,Female,Loyal Customer,43,Business travel,Eco,846,5,3,3,3,2,1,3,4,4,5,4,2,4,1,0,0.0,satisfied +10839,116545,Female,Loyal Customer,35,Personal Travel,Eco,342,3,3,3,4,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +10840,103271,Female,Loyal Customer,34,Personal Travel,Eco,888,1,2,1,4,4,1,4,4,2,1,3,3,3,4,2,9.0,neutral or dissatisfied +10841,34652,Male,Loyal Customer,43,Personal Travel,Eco,427,2,4,2,4,2,3,4,5,2,3,4,4,4,4,159,134.0,neutral or dissatisfied +10842,53725,Male,Loyal Customer,43,Personal Travel,Eco,1208,2,1,2,3,1,2,1,1,4,1,3,3,4,1,3,0.0,neutral or dissatisfied +10843,1959,Female,Loyal Customer,54,Business travel,Business,2795,0,0,0,4,5,1,3,1,1,1,1,2,1,4,0,0.0,satisfied +10844,24127,Female,Loyal Customer,28,Personal Travel,Eco,584,3,4,3,4,5,3,5,5,4,5,5,3,4,5,0,1.0,neutral or dissatisfied +10845,55229,Female,disloyal Customer,21,Business travel,Business,1009,4,4,4,1,5,4,5,5,5,5,4,4,5,5,67,65.0,satisfied +10846,4379,Male,disloyal Customer,25,Business travel,Business,473,3,5,3,2,4,3,4,4,5,5,1,5,2,4,4,2.0,neutral or dissatisfied +10847,94877,Male,Loyal Customer,68,Business travel,Business,3939,1,5,5,5,3,3,2,1,1,1,1,1,1,1,17,16.0,neutral or dissatisfied +10848,50094,Female,disloyal Customer,35,Business travel,Eco,421,4,2,4,4,1,4,1,1,4,5,3,3,4,1,0,0.0,neutral or dissatisfied +10849,93216,Male,disloyal Customer,16,Business travel,Eco,835,1,1,1,1,3,1,2,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +10850,44687,Male,Loyal Customer,38,Business travel,Business,173,5,5,3,5,3,5,3,4,4,4,4,1,4,5,80,81.0,satisfied +10851,48269,Female,Loyal Customer,37,Business travel,Eco Plus,236,3,1,4,1,3,3,3,3,4,3,3,3,3,3,1,0.0,neutral or dissatisfied +10852,34924,Male,Loyal Customer,39,Business travel,Business,395,2,1,1,1,3,3,3,2,2,2,2,1,2,4,0,4.0,neutral or dissatisfied +10853,84353,Female,Loyal Customer,56,Business travel,Business,606,2,2,2,2,4,5,4,5,5,5,5,3,5,4,1,0.0,satisfied +10854,100522,Male,Loyal Customer,22,Personal Travel,Eco,580,0,4,0,4,4,0,4,4,3,4,4,5,4,4,2,0.0,satisfied +10855,57395,Female,Loyal Customer,43,Personal Travel,Eco,472,4,5,4,3,5,1,2,2,2,4,4,5,2,1,0,0.0,satisfied +10856,65448,Female,disloyal Customer,28,Business travel,Business,1303,4,4,4,3,3,4,3,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +10857,107406,Male,Loyal Customer,28,Business travel,Business,2164,4,4,4,4,5,5,5,5,3,5,4,3,5,5,6,3.0,satisfied +10858,61725,Male,Loyal Customer,51,Business travel,Eco,1104,4,2,1,2,4,4,4,4,4,1,5,1,3,4,14,0.0,satisfied +10859,83857,Female,Loyal Customer,8,Personal Travel,Eco,425,4,0,4,3,1,4,1,1,5,3,5,5,5,1,0,0.0,satisfied +10860,110811,Female,Loyal Customer,56,Personal Travel,Eco,990,4,5,4,1,4,4,5,3,3,4,3,5,3,3,65,68.0,neutral or dissatisfied +10861,74158,Male,Loyal Customer,30,Personal Travel,Eco,592,3,3,3,3,4,3,1,4,4,3,3,5,5,4,0,0.0,neutral or dissatisfied +10862,107358,Male,Loyal Customer,9,Personal Travel,Eco,584,1,1,1,4,2,1,2,2,1,4,4,3,4,2,18,16.0,neutral or dissatisfied +10863,90194,Female,Loyal Customer,40,Personal Travel,Eco,1127,4,4,4,1,2,4,2,2,3,2,5,3,5,2,0,0.0,neutral or dissatisfied +10864,119933,Male,Loyal Customer,41,Business travel,Business,868,1,1,1,1,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +10865,101180,Male,Loyal Customer,62,Personal Travel,Eco,583,3,2,3,3,5,3,5,5,4,3,4,1,3,5,7,3.0,neutral or dissatisfied +10866,123180,Female,Loyal Customer,23,Business travel,Eco,250,0,4,0,3,3,0,3,3,3,5,4,1,1,3,54,31.0,satisfied +10867,15945,Female,Loyal Customer,16,Personal Travel,Eco,607,1,4,0,3,3,0,4,3,3,5,5,3,4,3,27,20.0,neutral or dissatisfied +10868,113943,Male,Loyal Customer,10,Business travel,Business,1750,3,3,3,3,4,4,4,4,3,3,3,4,4,4,0,0.0,satisfied +10869,35631,Female,disloyal Customer,25,Business travel,Eco Plus,1165,3,3,4,3,4,4,4,4,4,5,4,1,3,4,1,0.0,neutral or dissatisfied +10870,105349,Female,Loyal Customer,38,Personal Travel,Eco,409,2,5,2,5,1,2,1,1,2,5,2,4,2,1,0,0.0,neutral or dissatisfied +10871,38099,Female,Loyal Customer,33,Business travel,Business,1674,3,3,3,3,2,5,5,2,2,2,2,2,2,1,0,0.0,satisfied +10872,57294,Female,Loyal Customer,54,Business travel,Business,2369,3,3,3,3,3,4,4,4,4,4,4,3,4,3,82,62.0,satisfied +10873,110365,Male,Loyal Customer,23,Business travel,Business,3552,1,1,1,1,5,5,5,5,5,4,5,3,5,5,18,0.0,satisfied +10874,27623,Female,disloyal Customer,26,Business travel,Eco Plus,679,2,0,2,2,2,2,2,2,5,3,2,2,2,2,53,42.0,neutral or dissatisfied +10875,120189,Female,Loyal Customer,37,Business travel,Business,2033,2,2,2,2,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +10876,109103,Male,Loyal Customer,10,Personal Travel,Eco,928,3,5,3,4,5,3,5,5,3,3,4,5,4,5,0,1.0,neutral or dissatisfied +10877,120274,Female,Loyal Customer,50,Business travel,Business,1576,3,3,3,3,4,5,4,4,4,4,4,4,4,5,6,37.0,satisfied +10878,30170,Male,Loyal Customer,64,Personal Travel,Eco,261,4,3,0,2,1,0,1,1,2,4,4,2,3,1,3,7.0,neutral or dissatisfied +10879,43153,Female,disloyal Customer,23,Business travel,Eco,1368,2,2,2,1,1,2,1,1,1,3,3,5,3,1,0,10.0,neutral or dissatisfied +10880,111401,Male,Loyal Customer,33,Personal Travel,Eco,1050,5,4,5,4,5,5,5,5,3,1,4,4,4,5,0,0.0,satisfied +10881,111822,Male,disloyal Customer,29,Business travel,Business,1605,1,1,1,2,3,1,3,3,5,2,3,3,4,3,27,1.0,neutral or dissatisfied +10882,53035,Male,disloyal Customer,22,Business travel,Business,1190,1,2,1,3,2,1,2,2,2,2,3,3,2,2,0,0.0,neutral or dissatisfied +10883,31719,Male,Loyal Customer,31,Personal Travel,Eco,853,1,5,1,2,1,1,1,1,4,3,5,4,4,1,13,13.0,neutral or dissatisfied +10884,64105,Male,Loyal Customer,78,Business travel,Eco Plus,519,2,3,3,3,2,2,2,2,3,1,4,1,4,2,0,14.0,neutral or dissatisfied +10885,121397,Male,Loyal Customer,63,Personal Travel,Business,331,3,4,3,4,2,4,5,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +10886,20692,Female,Loyal Customer,26,Business travel,Business,510,5,5,5,5,5,5,5,5,1,3,5,5,5,5,149,168.0,satisfied +10887,62515,Male,Loyal Customer,53,Business travel,Business,1846,3,3,3,3,4,4,4,4,4,5,4,5,4,3,10,1.0,satisfied +10888,129011,Female,disloyal Customer,46,Business travel,Business,2704,4,4,4,2,4,4,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +10889,89224,Female,Loyal Customer,56,Personal Travel,Eco,2116,1,1,1,3,4,3,4,1,1,1,5,2,1,4,0,0.0,neutral or dissatisfied +10890,23579,Female,Loyal Customer,38,Business travel,Eco,792,5,3,4,4,5,5,5,5,3,4,3,4,5,5,0,0.0,satisfied +10891,28395,Female,Loyal Customer,27,Business travel,Business,2304,5,5,5,5,5,5,5,5,4,5,4,4,5,5,48,28.0,satisfied +10892,18253,Female,Loyal Customer,15,Personal Travel,Eco,235,1,4,1,3,2,1,2,2,3,4,5,5,4,2,0,0.0,neutral or dissatisfied +10893,129597,Female,Loyal Customer,49,Business travel,Business,3496,3,3,3,3,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +10894,20579,Male,Loyal Customer,9,Personal Travel,Eco,533,2,5,2,1,2,2,3,2,3,4,4,5,4,2,28,11.0,neutral or dissatisfied +10895,83907,Female,Loyal Customer,61,Business travel,Business,2101,1,1,1,1,4,4,4,4,4,4,4,4,4,3,4,0.0,satisfied +10896,104320,Male,Loyal Customer,51,Business travel,Business,409,3,4,4,4,5,3,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +10897,126717,Female,Loyal Customer,23,Business travel,Business,2402,5,5,5,5,4,5,4,4,3,3,4,4,5,4,17,34.0,satisfied +10898,59343,Male,disloyal Customer,24,Business travel,Eco,900,4,4,4,3,5,4,4,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +10899,61583,Female,Loyal Customer,21,Personal Travel,Business,1635,5,2,5,3,2,5,2,2,3,5,4,2,4,2,28,9.0,satisfied +10900,11225,Male,Loyal Customer,28,Personal Travel,Eco,191,3,1,3,1,3,3,3,3,3,5,1,3,2,3,0,0.0,neutral or dissatisfied +10901,89544,Female,Loyal Customer,58,Business travel,Business,1515,2,2,2,2,2,4,5,4,4,4,4,3,4,4,32,14.0,satisfied +10902,84177,Male,Loyal Customer,52,Personal Travel,Eco,231,3,5,3,3,5,3,3,5,4,2,5,5,4,5,20,39.0,neutral or dissatisfied +10903,23208,Female,Loyal Customer,51,Personal Travel,Eco,393,1,5,1,4,2,3,4,1,1,1,1,1,1,2,3,4.0,neutral or dissatisfied +10904,108465,Female,Loyal Customer,12,Personal Travel,Eco,1444,4,4,3,2,2,3,2,2,4,3,4,5,5,2,47,40.0,neutral or dissatisfied +10905,121204,Female,Loyal Customer,17,Business travel,Eco Plus,2402,5,3,3,3,5,5,5,4,3,2,1,5,2,5,0,0.0,satisfied +10906,95210,Female,Loyal Customer,7,Personal Travel,Eco,496,3,4,3,2,3,3,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +10907,9878,Female,disloyal Customer,39,Business travel,Business,357,1,1,1,1,1,1,1,4,5,1,1,1,1,1,182,194.0,neutral or dissatisfied +10908,120629,Female,Loyal Customer,49,Business travel,Business,280,3,3,3,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +10909,3329,Male,Loyal Customer,31,Business travel,Business,3785,0,0,0,1,5,5,5,5,4,5,5,4,4,5,0,56.0,satisfied +10910,117811,Female,disloyal Customer,55,Business travel,Eco,328,1,4,0,3,3,0,2,3,2,3,4,1,2,3,0,3.0,neutral or dissatisfied +10911,24030,Female,Loyal Customer,65,Business travel,Eco,162,3,4,4,4,3,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +10912,48664,Female,Loyal Customer,39,Business travel,Business,3781,4,4,4,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +10913,106042,Male,Loyal Customer,31,Business travel,Business,1862,4,4,4,4,4,4,4,4,3,4,4,4,5,4,10,9.0,satisfied +10914,28809,Female,Loyal Customer,48,Business travel,Eco,978,5,5,2,5,2,2,3,5,5,5,5,3,5,5,0,3.0,satisfied +10915,37090,Female,Loyal Customer,58,Business travel,Eco,1189,4,2,2,2,3,2,2,5,5,4,5,5,5,4,0,0.0,satisfied +10916,71506,Male,Loyal Customer,43,Business travel,Business,3600,5,5,2,5,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +10917,123515,Male,Loyal Customer,32,Personal Travel,Eco,2125,2,1,2,3,1,2,1,1,2,1,3,1,3,1,0,12.0,neutral or dissatisfied +10918,85085,Male,Loyal Customer,28,Business travel,Business,874,2,4,2,2,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +10919,73157,Male,Loyal Customer,38,Personal Travel,Business,1145,2,5,2,2,4,4,5,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +10920,56025,Female,Loyal Customer,34,Business travel,Business,2475,2,3,2,2,5,5,5,5,5,3,4,5,3,5,30,9.0,satisfied +10921,49387,Male,disloyal Customer,22,Business travel,Eco,89,3,4,3,2,5,3,5,5,2,4,3,2,5,5,0,0.0,neutral or dissatisfied +10922,85726,Female,Loyal Customer,56,Business travel,Business,3867,4,4,4,4,4,3,4,1,1,1,4,4,1,4,0,0.0,neutral or dissatisfied +10923,101435,Female,Loyal Customer,50,Business travel,Business,3377,3,3,3,3,4,5,4,4,4,5,4,4,4,5,0,0.0,satisfied +10924,18288,Male,Loyal Customer,22,Business travel,Eco,640,3,4,4,4,3,4,5,3,5,1,5,4,3,3,14,0.0,satisfied +10925,33764,Female,disloyal Customer,26,Business travel,Eco Plus,266,3,0,3,4,3,3,5,3,2,1,4,3,3,3,0,8.0,neutral or dissatisfied +10926,49318,Female,Loyal Customer,42,Business travel,Business,3663,2,2,2,2,5,4,1,5,5,5,5,4,5,3,0,0.0,satisfied +10927,121573,Female,Loyal Customer,25,Business travel,Business,3208,5,5,5,5,4,4,4,4,3,5,5,5,4,4,4,0.0,satisfied +10928,97921,Female,Loyal Customer,51,Business travel,Business,2121,2,2,2,2,3,4,4,5,5,5,5,5,5,3,88,75.0,satisfied +10929,53343,Male,Loyal Customer,43,Business travel,Business,1452,2,1,2,2,3,2,3,4,4,4,4,3,4,3,14,0.0,satisfied +10930,5999,Female,Loyal Customer,53,Business travel,Business,3311,4,4,4,4,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +10931,98092,Male,Loyal Customer,25,Personal Travel,Eco,845,2,4,2,3,1,2,1,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +10932,18544,Male,disloyal Customer,30,Business travel,Eco,127,2,0,2,4,4,2,5,4,4,1,1,5,2,4,9,0.0,neutral or dissatisfied +10933,37264,Female,Loyal Customer,29,Business travel,Eco,828,5,5,5,5,5,5,5,5,3,3,5,1,5,5,17,5.0,satisfied +10934,9156,Male,Loyal Customer,39,Business travel,Business,2548,2,2,2,2,5,5,5,5,5,5,5,5,5,4,49,50.0,satisfied +10935,3033,Male,Loyal Customer,13,Personal Travel,Eco Plus,862,3,3,3,4,5,3,5,5,3,1,3,1,4,5,1,0.0,neutral or dissatisfied +10936,100610,Male,Loyal Customer,56,Business travel,Business,1670,1,1,1,1,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +10937,60716,Female,Loyal Customer,25,Business travel,Business,1725,2,2,4,4,2,2,2,2,4,1,1,4,1,2,34,18.0,neutral or dissatisfied +10938,128258,Male,Loyal Customer,27,Business travel,Business,3036,4,2,4,4,4,5,4,4,4,2,4,3,5,4,0,0.0,satisfied +10939,28756,Male,disloyal Customer,37,Business travel,Eco,624,3,3,3,3,3,3,3,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +10940,95058,Male,Loyal Customer,13,Personal Travel,Eco,239,3,5,0,3,3,0,3,3,5,2,4,3,4,3,1,0.0,neutral or dissatisfied +10941,24331,Female,Loyal Customer,27,Personal Travel,Eco Plus,1083,2,4,2,2,2,2,2,2,3,5,5,5,4,2,22,26.0,neutral or dissatisfied +10942,31677,Female,disloyal Customer,24,Business travel,Eco,844,3,3,3,2,1,3,1,1,3,1,2,3,5,1,0,0.0,neutral or dissatisfied +10943,98673,Male,Loyal Customer,44,Personal Travel,Eco,992,1,5,2,4,1,2,1,1,5,5,5,5,5,1,4,8.0,neutral or dissatisfied +10944,6700,Male,Loyal Customer,42,Business travel,Business,3119,1,1,1,1,5,4,2,5,5,5,5,1,5,1,0,0.0,satisfied +10945,83343,Male,Loyal Customer,20,Business travel,Business,187,5,5,5,5,4,4,5,4,3,5,4,4,4,4,0,0.0,satisfied +10946,50073,Female,Loyal Customer,35,Business travel,Business,3864,3,5,5,5,3,3,3,1,1,1,3,2,1,1,92,80.0,neutral or dissatisfied +10947,91432,Female,Loyal Customer,31,Personal Travel,Eco,549,3,0,3,1,3,3,4,3,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +10948,49830,Male,Loyal Customer,37,Business travel,Eco,110,1,3,3,3,1,1,1,1,1,1,3,2,3,1,0,0.0,neutral or dissatisfied +10949,21596,Female,Loyal Customer,28,Business travel,Business,1695,5,5,5,5,5,5,5,5,1,1,3,3,5,5,0,15.0,satisfied +10950,8568,Male,Loyal Customer,55,Business travel,Business,109,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +10951,4918,Female,disloyal Customer,13,Business travel,Business,1020,5,0,5,1,3,5,3,3,3,5,4,5,4,3,22,0.0,satisfied +10952,126553,Male,Loyal Customer,52,Personal Travel,Eco,644,2,5,3,3,4,3,4,4,2,4,2,1,3,4,0,0.0,neutral or dissatisfied +10953,124779,Male,Loyal Customer,56,Business travel,Business,1863,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,6.0,satisfied +10954,90403,Female,Loyal Customer,41,Personal Travel,Business,404,1,4,1,2,4,5,4,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +10955,47899,Male,Loyal Customer,49,Business travel,Business,150,4,4,4,4,4,2,5,5,5,5,3,2,5,1,0,0.0,satisfied +10956,123939,Female,Loyal Customer,61,Personal Travel,Eco,546,2,5,1,5,5,4,2,3,3,1,2,5,3,3,0,0.0,neutral or dissatisfied +10957,10799,Female,Loyal Customer,44,Business travel,Business,2340,1,1,1,1,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +10958,15774,Female,Loyal Customer,68,Business travel,Eco,254,3,5,5,5,3,4,4,3,3,3,3,2,3,1,2,0.0,neutral or dissatisfied +10959,83418,Male,Loyal Customer,59,Business travel,Eco,632,3,2,2,2,3,3,3,3,4,5,4,1,3,3,2,10.0,neutral or dissatisfied +10960,70020,Male,disloyal Customer,38,Business travel,Business,583,4,5,5,4,2,5,2,2,3,4,4,4,4,2,0,0.0,satisfied +10961,95047,Female,Loyal Customer,29,Personal Travel,Eco,248,4,4,4,3,3,4,3,3,3,4,4,4,4,3,2,0.0,neutral or dissatisfied +10962,76826,Female,disloyal Customer,26,Business travel,Business,1851,4,4,4,1,5,4,5,5,4,3,5,4,4,5,0,0.0,satisfied +10963,17454,Female,Loyal Customer,23,Business travel,Eco Plus,351,3,2,2,2,3,2,4,3,2,2,4,3,3,3,0,67.0,neutral or dissatisfied +10964,83496,Male,Loyal Customer,57,Business travel,Business,3191,4,4,4,4,4,3,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +10965,109522,Female,Loyal Customer,59,Business travel,Business,1935,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +10966,61912,Female,Loyal Customer,34,Business travel,Business,1697,5,5,5,5,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +10967,28048,Male,Loyal Customer,50,Business travel,Business,1739,4,1,1,1,1,4,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +10968,23918,Female,Loyal Customer,65,Personal Travel,Eco,579,2,1,2,4,3,4,4,5,5,2,5,4,5,2,95,88.0,neutral or dissatisfied +10969,41396,Female,Loyal Customer,22,Business travel,Business,1869,1,1,1,1,4,4,4,4,4,2,5,1,1,4,0,0.0,satisfied +10970,9500,Female,Loyal Customer,28,Business travel,Eco,322,1,2,2,2,1,1,1,1,2,4,4,2,4,1,0,0.0,neutral or dissatisfied +10971,17556,Male,disloyal Customer,25,Business travel,Eco,1034,3,4,4,3,4,4,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +10972,86992,Male,Loyal Customer,48,Personal Travel,Eco,907,2,5,2,2,2,2,5,2,3,4,5,4,4,2,30,36.0,neutral or dissatisfied +10973,18175,Male,Loyal Customer,51,Business travel,Eco Plus,363,5,5,5,5,5,5,5,5,4,1,1,1,1,5,1,42.0,satisfied +10974,127557,Female,Loyal Customer,15,Personal Travel,Eco Plus,1009,3,2,3,3,2,3,2,2,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +10975,71074,Male,Loyal Customer,55,Personal Travel,Eco,802,4,4,4,2,5,4,2,5,1,2,5,4,5,5,36,30.0,neutral or dissatisfied +10976,94242,Male,disloyal Customer,54,Business travel,Business,239,4,4,4,3,4,4,1,4,3,4,5,4,5,4,16,9.0,satisfied +10977,34815,Male,Loyal Customer,37,Personal Travel,Eco,209,2,1,2,3,4,2,4,4,3,2,3,2,3,4,21,12.0,neutral or dissatisfied +10978,125848,Male,disloyal Customer,37,Business travel,Eco,861,2,2,2,2,3,2,3,3,2,1,3,1,3,3,0,8.0,neutral or dissatisfied +10979,88027,Female,disloyal Customer,25,Business travel,Business,594,3,5,3,3,5,3,5,5,3,2,4,4,4,5,0,8.0,neutral or dissatisfied +10980,128308,Female,disloyal Customer,40,Business travel,Business,338,4,3,3,3,2,3,2,2,5,4,5,4,4,2,66,69.0,neutral or dissatisfied +10981,96190,Male,disloyal Customer,35,Business travel,Eco,546,3,3,3,4,2,3,2,2,1,2,4,1,3,2,6,9.0,neutral or dissatisfied +10982,69309,Male,Loyal Customer,60,Business travel,Business,1089,4,4,4,4,2,4,5,5,5,5,5,5,5,5,27,22.0,satisfied +10983,52603,Male,Loyal Customer,43,Business travel,Eco,110,4,1,1,1,5,4,5,5,4,5,3,3,3,5,0,0.0,neutral or dissatisfied +10984,10049,Female,Loyal Customer,53,Business travel,Eco,326,2,5,5,5,2,4,3,2,2,2,2,2,2,3,53,44.0,neutral or dissatisfied +10985,75392,Male,Loyal Customer,23,Business travel,Business,2585,1,1,1,1,3,3,3,3,4,2,4,3,4,3,4,0.0,satisfied +10986,7893,Female,Loyal Customer,17,Personal Travel,Eco,948,2,4,3,3,4,3,4,4,5,1,5,3,2,4,7,15.0,neutral or dissatisfied +10987,121096,Male,Loyal Customer,55,Personal Travel,Eco,1558,1,4,1,1,3,1,3,3,5,5,3,4,4,3,0,5.0,neutral or dissatisfied +10988,129356,Female,Loyal Customer,8,Business travel,Business,2475,1,1,1,1,5,5,5,5,5,3,4,3,5,5,1,0.0,satisfied +10989,122349,Female,disloyal Customer,23,Business travel,Eco,529,4,5,4,4,4,4,4,4,5,2,5,3,4,4,0,0.0,neutral or dissatisfied +10990,28241,Male,Loyal Customer,32,Personal Travel,Eco,1009,4,5,4,3,1,4,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +10991,74731,Female,Loyal Customer,37,Personal Travel,Eco,1205,4,1,3,4,3,3,3,3,3,1,4,3,4,3,4,4.0,neutral or dissatisfied +10992,61015,Male,Loyal Customer,34,Business travel,Business,3365,3,3,3,3,4,4,4,3,5,5,4,4,5,4,0,40.0,satisfied +10993,92832,Male,Loyal Customer,54,Personal Travel,Eco,1587,3,5,3,4,5,3,2,5,3,5,3,3,4,5,25,7.0,neutral or dissatisfied +10994,105109,Male,Loyal Customer,29,Business travel,Business,281,2,5,5,5,2,2,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +10995,75994,Female,disloyal Customer,25,Business travel,Business,297,5,4,5,3,4,5,4,4,3,5,5,3,5,4,0,0.0,satisfied +10996,126772,Female,Loyal Customer,40,Business travel,Business,2521,5,5,5,5,3,4,4,4,4,4,4,3,4,5,8,0.0,satisfied +10997,17642,Female,Loyal Customer,29,Business travel,Business,3794,3,3,3,3,4,4,4,4,3,5,3,3,2,4,18,1.0,satisfied +10998,111297,Female,Loyal Customer,41,Business travel,Business,3197,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +10999,125890,Male,Loyal Customer,12,Personal Travel,Eco,861,2,5,2,4,3,2,3,3,4,3,4,4,5,3,0,16.0,neutral or dissatisfied +11000,20295,Male,Loyal Customer,12,Personal Travel,Eco,235,1,4,0,4,3,0,3,3,2,3,1,2,5,3,10,0.0,neutral or dissatisfied +11001,59611,Female,Loyal Customer,46,Business travel,Business,2965,4,4,4,4,4,4,5,5,5,5,5,4,5,4,13,0.0,satisfied +11002,24093,Male,Loyal Customer,19,Business travel,Business,3217,5,5,5,5,5,5,5,5,1,2,1,2,2,5,0,0.0,satisfied +11003,57929,Female,Loyal Customer,18,Business travel,Eco Plus,305,3,4,4,4,3,3,1,3,4,1,3,3,4,3,0,8.0,neutral or dissatisfied +11004,23070,Female,disloyal Customer,49,Business travel,Eco Plus,820,2,1,1,3,4,2,2,4,3,3,2,1,2,4,0,0.0,neutral or dissatisfied +11005,6512,Female,disloyal Customer,33,Business travel,Business,599,1,1,1,3,3,1,3,3,3,4,4,5,5,3,2,2.0,neutral or dissatisfied +11006,58652,Male,Loyal Customer,21,Personal Travel,Eco,867,4,4,4,2,1,4,1,1,4,4,1,4,3,1,0,0.0,neutral or dissatisfied +11007,42462,Female,Loyal Customer,22,Business travel,Eco Plus,926,4,3,3,3,4,4,5,4,2,2,2,1,5,4,0,0.0,satisfied +11008,1950,Female,Loyal Customer,47,Business travel,Eco,190,3,4,4,4,1,4,3,4,4,3,4,1,4,1,0,0.0,neutral or dissatisfied +11009,110521,Female,Loyal Customer,22,Business travel,Business,2785,3,3,3,3,5,5,5,5,5,2,4,3,5,5,0,0.0,satisfied +11010,106507,Female,Loyal Customer,70,Personal Travel,Eco Plus,495,3,3,2,3,5,4,3,4,4,2,4,4,4,2,0,0.0,neutral or dissatisfied +11011,29730,Female,Loyal Customer,35,Personal Travel,Eco Plus,2777,2,4,2,3,2,5,5,4,4,4,4,5,4,5,0,0.0,neutral or dissatisfied +11012,76552,Male,Loyal Customer,18,Business travel,Business,547,5,5,5,5,5,5,5,5,3,2,5,4,5,5,0,0.0,satisfied +11013,10081,Male,Loyal Customer,36,Personal Travel,Eco,258,4,2,4,3,4,4,2,4,1,1,3,1,2,4,0,0.0,neutral or dissatisfied +11014,116934,Female,Loyal Customer,39,Business travel,Business,304,5,5,5,5,2,5,4,5,5,5,5,4,5,4,3,3.0,satisfied +11015,16012,Male,Loyal Customer,36,Business travel,Eco,380,2,1,1,1,2,2,2,2,4,1,3,2,3,2,25,31.0,neutral or dissatisfied +11016,115240,Male,disloyal Customer,20,Business travel,Eco,480,2,4,2,3,2,2,2,2,4,4,4,1,4,2,36,23.0,neutral or dissatisfied +11017,114868,Female,Loyal Customer,57,Business travel,Business,308,4,4,4,4,4,5,5,4,4,4,4,3,4,4,8,9.0,satisfied +11018,31104,Male,Loyal Customer,51,Business travel,Eco Plus,1014,5,2,2,2,5,5,5,5,5,1,3,4,2,5,5,5.0,satisfied +11019,23859,Female,disloyal Customer,27,Business travel,Eco,552,3,0,3,1,2,3,2,2,1,2,4,5,3,2,0,23.0,neutral or dissatisfied +11020,20665,Male,Loyal Customer,30,Business travel,Business,552,5,5,5,5,4,4,4,4,2,1,2,1,1,4,0,0.0,satisfied +11021,118096,Male,Loyal Customer,30,Business travel,Business,1671,4,4,4,4,5,4,5,5,4,5,4,5,5,5,31,5.0,satisfied +11022,42791,Female,Loyal Customer,42,Business travel,Eco,349,5,1,1,1,5,2,5,5,5,5,5,2,5,3,0,0.0,satisfied +11023,119247,Female,Loyal Customer,25,Personal Travel,Eco Plus,257,3,5,3,1,1,3,1,1,1,1,1,2,5,1,0,0.0,neutral or dissatisfied +11024,34216,Male,Loyal Customer,47,Personal Travel,Eco,1046,3,5,3,4,1,3,1,1,2,1,5,5,3,1,17,19.0,neutral or dissatisfied +11025,107163,Male,Loyal Customer,39,Business travel,Business,402,5,5,5,5,5,5,5,5,5,5,5,4,5,3,3,1.0,satisfied +11026,2100,Female,Loyal Customer,48,Personal Travel,Eco,785,2,5,2,1,2,5,4,2,2,2,1,4,2,5,0,8.0,neutral or dissatisfied +11027,85356,Male,Loyal Customer,23,Personal Travel,Eco Plus,689,5,5,5,1,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +11028,103576,Female,Loyal Customer,49,Personal Travel,Eco,604,1,5,1,4,4,5,5,5,5,1,5,3,5,5,18,0.0,neutral or dissatisfied +11029,71110,Female,disloyal Customer,41,Business travel,Business,2072,1,1,1,2,2,1,2,2,4,3,3,4,4,2,25,5.0,neutral or dissatisfied +11030,64177,Female,Loyal Customer,42,Business travel,Business,989,1,1,1,1,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +11031,5716,Female,Loyal Customer,47,Personal Travel,Eco,299,3,5,3,4,4,4,4,3,3,3,3,5,3,3,82,75.0,neutral or dissatisfied +11032,22831,Female,Loyal Customer,33,Business travel,Business,2494,2,2,2,2,5,4,5,5,5,5,5,2,5,4,0,0.0,satisfied +11033,54600,Female,Loyal Customer,57,Business travel,Business,787,1,0,0,2,4,3,3,5,5,0,5,1,5,4,0,0.0,neutral or dissatisfied +11034,105992,Male,Loyal Customer,47,Business travel,Business,1999,5,5,5,5,5,5,5,4,4,4,4,5,4,4,20,0.0,satisfied +11035,9721,Male,Loyal Customer,9,Personal Travel,Eco,199,3,5,3,4,3,3,3,4,2,5,4,3,3,3,112,143.0,neutral or dissatisfied +11036,17720,Female,Loyal Customer,39,Business travel,Business,3965,3,3,3,3,4,3,2,4,4,4,4,2,4,4,0,0.0,satisfied +11037,107142,Male,Loyal Customer,41,Business travel,Business,3996,1,1,1,1,4,5,4,4,4,4,4,3,4,4,0,3.0,satisfied +11038,35609,Female,Loyal Customer,59,Personal Travel,Eco Plus,828,2,5,2,1,2,4,5,4,4,2,4,5,4,4,58,70.0,neutral or dissatisfied +11039,106993,Male,Loyal Customer,35,Personal Travel,Eco,1036,1,5,1,2,3,1,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +11040,20834,Female,Loyal Customer,37,Business travel,Eco,515,1,3,5,3,1,1,1,1,1,5,3,2,4,1,6,21.0,neutral or dissatisfied +11041,122568,Female,Loyal Customer,55,Business travel,Business,3074,3,3,3,3,2,4,5,5,5,5,5,5,5,4,36,22.0,satisfied +11042,116240,Female,Loyal Customer,48,Personal Travel,Eco,417,3,1,3,3,4,3,2,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +11043,60595,Male,Loyal Customer,23,Personal Travel,Eco,1558,1,3,0,3,2,0,1,2,4,2,4,4,3,2,0,0.0,neutral or dissatisfied +11044,37964,Female,Loyal Customer,45,Business travel,Business,1623,1,1,1,1,3,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +11045,10198,Female,Loyal Customer,47,Business travel,Business,3939,1,1,3,1,5,5,5,5,2,5,4,5,4,5,0,0.0,satisfied +11046,29265,Female,Loyal Customer,27,Business travel,Eco,859,5,3,3,3,5,5,5,5,4,2,5,1,5,5,0,12.0,satisfied +11047,108711,Male,Loyal Customer,20,Personal Travel,Eco,425,2,1,2,4,5,2,5,5,3,1,3,1,3,5,14,0.0,neutral or dissatisfied +11048,31996,Female,Loyal Customer,57,Personal Travel,Business,216,3,4,3,4,4,5,5,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +11049,64752,Female,Loyal Customer,47,Business travel,Business,3623,0,0,0,2,4,4,4,2,2,2,2,4,2,5,6,44.0,satisfied +11050,25555,Male,Loyal Customer,33,Business travel,Business,3305,4,4,4,4,5,5,5,5,5,2,5,5,5,5,23,13.0,satisfied +11051,47913,Male,Loyal Customer,59,Personal Travel,Eco,834,2,4,2,1,4,2,4,4,3,5,5,5,5,4,17,18.0,neutral or dissatisfied +11052,1872,Female,Loyal Customer,48,Business travel,Eco,931,3,4,4,4,2,3,3,3,3,3,3,4,3,1,67,73.0,neutral or dissatisfied +11053,111764,Male,Loyal Customer,42,Business travel,Business,1436,5,5,5,5,3,5,4,4,4,4,4,4,4,3,8,0.0,satisfied +11054,19425,Female,disloyal Customer,11,Business travel,Eco,645,3,2,4,3,1,4,1,1,1,2,3,4,4,1,22,28.0,neutral or dissatisfied +11055,91300,Male,Loyal Customer,55,Business travel,Business,3219,4,4,4,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +11056,103348,Female,Loyal Customer,44,Business travel,Business,1371,1,1,1,1,5,5,5,3,3,4,4,5,5,5,146,145.0,satisfied +11057,31858,Female,Loyal Customer,35,Personal Travel,Eco,2640,2,1,2,3,5,2,5,5,4,3,2,3,3,5,0,0.0,neutral or dissatisfied +11058,47697,Female,Loyal Customer,62,Personal Travel,Eco,1235,1,5,1,2,5,4,4,4,4,1,3,4,4,3,0,0.0,neutral or dissatisfied +11059,121244,Female,Loyal Customer,32,Business travel,Business,2075,3,3,3,3,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +11060,109925,Female,Loyal Customer,21,Personal Travel,Eco,971,2,5,2,3,5,2,5,5,5,3,4,3,5,5,38,37.0,neutral or dissatisfied +11061,37562,Male,Loyal Customer,58,Business travel,Eco,669,3,2,2,2,3,3,3,3,2,2,4,4,4,3,31,27.0,neutral or dissatisfied +11062,78776,Male,Loyal Customer,17,Business travel,Business,3481,1,1,1,1,5,4,5,5,3,2,5,4,5,5,0,0.0,satisfied +11063,37099,Male,Loyal Customer,22,Business travel,Business,2252,1,1,1,1,4,4,4,4,2,3,4,4,5,4,0,0.0,satisfied +11064,86883,Male,Loyal Customer,24,Personal Travel,Eco Plus,692,1,1,1,3,4,1,4,4,1,5,2,1,3,4,0,0.0,neutral or dissatisfied +11065,119102,Female,Loyal Customer,30,Business travel,Business,3629,4,4,1,4,4,4,4,4,1,5,2,1,3,4,0,0.0,neutral or dissatisfied +11066,113876,Male,Loyal Customer,39,Personal Travel,Eco,1592,3,4,3,3,3,3,3,3,2,1,3,2,4,3,0,0.0,neutral or dissatisfied +11067,53088,Female,Loyal Customer,50,Personal Travel,Eco,2327,1,1,2,2,1,1,2,5,5,2,5,4,5,2,90,63.0,neutral or dissatisfied +11068,21012,Male,Loyal Customer,39,Business travel,Business,2368,2,2,2,2,4,5,4,5,5,5,5,3,5,4,30,25.0,satisfied +11069,104255,Male,Loyal Customer,41,Business travel,Business,3594,2,2,2,2,3,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +11070,106399,Male,disloyal Customer,22,Business travel,Eco,551,4,0,4,2,3,4,3,3,5,3,2,2,5,3,0,0.0,neutral or dissatisfied +11071,104345,Female,Loyal Customer,45,Personal Travel,Eco,528,2,4,2,1,2,5,5,1,1,2,2,3,1,5,0,0.0,neutral or dissatisfied +11072,61989,Female,disloyal Customer,22,Business travel,Eco,1199,4,4,4,4,4,5,4,5,5,5,5,4,5,4,2,37.0,satisfied +11073,119659,Male,Loyal Customer,34,Business travel,Business,2025,1,1,1,1,5,3,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +11074,100558,Female,Loyal Customer,19,Business travel,Eco Plus,1111,4,5,5,5,4,3,4,4,4,3,3,4,4,4,55,43.0,neutral or dissatisfied +11075,69798,Male,Loyal Customer,48,Business travel,Eco,1055,4,3,3,3,4,4,4,4,3,2,3,2,3,4,0,7.0,neutral or dissatisfied +11076,97237,Female,Loyal Customer,47,Business travel,Business,3421,0,0,0,2,4,5,5,3,3,4,4,5,3,4,0,0.0,satisfied +11077,125050,Male,Loyal Customer,13,Personal Travel,Eco,2300,3,3,3,4,3,5,3,3,2,3,3,3,4,3,0,28.0,neutral or dissatisfied +11078,1457,Male,Loyal Customer,37,Business travel,Business,695,2,4,4,4,4,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +11079,97287,Female,Loyal Customer,49,Business travel,Business,347,1,1,1,1,5,4,4,4,4,4,4,4,4,3,1,0.0,satisfied +11080,1965,Male,disloyal Customer,65,Business travel,Eco,295,1,1,1,3,1,1,4,1,2,3,3,3,3,1,7,0.0,neutral or dissatisfied +11081,76667,Male,Loyal Customer,65,Personal Travel,Eco,534,4,5,4,3,1,4,1,1,3,5,4,4,5,1,0,24.0,neutral or dissatisfied +11082,58685,Male,Loyal Customer,56,Business travel,Business,1896,3,3,3,3,2,4,4,4,4,5,4,3,4,5,2,2.0,satisfied +11083,28633,Male,Loyal Customer,27,Business travel,Business,2466,1,1,1,1,5,5,5,5,3,3,5,2,4,5,0,0.0,satisfied +11084,83481,Female,Loyal Customer,44,Business travel,Eco,946,1,3,1,3,4,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +11085,12943,Female,Loyal Customer,10,Personal Travel,Eco,794,3,1,3,3,2,3,2,2,3,2,2,1,2,2,0,0.0,neutral or dissatisfied +11086,119179,Female,Loyal Customer,58,Business travel,Business,3133,5,5,5,5,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +11087,50965,Female,Loyal Customer,21,Personal Travel,Eco,190,3,4,0,1,3,0,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +11088,14423,Female,Loyal Customer,8,Personal Travel,Eco,693,3,5,3,3,3,3,3,3,5,3,4,5,4,3,28,44.0,neutral or dissatisfied +11089,46601,Male,Loyal Customer,53,Business travel,Business,3859,1,1,5,1,5,5,2,4,4,4,4,3,4,5,0,0.0,satisfied +11090,101607,Male,Loyal Customer,26,Business travel,Business,3033,4,4,4,4,4,4,4,4,4,2,4,3,5,4,2,0.0,satisfied +11091,4299,Female,Loyal Customer,59,Personal Travel,Eco,502,1,3,1,3,4,3,2,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +11092,35677,Male,Loyal Customer,48,Business travel,Business,2521,4,5,5,5,3,4,4,1,3,4,3,4,4,4,0,0.0,neutral or dissatisfied +11093,88579,Male,Loyal Customer,59,Personal Travel,Eco,406,1,4,4,3,3,4,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +11094,107319,Female,Loyal Customer,45,Business travel,Eco Plus,283,4,3,3,3,4,4,3,3,3,4,3,4,3,4,50,69.0,neutral or dissatisfied +11095,79263,Male,Loyal Customer,7,Personal Travel,Eco,1598,3,2,3,4,3,3,3,3,1,3,3,1,4,3,0,0.0,neutral or dissatisfied +11096,51971,Male,Loyal Customer,48,Business travel,Business,1501,5,1,1,1,4,4,3,5,5,4,5,2,5,1,0,9.0,neutral or dissatisfied +11097,63746,Male,Loyal Customer,53,Personal Travel,Eco,1660,1,4,1,4,5,1,5,5,4,3,5,4,4,5,18,0.0,neutral or dissatisfied +11098,20397,Female,Loyal Customer,42,Personal Travel,Eco,459,3,4,3,4,3,3,3,3,4,2,2,3,5,3,145,140.0,neutral or dissatisfied +11099,40431,Male,Loyal Customer,34,Business travel,Business,175,3,3,3,3,1,5,5,3,3,4,4,4,3,1,0,2.0,satisfied +11100,77221,Male,Loyal Customer,44,Business travel,Business,1590,3,3,3,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +11101,22404,Male,disloyal Customer,37,Business travel,Eco,238,3,3,3,3,3,3,3,2,2,3,3,3,2,3,152,163.0,neutral or dissatisfied +11102,7170,Male,Loyal Customer,46,Business travel,Business,135,2,2,5,2,3,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +11103,127095,Female,disloyal Customer,24,Business travel,Eco,651,3,2,3,3,3,3,3,3,1,5,4,1,3,3,0,0.0,neutral or dissatisfied +11104,404,Male,Loyal Customer,39,Business travel,Business,102,4,5,4,4,2,3,3,2,2,1,4,1,2,2,0,0.0,neutral or dissatisfied +11105,53748,Male,Loyal Customer,46,Personal Travel,Eco Plus,1190,5,4,5,4,2,5,2,2,4,5,5,4,4,2,0,0.0,satisfied +11106,91287,Male,Loyal Customer,35,Business travel,Business,2976,3,3,3,3,4,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +11107,93053,Male,disloyal Customer,58,Business travel,Business,297,5,5,5,3,2,5,2,2,5,2,4,4,5,2,1,0.0,satisfied +11108,10009,Female,Loyal Customer,10,Personal Travel,Eco,508,2,5,2,1,4,2,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +11109,117161,Female,Loyal Customer,54,Personal Travel,Eco,621,2,3,2,1,4,2,5,2,2,2,4,5,2,5,0,0.0,neutral or dissatisfied +11110,25644,Female,Loyal Customer,28,Personal Travel,Eco,526,2,4,2,4,2,2,2,2,4,4,4,2,3,2,0,0.0,neutral or dissatisfied +11111,60820,Male,Loyal Customer,60,Personal Travel,Eco,524,2,4,2,3,5,2,5,5,3,4,5,5,5,5,25,21.0,neutral or dissatisfied +11112,100571,Female,Loyal Customer,46,Business travel,Business,486,1,1,1,1,5,4,4,4,4,4,4,3,4,4,7,14.0,satisfied +11113,14582,Female,disloyal Customer,45,Business travel,Eco,986,1,1,1,3,5,1,3,5,5,5,5,4,3,5,0,0.0,neutral or dissatisfied +11114,99018,Male,Loyal Customer,36,Business travel,Eco Plus,479,3,3,3,3,3,3,3,3,2,5,4,2,4,3,56,46.0,neutral or dissatisfied +11115,83809,Female,Loyal Customer,50,Business travel,Business,3354,4,4,3,4,4,5,4,5,5,5,5,4,5,3,31,29.0,satisfied +11116,85842,Male,Loyal Customer,59,Personal Travel,Eco,666,2,5,2,3,2,2,2,2,4,5,3,5,2,2,0,4.0,neutral or dissatisfied +11117,110679,Male,Loyal Customer,32,Personal Travel,Eco,945,5,2,5,3,1,5,4,1,2,2,4,3,3,1,1,0.0,satisfied +11118,8560,Female,Loyal Customer,41,Business travel,Business,109,5,5,4,5,2,4,5,4,4,4,4,5,4,3,0,3.0,satisfied +11119,105314,Female,Loyal Customer,33,Business travel,Business,452,1,1,4,1,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +11120,89019,Male,Loyal Customer,42,Business travel,Business,2139,2,3,3,3,2,2,3,2,2,2,2,3,2,3,30,22.0,neutral or dissatisfied +11121,100875,Female,Loyal Customer,28,Business travel,Business,2133,3,3,3,3,4,4,4,4,3,3,5,5,4,4,69,60.0,satisfied +11122,51086,Female,Loyal Customer,66,Personal Travel,Eco,110,3,3,3,4,4,4,4,5,5,3,5,4,5,3,7,5.0,neutral or dissatisfied +11123,59258,Female,Loyal Customer,28,Business travel,Business,3904,2,2,2,2,4,4,4,5,2,3,5,4,4,4,14,0.0,satisfied +11124,59377,Male,disloyal Customer,33,Business travel,Eco,2504,2,2,2,4,5,2,5,5,2,3,4,3,4,5,0,0.0,neutral or dissatisfied +11125,65591,Male,Loyal Customer,33,Business travel,Business,3179,3,3,3,3,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +11126,87632,Male,disloyal Customer,52,Business travel,Business,606,2,2,2,3,1,2,1,1,3,2,4,3,4,1,0,0.0,satisfied +11127,129836,Female,Loyal Customer,49,Personal Travel,Eco,337,4,5,4,3,5,4,4,5,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +11128,111167,Male,Loyal Customer,57,Personal Travel,Eco Plus,1111,3,5,3,3,2,3,4,2,4,2,4,5,4,2,1,0.0,neutral or dissatisfied +11129,102617,Male,Loyal Customer,56,Personal Travel,Eco,1294,2,5,2,3,1,2,1,1,3,2,5,5,5,1,7,0.0,neutral or dissatisfied +11130,47721,Female,Loyal Customer,51,Business travel,Business,3107,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +11131,21433,Female,Loyal Customer,67,Business travel,Business,377,4,3,3,3,4,3,4,4,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +11132,105703,Female,Loyal Customer,27,Business travel,Business,925,2,2,2,2,2,3,2,2,1,3,4,1,3,2,0,4.0,neutral or dissatisfied +11133,72019,Male,Loyal Customer,24,Business travel,Business,3711,3,3,3,3,5,5,5,4,5,4,4,5,3,5,0,0.0,satisfied +11134,64188,Female,Loyal Customer,21,Personal Travel,Eco,1047,3,1,3,3,1,3,1,1,4,1,4,1,3,1,0,0.0,neutral or dissatisfied +11135,79315,Female,Loyal Customer,60,Personal Travel,Eco,2248,3,4,3,4,3,3,3,5,5,3,3,4,5,3,0,0.0,neutral or dissatisfied +11136,12332,Male,disloyal Customer,48,Business travel,Business,285,3,3,3,3,1,3,1,1,3,5,4,4,3,1,0,0.0,neutral or dissatisfied +11137,32126,Female,Loyal Customer,34,Business travel,Eco,216,4,2,5,2,4,4,4,4,1,1,3,4,3,4,14,16.0,satisfied +11138,28186,Male,Loyal Customer,70,Personal Travel,Eco,933,1,4,2,3,3,2,3,3,3,3,5,5,5,3,11,5.0,neutral or dissatisfied +11139,30518,Male,disloyal Customer,37,Business travel,Eco,373,2,4,2,3,5,2,4,5,3,3,4,1,3,5,0,0.0,neutral or dissatisfied +11140,70418,Female,Loyal Customer,33,Personal Travel,Eco Plus,1562,1,5,1,4,1,1,1,1,5,5,5,3,4,1,58,48.0,neutral or dissatisfied +11141,71317,Female,Loyal Customer,27,Business travel,Business,1514,5,5,5,5,4,4,4,4,3,3,5,4,5,4,13,12.0,satisfied +11142,54595,Male,disloyal Customer,25,Business travel,Business,964,5,0,5,4,3,5,3,3,5,2,5,5,5,3,0,0.0,satisfied +11143,77206,Female,Loyal Customer,54,Personal Travel,Eco,2994,4,4,4,3,4,2,2,3,5,4,4,2,5,2,0,0.0,satisfied +11144,24775,Male,disloyal Customer,38,Business travel,Eco,528,2,4,3,4,3,3,1,3,4,5,3,3,3,3,0,1.0,neutral or dissatisfied +11145,24023,Female,Loyal Customer,37,Business travel,Eco,562,2,4,4,4,2,2,2,2,4,4,4,1,3,2,27,30.0,neutral or dissatisfied +11146,122211,Female,Loyal Customer,49,Business travel,Business,2943,1,1,1,1,4,5,5,4,4,5,4,5,4,4,7,1.0,satisfied +11147,116649,Female,disloyal Customer,25,Business travel,Eco Plus,337,2,4,2,3,2,5,5,1,5,4,3,5,1,5,146,140.0,neutral or dissatisfied +11148,22871,Male,Loyal Customer,12,Personal Travel,Eco,147,4,3,4,3,3,4,3,3,2,5,2,2,3,3,0,1.0,satisfied +11149,97998,Female,Loyal Customer,53,Business travel,Business,612,2,2,2,2,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +11150,19817,Male,Loyal Customer,30,Business travel,Business,3236,5,4,5,4,5,4,5,5,3,5,3,4,3,5,23,17.0,neutral or dissatisfied +11151,50411,Female,disloyal Customer,26,Business travel,Eco,110,1,0,1,5,5,1,5,5,1,5,3,4,2,5,0,,neutral or dissatisfied +11152,69620,Male,Loyal Customer,33,Personal Travel,Eco Plus,2586,2,5,2,5,2,5,5,5,4,4,5,5,5,5,0,24.0,neutral or dissatisfied +11153,90436,Male,Loyal Customer,42,Business travel,Business,545,1,1,1,1,4,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +11154,82185,Male,Loyal Customer,40,Business travel,Business,1927,2,3,2,2,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +11155,108178,Female,Loyal Customer,19,Personal Travel,Eco,990,2,5,2,2,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +11156,48110,Female,Loyal Customer,45,Business travel,Business,2624,2,2,2,2,2,3,2,5,5,5,4,4,5,3,0,0.0,satisfied +11157,94717,Male,Loyal Customer,37,Business travel,Eco,189,1,5,5,5,1,2,1,1,4,5,4,3,3,1,7,17.0,neutral or dissatisfied +11158,29606,Female,Loyal Customer,26,Business travel,Business,1533,1,2,2,2,1,2,1,1,2,3,4,2,3,1,0,22.0,neutral or dissatisfied +11159,28924,Female,Loyal Customer,48,Business travel,Eco,679,3,2,2,2,4,2,4,3,3,3,3,2,3,3,0,0.0,satisfied +11160,124134,Female,Loyal Customer,11,Personal Travel,Eco,529,4,4,4,5,5,4,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +11161,101487,Female,Loyal Customer,45,Business travel,Business,3845,2,2,2,2,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +11162,27202,Female,Loyal Customer,35,Business travel,Business,2717,4,4,4,4,3,2,3,4,4,4,4,1,4,1,0,2.0,neutral or dissatisfied +11163,47313,Male,disloyal Customer,22,Business travel,Eco,588,0,0,0,1,4,0,2,4,4,1,2,4,3,4,0,0.0,satisfied +11164,39311,Male,Loyal Customer,48,Personal Travel,Eco,268,4,3,4,3,4,4,4,4,1,5,4,2,3,4,15,0.0,neutral or dissatisfied +11165,74427,Female,Loyal Customer,57,Business travel,Business,1205,2,2,2,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +11166,16650,Male,Loyal Customer,14,Business travel,Eco,488,0,3,0,2,5,0,5,5,4,3,2,5,2,5,18,16.0,satisfied +11167,103311,Male,Loyal Customer,31,Business travel,Business,2364,5,5,5,5,4,4,4,4,3,2,5,4,4,4,0,0.0,satisfied +11168,73956,Female,Loyal Customer,54,Personal Travel,Eco,2342,1,2,1,2,1,1,1,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +11169,88392,Male,disloyal Customer,25,Business travel,Eco,581,1,2,1,2,5,1,5,5,4,1,3,4,3,5,0,2.0,neutral or dissatisfied +11170,50390,Female,Loyal Customer,37,Business travel,Eco,373,4,3,3,3,4,4,4,4,1,5,4,1,5,4,1,0.0,satisfied +11171,102972,Female,Loyal Customer,12,Personal Travel,Business,460,3,5,3,1,2,3,5,2,3,2,4,4,5,2,9,1.0,neutral or dissatisfied +11172,121547,Male,Loyal Customer,55,Business travel,Business,3086,3,4,3,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +11173,45467,Male,Loyal Customer,30,Business travel,Business,522,5,5,5,5,4,4,4,4,4,2,3,4,4,4,0,0.0,satisfied +11174,105391,Female,Loyal Customer,67,Personal Travel,Eco,369,2,3,2,1,5,3,3,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +11175,25322,Female,Loyal Customer,67,Personal Travel,Business,945,3,1,3,4,4,4,4,2,2,3,2,3,2,1,13,18.0,neutral or dissatisfied +11176,26458,Female,Loyal Customer,46,Business travel,Business,442,3,1,1,1,3,1,2,3,3,3,3,2,3,3,1,0.0,neutral or dissatisfied +11177,107470,Male,Loyal Customer,28,Personal Travel,Eco,1121,3,4,3,5,4,3,4,4,3,2,4,5,5,4,1,6.0,neutral or dissatisfied +11178,31117,Male,Loyal Customer,50,Business travel,Eco,991,4,3,3,3,4,4,4,4,5,1,2,4,4,4,0,33.0,satisfied +11179,110725,Male,Loyal Customer,45,Business travel,Business,2803,5,5,5,5,3,5,4,4,4,4,4,5,4,5,13,6.0,satisfied +11180,62267,Female,Loyal Customer,52,Personal Travel,Eco Plus,2425,1,4,1,1,2,4,5,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +11181,118439,Male,Loyal Customer,39,Business travel,Business,2425,4,4,4,4,4,4,4,4,4,5,4,5,4,3,10,1.0,satisfied +11182,32080,Male,Loyal Customer,49,Business travel,Eco,163,5,4,4,4,5,5,5,5,5,1,2,4,2,5,0,5.0,satisfied +11183,54913,Male,Loyal Customer,47,Business travel,Business,862,4,4,4,4,5,4,5,5,5,5,5,4,5,4,3,0.0,satisfied +11184,1645,Female,Loyal Customer,41,Business travel,Business,1808,2,2,2,2,5,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +11185,35967,Male,Loyal Customer,43,Personal Travel,Eco,231,2,4,2,4,4,2,4,4,1,4,4,3,3,4,96,102.0,neutral or dissatisfied +11186,20874,Female,Loyal Customer,40,Business travel,Eco Plus,357,5,3,3,3,5,5,5,5,3,5,4,3,1,5,0,0.0,satisfied +11187,8753,Female,Loyal Customer,55,Business travel,Business,3989,2,2,4,2,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +11188,2593,Male,Loyal Customer,67,Personal Travel,Eco,280,3,3,3,4,3,3,3,3,2,4,4,2,3,3,45,38.0,neutral or dissatisfied +11189,70580,Male,Loyal Customer,62,Personal Travel,Eco,1258,0,4,0,5,4,0,4,4,3,4,5,5,4,4,0,0.0,satisfied +11190,111557,Female,Loyal Customer,45,Business travel,Business,1902,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +11191,108517,Male,Loyal Customer,29,Personal Travel,Eco,519,1,4,2,2,4,2,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +11192,62866,Female,Loyal Customer,30,Business travel,Business,2583,3,4,4,4,3,3,3,3,2,2,3,2,3,3,0,0.0,neutral or dissatisfied +11193,14307,Male,Loyal Customer,43,Business travel,Business,3721,1,1,1,1,4,4,1,5,5,5,5,4,5,1,5,0.0,satisfied +11194,43234,Male,Loyal Customer,58,Business travel,Business,347,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +11195,51067,Female,Loyal Customer,44,Personal Travel,Eco,109,1,1,1,3,3,3,4,4,4,1,4,3,4,1,20,23.0,neutral or dissatisfied +11196,83183,Male,Loyal Customer,70,Personal Travel,Eco,549,4,0,4,2,4,4,4,4,3,4,5,5,5,4,0,1.0,neutral or dissatisfied +11197,64877,Male,Loyal Customer,46,Business travel,Business,469,5,5,5,5,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +11198,7532,Male,Loyal Customer,31,Business travel,Business,762,2,2,2,2,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +11199,45493,Female,Loyal Customer,63,Personal Travel,Eco,522,4,4,2,2,1,1,5,5,5,2,5,1,5,1,0,0.0,neutral or dissatisfied +11200,18028,Male,disloyal Customer,19,Business travel,Eco,488,3,0,2,5,3,2,3,3,3,4,3,5,2,3,0,0.0,neutral or dissatisfied +11201,51759,Female,Loyal Customer,49,Personal Travel,Eco,370,3,4,3,1,3,1,4,5,5,3,5,2,5,5,0,0.0,neutral or dissatisfied +11202,3121,Female,disloyal Customer,29,Business travel,Eco,1013,5,4,4,1,3,4,3,3,3,5,1,1,4,3,0,0.0,satisfied +11203,37385,Male,disloyal Customer,25,Business travel,Eco,944,4,3,3,3,5,3,5,5,5,2,4,3,1,5,3,0.0,satisfied +11204,55654,Female,Loyal Customer,48,Business travel,Business,2543,3,3,2,3,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +11205,92998,Female,disloyal Customer,30,Business travel,Eco Plus,738,2,2,2,3,4,2,3,4,2,3,3,3,3,4,0,0.0,neutral or dissatisfied +11206,20585,Male,Loyal Customer,23,Personal Travel,Eco,773,2,5,2,3,5,2,5,5,4,5,5,3,5,5,2,0.0,neutral or dissatisfied +11207,121012,Female,Loyal Customer,55,Personal Travel,Eco,951,1,4,1,3,5,4,3,4,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +11208,42338,Female,Loyal Customer,58,Personal Travel,Eco,550,2,2,2,3,3,1,2,3,3,2,3,2,3,1,0,0.0,neutral or dissatisfied +11209,24255,Female,Loyal Customer,62,Personal Travel,Eco,302,2,5,2,3,2,4,4,5,5,2,5,4,5,4,59,54.0,neutral or dissatisfied +11210,68774,Male,Loyal Customer,51,Business travel,Business,2370,5,5,2,5,2,4,5,5,5,5,5,3,5,5,16,17.0,satisfied +11211,89195,Female,Loyal Customer,68,Personal Travel,Eco,1892,5,2,5,3,4,4,4,2,2,5,2,1,2,1,0,0.0,satisfied +11212,115702,Female,disloyal Customer,33,Business travel,Eco,372,1,4,1,4,1,1,1,1,3,2,4,2,3,1,4,0.0,neutral or dissatisfied +11213,105498,Female,Loyal Customer,61,Personal Travel,Eco,516,1,3,1,1,3,3,2,3,3,1,3,4,3,1,10,13.0,neutral or dissatisfied +11214,65031,Male,Loyal Customer,31,Personal Travel,Eco,190,3,5,3,1,5,3,5,5,3,2,5,4,4,5,0,0.0,neutral or dissatisfied +11215,6714,Female,Loyal Customer,54,Personal Travel,Eco,438,3,5,3,3,5,4,5,3,3,3,4,3,3,3,0,0.0,neutral or dissatisfied +11216,95711,Female,Loyal Customer,37,Business travel,Eco,453,3,4,4,4,3,3,3,3,4,2,3,2,3,3,15,3.0,neutral or dissatisfied +11217,8249,Male,Loyal Customer,24,Personal Travel,Eco,530,3,4,3,3,1,3,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +11218,32819,Female,disloyal Customer,23,Business travel,Eco,216,1,2,0,3,4,0,3,4,2,3,3,2,4,4,11,13.0,neutral or dissatisfied +11219,33906,Female,Loyal Customer,24,Personal Travel,Eco,1504,3,4,3,4,5,3,5,5,2,4,4,2,4,5,0,0.0,neutral or dissatisfied +11220,2256,Female,Loyal Customer,55,Business travel,Business,2829,1,1,1,1,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +11221,50318,Female,Loyal Customer,47,Business travel,Eco,421,5,5,5,5,2,2,3,5,5,5,5,2,5,5,0,0.0,satisfied +11222,35391,Male,Loyal Customer,17,Business travel,Business,1056,5,5,5,5,4,4,4,4,3,3,5,3,1,4,6,0.0,satisfied +11223,18609,Male,Loyal Customer,35,Business travel,Eco,127,4,4,4,4,4,5,4,4,5,4,4,5,2,4,0,0.0,satisfied +11224,20000,Male,Loyal Customer,36,Business travel,Eco,589,4,2,2,2,4,4,4,4,5,4,4,4,5,4,0,0.0,satisfied +11225,94331,Female,Loyal Customer,51,Business travel,Business,248,5,5,5,5,2,5,4,4,4,4,4,4,4,3,1,1.0,satisfied +11226,90406,Male,Loyal Customer,43,Business travel,Business,3733,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +11227,20459,Female,disloyal Customer,36,Business travel,Eco,177,2,4,2,5,5,2,5,5,1,1,3,4,2,5,0,0.0,neutral or dissatisfied +11228,114570,Female,Loyal Customer,52,Personal Travel,Business,371,1,5,1,2,5,1,5,1,1,1,1,1,1,4,13,9.0,neutral or dissatisfied +11229,127033,Female,Loyal Customer,48,Business travel,Business,325,5,1,1,1,4,2,2,5,5,4,5,2,5,3,2,6.0,neutral or dissatisfied +11230,13011,Male,disloyal Customer,25,Business travel,Eco,374,5,4,5,5,4,5,4,4,3,2,5,3,3,4,0,1.0,satisfied +11231,99440,Female,Loyal Customer,57,Personal Travel,Eco Plus,337,1,5,1,3,5,3,2,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +11232,91449,Female,Loyal Customer,52,Business travel,Business,859,1,1,4,1,5,4,5,2,2,2,2,3,2,4,0,2.0,satisfied +11233,9495,Female,disloyal Customer,64,Business travel,Eco,239,3,3,3,3,2,3,2,2,3,3,3,4,3,2,1,0.0,neutral or dissatisfied +11234,127690,Male,disloyal Customer,27,Business travel,Business,2133,1,1,1,4,3,1,3,3,4,3,3,5,5,3,0,0.0,neutral or dissatisfied +11235,90750,Female,disloyal Customer,39,Business travel,Business,270,2,1,1,1,3,1,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +11236,104919,Female,Loyal Customer,36,Business travel,Eco,210,3,2,2,2,3,3,3,3,2,1,3,2,3,3,32,33.0,neutral or dissatisfied +11237,57051,Female,Loyal Customer,49,Business travel,Business,2133,2,2,2,2,5,4,4,5,5,5,5,4,5,5,20,2.0,satisfied +11238,74635,Male,Loyal Customer,62,Business travel,Eco,835,2,5,5,5,2,2,2,2,3,3,1,3,2,2,0,0.0,neutral or dissatisfied +11239,10942,Male,Loyal Customer,39,Business travel,Business,3622,2,5,1,5,5,4,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +11240,128853,Female,Loyal Customer,14,Personal Travel,Eco,2475,4,2,4,3,4,5,5,1,1,2,2,5,4,5,3,21.0,neutral or dissatisfied +11241,55822,Male,Loyal Customer,50,Business travel,Business,1416,4,4,4,4,5,4,4,3,3,3,3,5,3,3,5,28.0,satisfied +11242,5086,Female,Loyal Customer,63,Business travel,Business,3145,1,1,1,1,1,5,4,4,4,4,4,3,4,3,0,1.0,satisfied +11243,52020,Female,disloyal Customer,34,Business travel,Eco,328,4,0,4,1,3,4,3,3,3,1,3,4,1,3,0,0.0,neutral or dissatisfied +11244,27228,Male,Loyal Customer,40,Business travel,Business,2681,2,1,5,1,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +11245,128271,Male,Loyal Customer,52,Business travel,Business,251,1,1,5,1,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +11246,609,Male,Loyal Customer,50,Business travel,Business,3643,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,12.0,satisfied +11247,61058,Male,Loyal Customer,49,Business travel,Business,1546,2,2,2,2,2,4,4,4,4,4,4,3,4,4,18,1.0,satisfied +11248,105990,Male,Loyal Customer,47,Personal Travel,Eco,912,0,4,0,4,1,0,1,1,3,5,5,4,5,1,15,33.0,satisfied +11249,29301,Female,disloyal Customer,24,Business travel,Eco,473,2,0,2,3,3,2,3,3,5,4,4,4,2,3,0,0.0,neutral or dissatisfied +11250,62176,Female,Loyal Customer,57,Business travel,Business,2454,1,3,3,3,2,3,4,1,1,1,1,1,1,4,11,0.0,neutral or dissatisfied +11251,82786,Male,disloyal Customer,42,Business travel,Business,231,2,2,2,3,3,2,4,3,3,3,3,1,3,3,31,41.0,neutral or dissatisfied +11252,50121,Female,Loyal Customer,33,Business travel,Eco,326,2,4,4,4,2,2,2,2,2,2,3,2,4,2,65,55.0,neutral or dissatisfied +11253,122744,Female,Loyal Customer,38,Business travel,Business,651,2,1,1,1,1,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +11254,44215,Male,Loyal Customer,48,Business travel,Business,118,3,3,3,3,1,4,1,5,5,5,4,2,5,4,0,2.0,satisfied +11255,118108,Female,Loyal Customer,63,Personal Travel,Eco,1999,1,4,1,2,5,4,4,2,2,1,2,5,2,5,66,49.0,neutral or dissatisfied +11256,121987,Female,disloyal Customer,40,Business travel,Business,130,3,3,3,2,2,3,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +11257,56785,Female,Loyal Customer,48,Personal Travel,Eco Plus,1085,5,3,5,2,3,4,4,1,1,5,1,5,1,2,0,0.0,satisfied +11258,80702,Female,Loyal Customer,17,Personal Travel,Eco,748,4,4,4,2,5,4,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +11259,75740,Female,Loyal Customer,54,Business travel,Eco,868,1,3,3,3,1,3,4,1,1,1,1,4,1,4,28,42.0,neutral or dissatisfied +11260,70043,Female,Loyal Customer,49,Personal Travel,Eco,583,3,5,3,3,2,5,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +11261,42419,Female,Loyal Customer,54,Personal Travel,Eco Plus,748,2,2,2,3,4,3,2,1,1,2,1,4,1,4,0,6.0,neutral or dissatisfied +11262,121515,Male,Loyal Customer,47,Business travel,Business,3240,2,2,2,2,2,4,4,2,2,2,2,5,2,3,0,7.0,satisfied +11263,81578,Male,Loyal Customer,61,Personal Travel,Eco,1039,1,4,1,3,2,1,2,2,4,4,4,4,5,2,0,0.0,neutral or dissatisfied +11264,103973,Male,Loyal Customer,37,Business travel,Eco Plus,370,4,3,1,3,4,4,4,4,2,2,2,5,5,4,0,0.0,satisfied +11265,100651,Female,Loyal Customer,62,Personal Travel,Eco Plus,349,2,4,2,4,1,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +11266,101023,Male,Loyal Customer,45,Personal Travel,Eco,867,3,2,3,4,3,3,3,3,3,5,3,2,3,3,40,41.0,neutral or dissatisfied +11267,101702,Female,Loyal Customer,51,Business travel,Business,1624,4,4,1,4,2,3,4,5,5,4,5,3,5,3,3,0.0,satisfied +11268,103499,Male,Loyal Customer,21,Business travel,Business,1047,3,3,3,3,4,5,4,4,4,2,4,3,4,4,2,6.0,satisfied +11269,31591,Male,Loyal Customer,45,Business travel,Business,602,2,3,2,2,2,3,2,2,2,2,2,2,2,2,1,0.0,neutral or dissatisfied +11270,96835,Male,Loyal Customer,36,Business travel,Business,3517,1,2,1,2,1,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +11271,16479,Female,Loyal Customer,34,Personal Travel,Eco Plus,529,2,4,2,2,2,3,3,3,5,4,5,3,5,3,108,137.0,neutral or dissatisfied +11272,39892,Female,Loyal Customer,40,Personal Travel,Eco,221,3,0,3,5,1,3,1,1,5,3,4,3,4,1,14,15.0,neutral or dissatisfied +11273,121305,Male,Loyal Customer,43,Business travel,Business,3061,4,4,4,4,5,5,4,3,3,2,3,5,3,4,0,0.0,satisfied +11274,53354,Male,Loyal Customer,20,Business travel,Business,1452,3,5,5,5,3,3,3,3,3,4,2,3,2,3,12,26.0,neutral or dissatisfied +11275,93645,Male,Loyal Customer,45,Business travel,Business,3750,5,3,5,5,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +11276,98330,Female,Loyal Customer,56,Business travel,Business,1237,3,3,5,3,5,4,4,4,4,4,4,5,4,4,19,17.0,satisfied +11277,17338,Male,Loyal Customer,49,Business travel,Business,1707,5,5,5,5,2,3,4,4,4,4,4,2,4,5,5,0.0,satisfied +11278,91007,Male,Loyal Customer,62,Personal Travel,Eco,444,2,4,2,3,1,2,1,1,3,3,5,5,5,1,0,1.0,neutral or dissatisfied +11279,118562,Male,Loyal Customer,33,Business travel,Business,3596,1,1,1,1,3,3,3,3,5,3,5,4,4,3,0,0.0,satisfied +11280,72985,Male,disloyal Customer,24,Business travel,Eco,944,1,1,1,4,4,1,4,4,1,3,4,3,4,4,0,0.0,neutral or dissatisfied +11281,29888,Male,Loyal Customer,39,Business travel,Business,1759,3,3,3,3,1,3,2,5,5,5,3,4,5,3,0,0.0,satisfied +11282,72850,Male,Loyal Customer,67,Personal Travel,Eco,1168,1,5,0,1,5,0,5,5,3,5,4,4,5,5,64,60.0,neutral or dissatisfied +11283,119088,Male,Loyal Customer,46,Business travel,Business,1107,4,4,4,4,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +11284,68382,Female,Loyal Customer,21,Business travel,Business,1045,1,1,1,1,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +11285,15375,Female,Loyal Customer,56,Business travel,Eco,331,4,3,2,2,4,1,1,4,4,4,4,3,4,5,38,27.0,satisfied +11286,43055,Male,Loyal Customer,36,Business travel,Business,192,5,5,5,5,4,1,3,5,5,5,3,2,5,5,0,0.0,satisfied +11287,104886,Female,Loyal Customer,70,Personal Travel,Eco,327,1,0,1,2,5,5,5,3,3,1,3,4,3,4,21,12.0,neutral or dissatisfied +11288,46537,Male,Loyal Customer,62,Business travel,Eco,251,1,2,4,2,1,1,1,1,1,4,3,3,4,1,0,0.0,neutral or dissatisfied +11289,72539,Male,Loyal Customer,50,Business travel,Business,1017,3,3,3,3,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +11290,49045,Male,Loyal Customer,64,Business travel,Eco,86,3,4,4,4,4,3,4,4,4,5,5,2,3,4,0,0.0,satisfied +11291,71677,Female,Loyal Customer,40,Personal Travel,Eco,1197,4,2,4,3,4,4,4,4,1,1,2,3,4,4,0,1.0,neutral or dissatisfied +11292,74707,Female,Loyal Customer,69,Personal Travel,Eco,1171,1,3,1,2,1,4,1,1,1,1,1,3,1,1,42,34.0,neutral or dissatisfied +11293,35118,Male,Loyal Customer,30,Business travel,Eco,972,3,5,5,5,3,4,3,3,4,1,3,4,2,3,0,0.0,satisfied +11294,33545,Male,Loyal Customer,29,Personal Travel,Business,399,2,4,2,5,2,2,2,2,4,5,4,3,4,2,39,48.0,neutral or dissatisfied +11295,65037,Female,Loyal Customer,58,Personal Travel,Eco,190,3,5,3,4,5,4,4,4,4,3,5,5,4,3,0,1.0,neutral or dissatisfied +11296,80581,Male,Loyal Customer,64,Personal Travel,Eco,1747,5,4,5,1,1,5,1,1,5,2,5,5,4,1,0,0.0,satisfied +11297,89728,Male,Loyal Customer,43,Personal Travel,Eco,950,1,3,1,4,4,1,4,4,5,2,4,5,1,4,0,0.0,neutral or dissatisfied +11298,37210,Female,Loyal Customer,64,Personal Travel,Eco,680,5,5,5,1,4,4,4,1,1,5,1,4,1,5,44,48.0,satisfied +11299,18617,Male,disloyal Customer,39,Personal Travel,Eco,192,1,5,1,3,2,1,3,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +11300,27795,Female,Loyal Customer,51,Business travel,Eco,1448,4,2,2,2,1,5,3,4,4,4,4,3,4,3,0,0.0,satisfied +11301,106302,Male,Loyal Customer,50,Business travel,Business,998,5,5,5,5,5,5,5,4,4,4,4,5,4,4,9,5.0,satisfied +11302,17035,Female,Loyal Customer,33,Personal Travel,Eco Plus,781,3,3,3,4,3,3,3,3,5,1,1,1,5,3,0,0.0,neutral or dissatisfied +11303,80594,Female,Loyal Customer,61,Business travel,Business,1747,2,2,4,2,3,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +11304,55566,Male,Loyal Customer,69,Business travel,Business,395,2,2,2,2,2,3,2,2,2,2,2,4,2,3,0,2.0,satisfied +11305,122755,Female,Loyal Customer,68,Personal Travel,Eco,651,3,0,3,1,2,5,5,4,4,3,4,5,4,3,21,3.0,neutral or dissatisfied +11306,40833,Female,disloyal Customer,26,Business travel,Eco,590,3,1,4,3,2,4,1,2,1,4,3,1,4,2,115,116.0,neutral or dissatisfied +11307,91486,Female,Loyal Customer,42,Personal Travel,Eco,859,2,4,2,4,3,4,5,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +11308,33565,Male,Loyal Customer,36,Business travel,Eco,399,3,3,3,3,3,3,3,3,2,5,3,4,4,3,55,83.0,neutral or dissatisfied +11309,115202,Female,Loyal Customer,45,Business travel,Business,371,4,4,4,4,2,4,5,5,5,5,5,4,5,5,10,7.0,satisfied +11310,74778,Female,Loyal Customer,45,Business travel,Business,3398,4,4,4,4,4,4,4,5,5,5,5,3,5,5,1,0.0,satisfied +11311,29049,Male,Loyal Customer,51,Personal Travel,Eco,605,0,4,0,2,4,4,4,4,4,2,5,5,5,4,0,0.0,satisfied +11312,42396,Male,Loyal Customer,30,Business travel,Eco Plus,838,4,5,5,5,4,4,4,4,2,2,4,2,1,4,0,0.0,satisfied +11313,121148,Female,Loyal Customer,57,Business travel,Business,2402,5,5,2,5,2,4,4,4,4,4,4,4,4,5,7,0.0,satisfied +11314,60566,Female,Loyal Customer,20,Personal Travel,Eco Plus,862,2,1,2,2,1,2,1,1,2,1,1,1,1,1,2,0.0,neutral or dissatisfied +11315,90861,Female,disloyal Customer,44,Business travel,Business,271,3,3,3,3,5,3,5,5,4,5,4,5,5,5,0,0.0,satisfied +11316,118298,Female,Loyal Customer,30,Business travel,Business,602,3,3,3,3,5,5,5,5,3,3,4,4,4,5,0,0.0,satisfied +11317,67110,Female,Loyal Customer,45,Business travel,Eco,1121,2,3,3,3,2,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +11318,53879,Male,Loyal Customer,35,Personal Travel,Eco,140,4,1,0,3,2,0,2,2,1,4,4,2,4,2,0,0.0,neutral or dissatisfied +11319,88476,Female,Loyal Customer,52,Business travel,Business,145,3,3,3,3,5,3,4,3,3,3,3,2,3,4,0,3.0,neutral or dissatisfied +11320,48192,Male,Loyal Customer,51,Business travel,Eco,259,2,1,2,1,2,2,2,2,5,3,1,5,1,2,0,0.0,satisfied +11321,20288,Female,Loyal Customer,67,Personal Travel,Eco,235,3,5,3,5,4,5,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +11322,85802,Male,Loyal Customer,46,Business travel,Eco,266,4,2,2,2,3,4,3,3,1,4,3,2,3,3,0,0.0,neutral or dissatisfied +11323,13892,Female,Loyal Customer,26,Business travel,Eco Plus,667,5,1,1,1,5,5,3,5,4,2,4,3,4,5,5,0.0,satisfied +11324,78664,Female,Loyal Customer,29,Business travel,Business,2589,3,3,3,3,5,5,5,5,4,2,5,5,5,5,0,0.0,satisfied +11325,69131,Male,Loyal Customer,60,Business travel,Business,1598,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +11326,25049,Female,Loyal Customer,46,Business travel,Eco,594,3,5,5,5,2,1,2,3,3,3,3,4,3,3,5,0.0,satisfied +11327,99521,Male,Loyal Customer,67,Business travel,Eco Plus,307,2,2,2,2,1,2,1,1,3,2,4,1,4,1,0,0.0,neutral or dissatisfied +11328,42853,Male,Loyal Customer,33,Personal Travel,Eco,328,4,2,4,3,3,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +11329,74163,Male,Loyal Customer,46,Personal Travel,Eco,641,4,4,4,3,1,4,1,1,3,5,5,5,5,1,0,0.0,satisfied +11330,4237,Male,Loyal Customer,33,Business travel,Business,1020,3,5,5,5,3,3,3,3,4,2,4,2,4,3,0,0.0,neutral or dissatisfied +11331,101710,Female,disloyal Customer,26,Business travel,Eco,1624,2,2,2,4,4,2,4,4,2,5,4,4,4,4,4,6.0,neutral or dissatisfied +11332,898,Female,disloyal Customer,40,Business travel,Business,247,2,3,3,4,4,3,4,4,2,1,4,3,4,4,19,15.0,neutral or dissatisfied +11333,17690,Female,Loyal Customer,18,Personal Travel,Eco,349,4,4,5,4,5,5,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +11334,72913,Male,disloyal Customer,20,Business travel,Eco,1096,2,2,2,1,5,2,5,5,3,3,4,4,4,5,1,0.0,neutral or dissatisfied +11335,95173,Female,Loyal Customer,61,Personal Travel,Eco,441,3,5,3,2,4,1,3,4,4,3,4,4,4,4,0,2.0,neutral or dissatisfied +11336,51751,Female,Loyal Customer,64,Personal Travel,Eco,651,1,1,1,4,4,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +11337,90066,Female,disloyal Customer,25,Business travel,Business,983,3,0,3,2,4,3,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +11338,25486,Male,Loyal Customer,56,Business travel,Eco,547,4,3,4,4,4,4,4,4,4,3,3,4,1,4,67,53.0,satisfied +11339,83215,Female,disloyal Customer,26,Business travel,Business,1979,2,2,2,3,2,2,2,2,3,3,4,4,5,2,59,44.0,neutral or dissatisfied +11340,46593,Male,Loyal Customer,30,Business travel,Business,125,1,5,5,5,3,3,1,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +11341,106690,Female,Loyal Customer,33,Business travel,Business,516,3,3,3,3,5,4,5,5,5,5,5,5,5,3,39,24.0,satisfied +11342,69239,Male,Loyal Customer,28,Business travel,Business,2538,3,2,2,2,3,3,3,2,5,4,4,3,3,3,219,213.0,neutral or dissatisfied +11343,24133,Male,Loyal Customer,16,Personal Travel,Eco,510,4,4,4,2,3,4,3,3,3,3,5,5,5,3,55,40.0,neutral or dissatisfied +11344,122639,Female,disloyal Customer,25,Business travel,Eco Plus,728,2,2,2,3,1,2,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +11345,84480,Female,Loyal Customer,41,Business travel,Business,2677,1,1,1,1,5,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +11346,87146,Female,Loyal Customer,60,Personal Travel,Eco Plus,640,3,1,3,2,1,2,2,2,2,3,2,3,2,2,2,0.0,neutral or dissatisfied +11347,119332,Female,Loyal Customer,47,Personal Travel,Eco,214,2,4,2,1,4,1,4,3,3,2,3,5,3,2,0,13.0,neutral or dissatisfied +11348,129455,Female,Loyal Customer,57,Business travel,Business,1528,1,1,1,1,3,4,5,2,2,2,2,4,2,3,1,1.0,satisfied +11349,98569,Female,Loyal Customer,53,Business travel,Business,951,4,4,3,4,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +11350,31849,Female,disloyal Customer,66,Business travel,Eco,1371,1,1,1,3,4,1,4,4,2,5,4,4,4,4,4,0.0,neutral or dissatisfied +11351,50509,Male,Loyal Customer,43,Personal Travel,Eco,238,3,2,3,3,2,3,2,2,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +11352,36834,Male,Loyal Customer,57,Business travel,Business,2640,3,1,4,4,3,3,3,3,3,3,3,4,3,3,0,14.0,neutral or dissatisfied +11353,100291,Female,Loyal Customer,44,Business travel,Business,1073,3,3,2,3,2,4,4,4,4,4,4,4,4,4,107,111.0,satisfied +11354,15444,Female,Loyal Customer,26,Business travel,Business,2561,2,5,5,5,2,2,2,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +11355,80888,Male,Loyal Customer,79,Business travel,Eco Plus,484,3,2,3,2,3,3,3,3,1,3,4,4,4,3,0,0.0,neutral or dissatisfied +11356,11763,Female,Loyal Customer,31,Business travel,Eco,429,0,0,0,3,2,3,2,2,3,4,4,1,3,2,5,0.0,satisfied +11357,109360,Female,disloyal Customer,41,Business travel,Business,1189,5,5,5,4,5,1,1,5,4,4,5,1,5,1,150,149.0,satisfied +11358,84818,Female,Loyal Customer,40,Business travel,Business,547,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +11359,104027,Male,Loyal Customer,50,Business travel,Business,1262,4,4,4,4,2,5,5,5,5,4,5,5,5,4,25,52.0,satisfied +11360,107475,Female,Loyal Customer,50,Business travel,Business,711,2,2,2,2,5,5,5,4,4,4,4,5,4,4,27,44.0,satisfied +11361,112221,Female,Loyal Customer,48,Business travel,Business,1199,4,5,5,5,2,4,4,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +11362,45301,Female,Loyal Customer,43,Business travel,Business,222,3,3,3,3,1,3,1,5,5,5,5,1,5,5,0,0.0,satisfied +11363,37050,Female,Loyal Customer,35,Personal Travel,Eco Plus,1105,5,3,5,3,3,3,3,3,4,4,4,3,3,3,0,0.0,satisfied +11364,124630,Male,Loyal Customer,18,Personal Travel,Eco,1671,2,3,2,4,2,2,2,2,2,4,4,3,3,2,0,10.0,neutral or dissatisfied +11365,55325,Male,Loyal Customer,25,Business travel,Business,3686,3,3,3,3,3,3,3,3,2,2,4,2,3,3,10,52.0,neutral or dissatisfied +11366,84699,Female,Loyal Customer,51,Business travel,Business,547,4,4,4,4,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +11367,116534,Male,Loyal Customer,29,Personal Travel,Eco,417,1,5,2,3,1,2,1,1,4,2,3,5,1,1,0,0.0,neutral or dissatisfied +11368,356,Male,Loyal Customer,50,Business travel,Business,102,4,4,4,4,2,5,4,4,4,4,5,4,4,5,23,24.0,satisfied +11369,82222,Male,Loyal Customer,60,Business travel,Business,405,2,4,4,4,1,4,3,2,2,2,2,3,2,4,0,13.0,neutral or dissatisfied +11370,3279,Male,Loyal Customer,19,Personal Travel,Eco,425,2,0,2,2,5,2,5,5,5,5,5,4,4,5,2,13.0,neutral or dissatisfied +11371,86510,Male,Loyal Customer,21,Personal Travel,Eco,762,3,2,3,3,4,3,4,4,2,1,4,3,3,4,22,23.0,neutral or dissatisfied +11372,79627,Male,disloyal Customer,26,Business travel,Eco,760,2,2,2,3,1,2,1,1,3,4,4,4,3,1,15,0.0,neutral or dissatisfied +11373,12315,Male,Loyal Customer,53,Business travel,Business,253,2,2,2,2,5,1,1,4,4,4,4,4,4,4,5,4.0,satisfied +11374,55299,Male,disloyal Customer,18,Business travel,Eco,1381,4,4,4,4,4,4,4,4,4,4,1,3,1,4,0,2.0,satisfied +11375,32745,Male,disloyal Customer,41,Business travel,Eco,101,3,5,3,3,3,3,3,3,4,2,4,5,3,3,0,0.0,neutral or dissatisfied +11376,49536,Male,Loyal Customer,57,Business travel,Eco,421,5,4,4,4,5,5,5,5,2,2,1,1,5,5,0,0.0,satisfied +11377,4609,Female,disloyal Customer,20,Business travel,Eco,719,5,5,5,2,2,5,2,2,4,2,5,4,4,2,4,0.0,satisfied +11378,34953,Male,Loyal Customer,45,Personal Travel,Eco,187,2,5,0,4,5,0,5,5,3,2,4,3,4,5,0,0.0,neutral or dissatisfied +11379,110355,Female,Loyal Customer,57,Business travel,Business,2314,1,1,1,1,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +11380,111432,Male,disloyal Customer,11,Business travel,Eco,896,1,1,1,4,5,1,5,5,3,3,3,1,3,5,17,15.0,neutral or dissatisfied +11381,35664,Male,Loyal Customer,57,Business travel,Business,2569,3,3,3,3,4,4,4,1,4,4,3,4,4,4,9,18.0,satisfied +11382,129247,Female,Loyal Customer,33,Personal Travel,Eco,1464,1,4,1,4,1,3,3,3,5,3,5,3,4,3,177,152.0,neutral or dissatisfied +11383,86641,Male,Loyal Customer,26,Business travel,Business,3581,4,4,4,4,4,5,4,4,3,3,5,5,5,4,0,0.0,satisfied +11384,24558,Male,Loyal Customer,28,Business travel,Business,3522,3,2,2,2,3,3,3,3,4,5,3,4,3,3,6,0.0,neutral or dissatisfied +11385,21706,Male,Loyal Customer,29,Personal Travel,Eco,746,3,5,3,3,5,3,5,5,1,4,2,2,4,5,0,0.0,neutral or dissatisfied +11386,70007,Male,Loyal Customer,33,Personal Travel,Eco,236,1,4,1,1,3,1,3,3,5,3,4,4,5,3,0,11.0,neutral or dissatisfied +11387,79719,Female,Loyal Customer,38,Personal Travel,Eco,762,2,5,2,2,3,2,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +11388,38352,Female,Loyal Customer,41,Business travel,Business,1180,2,2,2,2,1,3,1,5,5,5,5,1,5,4,0,0.0,satisfied +11389,12036,Male,Loyal Customer,68,Business travel,Eco,351,4,2,2,2,4,4,4,4,1,1,3,2,3,4,0,0.0,satisfied +11390,30483,Male,Loyal Customer,51,Business travel,Eco Plus,1201,2,2,2,2,2,2,2,2,1,2,2,5,3,2,0,0.0,satisfied +11391,50478,Male,disloyal Customer,37,Business travel,Eco,326,3,2,3,4,2,3,2,2,4,4,4,1,4,2,4,6.0,neutral or dissatisfied +11392,107918,Male,disloyal Customer,26,Business travel,Business,611,5,5,5,4,2,5,2,2,4,3,5,4,5,2,23,19.0,satisfied +11393,13257,Male,Loyal Customer,48,Business travel,Eco,657,3,5,5,5,3,3,3,3,3,2,4,2,3,3,0,0.0,neutral or dissatisfied +11394,29513,Male,Loyal Customer,15,Business travel,Eco Plus,1107,0,3,0,1,4,0,4,4,1,4,5,2,3,4,0,0.0,satisfied +11395,97397,Female,Loyal Customer,65,Personal Travel,Eco Plus,872,4,0,3,1,4,5,5,2,2,3,5,3,2,4,5,2.0,neutral or dissatisfied +11396,83958,Female,Loyal Customer,36,Business travel,Business,321,0,0,0,3,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +11397,75803,Male,Loyal Customer,48,Business travel,Business,868,1,1,1,1,4,5,5,5,5,5,5,5,5,3,24,8.0,satisfied +11398,43560,Female,disloyal Customer,25,Business travel,Eco,637,3,4,3,4,4,3,4,4,1,5,5,1,1,4,1,0.0,neutral or dissatisfied +11399,95420,Male,disloyal Customer,20,Business travel,Eco,323,2,0,1,1,5,1,5,5,3,2,4,4,4,5,29,19.0,neutral or dissatisfied +11400,125567,Male,Loyal Customer,57,Personal Travel,Eco,226,2,4,2,4,3,2,5,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +11401,61088,Female,Loyal Customer,64,Personal Travel,Eco,1546,3,5,3,2,3,5,4,4,4,3,1,3,4,3,0,0.0,neutral or dissatisfied +11402,95933,Female,Loyal Customer,35,Personal Travel,Eco,1411,2,3,2,3,3,2,5,3,2,1,3,1,3,3,43,29.0,neutral or dissatisfied +11403,92327,Male,disloyal Customer,23,Business travel,Eco,1075,5,5,5,3,5,5,5,3,2,4,5,5,5,5,0,0.0,satisfied +11404,67424,Female,disloyal Customer,24,Business travel,Eco,721,1,1,1,3,5,1,5,5,4,3,5,3,4,5,12,2.0,neutral or dissatisfied +11405,120325,Male,Loyal Customer,53,Personal Travel,Eco,268,3,0,3,4,5,3,5,5,4,2,4,3,5,5,90,89.0,neutral or dissatisfied +11406,73086,Male,Loyal Customer,30,Business travel,Business,1085,2,1,1,1,2,2,2,2,1,1,4,1,3,2,0,0.0,neutral or dissatisfied +11407,11450,Female,Loyal Customer,34,Business travel,Business,216,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +11408,120181,Male,Loyal Customer,52,Business travel,Business,1927,3,3,3,3,3,4,4,2,2,2,2,4,2,3,75,75.0,satisfied +11409,88276,Female,Loyal Customer,33,Business travel,Business,270,2,3,3,3,3,3,4,2,2,1,2,3,2,4,49,38.0,neutral or dissatisfied +11410,82352,Male,Loyal Customer,37,Business travel,Business,453,1,5,3,3,5,3,4,1,1,1,1,1,1,4,9,0.0,neutral or dissatisfied +11411,88223,Male,Loyal Customer,37,Business travel,Eco,406,4,5,5,5,4,4,4,4,1,2,3,1,3,4,17,37.0,neutral or dissatisfied +11412,32325,Male,disloyal Customer,39,Business travel,Eco,101,3,0,3,3,3,3,3,3,5,5,2,5,2,3,10,9.0,neutral or dissatisfied +11413,59233,Male,disloyal Customer,27,Business travel,Eco,649,2,3,2,3,5,2,5,5,2,3,2,1,3,5,0,19.0,neutral or dissatisfied +11414,71559,Female,Loyal Customer,22,Business travel,Business,1197,5,1,1,1,5,4,5,5,2,5,4,2,3,5,0,0.0,neutral or dissatisfied +11415,51158,Male,Loyal Customer,48,Personal Travel,Eco,250,4,4,4,3,1,4,1,1,4,2,5,5,5,1,0,23.0,neutral or dissatisfied +11416,104539,Male,Loyal Customer,26,Personal Travel,Eco,1256,4,4,4,2,5,4,5,5,5,2,5,3,4,5,2,0.0,satisfied +11417,19751,Female,Loyal Customer,42,Business travel,Business,2683,1,1,5,1,2,2,5,4,4,5,4,2,4,2,0,0.0,satisfied +11418,28882,Male,Loyal Customer,38,Business travel,Business,3883,5,5,5,5,4,1,4,5,5,5,5,3,5,3,0,0.0,satisfied +11419,91928,Female,Loyal Customer,60,Business travel,Business,2586,4,4,4,4,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11420,99419,Female,disloyal Customer,20,Business travel,Eco,337,1,3,1,2,4,1,4,4,3,4,1,5,4,4,0,0.0,neutral or dissatisfied +11421,51991,Female,Loyal Customer,64,Personal Travel,Eco Plus,347,4,3,4,4,3,2,3,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +11422,86523,Male,Loyal Customer,37,Personal Travel,Eco,762,5,5,5,5,5,5,5,5,5,3,4,3,4,5,0,0.0,satisfied +11423,70393,Female,Loyal Customer,22,Business travel,Business,1562,1,3,3,3,1,1,1,1,3,4,3,2,4,1,4,2.0,neutral or dissatisfied +11424,53563,Male,Loyal Customer,26,Business travel,Business,3819,1,1,1,1,4,4,4,4,1,1,4,3,4,4,0,0.0,satisfied +11425,52268,Female,Loyal Customer,51,Business travel,Eco,451,3,2,2,2,4,3,2,3,3,3,3,1,3,3,8,1.0,neutral or dissatisfied +11426,127371,Female,disloyal Customer,24,Business travel,Business,1009,0,5,0,1,3,0,4,3,4,2,5,4,5,3,34,32.0,satisfied +11427,91866,Male,Loyal Customer,45,Business travel,Business,1995,2,2,2,2,3,4,5,4,4,4,4,4,4,3,4,0.0,satisfied +11428,82992,Female,Loyal Customer,55,Business travel,Business,1861,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,3.0,satisfied +11429,92783,Male,Loyal Customer,48,Personal Travel,Eco,1671,4,5,4,4,2,4,2,2,1,1,2,3,4,2,0,0.0,neutral or dissatisfied +11430,67787,Male,Loyal Customer,28,Business travel,Business,1205,4,4,4,4,5,5,5,5,4,5,4,4,4,5,0,0.0,satisfied +11431,82897,Male,Loyal Customer,64,Personal Travel,Eco,594,3,4,3,2,4,3,4,4,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +11432,36922,Female,Loyal Customer,60,Personal Travel,Eco,740,2,2,2,2,4,1,1,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +11433,120874,Male,disloyal Customer,36,Business travel,Business,861,3,3,3,1,3,3,3,3,5,4,5,3,4,3,14,0.0,neutral or dissatisfied +11434,24652,Female,Loyal Customer,38,Business travel,Business,1760,3,3,5,3,2,4,2,3,3,4,3,2,3,1,0,8.0,satisfied +11435,72101,Male,Loyal Customer,63,Personal Travel,Eco,2556,2,3,2,1,5,2,5,5,1,1,5,5,4,5,0,13.0,neutral or dissatisfied +11436,122194,Female,disloyal Customer,34,Business travel,Business,544,2,2,2,1,4,2,4,4,3,3,5,4,5,4,0,1.0,neutral or dissatisfied +11437,77109,Male,disloyal Customer,35,Business travel,Business,1481,2,2,2,3,3,2,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +11438,111465,Female,Loyal Customer,47,Personal Travel,Eco,836,2,5,1,3,1,3,3,5,1,3,3,3,1,3,204,205.0,neutral or dissatisfied +11439,89072,Male,Loyal Customer,27,Business travel,Business,1947,4,4,4,4,2,2,2,2,4,4,4,5,4,2,0,0.0,satisfied +11440,100340,Female,disloyal Customer,36,Business travel,Eco,634,4,4,3,3,5,3,5,5,4,2,3,1,4,5,108,120.0,neutral or dissatisfied +11441,43678,Female,Loyal Customer,18,Personal Travel,Eco Plus,695,5,1,5,4,4,5,3,4,2,2,3,1,3,4,0,0.0,satisfied +11442,82493,Female,disloyal Customer,34,Business travel,Eco,488,2,4,2,4,4,2,4,4,1,2,4,3,4,4,55,60.0,neutral or dissatisfied +11443,120811,Female,Loyal Customer,51,Business travel,Business,2852,3,3,3,3,1,4,4,4,4,4,4,3,4,2,0,1.0,satisfied +11444,43985,Male,disloyal Customer,22,Business travel,Eco,397,4,4,4,4,3,4,1,3,3,3,2,4,3,3,62,66.0,neutral or dissatisfied +11445,22808,Male,Loyal Customer,41,Business travel,Business,134,2,2,5,2,3,4,3,4,4,4,3,1,4,3,67,51.0,satisfied +11446,117228,Female,Loyal Customer,11,Personal Travel,Eco,621,1,4,1,3,4,1,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +11447,88960,Male,Loyal Customer,30,Business travel,Business,3327,2,5,5,5,2,2,2,2,2,4,4,3,3,2,3,0.0,neutral or dissatisfied +11448,127076,Male,Loyal Customer,47,Business travel,Business,338,5,5,5,5,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +11449,24753,Male,Loyal Customer,51,Business travel,Business,2148,5,5,5,5,3,5,2,2,2,2,2,1,2,2,6,28.0,satisfied +11450,45193,Male,disloyal Customer,26,Business travel,Eco,1037,4,4,4,4,4,4,4,4,4,5,3,4,3,4,0,2.0,neutral or dissatisfied +11451,23637,Female,Loyal Customer,22,Personal Travel,Eco,793,3,4,3,3,2,3,2,2,4,3,4,3,5,2,102,106.0,neutral or dissatisfied +11452,64903,Male,Loyal Customer,35,Business travel,Eco,551,3,2,2,2,3,3,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +11453,124614,Female,Loyal Customer,42,Business travel,Business,1671,3,3,4,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +11454,60247,Female,Loyal Customer,32,Personal Travel,Eco,1506,3,5,3,4,2,3,2,2,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +11455,6942,Male,Loyal Customer,35,Business travel,Business,2383,4,4,4,4,2,5,4,4,4,4,4,3,4,4,24,13.0,satisfied +11456,113851,Male,Loyal Customer,32,Business travel,Business,1592,2,1,1,1,2,2,2,2,3,4,4,4,4,2,4,0.0,neutral or dissatisfied +11457,99298,Male,Loyal Customer,60,Business travel,Business,3852,4,5,5,5,5,4,3,4,4,3,4,1,4,2,0,0.0,neutral or dissatisfied +11458,60457,Female,Loyal Customer,38,Business travel,Business,2978,4,4,4,4,3,4,5,5,5,5,5,4,5,5,5,0.0,satisfied +11459,85280,Female,Loyal Customer,17,Personal Travel,Eco,689,2,4,2,5,1,2,1,1,3,3,4,5,5,1,0,3.0,neutral or dissatisfied +11460,101480,Male,Loyal Customer,47,Business travel,Business,3486,3,3,3,3,5,4,5,4,4,4,4,4,4,4,2,0.0,satisfied +11461,92418,Male,Loyal Customer,44,Business travel,Business,2116,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +11462,71847,Male,disloyal Customer,31,Business travel,Business,1846,3,3,3,4,5,3,5,5,3,5,5,5,4,5,5,0.0,neutral or dissatisfied +11463,76017,Female,Loyal Customer,47,Business travel,Business,237,4,4,4,4,3,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +11464,58824,Male,Loyal Customer,56,Personal Travel,Eco,1012,2,5,2,1,3,2,3,3,1,3,4,3,4,3,0,0.0,neutral or dissatisfied +11465,26872,Male,Loyal Customer,43,Business travel,Business,2329,5,5,4,5,3,4,3,5,5,5,5,2,5,5,5,0.0,satisfied +11466,51833,Female,disloyal Customer,61,Business travel,Eco Plus,370,1,0,0,2,1,1,1,1,3,2,2,3,5,1,0,0.0,neutral or dissatisfied +11467,110819,Male,Loyal Customer,28,Personal Travel,Eco,997,1,5,1,5,3,1,3,3,5,5,5,5,5,3,3,4.0,neutral or dissatisfied +11468,51653,Female,Loyal Customer,31,Business travel,Eco,370,1,5,5,5,1,1,1,1,2,4,4,2,4,1,7,0.0,neutral or dissatisfied +11469,12327,Female,disloyal Customer,20,Business travel,Eco,190,4,4,4,1,4,4,4,4,4,3,2,3,2,4,2,0.0,satisfied +11470,7977,Male,Loyal Customer,49,Business travel,Business,3285,2,2,5,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +11471,128374,Female,Loyal Customer,55,Business travel,Business,304,0,0,0,4,4,4,5,1,1,1,1,4,1,5,0,0.0,satisfied +11472,14199,Male,Loyal Customer,18,Business travel,Eco,692,3,4,4,4,3,3,2,3,3,5,4,3,3,3,9,22.0,neutral or dissatisfied +11473,36816,Female,Loyal Customer,48,Personal Travel,Eco,2300,2,5,2,3,2,3,3,4,4,5,5,3,3,3,0,0.0,neutral or dissatisfied +11474,87489,Male,Loyal Customer,62,Business travel,Business,2878,2,2,2,2,2,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +11475,98046,Male,Loyal Customer,44,Business travel,Business,1751,3,3,3,3,5,3,5,5,5,5,5,4,5,3,0,0.0,satisfied +11476,53155,Female,Loyal Customer,51,Business travel,Business,3738,1,1,1,1,3,4,4,4,4,4,4,5,4,4,55,39.0,satisfied +11477,85438,Male,Loyal Customer,53,Business travel,Business,3005,2,2,2,2,3,4,5,5,5,4,4,3,5,3,0,0.0,satisfied +11478,54662,Female,disloyal Customer,37,Business travel,Eco,965,2,2,2,2,5,2,5,5,3,5,2,1,2,5,1,0.0,neutral or dissatisfied +11479,53822,Female,Loyal Customer,22,Business travel,Business,2971,3,3,3,3,4,4,3,4,4,4,3,1,5,4,0,0.0,satisfied +11480,99366,Male,Loyal Customer,36,Personal Travel,Eco,409,2,2,2,3,3,2,3,3,4,3,3,2,4,3,0,0.0,neutral or dissatisfied +11481,16359,Female,Loyal Customer,56,Business travel,Eco,319,4,2,2,2,2,3,3,4,4,4,4,5,4,2,0,0.0,satisfied +11482,103114,Male,Loyal Customer,11,Personal Travel,Eco,460,3,3,3,1,1,3,1,1,2,4,4,5,4,1,0,0.0,neutral or dissatisfied +11483,108188,Male,Loyal Customer,57,Business travel,Business,2348,3,3,3,3,2,5,5,5,5,5,5,4,5,4,10,17.0,satisfied +11484,22679,Female,Loyal Customer,53,Business travel,Business,2327,4,4,4,4,3,1,5,4,4,4,4,3,4,1,0,0.0,satisfied +11485,44035,Female,disloyal Customer,40,Business travel,Business,237,1,1,1,4,5,1,5,5,4,3,3,3,4,5,0,0.0,neutral or dissatisfied +11486,11956,Male,Loyal Customer,51,Business travel,Business,781,2,2,2,2,5,5,5,2,2,2,2,3,2,5,70,70.0,satisfied +11487,108724,Male,Loyal Customer,7,Business travel,Business,1966,4,3,3,3,4,3,4,4,3,3,3,3,3,4,58,65.0,neutral or dissatisfied +11488,9269,Female,Loyal Customer,39,Business travel,Business,2264,5,5,4,5,5,4,4,5,5,5,5,4,5,3,30,16.0,satisfied +11489,43238,Female,Loyal Customer,42,Business travel,Business,2873,5,5,5,5,3,4,4,4,4,5,4,4,4,3,0,0.0,satisfied +11490,17610,Male,Loyal Customer,11,Personal Travel,Eco,196,2,5,2,4,2,2,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +11491,95214,Male,Loyal Customer,31,Personal Travel,Eco,441,4,4,4,5,1,4,4,1,5,5,4,1,1,1,0,6.0,neutral or dissatisfied +11492,51739,Female,Loyal Customer,38,Personal Travel,Eco,598,2,0,2,3,4,2,4,4,3,5,4,3,4,4,0,0.0,neutral or dissatisfied +11493,53921,Male,disloyal Customer,57,Business travel,Eco Plus,191,2,2,2,4,4,2,4,4,3,5,4,2,2,4,14,14.0,neutral or dissatisfied +11494,69149,Female,Loyal Customer,61,Personal Travel,Eco,2248,3,1,3,3,2,4,3,4,4,3,4,2,4,4,2,0.0,neutral or dissatisfied +11495,103691,Female,disloyal Customer,15,Business travel,Eco,466,0,3,0,2,5,0,5,5,1,3,4,3,1,5,0,0.0,satisfied +11496,16276,Male,Loyal Customer,59,Personal Travel,Eco,946,4,1,4,3,5,4,5,5,1,5,4,1,3,5,80,81.0,neutral or dissatisfied +11497,119916,Male,Loyal Customer,36,Business travel,Business,2137,3,5,5,5,2,2,3,3,3,3,3,2,3,2,14,0.0,neutral or dissatisfied +11498,4542,Male,Loyal Customer,32,Business travel,Business,719,4,4,4,4,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +11499,93773,Female,Loyal Customer,43,Business travel,Business,1865,2,2,2,2,5,5,4,4,4,4,4,3,4,4,7,0.0,satisfied +11500,37883,Male,Loyal Customer,14,Business travel,Business,2572,3,1,1,1,3,3,3,3,4,4,3,2,4,3,36,51.0,neutral or dissatisfied +11501,116904,Female,Loyal Customer,43,Business travel,Business,3515,4,4,4,4,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +11502,91323,Female,disloyal Customer,20,Business travel,Eco Plus,270,3,2,3,4,5,3,5,5,2,4,4,4,3,5,0,9.0,neutral or dissatisfied +11503,68629,Female,Loyal Customer,39,Business travel,Business,3978,5,5,5,5,4,5,4,3,3,4,3,5,3,5,0,0.0,satisfied +11504,76143,Female,disloyal Customer,36,Business travel,Business,689,3,3,3,2,2,3,2,2,4,4,4,3,5,2,40,38.0,neutral or dissatisfied +11505,29181,Female,Loyal Customer,60,Business travel,Eco Plus,650,4,5,5,5,4,5,5,4,4,4,4,1,4,5,0,0.0,satisfied +11506,112962,Male,Loyal Customer,28,Personal Travel,Eco,1313,2,5,3,4,4,3,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +11507,14158,Female,Loyal Customer,58,Business travel,Business,620,1,1,1,1,5,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +11508,128801,Male,Loyal Customer,40,Business travel,Business,2586,4,4,4,4,5,5,5,5,2,4,4,5,4,5,0,0.0,satisfied +11509,89122,Male,Loyal Customer,48,Business travel,Eco,1919,1,5,4,5,1,1,1,1,2,2,3,3,3,1,35,21.0,neutral or dissatisfied +11510,51915,Female,Loyal Customer,23,Personal Travel,Eco,507,1,5,1,1,2,1,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +11511,93654,Female,Loyal Customer,15,Business travel,Business,547,3,3,3,3,4,4,4,4,5,2,4,5,4,4,0,26.0,satisfied +11512,34162,Female,disloyal Customer,39,Business travel,Business,1189,3,3,3,3,4,3,4,4,4,1,3,1,3,4,23,18.0,neutral or dissatisfied +11513,88475,Female,Loyal Customer,39,Business travel,Business,442,1,4,4,4,3,4,4,1,1,1,1,3,1,1,18,14.0,neutral or dissatisfied +11514,6377,Male,Loyal Customer,46,Business travel,Eco,296,3,2,2,2,4,3,4,4,3,1,4,3,4,4,4,0.0,neutral or dissatisfied +11515,72515,Female,Loyal Customer,34,Business travel,Business,964,3,5,2,5,1,1,1,3,3,3,3,1,3,1,64,68.0,neutral or dissatisfied +11516,27649,Male,Loyal Customer,52,Personal Travel,Eco Plus,679,3,5,3,2,4,3,2,4,4,5,4,5,4,4,0,7.0,neutral or dissatisfied +11517,12144,Female,Loyal Customer,40,Business travel,Business,1785,5,4,5,5,2,1,2,3,3,4,3,3,3,1,0,19.0,satisfied +11518,120092,Male,Loyal Customer,51,Business travel,Business,683,1,1,1,1,3,5,5,5,5,5,5,5,5,3,3,4.0,satisfied +11519,17109,Female,Loyal Customer,7,Personal Travel,Eco,416,2,2,2,4,1,2,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +11520,18996,Male,Loyal Customer,53,Personal Travel,Eco,451,3,5,5,2,1,5,1,1,3,1,4,3,4,1,8,33.0,neutral or dissatisfied +11521,39826,Female,Loyal Customer,42,Business travel,Business,2988,1,1,1,1,1,4,4,5,5,4,5,1,5,5,0,0.0,satisfied +11522,113682,Female,Loyal Customer,40,Personal Travel,Eco,223,3,4,0,2,4,0,3,4,3,2,5,3,5,4,0,0.0,neutral or dissatisfied +11523,115123,Male,Loyal Customer,28,Business travel,Business,1580,3,1,3,3,5,5,5,5,3,5,4,3,5,5,20,11.0,satisfied +11524,38226,Male,Loyal Customer,22,Business travel,Eco Plus,1197,4,4,4,4,4,4,5,4,4,4,2,1,5,4,0,0.0,satisfied +11525,103450,Male,Loyal Customer,52,Business travel,Business,1739,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +11526,119612,Male,Loyal Customer,56,Personal Travel,Eco,1979,2,1,2,3,5,2,5,5,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +11527,77104,Female,Loyal Customer,42,Business travel,Business,1481,3,3,3,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +11528,67643,Male,Loyal Customer,39,Business travel,Business,3797,3,3,3,3,2,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +11529,1062,Male,Loyal Customer,69,Personal Travel,Eco,164,5,2,5,3,4,5,4,4,1,1,4,1,4,4,0,0.0,satisfied +11530,122728,Male,Loyal Customer,49,Business travel,Business,3649,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +11531,19283,Male,Loyal Customer,48,Business travel,Eco,299,5,3,3,3,5,5,5,5,1,3,1,5,3,5,69,74.0,satisfied +11532,29001,Male,Loyal Customer,50,Business travel,Eco,937,2,1,1,1,2,2,2,2,3,1,4,4,4,2,0,0.0,neutral or dissatisfied +11533,59987,Female,Loyal Customer,45,Personal Travel,Eco,997,2,5,2,4,2,5,5,2,2,2,2,5,2,4,0,0.0,neutral or dissatisfied +11534,11630,Male,Loyal Customer,21,Personal Travel,Eco Plus,657,1,4,2,4,5,2,3,5,5,2,5,2,4,5,31,16.0,neutral or dissatisfied +11535,92591,Female,Loyal Customer,52,Business travel,Business,2218,1,1,1,1,4,4,5,5,5,5,5,5,5,5,116,124.0,satisfied +11536,77616,Female,Loyal Customer,46,Business travel,Business,2297,5,5,5,5,4,5,4,4,4,4,4,4,4,5,0,2.0,satisfied +11537,78041,Male,Loyal Customer,9,Personal Travel,Eco,332,3,4,4,2,1,4,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +11538,71811,Male,Loyal Customer,23,Business travel,Business,1726,3,5,5,5,3,3,3,3,1,5,2,1,3,3,0,2.0,neutral or dissatisfied +11539,112851,Male,Loyal Customer,46,Business travel,Business,1164,3,3,3,3,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +11540,19447,Female,Loyal Customer,56,Business travel,Eco,363,4,2,5,2,5,1,4,4,4,4,4,1,4,4,17,41.0,satisfied +11541,15667,Male,Loyal Customer,15,Personal Travel,Eco,764,3,4,3,3,4,3,4,4,1,3,4,2,4,4,22,11.0,neutral or dissatisfied +11542,118962,Male,disloyal Customer,40,Business travel,Business,570,3,3,3,1,2,3,2,2,4,4,4,5,4,2,4,8.0,neutral or dissatisfied +11543,78953,Female,disloyal Customer,20,Business travel,Eco,356,2,0,1,2,4,1,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +11544,53556,Male,Loyal Customer,53,Business travel,Business,1704,1,1,1,1,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +11545,72689,Male,Loyal Customer,9,Personal Travel,Eco,1119,4,3,4,3,4,4,4,4,2,4,4,4,4,4,0,0.0,neutral or dissatisfied +11546,106963,Male,disloyal Customer,28,Business travel,Business,937,2,1,1,4,5,1,5,5,4,2,4,5,5,5,22,61.0,neutral or dissatisfied +11547,42703,Female,Loyal Customer,16,Personal Travel,Eco,627,2,3,2,4,5,2,5,5,1,5,4,2,4,5,3,24.0,neutral or dissatisfied +11548,113156,Male,Loyal Customer,40,Business travel,Business,628,1,3,3,3,4,3,3,1,1,1,1,1,1,1,8,7.0,neutral or dissatisfied +11549,58551,Male,Loyal Customer,11,Personal Travel,Eco,1514,4,5,5,5,4,5,1,4,4,4,3,3,5,4,1,1.0,neutral or dissatisfied +11550,30177,Male,Loyal Customer,28,Business travel,Eco Plus,261,4,2,2,2,4,4,4,4,4,4,5,4,1,4,0,0.0,satisfied +11551,96521,Male,Loyal Customer,54,Personal Travel,Eco,302,3,1,3,4,3,3,3,3,3,2,4,2,4,3,0,4.0,neutral or dissatisfied +11552,28552,Female,Loyal Customer,25,Personal Travel,Eco,2688,1,4,1,3,5,1,5,5,5,5,4,4,4,5,20,0.0,neutral or dissatisfied +11553,82388,Male,disloyal Customer,27,Business travel,Business,501,0,0,0,4,3,0,3,3,3,5,4,4,5,3,0,0.0,satisfied +11554,66397,Female,Loyal Customer,59,Business travel,Eco,1562,1,4,4,4,4,4,3,1,1,1,1,2,1,1,14,19.0,neutral or dissatisfied +11555,24204,Female,disloyal Customer,37,Business travel,Eco,302,0,0,1,1,5,1,5,5,1,3,5,3,3,5,0,0.0,satisfied +11556,27168,Male,disloyal Customer,37,Business travel,Business,1177,3,3,3,3,3,5,5,4,4,4,4,5,2,5,0,0.0,neutral or dissatisfied +11557,3305,Female,Loyal Customer,36,Personal Travel,Eco Plus,419,1,1,1,4,1,1,1,1,2,3,4,4,4,1,42,57.0,neutral or dissatisfied +11558,22411,Female,disloyal Customer,36,Business travel,Eco,143,2,3,2,1,5,2,5,5,1,3,5,5,5,5,0,0.0,neutral or dissatisfied +11559,102109,Female,Loyal Customer,51,Business travel,Business,3678,4,4,4,4,5,4,4,4,4,4,4,5,4,4,42,31.0,satisfied +11560,48167,Male,disloyal Customer,23,Business travel,Eco,236,1,0,0,3,0,3,3,5,3,5,3,3,1,3,61,148.0,neutral or dissatisfied +11561,116361,Male,Loyal Customer,36,Personal Travel,Eco,446,3,4,3,3,2,3,1,2,5,4,5,3,5,2,23,17.0,neutral or dissatisfied +11562,51865,Male,Loyal Customer,31,Personal Travel,Eco,522,1,1,4,4,2,4,2,2,4,4,3,3,4,2,16,25.0,neutral or dissatisfied +11563,23966,Female,Loyal Customer,49,Business travel,Eco,596,5,2,2,2,4,1,3,5,5,5,5,2,5,2,0,0.0,satisfied +11564,120579,Male,disloyal Customer,29,Business travel,Business,980,2,2,2,3,5,2,5,5,3,2,4,5,4,5,1,0.0,neutral or dissatisfied +11565,78814,Female,Loyal Customer,26,Personal Travel,Eco,447,2,2,2,3,3,2,3,3,3,3,4,1,3,3,0,1.0,neutral or dissatisfied +11566,92118,Female,Loyal Customer,26,Personal Travel,Eco,1532,2,2,2,3,1,2,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +11567,6518,Male,Loyal Customer,27,Business travel,Business,599,3,5,5,5,3,2,3,3,2,2,4,3,4,3,0,0.0,neutral or dissatisfied +11568,102019,Male,Loyal Customer,50,Business travel,Business,1761,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +11569,54437,Male,Loyal Customer,24,Business travel,Eco Plus,305,0,5,0,4,3,0,4,3,5,1,1,3,4,3,0,3.0,satisfied +11570,35965,Female,Loyal Customer,13,Personal Travel,Eco,231,0,5,0,4,2,0,3,2,3,5,3,4,1,2,0,0.0,satisfied +11571,61188,Male,Loyal Customer,33,Business travel,Business,862,4,4,4,4,5,5,5,5,4,3,4,4,5,5,9,13.0,satisfied +11572,90260,Male,Loyal Customer,25,Business travel,Business,757,1,1,1,1,5,5,5,5,5,5,5,5,5,5,6,0.0,satisfied +11573,72298,Male,Loyal Customer,55,Personal Travel,Eco,919,2,5,2,3,3,2,3,3,2,4,1,3,5,3,0,0.0,neutral or dissatisfied +11574,52294,Male,disloyal Customer,27,Business travel,Eco,651,4,2,4,4,5,4,5,5,2,4,3,3,3,5,0,1.0,neutral or dissatisfied +11575,113140,Female,Loyal Customer,43,Business travel,Business,2128,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +11576,1179,Male,Loyal Customer,48,Personal Travel,Eco,134,1,1,1,2,4,1,2,4,4,2,1,2,1,4,10,18.0,neutral or dissatisfied +11577,13140,Male,Loyal Customer,28,Personal Travel,Eco,427,1,4,2,3,1,2,1,1,3,5,3,3,2,1,3,2.0,neutral or dissatisfied +11578,42288,Female,Loyal Customer,48,Business travel,Business,1899,0,0,0,1,5,1,2,2,2,2,2,2,2,2,2,0.0,satisfied +11579,120780,Female,Loyal Customer,24,Personal Travel,Eco,678,3,5,3,2,1,3,1,1,4,4,5,5,4,1,0,6.0,neutral or dissatisfied +11580,47906,Female,Loyal Customer,43,Business travel,Eco,451,1,3,3,3,5,3,3,1,1,1,1,3,1,2,10,22.0,neutral or dissatisfied +11581,81953,Female,Loyal Customer,57,Business travel,Business,1532,1,1,1,1,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +11582,123608,Male,Loyal Customer,45,Business travel,Business,1773,2,2,2,2,2,3,5,5,5,4,5,3,5,5,25,17.0,satisfied +11583,17224,Female,Loyal Customer,39,Business travel,Eco,1092,5,1,1,1,5,5,5,5,4,3,3,5,4,5,0,0.0,satisfied +11584,79696,Male,Loyal Customer,47,Personal Travel,Eco,762,2,4,2,2,5,2,5,5,3,5,5,3,4,5,37,22.0,neutral or dissatisfied +11585,49791,Male,Loyal Customer,34,Business travel,Business,1684,4,4,4,4,1,2,4,3,3,3,3,5,3,4,0,10.0,satisfied +11586,128919,Female,Loyal Customer,51,Business travel,Business,236,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +11587,11854,Male,Loyal Customer,51,Business travel,Business,2035,3,3,3,3,2,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +11588,38019,Male,disloyal Customer,62,Business travel,Eco,1237,3,3,3,4,3,3,3,3,1,5,3,2,5,3,5,8.0,neutral or dissatisfied +11589,101495,Female,Loyal Customer,30,Business travel,Business,2370,4,4,4,4,4,3,4,4,2,2,3,3,3,4,10,4.0,neutral or dissatisfied +11590,23222,Female,Loyal Customer,67,Personal Travel,Eco,326,3,3,3,1,4,4,2,5,5,3,5,3,5,4,2,0.0,neutral or dissatisfied +11591,89421,Female,disloyal Customer,34,Business travel,Eco,151,1,5,1,2,4,1,4,4,4,1,1,3,3,4,2,3.0,neutral or dissatisfied +11592,15164,Female,Loyal Customer,17,Personal Travel,Eco Plus,912,3,5,3,1,1,3,1,1,4,4,4,4,4,1,1,21.0,neutral or dissatisfied +11593,40717,Female,Loyal Customer,31,Business travel,Business,3018,1,1,2,1,5,4,5,5,5,2,4,3,3,5,0,0.0,satisfied +11594,8762,Male,Loyal Customer,44,Personal Travel,Eco,1147,2,5,2,1,3,2,5,3,3,2,3,4,4,3,108,126.0,neutral or dissatisfied +11595,112667,Female,Loyal Customer,58,Business travel,Business,3819,5,5,5,5,2,5,5,4,4,4,4,4,4,3,8,0.0,satisfied +11596,107117,Female,Loyal Customer,57,Business travel,Business,842,3,3,1,3,2,2,2,5,3,5,5,2,5,2,226,223.0,satisfied +11597,71659,Male,Loyal Customer,66,Personal Travel,Eco,1197,4,2,4,3,1,4,1,1,3,5,3,1,3,1,1,0.0,neutral or dissatisfied +11598,127306,Female,disloyal Customer,43,Business travel,Business,1172,4,4,4,3,3,4,3,3,5,5,3,4,4,3,0,0.0,satisfied +11599,121944,Female,Loyal Customer,41,Business travel,Business,3816,4,4,4,4,3,4,5,5,5,5,5,5,5,4,50,58.0,satisfied +11600,19191,Female,Loyal Customer,49,Business travel,Eco,542,1,3,3,3,2,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +11601,111377,Female,Loyal Customer,40,Business travel,Business,3702,4,4,4,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +11602,116194,Female,Loyal Customer,56,Personal Travel,Eco,447,4,4,4,3,3,5,4,3,3,4,5,4,3,3,0,0.0,neutral or dissatisfied +11603,19629,Male,Loyal Customer,22,Business travel,Business,3823,3,3,3,3,4,4,4,4,5,4,2,4,1,4,82,75.0,satisfied +11604,123038,Male,disloyal Customer,43,Business travel,Eco,590,1,4,1,3,2,1,4,2,4,2,3,4,3,2,0,0.0,neutral or dissatisfied +11605,81629,Female,disloyal Customer,21,Business travel,Eco,1142,1,1,1,3,1,1,1,1,4,4,4,2,4,1,16,5.0,neutral or dissatisfied +11606,63722,Female,disloyal Customer,9,Business travel,Eco,958,4,4,4,3,3,4,1,3,5,3,3,5,5,3,0,0.0,satisfied +11607,27609,Male,Loyal Customer,36,Personal Travel,Eco,954,3,2,3,4,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +11608,84667,Female,disloyal Customer,25,Business travel,Eco,1043,2,2,2,3,4,2,4,4,2,5,3,1,3,4,1,4.0,neutral or dissatisfied +11609,102691,Male,Loyal Customer,17,Business travel,Business,365,2,2,2,2,4,5,4,4,4,2,4,3,5,4,0,0.0,satisfied +11610,73215,Female,Loyal Customer,52,Business travel,Business,1258,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +11611,5470,Male,Loyal Customer,24,Personal Travel,Eco,265,1,3,0,3,4,0,4,4,4,5,4,2,3,4,6,14.0,neutral or dissatisfied +11612,83417,Female,Loyal Customer,56,Business travel,Eco,632,4,5,5,5,4,4,3,4,4,4,4,2,4,5,0,0.0,satisfied +11613,62085,Female,Loyal Customer,65,Personal Travel,Eco Plus,2475,1,4,1,3,5,5,4,1,1,1,1,4,1,3,0,5.0,neutral or dissatisfied +11614,122091,Male,Loyal Customer,24,Personal Travel,Eco,130,3,4,3,2,4,3,4,4,4,3,4,4,4,4,3,2.0,neutral or dissatisfied +11615,64696,Female,Loyal Customer,56,Business travel,Business,3956,4,4,4,4,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +11616,95922,Male,Loyal Customer,49,Business travel,Eco,1411,4,2,4,2,3,4,3,3,1,3,2,1,2,3,33,14.0,neutral or dissatisfied +11617,3315,Male,Loyal Customer,51,Business travel,Business,2730,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,11.0,satisfied +11618,31323,Male,Loyal Customer,8,Personal Travel,Eco Plus,680,3,4,3,2,1,3,2,1,5,5,4,4,4,1,17,31.0,neutral or dissatisfied +11619,74822,Male,Loyal Customer,41,Personal Travel,Eco Plus,1464,1,5,1,2,5,1,5,5,5,3,5,5,4,5,0,0.0,neutral or dissatisfied +11620,43577,Male,disloyal Customer,37,Business travel,Business,1099,4,4,4,4,1,4,1,1,3,2,3,4,3,1,17,26.0,neutral or dissatisfied +11621,88338,Female,Loyal Customer,55,Business travel,Business,3662,2,2,3,2,3,4,4,5,5,4,5,4,5,4,0,3.0,satisfied +11622,54955,Male,Loyal Customer,46,Business travel,Business,1635,2,2,2,2,5,3,4,2,2,2,2,4,2,3,21,1.0,satisfied +11623,125120,Female,Loyal Customer,66,Personal Travel,Eco,361,3,4,3,1,5,4,4,2,2,3,5,5,2,3,1,32.0,neutral or dissatisfied +11624,122495,Female,Loyal Customer,33,Business travel,Business,930,2,2,2,2,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +11625,32428,Male,disloyal Customer,33,Business travel,Eco,201,2,1,2,3,1,2,1,1,4,5,4,2,4,1,4,8.0,neutral or dissatisfied +11626,81640,Female,Loyal Customer,26,Personal Travel,Business,907,5,4,5,2,5,5,5,5,4,5,5,4,5,5,0,19.0,satisfied +11627,51613,Female,Loyal Customer,59,Business travel,Eco,425,4,5,5,5,4,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +11628,104104,Male,Loyal Customer,42,Business travel,Business,1731,1,1,1,1,3,4,1,4,4,4,4,5,4,3,0,1.0,satisfied +11629,51882,Female,Loyal Customer,57,Business travel,Business,3258,5,5,5,5,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +11630,100203,Female,Loyal Customer,53,Personal Travel,Eco Plus,468,1,5,3,4,5,5,5,1,1,3,1,3,1,5,22,40.0,neutral or dissatisfied +11631,69975,Female,Loyal Customer,47,Business travel,Business,236,1,1,1,1,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +11632,96157,Male,Loyal Customer,21,Business travel,Business,328,0,0,0,2,5,5,5,5,5,5,5,3,4,5,0,0.0,satisfied +11633,61632,Female,disloyal Customer,18,Business travel,Eco,1334,4,3,3,3,1,4,1,1,3,4,5,4,4,1,0,0.0,satisfied +11634,28835,Female,Loyal Customer,35,Business travel,Business,954,2,2,2,2,1,1,2,4,4,4,4,3,4,4,0,0.0,satisfied +11635,102056,Male,Loyal Customer,38,Personal Travel,Business,226,3,4,3,2,3,5,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +11636,93074,Male,Loyal Customer,20,Business travel,Eco Plus,297,2,4,4,4,2,2,4,2,2,4,3,1,3,2,0,0.0,neutral or dissatisfied +11637,57379,Male,Loyal Customer,59,Personal Travel,Eco Plus,414,2,2,2,3,3,2,3,3,3,1,3,2,3,3,1,8.0,neutral or dissatisfied +11638,289,Male,Loyal Customer,51,Personal Travel,Eco Plus,825,2,5,3,5,4,3,4,4,3,3,4,5,5,4,0,0.0,neutral or dissatisfied +11639,121168,Female,Loyal Customer,59,Personal Travel,Eco,2370,4,4,4,1,4,1,1,3,5,4,5,1,3,1,0,0.0,satisfied +11640,43154,Male,Loyal Customer,47,Business travel,Eco,1368,5,5,2,5,5,5,5,5,5,2,1,1,1,5,0,0.0,satisfied +11641,117453,Female,Loyal Customer,25,Personal Travel,Eco,1107,1,5,1,4,5,1,5,5,4,5,4,4,5,5,47,39.0,neutral or dissatisfied +11642,46902,Male,Loyal Customer,38,Business travel,Business,845,4,4,4,4,5,4,1,5,5,5,5,4,5,2,0,0.0,satisfied +11643,3779,Male,Loyal Customer,39,Business travel,Business,2336,5,4,5,5,4,4,5,5,5,5,5,3,5,3,12,0.0,satisfied +11644,103389,Female,Loyal Customer,49,Business travel,Business,3975,0,0,0,2,5,4,5,2,2,2,2,4,2,3,38,31.0,satisfied +11645,22360,Female,Loyal Customer,41,Business travel,Business,143,3,3,3,3,2,2,4,4,4,4,5,3,4,3,0,0.0,satisfied +11646,119768,Female,Loyal Customer,46,Business travel,Business,936,3,3,2,3,4,5,4,4,4,4,4,4,4,3,21,5.0,satisfied +11647,29292,Female,Loyal Customer,39,Business travel,Eco,550,4,2,2,2,4,4,4,4,2,5,2,4,2,4,0,0.0,satisfied +11648,14215,Male,Loyal Customer,68,Personal Travel,Eco,620,3,5,3,1,2,3,2,2,4,4,5,3,4,2,15,24.0,neutral or dissatisfied +11649,50929,Female,Loyal Customer,60,Personal Travel,Eco,77,3,5,3,1,5,4,5,4,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +11650,38323,Male,Loyal Customer,21,Personal Travel,Business,1050,4,4,4,4,1,4,2,1,1,5,3,1,4,1,4,0.0,satisfied +11651,85578,Female,Loyal Customer,50,Business travel,Eco,153,1,4,4,4,4,4,3,1,1,1,1,4,1,2,27,40.0,neutral or dissatisfied +11652,7644,Male,Loyal Customer,48,Business travel,Business,3764,1,1,2,1,3,4,4,5,5,5,5,3,5,3,0,5.0,satisfied +11653,25556,Female,Loyal Customer,52,Business travel,Business,696,2,1,1,1,1,4,4,2,2,2,2,3,2,2,6,0.0,neutral or dissatisfied +11654,95900,Male,Loyal Customer,37,Personal Travel,Eco,759,3,3,3,3,4,3,4,4,2,2,3,1,3,4,23,25.0,neutral or dissatisfied +11655,105900,Male,disloyal Customer,24,Business travel,Eco,283,2,0,2,2,5,2,4,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +11656,80658,Male,Loyal Customer,9,Business travel,Eco,821,2,3,3,3,2,1,4,2,2,1,4,1,4,2,2,0.0,neutral or dissatisfied +11657,123791,Female,Loyal Customer,52,Business travel,Business,1844,5,5,5,5,2,5,4,4,4,4,4,4,4,4,0,2.0,satisfied +11658,81056,Female,Loyal Customer,27,Personal Travel,Eco,1399,0,3,0,2,4,0,4,4,1,2,2,4,3,4,0,2.0,satisfied +11659,101215,Male,Loyal Customer,68,Personal Travel,Eco,1235,2,4,2,1,5,2,5,5,3,3,4,4,4,5,0,0.0,neutral or dissatisfied +11660,76054,Female,disloyal Customer,22,Business travel,Eco,669,2,0,2,2,5,2,5,5,3,2,5,3,4,5,45,30.0,neutral or dissatisfied +11661,14319,Female,Loyal Customer,63,Business travel,Business,2581,2,2,2,2,3,5,1,5,5,5,5,2,5,1,0,0.0,satisfied +11662,26538,Male,Loyal Customer,18,Personal Travel,Eco,990,2,5,2,1,1,2,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +11663,27440,Male,disloyal Customer,14,Business travel,Eco,697,4,4,4,3,3,4,3,3,1,2,5,3,3,3,0,0.0,satisfied +11664,11748,Male,disloyal Customer,19,Business travel,Business,429,0,0,0,4,3,0,3,3,5,4,5,5,4,3,0,4.0,satisfied +11665,37753,Female,disloyal Customer,36,Business travel,Eco Plus,1069,4,4,4,4,2,4,1,2,5,5,5,3,4,2,33,15.0,neutral or dissatisfied +11666,7080,Female,Loyal Customer,43,Business travel,Business,2728,1,3,4,3,4,2,2,2,2,2,1,4,2,2,10,7.0,neutral or dissatisfied +11667,5749,Female,Loyal Customer,39,Business travel,Business,859,3,3,3,3,1,4,3,3,3,3,3,4,3,4,77,66.0,neutral or dissatisfied +11668,36409,Female,Loyal Customer,53,Business travel,Business,369,2,2,2,2,1,1,1,5,5,5,5,1,5,1,15,7.0,satisfied +11669,54165,Male,Loyal Customer,48,Business travel,Eco,1400,5,3,3,3,5,5,5,5,2,4,2,2,5,5,0,0.0,satisfied +11670,80716,Female,disloyal Customer,36,Business travel,Business,920,2,2,2,3,4,2,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +11671,53627,Female,Loyal Customer,49,Business travel,Eco,374,4,2,2,2,4,3,5,4,4,4,4,2,4,2,0,0.0,satisfied +11672,64910,Female,disloyal Customer,22,Business travel,Business,190,4,1,4,2,4,4,4,4,3,5,2,3,3,4,3,0.0,neutral or dissatisfied +11673,70274,Male,Loyal Customer,48,Business travel,Business,2912,2,2,2,2,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +11674,97064,Female,disloyal Customer,41,Business travel,Business,1497,1,2,2,3,3,1,2,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +11675,49565,Male,disloyal Customer,27,Business travel,Eco,262,3,0,3,3,1,3,1,1,5,4,1,4,1,1,35,43.0,neutral or dissatisfied +11676,10901,Male,Loyal Customer,57,Business travel,Eco,201,2,2,4,2,2,2,2,2,4,5,1,4,1,2,0,0.0,neutral or dissatisfied +11677,79683,Female,Loyal Customer,58,Personal Travel,Eco,762,1,4,1,4,4,5,5,1,1,1,1,5,1,4,0,0.0,neutral or dissatisfied +11678,125817,Male,disloyal Customer,28,Business travel,Eco,861,3,3,3,4,3,2,2,3,1,4,3,2,2,2,300,307.0,neutral or dissatisfied +11679,53773,Male,Loyal Customer,30,Business travel,Eco Plus,1195,0,0,0,4,5,0,5,5,1,4,4,4,1,5,2,2.0,satisfied +11680,35101,Male,Loyal Customer,39,Business travel,Business,3745,1,1,1,1,2,1,3,4,4,4,4,1,4,2,0,0.0,satisfied +11681,12401,Female,Loyal Customer,78,Business travel,Business,2258,3,3,3,3,3,5,5,4,4,4,4,3,4,2,0,0.0,satisfied +11682,22099,Female,Loyal Customer,68,Personal Travel,Eco,782,2,4,2,5,2,2,3,4,3,4,5,3,4,3,172,162.0,neutral or dissatisfied +11683,117176,Male,Loyal Customer,13,Personal Travel,Eco,646,2,4,2,4,5,2,5,5,1,3,2,3,2,5,1,0.0,neutral or dissatisfied +11684,19880,Male,Loyal Customer,77,Business travel,Business,343,1,2,1,1,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +11685,100930,Male,Loyal Customer,26,Personal Travel,Eco,838,2,5,2,1,5,2,2,5,4,4,5,5,5,5,2,6.0,neutral or dissatisfied +11686,116272,Male,Loyal Customer,8,Personal Travel,Eco,325,1,1,1,4,3,1,3,3,3,5,3,2,4,3,28,24.0,neutral or dissatisfied +11687,125156,Female,Loyal Customer,53,Business travel,Business,813,5,5,1,5,2,4,5,2,2,2,2,5,2,3,41,,satisfied +11688,28456,Female,disloyal Customer,29,Business travel,Eco,1029,3,3,3,3,3,2,2,2,4,2,3,2,1,2,0,18.0,neutral or dissatisfied +11689,13403,Female,Loyal Customer,55,Business travel,Business,475,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +11690,114771,Male,Loyal Customer,33,Business travel,Business,2858,4,4,4,4,5,5,5,5,4,5,4,3,4,5,0,0.0,satisfied +11691,56077,Male,Loyal Customer,53,Personal Travel,Eco,2586,3,1,3,3,3,3,3,3,1,2,4,3,4,3,2,0.0,neutral or dissatisfied +11692,66238,Female,Loyal Customer,23,Business travel,Business,3166,2,2,2,2,4,4,4,4,3,5,3,3,5,4,0,0.0,satisfied +11693,73585,Female,Loyal Customer,56,Business travel,Business,2237,5,5,5,5,3,5,4,3,3,4,5,5,3,5,0,6.0,satisfied +11694,51618,Male,Loyal Customer,62,Business travel,Business,3261,3,3,3,3,5,3,1,4,4,4,4,4,4,4,0,0.0,satisfied +11695,110672,Male,Loyal Customer,29,Business travel,Business,2442,2,3,3,3,2,2,2,2,1,5,4,3,4,2,21,22.0,neutral or dissatisfied +11696,5384,Female,Loyal Customer,21,Personal Travel,Eco,733,3,1,3,2,2,3,3,2,4,5,2,2,2,2,0,0.0,neutral or dissatisfied +11697,73460,Male,Loyal Customer,39,Personal Travel,Eco,1144,3,5,3,3,4,3,4,4,2,5,5,4,3,4,0,0.0,neutral or dissatisfied +11698,108451,Male,Loyal Customer,40,Business travel,Business,1044,1,4,4,4,2,2,1,1,1,1,1,1,1,4,70,76.0,neutral or dissatisfied +11699,79569,Male,disloyal Customer,16,Business travel,Eco,762,2,2,2,2,1,2,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +11700,85053,Female,Loyal Customer,41,Business travel,Business,731,1,1,1,1,4,5,4,4,4,4,4,4,4,4,27,11.0,satisfied +11701,115180,Male,disloyal Customer,37,Business travel,Business,337,2,2,2,3,5,2,5,5,5,4,4,4,4,5,18,18.0,neutral or dissatisfied +11702,99363,Female,Loyal Customer,28,Business travel,Eco,409,3,5,5,5,3,3,3,3,4,2,4,4,3,3,0,0.0,neutral or dissatisfied +11703,49954,Female,Loyal Customer,36,Business travel,Business,373,3,3,3,3,5,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +11704,66015,Female,Loyal Customer,39,Business travel,Business,2685,3,3,3,3,3,5,5,4,4,4,4,5,4,3,41,41.0,satisfied +11705,101883,Female,disloyal Customer,23,Business travel,Eco,2039,5,5,5,3,4,5,4,4,5,2,3,4,5,4,68,58.0,satisfied +11706,115987,Female,Loyal Customer,55,Personal Travel,Eco,446,4,4,4,1,5,5,5,5,5,4,3,5,5,4,43,42.0,satisfied +11707,57253,Male,Loyal Customer,38,Business travel,Eco,628,3,1,1,1,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +11708,63877,Female,Loyal Customer,18,Business travel,Eco,1192,4,5,5,5,4,4,2,4,4,4,3,2,3,4,0,6.0,neutral or dissatisfied +11709,98312,Female,Loyal Customer,18,Personal Travel,Eco,1565,2,2,2,3,2,2,2,2,3,5,4,3,3,2,0,6.0,neutral or dissatisfied +11710,99413,Male,disloyal Customer,22,Business travel,Eco,314,2,0,2,3,5,2,5,5,2,3,3,1,5,5,0,0.0,neutral or dissatisfied +11711,91190,Female,Loyal Customer,46,Personal Travel,Eco,581,2,1,2,1,1,2,1,3,3,2,5,4,3,4,42,40.0,neutral or dissatisfied +11712,106857,Female,Loyal Customer,57,Personal Travel,Business,577,2,2,2,3,1,4,4,4,4,2,4,1,4,1,4,13.0,neutral or dissatisfied +11713,53013,Female,disloyal Customer,25,Business travel,Eco,1208,3,3,3,3,4,3,5,4,2,2,4,3,3,4,0,31.0,neutral or dissatisfied +11714,89103,Female,Loyal Customer,41,Business travel,Business,2116,1,1,1,1,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +11715,120361,Male,Loyal Customer,59,Business travel,Business,366,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,19.0,satisfied +11716,34853,Male,Loyal Customer,41,Business travel,Eco,1826,1,4,4,4,1,1,1,1,2,1,3,3,2,1,71,60.0,neutral or dissatisfied +11717,36679,Male,Loyal Customer,53,Personal Travel,Eco,1121,3,4,3,4,4,3,4,4,4,2,3,3,5,4,0,0.0,neutral or dissatisfied +11718,52075,Female,disloyal Customer,23,Business travel,Eco,438,3,0,3,5,4,3,4,4,1,4,3,2,1,4,0,3.0,neutral or dissatisfied +11719,68729,Male,Loyal Customer,40,Personal Travel,Eco Plus,175,3,5,3,2,5,3,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +11720,43150,Female,Loyal Customer,10,Personal Travel,Eco Plus,414,2,4,1,4,2,1,2,2,1,5,5,1,3,2,4,0.0,neutral or dissatisfied +11721,124605,Male,Loyal Customer,32,Business travel,Business,1671,2,4,4,4,2,2,2,2,1,1,3,3,3,2,16,26.0,neutral or dissatisfied +11722,90274,Female,Loyal Customer,43,Business travel,Business,2542,1,5,5,5,5,4,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +11723,27810,Male,Loyal Customer,19,Business travel,Business,3888,1,1,1,1,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +11724,70719,Male,disloyal Customer,27,Business travel,Eco,675,3,3,3,3,2,3,2,2,2,2,4,2,4,2,2,0.0,neutral or dissatisfied +11725,95302,Female,Loyal Customer,15,Personal Travel,Eco,189,1,2,1,2,2,1,1,2,1,1,2,2,2,2,19,14.0,neutral or dissatisfied +11726,45740,Male,Loyal Customer,47,Business travel,Business,1772,2,2,2,2,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11727,76606,Female,Loyal Customer,48,Business travel,Business,2473,3,3,1,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +11728,65732,Female,Loyal Customer,25,Business travel,Business,1061,4,4,4,4,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +11729,102809,Male,Loyal Customer,55,Business travel,Business,342,3,3,3,3,2,4,5,4,4,4,4,3,4,4,61,60.0,satisfied +11730,98770,Male,Loyal Customer,17,Personal Travel,Eco,2075,4,5,3,1,1,3,2,1,4,3,4,4,5,1,26,0.0,neutral or dissatisfied +11731,101823,Female,Loyal Customer,20,Personal Travel,Eco,1521,0,1,0,3,4,0,3,4,1,2,3,1,4,4,0,0.0,satisfied +11732,77577,Female,Loyal Customer,57,Business travel,Business,2313,2,3,3,3,1,2,2,2,2,2,2,3,2,3,59,51.0,neutral or dissatisfied +11733,118312,Male,Loyal Customer,51,Business travel,Business,639,5,5,1,5,5,4,4,5,5,5,5,5,5,5,1,9.0,satisfied +11734,94227,Male,Loyal Customer,44,Business travel,Business,293,5,5,5,5,2,4,4,4,4,4,4,5,4,5,6,9.0,satisfied +11735,72632,Male,Loyal Customer,36,Personal Travel,Eco,985,1,4,1,3,2,1,4,2,5,2,4,5,4,2,0,0.0,neutral or dissatisfied +11736,75900,Male,Loyal Customer,49,Business travel,Business,1765,2,1,4,4,3,2,2,1,5,4,4,2,1,2,294,296.0,neutral or dissatisfied +11737,16028,Male,Loyal Customer,54,Personal Travel,Eco,780,2,1,2,3,4,2,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +11738,41142,Male,Loyal Customer,65,Personal Travel,Eco,224,1,5,1,1,3,1,1,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +11739,4073,Male,Loyal Customer,64,Personal Travel,Eco Plus,425,2,2,2,2,2,2,2,2,3,2,2,1,3,2,9,84.0,neutral or dissatisfied +11740,113882,Female,Loyal Customer,38,Personal Travel,Eco Plus,1363,3,4,3,3,4,3,4,4,5,2,4,3,4,4,19,0.0,neutral or dissatisfied +11741,31181,Female,Loyal Customer,51,Business travel,Business,1620,2,1,1,1,3,3,3,2,2,2,2,3,2,4,65,77.0,neutral or dissatisfied +11742,123460,Male,disloyal Customer,21,Business travel,Eco,911,3,3,3,4,1,3,1,1,4,3,5,3,5,1,0,0.0,neutral or dissatisfied +11743,118968,Male,Loyal Customer,33,Personal Travel,Eco,570,3,4,3,5,2,3,2,2,3,5,5,5,4,2,0,3.0,neutral or dissatisfied +11744,99012,Female,Loyal Customer,40,Personal Travel,Eco Plus,543,2,0,2,3,5,2,5,5,4,4,4,5,5,5,13,0.0,neutral or dissatisfied +11745,9485,Female,Loyal Customer,44,Business travel,Business,3059,5,5,5,5,5,4,5,5,5,5,5,4,5,4,5,0.0,satisfied +11746,61820,Female,Loyal Customer,42,Personal Travel,Eco,1379,2,5,2,1,5,3,5,2,2,2,4,1,2,2,0,0.0,neutral or dissatisfied +11747,110056,Male,Loyal Customer,28,Personal Travel,Eco,2173,4,5,4,5,3,4,3,3,4,3,4,4,5,3,5,0.0,satisfied +11748,83267,Male,Loyal Customer,77,Business travel,Business,1979,4,4,4,4,2,4,3,4,4,4,4,1,4,2,15,0.0,neutral or dissatisfied +11749,40964,Male,Loyal Customer,38,Business travel,Business,2125,2,2,2,2,3,2,1,5,5,5,5,4,5,4,0,3.0,satisfied +11750,101298,Female,Loyal Customer,53,Personal Travel,Eco,444,1,4,4,4,5,5,5,2,2,4,1,4,2,5,2,0.0,neutral or dissatisfied +11751,91377,Male,Loyal Customer,80,Business travel,Eco Plus,406,3,5,5,5,3,3,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +11752,78642,Male,Loyal Customer,56,Business travel,Business,2172,2,2,4,2,5,5,5,4,4,5,4,3,4,4,0,0.0,satisfied +11753,57840,Male,Loyal Customer,37,Business travel,Eco,1091,3,1,1,1,3,3,3,3,3,1,3,4,4,3,0,7.0,neutral or dissatisfied +11754,103115,Female,Loyal Customer,65,Personal Travel,Eco,546,3,3,3,3,2,4,3,2,2,3,2,3,2,2,8,7.0,neutral or dissatisfied +11755,114732,Female,Loyal Customer,59,Business travel,Business,3272,1,1,1,1,4,4,5,4,4,4,4,4,4,3,60,52.0,satisfied +11756,120907,Female,Loyal Customer,30,Business travel,Business,992,3,3,3,3,1,2,1,1,3,5,4,3,5,1,3,9.0,satisfied +11757,49550,Female,disloyal Customer,37,Business travel,Eco,109,4,4,4,5,4,4,4,4,3,5,3,1,4,4,0,0.0,neutral or dissatisfied +11758,98663,Female,Loyal Customer,9,Personal Travel,Eco,920,3,2,3,3,1,3,1,1,2,3,3,3,4,1,28,14.0,neutral or dissatisfied +11759,13515,Female,Loyal Customer,36,Business travel,Eco,106,4,4,4,4,4,4,4,4,3,2,1,1,2,4,0,0.0,satisfied +11760,43830,Male,disloyal Customer,21,Business travel,Eco,114,2,4,2,5,2,2,2,2,1,5,1,2,2,2,0,0.0,neutral or dissatisfied +11761,14878,Female,disloyal Customer,29,Business travel,Eco,343,1,1,1,2,2,1,4,2,1,3,3,4,3,2,0,0.0,neutral or dissatisfied +11762,80837,Male,Loyal Customer,9,Business travel,Business,484,3,4,4,4,3,3,3,3,1,5,3,1,4,3,13,2.0,neutral or dissatisfied +11763,39726,Female,Loyal Customer,63,Business travel,Business,320,3,3,3,3,5,4,3,3,3,3,3,3,3,4,1,0.0,neutral or dissatisfied +11764,105315,Female,Loyal Customer,39,Business travel,Business,409,4,4,4,4,4,5,5,4,4,4,4,5,4,4,6,0.0,satisfied +11765,21018,Male,Loyal Customer,36,Business travel,Business,2884,3,3,3,3,5,1,3,5,5,5,5,2,5,4,20,8.0,satisfied +11766,80988,Female,Loyal Customer,43,Business travel,Business,2529,0,0,0,3,4,2,3,5,5,5,5,2,5,3,0,0.0,satisfied +11767,49775,Male,Loyal Customer,79,Business travel,Business,3924,1,3,3,3,5,3,4,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +11768,126583,Male,Loyal Customer,61,Personal Travel,Business,1337,3,5,3,5,3,5,4,1,1,3,1,3,1,4,9,17.0,neutral or dissatisfied +11769,129258,Male,Loyal Customer,55,Business travel,Business,3737,3,3,3,3,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +11770,43843,Female,Loyal Customer,52,Business travel,Eco,199,5,4,4,4,3,2,3,5,5,5,5,1,5,4,0,0.0,satisfied +11771,82373,Male,Loyal Customer,12,Personal Travel,Eco Plus,453,3,3,3,3,2,3,5,2,2,4,3,2,4,2,0,4.0,neutral or dissatisfied +11772,5942,Male,Loyal Customer,37,Business travel,Eco Plus,108,3,4,4,4,3,3,3,3,2,3,2,2,3,3,13,13.0,neutral or dissatisfied +11773,129082,Male,disloyal Customer,23,Business travel,Business,2218,5,0,5,3,2,5,2,2,5,3,5,5,5,2,1,1.0,satisfied +11774,69245,Male,Loyal Customer,40,Business travel,Business,733,3,3,3,3,3,5,4,5,5,5,5,5,5,5,0,25.0,satisfied +11775,73089,Male,Loyal Customer,23,Personal Travel,Eco,1085,3,4,4,5,3,4,2,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +11776,98972,Male,disloyal Customer,21,Business travel,Eco,479,2,4,2,4,1,2,2,1,1,4,3,2,3,1,9,14.0,neutral or dissatisfied +11777,27130,Female,Loyal Customer,19,Business travel,Business,2681,4,4,5,4,5,4,4,3,2,4,5,4,3,4,0,13.0,satisfied +11778,21826,Female,disloyal Customer,41,Business travel,Eco,640,2,4,2,4,2,2,2,2,2,3,3,3,1,2,9,1.0,neutral or dissatisfied +11779,31816,Female,Loyal Customer,45,Personal Travel,Eco,4983,3,1,3,2,3,1,1,2,5,2,3,1,4,1,2,0.0,neutral or dissatisfied +11780,115181,Male,Loyal Customer,41,Business travel,Business,337,3,3,3,3,2,5,4,4,4,4,4,5,4,3,2,0.0,satisfied +11781,87329,Male,Loyal Customer,13,Personal Travel,Eco,1027,3,4,3,5,4,3,4,4,2,4,4,3,5,4,35,29.0,neutral or dissatisfied +11782,119285,Male,Loyal Customer,49,Business travel,Business,1823,4,5,4,4,3,5,4,5,5,5,4,3,5,4,0,0.0,satisfied +11783,92304,Female,Loyal Customer,10,Personal Travel,Business,2615,3,1,3,3,2,3,2,2,2,5,2,1,4,2,30,0.0,neutral or dissatisfied +11784,123314,Female,Loyal Customer,26,Business travel,Eco Plus,507,1,1,1,1,1,1,2,1,1,2,4,1,3,1,93,87.0,neutral or dissatisfied +11785,79737,Female,Loyal Customer,47,Business travel,Eco Plus,749,3,1,3,1,3,4,4,3,3,3,3,2,3,4,50,34.0,neutral or dissatisfied +11786,85161,Male,Loyal Customer,43,Business travel,Business,1282,2,1,1,1,3,2,3,2,2,2,2,3,2,3,85,69.0,neutral or dissatisfied +11787,114279,Male,Loyal Customer,35,Personal Travel,Eco,967,2,5,2,2,3,2,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +11788,28317,Male,Loyal Customer,54,Business travel,Business,2860,2,2,2,2,3,1,2,5,5,5,5,4,5,4,0,0.0,satisfied +11789,123232,Male,Loyal Customer,35,Personal Travel,Eco,328,2,4,2,2,4,2,4,4,1,5,5,1,3,4,11,60.0,neutral or dissatisfied +11790,121985,Male,Loyal Customer,31,Business travel,Business,130,1,1,1,1,5,5,5,5,4,4,4,5,5,5,0,0.0,satisfied +11791,126395,Female,Loyal Customer,65,Personal Travel,Eco,600,2,1,2,4,3,3,4,2,2,2,2,1,2,2,5,3.0,neutral or dissatisfied +11792,66122,Female,Loyal Customer,55,Business travel,Eco,583,1,5,5,5,2,3,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +11793,3419,Female,Loyal Customer,49,Personal Travel,Eco,315,1,4,1,1,5,4,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +11794,85598,Female,disloyal Customer,40,Business travel,Business,259,2,2,2,3,1,2,1,1,3,1,4,4,3,1,56,48.0,neutral or dissatisfied +11795,55973,Male,Loyal Customer,39,Personal Travel,Eco,1620,2,4,2,5,4,2,1,4,5,3,4,4,5,4,18,21.0,neutral or dissatisfied +11796,37602,Male,Loyal Customer,60,Personal Travel,Eco,1005,5,4,5,4,5,1,1,3,2,5,5,1,5,1,431,402.0,satisfied +11797,49708,Male,Loyal Customer,41,Business travel,Business,2138,1,5,5,5,4,2,3,1,1,1,1,4,1,3,12,2.0,neutral or dissatisfied +11798,124047,Female,Loyal Customer,26,Business travel,Eco Plus,184,5,2,2,2,5,4,3,5,1,1,4,2,4,5,0,0.0,neutral or dissatisfied +11799,95998,Female,Loyal Customer,54,Business travel,Business,795,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +11800,116979,Male,Loyal Customer,52,Business travel,Business,1647,1,1,1,1,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +11801,64079,Male,Loyal Customer,9,Personal Travel,Eco,921,2,4,2,1,2,2,2,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +11802,78347,Female,Loyal Customer,27,Personal Travel,Eco,1547,2,5,3,3,3,3,1,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +11803,99144,Female,Loyal Customer,44,Business travel,Eco Plus,181,2,2,2,2,2,4,3,2,2,2,2,2,2,1,23,20.0,neutral or dissatisfied +11804,25629,Male,Loyal Customer,31,Business travel,Business,3612,2,2,2,2,2,2,2,2,4,4,3,1,3,2,12,1.0,neutral or dissatisfied +11805,81786,Female,Loyal Customer,35,Business travel,Business,1310,4,4,4,4,3,5,5,5,5,5,5,4,5,5,0,61.0,satisfied +11806,1204,Male,Loyal Customer,18,Personal Travel,Eco,482,3,3,5,3,3,5,3,3,3,2,3,2,4,3,0,7.0,neutral or dissatisfied +11807,49405,Male,Loyal Customer,49,Business travel,Business,2308,3,4,4,4,3,3,4,3,3,3,3,4,3,3,16,9.0,neutral or dissatisfied +11808,42022,Male,Loyal Customer,40,Business travel,Business,3629,0,4,0,2,5,4,1,2,2,2,2,1,2,1,0,0.0,satisfied +11809,16204,Male,Loyal Customer,11,Personal Travel,Eco,199,2,5,2,3,2,3,2,4,2,5,4,2,3,2,134,136.0,neutral or dissatisfied +11810,58677,Male,Loyal Customer,55,Business travel,Business,622,4,4,4,4,2,5,4,2,2,2,2,5,2,4,3,12.0,satisfied +11811,55288,Female,Loyal Customer,59,Business travel,Eco,1585,4,2,5,2,3,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +11812,28688,Male,Loyal Customer,23,Personal Travel,Eco,2797,1,3,0,4,3,0,1,3,3,1,3,2,4,3,0,0.0,neutral or dissatisfied +11813,64531,Male,Loyal Customer,47,Business travel,Business,3101,1,1,1,1,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +11814,120771,Female,Loyal Customer,25,Business travel,Business,1774,2,4,5,5,2,2,2,2,1,3,3,2,3,2,104,108.0,neutral or dissatisfied +11815,33600,Female,Loyal Customer,48,Business travel,Business,474,1,1,1,1,2,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +11816,2962,Female,Loyal Customer,27,Personal Travel,Eco,835,4,4,4,2,1,4,1,1,4,2,5,5,4,1,0,0.0,satisfied +11817,46594,Male,Loyal Customer,35,Business travel,Business,3036,2,2,3,2,3,2,3,4,4,4,5,4,4,5,10,2.0,satisfied +11818,97780,Female,disloyal Customer,39,Business travel,Business,471,3,3,3,1,4,3,4,4,5,2,4,4,4,4,1,0.0,neutral or dissatisfied +11819,73032,Female,Loyal Customer,55,Personal Travel,Eco,1096,1,2,1,3,5,2,3,3,3,1,3,4,3,4,0,0.0,neutral or dissatisfied +11820,54644,Male,Loyal Customer,31,Business travel,Business,3366,1,1,1,1,5,5,5,5,2,4,1,4,5,5,0,0.0,satisfied +11821,49619,Male,Loyal Customer,50,Business travel,Business,3915,1,1,1,1,5,1,4,4,4,4,5,5,4,1,0,0.0,satisfied +11822,37291,Female,Loyal Customer,40,Business travel,Eco,1011,4,2,2,2,4,4,4,4,4,1,5,4,2,4,60,87.0,satisfied +11823,117324,Male,Loyal Customer,27,Personal Travel,Eco Plus,304,4,3,4,2,1,4,1,1,5,3,2,5,3,1,14,17.0,neutral or dissatisfied +11824,27291,Female,Loyal Customer,40,Business travel,Eco,697,5,1,1,1,5,5,5,5,2,2,1,3,5,5,0,0.0,satisfied +11825,103747,Female,disloyal Customer,23,Business travel,Business,405,4,0,4,5,5,4,5,5,3,2,5,5,4,5,22,27.0,satisfied +11826,79384,Male,Loyal Customer,58,Business travel,Business,502,2,2,2,2,3,4,4,4,4,4,4,5,4,4,14,10.0,satisfied +11827,92289,Female,Loyal Customer,52,Business travel,Business,1814,5,5,5,5,4,5,4,2,2,2,2,3,2,5,5,0.0,satisfied +11828,53892,Male,Loyal Customer,53,Personal Travel,Eco,140,2,3,2,1,5,2,4,5,2,2,1,3,5,5,8,4.0,neutral or dissatisfied +11829,126602,Female,Loyal Customer,30,Business travel,Business,1337,2,2,2,2,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +11830,110912,Male,Loyal Customer,33,Business travel,Business,406,3,4,4,4,3,3,3,3,4,5,1,4,1,3,3,45.0,neutral or dissatisfied +11831,17721,Female,Loyal Customer,32,Business travel,Business,1895,4,4,4,4,5,5,5,5,4,5,1,5,1,5,0,0.0,satisfied +11832,112740,Female,Loyal Customer,29,Business travel,Business,605,2,2,2,2,4,4,4,4,3,4,5,3,4,4,12,0.0,satisfied +11833,106367,Male,Loyal Customer,16,Business travel,Business,2984,3,4,5,4,3,3,3,3,1,3,4,3,3,3,0,0.0,neutral or dissatisfied +11834,97526,Female,Loyal Customer,34,Business travel,Business,2621,3,3,2,3,5,3,4,3,3,3,3,3,3,2,91,84.0,neutral or dissatisfied +11835,52881,Male,disloyal Customer,21,Business travel,Eco,624,4,3,4,4,5,4,5,5,3,2,4,3,5,5,94,79.0,satisfied +11836,7601,Male,Loyal Customer,25,Business travel,Business,1835,4,4,4,4,4,4,4,4,3,4,5,3,5,4,0,0.0,satisfied +11837,77566,Female,disloyal Customer,26,Business travel,Business,689,5,5,5,2,2,5,1,2,4,4,4,3,4,2,0,0.0,satisfied +11838,119797,Male,Loyal Customer,42,Business travel,Business,1948,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11839,109865,Male,Loyal Customer,68,Business travel,Eco,1033,2,4,4,4,2,2,2,2,3,5,3,1,3,2,37,24.0,neutral or dissatisfied +11840,71600,Male,Loyal Customer,46,Business travel,Eco,1182,2,2,3,2,2,2,2,2,3,5,3,2,3,2,0,30.0,neutral or dissatisfied +11841,7128,Female,Loyal Customer,59,Business travel,Business,2801,2,2,2,2,5,5,5,5,5,5,4,5,5,4,20,15.0,satisfied +11842,104117,Female,Loyal Customer,18,Personal Travel,Eco Plus,297,3,5,3,3,2,3,2,2,5,5,4,5,5,2,28,23.0,neutral or dissatisfied +11843,7939,Male,disloyal Customer,39,Business travel,Business,594,3,3,3,2,2,3,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +11844,122661,Female,Loyal Customer,40,Business travel,Business,2510,3,3,3,3,3,4,4,5,5,5,5,3,5,4,0,33.0,satisfied +11845,33912,Male,Loyal Customer,49,Business travel,Business,1941,4,4,4,4,3,2,4,4,4,4,4,2,4,1,46,51.0,satisfied +11846,106741,Male,disloyal Customer,22,Business travel,Eco,945,3,2,2,2,2,2,1,2,3,2,3,4,3,2,36,37.0,neutral or dissatisfied +11847,2271,Male,disloyal Customer,27,Business travel,Business,672,3,4,4,1,2,4,2,2,3,2,4,5,5,2,0,0.0,neutral or dissatisfied +11848,4262,Female,disloyal Customer,25,Business travel,Business,502,5,4,5,2,1,5,1,1,5,3,5,5,4,1,0,0.0,satisfied +11849,124026,Male,Loyal Customer,66,Personal Travel,Eco,184,2,3,2,4,5,2,5,5,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +11850,128378,Male,Loyal Customer,30,Business travel,Business,3201,2,2,2,2,4,4,4,4,3,3,5,4,4,4,7,3.0,satisfied +11851,125648,Female,Loyal Customer,31,Business travel,Business,759,1,2,2,2,1,1,1,1,2,4,3,2,3,1,0,0.0,neutral or dissatisfied +11852,75821,Male,disloyal Customer,23,Business travel,Business,1040,5,5,5,3,5,5,5,5,4,5,4,4,4,5,18,46.0,satisfied +11853,85479,Female,disloyal Customer,47,Business travel,Eco,214,3,5,3,3,3,3,3,3,3,3,2,3,3,3,63,66.0,neutral or dissatisfied +11854,101145,Male,Loyal Customer,25,Business travel,Business,583,2,1,1,1,2,2,2,2,1,3,4,4,3,2,17,9.0,neutral or dissatisfied +11855,83810,Female,disloyal Customer,21,Business travel,Eco,425,1,5,1,3,2,1,1,2,5,4,4,5,4,2,10,2.0,neutral or dissatisfied +11856,38502,Female,Loyal Customer,42,Business travel,Eco,2569,4,2,2,2,3,4,4,4,4,4,4,3,4,2,0,0.0,satisfied +11857,87123,Male,Loyal Customer,22,Personal Travel,Eco,594,2,5,2,2,5,2,5,5,2,1,3,2,5,5,0,0.0,neutral or dissatisfied +11858,115214,Female,Loyal Customer,51,Business travel,Business,337,2,2,2,2,5,5,5,5,5,4,5,5,4,5,138,136.0,satisfied +11859,85957,Female,disloyal Customer,22,Business travel,Business,447,0,4,0,3,4,0,3,4,5,4,5,3,5,4,7,1.0,satisfied +11860,50641,Male,Loyal Customer,50,Personal Travel,Eco,421,1,4,1,4,5,1,5,5,2,1,3,1,4,5,23,27.0,neutral or dissatisfied +11861,122539,Female,Loyal Customer,41,Business travel,Business,500,3,3,3,3,4,4,4,4,4,5,4,5,4,3,0,0.0,satisfied +11862,88969,Female,Loyal Customer,14,Business travel,Business,2925,5,5,5,5,5,5,5,5,4,5,5,3,5,5,2,0.0,satisfied +11863,120407,Male,Loyal Customer,38,Business travel,Business,449,3,4,4,4,4,3,2,3,3,3,3,1,3,2,10,16.0,neutral or dissatisfied +11864,80611,Male,Loyal Customer,38,Business travel,Business,236,3,3,3,3,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +11865,27786,Female,Loyal Customer,44,Business travel,Eco,909,4,1,5,5,2,1,5,4,4,4,4,3,4,1,0,7.0,satisfied +11866,82843,Female,Loyal Customer,48,Business travel,Business,594,1,1,2,1,5,4,5,5,5,5,5,5,5,4,0,3.0,satisfied +11867,44492,Male,disloyal Customer,23,Business travel,Eco,261,2,4,2,5,5,2,5,5,3,3,2,4,3,5,1,0.0,neutral or dissatisfied +11868,120999,Female,disloyal Customer,24,Business travel,Eco,520,1,2,1,3,5,1,5,5,1,4,4,1,3,5,97,95.0,neutral or dissatisfied +11869,61926,Female,Loyal Customer,17,Personal Travel,Eco,550,3,5,3,4,5,3,5,5,3,2,4,4,5,5,27,33.0,neutral or dissatisfied +11870,82108,Male,Loyal Customer,14,Personal Travel,Eco,1276,2,4,2,5,4,2,4,4,5,1,5,1,4,4,0,0.0,neutral or dissatisfied +11871,36099,Female,Loyal Customer,66,Personal Travel,Eco,399,2,4,2,2,2,4,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +11872,80836,Female,Loyal Customer,25,Business travel,Business,484,4,1,1,1,4,4,4,4,3,3,3,2,3,4,0,10.0,neutral or dissatisfied +11873,47025,Male,Loyal Customer,38,Business travel,Business,602,2,2,2,2,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +11874,77015,Female,Loyal Customer,49,Business travel,Business,368,2,2,2,2,3,4,4,4,4,4,4,5,4,3,7,5.0,satisfied +11875,56775,Female,Loyal Customer,67,Personal Travel,Eco Plus,1085,1,5,1,1,3,5,2,4,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +11876,84393,Male,Loyal Customer,48,Business travel,Business,1798,3,4,4,4,2,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +11877,50796,Female,Loyal Customer,35,Personal Travel,Eco,77,2,5,0,3,1,0,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +11878,36055,Male,Loyal Customer,55,Business travel,Business,3361,3,5,5,5,3,3,4,3,3,3,3,1,3,2,0,9.0,neutral or dissatisfied +11879,106776,Female,Loyal Customer,13,Personal Travel,Eco,837,3,4,3,5,3,3,3,3,3,5,1,2,1,3,18,12.0,neutral or dissatisfied +11880,110976,Male,disloyal Customer,24,Business travel,Business,240,0,0,0,5,5,0,5,5,4,5,4,4,5,5,0,0.0,satisfied +11881,25359,Male,Loyal Customer,42,Business travel,Business,1983,4,4,1,4,5,5,3,1,1,2,1,5,1,2,3,0.0,satisfied +11882,47470,Female,Loyal Customer,48,Personal Travel,Eco,501,3,4,3,1,5,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +11883,101619,Male,Loyal Customer,33,Personal Travel,Eco,1371,2,3,2,4,5,2,2,5,1,2,4,1,3,5,3,0.0,neutral or dissatisfied +11884,74788,Female,disloyal Customer,25,Business travel,Business,1431,5,0,5,3,4,5,4,4,3,5,4,3,5,4,0,0.0,satisfied +11885,43364,Female,Loyal Customer,21,Personal Travel,Eco,387,2,4,2,3,1,2,1,1,4,4,5,4,5,1,0,0.0,neutral or dissatisfied +11886,25858,Female,Loyal Customer,37,Personal Travel,Eco,692,1,4,1,1,3,1,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +11887,29085,Male,Loyal Customer,38,Personal Travel,Eco,987,1,4,0,1,2,0,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +11888,113716,Male,Loyal Customer,27,Personal Travel,Eco,258,4,1,4,4,2,4,2,2,4,4,3,4,3,2,0,0.0,satisfied +11889,24198,Male,Loyal Customer,53,Business travel,Eco,147,3,4,4,4,3,3,3,3,4,5,3,3,4,3,0,13.0,neutral or dissatisfied +11890,76253,Female,Loyal Customer,20,Personal Travel,Eco,1399,2,4,2,3,3,2,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +11891,40043,Male,Loyal Customer,34,Business travel,Eco,866,0,0,0,4,1,0,1,1,1,1,3,4,3,1,0,0.0,satisfied +11892,38756,Female,Loyal Customer,51,Business travel,Eco,354,5,2,2,2,1,2,4,5,5,5,5,5,5,4,0,0.0,satisfied +11893,9656,Male,disloyal Customer,25,Business travel,Business,277,2,4,3,4,3,3,1,3,1,4,3,2,4,3,0,0.0,neutral or dissatisfied +11894,14239,Male,Loyal Customer,29,Business travel,Business,2471,2,2,3,2,3,3,3,3,4,2,4,3,5,3,0,0.0,satisfied +11895,87956,Male,Loyal Customer,51,Business travel,Business,545,5,5,5,5,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +11896,92983,Female,Loyal Customer,58,Business travel,Business,738,3,3,3,3,5,4,5,4,4,4,4,5,4,4,1,9.0,satisfied +11897,86194,Female,Loyal Customer,73,Business travel,Business,2561,5,5,5,5,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +11898,95056,Male,Loyal Customer,8,Personal Travel,Eco,189,1,3,0,4,4,0,4,4,2,1,3,1,3,4,66,64.0,neutral or dissatisfied +11899,100115,Female,disloyal Customer,44,Business travel,Business,725,2,2,2,2,2,2,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +11900,80947,Male,Loyal Customer,48,Business travel,Business,3905,0,1,1,1,4,4,5,1,1,1,1,5,1,5,0,0.0,satisfied +11901,121472,Female,Loyal Customer,11,Personal Travel,Eco,331,3,2,3,4,4,3,4,4,1,1,3,4,4,4,0,0.0,neutral or dissatisfied +11902,16501,Female,Loyal Customer,57,Business travel,Eco,143,3,1,1,1,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +11903,2244,Female,disloyal Customer,33,Business travel,Business,630,3,3,3,5,2,3,2,2,4,2,4,5,5,2,0,1.0,neutral or dissatisfied +11904,24456,Female,Loyal Customer,34,Business travel,Eco,547,5,3,3,3,5,5,5,5,2,3,4,4,2,5,0,3.0,satisfied +11905,19422,Female,Loyal Customer,33,Business travel,Eco,645,4,1,4,1,4,4,4,4,4,2,2,3,2,4,25,40.0,satisfied +11906,58361,Male,disloyal Customer,9,Personal Travel,Eco,646,3,5,3,3,3,3,3,3,2,4,5,2,5,3,2,0.0,neutral or dissatisfied +11907,63856,Male,Loyal Customer,45,Business travel,Business,2952,2,2,3,2,3,4,4,5,5,5,5,5,5,4,0,2.0,satisfied +11908,73382,Male,Loyal Customer,44,Business travel,Business,3775,5,5,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +11909,2794,Male,Loyal Customer,44,Business travel,Eco,364,3,3,4,4,3,3,3,3,5,3,3,5,1,3,0,14.0,satisfied +11910,39405,Female,Loyal Customer,47,Personal Travel,Eco,546,1,1,2,3,4,4,3,4,4,2,4,3,4,4,5,0.0,neutral or dissatisfied +11911,68867,Female,Loyal Customer,63,Business travel,Business,3252,2,1,3,3,5,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +11912,108754,Female,Loyal Customer,29,Business travel,Business,3871,1,1,1,1,5,5,5,5,3,3,4,5,4,5,46,63.0,satisfied +11913,74231,Female,Loyal Customer,25,Business travel,Business,888,3,3,3,3,5,5,5,5,4,3,4,5,5,5,30,52.0,satisfied +11914,44313,Female,Loyal Customer,62,Personal Travel,Eco,305,2,3,2,3,5,4,3,1,1,2,2,2,1,2,0,9.0,neutral or dissatisfied +11915,62685,Male,Loyal Customer,28,Business travel,Business,2367,3,3,3,3,3,3,3,3,3,4,4,4,4,3,0,0.0,satisfied +11916,97306,Female,disloyal Customer,29,Business travel,Eco,872,4,4,4,4,3,4,5,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +11917,42744,Male,Loyal Customer,36,Personal Travel,Eco Plus,536,3,4,3,3,4,3,4,4,5,5,5,5,5,4,19,13.0,neutral or dissatisfied +11918,38858,Male,Loyal Customer,38,Business travel,Eco,2153,3,4,4,4,3,5,3,3,5,1,3,4,1,3,18,28.0,satisfied +11919,127144,Male,Loyal Customer,58,Personal Travel,Eco,621,3,5,3,4,1,3,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +11920,89586,Male,Loyal Customer,26,Business travel,Business,3101,2,2,2,2,2,2,2,2,5,5,4,3,5,2,17,13.0,satisfied +11921,104976,Female,Loyal Customer,46,Business travel,Business,3345,3,5,5,5,5,4,4,3,3,3,3,2,3,3,18,11.0,neutral or dissatisfied +11922,10773,Female,Loyal Customer,39,Business travel,Business,3454,2,5,5,5,5,4,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +11923,29851,Female,Loyal Customer,61,Business travel,Business,2119,0,4,1,4,5,2,4,4,4,4,4,5,4,3,0,0.0,satisfied +11924,12161,Female,disloyal Customer,30,Business travel,Eco,986,3,2,2,1,3,2,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +11925,1356,Female,Loyal Customer,47,Business travel,Business,3568,2,2,2,2,3,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +11926,25762,Female,Loyal Customer,65,Personal Travel,Eco,356,1,5,1,2,3,5,5,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +11927,39197,Male,Loyal Customer,36,Personal Travel,Eco,318,1,5,1,3,3,1,3,3,4,1,2,1,3,3,0,0.0,neutral or dissatisfied +11928,114596,Female,Loyal Customer,38,Business travel,Business,3680,1,1,1,1,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +11929,45634,Female,disloyal Customer,45,Business travel,Eco,113,2,0,2,3,1,2,1,1,2,4,1,3,5,1,0,27.0,neutral or dissatisfied +11930,88180,Female,Loyal Customer,45,Business travel,Business,3550,1,1,1,1,4,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +11931,19165,Female,Loyal Customer,25,Business travel,Business,304,4,1,1,1,4,3,4,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +11932,62967,Female,Loyal Customer,22,Business travel,Business,3246,5,5,5,5,4,4,4,4,3,4,5,5,4,4,0,0.0,satisfied +11933,106253,Male,Loyal Customer,41,Personal Travel,Business,1500,0,4,0,2,3,4,5,5,5,4,1,5,5,3,0,2.0,satisfied +11934,77493,Male,disloyal Customer,14,Business travel,Eco,989,4,4,4,4,5,4,5,5,2,5,3,4,3,5,0,0.0,neutral or dissatisfied +11935,54972,Male,Loyal Customer,52,Business travel,Business,1334,1,1,1,1,3,4,5,4,4,5,4,3,4,5,7,8.0,satisfied +11936,83138,Male,Loyal Customer,33,Personal Travel,Eco,1127,4,5,4,2,3,4,3,3,5,2,4,4,5,3,0,0.0,neutral or dissatisfied +11937,15504,Male,Loyal Customer,47,Personal Travel,Eco,433,3,5,3,5,4,3,5,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +11938,65125,Female,Loyal Customer,39,Personal Travel,Eco,190,4,2,4,3,5,4,5,5,1,2,3,3,3,5,54,48.0,neutral or dissatisfied +11939,71140,Male,Loyal Customer,29,Business travel,Business,585,3,1,1,1,3,3,3,3,2,5,4,2,4,3,0,0.0,neutral or dissatisfied +11940,124437,Female,disloyal Customer,23,Business travel,Eco,1262,3,3,3,3,2,3,2,2,5,2,4,4,5,2,0,0.0,neutral or dissatisfied +11941,101803,Female,Loyal Customer,26,Business travel,Business,1521,3,4,4,4,3,3,3,3,4,5,3,2,4,3,30,23.0,neutral or dissatisfied +11942,71276,Male,Loyal Customer,47,Personal Travel,Eco,733,3,1,3,3,2,3,2,2,4,2,4,3,3,2,0,0.0,neutral or dissatisfied +11943,120016,Male,Loyal Customer,7,Personal Travel,Eco,328,3,2,3,4,4,3,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +11944,16551,Female,Loyal Customer,39,Business travel,Business,2619,5,5,5,5,4,4,2,4,4,4,4,3,4,3,4,48.0,satisfied +11945,4959,Male,Loyal Customer,46,Business travel,Eco,531,3,2,2,2,3,3,3,3,4,4,3,2,4,3,98,90.0,neutral or dissatisfied +11946,93326,Male,Loyal Customer,56,Business travel,Business,1653,2,2,4,2,3,5,4,5,5,5,5,5,5,3,11,3.0,satisfied +11947,45057,Female,Loyal Customer,58,Business travel,Eco,342,4,5,5,5,3,1,4,4,4,4,4,5,4,5,24,18.0,satisfied +11948,54186,Female,Loyal Customer,10,Personal Travel,Eco,1400,0,1,0,3,4,0,4,4,4,3,3,1,4,4,0,0.0,satisfied +11949,123604,Female,Loyal Customer,59,Personal Travel,Eco,1773,2,3,2,4,2,3,4,2,2,2,2,2,2,1,23,3.0,neutral or dissatisfied +11950,6020,Female,Loyal Customer,48,Business travel,Business,691,2,4,4,4,4,3,3,2,2,2,2,4,2,1,0,7.0,neutral or dissatisfied +11951,7131,Male,Loyal Customer,50,Business travel,Business,1526,2,2,2,2,3,5,5,3,3,4,5,3,3,5,0,22.0,satisfied +11952,36456,Female,Loyal Customer,34,Business travel,Business,3835,3,2,2,2,1,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +11953,62361,Female,Loyal Customer,65,Personal Travel,Eco,1589,2,4,2,1,5,5,5,1,1,2,1,5,1,4,0,4.0,neutral or dissatisfied +11954,12328,Female,Loyal Customer,30,Business travel,Eco,262,3,3,5,5,3,2,3,3,3,2,4,3,4,3,6,0.0,neutral or dissatisfied +11955,64490,Female,disloyal Customer,25,Business travel,Business,247,3,5,3,2,5,3,5,5,5,4,5,3,4,5,46,54.0,neutral or dissatisfied +11956,607,Female,disloyal Customer,27,Business travel,Business,89,4,4,4,3,3,4,3,3,4,3,4,5,4,3,3,21.0,satisfied +11957,125815,Female,disloyal Customer,62,Business travel,Business,920,2,2,2,1,1,2,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +11958,15334,Female,Loyal Customer,8,Personal Travel,Eco,646,4,3,4,4,1,4,1,1,2,2,2,1,5,1,0,0.0,neutral or dissatisfied +11959,14084,Male,disloyal Customer,42,Business travel,Eco,425,2,1,2,3,1,2,1,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +11960,74201,Female,Loyal Customer,22,Business travel,Eco Plus,641,1,5,4,5,1,1,3,1,3,2,3,2,4,1,9,0.0,neutral or dissatisfied +11961,92110,Male,Loyal Customer,44,Personal Travel,Eco,1576,1,5,2,1,5,2,3,5,4,5,4,5,5,5,11,4.0,neutral or dissatisfied +11962,47496,Female,Loyal Customer,18,Personal Travel,Eco,599,4,4,4,5,5,4,5,5,1,3,4,3,4,5,59,59.0,neutral or dissatisfied +11963,105497,Male,Loyal Customer,58,Personal Travel,Eco,516,2,5,2,1,2,2,2,4,2,5,4,2,5,2,181,185.0,neutral or dissatisfied +11964,26943,Female,Loyal Customer,60,Business travel,Eco,2402,2,2,2,2,5,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +11965,54176,Female,Loyal Customer,80,Business travel,Business,3201,2,2,2,2,1,1,1,5,5,5,5,3,5,1,0,0.0,satisfied +11966,120507,Male,Loyal Customer,33,Business travel,Eco Plus,449,4,2,2,2,4,4,4,4,2,3,4,2,5,4,0,0.0,satisfied +11967,117615,Male,Loyal Customer,50,Business travel,Business,2146,1,2,2,2,1,4,4,1,1,1,1,3,1,1,6,0.0,neutral or dissatisfied +11968,41855,Female,disloyal Customer,24,Business travel,Eco,483,3,4,3,4,5,3,3,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +11969,118416,Male,Loyal Customer,46,Business travel,Business,2937,2,2,2,2,5,4,5,5,5,5,5,3,5,5,4,2.0,satisfied +11970,117264,Female,Loyal Customer,49,Personal Travel,Eco,621,2,4,2,1,2,4,5,4,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +11971,32293,Male,Loyal Customer,51,Business travel,Business,101,4,4,4,4,3,2,3,4,4,4,5,4,4,2,0,2.0,satisfied +11972,37473,Male,Loyal Customer,44,Business travel,Business,972,4,4,4,4,5,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +11973,25294,Male,Loyal Customer,23,Personal Travel,Eco,321,4,3,4,5,1,4,1,1,4,3,5,5,3,1,0,0.0,neutral or dissatisfied +11974,53982,Female,Loyal Customer,14,Personal Travel,Eco Plus,1117,3,4,3,1,4,3,4,4,5,4,5,4,5,4,50,26.0,neutral or dissatisfied +11975,81140,Female,Loyal Customer,42,Business travel,Eco Plus,591,4,3,1,1,1,3,2,4,4,4,4,1,4,3,3,0.0,satisfied +11976,44082,Female,Loyal Customer,38,Business travel,Eco Plus,251,2,3,3,3,2,2,2,2,1,1,4,4,3,2,0,8.0,neutral or dissatisfied +11977,83278,Female,Loyal Customer,16,Personal Travel,Eco,1979,2,5,2,3,2,5,3,5,3,1,3,3,2,3,301,304.0,neutral or dissatisfied +11978,33037,Female,Loyal Customer,31,Personal Travel,Eco,101,4,4,4,5,4,4,4,4,5,3,4,5,5,4,0,0.0,satisfied +11979,122386,Female,Loyal Customer,20,Personal Travel,Eco,529,4,4,4,1,2,4,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +11980,95401,Female,Loyal Customer,15,Personal Travel,Eco,192,1,5,1,2,5,1,2,5,5,2,4,5,5,5,5,2.0,neutral or dissatisfied +11981,46178,Female,Loyal Customer,27,Business travel,Eco Plus,627,0,0,0,3,2,0,2,2,2,2,3,1,1,2,83,69.0,satisfied +11982,33137,Male,Loyal Customer,12,Personal Travel,Eco,101,5,4,5,5,3,5,3,3,5,5,5,4,4,3,0,0.0,satisfied +11983,117306,Female,Loyal Customer,85,Business travel,Business,325,1,1,1,1,4,4,4,5,5,4,5,4,5,4,0,0.0,satisfied +11984,44446,Male,Loyal Customer,12,Personal Travel,Eco Plus,420,3,4,3,4,2,3,2,2,4,2,5,5,4,2,0,0.0,neutral or dissatisfied +11985,26650,Male,Loyal Customer,24,Business travel,Business,270,3,4,4,4,3,3,3,3,3,2,4,3,4,3,0,0.0,neutral or dissatisfied +11986,52148,Female,Loyal Customer,41,Business travel,Business,751,3,3,3,3,2,5,5,4,4,4,4,5,4,4,66,56.0,satisfied +11987,1572,Female,disloyal Customer,25,Business travel,Business,140,3,0,3,1,2,3,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +11988,97623,Female,Loyal Customer,51,Business travel,Business,3712,4,4,4,4,3,5,4,4,4,4,4,5,4,4,16,0.0,satisfied +11989,40031,Male,Loyal Customer,19,Personal Travel,Eco,525,2,2,5,3,3,5,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +11990,126540,Female,Loyal Customer,40,Business travel,Business,644,5,5,5,5,2,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +11991,63907,Female,Loyal Customer,60,Business travel,Business,792,3,3,3,3,4,5,3,3,3,4,3,3,3,3,0,0.0,satisfied +11992,46853,Female,Loyal Customer,35,Business travel,Eco,844,3,3,3,3,3,3,3,3,1,3,3,5,4,3,10,1.0,satisfied +11993,6818,Male,Loyal Customer,30,Personal Travel,Eco,224,0,4,0,3,1,0,1,1,3,1,5,5,4,1,3,4.0,satisfied +11994,24058,Male,Loyal Customer,17,Personal Travel,Eco,427,1,4,5,3,3,5,3,3,2,4,3,3,4,3,11,6.0,neutral or dissatisfied +11995,29547,Female,Loyal Customer,43,Business travel,Eco,909,5,1,3,1,1,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +11996,69106,Female,Loyal Customer,47,Business travel,Eco Plus,1389,3,2,2,2,4,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +11997,59464,Female,disloyal Customer,20,Business travel,Eco,758,2,2,2,3,3,2,3,3,5,3,5,3,4,3,9,0.0,neutral or dissatisfied +11998,106760,Male,Loyal Customer,27,Personal Travel,Eco,829,2,4,1,2,4,1,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +11999,29715,Female,disloyal Customer,15,Business travel,Eco,2846,4,3,3,3,5,4,5,5,3,5,5,3,5,5,4,0.0,satisfied +12000,122518,Female,Loyal Customer,41,Business travel,Business,3226,5,4,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +12001,127888,Male,Loyal Customer,38,Business travel,Business,1671,5,5,3,5,3,5,5,3,3,3,3,5,3,3,3,0.0,satisfied +12002,107771,Female,Loyal Customer,52,Business travel,Eco Plus,405,2,4,1,4,1,3,4,3,3,2,3,1,3,4,40,42.0,neutral or dissatisfied +12003,78304,Male,Loyal Customer,33,Personal Travel,Eco,1598,2,5,2,4,1,2,1,1,5,3,5,3,4,1,0,2.0,neutral or dissatisfied +12004,18921,Male,Loyal Customer,26,Personal Travel,Eco,448,2,4,2,1,2,2,2,2,3,2,5,4,5,2,1,0.0,neutral or dissatisfied +12005,96144,Female,Loyal Customer,55,Business travel,Business,3703,3,3,3,3,4,5,4,4,4,5,4,4,4,3,1,15.0,satisfied +12006,28514,Female,Loyal Customer,34,Business travel,Business,2640,3,3,2,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +12007,20194,Female,Loyal Customer,7,Personal Travel,Business,349,2,5,2,5,3,2,3,3,5,2,2,1,5,3,0,0.0,neutral or dissatisfied +12008,6917,Female,Loyal Customer,69,Personal Travel,Eco,265,2,2,0,3,5,2,3,4,4,0,4,2,4,1,0,0.0,neutral or dissatisfied +12009,68224,Female,disloyal Customer,13,Business travel,Eco,631,5,0,5,3,4,5,4,4,3,5,4,4,4,4,0,0.0,satisfied +12010,42667,Male,Loyal Customer,39,Business travel,Business,2926,2,2,2,2,3,1,5,4,4,4,4,1,4,5,50,58.0,satisfied +12011,108110,Male,Loyal Customer,45,Business travel,Business,2796,3,3,3,3,5,4,4,4,4,4,4,5,4,5,72,89.0,satisfied +12012,46986,Female,Loyal Customer,52,Personal Travel,Eco,666,3,4,3,3,3,5,4,1,1,3,5,5,1,3,7,25.0,neutral or dissatisfied +12013,52247,Female,Loyal Customer,58,Business travel,Business,2395,3,2,2,2,3,3,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +12014,14116,Male,Loyal Customer,54,Business travel,Business,413,4,4,4,4,5,4,5,5,5,5,5,5,5,3,0,16.0,satisfied +12015,72181,Male,disloyal Customer,50,Business travel,Eco,594,2,2,2,3,1,2,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +12016,85833,Female,Loyal Customer,44,Personal Travel,Eco,666,3,4,3,5,3,2,2,1,1,3,1,4,1,4,3,33.0,neutral or dissatisfied +12017,13117,Male,Loyal Customer,34,Business travel,Business,1660,3,3,3,3,1,5,5,4,4,4,4,1,4,4,0,0.0,satisfied +12018,113676,Female,Loyal Customer,42,Personal Travel,Eco,386,2,5,2,5,4,2,3,2,2,2,2,5,2,4,0,1.0,neutral or dissatisfied +12019,86668,Male,Loyal Customer,57,Personal Travel,Eco,746,2,4,2,2,4,2,4,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +12020,112842,Male,Loyal Customer,44,Business travel,Business,3848,2,2,2,2,2,4,5,4,4,4,4,3,4,3,74,65.0,satisfied +12021,13420,Male,disloyal Customer,35,Business travel,Eco,409,2,0,2,3,5,2,5,5,1,2,3,4,5,5,0,27.0,neutral or dissatisfied +12022,119243,Female,disloyal Customer,39,Business travel,Business,290,3,3,3,3,2,3,2,2,5,3,5,4,4,2,0,0.0,neutral or dissatisfied +12023,93627,Female,Loyal Customer,39,Business travel,Business,177,1,3,4,3,4,3,4,1,1,1,1,4,1,2,19,24.0,neutral or dissatisfied +12024,33876,Male,Loyal Customer,37,Business travel,Eco,1105,5,5,3,5,5,5,5,5,5,2,5,1,2,5,4,1.0,satisfied +12025,7657,Male,Loyal Customer,35,Business travel,Business,3723,2,2,2,2,5,4,4,3,3,3,3,4,3,5,26,11.0,satisfied +12026,48522,Female,Loyal Customer,49,Business travel,Business,2860,2,2,2,2,4,2,4,4,4,4,4,2,4,4,0,0.0,satisfied +12027,2858,Female,Loyal Customer,36,Business travel,Business,3655,2,1,2,2,3,4,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +12028,54846,Male,Loyal Customer,41,Business travel,Business,1900,3,2,3,3,2,4,5,5,5,5,5,5,5,4,11,14.0,satisfied +12029,7094,Female,Loyal Customer,37,Business travel,Eco,157,4,1,5,5,4,4,4,4,4,3,2,1,3,4,0,0.0,satisfied +12030,75505,Female,Loyal Customer,69,Personal Travel,Eco Plus,2585,2,5,2,5,3,4,4,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +12031,58407,Female,Loyal Customer,62,Business travel,Business,733,1,5,5,5,1,3,4,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +12032,69765,Male,Loyal Customer,63,Personal Travel,Eco,1085,1,4,1,3,3,1,4,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +12033,102421,Male,Loyal Customer,23,Personal Travel,Eco,197,2,4,2,4,1,2,1,1,1,2,4,1,3,1,1,0.0,neutral or dissatisfied +12034,95066,Male,Loyal Customer,17,Personal Travel,Eco,239,2,4,2,1,4,2,4,4,4,5,4,3,1,4,0,0.0,neutral or dissatisfied +12035,20821,Female,disloyal Customer,9,Business travel,Eco,508,5,3,5,5,5,5,5,5,2,3,1,3,2,5,0,0.0,satisfied +12036,74580,Female,disloyal Customer,25,Business travel,Business,1431,4,5,4,3,5,4,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +12037,14188,Female,disloyal Customer,23,Business travel,Eco,620,4,5,4,4,3,4,3,3,2,1,4,5,3,3,0,0.0,satisfied +12038,13458,Female,Loyal Customer,21,Personal Travel,Eco,409,3,4,3,1,3,3,3,3,1,1,4,2,3,3,71,83.0,neutral or dissatisfied +12039,55597,Male,Loyal Customer,45,Business travel,Business,404,5,5,5,5,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +12040,49388,Male,disloyal Customer,36,Business travel,Eco,158,3,0,3,1,5,3,1,5,3,4,1,4,1,5,0,17.0,neutral or dissatisfied +12041,121117,Male,Loyal Customer,52,Business travel,Business,2370,4,4,4,4,4,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +12042,28287,Male,Loyal Customer,39,Business travel,Business,3887,4,4,4,4,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +12043,100760,Male,Loyal Customer,37,Business travel,Business,1411,4,4,4,4,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +12044,5330,Male,Loyal Customer,31,Personal Travel,Business,812,3,1,3,4,5,3,2,5,2,5,3,2,3,5,0,0.0,neutral or dissatisfied +12045,70494,Female,Loyal Customer,42,Business travel,Eco,867,4,2,2,2,5,1,3,5,5,4,5,1,5,5,0,0.0,satisfied +12046,44300,Male,disloyal Customer,36,Business travel,Eco,1428,2,2,2,1,3,2,3,3,3,3,5,4,5,3,5,19.0,neutral or dissatisfied +12047,3692,Male,Loyal Customer,37,Business travel,Business,2327,1,2,2,2,5,4,4,1,1,1,1,3,1,1,53,62.0,neutral or dissatisfied +12048,124747,Female,disloyal Customer,25,Business travel,Business,280,4,0,4,2,4,4,5,4,5,3,4,3,5,4,0,0.0,satisfied +12049,119389,Female,Loyal Customer,50,Business travel,Business,2994,2,5,2,2,5,5,5,4,4,4,4,3,4,5,8,15.0,satisfied +12050,7702,Male,Loyal Customer,57,Personal Travel,Eco,604,4,4,4,3,3,4,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +12051,63419,Male,Loyal Customer,24,Personal Travel,Eco,337,3,5,5,4,5,5,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +12052,53663,Male,Loyal Customer,51,Personal Travel,Business,1208,3,3,3,3,3,3,1,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +12053,39261,Male,disloyal Customer,29,Business travel,Eco,67,4,3,4,2,2,4,2,2,3,4,4,1,5,2,0,0.0,neutral or dissatisfied +12054,12292,Male,Loyal Customer,38,Business travel,Eco,383,5,4,4,4,5,5,5,5,4,4,5,5,2,5,40,36.0,satisfied +12055,127681,Female,Loyal Customer,55,Business travel,Business,1773,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +12056,42693,Female,Loyal Customer,9,Personal Travel,Eco,516,2,4,2,4,2,2,2,2,5,3,4,3,4,2,0,12.0,neutral or dissatisfied +12057,10632,Female,Loyal Customer,50,Business travel,Business,140,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +12058,1591,Male,Loyal Customer,61,Personal Travel,Eco,140,4,0,4,5,2,4,2,2,3,5,5,4,5,2,33,25.0,neutral or dissatisfied +12059,79306,Female,Loyal Customer,34,Business travel,Business,2248,3,1,3,3,5,5,5,4,5,3,5,5,3,5,5,4.0,satisfied +12060,112402,Male,disloyal Customer,22,Business travel,Eco,850,3,2,2,4,3,2,3,3,4,2,4,5,4,3,124,126.0,neutral or dissatisfied +12061,52481,Male,Loyal Customer,33,Personal Travel,Eco Plus,451,5,4,5,4,4,5,4,4,4,3,4,4,3,4,0,0.0,satisfied +12062,100676,Female,Loyal Customer,42,Business travel,Business,889,3,3,3,3,2,5,5,5,5,4,5,5,5,3,28,28.0,satisfied +12063,3394,Male,disloyal Customer,20,Business travel,Business,296,5,0,5,3,1,5,1,1,4,2,5,4,4,1,0,0.0,satisfied +12064,49134,Female,disloyal Customer,21,Business travel,Eco,156,3,0,3,3,3,3,2,3,4,5,3,5,1,3,0,0.0,neutral or dissatisfied +12065,68466,Female,Loyal Customer,51,Business travel,Business,3906,1,1,1,1,2,5,4,3,3,4,3,4,3,5,0,0.0,satisfied +12066,40170,Male,Loyal Customer,31,Business travel,Business,1533,4,4,4,4,5,5,5,5,5,5,1,2,3,5,0,0.0,satisfied +12067,118657,Female,Loyal Customer,45,Business travel,Business,3951,3,5,5,5,5,3,2,3,3,3,3,1,3,3,17,24.0,neutral or dissatisfied +12068,28848,Male,Loyal Customer,46,Business travel,Eco,987,2,5,5,5,3,2,3,3,3,5,4,5,3,3,0,0.0,satisfied +12069,75592,Female,Loyal Customer,44,Business travel,Eco,337,4,1,1,1,2,1,1,4,4,4,4,5,4,3,22,22.0,satisfied +12070,119980,Male,Loyal Customer,14,Personal Travel,Eco,868,2,4,2,3,4,2,4,4,1,2,4,3,4,4,0,11.0,neutral or dissatisfied +12071,20284,Female,Loyal Customer,18,Personal Travel,Eco,179,2,1,0,2,2,0,2,2,3,1,3,4,3,2,0,19.0,neutral or dissatisfied +12072,47507,Female,Loyal Customer,53,Personal Travel,Eco,558,3,2,3,4,4,3,3,2,2,3,2,1,2,2,0,0.0,neutral or dissatisfied +12073,62206,Female,Loyal Customer,42,Personal Travel,Eco,2454,2,4,2,3,4,4,4,4,4,2,4,5,4,5,31,35.0,neutral or dissatisfied +12074,101920,Male,Loyal Customer,9,Business travel,Eco Plus,2039,2,2,2,2,2,2,3,2,4,1,3,3,3,2,7,0.0,neutral or dissatisfied +12075,14921,Male,Loyal Customer,53,Business travel,Eco Plus,296,4,5,5,5,4,4,4,4,4,4,4,3,4,4,13,11.0,satisfied +12076,67398,Female,disloyal Customer,30,Business travel,Eco,769,1,1,1,3,4,1,4,4,1,3,4,3,3,4,48,34.0,neutral or dissatisfied +12077,103726,Female,Loyal Customer,34,Personal Travel,Eco,405,4,4,4,4,4,4,4,4,3,3,4,3,5,4,0,0.0,neutral or dissatisfied +12078,125772,Male,Loyal Customer,39,Business travel,Business,2629,3,3,3,3,5,4,4,4,4,5,4,3,4,3,0,17.0,satisfied +12079,65187,Male,Loyal Customer,18,Personal Travel,Eco,282,4,4,4,3,1,4,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +12080,18615,Male,Loyal Customer,7,Personal Travel,Eco,201,2,4,2,2,2,2,2,2,1,1,2,5,2,2,0,0.0,neutral or dissatisfied +12081,117089,Male,Loyal Customer,60,Business travel,Eco,646,1,3,3,3,1,1,1,1,1,2,4,3,4,1,42,39.0,neutral or dissatisfied +12082,86030,Male,Loyal Customer,19,Personal Travel,Eco,432,4,5,4,1,2,4,2,2,4,5,4,2,5,2,0,0.0,neutral or dissatisfied +12083,68919,Male,Loyal Customer,29,Personal Travel,Eco,936,5,5,5,3,2,5,2,2,2,1,1,4,4,2,0,0.0,satisfied +12084,112263,Female,Loyal Customer,50,Business travel,Business,1447,4,4,4,4,2,5,5,4,4,4,4,3,4,5,43,37.0,satisfied +12085,116926,Female,Loyal Customer,59,Business travel,Business,2597,2,1,1,1,4,2,2,2,2,2,2,2,2,2,30,24.0,neutral or dissatisfied +12086,73983,Female,Loyal Customer,49,Business travel,Eco Plus,2585,2,4,4,4,2,2,2,3,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +12087,39012,Female,Loyal Customer,38,Business travel,Eco,391,4,4,4,4,4,4,4,4,5,3,2,4,1,4,0,0.0,satisfied +12088,70682,Female,Loyal Customer,49,Personal Travel,Eco,447,2,5,1,1,4,1,4,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +12089,23972,Male,Loyal Customer,35,Business travel,Eco,596,1,4,4,4,1,1,1,1,4,1,4,4,4,1,0,0.0,neutral or dissatisfied +12090,120617,Male,disloyal Customer,27,Business travel,Business,280,5,5,5,2,4,5,4,4,3,2,4,5,4,4,36,35.0,satisfied +12091,8929,Male,Loyal Customer,51,Business travel,Eco,984,2,1,1,1,2,2,2,2,2,5,2,3,3,2,7,0.0,neutral or dissatisfied +12092,53146,Male,Loyal Customer,21,Personal Travel,Eco,413,3,5,5,2,1,5,1,1,4,4,5,5,4,1,86,68.0,neutral or dissatisfied +12093,120296,Male,disloyal Customer,23,Business travel,Eco,268,2,0,2,1,4,2,5,4,4,3,5,4,4,4,0,11.0,neutral or dissatisfied +12094,104154,Male,disloyal Customer,58,Business travel,Business,349,1,1,1,4,4,1,2,4,2,2,3,2,3,4,0,0.0,neutral or dissatisfied +12095,38199,Female,Loyal Customer,41,Business travel,Eco Plus,1010,5,5,5,5,2,2,3,4,4,5,4,4,4,1,0,0.0,satisfied +12096,29234,Male,Loyal Customer,41,Business travel,Eco,873,4,5,3,5,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +12097,33492,Male,Loyal Customer,50,Personal Travel,Eco,2496,3,5,3,4,1,3,3,1,5,3,3,3,5,1,4,0.0,neutral or dissatisfied +12098,11942,Female,Loyal Customer,9,Business travel,Eco,781,1,3,3,3,1,1,2,1,1,2,4,4,3,1,0,5.0,neutral or dissatisfied +12099,48360,Male,disloyal Customer,23,Business travel,Eco,674,3,3,3,3,1,3,2,1,2,5,4,2,3,1,0,2.0,neutral or dissatisfied +12100,74251,Female,Loyal Customer,67,Business travel,Business,1709,2,4,4,4,1,2,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +12101,128936,Female,Loyal Customer,41,Business travel,Business,2273,3,3,1,3,3,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +12102,12200,Male,Loyal Customer,47,Business travel,Business,201,0,5,0,5,3,5,5,5,5,5,5,3,5,4,8,5.0,satisfied +12103,16161,Male,Loyal Customer,36,Business travel,Business,3801,4,4,4,4,3,3,1,5,5,5,5,1,5,2,0,0.0,satisfied +12104,28036,Female,Loyal Customer,45,Business travel,Business,2537,3,3,3,3,1,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +12105,108580,Male,disloyal Customer,25,Business travel,Business,696,4,0,4,3,5,4,5,5,4,4,4,4,5,5,14,19.0,neutral or dissatisfied +12106,58815,Female,Loyal Customer,67,Personal Travel,Eco,1012,2,1,1,2,2,1,2,4,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +12107,96924,Male,Loyal Customer,49,Business travel,Business,3225,3,3,2,3,4,5,4,5,5,5,5,5,5,5,1,0.0,satisfied +12108,118599,Male,disloyal Customer,40,Business travel,Business,370,1,1,1,2,4,1,5,4,3,2,4,5,4,4,6,0.0,neutral or dissatisfied +12109,18126,Female,Loyal Customer,80,Business travel,Eco,120,3,4,4,4,2,3,3,3,3,3,3,2,3,1,76,64.0,neutral or dissatisfied +12110,7682,Male,Loyal Customer,57,Business travel,Eco,204,4,2,2,2,4,4,4,4,5,2,2,2,3,4,0,0.0,satisfied +12111,81795,Female,disloyal Customer,28,Business travel,Eco,950,2,2,2,4,3,2,3,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +12112,100694,Male,Loyal Customer,70,Personal Travel,Eco,677,1,1,1,3,4,1,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +12113,37496,Female,Loyal Customer,41,Business travel,Eco,1028,1,3,3,3,1,1,1,1,3,2,2,4,2,1,0,0.0,neutral or dissatisfied +12114,69834,Female,disloyal Customer,36,Business travel,Eco,945,1,1,1,3,1,1,1,1,2,5,5,1,1,1,0,0.0,neutral or dissatisfied +12115,56283,Female,Loyal Customer,49,Business travel,Business,2227,3,3,3,3,5,5,4,4,4,4,4,3,4,5,21,16.0,satisfied +12116,120260,Female,disloyal Customer,39,Business travel,Business,237,4,4,4,2,3,4,3,3,4,4,5,4,5,3,0,0.0,satisfied +12117,38693,Male,Loyal Customer,28,Business travel,Business,2342,5,5,4,5,5,5,5,5,1,1,3,5,4,5,21,9.0,satisfied +12118,61101,Male,Loyal Customer,24,Personal Travel,Eco,1506,3,2,3,3,5,3,5,5,2,5,3,2,3,5,0,1.0,neutral or dissatisfied +12119,46561,Male,Loyal Customer,43,Business travel,Business,125,0,4,0,1,1,1,1,3,5,3,2,1,4,1,142,148.0,satisfied +12120,104668,Male,Loyal Customer,30,Personal Travel,Eco,641,3,5,2,3,5,2,2,5,3,3,2,2,3,5,27,14.0,neutral or dissatisfied +12121,94085,Female,disloyal Customer,24,Business travel,Eco,189,2,0,3,2,3,3,3,3,4,3,4,4,5,3,1,0.0,neutral or dissatisfied +12122,20251,Male,Loyal Customer,67,Business travel,Business,2895,4,5,5,5,4,4,3,2,2,2,4,4,2,3,20,14.0,neutral or dissatisfied +12123,17185,Female,Loyal Customer,48,Personal Travel,Eco,643,3,5,3,1,3,4,5,2,2,3,2,4,2,5,9,20.0,neutral or dissatisfied +12124,110133,Male,Loyal Customer,51,Business travel,Business,1523,2,2,2,2,4,5,5,5,5,5,5,5,5,3,2,5.0,satisfied +12125,94226,Male,Loyal Customer,57,Business travel,Business,1761,1,1,1,1,4,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +12126,120546,Female,Loyal Customer,37,Business travel,Business,2176,3,3,3,3,3,5,4,4,4,4,4,3,4,3,118,112.0,satisfied +12127,95372,Male,Loyal Customer,55,Personal Travel,Eco,528,2,4,2,2,1,2,1,1,3,4,4,3,4,1,30,17.0,neutral or dissatisfied +12128,17147,Female,Loyal Customer,24,Business travel,Business,926,4,4,4,4,2,2,2,2,3,4,2,5,2,2,0,0.0,satisfied +12129,31115,Male,Loyal Customer,27,Business travel,Eco,991,4,3,3,3,4,4,4,4,5,3,4,4,5,4,0,0.0,satisfied +12130,120934,Male,disloyal Customer,29,Business travel,Business,992,3,3,3,3,5,3,5,5,4,5,5,5,5,5,0,0.0,neutral or dissatisfied +12131,79536,Male,Loyal Customer,52,Business travel,Business,712,1,1,1,1,4,4,4,5,5,5,5,4,5,4,0,17.0,satisfied +12132,116302,Female,Loyal Customer,69,Personal Travel,Eco,358,1,3,4,3,1,2,2,4,4,4,1,1,4,1,13,15.0,neutral or dissatisfied +12133,66125,Female,disloyal Customer,34,Business travel,Eco,583,2,0,3,1,4,3,4,4,4,2,3,3,3,4,0,0.0,neutral or dissatisfied +12134,122403,Female,Loyal Customer,10,Personal Travel,Eco Plus,529,1,4,1,3,1,1,1,1,4,2,5,5,5,1,8,7.0,neutral or dissatisfied +12135,45819,Female,Loyal Customer,65,Personal Travel,Eco,517,3,5,3,2,3,5,4,1,1,3,1,3,1,5,0,0.0,neutral or dissatisfied +12136,68624,Female,disloyal Customer,37,Business travel,Business,237,2,1,1,2,4,1,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +12137,21687,Female,disloyal Customer,24,Business travel,Eco,746,4,3,3,3,5,3,5,5,3,3,4,2,3,5,71,48.0,neutral or dissatisfied +12138,88026,Female,Loyal Customer,55,Business travel,Business,3627,3,3,3,3,3,5,5,3,3,4,3,4,3,4,5,0.0,satisfied +12139,40211,Male,Loyal Customer,33,Business travel,Business,3133,2,2,5,2,4,4,4,4,2,2,1,2,2,4,0,12.0,satisfied +12140,29936,Male,Loyal Customer,33,Business travel,Business,234,1,3,4,3,1,1,1,1,4,4,4,3,4,1,30,28.0,neutral or dissatisfied +12141,74192,Female,Loyal Customer,52,Personal Travel,Eco,721,4,5,4,2,2,5,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +12142,101568,Female,Loyal Customer,26,Personal Travel,Eco Plus,345,2,3,2,4,3,2,3,3,3,5,4,3,4,3,32,14.0,neutral or dissatisfied +12143,109595,Female,Loyal Customer,53,Business travel,Business,2456,5,5,5,5,3,4,4,5,5,5,5,5,5,4,75,85.0,satisfied +12144,64905,Male,Loyal Customer,33,Business travel,Business,2566,4,4,5,5,4,4,4,4,1,4,3,1,4,4,0,0.0,neutral or dissatisfied +12145,87057,Female,Loyal Customer,47,Business travel,Business,1792,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +12146,1482,Male,Loyal Customer,14,Personal Travel,Business,737,4,3,4,1,1,4,1,1,2,3,1,1,5,1,0,3.0,neutral or dissatisfied +12147,28735,Male,Loyal Customer,28,Business travel,Business,2033,2,2,2,2,5,5,5,5,3,5,5,5,4,5,0,5.0,satisfied +12148,60228,Male,disloyal Customer,35,Business travel,Eco,991,3,3,3,4,1,3,1,1,2,4,3,4,4,1,0,8.0,neutral or dissatisfied +12149,19206,Female,disloyal Customer,26,Business travel,Eco,459,3,5,3,3,3,3,3,3,4,3,3,2,5,3,0,13.0,neutral or dissatisfied +12150,90770,Female,Loyal Customer,43,Business travel,Business,3432,1,1,1,1,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +12151,78971,Male,Loyal Customer,49,Business travel,Business,2751,1,1,1,1,4,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +12152,49325,Female,Loyal Customer,39,Business travel,Business,89,3,3,2,3,3,1,3,5,5,5,3,4,5,2,5,7.0,satisfied +12153,7693,Male,Loyal Customer,24,Personal Travel,Eco,604,3,5,4,4,4,4,3,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +12154,99640,Female,Loyal Customer,61,Personal Travel,Business,1670,3,0,4,2,2,4,1,4,4,4,3,5,4,1,0,0.0,neutral or dissatisfied +12155,58601,Female,Loyal Customer,31,Personal Travel,Eco,334,4,5,4,2,4,4,4,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +12156,52787,Female,Loyal Customer,39,Business travel,Eco,1874,3,1,1,1,3,3,3,3,2,5,3,3,2,3,0,0.0,neutral or dissatisfied +12157,48535,Male,disloyal Customer,63,Business travel,Eco,453,4,0,4,1,1,4,1,1,4,1,5,2,3,1,105,100.0,neutral or dissatisfied +12158,78832,Female,Loyal Customer,44,Personal Travel,Eco,447,3,5,3,4,5,5,5,3,3,3,3,5,3,4,14,23.0,neutral or dissatisfied +12159,42093,Male,Loyal Customer,24,Business travel,Eco,964,4,3,3,3,4,4,5,4,3,3,1,1,2,4,0,0.0,satisfied +12160,59098,Male,Loyal Customer,66,Personal Travel,Eco,1846,3,2,4,3,4,4,4,4,1,1,3,1,3,4,7,7.0,neutral or dissatisfied +12161,618,Male,disloyal Customer,27,Business travel,Business,140,0,0,0,4,5,0,5,5,4,5,5,5,5,5,0,0.0,satisfied +12162,66852,Male,Loyal Customer,45,Personal Travel,Eco,731,1,5,1,4,4,1,4,4,1,4,2,3,1,4,0,0.0,neutral or dissatisfied +12163,119968,Female,Loyal Customer,46,Personal Travel,Eco,868,1,5,1,5,1,4,4,5,5,1,5,1,5,1,1,15.0,neutral or dissatisfied +12164,85797,Male,Loyal Customer,38,Business travel,Business,3434,2,3,2,2,5,3,3,3,3,3,2,2,3,3,25,39.0,neutral or dissatisfied +12165,33900,Female,Loyal Customer,61,Personal Travel,Eco,1226,1,3,1,3,3,5,2,1,1,1,1,5,1,1,0,0.0,neutral or dissatisfied +12166,102700,Male,Loyal Customer,53,Business travel,Business,2511,1,1,1,1,3,5,4,5,5,5,5,4,5,5,2,0.0,satisfied +12167,67542,Male,Loyal Customer,19,Personal Travel,Business,1313,2,5,2,1,4,2,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +12168,65713,Male,Loyal Customer,68,Business travel,Business,1061,3,4,4,4,5,3,2,3,3,3,3,3,3,3,23,10.0,neutral or dissatisfied +12169,82978,Female,Loyal Customer,58,Business travel,Business,3591,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +12170,112174,Male,Loyal Customer,41,Personal Travel,Eco,895,1,4,1,5,3,1,3,3,4,3,5,4,4,3,50,49.0,neutral or dissatisfied +12171,7564,Female,Loyal Customer,38,Personal Travel,Eco Plus,606,1,5,1,2,4,1,4,4,5,2,4,3,4,4,87,109.0,neutral or dissatisfied +12172,77653,Female,Loyal Customer,50,Business travel,Business,3421,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +12173,12683,Male,Loyal Customer,22,Business travel,Business,689,5,5,5,5,4,4,4,4,5,5,4,4,5,4,10,0.0,satisfied +12174,108928,Male,Loyal Customer,66,Personal Travel,Eco,1075,0,5,0,4,5,0,5,5,4,5,4,2,2,5,5,5.0,satisfied +12175,105386,Male,Loyal Customer,33,Business travel,Business,3360,2,2,5,2,4,4,4,4,2,5,2,5,5,4,0,0.0,satisfied +12176,6345,Male,Loyal Customer,51,Business travel,Business,3471,0,0,0,2,5,5,5,4,4,4,4,3,4,5,67,82.0,satisfied +12177,65106,Female,Loyal Customer,56,Personal Travel,Eco,469,3,4,3,2,3,5,5,5,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +12178,38075,Female,Loyal Customer,35,Business travel,Eco,1121,5,4,4,4,5,5,5,5,3,2,4,4,1,5,9,4.0,satisfied +12179,19247,Female,Loyal Customer,13,Personal Travel,Eco,782,3,4,3,1,5,3,5,5,5,4,4,5,4,5,79,79.0,neutral or dissatisfied +12180,5551,Female,Loyal Customer,50,Personal Travel,Eco Plus,431,4,5,4,3,2,4,4,2,2,4,2,4,2,5,0,15.0,neutral or dissatisfied +12181,82268,Female,disloyal Customer,22,Business travel,Eco,1203,3,3,3,3,5,3,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +12182,89325,Male,Loyal Customer,46,Business travel,Business,1541,2,2,2,2,3,4,5,5,5,5,5,4,5,3,7,12.0,satisfied +12183,87770,Female,Loyal Customer,32,Business travel,Business,2397,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +12184,78491,Female,Loyal Customer,28,Business travel,Business,666,2,5,5,5,2,2,2,2,2,4,3,1,2,2,0,9.0,neutral or dissatisfied +12185,80619,Male,Loyal Customer,36,Personal Travel,Eco,236,2,4,2,4,3,2,3,3,3,3,5,4,4,3,0,2.0,neutral or dissatisfied +12186,91514,Female,Loyal Customer,15,Business travel,Business,1620,1,1,1,1,4,4,4,4,4,2,1,3,2,4,9,0.0,satisfied +12187,68983,Female,disloyal Customer,8,Business travel,Eco,700,3,3,3,3,5,3,5,5,2,2,3,1,3,5,0,0.0,neutral or dissatisfied +12188,437,Male,Loyal Customer,46,Personal Travel,Business,134,3,4,3,2,4,5,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +12189,95891,Male,Loyal Customer,59,Personal Travel,Eco,580,1,5,2,4,2,2,2,2,4,4,5,3,4,2,10,0.0,neutral or dissatisfied +12190,46598,Female,Loyal Customer,55,Business travel,Business,3122,3,1,1,1,5,4,4,3,3,3,3,3,3,4,3,0.0,neutral or dissatisfied +12191,45780,Male,Loyal Customer,25,Business travel,Business,3036,3,1,1,1,3,3,3,3,2,1,2,1,3,3,6,7.0,neutral or dissatisfied +12192,100049,Female,Loyal Customer,50,Personal Travel,Eco,281,3,5,3,1,4,3,1,2,2,3,2,1,2,3,14,10.0,neutral or dissatisfied +12193,94971,Male,Loyal Customer,55,Business travel,Business,2988,4,5,5,5,4,3,3,2,2,2,4,2,2,1,3,0.0,neutral or dissatisfied +12194,20332,Female,Loyal Customer,54,Business travel,Eco,265,4,4,4,4,4,5,2,4,4,4,4,5,4,1,0,0.0,satisfied +12195,108453,Female,disloyal Customer,17,Business travel,Eco,1444,3,3,3,1,1,3,1,1,5,2,4,3,1,1,21,5.0,neutral or dissatisfied +12196,107349,Female,Loyal Customer,25,Business travel,Business,1910,2,2,2,2,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +12197,9275,Female,Loyal Customer,51,Business travel,Business,2846,1,1,1,1,3,4,4,2,2,3,2,4,2,5,11,0.0,satisfied +12198,65211,Male,Loyal Customer,33,Business travel,Business,190,1,1,1,1,5,5,5,5,3,2,4,4,5,5,5,2.0,satisfied +12199,97629,Female,Loyal Customer,22,Business travel,Business,2871,4,3,4,4,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +12200,49667,Female,Loyal Customer,35,Business travel,Eco,89,3,4,4,4,3,3,3,3,1,4,3,1,4,3,46,55.0,neutral or dissatisfied +12201,95288,Female,Loyal Customer,61,Personal Travel,Eco,319,1,4,1,4,5,3,3,3,3,1,3,1,3,2,0,0.0,neutral or dissatisfied +12202,49625,Male,Loyal Customer,50,Business travel,Eco,209,5,1,1,1,5,5,5,5,4,5,3,2,1,5,15,16.0,satisfied +12203,28919,Female,Loyal Customer,31,Business travel,Business,1050,3,4,4,4,3,3,3,3,1,1,4,4,3,3,0,2.0,neutral or dissatisfied +12204,43001,Male,disloyal Customer,24,Business travel,Business,236,5,5,5,4,1,5,1,1,3,2,2,4,1,1,0,0.0,satisfied +12205,55563,Male,Loyal Customer,34,Personal Travel,Eco Plus,550,2,0,2,5,2,2,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +12206,124862,Male,Loyal Customer,41,Business travel,Business,2254,2,2,2,2,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +12207,117371,Male,Loyal Customer,46,Business travel,Business,2394,2,2,3,2,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +12208,94349,Male,Loyal Customer,37,Business travel,Business,239,1,1,4,1,3,4,5,4,4,4,4,4,4,5,3,12.0,satisfied +12209,38954,Female,disloyal Customer,62,Business travel,Eco Plus,320,3,3,3,3,1,3,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +12210,12531,Male,disloyal Customer,45,Business travel,Eco,788,2,2,2,4,2,2,1,2,4,4,5,1,1,2,0,0.0,neutral or dissatisfied +12211,43780,Female,Loyal Customer,19,Personal Travel,Eco,386,2,5,2,4,4,2,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +12212,116094,Male,Loyal Customer,32,Personal Travel,Eco,308,2,2,2,2,3,2,3,3,4,1,3,3,3,3,97,89.0,neutral or dissatisfied +12213,27507,Female,Loyal Customer,33,Business travel,Business,978,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +12214,41602,Male,Loyal Customer,36,Personal Travel,Eco,1504,4,5,4,5,1,4,1,1,3,5,3,3,5,1,3,8.0,neutral or dissatisfied +12215,87971,Male,disloyal Customer,44,Business travel,Business,442,5,5,5,1,4,5,5,4,3,3,4,5,4,4,0,0.0,satisfied +12216,63083,Female,Loyal Customer,25,Personal Travel,Eco,967,4,4,4,2,4,4,3,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +12217,51674,Female,disloyal Customer,12,Business travel,Eco,651,1,0,1,3,4,1,4,4,5,5,1,4,3,4,0,0.0,neutral or dissatisfied +12218,84417,Male,Loyal Customer,8,Personal Travel,Eco,606,1,4,1,2,3,1,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +12219,50771,Male,Loyal Customer,18,Personal Travel,Eco,308,4,4,4,2,5,4,5,5,5,3,4,3,4,5,0,0.0,satisfied +12220,22502,Female,Loyal Customer,8,Personal Travel,Eco,83,2,4,2,1,1,2,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +12221,22569,Male,Loyal Customer,38,Business travel,Business,646,4,4,4,4,4,2,5,5,5,5,5,1,5,3,5,2.0,satisfied +12222,113650,Female,Loyal Customer,62,Personal Travel,Eco,258,4,5,0,5,4,4,2,4,4,0,4,5,4,5,0,0.0,neutral or dissatisfied +12223,86644,Female,disloyal Customer,24,Business travel,Eco,346,1,0,2,3,3,2,3,3,4,3,4,5,4,3,0,4.0,neutral or dissatisfied +12224,18628,Male,Loyal Customer,50,Personal Travel,Eco,253,1,2,1,3,5,1,5,5,3,4,4,1,3,5,0,4.0,neutral or dissatisfied +12225,106178,Female,Loyal Customer,16,Personal Travel,Eco,444,2,5,3,4,5,3,5,5,4,2,5,5,4,5,50,55.0,neutral or dissatisfied +12226,77392,Male,Loyal Customer,17,Personal Travel,Eco,584,3,4,3,4,2,3,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +12227,125077,Male,Loyal Customer,41,Business travel,Business,361,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +12228,27352,Male,Loyal Customer,35,Business travel,Business,3870,2,1,1,1,3,3,3,2,2,2,2,1,2,3,9,0.0,neutral or dissatisfied +12229,50419,Male,disloyal Customer,24,Business travel,Eco,110,5,0,4,4,3,4,3,3,2,1,3,1,1,3,7,0.0,satisfied +12230,4105,Female,Loyal Customer,24,Business travel,Business,2048,2,2,5,2,4,4,4,4,5,3,5,3,4,4,0,25.0,satisfied +12231,117726,Female,Loyal Customer,41,Business travel,Eco,833,3,2,2,2,2,3,2,2,3,4,4,1,3,2,0,0.0,neutral or dissatisfied +12232,18542,Female,Loyal Customer,59,Business travel,Business,2381,3,1,1,1,1,3,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +12233,26927,Male,Loyal Customer,31,Personal Travel,Eco,1770,1,3,1,4,3,1,1,3,3,4,3,4,3,3,50,21.0,neutral or dissatisfied +12234,26334,Male,Loyal Customer,27,Business travel,Business,2230,1,1,1,1,4,4,4,4,2,4,3,5,2,4,0,0.0,satisfied +12235,62770,Male,disloyal Customer,13,Business travel,Eco,2367,3,3,3,4,1,3,1,1,1,2,3,2,4,1,77,68.0,neutral or dissatisfied +12236,12627,Male,Loyal Customer,58,Business travel,Business,844,1,1,1,1,3,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +12237,11805,Female,Loyal Customer,7,Personal Travel,Eco Plus,429,3,3,3,3,5,3,5,5,5,2,2,5,4,5,2,10.0,neutral or dissatisfied +12238,52352,Male,Loyal Customer,54,Personal Travel,Eco,493,1,5,1,3,3,1,3,3,4,4,4,4,5,3,0,25.0,neutral or dissatisfied +12239,128102,Male,Loyal Customer,39,Business travel,Business,2860,3,3,3,3,4,4,4,3,2,4,5,4,4,4,46,69.0,satisfied +12240,22263,Female,Loyal Customer,41,Business travel,Business,1671,1,1,1,1,2,1,3,5,5,4,5,2,5,2,0,0.0,satisfied +12241,85070,Female,Loyal Customer,55,Business travel,Business,731,2,2,2,2,3,4,4,4,4,4,4,5,4,3,119,122.0,satisfied +12242,112297,Male,Loyal Customer,56,Business travel,Business,1671,3,3,3,3,4,3,5,1,1,2,1,5,1,4,25,4.0,satisfied +12243,58905,Male,disloyal Customer,29,Business travel,Eco,888,3,3,3,3,4,3,4,4,3,2,4,2,4,4,1,0.0,neutral or dissatisfied +12244,59218,Male,Loyal Customer,57,Personal Travel,Eco,1440,1,5,1,5,4,1,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +12245,113778,Female,Loyal Customer,57,Personal Travel,Eco,236,4,4,4,1,5,4,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +12246,47197,Female,Loyal Customer,52,Business travel,Business,554,2,1,1,1,3,3,4,2,2,2,2,2,2,1,15,23.0,neutral or dissatisfied +12247,55995,Female,Loyal Customer,27,Business travel,Business,2586,3,3,3,3,4,5,5,4,5,4,4,5,3,5,0,0.0,satisfied +12248,117318,Male,Loyal Customer,64,Personal Travel,Eco Plus,651,2,4,2,3,2,2,2,2,1,2,3,2,4,2,43,32.0,neutral or dissatisfied +12249,7082,Female,Loyal Customer,58,Business travel,Eco,273,2,3,3,3,4,2,2,2,2,2,2,1,2,1,36,39.0,neutral or dissatisfied +12250,30611,Male,Loyal Customer,54,Personal Travel,Eco,472,3,4,3,3,3,3,3,3,3,2,5,5,5,3,0,0.0,neutral or dissatisfied +12251,70152,Female,Loyal Customer,19,Personal Travel,Eco,550,3,2,3,4,1,3,1,1,4,2,2,1,4,1,0,0.0,neutral or dissatisfied +12252,57849,Male,Loyal Customer,41,Business travel,Business,2329,1,1,1,1,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +12253,44690,Female,disloyal Customer,15,Business travel,Eco,268,4,0,4,4,3,4,3,3,4,2,5,1,5,3,0,0.0,neutral or dissatisfied +12254,69986,Male,Loyal Customer,35,Business travel,Business,2903,3,2,4,2,2,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +12255,114532,Male,Loyal Customer,35,Personal Travel,Business,390,1,5,5,5,2,5,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +12256,102612,Female,Loyal Customer,41,Business travel,Business,2428,1,1,1,1,4,5,5,4,4,4,4,3,4,5,49,47.0,satisfied +12257,128165,Male,Loyal Customer,27,Business travel,Business,1972,1,1,1,1,4,5,4,4,4,2,5,4,5,4,0,0.0,satisfied +12258,97886,Female,Loyal Customer,59,Business travel,Business,793,4,4,4,4,4,4,4,4,4,4,4,5,4,4,6,0.0,satisfied +12259,75079,Female,Loyal Customer,33,Business travel,Eco Plus,2611,3,1,5,1,3,3,3,3,4,1,3,3,2,3,0,0.0,neutral or dissatisfied +12260,91468,Female,Loyal Customer,40,Business travel,Eco,459,1,5,4,5,1,1,1,1,4,4,4,3,3,1,16,7.0,neutral or dissatisfied +12261,64839,Male,Loyal Customer,40,Business travel,Business,1575,3,3,3,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +12262,4806,Female,Loyal Customer,62,Personal Travel,Eco,403,3,5,3,3,5,4,5,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +12263,70458,Female,Loyal Customer,41,Business travel,Business,3531,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +12264,118659,Male,Loyal Customer,19,Business travel,Business,2782,5,5,5,5,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +12265,58255,Male,Loyal Customer,60,Business travel,Business,2072,1,1,1,1,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +12266,23649,Male,disloyal Customer,21,Business travel,Eco,73,3,0,3,4,3,3,4,3,3,5,5,5,5,3,0,0.0,neutral or dissatisfied +12267,22169,Male,Loyal Customer,25,Business travel,Eco,533,2,5,5,5,2,2,1,2,1,3,4,2,3,2,17,6.0,neutral or dissatisfied +12268,21139,Male,Loyal Customer,26,Personal Travel,Eco,106,1,3,1,3,4,1,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +12269,20698,Male,Loyal Customer,22,Business travel,Eco,510,5,5,5,5,5,5,5,5,4,2,2,1,4,5,13,4.0,satisfied +12270,75810,Male,Loyal Customer,27,Business travel,Business,868,4,4,4,4,4,5,4,4,4,4,5,5,5,4,0,3.0,satisfied +12271,45650,Female,Loyal Customer,8,Personal Travel,Eco,260,1,3,1,2,1,1,1,1,4,1,2,1,5,1,0,13.0,neutral or dissatisfied +12272,45714,Female,disloyal Customer,12,Business travel,Eco,1068,2,2,2,4,3,2,5,3,4,2,4,3,3,3,0,23.0,neutral or dissatisfied +12273,102089,Male,Loyal Customer,44,Business travel,Business,386,5,5,5,5,2,4,4,4,4,4,4,3,4,3,17,18.0,satisfied +12274,128709,Male,Loyal Customer,26,Business travel,Business,1235,2,2,2,2,5,5,5,5,4,3,4,3,4,5,0,12.0,satisfied +12275,11560,Female,Loyal Customer,59,Business travel,Business,1789,1,1,3,1,5,5,4,4,4,4,4,5,4,5,13,9.0,satisfied +12276,95077,Female,Loyal Customer,25,Personal Travel,Eco,248,3,4,3,3,2,3,2,2,5,5,5,5,4,2,0,3.0,neutral or dissatisfied +12277,73749,Male,Loyal Customer,54,Personal Travel,Eco,192,3,2,3,4,2,3,2,2,3,5,3,3,4,2,0,0.0,neutral or dissatisfied +12278,48963,Male,Loyal Customer,61,Business travel,Business,109,1,1,1,1,3,2,2,4,4,4,3,5,4,3,0,0.0,satisfied +12279,98846,Male,Loyal Customer,52,Business travel,Business,1482,5,5,2,5,4,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +12280,109834,Female,Loyal Customer,23,Business travel,Business,1204,1,1,4,1,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +12281,48910,Female,disloyal Customer,23,Business travel,Eco,421,5,0,5,4,2,5,1,2,5,4,5,5,1,2,0,0.0,satisfied +12282,3395,Female,Loyal Customer,57,Business travel,Business,296,2,2,5,5,4,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +12283,116438,Female,Loyal Customer,19,Personal Travel,Eco,390,1,2,1,4,4,1,4,4,2,3,4,2,3,4,0,0.0,neutral or dissatisfied +12284,118753,Male,Loyal Customer,37,Personal Travel,Eco,370,0,4,0,4,5,0,5,5,1,3,3,3,3,5,0,0.0,satisfied +12285,83078,Female,Loyal Customer,59,Business travel,Business,2437,1,1,5,1,5,5,1,5,5,5,5,3,5,4,1,0.0,satisfied +12286,20989,Male,Loyal Customer,30,Personal Travel,Eco,803,1,4,1,4,3,1,3,3,1,1,3,3,1,3,0,0.0,neutral or dissatisfied +12287,113733,Female,Loyal Customer,53,Personal Travel,Eco,397,3,5,5,2,5,5,4,2,2,5,2,5,2,3,69,82.0,neutral or dissatisfied +12288,68651,Female,disloyal Customer,55,Business travel,Business,175,5,4,4,2,1,5,1,1,5,3,4,4,5,1,0,0.0,satisfied +12289,15892,Female,Loyal Customer,30,Business travel,Eco,269,0,0,0,1,5,0,5,5,4,1,4,2,4,5,0,15.0,satisfied +12290,8597,Female,Loyal Customer,50,Business travel,Eco Plus,109,3,4,3,4,4,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +12291,23114,Male,Loyal Customer,49,Business travel,Business,3675,4,4,4,4,4,4,3,5,5,5,5,3,5,1,0,0.0,satisfied +12292,96285,Male,Loyal Customer,17,Personal Travel,Eco,687,4,4,4,2,5,4,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +12293,38214,Male,Loyal Customer,54,Business travel,Eco Plus,691,5,3,3,3,5,5,5,5,4,5,3,1,3,5,64,58.0,satisfied +12294,8233,Male,Loyal Customer,24,Personal Travel,Eco,125,5,4,5,3,2,5,2,2,5,5,3,4,5,2,0,0.0,satisfied +12295,108143,Female,disloyal Customer,50,Business travel,Eco,705,3,3,3,4,2,3,2,2,2,1,4,1,3,2,5,5.0,neutral or dissatisfied +12296,2449,Male,Loyal Customer,21,Personal Travel,Eco Plus,767,1,3,1,1,1,1,1,1,4,2,1,1,2,1,5,,neutral or dissatisfied +12297,111380,Male,Loyal Customer,43,Business travel,Business,2168,3,3,3,3,3,3,3,3,4,2,2,3,3,3,135,124.0,neutral or dissatisfied +12298,39733,Male,Loyal Customer,50,Personal Travel,Eco,320,5,5,5,3,4,5,4,4,1,3,4,1,1,4,0,0.0,satisfied +12299,95354,Male,Loyal Customer,14,Personal Travel,Eco,319,4,3,4,4,3,4,3,3,1,4,4,3,3,3,8,2.0,neutral or dissatisfied +12300,70242,Female,Loyal Customer,60,Business travel,Business,1592,4,4,4,4,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +12301,95447,Female,disloyal Customer,57,Business travel,Business,248,4,4,4,3,2,4,2,2,3,2,5,3,5,2,0,0.0,satisfied +12302,57506,Female,disloyal Customer,22,Business travel,Eco,1075,5,5,5,3,5,5,5,5,5,4,5,5,5,5,0,24.0,satisfied +12303,26988,Male,Loyal Customer,36,Business travel,Eco,867,4,3,3,3,4,4,4,4,5,4,4,5,5,4,0,0.0,satisfied +12304,38503,Male,Loyal Customer,32,Business travel,Business,2586,5,5,5,5,4,4,4,4,4,4,4,5,1,4,0,0.0,satisfied +12305,56274,Female,Loyal Customer,51,Business travel,Business,2227,2,4,4,4,3,2,3,2,2,2,2,1,2,3,0,2.0,neutral or dissatisfied +12306,81759,Female,Loyal Customer,49,Business travel,Business,1310,1,1,1,1,5,5,4,4,4,4,4,3,4,3,1,0.0,satisfied +12307,87074,Male,Loyal Customer,59,Business travel,Business,645,2,2,2,2,3,4,5,4,4,4,4,3,4,3,68,56.0,satisfied +12308,63305,Male,Loyal Customer,28,Business travel,Business,2901,3,4,4,4,3,3,3,3,4,5,2,4,1,3,24,35.0,neutral or dissatisfied +12309,117490,Male,Loyal Customer,51,Business travel,Eco,507,2,3,3,3,3,2,3,3,1,4,4,3,3,3,9,8.0,neutral or dissatisfied +12310,87931,Male,Loyal Customer,67,Business travel,Business,2359,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +12311,68220,Male,Loyal Customer,72,Business travel,Business,432,4,4,4,4,2,4,3,4,4,4,4,4,4,3,0,1.0,neutral or dissatisfied +12312,12202,Male,disloyal Customer,27,Business travel,Business,201,0,0,0,3,2,0,2,2,5,4,4,3,4,2,0,7.0,satisfied +12313,24359,Male,Loyal Customer,36,Business travel,Eco Plus,634,5,1,1,1,5,5,5,5,2,2,5,4,5,5,0,0.0,satisfied +12314,80121,Female,Loyal Customer,51,Business travel,Business,2586,3,3,5,3,4,4,4,4,2,4,5,4,5,4,0,0.0,satisfied +12315,57797,Male,Loyal Customer,41,Business travel,Business,2539,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +12316,107457,Male,Loyal Customer,58,Personal Travel,Eco Plus,717,1,4,1,3,2,1,3,2,3,5,5,3,5,2,5,0.0,neutral or dissatisfied +12317,109351,Female,Loyal Customer,40,Business travel,Business,2917,2,4,4,4,2,2,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +12318,56045,Female,disloyal Customer,44,Business travel,Eco,2475,2,2,2,4,2,3,3,3,5,4,3,3,4,3,0,0.0,neutral or dissatisfied +12319,102519,Female,Loyal Customer,23,Personal Travel,Eco,397,3,4,3,3,4,3,4,4,4,4,5,3,5,4,20,5.0,neutral or dissatisfied +12320,122573,Female,Loyal Customer,48,Business travel,Business,3186,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +12321,50838,Female,Loyal Customer,7,Personal Travel,Eco,109,3,0,3,3,5,3,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +12322,70772,Male,Loyal Customer,56,Business travel,Business,328,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +12323,47180,Male,Loyal Customer,18,Business travel,Business,2684,5,5,5,5,5,5,5,5,4,3,1,4,5,5,0,0.0,satisfied +12324,92693,Female,Loyal Customer,38,Personal Travel,Eco,507,1,1,2,4,2,2,2,2,1,4,3,4,3,2,0,0.0,neutral or dissatisfied +12325,60448,Male,Loyal Customer,56,Business travel,Business,3995,4,4,4,4,3,4,5,4,4,5,4,5,4,3,0,0.0,satisfied +12326,96417,Female,Loyal Customer,33,Personal Travel,Eco,1246,2,4,1,4,3,1,3,3,2,4,2,2,3,3,128,130.0,neutral or dissatisfied +12327,58808,Male,Loyal Customer,49,Personal Travel,Eco,1012,2,4,1,2,4,1,4,4,4,3,3,1,4,4,0,0.0,neutral or dissatisfied +12328,12628,Female,disloyal Customer,42,Business travel,Business,844,2,2,2,2,1,2,1,1,4,2,4,3,4,1,0,2.0,neutral or dissatisfied +12329,91581,Female,Loyal Customer,54,Personal Travel,Eco,1123,3,4,3,5,2,5,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +12330,60702,Female,Loyal Customer,29,Business travel,Eco,1725,2,4,4,4,2,2,2,2,3,1,3,2,1,2,240,212.0,neutral or dissatisfied +12331,40006,Male,Loyal Customer,40,Business travel,Business,3503,1,5,1,1,4,1,3,5,5,5,5,1,5,4,3,0.0,satisfied +12332,71016,Male,Loyal Customer,38,Business travel,Business,3374,3,1,1,1,4,4,4,3,3,3,3,4,3,1,1,0.0,neutral or dissatisfied +12333,97043,Male,Loyal Customer,14,Personal Travel,Business,1313,3,4,3,3,5,3,5,5,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +12334,94991,Male,Loyal Customer,60,Personal Travel,Eco,562,3,5,3,2,4,3,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +12335,81099,Female,Loyal Customer,48,Business travel,Business,991,4,4,4,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +12336,88825,Male,Loyal Customer,38,Business travel,Eco Plus,115,4,1,4,4,4,4,4,4,1,2,2,2,2,4,0,0.0,neutral or dissatisfied +12337,42129,Female,disloyal Customer,38,Business travel,Eco Plus,996,4,4,4,4,5,4,4,5,5,5,4,1,2,5,0,0.0,neutral or dissatisfied +12338,53033,Female,Loyal Customer,44,Business travel,Business,3917,3,2,2,2,1,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +12339,35832,Female,Loyal Customer,28,Business travel,Business,997,1,1,1,1,3,3,3,3,5,1,3,5,5,3,0,0.0,satisfied +12340,126973,Male,Loyal Customer,61,Business travel,Business,338,1,4,4,4,3,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +12341,39619,Male,Loyal Customer,62,Personal Travel,Eco,954,2,5,2,1,3,2,3,3,5,3,5,4,4,3,0,24.0,neutral or dissatisfied +12342,119687,Female,Loyal Customer,51,Business travel,Business,1325,2,2,3,2,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +12343,122008,Male,Loyal Customer,45,Business travel,Business,130,0,4,0,4,2,4,4,1,1,1,1,5,1,3,0,0.0,satisfied +12344,116001,Female,Loyal Customer,58,Personal Travel,Eco,325,3,4,3,3,2,5,1,5,5,3,5,5,5,1,12,6.0,neutral or dissatisfied +12345,2938,Female,Loyal Customer,42,Business travel,Business,835,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +12346,108720,Female,disloyal Customer,24,Business travel,Eco,591,5,4,5,5,5,4,5,5,3,2,5,4,4,5,0,0.0,satisfied +12347,56732,Male,Loyal Customer,70,Personal Travel,Eco,997,4,2,3,4,2,3,2,2,3,5,3,2,3,2,0,0.0,neutral or dissatisfied +12348,24450,Male,Loyal Customer,32,Business travel,Business,2266,2,5,2,2,5,5,5,5,1,5,1,1,1,5,4,30.0,satisfied +12349,9225,Female,Loyal Customer,80,Business travel,Business,100,2,5,5,5,2,3,4,1,1,1,2,4,1,3,0,0.0,neutral or dissatisfied +12350,25335,Male,Loyal Customer,34,Personal Travel,Eco,837,0,4,0,3,4,0,4,4,4,3,4,5,4,4,0,1.0,satisfied +12351,6960,Male,Loyal Customer,52,Business travel,Business,436,1,1,1,1,4,4,5,4,4,4,4,4,4,5,17,9.0,satisfied +12352,46371,Male,Loyal Customer,13,Business travel,Eco,1013,3,5,5,5,3,3,4,3,2,2,3,2,4,3,40,51.0,neutral or dissatisfied +12353,15987,Female,Loyal Customer,27,Business travel,Business,2801,5,5,5,5,4,4,4,4,1,2,5,2,4,4,0,0.0,satisfied +12354,21398,Male,disloyal Customer,36,Business travel,Eco,377,2,0,3,2,4,3,4,4,1,2,1,2,4,4,0,0.0,neutral or dissatisfied +12355,59437,Female,Loyal Customer,52,Business travel,Business,1799,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,20.0,satisfied +12356,33296,Female,Loyal Customer,47,Personal Travel,Eco Plus,101,1,4,1,4,5,5,4,3,3,1,3,4,3,5,0,4.0,neutral or dissatisfied +12357,69997,Female,Loyal Customer,51,Personal Travel,Eco,236,2,3,2,3,1,3,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +12358,87230,Male,Loyal Customer,53,Business travel,Business,2141,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,5.0,satisfied +12359,90544,Female,Loyal Customer,57,Business travel,Business,1699,5,5,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +12360,46591,Male,Loyal Customer,39,Business travel,Business,3424,5,1,5,5,4,5,3,5,5,5,4,5,5,2,0,0.0,satisfied +12361,82002,Female,disloyal Customer,44,Business travel,Eco,824,1,1,1,4,1,1,1,1,3,5,3,3,3,1,52,110.0,neutral or dissatisfied +12362,33456,Male,Loyal Customer,20,Personal Travel,Eco,2409,1,4,1,3,1,1,1,1,2,1,4,4,3,1,0,6.0,neutral or dissatisfied +12363,41005,Female,Loyal Customer,7,Personal Travel,Eco,1362,4,4,4,3,4,4,4,4,4,3,3,4,4,4,5,17.0,neutral or dissatisfied +12364,107985,Male,disloyal Customer,21,Business travel,Eco,271,5,5,5,3,2,5,1,2,4,2,4,5,4,2,0,0.0,satisfied +12365,60910,Male,Loyal Customer,14,Personal Travel,Eco,589,1,2,1,4,4,1,1,4,4,3,3,4,3,4,73,69.0,neutral or dissatisfied +12366,17696,Male,disloyal Customer,42,Business travel,Eco,854,2,2,2,1,2,2,2,2,5,5,4,1,1,2,0,0.0,neutral or dissatisfied +12367,42716,Male,Loyal Customer,38,Business travel,Eco,912,5,4,4,4,5,5,5,5,2,4,1,2,5,5,29,34.0,satisfied +12368,120693,Male,Loyal Customer,21,Personal Travel,Eco,280,2,3,2,3,1,2,1,1,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +12369,22238,Female,disloyal Customer,25,Business travel,Business,143,2,0,2,3,3,2,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +12370,9987,Female,Loyal Customer,15,Personal Travel,Eco,534,3,4,3,2,3,3,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +12371,12909,Female,Loyal Customer,59,Business travel,Business,794,5,3,3,3,5,3,2,5,5,4,5,3,5,3,0,5.0,neutral or dissatisfied +12372,35291,Male,Loyal Customer,25,Business travel,Business,1801,2,3,3,3,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +12373,75739,Female,Loyal Customer,31,Business travel,Business,868,1,5,5,5,1,1,1,1,3,3,4,3,4,1,32,30.0,neutral or dissatisfied +12374,50474,Female,disloyal Customer,30,Business travel,Eco,89,3,3,3,4,2,3,5,2,3,1,4,1,4,2,0,0.0,neutral or dissatisfied +12375,116322,Female,Loyal Customer,42,Personal Travel,Eco,337,3,5,3,5,5,5,5,2,2,3,2,1,2,5,2,0.0,neutral or dissatisfied +12376,19500,Male,Loyal Customer,43,Business travel,Eco,508,2,4,4,4,2,2,2,2,3,3,1,2,3,2,89,94.0,satisfied +12377,64027,Male,Loyal Customer,51,Business travel,Business,2525,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +12378,65688,Female,disloyal Customer,23,Business travel,Eco,926,2,2,2,3,1,2,1,1,4,3,3,3,2,1,0,0.0,neutral or dissatisfied +12379,120979,Female,disloyal Customer,45,Business travel,Eco,861,3,3,3,3,4,3,3,4,1,2,3,3,4,4,0,0.0,neutral or dissatisfied +12380,30307,Female,Loyal Customer,62,Personal Travel,Eco,1476,1,5,1,4,2,3,5,1,1,1,1,3,1,5,0,47.0,neutral or dissatisfied +12381,63084,Female,Loyal Customer,70,Personal Travel,Eco,862,2,4,2,2,3,5,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +12382,107184,Female,disloyal Customer,34,Business travel,Eco,668,2,1,2,3,3,2,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +12383,119650,Male,Loyal Customer,29,Business travel,Business,1899,1,4,1,4,1,1,1,1,2,2,3,3,3,1,1,0.0,neutral or dissatisfied +12384,9845,Male,Loyal Customer,53,Business travel,Business,1741,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +12385,113135,Female,Loyal Customer,40,Personal Travel,Eco Plus,543,3,5,5,5,4,5,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +12386,35702,Female,Loyal Customer,39,Personal Travel,Eco,2586,4,2,4,3,4,3,3,4,5,3,4,3,2,3,15,0.0,neutral or dissatisfied +12387,54512,Female,disloyal Customer,16,Business travel,Eco,925,3,3,3,1,3,3,5,3,1,2,2,1,5,3,0,0.0,neutral or dissatisfied +12388,18842,Male,Loyal Customer,40,Business travel,Business,3513,3,3,3,3,1,2,2,4,4,4,4,5,4,4,8,12.0,satisfied +12389,9900,Male,disloyal Customer,25,Business travel,Business,534,2,0,2,3,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +12390,31507,Male,Loyal Customer,32,Business travel,Business,2992,2,4,4,4,2,2,2,2,2,2,4,4,4,2,0,9.0,neutral or dissatisfied +12391,59480,Male,disloyal Customer,62,Business travel,Eco,758,2,2,2,4,2,2,2,2,4,2,4,4,4,2,11,12.0,neutral or dissatisfied +12392,91104,Male,Loyal Customer,42,Personal Travel,Eco,515,3,5,2,2,4,2,4,4,4,2,4,4,5,4,0,0.0,neutral or dissatisfied +12393,8593,Female,Loyal Customer,12,Personal Travel,Eco,109,2,4,2,3,3,2,3,3,4,4,5,3,4,3,7,0.0,neutral or dissatisfied +12394,104899,Male,disloyal Customer,27,Business travel,Business,1565,4,4,4,4,3,4,3,3,4,3,4,4,4,3,0,0.0,satisfied +12395,107212,Male,Loyal Customer,43,Business travel,Business,3110,2,2,2,2,4,5,4,4,4,4,4,4,4,5,1,2.0,satisfied +12396,65317,Female,Loyal Customer,40,Business travel,Business,432,3,3,3,3,2,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +12397,96865,Female,Loyal Customer,36,Business travel,Business,3165,2,4,1,1,2,3,3,2,2,2,2,3,2,3,13,10.0,neutral or dissatisfied +12398,44114,Female,Loyal Customer,12,Personal Travel,Eco Plus,257,3,3,3,3,5,3,5,5,3,3,4,5,3,5,35,47.0,neutral or dissatisfied +12399,7515,Female,Loyal Customer,59,Business travel,Business,3792,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +12400,46486,Female,Loyal Customer,29,Business travel,Business,2166,2,2,2,2,4,4,3,4,5,3,5,3,2,4,0,0.0,satisfied +12401,48322,Male,Loyal Customer,12,Personal Travel,Eco,1203,3,5,3,5,3,3,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +12402,38789,Male,disloyal Customer,38,Business travel,Business,353,4,3,3,1,2,3,2,2,4,5,4,5,4,2,4,4.0,satisfied +12403,115679,Male,Loyal Customer,48,Business travel,Eco,337,3,4,4,4,3,3,3,3,3,4,3,3,4,3,16,8.0,neutral or dissatisfied +12404,69552,Female,Loyal Customer,70,Business travel,Business,2475,1,5,2,5,1,1,1,2,5,1,2,1,1,1,37,33.0,neutral or dissatisfied +12405,33329,Male,disloyal Customer,40,Business travel,Eco,1410,3,3,3,2,5,3,5,5,3,3,4,4,4,5,1,0.0,neutral or dissatisfied +12406,113690,Male,Loyal Customer,46,Personal Travel,Eco,407,4,2,4,3,1,4,1,1,3,1,4,1,3,1,38,39.0,neutral or dissatisfied +12407,26825,Female,Loyal Customer,62,Business travel,Eco,224,5,4,4,4,2,5,1,5,5,5,5,3,5,5,0,5.0,satisfied +12408,90932,Male,Loyal Customer,30,Business travel,Business,2463,5,5,5,5,4,4,4,4,4,5,1,1,2,4,0,0.0,satisfied +12409,37298,Female,Loyal Customer,48,Business travel,Eco,944,4,5,5,5,2,5,5,4,4,4,4,2,4,5,0,0.0,satisfied +12410,124761,Female,Loyal Customer,45,Business travel,Business,1531,1,1,1,1,5,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +12411,61450,Female,Loyal Customer,57,Business travel,Business,2419,2,2,2,2,2,4,5,4,4,4,4,3,4,3,112,77.0,satisfied +12412,14392,Male,Loyal Customer,39,Business travel,Eco,900,1,5,4,4,1,1,1,1,1,1,4,2,3,1,43,19.0,neutral or dissatisfied +12413,115806,Male,Loyal Customer,45,Business travel,Business,337,0,0,0,3,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +12414,48325,Female,Loyal Customer,46,Business travel,Business,2432,2,4,2,2,2,4,5,4,4,5,4,5,4,3,0,1.0,satisfied +12415,108187,Male,Loyal Customer,45,Business travel,Business,2059,3,3,3,3,4,4,4,3,3,4,3,5,3,4,31,14.0,satisfied +12416,25701,Male,Loyal Customer,61,Business travel,Eco,447,5,2,2,2,5,5,5,5,1,1,2,1,2,5,0,0.0,satisfied +12417,66242,Female,Loyal Customer,40,Business travel,Eco,460,5,5,2,5,5,5,5,5,2,5,5,5,2,5,0,0.0,satisfied +12418,34296,Male,Loyal Customer,37,Personal Travel,Eco,280,4,5,4,3,4,3,3,3,4,4,5,3,5,3,151,182.0,neutral or dissatisfied +12419,110550,Female,Loyal Customer,52,Business travel,Business,551,4,4,4,4,4,4,5,5,5,5,5,4,5,5,22,19.0,satisfied +12420,123676,Female,disloyal Customer,25,Business travel,Eco,214,3,1,4,2,3,4,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +12421,79116,Female,Loyal Customer,31,Personal Travel,Eco,356,2,5,2,3,4,2,4,4,5,5,3,2,2,4,0,0.0,neutral or dissatisfied +12422,102303,Male,Loyal Customer,51,Business travel,Eco,397,2,4,4,4,2,2,2,2,2,5,3,1,3,2,0,0.0,neutral or dissatisfied +12423,74776,Female,disloyal Customer,26,Business travel,Business,1431,1,5,1,2,4,1,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +12424,114099,Female,Loyal Customer,67,Personal Travel,Eco,1947,2,5,2,3,2,4,4,5,4,3,4,4,5,4,188,183.0,neutral or dissatisfied +12425,109342,Male,Loyal Customer,42,Business travel,Business,2334,5,5,5,5,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +12426,99340,Male,disloyal Customer,25,Business travel,Eco,847,2,2,2,2,1,2,1,1,5,5,5,3,5,1,0,10.0,neutral or dissatisfied +12427,127970,Female,Loyal Customer,36,Business travel,Business,3614,5,5,5,5,5,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +12428,60656,Male,Loyal Customer,55,Business travel,Business,1591,1,1,1,1,4,4,4,1,1,1,1,4,1,3,6,0.0,neutral or dissatisfied +12429,17343,Female,Loyal Customer,43,Business travel,Eco,563,4,4,4,4,2,3,5,4,4,4,4,5,4,1,64,57.0,satisfied +12430,78716,Female,Loyal Customer,43,Business travel,Business,447,4,4,4,4,4,4,5,5,5,5,5,4,5,3,9,0.0,satisfied +12431,85550,Female,Loyal Customer,46,Business travel,Business,2022,3,3,3,3,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +12432,93252,Male,disloyal Customer,15,Business travel,Business,1180,0,0,0,4,5,0,5,5,5,2,5,3,4,5,11,0.0,satisfied +12433,126391,Male,Loyal Customer,70,Personal Travel,Eco,590,2,4,2,5,5,2,5,5,5,2,4,3,4,5,0,0.0,neutral or dissatisfied +12434,92625,Female,Loyal Customer,44,Business travel,Business,2531,2,2,2,2,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +12435,40980,Female,Loyal Customer,69,Personal Travel,Eco Plus,601,3,4,3,3,4,4,2,3,3,3,3,4,3,2,0,7.0,neutral or dissatisfied +12436,12359,Female,Loyal Customer,36,Business travel,Eco,190,4,4,4,4,4,4,4,4,2,2,3,1,4,4,1,0.0,neutral or dissatisfied +12437,80567,Female,Loyal Customer,52,Business travel,Eco,1747,1,5,5,5,3,2,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +12438,129868,Male,Loyal Customer,47,Business travel,Eco Plus,447,3,4,4,4,4,3,4,4,2,5,3,1,4,4,0,0.0,neutral or dissatisfied +12439,67880,Male,Loyal Customer,21,Personal Travel,Eco,1431,2,4,1,3,2,1,1,2,3,5,1,5,5,2,6,17.0,neutral or dissatisfied +12440,44151,Male,Loyal Customer,42,Business travel,Eco Plus,120,5,2,1,2,5,5,5,5,3,5,1,1,1,5,0,0.0,satisfied +12441,37692,Male,Loyal Customer,34,Personal Travel,Eco,1041,3,4,3,4,3,3,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +12442,64011,Male,Loyal Customer,43,Business travel,Business,612,4,4,4,4,2,5,4,5,5,5,5,4,5,3,11,8.0,satisfied +12443,70515,Female,Loyal Customer,31,Personal Travel,Eco,867,3,1,2,4,2,2,2,2,4,5,4,3,3,2,0,0.0,neutral or dissatisfied +12444,26790,Male,disloyal Customer,36,Business travel,Business,226,4,4,4,1,3,4,5,3,4,2,3,1,3,3,0,0.0,neutral or dissatisfied +12445,101034,Female,Loyal Customer,34,Personal Travel,Eco Plus,867,4,5,5,4,1,5,1,1,5,3,4,2,1,1,29,33.0,neutral or dissatisfied +12446,114591,Male,Loyal Customer,55,Business travel,Business,2389,1,1,1,1,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +12447,20008,Male,Loyal Customer,68,Personal Travel,Eco,599,3,4,2,1,2,2,2,2,3,3,4,1,1,2,78,65.0,neutral or dissatisfied +12448,94904,Female,disloyal Customer,40,Business travel,Business,319,3,3,3,4,3,3,3,3,4,2,4,2,3,3,1,1.0,neutral or dissatisfied +12449,12823,Female,Loyal Customer,41,Business travel,Business,528,4,4,4,4,1,2,4,4,4,4,4,3,4,3,0,0.0,satisfied +12450,60998,Male,Loyal Customer,41,Business travel,Business,649,3,3,3,3,2,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +12451,10801,Male,Loyal Customer,38,Business travel,Business,158,3,3,3,3,2,5,5,4,4,4,5,4,4,5,0,0.0,satisfied +12452,74830,Male,disloyal Customer,44,Business travel,Business,1797,4,4,4,5,1,4,1,1,3,5,4,5,4,1,0,7.0,satisfied +12453,32443,Male,Loyal Customer,64,Business travel,Business,216,0,5,0,4,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +12454,109616,Female,Loyal Customer,46,Business travel,Business,2337,3,3,2,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +12455,54007,Male,disloyal Customer,22,Business travel,Eco,395,4,5,4,2,5,4,5,5,5,5,1,2,3,5,21,29.0,neutral or dissatisfied +12456,114179,Female,disloyal Customer,23,Business travel,Eco,967,5,5,5,4,5,5,5,5,4,5,4,5,5,5,0,13.0,satisfied +12457,112669,Female,Loyal Customer,42,Business travel,Business,1617,3,3,3,3,3,4,4,4,4,4,4,4,4,4,63,60.0,satisfied +12458,38459,Male,disloyal Customer,38,Business travel,Eco,826,1,1,1,3,1,1,1,1,1,4,2,4,5,1,0,0.0,neutral or dissatisfied +12459,116615,Female,disloyal Customer,38,Business travel,Business,371,2,2,2,1,4,2,4,4,5,2,4,4,5,4,4,0.0,neutral or dissatisfied +12460,58951,Female,Loyal Customer,54,Personal Travel,Eco Plus,888,2,5,2,3,3,4,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +12461,89509,Female,disloyal Customer,27,Business travel,Business,1035,4,4,4,3,4,4,4,4,3,3,4,5,4,4,0,18.0,satisfied +12462,124541,Female,Loyal Customer,17,Business travel,Business,1276,4,4,4,4,4,4,4,4,5,3,5,3,4,4,0,0.0,satisfied +12463,69988,Female,Loyal Customer,32,Business travel,Eco,236,2,4,4,4,2,2,2,2,1,1,4,1,3,2,0,14.0,neutral or dissatisfied +12464,107081,Male,Loyal Customer,45,Business travel,Business,480,1,1,1,1,3,4,5,4,4,4,4,4,4,4,71,54.0,satisfied +12465,79658,Male,disloyal Customer,37,Business travel,Business,362,4,4,4,3,3,4,3,3,4,5,4,1,3,3,0,0.0,neutral or dissatisfied +12466,125855,Female,Loyal Customer,24,Business travel,Eco,951,3,2,2,2,3,3,1,3,4,3,1,4,1,3,24,9.0,neutral or dissatisfied +12467,88571,Male,Loyal Customer,66,Personal Travel,Eco,442,4,4,4,3,5,4,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +12468,100583,Female,Loyal Customer,44,Business travel,Business,486,5,5,5,5,1,2,1,4,4,5,4,1,4,3,50,37.0,satisfied +12469,55160,Female,Loyal Customer,44,Personal Travel,Eco,1379,3,3,3,5,5,5,3,4,4,3,4,1,4,5,30,27.0,neutral or dissatisfied +12470,107110,Male,Loyal Customer,36,Business travel,Business,842,1,1,1,1,4,5,4,4,4,4,4,3,4,3,21,15.0,satisfied +12471,60665,Female,Loyal Customer,46,Personal Travel,Eco,1620,2,4,2,3,5,5,4,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +12472,106354,Male,disloyal Customer,18,Business travel,Business,551,4,0,3,2,3,3,3,5,5,5,5,3,3,3,191,189.0,satisfied +12473,6695,Female,Loyal Customer,21,Business travel,Business,403,3,1,1,1,3,3,3,3,3,2,4,3,3,3,0,36.0,neutral or dissatisfied +12474,128371,Female,Loyal Customer,40,Business travel,Business,2688,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +12475,3484,Female,disloyal Customer,31,Business travel,Eco,990,2,2,2,4,5,2,5,5,3,1,4,1,4,5,0,0.0,neutral or dissatisfied +12476,9462,Male,Loyal Customer,68,Personal Travel,Eco,362,2,4,2,3,1,2,1,1,3,4,5,3,4,1,24,30.0,neutral or dissatisfied +12477,11969,Female,Loyal Customer,45,Business travel,Business,1775,4,3,4,4,3,5,4,4,4,4,4,5,4,4,22,18.0,satisfied +12478,102071,Male,Loyal Customer,49,Business travel,Business,407,4,4,4,4,5,5,4,4,4,4,4,3,4,3,16,5.0,satisfied +12479,111035,Female,disloyal Customer,26,Business travel,Eco,319,3,2,3,4,1,3,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +12480,116483,Female,Loyal Customer,11,Personal Travel,Eco,333,2,3,2,2,1,2,1,1,1,5,5,4,4,1,0,0.0,neutral or dissatisfied +12481,8996,Female,Loyal Customer,53,Business travel,Business,228,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +12482,82330,Female,Loyal Customer,9,Personal Travel,Eco,456,3,2,3,4,4,3,1,4,1,3,3,1,3,4,0,0.0,neutral or dissatisfied +12483,125089,Male,Loyal Customer,55,Business travel,Business,361,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,3.0,satisfied +12484,128294,Female,Loyal Customer,37,Business travel,Business,2080,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +12485,43416,Male,Loyal Customer,34,Business travel,Eco Plus,436,3,4,4,4,3,2,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +12486,111870,Female,disloyal Customer,25,Business travel,Business,628,2,0,2,4,2,2,2,2,3,3,5,5,5,2,20,0.0,neutral or dissatisfied +12487,1699,Male,Loyal Customer,49,Business travel,Business,2484,3,3,5,3,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +12488,53911,Male,Loyal Customer,39,Personal Travel,Eco,191,2,5,2,2,4,2,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +12489,5810,Female,Loyal Customer,36,Business travel,Eco,273,5,2,2,2,5,4,5,5,3,1,3,1,3,5,0,0.0,neutral or dissatisfied +12490,111120,Female,Loyal Customer,49,Business travel,Business,1598,5,5,4,5,5,5,4,3,3,3,3,4,3,3,15,5.0,satisfied +12491,17927,Female,Loyal Customer,38,Business travel,Eco Plus,789,5,5,5,5,5,5,5,5,4,3,3,3,5,5,15,6.0,satisfied +12492,105159,Female,disloyal Customer,23,Business travel,Eco,281,2,0,2,5,5,2,5,5,4,2,5,5,3,5,0,0.0,neutral or dissatisfied +12493,42727,Female,Loyal Customer,41,Business travel,Business,2351,2,2,2,2,2,5,4,3,3,3,3,3,3,3,0,4.0,satisfied +12494,100394,Female,Loyal Customer,42,Personal Travel,Eco,1204,2,5,2,3,4,1,5,5,5,2,5,4,5,5,9,0.0,neutral or dissatisfied +12495,87755,Male,disloyal Customer,38,Business travel,Business,214,3,3,3,1,5,3,4,5,4,2,5,5,5,5,6,4.0,neutral or dissatisfied +12496,74191,Male,Loyal Customer,18,Personal Travel,Eco,641,3,5,3,2,4,3,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +12497,46931,Male,disloyal Customer,22,Business travel,Eco,964,3,3,3,5,3,3,3,3,1,5,3,3,2,3,0,5.0,neutral or dissatisfied +12498,20469,Female,Loyal Customer,48,Personal Travel,Eco,84,2,2,2,3,3,3,3,3,3,2,2,4,3,1,0,3.0,neutral or dissatisfied +12499,101340,Male,Loyal Customer,19,Personal Travel,Eco,1771,3,4,3,3,1,3,1,1,1,5,4,3,4,1,28,31.0,neutral or dissatisfied +12500,49365,Female,disloyal Customer,25,Business travel,Eco,326,2,5,2,5,2,2,2,2,2,5,1,3,2,2,0,4.0,neutral or dissatisfied +12501,85692,Female,Loyal Customer,59,Business travel,Business,1547,4,4,4,4,2,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +12502,47724,Male,Loyal Customer,40,Business travel,Business,462,3,3,4,3,3,5,5,4,4,4,4,3,4,5,17,11.0,satisfied +12503,111485,Male,Loyal Customer,26,Personal Travel,Eco,1452,3,2,3,3,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +12504,1910,Male,Loyal Customer,44,Business travel,Business,2955,3,5,5,5,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +12505,4457,Female,Loyal Customer,26,Personal Travel,Eco Plus,762,1,3,1,3,3,1,2,3,1,2,3,4,4,3,63,44.0,neutral or dissatisfied +12506,67086,Female,disloyal Customer,28,Business travel,Eco,1119,4,3,3,2,4,3,4,4,2,4,2,2,2,4,0,15.0,neutral or dissatisfied +12507,120262,Female,Loyal Customer,53,Business travel,Business,237,1,2,2,2,5,2,2,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +12508,114419,Male,Loyal Customer,50,Business travel,Business,1525,5,5,2,5,4,5,4,5,5,5,5,4,5,5,2,11.0,satisfied +12509,100385,Male,Loyal Customer,52,Personal Travel,Eco,1011,2,1,2,2,5,2,5,5,4,4,2,1,2,5,0,10.0,neutral or dissatisfied +12510,96089,Female,Loyal Customer,28,Personal Travel,Eco,1090,4,4,4,2,1,4,1,1,4,1,4,1,2,1,26,18.0,neutral or dissatisfied +12511,106167,Male,Loyal Customer,57,Personal Travel,Eco,436,3,5,3,2,5,3,5,5,4,2,4,3,5,5,69,74.0,neutral or dissatisfied +12512,35985,Female,Loyal Customer,43,Business travel,Business,2496,2,2,2,2,5,5,5,1,1,3,3,5,2,5,5,1.0,satisfied +12513,27484,Male,Loyal Customer,42,Business travel,Eco,679,3,1,1,1,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +12514,122566,Female,Loyal Customer,46,Personal Travel,Eco Plus,500,4,3,2,4,2,3,3,4,4,2,4,1,4,4,0,0.0,satisfied +12515,113755,Female,Loyal Customer,55,Personal Travel,Eco,386,2,5,2,3,5,4,4,1,1,2,5,3,1,5,0,0.0,neutral or dissatisfied +12516,73294,Male,Loyal Customer,46,Business travel,Business,2923,1,1,1,1,3,5,5,5,5,5,5,3,5,5,28,23.0,satisfied +12517,102869,Male,disloyal Customer,51,Business travel,Business,472,5,4,4,2,5,5,5,5,5,2,4,3,5,5,18,12.0,satisfied +12518,113604,Female,disloyal Customer,41,Business travel,Business,223,2,2,2,4,4,2,4,4,1,1,4,4,4,4,18,22.0,neutral or dissatisfied +12519,48195,Male,disloyal Customer,17,Business travel,Eco,391,3,4,3,4,4,3,4,4,3,3,3,2,4,4,1,3.0,neutral or dissatisfied +12520,72856,Male,Loyal Customer,60,Business travel,Business,700,3,3,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +12521,92450,Male,Loyal Customer,51,Business travel,Business,1892,3,3,2,3,5,3,5,4,4,4,4,3,4,5,0,0.0,satisfied +12522,53199,Male,Loyal Customer,46,Business travel,Eco,612,4,5,5,5,4,4,4,4,1,3,2,4,2,4,0,0.0,satisfied +12523,2527,Male,disloyal Customer,39,Business travel,Business,280,3,3,3,2,5,3,5,5,5,4,5,3,4,5,3,1.0,neutral or dissatisfied +12524,21401,Female,Loyal Customer,38,Business travel,Eco,331,4,5,5,5,4,4,4,4,5,3,2,4,4,4,0,0.0,satisfied +12525,86139,Female,Loyal Customer,56,Business travel,Business,306,0,0,0,2,4,4,5,2,2,5,5,3,2,4,0,0.0,satisfied +12526,56923,Female,disloyal Customer,54,Business travel,Business,2454,4,4,4,3,4,4,4,4,5,3,5,5,5,4,34,38.0,satisfied +12527,58448,Male,Loyal Customer,60,Personal Travel,Eco,733,2,2,2,4,5,2,5,5,1,1,3,3,4,5,0,0.0,neutral or dissatisfied +12528,78898,Female,Loyal Customer,15,Personal Travel,Eco,1727,2,5,2,4,2,2,2,2,3,3,4,3,3,2,0,1.0,neutral or dissatisfied +12529,23511,Male,disloyal Customer,41,Business travel,Business,349,2,2,2,2,3,2,3,3,1,5,1,3,2,3,35,57.0,neutral or dissatisfied +12530,125138,Female,Loyal Customer,51,Business travel,Business,1765,1,1,1,1,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +12531,10616,Female,disloyal Customer,39,Business travel,Business,140,5,5,5,3,4,5,4,4,3,5,4,5,4,4,100,97.0,satisfied +12532,57517,Male,Loyal Customer,59,Business travel,Business,3749,5,5,5,5,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +12533,45910,Male,Loyal Customer,42,Business travel,Eco,563,4,1,1,1,4,4,4,4,3,4,5,2,1,4,12,2.0,satisfied +12534,42368,Female,Loyal Customer,27,Personal Travel,Eco,329,3,5,5,2,4,5,4,4,2,5,5,5,5,4,27,12.0,neutral or dissatisfied +12535,81662,Male,disloyal Customer,24,Business travel,Eco,907,2,2,2,3,1,2,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +12536,89136,Male,Loyal Customer,51,Business travel,Business,1892,2,5,2,2,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +12537,61064,Male,disloyal Customer,22,Business travel,Eco,1071,3,3,3,4,2,3,2,2,4,1,3,3,4,2,3,34.0,neutral or dissatisfied +12538,45388,Male,Loyal Customer,12,Personal Travel,Eco Plus,188,1,4,1,5,1,1,1,1,3,3,5,5,4,1,14,6.0,neutral or dissatisfied +12539,67489,Female,disloyal Customer,41,Business travel,Eco Plus,641,3,3,3,3,3,3,3,3,4,5,3,3,4,3,62,62.0,neutral or dissatisfied +12540,71020,Female,Loyal Customer,47,Business travel,Business,802,1,1,5,1,1,3,4,1,1,1,1,1,1,4,24,18.0,neutral or dissatisfied +12541,88784,Female,Loyal Customer,44,Business travel,Business,240,0,0,0,3,4,5,5,4,4,2,2,4,4,4,0,0.0,satisfied +12542,84408,Female,Loyal Customer,20,Personal Travel,Eco,606,3,4,3,3,1,3,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +12543,117705,Male,disloyal Customer,24,Business travel,Eco,1009,4,4,4,3,2,4,2,2,5,2,4,5,4,2,52,26.0,neutral or dissatisfied +12544,62415,Male,Loyal Customer,25,Business travel,Business,2457,1,1,1,1,5,5,5,4,2,3,4,5,3,5,131,122.0,satisfied +12545,13618,Male,Loyal Customer,48,Business travel,Business,1014,5,5,5,5,3,4,4,4,4,4,4,3,4,3,29,47.0,satisfied +12546,13493,Female,Loyal Customer,27,Business travel,Business,227,3,3,3,3,5,4,5,5,4,3,3,3,5,5,12,31.0,satisfied +12547,99636,Female,disloyal Customer,26,Business travel,Eco Plus,1154,1,1,1,4,3,1,4,3,2,1,3,2,4,3,7,18.0,neutral or dissatisfied +12548,38119,Female,Loyal Customer,52,Business travel,Eco,1249,4,1,2,2,5,2,2,4,4,4,4,1,4,3,0,0.0,satisfied +12549,55594,Male,Loyal Customer,40,Business travel,Business,3975,1,1,3,1,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +12550,65446,Male,Loyal Customer,57,Business travel,Business,3488,3,3,3,3,3,4,5,4,4,4,4,4,4,5,62,65.0,satisfied +12551,48497,Male,Loyal Customer,25,Business travel,Business,1797,1,1,5,1,5,5,5,5,1,3,5,1,4,5,0,0.0,satisfied +12552,60095,Female,Loyal Customer,29,Business travel,Business,2797,5,5,5,5,3,3,3,3,3,5,4,4,4,3,0,0.0,satisfied +12553,56400,Female,disloyal Customer,29,Business travel,Business,719,3,3,3,2,2,3,2,2,4,4,4,5,5,2,12,0.0,neutral or dissatisfied +12554,52897,Female,Loyal Customer,63,Personal Travel,Eco,1024,4,4,4,4,5,3,5,4,4,4,4,1,4,1,0,0.0,satisfied +12555,60106,Male,disloyal Customer,23,Business travel,Eco,1005,3,3,3,4,5,3,5,5,4,3,4,3,4,5,1,0.0,neutral or dissatisfied +12556,121219,Male,Loyal Customer,24,Business travel,Business,2075,5,4,5,5,4,4,4,4,3,3,4,5,5,4,7,19.0,satisfied +12557,17984,Female,Loyal Customer,33,Business travel,Business,1991,3,3,3,3,5,2,3,5,5,5,5,5,5,5,0,0.0,satisfied +12558,101429,Female,Loyal Customer,46,Business travel,Business,345,2,4,5,4,4,4,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +12559,88978,Male,Loyal Customer,67,Personal Travel,Eco,1184,1,1,1,3,1,1,1,1,2,1,3,3,2,1,0,0.0,neutral or dissatisfied +12560,67277,Female,Loyal Customer,23,Personal Travel,Eco,1121,1,4,1,1,2,1,2,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +12561,81009,Female,Loyal Customer,59,Business travel,Business,3660,0,0,0,3,4,4,5,5,5,5,5,4,5,3,92,84.0,satisfied +12562,77278,Female,Loyal Customer,35,Business travel,Business,1931,3,1,1,1,3,1,2,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +12563,63981,Female,Loyal Customer,24,Personal Travel,Eco Plus,1192,4,4,4,1,5,4,5,5,3,5,3,4,4,5,5,0.0,neutral or dissatisfied +12564,12209,Female,Loyal Customer,49,Business travel,Business,1502,2,2,4,2,5,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +12565,54073,Female,Loyal Customer,35,Business travel,Business,1416,1,2,2,2,2,2,2,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +12566,102601,Female,Loyal Customer,50,Personal Travel,Eco Plus,386,3,4,3,1,5,4,5,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +12567,85224,Male,Loyal Customer,45,Business travel,Business,882,5,2,5,5,3,4,2,5,5,5,5,1,5,4,0,0.0,satisfied +12568,29095,Female,Loyal Customer,51,Personal Travel,Eco,697,1,5,1,1,5,5,4,2,2,1,2,3,2,5,0,4.0,neutral or dissatisfied +12569,68942,Female,Loyal Customer,70,Personal Travel,Eco,646,4,1,4,3,5,2,3,3,3,4,3,2,3,3,5,20.0,neutral or dissatisfied +12570,108637,Male,Loyal Customer,23,Personal Travel,Eco,1547,0,4,0,3,4,0,4,4,3,3,4,5,4,4,0,0.0,satisfied +12571,126989,Female,Loyal Customer,31,Business travel,Business,1754,5,5,5,5,4,4,4,4,4,4,5,5,5,4,0,1.0,satisfied +12572,45378,Female,Loyal Customer,40,Business travel,Eco Plus,150,3,5,5,5,3,3,3,3,1,2,2,3,2,3,0,0.0,satisfied +12573,89973,Female,Loyal Customer,37,Personal Travel,Eco,1487,3,4,3,5,2,3,2,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +12574,12693,Male,Loyal Customer,25,Business travel,Business,721,3,3,3,3,2,2,2,2,1,2,1,4,3,2,0,0.0,satisfied +12575,33815,Female,Loyal Customer,61,Business travel,Business,2591,3,3,3,3,3,4,3,3,3,3,3,1,3,5,0,11.0,satisfied +12576,34631,Female,disloyal Customer,36,Business travel,Eco,427,3,0,3,4,3,3,3,3,1,4,1,4,3,3,10,0.0,neutral or dissatisfied +12577,113810,Female,disloyal Customer,22,Business travel,Business,397,5,0,5,2,4,0,4,4,4,3,5,4,5,4,0,0.0,satisfied +12578,13156,Female,Loyal Customer,31,Personal Travel,Eco,562,4,5,4,2,2,4,2,2,4,2,5,5,5,2,39,28.0,neutral or dissatisfied +12579,119194,Male,Loyal Customer,52,Business travel,Business,3309,3,3,3,3,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +12580,9877,Male,Loyal Customer,42,Business travel,Business,508,3,4,3,4,3,3,3,3,3,3,3,1,3,3,7,0.0,neutral or dissatisfied +12581,40328,Female,Loyal Customer,24,Business travel,Eco Plus,358,4,3,3,3,4,4,5,4,1,5,4,5,4,4,0,0.0,satisfied +12582,129209,Female,Loyal Customer,50,Personal Travel,Eco,2288,2,5,2,3,1,5,3,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +12583,60711,Female,Loyal Customer,72,Business travel,Eco,1605,2,2,2,2,5,2,2,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +12584,117385,Female,disloyal Customer,32,Business travel,Business,912,3,3,3,4,3,3,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +12585,97761,Female,Loyal Customer,10,Personal Travel,Eco,787,1,4,1,1,2,1,2,2,5,4,4,3,5,2,1,0.0,neutral or dissatisfied +12586,3264,Female,Loyal Customer,61,Business travel,Business,2342,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +12587,103711,Male,Loyal Customer,30,Personal Travel,Eco,251,5,5,0,2,2,0,2,2,5,5,4,5,4,2,0,0.0,satisfied +12588,62373,Male,Loyal Customer,34,Business travel,Business,2704,5,5,5,5,5,3,5,5,5,5,5,5,5,3,1,0.0,satisfied +12589,48283,Male,Loyal Customer,58,Personal Travel,Eco Plus,173,1,5,0,1,0,3,3,3,1,3,4,3,5,3,150,155.0,neutral or dissatisfied +12590,122344,Female,Loyal Customer,34,Business travel,Business,2801,1,1,1,1,2,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +12591,104110,Male,Loyal Customer,32,Personal Travel,Eco,297,3,4,3,2,3,3,3,3,3,5,4,5,4,3,7,0.0,neutral or dissatisfied +12592,1760,Female,Loyal Customer,55,Business travel,Eco Plus,364,2,2,2,2,1,4,4,2,2,2,2,1,2,4,17,17.0,neutral or dissatisfied +12593,6674,Male,Loyal Customer,59,Business travel,Business,438,1,1,1,1,5,5,5,4,4,4,4,5,4,4,8,2.0,satisfied +12594,55590,Female,Loyal Customer,57,Business travel,Business,1839,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +12595,122964,Male,Loyal Customer,30,Business travel,Business,507,4,4,4,4,5,5,5,5,3,4,4,3,5,5,0,0.0,satisfied +12596,49400,Female,Loyal Customer,55,Business travel,Business,3020,3,3,4,3,5,5,3,5,5,5,4,5,5,2,0,0.0,satisfied +12597,8275,Female,Loyal Customer,43,Personal Travel,Eco,125,4,4,4,2,4,2,3,5,5,4,3,3,5,2,0,0.0,neutral or dissatisfied +12598,91584,Male,Loyal Customer,37,Personal Travel,Eco,1123,3,5,3,3,3,4,4,5,3,5,4,4,4,4,211,187.0,neutral or dissatisfied +12599,97144,Male,disloyal Customer,14,Business travel,Eco,1497,2,2,2,4,1,2,1,1,2,1,3,2,3,1,85,70.0,neutral or dissatisfied +12600,100293,Female,Loyal Customer,29,Business travel,Business,1053,2,5,4,5,2,2,2,2,2,1,4,4,3,2,27,35.0,neutral or dissatisfied +12601,55304,Male,disloyal Customer,23,Business travel,Eco,949,5,4,4,2,4,4,5,4,4,5,3,5,4,4,37,39.0,satisfied +12602,85138,Female,Loyal Customer,46,Business travel,Business,3212,5,5,5,5,2,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +12603,89012,Male,Loyal Customer,54,Business travel,Business,2092,1,1,1,1,2,5,5,4,4,4,4,3,4,3,1,2.0,satisfied +12604,88374,Female,disloyal Customer,25,Business travel,Eco,515,1,2,1,2,1,1,1,1,2,5,2,4,2,1,6,0.0,neutral or dissatisfied +12605,43326,Female,disloyal Customer,34,Business travel,Eco,387,4,0,4,3,2,4,3,2,1,4,3,3,4,2,0,0.0,neutral or dissatisfied +12606,80854,Female,Loyal Customer,43,Personal Travel,Eco,484,2,4,2,3,1,4,3,5,5,2,1,2,5,1,13,16.0,neutral or dissatisfied +12607,97450,Female,Loyal Customer,65,Personal Travel,Business,484,1,5,1,4,5,5,5,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +12608,59187,Male,Loyal Customer,12,Personal Travel,Business,1440,4,4,4,2,4,4,1,4,3,4,4,3,4,4,8,0.0,satisfied +12609,101742,Female,Loyal Customer,37,Business travel,Business,1590,5,5,3,5,4,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +12610,11004,Female,Loyal Customer,75,Business travel,Business,2152,3,3,3,3,2,3,1,5,5,5,5,5,5,1,0,0.0,satisfied +12611,108666,Male,Loyal Customer,36,Business travel,Business,484,3,3,3,3,2,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +12612,12248,Female,Loyal Customer,36,Business travel,Business,2063,5,1,5,5,5,3,3,4,4,4,5,2,4,5,0,0.0,satisfied +12613,99724,Male,Loyal Customer,40,Business travel,Business,3584,3,3,3,3,5,4,5,5,5,5,5,4,5,3,7,0.0,satisfied +12614,73454,Female,Loyal Customer,41,Personal Travel,Eco,1005,4,4,3,1,3,3,3,3,4,2,4,5,5,3,0,0.0,satisfied +12615,96175,Female,Loyal Customer,28,Business travel,Business,3572,2,2,5,2,2,2,2,2,3,1,4,4,3,2,31,30.0,neutral or dissatisfied +12616,85309,Male,Loyal Customer,52,Personal Travel,Eco,874,3,5,3,5,4,3,4,4,4,5,4,5,4,4,0,0.0,neutral or dissatisfied +12617,94878,Male,Loyal Customer,39,Business travel,Eco,248,3,4,5,4,3,3,3,3,3,4,4,1,4,3,2,8.0,neutral or dissatisfied +12618,19437,Female,Loyal Customer,67,Personal Travel,Eco,645,2,2,2,3,2,3,3,4,4,2,2,2,4,4,0,0.0,neutral or dissatisfied +12619,26774,Male,Loyal Customer,41,Business travel,Business,3669,3,3,3,3,3,1,1,3,3,3,3,5,3,3,0,1.0,satisfied +12620,56778,Male,Loyal Customer,13,Personal Travel,Eco Plus,937,1,3,1,2,2,1,2,2,3,1,1,5,3,2,0,20.0,neutral or dissatisfied +12621,55414,Male,Loyal Customer,51,Business travel,Business,2521,1,1,1,1,5,5,5,5,2,4,5,5,3,5,0,0.0,satisfied +12622,95656,Male,Loyal Customer,44,Business travel,Business,1514,3,4,4,4,3,3,4,3,3,3,3,3,3,4,24,6.0,neutral or dissatisfied +12623,20921,Male,Loyal Customer,45,Business travel,Eco,689,3,2,2,2,3,3,3,3,4,2,2,3,5,3,0,0.0,satisfied +12624,14917,Female,Loyal Customer,38,Personal Travel,Eco,315,2,3,2,4,4,2,4,4,4,2,4,3,1,4,0,0.0,neutral or dissatisfied +12625,18581,Male,disloyal Customer,40,Business travel,Eco,253,3,2,2,4,4,2,4,4,2,5,3,1,3,4,0,0.0,neutral or dissatisfied +12626,42277,Male,Loyal Customer,23,Business travel,Business,726,3,3,3,3,4,4,4,4,2,1,4,3,1,4,0,0.0,satisfied +12627,10749,Female,Loyal Customer,36,Business travel,Business,3727,4,4,4,4,5,5,4,5,5,5,5,5,5,3,48,41.0,satisfied +12628,102714,Female,Loyal Customer,33,Personal Travel,Eco,365,4,5,4,4,3,4,1,3,3,3,5,5,4,3,13,8.0,satisfied +12629,36380,Female,Loyal Customer,36,Business travel,Business,2958,2,5,5,5,5,2,3,2,2,2,2,2,2,2,27,13.0,neutral or dissatisfied +12630,89392,Male,Loyal Customer,56,Business travel,Business,151,1,2,2,2,3,2,2,1,1,1,1,3,1,4,0,7.0,neutral or dissatisfied +12631,74805,Female,Loyal Customer,40,Business travel,Business,1464,2,2,3,2,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +12632,54416,Female,Loyal Customer,33,Business travel,Eco,305,4,3,2,3,4,4,4,4,3,1,3,5,1,4,0,0.0,satisfied +12633,84977,Female,Loyal Customer,55,Business travel,Business,1590,2,2,2,2,5,3,4,2,2,2,2,4,2,3,1,0.0,satisfied +12634,61613,Female,Loyal Customer,43,Business travel,Business,1635,1,1,5,1,3,4,4,2,2,2,2,3,2,4,3,0.0,satisfied +12635,19739,Female,Loyal Customer,31,Personal Travel,Eco,475,3,4,3,3,4,3,4,4,4,3,2,2,5,4,0,0.0,neutral or dissatisfied +12636,121109,Female,Loyal Customer,11,Personal Travel,Business,2521,3,5,3,4,1,3,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +12637,101311,Female,Loyal Customer,57,Personal Travel,Business,986,2,5,2,4,3,5,5,4,4,2,4,4,4,5,82,67.0,neutral or dissatisfied +12638,37317,Male,Loyal Customer,52,Business travel,Business,2442,1,1,1,1,1,2,2,4,4,4,4,1,4,1,5,0.0,satisfied +12639,14108,Male,Loyal Customer,19,Personal Travel,Eco,371,2,2,2,3,5,2,4,5,2,1,3,4,3,5,1,7.0,neutral or dissatisfied +12640,98977,Female,Loyal Customer,58,Personal Travel,Eco,569,2,3,2,3,1,4,4,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +12641,116401,Male,Loyal Customer,10,Personal Travel,Eco,371,1,1,1,4,2,1,2,2,4,1,4,2,4,2,0,9.0,neutral or dissatisfied +12642,73353,Male,Loyal Customer,41,Business travel,Eco,1012,3,5,5,5,3,3,3,3,3,5,3,2,4,3,1,1.0,neutral or dissatisfied +12643,71599,Female,Loyal Customer,14,Business travel,Business,1012,3,2,2,2,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +12644,112156,Female,Loyal Customer,51,Business travel,Business,1611,5,3,3,3,2,3,4,5,5,4,5,4,5,4,61,53.0,neutral or dissatisfied +12645,20960,Male,Loyal Customer,53,Business travel,Business,721,5,5,5,5,2,5,4,5,5,5,5,2,5,3,0,4.0,satisfied +12646,70879,Female,Loyal Customer,58,Personal Travel,Eco Plus,761,2,4,2,2,4,4,5,3,3,2,4,4,3,4,0,0.0,neutral or dissatisfied +12647,25121,Male,Loyal Customer,40,Personal Travel,Eco,946,2,4,2,2,1,2,1,1,4,4,2,2,4,1,0,0.0,neutral or dissatisfied +12648,101093,Female,Loyal Customer,55,Business travel,Business,2263,3,3,3,3,5,4,5,5,5,5,5,4,5,4,21,15.0,satisfied +12649,74839,Male,Loyal Customer,59,Business travel,Business,297,3,4,4,4,2,3,4,3,3,3,3,2,3,2,5,0.0,neutral or dissatisfied +12650,85781,Female,Loyal Customer,51,Business travel,Business,2300,4,4,4,4,3,4,5,2,2,2,2,4,2,5,1,0.0,satisfied +12651,39435,Female,Loyal Customer,30,Business travel,Eco,129,4,1,1,1,4,5,4,4,1,3,2,4,2,4,0,0.0,satisfied +12652,26602,Female,disloyal Customer,24,Business travel,Eco,406,3,5,3,4,1,3,2,1,3,2,2,1,5,1,0,0.0,neutral or dissatisfied +12653,51115,Male,Loyal Customer,48,Personal Travel,Eco,109,0,5,0,2,4,0,4,4,4,3,5,3,4,4,0,0.0,satisfied +12654,129479,Male,Loyal Customer,49,Business travel,Business,2611,1,1,1,1,3,3,4,4,4,4,4,4,4,3,0,0.0,satisfied +12655,124730,Female,Loyal Customer,27,Personal Travel,Eco,399,1,1,1,3,5,1,5,5,3,5,4,1,4,5,0,0.0,neutral or dissatisfied +12656,23369,Male,Loyal Customer,32,Business travel,Eco,1014,2,2,2,2,2,2,2,2,3,4,3,4,4,2,24,8.0,neutral or dissatisfied +12657,36163,Female,Loyal Customer,44,Business travel,Eco,1674,3,4,4,4,2,5,2,3,3,3,3,3,3,4,51,43.0,satisfied +12658,64252,Female,Loyal Customer,66,Personal Travel,Eco,1660,4,4,4,1,3,4,4,5,5,4,5,5,5,3,15,0.0,neutral or dissatisfied +12659,65626,Female,Loyal Customer,23,Personal Travel,Eco,237,1,5,1,5,4,1,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +12660,23709,Female,Loyal Customer,30,Personal Travel,Eco,251,0,4,0,3,2,0,2,2,4,2,5,5,5,2,0,0.0,satisfied +12661,65520,Female,Loyal Customer,52,Business travel,Business,1616,3,3,3,3,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +12662,116104,Male,Loyal Customer,15,Personal Travel,Eco,342,3,2,3,4,2,3,1,2,4,2,3,4,4,2,9,8.0,neutral or dissatisfied +12663,72650,Male,Loyal Customer,62,Personal Travel,Eco,1119,2,4,2,1,3,2,4,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +12664,87305,Female,Loyal Customer,52,Personal Travel,Eco,577,3,4,3,3,5,5,4,3,3,3,3,5,3,5,0,0.0,neutral or dissatisfied +12665,42452,Female,disloyal Customer,20,Business travel,Eco,866,1,1,1,5,3,1,3,3,1,3,5,2,5,3,13,0.0,neutral or dissatisfied +12666,105620,Male,disloyal Customer,23,Business travel,Eco,883,2,2,2,3,2,2,3,2,5,3,4,5,4,2,28,15.0,neutral or dissatisfied +12667,41831,Female,disloyal Customer,40,Business travel,Business,196,3,3,3,3,5,3,5,5,1,3,5,1,1,5,0,0.0,neutral or dissatisfied +12668,58003,Male,Loyal Customer,43,Business travel,Business,1779,1,1,4,1,2,4,5,5,5,4,5,4,5,3,0,0.0,satisfied +12669,68326,Male,Loyal Customer,32,Business travel,Eco,2165,2,1,1,1,2,2,2,2,1,2,1,4,2,2,0,0.0,neutral or dissatisfied +12670,77007,Female,Loyal Customer,59,Business travel,Business,368,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +12671,68346,Male,disloyal Customer,46,Business travel,Business,1598,3,3,3,2,1,3,1,1,4,4,3,5,4,1,0,4.0,neutral or dissatisfied +12672,113204,Female,Loyal Customer,62,Business travel,Business,3251,4,4,4,4,5,4,4,4,4,4,4,5,4,3,43,35.0,satisfied +12673,2008,Male,Loyal Customer,40,Personal Travel,Eco Plus,351,1,3,1,3,3,1,4,3,1,1,2,4,2,3,0,0.0,neutral or dissatisfied +12674,5022,Male,Loyal Customer,54,Business travel,Business,1966,2,2,2,2,3,5,4,4,4,4,5,5,4,5,0,0.0,satisfied +12675,11390,Female,disloyal Customer,37,Business travel,Business,295,2,2,2,3,2,2,2,2,4,3,5,3,4,2,2,5.0,neutral or dissatisfied +12676,25313,Female,disloyal Customer,25,Business travel,Eco,432,1,3,1,3,2,1,2,2,3,3,4,1,3,2,9,10.0,neutral or dissatisfied +12677,10093,Male,Loyal Customer,42,Business travel,Business,363,2,4,4,4,5,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +12678,74113,Male,disloyal Customer,7,Business travel,Eco,592,1,2,0,3,0,1,1,2,2,4,4,1,1,1,188,244.0,neutral or dissatisfied +12679,7397,Male,Loyal Customer,46,Business travel,Business,2186,2,2,2,2,3,4,5,4,4,4,4,4,4,5,40,27.0,satisfied +12680,52415,Male,Loyal Customer,15,Personal Travel,Eco,261,4,2,4,3,4,4,4,4,2,3,4,4,3,4,0,0.0,neutral or dissatisfied +12681,34482,Male,Loyal Customer,16,Personal Travel,Eco,266,2,0,2,4,3,2,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +12682,99426,Male,Loyal Customer,15,Personal Travel,Eco,337,3,4,4,3,4,4,4,4,4,3,5,4,5,4,7,11.0,neutral or dissatisfied +12683,83116,Male,Loyal Customer,14,Personal Travel,Eco,1127,3,5,4,4,3,4,3,3,4,2,5,4,4,3,0,0.0,neutral or dissatisfied +12684,82671,Male,disloyal Customer,43,Business travel,Business,632,3,3,3,1,2,3,2,2,5,5,4,4,5,2,0,0.0,neutral or dissatisfied +12685,13653,Female,Loyal Customer,32,Business travel,Business,2451,2,2,2,2,2,2,2,2,3,4,3,4,4,2,2,0.0,neutral or dissatisfied +12686,12062,Female,Loyal Customer,16,Personal Travel,Eco,351,4,4,4,4,5,4,5,5,1,2,4,2,3,5,0,0.0,neutral or dissatisfied +12687,31327,Male,Loyal Customer,38,Personal Travel,Eco,1123,5,5,4,3,2,4,2,2,4,3,5,5,4,2,31,29.0,satisfied +12688,84451,Male,Loyal Customer,44,Business travel,Business,290,2,2,4,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +12689,603,Female,disloyal Customer,24,Business travel,Eco,270,4,0,4,3,4,4,4,4,5,4,5,4,4,4,0,0.0,neutral or dissatisfied +12690,10330,Female,Loyal Customer,54,Business travel,Business,3719,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,4.0,satisfied +12691,33498,Female,Loyal Customer,26,Personal Travel,Eco Plus,2496,2,5,2,4,5,2,5,5,2,1,5,3,3,5,0,0.0,neutral or dissatisfied +12692,7876,Female,disloyal Customer,34,Business travel,Eco,910,2,2,2,4,5,2,5,5,4,4,4,2,4,5,0,0.0,neutral or dissatisfied +12693,39847,Female,Loyal Customer,44,Business travel,Eco,272,5,5,4,5,2,4,1,4,4,5,4,1,4,4,0,0.0,satisfied +12694,40252,Female,Loyal Customer,24,Business travel,Business,347,3,1,1,1,3,3,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +12695,73333,Female,Loyal Customer,53,Business travel,Business,1182,5,5,5,5,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +12696,122819,Male,Loyal Customer,16,Personal Travel,Eco,599,2,2,2,4,1,2,1,1,4,2,4,3,4,1,5,12.0,neutral or dissatisfied +12697,35253,Male,Loyal Customer,47,Business travel,Eco,1035,4,3,3,3,5,4,5,5,3,3,4,2,4,5,1,3.0,neutral or dissatisfied +12698,33992,Female,Loyal Customer,25,Business travel,Business,1598,4,4,4,4,5,5,5,5,3,5,5,3,5,5,0,0.0,satisfied +12699,12042,Male,disloyal Customer,34,Business travel,Eco,376,2,0,2,5,3,2,1,3,5,2,2,4,5,3,0,,neutral or dissatisfied +12700,6026,Female,disloyal Customer,27,Business travel,Business,691,0,0,0,4,3,0,3,3,3,4,5,5,4,3,0,0.0,satisfied +12701,100983,Male,Loyal Customer,32,Personal Travel,Eco,1524,1,5,1,3,5,1,5,5,3,4,3,4,1,5,24,0.0,neutral or dissatisfied +12702,107252,Female,disloyal Customer,58,Business travel,Business,307,3,3,3,4,5,3,5,5,4,5,5,5,5,5,50,71.0,neutral or dissatisfied +12703,115234,Male,disloyal Customer,45,Business travel,Eco,390,1,2,1,3,1,1,1,1,4,5,3,4,3,1,0,0.0,neutral or dissatisfied +12704,45686,Male,Loyal Customer,30,Business travel,Business,826,2,2,2,2,4,4,4,4,2,2,2,4,3,4,4,0.0,satisfied +12705,104596,Male,Loyal Customer,16,Personal Travel,Eco,369,2,3,2,4,4,2,4,4,1,5,4,1,4,4,6,4.0,neutral or dissatisfied +12706,78897,Female,Loyal Customer,22,Business travel,Business,1727,1,1,1,1,1,1,1,1,1,4,2,2,4,1,9,34.0,neutral or dissatisfied +12707,83298,Female,Loyal Customer,23,Business travel,Business,1956,3,4,3,3,4,4,4,4,3,2,3,3,5,4,1,25.0,satisfied +12708,112554,Female,Loyal Customer,50,Business travel,Eco Plus,846,2,3,5,5,2,3,4,3,3,2,3,3,3,4,24,11.0,neutral or dissatisfied +12709,16222,Male,Loyal Customer,58,Personal Travel,Business,266,3,0,3,2,3,5,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +12710,84091,Female,Loyal Customer,70,Personal Travel,Eco,932,2,5,2,5,3,5,5,2,2,2,3,4,2,5,2,11.0,neutral or dissatisfied +12711,54592,Male,disloyal Customer,24,Business travel,Business,964,4,4,3,3,2,3,2,2,4,5,4,4,4,2,5,0.0,satisfied +12712,12621,Male,Loyal Customer,57,Personal Travel,Eco,802,1,5,1,3,2,1,2,2,2,3,4,4,2,2,0,0.0,neutral or dissatisfied +12713,68955,Male,Loyal Customer,60,Personal Travel,Business,700,3,4,3,3,2,5,4,1,1,3,1,3,1,5,70,61.0,neutral or dissatisfied +12714,87974,Female,disloyal Customer,32,Business travel,Business,545,2,2,2,4,4,2,4,4,5,2,5,5,4,4,10,9.0,neutral or dissatisfied +12715,127288,Male,Loyal Customer,55,Business travel,Business,2460,1,1,4,1,4,4,5,5,5,5,5,3,5,4,2,17.0,satisfied +12716,21665,Male,disloyal Customer,30,Business travel,Eco,746,2,2,2,5,1,2,1,1,2,2,5,3,5,1,0,0.0,neutral or dissatisfied +12717,13886,Female,Loyal Customer,17,Personal Travel,Eco,667,3,5,3,5,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +12718,37095,Male,disloyal Customer,19,Business travel,Eco,1046,1,1,1,3,5,1,5,5,5,3,4,3,3,5,66,56.0,neutral or dissatisfied +12719,5601,Male,Loyal Customer,30,Business travel,Business,3263,1,1,1,1,3,4,3,3,3,2,5,3,5,3,23,23.0,satisfied +12720,16424,Female,Loyal Customer,38,Business travel,Eco,529,5,2,2,2,5,5,5,5,1,4,5,5,3,5,0,0.0,satisfied +12721,54237,Female,Loyal Customer,45,Business travel,Business,1222,4,4,4,4,3,5,5,5,5,5,5,4,5,2,0,0.0,satisfied +12722,103479,Male,Loyal Customer,53,Business travel,Business,382,1,1,1,1,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +12723,76283,Male,Loyal Customer,40,Personal Travel,Eco,1927,2,5,2,2,1,2,1,1,4,3,5,4,5,1,21,8.0,neutral or dissatisfied +12724,96566,Female,Loyal Customer,54,Business travel,Business,333,1,1,1,1,2,5,5,4,4,4,4,3,4,4,0,1.0,satisfied +12725,17913,Female,Loyal Customer,24,Business travel,Business,2495,4,4,4,4,5,5,5,5,2,5,4,1,1,5,0,0.0,satisfied +12726,51923,Female,Loyal Customer,14,Business travel,Eco Plus,601,5,2,2,2,5,5,5,5,1,5,1,5,3,5,0,0.0,satisfied +12727,81424,Female,Loyal Customer,52,Business travel,Eco,393,3,1,1,1,1,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +12728,64675,Male,Loyal Customer,21,Business travel,Business,190,2,2,2,2,5,5,4,5,3,2,4,5,5,5,0,5.0,satisfied +12729,54816,Male,Loyal Customer,32,Business travel,Eco,862,0,0,0,2,5,0,5,5,2,2,2,5,3,5,0,0.0,satisfied +12730,62850,Male,Loyal Customer,53,Personal Travel,Business,2218,2,1,2,3,3,3,2,3,3,2,4,4,3,4,3,0.0,neutral or dissatisfied +12731,92594,Female,Loyal Customer,55,Business travel,Business,2342,2,2,2,2,4,3,5,5,5,5,5,3,5,5,6,0.0,satisfied +12732,84292,Female,disloyal Customer,49,Business travel,Business,235,2,2,2,3,1,2,1,1,4,5,4,3,4,1,0,0.0,satisfied +12733,102225,Male,disloyal Customer,64,Business travel,Business,258,3,4,4,3,1,3,1,1,4,5,5,5,5,1,15,0.0,neutral or dissatisfied +12734,88183,Male,Loyal Customer,53,Business travel,Business,444,1,1,1,1,2,2,2,5,3,5,5,2,5,2,160,153.0,satisfied +12735,124195,Female,Loyal Customer,48,Business travel,Business,2176,3,3,3,3,4,4,4,4,2,5,4,4,4,4,135,118.0,satisfied +12736,71444,Female,disloyal Customer,52,Business travel,Business,867,4,4,4,3,3,4,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +12737,112695,Female,disloyal Customer,33,Business travel,Business,605,3,3,3,4,2,3,2,2,4,5,5,4,5,2,11,0.0,neutral or dissatisfied +12738,56415,Female,Loyal Customer,58,Business travel,Business,2091,3,3,4,3,5,5,4,4,4,4,4,5,4,3,59,50.0,satisfied +12739,90694,Male,Loyal Customer,23,Business travel,Business,581,4,4,5,4,4,4,4,4,5,5,4,4,5,4,0,14.0,satisfied +12740,3173,Female,Loyal Customer,40,Business travel,Business,693,5,5,5,5,3,4,4,4,4,4,4,5,4,5,47,30.0,satisfied +12741,82891,Female,Loyal Customer,63,Personal Travel,Eco,645,5,5,5,2,4,4,5,4,4,5,4,3,4,4,0,0.0,satisfied +12742,69079,Female,Loyal Customer,65,Personal Travel,Eco,1389,4,5,4,2,5,5,5,4,4,4,4,4,4,4,8,0.0,neutral or dissatisfied +12743,41148,Female,Loyal Customer,46,Personal Travel,Eco,140,4,4,4,5,5,1,2,4,4,4,4,3,4,4,64,50.0,neutral or dissatisfied +12744,112430,Male,Loyal Customer,44,Business travel,Business,1642,1,1,1,1,2,5,4,4,4,4,4,3,4,4,3,0.0,satisfied +12745,67391,Male,disloyal Customer,18,Business travel,Eco,722,0,0,0,2,3,0,3,3,4,2,5,4,4,3,14,17.0,satisfied +12746,3898,Female,Loyal Customer,50,Business travel,Business,213,1,5,3,3,3,2,1,1,1,1,1,3,1,1,0,2.0,neutral or dissatisfied +12747,18446,Male,Loyal Customer,41,Business travel,Business,2083,3,3,3,3,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +12748,12986,Female,Loyal Customer,42,Business travel,Eco,374,4,3,3,3,1,3,1,4,4,4,4,2,4,2,52,42.0,satisfied +12749,12226,Male,Loyal Customer,21,Personal Travel,Business,127,2,1,0,2,3,0,3,3,3,3,2,4,2,3,0,0.0,neutral or dissatisfied +12750,3750,Female,disloyal Customer,22,Business travel,Eco,431,1,1,1,1,1,1,1,1,3,2,1,3,2,1,0,0.0,neutral or dissatisfied +12751,86379,Female,Loyal Customer,44,Business travel,Business,2616,4,4,4,4,4,5,4,5,5,5,5,3,5,3,5,3.0,satisfied +12752,19985,Female,Loyal Customer,66,Business travel,Business,3530,2,2,2,2,1,2,1,4,4,4,4,3,4,2,67,85.0,satisfied +12753,74184,Female,Loyal Customer,66,Personal Travel,Eco,678,3,4,3,4,4,4,4,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +12754,115547,Female,Loyal Customer,24,Business travel,Business,2751,3,4,4,4,3,3,3,3,2,5,3,1,3,3,0,0.0,neutral or dissatisfied +12755,108579,Male,Loyal Customer,55,Business travel,Business,813,3,3,3,3,5,4,5,3,3,3,3,5,3,3,81,68.0,satisfied +12756,14391,Female,disloyal Customer,22,Business travel,Eco,789,5,5,5,3,4,5,4,4,2,4,3,3,2,4,0,0.0,satisfied +12757,9063,Male,disloyal Customer,19,Business travel,Eco,108,2,1,2,4,4,2,4,4,2,5,4,2,4,4,59,65.0,neutral or dissatisfied +12758,23252,Male,Loyal Customer,43,Business travel,Business,3782,1,1,1,1,3,3,3,4,4,4,4,1,4,1,0,0.0,satisfied +12759,51889,Female,Loyal Customer,50,Business travel,Eco,601,3,5,5,5,2,1,5,3,3,3,3,3,3,3,0,0.0,satisfied +12760,47523,Female,Loyal Customer,56,Personal Travel,Eco,541,2,4,2,3,4,3,3,2,2,2,2,1,2,2,0,3.0,neutral or dissatisfied +12761,43088,Male,Loyal Customer,56,Personal Travel,Eco,236,3,5,3,3,1,3,1,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +12762,47092,Female,Loyal Customer,69,Personal Travel,Eco,639,1,2,1,4,4,4,3,1,1,1,1,1,1,3,84,114.0,neutral or dissatisfied +12763,103149,Female,disloyal Customer,32,Business travel,Business,272,2,1,1,1,1,1,1,1,4,3,5,4,5,1,2,0.0,neutral or dissatisfied +12764,23862,Male,Loyal Customer,11,Personal Travel,Eco,552,1,4,1,1,2,1,2,2,4,5,4,5,3,2,0,0.0,neutral or dissatisfied +12765,118458,Female,disloyal Customer,43,Business travel,Business,370,2,2,2,4,3,2,3,3,4,3,4,5,4,3,26,32.0,neutral or dissatisfied +12766,97373,Male,Loyal Customer,66,Personal Travel,Eco,347,2,4,2,3,4,2,4,4,4,4,5,5,5,4,119,115.0,neutral or dissatisfied +12767,44105,Female,disloyal Customer,21,Business travel,Eco,257,3,3,3,4,2,3,2,2,4,4,3,2,3,2,0,0.0,neutral or dissatisfied +12768,7428,Male,Loyal Customer,25,Business travel,Eco,552,1,3,3,3,1,1,3,1,3,2,4,1,4,1,14,10.0,neutral or dissatisfied +12769,95684,Female,Loyal Customer,49,Personal Travel,Business,181,2,4,2,1,5,4,5,5,5,2,5,4,5,3,10,1.0,neutral or dissatisfied +12770,64662,Female,Loyal Customer,53,Business travel,Business,247,0,0,0,4,2,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +12771,100209,Female,Loyal Customer,41,Business travel,Business,2238,5,5,5,5,2,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +12772,79594,Female,Loyal Customer,40,Business travel,Business,2406,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +12773,89356,Male,Loyal Customer,10,Personal Travel,Eco,1541,4,1,4,1,3,4,3,3,3,3,2,4,1,3,0,0.0,satisfied +12774,109119,Male,Loyal Customer,49,Personal Travel,Eco Plus,849,2,3,2,1,1,2,1,1,5,5,5,4,4,1,0,0.0,neutral or dissatisfied +12775,54887,Male,Loyal Customer,54,Personal Travel,Eco,862,2,1,2,3,1,2,1,1,4,3,3,2,2,1,5,0.0,neutral or dissatisfied +12776,98627,Male,Loyal Customer,66,Business travel,Eco,992,1,1,3,1,1,1,1,1,3,5,3,1,3,1,4,0.0,neutral or dissatisfied +12777,42249,Female,disloyal Customer,39,Business travel,Business,817,3,3,3,3,4,3,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +12778,104516,Female,Loyal Customer,52,Business travel,Eco,942,1,1,1,1,4,4,4,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +12779,107171,Female,Loyal Customer,25,Business travel,Business,3177,3,5,5,5,3,4,3,3,2,2,4,4,4,3,30,27.0,neutral or dissatisfied +12780,48837,Female,Loyal Customer,51,Personal Travel,Business,190,2,1,0,3,3,4,3,1,1,0,1,3,1,4,13,14.0,neutral or dissatisfied +12781,100674,Female,Loyal Customer,36,Business travel,Eco,628,3,4,4,4,3,3,3,3,4,3,3,2,3,3,50,41.0,neutral or dissatisfied +12782,100204,Male,Loyal Customer,56,Business travel,Business,2702,3,3,3,3,4,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +12783,18979,Female,Loyal Customer,24,Business travel,Business,2679,2,5,5,5,2,2,2,2,2,3,3,1,3,2,0,6.0,neutral or dissatisfied +12784,16925,Female,Loyal Customer,32,Business travel,Business,1524,4,4,4,4,4,4,4,4,2,3,2,4,2,4,15,9.0,satisfied +12785,94794,Female,Loyal Customer,45,Business travel,Eco,562,3,3,3,3,3,4,3,3,3,3,3,3,3,1,12,0.0,neutral or dissatisfied +12786,109410,Male,Loyal Customer,28,Business travel,Business,2823,1,1,1,1,3,4,3,3,3,3,4,4,5,3,0,0.0,satisfied +12787,67736,Male,disloyal Customer,36,Business travel,Eco,1465,3,2,2,2,1,3,1,1,2,2,1,4,2,1,0,0.0,neutral or dissatisfied +12788,51273,Female,disloyal Customer,40,Business travel,Business,199,4,4,4,3,3,4,3,3,1,5,1,1,1,3,118,124.0,neutral or dissatisfied +12789,48561,Male,Loyal Customer,40,Personal Travel,Eco,737,2,1,2,4,5,2,5,5,3,4,4,2,3,5,0,7.0,neutral or dissatisfied +12790,74894,Female,Loyal Customer,39,Business travel,Business,2475,1,1,3,1,5,5,4,4,4,4,4,5,4,5,0,,satisfied +12791,14963,Female,Loyal Customer,32,Business travel,Business,3838,1,1,1,1,3,5,3,3,4,1,1,5,5,3,0,0.0,satisfied +12792,38882,Female,Loyal Customer,19,Business travel,Business,1784,5,5,3,5,4,4,4,4,4,3,3,2,5,4,0,2.0,satisfied +12793,129760,Male,Loyal Customer,41,Business travel,Eco,308,1,4,4,4,1,1,1,1,2,4,3,3,3,1,0,0.0,neutral or dissatisfied +12794,122554,Male,Loyal Customer,12,Personal Travel,Eco,500,0,5,0,1,2,0,2,2,5,2,4,5,5,2,0,0.0,satisfied +12795,3745,Female,Loyal Customer,43,Personal Travel,Eco,427,1,2,5,3,2,3,4,2,2,5,2,1,2,1,0,0.0,neutral or dissatisfied +12796,39771,Female,Loyal Customer,32,Business travel,Business,521,2,4,4,4,2,2,2,2,2,1,3,4,4,2,13,11.0,neutral or dissatisfied +12797,60496,Female,disloyal Customer,27,Business travel,Business,862,2,2,2,3,3,2,3,3,4,5,5,4,5,3,10,2.0,neutral or dissatisfied +12798,93512,Female,Loyal Customer,42,Business travel,Eco Plus,1107,3,3,3,3,5,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +12799,29096,Male,Loyal Customer,44,Personal Travel,Eco,1050,4,5,4,2,4,4,1,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +12800,27594,Male,Loyal Customer,58,Personal Travel,Eco,954,2,3,2,3,3,2,2,3,5,3,2,5,4,3,28,48.0,neutral or dissatisfied +12801,20474,Male,Loyal Customer,41,Personal Travel,Eco Plus,177,4,3,4,2,2,4,2,2,5,2,1,4,1,2,30,20.0,neutral or dissatisfied +12802,111385,Male,Loyal Customer,39,Business travel,Business,773,2,3,3,3,5,4,4,2,2,2,2,4,2,3,4,20.0,neutral or dissatisfied +12803,85157,Male,Loyal Customer,52,Business travel,Business,689,2,2,2,2,5,4,5,5,5,5,5,5,5,5,4,0.0,satisfied +12804,14919,Male,Loyal Customer,8,Personal Travel,Eco,343,3,4,3,5,4,3,4,4,3,5,4,4,5,4,0,0.0,neutral or dissatisfied +12805,62219,Male,Loyal Customer,59,Personal Travel,Eco,2425,4,2,4,3,3,4,3,3,3,5,3,4,3,3,39,0.0,neutral or dissatisfied +12806,22729,Female,Loyal Customer,42,Business travel,Business,1968,5,5,5,5,4,5,2,5,5,5,3,1,5,3,0,0.0,satisfied +12807,72535,Male,Loyal Customer,22,Business travel,Business,985,3,5,5,5,3,3,3,3,4,2,3,3,3,3,0,16.0,neutral or dissatisfied +12808,121369,Male,Loyal Customer,53,Personal Travel,Eco,1670,4,2,4,4,4,4,4,4,2,5,4,4,3,4,0,17.0,neutral or dissatisfied +12809,98163,Female,Loyal Customer,53,Personal Travel,Eco,562,1,4,1,1,5,5,5,1,1,1,1,5,1,5,0,0.0,neutral or dissatisfied +12810,57488,Male,Loyal Customer,55,Business travel,Business,1782,5,5,5,5,4,5,5,2,2,2,2,3,2,3,8,2.0,satisfied +12811,125355,Male,disloyal Customer,26,Business travel,Eco,599,1,2,1,2,5,1,5,5,1,5,3,1,2,5,94,126.0,neutral or dissatisfied +12812,9289,Male,Loyal Customer,43,Personal Travel,Eco,1157,2,4,3,3,2,3,2,2,5,4,5,4,5,2,0,12.0,neutral or dissatisfied +12813,87450,Female,Loyal Customer,58,Business travel,Business,321,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +12814,46992,Male,Loyal Customer,51,Business travel,Eco Plus,776,4,1,1,1,4,4,4,4,1,4,2,5,3,4,27,29.0,satisfied +12815,13736,Male,Loyal Customer,57,Business travel,Eco,401,2,3,4,3,2,2,2,2,5,2,1,2,5,2,186,172.0,satisfied +12816,2850,Female,Loyal Customer,17,Business travel,Business,2711,3,1,1,1,3,2,3,3,1,5,4,2,4,3,11,15.0,neutral or dissatisfied +12817,127433,Male,Loyal Customer,46,Personal Travel,Eco,868,1,5,2,4,2,2,2,2,2,3,1,4,3,2,0,3.0,neutral or dissatisfied +12818,15862,Female,Loyal Customer,52,Business travel,Business,2858,4,4,4,4,4,2,4,4,4,4,4,2,4,5,0,0.0,satisfied +12819,1165,Female,Loyal Customer,55,Personal Travel,Eco,354,2,5,2,1,3,2,5,1,1,2,5,2,1,5,39,47.0,neutral or dissatisfied +12820,35802,Male,Loyal Customer,45,Business travel,Business,937,4,4,4,4,5,4,4,5,5,5,5,3,5,4,2,5.0,satisfied +12821,55680,Female,Loyal Customer,55,Business travel,Business,2865,1,1,1,1,2,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +12822,6638,Male,disloyal Customer,27,Business travel,Business,416,4,4,4,5,4,4,4,4,3,5,4,5,4,4,17,18.0,satisfied +12823,44317,Female,Loyal Customer,35,Personal Travel,Eco,837,4,4,4,3,2,4,2,2,4,5,5,5,5,2,0,0.0,satisfied +12824,33591,Male,Loyal Customer,42,Business travel,Eco,474,5,4,4,4,5,5,5,5,5,2,3,2,2,5,3,0.0,satisfied +12825,10684,Male,Loyal Customer,47,Business travel,Eco,216,2,2,2,2,2,2,2,2,4,4,2,4,3,2,21,29.0,neutral or dissatisfied +12826,6829,Female,Loyal Customer,44,Personal Travel,Eco,303,2,5,2,5,2,5,5,5,5,5,4,5,3,5,134,168.0,neutral or dissatisfied +12827,123912,Male,Loyal Customer,19,Personal Travel,Eco,544,3,4,3,2,4,3,4,4,3,4,5,1,1,4,30,37.0,neutral or dissatisfied +12828,103045,Male,disloyal Customer,23,Business travel,Eco,546,3,4,3,3,2,3,2,2,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +12829,92897,Male,disloyal Customer,25,Business travel,Business,134,1,0,1,5,5,1,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +12830,17183,Female,Loyal Customer,33,Personal Travel,Eco,643,3,5,3,3,2,3,4,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +12831,77789,Female,Loyal Customer,18,Personal Travel,Eco,731,4,4,4,4,1,4,1,1,1,4,3,4,3,1,0,0.0,neutral or dissatisfied +12832,83815,Male,Loyal Customer,46,Business travel,Business,425,4,4,4,4,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +12833,84676,Female,disloyal Customer,18,Business travel,Eco,1028,3,3,3,4,4,3,3,4,3,5,4,2,4,4,16,34.0,neutral or dissatisfied +12834,90179,Male,Loyal Customer,32,Personal Travel,Eco,1127,2,4,1,1,1,1,1,1,5,2,3,3,5,1,48,21.0,neutral or dissatisfied +12835,126910,Male,disloyal Customer,41,Business travel,Business,646,1,1,1,4,1,1,1,1,3,4,5,3,4,1,31,23.0,neutral or dissatisfied +12836,66849,Male,Loyal Customer,46,Personal Travel,Eco,731,3,2,3,3,4,3,4,4,2,4,3,4,3,4,124,115.0,neutral or dissatisfied +12837,51549,Female,Loyal Customer,46,Business travel,Eco,455,5,3,3,3,3,1,1,4,4,5,4,5,4,1,41,29.0,satisfied +12838,54588,Female,Loyal Customer,53,Business travel,Business,3032,5,5,5,5,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +12839,122300,Female,Loyal Customer,69,Personal Travel,Eco,544,3,4,3,1,1,2,2,4,4,3,4,5,4,4,0,5.0,neutral or dissatisfied +12840,25086,Male,Loyal Customer,54,Business travel,Business,2716,1,1,1,1,1,2,3,4,4,4,4,2,4,5,0,0.0,satisfied +12841,73770,Female,Loyal Customer,12,Personal Travel,Eco,192,3,4,0,2,1,0,1,1,5,5,4,3,5,1,0,2.0,neutral or dissatisfied +12842,28168,Female,disloyal Customer,36,Business travel,Eco,459,2,2,2,4,1,2,1,1,3,1,3,3,4,1,0,5.0,neutral or dissatisfied +12843,94319,Female,Loyal Customer,65,Business travel,Business,1741,0,0,0,1,2,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +12844,2798,Male,Loyal Customer,27,Personal Travel,Eco,764,2,5,2,4,4,2,4,4,2,1,3,3,2,4,0,14.0,neutral or dissatisfied +12845,114737,Female,Loyal Customer,55,Business travel,Business,308,3,3,3,3,3,4,5,5,5,5,5,4,5,3,13,2.0,satisfied +12846,56597,Male,Loyal Customer,50,Business travel,Business,1703,2,2,2,2,5,4,5,5,5,5,5,5,5,3,2,3.0,satisfied +12847,108316,Male,Loyal Customer,35,Business travel,Business,1750,3,3,2,3,5,4,5,5,5,5,5,3,5,4,2,0.0,satisfied +12848,35165,Female,Loyal Customer,44,Business travel,Eco,1035,4,3,3,3,4,5,5,4,2,1,1,5,3,5,162,178.0,satisfied +12849,10734,Female,Loyal Customer,60,Business travel,Business,429,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +12850,62723,Female,Loyal Customer,31,Business travel,Business,2338,2,2,2,2,5,5,5,5,3,5,4,3,5,5,0,0.0,satisfied +12851,14533,Male,Loyal Customer,45,Business travel,Eco,368,4,4,4,4,4,4,4,4,1,3,4,1,1,4,0,0.0,satisfied +12852,29997,Female,Loyal Customer,63,Business travel,Business,3893,1,5,5,5,3,4,3,4,4,4,1,4,4,4,0,0.0,neutral or dissatisfied +12853,119385,Male,Loyal Customer,49,Business travel,Business,2820,1,1,1,1,2,4,4,4,4,4,4,5,4,4,62,66.0,satisfied +12854,94241,Male,Loyal Customer,45,Business travel,Business,319,4,4,4,4,4,4,5,4,4,5,4,3,4,5,3,0.0,satisfied +12855,66265,Female,Loyal Customer,46,Personal Travel,Eco,550,2,0,2,2,4,2,1,5,5,2,5,2,5,3,13,12.0,neutral or dissatisfied +12856,127562,Male,Loyal Customer,43,Business travel,Business,1670,1,1,1,1,4,3,4,2,2,2,2,3,2,5,0,0.0,satisfied +12857,128084,Male,Loyal Customer,41,Business travel,Eco,2917,3,4,4,4,3,3,3,1,5,1,3,3,3,3,20,36.0,neutral or dissatisfied +12858,90786,Female,Loyal Customer,26,Business travel,Business,3025,2,3,3,3,2,2,2,2,1,5,4,1,4,2,19,9.0,neutral or dissatisfied +12859,22726,Male,Loyal Customer,30,Business travel,Business,2292,3,3,5,3,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +12860,27519,Male,Loyal Customer,21,Personal Travel,Eco,1050,1,4,1,2,3,1,3,3,4,3,4,4,4,3,50,39.0,neutral or dissatisfied +12861,96414,Male,Loyal Customer,40,Personal Travel,Eco,1342,1,4,1,1,5,1,5,5,3,5,4,4,4,5,0,0.0,neutral or dissatisfied +12862,63908,Male,Loyal Customer,48,Business travel,Business,772,3,3,3,3,4,3,3,4,4,5,4,2,4,1,0,0.0,satisfied +12863,42746,Male,Loyal Customer,67,Personal Travel,Business,419,4,3,4,3,3,4,4,4,4,4,4,1,4,3,3,0.0,satisfied +12864,12215,Male,Loyal Customer,40,Business travel,Business,192,2,2,2,2,5,4,4,4,4,5,5,5,4,5,0,0.0,satisfied +12865,81502,Female,Loyal Customer,37,Personal Travel,Eco,528,1,4,1,5,3,1,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +12866,40309,Male,Loyal Customer,61,Personal Travel,Eco,402,3,2,5,1,3,5,3,3,3,3,2,4,2,3,0,2.0,neutral or dissatisfied +12867,113097,Female,Loyal Customer,14,Personal Travel,Eco,543,4,4,4,2,3,4,3,3,4,2,5,3,4,3,10,10.0,neutral or dissatisfied +12868,18429,Female,Loyal Customer,43,Business travel,Business,3612,2,2,2,2,2,4,4,4,4,4,5,3,4,3,0,0.0,satisfied +12869,56084,Male,Loyal Customer,42,Business travel,Business,2475,4,3,4,4,5,5,5,3,5,5,5,5,3,5,0,0.0,satisfied +12870,104584,Male,Loyal Customer,51,Business travel,Business,2005,4,5,5,5,3,4,3,4,4,4,4,4,4,2,51,54.0,neutral or dissatisfied +12871,27196,Female,Loyal Customer,29,Business travel,Eco,2182,4,5,5,5,4,4,4,4,3,3,3,2,2,4,0,0.0,neutral or dissatisfied +12872,86393,Female,Loyal Customer,49,Business travel,Business,853,3,3,3,3,4,5,4,5,5,5,5,3,5,5,7,0.0,satisfied +12873,18350,Male,Loyal Customer,37,Personal Travel,Eco,200,2,5,2,2,4,2,4,4,2,2,1,3,2,4,14,14.0,neutral or dissatisfied +12874,5090,Female,Loyal Customer,37,Business travel,Eco,235,4,4,4,4,4,4,4,4,5,2,5,2,2,4,0,22.0,satisfied +12875,94363,Female,Loyal Customer,41,Business travel,Business,2858,5,5,3,5,2,4,5,4,4,4,4,4,4,3,59,43.0,satisfied +12876,595,Male,Loyal Customer,44,Business travel,Business,229,5,5,5,5,3,5,4,5,5,5,5,5,5,5,36,22.0,satisfied +12877,50616,Male,Loyal Customer,8,Personal Travel,Eco,109,3,2,3,4,3,3,3,3,4,5,3,3,4,3,25,24.0,neutral or dissatisfied +12878,708,Male,Loyal Customer,38,Business travel,Business,3358,1,4,4,4,3,2,3,3,3,3,1,1,3,4,0,0.0,neutral or dissatisfied +12879,75473,Male,Loyal Customer,49,Personal Travel,Eco,2342,2,1,2,2,5,2,5,5,2,1,2,4,3,5,7,6.0,neutral or dissatisfied +12880,114608,Male,Loyal Customer,51,Business travel,Business,2986,2,2,2,2,3,4,5,5,5,5,5,4,5,4,3,5.0,satisfied +12881,4623,Female,Loyal Customer,42,Business travel,Business,2089,2,2,2,2,5,4,4,2,2,2,2,3,2,4,0,0.0,satisfied +12882,33898,Female,Loyal Customer,55,Personal Travel,Eco,1504,2,3,2,3,2,3,3,4,4,4,4,3,1,3,265,253.0,neutral or dissatisfied +12883,23841,Female,Loyal Customer,22,Business travel,Eco Plus,715,5,4,4,4,5,5,5,5,1,5,5,3,3,5,0,0.0,satisfied +12884,129877,Male,Loyal Customer,41,Personal Travel,Eco Plus,308,3,5,3,4,2,3,2,2,5,5,5,5,4,2,0,0.0,neutral or dissatisfied +12885,47934,Female,Loyal Customer,30,Personal Travel,Eco,329,3,2,3,1,5,3,5,5,2,4,1,3,2,5,75,57.0,neutral or dissatisfied +12886,97544,Female,disloyal Customer,35,Business travel,Eco,675,4,4,4,4,4,4,4,4,4,4,1,5,5,4,16,1.0,neutral or dissatisfied +12887,10971,Female,disloyal Customer,40,Business travel,Business,458,3,3,3,3,5,3,5,5,4,2,4,4,3,5,0,0.0,neutral or dissatisfied +12888,61323,Female,disloyal Customer,25,Business travel,Eco Plus,462,4,3,5,4,2,5,3,2,1,5,3,2,3,2,25,19.0,neutral or dissatisfied +12889,20313,Female,Loyal Customer,11,Personal Travel,Eco,900,2,5,2,1,4,2,4,4,4,5,3,1,5,4,0,0.0,neutral or dissatisfied +12890,21939,Female,disloyal Customer,18,Business travel,Eco,551,1,0,1,3,3,1,1,3,2,2,3,2,3,3,25,19.0,neutral or dissatisfied +12891,37654,Female,Loyal Customer,26,Personal Travel,Eco,944,2,3,2,3,2,2,3,2,3,5,3,2,4,2,5,0.0,neutral or dissatisfied +12892,45068,Female,Loyal Customer,49,Personal Travel,Eco,342,3,4,3,3,3,4,5,3,3,3,3,5,3,5,11,20.0,neutral or dissatisfied +12893,84624,Female,Loyal Customer,39,Personal Travel,Eco,669,1,5,0,2,3,0,1,3,4,3,5,4,5,3,5,20.0,neutral or dissatisfied +12894,122762,Male,Loyal Customer,51,Business travel,Business,2071,5,5,4,5,2,5,5,5,5,5,5,4,5,5,0,3.0,satisfied +12895,27558,Male,Loyal Customer,37,Personal Travel,Eco,954,3,3,4,4,2,4,2,2,4,5,3,1,3,2,0,25.0,neutral or dissatisfied +12896,11098,Female,Loyal Customer,55,Personal Travel,Eco,309,1,5,1,5,3,5,4,2,2,1,2,5,2,4,0,5.0,neutral or dissatisfied +12897,95565,Male,Loyal Customer,46,Personal Travel,Eco Plus,458,3,3,3,1,2,3,2,2,1,2,3,5,4,2,0,8.0,neutral or dissatisfied +12898,22967,Male,Loyal Customer,29,Business travel,Business,489,2,5,5,5,2,2,2,2,4,4,2,3,3,2,0,0.0,neutral or dissatisfied +12899,9470,Female,Loyal Customer,30,Business travel,Eco Plus,368,2,2,2,2,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +12900,69516,Male,Loyal Customer,47,Business travel,Business,2475,5,5,5,5,3,3,3,4,3,4,5,3,5,3,0,0.0,satisfied +12901,78019,Male,Loyal Customer,60,Business travel,Business,3441,0,1,1,3,3,1,3,2,2,4,4,1,2,3,0,0.0,satisfied +12902,46380,Female,disloyal Customer,20,Business travel,Eco,1013,2,3,3,3,5,3,5,5,2,3,2,5,5,5,0,0.0,neutral or dissatisfied +12903,67387,Male,Loyal Customer,39,Business travel,Business,3455,1,1,1,1,3,5,5,4,4,4,4,3,4,4,13,0.0,satisfied +12904,98494,Male,Loyal Customer,58,Business travel,Business,2710,1,1,1,1,3,3,3,5,4,4,5,3,3,3,136,140.0,satisfied +12905,23314,Female,Loyal Customer,39,Business travel,Business,1845,1,3,3,3,4,2,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +12906,11865,Female,Loyal Customer,47,Business travel,Business,3441,1,1,1,1,3,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +12907,93888,Female,Loyal Customer,49,Business travel,Business,1690,3,5,5,5,2,4,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +12908,64041,Male,disloyal Customer,48,Business travel,Business,919,3,3,3,2,4,3,5,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +12909,45007,Female,Loyal Customer,70,Business travel,Business,118,2,1,1,1,4,3,4,2,2,2,2,2,2,3,0,5.0,neutral or dissatisfied +12910,75076,Female,Loyal Customer,38,Personal Travel,Eco,2611,2,2,2,4,2,2,2,2,3,3,2,1,3,2,0,0.0,neutral or dissatisfied +12911,73610,Female,disloyal Customer,25,Business travel,Eco,204,1,3,1,4,4,1,4,4,2,1,3,1,3,4,0,5.0,neutral or dissatisfied +12912,66324,Female,Loyal Customer,20,Personal Travel,Eco,852,1,4,2,3,3,2,2,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +12913,44499,Male,Loyal Customer,68,Business travel,Eco,503,4,1,1,1,4,4,4,4,1,1,5,1,2,4,0,0.0,satisfied +12914,4170,Female,Loyal Customer,16,Personal Travel,Eco,427,2,4,2,4,3,2,3,3,1,5,4,4,4,3,0,0.0,neutral or dissatisfied +12915,173,Female,Loyal Customer,57,Business travel,Business,227,1,1,1,1,2,5,4,5,5,5,5,4,5,4,10,10.0,satisfied +12916,61847,Male,Loyal Customer,67,Business travel,Eco Plus,1346,1,4,4,4,1,1,1,1,2,4,4,4,4,1,11,0.0,neutral or dissatisfied +12917,14490,Male,Loyal Customer,63,Personal Travel,Eco,495,3,4,3,3,4,3,3,4,3,4,4,4,4,4,0,31.0,neutral or dissatisfied +12918,124507,Male,Loyal Customer,9,Personal Travel,Eco,930,4,4,4,5,2,4,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +12919,111467,Female,Loyal Customer,20,Personal Travel,Eco,1024,2,4,2,3,4,2,2,4,3,4,4,5,4,4,45,34.0,neutral or dissatisfied +12920,2895,Male,Loyal Customer,61,Personal Travel,Eco,409,3,1,3,1,5,3,4,5,3,4,1,1,2,5,20,12.0,neutral or dissatisfied +12921,101222,Male,Loyal Customer,47,Business travel,Business,1069,5,5,5,5,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +12922,17018,Female,disloyal Customer,22,Business travel,Eco,781,2,2,2,3,2,2,2,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +12923,20618,Male,Loyal Customer,52,Personal Travel,Eco,864,1,5,1,1,5,1,3,5,5,5,4,4,5,5,21,13.0,neutral or dissatisfied +12924,12703,Female,Loyal Customer,44,Business travel,Eco,851,1,2,2,2,5,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +12925,21851,Male,Loyal Customer,33,Personal Travel,Business,551,2,1,2,3,1,2,1,1,2,5,3,2,2,1,0,0.0,neutral or dissatisfied +12926,23495,Male,Loyal Customer,28,Personal Travel,Business,303,3,5,3,5,4,3,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +12927,21600,Female,disloyal Customer,36,Business travel,Eco,780,2,2,2,2,4,2,4,4,1,2,4,5,5,4,99,98.0,neutral or dissatisfied +12928,5919,Male,Loyal Customer,37,Personal Travel,Eco,173,2,5,2,3,2,1,3,4,5,5,1,3,4,3,115,148.0,neutral or dissatisfied +12929,33238,Male,Loyal Customer,48,Business travel,Eco Plus,102,4,4,4,4,4,4,4,4,3,5,1,2,2,4,0,0.0,satisfied +12930,19093,Female,Loyal Customer,57,Personal Travel,Eco,296,0,2,0,3,5,2,3,1,1,0,1,4,1,4,0,0.0,satisfied +12931,93571,Female,Loyal Customer,59,Business travel,Business,1891,3,3,3,3,5,5,4,5,5,5,4,5,5,5,0,4.0,satisfied +12932,102038,Male,Loyal Customer,31,Business travel,Business,1972,2,2,2,2,5,5,5,5,3,3,5,4,5,5,11,8.0,satisfied +12933,88891,Male,Loyal Customer,21,Business travel,Eco,859,2,3,5,3,2,2,3,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +12934,98868,Female,Loyal Customer,56,Business travel,Business,3726,1,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +12935,10216,Female,Loyal Customer,24,Business travel,Business,3332,2,2,2,2,5,4,5,5,4,2,5,3,5,5,61,69.0,satisfied +12936,43217,Female,disloyal Customer,62,Business travel,Eco,423,3,3,3,3,3,3,3,3,3,2,2,4,2,3,6,7.0,neutral or dissatisfied +12937,123215,Male,Loyal Customer,46,Personal Travel,Eco,600,3,4,4,3,5,4,5,5,1,1,4,1,3,5,0,0.0,neutral or dissatisfied +12938,54481,Female,Loyal Customer,54,Business travel,Eco,925,3,3,3,3,4,3,4,3,3,3,3,3,3,3,0,0.0,satisfied +12939,101273,Male,Loyal Customer,18,Business travel,Business,1910,2,2,2,2,4,4,4,4,5,2,4,3,5,4,0,0.0,satisfied +12940,107357,Female,disloyal Customer,35,Business travel,Eco,584,2,0,3,2,4,3,4,4,1,4,5,4,4,4,7,0.0,neutral or dissatisfied +12941,71820,Male,disloyal Customer,31,Business travel,Eco,981,1,1,1,2,5,1,5,5,1,4,1,3,3,5,0,0.0,neutral or dissatisfied +12942,90298,Male,Loyal Customer,30,Personal Travel,Eco,932,2,5,1,3,4,1,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +12943,30112,Female,Loyal Customer,67,Personal Travel,Eco,261,2,1,2,3,3,3,4,5,5,2,5,3,5,3,54,56.0,neutral or dissatisfied +12944,49518,Female,disloyal Customer,36,Business travel,Eco,262,3,0,3,1,5,3,2,5,4,5,5,1,3,5,16,13.0,neutral or dissatisfied +12945,95689,Male,disloyal Customer,42,Business travel,Business,453,2,2,2,4,3,2,3,3,4,2,4,5,4,3,8,0.0,neutral or dissatisfied +12946,3877,Female,Loyal Customer,37,Business travel,Business,3812,2,2,2,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +12947,100197,Male,Loyal Customer,28,Business travel,Business,2220,4,4,4,4,4,4,4,4,5,5,4,3,5,4,0,0.0,satisfied +12948,85444,Female,disloyal Customer,34,Business travel,Business,332,2,2,2,4,2,2,2,2,3,5,4,5,5,2,33,44.0,neutral or dissatisfied +12949,63494,Male,Loyal Customer,41,Personal Travel,Eco Plus,651,3,1,3,4,3,3,3,3,1,5,4,4,3,3,0,0.0,neutral or dissatisfied +12950,122457,Male,disloyal Customer,24,Business travel,Eco,575,5,0,5,4,4,5,4,4,5,5,5,3,5,4,0,0.0,satisfied +12951,84604,Female,disloyal Customer,23,Business travel,Eco,669,4,4,4,4,2,4,2,2,4,2,4,1,3,2,1,0.0,neutral or dissatisfied +12952,97047,Male,Loyal Customer,21,Personal Travel,Business,715,3,5,3,5,2,3,2,2,4,5,5,3,5,2,91,106.0,neutral or dissatisfied +12953,22057,Female,Loyal Customer,34,Business travel,Business,3699,3,1,4,4,5,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +12954,17846,Male,disloyal Customer,28,Business travel,Eco,636,3,3,3,3,2,3,2,2,1,4,3,1,3,2,0,,neutral or dissatisfied +12955,61345,Female,Loyal Customer,58,Business travel,Business,2389,5,5,5,5,4,5,5,5,5,5,5,4,5,5,5,0.0,satisfied +12956,2960,Female,disloyal Customer,28,Business travel,Business,835,5,5,5,5,3,5,3,3,5,5,4,3,4,3,0,0.0,satisfied +12957,101522,Male,Loyal Customer,13,Personal Travel,Eco,345,3,3,3,3,2,3,2,2,3,1,3,5,3,2,20,19.0,neutral or dissatisfied +12958,89462,Male,Loyal Customer,37,Personal Travel,Eco,134,2,0,0,2,5,0,5,5,5,2,3,5,1,5,90,88.0,neutral or dissatisfied +12959,12636,Male,Loyal Customer,38,Business travel,Eco,844,2,5,5,5,2,2,2,2,3,3,3,4,4,2,64,42.0,neutral or dissatisfied +12960,127730,Female,Loyal Customer,32,Business travel,Business,2373,2,3,3,3,2,2,2,2,2,5,4,1,4,2,0,2.0,neutral or dissatisfied +12961,113543,Male,Loyal Customer,37,Business travel,Business,1954,4,2,2,2,3,3,3,4,4,3,4,1,4,4,10,4.0,neutral or dissatisfied +12962,5721,Male,Loyal Customer,40,Personal Travel,Eco,299,1,5,1,4,3,1,3,3,3,2,5,4,4,3,0,0.0,neutral or dissatisfied +12963,88494,Male,disloyal Customer,17,Business travel,Eco,250,5,4,5,1,2,5,2,2,4,5,2,5,5,2,0,0.0,satisfied +12964,19603,Male,Loyal Customer,65,Personal Travel,Eco Plus,173,3,2,3,3,4,3,4,4,4,5,4,2,4,4,0,0.0,neutral or dissatisfied +12965,69027,Male,Loyal Customer,53,Business travel,Business,1391,1,1,1,1,3,4,4,5,5,5,5,3,5,5,0,17.0,satisfied +12966,22934,Male,Loyal Customer,51,Business travel,Eco,489,4,5,5,5,4,4,4,4,5,1,5,5,4,4,15,10.0,satisfied +12967,23391,Male,Loyal Customer,40,Business travel,Business,483,3,3,3,3,5,5,4,5,5,5,5,5,5,3,61,76.0,satisfied +12968,55301,Male,Loyal Customer,60,Business travel,Business,2072,3,5,5,5,2,3,2,3,3,3,3,4,3,3,68,53.0,neutral or dissatisfied +12969,106083,Female,Loyal Customer,53,Business travel,Business,2569,1,1,1,1,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +12970,14818,Female,Loyal Customer,30,Business travel,Business,563,4,4,5,4,4,4,4,4,1,1,5,2,3,4,0,7.0,satisfied +12971,116453,Female,Loyal Customer,19,Personal Travel,Eco,373,4,4,4,4,2,4,2,2,2,4,4,4,4,2,0,0.0,satisfied +12972,58234,Male,Loyal Customer,37,Personal Travel,Eco,925,2,4,2,5,2,2,2,2,3,3,4,5,4,2,1,7.0,neutral or dissatisfied +12973,46203,Female,Loyal Customer,45,Business travel,Business,679,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,17.0,satisfied +12974,49766,Male,Loyal Customer,47,Business travel,Business,2005,2,2,3,2,1,3,2,4,4,4,4,1,4,2,0,0.0,satisfied +12975,88150,Male,Loyal Customer,44,Business travel,Business,3222,4,4,4,4,3,4,5,5,5,4,5,3,5,5,47,49.0,satisfied +12976,46173,Female,Loyal Customer,66,Personal Travel,Eco,604,2,4,2,4,4,5,4,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +12977,53496,Female,Loyal Customer,31,Personal Travel,Eco,2288,4,3,4,4,4,5,3,4,2,4,4,3,3,3,0,13.0,neutral or dissatisfied +12978,86769,Female,disloyal Customer,25,Business travel,Business,484,1,0,1,4,4,1,4,4,4,2,5,4,4,4,0,3.0,neutral or dissatisfied +12979,17322,Female,Loyal Customer,37,Personal Travel,Eco,403,1,4,1,3,3,1,4,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +12980,29720,Male,Loyal Customer,54,Personal Travel,Business,2797,2,4,2,3,2,3,5,3,5,3,3,5,1,5,0,0.0,neutral or dissatisfied +12981,18895,Female,Loyal Customer,49,Business travel,Eco,448,2,2,2,2,3,4,4,2,2,2,2,2,2,4,6,8.0,neutral or dissatisfied +12982,54647,Female,Loyal Customer,44,Business travel,Business,2275,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +12983,9428,Male,Loyal Customer,57,Business travel,Business,299,2,2,2,2,3,4,4,4,4,4,4,5,4,4,23,18.0,satisfied +12984,123249,Male,Loyal Customer,49,Personal Travel,Eco,328,2,0,2,1,4,2,3,4,5,4,5,4,5,4,0,8.0,neutral or dissatisfied +12985,75455,Male,Loyal Customer,56,Business travel,Business,830,1,3,3,3,1,4,3,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +12986,12684,Male,Loyal Customer,46,Business travel,Eco,689,3,3,3,3,3,3,3,3,2,4,3,5,3,3,5,3.0,satisfied +12987,27491,Male,Loyal Customer,52,Business travel,Business,1592,0,5,0,1,4,1,2,1,1,1,1,3,1,2,0,0.0,satisfied +12988,16331,Female,Loyal Customer,25,Personal Travel,Eco,602,1,5,1,2,5,1,5,5,3,4,4,3,5,5,0,1.0,neutral or dissatisfied +12989,98424,Male,Loyal Customer,56,Business travel,Business,1910,1,1,1,1,4,4,4,5,5,5,5,3,5,3,59,44.0,satisfied +12990,81250,Male,disloyal Customer,27,Business travel,Business,1020,4,4,4,1,1,4,1,1,5,2,5,3,4,1,0,0.0,satisfied +12991,11610,Female,Loyal Customer,28,Personal Travel,Eco,657,2,4,2,4,1,2,5,1,2,4,2,5,1,1,0,0.0,neutral or dissatisfied +12992,64979,Female,disloyal Customer,27,Business travel,Eco,224,4,0,4,3,1,4,1,1,3,2,1,2,4,1,0,0.0,neutral or dissatisfied +12993,74502,Female,disloyal Customer,20,Business travel,Business,1438,5,1,5,4,4,5,4,4,3,2,4,5,5,4,0,2.0,satisfied +12994,100996,Male,Loyal Customer,52,Business travel,Business,1884,3,3,3,3,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +12995,103657,Female,Loyal Customer,54,Business travel,Business,2179,4,4,4,4,4,5,4,4,4,4,4,4,4,5,7,0.0,satisfied +12996,82409,Male,Loyal Customer,38,Business travel,Business,502,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +12997,30475,Male,disloyal Customer,27,Business travel,Eco,377,3,4,3,5,2,3,5,2,4,1,4,2,5,2,0,0.0,neutral or dissatisfied +12998,5302,Female,Loyal Customer,43,Personal Travel,Eco,351,3,4,3,2,4,5,5,5,5,3,3,5,5,5,0,0.0,neutral or dissatisfied +12999,95277,Male,Loyal Customer,46,Personal Travel,Eco,293,4,1,4,4,2,4,4,2,1,3,4,1,4,2,0,0.0,neutral or dissatisfied +13000,30204,Male,Loyal Customer,15,Business travel,Eco Plus,399,4,4,4,4,4,4,5,4,1,4,4,5,1,4,0,0.0,satisfied +13001,117065,Male,Loyal Customer,24,Business travel,Business,3202,3,3,3,3,5,5,5,5,3,5,5,5,5,5,2,0.0,satisfied +13002,125216,Male,Loyal Customer,25,Personal Travel,Eco,651,2,5,2,2,4,2,4,4,4,2,4,2,1,4,1,0.0,neutral or dissatisfied +13003,69367,Male,Loyal Customer,44,Business travel,Business,1096,3,3,5,3,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +13004,93159,Male,Loyal Customer,60,Business travel,Business,3556,4,2,2,2,5,2,2,4,4,4,4,3,4,4,40,26.0,neutral or dissatisfied +13005,121215,Female,Loyal Customer,21,Personal Travel,Business,2075,2,5,2,1,3,2,3,3,2,5,5,2,3,3,0,0.0,neutral or dissatisfied +13006,75555,Female,Loyal Customer,52,Business travel,Business,337,3,3,3,3,4,4,4,5,5,5,5,4,5,4,41,33.0,satisfied +13007,119455,Male,Loyal Customer,33,Personal Travel,Business,759,4,4,4,1,5,4,5,5,4,5,5,4,5,5,0,6.0,neutral or dissatisfied +13008,120286,Female,Loyal Customer,47,Business travel,Business,3959,4,4,4,4,3,3,5,5,5,5,5,5,5,3,71,58.0,satisfied +13009,82082,Female,Loyal Customer,77,Business travel,Eco,1276,4,4,4,4,4,4,4,4,1,3,3,4,3,4,190,215.0,neutral or dissatisfied +13010,12266,Male,Loyal Customer,43,Business travel,Eco,190,5,2,2,2,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +13011,43302,Female,Loyal Customer,65,Business travel,Eco,463,5,5,5,5,5,2,1,5,5,5,5,3,5,1,0,0.0,satisfied +13012,101416,Female,Loyal Customer,41,Personal Travel,Eco,486,2,4,2,3,5,2,5,5,4,4,5,4,4,5,35,25.0,neutral or dissatisfied +13013,100005,Male,Loyal Customer,51,Business travel,Business,220,4,4,4,4,3,4,5,5,5,5,4,5,5,4,0,0.0,satisfied +13014,119004,Male,Loyal Customer,13,Personal Travel,Eco,459,3,4,3,3,3,3,3,3,3,5,5,4,5,3,0,0.0,neutral or dissatisfied +13015,48574,Male,Loyal Customer,36,Personal Travel,Eco,819,2,3,2,4,2,2,2,2,2,2,2,4,5,2,0,0.0,neutral or dissatisfied +13016,49377,Female,Loyal Customer,48,Business travel,Business,3956,0,3,0,3,2,2,3,5,5,5,5,1,5,2,0,0.0,satisfied +13017,76363,Female,Loyal Customer,43,Business travel,Business,931,3,3,3,3,5,4,5,4,4,5,4,4,4,5,0,3.0,satisfied +13018,18859,Male,Loyal Customer,18,Business travel,Eco,500,4,5,5,5,4,5,4,4,5,5,3,2,1,4,13,12.0,satisfied +13019,72316,Male,Loyal Customer,68,Personal Travel,Eco Plus,919,4,4,4,5,2,4,2,2,5,4,3,3,2,2,26,18.0,neutral or dissatisfied +13020,14482,Female,Loyal Customer,25,Business travel,Eco,495,0,3,0,4,3,0,3,3,3,5,5,4,3,3,0,0.0,satisfied +13021,2393,Male,disloyal Customer,38,Business travel,Business,767,3,3,3,3,4,3,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +13022,112071,Female,Loyal Customer,51,Business travel,Business,1491,1,1,1,1,4,4,4,2,2,2,2,3,2,4,2,0.0,satisfied +13023,123131,Female,Loyal Customer,31,Business travel,Business,2895,4,3,3,3,4,4,4,4,3,5,3,2,2,4,0,0.0,neutral or dissatisfied +13024,4856,Male,Loyal Customer,33,Business travel,Business,408,4,4,4,4,5,5,5,5,1,1,2,2,5,5,1,5.0,satisfied +13025,34984,Female,Loyal Customer,16,Personal Travel,Eco,273,3,4,3,1,3,3,3,3,3,3,5,5,2,3,50,75.0,neutral or dissatisfied +13026,32391,Female,disloyal Customer,27,Business travel,Eco,101,3,2,3,3,4,3,4,4,2,5,4,1,4,4,0,2.0,neutral or dissatisfied +13027,66874,Female,Loyal Customer,41,Business travel,Business,2705,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,2.0,satisfied +13028,45799,Male,Loyal Customer,42,Business travel,Eco,391,2,3,5,3,2,2,2,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +13029,9067,Male,disloyal Customer,24,Business travel,Eco,160,2,4,2,3,4,2,4,4,3,1,3,4,4,4,0,0.0,neutral or dissatisfied +13030,29283,Female,Loyal Customer,29,Business travel,Business,834,3,2,2,2,3,3,3,3,1,5,4,3,3,3,0,0.0,neutral or dissatisfied +13031,74260,Female,Loyal Customer,54,Business travel,Business,3325,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,39.0,satisfied +13032,129779,Male,Loyal Customer,37,Personal Travel,Eco,421,4,5,4,2,3,4,4,3,3,3,3,2,4,3,0,0.0,satisfied +13033,99681,Female,Loyal Customer,58,Business travel,Business,2140,1,1,5,1,2,4,4,4,4,4,4,3,4,3,23,27.0,satisfied +13034,46497,Female,Loyal Customer,44,Business travel,Eco,73,2,4,4,4,5,3,2,2,2,2,2,3,2,3,0,0.0,satisfied +13035,81710,Female,disloyal Customer,36,Business travel,Business,907,2,1,1,1,4,1,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +13036,11271,Female,Loyal Customer,59,Personal Travel,Eco,166,4,3,4,3,2,4,4,3,3,4,3,5,3,4,0,0.0,neutral or dissatisfied +13037,122417,Male,Loyal Customer,48,Business travel,Business,1916,2,3,3,3,1,2,1,2,2,3,2,1,2,1,4,50.0,neutral or dissatisfied +13038,38112,Female,Loyal Customer,26,Business travel,Business,1185,4,4,5,5,4,3,4,4,4,3,4,3,4,4,24,18.0,neutral or dissatisfied +13039,22181,Female,Loyal Customer,66,Business travel,Business,2322,3,5,4,4,4,4,4,3,3,3,3,1,3,4,96,84.0,neutral or dissatisfied +13040,71778,Male,disloyal Customer,39,Business travel,Business,1726,2,1,1,1,5,1,3,5,3,4,4,3,4,5,0,17.0,neutral or dissatisfied +13041,47671,Female,Loyal Customer,65,Personal Travel,Eco,1242,4,4,4,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +13042,40132,Male,Loyal Customer,61,Business travel,Eco Plus,368,5,3,1,3,5,5,5,5,2,2,2,2,3,5,13,4.0,satisfied +13043,110781,Male,Loyal Customer,22,Business travel,Business,3696,3,2,2,2,3,3,3,3,2,2,4,3,3,3,12,11.0,neutral or dissatisfied +13044,20135,Male,Loyal Customer,44,Personal Travel,Eco,416,2,5,2,2,2,2,2,2,5,2,5,1,1,2,0,0.0,neutral or dissatisfied +13045,50173,Male,Loyal Customer,46,Business travel,Business,190,2,5,5,5,3,4,3,3,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +13046,53246,Male,Loyal Customer,33,Business travel,Eco Plus,612,4,5,5,5,4,4,4,4,3,2,1,1,5,4,17,0.0,satisfied +13047,88810,Female,disloyal Customer,20,Business travel,Eco Plus,404,2,2,2,4,3,2,3,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +13048,59823,Male,Loyal Customer,54,Business travel,Business,1068,1,1,1,1,4,5,4,3,3,4,3,3,3,5,2,0.0,satisfied +13049,37491,Male,Loyal Customer,49,Business travel,Eco,1069,5,4,4,4,5,5,5,5,3,5,1,5,3,5,15,5.0,satisfied +13050,96589,Female,Loyal Customer,59,Business travel,Business,861,5,5,4,5,4,5,4,4,4,4,4,5,4,5,22,19.0,satisfied +13051,86232,Male,disloyal Customer,25,Business travel,Eco,306,2,1,2,4,3,2,3,3,3,3,3,4,3,3,29,29.0,neutral or dissatisfied +13052,115506,Female,Loyal Customer,25,Business travel,Business,3670,2,5,5,5,2,2,2,2,3,2,2,3,1,2,43,59.0,neutral or dissatisfied +13053,29592,Female,Loyal Customer,53,Business travel,Business,1448,5,5,5,5,1,3,4,5,5,5,5,1,5,3,2,0.0,satisfied +13054,88611,Male,Loyal Customer,21,Personal Travel,Eco,404,2,3,2,4,1,2,1,1,5,4,2,2,5,1,1,0.0,neutral or dissatisfied +13055,91646,Male,Loyal Customer,17,Personal Travel,Eco,1199,4,3,4,1,3,4,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +13056,112356,Male,Loyal Customer,23,Business travel,Business,2531,2,2,2,2,4,4,4,4,5,2,5,5,4,4,1,11.0,satisfied +13057,60636,Female,Loyal Customer,60,Business travel,Business,1620,1,1,1,1,4,4,4,5,5,5,5,3,5,4,7,0.0,satisfied +13058,35861,Female,Loyal Customer,45,Personal Travel,Eco,1065,4,2,4,3,1,4,3,3,3,4,3,1,3,4,0,3.0,neutral or dissatisfied +13059,10919,Male,Loyal Customer,46,Business travel,Eco,301,3,2,2,2,3,3,3,3,4,2,2,3,3,3,0,0.0,neutral or dissatisfied +13060,97747,Female,Loyal Customer,49,Business travel,Business,3917,1,1,1,1,2,5,4,3,3,3,3,5,3,3,0,0.0,satisfied +13061,48722,Male,Loyal Customer,33,Business travel,Business,2823,3,3,3,3,5,5,4,5,4,4,5,4,4,5,0,0.0,satisfied +13062,90953,Female,disloyal Customer,28,Business travel,Eco,406,3,0,3,2,1,3,4,1,4,5,2,4,4,1,1,0.0,neutral or dissatisfied +13063,106034,Female,Loyal Customer,45,Personal Travel,Eco,682,3,5,3,1,4,5,4,5,5,3,3,3,5,3,20,28.0,neutral or dissatisfied +13064,97461,Female,Loyal Customer,46,Business travel,Business,2589,4,4,4,4,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +13065,7906,Male,Loyal Customer,38,Business travel,Business,1020,1,1,2,1,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +13066,89076,Female,Loyal Customer,60,Business travel,Eco,2139,2,3,2,3,1,3,2,2,2,2,2,4,2,3,40,16.0,neutral or dissatisfied +13067,71537,Female,Loyal Customer,30,Business travel,Business,1197,1,1,1,1,4,4,4,4,4,3,5,3,5,4,0,0.0,satisfied +13068,22674,Male,Loyal Customer,41,Business travel,Eco,589,5,3,3,3,5,5,5,5,4,5,3,5,4,5,0,0.0,satisfied +13069,71576,Female,Loyal Customer,54,Business travel,Business,2598,5,5,5,5,5,5,5,4,4,4,4,4,4,4,0,2.0,satisfied +13070,66651,Male,Loyal Customer,25,Business travel,Business,978,2,5,2,2,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +13071,57663,Female,Loyal Customer,45,Personal Travel,Eco,200,3,4,3,3,3,2,4,3,1,2,1,4,3,4,590,608.0,neutral or dissatisfied +13072,79858,Female,Loyal Customer,43,Business travel,Business,3696,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +13073,44221,Male,Loyal Customer,52,Business travel,Eco,222,2,5,5,5,2,2,2,2,2,5,4,2,5,2,82,66.0,satisfied +13074,115543,Male,disloyal Customer,34,Business travel,Eco,373,1,1,1,3,5,1,5,5,1,5,3,3,3,5,0,0.0,neutral or dissatisfied +13075,66024,Male,Loyal Customer,22,Business travel,Business,1911,5,5,3,5,3,3,3,3,4,4,5,4,4,3,114,106.0,satisfied +13076,89744,Male,Loyal Customer,33,Personal Travel,Eco,1096,4,2,4,4,3,4,2,3,4,4,3,3,4,3,22,64.0,neutral or dissatisfied +13077,103099,Female,Loyal Customer,22,Personal Travel,Eco,687,2,5,2,2,2,2,2,2,3,2,4,3,5,2,5,0.0,neutral or dissatisfied +13078,14717,Male,Loyal Customer,32,Personal Travel,Eco,419,4,3,4,2,1,4,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +13079,2874,Male,Loyal Customer,27,Personal Travel,Eco,491,3,2,3,2,3,3,3,1,5,2,2,3,1,3,181,201.0,neutral or dissatisfied +13080,125974,Male,Loyal Customer,50,Business travel,Business,2654,4,2,4,4,3,5,4,5,5,4,5,5,5,4,6,1.0,satisfied +13081,12900,Male,Loyal Customer,42,Business travel,Eco,674,1,2,2,2,1,1,1,1,2,2,4,4,3,1,0,5.0,neutral or dissatisfied +13082,112343,Female,Loyal Customer,44,Business travel,Business,3812,3,3,3,3,4,5,5,5,5,5,5,3,5,3,5,2.0,satisfied +13083,90774,Male,Loyal Customer,68,Business travel,Business,250,2,4,4,4,3,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +13084,32540,Female,Loyal Customer,54,Business travel,Eco,101,4,4,4,4,4,2,2,4,4,4,4,2,4,4,0,5.0,neutral or dissatisfied +13085,21718,Female,Loyal Customer,41,Business travel,Eco,821,3,1,1,1,3,3,3,3,3,2,4,4,3,3,0,6.0,satisfied +13086,129062,Female,Loyal Customer,24,Personal Travel,Eco,1846,3,3,3,4,3,2,2,3,1,4,3,2,2,2,249,313.0,neutral or dissatisfied +13087,121176,Male,Loyal Customer,62,Personal Travel,Eco,2521,2,4,2,1,3,2,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +13088,22298,Male,disloyal Customer,20,Business travel,Eco,208,5,3,5,1,3,5,3,3,5,4,3,4,4,3,0,0.0,satisfied +13089,124367,Female,Loyal Customer,59,Business travel,Business,808,1,1,2,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +13090,4113,Male,disloyal Customer,26,Business travel,Business,431,4,4,5,2,3,5,3,3,4,3,5,4,5,3,7,0.0,neutral or dissatisfied +13091,20940,Male,disloyal Customer,30,Business travel,Eco,803,1,1,1,4,3,1,3,3,2,2,3,3,3,3,94,86.0,neutral or dissatisfied +13092,104397,Male,disloyal Customer,20,Business travel,Eco,1147,1,1,1,3,1,1,1,1,4,4,4,4,4,1,26,10.0,neutral or dissatisfied +13093,54881,Male,Loyal Customer,23,Personal Travel,Eco,641,2,5,2,4,2,2,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +13094,14590,Male,Loyal Customer,11,Personal Travel,Eco,986,3,5,4,3,1,4,1,1,4,5,4,5,5,1,8,31.0,neutral or dissatisfied +13095,8265,Male,Loyal Customer,42,Personal Travel,Eco,402,2,4,3,2,2,3,2,2,5,2,4,3,5,2,0,16.0,neutral or dissatisfied +13096,99557,Male,Loyal Customer,10,Business travel,Eco,973,4,4,4,4,4,4,1,4,2,2,4,1,4,4,105,120.0,neutral or dissatisfied +13097,4329,Male,Loyal Customer,47,Business travel,Business,1637,1,1,1,1,5,4,4,2,2,2,2,3,2,4,2,43.0,satisfied +13098,22827,Female,Loyal Customer,32,Business travel,Eco,147,0,0,0,4,4,0,5,4,1,2,1,5,5,4,0,0.0,satisfied +13099,54988,Female,Loyal Customer,51,Business travel,Business,3320,5,5,5,5,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +13100,46950,Male,Loyal Customer,43,Personal Travel,Eco,845,3,4,3,3,4,3,4,4,4,5,4,3,4,4,88,84.0,neutral or dissatisfied +13101,25445,Male,disloyal Customer,29,Business travel,Eco,669,3,2,2,4,5,2,2,5,4,3,2,4,5,5,0,0.0,neutral or dissatisfied +13102,3526,Male,Loyal Customer,60,Business travel,Business,557,1,2,2,2,2,4,3,1,1,1,1,2,1,3,0,26.0,neutral or dissatisfied +13103,73931,Male,Loyal Customer,32,Business travel,Eco,2342,3,1,1,1,3,3,3,4,2,2,3,3,2,3,0,22.0,neutral or dissatisfied +13104,84324,Male,disloyal Customer,36,Business travel,Business,591,2,2,2,5,3,2,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +13105,125376,Female,disloyal Customer,21,Business travel,Business,1440,4,0,4,1,4,4,4,4,3,4,5,4,4,4,0,40.0,satisfied +13106,79324,Male,Loyal Customer,57,Business travel,Business,3111,1,1,1,1,3,5,4,5,5,5,5,3,5,5,38,28.0,satisfied +13107,75184,Male,disloyal Customer,31,Business travel,Eco,1723,3,3,3,2,1,3,1,1,3,3,2,2,3,1,0,19.0,neutral or dissatisfied +13108,79038,Male,Loyal Customer,35,Business travel,Eco,226,2,3,3,3,2,2,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +13109,83057,Male,Loyal Customer,43,Business travel,Business,1145,3,5,5,5,4,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +13110,75271,Female,Loyal Customer,40,Personal Travel,Eco,1846,4,5,4,1,2,4,3,2,1,5,3,3,3,2,0,0.0,satisfied +13111,93486,Female,Loyal Customer,57,Business travel,Business,1107,2,2,2,2,4,5,5,5,5,5,5,5,5,4,1,0.0,satisfied +13112,15103,Male,Loyal Customer,57,Personal Travel,Eco,239,2,3,0,3,3,0,3,3,2,3,2,2,3,3,0,0.0,neutral or dissatisfied +13113,100581,Female,Loyal Customer,31,Business travel,Business,486,2,5,5,5,2,2,2,2,4,1,3,2,3,2,66,47.0,neutral or dissatisfied +13114,69890,Female,Loyal Customer,41,Business travel,Business,1514,3,3,3,3,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +13115,119294,Male,Loyal Customer,44,Business travel,Eco,214,2,3,3,3,2,2,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +13116,8023,Female,Loyal Customer,55,Business travel,Business,294,0,0,0,4,3,4,4,1,1,1,1,5,1,5,0,0.0,satisfied +13117,8703,Male,Loyal Customer,48,Personal Travel,Eco,280,4,3,4,3,3,4,3,3,2,4,5,2,5,3,0,0.0,satisfied +13118,82734,Male,Loyal Customer,43,Business travel,Business,409,1,1,1,1,4,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +13119,47650,Male,Loyal Customer,27,Business travel,Eco,1504,2,5,5,5,2,2,2,2,4,4,4,2,4,2,89,95.0,neutral or dissatisfied +13120,107818,Female,Loyal Customer,42,Business travel,Business,349,2,2,2,2,1,4,3,2,2,2,2,3,2,4,21,10.0,neutral or dissatisfied +13121,61146,Female,disloyal Customer,23,Business travel,Business,967,5,5,5,1,2,5,2,2,3,2,5,3,4,2,0,0.0,satisfied +13122,108597,Male,Loyal Customer,46,Business travel,Business,3108,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +13123,50666,Female,Loyal Customer,61,Personal Travel,Eco,109,2,4,2,4,4,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +13124,69345,Female,Loyal Customer,27,Business travel,Business,3194,5,5,5,5,4,4,4,4,3,4,4,5,5,4,31,21.0,satisfied +13125,125075,Female,Loyal Customer,41,Business travel,Business,3758,1,1,1,1,2,5,5,5,5,5,5,4,5,5,23,,satisfied +13126,94956,Female,Loyal Customer,49,Business travel,Eco,248,4,4,1,4,3,3,4,4,4,4,4,5,4,3,0,0.0,satisfied +13127,43614,Female,disloyal Customer,37,Business travel,Eco,119,2,2,2,2,3,2,3,3,3,4,1,3,1,3,0,0.0,neutral or dissatisfied +13128,15022,Female,Loyal Customer,38,Personal Travel,Eco,557,1,5,1,2,4,1,4,4,3,4,4,1,3,4,0,0.0,neutral or dissatisfied +13129,121458,Female,Loyal Customer,63,Business travel,Business,257,1,1,1,1,2,5,3,5,5,5,5,1,5,5,0,0.0,satisfied +13130,118984,Male,Loyal Customer,44,Business travel,Business,2345,1,1,1,1,5,4,5,4,4,5,4,5,4,3,1,0.0,satisfied +13131,78845,Male,Loyal Customer,40,Business travel,Business,554,1,1,1,1,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +13132,127858,Female,Loyal Customer,60,Business travel,Business,3921,1,1,1,1,2,4,4,5,5,5,5,5,5,5,1,0.0,satisfied +13133,49420,Male,disloyal Customer,35,Business travel,Eco,199,1,0,1,3,3,1,2,3,3,5,1,3,4,3,0,0.0,neutral or dissatisfied +13134,27673,Female,Loyal Customer,29,Business travel,Business,2354,3,4,4,4,3,3,3,3,3,2,4,1,4,3,0,0.0,neutral or dissatisfied +13135,54954,Female,Loyal Customer,49,Business travel,Business,1635,1,1,4,1,2,5,4,4,4,4,4,3,4,5,7,20.0,satisfied +13136,45320,Male,Loyal Customer,44,Business travel,Business,2896,4,4,4,4,2,4,1,5,5,5,5,1,5,1,0,0.0,satisfied +13137,46120,Male,Loyal Customer,22,Business travel,Business,1737,3,3,3,3,5,5,5,5,3,2,1,3,4,5,0,0.0,satisfied +13138,120020,Female,Loyal Customer,22,Personal Travel,Eco,328,4,4,4,4,3,4,3,3,2,1,4,1,3,3,0,0.0,neutral or dissatisfied +13139,108763,Female,Loyal Customer,41,Business travel,Business,1993,4,4,4,4,4,5,5,3,3,3,3,4,3,4,0,0.0,satisfied +13140,21916,Female,disloyal Customer,26,Business travel,Eco,448,2,2,2,3,3,2,3,3,3,1,3,1,4,3,0,0.0,neutral or dissatisfied +13141,112005,Male,Loyal Customer,55,Business travel,Eco Plus,533,1,3,3,3,1,1,1,1,3,2,4,1,3,1,20,21.0,neutral or dissatisfied +13142,124389,Female,Loyal Customer,49,Personal Travel,Eco,808,1,1,1,3,2,4,4,4,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +13143,90159,Female,Loyal Customer,62,Personal Travel,Eco,957,5,4,5,5,3,4,4,2,2,5,2,4,2,3,0,0.0,satisfied +13144,49,Male,disloyal Customer,20,Business travel,Eco,108,4,5,4,1,5,4,3,5,5,4,5,5,4,5,0,29.0,neutral or dissatisfied +13145,2542,Male,Loyal Customer,57,Business travel,Business,1880,0,0,0,3,5,4,4,2,2,2,5,4,2,3,0,12.0,satisfied +13146,59162,Female,disloyal Customer,8,Business travel,Eco Plus,1744,2,4,2,4,2,2,2,2,4,5,2,4,4,2,50,71.0,neutral or dissatisfied +13147,13192,Female,disloyal Customer,26,Business travel,Eco,419,1,0,1,2,3,1,3,3,3,4,2,1,3,3,0,0.0,neutral or dissatisfied +13148,40282,Female,Loyal Customer,19,Personal Travel,Eco,402,2,5,2,1,2,2,1,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +13149,7925,Male,Loyal Customer,43,Personal Travel,Eco,1020,4,1,5,4,3,5,3,3,1,3,3,2,3,3,0,8.0,neutral or dissatisfied +13150,67053,Male,disloyal Customer,28,Business travel,Business,964,2,2,2,3,4,2,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +13151,46901,Female,Loyal Customer,25,Business travel,Business,844,2,1,1,1,2,2,2,2,4,4,3,1,4,2,0,0.0,neutral or dissatisfied +13152,105715,Female,Loyal Customer,47,Business travel,Business,2699,4,4,4,4,2,5,5,4,4,4,4,4,4,3,7,0.0,satisfied +13153,119245,Female,Loyal Customer,44,Business travel,Business,2219,2,2,3,2,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +13154,102286,Male,Loyal Customer,39,Business travel,Business,258,3,3,3,3,4,4,5,5,5,5,5,4,5,5,52,48.0,satisfied +13155,114142,Male,Loyal Customer,29,Business travel,Business,3818,2,2,2,2,4,4,4,4,4,2,5,4,5,4,1,6.0,satisfied +13156,109533,Male,disloyal Customer,20,Business travel,Eco,920,2,2,2,4,5,2,5,5,2,2,3,3,4,5,14,0.0,neutral or dissatisfied +13157,40149,Male,Loyal Customer,57,Business travel,Business,402,5,5,5,5,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +13158,96660,Male,Loyal Customer,18,Personal Travel,Eco,937,2,5,2,1,5,2,5,5,3,3,4,4,5,5,20,16.0,neutral or dissatisfied +13159,108038,Female,Loyal Customer,65,Personal Travel,Eco,306,2,1,2,2,5,3,2,3,3,2,3,1,3,2,66,57.0,neutral or dissatisfied +13160,106715,Male,Loyal Customer,37,Business travel,Business,3568,5,3,5,5,4,4,4,5,5,5,5,3,5,3,7,0.0,satisfied +13161,32983,Female,Loyal Customer,42,Personal Travel,Eco,101,2,5,2,5,2,5,4,5,5,2,5,2,5,1,8,11.0,neutral or dissatisfied +13162,112546,Female,disloyal Customer,22,Business travel,Eco,862,3,3,3,3,1,3,1,1,3,3,5,4,5,1,0,0.0,neutral or dissatisfied +13163,86971,Male,Loyal Customer,41,Business travel,Eco,907,3,5,5,5,3,3,3,3,3,5,4,4,3,3,5,0.0,neutral or dissatisfied +13164,12156,Male,disloyal Customer,31,Business travel,Business,1075,3,3,3,4,3,3,3,3,3,1,2,4,5,3,0,0.0,neutral or dissatisfied +13165,80552,Female,Loyal Customer,49,Business travel,Business,1747,1,1,1,1,5,4,4,4,4,5,4,4,4,3,0,11.0,satisfied +13166,81646,Male,Loyal Customer,55,Business travel,Business,907,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +13167,110330,Female,Loyal Customer,56,Business travel,Business,787,4,4,4,4,2,4,4,5,5,5,5,4,5,3,4,0.0,satisfied +13168,122596,Male,Loyal Customer,28,Business travel,Business,728,2,2,3,2,4,4,4,4,3,3,4,3,4,4,55,78.0,satisfied +13169,37363,Male,disloyal Customer,37,Business travel,Eco,944,3,3,3,4,5,3,5,5,2,2,5,5,3,5,0,0.0,neutral or dissatisfied +13170,86810,Female,Loyal Customer,34,Business travel,Business,484,5,5,2,5,5,5,4,3,3,4,3,3,3,4,41,43.0,satisfied +13171,39383,Female,Loyal Customer,27,Business travel,Business,521,4,4,4,4,4,4,4,4,1,3,3,5,5,4,0,0.0,satisfied +13172,79556,Female,Loyal Customer,51,Business travel,Business,2464,5,2,5,5,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +13173,99707,Male,Loyal Customer,10,Personal Travel,Eco,2026,2,3,2,4,2,2,2,2,2,4,5,5,2,2,2,10.0,neutral or dissatisfied +13174,5941,Male,Loyal Customer,35,Business travel,Eco Plus,67,2,1,1,1,2,2,2,2,4,4,3,4,3,2,19,30.0,neutral or dissatisfied +13175,25258,Female,Loyal Customer,35,Business travel,Business,3880,1,1,1,1,2,1,3,4,4,5,4,4,4,1,8,0.0,satisfied +13176,122169,Male,Loyal Customer,59,Business travel,Business,603,1,1,1,1,4,5,5,2,2,3,2,3,2,3,0,0.0,satisfied +13177,8283,Female,Loyal Customer,56,Personal Travel,Eco,294,1,4,5,4,2,5,5,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +13178,27206,Male,disloyal Customer,54,Business travel,Business,2717,2,2,2,3,2,3,3,4,3,2,2,3,4,3,3,11.0,neutral or dissatisfied +13179,26733,Male,Loyal Customer,26,Business travel,Eco Plus,515,0,4,0,2,4,0,4,4,1,5,5,2,4,4,0,0.0,satisfied +13180,20792,Female,Loyal Customer,57,Business travel,Eco,457,3,1,1,1,2,4,3,3,3,3,3,2,3,5,61,59.0,satisfied +13181,68267,Female,Loyal Customer,34,Personal Travel,Eco,631,2,4,2,3,2,2,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +13182,121486,Male,Loyal Customer,35,Personal Travel,Eco,257,0,1,0,1,4,0,4,4,3,5,2,3,2,4,0,0.0,satisfied +13183,98839,Female,Loyal Customer,29,Personal Travel,Eco,763,2,4,2,1,5,2,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +13184,9052,Male,disloyal Customer,24,Business travel,Eco,160,2,0,1,4,4,1,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +13185,74747,Female,Loyal Customer,43,Personal Travel,Eco,1235,3,2,3,3,4,3,2,1,1,3,1,4,1,4,19,9.0,neutral or dissatisfied +13186,22616,Male,Loyal Customer,44,Personal Travel,Eco,223,2,4,2,1,2,2,4,2,4,2,5,5,5,2,0,0.0,neutral or dissatisfied +13187,86494,Male,Loyal Customer,35,Personal Travel,Eco,853,1,5,1,3,1,1,1,1,4,2,5,3,4,1,89,92.0,neutral or dissatisfied +13188,25766,Female,disloyal Customer,21,Business travel,Business,356,4,5,4,3,3,4,3,3,1,5,3,5,1,3,0,0.0,satisfied +13189,125992,Female,Loyal Customer,35,Personal Travel,Business,650,3,4,3,2,3,3,2,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +13190,61594,Male,Loyal Customer,46,Business travel,Business,1635,4,4,4,4,4,3,4,4,4,4,4,5,4,3,98,79.0,satisfied +13191,63406,Female,Loyal Customer,50,Personal Travel,Eco,337,3,1,3,3,3,2,4,2,1,4,3,4,2,4,170,174.0,neutral or dissatisfied +13192,55453,Male,disloyal Customer,38,Business travel,Business,2327,3,3,3,1,3,3,3,3,3,2,4,4,5,3,0,0.0,neutral or dissatisfied +13193,81221,Female,Loyal Customer,8,Personal Travel,Eco,1426,1,5,1,5,2,1,4,2,3,4,4,3,5,2,0,10.0,neutral or dissatisfied +13194,116011,Male,Loyal Customer,53,Personal Travel,Eco,446,3,5,3,3,1,3,1,1,4,2,5,5,4,1,0,0.0,neutral or dissatisfied +13195,66789,Male,Loyal Customer,21,Personal Travel,Eco,3784,1,2,1,2,1,1,2,3,5,1,2,2,2,2,2,2.0,neutral or dissatisfied +13196,36973,Female,Loyal Customer,34,Business travel,Eco,667,3,4,4,4,3,3,3,3,3,2,4,1,3,3,19,14.0,neutral or dissatisfied +13197,27914,Female,Loyal Customer,27,Business travel,Eco,689,0,1,1,3,3,1,3,3,3,1,4,3,2,3,0,0.0,satisfied +13198,67644,Female,Loyal Customer,45,Business travel,Business,1235,4,4,4,4,3,4,4,4,4,4,4,4,4,5,4,0.0,satisfied +13199,39691,Female,disloyal Customer,14,Business travel,Eco,1463,3,3,3,4,2,3,4,2,3,2,3,3,4,2,31,56.0,neutral or dissatisfied +13200,50531,Male,Loyal Customer,10,Personal Travel,Eco,190,0,1,0,3,1,0,1,1,3,1,4,1,3,1,0,0.0,satisfied +13201,15866,Male,Loyal Customer,51,Business travel,Eco,332,4,1,1,1,4,4,4,4,1,3,5,2,3,4,0,0.0,satisfied +13202,126942,Male,Loyal Customer,48,Business travel,Business,2771,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +13203,13849,Male,Loyal Customer,68,Business travel,Eco Plus,228,3,2,2,2,3,3,3,3,1,1,2,3,3,3,0,0.0,satisfied +13204,3131,Male,Loyal Customer,59,Business travel,Business,3225,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +13205,6193,Male,Loyal Customer,53,Business travel,Business,3514,1,1,1,1,2,4,4,3,3,3,3,5,3,4,0,15.0,satisfied +13206,7074,Male,Loyal Customer,37,Business travel,Business,2936,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +13207,70271,Female,Loyal Customer,45,Business travel,Business,852,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +13208,65849,Male,Loyal Customer,46,Business travel,Eco,989,5,1,1,1,5,5,5,5,5,2,3,2,1,5,0,0.0,satisfied +13209,16742,Male,Loyal Customer,29,Business travel,Eco Plus,1167,5,3,4,3,5,5,5,5,1,3,3,3,1,5,0,0.0,satisfied +13210,11501,Male,Loyal Customer,52,Personal Travel,Eco Plus,308,2,5,2,3,3,2,3,3,4,3,1,5,2,3,58,49.0,neutral or dissatisfied +13211,115025,Female,Loyal Customer,46,Business travel,Business,446,5,5,5,5,2,4,4,4,4,4,4,4,4,4,31,28.0,satisfied +13212,119760,Female,Loyal Customer,64,Personal Travel,Eco Plus,1303,2,2,2,3,1,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +13213,129083,Female,Loyal Customer,44,Business travel,Business,2342,4,4,4,4,5,4,4,4,4,4,4,4,4,5,36,19.0,satisfied +13214,1148,Male,Loyal Customer,34,Personal Travel,Eco,89,2,4,2,4,1,2,1,1,4,3,4,5,5,1,0,0.0,neutral or dissatisfied +13215,90424,Female,Loyal Customer,54,Business travel,Business,2414,1,1,3,1,2,4,4,5,5,5,5,3,5,5,0,2.0,satisfied +13216,106037,Female,disloyal Customer,47,Business travel,Business,452,3,3,3,4,5,3,5,5,5,2,4,4,4,5,4,2.0,neutral or dissatisfied +13217,48255,Male,Loyal Customer,67,Personal Travel,Eco,192,2,2,2,1,5,2,5,5,3,1,1,1,1,5,35,42.0,neutral or dissatisfied +13218,53974,Male,Loyal Customer,53,Personal Travel,Eco,1325,3,5,3,4,1,3,1,1,5,2,3,5,4,1,0,0.0,neutral or dissatisfied +13219,23856,Female,disloyal Customer,26,Business travel,Eco,522,0,0,0,4,4,0,4,4,4,4,5,2,4,4,0,0.0,satisfied +13220,89179,Female,Loyal Customer,35,Personal Travel,Eco,2139,1,4,2,3,3,2,3,3,5,4,4,4,5,3,0,0.0,neutral or dissatisfied +13221,126382,Male,Loyal Customer,68,Personal Travel,Eco,468,3,4,3,3,4,3,4,4,4,4,3,1,4,4,0,2.0,neutral or dissatisfied +13222,76210,Female,Loyal Customer,13,Personal Travel,Eco Plus,2422,0,2,0,3,3,0,2,3,1,2,1,1,2,3,0,0.0,satisfied +13223,124596,Female,Loyal Customer,66,Personal Travel,Eco,500,1,4,4,4,4,4,4,3,3,4,4,5,3,5,0,8.0,neutral or dissatisfied +13224,88506,Male,disloyal Customer,17,Business travel,Business,223,0,0,0,4,3,0,3,3,3,4,3,3,3,3,0,0.0,satisfied +13225,53317,Male,Loyal Customer,42,Personal Travel,Eco,758,2,4,2,4,3,2,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +13226,15212,Female,disloyal Customer,37,Business travel,Eco,529,2,1,2,3,4,2,4,4,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +13227,103041,Female,Loyal Customer,17,Business travel,Eco,460,3,3,3,3,3,3,2,3,2,4,3,3,3,3,0,0.0,neutral or dissatisfied +13228,129190,Female,Loyal Customer,43,Business travel,Business,2419,3,3,3,3,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +13229,14484,Male,Loyal Customer,32,Business travel,Business,541,4,4,4,4,5,5,5,5,1,2,5,2,1,5,0,8.0,satisfied +13230,33049,Female,Loyal Customer,33,Personal Travel,Eco,216,3,0,3,4,1,3,1,1,5,3,3,3,1,1,0,6.0,neutral or dissatisfied +13231,94195,Female,Loyal Customer,31,Business travel,Business,1581,4,4,4,4,5,5,5,5,3,2,4,5,5,5,18,13.0,satisfied +13232,9387,Male,Loyal Customer,46,Personal Travel,Eco,401,5,4,5,3,1,5,1,1,3,3,5,5,4,1,0,0.0,satisfied +13233,50080,Male,Loyal Customer,32,Business travel,Business,262,2,2,2,2,4,4,4,4,1,5,1,2,2,4,61,51.0,satisfied +13234,33541,Female,disloyal Customer,46,Business travel,Business,413,2,2,2,3,2,2,2,2,2,3,3,1,3,2,0,0.0,neutral or dissatisfied +13235,59306,Female,Loyal Customer,25,Business travel,Business,2556,1,1,1,1,4,4,4,4,4,2,4,3,5,4,12,0.0,satisfied +13236,93,Female,Loyal Customer,43,Business travel,Business,3513,1,2,2,2,2,3,3,1,1,1,1,2,1,1,101,123.0,neutral or dissatisfied +13237,25384,Male,Loyal Customer,27,Personal Travel,Eco,591,2,1,2,3,3,2,3,3,3,5,2,2,3,3,69,67.0,neutral or dissatisfied +13238,20642,Male,Loyal Customer,27,Personal Travel,Eco,911,3,2,3,4,4,3,4,4,1,5,3,3,4,4,38,16.0,neutral or dissatisfied +13239,69636,Male,Loyal Customer,53,Business travel,Business,2125,1,1,1,1,3,5,4,3,3,4,3,5,3,3,0,2.0,satisfied +13240,44884,Female,disloyal Customer,25,Business travel,Eco,557,3,0,4,3,1,4,4,1,2,4,3,4,2,1,0,0.0,neutral or dissatisfied +13241,31106,Male,Loyal Customer,52,Business travel,Eco,483,4,4,4,4,4,4,4,4,5,4,2,3,4,4,36,36.0,satisfied +13242,96405,Male,Loyal Customer,34,Personal Travel,Eco,1342,4,4,4,4,5,4,5,5,4,2,5,5,5,5,17,17.0,neutral or dissatisfied +13243,54161,Male,Loyal Customer,53,Business travel,Business,1400,2,1,2,1,4,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +13244,41127,Female,Loyal Customer,16,Business travel,Business,3488,2,5,5,5,4,4,2,4,2,4,4,2,4,4,104,129.0,neutral or dissatisfied +13245,72862,Female,disloyal Customer,27,Business travel,Eco,700,3,3,3,3,5,3,5,5,4,2,3,2,3,5,0,0.0,neutral or dissatisfied +13246,72909,Female,Loyal Customer,28,Business travel,Business,2396,2,2,4,2,4,4,4,4,5,3,4,4,4,4,111,100.0,satisfied +13247,17114,Female,Loyal Customer,12,Personal Travel,Eco Plus,416,1,3,1,3,1,1,1,1,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +13248,92979,Female,Loyal Customer,56,Business travel,Business,2104,5,5,5,5,5,4,4,1,1,2,1,4,1,3,113,101.0,satisfied +13249,36624,Female,disloyal Customer,62,Business travel,Eco,610,3,3,3,4,4,3,4,4,1,4,4,3,3,4,0,0.0,neutral or dissatisfied +13250,40994,Male,Loyal Customer,49,Business travel,Business,1362,2,2,2,2,4,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +13251,105299,Female,Loyal Customer,31,Business travel,Business,2749,3,1,1,1,3,3,3,3,1,1,3,2,3,3,36,27.0,neutral or dissatisfied +13252,11711,Male,Loyal Customer,57,Business travel,Business,2722,4,4,4,4,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +13253,47520,Female,Loyal Customer,46,Personal Travel,Eco,588,4,5,5,5,5,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +13254,115970,Female,Loyal Customer,22,Personal Travel,Eco,446,4,4,1,4,2,1,2,2,1,3,3,2,3,2,17,12.0,satisfied +13255,21238,Male,Loyal Customer,54,Personal Travel,Eco,192,3,4,3,3,2,3,2,2,5,5,5,3,4,2,1,0.0,neutral or dissatisfied +13256,128624,Male,Loyal Customer,47,Business travel,Business,3523,3,4,4,4,3,3,3,1,4,3,2,3,2,3,182,184.0,neutral or dissatisfied +13257,16296,Female,Loyal Customer,49,Business travel,Eco Plus,748,4,4,4,4,3,1,3,4,4,4,4,5,4,5,18,7.0,satisfied +13258,56043,Male,Loyal Customer,33,Business travel,Business,2586,2,2,2,2,2,2,2,4,3,2,2,2,3,2,97,180.0,neutral or dissatisfied +13259,78407,Male,disloyal Customer,50,Business travel,Business,453,2,3,3,1,4,2,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +13260,49360,Female,Loyal Customer,50,Business travel,Eco,262,4,1,1,1,1,2,2,4,4,4,4,4,4,4,0,8.0,satisfied +13261,113425,Female,Loyal Customer,40,Business travel,Business,2293,5,5,5,5,4,4,5,4,4,4,4,5,4,3,2,0.0,satisfied +13262,105202,Male,Loyal Customer,63,Personal Travel,Eco Plus,289,3,5,3,1,2,3,2,2,4,4,5,3,4,2,40,35.0,neutral or dissatisfied +13263,28696,Male,Loyal Customer,23,Personal Travel,Eco,2182,2,2,2,2,1,2,1,1,1,2,2,3,3,1,0,0.0,neutral or dissatisfied +13264,113653,Male,Loyal Customer,46,Personal Travel,Eco,397,4,5,4,2,4,4,4,4,4,3,4,3,4,4,99,94.0,neutral or dissatisfied +13265,15308,Female,Loyal Customer,53,Business travel,Eco,599,5,2,2,2,5,2,5,5,5,5,5,4,5,3,0,0.0,satisfied +13266,40339,Male,Loyal Customer,62,Personal Travel,Eco Plus,436,2,4,2,5,5,2,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +13267,105610,Female,Loyal Customer,54,Personal Travel,Business,842,2,4,3,1,4,5,5,5,5,3,4,5,5,4,13,0.0,neutral or dissatisfied +13268,101827,Male,Loyal Customer,12,Personal Travel,Eco,1521,2,5,2,1,3,2,5,3,3,5,3,4,4,3,2,0.0,neutral or dissatisfied +13269,61855,Female,Loyal Customer,31,Personal Travel,Eco Plus,1609,2,2,2,3,5,2,5,5,2,3,2,1,2,5,0,0.0,neutral or dissatisfied +13270,21739,Female,Loyal Customer,48,Business travel,Business,563,4,4,4,4,2,2,2,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +13271,122092,Male,Loyal Customer,45,Personal Travel,Eco,130,0,5,0,4,4,0,4,4,2,5,1,4,4,4,0,1.0,satisfied +13272,29423,Male,Loyal Customer,27,Personal Travel,Eco Plus,2349,5,4,5,3,1,5,1,1,5,2,4,4,2,1,0,0.0,satisfied +13273,57975,Female,Loyal Customer,43,Personal Travel,Eco,420,4,4,4,3,4,5,4,3,3,4,3,2,3,3,0,6.0,neutral or dissatisfied +13274,37244,Male,Loyal Customer,48,Personal Travel,Business,1076,4,5,4,3,2,5,4,2,2,4,2,3,2,3,3,0.0,neutral or dissatisfied +13275,23622,Female,Loyal Customer,32,Personal Travel,Eco,977,3,4,3,1,4,3,4,4,4,3,4,3,5,4,29,28.0,neutral or dissatisfied +13276,38133,Female,disloyal Customer,37,Business travel,Eco,797,4,4,4,1,1,4,1,1,1,2,3,2,4,1,0,0.0,neutral or dissatisfied +13277,77551,Male,Loyal Customer,39,Business travel,Business,586,3,3,3,3,4,3,2,2,2,2,2,5,2,1,3,0.0,satisfied +13278,52156,Male,Loyal Customer,44,Business travel,Business,509,1,1,3,1,2,2,4,5,5,5,5,2,5,3,0,0.0,satisfied +13279,61728,Female,Loyal Customer,15,Business travel,Business,1303,2,5,5,5,2,2,2,2,1,5,3,3,3,2,17,0.0,neutral or dissatisfied +13280,122591,Male,disloyal Customer,26,Business travel,Business,728,3,2,2,3,5,2,1,5,4,2,5,3,5,5,2,0.0,neutral or dissatisfied +13281,46961,Male,Loyal Customer,12,Personal Travel,Eco,819,2,3,2,3,5,2,5,5,1,2,2,5,3,5,67,59.0,neutral or dissatisfied +13282,110243,Female,Loyal Customer,46,Business travel,Business,1024,2,2,5,2,2,5,5,5,5,5,5,5,5,4,18,2.0,satisfied +13283,83288,Male,Loyal Customer,13,Personal Travel,Eco,2079,2,4,2,4,2,1,1,2,1,5,5,1,5,1,140,152.0,neutral or dissatisfied +13284,12709,Male,Loyal Customer,24,Business travel,Business,721,3,4,4,4,3,3,3,3,1,3,4,1,3,3,0,0.0,neutral or dissatisfied +13285,16496,Male,Loyal Customer,39,Business travel,Business,195,5,5,5,5,3,1,4,4,4,4,4,2,4,4,113,95.0,satisfied +13286,6476,Female,Loyal Customer,67,Personal Travel,Eco Plus,315,1,5,5,2,3,5,4,4,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +13287,16567,Male,disloyal Customer,21,Business travel,Eco,872,3,3,3,2,3,3,3,3,2,4,5,1,1,3,0,0.0,neutral or dissatisfied +13288,42074,Female,Loyal Customer,31,Personal Travel,Eco,106,2,5,2,5,5,2,5,5,5,4,4,4,5,5,0,8.0,neutral or dissatisfied +13289,25781,Female,Loyal Customer,36,Business travel,Eco,762,5,2,2,2,5,5,5,5,3,1,2,3,3,5,3,0.0,satisfied +13290,102450,Male,Loyal Customer,46,Personal Travel,Eco,397,2,4,2,4,3,2,3,3,2,5,4,4,4,3,24,12.0,neutral or dissatisfied +13291,24463,Female,Loyal Customer,59,Business travel,Eco,547,4,1,1,1,5,2,3,4,4,4,4,4,4,4,3,,satisfied +13292,5865,Female,Loyal Customer,31,Personal Travel,Eco,1020,4,4,4,2,4,4,4,4,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +13293,108862,Male,Loyal Customer,28,Personal Travel,Eco,2139,4,2,4,4,2,4,2,2,4,4,4,4,4,2,33,8.0,neutral or dissatisfied +13294,21640,Female,Loyal Customer,52,Personal Travel,Eco,780,2,2,2,1,5,1,1,1,1,2,1,2,1,4,1,0.0,neutral or dissatisfied +13295,35142,Male,Loyal Customer,39,Business travel,Business,1165,2,1,1,1,5,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +13296,7495,Male,Loyal Customer,35,Personal Travel,Eco,925,3,4,3,4,4,3,2,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +13297,98171,Female,disloyal Customer,24,Business travel,Business,562,4,0,4,3,4,4,4,4,3,3,4,5,5,4,12,0.0,satisfied +13298,12888,Male,Loyal Customer,46,Business travel,Business,3391,2,2,2,2,4,2,1,5,5,5,5,5,5,3,0,11.0,satisfied +13299,66879,Female,Loyal Customer,57,Business travel,Business,2778,5,5,5,5,2,5,4,5,5,5,5,4,5,3,15,3.0,satisfied +13300,124788,Male,Loyal Customer,43,Business travel,Business,280,0,0,0,4,3,4,5,3,3,3,3,3,3,4,28,11.0,satisfied +13301,89184,Female,Loyal Customer,10,Personal Travel,Eco,1947,3,3,3,4,5,3,5,5,3,4,3,5,2,5,0,1.0,neutral or dissatisfied +13302,61106,Female,Loyal Customer,13,Personal Travel,Eco,1709,4,2,4,4,5,4,5,5,4,1,3,4,3,5,0,0.0,neutral or dissatisfied +13303,23846,Male,disloyal Customer,34,Business travel,Eco,552,3,4,3,4,5,3,5,5,5,1,4,5,5,5,47,57.0,neutral or dissatisfied +13304,92811,Female,disloyal Customer,26,Business travel,Business,1587,1,1,1,3,4,1,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +13305,122685,Female,disloyal Customer,24,Business travel,Eco,361,4,0,4,4,1,4,1,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +13306,115931,Male,Loyal Customer,39,Business travel,Business,417,2,2,5,5,1,3,3,2,2,2,2,1,2,1,3,0.0,neutral or dissatisfied +13307,53276,Female,Loyal Customer,51,Business travel,Business,758,3,3,3,3,3,5,1,4,4,4,4,5,4,2,0,24.0,satisfied +13308,65486,Male,Loyal Customer,23,Personal Travel,Eco,1067,3,4,2,2,3,2,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +13309,14813,Male,Loyal Customer,11,Personal Travel,Eco,95,2,1,0,2,3,0,5,3,1,3,2,1,2,3,1,0.0,neutral or dissatisfied +13310,82684,Male,Loyal Customer,30,Business travel,Business,2720,1,1,1,1,4,5,4,4,4,2,5,3,4,4,0,0.0,satisfied +13311,71568,Female,Loyal Customer,53,Business travel,Business,1005,4,5,5,5,3,3,4,4,4,3,4,3,4,3,6,5.0,neutral or dissatisfied +13312,64069,Female,Loyal Customer,36,Business travel,Eco,519,5,2,2,2,5,5,5,5,3,2,3,5,3,5,34,41.0,satisfied +13313,15045,Male,disloyal Customer,9,Business travel,Eco,576,2,0,2,4,4,2,4,4,5,4,5,2,2,4,4,0.0,neutral or dissatisfied +13314,59519,Female,Loyal Customer,15,Personal Travel,Business,956,1,5,1,3,1,1,2,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +13315,28147,Male,Loyal Customer,61,Business travel,Eco,933,1,1,1,1,1,1,1,1,3,2,3,3,2,1,0,0.0,neutral or dissatisfied +13316,83031,Female,Loyal Customer,32,Business travel,Business,3001,3,2,2,2,3,3,3,3,3,3,4,3,4,3,37,119.0,neutral or dissatisfied +13317,39583,Female,disloyal Customer,25,Business travel,Eco,965,3,3,3,4,4,3,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +13318,110885,Female,Loyal Customer,55,Business travel,Eco,406,4,3,3,3,4,4,3,4,4,4,4,1,4,1,10,14.0,neutral or dissatisfied +13319,123071,Female,disloyal Customer,50,Business travel,Business,468,4,4,4,4,2,4,5,2,3,2,5,3,4,2,109,103.0,satisfied +13320,118378,Male,Loyal Customer,50,Business travel,Business,3914,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +13321,40734,Male,disloyal Customer,27,Business travel,Eco,599,1,1,2,3,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +13322,40946,Male,Loyal Customer,28,Personal Travel,Eco Plus,574,4,5,4,4,4,4,4,4,3,2,5,4,5,4,70,50.0,neutral or dissatisfied +13323,77372,Female,Loyal Customer,51,Business travel,Eco,532,4,2,2,2,5,3,3,3,3,4,3,4,3,2,1,0.0,neutral or dissatisfied +13324,32979,Male,Loyal Customer,65,Personal Travel,Eco,216,4,5,0,4,2,0,2,2,3,1,2,1,2,2,0,0.0,satisfied +13325,76345,Male,Loyal Customer,44,Business travel,Business,1851,2,2,5,2,4,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +13326,12404,Female,disloyal Customer,50,Business travel,Eco,201,1,2,1,3,5,1,5,5,3,3,3,4,3,5,20,17.0,neutral or dissatisfied +13327,47098,Female,Loyal Customer,50,Personal Travel,Eco,639,3,5,3,4,4,5,4,5,5,3,2,4,5,5,8,10.0,neutral or dissatisfied +13328,60546,Female,Loyal Customer,51,Personal Travel,Eco,862,2,5,2,4,3,5,5,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +13329,118455,Female,Loyal Customer,43,Business travel,Business,3927,4,1,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +13330,37187,Male,Loyal Customer,24,Personal Travel,Eco,1046,2,3,2,3,4,2,4,4,2,2,3,4,5,4,0,0.0,neutral or dissatisfied +13331,54356,Female,Loyal Customer,58,Business travel,Eco,835,4,5,5,5,2,3,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +13332,30751,Female,Loyal Customer,32,Personal Travel,Eco,977,2,4,2,1,2,2,2,2,3,4,4,4,5,2,0,0.0,neutral or dissatisfied +13333,124643,Male,disloyal Customer,43,Business travel,Business,399,1,2,2,2,4,1,4,4,4,5,5,3,4,4,35,30.0,neutral or dissatisfied +13334,27277,Female,Loyal Customer,40,Personal Travel,Business,697,3,5,3,1,1,5,2,4,4,3,4,4,4,3,0,5.0,neutral or dissatisfied +13335,49710,Male,Loyal Customer,58,Business travel,Business,1995,0,5,0,1,5,3,5,3,3,3,3,2,3,1,0,0.0,satisfied +13336,92424,Male,disloyal Customer,27,Business travel,Business,839,5,5,5,3,3,5,3,3,4,4,3,3,4,3,42,22.0,satisfied +13337,119133,Male,Loyal Customer,70,Business travel,Business,2910,2,1,1,1,4,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +13338,105713,Male,disloyal Customer,35,Business travel,Eco,883,2,2,2,3,4,2,4,4,4,3,3,4,2,4,25,15.0,neutral or dissatisfied +13339,100434,Female,Loyal Customer,35,Business travel,Business,1620,3,3,3,3,2,4,4,4,4,4,4,5,4,3,20,28.0,satisfied +13340,24071,Female,Loyal Customer,44,Business travel,Eco,866,3,2,5,5,4,3,1,3,3,3,3,1,3,5,0,0.0,satisfied +13341,113182,Male,Loyal Customer,52,Personal Travel,Eco,889,2,3,2,4,2,2,2,2,2,4,3,1,3,2,6,12.0,neutral or dissatisfied +13342,33609,Female,Loyal Customer,34,Business travel,Business,399,3,4,4,4,5,3,2,3,3,3,3,2,3,2,0,6.0,neutral or dissatisfied +13343,106748,Female,disloyal Customer,29,Business travel,Business,829,1,1,1,2,1,1,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +13344,10185,Male,Loyal Customer,48,Business travel,Business,429,2,2,2,2,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +13345,40912,Male,Loyal Customer,28,Personal Travel,Eco,590,1,3,2,5,5,2,5,5,4,5,4,2,5,5,45,64.0,neutral or dissatisfied +13346,39945,Female,Loyal Customer,62,Personal Travel,Eco,1086,3,5,3,4,4,4,5,1,1,3,1,3,1,3,0,49.0,neutral or dissatisfied +13347,52060,Female,Loyal Customer,45,Business travel,Eco,351,4,5,5,5,5,3,4,4,4,4,4,5,4,2,0,1.0,satisfied +13348,129716,Male,disloyal Customer,20,Business travel,Eco,447,3,3,3,4,4,3,4,4,3,2,4,3,3,4,0,0.0,neutral or dissatisfied +13349,100020,Female,Loyal Customer,24,Business travel,Business,3635,2,2,5,2,2,2,2,2,3,1,3,4,4,2,16,11.0,neutral or dissatisfied +13350,33592,Female,Loyal Customer,43,Business travel,Business,3809,4,4,4,4,1,4,3,5,5,5,5,3,5,3,0,0.0,satisfied +13351,106745,Female,Loyal Customer,31,Business travel,Business,945,3,3,3,3,4,4,4,4,3,5,5,3,4,4,0,0.0,satisfied +13352,10529,Male,Loyal Customer,56,Business travel,Business,3187,2,2,2,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +13353,88438,Male,disloyal Customer,26,Business travel,Eco,545,1,2,1,4,2,1,5,2,3,3,3,2,4,2,0,0.0,neutral or dissatisfied +13354,97308,Male,disloyal Customer,38,Business travel,Business,872,5,5,5,5,3,5,3,3,5,5,5,4,4,3,8,0.0,satisfied +13355,36994,Male,Loyal Customer,30,Business travel,Eco,667,5,5,5,5,5,5,5,5,4,3,3,5,5,5,0,0.0,satisfied +13356,73404,Male,Loyal Customer,41,Business travel,Business,1986,3,5,5,5,4,2,2,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +13357,42168,Male,Loyal Customer,26,Business travel,Business,817,2,2,4,2,5,4,5,5,4,2,3,1,3,5,0,0.0,satisfied +13358,21111,Male,Loyal Customer,45,Personal Travel,Eco,152,4,5,4,1,2,4,3,2,5,4,4,3,4,2,0,0.0,satisfied +13359,48062,Male,Loyal Customer,59,Business travel,Business,3829,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +13360,16181,Male,Loyal Customer,39,Business travel,Eco,277,2,4,4,4,2,2,2,2,3,3,4,1,4,2,20,34.0,neutral or dissatisfied +13361,77088,Male,Loyal Customer,24,Business travel,Business,1481,2,2,2,2,2,2,2,2,4,4,5,4,5,2,0,0.0,satisfied +13362,95594,Female,disloyal Customer,48,Business travel,Business,670,2,2,2,5,5,2,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +13363,84040,Male,disloyal Customer,48,Business travel,Business,879,2,2,2,1,5,2,1,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +13364,60594,Male,Loyal Customer,11,Personal Travel,Eco,1290,2,2,2,3,3,2,3,3,1,3,2,4,3,3,0,20.0,neutral or dissatisfied +13365,121207,Male,Loyal Customer,19,Personal Travel,Eco Plus,2402,4,1,4,4,4,4,4,2,1,4,3,4,2,4,0,1.0,neutral or dissatisfied +13366,111271,Female,Loyal Customer,53,Business travel,Business,2494,5,5,5,5,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +13367,63107,Male,Loyal Customer,67,Personal Travel,Eco Plus,909,2,5,2,1,2,1,1,5,3,4,5,1,3,1,423,400.0,neutral or dissatisfied +13368,33918,Female,Loyal Customer,62,Personal Travel,Eco,636,1,5,1,5,2,4,4,2,2,1,2,4,2,4,0,3.0,neutral or dissatisfied +13369,65597,Male,Loyal Customer,37,Business travel,Business,3581,3,3,3,3,3,3,4,3,3,3,3,2,3,3,10,19.0,neutral or dissatisfied +13370,53292,Male,Loyal Customer,61,Business travel,Business,3850,2,2,3,2,4,2,4,5,5,5,5,1,5,2,5,0.0,satisfied +13371,93940,Male,Loyal Customer,64,Business travel,Business,2062,5,5,3,5,2,3,3,5,5,5,5,4,5,4,0,0.0,satisfied +13372,77173,Male,Loyal Customer,45,Personal Travel,Eco,1355,2,2,2,4,2,2,2,2,1,2,3,3,3,2,0,0.0,neutral or dissatisfied +13373,26013,Female,disloyal Customer,23,Business travel,Eco,425,1,0,1,5,3,1,3,3,5,4,3,1,1,3,0,0.0,neutral or dissatisfied +13374,101103,Male,disloyal Customer,25,Business travel,Eco,1235,2,2,2,5,5,2,4,5,4,4,4,5,5,5,0,0.0,neutral or dissatisfied +13375,4403,Female,Loyal Customer,10,Business travel,Eco Plus,618,2,5,2,5,2,2,3,2,4,5,3,4,3,2,0,0.0,neutral or dissatisfied +13376,108839,Male,Loyal Customer,54,Business travel,Business,1947,3,3,3,3,2,5,4,5,5,5,5,5,5,5,8,17.0,satisfied +13377,61555,Male,Loyal Customer,49,Business travel,Business,2419,4,4,4,4,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +13378,57901,Female,Loyal Customer,68,Business travel,Eco,305,1,5,2,5,1,1,1,1,1,1,1,4,1,4,4,6.0,neutral or dissatisfied +13379,127699,Female,disloyal Customer,41,Business travel,Business,2133,3,3,3,1,5,3,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +13380,124642,Female,disloyal Customer,21,Business travel,Eco,399,4,0,4,2,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +13381,110647,Male,disloyal Customer,39,Business travel,Business,945,3,3,3,3,1,3,1,1,3,4,5,4,5,1,0,2.0,neutral or dissatisfied +13382,128950,Female,Loyal Customer,36,Business travel,Business,3984,1,1,1,1,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +13383,25286,Female,Loyal Customer,66,Business travel,Business,2899,1,1,5,1,5,4,2,5,5,5,5,1,5,4,0,0.0,satisfied +13384,41649,Female,Loyal Customer,43,Business travel,Business,1884,3,3,3,3,3,1,5,3,3,5,3,1,3,4,32,33.0,satisfied +13385,86105,Female,Loyal Customer,39,Business travel,Business,3335,4,4,4,4,2,5,4,4,4,4,4,5,4,4,25,17.0,satisfied +13386,100329,Male,Loyal Customer,11,Business travel,Eco,1011,1,1,1,1,1,1,1,1,4,5,3,3,2,1,0,0.0,neutral or dissatisfied +13387,4652,Female,Loyal Customer,42,Business travel,Business,2025,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,22.0,satisfied +13388,51705,Female,Loyal Customer,48,Business travel,Business,1972,5,4,4,4,1,2,2,1,1,2,5,1,1,1,0,0.0,neutral or dissatisfied +13389,74891,Male,Loyal Customer,60,Personal Travel,Business,2475,1,5,1,1,4,3,5,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +13390,125500,Male,Loyal Customer,51,Business travel,Business,3009,5,5,2,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +13391,13731,Female,disloyal Customer,66,Business travel,Eco,401,2,0,2,4,4,2,4,4,2,1,2,5,2,4,0,0.0,neutral or dissatisfied +13392,112508,Male,Loyal Customer,21,Personal Travel,Eco,862,3,4,3,3,1,3,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +13393,36885,Female,Loyal Customer,9,Personal Travel,Eco,1182,1,4,1,3,4,1,4,4,5,4,3,3,4,4,0,0.0,neutral or dissatisfied +13394,111939,Male,Loyal Customer,42,Business travel,Business,533,2,2,2,2,3,5,4,4,4,4,4,5,4,5,34,25.0,satisfied +13395,101346,Male,Loyal Customer,14,Personal Travel,Eco,2026,3,5,3,4,5,3,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +13396,115254,Female,Loyal Customer,31,Business travel,Business,446,2,2,2,2,4,4,4,4,5,4,4,4,5,4,51,44.0,satisfied +13397,95111,Female,Loyal Customer,18,Personal Travel,Eco,277,4,4,4,1,4,4,2,4,3,5,5,1,2,4,18,20.0,neutral or dissatisfied +13398,68838,Male,Loyal Customer,7,Personal Travel,Business,1061,4,5,4,1,3,4,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +13399,57166,Female,Loyal Customer,53,Business travel,Business,2227,5,3,5,5,5,4,4,4,4,4,4,4,4,3,3,0.0,satisfied +13400,55327,Female,Loyal Customer,58,Business travel,Business,1117,4,1,1,1,5,4,3,4,4,4,4,3,4,3,0,9.0,neutral or dissatisfied +13401,72756,Female,Loyal Customer,31,Business travel,Business,2150,5,5,5,5,4,4,4,4,4,2,5,5,5,4,14,0.0,satisfied +13402,114046,Female,Loyal Customer,25,Personal Travel,Eco,511,3,4,3,3,4,3,4,4,4,4,5,5,4,4,63,58.0,neutral or dissatisfied +13403,13189,Female,Loyal Customer,46,Business travel,Business,419,3,3,3,3,1,2,5,4,4,5,4,3,4,2,0,2.0,satisfied +13404,50047,Male,Loyal Customer,50,Business travel,Business,3951,0,3,0,2,5,5,5,1,1,1,1,4,1,2,0,0.0,satisfied +13405,112046,Male,Loyal Customer,12,Personal Travel,Eco,1123,1,1,1,4,2,1,5,2,3,1,3,3,4,2,3,0.0,neutral or dissatisfied +13406,4394,Male,Loyal Customer,59,Personal Travel,Eco,473,3,1,3,3,2,3,2,2,4,4,3,1,3,2,0,0.0,neutral or dissatisfied +13407,69066,Female,Loyal Customer,52,Business travel,Business,1389,1,1,1,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +13408,109796,Male,disloyal Customer,27,Business travel,Business,1011,4,3,3,2,4,3,4,4,3,4,4,5,4,4,35,22.0,satisfied +13409,44786,Female,Loyal Customer,48,Business travel,Business,3848,2,4,5,4,1,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +13410,62015,Female,Loyal Customer,42,Business travel,Eco,2475,3,3,3,3,1,3,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +13411,17870,Female,disloyal Customer,34,Business travel,Eco,425,3,1,2,4,4,2,4,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +13412,119761,Female,Loyal Customer,50,Personal Travel,Eco Plus,1303,1,4,2,2,2,3,5,4,4,2,3,4,4,3,10,0.0,neutral or dissatisfied +13413,86790,Female,Loyal Customer,47,Business travel,Business,2351,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,2.0,satisfied +13414,61573,Female,Loyal Customer,44,Business travel,Business,1303,5,5,5,5,3,5,4,4,4,4,4,4,4,3,1,7.0,satisfied +13415,95088,Female,Loyal Customer,20,Personal Travel,Eco,239,4,4,4,3,3,4,3,3,1,1,3,2,4,3,0,0.0,neutral or dissatisfied +13416,51330,Male,Loyal Customer,37,Business travel,Eco Plus,199,1,5,5,5,1,1,1,1,3,5,4,1,3,1,0,0.0,neutral or dissatisfied +13417,60458,Female,Loyal Customer,43,Business travel,Business,1699,2,2,2,2,4,4,4,3,3,3,3,4,3,4,2,0.0,satisfied +13418,26146,Male,disloyal Customer,36,Business travel,Eco,406,3,0,3,3,5,3,5,5,4,5,4,2,3,5,42,51.0,neutral or dissatisfied +13419,61456,Female,Loyal Customer,45,Business travel,Business,2442,4,4,4,4,2,3,5,4,4,5,4,4,4,5,21,18.0,satisfied +13420,116519,Male,Loyal Customer,61,Personal Travel,Eco,337,2,2,2,4,5,2,5,5,3,1,4,4,4,5,12,20.0,neutral or dissatisfied +13421,14081,Male,Loyal Customer,51,Business travel,Business,3380,3,3,3,3,3,5,5,4,4,4,4,1,4,5,0,0.0,satisfied +13422,15979,Female,disloyal Customer,36,Business travel,Business,780,3,3,3,3,3,3,3,3,5,5,4,4,4,3,16,70.0,neutral or dissatisfied +13423,52030,Male,Loyal Customer,34,Personal Travel,Eco,328,2,0,2,4,4,2,4,4,3,2,4,4,5,4,5,0.0,neutral or dissatisfied +13424,447,Female,Loyal Customer,51,Business travel,Business,354,1,1,1,1,5,5,5,5,5,5,5,5,5,5,7,8.0,satisfied +13425,686,Male,disloyal Customer,34,Business travel,Business,309,4,4,4,2,1,4,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +13426,92004,Male,Loyal Customer,52,Business travel,Business,1589,1,1,1,1,3,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +13427,31270,Female,Loyal Customer,29,Business travel,Business,3416,5,5,2,5,4,4,4,4,4,2,3,5,2,4,0,0.0,satisfied +13428,42960,Male,disloyal Customer,21,Business travel,Business,236,5,3,4,1,2,4,2,2,5,5,2,4,2,2,0,0.0,satisfied +13429,93989,Male,Loyal Customer,9,Personal Travel,Eco,1315,2,5,2,4,1,2,1,1,5,2,3,3,5,1,0,0.0,neutral or dissatisfied +13430,3771,Male,Loyal Customer,59,Business travel,Business,3263,5,5,5,5,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +13431,121736,Female,Loyal Customer,54,Business travel,Business,1856,5,5,5,5,2,4,3,5,5,5,5,3,5,4,0,0.0,satisfied +13432,49885,Female,Loyal Customer,56,Business travel,Eco,337,3,3,3,3,2,3,4,4,4,3,4,1,4,3,3,9.0,neutral or dissatisfied +13433,113177,Male,Loyal Customer,59,Personal Travel,Eco,889,4,4,4,2,1,4,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +13434,4153,Female,disloyal Customer,36,Business travel,Eco,431,1,4,1,4,5,1,5,5,3,5,3,3,4,5,0,0.0,neutral or dissatisfied +13435,125180,Male,Loyal Customer,42,Business travel,Business,2308,3,3,3,3,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +13436,52580,Male,Loyal Customer,75,Business travel,Business,119,3,4,4,4,1,4,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +13437,44085,Female,Loyal Customer,50,Business travel,Business,3098,4,4,4,4,4,4,4,3,3,4,3,4,3,5,0,0.0,satisfied +13438,96725,Male,Loyal Customer,20,Personal Travel,Eco,696,3,4,3,3,5,3,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +13439,58810,Female,Loyal Customer,18,Personal Travel,Eco,1012,2,4,1,3,3,1,3,3,3,5,4,1,3,3,0,4.0,neutral or dissatisfied +13440,82922,Female,Loyal Customer,28,Business travel,Business,594,2,2,2,2,4,4,4,4,5,3,4,5,5,4,0,0.0,satisfied +13441,56547,Male,disloyal Customer,27,Business travel,Business,997,4,5,5,3,3,5,3,3,5,3,5,3,4,3,0,0.0,satisfied +13442,87032,Female,Loyal Customer,45,Business travel,Business,640,3,3,3,3,5,5,5,3,3,3,3,5,3,5,65,59.0,satisfied +13443,69482,Female,Loyal Customer,38,Business travel,Business,3436,1,1,1,1,2,4,5,3,3,4,3,5,3,4,4,20.0,satisfied +13444,10390,Male,disloyal Customer,32,Business travel,Business,517,4,3,3,5,2,3,5,2,3,2,4,3,4,2,0,7.0,neutral or dissatisfied +13445,92690,Male,Loyal Customer,32,Personal Travel,Eco,507,1,5,5,5,4,5,4,4,4,3,4,4,5,4,11,4.0,neutral or dissatisfied +13446,98722,Male,Loyal Customer,55,Personal Travel,Eco Plus,861,3,5,2,4,3,2,3,3,4,4,4,5,4,3,2,11.0,neutral or dissatisfied +13447,72145,Male,Loyal Customer,29,Personal Travel,Eco,731,2,2,2,3,4,2,1,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +13448,42091,Male,Loyal Customer,41,Business travel,Eco,996,5,4,2,4,5,5,5,5,4,2,1,5,5,5,80,62.0,satisfied +13449,46040,Female,Loyal Customer,66,Business travel,Eco,991,2,1,4,1,4,3,3,2,2,2,2,1,2,4,0,7.0,neutral or dissatisfied +13450,32679,Female,Loyal Customer,63,Business travel,Business,101,2,4,4,4,3,3,3,4,4,4,2,3,4,4,0,0.0,neutral or dissatisfied +13451,43320,Female,Loyal Customer,38,Business travel,Eco,436,1,3,3,3,1,1,1,1,3,4,4,1,3,1,0,19.0,neutral or dissatisfied +13452,110197,Female,Loyal Customer,47,Business travel,Business,1056,4,4,4,4,3,5,5,4,4,4,4,4,4,4,45,49.0,satisfied +13453,79385,Male,Loyal Customer,24,Business travel,Business,1886,5,5,5,5,3,4,3,3,5,2,4,3,5,3,76,73.0,satisfied +13454,62730,Female,disloyal Customer,23,Business travel,Eco,2367,3,3,3,3,3,3,3,3,2,4,4,4,3,3,1,13.0,neutral or dissatisfied +13455,98077,Female,Loyal Customer,42,Personal Travel,Eco,1449,2,1,2,4,3,3,4,4,4,2,4,2,4,2,0,1.0,neutral or dissatisfied +13456,37230,Female,disloyal Customer,29,Business travel,Business,1041,1,1,1,5,3,1,3,3,3,3,5,5,4,3,16,2.0,neutral or dissatisfied +13457,115328,Female,Loyal Customer,55,Business travel,Business,446,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +13458,25059,Female,Loyal Customer,35,Business travel,Business,3191,2,2,2,2,2,5,1,5,5,5,5,5,5,5,0,0.0,satisfied +13459,41770,Female,disloyal Customer,44,Business travel,Eco,472,3,4,4,3,1,4,1,1,1,1,2,3,4,1,0,0.0,neutral or dissatisfied +13460,40726,Male,Loyal Customer,32,Business travel,Eco,558,5,2,2,2,5,5,5,5,4,5,4,1,1,5,0,0.0,satisfied +13461,63987,Male,Loyal Customer,22,Business travel,Business,1577,1,1,5,1,4,4,4,4,5,3,5,4,4,4,10,4.0,satisfied +13462,24299,Female,Loyal Customer,63,Business travel,Eco Plus,147,4,1,1,1,4,4,2,4,4,4,4,1,4,4,0,0.0,satisfied +13463,126681,Male,disloyal Customer,39,Business travel,Business,2521,3,3,3,4,2,3,2,2,3,3,4,4,4,2,3,0.0,neutral or dissatisfied +13464,58700,Male,Loyal Customer,60,Business travel,Business,4243,3,3,3,3,5,5,5,3,5,3,5,5,4,5,18,23.0,satisfied +13465,27467,Female,Loyal Customer,55,Business travel,Eco,1050,5,1,3,1,5,2,2,5,5,5,5,3,5,3,0,0.0,satisfied +13466,88864,Female,Loyal Customer,38,Business travel,Business,859,5,5,5,5,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +13467,64600,Female,Loyal Customer,44,Business travel,Business,2573,3,3,5,3,5,5,4,4,4,4,4,3,4,4,11,5.0,satisfied +13468,115785,Male,Loyal Customer,56,Business travel,Business,308,1,1,1,1,2,5,5,5,5,4,5,3,5,5,0,1.0,satisfied +13469,108691,Male,Loyal Customer,60,Business travel,Eco,177,2,3,3,3,3,2,3,3,2,5,2,1,2,3,49,55.0,neutral or dissatisfied +13470,76108,Female,Loyal Customer,40,Personal Travel,Eco Plus,669,3,5,3,1,4,3,4,4,4,5,5,5,5,4,0,0.0,neutral or dissatisfied +13471,56411,Male,Loyal Customer,24,Business travel,Business,1714,1,1,1,1,5,5,5,5,4,2,5,3,5,5,7,10.0,satisfied +13472,110303,Female,Loyal Customer,43,Business travel,Business,1535,5,3,5,5,4,5,4,5,5,5,5,4,5,5,3,0.0,satisfied +13473,72404,Male,Loyal Customer,56,Business travel,Business,1121,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +13474,96394,Female,disloyal Customer,21,Business travel,Eco,1246,4,4,4,3,3,4,2,3,4,5,5,5,5,3,106,,satisfied +13475,20563,Female,Loyal Customer,40,Business travel,Eco,606,2,3,3,3,2,3,2,2,2,3,2,4,3,2,54,38.0,neutral or dissatisfied +13476,1490,Female,disloyal Customer,24,Business travel,Business,737,5,0,5,3,5,5,5,5,3,4,4,5,5,5,0,5.0,satisfied +13477,45278,Male,Loyal Customer,37,Business travel,Business,150,3,3,3,3,5,2,2,5,5,5,5,3,5,2,0,0.0,satisfied +13478,59897,Female,Loyal Customer,60,Business travel,Business,1065,2,2,2,2,3,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +13479,8697,Female,disloyal Customer,47,Business travel,Eco,280,1,0,1,3,4,1,4,4,2,4,2,1,4,4,0,0.0,neutral or dissatisfied +13480,129487,Female,Loyal Customer,9,Personal Travel,Eco,2704,2,5,2,2,4,2,4,4,4,3,5,4,5,4,0,3.0,neutral or dissatisfied +13481,97053,Male,Loyal Customer,27,Business travel,Business,1129,2,1,2,2,5,4,5,5,4,4,5,5,5,5,29,31.0,satisfied +13482,10933,Female,Loyal Customer,57,Business travel,Business,216,2,4,4,4,4,4,3,1,1,1,2,3,1,1,0,0.0,neutral or dissatisfied +13483,30102,Female,Loyal Customer,20,Personal Travel,Eco,213,1,1,1,4,3,1,5,3,4,5,4,2,4,3,101,105.0,neutral or dissatisfied +13484,51535,Female,Loyal Customer,50,Business travel,Business,451,4,4,4,4,3,1,3,5,5,5,5,2,5,1,0,0.0,satisfied +13485,121338,Female,Loyal Customer,59,Business travel,Business,3203,5,5,5,5,4,5,5,2,2,2,2,4,2,3,7,20.0,satisfied +13486,91734,Male,Loyal Customer,63,Business travel,Business,588,3,1,2,1,2,1,1,3,3,3,3,4,3,3,12,6.0,neutral or dissatisfied +13487,35964,Male,disloyal Customer,35,Business travel,Business,231,3,3,3,4,3,2,2,1,3,3,3,2,3,2,156,156.0,neutral or dissatisfied +13488,99210,Female,Loyal Customer,59,Business travel,Business,495,1,1,1,1,5,5,5,4,4,4,4,4,4,5,9,0.0,satisfied +13489,125584,Female,disloyal Customer,17,Business travel,Eco,1446,3,3,3,2,4,3,4,4,5,4,4,3,5,4,0,19.0,neutral or dissatisfied +13490,21612,Male,Loyal Customer,36,Business travel,Business,2137,3,3,3,3,4,1,3,5,5,5,5,5,5,2,0,0.0,satisfied +13491,80598,Male,Loyal Customer,64,Business travel,Eco Plus,247,2,4,4,4,2,2,2,2,1,5,3,2,3,2,2,12.0,neutral or dissatisfied +13492,86136,Male,Loyal Customer,40,Business travel,Business,3306,3,3,3,3,5,4,4,4,4,4,4,3,4,3,22,49.0,satisfied +13493,106611,Male,Loyal Customer,68,Personal Travel,Eco,589,3,5,3,3,4,3,4,4,5,4,5,5,4,4,0,22.0,neutral or dissatisfied +13494,48775,Male,disloyal Customer,36,Business travel,Business,109,1,1,1,4,5,1,5,5,4,3,3,3,4,5,18,8.0,neutral or dissatisfied +13495,59196,Male,Loyal Customer,25,Business travel,Business,1440,5,5,5,5,4,4,4,4,4,5,4,4,5,4,0,0.0,satisfied +13496,44402,Male,Loyal Customer,71,Business travel,Business,3055,1,2,2,2,1,3,4,1,1,2,1,2,1,4,95,108.0,neutral or dissatisfied +13497,85685,Female,Loyal Customer,41,Business travel,Business,1547,4,4,4,4,3,4,4,5,5,5,5,3,5,3,0,3.0,satisfied +13498,99696,Male,Loyal Customer,10,Personal Travel,Eco,442,2,5,2,3,2,2,3,2,4,3,5,2,2,2,72,80.0,neutral or dissatisfied +13499,12677,Female,Loyal Customer,40,Business travel,Business,851,5,5,5,5,1,5,4,4,4,4,4,4,4,1,18,36.0,satisfied +13500,1388,Female,Loyal Customer,56,Personal Travel,Eco Plus,113,2,5,2,3,2,3,1,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +13501,38794,Female,disloyal Customer,23,Business travel,Eco,387,3,2,3,3,2,3,2,2,2,1,4,2,4,2,0,0.0,neutral or dissatisfied +13502,95563,Female,Loyal Customer,27,Personal Travel,Eco Plus,319,2,4,2,4,4,2,4,4,2,3,4,3,3,4,7,0.0,neutral or dissatisfied +13503,96452,Female,Loyal Customer,36,Business travel,Business,302,1,1,1,1,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +13504,127559,Male,Loyal Customer,54,Business travel,Business,1670,5,5,2,5,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +13505,48713,Female,disloyal Customer,37,Business travel,Business,77,1,2,2,4,1,2,1,1,2,1,3,1,4,1,59,58.0,neutral or dissatisfied +13506,33878,Male,Loyal Customer,32,Business travel,Eco,1105,0,0,0,5,2,0,2,2,2,4,5,1,4,2,0,0.0,satisfied +13507,122016,Male,disloyal Customer,25,Business travel,Business,130,5,0,5,2,5,5,5,5,3,2,5,3,5,5,3,0.0,satisfied +13508,88359,Male,Loyal Customer,66,Business travel,Business,442,1,1,1,1,4,4,4,5,5,5,5,5,5,4,2,0.0,satisfied +13509,119186,Male,Loyal Customer,50,Business travel,Business,2336,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,7.0,satisfied +13510,40863,Female,Loyal Customer,36,Personal Travel,Eco,588,5,5,5,5,2,5,2,2,3,2,5,5,4,2,0,0.0,satisfied +13511,76374,Male,Loyal Customer,41,Business travel,Business,3237,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +13512,80144,Female,Loyal Customer,29,Business travel,Business,2586,1,1,1,1,5,5,5,4,2,4,4,5,4,5,16,5.0,satisfied +13513,92091,Male,Loyal Customer,12,Business travel,Business,1532,3,3,3,3,3,3,3,3,4,5,4,1,4,3,0,0.0,neutral or dissatisfied +13514,109973,Male,Loyal Customer,67,Personal Travel,Eco,1130,2,4,2,5,3,2,3,3,5,4,4,5,5,3,39,36.0,neutral or dissatisfied +13515,87204,Female,disloyal Customer,25,Business travel,Eco,946,1,2,2,4,3,2,3,3,2,4,3,1,3,3,63,83.0,neutral or dissatisfied +13516,60674,Female,Loyal Customer,58,Business travel,Business,1620,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +13517,12718,Female,Loyal Customer,10,Business travel,Business,3036,5,5,5,5,5,5,5,5,2,4,5,4,2,5,0,0.0,satisfied +13518,28131,Female,Loyal Customer,18,Business travel,Eco,550,5,5,5,5,5,5,5,5,3,1,4,2,2,5,0,0.0,satisfied +13519,53601,Male,Loyal Customer,69,Personal Travel,Eco,3801,1,5,1,1,1,4,4,3,4,3,5,4,5,4,15,0.0,neutral or dissatisfied +13520,3934,Female,Loyal Customer,45,Business travel,Business,765,2,4,3,4,2,4,4,2,2,2,2,3,2,3,0,17.0,neutral or dissatisfied +13521,2409,Male,Loyal Customer,9,Business travel,Business,604,2,1,2,2,1,2,1,1,3,2,4,4,4,1,0,1.0,satisfied +13522,22632,Male,Loyal Customer,31,Personal Travel,Eco,300,2,4,4,2,1,4,1,1,3,3,4,4,5,1,78,68.0,neutral or dissatisfied +13523,87272,Female,Loyal Customer,31,Business travel,Eco,577,1,3,2,2,1,1,1,1,1,4,3,3,3,1,0,0.0,neutral or dissatisfied +13524,42677,Female,Loyal Customer,41,Business travel,Eco,627,2,3,5,5,2,2,2,2,2,1,4,1,4,2,0,0.0,neutral or dissatisfied +13525,42798,Male,Loyal Customer,58,Business travel,Business,677,1,1,1,1,4,3,3,1,1,2,1,1,1,3,78,81.0,neutral or dissatisfied +13526,38679,Female,Loyal Customer,36,Personal Travel,Eco,2588,1,5,2,4,2,2,2,2,5,4,3,5,5,2,0,0.0,neutral or dissatisfied +13527,63933,Female,Loyal Customer,32,Personal Travel,Eco,1158,3,3,3,3,4,3,4,4,1,5,2,4,4,4,0,15.0,neutral or dissatisfied +13528,36671,Female,Loyal Customer,25,Personal Travel,Eco,1010,3,3,3,3,1,3,1,1,1,5,5,1,2,1,0,22.0,neutral or dissatisfied +13529,7065,Female,Loyal Customer,53,Business travel,Business,1677,5,5,5,5,2,4,5,5,5,5,5,4,5,3,32,17.0,satisfied +13530,127923,Female,disloyal Customer,40,Business travel,Business,2300,5,5,5,4,5,5,5,5,3,5,3,5,4,5,0,0.0,satisfied +13531,853,Male,disloyal Customer,17,Business travel,Eco,229,3,3,3,3,5,3,5,5,4,3,4,1,3,5,0,0.0,neutral or dissatisfied +13532,124438,Male,Loyal Customer,39,Business travel,Eco Plus,1044,1,1,1,1,1,2,1,1,3,4,3,2,3,1,0,13.0,neutral or dissatisfied +13533,45937,Female,Loyal Customer,63,Personal Travel,Eco,563,2,2,1,4,2,3,3,2,2,1,2,2,2,1,46,66.0,neutral or dissatisfied +13534,66873,Male,Loyal Customer,25,Personal Travel,Eco Plus,731,4,1,4,3,2,4,2,2,1,1,3,1,3,2,5,0.0,satisfied +13535,118059,Male,Loyal Customer,53,Business travel,Business,3289,5,5,5,5,5,3,5,5,5,5,5,4,5,1,2,0.0,satisfied +13536,15876,Male,Loyal Customer,66,Business travel,Eco,332,4,3,3,3,4,4,4,4,4,3,3,5,3,4,0,0.0,satisfied +13537,58404,Male,disloyal Customer,29,Business travel,Business,528,1,1,1,5,3,1,3,3,5,3,5,5,5,3,29,11.0,neutral or dissatisfied +13538,121768,Female,Loyal Customer,56,Business travel,Business,3746,1,1,1,1,5,4,5,4,4,4,4,5,4,5,15,13.0,satisfied +13539,117996,Female,Loyal Customer,18,Personal Travel,Eco Plus,365,3,4,3,3,5,3,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +13540,3746,Female,Loyal Customer,8,Personal Travel,Eco,431,2,5,2,5,2,2,2,2,4,4,5,4,5,2,0,0.0,neutral or dissatisfied +13541,25544,Female,disloyal Customer,50,Personal Travel,Eco,547,2,3,2,3,2,2,1,2,2,2,4,5,3,2,2,0.0,neutral or dissatisfied +13542,87130,Female,Loyal Customer,30,Personal Travel,Eco,594,5,3,5,2,2,5,2,2,2,5,1,3,1,2,0,0.0,satisfied +13543,48226,Female,Loyal Customer,30,Personal Travel,Eco,192,3,4,3,5,4,3,4,4,5,3,5,4,5,4,30,20.0,neutral or dissatisfied +13544,106006,Male,Loyal Customer,51,Business travel,Business,1999,4,3,3,3,1,4,3,4,4,4,4,2,4,4,15,11.0,neutral or dissatisfied +13545,6891,Male,Loyal Customer,32,Business travel,Eco,265,2,3,1,3,2,2,2,2,1,2,4,4,3,2,2,0.0,neutral or dissatisfied +13546,122497,Male,Loyal Customer,41,Business travel,Business,2608,2,2,2,2,3,5,4,5,5,5,5,5,5,4,7,0.0,satisfied +13547,77479,Female,Loyal Customer,59,Personal Travel,Eco,2125,4,2,4,2,2,2,1,5,5,4,5,4,5,4,7,0.0,neutral or dissatisfied +13548,49076,Female,Loyal Customer,60,Business travel,Eco,308,4,1,1,1,2,5,4,4,4,4,4,1,4,3,0,21.0,satisfied +13549,15481,Male,Loyal Customer,61,Personal Travel,Eco,331,4,4,4,5,4,4,4,4,3,4,4,5,4,4,18,8.0,neutral or dissatisfied +13550,2581,Female,Loyal Customer,66,Business travel,Business,280,3,3,3,3,1,2,5,4,4,4,4,5,4,4,0,0.0,satisfied +13551,69349,Male,Loyal Customer,26,Business travel,Business,1096,2,2,2,2,3,3,3,3,5,2,5,4,4,3,0,32.0,satisfied +13552,119232,Female,Loyal Customer,57,Personal Travel,Eco,331,2,2,2,3,1,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +13553,57077,Male,Loyal Customer,39,Business travel,Business,1222,4,4,4,4,2,4,4,5,5,5,5,3,5,3,7,1.0,satisfied +13554,10087,Male,disloyal Customer,36,Business travel,Business,266,2,2,2,3,4,2,4,4,4,3,2,4,2,4,0,0.0,neutral or dissatisfied +13555,101876,Female,Loyal Customer,18,Personal Travel,Eco,1747,2,4,2,3,1,2,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +13556,57963,Female,Loyal Customer,16,Personal Travel,Eco,1670,2,4,2,4,2,2,2,2,3,2,4,1,1,2,0,0.0,neutral or dissatisfied +13557,16545,Male,Loyal Customer,32,Personal Travel,Eco,1134,2,5,3,1,3,3,3,3,5,5,4,4,4,3,47,57.0,neutral or dissatisfied +13558,12453,Male,Loyal Customer,65,Personal Travel,Eco,305,2,4,2,3,2,2,2,4,5,4,5,2,3,2,171,156.0,neutral or dissatisfied +13559,109146,Female,Loyal Customer,40,Business travel,Business,2795,4,4,4,4,2,4,5,5,5,5,5,3,5,4,6,6.0,satisfied +13560,46163,Male,Loyal Customer,47,Personal Travel,Eco,604,3,1,3,4,3,1,1,1,5,4,3,1,2,1,113,141.0,neutral or dissatisfied +13561,34340,Male,Loyal Customer,42,Business travel,Business,3181,5,5,5,5,3,2,3,4,4,4,4,5,4,5,4,4.0,satisfied +13562,71065,Male,Loyal Customer,42,Personal Travel,Eco,802,3,2,3,3,2,3,2,2,2,3,4,4,3,2,1,7.0,neutral or dissatisfied +13563,31745,Female,Loyal Customer,50,Business travel,Eco Plus,462,2,3,5,5,4,2,3,2,2,2,2,1,2,5,15,13.0,satisfied +13564,114073,Female,disloyal Customer,28,Business travel,Eco,1253,1,0,0,3,1,1,1,1,3,4,4,2,4,1,0,0.0,neutral or dissatisfied +13565,116901,Male,disloyal Customer,48,Business travel,Business,325,3,4,4,4,1,3,1,1,5,4,4,4,4,1,2,0.0,satisfied +13566,106446,Male,Loyal Customer,16,Personal Travel,Eco,1062,2,5,2,4,2,1,1,3,5,4,4,1,4,1,259,261.0,neutral or dissatisfied +13567,93219,Male,disloyal Customer,28,Business travel,Business,1460,3,3,3,1,2,3,2,2,3,2,5,5,4,2,1,1.0,neutral or dissatisfied +13568,376,Male,Loyal Customer,54,Business travel,Business,270,0,1,1,4,3,4,4,4,4,4,4,4,4,4,44,26.0,satisfied +13569,30811,Female,Loyal Customer,66,Personal Travel,Eco,1199,2,4,2,5,3,4,1,2,2,2,2,1,2,3,13,21.0,neutral or dissatisfied +13570,97982,Female,Loyal Customer,22,Personal Travel,Eco,616,2,2,2,3,2,2,2,2,4,3,3,2,3,2,16,15.0,neutral or dissatisfied +13571,82059,Female,Loyal Customer,59,Business travel,Business,2605,3,3,3,3,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +13572,36773,Female,disloyal Customer,21,Business travel,Eco,2602,3,3,3,3,3,3,3,2,5,3,2,3,4,3,54,54.0,neutral or dissatisfied +13573,47407,Female,disloyal Customer,21,Business travel,Eco,599,3,1,3,4,5,3,5,5,2,5,3,1,4,5,0,0.0,neutral or dissatisfied +13574,89620,Male,disloyal Customer,45,Business travel,Business,1096,4,4,4,2,3,4,3,3,5,2,4,5,5,3,18,15.0,satisfied +13575,43087,Female,Loyal Customer,51,Personal Travel,Eco,192,2,4,2,3,3,5,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +13576,101759,Female,Loyal Customer,14,Personal Travel,Eco,1590,3,4,3,3,3,3,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +13577,39636,Female,Loyal Customer,70,Personal Travel,Eco Plus,965,4,5,4,4,5,4,5,2,2,4,2,5,2,4,0,2.0,neutral or dissatisfied +13578,41344,Female,Loyal Customer,68,Personal Travel,Eco Plus,689,1,3,1,4,3,1,5,3,3,1,3,3,3,2,7,0.0,neutral or dissatisfied +13579,116702,Male,Loyal Customer,57,Business travel,Business,337,2,2,5,2,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +13580,77246,Female,disloyal Customer,8,Business travel,Eco,1140,2,2,2,3,4,2,4,4,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +13581,5557,Female,disloyal Customer,40,Business travel,Business,588,2,2,2,4,5,2,5,5,2,2,4,2,3,5,0,0.0,neutral or dissatisfied +13582,94994,Male,Loyal Customer,25,Personal Travel,Eco,323,3,1,3,4,4,3,4,4,1,1,4,4,4,4,72,78.0,neutral or dissatisfied +13583,67370,Female,Loyal Customer,50,Business travel,Business,592,4,4,2,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +13584,1003,Male,disloyal Customer,22,Business travel,Eco,113,1,1,1,4,3,1,3,3,4,1,3,3,4,3,52,59.0,neutral or dissatisfied +13585,122112,Female,Loyal Customer,26,Personal Travel,Eco,130,2,5,0,2,5,0,5,5,5,3,5,5,4,5,1,3.0,neutral or dissatisfied +13586,41673,Female,disloyal Customer,16,Business travel,Eco,843,4,4,4,2,5,4,5,5,4,2,3,2,1,5,0,2.0,satisfied +13587,53913,Male,Loyal Customer,54,Personal Travel,Eco,191,1,4,1,4,3,1,3,3,4,2,4,5,5,3,0,0.0,neutral or dissatisfied +13588,79381,Male,Loyal Customer,48,Business travel,Business,2767,5,5,5,5,3,5,4,4,4,4,4,4,4,3,28,15.0,satisfied +13589,90514,Male,disloyal Customer,40,Business travel,Business,442,1,1,1,3,2,1,2,2,3,3,5,5,4,2,4,0.0,neutral or dissatisfied +13590,86830,Female,Loyal Customer,50,Business travel,Eco,692,2,4,4,4,4,4,4,2,2,2,2,2,2,2,0,9.0,neutral or dissatisfied +13591,56184,Male,Loyal Customer,59,Personal Travel,Eco,1400,3,1,3,2,1,3,1,1,2,1,2,2,2,1,0,0.0,neutral or dissatisfied +13592,15704,Male,disloyal Customer,23,Business travel,Eco,419,4,0,4,3,2,4,2,2,1,1,3,4,4,2,70,55.0,satisfied +13593,47759,Male,disloyal Customer,24,Business travel,Eco,748,0,0,0,5,1,0,1,1,3,4,2,4,3,1,6,4.0,satisfied +13594,3263,Female,disloyal Customer,36,Business travel,Eco,479,4,3,4,4,3,4,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +13595,52249,Female,Loyal Customer,44,Business travel,Business,598,3,3,3,3,5,4,2,3,3,4,3,1,3,1,0,4.0,satisfied +13596,89429,Female,Loyal Customer,58,Personal Travel,Eco,134,0,0,0,3,3,3,3,3,3,0,1,2,3,5,47,48.0,satisfied +13597,7404,Female,Loyal Customer,55,Business travel,Business,3903,5,5,5,5,2,5,4,5,5,5,5,5,5,3,15,51.0,satisfied +13598,62722,Female,Loyal Customer,59,Business travel,Business,2556,2,2,2,2,4,4,4,5,4,4,4,4,4,4,5,0.0,satisfied +13599,118573,Female,Loyal Customer,57,Business travel,Eco,304,2,2,2,2,5,4,4,2,2,2,2,2,2,1,0,68.0,neutral or dissatisfied +13600,91776,Male,Loyal Customer,50,Personal Travel,Eco,590,3,3,4,3,5,4,3,5,2,4,1,3,5,5,24,21.0,neutral or dissatisfied +13601,21611,Female,Loyal Customer,54,Business travel,Business,853,4,4,4,4,4,4,4,4,5,4,4,4,3,4,383,358.0,satisfied +13602,59092,Female,Loyal Customer,40,Personal Travel,Eco,1723,1,5,1,1,3,1,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +13603,45700,Female,Loyal Customer,40,Business travel,Eco Plus,826,4,3,3,3,4,4,4,4,3,5,3,3,3,4,8,8.0,neutral or dissatisfied +13604,117670,Male,Loyal Customer,40,Personal Travel,Eco,1449,1,1,0,2,0,4,4,3,4,3,2,4,4,4,205,210.0,neutral or dissatisfied +13605,45915,Female,Loyal Customer,27,Business travel,Business,1513,2,1,1,1,2,2,2,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +13606,13503,Male,Loyal Customer,48,Business travel,Eco,106,5,5,1,1,5,5,5,5,3,2,5,4,3,5,0,3.0,satisfied +13607,67040,Male,disloyal Customer,11,Business travel,Business,1119,3,3,3,4,4,3,3,4,2,3,3,4,4,4,3,23.0,neutral or dissatisfied +13608,81933,Female,Loyal Customer,29,Business travel,Business,1522,3,3,3,3,5,5,5,5,5,5,4,4,5,5,0,12.0,satisfied +13609,21495,Male,Loyal Customer,67,Personal Travel,Eco,433,3,4,3,1,4,3,4,4,5,4,5,3,5,4,17,26.0,neutral or dissatisfied +13610,76499,Female,Loyal Customer,56,Business travel,Business,534,2,3,2,2,3,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +13611,82706,Male,Loyal Customer,12,Personal Travel,Eco,632,5,3,5,3,1,5,1,1,4,4,3,2,4,1,31,37.0,satisfied +13612,120219,Male,Loyal Customer,25,Business travel,Business,1325,3,5,5,5,3,3,3,3,1,2,4,4,4,3,0,52.0,neutral or dissatisfied +13613,22327,Female,Loyal Customer,31,Business travel,Eco,143,5,3,3,3,5,5,5,5,5,3,5,1,5,5,0,0.0,satisfied +13614,105072,Male,disloyal Customer,38,Business travel,Business,281,5,5,5,1,5,5,5,5,3,2,4,4,5,5,0,5.0,satisfied +13615,53625,Female,disloyal Customer,21,Business travel,Business,1874,4,0,4,1,1,4,1,1,5,3,3,3,1,1,2,0.0,satisfied +13616,17919,Male,Loyal Customer,66,Business travel,Eco,389,4,3,3,3,4,4,4,4,5,3,2,4,4,4,0,0.0,satisfied +13617,93504,Male,Loyal Customer,55,Personal Travel,Eco,1107,1,4,1,3,4,1,4,4,3,2,4,5,4,4,2,0.0,neutral or dissatisfied +13618,96511,Female,Loyal Customer,45,Personal Travel,Eco,436,0,5,0,2,4,5,5,4,4,0,4,5,4,4,0,9.0,satisfied +13619,104613,Male,Loyal Customer,54,Personal Travel,Eco Plus,369,2,3,2,3,2,2,2,2,2,5,4,4,3,2,6,8.0,neutral or dissatisfied +13620,869,Male,disloyal Customer,23,Business travel,Business,134,5,0,5,1,5,5,5,5,4,4,5,4,5,5,0,0.0,satisfied +13621,56989,Female,Loyal Customer,13,Personal Travel,Eco,2454,2,3,2,3,2,1,1,4,2,3,4,1,1,1,4,1.0,neutral or dissatisfied +13622,32697,Female,Loyal Customer,43,Business travel,Business,102,3,3,3,3,2,2,3,4,4,4,3,5,4,3,0,0.0,satisfied +13623,21347,Female,disloyal Customer,26,Business travel,Eco,761,2,2,2,3,1,2,1,1,2,5,4,4,3,1,0,0.0,neutral or dissatisfied +13624,37829,Male,Loyal Customer,28,Business travel,Eco,937,5,1,1,1,5,5,5,5,3,1,2,4,1,5,9,5.0,satisfied +13625,47628,Female,disloyal Customer,41,Business travel,Eco,1482,5,5,5,4,2,5,2,2,4,2,2,3,5,2,0,0.0,satisfied +13626,58426,Male,Loyal Customer,37,Business travel,Eco,333,5,4,4,4,5,5,5,5,5,2,4,2,4,5,27,16.0,satisfied +13627,100465,Female,Loyal Customer,34,Business travel,Business,580,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +13628,12244,Male,disloyal Customer,36,Business travel,Eco,201,3,4,3,3,2,3,2,2,4,4,5,1,2,2,8,2.0,neutral or dissatisfied +13629,81692,Female,Loyal Customer,24,Personal Travel,Eco,907,2,5,2,1,2,2,2,2,5,3,5,3,4,2,0,0.0,neutral or dissatisfied +13630,79224,Female,Loyal Customer,44,Business travel,Eco Plus,1990,3,2,2,2,4,3,4,3,3,3,3,4,3,4,2,10.0,neutral or dissatisfied +13631,106244,Male,Loyal Customer,57,Business travel,Business,1167,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +13632,71415,Male,Loyal Customer,43,Business travel,Business,3009,1,1,1,1,5,5,5,4,4,4,4,5,4,3,55,54.0,satisfied +13633,4389,Female,Loyal Customer,22,Personal Travel,Eco,607,2,5,3,3,4,3,4,4,5,3,5,5,4,4,0,0.0,neutral or dissatisfied +13634,28660,Female,Loyal Customer,68,Personal Travel,Eco,2384,2,4,2,1,5,4,4,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +13635,120825,Female,Loyal Customer,53,Business travel,Business,1898,4,4,4,4,2,5,4,5,5,5,5,4,5,3,23,8.0,satisfied +13636,21452,Female,disloyal Customer,32,Business travel,Eco,399,2,0,2,5,3,2,3,3,3,5,2,5,1,3,0,0.0,neutral or dissatisfied +13637,94277,Female,disloyal Customer,21,Business travel,Business,189,5,0,4,2,5,4,5,5,5,2,4,4,4,5,0,0.0,satisfied +13638,5707,Female,Loyal Customer,31,Personal Travel,Eco,196,1,5,0,4,2,0,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +13639,22683,Male,Loyal Customer,19,Business travel,Business,1984,5,5,5,5,3,3,3,3,4,2,2,5,2,3,27,33.0,satisfied +13640,16098,Male,Loyal Customer,22,Personal Travel,Eco,303,4,5,4,2,4,4,5,4,5,3,4,5,5,4,0,0.0,satisfied +13641,112674,Male,disloyal Customer,45,Business travel,Business,697,5,5,5,3,4,5,4,4,5,4,5,4,4,4,0,0.0,satisfied +13642,84913,Female,Loyal Customer,32,Personal Travel,Eco,481,2,5,2,3,2,2,2,2,2,3,1,2,5,2,0,0.0,neutral or dissatisfied +13643,78031,Male,Loyal Customer,50,Personal Travel,Eco,106,2,4,0,5,2,0,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +13644,30950,Female,disloyal Customer,20,Business travel,Eco,836,3,3,3,1,5,3,4,5,2,1,2,2,5,5,0,0.0,neutral or dissatisfied +13645,92219,Female,Loyal Customer,8,Personal Travel,Eco,1956,4,4,4,2,5,4,5,5,4,3,5,3,4,5,36,38.0,neutral or dissatisfied +13646,67302,Female,disloyal Customer,35,Business travel,Eco Plus,1121,3,3,3,4,3,3,3,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +13647,49001,Female,Loyal Customer,49,Business travel,Business,2771,1,1,1,1,3,3,1,4,4,4,4,3,4,3,0,0.0,satisfied +13648,57718,Male,Loyal Customer,44,Business travel,Business,1754,5,5,5,5,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +13649,56996,Female,Loyal Customer,31,Personal Travel,Eco,2454,2,5,2,5,2,2,2,2,3,4,5,4,5,2,6,0.0,neutral or dissatisfied +13650,119158,Female,Loyal Customer,65,Personal Travel,Business,257,2,3,2,3,1,1,2,5,5,2,3,3,5,5,0,0.0,neutral or dissatisfied +13651,82390,Male,Loyal Customer,39,Business travel,Business,2303,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +13652,110575,Female,Loyal Customer,55,Business travel,Business,643,1,1,1,1,4,4,5,4,4,4,4,3,4,4,72,59.0,satisfied +13653,94429,Female,Loyal Customer,48,Business travel,Business,239,5,5,5,5,2,4,5,4,4,4,4,4,4,4,12,4.0,satisfied +13654,51413,Female,Loyal Customer,14,Personal Travel,Eco Plus,337,1,4,1,3,4,1,4,4,3,3,5,4,4,4,0,0.0,neutral or dissatisfied +13655,783,Female,Loyal Customer,44,Business travel,Business,89,3,3,3,3,2,5,5,4,4,5,5,5,4,5,0,0.0,satisfied +13656,88189,Male,Loyal Customer,48,Business travel,Business,1609,3,3,3,3,2,5,5,5,5,5,5,3,5,4,0,10.0,satisfied +13657,76731,Female,Loyal Customer,36,Personal Travel,Eco Plus,481,4,3,4,5,5,4,5,5,2,4,5,1,1,5,0,0.0,neutral or dissatisfied +13658,98825,Male,disloyal Customer,16,Business travel,Eco,444,5,3,5,3,1,5,1,1,2,4,3,1,1,1,0,0.0,satisfied +13659,66865,Female,disloyal Customer,40,Business travel,Business,731,4,4,4,2,3,4,3,3,5,4,5,5,4,3,0,0.0,satisfied +13660,27867,Male,Loyal Customer,24,Business travel,Eco Plus,1448,4,5,5,5,4,4,5,4,3,2,3,1,3,4,1,0.0,satisfied +13661,46145,Female,disloyal Customer,28,Business travel,Eco,604,1,2,1,4,1,3,3,1,5,3,4,3,1,3,135,157.0,neutral or dissatisfied +13662,54532,Female,Loyal Customer,19,Personal Travel,Eco,925,3,4,4,4,1,4,1,1,5,5,4,4,4,1,4,0.0,neutral or dissatisfied +13663,85618,Male,Loyal Customer,49,Personal Travel,Eco,259,3,4,3,5,5,3,5,5,2,5,5,1,5,5,3,12.0,neutral or dissatisfied +13664,73247,Female,disloyal Customer,49,Business travel,Business,675,4,4,4,3,1,4,1,1,4,5,5,3,4,1,0,0.0,satisfied +13665,129701,Female,Loyal Customer,25,Business travel,Business,447,4,5,2,2,4,4,4,4,1,1,3,1,3,4,0,0.0,neutral or dissatisfied +13666,58706,Female,disloyal Customer,25,Business travel,Business,4243,1,4,1,4,1,2,3,3,2,3,5,3,4,3,0,1.0,neutral or dissatisfied +13667,27294,Male,Loyal Customer,27,Business travel,Business,1050,2,5,2,5,2,2,2,2,1,3,3,4,4,2,0,3.0,neutral or dissatisfied +13668,58653,Female,Loyal Customer,22,Personal Travel,Eco,867,2,3,2,3,3,2,3,3,1,3,3,2,3,3,0,0.0,neutral or dissatisfied +13669,83369,Male,Loyal Customer,72,Business travel,Business,1124,5,4,4,4,3,2,3,5,5,4,5,1,5,4,24,11.0,neutral or dissatisfied +13670,39191,Female,Loyal Customer,52,Business travel,Business,318,0,0,0,3,4,2,4,1,1,1,1,1,1,4,0,0.0,satisfied +13671,57274,Male,Loyal Customer,39,Personal Travel,Eco,628,2,5,2,3,1,2,1,1,3,4,5,5,5,1,0,0.0,neutral or dissatisfied +13672,20369,Male,Loyal Customer,32,Personal Travel,Eco,265,2,4,2,4,5,2,5,5,2,1,4,2,2,5,42,35.0,neutral or dissatisfied +13673,17408,Female,Loyal Customer,53,Business travel,Eco,351,4,2,2,2,5,2,4,4,4,4,4,5,4,5,0,0.0,satisfied +13674,76134,Female,Loyal Customer,33,Business travel,Business,546,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +13675,98800,Male,disloyal Customer,54,Business travel,Business,1111,3,3,3,4,2,3,4,2,4,2,4,5,4,2,46,38.0,neutral or dissatisfied +13676,46603,Male,disloyal Customer,36,Business travel,Eco,73,2,2,2,4,2,2,2,2,1,5,3,2,3,2,18,14.0,neutral or dissatisfied +13677,49585,Female,Loyal Customer,49,Business travel,Eco,308,5,1,1,1,3,1,2,5,5,5,5,4,5,4,0,0.0,satisfied +13678,60234,Female,disloyal Customer,59,Business travel,Eco,1007,2,2,2,3,5,2,4,5,1,3,3,5,1,5,8,8.0,neutral or dissatisfied +13679,16149,Male,Loyal Customer,33,Business travel,Business,199,4,4,4,4,4,4,4,4,3,4,2,4,5,4,0,0.0,satisfied +13680,91706,Male,disloyal Customer,23,Business travel,Eco,626,5,0,5,3,3,0,3,3,4,2,4,3,4,3,0,0.0,satisfied +13681,62502,Male,disloyal Customer,18,Business travel,Eco,1378,3,4,4,2,3,3,3,3,5,4,3,3,5,3,0,0.0,neutral or dissatisfied +13682,69845,Male,Loyal Customer,66,Personal Travel,Eco,1055,4,4,4,2,4,4,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +13683,49497,Female,Loyal Customer,41,Business travel,Eco,373,4,5,5,5,4,4,4,4,1,3,3,5,1,4,0,0.0,satisfied +13684,68613,Female,Loyal Customer,60,Business travel,Business,3952,0,4,0,4,2,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +13685,105719,Male,Loyal Customer,60,Business travel,Business,2202,2,4,5,4,4,4,3,2,2,2,2,2,2,2,14,16.0,neutral or dissatisfied +13686,102934,Female,Loyal Customer,64,Personal Travel,Eco,317,2,4,2,3,4,4,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +13687,33322,Male,Loyal Customer,45,Business travel,Business,2409,2,2,2,2,3,3,3,5,5,5,5,1,5,4,0,0.0,satisfied +13688,73298,Female,Loyal Customer,59,Business travel,Business,2411,3,3,3,3,5,4,4,4,4,4,4,4,4,5,20,16.0,satisfied +13689,464,Female,Loyal Customer,26,Business travel,Business,229,5,5,5,5,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +13690,58678,Female,disloyal Customer,23,Business travel,Eco,622,0,2,0,4,5,0,5,5,3,2,4,4,4,5,0,0.0,satisfied +13691,102632,Male,disloyal Customer,38,Business travel,Business,255,4,4,4,2,4,4,1,4,5,4,5,5,4,4,0,0.0,satisfied +13692,18326,Male,Loyal Customer,47,Personal Travel,Eco Plus,705,2,4,2,2,2,2,5,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +13693,42876,Male,Loyal Customer,26,Personal Travel,Eco,867,5,1,5,4,3,5,4,3,1,5,4,3,4,3,0,0.0,satisfied +13694,2407,Female,disloyal Customer,43,Business travel,Eco,604,2,1,2,4,5,2,5,5,3,2,4,3,4,5,12,10.0,neutral or dissatisfied +13695,29796,Female,Loyal Customer,42,Business travel,Business,3871,1,1,1,1,2,4,2,4,4,4,4,1,4,5,5,6.0,satisfied +13696,16292,Male,Loyal Customer,51,Personal Travel,Eco,748,2,4,2,3,3,2,3,3,4,4,1,4,1,3,34,6.0,neutral or dissatisfied +13697,2438,Female,Loyal Customer,40,Personal Travel,Eco,604,1,4,1,5,2,1,2,2,2,2,5,3,1,2,0,0.0,neutral or dissatisfied +13698,12996,Female,Loyal Customer,60,Business travel,Business,1893,1,1,1,1,4,5,4,4,4,4,4,3,4,4,82,69.0,satisfied +13699,120184,Female,Loyal Customer,50,Business travel,Business,1325,4,5,1,5,5,3,4,4,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +13700,38619,Female,Loyal Customer,42,Business travel,Business,2704,3,3,3,3,4,4,4,4,4,3,5,4,4,4,149,134.0,satisfied +13701,73808,Male,Loyal Customer,65,Personal Travel,Eco Plus,204,2,5,2,2,1,2,1,1,2,3,1,1,3,1,0,0.0,neutral or dissatisfied +13702,28564,Female,disloyal Customer,47,Business travel,Eco Plus,1201,3,2,2,2,4,3,4,4,2,4,4,5,2,4,0,0.0,neutral or dissatisfied +13703,128893,Male,Loyal Customer,64,Business travel,Business,3641,1,1,1,1,5,5,5,2,2,3,2,5,1,5,92,90.0,satisfied +13704,35389,Female,disloyal Customer,22,Business travel,Eco,669,1,0,1,4,2,1,5,2,4,3,5,1,5,2,0,0.0,neutral or dissatisfied +13705,24000,Male,Loyal Customer,41,Business travel,Eco,427,4,5,5,5,4,4,4,5,1,5,3,4,5,4,239,245.0,satisfied +13706,39393,Male,Loyal Customer,27,Business travel,Business,2084,4,4,4,4,5,5,5,5,4,2,2,1,3,5,0,0.0,satisfied +13707,1241,Male,Loyal Customer,16,Personal Travel,Eco,102,5,4,5,4,5,5,5,5,5,4,5,5,4,5,4,0.0,satisfied +13708,72748,Male,Loyal Customer,44,Business travel,Business,3015,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +13709,50287,Female,Loyal Customer,58,Business travel,Business,153,2,2,2,2,2,2,5,5,5,5,4,3,5,4,0,0.0,satisfied +13710,40865,Female,Loyal Customer,52,Personal Travel,Eco,588,1,4,1,2,2,5,5,3,3,1,3,4,3,5,102,87.0,neutral or dissatisfied +13711,27700,Female,Loyal Customer,31,Business travel,Eco Plus,1107,5,5,5,5,5,5,5,5,2,3,1,2,5,5,0,0.0,satisfied +13712,91882,Male,disloyal Customer,28,Business travel,Business,2586,4,4,4,3,2,4,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +13713,109737,Female,Loyal Customer,64,Personal Travel,Eco,534,3,1,2,4,2,4,4,3,3,2,3,1,3,2,2,0.0,neutral or dissatisfied +13714,32605,Male,Loyal Customer,38,Business travel,Eco,216,2,4,4,4,2,2,2,2,2,3,3,1,4,2,0,0.0,neutral or dissatisfied +13715,592,Male,disloyal Customer,55,Business travel,Business,102,1,1,1,4,3,1,3,3,5,5,4,5,5,3,0,0.0,neutral or dissatisfied +13716,49014,Female,Loyal Customer,56,Business travel,Business,3957,0,0,0,2,1,2,4,3,3,3,3,2,3,3,72,86.0,satisfied +13717,87544,Male,disloyal Customer,23,Business travel,Eco,782,4,4,4,4,1,4,5,1,3,4,2,3,2,1,0,0.0,satisfied +13718,98771,Male,Loyal Customer,54,Personal Travel,Eco,1814,1,4,2,5,4,2,4,4,5,5,5,4,4,4,85,62.0,neutral or dissatisfied +13719,73743,Female,Loyal Customer,37,Personal Travel,Eco,204,4,5,4,2,1,4,1,1,2,3,1,3,1,1,0,0.0,neutral or dissatisfied +13720,25934,Female,Loyal Customer,67,Personal Travel,Eco,594,1,5,1,1,3,4,4,2,2,1,2,5,2,3,2,42.0,neutral or dissatisfied +13721,14179,Male,Loyal Customer,30,Business travel,Business,1946,4,4,4,4,4,4,4,4,4,4,4,3,5,4,0,0.0,satisfied +13722,28283,Male,Loyal Customer,52,Business travel,Eco Plus,2402,5,3,5,5,5,5,5,5,3,3,1,5,3,5,1,0.0,satisfied +13723,17571,Female,disloyal Customer,26,Business travel,Eco,1034,2,2,2,1,3,2,1,3,2,4,3,1,5,3,1,0.0,neutral or dissatisfied +13724,81183,Female,Loyal Customer,7,Business travel,Business,3945,2,4,3,4,2,2,2,2,4,2,4,2,3,2,0,0.0,neutral or dissatisfied +13725,23032,Female,disloyal Customer,37,Business travel,Eco,680,2,2,2,3,4,2,4,4,2,1,4,1,3,4,27,10.0,neutral or dissatisfied +13726,70836,Male,Loyal Customer,42,Business travel,Business,2902,4,4,4,4,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +13727,24724,Female,disloyal Customer,25,Business travel,Eco,406,3,0,3,1,3,3,2,3,3,1,2,1,5,3,0,5.0,neutral or dissatisfied +13728,125241,Female,Loyal Customer,48,Personal Travel,Eco,1149,3,5,3,2,2,4,5,1,1,3,1,5,1,3,16,9.0,neutral or dissatisfied +13729,10900,Male,Loyal Customer,35,Business travel,Business,1504,2,1,1,1,2,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +13730,90139,Male,Loyal Customer,44,Business travel,Business,2497,2,2,2,2,5,4,5,4,4,5,4,4,4,3,0,0.0,satisfied +13731,5817,Female,Loyal Customer,65,Personal Travel,Eco,157,2,1,2,3,4,3,2,2,2,2,2,2,2,2,0,7.0,neutral or dissatisfied +13732,87804,Male,Loyal Customer,57,Business travel,Business,1851,2,2,2,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +13733,111440,Female,Loyal Customer,44,Business travel,Business,2181,4,4,5,4,2,5,5,5,5,5,5,5,5,4,43,23.0,satisfied +13734,88621,Male,Loyal Customer,67,Personal Travel,Eco,581,2,5,2,1,1,2,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +13735,44846,Female,Loyal Customer,60,Personal Travel,Eco,760,2,5,2,2,5,4,5,4,4,2,4,4,4,3,61,56.0,neutral or dissatisfied +13736,101656,Male,disloyal Customer,29,Business travel,Business,2106,2,2,2,4,4,2,4,4,2,3,4,2,3,4,6,0.0,neutral or dissatisfied +13737,52713,Male,Loyal Customer,34,Personal Travel,Eco,1162,2,5,2,3,3,2,3,3,4,2,4,3,4,3,3,7.0,neutral or dissatisfied +13738,80967,Male,Loyal Customer,52,Business travel,Business,2992,3,3,3,3,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +13739,121537,Female,Loyal Customer,21,Business travel,Business,1095,5,5,5,5,4,5,4,4,3,4,5,5,5,4,9,0.0,satisfied +13740,20024,Male,disloyal Customer,23,Business travel,Eco,528,1,5,1,2,2,1,2,2,2,5,2,4,1,2,9,6.0,neutral or dissatisfied +13741,122028,Male,Loyal Customer,62,Business travel,Business,130,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +13742,98583,Female,Loyal Customer,29,Business travel,Business,992,5,5,5,5,5,5,5,5,4,2,4,4,5,5,4,1.0,satisfied +13743,83515,Female,Loyal Customer,69,Personal Travel,Eco,946,3,2,3,3,2,3,3,2,2,3,2,2,2,2,0,5.0,neutral or dissatisfied +13744,86104,Female,Loyal Customer,44,Business travel,Business,2812,2,2,2,2,3,4,4,5,5,5,5,4,5,4,0,30.0,satisfied +13745,2691,Male,Loyal Customer,38,Business travel,Business,562,3,3,3,3,2,1,2,3,3,2,3,2,3,2,44,36.0,neutral or dissatisfied +13746,14831,Male,Loyal Customer,51,Business travel,Business,917,2,4,2,2,2,3,3,4,4,5,4,3,4,5,0,0.0,satisfied +13747,108656,Female,Loyal Customer,55,Business travel,Eco,1747,2,4,4,4,5,2,3,2,2,2,2,4,2,1,112,124.0,neutral or dissatisfied +13748,24769,Female,Loyal Customer,57,Business travel,Eco,432,4,2,2,2,1,2,2,4,4,4,4,3,4,3,0,0.0,satisfied +13749,63699,Male,Loyal Customer,18,Personal Travel,Eco,853,3,1,3,2,1,3,1,1,1,3,2,2,2,1,0,0.0,neutral or dissatisfied +13750,119039,Female,Loyal Customer,56,Business travel,Business,2378,2,3,3,3,4,3,3,2,2,2,2,2,2,1,0,44.0,neutral or dissatisfied +13751,46553,Male,Loyal Customer,33,Business travel,Eco,196,0,0,0,3,5,0,5,5,4,4,4,2,4,5,6,0.0,satisfied +13752,119972,Female,Loyal Customer,22,Personal Travel,Eco,1009,3,2,3,4,4,3,2,4,3,4,4,3,3,4,0,0.0,neutral or dissatisfied +13753,111022,Male,disloyal Customer,21,Business travel,Eco,268,3,1,3,2,3,3,3,3,3,1,2,3,2,3,0,0.0,neutral or dissatisfied +13754,80527,Male,Loyal Customer,35,Personal Travel,Eco Plus,2381,3,4,3,4,1,3,1,1,3,3,3,4,5,1,5,0.0,neutral or dissatisfied +13755,108518,Female,Loyal Customer,58,Personal Travel,Eco,519,5,3,5,3,3,1,3,4,4,5,4,1,4,1,3,0.0,satisfied +13756,103490,Female,Loyal Customer,57,Personal Travel,Eco,440,3,5,4,3,1,2,2,1,1,4,1,2,1,2,0,0.0,neutral or dissatisfied +13757,4365,Male,Loyal Customer,45,Business travel,Business,1875,2,2,2,2,4,5,5,4,4,4,4,3,4,5,0,7.0,satisfied +13758,110215,Male,Loyal Customer,52,Personal Travel,Eco,1310,3,5,3,4,5,3,5,5,5,3,4,4,5,5,39,28.0,neutral or dissatisfied +13759,58288,Male,Loyal Customer,30,Personal Travel,Eco,413,4,4,4,2,4,4,4,4,4,2,4,3,4,4,0,0.0,neutral or dissatisfied +13760,107897,Male,Loyal Customer,41,Business travel,Business,2626,3,3,3,3,5,5,5,4,4,4,4,3,4,3,51,42.0,satisfied +13761,15538,Male,Loyal Customer,55,Business travel,Business,412,2,2,2,2,4,5,2,5,5,4,5,3,5,3,25,2.0,satisfied +13762,115821,Female,Loyal Customer,45,Business travel,Business,325,0,0,0,1,3,4,3,3,3,3,3,1,3,1,13,9.0,satisfied +13763,41241,Male,Loyal Customer,40,Business travel,Business,643,1,1,1,1,5,5,3,3,3,3,3,5,3,1,0,5.0,satisfied +13764,74131,Female,Loyal Customer,77,Business travel,Business,3405,3,5,5,5,4,4,3,3,3,4,3,4,3,1,0,4.0,neutral or dissatisfied +13765,35453,Male,Loyal Customer,43,Personal Travel,Eco,944,2,4,1,2,1,1,5,1,3,4,1,5,3,1,0,0.0,neutral or dissatisfied +13766,438,Female,Loyal Customer,63,Personal Travel,Business,282,3,4,4,2,5,5,3,1,1,4,1,5,1,1,0,0.0,neutral or dissatisfied +13767,34370,Male,Loyal Customer,37,Business travel,Eco Plus,541,1,5,5,5,1,1,1,1,2,5,3,1,4,1,11,9.0,neutral or dissatisfied +13768,43660,Male,Loyal Customer,25,Business travel,Business,700,2,2,2,2,2,2,2,2,3,5,3,1,3,2,71,61.0,neutral or dissatisfied +13769,95756,Male,Loyal Customer,64,Personal Travel,Eco,453,0,1,0,2,5,0,3,5,4,4,2,3,2,5,0,0.0,satisfied +13770,124411,Female,Loyal Customer,33,Business travel,Business,2406,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +13771,33254,Male,Loyal Customer,57,Business travel,Eco Plus,216,2,5,5,5,2,2,2,2,1,4,4,1,4,2,1,0.0,neutral or dissatisfied +13772,117458,Female,Loyal Customer,13,Personal Travel,Eco,1107,4,2,3,3,5,3,4,5,2,3,3,1,4,5,0,0.0,satisfied +13773,72700,Male,Loyal Customer,35,Personal Travel,Eco,1121,4,4,4,3,2,4,2,2,5,4,4,5,4,2,40,38.0,neutral or dissatisfied +13774,113613,Male,Loyal Customer,13,Personal Travel,Eco,386,3,3,1,2,5,1,5,5,4,5,4,5,1,5,0,0.0,neutral or dissatisfied +13775,43178,Female,Loyal Customer,53,Business travel,Eco,282,4,2,2,2,2,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +13776,66114,Male,Loyal Customer,41,Business travel,Business,2228,3,3,3,3,5,5,5,4,4,4,4,5,4,4,13,21.0,satisfied +13777,8512,Female,Loyal Customer,40,Business travel,Eco,862,3,5,5,5,3,3,3,3,4,3,3,2,3,3,52,54.0,neutral or dissatisfied +13778,90566,Male,disloyal Customer,10,Business travel,Eco,515,3,0,3,1,4,3,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +13779,5374,Female,Loyal Customer,59,Business travel,Eco,785,3,2,2,2,5,3,3,3,3,3,3,4,3,1,3,31.0,neutral or dissatisfied +13780,94775,Female,disloyal Customer,22,Business travel,Eco,323,2,3,3,3,2,3,2,2,1,2,4,3,3,2,20,20.0,neutral or dissatisfied +13781,124200,Female,Loyal Customer,43,Business travel,Business,2176,3,3,4,3,4,2,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +13782,102633,Female,Loyal Customer,45,Business travel,Business,2089,4,4,4,4,5,5,5,5,5,5,5,3,5,5,7,7.0,satisfied +13783,68366,Female,Loyal Customer,57,Business travel,Business,2072,5,5,5,5,4,3,5,5,5,5,5,3,5,4,0,1.0,satisfied +13784,86791,Male,disloyal Customer,26,Business travel,Business,484,4,4,4,4,4,4,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +13785,65017,Male,Loyal Customer,36,Business travel,Eco,190,5,5,5,5,5,4,5,5,2,5,3,3,4,5,11,13.0,neutral or dissatisfied +13786,3973,Female,Loyal Customer,53,Personal Travel,Eco Plus,764,4,4,4,3,2,4,5,3,3,4,3,5,3,5,11,26.0,neutral or dissatisfied +13787,41576,Male,Loyal Customer,64,Personal Travel,Eco,1464,3,4,4,1,3,4,3,3,4,4,4,5,4,3,0,0.0,neutral or dissatisfied +13788,88376,Female,Loyal Customer,30,Business travel,Business,366,1,2,4,4,1,1,1,1,1,1,3,2,4,1,0,0.0,neutral or dissatisfied +13789,23172,Female,Loyal Customer,26,Personal Travel,Eco,300,2,4,2,3,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +13790,75186,Female,Loyal Customer,58,Business travel,Business,1846,1,1,1,1,4,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +13791,112441,Male,Loyal Customer,29,Business travel,Business,3845,3,2,2,2,3,3,3,3,1,4,4,2,4,3,2,8.0,neutral or dissatisfied +13792,79869,Female,Loyal Customer,43,Business travel,Business,2548,4,5,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +13793,54026,Male,Loyal Customer,44,Personal Travel,Eco,1091,3,2,3,4,2,3,1,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +13794,24658,Female,Loyal Customer,34,Business travel,Eco,861,2,5,5,5,2,2,2,2,2,2,4,1,3,2,0,7.0,neutral or dissatisfied +13795,86768,Male,Loyal Customer,29,Business travel,Business,1566,1,1,4,1,3,4,3,3,5,4,5,5,5,3,0,0.0,satisfied +13796,10738,Female,disloyal Customer,38,Business travel,Eco,224,1,2,0,3,3,0,2,3,3,3,3,2,3,3,0,2.0,neutral or dissatisfied +13797,93000,Female,Loyal Customer,39,Personal Travel,Eco Plus,738,4,5,4,4,5,4,5,5,4,3,4,4,5,5,0,5.0,neutral or dissatisfied +13798,4087,Female,disloyal Customer,27,Business travel,Business,544,2,2,2,4,3,2,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +13799,66811,Female,disloyal Customer,49,Business travel,Business,731,2,1,1,2,1,2,1,1,3,5,5,4,4,1,51,40.0,neutral or dissatisfied +13800,101133,Female,disloyal Customer,48,Business travel,Business,1090,2,2,2,4,5,2,3,5,4,5,4,3,5,5,19,2.0,neutral or dissatisfied +13801,41324,Female,Loyal Customer,44,Personal Travel,Eco,802,3,5,2,4,4,5,3,4,4,2,3,4,4,3,2,3.0,neutral or dissatisfied +13802,87878,Male,disloyal Customer,33,Business travel,Business,214,4,4,4,4,4,4,4,4,4,2,3,4,3,4,39,30.0,neutral or dissatisfied +13803,12033,Female,Loyal Customer,36,Business travel,Eco,376,4,5,3,5,4,4,4,4,3,2,3,1,4,4,73,66.0,satisfied +13804,4923,Female,Loyal Customer,11,Personal Travel,Eco,1020,2,4,2,3,5,2,5,5,2,3,4,2,4,5,0,31.0,neutral or dissatisfied +13805,91975,Male,Loyal Customer,32,Business travel,Business,2586,3,3,3,3,5,5,5,5,4,4,3,3,5,5,19,19.0,satisfied +13806,37155,Male,Loyal Customer,62,Business travel,Business,789,4,5,5,5,1,3,3,4,4,4,4,2,4,1,51,48.0,neutral or dissatisfied +13807,111627,Male,Loyal Customer,42,Business travel,Business,3836,3,3,4,3,5,5,4,5,5,4,5,3,5,4,40,36.0,satisfied +13808,60077,Female,Loyal Customer,39,Business travel,Business,3316,4,4,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +13809,128497,Male,Loyal Customer,20,Personal Travel,Eco,304,1,5,1,2,2,1,2,2,5,2,5,5,4,2,73,60.0,neutral or dissatisfied +13810,93976,Female,disloyal Customer,26,Business travel,Business,1218,5,4,4,3,5,4,5,5,3,2,4,5,5,5,0,0.0,satisfied +13811,85146,Female,Loyal Customer,40,Business travel,Business,2063,1,0,0,3,4,4,4,1,1,0,1,3,1,2,0,0.0,neutral or dissatisfied +13812,73540,Male,Loyal Customer,25,Personal Travel,Eco,594,0,5,0,3,3,0,3,3,3,4,2,1,1,3,0,0.0,satisfied +13813,35575,Male,Loyal Customer,39,Business travel,Eco Plus,1074,5,4,4,4,5,5,5,5,5,4,5,3,3,5,0,0.0,satisfied +13814,87065,Male,Loyal Customer,45,Business travel,Business,1937,1,1,4,1,4,5,4,4,4,4,4,4,4,5,1,12.0,satisfied +13815,40315,Female,Loyal Customer,12,Personal Travel,Eco,387,2,4,2,4,4,2,4,4,3,3,5,5,5,4,0,1.0,neutral or dissatisfied +13816,32003,Female,Loyal Customer,42,Personal Travel,Business,101,3,4,3,2,5,3,5,4,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +13817,94351,Female,Loyal Customer,41,Business travel,Business,1657,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +13818,75550,Male,disloyal Customer,26,Business travel,Business,337,5,4,5,3,2,5,2,2,4,3,4,3,4,2,0,0.0,satisfied +13819,108331,Female,Loyal Customer,41,Business travel,Business,1728,5,5,5,5,2,5,4,3,3,2,3,5,3,5,3,0.0,satisfied +13820,127063,Male,Loyal Customer,44,Business travel,Business,2027,3,3,3,3,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +13821,98657,Female,Loyal Customer,54,Personal Travel,Eco,861,4,4,4,3,3,4,5,5,5,4,5,3,5,3,12,54.0,neutral or dissatisfied +13822,78810,Female,Loyal Customer,27,Personal Travel,Eco,447,2,3,2,2,4,2,4,4,1,4,2,4,3,4,0,0.0,neutral or dissatisfied +13823,111569,Male,Loyal Customer,29,Business travel,Business,775,2,1,1,1,2,2,2,2,3,5,3,4,3,2,6,16.0,neutral or dissatisfied +13824,111165,Female,Loyal Customer,59,Business travel,Business,1111,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +13825,109690,Female,Loyal Customer,42,Personal Travel,Eco,802,3,5,3,3,2,5,4,4,4,3,4,2,4,2,12,4.0,neutral or dissatisfied +13826,20199,Male,Loyal Customer,49,Business travel,Eco Plus,334,4,1,1,1,4,4,4,4,1,1,4,4,3,4,0,0.0,neutral or dissatisfied +13827,49303,Male,disloyal Customer,27,Business travel,Eco,308,2,5,2,4,3,2,3,3,5,4,5,1,3,3,11,19.0,neutral or dissatisfied +13828,110222,Female,Loyal Customer,48,Business travel,Business,1011,2,2,3,2,2,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +13829,1565,Male,Loyal Customer,60,Business travel,Business,2853,3,3,3,3,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +13830,30545,Female,Loyal Customer,21,Business travel,Business,2549,5,5,5,5,3,4,3,3,4,2,2,2,1,3,0,11.0,satisfied +13831,30309,Male,Loyal Customer,39,Personal Travel,Eco,1476,4,3,3,1,2,3,1,2,4,2,3,1,5,2,0,2.0,neutral or dissatisfied +13832,126954,Female,Loyal Customer,43,Business travel,Business,3840,3,3,3,3,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +13833,1162,Female,Loyal Customer,12,Personal Travel,Eco,113,4,3,4,1,2,4,2,2,1,1,1,2,4,2,0,0.0,neutral or dissatisfied +13834,70089,Male,Loyal Customer,23,Business travel,Business,2162,3,3,3,3,4,5,4,4,3,4,5,4,4,4,20,16.0,satisfied +13835,8712,Male,Loyal Customer,54,Personal Travel,Eco,181,3,4,0,1,3,0,2,3,5,5,2,2,1,3,0,0.0,neutral or dissatisfied +13836,102187,Male,Loyal Customer,37,Business travel,Business,1763,5,5,5,5,3,4,4,5,5,5,5,4,5,3,21,4.0,satisfied +13837,58095,Female,Loyal Customer,15,Business travel,Business,2581,2,1,1,1,2,2,2,2,4,4,4,4,4,2,17,10.0,neutral or dissatisfied +13838,31131,Male,Loyal Customer,61,Business travel,Eco,991,2,4,4,4,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +13839,81149,Male,Loyal Customer,70,Personal Travel,Eco,1310,2,4,2,3,2,2,2,2,3,4,3,1,2,2,0,0.0,neutral or dissatisfied +13840,119319,Male,Loyal Customer,51,Personal Travel,Eco,214,3,0,3,1,1,3,1,1,5,4,4,5,4,1,0,0.0,neutral or dissatisfied +13841,75267,Male,Loyal Customer,41,Personal Travel,Eco,1744,2,2,3,3,2,3,2,2,3,3,3,2,2,2,8,2.0,neutral or dissatisfied +13842,66034,Male,Loyal Customer,51,Business travel,Business,3069,5,5,5,5,3,5,5,5,5,5,5,5,5,5,48,79.0,satisfied +13843,49162,Male,disloyal Customer,25,Business travel,Eco,373,4,0,4,1,5,4,2,5,1,1,5,2,3,5,0,0.0,neutral or dissatisfied +13844,100011,Male,disloyal Customer,49,Business travel,Business,281,4,4,4,3,5,4,5,5,5,3,4,3,4,5,21,11.0,satisfied +13845,19551,Male,disloyal Customer,40,Business travel,Eco,160,4,4,4,3,5,4,5,5,2,3,2,3,4,5,0,1.0,neutral or dissatisfied +13846,71168,Male,Loyal Customer,45,Business travel,Business,2926,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +13847,719,Female,disloyal Customer,27,Business travel,Business,158,2,2,2,3,1,2,1,1,2,1,3,1,4,1,0,10.0,neutral or dissatisfied +13848,25894,Female,Loyal Customer,70,Personal Travel,Eco,907,3,4,3,3,2,4,4,5,5,3,5,3,5,3,31,44.0,neutral or dissatisfied +13849,4225,Female,Loyal Customer,23,Business travel,Eco Plus,488,3,5,5,5,3,3,2,3,2,5,3,2,4,3,0,20.0,neutral or dissatisfied +13850,87344,Female,Loyal Customer,46,Business travel,Business,3957,3,3,3,3,4,5,4,4,4,4,4,5,4,5,18,16.0,satisfied +13851,111719,Female,Loyal Customer,49,Personal Travel,Eco,495,2,4,2,4,5,5,5,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +13852,102143,Male,Loyal Customer,46,Business travel,Business,3034,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +13853,110264,Male,Loyal Customer,41,Business travel,Business,883,5,5,1,5,4,5,5,4,4,4,4,5,4,4,10,13.0,satisfied +13854,127194,Female,Loyal Customer,42,Business travel,Business,3919,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +13855,100876,Female,Loyal Customer,28,Business travel,Business,2133,3,3,3,3,4,5,4,4,4,3,4,4,4,4,58,38.0,satisfied +13856,69782,Female,Loyal Customer,20,Business travel,Business,1055,3,3,3,3,4,4,4,4,5,3,4,4,4,4,2,0.0,satisfied +13857,103910,Male,Loyal Customer,54,Personal Travel,Business,533,5,4,5,4,4,4,5,1,1,5,1,4,1,3,0,0.0,satisfied +13858,41211,Female,Loyal Customer,69,Business travel,Business,1556,3,5,1,5,5,2,3,3,3,3,3,1,3,3,6,0.0,neutral or dissatisfied +13859,87398,Male,disloyal Customer,27,Business travel,Eco,425,3,2,3,3,1,3,5,1,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +13860,18802,Male,Loyal Customer,47,Business travel,Eco,448,4,2,2,2,4,4,4,4,3,4,1,5,3,4,43,46.0,satisfied +13861,90727,Female,Loyal Customer,47,Business travel,Business,404,1,1,1,1,3,5,4,5,5,5,5,3,5,4,0,7.0,satisfied +13862,73458,Female,Loyal Customer,40,Personal Travel,Eco,1005,4,4,4,1,4,4,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +13863,15725,Female,Loyal Customer,62,Business travel,Eco,424,4,2,2,2,3,3,4,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +13864,111856,Male,Loyal Customer,55,Business travel,Business,628,2,2,2,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +13865,62447,Male,Loyal Customer,57,Business travel,Business,1744,2,2,2,2,4,4,4,5,5,4,5,3,5,5,54,55.0,satisfied +13866,87571,Female,Loyal Customer,29,Business travel,Business,2855,2,1,1,1,2,2,2,2,2,3,2,3,2,2,0,0.0,neutral or dissatisfied +13867,16020,Male,Loyal Customer,46,Personal Travel,Eco,780,2,4,2,4,5,2,4,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +13868,43336,Male,Loyal Customer,28,Business travel,Business,2537,3,4,4,4,3,3,3,3,3,3,3,1,4,3,0,0.0,neutral or dissatisfied +13869,66294,Male,Loyal Customer,59,Business travel,Business,852,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,14.0,satisfied +13870,123700,Male,Loyal Customer,35,Personal Travel,Eco,214,3,2,0,2,3,0,3,3,2,3,1,1,2,3,0,0.0,neutral or dissatisfied +13871,100400,Male,Loyal Customer,52,Business travel,Business,2430,1,2,1,1,5,4,5,5,5,5,5,4,5,5,13,3.0,satisfied +13872,8177,Male,Loyal Customer,49,Business travel,Eco,125,2,4,4,4,2,2,2,2,1,4,3,2,4,2,0,0.0,neutral or dissatisfied +13873,80512,Male,Loyal Customer,36,Personal Travel,Eco,1749,2,4,2,4,5,2,3,5,2,2,4,1,3,5,23,41.0,neutral or dissatisfied +13874,62953,Male,Loyal Customer,39,Business travel,Business,862,2,3,2,2,3,5,4,4,4,4,4,4,4,3,10,0.0,satisfied +13875,82482,Female,Loyal Customer,40,Business travel,Business,502,5,5,5,5,3,5,5,5,5,5,5,3,5,5,1,0.0,satisfied +13876,8107,Female,Loyal Customer,29,Business travel,Business,402,3,3,3,3,5,5,5,5,4,3,4,4,4,5,0,0.0,satisfied +13877,36511,Female,disloyal Customer,31,Business travel,Eco,1211,2,2,2,3,2,2,2,2,1,1,2,2,3,2,0,0.0,neutral or dissatisfied +13878,117383,Male,Loyal Customer,13,Personal Travel,Eco Plus,1294,4,2,4,2,4,4,4,4,1,2,2,2,3,4,0,0.0,neutral or dissatisfied +13879,39258,Female,Loyal Customer,52,Business travel,Business,2896,4,1,1,1,4,4,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +13880,97005,Female,Loyal Customer,7,Personal Travel,Eco,883,4,4,4,4,1,4,1,1,2,5,4,4,4,1,1,3.0,neutral or dissatisfied +13881,44028,Male,Loyal Customer,29,Business travel,Business,2184,3,5,3,3,5,5,5,5,5,4,2,4,4,5,4,0.0,satisfied +13882,48780,Male,Loyal Customer,18,Business travel,Business,3932,4,3,4,4,3,3,4,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +13883,88703,Female,Loyal Customer,64,Personal Travel,Eco,581,1,5,2,2,4,4,4,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +13884,70645,Male,Loyal Customer,21,Business travel,Business,946,1,1,1,1,5,5,5,5,5,4,4,5,5,5,3,0.0,satisfied +13885,35569,Female,Loyal Customer,33,Business travel,Eco Plus,1028,4,3,3,3,4,4,4,4,2,5,5,5,1,4,12,76.0,satisfied +13886,9502,Female,Loyal Customer,20,Personal Travel,Eco,239,5,4,0,3,2,0,2,2,5,5,5,5,4,2,3,0.0,satisfied +13887,22123,Female,Loyal Customer,38,Personal Travel,Eco,743,1,4,1,4,2,1,5,2,3,4,4,3,5,2,46,47.0,neutral or dissatisfied +13888,17237,Female,disloyal Customer,57,Business travel,Eco,872,3,3,3,3,4,3,5,4,1,1,3,1,2,4,0,0.0,neutral or dissatisfied +13889,57256,Female,disloyal Customer,28,Business travel,Eco,804,4,4,4,3,4,4,1,4,3,2,4,1,3,4,0,0.0,neutral or dissatisfied +13890,23261,Male,Loyal Customer,38,Business travel,Eco Plus,1050,3,3,4,3,3,4,3,3,1,5,1,5,5,3,0,0.0,satisfied +13891,35,Male,Loyal Customer,39,Business travel,Business,1672,2,2,2,2,5,4,5,3,3,4,5,5,3,5,23,17.0,satisfied +13892,36335,Female,Loyal Customer,25,Personal Travel,Eco,187,2,4,2,3,3,2,3,3,4,4,5,4,3,3,0,17.0,neutral or dissatisfied +13893,104805,Female,Loyal Customer,56,Personal Travel,Eco,587,2,5,2,2,3,4,5,2,2,2,2,3,2,4,6,0.0,neutral or dissatisfied +13894,6838,Male,Loyal Customer,69,Personal Travel,Eco,223,3,5,0,3,3,0,2,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +13895,126607,Female,Loyal Customer,41,Business travel,Business,937,2,4,4,4,1,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +13896,112090,Female,disloyal Customer,25,Business travel,Business,1062,3,0,2,1,5,2,5,5,5,3,5,5,4,5,40,25.0,neutral or dissatisfied +13897,111652,Male,Loyal Customer,25,Business travel,Eco Plus,1558,3,4,4,4,3,3,2,3,2,1,4,1,4,3,8,0.0,neutral or dissatisfied +13898,53407,Male,Loyal Customer,22,Personal Travel,Business,2358,3,5,4,3,4,3,3,3,4,5,5,3,3,3,0,0.0,neutral or dissatisfied +13899,7903,Male,Loyal Customer,60,Business travel,Eco,1020,2,1,1,1,2,2,2,2,3,5,2,3,3,2,3,0.0,neutral or dissatisfied +13900,32051,Male,Loyal Customer,42,Business travel,Eco,101,4,3,3,3,4,4,4,4,2,1,2,2,5,4,0,0.0,satisfied +13901,124611,Female,disloyal Customer,34,Business travel,Business,1671,1,1,1,5,4,1,4,4,4,4,4,3,5,4,0,34.0,neutral or dissatisfied +13902,85471,Male,Loyal Customer,27,Business travel,Business,214,3,5,5,5,2,2,3,2,1,5,3,1,3,2,17,13.0,neutral or dissatisfied +13903,67937,Female,Loyal Customer,43,Personal Travel,Eco,1205,2,4,2,3,3,4,4,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +13904,44783,Male,disloyal Customer,13,Business travel,Eco,1250,3,3,3,4,2,3,2,2,4,3,4,4,3,2,0,0.0,neutral or dissatisfied +13905,51723,Female,Loyal Customer,13,Personal Travel,Eco,425,1,0,1,4,2,1,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +13906,44343,Female,Loyal Customer,39,Business travel,Eco Plus,230,4,1,1,1,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +13907,94862,Male,disloyal Customer,37,Business travel,Eco,239,3,1,3,3,1,3,1,1,4,4,4,3,3,1,29,24.0,neutral or dissatisfied +13908,104054,Male,Loyal Customer,57,Personal Travel,Eco,1262,2,4,1,5,1,1,1,1,3,3,5,5,4,1,8,8.0,neutral or dissatisfied +13909,74626,Female,disloyal Customer,26,Business travel,Eco,1064,3,3,3,4,3,3,3,3,1,1,4,2,4,3,0,0.0,neutral or dissatisfied +13910,127204,Female,disloyal Customer,23,Business travel,Eco Plus,221,0,0,0,4,5,0,5,5,1,1,5,5,3,5,6,0.0,satisfied +13911,66422,Male,Loyal Customer,66,Personal Travel,Eco,1562,3,3,3,4,4,3,4,4,4,1,3,2,3,4,63,48.0,neutral or dissatisfied +13912,20106,Female,Loyal Customer,31,Business travel,Eco,416,4,4,4,4,4,4,4,4,3,5,3,3,2,4,7,0.0,satisfied +13913,47904,Male,Loyal Customer,31,Business travel,Business,1992,1,2,2,2,1,1,1,1,4,3,3,3,3,1,61,88.0,neutral or dissatisfied +13914,40100,Male,disloyal Customer,24,Business travel,Eco,422,1,3,1,2,3,1,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +13915,35890,Female,Loyal Customer,59,Personal Travel,Eco,1023,1,5,1,3,4,4,4,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +13916,41476,Male,disloyal Customer,24,Business travel,Eco,1235,1,1,1,3,4,1,4,4,4,2,3,3,1,4,42,59.0,neutral or dissatisfied +13917,27079,Female,Loyal Customer,36,Business travel,Business,2496,4,4,4,4,1,3,4,5,5,5,5,5,5,4,7,0.0,satisfied +13918,123720,Male,Loyal Customer,48,Business travel,Business,214,4,4,5,4,4,5,4,3,3,4,5,5,3,5,0,0.0,satisfied +13919,37442,Female,Loyal Customer,40,Business travel,Business,1028,4,4,4,4,2,1,2,5,5,5,5,2,5,5,1,0.0,satisfied +13920,104891,Female,Loyal Customer,7,Personal Travel,Eco Plus,327,2,1,2,4,2,2,2,2,1,5,3,3,4,2,0,0.0,neutral or dissatisfied +13921,8596,Female,Loyal Customer,35,Business travel,Business,109,1,1,1,1,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +13922,65507,Female,Loyal Customer,26,Personal Travel,Eco Plus,1303,3,4,3,2,2,3,2,2,4,4,3,4,4,2,30,26.0,neutral or dissatisfied +13923,93775,Male,disloyal Customer,35,Business travel,Business,1865,1,0,0,2,5,0,5,5,3,5,2,3,3,5,4,6.0,neutral or dissatisfied +13924,20662,Male,Loyal Customer,48,Business travel,Eco,552,5,3,2,2,5,5,5,5,3,5,5,4,1,5,0,2.0,satisfied +13925,123079,Female,Loyal Customer,48,Business travel,Business,547,4,4,4,4,5,5,4,4,4,4,4,4,4,3,18,45.0,satisfied +13926,118264,Female,Loyal Customer,49,Business travel,Business,1972,1,1,1,1,3,4,4,4,4,4,4,3,4,3,6,0.0,satisfied +13927,46254,Male,Loyal Customer,14,Personal Travel,Eco,679,3,4,3,5,1,3,1,1,4,4,5,4,5,1,0,1.0,neutral or dissatisfied +13928,91212,Male,Loyal Customer,31,Personal Travel,Eco,271,3,0,3,3,5,3,5,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +13929,8605,Male,Loyal Customer,39,Personal Travel,Eco Plus,109,4,4,4,2,4,4,4,4,4,5,4,3,4,4,0,8.0,neutral or dissatisfied +13930,117308,Male,Loyal Customer,44,Business travel,Eco Plus,221,4,3,3,3,4,4,4,4,4,2,3,1,5,4,15,5.0,satisfied +13931,38847,Female,disloyal Customer,39,Business travel,Eco Plus,354,1,1,1,4,4,1,4,4,4,5,3,1,3,4,3,16.0,neutral or dissatisfied +13932,16825,Male,Loyal Customer,60,Personal Travel,Eco,645,3,4,3,4,1,3,1,1,1,2,4,2,4,1,0,6.0,neutral or dissatisfied +13933,103628,Male,disloyal Customer,26,Business travel,Business,251,3,4,3,3,4,3,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +13934,61152,Female,Loyal Customer,48,Business travel,Business,862,2,2,2,2,5,5,4,4,4,4,4,5,4,4,40,15.0,satisfied +13935,56098,Male,disloyal Customer,29,Business travel,Business,946,5,5,5,4,5,1,1,4,2,4,4,1,5,1,158,150.0,satisfied +13936,36056,Male,disloyal Customer,21,Business travel,Eco,399,0,0,0,1,4,0,4,4,2,3,5,5,1,4,0,0.0,satisfied +13937,82400,Male,disloyal Customer,25,Business travel,Business,500,4,4,4,4,1,4,1,1,3,3,4,3,5,1,0,0.0,satisfied +13938,6880,Male,Loyal Customer,45,Business travel,Business,1906,5,3,5,5,2,4,4,5,5,5,5,5,5,5,101,92.0,satisfied +13939,109866,Female,Loyal Customer,40,Business travel,Eco,1053,3,2,2,2,3,3,3,3,1,5,3,3,4,3,16,0.0,neutral or dissatisfied +13940,124336,Female,Loyal Customer,42,Business travel,Eco,1037,3,5,1,5,1,2,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +13941,109297,Male,disloyal Customer,24,Business travel,Eco,1136,5,5,5,5,5,5,1,5,5,3,5,3,4,5,0,0.0,satisfied +13942,77902,Female,Loyal Customer,43,Business travel,Business,2113,2,2,2,2,2,2,3,5,5,5,5,4,5,4,0,0.0,satisfied +13943,21590,Female,disloyal Customer,27,Business travel,Eco,780,4,4,4,3,3,4,4,3,5,1,2,2,5,3,0,0.0,neutral or dissatisfied +13944,58430,Male,Loyal Customer,47,Business travel,Business,3711,2,2,2,2,1,5,2,4,4,4,4,3,4,3,0,0.0,satisfied +13945,40949,Female,Loyal Customer,69,Personal Travel,Eco Plus,584,3,5,2,4,3,5,4,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +13946,115103,Female,Loyal Customer,57,Business travel,Business,3262,4,4,4,4,2,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +13947,101403,Female,Loyal Customer,25,Personal Travel,Eco,486,2,3,2,3,5,2,5,5,3,4,2,3,3,5,39,34.0,neutral or dissatisfied +13948,19287,Female,Loyal Customer,42,Business travel,Business,299,3,2,2,2,5,3,4,3,3,4,3,4,3,2,52,51.0,neutral or dissatisfied +13949,80990,Male,Loyal Customer,53,Business travel,Business,2379,1,1,1,1,4,1,2,5,5,4,5,4,5,3,64,53.0,satisfied +13950,27913,Male,Loyal Customer,24,Personal Travel,Business,689,3,1,3,2,5,3,5,5,4,5,1,1,1,5,0,7.0,neutral or dissatisfied +13951,44017,Male,Loyal Customer,26,Personal Travel,Eco,397,2,4,2,2,3,2,5,3,5,4,4,3,5,3,0,0.0,neutral or dissatisfied +13952,34980,Male,Loyal Customer,58,Business travel,Business,2622,3,2,2,2,1,3,4,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +13953,75133,Male,disloyal Customer,35,Business travel,Business,1726,3,4,4,3,1,4,1,1,4,3,4,3,4,1,0,19.0,neutral or dissatisfied +13954,52652,Female,Loyal Customer,33,Personal Travel,Eco,110,1,1,1,2,5,1,3,5,2,1,2,1,3,5,0,0.0,neutral or dissatisfied +13955,106118,Male,Loyal Customer,37,Business travel,Business,2989,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +13956,74986,Female,Loyal Customer,53,Business travel,Business,2586,5,5,5,5,4,3,5,4,4,4,4,4,4,5,13,21.0,satisfied +13957,15988,Female,Loyal Customer,44,Business travel,Eco,780,4,4,4,4,2,3,4,4,4,4,4,1,4,2,23,36.0,satisfied +13958,89678,Female,Loyal Customer,64,Business travel,Business,3849,4,3,3,3,3,3,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +13959,30217,Male,Loyal Customer,17,Personal Travel,Eco Plus,183,2,4,2,3,3,2,3,3,3,2,4,4,4,3,10,9.0,neutral or dissatisfied +13960,16977,Male,Loyal Customer,52,Business travel,Eco Plus,209,5,5,5,5,5,5,5,5,1,1,1,2,5,5,0,2.0,satisfied +13961,129612,Female,disloyal Customer,24,Business travel,Eco,447,3,4,3,4,5,3,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +13962,28820,Female,Loyal Customer,42,Business travel,Business,1842,4,4,4,4,4,3,3,3,3,3,3,4,3,5,10,0.0,satisfied +13963,6686,Female,Loyal Customer,48,Business travel,Business,3589,5,5,5,5,4,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +13964,124708,Female,Loyal Customer,61,Personal Travel,Eco,399,2,4,2,1,4,5,5,5,5,2,5,3,5,5,5,0.0,neutral or dissatisfied +13965,39143,Female,Loyal Customer,64,Personal Travel,Eco,119,2,4,2,3,4,4,4,5,5,2,5,4,5,4,24,18.0,neutral or dissatisfied +13966,103380,Female,Loyal Customer,46,Business travel,Business,237,5,2,5,5,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +13967,90272,Female,Loyal Customer,31,Business travel,Business,3785,4,4,4,4,4,4,4,4,4,2,5,4,5,4,84,,satisfied +13968,73278,Female,Loyal Customer,65,Personal Travel,Business,1120,4,2,4,3,4,3,4,4,4,4,1,1,4,4,94,90.0,neutral or dissatisfied +13969,58749,Female,disloyal Customer,52,Business travel,Business,864,5,5,5,2,2,5,2,2,4,4,4,3,5,2,0,0.0,satisfied +13970,70563,Male,Loyal Customer,61,Business travel,Eco,858,2,4,5,5,2,2,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +13971,123918,Male,Loyal Customer,23,Personal Travel,Eco,603,1,5,1,1,2,1,2,2,5,2,5,5,4,2,0,5.0,neutral or dissatisfied +13972,59419,Male,Loyal Customer,62,Personal Travel,Eco,2556,2,5,2,3,4,2,5,4,3,4,4,3,4,4,1,0.0,neutral or dissatisfied +13973,116160,Male,Loyal Customer,58,Personal Travel,Eco,325,2,3,2,4,5,2,5,5,4,4,4,2,4,5,0,0.0,neutral or dissatisfied +13974,112758,Female,Loyal Customer,38,Business travel,Business,588,2,2,2,2,2,5,4,4,4,5,4,3,4,5,66,58.0,satisfied +13975,93543,Female,Loyal Customer,24,Business travel,Business,2872,2,2,2,2,4,4,4,4,5,3,5,4,4,4,0,0.0,satisfied +13976,80696,Female,Loyal Customer,29,Business travel,Business,874,3,3,2,3,4,4,4,4,5,2,5,4,4,4,1,0.0,satisfied +13977,102192,Male,Loyal Customer,41,Business travel,Business,1953,2,2,2,2,2,5,4,2,2,3,2,5,2,4,0,0.0,satisfied +13978,92288,Male,Loyal Customer,41,Business travel,Business,1814,3,3,3,3,3,3,4,3,3,3,3,3,3,5,63,34.0,satisfied +13979,37983,Male,Loyal Customer,65,Personal Travel,Business,1185,3,1,2,3,3,4,4,2,2,2,2,4,2,4,46,44.0,neutral or dissatisfied +13980,69437,Male,Loyal Customer,18,Personal Travel,Eco,1096,1,3,1,1,2,1,2,2,1,4,2,4,4,2,0,5.0,neutral or dissatisfied +13981,40852,Female,Loyal Customer,35,Personal Travel,Eco,584,3,5,3,2,1,3,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +13982,49057,Female,Loyal Customer,41,Business travel,Eco,278,5,1,1,1,5,5,5,5,2,2,4,5,2,5,0,0.0,satisfied +13983,74592,Female,Loyal Customer,51,Business travel,Eco,1464,2,1,1,1,2,4,4,2,2,2,2,4,2,3,2,0.0,neutral or dissatisfied +13984,55644,Male,Loyal Customer,49,Personal Travel,Business,315,4,2,4,3,1,3,4,1,1,4,1,2,1,1,1,0.0,neutral or dissatisfied +13985,126679,Male,disloyal Customer,23,Business travel,Eco,902,3,3,3,5,1,3,1,1,5,2,4,5,5,1,4,0.0,neutral or dissatisfied +13986,60928,Male,disloyal Customer,54,Business travel,Business,888,3,3,3,2,1,3,3,1,4,3,5,4,5,1,0,15.0,neutral or dissatisfied +13987,45281,Male,Loyal Customer,39,Business travel,Business,222,4,4,4,4,4,4,4,5,5,5,5,1,5,1,0,0.0,satisfied +13988,85278,Female,Loyal Customer,67,Personal Travel,Eco,731,2,1,2,2,3,2,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +13989,47056,Male,Loyal Customer,43,Business travel,Eco,639,3,2,2,2,3,3,3,3,2,2,3,2,3,3,46,28.0,neutral or dissatisfied +13990,46875,Female,Loyal Customer,22,Business travel,Business,1634,2,2,2,2,5,5,5,5,2,3,5,1,2,5,0,0.0,satisfied +13991,115968,Female,Loyal Customer,20,Personal Travel,Eco,446,3,5,3,1,1,3,2,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +13992,41089,Female,Loyal Customer,48,Business travel,Business,1778,2,2,2,2,4,4,3,5,5,4,4,2,5,5,16,8.0,satisfied +13993,55653,Male,Loyal Customer,49,Business travel,Business,2492,0,0,0,3,5,5,4,2,2,1,1,3,2,5,10,12.0,satisfied +13994,54338,Male,Loyal Customer,27,Personal Travel,Eco,1597,2,4,3,3,2,3,3,2,4,2,5,3,4,2,19,12.0,neutral or dissatisfied +13995,40093,Male,Loyal Customer,37,Business travel,Eco,200,5,4,4,4,5,5,5,5,2,1,1,4,3,5,0,0.0,satisfied +13996,30371,Female,disloyal Customer,17,Business travel,Eco,862,2,2,2,3,4,2,4,4,4,5,3,4,4,4,14,23.0,neutral or dissatisfied +13997,95109,Male,Loyal Customer,68,Personal Travel,Eco,239,3,4,3,1,5,3,5,5,4,4,4,5,5,5,4,0.0,neutral or dissatisfied +13998,114232,Female,Loyal Customer,54,Business travel,Business,862,5,5,5,5,3,4,5,4,4,4,4,4,4,4,3,0.0,satisfied +13999,123029,Female,Loyal Customer,30,Business travel,Business,1848,2,2,2,2,4,4,4,4,5,5,5,5,5,4,7,3.0,satisfied +14000,108355,Male,Loyal Customer,34,Business travel,Business,1728,3,3,3,3,3,3,3,3,4,4,3,3,4,3,305,301.0,neutral or dissatisfied +14001,100579,Female,disloyal Customer,29,Business travel,Eco,486,1,3,1,3,3,1,3,3,3,1,2,2,2,3,0,10.0,neutral or dissatisfied +14002,24831,Male,disloyal Customer,28,Business travel,Eco,861,2,2,2,4,3,2,3,3,2,2,2,2,1,3,0,0.0,neutral or dissatisfied +14003,53278,Male,disloyal Customer,24,Business travel,Eco,758,5,5,5,2,5,5,5,5,4,4,5,4,3,5,32,28.0,satisfied +14004,123965,Female,Loyal Customer,44,Business travel,Business,184,5,5,5,5,2,4,5,4,4,5,5,3,4,5,0,0.0,satisfied +14005,58631,Female,Loyal Customer,25,Business travel,Business,3684,5,5,5,5,3,3,3,3,3,4,5,5,5,3,0,0.0,satisfied +14006,112768,Male,Loyal Customer,12,Business travel,Business,3386,2,3,4,4,2,3,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +14007,67270,Female,Loyal Customer,7,Personal Travel,Eco,1119,3,5,3,2,3,3,3,3,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +14008,19575,Female,Loyal Customer,63,Business travel,Eco,160,4,4,4,4,3,1,3,4,4,4,4,3,4,2,47,67.0,satisfied +14009,88487,Male,Loyal Customer,61,Business travel,Business,3475,2,2,2,2,2,1,3,5,5,5,5,4,5,2,8,3.0,satisfied +14010,80374,Female,disloyal Customer,23,Business travel,Eco,368,2,4,1,2,5,1,3,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +14011,3399,Male,Loyal Customer,53,Business travel,Business,296,1,1,1,1,4,1,5,4,4,4,4,2,4,3,0,0.0,satisfied +14012,99181,Female,Loyal Customer,37,Business travel,Business,462,2,5,5,5,2,4,3,2,2,2,2,4,2,4,10,7.0,neutral or dissatisfied +14013,82023,Male,Loyal Customer,70,Personal Travel,Eco,1517,2,4,2,5,2,2,2,2,2,4,2,5,4,2,3,0.0,neutral or dissatisfied +14014,82321,Female,Loyal Customer,39,Business travel,Business,2396,3,3,3,3,3,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +14015,87763,Female,Loyal Customer,45,Business travel,Business,214,5,5,5,5,3,4,5,4,4,4,5,5,4,3,0,0.0,satisfied +14016,45832,Male,Loyal Customer,50,Personal Travel,Eco,391,4,1,4,4,4,4,4,4,3,4,3,2,3,4,19,16.0,neutral or dissatisfied +14017,30931,Female,Loyal Customer,41,Business travel,Business,1819,4,4,4,4,5,5,5,4,5,5,3,5,2,5,116,161.0,satisfied +14018,94690,Female,disloyal Customer,40,Business travel,Business,273,1,1,1,4,1,1,1,1,2,3,4,1,3,1,0,0.0,neutral or dissatisfied +14019,54702,Female,Loyal Customer,38,Business travel,Business,387,5,5,4,5,1,5,2,4,4,4,4,4,4,2,4,0.0,satisfied +14020,115412,Male,Loyal Customer,67,Business travel,Eco,362,4,3,3,3,4,4,4,4,3,4,2,2,3,4,0,0.0,neutral or dissatisfied +14021,8619,Male,Loyal Customer,58,Business travel,Business,1863,0,0,0,4,2,5,5,5,5,5,5,4,5,4,9,12.0,satisfied +14022,42718,Male,disloyal Customer,48,Business travel,Eco,912,1,1,1,1,2,1,2,2,4,5,3,2,3,2,0,2.0,neutral or dissatisfied +14023,27376,Female,Loyal Customer,52,Business travel,Business,697,4,4,5,4,1,2,4,3,3,3,3,4,3,1,0,0.0,satisfied +14024,101525,Female,Loyal Customer,66,Personal Travel,Eco,345,3,4,3,5,2,5,4,2,2,3,3,3,2,3,8,0.0,neutral or dissatisfied +14025,68091,Female,Loyal Customer,34,Business travel,Business,3624,2,3,3,3,4,3,3,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +14026,26970,Male,Loyal Customer,49,Business travel,Eco,867,5,5,2,2,5,5,5,5,1,5,3,1,5,5,2,0.0,satisfied +14027,55,Male,Loyal Customer,36,Business travel,Business,3655,1,1,1,1,1,3,3,3,3,3,1,4,3,2,40,71.0,neutral or dissatisfied +14028,1659,Female,Loyal Customer,38,Business travel,Business,151,1,1,1,1,2,3,1,5,5,5,5,2,5,3,0,4.0,satisfied +14029,89657,Female,Loyal Customer,48,Business travel,Business,1089,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +14030,37943,Male,disloyal Customer,31,Business travel,Business,1065,3,3,3,3,5,3,5,5,3,3,3,1,3,5,0,0.0,neutral or dissatisfied +14031,22753,Male,Loyal Customer,62,Business travel,Eco,147,5,2,3,2,5,5,5,5,1,5,2,3,3,5,0,0.0,satisfied +14032,127052,Female,disloyal Customer,26,Business travel,Eco,338,3,1,3,4,3,3,3,3,4,4,3,4,3,3,0,4.0,neutral or dissatisfied +14033,89366,Female,Loyal Customer,24,Personal Travel,Eco,1587,4,4,4,3,2,4,2,2,5,2,4,4,4,2,0,1.0,neutral or dissatisfied +14034,61081,Female,Loyal Customer,16,Business travel,Eco,1506,3,3,3,3,3,3,2,3,2,1,3,4,3,3,2,6.0,neutral or dissatisfied +14035,41382,Male,Loyal Customer,50,Business travel,Eco,927,5,4,4,4,4,5,4,4,1,2,3,2,2,4,12,28.0,satisfied +14036,3812,Male,Loyal Customer,54,Business travel,Business,2560,1,1,2,1,3,5,5,3,3,2,3,3,3,3,20,2.0,satisfied +14037,79157,Female,Loyal Customer,49,Business travel,Eco,2239,1,3,3,3,1,4,4,1,1,1,1,2,1,1,8,0.0,neutral or dissatisfied +14038,82060,Male,Loyal Customer,47,Business travel,Business,1838,3,5,5,5,4,3,2,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +14039,86445,Female,Loyal Customer,44,Business travel,Business,3217,3,3,5,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +14040,63104,Female,disloyal Customer,15,Business travel,Eco,909,2,2,2,3,4,2,2,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +14041,124278,Male,Loyal Customer,41,Business travel,Business,1882,0,0,0,4,5,4,5,1,1,1,1,5,1,3,0,10.0,satisfied +14042,41070,Male,Loyal Customer,45,Business travel,Business,140,4,2,2,2,5,4,3,4,4,4,4,4,4,2,13,9.0,neutral or dissatisfied +14043,107685,Female,Loyal Customer,55,Business travel,Business,3007,4,4,4,4,5,5,5,5,5,5,5,4,5,3,53,45.0,satisfied +14044,70194,Male,Loyal Customer,47,Business travel,Business,3464,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,5.0,satisfied +14045,77929,Female,Loyal Customer,60,Business travel,Business,3277,0,0,0,2,2,5,5,4,4,4,4,4,4,5,0,6.0,satisfied +14046,33285,Male,Loyal Customer,51,Personal Travel,Eco Plus,101,2,3,0,4,3,0,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +14047,114847,Female,Loyal Customer,53,Business travel,Business,2501,1,1,1,1,5,4,4,3,3,3,3,3,3,4,7,0.0,satisfied +14048,25106,Male,Loyal Customer,19,Business travel,Business,946,3,3,3,3,5,5,5,5,5,2,5,4,5,5,0,8.0,satisfied +14049,62359,Male,Loyal Customer,32,Business travel,Business,1589,5,5,5,5,4,4,4,4,4,3,3,5,5,4,0,0.0,satisfied +14050,111398,Female,Loyal Customer,54,Personal Travel,Eco,1050,2,4,2,3,4,4,4,4,4,2,1,4,4,3,0,0.0,neutral or dissatisfied +14051,9369,Female,Loyal Customer,45,Business travel,Eco,384,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +14052,59290,Male,Loyal Customer,59,Business travel,Business,2486,4,4,4,4,5,4,4,5,5,5,5,5,5,3,9,9.0,satisfied +14053,119694,Female,disloyal Customer,28,Business travel,Business,1325,4,4,4,3,4,4,4,4,5,4,4,5,5,4,42,29.0,satisfied +14054,95647,Male,Loyal Customer,39,Business travel,Business,845,3,3,1,3,5,4,4,4,4,4,4,5,4,5,17,20.0,satisfied +14055,68817,Male,Loyal Customer,28,Business travel,Eco Plus,926,1,1,1,1,1,1,1,1,3,4,4,4,4,1,57,22.0,neutral or dissatisfied +14056,85108,Female,disloyal Customer,24,Business travel,Business,731,5,4,5,3,4,5,1,4,4,5,5,3,5,4,0,0.0,satisfied +14057,25734,Female,Loyal Customer,39,Personal Travel,Eco,528,2,4,2,4,2,2,2,2,3,2,4,4,4,2,0,0.0,neutral or dissatisfied +14058,41419,Female,Loyal Customer,64,Personal Travel,Eco,563,2,4,2,3,4,5,5,1,1,2,1,3,1,3,0,4.0,neutral or dissatisfied +14059,37896,Female,Loyal Customer,59,Business travel,Eco,937,5,2,2,2,5,4,3,5,5,5,5,5,5,3,1,0.0,satisfied +14060,90367,Male,Loyal Customer,40,Business travel,Business,223,4,4,4,4,4,3,3,1,1,2,4,4,1,2,9,4.0,neutral or dissatisfied +14061,128325,Female,disloyal Customer,32,Business travel,Business,338,2,2,2,4,4,2,4,4,4,4,4,5,4,4,0,0.0,neutral or dissatisfied +14062,63846,Male,Loyal Customer,55,Business travel,Business,2398,4,3,4,4,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +14063,35725,Female,Loyal Customer,31,Personal Travel,Eco Plus,2465,3,5,3,1,3,1,1,5,3,3,4,1,3,1,64,77.0,neutral or dissatisfied +14064,121636,Female,Loyal Customer,29,Business travel,Eco Plus,936,4,5,5,5,4,4,4,4,1,2,3,2,4,4,9,4.0,neutral or dissatisfied +14065,40823,Female,disloyal Customer,23,Business travel,Eco,558,3,0,3,3,2,3,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +14066,116760,Male,Loyal Customer,38,Personal Travel,Eco Plus,480,1,3,1,3,1,1,1,1,5,1,3,2,3,1,0,1.0,neutral or dissatisfied +14067,45917,Male,Loyal Customer,33,Business travel,Business,1578,2,2,2,2,4,3,4,4,1,2,5,1,5,4,0,0.0,satisfied +14068,36146,Female,disloyal Customer,13,Business travel,Eco Plus,1609,1,0,0,3,5,0,5,5,5,4,5,1,3,5,6,0.0,neutral or dissatisfied +14069,19533,Male,Loyal Customer,36,Business travel,Business,108,1,3,4,3,3,4,3,3,3,3,1,3,3,4,40,31.0,neutral or dissatisfied +14070,59832,Male,disloyal Customer,23,Business travel,Eco,1023,1,1,1,2,2,1,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +14071,27632,Male,Loyal Customer,38,Business travel,Eco Plus,937,1,2,2,2,1,1,1,1,4,2,2,2,2,1,0,0.0,neutral or dissatisfied +14072,95626,Female,Loyal Customer,69,Personal Travel,Eco,670,4,4,4,5,5,5,5,3,3,4,3,3,3,3,72,64.0,neutral or dissatisfied +14073,22065,Male,Loyal Customer,21,Business travel,Business,3179,5,5,5,5,5,5,5,5,2,5,2,3,5,5,0,0.0,satisfied +14074,40317,Male,Loyal Customer,28,Personal Travel,Eco,402,3,4,3,1,5,3,5,5,5,2,5,3,4,5,0,2.0,neutral or dissatisfied +14075,42735,Male,Loyal Customer,36,Business travel,Eco,136,5,5,5,5,5,5,5,5,3,3,4,1,1,5,0,0.0,satisfied +14076,98285,Female,disloyal Customer,37,Business travel,Eco,788,5,5,5,4,5,5,5,5,4,2,4,3,2,5,0,4.0,satisfied +14077,84412,Female,Loyal Customer,11,Personal Travel,Eco,633,1,5,1,2,5,1,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +14078,104385,Female,Loyal Customer,51,Personal Travel,Eco,228,3,5,3,2,1,5,5,3,3,3,3,1,3,1,8,1.0,neutral or dissatisfied +14079,31513,Female,Loyal Customer,51,Business travel,Eco,776,3,2,2,2,1,2,3,4,4,3,4,4,4,1,6,15.0,neutral or dissatisfied +14080,80573,Female,Loyal Customer,55,Business travel,Business,1747,3,3,1,3,3,4,5,5,5,5,5,4,5,5,3,0.0,satisfied +14081,17326,Female,Loyal Customer,11,Personal Travel,Eco,403,1,1,1,2,1,1,1,1,2,4,2,2,3,1,46,47.0,neutral or dissatisfied +14082,110793,Female,Loyal Customer,65,Business travel,Eco,705,4,3,3,3,3,5,2,3,3,4,3,3,3,4,16,,satisfied +14083,49347,Female,Loyal Customer,36,Business travel,Business,3119,0,4,0,4,2,3,2,2,2,2,2,5,2,5,0,18.0,satisfied +14084,78769,Male,disloyal Customer,27,Business travel,Eco,432,2,1,2,3,4,2,4,4,3,5,4,3,3,4,30,14.0,neutral or dissatisfied +14085,56020,Female,disloyal Customer,23,Business travel,Eco,2475,1,2,2,2,1,2,2,2,2,1,3,2,2,2,0,0.0,neutral or dissatisfied +14086,118720,Male,Loyal Customer,33,Personal Travel,Eco,338,2,4,2,4,2,2,2,2,4,4,5,4,5,2,13,12.0,neutral or dissatisfied +14087,100948,Male,Loyal Customer,52,Business travel,Eco,1142,2,4,2,4,2,2,2,2,4,1,4,2,4,2,0,25.0,neutral or dissatisfied +14088,3923,Male,Loyal Customer,44,Personal Travel,Eco,290,2,5,2,4,2,2,1,2,4,5,4,3,4,2,25,20.0,neutral or dissatisfied +14089,65454,Female,disloyal Customer,15,Business travel,Business,1303,5,5,5,2,3,5,2,3,5,2,5,5,5,3,21,39.0,satisfied +14090,43196,Male,Loyal Customer,27,Personal Travel,Eco,651,2,1,2,4,1,2,1,1,3,1,3,1,3,1,0,0.0,neutral or dissatisfied +14091,91622,Female,Loyal Customer,27,Business travel,Business,1199,1,1,1,1,4,4,4,4,3,5,4,3,4,4,106,124.0,satisfied +14092,25168,Female,Loyal Customer,36,Business travel,Eco,369,3,2,2,2,3,3,3,3,1,1,2,5,1,3,0,0.0,satisfied +14093,120326,Female,Loyal Customer,22,Personal Travel,Eco,268,2,5,0,3,1,0,1,1,5,5,1,2,4,1,38,52.0,neutral or dissatisfied +14094,55733,Female,Loyal Customer,53,Business travel,Business,2052,1,1,1,1,3,3,4,5,5,4,5,4,5,3,8,13.0,satisfied +14095,46462,Male,Loyal Customer,33,Business travel,Business,2946,2,2,2,2,5,5,4,5,5,2,5,3,4,5,0,0.0,satisfied +14096,49888,Female,Loyal Customer,56,Business travel,Eco,372,1,3,4,3,4,3,3,1,1,1,1,2,1,2,11,17.0,neutral or dissatisfied +14097,67837,Female,Loyal Customer,42,Business travel,Eco,1205,1,3,3,3,1,3,3,1,1,1,1,4,1,2,36,43.0,neutral or dissatisfied +14098,76875,Male,Loyal Customer,47,Business travel,Business,3188,2,5,2,5,3,2,2,2,2,2,2,3,2,3,1,2.0,neutral or dissatisfied +14099,117379,Female,Loyal Customer,51,Business travel,Business,1294,5,5,5,5,4,4,5,3,3,3,3,3,3,3,0,0.0,satisfied +14100,109414,Male,Loyal Customer,55,Business travel,Business,861,2,2,2,2,2,5,5,4,4,4,4,4,4,3,12,16.0,satisfied +14101,63835,Female,Loyal Customer,49,Business travel,Business,1172,4,4,4,4,3,4,4,4,4,5,4,3,4,5,0,3.0,satisfied +14102,24544,Female,Loyal Customer,34,Business travel,Business,3023,3,3,5,3,5,5,4,5,5,4,5,2,5,5,9,4.0,satisfied +14103,2658,Female,disloyal Customer,18,Business travel,Eco,622,0,5,0,3,5,0,2,5,3,3,5,4,4,5,0,0.0,satisfied +14104,123797,Female,Loyal Customer,42,Business travel,Business,603,1,1,1,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +14105,17639,Female,Loyal Customer,59,Business travel,Business,2339,3,3,1,3,5,5,4,4,4,4,4,3,4,3,4,0.0,satisfied +14106,11807,Male,Loyal Customer,51,Personal Travel,Eco Plus,429,3,1,2,4,3,2,2,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +14107,96717,Male,disloyal Customer,27,Business travel,Eco,696,3,3,3,4,2,3,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +14108,47445,Male,disloyal Customer,38,Business travel,Eco,199,2,2,2,4,1,2,1,1,4,2,3,2,4,1,116,98.0,neutral or dissatisfied +14109,4744,Male,Loyal Customer,56,Personal Travel,Eco,888,5,3,5,1,2,5,2,2,5,3,3,3,2,2,0,0.0,satisfied +14110,2104,Female,Loyal Customer,13,Personal Travel,Eco,785,1,4,1,3,2,1,2,2,3,2,5,3,5,2,21,35.0,neutral or dissatisfied +14111,59394,Female,Loyal Customer,63,Personal Travel,Eco,2399,1,5,0,4,4,3,5,1,1,0,1,3,1,3,0,11.0,neutral or dissatisfied +14112,121070,Male,Loyal Customer,38,Business travel,Business,2616,3,3,3,3,3,4,5,5,5,5,5,4,5,5,14,10.0,satisfied +14113,64678,Female,Loyal Customer,80,Business travel,Business,2776,4,4,4,4,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +14114,18824,Male,disloyal Customer,21,Business travel,Eco,551,4,0,4,3,4,4,4,4,1,1,3,2,3,4,0,0.0,neutral or dissatisfied +14115,123549,Female,Loyal Customer,34,Business travel,Business,1773,4,4,4,4,4,3,5,5,5,5,5,4,5,4,0,7.0,satisfied +14116,67082,Male,Loyal Customer,35,Business travel,Business,2113,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +14117,108619,Female,Loyal Customer,21,Personal Travel,Eco,696,3,5,3,2,1,3,2,1,4,2,5,5,5,1,24,15.0,neutral or dissatisfied +14118,16163,Male,Loyal Customer,67,Business travel,Business,1604,3,3,3,3,5,1,3,4,4,4,5,5,4,5,0,0.0,satisfied +14119,9916,Male,Loyal Customer,51,Business travel,Business,534,2,2,2,2,5,5,5,5,3,4,5,5,4,5,188,198.0,satisfied +14120,2621,Male,Loyal Customer,48,Business travel,Business,2275,5,5,5,5,3,5,5,4,4,4,4,5,4,4,25,23.0,satisfied +14121,103660,Male,Loyal Customer,58,Business travel,Business,405,4,4,4,4,3,4,4,3,3,3,3,3,3,3,2,0.0,satisfied +14122,19837,Male,Loyal Customer,70,Personal Travel,Eco,528,3,3,3,2,3,3,1,3,2,4,2,4,3,3,0,0.0,neutral or dissatisfied +14123,105550,Female,Loyal Customer,69,Personal Travel,Eco,611,2,5,2,1,2,3,4,1,1,2,1,3,1,2,33,22.0,neutral or dissatisfied +14124,122182,Male,Loyal Customer,50,Business travel,Business,544,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,11.0,satisfied +14125,59036,Male,Loyal Customer,53,Business travel,Business,1846,2,2,2,2,2,5,4,5,5,5,5,3,5,5,5,0.0,satisfied +14126,76600,Male,Loyal Customer,70,Business travel,Business,481,4,3,3,3,3,3,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +14127,84074,Male,Loyal Customer,26,Business travel,Eco,757,3,5,5,5,3,4,4,3,1,4,4,1,3,3,14,17.0,neutral or dissatisfied +14128,68271,Female,Loyal Customer,37,Personal Travel,Eco,631,2,4,2,5,2,2,2,2,5,4,4,4,4,2,0,0.0,neutral or dissatisfied +14129,25771,Male,Loyal Customer,28,Personal Travel,Business,762,4,4,4,3,2,4,3,2,5,3,5,3,5,2,23,12.0,neutral or dissatisfied +14130,97790,Female,Loyal Customer,69,Business travel,Eco,471,3,1,1,1,1,4,3,3,3,3,3,2,3,4,20,26.0,neutral or dissatisfied +14131,58661,Male,Loyal Customer,45,Personal Travel,Eco,867,3,1,3,2,2,3,2,2,4,3,1,4,1,2,106,92.0,neutral or dissatisfied +14132,36505,Male,Loyal Customer,56,Business travel,Eco,1121,3,5,5,5,4,3,4,4,2,4,1,1,1,4,70,107.0,satisfied +14133,35795,Male,Loyal Customer,21,Personal Travel,Eco,200,2,1,2,3,2,2,2,2,3,1,3,3,3,2,0,0.0,neutral or dissatisfied +14134,101694,Male,Loyal Customer,57,Personal Travel,Eco,1500,3,4,3,5,5,3,5,5,4,4,4,3,5,5,9,0.0,neutral or dissatisfied +14135,45622,Female,Loyal Customer,54,Business travel,Eco,391,2,3,3,3,1,3,3,2,2,2,2,2,2,2,1,0.0,neutral or dissatisfied +14136,104823,Female,disloyal Customer,39,Business travel,Business,426,5,5,5,5,3,5,3,3,3,4,5,5,5,3,21,0.0,satisfied +14137,11340,Female,Loyal Customer,64,Personal Travel,Eco,396,0,5,0,3,2,4,5,3,3,0,1,4,3,4,0,0.0,satisfied +14138,111736,Female,Loyal Customer,17,Business travel,Business,1154,3,3,3,3,4,5,4,4,5,2,4,4,4,4,0,2.0,satisfied +14139,34445,Female,Loyal Customer,57,Business travel,Business,228,2,2,4,2,2,5,4,5,5,5,5,3,5,1,18,15.0,satisfied +14140,123467,Male,Loyal Customer,42,Business travel,Business,2125,1,1,1,1,2,3,5,5,5,5,5,4,5,5,3,30.0,satisfied +14141,123828,Female,disloyal Customer,24,Business travel,Business,541,5,0,5,1,5,1,1,4,3,4,4,1,5,1,126,140.0,satisfied +14142,104851,Female,Loyal Customer,40,Business travel,Business,327,2,2,2,2,3,5,5,5,5,5,5,3,5,5,0,4.0,satisfied +14143,67588,Male,disloyal Customer,24,Business travel,Eco,1313,4,4,4,3,3,4,3,3,3,2,4,5,5,3,0,0.0,satisfied +14144,12243,Male,Loyal Customer,55,Business travel,Eco,190,5,5,5,5,5,5,5,5,4,3,2,2,5,5,0,0.0,satisfied +14145,127976,Female,Loyal Customer,60,Business travel,Business,3412,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +14146,115899,Female,Loyal Customer,39,Business travel,Business,325,0,0,0,2,5,3,1,4,4,5,5,2,4,5,32,22.0,satisfied +14147,58996,Male,Loyal Customer,49,Business travel,Business,1846,2,2,2,2,5,5,5,3,3,3,3,3,3,3,5,0.0,satisfied +14148,23527,Male,Loyal Customer,53,Business travel,Eco Plus,349,1,5,5,5,2,1,2,2,2,4,3,1,4,2,3,14.0,neutral or dissatisfied +14149,62975,Male,Loyal Customer,48,Business travel,Business,862,3,2,2,2,5,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +14150,34723,Female,Loyal Customer,35,Business travel,Business,2275,0,4,0,1,4,2,2,4,4,4,4,3,4,1,0,0.0,satisfied +14151,34291,Female,disloyal Customer,21,Business travel,Eco,280,5,0,5,1,5,5,5,5,3,1,2,5,2,5,113,107.0,satisfied +14152,41506,Female,disloyal Customer,25,Business travel,Eco,1482,4,4,4,4,4,4,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +14153,52816,Male,Loyal Customer,57,Business travel,Business,902,3,3,3,3,2,1,4,5,5,5,5,5,5,4,6,0.0,satisfied +14154,38223,Male,Loyal Customer,27,Personal Travel,Eco Plus,1220,3,1,3,3,3,3,5,3,1,3,2,3,3,3,0,0.0,neutral or dissatisfied +14155,118842,Male,Loyal Customer,45,Business travel,Eco Plus,369,5,2,2,2,5,5,5,5,1,4,4,1,1,5,0,0.0,satisfied +14156,128420,Male,disloyal Customer,42,Business travel,Eco,304,2,1,3,4,2,3,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +14157,84909,Male,Loyal Customer,19,Personal Travel,Eco,547,1,4,1,3,2,1,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +14158,89592,Female,Loyal Customer,39,Business travel,Business,1096,3,3,3,3,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +14159,34933,Female,Loyal Customer,67,Personal Travel,Eco,395,3,5,4,3,3,5,5,4,4,4,4,5,4,3,9,21.0,neutral or dissatisfied +14160,90913,Female,disloyal Customer,44,Business travel,Eco,404,3,3,3,4,5,3,2,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +14161,119976,Male,Loyal Customer,60,Personal Travel,Eco,1009,1,5,1,5,2,1,2,2,1,4,2,1,1,2,0,0.0,neutral or dissatisfied +14162,23780,Female,disloyal Customer,45,Business travel,Eco,438,2,4,2,4,5,2,1,5,5,3,3,3,4,5,0,0.0,neutral or dissatisfied +14163,44730,Male,Loyal Customer,26,Personal Travel,Eco,67,2,5,2,5,4,2,4,4,4,3,5,5,5,4,0,0.0,neutral or dissatisfied +14164,80685,Female,Loyal Customer,45,Business travel,Business,2840,3,3,3,3,2,4,4,5,5,5,5,5,5,3,14,6.0,satisfied +14165,67017,Female,disloyal Customer,29,Business travel,Business,985,2,2,2,2,4,2,2,4,4,2,4,3,5,4,29,20.0,neutral or dissatisfied +14166,46106,Male,disloyal Customer,31,Business travel,Eco,1201,2,2,2,2,2,2,2,2,4,1,3,2,4,2,4,0.0,neutral or dissatisfied +14167,15232,Male,Loyal Customer,43,Business travel,Business,416,4,4,4,4,1,1,1,5,5,5,5,4,5,2,0,10.0,satisfied +14168,90344,Female,disloyal Customer,23,Business travel,Business,515,4,4,4,5,1,4,1,1,5,5,4,3,4,1,92,111.0,satisfied +14169,80435,Male,Loyal Customer,29,Personal Travel,Eco,2248,3,5,3,3,4,3,4,4,4,4,5,3,4,4,1,0.0,neutral or dissatisfied +14170,80021,Female,Loyal Customer,51,Personal Travel,Eco,1076,3,5,3,1,3,5,4,1,1,3,1,4,1,5,97,100.0,neutral or dissatisfied +14171,35970,Female,Loyal Customer,17,Personal Travel,Eco,231,1,1,0,4,1,0,1,1,1,5,4,4,4,1,0,0.0,neutral or dissatisfied +14172,19352,Female,Loyal Customer,42,Business travel,Business,692,1,1,1,1,5,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +14173,13748,Male,Loyal Customer,48,Personal Travel,Eco,401,0,5,0,4,3,0,2,3,5,4,4,3,5,3,0,0.0,satisfied +14174,22694,Female,Loyal Customer,11,Business travel,Business,2203,1,5,5,5,1,1,1,1,3,1,4,4,4,1,55,57.0,neutral or dissatisfied +14175,101350,Female,Loyal Customer,51,Personal Travel,Eco,2026,2,4,2,2,4,5,4,2,2,2,2,5,2,4,18,13.0,neutral or dissatisfied +14176,46129,Male,Loyal Customer,53,Business travel,Eco,516,4,2,2,2,4,4,4,4,4,4,5,2,5,4,0,0.0,satisfied +14177,73830,Female,Loyal Customer,10,Personal Travel,Eco,1194,3,1,3,3,3,2,2,3,1,1,3,2,3,2,145,129.0,neutral or dissatisfied +14178,69675,Male,Loyal Customer,66,Personal Travel,Eco,569,2,4,2,2,4,2,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +14179,68112,Male,Loyal Customer,22,Personal Travel,Eco,813,2,4,2,2,3,2,3,3,4,3,5,2,4,3,52,60.0,neutral or dissatisfied +14180,41153,Male,Loyal Customer,16,Personal Travel,Eco,667,2,1,2,4,5,2,3,5,1,3,4,2,4,5,0,8.0,neutral or dissatisfied +14181,37522,Female,Loyal Customer,45,Business travel,Eco,1028,5,3,3,3,5,5,5,2,5,5,5,5,1,5,416,403.0,satisfied +14182,123027,Female,disloyal Customer,24,Business travel,Eco,590,4,5,4,1,3,4,3,3,4,3,5,3,4,3,46,42.0,satisfied +14183,51546,Male,Loyal Customer,26,Business travel,Business,370,1,1,1,1,4,4,4,4,5,2,4,4,1,4,0,0.0,satisfied +14184,46693,Female,Loyal Customer,18,Personal Travel,Eco,125,1,3,1,3,5,1,5,5,5,3,1,5,3,5,85,82.0,neutral or dissatisfied +14185,38261,Male,Loyal Customer,39,Business travel,Business,2131,2,2,2,2,2,3,1,4,4,4,4,2,4,5,57,46.0,satisfied +14186,5663,Female,Loyal Customer,60,Business travel,Business,3875,2,2,2,2,5,5,5,5,5,5,5,4,5,4,30,94.0,satisfied +14187,68761,Female,Loyal Customer,48,Business travel,Business,926,4,4,4,4,3,5,5,3,3,4,3,4,3,5,1,0.0,satisfied +14188,97530,Male,Loyal Customer,36,Personal Travel,Eco,265,3,3,3,2,2,3,2,2,1,3,1,1,2,2,0,0.0,neutral or dissatisfied +14189,52107,Female,Loyal Customer,41,Personal Travel,Eco,639,3,1,3,4,5,3,5,5,4,2,3,3,3,5,0,0.0,neutral or dissatisfied +14190,26922,Female,Loyal Customer,70,Personal Travel,Eco,1660,2,1,1,3,1,4,4,1,1,1,1,4,1,3,1,0.0,neutral or dissatisfied +14191,2644,Male,Loyal Customer,23,Business travel,Business,2340,4,4,4,4,2,3,2,2,5,2,4,4,5,2,0,0.0,satisfied +14192,115371,Male,disloyal Customer,23,Business travel,Eco,417,5,0,4,5,4,4,4,4,5,2,4,5,4,4,33,38.0,satisfied +14193,83475,Female,disloyal Customer,22,Business travel,Eco,946,5,5,5,2,5,5,5,5,3,4,5,3,4,5,0,11.0,satisfied +14194,27268,Male,Loyal Customer,46,Business travel,Business,1050,5,5,1,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +14195,27746,Male,Loyal Customer,23,Business travel,Eco,680,4,2,2,2,4,4,5,4,5,3,5,1,3,4,0,0.0,satisfied +14196,59070,Female,disloyal Customer,27,Business travel,Eco,1248,2,2,2,4,3,2,3,3,1,4,2,3,4,3,22,33.0,neutral or dissatisfied +14197,105123,Female,disloyal Customer,24,Business travel,Eco,289,1,5,1,3,1,1,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +14198,19281,Female,Loyal Customer,46,Business travel,Eco Plus,430,1,1,1,1,2,4,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +14199,45923,Male,Loyal Customer,53,Business travel,Business,2934,3,3,3,3,4,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +14200,116170,Female,Loyal Customer,38,Personal Travel,Eco,371,1,0,1,4,5,1,2,5,4,3,4,5,5,5,19,17.0,neutral or dissatisfied +14201,16820,Male,disloyal Customer,21,Business travel,Eco,645,0,3,0,2,2,0,2,2,2,2,4,3,2,2,0,0.0,satisfied +14202,14068,Male,Loyal Customer,57,Personal Travel,Eco Plus,980,3,4,3,4,4,3,4,4,4,5,4,3,4,4,94,73.0,neutral or dissatisfied +14203,98781,Female,Loyal Customer,40,Business travel,Business,2398,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +14204,90560,Male,Loyal Customer,52,Business travel,Business,3965,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +14205,5332,Female,Loyal Customer,28,Business travel,Business,733,3,3,3,3,5,5,5,5,5,5,4,3,5,5,13,52.0,satisfied +14206,17123,Female,Loyal Customer,25,Business travel,Business,1211,4,4,3,4,5,5,5,5,5,5,5,3,1,5,0,0.0,satisfied +14207,114831,Male,Loyal Customer,54,Business travel,Business,371,5,5,5,5,2,4,5,4,4,4,4,5,4,4,21,21.0,satisfied +14208,113561,Male,Loyal Customer,65,Business travel,Eco,258,2,1,1,1,2,2,2,2,4,5,2,1,2,2,0,4.0,neutral or dissatisfied +14209,85273,Female,Loyal Customer,37,Personal Travel,Eco,813,1,1,1,3,3,1,2,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +14210,120571,Female,Loyal Customer,27,Personal Travel,Eco,2176,3,3,3,1,1,3,1,1,5,1,3,5,4,1,0,9.0,neutral or dissatisfied +14211,93520,Female,Loyal Customer,56,Business travel,Business,1218,3,3,3,3,5,5,4,4,4,4,4,3,4,4,14,9.0,satisfied +14212,62403,Male,Loyal Customer,57,Personal Travel,Eco,2704,2,5,2,4,2,2,4,2,1,1,4,5,5,2,13,0.0,neutral or dissatisfied +14213,82142,Male,Loyal Customer,43,Business travel,Business,237,3,3,3,3,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +14214,31418,Male,Loyal Customer,30,Business travel,Eco,1546,5,5,5,5,5,5,5,5,2,3,2,2,5,5,8,7.0,satisfied +14215,100715,Female,Loyal Customer,59,Business travel,Business,1594,3,3,3,3,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +14216,102359,Male,Loyal Customer,50,Business travel,Business,2020,3,5,5,5,4,3,2,3,3,3,3,4,3,1,31,27.0,neutral or dissatisfied +14217,95833,Male,disloyal Customer,44,Business travel,Business,759,4,4,4,1,2,4,2,2,4,5,5,3,5,2,8,0.0,satisfied +14218,23907,Male,disloyal Customer,27,Business travel,Eco,589,1,3,1,2,5,1,5,5,2,3,2,2,2,5,0,0.0,neutral or dissatisfied +14219,15699,Male,Loyal Customer,61,Personal Travel,Business,419,2,5,2,4,5,1,4,5,5,2,5,5,5,1,14,0.0,neutral or dissatisfied +14220,22025,Female,disloyal Customer,24,Business travel,Eco,448,4,5,4,2,2,4,2,2,1,4,5,3,1,2,0,0.0,satisfied +14221,102619,Male,Loyal Customer,31,Personal Travel,Eco,1294,2,4,2,3,4,2,4,4,1,4,2,4,4,4,18,0.0,neutral or dissatisfied +14222,10548,Male,Loyal Customer,44,Business travel,Business,74,4,4,4,4,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +14223,16094,Female,Loyal Customer,66,Business travel,Business,349,0,0,0,2,2,1,1,5,5,5,5,2,5,4,0,0.0,satisfied +14224,81742,Female,Loyal Customer,42,Business travel,Eco,1416,3,2,2,2,4,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +14225,72082,Female,Loyal Customer,54,Business travel,Eco,2504,3,5,5,5,3,3,4,3,3,3,3,4,3,2,3,0.0,neutral or dissatisfied +14226,60278,Male,disloyal Customer,8,Business travel,Eco,2446,2,2,2,2,3,2,3,3,3,2,2,2,3,3,0,0.0,neutral or dissatisfied +14227,56350,Female,Loyal Customer,35,Business travel,Eco,200,2,2,2,2,2,2,2,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +14228,55093,Male,disloyal Customer,27,Business travel,Eco,1635,1,1,1,3,5,1,3,5,4,1,3,2,4,5,113,101.0,neutral or dissatisfied +14229,20803,Male,Loyal Customer,31,Business travel,Business,2394,2,2,5,2,3,4,3,3,2,4,1,3,5,3,0,0.0,satisfied +14230,98881,Female,Loyal Customer,55,Personal Travel,Eco,991,4,4,3,3,2,1,3,3,3,3,3,2,3,2,0,5.0,neutral or dissatisfied +14231,105794,Male,Loyal Customer,21,Personal Travel,Eco,925,1,4,1,3,2,1,2,2,5,5,1,5,2,2,63,61.0,neutral or dissatisfied +14232,28776,Male,disloyal Customer,28,Business travel,Business,987,5,5,5,2,3,5,2,3,4,4,4,5,4,3,57,54.0,satisfied +14233,110730,Female,Loyal Customer,49,Business travel,Business,2269,5,5,2,5,2,5,5,5,5,5,5,5,5,3,20,29.0,satisfied +14234,8212,Female,disloyal Customer,22,Business travel,Eco,335,3,2,3,3,2,3,2,2,2,3,4,2,4,2,87,91.0,neutral or dissatisfied +14235,21996,Female,Loyal Customer,69,Personal Travel,Eco,448,3,2,3,4,4,4,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +14236,66935,Male,Loyal Customer,39,Business travel,Business,3919,2,2,2,2,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +14237,96815,Female,Loyal Customer,47,Business travel,Business,816,3,3,3,3,2,4,4,5,5,5,5,4,5,5,2,0.0,satisfied +14238,97485,Male,Loyal Customer,55,Business travel,Business,3268,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +14239,52487,Female,Loyal Customer,33,Personal Travel,Eco Plus,598,3,1,3,4,2,3,2,2,1,3,4,1,3,2,90,89.0,neutral or dissatisfied +14240,2003,Female,Loyal Customer,53,Business travel,Business,2811,1,1,1,1,5,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +14241,63190,Female,disloyal Customer,50,Business travel,Business,447,5,1,1,4,5,5,5,5,4,4,5,5,5,5,1,9.0,satisfied +14242,122164,Female,Loyal Customer,24,Business travel,Business,2665,2,2,2,2,3,3,3,3,3,3,5,3,5,3,29,20.0,satisfied +14243,117820,Female,Loyal Customer,41,Personal Travel,Eco,328,2,0,2,1,2,2,5,2,3,2,5,4,4,2,5,1.0,neutral or dissatisfied +14244,106185,Male,Loyal Customer,69,Personal Travel,Eco,302,1,3,1,3,2,1,2,2,4,2,3,1,4,2,18,26.0,neutral or dissatisfied +14245,126126,Male,Loyal Customer,66,Business travel,Business,1654,3,5,5,5,2,4,4,3,3,2,3,2,3,3,10,5.0,neutral or dissatisfied +14246,7405,Female,Loyal Customer,28,Business travel,Business,552,3,3,3,3,4,4,4,4,3,2,5,3,5,4,15,29.0,satisfied +14247,41086,Male,Loyal Customer,37,Business travel,Eco,316,5,5,5,5,5,5,5,5,1,3,4,5,1,5,54,49.0,satisfied +14248,58915,Female,Loyal Customer,30,Personal Travel,Eco,888,2,3,2,4,1,2,1,1,2,5,3,4,4,1,70,81.0,neutral or dissatisfied +14249,102510,Female,Loyal Customer,66,Personal Travel,Eco,407,4,1,4,3,2,4,3,1,1,4,1,3,1,1,18,5.0,neutral or dissatisfied +14250,9244,Female,Loyal Customer,9,Personal Travel,Eco,100,2,1,2,3,4,2,4,4,3,2,4,2,3,4,0,0.0,neutral or dissatisfied +14251,70623,Male,Loyal Customer,53,Business travel,Business,1217,3,4,4,4,2,3,3,3,3,3,3,4,3,1,26,67.0,neutral or dissatisfied +14252,846,Female,Loyal Customer,39,Business travel,Business,2224,4,3,3,3,2,3,4,3,3,4,4,2,3,4,0,0.0,neutral or dissatisfied +14253,44636,Female,Loyal Customer,37,Business travel,Business,2216,5,5,5,5,3,5,4,5,5,5,4,1,5,5,1,0.0,satisfied +14254,95977,Female,disloyal Customer,29,Business travel,Business,775,1,1,1,2,5,1,5,5,5,3,4,3,5,5,2,3.0,neutral or dissatisfied +14255,43107,Female,Loyal Customer,46,Personal Travel,Eco,236,3,4,3,3,3,4,5,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +14256,57072,Female,Loyal Customer,58,Business travel,Business,2065,1,1,2,1,5,4,5,5,5,5,5,5,5,4,1,0.0,satisfied +14257,7391,Male,Loyal Customer,40,Business travel,Business,2499,3,3,3,3,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +14258,81296,Female,Loyal Customer,21,Personal Travel,Eco,1020,1,3,1,3,1,1,1,1,2,1,3,1,4,1,33,27.0,neutral or dissatisfied +14259,108337,Female,disloyal Customer,29,Business travel,Business,893,0,0,0,1,3,0,3,3,4,4,3,3,4,3,4,51.0,satisfied +14260,26011,Female,Loyal Customer,42,Business travel,Business,425,4,1,1,1,4,3,3,4,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +14261,31872,Male,Loyal Customer,46,Business travel,Business,4983,1,1,1,1,4,4,4,1,3,5,5,4,3,4,0,0.0,satisfied +14262,40538,Female,disloyal Customer,24,Business travel,Eco,216,3,4,3,3,3,3,3,3,3,5,1,1,5,3,0,0.0,neutral or dissatisfied +14263,99116,Male,Loyal Customer,38,Personal Travel,Eco,453,3,2,3,3,4,3,4,4,3,1,3,1,4,4,3,0.0,neutral or dissatisfied +14264,17401,Male,Loyal Customer,45,Business travel,Eco,351,3,2,2,2,3,3,3,1,3,1,3,3,1,3,189,182.0,neutral or dissatisfied +14265,53075,Male,Loyal Customer,32,Business travel,Eco Plus,1208,5,5,5,5,5,5,5,5,3,3,2,2,2,5,29,19.0,satisfied +14266,115938,Male,Loyal Customer,23,Business travel,Business,3244,3,3,5,3,4,4,4,4,1,4,3,4,2,4,13,5.0,satisfied +14267,36353,Male,Loyal Customer,24,Personal Travel,Eco Plus,187,1,5,1,3,5,1,5,5,5,1,2,1,3,5,0,0.0,neutral or dissatisfied +14268,20865,Male,Loyal Customer,54,Personal Travel,Eco,508,2,5,2,2,4,2,4,4,3,1,2,4,2,4,0,0.0,neutral or dissatisfied +14269,120800,Male,Loyal Customer,52,Business travel,Business,666,1,1,1,1,4,4,4,3,3,4,3,5,3,4,5,5.0,satisfied +14270,124077,Male,Loyal Customer,40,Business travel,Business,2402,2,2,2,2,3,2,2,1,3,3,3,2,4,2,207,227.0,neutral or dissatisfied +14271,42839,Male,Loyal Customer,33,Business travel,Business,328,3,3,3,3,4,5,4,4,2,5,3,3,4,4,0,0.0,satisfied +14272,52518,Female,Loyal Customer,59,Business travel,Business,3490,5,5,5,5,2,4,3,5,5,5,5,1,5,2,0,0.0,satisfied +14273,67268,Male,Loyal Customer,68,Personal Travel,Eco,1119,2,5,2,4,2,2,2,2,3,3,5,5,4,2,0,14.0,neutral or dissatisfied +14274,85789,Female,disloyal Customer,72,Business travel,Eco,526,3,2,3,4,2,3,2,2,2,2,4,2,4,2,0,2.0,neutral or dissatisfied +14275,58686,Male,Loyal Customer,23,Personal Travel,Business,299,3,5,3,3,4,3,4,4,4,3,4,5,4,4,4,11.0,neutral or dissatisfied +14276,14797,Male,Loyal Customer,52,Business travel,Business,2703,5,5,5,5,5,3,2,5,5,5,5,2,5,5,0,0.0,satisfied +14277,56425,Female,Loyal Customer,52,Business travel,Eco,719,2,5,5,5,5,4,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +14278,99266,Female,Loyal Customer,43,Business travel,Business,833,5,5,5,5,5,5,5,4,4,4,4,4,4,3,125,116.0,satisfied +14279,21208,Female,Loyal Customer,52,Business travel,Eco,317,3,5,5,5,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +14280,129713,Male,Loyal Customer,50,Business travel,Business,3266,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +14281,64652,Female,Loyal Customer,23,Business travel,Business,190,0,5,0,1,4,4,4,4,5,2,5,4,4,4,47,62.0,satisfied +14282,13324,Male,Loyal Customer,40,Business travel,Business,631,4,5,5,5,4,4,3,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +14283,125781,Male,disloyal Customer,26,Business travel,Eco,993,2,2,2,4,3,2,2,3,2,3,3,3,3,3,0,2.0,neutral or dissatisfied +14284,30529,Female,Loyal Customer,47,Business travel,Business,3648,4,3,3,3,5,4,3,2,2,2,4,2,2,1,14,33.0,neutral or dissatisfied +14285,7261,Female,Loyal Customer,44,Personal Travel,Eco,135,1,0,0,3,3,5,4,3,3,0,3,4,3,4,0,4.0,neutral or dissatisfied +14286,73684,Female,Loyal Customer,61,Business travel,Business,192,0,4,0,1,5,4,5,1,1,1,1,5,1,3,0,0.0,satisfied +14287,123048,Female,Loyal Customer,51,Business travel,Business,2823,5,5,5,5,2,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +14288,47383,Female,disloyal Customer,50,Business travel,Eco,532,4,2,4,4,1,4,1,1,1,2,4,1,3,1,0,0.0,neutral or dissatisfied +14289,34859,Female,Loyal Customer,42,Business travel,Business,2248,1,1,1,1,5,5,5,5,5,5,4,5,5,5,157,189.0,satisfied +14290,79591,Female,Loyal Customer,24,Business travel,Business,2879,4,4,4,4,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +14291,16790,Male,Loyal Customer,17,Personal Travel,Eco Plus,642,2,4,2,2,2,2,2,2,5,4,4,3,5,2,24,20.0,neutral or dissatisfied +14292,36675,Female,Loyal Customer,9,Personal Travel,Eco,1237,2,4,2,2,4,2,4,4,3,3,5,3,5,4,9,32.0,neutral or dissatisfied +14293,54038,Female,disloyal Customer,25,Business travel,Eco,1416,1,1,1,3,3,1,3,3,1,4,5,3,4,3,0,0.0,neutral or dissatisfied +14294,73807,Female,Loyal Customer,58,Personal Travel,Eco Plus,192,3,5,3,4,2,5,5,5,5,3,5,5,5,3,0,3.0,neutral or dissatisfied +14295,97947,Female,Loyal Customer,42,Business travel,Business,401,3,1,1,1,3,3,3,2,2,4,4,3,1,3,134,132.0,neutral or dissatisfied +14296,105768,Male,disloyal Customer,38,Business travel,Eco,387,3,0,3,1,3,3,3,3,1,2,5,5,1,3,1,0.0,neutral or dissatisfied +14297,6956,Male,disloyal Customer,25,Business travel,Business,501,2,4,2,4,3,2,3,3,4,5,5,4,4,3,0,2.0,neutral or dissatisfied +14298,36275,Male,Loyal Customer,29,Personal Travel,Eco,612,3,5,3,4,4,3,4,4,4,5,5,4,5,4,0,29.0,neutral or dissatisfied +14299,77734,Female,disloyal Customer,29,Business travel,Business,1282,5,5,5,3,2,5,2,2,4,2,4,4,5,2,0,0.0,satisfied +14300,41792,Male,Loyal Customer,58,Business travel,Business,2006,1,1,1,1,5,1,1,5,5,5,5,2,5,3,0,20.0,satisfied +14301,129184,Male,disloyal Customer,37,Business travel,Business,2288,2,2,2,5,4,2,4,4,3,2,3,4,4,4,21,3.0,neutral or dissatisfied +14302,123373,Female,Loyal Customer,20,Personal Travel,Eco,644,2,4,1,4,1,1,1,1,3,4,2,3,1,1,18,0.0,neutral or dissatisfied +14303,5504,Female,Loyal Customer,18,Personal Travel,Eco,910,1,4,1,3,4,1,4,4,3,4,5,3,4,4,0,0.0,neutral or dissatisfied +14304,53497,Female,Loyal Customer,67,Personal Travel,Eco,2419,1,4,1,3,1,1,1,3,5,4,4,1,3,1,48,49.0,neutral or dissatisfied +14305,63646,Male,Loyal Customer,37,Business travel,Business,1972,1,1,1,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +14306,82610,Female,Loyal Customer,37,Business travel,Business,2783,4,3,4,4,2,3,3,4,4,4,4,3,4,4,3,1.0,satisfied +14307,48675,Male,Loyal Customer,59,Business travel,Business,3380,5,1,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +14308,3470,Male,Loyal Customer,17,Personal Travel,Eco Plus,296,3,5,3,5,2,3,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +14309,116158,Female,Loyal Customer,55,Personal Travel,Eco,404,4,5,4,4,5,4,5,2,2,4,2,4,2,5,91,85.0,neutral or dissatisfied +14310,103150,Female,Loyal Customer,45,Business travel,Business,1865,5,1,5,5,3,4,5,5,5,5,5,4,5,3,1,3.0,satisfied +14311,8319,Female,Loyal Customer,8,Personal Travel,Eco Plus,335,4,4,4,1,2,4,2,2,5,5,5,3,5,2,18,21.0,neutral or dissatisfied +14312,23975,Female,disloyal Customer,37,Business travel,Eco,596,5,0,5,4,4,5,4,4,3,1,1,2,2,4,0,0.0,satisfied +14313,63477,Female,Loyal Customer,68,Personal Travel,Eco Plus,372,2,5,3,4,4,3,5,1,1,3,1,1,1,5,1,0.0,neutral or dissatisfied +14314,27819,Female,Loyal Customer,54,Business travel,Eco,280,1,1,1,1,2,4,4,1,1,1,1,1,1,4,8,8.0,neutral or dissatisfied +14315,38555,Female,Loyal Customer,51,Personal Travel,Eco,2586,2,4,2,3,4,4,4,5,5,2,3,5,5,4,0,0.0,neutral or dissatisfied +14316,19468,Female,Loyal Customer,50,Business travel,Business,1806,1,1,1,1,3,4,2,5,5,5,5,5,5,5,16,19.0,satisfied +14317,75484,Female,Loyal Customer,63,Personal Travel,Eco,2342,1,4,1,3,4,3,2,2,2,1,2,5,2,5,0,0.0,neutral or dissatisfied +14318,46859,Male,Loyal Customer,58,Business travel,Business,3823,2,3,3,3,2,2,2,4,3,4,3,2,1,2,149,136.0,neutral or dissatisfied +14319,126170,Female,Loyal Customer,25,Business travel,Business,3866,1,3,3,3,1,1,1,1,1,2,3,2,3,1,0,1.0,neutral or dissatisfied +14320,81509,Male,Loyal Customer,68,Personal Travel,Eco Plus,528,3,5,3,2,2,3,4,2,4,5,5,4,4,2,0,0.0,neutral or dissatisfied +14321,45793,Male,disloyal Customer,28,Business travel,Eco,391,1,0,1,2,1,1,1,1,3,1,5,5,3,1,0,0.0,neutral or dissatisfied +14322,120846,Female,Loyal Customer,29,Business travel,Business,992,1,3,3,3,1,1,1,1,2,2,2,1,2,1,0,19.0,neutral or dissatisfied +14323,43856,Female,Loyal Customer,48,Business travel,Eco,199,4,1,1,1,5,1,1,4,4,4,4,4,4,4,0,0.0,satisfied +14324,80808,Female,Loyal Customer,45,Business travel,Business,2071,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,38.0,satisfied +14325,43800,Male,Loyal Customer,58,Personal Travel,Eco,748,3,4,4,5,2,4,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +14326,35466,Female,Loyal Customer,41,Personal Travel,Eco,828,0,4,0,1,3,0,3,3,5,2,5,5,4,3,0,0.0,satisfied +14327,15857,Female,Loyal Customer,23,Business travel,Business,1936,0,0,0,3,5,3,3,5,5,1,4,3,5,5,0,0.0,satisfied +14328,14498,Male,Loyal Customer,47,Business travel,Business,3249,1,1,1,1,4,4,4,5,5,5,5,4,5,5,26,14.0,satisfied +14329,27329,Female,Loyal Customer,53,Business travel,Business,697,3,3,3,3,2,3,4,4,4,4,4,2,4,4,5,24.0,satisfied +14330,26641,Female,disloyal Customer,39,Business travel,Business,404,2,2,2,4,4,2,4,4,3,5,4,1,4,4,0,0.0,neutral or dissatisfied +14331,118817,Male,Loyal Customer,58,Business travel,Business,3005,1,1,1,1,4,5,4,4,4,5,4,5,4,3,0,0.0,satisfied +14332,31126,Female,disloyal Customer,11,Business travel,Eco,991,2,2,2,2,5,2,5,5,4,5,3,2,4,5,0,0.0,neutral or dissatisfied +14333,121019,Female,Loyal Customer,23,Personal Travel,Eco,993,3,4,3,1,4,3,3,4,4,5,4,3,4,4,13,0.0,neutral or dissatisfied +14334,84786,Male,Loyal Customer,26,Business travel,Business,547,5,5,1,5,4,4,4,4,3,5,5,3,5,4,0,0.0,satisfied +14335,109336,Female,Loyal Customer,7,Personal Travel,Eco,1188,5,4,5,3,4,5,1,4,4,2,3,1,1,4,0,0.0,satisfied +14336,56898,Female,Loyal Customer,34,Business travel,Business,2454,1,1,1,1,4,4,4,4,2,4,5,4,3,4,8,12.0,satisfied +14337,101761,Male,Loyal Customer,10,Personal Travel,Eco,1590,4,4,4,1,2,4,2,2,5,2,3,4,5,2,85,64.0,neutral or dissatisfied +14338,63365,Male,Loyal Customer,23,Personal Travel,Eco,372,5,0,5,1,4,5,4,4,4,4,5,5,2,4,0,0.0,satisfied +14339,75092,Male,Loyal Customer,58,Business travel,Business,1723,3,3,3,3,2,2,3,3,3,2,3,3,3,3,0,27.0,neutral or dissatisfied +14340,107837,Female,Loyal Customer,55,Personal Travel,Eco,349,5,1,5,3,4,4,4,5,5,5,5,1,5,1,0,0.0,satisfied +14341,21107,Female,Loyal Customer,68,Personal Travel,Eco,227,1,5,1,4,4,5,5,3,3,1,3,3,3,5,80,72.0,neutral or dissatisfied +14342,21250,Male,Loyal Customer,78,Business travel,Eco Plus,317,3,4,3,4,3,3,3,3,1,4,4,2,3,3,32,38.0,neutral or dissatisfied +14343,2074,Female,disloyal Customer,64,Business travel,Eco,812,1,1,1,3,1,1,1,1,3,3,4,1,3,1,74,84.0,neutral or dissatisfied +14344,65325,Female,Loyal Customer,41,Business travel,Business,1945,3,3,3,3,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +14345,115404,Female,Loyal Customer,32,Business travel,Business,2985,2,4,5,5,2,2,2,2,2,3,4,1,4,2,22,17.0,neutral or dissatisfied +14346,74117,Male,Loyal Customer,35,Business travel,Business,592,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,10.0,satisfied +14347,56563,Female,Loyal Customer,53,Business travel,Business,1085,4,4,4,4,3,5,5,4,4,4,4,3,4,5,16,4.0,satisfied +14348,118095,Female,Loyal Customer,46,Business travel,Business,1671,4,4,4,4,3,5,4,4,4,4,4,3,4,5,123,110.0,satisfied +14349,69235,Female,disloyal Customer,30,Business travel,Business,733,2,3,3,3,5,3,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +14350,17283,Female,Loyal Customer,52,Business travel,Business,2310,1,1,1,1,4,1,5,5,5,5,5,4,5,3,3,25.0,satisfied +14351,107419,Male,disloyal Customer,17,Business travel,Eco,725,4,4,4,3,3,4,3,3,1,1,3,1,4,3,81,58.0,neutral or dissatisfied +14352,57952,Female,Loyal Customer,50,Business travel,Business,2374,2,2,2,2,3,5,5,5,5,5,5,4,5,5,3,0.0,satisfied +14353,40528,Male,Loyal Customer,45,Business travel,Business,391,5,5,5,5,2,5,4,5,5,5,5,5,5,4,41,43.0,satisfied +14354,87672,Female,Loyal Customer,25,Business travel,Eco,606,2,3,3,3,2,2,3,2,1,2,3,3,3,2,30,28.0,neutral or dissatisfied +14355,96648,Male,Loyal Customer,41,Business travel,Eco,572,2,5,5,5,2,2,2,2,1,3,3,3,3,2,45,39.0,neutral or dissatisfied +14356,49870,Male,Loyal Customer,33,Business travel,Business,3782,5,3,5,5,5,5,5,5,4,2,2,1,3,5,10,14.0,satisfied +14357,57410,Female,disloyal Customer,36,Business travel,Eco,524,3,2,3,4,3,3,3,3,3,3,4,1,4,3,8,20.0,neutral or dissatisfied +14358,39295,Female,Loyal Customer,43,Personal Travel,Eco,67,3,5,3,4,3,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +14359,67923,Male,Loyal Customer,8,Personal Travel,Eco,1464,4,4,4,4,1,4,1,1,4,4,4,3,5,1,2,0.0,neutral or dissatisfied +14360,72106,Male,Loyal Customer,62,Personal Travel,Eco Plus,2504,3,2,3,4,2,3,2,2,3,4,3,4,3,2,0,0.0,neutral or dissatisfied +14361,125188,Male,Loyal Customer,57,Business travel,Business,2571,5,5,5,5,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14362,99605,Female,Loyal Customer,47,Business travel,Business,1940,4,4,4,4,5,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +14363,21425,Female,Loyal Customer,51,Business travel,Eco,377,3,1,1,1,2,2,5,3,3,3,3,4,3,1,0,0.0,satisfied +14364,72093,Male,Loyal Customer,45,Personal Travel,Eco,2615,3,5,3,3,2,3,2,2,5,4,4,3,5,2,0,0.0,neutral or dissatisfied +14365,21244,Female,Loyal Customer,38,Business travel,Eco Plus,192,5,3,3,3,5,5,5,5,2,5,2,3,4,5,4,5.0,satisfied +14366,112307,Female,Loyal Customer,57,Business travel,Business,957,4,4,4,4,2,5,4,3,3,3,3,3,3,4,25,30.0,satisfied +14367,44589,Female,Loyal Customer,23,Personal Travel,Eco,84,1,3,1,1,4,1,4,4,4,5,2,2,3,4,0,0.0,neutral or dissatisfied +14368,60429,Male,Loyal Customer,44,Business travel,Business,3885,2,2,2,2,2,4,5,4,4,3,4,3,4,3,10,0.0,satisfied +14369,22869,Male,Loyal Customer,49,Personal Travel,Eco,134,5,1,5,3,4,5,4,4,1,2,2,3,2,4,0,0.0,satisfied +14370,63295,Female,Loyal Customer,45,Business travel,Business,1790,5,4,5,5,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +14371,11525,Male,Loyal Customer,40,Personal Travel,Eco Plus,301,4,5,4,4,5,4,5,5,3,2,5,4,4,5,0,0.0,satisfied +14372,13726,Female,Loyal Customer,46,Business travel,Eco,384,4,2,2,2,2,2,2,4,4,4,4,1,4,3,14,26.0,satisfied +14373,86429,Female,Loyal Customer,60,Business travel,Business,749,2,2,2,2,5,5,5,4,4,4,4,4,4,4,14,17.0,satisfied +14374,77435,Female,Loyal Customer,64,Personal Travel,Eco,588,4,2,4,4,3,3,4,2,2,4,2,2,2,4,0,0.0,neutral or dissatisfied +14375,91991,Male,Loyal Customer,31,Business travel,Eco,236,1,4,3,4,1,1,1,1,2,2,3,2,4,1,30,36.0,neutral or dissatisfied +14376,128199,Female,Loyal Customer,40,Business travel,Business,2973,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +14377,44813,Male,Loyal Customer,26,Personal Travel,Eco,802,4,2,4,2,3,4,3,3,2,4,3,4,3,3,0,6.0,neutral or dissatisfied +14378,21605,Male,Loyal Customer,55,Business travel,Eco,794,5,1,1,1,5,5,5,5,5,5,3,1,5,5,18,2.0,satisfied +14379,66468,Male,Loyal Customer,44,Personal Travel,Eco Plus,1217,2,3,2,3,3,2,3,3,2,5,4,1,4,3,9,10.0,neutral or dissatisfied +14380,47128,Male,Loyal Customer,40,Business travel,Business,748,1,1,1,1,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +14381,61225,Male,Loyal Customer,60,Business travel,Business,862,5,5,5,5,3,4,5,5,5,4,5,3,5,5,3,0.0,satisfied +14382,124618,Male,Loyal Customer,26,Business travel,Business,1671,3,3,2,3,5,5,5,5,5,2,3,4,5,5,0,0.0,satisfied +14383,100720,Male,Loyal Customer,38,Business travel,Business,2005,2,2,2,2,3,5,5,5,5,5,5,5,5,3,2,0.0,satisfied +14384,54500,Female,Loyal Customer,51,Business travel,Business,3173,2,1,2,1,2,3,3,2,2,2,2,4,2,1,0,13.0,neutral or dissatisfied +14385,81680,Female,disloyal Customer,16,Business travel,Business,907,4,5,5,3,3,5,3,3,4,5,5,3,4,3,0,0.0,satisfied +14386,116213,Female,Loyal Customer,12,Personal Travel,Eco,371,4,1,4,4,3,4,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +14387,76343,Female,disloyal Customer,25,Business travel,Eco,954,3,3,3,2,4,3,4,4,2,3,3,3,1,4,0,0.0,neutral or dissatisfied +14388,33885,Male,Loyal Customer,68,Personal Travel,Eco,994,3,4,3,3,2,3,2,2,5,3,5,3,4,2,5,5.0,neutral or dissatisfied +14389,56838,Female,disloyal Customer,41,Business travel,Eco Plus,1605,2,2,2,3,1,2,1,1,3,5,3,3,3,1,26,18.0,neutral or dissatisfied +14390,80467,Female,Loyal Customer,77,Business travel,Business,3167,2,4,4,4,4,3,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +14391,61712,Male,Loyal Customer,52,Business travel,Eco,1635,4,2,2,2,4,4,4,4,4,4,1,3,3,4,0,0.0,neutral or dissatisfied +14392,2148,Female,disloyal Customer,25,Business travel,Business,431,4,0,4,5,1,4,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +14393,75168,Male,disloyal Customer,16,Business travel,Eco,1246,2,2,2,4,2,2,2,2,3,3,2,2,3,2,64,82.0,neutral or dissatisfied +14394,100627,Male,Loyal Customer,46,Business travel,Business,349,1,1,1,1,3,5,5,5,5,4,5,4,5,4,4,0.0,satisfied +14395,30524,Female,Loyal Customer,56,Business travel,Business,2672,2,2,2,2,2,3,4,2,2,1,2,4,2,2,81,89.0,neutral or dissatisfied +14396,38578,Male,Loyal Customer,14,Personal Travel,Eco,2586,3,1,2,3,1,2,1,1,2,5,4,2,3,1,0,0.0,neutral or dissatisfied +14397,108614,Female,Loyal Customer,26,Personal Travel,Eco,696,3,1,3,4,1,3,1,1,2,3,3,3,3,1,1,0.0,neutral or dissatisfied +14398,120704,Female,Loyal Customer,24,Personal Travel,Eco,280,3,4,3,4,2,3,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +14399,103455,Female,Loyal Customer,69,Business travel,Eco,448,4,3,3,3,2,3,4,4,4,4,4,2,4,2,10,0.0,neutral or dissatisfied +14400,86989,Male,Loyal Customer,47,Personal Travel,Eco,907,1,4,1,3,1,5,5,3,3,4,5,5,4,5,377,368.0,neutral or dissatisfied +14401,37624,Female,Loyal Customer,33,Personal Travel,Eco,1069,2,4,1,3,2,1,2,2,5,4,5,3,5,2,50,37.0,neutral or dissatisfied +14402,102845,Female,Loyal Customer,46,Business travel,Business,423,3,3,3,3,4,5,4,4,4,5,4,5,4,4,7,0.0,satisfied +14403,22052,Male,Loyal Customer,48,Business travel,Eco,321,4,1,1,1,4,4,4,4,1,3,4,3,3,4,3,0.0,satisfied +14404,25601,Female,Loyal Customer,52,Personal Travel,Eco,696,2,4,2,1,3,3,4,2,2,2,2,1,2,5,113,93.0,neutral or dissatisfied +14405,21689,Female,disloyal Customer,37,Business travel,Eco,346,4,1,4,4,1,4,1,1,1,2,3,2,3,1,4,0.0,neutral or dissatisfied +14406,83115,Male,disloyal Customer,26,Personal Travel,Eco,957,2,3,1,3,1,1,1,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +14407,63902,Male,Loyal Customer,30,Business travel,Business,3122,2,2,2,2,4,4,4,4,4,5,4,3,5,4,0,0.0,satisfied +14408,54110,Male,Loyal Customer,49,Business travel,Business,1569,2,2,2,2,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +14409,933,Female,Loyal Customer,57,Business travel,Business,134,1,1,1,1,2,4,4,3,3,3,1,2,3,2,0,0.0,neutral or dissatisfied +14410,43011,Male,Loyal Customer,50,Business travel,Eco,259,5,5,5,5,5,5,5,5,4,4,4,5,1,5,0,0.0,satisfied +14411,55895,Female,disloyal Customer,22,Business travel,Eco,473,4,2,4,3,5,4,5,5,4,4,3,3,4,5,0,0.0,neutral or dissatisfied +14412,92160,Male,Loyal Customer,22,Personal Travel,Eco Plus,1576,2,5,2,4,4,2,4,4,4,4,4,3,5,4,0,0.0,neutral or dissatisfied +14413,52792,Male,Loyal Customer,63,Personal Travel,Eco,1874,4,4,4,3,1,4,1,1,2,5,4,1,4,1,1,6.0,neutral or dissatisfied +14414,91825,Female,disloyal Customer,21,Business travel,Business,588,5,5,5,2,2,5,2,2,4,3,5,3,5,2,0,0.0,satisfied +14415,75366,Male,Loyal Customer,25,Personal Travel,Eco Plus,2486,5,3,5,2,5,4,4,5,2,3,4,4,4,4,0,0.0,satisfied +14416,27967,Female,Loyal Customer,11,Personal Travel,Eco,1660,3,5,3,4,5,3,5,5,5,5,5,5,5,5,0,10.0,neutral or dissatisfied +14417,32212,Female,Loyal Customer,39,Business travel,Eco,101,5,3,3,3,5,5,5,5,3,3,3,3,2,5,2,13.0,satisfied +14418,10202,Male,Loyal Customer,54,Business travel,Business,316,3,1,3,3,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14419,108747,Female,Loyal Customer,51,Business travel,Business,3802,4,4,4,4,5,4,4,5,5,5,5,4,5,4,20,35.0,satisfied +14420,114628,Female,Loyal Customer,49,Business travel,Business,2977,3,3,3,3,4,5,5,5,5,5,5,3,5,3,1,0.0,satisfied +14421,26984,Male,Loyal Customer,50,Business travel,Business,867,4,4,4,4,2,5,5,4,4,4,4,2,4,5,0,0.0,satisfied +14422,44616,Female,Loyal Customer,23,Personal Travel,Eco,566,2,5,2,4,2,2,2,2,4,4,4,4,5,2,6,0.0,neutral or dissatisfied +14423,46137,Male,Loyal Customer,52,Business travel,Eco,604,4,5,5,5,4,4,4,4,1,2,4,4,5,4,0,0.0,satisfied +14424,40923,Male,Loyal Customer,18,Personal Travel,Eco,558,2,3,2,4,1,2,3,1,1,5,4,4,4,1,8,5.0,neutral or dissatisfied +14425,129692,Female,Loyal Customer,41,Business travel,Business,447,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +14426,35542,Female,Loyal Customer,15,Personal Travel,Eco,1053,1,4,1,4,5,1,1,5,3,3,3,3,4,5,11,15.0,neutral or dissatisfied +14427,125590,Male,Loyal Customer,50,Business travel,Business,1587,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +14428,55920,Female,Loyal Customer,17,Personal Travel,Eco,733,1,2,1,4,5,1,1,5,4,2,4,1,4,5,0,4.0,neutral or dissatisfied +14429,129699,Female,disloyal Customer,39,Business travel,Business,308,4,4,4,1,1,4,1,1,5,4,4,5,4,1,52,65.0,neutral or dissatisfied +14430,77273,Male,Loyal Customer,46,Business travel,Business,1931,1,1,1,1,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +14431,20793,Female,Loyal Customer,48,Business travel,Eco,508,4,2,2,2,3,4,1,4,4,4,4,1,4,3,54,48.0,satisfied +14432,83209,Female,Loyal Customer,21,Personal Travel,Eco,1123,3,4,3,3,3,3,5,3,4,2,4,3,4,3,0,41.0,neutral or dissatisfied +14433,106203,Male,Loyal Customer,50,Business travel,Eco Plus,436,4,2,3,2,4,4,4,4,1,2,3,1,4,4,0,0.0,neutral or dissatisfied +14434,12992,Female,disloyal Customer,25,Business travel,Eco,438,2,5,2,4,2,5,5,5,1,4,3,5,1,5,141,128.0,neutral or dissatisfied +14435,30431,Female,disloyal Customer,41,Business travel,Business,614,4,4,4,3,5,4,5,5,5,1,2,1,1,5,0,0.0,satisfied +14436,55872,Male,Loyal Customer,40,Business travel,Business,733,5,5,5,5,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +14437,51901,Male,disloyal Customer,43,Business travel,Eco,601,2,3,2,1,3,2,3,3,5,4,2,1,1,3,0,0.0,neutral or dissatisfied +14438,109126,Male,Loyal Customer,24,Business travel,Business,2721,1,1,1,1,5,5,5,5,5,3,4,4,5,5,27,16.0,satisfied +14439,1380,Male,Loyal Customer,50,Business travel,Eco Plus,140,2,2,2,2,2,2,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +14440,39606,Male,Loyal Customer,25,Personal Travel,Eco,679,4,5,4,4,2,4,2,2,5,4,4,3,4,2,0,0.0,neutral or dissatisfied +14441,116067,Male,Loyal Customer,61,Personal Travel,Eco,325,2,5,2,2,1,2,1,1,4,3,2,5,5,1,5,1.0,neutral or dissatisfied +14442,38218,Female,Loyal Customer,57,Personal Travel,Eco Plus,1121,4,1,4,3,4,2,2,1,1,4,1,4,1,4,0,0.0,neutral or dissatisfied +14443,5678,Male,disloyal Customer,38,Business travel,Business,299,4,4,4,1,3,4,3,3,5,5,4,5,4,3,0,0.0,satisfied +14444,93377,Female,Loyal Customer,53,Business travel,Business,2955,2,2,2,2,2,4,5,5,5,5,5,3,5,5,25,17.0,satisfied +14445,110483,Female,Loyal Customer,24,Personal Travel,Eco,787,4,5,4,3,3,4,3,3,5,4,5,5,4,3,10,0.0,neutral or dissatisfied +14446,45192,Female,Loyal Customer,47,Business travel,Business,1437,3,4,4,4,4,2,2,3,3,3,3,4,3,1,2,,neutral or dissatisfied +14447,95286,Male,Loyal Customer,65,Personal Travel,Eco,458,2,4,2,3,2,2,2,2,3,2,5,5,5,2,12,3.0,neutral or dissatisfied +14448,97138,Female,disloyal Customer,46,Business travel,Business,1476,1,1,1,3,5,1,5,5,4,4,5,5,5,5,8,0.0,neutral or dissatisfied +14449,54678,Male,disloyal Customer,14,Business travel,Eco,854,1,2,2,3,2,2,2,2,3,5,3,2,3,2,9,7.0,neutral or dissatisfied +14450,18030,Male,disloyal Customer,37,Business travel,Eco,488,0,3,0,4,5,0,5,5,5,4,5,4,5,5,0,0.0,satisfied +14451,19718,Female,disloyal Customer,57,Business travel,Eco,409,4,1,4,3,4,4,4,4,2,3,3,1,3,4,23,54.0,neutral or dissatisfied +14452,7853,Female,Loyal Customer,33,Business travel,Business,3442,2,4,4,4,2,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +14453,24554,Male,Loyal Customer,36,Business travel,Business,696,2,4,4,4,4,4,3,2,2,2,2,1,2,4,17,15.0,neutral or dissatisfied +14454,84288,Female,Loyal Customer,42,Personal Travel,Eco Plus,334,1,3,4,4,1,1,5,5,5,4,3,2,5,5,59,37.0,neutral or dissatisfied +14455,20561,Female,disloyal Customer,22,Business travel,Eco,533,2,0,2,4,3,2,2,3,2,4,3,4,3,3,30,27.0,neutral or dissatisfied +14456,72788,Male,disloyal Customer,22,Business travel,Eco,645,3,0,3,3,1,3,1,1,4,5,1,5,3,1,0,0.0,neutral or dissatisfied +14457,109864,Male,Loyal Customer,21,Business travel,Business,1092,4,4,2,4,3,3,3,3,4,3,4,3,5,3,6,0.0,satisfied +14458,18487,Female,Loyal Customer,51,Business travel,Business,3683,1,1,2,1,5,4,3,5,5,5,5,4,5,3,0,12.0,satisfied +14459,23002,Female,Loyal Customer,25,Personal Travel,Eco,489,2,3,2,4,1,2,1,1,2,1,3,2,3,1,0,0.0,neutral or dissatisfied +14460,11202,Female,Loyal Customer,11,Personal Travel,Eco,301,2,5,2,3,3,2,3,3,3,2,5,3,4,3,0,0.0,neutral or dissatisfied +14461,15277,Female,Loyal Customer,35,Business travel,Eco,500,2,1,1,1,2,2,2,2,1,1,4,4,3,2,0,16.0,neutral or dissatisfied +14462,109665,Female,Loyal Customer,29,Business travel,Business,3433,2,1,1,1,2,2,2,2,2,2,4,2,3,2,18,10.0,neutral or dissatisfied +14463,125184,Male,Loyal Customer,48,Business travel,Business,651,5,5,5,5,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +14464,80334,Male,disloyal Customer,17,Business travel,Business,746,0,4,0,5,3,4,3,3,5,2,5,5,4,3,0,0.0,satisfied +14465,12780,Female,Loyal Customer,41,Business travel,Business,2727,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +14466,77296,Female,Loyal Customer,43,Business travel,Eco,391,5,2,3,2,5,5,5,5,4,3,5,5,5,5,469,493.0,satisfied +14467,91105,Male,Loyal Customer,54,Personal Travel,Eco,545,3,5,3,2,2,3,1,2,3,1,5,5,5,2,34,27.0,neutral or dissatisfied +14468,57191,Male,Loyal Customer,41,Business travel,Business,1514,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +14469,87500,Female,Loyal Customer,16,Business travel,Business,1560,2,3,3,3,2,2,2,2,4,5,4,2,4,2,8,0.0,neutral or dissatisfied +14470,71037,Female,disloyal Customer,22,Business travel,Eco,802,2,2,2,4,4,2,4,4,2,5,4,4,4,4,6,0.0,neutral or dissatisfied +14471,19325,Male,Loyal Customer,54,Business travel,Eco,694,3,2,2,2,2,3,2,2,1,1,4,3,3,2,0,3.0,neutral or dissatisfied +14472,99438,Male,disloyal Customer,30,Business travel,Eco Plus,337,2,2,2,4,1,2,1,1,2,3,3,4,4,1,0,0.0,neutral or dissatisfied +14473,72207,Male,Loyal Customer,41,Business travel,Business,2724,2,3,2,3,2,2,2,1,3,4,3,2,1,2,4,14.0,neutral or dissatisfied +14474,99473,Female,Loyal Customer,23,Business travel,Business,3118,4,3,3,3,4,4,4,4,1,3,4,4,4,4,5,3.0,neutral or dissatisfied +14475,89957,Male,Loyal Customer,21,Personal Travel,Eco,1310,3,5,3,5,4,3,5,4,3,4,5,3,4,4,0,4.0,neutral or dissatisfied +14476,7763,Female,disloyal Customer,21,Business travel,Eco,1080,2,2,2,1,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +14477,7228,Female,Loyal Customer,34,Business travel,Eco,135,4,5,5,5,4,4,4,4,2,2,1,5,3,4,0,0.0,satisfied +14478,72783,Male,Loyal Customer,41,Business travel,Business,1045,3,2,3,3,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +14479,109325,Male,Loyal Customer,10,Personal Travel,Eco,1188,2,4,2,2,5,2,5,5,3,2,4,4,4,5,32,25.0,neutral or dissatisfied +14480,129234,Male,Loyal Customer,41,Business travel,Business,1504,2,2,2,2,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14481,39270,Female,Loyal Customer,53,Business travel,Business,3329,2,2,5,2,5,2,2,1,1,1,2,2,1,4,0,0.0,neutral or dissatisfied +14482,81310,Male,Loyal Customer,41,Business travel,Business,1299,4,4,4,4,3,5,5,5,5,5,5,5,5,3,5,6.0,satisfied +14483,33407,Female,disloyal Customer,24,Business travel,Eco,2399,3,3,3,4,5,3,5,5,5,2,3,3,2,5,3,0.0,neutral or dissatisfied +14484,14446,Male,disloyal Customer,40,Business travel,Eco,674,4,4,4,2,5,4,5,5,2,5,3,4,3,5,42,25.0,neutral or dissatisfied +14485,77078,Female,Loyal Customer,65,Business travel,Business,591,3,3,3,3,2,2,4,3,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +14486,58477,Male,Loyal Customer,43,Business travel,Business,719,3,3,4,3,3,4,5,5,5,5,5,3,5,3,3,11.0,satisfied +14487,120838,Female,disloyal Customer,39,Business travel,Business,920,3,3,3,3,2,3,2,2,3,5,5,3,4,2,0,40.0,satisfied +14488,67547,Male,Loyal Customer,58,Personal Travel,Business,1205,3,1,3,1,4,2,2,4,4,3,4,3,4,4,53,61.0,neutral or dissatisfied +14489,102799,Female,disloyal Customer,24,Business travel,Eco,342,2,5,2,3,4,2,4,4,3,2,5,4,5,4,0,0.0,neutral or dissatisfied +14490,56200,Female,Loyal Customer,16,Personal Travel,Eco,1400,2,2,2,3,4,2,4,4,2,5,2,4,2,4,0,0.0,neutral or dissatisfied +14491,78800,Female,Loyal Customer,18,Personal Travel,Eco,432,3,4,3,3,5,3,5,5,3,5,5,4,4,5,7,0.0,neutral or dissatisfied +14492,83395,Female,disloyal Customer,24,Business travel,Business,632,5,5,5,4,2,5,2,2,4,5,5,5,4,2,0,0.0,satisfied +14493,103563,Male,disloyal Customer,33,Business travel,Business,604,2,2,2,3,5,2,5,5,3,2,5,3,4,5,54,65.0,neutral or dissatisfied +14494,101641,Female,disloyal Customer,27,Business travel,Business,786,0,0,0,4,1,0,1,1,5,2,3,4,5,1,0,0.0,satisfied +14495,63041,Male,Loyal Customer,35,Personal Travel,Eco,862,1,3,2,3,4,2,5,4,2,4,3,4,4,4,0,4.0,neutral or dissatisfied +14496,39441,Male,disloyal Customer,21,Business travel,Eco,129,1,2,1,3,3,1,3,3,2,4,4,1,4,3,0,7.0,neutral or dissatisfied +14497,126289,Female,Loyal Customer,61,Personal Travel,Eco,507,1,5,1,2,5,4,4,3,3,1,3,5,3,4,4,0.0,neutral or dissatisfied +14498,13631,Male,disloyal Customer,9,Business travel,Eco,1162,1,1,1,4,3,1,3,3,4,2,3,4,4,3,0,55.0,neutral or dissatisfied +14499,79727,Male,Loyal Customer,61,Personal Travel,Eco,760,2,5,2,4,2,3,3,5,2,5,5,3,3,3,318,325.0,neutral or dissatisfied +14500,121123,Female,Loyal Customer,51,Business travel,Business,2402,4,4,4,4,5,5,5,4,3,4,4,5,3,5,5,0.0,satisfied +14501,99059,Female,Loyal Customer,60,Business travel,Business,419,4,4,4,4,2,5,5,5,5,5,5,3,5,5,11,0.0,satisfied +14502,83922,Male,disloyal Customer,33,Business travel,Business,321,1,1,1,4,5,1,5,5,3,2,5,3,5,5,0,0.0,neutral or dissatisfied +14503,124055,Female,Loyal Customer,59,Business travel,Business,2153,3,3,2,3,2,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +14504,62296,Female,disloyal Customer,22,Business travel,Eco,414,4,5,4,4,2,4,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +14505,97977,Male,Loyal Customer,62,Personal Travel,Eco,401,3,5,3,3,1,3,1,1,3,1,4,5,1,1,6,5.0,neutral or dissatisfied +14506,61477,Female,Loyal Customer,9,Business travel,Business,2419,3,4,4,4,3,3,3,3,3,2,4,3,4,3,17,0.0,neutral or dissatisfied +14507,49125,Male,Loyal Customer,47,Business travel,Business,2100,2,2,5,2,5,2,3,4,4,4,5,4,4,4,1,2.0,satisfied +14508,70943,Female,Loyal Customer,16,Personal Travel,Eco,612,2,5,2,3,5,2,5,5,3,4,1,3,4,5,7,5.0,neutral or dissatisfied +14509,113441,Female,Loyal Customer,46,Business travel,Business,3978,1,2,4,2,1,3,2,1,1,1,1,1,1,3,44,38.0,neutral or dissatisfied +14510,97453,Male,Loyal Customer,52,Business travel,Business,484,2,2,2,2,4,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +14511,32463,Female,Loyal Customer,33,Business travel,Eco,216,3,4,4,4,3,3,3,3,2,3,2,3,3,3,0,0.0,neutral or dissatisfied +14512,19674,Male,disloyal Customer,46,Business travel,Eco,409,2,4,2,3,3,2,4,3,1,1,2,4,2,3,68,80.0,neutral or dissatisfied +14513,109730,Male,Loyal Customer,74,Business travel,Business,468,1,3,3,3,4,3,3,1,1,1,1,4,1,3,45,33.0,neutral or dissatisfied +14514,117710,Female,disloyal Customer,30,Business travel,Business,1009,4,4,4,4,4,4,4,4,4,4,4,4,4,4,28,34.0,neutral or dissatisfied +14515,31810,Female,Loyal Customer,16,Personal Travel,Eco,2603,1,3,1,2,1,5,5,2,1,3,3,5,1,5,4,33.0,neutral or dissatisfied +14516,57549,Male,Loyal Customer,30,Personal Travel,Eco Plus,413,2,5,2,2,4,2,3,4,4,3,4,4,4,4,0,11.0,neutral or dissatisfied +14517,32185,Male,Loyal Customer,46,Business travel,Business,2397,2,2,2,2,5,1,5,5,5,5,4,5,5,3,0,0.0,satisfied +14518,77752,Female,disloyal Customer,43,Business travel,Eco,413,2,2,2,4,4,2,4,4,3,1,4,4,4,4,10,2.0,neutral or dissatisfied +14519,49290,Male,disloyal Customer,37,Business travel,Eco,262,4,0,4,5,2,4,2,2,3,4,2,5,5,2,0,5.0,neutral or dissatisfied +14520,41751,Male,Loyal Customer,50,Business travel,Eco,456,4,4,2,4,4,4,4,4,5,4,2,4,4,4,1,10.0,satisfied +14521,74167,Male,Loyal Customer,45,Personal Travel,Eco,678,4,3,3,4,3,3,3,3,2,5,3,1,3,3,1,0.0,neutral or dissatisfied +14522,97955,Female,disloyal Customer,41,Business travel,Business,612,5,5,5,4,4,5,4,4,5,3,4,3,5,4,0,0.0,satisfied +14523,10543,Male,disloyal Customer,20,Business travel,Eco,74,4,0,5,1,2,5,2,2,5,5,5,3,5,2,0,0.0,satisfied +14524,119146,Female,Loyal Customer,50,Personal Travel,Eco Plus,119,1,3,1,3,1,3,2,5,5,1,5,3,5,5,0,0.0,neutral or dissatisfied +14525,88822,Male,Loyal Customer,17,Business travel,Eco Plus,594,5,1,1,1,5,5,4,5,1,1,4,1,5,5,0,0.0,satisfied +14526,48633,Female,Loyal Customer,58,Business travel,Business,262,0,1,1,4,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +14527,81885,Male,Loyal Customer,49,Business travel,Business,2409,1,1,1,1,4,4,5,4,4,4,4,3,4,4,3,1.0,satisfied +14528,116321,Female,Loyal Customer,57,Personal Travel,Eco,333,0,4,0,3,4,4,4,1,1,0,1,3,1,3,3,0.0,satisfied +14529,93640,Male,Loyal Customer,49,Personal Travel,Eco,577,4,2,4,4,1,4,2,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +14530,95669,Female,Loyal Customer,26,Business travel,Business,1557,5,5,4,5,5,4,5,5,2,3,4,2,3,5,0,0.0,neutral or dissatisfied +14531,17152,Male,disloyal Customer,37,Business travel,Business,643,4,5,5,3,3,5,3,3,5,5,4,5,4,3,3,0.0,neutral or dissatisfied +14532,109466,Female,disloyal Customer,32,Business travel,Business,966,3,3,3,4,2,3,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +14533,128840,Female,Loyal Customer,39,Personal Travel,Eco,2475,3,3,3,4,3,1,1,2,2,4,2,1,5,1,14,0.0,neutral or dissatisfied +14534,122640,Female,Loyal Customer,49,Business travel,Eco Plus,728,2,4,4,4,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +14535,104328,Male,Loyal Customer,42,Business travel,Business,1959,3,1,1,1,5,3,3,3,3,3,3,4,3,4,70,58.0,neutral or dissatisfied +14536,76785,Female,disloyal Customer,25,Business travel,Business,546,5,4,5,4,2,5,2,2,5,2,4,3,5,2,0,0.0,satisfied +14537,66311,Male,disloyal Customer,8,Business travel,Business,852,3,5,3,3,3,3,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +14538,19583,Male,Loyal Customer,26,Personal Travel,Eco,108,3,4,3,5,3,3,3,3,5,5,4,4,4,3,0,0.0,neutral or dissatisfied +14539,80047,Female,Loyal Customer,42,Personal Travel,Eco,1069,4,4,5,4,3,3,3,2,2,5,2,3,2,4,0,0.0,neutral or dissatisfied +14540,69794,Female,Loyal Customer,43,Business travel,Business,1055,5,5,5,5,5,5,5,5,5,4,4,5,3,5,128,148.0,satisfied +14541,32209,Male,Loyal Customer,33,Business travel,Eco,163,5,3,3,3,5,5,5,5,1,2,5,3,4,5,0,0.0,satisfied +14542,1252,Male,Loyal Customer,44,Personal Travel,Eco,354,2,5,2,2,2,2,1,2,4,5,2,4,1,2,0,0.0,neutral or dissatisfied +14543,124585,Female,Loyal Customer,49,Business travel,Business,1565,2,2,2,2,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +14544,82327,Female,disloyal Customer,25,Business travel,Eco,456,2,1,2,4,1,2,1,1,3,4,3,1,4,1,46,45.0,neutral or dissatisfied +14545,24159,Male,Loyal Customer,45,Business travel,Business,3511,0,4,0,4,1,1,5,3,3,3,3,5,3,4,0,8.0,satisfied +14546,31581,Female,Loyal Customer,57,Business travel,Business,3086,4,4,4,4,4,1,4,4,4,4,4,1,4,1,6,15.0,satisfied +14547,88269,Female,Loyal Customer,75,Business travel,Eco,270,4,1,1,1,2,3,4,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +14548,10004,Male,Loyal Customer,57,Personal Travel,Eco,534,3,2,3,3,1,3,1,1,1,2,4,1,3,1,86,80.0,neutral or dissatisfied +14549,2434,Female,Loyal Customer,70,Personal Travel,Eco,641,2,5,3,5,4,4,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +14550,26788,Male,Loyal Customer,64,Personal Travel,Eco Plus,1199,2,2,2,1,5,2,5,5,2,3,1,2,1,5,83,96.0,neutral or dissatisfied +14551,79334,Male,Loyal Customer,28,Business travel,Business,3551,3,3,4,3,5,5,5,5,3,2,4,4,5,5,41,22.0,satisfied +14552,111449,Male,disloyal Customer,48,Business travel,Business,836,3,3,3,1,4,3,4,4,5,2,4,3,4,4,5,4.0,neutral or dissatisfied +14553,119656,Male,Loyal Customer,59,Business travel,Business,507,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +14554,46600,Male,Loyal Customer,52,Business travel,Eco,125,4,4,4,4,3,4,3,3,4,4,3,2,2,3,5,2.0,satisfied +14555,51992,Male,Loyal Customer,41,Business travel,Eco Plus,347,4,5,3,5,4,4,4,4,3,1,3,3,2,4,0,0.0,satisfied +14556,120783,Female,Loyal Customer,41,Personal Travel,Eco,678,2,4,2,2,1,2,1,1,4,2,5,5,5,1,22,6.0,neutral or dissatisfied +14557,2886,Male,Loyal Customer,28,Personal Travel,Eco,491,1,5,1,1,4,1,4,4,4,1,1,3,4,4,39,26.0,neutral or dissatisfied +14558,124645,Male,Loyal Customer,46,Business travel,Business,3958,4,4,4,4,4,4,5,2,2,2,2,3,2,4,0,0.0,satisfied +14559,67673,Female,Loyal Customer,57,Business travel,Business,3829,5,5,5,5,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +14560,37700,Male,Loyal Customer,22,Personal Travel,Eco,944,2,5,2,5,5,2,5,5,1,3,3,2,2,5,0,0.0,neutral or dissatisfied +14561,75906,Female,Loyal Customer,52,Business travel,Business,203,4,4,4,4,2,3,2,4,4,4,3,1,4,2,0,0.0,satisfied +14562,74794,Female,disloyal Customer,25,Business travel,Business,1171,1,0,1,3,4,1,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +14563,89274,Female,disloyal Customer,39,Business travel,Business,453,4,4,4,3,1,4,1,1,4,2,5,3,4,1,60,54.0,neutral or dissatisfied +14564,48388,Male,Loyal Customer,45,Personal Travel,Eco,522,1,4,1,1,3,1,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +14565,17759,Male,Loyal Customer,23,Business travel,Eco Plus,383,3,5,5,5,3,3,2,3,3,4,3,1,4,3,8,1.0,neutral or dissatisfied +14566,27756,Female,Loyal Customer,39,Business travel,Business,1448,2,2,2,2,2,2,5,2,2,2,2,2,2,5,0,0.0,satisfied +14567,21466,Male,Loyal Customer,55,Business travel,Business,331,3,4,4,4,3,3,3,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +14568,91575,Male,Loyal Customer,36,Business travel,Eco,1123,4,3,3,3,4,4,4,4,5,4,3,4,4,4,264,247.0,neutral or dissatisfied +14569,118833,Male,disloyal Customer,23,Business travel,Eco,338,4,5,5,3,4,5,4,4,3,4,5,3,4,4,1,1.0,neutral or dissatisfied +14570,127876,Female,Loyal Customer,12,Personal Travel,Eco,1276,1,2,1,3,1,1,1,1,4,3,3,2,4,1,0,0.0,neutral or dissatisfied +14571,87205,Female,Loyal Customer,17,Business travel,Business,946,2,4,4,4,2,2,2,2,3,2,3,4,4,2,10,0.0,neutral or dissatisfied +14572,76309,Male,Loyal Customer,54,Business travel,Business,2182,2,1,2,1,3,2,4,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +14573,8838,Male,Loyal Customer,59,Business travel,Eco Plus,122,3,5,5,5,3,3,3,3,3,5,2,1,1,3,0,0.0,neutral or dissatisfied +14574,39935,Female,Loyal Customer,25,Business travel,Business,3345,5,5,5,5,2,2,2,2,5,5,4,4,3,2,3,1.0,satisfied +14575,76217,Male,disloyal Customer,24,Business travel,Business,1175,0,0,0,2,3,0,3,3,4,5,5,3,5,3,0,0.0,satisfied +14576,41112,Female,Loyal Customer,23,Business travel,Business,667,3,1,1,1,3,2,3,3,4,4,3,3,3,3,5,1.0,neutral or dissatisfied +14577,20,Female,Loyal Customer,42,Personal Travel,Eco,821,3,3,3,4,1,3,4,1,1,3,1,3,1,3,4,0.0,neutral or dissatisfied +14578,90375,Male,disloyal Customer,62,Business travel,Business,271,3,3,3,2,3,3,1,3,3,5,2,4,2,3,0,0.0,neutral or dissatisfied +14579,101998,Male,Loyal Customer,19,Personal Travel,Eco,628,2,1,1,4,1,1,1,3,2,4,4,1,4,1,249,236.0,neutral or dissatisfied +14580,7256,Female,Loyal Customer,12,Personal Travel,Eco,135,2,4,2,1,2,2,2,2,2,1,5,2,4,2,0,0.0,neutral or dissatisfied +14581,94089,Female,Loyal Customer,42,Personal Travel,Business,458,1,5,1,1,1,5,2,5,5,1,5,1,5,4,43,37.0,neutral or dissatisfied +14582,54877,Female,Loyal Customer,25,Personal Travel,Eco,862,3,2,3,4,4,3,4,4,3,2,3,2,4,4,3,0.0,neutral or dissatisfied +14583,98399,Male,Loyal Customer,31,Business travel,Business,462,4,4,4,4,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +14584,24267,Male,Loyal Customer,56,Personal Travel,Eco,147,3,3,3,4,2,3,2,2,1,4,3,4,3,2,58,44.0,neutral or dissatisfied +14585,5550,Female,Loyal Customer,46,Business travel,Business,2348,3,3,2,3,2,4,4,5,5,5,5,4,5,4,0,6.0,satisfied +14586,4852,Female,Loyal Customer,8,Business travel,Business,500,4,1,1,1,4,3,4,4,4,3,4,3,4,4,15,22.0,neutral or dissatisfied +14587,125537,Male,Loyal Customer,55,Business travel,Business,226,0,0,0,3,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +14588,53038,Female,Loyal Customer,39,Business travel,Business,2249,1,5,5,5,4,4,4,1,1,2,1,1,1,3,0,0.0,neutral or dissatisfied +14589,6051,Male,Loyal Customer,57,Personal Travel,Eco,1041,4,5,4,1,5,4,1,5,4,5,5,4,4,5,21,69.0,neutral or dissatisfied +14590,53118,Female,Loyal Customer,45,Business travel,Business,565,2,2,2,2,3,3,5,4,4,4,4,1,4,4,0,0.0,satisfied +14591,56482,Male,Loyal Customer,41,Personal Travel,Eco,4963,2,4,2,2,2,3,3,4,5,4,3,3,2,3,0,4.0,neutral or dissatisfied +14592,255,Male,Loyal Customer,26,Business travel,Business,3800,4,4,4,4,3,3,3,3,5,5,5,3,4,3,158,213.0,satisfied +14593,60586,Female,Loyal Customer,61,Business travel,Business,2034,3,5,5,5,5,3,3,3,3,4,3,2,3,2,14,11.0,neutral or dissatisfied +14594,58572,Male,Loyal Customer,45,Business travel,Business,1611,1,1,1,1,5,4,5,4,4,4,4,4,4,3,36,27.0,satisfied +14595,106555,Male,Loyal Customer,32,Business travel,Eco Plus,727,4,2,2,2,4,4,4,4,4,3,4,3,1,4,4,0.0,satisfied +14596,3572,Male,Loyal Customer,44,Personal Travel,Eco,227,1,4,1,3,4,1,4,4,3,5,5,4,3,4,16,19.0,neutral or dissatisfied +14597,59910,Male,Loyal Customer,54,Business travel,Business,2393,3,3,3,3,5,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +14598,61318,Female,disloyal Customer,38,Business travel,Business,853,4,4,4,2,1,4,5,1,4,3,5,4,5,1,1,0.0,satisfied +14599,5321,Male,Loyal Customer,58,Personal Travel,Eco Plus,383,1,1,4,3,5,4,5,5,2,4,3,2,3,5,0,0.0,neutral or dissatisfied +14600,126956,Female,Loyal Customer,55,Business travel,Business,2207,4,4,4,4,2,5,5,5,5,5,5,3,5,4,78,89.0,satisfied +14601,5214,Male,Loyal Customer,63,Business travel,Business,3438,5,5,4,5,4,5,4,4,4,5,4,5,4,5,0,0.0,satisfied +14602,48127,Male,Loyal Customer,57,Business travel,Business,2002,4,4,4,4,5,5,1,4,4,4,4,1,4,4,0,0.0,satisfied +14603,127301,Male,Loyal Customer,60,Business travel,Business,1979,2,2,2,2,3,5,4,2,2,2,2,5,2,5,35,18.0,satisfied +14604,11543,Male,Loyal Customer,48,Business travel,Business,772,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +14605,60153,Female,Loyal Customer,28,Personal Travel,Eco,1005,2,3,2,4,3,2,4,3,3,5,3,2,2,3,23,3.0,neutral or dissatisfied +14606,80510,Male,Loyal Customer,49,Business travel,Eco,1749,2,3,3,3,2,2,2,2,1,5,2,1,2,2,5,0.0,neutral or dissatisfied +14607,94176,Female,Loyal Customer,55,Business travel,Business,1523,2,2,3,2,5,4,4,5,5,5,5,5,5,4,0,8.0,satisfied +14608,100794,Female,Loyal Customer,23,Business travel,Business,1871,1,1,1,1,5,5,5,5,5,3,4,5,5,5,0,0.0,satisfied +14609,96217,Female,Loyal Customer,43,Business travel,Business,3548,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +14610,11550,Male,Loyal Customer,53,Business travel,Business,2409,2,2,5,2,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14611,103758,Male,Loyal Customer,44,Business travel,Business,3811,1,1,1,1,4,2,2,5,5,5,5,1,5,4,5,0.0,satisfied +14612,15003,Female,Loyal Customer,22,Personal Travel,Eco,1201,1,1,1,3,4,1,4,4,4,3,3,2,4,4,0,0.0,neutral or dissatisfied +14613,67198,Male,Loyal Customer,33,Personal Travel,Eco,964,3,5,3,2,1,3,1,1,3,4,5,5,5,1,2,2.0,neutral or dissatisfied +14614,12861,Female,Loyal Customer,47,Business travel,Eco Plus,489,4,3,3,3,3,2,3,4,4,4,4,1,4,4,0,0.0,satisfied +14615,31815,Female,Loyal Customer,49,Business travel,Business,4983,4,1,1,1,4,4,4,2,5,2,3,4,4,4,0,14.0,neutral or dissatisfied +14616,102059,Female,Loyal Customer,49,Personal Travel,Business,386,2,4,2,4,4,4,5,4,4,2,4,3,4,4,19,13.0,neutral or dissatisfied +14617,125963,Female,disloyal Customer,22,Business travel,Business,631,5,0,5,3,3,5,3,3,5,3,5,4,4,3,61,63.0,satisfied +14618,73670,Female,Loyal Customer,23,Business travel,Business,2395,1,2,2,2,1,1,1,1,4,5,3,4,3,1,1,7.0,neutral or dissatisfied +14619,64750,Female,disloyal Customer,23,Business travel,Eco,190,2,1,2,3,5,2,5,5,3,1,4,3,3,5,1,4.0,neutral or dissatisfied +14620,92200,Female,Loyal Customer,25,Business travel,Business,1956,3,1,1,1,3,3,3,3,4,2,3,2,3,3,15,0.0,neutral or dissatisfied +14621,127773,Male,Loyal Customer,45,Personal Travel,Eco Plus,255,1,3,1,3,5,1,2,5,2,2,4,1,3,5,0,5.0,neutral or dissatisfied +14622,58725,Male,Loyal Customer,41,Business travel,Business,2897,1,1,1,1,2,5,4,5,5,5,5,3,5,5,2,0.0,satisfied +14623,39352,Male,Loyal Customer,35,Personal Travel,Business,896,4,5,4,1,3,5,4,5,5,4,3,5,5,4,0,0.0,satisfied +14624,49288,Female,Loyal Customer,40,Business travel,Eco,109,5,3,3,3,5,5,5,5,1,5,2,3,5,5,0,0.0,satisfied +14625,115961,Female,Loyal Customer,48,Personal Travel,Eco,337,2,1,2,4,3,4,4,1,1,2,3,3,1,2,1,0.0,neutral or dissatisfied +14626,8110,Male,Loyal Customer,37,Business travel,Business,335,0,0,0,3,2,4,4,1,1,1,1,5,1,3,0,0.0,satisfied +14627,6661,Male,Loyal Customer,40,Personal Travel,Business,438,4,4,2,1,5,5,4,5,5,2,5,5,5,4,4,0.0,neutral or dissatisfied +14628,48861,Male,disloyal Customer,38,Business travel,Eco,86,4,0,4,3,5,4,5,5,3,3,2,5,5,5,0,0.0,neutral or dissatisfied +14629,82269,Female,Loyal Customer,20,Business travel,Business,1481,4,4,4,4,4,4,4,4,3,3,4,5,4,4,0,0.0,satisfied +14630,114195,Male,Loyal Customer,56,Business travel,Business,2706,4,4,4,4,4,5,5,4,4,5,4,5,4,3,5,0.0,satisfied +14631,66746,Male,Loyal Customer,60,Personal Travel,Eco,802,2,1,2,3,1,2,1,1,3,5,3,4,3,1,1,0.0,neutral or dissatisfied +14632,119416,Female,Loyal Customer,22,Business travel,Business,3749,2,5,5,5,2,1,2,2,4,3,3,1,4,2,0,0.0,neutral or dissatisfied +14633,59559,Male,Loyal Customer,42,Business travel,Business,787,4,1,4,4,5,5,5,3,3,3,3,3,3,3,6,1.0,satisfied +14634,40750,Male,disloyal Customer,25,Business travel,Eco,501,0,0,0,2,4,0,4,4,4,4,1,5,1,4,0,0.0,satisfied +14635,68596,Female,Loyal Customer,51,Personal Travel,Business,1739,4,5,4,4,2,3,5,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +14636,126999,Female,Loyal Customer,31,Business travel,Business,2307,3,3,3,3,5,5,5,5,3,5,4,5,4,5,75,58.0,satisfied +14637,10447,Male,disloyal Customer,20,Business travel,Eco,224,1,0,1,5,2,1,1,2,3,5,5,3,5,2,0,0.0,neutral or dissatisfied +14638,102295,Female,disloyal Customer,44,Business travel,Business,223,3,3,3,3,3,3,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +14639,37188,Female,Loyal Customer,13,Personal Travel,Eco,1237,2,2,2,2,2,2,2,2,2,3,1,4,1,2,0,0.0,neutral or dissatisfied +14640,38996,Male,Loyal Customer,43,Business travel,Business,1514,4,2,2,2,4,3,3,4,4,4,4,3,4,1,51,49.0,neutral or dissatisfied +14641,1508,Male,Loyal Customer,33,Personal Travel,Business,862,3,4,3,3,3,3,4,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +14642,116295,Male,Loyal Customer,47,Personal Travel,Eco,342,1,4,4,1,3,4,3,3,5,3,4,4,5,3,54,46.0,neutral or dissatisfied +14643,16052,Male,disloyal Customer,37,Business travel,Business,344,1,1,1,5,2,1,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +14644,70284,Female,Loyal Customer,29,Business travel,Eco,852,2,3,3,3,2,2,2,2,2,1,3,3,4,2,2,0.0,neutral or dissatisfied +14645,40449,Male,Loyal Customer,49,Business travel,Business,175,3,3,3,3,2,3,3,2,2,2,3,4,2,2,0,12.0,neutral or dissatisfied +14646,32053,Female,Loyal Customer,46,Business travel,Business,1832,0,5,0,2,1,2,4,1,1,1,1,3,1,3,0,0.0,satisfied +14647,106114,Male,Loyal Customer,40,Business travel,Business,2095,3,3,3,3,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +14648,31421,Female,Loyal Customer,31,Business travel,Business,1506,1,2,2,2,1,1,1,1,3,3,3,4,3,1,68,129.0,neutral or dissatisfied +14649,30019,Female,disloyal Customer,37,Business travel,Eco,234,3,2,4,4,2,4,2,2,1,4,4,4,3,2,0,0.0,neutral or dissatisfied +14650,7030,Male,Loyal Customer,23,Personal Travel,Eco,147,2,5,0,5,4,0,4,4,5,4,4,5,5,4,7,21.0,neutral or dissatisfied +14651,72876,Female,Loyal Customer,41,Business travel,Business,1096,3,4,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +14652,33905,Female,Loyal Customer,64,Personal Travel,Eco,1226,4,4,3,4,2,3,4,2,2,3,2,4,2,4,0,,neutral or dissatisfied +14653,120126,Male,disloyal Customer,25,Business travel,Eco,1313,4,4,4,1,1,4,1,1,3,5,5,5,5,1,0,5.0,neutral or dissatisfied +14654,112718,Male,Loyal Customer,13,Personal Travel,Eco,605,3,1,3,3,1,3,1,1,1,2,4,1,3,1,12,4.0,neutral or dissatisfied +14655,94973,Female,Loyal Customer,69,Business travel,Business,239,2,2,2,2,1,3,4,2,2,2,2,1,2,1,13,6.0,neutral or dissatisfied +14656,116733,Female,Loyal Customer,28,Personal Travel,Eco Plus,362,3,4,2,3,5,2,5,5,5,5,5,4,4,5,14,8.0,neutral or dissatisfied +14657,5430,Male,disloyal Customer,32,Business travel,Business,265,2,2,2,3,4,2,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +14658,104776,Female,Loyal Customer,17,Business travel,Business,2016,4,1,1,1,4,4,4,4,1,2,3,4,3,4,24,28.0,neutral or dissatisfied +14659,126051,Female,Loyal Customer,54,Business travel,Business,1790,2,2,3,2,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +14660,69484,Female,Loyal Customer,23,Business travel,Eco Plus,1089,2,3,4,4,2,2,3,2,2,1,4,2,3,2,1,8.0,neutral or dissatisfied +14661,89590,Male,Loyal Customer,48,Business travel,Business,1847,4,4,4,4,4,5,4,4,4,4,4,5,4,5,4,0.0,satisfied +14662,20398,Male,Loyal Customer,47,Personal Travel,Eco,459,3,4,5,4,2,5,2,2,5,3,4,3,5,2,0,0.0,neutral or dissatisfied +14663,69327,Female,Loyal Customer,54,Business travel,Business,3540,2,2,2,2,4,4,5,4,4,4,4,3,4,4,68,41.0,satisfied +14664,107071,Female,Loyal Customer,34,Personal Travel,Eco,480,2,3,2,3,3,2,3,3,3,2,3,3,4,3,28,13.0,neutral or dissatisfied +14665,52513,Female,Loyal Customer,42,Business travel,Business,110,0,4,0,3,5,2,2,4,4,4,2,2,4,2,0,0.0,satisfied +14666,71686,Female,Loyal Customer,43,Personal Travel,Eco,1012,2,3,2,4,1,4,1,1,1,2,1,1,1,2,31,23.0,neutral or dissatisfied +14667,104857,Male,Loyal Customer,36,Business travel,Business,2207,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +14668,58094,Female,Loyal Customer,57,Business travel,Eco,212,5,2,2,2,5,1,2,5,5,5,5,1,5,4,1,0.0,satisfied +14669,52685,Male,Loyal Customer,40,Personal Travel,Eco,110,3,5,3,4,2,3,2,2,2,5,2,5,2,2,0,0.0,neutral or dissatisfied +14670,16422,Male,Loyal Customer,44,Business travel,Business,445,3,3,3,3,4,3,3,4,4,4,4,4,4,2,0,0.0,satisfied +14671,19145,Female,Loyal Customer,31,Business travel,Business,2200,1,1,1,1,5,5,5,5,3,4,5,5,5,5,43,60.0,satisfied +14672,28544,Female,Loyal Customer,43,Personal Travel,Eco,2701,1,4,1,1,3,4,5,2,2,1,5,3,2,5,10,0.0,neutral or dissatisfied +14673,54344,Male,Loyal Customer,27,Business travel,Eco Plus,1597,2,2,2,2,2,2,2,2,1,1,4,1,4,2,24,28.0,neutral or dissatisfied +14674,100663,Male,Loyal Customer,28,Business travel,Business,2695,4,4,4,4,5,5,5,5,5,2,5,5,4,5,0,5.0,satisfied +14675,57483,Female,Loyal Customer,23,Business travel,Business,1589,2,5,2,2,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +14676,128095,Female,Loyal Customer,12,Personal Travel,Eco,2979,2,3,2,3,2,2,2,3,3,3,3,2,3,2,0,32.0,neutral or dissatisfied +14677,102887,Male,Loyal Customer,57,Business travel,Business,1037,3,3,3,3,3,5,5,4,4,4,4,4,4,5,4,42.0,satisfied +14678,17851,Female,disloyal Customer,29,Business travel,Eco,615,4,4,4,4,4,1,1,3,4,3,3,1,1,1,232,208.0,neutral or dissatisfied +14679,46089,Male,Loyal Customer,20,Personal Travel,Eco,541,2,4,2,3,4,2,4,4,2,2,4,2,3,4,38,38.0,neutral or dissatisfied +14680,66884,Female,Loyal Customer,55,Business travel,Business,1102,2,2,2,2,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +14681,37992,Female,Loyal Customer,33,Business travel,Eco,1197,0,0,0,1,5,0,5,5,4,3,5,3,5,5,0,0.0,satisfied +14682,94405,Female,disloyal Customer,26,Business travel,Eco,192,1,2,1,3,3,1,3,3,4,1,4,2,3,3,44,26.0,neutral or dissatisfied +14683,5765,Female,Loyal Customer,8,Personal Travel,Eco,642,3,4,3,2,2,3,2,2,3,2,4,5,5,2,0,2.0,neutral or dissatisfied +14684,88414,Male,Loyal Customer,47,Business travel,Business,1702,3,3,3,3,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +14685,61159,Male,disloyal Customer,26,Business travel,Business,909,0,0,0,4,5,0,1,5,5,4,5,3,5,5,0,0.0,satisfied +14686,46072,Female,Loyal Customer,16,Business travel,Business,2591,3,3,5,3,5,5,5,5,4,3,4,2,2,5,0,0.0,satisfied +14687,12150,Male,Loyal Customer,34,Business travel,Business,2348,5,5,5,5,3,5,2,2,2,2,2,1,2,1,4,7.0,satisfied +14688,111016,Female,Loyal Customer,46,Business travel,Business,319,0,0,0,1,4,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +14689,20426,Female,Loyal Customer,23,Personal Travel,Eco,299,3,5,3,3,4,3,4,4,3,2,5,4,5,4,58,48.0,neutral or dissatisfied +14690,41398,Female,Loyal Customer,43,Business travel,Eco,563,2,3,1,3,5,3,3,2,2,2,2,1,2,1,0,2.0,neutral or dissatisfied +14691,87412,Male,Loyal Customer,65,Personal Travel,Eco,425,2,4,2,3,4,2,4,4,3,5,5,5,4,4,0,0.0,neutral or dissatisfied +14692,45375,Female,Loyal Customer,38,Business travel,Eco Plus,188,5,2,2,2,5,5,5,5,5,4,3,2,1,5,20,17.0,satisfied +14693,24857,Male,Loyal Customer,55,Business travel,Business,3967,3,5,5,5,1,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +14694,31210,Female,Loyal Customer,41,Business travel,Business,628,5,5,2,5,2,1,5,3,3,2,3,2,3,3,0,0.0,satisfied +14695,121197,Male,Loyal Customer,56,Personal Travel,Eco,2402,3,0,3,1,3,2,2,4,3,5,4,2,4,2,0,1.0,neutral or dissatisfied +14696,36609,Female,disloyal Customer,41,Business travel,Eco,1197,1,1,1,4,5,1,5,5,4,4,4,1,4,5,0,18.0,neutral or dissatisfied +14697,78896,Male,disloyal Customer,54,Business travel,Eco,1337,4,3,3,4,2,4,2,2,3,3,2,4,4,2,2,0.0,neutral or dissatisfied +14698,16465,Male,Loyal Customer,68,Personal Travel,Eco,445,2,5,2,3,4,2,4,4,4,4,4,5,5,4,19,13.0,neutral or dissatisfied +14699,89686,Female,Loyal Customer,15,Business travel,Business,2431,2,2,1,2,5,5,5,5,3,4,2,5,4,5,0,14.0,satisfied +14700,17857,Female,Loyal Customer,26,Personal Travel,Business,425,3,2,3,3,5,3,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +14701,107908,Female,disloyal Customer,29,Business travel,Business,861,1,1,1,4,3,1,5,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +14702,38040,Male,Loyal Customer,40,Business travel,Business,3074,4,4,2,4,5,1,1,5,5,5,5,5,5,1,31,15.0,satisfied +14703,10647,Female,disloyal Customer,44,Business travel,Business,308,4,4,4,2,3,4,3,3,3,2,5,3,4,3,0,0.0,satisfied +14704,12020,Female,disloyal Customer,26,Business travel,Eco,376,1,5,0,3,5,0,5,5,4,2,5,3,5,5,15,9.0,neutral or dissatisfied +14705,69960,Female,Loyal Customer,29,Personal Travel,Eco,2174,1,2,1,4,5,1,2,5,3,3,2,4,4,5,2,0.0,neutral or dissatisfied +14706,99809,Male,Loyal Customer,26,Personal Travel,Eco,632,5,4,5,2,2,5,2,2,3,5,4,4,5,2,0,0.0,satisfied +14707,58931,Male,Loyal Customer,46,Personal Travel,Eco,888,2,1,2,4,2,2,5,2,3,4,3,3,3,2,3,0.0,neutral or dissatisfied +14708,36004,Female,Loyal Customer,59,Business travel,Eco,413,5,4,5,4,1,5,4,5,5,5,5,2,5,2,0,0.0,satisfied +14709,63921,Male,Loyal Customer,27,Personal Travel,Eco,1212,5,1,5,4,4,5,4,4,3,1,3,3,3,4,0,0.0,satisfied +14710,69804,Female,disloyal Customer,22,Business travel,Business,1345,4,0,4,2,5,4,5,5,3,4,5,4,4,5,0,0.0,satisfied +14711,30168,Female,Loyal Customer,50,Personal Travel,Eco,548,2,1,1,3,1,3,4,3,3,1,3,3,3,1,0,0.0,neutral or dissatisfied +14712,128682,Female,Loyal Customer,17,Personal Travel,Eco,2442,2,4,2,2,2,1,1,3,2,4,5,1,4,1,0,0.0,neutral or dissatisfied +14713,90327,Male,Loyal Customer,52,Business travel,Business,1820,2,2,2,2,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +14714,44921,Female,Loyal Customer,42,Business travel,Eco Plus,416,2,5,5,5,3,4,4,2,2,2,2,1,2,4,87,73.0,satisfied +14715,113696,Female,Loyal Customer,7,Personal Travel,Eco,236,3,4,3,4,4,3,4,4,3,5,5,4,4,4,70,66.0,neutral or dissatisfied +14716,126455,Male,Loyal Customer,50,Business travel,Business,1849,4,4,4,4,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +14717,46237,Female,Loyal Customer,19,Business travel,Business,3192,3,5,5,5,3,3,3,4,1,4,3,3,1,3,247,289.0,neutral or dissatisfied +14718,71329,Female,disloyal Customer,50,Business travel,Business,1514,4,3,3,4,1,4,1,1,4,4,5,3,5,1,0,0.0,satisfied +14719,28714,Male,Loyal Customer,34,Business travel,Business,2554,1,1,1,1,4,4,4,5,4,3,4,4,3,4,0,0.0,satisfied +14720,9009,Female,disloyal Customer,26,Business travel,Business,160,1,0,1,3,3,1,3,3,4,2,4,5,4,3,6,8.0,neutral or dissatisfied +14721,116709,Female,Loyal Customer,37,Business travel,Eco Plus,337,3,2,2,2,3,4,3,3,3,2,4,2,5,3,0,10.0,satisfied +14722,88929,Male,Loyal Customer,35,Business travel,Business,1199,5,5,5,5,4,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +14723,43534,Male,Loyal Customer,43,Business travel,Eco,643,2,2,3,2,2,2,2,2,3,4,2,1,3,2,0,10.0,neutral or dissatisfied +14724,95180,Female,Loyal Customer,41,Personal Travel,Eco,277,1,3,1,4,1,1,1,1,1,2,4,3,4,1,6,0.0,neutral or dissatisfied +14725,17022,Male,Loyal Customer,39,Business travel,Business,3690,5,5,5,5,2,5,4,3,3,3,3,4,3,5,0,0.0,satisfied +14726,62797,Female,Loyal Customer,67,Personal Travel,Eco,2447,1,3,1,4,1,3,3,2,1,3,4,3,3,3,282,286.0,neutral or dissatisfied +14727,118231,Female,Loyal Customer,37,Business travel,Business,1587,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +14728,124001,Female,Loyal Customer,51,Business travel,Business,3760,5,5,5,5,2,5,5,4,4,4,5,3,4,3,0,0.0,satisfied +14729,82280,Female,Loyal Customer,31,Personal Travel,Eco,1481,4,4,4,2,4,4,4,4,3,2,3,4,4,4,0,0.0,satisfied +14730,34236,Male,disloyal Customer,10,Business travel,Eco Plus,1237,3,4,3,5,4,3,4,4,3,2,2,1,5,4,0,2.0,neutral or dissatisfied +14731,84845,Female,disloyal Customer,36,Business travel,Eco,547,2,1,2,3,4,2,4,4,1,2,4,2,4,4,56,53.0,neutral or dissatisfied +14732,12465,Female,Loyal Customer,16,Personal Travel,Eco,192,2,4,0,3,2,0,2,2,2,2,4,4,4,2,0,0.0,neutral or dissatisfied +14733,80027,Male,Loyal Customer,60,Personal Travel,Eco,1096,2,1,2,3,4,2,3,4,4,3,3,3,2,4,116,126.0,neutral or dissatisfied +14734,56947,Female,Loyal Customer,32,Business travel,Business,2565,3,2,2,2,3,3,3,3,3,4,3,3,1,3,18,37.0,neutral or dissatisfied +14735,61604,Female,Loyal Customer,45,Business travel,Business,1346,5,5,5,5,2,4,4,4,4,4,4,3,4,5,6,0.0,satisfied +14736,115296,Female,disloyal Customer,42,Business travel,Business,390,4,3,3,2,2,4,2,2,3,3,5,3,5,2,2,0.0,satisfied +14737,129088,Male,Loyal Customer,46,Business travel,Business,2446,3,3,3,3,4,4,4,4,2,3,4,4,5,4,5,4.0,satisfied +14738,92412,Female,Loyal Customer,25,Business travel,Business,1892,4,4,4,4,4,4,4,4,5,3,5,3,4,4,0,5.0,satisfied +14739,113734,Male,Loyal Customer,49,Personal Travel,Eco,391,3,4,3,5,1,3,1,1,5,2,5,5,4,1,13,15.0,neutral or dissatisfied +14740,53361,Male,disloyal Customer,46,Business travel,Eco,1452,4,4,4,1,2,4,2,2,4,4,1,3,2,2,2,25.0,neutral or dissatisfied +14741,102846,Female,Loyal Customer,35,Business travel,Eco,423,3,4,4,4,3,3,3,3,4,1,3,3,4,3,30,30.0,neutral or dissatisfied +14742,127383,Female,Loyal Customer,35,Business travel,Business,868,2,3,3,3,1,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +14743,119507,Female,Loyal Customer,25,Business travel,Business,2498,2,5,5,5,2,2,2,2,1,2,3,1,4,2,0,0.0,neutral or dissatisfied +14744,109061,Male,Loyal Customer,44,Business travel,Eco,1105,4,5,5,5,4,4,4,4,4,2,3,3,2,4,0,0.0,neutral or dissatisfied +14745,116336,Female,Loyal Customer,44,Personal Travel,Eco,417,2,5,2,3,4,3,3,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +14746,103655,Female,disloyal Customer,40,Business travel,Business,251,2,2,2,4,5,2,5,5,4,3,4,5,5,5,14,13.0,neutral or dissatisfied +14747,4200,Male,disloyal Customer,24,Business travel,Business,888,3,1,3,3,5,3,5,5,2,1,3,1,3,5,36,34.0,neutral or dissatisfied +14748,20751,Male,Loyal Customer,29,Personal Travel,Eco,363,2,4,2,2,2,2,2,2,4,3,4,3,4,2,0,0.0,neutral or dissatisfied +14749,105303,Female,disloyal Customer,40,Personal Travel,Eco,738,2,1,2,4,5,2,4,5,3,1,3,1,4,5,0,0.0,neutral or dissatisfied +14750,71330,Female,Loyal Customer,52,Business travel,Business,1514,4,4,4,4,5,5,5,5,5,4,5,3,5,4,3,0.0,satisfied +14751,124202,Male,Loyal Customer,14,Business travel,Business,2176,4,4,4,4,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +14752,3776,Male,disloyal Customer,23,Business travel,Eco,599,3,4,3,4,3,5,5,3,2,4,5,5,5,5,499,473.0,neutral or dissatisfied +14753,42412,Female,Loyal Customer,24,Business travel,Eco Plus,550,5,2,2,2,5,5,5,5,3,5,5,2,5,5,0,0.0,satisfied +14754,21713,Male,Loyal Customer,25,Personal Travel,Eco Plus,746,3,4,3,5,1,3,2,1,5,4,4,4,4,1,20,9.0,neutral or dissatisfied +14755,34144,Male,Loyal Customer,48,Business travel,Eco,1237,5,2,2,2,5,5,5,5,3,1,2,5,1,5,0,5.0,satisfied +14756,129483,Male,disloyal Customer,41,Business travel,Business,2611,2,2,2,3,5,2,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +14757,25671,Male,Loyal Customer,67,Personal Travel,Eco,761,2,2,2,4,3,2,3,3,3,4,4,4,3,3,3,0.0,neutral or dissatisfied +14758,96807,Male,disloyal Customer,18,Business travel,Eco,781,3,3,3,1,5,3,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +14759,27186,Male,Loyal Customer,24,Personal Travel,Eco,2677,1,3,1,3,1,3,3,2,4,4,3,3,3,3,29,33.0,neutral or dissatisfied +14760,51831,Male,disloyal Customer,20,Business travel,Eco Plus,370,1,1,1,3,3,1,4,3,2,5,3,1,4,3,0,0.0,neutral or dissatisfied +14761,62774,Female,disloyal Customer,20,Business travel,Eco,870,3,3,3,2,4,3,4,4,2,4,2,3,3,4,15,16.0,neutral or dissatisfied +14762,81724,Male,disloyal Customer,13,Business travel,Business,1416,5,0,5,1,5,5,5,5,3,3,4,5,4,5,4,0.0,satisfied +14763,67207,Male,Loyal Customer,54,Personal Travel,Eco,929,3,5,4,2,3,4,3,3,3,4,5,4,4,3,0,20.0,neutral or dissatisfied +14764,39748,Female,Loyal Customer,49,Business travel,Business,2397,1,1,1,1,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +14765,80732,Male,disloyal Customer,37,Business travel,Business,393,1,1,1,2,5,1,5,5,3,2,5,4,5,5,0,0.0,neutral or dissatisfied +14766,45961,Female,Loyal Customer,70,Personal Travel,Eco Plus,913,3,4,3,1,5,4,5,1,1,3,1,5,1,4,0,4.0,neutral or dissatisfied +14767,81385,Female,disloyal Customer,30,Business travel,Eco,748,3,3,3,3,2,3,2,2,2,3,3,4,2,2,0,0.0,neutral or dissatisfied +14768,50407,Male,Loyal Customer,28,Business travel,Business,308,3,3,3,3,5,4,5,5,5,1,4,4,4,5,0,3.0,satisfied +14769,25461,Male,disloyal Customer,22,Business travel,Business,481,5,2,5,4,4,5,4,4,3,3,4,5,5,4,0,0.0,satisfied +14770,33732,Male,Loyal Customer,55,Personal Travel,Eco,899,1,1,1,3,1,1,4,1,3,2,2,2,3,1,29,40.0,neutral or dissatisfied +14771,49185,Female,Loyal Customer,47,Business travel,Business,2799,2,2,2,2,1,4,2,5,5,5,4,5,5,2,0,0.0,satisfied +14772,7614,Female,Loyal Customer,15,Personal Travel,Eco,802,4,1,4,2,4,4,4,4,2,1,2,2,2,4,0,0.0,satisfied +14773,53735,Male,Loyal Customer,40,Personal Travel,Eco,1190,2,5,2,2,5,2,5,5,3,3,3,4,4,5,23,4.0,neutral or dissatisfied +14774,126277,Female,Loyal Customer,21,Personal Travel,Eco,590,3,1,3,4,4,3,4,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +14775,88629,Male,Loyal Customer,23,Personal Travel,Eco,581,4,5,4,1,3,4,3,3,4,3,5,5,4,3,0,0.0,neutral or dissatisfied +14776,17196,Male,Loyal Customer,29,Business travel,Business,487,2,3,3,3,2,2,2,2,4,5,4,4,4,2,0,9.0,neutral or dissatisfied +14777,71159,Female,disloyal Customer,22,Business travel,Eco,246,3,0,3,2,4,3,3,4,5,4,4,2,5,4,8,0.0,neutral or dissatisfied +14778,66336,Female,Loyal Customer,50,Business travel,Business,3989,3,5,5,5,2,1,1,3,3,3,3,3,3,1,49,37.0,neutral or dissatisfied +14779,114735,Male,Loyal Customer,58,Business travel,Business,325,2,2,2,2,2,4,4,4,4,4,4,3,4,5,4,0.0,satisfied +14780,31511,Female,Loyal Customer,26,Business travel,Business,2957,3,2,2,2,3,3,3,3,2,2,2,1,3,3,0,0.0,neutral or dissatisfied +14781,99061,Male,Loyal Customer,68,Business travel,Business,3577,4,4,4,4,5,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +14782,46249,Male,disloyal Customer,26,Business travel,Business,279,4,0,4,2,1,4,1,1,4,4,2,2,5,1,0,0.0,neutral or dissatisfied +14783,128350,Female,Loyal Customer,52,Business travel,Business,3346,1,1,1,1,2,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +14784,50801,Male,Loyal Customer,65,Personal Travel,Eco,363,2,4,2,4,4,2,4,4,1,2,4,2,4,4,0,0.0,neutral or dissatisfied +14785,94816,Female,Loyal Customer,47,Business travel,Eco,239,3,2,2,2,1,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +14786,109133,Female,Loyal Customer,47,Business travel,Business,1685,3,3,3,3,2,4,4,4,4,4,4,3,4,4,0,6.0,satisfied +14787,121996,Male,Loyal Customer,53,Business travel,Business,3613,2,2,3,2,4,5,4,4,4,5,4,3,4,3,61,52.0,satisfied +14788,39528,Male,Loyal Customer,62,Personal Travel,Eco,1024,1,5,1,3,2,1,2,2,3,5,4,5,4,2,45,,neutral or dissatisfied +14789,42554,Male,Loyal Customer,31,Personal Travel,Eco,986,2,5,2,2,3,2,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +14790,80052,Female,Loyal Customer,26,Personal Travel,Eco,1096,4,3,4,3,4,4,3,4,4,5,1,5,2,4,8,0.0,satisfied +14791,91751,Male,disloyal Customer,25,Business travel,Business,590,5,5,5,3,1,5,1,1,3,3,5,4,4,1,0,0.0,satisfied +14792,55975,Female,Loyal Customer,48,Personal Travel,Eco,1620,2,5,2,2,4,5,5,3,3,2,3,3,3,5,28,25.0,neutral or dissatisfied +14793,1424,Male,Loyal Customer,59,Business travel,Business,3671,0,4,0,2,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +14794,106751,Male,disloyal Customer,21,Business travel,Eco,545,4,3,4,3,4,4,4,4,1,5,3,1,4,4,0,0.0,neutral or dissatisfied +14795,76959,Female,Loyal Customer,15,Business travel,Business,1990,2,1,1,1,2,1,2,2,1,2,4,4,3,2,0,10.0,neutral or dissatisfied +14796,76425,Female,Loyal Customer,52,Business travel,Business,2201,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +14797,12162,Male,Loyal Customer,56,Business travel,Eco,1214,3,4,2,4,3,3,3,3,3,5,2,4,2,3,22,4.0,neutral or dissatisfied +14798,42078,Female,Loyal Customer,53,Business travel,Eco Plus,106,5,2,2,2,2,1,1,5,5,5,5,2,5,5,0,0.0,satisfied +14799,66417,Male,Loyal Customer,30,Personal Travel,Eco,1562,2,5,2,1,4,2,3,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +14800,118085,Female,Loyal Customer,62,Business travel,Business,3599,4,1,1,1,2,4,4,4,4,4,4,3,4,3,93,71.0,neutral or dissatisfied +14801,112757,Male,Loyal Customer,46,Business travel,Eco,588,2,1,1,1,2,2,2,2,2,4,3,3,3,2,2,0.0,neutral or dissatisfied +14802,108415,Male,Loyal Customer,53,Business travel,Business,1444,1,1,4,1,5,4,4,4,4,4,4,4,4,4,18,0.0,satisfied +14803,15756,Female,Loyal Customer,30,Personal Travel,Eco,431,4,4,4,5,4,4,1,4,1,1,2,3,4,4,38,16.0,neutral or dissatisfied +14804,129388,Male,disloyal Customer,39,Business travel,Eco Plus,954,3,3,3,2,1,3,5,1,4,5,4,3,5,1,9,0.0,neutral or dissatisfied +14805,23833,Female,disloyal Customer,24,Business travel,Eco,1131,2,2,2,4,4,2,4,4,5,4,5,5,3,4,75,46.0,neutral or dissatisfied +14806,115222,Male,Loyal Customer,40,Business travel,Business,337,0,0,0,1,2,4,5,1,1,1,1,5,1,4,0,0.0,satisfied +14807,79218,Female,Loyal Customer,21,Personal Travel,Eco,1990,4,2,5,3,3,5,3,3,1,2,3,3,3,3,0,0.0,neutral or dissatisfied +14808,1642,Female,disloyal Customer,40,Business travel,Business,435,3,2,2,5,4,2,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +14809,12951,Female,Loyal Customer,40,Personal Travel,Eco,979,1,4,1,4,2,1,2,2,3,2,4,3,5,2,2,2.0,neutral or dissatisfied +14810,5480,Male,Loyal Customer,60,Personal Travel,Eco Plus,265,2,1,0,3,3,0,3,3,4,4,3,1,4,3,0,32.0,neutral or dissatisfied +14811,119371,Male,Loyal Customer,40,Business travel,Business,399,3,3,3,3,2,4,5,4,4,4,4,5,4,3,5,0.0,satisfied +14812,126930,Male,Loyal Customer,29,Business travel,Business,325,2,2,2,2,4,4,4,4,5,5,5,4,5,4,24,20.0,satisfied +14813,79616,Female,Loyal Customer,49,Business travel,Business,762,4,4,2,4,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +14814,100747,Female,Loyal Customer,44,Personal Travel,Eco,328,4,1,4,1,4,2,1,1,1,4,1,3,1,2,19,9.0,neutral or dissatisfied +14815,24441,Male,Loyal Customer,44,Business travel,Business,1736,5,5,5,5,2,5,4,3,3,3,3,4,3,5,30,23.0,satisfied +14816,48766,Male,Loyal Customer,52,Business travel,Business,3382,3,3,3,3,3,5,4,4,4,4,4,3,4,4,0,4.0,satisfied +14817,39159,Female,Loyal Customer,36,Business travel,Business,287,5,2,5,5,4,2,4,5,5,5,5,3,5,3,0,0.0,satisfied +14818,67323,Male,Loyal Customer,27,Personal Travel,Eco Plus,1121,2,5,2,4,3,2,3,3,3,4,4,4,4,3,5,0.0,neutral or dissatisfied +14819,119863,Female,Loyal Customer,8,Personal Travel,Eco,936,2,4,2,4,2,2,2,2,5,3,4,5,4,2,26,13.0,neutral or dissatisfied +14820,20833,Male,disloyal Customer,24,Business travel,Eco,508,2,1,2,2,3,2,5,3,4,3,2,4,3,3,0,0.0,neutral or dissatisfied +14821,101035,Female,Loyal Customer,58,Personal Travel,Eco Plus,806,3,4,3,4,5,2,4,5,5,3,5,5,5,1,76,71.0,neutral or dissatisfied +14822,93116,Male,Loyal Customer,18,Business travel,Business,1066,2,2,2,2,4,4,4,4,5,4,5,5,4,4,8,11.0,satisfied +14823,114201,Female,Loyal Customer,43,Business travel,Business,948,4,4,4,4,2,5,5,2,2,2,2,4,2,5,1,0.0,satisfied +14824,14557,Female,Loyal Customer,35,Business travel,Eco Plus,288,3,3,4,3,3,3,3,3,1,3,4,3,3,3,0,0.0,neutral or dissatisfied +14825,26193,Male,Loyal Customer,44,Business travel,Eco,406,3,1,1,1,3,3,3,3,2,1,3,3,3,3,0,0.0,neutral or dissatisfied +14826,50446,Male,Loyal Customer,39,Business travel,Business,2427,4,3,3,3,5,3,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +14827,125575,Male,Loyal Customer,31,Personal Travel,Eco,226,4,5,4,5,5,4,5,5,5,4,4,3,4,5,0,0.0,satisfied +14828,26374,Female,disloyal Customer,35,Business travel,Eco,861,1,1,1,3,1,1,1,1,1,4,3,2,4,1,0,0.0,neutral or dissatisfied +14829,19378,Female,Loyal Customer,46,Business travel,Business,844,5,5,5,5,3,5,2,4,4,4,4,3,4,2,0,0.0,satisfied +14830,34717,Female,Loyal Customer,56,Business travel,Eco,301,5,1,4,1,4,4,4,5,5,5,5,3,5,4,0,2.0,satisfied +14831,73240,Male,Loyal Customer,39,Personal Travel,Eco Plus,946,0,2,0,2,5,2,5,5,1,1,3,3,2,5,0,0.0,satisfied +14832,125046,Female,Loyal Customer,52,Personal Travel,Eco,2300,0,4,0,2,4,3,5,5,5,0,5,3,5,5,0,0.0,satisfied +14833,39763,Male,Loyal Customer,48,Business travel,Business,2989,1,4,1,1,5,3,1,2,2,2,2,4,2,2,0,0.0,satisfied +14834,25579,Female,Loyal Customer,32,Business travel,Business,3321,5,5,5,5,4,5,4,4,2,5,5,1,2,4,0,6.0,satisfied +14835,42622,Female,Loyal Customer,28,Business travel,Business,546,4,3,3,3,4,4,4,4,4,3,2,4,3,4,0,0.0,neutral or dissatisfied +14836,19815,Male,disloyal Customer,22,Business travel,Eco,654,4,3,3,1,3,3,3,3,3,3,1,5,2,3,20,19.0,neutral or dissatisfied +14837,124882,Male,Loyal Customer,41,Business travel,Eco,728,2,5,5,5,2,2,2,2,3,3,4,1,4,2,0,0.0,neutral or dissatisfied +14838,115940,Male,disloyal Customer,24,Business travel,Eco,446,2,1,2,3,3,2,4,3,1,1,4,1,4,3,0,6.0,neutral or dissatisfied +14839,119374,Male,Loyal Customer,53,Business travel,Business,399,2,2,2,2,5,5,5,5,5,5,5,5,5,3,29,41.0,satisfied +14840,79343,Male,disloyal Customer,27,Business travel,Eco,1020,2,2,2,2,3,2,3,3,4,3,4,4,5,3,0,0.0,neutral or dissatisfied +14841,1434,Male,Loyal Customer,28,Business travel,Business,3607,3,3,3,3,5,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +14842,52514,Male,disloyal Customer,26,Business travel,Eco,160,4,5,4,4,3,4,3,3,3,1,3,3,4,3,3,0.0,neutral or dissatisfied +14843,43721,Male,Loyal Customer,48,Personal Travel,Eco,489,2,3,2,3,4,2,4,4,1,5,4,3,4,4,0,0.0,neutral or dissatisfied +14844,109486,Female,Loyal Customer,18,Business travel,Business,920,4,4,4,4,4,4,4,4,5,2,5,5,5,4,16,3.0,satisfied +14845,112766,Male,Loyal Customer,56,Business travel,Business,2398,3,3,3,3,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +14846,48876,Female,Loyal Customer,55,Business travel,Business,262,0,0,0,3,5,3,4,3,3,3,3,2,3,3,0,0.0,satisfied +14847,126806,Female,Loyal Customer,41,Business travel,Business,2296,3,3,3,3,4,5,5,4,4,4,4,4,4,5,1,0.0,satisfied +14848,103449,Female,Loyal Customer,59,Business travel,Business,3136,2,2,2,2,4,4,5,3,3,3,3,5,3,4,6,0.0,satisfied +14849,29106,Male,Loyal Customer,50,Personal Travel,Eco,954,3,5,3,1,1,3,1,1,1,1,4,3,5,1,0,0.0,neutral or dissatisfied +14850,94864,Male,Loyal Customer,56,Business travel,Business,3400,3,1,1,1,1,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +14851,104150,Male,Loyal Customer,52,Business travel,Business,2063,1,3,1,1,2,4,4,4,4,4,4,5,4,3,4,33.0,satisfied +14852,71913,Female,Loyal Customer,58,Personal Travel,Eco,1744,2,2,2,4,5,4,4,1,1,2,1,2,1,3,1,0.0,neutral or dissatisfied +14853,115022,Male,Loyal Customer,58,Business travel,Business,1726,0,0,0,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +14854,125072,Male,Loyal Customer,35,Business travel,Business,361,3,3,3,3,3,5,5,4,4,4,4,3,4,3,17,5.0,satisfied +14855,21378,Male,disloyal Customer,33,Business travel,Eco,554,3,4,3,2,4,3,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +14856,75425,Male,Loyal Customer,46,Business travel,Business,2585,3,2,2,2,4,3,2,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +14857,111606,Male,Loyal Customer,43,Business travel,Business,1878,2,2,4,2,3,4,5,5,5,5,5,5,5,5,26,77.0,satisfied +14858,17897,Male,Loyal Customer,33,Personal Travel,Eco Plus,453,5,1,5,4,1,5,1,1,2,4,4,3,4,1,0,0.0,satisfied +14859,88718,Female,Loyal Customer,54,Personal Travel,Eco,646,3,4,3,3,5,5,1,5,5,3,5,2,5,4,0,8.0,neutral or dissatisfied +14860,2771,Female,Loyal Customer,41,Business travel,Business,2679,1,1,1,1,4,5,4,5,5,5,5,5,5,4,75,64.0,satisfied +14861,75351,Male,Loyal Customer,7,Personal Travel,Eco,2556,4,5,4,4,4,4,3,5,3,4,5,3,5,3,7,0.0,satisfied +14862,27531,Male,Loyal Customer,25,Personal Travel,Eco,605,2,5,2,3,1,2,1,1,3,2,4,3,4,1,113,107.0,neutral or dissatisfied +14863,112401,Female,disloyal Customer,26,Business travel,Business,948,2,2,2,4,3,2,3,3,3,5,5,3,5,3,75,62.0,neutral or dissatisfied +14864,65224,Female,Loyal Customer,39,Business travel,Business,1672,5,5,5,5,3,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +14865,16089,Female,Loyal Customer,49,Business travel,Business,3964,3,5,3,3,1,4,4,3,3,2,3,1,3,4,89,82.0,neutral or dissatisfied +14866,66497,Female,Loyal Customer,34,Business travel,Business,3903,3,2,2,2,4,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +14867,41785,Female,Loyal Customer,51,Personal Travel,Eco Plus,508,5,5,4,1,2,5,5,5,5,4,5,3,5,3,0,0.0,satisfied +14868,101059,Male,disloyal Customer,26,Business travel,Business,368,3,4,2,2,2,2,1,2,3,5,5,5,5,2,4,0.0,neutral or dissatisfied +14869,72723,Female,Loyal Customer,49,Business travel,Eco Plus,929,3,5,5,5,1,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +14870,76287,Female,disloyal Customer,25,Business travel,Business,2677,4,5,4,2,4,3,3,5,3,3,5,3,3,3,0,0.0,neutral or dissatisfied +14871,19561,Female,disloyal Customer,37,Business travel,Eco,173,3,0,3,1,5,3,5,5,1,2,4,4,5,5,0,0.0,neutral or dissatisfied +14872,111177,Female,Loyal Customer,26,Business travel,Business,1546,5,5,2,5,2,2,2,2,3,5,5,4,5,2,0,0.0,satisfied +14873,121213,Female,Loyal Customer,37,Personal Travel,Business,2075,2,5,2,2,1,4,3,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +14874,40832,Male,disloyal Customer,21,Business travel,Eco,532,0,3,0,1,2,0,2,2,4,5,3,3,3,2,96,79.0,satisfied +14875,92974,Male,Loyal Customer,58,Business travel,Business,738,4,4,4,4,2,5,5,4,4,4,4,4,4,5,5,6.0,satisfied +14876,80790,Female,Loyal Customer,56,Business travel,Business,692,1,1,1,1,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +14877,61400,Female,Loyal Customer,32,Personal Travel,Eco,679,2,3,2,3,2,2,2,2,3,3,1,4,2,2,0,0.0,neutral or dissatisfied +14878,24872,Female,Loyal Customer,42,Business travel,Business,356,3,3,3,3,3,4,3,3,3,4,3,3,3,3,2,10.0,neutral or dissatisfied +14879,27553,Male,Loyal Customer,14,Personal Travel,Eco,605,2,4,1,5,1,1,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +14880,37542,Female,Loyal Customer,31,Business travel,Business,2954,4,4,4,4,4,3,4,4,4,5,4,2,4,4,71,65.0,neutral or dissatisfied +14881,71210,Female,Loyal Customer,31,Business travel,Business,733,5,5,5,5,5,5,5,5,3,4,4,4,4,5,0,0.0,satisfied +14882,34357,Female,Loyal Customer,47,Business travel,Eco,541,5,1,1,1,3,3,4,5,5,5,5,4,5,2,7,0.0,satisfied +14883,19166,Male,Loyal Customer,69,Personal Travel,Eco,304,4,3,4,1,1,4,1,1,4,1,1,2,1,1,4,6.0,neutral or dissatisfied +14884,23457,Female,Loyal Customer,22,Business travel,Business,3513,3,5,5,5,3,3,3,3,3,4,3,4,4,3,29,26.0,neutral or dissatisfied +14885,17511,Male,Loyal Customer,51,Business travel,Eco,352,2,1,1,1,2,2,2,2,3,2,5,2,2,2,57,52.0,satisfied +14886,98061,Male,Loyal Customer,39,Business travel,Business,1985,2,3,2,3,1,3,3,2,2,2,2,3,2,3,65,65.0,neutral or dissatisfied +14887,102413,Female,Loyal Customer,46,Personal Travel,Eco,391,3,4,3,3,2,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +14888,123235,Male,Loyal Customer,30,Personal Travel,Eco,590,2,4,2,3,1,2,5,1,3,4,2,1,5,1,0,6.0,neutral or dissatisfied +14889,88705,Female,disloyal Customer,45,Personal Travel,Eco,646,1,3,0,2,5,0,5,5,2,3,4,3,5,5,14,7.0,neutral or dissatisfied +14890,97088,Male,disloyal Customer,30,Business travel,Business,1642,1,1,1,1,5,1,5,5,5,5,3,5,5,5,0,0.0,neutral or dissatisfied +14891,116437,Female,Loyal Customer,22,Personal Travel,Eco,325,3,3,3,4,3,3,3,3,3,4,3,2,5,3,68,61.0,neutral or dissatisfied +14892,22825,Female,Loyal Customer,30,Business travel,Business,2409,3,4,4,4,3,3,3,3,4,1,4,2,3,3,0,6.0,neutral or dissatisfied +14893,18757,Male,Loyal Customer,44,Business travel,Eco,1039,5,1,1,1,5,5,5,5,1,1,2,2,4,5,15,4.0,satisfied +14894,88546,Female,Loyal Customer,57,Personal Travel,Eco,594,1,1,1,2,1,3,2,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +14895,20120,Female,Loyal Customer,55,Business travel,Business,416,2,5,5,5,2,1,2,2,2,2,2,1,2,4,15,6.0,neutral or dissatisfied +14896,85079,Female,Loyal Customer,45,Business travel,Business,3055,2,2,2,2,2,4,4,3,3,3,3,4,3,5,11,43.0,satisfied +14897,109032,Male,disloyal Customer,15,Business travel,Business,488,5,4,5,4,4,5,4,4,4,3,4,5,4,4,22,1.0,satisfied +14898,9274,Male,Loyal Customer,61,Business travel,Business,1201,4,2,5,2,4,3,3,4,4,4,4,2,4,1,14,,neutral or dissatisfied +14899,59065,Female,Loyal Customer,35,Business travel,Eco,1744,3,5,4,5,3,3,3,3,4,4,3,2,3,3,94,73.0,neutral or dissatisfied +14900,22076,Female,Loyal Customer,62,Personal Travel,Eco,304,2,3,2,3,1,4,4,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +14901,42678,Male,Loyal Customer,30,Business travel,Business,604,4,4,4,4,4,4,4,1,2,2,3,4,2,4,109,147.0,satisfied +14902,109074,Male,Loyal Customer,12,Personal Travel,Eco,781,3,4,2,4,4,2,4,4,4,4,1,3,5,4,8,0.0,neutral or dissatisfied +14903,122669,Female,Loyal Customer,43,Business travel,Business,361,5,5,5,5,5,4,4,5,5,5,5,4,5,3,19,3.0,satisfied +14904,19296,Female,Loyal Customer,23,Business travel,Eco,299,2,5,5,5,2,2,1,2,1,2,2,1,2,2,3,4.0,neutral or dissatisfied +14905,9162,Male,Loyal Customer,35,Business travel,Eco,946,3,5,5,5,3,3,3,3,1,2,4,3,4,3,0,0.0,neutral or dissatisfied +14906,46458,Male,Loyal Customer,57,Business travel,Business,3997,3,3,5,3,4,5,4,5,5,4,4,4,5,3,8,14.0,satisfied +14907,114725,Male,Loyal Customer,49,Business travel,Business,372,1,5,1,1,2,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +14908,89073,Male,Loyal Customer,10,Business travel,Business,1947,2,5,5,5,2,3,2,2,1,1,4,2,3,2,0,0.0,neutral or dissatisfied +14909,126948,Male,Loyal Customer,59,Business travel,Business,646,3,3,3,3,5,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +14910,72430,Female,Loyal Customer,47,Business travel,Business,2250,2,2,2,2,4,4,4,5,5,5,5,5,5,5,3,0.0,satisfied +14911,118073,Female,Loyal Customer,26,Personal Travel,Eco Plus,1262,3,4,3,3,4,3,2,4,3,2,5,5,4,4,44,21.0,neutral or dissatisfied +14912,40881,Female,Loyal Customer,30,Personal Travel,Eco,599,1,3,1,5,2,1,1,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +14913,27796,Female,Loyal Customer,35,Business travel,Business,1448,4,4,4,4,1,2,1,2,2,2,2,5,2,1,6,22.0,satisfied +14914,83383,Male,Loyal Customer,20,Business travel,Eco Plus,1124,1,1,4,1,1,2,2,1,3,2,4,4,4,1,6,0.0,neutral or dissatisfied +14915,26742,Male,Loyal Customer,36,Business travel,Eco Plus,115,4,5,5,5,4,4,4,4,1,4,3,1,1,4,0,0.0,satisfied +14916,99848,Female,Loyal Customer,40,Personal Travel,Eco,587,3,5,3,3,3,3,3,3,5,2,5,4,4,3,6,0.0,neutral or dissatisfied +14917,22850,Male,Loyal Customer,25,Personal Travel,Eco,170,2,4,2,2,4,2,4,4,3,3,4,4,5,4,1,21.0,neutral or dissatisfied +14918,85914,Male,Loyal Customer,53,Business travel,Eco,761,2,2,2,2,2,2,2,2,1,2,3,2,4,2,0,0.0,neutral or dissatisfied +14919,104778,Male,Loyal Customer,28,Personal Travel,Business,587,2,4,2,4,3,2,3,3,5,2,5,5,4,3,0,0.0,neutral or dissatisfied +14920,45445,Male,Loyal Customer,33,Business travel,Eco Plus,458,4,5,5,5,4,4,4,4,2,1,3,4,2,4,0,0.0,satisfied +14921,78918,Female,Loyal Customer,40,Business travel,Business,500,2,2,3,2,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +14922,52277,Female,disloyal Customer,39,Business travel,Business,451,1,1,1,1,5,1,5,5,4,3,2,2,2,5,0,0.0,neutral or dissatisfied +14923,79641,Male,disloyal Customer,35,Business travel,Eco,760,4,4,4,3,2,4,2,2,2,2,5,1,5,2,64,52.0,neutral or dissatisfied +14924,100130,Male,disloyal Customer,30,Business travel,Business,725,1,1,1,4,5,1,5,5,3,3,4,3,5,5,5,0.0,neutral or dissatisfied +14925,69279,Male,Loyal Customer,62,Personal Travel,Eco,733,3,2,3,3,1,3,1,1,2,4,4,4,3,1,0,0.0,neutral or dissatisfied +14926,51820,Male,Loyal Customer,44,Business travel,Eco Plus,370,4,4,3,4,4,4,4,4,5,5,4,4,2,4,15,24.0,satisfied +14927,128089,Female,Loyal Customer,36,Business travel,Business,1345,2,1,1,1,2,2,2,1,2,3,4,2,1,2,0,40.0,neutral or dissatisfied +14928,28666,Female,Loyal Customer,17,Personal Travel,Eco,2355,4,5,4,2,1,4,1,1,1,1,2,5,3,1,0,0.0,neutral or dissatisfied +14929,20186,Female,disloyal Customer,47,Business travel,Eco Plus,403,3,3,3,5,3,3,1,3,4,2,4,5,1,3,73,63.0,neutral or dissatisfied +14930,70204,Female,Loyal Customer,10,Personal Travel,Eco,258,2,5,0,1,5,0,5,5,4,4,1,4,2,5,0,13.0,neutral or dissatisfied +14931,7326,Male,Loyal Customer,20,Business travel,Eco Plus,135,3,1,1,1,3,4,1,3,3,3,3,1,4,3,0,8.0,neutral or dissatisfied +14932,71968,Female,Loyal Customer,47,Business travel,Business,1440,4,4,4,4,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +14933,97451,Female,Loyal Customer,65,Personal Travel,Business,670,4,5,4,3,2,3,5,4,4,4,4,2,4,1,0,0.0,satisfied +14934,5514,Male,Loyal Customer,46,Business travel,Business,2233,4,1,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +14935,30932,Male,Loyal Customer,34,Business travel,Business,3278,4,4,4,4,2,4,1,4,4,4,4,4,4,5,0,12.0,satisfied +14936,15084,Male,Loyal Customer,39,Business travel,Business,239,2,2,2,2,5,2,5,5,5,5,5,1,5,1,5,0.0,satisfied +14937,10116,Male,disloyal Customer,14,Business travel,Business,984,5,0,5,2,2,5,2,2,4,4,4,3,5,2,10,0.0,satisfied +14938,19004,Female,disloyal Customer,24,Business travel,Eco,871,2,2,2,3,3,2,3,3,3,1,4,3,3,3,18,0.0,neutral or dissatisfied +14939,54153,Male,Loyal Customer,47,Business travel,Eco,1372,2,1,1,1,2,2,2,2,3,2,2,2,3,2,149,130.0,neutral or dissatisfied +14940,79770,Male,disloyal Customer,29,Business travel,Business,1035,4,4,4,4,5,4,5,5,3,5,3,4,4,5,0,0.0,neutral or dissatisfied +14941,76760,Male,disloyal Customer,21,Business travel,Business,689,4,2,4,1,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +14942,21064,Female,Loyal Customer,56,Business travel,Eco,106,5,4,4,4,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +14943,117776,Female,Loyal Customer,48,Personal Travel,Business,1912,2,4,2,3,4,5,5,2,2,2,2,5,2,3,0,0.0,neutral or dissatisfied +14944,90863,Male,Loyal Customer,20,Business travel,Business,581,4,5,5,5,4,4,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +14945,111785,Male,disloyal Customer,37,Business travel,Eco,120,2,4,2,4,4,2,4,4,2,3,4,4,4,4,51,38.0,neutral or dissatisfied +14946,47376,Male,Loyal Customer,28,Business travel,Eco,588,2,3,3,3,2,2,2,2,1,3,2,2,3,2,0,0.0,neutral or dissatisfied +14947,78704,Female,Loyal Customer,59,Business travel,Business,1656,1,2,2,2,1,3,3,1,1,1,1,3,1,2,3,6.0,neutral or dissatisfied +14948,121520,Female,Loyal Customer,36,Business travel,Business,2986,5,5,5,5,3,5,5,5,5,5,5,3,5,4,0,5.0,satisfied +14949,57308,Male,disloyal Customer,37,Business travel,Business,236,4,4,4,5,2,4,4,2,5,2,5,3,4,2,0,0.0,satisfied +14950,32456,Male,disloyal Customer,37,Business travel,Eco,101,2,5,2,4,2,2,2,2,1,3,2,2,2,2,0,0.0,neutral or dissatisfied +14951,118668,Male,Loyal Customer,69,Business travel,Business,221,4,4,4,4,2,5,1,5,5,5,3,5,5,5,4,0.0,satisfied +14952,84363,Male,Loyal Customer,51,Business travel,Business,2753,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +14953,121485,Female,Loyal Customer,64,Personal Travel,Eco,331,2,5,5,3,5,5,5,2,2,5,2,3,2,3,0,0.0,neutral or dissatisfied +14954,62511,Male,Loyal Customer,49,Business travel,Business,1846,2,2,2,2,2,4,5,4,4,4,4,5,4,5,3,0.0,satisfied +14955,21318,Male,Loyal Customer,12,Business travel,Eco Plus,692,3,3,4,3,3,3,4,3,3,2,4,2,3,3,1,3.0,neutral or dissatisfied +14956,23941,Male,Loyal Customer,23,Business travel,Business,936,1,4,4,4,1,1,1,1,1,5,3,1,4,1,18,10.0,neutral or dissatisfied +14957,84405,Female,Loyal Customer,37,Personal Travel,Eco,606,3,1,3,4,5,3,5,5,3,3,3,1,4,5,20,25.0,neutral or dissatisfied +14958,90387,Female,Loyal Customer,54,Personal Travel,Business,270,2,0,2,4,4,4,3,3,3,2,3,3,3,1,0,3.0,neutral or dissatisfied +14959,62520,Male,Loyal Customer,40,Business travel,Business,1846,5,5,5,5,5,4,4,5,5,5,5,3,5,3,0,27.0,satisfied +14960,108463,Female,Loyal Customer,60,Personal Travel,Eco,1444,2,0,2,4,2,5,5,5,5,4,5,5,4,5,119,153.0,neutral or dissatisfied +14961,73072,Male,disloyal Customer,20,Business travel,Eco,1085,3,3,3,4,4,3,4,4,4,1,3,2,3,4,0,0.0,neutral or dissatisfied +14962,8221,Male,Loyal Customer,54,Personal Travel,Eco,335,3,4,5,3,5,5,5,5,3,5,4,5,5,5,0,0.0,neutral or dissatisfied +14963,116862,Female,disloyal Customer,16,Business travel,Eco,651,2,4,2,3,3,2,5,3,3,4,5,5,5,3,36,29.0,neutral or dissatisfied +14964,26351,Male,Loyal Customer,43,Business travel,Business,3205,5,5,5,5,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +14965,117381,Female,Loyal Customer,21,Personal Travel,Eco,1294,1,4,1,1,5,1,5,5,5,2,4,4,5,5,22,29.0,neutral or dissatisfied +14966,67908,Female,Loyal Customer,34,Personal Travel,Eco,1205,3,4,3,3,5,3,5,5,4,5,3,3,4,5,3,0.0,neutral or dissatisfied +14967,37725,Male,Loyal Customer,11,Personal Travel,Eco,944,1,3,1,3,2,1,2,2,2,2,4,2,3,2,120,108.0,neutral or dissatisfied +14968,80693,Male,Loyal Customer,61,Business travel,Eco,748,2,5,5,5,2,2,2,2,4,5,2,3,3,2,0,0.0,neutral or dissatisfied +14969,125151,Female,Loyal Customer,59,Business travel,Business,1840,5,5,5,5,2,1,4,5,5,5,5,2,5,4,18,19.0,satisfied +14970,94842,Male,Loyal Customer,37,Business travel,Business,239,2,3,3,3,2,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +14971,13444,Male,Loyal Customer,35,Business travel,Business,2863,4,4,4,4,3,5,5,3,3,4,3,5,3,4,22,19.0,satisfied +14972,15833,Female,Loyal Customer,43,Business travel,Eco Plus,195,1,2,2,2,1,4,3,1,1,1,1,2,1,2,2,0.0,neutral or dissatisfied +14973,83273,Female,Loyal Customer,27,Personal Travel,Eco,1979,5,5,5,4,4,5,4,4,5,3,3,2,4,4,0,0.0,satisfied +14974,88941,Female,disloyal Customer,35,Business travel,Business,1199,1,1,1,4,3,1,3,3,4,2,5,4,5,3,1,0.0,neutral or dissatisfied +14975,44461,Male,Loyal Customer,51,Business travel,Business,1627,1,1,1,1,2,4,5,4,4,4,5,5,4,2,0,0.0,satisfied +14976,2837,Female,Loyal Customer,40,Business travel,Business,409,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,7.0,satisfied +14977,63019,Female,Loyal Customer,50,Business travel,Business,3107,5,5,1,5,2,4,5,5,5,4,5,5,5,3,14,5.0,satisfied +14978,39985,Female,Loyal Customer,47,Business travel,Eco Plus,1262,4,1,1,1,3,5,3,3,3,4,3,5,3,3,0,1.0,satisfied +14979,76390,Male,disloyal Customer,24,Business travel,Eco,531,3,2,3,4,5,3,5,5,1,5,3,3,3,5,0,16.0,neutral or dissatisfied +14980,16447,Female,Loyal Customer,36,Business travel,Business,2675,3,3,3,3,5,3,3,3,3,3,3,3,3,3,53,68.0,satisfied +14981,82248,Female,Loyal Customer,66,Personal Travel,Eco Plus,405,3,5,3,2,3,2,2,3,4,4,5,2,5,2,210,211.0,neutral or dissatisfied +14982,65751,Female,Loyal Customer,32,Personal Travel,Eco,1061,2,4,2,1,4,2,4,4,3,2,5,4,4,4,129,118.0,neutral or dissatisfied +14983,8148,Female,disloyal Customer,27,Business travel,Business,125,1,1,1,4,4,1,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +14984,6155,Female,Loyal Customer,24,Business travel,Business,475,3,3,3,3,3,3,3,3,3,5,4,1,3,3,15,11.0,neutral or dissatisfied +14985,103756,Male,Loyal Customer,51,Business travel,Business,2108,3,3,3,3,4,4,5,4,4,4,4,3,4,4,31,43.0,satisfied +14986,26266,Male,Loyal Customer,32,Business travel,Business,859,3,1,3,3,3,3,3,3,2,1,4,2,3,3,0,0.0,neutral or dissatisfied +14987,89399,Male,Loyal Customer,33,Business travel,Business,3362,4,4,4,4,5,5,4,5,3,3,5,3,5,5,5,0.0,satisfied +14988,21367,Female,Loyal Customer,48,Business travel,Business,1862,2,5,5,5,2,3,3,2,2,2,2,1,2,2,7,12.0,neutral or dissatisfied +14989,107180,Male,Loyal Customer,56,Business travel,Business,668,3,1,1,1,1,3,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +14990,82746,Female,Loyal Customer,47,Business travel,Business,3244,1,5,5,5,2,4,4,1,1,1,1,2,1,4,23,17.0,neutral or dissatisfied +14991,57261,Male,Loyal Customer,40,Business travel,Business,2389,2,4,4,4,5,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +14992,16908,Male,Loyal Customer,55,Personal Travel,Eco,746,4,4,4,3,4,3,3,3,2,4,4,3,4,3,183,152.0,neutral or dissatisfied +14993,79267,Male,Loyal Customer,37,Business travel,Eco Plus,998,1,2,2,2,1,1,1,1,3,4,3,1,3,1,0,93.0,neutral or dissatisfied +14994,58280,Male,Loyal Customer,41,Business travel,Business,2835,4,4,4,4,5,3,2,5,5,5,5,5,5,4,1,0.0,satisfied +14995,23272,Female,Loyal Customer,43,Business travel,Business,3172,3,1,1,1,3,2,3,3,3,3,3,1,3,4,32,50.0,neutral or dissatisfied +14996,10418,Female,Loyal Customer,49,Business travel,Business,517,1,1,1,1,3,4,5,4,4,4,4,4,4,3,2,17.0,satisfied +14997,110555,Male,Loyal Customer,56,Business travel,Business,674,5,5,5,5,3,5,5,5,5,5,5,5,5,4,58,53.0,satisfied +14998,34849,Female,Loyal Customer,52,Personal Travel,Eco Plus,301,2,1,2,3,4,3,4,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +14999,114030,Female,Loyal Customer,15,Personal Travel,Eco Plus,1838,2,5,2,3,2,2,2,2,4,4,3,5,5,2,0,0.0,neutral or dissatisfied +15000,106288,Female,Loyal Customer,9,Personal Travel,Eco,689,1,4,1,2,5,1,5,5,4,3,5,5,5,5,0,4.0,neutral or dissatisfied +15001,93751,Male,Loyal Customer,42,Business travel,Business,368,1,1,1,1,4,4,3,1,1,1,1,3,1,3,15,12.0,neutral or dissatisfied +15002,25287,Male,disloyal Customer,32,Business travel,Eco,321,3,5,4,2,1,4,1,1,2,5,1,1,4,1,9,17.0,neutral or dissatisfied +15003,16796,Male,Loyal Customer,44,Business travel,Eco,1017,4,4,4,4,4,4,4,4,5,2,4,1,3,4,0,0.0,satisfied +15004,8066,Female,disloyal Customer,25,Business travel,Business,125,3,4,3,3,2,3,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +15005,80238,Male,disloyal Customer,38,Business travel,Business,1269,5,5,5,5,2,5,2,2,3,2,4,5,5,2,8,3.0,satisfied +15006,93760,Male,Loyal Customer,56,Personal Travel,Eco,368,1,5,1,2,5,1,5,5,1,2,2,2,1,5,2,0.0,neutral or dissatisfied +15007,46007,Male,Loyal Customer,61,Business travel,Eco Plus,483,4,2,2,2,4,4,4,4,3,5,1,2,2,4,0,0.0,satisfied +15008,77950,Male,Loyal Customer,44,Business travel,Business,3291,1,1,5,1,5,4,5,5,5,5,5,5,5,5,15,0.0,satisfied +15009,38077,Male,Loyal Customer,46,Business travel,Business,2599,1,5,5,5,3,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +15010,85142,Female,Loyal Customer,45,Business travel,Business,696,5,2,5,5,4,4,4,4,4,4,4,3,4,3,1,7.0,satisfied +15011,18454,Female,disloyal Customer,33,Business travel,Eco,190,2,0,2,1,1,2,1,1,5,3,3,3,5,1,0,0.0,neutral or dissatisfied +15012,112713,Female,disloyal Customer,36,Business travel,Eco,323,3,3,3,3,4,3,4,4,2,5,3,4,4,4,42,50.0,neutral or dissatisfied +15013,29138,Female,Loyal Customer,23,Personal Travel,Eco,954,3,5,3,4,3,3,3,3,4,5,5,4,4,3,0,0.0,neutral or dissatisfied +15014,6791,Female,Loyal Customer,27,Business travel,Business,1960,2,4,3,4,2,2,2,2,4,5,3,2,3,2,20,13.0,neutral or dissatisfied +15015,90261,Female,Loyal Customer,58,Business travel,Business,3516,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +15016,104556,Female,Loyal Customer,49,Business travel,Business,3114,1,1,1,1,2,4,5,5,5,5,5,4,5,4,30,23.0,satisfied +15017,30199,Female,Loyal Customer,39,Business travel,Eco Plus,261,4,1,1,1,4,4,4,4,3,1,2,5,4,4,0,0.0,satisfied +15018,63057,Male,Loyal Customer,54,Personal Travel,Eco,862,2,3,2,4,4,2,5,4,1,4,4,1,3,4,0,0.0,neutral or dissatisfied +15019,123141,Male,Loyal Customer,48,Business travel,Business,3708,1,1,1,1,4,2,3,1,1,1,1,3,1,2,1,2.0,neutral or dissatisfied +15020,46467,Male,Loyal Customer,40,Business travel,Business,3821,3,3,3,3,2,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +15021,21948,Female,Loyal Customer,31,Business travel,Business,503,3,4,4,4,3,3,3,3,1,2,3,2,3,3,0,0.0,neutral or dissatisfied +15022,11631,Female,Loyal Customer,8,Personal Travel,Eco Plus,771,2,4,3,1,4,3,4,4,4,3,4,4,4,4,23,6.0,neutral or dissatisfied +15023,69647,Female,Loyal Customer,48,Business travel,Business,569,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +15024,15013,Female,Loyal Customer,51,Business travel,Eco,557,4,5,5,5,4,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +15025,61019,Female,Loyal Customer,45,Business travel,Business,1802,2,2,2,2,4,4,4,1,3,2,5,4,3,4,19,74.0,satisfied +15026,7189,Female,disloyal Customer,24,Business travel,Eco,135,1,2,1,3,1,1,1,1,4,4,4,1,4,1,5,2.0,neutral or dissatisfied +15027,87764,Male,Loyal Customer,46,Business travel,Business,214,2,2,2,2,3,5,4,5,5,5,4,4,5,5,0,10.0,satisfied +15028,88030,Male,Loyal Customer,54,Business travel,Business,2837,2,2,2,2,2,4,4,5,5,5,5,5,5,4,19,19.0,satisfied +15029,71058,Female,Loyal Customer,44,Personal Travel,Eco,802,4,3,4,3,5,2,3,2,2,4,2,1,2,4,103,108.0,satisfied +15030,106465,Male,Loyal Customer,41,Business travel,Business,1300,1,1,1,1,3,4,5,5,5,5,5,5,5,3,9,0.0,satisfied +15031,8068,Female,disloyal Customer,58,Business travel,Eco,335,2,2,2,4,2,2,2,2,4,1,3,4,3,2,0,4.0,neutral or dissatisfied +15032,47692,Female,Loyal Customer,14,Personal Travel,Eco,1242,1,4,1,1,1,1,1,1,3,2,4,5,4,1,1,0.0,neutral or dissatisfied +15033,76219,Female,Loyal Customer,32,Business travel,Business,1399,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +15034,101115,Male,Loyal Customer,45,Business travel,Business,583,2,2,2,2,5,5,5,4,4,4,4,4,4,5,16,15.0,satisfied +15035,118501,Female,disloyal Customer,22,Business travel,Eco,369,2,4,2,3,5,2,5,5,3,4,4,4,5,5,17,9.0,neutral or dissatisfied +15036,11557,Female,Loyal Customer,36,Business travel,Business,2303,3,3,3,3,3,4,5,4,4,4,4,3,4,4,10,0.0,satisfied +15037,29736,Male,Loyal Customer,58,Business travel,Business,1731,3,3,3,3,3,4,4,4,4,4,4,5,4,3,12,12.0,satisfied +15038,76770,Female,disloyal Customer,16,Business travel,Business,689,5,0,5,3,1,5,1,1,4,4,5,5,4,1,0,0.0,satisfied +15039,49738,Male,Loyal Customer,30,Business travel,Business,2121,3,3,3,3,5,5,3,5,2,2,1,4,1,5,10,10.0,satisfied +15040,35205,Female,Loyal Customer,23,Business travel,Business,1056,1,1,1,1,4,4,4,4,3,1,3,2,4,4,0,0.0,satisfied +15041,3202,Male,Loyal Customer,69,Personal Travel,Eco,585,3,4,3,3,4,3,4,4,4,5,5,5,4,4,33,20.0,neutral or dissatisfied +15042,4045,Female,Loyal Customer,63,Personal Travel,Eco,419,3,2,3,4,4,3,3,3,3,3,3,3,3,2,19,23.0,neutral or dissatisfied +15043,110929,Female,Loyal Customer,8,Personal Travel,Eco,581,2,5,2,1,4,2,4,4,5,3,4,4,5,4,0,5.0,neutral or dissatisfied +15044,65883,Female,Loyal Customer,32,Business travel,Eco Plus,1389,3,2,3,3,3,3,3,3,3,1,3,4,4,3,72,53.0,neutral or dissatisfied +15045,129733,Male,disloyal Customer,23,Business travel,Business,337,5,3,5,2,5,5,5,5,3,2,5,5,5,5,0,12.0,satisfied +15046,104531,Male,Loyal Customer,52,Business travel,Business,1047,3,3,3,3,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15047,109935,Male,Loyal Customer,69,Personal Travel,Eco,1052,1,4,1,4,5,1,2,5,3,4,5,3,4,5,70,58.0,neutral or dissatisfied +15048,107226,Male,Loyal Customer,12,Personal Travel,Eco,1751,2,5,2,3,2,2,2,2,1,4,3,3,4,2,1,0.0,neutral or dissatisfied +15049,30968,Male,Loyal Customer,38,Personal Travel,Eco Plus,1024,3,2,3,2,5,3,1,5,3,2,3,1,3,5,10,14.0,neutral or dissatisfied +15050,55214,Male,disloyal Customer,38,Business travel,Business,1009,2,2,2,1,1,2,1,1,4,2,5,3,4,1,35,17.0,neutral or dissatisfied +15051,19794,Male,Loyal Customer,67,Personal Travel,Eco,760,3,5,3,3,1,3,1,1,1,5,3,4,1,1,6,0.0,neutral or dissatisfied +15052,113159,Female,disloyal Customer,11,Business travel,Eco,677,4,4,4,2,2,4,2,2,3,5,4,5,5,2,18,3.0,neutral or dissatisfied +15053,116173,Female,Loyal Customer,40,Personal Travel,Eco,325,5,2,5,4,5,5,5,5,2,1,3,1,4,5,0,1.0,satisfied +15054,102397,Female,disloyal Customer,50,Business travel,Eco,223,3,4,3,3,2,3,3,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +15055,37737,Male,Loyal Customer,16,Personal Travel,Eco,944,1,2,1,2,2,1,2,2,2,1,2,3,2,2,0,0.0,neutral or dissatisfied +15056,38052,Female,Loyal Customer,58,Business travel,Eco,1197,2,1,5,1,3,3,3,2,2,2,2,4,2,3,20,2.0,neutral or dissatisfied +15057,23861,Male,Loyal Customer,61,Personal Travel,Eco,522,1,4,1,1,2,1,2,2,4,2,4,5,4,2,0,0.0,neutral or dissatisfied +15058,112414,Male,Loyal Customer,37,Business travel,Eco,819,4,2,2,2,4,4,4,4,4,4,3,3,3,4,12,8.0,neutral or dissatisfied +15059,90131,Female,Loyal Customer,38,Business travel,Business,2188,2,5,5,5,2,2,2,3,3,3,3,2,2,2,133,121.0,neutral or dissatisfied +15060,87088,Female,Loyal Customer,22,Business travel,Eco,594,4,1,1,1,4,4,5,4,3,1,2,5,3,4,36,23.0,satisfied +15061,51141,Male,Loyal Customer,9,Personal Travel,Eco,447,4,5,5,1,5,5,3,5,3,4,5,5,4,5,0,0.0,neutral or dissatisfied +15062,70443,Male,Loyal Customer,35,Business travel,Business,2569,0,4,0,4,5,3,4,5,5,1,1,1,5,2,0,5.0,satisfied +15063,95787,Male,Loyal Customer,45,Personal Travel,Eco,237,1,4,1,3,4,1,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +15064,92648,Male,Loyal Customer,58,Personal Travel,Eco,453,1,5,1,1,1,1,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +15065,111244,Female,Loyal Customer,58,Business travel,Business,1849,3,3,3,3,5,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +15066,104979,Male,Loyal Customer,42,Business travel,Business,2351,0,0,0,3,4,5,4,3,3,1,1,4,3,3,0,0.0,satisfied +15067,24051,Male,Loyal Customer,33,Personal Travel,Eco,427,3,4,3,3,2,3,2,2,4,2,4,1,1,2,28,42.0,neutral or dissatisfied +15068,74147,Female,Loyal Customer,44,Business travel,Business,769,3,3,3,3,5,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +15069,106656,Female,Loyal Customer,40,Business travel,Business,1590,2,2,3,2,3,5,4,4,4,4,4,3,4,4,13,20.0,satisfied +15070,93055,Female,Loyal Customer,43,Business travel,Business,297,1,1,2,1,5,5,5,5,5,5,5,3,5,3,10,0.0,satisfied +15071,1073,Female,Loyal Customer,38,Personal Travel,Eco,102,2,4,2,3,1,2,1,1,3,5,5,4,4,1,3,0.0,neutral or dissatisfied +15072,128351,Male,Loyal Customer,44,Business travel,Business,2694,1,1,1,1,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15073,61374,Male,disloyal Customer,18,Business travel,Business,679,5,3,4,3,2,4,2,2,5,4,5,5,4,2,0,0.0,satisfied +15074,94353,Female,disloyal Customer,61,Business travel,Business,323,1,1,1,5,5,1,5,5,3,3,4,5,5,5,0,0.0,neutral or dissatisfied +15075,52806,Male,Loyal Customer,55,Personal Travel,Business,2402,1,0,1,4,2,5,4,2,2,1,2,3,2,3,60,106.0,neutral or dissatisfied +15076,16829,Male,Loyal Customer,63,Personal Travel,Eco,645,2,1,2,4,3,2,2,3,2,2,3,1,4,3,0,0.0,neutral or dissatisfied +15077,16171,Female,Loyal Customer,44,Business travel,Eco,277,5,3,3,3,5,5,5,4,4,3,3,5,2,5,420,407.0,satisfied +15078,122204,Female,Loyal Customer,43,Business travel,Business,2204,3,1,4,1,2,3,3,3,3,4,3,1,3,1,0,10.0,neutral or dissatisfied +15079,89347,Female,disloyal Customer,60,Business travel,Eco,1587,1,1,1,3,2,1,2,2,3,3,3,2,3,2,0,11.0,neutral or dissatisfied +15080,98590,Female,disloyal Customer,28,Business travel,Business,861,3,3,3,3,1,3,1,1,3,5,4,4,4,1,87,65.0,neutral or dissatisfied +15081,102448,Male,Loyal Customer,52,Personal Travel,Eco,414,4,1,4,2,3,4,3,3,4,5,2,4,2,3,3,0.0,neutral or dissatisfied +15082,5318,Female,Loyal Customer,19,Business travel,Eco Plus,383,2,2,2,2,2,2,4,2,1,1,3,4,3,2,18,41.0,neutral or dissatisfied +15083,85403,Female,Loyal Customer,44,Business travel,Business,152,0,4,0,5,4,4,5,1,1,1,1,5,1,4,14,0.0,satisfied +15084,1112,Female,Loyal Customer,26,Personal Travel,Eco,102,4,4,4,3,2,4,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +15085,127109,Male,Loyal Customer,29,Personal Travel,Eco,621,2,1,2,3,3,2,3,3,1,4,2,1,3,3,4,0.0,neutral or dissatisfied +15086,49656,Male,Loyal Customer,38,Business travel,Business,262,0,0,0,2,1,4,5,3,3,3,3,3,3,5,0,7.0,satisfied +15087,116500,Male,Loyal Customer,25,Personal Travel,Eco,337,4,3,4,4,1,4,1,1,4,1,3,1,3,1,68,63.0,neutral or dissatisfied +15088,104115,Female,Loyal Customer,45,Business travel,Business,2737,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +15089,23784,Male,Loyal Customer,42,Business travel,Business,3874,3,3,3,3,4,5,2,5,5,5,5,1,5,3,16,12.0,satisfied +15090,20366,Female,Loyal Customer,9,Personal Travel,Eco,287,2,2,2,3,1,2,1,1,2,5,3,1,3,1,2,5.0,neutral or dissatisfied +15091,121082,Female,Loyal Customer,9,Personal Travel,Eco Plus,920,3,5,4,3,2,4,3,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +15092,106858,Female,Loyal Customer,55,Business travel,Business,577,4,4,4,4,2,4,4,3,3,3,3,3,3,5,11,0.0,satisfied +15093,113119,Male,Loyal Customer,25,Personal Travel,Eco,479,3,4,3,3,5,3,5,5,1,3,3,4,4,5,99,90.0,neutral or dissatisfied +15094,10203,Male,Loyal Customer,40,Business travel,Business,2025,4,4,4,4,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +15095,50323,Female,Loyal Customer,23,Business travel,Business,2670,5,5,5,5,5,5,5,5,1,3,2,4,4,5,0,0.0,satisfied +15096,72131,Female,Loyal Customer,34,Business travel,Business,2129,3,3,5,3,3,4,4,3,3,3,3,3,3,3,5,0.0,neutral or dissatisfied +15097,36290,Female,Loyal Customer,38,Business travel,Business,2008,5,5,2,5,4,4,5,5,5,4,5,3,5,2,22,33.0,satisfied +15098,33297,Male,Loyal Customer,13,Personal Travel,Eco Plus,101,2,5,2,3,3,2,2,3,3,4,5,3,4,3,0,1.0,neutral or dissatisfied +15099,62294,Male,Loyal Customer,41,Business travel,Business,3660,1,1,1,1,3,5,5,3,3,4,3,4,3,4,0,0.0,satisfied +15100,97226,Female,Loyal Customer,20,Personal Travel,Eco Plus,1476,2,4,2,1,5,2,5,5,3,3,5,4,4,5,0,0.0,neutral or dissatisfied +15101,50236,Male,Loyal Customer,17,Business travel,Business,109,3,3,3,3,5,5,5,5,2,2,5,2,2,5,0,0.0,satisfied +15102,85147,Male,disloyal Customer,28,Business travel,Business,689,4,4,4,3,3,4,3,3,5,2,5,4,5,3,22,5.0,neutral or dissatisfied +15103,42785,Male,Loyal Customer,50,Business travel,Eco,1118,3,1,1,1,3,3,3,3,1,3,2,3,3,3,0,25.0,neutral or dissatisfied +15104,86420,Female,disloyal Customer,26,Business travel,Eco,760,3,3,3,4,1,3,1,1,3,3,4,3,3,1,0,0.0,neutral or dissatisfied +15105,129026,Female,Loyal Customer,25,Personal Travel,Eco,2704,2,2,2,3,2,3,5,2,4,4,3,5,1,5,152,191.0,neutral or dissatisfied +15106,35202,Female,Loyal Customer,40,Business travel,Eco,1011,4,3,5,3,4,4,4,4,4,4,1,3,5,4,0,0.0,satisfied +15107,95081,Male,Loyal Customer,61,Personal Travel,Eco,248,5,4,5,5,3,5,2,3,3,2,5,4,5,3,0,0.0,satisfied +15108,14666,Male,disloyal Customer,23,Business travel,Eco,430,4,3,4,2,3,4,3,3,5,4,3,1,3,3,0,0.0,satisfied +15109,52725,Female,Loyal Customer,48,Business travel,Eco,406,3,4,4,4,5,4,4,4,4,3,4,3,4,3,15,0.0,neutral or dissatisfied +15110,90823,Female,Loyal Customer,56,Business travel,Business,240,3,5,3,3,2,5,4,4,4,4,4,4,4,4,0,7.0,satisfied +15111,45768,Male,Loyal Customer,31,Business travel,Business,391,5,5,4,5,4,4,4,4,4,3,3,2,4,4,0,0.0,satisfied +15112,117481,Female,Loyal Customer,40,Business travel,Business,2218,3,3,3,3,5,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +15113,117874,Female,Loyal Customer,35,Business travel,Business,2987,2,2,2,2,2,4,4,5,5,5,5,4,5,3,6,0.0,satisfied +15114,99016,Male,Loyal Customer,29,Personal Travel,Eco Plus,479,3,5,3,3,1,3,1,1,4,4,4,5,4,1,0,3.0,neutral or dissatisfied +15115,67960,Male,Loyal Customer,41,Business travel,Business,1464,5,5,5,5,2,5,4,4,4,4,4,5,4,4,4,0.0,satisfied +15116,67539,Female,Loyal Customer,42,Business travel,Business,1205,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +15117,78138,Female,Loyal Customer,28,Business travel,Business,1768,0,0,0,2,4,4,4,4,4,2,5,3,4,4,6,17.0,satisfied +15118,99816,Male,Loyal Customer,55,Business travel,Business,2077,3,3,5,3,2,5,5,4,4,4,4,4,4,5,5,8.0,satisfied +15119,44799,Male,disloyal Customer,47,Business travel,Business,802,3,3,3,3,2,3,2,2,2,2,3,3,4,2,0,1.0,neutral or dissatisfied +15120,14748,Male,disloyal Customer,39,Business travel,Eco,463,1,2,1,3,5,1,5,5,2,4,3,1,4,5,51,111.0,neutral or dissatisfied +15121,103298,Female,Loyal Customer,63,Personal Travel,Business,1371,3,4,2,1,5,3,4,1,1,2,1,4,1,3,24,21.0,neutral or dissatisfied +15122,1358,Female,Loyal Customer,63,Business travel,Business,113,5,2,5,5,5,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +15123,26126,Female,Loyal Customer,30,Business travel,Eco,404,5,2,2,2,5,5,5,5,2,5,3,4,5,5,0,0.0,satisfied +15124,20984,Male,Loyal Customer,43,Personal Travel,Eco,803,2,5,2,1,2,2,2,2,5,2,3,1,5,2,0,0.0,neutral or dissatisfied +15125,50250,Female,Loyal Customer,43,Business travel,Eco,153,3,3,3,3,5,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +15126,56912,Male,disloyal Customer,41,Business travel,Business,1209,4,4,4,4,4,4,4,5,4,3,4,4,4,4,158,177.0,satisfied +15127,6526,Male,Loyal Customer,28,Personal Travel,Eco,646,4,3,4,3,2,4,2,2,4,2,3,4,3,2,4,0.0,neutral or dissatisfied +15128,16840,Female,Loyal Customer,66,Personal Travel,Eco,645,3,1,3,3,2,4,4,3,3,3,4,3,3,4,0,1.0,neutral or dissatisfied +15129,81008,Female,Loyal Customer,58,Business travel,Business,3747,2,2,2,2,5,5,5,5,5,5,5,5,5,5,0,31.0,satisfied +15130,79793,Female,Loyal Customer,50,Business travel,Business,2274,4,4,4,4,5,4,4,4,4,4,4,3,4,4,0,17.0,satisfied +15131,64848,Male,Loyal Customer,27,Business travel,Eco,282,2,1,1,1,2,2,2,2,4,2,2,4,3,2,112,108.0,neutral or dissatisfied +15132,73899,Female,disloyal Customer,25,Business travel,Business,2218,1,0,1,3,4,1,4,4,5,4,4,4,4,4,2,6.0,neutral or dissatisfied +15133,105730,Female,Loyal Customer,25,Business travel,Business,1892,2,2,2,2,2,2,2,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +15134,54183,Female,Loyal Customer,49,Business travel,Business,1000,2,3,3,3,1,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +15135,120911,Female,disloyal Customer,42,Business travel,Business,861,3,3,3,1,5,3,5,5,4,2,4,4,4,5,32,23.0,satisfied +15136,120439,Female,Loyal Customer,37,Business travel,Eco,366,3,5,5,5,3,3,3,3,4,2,3,5,1,3,0,0.0,satisfied +15137,116771,Male,Loyal Customer,18,Personal Travel,Eco Plus,390,4,5,4,3,2,4,2,2,2,4,4,4,5,2,0,0.0,neutral or dissatisfied +15138,29965,Female,Loyal Customer,37,Business travel,Business,261,4,4,4,4,4,3,1,5,5,5,5,5,5,2,0,0.0,satisfied +15139,35513,Female,Loyal Customer,43,Personal Travel,Eco,1076,1,5,1,3,4,5,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +15140,66661,Male,Loyal Customer,45,Business travel,Business,978,1,1,1,1,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +15141,40517,Female,Loyal Customer,58,Business travel,Eco Plus,175,3,3,3,3,5,3,3,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +15142,103700,Male,Loyal Customer,42,Personal Travel,Eco,405,0,5,0,4,4,0,4,4,4,4,5,5,4,4,0,0.0,satisfied +15143,86736,Male,Loyal Customer,18,Personal Travel,Eco Plus,1747,2,3,2,4,1,2,1,1,3,2,3,1,3,1,28,44.0,neutral or dissatisfied +15144,75746,Male,Loyal Customer,39,Business travel,Business,1915,1,1,1,1,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +15145,87669,Male,disloyal Customer,21,Business travel,Eco,591,1,4,1,3,2,1,2,2,1,5,3,2,3,2,0,27.0,neutral or dissatisfied +15146,106070,Male,Loyal Customer,58,Personal Travel,Business,302,3,3,3,2,4,5,5,1,1,3,1,3,1,1,11,11.0,neutral or dissatisfied +15147,37944,Male,Loyal Customer,15,Business travel,Eco Plus,1068,4,5,4,5,4,4,4,4,1,4,5,1,2,4,2,0.0,satisfied +15148,56226,Male,Loyal Customer,54,Personal Travel,Eco,1585,2,5,2,1,5,2,5,5,5,5,4,3,5,5,19,14.0,neutral or dissatisfied +15149,106481,Female,Loyal Customer,43,Personal Travel,Eco,1624,3,3,3,3,3,1,3,3,3,3,3,4,3,3,45,55.0,neutral or dissatisfied +15150,55145,Male,Loyal Customer,66,Personal Travel,Eco,1379,4,3,4,3,4,4,4,4,1,3,2,4,3,4,15,5.0,satisfied +15151,125090,Female,disloyal Customer,34,Business travel,Eco,361,3,4,4,4,1,4,1,1,4,1,4,2,3,1,22,12.0,neutral or dissatisfied +15152,102976,Female,Loyal Customer,54,Business travel,Business,490,5,5,5,5,2,5,5,5,5,4,5,5,5,3,0,0.0,satisfied +15153,1149,Female,Loyal Customer,63,Personal Travel,Eco,282,1,5,1,4,3,4,4,4,4,1,4,3,4,4,35,28.0,neutral or dissatisfied +15154,76082,Male,Loyal Customer,43,Business travel,Eco,269,4,4,4,4,4,4,4,4,2,3,1,4,1,4,0,0.0,satisfied +15155,47961,Male,Loyal Customer,45,Personal Travel,Eco,550,3,0,3,2,3,3,3,3,4,5,4,3,5,3,0,0.0,neutral or dissatisfied +15156,25651,Female,Loyal Customer,27,Personal Travel,Eco,526,4,5,4,4,5,4,5,5,5,4,4,4,5,5,0,0.0,satisfied +15157,52101,Female,Loyal Customer,64,Personal Travel,Eco,438,3,4,3,4,3,4,5,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +15158,35629,Female,Loyal Customer,67,Personal Travel,Eco Plus,1035,2,5,2,1,4,5,4,1,1,2,1,3,1,3,0,0.0,neutral or dissatisfied +15159,14826,Female,Loyal Customer,44,Business travel,Eco,314,4,3,3,3,3,3,2,3,3,4,3,1,3,4,0,0.0,satisfied +15160,72117,Female,Loyal Customer,51,Business travel,Business,3756,2,5,2,2,3,4,5,2,2,3,2,3,2,3,0,0.0,satisfied +15161,76460,Female,Loyal Customer,25,Personal Travel,Business,547,2,4,2,3,4,2,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +15162,5548,Male,Loyal Customer,48,Personal Travel,Eco,431,2,4,2,1,5,2,2,5,5,3,4,3,4,5,0,0.0,neutral or dissatisfied +15163,23305,Male,disloyal Customer,34,Business travel,Business,359,2,2,2,1,1,2,1,1,3,3,2,5,2,1,9,4.0,neutral or dissatisfied +15164,12584,Female,Loyal Customer,49,Business travel,Eco,542,5,5,5,5,1,2,2,5,5,5,5,5,5,3,0,0.0,satisfied +15165,32242,Male,Loyal Customer,28,Business travel,Eco,102,4,4,4,4,4,4,4,4,3,5,1,4,5,4,0,0.0,satisfied +15166,20491,Female,disloyal Customer,38,Business travel,Eco,139,2,2,2,3,3,2,3,3,4,2,4,2,3,3,6,11.0,neutral or dissatisfied +15167,66048,Male,Loyal Customer,44,Business travel,Business,2234,3,1,2,1,1,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +15168,104917,Male,Loyal Customer,56,Business travel,Business,1800,4,3,4,4,3,5,4,5,5,5,5,5,5,5,17,15.0,satisfied +15169,52803,Female,Loyal Customer,40,Personal Travel,Eco Plus,1874,4,5,4,4,2,4,2,2,4,1,1,1,2,2,3,4.0,satisfied +15170,98652,Female,disloyal Customer,59,Business travel,Eco,520,2,2,2,3,1,2,1,1,3,1,3,4,3,1,38,105.0,neutral or dissatisfied +15171,109177,Male,Loyal Customer,40,Business travel,Eco,612,1,3,3,3,1,2,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +15172,37879,Female,disloyal Customer,25,Business travel,Eco,1023,2,2,2,3,1,2,1,1,1,4,3,2,4,1,0,0.0,neutral or dissatisfied +15173,99040,Female,Loyal Customer,59,Business travel,Business,181,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +15174,113391,Female,Loyal Customer,41,Business travel,Business,2736,2,2,2,2,5,5,4,5,5,5,5,3,5,3,0,2.0,satisfied +15175,23676,Male,disloyal Customer,22,Business travel,Eco,73,4,0,4,2,2,4,1,2,1,3,1,1,5,2,0,0.0,satisfied +15176,21819,Female,Loyal Customer,39,Business travel,Eco Plus,241,4,2,2,2,4,4,4,4,2,3,5,1,5,4,0,0.0,satisfied +15177,68763,Female,disloyal Customer,28,Business travel,Business,926,5,5,5,4,3,5,3,3,3,5,5,4,4,3,0,0.0,satisfied +15178,118074,Female,Loyal Customer,51,Business travel,Business,1276,5,5,5,5,3,5,4,4,4,5,4,5,4,4,46,37.0,satisfied +15179,123763,Male,disloyal Customer,23,Business travel,Eco,544,5,0,5,4,1,5,1,1,5,5,4,4,4,1,27,44.0,satisfied +15180,127256,Female,Loyal Customer,52,Business travel,Business,3701,5,5,3,5,2,4,5,4,4,4,4,4,4,5,15,4.0,satisfied +15181,114633,Female,disloyal Customer,34,Business travel,Business,371,3,3,3,5,5,3,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +15182,108221,Female,Loyal Customer,46,Personal Travel,Eco,777,3,4,3,3,4,4,5,5,5,3,5,5,5,5,2,8.0,neutral or dissatisfied +15183,43321,Male,Loyal Customer,42,Business travel,Business,3508,3,3,3,3,5,2,2,4,4,4,4,4,4,2,0,0.0,satisfied +15184,123233,Female,Loyal Customer,43,Personal Travel,Eco,600,2,2,2,1,2,2,2,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +15185,97454,Male,Loyal Customer,54,Business travel,Business,670,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,7.0,satisfied +15186,51259,Male,Loyal Customer,63,Business travel,Eco Plus,110,4,4,4,4,4,4,4,4,3,1,4,5,3,4,0,0.0,satisfied +15187,13651,Female,disloyal Customer,25,Business travel,Eco,196,0,0,0,4,2,0,2,2,4,4,2,3,5,2,0,0.0,satisfied +15188,80538,Female,Loyal Customer,27,Business travel,Business,1747,5,5,5,5,5,5,5,5,3,2,3,4,5,5,0,0.0,satisfied +15189,54498,Male,Loyal Customer,47,Business travel,Business,3645,3,2,3,3,3,1,2,4,4,4,4,3,4,1,11,3.0,satisfied +15190,112647,Female,Loyal Customer,20,Business travel,Business,1756,4,3,1,3,4,3,4,4,4,4,3,3,4,4,0,2.0,neutral or dissatisfied +15191,24227,Female,Loyal Customer,54,Business travel,Business,147,2,2,3,2,3,4,5,5,5,5,3,1,5,4,0,0.0,satisfied +15192,76546,Female,Loyal Customer,52,Business travel,Business,481,1,1,1,1,4,4,4,5,5,5,5,3,5,3,3,0.0,satisfied +15193,82067,Male,disloyal Customer,36,Business travel,Business,1276,3,3,3,4,1,3,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +15194,30246,Female,Loyal Customer,36,Business travel,Eco Plus,896,4,3,3,3,4,4,4,4,1,5,2,5,3,4,7,4.0,satisfied +15195,84260,Male,Loyal Customer,37,Business travel,Business,334,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +15196,7302,Male,Loyal Customer,63,Business travel,Business,135,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +15197,10973,Male,disloyal Customer,27,Business travel,Business,224,3,3,3,1,5,3,5,5,2,4,1,2,1,5,5,5.0,neutral or dissatisfied +15198,64405,Female,Loyal Customer,48,Business travel,Business,3713,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15199,99850,Female,Loyal Customer,62,Personal Travel,Eco,468,2,4,2,5,3,4,5,1,1,2,1,3,1,3,2,18.0,neutral or dissatisfied +15200,22971,Male,disloyal Customer,27,Business travel,Eco,817,3,3,3,3,4,3,4,4,1,2,5,4,5,4,0,0.0,neutral or dissatisfied +15201,106501,Male,Loyal Customer,59,Personal Travel,Eco,495,4,4,4,2,3,4,3,3,4,4,5,4,4,3,12,12.0,neutral or dissatisfied +15202,115085,Male,disloyal Customer,16,Business travel,Eco,362,2,4,2,4,3,2,2,3,4,5,4,3,3,3,16,11.0,neutral or dissatisfied +15203,80446,Male,Loyal Customer,57,Business travel,Business,2248,3,3,3,3,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +15204,47170,Female,Loyal Customer,49,Business travel,Eco,954,2,3,3,3,1,4,4,2,2,2,2,3,2,1,40,63.0,neutral or dissatisfied +15205,103857,Female,Loyal Customer,8,Personal Travel,Eco,882,2,3,2,3,4,2,4,4,4,1,3,4,4,4,72,81.0,neutral or dissatisfied +15206,77068,Female,Loyal Customer,44,Business travel,Business,3215,3,4,4,4,1,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +15207,8424,Female,Loyal Customer,54,Business travel,Business,862,3,3,3,3,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15208,121348,Male,Loyal Customer,68,Personal Travel,Eco,430,4,5,2,5,1,2,1,1,3,2,5,4,5,1,9,20.0,satisfied +15209,111761,Male,Loyal Customer,56,Business travel,Eco,1036,2,4,4,4,2,2,2,2,4,3,4,4,3,2,38,26.0,neutral or dissatisfied +15210,64112,Female,disloyal Customer,37,Business travel,Business,2288,3,3,3,3,1,3,1,1,3,3,3,3,4,1,10,0.0,satisfied +15211,41212,Female,disloyal Customer,27,Business travel,Eco,1091,2,2,2,2,2,2,2,2,4,4,4,2,1,2,0,0.0,neutral or dissatisfied +15212,17563,Male,Loyal Customer,27,Business travel,Business,1034,5,5,5,5,2,2,2,2,5,4,1,3,3,2,0,0.0,satisfied +15213,110067,Male,Loyal Customer,54,Business travel,Business,634,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +15214,22019,Female,Loyal Customer,26,Business travel,Eco Plus,503,5,2,2,2,5,5,4,5,5,3,3,3,2,5,0,0.0,satisfied +15215,101832,Female,Loyal Customer,21,Personal Travel,Eco,1521,1,4,1,3,1,1,1,1,1,3,3,2,4,1,0,0.0,neutral or dissatisfied +15216,11979,Female,Loyal Customer,43,Business travel,Business,643,2,2,2,2,4,3,3,5,5,5,5,5,5,1,62,56.0,satisfied +15217,10429,Female,Loyal Customer,48,Business travel,Business,312,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,2.0,satisfied +15218,48845,Female,Loyal Customer,63,Personal Travel,Business,308,1,4,1,4,4,5,4,1,1,1,5,3,1,3,0,0.0,neutral or dissatisfied +15219,27110,Female,Loyal Customer,17,Business travel,Business,2677,1,1,1,1,4,4,4,3,3,4,4,4,4,4,4,8.0,satisfied +15220,112825,Female,disloyal Customer,27,Business travel,Business,1390,4,4,4,1,2,4,2,2,3,5,4,3,4,2,8,0.0,satisfied +15221,59772,Female,disloyal Customer,20,Business travel,Eco,895,2,2,2,4,4,2,4,4,3,1,4,4,3,4,26,10.0,neutral or dissatisfied +15222,112838,Male,disloyal Customer,26,Business travel,Business,1476,1,1,1,5,1,1,1,1,5,3,4,5,4,1,4,0.0,neutral or dissatisfied +15223,35626,Female,Loyal Customer,47,Personal Travel,Eco Plus,1041,3,5,3,3,5,4,4,3,3,3,3,3,3,4,0,8.0,neutral or dissatisfied +15224,26512,Male,Loyal Customer,20,Personal Travel,Eco Plus,829,0,4,0,4,3,4,3,3,4,4,5,3,5,3,26,32.0,satisfied +15225,68140,Male,Loyal Customer,77,Business travel,Eco Plus,413,1,4,4,4,1,1,1,1,4,1,3,1,3,1,5,3.0,neutral or dissatisfied +15226,128784,Female,Loyal Customer,44,Personal Travel,Eco,2248,2,3,3,4,3,1,1,1,4,3,1,1,3,1,161,165.0,neutral or dissatisfied +15227,19341,Female,Loyal Customer,59,Personal Travel,Eco,694,1,4,0,2,4,5,5,2,2,0,2,4,2,3,4,0.0,neutral or dissatisfied +15228,47415,Female,Loyal Customer,25,Business travel,Business,532,1,1,3,1,4,4,4,4,2,5,3,5,1,4,0,0.0,satisfied +15229,107430,Female,Loyal Customer,29,Personal Travel,Eco,725,3,3,3,3,1,3,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +15230,95605,Male,Loyal Customer,22,Business travel,Business,3462,4,4,4,4,4,4,4,4,5,5,5,3,4,4,0,0.0,satisfied +15231,95391,Female,Loyal Customer,18,Personal Travel,Eco,187,3,5,3,3,2,3,5,2,4,4,4,4,4,2,89,75.0,neutral or dissatisfied +15232,10034,Male,Loyal Customer,44,Business travel,Eco,630,2,4,4,4,2,2,2,1,3,3,3,2,2,2,182,187.0,neutral or dissatisfied +15233,8962,Female,disloyal Customer,17,Business travel,Eco,812,5,4,4,3,3,4,3,3,5,2,2,4,5,3,0,0.0,satisfied +15234,73627,Male,Loyal Customer,28,Business travel,Business,2763,1,5,5,5,3,3,1,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +15235,75586,Female,Loyal Customer,44,Business travel,Business,337,2,3,3,3,5,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +15236,74649,Male,Loyal Customer,68,Personal Travel,Eco,1464,3,5,3,1,1,3,1,1,4,3,3,4,4,1,0,3.0,neutral or dissatisfied +15237,34654,Male,Loyal Customer,52,Personal Travel,Eco Plus,427,3,5,3,4,2,3,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +15238,68323,Male,disloyal Customer,43,Business travel,Eco,881,2,2,2,4,5,2,5,5,1,1,4,4,3,5,0,0.0,neutral or dissatisfied +15239,68265,Male,Loyal Customer,45,Personal Travel,Eco,631,2,5,2,3,4,2,2,4,5,5,5,4,5,4,0,10.0,neutral or dissatisfied +15240,98118,Female,Loyal Customer,44,Business travel,Business,2041,4,5,4,5,1,2,3,4,4,4,4,4,4,4,14,2.0,neutral or dissatisfied +15241,102358,Male,Loyal Customer,46,Business travel,Business,223,0,4,0,3,4,4,4,1,1,1,1,3,1,4,4,0.0,satisfied +15242,95593,Male,Loyal Customer,47,Business travel,Business,3175,4,4,4,4,2,4,5,3,3,3,3,3,3,4,5,0.0,satisfied +15243,95453,Male,Loyal Customer,42,Business travel,Business,3789,5,5,5,5,2,4,5,5,5,4,5,4,5,3,13,15.0,satisfied +15244,121501,Male,Loyal Customer,13,Personal Travel,Eco Plus,257,1,1,0,3,1,0,1,1,3,2,2,3,3,1,2,1.0,neutral or dissatisfied +15245,63573,Male,Loyal Customer,40,Business travel,Business,1737,2,2,2,2,3,4,5,4,4,5,4,5,4,5,0,0.0,satisfied +15246,100099,Male,disloyal Customer,22,Business travel,Eco,725,5,5,5,1,4,5,4,4,5,5,4,4,5,4,0,0.0,satisfied +15247,121084,Male,Loyal Customer,47,Business travel,Business,2013,1,1,1,1,2,5,4,4,4,4,4,4,4,4,14,8.0,satisfied +15248,36944,Female,Loyal Customer,23,Business travel,Business,718,4,4,4,4,4,4,4,4,3,1,5,5,1,4,0,0.0,satisfied +15249,10487,Male,Loyal Customer,54,Business travel,Business,2322,4,4,4,4,3,4,5,4,4,4,4,5,4,5,0,1.0,satisfied +15250,114879,Female,Loyal Customer,43,Business travel,Business,3930,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +15251,83186,Female,disloyal Customer,41,Business travel,Business,149,3,3,3,4,3,3,3,3,1,5,4,1,1,3,14,2.0,neutral or dissatisfied +15252,96367,Female,Loyal Customer,52,Business travel,Business,1246,2,1,2,2,5,4,5,5,5,5,5,3,5,4,68,51.0,satisfied +15253,47258,Male,Loyal Customer,44,Business travel,Business,3762,3,2,2,2,3,4,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +15254,41857,Female,Loyal Customer,51,Business travel,Eco,300,4,1,1,1,2,2,5,4,4,4,4,2,4,1,0,0.0,satisfied +15255,117791,Female,Loyal Customer,40,Business travel,Business,3275,5,5,5,5,2,5,5,4,4,4,4,5,4,4,1,0.0,satisfied +15256,78935,Female,Loyal Customer,69,Business travel,Eco,100,5,5,5,5,2,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +15257,43851,Male,Loyal Customer,37,Business travel,Eco,76,2,5,5,5,2,2,2,2,5,3,3,2,3,2,0,0.0,satisfied +15258,31015,Male,Loyal Customer,12,Personal Travel,Eco,391,4,5,4,5,3,4,3,3,3,5,5,3,5,3,54,51.0,satisfied +15259,84894,Female,Loyal Customer,69,Personal Travel,Eco,516,3,1,3,3,5,3,4,2,2,3,5,4,2,1,0,0.0,neutral or dissatisfied +15260,88930,Male,Loyal Customer,45,Business travel,Business,1199,2,2,2,2,2,5,5,5,5,5,5,4,5,4,43,34.0,satisfied +15261,129750,Male,Loyal Customer,38,Business travel,Eco,337,4,3,3,3,4,5,4,4,4,5,4,5,3,4,92,82.0,satisfied +15262,48261,Female,Loyal Customer,53,Personal Travel,Eco,414,1,2,1,4,1,3,4,3,3,1,4,4,3,3,0,0.0,neutral or dissatisfied +15263,77241,Female,Loyal Customer,58,Business travel,Business,1590,2,3,3,3,3,2,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +15264,85459,Female,Loyal Customer,42,Business travel,Business,1832,2,2,2,2,2,2,2,2,2,2,2,1,2,3,17,14.0,neutral or dissatisfied +15265,748,Male,Loyal Customer,54,Business travel,Business,2385,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15266,13006,Female,Loyal Customer,52,Business travel,Business,3021,2,4,4,4,1,4,4,2,2,2,2,3,2,2,1,13.0,neutral or dissatisfied +15267,89435,Female,Loyal Customer,35,Personal Travel,Eco,151,2,4,2,3,4,2,4,4,3,3,4,3,5,4,5,0.0,neutral or dissatisfied +15268,51942,Male,Loyal Customer,54,Business travel,Eco,347,5,2,4,2,5,5,5,5,3,4,3,3,3,5,0,3.0,satisfied +15269,63959,Male,Loyal Customer,46,Personal Travel,Eco,1192,4,4,4,3,1,4,1,1,5,3,4,5,5,1,2,0.0,satisfied +15270,45667,Female,Loyal Customer,12,Personal Travel,Eco Plus,260,1,3,1,3,4,1,4,4,3,1,2,1,5,4,0,3.0,neutral or dissatisfied +15271,119899,Female,Loyal Customer,45,Business travel,Business,936,2,2,2,2,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +15272,49555,Male,Loyal Customer,46,Business travel,Business,3932,4,4,4,4,1,2,1,3,3,3,3,5,3,4,10,7.0,satisfied +15273,91759,Male,Loyal Customer,59,Business travel,Business,3582,4,4,4,4,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +15274,114544,Male,Loyal Customer,63,Personal Travel,Business,342,2,5,3,1,2,5,4,4,4,3,4,3,4,4,9,8.0,neutral or dissatisfied +15275,90780,Female,Loyal Customer,48,Business travel,Business,3249,0,0,0,1,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +15276,39643,Male,Loyal Customer,77,Business travel,Business,3937,3,5,5,5,5,4,4,3,3,3,3,2,3,3,39,50.0,neutral or dissatisfied +15277,59946,Female,disloyal Customer,27,Business travel,Eco,1065,3,3,3,4,1,3,1,1,1,3,3,3,4,1,0,0.0,neutral or dissatisfied +15278,80500,Male,Loyal Customer,58,Business travel,Business,1749,4,4,5,4,4,4,5,2,2,2,2,4,2,3,10,0.0,satisfied +15279,71313,Female,disloyal Customer,23,Business travel,Eco,1185,1,1,1,3,1,1,1,1,3,3,4,4,4,1,14,4.0,neutral or dissatisfied +15280,99314,Male,Loyal Customer,40,Business travel,Business,337,3,3,3,3,3,4,4,5,5,4,5,5,5,4,0,1.0,satisfied +15281,17221,Male,Loyal Customer,64,Personal Travel,Business,872,3,3,3,4,5,3,3,5,5,3,5,2,5,2,0,0.0,neutral or dissatisfied +15282,120836,Male,Loyal Customer,25,Business travel,Business,920,5,5,5,5,5,4,5,5,4,5,5,3,4,5,0,6.0,satisfied +15283,86772,Male,disloyal Customer,23,Business travel,Eco,692,5,5,5,2,3,5,4,3,3,5,5,3,4,3,0,0.0,satisfied +15284,85867,Male,Loyal Customer,22,Personal Travel,Business,2172,2,4,1,3,1,1,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +15285,119846,Female,Loyal Customer,15,Business travel,Business,3588,2,4,2,4,2,2,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +15286,9638,Male,disloyal Customer,23,Business travel,Business,212,5,0,5,2,4,5,4,4,3,3,5,5,4,4,0,0.0,satisfied +15287,85717,Male,Loyal Customer,48,Business travel,Business,1895,5,5,5,5,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +15288,123021,Male,Loyal Customer,58,Business travel,Business,590,1,1,3,1,3,5,4,1,1,2,1,3,1,4,0,4.0,satisfied +15289,85026,Female,Loyal Customer,41,Personal Travel,Eco,1590,4,5,4,5,1,4,1,1,4,3,5,5,4,1,9,0.0,neutral or dissatisfied +15290,77046,Female,Loyal Customer,40,Business travel,Business,3124,5,5,5,5,2,4,5,3,3,4,3,5,3,3,0,0.0,satisfied +15291,15046,Female,Loyal Customer,41,Business travel,Business,576,1,3,3,3,5,2,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +15292,123446,Male,disloyal Customer,36,Business travel,Business,2125,1,1,1,5,2,1,2,2,3,4,4,4,5,2,6,0.0,neutral or dissatisfied +15293,43636,Female,Loyal Customer,52,Personal Travel,Business,852,4,1,4,4,3,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +15294,35294,Female,Loyal Customer,46,Business travel,Business,1545,1,1,1,1,3,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +15295,49408,Female,Loyal Customer,56,Business travel,Eco,109,2,5,5,5,3,4,1,1,1,2,1,4,1,5,25,18.0,satisfied +15296,10211,Male,Loyal Customer,53,Business travel,Business,396,2,2,2,2,5,5,4,5,5,5,5,3,5,5,6,18.0,satisfied +15297,69278,Male,Loyal Customer,22,Personal Travel,Eco,740,2,1,2,2,5,2,5,5,1,5,1,4,2,5,0,0.0,neutral or dissatisfied +15298,95454,Male,Loyal Customer,48,Business travel,Business,2572,5,5,5,5,4,4,5,5,5,5,5,3,5,3,63,69.0,satisfied +15299,19379,Female,Loyal Customer,43,Business travel,Eco,844,3,2,2,2,4,1,3,3,3,3,3,2,3,4,5,0.0,satisfied +15300,6752,Female,Loyal Customer,48,Business travel,Business,2963,3,3,3,3,2,5,5,5,5,5,5,4,5,3,45,41.0,satisfied +15301,113670,Female,Loyal Customer,46,Personal Travel,Eco,397,1,3,1,3,1,2,3,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +15302,92190,Female,Loyal Customer,40,Business travel,Business,1979,5,5,5,5,4,3,5,5,5,5,5,4,5,4,0,5.0,satisfied +15303,49277,Female,Loyal Customer,45,Business travel,Business,1950,5,5,2,5,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +15304,7351,Male,disloyal Customer,26,Business travel,Business,864,1,0,0,4,3,0,3,3,3,4,4,3,5,3,3,0.0,neutral or dissatisfied +15305,59816,Female,Loyal Customer,28,Personal Travel,Business,1068,4,1,4,3,5,4,1,5,4,3,4,2,3,5,0,0.0,neutral or dissatisfied +15306,29668,Male,Loyal Customer,66,Personal Travel,Eco,1533,2,4,2,1,5,2,2,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +15307,48542,Male,disloyal Customer,55,Business travel,Eco,337,3,1,4,1,5,4,5,5,3,4,1,4,2,5,0,0.0,neutral or dissatisfied +15308,63528,Male,Loyal Customer,56,Business travel,Business,3041,4,4,4,4,2,4,5,4,4,4,4,4,4,4,7,3.0,satisfied +15309,103044,Male,disloyal Customer,24,Business travel,Eco,786,2,2,2,3,5,2,5,5,4,3,4,5,5,5,24,22.0,neutral or dissatisfied +15310,27707,Male,Loyal Customer,53,Business travel,Business,1448,3,3,4,3,5,5,4,4,4,4,4,3,4,4,9,0.0,satisfied +15311,53881,Male,Loyal Customer,64,Personal Travel,Eco,140,3,2,3,3,4,3,4,4,2,4,3,2,3,4,15,5.0,neutral or dissatisfied +15312,126724,Male,disloyal Customer,43,Business travel,Eco,794,1,1,1,2,4,1,4,4,2,4,1,4,2,4,0,0.0,neutral or dissatisfied +15313,30473,Male,Loyal Customer,52,Business travel,Eco,377,4,1,1,1,4,4,4,4,4,2,1,4,5,4,0,0.0,satisfied +15314,79535,Female,Loyal Customer,41,Business travel,Business,762,2,2,2,2,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +15315,109099,Male,Loyal Customer,43,Personal Travel,Eco,781,2,2,2,4,5,2,5,5,1,5,4,2,4,5,2,0.0,neutral or dissatisfied +15316,16683,Male,Loyal Customer,38,Business travel,Eco Plus,488,3,4,4,4,3,4,3,3,5,5,4,5,1,3,4,10.0,satisfied +15317,46416,Male,Loyal Customer,35,Business travel,Eco,458,4,2,2,2,4,4,4,4,3,5,5,1,5,4,0,0.0,satisfied +15318,44031,Female,disloyal Customer,20,Business travel,Eco,237,2,0,2,2,5,2,5,5,5,2,4,5,1,5,0,0.0,neutral or dissatisfied +15319,61354,Male,Loyal Customer,41,Business travel,Eco,202,4,3,3,3,4,4,4,4,1,2,3,3,2,4,3,8.0,satisfied +15320,126487,Male,Loyal Customer,33,Business travel,Business,1972,4,4,3,4,5,5,5,5,3,1,1,3,1,5,0,0.0,satisfied +15321,109111,Male,Loyal Customer,39,Business travel,Business,781,2,4,2,2,2,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +15322,34851,Female,disloyal Customer,37,Business travel,Eco,1826,2,2,2,3,2,4,4,5,2,3,1,4,1,4,119,135.0,neutral or dissatisfied +15323,90990,Male,disloyal Customer,27,Business travel,Business,366,4,4,4,4,5,4,5,5,1,3,3,1,4,5,10,18.0,neutral or dissatisfied +15324,34064,Female,Loyal Customer,22,Personal Travel,Eco,1674,3,3,3,3,5,3,3,5,3,3,4,4,3,5,8,2.0,neutral or dissatisfied +15325,102653,Male,disloyal Customer,21,Business travel,Business,255,5,4,5,4,5,5,5,5,5,3,4,5,4,5,104,113.0,satisfied +15326,129465,Male,Loyal Customer,46,Business travel,Business,2611,5,5,5,5,2,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +15327,52413,Male,Loyal Customer,24,Personal Travel,Eco,370,3,0,3,4,5,3,5,5,5,2,4,4,4,5,2,8.0,neutral or dissatisfied +15328,9305,Female,disloyal Customer,35,Business travel,Business,419,2,2,2,2,2,3,4,4,5,5,4,4,5,4,179,209.0,neutral or dissatisfied +15329,45698,Male,Loyal Customer,42,Business travel,Eco Plus,896,2,1,1,1,2,2,2,2,4,5,1,4,2,2,7,8.0,neutral or dissatisfied +15330,118834,Female,Loyal Customer,36,Business travel,Business,338,5,5,5,5,4,4,5,4,4,4,4,4,4,4,25,20.0,satisfied +15331,75982,Female,Loyal Customer,44,Personal Travel,Eco,297,5,5,5,4,2,4,4,3,3,5,2,3,3,4,0,0.0,satisfied +15332,120429,Male,Loyal Customer,64,Business travel,Business,2324,4,4,4,4,2,4,5,4,4,4,4,5,4,3,2,1.0,satisfied +15333,87480,Male,Loyal Customer,35,Business travel,Business,321,3,1,1,1,2,3,3,3,3,3,3,4,3,3,4,0.0,neutral or dissatisfied +15334,129422,Male,disloyal Customer,25,Business travel,Business,414,4,4,4,1,4,1,1,4,3,4,4,1,5,1,141,141.0,neutral or dissatisfied +15335,126283,Male,Loyal Customer,12,Personal Travel,Eco,600,2,1,2,1,5,2,5,5,4,1,1,1,1,5,0,0.0,neutral or dissatisfied +15336,49227,Female,Loyal Customer,43,Business travel,Business,2670,2,2,2,2,5,4,2,4,4,4,3,5,4,5,0,0.0,satisfied +15337,128743,Male,Loyal Customer,52,Business travel,Business,2402,1,1,1,1,2,2,2,3,2,3,5,2,3,2,0,23.0,satisfied +15338,127952,Female,Loyal Customer,40,Business travel,Business,1999,4,4,4,4,5,3,5,4,4,4,4,3,4,5,3,0.0,satisfied +15339,72771,Male,Loyal Customer,53,Business travel,Business,1748,4,4,4,4,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +15340,49089,Male,Loyal Customer,45,Business travel,Business,3979,1,1,1,1,4,3,1,4,4,4,4,5,4,1,0,0.0,satisfied +15341,98159,Male,Loyal Customer,37,Business travel,Business,162,2,2,2,2,2,3,4,3,3,3,2,1,3,2,0,11.0,neutral or dissatisfied +15342,101468,Male,Loyal Customer,41,Business travel,Business,345,4,4,4,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +15343,26510,Female,Loyal Customer,30,Personal Travel,Eco,829,1,5,1,5,2,1,3,2,5,4,5,3,5,2,5,0.0,neutral or dissatisfied +15344,44273,Female,Loyal Customer,45,Business travel,Eco Plus,222,2,2,2,2,3,2,2,2,2,2,2,3,2,4,28,21.0,satisfied +15345,1542,Male,Loyal Customer,32,Business travel,Business,3443,1,4,1,4,1,1,1,1,4,4,4,1,4,1,36,31.0,neutral or dissatisfied +15346,79284,Male,Loyal Customer,46,Business travel,Business,2248,2,2,2,2,3,5,5,1,1,2,1,3,1,4,0,33.0,satisfied +15347,62179,Female,Loyal Customer,59,Business travel,Business,2565,3,3,3,3,5,3,4,5,5,4,5,5,5,3,0,4.0,satisfied +15348,30452,Female,Loyal Customer,43,Business travel,Eco,991,2,1,4,4,5,3,2,2,2,2,2,1,2,2,55,42.0,satisfied +15349,7514,Female,disloyal Customer,23,Business travel,Eco,762,3,3,3,1,2,3,2,2,5,2,4,5,5,2,0,0.0,neutral or dissatisfied +15350,72241,Male,Loyal Customer,25,Business travel,Business,3715,4,4,4,4,4,5,4,4,5,5,4,5,5,4,0,0.0,satisfied +15351,77483,Male,disloyal Customer,29,Business travel,Business,1195,4,4,4,3,2,4,1,2,3,2,5,4,4,2,5,14.0,satisfied +15352,46299,Male,Loyal Customer,59,Personal Travel,Eco,533,1,4,1,3,5,1,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +15353,109910,Female,Loyal Customer,56,Business travel,Business,652,2,1,4,4,3,4,3,2,2,2,2,4,2,3,65,49.0,neutral or dissatisfied +15354,34890,Female,disloyal Customer,37,Business travel,Business,187,1,1,1,5,3,1,2,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +15355,79215,Male,Loyal Customer,58,Personal Travel,Eco,1990,2,3,2,3,3,2,3,3,1,2,3,2,3,3,0,0.0,neutral or dissatisfied +15356,19534,Male,disloyal Customer,22,Business travel,Eco,160,2,5,2,1,1,2,1,1,1,2,4,3,2,1,29,22.0,neutral or dissatisfied +15357,84356,Female,disloyal Customer,10,Business travel,Eco,606,4,1,4,3,3,4,3,3,2,1,3,1,4,3,0,25.0,neutral or dissatisfied +15358,19558,Female,disloyal Customer,55,Business travel,Eco,212,3,4,3,3,2,3,2,2,1,1,3,1,4,2,0,0.0,neutral or dissatisfied +15359,41776,Female,Loyal Customer,64,Personal Travel,Eco Plus,872,1,2,2,3,1,4,3,5,5,2,1,4,5,2,9,0.0,neutral or dissatisfied +15360,3823,Male,Loyal Customer,43,Business travel,Business,3862,3,5,5,5,1,4,3,3,3,3,3,2,3,4,0,6.0,neutral or dissatisfied +15361,122088,Male,Loyal Customer,11,Personal Travel,Eco,130,2,5,2,1,2,2,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +15362,16015,Female,Loyal Customer,46,Personal Travel,Eco,853,0,4,0,2,5,4,5,5,5,0,1,3,5,5,0,0.0,satisfied +15363,108642,Female,Loyal Customer,37,Personal Travel,Eco,528,3,5,5,2,5,5,5,5,4,1,1,4,3,5,8,0.0,neutral or dissatisfied +15364,96799,Female,disloyal Customer,26,Business travel,Business,488,2,0,2,3,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +15365,14008,Male,Loyal Customer,55,Personal Travel,Eco,615,2,5,2,5,2,2,2,3,4,5,5,2,4,2,207,178.0,neutral or dissatisfied +15366,36389,Female,Loyal Customer,18,Business travel,Eco Plus,200,3,5,5,5,3,3,1,3,2,4,4,3,3,3,0,0.0,neutral or dissatisfied +15367,122241,Male,Loyal Customer,48,Business travel,Business,1791,1,1,1,1,5,4,4,5,5,5,5,3,5,4,9,0.0,satisfied +15368,7856,Male,Loyal Customer,33,Personal Travel,Eco,1005,5,5,5,2,2,5,2,2,3,2,5,4,5,2,0,0.0,satisfied +15369,65611,Male,Loyal Customer,32,Business travel,Business,3273,3,2,3,3,3,3,3,3,3,3,3,1,4,3,17,13.0,neutral or dissatisfied +15370,94466,Female,disloyal Customer,24,Business travel,Eco,189,3,5,3,5,4,3,4,4,3,5,4,4,5,4,25,19.0,neutral or dissatisfied +15371,2280,Male,Loyal Customer,46,Business travel,Business,2603,4,4,4,4,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +15372,42500,Female,disloyal Customer,43,Business travel,Eco,541,3,0,3,3,2,3,2,2,1,5,4,3,3,2,0,0.0,neutral or dissatisfied +15373,25572,Male,Loyal Customer,43,Business travel,Business,1639,1,1,1,1,2,2,3,5,5,5,5,1,5,1,12,0.0,satisfied +15374,112324,Female,Loyal Customer,50,Business travel,Business,2479,1,5,5,5,2,4,3,1,1,1,1,3,1,1,114,86.0,neutral or dissatisfied +15375,20903,Female,Loyal Customer,58,Personal Travel,Business,721,4,2,4,3,4,4,5,2,1,2,4,5,3,5,201,209.0,satisfied +15376,107195,Male,Loyal Customer,20,Personal Travel,Eco,402,2,3,2,3,2,2,2,2,3,4,4,1,3,2,15,9.0,neutral or dissatisfied +15377,34263,Female,Loyal Customer,44,Business travel,Business,3540,1,1,1,1,2,3,1,5,5,5,5,1,5,4,0,0.0,satisfied +15378,117789,Female,disloyal Customer,22,Business travel,Eco,328,2,5,2,2,4,2,4,4,4,4,4,5,5,4,10,9.0,neutral or dissatisfied +15379,89496,Male,Loyal Customer,29,Business travel,Business,3725,3,5,5,5,3,3,3,3,4,2,3,1,3,3,21,8.0,neutral or dissatisfied +15380,64571,Male,Loyal Customer,41,Business travel,Business,190,1,1,1,1,5,4,4,4,4,4,5,4,4,5,6,18.0,satisfied +15381,70969,Female,Loyal Customer,25,Personal Travel,Business,978,4,4,3,2,1,3,1,1,4,2,5,4,5,1,29,55.0,neutral or dissatisfied +15382,3149,Female,Loyal Customer,37,Business travel,Business,2915,4,4,4,4,1,4,4,2,2,1,4,1,2,1,0,0.0,neutral or dissatisfied +15383,47838,Male,Loyal Customer,56,Business travel,Eco,412,3,3,5,5,3,3,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +15384,53023,Male,Loyal Customer,51,Business travel,Eco,1190,2,4,4,4,2,2,2,2,3,4,2,4,2,2,12,25.0,neutral or dissatisfied +15385,53856,Female,Loyal Customer,36,Business travel,Eco,191,4,2,2,2,4,3,4,4,1,2,2,4,3,4,0,0.0,neutral or dissatisfied +15386,23331,Male,Loyal Customer,29,Personal Travel,Eco,456,5,3,5,4,5,5,2,5,2,3,4,1,4,5,14,53.0,satisfied +15387,61036,Male,Loyal Customer,33,Personal Travel,Business,1703,1,4,1,3,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +15388,81110,Male,disloyal Customer,24,Business travel,Eco,991,1,1,1,3,5,1,5,5,5,4,4,4,5,5,0,0.0,neutral or dissatisfied +15389,43559,Male,Loyal Customer,45,Business travel,Eco,637,5,5,4,4,5,5,5,5,5,4,3,2,3,5,0,0.0,satisfied +15390,83768,Female,Loyal Customer,47,Personal Travel,Eco,926,2,4,2,4,2,5,4,2,2,2,2,3,2,5,0,1.0,neutral or dissatisfied +15391,102411,Male,Loyal Customer,19,Personal Travel,Eco,236,2,4,0,1,4,0,3,4,4,3,5,5,4,4,0,0.0,neutral or dissatisfied +15392,83487,Female,Loyal Customer,30,Business travel,Business,3029,3,1,1,1,3,3,3,3,4,4,4,2,3,3,16,13.0,neutral or dissatisfied +15393,446,Male,Loyal Customer,46,Business travel,Business,2978,0,5,0,2,3,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +15394,59375,Female,disloyal Customer,38,Business travel,Eco,949,4,4,4,3,4,4,4,4,4,2,1,3,1,4,0,0.0,neutral or dissatisfied +15395,4337,Female,Loyal Customer,53,Business travel,Business,1814,1,1,1,1,4,4,5,5,5,5,5,4,5,5,19,31.0,satisfied +15396,11187,Male,Loyal Customer,59,Personal Travel,Eco,224,2,4,2,3,2,2,2,2,1,1,4,3,3,2,0,2.0,neutral or dissatisfied +15397,27502,Female,Loyal Customer,72,Business travel,Business,2170,4,2,1,2,2,3,3,4,4,4,4,1,4,1,46,41.0,neutral or dissatisfied +15398,52206,Female,disloyal Customer,34,Business travel,Eco,751,3,3,3,2,5,3,5,5,3,1,5,1,3,5,0,2.0,neutral or dissatisfied +15399,45077,Female,Loyal Customer,34,Business travel,Business,1579,3,4,4,4,5,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +15400,31284,Female,Loyal Customer,20,Personal Travel,Eco,533,2,5,2,3,2,2,2,2,3,4,4,4,5,2,36,39.0,neutral or dissatisfied +15401,90170,Male,Loyal Customer,10,Personal Travel,Eco,1084,3,4,3,1,5,3,5,5,3,2,4,5,4,5,0,0.0,neutral or dissatisfied +15402,118275,Male,Loyal Customer,45,Business travel,Business,2405,1,1,1,1,3,5,5,5,5,5,5,4,5,3,10,2.0,satisfied +15403,100545,Male,Loyal Customer,39,Business travel,Business,580,4,4,2,4,5,4,4,5,5,5,5,3,5,5,22,3.0,satisfied +15404,4008,Female,Loyal Customer,65,Business travel,Business,479,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +15405,73273,Female,Loyal Customer,56,Business travel,Business,1012,5,5,5,5,5,5,5,4,4,4,4,3,4,5,0,2.0,satisfied +15406,4666,Female,Loyal Customer,66,Business travel,Business,3700,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,5.0,satisfied +15407,124540,Female,Loyal Customer,35,Business travel,Business,2372,2,4,4,4,3,3,4,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +15408,118041,Female,Loyal Customer,29,Business travel,Business,1262,3,3,3,3,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +15409,59153,Male,Loyal Customer,57,Business travel,Business,1726,5,5,5,5,3,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +15410,82267,Female,Loyal Customer,36,Business travel,Business,1481,3,3,3,3,5,4,4,5,5,5,5,5,5,3,1,0.0,satisfied +15411,85180,Male,Loyal Customer,29,Business travel,Business,1282,4,4,4,4,5,5,5,5,3,4,4,3,4,5,0,0.0,satisfied +15412,95978,Male,disloyal Customer,21,Business travel,Eco,1069,1,2,2,4,4,2,4,4,4,4,4,4,4,4,32,26.0,neutral or dissatisfied +15413,4155,Male,disloyal Customer,26,Business travel,Eco,427,2,2,2,3,1,2,1,1,2,5,3,3,3,1,0,0.0,neutral or dissatisfied +15414,33649,Male,Loyal Customer,9,Personal Travel,Eco,474,3,2,5,2,2,5,2,2,4,3,3,1,2,2,0,0.0,neutral or dissatisfied +15415,84392,Female,disloyal Customer,9,Business travel,Eco,591,5,4,5,2,5,5,1,5,3,5,5,4,4,5,0,0.0,satisfied +15416,95271,Female,Loyal Customer,16,Personal Travel,Eco,192,1,3,1,1,4,1,4,4,3,3,3,5,2,4,24,12.0,neutral or dissatisfied +15417,63853,Female,Loyal Customer,54,Business travel,Business,3725,4,4,1,4,5,5,5,4,4,4,4,3,4,4,8,4.0,satisfied +15418,77446,Female,Loyal Customer,40,Business travel,Business,107,0,5,0,5,4,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +15419,63574,Male,Loyal Customer,16,Personal Travel,Eco Plus,1737,3,3,3,4,1,3,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +15420,42659,Male,Loyal Customer,25,Business travel,Business,3428,4,4,2,4,5,4,5,5,3,4,3,5,2,5,20,3.0,satisfied +15421,50772,Male,Loyal Customer,34,Personal Travel,Eco,373,4,3,4,4,3,4,3,3,3,5,4,1,4,3,7,0.0,neutral or dissatisfied +15422,85367,Female,Loyal Customer,25,Personal Travel,Eco Plus,689,2,1,2,4,4,2,3,4,1,3,4,1,4,4,0,5.0,neutral or dissatisfied +15423,20801,Male,Loyal Customer,42,Business travel,Eco,508,5,4,4,4,5,5,5,5,4,2,1,3,1,5,54,46.0,satisfied +15424,5627,Male,Loyal Customer,43,Personal Travel,Eco,624,3,1,4,3,5,4,2,5,1,1,3,2,3,5,0,0.0,neutral or dissatisfied +15425,121591,Male,Loyal Customer,7,Personal Travel,Eco,912,4,2,4,4,3,4,3,3,2,2,3,3,3,3,0,0.0,satisfied +15426,82350,Female,Loyal Customer,47,Business travel,Business,3722,3,3,3,3,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +15427,45748,Female,disloyal Customer,23,Business travel,Eco,391,4,0,4,3,2,4,4,2,5,4,3,1,1,2,0,0.0,neutral or dissatisfied +15428,30222,Female,disloyal Customer,34,Business travel,Eco,1109,1,0,0,1,5,0,5,5,2,1,2,2,2,5,16,8.0,neutral or dissatisfied +15429,110187,Female,Loyal Customer,48,Personal Travel,Eco,882,3,4,3,4,1,4,4,5,5,3,5,5,5,2,20,8.0,neutral or dissatisfied +15430,24075,Female,Loyal Customer,44,Business travel,Business,866,2,5,2,2,5,3,2,2,2,2,2,1,2,3,27,35.0,neutral or dissatisfied +15431,79986,Female,Loyal Customer,50,Personal Travel,Eco,1035,4,5,4,2,5,4,4,3,3,4,4,4,3,5,0,8.0,neutral or dissatisfied +15432,77486,Male,Loyal Customer,51,Business travel,Business,1086,4,4,4,4,2,5,4,5,5,5,5,4,5,4,9,0.0,satisfied +15433,93208,Female,Loyal Customer,41,Personal Travel,Eco,1756,2,4,2,4,2,2,2,2,2,2,3,2,3,2,14,13.0,neutral or dissatisfied +15434,65733,Female,Loyal Customer,38,Business travel,Business,1061,1,5,4,5,2,3,3,1,1,1,1,4,1,3,1,0.0,neutral or dissatisfied +15435,13183,Male,Loyal Customer,34,Business travel,Eco,542,5,1,1,1,5,4,5,5,4,4,3,1,4,5,119,119.0,satisfied +15436,121504,Female,Loyal Customer,60,Personal Travel,Eco Plus,331,4,2,4,2,2,2,2,5,5,4,1,4,5,2,0,0.0,neutral or dissatisfied +15437,5239,Female,Loyal Customer,39,Business travel,Business,295,3,3,3,3,5,4,4,5,5,5,5,3,5,4,0,10.0,satisfied +15438,20385,Male,Loyal Customer,56,Personal Travel,Eco Plus,287,4,5,4,4,2,4,2,2,5,5,5,5,4,2,4,0.0,neutral or dissatisfied +15439,40204,Female,disloyal Customer,33,Business travel,Eco,436,3,1,3,2,5,3,3,5,2,1,2,4,2,5,19,29.0,neutral or dissatisfied +15440,105786,Male,Loyal Customer,27,Personal Travel,Eco,787,4,4,4,5,3,4,5,3,4,2,4,5,5,3,67,87.0,neutral or dissatisfied +15441,78084,Male,Loyal Customer,18,Personal Travel,Eco Plus,214,1,0,1,4,2,1,2,2,1,2,4,1,4,2,3,25.0,neutral or dissatisfied +15442,3259,Male,Loyal Customer,44,Business travel,Business,425,3,5,5,5,5,3,4,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +15443,89306,Male,Loyal Customer,24,Personal Travel,Eco,453,3,4,3,2,1,3,1,1,4,3,4,4,5,1,19,22.0,neutral or dissatisfied +15444,49763,Male,Loyal Customer,54,Business travel,Eco,158,5,4,4,4,5,5,5,5,4,4,2,2,4,5,0,2.0,satisfied +15445,89852,Male,Loyal Customer,60,Business travel,Business,1416,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +15446,129552,Male,Loyal Customer,22,Personal Travel,Eco,2342,3,4,3,3,2,3,2,2,2,2,3,3,3,2,1,0.0,neutral or dissatisfied +15447,38775,Female,Loyal Customer,44,Business travel,Business,2058,2,2,2,2,5,3,3,2,2,2,2,2,2,3,12,6.0,neutral or dissatisfied +15448,73220,Female,disloyal Customer,48,Business travel,Business,946,5,5,5,4,1,5,5,1,5,4,5,3,5,1,0,0.0,satisfied +15449,125452,Male,disloyal Customer,24,Business travel,Eco,2845,3,3,3,4,1,3,1,1,5,3,5,5,5,1,0,0.0,neutral or dissatisfied +15450,42812,Female,disloyal Customer,40,Business travel,Business,677,1,1,1,3,2,1,2,2,1,2,4,3,4,2,79,73.0,neutral or dissatisfied +15451,31444,Male,Loyal Customer,15,Personal Travel,Eco,1541,2,5,2,3,4,2,4,4,4,4,3,4,5,4,33,32.0,neutral or dissatisfied +15452,82576,Male,disloyal Customer,8,Business travel,Eco,528,2,0,2,1,5,2,5,5,3,5,5,4,4,5,0,0.0,neutral or dissatisfied +15453,104367,Male,Loyal Customer,44,Business travel,Business,228,1,1,1,1,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +15454,25289,Female,Loyal Customer,39,Business travel,Business,3867,5,5,5,5,1,4,2,5,5,5,5,4,5,3,0,0.0,satisfied +15455,72603,Male,Loyal Customer,22,Personal Travel,Eco,918,5,5,5,5,1,5,1,1,3,5,5,5,5,1,0,0.0,satisfied +15456,86183,Female,Loyal Customer,37,Business travel,Business,226,4,4,4,4,2,4,4,5,5,5,5,5,5,3,1,5.0,satisfied +15457,116144,Male,Loyal Customer,32,Personal Travel,Eco,325,3,4,3,3,5,3,4,5,1,5,5,3,4,5,54,52.0,neutral or dissatisfied +15458,25751,Male,Loyal Customer,23,Business travel,Eco,356,1,2,2,2,1,2,1,1,4,2,4,3,3,1,4,9.0,neutral or dissatisfied +15459,6597,Male,Loyal Customer,37,Personal Travel,Eco,618,2,5,2,1,4,2,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +15460,43628,Male,Loyal Customer,61,Personal Travel,Eco,252,2,4,2,4,2,2,5,2,4,5,5,1,1,2,0,0.0,neutral or dissatisfied +15461,48259,Female,Loyal Customer,49,Personal Travel,Eco,391,1,5,1,4,4,5,4,3,3,1,3,5,3,4,0,0.0,neutral or dissatisfied +15462,125388,Female,Loyal Customer,45,Business travel,Business,1440,1,5,4,5,5,4,4,1,1,1,1,3,1,1,0,9.0,neutral or dissatisfied +15463,123095,Female,Loyal Customer,27,Business travel,Business,507,3,2,2,2,3,2,3,3,1,1,3,2,3,3,58,54.0,neutral or dissatisfied +15464,8935,Female,Loyal Customer,58,Business travel,Business,402,4,4,4,4,3,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +15465,112182,Female,Loyal Customer,32,Personal Travel,Eco,895,1,3,1,3,5,1,5,5,2,5,3,3,3,5,10,1.0,neutral or dissatisfied +15466,60764,Male,Loyal Customer,59,Business travel,Business,628,3,3,3,3,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +15467,32729,Female,disloyal Customer,85,Business travel,Business,101,2,2,2,3,2,3,3,1,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +15468,82598,Female,Loyal Customer,40,Business travel,Business,2570,4,5,5,5,2,4,4,4,4,3,4,1,4,3,0,4.0,neutral or dissatisfied +15469,84397,Female,Loyal Customer,33,Business travel,Business,591,2,3,3,3,4,4,4,2,2,2,2,3,2,4,5,0.0,neutral or dissatisfied +15470,71406,Female,disloyal Customer,26,Business travel,Eco,334,2,2,3,4,5,3,5,5,3,3,3,4,4,5,19,13.0,neutral or dissatisfied +15471,23785,Male,Loyal Customer,45,Business travel,Eco,374,4,1,1,1,5,4,5,5,2,5,2,2,5,5,19,40.0,satisfied +15472,12296,Male,disloyal Customer,26,Business travel,Eco,253,3,0,3,3,4,3,1,4,4,4,2,1,4,4,13,14.0,neutral or dissatisfied +15473,61051,Male,Loyal Customer,22,Business travel,Business,1546,1,1,1,1,5,5,5,5,4,3,5,5,4,5,0,0.0,satisfied +15474,70031,Male,Loyal Customer,25,Business travel,Business,583,3,1,1,1,3,3,3,3,2,5,4,1,4,3,0,0.0,neutral or dissatisfied +15475,46576,Male,disloyal Customer,57,Business travel,Eco,125,1,4,0,3,3,0,3,3,4,4,3,2,4,3,74,72.0,neutral or dissatisfied +15476,60813,Male,Loyal Customer,45,Business travel,Business,3019,2,5,5,5,3,4,3,2,2,2,2,4,2,3,16,17.0,neutral or dissatisfied +15477,43768,Male,disloyal Customer,21,Business travel,Eco,546,3,4,3,4,2,3,2,2,5,5,3,3,4,2,0,1.0,neutral or dissatisfied +15478,49233,Male,Loyal Customer,69,Business travel,Business,89,0,5,0,4,3,4,2,4,4,4,4,1,4,4,0,0.0,satisfied +15479,22810,Male,Loyal Customer,38,Business travel,Business,3359,1,1,5,1,1,4,4,4,4,4,1,4,4,1,97,93.0,neutral or dissatisfied +15480,86723,Female,Loyal Customer,63,Personal Travel,Eco,1747,1,4,1,5,5,5,2,5,5,1,3,2,5,3,0,10.0,neutral or dissatisfied +15481,3717,Female,Loyal Customer,62,Personal Travel,Eco,431,3,4,3,4,4,5,5,1,1,3,1,5,1,5,4,0.0,neutral or dissatisfied +15482,7021,Female,Loyal Customer,33,Personal Travel,Eco,234,1,4,0,3,3,0,3,3,5,3,4,4,5,3,0,0.0,neutral or dissatisfied +15483,102037,Female,Loyal Customer,29,Business travel,Business,1581,5,5,5,5,5,5,5,5,4,2,5,4,4,5,0,0.0,satisfied +15484,112512,Male,Loyal Customer,40,Personal Travel,Eco,948,2,2,2,2,2,2,2,2,1,3,2,1,3,2,15,11.0,neutral or dissatisfied +15485,110329,Male,disloyal Customer,34,Business travel,Business,883,2,3,3,4,4,3,4,4,5,5,5,5,5,4,88,77.0,neutral or dissatisfied +15486,118289,Female,Loyal Customer,52,Business travel,Business,3886,3,3,3,3,5,5,4,2,2,2,2,3,2,3,9,0.0,satisfied +15487,105673,Male,Loyal Customer,55,Business travel,Business,1682,3,3,3,3,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +15488,88812,Female,Loyal Customer,36,Business travel,Eco Plus,406,3,4,4,4,3,3,3,3,1,2,4,1,3,3,9,0.0,neutral or dissatisfied +15489,27240,Female,Loyal Customer,51,Personal Travel,Eco,1024,4,3,4,3,2,3,5,4,4,4,4,2,4,2,0,9.0,neutral or dissatisfied +15490,70495,Female,Loyal Customer,17,Business travel,Business,3195,3,1,1,1,3,3,3,3,2,3,4,4,4,3,0,0.0,neutral or dissatisfied +15491,43198,Female,Loyal Customer,17,Business travel,Eco Plus,651,0,5,0,3,1,0,1,1,1,5,5,3,5,1,0,59.0,satisfied +15492,37658,Female,Loyal Customer,60,Personal Travel,Eco,1069,3,4,3,2,3,5,5,2,2,3,2,4,2,3,18,0.0,neutral or dissatisfied +15493,122628,Male,Loyal Customer,57,Personal Travel,Eco,728,2,4,2,4,5,2,5,5,3,5,4,2,5,5,0,0.0,neutral or dissatisfied +15494,21496,Male,Loyal Customer,70,Personal Travel,Eco,399,4,5,4,4,1,4,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +15495,17394,Male,Loyal Customer,41,Business travel,Eco,351,5,5,5,5,5,5,5,5,3,3,2,1,2,5,30,51.0,satisfied +15496,70282,Female,Loyal Customer,27,Business travel,Business,2184,3,3,3,3,4,5,4,4,5,5,4,3,5,4,0,10.0,satisfied +15497,83977,Female,Loyal Customer,53,Business travel,Business,3179,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,6.0,satisfied +15498,91723,Male,Loyal Customer,41,Business travel,Business,2678,2,2,2,2,3,5,4,5,5,4,5,4,5,3,16,19.0,satisfied +15499,46996,Male,Loyal Customer,43,Business travel,Eco Plus,737,2,5,5,5,2,2,2,2,2,1,4,3,4,2,0,14.0,neutral or dissatisfied +15500,35533,Female,Loyal Customer,54,Personal Travel,Eco,1005,2,3,2,2,2,2,3,1,1,2,1,4,1,2,0,14.0,neutral or dissatisfied +15501,36455,Male,Loyal Customer,8,Business travel,Business,3769,4,2,2,2,4,4,4,4,3,5,3,3,3,4,0,16.0,neutral or dissatisfied +15502,35679,Female,disloyal Customer,26,Business travel,Eco,1151,2,2,2,4,2,3,3,1,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +15503,119157,Male,Loyal Customer,68,Personal Travel,Business,331,3,4,3,2,5,5,4,5,5,3,3,3,5,3,0,0.0,neutral or dissatisfied +15504,110018,Male,Loyal Customer,62,Personal Travel,Eco,1204,4,1,4,1,2,4,2,2,3,2,2,2,1,2,6,0.0,satisfied +15505,7707,Male,Loyal Customer,53,Personal Travel,Eco,767,4,2,4,3,1,4,3,1,3,5,3,4,3,1,0,9.0,neutral or dissatisfied +15506,37112,Male,disloyal Customer,35,Business travel,Business,1129,4,4,4,2,4,4,3,4,2,4,4,4,1,4,10,19.0,neutral or dissatisfied +15507,49002,Male,Loyal Customer,49,Business travel,Eco,109,5,1,1,1,5,5,5,5,3,2,5,3,3,5,0,2.0,satisfied +15508,127746,Male,Loyal Customer,35,Business travel,Eco,601,2,2,2,2,2,2,2,2,2,5,4,2,3,2,7,10.0,neutral or dissatisfied +15509,18943,Female,Loyal Customer,11,Personal Travel,Eco,551,2,3,2,1,4,2,4,4,2,4,2,2,3,4,0,0.0,neutral or dissatisfied +15510,78803,Female,Loyal Customer,39,Personal Travel,Eco,432,2,5,2,5,4,2,4,4,4,2,5,3,2,4,0,0.0,neutral or dissatisfied +15511,107980,Male,Loyal Customer,38,Business travel,Eco Plus,825,1,1,3,3,1,1,1,1,2,3,3,3,3,1,1,31.0,neutral or dissatisfied +15512,3362,Male,Loyal Customer,47,Business travel,Business,296,3,3,3,3,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +15513,71036,Male,Loyal Customer,48,Business travel,Business,802,3,1,1,1,2,3,3,2,1,4,3,3,2,3,348,349.0,neutral or dissatisfied +15514,83139,Male,Loyal Customer,33,Personal Travel,Eco,983,4,5,4,4,1,4,1,1,4,2,4,5,5,1,0,0.0,satisfied +15515,18899,Female,Loyal Customer,60,Business travel,Business,2224,4,4,4,4,2,4,5,4,4,4,4,1,4,3,0,0.0,satisfied +15516,120235,Male,Loyal Customer,16,Personal Travel,Eco,1303,2,1,2,1,2,2,2,2,2,5,2,1,1,2,0,0.0,neutral or dissatisfied +15517,51021,Female,Loyal Customer,7,Personal Travel,Eco,77,1,3,1,2,4,1,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +15518,26685,Male,Loyal Customer,12,Personal Travel,Eco,270,4,5,4,2,5,4,5,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +15519,14894,Female,disloyal Customer,25,Business travel,Eco,315,3,3,4,4,3,4,3,3,2,4,3,2,4,3,21,33.0,neutral or dissatisfied +15520,93495,Female,disloyal Customer,22,Business travel,Eco,1107,3,3,3,3,3,3,3,3,3,3,5,4,5,3,7,2.0,neutral or dissatisfied +15521,112394,Female,disloyal Customer,47,Business travel,Business,853,2,2,2,5,4,2,4,4,5,4,4,5,5,4,0,7.0,neutral or dissatisfied +15522,95147,Female,Loyal Customer,48,Personal Travel,Eco,277,3,4,3,1,1,5,4,3,3,3,3,2,3,5,0,0.0,neutral or dissatisfied +15523,86163,Female,Loyal Customer,39,Business travel,Business,306,2,2,2,2,2,5,5,5,5,5,5,5,5,3,2,0.0,satisfied +15524,32345,Female,Loyal Customer,39,Business travel,Eco,201,4,5,5,5,4,4,4,4,4,5,1,4,5,4,0,0.0,satisfied +15525,69572,Female,Loyal Customer,34,Business travel,Business,2475,1,4,4,4,1,1,1,1,4,3,4,1,1,1,2,28.0,neutral or dissatisfied +15526,71601,Male,Loyal Customer,40,Business travel,Business,1197,1,1,1,1,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +15527,45420,Male,Loyal Customer,58,Business travel,Business,458,3,3,3,3,1,3,4,5,5,5,5,5,5,3,0,0.0,satisfied +15528,94215,Male,disloyal Customer,26,Business travel,Business,562,4,3,3,1,2,3,3,2,4,4,4,5,4,2,44,35.0,neutral or dissatisfied +15529,50056,Male,Loyal Customer,35,Business travel,Business,3460,3,2,2,2,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +15530,82640,Female,Loyal Customer,55,Personal Travel,Eco Plus,528,1,4,1,4,2,3,4,1,1,1,1,3,1,1,10,9.0,neutral or dissatisfied +15531,33476,Male,Loyal Customer,44,Business travel,Business,2422,5,5,3,5,1,5,3,4,4,5,4,4,4,1,6,0.0,satisfied +15532,109132,Female,Loyal Customer,44,Business travel,Business,3513,2,2,3,2,3,5,5,4,4,4,4,5,4,3,2,0.0,satisfied +15533,129109,Male,Loyal Customer,54,Personal Travel,Eco,2583,3,5,3,1,3,3,3,2,5,5,5,3,4,3,0,0.0,neutral or dissatisfied +15534,111838,Male,Loyal Customer,42,Personal Travel,Business,804,1,2,1,3,2,3,3,3,3,1,4,4,3,2,0,0.0,neutral or dissatisfied +15535,103881,Male,Loyal Customer,28,Personal Travel,Eco,882,3,3,4,4,5,4,5,5,5,4,5,5,4,5,0,0.0,neutral or dissatisfied +15536,101168,Male,Loyal Customer,19,Business travel,Business,2751,4,4,1,4,4,4,4,4,3,5,4,4,5,4,0,0.0,satisfied +15537,26549,Male,Loyal Customer,52,Personal Travel,Eco,990,2,2,2,4,1,2,1,1,3,1,3,4,4,1,0,0.0,neutral or dissatisfied +15538,62068,Male,Loyal Customer,26,Personal Travel,Eco,2475,2,2,2,2,4,2,4,4,3,1,2,2,2,4,0,0.0,neutral or dissatisfied +15539,13903,Male,Loyal Customer,54,Business travel,Business,3791,4,4,4,4,3,5,1,4,4,4,5,5,4,2,16,1.0,satisfied +15540,111899,Male,Loyal Customer,48,Personal Travel,Eco,628,3,5,3,5,1,3,1,1,4,5,4,3,4,1,5,5.0,neutral or dissatisfied +15541,5827,Female,Loyal Customer,25,Personal Travel,Eco,177,2,5,2,5,4,2,4,4,3,3,5,5,5,4,0,0.0,neutral or dissatisfied +15542,94361,Female,Loyal Customer,42,Business travel,Business,2787,2,2,2,2,4,5,5,5,5,5,5,5,5,4,4,0.0,satisfied +15543,65648,Female,Loyal Customer,49,Business travel,Business,1021,2,2,2,2,5,4,5,5,5,5,5,5,5,5,40,28.0,satisfied +15544,3596,Female,Loyal Customer,41,Business travel,Business,999,3,1,4,4,3,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +15545,58293,Male,Loyal Customer,48,Personal Travel,Eco,413,2,4,2,3,3,2,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +15546,52793,Male,disloyal Customer,64,Personal Travel,Eco,1874,5,5,5,2,4,5,4,4,1,3,2,3,1,4,0,0.0,satisfied +15547,122201,Male,disloyal Customer,24,Business travel,Business,544,4,4,4,3,4,4,4,4,5,5,4,4,5,4,0,0.0,satisfied +15548,48369,Male,Loyal Customer,64,Business travel,Eco,122,5,5,5,5,5,5,5,5,5,1,5,4,1,5,0,1.0,satisfied +15549,81150,Male,Loyal Customer,22,Personal Travel,Eco,1310,4,5,4,1,3,4,3,3,3,4,4,3,4,3,0,3.0,satisfied +15550,112818,Female,Loyal Customer,39,Business travel,Business,1390,2,2,2,2,5,5,4,3,3,4,3,3,3,4,9,0.0,satisfied +15551,128822,Male,Loyal Customer,52,Business travel,Business,2586,3,3,3,3,3,3,3,3,4,4,5,3,4,3,0,0.0,satisfied +15552,125368,Male,disloyal Customer,69,Personal Travel,Eco,599,3,0,3,3,3,2,2,4,4,3,4,2,3,2,155,163.0,neutral or dissatisfied +15553,88635,Male,Loyal Customer,36,Personal Travel,Eco,366,2,5,2,3,3,2,3,3,1,1,3,1,4,3,8,7.0,neutral or dissatisfied +15554,88067,Female,disloyal Customer,39,Business travel,Business,545,2,2,2,1,5,2,5,5,5,2,4,4,5,5,0,0.0,satisfied +15555,128627,Female,disloyal Customer,39,Business travel,Business,954,3,2,2,4,2,2,4,2,2,2,3,2,3,2,0,0.0,neutral or dissatisfied +15556,83987,Female,disloyal Customer,39,Business travel,Business,321,4,4,4,1,4,4,4,4,3,3,5,5,5,4,0,0.0,satisfied +15557,59168,Female,Loyal Customer,63,Personal Travel,Eco Plus,1846,1,5,1,5,4,4,5,2,2,1,3,5,2,4,5,0.0,neutral or dissatisfied +15558,74792,Male,Loyal Customer,46,Business travel,Business,1205,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +15559,97444,Female,Loyal Customer,35,Business travel,Business,822,4,4,4,4,2,5,4,3,3,3,3,5,3,3,47,47.0,satisfied +15560,21743,Male,disloyal Customer,14,Business travel,Eco,563,1,3,1,3,5,1,5,5,3,2,3,2,4,5,0,0.0,neutral or dissatisfied +15561,3378,Male,Loyal Customer,35,Business travel,Business,3243,3,4,4,4,5,4,4,3,3,3,3,3,3,3,24,38.0,neutral or dissatisfied +15562,51784,Female,Loyal Customer,39,Personal Travel,Eco,370,1,4,1,1,5,1,1,5,5,2,3,2,1,5,8,5.0,neutral or dissatisfied +15563,26337,Male,Loyal Customer,39,Business travel,Eco,834,5,1,1,1,5,5,5,5,2,1,2,4,2,5,62,59.0,satisfied +15564,80377,Female,Loyal Customer,59,Business travel,Eco,422,3,1,1,1,4,4,4,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +15565,51857,Male,Loyal Customer,13,Personal Travel,Eco,438,3,4,3,3,5,3,5,5,3,2,4,4,5,5,9,14.0,neutral or dissatisfied +15566,93866,Male,Loyal Customer,35,Business travel,Business,2401,2,1,1,1,3,2,3,2,2,2,2,4,2,3,22,14.0,neutral or dissatisfied +15567,59705,Male,Loyal Customer,56,Personal Travel,Eco,854,3,4,3,4,2,3,3,2,3,4,5,4,4,2,0,0.0,neutral or dissatisfied +15568,16749,Female,Loyal Customer,27,Business travel,Eco,569,4,4,4,4,4,4,4,4,1,3,2,2,2,4,0,0.0,satisfied +15569,33522,Female,Loyal Customer,55,Business travel,Eco,228,5,5,5,5,5,4,2,5,5,5,5,2,5,2,0,0.0,satisfied +15570,74376,Female,Loyal Customer,46,Business travel,Business,1464,1,1,1,1,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +15571,1370,Female,disloyal Customer,38,Business travel,Business,247,4,4,4,3,4,4,4,4,3,5,4,5,4,4,0,0.0,neutral or dissatisfied +15572,12661,Male,Loyal Customer,42,Business travel,Business,2810,3,3,3,3,3,5,4,5,5,5,5,3,5,5,8,0.0,satisfied +15573,123695,Female,Loyal Customer,51,Personal Travel,Eco,214,2,0,2,3,2,4,5,2,2,2,2,5,2,5,0,0.0,neutral or dissatisfied +15574,18821,Male,Loyal Customer,52,Business travel,Business,448,1,1,1,1,4,3,1,5,5,5,5,1,5,4,0,2.0,satisfied +15575,50887,Male,Loyal Customer,68,Personal Travel,Eco,77,4,4,4,2,1,4,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +15576,80262,Male,Loyal Customer,54,Personal Travel,Eco,1008,2,5,2,5,3,2,3,3,5,3,5,3,5,3,1,43.0,neutral or dissatisfied +15577,4032,Female,disloyal Customer,47,Business travel,Eco,479,2,0,2,2,3,2,3,3,3,5,5,4,4,3,0,7.0,neutral or dissatisfied +15578,39293,Female,Loyal Customer,66,Personal Travel,Eco,67,1,5,1,3,2,5,4,5,5,1,5,5,5,3,0,0.0,neutral or dissatisfied +15579,44963,Female,Loyal Customer,54,Personal Travel,Eco Plus,397,3,4,3,2,3,5,5,2,2,3,2,4,2,3,110,116.0,neutral or dissatisfied +15580,56381,Female,Loyal Customer,33,Business travel,Eco Plus,200,3,2,2,2,3,3,3,3,3,2,4,4,4,3,96,78.0,neutral or dissatisfied +15581,4688,Female,Loyal Customer,58,Personal Travel,Eco,489,2,3,2,1,3,1,2,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +15582,80448,Male,disloyal Customer,48,Business travel,Business,1299,2,2,2,3,5,2,5,5,4,2,5,4,5,5,2,0.0,neutral or dissatisfied +15583,80120,Male,disloyal Customer,25,Business travel,Eco,1061,5,5,5,3,5,4,1,5,2,5,5,1,3,1,0,0.0,satisfied +15584,99311,Female,Loyal Customer,37,Business travel,Business,337,5,5,5,5,3,4,5,3,3,4,3,5,3,3,6,0.0,satisfied +15585,46353,Female,disloyal Customer,27,Business travel,Business,1013,0,0,0,1,1,0,1,1,4,3,5,4,5,1,0,0.0,satisfied +15586,38448,Female,disloyal Customer,37,Business travel,Business,1104,1,1,1,4,4,1,4,4,2,5,3,1,4,4,10,9.0,neutral or dissatisfied +15587,79272,Male,Loyal Customer,14,Personal Travel,Eco,2454,3,5,3,5,1,3,1,1,4,5,2,3,1,1,16,0.0,neutral or dissatisfied +15588,66519,Male,Loyal Customer,53,Personal Travel,Eco,447,1,5,1,2,1,1,1,1,3,2,4,3,4,1,0,1.0,neutral or dissatisfied +15589,127012,Female,disloyal Customer,45,Business travel,Eco,304,3,2,3,4,1,3,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +15590,46156,Male,Loyal Customer,67,Personal Travel,Eco,604,5,5,4,4,5,4,5,5,3,3,4,5,5,5,77,99.0,satisfied +15591,39257,Male,disloyal Customer,57,Business travel,Eco,67,3,3,4,2,1,4,1,1,2,3,2,2,2,1,48,36.0,neutral or dissatisfied +15592,38903,Female,Loyal Customer,22,Business travel,Business,1990,3,3,3,3,4,4,4,4,3,3,2,2,2,4,20,33.0,satisfied +15593,106171,Male,Loyal Customer,15,Personal Travel,Eco,436,1,4,1,3,1,1,1,1,4,5,5,4,4,1,57,62.0,neutral or dissatisfied +15594,83341,Female,Loyal Customer,55,Business travel,Business,2694,5,5,5,5,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +15595,95023,Male,Loyal Customer,43,Personal Travel,Eco,277,2,3,5,3,3,5,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +15596,9710,Female,Loyal Customer,12,Personal Travel,Eco,212,2,1,0,1,3,0,3,3,2,1,1,3,2,3,22,8.0,neutral or dissatisfied +15597,15846,Male,Loyal Customer,29,Personal Travel,Eco,1107,2,5,2,3,4,2,4,4,3,2,4,3,4,4,9,0.0,neutral or dissatisfied +15598,58050,Female,disloyal Customer,28,Business travel,Business,612,2,2,2,1,2,2,2,2,3,3,5,4,4,2,0,0.0,neutral or dissatisfied +15599,27405,Female,Loyal Customer,52,Business travel,Eco,671,3,5,5,5,3,5,1,3,3,3,3,4,3,1,0,0.0,satisfied +15600,64035,Male,disloyal Customer,23,Business travel,Eco,919,2,2,2,4,4,2,4,4,1,1,3,1,4,4,18,21.0,neutral or dissatisfied +15601,28847,Female,Loyal Customer,44,Business travel,Eco,978,5,3,3,3,1,4,4,5,5,5,5,2,5,1,0,0.0,satisfied +15602,61060,Male,Loyal Customer,39,Business travel,Business,1506,4,4,4,4,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +15603,90870,Male,Loyal Customer,55,Business travel,Business,3420,4,4,4,4,2,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +15604,79443,Male,Loyal Customer,17,Personal Travel,Eco,187,2,5,2,1,1,2,1,1,4,3,5,3,4,1,17,11.0,neutral or dissatisfied +15605,6729,Female,Loyal Customer,57,Business travel,Business,3446,4,4,4,4,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +15606,71535,Female,disloyal Customer,26,Business travel,Business,1012,4,4,4,4,5,4,5,5,4,3,4,5,5,5,0,0.0,satisfied +15607,82502,Female,Loyal Customer,53,Business travel,Business,1749,2,2,2,2,5,4,5,5,5,5,5,5,5,5,58,48.0,satisfied +15608,69495,Male,Loyal Customer,8,Personal Travel,Eco Plus,1089,5,5,5,1,4,5,4,4,4,4,2,3,3,4,0,0.0,satisfied +15609,78929,Male,Loyal Customer,46,Business travel,Business,1911,2,2,4,2,5,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +15610,116960,Male,Loyal Customer,34,Business travel,Business,370,4,4,4,4,3,5,4,4,4,4,4,4,4,3,1,0.0,satisfied +15611,94479,Female,Loyal Customer,48,Business travel,Business,1658,1,1,1,1,2,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +15612,14962,Male,Loyal Customer,28,Business travel,Eco Plus,528,2,2,2,2,2,1,2,2,1,2,3,3,4,2,0,0.0,neutral or dissatisfied +15613,58093,Female,Loyal Customer,57,Business travel,Business,212,0,4,0,3,5,2,5,2,2,2,2,5,2,4,31,21.0,satisfied +15614,111210,Female,Loyal Customer,24,Business travel,Business,1506,2,3,3,3,2,3,2,2,2,1,4,4,3,2,11,0.0,neutral or dissatisfied +15615,103873,Female,Loyal Customer,60,Personal Travel,Eco,882,4,1,4,3,4,3,4,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +15616,68482,Male,Loyal Customer,36,Business travel,Business,1303,2,4,4,4,5,4,4,2,2,2,2,1,2,4,0,17.0,neutral or dissatisfied +15617,500,Male,Loyal Customer,48,Business travel,Business,2469,2,2,2,2,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +15618,115055,Male,Loyal Customer,46,Business travel,Business,296,5,5,5,5,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +15619,7752,Female,Loyal Customer,39,Business travel,Eco,613,4,5,5,5,4,4,4,4,5,3,2,2,1,4,0,1.0,satisfied +15620,48463,Male,Loyal Customer,20,Business travel,Business,2078,2,2,2,2,5,5,5,5,5,3,5,1,4,5,7,13.0,satisfied +15621,82577,Female,Loyal Customer,55,Business travel,Business,1785,5,5,1,5,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +15622,122649,Male,disloyal Customer,26,Business travel,Business,361,4,0,4,1,5,4,5,5,4,5,4,4,5,5,0,0.0,satisfied +15623,19633,Female,Loyal Customer,59,Business travel,Business,717,4,4,5,4,3,4,4,5,5,5,5,4,5,3,11,4.0,satisfied +15624,89119,Female,disloyal Customer,50,Business travel,Eco,1083,2,2,2,4,2,2,1,2,4,4,4,1,4,2,36,25.0,neutral or dissatisfied +15625,43582,Male,Loyal Customer,34,Business travel,Eco Plus,1499,3,1,1,1,3,4,3,3,1,1,1,3,5,3,1,0.0,satisfied +15626,99819,Male,Loyal Customer,56,Business travel,Business,587,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +15627,9885,Male,disloyal Customer,34,Business travel,Business,508,2,3,3,1,4,3,4,4,5,4,5,3,4,4,94,82.0,neutral or dissatisfied +15628,46583,Female,Loyal Customer,39,Business travel,Eco,125,5,1,1,1,5,5,5,5,2,2,3,5,2,5,131,,satisfied +15629,75736,Male,Loyal Customer,56,Business travel,Eco,813,3,1,1,1,4,3,4,4,1,5,3,2,4,4,0,0.0,neutral or dissatisfied +15630,45538,Male,disloyal Customer,30,Business travel,Eco,566,5,0,5,4,4,5,3,4,2,1,2,5,1,4,0,0.0,satisfied +15631,117500,Male,Loyal Customer,53,Personal Travel,Eco,507,5,4,2,4,2,2,2,2,5,2,4,4,5,2,35,38.0,satisfied +15632,30479,Female,disloyal Customer,26,Business travel,Eco,1201,1,1,1,3,2,1,2,2,1,1,4,4,3,2,10,0.0,neutral or dissatisfied +15633,32751,Female,Loyal Customer,46,Business travel,Business,2135,5,5,5,5,2,1,5,4,4,4,5,5,4,3,74,74.0,satisfied +15634,26348,Female,Loyal Customer,37,Business travel,Eco Plus,834,2,3,3,3,2,2,2,2,2,3,3,2,2,2,36,19.0,neutral or dissatisfied +15635,93923,Female,Loyal Customer,48,Business travel,Business,507,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +15636,106692,Female,disloyal Customer,24,Business travel,Business,516,4,0,4,5,1,4,1,1,5,4,4,4,5,1,28,33.0,satisfied +15637,1530,Female,Loyal Customer,40,Business travel,Business,3894,2,3,3,3,4,3,4,2,2,1,2,4,2,3,0,0.0,neutral or dissatisfied +15638,68311,Male,disloyal Customer,19,Business travel,Eco,963,5,5,5,2,4,5,4,4,5,3,3,3,5,4,0,0.0,satisfied +15639,108818,Male,Loyal Customer,61,Personal Travel,Eco Plus,581,2,3,2,4,5,2,5,5,3,3,3,1,3,5,18,13.0,neutral or dissatisfied +15640,106883,Female,Loyal Customer,52,Business travel,Business,577,3,3,3,3,5,4,3,3,3,3,3,4,3,3,39,35.0,neutral or dissatisfied +15641,38773,Female,Loyal Customer,37,Business travel,Business,2505,1,3,3,3,3,3,4,1,1,2,1,3,1,1,0,0.0,neutral or dissatisfied +15642,84835,Male,Loyal Customer,18,Business travel,Business,1640,1,1,2,1,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +15643,94074,Female,Loyal Customer,40,Business travel,Business,3761,2,2,3,2,2,4,5,3,3,3,3,4,3,5,0,0.0,satisfied +15644,81616,Male,Loyal Customer,58,Business travel,Business,3431,0,0,0,3,3,4,5,2,2,2,3,4,2,4,3,0.0,satisfied +15645,35582,Male,Loyal Customer,58,Business travel,Eco Plus,1080,5,3,3,3,5,5,5,5,5,4,5,5,2,5,4,0.0,satisfied +15646,62591,Female,Loyal Customer,52,Business travel,Eco,346,4,5,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +15647,114861,Female,disloyal Customer,45,Business travel,Business,480,1,1,1,4,4,1,2,4,4,4,4,3,4,4,56,44.0,neutral or dissatisfied +15648,100422,Female,Loyal Customer,17,Personal Travel,Eco Plus,1073,1,4,1,1,2,1,2,2,5,5,5,3,4,2,2,0.0,neutral or dissatisfied +15649,40052,Male,Loyal Customer,16,Personal Travel,Eco,866,2,3,2,3,1,2,1,1,2,4,3,3,4,1,0,0.0,neutral or dissatisfied +15650,16136,Female,Loyal Customer,29,Business travel,Eco Plus,725,4,2,2,2,4,4,4,4,1,2,3,2,3,4,46,71.0,neutral or dissatisfied +15651,22743,Male,Loyal Customer,36,Business travel,Business,147,4,4,4,4,2,5,5,4,4,4,3,3,4,3,0,0.0,satisfied +15652,45571,Female,disloyal Customer,25,Business travel,Eco,1025,3,4,4,3,5,4,4,5,2,4,1,3,1,5,0,0.0,neutral or dissatisfied +15653,45171,Male,Loyal Customer,9,Personal Travel,Eco,174,3,4,3,4,4,3,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +15654,83916,Male,Loyal Customer,42,Business travel,Eco Plus,752,2,1,1,1,2,2,2,2,3,4,1,4,2,2,46,47.0,neutral or dissatisfied +15655,100289,Male,Loyal Customer,33,Business travel,Business,1011,1,1,1,1,5,5,5,5,4,2,5,4,4,5,9,0.0,satisfied +15656,47972,Male,Loyal Customer,9,Personal Travel,Eco,550,1,4,1,4,1,1,1,1,4,4,4,3,4,1,30,24.0,neutral or dissatisfied +15657,119937,Female,disloyal Customer,29,Business travel,Eco,868,2,2,2,3,2,2,2,2,4,5,3,1,4,2,0,2.0,neutral or dissatisfied +15658,30886,Female,disloyal Customer,22,Business travel,Business,1546,4,0,3,3,2,3,2,2,2,4,4,4,4,2,121,105.0,neutral or dissatisfied +15659,96735,Female,Loyal Customer,21,Personal Travel,Eco,696,4,5,4,5,5,4,5,5,5,4,4,4,5,5,42,17.0,neutral or dissatisfied +15660,58615,Female,Loyal Customer,42,Business travel,Business,1507,2,2,2,2,2,5,4,3,3,4,3,4,3,5,15,6.0,satisfied +15661,93739,Female,Loyal Customer,60,Business travel,Business,1513,2,2,2,2,2,5,5,4,4,5,4,3,4,5,49,51.0,satisfied +15662,72609,Female,Loyal Customer,54,Personal Travel,Eco,1121,5,5,5,3,5,5,4,1,1,5,1,3,1,3,0,0.0,satisfied +15663,128437,Male,Loyal Customer,59,Business travel,Business,2101,3,4,4,4,1,1,1,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +15664,85319,Male,Loyal Customer,46,Personal Travel,Eco,1282,2,4,2,1,5,2,5,5,3,4,4,5,4,5,35,14.0,neutral or dissatisfied +15665,122311,Female,disloyal Customer,28,Business travel,Business,541,3,3,3,3,3,3,4,3,4,2,4,5,5,3,1,6.0,neutral or dissatisfied +15666,26634,Female,Loyal Customer,33,Business travel,Eco,270,2,1,1,1,2,3,2,2,3,2,4,3,4,2,0,10.0,neutral or dissatisfied +15667,102704,Female,Loyal Customer,43,Business travel,Business,2478,3,3,3,3,3,2,3,3,3,4,4,3,3,3,0,0.0,satisfied +15668,62164,Male,Loyal Customer,45,Business travel,Eco,2425,3,3,5,5,2,3,2,2,1,2,2,3,3,2,8,0.0,neutral or dissatisfied +15669,104392,Male,Loyal Customer,39,Business travel,Business,1024,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,3.0,satisfied +15670,61241,Female,disloyal Customer,20,Business travel,Eco,967,3,3,3,2,5,3,5,5,4,2,2,3,5,5,6,0.0,satisfied +15671,9163,Male,Loyal Customer,26,Personal Travel,Eco,946,4,2,4,3,1,4,1,1,3,3,4,4,3,1,4,13.0,neutral or dissatisfied +15672,12344,Female,disloyal Customer,36,Business travel,Eco,253,2,0,2,2,2,2,2,2,2,3,4,4,4,2,0,0.0,neutral or dissatisfied +15673,66375,Female,Loyal Customer,8,Personal Travel,Eco Plus,986,1,4,2,4,1,2,1,1,4,4,5,4,5,1,14,3.0,neutral or dissatisfied +15674,50596,Male,Loyal Customer,65,Personal Travel,Eco,109,3,4,3,4,2,3,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +15675,110728,Female,Loyal Customer,39,Business travel,Business,2446,2,2,2,2,4,4,5,5,5,5,5,3,5,5,2,0.0,satisfied +15676,50726,Male,Loyal Customer,16,Personal Travel,Eco,308,1,5,1,2,4,1,4,4,4,3,4,5,5,4,0,0.0,neutral or dissatisfied +15677,119566,Male,Loyal Customer,57,Business travel,Business,3320,5,5,5,5,3,5,5,4,4,4,4,5,4,5,4,7.0,satisfied +15678,5744,Male,Loyal Customer,41,Business travel,Business,3273,2,2,2,2,2,4,3,2,2,2,2,4,2,3,0,1.0,neutral or dissatisfied +15679,124246,Male,Loyal Customer,52,Personal Travel,Eco,1916,4,3,4,3,4,4,4,4,4,2,4,4,3,4,27,33.0,neutral or dissatisfied +15680,69570,Female,Loyal Customer,44,Business travel,Eco,2475,2,5,5,5,2,2,2,1,5,2,4,2,2,2,0,14.0,neutral or dissatisfied +15681,12527,Male,Loyal Customer,26,Business travel,Eco,871,5,3,3,3,5,5,5,5,2,4,4,1,5,5,8,10.0,satisfied +15682,80460,Female,disloyal Customer,45,Business travel,Business,1299,2,2,2,3,2,2,2,2,5,4,4,5,5,2,5,0.0,neutral or dissatisfied +15683,120789,Male,Loyal Customer,57,Personal Travel,Eco,678,3,4,3,2,1,3,2,1,5,5,4,1,2,1,0,2.0,neutral or dissatisfied +15684,50533,Male,Loyal Customer,40,Personal Travel,Eco,158,2,2,2,4,1,2,1,1,1,4,4,3,3,1,0,4.0,neutral or dissatisfied +15685,119935,Male,Loyal Customer,34,Business travel,Business,868,4,4,4,4,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +15686,1617,Male,Loyal Customer,69,Personal Travel,Eco,968,3,5,3,2,5,3,5,5,4,3,4,4,5,5,0,10.0,neutral or dissatisfied +15687,113051,Male,Loyal Customer,54,Business travel,Business,2349,5,5,5,5,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +15688,9405,Female,Loyal Customer,57,Business travel,Business,1849,3,3,3,3,4,4,5,4,4,5,4,3,4,5,0,3.0,satisfied +15689,35648,Male,disloyal Customer,25,Business travel,Eco,781,5,5,5,4,5,2,2,3,1,3,5,2,4,2,3,3.0,satisfied +15690,93835,Male,disloyal Customer,24,Business travel,Eco,391,2,5,2,4,4,2,4,4,1,4,2,2,3,4,19,51.0,neutral or dissatisfied +15691,70433,Female,Loyal Customer,40,Business travel,Business,3127,4,4,4,4,5,4,4,5,5,5,4,4,5,5,0,0.0,satisfied +15692,72080,Female,Loyal Customer,52,Business travel,Business,1004,1,1,4,1,4,4,4,5,5,5,5,3,5,4,5,0.0,satisfied +15693,37784,Male,Loyal Customer,28,Business travel,Eco Plus,1010,3,4,4,4,3,3,3,3,4,5,3,2,3,3,0,4.0,neutral or dissatisfied +15694,67516,Female,disloyal Customer,36,Business travel,Business,1126,3,3,3,3,2,3,2,2,4,5,4,4,5,2,0,17.0,neutral or dissatisfied +15695,119357,Male,Loyal Customer,56,Business travel,Business,2822,0,4,0,3,4,4,4,4,4,4,4,3,4,4,0,35.0,satisfied +15696,25364,Female,Loyal Customer,53,Business travel,Business,2139,1,1,1,1,2,2,2,4,4,4,4,3,4,4,4,24.0,satisfied +15697,78291,Male,Loyal Customer,53,Business travel,Business,1598,2,2,2,2,3,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +15698,12509,Female,Loyal Customer,26,Personal Travel,Eco Plus,190,1,1,1,2,2,1,2,2,4,4,1,2,2,2,103,102.0,neutral or dissatisfied +15699,114928,Female,Loyal Customer,46,Business travel,Business,2492,2,2,2,2,2,4,4,5,5,5,5,5,5,3,33,44.0,satisfied +15700,1072,Female,Loyal Customer,53,Personal Travel,Eco,113,3,2,3,3,2,3,2,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +15701,68524,Female,disloyal Customer,21,Business travel,Business,1013,5,0,5,3,5,5,5,5,3,4,4,4,4,5,26,28.0,satisfied +15702,33962,Male,Loyal Customer,47,Business travel,Business,1576,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +15703,92547,Male,Loyal Customer,63,Personal Travel,Eco,1892,1,5,1,4,2,1,2,2,2,3,4,3,5,2,9,3.0,neutral or dissatisfied +15704,19367,Female,Loyal Customer,45,Business travel,Business,3960,2,2,2,2,5,2,3,3,3,3,3,5,3,3,22,13.0,satisfied +15705,77695,Male,disloyal Customer,16,Business travel,Eco,689,4,4,4,5,1,4,1,1,3,2,5,5,5,1,0,0.0,neutral or dissatisfied +15706,73199,Female,Loyal Customer,46,Business travel,Business,3241,2,2,2,2,1,3,3,2,2,2,2,4,2,4,2,0.0,neutral or dissatisfied +15707,56931,Female,disloyal Customer,25,Business travel,Eco,1101,2,2,2,3,2,5,5,3,1,4,4,5,1,5,0,0.0,neutral or dissatisfied +15708,16635,Female,Loyal Customer,21,Business travel,Business,3903,1,1,1,1,5,4,5,5,3,3,3,3,4,5,0,3.0,satisfied +15709,4331,Male,Loyal Customer,59,Personal Travel,Eco Plus,665,3,2,3,4,5,3,5,5,1,1,4,4,3,5,1,0.0,neutral or dissatisfied +15710,60842,Male,Loyal Customer,61,Business travel,Business,1754,3,2,2,2,5,2,1,3,3,3,3,2,3,1,7,15.0,neutral or dissatisfied +15711,118252,Male,Loyal Customer,39,Business travel,Business,1849,2,2,2,2,2,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +15712,38430,Male,Loyal Customer,51,Business travel,Eco Plus,965,5,3,3,3,5,5,5,5,5,3,3,2,3,5,0,0.0,satisfied +15713,97792,Male,Loyal Customer,41,Business travel,Business,2396,3,3,3,3,3,5,4,2,2,2,2,5,2,5,1,2.0,satisfied +15714,32750,Female,Loyal Customer,53,Business travel,Business,3235,4,4,4,4,4,2,2,5,5,5,3,2,5,3,0,2.0,satisfied +15715,18271,Female,Loyal Customer,21,Personal Travel,Eco,235,5,5,5,2,4,5,4,4,5,4,4,5,5,4,0,0.0,satisfied +15716,29947,Female,Loyal Customer,50,Business travel,Business,95,1,5,5,5,3,3,2,2,2,2,1,1,2,3,0,,neutral or dissatisfied +15717,18336,Male,Loyal Customer,61,Personal Travel,Eco,554,2,4,2,4,4,2,4,4,5,3,4,4,4,4,110,98.0,neutral or dissatisfied +15718,35624,Male,Loyal Customer,63,Personal Travel,Eco Plus,1035,3,1,3,4,2,3,2,2,1,4,4,1,3,2,0,65.0,neutral or dissatisfied +15719,6311,Male,Loyal Customer,32,Business travel,Business,240,1,1,1,1,5,5,5,5,3,5,5,4,4,5,70,,satisfied +15720,123743,Female,Loyal Customer,36,Business travel,Eco,96,3,2,2,2,3,3,3,3,2,1,4,4,3,3,24,15.0,neutral or dissatisfied +15721,39160,Male,disloyal Customer,21,Business travel,Eco,296,2,5,2,3,3,2,2,3,1,4,5,4,4,3,0,0.0,neutral or dissatisfied +15722,46696,Female,Loyal Customer,65,Personal Travel,Eco,125,4,3,4,3,4,3,4,4,4,4,4,2,4,4,0,11.0,neutral or dissatisfied +15723,67035,Female,Loyal Customer,57,Business travel,Business,2436,2,2,2,2,2,5,4,2,2,2,2,5,2,5,8,38.0,satisfied +15724,2179,Male,Loyal Customer,49,Business travel,Business,1623,2,4,4,4,4,3,4,2,2,2,2,3,2,3,0,4.0,neutral or dissatisfied +15725,29780,Female,Loyal Customer,55,Personal Travel,Business,261,3,2,0,3,1,4,4,3,3,0,3,1,3,1,0,0.0,neutral or dissatisfied +15726,92580,Female,Loyal Customer,17,Personal Travel,Eco Plus,2092,4,4,4,5,4,4,1,4,4,5,4,4,5,4,0,9.0,neutral or dissatisfied +15727,50451,Male,Loyal Customer,16,Business travel,Eco,209,4,5,5,5,4,4,4,4,1,4,3,1,3,4,0,0.0,neutral or dissatisfied +15728,100889,Male,Loyal Customer,42,Business travel,Business,377,5,5,5,5,2,5,5,3,3,3,3,3,3,3,29,29.0,satisfied +15729,74686,Male,Loyal Customer,43,Personal Travel,Eco,1171,4,4,4,1,5,4,5,5,5,4,4,4,4,5,0,0.0,neutral or dissatisfied +15730,75785,Female,Loyal Customer,43,Personal Travel,Eco,868,2,2,3,3,1,4,3,5,5,3,5,1,5,2,15,10.0,neutral or dissatisfied +15731,59704,Female,Loyal Customer,35,Personal Travel,Eco,964,4,4,4,4,3,4,3,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +15732,28464,Female,Loyal Customer,64,Personal Travel,Eco,2588,1,2,1,3,1,3,2,1,3,4,3,2,1,2,0,23.0,neutral or dissatisfied +15733,83552,Female,disloyal Customer,24,Business travel,Business,1034,5,5,5,2,5,5,5,5,5,5,5,5,4,5,0,0.0,satisfied +15734,44717,Female,Loyal Customer,19,Personal Travel,Eco,67,2,4,2,3,1,2,1,1,4,2,5,4,4,1,82,70.0,neutral or dissatisfied +15735,110,Female,disloyal Customer,27,Business travel,Business,562,5,5,5,3,2,5,2,2,4,5,4,5,5,2,0,0.0,satisfied +15736,53628,Male,Loyal Customer,38,Business travel,Business,3112,1,1,5,1,5,4,5,5,5,5,5,3,5,5,0,1.0,satisfied +15737,88767,Female,Loyal Customer,40,Business travel,Business,442,3,3,3,3,5,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +15738,27951,Male,disloyal Customer,44,Business travel,Eco,897,3,3,3,4,1,3,1,1,2,4,5,5,3,1,11,0.0,neutral or dissatisfied +15739,61877,Female,Loyal Customer,14,Business travel,Eco,2521,2,4,4,4,2,2,1,2,1,1,4,4,4,2,0,5.0,neutral or dissatisfied +15740,29925,Female,disloyal Customer,35,Business travel,Eco,82,2,2,3,4,4,3,3,4,4,1,4,2,4,4,0,0.0,neutral or dissatisfied +15741,42859,Female,Loyal Customer,17,Personal Travel,Eco,328,4,5,4,4,5,4,5,5,1,5,2,5,4,5,0,0.0,neutral or dissatisfied +15742,59940,Male,Loyal Customer,31,Business travel,Business,1065,2,4,4,4,2,2,2,2,1,5,3,2,3,2,0,0.0,neutral or dissatisfied +15743,50425,Male,Loyal Customer,37,Business travel,Business,3778,4,3,1,1,1,4,4,4,4,4,4,2,4,1,0,4.0,neutral or dissatisfied +15744,13084,Female,Loyal Customer,65,Personal Travel,Business,595,3,2,3,3,5,3,4,3,3,3,3,3,3,1,93,97.0,neutral or dissatisfied +15745,4464,Male,Loyal Customer,60,Business travel,Eco,605,4,4,4,4,4,4,4,4,1,2,4,3,4,4,0,6.0,satisfied +15746,24340,Male,Loyal Customer,24,Business travel,Business,2386,2,5,4,5,2,2,2,2,1,4,3,1,2,2,0,0.0,neutral or dissatisfied +15747,87825,Female,disloyal Customer,80,Business travel,Business,214,2,1,1,4,1,3,2,5,5,2,5,3,5,3,12,0.0,satisfied +15748,126145,Male,Loyal Customer,24,Business travel,Business,650,1,4,1,4,1,1,1,1,1,2,2,3,3,1,9,0.0,neutral or dissatisfied +15749,63710,Male,disloyal Customer,27,Business travel,Business,160,1,2,2,3,1,2,1,1,3,2,5,4,4,1,65,51.0,neutral or dissatisfied +15750,2161,Female,Loyal Customer,39,Business travel,Business,1671,1,1,1,1,3,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +15751,12721,Male,disloyal Customer,14,Business travel,Eco,803,3,2,2,3,2,4,4,1,2,3,4,4,1,4,195,184.0,neutral or dissatisfied +15752,26010,Female,disloyal Customer,38,Business travel,Eco,425,2,3,2,3,3,2,3,3,2,3,3,2,2,3,9,0.0,neutral or dissatisfied +15753,106349,Male,Loyal Customer,21,Personal Travel,Business,674,3,5,2,3,2,2,1,2,5,3,4,5,4,2,11,16.0,neutral or dissatisfied +15754,119942,Female,disloyal Customer,30,Business travel,Eco,1009,3,3,3,1,5,3,5,5,1,3,2,4,2,5,0,2.0,neutral or dissatisfied +15755,17546,Female,disloyal Customer,16,Business travel,Eco,908,1,1,1,2,4,1,4,4,5,3,1,2,1,4,0,1.0,neutral or dissatisfied +15756,91669,Female,Loyal Customer,23,Personal Travel,Eco Plus,1199,5,2,5,3,5,2,5,5,2,2,4,1,4,5,0,0.0,satisfied +15757,53205,Female,Loyal Customer,32,Business travel,Business,612,3,4,4,4,3,3,3,3,2,5,3,1,3,3,22,55.0,neutral or dissatisfied +15758,35421,Male,Loyal Customer,65,Personal Travel,Eco,1074,5,4,5,3,5,5,5,5,5,4,4,3,5,5,6,13.0,satisfied +15759,47110,Male,Loyal Customer,43,Business travel,Business,2076,2,2,2,2,5,2,4,5,5,5,5,1,5,5,0,0.0,satisfied +15760,30600,Female,Loyal Customer,42,Business travel,Business,3576,4,4,4,4,1,3,1,4,4,4,4,5,4,1,0,2.0,satisfied +15761,64088,Female,Loyal Customer,39,Personal Travel,Eco,919,1,4,1,4,5,1,5,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +15762,64770,Female,Loyal Customer,56,Business travel,Business,1916,4,4,4,4,4,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +15763,129170,Female,Loyal Customer,47,Personal Travel,Eco,954,1,1,0,3,1,4,3,4,4,0,4,3,4,4,0,0.0,neutral or dissatisfied +15764,101634,Female,disloyal Customer,29,Business travel,Business,1371,0,1,1,3,4,1,4,4,5,5,4,5,4,4,9,0.0,satisfied +15765,54228,Female,Loyal Customer,25,Business travel,Eco,1222,5,4,4,4,5,5,5,5,1,3,1,2,3,5,0,2.0,satisfied +15766,78215,Female,Loyal Customer,30,Personal Travel,Eco,259,4,5,4,5,5,4,5,5,3,4,1,3,4,5,0,0.0,neutral or dissatisfied +15767,61218,Female,Loyal Customer,50,Business travel,Business,2734,2,2,2,2,2,5,5,4,4,3,4,4,4,3,0,0.0,satisfied +15768,102743,Male,Loyal Customer,40,Personal Travel,Eco,255,3,5,3,1,2,3,4,2,4,2,5,4,5,2,5,0.0,neutral or dissatisfied +15769,124394,Female,Loyal Customer,31,Business travel,Business,1806,2,2,2,2,2,2,2,2,3,5,4,4,5,2,0,0.0,satisfied +15770,111365,Female,Loyal Customer,44,Business travel,Business,1050,3,3,3,3,3,4,5,5,5,5,5,5,5,3,21,55.0,satisfied +15771,108608,Male,Loyal Customer,29,Business travel,Business,3419,3,3,3,3,4,5,4,4,5,4,5,2,4,4,0,0.0,satisfied +15772,17370,Male,Loyal Customer,23,Personal Travel,Eco Plus,563,1,3,1,3,3,1,3,3,5,5,2,3,5,3,0,0.0,neutral or dissatisfied +15773,7287,Male,Loyal Customer,45,Personal Travel,Eco,139,2,0,2,3,5,2,5,5,4,5,3,4,4,5,33,36.0,neutral or dissatisfied +15774,109914,Male,Loyal Customer,13,Personal Travel,Eco,1165,0,4,0,2,5,0,5,5,3,4,4,3,4,5,0,0.0,satisfied +15775,86011,Female,Loyal Customer,68,Business travel,Business,1954,4,3,5,5,5,3,3,4,4,4,4,4,4,2,30,41.0,neutral or dissatisfied +15776,77874,Male,Loyal Customer,33,Business travel,Business,1416,2,2,2,2,4,4,4,4,4,3,5,5,5,4,0,4.0,satisfied +15777,59620,Female,Loyal Customer,30,Business travel,Business,965,5,3,3,3,5,4,5,5,4,4,3,2,4,5,39,25.0,neutral or dissatisfied +15778,4081,Female,Loyal Customer,50,Business travel,Business,544,4,2,2,2,2,3,3,4,4,3,4,3,4,2,0,2.0,neutral or dissatisfied +15779,128662,Male,Loyal Customer,25,Business travel,Business,2419,1,1,1,1,4,4,4,5,3,5,4,4,5,4,2,0.0,satisfied +15780,29733,Male,disloyal Customer,44,Business travel,Eco,1052,3,3,3,4,3,3,3,3,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +15781,87810,Female,Loyal Customer,62,Business travel,Eco,214,3,2,2,2,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +15782,128474,Female,Loyal Customer,51,Personal Travel,Eco,621,2,4,2,1,2,4,4,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +15783,4586,Female,Loyal Customer,55,Business travel,Business,3068,5,5,4,5,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +15784,56963,Male,disloyal Customer,85,Business travel,Eco,954,4,5,5,4,5,4,4,2,2,4,3,4,1,4,0,9.0,neutral or dissatisfied +15785,114076,Male,Loyal Customer,57,Business travel,Business,1947,4,2,2,2,5,2,3,4,4,4,4,1,4,4,0,5.0,neutral or dissatisfied +15786,27161,Female,Loyal Customer,39,Business travel,Business,2701,3,1,3,3,4,4,4,5,1,4,1,4,4,4,0,0.0,satisfied +15787,122494,Female,Loyal Customer,58,Business travel,Business,2235,3,3,3,3,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +15788,117185,Female,Loyal Customer,33,Personal Travel,Eco,304,1,5,1,1,3,1,3,3,4,2,5,4,5,3,0,1.0,neutral or dissatisfied +15789,12173,Male,disloyal Customer,27,Business travel,Eco,1042,4,4,4,4,2,4,2,2,2,3,4,4,3,2,11,0.0,neutral or dissatisfied +15790,81419,Female,Loyal Customer,41,Business travel,Business,393,2,2,2,2,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +15791,7146,Male,Loyal Customer,36,Business travel,Business,1761,5,5,5,5,4,5,4,4,4,4,5,4,4,3,0,11.0,satisfied +15792,129833,Female,Loyal Customer,37,Personal Travel,Eco,337,1,4,2,4,3,2,3,3,3,3,4,4,5,3,0,0.0,neutral or dissatisfied +15793,16168,Female,disloyal Customer,44,Business travel,Eco,277,2,4,2,2,5,2,5,5,1,1,5,2,4,5,57,43.0,neutral or dissatisfied +15794,92183,Female,Loyal Customer,56,Business travel,Business,1979,1,1,1,1,5,3,5,5,5,5,5,3,5,3,0,15.0,satisfied +15795,95392,Female,Loyal Customer,13,Personal Travel,Eco,441,3,4,3,2,5,3,5,5,5,5,3,4,3,5,13,0.0,neutral or dissatisfied +15796,24048,Female,Loyal Customer,59,Personal Travel,Eco,427,2,5,2,2,3,4,4,1,1,2,3,4,1,3,0,0.0,neutral or dissatisfied +15797,67149,Female,Loyal Customer,22,Business travel,Eco,1121,5,1,1,1,5,5,3,5,4,4,3,1,5,5,4,3.0,satisfied +15798,6380,Female,Loyal Customer,43,Business travel,Business,213,5,5,4,5,4,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +15799,7471,Female,disloyal Customer,21,Business travel,Business,110,2,4,2,3,5,2,5,5,1,4,3,4,3,5,5,2.0,neutral or dissatisfied +15800,24011,Male,Loyal Customer,75,Business travel,Eco,427,2,2,2,2,2,2,2,2,4,1,4,3,3,2,5,0.0,neutral or dissatisfied +15801,13951,Male,Loyal Customer,15,Personal Travel,Eco,317,2,2,1,3,3,1,5,3,2,4,4,1,3,3,0,0.0,neutral or dissatisfied +15802,61837,Female,Loyal Customer,43,Business travel,Business,1464,4,4,4,4,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +15803,16694,Male,disloyal Customer,38,Business travel,Eco,200,4,5,4,4,4,4,3,4,5,3,3,2,2,4,0,0.0,satisfied +15804,31717,Male,Loyal Customer,54,Personal Travel,Eco,862,3,5,3,2,2,3,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +15805,33656,Male,Loyal Customer,47,Business travel,Eco Plus,399,4,5,5,5,4,4,4,4,4,3,1,5,5,4,0,0.0,satisfied +15806,112381,Female,Loyal Customer,25,Business travel,Business,2260,3,3,3,3,3,3,3,3,4,5,3,3,3,3,6,20.0,neutral or dissatisfied +15807,41464,Female,Loyal Customer,54,Business travel,Business,2739,1,1,1,1,3,2,5,5,5,5,5,3,5,2,0,8.0,satisfied +15808,112472,Female,Loyal Customer,63,Personal Travel,Eco,967,5,2,5,4,4,4,4,1,1,5,1,4,1,1,27,14.0,satisfied +15809,85976,Female,disloyal Customer,25,Business travel,Business,554,1,5,1,3,4,1,4,4,5,2,4,4,5,4,11,0.0,neutral or dissatisfied +15810,6536,Male,Loyal Customer,58,Business travel,Business,2801,1,1,1,1,2,5,4,3,3,4,3,5,3,5,4,5.0,satisfied +15811,88667,Female,Loyal Customer,65,Personal Travel,Eco,515,2,5,2,1,3,4,5,4,4,2,2,5,4,3,45,41.0,neutral or dissatisfied +15812,74966,Female,Loyal Customer,24,Personal Travel,Eco,2475,1,3,0,3,3,0,3,3,2,3,2,3,3,3,0,0.0,neutral or dissatisfied +15813,77518,Male,Loyal Customer,25,Business travel,Business,1521,3,3,3,3,5,5,5,5,1,2,1,4,2,5,0,0.0,satisfied +15814,23996,Female,Loyal Customer,37,Business travel,Business,3326,4,4,4,4,5,3,5,4,4,4,4,5,4,2,0,0.0,satisfied +15815,73069,Female,Loyal Customer,39,Business travel,Business,2561,1,5,5,5,1,4,4,1,1,1,1,4,1,3,108,111.0,neutral or dissatisfied +15816,40215,Male,Loyal Customer,48,Business travel,Business,436,5,5,5,5,4,3,3,5,5,5,5,1,5,5,0,0.0,satisfied +15817,15581,Female,Loyal Customer,27,Business travel,Business,2380,3,5,5,5,3,3,3,3,3,2,3,4,3,3,0,0.0,neutral or dissatisfied +15818,34199,Male,Loyal Customer,9,Personal Travel,Eco,1046,3,2,2,3,1,2,5,1,2,1,2,1,3,1,1,29.0,neutral or dissatisfied +15819,44240,Female,Loyal Customer,59,Business travel,Business,1647,2,2,4,2,5,4,3,2,2,2,2,3,2,4,0,3.0,neutral or dissatisfied +15820,124739,Male,Loyal Customer,21,Personal Travel,Eco Plus,399,4,5,4,1,1,4,1,1,4,2,5,3,4,1,0,7.0,satisfied +15821,126920,Male,Loyal Customer,41,Personal Travel,Business,651,3,2,3,4,4,3,3,2,2,3,2,2,2,1,0,1.0,neutral or dissatisfied +15822,120290,Female,Loyal Customer,14,Personal Travel,Eco,1576,3,4,3,3,5,3,5,5,5,2,4,3,5,5,30,39.0,neutral or dissatisfied +15823,4655,Male,disloyal Customer,25,Business travel,Business,364,2,2,2,4,4,2,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +15824,11762,Male,Loyal Customer,53,Business travel,Business,429,1,1,1,1,2,4,1,4,4,4,4,2,4,5,0,5.0,satisfied +15825,118119,Male,Loyal Customer,58,Personal Travel,Eco,1300,1,4,1,4,2,1,2,2,4,2,3,4,5,2,0,0.0,neutral or dissatisfied +15826,114206,Male,Loyal Customer,16,Business travel,Business,957,1,2,1,1,4,4,4,4,3,3,5,3,4,4,0,0.0,satisfied +15827,53582,Female,Loyal Customer,24,Business travel,Eco Plus,1195,1,1,1,1,1,1,4,1,3,2,4,4,4,1,3,2.0,neutral or dissatisfied +15828,128300,Male,Loyal Customer,40,Business travel,Business,621,1,1,4,1,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +15829,98417,Female,Loyal Customer,23,Personal Travel,Business,2176,2,2,2,4,1,2,1,1,3,3,3,1,3,1,17,0.0,neutral or dissatisfied +15830,49886,Female,Loyal Customer,49,Business travel,Business,2516,3,3,3,3,2,4,5,5,5,5,5,1,5,5,0,0.0,satisfied +15831,73855,Male,Loyal Customer,30,Personal Travel,Eco,1709,1,5,1,3,3,1,4,3,5,2,5,2,3,3,0,0.0,neutral or dissatisfied +15832,12589,Female,Loyal Customer,72,Business travel,Business,1886,2,3,3,3,1,4,4,2,2,2,2,2,2,1,2,16.0,neutral or dissatisfied +15833,16914,Female,Loyal Customer,53,Business travel,Eco Plus,746,4,5,4,5,2,3,2,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +15834,19089,Male,Loyal Customer,31,Business travel,Eco,296,0,0,0,2,5,0,5,5,3,1,1,3,2,5,0,0.0,satisfied +15835,60056,Female,Loyal Customer,51,Personal Travel,Eco Plus,1023,4,2,4,4,4,3,3,2,2,4,2,3,2,1,0,0.0,satisfied +15836,30070,Female,Loyal Customer,47,Personal Travel,Eco,183,5,4,5,3,5,5,4,3,3,5,3,4,3,4,11,14.0,satisfied +15837,12730,Female,Loyal Customer,25,Personal Travel,Eco,689,3,4,3,4,2,3,1,2,4,2,4,5,5,2,0,0.0,neutral or dissatisfied +15838,42777,Female,Loyal Customer,67,Personal Travel,Business,744,2,3,2,2,5,3,5,3,3,2,2,1,3,4,52,47.0,neutral or dissatisfied +15839,48846,Female,Loyal Customer,24,Personal Travel,Business,372,3,3,3,2,4,3,4,4,1,4,3,3,2,4,64,60.0,neutral or dissatisfied +15840,39217,Female,Loyal Customer,33,Business travel,Eco,67,0,1,1,4,4,1,4,4,4,2,1,2,2,4,0,13.0,satisfied +15841,63383,Male,Loyal Customer,24,Personal Travel,Eco,337,3,4,3,3,4,3,3,4,4,5,5,5,5,4,108,116.0,neutral or dissatisfied +15842,111780,Male,Loyal Customer,43,Business travel,Eco,1620,1,5,3,5,1,1,1,1,1,5,4,1,3,1,0,0.0,neutral or dissatisfied +15843,60804,Female,Loyal Customer,25,Personal Travel,Eco Plus,472,2,1,2,3,2,2,2,2,4,1,3,4,2,2,0,0.0,neutral or dissatisfied +15844,104958,Female,Loyal Customer,45,Business travel,Business,337,1,1,1,1,4,4,5,5,5,5,5,4,5,3,15,9.0,satisfied +15845,53289,Male,Loyal Customer,51,Business travel,Business,3591,3,3,3,3,4,1,2,4,4,4,4,1,4,5,4,0.0,satisfied +15846,18550,Female,disloyal Customer,36,Business travel,Eco,190,4,0,3,5,3,3,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +15847,111535,Male,disloyal Customer,29,Business travel,Business,775,3,4,4,2,1,4,1,1,3,5,4,4,5,1,46,77.0,neutral or dissatisfied +15848,1017,Male,Loyal Customer,61,Business travel,Business,2400,2,2,2,2,4,3,3,4,4,5,4,4,4,3,0,3.0,satisfied +15849,77912,Female,Loyal Customer,41,Business travel,Business,2498,4,4,4,4,4,5,5,4,4,4,4,3,4,3,0,1.0,satisfied +15850,106150,Male,Loyal Customer,57,Business travel,Eco,302,4,2,1,1,4,4,4,4,5,5,5,4,3,4,10,2.0,satisfied +15851,8456,Male,Loyal Customer,60,Business travel,Business,1379,5,5,5,5,2,5,4,4,4,5,4,4,4,4,35,28.0,satisfied +15852,125653,Male,Loyal Customer,54,Business travel,Business,899,4,4,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +15853,21337,Female,Loyal Customer,27,Business travel,Business,674,3,3,3,3,3,3,3,3,3,4,4,2,3,3,39,37.0,neutral or dissatisfied +15854,89615,Female,Loyal Customer,42,Business travel,Business,944,2,2,2,2,2,5,4,3,3,3,3,3,3,3,7,0.0,satisfied +15855,62939,Male,Loyal Customer,27,Business travel,Business,3255,5,5,5,5,4,4,4,4,4,3,4,4,4,4,16,0.0,satisfied +15856,74056,Male,disloyal Customer,40,Business travel,Business,2527,5,0,0,2,0,1,1,5,2,5,5,1,3,1,0,0.0,satisfied +15857,18458,Female,disloyal Customer,37,Business travel,Eco,192,2,0,2,2,5,2,5,5,1,1,2,5,4,5,0,0.0,neutral or dissatisfied +15858,11059,Male,Loyal Customer,14,Personal Travel,Eco,140,3,3,3,3,3,3,3,3,2,4,1,2,2,3,29,24.0,neutral or dissatisfied +15859,98213,Male,Loyal Customer,49,Business travel,Eco,842,2,5,5,5,2,2,2,2,1,3,3,2,3,2,0,0.0,neutral or dissatisfied +15860,96048,Male,disloyal Customer,11,Business travel,Business,1069,3,1,4,4,2,4,2,2,1,2,4,2,3,2,14,9.0,neutral or dissatisfied +15861,64789,Female,Loyal Customer,34,Business travel,Business,3840,2,5,3,3,1,3,2,2,2,2,2,2,2,3,35,46.0,neutral or dissatisfied +15862,122957,Male,Loyal Customer,57,Business travel,Business,2303,3,3,3,3,5,5,4,5,5,5,5,4,5,4,8,0.0,satisfied +15863,26490,Male,Loyal Customer,25,Business travel,Business,829,1,1,1,1,3,5,3,3,2,1,2,2,5,3,53,37.0,satisfied +15864,93965,Female,Loyal Customer,51,Business travel,Business,1670,3,3,3,3,3,5,4,2,2,2,2,3,2,3,5,0.0,satisfied +15865,27493,Male,disloyal Customer,56,Business travel,Eco,554,3,5,3,3,5,3,5,5,5,2,1,5,3,5,0,5.0,neutral or dissatisfied +15866,105762,Male,disloyal Customer,24,Business travel,Eco,263,3,1,3,4,2,3,5,2,2,2,4,3,4,2,1,7.0,neutral or dissatisfied +15867,3243,Female,Loyal Customer,46,Business travel,Business,479,3,3,2,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +15868,9220,Male,Loyal Customer,37,Business travel,Business,3741,4,4,4,4,2,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +15869,9010,Female,Loyal Customer,46,Personal Travel,Business,173,2,4,2,2,5,3,4,4,4,2,4,3,4,3,3,1.0,neutral or dissatisfied +15870,40608,Male,Loyal Customer,59,Personal Travel,Eco,391,2,4,2,5,2,2,1,2,3,4,4,3,4,2,3,0.0,neutral or dissatisfied +15871,45396,Female,Loyal Customer,54,Personal Travel,Eco,1437,3,5,3,1,5,3,4,3,3,3,3,5,3,3,41,31.0,neutral or dissatisfied +15872,4718,Male,Loyal Customer,21,Business travel,Business,364,3,3,3,3,5,5,5,5,4,3,5,4,4,5,0,0.0,satisfied +15873,66052,Female,Loyal Customer,54,Business travel,Business,945,4,4,4,4,1,3,2,5,5,5,5,5,5,1,0,19.0,satisfied +15874,31178,Female,Loyal Customer,52,Business travel,Eco,1620,5,3,3,3,2,5,4,5,5,5,5,5,5,2,0,0.0,satisfied +15875,5013,Male,Loyal Customer,54,Personal Travel,Eco,502,3,5,3,2,2,3,2,2,4,2,5,3,4,2,0,23.0,neutral or dissatisfied +15876,69760,Male,Loyal Customer,49,Personal Travel,Eco,1085,2,4,2,3,2,2,2,2,2,4,4,3,4,2,0,0.0,neutral or dissatisfied +15877,28327,Female,Loyal Customer,28,Business travel,Business,2675,3,3,3,3,4,4,4,4,5,3,2,4,4,4,0,0.0,satisfied +15878,76813,Female,Loyal Customer,66,Personal Travel,Eco,689,3,5,4,4,5,5,4,3,3,4,3,3,3,4,0,3.0,neutral or dissatisfied +15879,120591,Female,Loyal Customer,19,Business travel,Business,980,3,4,3,4,3,2,3,3,2,1,3,4,4,3,70,117.0,neutral or dissatisfied +15880,63654,Male,Loyal Customer,29,Personal Travel,Eco,1448,1,2,1,3,4,1,4,4,4,4,3,4,4,4,0,0.0,neutral or dissatisfied +15881,31171,Male,Loyal Customer,13,Personal Travel,Eco,604,1,5,1,2,2,1,2,2,5,3,4,3,4,2,0,0.0,neutral or dissatisfied +15882,75604,Female,Loyal Customer,21,Personal Travel,Eco,337,5,5,5,5,5,5,5,5,2,2,3,4,2,5,0,3.0,satisfied +15883,115450,Female,Loyal Customer,40,Business travel,Business,2613,3,3,3,3,4,5,5,4,4,4,4,3,4,5,6,8.0,satisfied +15884,97420,Female,Loyal Customer,33,Business travel,Business,2986,2,5,5,5,4,4,4,2,2,2,2,4,2,4,9,0.0,neutral or dissatisfied +15885,47777,Male,Loyal Customer,34,Business travel,Business,748,4,4,5,4,3,1,3,5,5,5,5,1,5,5,0,0.0,satisfied +15886,28520,Male,disloyal Customer,8,Business travel,Business,2640,2,2,2,4,5,2,5,5,1,5,3,4,4,5,0,0.0,neutral or dissatisfied +15887,3127,Male,Loyal Customer,22,Business travel,Eco Plus,1013,2,5,5,5,2,2,1,2,3,1,4,1,3,2,0,14.0,neutral or dissatisfied +15888,116108,Male,Loyal Customer,35,Personal Travel,Eco,390,2,2,2,3,1,2,1,1,3,2,3,3,4,1,0,15.0,neutral or dissatisfied +15889,8397,Female,Loyal Customer,26,Personal Travel,Eco,888,4,5,4,4,5,4,5,5,3,4,5,3,4,5,36,35.0,neutral or dissatisfied +15890,2790,Male,Loyal Customer,44,Business travel,Business,765,3,5,2,5,4,2,3,3,3,3,3,4,3,2,0,7.0,neutral or dissatisfied +15891,26675,Male,Loyal Customer,19,Personal Travel,Eco,515,3,5,3,5,3,3,2,3,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +15892,44084,Male,Loyal Customer,40,Business travel,Business,440,1,1,4,1,5,2,4,3,3,3,3,2,3,2,0,0.0,satisfied +15893,117954,Male,Loyal Customer,41,Business travel,Business,255,4,3,2,3,1,4,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +15894,88687,Male,Loyal Customer,8,Personal Travel,Eco,270,4,4,4,4,1,4,1,1,3,3,4,5,4,1,1,0.0,neutral or dissatisfied +15895,122133,Female,Loyal Customer,25,Business travel,Business,544,3,1,1,1,3,3,3,3,1,4,3,2,3,3,27,38.0,neutral or dissatisfied +15896,69488,Female,disloyal Customer,11,Business travel,Business,1089,4,5,5,3,2,5,2,2,5,3,4,5,5,2,0,0.0,satisfied +15897,93473,Male,Loyal Customer,44,Business travel,Eco Plus,671,1,1,3,3,2,1,2,2,3,1,3,3,4,2,29,5.0,neutral or dissatisfied +15898,64346,Male,Loyal Customer,23,Business travel,Business,1172,4,4,4,4,4,5,4,4,3,2,5,5,4,4,0,0.0,satisfied +15899,40707,Male,disloyal Customer,16,Business travel,Eco,590,2,0,2,2,2,2,3,2,4,2,2,5,5,2,0,28.0,neutral or dissatisfied +15900,66689,Female,Loyal Customer,49,Business travel,Business,3490,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +15901,120450,Male,Loyal Customer,61,Personal Travel,Eco,449,3,4,3,3,3,3,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +15902,107298,Female,Loyal Customer,15,Personal Travel,Eco,307,2,5,2,3,4,2,5,4,5,5,2,2,2,4,29,27.0,neutral or dissatisfied +15903,42279,Female,disloyal Customer,27,Business travel,Eco,451,2,2,2,4,1,2,1,1,4,5,4,1,3,1,68,61.0,neutral or dissatisfied +15904,11874,Female,Loyal Customer,37,Personal Travel,Eco,912,4,5,4,5,4,2,4,1,4,1,1,4,2,4,207,188.0,neutral or dissatisfied +15905,109609,Male,Loyal Customer,45,Personal Travel,Business,930,2,4,2,5,3,4,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +15906,110349,Male,Loyal Customer,56,Business travel,Business,925,4,4,4,4,5,5,5,5,5,5,5,4,5,5,13,0.0,satisfied +15907,85128,Female,disloyal Customer,44,Business travel,Business,731,5,5,5,5,1,5,1,1,3,5,5,3,5,1,0,5.0,satisfied +15908,122592,Female,Loyal Customer,28,Business travel,Business,728,3,3,3,3,4,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +15909,43578,Male,Loyal Customer,56,Personal Travel,Eco,1499,4,2,4,4,4,4,4,4,1,2,3,1,4,4,9,26.0,neutral or dissatisfied +15910,52610,Female,Loyal Customer,39,Business travel,Business,3183,5,5,5,5,4,4,3,5,5,5,5,4,5,2,0,7.0,satisfied +15911,80797,Male,Loyal Customer,57,Business travel,Business,1882,3,3,2,3,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +15912,96025,Female,Loyal Customer,47,Business travel,Business,2867,3,3,3,3,5,4,4,4,4,4,4,3,4,3,0,17.0,satisfied +15913,16507,Male,Loyal Customer,10,Personal Travel,Eco,246,1,5,1,4,4,1,4,4,3,5,4,4,4,4,80,95.0,neutral or dissatisfied +15914,31197,Male,disloyal Customer,26,Business travel,Eco,628,4,2,4,2,1,4,1,1,1,1,1,3,1,1,23,42.0,neutral or dissatisfied +15915,94588,Female,Loyal Customer,52,Business travel,Business,323,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +15916,80339,Male,Loyal Customer,51,Personal Travel,Business,952,2,2,2,4,3,3,4,4,4,2,4,2,4,4,0,0.0,neutral or dissatisfied +15917,76191,Female,Loyal Customer,19,Business travel,Business,2422,4,4,4,4,3,4,3,3,5,2,5,3,5,3,2,0.0,satisfied +15918,6773,Male,Loyal Customer,42,Business travel,Business,3429,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,5.0,satisfied +15919,56175,Male,Loyal Customer,66,Business travel,Eco,1000,4,2,2,2,4,4,4,4,2,2,1,2,1,4,7,0.0,satisfied +15920,37135,Male,Loyal Customer,32,Business travel,Business,1046,3,4,3,3,5,5,5,5,5,5,2,4,5,5,25,18.0,satisfied +15921,128920,Male,disloyal Customer,34,Business travel,Business,414,3,2,2,4,3,2,3,3,1,4,4,3,3,3,8,3.0,neutral or dissatisfied +15922,108833,Male,Loyal Customer,36,Business travel,Business,1199,2,5,5,5,4,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +15923,49384,Female,disloyal Customer,40,Business travel,Business,153,5,5,5,2,4,5,1,4,2,2,3,3,1,4,50,47.0,satisfied +15924,100426,Male,Loyal Customer,58,Business travel,Business,1620,1,1,1,1,5,4,4,5,5,5,5,5,5,3,12,0.0,satisfied +15925,86804,Female,disloyal Customer,30,Business travel,Business,692,2,2,2,2,3,2,3,3,3,4,4,3,4,3,1,0.0,neutral or dissatisfied +15926,83769,Female,Loyal Customer,15,Personal Travel,Eco,926,2,5,2,2,4,2,4,4,3,2,4,3,4,4,7,0.0,neutral or dissatisfied +15927,25974,Female,Loyal Customer,34,Business travel,Eco Plus,946,4,4,4,4,4,4,4,4,1,3,4,2,4,4,24,12.0,satisfied +15928,60830,Female,Loyal Customer,47,Business travel,Business,680,3,3,5,3,4,3,3,3,3,3,3,2,3,1,37,32.0,neutral or dissatisfied +15929,63819,Male,disloyal Customer,8,Business travel,Eco,1192,3,3,3,2,3,3,5,3,1,1,3,3,2,3,0,0.0,neutral or dissatisfied +15930,12644,Male,Loyal Customer,21,Personal Travel,Eco,844,4,4,4,2,2,4,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +15931,119236,Male,Loyal Customer,51,Personal Travel,Eco,331,1,5,1,2,5,1,5,5,2,2,1,2,1,5,0,0.0,neutral or dissatisfied +15932,56000,Male,disloyal Customer,22,Business travel,Eco,2586,1,1,1,1,1,2,2,4,4,4,5,2,3,2,43,57.0,neutral or dissatisfied +15933,25931,Male,Loyal Customer,39,Personal Travel,Eco,594,4,5,4,2,1,4,1,1,1,2,4,1,1,1,4,7.0,satisfied +15934,88437,Male,Loyal Customer,44,Business travel,Business,1727,2,1,4,4,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +15935,30784,Female,Loyal Customer,50,Business travel,Business,3567,2,3,5,3,4,2,2,2,2,2,2,4,2,3,6,23.0,neutral or dissatisfied +15936,30787,Female,Loyal Customer,80,Business travel,Eco,495,4,3,5,3,3,4,3,4,4,4,4,4,4,1,11,22.0,neutral or dissatisfied +15937,26497,Male,Loyal Customer,46,Business travel,Business,829,2,2,2,2,4,3,2,4,4,4,4,3,4,4,0,0.0,satisfied +15938,83654,Female,disloyal Customer,38,Business travel,Eco,577,2,2,3,3,3,3,3,3,2,2,4,3,3,3,0,0.0,neutral or dissatisfied +15939,80427,Female,Loyal Customer,67,Business travel,Business,2248,1,3,3,3,1,1,1,3,3,1,3,1,4,1,290,271.0,neutral or dissatisfied +15940,87733,Male,Loyal Customer,19,Business travel,Business,4502,2,1,2,2,2,2,2,3,5,1,2,2,2,2,12,42.0,neutral or dissatisfied +15941,42046,Female,Loyal Customer,73,Business travel,Business,116,3,2,2,2,5,4,4,2,2,2,3,3,2,1,0,0.0,neutral or dissatisfied +15942,92013,Female,Loyal Customer,22,Business travel,Business,1576,2,2,2,2,2,2,2,2,2,4,4,3,3,2,1,0.0,neutral or dissatisfied +15943,95481,Male,Loyal Customer,30,Business travel,Eco Plus,323,4,4,4,4,4,4,4,4,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +15944,88553,Female,Loyal Customer,19,Personal Travel,Eco,366,4,4,4,5,1,4,1,1,3,3,4,3,4,1,48,44.0,neutral or dissatisfied +15945,95049,Male,Loyal Customer,8,Personal Travel,Eco,239,3,5,3,1,2,3,4,2,4,3,5,4,5,2,38,30.0,neutral or dissatisfied +15946,70694,Female,Loyal Customer,54,Business travel,Business,3207,4,4,4,4,5,5,5,5,5,4,5,5,5,5,0,0.0,satisfied +15947,105868,Male,Loyal Customer,16,Personal Travel,Eco Plus,787,3,4,3,2,4,3,4,4,5,2,5,3,5,4,0,1.0,neutral or dissatisfied +15948,103392,Female,Loyal Customer,50,Business travel,Business,237,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +15949,106262,Female,Loyal Customer,28,Business travel,Business,1500,3,3,3,3,4,4,4,4,5,5,4,3,4,4,9,8.0,satisfied +15950,105897,Male,Loyal Customer,57,Business travel,Business,3770,1,1,1,1,2,4,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +15951,100344,Male,Loyal Customer,35,Personal Travel,Eco,1053,2,4,2,3,3,2,3,3,5,5,5,3,4,3,4,1.0,neutral or dissatisfied +15952,127896,Female,Loyal Customer,39,Business travel,Business,1671,5,5,5,5,4,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +15953,15136,Male,Loyal Customer,55,Business travel,Business,2472,3,3,3,3,2,5,5,4,4,4,4,5,4,1,0,0.0,satisfied +15954,114917,Male,Loyal Customer,39,Business travel,Business,2371,2,2,5,2,4,4,4,5,5,5,5,4,5,3,21,17.0,satisfied +15955,97725,Male,disloyal Customer,23,Business travel,Business,587,4,0,4,3,4,3,3,5,3,4,4,3,4,3,152,149.0,satisfied +15956,4999,Female,Loyal Customer,41,Business travel,Business,502,2,4,3,4,5,4,4,2,2,2,2,2,2,1,7,5.0,neutral or dissatisfied +15957,111731,Male,Loyal Customer,53,Business travel,Business,1663,1,1,1,1,2,4,4,4,4,4,4,3,4,3,14,5.0,satisfied +15958,53857,Female,Loyal Customer,59,Business travel,Business,1586,5,5,5,5,3,5,4,5,5,5,3,4,5,3,0,2.0,satisfied +15959,75602,Male,Loyal Customer,24,Personal Travel,Eco,337,4,5,4,4,4,4,4,4,3,3,4,3,5,4,3,3.0,neutral or dissatisfied +15960,109632,Male,Loyal Customer,54,Business travel,Business,802,3,3,3,3,5,4,5,4,4,4,4,5,4,3,6,7.0,satisfied +15961,74084,Male,Loyal Customer,52,Business travel,Business,641,3,3,3,3,4,4,4,5,5,5,5,4,5,5,22,17.0,satisfied +15962,77676,Female,disloyal Customer,26,Business travel,Business,731,3,5,3,1,1,3,1,1,4,2,5,5,4,1,17,8.0,neutral or dissatisfied +15963,115651,Male,Loyal Customer,31,Business travel,Eco,390,2,5,4,5,2,2,2,2,1,3,3,2,4,2,31,37.0,neutral or dissatisfied +15964,19697,Female,disloyal Customer,45,Business travel,Eco,409,4,4,4,4,1,4,4,1,4,2,4,3,4,1,52,51.0,neutral or dissatisfied +15965,121152,Female,Loyal Customer,29,Business travel,Business,2521,2,4,4,4,2,2,2,3,1,2,4,2,2,2,92,136.0,neutral or dissatisfied +15966,117168,Female,Loyal Customer,68,Personal Travel,Eco,370,3,4,3,1,2,5,5,5,5,3,5,1,5,1,12,5.0,neutral or dissatisfied +15967,77465,Female,disloyal Customer,36,Business travel,Eco,507,2,2,2,3,5,2,5,5,3,1,3,2,4,5,0,0.0,neutral or dissatisfied +15968,24384,Female,Loyal Customer,46,Business travel,Eco,269,4,4,4,4,5,1,2,4,4,4,4,1,4,1,39,37.0,satisfied +15969,95002,Female,Loyal Customer,57,Personal Travel,Eco,293,4,4,4,4,5,3,3,3,3,4,3,4,3,4,0,3.0,satisfied +15970,20210,Female,Loyal Customer,20,Personal Travel,Business,137,3,0,3,2,3,3,5,3,5,2,3,5,1,3,2,29.0,neutral or dissatisfied +15971,28265,Male,Loyal Customer,25,Personal Travel,Eco,1542,2,4,2,2,1,2,1,1,5,4,3,3,4,1,0,0.0,neutral or dissatisfied +15972,60393,Female,Loyal Customer,56,Business travel,Eco,1052,2,2,4,2,3,4,4,2,2,2,2,4,2,1,5,0.0,neutral or dissatisfied +15973,48620,Female,Loyal Customer,70,Personal Travel,Eco Plus,737,5,4,5,5,5,4,5,1,1,5,1,5,1,5,0,0.0,satisfied +15974,129434,Male,Loyal Customer,74,Business travel,Business,236,1,2,2,2,2,4,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +15975,63806,Female,Loyal Customer,36,Business travel,Eco,1224,4,1,1,1,4,4,4,4,3,1,2,5,5,4,0,0.0,satisfied +15976,38666,Female,Loyal Customer,16,Personal Travel,Eco,2611,4,3,4,1,4,4,5,4,1,4,4,3,3,4,6,9.0,satisfied +15977,116993,Female,Loyal Customer,52,Business travel,Business,2196,5,5,5,5,4,4,4,4,4,5,4,5,4,3,10,2.0,satisfied +15978,104930,Male,Loyal Customer,62,Personal Travel,Eco,210,2,2,2,2,5,2,4,5,1,2,1,1,2,5,50,51.0,neutral or dissatisfied +15979,20373,Female,Loyal Customer,28,Personal Travel,Eco,265,3,1,3,3,2,3,2,2,3,4,3,4,3,2,49,37.0,neutral or dissatisfied +15980,38823,Female,Loyal Customer,44,Personal Travel,Eco,354,3,4,3,4,2,4,3,4,4,3,2,4,4,4,53,49.0,neutral or dissatisfied +15981,106721,Male,disloyal Customer,47,Business travel,Business,829,3,3,3,2,4,3,4,4,5,3,5,5,5,4,0,0.0,neutral or dissatisfied +15982,68340,Female,Loyal Customer,57,Business travel,Business,1598,4,4,4,4,3,5,4,4,4,4,4,3,4,3,3,0.0,satisfied +15983,31529,Female,Loyal Customer,61,Personal Travel,Eco,862,3,4,3,2,4,4,5,3,3,3,3,4,3,5,10,33.0,neutral or dissatisfied +15984,56564,Female,Loyal Customer,40,Business travel,Business,1693,1,1,1,1,4,5,5,4,4,4,4,3,4,3,20,30.0,satisfied +15985,111029,Male,Loyal Customer,46,Business travel,Eco,240,2,4,4,4,2,2,2,2,3,5,3,4,4,2,48,47.0,neutral or dissatisfied +15986,34128,Male,disloyal Customer,46,Business travel,Business,1189,5,5,5,2,3,5,3,3,2,5,4,4,2,3,0,0.0,satisfied +15987,45447,Female,Loyal Customer,47,Business travel,Business,2618,4,4,5,4,3,5,5,4,4,4,4,5,4,3,7,5.0,satisfied +15988,101561,Female,disloyal Customer,37,Business travel,Eco Plus,345,2,2,2,3,3,2,3,3,3,3,4,3,4,3,44,36.0,neutral or dissatisfied +15989,94790,Male,Loyal Customer,43,Business travel,Business,319,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +15990,40860,Female,Loyal Customer,30,Personal Travel,Eco,541,3,2,3,4,3,3,3,3,4,2,3,4,4,3,0,0.0,neutral or dissatisfied +15991,122387,Male,Loyal Customer,66,Personal Travel,Eco,529,3,4,3,5,1,3,1,1,3,5,5,3,5,1,17,4.0,neutral or dissatisfied +15992,93623,Male,Loyal Customer,37,Business travel,Eco,577,1,3,3,3,1,1,1,1,4,2,1,2,1,1,27,28.0,neutral or dissatisfied +15993,83077,Female,Loyal Customer,43,Business travel,Business,1084,4,5,5,5,5,3,3,4,4,4,4,2,4,2,8,0.0,neutral or dissatisfied +15994,66174,Male,disloyal Customer,45,Business travel,Business,460,2,2,2,5,5,2,3,5,5,5,4,5,4,5,0,0.0,neutral or dissatisfied +15995,67836,Female,Loyal Customer,57,Business travel,Eco,771,5,4,2,4,4,3,1,5,5,5,5,1,5,3,0,0.0,satisfied +15996,54587,Male,Loyal Customer,54,Business travel,Business,3180,5,5,5,5,3,4,5,5,5,5,5,4,5,5,41,28.0,satisfied +15997,88963,Female,Loyal Customer,57,Business travel,Business,1199,4,4,4,4,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +15998,41788,Male,Loyal Customer,32,Business travel,Business,196,2,2,2,2,4,4,5,4,4,3,5,4,4,4,18,30.0,satisfied +15999,125645,Male,Loyal Customer,41,Business travel,Business,1555,5,5,5,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +16000,73515,Male,Loyal Customer,59,Business travel,Business,3775,3,3,3,3,2,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +16001,19162,Male,Loyal Customer,52,Business travel,Eco,304,4,2,2,2,4,4,4,4,1,5,3,3,4,4,0,2.0,neutral or dissatisfied +16002,98988,Male,Loyal Customer,56,Personal Travel,Eco,479,4,5,4,4,3,4,3,3,4,4,4,3,2,3,26,18.0,neutral or dissatisfied +16003,47525,Male,Loyal Customer,41,Personal Travel,Eco,584,3,4,3,5,2,3,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +16004,82871,Female,Loyal Customer,43,Business travel,Business,3076,5,5,5,5,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +16005,60426,Male,disloyal Customer,29,Business travel,Business,775,3,3,3,3,5,3,3,5,3,1,4,4,3,5,0,0.0,neutral or dissatisfied +16006,84610,Male,Loyal Customer,45,Business travel,Business,2629,5,5,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +16007,113025,Female,Loyal Customer,52,Business travel,Business,3696,1,2,1,1,3,4,4,4,4,4,4,3,4,5,71,70.0,satisfied +16008,82606,Female,Loyal Customer,41,Business travel,Eco,528,3,4,4,4,3,3,3,3,1,2,4,4,3,3,0,0.0,neutral or dissatisfied +16009,63637,Female,Loyal Customer,36,Business travel,Eco,602,3,3,3,3,3,2,3,3,2,3,4,4,3,3,10,14.0,neutral or dissatisfied +16010,127115,Male,Loyal Customer,38,Personal Travel,Eco,304,3,4,3,2,3,3,3,3,4,2,4,4,4,3,8,8.0,neutral or dissatisfied +16011,60760,Male,Loyal Customer,25,Business travel,Business,3146,1,1,3,1,4,4,4,4,5,2,4,4,5,4,5,0.0,satisfied +16012,103953,Female,Loyal Customer,58,Business travel,Eco,770,4,2,2,2,5,3,1,4,4,4,4,4,4,3,16,10.0,satisfied +16013,65016,Male,Loyal Customer,53,Business travel,Eco,247,4,1,1,1,4,4,4,4,2,4,3,5,4,4,0,0.0,satisfied +16014,103614,Female,Loyal Customer,38,Business travel,Business,3300,4,4,4,4,2,5,5,5,5,5,5,4,5,4,27,27.0,satisfied +16015,112516,Female,Loyal Customer,52,Personal Travel,Eco,957,1,5,2,3,4,5,4,2,2,2,2,5,2,3,43,42.0,neutral or dissatisfied +16016,128665,Female,Loyal Customer,19,Business travel,Business,2288,2,2,2,2,5,4,5,5,3,4,4,3,5,5,5,0.0,satisfied +16017,103797,Female,Loyal Customer,43,Business travel,Business,979,3,3,3,3,3,5,4,5,5,5,5,4,5,5,34,29.0,satisfied +16018,46046,Male,disloyal Customer,17,Business travel,Eco,964,3,4,4,1,3,4,5,3,3,3,4,4,3,3,4,0.0,neutral or dissatisfied +16019,38653,Female,Loyal Customer,40,Business travel,Business,2704,5,5,5,5,3,5,2,4,4,4,4,5,4,3,0,0.0,satisfied +16020,50005,Male,Loyal Customer,30,Business travel,Eco,199,1,4,4,4,1,1,1,1,4,4,3,2,2,1,59,50.0,neutral or dissatisfied +16021,48145,Male,Loyal Customer,47,Business travel,Business,2255,2,4,4,4,5,2,2,2,2,2,2,1,2,2,6,5.0,neutral or dissatisfied +16022,110733,Female,Loyal Customer,47,Business travel,Business,997,3,3,3,3,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +16023,33659,Female,Loyal Customer,44,Business travel,Eco Plus,399,2,5,5,5,4,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +16024,58983,Male,Loyal Customer,48,Business travel,Business,1652,3,3,3,3,3,5,4,5,5,5,5,5,5,4,17,37.0,satisfied +16025,122865,Female,Loyal Customer,52,Business travel,Business,3708,0,0,0,4,4,5,5,1,1,1,1,3,1,4,4,0.0,satisfied +16026,27350,Female,disloyal Customer,28,Business travel,Eco,954,3,2,2,2,2,2,2,2,3,4,3,5,5,2,0,3.0,neutral or dissatisfied +16027,26361,Male,disloyal Customer,30,Business travel,Eco,894,4,4,4,5,3,4,3,3,1,3,1,2,2,3,0,0.0,neutral or dissatisfied +16028,108784,Male,disloyal Customer,30,Business travel,Eco,406,3,3,3,3,2,3,2,2,1,3,3,1,3,2,20,19.0,neutral or dissatisfied +16029,105171,Male,Loyal Customer,47,Personal Travel,Eco,220,1,3,1,1,3,1,3,3,5,3,3,5,1,3,15,12.0,neutral or dissatisfied +16030,88823,Female,Loyal Customer,16,Business travel,Eco Plus,250,3,2,2,2,3,3,2,3,2,3,3,2,3,3,0,0.0,neutral or dissatisfied +16031,61018,Female,disloyal Customer,17,Business travel,Eco,3365,3,3,3,4,3,4,4,2,4,4,4,4,3,4,0,0.0,neutral or dissatisfied +16032,103590,Female,Loyal Customer,41,Business travel,Business,2920,1,1,1,1,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +16033,108764,Female,Loyal Customer,59,Business travel,Business,545,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +16034,115781,Male,disloyal Customer,39,Business travel,Eco,325,3,4,3,3,3,3,3,3,4,2,3,3,4,3,0,7.0,neutral or dissatisfied +16035,85767,Male,disloyal Customer,26,Business travel,Business,666,1,0,0,4,1,0,1,1,4,5,4,4,4,1,45,39.0,neutral or dissatisfied +16036,5570,Male,Loyal Customer,54,Personal Travel,Eco,588,3,2,3,3,4,3,4,4,2,3,4,1,3,4,45,101.0,neutral or dissatisfied +16037,41579,Male,Loyal Customer,47,Personal Travel,Eco,1242,3,5,3,5,3,3,3,3,5,2,5,3,5,3,0,14.0,neutral or dissatisfied +16038,115068,Male,disloyal Customer,23,Business travel,Eco,325,1,1,1,4,1,1,1,1,2,2,4,4,4,1,0,0.0,neutral or dissatisfied +16039,9836,Female,Loyal Customer,30,Business travel,Business,1511,3,3,3,3,4,5,4,4,5,5,5,3,5,4,0,35.0,satisfied +16040,56205,Female,disloyal Customer,20,Business travel,Eco Plus,1400,2,3,2,3,2,2,2,2,2,1,4,1,4,2,6,0.0,neutral or dissatisfied +16041,49259,Male,disloyal Customer,62,Business travel,Eco,109,3,4,3,3,5,3,4,5,4,3,4,2,4,5,0,4.0,neutral or dissatisfied +16042,98078,Female,Loyal Customer,47,Personal Travel,Eco,1449,3,4,3,2,1,2,1,3,3,3,1,1,3,4,19,12.0,neutral or dissatisfied +16043,33305,Female,Loyal Customer,66,Personal Travel,Eco Plus,102,3,2,0,4,2,3,4,2,2,0,2,3,2,3,0,5.0,neutral or dissatisfied +16044,110458,Female,Loyal Customer,18,Personal Travel,Eco,919,2,3,2,2,3,2,3,3,4,2,5,3,2,3,0,0.0,neutral or dissatisfied +16045,105500,Female,Loyal Customer,42,Business travel,Business,2415,3,4,3,3,5,5,5,5,5,5,5,3,5,3,8,0.0,satisfied +16046,12743,Male,Loyal Customer,7,Personal Travel,Eco,803,3,2,3,3,4,3,4,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +16047,76742,Male,Loyal Customer,41,Business travel,Business,2203,1,1,1,1,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +16048,106640,Male,Loyal Customer,32,Business travel,Eco Plus,306,1,2,2,2,1,1,1,1,4,4,3,3,4,1,14,26.0,neutral or dissatisfied +16049,73683,Female,disloyal Customer,26,Business travel,Eco,192,3,2,4,3,2,4,2,2,1,5,3,2,3,2,2,2.0,neutral or dissatisfied +16050,96930,Male,Loyal Customer,31,Personal Travel,Eco Plus,1105,2,2,2,4,4,2,4,4,3,2,3,1,3,4,0,6.0,neutral or dissatisfied +16051,19955,Male,Loyal Customer,49,Business travel,Eco Plus,240,4,4,4,4,5,4,5,5,5,1,1,4,3,5,0,0.0,satisfied +16052,54227,Female,Loyal Customer,36,Business travel,Eco,1222,4,1,5,1,4,4,4,4,3,5,3,1,3,4,0,0.0,satisfied +16053,13746,Male,disloyal Customer,44,Business travel,Eco,441,2,0,2,4,2,1,1,5,1,3,5,1,4,1,247,237.0,neutral or dissatisfied +16054,77545,Female,Loyal Customer,34,Business travel,Business,2131,1,5,5,5,5,4,3,1,1,1,1,2,1,1,14,20.0,neutral or dissatisfied +16055,128660,Female,Loyal Customer,45,Business travel,Business,2419,4,4,2,4,5,5,5,3,4,5,5,5,5,5,0,0.0,satisfied +16056,20205,Female,Loyal Customer,44,Business travel,Business,235,2,2,2,2,1,4,4,2,2,2,2,1,2,3,25,36.0,neutral or dissatisfied +16057,6427,Female,Loyal Customer,63,Personal Travel,Eco,315,2,5,2,4,3,1,2,4,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +16058,30422,Male,disloyal Customer,22,Business travel,Eco,1014,4,4,4,2,2,4,2,2,2,3,2,4,4,2,0,6.0,satisfied +16059,119713,Male,disloyal Customer,24,Business travel,Eco,1325,1,1,1,1,3,1,3,3,5,5,4,5,5,3,10,0.0,neutral or dissatisfied +16060,55736,Female,disloyal Customer,14,Business travel,Eco,1353,5,5,5,3,3,5,3,3,4,3,3,3,4,3,2,0.0,satisfied +16061,10523,Male,disloyal Customer,26,Business travel,Business,316,3,0,3,2,4,3,4,4,5,5,4,3,4,4,35,36.0,neutral or dissatisfied +16062,33560,Male,Loyal Customer,56,Business travel,Business,474,3,3,3,3,1,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +16063,9201,Female,disloyal Customer,18,Business travel,Eco,227,3,3,3,1,4,3,4,4,1,2,4,3,4,4,0,0.0,neutral or dissatisfied +16064,22407,Male,Loyal Customer,38,Business travel,Business,143,3,3,4,3,1,1,2,5,5,5,4,4,5,1,0,24.0,satisfied +16065,1976,Male,Loyal Customer,50,Personal Travel,Eco,351,2,5,2,1,1,2,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +16066,69759,Male,Loyal Customer,63,Personal Travel,Eco,1085,2,5,1,4,3,1,4,3,4,4,4,5,5,3,4,6.0,neutral or dissatisfied +16067,119514,Male,disloyal Customer,27,Business travel,Eco,899,1,1,1,4,5,1,5,5,2,5,4,2,4,5,0,0.0,neutral or dissatisfied +16068,29523,Female,Loyal Customer,68,Business travel,Eco,1009,1,3,3,3,4,4,3,1,1,1,1,1,1,3,0,3.0,neutral or dissatisfied +16069,112572,Female,Loyal Customer,48,Business travel,Business,2018,5,5,5,5,5,5,4,4,4,4,4,5,4,3,7,3.0,satisfied +16070,109246,Male,Loyal Customer,45,Personal Travel,Eco,793,3,4,3,1,1,3,1,1,4,3,5,3,4,1,36,30.0,neutral or dissatisfied +16071,41319,Male,Loyal Customer,35,Personal Travel,Eco,802,3,2,3,3,1,3,1,1,3,5,4,3,3,1,0,0.0,neutral or dissatisfied +16072,108440,Female,Loyal Customer,44,Business travel,Eco,1444,1,4,4,4,2,2,2,1,1,1,1,3,1,4,16,0.0,neutral or dissatisfied +16073,38656,Male,disloyal Customer,29,Business travel,Business,2704,3,3,3,2,5,3,5,5,4,4,4,1,1,5,0,0.0,neutral or dissatisfied +16074,71623,Female,disloyal Customer,80,Business travel,Business,612,1,1,1,1,2,5,2,1,1,1,1,5,1,1,0,7.0,neutral or dissatisfied +16075,73986,Female,Loyal Customer,28,Business travel,Eco Plus,2342,3,2,2,2,3,3,3,3,4,5,3,2,3,3,77,54.0,neutral or dissatisfied +16076,113003,Female,Loyal Customer,39,Personal Travel,Eco,1751,5,4,5,3,4,5,4,4,1,4,3,4,4,4,15,14.0,satisfied +16077,20227,Male,Loyal Customer,54,Business travel,Eco,235,4,4,3,4,4,4,4,4,5,1,4,1,5,4,0,0.0,satisfied +16078,6385,Female,Loyal Customer,31,Business travel,Business,3160,3,1,1,1,3,3,3,3,2,2,4,1,3,3,85,78.0,neutral or dissatisfied +16079,103145,Male,Loyal Customer,42,Personal Travel,Eco Plus,786,3,4,3,2,4,3,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +16080,112424,Male,disloyal Customer,18,Business travel,Eco,850,4,4,4,4,4,4,4,4,4,2,5,4,5,4,50,39.0,satisfied +16081,26000,Male,Loyal Customer,23,Personal Travel,Eco Plus,577,3,5,3,3,4,3,4,4,3,4,5,3,4,4,7,0.0,neutral or dissatisfied +16082,14342,Male,Loyal Customer,11,Personal Travel,Eco,429,4,1,4,3,5,4,5,5,2,3,3,1,3,5,0,0.0,neutral or dissatisfied +16083,16843,Male,Loyal Customer,33,Business travel,Eco Plus,645,4,5,5,5,4,4,4,4,2,1,4,4,2,4,44,37.0,satisfied +16084,30537,Male,Loyal Customer,75,Business travel,Business,2939,3,3,3,3,5,4,4,1,5,3,5,4,4,4,157,183.0,satisfied +16085,62021,Female,disloyal Customer,22,Business travel,Business,2586,4,2,4,5,3,4,3,3,4,4,3,5,5,3,0,0.0,satisfied +16086,128284,Male,disloyal Customer,41,Business travel,Business,651,4,4,4,4,3,4,3,3,4,2,5,5,5,3,8,2.0,satisfied +16087,70700,Female,disloyal Customer,38,Business travel,Eco,437,5,0,5,3,5,5,5,5,1,1,4,1,5,5,0,0.0,satisfied +16088,92658,Male,Loyal Customer,33,Personal Travel,Eco,453,3,1,3,2,5,3,5,5,4,5,3,3,3,5,0,0.0,neutral or dissatisfied +16089,76357,Female,Loyal Customer,32,Personal Travel,Eco,1851,3,1,3,2,4,3,4,4,4,5,3,4,2,4,1,0.0,neutral or dissatisfied +16090,81995,Male,Loyal Customer,59,Business travel,Business,1535,1,1,1,1,4,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +16091,116502,Male,Loyal Customer,62,Personal Travel,Eco,308,1,2,1,4,2,1,2,2,1,1,4,3,4,2,9,5.0,neutral or dissatisfied +16092,117110,Female,Loyal Customer,17,Business travel,Business,621,3,3,3,3,2,2,2,2,4,2,3,5,2,2,2,0.0,satisfied +16093,121764,Male,Loyal Customer,30,Personal Travel,Business,366,3,2,3,3,1,3,1,1,1,5,4,3,4,1,14,21.0,neutral or dissatisfied +16094,46247,Male,Loyal Customer,59,Business travel,Eco,352,5,3,3,3,5,5,5,5,2,3,4,1,4,5,92,96.0,satisfied +16095,66526,Female,Loyal Customer,58,Business travel,Eco Plus,447,4,5,3,5,1,3,5,4,4,4,4,3,4,1,0,0.0,satisfied +16096,125208,Female,disloyal Customer,29,Business travel,Eco,651,2,0,1,3,4,1,1,4,3,5,2,2,5,4,0,0.0,neutral or dissatisfied +16097,40597,Female,Loyal Customer,41,Business travel,Eco,391,1,2,2,2,1,1,1,1,1,4,3,4,4,1,20,23.0,neutral or dissatisfied +16098,55570,Female,Loyal Customer,43,Business travel,Business,3020,5,5,1,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +16099,95823,Female,Loyal Customer,48,Business travel,Business,1428,2,2,2,2,5,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +16100,98966,Male,disloyal Customer,22,Business travel,Eco,169,3,2,3,2,4,3,4,4,4,2,1,4,2,4,0,0.0,neutral or dissatisfied +16101,41192,Male,Loyal Customer,52,Business travel,Eco,1091,3,2,2,2,4,3,4,4,1,5,3,3,1,4,9,12.0,satisfied +16102,897,Female,disloyal Customer,16,Business travel,Eco,158,5,0,5,1,5,5,5,5,3,5,4,5,4,5,0,0.0,satisfied +16103,99428,Female,Loyal Customer,70,Personal Travel,Eco,406,2,2,2,4,2,4,4,4,4,2,4,1,4,4,0,9.0,neutral or dissatisfied +16104,103345,Female,Loyal Customer,43,Personal Travel,Eco,1139,3,5,3,3,3,4,4,2,2,3,2,5,2,4,33,56.0,neutral or dissatisfied +16105,113375,Female,Loyal Customer,57,Business travel,Business,386,5,5,5,5,2,4,4,2,2,2,2,5,2,4,0,0.0,satisfied +16106,62408,Female,Loyal Customer,51,Business travel,Business,2704,4,4,2,4,5,3,4,4,4,4,4,4,4,5,40,12.0,satisfied +16107,116143,Male,Loyal Customer,20,Personal Travel,Eco,342,2,4,2,3,4,2,3,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +16108,36886,Female,Loyal Customer,31,Personal Travel,Eco,1182,3,5,3,1,1,3,1,1,3,3,4,4,4,1,6,0.0,neutral or dissatisfied +16109,47088,Male,Loyal Customer,29,Personal Travel,Eco,639,1,5,2,4,5,2,5,5,3,2,4,5,5,5,0,0.0,neutral or dissatisfied +16110,77840,Female,Loyal Customer,53,Business travel,Business,2379,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,9.0,satisfied +16111,100320,Male,Loyal Customer,31,Business travel,Business,3896,2,2,2,2,4,4,4,3,5,5,5,4,4,4,138,120.0,satisfied +16112,87605,Female,Loyal Customer,50,Business travel,Business,2331,3,3,3,3,3,4,5,3,3,3,3,5,3,5,0,1.0,satisfied +16113,27511,Female,Loyal Customer,52,Business travel,Eco,650,3,4,4,4,1,4,3,2,2,3,2,1,2,2,5,25.0,neutral or dissatisfied +16114,119128,Male,Loyal Customer,59,Personal Travel,Eco Plus,1107,4,3,4,4,2,4,3,2,4,4,3,2,4,2,35,27.0,neutral or dissatisfied +16115,14457,Male,Loyal Customer,57,Business travel,Business,274,0,0,0,5,5,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +16116,68120,Male,Loyal Customer,49,Personal Travel,Eco,813,4,0,4,3,4,4,1,4,2,2,4,4,4,4,47,45.0,neutral or dissatisfied +16117,7372,Male,Loyal Customer,65,Personal Travel,Eco,783,5,1,5,4,5,5,1,5,1,3,4,4,4,5,0,0.0,satisfied +16118,97543,Male,disloyal Customer,21,Business travel,Eco,675,3,3,3,3,1,3,1,1,4,1,3,4,3,1,3,0.0,neutral or dissatisfied +16119,118471,Female,Loyal Customer,39,Business travel,Business,3689,5,5,5,5,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +16120,62919,Male,Loyal Customer,35,Business travel,Business,862,2,2,2,2,5,5,4,3,3,3,3,4,3,5,0,3.0,satisfied +16121,20937,Female,Loyal Customer,46,Business travel,Eco,689,4,3,3,3,4,4,3,4,4,4,4,2,4,1,0,0.0,neutral or dissatisfied +16122,58079,Female,Loyal Customer,59,Business travel,Business,612,4,4,4,4,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +16123,103120,Female,Loyal Customer,62,Personal Travel,Eco,546,2,4,2,1,2,2,1,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +16124,54189,Male,Loyal Customer,14,Personal Travel,Eco,1400,3,5,3,1,1,3,1,1,5,4,3,4,4,1,0,0.0,neutral or dissatisfied +16125,95414,Female,Loyal Customer,40,Personal Travel,Eco,239,3,1,3,2,4,3,4,4,1,4,3,1,3,4,12,12.0,neutral or dissatisfied +16126,123610,Male,Loyal Customer,59,Business travel,Business,1773,3,3,2,3,5,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +16127,56544,Male,disloyal Customer,36,Business travel,Business,1023,3,3,3,5,4,3,4,4,5,4,5,4,5,4,4,12.0,neutral or dissatisfied +16128,18638,Male,Loyal Customer,58,Personal Travel,Eco,190,2,5,2,3,2,2,2,2,3,5,4,5,4,2,0,0.0,neutral or dissatisfied +16129,56265,Female,disloyal Customer,27,Business travel,Eco,404,2,0,1,4,3,1,3,3,2,1,1,3,3,3,0,0.0,neutral or dissatisfied +16130,23095,Female,disloyal Customer,36,Business travel,Business,250,3,3,3,3,3,3,3,3,4,4,5,3,5,3,29,17.0,neutral or dissatisfied +16131,88246,Female,Loyal Customer,58,Business travel,Business,2110,3,3,3,3,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +16132,2688,Male,Loyal Customer,48,Business travel,Business,2009,2,2,2,2,4,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +16133,58328,Female,Loyal Customer,25,Personal Travel,Eco,1739,2,5,2,2,4,2,4,4,5,5,5,3,5,4,2,47.0,neutral or dissatisfied +16134,128802,Female,disloyal Customer,20,Business travel,Business,835,5,0,5,1,5,2,2,5,3,4,4,2,4,2,0,0.0,satisfied +16135,4191,Female,Loyal Customer,46,Business travel,Business,2477,3,3,3,3,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +16136,52157,Female,Loyal Customer,59,Business travel,Eco,651,4,1,1,1,3,5,2,4,4,4,4,5,4,1,0,0.0,satisfied +16137,35450,Male,Loyal Customer,38,Personal Travel,Eco,944,3,2,3,4,3,3,3,3,4,2,4,3,3,3,84,65.0,neutral or dissatisfied +16138,78955,Female,disloyal Customer,24,Business travel,Business,356,2,3,2,2,5,2,2,5,1,3,2,2,2,5,0,0.0,neutral or dissatisfied +16139,20913,Male,disloyal Customer,24,Business travel,Eco,689,3,3,3,2,4,3,4,4,1,4,5,1,5,4,0,19.0,neutral or dissatisfied +16140,61092,Male,Loyal Customer,61,Personal Travel,Eco,1506,2,5,2,2,4,2,4,4,3,3,4,5,4,4,9,7.0,neutral or dissatisfied +16141,24019,Female,Loyal Customer,47,Business travel,Eco,427,5,3,3,3,3,5,1,5,5,5,5,5,5,2,2,0.0,satisfied +16142,42039,Female,Loyal Customer,19,Business travel,Business,106,1,1,1,1,5,5,4,5,4,2,5,4,2,5,0,3.0,satisfied +16143,108952,Female,disloyal Customer,22,Business travel,Eco,667,0,3,0,2,4,3,4,4,3,4,4,3,5,4,2,0.0,satisfied +16144,72514,Male,Loyal Customer,48,Business travel,Eco,929,3,5,5,5,3,3,3,3,2,2,3,2,3,3,0,3.0,neutral or dissatisfied +16145,45465,Male,Loyal Customer,34,Business travel,Business,3290,5,5,5,5,2,3,3,4,4,5,4,4,4,4,29,19.0,satisfied +16146,52323,Male,Loyal Customer,31,Business travel,Business,3160,1,1,1,1,2,2,2,2,1,3,2,4,1,2,0,5.0,satisfied +16147,91894,Female,Loyal Customer,52,Business travel,Business,2586,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +16148,57581,Female,Loyal Customer,65,Business travel,Business,1597,4,1,1,1,4,3,2,4,4,4,4,4,4,2,7,27.0,neutral or dissatisfied +16149,10752,Female,Loyal Customer,52,Business travel,Business,3685,3,2,2,2,4,2,2,3,3,2,3,2,3,2,0,2.0,neutral or dissatisfied +16150,78797,Female,Loyal Customer,74,Business travel,Eco,154,3,5,4,5,4,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +16151,20370,Male,Loyal Customer,16,Personal Travel,Eco,287,1,5,1,4,1,1,1,1,4,3,5,4,4,1,23,8.0,neutral or dissatisfied +16152,9464,Male,Loyal Customer,17,Personal Travel,Eco,310,3,5,3,1,4,3,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +16153,35433,Male,Loyal Customer,35,Personal Travel,Eco,1118,2,5,2,3,3,2,3,3,5,3,4,4,5,3,0,37.0,neutral or dissatisfied +16154,4625,Male,disloyal Customer,27,Business travel,Business,364,2,2,2,3,2,2,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +16155,38205,Male,Loyal Customer,22,Business travel,Eco Plus,1249,2,5,3,5,2,2,4,2,3,1,3,3,4,2,0,0.0,neutral or dissatisfied +16156,100,Female,disloyal Customer,23,Business travel,Eco,562,0,4,0,4,5,0,5,5,4,2,5,4,5,5,27,36.0,satisfied +16157,94578,Female,disloyal Customer,39,Business travel,Business,239,1,1,1,3,1,1,1,1,3,5,4,1,4,1,50,47.0,neutral or dissatisfied +16158,9641,Female,disloyal Customer,32,Business travel,Business,284,2,2,2,4,1,2,1,1,5,5,4,3,5,1,0,10.0,neutral or dissatisfied +16159,26017,Male,Loyal Customer,37,Business travel,Eco,425,4,2,3,3,4,4,4,4,1,4,5,5,4,4,0,1.0,satisfied +16160,80291,Female,Loyal Customer,59,Business travel,Business,1738,3,3,3,3,4,5,5,4,4,4,4,4,4,3,0,21.0,satisfied +16161,9837,Female,Loyal Customer,55,Business travel,Business,531,1,1,1,1,4,5,5,4,4,4,4,3,4,5,4,0.0,satisfied +16162,68550,Female,disloyal Customer,39,Business travel,Business,1013,5,5,5,3,4,5,4,4,4,4,4,5,4,4,6,1.0,satisfied +16163,86168,Female,Loyal Customer,57,Business travel,Business,1938,1,1,1,1,2,5,4,3,3,3,3,4,3,4,0,0.0,satisfied +16164,64272,Male,Loyal Customer,57,Business travel,Business,1192,2,2,2,2,5,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +16165,1874,Male,Loyal Customer,44,Business travel,Eco,931,3,5,4,5,3,3,3,3,4,4,3,4,4,3,0,4.0,neutral or dissatisfied +16166,124441,Male,Loyal Customer,19,Personal Travel,Eco Plus,1262,3,4,4,3,1,4,1,1,4,2,3,3,5,1,0,0.0,neutral or dissatisfied +16167,43180,Female,disloyal Customer,40,Business travel,Business,282,3,3,3,4,4,3,4,4,4,4,3,2,3,4,27,13.0,neutral or dissatisfied +16168,84198,Female,Loyal Customer,48,Business travel,Business,2391,4,4,4,4,3,4,5,2,2,2,2,4,2,4,0,2.0,satisfied +16169,69346,Female,Loyal Customer,28,Business travel,Business,2264,1,1,5,1,3,3,3,3,5,4,5,5,4,3,1,1.0,satisfied +16170,76918,Male,Loyal Customer,33,Personal Travel,Eco Plus,630,1,4,1,2,4,1,4,4,5,5,5,3,4,4,24,11.0,neutral or dissatisfied +16171,12961,Male,Loyal Customer,32,Business travel,Eco Plus,456,3,4,4,4,3,3,3,3,2,4,4,1,3,3,0,9.0,neutral or dissatisfied +16172,98404,Male,Loyal Customer,50,Business travel,Business,675,3,1,1,1,3,3,3,4,5,3,3,3,4,3,311,299.0,neutral or dissatisfied +16173,60362,Male,Loyal Customer,52,Business travel,Business,1452,4,1,4,4,5,5,4,5,5,5,5,5,5,4,3,0.0,satisfied +16174,126946,Female,Loyal Customer,48,Business travel,Business,621,1,1,4,1,5,5,5,1,1,2,1,5,1,5,0,0.0,satisfied +16175,109827,Female,Loyal Customer,29,Business travel,Business,3356,3,3,5,3,4,4,4,4,3,5,5,5,5,4,17,5.0,satisfied +16176,76125,Male,Loyal Customer,36,Business travel,Business,546,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16177,119740,Male,Loyal Customer,28,Personal Travel,Eco,1303,2,5,2,4,1,2,1,1,4,1,4,5,3,1,2,0.0,neutral or dissatisfied +16178,98378,Male,Loyal Customer,64,Business travel,Eco Plus,1189,4,1,1,1,4,4,4,4,3,3,3,2,4,4,0,12.0,neutral or dissatisfied +16179,112484,Female,Loyal Customer,44,Personal Travel,Eco,967,3,5,3,3,4,4,5,2,2,3,2,4,2,3,2,0.0,neutral or dissatisfied +16180,8098,Female,Loyal Customer,40,Business travel,Business,530,3,3,3,3,4,5,5,5,5,5,5,5,5,4,32,24.0,satisfied +16181,21716,Male,disloyal Customer,36,Business travel,Eco,952,2,2,2,2,3,2,3,3,2,5,1,4,2,3,0,0.0,neutral or dissatisfied +16182,18650,Female,Loyal Customer,16,Personal Travel,Eco,201,3,4,3,3,2,3,2,2,3,3,4,2,3,2,2,0.0,neutral or dissatisfied +16183,94802,Male,Loyal Customer,30,Business travel,Business,189,4,5,5,5,2,2,4,2,1,2,3,4,4,2,3,0.0,neutral or dissatisfied +16184,110541,Male,disloyal Customer,20,Business travel,Business,551,5,4,5,3,2,5,2,2,4,2,5,4,4,2,4,0.0,satisfied +16185,32082,Male,Loyal Customer,31,Business travel,Business,102,0,5,0,1,5,3,3,5,3,4,2,3,1,5,0,0.0,satisfied +16186,88726,Female,Loyal Customer,32,Personal Travel,Eco,406,2,5,2,2,5,2,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +16187,26084,Female,Loyal Customer,69,Business travel,Eco,591,2,4,4,4,1,3,3,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +16188,105438,Female,Loyal Customer,47,Business travel,Business,998,2,2,2,2,4,4,3,2,2,2,2,1,2,2,5,13.0,neutral or dissatisfied +16189,111098,Female,disloyal Customer,39,Business travel,Business,240,5,5,5,3,2,5,2,2,3,4,5,3,4,2,16,9.0,satisfied +16190,58315,Female,Loyal Customer,41,Business travel,Business,1739,3,3,3,3,4,3,4,4,4,4,4,3,4,3,40,49.0,satisfied +16191,100816,Female,Loyal Customer,58,Business travel,Business,711,5,5,5,5,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +16192,26625,Female,disloyal Customer,23,Business travel,Eco,581,2,0,2,4,5,2,2,5,3,2,2,1,4,5,2,0.0,neutral or dissatisfied +16193,4805,Male,Loyal Customer,12,Personal Travel,Eco,438,4,5,5,2,5,5,5,5,3,5,4,3,4,5,3,3.0,satisfied +16194,90610,Male,Loyal Customer,48,Business travel,Business,515,5,5,5,5,4,5,5,5,5,5,5,3,5,4,1,0.0,satisfied +16195,56219,Male,Loyal Customer,63,Business travel,Business,1585,1,1,5,1,2,4,5,4,4,5,4,5,4,4,11,11.0,satisfied +16196,46873,Male,disloyal Customer,22,Business travel,Eco,819,2,2,2,1,3,2,3,3,1,1,2,1,2,3,0,0.0,neutral or dissatisfied +16197,85429,Female,Loyal Customer,53,Business travel,Business,2020,3,3,5,3,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +16198,53884,Male,Loyal Customer,12,Personal Travel,Eco,191,4,5,4,2,1,4,1,1,4,3,4,3,4,1,2,0.0,satisfied +16199,13491,Female,Loyal Customer,38,Business travel,Business,152,4,1,4,4,3,3,2,4,4,4,4,4,4,4,0,0.0,satisfied +16200,66766,Female,Loyal Customer,59,Business travel,Business,3646,5,5,5,5,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +16201,15785,Female,Loyal Customer,65,Personal Travel,Eco,254,3,4,0,5,4,4,4,4,4,0,4,5,4,5,0,0.0,neutral or dissatisfied +16202,19515,Male,Loyal Customer,32,Personal Travel,Eco,566,1,4,1,1,1,1,1,1,5,2,4,4,4,1,0,0.0,neutral or dissatisfied +16203,28387,Male,Loyal Customer,12,Personal Travel,Eco,763,2,4,2,1,3,2,4,3,4,2,3,4,2,3,1,4.0,neutral or dissatisfied +16204,12800,Male,Loyal Customer,57,Business travel,Eco,641,5,2,5,5,5,5,5,5,1,5,4,3,4,5,2,0.0,satisfied +16205,51541,Male,Loyal Customer,54,Business travel,Eco,261,5,1,2,1,5,5,5,5,3,2,4,4,5,5,7,3.0,satisfied +16206,48477,Male,Loyal Customer,47,Business travel,Business,833,3,5,3,3,1,2,5,4,4,4,4,4,4,3,2,0.0,satisfied +16207,52006,Male,disloyal Customer,20,Business travel,Eco,328,1,0,1,3,2,1,2,2,2,4,5,5,5,2,0,0.0,neutral or dissatisfied +16208,48356,Male,disloyal Customer,37,Business travel,Eco,522,2,0,2,4,1,2,1,1,1,3,4,4,3,1,0,7.0,neutral or dissatisfied +16209,36270,Male,Loyal Customer,27,Personal Travel,Eco,728,3,5,3,3,1,3,1,1,1,1,2,5,5,1,0,0.0,neutral or dissatisfied +16210,96436,Female,Loyal Customer,60,Business travel,Business,436,4,4,3,4,3,4,4,5,5,5,5,3,5,5,8,9.0,satisfied +16211,8822,Male,Loyal Customer,33,Personal Travel,Eco,522,4,4,4,3,3,4,3,3,3,4,4,3,4,3,22,83.0,neutral or dissatisfied +16212,128655,Male,disloyal Customer,38,Business travel,Business,2288,4,4,4,3,4,4,4,4,3,2,4,5,5,4,14,12.0,neutral or dissatisfied +16213,23725,Female,disloyal Customer,27,Business travel,Eco Plus,251,2,2,2,3,3,2,1,3,2,4,4,3,3,3,72,73.0,neutral or dissatisfied +16214,30160,Male,Loyal Customer,18,Personal Travel,Eco,399,2,4,2,2,3,2,3,3,5,2,4,3,5,3,10,21.0,neutral or dissatisfied +16215,9128,Male,Loyal Customer,35,Personal Travel,Eco,707,3,5,3,1,3,3,1,3,4,2,5,5,5,3,98,99.0,neutral or dissatisfied +16216,69592,Female,Loyal Customer,46,Personal Travel,Eco,2475,1,3,0,4,0,1,1,2,4,2,3,1,1,1,4,0.0,neutral or dissatisfied +16217,105356,Female,Loyal Customer,55,Personal Travel,Eco,409,1,2,1,4,4,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +16218,17616,Female,Loyal Customer,30,Business travel,Business,622,3,1,3,3,4,4,4,4,2,2,5,5,5,4,9,0.0,satisfied +16219,124464,Female,Loyal Customer,53,Personal Travel,Eco,980,4,3,4,3,3,3,4,1,1,4,1,4,1,1,0,0.0,satisfied +16220,21586,Female,disloyal Customer,22,Business travel,Eco,380,4,3,4,3,1,4,1,1,2,2,3,4,4,1,0,0.0,neutral or dissatisfied +16221,119458,Female,Loyal Customer,57,Personal Travel,Business,759,2,4,2,3,4,4,4,4,4,2,4,3,4,4,0,41.0,neutral or dissatisfied +16222,72063,Female,Loyal Customer,46,Business travel,Business,2556,3,3,3,3,4,3,5,5,5,5,5,4,5,3,13,0.0,satisfied +16223,53087,Female,Loyal Customer,41,Personal Travel,Eco,2327,2,4,2,2,3,2,3,3,1,4,3,2,5,3,0,0.0,neutral or dissatisfied +16224,9328,Male,Loyal Customer,35,Personal Travel,Eco,419,3,5,3,4,3,3,3,2,1,3,4,3,2,3,180,165.0,neutral or dissatisfied +16225,33007,Male,Loyal Customer,46,Personal Travel,Eco,101,2,5,0,5,3,0,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +16226,28238,Male,Loyal Customer,21,Personal Travel,Eco,1009,2,5,2,1,2,2,2,2,3,4,5,5,5,2,0,4.0,neutral or dissatisfied +16227,88950,Male,Loyal Customer,39,Business travel,Business,1199,2,2,2,2,5,5,4,5,5,4,5,3,5,5,0,0.0,satisfied +16228,51479,Female,disloyal Customer,23,Business travel,Business,598,4,5,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +16229,92956,Male,disloyal Customer,25,Business travel,Eco Plus,134,1,0,0,1,2,0,2,2,1,3,3,4,1,2,0,0.0,neutral or dissatisfied +16230,108064,Female,Loyal Customer,60,Business travel,Business,1784,2,3,3,3,3,3,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +16231,7559,Male,Loyal Customer,32,Personal Travel,Eco,606,2,5,2,3,2,2,5,2,5,2,4,4,4,2,0,16.0,neutral or dissatisfied +16232,30514,Male,disloyal Customer,21,Business travel,Eco,377,3,4,3,5,2,3,2,2,2,1,5,1,4,2,5,0.0,neutral or dissatisfied +16233,25033,Female,Loyal Customer,16,Personal Travel,Eco,907,1,4,0,1,0,1,5,4,3,5,4,5,5,5,129,133.0,neutral or dissatisfied +16234,27520,Female,Loyal Customer,57,Personal Travel,Eco,697,2,4,2,4,1,3,4,5,5,2,5,3,5,3,0,0.0,neutral or dissatisfied +16235,102294,Female,disloyal Customer,68,Business travel,Eco,223,3,2,3,4,3,3,5,3,4,3,4,4,3,3,0,9.0,neutral or dissatisfied +16236,37849,Female,disloyal Customer,27,Business travel,Eco,937,4,3,3,2,2,3,2,2,3,2,1,5,5,2,0,0.0,satisfied +16237,23139,Female,Loyal Customer,52,Business travel,Business,3268,4,1,1,1,3,4,3,4,4,4,4,4,4,3,0,9.0,neutral or dissatisfied +16238,36256,Female,Loyal Customer,46,Business travel,Business,2981,3,3,3,3,4,1,3,5,5,5,5,5,5,3,0,0.0,satisfied +16239,5313,Female,Loyal Customer,33,Business travel,Eco Plus,295,2,4,4,4,2,2,2,2,3,5,3,3,3,2,0,0.0,neutral or dissatisfied +16240,29810,Male,disloyal Customer,54,Business travel,Eco,95,1,0,1,3,3,1,3,3,5,4,1,5,5,3,0,0.0,neutral or dissatisfied +16241,31468,Female,Loyal Customer,35,Business travel,Eco,862,4,2,2,2,4,4,4,4,4,2,5,5,2,4,0,0.0,satisfied +16242,74790,Female,Loyal Customer,45,Business travel,Eco Plus,1235,2,5,5,5,5,3,4,2,2,2,2,2,2,4,56,39.0,neutral or dissatisfied +16243,102629,Female,Loyal Customer,41,Business travel,Business,601,3,3,3,3,4,5,4,5,5,5,5,4,5,5,46,50.0,satisfied +16244,20762,Female,disloyal Customer,23,Business travel,Business,515,0,4,1,4,3,1,3,3,5,4,5,4,5,3,122,110.0,satisfied +16245,50414,Male,Loyal Customer,56,Business travel,Business,2938,3,3,3,3,2,5,1,4,4,4,4,3,4,5,0,0.0,satisfied +16246,92222,Male,Loyal Customer,54,Personal Travel,Eco,1979,4,1,4,3,3,4,3,3,4,5,3,2,4,3,0,0.0,satisfied +16247,22255,Female,Loyal Customer,34,Business travel,Business,208,0,3,1,3,1,5,2,4,4,4,4,4,4,5,25,22.0,satisfied +16248,20969,Female,Loyal Customer,59,Personal Travel,Eco,689,0,4,0,2,5,5,4,2,2,4,2,3,2,3,24,37.0,satisfied +16249,47670,Female,disloyal Customer,27,Business travel,Eco,1211,2,2,2,3,2,2,2,2,3,3,3,1,4,2,0,0.0,neutral or dissatisfied +16250,74249,Male,Loyal Customer,48,Business travel,Eco,1709,3,3,3,3,3,3,3,3,2,5,4,4,4,3,78,69.0,neutral or dissatisfied +16251,94377,Female,disloyal Customer,23,Business travel,Eco,148,4,1,4,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +16252,27626,Male,Loyal Customer,32,Business travel,Eco Plus,671,0,0,0,4,4,0,4,4,1,1,4,3,5,4,0,0.0,satisfied +16253,41364,Male,Loyal Customer,59,Business travel,Eco,775,4,4,4,4,4,4,4,4,4,2,2,3,3,4,37,51.0,satisfied +16254,117634,Female,Loyal Customer,16,Personal Travel,Eco,843,3,2,3,3,4,3,4,4,1,5,4,3,4,4,1,5.0,neutral or dissatisfied +16255,95901,Female,Loyal Customer,31,Personal Travel,Eco,580,3,5,3,5,4,3,3,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +16256,100570,Male,Loyal Customer,40,Business travel,Business,2899,5,5,5,5,4,5,5,4,4,5,4,3,4,5,20,21.0,satisfied +16257,65007,Male,Loyal Customer,73,Business travel,Business,3887,2,4,4,4,2,4,4,2,2,3,2,3,2,4,13,34.0,neutral or dissatisfied +16258,39525,Male,Loyal Customer,25,Personal Travel,Eco,852,2,4,3,1,1,3,2,1,3,2,5,4,5,1,0,24.0,neutral or dissatisfied +16259,117694,Male,Loyal Customer,18,Personal Travel,Eco,2075,4,3,3,2,3,3,3,3,1,2,4,2,5,3,0,0.0,satisfied +16260,9139,Male,Loyal Customer,44,Business travel,Business,227,3,3,3,3,4,5,4,3,3,4,3,5,3,5,1,7.0,satisfied +16261,33802,Male,Loyal Customer,56,Business travel,Business,1428,2,2,2,2,2,3,4,4,4,4,4,4,4,2,3,0.0,satisfied +16262,24953,Female,Loyal Customer,37,Personal Travel,Eco,1747,4,2,4,3,5,4,5,5,3,3,4,4,3,5,5,0.0,satisfied +16263,125143,Female,Loyal Customer,30,Business travel,Business,1999,1,1,1,1,5,5,5,5,5,5,4,3,4,5,0,0.0,satisfied +16264,104250,Female,Loyal Customer,52,Personal Travel,Eco,1276,4,1,5,2,4,2,2,4,4,5,4,4,4,1,0,0.0,satisfied +16265,63443,Female,Loyal Customer,27,Personal Travel,Eco,337,2,4,2,1,5,2,5,5,3,4,4,5,5,5,85,81.0,neutral or dissatisfied +16266,70669,Male,disloyal Customer,20,Business travel,Eco,447,1,4,2,2,2,2,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +16267,67044,Female,Loyal Customer,53,Business travel,Business,2565,2,1,1,1,1,4,4,2,2,2,2,3,2,1,0,62.0,neutral or dissatisfied +16268,90361,Male,Loyal Customer,16,Business travel,Business,404,2,5,5,5,2,2,2,2,1,5,3,4,3,2,0,0.0,neutral or dissatisfied +16269,30403,Male,Loyal Customer,51,Personal Travel,Eco,775,2,5,2,3,1,2,1,1,3,5,4,4,1,1,0,0.0,neutral or dissatisfied +16270,99261,Female,Loyal Customer,39,Business travel,Business,2418,5,5,5,5,5,5,5,3,3,3,3,4,3,5,0,7.0,satisfied +16271,88083,Male,Loyal Customer,43,Business travel,Business,515,4,4,4,4,4,5,5,2,2,2,2,4,2,5,7,8.0,satisfied +16272,65553,Male,Loyal Customer,57,Business travel,Business,237,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +16273,81372,Female,Loyal Customer,67,Personal Travel,Eco,282,2,4,2,3,3,4,5,5,5,2,5,3,5,3,12,0.0,neutral or dissatisfied +16274,81862,Female,Loyal Customer,40,Personal Travel,Eco Plus,1416,2,5,2,1,4,2,4,4,2,3,4,2,4,4,0,0.0,neutral or dissatisfied +16275,56504,Male,Loyal Customer,42,Business travel,Business,1068,1,1,5,1,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +16276,55962,Female,Loyal Customer,27,Business travel,Business,1620,2,4,4,4,2,2,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +16277,96688,Male,Loyal Customer,52,Business travel,Business,813,4,1,1,1,4,4,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +16278,39591,Male,disloyal Customer,44,Business travel,Eco,565,4,4,5,1,2,5,2,2,4,5,4,3,3,2,22,7.0,neutral or dissatisfied +16279,63680,Male,Loyal Customer,34,Personal Travel,Eco,1047,3,5,3,2,5,3,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +16280,126849,Female,Loyal Customer,36,Business travel,Eco,744,4,1,1,1,4,5,4,4,3,2,1,1,1,4,0,0.0,satisfied +16281,10879,Male,disloyal Customer,38,Business travel,Eco,140,2,3,2,3,1,2,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +16282,111649,Male,Loyal Customer,34,Personal Travel,Eco,1290,1,2,1,3,2,1,2,2,1,5,4,1,4,2,22,11.0,neutral or dissatisfied +16283,21191,Female,disloyal Customer,21,Business travel,Eco,317,5,0,5,3,5,5,5,5,1,5,4,4,2,5,0,0.0,satisfied +16284,114566,Male,Loyal Customer,41,Personal Travel,Business,480,1,3,1,1,2,5,4,3,3,1,3,5,3,4,3,0.0,neutral or dissatisfied +16285,58334,Female,Loyal Customer,43,Business travel,Business,1899,3,3,3,3,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +16286,106417,Female,Loyal Customer,20,Personal Travel,Eco,488,4,4,4,1,2,4,2,2,5,3,4,4,5,2,32,17.0,neutral or dissatisfied +16287,51900,Female,Loyal Customer,47,Business travel,Eco,507,5,3,3,3,2,4,2,5,5,5,5,4,5,5,0,0.0,satisfied +16288,8675,Male,disloyal Customer,22,Business travel,Eco,227,2,2,2,3,5,2,5,5,3,2,2,1,2,5,0,0.0,neutral or dissatisfied +16289,41460,Female,Loyal Customer,29,Personal Travel,Business,1334,2,5,2,4,4,2,4,4,5,5,4,4,5,4,16,13.0,neutral or dissatisfied +16290,29066,Male,Loyal Customer,34,Personal Travel,Eco,1050,4,2,4,3,4,4,4,4,2,4,4,4,3,4,0,0.0,neutral or dissatisfied +16291,99633,Female,Loyal Customer,52,Personal Travel,Eco,1224,3,4,3,4,2,3,3,1,1,3,5,2,1,1,0,0.0,neutral or dissatisfied +16292,100793,Female,Loyal Customer,53,Business travel,Business,2729,3,3,3,3,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +16293,21115,Male,Loyal Customer,20,Personal Travel,Eco,214,0,5,0,1,4,0,4,4,1,1,3,1,3,4,0,0.0,satisfied +16294,66769,Male,Loyal Customer,13,Business travel,Eco Plus,802,1,3,3,3,1,1,3,1,1,3,3,1,3,1,14,40.0,neutral or dissatisfied +16295,98218,Female,Loyal Customer,31,Business travel,Business,1825,3,3,3,3,2,2,2,2,3,4,4,1,2,2,1,4.0,satisfied +16296,53264,Male,Loyal Customer,41,Personal Travel,Business,901,1,3,1,2,3,1,3,5,5,1,5,4,5,4,0,0.0,neutral or dissatisfied +16297,90999,Male,Loyal Customer,68,Personal Travel,Eco,594,3,5,3,4,4,3,4,4,1,2,5,2,4,4,0,0.0,neutral or dissatisfied +16298,115257,Female,Loyal Customer,67,Business travel,Eco,371,4,2,2,2,2,3,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +16299,70519,Male,Loyal Customer,50,Business travel,Business,3388,3,3,3,3,4,4,5,5,5,5,5,4,5,3,1,6.0,satisfied +16300,18775,Female,Loyal Customer,70,Personal Travel,Business,448,2,5,2,2,3,4,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +16301,62626,Female,Loyal Customer,22,Personal Travel,Eco,1846,2,5,2,2,5,2,5,5,3,2,1,1,1,5,0,0.0,neutral or dissatisfied +16302,46589,Male,Loyal Customer,45,Business travel,Business,125,4,4,4,4,5,3,3,2,2,2,4,1,2,2,0,0.0,neutral or dissatisfied +16303,69670,Female,Loyal Customer,53,Personal Travel,Eco,569,2,4,2,2,3,5,2,2,2,2,2,2,2,1,19,9.0,neutral or dissatisfied +16304,124511,Female,disloyal Customer,18,Business travel,Eco Plus,930,2,3,3,4,4,3,4,4,4,2,4,3,4,4,86,62.0,neutral or dissatisfied +16305,57926,Male,Loyal Customer,43,Business travel,Eco Plus,305,4,3,2,3,4,4,4,4,4,1,3,4,3,4,6,6.0,neutral or dissatisfied +16306,56100,Female,Loyal Customer,34,Business travel,Business,2402,4,4,4,4,5,5,5,5,5,5,5,5,5,5,0,13.0,satisfied +16307,119570,Female,Loyal Customer,45,Business travel,Business,759,4,4,3,4,3,5,4,5,5,5,5,5,5,4,3,20.0,satisfied +16308,110966,Female,disloyal Customer,41,Business travel,Business,197,2,2,2,4,2,2,2,2,1,3,3,1,3,2,32,33.0,neutral or dissatisfied +16309,117291,Male,Loyal Customer,38,Business travel,Eco Plus,368,2,2,2,2,2,2,2,2,1,5,3,4,3,2,76,71.0,neutral or dissatisfied +16310,75127,Female,Loyal Customer,60,Business travel,Business,1652,4,4,4,4,5,5,4,5,5,5,5,5,5,4,32,7.0,satisfied +16311,35309,Female,disloyal Customer,28,Business travel,Eco,1069,4,5,5,4,4,5,4,4,1,1,3,4,3,4,0,19.0,neutral or dissatisfied +16312,41111,Male,Loyal Customer,48,Business travel,Eco,295,4,1,1,1,5,4,5,5,3,2,3,5,2,5,44,30.0,satisfied +16313,4802,Female,Loyal Customer,49,Personal Travel,Eco,438,3,4,3,4,4,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +16314,114098,Female,Loyal Customer,31,Personal Travel,Eco,1947,3,5,3,2,3,3,3,3,5,3,5,5,5,3,0,2.0,neutral or dissatisfied +16315,5251,Female,Loyal Customer,57,Business travel,Business,295,1,1,1,1,5,3,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +16316,10046,Male,Loyal Customer,52,Business travel,Business,3129,3,3,5,3,5,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +16317,60726,Male,Loyal Customer,59,Personal Travel,Eco,1605,2,4,2,3,4,2,4,4,3,3,5,4,4,4,0,10.0,neutral or dissatisfied +16318,71988,Female,Loyal Customer,22,Personal Travel,Eco,1440,2,5,2,5,5,2,5,5,3,3,3,5,5,5,33,58.0,neutral or dissatisfied +16319,110701,Male,Loyal Customer,37,Personal Travel,Eco,1005,2,5,2,3,3,2,3,3,5,3,5,4,4,3,11,6.0,neutral or dissatisfied +16320,27092,Male,Loyal Customer,21,Business travel,Business,1721,1,1,1,1,4,5,4,4,2,3,4,5,5,4,0,0.0,satisfied +16321,111043,Male,Loyal Customer,38,Business travel,Business,2405,1,1,1,1,5,1,3,5,5,5,5,3,5,3,11,7.0,satisfied +16322,118124,Female,disloyal Customer,24,Business travel,Eco,1275,4,4,4,1,3,4,3,3,4,4,5,3,4,3,0,0.0,satisfied +16323,63454,Male,Loyal Customer,40,Business travel,Business,2311,3,3,3,3,3,4,4,4,4,4,4,5,4,4,23,19.0,satisfied +16324,43607,Female,Loyal Customer,42,Business travel,Business,2683,1,4,3,3,3,4,4,1,1,2,1,1,1,2,0,0.0,neutral or dissatisfied +16325,32637,Female,disloyal Customer,24,Business travel,Eco,163,5,0,5,3,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +16326,78371,Male,Loyal Customer,53,Business travel,Business,980,5,5,3,5,2,5,4,5,5,5,5,4,5,3,3,64.0,satisfied +16327,94593,Male,Loyal Customer,60,Business travel,Business,3052,3,3,3,3,3,5,5,4,4,4,4,3,4,3,0,1.0,satisfied +16328,17582,Female,Loyal Customer,27,Personal Travel,Eco,1034,3,5,3,3,2,3,2,2,3,5,5,4,4,2,17,30.0,neutral or dissatisfied +16329,3443,Male,Loyal Customer,64,Personal Travel,Eco,296,3,4,3,1,1,3,1,1,4,2,4,3,5,1,0,0.0,neutral or dissatisfied +16330,90067,Male,Loyal Customer,52,Business travel,Business,957,2,2,2,2,4,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +16331,80421,Female,Loyal Customer,36,Business travel,Business,2248,1,1,4,1,5,5,5,5,5,5,5,4,5,5,7,0.0,satisfied +16332,19228,Male,Loyal Customer,13,Personal Travel,Eco Plus,459,1,5,1,5,4,1,5,4,2,2,4,5,5,4,0,7.0,neutral or dissatisfied +16333,75798,Female,Loyal Customer,60,Personal Travel,Eco,868,4,3,4,4,2,4,4,4,4,4,4,4,4,2,0,41.0,neutral or dissatisfied +16334,93277,Female,Loyal Customer,39,Personal Travel,Eco,806,5,3,5,3,4,3,4,4,5,3,1,1,3,4,16,3.0,satisfied +16335,77398,Male,Loyal Customer,48,Personal Travel,Eco,626,2,5,2,4,3,2,2,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +16336,34728,Male,Loyal Customer,40,Business travel,Eco,209,4,1,1,1,4,4,4,2,1,2,4,4,1,4,168,180.0,satisfied +16337,49631,Male,Loyal Customer,37,Business travel,Business,266,2,5,5,5,2,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +16338,78211,Female,Loyal Customer,14,Personal Travel,Eco,317,2,4,2,3,5,2,5,5,3,1,3,3,4,5,0,0.0,neutral or dissatisfied +16339,49181,Male,disloyal Customer,30,Business travel,Eco,250,2,0,2,5,3,2,3,3,1,4,3,5,5,3,40,49.0,neutral or dissatisfied +16340,66829,Female,Loyal Customer,55,Business travel,Business,731,1,1,1,1,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +16341,89132,Male,Loyal Customer,41,Business travel,Business,1947,2,1,1,1,3,2,3,2,2,2,2,1,2,4,3,7.0,neutral or dissatisfied +16342,42808,Female,Loyal Customer,45,Business travel,Eco,677,5,4,4,4,5,2,2,4,4,5,4,3,4,3,18,18.0,satisfied +16343,93065,Male,Loyal Customer,64,Business travel,Business,2739,4,4,4,4,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +16344,102060,Female,Loyal Customer,24,Personal Travel,Business,226,1,5,1,1,4,1,4,4,5,3,5,4,5,4,1,0.0,neutral or dissatisfied +16345,120884,Male,Loyal Customer,43,Business travel,Business,861,5,5,3,5,3,4,5,5,5,5,5,3,5,4,0,11.0,satisfied +16346,5633,Female,Loyal Customer,29,Business travel,Eco Plus,685,1,4,4,4,1,1,1,1,4,2,3,2,4,1,27,18.0,neutral or dissatisfied +16347,113055,Male,disloyal Customer,24,Business travel,Eco,569,4,0,4,1,5,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +16348,111168,Male,disloyal Customer,49,Business travel,Business,1506,2,2,2,4,3,2,3,3,4,2,5,5,4,3,14,0.0,neutral or dissatisfied +16349,77307,Female,Loyal Customer,27,Personal Travel,Business,588,2,5,2,5,5,2,5,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +16350,2294,Female,Loyal Customer,29,Business travel,Business,3669,5,5,5,5,5,5,5,5,5,3,5,3,5,5,4,5.0,satisfied +16351,60684,Female,disloyal Customer,35,Business travel,Business,1605,2,2,2,3,1,2,3,1,3,2,5,3,5,1,0,0.0,neutral or dissatisfied +16352,16961,Male,Loyal Customer,32,Business travel,Business,3315,2,2,2,2,5,5,5,5,2,5,2,1,1,5,0,0.0,satisfied +16353,67701,Male,Loyal Customer,14,Business travel,Eco,1464,2,5,5,5,2,2,4,2,2,5,4,2,4,2,20,11.0,neutral or dissatisfied +16354,118220,Male,disloyal Customer,24,Business travel,Eco,735,1,1,1,2,4,1,4,4,4,4,2,1,2,4,16,12.0,neutral or dissatisfied +16355,106158,Male,Loyal Customer,22,Personal Travel,Eco,302,5,1,5,3,3,5,2,3,4,4,4,2,3,3,15,7.0,satisfied +16356,84883,Male,Loyal Customer,23,Personal Travel,Eco,516,3,5,3,4,5,3,5,5,1,2,3,2,3,5,14,11.0,neutral or dissatisfied +16357,78104,Male,Loyal Customer,24,Personal Travel,Eco,684,1,1,1,3,1,1,1,1,1,2,4,3,3,1,15,28.0,neutral or dissatisfied +16358,121266,Female,Loyal Customer,58,Personal Travel,Eco,2075,4,5,4,3,2,3,5,1,1,4,4,3,1,5,75,84.0,neutral or dissatisfied +16359,66927,Female,Loyal Customer,18,Business travel,Business,3410,4,1,4,4,5,5,5,5,3,4,4,5,5,5,0,0.0,satisfied +16360,25421,Female,Loyal Customer,42,Personal Travel,Eco Plus,1105,2,1,2,2,5,1,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +16361,124520,Male,Loyal Customer,48,Business travel,Business,1783,4,4,4,4,4,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +16362,61403,Male,Loyal Customer,57,Personal Travel,Eco,679,1,5,1,1,4,1,4,4,3,4,4,4,4,4,28,33.0,neutral or dissatisfied +16363,113129,Male,Loyal Customer,16,Personal Travel,Eco Plus,569,3,3,4,2,3,4,3,3,2,2,3,1,2,3,0,0.0,neutral or dissatisfied +16364,26106,Male,disloyal Customer,26,Business travel,Eco Plus,591,1,1,1,2,5,1,4,5,3,1,2,2,2,5,0,0.0,neutral or dissatisfied +16365,79447,Female,disloyal Customer,20,Business travel,Business,269,5,0,5,4,5,3,3,4,2,4,5,3,5,3,138,136.0,satisfied +16366,79319,Male,Loyal Customer,26,Personal Travel,Eco Plus,2248,2,5,2,1,3,2,3,3,4,4,4,4,4,3,41,25.0,neutral or dissatisfied +16367,52055,Male,Loyal Customer,72,Business travel,Eco,639,5,2,3,2,5,5,5,5,1,5,1,4,5,5,7,5.0,satisfied +16368,66153,Male,disloyal Customer,26,Business travel,Business,550,1,1,1,3,5,1,5,5,2,4,4,2,3,5,0,9.0,neutral or dissatisfied +16369,78889,Male,Loyal Customer,56,Business travel,Business,1727,1,1,1,1,2,3,5,3,3,3,3,5,3,5,0,2.0,satisfied +16370,27561,Female,Loyal Customer,24,Personal Travel,Eco,697,2,2,2,3,2,2,2,2,2,1,3,2,4,2,0,0.0,neutral or dissatisfied +16371,48022,Male,Loyal Customer,23,Business travel,Business,1384,4,4,4,4,4,4,4,4,2,5,5,3,3,4,0,6.0,satisfied +16372,129572,Female,disloyal Customer,24,Business travel,Eco Plus,2342,2,4,2,3,5,2,3,5,2,2,2,2,4,5,4,3.0,neutral or dissatisfied +16373,80903,Male,Loyal Customer,33,Personal Travel,Business,341,2,5,2,2,2,2,1,2,3,4,4,4,4,2,18,24.0,neutral or dissatisfied +16374,21353,Male,Loyal Customer,62,Personal Travel,Eco,761,2,4,1,3,4,1,4,4,5,3,4,3,5,4,31,62.0,neutral or dissatisfied +16375,2026,Male,Loyal Customer,19,Business travel,Business,733,4,4,4,4,5,4,5,5,4,5,4,5,5,5,0,0.0,satisfied +16376,15011,Female,Loyal Customer,33,Business travel,Business,2194,2,2,2,2,2,2,3,4,4,4,4,3,4,1,4,0.0,satisfied +16377,674,Female,Loyal Customer,41,Business travel,Business,113,5,5,5,5,2,4,4,5,5,5,5,4,5,4,47,49.0,satisfied +16378,72835,Female,Loyal Customer,28,Business travel,Business,2938,4,4,4,4,4,4,4,4,5,4,4,4,5,4,9,0.0,satisfied +16379,92557,Female,Loyal Customer,58,Personal Travel,Eco,1892,1,4,1,3,4,4,5,2,2,1,4,1,2,5,8,0.0,neutral or dissatisfied +16380,34112,Female,Loyal Customer,42,Business travel,Eco,1189,5,5,5,5,5,1,4,5,5,5,5,4,5,3,0,0.0,satisfied +16381,113467,Female,Loyal Customer,37,Business travel,Eco,397,3,1,1,1,3,3,3,3,1,2,3,1,4,3,28,25.0,neutral or dissatisfied +16382,102624,Female,Loyal Customer,52,Business travel,Business,3698,5,5,5,5,2,5,4,5,5,4,5,3,5,4,6,16.0,satisfied +16383,6778,Male,Loyal Customer,53,Business travel,Business,2442,4,4,2,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +16384,129684,Male,Loyal Customer,44,Business travel,Business,337,1,1,1,1,2,4,5,4,4,4,4,3,4,4,0,3.0,satisfied +16385,66658,Female,Loyal Customer,51,Business travel,Business,978,5,5,5,5,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +16386,82161,Male,disloyal Customer,26,Business travel,Business,237,3,4,3,5,4,3,4,4,3,2,5,3,5,4,0,20.0,neutral or dissatisfied +16387,128105,Male,Loyal Customer,40,Personal Travel,Business,1587,3,4,3,4,2,5,5,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +16388,95700,Male,disloyal Customer,36,Business travel,Business,237,2,3,3,3,5,3,5,5,3,4,4,4,4,5,6,5.0,neutral or dissatisfied +16389,28934,Male,Loyal Customer,50,Business travel,Business,1050,1,3,1,1,5,1,4,4,4,4,4,1,4,3,0,0.0,satisfied +16390,91945,Female,Loyal Customer,24,Personal Travel,Eco,2475,5,3,5,3,4,5,4,4,1,3,3,3,2,4,0,0.0,satisfied +16391,91215,Male,Loyal Customer,20,Personal Travel,Eco,406,5,4,5,3,4,5,4,4,4,5,4,3,4,4,2,1.0,satisfied +16392,58644,Female,Loyal Customer,48,Business travel,Business,867,3,3,3,3,5,4,5,4,4,4,4,3,4,4,41,12.0,satisfied +16393,25242,Female,Loyal Customer,15,Personal Travel,Eco,842,2,4,2,1,5,2,5,5,5,3,4,4,5,5,0,0.0,neutral or dissatisfied +16394,25775,Male,Loyal Customer,54,Business travel,Eco,762,4,1,1,1,4,4,4,4,5,2,1,1,1,4,0,20.0,satisfied +16395,21536,Female,Loyal Customer,7,Personal Travel,Eco,356,1,5,1,3,2,1,5,2,3,2,4,5,5,2,15,0.0,neutral or dissatisfied +16396,60851,Female,Loyal Customer,30,Personal Travel,Eco,1754,2,3,2,4,2,2,2,2,2,3,1,3,4,2,39,12.0,neutral or dissatisfied +16397,32153,Female,Loyal Customer,46,Business travel,Eco,163,5,2,2,2,2,3,3,5,5,5,5,5,5,1,0,0.0,satisfied +16398,118075,Female,disloyal Customer,45,Business travel,Business,1276,2,2,2,3,5,2,5,5,5,4,5,4,4,5,8,0.0,neutral or dissatisfied +16399,69340,Female,Loyal Customer,45,Business travel,Business,1096,3,3,3,3,4,4,4,5,5,5,5,4,5,4,17,18.0,satisfied +16400,77382,Female,Loyal Customer,58,Business travel,Business,199,4,4,4,4,5,2,3,5,5,4,5,2,5,5,4,9.0,satisfied +16401,31472,Female,disloyal Customer,20,Business travel,Eco,967,2,2,2,2,1,2,1,1,4,2,3,5,1,1,70,99.0,neutral or dissatisfied +16402,25522,Male,Loyal Customer,66,Personal Travel,Eco,547,4,2,4,3,5,4,5,5,1,2,4,3,3,5,6,0.0,satisfied +16403,65025,Female,Loyal Customer,64,Personal Travel,Eco,190,5,4,5,1,5,5,5,5,5,5,1,5,5,4,0,0.0,satisfied +16404,25899,Female,Loyal Customer,65,Personal Travel,Eco,907,3,5,3,3,3,5,4,2,2,3,2,5,2,3,7,0.0,neutral or dissatisfied +16405,116334,Female,Loyal Customer,13,Personal Travel,Eco,358,2,5,2,4,5,2,5,5,3,5,4,5,5,5,52,52.0,neutral or dissatisfied +16406,52794,Male,Loyal Customer,24,Personal Travel,Eco,1874,2,4,2,3,3,2,3,3,3,2,4,1,2,3,2,22.0,neutral or dissatisfied +16407,107988,Male,Loyal Customer,57,Business travel,Business,3760,0,0,0,3,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +16408,91938,Male,Loyal Customer,57,Business travel,Eco,2475,5,3,3,3,5,5,5,5,1,2,5,2,3,5,4,0.0,satisfied +16409,5010,Male,Loyal Customer,18,Personal Travel,Eco,502,3,4,3,5,1,3,1,1,4,2,5,5,5,1,0,0.0,neutral or dissatisfied +16410,23768,Female,Loyal Customer,60,Business travel,Business,2925,2,2,5,2,4,5,4,4,4,5,4,4,4,4,13,0.0,satisfied +16411,745,Female,Loyal Customer,58,Business travel,Business,2649,3,2,2,2,4,3,2,3,3,3,3,4,3,2,3,48.0,neutral or dissatisfied +16412,79036,Male,disloyal Customer,39,Business travel,Business,356,3,3,3,3,3,3,3,3,3,2,4,4,3,3,0,0.0,neutral or dissatisfied +16413,58170,Male,Loyal Customer,31,Business travel,Business,925,1,1,1,1,5,5,5,5,4,2,5,5,4,5,11,6.0,satisfied +16414,263,Male,Loyal Customer,43,Personal Travel,Business,802,1,2,1,3,2,3,3,2,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +16415,15642,Male,Loyal Customer,33,Business travel,Eco Plus,292,0,0,0,3,5,0,5,5,3,2,4,5,5,5,0,0.0,satisfied +16416,120829,Male,disloyal Customer,21,Business travel,Business,920,0,5,0,2,5,0,5,5,3,2,4,4,4,5,0,0.0,satisfied +16417,41520,Male,Loyal Customer,31,Business travel,Eco,1242,5,2,2,2,5,5,5,5,1,2,1,4,2,5,0,0.0,satisfied +16418,25002,Female,Loyal Customer,13,Personal Travel,Eco,692,3,5,3,2,2,3,2,2,4,2,4,4,5,2,0,0.0,neutral or dissatisfied +16419,46436,Male,Loyal Customer,50,Business travel,Business,2408,2,2,2,2,3,2,2,5,5,4,5,3,5,5,0,0.0,satisfied +16420,3317,Male,Loyal Customer,66,Business travel,Business,2565,4,4,5,4,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +16421,38115,Female,disloyal Customer,38,Business travel,Eco,1237,3,3,3,3,3,3,3,3,3,4,4,2,2,3,0,0.0,neutral or dissatisfied +16422,12254,Female,Loyal Customer,38,Business travel,Business,3326,4,4,5,4,5,3,4,4,4,4,4,1,4,3,8,0.0,satisfied +16423,82449,Female,Loyal Customer,44,Business travel,Business,2810,3,5,5,5,4,3,4,3,3,3,3,3,3,3,12,0.0,neutral or dissatisfied +16424,22873,Female,Loyal Customer,57,Personal Travel,Eco,302,1,4,1,4,2,2,4,1,1,1,1,2,1,2,10,6.0,neutral or dissatisfied +16425,101708,Male,Loyal Customer,35,Business travel,Business,1624,1,4,4,4,2,4,3,1,1,1,1,3,1,2,12,21.0,neutral or dissatisfied +16426,13993,Male,Loyal Customer,60,Business travel,Eco,160,5,1,4,1,3,5,3,3,4,1,4,5,4,3,130,121.0,satisfied +16427,120010,Female,Loyal Customer,53,Business travel,Business,111,2,1,1,1,2,3,3,4,4,4,2,4,4,2,0,0.0,neutral or dissatisfied +16428,50825,Female,Loyal Customer,70,Personal Travel,Eco,86,2,4,2,2,2,5,5,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +16429,59610,Female,Loyal Customer,23,Business travel,Business,3872,2,4,4,4,2,3,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +16430,74887,Male,Loyal Customer,62,Business travel,Business,2446,3,5,5,5,3,3,4,3,3,3,3,4,3,2,1,,neutral or dissatisfied +16431,70153,Male,Loyal Customer,53,Personal Travel,Eco,550,2,3,2,2,2,2,5,2,3,2,1,3,5,2,8,2.0,neutral or dissatisfied +16432,75745,Female,disloyal Customer,25,Business travel,Business,868,3,0,3,4,2,3,2,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +16433,38204,Male,Loyal Customer,27,Business travel,Eco Plus,1249,5,4,4,4,5,5,5,5,5,4,3,4,5,5,2,0.0,satisfied +16434,69663,Male,disloyal Customer,39,Business travel,Eco,169,2,2,2,3,5,2,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +16435,82672,Male,Loyal Customer,56,Business travel,Business,632,1,4,4,4,3,3,4,1,1,2,1,2,1,3,0,1.0,neutral or dissatisfied +16436,31692,Male,Loyal Customer,47,Business travel,Eco,862,5,3,3,3,5,5,5,5,1,3,3,4,1,5,74,70.0,satisfied +16437,68290,Female,Loyal Customer,19,Personal Travel,Eco,806,1,3,1,3,1,1,1,1,4,3,2,4,2,1,0,0.0,neutral or dissatisfied +16438,31504,Female,Loyal Customer,69,Business travel,Eco,853,3,3,3,3,5,2,2,3,3,3,3,4,3,2,68,82.0,neutral or dissatisfied +16439,70476,Male,Loyal Customer,32,Business travel,Business,2411,4,2,2,2,4,3,4,4,2,1,3,1,2,4,0,0.0,neutral or dissatisfied +16440,108726,Female,disloyal Customer,42,Business travel,Eco,191,4,2,4,4,4,4,2,4,4,3,4,1,3,4,0,3.0,neutral or dissatisfied +16441,42655,Female,Loyal Customer,47,Personal Travel,Eco Plus,546,2,2,2,3,5,4,3,2,2,2,2,1,2,2,0,24.0,neutral or dissatisfied +16442,78119,Female,Loyal Customer,36,Business travel,Business,1797,4,5,5,5,3,3,2,4,4,4,4,2,4,1,8,0.0,neutral or dissatisfied +16443,12545,Female,disloyal Customer,29,Business travel,Eco,871,1,1,1,2,1,1,1,1,4,4,4,1,1,1,9,0.0,neutral or dissatisfied +16444,61279,Male,Loyal Customer,36,Personal Travel,Eco,862,3,5,3,1,2,3,2,2,3,4,5,4,4,2,1,2.0,neutral or dissatisfied +16445,30651,Female,Loyal Customer,58,Personal Travel,Eco,770,1,4,0,2,3,4,4,3,3,0,3,4,3,4,0,0.0,neutral or dissatisfied +16446,47377,Male,Loyal Customer,48,Business travel,Business,2304,1,5,5,5,5,3,2,1,1,1,1,1,1,2,17,8.0,neutral or dissatisfied +16447,123486,Female,Loyal Customer,34,Business travel,Business,2077,4,4,4,4,2,4,3,4,4,3,4,1,4,4,12,0.0,neutral or dissatisfied +16448,79889,Female,Loyal Customer,29,Business travel,Business,3737,5,5,4,5,5,5,5,3,4,4,5,5,5,5,172,156.0,satisfied +16449,52991,Female,Loyal Customer,52,Business travel,Eco,1208,4,2,2,2,5,3,2,4,4,4,4,4,4,2,5,0.0,satisfied +16450,48685,Female,Loyal Customer,60,Business travel,Business,2416,2,2,2,2,3,4,5,4,4,4,5,5,4,4,0,3.0,satisfied +16451,56208,Male,Loyal Customer,45,Business travel,Business,1400,3,3,3,3,3,5,5,3,3,2,3,3,3,4,0,0.0,satisfied +16452,1822,Female,Loyal Customer,31,Business travel,Business,500,2,1,1,1,2,2,2,2,2,5,3,1,2,2,0,0.0,neutral or dissatisfied +16453,114832,Male,Loyal Customer,40,Business travel,Business,2100,5,5,5,5,4,4,4,4,4,4,4,5,4,3,15,7.0,satisfied +16454,118122,Male,Loyal Customer,54,Business travel,Business,1506,3,3,3,3,3,4,5,5,5,5,5,3,5,5,11,1.0,satisfied +16455,43919,Male,Loyal Customer,48,Personal Travel,Eco,114,1,3,0,3,0,4,4,1,4,2,2,4,1,4,138,131.0,neutral or dissatisfied +16456,119304,Female,Loyal Customer,58,Business travel,Business,2248,5,5,5,5,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +16457,97218,Female,Loyal Customer,48,Business travel,Business,3361,3,3,3,3,3,4,5,2,2,2,2,4,2,4,0,0.0,satisfied +16458,100600,Female,Loyal Customer,47,Business travel,Business,2253,2,2,2,2,4,5,4,3,3,4,3,4,3,5,0,1.0,satisfied +16459,76398,Male,Loyal Customer,32,Personal Travel,Eco,931,2,5,2,3,1,2,5,1,5,3,4,4,5,1,6,0.0,neutral or dissatisfied +16460,53948,Female,disloyal Customer,22,Business travel,Eco,1325,5,5,5,3,4,5,4,4,2,4,1,2,2,4,4,0.0,satisfied +16461,56327,Female,disloyal Customer,35,Business travel,Business,200,3,3,3,4,1,3,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +16462,13064,Female,Loyal Customer,45,Business travel,Business,936,3,3,3,3,4,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +16463,109134,Female,Loyal Customer,56,Business travel,Business,2832,4,5,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +16464,78481,Female,Loyal Customer,44,Business travel,Business,3622,1,1,1,1,2,4,5,3,3,3,3,5,3,5,0,12.0,satisfied +16465,40718,Male,disloyal Customer,16,Business travel,Eco,588,5,0,5,1,1,5,1,1,1,3,1,3,5,1,0,0.0,satisfied +16466,58045,Female,Loyal Customer,32,Business travel,Business,1678,2,2,3,2,5,5,5,5,3,5,5,4,4,5,54,36.0,satisfied +16467,76165,Male,Loyal Customer,36,Personal Travel,Eco,546,1,5,1,3,1,1,1,1,3,2,4,4,1,1,0,2.0,neutral or dissatisfied +16468,29858,Female,Loyal Customer,25,Business travel,Eco,627,4,3,1,3,4,4,3,4,4,2,1,2,2,4,0,2.0,satisfied +16469,124959,Male,Loyal Customer,36,Business travel,Business,184,2,1,1,1,5,4,3,4,4,4,2,2,4,4,0,0.0,neutral or dissatisfied +16470,10145,Male,Loyal Customer,53,Business travel,Business,1918,2,2,5,2,3,5,4,5,5,5,5,3,5,4,1,3.0,satisfied +16471,47791,Male,Loyal Customer,41,Business travel,Eco,329,4,3,2,3,4,4,4,4,4,3,5,4,1,4,0,0.0,satisfied +16472,3184,Male,Loyal Customer,53,Business travel,Eco,693,2,4,4,4,2,2,2,2,2,5,4,4,4,2,0,0.0,neutral or dissatisfied +16473,111463,Male,Loyal Customer,25,Personal Travel,Eco,836,1,4,1,5,5,1,5,5,3,4,4,3,5,5,32,34.0,neutral or dissatisfied +16474,52392,Male,Loyal Customer,9,Personal Travel,Eco,370,1,2,1,4,2,1,2,2,3,4,4,4,4,2,0,19.0,neutral or dissatisfied +16475,127322,Male,Loyal Customer,43,Business travel,Business,3098,2,3,3,3,1,2,2,0,0,1,2,2,0,1,3,0.0,neutral or dissatisfied +16476,9087,Male,Loyal Customer,57,Personal Travel,Eco,173,1,1,0,3,5,0,3,5,4,3,3,2,3,5,0,26.0,neutral or dissatisfied +16477,92189,Female,Loyal Customer,38,Business travel,Eco,1979,3,3,1,3,3,2,3,3,4,5,3,3,3,3,0,0.0,neutral or dissatisfied +16478,22659,Male,Loyal Customer,38,Personal Travel,Eco Plus,223,1,5,0,4,3,0,4,3,3,5,5,5,4,3,79,74.0,neutral or dissatisfied +16479,75599,Female,Loyal Customer,28,Personal Travel,Eco,337,3,4,3,3,3,3,3,3,3,5,4,1,3,3,0,0.0,neutral or dissatisfied +16480,128998,Female,Loyal Customer,27,Business travel,Business,2611,3,3,3,3,5,5,5,4,5,3,5,5,4,5,0,0.0,satisfied +16481,100244,Female,Loyal Customer,39,Business travel,Business,1052,1,1,1,1,5,5,5,5,5,5,5,5,5,4,3,0.0,satisfied +16482,51686,Female,Loyal Customer,30,Business travel,Business,1736,3,4,4,4,3,3,3,3,1,4,3,1,4,3,0,0.0,neutral or dissatisfied +16483,116098,Male,Loyal Customer,61,Personal Travel,Eco,480,4,4,4,3,5,4,5,5,3,2,4,2,3,5,1,0.0,neutral or dissatisfied +16484,34465,Female,Loyal Customer,52,Business travel,Eco,266,4,2,5,5,4,1,1,4,4,4,4,2,4,4,0,0.0,satisfied +16485,119644,Female,disloyal Customer,37,Business travel,Business,507,3,4,4,4,4,4,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +16486,29756,Male,Loyal Customer,54,Business travel,Business,261,3,1,1,1,3,3,4,3,3,4,3,4,3,4,22,16.0,neutral or dissatisfied +16487,86858,Male,Loyal Customer,10,Personal Travel,Eco,484,2,2,2,2,2,2,2,2,3,3,5,3,4,2,98,102.0,neutral or dissatisfied +16488,102960,Male,Loyal Customer,23,Business travel,Eco Plus,719,3,3,4,4,3,3,4,3,3,2,3,4,3,3,1,0.0,neutral or dissatisfied +16489,123895,Male,Loyal Customer,21,Personal Travel,Eco,573,2,4,3,3,1,3,1,1,2,5,3,3,3,1,13,10.0,neutral or dissatisfied +16490,98892,Female,Loyal Customer,31,Personal Travel,Eco Plus,991,2,5,2,2,2,2,2,2,5,3,5,5,4,2,56,62.0,neutral or dissatisfied +16491,14896,Male,Loyal Customer,55,Business travel,Business,1540,3,3,4,4,2,3,4,3,3,3,3,1,3,1,0,19.0,neutral or dissatisfied +16492,71206,Male,disloyal Customer,27,Business travel,Business,733,5,5,5,2,4,5,1,4,5,2,5,3,4,4,23,8.0,satisfied +16493,115425,Female,Loyal Customer,62,Business travel,Business,390,2,2,2,2,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +16494,52478,Male,Loyal Customer,55,Personal Travel,Eco Plus,261,1,5,1,1,3,1,4,3,1,4,4,5,2,3,0,0.0,neutral or dissatisfied +16495,17101,Female,Loyal Customer,46,Personal Travel,Eco,416,2,3,2,3,2,1,3,4,4,2,4,4,4,5,29,32.0,neutral or dissatisfied +16496,109292,Male,Loyal Customer,40,Business travel,Business,1072,5,5,5,5,5,5,4,5,5,5,5,4,5,4,90,82.0,satisfied +16497,69696,Female,Loyal Customer,42,Business travel,Business,1372,5,1,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +16498,18295,Female,Loyal Customer,34,Personal Travel,Eco,640,1,5,1,4,1,1,1,1,3,5,4,4,4,1,3,20.0,neutral or dissatisfied +16499,82541,Female,Loyal Customer,46,Business travel,Eco,629,4,1,1,1,5,4,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +16500,7165,Male,Loyal Customer,38,Business travel,Eco,135,4,3,3,3,4,4,4,4,3,5,3,2,3,4,0,43.0,neutral or dissatisfied +16501,29847,Female,Loyal Customer,78,Business travel,Business,1531,0,5,1,3,3,4,3,2,2,2,4,2,2,2,0,0.0,satisfied +16502,125519,Female,disloyal Customer,38,Business travel,Business,226,4,4,4,2,3,4,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +16503,68648,Female,Loyal Customer,40,Business travel,Business,237,4,4,4,4,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16504,77608,Male,Loyal Customer,50,Business travel,Business,3642,3,5,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +16505,25193,Male,Loyal Customer,44,Personal Travel,Eco,577,5,5,5,4,2,5,5,2,4,5,5,3,4,2,0,0.0,satisfied +16506,39715,Female,Loyal Customer,53,Business travel,Eco,410,4,4,4,4,4,4,3,4,4,4,4,2,4,2,0,0.0,satisfied +16507,85720,Male,Loyal Customer,40,Business travel,Business,2105,2,5,2,2,4,4,4,5,5,5,5,4,5,5,31,12.0,satisfied +16508,94472,Male,disloyal Customer,38,Business travel,Business,441,1,1,1,3,4,1,4,4,3,5,4,3,5,4,0,0.0,neutral or dissatisfied +16509,94449,Female,disloyal Customer,54,Business travel,Eco,239,3,2,3,3,5,3,5,5,1,4,4,4,4,5,10,10.0,neutral or dissatisfied +16510,28482,Female,Loyal Customer,44,Business travel,Eco,1739,5,3,3,3,4,4,2,5,5,5,5,5,5,5,14,0.0,satisfied +16511,52299,Female,Loyal Customer,54,Business travel,Business,2101,2,3,3,3,3,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +16512,61563,Male,Loyal Customer,12,Personal Travel,Eco Plus,2419,1,4,1,4,2,1,2,2,3,5,3,4,4,2,60,59.0,neutral or dissatisfied +16513,117982,Female,Loyal Customer,35,Personal Travel,Eco,255,1,3,1,2,1,1,1,1,2,2,2,3,2,1,96,88.0,neutral or dissatisfied +16514,127549,Male,Loyal Customer,34,Personal Travel,Eco,1009,2,3,2,4,5,2,5,5,4,1,4,4,3,5,0,0.0,neutral or dissatisfied +16515,97950,Female,disloyal Customer,22,Business travel,Eco,616,5,0,5,2,4,5,4,4,5,2,4,4,5,4,0,5.0,satisfied +16516,128850,Female,Loyal Customer,14,Personal Travel,Eco,2586,3,4,3,2,3,2,2,5,4,3,5,2,4,2,3,0.0,neutral or dissatisfied +16517,118798,Female,Loyal Customer,54,Personal Travel,Eco,368,2,4,5,4,2,4,4,2,2,5,4,4,2,3,0,9.0,neutral or dissatisfied +16518,47044,Male,disloyal Customer,22,Business travel,Eco,639,2,4,2,3,2,2,2,2,4,4,1,2,1,2,0,0.0,neutral or dissatisfied +16519,93124,Male,Loyal Customer,56,Business travel,Business,2161,5,4,5,5,5,4,5,5,5,5,5,4,5,4,47,40.0,satisfied +16520,99232,Male,disloyal Customer,51,Business travel,Eco,495,3,2,3,2,2,3,2,2,4,2,3,4,2,2,0,0.0,neutral or dissatisfied +16521,89641,Female,Loyal Customer,38,Business travel,Business,950,2,1,1,1,2,2,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +16522,108477,Female,Loyal Customer,61,Personal Travel,Eco Plus,1444,3,2,3,3,5,2,3,4,4,3,4,4,4,1,15,23.0,neutral or dissatisfied +16523,114259,Male,Loyal Customer,77,Business travel,Business,453,1,1,1,1,3,4,2,3,3,4,3,2,3,3,40,57.0,satisfied +16524,97279,Female,Loyal Customer,52,Business travel,Business,347,3,4,4,4,5,3,4,3,3,4,3,3,3,2,19,5.0,neutral or dissatisfied +16525,26295,Female,Loyal Customer,51,Business travel,Business,1199,5,5,5,5,4,3,5,4,4,4,4,4,4,2,2,11.0,satisfied +16526,38139,Male,Loyal Customer,17,Personal Travel,Eco,1010,2,4,2,4,3,2,3,3,1,2,3,3,4,3,5,19.0,neutral or dissatisfied +16527,102331,Female,Loyal Customer,16,Business travel,Business,407,3,5,5,5,3,3,3,3,1,5,3,1,4,3,54,43.0,neutral or dissatisfied +16528,80647,Female,Loyal Customer,30,Business travel,Business,2781,1,1,1,1,4,4,4,4,3,4,5,4,4,4,0,5.0,satisfied +16529,61817,Male,Loyal Customer,64,Personal Travel,Eco,1303,0,5,1,1,4,1,4,4,3,4,4,5,5,4,2,0.0,satisfied +16530,47890,Female,Loyal Customer,37,Business travel,Eco,550,5,4,4,4,5,5,5,5,4,5,4,3,5,5,0,0.0,satisfied +16531,24243,Male,Loyal Customer,38,Personal Travel,Eco,134,4,4,4,4,5,4,5,5,4,3,4,3,3,5,0,9.0,satisfied +16532,27371,Female,Loyal Customer,23,Business travel,Business,3441,5,4,4,4,5,4,5,5,2,4,4,3,3,5,1,10.0,neutral or dissatisfied +16533,29944,Male,Loyal Customer,38,Business travel,Business,399,3,3,3,3,5,5,2,5,5,5,5,1,5,3,0,0.0,satisfied +16534,52584,Male,Loyal Customer,57,Business travel,Eco,160,4,1,3,1,4,4,4,4,1,2,4,4,1,4,0,0.0,satisfied +16535,103774,Female,Loyal Customer,39,Business travel,Business,2185,4,4,4,4,5,5,4,5,5,5,5,4,5,4,33,25.0,satisfied +16536,125658,Male,Loyal Customer,40,Business travel,Business,2922,5,5,5,5,2,5,5,3,3,4,3,5,3,5,1,0.0,satisfied +16537,29408,Female,Loyal Customer,19,Personal Travel,Eco,2409,5,2,4,4,1,4,1,1,3,3,4,3,4,1,0,0.0,satisfied +16538,99424,Male,Loyal Customer,34,Personal Travel,Eco,337,3,2,3,4,2,3,5,2,3,4,4,4,4,2,21,7.0,neutral or dissatisfied +16539,107674,Female,disloyal Customer,58,Business travel,Business,405,3,3,3,4,4,3,4,4,5,2,5,5,4,4,12,0.0,neutral or dissatisfied +16540,105717,Female,Loyal Customer,35,Business travel,Business,2520,2,1,3,1,1,3,4,2,2,2,2,1,2,2,17,5.0,neutral or dissatisfied +16541,50912,Female,Loyal Customer,51,Personal Travel,Eco,156,3,4,0,4,3,4,5,5,5,0,5,5,5,4,0,0.0,neutral or dissatisfied +16542,59595,Female,Loyal Customer,24,Business travel,Business,1673,1,1,1,1,4,4,4,4,4,3,5,4,4,4,3,6.0,satisfied +16543,14805,Male,disloyal Customer,38,Business travel,Eco,95,3,3,3,3,3,3,3,3,2,5,3,1,4,3,87,59.0,neutral or dissatisfied +16544,7301,Female,disloyal Customer,43,Business travel,Business,116,3,3,3,4,2,3,2,2,3,5,4,3,5,2,7,43.0,neutral or dissatisfied +16545,70835,Female,disloyal Customer,16,Business travel,Business,761,5,4,5,2,3,5,3,3,3,3,5,3,4,3,0,44.0,satisfied +16546,103331,Female,Loyal Customer,70,Personal Travel,Eco,1371,2,4,2,3,4,3,5,3,3,2,4,5,3,4,0,0.0,neutral or dissatisfied +16547,126021,Male,Loyal Customer,39,Business travel,Business,650,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16548,104099,Male,Loyal Customer,42,Business travel,Business,3857,0,0,0,3,3,4,5,5,5,5,5,3,5,5,3,5.0,satisfied +16549,103738,Male,Loyal Customer,27,Personal Travel,Eco,405,3,4,3,2,2,3,2,2,3,3,5,5,5,2,85,76.0,neutral or dissatisfied +16550,81695,Male,Loyal Customer,17,Personal Travel,Eco,907,3,5,3,2,1,3,1,1,5,4,5,5,5,1,1,8.0,neutral or dissatisfied +16551,36621,Male,Loyal Customer,53,Business travel,Eco,785,4,4,4,4,3,4,3,3,1,2,1,4,2,3,7,2.0,satisfied +16552,35787,Male,Loyal Customer,56,Personal Travel,Eco,200,2,5,2,2,4,2,5,4,4,3,5,5,2,4,0,0.0,neutral or dissatisfied +16553,9422,Male,Loyal Customer,41,Business travel,Business,3397,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +16554,12550,Female,Loyal Customer,34,Personal Travel,Eco,788,3,3,3,4,2,3,2,2,3,2,4,4,3,2,51,54.0,neutral or dissatisfied +16555,4558,Female,Loyal Customer,45,Business travel,Eco,561,2,5,2,2,3,3,3,2,2,2,2,2,2,4,64,54.0,neutral or dissatisfied +16556,79389,Male,Loyal Customer,39,Business travel,Business,3896,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +16557,84550,Male,Loyal Customer,12,Personal Travel,Eco,2556,1,1,1,4,4,1,4,4,3,4,3,1,4,4,1,0.0,neutral or dissatisfied +16558,86727,Male,Loyal Customer,13,Personal Travel,Eco,1747,5,1,5,2,2,5,2,2,2,5,1,3,1,2,0,0.0,satisfied +16559,20040,Male,Loyal Customer,56,Business travel,Eco,528,2,4,4,4,2,2,2,2,4,4,4,3,3,2,4,0.0,neutral or dissatisfied +16560,23159,Female,Loyal Customer,21,Personal Travel,Eco,223,1,4,1,1,1,1,1,1,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +16561,62724,Male,Loyal Customer,29,Business travel,Business,2399,4,3,4,3,4,4,4,4,2,5,3,4,2,4,3,11.0,neutral or dissatisfied +16562,128868,Male,disloyal Customer,29,Business travel,Business,1443,0,0,0,5,0,2,2,3,5,4,4,2,3,2,0,0.0,satisfied +16563,64106,Female,Loyal Customer,54,Personal Travel,Eco Plus,919,4,4,4,3,3,3,3,4,4,4,4,4,4,2,36,34.0,neutral or dissatisfied +16564,62896,Female,Loyal Customer,44,Business travel,Business,862,3,3,3,3,3,5,5,2,2,2,2,5,2,3,0,0.0,satisfied +16565,125763,Male,Loyal Customer,22,Business travel,Business,2554,5,1,5,5,4,4,4,4,5,3,4,4,5,4,28,34.0,satisfied +16566,13994,Male,Loyal Customer,40,Business travel,Eco,160,5,3,4,4,5,5,5,5,4,1,4,4,3,5,0,0.0,satisfied +16567,10841,Female,disloyal Customer,55,Business travel,Eco,201,3,4,2,3,5,2,5,5,3,4,3,3,4,5,0,0.0,neutral or dissatisfied +16568,2452,Male,Loyal Customer,50,Business travel,Business,674,2,1,1,1,3,4,3,2,2,2,2,2,2,4,15,52.0,neutral or dissatisfied +16569,58052,Male,Loyal Customer,36,Business travel,Business,642,3,3,3,3,4,4,4,4,4,4,4,5,4,5,11,0.0,satisfied +16570,48140,Female,Loyal Customer,38,Business travel,Eco,391,2,3,3,3,2,2,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +16571,26915,Male,disloyal Customer,42,Business travel,Eco,1385,3,3,3,4,4,3,4,4,1,3,2,1,3,4,0,3.0,neutral or dissatisfied +16572,63728,Female,Loyal Customer,32,Business travel,Eco,1660,4,4,4,4,4,4,4,4,4,1,4,1,4,4,5,0.0,neutral or dissatisfied +16573,70273,Male,disloyal Customer,29,Business travel,Business,852,1,1,1,1,2,1,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +16574,102207,Male,Loyal Customer,35,Business travel,Business,3627,5,5,5,5,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +16575,37771,Male,Loyal Customer,64,Business travel,Eco Plus,1069,4,5,5,5,4,4,4,4,4,4,2,3,4,4,0,0.0,satisfied +16576,110570,Female,Loyal Customer,51,Business travel,Business,488,2,2,2,2,2,5,4,5,5,5,5,3,5,5,27,28.0,satisfied +16577,98395,Male,Loyal Customer,48,Business travel,Business,3155,1,1,1,1,2,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +16578,30872,Male,disloyal Customer,20,Business travel,Eco,1506,1,1,1,3,1,1,1,1,3,5,3,4,2,1,0,0.0,neutral or dissatisfied +16579,90176,Female,Loyal Customer,43,Personal Travel,Eco,1084,3,5,3,3,3,5,4,2,2,3,1,5,2,5,0,0.0,neutral or dissatisfied +16580,83581,Female,disloyal Customer,44,Business travel,Eco,536,1,1,1,2,2,1,2,2,1,1,2,2,1,2,0,0.0,neutral or dissatisfied +16581,15621,Female,Loyal Customer,11,Personal Travel,Eco,296,2,5,2,3,2,1,5,3,3,5,5,5,5,5,143,148.0,neutral or dissatisfied +16582,104920,Female,Loyal Customer,38,Business travel,Business,210,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +16583,80198,Female,Loyal Customer,36,Personal Travel,Eco,2586,2,4,2,4,2,5,4,3,4,3,5,4,4,4,6,0.0,neutral or dissatisfied +16584,27510,Male,disloyal Customer,37,Business travel,Eco,556,4,0,4,2,1,4,1,1,3,1,2,3,1,1,0,3.0,neutral or dissatisfied +16585,14118,Female,disloyal Customer,35,Business travel,Business,654,3,3,3,4,1,3,1,1,3,3,3,1,4,1,83,86.0,neutral or dissatisfied +16586,125835,Female,disloyal Customer,25,Business travel,Business,861,3,5,3,1,3,3,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +16587,77767,Female,Loyal Customer,45,Personal Travel,Eco,689,3,4,3,4,4,4,5,3,3,3,3,3,3,4,23,7.0,neutral or dissatisfied +16588,127713,Male,Loyal Customer,50,Business travel,Business,255,2,2,2,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +16589,122482,Male,Loyal Customer,68,Personal Travel,Eco,575,4,5,4,3,1,4,3,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +16590,116367,Female,Loyal Customer,29,Personal Travel,Eco,308,1,3,1,4,3,1,1,3,3,3,4,1,4,3,21,17.0,neutral or dissatisfied +16591,15593,Male,Loyal Customer,17,Business travel,Business,3346,2,4,4,4,2,2,2,2,1,1,3,4,4,2,15,0.0,neutral or dissatisfied +16592,76769,Male,Loyal Customer,43,Business travel,Business,3666,3,3,3,3,2,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +16593,83760,Female,Loyal Customer,39,Business travel,Business,1039,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +16594,47405,Female,Loyal Customer,27,Business travel,Business,2192,1,1,5,1,2,2,2,2,3,3,4,5,5,2,42,,satisfied +16595,61964,Male,Loyal Customer,44,Business travel,Business,2052,2,2,2,2,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +16596,44068,Male,Loyal Customer,14,Personal Travel,Eco,456,4,5,4,2,5,4,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +16597,78994,Male,Loyal Customer,55,Business travel,Business,1779,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,9.0,satisfied +16598,23767,Female,Loyal Customer,32,Business travel,Business,2232,3,3,3,3,5,5,5,5,5,4,4,5,4,5,0,0.0,satisfied +16599,38349,Female,disloyal Customer,25,Business travel,Eco,1173,1,1,1,4,3,1,1,3,1,5,4,1,3,3,23,50.0,neutral or dissatisfied +16600,53214,Male,disloyal Customer,28,Business travel,Eco,612,4,3,4,4,3,4,3,3,4,5,4,3,3,3,0,0.0,neutral or dissatisfied +16601,26759,Female,Loyal Customer,34,Personal Travel,Eco,859,2,4,2,3,1,2,1,1,3,5,2,4,2,1,0,11.0,neutral or dissatisfied +16602,127641,Male,Loyal Customer,69,Personal Travel,Eco,1773,1,4,1,3,5,1,5,5,2,4,5,1,3,5,0,0.0,neutral or dissatisfied +16603,20415,Female,Loyal Customer,35,Business travel,Business,2842,0,0,0,4,3,2,5,2,2,2,2,5,2,2,0,0.0,satisfied +16604,79490,Male,Loyal Customer,46,Personal Travel,Business,762,2,5,2,2,3,5,4,2,2,2,2,3,2,4,6,4.0,neutral or dissatisfied +16605,117637,Female,Loyal Customer,62,Personal Travel,Eco,347,2,5,2,1,2,5,4,4,4,2,4,4,4,5,17,12.0,neutral or dissatisfied +16606,78277,Female,Loyal Customer,43,Business travel,Business,1598,4,4,4,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +16607,73759,Male,Loyal Customer,24,Personal Travel,Eco,204,3,3,0,3,5,0,4,5,1,1,2,3,3,5,64,54.0,neutral or dissatisfied +16608,80439,Female,Loyal Customer,27,Personal Travel,Eco,2248,4,5,4,1,3,4,3,3,5,4,3,4,4,3,0,0.0,satisfied +16609,110400,Female,Loyal Customer,36,Business travel,Eco,925,1,3,3,3,1,1,1,1,1,5,2,4,3,1,35,35.0,neutral or dissatisfied +16610,53883,Male,Loyal Customer,40,Personal Travel,Eco,140,2,4,2,4,3,2,5,3,4,4,4,3,3,3,0,0.0,neutral or dissatisfied +16611,129008,Male,Loyal Customer,57,Business travel,Business,2611,2,3,3,3,2,2,2,1,4,2,3,2,3,2,0,0.0,neutral or dissatisfied +16612,37257,Male,Loyal Customer,35,Business travel,Eco,1028,4,5,5,5,4,4,4,4,1,2,1,4,3,4,0,0.0,satisfied +16613,77780,Male,Loyal Customer,40,Personal Travel,Eco,696,4,4,5,3,4,5,4,4,3,5,4,3,5,4,5,18.0,neutral or dissatisfied +16614,118166,Male,Loyal Customer,45,Business travel,Business,1444,2,2,2,2,2,5,4,4,4,4,4,5,4,5,30,17.0,satisfied +16615,56342,Male,Loyal Customer,50,Business travel,Business,200,3,2,2,2,1,2,3,1,1,1,3,4,1,4,0,0.0,neutral or dissatisfied +16616,121278,Male,Loyal Customer,47,Business travel,Business,2075,2,2,2,2,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +16617,62877,Male,Loyal Customer,50,Personal Travel,Eco,2446,1,4,1,2,5,1,5,5,1,2,2,3,4,5,0,0.0,neutral or dissatisfied +16618,60843,Male,Loyal Customer,14,Business travel,Eco,1754,2,5,5,5,2,2,4,2,4,1,2,3,3,2,28,33.0,neutral or dissatisfied +16619,123425,Female,Loyal Customer,65,Personal Travel,Eco Plus,1337,4,4,4,5,5,3,5,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +16620,125909,Female,Loyal Customer,33,Personal Travel,Eco,861,2,5,2,4,3,2,3,3,4,5,4,5,4,3,0,0.0,neutral or dissatisfied +16621,103589,Male,Loyal Customer,42,Business travel,Business,2381,1,1,1,1,2,5,4,5,5,5,5,3,5,5,5,0.0,satisfied +16622,75409,Female,Loyal Customer,54,Business travel,Business,2330,4,4,4,4,5,5,5,3,3,3,3,4,3,5,36,17.0,satisfied +16623,10042,Male,Loyal Customer,48,Business travel,Business,326,5,5,5,5,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +16624,19171,Male,Loyal Customer,15,Personal Travel,Eco Plus,304,4,5,4,4,5,4,5,5,4,4,4,5,5,5,4,2.0,neutral or dissatisfied +16625,57402,Female,Loyal Customer,14,Personal Travel,Eco Plus,1186,3,4,3,1,3,3,3,3,5,3,3,4,5,3,7,0.0,neutral or dissatisfied +16626,33428,Female,Loyal Customer,72,Business travel,Eco,2399,4,3,3,3,3,4,5,5,5,4,5,1,5,4,0,0.0,satisfied +16627,86106,Male,disloyal Customer,26,Business travel,Business,226,3,0,3,2,3,3,3,3,5,2,4,3,5,3,17,21.0,neutral or dissatisfied +16628,57619,Female,Loyal Customer,56,Business travel,Business,200,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +16629,29793,Female,Loyal Customer,42,Business travel,Eco,204,5,1,1,1,3,3,4,5,5,5,5,5,5,2,0,22.0,satisfied +16630,65322,Female,Loyal Customer,31,Business travel,Business,432,4,4,2,4,5,5,5,5,4,2,5,3,5,5,3,6.0,satisfied +16631,29005,Female,Loyal Customer,22,Business travel,Business,2652,2,2,2,2,4,4,4,4,1,3,3,3,3,4,0,0.0,satisfied +16632,75976,Male,Loyal Customer,31,Business travel,Business,2415,0,0,0,2,5,5,5,5,1,5,2,2,5,5,0,0.0,satisfied +16633,124903,Male,disloyal Customer,32,Business travel,Business,728,2,2,2,1,5,2,5,5,5,4,4,5,4,5,1,0.0,neutral or dissatisfied +16634,91061,Male,Loyal Customer,30,Personal Travel,Eco,270,2,4,1,3,4,1,4,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +16635,63244,Female,disloyal Customer,26,Business travel,Business,337,0,0,0,4,3,0,3,3,4,4,4,5,4,3,0,0.0,satisfied +16636,45782,Female,Loyal Customer,44,Business travel,Eco,391,5,3,3,3,3,3,1,5,5,5,5,1,5,5,0,3.0,satisfied +16637,67885,Female,Loyal Customer,31,Personal Travel,Eco,1205,4,1,4,4,4,4,5,4,4,2,3,3,3,4,8,0.0,neutral or dissatisfied +16638,122254,Male,Loyal Customer,49,Business travel,Business,141,2,1,1,1,5,4,3,3,3,3,2,4,3,1,61,58.0,neutral or dissatisfied +16639,6473,Female,Loyal Customer,17,Personal Travel,Eco Plus,296,3,4,3,3,3,2,2,4,3,5,5,2,3,2,89,148.0,neutral or dissatisfied +16640,17685,Male,Loyal Customer,42,Business travel,Eco Plus,1039,5,4,4,4,5,5,5,5,4,5,5,3,1,5,17,16.0,satisfied +16641,51314,Male,Loyal Customer,41,Business travel,Eco Plus,304,2,5,5,5,3,2,3,3,2,4,3,4,4,3,127,119.0,neutral or dissatisfied +16642,117882,Male,disloyal Customer,21,Business travel,Business,255,4,0,4,3,4,4,4,4,5,4,4,4,4,4,5,1.0,satisfied +16643,111320,Female,Loyal Customer,53,Business travel,Business,283,4,4,4,4,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +16644,67404,Female,Loyal Customer,40,Business travel,Business,641,5,5,5,5,4,5,4,3,3,3,3,3,3,5,14,15.0,satisfied +16645,9747,Male,Loyal Customer,42,Personal Travel,Eco,908,3,3,3,2,5,3,5,5,5,5,4,4,3,5,6,15.0,neutral or dissatisfied +16646,95138,Male,Loyal Customer,55,Personal Travel,Eco,239,5,4,5,2,2,5,2,2,5,4,5,5,5,2,0,0.0,satisfied +16647,58447,Female,Loyal Customer,63,Personal Travel,Eco,528,3,2,3,3,3,4,4,2,2,3,1,3,2,2,11,0.0,neutral or dissatisfied +16648,67943,Female,Loyal Customer,41,Personal Travel,Eco,1205,1,2,1,4,3,1,3,3,3,5,4,4,3,3,5,23.0,neutral or dissatisfied +16649,42636,Female,Loyal Customer,22,Personal Travel,Eco,223,4,5,4,4,2,4,2,2,4,5,5,5,4,2,0,0.0,satisfied +16650,40012,Male,Loyal Customer,44,Business travel,Business,2859,4,4,4,4,1,5,5,3,3,5,3,3,3,4,0,0.0,satisfied +16651,75811,Female,Loyal Customer,38,Business travel,Eco Plus,413,3,4,4,4,3,3,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +16652,63705,Female,Loyal Customer,53,Business travel,Business,1660,1,1,1,1,2,5,5,5,5,5,5,5,5,3,26,13.0,satisfied +16653,48806,Male,Loyal Customer,30,Personal Travel,Business,262,1,2,1,3,2,1,2,2,3,5,4,3,3,2,23,37.0,neutral or dissatisfied +16654,117146,Male,Loyal Customer,50,Personal Travel,Eco,338,3,4,3,3,3,3,3,3,4,2,5,4,4,3,9,4.0,neutral or dissatisfied +16655,109089,Female,Loyal Customer,30,Personal Travel,Eco,816,2,0,2,1,3,2,3,3,5,3,5,4,4,3,79,62.0,neutral or dissatisfied +16656,82590,Male,Loyal Customer,60,Business travel,Business,2315,1,1,1,1,2,5,5,4,4,4,4,4,4,5,26,23.0,satisfied +16657,120467,Male,Loyal Customer,44,Personal Travel,Eco,449,3,5,3,1,2,3,2,2,4,4,4,3,5,2,4,0.0,neutral or dissatisfied +16658,59016,Female,Loyal Customer,56,Business travel,Business,1846,3,4,3,3,4,4,4,5,5,5,5,5,5,3,19,24.0,satisfied +16659,117972,Male,Loyal Customer,34,Personal Travel,Eco,255,4,4,0,4,1,0,1,1,5,3,5,2,2,1,0,0.0,neutral or dissatisfied +16660,54605,Male,disloyal Customer,24,Business travel,Eco,854,1,1,1,1,2,1,2,2,4,1,5,5,3,2,0,0.0,neutral or dissatisfied +16661,101399,Female,Loyal Customer,60,Business travel,Business,486,1,1,2,1,4,4,5,4,4,4,4,5,4,3,1,0.0,satisfied +16662,77894,Female,Loyal Customer,44,Business travel,Business,3596,4,4,4,4,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +16663,89424,Female,Loyal Customer,44,Business travel,Eco,134,5,1,1,1,5,5,5,1,4,1,5,5,4,5,153,135.0,satisfied +16664,56256,Female,Loyal Customer,48,Business travel,Business,3788,3,4,4,4,1,4,3,3,3,3,3,1,3,2,29,28.0,neutral or dissatisfied +16665,87294,Male,Loyal Customer,52,Personal Travel,Eco,577,3,4,3,4,5,3,5,5,4,2,5,3,5,5,20,11.0,neutral or dissatisfied +16666,55934,Male,Loyal Customer,50,Business travel,Business,2581,3,3,3,3,4,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +16667,65910,Female,Loyal Customer,49,Business travel,Eco,569,1,3,3,3,2,4,3,1,1,1,1,3,1,3,0,19.0,neutral or dissatisfied +16668,80406,Female,Loyal Customer,39,Business travel,Business,1416,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +16669,40643,Male,Loyal Customer,63,Personal Travel,Eco Plus,411,1,5,1,2,4,1,4,4,5,3,4,5,4,4,0,0.0,neutral or dissatisfied +16670,13601,Female,Loyal Customer,55,Business travel,Eco Plus,152,3,3,3,3,1,1,5,4,4,3,4,5,4,5,0,0.0,satisfied +16671,87072,Female,Loyal Customer,51,Business travel,Business,1875,2,2,2,2,3,5,5,5,5,5,5,5,5,3,2,0.0,satisfied +16672,4500,Male,Loyal Customer,52,Business travel,Business,3814,4,4,4,4,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +16673,81382,Male,Loyal Customer,59,Business travel,Business,1013,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +16674,38043,Male,Loyal Customer,51,Business travel,Business,1237,2,2,2,2,5,5,5,5,2,4,3,5,3,5,195,180.0,satisfied +16675,106106,Female,Loyal Customer,46,Business travel,Business,2343,1,1,1,1,3,4,4,3,3,4,3,4,3,5,0,5.0,satisfied +16676,94019,Female,Loyal Customer,42,Business travel,Business,248,0,0,0,4,4,5,5,2,2,2,2,4,2,3,6,0.0,satisfied +16677,76007,Male,Loyal Customer,59,Business travel,Business,3149,1,1,1,1,1,4,3,1,1,1,1,4,1,2,3,5.0,neutral or dissatisfied +16678,40760,Male,Loyal Customer,27,Business travel,Business,588,3,3,3,3,4,4,4,4,5,1,3,3,4,4,0,0.0,satisfied +16679,80931,Female,Loyal Customer,22,Personal Travel,Eco,341,2,5,2,3,1,2,1,1,4,3,5,4,4,1,0,5.0,neutral or dissatisfied +16680,15974,Female,Loyal Customer,31,Business travel,Eco Plus,528,0,0,0,4,0,2,2,3,1,2,3,2,3,2,140,138.0,satisfied +16681,63671,Male,Loyal Customer,59,Personal Travel,Eco Plus,2405,3,1,2,3,4,2,2,4,1,4,3,4,3,4,16,4.0,neutral or dissatisfied +16682,124699,Male,Loyal Customer,39,Business travel,Business,399,3,1,1,1,4,3,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +16683,51696,Female,Loyal Customer,29,Business travel,Business,3799,1,1,5,1,5,5,5,5,3,1,1,2,4,5,0,0.0,satisfied +16684,100166,Male,Loyal Customer,56,Personal Travel,Eco,468,0,5,0,2,5,0,5,5,4,5,5,4,4,5,0,0.0,satisfied +16685,101181,Male,Loyal Customer,27,Personal Travel,Eco,1069,2,4,1,4,5,1,5,5,5,2,4,4,4,5,0,0.0,neutral or dissatisfied +16686,23290,Female,Loyal Customer,28,Business travel,Business,3952,4,4,4,4,4,4,4,4,1,3,4,4,1,4,48,32.0,satisfied +16687,84238,Female,Loyal Customer,20,Business travel,Eco Plus,432,2,1,1,1,2,2,2,2,2,2,4,4,4,2,11,18.0,neutral or dissatisfied +16688,57580,Female,Loyal Customer,43,Business travel,Business,1597,5,5,5,5,4,3,5,5,5,5,5,5,5,3,0,1.0,satisfied +16689,93770,Female,Loyal Customer,36,Business travel,Eco Plus,368,1,2,2,2,1,1,1,1,4,5,4,4,3,1,0,0.0,neutral or dissatisfied +16690,29127,Male,Loyal Customer,54,Personal Travel,Eco,679,2,5,2,4,1,2,1,1,4,3,1,5,1,1,0,2.0,neutral or dissatisfied +16691,100861,Male,Loyal Customer,68,Personal Travel,Business,1605,3,2,3,4,5,3,4,4,4,3,4,1,4,4,1,0.0,neutral or dissatisfied +16692,119078,Male,Loyal Customer,39,Business travel,Business,1750,1,1,1,1,4,5,4,5,5,4,5,4,5,4,0,0.0,satisfied +16693,29661,Male,Loyal Customer,52,Personal Travel,Eco,680,0,4,0,1,5,0,5,5,3,2,5,3,4,5,6,3.0,satisfied +16694,109610,Male,Loyal Customer,31,Personal Travel,Business,802,3,4,3,2,3,3,3,3,1,4,2,4,4,3,24,27.0,neutral or dissatisfied +16695,47746,Female,Loyal Customer,41,Business travel,Business,550,1,1,1,1,1,2,1,2,2,2,2,1,2,5,0,0.0,satisfied +16696,30203,Male,Loyal Customer,56,Business travel,Eco Plus,183,4,1,1,1,4,4,4,4,4,3,2,4,2,4,0,0.0,satisfied +16697,55716,Male,Loyal Customer,70,Personal Travel,Eco,895,2,4,2,2,5,2,5,5,5,3,4,5,4,5,0,0.0,neutral or dissatisfied +16698,53719,Male,Loyal Customer,42,Personal Travel,Eco,1208,4,1,4,2,4,4,4,4,4,3,2,4,2,4,6,0.0,neutral or dissatisfied +16699,38466,Female,Loyal Customer,46,Business travel,Business,846,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +16700,61328,Female,Loyal Customer,23,Personal Travel,Eco Plus,909,1,5,0,3,5,0,5,5,1,2,5,4,1,5,1,0.0,neutral or dissatisfied +16701,32350,Female,Loyal Customer,61,Business travel,Business,2288,2,2,3,2,4,2,1,4,4,4,4,3,4,1,0,0.0,satisfied +16702,116468,Male,Loyal Customer,65,Personal Travel,Eco,358,2,3,2,2,4,2,1,4,2,1,2,1,3,4,0,0.0,neutral or dissatisfied +16703,70893,Male,Loyal Customer,29,Business travel,Business,1721,4,4,4,4,3,3,3,3,3,3,5,4,5,3,0,0.0,satisfied +16704,7488,Female,Loyal Customer,45,Business travel,Business,3277,4,4,1,4,4,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +16705,20167,Female,Loyal Customer,35,Business travel,Business,438,4,2,2,2,1,3,4,4,4,4,4,1,4,2,80,90.0,neutral or dissatisfied +16706,37920,Female,Loyal Customer,25,Personal Travel,Eco,1023,2,2,1,3,5,1,5,5,2,2,1,4,3,5,0,6.0,neutral or dissatisfied +16707,21732,Female,Loyal Customer,52,Business travel,Business,2502,1,1,2,1,5,3,2,4,4,4,4,5,4,1,0,2.0,satisfied +16708,88186,Female,Loyal Customer,28,Business travel,Business,2503,1,1,1,1,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +16709,62704,Male,Loyal Customer,40,Business travel,Business,2449,4,4,4,4,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +16710,117727,Male,Loyal Customer,53,Business travel,Business,833,5,5,5,5,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +16711,12574,Male,Loyal Customer,57,Business travel,Business,2073,4,4,4,4,5,4,3,4,4,4,4,1,4,1,29,23.0,neutral or dissatisfied +16712,55127,Male,Loyal Customer,20,Personal Travel,Eco,1379,3,1,3,4,3,3,4,3,4,3,3,2,3,3,29,29.0,neutral or dissatisfied +16713,31299,Female,disloyal Customer,23,Business travel,Eco,680,5,5,5,2,3,5,3,3,3,2,5,4,5,3,12,11.0,satisfied +16714,72322,Male,Loyal Customer,28,Business travel,Business,2717,4,2,2,2,4,4,4,4,2,3,4,4,4,4,0,3.0,neutral or dissatisfied +16715,98895,Male,Loyal Customer,35,Business travel,Business,3229,4,4,4,4,5,5,5,2,2,2,2,4,2,5,10,6.0,satisfied +16716,110511,Female,Loyal Customer,44,Personal Travel,Eco Plus,925,1,5,1,4,3,5,4,1,1,1,1,3,1,4,10,5.0,neutral or dissatisfied +16717,49706,Male,Loyal Customer,72,Business travel,Business,110,3,3,5,3,3,5,5,3,3,4,3,3,3,2,0,0.0,satisfied +16718,93786,Male,disloyal Customer,25,Business travel,Eco,1259,3,2,2,1,4,2,4,4,3,5,5,3,5,4,11,12.0,neutral or dissatisfied +16719,75017,Male,disloyal Customer,38,Business travel,Business,236,3,3,3,3,5,3,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +16720,90044,Male,disloyal Customer,22,Business travel,Business,1127,0,0,1,2,4,1,4,4,3,3,4,4,5,4,0,0.0,satisfied +16721,55052,Male,Loyal Customer,54,Business travel,Eco,1635,1,0,0,2,4,1,4,4,3,2,1,2,2,4,11,0.0,neutral or dissatisfied +16722,129333,Male,Loyal Customer,15,Business travel,Business,2475,2,2,2,2,3,3,3,3,5,4,5,5,5,3,6,0.0,satisfied +16723,126209,Male,disloyal Customer,26,Business travel,Eco,328,4,0,4,4,5,4,4,5,3,1,4,3,3,5,5,41.0,neutral or dissatisfied +16724,95782,Female,Loyal Customer,34,Personal Travel,Eco,237,2,2,0,3,3,0,3,3,2,1,3,4,4,3,0,2.0,neutral or dissatisfied +16725,79078,Female,Loyal Customer,62,Personal Travel,Eco,356,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,1.0,neutral or dissatisfied +16726,81309,Female,Loyal Customer,51,Business travel,Business,3498,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +16727,115300,Female,Loyal Customer,47,Business travel,Business,333,5,5,3,5,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +16728,126529,Male,Loyal Customer,26,Personal Travel,Business,644,0,5,0,3,4,0,4,4,5,2,4,3,4,4,0,0.0,satisfied +16729,27478,Male,Loyal Customer,12,Business travel,Business,3481,2,2,2,2,4,4,4,4,1,5,1,4,1,4,6,0.0,satisfied +16730,60038,Male,Loyal Customer,40,Business travel,Business,3891,3,3,3,3,4,4,5,4,4,4,4,5,4,4,19,14.0,satisfied +16731,96743,Female,Loyal Customer,14,Business travel,Eco Plus,696,1,5,5,5,1,1,3,1,3,5,3,3,3,1,50,51.0,neutral or dissatisfied +16732,38581,Female,disloyal Customer,23,Business travel,Eco,1352,4,4,4,3,4,4,4,4,2,5,3,2,5,4,35,34.0,satisfied +16733,6405,Female,Loyal Customer,37,Personal Travel,Eco,213,4,0,4,3,5,4,5,5,4,3,4,3,5,5,0,0.0,satisfied +16734,49427,Male,disloyal Customer,41,Business travel,Eco,373,3,5,3,4,5,3,5,5,4,2,5,1,5,5,24,29.0,neutral or dissatisfied +16735,20525,Female,disloyal Customer,35,Business travel,Eco,533,3,5,3,3,1,3,1,1,5,4,4,3,4,1,0,0.0,neutral or dissatisfied +16736,96365,Male,Loyal Customer,7,Personal Travel,Business,1342,2,4,2,4,2,2,4,2,5,2,4,4,3,2,0,15.0,neutral or dissatisfied +16737,79652,Female,disloyal Customer,65,Business travel,Eco,362,4,3,4,3,2,4,2,2,3,3,3,2,1,2,60,46.0,neutral or dissatisfied +16738,64477,Male,disloyal Customer,13,Business travel,Eco,551,5,5,5,3,5,5,1,5,5,5,5,5,4,5,0,0.0,satisfied +16739,44664,Male,Loyal Customer,33,Business travel,Eco,268,4,5,5,5,4,4,4,4,1,4,5,2,4,4,0,0.0,satisfied +16740,72192,Male,Loyal Customer,41,Business travel,Eco,594,4,4,2,4,3,4,3,3,2,3,3,5,4,3,86,92.0,satisfied +16741,68108,Male,Loyal Customer,19,Personal Travel,Eco,868,0,3,0,3,4,0,4,4,4,1,2,1,3,4,3,3.0,satisfied +16742,25479,Female,Loyal Customer,57,Business travel,Eco,481,4,1,1,1,4,2,2,4,4,4,4,1,4,5,0,0.0,satisfied +16743,67071,Male,Loyal Customer,26,Business travel,Business,2628,3,3,3,3,5,5,5,5,4,3,5,4,4,5,10,5.0,satisfied +16744,70639,Female,Loyal Customer,46,Business travel,Business,946,1,1,1,1,4,4,5,5,5,5,5,4,5,4,0,6.0,satisfied +16745,50186,Male,disloyal Customer,54,Business travel,Eco,109,3,0,3,1,3,3,3,3,5,1,4,1,2,3,0,0.0,neutral or dissatisfied +16746,56014,Male,Loyal Customer,49,Business travel,Business,2475,4,4,5,4,4,4,4,5,3,4,5,4,4,4,0,0.0,satisfied +16747,124444,Female,disloyal Customer,34,Business travel,Business,980,1,1,1,2,1,2,2,4,4,4,4,2,4,2,163,186.0,neutral or dissatisfied +16748,35897,Male,Loyal Customer,45,Business travel,Eco Plus,1068,5,2,2,2,5,5,5,1,3,1,4,5,3,5,135,140.0,satisfied +16749,98796,Female,Loyal Customer,58,Personal Travel,Eco,630,3,3,3,5,2,4,5,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +16750,110533,Female,disloyal Customer,15,Business travel,Business,488,4,0,5,1,5,5,4,5,4,2,5,3,4,5,53,49.0,satisfied +16751,53659,Male,Loyal Customer,57,Business travel,Business,3964,1,1,1,1,4,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +16752,41740,Female,Loyal Customer,31,Personal Travel,Eco,695,2,3,2,1,2,2,2,2,4,5,1,2,1,2,0,0.0,neutral or dissatisfied +16753,79309,Male,Loyal Customer,30,Personal Travel,Eco,2248,2,4,2,1,1,2,1,1,4,3,3,5,4,1,0,0.0,neutral or dissatisfied +16754,7049,Female,Loyal Customer,45,Business travel,Business,157,1,1,1,1,3,5,5,5,5,5,5,5,5,3,33,26.0,satisfied +16755,98594,Male,Loyal Customer,51,Business travel,Business,966,1,1,1,1,3,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +16756,128692,Female,disloyal Customer,24,Business travel,Eco Plus,2419,3,1,3,3,3,5,5,1,3,4,4,5,4,5,0,13.0,neutral or dissatisfied +16757,68460,Female,Loyal Customer,47,Business travel,Business,3345,3,3,3,3,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +16758,104815,Male,Loyal Customer,47,Personal Travel,Eco,587,4,4,4,1,4,4,4,4,3,5,5,3,5,4,20,8.0,neutral or dissatisfied +16759,99086,Male,Loyal Customer,46,Business travel,Business,2004,3,3,3,3,5,4,5,4,4,4,4,4,4,5,0,1.0,satisfied +16760,118623,Male,Loyal Customer,60,Business travel,Eco,338,1,3,3,3,1,1,1,1,1,2,2,2,3,1,0,0.0,neutral or dissatisfied +16761,124042,Female,disloyal Customer,21,Business travel,Business,184,4,4,4,3,4,4,5,4,4,2,5,4,5,4,50,42.0,satisfied +16762,93128,Male,disloyal Customer,21,Business travel,Business,1075,4,0,4,4,4,2,2,5,3,4,5,2,4,2,204,218.0,satisfied +16763,108570,Male,disloyal Customer,20,Business travel,Eco,696,3,3,3,4,3,3,3,3,4,4,3,2,4,3,0,16.0,neutral or dissatisfied +16764,65295,Male,Loyal Customer,61,Personal Travel,Eco Plus,551,3,3,4,4,4,4,4,4,2,1,4,2,3,4,29,21.0,neutral or dissatisfied +16765,44346,Female,Loyal Customer,43,Business travel,Business,308,5,5,3,5,3,4,5,5,5,4,5,5,5,1,0,0.0,satisfied +16766,13801,Female,Loyal Customer,30,Personal Travel,Eco,450,2,5,2,3,4,2,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +16767,54125,Male,Loyal Customer,38,Business travel,Business,1400,5,5,5,5,1,5,3,5,5,5,5,4,5,1,7,0.0,satisfied +16768,43530,Male,Loyal Customer,45,Business travel,Eco,920,5,1,1,1,5,5,5,5,3,3,1,2,5,5,5,0.0,satisfied +16769,86678,Male,Loyal Customer,31,Business travel,Eco Plus,952,2,1,1,1,2,2,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +16770,38696,Female,Loyal Customer,50,Business travel,Eco,2583,4,3,3,3,2,4,2,4,4,4,4,1,4,2,3,0.0,satisfied +16771,9200,Female,Loyal Customer,52,Business travel,Business,227,1,1,1,1,4,5,5,5,5,5,5,5,5,5,5,3.0,satisfied +16772,7251,Male,Loyal Customer,45,Personal Travel,Eco,139,4,2,4,3,1,4,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +16773,75771,Male,Loyal Customer,61,Personal Travel,Eco,813,4,1,4,3,1,4,1,1,2,3,3,4,3,1,6,0.0,neutral or dissatisfied +16774,93502,Female,Loyal Customer,33,Personal Travel,Eco,1107,3,5,2,2,4,2,4,4,3,4,1,5,5,4,3,4.0,neutral or dissatisfied +16775,38167,Male,Loyal Customer,49,Personal Travel,Eco,1249,2,5,2,3,3,2,3,3,3,2,3,3,4,3,41,20.0,neutral or dissatisfied +16776,104215,Female,Loyal Customer,47,Business travel,Business,680,2,2,2,2,4,5,5,4,4,4,4,4,4,3,57,42.0,satisfied +16777,78617,Male,disloyal Customer,49,Business travel,Business,1426,3,3,3,3,1,3,1,1,5,5,5,5,5,1,0,4.0,neutral or dissatisfied +16778,29158,Female,disloyal Customer,30,Business travel,Eco Plus,954,2,2,2,2,3,2,3,3,2,1,2,3,2,3,4,21.0,neutral or dissatisfied +16779,92361,Female,Loyal Customer,43,Business travel,Business,1919,3,3,3,3,4,4,5,4,4,5,4,3,4,4,16,0.0,satisfied +16780,85969,Female,disloyal Customer,26,Business travel,Business,447,2,0,2,4,1,2,1,1,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +16781,44501,Female,Loyal Customer,52,Business travel,Business,2841,1,1,1,1,2,1,2,5,5,5,5,2,5,3,1,3.0,satisfied +16782,112822,Male,disloyal Customer,33,Business travel,Business,715,3,3,3,4,4,3,1,4,3,2,4,5,4,4,34,18.0,neutral or dissatisfied +16783,34903,Male,Loyal Customer,41,Business travel,Business,2510,1,1,1,1,5,5,4,5,5,5,4,1,5,3,114,111.0,satisfied +16784,98209,Female,Loyal Customer,43,Business travel,Business,3307,4,4,4,4,5,5,5,5,5,5,5,3,5,3,0,7.0,satisfied +16785,87454,Male,Loyal Customer,43,Business travel,Business,2138,2,2,2,2,3,5,4,4,4,4,4,3,4,3,15,17.0,satisfied +16786,66536,Female,Loyal Customer,19,Personal Travel,Eco,733,2,4,2,4,2,2,2,2,2,4,2,1,3,2,1,0.0,neutral or dissatisfied +16787,62829,Female,Loyal Customer,58,Personal Travel,Eco,2338,3,5,3,5,4,3,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +16788,93198,Male,disloyal Customer,37,Business travel,Business,896,1,2,2,3,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +16789,2059,Male,Loyal Customer,30,Business travel,Business,2469,2,2,2,2,2,3,2,2,2,5,4,4,3,2,0,0.0,neutral or dissatisfied +16790,117837,Female,Loyal Customer,25,Business travel,Business,1697,3,3,5,3,5,5,5,5,4,5,5,4,5,5,23,25.0,satisfied +16791,84021,Male,Loyal Customer,41,Personal Travel,Eco,373,3,5,3,4,1,3,1,1,4,2,2,2,5,1,0,0.0,neutral or dissatisfied +16792,9384,Female,Loyal Customer,42,Personal Travel,Eco,441,2,4,2,2,2,5,4,5,5,2,5,3,5,5,13,12.0,neutral or dissatisfied +16793,29428,Female,Loyal Customer,27,Business travel,Eco,2149,3,3,2,3,3,4,3,3,1,2,3,5,5,3,0,0.0,satisfied +16794,46192,Female,Loyal Customer,41,Business travel,Business,472,1,1,1,1,1,5,2,3,3,2,3,5,3,3,0,0.0,satisfied +16795,56477,Male,Loyal Customer,57,Business travel,Business,4963,4,4,4,4,3,3,3,5,3,4,4,3,4,3,4,13.0,satisfied +16796,105538,Female,Loyal Customer,46,Business travel,Business,611,3,2,4,2,3,3,3,1,3,4,3,3,4,3,140,127.0,neutral or dissatisfied +16797,21692,Male,Loyal Customer,78,Business travel,Business,2842,3,3,3,3,1,4,3,3,3,3,3,1,3,4,12,1.0,neutral or dissatisfied +16798,114595,Male,disloyal Customer,44,Business travel,Business,308,4,4,4,1,4,4,4,4,3,2,4,5,5,4,18,17.0,neutral or dissatisfied +16799,107567,Female,Loyal Customer,41,Personal Travel,Eco,1521,4,4,4,2,1,4,1,1,5,1,4,2,2,1,0,0.0,satisfied +16800,58766,Female,Loyal Customer,40,Business travel,Business,2597,3,3,3,3,3,5,5,5,5,5,5,4,5,4,20,23.0,satisfied +16801,110656,Male,Loyal Customer,36,Business travel,Business,1005,2,1,1,1,2,3,4,2,2,2,2,4,2,1,27,28.0,neutral or dissatisfied +16802,12843,Female,Loyal Customer,47,Personal Travel,Eco,641,1,3,1,4,2,4,4,2,2,1,2,2,2,1,12,0.0,neutral or dissatisfied +16803,45196,Male,disloyal Customer,25,Business travel,Eco,606,5,4,5,2,4,5,4,4,1,4,4,1,1,4,0,0.0,satisfied +16804,115917,Male,disloyal Customer,37,Business travel,Eco,404,1,3,1,5,1,1,1,1,3,5,4,5,2,1,0,0.0,neutral or dissatisfied +16805,9715,Female,Loyal Customer,58,Personal Travel,Eco,277,3,3,3,3,1,2,2,3,3,3,3,3,3,4,51,61.0,neutral or dissatisfied +16806,3354,Male,Loyal Customer,41,Business travel,Business,296,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,11.0,satisfied +16807,34207,Female,Loyal Customer,32,Personal Travel,Eco,1046,1,3,1,3,5,1,5,5,2,1,4,2,4,5,3,1.0,neutral or dissatisfied +16808,114257,Female,Loyal Customer,47,Business travel,Eco,462,4,3,3,3,5,4,3,5,5,4,5,4,5,3,26,6.0,neutral or dissatisfied +16809,28867,Female,Loyal Customer,25,Business travel,Business,954,4,4,3,4,3,3,3,3,2,1,1,1,2,3,0,0.0,satisfied +16810,38105,Female,Loyal Customer,43,Business travel,Eco,1197,1,1,1,1,4,4,4,1,1,1,1,4,1,1,12,6.0,neutral or dissatisfied +16811,52559,Female,Loyal Customer,56,Business travel,Business,119,1,1,1,1,5,4,1,4,4,4,5,3,4,2,0,0.0,satisfied +16812,77650,Female,Loyal Customer,41,Business travel,Business,689,4,4,4,4,5,5,5,4,4,4,4,5,4,5,0,4.0,satisfied +16813,124236,Male,Loyal Customer,39,Business travel,Business,1916,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,9.0,satisfied +16814,9804,Female,Loyal Customer,32,Business travel,Business,2089,5,5,5,5,4,4,4,4,4,2,4,4,5,4,4,15.0,satisfied +16815,119129,Female,Loyal Customer,15,Personal Travel,Eco Plus,1107,1,1,1,4,5,1,5,5,2,5,4,3,3,5,6,0.0,neutral or dissatisfied +16816,74828,Male,Loyal Customer,29,Personal Travel,Eco Plus,1235,1,5,1,1,2,1,3,2,2,2,3,5,5,2,0,0.0,neutral or dissatisfied +16817,53420,Male,disloyal Customer,25,Business travel,Eco,2442,5,5,5,5,4,5,4,4,2,3,4,3,4,4,44,39.0,satisfied +16818,28556,Female,Loyal Customer,20,Personal Travel,Eco,2701,1,4,1,3,2,1,2,2,4,5,4,5,4,2,17,0.0,neutral or dissatisfied +16819,8950,Male,Loyal Customer,23,Personal Travel,Eco,328,1,1,1,2,3,1,3,3,4,3,2,1,3,3,22,55.0,neutral or dissatisfied +16820,120349,Male,Loyal Customer,56,Personal Travel,Business,449,5,4,5,4,5,5,5,2,2,5,2,4,2,5,9,0.0,satisfied +16821,56831,Male,Loyal Customer,64,Personal Travel,Eco,1605,1,5,1,4,2,1,5,2,3,4,3,4,5,2,15,8.0,neutral or dissatisfied +16822,128628,Female,disloyal Customer,24,Business travel,Eco,554,0,0,0,4,5,0,5,5,1,5,1,1,3,5,0,0.0,satisfied +16823,100552,Male,Loyal Customer,16,Personal Travel,Eco Plus,580,3,4,3,4,4,3,4,4,3,5,4,4,4,4,25,20.0,neutral or dissatisfied +16824,121600,Female,Loyal Customer,51,Personal Travel,Eco,936,4,4,4,1,5,5,3,3,3,4,3,1,3,1,88,71.0,neutral or dissatisfied +16825,80103,Male,Loyal Customer,60,Business travel,Business,1620,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +16826,31525,Male,Loyal Customer,61,Business travel,Eco,462,3,2,2,2,3,3,3,3,2,3,4,1,4,3,2,16.0,satisfied +16827,107692,Female,disloyal Customer,24,Business travel,Eco,405,4,0,4,5,2,4,5,2,4,3,5,5,4,2,0,0.0,satisfied +16828,74355,Male,Loyal Customer,32,Business travel,Business,3395,5,5,5,5,3,2,3,3,3,2,5,5,5,3,0,0.0,satisfied +16829,114430,Female,Loyal Customer,49,Business travel,Business,3471,2,3,3,3,5,2,1,2,2,2,2,3,2,3,56,47.0,neutral or dissatisfied +16830,128866,Female,Loyal Customer,55,Business travel,Business,2454,3,4,3,3,5,5,5,5,2,4,4,5,5,5,0,0.0,satisfied +16831,83932,Female,Loyal Customer,43,Business travel,Business,4000,2,2,2,2,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +16832,47990,Female,Loyal Customer,37,Business travel,Eco Plus,817,4,5,5,5,5,4,4,4,2,2,3,4,5,4,213,204.0,satisfied +16833,52761,Female,Loyal Customer,48,Business travel,Eco,1874,1,1,1,1,3,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +16834,111709,Female,Loyal Customer,27,Business travel,Business,2553,4,4,4,4,4,4,4,4,3,1,2,3,3,4,49,38.0,neutral or dissatisfied +16835,22734,Male,disloyal Customer,37,Business travel,Eco,147,2,0,2,2,4,2,3,4,2,3,4,2,1,4,0,0.0,neutral or dissatisfied +16836,60558,Female,Loyal Customer,38,Business travel,Eco Plus,241,5,2,2,2,5,5,5,5,3,3,3,4,1,5,0,24.0,satisfied +16837,90966,Female,Loyal Customer,18,Business travel,Business,3515,1,1,1,1,3,3,3,3,2,4,2,2,5,3,0,0.0,satisfied +16838,93297,Male,Loyal Customer,38,Business travel,Eco Plus,867,2,5,5,5,2,2,2,2,2,1,4,4,4,2,59,54.0,neutral or dissatisfied +16839,129529,Male,Loyal Customer,44,Business travel,Business,2583,4,4,4,4,4,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +16840,66010,Male,Loyal Customer,56,Business travel,Business,3501,5,5,2,5,4,4,4,5,5,4,5,4,4,4,283,317.0,satisfied +16841,82654,Female,Loyal Customer,54,Business travel,Business,3015,3,3,3,3,4,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +16842,83672,Female,disloyal Customer,34,Business travel,Eco,577,2,2,2,4,5,2,5,5,1,4,3,2,4,5,0,0.0,neutral or dissatisfied +16843,92343,Male,Loyal Customer,45,Business travel,Eco,2556,4,2,2,2,4,4,4,2,3,3,3,4,1,4,0,19.0,neutral or dissatisfied +16844,128999,Female,Loyal Customer,40,Business travel,Business,2704,5,5,5,5,5,4,4,5,2,3,5,4,4,4,0,0.0,satisfied +16845,25330,Female,Loyal Customer,30,Business travel,Business,3539,3,3,2,3,5,5,5,5,5,4,3,2,4,5,0,0.0,satisfied +16846,14814,Female,Loyal Customer,51,Personal Travel,Eco,95,2,4,2,2,4,4,4,5,5,2,5,5,5,1,1,0.0,neutral or dissatisfied +16847,101184,Male,Loyal Customer,49,Personal Travel,Eco,775,2,5,2,2,4,2,4,4,5,5,1,3,2,4,18,5.0,neutral or dissatisfied +16848,110196,Female,Loyal Customer,49,Business travel,Business,1072,2,2,4,2,2,4,5,4,4,4,4,4,4,4,11,4.0,satisfied +16849,85036,Female,disloyal Customer,13,Business travel,Eco,1126,4,4,4,4,2,4,2,2,2,4,3,4,4,2,26,21.0,neutral or dissatisfied +16850,94671,Female,Loyal Customer,44,Business travel,Business,2692,0,0,0,4,3,5,5,1,1,1,1,5,1,5,3,2.0,satisfied +16851,73949,Female,Loyal Customer,48,Business travel,Eco,718,2,2,2,2,2,2,1,2,2,2,2,3,2,1,10,0.0,neutral or dissatisfied +16852,52347,Male,Loyal Customer,48,Business travel,Business,455,2,2,2,2,1,2,3,5,5,5,5,3,5,4,0,0.0,satisfied +16853,95950,Male,Loyal Customer,57,Business travel,Business,2449,4,4,4,4,2,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +16854,72614,Male,Loyal Customer,51,Personal Travel,Eco,918,3,5,3,5,3,3,3,3,3,4,4,3,5,3,0,0.0,neutral or dissatisfied +16855,107289,Male,Loyal Customer,65,Business travel,Business,307,4,4,4,4,2,2,3,4,4,4,4,2,4,2,0,0.0,neutral or dissatisfied +16856,129559,Female,Loyal Customer,58,Personal Travel,Eco,2342,4,0,4,4,4,5,5,3,3,4,3,3,3,4,0,0.0,neutral or dissatisfied +16857,93263,Female,Loyal Customer,49,Business travel,Business,867,2,2,2,2,2,4,4,5,5,5,5,3,5,3,5,0.0,satisfied +16858,123105,Male,disloyal Customer,20,Business travel,Eco,590,3,1,3,2,1,3,1,1,1,4,2,1,3,1,0,0.0,neutral or dissatisfied +16859,97357,Male,Loyal Customer,50,Business travel,Business,443,2,2,2,2,4,1,3,4,4,5,4,1,4,3,0,1.0,satisfied +16860,16931,Female,Loyal Customer,41,Business travel,Eco,820,4,5,5,5,3,4,3,3,4,1,1,3,1,3,0,10.0,satisfied +16861,117312,Male,Loyal Customer,37,Personal Travel,Eco Plus,325,0,4,0,4,5,0,5,5,4,3,1,4,3,5,3,0.0,satisfied +16862,30999,Female,Loyal Customer,41,Business travel,Business,2499,1,1,5,1,2,4,1,4,4,4,4,1,4,3,38,45.0,satisfied +16863,10123,Female,disloyal Customer,23,Business travel,Eco,984,3,3,3,3,5,3,4,5,1,4,2,3,3,5,0,0.0,neutral or dissatisfied +16864,64536,Female,Loyal Customer,45,Business travel,Business,469,4,4,4,4,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +16865,24873,Male,Loyal Customer,67,Personal Travel,Eco,356,2,3,2,4,1,2,1,1,1,3,4,4,3,1,0,0.0,neutral or dissatisfied +16866,77336,Male,Loyal Customer,46,Business travel,Business,1960,2,2,2,2,3,5,4,4,4,4,4,4,4,3,39,37.0,satisfied +16867,112840,Male,disloyal Customer,27,Business travel,Business,1211,3,3,3,5,5,3,5,5,5,2,5,3,4,5,33,25.0,neutral or dissatisfied +16868,71382,Female,Loyal Customer,19,Personal Travel,Eco,258,3,2,0,4,3,0,3,3,1,2,4,4,4,3,0,0.0,neutral or dissatisfied +16869,3125,Male,Loyal Customer,10,Personal Travel,Eco,1013,3,2,3,3,2,3,2,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +16870,21469,Male,Loyal Customer,50,Business travel,Eco,164,4,3,3,3,5,4,5,5,2,4,4,1,4,5,3,0.0,neutral or dissatisfied +16871,76224,Female,Loyal Customer,35,Business travel,Eco,1175,1,1,1,1,1,1,1,1,1,4,4,2,4,1,0,6.0,neutral or dissatisfied +16872,4164,Female,Loyal Customer,12,Personal Travel,Eco,427,5,2,5,4,1,5,1,1,3,2,3,3,4,1,0,16.0,satisfied +16873,115402,Male,Loyal Customer,34,Business travel,Business,2581,4,4,4,4,5,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +16874,12614,Male,Loyal Customer,38,Business travel,Business,802,5,5,5,5,5,3,1,5,5,5,5,5,5,1,0,24.0,satisfied +16875,104844,Male,Loyal Customer,17,Personal Travel,Eco,472,3,3,3,3,4,3,4,4,1,2,3,3,3,4,1,0.0,neutral or dissatisfied +16876,102658,Male,Loyal Customer,31,Business travel,Business,255,2,2,2,2,5,5,5,5,3,3,4,3,5,5,7,0.0,satisfied +16877,88076,Male,Loyal Customer,50,Business travel,Business,1677,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16878,68549,Female,Loyal Customer,36,Personal Travel,Eco,1013,4,2,5,3,5,5,5,5,1,1,3,4,4,5,0,0.0,neutral or dissatisfied +16879,118061,Female,Loyal Customer,50,Business travel,Eco,862,5,2,2,2,5,5,5,1,1,1,5,5,1,5,124,134.0,satisfied +16880,98124,Male,Loyal Customer,60,Personal Travel,Eco,426,2,4,4,5,2,4,2,2,4,3,5,3,5,2,0,0.0,neutral or dissatisfied +16881,38494,Male,Loyal Customer,40,Business travel,Eco,2586,4,5,5,5,4,4,4,4,2,1,4,5,4,4,0,0.0,satisfied +16882,87645,Female,Loyal Customer,25,Business travel,Business,606,1,1,1,1,5,5,5,5,5,3,5,3,4,5,3,19.0,satisfied +16883,117723,Male,disloyal Customer,39,Business travel,Business,935,3,3,3,2,3,3,3,3,5,5,5,3,5,3,6,0.0,neutral or dissatisfied +16884,117877,Male,disloyal Customer,23,Business travel,Business,255,5,4,5,3,1,5,1,1,5,5,5,5,5,1,0,0.0,satisfied +16885,7571,Female,Loyal Customer,52,Business travel,Business,594,3,2,2,2,2,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +16886,25642,Female,Loyal Customer,47,Personal Travel,Eco,526,1,5,1,4,5,5,4,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +16887,73159,Female,Loyal Customer,39,Business travel,Business,1145,2,2,3,2,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +16888,24381,Male,disloyal Customer,28,Business travel,Eco,669,3,3,3,3,3,3,4,3,2,1,3,1,3,3,0,0.0,neutral or dissatisfied +16889,112602,Male,disloyal Customer,25,Business travel,Eco,639,2,2,2,4,4,2,4,4,1,3,3,3,4,4,4,30.0,neutral or dissatisfied +16890,18063,Female,Loyal Customer,40,Business travel,Business,3478,2,5,5,5,3,4,4,2,2,2,2,2,2,2,76,60.0,neutral or dissatisfied +16891,60712,Male,disloyal Customer,25,Business travel,Eco,1605,2,2,2,2,5,2,5,5,3,4,2,4,3,5,23,5.0,neutral or dissatisfied +16892,15392,Female,Loyal Customer,39,Business travel,Eco,433,3,5,5,5,3,3,3,3,3,3,4,2,3,3,49,38.0,neutral or dissatisfied +16893,129726,Female,disloyal Customer,21,Business travel,Eco,447,5,5,5,2,3,5,3,3,4,5,4,4,4,3,0,0.0,satisfied +16894,27157,Male,Loyal Customer,40,Business travel,Eco,2701,2,1,1,1,2,2,2,4,4,2,4,2,3,2,0,0.0,neutral or dissatisfied +16895,31212,Male,Loyal Customer,54,Personal Travel,Eco,628,1,5,1,2,5,1,1,5,5,5,5,4,5,5,27,20.0,neutral or dissatisfied +16896,43390,Female,Loyal Customer,36,Personal Travel,Eco,387,2,4,2,2,3,2,3,3,5,2,4,3,5,3,0,0.0,neutral or dissatisfied +16897,86430,Male,disloyal Customer,24,Business travel,Eco,762,4,4,4,3,3,4,3,3,1,5,3,1,4,3,0,6.0,neutral or dissatisfied +16898,108822,Male,Loyal Customer,12,Personal Travel,Business,1199,2,5,2,1,5,2,5,5,3,1,5,1,4,5,0,7.0,neutral or dissatisfied +16899,66895,Male,Loyal Customer,21,Business travel,Business,3004,5,5,5,5,5,5,5,5,3,3,5,3,4,5,0,0.0,satisfied +16900,28765,Female,Loyal Customer,21,Personal Travel,Eco,1024,4,4,4,3,4,4,4,4,3,4,4,5,4,4,0,0.0,neutral or dissatisfied +16901,96265,Male,Loyal Customer,68,Personal Travel,Eco,666,2,4,2,1,4,2,4,4,5,5,4,3,5,4,12,8.0,neutral or dissatisfied +16902,67115,Female,Loyal Customer,25,Business travel,Business,3371,3,5,5,5,3,3,3,3,2,4,4,4,3,3,2,36.0,neutral or dissatisfied +16903,15209,Male,Loyal Customer,45,Business travel,Eco,445,4,4,4,4,4,4,4,4,2,3,1,4,2,4,0,0.0,satisfied +16904,2330,Female,Loyal Customer,27,Personal Travel,Eco,691,2,3,2,4,5,2,5,5,2,2,3,2,4,5,76,84.0,neutral or dissatisfied +16905,125723,Female,Loyal Customer,67,Personal Travel,Eco,759,2,3,2,3,4,3,3,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +16906,74517,Male,Loyal Customer,18,Business travel,Business,1464,3,3,3,3,4,4,4,4,4,4,5,4,5,4,4,0.0,satisfied +16907,22035,Female,Loyal Customer,53,Personal Travel,Eco Plus,551,2,1,1,3,1,3,4,4,4,1,4,3,4,1,0,0.0,neutral or dissatisfied +16908,25211,Female,Loyal Customer,35,Business travel,Eco,925,4,2,2,2,4,4,4,4,5,1,4,4,1,4,34,9.0,satisfied +16909,63631,Female,disloyal Customer,43,Business travel,Business,602,3,3,3,5,4,3,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +16910,16004,Female,disloyal Customer,29,Business travel,Eco,780,2,2,2,3,2,3,3,3,5,3,2,3,1,3,172,192.0,neutral or dissatisfied +16911,88856,Female,disloyal Customer,26,Business travel,Business,581,3,5,3,2,5,3,4,5,4,4,5,3,5,5,70,75.0,neutral or dissatisfied +16912,113480,Female,disloyal Customer,25,Business travel,Business,236,4,0,4,2,3,4,3,3,5,5,5,3,4,3,4,0.0,neutral or dissatisfied +16913,37783,Male,Loyal Customer,43,Business travel,Eco Plus,1035,4,4,4,4,4,4,4,4,5,5,4,2,2,4,29,17.0,satisfied +16914,34529,Male,Loyal Customer,28,Business travel,Eco,636,4,2,4,4,4,4,4,4,1,4,3,4,3,4,0,0.0,satisfied +16915,74074,Male,Loyal Customer,32,Business travel,Business,2739,1,5,1,1,4,4,4,4,5,5,5,4,5,4,338,316.0,satisfied +16916,84937,Female,Loyal Customer,37,Personal Travel,Eco,547,3,1,4,4,3,4,3,3,4,4,3,2,3,3,5,2.0,neutral or dissatisfied +16917,126208,Male,Loyal Customer,29,Business travel,Eco,547,2,5,5,5,2,2,2,2,4,1,4,1,3,2,23,12.0,neutral or dissatisfied +16918,78237,Male,Loyal Customer,50,Business travel,Business,259,2,2,2,2,4,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +16919,79709,Male,Loyal Customer,57,Personal Travel,Eco,760,4,5,4,2,1,4,1,1,5,4,5,5,4,1,0,0.0,neutral or dissatisfied +16920,129355,Male,Loyal Customer,39,Business travel,Business,2475,1,1,2,1,2,4,4,4,4,4,4,3,4,5,25,13.0,satisfied +16921,112157,Female,Loyal Customer,57,Business travel,Business,3897,2,1,1,1,3,3,3,2,2,2,2,3,2,3,17,10.0,neutral or dissatisfied +16922,99973,Male,Loyal Customer,44,Business travel,Business,2744,4,4,4,4,4,4,4,4,4,4,5,4,5,4,342,336.0,satisfied +16923,71093,Female,Loyal Customer,28,Business travel,Eco Plus,802,2,2,2,2,2,2,2,2,1,2,2,2,3,2,26,28.0,neutral or dissatisfied +16924,83137,Female,Loyal Customer,52,Personal Travel,Eco,1145,2,5,2,3,2,5,4,2,2,2,2,3,2,3,27,97.0,neutral or dissatisfied +16925,102859,Female,disloyal Customer,37,Business travel,Business,423,4,4,4,2,5,4,5,5,5,2,5,4,5,5,0,0.0,satisfied +16926,117229,Male,Loyal Customer,33,Personal Travel,Eco,370,3,3,3,3,1,3,1,1,1,3,3,1,2,1,14,18.0,neutral or dissatisfied +16927,40289,Male,Loyal Customer,40,Personal Travel,Eco,531,3,5,3,5,2,3,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +16928,52588,Female,Loyal Customer,62,Business travel,Eco,119,2,1,1,1,3,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +16929,91203,Male,Loyal Customer,67,Personal Travel,Eco,270,3,0,3,2,3,3,4,3,5,4,3,4,3,3,0,0.0,neutral or dissatisfied +16930,87701,Male,Loyal Customer,64,Personal Travel,Eco,591,2,4,2,5,2,2,5,2,4,5,4,4,5,2,0,0.0,neutral or dissatisfied +16931,92719,Female,disloyal Customer,36,Business travel,Business,876,3,3,3,4,4,3,4,4,2,2,4,4,4,4,29,6.0,neutral or dissatisfied +16932,59109,Female,Loyal Customer,32,Personal Travel,Eco,1744,3,2,2,2,2,2,2,2,2,2,1,2,3,2,2,3.0,neutral or dissatisfied +16933,90773,Male,Loyal Customer,48,Business travel,Business,2889,5,5,2,5,4,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +16934,22623,Male,Loyal Customer,23,Personal Travel,Eco,646,2,3,1,4,1,1,1,1,4,5,3,3,3,1,12,5.0,neutral or dissatisfied +16935,90460,Male,Loyal Customer,34,Business travel,Business,2500,5,3,5,5,3,5,5,4,4,5,4,5,4,5,0,0.0,satisfied +16936,65930,Female,Loyal Customer,40,Personal Travel,Eco,569,3,2,3,2,2,3,2,2,3,4,3,2,2,2,0,0.0,neutral or dissatisfied +16937,120775,Female,Loyal Customer,29,Personal Travel,Eco,678,3,5,3,2,3,3,3,3,4,3,5,4,4,3,0,0.0,neutral or dissatisfied +16938,91283,Female,Loyal Customer,22,Business travel,Business,2160,1,1,2,1,5,5,5,5,5,2,5,4,4,5,0,47.0,satisfied +16939,27638,Female,Loyal Customer,37,Business travel,Eco Plus,279,5,4,1,1,5,5,5,5,5,3,4,1,2,5,14,,satisfied +16940,55461,Male,Loyal Customer,38,Personal Travel,Business,1825,1,5,1,4,2,5,5,5,5,1,5,4,5,5,0,0.0,neutral or dissatisfied +16941,109163,Female,Loyal Customer,31,Business travel,Business,3350,1,1,1,1,4,4,4,4,4,2,4,4,4,4,0,5.0,satisfied +16942,14876,Female,disloyal Customer,27,Business travel,Eco,343,3,4,3,4,3,3,4,3,3,2,4,1,3,3,0,2.0,neutral or dissatisfied +16943,126469,Female,Loyal Customer,51,Business travel,Business,1849,4,4,4,4,5,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +16944,119418,Male,Loyal Customer,73,Business travel,Business,399,5,5,5,5,4,4,4,4,4,4,4,4,4,1,0,0.0,satisfied +16945,106330,Male,disloyal Customer,39,Business travel,Eco,425,5,0,5,3,4,5,4,4,4,3,4,2,1,4,44,41.0,satisfied +16946,113452,Female,Loyal Customer,41,Business travel,Business,2888,2,5,2,2,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16947,5425,Female,Loyal Customer,56,Business travel,Business,3668,5,5,5,5,5,5,5,4,4,4,4,4,4,3,0,9.0,satisfied +16948,78993,Male,Loyal Customer,49,Business travel,Business,356,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,8.0,satisfied +16949,27148,Female,Loyal Customer,59,Business travel,Business,2640,2,4,4,4,2,2,2,4,2,2,2,2,3,2,0,0.0,neutral or dissatisfied +16950,34557,Male,Loyal Customer,42,Business travel,Business,1598,3,3,5,3,2,4,5,2,2,2,2,5,2,1,0,0.0,satisfied +16951,30173,Male,Loyal Customer,59,Personal Travel,Eco,373,4,5,4,3,5,4,5,5,5,1,5,5,4,5,0,0.0,neutral or dissatisfied +16952,99219,Male,Loyal Customer,39,Business travel,Business,495,3,3,3,3,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +16953,24763,Female,disloyal Customer,16,Business travel,Eco,528,5,0,5,4,2,5,2,2,5,1,2,3,1,2,0,9.0,satisfied +16954,41946,Female,Loyal Customer,50,Business travel,Business,125,4,4,4,4,4,4,4,5,5,5,4,4,5,3,0,0.0,satisfied +16955,88539,Female,Loyal Customer,15,Personal Travel,Eco,406,4,5,4,1,2,4,1,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +16956,4420,Male,disloyal Customer,22,Business travel,Eco,762,0,0,0,1,4,0,4,4,5,4,5,3,5,4,0,0.0,satisfied +16957,56747,Male,Loyal Customer,31,Business travel,Business,1085,3,3,3,3,4,3,4,4,3,3,5,3,5,4,3,0.0,satisfied +16958,110653,Male,Loyal Customer,43,Business travel,Business,945,3,3,3,3,5,5,5,5,5,4,5,5,5,3,11,13.0,satisfied +16959,2096,Male,Loyal Customer,56,Personal Travel,Eco,733,2,1,1,4,2,1,3,2,4,4,4,4,3,2,0,3.0,neutral or dissatisfied +16960,101962,Male,Loyal Customer,18,Business travel,Business,3108,3,5,5,5,3,3,3,3,2,4,4,2,3,3,4,0.0,neutral or dissatisfied +16961,124553,Male,Loyal Customer,61,Personal Travel,Eco Plus,1276,1,3,0,3,3,0,3,3,2,2,2,2,3,3,1,15.0,neutral or dissatisfied +16962,24451,Female,Loyal Customer,28,Business travel,Eco,547,0,0,0,1,1,0,1,1,3,1,1,4,5,1,0,0.0,satisfied +16963,61041,Female,disloyal Customer,22,Business travel,Eco,1117,3,3,3,3,2,3,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +16964,47187,Female,disloyal Customer,36,Business travel,Eco,748,1,1,1,1,2,1,2,2,5,1,4,2,5,2,0,0.0,neutral or dissatisfied +16965,82686,Female,Loyal Customer,72,Business travel,Business,1934,5,5,5,5,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +16966,105853,Male,Loyal Customer,52,Business travel,Eco Plus,925,3,5,5,5,2,3,2,2,1,2,3,2,3,2,6,20.0,neutral or dissatisfied +16967,76567,Male,disloyal Customer,13,Business travel,Eco,516,1,1,1,4,2,1,2,2,2,5,3,4,3,2,9,6.0,neutral or dissatisfied +16968,127112,Female,Loyal Customer,48,Personal Travel,Eco,651,1,4,1,5,3,4,4,5,5,1,5,4,5,3,0,3.0,neutral or dissatisfied +16969,24961,Male,disloyal Customer,54,Business travel,Business,226,3,2,2,4,1,3,1,1,5,4,2,4,3,1,0,0.0,neutral or dissatisfied +16970,91905,Female,Loyal Customer,31,Business travel,Business,2475,5,5,5,5,4,4,4,4,4,3,5,3,5,4,0,10.0,satisfied +16971,4004,Male,Loyal Customer,49,Business travel,Business,419,4,4,4,4,4,5,4,4,4,4,4,3,4,5,0,18.0,satisfied +16972,90581,Male,Loyal Customer,50,Business travel,Business,2779,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +16973,35244,Male,Loyal Customer,47,Business travel,Business,1076,1,1,1,1,4,1,3,2,2,2,2,5,2,3,0,0.0,satisfied +16974,32547,Male,Loyal Customer,35,Business travel,Business,3950,5,5,5,5,2,2,2,5,5,5,3,1,5,1,0,6.0,satisfied +16975,119510,Female,disloyal Customer,32,Business travel,Eco,759,2,2,2,3,3,2,5,3,2,2,3,3,4,3,48,61.0,neutral or dissatisfied +16976,101307,Male,Loyal Customer,56,Business travel,Eco Plus,763,2,1,1,1,3,2,3,3,2,2,3,1,2,3,20,17.0,neutral or dissatisfied +16977,98032,Male,Loyal Customer,21,Personal Travel,Eco,1014,2,3,2,3,5,2,5,5,1,3,4,2,3,5,6,3.0,neutral or dissatisfied +16978,93978,Female,Loyal Customer,56,Business travel,Eco,1218,3,3,3,3,3,4,3,2,2,3,2,1,2,4,15,0.0,neutral or dissatisfied +16979,46674,Female,Loyal Customer,69,Personal Travel,Eco,125,2,4,2,3,2,3,4,1,1,2,1,5,1,1,0,0.0,neutral or dissatisfied +16980,97120,Female,Loyal Customer,55,Business travel,Business,3686,1,1,1,1,4,4,5,3,3,4,3,3,3,4,5,11.0,satisfied +16981,65415,Female,Loyal Customer,50,Business travel,Business,631,5,5,5,5,5,4,5,5,5,5,5,3,5,5,2,2.0,satisfied +16982,73843,Male,disloyal Customer,27,Business travel,Business,785,5,5,5,2,4,5,4,4,5,4,5,3,4,4,0,0.0,satisfied +16983,109893,Female,Loyal Customer,59,Business travel,Business,3510,3,3,3,3,4,4,4,1,2,4,2,4,3,4,194,183.0,satisfied +16984,31555,Female,Loyal Customer,35,Personal Travel,Eco,967,2,5,2,3,2,2,2,2,5,4,4,5,5,2,0,2.0,neutral or dissatisfied +16985,82646,Female,disloyal Customer,23,Business travel,Business,120,2,3,2,3,2,2,2,2,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +16986,13198,Female,Loyal Customer,36,Personal Travel,Eco,542,1,3,1,1,1,1,1,1,3,2,4,4,3,1,0,0.0,neutral or dissatisfied +16987,30819,Female,Loyal Customer,49,Business travel,Business,1026,2,2,2,2,2,2,3,2,2,2,2,4,2,3,0,3.0,neutral or dissatisfied +16988,112950,Male,Loyal Customer,21,Personal Travel,Eco,1242,1,4,1,3,4,1,4,4,5,5,4,4,5,4,17,6.0,neutral or dissatisfied +16989,5085,Female,Loyal Customer,74,Business travel,Business,235,1,1,1,1,3,3,4,5,5,5,5,3,5,5,5,0.0,satisfied +16990,577,Female,Loyal Customer,48,Business travel,Business,164,5,1,5,5,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +16991,72474,Male,Loyal Customer,25,Business travel,Business,2737,1,1,1,1,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +16992,68389,Female,Loyal Customer,28,Business travel,Business,1045,2,2,2,2,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +16993,84557,Female,Loyal Customer,70,Personal Travel,Eco,2399,3,4,3,1,3,5,4,1,1,3,3,3,1,5,0,0.0,neutral or dissatisfied +16994,73529,Male,Loyal Customer,58,Business travel,Business,594,5,5,2,5,3,4,4,2,2,2,2,3,2,5,0,0.0,satisfied +16995,18960,Female,disloyal Customer,25,Business travel,Eco Plus,500,1,1,1,3,5,1,5,5,1,1,4,2,4,5,0,7.0,neutral or dissatisfied +16996,21450,Female,Loyal Customer,29,Business travel,Business,331,5,5,5,5,5,5,5,5,2,4,1,5,1,5,0,0.0,satisfied +16997,24594,Female,Loyal Customer,40,Business travel,Eco,666,5,2,2,2,5,5,5,5,3,3,4,5,3,5,0,0.0,satisfied +16998,80582,Male,Loyal Customer,59,Personal Travel,Eco,1747,2,0,2,1,1,2,1,1,4,2,5,3,4,1,11,0.0,neutral or dissatisfied +16999,46965,Male,Loyal Customer,22,Personal Travel,Eco,833,2,4,3,1,1,3,5,1,4,3,4,3,5,1,0,9.0,neutral or dissatisfied +17000,15537,Female,Loyal Customer,29,Business travel,Business,2180,4,4,4,4,5,5,5,5,4,1,2,3,5,5,0,0.0,satisfied +17001,110123,Female,Loyal Customer,52,Business travel,Business,2490,4,4,4,4,3,4,4,2,2,2,2,3,2,4,12,0.0,satisfied +17002,12634,Male,Loyal Customer,28,Business travel,Business,1875,3,3,3,3,4,4,4,4,5,2,5,5,1,4,2,0.0,satisfied +17003,22137,Male,Loyal Customer,42,Business travel,Business,3887,5,1,1,1,5,4,4,5,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +17004,119778,Male,Loyal Customer,11,Personal Travel,Business,912,5,5,5,1,4,5,4,4,3,2,4,5,4,4,0,0.0,satisfied +17005,56527,Male,Loyal Customer,28,Business travel,Business,1023,3,3,4,3,4,4,4,4,3,2,4,5,4,4,30,4.0,satisfied +17006,66372,Male,Loyal Customer,50,Business travel,Business,986,3,3,3,3,2,5,5,4,4,4,4,3,4,4,75,87.0,satisfied +17007,126548,Male,Loyal Customer,60,Personal Travel,Eco,644,1,2,1,4,4,1,4,4,2,1,4,3,4,4,119,119.0,neutral or dissatisfied +17008,76550,Male,Loyal Customer,58,Business travel,Business,2029,2,2,2,2,5,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +17009,15141,Male,disloyal Customer,27,Business travel,Eco,1042,3,3,3,1,4,3,4,4,4,5,1,5,4,4,0,0.0,neutral or dissatisfied +17010,68638,Female,Loyal Customer,62,Business travel,Business,2059,0,0,0,2,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +17011,12208,Female,disloyal Customer,23,Business travel,Business,127,4,5,4,5,5,4,5,5,5,4,4,3,4,5,0,0.0,satisfied +17012,28965,Female,disloyal Customer,23,Business travel,Eco,1050,2,2,2,3,1,2,1,1,2,1,4,2,3,1,0,0.0,neutral or dissatisfied +17013,97897,Male,disloyal Customer,22,Business travel,Eco,722,2,1,1,4,2,1,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +17014,81827,Male,Loyal Customer,57,Personal Travel,Eco,1310,2,5,2,4,3,2,3,3,5,3,3,5,4,3,3,0.0,neutral or dissatisfied +17015,109312,Female,Loyal Customer,49,Business travel,Eco,1188,3,3,3,3,4,3,4,3,3,3,3,4,3,4,98,114.0,neutral or dissatisfied +17016,46972,Female,Loyal Customer,45,Personal Travel,Eco,848,2,4,2,3,5,5,4,3,3,2,3,3,3,3,0,11.0,neutral or dissatisfied +17017,83456,Male,Loyal Customer,51,Business travel,Business,2584,2,2,2,2,3,5,4,5,5,5,5,5,5,3,3,0.0,satisfied +17018,102880,Male,Loyal Customer,48,Personal Travel,Eco,472,1,5,5,2,1,5,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +17019,118444,Female,Loyal Customer,57,Business travel,Business,1698,1,3,1,1,2,5,4,4,4,4,4,5,4,5,15,13.0,satisfied +17020,53209,Male,Loyal Customer,53,Business travel,Eco,612,3,1,1,1,2,3,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +17021,67162,Female,Loyal Customer,27,Personal Travel,Eco,918,4,4,5,4,1,5,4,1,5,2,4,3,5,1,13,1.0,satisfied +17022,5989,Male,Loyal Customer,57,Business travel,Business,672,1,1,5,1,2,4,5,5,5,4,5,4,5,5,0,2.0,satisfied +17023,99844,Male,disloyal Customer,36,Business travel,Business,280,1,1,1,4,3,1,3,3,3,3,3,3,4,3,50,64.0,neutral or dissatisfied +17024,64237,Female,Loyal Customer,25,Business travel,Eco,1660,4,2,4,2,4,4,2,4,4,4,2,2,4,4,0,17.0,neutral or dissatisfied +17025,99593,Female,Loyal Customer,59,Personal Travel,Eco,973,2,2,2,3,3,2,3,1,1,2,1,1,1,2,10,3.0,neutral or dissatisfied +17026,53865,Female,disloyal Customer,43,Business travel,Eco,140,2,0,2,3,4,2,2,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +17027,125686,Female,Loyal Customer,50,Business travel,Business,3813,5,5,1,5,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +17028,57525,Male,Loyal Customer,24,Business travel,Business,1954,5,5,5,5,5,5,5,5,3,4,5,4,4,5,4,0.0,satisfied +17029,66460,Male,Loyal Customer,39,Personal Travel,Eco,1217,2,4,2,1,1,2,1,1,5,3,5,3,4,1,15,39.0,neutral or dissatisfied +17030,124420,Male,Loyal Customer,46,Business travel,Business,1044,2,2,2,2,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +17031,19190,Female,Loyal Customer,42,Business travel,Business,542,5,3,5,5,1,3,4,5,5,5,5,1,5,1,3,0.0,satisfied +17032,79679,Female,Loyal Customer,20,Personal Travel,Eco,762,1,4,1,3,5,1,5,5,4,4,3,4,4,5,31,0.0,neutral or dissatisfied +17033,71643,Female,Loyal Customer,46,Personal Travel,Eco,1120,1,1,1,3,4,3,3,4,4,1,1,2,4,1,0,0.0,neutral or dissatisfied +17034,103381,Male,disloyal Customer,54,Business travel,Business,237,4,4,4,2,4,4,3,4,3,3,5,5,5,4,6,0.0,satisfied +17035,28657,Male,Loyal Customer,11,Personal Travel,Eco,2404,1,4,1,2,4,1,3,4,3,1,2,4,1,4,7,0.0,neutral or dissatisfied +17036,17121,Female,Loyal Customer,8,Personal Travel,Eco Plus,821,3,5,3,1,2,3,2,2,3,4,5,3,4,2,0,0.0,neutral or dissatisfied +17037,106198,Female,Loyal Customer,52,Business travel,Business,3893,0,0,0,1,2,5,4,4,4,1,1,4,4,5,0,0.0,satisfied +17038,34825,Male,Loyal Customer,26,Business travel,Eco Plus,209,3,1,1,1,3,4,3,3,1,5,3,3,5,3,0,0.0,satisfied +17039,84054,Male,Loyal Customer,23,Business travel,Business,3259,3,1,3,3,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +17040,114288,Female,Loyal Customer,67,Personal Travel,Eco,862,4,2,5,4,5,4,4,1,1,5,1,3,1,2,0,0.0,satisfied +17041,56036,Male,Loyal Customer,32,Business travel,Eco,2475,3,4,4,4,3,3,3,3,1,5,2,3,4,3,4,0.0,neutral or dissatisfied +17042,64784,Male,Loyal Customer,34,Business travel,Business,2157,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +17043,102427,Female,Loyal Customer,53,Personal Travel,Eco,236,1,4,1,2,1,3,5,3,3,1,3,1,3,3,2,5.0,neutral or dissatisfied +17044,71076,Female,Loyal Customer,60,Personal Travel,Eco,802,4,3,4,3,2,4,2,4,4,4,4,5,4,1,32,5.0,neutral or dissatisfied +17045,95029,Male,Loyal Customer,67,Personal Travel,Eco,293,2,4,2,4,5,2,5,5,2,1,3,1,3,5,6,0.0,neutral or dissatisfied +17046,92661,Female,Loyal Customer,56,Business travel,Eco Plus,453,3,5,5,5,3,2,2,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +17047,81749,Female,Loyal Customer,39,Business travel,Business,3228,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +17048,5357,Male,Loyal Customer,45,Business travel,Business,2161,4,4,4,4,2,4,4,3,3,4,3,3,3,4,31,33.0,satisfied +17049,31175,Female,Loyal Customer,48,Business travel,Business,1620,3,3,4,3,5,4,4,5,5,5,5,3,5,1,2,15.0,satisfied +17050,26450,Female,Loyal Customer,8,Business travel,Business,787,4,2,2,2,4,4,4,4,3,2,3,4,4,4,13,3.0,neutral or dissatisfied +17051,65505,Female,Loyal Customer,23,Personal Travel,Eco Plus,1067,2,4,2,3,2,2,2,2,3,3,3,3,4,2,0,0.0,neutral or dissatisfied +17052,94237,Female,Loyal Customer,44,Business travel,Business,2852,2,2,4,2,3,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +17053,1119,Male,Loyal Customer,33,Personal Travel,Eco,354,1,4,5,4,2,5,2,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +17054,3129,Female,Loyal Customer,50,Business travel,Business,140,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +17055,94058,Male,Loyal Customer,59,Business travel,Business,1555,1,1,1,1,5,4,5,5,2,4,4,5,3,5,166,162.0,satisfied +17056,70474,Male,disloyal Customer,25,Business travel,Business,867,3,4,3,4,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +17057,18231,Male,disloyal Customer,27,Business travel,Eco,137,4,0,4,3,2,4,2,2,4,2,5,4,2,2,0,0.0,satisfied +17058,55373,Female,Loyal Customer,27,Business travel,Business,413,5,5,5,5,5,5,5,5,5,5,5,4,4,5,32,20.0,satisfied +17059,81957,Female,disloyal Customer,23,Business travel,Eco,1363,3,3,3,4,5,3,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +17060,50001,Female,Loyal Customer,45,Business travel,Business,56,1,2,2,2,5,3,4,4,4,4,1,4,4,4,0,0.0,neutral or dissatisfied +17061,27685,Female,Loyal Customer,62,Business travel,Business,3740,4,4,4,4,3,4,3,4,4,3,4,4,4,1,60,54.0,neutral or dissatisfied +17062,79035,Male,Loyal Customer,56,Business travel,Business,2736,2,2,2,2,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +17063,98450,Female,Loyal Customer,50,Business travel,Business,3905,1,1,1,1,5,5,5,5,5,5,5,5,5,5,0,6.0,satisfied +17064,20987,Male,Loyal Customer,37,Personal Travel,Eco,721,3,4,3,2,3,3,3,3,4,1,2,3,4,3,0,0.0,neutral or dissatisfied +17065,82974,Male,disloyal Customer,20,Business travel,Business,1127,4,0,4,3,5,4,5,5,3,5,5,5,5,5,21,20.0,satisfied +17066,64683,Male,Loyal Customer,48,Business travel,Business,1969,0,4,0,4,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +17067,109742,Female,Loyal Customer,15,Personal Travel,Eco,534,2,5,2,4,1,2,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +17068,2748,Male,Loyal Customer,59,Business travel,Business,3778,2,2,2,2,4,5,5,5,5,4,5,4,5,4,0,0.0,satisfied +17069,80116,Female,Loyal Customer,17,Personal Travel,Eco,1620,1,5,1,1,1,1,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +17070,23247,Male,Loyal Customer,34,Business travel,Business,3990,4,4,4,4,2,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +17071,53,Male,disloyal Customer,37,Business travel,Business,212,2,3,3,4,3,3,1,3,4,2,5,3,5,3,4,1.0,neutral or dissatisfied +17072,52558,Male,Loyal Customer,45,Business travel,Business,160,4,4,4,4,2,1,3,4,4,4,4,3,4,2,0,0.0,satisfied +17073,111509,Female,Loyal Customer,37,Business travel,Eco,391,2,1,1,1,2,2,2,2,2,2,3,4,3,2,44,32.0,neutral or dissatisfied +17074,49166,Male,disloyal Customer,42,Business travel,Eco,308,4,5,4,2,4,4,2,4,2,3,5,2,2,4,0,0.0,neutral or dissatisfied +17075,10828,Male,Loyal Customer,53,Business travel,Business,316,1,1,1,1,3,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +17076,69763,Female,Loyal Customer,7,Personal Travel,Eco,1085,3,4,3,4,3,3,3,1,2,4,4,3,4,3,144,173.0,neutral or dissatisfied +17077,123796,Female,disloyal Customer,16,Business travel,Eco,544,4,0,4,5,5,4,2,5,5,5,5,4,4,5,35,18.0,satisfied +17078,84055,Female,disloyal Customer,23,Business travel,Eco,773,1,1,1,2,1,1,1,1,4,4,5,3,4,1,0,0.0,neutral or dissatisfied +17079,94230,Male,Loyal Customer,45,Business travel,Business,677,4,4,2,4,2,5,5,4,4,4,4,4,4,4,0,1.0,satisfied +17080,82395,Male,disloyal Customer,27,Business travel,Business,501,1,2,2,1,5,2,5,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +17081,85967,Male,Loyal Customer,27,Business travel,Business,554,4,4,4,4,5,5,5,5,3,5,4,4,4,5,7,2.0,satisfied +17082,70592,Male,Loyal Customer,25,Business travel,Business,2611,2,4,4,4,3,2,2,4,4,2,3,2,3,2,0,25.0,neutral or dissatisfied +17083,4223,Male,Loyal Customer,28,Business travel,Business,888,2,2,3,2,4,4,4,4,3,2,4,3,5,4,69,97.0,satisfied +17084,88453,Female,disloyal Customer,80,Business travel,Eco,181,3,4,3,3,1,3,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +17085,69350,Male,disloyal Customer,47,Business travel,Business,1096,1,1,1,4,3,1,2,3,4,3,5,3,4,3,1,0.0,neutral or dissatisfied +17086,521,Female,disloyal Customer,59,Business travel,Business,158,2,2,2,1,1,2,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +17087,116635,Female,disloyal Customer,34,Business travel,Eco Plus,373,1,1,1,4,1,1,1,1,4,2,3,1,4,1,17,7.0,neutral or dissatisfied +17088,45035,Female,Loyal Customer,35,Business travel,Business,837,1,3,3,3,1,4,4,1,1,1,1,3,1,3,32,47.0,neutral or dissatisfied +17089,70185,Female,Loyal Customer,49,Business travel,Business,1562,0,0,0,1,3,5,4,3,3,3,3,3,3,4,3,16.0,satisfied +17090,73642,Female,disloyal Customer,21,Business travel,Business,204,5,4,5,4,1,5,1,1,5,2,5,4,4,1,0,0.0,satisfied +17091,104978,Male,Loyal Customer,33,Business travel,Business,2126,1,5,5,5,1,1,1,1,2,2,3,4,3,1,0,0.0,neutral or dissatisfied +17092,30314,Female,disloyal Customer,44,Business travel,Eco,391,4,0,4,4,5,4,5,5,3,1,4,1,2,5,30,20.0,satisfied +17093,9416,Female,disloyal Customer,22,Business travel,Eco,299,4,2,4,1,4,4,4,4,4,2,5,4,5,4,0,6.0,satisfied +17094,97230,Male,disloyal Customer,15,Business travel,Business,296,1,3,1,3,5,1,5,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +17095,129613,Female,Loyal Customer,44,Business travel,Business,2108,1,2,2,2,5,4,3,1,1,1,1,2,1,1,2,0.0,neutral or dissatisfied +17096,57375,Male,Loyal Customer,32,Business travel,Eco Plus,414,3,3,4,3,3,3,3,3,4,2,4,2,3,3,5,9.0,neutral or dissatisfied +17097,78540,Male,Loyal Customer,31,Personal Travel,Eco,526,3,4,3,4,1,3,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +17098,61,Male,Loyal Customer,42,Business travel,Business,3391,3,3,3,3,2,5,4,4,4,4,5,5,4,3,0,0.0,satisfied +17099,90545,Female,disloyal Customer,22,Business travel,Eco,406,3,4,2,2,1,2,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +17100,82744,Female,Loyal Customer,46,Business travel,Eco,409,1,3,3,3,4,2,3,1,1,1,1,2,1,3,0,0.0,neutral or dissatisfied +17101,33737,Female,Loyal Customer,39,Business travel,Eco Plus,814,4,3,3,3,4,4,4,4,5,2,4,4,5,4,5,0.0,satisfied +17102,128180,Female,Loyal Customer,18,Personal Travel,Eco,1972,3,0,3,4,3,3,3,3,3,4,3,3,4,3,0,0.0,neutral or dissatisfied +17103,114218,Female,Loyal Customer,31,Business travel,Business,3189,3,5,5,5,3,3,3,3,1,5,4,1,4,3,16,11.0,neutral or dissatisfied +17104,58844,Female,Loyal Customer,30,Business travel,Business,2732,5,5,5,5,4,4,4,4,5,5,4,3,5,4,1,0.0,satisfied +17105,77064,Male,Loyal Customer,28,Business travel,Business,991,3,3,3,3,5,5,5,5,5,3,4,4,4,5,0,0.0,satisfied +17106,23212,Male,Loyal Customer,37,Business travel,Business,2494,0,0,0,1,5,3,5,3,3,3,3,3,3,1,0,0.0,satisfied +17107,30315,Female,Loyal Customer,38,Business travel,Business,391,2,2,2,2,1,4,1,5,5,5,5,3,5,5,12,12.0,satisfied +17108,21328,Male,Loyal Customer,27,Business travel,Business,2606,2,2,2,2,5,4,5,5,4,4,5,3,1,5,24,6.0,satisfied +17109,69468,Female,Loyal Customer,39,Personal Travel,Eco,1096,1,5,2,3,5,2,1,5,2,2,4,5,3,5,0,0.0,neutral or dissatisfied +17110,21403,Female,Loyal Customer,23,Business travel,Business,331,2,2,2,2,4,4,4,4,2,3,1,2,5,4,0,0.0,satisfied +17111,60698,Male,Loyal Customer,57,Business travel,Business,1605,5,5,2,5,2,5,4,3,3,3,3,3,3,3,38,24.0,satisfied +17112,28807,Female,Loyal Customer,53,Business travel,Eco,978,4,2,2,2,3,3,2,3,3,4,3,4,3,1,5,0.0,satisfied +17113,99975,Female,Loyal Customer,40,Business travel,Business,1944,0,5,0,2,2,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +17114,78921,Female,Loyal Customer,46,Business travel,Business,501,2,2,5,2,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +17115,59452,Male,Loyal Customer,45,Business travel,Business,3254,1,1,1,1,5,5,5,5,5,5,5,3,5,3,89,80.0,satisfied +17116,7345,Female,Loyal Customer,39,Personal Travel,Eco,606,2,4,2,4,4,2,4,4,4,4,5,5,5,4,36,33.0,neutral or dissatisfied +17117,57328,Male,disloyal Customer,25,Business travel,Business,414,3,5,3,5,2,3,2,2,4,5,5,5,5,2,0,0.0,neutral or dissatisfied +17118,86228,Male,Loyal Customer,39,Business travel,Eco,226,1,4,4,4,1,1,1,1,2,5,3,3,4,1,22,9.0,neutral or dissatisfied +17119,90891,Female,Loyal Customer,37,Business travel,Eco,545,2,3,1,3,2,2,2,2,3,4,2,4,3,2,67,64.0,neutral or dissatisfied +17120,129314,Male,Loyal Customer,35,Business travel,Business,2586,2,2,2,2,2,5,4,5,5,5,5,3,5,3,0,4.0,satisfied +17121,37472,Female,Loyal Customer,19,Business travel,Business,1796,4,4,4,4,5,5,5,5,2,4,1,1,1,5,0,3.0,satisfied +17122,24806,Male,Loyal Customer,24,Business travel,Eco,828,5,3,3,3,5,5,3,5,2,3,1,2,4,5,24,3.0,satisfied +17123,81222,Male,Loyal Customer,53,Personal Travel,Eco,1426,3,5,3,3,1,3,1,1,2,1,3,1,5,1,0,4.0,neutral or dissatisfied +17124,106811,Male,Loyal Customer,34,Business travel,Business,1488,4,4,4,4,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +17125,920,Male,Loyal Customer,49,Business travel,Business,270,5,5,5,5,2,5,5,4,4,4,4,3,4,5,9,4.0,satisfied +17126,47030,Male,Loyal Customer,52,Business travel,Eco,639,5,2,2,2,5,5,5,5,3,3,4,3,3,5,0,27.0,satisfied +17127,103259,Female,Loyal Customer,27,Business travel,Business,888,1,1,1,1,5,4,5,5,4,5,4,4,4,5,38,29.0,satisfied +17128,84368,Female,disloyal Customer,52,Business travel,Business,591,4,3,3,1,4,4,4,4,5,4,4,3,5,4,0,6.0,neutral or dissatisfied +17129,14553,Male,Loyal Customer,21,Personal Travel,Eco,368,2,1,2,2,4,2,4,4,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +17130,83533,Female,Loyal Customer,23,Business travel,Business,2925,3,3,3,3,4,4,4,4,4,5,5,4,5,4,79,137.0,satisfied +17131,20542,Male,Loyal Customer,43,Business travel,Eco,533,3,5,2,2,3,3,3,3,3,5,1,5,4,3,0,26.0,satisfied +17132,96220,Female,Loyal Customer,49,Business travel,Business,687,3,3,3,3,5,3,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +17133,13448,Male,Loyal Customer,25,Personal Travel,Eco,491,2,3,2,3,4,2,4,4,2,4,3,3,2,4,0,3.0,neutral or dissatisfied +17134,69668,Male,Loyal Customer,49,Personal Travel,Eco,569,2,4,2,2,2,2,2,2,5,3,4,4,5,2,0,0.0,neutral or dissatisfied +17135,78873,Male,Loyal Customer,28,Business travel,Business,1995,4,4,4,4,2,2,2,2,3,5,4,4,4,2,0,6.0,satisfied +17136,87802,Female,Loyal Customer,36,Business travel,Eco,214,1,1,1,1,1,1,1,1,1,5,4,1,3,1,0,0.0,neutral or dissatisfied +17137,41836,Female,Loyal Customer,59,Business travel,Business,3581,1,1,1,1,2,4,1,4,4,3,4,4,4,3,0,0.0,satisfied +17138,59395,Female,Loyal Customer,60,Personal Travel,Eco,2556,2,4,2,2,4,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +17139,108256,Female,Loyal Customer,23,Business travel,Eco,895,4,1,1,1,4,4,3,4,4,3,3,1,3,4,1,11.0,neutral or dissatisfied +17140,64892,Male,Loyal Customer,43,Business travel,Business,247,2,5,5,5,2,2,2,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +17141,78209,Male,Loyal Customer,60,Personal Travel,Eco,153,4,5,4,1,1,4,1,1,3,2,5,4,5,1,0,0.0,satisfied +17142,8855,Female,Loyal Customer,44,Business travel,Business,539,1,1,1,1,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +17143,57544,Female,Loyal Customer,45,Personal Travel,Eco,413,3,4,3,5,4,3,2,5,5,3,2,1,5,5,0,0.0,neutral or dissatisfied +17144,24789,Male,Loyal Customer,17,Personal Travel,Eco,432,3,2,3,4,5,3,5,5,3,3,4,3,3,5,0,0.0,neutral or dissatisfied +17145,121216,Male,Loyal Customer,60,Business travel,Business,2075,5,5,4,5,4,3,4,2,2,2,2,4,2,3,1,0.0,satisfied +17146,61970,Male,Loyal Customer,7,Personal Travel,Eco,2400,4,5,4,4,1,4,1,1,3,4,4,4,5,1,25,16.0,neutral or dissatisfied +17147,53682,Female,Loyal Customer,29,Business travel,Eco,1208,0,0,0,4,4,0,4,4,4,4,3,1,1,4,0,0.0,satisfied +17148,82674,Female,Loyal Customer,35,Business travel,Business,2049,3,3,3,3,5,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +17149,102416,Male,Loyal Customer,68,Personal Travel,Eco,414,4,3,4,4,4,4,1,4,5,4,3,3,2,4,16,7.0,neutral or dissatisfied +17150,40769,Female,Loyal Customer,54,Business travel,Eco,501,3,5,5,5,5,4,4,2,2,3,2,1,2,4,0,0.0,neutral or dissatisfied +17151,43834,Female,Loyal Customer,48,Business travel,Business,1845,4,4,4,4,5,2,2,4,4,4,4,2,4,4,0,0.0,satisfied +17152,16725,Male,disloyal Customer,39,Business travel,Business,1167,1,2,2,3,3,2,3,3,5,1,2,3,5,3,46,86.0,neutral or dissatisfied +17153,35468,Male,Loyal Customer,9,Personal Travel,Eco,1005,3,2,3,3,5,3,5,5,4,2,2,2,2,5,0,1.0,neutral or dissatisfied +17154,11184,Male,Loyal Customer,48,Personal Travel,Eco,158,3,2,3,4,1,3,1,1,4,2,4,3,3,1,0,0.0,neutral or dissatisfied +17155,124115,Female,Loyal Customer,34,Business travel,Business,529,1,1,1,1,5,4,4,5,5,4,5,3,5,4,0,0.0,satisfied +17156,66740,Male,Loyal Customer,31,Personal Travel,Eco,802,3,2,3,2,2,3,2,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +17157,110182,Male,Loyal Customer,56,Personal Travel,Eco,979,4,4,4,3,2,4,2,2,5,2,5,5,4,2,0,0.0,neutral or dissatisfied +17158,127885,Male,Loyal Customer,35,Business travel,Business,3288,2,2,2,2,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +17159,98798,Female,Loyal Customer,58,Personal Travel,Eco,630,2,1,2,4,3,3,3,4,4,2,4,1,4,2,17,4.0,neutral or dissatisfied +17160,87000,Male,Loyal Customer,24,Personal Travel,Eco,907,2,5,2,4,4,2,4,4,4,2,5,5,5,4,28,12.0,neutral or dissatisfied +17161,35721,Female,Loyal Customer,42,Personal Travel,Eco,2576,2,3,1,3,1,2,4,2,5,4,1,4,4,4,96,83.0,neutral or dissatisfied +17162,59191,Female,Loyal Customer,58,Business travel,Business,1440,3,2,3,3,2,5,5,4,4,4,4,5,4,4,8,24.0,satisfied +17163,108476,Male,Loyal Customer,33,Personal Travel,Eco Plus,1444,5,4,5,2,2,5,2,2,3,2,4,3,4,2,18,26.0,satisfied +17164,13798,Female,Loyal Customer,36,Business travel,Business,195,3,3,3,3,5,2,5,5,5,5,4,4,5,5,28,0.0,satisfied +17165,110580,Male,Loyal Customer,24,Business travel,Eco,674,1,1,1,1,1,1,1,1,4,3,2,4,1,1,14,23.0,neutral or dissatisfied +17166,93411,Female,Loyal Customer,38,Business travel,Business,723,2,1,1,1,1,4,3,2,2,2,2,4,2,3,4,6.0,neutral or dissatisfied +17167,42610,Male,Loyal Customer,54,Business travel,Eco,223,3,2,4,2,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +17168,53712,Male,Loyal Customer,44,Personal Travel,Eco,1208,3,5,3,1,5,3,5,5,2,1,4,3,5,5,10,0.0,neutral or dissatisfied +17169,103445,Female,Loyal Customer,39,Business travel,Business,448,5,5,5,5,2,4,4,4,4,4,4,3,4,5,15,0.0,satisfied +17170,48759,Female,Loyal Customer,49,Business travel,Business,1729,3,4,4,4,3,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +17171,57751,Female,Loyal Customer,32,Business travel,Business,2611,2,2,3,2,5,5,5,5,4,5,5,5,3,5,35,38.0,satisfied +17172,98756,Male,Loyal Customer,30,Business travel,Business,2075,3,5,5,5,3,3,3,3,1,2,1,1,2,3,26,40.0,neutral or dissatisfied +17173,6151,Female,disloyal Customer,26,Business travel,Eco,409,4,2,4,4,3,4,5,3,3,2,4,2,4,3,0,0.0,neutral or dissatisfied +17174,89978,Male,Loyal Customer,48,Business travel,Business,3934,4,4,3,4,5,4,4,5,5,5,5,3,5,4,0,7.0,satisfied +17175,21354,Male,Loyal Customer,47,Personal Travel,Eco,674,2,4,2,1,5,2,2,5,5,3,4,5,5,5,6,0.0,neutral or dissatisfied +17176,15748,Male,Loyal Customer,29,Business travel,Business,3890,2,1,1,1,2,2,2,2,5,3,2,2,3,2,165,167.0,neutral or dissatisfied +17177,46631,Female,Loyal Customer,39,Business travel,Business,3452,2,3,3,3,2,3,3,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +17178,50143,Female,Loyal Customer,33,Business travel,Business,2814,5,5,5,5,2,2,1,2,2,2,2,3,2,2,0,19.0,satisfied +17179,63823,Male,Loyal Customer,52,Personal Travel,Business,1192,3,5,4,3,3,4,4,1,1,4,1,4,1,5,0,0.0,neutral or dissatisfied +17180,6492,Female,Loyal Customer,54,Personal Travel,Eco,557,3,4,4,1,5,5,4,3,3,4,3,4,3,5,0,0.0,neutral or dissatisfied +17181,107410,Male,disloyal Customer,20,Business travel,Eco,725,4,5,5,3,2,5,3,2,4,2,4,2,3,2,42,46.0,neutral or dissatisfied +17182,36546,Female,disloyal Customer,17,Business travel,Eco,1121,4,4,4,2,2,4,2,2,2,5,4,2,1,2,0,0.0,satisfied +17183,23722,Male,Loyal Customer,37,Personal Travel,Eco,251,3,4,0,3,3,0,3,3,2,3,2,1,4,3,0,0.0,neutral or dissatisfied +17184,31992,Female,Loyal Customer,21,Personal Travel,Business,102,3,4,3,3,5,3,5,5,3,3,4,3,5,5,0,0.0,neutral or dissatisfied +17185,100390,Female,Loyal Customer,17,Personal Travel,Eco,1034,3,5,3,3,4,3,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +17186,76010,Female,Loyal Customer,58,Business travel,Business,311,3,4,4,4,1,4,4,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +17187,97362,Female,Loyal Customer,36,Personal Travel,Eco,872,4,2,4,3,2,4,1,2,1,2,3,4,3,2,0,0.0,neutral or dissatisfied +17188,33006,Female,Loyal Customer,24,Personal Travel,Eco,101,4,3,4,3,3,4,4,3,1,1,4,5,4,3,14,21.0,neutral or dissatisfied +17189,95008,Male,Loyal Customer,37,Personal Travel,Eco,528,2,2,2,3,3,2,3,3,1,1,4,1,3,3,27,20.0,neutral or dissatisfied +17190,29641,Female,Loyal Customer,38,Personal Travel,Eco,680,3,5,3,3,3,3,2,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +17191,18360,Male,Loyal Customer,30,Business travel,Business,3509,0,5,0,1,4,4,2,4,5,3,5,1,3,4,0,0.0,satisfied +17192,61934,Female,disloyal Customer,22,Business travel,Eco,550,2,0,2,1,5,2,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +17193,59828,Female,Loyal Customer,39,Business travel,Business,2355,5,5,1,5,5,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +17194,106303,Female,disloyal Customer,25,Business travel,Business,998,4,0,4,4,2,4,2,2,3,5,5,5,5,2,0,11.0,satisfied +17195,10366,Male,Loyal Customer,43,Business travel,Business,2130,3,3,3,3,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +17196,129347,Female,Loyal Customer,60,Personal Travel,Eco,2475,3,1,3,4,1,3,3,1,1,3,1,4,1,2,0,0.0,neutral or dissatisfied +17197,91580,Female,Loyal Customer,60,Business travel,Business,3611,1,1,1,1,2,1,3,4,4,4,4,3,4,4,0,1.0,satisfied +17198,91724,Male,disloyal Customer,23,Business travel,Business,590,0,0,0,5,5,0,5,5,4,2,5,3,4,5,14,3.0,satisfied +17199,47853,Female,Loyal Customer,71,Business travel,Business,1704,3,3,3,3,1,3,3,5,5,4,5,2,5,3,0,0.0,satisfied +17200,20198,Male,Loyal Customer,62,Business travel,Eco Plus,349,5,5,3,5,5,5,5,5,4,1,1,5,3,5,0,0.0,satisfied +17201,76984,Female,disloyal Customer,22,Business travel,Business,422,4,0,3,4,1,3,1,1,5,4,5,5,5,1,17,11.0,satisfied +17202,35887,Male,Loyal Customer,63,Personal Travel,Eco,1065,2,4,2,4,5,2,5,5,5,3,4,3,5,5,0,0.0,neutral or dissatisfied +17203,56845,Male,Loyal Customer,46,Business travel,Business,2454,2,2,2,2,5,4,4,4,3,4,5,4,4,4,44,26.0,satisfied +17204,95019,Female,Loyal Customer,61,Personal Travel,Eco,248,4,5,4,1,3,5,5,5,5,4,5,3,5,3,4,0.0,satisfied +17205,123144,Male,disloyal Customer,21,Business travel,Eco,328,5,0,5,3,4,5,4,4,3,3,5,3,4,4,3,0.0,satisfied +17206,35300,Male,disloyal Customer,22,Business travel,Eco,1028,4,4,4,4,1,4,1,1,2,2,2,3,2,1,0,33.0,satisfied +17207,103976,Female,Loyal Customer,70,Personal Travel,Eco Plus,533,2,4,2,1,3,5,4,4,4,2,4,5,4,5,33,29.0,neutral or dissatisfied +17208,92221,Male,Loyal Customer,33,Personal Travel,Eco,1956,3,4,3,3,4,3,4,4,1,4,3,4,4,4,0,0.0,neutral or dissatisfied +17209,8457,Female,Loyal Customer,42,Business travel,Business,1379,1,2,2,2,5,3,4,1,1,1,1,3,1,1,48,49.0,neutral or dissatisfied +17210,12797,Male,disloyal Customer,27,Business travel,Eco,817,3,3,3,1,3,1,1,3,1,4,5,1,3,1,146,155.0,neutral or dissatisfied +17211,28888,Female,Loyal Customer,64,Business travel,Business,671,4,4,4,4,1,4,1,4,4,3,4,1,4,1,0,0.0,satisfied +17212,77998,Female,Loyal Customer,61,Business travel,Eco,332,3,1,1,1,4,3,3,3,3,3,3,3,3,2,0,36.0,neutral or dissatisfied +17213,51676,Female,Loyal Customer,68,Business travel,Business,2394,2,4,4,4,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +17214,57829,Male,Loyal Customer,62,Personal Travel,Eco Plus,622,4,5,4,3,2,4,2,2,2,4,2,4,4,2,0,0.0,neutral or dissatisfied +17215,128748,Female,Loyal Customer,67,Business travel,Business,1893,2,2,2,2,2,2,2,3,3,3,3,2,2,2,0,0.0,neutral or dissatisfied +17216,84283,Male,Loyal Customer,46,Personal Travel,Eco,334,3,5,3,3,3,3,3,3,5,4,5,5,5,3,58,72.0,neutral or dissatisfied +17217,90148,Male,Loyal Customer,22,Business travel,Business,2369,3,1,1,1,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +17218,122941,Male,Loyal Customer,52,Business travel,Business,600,1,1,1,1,3,4,4,4,4,4,4,5,4,3,11,0.0,satisfied +17219,17745,Male,Loyal Customer,53,Business travel,Business,456,3,2,2,2,5,3,3,3,3,2,3,2,3,2,0,45.0,neutral or dissatisfied +17220,125634,Female,Loyal Customer,41,Business travel,Business,3556,1,1,2,1,2,4,4,4,4,4,4,5,4,3,0,13.0,satisfied +17221,85624,Male,Loyal Customer,20,Personal Travel,Eco,259,2,1,2,2,2,2,1,2,4,2,2,1,2,2,14,19.0,neutral or dissatisfied +17222,85964,Female,Loyal Customer,54,Business travel,Business,1714,2,2,2,2,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +17223,93745,Male,disloyal Customer,20,Business travel,Business,368,5,4,5,5,1,5,1,1,5,5,5,3,4,1,0,0.0,satisfied +17224,57309,Male,Loyal Customer,59,Business travel,Business,2203,4,4,4,4,3,4,5,4,4,4,4,3,4,5,67,52.0,satisfied +17225,83730,Male,disloyal Customer,50,Business travel,Eco,627,4,0,4,3,2,4,2,2,3,2,4,2,5,2,0,0.0,satisfied +17226,7830,Male,Loyal Customer,48,Personal Travel,Eco,650,1,2,1,3,3,1,3,3,2,5,2,1,2,3,0,0.0,neutral or dissatisfied +17227,49683,Male,disloyal Customer,23,Business travel,Eco,89,3,4,3,4,4,3,4,4,2,4,4,4,3,4,4,7.0,neutral or dissatisfied +17228,104293,Male,disloyal Customer,29,Business travel,Eco,382,2,2,2,4,4,2,4,4,1,5,4,1,4,4,17,21.0,neutral or dissatisfied +17229,113986,Female,Loyal Customer,16,Business travel,Business,1750,1,1,1,1,5,5,5,5,4,3,4,4,5,5,8,0.0,satisfied +17230,74046,Male,Loyal Customer,56,Business travel,Eco,1194,1,1,3,1,1,1,1,1,3,4,3,2,4,1,58,89.0,neutral or dissatisfied +17231,69606,Male,Loyal Customer,35,Personal Travel,Eco,2475,1,1,1,4,1,1,1,2,3,4,4,1,2,1,0,0.0,neutral or dissatisfied +17232,62549,Male,disloyal Customer,25,Business travel,Business,1037,5,2,5,3,2,5,2,2,4,5,3,5,5,2,31,0.0,satisfied +17233,107516,Male,Loyal Customer,45,Business travel,Business,838,4,4,4,4,3,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +17234,81977,Female,disloyal Customer,22,Business travel,Eco,1432,2,1,1,3,2,2,3,2,3,2,3,1,2,2,40,44.0,neutral or dissatisfied +17235,95912,Female,Loyal Customer,50,Personal Travel,Eco Plus,580,3,1,3,4,2,3,3,3,3,3,3,2,3,1,69,56.0,neutral or dissatisfied +17236,104648,Female,Loyal Customer,37,Personal Travel,Eco,1754,1,4,1,3,2,1,2,2,5,1,5,3,1,2,0,0.0,neutral or dissatisfied +17237,19485,Female,Loyal Customer,56,Personal Travel,Eco,84,3,2,0,3,1,3,4,2,2,0,2,3,2,4,0,19.0,neutral or dissatisfied +17238,3758,Male,Loyal Customer,35,Personal Travel,Eco Plus,544,1,4,3,1,3,3,3,3,5,5,4,4,4,3,0,27.0,neutral or dissatisfied +17239,61849,Male,disloyal Customer,22,Business travel,Eco Plus,1346,5,0,5,3,1,5,1,1,3,5,4,4,5,1,0,0.0,satisfied +17240,97348,Female,disloyal Customer,43,Business travel,Eco,347,5,3,5,3,1,5,1,1,3,3,5,5,1,1,0,0.0,satisfied +17241,20847,Male,Loyal Customer,67,Personal Travel,Eco,534,3,4,3,3,4,3,4,4,3,2,4,5,5,4,30,26.0,neutral or dissatisfied +17242,105313,Male,Loyal Customer,51,Business travel,Business,3377,5,5,5,5,2,5,4,2,2,2,2,5,2,4,25,37.0,satisfied +17243,70120,Female,Loyal Customer,53,Business travel,Business,3232,1,1,1,1,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +17244,30206,Male,Loyal Customer,67,Personal Travel,Eco Plus,261,5,3,5,3,1,5,3,1,3,2,4,4,3,1,0,0.0,satisfied +17245,51918,Female,disloyal Customer,26,Business travel,Eco Plus,507,2,5,2,5,4,2,4,4,4,5,3,4,1,4,0,35.0,neutral or dissatisfied +17246,45334,Female,Loyal Customer,50,Business travel,Eco,222,4,4,4,4,1,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +17247,122967,Male,Loyal Customer,40,Business travel,Business,3657,5,5,5,5,4,5,4,3,3,3,3,3,3,3,0,33.0,satisfied +17248,101788,Male,Loyal Customer,48,Business travel,Business,1680,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +17249,35822,Male,Loyal Customer,39,Business travel,Eco,1065,3,1,1,1,3,3,3,3,3,4,2,1,2,3,37,47.0,neutral or dissatisfied +17250,116278,Female,Loyal Customer,60,Personal Travel,Eco,362,3,5,3,5,3,4,4,2,2,3,2,4,2,5,0,0.0,neutral or dissatisfied +17251,118397,Female,Loyal Customer,56,Business travel,Business,3893,0,1,1,2,5,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +17252,37724,Female,Loyal Customer,67,Personal Travel,Eco,944,4,2,4,4,3,4,3,1,1,4,1,2,1,2,0,0.0,satisfied +17253,68759,Male,Loyal Customer,57,Business travel,Business,3837,1,1,1,1,5,4,4,2,2,2,2,3,2,4,9,20.0,satisfied +17254,89216,Female,Loyal Customer,13,Personal Travel,Eco,1892,3,1,3,3,2,3,2,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +17255,110944,Female,Loyal Customer,65,Personal Travel,Eco,404,3,4,3,4,2,2,3,5,5,3,5,3,5,5,0,13.0,neutral or dissatisfied +17256,67982,Male,Loyal Customer,59,Business travel,Eco Plus,1171,1,2,2,2,1,1,1,1,2,2,4,2,3,1,0,0.0,neutral or dissatisfied +17257,81541,Male,Loyal Customer,58,Personal Travel,Eco,1124,2,3,2,3,4,2,4,4,2,1,1,1,2,4,0,0.0,neutral or dissatisfied +17258,39647,Female,Loyal Customer,64,Personal Travel,Eco,1172,3,5,3,3,3,5,4,1,1,3,1,5,1,4,15,11.0,neutral or dissatisfied +17259,20177,Female,Loyal Customer,37,Personal Travel,Eco,403,2,5,2,3,3,2,3,3,3,2,4,4,4,3,0,0.0,neutral or dissatisfied +17260,2676,Male,Loyal Customer,25,Personal Travel,Eco,597,2,4,2,3,4,2,4,4,4,5,3,2,4,4,0,0.0,neutral or dissatisfied +17261,108230,Female,Loyal Customer,43,Business travel,Business,3328,2,2,2,2,4,4,5,4,4,4,4,5,4,3,0,6.0,satisfied +17262,75150,Male,disloyal Customer,29,Business travel,Business,1214,4,4,4,3,3,4,3,3,4,5,4,3,5,3,32,16.0,satisfied +17263,43004,Male,disloyal Customer,21,Business travel,Eco,391,2,1,2,2,5,2,5,5,4,5,2,2,2,5,4,2.0,neutral or dissatisfied +17264,29194,Male,Loyal Customer,58,Personal Travel,Eco Plus,987,4,5,5,1,1,5,1,1,3,2,4,3,5,1,0,0.0,satisfied +17265,6975,Female,Loyal Customer,32,Business travel,Business,436,5,5,5,5,4,4,4,4,5,5,4,4,4,4,17,10.0,satisfied +17266,79581,Female,Loyal Customer,50,Business travel,Business,1670,2,3,3,3,2,3,3,2,2,2,2,4,2,2,28,23.0,neutral or dissatisfied +17267,81278,Male,disloyal Customer,27,Business travel,Eco,1020,3,3,3,3,2,3,4,2,3,2,2,1,2,2,18,12.0,neutral or dissatisfied +17268,23667,Female,Loyal Customer,40,Business travel,Business,1710,1,1,1,1,4,2,5,5,5,5,5,5,5,1,0,0.0,satisfied +17269,35934,Female,Loyal Customer,9,Personal Travel,Eco,2381,3,5,3,1,2,3,1,2,4,3,5,4,2,2,22,0.0,neutral or dissatisfied +17270,96643,Male,Loyal Customer,54,Business travel,Business,972,3,4,1,4,3,3,4,3,3,3,3,3,3,1,0,12.0,neutral or dissatisfied +17271,46494,Male,disloyal Customer,41,Business travel,Eco,73,1,0,1,1,1,1,1,1,1,3,1,2,2,1,0,0.0,neutral or dissatisfied +17272,105671,Female,disloyal Customer,25,Business travel,Business,925,3,5,3,4,1,3,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +17273,56310,Male,disloyal Customer,56,Business travel,Business,200,5,5,5,4,5,5,5,5,4,3,5,3,5,5,111,115.0,satisfied +17274,42633,Male,Loyal Customer,43,Business travel,Eco,546,3,4,4,4,3,3,3,3,3,5,3,3,4,3,0,1.0,neutral or dissatisfied +17275,97884,Female,Loyal Customer,28,Business travel,Business,2010,4,4,4,4,3,3,3,3,4,4,5,4,5,3,0,0.0,satisfied +17276,60415,Female,Loyal Customer,25,Personal Travel,Eco Plus,1452,4,4,4,2,2,4,2,2,5,5,3,4,4,2,2,0.0,neutral or dissatisfied +17277,108447,Female,Loyal Customer,36,Business travel,Eco,1444,4,1,1,1,4,3,4,4,1,2,4,1,3,4,0,0.0,neutral or dissatisfied +17278,41812,Female,disloyal Customer,36,Business travel,Eco,196,2,0,2,2,4,2,4,4,4,2,4,5,1,4,12,2.0,neutral or dissatisfied +17279,54234,Female,Loyal Customer,30,Business travel,Business,3702,3,3,3,3,2,2,2,2,3,5,2,2,5,2,4,0.0,satisfied +17280,36229,Female,Loyal Customer,47,Personal Travel,Eco,496,3,5,3,3,2,4,5,2,2,3,2,5,2,5,0,0.0,neutral or dissatisfied +17281,24372,Female,Loyal Customer,22,Business travel,Business,669,1,1,1,1,2,2,2,2,2,5,1,5,5,2,0,0.0,satisfied +17282,129126,Female,Loyal Customer,21,Business travel,Business,1594,3,3,4,3,2,3,2,2,3,5,4,4,4,2,0,0.0,satisfied +17283,38356,Female,Loyal Customer,55,Business travel,Business,2135,3,3,4,3,5,4,4,3,3,3,3,3,3,1,0,44.0,neutral or dissatisfied +17284,93273,Male,Loyal Customer,49,Business travel,Business,2462,2,1,2,2,2,4,5,5,5,5,5,5,5,5,11,8.0,satisfied +17285,22180,Female,Loyal Customer,55,Business travel,Eco,565,2,1,4,1,3,2,2,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +17286,10571,Female,Loyal Customer,57,Business travel,Business,1938,3,3,3,3,2,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +17287,101243,Male,Loyal Customer,63,Personal Travel,Eco,1587,2,5,2,1,4,2,4,4,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +17288,68511,Female,disloyal Customer,29,Business travel,Business,1303,2,2,2,4,3,2,5,3,3,5,5,4,4,3,0,0.0,neutral or dissatisfied +17289,77075,Male,Loyal Customer,47,Business travel,Business,3711,4,4,4,4,2,2,1,5,5,5,5,2,5,2,0,0.0,satisfied +17290,55679,Female,Loyal Customer,56,Business travel,Business,1062,1,1,1,1,4,5,4,4,4,4,4,5,4,5,32,29.0,satisfied +17291,105621,Male,Loyal Customer,40,Business travel,Business,842,4,4,4,4,3,5,4,4,4,4,4,5,4,5,1,0.0,satisfied +17292,84374,Female,Loyal Customer,57,Business travel,Business,3750,1,1,5,1,3,5,5,2,2,2,2,3,2,3,0,0.0,satisfied +17293,48450,Male,Loyal Customer,37,Business travel,Eco,819,2,2,2,2,2,2,2,2,3,5,1,2,5,2,24,17.0,satisfied +17294,45821,Male,Loyal Customer,57,Personal Travel,Eco,391,2,2,4,4,4,2,2,2,1,3,3,2,1,2,142,135.0,neutral or dissatisfied +17295,120244,Male,Loyal Customer,31,Personal Travel,Eco,1325,4,5,4,2,1,4,5,1,4,5,3,3,4,1,0,,neutral or dissatisfied +17296,79781,Female,Loyal Customer,39,Personal Travel,Business,1076,3,4,3,4,2,4,5,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +17297,22448,Female,Loyal Customer,21,Personal Travel,Eco,83,2,4,0,3,5,0,5,5,4,4,4,3,5,5,0,0.0,neutral or dissatisfied +17298,119440,Male,Loyal Customer,39,Business travel,Business,399,5,5,5,5,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +17299,45563,Female,Loyal Customer,8,Business travel,Business,1918,1,2,2,2,1,1,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +17300,12940,Female,Loyal Customer,58,Personal Travel,Eco,809,3,4,3,3,5,4,4,2,2,3,2,3,2,1,25,19.0,neutral or dissatisfied +17301,119841,Female,Loyal Customer,53,Business travel,Eco,936,3,1,2,1,1,4,3,3,3,3,3,2,3,4,2,6.0,neutral or dissatisfied +17302,129481,Male,Loyal Customer,47,Business travel,Business,2704,1,1,1,1,4,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +17303,7816,Male,disloyal Customer,30,Business travel,Eco,650,3,3,3,3,3,3,3,3,1,4,3,4,3,3,2,0.0,neutral or dissatisfied +17304,121877,Female,Loyal Customer,25,Business travel,Eco,366,4,2,2,2,4,4,3,4,4,5,4,4,2,4,15,4.0,satisfied +17305,82041,Female,Loyal Customer,15,Personal Travel,Eco,1522,4,2,5,4,4,5,4,4,3,5,4,2,4,4,3,1.0,neutral or dissatisfied +17306,48737,Male,Loyal Customer,40,Business travel,Business,2235,1,3,1,3,2,3,3,2,2,2,1,2,2,4,0,0.0,neutral or dissatisfied +17307,72589,Male,disloyal Customer,23,Business travel,Eco,985,2,2,2,1,1,2,1,1,3,4,1,3,1,1,0,0.0,neutral or dissatisfied +17308,111316,Female,Loyal Customer,58,Business travel,Business,3520,2,2,2,2,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +17309,27968,Female,Loyal Customer,24,Business travel,Eco Plus,1770,5,4,4,4,5,5,4,5,1,5,3,2,4,5,0,8.0,satisfied +17310,24306,Female,Loyal Customer,54,Business travel,Eco Plus,151,5,3,5,3,5,4,1,5,5,5,5,1,5,4,0,0.0,satisfied +17311,76200,Female,Loyal Customer,30,Business travel,Business,2422,2,3,3,3,2,2,2,2,3,2,3,1,4,2,0,24.0,neutral or dissatisfied +17312,59195,Male,Loyal Customer,41,Business travel,Business,1440,1,1,1,1,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +17313,113931,Female,disloyal Customer,19,Business travel,Eco,930,5,5,5,3,2,5,2,2,3,4,5,4,4,2,18,31.0,satisfied +17314,100210,Male,disloyal Customer,44,Business travel,Business,762,4,4,4,3,2,4,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +17315,18941,Female,Loyal Customer,49,Personal Travel,Eco,551,3,1,3,3,3,4,4,4,4,3,3,4,4,4,38,36.0,neutral or dissatisfied +17316,39745,Male,Loyal Customer,51,Personal Travel,Eco Plus,320,4,4,4,4,4,4,4,4,5,2,1,2,5,4,0,0.0,neutral or dissatisfied +17317,129593,Male,Loyal Customer,26,Personal Travel,Business,337,2,4,2,2,3,2,3,3,1,4,1,4,4,3,8,8.0,neutral or dissatisfied +17318,102477,Female,Loyal Customer,62,Personal Travel,Eco,391,3,4,3,5,2,3,2,3,3,3,3,3,3,1,0,3.0,neutral or dissatisfied +17319,34017,Female,Loyal Customer,51,Personal Travel,Eco,1576,2,4,2,4,3,4,4,3,3,2,3,4,3,4,34,36.0,neutral or dissatisfied +17320,632,Female,Loyal Customer,47,Business travel,Business,158,3,3,3,3,2,5,4,4,4,4,5,4,4,5,0,1.0,satisfied +17321,45237,Female,Loyal Customer,8,Personal Travel,Eco,1013,1,2,0,3,4,0,4,4,2,5,3,1,3,4,15,65.0,neutral or dissatisfied +17322,21037,Female,Loyal Customer,44,Business travel,Business,2941,1,1,1,1,1,2,2,5,5,4,4,5,5,1,50,55.0,satisfied +17323,122974,Male,disloyal Customer,28,Business travel,Business,650,4,4,4,3,5,4,5,5,4,3,4,3,4,5,1,0.0,satisfied +17324,50564,Female,Loyal Customer,61,Personal Travel,Eco,304,1,4,1,2,2,2,1,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +17325,102683,Female,Loyal Customer,42,Business travel,Business,1602,4,4,4,4,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +17326,1703,Female,Loyal Customer,45,Business travel,Business,364,1,1,1,1,5,5,5,2,2,3,2,3,2,4,34,35.0,satisfied +17327,18796,Female,disloyal Customer,22,Business travel,Business,503,5,0,5,5,4,5,4,4,4,3,2,4,1,4,0,0.0,satisfied +17328,107783,Female,disloyal Customer,22,Business travel,Eco,666,2,2,2,3,5,2,5,5,3,2,4,1,3,5,0,0.0,neutral or dissatisfied +17329,33550,Female,Loyal Customer,39,Business travel,Eco,399,5,5,5,5,5,5,5,5,1,1,3,1,2,5,5,1.0,satisfied +17330,70678,Female,disloyal Customer,39,Business travel,Eco,447,2,2,1,3,4,1,4,4,4,1,3,4,4,4,0,0.0,neutral or dissatisfied +17331,67237,Male,Loyal Customer,44,Personal Travel,Eco,1121,1,5,1,4,2,1,2,2,4,4,4,3,4,2,71,97.0,neutral or dissatisfied +17332,95260,Male,Loyal Customer,41,Personal Travel,Eco,239,4,5,0,4,4,0,4,4,4,4,1,1,3,4,14,41.0,neutral or dissatisfied +17333,66976,Female,Loyal Customer,40,Business travel,Business,2553,2,4,2,2,4,5,5,2,2,2,2,4,2,4,0,3.0,satisfied +17334,73870,Male,Loyal Customer,53,Business travel,Business,2342,2,5,5,5,4,2,2,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +17335,34814,Female,Loyal Customer,44,Personal Travel,Eco,264,4,1,4,2,2,2,2,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +17336,103581,Male,Loyal Customer,31,Business travel,Business,3236,4,4,4,4,4,4,4,4,3,3,5,4,5,4,15,0.0,satisfied +17337,75471,Female,Loyal Customer,14,Personal Travel,Eco,2585,3,3,2,4,2,2,2,2,3,2,3,4,3,2,13,0.0,neutral or dissatisfied +17338,13054,Female,Loyal Customer,54,Personal Travel,Eco Plus,438,3,4,3,2,5,3,1,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +17339,124302,Female,Loyal Customer,36,Business travel,Business,255,2,1,4,1,5,4,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +17340,109279,Male,Loyal Customer,51,Business travel,Business,3798,2,2,2,2,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +17341,793,Female,Loyal Customer,49,Business travel,Business,3125,4,4,4,4,5,4,4,5,5,5,5,5,5,5,102,96.0,satisfied +17342,77891,Male,Loyal Customer,43,Business travel,Business,456,4,4,4,4,3,4,5,3,3,3,3,5,3,5,0,4.0,satisfied +17343,7653,Female,Loyal Customer,20,Business travel,Business,604,5,5,5,5,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +17344,90666,Male,Loyal Customer,58,Business travel,Business,545,1,1,1,1,5,4,5,5,5,5,5,3,5,3,82,72.0,satisfied +17345,80039,Female,Loyal Customer,49,Personal Travel,Eco,950,2,3,2,3,5,4,5,2,2,2,2,1,2,5,0,2.0,neutral or dissatisfied +17346,94464,Male,disloyal Customer,21,Business travel,Eco,239,5,0,5,3,5,5,3,5,5,2,4,4,4,5,107,115.0,satisfied +17347,127331,Female,disloyal Customer,29,Business travel,Business,507,3,3,3,2,2,3,4,2,4,3,5,5,4,2,8,0.0,neutral or dissatisfied +17348,72191,Male,Loyal Customer,46,Business travel,Business,2509,3,5,2,5,2,3,2,1,3,4,4,2,1,2,168,201.0,neutral or dissatisfied +17349,124146,Male,Loyal Customer,50,Business travel,Business,3744,5,5,5,5,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +17350,93649,Female,Loyal Customer,48,Business travel,Business,3768,3,3,3,3,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +17351,36853,Female,Loyal Customer,45,Business travel,Business,3444,4,4,4,4,4,4,4,4,4,5,4,3,4,5,0,14.0,satisfied +17352,107205,Female,Loyal Customer,52,Personal Travel,Eco,402,3,5,3,2,4,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +17353,85267,Female,Loyal Customer,22,Personal Travel,Eco,696,2,4,2,2,3,2,3,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +17354,78703,Female,Loyal Customer,30,Business travel,Business,2052,5,5,5,5,4,4,4,4,3,2,4,3,5,4,0,6.0,satisfied +17355,106201,Female,disloyal Customer,22,Business travel,Eco,436,3,4,3,1,4,3,4,4,5,4,5,5,5,4,0,0.0,neutral or dissatisfied +17356,114638,Female,disloyal Customer,25,Business travel,Business,296,0,4,0,2,1,0,1,1,4,3,5,5,5,1,20,15.0,satisfied +17357,20900,Female,Loyal Customer,26,Business travel,Business,3325,1,1,1,1,4,4,4,4,3,2,4,3,4,4,0,0.0,satisfied +17358,22885,Female,Loyal Customer,37,Personal Travel,Eco,147,2,3,2,3,3,2,3,3,3,4,4,3,3,3,8,3.0,neutral or dissatisfied +17359,23322,Female,Loyal Customer,43,Business travel,Eco,674,4,4,4,4,2,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +17360,47410,Male,Loyal Customer,39,Business travel,Eco,590,4,3,2,2,4,3,4,4,3,1,3,3,3,4,14,15.0,neutral or dissatisfied +17361,71080,Female,Loyal Customer,8,Personal Travel,Eco,802,4,4,4,3,4,4,5,4,5,5,5,1,1,4,0,32.0,neutral or dissatisfied +17362,7750,Male,Loyal Customer,26,Business travel,Eco,1013,4,2,2,2,4,4,1,4,4,4,1,1,2,4,83,85.0,neutral or dissatisfied +17363,24142,Female,Loyal Customer,36,Business travel,Eco,134,2,5,5,5,2,2,2,2,5,1,2,1,4,2,3,0.0,satisfied +17364,37416,Female,Loyal Customer,51,Business travel,Business,3320,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +17365,18062,Female,disloyal Customer,24,Business travel,Business,488,4,3,4,4,2,4,5,2,1,3,4,4,1,2,0,0.0,satisfied +17366,72164,Male,Loyal Customer,54,Business travel,Eco Plus,331,4,1,1,1,3,4,3,3,2,4,1,3,4,3,0,0.0,satisfied +17367,82251,Male,Loyal Customer,57,Business travel,Business,1481,4,4,4,4,4,5,4,2,2,2,2,3,2,3,63,119.0,satisfied +17368,25389,Female,disloyal Customer,21,Business travel,Eco,191,2,4,2,1,3,2,3,3,2,1,4,4,2,3,4,0.0,neutral or dissatisfied +17369,34100,Male,Loyal Customer,70,Personal Travel,Business,1189,2,1,2,3,3,2,2,4,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +17370,18061,Female,Loyal Customer,17,Business travel,Business,488,3,5,5,5,3,3,3,3,3,3,4,3,3,3,7,9.0,neutral or dissatisfied +17371,59487,Male,Loyal Customer,16,Personal Travel,Eco,921,3,5,3,3,1,3,1,1,4,5,4,4,5,1,97,101.0,neutral or dissatisfied +17372,76029,Male,Loyal Customer,28,Personal Travel,Eco,237,1,5,0,4,3,0,3,3,3,2,4,4,4,3,11,15.0,neutral or dissatisfied +17373,28382,Male,disloyal Customer,22,Business travel,Eco,763,3,3,3,3,1,3,1,1,2,1,3,3,3,1,0,0.0,neutral or dissatisfied +17374,22524,Female,disloyal Customer,24,Business travel,Eco Plus,208,5,0,5,1,1,5,4,1,2,5,2,3,4,1,0,0.0,satisfied +17375,1635,Female,Loyal Customer,22,Personal Travel,Eco,999,3,3,3,3,2,3,2,2,4,3,1,5,2,2,10,0.0,neutral or dissatisfied +17376,107413,Male,disloyal Customer,33,Business travel,Eco,725,4,4,4,2,2,4,4,2,4,4,2,2,3,2,0,0.0,neutral or dissatisfied +17377,18275,Male,Loyal Customer,39,Business travel,Eco Plus,228,5,1,1,1,5,5,5,5,4,3,3,2,5,5,0,0.0,satisfied +17378,79164,Female,disloyal Customer,20,Business travel,Eco,1325,4,4,4,3,4,5,4,4,5,5,5,4,5,4,0,0.0,neutral or dissatisfied +17379,23418,Female,Loyal Customer,62,Personal Travel,Eco,541,2,5,2,4,4,5,4,4,4,2,4,5,4,3,49,63.0,neutral or dissatisfied +17380,110813,Male,Loyal Customer,63,Personal Travel,Eco,997,3,5,3,2,4,3,4,4,3,4,4,5,5,4,12,45.0,neutral or dissatisfied +17381,104208,Female,Loyal Customer,52,Business travel,Business,680,2,2,2,2,4,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +17382,59550,Male,Loyal Customer,30,Business travel,Business,854,1,1,1,1,5,4,5,5,4,3,4,3,5,5,2,0.0,satisfied +17383,2949,Male,Loyal Customer,22,Business travel,Business,2177,4,4,4,4,4,4,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +17384,26443,Male,Loyal Customer,32,Business travel,Business,842,3,3,3,3,4,4,4,4,2,1,1,2,5,4,0,0.0,satisfied +17385,3942,Female,disloyal Customer,20,Business travel,Eco,765,4,4,4,3,2,4,2,2,2,2,4,1,4,2,0,3.0,neutral or dissatisfied +17386,109051,Female,disloyal Customer,39,Business travel,Business,781,3,3,3,4,5,3,5,5,1,4,3,4,4,5,20,8.0,neutral or dissatisfied +17387,56288,Male,Loyal Customer,56,Business travel,Business,2227,2,2,2,2,5,5,4,4,4,4,4,4,4,4,120,99.0,satisfied +17388,9977,Male,Loyal Customer,26,Personal Travel,Eco,515,3,4,3,3,1,3,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +17389,35784,Female,Loyal Customer,62,Personal Travel,Eco,200,3,3,3,2,5,5,1,2,2,3,2,3,2,3,0,0.0,neutral or dissatisfied +17390,106328,Male,disloyal Customer,22,Business travel,Eco,825,3,3,3,4,5,3,3,5,4,3,3,2,3,5,0,2.0,neutral or dissatisfied +17391,108946,Male,disloyal Customer,16,Business travel,Eco,1066,2,2,2,3,5,2,5,5,4,2,3,1,3,5,43,25.0,neutral or dissatisfied +17392,64151,Female,Loyal Customer,60,Business travel,Business,3748,5,1,5,5,2,4,4,5,5,5,5,5,5,3,45,33.0,satisfied +17393,22707,Male,Loyal Customer,13,Personal Travel,Eco,589,3,4,4,4,2,4,2,2,5,5,5,4,5,2,0,6.0,neutral or dissatisfied +17394,42291,Female,Loyal Customer,76,Business travel,Eco,434,4,4,4,4,5,2,5,4,4,4,4,3,4,5,0,0.0,satisfied +17395,95055,Female,Loyal Customer,47,Personal Travel,Eco,323,4,4,4,4,2,3,5,3,3,4,3,2,3,1,0,0.0,satisfied +17396,71927,Female,disloyal Customer,20,Business travel,Eco,921,2,2,2,3,5,2,5,5,3,3,4,3,5,5,4,21.0,neutral or dissatisfied +17397,75953,Female,Loyal Customer,61,Business travel,Business,1509,0,0,0,2,3,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +17398,73691,Male,disloyal Customer,20,Business travel,Business,204,4,0,4,3,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +17399,83100,Female,Loyal Customer,19,Personal Travel,Eco,983,1,5,1,1,1,1,1,1,5,5,5,5,4,1,0,0.0,neutral or dissatisfied +17400,61299,Female,Loyal Customer,42,Personal Travel,Eco,862,2,3,2,3,2,2,2,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +17401,93534,Male,Loyal Customer,65,Personal Travel,Eco,1315,2,4,2,1,2,2,2,2,5,3,5,4,5,2,6,0.0,neutral or dissatisfied +17402,23769,Female,Loyal Customer,46,Personal Travel,Business,374,3,3,3,3,4,2,4,1,1,3,1,3,1,2,50,53.0,neutral or dissatisfied +17403,80775,Male,Loyal Customer,39,Business travel,Business,484,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +17404,83259,Female,Loyal Customer,33,Business travel,Business,1956,4,3,4,3,5,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +17405,44500,Male,Loyal Customer,38,Business travel,Business,411,3,3,3,3,2,1,3,1,1,2,1,4,1,4,0,10.0,satisfied +17406,110282,Female,Loyal Customer,42,Personal Travel,Business,663,1,4,1,4,2,3,3,5,5,1,5,4,5,2,35,24.0,neutral or dissatisfied +17407,41124,Female,Loyal Customer,53,Business travel,Eco,140,3,4,4,4,1,2,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +17408,59834,Male,Loyal Customer,60,Business travel,Business,997,5,5,5,5,3,4,4,5,5,4,5,3,5,3,0,0.0,satisfied +17409,90656,Female,Loyal Customer,47,Business travel,Business,1831,2,5,2,5,1,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +17410,129451,Female,Loyal Customer,25,Personal Travel,Eco,414,1,4,1,4,5,1,5,5,1,1,1,3,4,5,52,49.0,neutral or dissatisfied +17411,57034,Male,Loyal Customer,28,Business travel,Eco Plus,2565,2,3,1,3,2,2,2,3,3,3,4,2,4,2,227,245.0,neutral or dissatisfied +17412,40308,Male,Loyal Customer,60,Personal Travel,Eco,387,1,5,1,4,2,1,2,2,1,5,3,1,5,2,0,0.0,neutral or dissatisfied +17413,95103,Male,Loyal Customer,64,Personal Travel,Eco,562,1,5,1,1,2,1,2,2,5,5,5,5,5,2,64,59.0,neutral or dissatisfied +17414,22767,Male,disloyal Customer,21,Business travel,Eco,170,4,4,4,3,5,4,5,5,3,5,4,2,4,5,0,0.0,neutral or dissatisfied +17415,30359,Female,disloyal Customer,30,Business travel,Eco,641,2,3,2,4,3,2,1,3,1,3,1,5,3,3,8,13.0,neutral or dissatisfied +17416,97933,Male,Loyal Customer,22,Business travel,Business,655,2,4,4,4,2,3,2,2,4,3,4,1,3,2,0,0.0,neutral or dissatisfied +17417,126504,Female,Loyal Customer,7,Personal Travel,Eco,1972,1,3,1,4,2,1,2,2,4,2,5,3,4,2,9,10.0,neutral or dissatisfied +17418,49394,Female,Loyal Customer,35,Business travel,Eco,109,5,2,2,2,5,5,5,5,2,2,3,3,1,5,0,0.0,satisfied +17419,100641,Female,disloyal Customer,15,Business travel,Eco,349,4,0,4,2,2,4,2,2,5,5,5,4,3,2,0,0.0,satisfied +17420,107695,Female,Loyal Customer,30,Business travel,Business,251,1,1,1,1,5,5,5,5,5,5,4,3,4,5,3,8.0,satisfied +17421,49250,Female,Loyal Customer,40,Business travel,Eco,86,4,1,1,1,4,4,4,4,5,3,3,5,1,4,51,36.0,satisfied +17422,82780,Female,Loyal Customer,24,Personal Travel,Eco Plus,926,3,3,3,2,2,3,2,2,5,1,4,2,2,2,0,10.0,neutral or dissatisfied +17423,19126,Male,Loyal Customer,55,Personal Travel,Eco,265,3,1,3,3,5,3,2,5,1,4,4,1,4,5,0,,neutral or dissatisfied +17424,109115,Female,Loyal Customer,17,Business travel,Business,849,4,4,2,4,4,4,4,4,3,5,5,5,5,4,0,4.0,satisfied +17425,73025,Female,Loyal Customer,25,Personal Travel,Eco,1096,3,4,3,3,2,3,2,2,5,5,1,3,5,2,0,0.0,neutral or dissatisfied +17426,106131,Male,disloyal Customer,47,Business travel,Business,436,3,3,3,5,1,3,1,1,4,4,4,4,5,1,0,0.0,satisfied +17427,121053,Female,Loyal Customer,22,Personal Travel,Eco,992,2,4,3,1,2,3,1,2,3,2,4,3,5,2,0,0.0,neutral or dissatisfied +17428,99664,Female,Loyal Customer,57,Personal Travel,Eco,1050,2,4,2,4,4,3,3,5,5,2,5,3,5,4,69,72.0,neutral or dissatisfied +17429,73482,Male,Loyal Customer,8,Personal Travel,Eco,1144,2,5,2,2,2,1,1,4,4,3,5,1,3,1,1128,1115.0,neutral or dissatisfied +17430,123171,Male,Loyal Customer,38,Business travel,Eco,250,4,4,4,4,4,4,4,4,3,3,2,5,1,4,0,0.0,satisfied +17431,12945,Female,Loyal Customer,20,Personal Travel,Eco,456,3,5,3,4,4,3,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +17432,12681,Female,disloyal Customer,44,Business travel,Eco,689,2,2,2,3,5,2,5,5,4,1,3,1,4,5,0,72.0,neutral or dissatisfied +17433,29485,Female,Loyal Customer,36,Business travel,Eco,1107,5,2,2,2,5,5,5,5,3,1,4,5,4,5,36,25.0,satisfied +17434,113243,Female,Loyal Customer,51,Personal Travel,Business,414,4,5,4,2,5,3,3,2,2,4,2,2,2,5,84,74.0,neutral or dissatisfied +17435,8366,Female,Loyal Customer,43,Business travel,Business,773,1,1,1,1,3,4,5,3,3,4,3,3,3,3,0,0.0,satisfied +17436,70419,Male,Loyal Customer,31,Personal Travel,Eco Plus,1562,2,5,2,2,2,2,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +17437,75619,Male,Loyal Customer,30,Personal Travel,Eco,337,4,2,4,3,5,4,5,5,1,5,4,3,3,5,0,0.0,neutral or dissatisfied +17438,84095,Female,Loyal Customer,54,Business travel,Business,757,1,1,1,1,2,5,5,3,3,3,3,5,3,5,0,0.0,satisfied +17439,4742,Male,Loyal Customer,21,Personal Travel,Eco,888,2,4,1,4,4,1,4,4,3,3,3,4,4,4,45,32.0,neutral or dissatisfied +17440,46170,Female,Loyal Customer,33,Personal Travel,Eco,516,1,4,2,3,2,2,2,2,1,1,4,2,4,2,24,28.0,neutral or dissatisfied +17441,6103,Female,Loyal Customer,43,Business travel,Business,409,4,4,4,4,3,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +17442,106156,Male,Loyal Customer,41,Personal Travel,Eco,436,3,5,3,4,2,3,2,2,5,2,4,3,5,2,0,0.0,neutral or dissatisfied +17443,80227,Female,Loyal Customer,27,Personal Travel,Eco,2153,3,4,3,2,4,3,4,4,3,2,4,3,5,4,97,85.0,neutral or dissatisfied +17444,2235,Male,Loyal Customer,26,Personal Travel,Eco,859,2,5,2,4,3,2,3,3,1,4,5,4,2,3,0,0.0,neutral or dissatisfied +17445,4294,Female,Loyal Customer,43,Personal Travel,Eco,502,1,4,1,2,3,5,5,5,5,1,3,5,5,5,0,0.0,neutral or dissatisfied +17446,84815,Male,disloyal Customer,25,Business travel,Eco,516,2,2,3,2,1,3,1,1,4,5,3,3,3,1,0,0.0,neutral or dissatisfied +17447,15592,Female,Loyal Customer,55,Business travel,Business,2850,0,0,0,4,1,1,1,5,5,5,5,3,5,2,0,0.0,satisfied +17448,61900,Male,Loyal Customer,58,Business travel,Business,2521,5,5,5,5,2,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +17449,112278,Female,Loyal Customer,23,Personal Travel,Eco,1447,5,4,5,4,5,5,5,5,4,1,3,3,4,5,1,0.0,satisfied +17450,62654,Female,Loyal Customer,45,Personal Travel,Eco,1846,2,4,2,2,5,3,5,4,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +17451,11293,Female,Loyal Customer,58,Personal Travel,Eco,247,3,5,3,3,3,5,5,2,2,3,2,5,2,3,110,112.0,neutral or dissatisfied +17452,62865,Female,disloyal Customer,35,Business travel,Eco,1039,2,2,2,3,4,2,1,4,4,4,2,4,3,4,4,0.0,neutral or dissatisfied +17453,23257,Male,disloyal Customer,12,Business travel,Eco,783,5,5,5,2,4,5,4,4,2,1,1,5,4,4,0,0.0,satisfied +17454,52742,Female,disloyal Customer,27,Business travel,Eco,2306,2,2,2,3,2,2,2,2,4,1,4,3,1,2,0,2.0,neutral or dissatisfied +17455,109828,Female,Loyal Customer,34,Business travel,Business,3825,4,4,3,4,3,4,5,4,4,4,4,3,4,3,16,9.0,satisfied +17456,3247,Male,Loyal Customer,49,Business travel,Business,1627,2,2,2,2,2,4,4,2,2,2,2,3,2,5,8,20.0,satisfied +17457,35407,Female,disloyal Customer,38,Business travel,Eco,544,2,3,2,1,2,2,2,2,4,2,2,4,4,2,0,0.0,neutral or dissatisfied +17458,6126,Female,Loyal Customer,38,Business travel,Business,3755,2,2,2,2,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +17459,36478,Female,Loyal Customer,40,Business travel,Business,1730,5,5,5,5,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +17460,11039,Female,Loyal Customer,46,Personal Travel,Eco,312,5,1,5,3,3,3,3,4,4,5,4,1,4,2,0,2.0,satisfied +17461,108987,Male,Loyal Customer,60,Business travel,Business,3017,1,1,1,1,5,5,5,3,3,3,3,4,3,4,0,12.0,satisfied +17462,62227,Male,Loyal Customer,52,Personal Travel,Eco,2454,2,4,2,2,1,2,1,1,3,4,5,4,4,1,0,0.0,neutral or dissatisfied +17463,109362,Male,Loyal Customer,50,Business travel,Business,1189,1,1,1,1,2,5,5,4,4,4,4,5,4,5,26,20.0,satisfied +17464,90682,Female,Loyal Customer,30,Business travel,Business,2237,1,1,1,1,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +17465,19346,Female,Loyal Customer,70,Personal Travel,Eco Plus,743,3,5,3,1,5,5,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +17466,125109,Female,Loyal Customer,43,Business travel,Business,1568,1,1,1,1,3,3,3,4,4,4,4,3,4,3,0,5.0,satisfied +17467,110735,Male,Loyal Customer,57,Business travel,Business,1768,3,3,3,3,4,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +17468,46500,Male,Loyal Customer,40,Business travel,Eco,73,5,3,3,3,5,5,5,5,2,3,1,1,3,5,0,0.0,satisfied +17469,88844,Female,Loyal Customer,10,Personal Travel,Eco Plus,366,5,1,5,4,4,5,4,4,3,4,3,4,4,4,0,0.0,satisfied +17470,23361,Female,Loyal Customer,38,Business travel,Eco,1014,4,2,2,2,4,4,4,4,3,4,4,3,3,4,10,10.0,satisfied +17471,87326,Male,disloyal Customer,11,Business travel,Eco,1027,3,2,2,4,4,2,2,4,1,3,3,4,3,4,0,0.0,neutral or dissatisfied +17472,52465,Male,Loyal Customer,34,Business travel,Eco Plus,370,2,1,1,1,2,3,2,2,4,1,3,4,3,2,0,0.0,neutral or dissatisfied +17473,64626,Male,Loyal Customer,49,Business travel,Business,1957,4,4,4,4,5,5,4,4,4,4,4,4,4,5,9,0.0,satisfied +17474,105142,Female,disloyal Customer,27,Business travel,Business,289,2,1,1,3,2,1,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +17475,20057,Male,Loyal Customer,26,Personal Travel,Eco,566,3,3,4,2,5,4,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +17476,22942,Male,disloyal Customer,27,Business travel,Eco,641,5,0,4,4,2,4,2,2,1,1,3,4,1,2,0,0.0,satisfied +17477,108869,Female,Loyal Customer,69,Personal Travel,Eco Plus,1892,1,3,1,3,5,4,1,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +17478,68705,Female,Loyal Customer,43,Personal Travel,Eco,175,4,5,4,5,2,4,4,3,3,4,3,3,3,5,0,0.0,satisfied +17479,20631,Male,Loyal Customer,56,Business travel,Eco,911,5,2,2,2,5,5,5,5,3,1,4,3,2,5,65,95.0,satisfied +17480,123680,Female,Loyal Customer,42,Business travel,Business,2270,1,3,4,3,1,3,2,4,4,3,1,3,4,4,1,0.0,neutral or dissatisfied +17481,80758,Female,Loyal Customer,45,Business travel,Business,440,3,4,4,4,1,4,3,3,3,3,3,2,3,3,13,0.0,neutral or dissatisfied +17482,87337,Male,Loyal Customer,52,Personal Travel,Business,425,3,0,3,1,2,4,4,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +17483,124007,Female,Loyal Customer,30,Business travel,Eco,184,2,1,4,1,2,2,2,2,2,2,4,1,3,2,4,23.0,neutral or dissatisfied +17484,128910,Female,Loyal Customer,46,Business travel,Eco,748,4,4,4,4,2,2,1,4,4,4,4,1,4,5,0,0.0,satisfied +17485,121045,Female,Loyal Customer,52,Personal Travel,Eco,861,2,4,2,3,4,3,4,5,5,2,2,1,5,3,0,7.0,neutral or dissatisfied +17486,89502,Male,Loyal Customer,37,Personal Travel,Eco,655,4,4,4,4,1,4,1,1,4,3,2,1,4,1,0,0.0,neutral or dissatisfied +17487,12719,Female,disloyal Customer,22,Business travel,Eco,689,3,3,3,3,4,3,2,4,2,4,3,4,2,4,35,30.0,neutral or dissatisfied +17488,106169,Male,Loyal Customer,66,Personal Travel,Eco,302,4,3,4,3,2,4,2,2,4,4,3,1,3,2,0,4.0,neutral or dissatisfied +17489,16858,Male,Loyal Customer,25,Business travel,Business,746,1,1,1,1,5,4,5,5,5,1,1,4,1,5,0,47.0,satisfied +17490,109092,Female,Loyal Customer,13,Personal Travel,Eco,957,3,2,3,2,5,3,5,5,2,3,2,3,3,5,0,0.0,neutral or dissatisfied +17491,127032,Male,Loyal Customer,51,Business travel,Business,646,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +17492,36906,Male,Loyal Customer,60,Business travel,Business,572,2,2,2,2,4,1,2,5,5,5,5,3,5,4,0,0.0,satisfied +17493,118428,Male,Loyal Customer,43,Business travel,Business,2192,1,1,1,1,5,5,5,5,5,5,5,4,5,4,65,78.0,satisfied +17494,117486,Female,disloyal Customer,32,Business travel,Eco,507,2,2,2,4,2,2,2,2,4,3,3,1,4,2,13,17.0,neutral or dissatisfied +17495,56123,Male,disloyal Customer,25,Business travel,Eco,1400,2,2,2,3,5,2,5,5,3,4,5,5,5,5,0,0.0,satisfied +17496,50971,Female,Loyal Customer,9,Personal Travel,Eco,308,2,5,4,1,4,4,4,4,5,5,4,5,4,4,0,1.0,neutral or dissatisfied +17497,125631,Female,Loyal Customer,22,Business travel,Business,3942,1,1,1,1,5,5,5,5,4,4,4,5,5,5,11,8.0,satisfied +17498,35061,Female,disloyal Customer,15,Business travel,Eco,1028,1,1,1,4,5,1,5,5,2,4,4,3,4,5,9,1.0,neutral or dissatisfied +17499,41475,Male,Loyal Customer,54,Business travel,Business,1428,5,5,5,5,5,3,5,5,5,5,5,2,5,1,48,38.0,satisfied +17500,93626,Male,Loyal Customer,43,Business travel,Eco,577,2,1,1,1,1,2,1,1,4,3,4,3,5,1,8,1.0,satisfied +17501,66296,Female,disloyal Customer,37,Business travel,Business,852,3,3,3,1,5,3,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +17502,76321,Female,Loyal Customer,37,Personal Travel,Eco,2182,5,4,5,4,5,5,5,5,3,4,2,1,1,5,0,0.0,satisfied +17503,122320,Female,Loyal Customer,58,Business travel,Eco Plus,544,3,5,1,1,5,4,4,4,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +17504,30620,Male,Loyal Customer,34,Business travel,Business,2704,3,5,5,5,2,1,1,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +17505,127353,Female,Loyal Customer,29,Personal Travel,Eco,507,5,3,5,3,5,5,1,5,1,3,4,4,3,5,0,0.0,satisfied +17506,115069,Female,disloyal Customer,26,Business travel,Business,446,2,3,3,2,2,3,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +17507,8947,Male,Loyal Customer,43,Personal Travel,Eco,328,3,2,3,4,4,3,4,4,3,4,3,3,3,4,14,17.0,neutral or dissatisfied +17508,128338,Male,Loyal Customer,58,Business travel,Business,2888,5,5,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +17509,109923,Male,Loyal Customer,48,Personal Travel,Eco,971,3,2,3,3,4,3,4,4,2,3,2,3,3,4,15,0.0,neutral or dissatisfied +17510,46051,Male,Loyal Customer,16,Personal Travel,Eco,964,2,4,2,3,2,2,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +17511,62358,Male,Loyal Customer,53,Business travel,Business,1589,5,5,5,5,2,3,4,5,5,5,5,3,5,5,0,0.0,satisfied +17512,58855,Male,Loyal Customer,48,Business travel,Business,488,4,4,4,4,2,5,4,4,4,4,4,3,4,3,0,6.0,satisfied +17513,23671,Female,Loyal Customer,31,Business travel,Eco,212,4,3,3,3,4,4,4,4,2,1,4,5,2,4,19,13.0,satisfied +17514,127177,Female,Loyal Customer,38,Personal Travel,Eco,304,2,2,2,3,1,2,1,1,1,3,3,1,3,1,0,0.0,neutral or dissatisfied +17515,48114,Female,Loyal Customer,56,Business travel,Business,192,3,3,3,3,1,4,1,4,4,5,3,5,4,3,125,130.0,satisfied +17516,105946,Male,Loyal Customer,60,Personal Travel,Business,2329,2,5,2,2,4,4,4,1,1,2,1,5,1,5,8,28.0,neutral or dissatisfied +17517,112020,Male,Loyal Customer,39,Business travel,Business,680,2,2,2,2,2,5,4,5,5,5,5,4,5,3,15,4.0,satisfied +17518,89526,Male,Loyal Customer,7,Personal Travel,Business,1035,2,5,2,3,4,2,4,4,4,5,5,5,4,4,0,0.0,neutral or dissatisfied +17519,6268,Male,Loyal Customer,39,Business travel,Business,1507,1,1,4,1,4,4,4,4,4,4,4,5,4,3,1,0.0,satisfied +17520,85787,Female,Loyal Customer,60,Business travel,Business,666,1,1,1,1,3,4,5,4,4,4,4,4,4,4,3,0.0,satisfied +17521,29589,Female,Loyal Customer,31,Business travel,Business,2261,5,5,5,5,4,4,4,4,3,5,2,5,5,4,0,0.0,satisfied +17522,98411,Female,disloyal Customer,40,Business travel,Business,462,1,1,1,1,5,1,5,5,5,4,5,5,5,5,19,12.0,neutral or dissatisfied +17523,126189,Male,disloyal Customer,30,Business travel,Eco,507,3,3,3,3,1,3,5,1,4,4,3,4,3,1,1,8.0,neutral or dissatisfied +17524,20939,Male,disloyal Customer,24,Business travel,Eco,689,1,1,1,5,2,1,5,2,4,5,5,3,4,2,56,47.0,neutral or dissatisfied +17525,40422,Female,Loyal Customer,23,Business travel,Business,290,1,1,1,1,1,1,1,1,2,5,4,4,3,1,0,0.0,neutral or dissatisfied +17526,70968,Female,Loyal Customer,41,Personal Travel,Business,802,2,4,2,3,3,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +17527,51485,Female,Loyal Customer,46,Business travel,Business,1953,3,4,4,4,4,4,3,3,3,2,3,4,3,1,0,0.0,neutral or dissatisfied +17528,64055,Male,Loyal Customer,9,Business travel,Business,2100,4,4,4,4,4,4,4,4,2,2,2,4,3,4,5,25.0,neutral or dissatisfied +17529,53389,Male,Loyal Customer,12,Personal Travel,Eco,1452,0,3,0,1,3,0,3,3,3,2,4,2,2,3,14,1.0,satisfied +17530,115110,Female,Loyal Customer,49,Business travel,Business,2956,5,2,5,5,4,5,4,2,2,2,2,5,2,3,23,17.0,satisfied +17531,112518,Male,Loyal Customer,12,Personal Travel,Eco,967,2,4,1,2,1,3,1,4,3,5,4,1,4,1,131,134.0,neutral or dissatisfied +17532,59878,Female,Loyal Customer,58,Business travel,Business,1023,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +17533,95838,Male,disloyal Customer,28,Business travel,Business,580,4,3,3,2,1,3,1,1,3,4,5,4,5,1,3,4.0,satisfied +17534,92743,Female,Loyal Customer,54,Personal Travel,Eco,1276,2,4,1,1,2,3,5,3,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +17535,92931,Female,disloyal Customer,42,Business travel,Eco,134,2,0,2,4,4,2,4,4,1,4,1,3,3,4,0,0.0,neutral or dissatisfied +17536,94111,Female,Loyal Customer,21,Personal Travel,Business,239,0,3,0,3,3,0,3,3,1,2,4,2,4,3,6,2.0,satisfied +17537,4127,Female,disloyal Customer,20,Business travel,Eco,431,0,0,0,2,3,0,1,3,3,3,5,5,5,3,0,0.0,satisfied +17538,85725,Female,Loyal Customer,43,Business travel,Business,526,2,1,1,1,4,2,2,2,2,2,2,2,2,2,17,17.0,neutral or dissatisfied +17539,92674,Male,Loyal Customer,48,Business travel,Business,507,5,5,5,5,3,5,4,5,5,5,5,3,5,5,0,4.0,satisfied +17540,59229,Female,Loyal Customer,54,Business travel,Business,649,5,5,3,5,5,4,5,2,2,2,2,3,2,5,5,1.0,satisfied +17541,106561,Male,Loyal Customer,48,Business travel,Business,1024,1,1,1,1,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +17542,88117,Female,disloyal Customer,22,Business travel,Business,594,5,0,5,2,3,5,3,3,5,4,5,4,4,3,0,0.0,satisfied +17543,28817,Male,Loyal Customer,35,Business travel,Eco,1050,4,3,3,3,4,4,4,4,2,1,2,5,4,4,0,10.0,satisfied +17544,46976,Male,Loyal Customer,18,Personal Travel,Eco,776,4,3,4,3,3,4,3,3,3,5,3,4,4,3,0,0.0,satisfied +17545,47725,Male,Loyal Customer,44,Business travel,Business,838,4,4,4,4,4,4,4,3,3,3,3,5,3,5,0,0.0,satisfied +17546,20072,Male,Loyal Customer,70,Personal Travel,Eco,723,3,3,3,3,4,3,3,4,2,5,3,3,4,4,3,0.0,neutral or dissatisfied +17547,115619,Female,Loyal Customer,53,Business travel,Business,2187,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +17548,12032,Female,Loyal Customer,37,Business travel,Business,3374,2,1,1,1,4,3,3,2,2,2,2,1,2,3,1,0.0,neutral or dissatisfied +17549,79560,Female,Loyal Customer,46,Business travel,Business,762,4,4,4,4,3,4,4,4,4,4,4,3,4,3,33,13.0,satisfied +17550,92276,Male,Loyal Customer,60,Business travel,Eco,2036,2,4,4,4,3,2,3,3,1,4,3,1,4,3,5,0.0,neutral or dissatisfied +17551,55380,Male,disloyal Customer,16,Business travel,Eco,678,3,3,3,3,1,3,1,1,1,1,4,2,4,1,5,41.0,neutral or dissatisfied +17552,35303,Female,disloyal Customer,42,Business travel,Eco,972,1,1,1,2,4,1,4,4,5,2,4,4,1,4,0,0.0,neutral or dissatisfied +17553,25916,Male,disloyal Customer,44,Business travel,Eco,594,5,2,5,3,2,5,5,2,2,1,2,5,1,2,13,16.0,satisfied +17554,17046,Female,Loyal Customer,30,Business travel,Business,1134,4,3,4,4,4,4,4,4,4,5,3,4,2,4,0,0.0,satisfied +17555,30691,Male,Loyal Customer,48,Business travel,Eco,680,5,3,2,2,5,5,5,5,4,3,1,3,4,5,0,0.0,satisfied +17556,71347,Male,Loyal Customer,19,Personal Travel,Eco,1514,3,5,3,4,3,3,5,3,3,5,3,3,5,3,0,0.0,neutral or dissatisfied +17557,60396,Male,Loyal Customer,13,Personal Travel,Eco,1452,1,1,1,4,5,1,5,5,4,4,3,3,4,5,14,2.0,neutral or dissatisfied +17558,119623,Male,Loyal Customer,43,Personal Travel,Eco Plus,335,3,5,3,4,2,3,2,2,1,5,4,1,3,2,0,0.0,neutral or dissatisfied +17559,24145,Male,Loyal Customer,45,Business travel,Business,302,2,2,2,2,1,4,3,5,5,5,5,5,5,3,0,0.0,satisfied +17560,88317,Female,disloyal Customer,52,Business travel,Business,515,5,5,5,4,3,5,3,3,4,3,5,5,5,3,0,5.0,satisfied +17561,114494,Male,Loyal Customer,51,Business travel,Business,2521,0,0,0,4,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +17562,39496,Male,Loyal Customer,31,Personal Travel,Eco,1368,2,4,2,2,4,2,4,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +17563,56634,Female,Loyal Customer,36,Business travel,Business,2513,1,4,4,4,5,4,4,1,1,1,1,1,1,4,58,87.0,neutral or dissatisfied +17564,5643,Male,Loyal Customer,46,Business travel,Business,2564,1,5,5,5,2,3,2,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +17565,48921,Male,Loyal Customer,40,Business travel,Eco,134,4,1,1,1,4,4,4,4,1,5,2,4,4,4,0,0.0,satisfied +17566,13912,Female,Loyal Customer,30,Business travel,Eco,192,5,1,1,1,5,5,5,5,3,2,2,4,2,5,0,0.0,satisfied +17567,16227,Female,Loyal Customer,47,Business travel,Business,266,3,4,4,4,3,3,3,3,3,3,3,1,3,2,52,49.0,neutral or dissatisfied +17568,86355,Male,Loyal Customer,43,Business travel,Business,3091,2,2,2,2,2,4,5,3,3,3,3,4,3,4,3,0.0,satisfied +17569,99100,Female,disloyal Customer,28,Business travel,Business,419,5,5,5,2,3,5,2,3,5,3,5,4,5,3,1,2.0,satisfied +17570,25119,Female,Loyal Customer,18,Personal Travel,Eco,946,2,5,2,1,2,2,3,2,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +17571,72523,Male,Loyal Customer,39,Business travel,Business,3944,1,1,4,1,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +17572,5279,Female,Loyal Customer,38,Personal Travel,Eco,351,2,5,2,3,5,2,5,5,5,4,5,3,5,5,0,5.0,neutral or dissatisfied +17573,14361,Male,Loyal Customer,33,Personal Travel,Eco Plus,429,4,1,4,4,4,4,4,4,4,5,4,1,3,4,0,0.0,satisfied +17574,16592,Male,Loyal Customer,16,Personal Travel,Eco Plus,872,4,2,4,3,3,4,3,3,4,3,3,2,4,3,37,46.0,neutral or dissatisfied +17575,33193,Male,Loyal Customer,64,Business travel,Eco Plus,102,4,4,4,4,4,4,4,4,5,4,4,2,1,4,34,38.0,satisfied +17576,106204,Male,Loyal Customer,43,Business travel,Business,302,1,1,1,1,5,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +17577,31038,Male,disloyal Customer,23,Business travel,Eco,641,0,0,0,2,1,0,1,1,4,3,3,3,3,1,0,3.0,satisfied +17578,65958,Male,disloyal Customer,60,Business travel,Business,1372,2,2,2,1,5,2,4,5,5,2,5,5,4,5,18,0.0,neutral or dissatisfied +17579,11002,Female,disloyal Customer,20,Business travel,Eco,140,3,0,4,1,2,4,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +17580,37126,Male,disloyal Customer,25,Business travel,Eco,1237,1,1,1,3,1,2,2,3,3,1,2,2,5,2,183,196.0,neutral or dissatisfied +17581,25537,Female,Loyal Customer,26,Personal Travel,Eco,516,3,5,3,4,4,3,4,4,3,5,2,4,3,4,44,51.0,neutral or dissatisfied +17582,96715,Male,disloyal Customer,14,Business travel,Business,696,4,2,4,2,5,4,1,5,4,5,4,4,5,5,0,0.0,satisfied +17583,9871,Male,Loyal Customer,42,Business travel,Business,3968,3,5,5,5,3,4,4,3,3,3,3,2,3,4,0,8.0,neutral or dissatisfied +17584,75877,Male,Loyal Customer,60,Personal Travel,Eco,1972,3,4,3,3,3,3,1,3,1,4,2,3,3,3,0,0.0,neutral or dissatisfied +17585,11143,Male,Loyal Customer,52,Personal Travel,Eco,201,4,5,0,5,4,0,4,4,4,2,5,2,1,4,5,6.0,neutral or dissatisfied +17586,43000,Male,Loyal Customer,34,Business travel,Business,3250,1,1,1,1,4,5,1,4,4,4,5,3,4,3,0,0.0,satisfied +17587,72252,Female,disloyal Customer,22,Business travel,Eco,919,1,1,1,4,5,1,5,5,3,3,4,4,4,5,35,46.0,neutral or dissatisfied +17588,18690,Female,Loyal Customer,24,Personal Travel,Eco,253,4,4,4,5,4,4,4,4,4,2,3,2,2,4,59,49.0,neutral or dissatisfied +17589,19834,Female,Loyal Customer,70,Personal Travel,Eco,413,3,3,3,2,3,5,1,3,3,3,3,3,3,5,3,0.0,neutral or dissatisfied +17590,118232,Male,disloyal Customer,20,Business travel,Eco,1587,3,3,3,3,2,3,2,2,4,2,4,4,3,2,11,0.0,neutral or dissatisfied +17591,116996,Female,disloyal Customer,22,Business travel,Business,338,0,0,0,4,2,0,2,2,5,5,5,5,5,2,37,32.0,satisfied +17592,48694,Female,disloyal Customer,49,Business travel,Business,326,4,4,4,3,4,4,5,4,5,5,5,4,4,4,0,0.0,satisfied +17593,44850,Female,Loyal Customer,40,Business travel,Eco,413,5,2,2,2,5,5,5,5,1,5,5,4,4,5,43,39.0,satisfied +17594,38331,Female,disloyal Customer,39,Business travel,Business,1133,2,2,2,3,3,2,3,3,5,1,5,2,2,3,0,0.0,neutral or dissatisfied +17595,84613,Female,Loyal Customer,40,Business travel,Business,669,5,5,5,5,3,5,5,5,5,5,5,3,5,4,11,3.0,satisfied +17596,73792,Female,Loyal Customer,45,Business travel,Eco Plus,192,3,5,4,5,3,4,3,3,3,3,3,1,3,3,24,23.0,neutral or dissatisfied +17597,96447,Female,Loyal Customer,27,Business travel,Business,1608,3,2,3,3,4,4,4,4,3,2,5,3,5,4,0,0.0,satisfied +17598,86175,Male,Loyal Customer,55,Business travel,Business,2044,3,3,5,3,4,5,5,4,4,4,4,5,4,4,30,39.0,satisfied +17599,26294,Female,Loyal Customer,23,Business travel,Eco,1199,5,4,4,4,5,5,4,5,1,1,1,3,1,5,1,0.0,satisfied +17600,34594,Male,disloyal Customer,63,Business travel,Eco,998,3,4,4,1,2,4,2,2,1,5,2,2,2,2,23,30.0,neutral or dissatisfied +17601,15342,Male,Loyal Customer,42,Business travel,Business,2944,2,2,2,2,5,5,4,5,5,5,4,5,5,5,0,0.0,satisfied +17602,125398,Male,Loyal Customer,41,Business travel,Business,1040,5,5,5,5,3,2,2,5,5,5,5,4,5,3,0,,satisfied +17603,44784,Male,disloyal Customer,27,Business travel,Eco,1250,3,3,3,4,4,3,2,4,1,3,4,2,4,4,1,6.0,neutral or dissatisfied +17604,19745,Female,Loyal Customer,34,Personal Travel,Eco Plus,409,2,1,2,3,3,2,3,3,3,1,4,1,3,3,1,0.0,neutral or dissatisfied +17605,67414,Male,Loyal Customer,72,Business travel,Eco,592,2,1,1,1,1,2,1,1,2,5,2,2,2,1,17,105.0,neutral or dissatisfied +17606,45596,Male,Loyal Customer,54,Business travel,Eco,230,5,2,2,2,4,5,4,4,4,2,5,1,5,4,0,0.0,satisfied +17607,5028,Male,Loyal Customer,37,Business travel,Business,3236,2,3,4,3,1,3,3,2,2,2,2,1,2,4,93,102.0,neutral or dissatisfied +17608,6845,Female,disloyal Customer,17,Business travel,Eco Plus,223,4,1,4,3,5,4,5,5,4,1,4,2,3,5,0,0.0,neutral or dissatisfied +17609,91447,Female,Loyal Customer,46,Business travel,Business,859,4,4,4,4,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +17610,28731,Male,disloyal Customer,28,Business travel,Eco,2149,3,3,3,5,3,3,3,3,3,2,4,5,3,3,0,0.0,neutral or dissatisfied +17611,99290,Male,Loyal Customer,18,Personal Travel,Eco,935,3,5,3,3,5,3,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +17612,80838,Female,disloyal Customer,21,Business travel,Business,484,4,4,4,4,5,4,5,5,3,4,4,5,5,5,0,0.0,satisfied +17613,55233,Female,Loyal Customer,34,Business travel,Business,1009,3,3,3,3,3,4,4,3,3,3,3,1,3,1,11,8.0,neutral or dissatisfied +17614,88669,Female,Loyal Customer,45,Personal Travel,Eco,271,1,4,1,4,3,4,4,5,5,1,4,5,5,3,3,0.0,neutral or dissatisfied +17615,81738,Male,Loyal Customer,52,Business travel,Business,3761,1,1,1,1,4,4,4,5,5,4,5,3,5,5,0,0.0,satisfied +17616,96570,Female,disloyal Customer,72,Business travel,Business,333,5,5,5,1,3,5,3,3,3,2,4,3,4,3,0,0.0,satisfied +17617,126069,Female,disloyal Customer,25,Business travel,Business,631,2,0,2,4,4,2,4,4,5,2,5,5,5,4,0,9.0,neutral or dissatisfied +17618,49652,Male,Loyal Customer,40,Business travel,Business,193,2,2,5,2,3,1,2,5,5,5,5,3,5,1,12,12.0,satisfied +17619,94283,Male,Loyal Customer,32,Business travel,Business,2220,4,4,4,4,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +17620,13818,Female,Loyal Customer,24,Business travel,Business,2604,5,5,1,5,5,4,5,5,3,1,2,3,3,5,9,9.0,satisfied +17621,55892,Female,Loyal Customer,41,Business travel,Business,733,3,4,4,4,2,3,4,3,3,3,3,1,3,2,0,13.0,neutral or dissatisfied +17622,124480,Female,Loyal Customer,60,Business travel,Business,2146,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +17623,106962,Male,Loyal Customer,51,Business travel,Business,2444,2,2,2,2,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +17624,50133,Male,Loyal Customer,35,Business travel,Business,308,0,1,1,2,4,4,2,5,5,5,5,3,5,4,0,0.0,satisfied +17625,127086,Male,Loyal Customer,32,Business travel,Business,304,3,4,4,4,3,3,3,3,2,5,3,3,3,3,0,0.0,neutral or dissatisfied +17626,22059,Female,Loyal Customer,53,Business travel,Business,1580,1,1,1,1,5,3,5,5,5,5,5,2,5,4,2,1.0,satisfied +17627,115458,Female,Loyal Customer,48,Business travel,Business,358,1,1,1,1,3,5,5,3,3,3,3,5,3,4,16,10.0,satisfied +17628,129506,Female,Loyal Customer,38,Business travel,Eco,346,2,5,5,5,2,2,2,2,4,2,1,5,5,2,0,0.0,satisfied +17629,114674,Female,Loyal Customer,45,Business travel,Business,3567,0,0,0,2,4,4,5,4,4,4,4,4,4,3,1,0.0,satisfied +17630,89254,Male,Loyal Customer,44,Business travel,Business,2262,2,2,2,2,5,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +17631,53613,Female,Loyal Customer,48,Business travel,Eco,1874,2,4,3,4,2,4,2,2,2,2,2,1,2,1,5,0.0,satisfied +17632,42758,Male,Loyal Customer,40,Business travel,Eco,493,1,3,3,3,1,1,1,1,1,5,4,1,3,1,0,0.0,neutral or dissatisfied +17633,41737,Female,Loyal Customer,29,Business travel,Business,2157,4,4,4,4,5,5,5,5,3,1,4,2,4,5,0,0.0,satisfied +17634,96559,Female,disloyal Customer,38,Business travel,Business,436,2,2,2,1,3,2,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +17635,104002,Male,Loyal Customer,40,Business travel,Eco,963,5,4,4,4,5,5,5,5,4,1,2,3,4,5,4,0.0,satisfied +17636,108653,Female,Loyal Customer,33,Business travel,Business,1747,5,5,5,5,3,5,5,5,5,5,5,5,5,5,22,37.0,satisfied +17637,358,Female,disloyal Customer,39,Business travel,Business,247,2,2,2,4,5,2,5,5,4,4,4,5,4,5,42,96.0,neutral or dissatisfied +17638,57303,Male,Loyal Customer,10,Personal Travel,Business,236,4,5,4,4,3,4,3,3,5,2,5,3,5,3,0,0.0,satisfied +17639,107161,Female,Loyal Customer,57,Business travel,Business,1631,2,2,2,2,3,5,4,5,5,5,5,3,5,5,10,3.0,satisfied +17640,29919,Male,Loyal Customer,38,Business travel,Business,3828,5,5,5,5,5,2,2,5,5,5,5,5,5,5,11,18.0,satisfied +17641,76267,Female,disloyal Customer,16,Business travel,Eco,1927,1,1,1,4,5,1,4,5,1,4,4,3,3,5,55,36.0,neutral or dissatisfied +17642,15007,Male,Loyal Customer,57,Personal Travel,Business,557,2,2,2,3,1,4,3,3,3,2,2,3,3,2,0,0.0,neutral or dissatisfied +17643,21360,Male,Loyal Customer,68,Personal Travel,Eco,674,3,5,3,3,3,3,3,3,3,4,5,3,4,3,24,24.0,neutral or dissatisfied +17644,122027,Female,Loyal Customer,33,Business travel,Business,130,2,2,4,2,4,5,5,4,4,4,4,5,4,3,0,14.0,satisfied +17645,54945,Male,Loyal Customer,11,Personal Travel,Business,1303,3,4,3,2,2,3,5,2,3,2,5,4,5,2,0,0.0,neutral or dissatisfied +17646,30091,Female,Loyal Customer,61,Personal Travel,Eco,503,4,3,4,3,4,4,4,1,1,4,1,1,1,4,0,0.0,neutral or dissatisfied +17647,23129,Female,Loyal Customer,56,Business travel,Business,3900,4,1,4,4,2,5,1,5,5,4,5,3,5,4,103,85.0,satisfied +17648,12875,Female,disloyal Customer,36,Business travel,Eco,456,2,0,2,2,1,2,1,1,4,3,1,4,1,1,1,13.0,neutral or dissatisfied +17649,125440,Male,Loyal Customer,41,Business travel,Business,2917,4,4,4,4,4,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +17650,84725,Male,disloyal Customer,24,Business travel,Eco,547,4,0,4,2,3,4,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +17651,78863,Male,Loyal Customer,57,Business travel,Business,2617,2,2,2,2,2,4,4,4,4,4,4,4,4,5,0,53.0,satisfied +17652,46569,Male,Loyal Customer,47,Business travel,Business,2848,3,3,3,3,5,4,3,5,5,5,5,3,5,5,54,82.0,satisfied +17653,47503,Male,Loyal Customer,47,Personal Travel,Eco,590,3,1,2,3,1,2,1,1,3,1,3,2,4,1,0,0.0,neutral or dissatisfied +17654,124593,Male,Loyal Customer,37,Business travel,Eco,100,3,5,5,5,3,2,3,3,2,3,4,1,4,3,7,24.0,neutral or dissatisfied +17655,6549,Female,disloyal Customer,27,Business travel,Business,473,4,4,4,3,1,4,1,1,4,2,4,3,5,1,62,60.0,satisfied +17656,20009,Female,Loyal Customer,67,Personal Travel,Eco,599,3,4,3,2,3,1,4,4,4,3,4,4,4,5,20,30.0,neutral or dissatisfied +17657,90578,Male,disloyal Customer,37,Business travel,Business,442,4,4,4,1,1,4,1,1,3,2,5,4,4,1,70,62.0,satisfied +17658,69769,Male,Loyal Customer,58,Personal Travel,Eco Plus,1085,3,2,3,4,1,3,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +17659,73689,Male,Loyal Customer,70,Business travel,Eco,204,3,5,5,5,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +17660,72859,Male,Loyal Customer,29,Business travel,Business,700,2,4,4,4,2,2,2,2,2,4,3,1,3,2,3,8.0,neutral or dissatisfied +17661,77635,Male,Loyal Customer,50,Business travel,Business,2828,1,1,1,1,4,5,4,4,4,5,4,4,4,5,0,11.0,satisfied +17662,42186,Male,Loyal Customer,36,Business travel,Business,817,3,3,3,3,3,3,1,5,5,5,5,4,5,3,0,0.0,satisfied +17663,115522,Female,disloyal Customer,17,Business travel,Business,372,4,5,4,2,3,4,3,3,5,2,5,5,5,3,0,0.0,satisfied +17664,123256,Female,Loyal Customer,43,Personal Travel,Eco,650,2,4,2,3,5,5,3,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +17665,23686,Male,Loyal Customer,50,Business travel,Eco,73,4,1,1,1,4,4,4,4,1,1,3,1,4,4,0,0.0,neutral or dissatisfied +17666,47259,Male,Loyal Customer,36,Business travel,Business,184,2,2,2,2,2,5,4,5,5,5,5,5,5,5,28,0.0,satisfied +17667,81726,Female,Loyal Customer,31,Personal Travel,Business,1310,4,4,4,3,5,4,5,5,5,5,4,3,5,5,0,0.0,satisfied +17668,100763,Female,Loyal Customer,44,Business travel,Business,1504,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +17669,114987,Female,Loyal Customer,35,Business travel,Business,325,2,1,1,1,2,3,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +17670,1117,Male,Loyal Customer,29,Personal Travel,Eco,229,2,5,2,3,1,2,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +17671,76123,Male,Loyal Customer,59,Business travel,Business,2376,1,1,1,1,5,5,5,4,4,4,4,3,4,5,7,11.0,satisfied +17672,118813,Female,Loyal Customer,52,Business travel,Business,651,3,3,3,3,3,5,5,3,3,2,3,3,3,3,0,1.0,satisfied +17673,7793,Male,Loyal Customer,60,Business travel,Business,3202,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +17674,73161,Male,Loyal Customer,31,Business travel,Business,1924,2,2,4,2,2,2,2,2,5,2,5,5,4,2,0,0.0,satisfied +17675,125363,Female,Loyal Customer,41,Personal Travel,Eco,599,3,4,3,1,4,3,4,4,4,4,4,5,4,4,56,86.0,neutral or dissatisfied +17676,18180,Male,Loyal Customer,51,Business travel,Business,224,4,4,4,4,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +17677,16050,Male,Loyal Customer,61,Business travel,Business,2273,4,4,5,4,4,3,1,4,4,4,4,1,4,5,0,0.0,satisfied +17678,63417,Female,Loyal Customer,65,Personal Travel,Eco,337,2,2,2,3,1,3,3,2,2,2,2,2,2,2,6,12.0,neutral or dissatisfied +17679,107572,Male,Loyal Customer,17,Personal Travel,Eco,1680,1,5,1,3,3,1,3,3,1,5,2,2,4,3,43,49.0,neutral or dissatisfied +17680,7278,Male,Loyal Customer,45,Personal Travel,Eco,139,4,0,4,4,3,4,3,3,4,3,5,4,5,3,11,7.0,neutral or dissatisfied +17681,66861,Female,Loyal Customer,54,Personal Travel,Eco,731,4,3,4,5,5,4,4,3,3,4,1,5,3,5,3,0.0,neutral or dissatisfied +17682,78425,Male,Loyal Customer,52,Business travel,Business,3067,1,1,1,1,5,5,5,5,5,4,5,3,5,3,6,0.0,satisfied +17683,69578,Female,Loyal Customer,20,Business travel,Eco,2475,5,5,3,3,5,4,5,3,2,4,5,5,5,5,0,0.0,satisfied +17684,12037,Female,Loyal Customer,37,Business travel,Eco,376,5,5,5,5,5,5,5,5,1,1,4,3,2,5,0,0.0,satisfied +17685,129678,Female,Loyal Customer,47,Business travel,Business,2815,3,3,3,3,2,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +17686,16704,Male,Loyal Customer,51,Business travel,Business,284,0,0,0,2,1,3,1,5,5,5,5,5,5,5,65,70.0,satisfied +17687,5874,Female,Loyal Customer,41,Business travel,Business,67,4,4,4,4,4,4,4,4,4,4,5,5,4,4,0,1.0,satisfied +17688,28267,Male,Loyal Customer,24,Business travel,Eco Plus,1542,5,4,4,4,5,5,5,5,2,1,5,2,3,5,0,0.0,satisfied +17689,72873,Male,Loyal Customer,64,Personal Travel,Eco Plus,700,1,5,1,3,1,1,1,1,2,4,4,5,5,1,5,0.0,neutral or dissatisfied +17690,2058,Female,disloyal Customer,27,Business travel,Eco,785,4,4,4,4,2,4,2,2,4,3,4,2,4,2,18,10.0,neutral or dissatisfied +17691,8323,Female,Loyal Customer,47,Personal Travel,Eco Plus,294,4,4,4,5,3,4,5,1,1,4,1,5,1,5,7,9.0,neutral or dissatisfied +17692,109222,Male,disloyal Customer,16,Business travel,Eco,612,1,3,1,3,4,1,5,4,3,5,4,2,3,4,37,37.0,neutral or dissatisfied +17693,114829,Female,Loyal Customer,44,Business travel,Business,3288,1,1,1,1,2,5,5,4,4,4,4,4,4,4,18,13.0,satisfied +17694,75313,Male,disloyal Customer,34,Business travel,Business,2504,3,3,3,1,3,3,3,3,2,5,5,3,3,3,0,0.0,neutral or dissatisfied +17695,59865,Male,Loyal Customer,36,Business travel,Eco,1065,3,3,3,3,3,3,3,3,4,2,3,1,4,3,0,0.0,neutral or dissatisfied +17696,29654,Female,Loyal Customer,49,Personal Travel,Eco,1448,2,5,2,3,2,3,4,2,2,2,2,1,2,3,8,0.0,neutral or dissatisfied +17697,8328,Female,disloyal Customer,13,Business travel,Eco,661,2,0,3,5,3,3,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +17698,3941,Female,Loyal Customer,26,Business travel,Business,3342,1,1,1,1,2,3,2,2,3,3,5,3,4,2,0,0.0,satisfied +17699,80147,Female,Loyal Customer,56,Business travel,Business,2586,3,3,3,3,4,4,4,5,4,5,4,4,3,4,0,0.0,satisfied +17700,28890,Male,Loyal Customer,37,Business travel,Eco,937,4,1,1,1,4,4,4,4,1,4,1,1,2,4,15,4.0,satisfied +17701,55480,Female,Loyal Customer,38,Business travel,Eco Plus,1825,2,4,4,4,2,2,2,2,4,4,3,2,4,2,0,0.0,neutral or dissatisfied +17702,10690,Male,Loyal Customer,56,Business travel,Business,2016,3,2,2,2,5,2,2,3,3,3,3,1,3,4,21,32.0,neutral or dissatisfied +17703,65485,Female,Loyal Customer,63,Personal Travel,Eco,1303,1,5,1,3,4,3,5,2,2,1,2,4,2,4,7,0.0,neutral or dissatisfied +17704,75945,Female,disloyal Customer,22,Business travel,Business,297,5,0,5,3,2,5,2,2,4,2,5,3,5,2,0,0.0,satisfied +17705,40790,Female,Loyal Customer,47,Business travel,Eco,588,3,1,1,1,3,5,3,3,3,3,3,3,3,2,0,9.0,satisfied +17706,109408,Female,Loyal Customer,41,Business travel,Business,861,3,3,3,3,3,4,4,5,5,5,5,4,5,4,40,29.0,satisfied +17707,2491,Female,Loyal Customer,39,Business travel,Eco,1379,2,2,2,2,2,2,2,2,4,2,4,1,4,2,39,35.0,neutral or dissatisfied +17708,9265,Male,Loyal Customer,59,Business travel,Business,3124,2,2,2,2,5,4,5,5,5,5,5,3,5,5,15,0.0,satisfied +17709,74228,Male,disloyal Customer,19,Business travel,Eco,1007,3,3,3,2,2,3,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +17710,55559,Female,disloyal Customer,25,Business travel,Eco Plus,550,3,3,3,4,1,3,1,1,4,5,3,3,4,1,39,47.0,neutral or dissatisfied +17711,79817,Male,disloyal Customer,16,Business travel,Business,1089,0,3,0,1,4,0,4,4,3,4,5,3,5,4,30,1.0,satisfied +17712,116849,Female,Loyal Customer,47,Business travel,Business,325,1,1,1,1,2,5,5,5,5,5,5,4,5,4,7,5.0,satisfied +17713,73225,Female,Loyal Customer,30,Business travel,Business,946,1,2,2,2,1,1,1,1,2,2,3,3,3,1,43,41.0,neutral or dissatisfied +17714,125635,Male,disloyal Customer,39,Business travel,Eco,899,3,4,4,3,3,4,3,3,1,2,4,2,4,3,0,0.0,neutral or dissatisfied +17715,20637,Female,Loyal Customer,28,Business travel,Business,793,5,5,5,5,4,4,4,4,1,5,1,1,3,4,57,67.0,satisfied +17716,59874,Male,Loyal Customer,58,Business travel,Business,2615,3,3,3,3,5,4,5,4,4,5,4,3,4,4,19,16.0,satisfied +17717,71251,Female,Loyal Customer,52,Business travel,Business,733,3,3,3,3,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +17718,127990,Male,Loyal Customer,23,Personal Travel,Eco Plus,1149,2,5,2,1,3,2,2,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +17719,87671,Female,Loyal Customer,49,Business travel,Business,3670,1,3,3,3,3,3,4,1,1,1,1,1,1,4,9,0.0,neutral or dissatisfied +17720,68042,Female,Loyal Customer,48,Business travel,Business,868,5,5,2,5,5,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +17721,77542,Male,Loyal Customer,24,Business travel,Business,986,1,1,1,1,4,4,4,4,4,2,4,3,5,4,0,6.0,satisfied +17722,26838,Female,disloyal Customer,22,Business travel,Eco,224,5,0,5,2,2,5,2,2,1,5,1,5,1,2,0,0.0,satisfied +17723,66762,Male,Loyal Customer,51,Personal Travel,Eco,802,3,5,3,3,1,3,1,1,2,2,5,2,1,1,73,49.0,neutral or dissatisfied +17724,91085,Male,Loyal Customer,38,Personal Travel,Eco,271,2,2,2,3,5,2,5,5,3,3,3,1,3,5,17,11.0,neutral or dissatisfied +17725,62283,Male,Loyal Customer,54,Business travel,Business,2366,3,3,3,3,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +17726,9236,Male,Loyal Customer,43,Business travel,Business,3114,4,4,4,4,2,1,3,5,5,5,3,4,5,3,0,0.0,satisfied +17727,87650,Female,Loyal Customer,47,Business travel,Business,606,1,1,1,1,2,4,5,4,4,4,4,4,4,5,2,8.0,satisfied +17728,16885,Male,Loyal Customer,22,Business travel,Business,708,2,2,2,2,5,5,5,5,2,2,5,4,3,5,0,0.0,satisfied +17729,98069,Female,Loyal Customer,43,Business travel,Eco,1449,2,1,1,1,5,3,4,2,2,2,2,3,2,4,0,6.0,neutral or dissatisfied +17730,33154,Male,Loyal Customer,64,Personal Travel,Eco,163,3,5,3,2,2,3,2,2,4,4,4,3,4,2,0,9.0,neutral or dissatisfied +17731,33902,Female,Loyal Customer,63,Personal Travel,Eco,1226,3,4,3,3,3,3,3,1,1,3,3,4,1,1,18,0.0,neutral or dissatisfied +17732,121976,Male,Loyal Customer,57,Business travel,Business,2880,2,2,2,2,5,5,5,5,5,5,5,4,5,5,15,23.0,satisfied +17733,11880,Male,Loyal Customer,9,Personal Travel,Eco,912,2,5,2,3,2,1,2,5,3,5,5,2,3,2,181,170.0,neutral or dissatisfied +17734,70826,Male,Loyal Customer,9,Personal Travel,Eco Plus,624,3,4,3,3,1,3,5,1,5,4,4,1,1,1,0,0.0,neutral or dissatisfied +17735,92037,Male,Loyal Customer,19,Business travel,Business,1589,4,4,4,4,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +17736,34324,Male,Loyal Customer,50,Personal Travel,Eco,2454,2,4,2,5,2,2,2,2,5,3,4,3,4,2,21,0.0,neutral or dissatisfied +17737,103837,Male,disloyal Customer,36,Business travel,Eco,882,3,3,3,4,4,3,4,4,2,2,4,3,4,4,0,0.0,neutral or dissatisfied +17738,101325,Female,Loyal Customer,22,Personal Travel,Eco,986,4,5,4,3,5,4,5,5,4,4,5,3,4,5,8,5.0,neutral or dissatisfied +17739,92972,Female,Loyal Customer,52,Personal Travel,Business,738,2,5,2,4,3,4,4,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +17740,46060,Female,Loyal Customer,49,Business travel,Eco Plus,964,5,3,1,1,5,1,1,5,5,5,5,2,5,3,0,1.0,satisfied +17741,82781,Male,Loyal Customer,40,Business travel,Business,1988,1,1,1,1,2,4,5,5,5,5,5,3,5,3,22,7.0,satisfied +17742,9441,Female,Loyal Customer,34,Business travel,Eco,299,2,2,2,2,2,2,2,2,3,4,3,2,2,2,0,8.0,neutral or dissatisfied +17743,29201,Female,Loyal Customer,51,Personal Travel,Eco Plus,679,2,2,2,4,2,3,4,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +17744,6324,Female,Loyal Customer,49,Business travel,Business,296,3,3,4,3,2,5,5,4,4,4,4,5,4,3,12,19.0,satisfied +17745,57681,Female,Loyal Customer,53,Business travel,Business,1769,3,3,3,3,4,4,4,5,5,5,5,3,5,3,3,0.0,satisfied +17746,87467,Male,disloyal Customer,26,Business travel,Business,321,1,4,1,4,3,1,3,3,5,2,4,4,4,3,0,5.0,neutral or dissatisfied +17747,11191,Male,Loyal Customer,55,Personal Travel,Eco,312,1,4,1,4,3,1,3,3,3,2,5,4,4,3,106,101.0,neutral or dissatisfied +17748,127356,Female,Loyal Customer,66,Personal Travel,Eco,507,2,4,2,3,2,4,5,2,2,2,2,3,2,5,0,0.0,neutral or dissatisfied +17749,46169,Male,Loyal Customer,67,Personal Travel,Eco,604,2,4,2,2,3,2,3,3,3,4,5,5,5,3,17,17.0,neutral or dissatisfied +17750,75056,Male,Loyal Customer,18,Personal Travel,Eco,1592,1,4,1,2,1,1,1,1,3,4,4,5,5,1,0,0.0,neutral or dissatisfied +17751,67543,Male,Loyal Customer,41,Personal Travel,Business,1205,2,4,2,4,3,2,3,2,2,2,2,2,2,1,10,14.0,neutral or dissatisfied +17752,35512,Male,Loyal Customer,38,Personal Travel,Eco,1076,1,3,1,3,2,1,4,2,2,4,3,1,4,2,4,24.0,neutral or dissatisfied +17753,94784,Male,Loyal Customer,41,Business travel,Eco,239,1,2,2,2,1,1,1,1,4,2,4,3,3,1,54,51.0,neutral or dissatisfied +17754,47370,Female,Loyal Customer,18,Business travel,Eco,574,4,5,5,5,4,4,2,4,4,4,3,1,4,4,0,0.0,neutral or dissatisfied +17755,54809,Male,Loyal Customer,51,Business travel,Eco,641,5,5,5,5,4,5,4,4,5,5,3,4,1,4,0,0.0,satisfied +17756,116069,Female,Loyal Customer,14,Personal Travel,Eco,308,4,5,4,3,4,4,5,4,4,5,4,3,4,4,55,52.0,neutral or dissatisfied +17757,2896,Male,Loyal Customer,12,Personal Travel,Eco,409,2,5,3,2,2,3,2,2,3,3,4,3,4,2,10,25.0,neutral or dissatisfied +17758,68221,Female,disloyal Customer,28,Business travel,Business,631,5,5,5,2,5,5,5,5,3,4,5,4,4,5,0,0.0,satisfied +17759,25187,Male,Loyal Customer,34,Business travel,Business,577,3,4,4,4,5,4,4,3,3,2,3,1,3,3,27,18.0,neutral or dissatisfied +17760,109848,Female,Loyal Customer,57,Business travel,Business,1101,2,2,2,2,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +17761,21661,Male,disloyal Customer,30,Business travel,Eco,746,4,4,4,2,1,4,1,1,2,5,5,1,2,1,11,5.0,neutral or dissatisfied +17762,53996,Male,Loyal Customer,36,Personal Travel,Eco,1825,1,1,1,4,4,1,4,4,2,5,2,4,4,4,4,12.0,neutral or dissatisfied +17763,94559,Female,disloyal Customer,22,Business travel,Eco,239,3,1,3,3,2,3,2,2,3,5,3,4,2,2,48,41.0,neutral or dissatisfied +17764,113194,Male,disloyal Customer,37,Business travel,Business,197,5,5,5,5,4,5,4,4,5,4,4,3,5,4,10,8.0,satisfied +17765,67201,Female,disloyal Customer,43,Personal Travel,Eco,929,4,5,5,1,5,5,5,5,4,3,4,5,4,5,0,3.0,neutral or dissatisfied +17766,20819,Female,Loyal Customer,31,Business travel,Business,534,5,5,5,5,4,4,4,4,3,3,5,5,3,4,0,0.0,satisfied +17767,26354,Male,Loyal Customer,53,Business travel,Business,3435,1,1,1,1,2,4,5,4,4,5,4,5,4,3,13,2.0,satisfied +17768,48202,Female,disloyal Customer,20,Business travel,Eco,236,2,2,2,1,2,2,2,2,3,1,2,2,1,2,0,40.0,neutral or dissatisfied +17769,73389,Female,Loyal Customer,49,Business travel,Business,1005,3,3,2,3,5,4,4,3,3,4,3,3,3,4,0,0.0,satisfied +17770,111396,Female,Loyal Customer,7,Personal Travel,Eco,1180,4,4,4,2,3,4,3,3,4,2,4,5,5,3,0,0.0,satisfied +17771,517,Male,Loyal Customer,50,Business travel,Business,1935,0,0,0,4,5,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +17772,53633,Female,Loyal Customer,22,Personal Travel,Eco,1874,2,2,2,3,4,2,4,4,4,2,4,3,4,4,17,0.0,neutral or dissatisfied +17773,45175,Female,Loyal Customer,17,Personal Travel,Eco,130,4,4,4,3,1,4,1,1,2,5,4,3,4,1,0,3.0,neutral or dissatisfied +17774,118671,Female,disloyal Customer,20,Business travel,Eco,370,4,2,4,3,2,4,2,2,3,4,4,1,3,2,23,19.0,neutral or dissatisfied +17775,111388,Female,Loyal Customer,34,Business travel,Business,2077,3,3,3,3,1,4,1,4,4,4,4,5,4,1,8,54.0,satisfied +17776,73539,Male,disloyal Customer,19,Business travel,Eco,594,2,1,3,3,4,3,4,4,4,4,4,2,4,4,14,12.0,neutral or dissatisfied +17777,94581,Female,Loyal Customer,43,Business travel,Business,1590,4,4,5,4,2,5,5,4,4,4,4,5,4,3,1,0.0,satisfied +17778,66776,Female,disloyal Customer,17,Business travel,Eco,802,2,2,2,2,1,2,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +17779,34202,Male,Loyal Customer,63,Personal Travel,Eco,1129,3,4,3,3,4,3,4,4,4,3,4,3,4,4,3,4.0,neutral or dissatisfied +17780,13171,Male,Loyal Customer,53,Personal Travel,Eco Plus,427,3,5,3,1,3,3,3,3,4,3,1,3,4,3,20,22.0,neutral or dissatisfied +17781,25553,Male,Loyal Customer,44,Personal Travel,Eco Plus,547,2,3,2,4,3,2,3,3,1,4,4,4,3,3,6,16.0,neutral or dissatisfied +17782,2692,Female,Loyal Customer,60,Business travel,Business,562,1,1,1,1,5,4,5,5,5,5,5,4,5,5,79,89.0,satisfied +17783,91846,Female,Loyal Customer,57,Business travel,Business,1797,2,2,3,2,5,3,4,3,3,3,3,3,3,5,7,0.0,satisfied +17784,28347,Female,Loyal Customer,64,Personal Travel,Eco,867,1,1,1,3,1,4,4,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +17785,46929,Female,disloyal Customer,37,Business travel,Eco,444,2,1,2,3,5,2,5,5,2,3,4,4,3,5,12,0.0,neutral or dissatisfied +17786,107038,Female,Loyal Customer,60,Business travel,Business,395,3,3,3,3,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +17787,113152,Male,disloyal Customer,16,Business travel,Eco,889,3,3,3,3,1,3,1,1,1,5,4,1,4,1,6,5.0,neutral or dissatisfied +17788,54385,Male,disloyal Customer,27,Business travel,Eco,305,4,0,4,1,3,4,3,3,1,5,3,4,5,3,0,0.0,satisfied +17789,9079,Male,Loyal Customer,64,Personal Travel,Eco,173,3,2,3,3,4,3,4,4,2,2,3,1,2,4,9,6.0,neutral or dissatisfied +17790,9142,Male,Loyal Customer,51,Business travel,Business,2925,0,0,0,4,2,4,4,5,5,3,3,3,5,3,0,10.0,satisfied +17791,25176,Male,Loyal Customer,25,Business travel,Business,2021,5,5,5,5,3,3,3,3,5,3,4,3,2,3,29,21.0,satisfied +17792,38877,Female,Loyal Customer,50,Business travel,Business,2480,3,3,3,3,5,3,1,4,4,4,4,5,4,2,0,0.0,satisfied +17793,44506,Female,Loyal Customer,44,Personal Travel,Eco,503,3,4,3,2,3,5,5,2,2,3,2,5,2,3,0,0.0,neutral or dissatisfied +17794,94570,Female,Loyal Customer,56,Business travel,Business,3587,1,1,2,1,4,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +17795,51116,Male,Loyal Customer,70,Personal Travel,Eco,109,3,5,3,1,5,3,5,5,1,1,5,1,5,5,0,0.0,neutral or dissatisfied +17796,51395,Female,Loyal Customer,38,Personal Travel,Eco Plus,308,2,5,2,4,1,2,1,1,3,2,1,2,5,1,19,14.0,neutral or dissatisfied +17797,111366,Male,Loyal Customer,56,Business travel,Business,3700,4,4,5,4,4,4,4,5,5,5,5,5,5,4,8,3.0,satisfied +17798,92782,Female,Loyal Customer,64,Personal Travel,Eco,1671,2,1,2,1,4,1,2,2,2,2,2,2,2,2,26,10.0,neutral or dissatisfied +17799,71687,Female,Loyal Customer,25,Personal Travel,Eco,1197,4,5,4,1,2,4,2,2,4,4,5,3,4,2,9,0.0,neutral or dissatisfied +17800,92296,Female,Loyal Customer,37,Personal Travel,Eco,1814,3,5,3,1,3,3,3,3,4,4,3,4,5,3,0,0.0,neutral or dissatisfied +17801,93720,Female,Loyal Customer,51,Business travel,Business,630,4,4,4,4,5,3,3,4,4,4,4,4,4,1,2,8.0,neutral or dissatisfied +17802,95799,Female,Loyal Customer,57,Business travel,Business,2417,4,4,3,4,4,5,5,5,5,4,5,4,5,3,12,18.0,satisfied +17803,42399,Male,Loyal Customer,59,Business travel,Eco Plus,329,4,4,4,4,4,4,4,4,3,1,3,1,5,4,0,0.0,satisfied +17804,21287,Male,Loyal Customer,24,Business travel,Business,1710,5,5,5,5,4,4,4,4,4,1,2,3,4,4,32,12.0,satisfied +17805,112043,Female,disloyal Customer,45,Business travel,Eco,1123,4,4,4,2,2,4,4,2,2,1,2,4,2,2,27,24.0,neutral or dissatisfied +17806,94773,Female,Loyal Customer,32,Business travel,Eco,192,3,1,5,1,3,3,3,3,1,1,4,4,4,3,4,4.0,neutral or dissatisfied +17807,91314,Female,Loyal Customer,53,Business travel,Business,442,4,4,4,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +17808,56858,Female,Loyal Customer,34,Business travel,Business,2565,1,1,1,1,4,3,3,3,5,3,4,3,5,3,0,0.0,satisfied +17809,5038,Female,Loyal Customer,48,Business travel,Business,3310,1,1,5,1,3,4,5,4,4,4,4,3,4,5,1,40.0,satisfied +17810,125989,Male,Loyal Customer,66,Personal Travel,Business,507,2,5,3,5,5,5,5,4,4,3,4,3,4,5,0,3.0,neutral or dissatisfied +17811,70857,Female,Loyal Customer,47,Business travel,Business,761,2,2,2,2,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +17812,25584,Female,disloyal Customer,25,Business travel,Eco,696,4,4,4,4,4,4,4,4,3,4,4,2,3,4,28,32.0,neutral or dissatisfied +17813,111089,Female,Loyal Customer,9,Personal Travel,Eco,319,2,4,2,3,4,2,4,4,1,5,3,2,4,4,16,6.0,neutral or dissatisfied +17814,60312,Female,disloyal Customer,24,Business travel,Eco,406,4,5,4,3,2,4,2,2,5,3,4,5,5,2,0,0.0,satisfied +17815,28143,Male,Loyal Customer,34,Business travel,Eco,859,5,2,5,2,5,5,5,5,3,3,1,3,3,5,0,0.0,satisfied +17816,92747,Male,Loyal Customer,22,Personal Travel,Eco,1276,2,5,2,3,4,2,4,4,3,4,3,3,4,4,0,0.0,neutral or dissatisfied +17817,121385,Male,Loyal Customer,17,Personal Travel,Eco,2279,2,4,2,1,5,2,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +17818,74883,Male,Loyal Customer,57,Business travel,Business,2586,3,3,3,3,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +17819,33757,Male,Loyal Customer,58,Business travel,Eco,266,4,1,1,1,3,4,3,3,4,4,3,2,3,3,14,40.0,neutral or dissatisfied +17820,24954,Female,Loyal Customer,19,Personal Travel,Eco,1747,4,4,3,1,4,3,4,4,5,3,4,5,5,4,0,0.0,satisfied +17821,75874,Female,disloyal Customer,28,Business travel,Eco,1972,4,5,5,4,4,4,4,4,3,2,2,3,3,4,0,0.0,neutral or dissatisfied +17822,20440,Female,Loyal Customer,53,Business travel,Eco,177,5,2,2,2,1,2,5,5,5,5,5,2,5,5,0,0.0,satisfied +17823,59335,Male,Loyal Customer,26,Business travel,Business,2338,4,4,4,4,4,4,4,4,5,5,3,4,4,4,18,0.0,satisfied +17824,21865,Female,Loyal Customer,61,Business travel,Eco,551,4,1,1,1,4,3,4,3,3,4,3,2,3,3,65,64.0,neutral or dissatisfied +17825,81730,Female,Loyal Customer,47,Business travel,Business,1416,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +17826,125002,Female,Loyal Customer,37,Business travel,Business,3210,2,2,2,2,5,3,3,5,5,5,5,5,5,3,0,0.0,satisfied +17827,114118,Female,Loyal Customer,40,Personal Travel,Business,909,2,1,2,3,5,4,3,1,1,2,1,2,1,2,6,0.0,neutral or dissatisfied +17828,52474,Female,Loyal Customer,64,Personal Travel,Eco Plus,261,3,5,0,1,5,3,2,5,5,0,1,2,5,4,0,3.0,neutral or dissatisfied +17829,103543,Female,Loyal Customer,35,Business travel,Business,2244,3,4,2,2,1,4,4,3,3,3,3,4,3,4,0,2.0,neutral or dissatisfied +17830,95382,Female,Loyal Customer,59,Personal Travel,Eco,273,4,4,4,1,3,4,4,1,1,4,1,5,1,1,0,0.0,satisfied +17831,39689,Male,disloyal Customer,20,Business travel,Eco,1463,1,1,1,3,1,1,1,1,5,2,2,5,5,1,115,131.0,neutral or dissatisfied +17832,119710,Female,Loyal Customer,41,Business travel,Business,3050,2,5,2,2,3,5,4,4,4,4,4,5,4,4,0,5.0,satisfied +17833,41669,Female,disloyal Customer,45,Business travel,Eco,843,3,4,4,1,2,4,2,2,3,3,4,5,3,2,0,0.0,neutral or dissatisfied +17834,10830,Female,disloyal Customer,36,Business travel,Business,216,2,2,2,4,4,2,4,4,3,3,5,4,5,4,3,2.0,neutral or dissatisfied +17835,121924,Male,Loyal Customer,49,Business travel,Business,413,2,2,2,2,2,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +17836,76754,Female,Loyal Customer,33,Business travel,Business,689,5,5,3,5,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +17837,42172,Female,disloyal Customer,22,Business travel,Eco,817,3,3,3,2,3,3,3,3,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +17838,47106,Male,Loyal Customer,49,Personal Travel,Eco Plus,639,2,5,2,3,3,2,2,3,4,2,5,3,5,3,0,14.0,neutral or dissatisfied +17839,59960,Female,Loyal Customer,52,Business travel,Business,3066,1,1,1,1,2,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +17840,51061,Female,Loyal Customer,57,Personal Travel,Eco,373,0,3,0,3,3,3,3,2,2,0,2,1,2,2,0,0.0,satisfied +17841,96604,Male,disloyal Customer,29,Business travel,Business,972,2,2,2,2,3,2,3,3,5,4,5,5,5,3,2,,neutral or dissatisfied +17842,113241,Male,Loyal Customer,41,Personal Travel,Business,236,4,4,4,3,5,2,2,3,3,4,3,1,3,1,1,0.0,neutral or dissatisfied +17843,101179,Male,Loyal Customer,63,Personal Travel,Eco,1069,4,5,4,2,4,4,5,4,3,4,5,5,4,4,37,32.0,satisfied +17844,26856,Female,Loyal Customer,61,Personal Travel,Eco,224,2,4,0,4,5,5,5,5,5,0,5,4,5,3,0,0.0,neutral or dissatisfied +17845,61561,Male,Loyal Customer,26,Personal Travel,Eco Plus,2253,4,1,4,3,3,4,3,3,2,3,3,3,3,3,0,0.0,neutral or dissatisfied +17846,127253,Female,Loyal Customer,47,Business travel,Eco,1107,1,1,1,1,1,4,3,1,1,1,1,2,1,1,21,26.0,neutral or dissatisfied +17847,55880,Female,disloyal Customer,21,Business travel,Eco,733,2,2,2,4,5,2,4,5,2,5,4,4,3,5,7,36.0,neutral or dissatisfied +17848,119484,Female,Loyal Customer,45,Business travel,Business,2957,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +17849,122128,Female,Loyal Customer,31,Business travel,Business,1723,5,5,5,5,4,5,4,4,4,5,4,3,5,4,0,28.0,satisfied +17850,20004,Female,Loyal Customer,68,Business travel,Eco,589,4,5,3,5,1,3,3,4,4,4,4,4,4,3,0,0.0,satisfied +17851,37740,Female,Loyal Customer,24,Personal Travel,Eco,1097,2,1,2,4,5,2,5,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +17852,21044,Male,Loyal Customer,47,Business travel,Business,3349,1,1,1,1,5,4,1,5,5,5,4,3,5,2,0,0.0,satisfied +17853,36206,Female,Loyal Customer,60,Business travel,Eco,496,5,4,3,3,1,1,5,5,5,5,5,5,5,3,0,0.0,satisfied +17854,53314,Male,Loyal Customer,60,Personal Travel,Eco,758,2,4,2,5,5,2,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +17855,63133,Female,Loyal Customer,57,Business travel,Business,337,3,3,3,3,3,3,3,3,3,3,3,2,3,4,8,0.0,neutral or dissatisfied +17856,26764,Female,Loyal Customer,67,Personal Travel,Eco,859,4,4,4,3,3,3,3,1,1,4,1,3,1,4,0,0.0,neutral or dissatisfied +17857,66510,Male,Loyal Customer,13,Personal Travel,Eco,447,1,5,1,3,3,1,2,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +17858,75995,Female,Loyal Customer,49,Business travel,Business,3198,1,1,1,1,5,4,5,5,5,5,5,5,5,3,0,2.0,satisfied +17859,94446,Male,disloyal Customer,25,Business travel,Business,562,2,0,2,3,5,2,5,5,4,2,5,4,5,5,6,0.0,neutral or dissatisfied +17860,72159,Female,Loyal Customer,48,Personal Travel,Eco,731,4,3,4,3,3,3,2,5,5,4,5,3,5,3,1,0.0,neutral or dissatisfied +17861,109191,Female,Loyal Customer,38,Business travel,Eco,483,2,4,4,4,2,2,2,2,2,5,4,1,3,2,0,7.0,neutral or dissatisfied +17862,101204,Male,Loyal Customer,43,Personal Travel,Eco,1069,1,3,1,1,1,1,1,1,3,1,1,4,1,1,19,6.0,neutral or dissatisfied +17863,54126,Female,Loyal Customer,37,Business travel,Business,1400,4,4,4,4,5,3,1,4,4,4,4,5,4,2,0,0.0,satisfied +17864,95297,Male,Loyal Customer,10,Personal Travel,Eco,323,2,3,2,3,5,2,5,5,4,3,4,2,4,5,3,4.0,neutral or dissatisfied +17865,38460,Male,Loyal Customer,29,Personal Travel,Eco,1226,3,4,3,3,4,3,4,4,2,5,4,1,3,4,0,20.0,neutral or dissatisfied +17866,21457,Female,Loyal Customer,63,Business travel,Business,377,1,5,5,5,3,4,4,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +17867,32869,Male,Loyal Customer,29,Personal Travel,Eco,101,4,5,0,2,2,0,4,2,5,2,4,3,5,2,0,0.0,satisfied +17868,54602,Male,Loyal Customer,32,Personal Travel,Business,964,3,5,3,2,5,3,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +17869,96071,Female,Loyal Customer,68,Personal Travel,Eco,795,1,5,1,3,4,4,5,3,3,1,5,5,3,4,0,0.0,neutral or dissatisfied +17870,82976,Female,Loyal Customer,48,Business travel,Business,1127,3,3,3,3,2,5,5,5,5,5,5,3,5,5,13,43.0,satisfied +17871,52029,Male,Loyal Customer,35,Personal Travel,Eco,328,1,2,1,2,3,1,3,3,3,1,2,2,3,3,0,0.0,neutral or dissatisfied +17872,73942,Male,Loyal Customer,22,Business travel,Business,2330,3,2,2,2,3,3,3,2,4,2,4,3,4,3,12,4.0,neutral or dissatisfied +17873,7484,Female,Loyal Customer,39,Business travel,Business,2243,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,4.0,satisfied +17874,58323,Female,disloyal Customer,37,Business travel,Eco,239,2,0,3,3,5,3,5,5,2,2,1,1,3,5,13,0.0,neutral or dissatisfied +17875,651,Male,Loyal Customer,54,Business travel,Business,247,4,4,4,4,3,4,4,5,5,5,5,4,5,4,112,119.0,satisfied +17876,6031,Male,Loyal Customer,61,Business travel,Business,690,3,5,5,5,4,3,3,3,3,3,3,2,3,1,77,68.0,neutral or dissatisfied +17877,13590,Male,Loyal Customer,62,Personal Travel,Eco,152,1,4,0,2,3,0,3,3,5,4,4,5,5,3,8,,neutral or dissatisfied +17878,49528,Male,disloyal Customer,41,Business travel,Eco,77,2,5,1,4,3,1,3,3,3,5,3,5,2,3,0,0.0,neutral or dissatisfied +17879,116710,Male,Loyal Customer,44,Business travel,Eco Plus,372,5,5,5,5,5,5,5,5,3,1,1,1,3,5,0,4.0,satisfied +17880,116848,Male,Loyal Customer,61,Personal Travel,Business,646,2,1,2,2,5,2,3,4,4,2,2,1,4,1,1,0.0,neutral or dissatisfied +17881,84729,Female,Loyal Customer,48,Business travel,Business,1894,3,3,3,3,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +17882,25062,Female,Loyal Customer,24,Personal Travel,Eco,594,5,5,5,2,4,5,4,4,2,3,5,4,5,4,12,3.0,satisfied +17883,65466,Male,Loyal Customer,52,Business travel,Business,3118,1,1,1,1,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +17884,10427,Male,Loyal Customer,54,Business travel,Business,3403,2,2,2,2,4,4,5,4,4,4,4,5,4,4,44,35.0,satisfied +17885,71705,Female,Loyal Customer,12,Personal Travel,Eco Plus,1005,2,5,2,1,1,2,1,1,5,3,5,4,4,1,29,23.0,neutral or dissatisfied +17886,46242,Female,Loyal Customer,73,Business travel,Business,1648,4,3,3,3,2,2,2,4,4,4,4,4,4,1,1,0.0,neutral or dissatisfied +17887,17619,Male,Loyal Customer,41,Business travel,Eco,622,4,3,3,3,4,4,4,4,4,5,1,3,3,4,33,26.0,satisfied +17888,109027,Female,Loyal Customer,55,Business travel,Business,2309,2,2,2,2,2,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +17889,108713,Male,Loyal Customer,40,Business travel,Business,2041,4,4,4,4,3,4,4,5,5,5,5,5,5,4,85,82.0,satisfied +17890,13528,Male,disloyal Customer,25,Business travel,Eco,152,0,0,1,5,5,1,5,5,1,5,5,1,2,5,24,42.0,satisfied +17891,8981,Female,Loyal Customer,36,Personal Travel,Eco,725,1,1,1,3,5,1,4,5,2,2,4,3,4,5,30,4.0,neutral or dissatisfied +17892,71111,Male,Loyal Customer,33,Business travel,Business,2072,2,2,2,2,4,4,4,4,3,5,5,5,5,4,0,0.0,satisfied +17893,28180,Male,Loyal Customer,40,Personal Travel,Eco,834,2,4,2,2,3,2,3,3,4,5,4,4,5,3,38,24.0,neutral or dissatisfied +17894,71375,Male,disloyal Customer,18,Business travel,Eco,258,3,2,3,4,4,3,4,4,2,4,4,1,3,4,19,11.0,neutral or dissatisfied +17895,73312,Male,Loyal Customer,45,Business travel,Business,1197,2,1,2,2,3,5,5,5,5,5,5,4,5,3,0,19.0,satisfied +17896,103854,Female,Loyal Customer,16,Business travel,Business,1056,2,3,3,3,2,1,2,2,4,2,3,3,3,2,0,0.0,neutral or dissatisfied +17897,2150,Male,disloyal Customer,49,Business travel,Business,685,3,3,3,3,4,3,4,4,5,3,5,3,4,4,0,0.0,neutral or dissatisfied +17898,100503,Female,Loyal Customer,18,Business travel,Business,3864,1,4,4,4,1,1,1,1,2,5,4,4,4,1,0,0.0,neutral or dissatisfied +17899,82477,Male,Loyal Customer,53,Personal Travel,Eco,509,4,5,4,5,4,4,1,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +17900,102590,Female,Loyal Customer,30,Business travel,Eco Plus,488,4,1,1,1,4,3,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +17901,55436,Male,Loyal Customer,39,Business travel,Business,2521,4,4,4,4,3,3,3,5,2,3,4,3,5,3,0,0.0,satisfied +17902,8020,Male,Loyal Customer,50,Business travel,Business,2744,4,4,4,4,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +17903,98279,Male,Loyal Customer,51,Business travel,Business,2486,4,4,4,4,1,4,1,4,4,4,4,3,4,4,0,0.0,satisfied +17904,117682,Female,Loyal Customer,34,Business travel,Business,2075,4,4,5,4,3,5,4,4,4,4,4,4,4,3,66,57.0,satisfied +17905,94506,Female,Loyal Customer,55,Business travel,Business,2082,5,5,5,5,4,4,4,4,4,4,4,5,4,5,1,0.0,satisfied +17906,9329,Male,Loyal Customer,52,Personal Travel,Eco,542,2,5,2,1,4,2,4,4,4,3,4,4,5,4,36,27.0,neutral or dissatisfied +17907,50459,Female,Loyal Customer,56,Business travel,Eco,190,2,3,4,4,4,3,3,2,2,2,2,3,2,2,13,8.0,neutral or dissatisfied +17908,23923,Female,Loyal Customer,48,Personal Travel,Eco,579,2,3,2,3,1,1,5,3,3,2,3,3,3,1,2,9.0,neutral or dissatisfied +17909,6817,Male,Loyal Customer,43,Personal Travel,Eco,235,3,1,3,2,3,3,3,3,3,4,1,3,1,3,0,0.0,neutral or dissatisfied +17910,67944,Male,Loyal Customer,10,Personal Travel,Eco,1235,3,5,3,2,1,3,1,1,5,2,4,5,4,1,2,0.0,neutral or dissatisfied +17911,48250,Female,Loyal Customer,41,Personal Travel,Eco,173,2,2,0,3,0,1,1,1,5,4,4,1,2,1,183,173.0,neutral or dissatisfied +17912,101042,Male,Loyal Customer,53,Business travel,Business,368,1,1,1,1,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +17913,90222,Female,Loyal Customer,45,Business travel,Business,2329,5,5,5,5,3,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +17914,115635,Female,Loyal Customer,41,Business travel,Business,337,1,1,1,1,5,5,5,4,4,4,4,5,4,3,8,4.0,satisfied +17915,66286,Male,Loyal Customer,44,Personal Travel,Eco Plus,550,3,1,4,3,1,4,2,1,4,5,1,1,2,1,1,0.0,neutral or dissatisfied +17916,101118,Male,Loyal Customer,46,Business travel,Business,1069,3,3,3,3,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +17917,124140,Male,Loyal Customer,18,Personal Travel,Eco,529,3,2,1,3,3,1,3,3,4,3,3,2,2,3,22,25.0,neutral or dissatisfied +17918,25027,Female,Loyal Customer,58,Business travel,Eco,907,1,0,0,4,4,4,3,5,5,1,5,4,5,3,12,10.0,neutral or dissatisfied +17919,5590,Female,Loyal Customer,50,Business travel,Business,2727,3,5,5,5,1,3,4,3,3,3,3,3,3,4,11,41.0,neutral or dissatisfied +17920,83489,Female,Loyal Customer,52,Business travel,Business,2528,3,3,3,3,3,3,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +17921,108915,Male,Loyal Customer,42,Business travel,Business,2583,4,3,3,3,4,4,4,3,2,3,4,4,2,4,257,241.0,neutral or dissatisfied +17922,63155,Female,disloyal Customer,36,Business travel,Business,447,2,2,2,4,3,2,2,3,5,2,5,3,4,3,14,7.0,neutral or dissatisfied +17923,69850,Male,Loyal Customer,14,Personal Travel,Eco,1055,3,4,3,1,1,3,1,1,4,3,4,3,5,1,20,19.0,neutral or dissatisfied +17924,63242,Female,Loyal Customer,54,Business travel,Business,3408,4,4,4,4,2,4,4,5,5,5,5,4,5,3,2,0.0,satisfied +17925,30074,Male,Loyal Customer,22,Personal Travel,Eco,213,1,3,1,3,1,1,1,1,1,5,3,4,3,1,0,0.0,neutral or dissatisfied +17926,123197,Female,Loyal Customer,45,Personal Travel,Eco,507,1,4,2,3,4,5,5,5,5,2,5,3,5,3,0,1.0,neutral or dissatisfied +17927,70366,Female,Loyal Customer,47,Business travel,Business,3715,3,2,2,2,3,2,2,3,3,3,3,2,3,1,0,12.0,neutral or dissatisfied +17928,101047,Female,Loyal Customer,46,Business travel,Business,368,3,3,3,3,2,5,5,5,5,5,5,5,5,5,18,5.0,satisfied +17929,117515,Male,Loyal Customer,63,Business travel,Eco Plus,107,5,5,5,5,5,5,5,5,3,2,1,1,1,5,1,0.0,satisfied +17930,13020,Female,Loyal Customer,44,Business travel,Business,2460,4,5,3,5,3,3,4,4,4,4,4,1,4,4,78,68.0,neutral or dissatisfied +17931,105815,Female,Loyal Customer,42,Personal Travel,Eco,787,3,4,3,2,3,4,4,5,5,3,5,4,5,4,43,75.0,neutral or dissatisfied +17932,10698,Male,Loyal Customer,29,Business travel,Business,74,2,2,2,2,2,2,2,2,2,3,4,2,4,2,0,0.0,neutral or dissatisfied +17933,42170,Female,Loyal Customer,22,Business travel,Business,834,4,2,2,2,4,4,4,4,2,2,3,4,4,4,0,7.0,neutral or dissatisfied +17934,9536,Female,disloyal Customer,25,Business travel,Business,288,5,4,5,4,4,5,4,4,5,4,5,5,5,4,0,0.0,satisfied +17935,8729,Female,Loyal Customer,48,Personal Travel,Eco,227,1,3,1,3,4,4,4,4,4,1,4,3,4,1,49,45.0,neutral or dissatisfied +17936,51517,Female,Loyal Customer,56,Business travel,Eco,425,2,5,5,5,4,1,2,2,2,2,2,3,2,2,0,0.0,satisfied +17937,88955,Female,disloyal Customer,29,Business travel,Business,1184,1,1,1,1,1,1,1,1,5,4,4,4,4,1,0,0.0,neutral or dissatisfied +17938,6153,Male,Loyal Customer,58,Business travel,Business,501,2,2,2,2,5,4,5,3,3,4,3,4,3,3,14,15.0,satisfied +17939,91836,Male,Loyal Customer,24,Personal Travel,Eco Plus,532,1,4,3,5,3,3,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +17940,125032,Male,Loyal Customer,42,Business travel,Business,2300,4,4,4,4,3,3,3,5,5,3,5,3,3,3,5,11.0,satisfied +17941,92449,Male,Loyal Customer,45,Business travel,Business,2139,3,3,3,3,4,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +17942,106847,Male,Loyal Customer,43,Personal Travel,Eco,1733,1,4,2,4,4,2,4,4,4,4,5,3,5,4,1,9.0,neutral or dissatisfied +17943,49137,Female,disloyal Customer,24,Business travel,Eco,86,5,4,5,1,4,5,4,4,4,3,2,4,4,4,0,0.0,satisfied +17944,11621,Female,Loyal Customer,51,Personal Travel,Eco,657,1,2,1,3,3,3,4,3,3,1,3,1,3,4,5,0.0,neutral or dissatisfied +17945,89013,Male,Loyal Customer,27,Business travel,Business,2139,4,4,5,4,4,4,4,4,5,5,5,3,4,4,1,0.0,satisfied +17946,24088,Female,Loyal Customer,27,Business travel,Business,3163,1,1,1,1,4,4,4,4,1,5,1,4,1,4,0,0.0,satisfied +17947,77128,Female,Loyal Customer,26,Personal Travel,Eco Plus,1481,3,5,3,1,2,3,1,2,4,2,5,4,5,2,0,0.0,neutral or dissatisfied +17948,73858,Female,Loyal Customer,67,Personal Travel,Eco,1810,3,5,4,1,1,5,5,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +17949,104697,Male,disloyal Customer,39,Business travel,Business,159,2,2,2,1,4,2,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +17950,63429,Male,Loyal Customer,14,Personal Travel,Eco,447,4,4,4,4,5,4,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +17951,38742,Female,Loyal Customer,44,Business travel,Business,3179,4,4,4,4,3,3,3,4,4,4,4,1,4,1,11,0.0,satisfied +17952,70960,Female,disloyal Customer,42,Business travel,Business,802,2,2,2,1,5,2,5,5,4,4,4,3,5,5,0,12.0,neutral or dissatisfied +17953,114333,Female,Loyal Customer,70,Personal Travel,Eco,846,2,4,2,2,2,5,5,5,5,2,5,5,5,3,51,32.0,neutral or dissatisfied +17954,67176,Male,Loyal Customer,10,Personal Travel,Eco,985,3,4,3,1,2,3,2,2,4,2,4,5,5,2,12,11.0,neutral or dissatisfied +17955,13160,Male,Loyal Customer,57,Personal Travel,Eco,562,2,1,2,4,1,2,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +17956,9155,Male,Loyal Customer,29,Personal Travel,Eco Plus,227,1,5,1,3,1,1,1,1,4,5,5,3,4,1,30,40.0,neutral or dissatisfied +17957,25896,Male,Loyal Customer,20,Personal Travel,Eco,907,2,2,2,2,1,2,1,1,1,2,2,4,3,1,13,8.0,neutral or dissatisfied +17958,128391,Female,Loyal Customer,43,Business travel,Eco,355,3,5,5,5,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +17959,18010,Female,Loyal Customer,56,Personal Travel,Eco,332,4,5,4,2,2,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +17960,51152,Female,Loyal Customer,31,Personal Travel,Eco,86,2,2,2,4,2,2,2,2,3,4,3,3,4,2,9,6.0,neutral or dissatisfied +17961,100619,Female,disloyal Customer,27,Business travel,Eco,1121,4,4,4,2,4,4,4,4,5,2,4,2,4,4,17,3.0,neutral or dissatisfied +17962,90440,Female,Loyal Customer,48,Business travel,Business,3998,2,2,2,2,3,5,4,2,2,2,2,5,2,4,1,0.0,satisfied +17963,105710,Female,disloyal Customer,23,Business travel,Eco,787,1,1,1,3,4,1,4,4,2,5,4,2,4,4,22,24.0,neutral or dissatisfied +17964,2460,Male,Loyal Customer,22,Business travel,Business,2708,1,1,1,1,1,1,1,1,1,1,4,4,3,1,0,18.0,neutral or dissatisfied +17965,122606,Female,Loyal Customer,48,Business travel,Eco,728,4,5,5,5,5,3,4,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +17966,40898,Female,Loyal Customer,44,Personal Travel,Eco,599,2,2,2,3,2,2,2,2,5,4,3,2,1,2,139,139.0,neutral or dissatisfied +17967,98338,Female,Loyal Customer,54,Business travel,Business,1046,4,4,4,4,3,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +17968,18551,Female,Loyal Customer,19,Business travel,Business,3842,5,5,5,5,5,5,5,5,1,5,5,1,4,5,0,0.0,satisfied +17969,22830,Female,disloyal Customer,34,Business travel,Eco,151,2,3,2,4,3,2,3,3,2,2,3,2,3,3,15,0.0,neutral or dissatisfied +17970,113593,Male,disloyal Customer,20,Business travel,Eco,407,2,1,1,3,5,1,5,5,4,2,4,3,4,5,0,1.0,neutral or dissatisfied +17971,7973,Female,Loyal Customer,70,Personal Travel,Eco Plus,594,3,4,3,4,2,3,4,5,5,3,3,2,5,5,0,1.0,neutral or dissatisfied +17972,24812,Female,disloyal Customer,21,Business travel,Eco,828,5,5,5,4,2,5,2,2,3,1,4,3,1,2,0,20.0,satisfied +17973,11899,Female,disloyal Customer,38,Business travel,Business,744,3,3,3,2,4,3,4,4,5,4,5,5,4,4,35,33.0,neutral or dissatisfied +17974,118327,Female,Loyal Customer,53,Business travel,Business,3738,3,3,3,3,4,4,4,4,4,5,4,5,4,5,5,4.0,satisfied +17975,26546,Female,Loyal Customer,7,Personal Travel,Eco,990,2,4,2,1,2,2,2,2,5,3,5,3,5,2,0,0.0,neutral or dissatisfied +17976,106792,Female,Loyal Customer,58,Business travel,Business,1642,5,5,5,5,4,5,4,5,5,5,5,3,5,5,13,24.0,satisfied +17977,34467,Male,Loyal Customer,48,Business travel,Eco,266,5,1,1,1,5,5,5,5,2,3,5,4,4,5,0,21.0,satisfied +17978,58419,Male,disloyal Customer,22,Business travel,Eco,733,3,3,3,3,3,3,3,3,2,2,3,3,4,3,42,42.0,neutral or dissatisfied +17979,74034,Male,Loyal Customer,50,Personal Travel,Eco,1471,3,4,3,5,3,3,3,3,4,5,4,4,5,3,0,0.0,neutral or dissatisfied +17980,65630,Male,Loyal Customer,55,Personal Travel,Eco,237,2,5,2,1,5,2,5,5,5,4,4,3,5,5,1,0.0,neutral or dissatisfied +17981,7208,Male,disloyal Customer,54,Business travel,Business,135,3,3,3,2,1,3,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +17982,45137,Male,Loyal Customer,56,Business travel,Eco,174,4,3,3,3,4,4,4,4,5,4,1,4,1,4,0,0.0,satisfied +17983,58673,Male,Loyal Customer,38,Business travel,Business,1744,3,3,2,3,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +17984,91642,Female,Loyal Customer,70,Personal Travel,Eco,1184,4,4,4,3,5,3,5,4,4,4,4,5,4,5,0,0.0,satisfied +17985,37031,Male,Loyal Customer,35,Business travel,Business,994,3,3,3,3,3,4,1,4,4,4,4,5,4,4,0,0.0,satisfied +17986,86441,Female,Loyal Customer,47,Business travel,Business,2981,2,5,1,1,3,4,3,2,2,2,2,4,2,1,15,0.0,neutral or dissatisfied +17987,13246,Female,Loyal Customer,40,Business travel,Eco,657,4,4,4,4,4,4,4,4,2,1,3,2,3,4,0,0.0,satisfied +17988,94732,Female,Loyal Customer,37,Business travel,Eco,239,3,3,3,3,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +17989,49875,Male,Loyal Customer,24,Business travel,Business,1738,1,3,2,3,1,1,1,1,2,1,1,1,2,1,0,8.0,neutral or dissatisfied +17990,114811,Male,Loyal Customer,57,Business travel,Business,3821,3,3,4,3,4,4,4,5,4,5,4,4,4,4,181,202.0,satisfied +17991,50682,Male,Loyal Customer,54,Personal Travel,Eco,109,4,3,4,2,2,4,2,2,2,3,3,3,3,2,0,0.0,neutral or dissatisfied +17992,39096,Female,Loyal Customer,70,Personal Travel,Eco,984,3,4,3,2,4,5,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +17993,22513,Male,disloyal Customer,27,Business travel,Eco Plus,143,1,2,2,5,5,2,5,5,2,1,4,3,3,5,0,0.0,neutral or dissatisfied +17994,86801,Male,Loyal Customer,39,Business travel,Business,2419,1,1,5,1,5,5,4,5,5,4,5,5,5,3,26,22.0,satisfied +17995,84535,Male,Loyal Customer,32,Business travel,Business,2615,3,2,2,2,3,3,3,3,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +17996,119053,Female,Loyal Customer,33,Business travel,Business,2279,3,4,4,4,3,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +17997,82778,Male,Loyal Customer,12,Personal Travel,Eco,926,4,3,4,4,4,4,4,4,4,5,1,2,1,4,0,0.0,neutral or dissatisfied +17998,126605,Female,disloyal Customer,25,Business travel,Business,1337,4,0,4,1,4,4,4,4,4,5,4,4,5,4,11,3.0,satisfied +17999,111916,Male,Loyal Customer,51,Business travel,Business,2581,5,5,5,5,5,4,5,4,4,4,4,3,4,5,3,0.0,satisfied +18000,23221,Female,Loyal Customer,55,Personal Travel,Eco,326,3,1,3,1,2,1,2,1,1,3,1,1,1,1,47,44.0,neutral or dissatisfied +18001,110320,Male,Loyal Customer,43,Business travel,Business,798,5,5,5,5,2,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +18002,113305,Female,disloyal Customer,33,Business travel,Business,414,3,3,3,1,3,2,2,5,5,4,4,2,3,2,145,126.0,neutral or dissatisfied +18003,66996,Male,Loyal Customer,47,Business travel,Business,1570,3,3,3,3,2,4,5,5,5,5,5,5,5,3,1,0.0,satisfied +18004,84136,Male,Loyal Customer,43,Business travel,Eco,382,3,1,5,5,2,3,2,2,1,1,4,3,4,2,0,0.0,neutral or dissatisfied +18005,108202,Female,Loyal Customer,39,Personal Travel,Eco Plus,1105,3,1,3,2,1,3,1,1,3,1,2,1,2,1,85,90.0,neutral or dissatisfied +18006,36673,Male,Loyal Customer,69,Personal Travel,Eco,1249,1,5,1,2,3,1,3,3,2,2,5,5,3,3,11,0.0,neutral or dissatisfied +18007,72418,Male,Loyal Customer,49,Business travel,Business,2257,5,5,2,5,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +18008,92568,Female,Loyal Customer,56,Business travel,Business,2139,4,4,4,4,5,4,5,3,3,3,3,5,3,4,0,0.0,satisfied +18009,69889,Female,Loyal Customer,38,Business travel,Business,1514,2,2,2,2,3,4,4,4,4,4,4,5,4,4,7,0.0,satisfied +18010,127257,Female,Loyal Customer,54,Business travel,Business,3782,4,4,4,4,4,4,4,4,4,4,4,4,4,4,11,0.0,satisfied +18011,71068,Female,Loyal Customer,43,Personal Travel,Eco,802,2,4,2,5,1,1,5,5,5,2,5,4,5,3,13,0.0,neutral or dissatisfied +18012,5299,Female,Loyal Customer,19,Personal Travel,Eco,190,2,3,0,1,3,0,3,3,2,2,2,2,4,3,2,0.0,neutral or dissatisfied +18013,89288,Male,Loyal Customer,70,Business travel,Business,453,4,5,5,5,3,4,4,4,4,4,4,3,4,1,12,15.0,neutral or dissatisfied +18014,92761,Male,Loyal Customer,44,Business travel,Business,3528,5,5,5,5,4,4,5,4,4,4,4,3,4,4,10,0.0,satisfied +18015,19957,Male,Loyal Customer,52,Business travel,Eco Plus,343,3,1,1,1,3,3,3,3,2,4,4,3,2,3,188,183.0,neutral or dissatisfied +18016,79900,Male,Loyal Customer,54,Business travel,Business,1005,3,3,3,3,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +18017,24216,Female,disloyal Customer,32,Business travel,Eco,170,3,4,3,3,1,3,1,1,1,5,4,2,4,1,0,0.0,neutral or dissatisfied +18018,55120,Female,Loyal Customer,53,Personal Travel,Eco,1608,1,5,1,4,4,4,5,3,3,1,5,5,3,4,14,24.0,neutral or dissatisfied +18019,64622,Male,disloyal Customer,34,Business travel,Business,247,2,2,2,5,3,2,3,3,5,3,4,5,4,3,4,4.0,neutral or dissatisfied +18020,50975,Female,Loyal Customer,22,Personal Travel,Eco,190,4,5,0,4,1,0,1,1,4,4,4,4,5,1,0,0.0,neutral or dissatisfied +18021,62324,Male,Loyal Customer,49,Personal Travel,Eco,414,2,2,2,3,3,2,3,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +18022,88185,Female,Loyal Customer,45,Business travel,Business,581,1,1,1,1,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +18023,43635,Female,disloyal Customer,28,Business travel,Business,1034,3,3,3,2,1,3,1,1,5,2,4,4,5,1,30,43.0,neutral or dissatisfied +18024,97833,Male,Loyal Customer,56,Personal Travel,Eco,395,3,5,2,5,3,2,3,3,3,3,4,4,4,3,0,5.0,neutral or dissatisfied +18025,75497,Male,Loyal Customer,43,Business travel,Business,2585,4,4,3,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +18026,1090,Male,Loyal Customer,8,Personal Travel,Eco,396,3,4,3,5,4,3,4,4,3,3,4,5,5,4,0,11.0,neutral or dissatisfied +18027,67298,Female,disloyal Customer,25,Business travel,Eco Plus,985,3,4,3,3,5,3,5,5,2,5,4,3,4,5,0,0.0,neutral or dissatisfied +18028,20209,Female,Loyal Customer,60,Personal Travel,Business,346,1,5,5,4,3,5,5,1,1,5,1,4,1,4,9,8.0,neutral or dissatisfied +18029,114906,Female,Loyal Customer,46,Business travel,Business,1745,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +18030,62645,Female,Loyal Customer,30,Personal Travel,Eco,1652,2,4,2,5,3,2,3,3,3,4,4,2,4,3,37,46.0,neutral or dissatisfied +18031,86850,Male,Loyal Customer,28,Personal Travel,Eco,692,5,5,5,3,4,5,4,4,4,2,4,3,4,4,0,0.0,satisfied +18032,82219,Male,Loyal Customer,51,Business travel,Business,1934,2,2,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +18033,25498,Female,Loyal Customer,12,Business travel,Business,516,3,3,3,3,3,3,3,3,2,5,3,4,4,3,0,8.0,neutral or dissatisfied +18034,21660,Male,disloyal Customer,36,Business travel,Eco,746,2,2,2,2,1,2,1,1,2,4,1,2,1,1,0,0.0,neutral or dissatisfied +18035,35483,Male,Loyal Customer,29,Personal Travel,Eco,944,3,3,3,4,5,3,5,5,2,5,5,2,2,5,1,3.0,neutral or dissatisfied +18036,91075,Female,Loyal Customer,68,Personal Travel,Eco,270,1,4,0,1,5,5,4,4,4,0,4,5,4,5,0,0.0,neutral or dissatisfied +18037,15828,Male,Loyal Customer,44,Business travel,Eco,195,5,5,5,5,5,5,5,5,1,3,5,2,3,5,98,84.0,satisfied +18038,31610,Male,Loyal Customer,52,Business travel,Business,853,4,4,4,4,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +18039,79081,Female,Loyal Customer,54,Personal Travel,Eco,306,1,5,5,2,3,5,4,5,5,5,5,3,5,5,0,0.0,neutral or dissatisfied +18040,8701,Female,Loyal Customer,41,Business travel,Eco,181,4,3,2,2,4,4,4,4,2,1,4,5,4,4,0,0.0,satisfied +18041,116841,Female,Loyal Customer,68,Personal Travel,Business,646,3,4,3,3,3,4,4,4,4,3,4,2,4,2,24,17.0,neutral or dissatisfied +18042,5031,Male,Loyal Customer,55,Business travel,Business,3407,3,3,3,3,2,4,4,5,5,5,5,4,5,3,17,24.0,satisfied +18043,2487,Male,disloyal Customer,22,Business travel,Eco,1379,3,3,3,5,4,3,4,4,4,3,5,5,5,4,3,11.0,neutral or dissatisfied +18044,5992,Female,Loyal Customer,56,Business travel,Business,3552,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +18045,52700,Female,Loyal Customer,51,Personal Travel,Eco Plus,119,3,1,3,2,1,3,2,1,1,3,1,4,1,4,1,0.0,neutral or dissatisfied +18046,100342,Female,Loyal Customer,36,Business travel,Business,1918,1,1,1,1,3,3,4,5,5,5,5,4,5,3,0,3.0,satisfied +18047,22882,Female,Loyal Customer,26,Personal Travel,Eco,147,1,4,1,3,5,1,5,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +18048,20660,Female,Loyal Customer,51,Business travel,Eco,522,4,1,1,1,4,4,4,3,5,5,3,4,1,4,218,210.0,satisfied +18049,118898,Female,disloyal Customer,25,Business travel,Business,587,5,4,5,1,1,5,1,1,5,4,4,3,4,1,9,3.0,satisfied +18050,15648,Female,Loyal Customer,62,Personal Travel,Eco Plus,296,3,4,3,2,2,4,5,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +18051,79891,Female,Loyal Customer,56,Business travel,Eco,1080,2,4,4,4,1,4,3,3,3,2,3,3,3,4,6,0.0,neutral or dissatisfied +18052,56667,Female,Loyal Customer,52,Personal Travel,Eco,937,3,3,4,1,5,3,4,4,4,4,4,4,4,2,0,18.0,neutral or dissatisfied +18053,118977,Male,Loyal Customer,42,Business travel,Business,1847,3,3,3,3,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18054,70496,Male,Loyal Customer,34,Business travel,Eco,867,2,4,4,4,2,2,2,2,4,4,4,4,3,2,0,0.0,neutral or dissatisfied +18055,96075,Female,Loyal Customer,59,Personal Travel,Eco,583,2,5,2,3,3,5,5,2,2,2,1,5,2,3,0,0.0,neutral or dissatisfied +18056,72134,Male,disloyal Customer,33,Business travel,Business,731,1,1,1,1,4,1,4,4,4,2,5,3,5,4,0,1.0,neutral or dissatisfied +18057,119275,Female,Loyal Customer,52,Business travel,Business,2593,5,5,5,5,4,5,3,5,3,4,4,3,3,3,54,178.0,satisfied +18058,39144,Female,Loyal Customer,9,Personal Travel,Eco,228,4,5,4,4,3,4,3,3,3,2,5,5,5,3,0,0.0,satisfied +18059,66771,Female,disloyal Customer,24,Business travel,Eco,802,4,4,4,3,3,4,3,3,3,3,4,3,4,3,9,3.0,satisfied +18060,123009,Male,Loyal Customer,28,Business travel,Business,650,2,3,3,3,2,2,2,2,2,3,4,1,4,2,26,74.0,neutral or dissatisfied +18061,116789,Male,Loyal Customer,30,Personal Travel,Eco Plus,325,4,5,4,5,3,4,3,3,3,2,5,2,4,3,1,0.0,neutral or dissatisfied +18062,84768,Male,Loyal Customer,51,Business travel,Business,547,3,3,3,3,2,4,4,5,5,4,5,3,5,5,0,10.0,satisfied +18063,98677,Male,Loyal Customer,20,Personal Travel,Eco,873,4,0,4,1,2,4,2,2,4,5,5,5,4,2,0,4.0,neutral or dissatisfied +18064,74988,Male,Loyal Customer,36,Business travel,Eco Plus,2475,3,2,2,2,3,2,3,3,2,5,4,3,3,3,0,0.0,neutral or dissatisfied +18065,48143,Female,Loyal Customer,40,Business travel,Business,192,5,5,2,5,5,1,2,5,5,5,3,3,5,3,0,0.0,satisfied +18066,49200,Male,disloyal Customer,17,Business travel,Eco,109,2,4,2,3,2,1,1,2,1,3,4,1,2,1,150,151.0,neutral or dissatisfied +18067,83870,Female,Loyal Customer,45,Personal Travel,Eco Plus,425,1,1,1,3,5,3,2,2,2,1,3,4,2,3,14,23.0,neutral or dissatisfied +18068,23825,Female,Loyal Customer,29,Business travel,Eco Plus,374,2,4,4,4,2,2,2,2,4,3,4,3,4,2,11,0.0,neutral or dissatisfied +18069,111848,Female,Loyal Customer,60,Business travel,Business,628,2,2,4,2,3,5,5,4,4,5,4,3,4,3,4,0.0,satisfied +18070,103506,Female,Loyal Customer,14,Business travel,Business,2515,5,5,5,5,4,4,4,4,4,2,4,5,4,4,8,,satisfied +18071,72025,Female,disloyal Customer,30,Business travel,Business,3711,1,1,1,5,1,2,2,5,5,5,4,2,5,2,0,0.0,neutral or dissatisfied +18072,66720,Female,Loyal Customer,57,Personal Travel,Eco,802,3,5,3,3,5,4,5,4,4,3,4,3,4,3,54,115.0,neutral or dissatisfied +18073,97823,Female,Loyal Customer,58,Business travel,Business,3929,5,5,5,5,5,4,5,4,4,4,4,3,4,5,66,46.0,satisfied +18074,74148,Female,Loyal Customer,50,Business travel,Eco,592,3,1,1,1,5,4,4,3,3,3,3,2,3,3,70,82.0,neutral or dissatisfied +18075,95552,Male,Loyal Customer,50,Personal Travel,Eco Plus,189,2,5,2,3,2,2,2,2,4,4,4,4,4,2,9,7.0,neutral or dissatisfied +18076,53708,Male,Loyal Customer,57,Business travel,Eco,1208,5,5,4,4,5,5,5,5,1,2,4,1,1,5,27,,satisfied +18077,1987,Male,Loyal Customer,47,Personal Travel,Eco,190,3,4,3,3,3,3,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +18078,115238,Male,disloyal Customer,37,Business travel,Business,358,3,3,3,1,4,3,4,4,4,3,4,5,4,4,2,0.0,satisfied +18079,105527,Female,disloyal Customer,24,Business travel,Business,611,1,2,0,3,5,0,5,5,1,3,4,2,4,5,2,7.0,neutral or dissatisfied +18080,43485,Female,disloyal Customer,19,Business travel,Eco,679,1,1,1,4,1,1,1,1,1,2,4,1,4,1,64,88.0,neutral or dissatisfied +18081,110621,Female,disloyal Customer,23,Business travel,Eco,719,1,1,1,3,2,1,2,2,3,3,4,4,5,2,65,64.0,neutral or dissatisfied +18082,38684,Female,disloyal Customer,17,Business travel,Eco Plus,2588,5,5,5,1,2,5,2,2,5,1,3,1,2,2,91,75.0,satisfied +18083,3610,Female,Loyal Customer,62,Business travel,Eco Plus,999,3,2,2,2,3,3,3,3,5,3,3,3,2,3,86,140.0,neutral or dissatisfied +18084,59630,Female,Loyal Customer,25,Business travel,Business,2341,4,4,4,4,3,3,3,3,5,3,5,5,4,3,0,0.0,satisfied +18085,21794,Female,Loyal Customer,55,Business travel,Business,2511,3,2,2,2,5,3,4,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +18086,115024,Female,Loyal Customer,53,Business travel,Business,337,1,1,1,1,3,5,4,5,5,5,5,3,5,5,32,80.0,satisfied +18087,118490,Male,Loyal Customer,48,Business travel,Business,3938,0,0,0,4,5,4,5,4,4,4,4,3,4,4,11,5.0,satisfied +18088,51035,Male,Loyal Customer,59,Personal Travel,Eco,190,2,4,2,4,1,2,1,1,5,3,5,4,5,1,0,0.0,neutral or dissatisfied +18089,46680,Female,Loyal Customer,62,Personal Travel,Eco,125,1,4,0,3,3,4,4,2,2,0,2,1,2,3,5,2.0,neutral or dissatisfied +18090,114265,Female,Loyal Customer,26,Business travel,Business,2623,4,3,3,3,4,4,4,4,3,5,4,1,4,4,31,20.0,neutral or dissatisfied +18091,123487,Female,disloyal Customer,21,Business travel,Business,1032,4,2,4,3,3,4,3,3,4,4,5,3,5,3,16,0.0,satisfied +18092,91493,Male,disloyal Customer,36,Business travel,Business,391,4,4,4,2,3,4,3,3,3,3,4,3,4,3,8,4.0,neutral or dissatisfied +18093,52952,Female,Loyal Customer,23,Personal Travel,Eco,1448,1,4,1,5,4,1,1,4,4,2,4,5,1,4,0,0.0,neutral or dissatisfied +18094,71416,Male,disloyal Customer,29,Business travel,Business,867,2,2,2,4,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +18095,127261,Male,disloyal Customer,10,Business travel,Eco,1107,3,3,3,4,3,3,5,3,2,1,4,4,4,3,5,11.0,neutral or dissatisfied +18096,50141,Male,Loyal Customer,41,Business travel,Business,78,2,3,3,3,1,4,3,3,3,3,2,1,3,4,0,0.0,neutral or dissatisfied +18097,102577,Female,Loyal Customer,20,Business travel,Eco Plus,407,3,4,4,4,3,3,3,3,1,5,3,2,4,3,45,34.0,neutral or dissatisfied +18098,15193,Female,Loyal Customer,46,Business travel,Business,2773,3,3,3,3,4,1,1,4,4,4,4,3,4,4,0,0.0,satisfied +18099,104608,Male,Loyal Customer,51,Business travel,Business,1738,2,4,2,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +18100,8561,Female,Loyal Customer,41,Business travel,Business,2999,3,4,5,5,2,4,4,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +18101,105584,Female,Loyal Customer,48,Personal Travel,Eco,577,1,4,1,3,3,5,5,1,1,1,3,4,1,4,25,34.0,neutral or dissatisfied +18102,87098,Male,Loyal Customer,28,Personal Travel,Eco,645,4,5,4,2,5,4,2,5,3,2,4,3,1,5,0,0.0,neutral or dissatisfied +18103,30626,Male,Loyal Customer,20,Personal Travel,Business,770,1,4,1,1,2,1,2,2,5,2,5,4,5,2,0,0.0,neutral or dissatisfied +18104,88977,Female,Loyal Customer,54,Personal Travel,Eco,1312,2,5,2,2,4,3,5,3,3,2,4,5,3,4,27,14.0,neutral or dissatisfied +18105,43893,Male,disloyal Customer,29,Business travel,Eco,114,2,3,2,3,4,2,4,4,4,4,1,1,2,4,0,0.0,neutral or dissatisfied +18106,306,Male,disloyal Customer,26,Business travel,Business,821,5,5,5,3,3,4,3,3,3,4,5,4,5,3,0,0.0,satisfied +18107,63109,Male,Loyal Customer,37,Personal Travel,Eco Plus,967,4,4,4,2,3,4,3,3,3,5,4,3,5,3,0,2.0,neutral or dissatisfied +18108,34760,Male,Loyal Customer,60,Business travel,Eco,301,3,4,4,4,3,3,3,3,1,3,3,4,4,3,10,17.0,neutral or dissatisfied +18109,29079,Male,Loyal Customer,23,Personal Travel,Eco,937,1,1,1,3,2,1,2,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +18110,6490,Male,Loyal Customer,34,Personal Travel,Eco,557,3,3,3,4,3,3,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +18111,31910,Male,Loyal Customer,44,Business travel,Business,2237,3,3,4,3,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +18112,83602,Female,Loyal Customer,41,Business travel,Business,3469,2,2,2,2,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +18113,75629,Female,disloyal Customer,36,Business travel,Eco Plus,337,1,1,1,1,4,1,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +18114,97263,Male,Loyal Customer,50,Personal Travel,Eco,296,3,4,3,3,4,3,3,4,3,5,5,4,4,4,8,4.0,neutral or dissatisfied +18115,69260,Female,Loyal Customer,40,Business travel,Business,733,1,4,3,4,2,4,3,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +18116,14200,Female,Loyal Customer,23,Business travel,Business,1973,2,5,5,5,2,2,2,2,3,1,2,1,3,2,0,0.0,neutral or dissatisfied +18117,32678,Male,Loyal Customer,47,Business travel,Business,216,1,3,3,3,5,3,3,3,3,4,1,2,3,1,0,0.0,neutral or dissatisfied +18118,124199,Female,Loyal Customer,39,Business travel,Business,2176,3,3,3,3,4,4,4,5,5,5,5,3,5,3,13,0.0,satisfied +18119,98616,Female,Loyal Customer,51,Business travel,Business,861,5,5,5,5,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +18120,115475,Male,Loyal Customer,16,Business travel,Eco,404,2,4,3,4,2,1,3,2,4,1,3,2,4,2,8,0.0,neutral or dissatisfied +18121,93715,Female,Loyal Customer,26,Personal Travel,Eco Plus,689,3,1,3,3,2,3,3,2,4,4,3,3,3,2,17,12.0,neutral or dissatisfied +18122,51473,Female,Loyal Customer,51,Business travel,Business,2423,4,4,4,4,3,4,4,4,4,4,4,4,4,5,0,6.0,satisfied +18123,28189,Male,Loyal Customer,64,Personal Travel,Eco,933,1,4,0,4,4,0,4,4,1,5,4,4,4,4,0,0.0,neutral or dissatisfied +18124,45598,Male,Loyal Customer,58,Business travel,Business,1521,1,1,1,1,5,3,3,1,1,1,1,4,1,1,0,16.0,neutral or dissatisfied +18125,109303,Male,Loyal Customer,15,Business travel,Eco,1072,1,2,2,2,1,1,2,1,4,2,3,4,3,1,0,0.0,neutral or dissatisfied +18126,14977,Male,Loyal Customer,56,Business travel,Eco,527,5,1,1,1,5,5,5,5,5,3,1,2,4,5,0,6.0,satisfied +18127,76655,Male,Loyal Customer,20,Personal Travel,Eco,547,2,3,2,4,1,2,4,1,2,1,3,1,3,1,18,24.0,neutral or dissatisfied +18128,97662,Female,disloyal Customer,32,Business travel,Business,491,1,1,1,4,5,1,5,5,3,4,4,5,5,5,11,9.0,neutral or dissatisfied +18129,65344,Male,Loyal Customer,25,Business travel,Business,631,5,5,5,5,2,2,2,2,4,4,4,4,4,2,1,0.0,satisfied +18130,4559,Female,Loyal Customer,59,Business travel,Business,2970,1,1,1,1,4,2,1,5,5,5,4,5,5,5,0,0.0,satisfied +18131,17877,Female,Loyal Customer,43,Personal Travel,Eco,201,4,2,4,3,5,4,3,3,3,4,3,3,3,2,91,81.0,satisfied +18132,126153,Female,Loyal Customer,52,Business travel,Business,2609,2,2,2,2,2,5,5,2,2,2,2,5,2,4,7,10.0,satisfied +18133,53099,Female,Loyal Customer,61,Personal Travel,Business,1628,2,1,2,3,2,2,4,1,1,2,1,2,1,4,10,39.0,neutral or dissatisfied +18134,107616,Male,disloyal Customer,25,Business travel,Eco,423,3,1,3,3,3,3,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +18135,110480,Female,Loyal Customer,16,Personal Travel,Eco,883,2,4,2,3,1,2,1,1,1,1,4,2,3,1,0,0.0,neutral or dissatisfied +18136,96565,Male,Loyal Customer,39,Business travel,Business,333,1,1,1,1,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +18137,22795,Female,disloyal Customer,24,Business travel,Eco,147,4,5,3,1,5,3,5,5,3,1,1,2,4,5,4,2.0,satisfied +18138,94474,Male,disloyal Customer,27,Business travel,Business,148,1,0,0,3,2,0,2,2,5,2,5,3,5,2,26,38.0,neutral or dissatisfied +18139,49810,Male,disloyal Customer,24,Business travel,Eco,109,3,2,3,4,2,3,2,2,2,4,4,2,4,2,55,51.0,neutral or dissatisfied +18140,44737,Male,Loyal Customer,85,Business travel,Eco Plus,67,1,3,3,3,1,1,1,2,5,4,3,1,4,1,0,8.0,neutral or dissatisfied +18141,1909,Female,Loyal Customer,33,Business travel,Business,2061,3,5,5,5,4,3,4,3,3,3,3,1,3,2,2,0.0,neutral or dissatisfied +18142,103184,Female,Loyal Customer,58,Business travel,Eco Plus,272,4,4,3,4,3,4,3,4,4,4,4,1,4,2,24,0.0,neutral or dissatisfied +18143,38805,Male,Loyal Customer,36,Personal Travel,Eco,354,5,5,5,3,5,5,5,5,1,3,1,5,1,5,0,0.0,satisfied +18144,26912,Male,Loyal Customer,32,Business travel,Business,1660,4,4,4,4,4,4,4,4,4,2,4,4,4,4,0,0.0,satisfied +18145,60724,Female,Loyal Customer,24,Personal Travel,Eco,1605,2,5,2,4,1,2,1,1,5,2,4,3,5,1,0,0.0,neutral or dissatisfied +18146,37539,Male,disloyal Customer,22,Business travel,Eco,828,2,2,2,2,1,2,1,1,3,4,2,3,3,1,23,29.0,neutral or dissatisfied +18147,30099,Male,Loyal Customer,11,Personal Travel,Eco,539,4,4,4,3,1,4,1,1,4,5,5,5,4,1,0,0.0,satisfied +18148,9544,Female,Loyal Customer,47,Business travel,Business,228,3,3,3,3,4,4,5,5,5,5,5,5,5,3,27,15.0,satisfied +18149,74103,Female,Loyal Customer,51,Business travel,Business,592,3,3,3,3,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +18150,22010,Male,Loyal Customer,64,Personal Travel,Eco,551,4,5,4,2,3,4,3,3,3,1,2,5,5,3,0,0.0,neutral or dissatisfied +18151,117433,Female,Loyal Customer,22,Business travel,Business,2545,3,3,4,3,4,4,4,4,4,4,5,3,4,4,17,0.0,satisfied +18152,20150,Female,Loyal Customer,61,Business travel,Eco,403,5,1,1,1,1,4,5,5,5,5,5,1,5,3,0,0.0,satisfied +18153,28921,Male,Loyal Customer,53,Business travel,Business,3753,2,2,2,2,3,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +18154,100625,Male,Loyal Customer,43,Business travel,Business,1555,2,3,3,3,2,4,3,2,2,2,2,2,2,1,23,23.0,neutral or dissatisfied +18155,96237,Female,Loyal Customer,55,Business travel,Business,3252,2,4,2,2,4,3,3,5,5,5,5,2,5,1,27,26.0,satisfied +18156,17097,Male,Loyal Customer,49,Personal Travel,Eco,416,4,4,4,1,4,3,3,5,4,1,5,3,2,3,157,158.0,neutral or dissatisfied +18157,108598,Male,Loyal Customer,48,Business travel,Business,2941,4,1,1,1,3,3,3,4,4,4,4,4,4,4,10,48.0,neutral or dissatisfied +18158,37970,Female,disloyal Customer,26,Business travel,Business,1237,5,5,5,2,3,5,3,3,3,2,5,3,5,3,0,0.0,satisfied +18159,107904,Male,Loyal Customer,33,Business travel,Business,861,5,5,5,5,3,3,3,3,5,4,4,4,4,3,2,0.0,satisfied +18160,124352,Male,disloyal Customer,23,Business travel,Business,808,4,5,4,2,4,4,4,4,3,5,4,3,5,4,0,0.0,satisfied +18161,121664,Male,Loyal Customer,48,Business travel,Business,511,5,5,5,5,3,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +18162,53844,Male,Loyal Customer,59,Business travel,Eco,191,1,5,5,5,1,1,1,2,5,3,3,1,1,1,132,122.0,neutral or dissatisfied +18163,41815,Male,Loyal Customer,63,Business travel,Eco,257,3,3,2,3,3,3,3,3,1,2,1,3,2,3,0,4.0,satisfied +18164,31505,Female,Loyal Customer,45,Business travel,Eco,916,4,2,2,2,2,4,3,4,4,4,4,3,4,3,25,27.0,satisfied +18165,102752,Male,Loyal Customer,7,Personal Travel,Eco Plus,255,2,2,2,3,2,2,2,2,4,1,4,3,4,2,54,47.0,neutral or dissatisfied +18166,123481,Female,Loyal Customer,51,Business travel,Business,2296,1,1,4,1,5,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +18167,121220,Female,Loyal Customer,52,Business travel,Business,2075,4,2,2,2,3,3,4,4,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +18168,11649,Male,Loyal Customer,56,Business travel,Business,3854,4,3,4,4,2,5,5,1,1,2,1,5,1,4,0,0.0,satisfied +18169,129382,Male,disloyal Customer,28,Business travel,Eco,954,2,2,2,1,3,2,3,3,5,4,1,1,3,3,0,0.0,neutral or dissatisfied +18170,46319,Male,disloyal Customer,65,Business travel,Eco,420,3,0,3,5,4,3,4,4,5,1,3,5,3,4,35,45.0,neutral or dissatisfied +18171,38081,Male,Loyal Customer,46,Business travel,Eco,1121,3,1,1,1,3,3,3,3,2,5,5,1,2,3,0,0.0,satisfied +18172,20615,Male,Loyal Customer,74,Business travel,Eco,464,3,2,2,2,3,3,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +18173,117783,Female,Loyal Customer,34,Business travel,Business,328,1,1,1,1,5,5,5,5,5,5,5,3,5,4,35,26.0,satisfied +18174,42159,Male,Loyal Customer,18,Personal Travel,Business,834,2,5,2,3,4,2,4,4,5,2,1,1,1,4,127,120.0,neutral or dissatisfied +18175,108407,Male,Loyal Customer,30,Business travel,Business,1636,1,3,3,3,1,1,1,1,3,4,3,1,4,1,1,0.0,neutral or dissatisfied +18176,38433,Male,Loyal Customer,56,Business travel,Business,2277,5,5,5,5,5,5,5,5,1,4,3,5,2,5,196,170.0,satisfied +18177,97852,Female,Loyal Customer,54,Business travel,Business,2699,4,3,4,4,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +18178,30729,Male,Loyal Customer,53,Personal Travel,Eco,532,1,3,1,3,4,1,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +18179,108045,Male,Loyal Customer,49,Business travel,Business,1903,1,1,1,1,3,4,5,4,4,4,4,3,4,4,6,4.0,satisfied +18180,123308,Female,Loyal Customer,47,Business travel,Business,2894,5,5,5,5,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +18181,121666,Male,Loyal Customer,51,Business travel,Business,511,3,3,3,3,5,5,4,4,4,4,4,5,4,3,3,0.0,satisfied +18182,78958,Male,Loyal Customer,53,Business travel,Business,1592,4,4,4,4,5,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +18183,81865,Male,disloyal Customer,25,Business travel,Eco,1050,3,3,3,2,1,3,1,1,3,3,4,5,4,1,0,0.0,neutral or dissatisfied +18184,37301,Female,Loyal Customer,42,Business travel,Eco,1035,5,2,2,2,2,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +18185,128890,Female,Loyal Customer,50,Business travel,Business,2454,1,1,1,1,4,4,4,4,2,5,4,4,3,4,0,0.0,satisfied +18186,62375,Male,Loyal Customer,52,Business travel,Business,2704,3,5,3,3,2,4,4,4,4,4,4,4,4,3,5,0.0,satisfied +18187,107339,Male,Loyal Customer,58,Business travel,Eco,632,4,2,2,2,4,4,4,4,4,5,3,2,4,4,5,7.0,neutral or dissatisfied +18188,62464,Male,Loyal Customer,53,Personal Travel,Business,1744,1,4,2,2,3,5,4,4,4,2,4,4,4,5,104,98.0,neutral or dissatisfied +18189,70503,Female,Loyal Customer,14,Personal Travel,Eco,867,3,4,3,3,4,3,4,4,5,4,5,4,2,4,0,0.0,neutral or dissatisfied +18190,38422,Male,Loyal Customer,37,Business travel,Eco,965,4,2,2,2,4,4,4,4,5,5,2,1,3,4,2,0.0,satisfied +18191,50432,Female,Loyal Customer,49,Business travel,Business,3333,1,5,5,5,5,4,4,1,1,1,1,2,1,2,4,0.0,neutral or dissatisfied +18192,71846,Male,Loyal Customer,58,Business travel,Business,1726,4,2,4,2,4,2,4,4,4,3,4,1,4,4,0,0.0,neutral or dissatisfied +18193,100730,Female,disloyal Customer,24,Business travel,Eco,328,0,0,0,2,2,0,2,2,4,2,5,5,5,2,0,0.0,satisfied +18194,76526,Female,disloyal Customer,38,Business travel,Business,516,4,4,4,4,1,4,1,1,3,3,5,3,5,1,4,22.0,satisfied +18195,56533,Male,Loyal Customer,59,Business travel,Business,3758,2,2,5,2,2,5,5,4,4,4,4,3,4,5,42,41.0,satisfied +18196,104678,Female,disloyal Customer,22,Business travel,Business,641,0,4,0,5,1,0,2,1,4,3,5,5,4,1,8,0.0,satisfied +18197,37632,Male,Loyal Customer,39,Personal Travel,Eco,1076,3,4,3,2,3,3,1,3,5,3,5,4,5,3,15,18.0,neutral or dissatisfied +18198,59569,Male,Loyal Customer,42,Business travel,Business,1583,5,5,5,5,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +18199,127857,Female,disloyal Customer,24,Business travel,Eco,1276,3,3,3,2,4,3,4,4,5,2,5,4,5,4,0,9.0,neutral or dissatisfied +18200,86642,Male,Loyal Customer,46,Business travel,Eco,346,4,2,2,2,4,4,4,4,2,1,2,1,1,4,7,12.0,satisfied +18201,85231,Female,disloyal Customer,27,Business travel,Eco,874,2,2,2,3,1,2,1,1,4,2,3,1,4,1,96,80.0,neutral or dissatisfied +18202,121146,Female,Loyal Customer,38,Business travel,Business,2370,1,3,5,5,2,2,4,1,1,1,1,1,1,2,1,0.0,neutral or dissatisfied +18203,116987,Female,Loyal Customer,16,Business travel,Business,621,2,5,5,5,2,2,2,2,1,2,4,2,3,2,2,4.0,neutral or dissatisfied +18204,42849,Male,Loyal Customer,44,Business travel,Eco,328,2,4,4,4,3,2,3,3,4,1,3,1,3,3,0,0.0,neutral or dissatisfied +18205,6447,Female,Loyal Customer,59,Personal Travel,Eco,315,1,3,1,4,1,5,4,3,3,1,4,4,3,4,0,18.0,neutral or dissatisfied +18206,124397,Male,disloyal Customer,37,Business travel,Eco Plus,408,3,3,3,3,2,3,1,2,1,1,3,3,3,2,0,0.0,neutral or dissatisfied +18207,104546,Male,Loyal Customer,61,Personal Travel,Eco,1047,5,3,5,1,2,5,1,2,3,3,2,3,3,2,0,0.0,satisfied +18208,114892,Female,Loyal Customer,47,Business travel,Business,417,5,1,5,5,4,4,5,2,2,2,2,3,2,5,66,51.0,satisfied +18209,44429,Male,Loyal Customer,42,Business travel,Eco,542,2,2,2,2,2,2,2,2,4,4,3,1,4,2,21,8.0,neutral or dissatisfied +18210,9324,Female,disloyal Customer,21,Business travel,Eco,542,2,3,2,4,1,2,1,1,3,2,3,3,4,1,35,42.0,neutral or dissatisfied +18211,44159,Female,disloyal Customer,40,Business travel,Business,229,4,4,4,3,5,4,5,5,3,1,3,3,5,5,5,5.0,neutral or dissatisfied +18212,18402,Male,Loyal Customer,42,Business travel,Business,284,2,3,3,3,3,3,4,2,2,2,2,3,2,2,114,100.0,neutral or dissatisfied +18213,118067,Male,Loyal Customer,49,Personal Travel,Eco,1262,2,4,2,1,4,2,4,4,3,3,5,3,5,4,46,32.0,neutral or dissatisfied +18214,119733,Female,Loyal Customer,54,Business travel,Business,1030,4,4,4,4,2,1,3,2,2,2,2,2,2,4,0,0.0,satisfied +18215,34142,Male,Loyal Customer,28,Business travel,Business,2746,2,5,5,5,2,2,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +18216,91463,Female,disloyal Customer,29,Business travel,Eco,859,4,4,4,4,2,4,2,2,2,4,4,2,3,2,7,17.0,neutral or dissatisfied +18217,25519,Female,disloyal Customer,21,Business travel,Eco,481,4,3,4,1,4,4,4,4,4,5,3,5,2,4,21,18.0,satisfied +18218,58753,Female,Loyal Customer,46,Business travel,Business,1050,3,3,3,3,4,4,4,4,4,4,4,3,4,5,64,71.0,satisfied +18219,107583,Male,Loyal Customer,44,Personal Travel,Eco Plus,1521,3,5,4,4,3,4,3,3,4,4,3,5,5,3,3,9.0,neutral or dissatisfied +18220,68924,Female,Loyal Customer,28,Business travel,Business,936,2,2,2,2,5,5,5,5,5,5,5,4,4,5,0,0.0,satisfied +18221,89091,Male,Loyal Customer,54,Business travel,Business,2139,5,5,5,5,5,5,4,2,2,2,2,3,2,4,107,104.0,satisfied +18222,83387,Male,Loyal Customer,45,Business travel,Business,632,4,4,2,4,2,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +18223,118394,Male,Loyal Customer,52,Business travel,Business,2287,2,5,5,5,1,2,2,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +18224,123381,Female,Loyal Customer,42,Business travel,Business,3010,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +18225,44709,Male,Loyal Customer,39,Personal Travel,Eco,67,3,4,0,2,2,0,5,2,3,2,5,5,5,2,19,20.0,neutral or dissatisfied +18226,19814,Female,Loyal Customer,20,Business travel,Business,654,3,3,3,3,3,3,3,3,2,1,2,2,3,3,25,28.0,satisfied +18227,56779,Male,Loyal Customer,68,Personal Travel,Eco Plus,997,3,5,3,5,2,3,1,2,3,3,4,4,5,2,0,23.0,neutral or dissatisfied +18228,109238,Male,Loyal Customer,19,Personal Travel,Eco,616,1,1,1,3,1,1,1,1,4,5,3,1,3,1,0,0.0,neutral or dissatisfied +18229,40369,Female,Loyal Customer,33,Business travel,Business,3954,4,4,4,4,1,2,3,3,3,3,3,2,3,2,0,16.0,satisfied +18230,3079,Female,Loyal Customer,42,Business travel,Business,594,5,5,5,5,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +18231,47432,Female,Loyal Customer,46,Business travel,Business,174,0,4,0,4,5,4,4,3,3,3,3,3,3,1,0,0.0,satisfied +18232,4743,Male,Loyal Customer,26,Personal Travel,Eco,888,2,4,2,4,3,2,3,3,4,4,5,4,5,3,17,10.0,neutral or dissatisfied +18233,69424,Female,Loyal Customer,44,Business travel,Business,696,3,3,3,3,3,2,2,3,3,3,3,4,3,1,10,7.0,neutral or dissatisfied +18234,25163,Male,Loyal Customer,35,Business travel,Eco Plus,2106,2,3,3,3,2,2,2,2,3,1,4,3,3,2,21,0.0,neutral or dissatisfied +18235,63838,Female,Loyal Customer,21,Business travel,Business,1839,2,2,2,2,3,4,3,3,4,4,4,4,4,3,0,26.0,satisfied +18236,45002,Female,Loyal Customer,52,Business travel,Business,1553,4,4,4,4,5,1,3,3,3,3,3,2,3,3,0,10.0,satisfied +18237,61336,Female,disloyal Customer,43,Business travel,Business,602,3,3,3,4,5,3,5,5,4,5,5,3,4,5,0,4.0,neutral or dissatisfied +18238,114443,Male,Loyal Customer,44,Business travel,Business,3916,2,2,2,2,2,5,5,1,1,2,1,4,1,5,0,1.0,satisfied +18239,10133,Female,Loyal Customer,28,Personal Travel,Eco,975,3,4,3,4,3,3,1,3,2,4,2,4,4,3,16,12.0,neutral or dissatisfied +18240,73937,Male,Loyal Customer,31,Business travel,Eco,2342,2,4,4,4,2,2,2,3,1,3,3,2,4,2,3,27.0,neutral or dissatisfied +18241,84267,Male,Loyal Customer,46,Business travel,Eco,334,3,1,1,1,3,3,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +18242,33747,Female,Loyal Customer,31,Business travel,Eco Plus,2277,5,1,1,1,5,5,5,5,5,1,4,2,2,5,0,0.0,satisfied +18243,100947,Female,Loyal Customer,51,Business travel,Business,2147,2,2,2,2,5,4,5,5,5,5,5,5,5,3,25,3.0,satisfied +18244,63594,Female,Loyal Customer,56,Personal Travel,Eco,2133,2,1,2,3,4,2,2,4,4,2,4,1,4,1,0,0.0,neutral or dissatisfied +18245,40659,Female,Loyal Customer,54,Business travel,Business,590,2,4,2,2,5,5,4,4,4,5,4,4,4,5,6,50.0,satisfied +18246,19675,Male,Loyal Customer,31,Business travel,Business,3935,5,5,5,5,4,4,4,4,4,1,2,2,5,4,55,48.0,satisfied +18247,68880,Male,Loyal Customer,28,Business travel,Eco,936,1,2,2,2,1,1,1,1,3,3,3,1,2,1,0,0.0,neutral or dissatisfied +18248,38763,Male,Loyal Customer,48,Business travel,Eco,387,5,1,1,1,5,5,5,5,3,1,1,1,3,5,0,0.0,satisfied +18249,51874,Male,disloyal Customer,29,Business travel,Eco,771,1,1,1,1,5,1,3,5,2,5,2,1,1,5,83,76.0,neutral or dissatisfied +18250,17670,Female,Loyal Customer,45,Business travel,Business,3575,0,0,0,1,5,2,2,4,4,4,2,1,4,4,12,23.0,satisfied +18251,22343,Male,disloyal Customer,68,Business travel,Eco,238,3,1,3,4,4,3,4,4,2,5,4,2,4,4,0,0.0,neutral or dissatisfied +18252,55173,Female,Loyal Customer,67,Personal Travel,Eco,1379,4,4,3,4,2,5,4,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +18253,58089,Male,Loyal Customer,54,Business travel,Business,589,3,1,5,1,2,4,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +18254,109938,Female,Loyal Customer,29,Personal Travel,Eco,971,2,2,2,3,4,2,4,4,1,2,3,4,3,4,1,0.0,neutral or dissatisfied +18255,49114,Female,Loyal Customer,47,Business travel,Eco,209,5,4,3,4,4,5,1,5,5,5,5,1,5,1,0,0.0,satisfied +18256,107634,Male,disloyal Customer,23,Business travel,Business,251,0,0,0,3,4,0,4,4,4,3,4,5,4,4,33,20.0,satisfied +18257,11314,Male,Loyal Customer,54,Personal Travel,Eco,667,1,2,1,3,3,1,4,3,1,2,3,1,4,3,3,0.0,neutral or dissatisfied +18258,88596,Female,Loyal Customer,17,Personal Travel,Eco,270,4,5,4,4,1,4,1,1,5,5,4,5,5,1,4,0.0,satisfied +18259,120141,Male,Loyal Customer,11,Business travel,Business,1475,3,3,3,3,5,5,5,5,5,3,4,5,4,5,46,23.0,satisfied +18260,17909,Male,disloyal Customer,35,Business travel,Eco,900,1,1,1,2,3,1,3,3,2,5,2,3,2,3,1,20.0,neutral or dissatisfied +18261,37615,Female,Loyal Customer,33,Personal Travel,Eco,944,3,2,3,4,2,3,2,2,3,1,3,3,3,2,0,5.0,neutral or dissatisfied +18262,5461,Male,Loyal Customer,47,Personal Travel,Eco,265,2,3,2,3,2,2,2,2,1,2,3,4,2,2,0,0.0,neutral or dissatisfied +18263,94304,Male,Loyal Customer,36,Business travel,Business,2711,4,4,4,4,3,4,4,5,5,5,5,4,5,5,2,0.0,satisfied +18264,95052,Female,Loyal Customer,70,Personal Travel,Eco,189,1,4,1,3,2,5,5,3,3,1,3,4,3,3,43,44.0,neutral or dissatisfied +18265,49780,Female,disloyal Customer,21,Business travel,Eco,262,1,1,1,3,3,1,3,3,4,3,3,1,4,3,0,0.0,neutral or dissatisfied +18266,81316,Female,disloyal Customer,25,Business travel,Business,1299,3,0,3,3,1,3,1,1,3,5,5,3,4,1,109,74.0,neutral or dissatisfied +18267,122894,Male,Loyal Customer,39,Personal Travel,Eco Plus,226,3,4,0,1,4,0,4,4,5,3,4,3,4,4,0,0.0,neutral or dissatisfied +18268,122205,Male,Loyal Customer,39,Business travel,Business,3717,5,5,5,5,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +18269,9569,Female,disloyal Customer,27,Business travel,Business,229,2,2,2,4,3,2,3,3,3,2,5,4,5,3,0,0.0,neutral or dissatisfied +18270,67635,Female,Loyal Customer,39,Business travel,Business,1188,5,5,5,5,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +18271,39133,Male,Loyal Customer,44,Business travel,Eco,119,4,1,1,1,4,4,4,4,4,3,3,5,1,4,15,0.0,satisfied +18272,123438,Male,disloyal Customer,26,Business travel,Business,2296,3,3,3,1,5,3,5,5,5,2,5,3,5,5,9,3.0,neutral or dissatisfied +18273,44128,Female,disloyal Customer,41,Business travel,Business,74,4,5,5,2,4,5,4,4,1,5,4,3,2,4,0,0.0,satisfied +18274,108748,Male,Loyal Customer,42,Business travel,Business,3170,1,1,1,1,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +18275,127342,Female,Loyal Customer,45,Business travel,Business,507,5,5,5,5,4,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +18276,53286,Male,Loyal Customer,42,Business travel,Business,901,4,4,3,4,4,4,1,2,2,3,2,2,2,3,14,0.0,satisfied +18277,26020,Female,Loyal Customer,35,Personal Travel,Eco,425,3,2,3,3,1,3,1,1,1,3,3,1,3,1,2,0.0,neutral or dissatisfied +18278,5677,Female,Loyal Customer,35,Business travel,Business,3805,3,3,3,3,4,5,5,3,3,4,4,4,3,3,0,0.0,satisfied +18279,86378,Male,Loyal Customer,44,Business travel,Business,1559,1,1,1,1,2,4,5,3,3,4,3,4,3,4,12,9.0,satisfied +18280,5445,Female,Loyal Customer,44,Business travel,Business,3594,3,3,3,3,4,4,5,5,5,5,5,4,5,4,7,13.0,satisfied +18281,108705,Male,Loyal Customer,58,Business travel,Business,3400,1,1,1,1,2,4,5,4,4,5,4,3,4,4,19,7.0,satisfied +18282,86431,Female,disloyal Customer,35,Business travel,Eco,762,2,2,2,4,2,2,2,2,3,1,3,1,3,2,3,0.0,neutral or dissatisfied +18283,95561,Male,Loyal Customer,70,Personal Travel,Eco Plus,677,3,4,3,2,2,3,2,2,5,5,5,4,4,2,29,16.0,neutral or dissatisfied +18284,110456,Male,Loyal Customer,41,Personal Travel,Eco,842,4,4,4,2,4,4,4,4,1,5,5,4,1,4,13,0.0,neutral or dissatisfied +18285,108896,Male,Loyal Customer,46,Business travel,Business,3889,5,3,5,5,5,5,4,5,5,5,5,4,5,5,13,2.0,satisfied +18286,39262,Female,Loyal Customer,39,Business travel,Eco,67,3,2,2,2,3,3,3,3,4,2,4,4,3,3,35,26.0,neutral or dissatisfied +18287,126378,Male,Loyal Customer,45,Personal Travel,Eco,468,3,4,3,1,1,3,1,1,3,4,4,4,5,1,110,116.0,neutral or dissatisfied +18288,47743,Male,Loyal Customer,41,Business travel,Business,329,5,5,5,5,1,1,5,4,4,4,4,4,4,2,0,0.0,satisfied +18289,34163,Male,disloyal Customer,25,Business travel,Eco,1237,4,4,4,2,5,4,3,5,3,2,4,1,3,5,0,0.0,satisfied +18290,26580,Female,Loyal Customer,35,Business travel,Business,2458,4,4,4,4,2,3,3,3,3,4,3,1,3,4,0,0.0,satisfied +18291,2792,Male,Loyal Customer,24,Business travel,Business,3902,2,1,1,1,2,2,2,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +18292,51512,Female,Loyal Customer,53,Business travel,Eco,493,5,1,1,1,1,1,5,4,4,5,4,1,4,2,2,6.0,satisfied +18293,10599,Female,disloyal Customer,24,Business travel,Eco,224,2,2,3,3,5,3,5,5,3,1,4,3,4,5,4,14.0,neutral or dissatisfied +18294,100719,Male,Loyal Customer,42,Business travel,Business,328,1,1,1,1,3,5,4,4,4,4,4,4,4,3,28,20.0,satisfied +18295,83149,Female,Loyal Customer,46,Personal Travel,Eco,983,2,4,2,3,5,4,4,1,1,2,5,3,1,3,8,36.0,neutral or dissatisfied +18296,45806,Male,Loyal Customer,43,Business travel,Business,411,2,5,5,5,5,4,4,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +18297,124785,Female,Loyal Customer,66,Business travel,Business,2327,1,1,1,1,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +18298,67746,Female,Loyal Customer,47,Business travel,Business,1438,2,1,1,1,5,4,3,2,2,2,2,4,2,3,10,7.0,neutral or dissatisfied +18299,111378,Male,disloyal Customer,27,Business travel,Business,1111,2,3,3,4,5,3,5,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +18300,72775,Male,Loyal Customer,53,Business travel,Business,1856,5,5,5,5,5,5,5,5,5,5,5,3,5,4,9,0.0,satisfied +18301,99362,Female,Loyal Customer,53,Business travel,Business,409,1,1,1,1,5,5,5,5,5,5,5,3,5,4,12,3.0,satisfied +18302,82819,Female,Loyal Customer,46,Business travel,Business,645,3,4,4,4,1,4,3,3,3,3,3,2,3,1,0,15.0,neutral or dissatisfied +18303,18138,Male,disloyal Customer,26,Business travel,Eco,750,2,2,2,3,1,2,1,1,4,1,1,2,3,1,0,0.0,neutral or dissatisfied +18304,92266,Female,Loyal Customer,40,Business travel,Business,1900,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +18305,25712,Female,Loyal Customer,50,Business travel,Eco,447,3,1,1,1,4,4,4,4,4,3,4,3,4,1,11,0.0,satisfied +18306,54159,Male,Loyal Customer,25,Business travel,Business,1400,1,3,3,3,1,1,1,1,2,1,2,3,2,1,0,0.0,neutral or dissatisfied +18307,31979,Female,Loyal Customer,58,Business travel,Business,2351,2,2,2,2,2,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +18308,80577,Male,Loyal Customer,37,Business travel,Eco,247,2,1,1,1,2,2,2,2,4,3,4,3,3,2,0,0.0,neutral or dissatisfied +18309,75668,Female,Loyal Customer,44,Business travel,Business,3407,4,4,4,4,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +18310,69854,Female,Loyal Customer,29,Personal Travel,Eco,1055,2,4,2,1,1,2,1,1,4,4,4,4,4,1,8,0.0,neutral or dissatisfied +18311,28970,Female,Loyal Customer,52,Business travel,Business,3758,4,2,2,2,1,2,2,4,4,4,4,3,4,3,0,7.0,neutral or dissatisfied +18312,46446,Male,Loyal Customer,64,Personal Travel,Eco,1199,2,3,2,4,1,2,1,1,4,1,4,2,4,1,2,6.0,neutral or dissatisfied +18313,104683,Male,Loyal Customer,47,Business travel,Business,159,2,5,5,5,5,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +18314,90118,Male,Loyal Customer,40,Business travel,Business,1127,2,5,5,5,4,4,4,2,2,2,2,4,2,3,41,65.0,neutral or dissatisfied +18315,115281,Female,Loyal Customer,41,Business travel,Business,3007,4,4,4,4,4,4,4,4,3,5,4,4,3,4,144,135.0,satisfied +18316,88105,Female,Loyal Customer,31,Business travel,Business,3593,5,5,5,5,5,5,5,5,3,4,4,4,5,5,0,0.0,satisfied +18317,124458,Male,Loyal Customer,29,Business travel,Business,980,4,4,2,4,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +18318,113456,Female,Loyal Customer,44,Business travel,Business,258,3,3,3,3,5,5,5,4,4,4,4,4,4,5,23,20.0,satisfied +18319,19623,Male,Loyal Customer,49,Business travel,Business,717,3,2,2,2,4,3,3,3,3,2,3,1,3,4,7,0.0,neutral or dissatisfied +18320,108533,Male,Loyal Customer,32,Personal Travel,Eco,649,3,2,3,4,1,3,1,1,4,5,4,1,4,1,0,0.0,neutral or dissatisfied +18321,118126,Male,Loyal Customer,68,Personal Travel,Eco Plus,1506,1,5,0,1,1,0,1,1,3,1,2,4,5,1,8,6.0,neutral or dissatisfied +18322,58457,Male,Loyal Customer,48,Business travel,Business,733,4,4,4,4,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +18323,104484,Male,Loyal Customer,44,Business travel,Business,1730,2,2,2,2,4,5,5,3,3,4,3,5,3,4,0,0.0,satisfied +18324,39036,Female,Loyal Customer,66,Personal Travel,Eco,260,3,0,0,2,3,4,3,1,1,0,1,5,1,1,0,25.0,neutral or dissatisfied +18325,4323,Male,Loyal Customer,36,Business travel,Business,2740,2,5,5,5,1,4,3,1,1,1,2,1,1,2,0,0.0,neutral or dissatisfied +18326,67052,Female,Loyal Customer,30,Business travel,Business,3468,3,5,5,5,3,2,3,3,1,1,3,3,4,3,4,9.0,neutral or dissatisfied +18327,120154,Female,disloyal Customer,17,Business travel,Eco,1091,5,5,5,2,5,3,3,5,2,5,4,3,3,3,0,7.0,satisfied +18328,91134,Female,Loyal Customer,62,Personal Travel,Eco,250,3,5,3,2,2,5,4,3,3,3,3,4,3,5,0,0.0,neutral or dissatisfied +18329,29709,Female,Loyal Customer,33,Business travel,Business,2304,5,5,5,5,4,3,1,4,4,5,4,2,4,2,16,10.0,satisfied +18330,91264,Male,Loyal Customer,68,Personal Travel,Eco,646,3,3,2,4,3,2,3,3,1,1,1,2,1,3,80,82.0,neutral or dissatisfied +18331,97575,Male,Loyal Customer,39,Business travel,Eco,337,3,3,3,3,3,3,3,3,3,4,4,3,4,3,59,53.0,neutral or dissatisfied +18332,64821,Female,Loyal Customer,46,Business travel,Business,551,4,4,4,4,5,4,4,4,4,4,4,3,4,5,0,4.0,satisfied +18333,90748,Female,disloyal Customer,50,Business travel,Eco,581,1,1,1,2,3,1,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +18334,123161,Male,disloyal Customer,28,Business travel,Eco,250,2,0,2,1,4,2,4,4,3,3,2,2,3,4,0,0.0,neutral or dissatisfied +18335,58707,Male,disloyal Customer,59,Business travel,Business,2743,3,2,2,4,3,2,2,2,3,5,4,2,2,2,0,4.0,neutral or dissatisfied +18336,13987,Male,Loyal Customer,41,Personal Travel,Business,541,4,4,4,3,2,5,4,2,2,4,2,5,2,4,0,0.0,neutral or dissatisfied +18337,111511,Female,Loyal Customer,37,Business travel,Eco,391,4,1,1,1,4,4,4,4,4,2,2,3,2,4,6,0.0,neutral or dissatisfied +18338,2134,Female,disloyal Customer,45,Business travel,Eco,431,3,3,3,3,3,3,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +18339,120304,Female,Loyal Customer,50,Business travel,Business,2062,3,3,3,3,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +18340,127992,Female,Loyal Customer,54,Business travel,Business,1488,3,3,3,3,4,5,4,5,5,5,5,3,5,5,11,18.0,satisfied +18341,124968,Female,Loyal Customer,40,Business travel,Business,184,0,5,0,5,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +18342,71122,Female,Loyal Customer,47,Business travel,Business,1739,5,5,5,5,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +18343,69281,Female,Loyal Customer,64,Personal Travel,Eco,733,1,4,1,1,3,5,1,2,2,1,2,2,2,2,0,7.0,neutral or dissatisfied +18344,121444,Male,Loyal Customer,60,Business travel,Business,2887,2,5,5,5,3,4,3,2,2,2,2,1,2,3,19,19.0,neutral or dissatisfied +18345,87478,Male,Loyal Customer,49,Business travel,Business,3796,4,4,4,4,4,4,4,5,5,5,5,4,5,3,0,3.0,satisfied +18346,67297,Male,Loyal Customer,48,Business travel,Business,2187,4,4,4,4,3,5,5,4,4,4,4,5,4,3,41,92.0,satisfied +18347,13647,Female,Loyal Customer,36,Business travel,Business,196,2,2,2,2,5,3,4,5,5,5,5,5,5,4,54,36.0,satisfied +18348,66449,Male,Loyal Customer,50,Business travel,Eco,1217,4,3,3,3,4,4,4,4,3,3,4,4,4,4,25,15.0,neutral or dissatisfied +18349,94839,Female,disloyal Customer,38,Business travel,Eco,248,2,1,2,4,2,2,2,2,3,4,3,3,4,2,26,21.0,neutral or dissatisfied +18350,74556,Female,Loyal Customer,46,Business travel,Eco,1431,2,4,4,4,1,4,3,2,2,2,2,1,2,3,3,0.0,neutral or dissatisfied +18351,115673,Female,disloyal Customer,33,Business travel,Business,417,2,3,3,5,3,3,3,3,3,4,4,5,5,3,0,0.0,neutral or dissatisfied +18352,119723,Female,Loyal Customer,47,Business travel,Business,3251,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +18353,121538,Male,Loyal Customer,28,Business travel,Business,3046,1,1,1,1,4,4,4,4,5,2,5,4,4,4,0,0.0,satisfied +18354,98900,Female,Loyal Customer,34,Personal Travel,Business,569,1,5,1,3,2,4,5,3,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +18355,81001,Female,Loyal Customer,28,Personal Travel,Eco,297,4,5,4,1,5,4,5,5,4,5,4,3,5,5,0,16.0,neutral or dissatisfied +18356,86597,Male,disloyal Customer,22,Business travel,Business,746,3,2,3,3,3,3,3,3,1,4,4,2,4,3,0,14.0,neutral or dissatisfied +18357,62503,Male,Loyal Customer,55,Business travel,Business,1744,2,2,4,2,5,4,4,4,4,4,4,4,4,5,0,11.0,satisfied +18358,88136,Female,Loyal Customer,36,Business travel,Business,2555,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +18359,53147,Male,Loyal Customer,70,Personal Travel,Eco,413,2,4,2,5,2,2,3,2,5,2,4,5,5,2,1,0.0,neutral or dissatisfied +18360,69479,Female,Loyal Customer,43,Business travel,Business,3642,2,2,2,2,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +18361,115788,Female,Loyal Customer,76,Business travel,Business,3965,1,5,5,5,5,4,4,1,1,2,1,1,1,1,16,12.0,neutral or dissatisfied +18362,88155,Male,Loyal Customer,56,Business travel,Business,270,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,1.0,satisfied +18363,13453,Female,Loyal Customer,68,Personal Travel,Eco,475,2,4,2,3,2,3,2,1,1,2,1,3,1,5,117,110.0,neutral or dissatisfied +18364,36041,Male,Loyal Customer,43,Business travel,Business,474,5,5,5,5,5,4,4,4,4,4,4,4,4,2,0,0.0,satisfied +18365,15692,Male,Loyal Customer,39,Personal Travel,Eco,335,1,4,1,3,2,1,3,2,3,5,5,5,5,2,0,0.0,neutral or dissatisfied +18366,6720,Female,Loyal Customer,34,Personal Travel,Eco,438,1,4,1,1,3,1,3,3,5,2,5,2,5,3,0,0.0,neutral or dissatisfied +18367,59825,Male,Loyal Customer,50,Business travel,Business,2160,1,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +18368,25852,Female,Loyal Customer,48,Personal Travel,Eco,692,4,4,4,3,3,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +18369,116440,Female,Loyal Customer,22,Personal Travel,Eco,447,0,5,0,1,1,0,3,1,3,2,5,4,5,1,0,0.0,satisfied +18370,108926,Female,Loyal Customer,25,Personal Travel,Eco,1075,1,2,1,3,4,1,4,4,4,3,3,4,3,4,0,0.0,neutral or dissatisfied +18371,33894,Female,disloyal Customer,25,Business travel,Eco,1504,1,1,1,5,5,1,5,5,2,5,5,5,5,5,0,0.0,neutral or dissatisfied +18372,38925,Male,disloyal Customer,30,Business travel,Eco,162,3,0,3,4,3,3,3,3,3,2,1,4,5,3,0,0.0,neutral or dissatisfied +18373,128776,Male,Loyal Customer,61,Personal Travel,Eco Plus,550,5,5,5,4,1,5,1,1,1,3,5,2,5,1,0,0.0,satisfied +18374,7056,Male,disloyal Customer,24,Business travel,Eco,273,4,4,4,4,2,4,4,2,4,3,4,5,5,2,72,116.0,satisfied +18375,365,Female,Loyal Customer,42,Business travel,Business,1924,2,2,2,2,5,5,4,4,4,4,4,5,4,4,13,7.0,satisfied +18376,75928,Male,Loyal Customer,64,Personal Travel,Eco,205,2,5,0,3,3,0,3,3,2,4,4,1,4,3,94,95.0,neutral or dissatisfied +18377,102582,Female,disloyal Customer,26,Business travel,Eco Plus,407,4,1,4,3,1,4,1,1,1,5,2,2,3,1,40,33.0,neutral or dissatisfied +18378,110042,Female,Loyal Customer,23,Business travel,Business,2039,3,2,2,2,3,3,3,3,2,2,2,4,4,3,2,0.0,neutral or dissatisfied +18379,20175,Female,Loyal Customer,25,Personal Travel,Eco,403,0,5,0,1,3,0,3,3,5,2,4,5,4,3,7,5.0,satisfied +18380,119598,Female,Loyal Customer,49,Business travel,Business,1979,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +18381,54325,Male,Loyal Customer,23,Business travel,Business,1597,3,4,4,4,2,3,3,3,5,1,2,3,1,3,146,102.0,neutral or dissatisfied +18382,6163,Male,Loyal Customer,49,Business travel,Eco,409,1,1,4,1,1,1,1,1,1,3,3,1,2,1,0,0.0,neutral or dissatisfied +18383,17997,Male,Loyal Customer,29,Business travel,Business,3801,2,2,3,2,4,4,4,4,2,3,5,4,2,4,0,0.0,satisfied +18384,7596,Female,Loyal Customer,17,Business travel,Business,2728,1,1,1,1,5,5,5,5,3,4,5,5,5,5,0,0.0,satisfied +18385,61510,Female,Loyal Customer,14,Personal Travel,Eco,2288,4,3,4,3,1,4,1,1,1,2,3,4,2,1,23,0.0,neutral or dissatisfied +18386,37648,Female,Loyal Customer,14,Personal Travel,Eco,1047,3,5,3,4,2,3,2,2,4,4,4,4,4,2,40,28.0,neutral or dissatisfied +18387,110661,Male,disloyal Customer,10,Business travel,Business,837,4,0,4,2,4,4,4,4,3,2,5,4,5,4,3,2.0,satisfied +18388,77533,Male,Loyal Customer,44,Business travel,Business,1889,1,1,1,1,2,4,5,4,4,4,4,4,4,3,98,91.0,satisfied +18389,84561,Female,Loyal Customer,10,Personal Travel,Eco,2486,1,1,1,3,4,1,4,4,3,5,2,3,3,4,1,0.0,neutral or dissatisfied +18390,1316,Female,Loyal Customer,39,Business travel,Business,2204,1,1,1,1,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +18391,58233,Male,Loyal Customer,40,Personal Travel,Eco,925,2,4,2,3,2,2,2,2,5,5,4,3,5,2,16,0.0,neutral or dissatisfied +18392,66742,Male,Loyal Customer,8,Personal Travel,Eco,802,2,3,3,3,5,3,1,5,1,2,5,4,3,5,0,0.0,neutral or dissatisfied +18393,103672,Male,Loyal Customer,30,Business travel,Business,1823,2,2,2,2,5,5,5,5,3,3,4,5,5,5,0,0.0,satisfied +18394,31009,Female,Loyal Customer,33,Business travel,Business,391,2,2,2,2,2,2,2,2,2,2,2,1,2,2,29,26.0,neutral or dissatisfied +18395,18246,Female,Loyal Customer,62,Business travel,Business,346,4,2,2,2,5,4,3,4,4,3,4,3,4,4,1,12.0,neutral or dissatisfied +18396,27489,Female,Loyal Customer,53,Business travel,Eco,671,1,5,5,5,4,4,3,1,1,1,1,3,1,2,0,4.0,neutral or dissatisfied +18397,24121,Male,Loyal Customer,32,Personal Travel,Eco,779,1,3,1,5,1,3,5,4,2,2,3,5,4,5,138,150.0,neutral or dissatisfied +18398,22860,Female,Loyal Customer,47,Personal Travel,Eco,302,3,4,3,2,4,4,5,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +18399,125329,Male,Loyal Customer,36,Business travel,Business,599,3,3,3,3,5,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +18400,8230,Female,Loyal Customer,36,Personal Travel,Eco,125,2,4,2,2,1,2,1,1,2,1,3,5,4,1,0,0.0,neutral or dissatisfied +18401,61157,Female,Loyal Customer,40,Business travel,Business,967,1,1,1,1,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +18402,83419,Female,disloyal Customer,21,Business travel,Business,232,0,3,0,5,4,0,4,4,4,3,2,5,3,4,0,0.0,satisfied +18403,10934,Male,Loyal Customer,43,Business travel,Eco,158,2,2,5,2,2,2,2,2,4,3,2,2,2,2,112,109.0,neutral or dissatisfied +18404,72331,Female,Loyal Customer,36,Business travel,Business,3214,3,3,3,3,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +18405,97677,Female,Loyal Customer,24,Personal Travel,Eco,272,2,4,2,4,5,2,5,5,4,3,3,1,4,5,0,5.0,neutral or dissatisfied +18406,20884,Male,Loyal Customer,29,Business travel,Eco Plus,508,5,3,3,3,5,5,5,5,2,4,3,1,2,5,0,0.0,satisfied +18407,107335,Female,Loyal Customer,49,Business travel,Business,632,1,1,4,1,4,5,5,4,4,4,4,4,4,5,11,20.0,satisfied +18408,51076,Male,Loyal Customer,52,Personal Travel,Eco,337,1,5,1,1,2,1,2,2,2,3,5,3,3,2,0,0.0,neutral or dissatisfied +18409,55876,Male,Loyal Customer,55,Business travel,Business,2335,1,1,1,1,3,5,4,5,5,5,5,4,5,4,2,3.0,satisfied +18410,72222,Female,Loyal Customer,52,Business travel,Business,2258,4,4,4,4,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +18411,63546,Male,Loyal Customer,45,Personal Travel,Eco,1009,2,2,2,3,5,2,5,5,1,2,4,2,3,5,0,0.0,neutral or dissatisfied +18412,17524,Male,Loyal Customer,61,Personal Travel,Eco,241,3,5,3,3,5,3,5,5,5,5,5,3,4,5,39,29.0,neutral or dissatisfied +18413,62557,Male,disloyal Customer,29,Business travel,Eco,922,2,2,2,4,1,2,1,1,1,5,3,3,3,1,0,0.0,neutral or dissatisfied +18414,28936,Female,Loyal Customer,55,Business travel,Eco,697,2,4,3,3,5,3,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +18415,65594,Male,disloyal Customer,22,Business travel,Eco,175,4,1,5,2,5,5,5,5,4,4,3,2,3,5,0,0.0,neutral or dissatisfied +18416,31929,Male,Loyal Customer,37,Business travel,Business,216,5,5,5,5,3,5,4,5,5,5,4,3,5,5,0,0.0,satisfied +18417,114760,Female,Loyal Customer,42,Business travel,Business,3094,2,2,2,2,4,4,5,5,5,5,5,5,5,3,55,50.0,satisfied +18418,124304,Male,Loyal Customer,63,Business travel,Eco,255,2,5,3,5,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +18419,75316,Male,Loyal Customer,46,Business travel,Business,2486,1,1,1,1,5,3,4,5,5,5,5,3,5,5,0,7.0,satisfied +18420,86398,Female,Loyal Customer,29,Business travel,Business,2558,4,4,4,4,4,4,4,4,4,2,5,5,5,4,10,0.0,satisfied +18421,107798,Male,Loyal Customer,67,Business travel,Business,349,0,1,1,3,3,5,4,3,3,3,3,4,3,4,26,9.0,satisfied +18422,5540,Male,Loyal Customer,12,Personal Travel,Eco,404,1,1,1,3,5,1,5,5,3,3,3,3,2,5,0,0.0,neutral or dissatisfied +18423,11439,Male,Loyal Customer,31,Business travel,Eco Plus,163,1,5,4,4,1,1,1,1,2,4,1,4,1,1,0,0.0,neutral or dissatisfied +18424,18679,Male,Loyal Customer,19,Personal Travel,Eco,253,0,4,0,3,2,0,2,2,3,1,4,2,3,2,0,0.0,satisfied +18425,85043,Male,Loyal Customer,54,Business travel,Business,813,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,1.0,satisfied +18426,128111,Male,disloyal Customer,23,Business travel,Eco,1344,2,3,3,1,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +18427,118746,Female,Loyal Customer,55,Personal Travel,Eco,325,4,5,4,3,4,5,5,4,2,4,1,5,4,5,138,137.0,neutral or dissatisfied +18428,70346,Male,Loyal Customer,49,Personal Travel,Eco,986,2,4,3,5,3,3,3,3,3,5,5,3,4,3,0,0.0,neutral or dissatisfied +18429,117391,Male,Loyal Customer,49,Personal Travel,Eco,912,2,4,2,2,3,2,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +18430,52676,Male,Loyal Customer,32,Personal Travel,Eco,160,3,5,3,3,3,3,2,3,3,4,4,4,4,3,0,0.0,neutral or dissatisfied +18431,64390,Male,Loyal Customer,63,Personal Travel,Eco,1212,1,0,1,3,4,1,4,4,3,4,5,4,4,4,0,7.0,neutral or dissatisfied +18432,76726,Male,Loyal Customer,31,Business travel,Eco Plus,357,0,0,0,4,3,0,3,3,3,4,3,5,3,3,0,0.0,satisfied +18433,114862,Male,disloyal Customer,42,Business travel,Business,371,5,5,5,5,2,5,2,2,5,2,5,4,4,2,29,18.0,satisfied +18434,73245,Female,Loyal Customer,45,Business travel,Business,675,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +18435,62783,Male,Loyal Customer,31,Business travel,Eco,2399,4,1,3,3,4,4,4,4,1,2,4,5,1,4,0,0.0,satisfied +18436,68081,Male,Loyal Customer,42,Business travel,Business,868,1,1,4,1,4,4,4,2,2,2,2,4,2,5,16,3.0,satisfied +18437,67453,Female,Loyal Customer,54,Personal Travel,Eco,678,3,4,3,1,2,4,4,1,1,3,1,5,1,4,8,5.0,neutral or dissatisfied +18438,66855,Female,Loyal Customer,54,Personal Travel,Eco,731,1,4,1,3,4,4,4,2,2,1,2,4,2,1,2,6.0,neutral or dissatisfied +18439,3789,Male,disloyal Customer,39,Business travel,Eco,199,2,2,2,3,1,2,1,1,4,2,4,2,3,1,50,32.0,neutral or dissatisfied +18440,19668,Female,Loyal Customer,80,Business travel,Business,3363,4,4,3,4,5,4,5,3,3,3,3,5,3,4,13,10.0,satisfied +18441,41139,Male,Loyal Customer,35,Personal Travel,Eco,429,3,5,3,1,5,3,2,5,4,2,2,3,5,5,0,0.0,neutral or dissatisfied +18442,64371,Female,Loyal Customer,47,Personal Travel,Eco,1158,2,3,2,3,2,5,3,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +18443,67363,Male,Loyal Customer,46,Personal Travel,Business,641,0,4,0,1,5,4,5,3,3,0,3,4,3,4,1,0.0,satisfied +18444,47768,Female,Loyal Customer,45,Business travel,Business,834,5,5,5,5,2,1,4,4,4,4,4,2,4,1,39,43.0,satisfied +18445,80798,Female,Loyal Customer,28,Business travel,Business,2834,1,1,1,1,4,4,4,4,4,5,4,3,4,4,0,0.0,satisfied +18446,88059,Male,Loyal Customer,31,Business travel,Business,3340,1,1,1,1,3,4,3,3,5,3,4,5,5,3,17,12.0,satisfied +18447,128939,Female,Loyal Customer,51,Business travel,Business,2668,2,2,2,2,2,5,5,4,4,4,4,4,4,4,8,0.0,satisfied +18448,44048,Male,Loyal Customer,54,Personal Travel,Eco,237,2,5,2,3,1,2,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +18449,82583,Male,disloyal Customer,27,Business travel,Business,528,2,2,2,3,4,2,4,4,4,5,4,4,5,4,0,0.0,neutral or dissatisfied +18450,109189,Female,disloyal Customer,29,Business travel,Eco,612,2,1,2,4,4,2,4,4,4,3,3,1,3,4,21,26.0,neutral or dissatisfied +18451,73991,Female,Loyal Customer,31,Personal Travel,Business,1972,4,2,4,4,4,4,4,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +18452,100525,Male,Loyal Customer,69,Personal Travel,Eco,580,4,2,4,3,2,4,2,2,4,5,4,1,3,2,12,0.0,neutral or dissatisfied +18453,77726,Male,Loyal Customer,25,Business travel,Business,689,2,3,3,3,2,2,2,2,3,5,4,1,3,2,0,0.0,neutral or dissatisfied +18454,76620,Male,disloyal Customer,29,Business travel,Eco,516,1,4,1,2,3,1,3,3,4,2,2,1,5,3,5,0.0,neutral or dissatisfied +18455,69007,Male,Loyal Customer,33,Business travel,Business,1389,5,5,5,5,4,4,4,4,4,3,5,5,4,4,0,0.0,satisfied +18456,60773,Female,Loyal Customer,55,Business travel,Eco,628,4,2,2,2,3,3,1,4,4,4,4,2,4,1,0,0.0,satisfied +18457,67619,Female,Loyal Customer,46,Business travel,Business,1438,3,3,3,3,2,4,5,5,5,5,5,5,5,5,59,55.0,satisfied +18458,43845,Male,Loyal Customer,48,Business travel,Eco,174,4,4,4,4,4,4,4,4,5,3,4,3,4,4,0,30.0,satisfied +18459,121517,Female,disloyal Customer,23,Business travel,Eco,936,3,3,3,4,2,3,2,2,4,3,3,4,4,2,0,0.0,neutral or dissatisfied +18460,104454,Male,Loyal Customer,50,Business travel,Business,1015,1,1,5,1,2,4,5,2,2,2,2,5,2,4,17,6.0,satisfied +18461,69172,Female,disloyal Customer,37,Business travel,Eco,187,1,0,1,3,5,1,5,5,5,1,1,1,5,5,0,0.0,neutral or dissatisfied +18462,116355,Male,Loyal Customer,34,Personal Travel,Eco,446,2,4,2,5,5,2,5,5,5,2,4,3,5,5,10,13.0,neutral or dissatisfied +18463,108333,Female,disloyal Customer,27,Business travel,Business,1844,2,2,2,1,1,2,1,1,3,2,5,4,4,1,6,5.0,neutral or dissatisfied +18464,60714,Male,Loyal Customer,43,Business travel,Business,1605,3,2,2,2,3,4,4,3,3,3,3,1,3,1,7,19.0,neutral or dissatisfied +18465,118040,Female,Loyal Customer,53,Business travel,Business,1528,3,3,3,3,5,4,4,4,4,4,4,5,4,3,1,0.0,satisfied +18466,24100,Male,Loyal Customer,47,Personal Travel,Business,584,1,4,1,4,5,4,5,1,1,1,1,3,1,3,2,12.0,neutral or dissatisfied +18467,107036,Male,disloyal Customer,39,Business travel,Business,395,1,1,1,1,3,1,3,3,3,3,5,3,4,3,0,0.0,neutral or dissatisfied +18468,34981,Male,Loyal Customer,9,Personal Travel,Eco,273,0,1,0,2,4,0,4,4,4,3,3,1,3,4,0,0.0,satisfied +18469,22960,Male,Loyal Customer,30,Business travel,Business,3598,3,3,3,3,2,2,2,2,4,5,5,3,3,2,0,0.0,satisfied +18470,87363,Male,disloyal Customer,35,Business travel,Business,425,4,4,4,4,2,4,2,2,4,5,4,3,5,2,0,0.0,neutral or dissatisfied +18471,40735,Male,Loyal Customer,40,Business travel,Business,584,2,2,2,2,3,5,5,5,5,5,5,3,5,2,0,0.0,satisfied +18472,87451,Male,Loyal Customer,48,Business travel,Business,1555,2,2,2,2,2,5,4,3,3,4,3,5,3,4,7,8.0,satisfied +18473,91436,Male,Loyal Customer,55,Personal Travel,Business,859,1,4,1,1,2,5,5,1,1,1,1,4,1,4,10,35.0,neutral or dissatisfied +18474,54221,Female,Loyal Customer,57,Business travel,Eco,1222,4,2,4,4,4,1,5,3,3,4,3,5,3,1,14,14.0,satisfied +18475,100419,Female,Loyal Customer,30,Personal Travel,Eco Plus,1092,4,1,4,2,2,4,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +18476,81708,Male,Loyal Customer,57,Business travel,Business,2204,2,2,2,2,5,5,4,3,3,3,3,4,3,3,0,12.0,satisfied +18477,114033,Male,disloyal Customer,24,Business travel,Business,512,5,0,4,2,2,4,2,2,5,3,5,3,5,2,0,0.0,satisfied +18478,98721,Male,Loyal Customer,33,Personal Travel,Eco Plus,861,3,4,3,4,5,3,5,5,5,5,4,4,4,5,59,52.0,neutral or dissatisfied +18479,90304,Female,Loyal Customer,26,Personal Travel,Eco,773,2,5,2,1,1,2,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +18480,60688,Male,Loyal Customer,36,Business travel,Business,1725,4,4,4,4,2,4,4,5,5,5,5,4,5,3,26,1.0,satisfied +18481,126853,Female,disloyal Customer,20,Business travel,Eco,744,4,4,4,2,4,4,4,4,2,5,2,3,2,4,0,2.0,neutral or dissatisfied +18482,102655,Male,Loyal Customer,59,Business travel,Business,255,5,5,5,5,5,5,4,5,5,5,5,4,5,4,11,0.0,satisfied +18483,23240,Male,Loyal Customer,13,Personal Travel,Eco,549,2,3,2,3,3,2,2,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +18484,85393,Male,Loyal Customer,40,Business travel,Business,2865,1,1,5,1,4,5,4,5,5,4,5,4,5,5,14,0.0,satisfied +18485,28245,Female,Loyal Customer,50,Personal Travel,Eco,1009,2,1,2,4,3,3,4,5,5,2,5,2,5,3,4,0.0,neutral or dissatisfied +18486,97023,Male,Loyal Customer,45,Business travel,Business,359,4,4,4,4,5,4,5,5,5,5,5,4,5,4,11,2.0,satisfied +18487,49061,Male,Loyal Customer,49,Business travel,Eco,209,4,5,5,5,4,4,4,4,1,3,5,3,4,4,0,0.0,satisfied +18488,128306,Male,disloyal Customer,23,Business travel,Eco,370,4,0,4,2,1,4,1,1,5,5,4,5,4,1,117,115.0,satisfied +18489,74973,Male,Loyal Customer,55,Personal Travel,Eco,2475,1,4,1,2,3,1,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +18490,88399,Male,Loyal Customer,52,Business travel,Eco,646,2,1,1,1,2,2,2,2,3,3,3,3,2,2,0,3.0,neutral or dissatisfied +18491,76614,Female,Loyal Customer,62,Business travel,Business,2203,4,5,5,5,5,3,3,4,4,3,4,4,4,3,20,16.0,neutral or dissatisfied +18492,9476,Male,Loyal Customer,47,Personal Travel,Eco Plus,288,1,4,4,3,3,4,1,3,5,5,4,3,5,3,34,25.0,neutral or dissatisfied +18493,42806,Female,Loyal Customer,54,Business travel,Business,2779,2,2,1,2,2,2,2,4,4,4,4,4,4,5,8,11.0,satisfied +18494,24987,Female,disloyal Customer,25,Business travel,Eco,692,1,1,1,4,4,1,4,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +18495,24222,Female,Loyal Customer,64,Business travel,Business,2866,1,5,5,5,2,3,3,1,1,1,1,3,1,3,0,6.0,neutral or dissatisfied +18496,102562,Female,disloyal Customer,23,Business travel,Eco,223,3,5,3,2,3,3,3,3,4,4,5,5,5,3,4,8.0,neutral or dissatisfied +18497,70710,Female,Loyal Customer,56,Business travel,Business,2463,5,5,5,5,4,4,4,5,5,5,5,3,5,4,2,2.0,satisfied +18498,53587,Female,Loyal Customer,46,Personal Travel,Eco,391,4,4,5,3,1,2,3,4,4,5,1,1,4,5,7,0.0,neutral or dissatisfied +18499,123355,Female,Loyal Customer,51,Business travel,Business,2437,3,3,3,3,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +18500,116700,Male,Loyal Customer,33,Business travel,Eco Plus,371,2,3,3,3,2,2,2,2,1,4,3,1,3,2,51,67.0,neutral or dissatisfied +18501,12624,Male,disloyal Customer,49,Business travel,Eco Plus,802,3,3,3,2,1,3,1,1,1,5,3,4,2,1,2,9.0,neutral or dissatisfied +18502,85006,Male,Loyal Customer,45,Business travel,Business,1590,2,2,2,2,5,4,4,5,5,5,5,5,5,5,0,8.0,satisfied +18503,53986,Female,Loyal Customer,38,Business travel,Business,1825,2,4,2,2,2,4,3,5,5,5,5,5,5,4,2,41.0,satisfied +18504,14218,Male,Loyal Customer,66,Personal Travel,Eco,620,3,5,3,3,1,3,1,1,4,5,5,5,4,1,3,54.0,neutral or dissatisfied +18505,119479,Male,disloyal Customer,30,Business travel,Business,899,2,2,2,1,2,2,2,2,5,4,4,5,4,2,0,24.0,neutral or dissatisfied +18506,17933,Female,Loyal Customer,24,Personal Travel,Eco Plus,789,2,5,2,5,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +18507,7494,Female,Loyal Customer,16,Business travel,Business,2419,1,1,1,1,5,5,5,5,2,3,5,5,2,5,0,0.0,satisfied +18508,11476,Female,disloyal Customer,25,Business travel,Eco Plus,201,4,5,4,4,3,4,1,3,1,5,3,3,2,3,0,0.0,neutral or dissatisfied +18509,73645,Female,Loyal Customer,40,Business travel,Business,1781,3,3,3,3,4,4,5,5,5,5,4,4,5,5,0,0.0,satisfied +18510,105773,Female,Loyal Customer,70,Business travel,Eco,387,3,4,4,4,1,4,4,3,3,3,3,1,3,4,1,0.0,neutral or dissatisfied +18511,126049,Male,Loyal Customer,41,Business travel,Business,3079,4,4,4,4,3,5,4,5,5,5,5,4,5,5,3,0.0,satisfied +18512,10920,Female,Loyal Customer,22,Business travel,Eco,301,2,2,4,2,2,3,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +18513,73499,Female,disloyal Customer,42,Business travel,Business,1005,4,5,5,5,1,4,1,1,3,5,4,3,4,1,5,3.0,satisfied +18514,75457,Male,Loyal Customer,45,Business travel,Business,1520,3,2,2,2,3,4,3,3,3,3,3,4,3,1,12,7.0,neutral or dissatisfied +18515,57300,Male,Loyal Customer,40,Business travel,Business,1914,4,4,4,4,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +18516,86919,Female,Loyal Customer,50,Personal Travel,Eco,341,4,4,4,3,3,4,4,5,5,4,5,4,5,4,31,24.0,neutral or dissatisfied +18517,89775,Female,Loyal Customer,54,Personal Travel,Eco,1080,1,3,1,3,4,1,4,4,4,1,4,1,4,5,0,1.0,neutral or dissatisfied +18518,29320,Female,Loyal Customer,66,Personal Travel,Eco,859,2,3,2,3,2,4,3,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +18519,56203,Female,Loyal Customer,47,Business travel,Business,1400,2,2,2,2,5,4,4,4,4,4,4,4,4,4,13,46.0,satisfied +18520,55554,Male,Loyal Customer,25,Personal Travel,Eco,550,1,0,1,3,4,1,4,4,1,2,3,5,1,4,122,124.0,neutral or dissatisfied +18521,48275,Female,disloyal Customer,25,Business travel,Eco Plus,192,2,3,1,4,4,1,5,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +18522,75013,Male,disloyal Customer,22,Business travel,Eco,236,2,0,2,1,3,2,3,3,4,3,4,3,5,3,0,0.0,neutral or dissatisfied +18523,73795,Male,Loyal Customer,39,Business travel,Business,3325,0,5,0,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +18524,113184,Male,disloyal Customer,35,Business travel,Business,407,1,1,1,1,2,1,2,2,3,5,4,3,5,2,77,84.0,neutral or dissatisfied +18525,82729,Male,Loyal Customer,49,Business travel,Business,1683,3,3,5,3,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +18526,129577,Male,Loyal Customer,62,Personal Travel,Eco Plus,2342,1,5,1,1,5,1,5,5,4,1,3,3,3,5,5,6.0,neutral or dissatisfied +18527,124789,Female,disloyal Customer,24,Business travel,Eco,280,4,4,4,4,5,4,5,5,3,4,5,5,5,5,0,0.0,satisfied +18528,39887,Female,Loyal Customer,59,Personal Travel,Eco,272,2,0,2,3,5,4,5,1,1,2,1,4,1,3,0,4.0,neutral or dissatisfied +18529,2859,Female,Loyal Customer,47,Business travel,Business,2420,3,3,3,3,5,3,2,3,3,3,3,3,3,2,106,119.0,neutral or dissatisfied +18530,69160,Male,disloyal Customer,17,Business travel,Eco,187,3,1,3,3,5,3,5,5,2,2,3,4,4,5,0,0.0,neutral or dissatisfied +18531,104812,Male,Loyal Customer,68,Personal Travel,Eco,587,2,3,2,4,1,2,5,1,4,4,5,3,1,1,0,18.0,neutral or dissatisfied +18532,73904,Female,Loyal Customer,39,Business travel,Business,2218,5,5,5,5,2,5,5,4,4,5,4,4,4,3,0,0.0,satisfied +18533,57425,Female,Loyal Customer,22,Personal Travel,Business,533,1,4,1,1,2,1,5,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +18534,120839,Female,Loyal Customer,28,Business travel,Business,993,3,3,3,3,5,5,5,5,4,2,4,5,5,5,0,0.0,satisfied +18535,92265,Male,Loyal Customer,57,Business travel,Business,1900,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +18536,63549,Female,Loyal Customer,47,Personal Travel,Eco,1009,2,4,2,4,5,5,2,4,4,2,4,3,4,1,2,0.0,neutral or dissatisfied +18537,31921,Female,disloyal Customer,24,Business travel,Eco,101,2,0,3,3,5,3,5,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +18538,98971,Male,Loyal Customer,75,Business travel,Business,3509,1,1,1,1,2,1,1,5,5,5,5,5,5,4,2,1.0,satisfied +18539,58083,Female,Loyal Customer,28,Business travel,Business,1705,3,5,5,5,3,2,3,3,3,1,2,4,2,3,19,4.0,neutral or dissatisfied +18540,82808,Female,Loyal Customer,56,Business travel,Business,235,4,2,2,2,4,2,1,4,4,3,4,2,4,4,76,102.0,neutral or dissatisfied +18541,98449,Female,Loyal Customer,38,Personal Travel,Eco,814,4,0,4,4,5,4,5,5,5,3,4,3,5,5,9,57.0,neutral or dissatisfied +18542,115120,Female,Loyal Customer,57,Business travel,Business,3553,3,3,3,3,2,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +18543,118550,Female,Loyal Customer,40,Business travel,Business,2468,5,5,4,5,3,4,5,4,4,4,4,5,4,4,9,17.0,satisfied +18544,113499,Female,Loyal Customer,56,Business travel,Business,2255,4,4,4,4,3,4,4,4,4,4,4,4,4,4,26,14.0,satisfied +18545,35012,Female,Loyal Customer,26,Business travel,Business,1546,2,2,2,2,5,5,5,5,3,3,4,4,4,5,0,3.0,satisfied +18546,1602,Female,Loyal Customer,10,Personal Travel,Eco,140,3,0,0,1,1,0,1,1,3,5,5,4,5,1,35,24.0,neutral or dissatisfied +18547,31350,Female,Loyal Customer,25,Personal Travel,Eco,1069,2,5,2,3,1,2,1,1,5,3,5,5,5,1,2,10.0,neutral or dissatisfied +18548,40874,Female,Loyal Customer,54,Personal Travel,Eco,599,2,4,2,3,5,4,3,5,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +18549,118316,Male,Loyal Customer,46,Business travel,Business,602,4,4,4,4,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +18550,87529,Female,Loyal Customer,60,Business travel,Business,2559,0,0,0,2,3,4,4,2,2,4,4,4,2,5,0,0.0,satisfied +18551,98306,Female,Loyal Customer,35,Business travel,Business,1565,1,1,1,1,2,5,4,4,4,4,4,4,4,3,31,42.0,satisfied +18552,65477,Male,Loyal Customer,27,Business travel,Business,2585,3,2,2,2,3,3,3,3,2,3,4,2,4,3,0,0.0,neutral or dissatisfied +18553,54297,Female,Loyal Customer,47,Personal Travel,Eco,1075,2,5,2,4,2,5,4,4,4,2,4,5,4,3,19,13.0,neutral or dissatisfied +18554,101947,Female,Loyal Customer,25,Business travel,Business,1935,1,1,1,1,5,5,5,5,4,5,5,4,4,5,2,2.0,satisfied +18555,89138,Female,Loyal Customer,60,Business travel,Business,1947,2,2,2,2,4,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +18556,40822,Female,Loyal Customer,32,Business travel,Business,3338,5,2,5,5,3,3,3,3,2,2,1,5,5,3,0,0.0,satisfied +18557,73179,Female,Loyal Customer,34,Business travel,Business,3357,3,3,3,3,3,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +18558,61281,Male,Loyal Customer,15,Personal Travel,Eco,909,3,5,3,3,5,3,5,5,3,3,5,1,2,5,0,0.0,neutral or dissatisfied +18559,81476,Female,Loyal Customer,35,Business travel,Business,3978,2,4,3,4,1,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +18560,95542,Male,Loyal Customer,65,Personal Travel,Eco Plus,248,1,1,1,3,5,1,5,5,3,4,4,1,3,5,36,33.0,neutral or dissatisfied +18561,68158,Female,Loyal Customer,40,Business travel,Business,2988,4,4,4,4,2,4,4,4,4,4,4,3,4,5,7,57.0,satisfied +18562,56716,Female,Loyal Customer,65,Personal Travel,Eco,937,2,1,2,3,2,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +18563,30301,Female,disloyal Customer,12,Business travel,Eco,1476,3,3,3,3,4,3,4,4,1,5,4,3,4,4,0,17.0,neutral or dissatisfied +18564,52049,Male,Loyal Customer,67,Personal Travel,Business,438,1,5,4,5,2,5,5,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +18565,122615,Male,Loyal Customer,44,Personal Travel,Eco,728,3,1,3,3,4,3,4,4,1,2,4,1,4,4,1,5.0,neutral or dissatisfied +18566,61743,Male,disloyal Customer,37,Business travel,Eco,903,1,0,0,3,0,5,5,2,1,3,4,5,1,5,151,131.0,neutral or dissatisfied +18567,101610,Female,Loyal Customer,52,Business travel,Business,1371,5,5,5,5,5,4,4,3,3,4,3,5,3,4,1,0.0,satisfied +18568,76442,Female,Loyal Customer,35,Personal Travel,Eco,405,3,5,3,1,4,3,5,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +18569,34474,Female,Loyal Customer,56,Business travel,Eco,266,4,2,2,2,1,1,3,3,3,4,3,4,3,4,0,0.0,satisfied +18570,83471,Female,Loyal Customer,48,Business travel,Business,946,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,5.0,satisfied +18571,17333,Female,Loyal Customer,43,Business travel,Business,2383,2,3,3,3,5,3,3,2,2,2,2,1,2,3,7,0.0,neutral or dissatisfied +18572,2214,Female,Loyal Customer,50,Business travel,Business,3100,1,1,1,1,5,5,5,5,5,5,5,5,5,3,10,8.0,satisfied +18573,37701,Male,Loyal Customer,27,Personal Travel,Eco,1076,2,4,2,3,2,2,2,2,3,3,5,5,4,2,0,0.0,neutral or dissatisfied +18574,49506,Male,Loyal Customer,36,Business travel,Business,238,2,2,2,2,4,4,4,5,3,4,5,4,2,4,155,144.0,satisfied +18575,85242,Female,disloyal Customer,36,Business travel,Eco,331,2,0,2,1,3,2,3,3,4,5,4,2,3,3,0,1.0,neutral or dissatisfied +18576,58060,Female,Loyal Customer,55,Business travel,Business,3235,5,5,5,5,3,4,5,4,4,4,4,3,4,3,15,2.0,satisfied +18577,50341,Male,Loyal Customer,16,Business travel,Business,1593,4,4,4,4,4,4,4,4,3,2,5,5,4,4,0,2.0,satisfied +18578,35190,Female,disloyal Customer,28,Business travel,Eco,1076,2,2,2,4,2,2,2,2,4,3,2,5,5,2,0,36.0,satisfied +18579,38572,Female,Loyal Customer,24,Personal Travel,Eco,2475,2,4,2,2,4,2,4,4,4,3,4,5,4,4,3,0.0,neutral or dissatisfied +18580,103866,Female,Loyal Customer,52,Personal Travel,Eco,869,2,3,2,4,1,4,3,3,3,2,2,1,3,3,0,30.0,neutral or dissatisfied +18581,71724,Male,Loyal Customer,17,Personal Travel,Eco,1007,2,4,2,1,3,2,3,3,4,5,5,5,5,3,80,85.0,neutral or dissatisfied +18582,30944,Female,Loyal Customer,30,Business travel,Business,2088,3,4,4,4,3,3,3,3,3,2,4,2,3,3,5,26.0,neutral or dissatisfied +18583,7359,Female,Loyal Customer,46,Personal Travel,Business,783,2,4,2,3,3,5,4,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +18584,40739,Male,Loyal Customer,57,Business travel,Eco,584,4,1,1,1,4,4,4,4,1,4,4,1,1,4,0,0.0,satisfied +18585,126931,Female,Loyal Customer,42,Business travel,Business,2052,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +18586,116802,Female,Loyal Customer,38,Personal Travel,Eco Plus,325,2,1,3,3,5,3,5,5,3,1,3,4,2,5,0,0.0,neutral or dissatisfied +18587,92133,Female,Loyal Customer,13,Personal Travel,Eco,1535,2,5,3,1,2,3,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +18588,32113,Female,disloyal Customer,42,Business travel,Eco,216,1,5,1,4,5,1,4,5,4,2,2,1,4,5,0,18.0,neutral or dissatisfied +18589,104513,Female,Loyal Customer,56,Business travel,Business,3853,3,3,3,3,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +18590,21286,Female,Loyal Customer,39,Business travel,Eco,620,4,4,4,4,4,4,4,4,2,2,5,5,2,4,0,0.0,satisfied +18591,48985,Male,disloyal Customer,40,Business travel,Eco,447,2,0,1,4,3,1,3,3,5,1,4,3,3,3,0,0.0,neutral or dissatisfied +18592,111266,Male,Loyal Customer,47,Business travel,Business,459,2,2,2,2,2,5,4,4,4,4,4,3,4,5,3,16.0,satisfied +18593,110691,Female,Loyal Customer,22,Personal Travel,Eco,829,2,4,3,2,5,3,5,5,5,3,4,3,5,5,61,51.0,neutral or dissatisfied +18594,73911,Female,Loyal Customer,41,Business travel,Business,2585,3,3,3,3,5,5,5,5,2,4,5,5,5,5,67,79.0,satisfied +18595,110681,Female,Loyal Customer,27,Personal Travel,Eco,837,1,4,1,4,5,1,5,5,5,4,4,3,5,5,8,8.0,neutral or dissatisfied +18596,73166,Male,Loyal Customer,35,Personal Travel,Eco,1145,3,4,3,2,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +18597,23632,Male,disloyal Customer,40,Business travel,Eco,793,3,2,2,3,2,2,3,2,3,5,3,4,4,2,27,20.0,neutral or dissatisfied +18598,35865,Male,Loyal Customer,10,Personal Travel,Eco,937,3,1,3,4,3,3,3,3,1,5,4,1,4,3,0,0.0,neutral or dissatisfied +18599,23154,Female,disloyal Customer,80,Business travel,Business,223,5,5,5,3,5,2,1,4,4,5,4,1,4,5,0,0.0,satisfied +18600,32970,Male,Loyal Customer,40,Personal Travel,Eco,84,3,5,3,4,5,3,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +18601,101469,Female,Loyal Customer,50,Business travel,Business,345,0,0,0,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +18602,119619,Female,Loyal Customer,35,Business travel,Business,1837,0,1,1,1,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +18603,25878,Male,Loyal Customer,27,Business travel,Business,3928,2,2,5,2,5,5,5,5,5,1,1,3,2,5,7,1.0,satisfied +18604,117629,Female,Loyal Customer,25,Personal Travel,Eco,843,3,4,2,3,2,4,2,5,3,5,5,2,5,2,160,150.0,neutral or dissatisfied +18605,93264,Male,disloyal Customer,22,Business travel,Eco,867,1,1,1,5,1,1,1,1,3,4,5,3,5,1,15,0.0,neutral or dissatisfied +18606,49804,Female,Loyal Customer,39,Business travel,Business,2158,5,5,5,5,1,2,1,4,4,4,4,3,4,3,0,0.0,satisfied +18607,52821,Female,Loyal Customer,11,Personal Travel,Eco,2402,3,3,3,4,3,5,5,1,2,1,2,5,3,5,168,136.0,neutral or dissatisfied +18608,47119,Male,Loyal Customer,27,Personal Travel,Eco,784,1,4,2,5,4,2,4,4,4,4,4,4,4,4,24,47.0,neutral or dissatisfied +18609,86328,Male,Loyal Customer,52,Business travel,Business,749,1,1,1,1,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +18610,117175,Female,Loyal Customer,18,Personal Travel,Eco,647,1,4,1,1,1,1,1,1,2,5,5,1,5,1,0,0.0,neutral or dissatisfied +18611,106763,Female,Loyal Customer,39,Personal Travel,Eco,837,1,4,1,1,4,1,4,4,4,4,5,4,4,4,0,2.0,neutral or dissatisfied +18612,20858,Female,Loyal Customer,39,Personal Travel,Eco,457,1,5,1,3,2,1,4,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +18613,101524,Female,Loyal Customer,37,Personal Travel,Eco,345,3,5,3,4,2,3,2,2,4,5,4,4,4,2,0,0.0,neutral or dissatisfied +18614,122195,Female,Loyal Customer,33,Business travel,Business,3020,5,5,3,5,5,4,4,4,4,4,4,4,4,3,15,20.0,satisfied +18615,122808,Male,Loyal Customer,20,Personal Travel,Eco,599,2,2,2,3,5,2,5,5,1,5,4,4,4,5,71,57.0,neutral or dissatisfied +18616,119400,Male,Loyal Customer,52,Business travel,Business,3057,5,5,5,5,5,5,5,3,3,2,3,4,3,3,0,0.0,satisfied +18617,69353,Male,Loyal Customer,55,Business travel,Business,1089,2,2,2,2,3,4,4,5,5,5,5,3,5,3,0,4.0,satisfied +18618,2167,Male,Loyal Customer,41,Business travel,Business,2367,2,5,3,5,2,2,3,2,2,2,2,3,2,4,31,39.0,neutral or dissatisfied +18619,109130,Female,Loyal Customer,47,Business travel,Business,684,4,4,4,4,5,4,5,5,5,5,5,4,5,5,3,9.0,satisfied +18620,30892,Male,disloyal Customer,28,Business travel,Eco,841,2,2,2,3,5,2,5,5,4,3,3,4,2,5,0,0.0,neutral or dissatisfied +18621,61376,Female,Loyal Customer,60,Business travel,Business,679,5,5,5,5,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +18622,119973,Female,Loyal Customer,25,Personal Travel,Eco,868,3,5,3,1,4,3,1,4,1,4,5,3,2,4,0,0.0,neutral or dissatisfied +18623,7905,Female,Loyal Customer,27,Business travel,Eco,1020,3,1,1,1,3,2,3,3,4,4,4,3,3,3,0,5.0,neutral or dissatisfied +18624,93183,Female,Loyal Customer,46,Business travel,Business,1773,5,5,5,5,4,5,4,5,5,5,5,3,5,4,2,0.0,satisfied +18625,15116,Male,Loyal Customer,45,Business travel,Eco,912,4,1,1,1,4,4,4,4,4,2,4,3,2,4,33,34.0,satisfied +18626,87857,Female,Loyal Customer,61,Personal Travel,Eco,214,3,0,3,5,3,5,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +18627,41975,Female,Loyal Customer,13,Personal Travel,Eco,525,4,5,4,1,4,4,4,4,3,4,4,5,4,4,0,0.0,satisfied +18628,97861,Female,Loyal Customer,33,Personal Travel,Business,684,3,5,3,2,2,4,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +18629,23662,Male,Loyal Customer,47,Business travel,Business,196,4,4,4,4,1,1,3,4,4,4,3,1,4,3,0,0.0,satisfied +18630,42928,Male,Loyal Customer,47,Business travel,Business,2684,3,3,3,3,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +18631,48973,Female,disloyal Customer,30,Business travel,Eco,262,2,0,2,4,4,2,4,4,2,4,1,2,1,4,39,37.0,neutral or dissatisfied +18632,20163,Female,disloyal Customer,34,Business travel,Eco,403,3,1,3,4,5,3,5,5,2,2,4,2,4,5,6,0.0,neutral or dissatisfied +18633,90546,Female,disloyal Customer,23,Business travel,Eco,545,5,0,5,3,1,5,1,1,5,2,5,5,5,1,0,0.0,satisfied +18634,58741,Female,Loyal Customer,41,Business travel,Business,1197,3,3,3,3,5,4,4,4,4,4,4,3,4,5,14,38.0,satisfied +18635,32636,Female,disloyal Customer,19,Business travel,Eco,102,2,3,3,3,5,3,5,5,4,2,3,4,4,5,0,0.0,neutral or dissatisfied +18636,25886,Female,Loyal Customer,22,Business travel,Business,1979,1,0,0,4,2,0,2,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +18637,81829,Male,Loyal Customer,23,Personal Travel,Eco,1487,3,5,3,1,1,3,1,1,5,4,4,4,5,1,0,0.0,neutral or dissatisfied +18638,76130,Male,Loyal Customer,22,Business travel,Business,3587,5,5,5,5,4,4,4,4,3,5,5,3,4,4,8,0.0,satisfied +18639,87673,Female,Loyal Customer,46,Business travel,Eco,591,2,4,4,4,1,3,3,2,2,2,2,1,2,2,46,39.0,neutral or dissatisfied +18640,113816,Male,Loyal Customer,39,Business travel,Eco Plus,258,1,1,1,1,1,1,1,1,1,5,4,1,4,1,0,0.0,neutral or dissatisfied +18641,116675,Male,Loyal Customer,57,Business travel,Eco Plus,342,3,4,4,4,4,3,4,4,3,2,3,4,3,4,18,25.0,neutral or dissatisfied +18642,118590,Male,Loyal Customer,58,Business travel,Business,3762,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +18643,78806,Male,Loyal Customer,16,Personal Travel,Eco,447,3,4,3,5,1,3,1,1,4,2,4,5,5,1,0,0.0,neutral or dissatisfied +18644,110808,Female,Loyal Customer,20,Personal Travel,Eco,1105,2,1,2,4,5,2,5,5,4,2,4,3,3,5,24,17.0,neutral or dissatisfied +18645,89067,Male,Loyal Customer,40,Business travel,Business,1892,2,2,2,2,4,5,4,3,3,4,3,4,3,5,7,14.0,satisfied +18646,107429,Female,Loyal Customer,21,Personal Travel,Eco,717,2,5,2,3,2,2,2,2,4,4,5,3,5,2,2,0.0,neutral or dissatisfied +18647,38017,Female,disloyal Customer,22,Business travel,Eco,1121,5,5,5,3,3,5,3,3,1,4,3,2,5,3,0,0.0,satisfied +18648,64605,Male,Loyal Customer,51,Business travel,Business,190,2,2,2,2,2,4,4,4,4,4,4,5,4,3,11,1.0,satisfied +18649,107678,Male,Loyal Customer,43,Business travel,Eco,251,4,4,1,1,5,4,5,5,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +18650,95320,Female,Loyal Customer,51,Personal Travel,Eco,319,3,4,3,5,3,3,4,3,3,3,3,1,3,3,1,0.0,neutral or dissatisfied +18651,26148,Male,Loyal Customer,53,Business travel,Business,404,5,5,5,5,3,5,2,3,3,3,3,1,3,5,19,33.0,satisfied +18652,94867,Female,disloyal Customer,21,Business travel,Eco,293,2,3,2,3,2,2,2,2,1,1,3,3,3,2,28,13.0,neutral or dissatisfied +18653,97370,Male,Loyal Customer,31,Personal Travel,Eco,1020,1,4,1,4,3,1,5,3,2,4,3,3,3,3,1,0.0,neutral or dissatisfied +18654,95958,Female,Loyal Customer,43,Business travel,Business,3425,2,2,2,2,4,5,4,3,3,3,3,3,3,5,0,0.0,satisfied +18655,34879,Female,Loyal Customer,17,Personal Travel,Eco,2248,3,3,3,2,1,3,1,1,5,2,5,5,4,1,9,8.0,neutral or dissatisfied +18656,62449,Male,disloyal Customer,29,Business travel,Business,1723,2,2,2,4,5,2,3,5,5,3,3,4,4,5,0,4.0,neutral or dissatisfied +18657,7754,Female,Loyal Customer,44,Personal Travel,Eco,1013,4,2,4,3,1,4,4,4,4,4,4,1,4,3,66,77.0,neutral or dissatisfied +18658,44112,Female,Loyal Customer,33,Business travel,Eco Plus,257,1,3,3,3,1,1,1,1,4,4,3,2,4,1,0,0.0,neutral or dissatisfied +18659,41900,Female,Loyal Customer,33,Business travel,Business,129,1,1,1,1,3,5,2,4,4,4,5,4,4,3,0,0.0,satisfied +18660,21652,Female,Loyal Customer,41,Business travel,Business,2183,1,1,1,1,4,5,5,4,4,4,4,5,4,5,18,1.0,satisfied +18661,12608,Male,Loyal Customer,21,Personal Travel,Eco,542,4,5,4,5,1,4,1,1,3,3,4,5,5,1,8,49.0,neutral or dissatisfied +18662,128579,Male,Loyal Customer,51,Business travel,Business,2552,1,1,1,1,4,4,4,5,2,4,4,4,4,4,0,2.0,satisfied +18663,81254,Female,Loyal Customer,48,Business travel,Business,3072,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,7.0,satisfied +18664,90752,Female,disloyal Customer,25,Business travel,Eco,594,4,3,4,4,2,4,4,2,1,3,3,3,3,2,0,0.0,neutral or dissatisfied +18665,27572,Female,Loyal Customer,50,Personal Travel,Eco,954,3,4,3,3,3,5,5,5,5,3,5,5,5,3,2,0.0,neutral or dissatisfied +18666,112710,Female,Loyal Customer,73,Business travel,Business,3198,4,4,4,4,1,1,3,5,5,5,5,4,5,5,5,0.0,satisfied +18667,121043,Female,Loyal Customer,20,Personal Travel,Eco,1013,2,1,2,3,1,2,4,1,3,1,4,4,3,1,0,0.0,neutral or dissatisfied +18668,36894,Male,disloyal Customer,35,Business travel,Eco,1368,3,3,3,1,4,3,4,4,4,5,3,4,4,4,0,0.0,neutral or dissatisfied +18669,77143,Male,disloyal Customer,40,Business travel,Business,365,2,2,2,4,1,2,1,1,3,4,3,2,4,1,38,17.0,neutral or dissatisfied +18670,55264,Male,Loyal Customer,30,Business travel,Business,2007,2,5,5,5,2,1,2,2,1,1,2,2,3,2,42,20.0,neutral or dissatisfied +18671,41447,Female,Loyal Customer,56,Business travel,Business,2144,3,3,3,3,5,4,4,4,4,4,4,5,4,3,74,71.0,satisfied +18672,62027,Male,disloyal Customer,13,Business travel,Eco,820,4,4,4,3,3,4,3,3,5,2,3,3,4,3,0,0.0,satisfied +18673,6548,Female,Loyal Customer,59,Business travel,Business,618,1,1,1,1,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +18674,39154,Male,Loyal Customer,21,Personal Travel,Eco Plus,228,2,5,0,3,1,0,1,1,4,2,1,2,3,1,0,3.0,neutral or dissatisfied +18675,126286,Male,Loyal Customer,54,Personal Travel,Eco,328,4,2,4,4,3,4,3,3,2,4,4,3,3,3,0,0.0,neutral or dissatisfied +18676,25339,Male,Loyal Customer,48,Personal Travel,Eco,837,5,4,5,1,3,5,3,3,4,2,5,5,5,3,0,0.0,satisfied +18677,11509,Male,Loyal Customer,70,Personal Travel,Eco Plus,312,1,4,1,4,2,1,2,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +18678,2601,Male,Loyal Customer,18,Personal Travel,Eco,304,2,5,2,4,1,2,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +18679,69787,Male,Loyal Customer,43,Personal Travel,Business,1055,2,4,2,1,2,5,5,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +18680,92164,Female,Loyal Customer,33,Personal Travel,Business,1979,4,4,4,4,4,4,5,1,1,4,1,5,1,1,0,0.0,neutral or dissatisfied +18681,1318,Female,Loyal Customer,44,Business travel,Business,134,3,3,3,3,3,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +18682,110486,Male,Loyal Customer,47,Personal Travel,Eco,787,1,4,1,4,1,1,1,1,4,3,3,5,3,1,3,0.0,neutral or dissatisfied +18683,65854,Female,Loyal Customer,63,Personal Travel,Eco,1389,2,4,2,4,2,4,1,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +18684,89803,Female,Loyal Customer,55,Business travel,Business,1802,3,3,3,3,2,4,5,4,4,4,4,3,4,4,1,0.0,satisfied +18685,60437,Male,Loyal Customer,30,Business travel,Business,862,4,4,4,4,3,3,3,3,4,3,4,4,5,3,0,0.0,satisfied +18686,58362,Male,Loyal Customer,43,Personal Travel,Eco,599,4,5,4,5,4,4,4,4,3,1,2,5,1,4,12,0.0,satisfied +18687,126243,Male,disloyal Customer,28,Business travel,Eco,468,3,4,3,1,5,3,1,5,3,3,3,1,2,5,0,0.0,neutral or dissatisfied +18688,100955,Female,Loyal Customer,30,Business travel,Business,1142,4,4,1,1,4,4,4,4,4,1,3,4,4,4,0,15.0,neutral or dissatisfied +18689,3813,Female,disloyal Customer,38,Business travel,Business,650,3,3,3,1,5,3,2,5,4,4,4,4,5,5,0,0.0,neutral or dissatisfied +18690,93805,Female,Loyal Customer,57,Business travel,Eco Plus,859,4,1,1,1,4,3,5,4,4,4,4,1,4,5,1,0.0,satisfied +18691,64451,Male,Loyal Customer,48,Personal Travel,Eco,989,4,5,4,4,1,4,1,1,5,5,5,4,5,1,2,7.0,neutral or dissatisfied +18692,99161,Male,Loyal Customer,22,Business travel,Business,986,3,3,3,3,4,4,4,4,4,5,4,4,5,4,16,15.0,satisfied +18693,76515,Male,Loyal Customer,31,Business travel,Business,2138,3,3,3,3,5,5,5,5,3,3,5,3,4,5,0,10.0,satisfied +18694,91929,Female,Loyal Customer,46,Business travel,Business,2446,5,5,5,5,2,3,4,4,4,4,4,5,4,4,0,0.0,satisfied +18695,127440,Female,Loyal Customer,49,Business travel,Business,3860,5,5,5,5,5,4,5,4,4,4,4,3,4,4,0,9.0,satisfied +18696,100251,Male,disloyal Customer,35,Business travel,Business,1053,2,2,2,4,2,2,2,2,5,2,4,4,5,2,27,46.0,neutral or dissatisfied +18697,40412,Male,disloyal Customer,23,Business travel,Eco,290,0,3,0,4,4,0,4,4,3,2,3,1,4,4,0,0.0,satisfied +18698,100998,Female,Loyal Customer,52,Business travel,Business,564,3,3,3,3,2,5,4,5,5,5,5,3,5,4,18,12.0,satisfied +18699,95513,Female,Loyal Customer,44,Business travel,Eco Plus,189,1,0,0,3,3,4,3,2,2,1,2,1,2,1,0,0.0,neutral or dissatisfied +18700,93321,Male,disloyal Customer,58,Business travel,Business,287,4,4,4,4,5,4,5,5,4,2,4,4,5,5,0,0.0,satisfied +18701,116738,Female,Loyal Customer,52,Personal Travel,Eco Plus,446,1,5,5,2,4,5,5,3,3,5,3,5,3,4,49,45.0,neutral or dissatisfied +18702,15407,Female,Loyal Customer,33,Business travel,Eco,164,3,3,3,3,3,3,3,3,4,4,3,3,4,3,9,8.0,neutral or dissatisfied +18703,12155,Male,Loyal Customer,49,Business travel,Eco,1214,5,2,2,2,5,5,5,5,2,2,3,3,4,5,108,107.0,satisfied +18704,25890,Female,disloyal Customer,54,Business travel,Eco,907,4,4,4,4,5,4,5,5,1,1,3,3,4,5,17,17.0,neutral or dissatisfied +18705,87047,Female,disloyal Customer,43,Business travel,Business,594,2,2,2,2,2,1,1,4,4,4,4,1,4,1,160,156.0,neutral or dissatisfied +18706,83005,Male,disloyal Customer,25,Business travel,Eco,1084,5,5,5,3,5,5,2,5,3,5,4,3,5,5,0,0.0,satisfied +18707,1034,Female,Loyal Customer,46,Business travel,Business,140,1,5,4,4,3,4,4,3,3,3,1,3,3,3,25,13.0,neutral or dissatisfied +18708,15353,Male,Loyal Customer,69,Personal Travel,Business,399,3,2,3,4,1,3,3,2,2,3,2,1,2,1,0,16.0,neutral or dissatisfied +18709,77302,Male,disloyal Customer,25,Business travel,Business,599,2,5,2,5,2,2,2,2,3,3,5,3,5,2,0,0.0,neutral or dissatisfied +18710,117231,Female,Loyal Customer,10,Personal Travel,Eco,621,3,4,3,3,4,3,1,4,3,4,4,5,5,4,15,10.0,neutral or dissatisfied +18711,111447,Male,Loyal Customer,34,Business travel,Eco,836,2,3,2,2,2,1,2,2,3,3,4,4,3,2,44,33.0,neutral or dissatisfied +18712,22148,Male,Loyal Customer,26,Business travel,Business,565,2,2,2,2,4,4,4,4,4,3,4,3,2,4,65,61.0,satisfied +18713,74885,Male,Loyal Customer,50,Business travel,Business,2586,4,1,4,4,5,5,4,5,5,5,5,4,5,3,23,0.0,satisfied +18714,55084,Male,Loyal Customer,22,Business travel,Eco,1635,2,4,4,4,2,2,4,2,3,3,3,1,4,2,31,30.0,neutral or dissatisfied +18715,297,Female,Loyal Customer,55,Business travel,Business,590,1,1,1,1,3,5,4,4,4,4,4,3,4,5,62,67.0,satisfied +18716,79820,Female,Loyal Customer,54,Business travel,Business,2576,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +18717,8008,Female,Loyal Customer,55,Business travel,Business,1660,0,5,0,1,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +18718,84653,Male,Loyal Customer,21,Personal Travel,Eco,363,4,4,4,3,2,4,2,2,4,5,4,5,4,2,0,0.0,satisfied +18719,105350,Female,Loyal Customer,11,Personal Travel,Eco,528,4,4,4,1,4,4,4,4,4,4,4,4,5,4,25,13.0,neutral or dissatisfied +18720,58610,Female,Loyal Customer,51,Personal Travel,Eco Plus,334,3,1,3,3,5,4,3,3,3,3,3,1,3,3,40,38.0,neutral or dissatisfied +18721,76475,Female,Loyal Customer,39,Business travel,Business,3705,3,2,4,2,5,3,3,3,3,3,3,1,3,1,0,1.0,neutral or dissatisfied +18722,2311,Female,disloyal Customer,22,Business travel,Eco,272,1,2,1,4,4,1,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +18723,13195,Male,Loyal Customer,51,Business travel,Eco,142,5,2,3,2,5,5,5,5,2,5,2,1,3,5,11,0.0,satisfied +18724,7315,Female,Loyal Customer,59,Personal Travel,Eco Plus,116,1,4,0,4,5,4,2,4,4,0,5,4,4,4,61,57.0,neutral or dissatisfied +18725,14660,Female,Loyal Customer,63,Personal Travel,Eco,162,2,4,2,4,5,5,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +18726,96186,Female,Loyal Customer,60,Business travel,Eco,666,2,1,1,1,3,3,3,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied +18727,8784,Male,Loyal Customer,39,Business travel,Business,2051,2,1,2,2,4,2,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +18728,43732,Male,Loyal Customer,34,Personal Travel,Eco Plus,489,1,2,4,3,4,4,4,4,2,3,4,4,3,4,0,8.0,neutral or dissatisfied +18729,110923,Male,Loyal Customer,68,Personal Travel,Eco,545,4,2,4,3,4,4,4,4,1,3,3,4,3,4,18,31.0,neutral or dissatisfied +18730,101615,Female,disloyal Customer,28,Business travel,Business,1139,3,3,3,2,3,3,3,3,3,5,5,4,4,3,9,3.0,neutral or dissatisfied +18731,4756,Female,Loyal Customer,18,Personal Travel,Business,403,3,4,3,1,3,3,3,3,5,3,5,3,5,3,5,0.0,neutral or dissatisfied +18732,63259,Male,Loyal Customer,43,Business travel,Business,337,3,3,3,3,4,4,5,5,5,5,5,5,5,3,94,91.0,satisfied +18733,32920,Female,Loyal Customer,58,Personal Travel,Eco,101,4,5,4,2,4,5,1,2,2,4,2,4,2,4,0,0.0,neutral or dissatisfied +18734,78988,Female,Loyal Customer,51,Business travel,Business,3593,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +18735,32308,Female,Loyal Customer,37,Business travel,Business,163,5,5,5,5,2,1,1,4,4,4,5,2,4,4,0,0.0,satisfied +18736,92890,Female,Loyal Customer,43,Business travel,Business,3486,1,1,1,1,2,4,5,5,5,4,4,4,5,3,0,11.0,satisfied +18737,37222,Male,disloyal Customer,35,Business travel,Business,1076,2,1,1,3,4,1,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +18738,106061,Female,Loyal Customer,48,Business travel,Business,302,0,0,0,2,5,5,5,3,3,3,3,3,3,5,0,0.0,satisfied +18739,121903,Male,Loyal Customer,29,Personal Travel,Eco,366,3,4,5,2,1,5,1,1,5,2,5,5,5,1,1,0.0,neutral or dissatisfied +18740,35120,Male,Loyal Customer,60,Business travel,Eco,1028,5,3,3,3,5,5,5,5,2,2,1,1,4,5,57,120.0,satisfied +18741,92093,Male,disloyal Customer,25,Business travel,Business,1532,5,0,5,4,5,5,2,5,5,2,4,3,4,5,0,0.0,satisfied +18742,126722,Female,disloyal Customer,9,Business travel,Eco,1340,2,2,2,3,3,2,3,3,4,4,3,3,5,3,0,0.0,neutral or dissatisfied +18743,49689,Female,Loyal Customer,49,Business travel,Business,2545,4,1,4,4,4,4,2,4,4,4,5,2,4,3,0,0.0,satisfied +18744,101933,Male,Loyal Customer,47,Personal Travel,Business,628,3,5,3,1,4,5,5,4,4,3,4,3,4,5,2,4.0,neutral or dissatisfied +18745,107,Male,Loyal Customer,47,Business travel,Business,3477,4,4,4,4,2,4,5,5,5,5,5,5,5,3,0,27.0,satisfied +18746,125315,Female,Loyal Customer,52,Personal Travel,Eco Plus,678,1,4,0,2,2,4,4,3,3,0,3,5,3,3,51,43.0,neutral or dissatisfied +18747,83376,Male,Loyal Customer,30,Personal Travel,Eco,1124,2,5,2,1,5,2,5,5,3,2,3,5,4,5,6,10.0,neutral or dissatisfied +18748,41165,Female,Loyal Customer,8,Personal Travel,Eco,224,2,5,0,4,3,0,3,3,4,2,4,5,4,3,1,0.0,neutral or dissatisfied +18749,36961,Female,Loyal Customer,30,Business travel,Business,3843,2,2,2,2,2,2,2,2,4,5,4,5,3,2,130,122.0,satisfied +18750,119189,Male,Loyal Customer,37,Business travel,Eco,290,3,5,5,5,3,3,3,3,4,3,2,1,3,3,24,14.0,neutral or dissatisfied +18751,125233,Female,disloyal Customer,22,Business travel,Business,1149,5,5,5,3,1,5,1,1,4,3,5,3,4,1,0,0.0,satisfied +18752,80006,Female,Loyal Customer,52,Personal Travel,Eco,1207,2,3,2,4,1,3,3,3,3,2,3,4,3,2,19,50.0,neutral or dissatisfied +18753,26015,Male,disloyal Customer,21,Business travel,Eco,425,2,1,2,3,1,2,4,1,4,1,3,3,4,1,25,16.0,neutral or dissatisfied +18754,39238,Female,Loyal Customer,53,Business travel,Business,268,0,0,0,3,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +18755,83302,Male,Loyal Customer,47,Business travel,Eco Plus,2079,1,5,5,5,1,1,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +18756,28682,Female,Loyal Customer,49,Business travel,Eco,2777,1,4,4,4,2,3,4,1,1,1,1,4,1,3,6,0.0,neutral or dissatisfied +18757,74849,Female,Loyal Customer,36,Business travel,Business,2136,2,2,5,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +18758,80624,Female,disloyal Customer,47,Business travel,Eco Plus,236,5,5,5,3,5,5,5,5,3,3,5,3,2,5,0,5.0,satisfied +18759,13848,Male,Loyal Customer,29,Business travel,Eco Plus,594,4,1,1,1,4,4,4,4,4,5,1,1,5,4,0,0.0,satisfied +18760,112027,Female,disloyal Customer,59,Business travel,Eco,280,3,5,3,4,5,3,5,5,1,2,5,1,4,5,0,0.0,neutral or dissatisfied +18761,90439,Male,Loyal Customer,64,Business travel,Business,404,1,1,1,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +18762,122631,Male,Loyal Customer,43,Personal Travel,Eco,728,2,5,2,5,4,2,5,4,2,1,1,3,4,4,0,0.0,neutral or dissatisfied +18763,85086,Female,Loyal Customer,47,Business travel,Business,874,1,1,1,1,5,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +18764,126479,Male,Loyal Customer,53,Business travel,Eco,1788,3,3,3,3,3,3,3,3,3,4,3,1,4,3,0,9.0,neutral or dissatisfied +18765,24764,Female,Loyal Customer,35,Business travel,Business,432,2,4,4,4,1,3,3,2,2,2,2,2,2,3,0,10.0,neutral or dissatisfied +18766,66823,Female,disloyal Customer,24,Business travel,Eco,731,2,2,2,3,5,2,5,5,4,2,4,4,5,5,6,0.0,neutral or dissatisfied +18767,79450,Female,Loyal Customer,35,Business travel,Business,2142,3,1,5,5,4,4,4,3,3,4,3,2,3,1,64,71.0,neutral or dissatisfied +18768,67783,Female,disloyal Customer,25,Business travel,Eco,1205,1,1,1,3,3,1,3,3,2,3,3,4,4,3,17,16.0,neutral or dissatisfied +18769,20640,Female,Loyal Customer,50,Personal Travel,Eco,793,3,4,3,3,4,4,5,2,2,3,2,5,2,4,0,11.0,neutral or dissatisfied +18770,63173,Male,Loyal Customer,44,Business travel,Business,337,2,3,2,2,4,5,5,5,5,5,5,5,5,5,2,0.0,satisfied +18771,46472,Male,Loyal Customer,51,Business travel,Business,3053,3,4,4,4,2,4,4,3,3,3,3,3,3,1,27,44.0,neutral or dissatisfied +18772,126298,Male,Loyal Customer,64,Personal Travel,Eco,631,2,2,2,2,2,2,2,2,1,3,3,3,2,2,0,0.0,neutral or dissatisfied +18773,82865,Female,disloyal Customer,25,Business travel,Business,594,4,4,4,2,3,4,3,3,4,5,4,5,4,3,1,1.0,satisfied +18774,39880,Male,Loyal Customer,8,Personal Travel,Eco,221,1,4,0,1,2,0,2,2,4,1,1,4,1,2,0,0.0,neutral or dissatisfied +18775,43572,Female,disloyal Customer,27,Business travel,Eco,1499,4,4,4,3,3,4,3,3,3,2,2,4,2,3,0,8.0,neutral or dissatisfied +18776,85375,Female,Loyal Customer,57,Business travel,Business,214,2,4,4,4,4,3,2,3,3,2,2,3,3,3,10,4.0,neutral or dissatisfied +18777,42077,Female,Loyal Customer,33,Business travel,Eco Plus,116,5,3,3,3,5,5,5,5,3,2,3,4,3,5,0,0.0,satisfied +18778,29966,Female,disloyal Customer,62,Business travel,Eco,261,3,0,3,4,5,3,5,5,2,3,5,4,2,5,0,0.0,neutral or dissatisfied +18779,20472,Female,Loyal Customer,35,Business travel,Eco Plus,177,3,4,4,4,3,3,3,3,1,1,3,1,3,3,5,0.0,neutral or dissatisfied +18780,3115,Male,Loyal Customer,45,Business travel,Business,2141,2,2,2,2,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +18781,104116,Male,Loyal Customer,49,Personal Travel,Eco Plus,297,4,5,4,1,2,4,2,2,3,5,4,5,5,2,0,0.0,neutral or dissatisfied +18782,38498,Female,Loyal Customer,40,Business travel,Business,2465,3,3,3,3,2,4,5,3,3,4,3,1,3,2,126,115.0,satisfied +18783,51665,Female,disloyal Customer,26,Business travel,Eco,598,1,5,0,1,1,0,1,1,2,1,4,4,1,1,3,0.0,neutral or dissatisfied +18784,44976,Male,Loyal Customer,40,Business travel,Business,3196,4,1,1,1,4,4,4,3,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +18785,67961,Female,disloyal Customer,54,Business travel,Business,1205,4,5,5,2,5,4,5,5,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +18786,52092,Male,Loyal Customer,56,Business travel,Eco,351,4,1,1,1,4,4,4,4,5,3,5,3,3,4,0,0.0,satisfied +18787,49699,Female,Loyal Customer,27,Business travel,Business,3249,3,3,3,3,4,4,4,4,3,5,2,5,4,4,11,8.0,satisfied +18788,105486,Male,Loyal Customer,40,Business travel,Business,2619,2,2,2,2,4,4,4,5,5,5,5,5,5,4,18,10.0,satisfied +18789,94310,Male,Loyal Customer,58,Business travel,Business,3676,4,4,4,4,5,4,4,4,4,4,4,3,4,3,2,3.0,satisfied +18790,42334,Female,Loyal Customer,27,Personal Travel,Eco,834,3,2,3,4,4,3,4,4,4,1,3,1,3,4,0,0.0,neutral or dissatisfied +18791,123878,Male,disloyal Customer,21,Business travel,Eco,144,3,0,3,2,4,3,5,4,4,2,2,3,2,4,0,0.0,neutral or dissatisfied +18792,51859,Male,Loyal Customer,37,Business travel,Eco Plus,438,2,5,4,5,2,2,2,2,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +18793,29739,Male,Loyal Customer,42,Business travel,Business,183,4,4,4,4,5,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +18794,60178,Male,Loyal Customer,69,Personal Travel,Eco,1120,1,4,1,5,2,1,2,2,4,5,5,5,4,2,0,0.0,neutral or dissatisfied +18795,63135,Female,Loyal Customer,71,Business travel,Business,3614,2,3,3,3,4,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +18796,36189,Male,disloyal Customer,29,Business travel,Business,496,3,3,3,2,1,3,1,1,3,4,2,2,3,1,0,0.0,neutral or dissatisfied +18797,20108,Female,Loyal Customer,49,Business travel,Business,3768,1,2,4,2,2,4,4,1,1,1,1,3,1,3,126,125.0,neutral or dissatisfied +18798,34854,Male,Loyal Customer,26,Business travel,Business,1826,2,2,5,2,4,4,4,4,5,1,5,5,4,4,0,0.0,satisfied +18799,51206,Female,disloyal Customer,62,Business travel,Eco Plus,86,2,2,2,1,4,2,2,4,1,3,5,1,4,4,42,46.0,neutral or dissatisfied +18800,16248,Male,Loyal Customer,22,Business travel,Business,946,2,2,3,2,4,4,4,4,5,3,5,2,3,4,75,69.0,satisfied +18801,85497,Female,Loyal Customer,14,Personal Travel,Eco,332,3,4,4,4,1,4,1,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +18802,111092,Male,Loyal Customer,57,Personal Travel,Eco,197,1,5,1,5,4,1,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +18803,95664,Female,Loyal Customer,39,Business travel,Eco Plus,845,2,4,2,2,2,2,2,2,4,3,3,1,2,2,9,0.0,neutral or dissatisfied +18804,116419,Female,Loyal Customer,50,Personal Travel,Eco,325,5,2,5,3,3,2,3,5,5,5,5,1,5,3,0,0.0,satisfied +18805,121597,Female,Loyal Customer,53,Personal Travel,Eco,936,1,4,1,3,3,4,4,2,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +18806,113422,Male,Loyal Customer,52,Business travel,Business,2320,5,5,4,5,5,4,5,4,4,4,4,3,4,4,36,18.0,satisfied +18807,35314,Female,Loyal Customer,60,Business travel,Eco,944,1,1,1,1,3,3,4,1,1,1,1,1,1,2,32,105.0,neutral or dissatisfied +18808,78560,Female,disloyal Customer,26,Business travel,Business,666,4,4,3,3,3,3,2,3,5,4,4,5,5,3,0,0.0,neutral or dissatisfied +18809,59039,Female,disloyal Customer,41,Business travel,Eco,1846,1,1,1,3,1,1,1,1,2,3,3,2,4,1,15,20.0,neutral or dissatisfied +18810,114294,Female,Loyal Customer,17,Personal Travel,Eco,957,1,1,1,4,1,1,1,1,2,3,3,1,4,1,115,131.0,neutral or dissatisfied +18811,5204,Male,Loyal Customer,34,Business travel,Business,2723,2,1,2,2,3,5,4,4,4,4,4,4,4,3,0,2.0,satisfied +18812,81021,Female,Loyal Customer,56,Personal Travel,Business,1399,1,2,1,3,2,4,4,1,1,1,5,4,1,1,0,0.0,neutral or dissatisfied +18813,31709,Male,Loyal Customer,48,Personal Travel,Eco,862,4,5,4,3,4,4,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +18814,38890,Male,Loyal Customer,66,Business travel,Business,3592,2,2,2,2,5,3,4,2,2,2,2,1,2,2,0,3.0,neutral or dissatisfied +18815,124923,Male,disloyal Customer,25,Business travel,Eco,728,2,2,2,3,5,2,5,5,4,3,4,5,2,5,2,5.0,neutral or dissatisfied +18816,45764,Female,disloyal Customer,23,Business travel,Eco,391,4,5,4,4,3,4,3,3,5,5,2,4,3,3,0,0.0,satisfied +18817,11775,Female,Loyal Customer,23,Personal Travel,Eco,429,4,1,4,3,2,4,2,2,4,1,2,4,2,2,4,2.0,satisfied +18818,106544,Female,Loyal Customer,45,Business travel,Business,3322,1,1,5,1,5,5,4,5,5,5,5,4,5,4,0,3.0,satisfied +18819,97628,Male,Loyal Customer,28,Business travel,Eco Plus,764,1,4,4,4,1,1,1,1,1,4,4,4,3,1,0,36.0,neutral or dissatisfied +18820,114783,Female,disloyal Customer,22,Business travel,Eco,404,2,4,2,5,2,2,2,2,5,5,5,5,4,2,23,22.0,neutral or dissatisfied +18821,79257,Male,Loyal Customer,46,Personal Travel,Eco,1598,4,5,4,4,2,4,2,2,3,2,4,5,5,2,0,0.0,satisfied +18822,4154,Female,Loyal Customer,39,Business travel,Business,2168,3,3,3,3,4,3,3,4,4,4,4,2,4,1,0,22.0,satisfied +18823,95871,Male,Loyal Customer,57,Business travel,Business,3007,1,3,3,3,4,3,2,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +18824,88907,Female,Loyal Customer,24,Personal Travel,Eco,859,2,4,2,3,4,2,4,4,5,2,3,4,5,4,0,0.0,neutral or dissatisfied +18825,56258,Female,Loyal Customer,41,Business travel,Eco,404,2,4,4,4,2,2,2,2,2,1,2,1,2,2,0,0.0,neutral or dissatisfied +18826,22905,Female,Loyal Customer,44,Personal Travel,Eco Plus,170,3,5,0,4,2,5,4,2,2,0,2,4,2,4,0,0.0,neutral or dissatisfied +18827,16997,Male,disloyal Customer,12,Business travel,Eco,843,2,3,3,3,3,3,3,3,1,5,5,1,4,3,0,2.0,neutral or dissatisfied +18828,5609,Female,Loyal Customer,55,Business travel,Business,3496,5,5,3,5,5,4,4,4,4,4,4,3,4,5,5,0.0,satisfied +18829,36383,Female,Loyal Customer,51,Personal Travel,Eco,200,3,4,3,2,4,4,5,1,1,3,1,5,1,3,0,0.0,neutral or dissatisfied +18830,116556,Female,Loyal Customer,20,Personal Travel,Eco,337,3,5,3,4,5,3,5,5,4,2,5,2,3,5,0,0.0,neutral or dissatisfied +18831,37501,Male,Loyal Customer,13,Business travel,Business,972,1,1,1,1,5,4,5,5,3,5,3,2,4,5,0,0.0,satisfied +18832,83075,Male,disloyal Customer,29,Business travel,Eco,983,2,1,1,4,4,1,4,4,1,4,3,2,3,4,12,2.0,neutral or dissatisfied +18833,99118,Male,Loyal Customer,46,Personal Travel,Eco,237,0,4,0,5,1,0,1,1,5,5,5,5,5,1,0,0.0,satisfied +18834,29822,Female,Loyal Customer,39,Business travel,Business,204,2,2,2,2,5,4,2,4,4,4,5,1,4,5,0,0.0,satisfied +18835,50554,Male,Loyal Customer,43,Personal Travel,Eco,278,4,5,4,2,3,4,3,3,4,4,4,4,5,3,0,,neutral or dissatisfied +18836,40991,Male,Loyal Customer,61,Personal Travel,Eco,984,4,4,4,1,4,4,5,4,5,3,4,4,4,4,7,0.0,neutral or dissatisfied +18837,30788,Male,Loyal Customer,33,Business travel,Business,2825,4,4,4,4,5,4,4,1,2,3,2,4,4,4,220,238.0,satisfied +18838,89266,Female,Loyal Customer,56,Business travel,Business,3423,3,3,3,3,3,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18839,40453,Female,Loyal Customer,39,Business travel,Business,175,1,1,5,1,4,1,3,5,5,5,5,4,5,3,0,0.0,satisfied +18840,129743,Female,Loyal Customer,16,Business travel,Business,337,2,3,3,3,2,2,2,4,3,3,3,2,1,2,148,150.0,neutral or dissatisfied +18841,105446,Male,Loyal Customer,28,Business travel,Business,2488,1,1,1,1,3,4,3,3,5,3,5,4,5,3,36,37.0,satisfied +18842,94569,Female,Loyal Customer,48,Business travel,Eco,248,4,2,2,2,5,1,2,4,4,4,4,4,4,4,17,14.0,neutral or dissatisfied +18843,104957,Male,Loyal Customer,54,Business travel,Business,314,4,4,4,4,3,4,4,5,5,5,5,5,5,3,0,5.0,satisfied +18844,33765,Female,Loyal Customer,39,Business travel,Eco Plus,266,3,5,5,5,3,2,3,3,5,1,5,1,4,3,0,27.0,satisfied +18845,111776,Male,disloyal Customer,23,Business travel,Business,1344,4,0,5,2,5,4,4,5,3,4,5,4,5,4,136,116.0,satisfied +18846,97324,Male,Loyal Customer,29,Business travel,Business,347,5,5,5,5,4,4,4,4,5,4,4,4,4,4,23,20.0,satisfied +18847,92076,Male,Loyal Customer,72,Business travel,Eco,1454,2,4,4,4,2,2,2,2,2,1,3,2,4,2,9,0.0,neutral or dissatisfied +18848,99576,Female,Loyal Customer,44,Business travel,Eco,930,3,5,5,5,5,4,4,3,3,3,3,4,3,2,18,32.0,neutral or dissatisfied +18849,17999,Female,Loyal Customer,29,Business travel,Business,332,2,5,5,5,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +18850,103379,Male,Loyal Customer,54,Business travel,Business,237,5,5,5,5,2,4,4,4,4,4,4,5,4,4,120,108.0,satisfied +18851,1315,Female,disloyal Customer,25,Business travel,Business,247,4,5,5,3,3,5,3,3,5,3,5,5,5,3,0,0.0,satisfied +18852,51045,Male,Loyal Customer,32,Personal Travel,Eco,266,3,0,3,1,3,3,3,3,4,3,5,5,5,3,0,0.0,neutral or dissatisfied +18853,34076,Male,Loyal Customer,52,Personal Travel,Eco,1674,3,1,3,3,2,3,5,2,2,4,4,2,3,2,70,58.0,neutral or dissatisfied +18854,127837,Female,Loyal Customer,55,Business travel,Business,3323,4,4,4,4,3,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +18855,80950,Female,Loyal Customer,42,Personal Travel,Eco Plus,341,1,5,1,5,5,5,4,2,2,1,4,4,2,4,0,0.0,neutral or dissatisfied +18856,78917,Female,Loyal Customer,60,Business travel,Business,2296,4,4,4,4,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18857,53569,Male,disloyal Customer,21,Business travel,Eco,1195,2,1,1,2,1,1,1,1,3,2,5,5,2,1,0,0.0,neutral or dissatisfied +18858,108003,Female,Loyal Customer,47,Personal Travel,Eco,271,3,1,3,4,4,4,3,5,5,3,3,4,5,3,20,0.0,neutral or dissatisfied +18859,25495,Female,disloyal Customer,22,Business travel,Eco,547,5,0,5,1,4,5,4,4,3,4,3,3,5,4,0,0.0,satisfied +18860,36536,Male,disloyal Customer,24,Business travel,Eco,1197,2,2,2,4,5,2,5,5,5,5,2,4,4,5,0,64.0,neutral or dissatisfied +18861,68043,Female,Loyal Customer,51,Business travel,Business,3897,2,2,3,2,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +18862,78276,Male,disloyal Customer,37,Business travel,Business,1598,4,4,4,2,4,4,4,4,5,4,5,5,5,4,77,70.0,neutral or dissatisfied +18863,79302,Male,Loyal Customer,40,Business travel,Business,2248,1,5,5,5,1,1,1,4,3,4,3,1,3,1,330,320.0,neutral or dissatisfied +18864,90421,Female,Loyal Customer,51,Business travel,Business,1724,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +18865,92921,Female,Loyal Customer,54,Business travel,Business,134,1,1,1,1,5,5,5,3,3,4,4,5,3,4,0,0.0,satisfied +18866,32706,Female,disloyal Customer,39,Business travel,Eco,163,2,5,1,1,2,1,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +18867,115573,Male,Loyal Customer,43,Business travel,Business,3386,3,2,2,2,1,3,4,3,3,3,3,3,3,2,24,10.0,neutral or dissatisfied +18868,123868,Female,Loyal Customer,59,Business travel,Business,3091,1,1,1,1,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +18869,86345,Male,Loyal Customer,53,Business travel,Business,1557,4,4,4,4,4,5,5,4,4,4,4,4,4,3,28,18.0,satisfied +18870,118212,Male,Loyal Customer,25,Business travel,Eco Plus,1444,4,5,5,5,4,4,1,4,4,4,4,3,3,4,0,0.0,neutral or dissatisfied +18871,110417,Female,Loyal Customer,58,Business travel,Business,2878,3,4,4,4,2,4,4,3,3,2,3,4,3,1,1,0.0,neutral or dissatisfied +18872,120190,Male,Loyal Customer,50,Business travel,Business,2091,1,1,3,1,4,4,4,5,5,5,5,3,5,3,10,8.0,satisfied +18873,101100,Female,disloyal Customer,23,Business travel,Eco,1069,1,0,0,2,3,0,2,3,4,4,5,4,5,3,0,9.0,neutral or dissatisfied +18874,34029,Female,Loyal Customer,36,Personal Travel,Eco,1598,3,5,3,4,2,3,2,2,5,5,4,5,5,2,27,6.0,neutral or dissatisfied +18875,42184,Female,Loyal Customer,48,Business travel,Business,834,3,3,3,3,3,1,5,5,5,5,5,4,5,3,0,0.0,satisfied +18876,124640,Male,disloyal Customer,22,Business travel,Business,399,4,0,4,4,3,4,3,3,4,4,5,3,4,3,0,0.0,satisfied +18877,77316,Male,Loyal Customer,40,Business travel,Business,588,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +18878,15768,Female,Loyal Customer,45,Business travel,Eco,198,4,1,1,1,3,4,2,4,4,4,4,5,4,2,0,0.0,satisfied +18879,117803,Male,Loyal Customer,58,Business travel,Business,2359,0,0,0,3,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +18880,106896,Male,Loyal Customer,38,Personal Travel,Eco,577,2,5,2,3,4,2,4,4,5,3,5,3,5,4,10,0.0,neutral or dissatisfied +18881,110325,Male,disloyal Customer,28,Business travel,Eco,883,3,3,3,4,1,3,1,1,4,1,3,3,3,1,0,0.0,neutral or dissatisfied +18882,26657,Female,disloyal Customer,26,Business travel,Eco,181,1,0,1,3,4,1,4,4,5,5,2,3,2,4,4,0.0,neutral or dissatisfied +18883,30052,Female,Loyal Customer,16,Business travel,Eco,548,4,1,1,1,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +18884,97158,Male,Loyal Customer,22,Business travel,Business,3959,2,4,4,4,2,2,2,2,2,3,4,4,4,2,15,11.0,neutral or dissatisfied +18885,31842,Male,Loyal Customer,21,Business travel,Business,2677,2,5,2,2,4,4,4,4,5,2,3,5,5,4,0,0.0,satisfied +18886,79221,Male,Loyal Customer,44,Personal Travel,Eco,1990,1,4,1,2,5,1,5,5,2,1,5,3,5,5,0,0.0,neutral or dissatisfied +18887,49030,Female,Loyal Customer,45,Business travel,Eco,190,5,5,5,5,2,4,5,5,5,5,5,5,5,1,42,91.0,satisfied +18888,52122,Male,Loyal Customer,54,Business travel,Eco Plus,639,2,3,3,3,2,2,2,2,3,2,5,1,2,2,0,0.0,satisfied +18889,78712,Female,disloyal Customer,38,Business travel,Eco,447,3,2,3,3,3,3,2,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +18890,84035,Female,Loyal Customer,34,Business travel,Business,773,3,3,3,3,2,5,5,5,5,5,5,4,5,4,65,47.0,satisfied +18891,60462,Male,Loyal Customer,57,Business travel,Business,862,3,2,2,2,4,3,3,3,3,3,3,3,3,4,3,8.0,neutral or dissatisfied +18892,103771,Male,Loyal Customer,55,Business travel,Business,2806,3,3,4,3,3,4,3,3,3,3,3,2,3,2,2,0.0,neutral or dissatisfied +18893,38432,Female,Loyal Customer,47,Business travel,Eco Plus,965,4,5,5,5,3,5,2,4,4,4,4,5,4,2,41,32.0,satisfied +18894,22921,Female,Loyal Customer,39,Business travel,Business,1690,2,2,4,2,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +18895,116454,Female,Loyal Customer,13,Personal Travel,Eco,296,3,4,3,3,5,3,5,5,2,1,4,4,3,5,53,58.0,neutral or dissatisfied +18896,109065,Female,Loyal Customer,38,Business travel,Business,3741,1,2,2,2,3,1,2,1,1,1,1,1,1,2,30,9.0,neutral or dissatisfied +18897,74317,Female,Loyal Customer,57,Business travel,Business,1171,2,1,1,1,1,2,2,2,2,1,2,4,2,3,45,52.0,neutral or dissatisfied +18898,77151,Male,Loyal Customer,25,Personal Travel,Eco,1865,3,4,3,4,3,3,3,3,4,1,3,4,2,3,27,0.0,neutral or dissatisfied +18899,68304,Male,Loyal Customer,70,Personal Travel,Eco,1797,1,5,1,4,4,1,4,4,5,4,4,3,3,4,0,7.0,neutral or dissatisfied +18900,123595,Male,Loyal Customer,29,Personal Travel,Eco,1773,2,4,2,5,1,2,1,1,2,4,4,1,5,1,0,0.0,neutral or dissatisfied +18901,96282,Female,Loyal Customer,65,Personal Travel,Eco,687,1,4,1,3,2,5,5,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +18902,121540,Female,Loyal Customer,26,Business travel,Business,936,3,3,3,3,4,4,4,4,3,4,4,5,5,4,3,0.0,satisfied +18903,94383,Male,disloyal Customer,24,Business travel,Eco,239,3,5,3,3,3,3,5,3,3,2,5,4,5,3,2,0.0,neutral or dissatisfied +18904,118942,Female,Loyal Customer,38,Business travel,Business,3345,5,5,5,5,3,5,4,4,4,4,4,5,4,3,3,19.0,satisfied +18905,119857,Female,Loyal Customer,28,Business travel,Eco,912,2,3,3,3,2,2,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +18906,13659,Male,Loyal Customer,33,Business travel,Business,1902,3,3,3,3,4,4,4,4,2,1,5,5,1,4,0,0.0,satisfied +18907,92978,Female,Loyal Customer,48,Business travel,Business,2265,1,1,1,1,4,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +18908,123186,Male,Loyal Customer,42,Personal Travel,Eco,328,4,0,4,4,4,4,1,4,3,2,3,4,4,4,4,36.0,neutral or dissatisfied +18909,11876,Female,Loyal Customer,49,Personal Travel,Eco,1042,2,5,2,3,2,4,5,3,3,2,2,4,3,4,58,43.0,neutral or dissatisfied +18910,107992,Male,Loyal Customer,32,Business travel,Business,2153,4,1,1,1,4,4,4,4,4,4,3,3,4,4,25,17.0,neutral or dissatisfied +18911,78915,Male,Loyal Customer,42,Business travel,Business,1667,1,1,1,1,3,5,4,4,4,4,4,5,4,3,51,28.0,satisfied +18912,117935,Female,Loyal Customer,43,Business travel,Business,3598,4,2,2,2,5,4,4,4,4,4,4,2,4,4,30,18.0,neutral or dissatisfied +18913,51243,Female,Loyal Customer,33,Business travel,Eco Plus,308,0,0,0,1,3,0,3,3,3,2,5,1,3,3,13,13.0,satisfied +18914,98640,Male,disloyal Customer,22,Business travel,Eco,834,2,2,2,3,3,2,3,3,3,5,4,4,4,3,22,6.0,neutral or dissatisfied +18915,129094,Male,disloyal Customer,25,Business travel,Eco,2583,2,2,2,4,2,2,2,4,3,4,3,2,4,2,50,43.0,neutral or dissatisfied +18916,1657,Male,Loyal Customer,47,Business travel,Business,435,3,1,3,1,2,3,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +18917,109376,Female,disloyal Customer,9,Business travel,Eco,1046,3,3,3,4,1,3,1,1,3,1,3,2,3,1,35,9.0,neutral or dissatisfied +18918,122535,Female,disloyal Customer,28,Business travel,Business,500,3,3,3,4,2,3,2,2,4,2,4,3,5,2,37,30.0,neutral or dissatisfied +18919,93030,Male,disloyal Customer,23,Business travel,Eco,436,0,4,0,1,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +18920,3049,Male,Loyal Customer,62,Personal Travel,Eco,489,3,2,3,4,5,3,2,5,4,5,4,1,3,5,0,28.0,neutral or dissatisfied +18921,123741,Male,disloyal Customer,33,Business travel,Eco,96,3,3,2,4,5,2,2,5,1,2,4,2,4,5,0,0.0,neutral or dissatisfied +18922,18373,Female,Loyal Customer,34,Personal Travel,Eco,169,3,5,3,4,1,3,1,1,4,5,5,5,4,1,16,40.0,neutral or dissatisfied +18923,37434,Female,disloyal Customer,20,Business travel,Eco,1028,2,2,2,3,5,2,5,5,3,3,4,3,4,5,39,32.0,neutral or dissatisfied +18924,39451,Male,Loyal Customer,55,Personal Travel,Eco,129,2,0,2,2,5,2,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +18925,30705,Male,Loyal Customer,9,Business travel,Eco Plus,680,4,2,1,2,4,4,5,4,1,1,3,2,3,4,0,0.0,satisfied +18926,95159,Male,Loyal Customer,28,Personal Travel,Eco,239,2,5,2,3,5,2,5,5,5,3,4,4,4,5,31,27.0,neutral or dissatisfied +18927,87759,Female,Loyal Customer,33,Business travel,Business,214,5,5,5,5,4,4,5,5,5,5,5,3,5,4,1,0.0,satisfied +18928,103968,Female,Loyal Customer,21,Personal Travel,Eco,770,3,4,3,4,4,3,4,4,5,5,5,3,4,4,0,3.0,neutral or dissatisfied +18929,104794,Female,Loyal Customer,49,Business travel,Business,587,2,2,2,2,3,5,4,4,4,5,4,5,4,5,81,99.0,satisfied +18930,81545,Male,Loyal Customer,34,Personal Travel,Eco,1124,2,4,2,1,4,2,4,4,4,2,3,5,5,4,23,17.0,neutral or dissatisfied +18931,111520,Male,Loyal Customer,36,Personal Travel,Eco,391,2,4,3,2,1,3,1,1,5,5,4,4,4,1,34,18.0,neutral or dissatisfied +18932,78947,Female,Loyal Customer,41,Business travel,Business,1951,5,2,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +18933,57373,Male,Loyal Customer,27,Personal Travel,Eco,414,4,3,4,1,5,4,1,5,3,2,3,5,1,5,0,12.0,neutral or dissatisfied +18934,117895,Male,Loyal Customer,43,Business travel,Eco,255,1,1,1,1,2,1,2,2,4,5,2,3,2,2,12,7.0,neutral or dissatisfied +18935,92210,Female,Loyal Customer,12,Personal Travel,Eco,1979,1,2,1,4,4,1,4,4,2,1,4,3,3,4,4,0.0,neutral or dissatisfied +18936,10167,Female,disloyal Customer,23,Business travel,Eco,224,4,0,4,3,1,4,1,1,3,5,5,5,4,1,0,0.0,neutral or dissatisfied +18937,106954,Male,Loyal Customer,22,Business travel,Business,937,2,2,2,2,5,5,5,5,3,4,4,3,4,5,17,21.0,satisfied +18938,3827,Male,disloyal Customer,26,Business travel,Eco,650,2,3,2,3,5,2,5,5,2,4,4,1,3,5,0,0.0,neutral or dissatisfied +18939,10414,Male,Loyal Customer,45,Business travel,Business,1883,2,2,2,2,2,4,5,4,4,4,4,3,4,5,66,58.0,satisfied +18940,128152,Male,Loyal Customer,55,Business travel,Business,1972,1,1,5,1,2,3,4,1,1,2,1,5,1,4,0,0.0,satisfied +18941,23191,Male,Loyal Customer,30,Personal Travel,Eco,223,3,1,0,3,2,0,2,2,2,4,4,4,4,2,20,14.0,neutral or dissatisfied +18942,1526,Female,Loyal Customer,47,Business travel,Business,987,1,1,1,1,3,3,4,1,1,1,1,4,1,4,0,8.0,neutral or dissatisfied +18943,102013,Male,disloyal Customer,39,Business travel,Business,258,4,4,4,3,3,4,2,3,3,3,5,3,4,3,14,2.0,neutral or dissatisfied +18944,122958,Female,Loyal Customer,48,Business travel,Business,2661,5,5,5,5,2,5,4,5,5,5,5,4,5,3,5,19.0,satisfied +18945,120961,Female,Loyal Customer,58,Business travel,Eco,861,2,3,3,3,1,3,2,2,2,2,2,1,2,1,4,25.0,neutral or dissatisfied +18946,104358,Male,Loyal Customer,66,Personal Travel,Eco Plus,452,5,1,5,2,3,5,3,3,1,2,2,3,3,3,0,0.0,satisfied +18947,110165,Male,Loyal Customer,36,Personal Travel,Eco,882,3,5,3,4,2,3,1,2,4,3,5,3,4,2,14,0.0,neutral or dissatisfied +18948,12602,Female,Loyal Customer,33,Personal Travel,Eco,542,3,4,3,4,1,3,1,1,2,1,1,4,2,1,12,7.0,neutral or dissatisfied +18949,6233,Male,Loyal Customer,60,Business travel,Business,3431,5,5,2,5,3,5,5,4,4,4,4,5,4,4,66,98.0,satisfied +18950,72678,Male,Loyal Customer,7,Personal Travel,Eco,964,4,1,4,2,5,4,5,5,1,1,3,2,3,5,11,3.0,neutral or dissatisfied +18951,22920,Female,Loyal Customer,45,Business travel,Business,489,2,2,2,2,2,5,4,5,5,4,5,5,5,4,0,0.0,satisfied +18952,77839,Female,disloyal Customer,33,Business travel,Business,731,2,2,2,3,5,2,5,5,5,5,5,4,4,5,0,0.0,neutral or dissatisfied +18953,19197,Male,Loyal Customer,56,Business travel,Business,142,5,5,2,5,4,2,2,4,4,4,5,1,4,1,0,0.0,satisfied +18954,55427,Female,Loyal Customer,39,Business travel,Business,2521,5,5,5,5,4,4,4,4,3,5,4,4,5,4,14,21.0,satisfied +18955,24606,Female,Loyal Customer,51,Business travel,Eco,666,2,5,5,5,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +18956,13695,Female,Loyal Customer,33,Business travel,Business,3567,4,5,5,5,5,3,2,4,4,4,4,3,4,3,0,0.0,neutral or dissatisfied +18957,77571,Male,Loyal Customer,44,Business travel,Business,3294,2,2,2,2,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +18958,78796,Male,Loyal Customer,17,Business travel,Business,554,3,2,2,2,3,3,3,3,3,5,3,2,4,3,0,7.0,neutral or dissatisfied +18959,25849,Female,Loyal Customer,33,Business travel,Business,3493,3,4,4,4,3,3,4,3,3,3,3,3,3,3,2,0.0,neutral or dissatisfied +18960,3068,Female,disloyal Customer,28,Business travel,Business,413,3,3,3,5,5,3,5,5,5,4,5,4,4,5,5,0.0,neutral or dissatisfied +18961,55545,Female,disloyal Customer,22,Business travel,Eco,150,0,0,0,1,4,0,4,4,5,4,4,2,5,4,0,0.0,satisfied +18962,88818,Male,Loyal Customer,36,Business travel,Eco Plus,271,3,5,5,5,3,3,3,3,1,4,3,3,4,3,8,12.0,neutral or dissatisfied +18963,103409,Female,Loyal Customer,34,Business travel,Business,237,5,5,5,5,3,5,5,4,4,4,4,5,4,3,71,,satisfied +18964,30167,Female,Loyal Customer,13,Personal Travel,Eco,399,2,4,2,1,4,2,4,4,3,4,4,3,4,4,0,0.0,neutral or dissatisfied +18965,16017,Male,Loyal Customer,15,Personal Travel,Eco,722,3,2,3,4,5,3,5,5,2,1,4,4,4,5,51,79.0,neutral or dissatisfied +18966,23441,Female,Loyal Customer,46,Business travel,Business,2072,4,4,4,4,3,1,4,5,5,5,5,4,5,4,0,0.0,satisfied +18967,9213,Female,Loyal Customer,44,Business travel,Business,100,0,4,0,2,4,4,4,3,2,5,4,4,5,4,230,214.0,satisfied +18968,68572,Female,Loyal Customer,60,Business travel,Business,1616,3,3,3,3,5,5,4,2,2,2,2,3,2,5,43,23.0,satisfied +18969,4115,Male,Loyal Customer,55,Business travel,Business,3384,3,3,3,3,4,3,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +18970,9666,Female,Loyal Customer,53,Business travel,Business,199,2,2,2,2,3,4,4,4,4,4,4,4,4,5,4,39.0,satisfied +18971,56348,Female,Loyal Customer,30,Business travel,Eco,200,4,5,5,5,4,4,4,4,3,3,4,4,3,4,0,0.0,neutral or dissatisfied +18972,93021,Female,Loyal Customer,30,Personal Travel,Eco,1524,3,2,3,2,4,3,4,4,1,1,2,4,3,4,0,0.0,neutral or dissatisfied +18973,9616,Male,Loyal Customer,52,Personal Travel,Eco,229,2,5,0,2,2,0,4,2,3,4,5,4,5,2,66,72.0,neutral or dissatisfied +18974,103461,Female,Loyal Customer,13,Personal Travel,Eco,448,2,3,2,4,3,2,2,3,2,2,2,4,3,3,0,0.0,neutral or dissatisfied +18975,8000,Male,Loyal Customer,39,Business travel,Business,402,4,4,4,4,3,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +18976,10261,Female,Loyal Customer,7,Personal Travel,Business,166,4,4,4,4,5,4,1,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +18977,6627,Male,Loyal Customer,17,Business travel,Business,719,3,4,3,3,4,4,4,4,3,3,3,4,1,4,0,0.0,satisfied +18978,41027,Female,disloyal Customer,26,Business travel,Eco,989,2,2,2,3,5,2,5,5,5,4,1,1,4,5,0,0.0,neutral or dissatisfied +18979,54494,Male,Loyal Customer,66,Business travel,Eco,925,1,3,3,3,1,1,1,1,1,1,3,3,3,1,0,0.0,neutral or dissatisfied +18980,67816,Female,Loyal Customer,44,Business travel,Eco,835,4,3,3,3,3,4,3,4,4,4,4,3,4,4,92,104.0,neutral or dissatisfied +18981,116828,Male,Loyal Customer,37,Business travel,Business,370,3,3,3,3,3,3,3,3,3,3,3,3,3,3,34,32.0,neutral or dissatisfied +18982,57363,Male,Loyal Customer,69,Personal Travel,Eco,414,3,5,3,1,3,3,3,3,2,4,5,2,2,3,0,0.0,neutral or dissatisfied +18983,114991,Female,Loyal Customer,59,Business travel,Business,3043,2,2,2,2,2,5,5,5,5,5,5,4,5,3,22,13.0,satisfied +18984,23626,Female,disloyal Customer,37,Business travel,Eco,911,2,2,2,3,1,2,1,1,4,2,1,1,3,1,0,0.0,neutral or dissatisfied +18985,96970,Female,Loyal Customer,46,Business travel,Business,883,5,2,2,2,1,3,4,5,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +18986,96676,Female,Loyal Customer,28,Business travel,Eco Plus,1036,4,4,4,4,4,4,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +18987,7293,Male,Loyal Customer,69,Personal Travel,Eco,135,3,0,3,3,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +18988,30118,Male,Loyal Customer,69,Personal Travel,Eco,95,5,5,5,5,2,5,2,2,3,3,1,4,4,2,0,0.0,satisfied +18989,87926,Male,Loyal Customer,52,Business travel,Business,3131,1,2,2,2,3,3,3,1,1,1,1,2,1,1,0,0.0,neutral or dissatisfied +18990,116536,Female,Loyal Customer,19,Personal Travel,Eco,447,2,4,2,4,4,2,4,4,5,5,4,5,5,4,34,43.0,neutral or dissatisfied +18991,25658,Male,Loyal Customer,31,Business travel,Business,2730,3,3,4,3,5,5,5,5,2,4,1,2,3,5,5,0.0,satisfied +18992,81358,Female,Loyal Customer,54,Personal Travel,Eco,1299,3,4,3,4,4,4,5,4,4,3,4,5,4,3,30,35.0,neutral or dissatisfied +18993,38673,Male,Loyal Customer,49,Personal Travel,Eco,2588,3,3,4,4,2,4,4,2,1,3,2,1,3,2,0,0.0,neutral or dissatisfied +18994,106749,Male,Loyal Customer,46,Business travel,Eco,837,5,4,4,4,5,5,5,5,5,1,5,1,2,5,0,0.0,satisfied +18995,51203,Male,Loyal Customer,41,Business travel,Eco Plus,447,2,5,5,5,2,2,2,2,2,3,1,4,2,2,62,46.0,satisfied +18996,91827,Male,Loyal Customer,41,Business travel,Business,3961,3,3,5,3,3,5,4,5,5,5,5,3,5,4,17,4.0,satisfied +18997,8114,Female,Loyal Customer,48,Business travel,Business,3872,1,1,4,1,2,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +18998,84706,Male,disloyal Customer,8,Business travel,Eco,516,2,2,2,4,5,2,5,5,4,1,3,2,4,5,34,25.0,neutral or dissatisfied +18999,227,Female,Loyal Customer,56,Personal Travel,Eco,213,3,0,0,3,4,4,5,5,5,0,5,3,5,5,20,8.0,neutral or dissatisfied +19000,2247,Female,Loyal Customer,42,Business travel,Business,693,2,1,1,1,2,2,2,2,5,3,3,2,4,2,815,822.0,neutral or dissatisfied +19001,25797,Female,Loyal Customer,59,Personal Travel,Eco,762,3,5,3,1,2,4,4,4,4,3,4,3,4,5,0,2.0,neutral or dissatisfied +19002,67868,Female,Loyal Customer,63,Personal Travel,Eco,1438,1,4,1,5,4,5,4,2,2,1,2,3,2,5,0,0.0,neutral or dissatisfied +19003,27654,Male,disloyal Customer,39,Business travel,Business,1107,2,2,2,3,2,2,2,2,1,3,2,4,3,2,0,0.0,neutral or dissatisfied +19004,97671,Female,Loyal Customer,39,Business travel,Business,1742,2,2,2,2,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +19005,593,Female,Loyal Customer,50,Business travel,Business,247,2,2,2,2,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +19006,120989,Female,Loyal Customer,46,Business travel,Business,2710,2,2,3,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +19007,33739,Female,disloyal Customer,23,Business travel,Eco,899,2,2,2,4,5,2,5,5,2,3,3,4,4,5,0,37.0,neutral or dissatisfied +19008,82572,Female,Loyal Customer,58,Business travel,Business,1738,2,2,2,2,2,5,4,4,4,5,4,3,4,4,0,9.0,satisfied +19009,79288,Female,Loyal Customer,50,Business travel,Business,2248,5,5,5,5,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +19010,53896,Female,Loyal Customer,49,Personal Travel,Eco,224,2,5,0,1,4,4,5,3,3,0,3,5,3,3,0,0.0,neutral or dissatisfied +19011,43589,Female,disloyal Customer,37,Business travel,Eco,228,2,0,2,2,4,2,4,4,2,2,1,1,3,4,31,55.0,neutral or dissatisfied +19012,18252,Male,Loyal Customer,14,Personal Travel,Eco,346,2,4,2,2,3,2,3,3,5,5,4,4,4,3,12,22.0,neutral or dissatisfied +19013,81612,Male,Loyal Customer,17,Personal Travel,Eco,349,3,4,2,3,4,2,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +19014,4494,Female,Loyal Customer,41,Business travel,Business,435,2,1,1,1,1,4,4,2,2,2,2,4,2,4,36,26.0,neutral or dissatisfied +19015,102925,Female,disloyal Customer,27,Business travel,Eco,436,4,2,4,2,4,4,4,4,3,2,2,4,2,4,5,0.0,neutral or dissatisfied +19016,32467,Male,Loyal Customer,34,Business travel,Eco,102,3,1,1,1,3,3,3,3,2,2,3,3,4,3,0,0.0,neutral or dissatisfied +19017,75483,Male,Loyal Customer,46,Personal Travel,Eco,2342,2,3,2,2,1,2,1,1,4,4,5,4,5,1,0,2.0,neutral or dissatisfied +19018,109333,Female,Loyal Customer,42,Personal Travel,Eco,1136,2,5,2,4,3,3,5,4,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +19019,67312,Female,Loyal Customer,34,Business travel,Eco Plus,985,4,1,1,1,4,4,4,4,1,2,3,4,1,4,0,0.0,satisfied +19020,78651,Female,disloyal Customer,22,Business travel,Eco,2172,4,4,4,1,4,4,4,4,2,3,4,4,5,4,1,0.0,satisfied +19021,76395,Female,Loyal Customer,52,Personal Travel,Eco,931,1,5,0,4,3,5,4,1,1,0,3,4,1,4,3,0.0,neutral or dissatisfied +19022,91700,Female,Loyal Customer,30,Business travel,Business,2670,2,2,2,2,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +19023,7068,Female,Loyal Customer,47,Business travel,Business,157,1,1,1,1,5,5,5,5,5,5,4,5,5,5,0,0.0,satisfied +19024,66764,Female,Loyal Customer,47,Personal Travel,Eco,978,3,4,3,1,2,4,5,2,2,3,4,4,2,4,0,0.0,neutral or dissatisfied +19025,23340,Female,Loyal Customer,68,Personal Travel,Eco,641,1,4,1,3,3,5,4,5,5,1,5,3,5,3,11,12.0,neutral or dissatisfied +19026,101542,Male,Loyal Customer,17,Personal Travel,Eco,345,1,1,1,4,3,1,3,3,3,1,4,2,4,3,0,0.0,neutral or dissatisfied +19027,84594,Male,disloyal Customer,37,Business travel,Business,707,1,0,0,2,1,0,1,1,4,3,4,5,4,1,6,5.0,neutral or dissatisfied +19028,69118,Female,disloyal Customer,31,Business travel,Eco,1598,4,4,4,3,5,4,5,5,4,5,3,3,3,5,8,0.0,neutral or dissatisfied +19029,95962,Male,Loyal Customer,44,Business travel,Business,1841,5,5,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +19030,111973,Male,Loyal Customer,58,Business travel,Eco,533,5,5,5,5,5,5,5,5,1,2,5,1,2,5,0,0.0,satisfied +19031,57622,Female,disloyal Customer,48,Business travel,Business,200,4,3,3,3,2,4,2,2,4,4,5,4,4,2,3,0.0,neutral or dissatisfied +19032,32960,Female,Loyal Customer,8,Personal Travel,Eco,101,2,4,2,2,1,2,1,1,3,1,2,3,2,1,0,0.0,neutral or dissatisfied +19033,54288,Female,Loyal Customer,24,Business travel,Eco,1075,4,3,3,3,4,4,4,4,3,4,2,5,5,4,5,2.0,satisfied +19034,63181,Male,Loyal Customer,44,Business travel,Business,3179,3,4,3,3,2,5,5,5,5,5,5,4,5,5,33,24.0,satisfied +19035,6669,Male,Loyal Customer,41,Business travel,Business,2035,3,3,3,3,5,5,4,5,5,5,5,5,5,5,17,8.0,satisfied +19036,2951,Male,disloyal Customer,25,Business travel,Eco,835,2,2,2,4,2,2,2,2,4,1,4,1,3,2,0,0.0,neutral or dissatisfied +19037,50235,Female,Loyal Customer,58,Business travel,Eco,209,3,3,3,3,5,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +19038,13791,Female,disloyal Customer,28,Business travel,Eco Plus,925,3,3,3,3,3,3,3,3,3,5,1,1,3,3,66,69.0,neutral or dissatisfied +19039,54586,Female,Loyal Customer,40,Business travel,Business,3986,5,5,5,5,3,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +19040,36564,Female,Loyal Customer,26,Business travel,Eco,1185,1,1,1,1,1,1,2,1,4,3,3,3,3,1,10,9.0,neutral or dissatisfied +19041,99830,Female,Loyal Customer,42,Business travel,Business,2742,3,3,3,3,2,5,4,4,4,4,4,5,4,3,6,0.0,satisfied +19042,110421,Female,disloyal Customer,26,Business travel,Business,387,2,2,2,3,4,2,4,4,4,3,3,1,4,4,6,17.0,neutral or dissatisfied +19043,100813,Female,Loyal Customer,17,Business travel,Business,2218,4,1,1,1,4,4,4,1,1,1,1,4,2,4,222,205.0,neutral or dissatisfied +19044,32836,Male,Loyal Customer,20,Personal Travel,Eco,101,4,5,4,2,2,4,2,2,3,2,4,4,5,2,0,0.0,satisfied +19045,44196,Female,Loyal Customer,48,Personal Travel,Eco,231,4,3,4,3,5,5,4,1,1,4,1,4,1,3,0,0.0,neutral or dissatisfied +19046,10984,Female,Loyal Customer,52,Business travel,Business,3489,3,3,3,3,4,5,3,4,4,4,3,2,4,3,0,10.0,satisfied +19047,128699,Female,Loyal Customer,57,Business travel,Business,1464,1,1,2,1,5,4,4,4,4,5,4,3,4,3,71,94.0,satisfied +19048,41992,Female,Loyal Customer,49,Business travel,Eco,116,4,2,2,2,5,2,4,4,4,4,4,4,4,2,0,0.0,satisfied +19049,1146,Female,Loyal Customer,64,Personal Travel,Eco,102,2,4,2,3,5,4,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +19050,32379,Female,Loyal Customer,56,Business travel,Eco,101,5,2,4,2,5,2,1,5,5,5,5,5,5,1,0,0.0,satisfied +19051,26043,Male,Loyal Customer,60,Business travel,Business,432,3,5,3,3,5,3,1,5,5,4,5,2,5,5,0,0.0,satisfied +19052,114128,Male,Loyal Customer,53,Business travel,Business,853,4,4,4,4,4,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +19053,122326,Male,Loyal Customer,43,Business travel,Eco Plus,573,3,1,1,1,3,3,3,3,2,4,3,1,3,3,0,1.0,neutral or dissatisfied +19054,81828,Male,Loyal Customer,7,Personal Travel,Eco,1487,2,4,2,3,4,2,4,4,4,3,4,4,5,4,0,0.0,neutral or dissatisfied +19055,84872,Male,Loyal Customer,59,Personal Travel,Eco,534,3,2,3,1,3,3,3,3,2,4,2,1,2,3,0,0.0,neutral or dissatisfied +19056,78349,Male,Loyal Customer,45,Personal Travel,Eco,1547,3,4,3,3,2,3,2,2,4,2,4,3,4,2,0,0.0,neutral or dissatisfied +19057,123359,Female,Loyal Customer,60,Business travel,Eco,644,4,5,5,5,3,4,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +19058,102605,Male,Loyal Customer,56,Personal Travel,Eco Plus,397,1,5,1,2,4,1,4,4,3,5,4,5,5,4,3,0.0,neutral or dissatisfied +19059,75616,Male,Loyal Customer,27,Personal Travel,Eco,337,4,4,4,1,4,5,4,3,5,5,4,4,3,4,135,135.0,neutral or dissatisfied +19060,120552,Male,disloyal Customer,23,Business travel,Eco,810,3,3,3,3,2,3,2,2,1,4,2,4,3,2,0,10.0,neutral or dissatisfied +19061,44820,Male,disloyal Customer,49,Personal Travel,Eco,491,5,4,5,2,3,5,3,3,1,4,3,3,4,3,0,,satisfied +19062,97477,Male,Loyal Customer,53,Business travel,Business,756,3,3,3,3,4,4,5,4,4,4,4,5,4,3,18,4.0,satisfied +19063,28104,Female,disloyal Customer,27,Business travel,Eco,550,3,0,3,5,1,3,1,1,3,4,1,2,3,1,0,0.0,neutral or dissatisfied +19064,41894,Male,Loyal Customer,34,Business travel,Eco,129,3,4,4,4,3,4,3,3,3,2,4,5,5,3,0,0.0,satisfied +19065,24906,Male,disloyal Customer,25,Business travel,Eco,762,3,3,3,1,5,3,5,5,3,3,5,2,2,5,42,25.0,neutral or dissatisfied +19066,17520,Male,Loyal Customer,41,Personal Travel,Eco,341,3,5,3,5,3,3,5,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +19067,20025,Male,disloyal Customer,22,Business travel,Eco,607,2,4,2,1,4,2,5,4,1,5,5,1,3,4,106,97.0,neutral or dissatisfied +19068,85834,Male,Loyal Customer,33,Personal Travel,Eco,666,1,4,1,5,3,1,3,3,4,5,3,1,1,3,0,0.0,neutral or dissatisfied +19069,118912,Female,Loyal Customer,53,Personal Travel,Eco,570,1,2,1,4,4,4,3,5,5,1,5,4,5,1,0,0.0,neutral or dissatisfied +19070,105458,Female,Loyal Customer,13,Personal Travel,Eco,998,2,5,2,3,2,2,2,2,3,5,2,2,5,2,0,0.0,neutral or dissatisfied +19071,9114,Female,Loyal Customer,46,Business travel,Business,3302,4,4,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +19072,12009,Female,disloyal Customer,37,Business travel,Business,351,1,2,2,3,3,2,3,3,4,5,3,3,4,3,8,0.0,neutral or dissatisfied +19073,28141,Female,disloyal Customer,25,Business travel,Eco,933,5,5,5,3,3,5,3,3,5,1,4,1,4,3,0,0.0,satisfied +19074,73042,Male,Loyal Customer,24,Personal Travel,Eco,944,3,2,3,2,3,3,5,3,4,1,2,1,2,3,7,0.0,neutral or dissatisfied +19075,66253,Female,Loyal Customer,64,Personal Travel,Eco,460,2,2,2,4,2,3,4,5,5,2,4,1,5,2,0,0.0,neutral or dissatisfied +19076,32476,Male,Loyal Customer,33,Business travel,Eco,216,5,3,3,3,5,5,5,5,3,1,4,1,4,5,40,45.0,satisfied +19077,47080,Female,Loyal Customer,53,Personal Travel,Eco,438,3,4,3,3,4,4,5,3,3,3,3,3,3,4,33,12.0,neutral or dissatisfied +19078,66862,Male,Loyal Customer,8,Personal Travel,Eco,731,3,2,3,3,4,3,4,4,1,5,4,3,3,4,25,52.0,neutral or dissatisfied +19079,41078,Female,Loyal Customer,53,Business travel,Business,1667,4,4,4,4,5,3,1,5,5,5,5,5,5,2,0,0.0,satisfied +19080,84365,Female,Loyal Customer,57,Business travel,Eco,606,2,2,2,2,1,3,3,2,2,2,2,3,2,1,20,16.0,neutral or dissatisfied +19081,126967,Male,Loyal Customer,45,Business travel,Business,3315,3,3,3,3,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +19082,77022,Female,Loyal Customer,47,Business travel,Business,422,1,1,2,2,5,4,3,1,1,1,1,4,1,4,27,21.0,neutral or dissatisfied +19083,87888,Male,Loyal Customer,43,Business travel,Business,2904,5,5,5,5,2,5,5,4,4,4,4,5,4,3,12,12.0,satisfied +19084,67756,Male,Loyal Customer,48,Business travel,Business,1550,2,2,2,2,3,4,5,3,3,4,3,3,3,5,0,0.0,satisfied +19085,124313,Male,disloyal Customer,36,Business travel,Eco,201,2,5,2,4,4,2,4,4,4,4,4,2,3,4,0,0.0,neutral or dissatisfied +19086,64617,Female,Loyal Customer,48,Business travel,Business,247,2,2,2,2,4,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +19087,40436,Male,Loyal Customer,34,Business travel,Business,2156,4,4,4,4,4,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +19088,54822,Male,Loyal Customer,29,Business travel,Business,3690,5,5,5,5,5,5,5,5,1,2,4,3,2,5,23,25.0,satisfied +19089,107645,Male,Loyal Customer,60,Business travel,Business,3986,4,4,4,4,4,5,5,5,5,5,5,3,5,5,97,96.0,satisfied +19090,2399,Female,Loyal Customer,46,Business travel,Business,767,2,2,2,2,2,4,5,2,2,2,2,3,2,3,12,11.0,satisfied +19091,25254,Female,Loyal Customer,35,Business travel,Business,1840,2,3,2,2,4,4,5,4,4,3,4,3,4,4,0,0.0,satisfied +19092,51174,Female,Loyal Customer,56,Personal Travel,Eco,326,4,1,4,4,2,3,3,4,4,4,4,3,4,2,0,5.0,neutral or dissatisfied +19093,89045,Female,Loyal Customer,57,Business travel,Business,1947,5,5,5,5,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +19094,108095,Female,Loyal Customer,9,Business travel,Business,1997,1,3,3,3,1,1,1,1,2,1,4,2,4,1,2,11.0,neutral or dissatisfied +19095,104924,Male,Loyal Customer,52,Business travel,Business,210,1,1,3,1,3,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +19096,15590,Female,Loyal Customer,55,Business travel,Business,228,1,1,1,1,3,4,2,5,5,5,5,1,5,1,0,0.0,satisfied +19097,55476,Male,Loyal Customer,34,Personal Travel,Eco,1825,2,4,2,3,1,2,1,1,4,5,4,4,4,1,0,0.0,neutral or dissatisfied +19098,101705,Male,Loyal Customer,38,Business travel,Business,1624,4,4,4,4,3,4,4,5,5,5,5,3,5,3,49,30.0,satisfied +19099,7318,Male,Loyal Customer,30,Personal Travel,Eco Plus,116,3,3,3,2,3,3,3,3,4,4,3,2,2,3,0,0.0,neutral or dissatisfied +19100,21774,Male,disloyal Customer,22,Business travel,Eco,341,5,0,5,3,2,5,2,2,3,3,3,2,5,2,23,16.0,satisfied +19101,37228,Male,Loyal Customer,39,Business travel,Business,2356,4,4,4,4,3,5,4,4,4,4,4,4,4,3,7,2.0,satisfied +19102,125486,Female,Loyal Customer,39,Business travel,Eco Plus,2979,2,2,2,2,2,2,2,4,5,4,3,2,4,2,0,0.0,neutral or dissatisfied +19103,9741,Male,disloyal Customer,35,Business travel,Business,908,3,3,3,2,3,3,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +19104,86729,Male,Loyal Customer,28,Personal Travel,Eco,1747,4,3,4,4,2,4,2,2,1,3,2,2,4,2,0,0.0,neutral or dissatisfied +19105,42364,Male,Loyal Customer,52,Personal Travel,Eco,329,5,2,5,4,5,5,5,5,4,2,4,3,3,5,0,0.0,satisfied +19106,44852,Male,Loyal Customer,50,Personal Travel,Eco,413,2,4,2,4,4,2,4,4,3,2,5,3,4,4,0,0.0,neutral or dissatisfied +19107,114824,Male,Loyal Customer,57,Business travel,Business,372,2,2,5,2,2,5,4,5,5,4,5,5,5,5,47,50.0,satisfied +19108,36948,Male,Loyal Customer,48,Personal Travel,Eco,718,2,4,3,3,2,3,2,2,2,3,4,2,4,2,0,0.0,neutral or dissatisfied +19109,23050,Male,disloyal Customer,22,Business travel,Eco,820,2,2,2,4,3,2,3,3,5,5,4,4,4,3,13,0.0,neutral or dissatisfied +19110,9000,Female,Loyal Customer,64,Personal Travel,Eco,228,4,3,4,3,2,2,2,2,2,4,2,4,2,2,79,80.0,neutral or dissatisfied +19111,50821,Male,Loyal Customer,34,Personal Travel,Eco,199,3,2,3,3,3,3,3,3,2,4,4,3,4,3,0,0.0,neutral or dissatisfied +19112,100290,Female,disloyal Customer,29,Business travel,Business,1092,1,1,1,2,4,1,4,4,5,2,5,4,4,4,4,0.0,neutral or dissatisfied +19113,119789,Male,Loyal Customer,51,Business travel,Business,2152,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +19114,106827,Male,Loyal Customer,10,Personal Travel,Eco,1488,3,4,2,2,4,2,4,4,3,1,5,2,5,4,0,4.0,neutral or dissatisfied +19115,17387,Male,Loyal Customer,44,Business travel,Business,1659,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +19116,78156,Male,Loyal Customer,57,Business travel,Business,259,0,0,0,1,4,5,4,3,3,3,3,4,3,3,10,17.0,satisfied +19117,35733,Female,Loyal Customer,42,Personal Travel,Eco Plus,2586,3,2,3,4,3,5,4,3,2,2,4,4,3,4,40,60.0,neutral or dissatisfied +19118,41300,Female,Loyal Customer,34,Personal Travel,Business,1041,2,2,2,3,1,3,3,1,1,2,3,3,1,3,0,0.0,neutral or dissatisfied +19119,73147,Female,disloyal Customer,26,Business travel,Business,1068,5,5,5,1,3,5,3,3,4,4,5,4,5,3,17,22.0,satisfied +19120,117541,Male,disloyal Customer,20,Business travel,Eco,1020,2,2,2,2,5,2,1,5,5,4,4,4,5,5,26,21.0,satisfied +19121,8591,Female,Loyal Customer,50,Personal Travel,Eco,109,1,4,1,3,5,5,5,2,2,1,5,5,2,3,0,0.0,neutral or dissatisfied +19122,26313,Female,Loyal Customer,40,Personal Travel,Eco,2139,5,5,5,5,5,5,5,5,3,5,5,4,4,5,45,54.0,satisfied +19123,69351,Male,disloyal Customer,25,Business travel,Business,1089,0,0,0,4,2,0,2,2,5,3,4,3,5,2,0,0.0,satisfied +19124,102737,Female,Loyal Customer,37,Personal Travel,Eco,255,4,5,4,1,3,4,3,3,4,5,5,3,4,3,0,0.0,neutral or dissatisfied +19125,45395,Female,Loyal Customer,72,Business travel,Business,1437,4,5,4,5,2,4,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +19126,5494,Female,Loyal Customer,34,Business travel,Business,910,2,2,2,2,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +19127,34580,Female,Loyal Customer,43,Business travel,Eco,1598,2,2,2,2,3,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +19128,35630,Male,Loyal Customer,35,Business travel,Eco Plus,950,4,5,5,5,4,4,4,4,5,5,1,3,4,4,3,3.0,satisfied +19129,100055,Male,Loyal Customer,20,Personal Travel,Eco,289,3,3,3,3,4,3,4,4,2,1,4,3,4,4,29,19.0,neutral or dissatisfied +19130,24786,Female,Loyal Customer,58,Personal Travel,Eco,528,3,4,3,1,5,4,4,4,4,3,1,5,4,3,0,0.0,neutral or dissatisfied +19131,103355,Male,disloyal Customer,26,Business travel,Business,342,3,5,3,5,4,3,4,4,5,2,4,5,5,4,45,47.0,neutral or dissatisfied +19132,114717,Male,Loyal Customer,36,Business travel,Business,2567,1,1,1,1,2,5,5,3,3,3,3,5,3,4,12,4.0,satisfied +19133,4929,Male,disloyal Customer,27,Business travel,Business,268,0,0,0,2,2,0,2,2,3,4,5,5,4,2,0,21.0,satisfied +19134,73060,Female,disloyal Customer,25,Business travel,Eco Plus,1089,1,4,1,4,4,1,4,4,1,4,3,4,4,4,52,36.0,neutral or dissatisfied +19135,13788,Female,Loyal Customer,44,Personal Travel,Eco,925,3,4,3,2,2,5,5,4,4,3,4,4,4,4,16,1.0,neutral or dissatisfied +19136,129490,Male,Loyal Customer,47,Personal Travel,Eco,2611,3,4,3,3,1,3,1,1,1,5,4,2,4,1,1,6.0,neutral or dissatisfied +19137,97899,Female,Loyal Customer,23,Business travel,Business,391,4,4,4,4,4,4,4,4,3,2,3,2,3,4,27,34.0,neutral or dissatisfied +19138,107197,Female,Loyal Customer,7,Personal Travel,Eco,402,2,4,2,2,1,2,1,1,4,5,4,3,5,1,0,0.0,neutral or dissatisfied +19139,20533,Male,Loyal Customer,54,Business travel,Eco,633,4,4,4,4,4,4,4,4,4,2,4,2,2,4,3,0.0,satisfied +19140,11826,Female,Loyal Customer,47,Business travel,Business,2617,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,1.0,satisfied +19141,105660,Female,Loyal Customer,28,Business travel,Business,3917,3,3,3,3,4,4,4,4,4,3,5,5,4,4,0,0.0,satisfied +19142,22159,Female,Loyal Customer,28,Business travel,Business,773,1,1,1,1,3,4,4,1,5,4,5,4,3,4,169,163.0,satisfied +19143,6050,Female,Loyal Customer,29,Personal Travel,Eco,925,3,5,3,3,5,3,5,5,4,3,4,5,4,5,49,49.0,neutral or dissatisfied +19144,96614,Female,Loyal Customer,39,Business travel,Business,3517,2,2,2,2,4,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +19145,18727,Female,Loyal Customer,52,Business travel,Eco Plus,383,2,5,5,5,3,3,3,2,2,2,2,1,2,4,10,3.0,neutral or dissatisfied +19146,114654,Male,Loyal Customer,49,Business travel,Business,296,5,5,5,5,3,5,4,5,5,5,5,3,5,4,4,0.0,satisfied +19147,11161,Male,Loyal Customer,8,Personal Travel,Eco,316,2,5,2,5,5,2,5,5,5,5,5,4,5,5,0,0.0,neutral or dissatisfied +19148,1517,Female,Loyal Customer,24,Business travel,Business,3172,1,1,1,1,5,5,5,5,4,3,4,3,5,5,2,0.0,satisfied +19149,118065,Male,Loyal Customer,45,Personal Travel,Eco,1044,3,5,2,4,2,2,2,2,3,4,4,2,1,2,32,18.0,neutral or dissatisfied +19150,77880,Female,Loyal Customer,53,Business travel,Business,1512,2,2,2,2,4,2,1,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +19151,92686,Male,disloyal Customer,23,Business travel,Eco,507,4,5,4,2,3,4,2,3,4,3,4,3,4,3,0,0.0,satisfied +19152,4022,Female,disloyal Customer,23,Business travel,Business,483,5,0,5,5,4,5,4,4,5,5,5,3,5,4,0,0.0,satisfied +19153,106657,Female,Loyal Customer,41,Business travel,Business,1590,3,3,3,3,2,5,5,3,3,3,3,5,3,4,0,0.0,satisfied +19154,39830,Male,Loyal Customer,35,Business travel,Business,221,1,1,1,1,5,1,2,4,4,4,4,5,4,1,0,11.0,satisfied +19155,42411,Female,Loyal Customer,57,Business travel,Eco Plus,451,3,2,2,2,4,4,4,3,3,3,3,1,3,3,51,50.0,neutral or dissatisfied +19156,99387,Male,Loyal Customer,36,Business travel,Eco,337,2,4,4,4,2,2,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +19157,114003,Female,Loyal Customer,52,Personal Travel,Eco,1844,2,5,2,4,2,1,1,5,4,5,4,1,5,1,98,214.0,neutral or dissatisfied +19158,4421,Female,Loyal Customer,59,Business travel,Business,3413,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +19159,112180,Female,disloyal Customer,66,Personal Travel,Eco,895,2,4,2,2,1,2,2,1,3,2,4,4,5,1,32,23.0,neutral or dissatisfied +19160,98793,Male,Loyal Customer,29,Personal Travel,Eco,630,4,2,4,3,5,4,5,5,3,5,3,3,4,5,3,1.0,neutral or dissatisfied +19161,13512,Female,Loyal Customer,43,Business travel,Eco,106,4,4,4,4,4,5,2,4,4,4,4,2,4,5,0,0.0,satisfied +19162,128650,Female,disloyal Customer,28,Business travel,Business,2442,1,1,1,4,1,4,4,5,4,4,5,4,3,4,0,0.0,neutral or dissatisfied +19163,35176,Male,disloyal Customer,38,Business travel,Business,1097,4,4,4,4,1,4,1,1,1,3,1,5,4,1,17,20.0,satisfied +19164,57770,Female,disloyal Customer,28,Business travel,Eco,2704,2,2,2,4,2,4,4,2,4,4,3,4,1,4,1,5.0,neutral or dissatisfied +19165,36848,Female,Loyal Customer,62,Business travel,Eco Plus,369,1,2,2,2,1,1,1,1,3,4,3,1,3,1,155,163.0,neutral or dissatisfied +19166,104936,Female,Loyal Customer,44,Business travel,Business,1736,3,5,3,3,4,4,5,5,5,5,5,4,5,4,12,17.0,satisfied +19167,3888,Female,disloyal Customer,40,Business travel,Business,213,4,4,4,3,5,4,5,5,4,4,3,3,3,5,0,2.0,neutral or dissatisfied +19168,33722,Female,Loyal Customer,50,Personal Travel,Eco,899,2,3,2,3,5,4,3,1,1,2,1,3,1,2,0,0.0,neutral or dissatisfied +19169,119810,Male,disloyal Customer,27,Business travel,Business,912,1,1,1,1,3,1,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +19170,48290,Male,Loyal Customer,58,Business travel,Business,807,2,4,4,4,3,3,4,2,2,2,2,1,2,3,17,3.0,neutral or dissatisfied +19171,68868,Female,Loyal Customer,46,Business travel,Business,3149,1,1,1,1,2,5,4,5,5,5,5,4,5,3,74,73.0,satisfied +19172,40113,Male,disloyal Customer,32,Business travel,Eco,368,3,4,3,4,2,3,1,2,3,4,4,1,4,2,0,0.0,neutral or dissatisfied +19173,17581,Male,Loyal Customer,22,Personal Travel,Eco,1034,2,4,2,2,5,2,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +19174,56770,Male,Loyal Customer,26,Business travel,Eco Plus,937,0,5,0,4,3,0,3,3,3,3,4,3,3,3,0,3.0,satisfied +19175,60896,Male,Loyal Customer,13,Personal Travel,Eco,420,2,2,2,3,2,2,2,2,1,4,3,1,3,2,6,9.0,neutral or dissatisfied +19176,111654,Male,Loyal Customer,36,Personal Travel,Eco Plus,1558,4,5,4,3,1,4,1,1,4,4,4,5,4,1,26,32.0,neutral or dissatisfied +19177,101304,Female,Loyal Customer,24,Business travel,Business,763,3,3,3,3,4,4,4,4,3,4,5,5,4,4,6,0.0,satisfied +19178,51476,Female,disloyal Customer,47,Business travel,Business,451,4,3,3,4,2,4,2,2,4,4,4,5,5,2,20,8.0,neutral or dissatisfied +19179,20653,Male,Loyal Customer,54,Business travel,Business,2394,3,3,3,3,5,4,1,5,5,5,5,3,5,1,0,12.0,satisfied +19180,86567,Female,disloyal Customer,26,Business travel,Eco Plus,762,1,1,1,1,3,1,4,3,4,2,1,2,1,3,73,55.0,neutral or dissatisfied +19181,95802,Male,Loyal Customer,40,Business travel,Business,1050,3,3,3,3,4,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +19182,30107,Female,Loyal Customer,25,Personal Travel,Eco,204,3,2,3,3,2,3,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +19183,39560,Male,Loyal Customer,13,Business travel,Business,1786,5,5,1,5,2,2,2,2,4,1,2,2,5,2,0,0.0,satisfied +19184,37471,Female,disloyal Customer,31,Business travel,Eco,1056,2,2,2,4,2,2,2,2,3,4,3,5,2,2,0,0.0,neutral or dissatisfied +19185,1905,Female,Loyal Customer,56,Business travel,Business,383,1,1,1,1,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +19186,25433,Female,Loyal Customer,32,Business travel,Business,2560,1,1,1,1,5,5,5,5,5,2,5,2,4,5,28,32.0,satisfied +19187,113019,Female,Loyal Customer,60,Business travel,Business,2407,4,4,4,4,3,4,4,4,4,4,4,5,4,3,12,0.0,satisfied +19188,118207,Female,Loyal Customer,53,Personal Travel,Eco,1444,2,4,2,2,4,5,3,4,4,2,3,4,4,1,1,3.0,neutral or dissatisfied +19189,44,Male,Loyal Customer,51,Business travel,Business,2077,4,1,4,4,2,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +19190,82588,Male,Loyal Customer,36,Business travel,Business,3152,3,3,3,3,2,4,5,5,5,5,5,3,5,5,2,0.0,satisfied +19191,81397,Female,Loyal Customer,59,Personal Travel,Eco,748,2,5,2,3,3,5,5,3,3,2,3,4,3,5,0,0.0,neutral or dissatisfied +19192,60912,Male,Loyal Customer,34,Personal Travel,Eco,589,1,5,1,4,4,1,4,4,4,4,5,3,5,4,0,20.0,neutral or dissatisfied +19193,36246,Female,Loyal Customer,38,Business travel,Business,2953,1,1,2,1,4,5,1,3,3,4,3,5,3,2,0,26.0,satisfied +19194,127659,Male,Loyal Customer,8,Personal Travel,Business,2153,3,4,4,5,4,4,1,4,4,3,5,3,4,4,5,0.0,neutral or dissatisfied +19195,95713,Female,Loyal Customer,42,Business travel,Business,3698,4,1,1,1,5,4,4,4,4,4,4,4,4,1,1,4.0,neutral or dissatisfied +19196,66120,Female,Loyal Customer,43,Business travel,Business,583,5,5,5,5,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +19197,41553,Female,Loyal Customer,44,Business travel,Business,1464,2,3,5,3,2,4,4,2,2,2,2,2,2,2,4,15.0,neutral or dissatisfied +19198,108525,Male,Loyal Customer,50,Personal Travel,Business,649,1,2,2,4,1,4,4,4,4,2,4,2,4,2,0,0.0,neutral or dissatisfied +19199,44262,Female,Loyal Customer,39,Personal Travel,Eco,235,3,4,3,3,3,3,4,3,3,5,5,4,5,3,42,63.0,neutral or dissatisfied +19200,70080,Male,Loyal Customer,49,Business travel,Business,460,2,2,2,2,4,5,4,2,2,2,2,5,2,5,0,0.0,satisfied +19201,76248,Female,Loyal Customer,46,Personal Travel,Eco,1175,4,1,4,2,3,3,3,1,1,4,1,3,1,4,0,0.0,neutral or dissatisfied +19202,31344,Female,disloyal Customer,24,Business travel,Eco,1069,2,2,2,2,3,2,5,3,4,3,4,1,5,3,2,0.0,satisfied +19203,104458,Female,disloyal Customer,25,Business travel,Business,1123,5,3,5,2,1,5,1,1,4,4,5,3,4,1,1,0.0,satisfied +19204,114946,Male,Loyal Customer,59,Business travel,Business,3846,3,3,3,3,4,4,5,4,4,4,4,5,4,5,23,17.0,satisfied +19205,60993,Female,Loyal Customer,33,Personal Travel,Business,649,3,2,3,4,2,3,4,2,2,3,2,1,2,3,13,22.0,neutral or dissatisfied +19206,13353,Female,Loyal Customer,20,Business travel,Business,748,4,1,1,1,4,3,4,4,3,4,3,2,4,4,107,88.0,neutral or dissatisfied +19207,87043,Female,Loyal Customer,59,Business travel,Business,594,2,1,2,2,4,4,5,3,3,3,3,4,3,3,0,17.0,satisfied +19208,37242,Male,Loyal Customer,16,Personal Travel,Business,1076,5,3,5,4,5,5,5,5,1,3,4,2,3,5,0,0.0,satisfied +19209,9572,Female,disloyal Customer,22,Business travel,Eco,288,2,2,2,4,4,2,4,4,2,3,4,4,4,4,63,65.0,neutral or dissatisfied +19210,87455,Female,Loyal Customer,45,Business travel,Business,2651,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +19211,124005,Male,Loyal Customer,41,Business travel,Business,184,1,1,1,1,1,3,3,4,4,4,1,4,4,3,0,0.0,neutral or dissatisfied +19212,22990,Male,Loyal Customer,32,Personal Travel,Eco,1041,3,4,3,1,4,3,4,4,5,2,5,4,5,4,2,0.0,neutral or dissatisfied +19213,61808,Male,Loyal Customer,42,Personal Travel,Eco,1379,2,5,2,4,1,2,1,1,3,3,4,4,4,1,26,24.0,neutral or dissatisfied +19214,112907,Female,Loyal Customer,41,Business travel,Business,2193,2,2,2,2,3,3,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +19215,62424,Female,disloyal Customer,25,Business travel,Business,1289,4,5,4,4,4,4,1,4,4,5,4,3,5,4,1,0.0,satisfied +19216,122937,Female,Loyal Customer,26,Business travel,Business,3691,4,5,4,4,4,4,4,4,5,2,4,4,4,4,20,25.0,satisfied +19217,56687,Male,Loyal Customer,48,Personal Travel,Eco,1023,3,5,3,1,1,3,1,1,3,5,3,5,4,1,0,0.0,neutral or dissatisfied +19218,26966,Female,Loyal Customer,42,Business travel,Business,2889,4,4,4,4,3,1,3,5,5,5,5,1,5,1,0,0.0,satisfied +19219,107816,Male,disloyal Customer,41,Business travel,Business,349,3,3,3,3,5,3,5,5,4,1,2,2,2,5,14,13.0,neutral or dissatisfied +19220,33010,Female,Loyal Customer,45,Personal Travel,Eco,101,5,5,0,5,2,2,3,1,1,0,1,2,1,4,0,4.0,satisfied +19221,108578,Male,Loyal Customer,28,Business travel,Business,2684,4,4,4,4,4,4,4,4,5,5,5,4,3,4,148,175.0,satisfied +19222,14259,Male,Loyal Customer,16,Personal Travel,Business,429,2,3,2,1,3,2,2,3,4,5,5,2,5,3,0,1.0,neutral or dissatisfied +19223,97193,Male,Loyal Customer,14,Personal Travel,Eco,1390,2,4,2,1,2,3,4,4,5,3,4,4,3,4,198,187.0,neutral or dissatisfied +19224,48398,Male,Loyal Customer,11,Personal Travel,Eco,522,3,5,3,5,3,3,1,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +19225,40459,Female,disloyal Customer,37,Business travel,Eco,188,1,0,1,3,4,1,4,4,4,4,3,2,3,4,32,18.0,neutral or dissatisfied +19226,46993,Male,Loyal Customer,55,Business travel,Eco Plus,737,4,2,2,2,4,4,4,4,3,1,4,1,1,4,11,17.0,satisfied +19227,6181,Female,Loyal Customer,13,Personal Travel,Eco,409,4,5,4,3,1,4,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +19228,726,Male,Loyal Customer,56,Business travel,Business,89,3,5,3,5,2,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +19229,38972,Male,Loyal Customer,36,Business travel,Eco,230,3,2,2,2,3,3,3,3,3,3,3,5,4,3,0,1.0,satisfied +19230,46034,Male,Loyal Customer,50,Business travel,Business,2797,4,4,4,4,2,2,5,5,5,5,5,3,5,1,42,47.0,satisfied +19231,34160,Male,disloyal Customer,25,Business travel,Eco,1129,1,0,0,1,5,0,5,5,3,2,5,4,3,5,0,0.0,neutral or dissatisfied +19232,10400,Female,Loyal Customer,49,Business travel,Business,312,1,1,1,1,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +19233,53919,Male,Loyal Customer,60,Business travel,Eco Plus,140,5,3,3,3,5,5,5,5,5,3,4,1,3,5,0,0.0,satisfied +19234,51264,Male,disloyal Customer,56,Business travel,Eco Plus,89,3,3,3,2,5,3,2,5,5,5,3,2,1,5,5,6.0,neutral or dissatisfied +19235,56082,Male,Loyal Customer,33,Personal Travel,Eco,2475,2,2,2,4,2,5,5,3,2,3,4,5,4,5,0,0.0,neutral or dissatisfied +19236,104236,Male,Loyal Customer,33,Business travel,Business,1276,2,2,2,2,4,4,4,4,5,3,5,3,4,4,9,1.0,satisfied +19237,105988,Male,Loyal Customer,38,Business travel,Eco,912,4,2,2,2,3,4,4,3,2,2,2,4,3,4,165,152.0,neutral or dissatisfied +19238,29115,Female,Loyal Customer,28,Personal Travel,Eco,978,2,5,2,4,2,2,4,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +19239,88243,Male,disloyal Customer,26,Business travel,Business,646,5,5,5,4,4,5,4,4,4,5,5,5,5,4,0,0.0,satisfied +19240,77406,Male,Loyal Customer,68,Personal Travel,Eco,532,1,4,1,3,5,1,5,5,3,5,4,5,4,5,35,22.0,neutral or dissatisfied +19241,7192,Male,Loyal Customer,59,Business travel,Business,1980,4,4,4,4,3,5,5,4,4,4,4,4,4,5,14,9.0,satisfied +19242,66966,Female,Loyal Customer,55,Business travel,Business,985,2,2,2,2,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +19243,119152,Male,Loyal Customer,51,Business travel,Business,3374,2,2,2,2,3,4,4,5,5,5,5,4,5,3,0,11.0,satisfied +19244,114323,Female,Loyal Customer,48,Personal Travel,Eco,853,5,5,5,4,4,4,5,4,4,5,1,4,4,4,7,0.0,satisfied +19245,121024,Male,Loyal Customer,39,Personal Travel,Eco,992,4,4,4,3,2,4,2,2,4,4,4,3,4,2,0,14.0,neutral or dissatisfied +19246,94338,Female,Loyal Customer,22,Business travel,Business,192,5,5,5,5,5,5,4,5,3,5,5,3,4,5,0,0.0,satisfied +19247,67117,Female,Loyal Customer,19,Business travel,Eco,1121,2,2,2,2,2,2,3,2,2,4,3,1,3,2,3,0.0,neutral or dissatisfied +19248,88398,Male,Loyal Customer,47,Business travel,Business,1734,4,4,4,4,2,4,4,5,5,5,5,4,5,3,5,0.0,satisfied +19249,73149,Male,Loyal Customer,33,Business travel,Eco Plus,1068,2,3,5,3,2,2,2,2,3,2,4,4,3,2,86,92.0,neutral or dissatisfied +19250,96326,Male,disloyal Customer,22,Business travel,Eco,359,3,5,3,3,3,3,4,3,4,5,4,3,5,3,0,1.0,neutral or dissatisfied +19251,85722,Male,Loyal Customer,56,Business travel,Business,3959,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +19252,77798,Female,Loyal Customer,37,Personal Travel,Eco,813,3,0,3,3,2,3,2,2,5,4,3,3,5,2,16,5.0,neutral or dissatisfied +19253,117593,Female,Loyal Customer,36,Business travel,Business,2547,1,5,5,5,5,3,4,1,1,1,1,3,1,2,43,42.0,neutral or dissatisfied +19254,102982,Female,Loyal Customer,46,Business travel,Business,3538,5,5,2,5,5,4,5,5,5,4,5,3,5,4,0,0.0,satisfied +19255,117920,Female,disloyal Customer,40,Business travel,Business,365,2,2,2,4,1,2,1,1,3,3,3,1,3,1,27,21.0,neutral or dissatisfied +19256,58386,Female,Loyal Customer,52,Business travel,Business,2945,2,2,2,2,3,4,5,4,4,4,4,3,4,3,55,55.0,satisfied +19257,2976,Female,Loyal Customer,44,Business travel,Business,462,4,4,4,4,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +19258,47784,Female,disloyal Customer,24,Business travel,Eco,451,3,0,3,2,5,3,5,5,3,5,4,2,1,5,0,0.0,neutral or dissatisfied +19259,105720,Female,disloyal Customer,17,Business travel,Eco,842,4,4,4,1,4,4,4,4,5,5,4,4,4,4,0,0.0,satisfied +19260,103009,Male,Loyal Customer,45,Business travel,Business,546,4,4,4,4,3,4,4,2,2,2,2,3,2,4,7,0.0,satisfied +19261,8466,Female,Loyal Customer,11,Personal Travel,Eco,1379,2,1,2,2,4,2,5,4,1,5,3,2,3,4,6,8.0,neutral or dissatisfied +19262,31902,Male,Loyal Customer,33,Business travel,Business,3918,4,4,4,4,5,5,4,5,5,2,5,3,4,5,0,0.0,satisfied +19263,79024,Male,Loyal Customer,60,Business travel,Business,226,4,4,5,4,5,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +19264,96156,Female,Loyal Customer,54,Business travel,Business,2794,1,1,1,1,4,5,5,4,4,4,4,4,4,5,0,1.0,satisfied +19265,82293,Male,Loyal Customer,32,Personal Travel,Eco Plus,1481,1,4,1,4,4,1,4,4,5,4,4,3,4,4,0,0.0,neutral or dissatisfied +19266,44864,Male,Loyal Customer,44,Business travel,Business,3221,2,1,1,1,5,3,3,2,2,2,2,2,2,3,0,6.0,neutral or dissatisfied +19267,56197,Male,Loyal Customer,62,Personal Travel,Eco,1400,2,3,2,3,3,2,3,3,4,5,4,2,4,3,0,0.0,neutral or dissatisfied +19268,110193,Male,Loyal Customer,48,Personal Travel,Eco,1056,1,1,1,3,3,1,2,3,2,4,3,4,2,3,5,0.0,neutral or dissatisfied +19269,63332,Male,disloyal Customer,37,Business travel,Eco,337,4,1,5,3,3,5,3,3,2,3,4,4,4,3,0,26.0,neutral or dissatisfied +19270,4480,Female,Loyal Customer,40,Business travel,Business,1623,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,13.0,satisfied +19271,29979,Female,disloyal Customer,28,Business travel,Eco,725,2,2,2,1,2,2,4,2,2,1,1,5,1,2,6,2.0,neutral or dissatisfied +19272,108954,Female,Loyal Customer,60,Business travel,Business,655,1,1,1,1,5,4,4,5,5,5,5,3,5,5,15,0.0,satisfied +19273,83461,Female,disloyal Customer,24,Business travel,Business,946,4,0,4,1,1,4,1,1,4,3,4,4,4,1,2,0.0,satisfied +19274,116317,Male,Loyal Customer,37,Personal Travel,Eco,362,2,5,2,5,2,2,2,2,3,5,4,4,4,2,2,2.0,neutral or dissatisfied +19275,36085,Female,Loyal Customer,67,Personal Travel,Eco,474,4,5,4,3,2,3,3,3,3,4,3,5,3,5,0,0.0,neutral or dissatisfied +19276,115385,Female,Loyal Customer,45,Business travel,Business,337,4,4,4,4,5,5,4,5,5,5,5,5,5,4,13,5.0,satisfied +19277,68094,Female,Loyal Customer,48,Business travel,Business,2948,3,2,2,2,4,4,3,3,3,3,3,4,3,2,31,38.0,neutral or dissatisfied +19278,55999,Female,Loyal Customer,52,Business travel,Business,2475,1,1,1,1,2,5,5,4,4,4,4,3,4,3,3,0.0,satisfied +19279,99483,Male,Loyal Customer,33,Business travel,Business,2872,2,5,5,5,2,2,2,2,2,1,4,2,4,2,16,12.0,neutral or dissatisfied +19280,84732,Male,Loyal Customer,56,Business travel,Business,2930,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +19281,105906,Male,disloyal Customer,23,Business travel,Business,283,4,3,4,4,4,4,5,4,4,5,4,1,4,4,33,17.0,neutral or dissatisfied +19282,25727,Male,Loyal Customer,14,Personal Travel,Eco,528,3,5,3,4,4,3,4,4,1,5,5,1,1,4,0,0.0,neutral or dissatisfied +19283,114586,Male,Loyal Customer,52,Business travel,Business,417,4,4,4,4,5,5,5,4,4,5,4,3,4,4,62,58.0,satisfied +19284,109623,Male,disloyal Customer,29,Business travel,Business,802,2,2,2,1,4,2,1,4,4,4,4,3,4,4,8,0.0,neutral or dissatisfied +19285,50405,Female,disloyal Customer,45,Business travel,Eco,89,1,0,0,2,2,0,3,2,5,5,5,3,2,2,0,31.0,neutral or dissatisfied +19286,128154,Female,Loyal Customer,59,Business travel,Business,1788,1,1,1,1,4,3,5,5,5,4,5,5,5,5,0,0.0,satisfied +19287,16506,Male,Loyal Customer,32,Personal Travel,Eco,195,2,4,2,4,4,2,4,4,1,2,2,1,3,4,1,0.0,neutral or dissatisfied +19288,115215,Female,Loyal Customer,24,Business travel,Business,362,3,2,2,2,3,2,3,3,2,4,4,3,3,3,34,26.0,neutral or dissatisfied +19289,10786,Female,Loyal Customer,25,Business travel,Business,224,2,2,2,2,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +19290,38971,Female,Loyal Customer,52,Business travel,Eco,406,2,2,2,2,4,1,3,2,2,2,2,1,2,2,0,42.0,satisfied +19291,109615,Male,Loyal Customer,60,Business travel,Business,930,1,1,1,1,2,4,5,5,5,5,5,3,5,5,12,12.0,satisfied +19292,62928,Male,Loyal Customer,49,Business travel,Business,948,3,2,2,2,1,3,4,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +19293,4530,Female,Loyal Customer,23,Business travel,Business,2559,1,1,1,1,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +19294,87356,Female,Loyal Customer,53,Business travel,Business,3944,4,4,1,4,3,5,5,4,4,4,4,3,4,3,1,2.0,satisfied +19295,42602,Female,disloyal Customer,39,Business travel,Business,866,2,2,2,1,4,2,4,4,3,2,4,3,2,4,0,0.0,neutral or dissatisfied +19296,67001,Female,Loyal Customer,53,Business travel,Business,985,4,4,4,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +19297,109400,Female,disloyal Customer,25,Business travel,Business,1189,5,5,5,4,2,5,2,2,3,4,5,4,4,2,0,0.0,satisfied +19298,95092,Female,Loyal Customer,19,Personal Travel,Eco,189,2,5,2,4,5,2,5,5,4,2,4,4,5,5,8,16.0,neutral or dissatisfied +19299,10155,Female,Loyal Customer,60,Business travel,Business,3552,3,3,3,3,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +19300,52640,Female,Loyal Customer,16,Personal Travel,Eco,119,2,5,2,2,3,2,3,3,4,3,4,1,2,3,0,0.0,neutral or dissatisfied +19301,15604,Female,disloyal Customer,36,Business travel,Eco,229,4,2,4,3,4,4,4,4,3,4,4,2,4,4,74,66.0,neutral or dissatisfied +19302,55021,Female,Loyal Customer,60,Business travel,Business,1379,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +19303,23744,Female,Loyal Customer,41,Personal Travel,Business,1083,2,5,2,5,5,4,3,5,5,2,5,1,5,4,0,10.0,neutral or dissatisfied +19304,123465,Female,Loyal Customer,34,Business travel,Business,2077,2,2,2,2,2,5,4,4,4,4,4,3,4,5,6,0.0,satisfied +19305,44948,Male,Loyal Customer,41,Business travel,Business,397,3,2,1,2,1,2,2,3,3,3,3,1,3,2,38,42.0,neutral or dissatisfied +19306,31148,Male,Loyal Customer,36,Business travel,Business,3057,3,1,1,1,3,2,1,3,3,3,3,1,3,2,22,14.0,neutral or dissatisfied +19307,93289,Female,Loyal Customer,65,Personal Travel,Eco,806,3,4,3,2,5,2,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +19308,54745,Male,Loyal Customer,56,Personal Travel,Eco,854,2,4,2,3,5,2,5,5,5,2,5,3,5,5,0,0.0,neutral or dissatisfied +19309,818,Female,Loyal Customer,37,Business travel,Business,3853,3,3,3,3,1,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +19310,95694,Male,Loyal Customer,41,Business travel,Business,3261,0,4,0,1,4,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +19311,58023,Female,Loyal Customer,9,Personal Travel,Eco,1721,4,4,4,5,3,4,3,3,5,5,3,5,4,3,56,52.0,satisfied +19312,45245,Female,Loyal Customer,36,Personal Travel,Eco,1013,4,4,4,3,2,4,3,2,3,4,3,2,4,2,0,0.0,neutral or dissatisfied +19313,59668,Female,Loyal Customer,7,Personal Travel,Eco,854,2,5,2,1,1,2,1,1,4,5,4,5,5,1,3,0.0,neutral or dissatisfied +19314,123875,Male,Loyal Customer,48,Business travel,Business,2440,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,1.0,satisfied +19315,51291,Female,disloyal Customer,30,Business travel,Eco Plus,110,2,3,3,5,5,3,5,5,1,4,3,4,1,5,30,30.0,neutral or dissatisfied +19316,21302,Female,Loyal Customer,65,Personal Travel,Eco,620,3,5,3,3,4,4,5,3,3,3,3,3,3,5,0,0.0,neutral or dissatisfied +19317,10180,Male,Loyal Customer,45,Business travel,Business,2536,5,5,5,5,4,5,5,1,1,2,1,5,1,4,0,0.0,satisfied +19318,8371,Male,Loyal Customer,46,Business travel,Business,701,3,3,3,3,3,3,4,3,3,2,3,4,3,4,0,7.0,neutral or dissatisfied +19319,27070,Female,Loyal Customer,66,Personal Travel,Eco,1399,2,3,2,4,4,5,4,4,4,2,4,1,4,3,14,2.0,neutral or dissatisfied +19320,125061,Female,Loyal Customer,42,Business travel,Business,90,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,4.0,satisfied +19321,59180,Female,Loyal Customer,48,Business travel,Business,1440,1,1,1,1,4,5,4,2,2,2,2,3,2,3,1,0.0,satisfied +19322,113701,Male,Loyal Customer,14,Personal Travel,Eco,223,4,2,0,4,4,0,2,4,2,2,4,2,4,4,0,0.0,neutral or dissatisfied +19323,99661,Female,Loyal Customer,23,Personal Travel,Eco,920,5,4,5,3,5,5,5,5,4,3,5,4,4,5,7,2.0,satisfied +19324,48088,Male,Loyal Customer,47,Business travel,Eco,192,3,2,2,2,3,3,3,3,4,2,5,4,3,3,0,0.0,satisfied +19325,53951,Male,Loyal Customer,52,Business travel,Business,1325,5,5,5,5,2,4,4,5,5,4,5,1,5,4,0,0.0,neutral or dissatisfied +19326,118546,Female,Loyal Customer,45,Business travel,Business,3970,2,4,2,2,2,4,5,4,4,4,4,3,4,5,4,0.0,satisfied +19327,63453,Male,Loyal Customer,47,Business travel,Business,447,1,1,1,1,4,4,5,5,5,5,5,4,5,5,40,29.0,satisfied +19328,121460,Female,Loyal Customer,9,Personal Travel,Eco,257,5,4,5,3,3,5,2,3,4,2,3,1,3,3,0,0.0,satisfied +19329,27331,Female,Loyal Customer,40,Business travel,Business,679,3,3,3,3,5,3,1,5,5,5,5,1,5,5,0,0.0,satisfied +19330,11992,Female,Loyal Customer,29,Personal Travel,Eco,643,2,5,2,1,5,2,5,5,4,2,5,5,4,5,19,8.0,neutral or dissatisfied +19331,762,Female,Loyal Customer,37,Business travel,Business,3638,3,3,3,3,2,5,4,5,5,5,4,5,5,4,0,0.0,satisfied +19332,59662,Female,Loyal Customer,45,Personal Travel,Eco,787,1,5,1,1,4,5,4,1,1,1,5,5,1,4,0,0.0,neutral or dissatisfied +19333,54197,Male,Loyal Customer,66,Personal Travel,Eco,1400,2,5,2,1,2,2,2,2,3,2,5,5,4,2,0,0.0,neutral or dissatisfied +19334,104666,Male,disloyal Customer,36,Business travel,Eco,241,2,0,2,2,4,2,2,4,1,1,2,5,5,4,9,4.0,neutral or dissatisfied +19335,62316,Female,disloyal Customer,43,Business travel,Eco,414,3,4,3,3,2,3,2,2,2,1,3,3,3,2,29,19.0,neutral or dissatisfied +19336,53193,Female,Loyal Customer,26,Business travel,Business,2509,1,1,1,1,4,4,4,2,3,1,4,4,2,4,412,410.0,satisfied +19337,38699,Male,disloyal Customer,23,Business travel,Eco,953,1,2,2,2,1,2,1,1,2,3,4,5,5,1,0,0.0,neutral or dissatisfied +19338,45743,Female,disloyal Customer,25,Business travel,Business,391,4,2,4,3,5,4,5,5,3,5,3,4,4,5,10,7.0,neutral or dissatisfied +19339,89941,Female,Loyal Customer,7,Personal Travel,Eco,1310,3,3,3,3,2,3,2,2,1,3,4,2,4,2,0,0.0,neutral or dissatisfied +19340,88245,Female,Loyal Customer,57,Business travel,Business,270,4,4,4,4,4,4,4,4,4,4,4,3,4,5,4,2.0,satisfied +19341,86037,Male,Loyal Customer,67,Personal Travel,Eco,528,2,4,2,3,5,2,5,5,3,2,4,5,5,5,7,4.0,neutral or dissatisfied +19342,91369,Male,Loyal Customer,70,Personal Travel,Eco Plus,270,1,4,1,3,5,1,5,5,3,1,3,4,3,5,0,0.0,neutral or dissatisfied +19343,58506,Male,Loyal Customer,34,Business travel,Business,3642,4,5,5,5,2,4,3,4,4,4,4,1,4,2,13,18.0,neutral or dissatisfied +19344,36022,Male,Loyal Customer,54,Business travel,Business,474,3,3,3,3,3,5,4,4,4,4,4,1,4,2,0,0.0,satisfied +19345,79079,Male,Loyal Customer,23,Personal Travel,Eco,356,3,4,3,3,3,3,3,3,4,3,5,4,5,3,5,1.0,neutral or dissatisfied +19346,55346,Male,disloyal Customer,24,Business travel,Business,594,5,4,5,4,3,5,3,3,5,3,4,4,4,3,1,0.0,satisfied +19347,29275,Male,Loyal Customer,38,Business travel,Eco,873,2,5,5,5,2,2,2,2,3,5,4,4,3,2,0,0.0,neutral or dissatisfied +19348,121524,Male,disloyal Customer,24,Business travel,Business,912,4,3,4,3,5,4,5,5,3,2,5,4,5,5,3,33.0,satisfied +19349,44719,Female,Loyal Customer,66,Personal Travel,Eco,67,2,4,0,1,2,4,4,3,3,0,2,3,3,4,10,10.0,neutral or dissatisfied +19350,83526,Female,Loyal Customer,36,Personal Travel,Eco,946,2,1,1,2,1,1,1,1,3,4,3,4,2,1,0,0.0,neutral or dissatisfied +19351,123655,Female,Loyal Customer,43,Business travel,Business,2404,0,5,0,1,3,5,5,5,5,1,1,3,5,4,4,0.0,satisfied +19352,109952,Female,Loyal Customer,24,Personal Travel,Eco,1165,2,4,2,4,2,2,2,2,5,2,4,3,4,2,0,0.0,neutral or dissatisfied +19353,105119,Female,Loyal Customer,46,Business travel,Eco,220,1,2,2,2,5,2,2,1,1,1,1,2,1,1,32,24.0,neutral or dissatisfied +19354,88561,Female,Loyal Customer,26,Personal Travel,Eco,581,3,4,3,3,5,3,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +19355,6127,Male,Loyal Customer,58,Business travel,Business,491,2,2,5,2,2,4,5,5,5,5,5,4,5,5,21,8.0,satisfied +19356,57447,Male,Loyal Customer,44,Business travel,Business,3705,1,1,3,1,4,4,5,4,4,4,4,5,4,4,14,14.0,satisfied +19357,66193,Female,Loyal Customer,58,Business travel,Business,1646,2,5,5,5,5,3,3,2,2,2,2,3,2,4,45,33.0,neutral or dissatisfied +19358,14996,Female,Loyal Customer,23,Business travel,Eco,1201,0,5,0,4,3,0,4,3,2,4,2,3,2,3,0,0.0,satisfied +19359,18205,Female,Loyal Customer,53,Business travel,Business,2450,1,1,1,1,4,2,3,4,4,4,4,4,4,5,2,43.0,satisfied +19360,43641,Female,Loyal Customer,27,Business travel,Business,1097,5,5,4,5,2,3,2,2,2,3,3,3,1,2,0,3.0,satisfied +19361,86833,Male,disloyal Customer,44,Business travel,Eco,484,5,2,4,3,3,4,5,3,3,2,2,2,3,3,41,44.0,satisfied +19362,81283,Male,Loyal Customer,35,Personal Travel,Eco,1020,3,1,3,2,4,3,4,4,3,1,2,2,3,4,0,15.0,neutral or dissatisfied +19363,26403,Male,Loyal Customer,24,Personal Travel,Eco,957,4,5,4,4,4,4,4,4,5,3,5,3,4,4,56,43.0,neutral or dissatisfied +19364,15191,Male,disloyal Customer,26,Business travel,Eco,500,2,2,2,4,5,2,5,5,4,1,4,1,3,5,0,113.0,neutral or dissatisfied +19365,7485,Male,Loyal Customer,52,Business travel,Business,925,5,5,5,5,3,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +19366,55368,Female,disloyal Customer,22,Business travel,Business,678,5,3,5,4,2,5,2,2,3,2,5,5,5,2,0,27.0,satisfied +19367,66773,Female,Loyal Customer,31,Business travel,Business,2324,1,1,1,1,3,3,3,3,4,3,4,4,5,3,4,0.0,satisfied +19368,65375,Male,Loyal Customer,56,Business travel,Business,432,1,1,1,1,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +19369,61759,Male,Loyal Customer,33,Personal Travel,Eco,1303,3,5,3,3,3,3,3,3,3,5,4,5,5,3,0,14.0,neutral or dissatisfied +19370,32500,Male,Loyal Customer,44,Business travel,Eco,163,3,2,5,5,3,3,3,3,3,3,3,4,3,3,0,4.0,neutral or dissatisfied +19371,128069,Female,Loyal Customer,52,Business travel,Business,2860,3,3,3,3,4,4,4,5,2,4,5,4,5,4,0,47.0,satisfied +19372,51498,Female,Loyal Customer,21,Personal Travel,Business,370,2,3,5,4,5,5,5,5,3,2,5,2,4,5,0,0.0,neutral or dissatisfied +19373,4493,Male,Loyal Customer,42,Business travel,Business,3067,4,4,4,4,2,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +19374,114058,Female,disloyal Customer,50,Business travel,Business,1947,1,1,1,2,3,1,3,3,4,5,4,3,5,3,4,13.0,neutral or dissatisfied +19375,62461,Female,Loyal Customer,28,Personal Travel,Business,1846,3,3,3,4,1,3,1,1,1,2,3,3,4,1,2,0.0,neutral or dissatisfied +19376,50006,Female,Loyal Customer,59,Business travel,Eco,86,3,4,4,4,3,2,3,3,3,3,3,1,3,4,36,30.0,neutral or dissatisfied +19377,24719,Male,Loyal Customer,25,Personal Travel,Eco,549,4,5,5,3,2,5,2,2,2,1,4,4,4,2,0,0.0,neutral or dissatisfied +19378,73650,Female,Loyal Customer,75,Business travel,Business,1664,2,2,2,2,5,3,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +19379,16554,Male,disloyal Customer,24,Business travel,Eco,1092,3,3,3,1,3,3,3,3,4,4,3,2,1,3,0,0.0,satisfied +19380,121637,Female,disloyal Customer,21,Business travel,Eco,912,2,2,2,5,2,2,2,2,5,5,5,3,4,2,0,0.0,neutral or dissatisfied +19381,58902,Male,disloyal Customer,36,Business travel,Eco,488,1,1,1,3,1,1,4,1,3,4,3,4,3,1,1,0.0,neutral or dissatisfied +19382,13260,Female,disloyal Customer,22,Business travel,Eco,657,2,4,2,3,2,2,2,2,3,4,4,2,3,2,0,0.0,neutral or dissatisfied +19383,113353,Female,Loyal Customer,40,Business travel,Business,2401,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +19384,61496,Male,Loyal Customer,41,Business travel,Business,2253,1,5,2,5,2,3,3,1,1,1,1,4,1,2,8,0.0,neutral or dissatisfied +19385,7855,Male,Loyal Customer,15,Personal Travel,Eco,1005,4,3,4,3,4,3,3,2,4,4,1,3,3,3,392,401.0,neutral or dissatisfied +19386,76058,Male,Loyal Customer,47,Business travel,Business,669,1,2,2,2,5,4,4,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +19387,50732,Male,Loyal Customer,19,Personal Travel,Eco,190,1,4,1,5,3,1,3,3,5,4,5,5,4,3,36,35.0,neutral or dissatisfied +19388,90498,Female,Loyal Customer,56,Business travel,Business,646,2,2,2,2,5,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +19389,110053,Female,Loyal Customer,38,Personal Travel,Eco,2039,3,4,3,3,1,3,2,1,3,3,5,5,5,1,11,13.0,neutral or dissatisfied +19390,52595,Female,Loyal Customer,35,Business travel,Business,119,2,3,3,3,2,2,2,3,3,2,2,1,3,2,0,13.0,neutral or dissatisfied +19391,71821,Female,disloyal Customer,21,Business travel,Eco,760,5,5,5,3,3,5,1,3,4,2,4,4,5,3,0,0.0,satisfied +19392,39106,Female,Loyal Customer,43,Business travel,Business,2062,1,1,4,1,4,5,1,4,4,4,3,3,4,5,0,0.0,satisfied +19393,40884,Female,Loyal Customer,57,Personal Travel,Eco,584,3,4,3,5,2,5,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +19394,32196,Male,Loyal Customer,44,Business travel,Business,3573,2,2,2,2,1,2,1,4,4,4,5,3,4,1,4,13.0,satisfied +19395,29116,Female,Loyal Customer,13,Personal Travel,Eco,679,3,5,3,2,3,3,3,3,5,4,5,5,4,3,0,0.0,neutral or dissatisfied +19396,61838,Female,disloyal Customer,37,Business travel,Business,1379,3,3,3,3,1,3,1,1,3,5,5,3,4,1,0,4.0,neutral or dissatisfied +19397,110883,Male,Loyal Customer,48,Business travel,Business,404,5,5,5,5,5,4,5,5,5,5,5,3,5,5,8,7.0,satisfied +19398,76777,Female,Loyal Customer,22,Business travel,Business,2768,2,3,1,3,2,3,2,2,3,3,4,2,4,2,0,0.0,neutral or dissatisfied +19399,13231,Male,Loyal Customer,24,Business travel,Business,771,2,3,3,3,2,2,2,2,2,2,3,3,4,2,0,0.0,neutral or dissatisfied +19400,70524,Female,Loyal Customer,49,Business travel,Business,1258,3,3,3,3,3,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +19401,88007,Female,Loyal Customer,45,Business travel,Business,270,2,2,2,2,2,4,4,5,5,5,5,4,5,4,5,1.0,satisfied +19402,90854,Male,Loyal Customer,53,Business travel,Eco,646,3,3,3,3,2,3,2,2,3,1,4,4,4,2,0,3.0,neutral or dissatisfied +19403,39993,Male,Loyal Customer,54,Business travel,Eco,508,3,5,5,5,3,3,3,3,2,1,2,3,2,3,9,17.0,neutral or dissatisfied +19404,59900,Female,Loyal Customer,43,Business travel,Business,1023,4,4,4,4,4,5,5,3,3,3,3,3,3,4,0,0.0,satisfied +19405,88139,Female,disloyal Customer,38,Business travel,Business,442,5,0,0,3,4,0,4,4,4,3,5,5,5,4,8,3.0,satisfied +19406,27232,Male,disloyal Customer,9,Business travel,Eco,1024,3,3,3,3,3,3,3,3,5,4,2,5,4,3,0,0.0,satisfied +19407,24636,Male,Loyal Customer,52,Personal Travel,Eco,666,2,1,2,3,5,2,5,5,1,2,4,2,3,5,2,0.0,neutral or dissatisfied +19408,53674,Female,Loyal Customer,39,Business travel,Business,2928,1,1,1,1,5,1,2,4,4,4,4,3,4,5,17,0.0,satisfied +19409,4994,Female,Loyal Customer,27,Business travel,Business,3450,3,4,4,4,3,3,3,3,1,3,4,4,4,3,0,0.0,neutral or dissatisfied +19410,90889,Male,disloyal Customer,27,Business travel,Business,270,2,2,2,4,3,2,3,3,1,5,3,4,3,3,41,51.0,neutral or dissatisfied +19411,102685,Female,Loyal Customer,64,Business travel,Eco,255,1,5,5,5,5,4,4,1,1,1,1,3,1,3,13,40.0,neutral or dissatisfied +19412,97782,Female,disloyal Customer,21,Business travel,Eco,471,3,0,3,4,2,3,2,2,4,3,4,5,4,2,112,116.0,neutral or dissatisfied +19413,107474,Female,Loyal Customer,29,Business travel,Business,711,5,5,5,5,3,4,3,3,5,2,4,3,4,3,0,0.0,satisfied +19414,4658,Male,Loyal Customer,52,Business travel,Business,3847,3,1,5,1,4,3,2,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +19415,58656,Male,Loyal Customer,13,Personal Travel,Eco,867,3,4,3,3,3,5,2,3,3,5,5,2,3,2,157,142.0,neutral or dissatisfied +19416,57111,Female,Loyal Customer,45,Business travel,Eco,1222,2,2,4,4,1,4,3,3,3,2,3,1,3,2,9,0.0,neutral or dissatisfied +19417,101560,Female,Loyal Customer,53,Business travel,Business,2658,0,1,1,4,5,4,4,3,3,2,2,4,3,5,29,26.0,satisfied +19418,99938,Male,Loyal Customer,62,Personal Travel,Eco Plus,764,2,4,2,1,3,2,5,3,4,3,4,5,5,3,6,20.0,neutral or dissatisfied +19419,113275,Male,Loyal Customer,47,Business travel,Business,414,5,5,5,5,5,4,5,4,4,4,4,3,4,3,43,37.0,satisfied +19420,129675,Female,disloyal Customer,39,Business travel,Business,447,1,1,1,4,4,1,4,4,3,1,4,3,4,4,0,0.0,neutral or dissatisfied +19421,89651,Male,disloyal Customer,26,Business travel,Business,1096,2,2,2,2,2,2,2,2,2,3,3,2,3,2,0,0.0,neutral or dissatisfied +19422,45390,Male,Loyal Customer,31,Business travel,Eco Plus,222,4,5,5,5,4,4,4,4,1,5,2,4,4,4,0,0.0,satisfied +19423,54320,Male,Loyal Customer,16,Business travel,Business,1597,5,5,5,5,4,4,4,4,1,4,3,3,5,4,0,0.0,satisfied +19424,8033,Female,Loyal Customer,47,Business travel,Business,2324,1,1,1,1,4,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +19425,123772,Male,disloyal Customer,27,Business travel,Business,544,2,2,2,1,1,2,1,1,3,5,4,3,5,1,0,0.0,neutral or dissatisfied +19426,45162,Male,Loyal Customer,35,Business travel,Business,1847,4,5,5,5,2,4,3,3,3,3,4,4,3,1,81,96.0,neutral or dissatisfied +19427,16864,Female,Loyal Customer,28,Business travel,Business,746,1,1,1,1,3,3,3,3,3,1,1,4,2,3,3,0.0,satisfied +19428,103397,Male,Loyal Customer,55,Business travel,Business,2797,2,2,2,2,4,5,5,5,5,5,5,4,5,3,52,48.0,satisfied +19429,61917,Female,Loyal Customer,45,Business travel,Business,550,4,4,4,4,5,5,5,5,5,4,5,5,5,3,0,3.0,satisfied +19430,122337,Female,disloyal Customer,22,Business travel,Eco,541,1,5,1,4,1,1,1,1,4,5,4,5,4,1,39,22.0,neutral or dissatisfied +19431,44879,Male,Loyal Customer,29,Personal Travel,Eco,296,1,3,1,3,1,1,2,1,1,1,3,3,4,1,0,0.0,neutral or dissatisfied +19432,69694,Female,Loyal Customer,44,Business travel,Business,1372,4,4,4,4,5,5,5,3,2,4,4,5,3,5,141,129.0,satisfied +19433,85391,Female,Loyal Customer,47,Business travel,Business,3156,1,1,1,1,5,4,5,3,4,4,5,5,3,5,581,580.0,satisfied +19434,82062,Female,Loyal Customer,53,Business travel,Business,3897,3,3,3,3,4,4,4,4,4,4,4,4,4,5,0,29.0,satisfied +19435,118406,Female,Loyal Customer,20,Business travel,Business,2862,2,2,2,2,5,5,5,5,3,3,5,4,4,5,0,0.0,satisfied +19436,35869,Male,Loyal Customer,9,Personal Travel,Eco,1065,4,4,4,5,2,4,2,2,5,5,5,3,4,2,0,18.0,neutral or dissatisfied +19437,37548,Male,disloyal Customer,25,Business travel,Eco,972,1,1,1,4,1,1,3,1,4,5,1,2,5,1,0,0.0,neutral or dissatisfied +19438,6224,Male,Loyal Customer,27,Business travel,Business,3692,4,4,4,4,3,4,3,3,5,4,4,4,4,3,0,0.0,satisfied +19439,85502,Male,Loyal Customer,60,Personal Travel,Eco,152,3,4,3,3,1,3,1,1,4,4,4,5,4,1,0,0.0,neutral or dissatisfied +19440,36268,Male,Loyal Customer,68,Personal Travel,Eco,728,3,3,3,4,3,3,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +19441,7292,Female,Loyal Customer,64,Personal Travel,Eco,139,3,3,0,3,3,4,3,4,4,0,4,4,4,4,0,0.0,neutral or dissatisfied +19442,58654,Male,Loyal Customer,32,Personal Travel,Eco,867,2,1,2,2,4,2,4,4,4,1,1,2,1,4,0,0.0,neutral or dissatisfied +19443,42086,Male,Loyal Customer,40,Business travel,Eco,344,4,3,3,3,4,4,4,4,2,2,2,3,3,4,0,0.0,satisfied +19444,101355,Female,Loyal Customer,54,Business travel,Business,2200,4,4,3,4,4,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +19445,65109,Female,Loyal Customer,63,Personal Travel,Eco,190,1,5,1,1,2,5,5,3,3,1,2,5,3,4,0,0.0,neutral or dissatisfied +19446,116373,Male,Loyal Customer,11,Personal Travel,Eco,358,3,4,3,3,3,3,3,3,4,5,4,4,4,3,41,39.0,neutral or dissatisfied +19447,4086,Male,disloyal Customer,25,Business travel,Business,427,2,2,2,3,5,2,5,5,1,4,3,2,3,5,0,0.0,neutral or dissatisfied +19448,34349,Female,Loyal Customer,39,Business travel,Eco,427,5,1,1,1,5,5,5,5,4,1,5,5,2,5,225,218.0,satisfied +19449,33868,Male,Loyal Customer,27,Business travel,Eco Plus,1562,3,1,1,1,3,3,3,3,4,3,4,2,4,3,0,0.0,neutral or dissatisfied +19450,42330,Female,Loyal Customer,47,Personal Travel,Eco,550,3,1,3,4,5,3,4,4,4,3,3,3,4,2,0,8.0,neutral or dissatisfied +19451,112543,Male,Loyal Customer,64,Business travel,Business,862,3,3,3,3,5,4,5,5,5,5,5,4,5,3,22,21.0,satisfied +19452,40715,Female,disloyal Customer,11,Business travel,Eco,599,2,0,1,4,3,1,3,3,1,2,4,1,3,3,0,0.0,neutral or dissatisfied +19453,42467,Male,disloyal Customer,20,Business travel,Business,429,0,0,0,5,5,0,5,5,4,2,5,4,5,5,0,0.0,satisfied +19454,77350,Male,Loyal Customer,27,Business travel,Business,599,2,2,2,2,5,5,5,5,3,2,4,3,4,5,0,0.0,satisfied +19455,13082,Male,Loyal Customer,29,Business travel,Business,3195,5,5,5,5,5,5,5,5,3,5,5,5,4,5,0,0.0,satisfied +19456,9510,Male,Loyal Customer,34,Personal Travel,Eco,322,4,5,4,2,1,4,1,1,1,3,1,2,2,1,0,0.0,neutral or dissatisfied +19457,22745,Male,Loyal Customer,33,Business travel,Eco,302,5,3,3,3,5,4,5,5,1,1,4,1,4,5,0,0.0,satisfied +19458,23498,Male,Loyal Customer,41,Business travel,Business,1590,0,0,0,2,4,5,4,5,5,5,5,1,5,5,3,0.0,satisfied +19459,34431,Female,Loyal Customer,27,Business travel,Eco,680,1,4,4,4,1,1,1,1,2,5,3,1,3,1,0,0.0,neutral or dissatisfied +19460,35986,Male,disloyal Customer,23,Business travel,Eco,1079,2,3,3,3,3,1,1,4,3,4,3,1,2,1,8,0.0,neutral or dissatisfied +19461,114237,Female,disloyal Customer,25,Business travel,Eco,846,3,4,4,3,3,4,3,3,4,1,4,3,4,3,51,59.0,neutral or dissatisfied +19462,33400,Male,Loyal Customer,51,Business travel,Business,2614,1,1,1,1,4,4,4,3,2,3,5,4,3,4,0,0.0,satisfied +19463,44856,Female,disloyal Customer,25,Business travel,Eco,585,2,2,2,4,2,2,1,2,2,3,4,2,4,2,19,7.0,neutral or dissatisfied +19464,89217,Male,Loyal Customer,57,Personal Travel,Eco,1947,1,4,1,2,2,1,2,2,3,4,4,5,4,2,24,5.0,neutral or dissatisfied +19465,22814,Female,Loyal Customer,47,Business travel,Business,2466,3,3,3,3,2,3,1,4,4,4,3,5,4,5,0,0.0,satisfied +19466,58878,Male,Loyal Customer,47,Business travel,Business,1538,3,3,3,3,3,5,5,4,4,4,4,3,4,4,1,11.0,satisfied +19467,71873,Female,Loyal Customer,24,Personal Travel,Eco,1652,1,3,1,1,4,1,4,4,2,5,4,4,2,4,13,28.0,neutral or dissatisfied +19468,47938,Female,Loyal Customer,14,Personal Travel,Eco,451,3,3,3,3,2,3,2,2,2,2,3,4,4,2,10,7.0,neutral or dissatisfied +19469,110954,Female,Loyal Customer,21,Personal Travel,Eco Plus,545,0,4,0,4,2,0,5,2,3,5,4,4,4,2,0,0.0,satisfied +19470,91648,Male,Loyal Customer,46,Personal Travel,Eco,1199,1,3,1,3,2,1,2,2,3,5,4,2,4,2,5,0.0,neutral or dissatisfied +19471,31304,Female,Loyal Customer,51,Business travel,Eco,680,5,3,1,3,3,1,5,5,5,5,5,5,5,1,12,21.0,satisfied +19472,57737,Male,Loyal Customer,59,Personal Travel,Eco,1754,1,5,1,4,4,1,4,4,3,5,3,5,4,4,0,0.0,neutral or dissatisfied +19473,128548,Female,Loyal Customer,34,Business travel,Business,2108,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +19474,12187,Female,Loyal Customer,26,Personal Travel,Eco,1075,3,5,3,4,3,3,3,3,3,4,4,5,4,3,0,0.0,neutral or dissatisfied +19475,37454,Male,disloyal Customer,50,Business travel,Business,1069,2,2,2,1,5,2,5,5,4,3,3,3,5,5,29,22.0,neutral or dissatisfied +19476,94451,Male,Loyal Customer,58,Business travel,Business,562,3,3,3,3,3,5,5,5,5,5,5,4,5,3,15,0.0,satisfied +19477,27571,Male,Loyal Customer,52,Personal Travel,Eco,937,2,4,2,1,1,2,3,1,4,5,4,3,5,1,0,2.0,neutral or dissatisfied +19478,112633,Female,disloyal Customer,26,Business travel,Eco Plus,602,3,2,3,4,2,3,2,2,3,1,3,1,4,2,11,13.0,neutral or dissatisfied +19479,55711,Female,Loyal Customer,30,Personal Travel,Eco,1062,2,3,2,3,3,2,3,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +19480,42350,Female,Loyal Customer,55,Personal Travel,Eco,329,2,5,2,3,3,2,3,1,1,2,1,2,1,1,0,0.0,neutral or dissatisfied +19481,83144,Male,Loyal Customer,60,Personal Travel,Eco,1127,2,4,2,4,5,2,5,5,3,4,3,5,5,5,0,0.0,neutral or dissatisfied +19482,74841,Female,Loyal Customer,31,Personal Travel,Eco,1797,2,5,2,2,1,2,1,1,5,3,3,4,5,1,15,1.0,neutral or dissatisfied +19483,59438,Male,Loyal Customer,25,Business travel,Business,3017,2,2,4,2,1,2,2,1,4,3,4,2,2,2,351,357.0,neutral or dissatisfied +19484,89701,Male,disloyal Customer,17,Business travel,Business,1080,5,0,5,4,4,5,4,4,1,3,5,3,2,4,0,0.0,satisfied +19485,89303,Female,Loyal Customer,40,Personal Travel,Eco,453,2,5,2,4,4,2,3,4,2,4,3,1,4,4,0,0.0,neutral or dissatisfied +19486,24608,Female,Loyal Customer,35,Business travel,Eco,526,5,1,1,1,5,5,5,5,1,5,1,3,4,5,0,0.0,satisfied +19487,127211,Female,Loyal Customer,11,Personal Travel,Eco Plus,338,5,2,5,3,1,5,2,1,2,2,3,2,3,1,0,0.0,satisfied +19488,9582,Female,Loyal Customer,35,Business travel,Business,283,2,2,2,2,4,4,4,1,5,3,2,4,5,4,104,134.0,satisfied +19489,92715,Female,Loyal Customer,41,Business travel,Business,1276,2,2,2,2,3,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +19490,123606,Male,Loyal Customer,59,Personal Travel,Eco,1773,2,1,2,3,2,2,2,2,3,4,3,3,3,2,113,122.0,neutral or dissatisfied +19491,15261,Female,Loyal Customer,32,Business travel,Eco Plus,529,2,3,3,3,2,2,2,2,3,5,3,2,4,2,11,0.0,neutral or dissatisfied +19492,114222,Female,disloyal Customer,26,Business travel,Eco,862,2,1,1,4,2,1,3,2,3,3,3,3,3,2,38,33.0,neutral or dissatisfied +19493,50427,Male,Loyal Customer,58,Business travel,Business,262,3,1,1,1,3,4,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +19494,77738,Male,Loyal Customer,52,Business travel,Eco,696,3,3,5,3,3,3,3,3,4,4,3,3,4,3,5,4.0,neutral or dissatisfied +19495,6522,Male,Loyal Customer,23,Personal Travel,Eco,599,1,2,1,4,5,1,5,5,1,2,4,2,3,5,0,0.0,neutral or dissatisfied +19496,58297,Male,disloyal Customer,48,Business travel,Business,678,2,2,2,3,3,2,3,3,4,3,4,4,5,3,41,30.0,neutral or dissatisfied +19497,63414,Female,Loyal Customer,9,Personal Travel,Eco,337,1,3,5,4,4,5,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +19498,101327,Male,Loyal Customer,55,Personal Travel,Eco,986,4,5,4,3,3,4,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +19499,15034,Female,Loyal Customer,49,Business travel,Business,488,2,2,5,2,3,1,5,5,5,5,5,3,5,4,6,18.0,satisfied +19500,110678,Male,Loyal Customer,43,Business travel,Business,605,4,4,4,4,2,3,3,4,4,4,4,3,4,4,5,0.0,neutral or dissatisfied +19501,69691,Female,Loyal Customer,59,Business travel,Business,1372,4,4,4,4,4,4,4,4,4,4,4,4,4,5,5,8.0,satisfied +19502,72988,Female,disloyal Customer,20,Business travel,Eco,1096,1,1,1,2,1,1,1,1,2,2,3,3,5,1,0,0.0,neutral or dissatisfied +19503,86108,Female,Loyal Customer,51,Business travel,Business,3144,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +19504,84792,Male,Loyal Customer,56,Business travel,Business,547,4,4,4,4,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +19505,29087,Female,Loyal Customer,9,Personal Travel,Eco,679,4,3,4,2,4,4,4,4,1,4,2,3,1,4,21,9.0,neutral or dissatisfied +19506,32235,Male,Loyal Customer,53,Business travel,Business,102,2,2,2,2,1,2,2,5,5,5,3,3,5,2,0,7.0,satisfied +19507,124962,Female,Loyal Customer,48,Business travel,Business,184,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +19508,1869,Female,Loyal Customer,16,Business travel,Business,2200,3,5,5,5,3,3,3,3,4,4,3,4,3,3,0,15.0,neutral or dissatisfied +19509,113654,Male,Loyal Customer,63,Personal Travel,Eco,197,1,4,1,3,5,1,5,5,3,5,3,4,4,5,4,0.0,neutral or dissatisfied +19510,31647,Male,Loyal Customer,55,Business travel,Eco,853,4,1,1,1,4,4,4,4,4,3,5,3,4,4,3,10.0,satisfied +19511,114355,Male,Loyal Customer,49,Business travel,Business,3965,3,3,3,3,4,4,5,3,3,3,3,4,3,5,46,31.0,satisfied +19512,77162,Male,Loyal Customer,54,Business travel,Eco,1450,3,4,4,4,3,3,3,3,3,4,4,2,3,3,63,92.0,neutral or dissatisfied +19513,66592,Male,Loyal Customer,40,Business travel,Business,761,1,1,1,1,4,4,4,5,5,5,5,4,5,3,26,29.0,satisfied +19514,61463,Female,Loyal Customer,54,Business travel,Business,2288,5,5,5,5,4,5,4,5,5,5,5,3,5,4,10,1.0,satisfied +19515,35182,Male,Loyal Customer,45,Business travel,Business,2145,1,3,5,3,3,3,2,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +19516,37089,Female,Loyal Customer,52,Business travel,Business,2883,5,5,5,5,5,4,1,5,5,5,5,5,5,4,39,38.0,satisfied +19517,93782,Female,Loyal Customer,38,Personal Travel,Eco,1865,2,3,1,2,1,5,5,3,4,5,5,5,4,5,292,291.0,neutral or dissatisfied +19518,21312,Female,Loyal Customer,29,Personal Travel,Eco,620,4,5,4,2,3,4,3,3,5,3,4,4,4,3,0,0.0,satisfied +19519,41135,Male,disloyal Customer,21,Business travel,Eco,140,2,3,2,3,4,2,5,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +19520,115976,Female,Loyal Customer,19,Personal Travel,Eco,373,2,0,2,4,3,2,3,3,1,5,4,4,1,3,0,0.0,neutral or dissatisfied +19521,23938,Female,Loyal Customer,34,Personal Travel,Eco,616,1,5,1,2,4,1,4,4,4,4,3,5,3,4,0,0.0,neutral or dissatisfied +19522,70412,Male,Loyal Customer,63,Personal Travel,Eco,1562,3,5,3,3,4,3,4,4,1,2,5,1,2,4,0,0.0,neutral or dissatisfied +19523,9263,Female,disloyal Customer,22,Business travel,Business,441,4,0,4,2,2,4,5,2,3,5,4,3,5,2,0,0.0,satisfied +19524,19241,Male,Loyal Customer,22,Business travel,Business,3202,1,2,2,2,1,1,1,1,4,2,4,2,3,1,0,0.0,neutral or dissatisfied +19525,26469,Female,Loyal Customer,47,Personal Travel,Eco,842,1,5,1,2,5,4,5,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +19526,114849,Female,disloyal Customer,25,Business travel,Business,325,1,5,1,4,1,1,5,1,4,3,4,5,4,1,1,0.0,neutral or dissatisfied +19527,32077,Male,Loyal Customer,46,Business travel,Business,3320,0,5,0,2,4,1,2,2,2,2,2,1,2,3,0,0.0,satisfied +19528,21693,Male,Loyal Customer,77,Business travel,Eco,346,3,1,1,1,3,3,3,3,3,1,1,3,1,3,5,0.0,neutral or dissatisfied +19529,127946,Male,Loyal Customer,69,Personal Travel,Eco Plus,2300,0,4,0,1,1,0,1,1,5,2,3,4,4,1,6,0.0,satisfied +19530,128551,Female,disloyal Customer,33,Business travel,Eco Plus,325,1,1,1,4,5,1,5,5,4,5,3,1,3,5,0,0.0,neutral or dissatisfied +19531,21947,Male,Loyal Customer,37,Business travel,Business,3308,2,2,2,2,3,2,1,5,5,4,5,4,5,5,0,0.0,satisfied +19532,41629,Female,Loyal Customer,22,Business travel,Business,3225,3,2,2,2,3,3,3,3,4,4,3,3,3,3,0,0.0,neutral or dissatisfied +19533,74183,Female,Loyal Customer,48,Personal Travel,Eco,641,2,4,2,1,4,4,5,1,1,2,2,3,1,3,0,0.0,neutral or dissatisfied +19534,108682,Male,Loyal Customer,37,Business travel,Business,3804,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +19535,49846,Female,Loyal Customer,51,Business travel,Business,2458,1,5,5,5,4,4,3,1,1,1,1,3,1,2,0,0.0,neutral or dissatisfied +19536,31031,Female,Loyal Customer,21,Personal Travel,Business,641,1,4,2,3,1,2,1,1,4,5,4,3,4,1,0,0.0,neutral or dissatisfied +19537,115589,Female,Loyal Customer,20,Business travel,Business,1759,2,2,3,2,2,2,2,2,4,5,4,2,3,2,1,0.0,neutral or dissatisfied +19538,39772,Male,Loyal Customer,28,Business travel,Eco,521,4,3,3,3,4,4,4,4,3,3,2,4,2,4,0,0.0,satisfied +19539,124395,Female,Loyal Customer,29,Business travel,Eco Plus,575,5,4,4,4,5,4,5,5,2,2,4,1,4,5,18,11.0,neutral or dissatisfied +19540,11859,Male,disloyal Customer,29,Business travel,Business,912,1,1,1,4,1,1,1,1,5,3,5,5,5,1,9,5.0,neutral or dissatisfied +19541,96824,Male,disloyal Customer,19,Business travel,Business,571,4,5,5,2,5,5,5,5,5,2,4,4,4,5,23,41.0,satisfied +19542,97999,Male,Loyal Customer,43,Business travel,Business,391,1,1,1,1,5,4,4,4,4,4,4,5,4,4,2,0.0,satisfied +19543,117587,Male,Loyal Customer,67,Business travel,Business,2456,2,2,2,2,3,3,4,2,2,2,2,2,2,1,89,84.0,neutral or dissatisfied +19544,19120,Female,disloyal Customer,21,Business travel,Eco,265,2,0,2,1,1,2,1,1,5,2,1,5,1,1,0,0.0,neutral or dissatisfied +19545,113433,Female,Loyal Customer,56,Business travel,Business,397,3,5,5,5,5,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +19546,25068,Female,Loyal Customer,39,Personal Travel,Eco,594,2,1,2,3,5,2,5,5,3,5,3,3,3,5,7,7.0,neutral or dissatisfied +19547,20034,Male,Loyal Customer,42,Business travel,Eco,607,4,2,5,2,4,4,4,4,4,5,2,3,3,4,74,65.0,neutral or dissatisfied +19548,59213,Male,Loyal Customer,8,Personal Travel,Eco,1440,1,2,1,3,3,1,3,3,4,4,4,2,3,3,61,70.0,neutral or dissatisfied +19549,108422,Male,Loyal Customer,54,Business travel,Business,1444,4,4,4,4,3,5,4,4,4,4,4,3,4,3,32,10.0,satisfied +19550,119303,Male,disloyal Customer,27,Business travel,Business,214,4,4,4,4,3,4,3,3,3,1,3,2,4,3,0,67.0,neutral or dissatisfied +19551,27805,Female,Loyal Customer,28,Business travel,Business,909,1,3,3,3,1,1,1,1,4,2,3,2,3,1,0,0.0,neutral or dissatisfied +19552,108612,Male,Loyal Customer,58,Personal Travel,Eco,813,5,1,5,3,5,5,5,5,1,2,3,4,4,5,0,2.0,satisfied +19553,121615,Female,Loyal Customer,69,Personal Travel,Eco,912,3,5,3,2,4,5,4,2,2,3,2,4,2,5,60,43.0,neutral or dissatisfied +19554,111163,Male,Loyal Customer,56,Business travel,Business,2841,5,5,2,5,4,5,5,5,5,5,5,3,5,4,39,21.0,satisfied +19555,22723,Male,Loyal Customer,52,Business travel,Business,1597,3,4,5,5,2,3,2,2,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +19556,62190,Male,disloyal Customer,17,Business travel,Eco,2454,3,3,3,3,3,3,3,3,4,1,3,2,3,3,0,0.0,neutral or dissatisfied +19557,63385,Male,Loyal Customer,58,Personal Travel,Eco,337,4,1,4,3,1,4,4,1,4,4,2,2,2,1,0,14.0,neutral or dissatisfied +19558,105425,Female,Loyal Customer,38,Business travel,Business,3172,3,3,3,3,4,3,3,4,4,4,4,5,4,4,0,0.0,satisfied +19559,94186,Male,Loyal Customer,48,Business travel,Business,3792,3,3,3,3,2,5,4,4,4,4,4,3,4,4,14,21.0,satisfied +19560,123723,Female,disloyal Customer,26,Business travel,Business,214,1,4,2,3,5,2,5,5,4,2,5,3,4,5,0,0.0,neutral or dissatisfied +19561,37389,Female,Loyal Customer,28,Business travel,Business,989,5,5,5,5,4,4,4,4,4,3,1,2,5,4,0,0.0,satisfied +19562,5768,Male,Loyal Customer,33,Business travel,Business,3741,2,3,3,3,2,2,2,2,2,3,2,2,2,2,0,0.0,neutral or dissatisfied +19563,102983,Male,Loyal Customer,49,Business travel,Business,460,1,1,3,1,5,5,5,5,5,4,5,3,5,4,0,0.0,satisfied +19564,120169,Female,disloyal Customer,22,Business travel,Eco,335,3,4,3,2,2,3,2,2,4,4,4,5,4,2,9,0.0,neutral or dissatisfied +19565,56828,Male,Loyal Customer,44,Personal Travel,Eco,1605,3,4,3,2,3,3,3,3,4,3,5,3,4,3,45,18.0,neutral or dissatisfied +19566,65247,Female,disloyal Customer,30,Business travel,Eco Plus,224,3,3,3,2,5,3,5,5,3,2,3,1,3,5,14,21.0,neutral or dissatisfied +19567,11021,Female,disloyal Customer,24,Business travel,Eco,163,5,0,5,1,3,5,2,3,1,2,5,5,2,3,0,0.0,satisfied +19568,46893,Male,Loyal Customer,32,Business travel,Business,909,2,2,2,2,5,5,5,5,5,1,3,3,4,5,0,0.0,satisfied +19569,31237,Female,Loyal Customer,46,Business travel,Business,2798,4,4,4,4,2,2,2,5,5,5,5,1,5,5,0,0.0,satisfied +19570,118190,Female,Loyal Customer,38,Business travel,Business,1044,3,2,2,2,5,2,1,3,3,3,3,3,3,1,8,11.0,neutral or dissatisfied +19571,68432,Male,Loyal Customer,53,Business travel,Business,1864,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +19572,104445,Male,Loyal Customer,14,Business travel,Eco Plus,1138,3,1,3,3,3,3,4,3,1,2,3,1,3,3,2,11.0,neutral or dissatisfied +19573,101545,Female,Loyal Customer,66,Personal Travel,Eco,345,4,4,4,1,4,4,4,2,2,4,2,3,2,3,0,0.0,satisfied +19574,3960,Male,Loyal Customer,66,Personal Travel,Eco,765,3,5,3,4,3,3,3,3,5,3,5,4,4,3,0,85.0,neutral or dissatisfied +19575,51955,Female,disloyal Customer,24,Business travel,Eco,936,5,5,5,4,2,5,1,2,1,1,4,5,1,2,0,0.0,satisfied +19576,12097,Male,Loyal Customer,62,Business travel,Business,1529,1,1,1,1,3,1,3,5,5,5,5,3,5,5,5,0.0,satisfied +19577,61007,Male,Loyal Customer,40,Business travel,Business,3329,3,3,3,3,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +19578,83488,Female,disloyal Customer,26,Business travel,Business,946,4,0,4,1,4,4,4,4,3,3,5,3,4,4,0,10.0,neutral or dissatisfied +19579,36442,Male,Loyal Customer,16,Personal Travel,Eco,369,5,5,5,1,3,5,5,3,5,1,1,3,2,3,0,4.0,satisfied +19580,25189,Female,disloyal Customer,23,Business travel,Eco,177,2,4,3,3,1,3,1,1,1,4,4,4,3,1,0,0.0,neutral or dissatisfied +19581,113814,Male,Loyal Customer,38,Business travel,Eco Plus,386,3,3,3,3,3,3,3,3,4,5,4,1,3,3,45,28.0,neutral or dissatisfied +19582,56448,Female,Loyal Customer,21,Personal Travel,Eco,719,2,3,2,3,3,2,2,3,4,3,3,3,3,3,5,0.0,neutral or dissatisfied +19583,117596,Female,disloyal Customer,24,Business travel,Eco,1020,2,2,2,3,3,2,3,3,1,2,3,3,3,3,17,8.0,neutral or dissatisfied +19584,22901,Male,Loyal Customer,58,Personal Travel,Eco Plus,147,1,5,0,4,5,0,1,5,5,5,3,4,5,5,0,0.0,neutral or dissatisfied +19585,16900,Male,Loyal Customer,36,Personal Travel,Eco,746,2,5,3,2,3,3,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +19586,106525,Male,Loyal Customer,38,Personal Travel,Eco,271,3,3,3,4,3,3,3,3,3,5,4,4,3,3,57,59.0,neutral or dissatisfied +19587,78861,Male,Loyal Customer,18,Personal Travel,Eco Plus,528,3,5,3,1,2,3,2,2,3,4,5,3,5,2,0,0.0,neutral or dissatisfied +19588,74763,Male,Loyal Customer,63,Personal Travel,Eco,1205,2,4,2,4,2,2,2,2,2,2,4,4,4,2,76,,neutral or dissatisfied +19589,75363,Female,Loyal Customer,16,Personal Travel,Eco Plus,2556,2,4,2,3,2,3,2,4,4,5,4,2,3,2,0,13.0,neutral or dissatisfied +19590,92299,Male,Loyal Customer,53,Business travel,Business,2556,3,3,3,3,3,5,5,3,3,2,3,3,3,5,64,51.0,satisfied +19591,5151,Male,Loyal Customer,40,Business travel,Business,3699,2,5,1,1,4,4,4,1,1,1,2,4,1,2,0,0.0,neutral or dissatisfied +19592,52971,Male,Loyal Customer,56,Personal Travel,Eco,2306,3,1,3,1,2,3,2,2,2,4,2,4,1,2,23,34.0,neutral or dissatisfied +19593,91472,Male,Loyal Customer,17,Personal Travel,Eco,859,4,5,3,4,1,3,1,1,5,3,2,3,5,1,0,0.0,satisfied +19594,61939,Female,Loyal Customer,22,Business travel,Business,2161,4,4,4,4,4,4,4,4,3,4,5,4,4,4,0,0.0,satisfied +19595,30861,Male,disloyal Customer,20,Business travel,Eco,1486,2,2,2,4,3,2,3,3,1,5,4,4,1,3,0,0.0,neutral or dissatisfied +19596,125003,Female,Loyal Customer,41,Business travel,Eco,184,4,5,5,5,3,4,3,3,2,3,2,2,2,3,0,0.0,satisfied +19597,50285,Female,Loyal Customer,47,Business travel,Business,2227,4,4,4,4,5,2,1,5,5,5,3,2,5,5,0,0.0,satisfied +19598,78579,Male,Loyal Customer,23,Personal Travel,Eco,630,3,4,3,1,1,3,1,1,4,3,5,4,4,1,0,0.0,neutral or dissatisfied +19599,100882,Male,Loyal Customer,36,Business travel,Business,3927,1,1,1,1,4,4,4,3,3,4,3,1,3,1,0,0.0,satisfied +19600,23145,Female,Loyal Customer,44,Business travel,Business,250,0,0,0,1,4,1,5,5,5,5,2,1,5,5,0,0.0,satisfied +19601,37828,Female,Loyal Customer,39,Business travel,Business,1023,4,4,4,4,2,4,5,5,5,5,5,5,5,1,28,6.0,satisfied +19602,82679,Female,Loyal Customer,53,Business travel,Business,632,3,3,3,3,4,5,4,4,4,4,4,3,4,5,4,13.0,satisfied +19603,34073,Male,Loyal Customer,59,Personal Travel,Eco,1674,3,1,3,3,2,3,2,2,1,3,3,4,3,2,4,0.0,neutral or dissatisfied +19604,84984,Female,Loyal Customer,60,Business travel,Business,1590,4,4,4,4,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +19605,58991,Female,Loyal Customer,53,Business travel,Business,1846,4,4,4,4,2,4,4,4,4,4,4,5,4,4,24,15.0,satisfied +19606,108617,Female,Loyal Customer,54,Personal Travel,Eco,696,2,4,2,4,4,5,4,1,1,2,1,3,1,5,22,19.0,neutral or dissatisfied +19607,35161,Male,Loyal Customer,38,Business travel,Eco,1074,4,1,1,1,4,4,4,4,1,1,4,3,3,4,21,32.0,satisfied +19608,94010,Female,Loyal Customer,44,Business travel,Business,441,3,3,1,3,4,5,5,5,5,4,5,3,5,3,13,18.0,satisfied +19609,63410,Male,Loyal Customer,42,Personal Travel,Eco,447,3,1,3,4,2,3,2,2,2,3,3,2,4,2,0,0.0,neutral or dissatisfied +19610,639,Male,Loyal Customer,39,Business travel,Business,309,4,4,4,4,4,4,5,5,5,5,5,3,5,5,25,16.0,satisfied +19611,106108,Male,disloyal Customer,47,Business travel,Business,436,5,5,5,4,2,5,2,2,5,5,5,5,4,2,19,8.0,satisfied +19612,14260,Female,Loyal Customer,34,Personal Travel,Business,175,2,4,0,3,2,5,4,4,4,0,4,3,4,4,0,0.0,neutral or dissatisfied +19613,25190,Male,Loyal Customer,42,Personal Travel,Eco,577,3,2,3,4,5,3,5,5,3,4,3,3,3,5,1,0.0,neutral or dissatisfied +19614,125987,Male,Loyal Customer,25,Personal Travel,Business,507,2,4,2,2,3,2,3,3,2,3,5,3,2,3,5,2.0,neutral or dissatisfied +19615,21583,Male,Loyal Customer,42,Personal Travel,Eco Plus,164,3,5,0,3,3,0,3,3,3,5,4,3,5,3,0,0.0,neutral or dissatisfied +19616,1553,Female,Loyal Customer,68,Personal Travel,Eco,862,2,5,2,2,5,4,4,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +19617,94431,Female,Loyal Customer,62,Business travel,Business,239,2,3,3,3,2,3,3,2,2,3,2,3,2,4,0,0.0,neutral or dissatisfied +19618,13531,Female,disloyal Customer,17,Business travel,Eco,106,3,2,3,3,4,3,4,4,1,3,3,3,3,4,0,0.0,neutral or dissatisfied +19619,70373,Male,Loyal Customer,63,Personal Travel,Eco,1145,3,4,2,3,1,2,1,1,3,2,3,5,2,1,0,0.0,neutral or dissatisfied +19620,52373,Male,Loyal Customer,34,Personal Travel,Eco,651,2,0,2,2,2,2,4,2,4,3,5,5,5,2,0,0.0,neutral or dissatisfied +19621,117109,Female,disloyal Customer,40,Business travel,Business,325,1,1,1,3,1,1,1,1,2,4,4,3,3,1,0,0.0,neutral or dissatisfied +19622,38485,Male,Loyal Customer,41,Business travel,Business,2475,2,2,2,2,4,4,4,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +19623,11555,Female,disloyal Customer,20,Business travel,Eco,771,5,5,5,1,1,5,5,1,5,4,4,5,4,1,39,35.0,satisfied +19624,77084,Male,Loyal Customer,41,Personal Travel,Eco,991,3,4,3,5,5,3,5,5,5,3,4,4,4,5,0,0.0,neutral or dissatisfied +19625,65070,Male,Loyal Customer,9,Personal Travel,Eco,190,5,5,5,4,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +19626,9516,Female,disloyal Customer,32,Business travel,Business,228,2,2,2,5,4,2,5,4,5,4,5,3,5,4,48,94.0,neutral or dissatisfied +19627,4452,Male,Loyal Customer,34,Personal Travel,Eco Plus,762,2,2,2,3,4,2,1,4,4,4,4,2,4,4,102,93.0,neutral or dissatisfied +19628,123325,Female,disloyal Customer,39,Business travel,Eco Plus,231,2,2,2,1,2,2,2,2,4,4,3,4,4,2,0,0.0,satisfied +19629,64442,Female,disloyal Customer,30,Business travel,Eco,989,2,2,2,1,2,2,2,2,3,4,1,4,2,2,10,2.0,neutral or dissatisfied +19630,31445,Male,Loyal Customer,44,Business travel,Eco Plus,1541,5,3,3,3,5,5,5,5,5,5,4,3,4,5,10,32.0,satisfied +19631,94941,Female,Loyal Customer,40,Business travel,Business,3317,4,4,4,4,3,3,3,4,4,4,4,3,4,2,0,0.0,satisfied +19632,99255,Female,Loyal Customer,26,Business travel,Eco Plus,541,3,3,2,3,3,2,1,3,4,4,4,2,3,3,0,4.0,neutral or dissatisfied +19633,25074,Female,Loyal Customer,54,Business travel,Eco,957,3,5,5,5,3,3,4,3,3,3,3,4,3,4,35,36.0,neutral or dissatisfied +19634,22888,Female,Loyal Customer,37,Personal Travel,Eco,170,3,1,3,3,4,3,4,4,2,5,4,3,3,4,0,0.0,neutral or dissatisfied +19635,123945,Male,Loyal Customer,59,Business travel,Business,544,5,1,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +19636,97184,Female,Loyal Customer,36,Personal Travel,Eco,1313,3,2,2,4,5,2,5,5,4,3,2,4,3,5,0,0.0,neutral or dissatisfied +19637,51417,Male,Loyal Customer,15,Personal Travel,Eco Plus,86,1,3,1,2,2,1,2,2,1,4,2,2,2,2,10,24.0,neutral or dissatisfied +19638,84985,Female,Loyal Customer,26,Business travel,Business,1590,1,5,3,5,1,1,1,1,3,1,2,1,4,1,55,32.0,neutral or dissatisfied +19639,4629,Female,disloyal Customer,26,Business travel,Business,327,3,3,3,3,5,3,4,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +19640,53637,Female,Loyal Customer,17,Personal Travel,Eco,1874,2,2,2,3,5,2,5,5,4,2,4,1,3,5,0,6.0,neutral or dissatisfied +19641,5877,Male,Loyal Customer,58,Business travel,Business,1712,1,1,1,1,4,5,4,5,5,5,5,4,5,3,3,0.0,satisfied +19642,100806,Female,Loyal Customer,39,Business travel,Business,3733,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +19643,7498,Female,Loyal Customer,55,Personal Travel,Eco,925,1,5,1,3,2,5,4,4,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +19644,24490,Male,disloyal Customer,24,Business travel,Eco,481,2,4,2,4,1,2,1,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +19645,114424,Male,Loyal Customer,54,Business travel,Business,2172,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +19646,66728,Female,Loyal Customer,30,Personal Travel,Eco,802,3,3,4,3,3,4,3,3,3,2,3,4,4,3,4,13.0,neutral or dissatisfied +19647,17797,Male,Loyal Customer,38,Business travel,Business,3581,3,2,2,2,1,1,2,3,3,3,3,2,3,3,115,108.0,neutral or dissatisfied +19648,99984,Female,Loyal Customer,49,Personal Travel,Business,281,3,4,3,3,4,4,4,3,3,3,3,5,3,5,76,80.0,neutral or dissatisfied +19649,54726,Female,Loyal Customer,65,Personal Travel,Eco,964,3,4,3,1,3,5,4,2,2,3,2,4,2,3,8,0.0,neutral or dissatisfied +19650,60732,Male,Loyal Customer,32,Personal Travel,Eco,1605,3,4,3,5,4,3,4,4,4,5,3,3,4,4,10,0.0,neutral or dissatisfied +19651,71528,Female,Loyal Customer,24,Business travel,Business,1197,2,2,2,2,2,2,2,2,4,5,4,5,5,2,4,0.0,satisfied +19652,23940,Male,Loyal Customer,29,Business travel,Eco Plus,771,4,1,1,1,4,4,4,4,3,5,5,5,5,4,19,6.0,satisfied +19653,51771,Male,Loyal Customer,17,Personal Travel,Eco,370,2,4,2,3,4,2,4,4,4,3,1,1,4,4,28,31.0,neutral or dissatisfied +19654,20075,Female,Loyal Customer,18,Personal Travel,Eco,738,1,4,1,3,3,1,3,3,5,2,5,3,4,3,0,0.0,neutral or dissatisfied +19655,53455,Female,disloyal Customer,35,Business travel,Eco,2442,3,3,3,1,3,1,4,2,3,3,2,4,5,4,0,6.0,neutral or dissatisfied +19656,74170,Female,Loyal Customer,68,Personal Travel,Eco,641,1,5,1,4,5,5,5,2,2,1,2,3,2,3,0,0.0,neutral or dissatisfied +19657,98568,Male,disloyal Customer,36,Business travel,Eco,993,1,1,1,3,4,1,4,4,4,2,3,4,3,4,126,115.0,neutral or dissatisfied +19658,8526,Female,Loyal Customer,8,Personal Travel,Eco,862,3,5,3,2,4,3,4,4,3,3,5,4,4,4,0,14.0,neutral or dissatisfied +19659,4528,Female,Loyal Customer,55,Business travel,Business,3639,1,1,1,1,3,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +19660,119298,Female,Loyal Customer,63,Business travel,Business,214,2,5,5,5,5,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +19661,1232,Female,Loyal Customer,61,Personal Travel,Eco,134,1,4,0,4,3,3,4,5,5,0,1,3,5,1,0,0.0,neutral or dissatisfied +19662,120655,Male,disloyal Customer,21,Business travel,Eco,280,4,0,4,3,5,4,5,5,4,2,5,3,4,5,0,0.0,satisfied +19663,58950,Male,Loyal Customer,44,Personal Travel,Eco Plus,888,3,5,3,3,5,3,4,5,5,2,5,3,5,5,14,0.0,neutral or dissatisfied +19664,54279,Male,Loyal Customer,54,Personal Travel,Eco,1222,3,4,2,3,2,2,1,2,4,1,3,4,1,2,0,0.0,neutral or dissatisfied +19665,88405,Male,Loyal Customer,69,Business travel,Eco,270,2,3,3,3,2,2,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +19666,60236,Male,disloyal Customer,20,Business travel,Eco,209,2,0,2,3,1,2,1,1,2,5,4,1,5,1,0,0.0,neutral or dissatisfied +19667,43453,Female,Loyal Customer,24,Business travel,Business,2926,5,5,5,5,4,4,4,4,5,2,2,2,4,4,9,0.0,satisfied +19668,120090,Female,Loyal Customer,22,Business travel,Eco Plus,683,4,3,3,3,4,3,2,4,4,4,2,2,2,4,0,56.0,neutral or dissatisfied +19669,101284,Male,Loyal Customer,53,Business travel,Business,763,2,1,1,1,2,2,2,4,5,4,4,2,3,2,200,199.0,neutral or dissatisfied +19670,73897,Female,Loyal Customer,57,Business travel,Business,2342,5,5,2,5,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +19671,6047,Male,Loyal Customer,19,Personal Travel,Eco,925,3,2,3,3,1,3,3,1,1,5,2,1,3,1,0,20.0,neutral or dissatisfied +19672,126095,Female,disloyal Customer,36,Business travel,Business,328,3,3,3,2,2,3,2,2,5,5,5,5,5,2,0,,neutral or dissatisfied +19673,91186,Male,Loyal Customer,67,Personal Travel,Eco,404,2,5,2,3,3,2,3,3,4,2,4,4,4,3,0,0.0,neutral or dissatisfied +19674,45889,Male,disloyal Customer,28,Business travel,Eco,563,4,5,4,1,1,4,1,1,3,2,4,1,4,1,16,12.0,neutral or dissatisfied +19675,47288,Female,Loyal Customer,37,Business travel,Business,3991,2,2,2,2,3,2,2,5,5,5,5,2,5,4,0,0.0,satisfied +19676,42135,Female,Loyal Customer,17,Business travel,Eco Plus,996,2,2,1,1,2,2,1,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +19677,40593,Male,disloyal Customer,16,Business travel,Eco,411,3,3,3,3,2,3,2,2,2,4,4,4,4,2,19,10.0,neutral or dissatisfied +19678,10268,Male,Loyal Customer,30,Personal Travel,Business,429,2,3,2,3,5,2,5,5,1,1,1,3,4,5,0,0.0,neutral or dissatisfied +19679,109892,Female,Loyal Customer,23,Business travel,Business,1762,5,5,5,5,4,4,4,4,4,2,3,1,1,4,69,55.0,satisfied +19680,84923,Female,Loyal Customer,68,Personal Travel,Eco,547,2,3,2,4,5,2,3,3,3,2,3,1,3,3,91,108.0,neutral or dissatisfied +19681,75536,Female,Loyal Customer,44,Personal Travel,Business,337,1,4,1,3,5,4,4,2,2,1,2,4,2,5,1,0.0,neutral or dissatisfied +19682,92958,Male,disloyal Customer,25,Personal Travel,Business,1694,4,5,5,4,2,5,2,2,2,3,4,1,4,2,29,27.0,neutral or dissatisfied +19683,85427,Female,disloyal Customer,29,Business travel,Eco,214,3,1,3,1,3,3,3,3,5,2,2,3,4,3,152,153.0,neutral or dissatisfied +19684,87377,Female,Loyal Customer,34,Business travel,Business,425,3,3,3,3,2,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +19685,53031,Male,Loyal Customer,49,Business travel,Eco,1208,4,5,5,5,4,4,4,4,4,4,2,4,3,4,0,0.0,satisfied +19686,18038,Female,Loyal Customer,52,Business travel,Business,3177,2,5,5,5,4,3,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +19687,62318,Male,disloyal Customer,50,Business travel,Business,236,2,2,2,4,2,2,2,2,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +19688,38439,Female,disloyal Customer,21,Business travel,Eco,777,0,0,0,3,5,0,5,5,5,4,3,2,1,5,0,0.0,satisfied +19689,105365,Female,disloyal Customer,36,Business travel,Business,369,1,1,1,1,3,1,3,3,5,5,4,3,4,3,4,0.0,neutral or dissatisfied +19690,5466,Male,Loyal Customer,15,Personal Travel,Eco,287,4,1,4,3,3,4,3,3,1,3,2,4,2,3,0,0.0,neutral or dissatisfied +19691,98276,Female,Loyal Customer,58,Business travel,Eco,1072,2,4,4,4,3,4,3,2,2,2,2,3,2,3,1,16.0,neutral or dissatisfied +19692,59817,Female,Loyal Customer,48,Personal Travel,Business,1065,3,5,3,5,4,5,4,4,4,3,5,5,4,5,0,0.0,neutral or dissatisfied +19693,61779,Female,Loyal Customer,26,Personal Travel,Eco,1346,3,5,3,1,2,3,2,2,4,2,3,5,4,2,0,0.0,neutral or dissatisfied +19694,25188,Male,disloyal Customer,24,Business travel,Eco,577,2,1,2,3,4,2,2,4,3,4,2,1,2,4,1,5.0,neutral or dissatisfied +19695,10089,Male,Loyal Customer,13,Personal Travel,Eco Plus,266,4,0,4,1,2,4,2,2,4,3,5,5,4,2,41,46.0,neutral or dissatisfied +19696,126639,Male,Loyal Customer,19,Business travel,Business,2156,2,2,2,2,4,4,4,4,5,4,4,3,4,4,0,0.0,satisfied +19697,23274,Male,Loyal Customer,60,Personal Travel,Business,641,2,4,2,4,4,5,5,4,4,2,1,4,4,3,0,0.0,neutral or dissatisfied +19698,77458,Female,Loyal Customer,39,Business travel,Business,3926,5,5,5,5,3,5,5,5,5,5,5,4,5,3,15,0.0,satisfied +19699,120111,Male,Loyal Customer,9,Business travel,Business,1576,2,2,2,2,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +19700,43472,Male,Loyal Customer,58,Business travel,Business,594,1,3,3,3,4,4,4,1,1,1,1,4,1,4,0,8.0,neutral or dissatisfied +19701,57119,Male,Loyal Customer,12,Business travel,Business,3145,3,3,3,3,5,5,5,5,3,5,5,4,5,5,4,0.0,satisfied +19702,18418,Male,Loyal Customer,39,Personal Travel,Eco,750,3,3,3,5,5,3,5,5,2,1,4,2,5,5,0,78.0,neutral or dissatisfied +19703,5142,Male,Loyal Customer,45,Business travel,Business,2253,5,5,5,5,5,4,4,4,4,4,4,3,4,3,5,4.0,satisfied +19704,115364,Female,Loyal Customer,75,Business travel,Eco,390,2,3,2,2,1,3,2,2,2,2,2,3,2,4,24,16.0,neutral or dissatisfied +19705,116740,Female,Loyal Customer,70,Personal Travel,Eco Plus,404,1,3,1,4,3,4,4,2,2,1,2,2,2,2,47,40.0,neutral or dissatisfied +19706,120939,Female,Loyal Customer,47,Business travel,Business,992,5,5,4,5,2,4,5,4,4,4,4,5,4,3,4,0.0,satisfied +19707,58290,Female,Loyal Customer,40,Personal Travel,Eco,594,1,1,1,4,3,1,4,3,4,5,3,4,3,3,13,15.0,neutral or dissatisfied +19708,45048,Female,disloyal Customer,25,Business travel,Eco,265,1,2,1,3,4,1,5,4,4,1,3,3,4,4,85,80.0,neutral or dissatisfied +19709,89625,Male,Loyal Customer,56,Business travel,Eco,1089,2,3,3,3,2,2,2,2,3,4,3,1,3,2,0,0.0,neutral or dissatisfied +19710,61283,Female,Loyal Customer,58,Personal Travel,Eco,967,2,5,2,4,2,5,5,1,1,2,1,3,1,4,2,0.0,neutral or dissatisfied +19711,103222,Male,Loyal Customer,41,Business travel,Business,3865,4,4,1,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +19712,37128,Male,Loyal Customer,42,Business travel,Business,3945,3,5,5,5,1,3,3,3,3,3,3,1,3,2,7,13.0,neutral or dissatisfied +19713,75396,Male,disloyal Customer,23,Business travel,Eco,1452,2,2,2,3,1,2,1,1,4,3,3,3,5,1,0,0.0,neutral or dissatisfied +19714,15364,Male,Loyal Customer,45,Business travel,Business,164,1,1,3,1,2,2,4,5,5,5,5,3,5,5,0,0.0,satisfied +19715,19900,Female,Loyal Customer,52,Business travel,Business,296,4,4,4,4,2,2,1,5,5,5,5,2,5,5,4,0.0,satisfied +19716,92939,Female,Loyal Customer,19,Personal Travel,Eco,134,2,3,2,3,5,2,5,5,1,2,4,3,3,5,0,13.0,neutral or dissatisfied +19717,98803,Female,Loyal Customer,31,Business travel,Business,763,4,4,4,4,4,4,4,4,3,5,5,3,5,4,10,22.0,satisfied +19718,18841,Female,Loyal Customer,32,Business travel,Business,1869,4,4,4,4,4,4,4,4,3,2,4,2,1,4,0,1.0,satisfied +19719,48761,Female,Loyal Customer,57,Business travel,Business,2310,3,3,3,3,4,4,5,3,3,3,3,4,3,3,0,0.0,satisfied +19720,119508,Male,Loyal Customer,51,Business travel,Eco,759,3,5,5,5,2,3,2,2,3,2,3,4,3,2,0,0.0,neutral or dissatisfied +19721,98734,Male,Loyal Customer,49,Business travel,Business,1290,1,1,1,1,3,4,5,5,5,5,5,3,5,4,0,2.0,satisfied +19722,19107,Female,disloyal Customer,24,Business travel,Eco,265,3,0,3,3,4,3,4,4,2,2,2,4,1,4,0,0.0,neutral or dissatisfied +19723,67869,Female,Loyal Customer,21,Personal Travel,Eco,1235,2,5,2,3,2,2,2,2,5,4,5,5,4,2,4,9.0,neutral or dissatisfied +19724,12439,Male,Loyal Customer,9,Personal Travel,Eco,190,3,2,3,3,3,3,3,3,4,4,3,4,3,3,33,26.0,neutral or dissatisfied +19725,71423,Male,Loyal Customer,47,Business travel,Business,2086,3,3,3,3,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +19726,66457,Male,Loyal Customer,54,Personal Travel,Eco,1217,4,3,4,2,3,4,3,3,3,3,5,1,1,3,0,2.0,neutral or dissatisfied +19727,92059,Male,Loyal Customer,46,Business travel,Business,1535,3,3,3,3,3,5,4,2,2,3,2,3,2,4,0,0.0,satisfied +19728,86889,Female,disloyal Customer,36,Business travel,Business,352,4,4,4,5,2,4,2,2,5,2,4,4,4,2,8,0.0,neutral or dissatisfied +19729,22282,Male,Loyal Customer,44,Business travel,Eco,143,3,5,5,5,4,3,4,4,4,4,4,2,4,4,66,68.0,neutral or dissatisfied +19730,39964,Female,Loyal Customer,68,Personal Travel,Eco Plus,1086,3,3,2,3,3,4,4,1,1,2,1,2,1,4,0,0.0,neutral or dissatisfied +19731,5060,Male,disloyal Customer,22,Business travel,Eco,223,3,5,3,1,2,3,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +19732,129475,Male,Loyal Customer,47,Business travel,Business,2611,3,3,5,3,3,3,2,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +19733,79633,Female,Loyal Customer,26,Business travel,Eco,762,4,4,5,5,4,4,1,4,3,4,1,3,1,4,0,6.0,neutral or dissatisfied +19734,109876,Female,Loyal Customer,23,Business travel,Business,1716,4,1,1,1,4,4,4,4,3,3,3,4,4,4,19,2.0,neutral or dissatisfied +19735,116348,Male,Loyal Customer,25,Personal Travel,Eco,308,5,4,5,2,3,5,3,3,4,2,5,3,5,3,0,3.0,satisfied +19736,5291,Female,Loyal Customer,55,Personal Travel,Eco,190,2,5,2,3,2,4,4,1,1,2,1,3,1,4,32,32.0,neutral or dissatisfied +19737,972,Male,Loyal Customer,44,Business travel,Business,3876,2,2,2,2,3,5,5,5,5,5,4,3,5,4,0,0.0,satisfied +19738,113888,Male,Loyal Customer,53,Business travel,Business,2295,1,1,1,1,5,5,5,4,4,4,4,5,4,4,40,34.0,satisfied +19739,12054,Female,Loyal Customer,40,Business travel,Eco,376,2,4,2,2,2,2,2,2,4,5,4,3,4,2,19,11.0,neutral or dissatisfied +19740,123303,Male,Loyal Customer,46,Business travel,Business,1606,5,5,5,5,2,5,5,5,5,5,5,3,5,5,21,12.0,satisfied +19741,88543,Female,Loyal Customer,38,Personal Travel,Eco,404,5,3,5,1,5,5,5,5,1,2,5,3,4,5,0,0.0,satisfied +19742,30624,Female,Loyal Customer,51,Business travel,Business,3278,4,3,3,3,1,3,4,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +19743,40534,Female,Loyal Customer,47,Business travel,Eco,391,2,3,3,3,3,3,5,2,2,2,2,3,2,4,0,0.0,satisfied +19744,96969,Male,Loyal Customer,60,Business travel,Business,883,2,5,2,2,5,4,5,5,5,5,5,3,5,4,58,41.0,satisfied +19745,118461,Male,Loyal Customer,58,Business travel,Business,370,2,2,2,2,3,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +19746,56124,Female,Loyal Customer,46,Business travel,Business,1400,3,3,2,3,4,4,5,5,5,5,5,4,5,3,1,0.0,satisfied +19747,30731,Female,Loyal Customer,27,Business travel,Eco,1069,4,5,5,5,4,4,4,4,5,2,3,3,5,4,0,0.0,satisfied +19748,41505,Male,Loyal Customer,35,Business travel,Business,3293,1,1,1,1,5,3,2,4,4,5,4,2,4,4,43,59.0,satisfied +19749,122099,Female,Loyal Customer,43,Personal Travel,Eco,130,2,0,2,2,3,4,4,4,4,2,4,5,4,4,3,5.0,neutral or dissatisfied +19750,27319,Male,disloyal Customer,36,Business travel,Eco,956,1,1,1,2,1,1,1,1,5,1,2,5,4,1,20,2.0,neutral or dissatisfied +19751,60231,Female,disloyal Customer,25,Business travel,Eco,1120,3,3,3,3,5,3,5,5,4,3,4,2,4,5,5,12.0,neutral or dissatisfied +19752,60259,Female,Loyal Customer,20,Personal Travel,Eco,1506,2,4,2,3,2,2,2,2,2,2,4,2,4,2,0,8.0,neutral or dissatisfied +19753,9935,Male,Loyal Customer,56,Business travel,Business,3468,1,1,1,1,4,5,4,5,5,4,5,5,5,3,0,0.0,satisfied +19754,124971,Female,disloyal Customer,26,Business travel,Business,184,2,1,1,2,4,1,4,4,5,4,5,3,4,4,26,55.0,neutral or dissatisfied +19755,69069,Female,Loyal Customer,16,Business travel,Business,1389,5,3,5,5,3,3,3,3,3,3,4,3,5,3,5,0.0,satisfied +19756,96809,Female,disloyal Customer,45,Business travel,Eco,849,3,4,4,3,1,4,1,1,4,3,4,2,4,1,7,3.0,neutral or dissatisfied +19757,127637,Female,Loyal Customer,63,Personal Travel,Eco,1773,1,1,1,2,4,2,3,1,1,1,1,3,1,3,10,17.0,neutral or dissatisfied +19758,86167,Male,Loyal Customer,30,Business travel,Business,226,4,1,4,4,4,4,4,4,3,2,5,4,4,4,3,0.0,satisfied +19759,72779,Female,Loyal Customer,26,Business travel,Business,2699,2,4,4,4,2,2,2,2,3,1,3,1,4,2,3,0.0,neutral or dissatisfied +19760,7624,Female,Loyal Customer,49,Business travel,Business,767,3,3,3,3,5,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +19761,124142,Female,Loyal Customer,25,Business travel,Business,529,1,1,4,1,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +19762,81492,Male,Loyal Customer,21,Personal Travel,Eco,528,2,5,2,3,3,2,3,3,3,2,5,3,5,3,64,69.0,neutral or dissatisfied +19763,26991,Male,Loyal Customer,45,Business travel,Eco,867,1,3,3,3,1,1,1,1,1,3,4,1,4,1,0,0.0,neutral or dissatisfied +19764,120392,Male,Loyal Customer,37,Business travel,Business,2253,3,3,3,3,3,5,5,4,4,4,4,5,4,3,0,12.0,satisfied +19765,73717,Female,Loyal Customer,37,Business travel,Business,192,4,5,5,5,1,4,3,3,3,3,4,1,3,3,72,65.0,neutral or dissatisfied +19766,105441,Female,Loyal Customer,18,Business travel,Business,2699,3,3,3,3,5,5,5,5,5,3,4,4,5,5,0,0.0,satisfied +19767,11437,Female,disloyal Customer,50,Business travel,Business,201,4,4,4,5,3,4,3,3,5,4,4,3,4,3,0,0.0,satisfied +19768,76301,Female,Loyal Customer,24,Business travel,Business,2182,2,2,2,2,3,4,3,3,5,5,4,3,4,3,2,0.0,satisfied +19769,91198,Female,Loyal Customer,38,Personal Travel,Eco,406,2,4,2,4,5,2,1,5,4,4,5,5,5,5,9,0.0,neutral or dissatisfied +19770,129145,Male,Loyal Customer,54,Business travel,Business,1590,3,5,5,5,1,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +19771,101678,Female,Loyal Customer,42,Business travel,Business,1500,5,5,5,5,3,4,5,2,2,2,2,3,2,5,2,0.0,satisfied +19772,99063,Male,Loyal Customer,41,Business travel,Business,237,3,3,3,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +19773,3524,Male,Loyal Customer,57,Business travel,Business,2846,4,3,3,3,2,3,3,4,4,4,4,4,4,4,38,40.0,neutral or dissatisfied +19774,46354,Male,Loyal Customer,59,Business travel,Business,1585,3,4,4,4,3,3,3,3,3,3,3,3,3,1,0,72.0,neutral or dissatisfied +19775,69828,Female,Loyal Customer,56,Business travel,Business,1055,3,3,3,3,2,5,5,4,4,5,4,4,4,4,0,0.0,satisfied +19776,40919,Female,Loyal Customer,8,Personal Travel,Eco,532,3,4,3,4,3,3,3,3,4,5,5,4,5,3,0,0.0,neutral or dissatisfied +19777,109670,Female,Loyal Customer,41,Business travel,Eco,402,5,1,1,1,5,5,5,5,2,2,5,1,2,5,18,0.0,satisfied +19778,94825,Female,disloyal Customer,20,Business travel,Eco,239,1,4,1,2,4,1,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +19779,30438,Male,Loyal Customer,66,Personal Travel,Eco,851,2,3,2,3,3,2,3,3,2,2,2,1,2,3,1,3.0,neutral or dissatisfied +19780,87841,Male,Loyal Customer,33,Personal Travel,Eco,214,2,4,2,1,1,2,5,1,5,2,4,4,4,1,0,2.0,neutral or dissatisfied +19781,16695,Female,disloyal Customer,62,Business travel,Business,169,4,4,4,4,1,4,1,1,5,3,5,4,4,1,0,0.0,neutral or dissatisfied +19782,110592,Female,Loyal Customer,17,Personal Travel,Eco,674,5,4,5,2,5,5,5,5,4,4,5,4,5,5,29,30.0,satisfied +19783,51279,Female,Loyal Customer,60,Business travel,Eco Plus,238,5,4,4,4,1,5,5,4,4,5,4,3,4,2,0,11.0,satisfied +19784,120786,Male,Loyal Customer,47,Personal Travel,Eco,678,2,2,2,2,5,2,5,5,1,5,2,1,2,5,0,0.0,neutral or dissatisfied +19785,100471,Female,Loyal Customer,39,Business travel,Business,759,1,1,1,1,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +19786,38202,Male,Loyal Customer,20,Business travel,Eco Plus,1197,0,3,0,2,2,0,2,2,2,1,4,2,2,2,18,9.0,satisfied +19787,75072,Male,Loyal Customer,35,Personal Travel,Eco,2611,2,2,2,2,2,2,2,2,3,2,2,1,2,2,0,0.0,neutral or dissatisfied +19788,81935,Female,disloyal Customer,34,Business travel,Business,1535,4,4,4,2,3,4,3,3,3,4,4,5,4,3,21,24.0,neutral or dissatisfied +19789,34495,Male,Loyal Customer,54,Personal Travel,Eco,1990,0,3,0,4,2,0,2,2,3,3,3,2,3,2,0,0.0,satisfied +19790,33252,Male,disloyal Customer,37,Business travel,Eco Plus,101,3,3,3,3,2,3,2,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +19791,8129,Female,Loyal Customer,48,Business travel,Business,3563,5,5,5,5,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +19792,62168,Male,disloyal Customer,44,Business travel,Eco,1170,3,3,3,3,4,3,4,4,2,5,3,4,2,4,22,19.0,neutral or dissatisfied +19793,112425,Female,Loyal Customer,32,Business travel,Business,948,1,3,3,3,1,1,1,1,2,2,4,4,4,1,28,23.0,neutral or dissatisfied +19794,18196,Male,Loyal Customer,46,Business travel,Business,228,4,4,4,4,4,3,5,4,4,4,4,5,4,2,103,93.0,satisfied +19795,64495,Female,Loyal Customer,43,Business travel,Business,2306,3,3,3,3,4,4,4,3,4,5,4,4,3,4,624,615.0,satisfied +19796,28652,Male,Loyal Customer,54,Personal Travel,Eco,2404,2,3,2,3,5,2,5,5,2,1,4,4,4,5,0,0.0,neutral or dissatisfied +19797,39617,Male,Loyal Customer,58,Personal Travel,Eco,965,3,5,3,4,1,3,1,1,5,4,4,5,4,1,31,32.0,neutral or dissatisfied +19798,58668,Female,Loyal Customer,56,Personal Travel,Eco Plus,867,4,4,4,3,3,4,3,5,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +19799,42455,Female,Loyal Customer,32,Personal Travel,Eco,866,3,4,3,3,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +19800,76014,Male,disloyal Customer,41,Business travel,Business,311,5,5,5,4,3,5,3,3,5,2,5,5,4,3,0,0.0,satisfied +19801,104732,Male,Loyal Customer,54,Business travel,Business,1407,4,4,4,4,3,5,5,5,5,5,5,4,5,3,32,32.0,satisfied +19802,114276,Female,Loyal Customer,10,Personal Travel,Eco,862,4,4,4,4,3,4,3,3,4,4,4,2,4,3,10,0.0,satisfied +19803,104431,Female,Loyal Customer,23,Personal Travel,Eco,1024,3,2,3,4,2,3,1,2,2,1,4,2,3,2,0,0.0,neutral or dissatisfied +19804,70309,Female,Loyal Customer,56,Personal Travel,Eco,334,3,5,3,3,2,4,5,5,5,3,5,5,5,5,0,0.0,neutral or dissatisfied +19805,78419,Male,Loyal Customer,38,Business travel,Eco,201,2,2,2,2,2,2,2,2,4,3,3,3,3,2,0,0.0,neutral or dissatisfied +19806,9452,Male,Loyal Customer,51,Personal Travel,Eco,368,2,4,2,3,3,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +19807,4687,Male,Loyal Customer,17,Personal Travel,Eco,364,0,5,0,4,5,0,5,5,5,3,5,5,4,5,0,0.0,satisfied +19808,61610,Male,Loyal Customer,48,Business travel,Business,1379,5,5,5,5,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +19809,108676,Male,Loyal Customer,34,Business travel,Business,577,4,4,4,4,5,5,5,3,2,4,4,5,4,5,182,193.0,satisfied +19810,24054,Male,Loyal Customer,67,Personal Travel,Eco,562,2,4,2,4,1,2,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +19811,88859,Male,Loyal Customer,58,Business travel,Business,515,3,3,3,3,4,5,5,5,5,5,5,4,5,5,17,12.0,satisfied +19812,45230,Male,Loyal Customer,46,Business travel,Business,3455,1,5,5,5,1,3,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +19813,68699,Female,Loyal Customer,50,Personal Travel,Eco,237,2,4,2,1,5,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +19814,41088,Female,Loyal Customer,32,Business travel,Business,2270,0,5,1,3,5,5,5,5,2,2,2,4,1,5,0,0.0,satisfied +19815,2522,Male,Loyal Customer,43,Business travel,Business,2343,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +19816,99736,Female,disloyal Customer,20,Business travel,Eco,255,3,0,3,2,5,3,4,5,4,5,5,4,5,5,12,18.0,neutral or dissatisfied +19817,58144,Male,Loyal Customer,39,Personal Travel,Business,925,1,3,1,4,5,5,2,2,2,1,2,5,2,3,0,0.0,neutral or dissatisfied +19818,98596,Female,Loyal Customer,28,Business travel,Business,3124,4,4,4,4,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +19819,116843,Male,Loyal Customer,52,Personal Travel,Business,646,4,3,5,3,5,2,3,3,3,5,3,4,3,2,0,0.0,satisfied +19820,102817,Female,Loyal Customer,52,Business travel,Business,2244,2,2,2,2,2,4,4,5,5,4,5,5,5,3,24,17.0,satisfied +19821,78387,Male,Loyal Customer,41,Business travel,Eco,980,4,1,1,1,4,4,4,4,2,4,4,2,3,4,0,0.0,neutral or dissatisfied +19822,116796,Male,Loyal Customer,12,Personal Travel,Eco Plus,390,3,4,3,1,5,3,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +19823,43018,Male,Loyal Customer,61,Business travel,Business,236,2,1,1,1,2,2,2,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +19824,122883,Female,Loyal Customer,59,Personal Travel,Eco,226,3,5,3,4,4,4,5,1,1,3,1,4,1,3,1,18.0,neutral or dissatisfied +19825,6004,Female,Loyal Customer,43,Business travel,Business,2782,3,3,2,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +19826,108088,Male,Loyal Customer,32,Business travel,Business,997,3,3,3,3,4,4,4,4,5,4,5,4,4,4,12,11.0,satisfied +19827,27862,Female,disloyal Customer,28,Business travel,Eco Plus,1448,0,0,0,3,5,0,5,5,3,1,2,3,5,5,0,0.0,satisfied +19828,53357,Female,Loyal Customer,29,Business travel,Eco,1452,3,1,1,1,3,3,3,3,4,4,4,3,3,3,0,16.0,neutral or dissatisfied +19829,23795,Female,Loyal Customer,40,Business travel,Business,2472,2,5,5,5,2,1,2,2,2,2,2,4,2,3,4,15.0,neutral or dissatisfied +19830,117628,Female,Loyal Customer,61,Personal Travel,Eco,347,3,5,1,3,5,4,3,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +19831,97160,Male,Loyal Customer,42,Personal Travel,Eco,1390,2,5,2,4,5,2,5,5,1,5,3,5,5,5,24,9.0,neutral or dissatisfied +19832,22278,Male,Loyal Customer,59,Business travel,Eco,208,4,2,2,2,4,4,4,4,2,5,5,4,2,4,90,119.0,satisfied +19833,104656,Male,Loyal Customer,42,Business travel,Business,2772,3,2,3,3,3,5,5,4,4,4,4,5,4,3,41,34.0,satisfied +19834,23994,Male,Loyal Customer,42,Business travel,Business,3933,2,2,2,2,3,1,2,5,5,5,5,2,5,1,0,0.0,satisfied +19835,833,Male,Loyal Customer,47,Business travel,Business,229,5,5,3,5,3,4,5,3,3,4,3,3,3,5,36,27.0,satisfied +19836,93525,Male,Loyal Customer,29,Business travel,Eco,1218,1,4,5,4,1,1,1,1,1,2,3,4,4,1,0,0.0,neutral or dissatisfied +19837,70903,Female,Loyal Customer,41,Business travel,Eco,1721,4,5,5,5,4,4,4,4,1,2,3,4,4,4,0,0.0,neutral or dissatisfied +19838,56872,Male,Loyal Customer,59,Business travel,Business,2565,4,4,4,4,4,3,3,3,5,3,5,3,5,3,3,0.0,satisfied +19839,88351,Male,Loyal Customer,61,Business travel,Business,2249,5,5,5,5,2,4,4,4,4,4,4,4,4,5,1,0.0,satisfied +19840,30201,Female,disloyal Customer,27,Business travel,Eco Plus,261,1,1,1,1,4,1,4,4,3,5,2,4,5,4,0,0.0,neutral or dissatisfied +19841,8723,Male,Loyal Customer,35,Personal Travel,Eco,227,2,5,2,2,1,2,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +19842,54329,Male,disloyal Customer,28,Personal Travel,Eco,1597,2,4,2,1,1,2,1,1,4,4,4,3,4,1,0,0.0,neutral or dissatisfied +19843,119287,Female,Loyal Customer,42,Business travel,Business,2556,1,1,1,1,2,4,5,4,4,5,5,3,4,3,0,0.0,satisfied +19844,23049,Male,Loyal Customer,58,Business travel,Business,2260,1,1,1,1,3,5,4,4,4,5,4,3,4,4,0,0.0,satisfied +19845,48674,Male,Loyal Customer,51,Business travel,Business,134,2,2,5,2,5,4,5,5,5,5,4,5,5,3,0,0.0,satisfied +19846,64998,Female,disloyal Customer,35,Business travel,Eco,247,2,2,2,4,4,2,5,4,2,1,4,2,3,4,22,28.0,neutral or dissatisfied +19847,14332,Female,Loyal Customer,15,Personal Travel,Eco,395,3,5,3,1,4,3,5,4,3,4,5,3,5,4,47,37.0,neutral or dissatisfied +19848,84718,Female,Loyal Customer,39,Business travel,Business,547,4,4,4,4,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +19849,81059,Male,Loyal Customer,18,Personal Travel,Eco,1399,2,2,2,3,1,2,1,1,1,4,3,4,3,1,1,0.0,neutral or dissatisfied +19850,128400,Male,Loyal Customer,44,Business travel,Eco,338,1,1,1,1,1,1,1,1,4,5,4,2,3,1,7,2.0,neutral or dissatisfied +19851,17705,Male,Loyal Customer,39,Business travel,Business,311,2,3,4,3,2,4,4,2,2,2,2,3,2,2,0,6.0,neutral or dissatisfied +19852,72162,Female,Loyal Customer,60,Business travel,Business,2610,4,4,2,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +19853,100488,Female,disloyal Customer,28,Business travel,Business,580,4,4,4,2,3,4,3,3,5,5,5,5,5,3,0,0.0,neutral or dissatisfied +19854,112014,Male,Loyal Customer,30,Business travel,Business,3636,5,5,5,5,4,4,4,4,4,3,5,5,4,4,2,1.0,satisfied +19855,126423,Female,Loyal Customer,57,Business travel,Business,1778,5,5,5,5,3,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +19856,125583,Male,Loyal Customer,35,Personal Travel,Eco Plus,226,3,4,0,2,3,0,3,3,3,2,4,5,5,3,0,9.0,neutral or dissatisfied +19857,46982,Female,Loyal Customer,38,Personal Travel,Eco,853,3,4,3,4,5,3,5,5,4,5,4,5,5,5,11,22.0,neutral or dissatisfied +19858,1497,Male,Loyal Customer,55,Business travel,Business,1834,3,3,3,3,2,2,4,5,5,5,5,1,5,5,0,0.0,satisfied +19859,116794,Female,Loyal Customer,63,Personal Travel,Eco Plus,333,3,3,3,3,2,4,3,5,5,3,5,4,5,2,2,6.0,neutral or dissatisfied +19860,113934,Male,Loyal Customer,24,Personal Travel,Business,1728,3,3,3,5,2,3,2,2,3,5,5,3,1,2,2,0.0,neutral or dissatisfied +19861,21542,Female,Loyal Customer,42,Personal Travel,Eco,377,3,4,3,4,4,5,4,5,5,3,5,5,5,5,6,0.0,neutral or dissatisfied +19862,16064,Female,Loyal Customer,18,Business travel,Business,2792,2,2,2,2,5,5,5,5,1,5,3,1,5,5,0,0.0,satisfied +19863,25733,Male,Loyal Customer,21,Personal Travel,Eco,528,3,5,5,1,1,5,1,1,4,5,4,5,4,1,55,34.0,neutral or dissatisfied +19864,47290,Female,Loyal Customer,38,Business travel,Eco,584,2,1,1,1,2,3,2,2,1,1,3,4,3,2,0,0.0,neutral or dissatisfied +19865,103701,Male,Loyal Customer,54,Personal Travel,Eco,405,0,2,0,4,4,0,4,4,4,1,3,4,4,4,0,0.0,satisfied +19866,35379,Male,disloyal Customer,36,Business travel,Eco,610,3,0,3,4,2,3,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +19867,11622,Female,Loyal Customer,65,Personal Travel,Eco,657,4,2,4,3,5,4,4,3,3,4,5,1,3,4,0,25.0,neutral or dissatisfied +19868,7764,Female,disloyal Customer,35,Business travel,Business,990,1,0,0,3,2,0,3,2,4,4,5,5,4,2,44,55.0,neutral or dissatisfied +19869,27301,Male,disloyal Customer,25,Business travel,Eco,987,1,0,0,1,3,0,3,3,2,1,4,5,3,3,17,12.0,neutral or dissatisfied +19870,2366,Female,Loyal Customer,61,Personal Travel,Eco,925,3,5,3,4,2,5,5,5,5,3,5,4,5,4,16,18.0,neutral or dissatisfied +19871,66090,Male,Loyal Customer,42,Business travel,Business,1055,4,2,4,4,5,4,5,3,3,3,3,5,3,4,33,18.0,satisfied +19872,108735,Male,Loyal Customer,40,Business travel,Business,1917,1,1,2,1,5,4,4,5,5,5,5,5,5,5,0,3.0,satisfied +19873,117316,Female,Loyal Customer,9,Personal Travel,Eco Plus,621,3,5,3,4,4,3,4,4,2,4,4,2,2,4,20,15.0,neutral or dissatisfied +19874,66131,Male,Loyal Customer,68,Personal Travel,Eco,583,2,4,2,4,5,2,4,5,1,1,4,4,3,5,0,0.0,neutral or dissatisfied +19875,119867,Male,Loyal Customer,67,Personal Travel,Eco,1095,4,5,4,1,3,4,3,3,4,1,3,3,2,3,0,0.0,neutral or dissatisfied +19876,90559,Female,disloyal Customer,23,Business travel,Eco,240,1,0,1,3,1,1,1,1,3,5,5,4,4,1,0,2.0,neutral or dissatisfied +19877,106537,Female,disloyal Customer,30,Business travel,Eco,321,1,3,1,4,5,1,5,5,2,2,4,1,3,5,77,79.0,neutral or dissatisfied +19878,59717,Female,disloyal Customer,45,Business travel,Eco Plus,964,1,1,1,3,3,1,3,3,2,2,4,2,3,3,0,0.0,neutral or dissatisfied +19879,121969,Female,Loyal Customer,45,Business travel,Business,1611,2,1,1,1,1,3,3,2,2,1,2,2,2,2,0,0.0,neutral or dissatisfied +19880,47917,Female,Loyal Customer,18,Personal Travel,Eco,748,3,5,3,1,3,3,3,3,4,2,4,3,5,3,0,0.0,neutral or dissatisfied +19881,23198,Female,Loyal Customer,30,Personal Travel,Eco Plus,300,4,3,4,3,3,4,3,3,3,5,4,2,4,3,0,0.0,neutral or dissatisfied +19882,58497,Female,Loyal Customer,47,Business travel,Eco,719,2,4,4,4,5,3,3,2,2,2,2,2,2,4,55,43.0,neutral or dissatisfied +19883,111321,Male,Loyal Customer,35,Business travel,Business,283,2,1,1,1,5,4,3,2,2,2,2,1,2,2,0,6.0,neutral or dissatisfied +19884,8871,Female,Loyal Customer,53,Business travel,Business,3285,3,3,3,3,4,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +19885,65310,Female,Loyal Customer,41,Business travel,Business,3990,4,2,2,2,5,4,3,4,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +19886,40636,Male,Loyal Customer,46,Business travel,Eco Plus,391,1,0,0,3,4,1,4,4,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +19887,31593,Female,Loyal Customer,55,Business travel,Business,3962,1,4,5,4,1,3,3,1,1,2,1,4,1,1,18,41.0,neutral or dissatisfied +19888,80772,Male,disloyal Customer,23,Business travel,Business,440,0,0,0,4,1,0,1,1,5,4,4,4,4,1,0,0.0,satisfied +19889,84678,Female,Loyal Customer,24,Business travel,Eco,2182,2,4,4,4,2,2,4,2,3,5,4,4,4,2,15,9.0,neutral or dissatisfied +19890,59462,Male,disloyal Customer,23,Business travel,Eco,758,2,2,2,2,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +19891,9702,Male,Loyal Customer,13,Personal Travel,Eco,212,2,3,2,3,4,2,4,4,2,3,2,1,4,4,43,38.0,neutral or dissatisfied +19892,5853,Female,Loyal Customer,59,Business travel,Business,2846,3,3,2,3,2,5,4,5,5,5,5,5,5,5,18,5.0,satisfied +19893,110961,Male,disloyal Customer,27,Business travel,Business,197,1,1,1,4,5,1,5,5,5,4,4,5,4,5,27,3.0,neutral or dissatisfied +19894,60408,Female,Loyal Customer,18,Personal Travel,Eco,1452,3,1,3,2,2,3,5,2,4,3,2,2,3,2,0,0.0,neutral or dissatisfied +19895,95758,Female,Loyal Customer,36,Personal Travel,Eco,419,2,3,2,3,3,2,3,3,2,2,3,2,3,3,22,22.0,neutral or dissatisfied +19896,58697,Male,disloyal Customer,16,Business travel,Eco,960,1,1,1,4,1,3,3,3,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +19897,85541,Female,Loyal Customer,49,Business travel,Business,259,1,1,1,1,5,5,5,4,4,4,4,4,4,5,15,12.0,satisfied +19898,89294,Male,Loyal Customer,25,Business travel,Business,3786,4,5,5,5,4,4,4,4,4,1,2,2,3,4,0,0.0,neutral or dissatisfied +19899,16416,Female,Loyal Customer,25,Business travel,Business,2810,2,2,2,2,4,4,4,4,5,5,1,1,5,4,0,2.0,satisfied +19900,112129,Male,Loyal Customer,43,Business travel,Business,977,5,5,5,5,5,5,4,2,2,2,2,4,2,5,101,72.0,satisfied +19901,82997,Male,Loyal Customer,41,Business travel,Business,2417,3,3,3,3,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +19902,40367,Female,Loyal Customer,50,Business travel,Business,3330,1,3,3,3,4,3,4,1,1,1,1,3,1,1,3,5.0,neutral or dissatisfied +19903,29962,Female,Loyal Customer,26,Business travel,Eco,571,5,3,3,3,5,5,5,5,5,1,3,3,2,5,0,0.0,satisfied +19904,104223,Male,Loyal Customer,24,Business travel,Business,3461,1,2,2,2,1,1,1,1,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +19905,115139,Male,Loyal Customer,40,Business travel,Business,1710,1,2,2,2,2,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +19906,118186,Female,Loyal Customer,36,Business travel,Business,1444,2,3,3,3,1,4,4,2,2,2,2,2,2,2,61,29.0,neutral or dissatisfied +19907,118345,Female,Loyal Customer,39,Personal Travel,Eco,602,2,5,2,3,2,2,3,2,3,5,5,4,5,2,38,31.0,neutral or dissatisfied +19908,11073,Female,Loyal Customer,45,Personal Travel,Eco,247,1,5,1,3,3,4,4,2,2,1,5,5,2,3,0,0.0,neutral or dissatisfied +19909,52014,Female,Loyal Customer,46,Business travel,Business,2786,3,3,3,3,4,2,1,4,4,4,4,5,4,4,0,4.0,satisfied +19910,23125,Male,Loyal Customer,45,Business travel,Eco,646,5,5,4,4,5,5,5,5,3,5,1,1,4,5,0,2.0,satisfied +19911,3788,Female,disloyal Customer,37,Business travel,Eco,199,4,2,4,3,2,4,2,2,3,3,4,4,4,2,0,17.0,neutral or dissatisfied +19912,12517,Male,Loyal Customer,22,Business travel,Eco,871,4,1,1,1,4,4,5,4,1,3,1,3,1,4,8,4.0,satisfied +19913,52728,Male,Loyal Customer,31,Personal Travel,Eco,406,4,4,4,1,5,4,5,5,4,3,4,5,4,5,0,0.0,satisfied +19914,96694,Female,Loyal Customer,52,Business travel,Business,696,2,2,2,2,3,5,5,4,4,4,4,4,4,5,56,47.0,satisfied +19915,29264,Female,Loyal Customer,34,Business travel,Business,3393,4,5,5,5,5,4,4,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +19916,93898,Female,Loyal Customer,58,Personal Travel,Eco,588,1,4,1,2,2,4,5,2,2,1,2,3,2,4,26,13.0,neutral or dissatisfied +19917,16960,Female,Loyal Customer,34,Business travel,Business,1131,1,1,1,1,3,3,3,1,1,1,1,3,1,4,14,0.0,neutral or dissatisfied +19918,33052,Female,Loyal Customer,46,Personal Travel,Eco,101,2,4,2,4,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +19919,100226,Male,disloyal Customer,23,Business travel,Eco,1165,4,3,3,1,4,3,4,4,4,3,5,5,5,4,0,0.0,satisfied +19920,102717,Male,Loyal Customer,7,Personal Travel,Eco,255,4,3,4,1,2,4,2,2,2,5,3,5,1,2,32,31.0,neutral or dissatisfied +19921,64558,Female,Loyal Customer,45,Business travel,Business,1787,3,3,3,3,4,5,5,4,4,4,4,3,4,5,53,45.0,satisfied +19922,72680,Female,Loyal Customer,9,Personal Travel,Eco,1119,4,3,4,4,4,2,2,1,1,4,3,2,1,2,154,155.0,neutral or dissatisfied +19923,31877,Female,disloyal Customer,35,Business travel,Eco,1419,3,3,3,3,3,2,2,2,4,4,4,2,1,2,0,0.0,neutral or dissatisfied +19924,32738,Male,Loyal Customer,33,Business travel,Business,1888,2,3,3,3,4,4,2,4,4,5,3,3,3,4,6,11.0,neutral or dissatisfied +19925,10520,Male,Loyal Customer,45,Business travel,Business,2880,4,4,5,4,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +19926,52527,Female,Loyal Customer,40,Business travel,Eco,110,5,5,5,5,5,5,5,5,5,3,5,3,1,5,0,0.0,satisfied +19927,52116,Female,Loyal Customer,46,Personal Travel,Eco,351,3,5,3,3,5,4,4,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +19928,46795,Female,Loyal Customer,51,Business travel,Business,2884,4,1,1,1,2,2,2,4,4,4,4,2,4,3,0,15.0,neutral or dissatisfied +19929,57283,Female,Loyal Customer,70,Personal Travel,Eco,628,1,5,1,3,5,5,4,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +19930,118396,Male,Loyal Customer,44,Business travel,Business,338,1,1,1,1,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +19931,73935,Female,Loyal Customer,42,Business travel,Eco,2342,2,2,2,2,5,4,4,2,2,2,2,2,2,1,29,12.0,neutral or dissatisfied +19932,2043,Female,Loyal Customer,28,Business travel,Business,3019,3,3,3,3,4,4,4,4,5,5,5,3,4,4,0,0.0,satisfied +19933,81147,Male,Loyal Customer,50,Business travel,Business,1310,1,1,1,1,5,5,5,4,4,4,4,4,4,3,22,51.0,satisfied +19934,83220,Male,Loyal Customer,67,Personal Travel,Business,1979,1,3,1,1,2,5,4,3,3,1,2,1,3,1,0,0.0,neutral or dissatisfied +19935,82982,Female,Loyal Customer,39,Business travel,Business,3000,5,5,5,5,4,5,4,5,5,5,5,5,5,4,44,107.0,satisfied +19936,45490,Female,Loyal Customer,70,Personal Travel,Eco,522,4,3,5,1,3,1,2,2,2,5,2,4,2,4,0,0.0,neutral or dissatisfied +19937,60648,Male,Loyal Customer,49,Business travel,Eco,1620,3,2,2,2,3,3,3,3,4,5,4,2,3,3,0,0.0,neutral or dissatisfied +19938,84271,Male,Loyal Customer,41,Business travel,Eco,334,3,4,4,4,3,3,3,3,4,1,4,1,4,3,0,0.0,neutral or dissatisfied +19939,117759,Female,Loyal Customer,13,Business travel,Eco,1670,1,2,2,2,1,2,2,1,2,4,2,4,4,1,0,25.0,neutral or dissatisfied +19940,19428,Female,Loyal Customer,22,Business travel,Eco,645,5,5,5,5,5,5,3,5,1,5,1,1,2,5,0,0.0,satisfied +19941,22138,Male,Loyal Customer,39,Personal Travel,Eco,566,5,1,5,3,1,5,1,1,2,4,4,1,4,1,14,4.0,satisfied +19942,21230,Female,Loyal Customer,41,Personal Travel,Eco,192,1,4,1,3,5,1,5,5,4,5,5,5,4,5,0,0.0,neutral or dissatisfied +19943,17188,Female,Loyal Customer,37,Personal Travel,Eco,643,4,4,4,5,1,4,1,1,4,3,5,4,5,1,4,0.0,neutral or dissatisfied +19944,21952,Male,Loyal Customer,53,Business travel,Business,2471,1,1,5,1,5,1,3,4,4,4,4,2,4,5,0,0.0,satisfied +19945,40005,Female,Loyal Customer,56,Business travel,Eco,575,4,4,4,4,4,1,5,4,4,4,4,3,4,5,0,0.0,satisfied +19946,84898,Female,Loyal Customer,61,Personal Travel,Eco,534,2,4,3,1,2,5,5,1,1,3,1,3,1,5,26,15.0,neutral or dissatisfied +19947,38681,Female,Loyal Customer,68,Personal Travel,Eco,2611,4,1,4,4,5,4,4,4,4,4,4,1,4,1,63,52.0,neutral or dissatisfied +19948,59252,Female,Loyal Customer,18,Business travel,Business,3904,4,4,4,4,4,4,4,5,4,5,5,4,3,4,0,0.0,satisfied +19949,109633,Male,Loyal Customer,48,Business travel,Business,829,1,1,1,1,3,4,5,5,5,5,5,3,5,4,7,0.0,satisfied +19950,80742,Female,Loyal Customer,37,Personal Travel,Eco,448,4,4,5,1,5,5,2,5,3,2,4,5,4,5,0,7.0,neutral or dissatisfied +19951,42898,Male,disloyal Customer,44,Business travel,Eco,200,3,0,3,3,5,3,3,5,3,2,2,1,5,5,0,0.0,neutral or dissatisfied +19952,37098,Male,Loyal Customer,52,Business travel,Business,1189,2,2,2,2,1,3,5,4,4,4,4,2,4,2,0,0.0,satisfied +19953,9205,Male,Loyal Customer,55,Business travel,Business,1681,3,5,4,5,1,4,3,4,4,4,3,4,4,1,0,3.0,neutral or dissatisfied +19954,90657,Male,Loyal Customer,39,Business travel,Business,2510,0,0,0,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +19955,64907,Male,Loyal Customer,55,Business travel,Business,2376,1,5,5,5,3,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +19956,36805,Male,Loyal Customer,22,Personal Travel,Eco Plus,2704,3,5,3,3,3,2,4,5,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +19957,61715,Female,Loyal Customer,59,Business travel,Business,1605,3,3,3,3,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +19958,12747,Male,Loyal Customer,68,Personal Travel,Eco,689,2,3,2,1,2,2,5,2,5,2,5,2,4,2,97,96.0,neutral or dissatisfied +19959,31924,Male,Loyal Customer,45,Business travel,Business,2846,2,2,2,2,5,4,4,4,4,4,5,4,4,5,0,0.0,satisfied +19960,23955,Female,disloyal Customer,43,Business travel,Eco,536,4,0,3,2,4,3,4,4,3,2,3,4,1,4,0,0.0,neutral or dissatisfied +19961,55479,Male,Loyal Customer,22,Business travel,Business,1825,5,5,5,5,4,4,4,4,3,3,5,4,4,4,0,0.0,satisfied +19962,33788,Female,Loyal Customer,58,Business travel,Eco,588,4,1,1,1,5,3,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +19963,14065,Male,Loyal Customer,23,Business travel,Business,726,4,4,4,4,4,4,4,4,2,1,4,3,5,4,0,0.0,satisfied +19964,91224,Female,Loyal Customer,8,Personal Travel,Eco,404,1,5,1,3,4,1,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +19965,128236,Female,Loyal Customer,36,Personal Travel,Eco,602,3,4,3,3,2,3,2,2,4,5,4,3,4,2,1,0.0,neutral or dissatisfied +19966,94768,Male,Loyal Customer,61,Business travel,Business,189,4,4,4,4,5,3,4,3,3,3,4,2,3,2,72,70.0,neutral or dissatisfied +19967,16897,Male,Loyal Customer,23,Personal Travel,Eco,746,4,4,4,3,1,4,1,1,4,2,5,5,5,1,1,0.0,neutral or dissatisfied +19968,60954,Female,Loyal Customer,7,Business travel,Business,888,1,3,3,3,1,2,1,1,3,4,3,4,3,1,12,5.0,neutral or dissatisfied +19969,120604,Male,Loyal Customer,52,Business travel,Business,453,4,4,4,4,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +19970,70340,Female,disloyal Customer,17,Business travel,Eco,986,2,2,2,3,4,2,4,4,3,2,4,4,3,4,10,0.0,neutral or dissatisfied +19971,102323,Male,Loyal Customer,48,Business travel,Business,236,1,1,1,1,5,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +19972,59129,Female,Loyal Customer,40,Personal Travel,Eco,1744,1,2,1,3,3,1,3,3,4,5,4,2,4,3,12,0.0,neutral or dissatisfied +19973,10893,Male,Loyal Customer,39,Business travel,Business,224,1,1,1,1,4,5,4,5,5,5,5,3,5,5,3,3.0,satisfied +19974,17193,Female,Loyal Customer,45,Business travel,Eco Plus,643,4,1,1,1,1,4,2,4,4,4,4,4,4,5,8,0.0,satisfied +19975,15478,Female,Loyal Customer,16,Personal Travel,Eco,433,1,5,1,3,4,1,1,4,5,5,5,3,5,4,0,0.0,neutral or dissatisfied +19976,70593,Female,Loyal Customer,35,Business travel,Business,2611,2,2,2,2,3,3,3,5,3,4,5,3,5,3,0,0.0,satisfied +19977,78576,Male,Loyal Customer,51,Business travel,Business,630,5,5,5,5,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +19978,51392,Male,Loyal Customer,7,Personal Travel,Eco Plus,110,4,5,4,5,1,4,1,1,3,3,2,3,5,1,1,9.0,neutral or dissatisfied +19979,117320,Female,Loyal Customer,53,Personal Travel,Eco Plus,370,2,2,2,3,5,3,4,1,1,2,1,3,1,2,12,10.0,neutral or dissatisfied +19980,128223,Female,disloyal Customer,26,Business travel,Eco,602,2,1,2,4,4,2,2,4,2,3,4,1,4,4,24,29.0,neutral or dissatisfied +19981,36426,Male,Loyal Customer,25,Business travel,Business,369,1,3,3,3,1,1,1,1,1,3,4,2,4,1,11,8.0,neutral or dissatisfied +19982,112379,Male,Loyal Customer,52,Business travel,Business,2868,2,2,2,2,3,5,4,2,2,2,2,3,2,3,3,7.0,satisfied +19983,1589,Male,Loyal Customer,36,Personal Travel,Eco,140,3,3,3,3,5,3,5,5,1,1,1,3,3,5,4,0.0,neutral or dissatisfied +19984,80737,Female,Loyal Customer,52,Business travel,Business,393,2,1,1,1,4,3,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +19985,69513,Female,Loyal Customer,50,Business travel,Business,2475,4,4,3,4,4,3,3,4,5,5,4,3,5,3,0,0.0,satisfied +19986,108836,Male,Loyal Customer,62,Personal Travel,Eco,1199,1,4,0,4,4,0,3,4,1,5,4,2,3,4,6,7.0,neutral or dissatisfied +19987,88936,Female,Loyal Customer,36,Business travel,Business,2802,1,1,1,1,5,5,5,4,4,4,4,5,4,5,32,15.0,satisfied +19988,124035,Male,Loyal Customer,26,Personal Travel,Eco,184,1,5,1,1,2,1,2,2,3,1,2,2,1,2,0,0.0,neutral or dissatisfied +19989,59766,Male,Loyal Customer,31,Business travel,Business,1939,3,3,3,3,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +19990,45034,Female,Loyal Customer,24,Business travel,Eco,837,2,3,3,3,2,2,1,2,2,2,4,1,3,2,0,0.0,neutral or dissatisfied +19991,92126,Male,Loyal Customer,23,Personal Travel,Eco,1589,2,2,2,4,4,2,1,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +19992,125356,Female,disloyal Customer,28,Business travel,Eco,599,3,1,3,1,2,3,1,2,1,2,1,3,1,2,5,26.0,neutral or dissatisfied +19993,104204,Male,disloyal Customer,24,Business travel,Business,680,5,0,5,3,3,5,3,3,4,4,4,3,5,3,3,0.0,satisfied +19994,2033,Male,Loyal Customer,48,Business travel,Business,812,2,2,3,2,2,5,5,5,5,5,5,4,5,3,5,0.0,satisfied +19995,32538,Male,Loyal Customer,41,Business travel,Eco,102,3,1,5,1,3,3,3,3,1,5,4,5,3,3,1,6.0,satisfied +19996,13668,Male,Loyal Customer,36,Business travel,Business,462,2,2,2,2,4,5,4,3,3,2,3,4,3,2,0,0.0,satisfied +19997,28667,Male,Loyal Customer,12,Personal Travel,Eco,2614,4,2,4,3,4,4,4,4,2,2,1,4,2,4,0,0.0,neutral or dissatisfied +19998,95778,Male,Loyal Customer,25,Personal Travel,Eco,237,2,4,2,2,2,2,2,2,5,2,5,3,4,2,0,0.0,neutral or dissatisfied +19999,12011,Male,Loyal Customer,59,Business travel,Business,2144,5,5,5,5,4,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +20000,109418,Female,Loyal Customer,39,Business travel,Business,3111,3,3,3,3,3,5,5,5,5,5,5,5,5,5,61,60.0,satisfied +20001,41473,Female,disloyal Customer,35,Business travel,Eco,1504,2,3,3,4,2,2,4,2,4,4,4,1,3,2,27,14.0,neutral or dissatisfied +20002,63648,Male,Loyal Customer,50,Business travel,Business,1448,3,3,3,3,4,5,4,2,2,2,2,5,2,5,10,2.0,satisfied +20003,106923,Male,Loyal Customer,63,Personal Travel,Eco,1259,2,5,2,2,5,2,2,5,5,2,5,5,4,5,6,0.0,neutral or dissatisfied +20004,119544,Female,Loyal Customer,58,Personal Travel,Eco,899,1,5,1,3,3,5,5,1,1,1,1,3,1,4,0,4.0,neutral or dissatisfied +20005,75375,Female,Loyal Customer,34,Personal Travel,Business,2342,2,3,2,4,2,3,4,5,5,2,5,3,5,1,3,0.0,neutral or dissatisfied +20006,101530,Female,Loyal Customer,63,Personal Travel,Eco,345,3,1,3,3,2,4,4,2,2,3,2,1,2,1,1,5.0,neutral or dissatisfied +20007,14033,Male,Loyal Customer,54,Business travel,Business,3747,3,2,3,3,3,3,3,4,4,4,4,3,4,5,0,0.0,satisfied +20008,97529,Male,Loyal Customer,49,Personal Travel,Eco,439,4,5,4,2,4,4,4,4,5,5,5,5,5,4,7,3.0,neutral or dissatisfied +20009,79422,Female,Loyal Customer,34,Personal Travel,Eco,502,4,5,4,4,2,4,2,2,4,5,4,5,5,2,16,0.0,neutral or dissatisfied +20010,82555,Male,Loyal Customer,52,Business travel,Business,2619,2,2,4,2,2,4,4,2,2,2,2,3,2,4,3,22.0,neutral or dissatisfied +20011,53860,Female,Loyal Customer,30,Business travel,Business,2250,2,4,4,4,2,2,2,2,1,5,1,4,2,2,0,0.0,neutral or dissatisfied +20012,35281,Female,Loyal Customer,26,Business travel,Business,1069,3,1,1,1,3,3,3,3,4,4,4,2,4,3,11,0.0,neutral or dissatisfied +20013,96750,Female,Loyal Customer,45,Business travel,Business,3316,4,4,4,4,4,4,5,4,4,4,4,3,4,3,43,33.0,satisfied +20014,115505,Male,disloyal Customer,45,Business travel,Business,404,2,2,2,2,3,2,5,3,4,2,5,4,4,3,0,1.0,neutral or dissatisfied +20015,116515,Female,Loyal Customer,69,Personal Travel,Eco,337,1,5,1,3,4,4,5,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +20016,126359,Female,Loyal Customer,63,Personal Travel,Eco,468,5,4,5,3,3,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +20017,91803,Female,Loyal Customer,35,Personal Travel,Eco,626,2,2,2,4,1,2,1,1,3,3,3,1,3,1,29,15.0,neutral or dissatisfied +20018,32318,Male,Loyal Customer,28,Business travel,Business,216,0,4,0,2,4,4,4,4,2,4,1,5,3,4,0,69.0,satisfied +20019,20055,Male,disloyal Customer,55,Business travel,Eco,323,3,2,3,4,4,3,3,4,2,2,4,1,4,4,12,11.0,neutral or dissatisfied +20020,33524,Male,disloyal Customer,30,Business travel,Business,228,4,5,5,2,2,5,5,2,1,4,1,3,1,2,0,38.0,neutral or dissatisfied +20021,55442,Male,Loyal Customer,46,Personal Travel,Eco,2254,3,4,3,3,5,3,2,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +20022,59793,Male,Loyal Customer,39,Business travel,Eco Plus,1025,4,4,4,4,4,4,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +20023,61143,Male,Loyal Customer,26,Business travel,Business,2707,3,3,3,3,5,5,5,5,4,4,4,3,5,5,6,0.0,satisfied +20024,20411,Female,Loyal Customer,36,Business travel,Eco,299,4,5,5,5,4,3,4,4,3,2,2,2,2,4,0,0.0,neutral or dissatisfied +20025,111412,Female,disloyal Customer,25,Business travel,Business,1671,5,0,5,3,4,5,4,4,4,2,4,3,5,4,0,35.0,satisfied +20026,25302,Male,Loyal Customer,53,Business travel,Eco,432,5,4,4,4,5,5,5,5,1,1,2,1,4,5,0,0.0,satisfied +20027,110850,Male,Loyal Customer,46,Business travel,Business,404,1,1,1,1,5,5,5,4,4,4,4,5,4,3,7,0.0,satisfied +20028,91478,Male,Loyal Customer,27,Personal Travel,Eco,859,3,4,3,4,4,3,4,4,3,2,5,3,4,4,0,22.0,neutral or dissatisfied +20029,86242,Female,Loyal Customer,39,Personal Travel,Eco,226,2,3,0,4,4,0,4,4,1,1,4,3,3,4,0,15.0,neutral or dissatisfied +20030,106740,Male,Loyal Customer,56,Business travel,Eco,829,1,3,3,3,1,1,1,1,1,2,4,3,3,1,6,0.0,neutral or dissatisfied +20031,127263,Male,Loyal Customer,58,Business travel,Business,1633,3,3,3,3,5,3,3,3,3,3,3,3,3,1,0,5.0,neutral or dissatisfied +20032,3537,Female,Loyal Customer,25,Personal Travel,Eco Plus,557,3,4,4,3,4,4,4,4,3,1,3,2,5,4,32,,neutral or dissatisfied +20033,44564,Female,Loyal Customer,42,Business travel,Business,3569,3,3,3,3,4,1,5,5,5,5,4,1,5,5,17,16.0,satisfied +20034,31137,Female,Loyal Customer,24,Personal Travel,Eco,991,4,4,4,5,4,4,4,4,3,2,4,4,4,4,0,8.0,neutral or dissatisfied +20035,128038,Female,Loyal Customer,41,Personal Travel,Eco,1440,5,5,5,1,3,5,3,3,5,4,5,4,5,3,47,31.0,satisfied +20036,2995,Male,Loyal Customer,50,Business travel,Business,922,3,3,3,3,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +20037,33020,Male,Loyal Customer,32,Personal Travel,Eco,163,3,4,0,1,2,0,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +20038,115853,Female,disloyal Customer,23,Business travel,Eco,342,1,3,1,3,5,1,5,5,3,3,4,1,4,5,44,40.0,neutral or dissatisfied +20039,83319,Female,Loyal Customer,9,Personal Travel,Eco,1671,5,1,5,3,1,5,1,1,2,1,3,4,3,1,0,16.0,satisfied +20040,117218,Female,Loyal Customer,50,Personal Travel,Eco,370,2,4,2,1,1,2,5,4,4,2,4,5,4,4,4,2.0,neutral or dissatisfied +20041,26686,Male,Loyal Customer,10,Personal Travel,Eco,515,1,2,1,2,5,1,5,5,2,4,3,4,3,5,0,0.0,neutral or dissatisfied +20042,87111,Male,Loyal Customer,12,Personal Travel,Eco,594,4,3,4,1,4,4,4,4,4,5,2,4,4,4,73,61.0,neutral or dissatisfied +20043,23598,Male,Loyal Customer,60,Business travel,Business,692,4,4,4,4,4,5,3,2,2,2,2,3,2,2,9,14.0,satisfied +20044,13439,Female,Loyal Customer,34,Business travel,Business,409,2,4,4,4,4,4,4,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +20045,24371,Male,Loyal Customer,36,Business travel,Eco,669,5,3,1,3,5,5,5,5,1,5,5,5,4,5,0,0.0,satisfied +20046,111669,Female,disloyal Customer,11,Business travel,Eco,991,2,2,2,3,1,2,1,1,3,4,4,1,4,1,81,88.0,neutral or dissatisfied +20047,50210,Female,Loyal Customer,36,Business travel,Business,1519,3,4,4,4,2,4,3,2,2,2,3,3,2,3,44,37.0,neutral or dissatisfied +20048,64867,Male,Loyal Customer,35,Business travel,Business,190,1,1,1,1,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +20049,106746,Male,Loyal Customer,37,Business travel,Business,3387,2,2,2,2,3,2,2,2,2,2,2,2,2,4,0,3.0,neutral or dissatisfied +20050,42035,Female,disloyal Customer,17,Business travel,Eco,106,3,4,2,3,5,2,5,5,1,5,4,3,3,5,0,6.0,neutral or dissatisfied +20051,110228,Female,Loyal Customer,24,Business travel,Business,1138,3,3,3,3,3,3,3,3,4,4,4,3,4,3,0,0.0,satisfied +20052,8285,Male,Loyal Customer,36,Personal Travel,Eco,402,4,5,4,2,5,4,5,5,3,5,5,3,5,5,0,3.0,satisfied +20053,84144,Female,Loyal Customer,51,Business travel,Business,2310,3,3,3,3,5,5,5,4,4,4,4,4,4,5,1,0.0,satisfied +20054,113969,Male,disloyal Customer,27,Business travel,Business,1232,4,4,4,3,1,4,1,1,4,2,3,4,4,1,68,62.0,satisfied +20055,30296,Male,Loyal Customer,35,Business travel,Business,1476,5,5,5,5,4,2,4,4,4,4,4,2,4,2,0,0.0,satisfied +20056,26066,Female,Loyal Customer,31,Business travel,Business,2779,3,3,3,3,4,5,4,4,4,3,4,5,4,4,28,18.0,satisfied +20057,24433,Male,Loyal Customer,28,Personal Travel,Eco,634,2,4,2,3,4,2,4,4,4,5,4,5,5,4,0,0.0,neutral or dissatisfied +20058,24694,Female,disloyal Customer,41,Business travel,Business,397,5,5,5,4,5,5,5,5,4,5,5,4,5,5,0,0.0,satisfied +20059,71453,Female,Loyal Customer,29,Business travel,Eco,867,3,3,2,3,3,3,3,3,2,5,4,3,4,3,12,1.0,neutral or dissatisfied +20060,26539,Male,Loyal Customer,64,Personal Travel,Eco,1105,4,2,4,3,5,4,5,5,4,2,4,4,4,5,0,2.0,neutral or dissatisfied +20061,35355,Female,Loyal Customer,24,Business travel,Eco,1005,4,2,2,2,4,4,4,4,5,2,3,4,2,4,27,38.0,satisfied +20062,24494,Female,Loyal Customer,48,Personal Travel,Eco,481,2,5,2,3,5,1,3,4,4,2,4,5,4,1,0,0.0,neutral or dissatisfied +20063,57141,Female,Loyal Customer,24,Business travel,Business,3560,5,5,5,5,5,5,5,5,4,2,5,4,5,5,0,0.0,satisfied +20064,55615,Male,Loyal Customer,48,Personal Travel,Eco,404,4,3,1,3,5,1,5,5,1,4,3,3,3,5,0,0.0,satisfied +20065,80609,Female,Loyal Customer,55,Business travel,Business,236,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +20066,74200,Female,disloyal Customer,29,Business travel,Business,641,5,5,5,2,2,5,2,2,5,5,4,3,4,2,0,0.0,satisfied +20067,22536,Male,Loyal Customer,28,Personal Travel,Eco Plus,143,3,5,3,2,2,3,2,2,4,2,5,3,1,2,46,36.0,neutral or dissatisfied +20068,122267,Male,Loyal Customer,20,Personal Travel,Eco,573,3,4,3,4,4,3,4,4,3,3,5,4,4,4,1,27.0,neutral or dissatisfied +20069,13836,Male,Loyal Customer,21,Business travel,Business,1657,4,4,3,4,3,5,3,3,1,2,3,2,3,3,0,0.0,satisfied +20070,18480,Male,Loyal Customer,55,Business travel,Eco,262,4,5,5,5,4,4,4,4,2,2,1,1,4,4,5,0.0,satisfied +20071,37253,Female,disloyal Customer,24,Business travel,Eco,1076,2,2,2,5,4,2,4,4,2,2,5,3,4,4,0,0.0,neutral or dissatisfied +20072,102634,Male,Loyal Customer,47,Business travel,Business,3695,3,3,3,3,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +20073,84236,Male,Loyal Customer,7,Personal Travel,Eco,432,4,4,4,3,2,4,2,2,5,3,4,5,5,2,0,0.0,neutral or dissatisfied +20074,111108,Female,Loyal Customer,23,Personal Travel,Eco Plus,197,3,5,3,5,5,3,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +20075,101099,Male,disloyal Customer,36,Business travel,Business,583,1,1,1,4,2,1,2,2,5,2,5,3,4,2,25,7.0,neutral or dissatisfied +20076,95433,Male,Loyal Customer,34,Business travel,Eco Plus,277,1,0,0,4,3,0,3,3,2,1,4,2,4,3,0,0.0,neutral or dissatisfied +20077,45253,Male,Loyal Customer,30,Personal Travel,Eco,522,4,4,4,4,5,4,5,5,5,2,4,5,5,5,5,6.0,neutral or dissatisfied +20078,3159,Male,Loyal Customer,11,Personal Travel,Eco Plus,140,2,0,0,1,3,0,3,3,3,3,5,4,5,3,0,0.0,neutral or dissatisfied +20079,62860,Female,Loyal Customer,13,Business travel,Business,2583,2,2,5,2,5,5,5,5,4,2,3,4,5,5,0,0.0,satisfied +20080,95082,Female,Loyal Customer,40,Personal Travel,Eco,562,3,5,3,4,1,3,1,1,1,4,2,1,5,1,41,42.0,neutral or dissatisfied +20081,97484,Male,Loyal Customer,47,Business travel,Eco,756,2,3,5,3,3,2,3,3,4,3,3,1,4,3,18,7.0,neutral or dissatisfied +20082,108142,Male,Loyal Customer,80,Business travel,Business,705,3,5,5,5,1,2,1,3,3,3,3,1,3,1,6,2.0,neutral or dissatisfied +20083,77356,Male,disloyal Customer,25,Business travel,Business,626,3,4,2,5,2,2,2,2,3,5,4,4,5,2,0,0.0,neutral or dissatisfied +20084,24629,Female,Loyal Customer,54,Personal Travel,Eco,526,4,1,4,3,3,4,4,1,1,4,1,4,1,2,0,0.0,neutral or dissatisfied +20085,77795,Female,Loyal Customer,64,Personal Travel,Eco,874,2,3,2,4,3,2,3,5,5,2,3,4,5,2,22,12.0,neutral or dissatisfied +20086,36905,Male,Loyal Customer,27,Business travel,Eco,2072,0,0,0,2,2,0,2,2,4,4,4,2,1,2,0,0.0,satisfied +20087,109901,Male,Loyal Customer,54,Business travel,Business,2245,5,5,5,5,5,1,2,4,4,4,4,5,4,3,15,0.0,satisfied +20088,7555,Female,Loyal Customer,51,Business travel,Business,3231,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,4.0,satisfied +20089,97508,Female,Loyal Customer,34,Business travel,Eco Plus,670,1,4,4,4,1,1,1,1,2,1,3,4,4,1,34,53.0,neutral or dissatisfied +20090,85941,Female,Loyal Customer,53,Business travel,Business,3406,4,4,4,4,3,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +20091,94577,Female,disloyal Customer,24,Business travel,Eco,239,2,4,2,1,2,2,2,2,4,3,4,5,5,2,0,0.0,neutral or dissatisfied +20092,63837,Female,Loyal Customer,28,Business travel,Business,2647,5,5,5,5,4,4,4,4,4,5,4,4,4,4,0,2.0,satisfied +20093,4472,Male,Loyal Customer,62,Personal Travel,Eco,1005,2,3,3,1,3,3,3,3,1,3,1,2,3,3,17,58.0,neutral or dissatisfied +20094,87352,Male,Loyal Customer,41,Business travel,Business,2285,4,4,4,4,3,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +20095,68155,Female,Loyal Customer,57,Business travel,Business,3305,3,3,3,3,3,4,4,5,5,4,5,3,5,5,0,1.0,satisfied +20096,48248,Female,Loyal Customer,49,Personal Travel,Eco,391,1,5,1,3,4,4,4,4,4,1,4,3,4,5,0,0.0,neutral or dissatisfied +20097,44643,Male,Loyal Customer,65,Business travel,Business,3556,0,5,0,1,5,4,1,3,3,3,3,1,3,3,2,0.0,satisfied +20098,107432,Female,Loyal Customer,13,Personal Travel,Eco,468,1,4,5,1,4,5,4,4,3,2,5,5,5,4,29,20.0,neutral or dissatisfied +20099,96719,Male,disloyal Customer,24,Business travel,Eco,696,1,2,2,3,3,2,3,3,1,3,3,2,3,3,8,18.0,neutral or dissatisfied +20100,12133,Male,Loyal Customer,51,Business travel,Business,2818,5,5,5,5,4,5,4,4,4,4,4,3,4,3,46,15.0,satisfied +20101,120880,Female,disloyal Customer,20,Business travel,Eco,1013,3,4,4,3,5,4,5,5,4,2,4,3,5,5,0,2.0,neutral or dissatisfied +20102,84704,Male,Loyal Customer,54,Business travel,Business,481,1,1,1,1,4,4,4,5,5,5,5,5,5,4,0,1.0,satisfied +20103,97741,Male,Loyal Customer,40,Business travel,Business,587,1,1,1,1,2,5,4,4,4,4,4,5,4,3,0,6.0,satisfied +20104,39100,Female,Loyal Customer,58,Business travel,Business,328,1,4,4,4,1,1,1,1,3,3,3,1,3,1,150,158.0,neutral or dissatisfied +20105,1030,Female,disloyal Customer,27,Business travel,Eco,89,3,0,3,4,2,3,2,2,3,3,3,2,4,2,81,82.0,neutral or dissatisfied +20106,21096,Female,disloyal Customer,43,Business travel,Eco,106,2,0,2,3,4,2,4,4,3,2,5,2,3,4,0,0.0,neutral or dissatisfied +20107,53927,Male,Loyal Customer,47,Business travel,Eco Plus,140,1,4,4,4,1,1,1,1,2,1,2,1,2,1,1,0.0,neutral or dissatisfied +20108,90518,Female,Loyal Customer,55,Business travel,Business,2159,5,5,3,5,3,5,5,5,5,5,5,4,5,5,0,1.0,satisfied +20109,4981,Female,disloyal Customer,18,Business travel,Eco,502,1,4,1,3,4,1,4,4,3,4,4,4,5,4,0,49.0,neutral or dissatisfied +20110,71561,Female,Loyal Customer,28,Business travel,Business,2233,1,1,1,1,4,4,4,4,4,4,5,5,4,4,0,13.0,satisfied +20111,86102,Male,Loyal Customer,69,Personal Travel,Business,226,4,5,4,1,4,1,4,3,3,4,4,1,3,1,0,0.0,neutral or dissatisfied +20112,3878,Female,Loyal Customer,54,Business travel,Business,290,0,0,0,2,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +20113,108927,Female,Loyal Customer,36,Personal Travel,Eco,1183,1,5,1,1,1,4,4,4,2,4,4,4,5,4,138,128.0,neutral or dissatisfied +20114,64005,Male,Loyal Customer,54,Personal Travel,Eco,612,1,4,1,3,5,1,5,5,3,4,5,3,5,5,18,18.0,neutral or dissatisfied +20115,91338,Female,Loyal Customer,61,Personal Travel,Eco Plus,594,4,4,4,1,1,2,2,3,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +20116,76588,Female,Loyal Customer,49,Business travel,Business,547,2,5,5,5,4,3,3,2,2,2,2,4,2,3,0,4.0,neutral or dissatisfied +20117,11141,Female,Loyal Customer,65,Personal Travel,Eco,429,2,5,2,2,4,5,5,5,5,2,5,3,5,4,4,4.0,neutral or dissatisfied +20118,82397,Male,Loyal Customer,41,Business travel,Business,1771,3,3,3,3,3,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +20119,42083,Female,Loyal Customer,26,Personal Travel,Eco Plus,106,2,4,2,3,3,2,3,3,3,5,5,3,5,3,2,13.0,neutral or dissatisfied +20120,120986,Female,disloyal Customer,27,Business travel,Eco,992,3,3,3,3,3,3,3,3,4,2,4,4,3,3,15,13.0,neutral or dissatisfied +20121,85037,Female,disloyal Customer,35,Business travel,Eco Plus,1590,4,4,4,4,5,4,5,5,2,4,1,5,2,5,12,0.0,neutral or dissatisfied +20122,78940,Male,Loyal Customer,27,Personal Travel,Eco,500,2,2,2,3,3,2,1,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +20123,52979,Male,disloyal Customer,50,Business travel,Business,1208,2,2,2,4,5,2,5,5,4,5,5,3,5,5,0,0.0,neutral or dissatisfied +20124,63100,Male,Loyal Customer,19,Business travel,Business,2794,5,5,3,5,5,5,5,5,4,3,5,4,5,5,0,0.0,satisfied +20125,108937,Male,Loyal Customer,37,Personal Travel,Eco,1183,1,1,1,3,1,1,1,1,1,2,2,3,3,1,0,0.0,neutral or dissatisfied +20126,94977,Male,Loyal Customer,71,Business travel,Eco,239,2,3,3,3,2,2,2,2,3,4,4,1,4,2,11,11.0,neutral or dissatisfied +20127,59922,Female,disloyal Customer,15,Business travel,Eco,997,2,2,2,3,5,2,5,5,1,3,4,4,4,5,0,0.0,neutral or dissatisfied +20128,32711,Female,Loyal Customer,54,Business travel,Eco,102,5,1,1,1,4,3,5,4,4,5,4,1,4,2,1,5.0,satisfied +20129,31481,Male,Loyal Customer,38,Business travel,Eco,916,5,1,1,1,5,5,5,5,2,2,3,1,4,5,10,10.0,satisfied +20130,6616,Male,Loyal Customer,62,Personal Travel,Eco Plus,618,2,4,2,4,5,2,5,5,2,3,3,3,3,5,0,0.0,neutral or dissatisfied +20131,90023,Female,Loyal Customer,53,Business travel,Business,1127,4,4,4,4,3,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +20132,73521,Male,Loyal Customer,49,Business travel,Business,594,3,3,3,3,4,4,4,4,4,4,4,5,4,3,29,20.0,satisfied +20133,38384,Male,Loyal Customer,35,Business travel,Eco Plus,1133,3,3,3,3,3,3,3,3,5,3,2,1,4,3,0,0.0,satisfied +20134,14819,Male,Loyal Customer,45,Business travel,Eco,563,4,4,3,3,5,4,5,5,4,4,3,5,4,5,5,0.0,satisfied +20135,33135,Male,Loyal Customer,39,Personal Travel,Eco,102,2,3,2,2,4,2,4,4,1,2,2,1,2,4,0,0.0,neutral or dissatisfied +20136,64030,Male,Loyal Customer,47,Business travel,Business,2844,2,2,2,2,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +20137,103629,Male,disloyal Customer,26,Business travel,Business,405,2,0,2,4,1,2,1,1,5,2,5,4,4,1,0,0.0,neutral or dissatisfied +20138,55170,Female,Loyal Customer,12,Personal Travel,Eco,1635,2,4,2,2,1,2,3,1,3,3,5,3,4,1,86,92.0,neutral or dissatisfied +20139,64395,Male,Loyal Customer,48,Personal Travel,Eco,1192,2,4,2,3,1,2,1,1,1,5,3,1,2,1,0,0.0,neutral or dissatisfied +20140,72295,Female,Loyal Customer,11,Personal Travel,Eco,919,1,5,1,3,2,1,2,2,5,5,5,5,5,2,23,18.0,neutral or dissatisfied +20141,46542,Male,Loyal Customer,59,Business travel,Eco,125,5,1,5,1,5,5,5,5,4,3,2,5,3,5,0,0.0,satisfied +20142,62636,Male,Loyal Customer,52,Personal Travel,Eco,1744,3,4,3,4,1,3,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +20143,77659,Female,Loyal Customer,52,Business travel,Business,874,1,1,1,1,2,5,5,5,5,5,5,4,5,5,10,,satisfied +20144,31256,Female,Loyal Customer,52,Business travel,Eco,533,5,5,1,5,3,5,4,5,5,5,5,1,5,2,11,9.0,satisfied +20145,93977,Female,disloyal Customer,26,Business travel,Business,1218,5,5,5,2,3,5,3,3,5,5,5,5,5,3,5,9.0,satisfied +20146,39750,Female,Loyal Customer,53,Business travel,Eco,1174,2,5,5,5,5,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +20147,53610,Female,disloyal Customer,29,Business travel,Eco,1874,4,4,4,5,3,4,3,3,1,1,4,1,3,3,1,0.0,neutral or dissatisfied +20148,122221,Male,disloyal Customer,22,Business travel,Business,603,0,4,0,4,3,0,3,3,4,3,4,5,4,3,0,0.0,satisfied +20149,28644,Male,Loyal Customer,39,Personal Travel,Eco,2614,5,5,5,2,2,5,2,2,3,3,4,3,4,2,0,0.0,satisfied +20150,100370,Male,Loyal Customer,47,Personal Travel,Eco,1033,1,4,2,2,3,2,3,3,3,3,5,3,5,3,0,3.0,neutral or dissatisfied +20151,22185,Female,disloyal Customer,16,Business travel,Eco,565,5,0,5,1,2,5,2,2,5,3,4,4,3,2,0,0.0,satisfied +20152,102436,Female,Loyal Customer,51,Personal Travel,Eco,258,2,4,2,5,5,3,3,4,4,2,4,2,4,4,0,3.0,neutral or dissatisfied +20153,125034,Female,Loyal Customer,43,Business travel,Business,2300,3,3,3,3,5,5,5,3,3,3,5,5,3,5,0,20.0,satisfied +20154,16251,Male,Loyal Customer,45,Business travel,Business,1608,1,0,0,3,3,4,3,4,4,0,4,1,4,3,30,34.0,neutral or dissatisfied +20155,62480,Female,Loyal Customer,43,Business travel,Business,1846,1,1,1,1,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +20156,6567,Male,Loyal Customer,26,Business travel,Business,618,1,1,1,1,4,4,4,4,5,2,4,3,4,4,20,11.0,satisfied +20157,99044,Male,Loyal Customer,47,Business travel,Business,3360,5,5,5,5,2,5,4,5,5,5,5,5,5,5,4,9.0,satisfied +20158,86540,Female,Loyal Customer,64,Personal Travel,Eco,762,2,3,2,3,2,4,3,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +20159,114413,Male,Loyal Customer,51,Business travel,Business,372,4,4,4,4,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +20160,8458,Female,Loyal Customer,65,Business travel,Business,979,3,3,3,3,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +20161,1886,Female,Loyal Customer,48,Business travel,Business,2579,0,0,0,2,4,5,5,5,5,5,5,3,5,3,11,14.0,satisfied +20162,33414,Male,Loyal Customer,23,Business travel,Business,2556,2,2,2,2,5,5,5,1,3,4,5,5,1,5,0,0.0,satisfied +20163,40019,Female,disloyal Customer,27,Business travel,Eco,575,2,0,2,5,4,2,4,4,1,2,4,2,1,4,0,0.0,neutral or dissatisfied +20164,82326,Female,Loyal Customer,37,Business travel,Eco,456,2,1,1,1,2,2,2,2,2,4,3,2,3,2,73,67.0,neutral or dissatisfied +20165,25311,Female,Loyal Customer,17,Business travel,Eco,432,4,5,5,5,4,4,4,4,2,4,3,4,4,4,109,129.0,neutral or dissatisfied +20166,35590,Female,disloyal Customer,23,Business travel,Eco Plus,950,3,2,3,3,2,3,2,2,4,5,4,2,3,2,0,0.0,neutral or dissatisfied +20167,42998,Female,disloyal Customer,32,Business travel,Eco,192,4,5,4,2,4,4,4,4,3,5,2,1,3,4,0,0.0,neutral or dissatisfied +20168,46535,Female,disloyal Customer,33,Business travel,Eco,141,3,3,3,4,5,3,5,5,3,3,3,2,4,5,0,0.0,neutral or dissatisfied +20169,27879,Female,Loyal Customer,40,Personal Travel,Eco Plus,1448,2,2,2,4,2,2,1,2,4,2,4,1,4,2,9,0.0,neutral or dissatisfied +20170,19891,Male,Loyal Customer,44,Business travel,Business,296,5,5,5,5,3,4,3,5,5,5,5,2,5,2,0,0.0,satisfied +20171,97233,Male,disloyal Customer,24,Business travel,Eco,296,3,5,2,3,1,2,2,1,4,4,4,3,4,1,36,30.0,neutral or dissatisfied +20172,118624,Male,Loyal Customer,54,Business travel,Business,338,3,2,2,2,4,4,4,3,3,2,3,2,3,3,0,7.0,neutral or dissatisfied +20173,77531,Male,Loyal Customer,12,Personal Travel,Eco,1097,3,4,3,1,2,3,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +20174,115370,Female,disloyal Customer,22,Business travel,Eco,446,1,2,1,3,2,1,2,2,4,4,4,4,4,2,11,2.0,neutral or dissatisfied +20175,10300,Male,disloyal Customer,20,Business travel,Eco,301,4,0,4,2,4,4,4,4,3,5,5,3,4,4,0,0.0,neutral or dissatisfied +20176,20430,Male,Loyal Customer,24,Personal Travel,Eco,196,1,5,1,3,3,1,3,3,3,4,5,1,5,3,67,96.0,neutral or dissatisfied +20177,5563,Female,Loyal Customer,41,Business travel,Business,3020,5,5,4,5,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +20178,90631,Female,disloyal Customer,39,Business travel,Business,404,3,2,2,3,1,2,1,1,5,5,5,4,5,1,0,0.0,neutral or dissatisfied +20179,31413,Female,Loyal Customer,30,Business travel,Business,1506,4,4,4,4,5,5,5,5,2,5,4,4,5,5,0,4.0,satisfied +20180,78023,Female,disloyal Customer,35,Business travel,Eco,214,4,5,4,1,5,4,5,5,3,1,5,4,1,5,0,0.0,neutral or dissatisfied +20181,129395,Male,Loyal Customer,57,Business travel,Business,414,3,4,4,4,2,4,4,3,3,3,3,3,3,1,0,3.0,neutral or dissatisfied +20182,67503,Female,Loyal Customer,44,Business travel,Business,1973,5,5,4,5,5,5,4,4,4,3,4,3,4,5,10,15.0,satisfied +20183,88478,Male,Loyal Customer,23,Business travel,Eco,181,5,5,5,5,5,5,4,5,1,2,4,4,4,5,0,0.0,satisfied +20184,110505,Female,Loyal Customer,38,Business travel,Eco Plus,787,2,3,3,3,2,2,2,2,3,4,2,2,3,2,2,6.0,neutral or dissatisfied +20185,74748,Female,Loyal Customer,56,Personal Travel,Eco,1205,2,3,2,4,5,3,4,3,3,2,3,2,3,3,19,21.0,neutral or dissatisfied +20186,129626,Female,Loyal Customer,44,Business travel,Business,308,4,4,4,4,3,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +20187,1186,Male,Loyal Customer,69,Personal Travel,Eco,102,3,5,3,3,1,3,1,1,4,5,4,5,5,1,0,0.0,neutral or dissatisfied +20188,98242,Female,Loyal Customer,32,Business travel,Business,3487,5,5,5,5,4,4,4,4,5,5,4,3,4,4,0,0.0,satisfied +20189,23051,Female,Loyal Customer,56,Personal Travel,Business,820,1,2,1,3,1,5,4,3,1,4,4,4,2,4,154,146.0,neutral or dissatisfied +20190,30366,Female,Loyal Customer,58,Business travel,Eco,641,2,2,2,2,4,4,4,2,2,2,2,3,2,2,20,19.0,neutral or dissatisfied +20191,23874,Female,Loyal Customer,44,Business travel,Business,1593,2,2,2,2,3,4,4,4,4,4,4,3,4,5,22,11.0,satisfied +20192,105928,Male,disloyal Customer,40,Business travel,Business,1491,1,1,1,2,1,1,1,1,5,3,4,3,4,1,9,10.0,neutral or dissatisfied +20193,83632,Male,Loyal Customer,59,Business travel,Business,2973,5,5,5,5,3,5,5,4,4,4,4,5,4,5,32,20.0,satisfied +20194,114272,Female,Loyal Customer,39,Business travel,Eco,509,5,5,1,5,5,5,5,5,5,2,4,4,5,5,22,23.0,satisfied +20195,103358,Male,Loyal Customer,61,Business travel,Business,3042,0,0,0,2,1,1,1,3,5,4,5,1,5,1,149,146.0,satisfied +20196,52645,Male,Loyal Customer,23,Personal Travel,Eco,160,5,5,5,3,3,5,3,3,4,2,5,5,5,3,0,0.0,satisfied +20197,123730,Male,Loyal Customer,48,Personal Travel,Eco Plus,214,1,0,0,1,5,0,5,5,5,5,4,4,5,5,0,0.0,neutral or dissatisfied +20198,78480,Male,disloyal Customer,25,Business travel,Business,666,0,0,0,2,1,0,1,1,3,2,5,3,4,1,0,0.0,satisfied +20199,70146,Male,Loyal Customer,68,Personal Travel,Eco,550,3,3,3,4,5,3,4,5,1,3,3,3,4,5,8,7.0,neutral or dissatisfied +20200,69372,Female,Loyal Customer,48,Business travel,Business,2286,5,5,5,5,4,5,4,4,4,4,4,4,4,5,1,0.0,satisfied +20201,122589,Female,disloyal Customer,29,Business travel,Business,728,5,5,5,3,4,5,4,4,4,4,5,5,5,4,0,0.0,satisfied +20202,48938,Female,Loyal Customer,47,Business travel,Business,2849,5,5,5,5,1,1,2,4,4,5,4,2,4,4,55,58.0,satisfied +20203,107959,Male,Loyal Customer,53,Business travel,Business,825,3,3,3,3,2,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +20204,109634,Male,Loyal Customer,43,Business travel,Business,2388,3,3,3,3,3,5,5,3,3,4,3,3,3,4,17,13.0,satisfied +20205,81141,Female,Loyal Customer,68,Personal Travel,Eco Plus,991,3,2,3,3,2,4,3,4,4,3,4,2,4,3,2,34.0,neutral or dissatisfied +20206,80058,Male,Loyal Customer,63,Personal Travel,Eco,1069,3,4,3,2,5,3,5,5,3,5,2,2,5,5,0,3.0,neutral or dissatisfied +20207,12077,Female,Loyal Customer,32,Business travel,Eco Plus,376,0,0,0,1,1,0,1,1,1,4,4,4,5,1,5,0.0,satisfied +20208,40281,Female,Loyal Customer,8,Personal Travel,Eco,347,1,4,1,2,2,1,2,2,4,4,5,3,4,2,9,0.0,neutral or dissatisfied +20209,87415,Male,Loyal Customer,33,Personal Travel,Eco,425,2,5,2,5,1,2,1,1,5,3,5,3,4,1,79,78.0,neutral or dissatisfied +20210,52877,Male,Loyal Customer,21,Business travel,Business,836,3,3,3,3,5,5,5,5,1,1,4,3,5,5,0,0.0,satisfied +20211,83599,Female,disloyal Customer,23,Business travel,Business,409,0,0,0,1,4,0,2,4,4,3,4,4,4,4,0,0.0,satisfied +20212,111673,Female,disloyal Customer,22,Business travel,Eco,591,2,1,2,3,4,2,3,4,4,2,3,2,3,4,12,45.0,neutral or dissatisfied +20213,100997,Male,Loyal Customer,44,Business travel,Business,3759,5,5,5,5,3,4,5,4,4,4,4,3,4,5,7,0.0,satisfied +20214,113574,Female,Loyal Customer,42,Business travel,Eco,236,4,1,1,1,4,3,4,4,4,4,4,2,4,3,7,0.0,neutral or dissatisfied +20215,95980,Female,Loyal Customer,31,Business travel,Business,3477,1,1,1,1,4,4,4,4,4,2,5,3,4,4,36,34.0,satisfied +20216,122983,Female,Loyal Customer,60,Business travel,Business,2714,3,3,3,3,3,4,4,5,5,5,5,4,5,3,1,0.0,satisfied +20217,32087,Female,Loyal Customer,44,Business travel,Business,216,1,1,1,1,1,3,2,4,4,4,3,5,4,1,4,4.0,satisfied +20218,128419,Male,Loyal Customer,32,Business travel,Business,338,1,1,1,1,1,1,1,1,1,1,2,2,2,1,1,4.0,neutral or dissatisfied +20219,56131,Female,Loyal Customer,59,Business travel,Business,1504,2,2,2,2,5,4,4,4,4,4,4,3,4,3,7,0.0,satisfied +20220,59528,Female,Loyal Customer,52,Business travel,Business,854,3,3,3,3,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20221,64739,Female,Loyal Customer,57,Business travel,Eco,224,4,5,5,5,4,3,3,4,4,4,4,1,4,4,0,19.0,neutral or dissatisfied +20222,120230,Male,disloyal Customer,24,Business travel,Eco,1303,2,2,2,1,5,2,5,5,5,1,3,5,4,5,0,0.0,neutral or dissatisfied +20223,25230,Male,Loyal Customer,40,Business travel,Eco,387,3,4,4,4,3,3,3,3,1,3,4,2,3,3,22,17.0,neutral or dissatisfied +20224,127084,Female,Loyal Customer,26,Business travel,Business,2577,0,0,0,1,4,4,4,4,2,4,4,3,2,4,0,0.0,satisfied +20225,88730,Male,Loyal Customer,19,Personal Travel,Eco,270,3,0,3,1,5,3,5,5,3,4,4,5,4,5,34,26.0,neutral or dissatisfied +20226,40131,Female,Loyal Customer,9,Personal Travel,Eco,200,3,3,3,3,1,3,1,1,3,5,4,4,4,1,0,0.0,neutral or dissatisfied +20227,111433,Female,Loyal Customer,47,Personal Travel,Eco Plus,896,3,5,3,1,3,5,5,1,1,3,1,4,1,4,0,5.0,neutral or dissatisfied +20228,125372,Male,Loyal Customer,40,Business travel,Business,1440,2,1,1,1,1,3,2,2,2,2,2,2,2,1,0,7.0,neutral or dissatisfied +20229,5888,Male,disloyal Customer,44,Business travel,Business,108,1,1,1,2,5,1,5,5,3,2,4,3,4,5,108,130.0,neutral or dissatisfied +20230,110636,Female,Loyal Customer,16,Personal Travel,Eco Plus,719,2,4,2,4,3,2,5,3,5,5,5,4,5,3,10,16.0,neutral or dissatisfied +20231,76747,Male,Loyal Customer,59,Business travel,Business,205,2,2,2,2,3,2,3,1,1,1,2,1,1,1,85,76.0,neutral or dissatisfied +20232,113827,Female,Loyal Customer,16,Personal Travel,Eco Plus,397,1,3,1,2,4,1,3,4,3,2,1,2,2,4,0,0.0,neutral or dissatisfied +20233,37516,Female,Loyal Customer,46,Business travel,Eco,944,3,5,5,5,3,3,3,2,3,3,3,3,2,3,159,161.0,neutral or dissatisfied +20234,129147,Female,disloyal Customer,27,Business travel,Eco,679,1,1,1,4,1,1,1,1,3,5,3,1,3,1,0,0.0,neutral or dissatisfied +20235,123999,Male,Loyal Customer,62,Business travel,Eco,184,1,2,2,2,1,1,1,1,3,2,2,1,3,1,0,0.0,neutral or dissatisfied +20236,25801,Male,Loyal Customer,51,Personal Travel,Eco,762,2,1,2,3,5,2,5,5,3,5,4,4,3,5,22,7.0,neutral or dissatisfied +20237,6439,Female,Loyal Customer,67,Personal Travel,Eco,296,3,5,3,4,4,5,5,3,3,3,3,3,3,3,5,35.0,neutral or dissatisfied +20238,94067,Male,Loyal Customer,51,Business travel,Business,2154,4,5,3,5,4,4,3,4,4,3,4,3,4,1,17,10.0,neutral or dissatisfied +20239,81961,Female,Loyal Customer,58,Business travel,Business,1589,4,4,4,4,2,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +20240,60614,Female,Loyal Customer,44,Business travel,Business,991,4,4,4,4,4,4,4,4,4,4,4,3,4,3,69,72.0,satisfied +20241,95797,Male,Loyal Customer,47,Business travel,Eco Plus,237,2,3,5,3,2,2,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +20242,124870,Female,Loyal Customer,18,Personal Travel,Eco Plus,280,3,4,3,1,5,3,5,5,4,5,5,4,4,5,0,0.0,neutral or dissatisfied +20243,116395,Female,Loyal Customer,43,Personal Travel,Eco,362,3,5,3,3,5,4,5,1,1,3,1,4,1,5,36,43.0,neutral or dissatisfied +20244,77424,Male,Loyal Customer,55,Personal Travel,Eco,588,2,5,2,1,2,2,3,2,1,5,4,5,3,2,4,64.0,neutral or dissatisfied +20245,94095,Female,Loyal Customer,63,Personal Travel,Business,277,0,2,0,4,1,4,3,1,1,0,1,3,1,1,0,0.0,satisfied +20246,56085,Male,Loyal Customer,64,Business travel,Eco Plus,2586,3,1,1,1,3,2,2,1,1,4,4,2,4,2,6,9.0,neutral or dissatisfied +20247,61993,Female,Loyal Customer,49,Business travel,Business,2475,1,1,2,1,5,5,5,4,4,4,4,3,4,4,0,7.0,satisfied +20248,30719,Female,Loyal Customer,17,Business travel,Business,2272,3,5,5,5,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +20249,76454,Female,disloyal Customer,27,Business travel,Business,547,4,4,4,4,4,4,4,4,4,4,5,3,5,4,0,0.0,neutral or dissatisfied +20250,76630,Male,disloyal Customer,22,Business travel,Eco,134,4,0,4,4,4,4,4,4,4,4,2,3,5,4,0,0.0,satisfied +20251,116512,Female,Loyal Customer,64,Personal Travel,Eco,447,2,4,1,5,2,3,3,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +20252,94350,Female,Loyal Customer,47,Business travel,Business,323,0,0,0,3,4,5,5,1,1,1,1,3,1,5,0,0.0,satisfied +20253,116365,Female,Loyal Customer,65,Personal Travel,Eco,337,1,5,1,4,3,4,4,2,2,1,2,4,2,4,27,42.0,neutral or dissatisfied +20254,6279,Male,Loyal Customer,35,Business travel,Business,3597,4,4,4,4,4,3,3,5,5,5,5,3,5,1,0,0.0,satisfied +20255,49308,Female,Loyal Customer,23,Business travel,Business,3182,1,1,1,1,5,5,5,5,4,3,2,4,3,5,0,10.0,satisfied +20256,113508,Male,Loyal Customer,42,Business travel,Business,2381,3,3,3,3,4,5,4,4,4,4,4,3,4,5,9,1.0,satisfied +20257,3267,Female,Loyal Customer,32,Business travel,Eco,419,4,4,4,4,4,4,4,4,1,3,4,2,4,4,0,0.0,neutral or dissatisfied +20258,94185,Female,Loyal Customer,37,Business travel,Business,2938,3,3,3,3,5,5,4,5,5,5,5,5,5,4,0,11.0,satisfied +20259,117857,Male,Loyal Customer,54,Business travel,Business,2975,1,1,1,1,5,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +20260,37421,Female,Loyal Customer,72,Business travel,Business,3121,1,1,1,1,3,3,4,1,1,1,1,1,1,4,17,6.0,neutral or dissatisfied +20261,93477,Male,Loyal Customer,68,Personal Travel,Eco Plus,605,1,5,1,2,5,1,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +20262,74299,Female,disloyal Customer,24,Business travel,Eco,992,1,1,1,4,1,1,1,1,1,5,3,2,4,1,0,0.0,neutral or dissatisfied +20263,110206,Female,Loyal Customer,53,Business travel,Business,3666,4,4,4,4,2,5,5,5,5,5,5,3,5,5,3,0.0,satisfied +20264,93667,Female,disloyal Customer,38,Business travel,Eco,655,1,2,0,4,3,0,3,3,3,1,4,3,3,3,0,0.0,neutral or dissatisfied +20265,76091,Male,Loyal Customer,60,Personal Travel,Eco,669,3,5,3,5,4,3,4,4,4,2,5,3,5,4,0,0.0,neutral or dissatisfied +20266,55622,Male,Loyal Customer,46,Business travel,Business,1824,1,1,3,1,2,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +20267,53083,Female,Loyal Customer,54,Business travel,Business,2327,5,5,2,5,1,4,3,4,4,4,4,4,4,1,25,18.0,satisfied +20268,47218,Male,Loyal Customer,42,Personal Travel,Eco,954,4,0,4,4,1,4,1,1,3,1,4,4,2,1,0,0.0,neutral or dissatisfied +20269,10605,Male,Loyal Customer,53,Business travel,Business,3153,1,4,4,4,3,4,4,3,3,3,1,2,3,1,16,11.0,neutral or dissatisfied +20270,51165,Male,Loyal Customer,32,Personal Travel,Eco,77,3,5,3,1,1,3,1,1,2,2,1,3,5,1,2,0.0,neutral or dissatisfied +20271,67568,Female,disloyal Customer,25,Business travel,Business,1171,4,4,4,5,4,4,4,4,5,5,5,5,5,4,21,21.0,neutral or dissatisfied +20272,70787,Female,Loyal Customer,41,Business travel,Business,328,1,1,1,1,3,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20273,109552,Male,Loyal Customer,21,Personal Travel,Eco,992,2,5,2,3,5,2,5,5,5,5,4,3,5,5,20,0.0,neutral or dissatisfied +20274,103609,Female,Loyal Customer,33,Personal Travel,Business,405,5,5,5,4,2,4,5,1,1,5,3,3,1,5,0,0.0,satisfied +20275,129535,Female,disloyal Customer,22,Business travel,Eco,1102,5,5,5,2,2,5,2,2,5,5,3,4,5,2,0,0.0,satisfied +20276,18009,Female,Loyal Customer,46,Personal Travel,Eco,332,3,5,2,5,4,4,4,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +20277,47333,Female,Loyal Customer,49,Business travel,Eco,558,4,5,5,5,1,1,5,4,4,4,4,5,4,4,0,0.0,satisfied +20278,65510,Male,Loyal Customer,31,Business travel,Business,1616,3,3,3,3,1,2,1,1,3,5,5,5,4,1,0,0.0,satisfied +20279,5667,Male,Loyal Customer,62,Business travel,Business,196,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +20280,75870,Female,Loyal Customer,58,Business travel,Business,1972,3,3,3,3,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +20281,18468,Female,Loyal Customer,39,Business travel,Business,1558,2,2,5,2,2,5,2,5,5,5,3,2,5,3,16,17.0,satisfied +20282,40107,Female,Loyal Customer,41,Business travel,Eco,368,5,4,4,4,5,5,5,5,4,2,3,5,1,5,0,0.0,satisfied +20283,12350,Male,Loyal Customer,37,Business travel,Eco,192,2,4,4,4,2,2,2,2,2,2,4,2,4,2,83,75.0,neutral or dissatisfied +20284,113318,Female,Loyal Customer,41,Business travel,Business,2876,5,5,5,5,5,4,4,4,4,4,4,5,4,4,22,20.0,satisfied +20285,67561,Female,Loyal Customer,43,Business travel,Business,1205,4,4,4,4,5,5,4,5,5,5,5,3,5,5,5,8.0,satisfied +20286,10435,Female,Loyal Customer,52,Business travel,Business,1720,4,4,4,4,4,4,5,4,4,4,4,4,4,4,17,15.0,satisfied +20287,69743,Female,Loyal Customer,42,Business travel,Business,2591,4,4,4,4,3,4,5,2,2,2,2,3,2,5,4,23.0,satisfied +20288,128929,Female,Loyal Customer,58,Business travel,Business,3165,4,4,4,4,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +20289,25138,Female,Loyal Customer,33,Personal Travel,Eco,1249,4,4,5,1,5,5,5,5,4,2,5,5,5,5,0,15.0,neutral or dissatisfied +20290,50713,Male,Loyal Customer,11,Personal Travel,Eco,109,1,4,1,1,2,1,1,2,3,5,4,3,4,2,0,0.0,neutral or dissatisfied +20291,29882,Male,Loyal Customer,55,Business travel,Business,95,3,1,1,1,3,4,3,4,4,4,3,1,4,1,0,0.0,neutral or dissatisfied +20292,73024,Female,Loyal Customer,60,Personal Travel,Eco,1089,1,4,1,3,2,1,5,3,3,1,3,2,3,5,0,0.0,neutral or dissatisfied +20293,42531,Male,Loyal Customer,39,Business travel,Business,310,1,1,1,1,3,5,1,5,5,5,5,5,5,3,3,0.0,satisfied +20294,1984,Male,Loyal Customer,30,Personal Travel,Eco,293,5,4,5,2,1,5,1,1,4,5,4,5,4,1,13,2.0,satisfied +20295,22364,Female,disloyal Customer,24,Business travel,Eco,238,4,2,4,3,4,4,1,4,2,3,3,1,4,4,85,76.0,neutral or dissatisfied +20296,3624,Female,Loyal Customer,42,Personal Travel,Business,427,3,3,3,3,4,2,4,5,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +20297,50132,Female,disloyal Customer,38,Business travel,Eco,337,2,2,2,4,4,2,4,4,4,5,4,3,3,4,13,20.0,neutral or dissatisfied +20298,63274,Female,Loyal Customer,42,Business travel,Business,1850,5,5,5,5,5,4,5,4,4,4,4,3,4,4,2,0.0,satisfied +20299,42538,Male,Loyal Customer,55,Business travel,Eco,1174,4,1,1,1,4,4,4,4,3,4,4,5,3,4,0,0.0,satisfied +20300,126883,Female,Loyal Customer,49,Personal Travel,Eco,2077,2,3,2,3,4,4,3,1,1,2,1,2,1,2,0,0.0,neutral or dissatisfied +20301,64852,Female,Loyal Customer,79,Business travel,Business,1850,3,2,2,2,2,4,3,3,3,3,3,3,3,4,13,8.0,neutral or dissatisfied +20302,10562,Female,disloyal Customer,26,Business travel,Business,429,2,0,2,5,4,2,4,4,4,4,4,5,4,4,42,40.0,neutral or dissatisfied +20303,99056,Male,Loyal Customer,56,Business travel,Business,419,5,5,5,5,2,4,4,3,3,4,3,3,3,4,48,42.0,satisfied +20304,71558,Female,Loyal Customer,40,Business travel,Business,2305,3,3,3,3,3,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +20305,6043,Female,Loyal Customer,38,Business travel,Business,2029,2,4,4,4,5,4,4,2,2,2,2,3,2,4,15,17.0,neutral or dissatisfied +20306,41758,Female,Loyal Customer,58,Business travel,Eco Plus,230,4,1,1,1,3,3,4,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +20307,3056,Female,disloyal Customer,41,Business travel,Business,340,4,4,4,3,1,4,1,1,3,3,5,5,4,1,0,0.0,satisfied +20308,119109,Male,Loyal Customer,32,Personal Travel,Eco,1107,3,2,3,4,5,3,5,5,4,4,4,3,3,5,0,0.0,neutral or dissatisfied +20309,102179,Female,disloyal Customer,17,Business travel,Eco,397,3,4,3,3,3,3,3,3,3,5,4,1,3,3,4,7.0,neutral or dissatisfied +20310,31283,Male,Loyal Customer,35,Personal Travel,Eco,770,2,4,2,3,4,2,4,4,5,5,5,3,4,4,8,0.0,neutral or dissatisfied +20311,53809,Male,Loyal Customer,44,Business travel,Business,3053,3,5,3,3,2,4,1,5,5,5,3,2,5,1,5,2.0,satisfied +20312,109353,Male,Loyal Customer,56,Business travel,Business,2731,2,2,2,2,2,5,4,4,4,4,4,4,4,4,19,10.0,satisfied +20313,22804,Female,Loyal Customer,37,Business travel,Business,302,3,3,3,3,4,1,5,5,5,5,5,3,5,2,0,0.0,satisfied +20314,110633,Male,Loyal Customer,39,Personal Travel,Eco,719,1,4,1,2,3,1,4,3,3,3,4,3,5,3,9,8.0,neutral or dissatisfied +20315,129619,Female,Loyal Customer,58,Business travel,Business,2291,4,4,1,4,2,4,5,5,5,4,5,5,5,4,0,0.0,satisfied +20316,56859,Male,Loyal Customer,51,Business travel,Business,2565,5,5,5,5,5,5,5,3,4,3,4,5,5,5,0,0.0,satisfied +20317,124525,Female,Loyal Customer,67,Business travel,Business,1276,1,1,1,1,4,4,4,5,5,5,5,5,5,4,25,0.0,satisfied +20318,13557,Male,Loyal Customer,47,Personal Travel,Eco,227,5,5,5,2,3,5,4,3,4,4,4,5,5,3,0,0.0,satisfied +20319,20675,Female,disloyal Customer,30,Business travel,Eco,522,4,1,4,3,3,4,3,3,3,2,3,1,3,3,37,37.0,neutral or dissatisfied +20320,74032,Male,Loyal Customer,65,Personal Travel,Eco,1471,2,4,2,4,5,2,5,5,3,5,5,5,5,5,0,0.0,neutral or dissatisfied +20321,42988,Male,Loyal Customer,40,Business travel,Business,2940,3,3,3,3,4,5,4,5,5,5,5,2,5,5,0,6.0,satisfied +20322,86634,Male,disloyal Customer,37,Business travel,Eco,746,2,2,2,4,2,2,2,2,2,4,4,4,4,2,20,7.0,neutral or dissatisfied +20323,82178,Male,Loyal Customer,7,Personal Travel,Eco Plus,311,4,5,4,3,4,4,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +20324,92332,Female,disloyal Customer,27,Business travel,Business,2399,1,1,1,1,1,5,5,4,3,5,5,5,4,5,3,19.0,neutral or dissatisfied +20325,23038,Female,Loyal Customer,35,Personal Travel,Eco,1025,2,4,2,3,2,2,2,2,5,5,5,5,5,2,0,0.0,neutral or dissatisfied +20326,114101,Female,Loyal Customer,49,Business travel,Eco Plus,447,5,1,1,1,2,4,1,5,5,5,5,3,5,4,4,0.0,satisfied +20327,57508,Male,Loyal Customer,46,Business travel,Business,137,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,3.0,satisfied +20328,120813,Female,disloyal Customer,26,Business travel,Eco,666,2,4,2,4,3,2,3,3,4,2,3,3,3,3,0,0.0,neutral or dissatisfied +20329,120927,Female,disloyal Customer,27,Business travel,Business,992,3,2,2,2,2,2,4,2,4,2,4,3,5,2,0,5.0,neutral or dissatisfied +20330,44892,Male,disloyal Customer,66,Business travel,Eco,536,1,4,1,4,1,1,1,1,4,3,5,5,3,1,0,0.0,neutral or dissatisfied +20331,119334,Female,Loyal Customer,34,Personal Travel,Eco,214,2,2,2,3,1,2,3,1,1,3,4,4,4,1,0,0.0,neutral or dissatisfied +20332,104263,Female,disloyal Customer,27,Business travel,Eco,456,3,3,4,3,3,4,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +20333,32561,Male,Loyal Customer,52,Business travel,Business,2353,3,1,1,1,2,2,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +20334,3091,Female,disloyal Customer,17,Business travel,Eco,678,2,2,2,3,4,2,4,4,1,3,2,3,2,4,0,36.0,neutral or dissatisfied +20335,29587,Female,disloyal Customer,17,Business travel,Eco,1533,4,5,5,4,5,4,5,5,3,1,5,5,2,5,0,0.0,satisfied +20336,52397,Male,Loyal Customer,19,Personal Travel,Eco,493,4,4,4,3,4,4,4,4,3,3,5,3,4,4,0,0.0,neutral or dissatisfied +20337,116100,Female,Loyal Customer,52,Personal Travel,Eco,404,4,5,4,5,5,4,4,1,1,4,1,3,1,3,15,10.0,neutral or dissatisfied +20338,24128,Male,Loyal Customer,56,Personal Travel,Eco,779,1,4,1,4,4,1,4,4,3,3,4,4,4,4,0,0.0,neutral or dissatisfied +20339,41033,Male,Loyal Customer,26,Business travel,Business,1195,1,4,3,4,1,1,1,1,4,1,3,4,4,1,0,2.0,neutral or dissatisfied +20340,29827,Male,Loyal Customer,52,Business travel,Eco,95,4,2,1,1,4,4,4,4,5,5,2,5,3,4,0,0.0,satisfied +20341,98219,Male,Loyal Customer,43,Personal Travel,Eco,842,4,3,4,4,4,4,4,4,1,3,4,3,5,4,0,1.0,neutral or dissatisfied +20342,19811,Female,disloyal Customer,38,Business travel,Eco,413,1,3,2,4,2,2,2,5,5,3,3,2,3,2,185,176.0,neutral or dissatisfied +20343,105609,Male,Loyal Customer,70,Personal Travel,Business,842,5,4,5,2,3,5,4,3,3,5,3,5,3,4,0,26.0,satisfied +20344,28353,Female,Loyal Customer,54,Personal Travel,Eco,954,3,4,3,3,5,4,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +20345,51564,Female,disloyal Customer,22,Business travel,Eco,370,2,4,2,2,5,2,5,5,3,2,3,3,3,5,0,0.0,neutral or dissatisfied +20346,79638,Male,Loyal Customer,46,Business travel,Business,2093,4,4,4,4,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20347,103362,Male,Loyal Customer,43,Business travel,Business,3887,4,4,4,4,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +20348,114968,Male,Loyal Customer,40,Business travel,Business,373,5,5,5,5,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +20349,129554,Male,Loyal Customer,25,Personal Travel,Eco,2342,2,2,2,4,2,2,2,2,1,5,4,4,3,2,20,33.0,neutral or dissatisfied +20350,24375,Female,disloyal Customer,20,Business travel,Eco,669,5,4,4,4,2,4,3,2,4,4,5,3,3,2,0,0.0,satisfied +20351,94503,Male,Loyal Customer,58,Business travel,Eco,677,3,4,4,4,3,3,3,3,2,4,3,4,4,3,31,33.0,neutral or dissatisfied +20352,109310,Female,Loyal Customer,28,Business travel,Business,1634,2,4,4,4,2,2,2,2,3,3,3,2,4,2,1,0.0,neutral or dissatisfied +20353,27596,Female,Loyal Customer,54,Personal Travel,Eco,987,4,4,4,3,3,4,5,5,5,4,5,5,5,4,8,20.0,neutral or dissatisfied +20354,88128,Female,Loyal Customer,35,Business travel,Business,3490,1,1,1,1,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +20355,37308,Male,Loyal Customer,37,Business travel,Eco,1011,4,2,2,2,4,4,4,4,4,4,4,4,2,4,0,0.0,satisfied +20356,5369,Female,disloyal Customer,18,Business travel,Business,812,0,0,0,4,2,0,2,2,5,4,4,5,4,2,0,0.0,satisfied +20357,15689,Female,Loyal Customer,48,Business travel,Business,3281,4,2,2,2,2,2,2,4,4,4,4,4,4,3,0,13.0,neutral or dissatisfied +20358,14298,Male,Loyal Customer,41,Business travel,Business,395,4,4,2,4,1,5,1,4,4,4,4,5,4,2,0,7.0,satisfied +20359,98360,Male,disloyal Customer,27,Business travel,Eco,789,5,5,5,3,4,5,4,4,5,1,1,2,1,4,0,0.0,satisfied +20360,129105,Female,Loyal Customer,21,Personal Travel,Eco,2342,1,3,1,4,3,1,3,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +20361,14145,Female,Loyal Customer,61,Personal Travel,Eco,528,4,4,4,3,4,4,5,5,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +20362,87175,Male,disloyal Customer,35,Business travel,Business,946,3,3,3,4,2,3,1,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +20363,70465,Female,Loyal Customer,54,Business travel,Business,3283,1,1,1,1,4,5,5,5,5,5,5,4,5,4,0,2.0,satisfied +20364,24717,Male,Loyal Customer,17,Personal Travel,Eco,549,2,2,2,2,3,2,3,3,2,2,3,3,3,3,0,0.0,neutral or dissatisfied +20365,15252,Female,Loyal Customer,20,Personal Travel,Eco,529,2,4,2,4,1,2,1,1,4,5,4,4,5,1,0,0.0,neutral or dissatisfied +20366,128555,Female,Loyal Customer,49,Business travel,Eco Plus,647,3,1,1,1,1,4,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +20367,101929,Male,disloyal Customer,30,Business travel,Business,628,2,2,2,4,5,2,5,5,2,3,3,4,3,5,0,9.0,neutral or dissatisfied +20368,77354,Male,Loyal Customer,43,Business travel,Business,1587,4,4,4,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +20369,1301,Female,Loyal Customer,11,Personal Travel,Eco,134,4,4,0,2,2,0,3,2,5,1,5,4,1,2,0,0.0,neutral or dissatisfied +20370,57666,Female,Loyal Customer,7,Personal Travel,Eco,200,1,4,1,1,4,1,4,4,2,4,5,5,2,4,5,13.0,neutral or dissatisfied +20371,126762,Male,Loyal Customer,54,Personal Travel,Eco,2402,1,2,1,4,4,1,4,4,4,5,4,1,3,4,42,25.0,neutral or dissatisfied +20372,50943,Female,Loyal Customer,34,Personal Travel,Eco,266,4,4,4,4,5,4,5,5,4,2,5,4,4,5,0,0.0,satisfied +20373,83711,Female,Loyal Customer,34,Business travel,Business,577,4,4,4,4,5,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +20374,38106,Female,Loyal Customer,66,Business travel,Business,1185,4,4,4,4,4,4,4,5,5,5,5,2,5,4,0,0.0,satisfied +20375,53085,Male,Loyal Customer,48,Business travel,Business,2327,1,1,1,1,5,5,5,3,4,3,2,5,5,5,0,2.0,satisfied +20376,100827,Male,disloyal Customer,29,Business travel,Business,711,4,4,4,3,5,4,2,5,3,3,5,3,5,5,0,0.0,neutral or dissatisfied +20377,68384,Male,disloyal Customer,25,Business travel,Business,1045,0,0,0,2,4,0,3,4,4,2,4,4,5,4,0,0.0,satisfied +20378,105936,Male,disloyal Customer,21,Business travel,Eco,909,1,1,1,3,1,1,2,1,2,4,4,4,4,1,1,0.0,neutral or dissatisfied +20379,22134,Male,disloyal Customer,80,Business travel,Business,350,4,4,4,3,1,4,5,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +20380,88723,Female,Loyal Customer,9,Personal Travel,Eco,581,1,4,1,3,5,1,5,5,3,5,5,3,5,5,0,3.0,neutral or dissatisfied +20381,72446,Female,Loyal Customer,64,Business travel,Business,1121,1,0,0,3,2,3,3,2,2,0,2,2,2,1,0,0.0,neutral or dissatisfied +20382,67589,Female,Loyal Customer,55,Business travel,Business,1438,5,5,5,5,2,4,5,5,5,5,5,3,5,5,81,,satisfied +20383,5734,Female,Loyal Customer,17,Personal Travel,Eco Plus,196,1,4,1,1,3,1,3,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +20384,105410,Male,Loyal Customer,61,Personal Travel,Eco Plus,369,3,3,3,4,4,3,5,4,4,1,4,1,2,4,44,50.0,neutral or dissatisfied +20385,111980,Female,Loyal Customer,22,Personal Travel,Eco,533,3,5,3,1,5,3,5,5,4,4,5,3,5,5,30,18.0,neutral or dissatisfied +20386,59658,Female,Loyal Customer,49,Personal Travel,Eco,965,1,4,1,5,2,5,4,1,1,1,1,3,1,5,7,10.0,neutral or dissatisfied +20387,101516,Female,Loyal Customer,65,Business travel,Business,345,0,0,0,2,2,5,2,2,2,2,2,2,2,2,0,0.0,satisfied +20388,13035,Female,Loyal Customer,48,Personal Travel,Eco,438,3,4,3,1,5,5,3,1,1,3,1,4,1,3,4,8.0,neutral or dissatisfied +20389,115033,Male,disloyal Customer,22,Business travel,Business,417,4,2,4,5,4,4,4,4,3,2,5,5,4,4,0,0.0,satisfied +20390,70321,Male,Loyal Customer,20,Personal Travel,Eco,1501,5,4,5,5,4,5,4,4,3,5,5,1,4,4,0,0.0,satisfied +20391,25725,Female,Loyal Customer,50,Personal Travel,Eco,432,5,3,5,1,2,5,5,3,3,5,3,3,3,2,0,0.0,satisfied +20392,109399,Female,Loyal Customer,43,Business travel,Business,1799,1,1,1,1,5,4,5,5,5,5,5,5,5,5,1,0.0,satisfied +20393,53721,Male,Loyal Customer,38,Personal Travel,Eco,1208,4,1,4,4,2,4,2,2,1,4,3,2,3,2,0,0.0,neutral or dissatisfied +20394,116010,Male,Loyal Customer,37,Personal Travel,Eco,373,2,5,2,3,5,2,5,5,4,2,3,3,4,5,8,0.0,neutral or dissatisfied +20395,72226,Female,disloyal Customer,24,Business travel,Eco,921,3,3,3,1,5,3,5,5,5,4,5,3,5,5,0,0.0,neutral or dissatisfied +20396,128004,Female,Loyal Customer,57,Personal Travel,Eco,1488,2,2,1,3,5,2,3,1,1,1,1,3,1,3,0,0.0,neutral or dissatisfied +20397,127295,Male,Loyal Customer,42,Business travel,Eco Plus,707,1,5,5,5,1,1,1,1,2,4,3,1,3,1,32,34.0,neutral or dissatisfied +20398,1014,Male,Loyal Customer,37,Business travel,Business,3222,5,5,5,5,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +20399,26100,Female,Loyal Customer,70,Personal Travel,Eco,591,4,4,4,1,4,4,5,3,3,4,3,5,3,5,30,30.0,neutral or dissatisfied +20400,125935,Male,Loyal Customer,45,Personal Travel,Eco,951,2,1,2,4,5,2,5,5,2,5,3,3,3,5,0,0.0,neutral or dissatisfied +20401,91588,Female,disloyal Customer,36,Business travel,Business,1340,3,3,3,1,5,3,5,5,4,2,5,4,5,5,32,44.0,neutral or dissatisfied +20402,39821,Male,disloyal Customer,56,Business travel,Eco,132,1,3,1,3,5,1,5,5,4,3,3,2,4,5,0,0.0,neutral or dissatisfied +20403,27631,Female,Loyal Customer,25,Business travel,Eco Plus,978,4,2,2,2,4,4,5,4,2,4,3,5,3,4,0,0.0,satisfied +20404,3535,Female,Loyal Customer,55,Personal Travel,Eco,557,3,4,2,4,3,4,3,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +20405,35416,Female,Loyal Customer,74,Business travel,Business,2762,1,2,2,2,3,4,4,1,1,1,1,1,1,2,20,35.0,neutral or dissatisfied +20406,39561,Female,Loyal Customer,31,Business travel,Business,3582,2,2,2,2,5,5,5,5,4,2,3,3,4,5,0,0.0,satisfied +20407,107021,Female,disloyal Customer,44,Business travel,Business,480,3,3,3,4,4,3,4,4,3,3,4,5,4,4,2,0.0,satisfied +20408,107040,Female,disloyal Customer,23,Business travel,Business,395,4,5,4,1,1,4,4,1,3,4,5,5,4,1,0,0.0,satisfied +20409,56992,Male,Loyal Customer,45,Personal Travel,Eco,2565,2,3,2,2,4,2,4,4,3,2,2,4,2,4,7,,neutral or dissatisfied +20410,16241,Female,disloyal Customer,16,Business travel,Eco,631,0,0,0,1,1,0,1,1,2,1,3,5,4,1,70,47.0,satisfied +20411,69507,Male,disloyal Customer,51,Personal Travel,Eco,1746,1,0,1,4,1,1,1,1,5,3,5,4,4,1,20,22.0,neutral or dissatisfied +20412,93084,Female,Loyal Customer,59,Business travel,Eco,860,3,3,5,3,1,3,4,3,3,3,3,2,3,1,5,1.0,neutral or dissatisfied +20413,149,Male,Loyal Customer,37,Business travel,Business,3758,2,3,3,3,4,3,2,2,2,2,2,3,2,1,41,50.0,neutral or dissatisfied +20414,18364,Male,disloyal Customer,38,Business travel,Eco,169,3,0,4,3,4,4,4,4,2,3,3,2,3,4,5,0.0,neutral or dissatisfied +20415,90244,Female,Loyal Customer,43,Business travel,Eco,1121,1,2,2,2,1,1,1,1,2,4,4,1,3,1,192,185.0,neutral or dissatisfied +20416,597,Female,Loyal Customer,46,Business travel,Business,3100,2,2,2,2,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +20417,100077,Male,Loyal Customer,47,Business travel,Business,289,0,0,0,3,5,4,5,3,3,3,3,5,3,3,0,0.0,satisfied +20418,41678,Female,Loyal Customer,46,Personal Travel,Eco,347,1,4,3,3,5,5,5,3,3,3,3,5,3,5,0,11.0,neutral or dissatisfied +20419,71422,Male,Loyal Customer,43,Business travel,Business,1803,2,2,2,2,5,4,5,3,3,3,3,3,3,5,0,0.0,satisfied +20420,30907,Male,Loyal Customer,31,Business travel,Business,896,5,5,5,5,5,5,5,5,2,5,3,4,5,5,0,7.0,satisfied +20421,4192,Female,disloyal Customer,26,Business travel,Business,427,4,4,4,4,3,4,3,3,2,3,3,2,3,3,26,29.0,neutral or dissatisfied +20422,59979,Male,Loyal Customer,67,Personal Travel,Eco,937,3,1,2,3,2,2,2,2,1,3,3,4,4,2,34,13.0,neutral or dissatisfied +20423,32166,Male,Loyal Customer,33,Business travel,Business,2653,0,5,0,2,5,5,5,5,5,2,3,2,2,5,0,0.0,satisfied +20424,117746,Female,Loyal Customer,8,Personal Travel,Eco,935,4,4,4,5,3,4,3,3,5,5,5,4,5,3,6,0.0,neutral or dissatisfied +20425,41966,Female,disloyal Customer,26,Business travel,Eco,525,2,1,2,3,3,2,3,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +20426,83240,Female,Loyal Customer,41,Business travel,Business,1979,2,2,5,2,5,3,4,4,4,4,4,4,4,4,0,0.0,satisfied +20427,4283,Female,Loyal Customer,55,Personal Travel,Eco,502,2,5,2,4,5,4,4,4,4,2,2,5,4,5,0,8.0,neutral or dissatisfied +20428,77829,Male,Loyal Customer,19,Personal Travel,Eco,874,3,2,3,3,4,3,4,4,2,5,3,1,3,4,0,12.0,neutral or dissatisfied +20429,53443,Male,disloyal Customer,37,Business travel,Eco,2419,2,2,2,3,2,1,5,4,3,4,1,5,4,5,113,102.0,neutral or dissatisfied +20430,68072,Female,disloyal Customer,16,Business travel,Eco,813,1,1,1,3,2,1,2,2,1,1,4,2,4,2,0,0.0,neutral or dissatisfied +20431,55890,Female,disloyal Customer,38,Business travel,Business,473,4,4,4,4,3,4,3,3,4,2,4,5,5,3,0,0.0,satisfied +20432,54777,Male,Loyal Customer,61,Personal Travel,Eco Plus,964,3,5,3,5,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +20433,68261,Female,Loyal Customer,53,Personal Travel,Eco,631,2,5,2,5,3,5,4,1,1,2,1,3,1,5,0,13.0,neutral or dissatisfied +20434,1274,Male,Loyal Customer,10,Personal Travel,Eco,113,1,1,1,3,4,1,4,4,3,3,3,3,3,4,0,9.0,neutral or dissatisfied +20435,67631,Male,Loyal Customer,53,Business travel,Business,1188,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20436,26244,Male,Loyal Customer,39,Personal Travel,Eco,270,2,5,2,2,3,2,3,3,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +20437,48832,Male,Loyal Customer,65,Personal Travel,Business,421,2,2,2,3,2,2,3,3,3,2,5,2,3,1,0,2.0,neutral or dissatisfied +20438,72422,Male,Loyal Customer,39,Business travel,Business,985,1,1,1,1,3,4,5,4,4,5,4,3,4,3,0,7.0,satisfied +20439,13707,Female,Loyal Customer,63,Personal Travel,Eco Plus,300,4,2,4,4,2,4,3,5,5,4,5,2,5,4,117,114.0,neutral or dissatisfied +20440,29439,Female,Loyal Customer,51,Business travel,Business,421,1,1,1,1,1,2,3,4,4,4,4,4,4,2,0,0.0,satisfied +20441,8893,Female,Loyal Customer,20,Personal Travel,Eco,622,2,4,2,3,2,2,2,2,3,4,5,5,5,2,0,0.0,neutral or dissatisfied +20442,101743,Male,Loyal Customer,43,Business travel,Business,1590,1,1,1,1,3,3,5,4,4,5,4,5,4,3,0,0.0,satisfied +20443,48151,Male,Loyal Customer,33,Business travel,Business,1955,4,1,4,1,4,4,4,4,2,5,4,4,4,4,0,0.0,neutral or dissatisfied +20444,104735,Female,Loyal Customer,25,Business travel,Business,1342,4,4,4,4,5,5,5,5,4,3,5,5,5,5,0,0.0,satisfied +20445,40290,Female,Loyal Customer,26,Personal Travel,Eco,402,2,5,2,4,5,2,5,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +20446,107543,Male,Loyal Customer,48,Business travel,Business,1680,4,4,4,4,4,4,4,3,3,3,3,4,3,5,51,27.0,satisfied +20447,30873,Female,disloyal Customer,48,Business travel,Eco,1506,2,2,2,4,1,2,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +20448,44885,Male,Loyal Customer,36,Business travel,Eco,557,3,1,1,1,3,4,3,3,5,2,3,5,3,3,0,0.0,satisfied +20449,88018,Female,disloyal Customer,24,Business travel,Eco,545,4,0,4,2,5,4,5,5,5,3,4,4,5,5,7,18.0,satisfied +20450,28945,Female,Loyal Customer,46,Business travel,Business,2795,3,5,3,5,5,3,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +20451,124544,Female,Loyal Customer,47,Personal Travel,Eco,1276,2,5,2,4,4,4,5,1,1,2,1,3,1,5,0,5.0,neutral or dissatisfied +20452,107296,Female,Loyal Customer,40,Personal Travel,Eco,307,3,3,4,5,3,4,3,3,2,5,1,2,2,3,18,9.0,neutral or dissatisfied +20453,26358,Male,Loyal Customer,31,Business travel,Business,2559,2,4,2,2,5,4,5,5,2,1,5,3,1,5,0,0.0,satisfied +20454,47633,Female,Loyal Customer,72,Business travel,Business,1235,2,2,2,2,1,5,4,4,4,4,4,2,4,5,0,0.0,satisfied +20455,31066,Female,Loyal Customer,67,Personal Travel,Eco,862,2,5,2,4,2,5,5,1,1,2,1,5,1,3,0,0.0,neutral or dissatisfied +20456,6049,Male,Loyal Customer,57,Personal Travel,Eco,691,4,3,4,4,1,4,1,1,3,3,3,1,4,1,0,0.0,neutral or dissatisfied +20457,64153,Male,Loyal Customer,28,Business travel,Business,989,3,4,5,4,3,3,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +20458,10499,Male,Loyal Customer,51,Business travel,Business,3334,3,3,3,3,2,4,4,5,5,5,5,4,5,3,6,0.0,satisfied +20459,60917,Male,Loyal Customer,60,Business travel,Business,888,2,5,1,5,2,4,4,2,2,2,2,3,2,3,106,81.0,neutral or dissatisfied +20460,19157,Female,Loyal Customer,53,Business travel,Eco,304,5,5,5,5,4,3,4,4,4,5,4,2,4,3,0,0.0,satisfied +20461,68845,Female,Loyal Customer,34,Business travel,Business,2385,3,4,3,3,5,4,5,4,4,4,4,5,4,4,0,2.0,satisfied +20462,75517,Female,Loyal Customer,33,Business travel,Business,1774,3,1,3,3,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +20463,66909,Female,Loyal Customer,23,Business travel,Business,2753,3,3,3,3,4,4,4,4,3,5,4,3,5,4,0,65.0,satisfied +20464,80354,Male,disloyal Customer,25,Business travel,Business,422,2,4,2,3,4,2,4,4,4,2,4,4,5,4,0,1.0,neutral or dissatisfied +20465,8826,Female,Loyal Customer,22,Personal Travel,Eco,522,3,5,3,1,2,3,2,2,3,3,5,5,5,2,0,0.0,neutral or dissatisfied +20466,69503,Male,Loyal Customer,65,Personal Travel,Eco Plus,1096,4,1,4,3,4,4,4,4,2,2,1,2,3,4,15,33.0,neutral or dissatisfied +20467,77508,Female,Loyal Customer,49,Business travel,Business,1587,5,5,1,5,2,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +20468,70732,Female,disloyal Customer,21,Business travel,Eco,675,4,4,4,3,2,4,2,2,2,3,3,4,3,2,0,,neutral or dissatisfied +20469,78121,Female,Loyal Customer,26,Personal Travel,Eco,1797,1,4,1,2,4,1,4,4,2,5,5,5,1,4,0,0.0,neutral or dissatisfied +20470,59562,Female,disloyal Customer,24,Business travel,Business,964,4,5,4,2,1,4,1,1,5,4,5,4,4,1,0,0.0,satisfied +20471,22603,Male,Loyal Customer,33,Business travel,Eco,223,1,5,5,5,1,1,1,1,4,3,2,4,3,1,29,24.0,neutral or dissatisfied +20472,118351,Female,Loyal Customer,57,Personal Travel,Eco,639,1,5,1,4,4,5,4,5,5,1,5,4,5,4,23,20.0,neutral or dissatisfied +20473,126212,Female,Loyal Customer,30,Business travel,Business,631,4,4,2,4,4,4,4,4,3,3,3,1,3,4,41,37.0,neutral or dissatisfied +20474,23446,Male,Loyal Customer,45,Business travel,Eco,576,4,1,1,1,4,4,4,4,5,3,4,1,4,4,0,0.0,satisfied +20475,14725,Female,Loyal Customer,22,Business travel,Eco Plus,479,5,5,5,5,5,5,3,5,3,5,3,4,5,5,0,6.0,satisfied +20476,49949,Male,Loyal Customer,65,Business travel,Eco,153,3,3,3,3,3,3,3,3,1,3,3,1,3,3,19,11.0,neutral or dissatisfied +20477,62593,Male,Loyal Customer,23,Business travel,Eco,346,0,4,0,3,5,0,5,5,2,1,5,4,5,5,0,0.0,satisfied +20478,69931,Male,Loyal Customer,66,Personal Travel,Eco Plus,1514,1,5,0,5,5,0,5,5,3,2,5,3,4,5,0,0.0,neutral or dissatisfied +20479,65412,Female,Loyal Customer,49,Business travel,Business,631,2,2,2,2,5,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +20480,36923,Male,Loyal Customer,59,Personal Travel,Eco,740,2,4,2,4,1,2,1,1,4,5,4,3,5,1,11,43.0,neutral or dissatisfied +20481,120060,Male,Loyal Customer,52,Business travel,Business,683,3,3,3,3,3,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +20482,122271,Female,Loyal Customer,33,Personal Travel,Eco,544,3,4,2,4,1,2,5,1,4,3,2,1,2,1,0,0.0,neutral or dissatisfied +20483,107660,Male,Loyal Customer,46,Business travel,Business,251,1,1,1,1,3,4,5,4,4,4,4,4,4,3,9,1.0,satisfied +20484,77169,Male,disloyal Customer,26,Business travel,Business,1355,4,4,4,1,1,4,1,1,3,5,5,3,4,1,0,0.0,satisfied +20485,2567,Female,Loyal Customer,40,Business travel,Business,3311,5,5,5,5,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +20486,42962,Male,disloyal Customer,23,Business travel,Eco,391,5,3,5,2,2,5,1,2,3,1,4,3,5,2,0,0.0,satisfied +20487,11672,Female,disloyal Customer,23,Business travel,Eco,395,2,0,3,5,4,3,4,4,5,2,5,5,5,4,45,67.0,neutral or dissatisfied +20488,49042,Female,Loyal Customer,35,Business travel,Business,2008,1,1,4,1,5,4,2,4,4,4,5,3,4,1,0,0.0,satisfied +20489,39175,Male,Loyal Customer,43,Business travel,Business,237,0,0,0,3,2,5,1,1,1,1,1,3,1,5,0,0.0,satisfied +20490,84521,Male,Loyal Customer,28,Business travel,Business,2556,3,3,3,3,3,4,3,3,3,3,5,3,5,3,0,,satisfied +20491,83953,Female,Loyal Customer,60,Business travel,Business,1715,3,3,1,3,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +20492,75348,Male,Loyal Customer,50,Personal Travel,Eco,2615,2,5,2,3,2,3,3,5,4,5,5,3,3,3,0,16.0,neutral or dissatisfied +20493,20920,Female,disloyal Customer,52,Business travel,Eco,721,4,3,3,1,5,3,5,5,3,3,1,5,1,5,0,0.0,satisfied +20494,37665,Male,Loyal Customer,45,Personal Travel,Eco,1010,3,4,3,3,2,3,3,2,3,4,1,5,1,2,0,5.0,neutral or dissatisfied +20495,116281,Female,Loyal Customer,55,Personal Travel,Eco,446,1,4,5,3,5,5,4,4,4,5,4,3,4,4,5,8.0,neutral or dissatisfied +20496,128219,Female,Loyal Customer,53,Business travel,Eco,602,1,0,0,4,1,3,3,3,3,1,3,4,3,2,29,25.0,neutral or dissatisfied +20497,97197,Male,Loyal Customer,15,Personal Travel,Eco,1642,3,5,3,1,4,3,4,4,3,5,5,2,2,4,0,3.0,neutral or dissatisfied +20498,107613,Female,Loyal Customer,29,Business travel,Business,423,1,3,3,3,1,1,1,1,4,3,3,3,3,1,15,6.0,neutral or dissatisfied +20499,26248,Female,Loyal Customer,56,Business travel,Eco Plus,515,4,5,5,5,2,1,5,4,4,4,4,1,4,4,0,0.0,satisfied +20500,116479,Female,Loyal Customer,10,Personal Travel,Eco,342,1,2,1,3,2,1,2,2,4,2,3,4,4,2,0,0.0,neutral or dissatisfied +20501,11001,Male,Loyal Customer,46,Business travel,Eco,295,4,5,5,5,3,4,3,3,3,3,5,1,3,3,0,0.0,satisfied +20502,33596,Female,disloyal Customer,24,Business travel,Business,399,1,4,1,4,2,1,2,2,4,1,4,4,4,2,0,0.0,neutral or dissatisfied +20503,45024,Male,disloyal Customer,27,Business travel,Eco Plus,118,3,3,3,4,4,3,4,4,2,5,2,1,2,4,7,0.0,neutral or dissatisfied +20504,27598,Female,Loyal Customer,69,Personal Travel,Eco,679,2,5,2,4,5,4,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +20505,41217,Male,Loyal Customer,10,Personal Travel,Eco,1174,3,4,3,3,3,3,3,3,3,5,4,1,4,3,0,0.0,neutral or dissatisfied +20506,126704,Female,Loyal Customer,58,Business travel,Business,2370,4,4,4,4,3,5,4,4,4,4,4,5,4,5,3,0.0,satisfied +20507,36785,Female,Loyal Customer,38,Business travel,Eco,1088,4,4,1,4,4,4,4,1,3,2,1,4,5,4,9,0.0,satisfied +20508,103781,Female,disloyal Customer,29,Business travel,Business,882,3,4,4,4,3,4,3,3,3,4,4,4,4,3,10,0.0,neutral or dissatisfied +20509,124371,Female,disloyal Customer,22,Business travel,Eco,808,4,4,4,4,5,4,5,5,1,5,3,2,4,5,0,0.0,neutral or dissatisfied +20510,94048,Female,Loyal Customer,39,Business travel,Business,3421,4,4,4,4,2,5,5,4,4,4,4,3,4,4,11,4.0,satisfied +20511,74169,Male,Loyal Customer,22,Personal Travel,Eco,592,2,3,2,4,3,2,3,3,4,5,2,3,5,3,9,22.0,neutral or dissatisfied +20512,94519,Female,disloyal Customer,30,Business travel,Eco,562,2,3,2,4,4,2,4,4,1,2,4,3,4,4,0,0.0,neutral or dissatisfied +20513,77201,Male,Loyal Customer,52,Business travel,Business,2994,1,1,1,1,5,5,5,3,2,5,4,5,4,5,2,0.0,satisfied +20514,114143,Male,Loyal Customer,29,Business travel,Business,967,5,5,5,5,4,4,4,4,5,3,4,3,5,4,36,72.0,satisfied +20515,68305,Female,Loyal Customer,37,Personal Travel,Eco,1797,2,5,2,2,3,2,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +20516,84837,Male,Loyal Customer,19,Business travel,Eco,547,2,3,3,3,2,2,4,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +20517,9051,Female,Loyal Customer,41,Business travel,Business,160,3,5,3,3,3,4,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +20518,118526,Male,disloyal Customer,26,Business travel,Business,304,1,0,1,2,1,1,1,1,4,2,4,4,5,1,0,0.0,neutral or dissatisfied +20519,20030,Female,Loyal Customer,55,Business travel,Eco,528,4,2,2,2,5,3,3,4,4,4,4,4,4,1,27,22.0,neutral or dissatisfied +20520,38431,Male,disloyal Customer,15,Business travel,Eco,965,5,5,5,3,5,5,5,5,2,1,2,3,4,5,0,0.0,satisfied +20521,42067,Female,Loyal Customer,55,Personal Travel,Eco,241,4,4,4,3,4,5,4,5,5,4,5,5,5,5,0,0.0,satisfied +20522,75361,Female,Loyal Customer,61,Business travel,Eco Plus,986,4,3,4,3,3,3,3,4,4,4,4,5,4,5,0,0.0,satisfied +20523,10103,Male,Loyal Customer,41,Business travel,Business,3074,4,4,5,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +20524,2789,Female,Loyal Customer,35,Business travel,Business,765,3,3,2,3,2,3,4,3,3,3,3,1,3,4,0,21.0,neutral or dissatisfied +20525,65273,Male,Loyal Customer,47,Personal Travel,Eco Plus,469,1,5,1,4,3,1,5,3,5,1,4,4,1,3,2,0.0,neutral or dissatisfied +20526,55130,Female,Loyal Customer,39,Personal Travel,Eco,1346,3,5,3,2,1,3,1,1,4,5,3,4,5,1,0,0.0,neutral or dissatisfied +20527,92911,Female,Loyal Customer,38,Business travel,Business,1522,4,1,1,1,3,3,4,4,4,4,4,3,4,3,23,21.0,neutral or dissatisfied +20528,100797,Female,Loyal Customer,45,Business travel,Business,748,2,2,2,2,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +20529,67986,Female,Loyal Customer,54,Business travel,Eco Plus,835,3,5,5,5,3,2,2,3,3,3,3,3,3,2,3,9.0,neutral or dissatisfied +20530,40166,Male,disloyal Customer,46,Business travel,Eco,387,2,4,2,5,2,2,2,2,2,3,2,2,1,2,0,0.0,neutral or dissatisfied +20531,10623,Male,disloyal Customer,22,Business travel,Eco,216,2,3,2,3,1,2,1,1,1,4,4,4,4,1,0,0.0,neutral or dissatisfied +20532,47848,Male,Loyal Customer,67,Business travel,Business,1739,4,3,2,2,4,3,3,4,4,4,4,3,4,4,0,0.0,neutral or dissatisfied +20533,81242,Male,Loyal Customer,45,Business travel,Business,930,4,4,4,4,3,5,5,4,4,4,4,3,4,3,48,60.0,satisfied +20534,115451,Male,Loyal Customer,41,Business travel,Business,1631,5,5,5,5,4,5,5,4,4,4,4,5,4,4,0,2.0,satisfied +20535,115626,Female,Loyal Customer,58,Business travel,Eco,337,2,2,2,2,5,3,3,2,2,2,2,3,2,1,28,27.0,neutral or dissatisfied +20536,51729,Female,Loyal Customer,8,Personal Travel,Eco,493,2,5,5,2,5,5,5,5,3,3,5,5,4,5,0,0.0,neutral or dissatisfied +20537,77618,Female,disloyal Customer,24,Business travel,Business,731,5,0,5,3,1,5,1,1,5,2,4,3,4,1,36,44.0,satisfied +20538,2472,Female,Loyal Customer,25,Personal Travel,Eco,722,3,1,3,2,3,3,3,3,4,2,2,2,1,3,10,15.0,neutral or dissatisfied +20539,119333,Male,Loyal Customer,19,Personal Travel,Eco,214,4,1,4,1,3,4,3,3,1,5,1,3,2,3,16,28.0,neutral or dissatisfied +20540,6794,Male,Loyal Customer,44,Business travel,Eco,235,2,1,1,1,2,2,2,2,1,5,2,4,2,2,48,38.0,neutral or dissatisfied +20541,54493,Male,Loyal Customer,38,Business travel,Eco,925,1,3,3,3,1,1,1,1,4,1,4,2,4,1,0,0.0,neutral or dissatisfied +20542,88073,Male,disloyal Customer,37,Business travel,Business,406,4,4,4,4,4,4,4,4,5,4,4,3,5,4,0,0.0,satisfied +20543,42631,Male,Loyal Customer,33,Business travel,Business,481,2,2,2,2,5,5,5,5,3,1,5,4,4,5,0,0.0,satisfied +20544,87112,Female,Loyal Customer,54,Personal Travel,Eco,594,3,5,3,4,3,3,4,2,2,3,2,2,2,3,2,4.0,neutral or dissatisfied +20545,89525,Male,Loyal Customer,36,Personal Travel,Business,1047,3,4,3,3,3,4,5,2,2,3,3,5,2,3,13,0.0,neutral or dissatisfied +20546,61973,Male,Loyal Customer,39,Business travel,Business,2475,3,3,3,3,3,5,5,4,4,4,4,4,4,3,17,36.0,satisfied +20547,125520,Female,Loyal Customer,58,Business travel,Business,1595,0,0,0,2,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +20548,86318,Male,Loyal Customer,40,Personal Travel,Eco Plus,226,3,1,3,3,5,3,4,5,2,5,4,2,3,5,0,1.0,neutral or dissatisfied +20549,100508,Female,Loyal Customer,49,Business travel,Business,3313,2,2,2,2,5,4,4,4,4,4,4,3,4,3,0,5.0,satisfied +20550,104551,Male,Loyal Customer,61,Business travel,Business,3960,2,2,2,2,4,5,5,5,5,5,5,3,5,5,0,11.0,satisfied +20551,10428,Female,Loyal Customer,52,Business travel,Business,308,4,1,4,4,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +20552,98996,Male,Loyal Customer,9,Personal Travel,Eco,543,3,4,3,5,2,3,2,2,3,2,4,5,4,2,0,0.0,neutral or dissatisfied +20553,92413,Male,Loyal Customer,44,Business travel,Business,1947,4,3,4,4,2,3,4,4,4,4,4,4,4,5,0,15.0,satisfied +20554,5137,Female,Loyal Customer,70,Personal Travel,Eco,184,2,4,2,4,3,4,5,2,2,2,3,3,2,3,3,0.0,neutral or dissatisfied +20555,81315,Male,Loyal Customer,51,Business travel,Business,1299,1,1,4,1,2,5,5,4,4,4,4,3,4,4,19,0.0,satisfied +20556,127987,Male,Loyal Customer,15,Personal Travel,Eco,1149,4,4,3,4,5,3,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +20557,24644,Male,Loyal Customer,29,Personal Travel,Eco Plus,526,4,4,4,4,1,4,1,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +20558,87336,Female,Loyal Customer,47,Personal Travel,Business,425,3,4,3,2,2,4,4,2,2,3,2,4,2,4,1,0.0,neutral or dissatisfied +20559,46407,Female,Loyal Customer,61,Business travel,Business,458,3,3,3,3,5,1,4,4,4,4,4,3,4,5,0,0.0,satisfied +20560,23170,Male,Loyal Customer,14,Personal Travel,Eco,223,3,4,0,2,3,0,3,3,4,3,4,5,5,3,0,0.0,neutral or dissatisfied +20561,65396,Male,Loyal Customer,21,Personal Travel,Eco,631,2,3,2,2,3,2,3,3,5,3,3,5,2,3,0,0.0,neutral or dissatisfied +20562,28836,Male,Loyal Customer,46,Business travel,Business,3984,3,3,3,3,4,1,5,2,2,2,2,3,2,1,0,0.0,satisfied +20563,94140,Female,disloyal Customer,39,Business travel,Business,319,1,1,1,4,1,1,1,1,4,3,4,3,5,1,7,0.0,neutral or dissatisfied +20564,84068,Male,disloyal Customer,25,Business travel,Eco,757,2,2,2,3,5,2,4,5,2,5,3,3,4,5,0,0.0,neutral or dissatisfied +20565,87076,Female,Loyal Customer,37,Business travel,Business,594,4,4,1,4,2,5,5,4,4,4,4,3,4,4,14,0.0,satisfied +20566,87711,Male,Loyal Customer,39,Personal Travel,Eco,591,1,1,0,3,5,0,5,5,4,2,3,2,2,5,0,5.0,neutral or dissatisfied +20567,25943,Female,Loyal Customer,18,Business travel,Eco Plus,594,1,1,1,1,1,1,2,1,3,3,4,2,4,1,1,14.0,neutral or dissatisfied +20568,27925,Female,Loyal Customer,30,Personal Travel,Eco,689,3,5,3,2,2,3,1,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +20569,104990,Female,Loyal Customer,51,Personal Travel,Eco,337,1,1,1,3,2,3,3,3,3,1,3,2,3,2,13,4.0,neutral or dissatisfied +20570,7520,Female,Loyal Customer,38,Business travel,Business,3131,3,3,3,3,4,5,4,4,4,4,4,5,4,4,4,0.0,satisfied +20571,127381,Female,Loyal Customer,46,Business travel,Business,3000,1,1,4,1,2,5,4,4,4,5,4,3,4,3,2,1.0,satisfied +20572,102116,Female,Loyal Customer,32,Business travel,Business,3627,3,3,3,3,4,4,5,4,3,2,4,5,4,4,0,0.0,satisfied +20573,75614,Male,Loyal Customer,48,Personal Travel,Eco,337,3,4,3,3,4,3,4,4,4,2,4,4,5,4,0,5.0,neutral or dissatisfied +20574,43631,Female,Loyal Customer,46,Personal Travel,Eco,297,4,4,4,4,2,4,5,2,2,4,2,4,2,3,0,0.0,satisfied +20575,50012,Female,disloyal Customer,20,Business travel,Eco,308,3,1,3,3,2,3,2,2,2,4,2,3,2,2,0,0.0,neutral or dissatisfied +20576,1118,Female,Loyal Customer,69,Personal Travel,Eco,89,2,5,2,4,4,5,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +20577,546,Female,disloyal Customer,59,Business travel,Business,134,4,4,4,1,3,4,3,3,5,2,4,4,4,3,13,14.0,neutral or dissatisfied +20578,128701,Male,Loyal Customer,54,Business travel,Business,1464,1,0,0,4,3,3,4,5,5,0,1,3,5,3,72,55.0,neutral or dissatisfied +20579,38672,Male,Loyal Customer,31,Personal Travel,Eco,2704,1,3,1,4,2,1,2,2,1,4,4,4,3,2,32,21.0,neutral or dissatisfied +20580,117661,Female,Loyal Customer,77,Business travel,Eco,1449,3,4,2,4,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +20581,67141,Female,disloyal Customer,27,Business travel,Eco,1121,5,5,5,5,2,5,3,2,3,3,1,3,1,2,0,4.0,satisfied +20582,49390,Female,Loyal Customer,40,Business travel,Business,3291,4,4,2,4,3,3,1,4,4,4,4,2,4,1,0,0.0,satisfied +20583,259,Female,Loyal Customer,55,Business travel,Business,612,4,3,3,3,5,4,3,4,4,4,4,3,4,2,14,19.0,neutral or dissatisfied +20584,56577,Male,Loyal Customer,47,Business travel,Business,3075,3,3,3,3,3,5,4,5,5,5,5,3,5,4,77,58.0,satisfied +20585,44398,Male,disloyal Customer,27,Business travel,Eco,342,1,1,1,2,4,1,4,4,2,2,2,1,3,4,5,0.0,neutral or dissatisfied +20586,79724,Male,Loyal Customer,41,Personal Travel,Eco,712,3,5,3,5,4,3,4,4,5,5,4,3,5,4,0,0.0,neutral or dissatisfied +20587,35317,Female,disloyal Customer,21,Business travel,Eco,1028,4,4,4,5,3,4,3,3,3,3,2,5,4,3,0,0.0,satisfied +20588,51926,Female,disloyal Customer,25,Business travel,Eco Plus,601,4,2,4,4,1,4,1,1,4,1,3,4,3,1,0,0.0,neutral or dissatisfied +20589,22865,Female,Loyal Customer,65,Personal Travel,Eco,302,1,5,1,3,4,5,4,3,3,1,5,4,3,5,0,0.0,neutral or dissatisfied +20590,48601,Male,Loyal Customer,56,Personal Travel,Eco,848,2,4,2,1,4,2,4,4,4,3,4,3,4,4,61,69.0,neutral or dissatisfied +20591,7343,Female,Loyal Customer,21,Personal Travel,Eco,606,4,5,4,1,5,4,5,5,3,3,5,5,4,5,24,13.0,neutral or dissatisfied +20592,21575,Female,Loyal Customer,70,Personal Travel,Eco Plus,331,1,4,1,2,5,3,3,3,3,1,2,4,3,3,0,0.0,neutral or dissatisfied +20593,102944,Female,Loyal Customer,11,Personal Travel,Business,719,1,4,1,2,4,1,1,4,4,4,2,3,4,4,5,0.0,neutral or dissatisfied +20594,72692,Female,Loyal Customer,39,Personal Travel,Eco,1121,3,5,3,5,3,3,3,3,4,3,4,4,4,3,0,13.0,neutral or dissatisfied +20595,129039,Male,disloyal Customer,24,Business travel,Business,1051,5,5,5,3,2,5,2,2,5,2,5,3,4,2,0,2.0,satisfied +20596,45226,Male,Loyal Customer,63,Business travel,Eco,911,4,4,4,4,5,4,5,5,2,5,3,3,4,5,130,124.0,neutral or dissatisfied +20597,113758,Female,Loyal Customer,35,Personal Travel,Eco,226,4,4,0,5,2,0,3,2,3,5,5,3,4,2,1,0.0,neutral or dissatisfied +20598,89275,Female,Loyal Customer,80,Business travel,Eco,453,2,5,5,5,2,4,3,2,2,2,2,2,2,4,28,28.0,neutral or dissatisfied +20599,12354,Female,disloyal Customer,15,Business travel,Eco,192,4,2,4,3,3,4,3,3,4,2,3,1,4,3,9,1.0,neutral or dissatisfied +20600,63236,Female,Loyal Customer,27,Business travel,Business,3949,4,4,4,4,5,4,5,5,5,5,5,4,5,5,21,0.0,satisfied +20601,25169,Male,disloyal Customer,44,Business travel,Eco,369,3,0,3,2,4,3,4,4,1,1,1,1,5,4,0,0.0,neutral or dissatisfied +20602,70812,Female,disloyal Customer,24,Business travel,Eco,624,5,5,5,3,4,5,4,4,5,2,5,4,5,4,0,0.0,satisfied +20603,107650,Male,Loyal Customer,31,Personal Travel,Business,405,3,5,3,2,1,3,1,1,3,5,5,4,4,1,5,0.0,neutral or dissatisfied +20604,27958,Female,Loyal Customer,36,Business travel,Business,1770,3,2,3,3,1,2,3,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +20605,28202,Female,Loyal Customer,19,Personal Travel,Eco,550,2,3,2,3,1,2,1,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +20606,31653,Male,Loyal Customer,48,Business travel,Eco,967,4,5,3,3,4,4,4,4,2,4,5,1,1,4,38,37.0,satisfied +20607,76547,Female,Loyal Customer,36,Business travel,Business,1648,1,1,1,1,3,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +20608,14066,Male,Loyal Customer,33,Business travel,Business,2963,2,2,2,2,3,3,3,3,1,4,3,1,3,3,0,0.0,satisfied +20609,114264,Male,Loyal Customer,44,Business travel,Eco,509,3,4,4,4,4,3,4,4,4,1,5,2,1,4,3,3.0,satisfied +20610,53153,Male,Loyal Customer,29,Business travel,Eco Plus,955,4,3,3,3,4,4,4,4,2,2,1,2,1,4,1,0.0,satisfied +20611,123531,Male,disloyal Customer,27,Business travel,Eco Plus,2296,2,2,2,3,5,2,5,5,4,5,2,1,2,5,1,0.0,neutral or dissatisfied +20612,117183,Male,Loyal Customer,54,Personal Travel,Eco,304,5,5,5,3,3,5,3,3,4,4,5,4,5,3,1,0.0,satisfied +20613,3853,Male,Loyal Customer,55,Personal Travel,Eco,650,1,5,2,3,3,2,3,3,4,4,1,2,3,3,0,0.0,neutral or dissatisfied +20614,49622,Female,Loyal Customer,46,Business travel,Business,363,3,3,4,3,3,4,3,4,4,4,4,5,4,1,0,0.0,satisfied +20615,81770,Male,disloyal Customer,23,Business travel,Eco,1306,2,2,2,4,5,2,5,5,5,3,5,3,5,5,0,12.0,neutral or dissatisfied +20616,35496,Male,Loyal Customer,52,Personal Travel,Eco,944,3,3,3,2,2,3,2,2,3,1,1,2,1,2,0,0.0,neutral or dissatisfied +20617,125791,Female,Loyal Customer,28,Business travel,Business,2174,4,4,4,4,4,4,4,4,4,5,4,5,5,4,9,0.0,satisfied +20618,961,Male,disloyal Customer,33,Business travel,Business,354,4,4,4,3,2,4,2,2,3,2,3,4,4,2,4,0.0,neutral or dissatisfied +20619,53536,Male,Loyal Customer,27,Business travel,Eco Plus,2419,1,3,3,3,1,1,1,3,2,2,3,1,2,1,29,35.0,neutral or dissatisfied +20620,30995,Male,disloyal Customer,38,Business travel,Eco,391,5,5,5,1,1,5,1,1,4,2,3,3,2,1,16,15.0,satisfied +20621,101417,Male,Loyal Customer,55,Business travel,Business,2324,4,4,5,4,2,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +20622,43342,Male,Loyal Customer,24,Business travel,Business,387,3,3,3,3,3,3,3,3,3,5,3,1,4,3,18,23.0,neutral or dissatisfied +20623,8627,Male,Loyal Customer,41,Business travel,Business,1698,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,1.0,satisfied +20624,34967,Male,disloyal Customer,22,Business travel,Eco,273,4,2,4,2,5,4,5,5,4,2,4,5,3,5,43,36.0,satisfied +20625,56534,Male,Loyal Customer,46,Business travel,Business,3446,4,4,4,4,4,5,5,5,5,5,5,4,5,5,15,14.0,satisfied +20626,118162,Female,Loyal Customer,53,Business travel,Business,1440,1,1,5,1,2,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +20627,126158,Male,Loyal Customer,26,Business travel,Business,3956,3,1,1,1,3,3,3,3,3,3,3,2,4,3,26,18.0,neutral or dissatisfied +20628,30448,Male,Loyal Customer,45,Business travel,Eco,991,4,3,2,2,4,4,4,4,3,4,4,5,5,4,33,23.0,satisfied +20629,87311,Male,Loyal Customer,56,Business travel,Business,3216,4,4,4,4,2,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +20630,21986,Male,Loyal Customer,25,Personal Travel,Eco,500,0,5,0,2,2,0,2,2,4,5,4,4,4,2,10,1.0,satisfied +20631,16310,Male,disloyal Customer,25,Business travel,Eco,628,3,0,3,3,2,3,4,2,5,2,3,2,2,2,0,0.0,neutral or dissatisfied +20632,72516,Male,disloyal Customer,11,Business travel,Eco,1121,2,3,3,3,4,3,4,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +20633,68979,Female,Loyal Customer,42,Personal Travel,Eco,700,1,3,1,2,1,3,1,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +20634,60484,Female,Loyal Customer,46,Business travel,Eco,862,2,3,5,3,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +20635,52191,Female,Loyal Customer,26,Business travel,Eco,598,4,3,3,3,4,4,5,4,4,3,3,4,2,4,0,0.0,satisfied +20636,115125,Male,Loyal Customer,53,Business travel,Business,1704,1,1,1,1,4,4,5,4,4,4,4,4,4,4,12,8.0,satisfied +20637,73363,Female,disloyal Customer,27,Business travel,Business,1182,5,5,5,3,3,5,3,3,3,3,5,5,5,3,12,36.0,satisfied +20638,2824,Female,Loyal Customer,48,Business travel,Business,2026,1,1,1,1,2,5,4,4,4,4,4,4,4,4,2,0.0,satisfied +20639,22163,Female,Loyal Customer,48,Business travel,Eco,565,4,2,2,2,5,3,2,4,4,4,4,5,4,3,35,28.0,satisfied +20640,92426,Male,disloyal Customer,39,Business travel,Business,1947,3,3,3,3,2,3,2,2,5,3,5,3,5,2,0,13.0,neutral or dissatisfied +20641,85377,Male,Loyal Customer,56,Business travel,Business,1914,3,3,3,3,5,4,4,5,5,5,5,5,5,5,12,16.0,satisfied +20642,6655,Male,disloyal Customer,26,Business travel,Business,438,0,0,0,1,4,0,4,4,5,5,4,5,5,4,0,0.0,satisfied +20643,73605,Female,Loyal Customer,56,Business travel,Business,2444,4,4,4,4,5,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +20644,69014,Female,disloyal Customer,49,Business travel,Business,1521,2,2,2,5,2,2,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +20645,113588,Female,Loyal Customer,59,Business travel,Eco,407,3,3,3,3,3,3,3,3,3,3,3,4,3,1,29,22.0,neutral or dissatisfied +20646,72274,Female,Loyal Customer,47,Business travel,Business,921,3,5,5,5,3,3,3,3,3,3,3,1,3,3,0,2.0,neutral or dissatisfied +20647,20371,Female,Loyal Customer,18,Personal Travel,Eco,287,4,4,5,3,3,5,3,3,4,3,5,3,4,3,4,0.0,satisfied +20648,38785,Female,Loyal Customer,54,Business travel,Eco,387,2,2,2,2,2,3,3,2,2,2,2,4,2,3,26,24.0,neutral or dissatisfied +20649,10651,Female,Loyal Customer,59,Business travel,Business,316,2,2,2,2,4,4,5,5,5,5,5,3,5,5,0,2.0,satisfied +20650,52504,Female,Loyal Customer,39,Business travel,Business,110,3,3,3,3,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20651,65565,Female,Loyal Customer,48,Business travel,Business,1932,4,4,4,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +20652,66233,Female,Loyal Customer,38,Business travel,Business,2935,2,1,1,1,2,4,4,2,2,2,2,3,2,4,0,1.0,neutral or dissatisfied +20653,82179,Male,Loyal Customer,17,Personal Travel,Eco Plus,237,4,5,4,3,3,4,3,3,3,4,4,3,4,3,0,0.0,satisfied +20654,89430,Female,Loyal Customer,11,Personal Travel,Eco,151,2,4,2,5,4,2,3,4,4,4,4,3,4,4,0,3.0,neutral or dissatisfied +20655,99801,Female,Loyal Customer,48,Business travel,Business,232,3,3,3,3,3,1,2,4,4,4,4,4,4,1,0,0.0,satisfied +20656,18509,Female,disloyal Customer,24,Business travel,Eco,127,4,2,3,2,5,3,5,5,2,1,4,1,4,5,0,0.0,satisfied +20657,93999,Male,Loyal Customer,59,Business travel,Business,3654,4,5,4,4,5,4,5,5,5,5,5,4,5,3,31,27.0,satisfied +20658,123773,Female,disloyal Customer,27,Business travel,Business,544,2,2,2,3,3,2,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +20659,37335,Female,Loyal Customer,44,Business travel,Eco,1028,1,0,0,3,1,4,3,1,1,1,1,1,1,1,7,0.0,neutral or dissatisfied +20660,99797,Female,Loyal Customer,72,Business travel,Business,584,3,4,4,4,3,2,3,3,3,3,3,4,3,2,31,20.0,neutral or dissatisfied +20661,84059,Male,Loyal Customer,52,Business travel,Business,1716,2,2,2,2,3,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +20662,29584,Female,Loyal Customer,46,Business travel,Eco,1448,5,3,3,3,5,4,4,5,5,5,5,3,5,1,0,0.0,satisfied +20663,32405,Female,Loyal Customer,52,Business travel,Eco,102,5,5,5,5,1,4,2,5,5,5,5,3,5,5,0,0.0,satisfied +20664,27066,Female,disloyal Customer,8,Business travel,Eco,1399,2,2,2,3,5,2,5,5,2,1,4,2,2,5,0,0.0,neutral or dissatisfied +20665,43135,Female,Loyal Customer,62,Business travel,Eco Plus,173,2,3,3,3,2,2,3,2,2,2,2,2,2,1,34,57.0,neutral or dissatisfied +20666,67552,Male,Loyal Customer,15,Personal Travel,Business,1235,2,2,2,3,3,2,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +20667,8483,Female,Loyal Customer,42,Personal Travel,Eco Plus,1187,4,1,4,4,2,3,4,1,1,4,2,3,1,1,1,4.0,neutral or dissatisfied +20668,101441,Female,disloyal Customer,26,Business travel,Business,345,4,0,4,4,5,4,5,5,4,2,4,4,5,5,17,6.0,satisfied +20669,78137,Female,disloyal Customer,48,Business travel,Business,259,4,3,3,5,3,4,4,3,5,5,4,3,5,3,7,0.0,neutral or dissatisfied +20670,112911,Male,Loyal Customer,31,Business travel,Business,1390,1,1,1,1,4,4,4,4,5,3,3,1,2,4,0,0.0,satisfied +20671,72459,Female,Loyal Customer,15,Business travel,Business,2733,2,2,2,2,4,4,4,4,4,4,4,5,5,4,0,6.0,satisfied +20672,32813,Female,disloyal Customer,24,Business travel,Eco,102,3,3,3,4,3,3,5,3,3,5,3,1,4,3,1,0.0,neutral or dissatisfied +20673,33638,Female,Loyal Customer,37,Personal Travel,Eco,399,2,3,2,3,3,2,3,3,4,5,4,2,1,3,42,43.0,neutral or dissatisfied +20674,59111,Male,Loyal Customer,44,Personal Travel,Eco,1726,1,4,1,1,1,1,1,1,5,3,4,5,3,1,26,21.0,neutral or dissatisfied +20675,49219,Female,Loyal Customer,54,Business travel,Business,2663,1,1,1,1,4,1,4,5,5,5,5,1,5,3,0,0.0,satisfied +20676,2394,Female,Loyal Customer,47,Business travel,Business,2362,5,2,5,5,3,5,5,4,4,4,4,4,4,5,24,13.0,satisfied +20677,98374,Male,Loyal Customer,31,Personal Travel,Eco,1046,3,5,3,1,2,3,2,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +20678,94550,Female,Loyal Customer,58,Business travel,Business,3935,4,4,4,4,4,4,4,5,5,5,5,4,5,4,24,8.0,satisfied +20679,119568,Male,Loyal Customer,15,Business travel,Business,857,1,1,1,1,5,5,5,5,5,4,5,5,4,5,0,9.0,satisfied +20680,72102,Female,Loyal Customer,50,Business travel,Business,2556,3,3,3,3,3,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +20681,112076,Male,Loyal Customer,48,Business travel,Eco,1491,3,3,3,3,3,3,3,3,2,2,2,2,3,3,10,0.0,neutral or dissatisfied +20682,126345,Female,Loyal Customer,39,Personal Travel,Eco,631,3,4,3,4,3,3,3,3,4,5,3,1,3,3,2,27.0,neutral or dissatisfied +20683,117480,Male,Loyal Customer,27,Business travel,Business,507,5,5,5,5,3,3,3,3,4,4,4,4,5,3,34,42.0,satisfied +20684,84428,Male,Loyal Customer,69,Personal Travel,Eco,591,2,4,2,1,4,2,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +20685,113279,Female,Loyal Customer,56,Business travel,Business,2373,4,4,4,4,4,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +20686,76536,Female,Loyal Customer,43,Business travel,Business,3866,5,1,5,5,3,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +20687,93238,Male,disloyal Customer,54,Business travel,Business,1694,3,3,3,1,4,3,4,4,5,2,3,5,4,4,0,3.0,neutral or dissatisfied +20688,105883,Male,disloyal Customer,32,Business travel,Business,283,2,1,1,2,4,1,4,4,5,5,4,5,4,4,0,0.0,neutral or dissatisfied +20689,74771,Male,Loyal Customer,17,Personal Travel,Eco,1464,4,5,4,1,3,4,3,3,4,2,3,5,4,3,1,0.0,neutral or dissatisfied +20690,94696,Female,Loyal Customer,37,Business travel,Eco,189,1,1,1,1,1,2,1,1,1,4,3,4,3,1,10,4.0,neutral or dissatisfied +20691,8984,Female,Loyal Customer,67,Personal Travel,Eco,725,4,1,5,3,2,4,3,2,2,5,4,4,2,2,0,0.0,neutral or dissatisfied +20692,11573,Male,Loyal Customer,43,Business travel,Business,657,2,4,1,4,1,4,3,2,2,2,2,1,2,2,0,4.0,neutral or dissatisfied +20693,54440,Male,Loyal Customer,41,Business travel,Eco Plus,305,2,3,3,3,2,2,2,2,4,4,3,4,3,2,6,9.0,neutral or dissatisfied +20694,19380,Male,Loyal Customer,47,Business travel,Business,1994,5,5,5,5,5,5,5,2,3,3,4,5,2,5,352,350.0,satisfied +20695,126962,Male,disloyal Customer,37,Business travel,Business,304,4,4,4,2,3,4,3,3,5,4,5,5,5,3,0,0.0,satisfied +20696,65514,Male,Loyal Customer,48,Business travel,Business,1616,2,2,2,2,2,3,4,5,5,5,5,4,5,5,0,0.0,satisfied +20697,40191,Male,Loyal Customer,24,Business travel,Business,2795,3,5,5,5,3,3,3,3,3,1,3,1,3,3,0,0.0,neutral or dissatisfied +20698,3147,Female,disloyal Customer,28,Business travel,Business,140,4,4,4,2,1,4,3,1,3,3,5,4,4,1,0,0.0,satisfied +20699,27633,Female,Loyal Customer,29,Business travel,Eco Plus,987,4,5,5,5,4,4,4,4,5,3,5,2,4,4,0,0.0,satisfied +20700,68918,Male,Loyal Customer,54,Personal Travel,Eco,1061,1,4,1,2,4,1,4,4,5,3,4,4,4,4,0,0.0,neutral or dissatisfied +20701,107417,Female,Loyal Customer,44,Business travel,Business,3567,2,2,2,2,1,4,3,2,2,3,2,2,2,1,79,81.0,neutral or dissatisfied +20702,12836,Female,disloyal Customer,39,Business travel,Eco,417,1,2,1,4,5,1,5,5,3,1,3,3,3,5,8,0.0,neutral or dissatisfied +20703,95558,Male,Loyal Customer,21,Personal Travel,Eco Plus,277,1,2,1,3,1,1,1,1,1,2,2,1,3,1,0,0.0,neutral or dissatisfied +20704,96623,Female,disloyal Customer,39,Business travel,Business,937,2,2,2,3,3,2,3,3,4,5,5,5,5,3,36,21.0,neutral or dissatisfied +20705,5549,Male,disloyal Customer,26,Business travel,Business,404,1,4,1,3,3,1,3,3,5,5,5,5,4,3,0,0.0,neutral or dissatisfied +20706,78553,Male,Loyal Customer,45,Business travel,Business,2654,4,4,4,4,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +20707,58472,Male,Loyal Customer,41,Business travel,Business,2345,1,1,1,1,3,4,4,4,4,4,4,4,4,4,1,0.0,satisfied +20708,746,Male,Loyal Customer,44,Business travel,Business,102,1,2,2,2,1,4,3,3,3,3,1,4,3,2,6,7.0,neutral or dissatisfied +20709,64066,Female,Loyal Customer,46,Business travel,Eco,919,3,3,2,3,5,3,2,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +20710,79723,Male,Loyal Customer,30,Personal Travel,Eco,762,1,4,1,2,4,1,4,4,5,5,4,3,4,4,14,0.0,neutral or dissatisfied +20711,69662,Female,Loyal Customer,38,Business travel,Business,2545,4,4,4,4,4,1,4,5,5,5,3,2,5,4,0,0.0,satisfied +20712,31966,Male,Loyal Customer,45,Business travel,Business,1744,1,3,3,3,3,3,2,3,3,3,1,3,3,2,0,0.0,neutral or dissatisfied +20713,76519,Male,Loyal Customer,66,Business travel,Business,1964,3,1,1,1,4,4,3,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +20714,62450,Female,Loyal Customer,58,Business travel,Business,1744,3,3,3,3,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20715,92372,Male,Loyal Customer,41,Business travel,Business,2139,1,1,1,1,5,5,5,2,2,2,2,5,2,4,1,1.0,satisfied +20716,35194,Male,Loyal Customer,30,Business travel,Business,1076,4,4,4,4,4,4,4,4,4,4,3,4,1,4,67,62.0,satisfied +20717,75545,Female,disloyal Customer,39,Business travel,Business,337,2,2,2,1,3,2,3,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +20718,111603,Male,Loyal Customer,23,Personal Travel,Eco Plus,883,2,3,2,4,1,2,1,1,3,5,2,3,2,1,0,0.0,neutral or dissatisfied +20719,47553,Male,Loyal Customer,30,Business travel,Eco Plus,501,1,3,4,3,2,1,1,1,2,3,3,1,3,1,181,162.0,neutral or dissatisfied +20720,77258,Male,Loyal Customer,32,Personal Travel,Eco,1590,2,5,2,1,1,2,1,1,4,2,3,3,4,1,28,8.0,neutral or dissatisfied +20721,35498,Male,Loyal Customer,56,Personal Travel,Eco,1053,3,5,3,1,4,3,4,4,4,5,5,4,4,4,50,59.0,neutral or dissatisfied +20722,13298,Female,Loyal Customer,35,Business travel,Eco Plus,468,1,2,2,2,1,1,1,1,4,1,2,1,2,1,0,0.0,neutral or dissatisfied +20723,50225,Male,Loyal Customer,57,Business travel,Business,2639,1,1,1,1,3,5,2,4,4,4,4,1,4,1,0,0.0,satisfied +20724,69882,Female,Loyal Customer,42,Business travel,Business,2248,5,5,5,5,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +20725,59455,Female,disloyal Customer,25,Business travel,Business,901,0,0,0,5,3,0,3,3,4,5,5,3,5,3,6,0.0,satisfied +20726,55574,Male,Loyal Customer,44,Business travel,Business,3306,2,2,2,2,5,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +20727,46277,Male,Loyal Customer,53,Personal Travel,Eco,679,4,4,4,4,2,4,2,2,4,1,3,1,4,2,1,3.0,neutral or dissatisfied +20728,105029,Male,disloyal Customer,48,Business travel,Eco,255,2,2,2,4,3,2,3,3,2,1,3,3,4,3,16,12.0,neutral or dissatisfied +20729,81619,Male,Loyal Customer,24,Personal Travel,Eco Plus,334,3,4,3,3,1,3,1,1,4,4,3,1,3,1,0,0.0,neutral or dissatisfied +20730,102018,Male,Loyal Customer,60,Business travel,Business,3984,5,5,5,5,4,4,4,5,5,5,5,3,5,4,5,3.0,satisfied +20731,73406,Male,disloyal Customer,29,Business travel,Eco,1197,2,2,2,4,3,2,3,3,2,5,2,2,4,3,0,0.0,neutral or dissatisfied +20732,14504,Female,Loyal Customer,61,Business travel,Business,2122,3,1,5,5,5,4,4,3,3,3,3,4,3,3,24,24.0,neutral or dissatisfied +20733,100033,Female,Loyal Customer,24,Business travel,Business,1623,2,3,3,3,2,1,2,2,1,2,2,2,2,2,0,0.0,neutral or dissatisfied +20734,23350,Female,disloyal Customer,34,Business travel,Eco Plus,456,2,1,1,3,4,1,4,4,2,1,1,2,3,4,20,1.0,neutral or dissatisfied +20735,52621,Male,Loyal Customer,27,Business travel,Eco,160,5,3,3,3,5,5,5,5,3,1,3,4,1,5,0,0.0,satisfied +20736,127780,Male,disloyal Customer,21,Business travel,Eco,1037,1,1,1,2,5,1,5,5,3,5,2,1,3,5,41,30.0,neutral or dissatisfied +20737,43788,Male,Loyal Customer,27,Business travel,Eco Plus,481,5,4,4,4,5,5,5,5,1,2,3,4,4,5,0,0.0,satisfied +20738,89480,Female,Loyal Customer,30,Business travel,Business,1931,3,5,5,5,3,3,3,3,2,1,3,3,3,3,0,,neutral or dissatisfied +20739,41191,Male,Loyal Customer,24,Business travel,Business,3171,4,4,4,4,4,4,4,4,3,1,3,3,3,4,12,17.0,neutral or dissatisfied +20740,75676,Male,disloyal Customer,18,Business travel,Eco,868,5,5,5,4,2,5,2,2,4,3,5,3,5,2,0,0.0,satisfied +20741,96292,Female,Loyal Customer,66,Personal Travel,Eco,460,3,4,5,3,5,1,5,1,1,5,1,3,1,5,51,55.0,neutral or dissatisfied +20742,14206,Male,Loyal Customer,41,Business travel,Business,3712,1,2,2,2,1,3,3,1,1,1,1,2,1,2,0,7.0,neutral or dissatisfied +20743,83993,Male,Loyal Customer,67,Business travel,Business,321,2,5,5,5,4,3,3,2,2,2,2,4,2,1,0,8.0,neutral or dissatisfied +20744,82367,Male,Loyal Customer,63,Personal Travel,Eco,453,2,4,2,1,2,2,2,2,1,2,3,3,2,2,0,0.0,neutral or dissatisfied +20745,57420,Female,Loyal Customer,25,Business travel,Business,3456,3,3,3,3,4,4,4,4,3,5,5,5,5,4,0,0.0,satisfied +20746,9857,Female,Loyal Customer,66,Personal Travel,Eco,642,5,3,5,2,3,3,3,1,1,5,1,3,1,2,32,83.0,satisfied +20747,61686,Male,disloyal Customer,38,Business travel,Eco,1379,3,3,3,2,2,3,2,2,3,5,3,1,2,2,5,26.0,neutral or dissatisfied +20748,122806,Male,Loyal Customer,59,Business travel,Eco,199,2,1,4,1,2,2,2,2,2,2,3,4,3,2,0,0.0,neutral or dissatisfied +20749,18524,Male,disloyal Customer,30,Business travel,Eco,192,2,0,2,2,5,2,5,5,1,2,3,2,3,5,0,0.0,neutral or dissatisfied +20750,6634,Female,Loyal Customer,23,Personal Travel,Eco,719,3,5,3,2,2,3,2,2,5,3,4,4,5,2,3,0.0,neutral or dissatisfied +20751,118425,Male,Loyal Customer,46,Business travel,Business,3106,2,2,2,2,5,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20752,45930,Male,Loyal Customer,38,Personal Travel,Eco,641,1,3,1,2,4,1,2,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +20753,23921,Male,Loyal Customer,70,Personal Travel,Eco,589,3,4,3,3,5,3,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +20754,106550,Male,Loyal Customer,10,Personal Travel,Eco,719,3,4,4,5,4,4,4,4,4,3,5,4,5,4,0,0.0,neutral or dissatisfied +20755,21589,Female,Loyal Customer,51,Business travel,Eco,853,4,5,5,5,3,4,4,4,4,4,4,1,4,3,20,22.0,satisfied +20756,78582,Female,Loyal Customer,18,Personal Travel,Eco,630,2,2,2,2,1,2,4,1,3,3,2,1,2,1,0,0.0,neutral or dissatisfied +20757,78683,Male,disloyal Customer,27,Business travel,Business,761,3,3,3,5,5,3,5,5,3,3,5,4,4,5,0,7.0,neutral or dissatisfied +20758,66350,Female,disloyal Customer,28,Business travel,Business,986,5,5,5,4,1,5,1,1,4,4,5,4,4,1,0,0.0,satisfied +20759,30572,Female,Loyal Customer,53,Business travel,Eco,628,2,4,4,4,1,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +20760,128614,Female,Loyal Customer,35,Business travel,Business,3332,5,5,5,5,2,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +20761,75211,Female,disloyal Customer,34,Business travel,Eco,1491,2,2,2,3,5,2,5,5,4,2,3,1,2,5,0,0.0,neutral or dissatisfied +20762,22467,Female,Loyal Customer,30,Personal Travel,Eco,214,2,2,2,4,4,2,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +20763,19411,Male,Loyal Customer,19,Business travel,Business,2585,4,4,4,4,4,4,4,4,2,2,1,3,2,4,0,0.0,satisfied +20764,27193,Female,Loyal Customer,41,Business travel,Eco Plus,1177,1,3,3,3,1,1,1,1,3,2,1,1,4,1,0,0.0,neutral or dissatisfied +20765,81919,Male,Loyal Customer,44,Business travel,Business,1522,3,3,3,3,5,5,5,2,2,2,2,5,2,4,9,2.0,satisfied +20766,99335,Male,disloyal Customer,22,Business travel,Eco,337,3,4,3,3,3,3,3,3,3,4,4,5,5,3,2,0.0,neutral or dissatisfied +20767,48978,Male,Loyal Customer,39,Business travel,Business,2268,3,3,3,3,5,4,2,4,4,4,3,3,4,2,5,0.0,satisfied +20768,50894,Female,Loyal Customer,61,Personal Travel,Eco,326,1,4,1,3,1,4,4,4,4,1,4,3,4,2,0,0.0,neutral or dissatisfied +20769,48190,Male,Loyal Customer,51,Business travel,Business,173,3,1,3,1,5,4,3,1,1,1,3,4,1,3,0,10.0,neutral or dissatisfied +20770,84635,Female,Loyal Customer,59,Personal Travel,Eco,669,1,4,2,4,3,4,4,2,2,2,2,5,2,5,10,8.0,neutral or dissatisfied +20771,21406,Male,disloyal Customer,23,Business travel,Eco,356,4,1,4,3,5,4,5,5,3,2,5,4,5,5,20,13.0,satisfied +20772,57019,Male,Loyal Customer,39,Personal Travel,Eco,2434,4,5,4,4,4,3,3,5,2,4,5,3,5,3,15,18.0,neutral or dissatisfied +20773,104413,Male,Loyal Customer,44,Business travel,Business,3834,2,2,2,2,2,5,4,1,1,2,1,5,1,5,0,0.0,satisfied +20774,89982,Male,Loyal Customer,52,Business travel,Business,3178,4,4,4,4,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +20775,94286,Male,Loyal Customer,36,Business travel,Business,3191,4,4,4,4,2,4,5,4,4,5,4,4,4,3,71,94.0,satisfied +20776,110953,Male,Loyal Customer,51,Personal Travel,Eco Plus,406,4,4,4,1,1,4,1,1,4,4,5,3,5,1,8,14.0,neutral or dissatisfied +20777,24893,Female,Loyal Customer,30,Personal Travel,Eco,397,3,3,3,3,2,3,2,2,4,3,3,1,3,2,0,0.0,neutral or dissatisfied +20778,4066,Female,Loyal Customer,21,Personal Travel,Eco,479,3,3,3,4,1,3,1,1,4,3,3,3,4,1,39,53.0,neutral or dissatisfied +20779,47251,Male,Loyal Customer,39,Business travel,Business,588,1,1,1,1,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +20780,28914,Female,Loyal Customer,25,Business travel,Business,2039,5,5,5,5,4,4,4,4,5,1,1,3,4,4,0,0.0,satisfied +20781,1433,Female,Loyal Customer,40,Business travel,Business,1924,1,2,2,2,2,4,3,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +20782,78927,Female,Loyal Customer,58,Business travel,Business,2125,2,3,3,3,5,4,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +20783,86324,Female,Loyal Customer,23,Business travel,Business,1713,2,5,5,5,2,2,2,2,1,2,3,1,4,2,13,3.0,neutral or dissatisfied +20784,66818,Female,Loyal Customer,58,Business travel,Business,1774,5,5,5,5,2,5,5,4,4,4,4,3,4,3,4,11.0,satisfied +20785,85782,Female,Loyal Customer,51,Business travel,Business,1780,2,2,2,2,2,4,4,2,2,2,2,3,2,3,0,0.0,satisfied +20786,100775,Male,Loyal Customer,55,Business travel,Eco,1411,5,3,3,3,5,5,5,5,2,3,3,2,1,5,0,0.0,satisfied +20787,20436,Female,Loyal Customer,46,Business travel,Business,2407,5,2,5,5,2,4,5,5,5,5,5,5,5,3,1,6.0,satisfied +20788,41360,Female,Loyal Customer,36,Business travel,Eco,641,4,1,5,1,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +20789,101458,Female,Loyal Customer,43,Business travel,Business,3363,4,4,4,4,3,4,4,4,4,4,4,3,4,5,53,57.0,satisfied +20790,28172,Female,disloyal Customer,30,Business travel,Eco,150,2,3,2,4,4,2,4,4,4,3,3,1,4,4,0,0.0,neutral or dissatisfied +20791,3929,Male,Loyal Customer,7,Personal Travel,Eco Plus,290,3,5,3,1,4,3,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +20792,15282,Female,Loyal Customer,62,Personal Travel,Eco,500,3,5,3,1,5,5,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +20793,102332,Female,Loyal Customer,36,Business travel,Business,226,2,5,5,5,4,3,4,2,2,2,2,2,2,1,4,0.0,neutral or dissatisfied +20794,129404,Male,Loyal Customer,52,Business travel,Business,3073,5,5,5,5,2,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +20795,108339,Male,Loyal Customer,48,Business travel,Eco,1855,4,2,1,2,4,4,4,4,1,3,3,2,2,4,0,0.0,neutral or dissatisfied +20796,50802,Male,Loyal Customer,14,Personal Travel,Eco,86,2,4,2,3,1,2,1,1,5,4,5,5,4,1,0,12.0,neutral or dissatisfied +20797,67710,Female,Loyal Customer,45,Business travel,Business,1235,3,3,3,3,5,5,5,2,2,2,2,4,2,4,0,0.0,satisfied +20798,35213,Male,disloyal Customer,62,Business travel,Business,1076,3,3,3,3,4,3,4,4,2,5,1,5,3,4,0,0.0,neutral or dissatisfied +20799,50125,Female,Loyal Customer,62,Business travel,Eco,262,5,3,3,3,1,1,3,5,5,5,5,5,5,1,0,0.0,satisfied +20800,34438,Female,Loyal Customer,41,Business travel,Business,2422,2,2,2,2,2,2,2,2,4,4,4,2,5,2,0,0.0,satisfied +20801,95852,Male,disloyal Customer,27,Business travel,Business,580,4,4,4,4,3,4,3,3,3,5,4,5,4,3,16,11.0,satisfied +20802,95363,Male,Loyal Customer,33,Personal Travel,Eco,277,1,0,1,3,4,1,4,4,1,1,2,5,1,4,0,2.0,neutral or dissatisfied +20803,25338,Female,Loyal Customer,46,Personal Travel,Eco,829,3,5,3,3,5,4,5,1,1,3,1,5,1,5,0,0.0,neutral or dissatisfied +20804,16432,Female,Loyal Customer,56,Business travel,Business,416,2,2,2,2,5,5,2,3,3,3,3,3,3,1,0,0.0,satisfied +20805,60974,Female,Loyal Customer,33,Personal Travel,Eco,888,4,5,4,5,1,4,1,1,4,3,4,5,5,1,16,0.0,neutral or dissatisfied +20806,46000,Female,Loyal Customer,40,Personal Travel,Eco,483,3,0,2,4,2,2,2,4,5,5,5,2,3,2,220,232.0,neutral or dissatisfied +20807,84114,Female,Loyal Customer,52,Business travel,Business,2036,1,1,1,1,5,3,5,4,4,4,4,3,4,4,0,28.0,satisfied +20808,10606,Female,disloyal Customer,23,Business travel,Business,667,5,5,5,4,4,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +20809,92985,Male,Loyal Customer,31,Business travel,Business,2576,5,5,3,5,4,4,4,5,3,4,5,4,4,4,233,229.0,satisfied +20810,14269,Male,Loyal Customer,42,Business travel,Eco,429,5,2,2,2,5,5,5,5,3,2,3,1,3,5,31,24.0,satisfied +20811,34643,Male,Loyal Customer,52,Personal Travel,Eco,427,2,2,2,4,5,2,5,5,3,1,4,3,3,5,0,0.0,neutral or dissatisfied +20812,3863,Female,Loyal Customer,56,Business travel,Business,213,4,2,2,2,1,3,3,2,2,3,4,2,2,1,0,0.0,neutral or dissatisfied +20813,126603,Male,Loyal Customer,36,Business travel,Business,1337,2,4,4,4,2,2,2,2,2,1,2,4,2,1,40,27.0,neutral or dissatisfied +20814,113982,Female,Loyal Customer,57,Business travel,Eco,1750,2,4,4,4,1,3,3,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +20815,8941,Male,Loyal Customer,58,Business travel,Business,2303,2,2,2,2,3,4,5,5,5,5,5,5,5,4,17,10.0,satisfied +20816,35148,Male,Loyal Customer,35,Business travel,Eco,1035,5,5,4,4,5,5,5,5,2,1,5,5,5,5,20,9.0,satisfied +20817,48361,Male,disloyal Customer,11,Business travel,Eco,674,2,2,2,3,2,2,2,2,4,1,2,1,2,2,22,8.0,neutral or dissatisfied +20818,124353,Female,disloyal Customer,32,Business travel,Business,808,4,4,4,4,5,4,5,5,5,2,4,4,4,5,33,23.0,neutral or dissatisfied +20819,110403,Female,disloyal Customer,25,Business travel,Eco,925,2,2,2,3,5,2,5,5,4,5,4,4,4,5,0,0.0,neutral or dissatisfied +20820,115980,Female,Loyal Customer,12,Personal Travel,Eco,342,5,5,5,1,5,5,5,5,4,5,5,4,2,5,17,22.0,satisfied +20821,30585,Male,Loyal Customer,58,Personal Travel,Eco,628,2,5,2,4,2,2,2,2,3,5,5,3,4,2,0,0.0,neutral or dissatisfied +20822,1509,Male,disloyal Customer,30,Business travel,Business,922,2,2,2,5,4,2,4,4,4,5,5,3,5,4,9,17.0,neutral or dissatisfied +20823,86807,Male,Loyal Customer,40,Business travel,Business,1577,1,1,1,1,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +20824,94174,Male,Loyal Customer,57,Business travel,Business,2265,3,3,4,3,5,4,4,3,3,2,3,4,3,4,10,13.0,satisfied +20825,23429,Male,Loyal Customer,42,Personal Travel,Eco,1201,3,5,3,3,1,3,4,1,3,2,5,5,1,1,10,0.0,neutral or dissatisfied +20826,52746,Male,disloyal Customer,80,Business travel,Eco,806,4,4,4,3,4,2,2,1,5,4,4,2,4,2,206,183.0,neutral or dissatisfied +20827,122739,Male,Loyal Customer,27,Business travel,Business,2244,3,3,3,3,3,4,3,3,3,3,4,3,5,3,0,0.0,satisfied +20828,129556,Female,Loyal Customer,17,Personal Travel,Eco,2342,2,3,2,1,4,2,4,4,2,5,2,2,3,4,52,40.0,neutral or dissatisfied +20829,79796,Female,Loyal Customer,54,Business travel,Business,944,5,5,5,5,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +20830,9309,Female,Loyal Customer,19,Business travel,Business,542,4,4,4,4,5,5,5,5,5,2,4,4,4,5,0,9.0,satisfied +20831,83662,Male,Loyal Customer,35,Business travel,Business,3594,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +20832,123020,Female,disloyal Customer,30,Business travel,Business,590,4,5,5,2,5,5,3,5,5,4,5,5,4,5,0,0.0,satisfied +20833,97659,Female,Loyal Customer,57,Business travel,Business,2008,2,2,5,2,4,4,5,4,4,4,4,3,4,3,19,13.0,satisfied +20834,39245,Female,Loyal Customer,59,Business travel,Business,2613,5,5,5,5,3,5,2,4,4,4,4,5,4,4,9,2.0,satisfied +20835,98089,Male,Loyal Customer,43,Business travel,Business,928,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +20836,68381,Female,Loyal Customer,54,Business travel,Business,2640,5,5,5,5,2,5,5,2,2,2,2,4,2,5,2,0.0,satisfied +20837,89890,Male,Loyal Customer,22,Business travel,Business,1501,2,5,2,5,2,3,2,2,2,3,3,4,4,2,12,54.0,neutral or dissatisfied +20838,129040,Male,disloyal Customer,41,Business travel,Business,709,4,5,5,5,4,3,3,5,5,5,4,3,3,3,302,312.0,satisfied +20839,36318,Male,Loyal Customer,33,Business travel,Eco,187,4,3,3,3,4,4,4,4,2,1,4,5,2,4,0,23.0,satisfied +20840,118224,Female,disloyal Customer,26,Business travel,Business,735,4,5,5,3,5,5,5,5,4,3,4,4,5,5,0,8.0,satisfied +20841,121415,Female,Loyal Customer,55,Business travel,Business,3657,1,1,3,1,2,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +20842,82523,Male,Loyal Customer,38,Business travel,Eco,249,1,2,2,2,1,1,1,1,3,1,3,1,4,1,21,30.0,neutral or dissatisfied +20843,123554,Female,disloyal Customer,24,Business travel,Business,1186,0,3,0,3,4,0,4,4,3,3,4,4,4,4,13,0.0,satisfied +20844,22178,Male,Loyal Customer,32,Business travel,Business,633,2,4,4,4,2,2,2,2,1,4,2,2,2,2,0,0.0,neutral or dissatisfied +20845,8168,Male,Loyal Customer,16,Business travel,Business,2685,1,4,4,4,1,1,1,1,4,5,3,1,4,1,0,0.0,neutral or dissatisfied +20846,45392,Male,Loyal Customer,41,Business travel,Business,344,2,5,5,5,4,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +20847,22097,Male,Loyal Customer,54,Personal Travel,Eco,782,3,5,3,4,1,3,1,1,5,5,5,5,5,1,7,6.0,neutral or dissatisfied +20848,77976,Male,Loyal Customer,36,Business travel,Business,1965,3,4,4,4,5,2,3,2,2,2,3,1,2,4,0,0.0,neutral or dissatisfied +20849,85102,Female,Loyal Customer,43,Business travel,Business,689,3,3,3,3,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +20850,55621,Male,Loyal Customer,13,Personal Travel,Business,1824,1,5,1,4,4,1,4,4,3,3,5,5,5,4,0,8.0,neutral or dissatisfied +20851,125739,Male,Loyal Customer,47,Business travel,Business,3610,1,3,1,1,5,5,4,5,5,5,5,4,5,4,4,27.0,satisfied +20852,81455,Male,Loyal Customer,49,Business travel,Business,528,2,2,2,2,4,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +20853,80656,Female,Loyal Customer,59,Business travel,Business,3021,2,2,2,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +20854,58140,Female,Loyal Customer,48,Business travel,Business,925,1,1,1,1,2,4,5,5,5,5,5,4,5,4,44,88.0,satisfied +20855,40190,Female,Loyal Customer,63,Business travel,Eco,358,4,4,4,4,3,2,1,4,4,4,4,1,4,3,0,8.0,satisfied +20856,93643,Male,Loyal Customer,53,Business travel,Eco Plus,177,1,1,1,1,1,1,1,1,1,4,3,4,3,1,0,0.0,neutral or dissatisfied +20857,62986,Male,disloyal Customer,28,Business travel,Eco,853,2,2,2,3,4,2,4,4,2,1,3,2,3,4,2,19.0,neutral or dissatisfied +20858,24986,Female,Loyal Customer,31,Business travel,Business,1560,2,2,4,2,4,4,4,4,5,4,5,3,3,4,0,0.0,satisfied +20859,66702,Female,Loyal Customer,12,Business travel,Business,3540,3,3,3,3,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +20860,55628,Male,Loyal Customer,37,Business travel,Eco,324,4,1,1,1,4,4,4,4,4,3,3,2,5,4,0,0.0,satisfied +20861,108841,Female,Loyal Customer,49,Business travel,Business,2139,5,5,5,5,5,5,5,5,5,5,5,5,5,3,9,1.0,satisfied +20862,18614,Male,Loyal Customer,44,Personal Travel,Eco,201,4,5,4,3,2,4,2,2,4,5,5,3,3,2,0,0.0,satisfied +20863,51313,Male,Loyal Customer,60,Business travel,Eco Plus,110,1,1,1,1,1,1,1,1,4,1,3,1,2,1,0,16.0,neutral or dissatisfied +20864,303,Male,Loyal Customer,51,Business travel,Business,3183,2,2,2,2,3,5,5,5,5,5,5,5,5,5,13,11.0,satisfied +20865,10186,Female,Loyal Customer,32,Business travel,Business,2409,1,1,1,1,4,4,4,4,4,5,4,3,4,4,3,14.0,satisfied +20866,84567,Male,Loyal Customer,67,Personal Travel,Eco,2556,1,4,1,1,2,1,2,2,4,3,3,5,4,2,0,0.0,neutral or dissatisfied +20867,66001,Male,disloyal Customer,44,Business travel,Business,655,3,3,3,4,4,3,4,4,4,4,4,3,3,4,36,42.0,neutral or dissatisfied +20868,75581,Male,Loyal Customer,39,Business travel,Business,3795,2,2,2,2,3,5,5,5,5,5,5,4,5,4,4,2.0,satisfied +20869,15839,Male,Loyal Customer,37,Business travel,Business,1707,2,4,2,2,1,4,5,5,5,5,5,3,5,2,58,55.0,satisfied +20870,60361,Female,Loyal Customer,47,Business travel,Business,1476,1,1,1,1,5,4,5,5,5,5,5,4,5,5,1,6.0,satisfied +20871,2356,Male,disloyal Customer,21,Business travel,Business,925,5,0,5,4,1,5,1,1,3,4,5,3,4,1,0,23.0,satisfied +20872,100704,Male,Loyal Customer,41,Business travel,Business,677,2,2,2,2,3,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +20873,128872,Male,disloyal Customer,23,Business travel,Business,968,5,0,5,4,5,4,4,3,3,5,4,4,3,4,0,0.0,satisfied +20874,63455,Female,Loyal Customer,53,Business travel,Business,1712,4,4,4,4,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +20875,114324,Male,Loyal Customer,52,Personal Travel,Eco,948,2,0,3,1,3,3,3,3,4,3,4,5,5,3,9,13.0,neutral or dissatisfied +20876,98074,Female,Loyal Customer,29,Business travel,Business,1449,4,4,4,4,4,4,4,4,3,3,1,2,4,4,0,22.0,satisfied +20877,50286,Male,Loyal Customer,33,Business travel,Business,1953,4,2,2,2,2,2,4,2,1,4,4,4,4,2,34,37.0,neutral or dissatisfied +20878,22428,Female,Loyal Customer,34,Personal Travel,Eco,143,2,5,2,4,5,2,5,5,3,5,1,5,4,5,0,0.0,neutral or dissatisfied +20879,14481,Female,disloyal Customer,22,Business travel,Eco,541,3,4,3,1,4,3,4,4,3,5,2,1,4,4,0,0.0,neutral or dissatisfied +20880,118313,Female,disloyal Customer,23,Business travel,Eco,639,3,4,3,3,5,3,4,5,3,2,4,1,4,5,2,2.0,neutral or dissatisfied +20881,74189,Male,Loyal Customer,62,Personal Travel,Eco,641,3,4,2,3,4,2,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +20882,85779,Female,Loyal Customer,39,Business travel,Business,526,4,4,4,4,2,4,4,5,5,5,5,5,5,5,22,17.0,satisfied +20883,50769,Male,Loyal Customer,13,Personal Travel,Eco,86,2,1,2,3,2,2,2,2,3,5,3,2,4,2,8,11.0,neutral or dissatisfied +20884,467,Female,Loyal Customer,47,Business travel,Business,3730,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +20885,54964,Female,disloyal Customer,48,Business travel,Business,1635,2,3,3,3,1,2,1,1,3,4,5,3,4,1,0,14.0,neutral or dissatisfied +20886,80135,Male,Loyal Customer,54,Business travel,Business,2446,3,3,4,3,3,4,5,4,4,4,4,4,4,5,18,0.0,satisfied +20887,92802,Male,disloyal Customer,25,Business travel,Eco,869,4,3,3,4,1,4,1,1,3,2,3,4,4,1,0,0.0,neutral or dissatisfied +20888,9161,Female,Loyal Customer,42,Business travel,Business,975,4,4,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +20889,120018,Male,Loyal Customer,16,Personal Travel,Eco,328,3,4,5,4,2,5,4,2,5,2,5,3,5,2,0,0.0,neutral or dissatisfied +20890,105339,Female,Loyal Customer,45,Business travel,Business,528,3,3,3,3,4,4,5,5,5,5,5,4,5,5,10,6.0,satisfied +20891,69335,Male,Loyal Customer,25,Business travel,Business,1089,3,3,2,3,5,5,5,5,3,5,4,5,5,5,31,15.0,satisfied +20892,88565,Female,Loyal Customer,44,Personal Travel,Eco,545,1,2,1,3,5,4,4,4,4,1,5,4,4,4,0,0.0,neutral or dissatisfied +20893,1898,Male,Loyal Customer,38,Business travel,Business,2517,3,3,3,3,4,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +20894,46368,Male,Loyal Customer,29,Business travel,Business,1767,3,3,3,3,3,3,3,3,3,2,3,3,3,3,22,25.0,neutral or dissatisfied +20895,96117,Male,Loyal Customer,30,Business travel,Eco Plus,1090,5,1,1,1,5,4,5,5,1,2,4,3,3,5,0,0.0,neutral or dissatisfied +20896,104728,Male,Loyal Customer,56,Business travel,Business,2283,1,1,1,1,2,5,4,3,3,3,3,5,3,3,125,124.0,satisfied +20897,93302,Male,Loyal Customer,40,Business travel,Business,1733,1,1,1,1,2,4,4,5,5,5,5,3,5,5,9,0.0,satisfied +20898,4606,Female,Loyal Customer,43,Business travel,Business,719,3,3,3,3,4,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +20899,58534,Male,Loyal Customer,46,Business travel,Business,1918,4,4,4,4,2,4,4,5,5,5,5,3,5,4,17,0.0,satisfied +20900,114736,Male,Loyal Customer,29,Business travel,Business,2579,1,1,1,1,3,3,3,3,5,3,4,3,5,3,2,0.0,satisfied +20901,120980,Female,disloyal Customer,15,Business travel,Eco,951,3,3,3,4,4,3,5,4,4,5,5,4,5,4,1,0.0,neutral or dissatisfied +20902,114574,Female,Loyal Customer,58,Business travel,Business,2055,3,3,3,3,5,5,5,4,2,4,5,5,5,5,149,142.0,satisfied +20903,89042,Male,Loyal Customer,56,Business travel,Business,2139,2,2,2,2,5,4,4,3,2,5,5,4,3,4,130,134.0,satisfied +20904,83223,Female,Loyal Customer,55,Business travel,Business,1979,5,5,5,5,3,4,4,4,4,4,4,5,4,3,15,33.0,satisfied +20905,85987,Male,Loyal Customer,59,Business travel,Business,447,1,1,1,1,5,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +20906,123565,Female,Loyal Customer,35,Business travel,Business,1773,1,4,4,4,4,2,3,1,1,1,1,2,1,4,16,40.0,neutral or dissatisfied +20907,942,Male,Loyal Customer,46,Business travel,Business,309,5,5,5,5,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +20908,99623,Male,Loyal Customer,42,Business travel,Eco,1224,1,5,5,5,1,1,1,1,4,4,3,3,3,1,0,4.0,neutral or dissatisfied +20909,25009,Female,Loyal Customer,23,Personal Travel,Eco Plus,484,2,5,2,2,3,2,4,3,4,2,5,3,5,3,0,0.0,neutral or dissatisfied +20910,97257,Male,Loyal Customer,17,Business travel,Business,393,4,4,4,4,4,4,4,4,1,1,1,3,1,4,6,0.0,satisfied +20911,11568,Male,Loyal Customer,46,Business travel,Business,3485,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +20912,13449,Female,Loyal Customer,26,Personal Travel,Eco,491,2,5,2,2,1,2,1,1,4,5,3,2,3,1,0,27.0,neutral or dissatisfied +20913,99380,Female,Loyal Customer,41,Business travel,Business,2043,2,2,4,2,4,4,5,4,4,4,4,3,4,4,5,0.0,satisfied +20914,59683,Female,Loyal Customer,13,Personal Travel,Eco,965,3,4,3,3,5,3,5,5,5,3,5,4,4,5,0,0.0,neutral or dissatisfied +20915,3738,Male,Loyal Customer,40,Personal Travel,Eco,427,3,0,3,2,3,3,1,3,4,4,3,4,5,3,22,19.0,neutral or dissatisfied +20916,109403,Female,Loyal Customer,50,Personal Travel,Eco Plus,1189,2,5,3,3,3,5,5,3,3,3,5,5,3,3,4,0.0,neutral or dissatisfied +20917,11069,Female,Loyal Customer,23,Personal Travel,Eco,312,2,5,2,4,5,2,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +20918,46440,Female,Loyal Customer,43,Business travel,Eco,1304,1,1,1,1,2,3,3,1,1,1,1,3,1,4,24,10.0,neutral or dissatisfied +20919,104980,Female,disloyal Customer,45,Business travel,Eco,337,3,2,3,4,4,3,3,4,4,1,4,1,4,4,9,8.0,neutral or dissatisfied +20920,104384,Female,Loyal Customer,67,Personal Travel,Eco,228,3,5,3,1,2,5,5,4,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +20921,77401,Female,Loyal Customer,21,Personal Travel,Eco,590,2,1,2,3,3,2,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +20922,35519,Male,Loyal Customer,52,Personal Travel,Eco,1028,3,5,2,4,2,2,2,3,2,5,4,2,5,2,154,148.0,neutral or dissatisfied +20923,103737,Female,Loyal Customer,11,Personal Travel,Eco,251,3,1,3,3,4,3,4,4,2,3,3,3,4,4,0,0.0,neutral or dissatisfied +20924,74273,Female,disloyal Customer,24,Business travel,Eco,1003,1,1,1,1,5,1,5,5,5,5,4,4,4,5,0,0.0,neutral or dissatisfied +20925,91896,Female,disloyal Customer,30,Business travel,Business,2586,0,0,0,2,3,0,3,3,3,5,4,4,4,3,0,0.0,satisfied +20926,111062,Female,Loyal Customer,56,Personal Travel,Eco,319,3,5,3,4,4,5,5,4,4,3,4,2,4,5,93,89.0,neutral or dissatisfied +20927,121978,Male,Loyal Customer,54,Business travel,Business,185,5,5,5,5,2,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +20928,128509,Male,Loyal Customer,65,Personal Travel,Eco,304,3,5,3,5,1,3,1,1,4,2,5,4,5,1,0,0.0,neutral or dissatisfied +20929,64972,Female,Loyal Customer,37,Business travel,Eco,190,3,2,2,2,3,4,3,3,3,2,5,1,5,3,0,0.0,satisfied +20930,87837,Male,Loyal Customer,68,Personal Travel,Eco,214,3,0,3,4,4,3,3,4,3,5,3,1,4,4,1,0.0,neutral or dissatisfied +20931,45721,Male,disloyal Customer,18,Business travel,Eco,852,4,5,5,3,1,5,5,1,2,1,4,1,3,1,29,21.0,neutral or dissatisfied +20932,65201,Male,Loyal Customer,40,Business travel,Business,224,4,4,4,4,5,4,4,4,4,4,4,4,4,3,6,33.0,satisfied +20933,22437,Female,Loyal Customer,65,Personal Travel,Eco,208,2,2,2,1,1,1,2,1,1,2,1,4,1,4,1,0.0,neutral or dissatisfied +20934,17449,Male,Loyal Customer,49,Business travel,Eco Plus,376,5,4,4,4,5,5,5,5,3,5,3,3,4,5,0,0.0,satisfied +20935,10154,Male,Loyal Customer,40,Business travel,Business,1195,4,4,4,4,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +20936,13863,Female,disloyal Customer,29,Business travel,Eco,667,2,4,2,4,2,2,2,2,2,3,3,4,4,2,5,9.0,neutral or dissatisfied +20937,99506,Female,Loyal Customer,19,Personal Travel,Eco,283,1,3,1,3,4,1,4,4,3,2,4,1,4,4,0,3.0,neutral or dissatisfied +20938,58515,Male,Loyal Customer,16,Personal Travel,Eco,719,4,4,4,4,5,4,5,5,5,4,5,4,4,5,31,20.0,neutral or dissatisfied +20939,127939,Female,Loyal Customer,16,Personal Travel,Eco,2300,3,1,3,2,5,3,3,5,1,2,2,1,3,5,0,0.0,neutral or dissatisfied +20940,127830,Male,Loyal Customer,13,Personal Travel,Eco,1044,2,5,2,3,4,2,4,4,1,3,3,5,1,4,0,0.0,neutral or dissatisfied +20941,103599,Male,Loyal Customer,32,Business travel,Business,2582,2,2,2,2,5,5,5,5,3,2,4,4,5,5,0,0.0,satisfied +20942,108444,Male,disloyal Customer,22,Business travel,Eco,1444,1,1,1,4,1,1,1,1,3,5,3,4,3,1,0,7.0,neutral or dissatisfied +20943,21260,Male,Loyal Customer,68,Personal Travel,Business,903,3,5,3,2,1,1,3,1,1,3,1,3,1,2,82,65.0,neutral or dissatisfied +20944,61810,Female,Loyal Customer,16,Personal Travel,Eco,1379,2,5,2,1,5,2,5,5,5,5,5,4,4,5,27,25.0,neutral or dissatisfied +20945,54027,Female,Loyal Customer,42,Personal Travel,Eco,1091,3,3,3,4,5,3,4,5,5,3,5,2,5,3,0,0.0,neutral or dissatisfied +20946,107034,Male,Loyal Customer,39,Business travel,Business,2072,2,2,5,2,5,4,4,4,4,4,4,3,4,4,44,44.0,satisfied +20947,95267,Male,Loyal Customer,55,Personal Travel,Eco,192,2,5,2,1,5,2,4,5,3,2,4,4,5,5,95,91.0,neutral or dissatisfied +20948,8664,Female,Loyal Customer,55,Business travel,Business,280,2,5,3,3,5,2,2,2,2,2,2,3,2,2,0,9.0,neutral or dissatisfied +20949,76822,Male,Loyal Customer,45,Business travel,Business,1851,1,1,1,1,4,3,4,2,2,2,2,3,2,4,0,0.0,satisfied +20950,74684,Female,Loyal Customer,9,Personal Travel,Eco,1431,3,3,3,5,1,3,1,1,1,1,4,4,1,1,0,0.0,neutral or dissatisfied +20951,37114,Male,Loyal Customer,43,Business travel,Business,2456,1,1,1,1,1,2,5,4,4,5,4,4,4,5,37,44.0,satisfied +20952,70223,Male,Loyal Customer,52,Business travel,Business,2799,2,2,2,2,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +20953,125604,Male,Loyal Customer,15,Personal Travel,Eco,1587,3,5,4,4,3,4,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +20954,83032,Female,Loyal Customer,32,Business travel,Business,1602,5,5,5,5,5,5,5,5,4,2,5,5,4,5,0,15.0,satisfied +20955,88087,Male,Loyal Customer,45,Business travel,Business,270,0,1,1,2,5,4,4,1,1,1,1,3,1,3,77,76.0,satisfied +20956,18395,Female,disloyal Customer,38,Business travel,Eco,378,1,2,1,3,4,1,4,4,3,5,4,2,3,4,0,0.0,neutral or dissatisfied +20957,86116,Female,disloyal Customer,26,Business travel,Business,356,4,3,4,2,4,4,4,4,4,2,5,3,5,4,21,17.0,satisfied +20958,31648,Male,Loyal Customer,35,Business travel,Eco,862,4,4,4,4,4,4,4,4,3,2,5,3,1,4,0,0.0,satisfied +20959,54016,Female,disloyal Customer,24,Business travel,Eco,1091,2,2,2,1,3,2,3,3,5,2,3,5,4,3,0,0.0,neutral or dissatisfied +20960,55310,Male,Loyal Customer,38,Business travel,Business,3921,2,2,4,2,2,4,5,5,5,5,5,4,5,3,6,0.0,satisfied +20961,85341,Female,disloyal Customer,24,Business travel,Eco,696,1,1,1,4,5,1,4,5,4,4,5,3,5,5,0,0.0,neutral or dissatisfied +20962,118783,Male,Loyal Customer,9,Personal Travel,Eco,369,3,1,0,2,3,0,3,3,4,5,2,3,1,3,2,0.0,neutral or dissatisfied +20963,23217,Female,Loyal Customer,39,Personal Travel,Eco,326,4,3,4,3,5,4,5,5,4,4,5,3,5,5,68,99.0,satisfied +20964,113093,Male,Loyal Customer,45,Business travel,Business,2584,3,4,4,4,5,3,4,2,2,2,3,1,2,3,21,15.0,neutral or dissatisfied +20965,127766,Female,Loyal Customer,34,Personal Travel,Eco,255,3,2,3,3,1,3,1,1,4,2,3,4,4,1,0,0.0,neutral or dissatisfied +20966,50516,Male,Loyal Customer,14,Personal Travel,Eco,109,5,0,5,3,5,5,2,5,3,3,4,5,5,5,26,35.0,satisfied +20967,73589,Male,Loyal Customer,45,Business travel,Eco,204,1,4,4,4,2,1,2,2,3,4,4,4,4,2,0,1.0,neutral or dissatisfied +20968,63796,Male,Loyal Customer,27,Personal Travel,Eco,1721,2,4,2,5,5,2,5,5,1,3,3,5,2,5,0,0.0,neutral or dissatisfied +20969,31096,Male,disloyal Customer,20,Business travel,Eco,614,3,0,3,1,4,3,4,4,4,5,5,4,2,4,0,0.0,neutral or dissatisfied +20970,57180,Male,Loyal Customer,11,Personal Travel,Eco,2227,4,1,4,2,4,4,4,4,1,5,1,3,1,4,0,0.0,satisfied +20971,105907,Male,disloyal Customer,21,Business travel,Eco,283,3,1,4,3,3,4,4,3,3,2,3,4,4,3,0,0.0,neutral or dissatisfied +20972,6129,Female,Loyal Customer,40,Business travel,Business,3676,5,5,5,5,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +20973,95859,Female,Loyal Customer,51,Business travel,Business,2623,2,2,2,2,5,5,4,4,4,4,4,3,4,5,25,25.0,satisfied +20974,9478,Female,Loyal Customer,38,Personal Travel,Business,322,4,5,4,1,5,4,3,3,3,4,3,3,3,4,105,102.0,neutral or dissatisfied +20975,54721,Male,Loyal Customer,10,Personal Travel,Eco,787,4,4,4,1,3,4,3,3,3,2,5,5,5,3,1,0.0,neutral or dissatisfied +20976,79174,Male,Loyal Customer,40,Business travel,Business,2422,4,4,4,4,5,5,5,5,3,4,4,5,4,5,89,80.0,satisfied +20977,93988,Male,Loyal Customer,49,Personal Travel,Eco,1218,2,3,2,3,4,2,4,4,5,4,1,3,1,4,0,0.0,neutral or dissatisfied +20978,2238,Male,disloyal Customer,37,Business travel,Eco Plus,459,3,3,3,4,5,3,5,5,2,4,3,2,4,5,0,0.0,neutral or dissatisfied +20979,112719,Male,Loyal Customer,25,Personal Travel,Eco,605,1,5,1,1,4,1,4,4,2,5,4,5,5,4,0,0.0,neutral or dissatisfied +20980,90577,Male,Loyal Customer,49,Business travel,Business,271,4,4,4,4,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +20981,79459,Male,Loyal Customer,51,Business travel,Business,3717,3,3,3,3,2,4,4,4,4,4,4,5,4,3,0,1.0,satisfied +20982,110490,Female,Loyal Customer,47,Personal Travel,Eco,883,2,0,1,2,1,3,5,1,1,1,1,2,1,3,15,9.0,neutral or dissatisfied +20983,59755,Male,Loyal Customer,48,Business travel,Business,3279,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +20984,74545,Female,Loyal Customer,30,Business travel,Business,2756,1,1,1,1,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +20985,28334,Female,disloyal Customer,27,Business travel,Eco,867,1,1,1,4,4,1,4,4,1,2,3,1,3,4,0,0.0,neutral or dissatisfied +20986,74284,Male,Loyal Customer,44,Business travel,Business,2311,4,4,4,4,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +20987,78091,Female,Loyal Customer,67,Personal Travel,Eco Plus,152,3,2,0,3,2,4,4,5,5,0,5,4,5,2,4,0.0,neutral or dissatisfied +20988,28906,Male,Loyal Customer,25,Business travel,Business,3547,2,2,2,2,5,5,5,5,5,5,1,4,4,5,0,0.0,satisfied +20989,87575,Male,disloyal Customer,37,Business travel,Eco,432,3,2,4,4,1,4,1,1,3,5,3,2,4,1,0,0.0,neutral or dissatisfied +20990,42261,Male,Loyal Customer,14,Business travel,Eco,550,2,4,4,4,2,2,1,2,1,5,3,3,3,2,0,9.0,neutral or dissatisfied +20991,23285,Female,Loyal Customer,44,Business travel,Eco,979,3,4,4,4,5,3,5,3,3,3,3,1,3,3,8,0.0,satisfied +20992,129872,Female,Loyal Customer,32,Business travel,Eco Plus,337,4,2,4,2,4,4,4,4,5,1,3,5,1,4,0,1.0,satisfied +20993,40775,Female,Loyal Customer,52,Business travel,Eco,584,3,3,3,3,1,2,3,3,3,3,3,2,3,3,0,62.0,neutral or dissatisfied +20994,67823,Female,Loyal Customer,52,Business travel,Eco,771,4,4,4,4,4,2,1,3,3,4,3,1,3,3,57,51.0,satisfied +20995,18675,Male,Loyal Customer,42,Personal Travel,Eco,190,1,4,1,2,3,1,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +20996,70957,Male,Loyal Customer,34,Business travel,Business,2948,1,1,1,1,4,5,4,4,4,4,4,5,4,3,11,0.0,satisfied +20997,62739,Male,disloyal Customer,26,Business travel,Business,2367,4,4,4,4,4,2,2,3,2,4,4,2,3,2,282,280.0,neutral or dissatisfied +20998,8331,Female,Loyal Customer,50,Business travel,Business,3781,4,4,2,4,3,5,5,5,5,5,5,4,5,5,15,3.0,satisfied +20999,19784,Male,Loyal Customer,31,Business travel,Business,1532,1,1,1,1,1,1,1,1,3,2,4,1,3,1,13,12.0,neutral or dissatisfied +21000,61600,Female,Loyal Customer,50,Business travel,Business,1379,5,5,1,5,5,5,5,5,5,5,5,5,5,4,19,0.0,satisfied +21001,55657,Male,Loyal Customer,64,Personal Travel,Eco,296,3,5,3,5,4,3,4,4,4,4,4,2,1,4,0,0.0,neutral or dissatisfied +21002,99104,Male,Loyal Customer,32,Business travel,Business,3970,4,4,4,4,5,5,5,5,4,4,5,3,4,5,0,0.0,satisfied +21003,8278,Female,Loyal Customer,33,Personal Travel,Eco,530,1,5,2,1,1,2,1,1,3,3,5,5,4,1,8,6.0,neutral or dissatisfied +21004,77660,Male,Loyal Customer,28,Business travel,Business,689,3,3,3,3,5,5,5,5,4,3,4,5,4,5,0,0.0,satisfied +21005,91761,Male,Loyal Customer,65,Business travel,Business,590,2,1,1,1,1,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +21006,105761,Male,Loyal Customer,23,Business travel,Business,263,1,1,1,1,5,5,5,5,2,1,5,3,5,5,10,0.0,satisfied +21007,108027,Male,Loyal Customer,44,Business travel,Business,306,3,3,3,3,2,5,4,4,4,4,4,5,4,5,2,0.0,satisfied +21008,86904,Female,Loyal Customer,49,Business travel,Business,341,1,3,3,3,5,2,3,1,1,1,1,1,1,2,67,61.0,neutral or dissatisfied +21009,106997,Female,Loyal Customer,33,Personal Travel,Eco,937,2,2,2,4,4,2,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +21010,81849,Female,disloyal Customer,36,Personal Travel,Eco,1501,0,4,0,3,4,0,4,4,5,4,5,5,5,4,0,0.0,satisfied +21011,120974,Female,Loyal Customer,31,Business travel,Business,1898,2,4,5,5,2,2,2,2,4,1,3,2,3,2,0,0.0,neutral or dissatisfied +21012,33101,Female,Loyal Customer,13,Personal Travel,Eco,201,4,5,0,3,3,0,3,3,5,5,4,5,1,3,0,0.0,satisfied +21013,22816,Female,Loyal Customer,40,Business travel,Eco,147,4,2,2,2,4,4,4,1,4,3,2,4,2,4,146,156.0,neutral or dissatisfied +21014,16078,Male,Loyal Customer,70,Personal Travel,Eco,744,3,2,3,4,1,3,1,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +21015,127693,Female,Loyal Customer,45,Business travel,Business,2133,1,1,1,1,4,4,4,2,2,2,2,4,2,3,19,12.0,satisfied +21016,54209,Female,Loyal Customer,13,Business travel,Eco Plus,1504,4,2,2,2,4,4,5,4,3,1,5,3,2,4,8,1.0,satisfied +21017,127678,Female,Loyal Customer,52,Personal Travel,Eco,2153,1,5,1,3,2,4,4,3,3,1,3,4,3,3,0,0.0,neutral or dissatisfied +21018,118537,Female,Loyal Customer,11,Business travel,Business,2360,1,5,2,5,1,1,1,1,4,1,3,1,3,1,17,16.0,neutral or dissatisfied +21019,61886,Male,disloyal Customer,37,Business travel,Eco,636,2,3,2,3,1,2,1,1,1,4,4,2,4,1,22,14.0,neutral or dissatisfied +21020,30459,Male,Loyal Customer,56,Personal Travel,Eco,991,3,2,3,4,5,3,5,5,4,3,4,2,4,5,12,3.0,neutral or dissatisfied +21021,118740,Male,Loyal Customer,21,Personal Travel,Eco,368,2,1,2,3,3,2,5,3,2,4,4,2,4,3,0,0.0,neutral or dissatisfied +21022,108701,Male,Loyal Customer,11,Personal Travel,Eco Plus,577,2,4,2,1,4,2,4,4,3,5,5,4,4,4,1,0.0,neutral or dissatisfied +21023,61256,Male,Loyal Customer,34,Personal Travel,Eco,967,1,5,1,5,4,1,5,4,5,2,4,4,5,4,5,11.0,neutral or dissatisfied +21024,123435,Male,Loyal Customer,29,Personal Travel,Business,2296,1,4,1,3,4,1,4,4,5,2,3,5,4,4,8,0.0,neutral or dissatisfied +21025,126171,Female,disloyal Customer,22,Business travel,Eco,650,2,0,2,1,4,2,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +21026,59272,Male,Loyal Customer,34,Business travel,Eco,4243,5,5,5,5,5,5,5,4,5,2,5,5,5,5,4,1.0,satisfied +21027,128928,Male,Loyal Customer,57,Business travel,Business,1989,3,3,3,3,3,4,4,5,5,5,5,5,5,4,2,0.0,satisfied +21028,126115,Male,disloyal Customer,34,Business travel,Business,468,3,3,3,4,5,3,5,5,4,5,5,3,5,5,3,4.0,neutral or dissatisfied +21029,102957,Female,Loyal Customer,18,Personal Travel,Eco,719,3,4,3,3,4,3,1,4,5,5,4,4,5,4,0,0.0,neutral or dissatisfied +21030,111937,Female,Loyal Customer,52,Business travel,Business,533,4,4,4,4,5,4,5,5,5,5,5,4,5,4,5,0.0,satisfied +21031,125786,Male,Loyal Customer,53,Business travel,Business,3011,5,5,5,5,2,4,4,4,4,4,4,3,4,3,0,2.0,satisfied +21032,108630,Male,Loyal Customer,24,Business travel,Business,1547,4,1,1,1,4,4,4,4,2,3,4,4,4,4,7,0.0,neutral or dissatisfied +21033,21767,Male,Loyal Customer,24,Business travel,Eco,341,5,1,1,1,5,5,5,5,2,3,2,5,1,5,0,0.0,satisfied +21034,21894,Male,Loyal Customer,47,Business travel,Business,3425,3,3,3,3,3,2,5,5,5,5,5,5,5,4,0,0.0,satisfied +21035,110994,Female,Loyal Customer,47,Business travel,Business,3777,5,5,5,5,4,5,5,4,4,4,5,4,4,4,0,0.0,satisfied +21036,9832,Female,Loyal Customer,8,Personal Travel,Eco,476,4,2,4,3,4,4,4,4,1,5,4,2,3,4,1,0.0,neutral or dissatisfied +21037,90085,Male,Loyal Customer,60,Business travel,Business,3959,5,5,5,5,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +21038,49293,Male,Loyal Customer,62,Business travel,Business,2639,4,4,4,4,5,3,1,5,5,5,5,2,5,5,0,0.0,satisfied +21039,68937,Male,Loyal Customer,24,Business travel,Business,646,4,3,2,3,4,4,4,2,1,4,4,4,2,4,227,209.0,neutral or dissatisfied +21040,90343,Male,Loyal Customer,37,Business travel,Business,594,3,3,5,3,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +21041,75100,Female,Loyal Customer,45,Business travel,Business,1744,3,3,3,3,5,3,5,4,4,4,4,4,4,5,9,0.0,satisfied +21042,84651,Female,disloyal Customer,29,Business travel,Business,363,3,3,3,1,5,3,5,5,4,3,4,5,4,5,0,0.0,neutral or dissatisfied +21043,113633,Male,Loyal Customer,60,Personal Travel,Eco,407,2,4,4,3,1,4,1,1,1,1,4,4,3,1,14,12.0,neutral or dissatisfied +21044,70426,Male,disloyal Customer,24,Business travel,Business,187,0,4,0,4,1,0,1,1,4,4,5,5,4,1,15,4.0,satisfied +21045,30161,Male,Loyal Customer,17,Personal Travel,Eco,82,1,3,1,3,5,1,5,5,5,5,2,4,2,5,0,0.0,neutral or dissatisfied +21046,75311,Male,Loyal Customer,55,Business travel,Business,2486,1,1,1,1,4,4,4,4,2,4,5,4,5,4,15,27.0,satisfied +21047,40840,Female,disloyal Customer,40,Business travel,Business,132,3,3,3,3,1,3,1,1,3,4,5,4,5,1,0,0.0,neutral or dissatisfied +21048,20333,Male,disloyal Customer,26,Business travel,Business,287,3,4,3,1,4,3,4,4,2,4,4,3,2,4,17,9.0,neutral or dissatisfied +21049,42446,Female,disloyal Customer,30,Business travel,Eco,866,2,1,1,4,1,1,1,1,4,5,1,4,4,1,1,2.0,neutral or dissatisfied +21050,63097,Female,disloyal Customer,37,Business travel,Business,967,2,2,2,5,4,2,4,4,3,2,4,3,4,4,0,0.0,neutral or dissatisfied +21051,17089,Female,Loyal Customer,53,Business travel,Eco,416,4,3,3,3,3,3,2,4,4,4,4,1,4,3,3,1.0,satisfied +21052,114037,Male,Loyal Customer,47,Business travel,Business,3704,1,1,2,1,5,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +21053,3085,Male,Loyal Customer,24,Business travel,Business,594,1,1,1,1,4,4,4,4,5,4,4,4,5,4,10,25.0,satisfied +21054,58221,Male,Loyal Customer,57,Personal Travel,Eco,925,3,5,3,1,1,3,1,1,4,3,5,5,4,1,0,0.0,neutral or dissatisfied +21055,31022,Female,Loyal Customer,70,Personal Travel,Eco,391,4,1,4,2,4,3,3,4,4,4,4,2,4,1,20,47.0,neutral or dissatisfied +21056,28898,Male,Loyal Customer,26,Business travel,Business,1543,2,2,2,2,4,4,4,4,1,3,1,1,5,4,27,19.0,satisfied +21057,123401,Female,Loyal Customer,49,Business travel,Business,1337,1,1,1,1,5,4,5,2,2,2,2,3,2,4,0,2.0,satisfied +21058,67098,Female,disloyal Customer,38,Business travel,Eco,1102,3,3,3,3,5,3,5,5,4,2,3,3,3,5,4,12.0,neutral or dissatisfied +21059,65867,Male,Loyal Customer,50,Personal Travel,Eco,1389,5,5,5,4,4,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +21060,97079,Female,Loyal Customer,42,Business travel,Business,1390,5,5,5,5,5,5,4,5,5,5,5,3,5,5,6,0.0,satisfied +21061,122375,Male,Loyal Customer,54,Business travel,Eco,529,3,1,1,1,3,3,3,3,3,5,3,2,4,3,0,0.0,neutral or dissatisfied +21062,3167,Male,Loyal Customer,36,Business travel,Business,2097,3,3,2,3,4,4,5,3,3,3,3,4,3,3,20,5.0,satisfied +21063,89423,Female,Loyal Customer,55,Business travel,Business,151,1,1,1,1,4,4,3,5,5,5,3,1,5,3,0,0.0,satisfied +21064,61684,Male,Loyal Customer,55,Business travel,Business,1504,4,4,4,4,3,5,5,2,2,2,2,5,2,5,0,0.0,satisfied +21065,72964,Female,Loyal Customer,24,Business travel,Business,2634,5,5,5,5,5,5,5,5,4,2,4,4,5,5,17,0.0,satisfied +21066,98186,Male,Loyal Customer,51,Business travel,Business,3542,2,2,2,2,2,5,5,4,4,5,4,4,4,4,67,59.0,satisfied +21067,53403,Female,Loyal Customer,57,Business travel,Business,2253,2,5,5,5,4,2,4,2,2,2,2,1,2,3,11,17.0,neutral or dissatisfied +21068,126599,Male,Loyal Customer,59,Business travel,Business,1337,3,2,2,2,2,4,4,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +21069,44329,Female,disloyal Customer,38,Business travel,Eco,412,2,3,2,4,2,2,2,2,1,1,3,1,4,2,19,8.0,neutral or dissatisfied +21070,5037,Female,Loyal Customer,48,Business travel,Business,2629,0,5,0,2,3,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +21071,49720,Male,Loyal Customer,54,Business travel,Eco,109,1,0,0,4,3,1,2,3,1,5,3,4,3,3,0,0.0,neutral or dissatisfied +21072,102641,Female,Loyal Customer,50,Business travel,Business,3410,2,5,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +21073,56402,Male,disloyal Customer,49,Business travel,Business,719,5,5,5,3,2,5,2,2,3,4,4,3,5,2,16,20.0,satisfied +21074,118145,Female,Loyal Customer,43,Business travel,Business,1044,1,1,4,1,5,4,5,5,5,4,5,5,5,5,1,12.0,satisfied +21075,114785,Female,Loyal Customer,39,Business travel,Business,2883,1,1,1,1,2,4,5,5,5,5,5,3,5,5,22,25.0,satisfied +21076,76570,Male,Loyal Customer,30,Business travel,Business,1720,4,3,3,3,4,3,4,4,2,4,3,3,4,4,0,0.0,neutral or dissatisfied +21077,43611,Female,Loyal Customer,60,Business travel,Business,190,2,2,2,2,2,4,1,5,5,5,3,2,5,4,0,0.0,satisfied +21078,128186,Male,Loyal Customer,27,Personal Travel,Eco,1972,3,0,3,3,1,3,1,1,3,5,4,4,5,1,1,0.0,neutral or dissatisfied +21079,50041,Female,Loyal Customer,61,Business travel,Eco,134,2,4,4,4,3,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +21080,10109,Male,Loyal Customer,51,Personal Travel,Eco,391,3,4,3,3,1,3,1,1,3,2,1,4,2,1,0,0.0,neutral or dissatisfied +21081,44984,Male,Loyal Customer,63,Business travel,Business,222,4,4,4,4,1,1,1,4,4,4,5,3,4,5,5,1.0,satisfied +21082,27909,Male,disloyal Customer,37,Business travel,Eco,811,3,3,3,3,3,3,5,4,2,3,3,5,1,5,0,14.0,neutral or dissatisfied +21083,61115,Male,Loyal Customer,48,Personal Travel,Eco,120,4,4,0,4,4,0,4,4,1,5,5,4,4,4,9,2.0,satisfied +21084,71410,Female,Loyal Customer,56,Business travel,Business,1829,1,3,3,3,3,4,4,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +21085,20126,Male,Loyal Customer,40,Personal Travel,Eco,416,3,3,3,3,3,3,3,3,4,1,2,3,2,3,0,0.0,neutral or dissatisfied +21086,4040,Male,disloyal Customer,16,Business travel,Eco,479,1,1,1,4,1,1,1,1,3,3,3,2,4,1,43,27.0,neutral or dissatisfied +21087,70416,Male,Loyal Customer,29,Business travel,Eco Plus,1562,2,3,3,3,2,2,2,2,3,1,2,4,2,2,0,0.0,neutral or dissatisfied +21088,69445,Male,Loyal Customer,9,Personal Travel,Eco,1096,1,1,1,4,4,1,4,4,2,5,2,3,4,4,0,0.0,neutral or dissatisfied +21089,74712,Male,Loyal Customer,30,Personal Travel,Eco,1235,4,4,4,3,2,4,4,2,5,4,2,5,3,2,0,4.0,neutral or dissatisfied +21090,10194,Female,disloyal Customer,58,Business travel,Business,316,4,4,4,4,3,4,3,3,4,5,5,5,5,3,33,30.0,neutral or dissatisfied +21091,32773,Male,Loyal Customer,37,Business travel,Business,3878,1,1,1,1,3,4,3,1,1,2,1,1,1,3,0,4.0,neutral or dissatisfied +21092,98904,Female,Loyal Customer,34,Business travel,Business,543,5,5,4,5,2,5,4,4,4,4,4,3,4,5,6,6.0,satisfied +21093,103014,Female,disloyal Customer,37,Business travel,Business,460,3,3,3,1,3,3,3,3,4,5,4,5,4,3,42,71.0,neutral or dissatisfied +21094,14085,Female,Loyal Customer,39,Business travel,Business,371,4,4,4,4,2,3,2,4,4,5,4,2,4,1,0,0.0,satisfied +21095,110233,Male,Loyal Customer,28,Business travel,Business,1721,1,1,1,1,4,4,4,4,5,2,5,5,4,4,0,0.0,satisfied +21096,108242,Female,Loyal Customer,27,Business travel,Business,895,1,5,5,5,1,1,1,1,4,5,4,4,4,1,6,9.0,neutral or dissatisfied +21097,71244,Female,Loyal Customer,53,Business travel,Business,733,2,3,3,3,3,3,3,2,2,2,2,2,2,3,1,0.0,neutral or dissatisfied +21098,8645,Female,Loyal Customer,39,Business travel,Business,2977,3,1,3,3,5,5,5,4,4,4,4,4,4,3,0,19.0,satisfied +21099,59580,Male,Loyal Customer,39,Business travel,Business,1892,1,1,1,1,3,4,4,3,3,4,3,4,3,3,15,0.0,satisfied +21100,31267,Male,Loyal Customer,32,Business travel,Business,3432,3,3,3,3,5,5,5,5,2,4,4,2,5,5,41,64.0,satisfied +21101,49618,Male,disloyal Customer,33,Business travel,Eco,109,3,0,3,4,1,3,1,1,4,3,4,5,4,1,3,0.0,neutral or dissatisfied +21102,71455,Female,disloyal Customer,43,Business travel,Eco,467,2,4,2,3,4,2,4,4,3,2,1,4,2,4,23,54.0,neutral or dissatisfied +21103,108299,Male,Loyal Customer,51,Business travel,Business,1750,2,2,2,2,3,3,4,2,2,2,2,4,2,5,14,0.0,satisfied +21104,119777,Female,Loyal Customer,42,Business travel,Business,2666,2,1,1,1,4,4,4,2,2,3,2,2,2,1,2,54.0,neutral or dissatisfied +21105,63694,Female,Loyal Customer,38,Business travel,Business,3857,1,4,3,4,5,3,3,1,1,1,1,4,1,4,0,28.0,neutral or dissatisfied +21106,38291,Male,Loyal Customer,10,Personal Travel,Eco Plus,1180,3,5,3,1,2,3,1,2,3,5,3,5,4,2,13,19.0,neutral or dissatisfied +21107,5179,Female,Loyal Customer,46,Business travel,Business,3826,3,3,3,3,5,5,5,4,2,5,4,5,5,5,247,254.0,satisfied +21108,98888,Female,disloyal Customer,38,Business travel,Eco Plus,991,3,4,4,3,2,4,2,2,4,5,3,2,4,2,0,2.0,neutral or dissatisfied +21109,23730,Male,Loyal Customer,14,Personal Travel,Eco Plus,212,2,4,2,1,5,2,3,5,5,3,4,5,4,5,12,9.0,neutral or dissatisfied +21110,85765,Female,Loyal Customer,42,Business travel,Business,666,5,5,5,5,3,4,4,4,4,4,4,5,4,4,5,0.0,satisfied +21111,76444,Male,Loyal Customer,45,Business travel,Eco Plus,405,2,4,4,4,2,2,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +21112,9106,Male,Loyal Customer,44,Business travel,Business,3520,4,4,4,4,5,4,4,3,3,3,3,3,3,4,0,0.0,satisfied +21113,87291,Female,Loyal Customer,22,Personal Travel,Eco,577,5,5,5,3,1,5,1,1,4,2,5,3,4,1,0,0.0,satisfied +21114,6749,Female,Loyal Customer,42,Business travel,Business,1956,0,4,0,2,4,5,5,3,3,3,3,4,3,3,0,0.0,satisfied +21115,86467,Female,disloyal Customer,75,Business travel,Eco,394,3,1,3,4,3,3,3,3,4,1,3,4,4,3,26,23.0,neutral or dissatisfied +21116,81284,Female,Loyal Customer,22,Personal Travel,Eco,1020,1,3,1,2,2,1,4,2,5,5,4,1,5,2,7,0.0,neutral or dissatisfied +21117,120781,Male,Loyal Customer,16,Personal Travel,Eco,678,1,5,2,1,2,2,2,2,1,2,5,5,3,2,0,0.0,neutral or dissatisfied +21118,30574,Female,Loyal Customer,13,Business travel,Business,628,2,2,2,2,2,2,2,2,1,1,4,4,3,2,0,0.0,neutral or dissatisfied +21119,101938,Female,Loyal Customer,59,Business travel,Business,804,3,3,5,3,2,5,5,3,3,3,3,3,3,5,5,4.0,satisfied +21120,124658,Male,disloyal Customer,39,Business travel,Business,399,1,1,1,1,4,1,4,4,5,2,5,3,4,4,7,4.0,neutral or dissatisfied +21121,14123,Male,Loyal Customer,48,Personal Travel,Business,528,2,3,2,2,3,1,5,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +21122,121317,Female,Loyal Customer,12,Personal Travel,Eco,1009,4,4,4,4,1,4,1,1,4,2,5,4,5,1,0,0.0,satisfied +21123,87964,Male,Loyal Customer,41,Business travel,Business,406,1,1,1,1,2,5,5,4,4,5,4,4,4,5,74,66.0,satisfied +21124,117459,Male,Loyal Customer,41,Personal Travel,Eco,1107,3,0,3,1,3,3,3,3,3,4,4,3,4,3,21,5.0,neutral or dissatisfied +21125,89895,Female,Loyal Customer,29,Business travel,Business,1501,4,1,1,1,4,3,4,4,3,5,4,1,3,4,5,0.0,neutral or dissatisfied +21126,123980,Male,Loyal Customer,48,Business travel,Business,184,5,5,5,5,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21127,74380,Female,Loyal Customer,47,Business travel,Business,1464,2,2,2,2,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +21128,41790,Male,Loyal Customer,52,Business travel,Business,2780,4,4,4,4,1,5,1,5,5,5,5,1,5,3,0,0.0,satisfied +21129,78913,Female,Loyal Customer,68,Personal Travel,Eco,980,3,4,3,1,2,4,4,2,2,3,2,5,2,4,6,3.0,neutral or dissatisfied +21130,125580,Male,Loyal Customer,80,Business travel,Business,226,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +21131,25020,Male,disloyal Customer,27,Business travel,Eco,907,1,1,1,4,3,1,3,3,2,3,3,1,3,3,0,0.0,neutral or dissatisfied +21132,76925,Female,Loyal Customer,32,Business travel,Business,1823,4,4,1,4,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +21133,100688,Male,Loyal Customer,41,Personal Travel,Eco,628,2,5,2,5,2,2,2,2,5,5,5,3,4,2,0,0.0,neutral or dissatisfied +21134,16180,Female,disloyal Customer,21,Business travel,Eco,277,2,0,2,5,5,2,5,5,2,2,1,5,5,5,0,0.0,neutral or dissatisfied +21135,101125,Male,Loyal Customer,43,Business travel,Business,3744,3,1,3,3,1,3,3,3,3,3,3,2,3,2,45,43.0,neutral or dissatisfied +21136,118168,Male,disloyal Customer,13,Business travel,Business,1440,0,5,0,4,5,0,5,5,4,3,5,3,4,5,0,0.0,satisfied +21137,69285,Male,Loyal Customer,51,Personal Travel,Eco,733,2,5,1,3,4,1,4,4,3,1,3,5,1,4,2,0.0,neutral or dissatisfied +21138,1384,Female,Loyal Customer,52,Business travel,Eco Plus,140,4,3,3,3,5,2,3,4,4,4,4,2,4,3,0,0.0,satisfied +21139,123793,Female,disloyal Customer,23,Business travel,Eco,544,2,0,2,2,1,2,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +21140,3916,Female,Loyal Customer,30,Personal Travel,Eco,213,1,4,0,3,2,0,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +21141,63525,Female,Loyal Customer,32,Business travel,Business,2861,3,3,3,3,4,4,4,4,5,5,5,4,4,4,382,372.0,satisfied +21142,32949,Female,Loyal Customer,25,Personal Travel,Eco,216,2,3,2,3,2,2,2,2,3,4,3,3,3,2,53,54.0,neutral or dissatisfied +21143,62934,Male,Loyal Customer,42,Business travel,Business,3331,2,2,2,2,3,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +21144,89029,Male,Loyal Customer,43,Business travel,Business,1892,2,2,2,2,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +21145,65001,Female,Loyal Customer,36,Business travel,Eco,224,4,4,4,4,4,4,4,4,5,5,1,4,4,4,0,0.0,satisfied +21146,94463,Female,Loyal Customer,41,Business travel,Business,2021,0,5,0,1,5,4,4,4,4,3,3,5,4,3,0,0.0,satisfied +21147,53460,Female,Loyal Customer,35,Business travel,Eco,2442,1,2,1,1,1,1,1,1,3,3,3,1,1,1,0,0.0,neutral or dissatisfied +21148,78706,Male,Loyal Customer,42,Business travel,Business,528,4,4,4,4,2,4,5,4,4,4,4,4,4,3,2,0.0,satisfied +21149,69843,Male,Loyal Customer,31,Personal Travel,Eco,1055,3,5,4,1,5,4,5,5,4,5,4,5,4,5,0,0.0,neutral or dissatisfied +21150,38221,Female,Loyal Customer,65,Personal Travel,Eco Plus,1121,4,2,4,3,3,3,4,4,4,4,3,3,4,3,0,0.0,neutral or dissatisfied +21151,72340,Male,Loyal Customer,60,Business travel,Business,985,2,5,5,5,1,2,3,2,2,2,2,4,2,2,19,33.0,neutral or dissatisfied +21152,14915,Female,Loyal Customer,49,Personal Travel,Eco,315,2,2,2,4,2,5,5,3,5,4,4,5,3,5,158,169.0,neutral or dissatisfied +21153,76609,Female,disloyal Customer,24,Business travel,Eco,481,5,4,4,3,1,4,1,1,3,5,4,3,5,1,1,0.0,satisfied +21154,121745,Female,Loyal Customer,59,Personal Travel,Eco,1475,3,5,3,3,5,4,5,3,3,3,3,3,3,4,0,0.0,neutral or dissatisfied +21155,33521,Male,disloyal Customer,36,Business travel,Business,228,4,4,4,4,2,4,2,2,3,3,4,5,4,2,0,0.0,neutral or dissatisfied +21156,94254,Female,Loyal Customer,60,Business travel,Business,341,0,0,0,1,3,5,4,1,1,1,1,5,1,5,0,0.0,satisfied +21157,43066,Male,disloyal Customer,23,Business travel,Business,236,5,5,5,4,3,5,3,3,4,3,3,1,5,3,0,0.0,satisfied +21158,59542,Male,Loyal Customer,28,Business travel,Business,854,3,3,3,3,4,4,4,4,5,4,4,3,4,4,7,2.0,satisfied +21159,68291,Male,Loyal Customer,21,Personal Travel,Eco,806,1,5,1,2,2,1,2,2,3,1,5,2,4,2,0,0.0,neutral or dissatisfied +21160,59722,Female,Loyal Customer,29,Business travel,Eco Plus,854,3,4,4,4,3,3,3,3,1,1,3,3,3,3,0,0.0,neutral or dissatisfied +21161,16539,Female,Loyal Customer,54,Business travel,Eco,1134,5,2,2,2,2,5,3,5,5,5,5,2,5,3,69,81.0,satisfied +21162,77847,Male,Loyal Customer,50,Business travel,Eco Plus,874,2,3,2,3,2,2,2,2,1,5,3,1,3,2,20,15.0,neutral or dissatisfied +21163,84088,Female,Loyal Customer,33,Personal Travel,Eco,932,4,4,4,1,5,4,5,5,3,5,5,5,4,5,0,0.0,satisfied +21164,109802,Female,disloyal Customer,35,Business travel,Business,1011,2,2,2,3,4,2,4,4,5,3,5,4,5,4,28,25.0,neutral or dissatisfied +21165,72661,Male,Loyal Customer,23,Personal Travel,Eco,929,3,5,2,4,4,2,2,4,3,5,5,5,5,4,0,12.0,neutral or dissatisfied +21166,48790,Male,Loyal Customer,44,Business travel,Business,2535,2,5,5,5,3,2,2,2,2,2,2,2,2,2,8,13.0,neutral or dissatisfied +21167,27466,Male,Loyal Customer,31,Business travel,Business,1678,4,4,4,4,5,5,5,5,4,3,2,1,2,5,0,0.0,satisfied +21168,13523,Male,disloyal Customer,38,Business travel,Business,227,4,4,4,1,4,4,4,4,3,5,5,4,5,4,22,29.0,neutral or dissatisfied +21169,77334,Female,Loyal Customer,33,Business travel,Business,590,1,1,1,1,4,4,4,2,2,2,2,4,2,4,2,0.0,satisfied +21170,83408,Female,Loyal Customer,45,Business travel,Business,632,3,3,3,3,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +21171,106674,Female,Loyal Customer,54,Business travel,Business,451,5,5,5,5,4,5,4,4,4,4,4,3,4,3,49,42.0,satisfied +21172,94232,Female,Loyal Customer,45,Business travel,Business,189,4,4,4,4,2,5,4,4,4,4,4,3,4,4,1,0.0,satisfied +21173,29424,Male,Loyal Customer,26,Personal Travel,Eco Plus,2417,2,4,2,5,2,1,1,5,5,3,1,1,3,1,0,13.0,neutral or dissatisfied +21174,43117,Male,Loyal Customer,67,Personal Travel,Eco,192,3,2,3,4,2,3,5,2,4,1,3,4,4,2,0,0.0,neutral or dissatisfied +21175,65049,Male,Loyal Customer,41,Personal Travel,Eco,190,2,5,0,2,1,0,4,1,5,4,4,4,4,1,26,33.0,neutral or dissatisfied +21176,35915,Male,Loyal Customer,33,Personal Travel,Eco,2248,3,5,3,4,5,3,5,5,3,5,3,5,4,5,0,0.0,neutral or dissatisfied +21177,35445,Male,Loyal Customer,33,Personal Travel,Eco,1010,2,5,2,5,2,2,2,2,1,1,2,3,2,2,0,0.0,neutral or dissatisfied +21178,36661,Female,Loyal Customer,66,Personal Travel,Eco,1249,1,5,1,2,5,4,4,1,1,1,1,5,1,3,4,46.0,neutral or dissatisfied +21179,73781,Female,Loyal Customer,21,Personal Travel,Eco,192,3,1,3,4,2,3,2,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +21180,2927,Female,Loyal Customer,60,Business travel,Business,806,3,3,3,3,2,5,4,4,4,4,4,5,4,3,0,0.0,satisfied +21181,24261,Female,Loyal Customer,28,Personal Travel,Eco,302,3,5,3,5,2,3,2,2,3,5,4,1,5,2,0,0.0,neutral or dissatisfied +21182,102423,Female,Loyal Customer,34,Personal Travel,Eco,236,2,4,0,3,1,0,1,1,4,5,5,4,4,1,57,46.0,neutral or dissatisfied +21183,81255,Female,disloyal Customer,27,Business travel,Business,1020,3,3,3,3,2,3,2,2,3,2,4,5,4,2,0,10.0,neutral or dissatisfied +21184,64174,Female,Loyal Customer,32,Business travel,Business,3321,5,5,5,5,5,5,5,5,4,5,4,4,5,5,42,27.0,satisfied +21185,80466,Female,disloyal Customer,26,Business travel,Eco,1299,1,1,1,4,3,1,5,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +21186,113722,Female,Loyal Customer,45,Personal Travel,Eco,236,3,3,3,3,1,4,4,4,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +21187,23302,Male,Loyal Customer,52,Business travel,Business,2053,4,4,4,4,2,1,5,4,4,4,4,4,4,2,28,20.0,satisfied +21188,38651,Male,Loyal Customer,50,Business travel,Business,2588,4,4,4,4,2,2,3,4,4,4,4,1,4,2,2,9.0,neutral or dissatisfied +21189,108259,Female,Loyal Customer,36,Business travel,Eco,495,5,1,1,1,5,5,5,5,5,3,2,5,4,5,69,90.0,satisfied +21190,22382,Female,disloyal Customer,23,Business travel,Eco,238,3,1,2,3,5,2,5,5,1,4,2,4,3,5,0,7.0,neutral or dissatisfied +21191,106976,Male,Loyal Customer,42,Business travel,Business,572,2,2,2,2,1,2,3,2,2,2,2,3,2,2,0,0.0,satisfied +21192,56490,Female,Loyal Customer,56,Business travel,Business,3396,3,3,1,3,5,5,5,3,3,4,3,4,3,4,40,37.0,satisfied +21193,48252,Male,Loyal Customer,57,Personal Travel,Eco,391,2,5,2,1,5,2,4,5,3,5,4,5,4,5,74,66.0,neutral or dissatisfied +21194,53157,Female,Loyal Customer,56,Business travel,Business,589,1,1,4,1,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21195,93717,Female,Loyal Customer,15,Business travel,Business,2565,4,4,4,4,3,4,3,3,3,3,4,4,4,3,0,0.0,satisfied +21196,6926,Female,Loyal Customer,45,Business travel,Business,2187,3,3,3,3,3,5,4,4,4,4,4,3,4,3,16,13.0,satisfied +21197,61655,Male,Loyal Customer,32,Business travel,Business,1635,2,2,2,2,3,3,3,3,5,3,5,5,4,3,21,3.0,satisfied +21198,112238,Female,Loyal Customer,40,Business travel,Business,1703,5,5,5,5,4,5,4,5,5,5,5,4,5,4,0,1.0,satisfied +21199,66840,Male,disloyal Customer,36,Business travel,Eco,331,1,0,1,1,4,1,4,4,1,5,2,3,4,4,16,10.0,neutral or dissatisfied +21200,97909,Male,disloyal Customer,47,Business travel,Business,793,1,1,1,5,5,1,5,5,5,4,5,4,4,5,69,61.0,neutral or dissatisfied +21201,45867,Female,disloyal Customer,38,Business travel,Eco,913,4,4,4,1,2,4,2,2,2,5,5,1,2,2,36,13.0,neutral or dissatisfied +21202,70677,Female,Loyal Customer,27,Business travel,Eco,447,5,2,2,2,5,5,5,5,2,2,1,1,5,5,0,0.0,satisfied +21203,6340,Female,disloyal Customer,39,Business travel,Business,296,5,5,5,1,5,5,5,5,5,4,5,4,4,5,31,65.0,satisfied +21204,1558,Male,Loyal Customer,40,Personal Travel,Eco Plus,862,3,3,3,3,5,3,5,5,4,5,2,1,2,5,24,4.0,neutral or dissatisfied +21205,127490,Female,Loyal Customer,10,Personal Travel,Eco,2075,2,4,2,1,4,2,4,4,4,2,3,3,2,4,9,13.0,neutral or dissatisfied +21206,49785,Male,Loyal Customer,37,Business travel,Business,2521,1,1,1,1,1,3,2,5,5,5,5,2,5,5,36,30.0,satisfied +21207,70314,Female,Loyal Customer,39,Business travel,Business,1501,4,4,4,4,3,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21208,43481,Female,disloyal Customer,20,Business travel,Eco,524,4,4,4,4,3,4,3,3,1,1,3,3,3,3,20,10.0,neutral or dissatisfied +21209,41320,Male,Loyal Customer,39,Personal Travel,Eco,802,4,5,4,2,2,4,2,2,4,3,4,4,5,2,28,35.0,neutral or dissatisfied +21210,88522,Male,Loyal Customer,14,Personal Travel,Eco,404,2,3,2,1,1,2,1,1,4,4,4,4,1,1,2,21.0,neutral or dissatisfied +21211,39921,Male,Loyal Customer,34,Business travel,Business,1087,3,3,3,3,4,1,4,2,2,2,2,5,2,5,0,0.0,satisfied +21212,96636,Male,Loyal Customer,53,Business travel,Business,937,4,4,4,4,5,5,4,4,4,4,4,4,4,4,1,0.0,satisfied +21213,26014,Male,Loyal Customer,44,Business travel,Eco,425,2,1,1,1,2,2,2,2,4,1,3,3,4,2,0,3.0,neutral or dissatisfied +21214,112451,Female,Loyal Customer,48,Business travel,Eco,846,3,3,3,3,1,2,2,3,3,3,3,1,3,1,41,24.0,neutral or dissatisfied +21215,5350,Male,Loyal Customer,46,Business travel,Business,1874,4,4,4,4,3,5,5,4,4,5,4,4,4,5,0,8.0,satisfied +21216,6309,Female,disloyal Customer,20,Business travel,Business,315,5,2,5,5,5,5,5,5,5,2,5,3,4,5,0,14.0,satisfied +21217,42603,Female,Loyal Customer,19,Personal Travel,Eco,866,4,4,4,4,1,4,2,1,1,1,5,5,4,1,0,24.0,neutral or dissatisfied +21218,81625,Female,Loyal Customer,40,Business travel,Business,3319,1,1,1,1,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +21219,17363,Male,Loyal Customer,55,Personal Travel,Eco,563,2,2,2,4,4,2,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +21220,68103,Female,disloyal Customer,26,Business travel,Eco,813,1,1,1,1,2,1,5,2,4,4,2,3,5,2,5,0.0,neutral or dissatisfied +21221,50848,Female,Loyal Customer,64,Personal Travel,Eco,250,2,5,2,2,4,5,4,3,3,2,3,4,3,3,59,49.0,neutral or dissatisfied +21222,43096,Male,Loyal Customer,43,Personal Travel,Eco,173,4,4,4,2,4,4,4,4,2,4,3,2,3,4,0,0.0,neutral or dissatisfied +21223,5843,Female,Loyal Customer,46,Business travel,Business,1565,2,2,2,2,4,4,5,4,4,5,4,3,4,3,6,0.0,satisfied +21224,69888,Male,Loyal Customer,7,Personal Travel,Eco,2248,1,4,0,1,4,0,4,4,4,3,5,3,5,4,0,0.0,neutral or dissatisfied +21225,17549,Female,disloyal Customer,42,Business travel,Eco,970,3,2,2,4,2,2,4,2,4,5,4,1,3,2,0,0.0,neutral or dissatisfied +21226,39790,Male,Loyal Customer,60,Business travel,Business,272,2,3,3,3,3,3,4,2,2,2,2,1,2,2,0,15.0,neutral or dissatisfied +21227,42891,Female,Loyal Customer,47,Business travel,Eco,368,4,1,1,1,2,4,3,4,4,4,4,3,4,2,0,0.0,satisfied +21228,78774,Male,Loyal Customer,18,Business travel,Business,432,2,1,1,1,2,2,2,2,3,1,3,4,4,2,0,0.0,neutral or dissatisfied +21229,80277,Female,Loyal Customer,58,Business travel,Business,2488,1,1,1,1,5,4,4,4,5,4,4,4,5,4,241,242.0,satisfied +21230,118430,Male,Loyal Customer,48,Business travel,Business,1962,4,4,4,4,3,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +21231,98053,Male,disloyal Customer,55,Business travel,Eco,251,3,3,3,3,5,3,1,5,1,2,4,2,3,5,22,13.0,neutral or dissatisfied +21232,101745,Male,Loyal Customer,17,Business travel,Business,1590,3,3,3,3,5,5,5,5,5,4,5,3,5,5,78,77.0,satisfied +21233,103274,Male,Loyal Customer,16,Personal Travel,Eco,888,2,5,2,2,4,2,4,4,2,3,2,4,1,4,0,0.0,neutral or dissatisfied +21234,4118,Male,disloyal Customer,35,Business travel,Business,431,3,3,3,5,5,3,5,5,4,3,4,3,5,5,0,32.0,neutral or dissatisfied +21235,50368,Male,disloyal Customer,16,Business travel,Eco,372,0,0,0,3,3,0,3,3,4,4,1,4,1,3,0,0.0,satisfied +21236,9593,Female,Loyal Customer,16,Personal Travel,Eco,228,1,4,1,5,2,1,2,2,3,2,4,5,5,2,14,3.0,neutral or dissatisfied +21237,81572,Male,Loyal Customer,48,Personal Travel,Eco,936,2,1,1,2,4,1,2,4,4,1,2,2,3,4,28,36.0,neutral or dissatisfied +21238,2299,Female,disloyal Customer,20,Business travel,Eco,672,4,4,4,4,4,4,5,4,2,5,4,2,3,4,0,0.0,neutral or dissatisfied +21239,43696,Female,Loyal Customer,41,Business travel,Business,1511,3,3,3,3,5,2,1,4,4,4,4,2,4,5,1,0.0,satisfied +21240,4070,Female,disloyal Customer,22,Business travel,Eco Plus,425,1,1,1,3,5,1,5,5,4,1,4,4,4,5,0,0.0,neutral or dissatisfied +21241,8808,Male,disloyal Customer,20,Business travel,Eco,552,3,3,3,4,1,3,1,1,1,1,3,2,3,1,0,32.0,neutral or dissatisfied +21242,74407,Male,Loyal Customer,23,Business travel,Business,1602,4,4,4,4,3,3,3,3,4,4,5,4,5,3,0,1.0,satisfied +21243,103172,Male,Loyal Customer,20,Personal Travel,Eco,272,0,4,0,5,4,0,4,4,4,3,4,4,5,4,6,3.0,satisfied +21244,63901,Male,Loyal Customer,68,Business travel,Eco,1172,4,5,5,5,4,4,4,4,1,3,4,2,4,4,26,14.0,neutral or dissatisfied +21245,20575,Male,Loyal Customer,65,Personal Travel,Eco,533,4,4,4,3,2,4,2,2,1,4,4,1,4,2,0,0.0,neutral or dissatisfied +21246,71935,Female,Loyal Customer,61,Business travel,Eco Plus,244,2,3,3,3,5,3,3,3,3,2,3,2,3,2,104,87.0,neutral or dissatisfied +21247,122570,Female,Loyal Customer,44,Business travel,Business,728,4,4,4,4,5,4,5,5,5,4,5,5,5,3,0,0.0,satisfied +21248,109856,Female,disloyal Customer,27,Business travel,Eco,1165,2,2,2,3,1,2,1,1,2,1,4,2,4,1,16,10.0,neutral or dissatisfied +21249,55362,Male,Loyal Customer,40,Business travel,Business,413,1,1,1,1,3,5,5,3,3,4,3,5,3,5,16,25.0,satisfied +21250,120351,Female,Loyal Customer,7,Personal Travel,Business,337,2,4,2,3,1,2,1,1,4,2,5,3,4,1,0,1.0,neutral or dissatisfied +21251,106853,Male,Loyal Customer,45,Business travel,Business,3554,2,2,5,2,5,5,4,4,4,4,4,4,4,3,5,0.0,satisfied +21252,110224,Male,Loyal Customer,41,Business travel,Eco,1041,2,5,2,2,2,2,2,2,1,3,3,4,3,2,3,2.0,neutral or dissatisfied +21253,130,Female,Loyal Customer,39,Business travel,Business,1868,1,1,1,1,4,5,4,4,4,4,4,3,4,4,54,49.0,satisfied +21254,5127,Male,disloyal Customer,27,Business travel,Eco Plus,303,4,4,4,3,2,4,2,2,5,2,5,3,1,2,0,0.0,neutral or dissatisfied +21255,92926,Female,disloyal Customer,27,Business travel,Business,151,0,0,0,1,4,0,4,4,3,2,4,5,5,4,0,0.0,satisfied +21256,72483,Male,Loyal Customer,50,Business travel,Business,3592,3,4,3,3,5,5,4,2,2,2,2,3,2,3,39,34.0,satisfied +21257,101575,Female,Loyal Customer,54,Business travel,Business,1099,4,4,4,4,4,4,4,5,5,5,5,5,5,3,11,11.0,satisfied +21258,99884,Male,Loyal Customer,30,Business travel,Business,738,1,1,1,1,4,4,4,4,5,3,5,5,5,4,10,22.0,satisfied +21259,49649,Female,Loyal Customer,33,Business travel,Eco,304,0,0,0,2,1,0,1,1,3,4,3,3,4,1,32,22.0,satisfied +21260,38626,Female,disloyal Customer,24,Business travel,Eco,987,4,5,5,4,5,4,5,5,2,2,4,3,4,5,5,0.0,satisfied +21261,115067,Female,disloyal Customer,25,Business travel,Business,337,3,0,2,4,3,2,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +21262,49123,Female,disloyal Customer,33,Business travel,Eco,86,4,3,4,3,3,4,3,3,2,5,2,5,5,3,23,17.0,neutral or dissatisfied +21263,125831,Male,disloyal Customer,25,Business travel,Business,992,4,0,4,2,1,4,1,1,4,2,5,4,5,1,6,24.0,satisfied +21264,15205,Male,disloyal Customer,9,Business travel,Eco,529,2,4,2,1,3,2,2,3,5,3,4,5,5,3,0,0.0,neutral or dissatisfied +21265,119695,Female,Loyal Customer,46,Business travel,Business,1303,4,4,3,4,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +21266,77514,Female,disloyal Customer,23,Business travel,Eco,1521,1,2,2,2,4,1,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +21267,42030,Male,Loyal Customer,37,Business travel,Eco,116,2,4,4,4,2,2,2,2,3,2,4,4,3,2,0,0.0,neutral or dissatisfied +21268,86906,Female,Loyal Customer,47,Business travel,Business,341,2,2,2,2,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +21269,66945,Male,Loyal Customer,51,Business travel,Business,964,5,5,2,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +21270,19239,Male,Loyal Customer,22,Business travel,Business,3754,3,3,3,3,5,5,5,5,2,3,5,5,2,5,0,0.0,satisfied +21271,122451,Female,disloyal Customer,19,Business travel,Business,808,5,5,5,4,1,5,1,1,5,2,5,4,5,1,81,66.0,satisfied +21272,118364,Female,Loyal Customer,52,Business travel,Eco Plus,602,4,1,5,5,3,4,4,4,4,4,4,1,4,1,21,8.0,neutral or dissatisfied +21273,22586,Male,Loyal Customer,59,Business travel,Eco,300,5,5,5,5,5,5,5,5,4,4,4,2,3,5,0,0.0,satisfied +21274,122245,Female,Loyal Customer,36,Business travel,Business,144,2,3,3,3,2,3,3,2,2,1,2,2,2,4,0,0.0,neutral or dissatisfied +21275,109882,Male,disloyal Customer,10,Business travel,Business,1011,4,3,4,1,5,4,3,5,4,3,5,5,4,5,0,0.0,satisfied +21276,5848,Male,Loyal Customer,38,Business travel,Business,1020,4,4,4,4,3,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +21277,77106,Female,disloyal Customer,44,Business travel,Business,1481,2,3,3,3,4,2,4,4,3,4,5,5,5,4,0,0.0,neutral or dissatisfied +21278,62270,Female,Loyal Customer,57,Business travel,Business,2565,1,1,1,1,2,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +21279,54046,Female,Loyal Customer,32,Business travel,Business,1416,4,4,4,4,5,5,5,5,3,5,1,5,3,5,0,0.0,satisfied +21280,4621,Male,Loyal Customer,43,Personal Travel,Eco,719,3,4,3,3,4,3,4,4,1,5,3,4,3,4,13,18.0,neutral or dissatisfied +21281,114112,Female,Loyal Customer,47,Business travel,Business,2816,3,3,3,3,2,5,4,4,4,4,4,5,4,4,4,0.0,satisfied +21282,69466,Male,Loyal Customer,66,Personal Travel,Eco,1096,1,2,1,3,4,1,4,4,2,3,4,4,3,4,7,31.0,neutral or dissatisfied +21283,104598,Male,Loyal Customer,58,Personal Travel,Eco,369,3,1,3,4,1,3,1,1,1,2,4,2,3,1,0,0.0,neutral or dissatisfied +21284,21528,Female,Loyal Customer,57,Personal Travel,Eco,164,2,4,2,5,3,5,5,3,3,2,3,5,3,3,0,0.0,neutral or dissatisfied +21285,22003,Male,Loyal Customer,15,Personal Travel,Eco,448,1,5,1,3,3,1,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +21286,46104,Female,Loyal Customer,57,Business travel,Business,3545,2,2,5,2,1,1,3,3,3,4,3,5,3,4,0,0.0,satisfied +21287,95944,Female,disloyal Customer,35,Business travel,Business,1235,2,2,2,3,4,2,4,4,3,2,4,4,4,4,127,117.0,neutral or dissatisfied +21288,8267,Male,disloyal Customer,27,Personal Travel,Eco,335,2,5,2,2,4,2,4,4,4,3,5,3,4,4,0,0.0,neutral or dissatisfied +21289,71312,Female,Loyal Customer,25,Business travel,Business,1514,3,3,3,3,5,5,5,5,4,2,4,5,4,5,0,4.0,satisfied +21290,123482,Male,disloyal Customer,25,Business travel,Eco,1277,4,4,4,1,1,4,1,1,5,5,4,3,5,1,2,0.0,satisfied +21291,71871,Female,Loyal Customer,32,Personal Travel,Eco,1744,3,5,2,3,1,2,1,1,3,2,3,5,4,1,0,0.0,neutral or dissatisfied +21292,83276,Female,Loyal Customer,61,Personal Travel,Eco,1979,2,4,2,3,3,4,5,2,2,2,2,3,2,2,7,0.0,neutral or dissatisfied +21293,37527,Female,Loyal Customer,31,Business travel,Business,950,2,2,2,2,5,5,5,5,1,1,1,4,2,5,0,0.0,satisfied +21294,20146,Male,Loyal Customer,51,Business travel,Eco,403,1,1,4,1,1,1,1,1,2,4,3,4,3,1,86,84.0,neutral or dissatisfied +21295,57301,Male,Loyal Customer,39,Business travel,Business,3652,0,0,0,2,4,4,5,2,2,2,2,4,2,4,0,11.0,satisfied +21296,21443,Female,Loyal Customer,41,Business travel,Eco,377,4,5,3,3,4,4,4,4,1,5,1,2,2,4,0,0.0,satisfied +21297,52771,Female,Loyal Customer,32,Business travel,Eco,1874,4,4,4,4,4,4,4,4,4,3,5,1,5,4,0,0.0,satisfied +21298,38058,Male,disloyal Customer,25,Business travel,Eco,1249,4,3,3,4,5,3,5,5,2,5,5,1,2,5,6,0.0,neutral or dissatisfied +21299,115082,Male,disloyal Customer,41,Business travel,Business,390,4,4,4,1,1,4,1,1,3,5,5,5,5,1,8,4.0,neutral or dissatisfied +21300,74530,Female,Loyal Customer,34,Business travel,Business,1171,3,3,3,3,5,5,4,5,5,5,5,3,5,5,4,0.0,satisfied +21301,87107,Female,Loyal Customer,59,Personal Travel,Eco,594,2,4,1,1,1,1,1,2,2,1,2,2,2,4,17,13.0,neutral or dissatisfied +21302,50738,Female,Loyal Customer,7,Personal Travel,Eco,89,1,5,1,4,4,1,4,4,4,2,5,4,5,4,0,0.0,neutral or dissatisfied +21303,50304,Female,disloyal Customer,24,Business travel,Eco,109,2,3,1,4,5,1,3,5,2,3,4,3,3,5,0,0.0,neutral or dissatisfied +21304,6024,Female,Loyal Customer,45,Business travel,Business,925,3,3,3,3,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +21305,117211,Male,Loyal Customer,54,Personal Travel,Eco,304,1,4,1,4,5,1,5,5,5,2,4,5,5,5,10,11.0,neutral or dissatisfied +21306,19427,Female,Loyal Customer,29,Business travel,Business,645,1,2,2,2,1,1,1,1,2,5,3,4,3,1,30,47.0,neutral or dissatisfied +21307,118581,Male,Loyal Customer,48,Business travel,Eco,325,2,4,4,4,2,2,2,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +21308,120372,Female,Loyal Customer,30,Business travel,Business,337,5,5,5,5,4,4,4,4,4,3,5,4,4,4,0,0.0,satisfied +21309,10359,Male,Loyal Customer,62,Business travel,Business,2322,2,2,2,2,4,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +21310,87522,Female,Loyal Customer,66,Personal Travel,Eco,373,2,4,2,4,1,4,4,4,4,2,4,2,4,5,0,0.0,neutral or dissatisfied +21311,112909,Male,Loyal Customer,38,Business travel,Eco,990,4,5,1,5,4,4,4,4,5,1,5,1,5,4,28,22.0,satisfied +21312,17481,Female,Loyal Customer,55,Business travel,Business,241,3,3,3,3,4,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +21313,117943,Female,Loyal Customer,52,Business travel,Business,3011,5,5,5,5,4,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21314,16735,Male,Loyal Customer,52,Personal Travel,Eco,1167,2,5,1,3,4,1,4,4,3,4,3,2,5,4,0,0.0,neutral or dissatisfied +21315,39752,Male,Loyal Customer,35,Business travel,Business,521,5,5,1,5,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +21316,106333,Male,Loyal Customer,70,Personal Travel,Eco,825,2,5,2,2,4,2,4,4,3,4,4,5,4,4,0,1.0,neutral or dissatisfied +21317,84559,Male,Loyal Customer,47,Personal Travel,Eco,2504,1,4,1,1,1,1,1,1,3,1,5,1,5,1,1,0.0,neutral or dissatisfied +21318,25052,Female,disloyal Customer,41,Business travel,Eco,594,2,4,2,3,1,2,1,1,2,2,5,4,1,1,0,5.0,neutral or dissatisfied +21319,114055,Female,Loyal Customer,31,Business travel,Eco,2139,1,3,3,3,1,1,1,1,4,2,3,1,4,1,1,0.0,neutral or dissatisfied +21320,109347,Female,Loyal Customer,62,Personal Travel,Eco Plus,1072,2,4,3,2,2,4,5,1,1,3,1,4,1,5,100,88.0,neutral or dissatisfied +21321,83740,Male,disloyal Customer,38,Business travel,Business,1183,4,4,4,3,2,4,2,2,5,4,5,4,5,2,29,13.0,satisfied +21322,101141,Female,Loyal Customer,50,Business travel,Business,1090,3,3,3,3,2,5,5,4,4,4,4,5,4,3,109,97.0,satisfied +21323,121621,Female,Loyal Customer,30,Personal Travel,Eco,936,3,4,2,4,4,2,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +21324,98478,Male,Loyal Customer,45,Business travel,Business,3039,5,5,5,5,5,5,5,4,4,4,4,5,4,4,8,0.0,satisfied +21325,4870,Male,Loyal Customer,24,Personal Travel,Eco,500,2,3,2,4,4,2,4,4,2,5,3,3,3,4,7,2.0,neutral or dissatisfied +21326,82945,Male,Loyal Customer,57,Business travel,Business,983,3,3,3,3,4,4,4,4,4,5,4,3,4,4,1,45.0,satisfied +21327,17502,Female,Loyal Customer,36,Business travel,Eco,352,1,4,4,4,1,1,1,1,2,3,4,2,3,1,0,0.0,neutral or dissatisfied +21328,46233,Female,Loyal Customer,24,Business travel,Eco,679,3,2,5,2,3,3,2,3,4,3,3,2,4,3,32,11.0,neutral or dissatisfied +21329,50648,Female,Loyal Customer,16,Personal Travel,Eco,373,3,1,3,2,3,3,3,3,2,3,2,2,2,3,58,124.0,neutral or dissatisfied +21330,112177,Female,Loyal Customer,60,Personal Travel,Eco,895,5,5,5,2,4,4,2,1,1,5,1,3,1,3,0,0.0,satisfied +21331,65100,Female,Loyal Customer,26,Personal Travel,Eco,190,3,4,0,1,5,0,5,5,4,2,4,3,5,5,6,0.0,neutral or dissatisfied +21332,44718,Male,Loyal Customer,53,Personal Travel,Eco,160,1,5,0,4,5,0,5,5,3,4,5,5,5,5,0,0.0,neutral or dissatisfied +21333,62131,Female,Loyal Customer,26,Business travel,Eco,2454,1,1,0,3,5,0,5,5,2,4,2,2,4,5,0,0.0,neutral or dissatisfied +21334,25599,Female,Loyal Customer,7,Personal Travel,Eco,696,1,4,1,3,1,1,2,1,3,4,4,4,4,1,3,0.0,neutral or dissatisfied +21335,79312,Male,Loyal Customer,27,Personal Travel,Eco,2248,2,4,1,2,3,1,3,3,5,5,5,3,4,3,0,13.0,neutral or dissatisfied +21336,41875,Male,Loyal Customer,26,Business travel,Business,925,4,4,4,4,4,4,4,4,5,4,2,4,2,4,0,4.0,satisfied +21337,95646,Female,Loyal Customer,48,Business travel,Business,928,2,2,1,2,5,4,5,4,4,4,4,5,4,3,26,23.0,satisfied +21338,126229,Female,Loyal Customer,47,Business travel,Eco,107,5,3,3,3,2,5,4,5,5,5,5,1,5,1,0,0.0,satisfied +21339,123892,Male,Loyal Customer,47,Personal Travel,Eco,546,1,5,1,4,4,1,4,4,5,2,2,4,4,4,0,5.0,neutral or dissatisfied +21340,409,Male,Loyal Customer,48,Business travel,Business,229,1,5,5,5,4,3,4,1,1,1,1,2,1,2,39,45.0,neutral or dissatisfied +21341,28378,Female,disloyal Customer,44,Business travel,Eco,763,3,3,3,3,3,3,2,3,2,1,3,1,4,3,0,0.0,neutral or dissatisfied +21342,126143,Male,Loyal Customer,28,Business travel,Business,590,2,2,2,2,5,4,5,5,4,3,5,4,5,5,1,0.0,satisfied +21343,59033,Male,Loyal Customer,32,Business travel,Business,1846,4,4,4,4,5,5,5,5,4,4,4,3,5,5,3,42.0,satisfied +21344,117709,Male,disloyal Customer,29,Business travel,Business,1009,2,2,2,2,1,2,1,1,3,5,5,4,5,1,7,9.0,neutral or dissatisfied +21345,39953,Female,Loyal Customer,33,Personal Travel,Eco,1195,4,2,4,3,3,4,5,3,2,4,4,1,4,3,48,34.0,neutral or dissatisfied +21346,42694,Female,Loyal Customer,49,Personal Travel,Eco,604,2,5,2,4,4,4,5,1,1,2,1,4,1,4,7,0.0,neutral or dissatisfied +21347,31620,Male,Loyal Customer,49,Personal Travel,Business,862,3,5,3,1,3,4,4,2,2,3,1,4,2,5,0,0.0,neutral or dissatisfied +21348,6560,Male,Loyal Customer,40,Business travel,Business,2992,1,1,3,1,3,3,3,5,2,4,4,3,4,3,153,151.0,satisfied +21349,87582,Female,Loyal Customer,65,Personal Travel,Eco,432,2,4,4,3,1,3,3,4,4,4,3,4,4,5,0,2.0,neutral or dissatisfied +21350,29216,Male,Loyal Customer,58,Business travel,Business,834,2,2,2,2,2,5,4,4,4,4,4,4,4,5,0,2.0,satisfied +21351,85229,Female,Loyal Customer,37,Business travel,Business,3119,0,1,1,4,4,2,4,1,1,1,1,5,1,1,13,4.0,satisfied +21352,90736,Male,Loyal Customer,49,Business travel,Business,1944,2,2,2,2,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +21353,91091,Female,Loyal Customer,63,Personal Travel,Eco,594,1,3,1,3,5,3,4,1,1,1,4,1,1,3,18,14.0,neutral or dissatisfied +21354,5192,Male,Loyal Customer,43,Business travel,Business,383,5,3,5,5,4,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +21355,14548,Female,Loyal Customer,56,Personal Travel,Eco,362,1,5,1,3,2,5,4,1,1,1,1,4,1,5,0,0.0,neutral or dissatisfied +21356,39904,Female,disloyal Customer,27,Business travel,Eco Plus,272,2,2,2,3,2,2,2,2,4,3,3,1,3,2,9,10.0,neutral or dissatisfied +21357,65118,Female,Loyal Customer,31,Personal Travel,Eco,190,2,3,2,4,4,2,4,4,1,5,3,2,4,4,0,7.0,neutral or dissatisfied +21358,77332,Female,Loyal Customer,50,Business travel,Business,626,4,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +21359,29056,Female,Loyal Customer,64,Personal Travel,Eco,671,2,3,2,4,1,3,3,4,4,2,4,1,4,4,0,0.0,neutral or dissatisfied +21360,41911,Male,Loyal Customer,55,Business travel,Business,3860,5,5,5,5,4,3,2,4,4,4,5,3,4,4,0,0.0,satisfied +21361,31788,Male,disloyal Customer,38,Business travel,Eco,2677,5,5,5,3,5,3,3,3,2,5,4,3,5,3,0,19.0,satisfied +21362,55974,Female,Loyal Customer,69,Personal Travel,Eco,1620,3,5,3,1,2,3,4,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +21363,60916,Male,disloyal Customer,28,Business travel,Business,888,4,4,4,3,4,4,4,2,4,3,3,4,3,4,241,218.0,neutral or dissatisfied +21364,15100,Female,Loyal Customer,17,Personal Travel,Eco,322,1,3,1,4,5,1,5,5,4,3,5,3,3,5,38,29.0,neutral or dissatisfied +21365,115146,Male,Loyal Customer,44,Business travel,Business,2849,4,4,4,4,5,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +21366,16984,Male,Loyal Customer,28,Business travel,Business,610,4,4,4,4,4,4,4,4,2,4,5,4,1,4,0,0.0,satisfied +21367,86965,Male,Loyal Customer,29,Business travel,Business,1543,4,1,5,5,4,4,4,4,3,2,2,1,2,4,2,3.0,neutral or dissatisfied +21368,58276,Female,disloyal Customer,25,Business travel,Eco,678,4,4,4,3,4,4,4,4,2,4,4,3,4,4,0,12.0,neutral or dissatisfied +21369,76033,Female,Loyal Customer,48,Business travel,Business,237,0,0,0,1,2,5,4,2,2,2,1,3,2,4,0,0.0,satisfied +21370,47327,Male,disloyal Customer,33,Business travel,Eco,599,2,0,2,1,4,2,5,4,3,1,1,3,2,4,0,0.0,neutral or dissatisfied +21371,34171,Male,disloyal Customer,29,Business travel,Business,1189,3,3,3,3,4,3,3,4,2,4,3,1,3,4,91,90.0,neutral or dissatisfied +21372,49414,Male,Loyal Customer,35,Business travel,Eco,373,5,4,5,4,5,5,5,5,4,2,5,3,2,5,0,0.0,satisfied +21373,55135,Female,Loyal Customer,44,Personal Travel,Eco,1303,3,5,3,4,5,4,4,2,2,3,2,4,2,4,40,27.0,neutral or dissatisfied +21374,7483,Male,disloyal Customer,25,Business travel,Business,925,5,0,5,4,2,5,2,2,4,3,4,5,4,2,0,0.0,satisfied +21375,81644,Male,disloyal Customer,23,Business travel,Eco,907,0,0,0,3,5,0,5,5,5,4,5,4,4,5,42,33.0,satisfied +21376,70420,Female,Loyal Customer,51,Business travel,Business,2683,1,3,3,3,5,4,4,4,4,4,1,4,4,3,0,0.0,neutral or dissatisfied +21377,4282,Female,Loyal Customer,49,Business travel,Business,102,1,1,1,1,4,1,1,4,4,4,3,1,4,1,0,0.0,satisfied +21378,83017,Female,Loyal Customer,39,Business travel,Business,983,2,2,2,2,3,5,4,4,4,4,4,4,4,5,105,115.0,satisfied +21379,113703,Female,Loyal Customer,50,Personal Travel,Eco,407,2,5,4,2,1,1,4,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +21380,106625,Male,Loyal Customer,51,Business travel,Business,2195,4,1,4,4,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +21381,100898,Male,disloyal Customer,37,Business travel,Eco,377,2,2,2,3,4,2,4,4,4,5,4,3,4,4,63,61.0,neutral or dissatisfied +21382,325,Female,disloyal Customer,25,Business travel,Business,821,3,1,3,3,2,3,2,2,2,2,4,4,4,2,19,3.0,neutral or dissatisfied +21383,52805,Female,Loyal Customer,21,Business travel,Business,2402,2,2,2,2,4,4,4,4,3,3,5,5,4,4,0,3.0,satisfied +21384,11840,Female,Loyal Customer,39,Business travel,Business,1021,1,1,1,1,4,4,4,4,4,5,4,4,4,5,0,0.0,satisfied +21385,39378,Female,Loyal Customer,54,Business travel,Business,3271,4,4,4,4,2,1,2,3,3,4,3,1,3,2,0,0.0,satisfied +21386,71498,Female,Loyal Customer,69,Personal Travel,Business,1197,4,2,4,4,2,4,3,1,1,4,1,4,1,3,18,9.0,neutral or dissatisfied +21387,16228,Female,disloyal Customer,27,Business travel,Eco,266,2,0,2,2,1,2,1,1,4,2,1,1,5,1,0,0.0,neutral or dissatisfied +21388,64499,Female,Loyal Customer,42,Business travel,Business,3943,1,3,3,3,2,3,4,2,2,2,1,2,2,2,0,0.0,neutral or dissatisfied +21389,120340,Female,disloyal Customer,50,Business travel,Business,449,1,1,1,5,5,1,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +21390,9389,Female,Loyal Customer,43,Business travel,Eco Plus,384,1,1,1,1,4,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +21391,26037,Female,Loyal Customer,35,Business travel,Eco,432,5,2,2,2,5,5,5,5,2,1,3,5,4,5,100,95.0,satisfied +21392,8879,Male,Loyal Customer,46,Business travel,Eco,139,3,5,5,5,4,3,4,4,1,5,4,2,3,4,41,44.0,neutral or dissatisfied +21393,20838,Female,Loyal Customer,34,Business travel,Business,3469,3,3,5,3,4,3,5,5,5,4,5,4,5,2,0,0.0,satisfied +21394,34866,Female,disloyal Customer,23,Business travel,Eco,705,4,4,4,1,4,4,4,4,3,4,3,2,2,4,0,0.0,satisfied +21395,127477,Female,Loyal Customer,46,Business travel,Eco,2075,4,1,1,1,1,3,4,4,4,4,4,2,4,3,2,0.0,neutral or dissatisfied +21396,116142,Male,Loyal Customer,19,Personal Travel,Eco,362,2,4,5,5,4,5,1,4,5,3,5,3,4,4,47,47.0,neutral or dissatisfied +21397,99407,Male,Loyal Customer,48,Business travel,Eco,337,2,1,1,1,2,2,2,2,3,2,3,4,3,2,0,6.0,neutral or dissatisfied +21398,66155,Male,Loyal Customer,67,Personal Travel,Business,550,2,3,2,4,3,2,5,2,2,2,2,2,2,5,11,6.0,neutral or dissatisfied +21399,32705,Male,Loyal Customer,56,Business travel,Business,2236,4,4,4,4,3,4,4,2,2,2,4,3,2,2,0,0.0,neutral or dissatisfied +21400,121605,Female,Loyal Customer,32,Personal Travel,Eco,936,4,5,4,3,2,4,2,2,4,3,5,5,4,2,25,24.0,neutral or dissatisfied +21401,5709,Female,Loyal Customer,33,Personal Travel,Eco,234,3,4,0,5,1,0,3,1,3,5,4,5,4,1,10,36.0,neutral or dissatisfied +21402,70241,Female,Loyal Customer,39,Business travel,Business,1592,5,5,5,5,5,3,5,5,5,5,5,4,5,4,0,0.0,satisfied +21403,1093,Female,Loyal Customer,57,Personal Travel,Eco,482,3,5,3,5,3,1,3,4,4,3,4,2,4,4,1,0.0,neutral or dissatisfied +21404,25879,Female,Loyal Customer,34,Business travel,Eco,907,4,2,5,2,4,4,4,4,1,5,1,1,2,4,0,0.0,satisfied +21405,19619,Male,Loyal Customer,55,Personal Travel,Eco,416,2,2,2,3,1,2,1,1,2,2,3,2,4,1,4,3.0,neutral or dissatisfied +21406,94367,Female,Loyal Customer,40,Business travel,Business,3579,2,2,2,2,2,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +21407,120209,Male,Loyal Customer,60,Business travel,Eco,1430,2,2,2,2,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +21408,76695,Female,Loyal Customer,26,Personal Travel,Eco,547,2,3,2,4,1,2,1,1,2,5,4,2,3,1,0,0.0,neutral or dissatisfied +21409,23163,Female,Loyal Customer,14,Personal Travel,Eco,300,3,3,3,3,2,3,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +21410,6786,Female,Loyal Customer,31,Business travel,Eco,137,1,2,2,2,1,1,1,1,1,4,2,3,2,1,0,0.0,neutral or dissatisfied +21411,84141,Male,Loyal Customer,22,Personal Travel,Eco,782,3,1,3,4,3,3,3,3,4,3,3,3,3,3,3,0.0,neutral or dissatisfied +21412,36867,Male,Loyal Customer,57,Personal Travel,Eco,273,4,1,4,4,3,4,3,3,2,2,4,4,4,3,0,0.0,neutral or dissatisfied +21413,106578,Male,Loyal Customer,40,Personal Travel,Eco,1506,4,2,4,4,2,4,2,2,2,5,3,4,4,2,0,0.0,neutral or dissatisfied +21414,9994,Female,Loyal Customer,11,Personal Travel,Eco,508,2,5,2,5,3,2,3,3,4,4,4,5,4,3,0,4.0,neutral or dissatisfied +21415,89268,Female,disloyal Customer,29,Business travel,Business,453,3,3,3,3,1,3,1,1,4,4,4,3,5,1,0,0.0,neutral or dissatisfied +21416,11632,Female,Loyal Customer,41,Business travel,Business,835,3,3,3,3,2,5,5,3,3,4,3,3,3,3,22,14.0,satisfied +21417,41469,Female,Loyal Customer,33,Business travel,Business,3848,2,2,2,2,3,5,5,4,4,4,4,5,4,1,0,1.0,satisfied +21418,116066,Male,Loyal Customer,9,Personal Travel,Eco,358,2,1,5,3,2,5,2,2,2,3,3,1,4,2,8,2.0,neutral or dissatisfied +21419,60320,Female,Loyal Customer,48,Business travel,Business,836,1,1,1,1,2,5,5,5,5,5,5,3,5,4,54,59.0,satisfied +21420,66073,Male,Loyal Customer,17,Personal Travel,Eco,1055,2,4,2,4,1,2,1,1,2,3,3,1,3,1,13,19.0,neutral or dissatisfied +21421,110379,Female,Loyal Customer,32,Business travel,Eco,919,2,3,3,3,2,2,2,2,1,4,4,1,3,2,0,0.0,neutral or dissatisfied +21422,110879,Male,Loyal Customer,58,Business travel,Business,1538,3,3,3,3,3,4,5,4,4,4,4,5,4,3,5,0.0,satisfied +21423,55394,Male,Loyal Customer,10,Business travel,Eco Plus,594,2,3,3,3,2,2,1,2,4,1,3,2,3,2,3,8.0,neutral or dissatisfied +21424,31182,Male,Loyal Customer,61,Personal Travel,Eco,1620,2,4,1,2,2,1,1,2,4,3,3,5,5,2,1,4.0,neutral or dissatisfied +21425,3217,Male,disloyal Customer,46,Business travel,Business,1187,4,5,5,1,5,4,5,5,5,5,5,5,4,5,0,0.0,neutral or dissatisfied +21426,547,Male,Loyal Customer,50,Business travel,Business,309,5,5,5,5,3,5,5,4,4,4,4,5,4,4,0,10.0,satisfied +21427,99552,Female,Loyal Customer,25,Business travel,Business,829,2,2,2,2,5,5,5,5,3,3,4,3,5,5,0,0.0,satisfied +21428,10201,Female,Loyal Customer,51,Business travel,Business,429,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +21429,106421,Male,Loyal Customer,39,Personal Travel,Eco,674,2,4,3,1,3,3,3,3,4,2,4,5,5,3,45,26.0,neutral or dissatisfied +21430,9550,Female,Loyal Customer,42,Business travel,Business,3632,1,1,1,1,5,5,5,5,5,5,4,5,4,5,189,153.0,satisfied +21431,25459,Female,Loyal Customer,28,Business travel,Eco Plus,669,2,4,5,5,2,2,2,2,4,4,4,3,4,2,2,0.0,neutral or dissatisfied +21432,49239,Male,Loyal Customer,31,Business travel,Business,3970,2,2,2,2,5,5,5,5,3,5,4,5,1,5,0,11.0,satisfied +21433,57116,Female,disloyal Customer,29,Business travel,Eco,1222,3,3,3,2,1,3,1,1,3,2,3,2,3,1,1,0.0,neutral or dissatisfied +21434,113671,Female,Loyal Customer,13,Personal Travel,Eco,236,1,4,0,5,4,0,4,4,5,4,4,5,4,4,18,22.0,neutral or dissatisfied +21435,73809,Female,Loyal Customer,18,Personal Travel,Eco Plus,192,3,5,3,3,2,3,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +21436,74632,Female,disloyal Customer,39,Business travel,Eco,771,3,3,3,1,5,3,1,5,3,3,1,3,4,5,0,0.0,neutral or dissatisfied +21437,92577,Male,Loyal Customer,80,Business travel,Eco Plus,592,5,3,3,3,5,5,5,5,3,5,3,5,2,5,0,0.0,satisfied +21438,33319,Male,disloyal Customer,23,Business travel,Eco,1028,2,2,2,4,1,2,1,1,4,1,4,2,5,1,0,0.0,neutral or dissatisfied +21439,37591,Male,disloyal Customer,72,Business travel,Eco,550,1,2,1,3,1,1,1,1,3,2,3,4,3,1,3,0.0,neutral or dissatisfied +21440,43817,Male,Loyal Customer,58,Business travel,Business,3375,4,5,5,5,1,2,3,4,4,4,4,4,4,2,0,0.0,neutral or dissatisfied +21441,22980,Male,Loyal Customer,39,Business travel,Business,417,3,3,3,3,1,5,3,3,3,4,3,5,3,1,0,10.0,satisfied +21442,49997,Female,Loyal Customer,44,Business travel,Eco,262,2,3,3,3,1,4,3,3,3,2,3,1,3,3,22,8.0,neutral or dissatisfied +21443,95988,Male,Loyal Customer,46,Business travel,Business,3655,2,2,2,2,4,4,4,3,3,3,3,5,3,3,1,0.0,satisfied +21444,120644,Female,Loyal Customer,36,Business travel,Business,280,1,1,1,1,4,5,4,5,5,5,5,5,5,5,3,0.0,satisfied +21445,91603,Male,Loyal Customer,42,Business travel,Business,1340,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +21446,86894,Female,Loyal Customer,42,Business travel,Business,3069,0,0,0,5,3,4,5,5,5,5,5,3,5,3,36,46.0,satisfied +21447,86782,Male,Loyal Customer,30,Business travel,Business,2236,1,1,3,1,4,4,4,4,3,2,4,4,5,4,29,31.0,satisfied +21448,23990,Male,Loyal Customer,46,Business travel,Business,427,3,3,3,3,1,3,1,4,4,4,4,2,4,2,25,26.0,satisfied +21449,83224,Female,Loyal Customer,28,Business travel,Business,1956,2,2,2,2,5,5,5,5,3,3,5,3,5,5,0,0.0,satisfied +21450,26572,Female,Loyal Customer,48,Business travel,Eco,581,5,5,5,5,4,1,3,5,5,5,5,1,5,1,0,0.0,satisfied +21451,120787,Male,Loyal Customer,43,Personal Travel,Eco,678,3,5,3,1,3,3,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +21452,121379,Male,Loyal Customer,21,Business travel,Business,2279,2,2,2,2,5,5,5,5,4,2,3,5,4,5,2,0.0,satisfied +21453,33021,Female,Loyal Customer,17,Personal Travel,Eco,101,5,5,5,5,4,5,4,4,5,1,5,2,2,4,0,0.0,satisfied +21454,72501,Male,Loyal Customer,31,Business travel,Business,3442,1,2,2,2,1,1,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +21455,84106,Male,Loyal Customer,12,Personal Travel,Business,2036,3,4,3,2,5,3,5,5,5,2,5,5,4,5,0,19.0,neutral or dissatisfied +21456,26817,Male,Loyal Customer,38,Business travel,Eco,224,5,4,4,4,5,5,5,5,1,5,1,5,5,5,0,9.0,satisfied +21457,41562,Female,disloyal Customer,22,Business travel,Eco,1064,5,5,5,2,4,5,4,4,4,1,2,2,4,4,0,0.0,satisfied +21458,18297,Male,Loyal Customer,58,Personal Travel,Eco,645,1,4,0,4,4,0,3,4,2,3,1,2,4,4,0,0.0,neutral or dissatisfied +21459,8603,Male,disloyal Customer,38,Business travel,Business,109,3,3,3,1,3,3,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +21460,35798,Male,Loyal Customer,22,Business travel,Eco Plus,200,4,2,2,2,4,4,3,4,4,3,3,2,1,4,0,0.0,satisfied +21461,6002,Female,Loyal Customer,46,Business travel,Business,3319,1,1,1,1,4,5,5,4,4,4,4,3,4,3,10,10.0,satisfied +21462,59342,Male,disloyal Customer,10,Business travel,Eco,797,4,4,4,2,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +21463,4385,Female,Loyal Customer,35,Personal Travel,Eco,607,4,5,4,4,1,4,1,1,5,2,4,4,5,1,8,0.0,neutral or dissatisfied +21464,116225,Female,Loyal Customer,29,Personal Travel,Eco,373,2,0,5,4,3,5,1,3,5,2,1,1,2,3,0,0.0,neutral or dissatisfied +21465,22689,Female,Loyal Customer,23,Business travel,Eco,579,1,3,3,3,1,1,2,1,2,5,4,3,3,1,0,0.0,neutral or dissatisfied +21466,125825,Male,disloyal Customer,18,Business travel,Eco,861,4,4,4,4,1,4,1,1,3,5,4,5,5,1,37,29.0,neutral or dissatisfied +21467,98871,Female,Loyal Customer,53,Business travel,Business,991,4,4,4,4,4,5,5,4,4,4,4,5,4,5,8,8.0,satisfied +21468,89038,Male,Loyal Customer,53,Business travel,Business,1919,2,2,2,2,3,4,5,3,3,4,3,4,3,5,0,1.0,satisfied +21469,17891,Female,Loyal Customer,41,Business travel,Eco Plus,371,4,2,2,2,3,3,1,4,4,4,4,3,4,4,0,0.0,satisfied +21470,74524,Male,Loyal Customer,47,Business travel,Business,3814,2,2,2,2,4,5,4,3,3,3,3,5,3,4,20,7.0,satisfied +21471,63105,Male,Loyal Customer,39,Business travel,Eco Plus,462,2,1,1,1,2,2,2,2,2,3,3,4,4,2,12,11.0,neutral or dissatisfied +21472,84231,Male,Loyal Customer,69,Personal Travel,Eco,432,2,2,2,3,5,2,5,5,4,5,4,2,3,5,7,11.0,neutral or dissatisfied +21473,57047,Female,Loyal Customer,41,Business travel,Business,2133,4,4,4,4,2,4,5,4,4,4,4,4,4,4,6,0.0,satisfied +21474,103484,Male,disloyal Customer,26,Business travel,Eco,440,2,2,2,3,3,2,3,3,3,3,3,1,4,3,36,18.0,neutral or dissatisfied +21475,47208,Female,Loyal Customer,53,Personal Travel,Eco,748,3,4,3,1,4,3,2,2,2,3,4,1,2,1,0,0.0,neutral or dissatisfied +21476,77889,Female,Loyal Customer,60,Business travel,Business,3670,2,2,2,2,3,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +21477,30772,Male,Loyal Customer,59,Personal Travel,Business,895,2,2,2,3,4,3,3,1,1,2,1,2,1,2,12,14.0,neutral or dissatisfied +21478,83063,Female,Loyal Customer,54,Business travel,Business,957,1,1,1,1,4,4,4,5,5,5,5,5,5,3,10,12.0,satisfied +21479,104422,Female,Loyal Customer,55,Business travel,Eco,1036,3,5,3,5,5,3,4,3,3,3,3,3,3,3,50,48.0,neutral or dissatisfied +21480,71837,Female,Loyal Customer,66,Business travel,Eco,1846,2,1,1,1,1,3,3,2,2,2,2,4,2,4,1,7.0,neutral or dissatisfied +21481,53560,Male,Loyal Customer,18,Business travel,Business,2508,2,2,2,2,3,4,3,3,1,3,5,3,5,3,0,0.0,satisfied +21482,57582,Female,disloyal Customer,57,Business travel,Eco,997,2,2,2,3,2,2,2,2,4,1,3,1,4,2,0,0.0,neutral or dissatisfied +21483,107222,Male,Loyal Customer,51,Business travel,Business,1751,1,1,1,1,5,4,5,5,5,5,5,4,5,5,3,13.0,satisfied +21484,68931,Male,Loyal Customer,26,Business travel,Business,646,3,3,3,3,4,4,4,4,3,4,4,3,5,4,0,0.0,satisfied +21485,72939,Female,Loyal Customer,46,Business travel,Business,3935,2,2,2,2,4,4,4,4,4,5,4,3,4,5,0,0.0,satisfied +21486,16446,Female,disloyal Customer,15,Business travel,Eco,529,1,2,1,4,2,1,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +21487,111201,Female,Loyal Customer,52,Business travel,Business,1506,1,1,1,1,2,4,5,4,4,4,4,5,4,4,74,70.0,satisfied +21488,9117,Male,Loyal Customer,60,Business travel,Business,765,4,4,4,4,4,4,4,4,4,4,4,2,4,4,0,0.0,neutral or dissatisfied +21489,35381,Female,Loyal Customer,56,Business travel,Business,572,5,5,5,5,2,4,4,2,2,2,2,2,2,2,6,0.0,satisfied +21490,127646,Male,Loyal Customer,19,Personal Travel,Eco,1773,2,2,2,2,5,2,5,5,3,3,1,3,2,5,0,0.0,neutral or dissatisfied +21491,42912,Male,Loyal Customer,26,Personal Travel,Eco,368,4,3,4,4,4,4,3,4,4,2,3,2,3,4,0,0.0,neutral or dissatisfied +21492,29558,Female,disloyal Customer,43,Business travel,Eco,1088,3,3,3,1,2,3,3,2,4,4,3,3,2,2,0,0.0,neutral or dissatisfied +21493,88773,Male,Loyal Customer,58,Business travel,Business,3016,4,4,4,4,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +21494,46899,Female,Loyal Customer,15,Business travel,Business,959,3,4,4,4,3,2,3,3,1,1,3,2,3,3,0,0.0,neutral or dissatisfied +21495,65029,Male,Loyal Customer,42,Personal Travel,Eco,469,1,4,1,2,3,1,1,3,2,3,2,3,2,3,0,1.0,neutral or dissatisfied +21496,40161,Female,Loyal Customer,41,Personal Travel,Business,402,1,3,1,3,3,4,2,3,3,1,3,2,3,2,0,0.0,neutral or dissatisfied +21497,2826,Female,Loyal Customer,31,Business travel,Business,491,4,4,5,4,4,4,4,4,5,3,4,3,4,4,67,58.0,satisfied +21498,105820,Male,Loyal Customer,12,Personal Travel,Eco,787,1,5,1,2,5,1,5,5,5,5,5,5,5,5,21,0.0,neutral or dissatisfied +21499,38394,Male,Loyal Customer,34,Business travel,Eco Plus,1626,4,5,5,5,4,4,4,4,5,1,3,5,5,4,0,0.0,satisfied +21500,90252,Male,Loyal Customer,57,Business travel,Business,3005,2,2,2,2,5,5,4,5,5,5,5,5,5,5,6,1.0,satisfied +21501,129044,Male,Loyal Customer,39,Business travel,Business,1744,2,2,2,2,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +21502,30096,Female,Loyal Customer,30,Personal Travel,Eco,539,2,5,2,4,5,2,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +21503,11819,Female,disloyal Customer,22,Business travel,Eco,986,3,4,4,3,3,4,1,3,3,4,3,1,2,3,40,37.0,neutral or dissatisfied +21504,75568,Male,Loyal Customer,39,Business travel,Business,3718,3,4,3,4,3,4,3,3,3,3,3,3,3,4,8,2.0,neutral or dissatisfied +21505,76505,Male,Loyal Customer,58,Business travel,Business,547,2,2,2,2,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +21506,128033,Male,Loyal Customer,49,Business travel,Business,1440,1,1,1,1,5,4,5,5,5,5,5,3,5,3,0,1.0,satisfied +21507,26218,Female,Loyal Customer,63,Personal Travel,Eco,404,2,1,2,3,4,4,4,5,5,2,5,4,5,2,14,8.0,neutral or dissatisfied +21508,79254,Female,Loyal Customer,43,Business travel,Eco,1598,2,1,2,1,2,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +21509,46479,Female,Loyal Customer,58,Personal Travel,Business,251,2,5,2,2,1,2,3,1,1,2,1,1,1,5,0,0.0,neutral or dissatisfied +21510,123987,Female,disloyal Customer,26,Business travel,Business,184,4,0,4,5,2,4,2,2,5,5,4,4,5,2,0,0.0,satisfied +21511,18973,Female,Loyal Customer,52,Business travel,Eco Plus,500,5,3,5,3,5,2,2,5,5,5,5,4,5,3,0,0.0,satisfied +21512,111837,Male,disloyal Customer,10,Business travel,Business,804,3,3,2,3,5,2,5,5,3,2,3,1,3,5,0,0.0,neutral or dissatisfied +21513,57233,Male,Loyal Customer,32,Business travel,Business,1514,4,4,5,4,5,5,5,5,3,3,5,5,5,5,36,37.0,satisfied +21514,66092,Male,Loyal Customer,25,Business travel,Eco Plus,1055,4,4,1,1,4,4,1,4,3,1,3,4,3,4,0,4.0,neutral or dissatisfied +21515,797,Male,disloyal Customer,27,Business travel,Business,312,1,1,1,2,1,5,5,4,5,5,5,5,3,5,175,174.0,neutral or dissatisfied +21516,11888,Female,Loyal Customer,15,Personal Travel,Eco Plus,912,2,5,2,1,1,2,1,1,3,5,5,5,5,1,0,0.0,neutral or dissatisfied +21517,48115,Female,disloyal Customer,25,Business travel,Eco,391,4,0,4,5,3,4,4,3,2,1,2,3,2,3,0,0.0,satisfied +21518,89319,Female,Loyal Customer,40,Business travel,Business,1587,5,3,5,5,3,5,4,4,4,4,4,4,4,3,43,38.0,satisfied +21519,95757,Male,Loyal Customer,21,Personal Travel,Eco,237,4,5,4,4,2,4,2,2,4,2,4,4,4,2,2,0.0,satisfied +21520,10174,Male,Loyal Customer,42,Business travel,Business,3074,2,2,2,2,1,3,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +21521,89401,Female,Loyal Customer,46,Business travel,Business,134,4,4,4,4,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +21522,2126,Male,Loyal Customer,50,Business travel,Business,431,3,3,3,3,5,5,4,3,3,4,3,4,3,4,0,0.0,satisfied +21523,94702,Female,disloyal Customer,48,Business travel,Eco,239,4,2,4,3,1,4,1,1,1,2,4,2,4,1,15,7.0,neutral or dissatisfied +21524,68341,Male,Loyal Customer,47,Business travel,Business,1598,4,4,4,4,2,3,4,5,5,5,5,5,5,5,127,117.0,satisfied +21525,9930,Male,Loyal Customer,46,Business travel,Business,457,1,1,1,1,5,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +21526,87445,Male,disloyal Customer,25,Business travel,Business,373,5,0,5,4,2,0,4,2,3,5,5,4,5,2,0,2.0,satisfied +21527,118167,Female,Loyal Customer,35,Business travel,Business,1444,3,3,1,3,5,4,4,4,4,4,4,3,4,4,18,5.0,satisfied +21528,120643,Female,disloyal Customer,22,Business travel,Eco,280,1,5,1,2,4,1,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +21529,47993,Male,Loyal Customer,22,Business travel,Eco Plus,784,4,5,5,5,4,4,5,4,4,3,1,1,3,4,0,6.0,satisfied +21530,64921,Female,Loyal Customer,58,Business travel,Business,3530,5,5,1,5,4,5,5,5,5,5,4,3,5,3,0,1.0,satisfied +21531,69530,Female,disloyal Customer,29,Business travel,Business,2475,3,3,3,1,3,1,4,3,3,5,5,4,5,4,0,0.0,neutral or dissatisfied +21532,31548,Male,Loyal Customer,27,Personal Travel,Eco,967,3,5,3,5,4,3,4,4,4,2,5,5,5,4,0,0.0,neutral or dissatisfied +21533,38813,Female,Loyal Customer,23,Personal Travel,Eco,353,1,4,1,2,1,1,2,1,3,3,5,3,5,1,8,8.0,neutral or dissatisfied +21534,112737,Female,Loyal Customer,59,Business travel,Business,1713,2,2,4,2,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +21535,100074,Male,Loyal Customer,40,Business travel,Business,277,0,0,0,1,5,4,4,1,1,1,1,3,1,4,13,9.0,satisfied +21536,106783,Male,Loyal Customer,54,Personal Travel,Eco Plus,829,3,5,3,1,2,3,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +21537,27363,Female,Loyal Customer,46,Business travel,Eco,1050,5,3,3,3,1,1,4,5,5,5,5,4,5,3,0,4.0,satisfied +21538,44789,Female,Loyal Customer,44,Personal Travel,Eco,1250,5,4,5,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +21539,13370,Female,Loyal Customer,14,Personal Travel,Eco,748,1,5,1,1,5,1,1,5,5,2,1,3,1,5,0,0.0,neutral or dissatisfied +21540,54730,Female,Loyal Customer,45,Personal Travel,Eco,854,3,4,3,2,4,4,4,5,5,3,5,5,5,5,1,0.0,neutral or dissatisfied +21541,127034,Male,Loyal Customer,47,Business travel,Business,2495,1,1,3,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +21542,111676,Female,Loyal Customer,27,Personal Travel,Eco,991,1,5,1,3,1,1,1,1,5,3,5,5,5,1,19,4.0,neutral or dissatisfied +21543,26965,Female,disloyal Customer,28,Business travel,Eco,867,3,4,4,4,4,4,3,4,2,2,2,4,2,4,56,48.0,neutral or dissatisfied +21544,38837,Male,Loyal Customer,45,Business travel,Eco Plus,387,3,1,1,1,3,3,3,3,1,2,2,4,4,3,0,0.0,satisfied +21545,40807,Female,Loyal Customer,39,Business travel,Eco,590,4,5,5,5,4,4,4,4,3,5,2,4,2,4,7,9.0,neutral or dissatisfied +21546,57299,Female,Loyal Customer,43,Business travel,Business,1972,3,3,3,3,3,4,4,2,2,2,2,3,2,5,20,6.0,satisfied +21547,9889,Female,Loyal Customer,51,Business travel,Business,508,2,2,2,2,5,5,4,3,3,4,3,3,3,3,0,16.0,satisfied +21548,40897,Female,Loyal Customer,69,Personal Travel,Eco,588,3,3,3,4,5,3,4,2,2,3,2,3,2,1,0,0.0,neutral or dissatisfied +21549,3740,Male,Loyal Customer,66,Personal Travel,Eco,431,2,4,2,3,1,2,1,1,5,4,5,4,4,1,0,0.0,neutral or dissatisfied +21550,63191,Male,Loyal Customer,65,Business travel,Business,3969,0,0,0,2,4,4,4,2,2,2,2,4,2,3,2,5.0,satisfied +21551,104626,Female,Loyal Customer,46,Business travel,Eco,861,1,4,4,4,2,3,4,1,1,1,1,4,1,4,0,12.0,neutral or dissatisfied +21552,85713,Male,Loyal Customer,40,Business travel,Business,1547,1,1,1,1,2,5,5,2,2,3,2,4,2,4,1,0.0,satisfied +21553,52363,Female,Loyal Customer,64,Personal Travel,Eco,598,4,5,5,2,3,4,4,2,2,5,2,4,2,4,0,0.0,satisfied +21554,45868,Male,Loyal Customer,60,Business travel,Eco,641,2,5,5,5,2,2,2,2,1,5,1,5,3,2,10,10.0,satisfied +21555,16343,Female,Loyal Customer,50,Business travel,Business,3854,2,2,2,2,3,3,2,4,4,4,5,4,4,2,0,0.0,satisfied +21556,102285,Male,Loyal Customer,52,Business travel,Business,3736,1,1,1,1,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +21557,55372,Female,Loyal Customer,62,Business travel,Eco,678,2,5,5,5,5,3,2,2,2,2,2,2,2,1,6,42.0,neutral or dissatisfied +21558,3839,Male,Loyal Customer,21,Personal Travel,Eco,710,5,4,5,2,1,5,1,1,4,5,2,2,1,1,0,0.0,satisfied +21559,25417,Female,disloyal Customer,23,Business travel,Eco Plus,1105,2,0,1,1,2,1,2,2,3,2,4,2,3,2,13,3.0,neutral or dissatisfied +21560,74022,Female,disloyal Customer,16,Business travel,Eco,1333,5,5,5,1,3,5,3,3,3,4,4,3,5,3,0,0.0,satisfied +21561,20183,Male,Loyal Customer,9,Personal Travel,Eco,403,2,5,3,1,5,3,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +21562,88306,Male,Loyal Customer,59,Business travel,Business,594,1,1,1,1,3,5,5,5,5,4,5,4,5,3,0,0.0,satisfied +21563,104665,Male,Loyal Customer,65,Business travel,Business,641,2,4,4,4,3,3,2,2,2,2,2,4,2,2,7,7.0,neutral or dissatisfied +21564,81725,Female,Loyal Customer,28,Business travel,Business,2841,3,5,5,5,3,3,3,3,4,2,4,1,3,3,0,0.0,neutral or dissatisfied +21565,70572,Female,Loyal Customer,50,Personal Travel,Eco,1258,2,5,2,3,3,3,5,5,5,2,3,4,5,5,0,0.0,neutral or dissatisfied +21566,25345,Male,Loyal Customer,38,Business travel,Business,1558,5,5,5,5,1,1,4,3,3,3,3,5,3,2,0,0.0,satisfied +21567,128669,Male,Loyal Customer,50,Business travel,Business,2442,3,3,3,3,5,5,5,3,5,3,4,5,3,5,15,25.0,satisfied +21568,84954,Female,Loyal Customer,58,Business travel,Business,2475,1,1,1,1,5,4,4,5,5,5,5,3,5,4,0,1.0,satisfied +21569,82374,Male,Loyal Customer,56,Business travel,Business,1953,1,1,1,1,5,5,4,4,4,4,4,4,4,5,18,0.0,satisfied +21570,45761,Male,Loyal Customer,52,Business travel,Eco,391,5,4,4,4,4,5,4,4,2,5,4,1,1,4,0,0.0,satisfied +21571,86706,Female,Loyal Customer,45,Business travel,Business,1747,3,3,3,3,4,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +21572,76158,Female,disloyal Customer,38,Business travel,Eco,289,3,1,3,4,5,3,5,5,4,1,3,1,3,5,0,0.0,neutral or dissatisfied +21573,28243,Female,Loyal Customer,7,Personal Travel,Eco,1009,2,5,2,1,5,2,3,5,3,5,5,5,4,5,0,0.0,neutral or dissatisfied +21574,36294,Female,Loyal Customer,44,Business travel,Business,2263,4,4,4,4,5,4,2,4,4,4,5,2,4,3,0,0.0,satisfied +21575,32183,Female,Loyal Customer,55,Business travel,Business,1688,3,3,3,3,3,2,5,5,5,5,3,3,5,1,0,3.0,satisfied +21576,100485,Female,Loyal Customer,29,Business travel,Business,580,3,3,3,3,3,3,3,3,1,4,4,3,4,3,0,0.0,neutral or dissatisfied +21577,27426,Male,disloyal Customer,27,Business travel,Eco,954,3,3,3,3,3,3,3,3,1,1,3,3,3,3,0,6.0,neutral or dissatisfied +21578,13610,Female,Loyal Customer,38,Business travel,Eco Plus,106,2,4,4,4,2,2,2,2,4,2,3,2,4,2,0,0.0,neutral or dissatisfied +21579,98903,Male,Loyal Customer,65,Personal Travel,Business,543,3,2,3,2,2,2,2,2,2,3,4,1,2,4,0,0.0,neutral or dissatisfied +21580,45073,Male,Loyal Customer,37,Personal Travel,Eco,265,1,4,1,4,5,1,5,5,3,5,3,2,4,5,11,2.0,neutral or dissatisfied +21581,19009,Female,disloyal Customer,22,Business travel,Eco,871,2,2,2,3,5,2,5,5,4,4,3,2,4,5,0,0.0,neutral or dissatisfied +21582,101026,Female,Loyal Customer,29,Personal Travel,Eco,867,2,4,2,3,2,2,2,2,2,2,3,3,4,2,10,24.0,neutral or dissatisfied +21583,33713,Female,Loyal Customer,37,Personal Travel,Eco,759,4,4,4,4,5,4,5,5,4,3,4,3,4,5,0,0.0,satisfied +21584,72759,Male,disloyal Customer,23,Business travel,Business,1045,0,3,0,1,5,0,5,5,3,5,5,4,5,5,0,0.0,satisfied +21585,106283,Female,Loyal Customer,38,Business travel,Business,204,2,4,4,4,1,3,4,3,3,3,2,2,3,4,44,48.0,neutral or dissatisfied +21586,126821,Female,Loyal Customer,60,Business travel,Business,2125,3,3,3,3,3,3,5,4,4,4,4,4,4,4,4,0.0,satisfied +21587,60071,Female,Loyal Customer,45,Business travel,Business,1911,1,1,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +21588,99793,Female,disloyal Customer,27,Business travel,Eco,632,3,1,3,2,5,3,5,5,4,5,3,3,3,5,1,0.0,neutral or dissatisfied +21589,62504,Female,Loyal Customer,56,Business travel,Business,1781,4,5,4,4,4,5,4,5,5,5,5,3,5,3,0,6.0,satisfied +21590,2138,Female,Loyal Customer,13,Personal Travel,Eco,431,2,4,3,2,1,3,1,1,5,2,5,5,5,1,2,2.0,neutral or dissatisfied +21591,68298,Male,Loyal Customer,42,Business travel,Business,1797,5,5,5,5,5,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +21592,109519,Male,Loyal Customer,23,Business travel,Business,861,4,2,2,2,4,3,4,4,2,3,3,2,2,4,0,0.0,neutral or dissatisfied +21593,86655,Male,Loyal Customer,25,Personal Travel,Eco,746,1,4,1,3,3,1,3,3,3,4,5,3,5,3,0,0.0,neutral or dissatisfied +21594,56526,Male,Loyal Customer,55,Business travel,Business,2142,5,5,5,5,5,4,4,5,5,5,5,3,5,4,3,6.0,satisfied +21595,36990,Male,disloyal Customer,30,Business travel,Eco,667,4,4,5,4,2,5,2,2,4,1,3,2,3,2,20,21.0,neutral or dissatisfied +21596,57445,Male,Loyal Customer,49,Business travel,Business,334,0,0,0,2,3,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21597,102660,Male,disloyal Customer,37,Business travel,Business,255,5,5,5,2,4,5,4,4,5,4,5,5,4,4,3,0.0,satisfied +21598,110077,Female,Loyal Customer,31,Personal Travel,Business,1048,1,4,1,3,5,1,5,5,4,4,5,3,5,5,0,2.0,neutral or dissatisfied +21599,77740,Female,disloyal Customer,40,Business travel,Business,331,4,4,4,5,5,4,5,5,1,1,5,2,5,5,0,0.0,neutral or dissatisfied +21600,17779,Male,Loyal Customer,21,Business travel,Eco,1075,4,3,3,3,4,4,5,4,1,2,2,3,5,4,0,4.0,satisfied +21601,67275,Female,Loyal Customer,42,Personal Travel,Eco,929,1,4,1,4,3,4,4,1,1,1,1,4,1,5,11,2.0,neutral or dissatisfied +21602,42897,Male,disloyal Customer,33,Business travel,Eco,422,1,1,1,3,5,1,5,5,1,2,3,3,4,5,0,0.0,neutral or dissatisfied +21603,60034,Female,Loyal Customer,36,Personal Travel,Eco,1023,2,5,2,1,5,2,5,5,2,5,4,5,2,5,11,13.0,neutral or dissatisfied +21604,33763,Male,Loyal Customer,48,Personal Travel,Eco,266,3,0,3,5,3,3,3,3,5,5,5,3,5,3,0,0.0,neutral or dissatisfied +21605,75822,Female,Loyal Customer,25,Personal Travel,Business,1440,5,4,5,2,4,5,4,4,4,3,4,3,5,4,0,0.0,satisfied +21606,75429,Male,Loyal Customer,10,Business travel,Business,2342,2,4,4,4,2,2,2,2,4,5,3,3,4,2,6,16.0,neutral or dissatisfied +21607,41066,Male,Loyal Customer,42,Business travel,Business,3521,3,2,4,4,2,4,3,4,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +21608,124415,Female,Loyal Customer,46,Business travel,Business,2268,4,4,4,4,5,5,5,4,4,4,4,4,4,4,9,1.0,satisfied +21609,48418,Male,Loyal Customer,37,Business travel,Eco,948,5,3,3,3,5,5,5,5,2,2,5,2,3,5,30,28.0,satisfied +21610,53960,Male,Loyal Customer,48,Business travel,Business,1325,3,3,3,3,5,4,4,5,5,5,5,3,5,5,6,2.0,satisfied +21611,17653,Male,Loyal Customer,36,Business travel,Eco,1008,4,5,5,5,4,4,4,4,2,4,3,2,2,4,0,0.0,satisfied +21612,124108,Female,Loyal Customer,44,Business travel,Business,3506,3,3,3,3,2,4,5,4,4,5,4,3,4,3,2,1.0,satisfied +21613,73102,Female,Loyal Customer,40,Business travel,Business,2174,4,3,3,3,3,3,4,4,4,4,4,1,4,1,55,44.0,neutral or dissatisfied +21614,15467,Female,Loyal Customer,22,Personal Travel,Eco,331,5,5,3,4,5,3,5,5,3,2,4,4,5,5,0,0.0,satisfied +21615,78606,Female,Loyal Customer,59,Business travel,Business,1426,2,2,2,2,5,4,4,5,5,5,5,3,5,3,41,28.0,satisfied +21616,110827,Female,Loyal Customer,24,Personal Travel,Eco,990,3,5,3,3,3,3,3,3,3,3,4,3,4,3,0,0.0,neutral or dissatisfied +21617,77342,Female,Loyal Customer,43,Business travel,Business,2230,5,5,5,5,3,4,4,4,4,4,4,4,4,4,42,29.0,satisfied +21618,55308,Female,Loyal Customer,8,Personal Travel,Eco,2072,1,3,1,3,3,1,3,3,1,1,3,4,3,3,32,9.0,neutral or dissatisfied +21619,68808,Female,Loyal Customer,39,Personal Travel,Eco,861,4,3,4,1,3,4,3,3,1,1,2,2,5,3,0,0.0,neutral or dissatisfied +21620,76277,Male,Loyal Customer,38,Business travel,Eco,427,3,5,5,5,3,4,3,3,1,5,3,4,2,3,1,20.0,satisfied +21621,52308,Male,disloyal Customer,18,Business travel,Eco,651,5,4,4,2,5,4,5,5,2,3,5,5,4,5,0,0.0,satisfied +21622,37248,Female,Loyal Customer,52,Personal Travel,Business,944,1,2,1,2,2,3,2,2,2,1,2,1,2,2,34,48.0,neutral or dissatisfied +21623,21072,Female,Loyal Customer,60,Business travel,Eco,152,3,5,5,5,1,4,3,4,4,3,4,4,4,1,0,0.0,neutral or dissatisfied +21624,72919,Female,disloyal Customer,28,Business travel,Business,1096,2,3,3,3,5,3,5,5,3,4,4,4,4,5,0,0.0,neutral or dissatisfied +21625,87979,Female,Loyal Customer,58,Business travel,Business,250,0,1,1,3,4,4,4,1,1,1,1,4,1,3,13,3.0,satisfied +21626,124974,Male,Loyal Customer,48,Business travel,Business,184,5,5,5,5,3,4,4,4,4,4,5,3,4,4,0,0.0,satisfied +21627,35069,Female,Loyal Customer,60,Business travel,Business,2139,3,2,3,3,5,3,4,3,3,3,3,4,3,4,4,8.0,neutral or dissatisfied +21628,29557,Female,Loyal Customer,31,Business travel,Business,1779,5,5,5,5,5,5,5,5,5,3,3,5,2,5,0,0.0,satisfied +21629,123532,Female,Loyal Customer,15,Business travel,Eco Plus,2125,2,3,2,3,2,2,4,2,3,4,2,4,4,2,0,13.0,neutral or dissatisfied +21630,95027,Male,Loyal Customer,27,Personal Travel,Eco,248,2,5,2,5,2,2,2,2,4,2,5,3,4,2,44,39.0,neutral or dissatisfied +21631,54496,Male,Loyal Customer,51,Business travel,Eco,925,5,2,2,2,5,5,5,5,1,4,2,3,5,5,30,57.0,satisfied +21632,26677,Male,Loyal Customer,48,Personal Travel,Eco,404,2,4,2,2,1,2,1,1,3,4,5,5,4,1,0,0.0,neutral or dissatisfied +21633,33518,Female,Loyal Customer,61,Personal Travel,Eco,1554,1,5,1,4,2,5,5,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +21634,31669,Female,Loyal Customer,12,Business travel,Business,846,3,4,2,4,3,3,3,3,2,4,3,1,4,3,0,6.0,neutral or dissatisfied +21635,92179,Male,Loyal Customer,59,Business travel,Business,2079,1,1,2,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +21636,32691,Male,Loyal Customer,25,Business travel,Business,101,2,2,2,2,4,4,2,4,2,4,4,2,4,4,0,1.0,neutral or dissatisfied +21637,124738,Female,Loyal Customer,23,Personal Travel,Eco Plus,399,0,4,0,3,3,0,3,3,4,5,5,5,4,3,0,0.0,satisfied +21638,78382,Female,Loyal Customer,59,Business travel,Business,3446,1,1,2,1,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +21639,45999,Male,Loyal Customer,38,Personal Travel,Eco,483,3,4,5,3,3,5,3,3,5,4,3,2,5,3,49,64.0,neutral or dissatisfied +21640,1498,Male,disloyal Customer,20,Business travel,Eco,737,1,1,1,4,1,5,4,3,4,4,3,4,2,4,135,129.0,neutral or dissatisfied +21641,26144,Male,Loyal Customer,35,Business travel,Eco,581,4,3,5,3,4,4,4,4,2,2,2,3,1,4,74,79.0,satisfied +21642,1200,Male,Loyal Customer,43,Personal Travel,Eco,396,2,4,2,3,2,2,2,2,1,3,3,3,3,2,7,22.0,neutral or dissatisfied +21643,82047,Male,Loyal Customer,44,Personal Travel,Eco,1576,3,5,3,1,2,3,2,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +21644,78221,Female,Loyal Customer,62,Personal Travel,Eco,259,2,3,2,3,5,4,3,3,3,2,3,2,3,5,0,0.0,neutral or dissatisfied +21645,107836,Male,Loyal Customer,12,Personal Travel,Eco,349,2,5,2,2,4,2,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +21646,75371,Male,Loyal Customer,56,Business travel,Business,2342,3,3,3,3,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +21647,30668,Male,disloyal Customer,37,Business travel,Eco Plus,533,5,5,5,4,1,5,1,1,5,2,5,5,3,1,0,0.0,satisfied +21648,93588,Female,Loyal Customer,56,Personal Travel,Eco,159,2,5,2,2,3,5,5,5,5,2,5,5,5,3,36,31.0,neutral or dissatisfied +21649,88107,Male,Loyal Customer,58,Business travel,Business,404,1,5,1,1,2,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +21650,15005,Female,Loyal Customer,34,Business travel,Business,557,3,3,3,3,4,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +21651,93736,Female,disloyal Customer,72,Business travel,Business,368,1,1,1,2,4,1,4,4,3,1,2,2,2,4,0,2.0,neutral or dissatisfied +21652,73202,Male,Loyal Customer,28,Personal Travel,Eco,1258,2,1,2,3,4,2,4,4,3,3,2,2,3,4,14,0.0,neutral or dissatisfied +21653,10142,Male,Loyal Customer,44,Business travel,Business,2061,3,3,3,3,2,5,4,4,4,5,4,4,4,5,32,13.0,satisfied +21654,96689,Male,Loyal Customer,54,Business travel,Business,696,2,2,2,2,3,4,4,2,2,2,2,4,2,5,20,19.0,satisfied +21655,123669,Female,disloyal Customer,68,Business travel,Business,214,5,5,5,3,4,5,1,4,4,4,4,4,5,4,0,0.0,satisfied +21656,129454,Female,Loyal Customer,34,Personal Travel,Eco,414,2,2,2,4,1,2,1,1,2,4,4,3,4,1,1,0.0,neutral or dissatisfied +21657,41534,Female,disloyal Customer,34,Business travel,Eco,1100,2,2,2,3,4,2,4,4,4,3,1,1,5,4,0,0.0,neutral or dissatisfied +21658,52394,Female,Loyal Customer,67,Personal Travel,Eco,370,2,0,3,3,2,4,4,5,5,3,5,3,5,3,13,4.0,neutral or dissatisfied +21659,74479,Female,Loyal Customer,28,Business travel,Business,1126,2,2,2,2,5,5,5,5,4,3,4,4,5,5,0,0.0,satisfied +21660,90749,Female,Loyal Customer,57,Business travel,Business,2569,3,3,3,3,4,4,4,3,3,2,3,4,3,3,0,0.0,satisfied +21661,103241,Female,Loyal Customer,34,Business travel,Business,3239,1,1,1,1,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +21662,29003,Male,Loyal Customer,43,Business travel,Business,2169,5,5,5,5,1,3,2,4,4,4,4,3,4,1,0,0.0,satisfied +21663,19604,Female,Loyal Customer,56,Business travel,Eco Plus,160,4,5,5,5,5,1,2,4,4,4,4,2,4,5,79,90.0,satisfied +21664,123447,Male,Loyal Customer,53,Business travel,Eco,2077,3,5,5,5,3,3,3,3,4,1,3,3,3,3,11,0.0,neutral or dissatisfied +21665,76209,Male,Loyal Customer,46,Business travel,Business,2422,5,5,5,5,3,5,5,5,5,5,5,5,5,5,2,14.0,satisfied +21666,66525,Male,Loyal Customer,55,Business travel,Business,447,2,2,2,2,3,5,4,2,2,2,2,5,2,4,16,20.0,satisfied +21667,73785,Female,Loyal Customer,53,Business travel,Business,3206,5,5,5,5,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +21668,84085,Male,Loyal Customer,8,Personal Travel,Eco,757,1,4,1,5,5,1,5,5,4,3,5,4,4,5,0,0.0,neutral or dissatisfied +21669,110512,Female,Loyal Customer,25,Personal Travel,Eco Plus,663,0,5,0,2,4,0,4,4,2,3,4,5,3,4,0,0.0,satisfied +21670,70721,Male,Loyal Customer,49,Business travel,Business,675,2,2,2,2,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +21671,35676,Male,Loyal Customer,29,Business travel,Eco,2576,4,2,4,2,4,4,4,2,2,3,3,4,1,4,2,28.0,satisfied +21672,24445,Male,Loyal Customer,60,Business travel,Business,547,2,5,5,5,5,4,4,2,2,2,2,1,2,1,0,6.0,neutral or dissatisfied +21673,67490,Male,Loyal Customer,22,Business travel,Business,3973,4,4,4,4,4,5,4,4,3,4,4,3,4,4,0,3.0,satisfied +21674,33028,Female,Loyal Customer,13,Personal Travel,Eco,163,4,4,4,4,3,4,3,3,4,5,2,5,3,3,0,0.0,satisfied +21675,69262,Male,disloyal Customer,17,Business travel,Eco,740,1,1,1,4,2,1,2,2,1,5,3,2,4,2,2,0.0,neutral or dissatisfied +21676,99077,Female,Loyal Customer,59,Business travel,Business,2977,2,2,5,2,3,4,5,5,5,5,5,3,5,3,82,75.0,satisfied +21677,119745,Female,Loyal Customer,65,Personal Travel,Eco,1303,2,2,2,4,4,2,3,4,4,2,4,4,4,1,0,0.0,neutral or dissatisfied +21678,30756,Female,disloyal Customer,42,Business travel,Eco Plus,977,4,4,4,3,2,4,2,2,1,3,4,2,3,2,0,0.0,neutral or dissatisfied +21679,70115,Female,Loyal Customer,39,Business travel,Business,3979,2,2,2,2,1,3,3,2,2,2,2,2,2,2,17,11.0,neutral or dissatisfied +21680,93562,Male,Loyal Customer,50,Business travel,Business,719,4,4,4,4,3,4,5,2,2,2,2,3,2,5,56,54.0,satisfied +21681,105283,Male,Loyal Customer,41,Business travel,Business,738,2,2,2,2,5,5,4,3,3,2,3,4,3,3,9,16.0,satisfied +21682,65810,Female,Loyal Customer,25,Business travel,Business,1389,4,4,4,4,3,3,3,3,5,5,5,5,5,3,0,0.0,satisfied +21683,122969,Female,Loyal Customer,53,Business travel,Business,468,4,4,4,4,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +21684,85342,Female,Loyal Customer,59,Business travel,Business,3381,4,4,2,4,4,4,4,5,5,5,5,3,5,4,15,16.0,satisfied +21685,117130,Female,Loyal Customer,60,Personal Travel,Eco,370,1,4,1,3,4,4,4,5,5,1,5,1,5,4,0,0.0,neutral or dissatisfied +21686,4328,Female,Loyal Customer,24,Personal Travel,Eco,589,3,4,3,3,4,3,4,4,3,4,5,4,4,4,0,0.0,neutral or dissatisfied +21687,43400,Female,Loyal Customer,24,Personal Travel,Eco,347,4,4,4,1,1,4,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +21688,77196,Male,Loyal Customer,46,Personal Travel,Eco,290,3,5,3,3,5,3,5,5,3,4,4,5,5,5,0,0.0,neutral or dissatisfied +21689,40057,Female,disloyal Customer,27,Business travel,Eco Plus,866,3,4,4,2,1,4,1,1,5,3,2,5,4,1,0,0.0,neutral or dissatisfied +21690,19693,Female,Loyal Customer,40,Business travel,Business,3639,5,5,5,5,1,1,5,4,4,5,4,5,4,1,0,0.0,satisfied +21691,102876,Male,disloyal Customer,38,Business travel,Business,472,1,1,1,3,1,1,1,1,4,5,3,2,3,1,5,6.0,neutral or dissatisfied +21692,81263,Male,Loyal Customer,43,Business travel,Business,3142,2,2,2,2,4,5,4,5,5,5,5,5,5,4,15,87.0,satisfied +21693,54612,Female,Loyal Customer,42,Business travel,Business,3393,2,2,2,2,4,2,3,5,5,5,5,3,5,1,0,0.0,satisfied +21694,17315,Female,Loyal Customer,19,Personal Travel,Eco,403,1,5,3,5,1,3,1,1,3,4,4,5,5,1,89,92.0,neutral or dissatisfied +21695,40428,Male,disloyal Customer,27,Business travel,Eco,188,5,0,5,3,5,5,5,5,2,4,4,1,2,5,0,11.0,satisfied +21696,18390,Male,Loyal Customer,43,Business travel,Eco,378,4,5,5,5,4,4,4,4,1,2,2,2,4,4,0,0.0,satisfied +21697,108576,Female,disloyal Customer,22,Business travel,Eco,813,2,2,2,3,2,2,2,2,3,3,4,3,4,2,0,7.0,neutral or dissatisfied +21698,4160,Male,Loyal Customer,25,Personal Travel,Eco,427,5,3,5,4,3,5,3,3,1,2,4,4,3,3,122,125.0,satisfied +21699,119363,Female,Loyal Customer,37,Business travel,Business,1869,3,5,5,5,2,4,4,3,3,2,3,3,3,4,0,0.0,neutral or dissatisfied +21700,33860,Male,Loyal Customer,62,Personal Travel,Eco,1609,4,4,4,3,4,4,4,4,5,3,5,4,5,4,20,0.0,neutral or dissatisfied +21701,74336,Male,Loyal Customer,55,Business travel,Business,2795,2,1,1,1,4,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +21702,621,Male,Loyal Customer,28,Business travel,Business,2521,3,3,3,3,5,5,5,5,3,5,4,4,5,5,0,0.0,satisfied +21703,105248,Male,disloyal Customer,26,Business travel,Business,377,4,4,4,4,3,4,3,3,3,5,4,5,4,3,0,0.0,satisfied +21704,37758,Female,Loyal Customer,21,Business travel,Eco Plus,1076,0,4,0,3,1,4,1,1,2,1,1,1,3,1,0,0.0,satisfied +21705,24027,Female,Loyal Customer,11,Business travel,Business,595,1,1,5,1,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +21706,110173,Female,Loyal Customer,21,Personal Travel,Eco,882,3,3,3,3,3,3,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +21707,122161,Female,Loyal Customer,45,Business travel,Business,2659,4,3,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +21708,109814,Male,disloyal Customer,24,Business travel,Eco,1101,5,5,5,2,5,5,2,5,3,4,5,5,4,5,0,0.0,satisfied +21709,16614,Female,Loyal Customer,40,Personal Travel,Eco,1008,2,1,2,1,5,2,5,5,2,3,2,1,1,5,0,0.0,neutral or dissatisfied +21710,23584,Female,Loyal Customer,41,Business travel,Business,3014,2,2,4,2,5,5,3,4,4,5,4,4,4,4,0,0.0,satisfied +21711,7655,Female,disloyal Customer,21,Business travel,Business,767,4,0,4,3,4,4,4,4,3,2,5,3,4,4,15,7.0,satisfied +21712,126699,Male,Loyal Customer,58,Business travel,Business,2521,1,1,1,1,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21713,77014,Male,Loyal Customer,56,Business travel,Business,368,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +21714,121589,Male,Loyal Customer,52,Business travel,Business,536,3,3,1,3,2,2,4,4,4,4,4,1,4,4,0,0.0,satisfied +21715,110106,Male,Loyal Customer,29,Business travel,Business,1242,5,5,5,5,2,2,2,2,4,3,4,3,5,2,47,56.0,satisfied +21716,65680,Female,Loyal Customer,60,Personal Travel,Eco,926,2,5,2,3,5,5,5,4,4,2,4,5,4,5,0,0.0,neutral or dissatisfied +21717,67594,Female,Loyal Customer,59,Business travel,Business,2139,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +21718,30623,Male,Loyal Customer,43,Business travel,Business,3025,5,2,5,5,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +21719,80985,Male,Loyal Customer,33,Business travel,Business,2844,3,2,2,2,3,3,3,3,3,4,4,4,4,3,0,24.0,neutral or dissatisfied +21720,118505,Female,disloyal Customer,27,Business travel,Business,304,2,2,2,5,4,2,4,4,4,3,4,5,5,4,18,13.0,neutral or dissatisfied +21721,114940,Male,disloyal Customer,49,Business travel,Business,308,4,4,4,1,4,4,2,4,5,2,5,4,5,4,5,0.0,satisfied +21722,57138,Male,Loyal Customer,58,Business travel,Business,1222,1,1,1,1,2,5,5,4,4,4,4,5,4,3,6,0.0,satisfied +21723,115152,Female,Loyal Customer,39,Business travel,Business,2384,2,2,3,2,4,5,4,5,5,5,5,3,5,4,0,1.0,satisfied +21724,86222,Male,Loyal Customer,45,Business travel,Eco,356,2,4,4,4,2,2,2,2,2,3,2,2,3,2,3,0.0,satisfied +21725,6248,Male,Loyal Customer,44,Personal Travel,Eco,413,3,1,3,4,2,3,2,2,2,2,4,2,4,2,12,38.0,neutral or dissatisfied +21726,101000,Male,Loyal Customer,44,Business travel,Business,3889,2,2,2,2,3,4,4,3,3,4,3,3,3,5,22,10.0,satisfied +21727,45742,Female,Loyal Customer,49,Business travel,Business,3608,4,4,4,4,2,3,3,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +21728,114384,Male,Loyal Customer,53,Personal Travel,Eco Plus,862,1,2,2,4,1,2,1,1,2,1,3,1,4,1,7,0.0,neutral or dissatisfied +21729,41448,Female,Loyal Customer,52,Business travel,Business,1504,4,4,4,4,5,4,5,4,4,4,4,4,4,4,12,4.0,satisfied +21730,92204,Female,disloyal Customer,35,Business travel,Eco,1979,2,2,2,3,2,2,2,2,3,5,4,2,1,2,569,543.0,neutral or dissatisfied +21731,64227,Male,Loyal Customer,59,Business travel,Eco,1660,2,2,4,4,2,2,2,2,2,4,3,3,2,2,17,28.0,neutral or dissatisfied +21732,117799,Male,Loyal Customer,44,Business travel,Business,2059,5,5,5,5,3,5,4,4,4,4,4,5,4,4,14,6.0,satisfied +21733,50099,Female,Loyal Customer,36,Business travel,Business,2450,3,3,3,3,4,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +21734,44528,Male,Loyal Customer,58,Business travel,Business,157,4,4,3,4,2,5,1,5,5,5,3,1,5,3,0,0.0,satisfied +21735,113921,Male,Loyal Customer,40,Business travel,Business,3950,3,3,3,3,4,2,4,4,4,4,3,5,4,2,16,13.0,satisfied +21736,25750,Male,Loyal Customer,74,Business travel,Eco,356,4,3,5,3,5,4,5,5,5,5,4,4,1,5,14,0.0,satisfied +21737,43701,Female,Loyal Customer,39,Business travel,Eco,196,4,3,3,3,4,4,4,4,2,3,4,3,4,4,0,14.0,satisfied +21738,125325,Female,Loyal Customer,60,Business travel,Business,2062,3,3,3,3,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +21739,46611,Male,disloyal Customer,21,Business travel,Eco,212,4,1,4,4,3,4,3,3,3,4,3,4,3,3,80,71.0,neutral or dissatisfied +21740,72227,Male,Loyal Customer,51,Business travel,Business,3673,5,5,5,5,2,5,4,4,4,4,4,5,4,3,0,,satisfied +21741,10110,Female,Loyal Customer,23,Personal Travel,Eco Plus,391,2,1,2,3,5,2,4,5,4,4,4,4,3,5,0,1.0,neutral or dissatisfied +21742,48485,Female,disloyal Customer,27,Business travel,Eco,844,3,3,3,3,1,3,1,1,3,4,4,1,3,1,112,93.0,neutral or dissatisfied +21743,66523,Female,Loyal Customer,69,Business travel,Business,447,2,2,2,2,4,5,5,3,3,3,3,4,3,4,12,8.0,satisfied +21744,55804,Male,Loyal Customer,49,Personal Travel,Business,1416,3,2,3,2,1,2,2,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +21745,86365,Female,Loyal Customer,26,Business travel,Business,2513,3,2,3,3,4,4,4,4,4,4,5,5,5,4,0,0.0,satisfied +21746,90409,Male,Loyal Customer,40,Business travel,Business,646,5,5,5,5,5,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +21747,105445,Female,Loyal Customer,29,Business travel,Business,2658,1,1,5,1,4,4,4,4,5,3,4,3,5,4,0,0.0,satisfied +21748,108304,Female,Loyal Customer,45,Business travel,Business,1706,2,2,2,2,2,4,5,4,4,4,4,5,4,3,29,17.0,satisfied +21749,61117,Male,Loyal Customer,23,Business travel,Business,2560,1,1,1,1,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +21750,28339,Female,disloyal Customer,64,Business travel,Eco,867,1,1,1,4,2,1,2,2,3,2,3,1,4,2,0,0.0,neutral or dissatisfied +21751,27431,Male,Loyal Customer,31,Business travel,Business,978,3,2,2,2,3,3,3,3,1,4,1,2,2,3,0,0.0,neutral or dissatisfied +21752,36171,Female,disloyal Customer,33,Business travel,Eco,1149,1,1,1,3,4,1,4,4,1,4,3,1,4,4,8,12.0,neutral or dissatisfied +21753,111921,Female,Loyal Customer,36,Business travel,Business,3773,1,5,5,5,3,4,3,1,1,1,1,2,1,2,0,0.0,neutral or dissatisfied +21754,90098,Male,Loyal Customer,54,Business travel,Eco,1086,2,3,3,3,2,2,2,2,2,3,2,3,3,2,46,42.0,neutral or dissatisfied +21755,96172,Male,Loyal Customer,44,Business travel,Business,460,1,1,1,1,4,5,4,5,5,5,5,5,5,4,2,0.0,satisfied +21756,121758,Female,Loyal Customer,48,Business travel,Business,366,3,1,1,1,5,3,4,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +21757,4106,Female,Loyal Customer,53,Business travel,Business,431,3,3,3,3,3,4,5,5,5,5,5,3,5,3,38,33.0,satisfied +21758,38786,Male,disloyal Customer,33,Business travel,Business,354,2,2,2,3,4,2,4,4,4,2,4,3,3,4,6,0.0,neutral or dissatisfied +21759,65435,Male,Loyal Customer,59,Business travel,Business,2165,5,5,5,5,5,3,5,5,5,5,5,4,5,5,10,0.0,satisfied +21760,4937,Male,disloyal Customer,24,Business travel,Business,268,1,1,1,3,2,1,2,2,4,5,3,2,3,2,0,0.0,neutral or dissatisfied +21761,48754,Female,Loyal Customer,39,Business travel,Business,3764,0,4,1,1,4,4,4,3,3,3,3,3,3,3,0,0.0,satisfied +21762,18213,Female,disloyal Customer,39,Business travel,Business,224,2,2,2,1,5,2,1,5,4,1,4,4,1,5,25,27.0,satisfied +21763,63292,Female,Loyal Customer,34,Business travel,Business,447,3,2,2,2,1,2,2,3,3,3,3,3,3,1,19,10.0,neutral or dissatisfied +21764,102524,Male,Loyal Customer,12,Personal Travel,Eco,236,2,1,2,4,5,2,5,5,4,2,3,1,3,5,37,40.0,neutral or dissatisfied +21765,50687,Male,Loyal Customer,11,Personal Travel,Eco,56,3,2,3,4,2,3,2,2,2,3,3,3,3,2,73,76.0,neutral or dissatisfied +21766,67142,Female,Loyal Customer,16,Business travel,Eco,985,0,4,0,3,1,0,1,1,3,5,5,1,4,1,0,0.0,satisfied +21767,110916,Female,Loyal Customer,33,Business travel,Eco,404,3,2,2,2,3,4,3,3,4,2,3,2,1,3,4,0.0,satisfied +21768,91395,Female,disloyal Customer,25,Business travel,Eco,1033,3,3,3,3,4,3,4,4,1,3,4,1,3,4,120,107.0,neutral or dissatisfied +21769,88286,Female,disloyal Customer,25,Business travel,Business,404,5,4,5,5,2,5,2,2,4,3,5,3,5,2,0,4.0,satisfied +21770,9600,Female,Loyal Customer,42,Personal Travel,Eco,283,1,5,1,2,4,4,4,4,4,1,4,5,4,4,0,0.0,neutral or dissatisfied +21771,120410,Female,Loyal Customer,43,Business travel,Business,337,2,2,2,2,4,4,3,2,2,2,2,4,2,3,0,2.0,neutral or dissatisfied +21772,83164,Male,Loyal Customer,26,Business travel,Eco Plus,983,3,5,5,5,3,4,3,3,5,2,4,1,5,3,0,0.0,satisfied +21773,69219,Female,disloyal Customer,29,Business travel,Business,733,0,0,0,3,0,1,1,5,2,4,5,1,3,1,45,148.0,satisfied +21774,4607,Male,Loyal Customer,47,Business travel,Business,719,1,1,1,1,5,5,5,2,2,2,2,3,2,5,84,75.0,satisfied +21775,116795,Male,Loyal Customer,57,Personal Travel,Eco Plus,333,3,5,3,1,3,3,3,3,3,3,4,5,4,3,0,0.0,neutral or dissatisfied +21776,34147,Female,Loyal Customer,42,Business travel,Business,3855,4,2,2,2,2,4,3,4,4,4,4,1,4,4,17,38.0,neutral or dissatisfied +21777,80662,Male,Loyal Customer,34,Business travel,Eco,821,2,2,2,2,2,2,2,2,4,5,3,1,3,2,0,4.0,neutral or dissatisfied +21778,78976,Female,disloyal Customer,45,Business travel,Business,356,2,2,2,3,3,2,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +21779,109659,Male,Loyal Customer,45,Business travel,Business,1818,2,5,5,5,4,4,3,2,2,2,2,3,2,1,23,12.0,neutral or dissatisfied +21780,66915,Female,Loyal Customer,25,Business travel,Business,3347,3,3,3,3,5,5,5,5,3,4,5,4,5,5,0,0.0,satisfied +21781,17825,Female,Loyal Customer,31,Personal Travel,Eco,1075,3,3,3,3,1,3,1,1,3,2,3,4,1,1,4,0.0,neutral or dissatisfied +21782,25225,Female,Loyal Customer,27,Business travel,Business,1716,2,1,1,1,2,2,2,2,3,2,4,3,3,2,0,0.0,neutral or dissatisfied +21783,38164,Male,Loyal Customer,33,Personal Travel,Eco,1237,2,4,2,1,2,2,2,2,5,4,3,5,5,2,0,0.0,neutral or dissatisfied +21784,59728,Female,Loyal Customer,59,Personal Travel,Eco Plus,964,3,1,3,4,5,4,3,4,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +21785,127826,Male,Loyal Customer,53,Personal Travel,Eco,1262,3,4,2,3,3,2,3,3,4,3,4,5,4,3,2,0.0,neutral or dissatisfied +21786,61578,Female,Loyal Customer,51,Business travel,Business,1346,1,3,3,3,3,3,3,1,1,1,1,2,1,1,4,0.0,neutral or dissatisfied +21787,104801,Male,Loyal Customer,52,Business travel,Eco,187,2,3,4,4,3,2,3,3,2,5,3,3,4,3,10,2.0,neutral or dissatisfied +21788,45807,Female,Loyal Customer,45,Business travel,Business,3625,2,4,4,4,5,4,3,2,2,2,2,4,2,4,0,1.0,neutral or dissatisfied +21789,3815,Female,disloyal Customer,25,Business travel,Business,650,2,0,2,4,4,2,2,4,5,2,5,4,4,4,0,0.0,neutral or dissatisfied +21790,79121,Female,Loyal Customer,14,Personal Travel,Eco,306,2,5,2,3,3,2,3,3,5,5,4,3,5,3,0,0.0,neutral or dissatisfied +21791,91545,Male,disloyal Customer,10,Business travel,Eco,680,3,4,4,3,5,4,5,5,2,1,3,4,3,5,0,0.0,neutral or dissatisfied +21792,126714,Male,Loyal Customer,12,Business travel,Business,2402,4,4,4,4,4,4,4,4,2,5,2,4,4,4,0,0.0,neutral or dissatisfied +21793,29367,Female,Loyal Customer,47,Business travel,Business,2466,2,2,3,2,4,4,4,4,3,5,2,4,4,4,2,18.0,satisfied +21794,98433,Female,Loyal Customer,21,Personal Travel,Eco,1910,1,5,2,1,3,2,3,3,5,1,4,4,4,3,0,0.0,neutral or dissatisfied +21795,33579,Male,Loyal Customer,26,Business travel,Eco,474,5,3,3,3,5,5,5,5,2,4,5,3,2,5,0,0.0,satisfied +21796,20672,Male,disloyal Customer,37,Business travel,Eco,552,2,3,2,1,1,2,1,1,3,3,3,5,2,1,0,0.0,neutral or dissatisfied +21797,125719,Male,Loyal Customer,23,Personal Travel,Eco,759,2,2,2,3,4,2,4,4,3,5,3,3,2,4,22,16.0,neutral or dissatisfied +21798,107427,Female,Loyal Customer,26,Personal Travel,Eco,468,1,5,1,2,2,1,2,2,4,2,5,5,5,2,21,7.0,neutral or dissatisfied +21799,35949,Male,Loyal Customer,38,Business travel,Business,2185,2,2,2,2,3,3,3,4,4,4,4,4,4,3,0,21.0,satisfied +21800,90197,Female,Loyal Customer,58,Personal Travel,Eco,983,1,4,1,5,3,5,5,4,4,1,4,5,4,3,104,103.0,neutral or dissatisfied +21801,14899,Male,disloyal Customer,55,Business travel,Eco,315,3,3,3,4,4,3,4,4,3,2,3,1,4,4,63,50.0,neutral or dissatisfied +21802,18280,Female,Loyal Customer,30,Business travel,Eco Plus,228,4,5,3,5,4,3,4,4,1,4,4,1,3,4,97,95.0,neutral or dissatisfied +21803,116853,Male,Loyal Customer,48,Business travel,Business,3616,5,5,2,5,2,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +21804,99047,Female,Loyal Customer,43,Business travel,Business,237,0,0,0,5,4,5,5,2,2,1,1,3,2,3,11,8.0,satisfied +21805,51523,Male,Loyal Customer,58,Business travel,Eco,425,3,1,1,1,3,3,3,3,2,2,3,1,1,3,0,0.0,neutral or dissatisfied +21806,120672,Female,Loyal Customer,50,Business travel,Eco,280,4,5,2,5,2,4,3,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +21807,36400,Male,Loyal Customer,32,Business travel,Business,632,3,3,3,3,2,2,2,2,4,4,3,2,5,2,0,0.0,satisfied +21808,89282,Female,Loyal Customer,54,Business travel,Business,3132,5,5,5,5,5,5,4,3,3,3,3,3,3,3,0,0.0,satisfied +21809,61037,Female,Loyal Customer,31,Personal Travel,Business,1506,1,3,1,3,4,1,5,4,3,1,3,3,3,4,0,0.0,neutral or dissatisfied +21810,61234,Female,Loyal Customer,29,Business travel,Business,3784,3,1,1,1,3,3,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +21811,107676,Female,Loyal Customer,44,Business travel,Business,251,3,3,3,3,3,4,4,4,4,4,4,4,4,3,44,36.0,satisfied +21812,67938,Male,Loyal Customer,67,Personal Travel,Eco,1235,3,1,3,2,1,3,1,1,2,1,1,3,1,1,1,0.0,neutral or dissatisfied +21813,30744,Female,disloyal Customer,24,Business travel,Eco,977,5,5,5,3,3,5,3,3,1,1,1,5,5,3,7,0.0,satisfied +21814,110848,Male,Loyal Customer,54,Personal Travel,Business,404,1,5,1,5,2,4,5,2,2,1,2,3,2,3,18,32.0,neutral or dissatisfied +21815,116744,Female,Loyal Customer,58,Personal Travel,Eco Plus,371,3,5,3,3,1,4,4,1,1,3,1,5,1,2,0,0.0,neutral or dissatisfied +21816,19664,Female,disloyal Customer,23,Business travel,Eco,409,2,0,2,4,1,2,1,1,3,5,4,4,5,1,6,0.0,neutral or dissatisfied +21817,37194,Female,Loyal Customer,47,Business travel,Eco Plus,1288,2,3,3,3,5,3,3,2,2,2,2,2,2,3,73,68.0,neutral or dissatisfied +21818,110964,Male,Loyal Customer,43,Business travel,Business,197,1,4,4,4,1,4,4,4,4,4,1,3,4,1,15,9.0,neutral or dissatisfied +21819,13033,Female,Loyal Customer,31,Personal Travel,Eco,374,3,5,3,4,2,3,2,2,3,3,5,4,5,2,0,0.0,neutral or dissatisfied +21820,90873,Female,Loyal Customer,38,Business travel,Business,2238,1,2,2,2,4,4,3,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +21821,32661,Female,Loyal Customer,43,Business travel,Eco,216,5,2,5,2,4,4,2,5,5,5,5,5,5,3,0,0.0,satisfied +21822,90540,Male,Loyal Customer,30,Business travel,Business,581,1,1,1,1,2,2,2,2,3,3,5,4,4,2,96,101.0,satisfied +21823,72346,Female,Loyal Customer,56,Business travel,Business,1121,1,1,1,1,3,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +21824,41922,Female,Loyal Customer,42,Business travel,Business,129,1,1,1,1,5,1,5,4,4,4,4,1,4,4,6,0.0,satisfied +21825,88033,Female,Loyal Customer,30,Business travel,Business,3299,2,2,2,2,4,4,4,4,4,2,4,5,5,4,0,0.0,satisfied +21826,92545,Female,Loyal Customer,35,Personal Travel,Eco,1947,4,4,4,2,2,4,2,2,3,2,3,3,5,2,11,0.0,satisfied +21827,423,Female,disloyal Customer,30,Business travel,Business,270,1,2,2,1,2,2,2,2,5,3,5,5,5,2,0,0.0,neutral or dissatisfied +21828,127893,Female,disloyal Customer,35,Business travel,Business,1671,1,1,1,3,2,1,2,2,5,3,3,4,5,2,0,23.0,neutral or dissatisfied +21829,108734,Male,Loyal Customer,10,Personal Travel,Eco,591,1,4,1,5,5,1,5,5,5,4,4,5,5,5,2,5.0,neutral or dissatisfied +21830,109791,Male,Loyal Customer,26,Business travel,Business,2544,3,3,3,3,5,5,5,5,5,4,4,5,5,5,0,0.0,satisfied +21831,12432,Male,Loyal Customer,65,Personal Travel,Eco,190,3,4,0,1,1,0,1,1,4,1,1,5,1,1,0,0.0,neutral or dissatisfied +21832,30446,Male,Loyal Customer,24,Business travel,Business,991,1,1,1,1,5,5,5,5,5,1,5,5,2,5,64,55.0,satisfied +21833,7374,Male,Loyal Customer,39,Business travel,Business,2702,2,2,2,2,2,4,5,5,5,5,5,3,5,3,12,14.0,satisfied +21834,104916,Female,Loyal Customer,50,Business travel,Business,210,2,2,2,2,3,5,4,4,4,4,5,3,4,4,7,0.0,satisfied +21835,11722,Female,disloyal Customer,42,Business travel,Business,429,3,3,3,4,3,3,3,3,4,5,4,3,4,3,13,2.0,neutral or dissatisfied +21836,78632,Male,Loyal Customer,52,Business travel,Business,1426,5,5,5,5,4,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +21837,44023,Male,Loyal Customer,27,Business travel,Eco,680,0,0,0,2,4,0,4,4,3,5,2,3,2,4,57,51.0,satisfied +21838,119446,Male,disloyal Customer,22,Business travel,Eco,814,1,1,1,4,4,1,4,4,5,2,5,5,5,4,12,0.0,neutral or dissatisfied +21839,49246,Male,Loyal Customer,36,Business travel,Business,3494,4,4,5,4,1,3,1,5,5,5,5,5,5,5,0,5.0,satisfied +21840,22917,Female,disloyal Customer,35,Business travel,Eco,630,3,3,3,2,5,3,5,5,2,3,4,1,1,5,0,0.0,neutral or dissatisfied +21841,62165,Male,Loyal Customer,26,Business travel,Business,2454,1,4,4,4,1,1,1,1,1,1,2,1,3,1,0,0.0,neutral or dissatisfied +21842,6844,Male,Loyal Customer,41,Business travel,Business,2635,3,3,3,3,2,4,4,3,3,4,3,3,3,4,58,57.0,satisfied +21843,115658,Female,Loyal Customer,57,Business travel,Business,2057,5,5,5,5,2,5,5,2,2,2,2,3,2,5,12,4.0,satisfied +21844,94779,Female,Loyal Customer,53,Business travel,Business,3455,1,1,1,1,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +21845,123326,Female,disloyal Customer,30,Business travel,Eco Plus,590,2,2,2,3,1,2,1,1,2,4,4,4,4,1,50,54.0,neutral or dissatisfied +21846,122621,Female,Loyal Customer,53,Personal Travel,Eco,728,3,4,3,3,3,1,5,4,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +21847,121435,Male,Loyal Customer,70,Business travel,Eco,331,3,1,1,1,3,3,3,3,2,1,2,2,3,3,15,15.0,neutral or dissatisfied +21848,50779,Female,Loyal Customer,21,Personal Travel,Eco,109,1,2,1,2,5,1,4,5,1,1,3,1,3,5,35,55.0,neutral or dissatisfied +21849,105547,Female,Loyal Customer,11,Personal Travel,Eco,611,3,3,3,3,2,3,2,2,4,4,3,1,5,2,3,0.0,neutral or dissatisfied +21850,58025,Female,Loyal Customer,66,Personal Travel,Eco,1721,4,5,4,2,5,5,5,5,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +21851,95522,Female,disloyal Customer,65,Business travel,Eco Plus,128,3,3,3,1,4,3,5,4,4,2,2,5,5,4,0,0.0,neutral or dissatisfied +21852,7378,Male,Loyal Customer,9,Personal Travel,Eco,888,2,4,2,1,5,2,5,5,3,5,1,5,1,5,7,0.0,neutral or dissatisfied +21853,59795,Female,Loyal Customer,23,Personal Travel,Eco Plus,895,4,4,4,4,4,4,4,4,4,3,4,3,4,4,0,0.0,satisfied +21854,13461,Male,disloyal Customer,47,Personal Travel,Eco,409,1,4,3,3,2,3,2,2,3,5,3,2,4,2,1,0.0,neutral or dissatisfied +21855,93122,Female,disloyal Customer,23,Business travel,Eco,1075,3,3,3,5,2,3,2,2,3,5,5,3,5,2,41,32.0,neutral or dissatisfied +21856,10251,Male,Loyal Customer,41,Personal Travel,Business,166,4,4,4,4,3,5,4,2,2,4,2,5,2,5,0,0.0,satisfied +21857,115040,Female,Loyal Customer,52,Business travel,Business,2136,2,2,2,2,4,4,3,2,2,2,2,3,2,2,9,16.0,neutral or dissatisfied +21858,195,Male,Loyal Customer,36,Business travel,Business,3098,0,4,0,1,5,4,5,2,2,2,2,5,2,4,0,0.0,satisfied +21859,2801,Male,Loyal Customer,35,Personal Travel,Eco,764,4,4,4,4,2,4,2,2,3,4,4,5,5,2,0,0.0,satisfied +21860,78569,Male,disloyal Customer,24,Business travel,Eco,630,4,0,3,5,5,3,2,5,3,3,5,5,5,5,0,35.0,neutral or dissatisfied +21861,45607,Female,Loyal Customer,45,Business travel,Eco,313,5,4,4,4,4,5,5,5,5,5,5,2,5,5,0,1.0,satisfied +21862,63296,Male,Loyal Customer,16,Business travel,Business,3192,3,2,2,2,3,3,3,3,3,2,3,1,3,3,31,24.0,neutral or dissatisfied +21863,72800,Female,Loyal Customer,14,Personal Travel,Eco,1045,3,1,3,3,5,3,5,5,3,3,3,4,3,5,5,0.0,neutral or dissatisfied +21864,81886,Female,disloyal Customer,22,Business travel,Eco,680,0,0,0,4,3,0,3,3,3,4,4,4,4,3,0,0.0,satisfied +21865,100974,Female,disloyal Customer,50,Business travel,Business,1524,4,4,4,5,1,4,1,1,4,4,4,4,4,1,0,0.0,satisfied +21866,119848,Male,Loyal Customer,45,Business travel,Business,512,2,2,4,2,3,4,1,4,4,4,4,3,4,5,0,0.0,satisfied +21867,951,Female,Loyal Customer,44,Business travel,Business,3063,2,4,4,4,4,3,3,2,2,1,2,3,2,4,0,1.0,neutral or dissatisfied +21868,43642,Female,Loyal Customer,57,Business travel,Business,1908,4,4,4,4,2,2,2,2,2,2,2,2,2,5,0,0.0,satisfied +21869,68599,Male,Loyal Customer,52,Business travel,Business,1739,2,4,2,2,5,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +21870,34212,Male,Loyal Customer,49,Personal Travel,Eco,1237,4,1,5,3,5,2,4,4,4,2,4,4,1,4,266,255.0,neutral or dissatisfied +21871,46295,Female,Loyal Customer,26,Business travel,Business,2667,3,4,4,4,3,3,3,3,2,1,3,4,4,3,2,8.0,neutral or dissatisfied +21872,75597,Female,Loyal Customer,36,Personal Travel,Eco,337,3,5,3,2,1,3,1,1,4,2,5,3,5,1,0,0.0,neutral or dissatisfied +21873,34578,Male,disloyal Customer,27,Business travel,Eco,1576,5,5,5,3,5,5,5,2,5,4,5,5,2,5,211,219.0,satisfied +21874,113248,Female,Loyal Customer,19,Personal Travel,Business,391,1,5,1,3,1,1,1,1,5,3,4,5,5,1,34,33.0,neutral or dissatisfied +21875,81045,Male,Loyal Customer,45,Business travel,Business,1399,5,5,4,5,2,4,4,5,5,5,5,5,5,3,4,4.0,satisfied +21876,23628,Female,disloyal Customer,14,Business travel,Eco,752,5,5,5,2,5,0,5,5,3,2,3,2,2,5,115,109.0,satisfied +21877,73751,Male,Loyal Customer,28,Personal Travel,Eco,204,1,2,1,3,5,1,5,5,1,5,2,4,2,5,59,54.0,neutral or dissatisfied +21878,58923,Female,Loyal Customer,38,Personal Travel,Eco,888,2,4,1,2,4,1,4,4,5,2,4,3,4,4,16,0.0,neutral or dissatisfied +21879,42899,Male,Loyal Customer,36,Business travel,Business,2214,1,2,2,2,5,4,3,3,3,3,1,1,3,1,27,22.0,neutral or dissatisfied +21880,50946,Female,Loyal Customer,42,Personal Travel,Eco,326,4,4,4,4,4,3,3,3,2,2,3,3,1,3,283,276.0,neutral or dissatisfied +21881,36205,Male,Loyal Customer,55,Business travel,Business,3866,2,2,2,2,4,2,5,4,4,4,4,1,4,5,0,0.0,satisfied +21882,43762,Female,Loyal Customer,52,Business travel,Business,481,3,3,5,5,1,4,3,3,3,2,3,2,3,4,0,0.0,neutral or dissatisfied +21883,120191,Female,Loyal Customer,48,Business travel,Business,1303,1,1,1,1,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +21884,65174,Female,Loyal Customer,11,Personal Travel,Eco,247,1,1,1,2,4,1,4,4,3,3,3,1,3,4,17,18.0,neutral or dissatisfied +21885,33001,Male,Loyal Customer,20,Personal Travel,Eco,101,3,5,3,4,4,3,4,4,3,5,5,5,5,4,0,0.0,neutral or dissatisfied +21886,79878,Male,disloyal Customer,21,Business travel,Business,950,4,0,4,4,2,4,2,2,4,3,4,3,5,2,13,2.0,satisfied +21887,64261,Male,disloyal Customer,25,Business travel,Eco,744,3,3,3,2,5,3,5,5,3,4,5,4,4,5,0,0.0,neutral or dissatisfied +21888,52868,Male,disloyal Customer,18,Business travel,Eco,836,2,2,2,4,3,2,3,3,3,4,4,3,4,3,0,0.0,neutral or dissatisfied +21889,90459,Male,Loyal Customer,52,Business travel,Business,1773,5,5,5,5,3,5,5,5,5,5,5,3,5,3,0,8.0,satisfied +21890,46172,Female,Loyal Customer,25,Personal Travel,Eco,604,3,5,3,2,2,3,1,2,5,3,4,5,4,2,97,104.0,neutral or dissatisfied +21891,14858,Female,Loyal Customer,37,Business travel,Business,315,1,3,3,3,1,3,4,1,1,2,1,3,1,3,73,59.0,neutral or dissatisfied +21892,122766,Female,disloyal Customer,37,Business travel,Eco Plus,651,2,2,2,3,4,2,1,4,2,3,3,4,3,4,0,0.0,neutral or dissatisfied +21893,87719,Male,Loyal Customer,41,Business travel,Eco Plus,606,1,5,5,5,1,1,1,4,5,3,3,1,2,1,157,145.0,neutral or dissatisfied +21894,18151,Male,Loyal Customer,17,Personal Travel,Eco,296,3,4,3,1,3,3,2,5,2,4,5,2,3,2,219,209.0,neutral or dissatisfied +21895,82415,Female,Loyal Customer,37,Personal Travel,Business,502,2,5,2,5,2,5,5,1,1,2,1,4,1,4,0,0.0,neutral or dissatisfied +21896,32582,Female,disloyal Customer,17,Business travel,Eco,216,0,1,0,4,4,0,4,4,4,3,3,4,3,4,0,0.0,satisfied +21897,30506,Male,Loyal Customer,39,Business travel,Business,1620,2,2,2,2,3,4,4,4,4,4,4,2,4,2,46,83.0,satisfied +21898,128315,Male,Loyal Customer,60,Business travel,Business,651,4,4,4,4,3,5,4,5,5,5,5,4,5,3,54,55.0,satisfied +21899,106125,Female,disloyal Customer,30,Business travel,Eco,302,3,3,3,2,5,3,5,5,4,3,3,1,3,5,8,1.0,neutral or dissatisfied +21900,44386,Female,Loyal Customer,61,Personal Travel,Business,342,4,4,4,4,2,5,5,3,3,4,3,5,3,3,0,0.0,satisfied +21901,28402,Male,disloyal Customer,17,Business travel,Eco,1489,5,5,5,5,2,5,2,2,1,3,4,5,5,2,0,0.0,satisfied +21902,54094,Female,Loyal Customer,50,Personal Travel,Eco,1416,4,1,4,3,2,4,3,3,3,4,3,1,3,1,4,6.0,neutral or dissatisfied +21903,117336,Female,disloyal Customer,59,Business travel,Business,296,2,2,2,4,3,2,3,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +21904,7304,Female,Loyal Customer,35,Business travel,Business,139,5,5,5,5,5,5,4,4,4,4,5,3,4,4,0,0.0,satisfied +21905,72712,Male,Loyal Customer,46,Business travel,Business,3414,2,2,2,2,2,5,5,4,4,4,4,4,4,4,6,15.0,satisfied +21906,31720,Male,Loyal Customer,54,Personal Travel,Eco,846,1,5,1,4,3,1,3,3,5,5,4,4,5,3,31,27.0,neutral or dissatisfied +21907,90926,Female,Loyal Customer,24,Business travel,Business,2507,2,5,5,5,2,2,2,3,1,3,3,2,3,2,756,748.0,neutral or dissatisfied +21908,55189,Female,Loyal Customer,60,Business travel,Eco Plus,1379,2,5,5,5,4,3,4,2,2,2,2,2,2,3,10,14.0,neutral or dissatisfied +21909,99234,Female,disloyal Customer,27,Business travel,Eco,541,2,2,2,4,3,2,3,3,1,2,4,2,4,3,4,6.0,neutral or dissatisfied +21910,104439,Female,Loyal Customer,68,Personal Travel,Eco,1147,3,1,3,3,3,4,3,2,2,3,2,2,2,3,22,15.0,neutral or dissatisfied +21911,12765,Male,Loyal Customer,37,Personal Travel,Eco,689,1,4,1,5,3,1,3,3,5,3,4,4,4,3,0,0.0,neutral or dissatisfied +21912,3122,Female,Loyal Customer,28,Personal Travel,Eco,1013,4,2,4,3,5,4,5,5,2,5,3,3,3,5,0,0.0,satisfied +21913,80748,Female,Loyal Customer,19,Personal Travel,Eco,393,3,5,3,5,4,3,4,4,1,5,4,4,2,4,22,8.0,neutral or dissatisfied +21914,30389,Male,Loyal Customer,17,Personal Travel,Eco,862,3,5,3,1,3,3,2,3,3,4,5,3,5,3,0,4.0,neutral or dissatisfied +21915,97765,Female,Loyal Customer,46,Business travel,Eco Plus,587,2,4,4,4,3,4,3,2,2,2,2,1,2,1,57,60.0,neutral or dissatisfied +21916,59103,Female,Loyal Customer,9,Personal Travel,Eco,1744,4,4,4,4,5,4,5,5,5,4,5,4,4,5,0,0.0,neutral or dissatisfied +21917,75904,Female,disloyal Customer,23,Business travel,Eco,197,2,2,2,4,3,2,3,3,1,5,3,3,3,3,0,9.0,neutral or dissatisfied +21918,72578,Female,Loyal Customer,36,Business travel,Business,585,2,5,3,3,5,4,3,2,2,2,2,3,2,4,67,68.0,neutral or dissatisfied +21919,108620,Female,Loyal Customer,29,Personal Travel,Eco,696,2,4,2,2,4,2,4,4,4,5,5,4,4,4,0,0.0,neutral or dissatisfied +21920,85880,Female,Loyal Customer,46,Business travel,Business,2172,4,4,4,4,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +21921,31526,Female,Loyal Customer,66,Personal Travel,Eco,853,4,5,4,3,3,4,4,3,3,4,3,4,3,3,0,20.0,satisfied +21922,35878,Female,Loyal Customer,23,Personal Travel,Eco,1023,3,5,3,3,2,3,2,2,3,4,5,3,2,2,69,67.0,neutral or dissatisfied +21923,796,Female,disloyal Customer,37,Business travel,Business,158,3,3,3,4,3,3,3,3,4,4,4,1,3,3,0,0.0,neutral or dissatisfied +21924,106712,Female,Loyal Customer,52,Business travel,Business,2426,2,2,3,2,2,5,4,4,4,4,4,3,4,4,0,9.0,satisfied +21925,62827,Male,Loyal Customer,46,Personal Travel,Eco,2367,3,5,3,5,1,3,1,1,5,2,4,5,5,1,0,0.0,neutral or dissatisfied +21926,26151,Male,Loyal Customer,25,Business travel,Business,1792,5,5,5,5,5,5,5,5,4,4,5,5,4,5,0,0.0,satisfied +21927,46575,Male,Loyal Customer,69,Business travel,Business,73,2,2,2,2,1,2,2,2,3,4,3,2,3,2,565,586.0,neutral or dissatisfied +21928,104733,Female,Loyal Customer,39,Business travel,Eco,1246,3,4,4,4,3,3,3,3,2,4,4,1,4,3,0,0.0,neutral or dissatisfied +21929,16304,Male,disloyal Customer,38,Business travel,Eco,594,1,0,1,2,4,1,4,4,1,2,3,2,5,4,0,0.0,neutral or dissatisfied +21930,89337,Female,Loyal Customer,26,Business travel,Eco,1587,2,5,4,4,2,2,2,2,3,4,4,4,3,2,11,19.0,neutral or dissatisfied +21931,122667,Male,disloyal Customer,37,Business travel,Business,361,3,3,3,4,4,3,4,4,3,2,5,5,4,4,0,0.0,neutral or dissatisfied +21932,51878,Female,Loyal Customer,58,Business travel,Eco Plus,771,5,5,5,5,3,1,3,5,5,5,5,5,5,4,0,0.0,satisfied +21933,49509,Female,Loyal Customer,43,Business travel,Business,3389,3,3,5,3,1,2,3,5,5,5,5,5,5,5,0,0.0,satisfied +21934,54201,Male,Loyal Customer,18,Personal Travel,Eco,1504,0,4,0,1,3,0,3,3,3,2,5,3,4,3,0,0.0,satisfied +21935,92999,Male,Loyal Customer,35,Personal Travel,Eco Plus,738,5,5,5,4,4,5,3,4,3,2,4,4,5,4,0,30.0,satisfied +21936,82406,Male,Loyal Customer,56,Personal Travel,Eco,500,3,3,3,4,3,3,3,3,4,1,4,4,3,3,0,0.0,neutral or dissatisfied +21937,72782,Female,disloyal Customer,25,Business travel,Eco,1045,3,3,3,4,5,3,5,5,4,3,3,4,3,5,71,68.0,neutral or dissatisfied +21938,20904,Male,Loyal Customer,58,Personal Travel,Business,689,3,5,3,5,2,4,5,2,2,3,2,5,2,4,46,41.0,neutral or dissatisfied +21939,120374,Male,Loyal Customer,66,Business travel,Business,413,2,3,3,3,4,2,3,2,2,2,2,2,2,2,0,4.0,neutral or dissatisfied +21940,13284,Female,Loyal Customer,40,Personal Travel,Eco,468,3,5,3,1,3,3,3,3,4,2,4,3,5,3,15,0.0,neutral or dissatisfied +21941,1242,Male,Loyal Customer,54,Personal Travel,Eco,134,3,0,3,5,5,3,5,5,5,2,4,4,5,5,0,0.0,neutral or dissatisfied +21942,56026,Female,disloyal Customer,26,Business travel,Business,2586,3,3,3,2,3,3,3,5,5,5,4,3,4,3,36,10.0,neutral or dissatisfied +21943,65231,Male,Loyal Customer,50,Business travel,Business,3641,5,5,5,5,2,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +21944,17206,Female,Loyal Customer,63,Personal Travel,Eco,694,0,5,0,1,2,5,4,5,5,0,5,4,5,4,0,0.0,satisfied +21945,13196,Female,Loyal Customer,44,Business travel,Business,142,3,3,5,3,5,5,4,5,5,5,3,5,5,4,9,0.0,satisfied +21946,8288,Male,Loyal Customer,60,Personal Travel,Eco,294,2,4,2,4,2,2,2,2,5,5,4,3,5,2,0,0.0,neutral or dissatisfied +21947,118093,Male,Loyal Customer,44,Personal Travel,Eco Plus,1276,2,4,2,3,5,2,1,5,3,3,3,5,5,5,43,27.0,neutral or dissatisfied +21948,122437,Female,Loyal Customer,68,Personal Travel,Eco,1916,1,4,1,5,5,3,1,3,3,1,3,3,3,5,0,0.0,neutral or dissatisfied +21949,58733,Male,disloyal Customer,27,Business travel,Business,1050,4,4,4,3,2,4,2,2,3,3,4,5,4,2,0,0.0,satisfied +21950,47241,Male,disloyal Customer,12,Business travel,Eco,599,5,0,5,4,4,5,4,4,3,5,4,4,4,4,0,0.0,satisfied +21951,126865,Female,Loyal Customer,9,Personal Travel,Eco,2125,1,5,2,5,3,2,1,3,3,1,4,4,1,3,0,0.0,neutral or dissatisfied +21952,33267,Male,Loyal Customer,48,Personal Travel,Eco Plus,101,2,5,2,2,5,2,2,5,5,4,5,4,5,5,16,16.0,neutral or dissatisfied +21953,116251,Female,Loyal Customer,53,Personal Travel,Eco,480,3,4,3,3,2,3,4,3,3,3,5,2,3,1,0,,neutral or dissatisfied +21954,59644,Female,Loyal Customer,42,Business travel,Business,3665,5,5,5,5,3,4,2,5,5,5,5,1,5,3,0,0.0,satisfied +21955,76698,Female,Loyal Customer,56,Personal Travel,Eco,547,2,0,3,2,2,3,4,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +21956,100975,Male,Loyal Customer,43,Business travel,Business,1524,2,2,2,2,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +21957,16916,Female,disloyal Customer,27,Business travel,Eco Plus,746,1,1,1,4,4,1,4,4,4,4,4,1,4,4,86,77.0,neutral or dissatisfied +21958,125221,Female,Loyal Customer,57,Personal Travel,Eco,651,4,4,4,1,2,3,3,3,3,4,3,5,3,1,7,0.0,satisfied +21959,33458,Female,Loyal Customer,27,Business travel,Eco Plus,2399,0,0,0,3,5,0,5,5,1,2,5,4,1,5,0,6.0,satisfied +21960,64124,Male,Loyal Customer,31,Personal Travel,Eco,2311,5,1,5,2,5,1,5,5,4,4,1,1,1,5,2,0.0,satisfied +21961,4672,Female,Loyal Customer,38,Business travel,Business,489,2,2,2,2,4,3,2,2,2,2,2,3,2,3,9,10.0,neutral or dissatisfied +21962,96472,Female,Loyal Customer,51,Business travel,Business,302,3,5,3,3,2,5,4,5,5,5,5,4,5,4,1,0.0,satisfied +21963,124492,Female,Loyal Customer,29,Business travel,Business,2700,4,4,4,4,4,4,4,4,4,5,5,5,4,4,0,0.0,satisfied +21964,51474,Female,Loyal Customer,45,Business travel,Business,261,5,5,5,5,4,5,4,4,4,5,4,3,4,5,0,0.0,satisfied +21965,114668,Male,disloyal Customer,24,Business travel,Eco,358,1,4,1,3,2,1,2,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +21966,110603,Female,Loyal Customer,69,Personal Travel,Eco,674,2,1,2,3,3,4,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +21967,86434,Male,disloyal Customer,52,Business travel,Eco,762,1,0,0,4,3,0,3,3,3,4,4,2,3,3,0,0.0,neutral or dissatisfied +21968,123390,Female,Loyal Customer,28,Business travel,Business,1337,3,3,3,3,5,5,5,5,5,3,5,3,5,5,17,4.0,satisfied +21969,64710,Female,Loyal Customer,34,Business travel,Business,551,4,4,4,4,4,4,5,5,5,5,5,5,5,3,14,46.0,satisfied +21970,103191,Male,disloyal Customer,18,Business travel,Eco,814,0,0,0,1,5,0,5,5,5,2,4,5,5,5,55,58.0,satisfied +21971,66118,Male,Loyal Customer,39,Business travel,Business,583,3,3,3,3,4,4,5,4,4,4,4,5,4,3,66,61.0,satisfied +21972,79634,Female,Loyal Customer,48,Business travel,Eco,712,2,4,4,4,1,2,3,2,2,2,2,2,2,2,0,19.0,neutral or dissatisfied +21973,55757,Female,Loyal Customer,16,Personal Travel,Eco,1737,2,5,2,3,1,2,1,1,4,5,4,5,4,1,0,3.0,neutral or dissatisfied +21974,99967,Male,disloyal Customer,19,Business travel,Eco,888,2,2,2,4,1,2,1,1,4,2,3,4,4,1,0,0.0,neutral or dissatisfied +21975,51494,Male,Loyal Customer,33,Personal Travel,Business,370,3,4,3,3,2,3,2,2,4,4,3,1,3,2,4,0.0,neutral or dissatisfied +21976,59605,Male,Loyal Customer,44,Business travel,Business,3829,1,1,1,1,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +21977,23087,Male,Loyal Customer,56,Personal Travel,Eco,864,2,5,2,1,5,2,5,5,4,3,5,5,5,5,0,0.0,neutral or dissatisfied +21978,96349,Female,Loyal Customer,25,Personal Travel,Eco,1609,1,1,1,4,5,1,5,5,1,2,2,4,4,5,20,6.0,neutral or dissatisfied +21979,63369,Female,Loyal Customer,46,Personal Travel,Eco,447,5,4,5,1,4,5,5,5,5,5,5,3,5,5,23,15.0,satisfied +21980,29422,Male,Loyal Customer,50,Personal Travel,Eco Plus,2676,3,3,3,4,3,2,2,4,1,3,3,2,5,2,0,0.0,neutral or dissatisfied +21981,7684,Male,Loyal Customer,64,Business travel,Eco,204,5,3,3,3,5,5,5,5,5,2,1,1,4,5,0,0.0,satisfied +21982,43887,Male,Loyal Customer,36,Business travel,Business,199,2,2,2,2,3,1,3,5,5,5,4,4,5,4,0,0.0,satisfied +21983,20774,Male,Loyal Customer,38,Business travel,Business,2531,1,1,1,1,2,1,2,3,3,4,3,4,3,5,0,3.0,satisfied +21984,14277,Male,disloyal Customer,40,Business travel,Eco,429,2,0,2,4,1,2,1,1,1,3,4,2,5,1,0,0.0,neutral or dissatisfied +21985,40085,Female,Loyal Customer,44,Business travel,Eco Plus,493,4,5,4,5,3,1,2,4,4,4,4,1,4,2,0,0.0,satisfied +21986,34068,Female,Loyal Customer,17,Personal Travel,Eco,1674,1,4,1,5,5,1,5,5,3,3,3,5,2,5,41,40.0,neutral or dissatisfied +21987,49947,Male,Loyal Customer,59,Business travel,Business,3120,0,0,0,3,1,4,1,4,4,4,4,1,4,2,15,14.0,satisfied +21988,42329,Female,Loyal Customer,25,Personal Travel,Eco,550,3,2,2,3,2,2,2,2,1,1,4,4,4,2,3,3.0,neutral or dissatisfied +21989,93319,Female,Loyal Customer,56,Business travel,Business,3489,2,2,2,2,2,4,5,4,4,4,4,5,4,5,8,0.0,satisfied +21990,39230,Female,Loyal Customer,39,Business travel,Eco,67,5,1,1,1,5,5,5,1,5,3,4,5,5,5,358,410.0,satisfied +21991,127651,Female,disloyal Customer,21,Business travel,Eco,1773,1,1,1,3,3,1,3,3,5,2,4,3,4,3,10,15.0,neutral or dissatisfied +21992,33569,Female,disloyal Customer,35,Business travel,Eco,413,4,3,4,3,4,4,4,4,4,3,2,4,4,4,52,43.0,neutral or dissatisfied +21993,85352,Male,disloyal Customer,17,Business travel,Eco,731,3,3,3,3,2,3,2,2,2,1,3,1,3,2,0,0.0,neutral or dissatisfied +21994,44659,Male,Loyal Customer,47,Business travel,Business,160,2,4,4,4,5,4,4,3,3,3,2,1,3,2,21,52.0,neutral or dissatisfied +21995,74432,Female,Loyal Customer,54,Business travel,Business,1464,5,5,5,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +21996,127476,Male,disloyal Customer,28,Business travel,Business,2075,4,4,4,4,1,4,1,1,4,5,4,4,5,1,0,0.0,satisfied +21997,2638,Female,Loyal Customer,43,Business travel,Business,1557,4,4,4,4,2,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +21998,90988,Female,Loyal Customer,44,Business travel,Eco,406,2,1,1,1,1,4,3,2,2,2,2,4,2,4,15,10.0,neutral or dissatisfied +21999,12430,Male,Loyal Customer,62,Personal Travel,Eco,253,3,2,0,4,1,0,1,1,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +22000,63948,Male,Loyal Customer,54,Personal Travel,Eco,1192,1,5,1,3,3,1,4,3,4,5,4,5,4,3,1,3.0,neutral or dissatisfied +22001,128943,Male,disloyal Customer,20,Business travel,Eco,414,2,1,2,3,5,2,5,5,1,2,3,2,2,5,0,0.0,neutral or dissatisfied +22002,52393,Male,Loyal Customer,8,Personal Travel,Eco,370,2,1,4,3,3,4,3,3,3,3,3,1,4,3,19,12.0,neutral or dissatisfied +22003,93936,Male,disloyal Customer,52,Business travel,Eco,507,2,4,3,4,5,3,5,5,1,1,3,2,4,5,0,0.0,neutral or dissatisfied +22004,115424,Male,disloyal Customer,20,Business travel,Business,390,5,5,5,1,1,5,1,1,5,2,5,4,4,1,74,69.0,satisfied +22005,97960,Female,Loyal Customer,64,Personal Travel,Eco,612,4,4,4,4,3,3,2,2,2,4,2,4,2,3,11,32.0,satisfied +22006,33677,Female,Loyal Customer,22,Personal Travel,Business,667,4,4,4,3,4,4,4,4,5,3,4,5,5,4,0,0.0,neutral or dissatisfied +22007,91873,Male,Loyal Customer,46,Business travel,Business,2475,3,3,3,3,4,4,4,3,3,5,5,4,4,4,530,,satisfied +22008,66983,Male,Loyal Customer,28,Business travel,Business,3112,4,4,4,4,5,4,5,5,3,3,5,5,4,5,0,0.0,satisfied +22009,126344,Male,Loyal Customer,61,Personal Travel,Eco,328,3,4,3,1,3,3,3,3,1,1,5,4,2,3,0,0.0,neutral or dissatisfied +22010,126379,Female,Loyal Customer,17,Personal Travel,Eco,631,2,5,2,2,1,2,1,1,4,5,5,5,5,1,101,118.0,neutral or dissatisfied +22011,111730,Male,Loyal Customer,63,Business travel,Business,495,2,2,2,2,2,5,5,5,5,5,5,5,5,4,16,9.0,satisfied +22012,84686,Male,Loyal Customer,32,Personal Travel,Eco,2182,1,3,0,1,4,0,4,4,2,5,4,2,3,4,0,0.0,neutral or dissatisfied +22013,116091,Female,Loyal Customer,13,Personal Travel,Eco,362,1,5,1,3,5,1,5,5,5,2,5,5,4,5,26,18.0,neutral or dissatisfied +22014,50903,Male,Loyal Customer,67,Personal Travel,Eco,89,3,1,3,3,3,3,3,3,4,1,3,2,4,3,0,0.0,neutral or dissatisfied +22015,127922,Male,Loyal Customer,24,Business travel,Business,2300,2,2,2,2,4,5,4,4,3,5,4,5,4,4,0,0.0,satisfied +22016,28811,Female,disloyal Customer,49,Business travel,Eco,954,2,3,3,2,4,3,5,4,4,2,2,5,3,4,0,0.0,neutral or dissatisfied +22017,11973,Male,Loyal Customer,46,Business travel,Business,3577,5,5,5,5,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +22018,111416,Female,Loyal Customer,45,Personal Travel,Business,896,4,5,4,4,4,1,1,5,3,5,4,1,4,1,142,134.0,neutral or dissatisfied +22019,123853,Male,Loyal Customer,55,Business travel,Eco,544,3,3,3,3,3,3,3,3,3,5,2,3,3,3,0,11.0,neutral or dissatisfied +22020,38378,Female,Loyal Customer,46,Personal Travel,Eco,1173,3,4,3,2,3,4,4,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +22021,71746,Female,Loyal Customer,55,Business travel,Business,1744,4,4,4,4,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +22022,83123,Female,Loyal Customer,28,Personal Travel,Eco,1145,1,5,1,2,4,1,4,4,3,5,3,4,5,4,0,0.0,neutral or dissatisfied +22023,116773,Male,Loyal Customer,24,Personal Travel,Eco Plus,337,2,3,2,3,1,2,1,1,4,5,3,3,3,1,39,44.0,neutral or dissatisfied +22024,119149,Male,Loyal Customer,47,Business travel,Business,3928,4,5,4,4,5,5,5,4,4,4,4,5,4,3,0,11.0,satisfied +22025,102367,Male,disloyal Customer,23,Business travel,Eco,386,2,2,2,3,5,2,5,5,3,4,3,1,3,5,0,0.0,neutral or dissatisfied +22026,822,Male,Loyal Customer,47,Business travel,Business,158,5,5,4,5,3,4,4,3,3,4,4,4,3,4,0,0.0,satisfied +22027,114164,Female,Loyal Customer,37,Business travel,Business,819,3,3,3,3,5,4,5,4,4,4,4,5,4,5,53,55.0,satisfied +22028,4231,Male,Loyal Customer,28,Business travel,Business,2072,5,5,5,5,5,5,5,5,3,4,4,5,5,5,60,121.0,satisfied +22029,113768,Male,Loyal Customer,60,Personal Travel,Eco,226,3,5,3,4,2,3,3,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +22030,57863,Male,Loyal Customer,39,Business travel,Business,955,3,3,3,3,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +22031,114754,Female,Loyal Customer,37,Business travel,Business,2025,2,3,4,3,1,3,4,2,2,2,2,4,2,2,0,0.0,neutral or dissatisfied +22032,13714,Female,Loyal Customer,41,Business travel,Business,2097,1,1,1,1,4,2,4,5,5,4,5,1,5,2,14,16.0,satisfied +22033,33554,Male,disloyal Customer,39,Business travel,Eco,413,2,0,2,5,3,2,3,3,4,3,1,4,2,3,0,0.0,neutral or dissatisfied +22034,5284,Male,Loyal Customer,9,Personal Travel,Eco,383,3,5,3,1,4,3,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +22035,81109,Male,disloyal Customer,29,Business travel,Eco,991,2,2,2,2,1,2,1,1,4,3,3,2,2,1,5,0.0,neutral or dissatisfied +22036,49344,Female,Loyal Customer,57,Business travel,Business,1605,5,5,5,5,3,1,3,4,4,4,5,1,4,4,29,49.0,satisfied +22037,114718,Female,Loyal Customer,43,Business travel,Business,3607,4,4,4,4,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +22038,54214,Male,Loyal Customer,44,Personal Travel,Eco Plus,1400,0,3,0,2,1,0,1,1,5,5,1,2,1,1,7,0.0,satisfied +22039,24944,Male,Loyal Customer,38,Business travel,Business,1747,1,3,1,1,4,5,1,5,5,5,5,4,5,2,26,4.0,satisfied +22040,83301,Male,Loyal Customer,23,Business travel,Eco Plus,1956,4,2,2,2,4,4,2,4,1,1,2,2,4,4,3,0.0,neutral or dissatisfied +22041,72490,Female,Loyal Customer,40,Business travel,Business,1705,1,1,1,1,5,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +22042,79539,Female,Loyal Customer,48,Business travel,Business,2976,3,3,3,3,2,4,4,5,5,5,5,4,5,4,16,5.0,satisfied +22043,11276,Male,Loyal Customer,64,Personal Travel,Eco,458,2,1,2,4,3,2,3,3,3,1,3,4,4,3,0,0.0,neutral or dissatisfied +22044,112736,Male,Loyal Customer,49,Business travel,Business,723,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +22045,55966,Male,Loyal Customer,45,Business travel,Business,1620,4,5,5,5,5,2,4,4,4,4,4,4,4,4,1,18.0,neutral or dissatisfied +22046,124721,Female,Loyal Customer,9,Personal Travel,Eco,399,1,4,1,3,4,1,4,4,3,5,4,3,5,4,0,19.0,neutral or dissatisfied +22047,16197,Male,Loyal Customer,53,Personal Travel,Eco,277,4,4,0,4,5,0,4,5,2,4,4,1,3,5,12,25.0,satisfied +22048,80192,Male,Loyal Customer,47,Personal Travel,Eco,2586,1,3,1,2,1,3,3,4,1,3,2,3,3,3,26,19.0,neutral or dissatisfied +22049,66414,Male,Loyal Customer,19,Personal Travel,Eco,1562,4,4,4,2,4,4,4,4,5,2,4,4,5,4,0,0.0,neutral or dissatisfied +22050,108315,Female,Loyal Customer,35,Business travel,Business,1728,2,4,4,4,3,2,4,2,2,2,2,4,2,2,0,6.0,neutral or dissatisfied +22051,104831,Male,disloyal Customer,38,Business travel,Business,472,4,4,4,5,5,4,5,5,4,4,4,5,4,5,52,49.0,satisfied +22052,104771,Female,Loyal Customer,29,Personal Travel,Eco Plus,1246,3,4,3,3,2,3,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +22053,79089,Male,Loyal Customer,11,Personal Travel,Eco,226,2,4,2,3,3,2,3,3,4,3,4,3,1,3,0,0.0,neutral or dissatisfied +22054,105192,Male,Loyal Customer,48,Personal Travel,Eco,281,4,5,4,3,3,4,3,3,1,5,3,1,5,3,11,1.0,neutral or dissatisfied +22055,76784,Male,Loyal Customer,32,Business travel,Eco,689,3,1,1,1,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +22056,41309,Female,Loyal Customer,36,Business travel,Business,2116,1,1,1,1,2,4,2,5,5,5,5,3,5,5,52,70.0,satisfied +22057,97297,Female,Loyal Customer,49,Business travel,Business,843,2,2,2,2,3,5,5,4,4,3,4,5,4,3,3,5.0,satisfied +22058,12990,Male,disloyal Customer,42,Business travel,Eco,438,2,0,2,2,2,2,2,2,3,1,3,4,5,2,34,36.0,neutral or dissatisfied +22059,62202,Female,Loyal Customer,13,Personal Travel,Eco,2434,2,5,2,3,2,2,2,2,3,3,3,3,5,2,0,0.0,neutral or dissatisfied +22060,90095,Female,Loyal Customer,38,Business travel,Business,2638,3,3,3,3,4,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +22061,96063,Female,Loyal Customer,16,Personal Travel,Eco,1069,0,5,0,2,2,0,2,2,5,2,5,5,4,2,0,0.0,satisfied +22062,30567,Female,Loyal Customer,24,Business travel,Business,628,3,3,5,3,5,5,5,5,1,5,5,1,4,5,0,0.0,satisfied +22063,7636,Female,disloyal Customer,20,Business travel,Business,604,0,4,0,2,1,0,1,1,3,4,5,4,4,1,0,3.0,satisfied +22064,6343,Male,Loyal Customer,55,Business travel,Business,296,1,1,1,1,5,4,5,5,5,5,5,3,5,4,16,6.0,satisfied +22065,104673,Female,Loyal Customer,22,Personal Travel,Eco,641,3,5,4,1,2,4,2,2,5,2,5,4,5,2,41,50.0,neutral or dissatisfied +22066,127307,Male,Loyal Customer,30,Business travel,Business,1979,5,5,3,5,5,5,5,5,5,5,4,3,5,5,25,24.0,satisfied +22067,34122,Male,disloyal Customer,25,Business travel,Eco,1046,2,2,2,1,5,2,5,5,2,5,3,1,5,5,0,0.0,neutral or dissatisfied +22068,114262,Female,Loyal Customer,58,Business travel,Business,2127,4,2,2,2,2,3,4,4,4,4,4,3,4,3,1,0.0,neutral or dissatisfied +22069,120110,Male,Loyal Customer,20,Business travel,Business,1576,3,1,2,2,3,3,3,3,2,1,4,4,3,3,1,24.0,neutral or dissatisfied +22070,93573,Female,disloyal Customer,20,Business travel,Eco,159,2,4,3,3,5,3,5,5,2,2,4,3,3,5,9,42.0,neutral or dissatisfied +22071,103904,Female,disloyal Customer,50,Business travel,Eco Plus,1048,2,2,2,3,4,2,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +22072,44931,Male,Loyal Customer,44,Business travel,Business,1642,5,5,5,5,3,5,5,5,5,5,5,3,5,5,3,1.0,satisfied +22073,117081,Male,Loyal Customer,58,Business travel,Business,1747,1,3,3,3,5,2,2,1,1,1,1,4,1,2,29,21.0,neutral or dissatisfied +22074,58962,Female,Loyal Customer,40,Business travel,Business,1744,4,4,4,4,3,2,3,4,4,4,4,3,4,2,13,31.0,neutral or dissatisfied +22075,50941,Female,Loyal Customer,31,Personal Travel,Eco,109,4,2,4,2,4,4,4,4,1,4,2,1,2,4,0,0.0,neutral or dissatisfied +22076,67244,Male,Loyal Customer,62,Personal Travel,Eco,1017,1,3,2,4,1,2,1,1,3,4,4,3,4,1,0,3.0,neutral or dissatisfied +22077,76145,Male,Loyal Customer,50,Business travel,Eco,689,2,4,4,4,2,2,2,2,3,1,3,1,4,2,1,0.0,neutral or dissatisfied +22078,56677,Female,Loyal Customer,69,Personal Travel,Eco,937,4,4,4,3,2,3,3,3,3,4,3,2,3,3,1,17.0,neutral or dissatisfied +22079,20122,Male,Loyal Customer,38,Personal Travel,Eco,466,3,4,3,1,1,3,4,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +22080,108577,Female,Loyal Customer,39,Business travel,Business,2459,2,2,2,2,5,4,5,4,4,4,4,5,4,3,21,9.0,satisfied +22081,8324,Female,Loyal Customer,31,Personal Travel,Eco Plus,125,1,1,1,4,5,1,5,5,3,5,3,2,3,5,0,0.0,neutral or dissatisfied +22082,6262,Male,Loyal Customer,46,Business travel,Business,2327,3,3,3,3,4,5,4,4,4,4,4,5,4,4,23,22.0,satisfied +22083,75778,Female,Loyal Customer,42,Personal Travel,Eco,868,2,2,2,4,5,3,3,1,1,2,1,4,1,1,0,0.0,neutral or dissatisfied +22084,106662,Male,disloyal Customer,20,Business travel,Eco,1590,3,3,3,1,2,3,2,2,4,2,3,3,2,2,9,0.0,neutral or dissatisfied +22085,22187,Male,Loyal Customer,29,Business travel,Business,1995,2,5,5,5,2,2,2,2,3,3,3,3,3,2,49,45.0,neutral or dissatisfied +22086,21727,Male,disloyal Customer,23,Business travel,Eco,563,1,5,1,5,1,1,1,1,1,4,5,4,3,1,109,117.0,neutral or dissatisfied +22087,81180,Male,Loyal Customer,43,Business travel,Business,2204,1,1,1,1,2,5,5,4,4,4,4,5,4,3,13,21.0,satisfied +22088,34117,Female,Loyal Customer,22,Business travel,Eco,1179,4,1,1,1,4,4,3,4,1,5,2,1,2,4,0,0.0,satisfied +22089,65618,Male,Loyal Customer,27,Personal Travel,Eco,237,4,5,4,5,1,4,1,1,5,5,5,3,5,1,0,0.0,satisfied +22090,33929,Female,Loyal Customer,60,Business travel,Business,1612,2,2,2,2,4,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +22091,99812,Female,Loyal Customer,36,Business travel,Eco Plus,232,4,5,5,5,4,4,4,4,2,1,2,5,3,4,2,1.0,satisfied +22092,63059,Male,Loyal Customer,28,Personal Travel,Eco,862,4,3,4,3,2,4,2,2,3,4,3,3,3,2,6,4.0,neutral or dissatisfied +22093,119752,Male,Loyal Customer,9,Personal Travel,Eco,1325,1,2,1,3,2,1,2,2,4,2,4,1,4,2,0,0.0,neutral or dissatisfied +22094,82311,Female,disloyal Customer,36,Business travel,Eco Plus,1075,2,1,1,3,4,1,4,4,1,3,4,3,3,4,21,73.0,neutral or dissatisfied +22095,76179,Female,disloyal Customer,34,Business travel,Business,2422,3,3,3,3,1,3,1,1,4,4,4,4,5,1,16,0.0,neutral or dissatisfied +22096,87610,Female,disloyal Customer,17,Business travel,Eco,591,4,0,4,1,2,4,2,2,5,4,5,3,4,2,0,0.0,satisfied +22097,104736,Male,Loyal Customer,54,Business travel,Eco,1407,1,1,1,1,1,1,1,1,4,5,4,1,4,1,10,0.0,neutral or dissatisfied +22098,41322,Female,Loyal Customer,36,Personal Travel,Eco,802,1,4,2,4,1,2,1,1,4,4,3,3,1,1,1,0.0,neutral or dissatisfied +22099,98928,Female,Loyal Customer,58,Business travel,Business,479,3,3,3,3,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +22100,87462,Male,Loyal Customer,42,Business travel,Business,2261,5,5,5,5,3,5,5,4,4,5,4,5,4,3,0,0.0,satisfied +22101,24238,Female,Loyal Customer,65,Business travel,Business,302,1,1,1,1,5,1,3,4,4,4,4,5,4,2,0,0.0,satisfied +22102,31345,Female,Loyal Customer,30,Business travel,Business,1069,3,3,3,3,5,5,5,5,3,2,1,5,4,5,0,0.0,satisfied +22103,6966,Male,disloyal Customer,20,Business travel,Business,234,4,5,4,1,1,4,1,1,4,3,4,5,4,1,1,25.0,satisfied +22104,49561,Male,disloyal Customer,34,Business travel,Eco,308,4,0,4,4,4,4,4,4,1,3,1,3,4,4,0,5.0,neutral or dissatisfied +22105,111161,Male,Loyal Customer,57,Personal Travel,Eco,1050,1,5,2,4,5,2,5,5,4,2,4,3,5,5,20,13.0,neutral or dissatisfied +22106,95383,Male,Loyal Customer,24,Personal Travel,Eco,239,2,5,0,4,2,0,3,2,4,2,4,3,5,2,33,16.0,neutral or dissatisfied +22107,79196,Female,Loyal Customer,40,Business travel,Business,1990,3,4,3,3,4,3,4,4,4,4,4,5,4,5,7,0.0,satisfied +22108,123353,Female,Loyal Customer,41,Business travel,Business,3902,2,2,2,2,5,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +22109,73328,Male,disloyal Customer,23,Business travel,Eco,1197,2,2,2,1,5,2,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +22110,21014,Female,Loyal Customer,35,Personal Travel,Business,106,4,4,0,1,2,5,5,4,4,0,5,3,4,5,0,0.0,satisfied +22111,74421,Male,disloyal Customer,22,Business travel,Eco,1487,2,2,2,3,2,2,2,2,3,3,4,5,4,2,40,27.0,neutral or dissatisfied +22112,9905,Female,Loyal Customer,31,Business travel,Business,3323,2,2,2,2,5,5,5,5,4,4,5,4,5,5,13,11.0,satisfied +22113,92374,Female,Loyal Customer,37,Business travel,Business,447,1,1,1,1,5,4,4,3,3,3,3,4,3,4,0,0.0,satisfied +22114,56420,Female,disloyal Customer,36,Business travel,Business,719,2,2,2,2,5,2,5,5,4,4,4,3,5,5,7,2.0,neutral or dissatisfied +22115,112743,Female,Loyal Customer,39,Business travel,Business,590,5,5,5,5,4,5,5,4,4,4,4,4,4,5,21,18.0,satisfied +22116,44688,Female,disloyal Customer,56,Business travel,Eco,67,2,0,2,3,3,2,3,3,3,5,2,3,1,3,0,16.0,neutral or dissatisfied +22117,92201,Male,Loyal Customer,53,Business travel,Business,1979,5,5,5,5,4,5,4,3,3,4,3,5,3,4,9,0.0,satisfied +22118,200,Female,Loyal Customer,43,Business travel,Business,3175,1,3,3,3,5,3,4,1,1,1,1,3,1,1,54,55.0,neutral or dissatisfied +22119,65885,Male,Loyal Customer,50,Personal Travel,Eco Plus,1389,1,5,1,3,4,1,4,4,5,1,1,5,4,4,20,7.0,neutral or dissatisfied +22120,88467,Male,disloyal Customer,23,Business travel,Eco,270,2,3,3,1,1,3,1,1,1,1,1,1,4,1,13,20.0,neutral or dissatisfied +22121,97922,Female,Loyal Customer,39,Business travel,Business,1931,1,1,1,1,2,5,5,4,4,4,4,4,4,4,83,95.0,satisfied +22122,22543,Female,disloyal Customer,48,Business travel,Eco Plus,238,4,4,4,1,4,4,4,4,4,5,1,5,1,4,74,109.0,satisfied +22123,88456,Male,Loyal Customer,56,Business travel,Business,2173,3,3,3,3,4,5,3,4,4,4,4,5,4,3,0,0.0,satisfied +22124,33416,Female,Loyal Customer,23,Business travel,Eco,2399,5,3,3,3,5,5,3,5,5,5,3,4,5,5,0,0.0,satisfied +22125,57774,Female,Loyal Customer,42,Business travel,Business,2704,5,5,5,5,2,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +22126,1369,Female,Loyal Customer,52,Business travel,Business,3425,1,2,2,2,1,4,4,1,1,1,1,2,1,4,70,64.0,neutral or dissatisfied +22127,92446,Male,disloyal Customer,48,Business travel,Business,2092,3,3,3,2,5,3,5,5,4,5,5,3,4,5,8,0.0,neutral or dissatisfied +22128,99223,Female,Loyal Customer,47,Business travel,Business,3748,4,4,4,4,3,5,5,4,4,4,4,3,4,4,4,16.0,satisfied +22129,23149,Female,Loyal Customer,58,Business travel,Business,1861,3,3,3,3,5,4,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +22130,5544,Female,Loyal Customer,46,Personal Travel,Eco,431,2,5,5,3,3,5,4,3,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +22131,18919,Male,Loyal Customer,30,Personal Travel,Eco,551,2,1,3,3,3,3,5,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +22132,115601,Female,Loyal Customer,62,Business travel,Business,325,2,3,3,3,5,4,4,2,2,1,2,3,2,2,11,0.0,neutral or dissatisfied +22133,126506,Female,Loyal Customer,44,Business travel,Eco Plus,1849,3,2,2,2,4,2,3,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +22134,113597,Female,disloyal Customer,38,Business travel,Eco,386,2,1,1,2,2,1,2,2,3,1,2,3,1,2,25,17.0,neutral or dissatisfied +22135,59680,Female,Loyal Customer,22,Personal Travel,Eco,861,4,5,4,3,4,4,4,4,5,3,4,4,5,4,0,0.0,neutral or dissatisfied +22136,58567,Female,Loyal Customer,20,Business travel,Business,1186,5,5,5,5,5,5,5,5,3,5,4,4,5,5,5,0.0,satisfied +22137,116872,Female,Loyal Customer,38,Business travel,Business,646,2,2,2,2,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +22138,59371,Female,Loyal Customer,38,Business travel,Business,2615,3,5,5,5,5,4,3,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +22139,61888,Female,Loyal Customer,46,Personal Travel,Eco,2521,2,3,2,4,3,4,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +22140,52589,Male,Loyal Customer,34,Business travel,Eco,160,3,5,5,5,3,3,3,3,2,3,3,1,2,3,0,0.0,neutral or dissatisfied +22141,99442,Female,Loyal Customer,27,Personal Travel,Eco Plus,337,4,2,4,4,4,4,4,4,3,4,4,2,4,4,0,0.0,neutral or dissatisfied +22142,99783,Female,disloyal Customer,22,Business travel,Eco,584,2,5,2,1,4,2,4,4,4,3,4,4,5,4,5,14.0,neutral or dissatisfied +22143,101974,Male,Loyal Customer,69,Personal Travel,Eco,628,3,4,4,3,2,4,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +22144,100926,Female,Loyal Customer,54,Business travel,Business,2301,3,3,3,3,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +22145,24148,Female,disloyal Customer,30,Business travel,Eco,170,3,0,4,2,3,4,3,3,4,2,2,2,5,3,0,0.0,neutral or dissatisfied +22146,79339,Male,disloyal Customer,22,Business travel,Eco,1020,3,2,2,4,2,3,3,1,5,3,3,3,4,3,123,134.0,neutral or dissatisfied +22147,92008,Female,disloyal Customer,24,Business travel,Eco,1517,2,2,2,4,3,2,3,3,3,4,4,1,3,3,13,0.0,neutral or dissatisfied +22148,46144,Male,Loyal Customer,36,Business travel,Eco,516,2,3,3,3,2,2,2,2,3,4,3,3,4,2,1,0.0,neutral or dissatisfied +22149,5236,Male,Loyal Customer,59,Business travel,Business,3912,4,4,4,4,4,5,5,5,5,4,5,5,5,3,125,121.0,satisfied +22150,43219,Male,disloyal Customer,39,Business travel,Eco,423,1,0,1,3,2,1,2,2,1,1,5,5,1,2,14,21.0,neutral or dissatisfied +22151,46869,Female,Loyal Customer,35,Business travel,Eco,844,5,4,4,4,5,5,5,5,3,1,4,1,2,5,32,19.0,satisfied +22152,67779,Male,Loyal Customer,60,Business travel,Business,3352,3,3,3,3,2,3,4,3,3,3,3,4,3,1,0,2.0,neutral or dissatisfied +22153,37303,Female,Loyal Customer,32,Business travel,Business,3051,5,5,5,5,2,2,2,2,5,5,2,2,3,2,0,0.0,satisfied +22154,100938,Female,disloyal Customer,20,Business travel,Eco,1142,4,4,4,5,5,4,5,5,5,5,4,4,4,5,0,0.0,satisfied +22155,48308,Female,Loyal Customer,49,Personal Travel,Eco,1499,1,2,0,4,5,4,4,1,1,0,1,3,1,1,3,0.0,neutral or dissatisfied +22156,84688,Male,Loyal Customer,12,Personal Travel,Eco,2182,3,1,3,3,2,3,3,2,1,3,4,4,4,2,2,0.0,neutral or dissatisfied +22157,48781,Female,disloyal Customer,24,Business travel,Business,109,0,0,1,3,4,1,4,4,5,4,5,4,5,4,0,0.0,satisfied +22158,91817,Male,Loyal Customer,8,Personal Travel,Eco,590,2,2,2,3,5,2,5,5,3,2,3,4,4,5,0,0.0,neutral or dissatisfied +22159,32317,Female,Loyal Customer,61,Business travel,Eco,216,4,4,4,4,3,5,1,4,4,4,4,2,4,2,0,0.0,satisfied +22160,50109,Female,Loyal Customer,40,Business travel,Business,250,2,2,2,2,4,3,3,2,2,2,2,3,2,1,0,0.0,neutral or dissatisfied +22161,103929,Male,Loyal Customer,55,Business travel,Business,770,1,1,2,1,4,4,4,2,2,2,2,5,2,4,9,13.0,satisfied +22162,71385,Female,Loyal Customer,9,Personal Travel,Eco,258,3,1,3,3,1,3,1,1,2,4,3,3,4,1,36,43.0,neutral or dissatisfied +22163,92607,Female,Loyal Customer,48,Personal Travel,Eco,2218,3,3,3,3,1,2,4,2,2,3,2,4,2,1,0,0.0,neutral or dissatisfied +22164,92451,Female,Loyal Customer,18,Business travel,Business,2139,3,1,1,1,3,2,3,3,2,2,3,1,3,3,0,0.0,neutral or dissatisfied +22165,118408,Male,disloyal Customer,36,Business travel,Business,368,2,2,2,2,2,2,2,2,4,4,5,3,5,2,0,0.0,neutral or dissatisfied +22166,121757,Male,Loyal Customer,60,Business travel,Business,1680,1,5,5,5,1,1,1,1,5,3,2,1,3,1,200,172.0,neutral or dissatisfied +22167,32902,Male,Loyal Customer,53,Personal Travel,Eco,102,1,5,1,3,3,1,3,3,3,2,5,4,4,3,7,18.0,neutral or dissatisfied +22168,62112,Male,Loyal Customer,38,Business travel,Business,2565,3,3,3,3,4,4,5,2,2,2,2,3,2,4,42,37.0,satisfied +22169,20300,Male,Loyal Customer,26,Personal Travel,Eco,179,1,5,1,2,2,1,5,2,2,4,2,2,4,2,0,0.0,neutral or dissatisfied +22170,121542,Male,Loyal Customer,41,Business travel,Business,1032,2,2,2,2,5,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +22171,78017,Female,Loyal Customer,38,Business travel,Eco,214,3,1,1,1,3,3,3,3,3,1,4,3,3,3,0,14.0,neutral or dissatisfied +22172,13594,Female,Loyal Customer,58,Personal Travel,Eco,152,2,4,2,2,4,5,4,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +22173,59298,Male,Loyal Customer,33,Personal Travel,Business,2367,3,5,3,4,2,3,2,2,3,3,4,5,4,2,64,39.0,neutral or dissatisfied +22174,85995,Male,Loyal Customer,60,Business travel,Business,2831,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +22175,120633,Female,disloyal Customer,44,Business travel,Business,280,1,1,1,3,3,1,3,3,3,5,5,5,4,3,0,0.0,neutral or dissatisfied +22176,29519,Female,Loyal Customer,36,Business travel,Business,1870,3,3,3,3,2,1,3,4,4,4,4,4,4,4,0,0.0,satisfied +22177,20880,Female,disloyal Customer,59,Business travel,Eco Plus,508,3,3,3,4,4,3,4,4,2,1,3,1,4,4,0,0.0,neutral or dissatisfied +22178,102238,Female,Loyal Customer,44,Business travel,Eco,414,1,3,3,3,4,3,2,1,1,1,1,4,1,1,20,13.0,neutral or dissatisfied +22179,32084,Male,Loyal Customer,39,Business travel,Eco,101,4,3,3,3,4,5,4,4,2,4,5,4,4,4,0,0.0,satisfied +22180,19767,Female,Loyal Customer,48,Personal Travel,Eco Plus,779,4,5,4,2,4,2,1,4,3,5,5,1,4,1,219,223.0,neutral or dissatisfied +22181,112552,Female,Loyal Customer,19,Business travel,Eco Plus,909,4,3,3,3,4,4,1,4,4,2,4,2,3,4,50,41.0,neutral or dissatisfied +22182,22273,Male,Loyal Customer,37,Business travel,Business,3265,2,2,2,2,2,5,4,5,5,5,4,4,5,2,0,0.0,satisfied +22183,70778,Female,Loyal Customer,48,Business travel,Business,2544,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +22184,21008,Male,Loyal Customer,25,Personal Travel,Eco Plus,851,4,4,4,1,2,4,2,2,5,4,4,5,4,2,0,0.0,neutral or dissatisfied +22185,18740,Male,disloyal Customer,26,Business travel,Business,1167,1,1,1,3,4,1,4,4,1,1,2,3,4,4,0,2.0,neutral or dissatisfied +22186,42265,Female,Loyal Customer,48,Business travel,Eco,784,1,4,4,4,1,3,2,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +22187,118787,Female,Loyal Customer,12,Personal Travel,Eco,370,1,3,1,2,1,1,1,1,2,5,5,4,2,1,0,0.0,neutral or dissatisfied +22188,90561,Female,Loyal Customer,32,Business travel,Business,3878,4,2,4,4,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +22189,11354,Male,Loyal Customer,60,Personal Travel,Eco,224,2,4,2,4,5,2,5,5,1,5,3,2,4,5,0,0.0,neutral or dissatisfied +22190,110108,Male,Loyal Customer,61,Business travel,Business,3451,1,1,1,1,4,4,5,2,2,2,2,5,2,3,13,15.0,satisfied +22191,61262,Female,Loyal Customer,69,Personal Travel,Eco,909,2,3,2,4,5,3,3,5,5,2,5,4,5,4,15,10.0,neutral or dissatisfied +22192,24304,Male,disloyal Customer,25,Business travel,Eco Plus,302,2,0,2,5,4,2,4,4,1,4,3,5,3,4,0,0.0,neutral or dissatisfied +22193,61158,Female,Loyal Customer,49,Business travel,Business,862,5,5,5,5,4,4,4,5,5,5,5,4,5,4,61,44.0,satisfied +22194,121536,Female,Loyal Customer,48,Business travel,Business,2382,3,1,3,3,2,4,5,3,3,3,3,4,3,5,30,31.0,satisfied +22195,85985,Female,Loyal Customer,58,Business travel,Business,1956,2,2,2,2,2,4,4,5,5,5,5,4,5,5,13,14.0,satisfied +22196,116670,Female,Loyal Customer,42,Business travel,Business,3674,1,1,1,1,4,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +22197,40944,Male,Loyal Customer,20,Personal Travel,Eco Plus,588,1,4,1,4,3,1,3,3,4,5,4,5,5,3,0,0.0,neutral or dissatisfied +22198,92794,Male,Loyal Customer,28,Business travel,Business,1587,2,2,2,2,4,4,4,4,5,3,4,4,4,4,0,0.0,satisfied +22199,83786,Female,Loyal Customer,43,Business travel,Business,425,5,5,3,5,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +22200,74741,Female,Loyal Customer,26,Personal Travel,Eco,1464,3,4,3,3,3,5,5,4,3,4,4,5,3,5,298,273.0,neutral or dissatisfied +22201,1552,Female,Loyal Customer,25,Personal Travel,Eco,922,3,5,3,3,4,3,4,4,5,2,4,3,5,4,1,0.0,neutral or dissatisfied +22202,48600,Female,Loyal Customer,23,Personal Travel,Eco,737,2,5,2,3,4,2,4,4,4,2,4,3,5,4,114,113.0,neutral or dissatisfied +22203,121161,Female,Loyal Customer,40,Business travel,Eco,2521,3,1,1,1,3,3,3,4,3,1,2,3,3,3,6,49.0,neutral or dissatisfied +22204,87919,Female,disloyal Customer,22,Business travel,Business,594,4,0,4,3,5,4,5,5,5,4,5,5,5,5,0,0.0,satisfied +22205,68923,Male,disloyal Customer,23,Business travel,Business,936,4,2,4,1,2,4,4,2,3,5,4,4,5,2,0,0.0,satisfied +22206,9165,Male,Loyal Customer,57,Personal Travel,Eco,946,4,2,4,3,3,4,3,3,2,1,4,4,3,3,0,14.0,neutral or dissatisfied +22207,72294,Female,Loyal Customer,65,Personal Travel,Eco,921,3,4,3,3,4,4,5,2,2,3,2,3,2,5,0,0.0,neutral or dissatisfied +22208,68098,Female,disloyal Customer,28,Business travel,Eco,868,4,4,4,4,2,4,2,2,2,3,3,4,4,2,26,28.0,neutral or dissatisfied +22209,115687,Female,Loyal Customer,63,Business travel,Business,2181,3,5,1,5,2,3,4,3,3,3,3,3,3,4,3,13.0,neutral or dissatisfied +22210,3882,Male,Loyal Customer,42,Business travel,Business,213,4,2,3,3,4,3,4,1,1,1,4,3,1,4,59,44.0,neutral or dissatisfied +22211,88616,Male,Loyal Customer,22,Personal Travel,Eco,271,1,3,1,4,5,1,5,5,1,4,3,2,3,5,0,26.0,neutral or dissatisfied +22212,2493,Male,disloyal Customer,54,Business travel,Eco,1379,2,2,2,3,1,2,1,1,4,4,4,2,3,1,0,0.0,neutral or dissatisfied +22213,8570,Male,Loyal Customer,47,Business travel,Business,1948,3,3,3,3,5,5,5,4,4,4,5,3,4,5,0,0.0,satisfied +22214,36031,Female,Loyal Customer,73,Business travel,Business,1765,1,1,1,1,2,1,3,4,4,4,4,4,4,3,0,0.0,satisfied +22215,64725,Male,Loyal Customer,41,Business travel,Business,2604,0,0,0,3,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +22216,35775,Female,Loyal Customer,36,Business travel,Eco,200,4,2,2,2,4,4,4,4,1,2,3,2,4,4,0,0.0,neutral or dissatisfied +22217,102969,Female,Loyal Customer,42,Business travel,Business,2744,2,1,1,1,3,4,4,2,2,2,2,3,2,3,35,31.0,neutral or dissatisfied +22218,82735,Female,disloyal Customer,29,Business travel,Business,409,5,5,5,2,5,0,5,5,5,4,4,5,5,5,0,0.0,satisfied +22219,95591,Female,Loyal Customer,53,Business travel,Business,3384,5,5,4,5,4,5,4,5,5,5,5,4,5,3,37,31.0,satisfied +22220,121388,Female,Loyal Customer,30,Business travel,Business,2279,3,3,3,3,5,5,5,5,4,3,5,5,4,5,1,0.0,satisfied +22221,32864,Male,Loyal Customer,10,Personal Travel,Eco,216,0,0,0,3,2,0,2,2,3,3,4,5,4,2,0,0.0,satisfied +22222,11575,Female,Loyal Customer,44,Business travel,Eco,771,2,4,4,4,3,4,3,2,2,2,2,2,2,4,45,38.0,neutral or dissatisfied +22223,28391,Male,Loyal Customer,55,Personal Travel,Eco,763,3,5,4,3,2,4,2,2,5,4,4,5,5,2,0,0.0,neutral or dissatisfied +22224,22369,Male,Loyal Customer,45,Business travel,Business,3000,3,5,5,5,2,3,3,1,1,1,3,3,1,4,120,108.0,neutral or dissatisfied +22225,77191,Male,Loyal Customer,8,Personal Travel,Eco,290,2,4,2,4,1,2,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +22226,108261,Male,Loyal Customer,53,Business travel,Business,2537,2,2,3,2,2,4,4,4,4,4,4,5,4,1,29,20.0,satisfied +22227,77728,Male,Loyal Customer,54,Business travel,Business,1668,1,5,1,1,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +22228,23161,Female,Loyal Customer,40,Personal Travel,Eco,300,4,4,4,3,4,4,4,4,3,2,5,3,5,4,24,17.0,neutral or dissatisfied +22229,57485,Male,Loyal Customer,11,Personal Travel,Eco,1589,3,4,3,4,1,3,1,1,5,4,3,4,5,1,101,58.0,neutral or dissatisfied +22230,17765,Male,Loyal Customer,42,Personal Travel,Business,1214,2,3,2,4,4,2,4,3,3,2,3,1,3,1,3,27.0,neutral or dissatisfied +22231,27151,Male,disloyal Customer,29,Business travel,Business,2640,4,4,4,4,4,4,4,2,2,2,4,4,1,4,8,0.0,neutral or dissatisfied +22232,1519,Male,Loyal Customer,25,Business travel,Business,3267,1,1,1,1,5,5,5,5,3,3,5,5,4,5,0,0.0,satisfied +22233,92804,Female,Loyal Customer,46,Business travel,Business,1587,3,3,3,3,3,5,4,4,4,4,4,3,4,5,2,3.0,satisfied +22234,36831,Male,Loyal Customer,36,Business travel,Eco,369,5,5,5,5,5,5,5,5,1,3,3,5,4,5,16,4.0,satisfied +22235,61530,Female,Loyal Customer,35,Personal Travel,Eco,2419,3,2,3,3,5,3,1,5,3,4,4,1,3,5,27,13.0,neutral or dissatisfied +22236,71149,Female,Loyal Customer,42,Business travel,Business,1906,2,2,2,2,3,4,5,4,4,4,4,3,4,4,28,25.0,satisfied +22237,78984,Female,Loyal Customer,32,Business travel,Business,377,4,3,3,3,4,4,4,4,2,3,4,1,3,4,0,0.0,neutral or dissatisfied +22238,23112,Male,Loyal Customer,55,Business travel,Business,3259,4,4,4,4,1,3,1,4,4,4,4,4,4,5,0,0.0,satisfied +22239,85978,Male,Loyal Customer,29,Business travel,Business,528,1,1,4,1,4,4,4,4,4,2,4,3,5,4,0,0.0,satisfied +22240,122324,Male,Loyal Customer,51,Business travel,Eco Plus,544,2,5,5,5,2,2,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +22241,2711,Male,Loyal Customer,53,Personal Travel,Eco,562,4,4,4,3,3,4,3,3,5,4,5,5,5,3,0,0.0,neutral or dissatisfied +22242,14454,Female,Loyal Customer,64,Business travel,Business,761,3,5,5,5,2,4,4,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +22243,87709,Male,Loyal Customer,61,Personal Travel,Eco,606,1,4,1,2,1,1,1,1,5,4,5,5,5,1,70,61.0,neutral or dissatisfied +22244,55255,Female,Loyal Customer,44,Personal Travel,Eco,1009,2,3,2,3,5,3,4,1,1,2,1,4,1,1,2,0.0,neutral or dissatisfied +22245,29994,Male,Loyal Customer,45,Business travel,Business,627,3,3,3,3,2,4,3,3,3,3,3,4,3,3,0,10.0,neutral or dissatisfied +22246,25640,Male,Loyal Customer,50,Personal Travel,Eco,666,4,4,4,3,5,4,5,5,1,2,4,4,5,5,6,1.0,neutral or dissatisfied +22247,111559,Male,Loyal Customer,34,Business travel,Business,2149,1,1,5,1,4,5,5,4,4,5,4,4,4,5,26,14.0,satisfied +22248,38335,Female,Loyal Customer,50,Business travel,Eco,1050,4,5,5,5,2,1,3,4,4,4,4,1,4,3,0,0.0,satisfied +22249,16719,Male,Loyal Customer,58,Business travel,Eco Plus,284,5,4,2,4,5,5,5,5,3,2,2,1,2,5,60,45.0,satisfied +22250,27541,Female,Loyal Customer,66,Personal Travel,Eco,605,2,3,2,3,4,4,4,5,5,2,2,4,5,2,0,7.0,neutral or dissatisfied +22251,122184,Male,Loyal Customer,43,Business travel,Business,3984,4,4,4,4,2,5,4,2,2,3,2,3,2,5,7,0.0,satisfied +22252,110011,Male,disloyal Customer,24,Business travel,Eco,1204,5,5,5,4,2,5,5,2,5,3,4,5,5,2,15,0.0,satisfied +22253,12928,Female,Loyal Customer,45,Personal Travel,Eco,794,2,2,2,4,2,4,4,4,5,4,4,4,1,4,338,333.0,neutral or dissatisfied +22254,104898,Male,Loyal Customer,49,Business travel,Business,1565,2,2,2,2,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +22255,61223,Male,Loyal Customer,47,Business travel,Eco,967,4,5,3,5,3,4,3,3,1,1,3,4,4,3,23,45.0,neutral or dissatisfied +22256,32782,Male,disloyal Customer,23,Business travel,Eco,101,1,1,1,2,1,1,1,1,1,5,2,3,2,1,0,11.0,neutral or dissatisfied +22257,101736,Female,Loyal Customer,24,Business travel,Business,1590,3,3,3,3,3,3,3,3,2,3,4,3,3,3,0,0.0,neutral or dissatisfied +22258,110236,Male,disloyal Customer,18,Business travel,Eco,1147,3,3,3,4,3,3,3,3,4,3,4,1,4,3,0,21.0,neutral or dissatisfied +22259,24042,Male,Loyal Customer,43,Personal Travel,Eco,595,3,5,3,5,3,3,3,3,1,4,4,2,2,3,3,0.0,neutral or dissatisfied +22260,110562,Female,Loyal Customer,60,Business travel,Eco,643,3,3,3,3,5,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +22261,11164,Male,Loyal Customer,34,Personal Travel,Eco,140,1,5,1,1,2,1,2,2,4,5,3,4,4,2,45,50.0,neutral or dissatisfied +22262,113586,Male,Loyal Customer,47,Business travel,Eco,386,2,3,3,3,2,2,2,2,1,3,4,5,2,2,7,1.0,satisfied +22263,91630,Male,Loyal Customer,72,Business travel,Eco,1199,1,2,1,1,1,1,1,1,3,5,4,1,3,1,4,0.0,neutral or dissatisfied +22264,128196,Male,Loyal Customer,13,Personal Travel,Eco Plus,1788,2,5,2,4,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +22265,60097,Female,disloyal Customer,27,Business travel,Business,1012,4,3,3,2,3,3,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +22266,95972,Male,Loyal Customer,39,Business travel,Business,583,5,5,5,5,3,4,5,5,5,5,5,3,5,3,11,8.0,satisfied +22267,2076,Female,Loyal Customer,42,Business travel,Eco,812,5,1,1,1,2,3,2,5,5,5,5,1,5,1,39,32.0,satisfied +22268,73883,Female,disloyal Customer,30,Business travel,Business,2330,2,2,2,3,2,2,2,2,4,5,5,3,5,2,0,0.0,neutral or dissatisfied +22269,94890,Male,disloyal Customer,43,Business travel,Eco,239,3,0,3,4,5,3,5,5,3,3,5,5,5,5,2,0.0,neutral or dissatisfied +22270,21196,Female,Loyal Customer,52,Business travel,Eco,192,3,1,1,1,2,2,2,3,3,3,3,2,3,3,1,0.0,neutral or dissatisfied +22271,27367,Female,disloyal Customer,25,Business travel,Eco,1050,4,4,4,1,5,4,2,5,4,1,1,4,3,5,0,5.0,satisfied +22272,88037,Male,Loyal Customer,31,Business travel,Business,3502,1,1,1,1,4,4,4,4,5,3,5,4,4,4,26,28.0,satisfied +22273,110155,Female,Loyal Customer,7,Personal Travel,Eco,882,1,2,1,3,2,1,4,2,1,1,4,1,3,2,34,27.0,neutral or dissatisfied +22274,98932,Female,Loyal Customer,55,Business travel,Business,3678,4,5,5,5,2,2,2,4,4,3,4,1,4,3,9,7.0,neutral or dissatisfied +22275,10227,Male,Loyal Customer,51,Business travel,Business,1750,2,4,4,4,2,3,4,2,2,1,2,2,2,3,0,0.0,neutral or dissatisfied +22276,9838,Female,Loyal Customer,43,Business travel,Business,2523,2,2,2,2,4,5,4,4,4,4,4,3,4,5,47,28.0,satisfied +22277,9122,Female,Loyal Customer,33,Personal Travel,Eco,765,5,4,5,4,3,5,3,3,3,4,5,5,5,3,0,0.0,satisfied +22278,45738,Female,Loyal Customer,52,Personal Travel,Eco Plus,1463,4,4,4,4,1,2,3,2,2,4,2,3,2,3,0,0.0,neutral or dissatisfied +22279,27373,Female,disloyal Customer,31,Business travel,Eco,978,2,2,2,3,5,2,5,5,5,3,2,2,2,5,0,0.0,neutral or dissatisfied +22280,84442,Female,Loyal Customer,26,Personal Travel,Eco Plus,591,4,5,4,2,3,4,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +22281,83835,Male,disloyal Customer,39,Business travel,Eco,425,4,0,4,5,3,4,3,3,3,5,3,1,1,3,8,6.0,neutral or dissatisfied +22282,83763,Male,Loyal Customer,41,Business travel,Business,926,2,2,2,2,5,4,4,5,5,5,5,3,5,3,21,13.0,satisfied +22283,45071,Female,Loyal Customer,70,Personal Travel,Eco,342,2,4,2,5,1,2,4,4,4,2,4,4,4,1,118,107.0,neutral or dissatisfied +22284,23574,Female,Loyal Customer,29,Personal Travel,Eco,1015,1,3,1,4,5,1,5,5,4,1,2,3,4,5,32,57.0,neutral or dissatisfied +22285,118914,Male,Loyal Customer,36,Personal Travel,Eco,570,1,4,1,3,2,1,2,2,1,1,3,2,3,2,0,0.0,neutral or dissatisfied +22286,68380,Male,Loyal Customer,25,Business travel,Business,2060,1,1,1,1,4,5,4,4,5,3,4,3,4,4,0,0.0,satisfied +22287,5511,Female,Loyal Customer,51,Business travel,Business,3455,1,1,1,1,2,3,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +22288,63598,Female,disloyal Customer,29,Business travel,Eco Plus,2133,3,3,3,2,1,3,1,1,3,5,5,5,3,1,35,22.0,neutral or dissatisfied +22289,4637,Female,disloyal Customer,20,Business travel,Eco,364,2,4,2,3,5,2,2,5,5,2,4,4,5,5,47,48.0,neutral or dissatisfied +22290,91329,Female,disloyal Customer,20,Business travel,Eco,406,3,0,3,5,1,3,1,1,2,1,2,5,2,1,0,0.0,neutral or dissatisfied +22291,114960,Female,Loyal Customer,55,Business travel,Business,2001,2,2,2,2,4,4,4,4,4,4,4,4,4,3,24,21.0,satisfied +22292,116994,Male,Loyal Customer,29,Business travel,Business,646,3,3,3,3,4,4,4,4,4,3,5,3,4,4,0,0.0,satisfied +22293,62265,Male,Loyal Customer,68,Personal Travel,Eco Plus,2425,5,5,5,2,1,5,1,1,4,2,4,3,4,1,15,0.0,satisfied +22294,23254,Male,Loyal Customer,58,Business travel,Business,1847,1,3,3,3,1,3,3,1,1,1,1,1,1,1,0,0.0,neutral or dissatisfied +22295,119560,Male,Loyal Customer,16,Personal Travel,Eco,814,2,0,2,5,1,2,1,1,3,5,4,3,4,1,0,0.0,neutral or dissatisfied +22296,117072,Male,Loyal Customer,73,Business travel,Eco,325,1,2,2,2,1,1,1,1,2,4,3,3,4,1,1,0.0,neutral or dissatisfied +22297,123648,Female,Loyal Customer,43,Business travel,Business,2189,5,5,5,5,3,4,5,5,5,5,5,5,5,3,40,48.0,satisfied +22298,927,Male,disloyal Customer,39,Business travel,Business,354,2,2,2,2,4,2,4,4,4,4,3,1,3,4,0,0.0,neutral or dissatisfied +22299,61493,Female,disloyal Customer,42,Business travel,Business,2288,3,3,3,1,1,3,1,1,5,5,5,5,5,1,0,0.0,neutral or dissatisfied +22300,73246,Female,Loyal Customer,26,Business travel,Business,3986,4,4,4,4,4,4,4,4,4,3,4,5,5,4,0,0.0,satisfied +22301,121032,Female,Loyal Customer,23,Personal Travel,Eco,861,2,4,2,3,4,2,2,4,5,3,4,5,5,4,0,40.0,neutral or dissatisfied +22302,45776,Female,Loyal Customer,46,Business travel,Business,3860,3,3,3,3,3,1,1,5,5,5,4,1,5,3,0,0.0,satisfied +22303,96626,Female,Loyal Customer,59,Business travel,Business,2676,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +22304,120073,Female,Loyal Customer,49,Business travel,Business,683,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +22305,107614,Male,disloyal Customer,25,Business travel,Business,423,4,0,4,1,5,4,1,5,4,5,4,3,4,5,5,0.0,satisfied +22306,7680,Female,disloyal Customer,25,Business travel,Eco,604,3,3,3,3,4,3,4,4,3,1,4,4,4,4,0,0.0,neutral or dissatisfied +22307,117448,Female,Loyal Customer,36,Business travel,Eco,1020,2,2,2,2,2,2,2,2,3,4,3,2,4,2,12,0.0,neutral or dissatisfied +22308,100176,Male,Loyal Customer,38,Personal Travel,Eco,717,3,5,2,3,2,2,2,2,2,1,1,3,5,2,6,20.0,neutral or dissatisfied +22309,60836,Female,Loyal Customer,37,Business travel,Business,1754,1,1,2,1,4,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +22310,38493,Male,Loyal Customer,41,Business travel,Eco,2569,4,2,2,2,4,4,4,4,5,1,5,3,3,4,95,87.0,satisfied +22311,48867,Female,Loyal Customer,51,Business travel,Business,158,5,5,5,5,1,4,5,4,4,4,5,3,4,4,0,0.0,satisfied +22312,20552,Female,Loyal Customer,31,Business travel,Business,633,3,3,3,3,4,4,4,4,1,2,5,2,1,4,0,19.0,satisfied +22313,46502,Female,disloyal Customer,35,Business travel,Eco,73,3,0,3,4,3,3,3,3,1,1,2,4,3,3,31,23.0,neutral or dissatisfied +22314,75343,Male,Loyal Customer,21,Personal Travel,Eco,2504,3,1,3,1,3,1,2,4,3,2,2,2,1,2,0,1.0,neutral or dissatisfied +22315,104726,Female,Loyal Customer,13,Business travel,Business,3851,5,5,5,5,5,5,5,5,3,2,5,4,4,5,0,0.0,satisfied +22316,2932,Female,Loyal Customer,37,Personal Travel,Eco,806,2,4,2,1,2,2,2,2,2,3,5,2,5,2,0,0.0,neutral or dissatisfied +22317,36630,Male,Loyal Customer,20,Business travel,Eco,1121,4,4,5,5,4,4,4,4,4,2,4,2,5,4,10,0.0,satisfied +22318,99586,Female,Loyal Customer,39,Personal Travel,Eco,802,1,5,0,4,0,3,3,4,3,4,3,3,4,3,140,158.0,neutral or dissatisfied +22319,126660,Female,Loyal Customer,64,Personal Travel,Eco,602,2,4,2,4,5,4,4,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +22320,100555,Female,Loyal Customer,60,Personal Travel,Eco Plus,759,5,2,5,4,5,4,4,1,1,5,1,2,1,3,0,0.0,satisfied +22321,45559,Female,Loyal Customer,37,Business travel,Eco,1304,2,1,1,1,2,3,2,2,4,1,4,1,1,2,0,0.0,satisfied +22322,30837,Male,Loyal Customer,10,Personal Travel,Eco,896,1,4,1,3,1,1,4,1,3,1,4,4,5,1,0,0.0,neutral or dissatisfied +22323,14151,Female,Loyal Customer,57,Personal Travel,Eco,594,2,3,1,4,5,4,3,3,3,1,3,3,3,4,19,33.0,neutral or dissatisfied +22324,63081,Male,Loyal Customer,28,Personal Travel,Eco,967,3,5,3,1,4,3,4,4,3,3,4,4,5,4,0,0.0,neutral or dissatisfied +22325,93791,Male,disloyal Customer,50,Business travel,Business,1259,2,2,2,4,2,2,2,2,3,2,5,3,4,2,0,0.0,neutral or dissatisfied +22326,114994,Male,Loyal Customer,60,Business travel,Business,2994,5,5,5,5,2,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +22327,2722,Female,Loyal Customer,56,Business travel,Business,2645,1,1,1,1,5,5,5,3,4,5,5,5,4,5,227,208.0,satisfied +22328,123779,Male,Loyal Customer,60,Business travel,Business,541,3,3,2,3,3,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +22329,95264,Female,Loyal Customer,46,Personal Travel,Eco,187,2,5,0,5,5,4,4,5,5,0,5,3,5,5,0,0.0,neutral or dissatisfied +22330,85955,Female,Loyal Customer,55,Business travel,Business,3475,2,2,2,2,5,5,4,5,5,5,5,3,5,4,71,64.0,satisfied +22331,46922,Male,disloyal Customer,34,Business travel,Eco,833,1,1,1,1,1,1,1,1,5,3,4,5,5,1,0,13.0,neutral or dissatisfied +22332,96057,Female,disloyal Customer,30,Business travel,Eco,795,3,3,3,4,5,3,5,5,2,5,4,2,3,5,0,0.0,neutral or dissatisfied +22333,61353,Male,Loyal Customer,70,Business travel,Eco,202,3,5,5,5,3,3,3,3,3,2,3,4,3,3,27,29.0,neutral or dissatisfied +22334,90706,Female,disloyal Customer,26,Business travel,Business,515,4,4,4,4,2,4,2,2,4,3,4,4,4,2,0,0.0,satisfied +22335,107392,Male,disloyal Customer,25,Business travel,Business,523,2,0,2,3,4,2,4,4,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +22336,11407,Male,Loyal Customer,48,Business travel,Business,3122,2,2,2,2,3,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +22337,10582,Male,Loyal Customer,37,Business travel,Business,3217,4,4,4,4,4,4,5,5,5,5,5,3,5,4,0,1.0,satisfied +22338,24378,Female,Loyal Customer,40,Business travel,Eco,669,1,5,5,5,1,1,1,1,2,4,4,4,4,1,0,6.0,neutral or dissatisfied +22339,34675,Female,Loyal Customer,51,Business travel,Eco,264,4,5,5,5,5,5,1,4,4,4,4,2,4,4,0,0.0,satisfied +22340,71214,Male,disloyal Customer,30,Business travel,Business,733,2,2,2,3,3,2,5,3,4,4,4,4,5,3,0,0.0,neutral or dissatisfied +22341,68113,Female,Loyal Customer,59,Personal Travel,Eco,813,5,4,5,3,2,4,5,1,1,5,1,3,1,5,0,0.0,satisfied +22342,112733,Male,Loyal Customer,43,Personal Travel,Eco,672,2,4,2,1,3,2,3,3,5,4,5,4,4,3,8,0.0,neutral or dissatisfied +22343,105325,Female,Loyal Customer,55,Business travel,Business,1757,4,4,4,4,5,5,4,5,5,4,5,3,5,4,11,28.0,satisfied +22344,85875,Female,disloyal Customer,37,Business travel,Business,1267,5,0,0,5,4,0,4,4,3,5,5,3,4,4,0,0.0,satisfied +22345,44715,Male,Loyal Customer,12,Personal Travel,Eco,67,3,5,3,1,3,3,3,3,3,3,4,5,4,3,81,90.0,neutral or dissatisfied +22346,86922,Female,Loyal Customer,19,Personal Travel,Eco,352,1,4,1,3,5,1,5,5,3,4,5,3,4,5,0,0.0,neutral or dissatisfied +22347,78132,Male,Loyal Customer,42,Business travel,Business,259,3,1,1,1,2,3,3,3,3,3,3,3,3,2,0,0.0,neutral or dissatisfied +22348,57193,Male,Loyal Customer,29,Business travel,Business,1514,1,1,1,1,5,5,5,5,3,5,4,5,5,5,5,0.0,satisfied +22349,74861,Male,Loyal Customer,59,Personal Travel,Eco,1995,2,1,2,3,1,2,1,1,1,5,2,3,3,1,5,0.0,neutral or dissatisfied +22350,4055,Male,Loyal Customer,69,Personal Travel,Eco,483,2,5,2,3,5,2,5,5,4,4,5,4,5,5,0,0.0,neutral or dissatisfied +22351,56773,Male,Loyal Customer,29,Personal Travel,Eco Plus,997,4,1,4,4,5,4,5,5,2,5,3,1,4,5,3,0.0,neutral or dissatisfied +22352,16196,Male,Loyal Customer,23,Personal Travel,Eco,277,4,3,4,1,1,4,1,1,4,4,3,2,1,1,41,50.0,satisfied +22353,14466,Female,Loyal Customer,18,Personal Travel,Eco,674,1,4,1,3,5,1,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +22354,124627,Female,Loyal Customer,16,Personal Travel,Eco,1671,2,2,2,3,1,2,1,1,4,5,3,2,3,1,0,0.0,neutral or dissatisfied +22355,111967,Female,Loyal Customer,48,Business travel,Eco,533,1,1,1,1,1,4,4,2,2,1,2,2,2,2,66,60.0,neutral or dissatisfied +22356,90431,Female,Loyal Customer,38,Business travel,Business,545,1,2,1,1,3,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +22357,84619,Female,Loyal Customer,53,Business travel,Eco,269,3,1,1,1,5,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +22358,55070,Male,Loyal Customer,43,Business travel,Business,1504,3,2,2,2,5,1,2,3,3,3,3,3,3,1,41,28.0,neutral or dissatisfied +22359,118552,Male,disloyal Customer,29,Business travel,Business,651,2,2,2,1,4,2,5,4,3,4,5,3,5,4,23,21.0,neutral or dissatisfied +22360,66979,Male,Loyal Customer,44,Business travel,Business,985,1,1,1,1,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +22361,89748,Male,Loyal Customer,65,Personal Travel,Eco,1035,1,4,1,2,1,1,1,1,4,3,5,5,5,1,0,3.0,neutral or dissatisfied +22362,24028,Male,Loyal Customer,16,Business travel,Business,3130,2,5,5,5,2,2,2,2,4,4,4,1,3,2,39,24.0,neutral or dissatisfied +22363,63013,Female,Loyal Customer,37,Business travel,Eco,967,2,1,1,1,2,2,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +22364,46615,Female,disloyal Customer,55,Business travel,Eco,125,3,2,3,2,4,3,5,4,4,3,2,4,3,4,1,6.0,neutral or dissatisfied +22365,44198,Male,Loyal Customer,17,Personal Travel,Eco,157,2,5,2,1,3,2,3,3,5,3,4,4,4,3,0,6.0,neutral or dissatisfied +22366,36489,Male,Loyal Customer,29,Personal Travel,Business,1185,3,5,3,3,4,3,4,4,4,2,4,4,4,4,0,1.0,neutral or dissatisfied +22367,4729,Female,Loyal Customer,44,Business travel,Business,2171,4,4,4,4,5,5,5,4,4,5,4,3,4,3,83,61.0,satisfied +22368,84629,Female,Loyal Customer,58,Personal Travel,Eco,669,2,4,2,1,3,4,5,4,4,2,4,5,4,4,6,0.0,neutral or dissatisfied +22369,98012,Male,Loyal Customer,35,Business travel,Business,2379,1,1,1,1,2,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +22370,13724,Male,Loyal Customer,35,Business travel,Business,2423,3,3,3,3,5,1,5,4,4,4,4,1,4,1,10,5.0,satisfied +22371,110402,Male,Loyal Customer,42,Business travel,Eco,883,2,2,2,2,2,2,2,2,4,1,3,4,3,2,44,46.0,neutral or dissatisfied +22372,56956,Male,Loyal Customer,51,Business travel,Business,2425,1,3,3,3,1,1,1,2,1,2,1,1,4,1,4,13.0,neutral or dissatisfied +22373,66690,Male,Loyal Customer,41,Business travel,Eco,802,1,2,3,2,1,1,1,1,2,3,2,1,2,1,40,39.0,neutral or dissatisfied +22374,45802,Male,Loyal Customer,46,Business travel,Eco,391,2,4,4,4,2,2,2,2,2,5,4,5,1,2,0,4.0,satisfied +22375,71621,Male,Loyal Customer,40,Business travel,Business,2882,5,5,5,5,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +22376,32769,Male,Loyal Customer,48,Business travel,Business,3062,5,5,5,5,1,3,3,5,5,5,4,4,5,2,0,0.0,satisfied +22377,92255,Male,Loyal Customer,42,Personal Travel,Eco,1670,3,4,3,5,1,3,1,1,3,4,3,2,5,1,0,0.0,neutral or dissatisfied +22378,87162,Male,disloyal Customer,36,Business travel,Business,946,2,2,2,3,2,2,2,2,4,3,5,5,4,2,0,0.0,neutral or dissatisfied +22379,78259,Female,Loyal Customer,20,Business travel,Business,2783,3,2,2,2,3,3,3,3,3,1,4,2,3,3,0,0.0,neutral or dissatisfied +22380,108837,Female,Loyal Customer,7,Personal Travel,Eco,1199,4,5,4,3,5,4,5,5,1,1,3,5,4,5,0,16.0,neutral or dissatisfied +22381,117526,Female,disloyal Customer,27,Business travel,Business,872,3,3,3,4,5,3,5,5,3,4,4,1,3,5,8,0.0,neutral or dissatisfied +22382,113114,Male,Loyal Customer,60,Personal Travel,Eco,543,2,1,2,2,2,2,2,2,4,5,1,4,2,2,34,13.0,neutral or dissatisfied +22383,4194,Male,Loyal Customer,50,Business travel,Eco Plus,427,3,4,2,2,3,3,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +22384,116107,Male,Loyal Customer,24,Personal Travel,Eco,296,3,5,3,3,1,3,1,1,3,5,5,3,5,1,0,0.0,neutral or dissatisfied +22385,129277,Female,Loyal Customer,33,Personal Travel,Eco,2521,1,2,1,3,4,1,4,4,2,1,3,2,4,4,0,0.0,neutral or dissatisfied +22386,86354,Female,Loyal Customer,42,Business travel,Business,749,3,3,3,3,2,4,4,4,4,5,4,3,4,3,0,0.0,satisfied +22387,108498,Male,Loyal Customer,41,Business travel,Business,287,4,4,4,4,3,4,5,4,4,4,4,5,4,3,0,9.0,satisfied +22388,4894,Female,Loyal Customer,8,Personal Travel,Eco Plus,408,1,4,1,2,2,1,2,2,3,5,5,4,5,2,0,0.0,neutral or dissatisfied +22389,28896,Male,disloyal Customer,23,Business travel,Eco,987,4,4,4,3,3,4,3,3,5,3,1,2,4,3,0,0.0,satisfied +22390,57604,Male,disloyal Customer,20,Business travel,Eco,563,4,0,3,2,5,3,5,5,4,5,4,5,5,5,11,0.0,satisfied +22391,96216,Female,Loyal Customer,22,Business travel,Eco,546,2,3,3,3,2,2,3,2,3,1,3,4,3,2,0,0.0,neutral or dissatisfied +22392,6744,Male,Loyal Customer,48,Business travel,Business,2793,0,4,1,4,5,5,5,2,2,2,2,4,2,4,6,6.0,satisfied +22393,54092,Female,Loyal Customer,31,Personal Travel,Eco,1416,2,3,2,4,5,2,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +22394,122550,Female,Loyal Customer,16,Business travel,Business,3215,4,4,4,4,4,3,4,4,4,2,4,1,4,4,0,11.0,neutral or dissatisfied +22395,87197,Male,Loyal Customer,43,Business travel,Business,946,5,5,5,5,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +22396,120578,Male,Loyal Customer,35,Business travel,Business,2231,4,4,4,4,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +22397,68423,Female,Loyal Customer,32,Personal Travel,Eco,1045,1,1,1,2,4,1,4,4,1,2,2,4,1,4,0,0.0,neutral or dissatisfied +22398,122411,Female,disloyal Customer,21,Business travel,Eco,1176,4,3,3,4,5,4,5,5,4,2,3,5,4,5,4,21.0,satisfied +22399,914,Male,disloyal Customer,77,Business travel,Business,270,2,1,1,3,4,4,4,2,2,2,2,2,2,2,0,5.0,neutral or dissatisfied +22400,63726,Female,Loyal Customer,43,Business travel,Business,3083,2,2,2,2,2,3,1,5,5,5,5,3,5,2,0,0.0,satisfied +22401,23026,Male,Loyal Customer,54,Business travel,Business,1080,1,1,1,1,3,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +22402,39661,Female,Loyal Customer,44,Personal Travel,Eco,224,2,5,2,3,5,4,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +22403,101770,Female,disloyal Customer,26,Business travel,Business,1521,5,5,5,4,2,5,2,2,4,4,4,4,4,2,0,0.0,satisfied +22404,23251,Male,Loyal Customer,34,Business travel,Business,783,3,3,2,3,4,3,2,3,3,3,3,2,3,2,0,0.0,satisfied +22405,115469,Male,Loyal Customer,45,Business travel,Business,358,2,2,2,2,2,5,4,4,4,4,4,5,4,3,66,58.0,satisfied +22406,8171,Male,Loyal Customer,53,Business travel,Business,3626,3,3,3,3,4,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +22407,48628,Female,Loyal Customer,70,Business travel,Business,109,3,3,3,3,2,4,4,4,4,4,5,5,4,4,3,3.0,satisfied +22408,36098,Male,Loyal Customer,26,Personal Travel,Eco,399,2,4,3,3,1,3,1,1,5,3,5,3,5,1,0,0.0,neutral or dissatisfied +22409,116697,Female,Loyal Customer,22,Business travel,Eco Plus,337,2,1,1,1,2,2,1,2,2,5,4,2,3,2,0,0.0,neutral or dissatisfied +22410,74377,Male,disloyal Customer,49,Business travel,Business,1235,3,3,3,5,2,3,3,2,4,4,4,5,4,2,19,108.0,neutral or dissatisfied +22411,110625,Female,Loyal Customer,32,Business travel,Business,727,3,4,2,4,3,2,3,3,1,2,2,2,3,3,38,25.0,neutral or dissatisfied +22412,35395,Male,Loyal Customer,34,Business travel,Business,1076,1,0,0,3,4,4,4,3,3,0,3,1,3,4,0,0.0,neutral or dissatisfied +22413,34725,Female,Loyal Customer,29,Business travel,Business,2678,1,1,1,1,4,4,4,4,1,2,3,3,3,4,58,58.0,satisfied +22414,10460,Male,Loyal Customer,39,Business travel,Business,224,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +22415,127036,Female,Loyal Customer,56,Business travel,Business,3194,2,2,2,2,2,4,4,5,5,4,5,4,5,5,0,0.0,satisfied +22416,22116,Male,disloyal Customer,39,Business travel,Eco,694,1,1,1,4,3,1,3,3,2,1,1,3,1,3,0,0.0,neutral or dissatisfied +22417,51684,Male,Loyal Customer,25,Business travel,Business,493,3,4,4,4,3,3,3,3,1,2,4,2,3,3,0,0.0,neutral or dissatisfied +22418,90354,Male,Loyal Customer,42,Business travel,Business,406,5,5,5,5,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +22419,114844,Male,Loyal Customer,56,Business travel,Business,372,1,1,1,1,2,5,4,5,5,5,5,5,5,3,60,61.0,satisfied +22420,4760,Female,Loyal Customer,35,Business travel,Business,3382,1,1,1,1,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +22421,124985,Male,Loyal Customer,41,Business travel,Business,184,2,2,2,2,2,4,4,4,4,4,5,5,4,3,0,0.0,satisfied +22422,108768,Female,Loyal Customer,50,Business travel,Business,2483,4,4,4,4,3,4,5,4,4,5,4,3,4,3,19,25.0,satisfied +22423,87389,Female,Loyal Customer,55,Business travel,Business,3831,2,2,2,2,2,4,4,5,5,5,5,4,5,4,5,0.0,satisfied +22424,32800,Female,Loyal Customer,65,Business travel,Business,2197,3,3,3,3,2,2,4,5,5,5,3,3,5,2,3,5.0,satisfied +22425,69547,Female,Loyal Customer,33,Business travel,Business,2475,4,4,4,4,2,2,2,4,2,4,5,2,3,2,0,0.0,satisfied +22426,78090,Female,Loyal Customer,68,Personal Travel,Eco Plus,214,2,0,2,4,4,4,5,1,1,2,1,4,1,5,0,0.0,neutral or dissatisfied +22427,76399,Male,Loyal Customer,49,Personal Travel,Eco,931,2,5,2,3,5,2,5,5,3,3,5,4,4,5,50,36.0,neutral or dissatisfied +22428,78320,Female,Loyal Customer,56,Business travel,Business,1547,3,4,4,4,3,4,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +22429,63284,Male,Loyal Customer,37,Business travel,Business,1797,4,5,3,5,5,2,1,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +22430,122502,Male,Loyal Customer,45,Business travel,Business,3402,3,3,3,3,4,5,5,4,4,4,4,4,4,5,2,0.0,satisfied +22431,128288,Male,Loyal Customer,56,Business travel,Business,3622,3,3,3,3,4,5,4,3,3,3,3,3,3,5,14,24.0,satisfied +22432,103913,Male,Loyal Customer,53,Business travel,Business,770,2,2,2,2,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +22433,42505,Female,Loyal Customer,66,Personal Travel,Eco,541,2,4,2,1,5,5,4,5,5,2,5,3,5,4,0,0.0,neutral or dissatisfied +22434,70341,Female,disloyal Customer,56,Business travel,Eco,586,3,1,3,3,5,3,5,5,3,4,3,3,3,5,1,0.0,neutral or dissatisfied +22435,62891,Male,Loyal Customer,18,Business travel,Business,862,2,2,2,2,4,4,4,4,5,2,5,5,5,4,0,0.0,satisfied +22436,44133,Male,disloyal Customer,40,Business travel,Eco,98,2,0,2,3,4,2,4,4,3,3,4,3,5,4,14,23.0,neutral or dissatisfied +22437,128222,Male,Loyal Customer,44,Business travel,Eco,602,3,2,2,2,3,3,3,3,1,3,3,4,4,3,1,0.0,neutral or dissatisfied +22438,62223,Female,Loyal Customer,68,Personal Travel,Eco,2565,5,2,5,3,1,4,3,3,3,5,3,2,3,3,0,0.0,satisfied +22439,88049,Male,Loyal Customer,31,Business travel,Business,1639,1,1,1,1,3,4,3,3,5,5,4,4,5,3,1,2.0,satisfied +22440,75114,Male,Loyal Customer,59,Business travel,Business,1744,5,5,5,5,5,3,4,5,5,5,5,5,5,3,0,24.0,satisfied +22441,71426,Female,disloyal Customer,22,Business travel,Business,867,4,0,3,4,4,3,4,4,3,5,4,4,4,4,3,0.0,satisfied +22442,40618,Female,Loyal Customer,34,Personal Travel,Eco,391,2,5,2,4,2,2,2,2,4,2,3,3,4,2,0,0.0,neutral or dissatisfied +22443,48288,Female,Loyal Customer,60,Business travel,Business,1510,1,1,1,1,5,5,3,4,4,4,4,4,4,3,93,77.0,satisfied +22444,295,Female,Loyal Customer,54,Personal Travel,Eco,1250,4,1,4,2,3,2,2,4,4,4,4,3,4,3,123,120.0,neutral or dissatisfied +22445,28693,Male,Loyal Customer,46,Business travel,Business,2182,3,3,3,3,4,5,3,5,5,5,5,4,5,1,0,0.0,satisfied +22446,61398,Female,Loyal Customer,30,Personal Travel,Eco,679,2,1,1,2,4,1,2,4,2,3,2,3,2,4,8,0.0,neutral or dissatisfied +22447,46460,Male,Loyal Customer,56,Business travel,Business,125,1,1,4,1,5,4,4,5,5,5,4,5,5,3,19,17.0,satisfied +22448,127606,Female,Loyal Customer,58,Business travel,Business,1773,4,4,4,4,3,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +22449,96893,Female,Loyal Customer,69,Personal Travel,Eco,1105,1,4,1,4,3,4,4,4,4,1,4,1,4,1,20,28.0,neutral or dissatisfied +22450,27811,Female,Loyal Customer,31,Business travel,Business,1533,4,4,4,4,5,5,5,5,5,2,4,1,4,5,0,0.0,satisfied +22451,87090,Female,Loyal Customer,30,Business travel,Eco,640,0,0,0,1,4,0,4,4,4,5,3,1,4,4,6,23.0,satisfied +22452,123673,Male,Loyal Customer,58,Business travel,Business,1614,3,5,5,5,3,3,3,2,2,2,3,2,2,3,0,0.0,neutral or dissatisfied +22453,58747,Male,disloyal Customer,20,Business travel,Eco,1005,2,2,2,3,2,2,5,2,5,5,5,3,5,2,17,26.0,neutral or dissatisfied +22454,113290,Male,Loyal Customer,33,Business travel,Business,2046,4,4,4,4,5,5,5,5,4,4,5,3,5,5,0,0.0,satisfied +22455,24031,Female,Loyal Customer,43,Business travel,Eco,427,5,5,3,3,5,3,5,5,5,5,5,3,5,2,1,0.0,satisfied +22456,89265,Male,disloyal Customer,23,Business travel,Business,453,4,4,4,4,5,4,5,5,5,2,5,4,4,5,0,0.0,satisfied +22457,83527,Male,Loyal Customer,27,Personal Travel,Eco,946,2,4,2,3,1,2,1,1,3,2,3,3,4,1,19,3.0,neutral or dissatisfied +22458,28609,Female,Loyal Customer,36,Business travel,Business,2378,3,3,3,3,2,4,3,4,4,4,4,4,4,5,10,0.0,satisfied +22459,48153,Male,Loyal Customer,55,Business travel,Business,414,4,1,1,1,4,3,3,4,4,4,4,1,4,1,58,62.0,neutral or dissatisfied +22460,117627,Male,Loyal Customer,45,Personal Travel,Eco,347,1,5,1,2,5,1,5,5,3,2,5,3,5,5,35,34.0,neutral or dissatisfied +22461,120586,Male,Loyal Customer,49,Business travel,Eco,980,3,2,2,2,4,3,4,4,4,4,3,2,3,4,76,96.0,neutral or dissatisfied +22462,81604,Male,Loyal Customer,36,Business travel,Business,3137,1,4,4,4,2,1,1,1,2,4,3,1,4,1,221,272.0,neutral or dissatisfied +22463,75019,Female,Loyal Customer,53,Business travel,Business,236,5,2,2,2,2,3,3,5,5,4,5,4,5,3,1,9.0,neutral or dissatisfied +22464,37042,Male,Loyal Customer,74,Business travel,Eco,594,4,4,4,4,4,4,4,4,2,4,3,2,4,4,23,28.0,neutral or dissatisfied +22465,69879,Female,Loyal Customer,27,Business travel,Business,2248,1,1,1,1,2,2,2,2,5,4,5,5,4,2,0,0.0,satisfied +22466,82212,Male,Loyal Customer,49,Business travel,Business,405,4,4,1,4,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +22467,70140,Female,Loyal Customer,69,Personal Travel,Eco,460,4,4,4,2,1,5,3,1,1,4,1,2,1,5,0,3.0,satisfied +22468,69274,Female,Loyal Customer,49,Personal Travel,Eco,740,2,5,2,2,2,5,5,3,3,2,3,5,3,5,0,10.0,neutral or dissatisfied +22469,81097,Male,Loyal Customer,57,Business travel,Business,2347,2,2,2,2,4,4,5,4,4,4,4,4,4,3,121,102.0,satisfied +22470,62102,Female,Loyal Customer,18,Personal Travel,Business,2454,3,5,3,4,4,3,5,4,2,2,5,2,1,4,2,0.0,neutral or dissatisfied +22471,41261,Female,Loyal Customer,44,Personal Travel,Eco,1034,3,2,3,3,2,3,3,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +22472,61293,Female,Loyal Customer,7,Personal Travel,Eco,967,2,5,2,1,5,2,5,5,4,3,5,3,5,5,1,0.0,neutral or dissatisfied +22473,44746,Female,Loyal Customer,39,Business travel,Business,589,3,4,4,4,3,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +22474,7718,Male,disloyal Customer,27,Business travel,Business,806,0,1,1,2,3,1,3,3,4,4,4,4,5,3,0,0.0,satisfied +22475,104862,Female,Loyal Customer,38,Business travel,Eco,327,2,5,5,5,2,2,2,2,1,3,4,3,4,2,6,8.0,neutral or dissatisfied +22476,110288,Female,Loyal Customer,46,Business travel,Business,1790,4,4,4,4,4,4,4,4,2,5,5,4,3,4,142,137.0,satisfied +22477,105846,Female,Loyal Customer,11,Business travel,Eco Plus,883,3,3,2,2,3,3,4,3,4,2,3,2,3,3,5,10.0,neutral or dissatisfied +22478,42333,Female,Loyal Customer,33,Personal Travel,Eco,834,2,5,2,1,4,2,2,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +22479,42681,Female,Loyal Customer,34,Business travel,Business,3296,4,4,4,4,5,2,2,4,4,4,4,3,4,1,0,0.0,satisfied +22480,93235,Male,Loyal Customer,32,Personal Travel,Eco,1694,4,4,4,4,4,4,4,4,5,2,4,3,3,4,26,31.0,neutral or dissatisfied +22481,61199,Male,Loyal Customer,27,Business travel,Business,862,1,1,1,1,5,5,5,5,5,5,4,5,4,5,0,13.0,satisfied +22482,62720,Female,Loyal Customer,25,Business travel,Business,2486,3,3,2,3,5,5,5,3,5,5,4,5,5,5,0,3.0,satisfied +22483,98345,Male,Loyal Customer,49,Business travel,Business,3895,1,1,1,1,4,5,4,2,2,2,2,4,2,4,3,0.0,satisfied +22484,116418,Male,Loyal Customer,63,Personal Travel,Eco,373,3,5,4,4,2,4,2,2,3,3,5,3,4,2,0,1.0,neutral or dissatisfied +22485,116352,Female,Loyal Customer,17,Personal Travel,Eco,342,2,5,2,2,3,2,3,3,5,4,4,5,4,3,0,0.0,neutral or dissatisfied +22486,58465,Male,Loyal Customer,67,Personal Travel,Eco Plus,733,4,4,4,3,1,4,1,1,1,3,3,2,3,1,2,0.0,neutral or dissatisfied +22487,83841,Male,Loyal Customer,31,Personal Travel,Eco,425,4,4,4,5,2,4,1,2,4,2,5,5,4,2,0,0.0,satisfied +22488,26833,Female,Loyal Customer,55,Business travel,Eco,224,5,1,1,1,5,2,1,5,5,5,5,4,5,5,0,0.0,satisfied +22489,60541,Female,Loyal Customer,69,Personal Travel,Eco,862,3,5,3,4,5,5,4,2,2,3,3,3,2,5,4,18.0,neutral or dissatisfied +22490,119591,Female,Loyal Customer,43,Business travel,Business,1979,4,4,4,4,3,3,4,4,4,4,4,1,4,2,0,0.0,neutral or dissatisfied +22491,119274,Female,Loyal Customer,42,Business travel,Business,214,2,2,5,2,4,5,5,5,5,5,4,4,5,3,0,0.0,satisfied +22492,61784,Female,Loyal Customer,64,Personal Travel,Eco,1635,2,4,2,3,5,4,4,3,3,2,3,4,3,5,3,0.0,neutral or dissatisfied +22493,54330,Female,Loyal Customer,20,Personal Travel,Eco,1597,2,5,2,4,2,2,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +22494,72764,Male,Loyal Customer,23,Business travel,Business,3260,4,4,4,4,5,5,5,5,4,3,4,5,4,5,27,6.0,satisfied +22495,68657,Female,Loyal Customer,38,Business travel,Business,175,4,5,5,5,3,3,3,1,1,1,4,1,1,1,0,0.0,neutral or dissatisfied +22496,70097,Female,Loyal Customer,42,Business travel,Business,3318,3,3,3,3,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +22497,10976,Female,Loyal Customer,43,Business travel,Eco,201,2,3,3,3,4,3,4,1,1,2,1,1,1,1,24,26.0,neutral or dissatisfied +22498,49805,Male,disloyal Customer,37,Business travel,Eco,262,1,4,1,3,3,1,3,3,1,3,4,2,3,3,0,0.0,neutral or dissatisfied +22499,32797,Male,disloyal Customer,37,Business travel,Eco,163,3,0,3,1,3,3,3,3,3,5,5,3,1,3,5,5.0,neutral or dissatisfied +22500,33790,Female,Loyal Customer,33,Personal Travel,Eco,588,2,5,2,1,4,2,4,4,3,5,5,5,2,4,0,1.0,neutral or dissatisfied +22501,62387,Male,Loyal Customer,30,Business travel,Eco,2704,4,4,4,4,4,4,4,4,2,4,4,2,4,4,21,11.0,satisfied +22502,40969,Female,Loyal Customer,36,Personal Travel,Eco,507,2,5,2,3,4,2,4,4,1,5,5,4,3,4,0,0.0,neutral or dissatisfied +22503,19584,Male,Loyal Customer,56,Personal Travel,Eco,160,3,3,3,4,4,3,1,4,1,3,4,4,3,4,29,25.0,neutral or dissatisfied +22504,80890,Female,Loyal Customer,43,Personal Travel,Eco Plus,484,3,2,3,3,2,2,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +22505,17739,Male,disloyal Customer,37,Business travel,Eco,383,3,4,3,4,3,3,3,3,1,2,3,4,4,3,0,0.0,neutral or dissatisfied +22506,18807,Male,Loyal Customer,41,Business travel,Eco,448,5,1,1,1,5,5,5,5,5,1,1,5,1,5,0,2.0,satisfied +22507,1346,Male,Loyal Customer,58,Business travel,Business,3786,5,5,5,5,3,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +22508,54874,Female,Loyal Customer,22,Business travel,Eco,862,2,5,1,5,2,2,1,2,3,3,4,2,3,2,23,11.0,neutral or dissatisfied +22509,52813,Male,disloyal Customer,12,Business travel,Eco,1341,4,4,4,3,4,4,4,4,2,5,2,1,3,4,5,31.0,neutral or dissatisfied +22510,32681,Female,disloyal Customer,33,Business travel,Eco,201,2,0,2,1,2,2,2,2,4,2,5,2,1,2,1,3.0,neutral or dissatisfied +22511,125601,Female,Loyal Customer,27,Personal Travel,Eco,1587,3,4,3,3,2,3,4,2,4,2,4,5,4,2,6,3.0,neutral or dissatisfied +22512,112528,Female,Loyal Customer,18,Personal Travel,Eco,862,2,4,2,4,1,2,1,1,5,3,4,5,5,1,9,1.0,neutral or dissatisfied +22513,52965,Male,disloyal Customer,30,Business travel,Eco,1082,3,3,3,3,3,2,2,1,4,2,2,2,1,2,0,2.0,neutral or dissatisfied +22514,63757,Female,Loyal Customer,13,Personal Travel,Eco Plus,1660,3,4,3,1,2,3,2,2,3,4,5,5,5,2,0,3.0,neutral or dissatisfied +22515,2888,Female,Loyal Customer,14,Personal Travel,Eco,409,2,1,2,3,3,2,5,3,4,3,3,3,2,3,15,28.0,neutral or dissatisfied +22516,101210,Male,Loyal Customer,65,Personal Travel,Eco,1235,1,5,1,2,2,1,2,2,5,4,4,5,4,2,7,0.0,neutral or dissatisfied +22517,99704,Female,Loyal Customer,43,Business travel,Business,2026,1,2,2,2,1,2,4,1,1,1,1,1,1,3,14,34.0,neutral or dissatisfied +22518,62406,Female,Loyal Customer,31,Personal Travel,Eco,2704,4,4,4,1,3,4,3,3,3,5,4,3,5,3,5,1.0,neutral or dissatisfied +22519,69302,Female,Loyal Customer,39,Business travel,Business,3600,2,2,2,2,5,3,3,2,2,2,2,4,2,4,0,0.0,neutral or dissatisfied +22520,19812,Male,Loyal Customer,38,Business travel,Eco,528,3,5,5,5,3,3,3,3,2,4,4,1,5,3,0,0.0,satisfied +22521,82650,Male,disloyal Customer,26,Business travel,Business,120,2,5,3,2,2,3,4,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +22522,9410,Female,disloyal Customer,22,Business travel,Eco,1136,3,3,3,4,5,3,1,5,1,3,3,2,3,5,18,47.0,neutral or dissatisfied +22523,8067,Female,disloyal Customer,23,Business travel,Business,125,4,0,5,4,3,5,3,3,3,3,5,5,4,3,0,0.0,satisfied +22524,92872,Female,Loyal Customer,42,Business travel,Business,134,0,4,0,4,2,5,4,4,4,5,5,4,4,3,23,14.0,satisfied +22525,28086,Male,Loyal Customer,43,Business travel,Business,2794,2,2,2,2,2,1,3,4,4,4,4,4,4,1,1,0.0,satisfied +22526,43819,Female,Loyal Customer,25,Personal Travel,Business,174,4,4,4,4,4,4,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +22527,40880,Female,Loyal Customer,11,Personal Travel,Eco,558,2,2,2,4,1,2,1,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +22528,11982,Male,Loyal Customer,33,Business travel,Business,3475,2,1,2,2,5,5,5,5,4,4,5,2,5,5,45,25.0,satisfied +22529,129821,Female,Loyal Customer,62,Personal Travel,Eco,308,2,5,4,3,2,4,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +22530,388,Male,Loyal Customer,69,Business travel,Business,2848,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +22531,70564,Female,disloyal Customer,30,Business travel,Eco,858,3,4,4,5,3,4,3,3,3,3,1,3,5,3,0,8.0,neutral or dissatisfied +22532,44540,Male,Loyal Customer,49,Personal Travel,Eco,128,0,2,0,4,2,0,2,2,1,2,4,2,4,2,0,0.0,satisfied +22533,17216,Male,Loyal Customer,7,Personal Travel,Eco Plus,1107,3,3,2,4,1,2,1,1,4,4,1,2,1,1,0,0.0,neutral or dissatisfied +22534,70448,Female,Loyal Customer,10,Personal Travel,Eco,187,3,4,0,2,5,0,5,5,4,4,5,5,5,5,0,0.0,neutral or dissatisfied +22535,27067,Female,disloyal Customer,27,Business travel,Eco,999,2,2,2,4,5,2,5,5,4,1,4,1,2,5,0,0.0,neutral or dissatisfied +22536,69559,Male,Loyal Customer,28,Business travel,Business,2475,1,1,1,1,4,4,4,3,2,3,5,4,3,4,0,3.0,satisfied +22537,73074,Male,Loyal Customer,39,Business travel,Business,2855,4,4,4,4,5,4,5,3,3,3,3,4,3,3,5,0.0,satisfied +22538,44146,Male,Loyal Customer,17,Personal Travel,Eco,120,3,5,3,4,4,3,4,4,2,4,1,3,5,4,33,13.0,neutral or dissatisfied +22539,10380,Female,Loyal Customer,46,Business travel,Business,1998,4,4,4,4,4,5,5,4,4,4,4,4,4,5,18,23.0,satisfied +22540,91135,Female,Loyal Customer,51,Personal Travel,Eco,406,2,5,2,5,5,5,5,5,5,2,5,3,5,3,6,6.0,neutral or dissatisfied +22541,92381,Female,Loyal Customer,32,Personal Travel,Business,1947,4,4,4,1,5,4,5,5,5,4,3,4,5,5,0,0.0,neutral or dissatisfied +22542,22334,Female,disloyal Customer,23,Business travel,Eco,143,1,1,1,3,5,1,5,5,1,1,3,4,3,5,87,84.0,neutral or dissatisfied +22543,48173,Female,Loyal Customer,49,Business travel,Eco,236,4,1,1,1,1,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +22544,88964,Male,disloyal Customer,25,Business travel,Eco,1199,3,2,2,5,5,2,5,5,4,4,4,3,5,5,6,0.0,satisfied +22545,38963,Male,Loyal Customer,8,Personal Travel,Business,230,2,4,2,1,1,2,1,1,3,3,5,3,5,1,0,13.0,neutral or dissatisfied +22546,74384,Male,Loyal Customer,46,Business travel,Business,1431,3,3,3,3,3,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +22547,66608,Female,Loyal Customer,46,Personal Travel,Eco,761,3,4,3,3,1,1,5,1,1,3,1,1,1,2,5,0.0,neutral or dissatisfied +22548,66014,Male,disloyal Customer,37,Business travel,Business,1055,3,3,3,3,1,3,1,1,4,4,5,4,4,1,0,0.0,neutral or dissatisfied +22549,89379,Male,Loyal Customer,49,Business travel,Business,134,5,5,4,5,4,4,5,4,4,4,4,4,4,5,6,0.0,satisfied +22550,102406,Female,Loyal Customer,33,Personal Travel,Eco,386,1,5,1,4,3,1,3,3,3,2,4,3,5,3,0,0.0,neutral or dissatisfied +22551,2783,Female,Loyal Customer,52,Business travel,Business,1718,1,1,1,1,3,5,5,5,5,5,5,4,5,3,40,34.0,satisfied +22552,38324,Male,Loyal Customer,52,Personal Travel,Business,1111,2,4,3,3,1,4,3,4,4,3,1,1,4,1,0,17.0,neutral or dissatisfied +22553,126059,Female,Loyal Customer,41,Business travel,Business,3615,1,1,1,1,4,4,5,5,5,5,5,4,5,5,0,5.0,satisfied +22554,53804,Male,Loyal Customer,50,Business travel,Eco,140,4,5,5,5,4,4,4,4,4,3,2,5,1,4,16,11.0,satisfied +22555,75042,Female,Loyal Customer,42,Personal Travel,Eco,236,4,4,0,3,2,4,3,5,5,0,5,2,5,2,0,0.0,neutral or dissatisfied +22556,37065,Male,Loyal Customer,41,Business travel,Business,1072,2,2,3,2,4,3,5,5,5,5,5,4,5,5,7,3.0,satisfied +22557,122929,Male,Loyal Customer,46,Business travel,Business,2464,2,2,2,2,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22558,100721,Male,Loyal Customer,56,Business travel,Business,2682,1,1,1,1,4,4,4,5,5,5,5,4,5,5,50,51.0,satisfied +22559,127650,Male,disloyal Customer,54,Business travel,Business,990,5,4,4,4,1,5,1,1,4,4,3,5,5,1,0,0.0,satisfied +22560,12577,Female,disloyal Customer,26,Business travel,Eco,542,5,0,5,1,4,0,4,4,5,4,1,3,1,4,13,6.0,satisfied +22561,90636,Male,Loyal Customer,40,Business travel,Business,581,2,3,3,3,2,4,3,2,2,2,2,1,2,4,4,0.0,neutral or dissatisfied +22562,68748,Male,disloyal Customer,22,Business travel,Eco,1021,1,0,0,3,0,5,5,4,2,4,4,5,4,5,269,255.0,neutral or dissatisfied +22563,67739,Male,Loyal Customer,49,Business travel,Business,1205,4,1,1,1,4,2,3,4,4,3,4,2,4,4,0,0.0,neutral or dissatisfied +22564,117608,Female,Loyal Customer,55,Business travel,Business,2284,5,5,5,5,5,4,5,5,5,5,5,5,5,5,11,2.0,satisfied +22565,122158,Female,Loyal Customer,52,Business travel,Business,2638,5,5,5,5,2,5,5,4,4,4,4,3,4,3,32,72.0,satisfied +22566,111707,Female,Loyal Customer,54,Business travel,Eco,495,1,1,1,1,5,3,4,1,1,1,1,3,1,4,56,44.0,neutral or dissatisfied +22567,113912,Female,Loyal Customer,38,Business travel,Business,2329,1,1,1,1,4,5,4,4,4,4,4,4,4,4,10,0.0,satisfied +22568,26370,Male,Loyal Customer,28,Business travel,Eco,991,1,5,5,5,1,1,1,1,4,4,4,1,3,1,0,0.0,neutral or dissatisfied +22569,81996,Female,Loyal Customer,51,Business travel,Business,1589,3,3,3,3,2,4,5,5,5,5,5,3,5,5,36,51.0,satisfied +22570,76938,Female,Loyal Customer,41,Business travel,Business,1727,1,1,1,1,2,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +22571,36376,Female,disloyal Customer,26,Business travel,Eco,200,2,0,1,2,5,1,5,5,1,5,5,3,3,5,0,0.0,neutral or dissatisfied +22572,117347,Female,Loyal Customer,43,Business travel,Business,296,3,3,3,3,5,4,4,5,5,5,5,5,5,3,3,0.0,satisfied +22573,44143,Male,Loyal Customer,53,Personal Travel,Eco,98,3,4,3,4,5,3,3,5,4,5,5,5,5,5,45,56.0,neutral or dissatisfied +22574,24327,Male,Loyal Customer,26,Business travel,Business,2839,3,5,5,5,3,3,3,3,1,5,4,3,4,3,75,65.0,neutral or dissatisfied +22575,92952,Male,disloyal Customer,25,Business travel,Business,134,3,4,2,3,5,2,1,5,3,4,4,3,5,5,10,16.0,neutral or dissatisfied +22576,91703,Male,Loyal Customer,41,Business travel,Business,2486,3,3,2,3,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +22577,40283,Female,Loyal Customer,11,Personal Travel,Eco,358,1,4,5,2,4,5,4,4,5,3,4,5,4,4,0,19.0,neutral or dissatisfied +22578,127020,Female,Loyal Customer,51,Business travel,Business,2234,5,5,5,5,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +22579,23587,Female,Loyal Customer,54,Business travel,Business,2505,3,2,3,3,3,1,4,4,4,4,4,3,4,5,13,33.0,satisfied +22580,128355,Male,disloyal Customer,25,Business travel,Business,338,3,0,3,5,2,3,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +22581,26851,Male,Loyal Customer,61,Personal Travel,Eco,224,5,5,5,5,4,5,5,4,4,2,4,3,4,4,0,0.0,satisfied +22582,114495,Male,Loyal Customer,46,Business travel,Business,3450,4,4,4,4,5,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +22583,101975,Male,Loyal Customer,58,Personal Travel,Eco,628,2,4,2,3,5,2,5,5,4,2,4,4,4,5,17,5.0,neutral or dissatisfied +22584,487,Male,disloyal Customer,23,Business travel,Business,158,0,5,0,2,2,0,2,2,4,4,4,3,4,2,0,0.0,satisfied +22585,66130,Female,Loyal Customer,55,Personal Travel,Eco,583,2,2,2,4,5,4,4,5,5,2,3,4,5,3,69,65.0,neutral or dissatisfied +22586,788,Female,disloyal Customer,30,Business travel,Business,89,1,2,2,4,2,2,2,2,4,4,4,1,4,2,9,0.0,neutral or dissatisfied +22587,66262,Male,Loyal Customer,34,Personal Travel,Eco,550,1,4,1,2,3,1,3,3,3,4,5,5,4,3,0,0.0,neutral or dissatisfied +22588,77310,Male,Loyal Customer,35,Business travel,Business,1674,1,1,1,1,4,5,5,5,5,5,5,3,5,5,0,4.0,satisfied +22589,104849,Male,Loyal Customer,59,Personal Travel,Business,327,3,0,3,4,4,4,5,1,1,3,1,3,1,3,10,0.0,neutral or dissatisfied +22590,105375,Female,Loyal Customer,51,Business travel,Business,1877,3,3,5,3,2,4,4,4,4,4,4,4,4,5,6,0.0,satisfied +22591,57943,Female,Loyal Customer,52,Personal Travel,Eco,837,4,5,4,3,2,4,4,5,5,4,4,5,5,4,0,11.0,neutral or dissatisfied +22592,5596,Female,Loyal Customer,54,Business travel,Business,685,2,2,5,2,3,4,4,4,4,4,4,4,4,5,2,0.0,satisfied +22593,117875,Female,disloyal Customer,24,Business travel,Business,365,4,0,4,3,1,4,1,1,4,5,4,5,4,1,0,0.0,satisfied +22594,83570,Female,disloyal Customer,24,Business travel,Eco,936,5,5,5,3,4,5,4,4,4,5,5,4,4,4,0,0.0,satisfied +22595,15088,Female,Loyal Customer,62,Business travel,Business,2341,2,1,1,1,3,3,4,2,2,2,2,4,2,3,19,6.0,neutral or dissatisfied +22596,2643,Male,Loyal Customer,30,Business travel,Business,622,1,1,1,1,2,2,2,2,3,5,5,4,5,2,0,0.0,satisfied +22597,31254,Male,Loyal Customer,12,Personal Travel,Business,533,2,4,2,4,5,2,5,5,5,2,5,5,4,5,13,12.0,neutral or dissatisfied +22598,3452,Male,Loyal Customer,10,Personal Travel,Eco,315,4,5,2,4,3,2,2,3,3,2,5,5,4,3,0,0.0,neutral or dissatisfied +22599,32733,Female,Loyal Customer,47,Business travel,Business,2701,2,2,2,2,2,4,4,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +22600,51074,Male,Loyal Customer,27,Personal Travel,Eco,193,2,5,2,2,4,2,4,4,5,4,2,5,1,4,0,0.0,neutral or dissatisfied +22601,102219,Male,disloyal Customer,23,Business travel,Business,407,4,0,3,5,4,3,4,4,4,3,5,3,4,4,38,43.0,satisfied +22602,1325,Male,Loyal Customer,39,Business travel,Business,3752,5,5,5,5,3,5,4,4,4,4,5,3,4,5,12,8.0,satisfied +22603,8382,Male,Loyal Customer,61,Personal Travel,Eco,701,3,4,3,2,4,3,4,4,5,2,5,5,5,4,0,5.0,neutral or dissatisfied +22604,19030,Male,Loyal Customer,53,Personal Travel,Eco,871,2,2,1,3,1,1,1,1,1,3,3,1,2,1,22,54.0,neutral or dissatisfied +22605,90228,Female,Loyal Customer,54,Business travel,Eco Plus,1084,2,1,1,1,2,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +22606,129689,Male,Loyal Customer,49,Business travel,Business,1933,2,2,2,2,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +22607,19201,Female,Loyal Customer,29,Personal Travel,Eco,542,3,5,3,2,5,3,5,5,2,5,3,4,5,5,0,4.0,neutral or dissatisfied +22608,57075,Male,Loyal Customer,34,Personal Travel,Eco,2065,4,1,4,2,4,4,4,4,4,1,2,1,3,4,0,0.0,neutral or dissatisfied +22609,65881,Female,Loyal Customer,50,Business travel,Eco Plus,1389,3,3,3,3,1,4,3,3,3,3,3,4,3,4,27,40.0,neutral or dissatisfied +22610,121450,Female,Loyal Customer,22,Business travel,Business,3873,4,1,1,1,4,4,4,4,1,4,4,1,4,4,0,0.0,neutral or dissatisfied +22611,34752,Female,disloyal Customer,27,Business travel,Eco,264,1,2,1,2,3,1,3,3,3,3,2,1,2,3,0,13.0,neutral or dissatisfied +22612,25706,Female,Loyal Customer,36,Business travel,Business,2634,1,1,3,1,2,1,1,5,5,5,5,2,5,5,0,0.0,satisfied +22613,231,Female,Loyal Customer,47,Business travel,Business,1957,1,1,1,1,5,5,4,4,4,4,5,3,4,3,14,10.0,satisfied +22614,57291,Male,Loyal Customer,28,Personal Travel,Eco Plus,628,5,4,5,3,4,5,4,4,2,4,1,4,4,4,0,0.0,satisfied +22615,34049,Female,Loyal Customer,40,Business travel,Eco,1674,4,2,2,2,4,5,4,4,2,3,5,4,5,4,2,0.0,satisfied +22616,81899,Male,Loyal Customer,28,Business travel,Business,680,2,1,1,1,2,2,2,2,4,2,2,2,2,2,9,45.0,neutral or dissatisfied +22617,22988,Male,Loyal Customer,7,Personal Travel,Eco,956,2,2,3,4,3,3,3,3,4,2,3,4,4,3,16,3.0,neutral or dissatisfied +22618,22377,Male,disloyal Customer,22,Business travel,Eco,143,3,1,3,4,3,3,3,3,5,4,4,3,1,3,114,136.0,neutral or dissatisfied +22619,95254,Female,Loyal Customer,53,Personal Travel,Eco,187,2,5,2,1,3,3,1,1,1,2,1,4,1,4,25,22.0,neutral or dissatisfied +22620,49691,Female,Loyal Customer,59,Business travel,Business,3835,2,1,1,1,2,3,4,1,1,1,2,3,1,4,15,46.0,neutral or dissatisfied +22621,47952,Male,Loyal Customer,29,Personal Travel,Eco,550,1,4,1,5,2,1,2,2,4,4,4,5,4,2,0,0.0,neutral or dissatisfied +22622,75741,Male,Loyal Customer,25,Business travel,Business,868,2,3,2,3,2,3,2,2,2,1,3,2,3,2,13,14.0,neutral or dissatisfied +22623,95427,Male,Loyal Customer,41,Business travel,Business,2994,1,1,1,1,3,4,4,5,5,5,5,3,5,4,4,8.0,satisfied +22624,63855,Female,Loyal Customer,56,Business travel,Business,2534,3,3,3,3,5,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +22625,100081,Female,Loyal Customer,35,Personal Travel,Eco Plus,289,2,4,2,3,3,2,4,3,5,2,4,5,4,3,0,0.0,neutral or dissatisfied +22626,120130,Female,disloyal Customer,30,Business travel,Eco Plus,1576,3,3,3,4,2,3,2,2,1,3,4,3,3,2,0,0.0,neutral or dissatisfied +22627,64610,Female,Loyal Customer,31,Business travel,Business,3880,4,4,2,4,4,4,4,4,3,4,5,4,5,4,0,0.0,satisfied +22628,54017,Male,Loyal Customer,21,Business travel,Business,1091,4,4,5,4,4,5,4,4,5,2,2,2,4,4,10,0.0,satisfied +22629,48881,Male,Loyal Customer,45,Business travel,Eco,373,2,4,4,4,2,2,2,2,3,5,2,3,2,2,0,13.0,satisfied +22630,114216,Male,Loyal Customer,48,Business travel,Business,2981,1,3,3,3,3,3,4,1,1,1,1,1,1,3,5,1.0,neutral or dissatisfied +22631,34533,Male,Loyal Customer,23,Business travel,Business,1924,2,5,1,5,2,2,2,2,4,5,3,3,4,2,0,0.0,neutral or dissatisfied +22632,64847,Male,Loyal Customer,46,Business travel,Business,2665,3,5,4,5,5,4,3,3,3,3,3,4,3,3,0,0.0,neutral or dissatisfied +22633,126462,Male,Loyal Customer,51,Business travel,Business,1849,2,2,2,2,2,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +22634,36633,Female,disloyal Customer,23,Business travel,Eco,785,2,2,2,4,1,2,1,1,1,3,3,2,3,1,0,0.0,neutral or dissatisfied +22635,46373,Female,Loyal Customer,59,Business travel,Business,1013,4,5,5,5,5,3,3,4,4,4,4,1,4,2,22,27.0,neutral or dissatisfied +22636,93744,Female,disloyal Customer,21,Business travel,Business,368,4,2,4,3,3,4,3,3,5,5,4,4,5,3,0,0.0,satisfied +22637,74080,Male,Loyal Customer,45,Business travel,Business,2845,3,3,2,3,4,5,4,5,5,5,5,5,5,5,27,39.0,satisfied +22638,13471,Male,Loyal Customer,31,Business travel,Eco Plus,409,0,0,0,1,5,0,5,5,5,4,1,1,5,5,7,10.0,satisfied +22639,125618,Female,Loyal Customer,70,Personal Travel,Business,814,4,0,4,3,2,5,5,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +22640,53183,Female,Loyal Customer,39,Business travel,Eco,589,4,4,2,4,4,4,4,4,4,1,1,2,3,4,31,19.0,satisfied +22641,11357,Male,Loyal Customer,32,Personal Travel,Eco,429,4,4,2,3,1,2,1,1,5,4,3,5,4,1,0,0.0,neutral or dissatisfied +22642,59509,Female,disloyal Customer,9,Business travel,Eco,854,2,2,2,3,2,2,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +22643,120705,Female,Loyal Customer,64,Personal Travel,Eco,280,1,4,1,2,2,5,4,3,3,1,5,4,3,4,10,56.0,neutral or dissatisfied +22644,78724,Female,Loyal Customer,37,Business travel,Business,2130,3,3,3,3,3,5,4,5,5,5,5,5,5,3,21,11.0,satisfied +22645,118070,Female,disloyal Customer,15,Business travel,Eco Plus,1262,1,3,1,4,5,1,5,5,1,2,4,4,3,5,1,0.0,neutral or dissatisfied +22646,12406,Female,disloyal Customer,16,Business travel,Eco,192,3,2,3,3,3,3,3,3,1,2,4,3,4,3,32,22.0,neutral or dissatisfied +22647,90523,Male,disloyal Customer,27,Business travel,Business,406,4,4,4,5,2,4,2,2,5,3,5,5,4,2,2,0.0,neutral or dissatisfied +22648,84930,Female,Loyal Customer,54,Personal Travel,Eco,547,4,4,4,4,4,4,4,5,5,4,5,1,5,4,0,0.0,satisfied +22649,112529,Female,Loyal Customer,60,Personal Travel,Eco,957,2,5,2,4,4,5,4,2,2,2,2,4,2,3,118,104.0,neutral or dissatisfied +22650,101799,Male,Loyal Customer,19,Business travel,Business,1521,3,2,2,2,3,3,3,3,1,4,4,4,4,3,1,2.0,neutral or dissatisfied +22651,75110,Female,Loyal Customer,24,Business travel,Business,1744,2,2,2,2,5,5,5,5,5,2,5,5,5,5,0,0.0,satisfied +22652,79448,Female,Loyal Customer,58,Business travel,Business,2967,4,4,5,4,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +22653,61897,Male,Loyal Customer,11,Personal Travel,Eco Plus,2521,2,4,2,3,1,2,1,1,1,1,4,3,4,1,13,4.0,neutral or dissatisfied +22654,66956,Male,Loyal Customer,51,Business travel,Business,964,3,3,3,3,2,4,5,5,5,5,5,5,5,5,28,8.0,satisfied +22655,16255,Female,disloyal Customer,29,Business travel,Eco,748,5,5,5,2,2,5,3,2,3,3,2,2,4,2,0,0.0,satisfied +22656,103717,Female,Loyal Customer,55,Personal Travel,Eco,405,3,4,3,1,4,4,5,1,1,3,1,5,1,3,0,10.0,neutral or dissatisfied +22657,86016,Female,disloyal Customer,40,Business travel,Business,554,3,3,3,2,5,3,5,5,3,5,5,5,4,5,18,5.0,neutral or dissatisfied +22658,106571,Female,Loyal Customer,45,Business travel,Business,1506,3,3,3,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +22659,33393,Male,Loyal Customer,56,Business travel,Business,2917,3,3,3,3,4,4,4,5,1,4,5,4,4,4,0,0.0,satisfied +22660,100739,Male,Loyal Customer,42,Business travel,Eco,328,2,1,1,1,2,2,2,2,4,1,4,1,4,2,28,19.0,neutral or dissatisfied +22661,52837,Male,Loyal Customer,23,Business travel,Eco,1721,4,5,5,5,4,4,3,4,5,5,5,3,2,4,2,0.0,satisfied +22662,109789,Male,disloyal Customer,25,Business travel,Eco,1052,2,1,1,2,5,1,5,5,4,2,4,3,5,5,24,12.0,neutral or dissatisfied +22663,97580,Male,disloyal Customer,36,Business travel,Eco,337,1,1,1,4,1,1,1,1,3,2,3,4,3,1,29,30.0,neutral or dissatisfied +22664,10253,Female,Loyal Customer,43,Personal Travel,Business,163,2,4,2,1,5,5,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +22665,32005,Male,Loyal Customer,33,Personal Travel,Business,216,2,0,2,1,5,2,1,5,4,2,5,4,4,5,0,0.0,neutral or dissatisfied +22666,22032,Female,Loyal Customer,30,Personal Travel,Eco Plus,503,3,5,3,1,1,3,2,1,4,5,5,5,4,1,0,0.0,neutral or dissatisfied +22667,64221,Male,Loyal Customer,30,Business travel,Business,1660,4,4,4,4,4,4,4,4,3,2,3,3,4,4,0,2.0,satisfied +22668,127668,Male,Loyal Customer,35,Business travel,Business,2153,1,1,1,1,2,3,5,3,3,4,3,5,3,5,0,27.0,satisfied +22669,101949,Male,Loyal Customer,50,Business travel,Business,628,3,3,3,3,4,5,4,5,5,4,5,4,5,3,0,0.0,satisfied +22670,128108,Male,Loyal Customer,12,Business travel,Business,1587,3,3,3,3,3,4,3,3,3,4,4,3,4,3,7,18.0,satisfied +22671,55207,Male,Loyal Customer,36,Business travel,Eco Plus,903,4,1,1,1,4,3,4,4,4,4,4,2,4,4,0,18.0,neutral or dissatisfied +22672,66110,Male,Loyal Customer,20,Business travel,Business,1856,3,3,3,3,4,4,4,4,4,4,5,4,4,4,0,0.0,satisfied +22673,6836,Male,Loyal Customer,18,Personal Travel,Eco,235,3,5,3,5,2,3,2,2,5,4,4,4,5,2,40,28.0,neutral or dissatisfied +22674,121059,Female,Loyal Customer,46,Personal Travel,Eco,992,3,4,3,2,5,5,5,5,5,3,1,3,5,5,0,0.0,neutral or dissatisfied +22675,56983,Male,Loyal Customer,33,Personal Travel,Eco,2565,2,5,2,2,2,2,2,2,2,3,4,2,1,2,0,2.0,neutral or dissatisfied +22676,32847,Male,Loyal Customer,49,Personal Travel,Eco,101,4,1,4,4,2,4,2,2,2,3,4,4,3,2,0,2.0,neutral or dissatisfied +22677,33872,Male,disloyal Customer,30,Business travel,Eco,994,4,4,4,1,5,4,4,5,1,5,3,4,3,5,0,0.0,satisfied +22678,17867,Male,Loyal Customer,58,Business travel,Eco,425,2,1,3,1,2,2,2,2,4,5,1,4,5,2,0,0.0,satisfied +22679,12610,Female,Loyal Customer,37,Business travel,Eco Plus,542,1,2,2,2,1,1,1,1,4,4,4,1,3,1,0,12.0,neutral or dissatisfied +22680,109748,Female,Loyal Customer,40,Personal Travel,Eco,534,2,4,2,1,4,2,1,4,5,5,5,4,4,4,0,0.0,neutral or dissatisfied +22681,122394,Male,Loyal Customer,50,Personal Travel,Eco,529,2,4,2,2,2,2,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +22682,40602,Male,Loyal Customer,49,Personal Travel,Eco,391,3,4,5,4,3,5,3,3,5,3,5,4,4,3,0,0.0,neutral or dissatisfied +22683,84284,Female,Loyal Customer,66,Personal Travel,Eco,334,3,4,3,3,3,4,5,5,5,3,5,5,5,3,3,3.0,neutral or dissatisfied +22684,96769,Female,Loyal Customer,52,Business travel,Business,3249,3,3,3,3,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +22685,16647,Male,Loyal Customer,46,Business travel,Business,3771,4,4,1,4,4,1,3,4,4,4,4,5,4,3,9,4.0,satisfied +22686,129598,Female,Loyal Customer,35,Business travel,Business,2307,5,5,5,5,5,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +22687,50948,Male,Loyal Customer,55,Personal Travel,Eco,109,3,4,3,2,2,3,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +22688,71844,Female,Loyal Customer,26,Business travel,Eco,1846,3,3,3,3,3,3,3,3,2,5,4,3,3,3,0,16.0,neutral or dissatisfied +22689,11153,Female,Loyal Customer,32,Personal Travel,Eco,429,1,1,1,2,5,1,5,5,2,5,1,1,1,5,0,0.0,neutral or dissatisfied +22690,112593,Male,Loyal Customer,40,Business travel,Business,3786,3,2,2,2,2,2,2,3,3,3,3,2,3,3,16,16.0,neutral or dissatisfied +22691,119317,Male,Loyal Customer,13,Personal Travel,Eco,214,2,0,2,3,4,2,2,4,4,3,5,4,5,4,8,10.0,neutral or dissatisfied +22692,12686,Male,Loyal Customer,42,Business travel,Business,2598,2,2,2,2,3,1,1,5,5,5,5,4,5,4,4,0.0,satisfied +22693,33244,Female,disloyal Customer,18,Business travel,Eco,102,3,0,3,2,4,3,3,4,1,3,3,1,5,4,0,0.0,neutral or dissatisfied +22694,14785,Male,Loyal Customer,55,Business travel,Business,622,2,2,2,2,5,5,5,3,3,3,3,5,3,3,0,6.0,satisfied +22695,63850,Male,disloyal Customer,48,Business travel,Business,1172,3,3,3,4,5,3,1,5,4,3,4,5,4,5,72,55.0,neutral or dissatisfied +22696,123947,Female,disloyal Customer,10,Business travel,Business,646,0,0,0,4,1,0,1,1,3,3,5,3,5,1,4,2.0,satisfied +22697,19654,Male,disloyal Customer,20,Business travel,Eco,363,3,0,3,4,3,3,4,3,4,3,1,4,4,3,0,0.0,neutral or dissatisfied +22698,105286,Female,disloyal Customer,23,Business travel,Eco,967,2,2,2,1,3,2,3,3,5,2,5,3,5,3,47,50.0,neutral or dissatisfied +22699,111758,Male,disloyal Customer,31,Business travel,Eco,1441,1,1,1,3,3,1,3,3,1,4,4,1,3,3,18,6.0,neutral or dissatisfied +22700,50824,Male,Loyal Customer,41,Personal Travel,Eco,109,4,5,0,3,5,0,5,5,3,3,5,5,5,5,0,0.0,neutral or dissatisfied +22701,73075,Female,Loyal Customer,25,Business travel,Business,1085,1,1,1,1,4,4,4,4,5,3,5,3,4,4,9,0.0,satisfied +22702,128480,Female,Loyal Customer,7,Personal Travel,Eco,338,1,5,1,1,4,1,4,4,5,4,4,3,5,4,0,0.0,neutral or dissatisfied +22703,36009,Male,Loyal Customer,32,Business travel,Business,1817,2,2,2,2,4,4,4,4,4,5,5,4,1,4,0,0.0,satisfied +22704,60949,Female,Loyal Customer,50,Business travel,Business,1899,1,1,1,1,2,4,5,4,4,4,4,3,4,3,2,0.0,satisfied +22705,43228,Female,Loyal Customer,25,Personal Travel,Eco Plus,423,1,0,1,1,5,1,5,5,4,2,4,3,4,5,33,35.0,neutral or dissatisfied +22706,57042,Male,Loyal Customer,67,Personal Travel,Business,2133,3,5,3,4,3,5,3,4,4,3,1,4,4,3,23,26.0,neutral or dissatisfied +22707,42454,Female,Loyal Customer,36,Personal Travel,Eco,866,2,5,2,1,2,2,2,2,5,4,5,3,4,2,0,0.0,neutral or dissatisfied +22708,22248,Male,disloyal Customer,20,Business travel,Eco,83,3,4,2,1,4,2,4,4,1,3,1,2,5,4,0,0.0,neutral or dissatisfied +22709,6203,Female,Loyal Customer,66,Personal Travel,Eco Plus,409,1,4,1,4,4,4,5,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +22710,4357,Male,Loyal Customer,39,Business travel,Business,2142,5,5,5,5,4,4,5,4,4,4,4,4,4,3,0,10.0,satisfied +22711,14710,Male,Loyal Customer,61,Personal Travel,Eco,419,4,3,4,2,4,4,2,4,3,5,2,4,3,4,0,0.0,neutral or dissatisfied +22712,110475,Female,Loyal Customer,64,Personal Travel,Eco,883,4,3,5,3,4,2,5,4,4,5,4,1,4,4,12,9.0,neutral or dissatisfied +22713,29398,Male,Loyal Customer,37,Business travel,Eco,957,1,4,4,4,1,1,1,3,2,3,3,1,2,1,0,53.0,neutral or dissatisfied +22714,109649,Female,disloyal Customer,40,Business travel,Business,808,4,3,3,3,2,3,5,2,4,3,3,1,3,2,26,30.0,neutral or dissatisfied +22715,48951,Male,Loyal Customer,31,Business travel,Eco,373,0,0,0,5,1,0,1,1,1,4,1,2,4,1,0,0.0,satisfied +22716,83895,Male,Loyal Customer,31,Business travel,Business,1450,1,1,1,1,5,5,5,5,4,2,4,5,4,5,3,5.0,satisfied +22717,66404,Female,Loyal Customer,55,Business travel,Eco,1562,2,4,3,4,5,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +22718,89807,Male,Loyal Customer,43,Business travel,Business,2885,1,1,1,1,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +22719,85325,Female,Loyal Customer,68,Personal Travel,Eco,813,2,4,2,3,3,3,3,2,2,2,2,1,2,4,1,0.0,neutral or dissatisfied +22720,98557,Female,Loyal Customer,44,Business travel,Business,3387,3,5,5,5,2,4,4,3,3,3,3,1,3,1,23,11.0,neutral or dissatisfied +22721,73344,Female,Loyal Customer,47,Business travel,Business,1182,2,3,3,3,2,3,3,2,2,2,2,4,2,2,11,0.0,neutral or dissatisfied +22722,81368,Male,Loyal Customer,46,Business travel,Business,1671,2,2,2,2,4,5,4,5,5,5,5,3,5,3,0,18.0,satisfied +22723,118391,Female,Loyal Customer,48,Business travel,Business,3040,5,5,5,5,3,4,4,3,3,3,3,4,3,5,17,9.0,satisfied +22724,87496,Male,disloyal Customer,24,Business travel,Eco,321,4,0,3,3,2,3,2,2,4,5,5,5,4,2,0,0.0,satisfied +22725,90384,Female,Loyal Customer,42,Business travel,Business,271,0,0,0,2,3,5,5,3,3,3,3,3,3,3,0,0.0,satisfied +22726,47684,Male,Loyal Customer,21,Personal Travel,Eco,715,3,4,4,4,1,4,2,1,5,5,2,4,1,1,0,0.0,neutral or dissatisfied +22727,103834,Female,Loyal Customer,22,Business travel,Eco,1048,3,2,2,2,3,2,1,3,4,3,4,1,4,3,18,11.0,neutral or dissatisfied +22728,38492,Male,Loyal Customer,48,Business travel,Eco,2475,2,3,3,3,1,2,1,1,2,1,3,1,5,1,8,6.0,satisfied +22729,26078,Male,disloyal Customer,21,Business travel,Eco,591,2,3,2,4,1,2,1,1,4,1,2,3,2,1,0,5.0,neutral or dissatisfied +22730,34015,Female,Loyal Customer,31,Personal Travel,Eco,1598,1,1,1,3,1,1,1,1,3,4,1,4,2,1,19,3.0,neutral or dissatisfied +22731,11994,Female,Loyal Customer,39,Personal Travel,Eco,643,3,5,3,2,3,3,3,3,5,3,5,4,5,3,6,27.0,neutral or dissatisfied +22732,123419,Male,Loyal Customer,15,Personal Travel,Eco,1337,3,4,3,4,1,3,1,1,5,4,5,3,4,1,0,0.0,neutral or dissatisfied +22733,22325,Male,disloyal Customer,33,Business travel,Eco,143,2,5,2,4,3,2,1,3,4,5,4,2,3,3,0,0.0,neutral or dissatisfied +22734,100450,Male,Loyal Customer,37,Business travel,Eco Plus,1180,1,2,2,2,1,1,1,1,4,5,2,4,2,1,11,4.0,neutral or dissatisfied +22735,117788,Female,Loyal Customer,51,Business travel,Business,3832,0,0,0,3,5,5,5,5,5,5,1,5,5,4,17,9.0,satisfied +22736,113738,Female,Loyal Customer,65,Personal Travel,Eco,236,3,4,0,3,2,1,5,3,3,0,3,2,3,4,0,1.0,neutral or dissatisfied +22737,39324,Female,Loyal Customer,35,Business travel,Eco Plus,67,4,2,2,2,4,4,4,4,1,2,2,2,2,4,4,10.0,satisfied +22738,119949,Male,Loyal Customer,56,Business travel,Business,2934,4,4,4,4,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +22739,110172,Female,Loyal Customer,42,Personal Travel,Eco,979,1,4,1,2,5,5,4,1,1,1,1,4,1,4,46,39.0,neutral or dissatisfied +22740,22766,Female,Loyal Customer,41,Business travel,Business,3218,1,1,1,1,5,2,3,5,5,5,5,4,5,2,0,0.0,satisfied +22741,27104,Male,Loyal Customer,49,Personal Travel,Eco,1721,4,4,4,3,3,4,3,3,3,5,3,5,5,3,0,0.0,neutral or dissatisfied +22742,71401,Female,Loyal Customer,55,Business travel,Business,3731,0,0,0,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +22743,23362,Female,Loyal Customer,32,Business travel,Eco,1014,4,5,5,5,4,4,4,4,5,2,3,2,4,4,0,0.0,satisfied +22744,30146,Male,Loyal Customer,15,Personal Travel,Eco,123,4,5,4,3,1,4,1,1,5,5,4,1,4,1,0,0.0,neutral or dissatisfied +22745,83923,Male,disloyal Customer,28,Business travel,Business,321,4,4,4,3,5,4,5,5,3,5,4,5,5,5,12,0.0,neutral or dissatisfied +22746,79424,Female,Loyal Customer,57,Personal Travel,Eco,502,4,5,4,3,2,4,5,4,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +22747,91282,Female,Loyal Customer,29,Business travel,Eco Plus,240,2,4,4,4,2,3,2,2,3,3,3,1,4,2,61,55.0,neutral or dissatisfied +22748,88684,Male,Loyal Customer,63,Personal Travel,Eco,406,4,5,4,3,3,4,3,3,4,4,4,4,4,3,0,0.0,neutral or dissatisfied +22749,62879,Male,Loyal Customer,42,Personal Travel,Eco,2218,4,2,4,3,2,4,2,2,4,5,3,4,3,2,19,20.0,neutral or dissatisfied +22750,95239,Female,Loyal Customer,48,Personal Travel,Eco,277,3,1,3,2,3,2,2,4,4,3,4,1,4,4,11,10.0,neutral or dissatisfied +22751,115742,Male,Loyal Customer,44,Business travel,Business,1736,1,1,4,1,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +22752,30190,Female,Loyal Customer,49,Business travel,Eco Plus,725,5,3,3,3,4,3,2,5,5,5,5,5,5,4,0,0.0,satisfied +22753,129256,Male,Loyal Customer,68,Personal Travel,Eco,1464,2,3,2,4,1,2,3,1,3,5,3,2,3,1,0,0.0,neutral or dissatisfied +22754,83090,Male,disloyal Customer,34,Business travel,Eco,983,2,2,2,4,3,2,3,3,3,1,4,3,3,3,0,0.0,neutral or dissatisfied +22755,15020,Female,Loyal Customer,16,Personal Travel,Eco,557,1,5,1,1,2,1,2,2,4,2,2,3,5,2,6,9.0,neutral or dissatisfied +22756,32346,Female,Loyal Customer,42,Business travel,Eco,102,2,1,5,1,5,4,3,2,2,2,2,2,2,3,3,2.0,neutral or dissatisfied +22757,76905,Female,Loyal Customer,15,Personal Travel,Eco,630,1,5,1,1,2,1,2,2,4,5,4,5,5,2,0,0.0,neutral or dissatisfied +22758,81428,Male,Loyal Customer,32,Personal Travel,Eco,393,2,5,3,1,3,3,3,3,4,4,5,3,5,3,0,0.0,neutral or dissatisfied +22759,116559,Female,Loyal Customer,42,Personal Travel,Eco,417,3,4,3,4,4,3,3,4,4,3,4,3,4,4,17,17.0,neutral or dissatisfied +22760,81212,Male,Loyal Customer,45,Business travel,Business,1426,2,2,5,2,5,5,5,3,3,2,3,4,3,4,0,0.0,satisfied +22761,65086,Female,Loyal Customer,57,Personal Travel,Eco,551,2,2,2,4,3,4,4,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +22762,43715,Female,Loyal Customer,16,Personal Travel,Eco,257,1,2,0,2,2,0,2,2,2,5,3,4,2,2,0,0.0,neutral or dissatisfied +22763,32653,Female,disloyal Customer,26,Business travel,Eco,216,3,2,3,3,3,3,3,3,1,3,3,4,3,3,0,0.0,neutral or dissatisfied +22764,25157,Female,Loyal Customer,13,Business travel,Eco,2106,5,1,1,1,5,5,5,5,3,3,3,4,3,5,9,6.0,satisfied +22765,68589,Female,Loyal Customer,7,Personal Travel,Eco,1616,3,5,3,1,3,1,1,4,3,3,4,1,3,1,279,261.0,neutral or dissatisfied +22766,52948,Male,Loyal Customer,53,Business travel,Eco,1048,5,1,1,1,4,5,4,4,2,1,1,5,1,4,9,0.0,satisfied +22767,112860,Male,Loyal Customer,23,Business travel,Business,1720,1,1,1,1,5,4,5,5,5,3,4,5,5,5,0,0.0,satisfied +22768,28935,Female,Loyal Customer,50,Business travel,Business,2972,1,5,2,5,3,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +22769,106490,Male,Loyal Customer,30,Business travel,Business,2894,1,4,4,4,1,1,1,1,3,5,3,3,4,1,0,0.0,neutral or dissatisfied +22770,2319,Female,Loyal Customer,27,Personal Travel,Eco,690,4,5,4,4,2,4,5,2,4,2,4,5,5,2,0,0.0,satisfied +22771,82838,Male,Loyal Customer,23,Business travel,Business,2456,2,2,2,2,5,5,5,5,5,4,4,3,4,5,0,0.0,satisfied +22772,20039,Female,Loyal Customer,33,Business travel,Business,1948,3,3,1,3,4,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +22773,47043,Male,Loyal Customer,38,Business travel,Eco,602,2,1,1,1,2,2,2,2,1,1,2,2,3,2,23,45.0,neutral or dissatisfied +22774,64453,Male,Loyal Customer,43,Personal Travel,Eco,989,1,4,0,1,4,0,5,4,5,4,4,5,4,4,0,0.0,neutral or dissatisfied +22775,60346,Female,Loyal Customer,49,Personal Travel,Eco,1024,4,4,4,4,3,5,4,5,5,4,5,3,5,5,7,0.0,neutral or dissatisfied +22776,37085,Female,Loyal Customer,42,Business travel,Business,1859,2,2,2,2,5,4,5,3,3,4,3,5,3,5,0,3.0,satisfied +22777,81973,Male,Loyal Customer,59,Business travel,Business,1517,5,5,5,5,4,5,4,3,3,3,3,4,3,3,0,0.0,satisfied +22778,122314,Female,Loyal Customer,30,Business travel,Business,541,4,4,4,4,5,5,5,5,5,2,5,3,5,5,52,60.0,satisfied +22779,35844,Female,disloyal Customer,22,Business travel,Business,1023,0,0,0,2,4,0,4,4,2,5,5,4,5,4,112,97.0,satisfied +22780,17438,Male,Loyal Customer,35,Personal Travel,Eco,376,2,5,2,3,4,2,2,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +22781,29742,Female,Loyal Customer,59,Business travel,Business,2208,3,3,3,3,2,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +22782,544,Male,Loyal Customer,30,Business travel,Business,3904,5,5,5,5,3,3,3,3,3,4,5,5,4,3,0,0.0,satisfied +22783,51864,Male,Loyal Customer,48,Business travel,Eco,522,4,4,4,4,4,4,4,4,5,1,4,2,3,4,0,0.0,satisfied +22784,12120,Female,Loyal Customer,66,Personal Travel,Eco,1034,1,5,1,2,3,4,5,1,1,1,1,5,1,3,0,13.0,neutral or dissatisfied +22785,97694,Female,Loyal Customer,21,Business travel,Business,456,5,5,2,5,5,5,5,5,5,5,4,5,4,5,0,0.0,satisfied +22786,129557,Female,Loyal Customer,29,Personal Travel,Eco,2342,1,4,2,1,4,2,4,4,2,2,4,2,2,4,13,9.0,neutral or dissatisfied +22787,120002,Female,Loyal Customer,55,Business travel,Business,328,5,5,5,5,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +22788,59031,Female,Loyal Customer,23,Business travel,Business,1846,3,5,1,1,3,2,3,3,2,1,3,4,4,3,9,0.0,neutral or dissatisfied +22789,87570,Female,Loyal Customer,33,Business travel,Business,432,3,3,3,3,5,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +22790,107638,Female,disloyal Customer,43,Business travel,Business,405,3,3,3,3,5,3,3,5,3,4,4,3,4,5,3,1.0,neutral or dissatisfied +22791,73736,Female,Loyal Customer,63,Personal Travel,Eco,192,2,5,0,3,3,5,4,1,1,0,1,3,1,4,0,0.0,neutral or dissatisfied +22792,99558,Female,Loyal Customer,58,Business travel,Business,930,5,5,5,5,3,5,5,4,4,4,4,5,4,4,6,11.0,satisfied +22793,111409,Male,disloyal Customer,15,Business travel,Business,1111,0,0,0,5,5,0,4,5,4,5,5,4,4,5,0,2.0,satisfied +22794,116625,Female,Loyal Customer,73,Business travel,Eco Plus,390,3,5,5,5,5,3,4,3,3,3,3,4,3,2,9,2.0,neutral or dissatisfied +22795,31164,Female,Loyal Customer,71,Business travel,Eco Plus,801,4,1,1,1,2,5,3,4,4,4,4,4,4,2,0,0.0,satisfied +22796,77148,Male,disloyal Customer,30,Business travel,Business,1865,3,3,3,3,3,3,3,3,4,2,4,3,4,3,0,0.0,neutral or dissatisfied +22797,129113,Male,Loyal Customer,48,Business travel,Business,2342,4,4,4,4,5,5,5,4,3,4,5,5,5,5,0,13.0,satisfied +22798,90677,Male,Loyal Customer,50,Business travel,Business,3465,1,1,1,1,3,4,4,5,5,5,5,5,5,3,31,24.0,satisfied +22799,99246,Male,Loyal Customer,48,Personal Travel,Eco,541,4,3,4,4,3,4,3,3,4,1,2,3,1,3,3,0.0,satisfied +22800,59257,Male,Loyal Customer,66,Personal Travel,Eco,3904,2,4,2,2,2,1,1,3,3,5,4,1,3,1,1,0.0,neutral or dissatisfied +22801,123028,Male,disloyal Customer,22,Business travel,Eco,468,4,4,4,4,1,4,1,1,5,3,4,5,5,1,0,2.0,satisfied +22802,49306,Male,Loyal Customer,37,Business travel,Eco,421,4,1,1,1,4,4,4,4,1,1,3,4,5,4,0,0.0,satisfied +22803,99388,Female,Loyal Customer,60,Business travel,Business,2009,0,0,0,3,4,5,5,4,4,4,4,3,4,4,1,0.0,satisfied +22804,94684,Male,disloyal Customer,59,Business travel,Eco,239,2,1,2,3,3,2,3,3,3,3,2,3,3,3,0,0.0,neutral or dissatisfied +22805,30904,Male,Loyal Customer,54,Business travel,Eco,896,5,3,3,3,5,5,5,5,1,5,1,3,1,5,16,4.0,satisfied +22806,62985,Female,Loyal Customer,30,Business travel,Business,862,3,4,4,4,3,3,3,3,4,3,3,3,4,3,2,0.0,neutral or dissatisfied +22807,24055,Male,Loyal Customer,63,Personal Travel,Eco,427,4,1,4,3,1,4,1,1,4,5,3,2,4,1,0,0.0,satisfied +22808,88672,Female,Loyal Customer,44,Personal Travel,Eco,444,3,5,3,5,4,5,4,2,2,3,2,3,2,4,10,0.0,neutral or dissatisfied +22809,63482,Female,Loyal Customer,66,Personal Travel,Eco Plus,447,2,5,2,3,3,4,4,1,1,2,1,4,1,3,0,0.0,neutral or dissatisfied +22810,36476,Male,Loyal Customer,65,Business travel,Business,3509,3,4,4,4,1,3,2,3,3,3,3,4,3,1,0,0.0,neutral or dissatisfied +22811,105529,Female,disloyal Customer,22,Business travel,Eco,611,2,0,1,5,3,1,3,3,5,5,5,4,4,3,0,0.0,neutral or dissatisfied +22812,1513,Female,disloyal Customer,38,Business travel,Business,987,3,3,3,5,1,3,1,1,5,4,5,4,4,1,2,16.0,neutral or dissatisfied +22813,2190,Male,Loyal Customer,30,Personal Travel,Eco,624,3,5,3,3,5,3,4,5,3,4,1,5,3,5,0,0.0,neutral or dissatisfied +22814,41098,Male,Loyal Customer,41,Business travel,Business,140,4,4,4,4,2,3,5,5,5,5,3,3,5,5,15,18.0,satisfied +22815,52665,Male,Loyal Customer,15,Personal Travel,Eco,160,2,5,2,3,1,2,1,1,3,5,4,5,4,1,3,0.0,neutral or dissatisfied +22816,101687,Female,disloyal Customer,37,Business travel,Business,1500,4,4,4,3,3,4,3,3,4,3,4,3,5,3,0,0.0,satisfied +22817,58702,Male,Loyal Customer,40,Business travel,Business,4243,2,5,5,5,2,2,2,4,3,1,3,2,1,2,0,19.0,neutral or dissatisfied +22818,120983,Male,Loyal Customer,54,Business travel,Eco,920,2,4,4,4,2,2,2,2,1,1,4,2,3,2,0,74.0,neutral or dissatisfied +22819,35940,Male,Loyal Customer,67,Personal Travel,Eco Plus,2381,4,4,4,4,3,4,3,3,3,5,4,3,5,3,88,79.0,neutral or dissatisfied +22820,52341,Male,disloyal Customer,23,Business travel,Eco,261,0,5,0,3,1,0,1,1,4,4,1,5,5,1,0,1.0,satisfied +22821,13683,Male,Loyal Customer,48,Personal Travel,Eco,954,3,3,3,4,3,5,5,5,4,2,3,5,1,5,150,136.0,neutral or dissatisfied +22822,1206,Male,Loyal Customer,27,Personal Travel,Eco,354,3,5,3,3,1,3,1,1,3,2,4,3,4,1,16,41.0,neutral or dissatisfied +22823,125904,Female,Loyal Customer,59,Personal Travel,Eco,951,3,4,3,4,4,3,4,2,2,3,2,4,2,1,0,5.0,neutral or dissatisfied +22824,61554,Female,Loyal Customer,30,Business travel,Business,2253,1,1,1,1,4,4,4,4,3,3,5,4,5,4,0,0.0,satisfied +22825,112804,Male,disloyal Customer,27,Business travel,Business,1211,3,3,3,3,2,3,2,2,4,1,2,2,2,2,1,11.0,neutral or dissatisfied +22826,41283,Male,Loyal Customer,41,Personal Travel,Eco,788,2,4,2,5,2,2,2,2,5,3,4,4,4,2,7,2.0,neutral or dissatisfied +22827,43630,Male,Loyal Customer,66,Personal Travel,Eco,252,3,3,3,3,2,3,2,2,4,5,3,4,4,2,0,0.0,neutral or dissatisfied +22828,121901,Male,Loyal Customer,7,Personal Travel,Eco,366,1,5,5,3,5,5,5,5,4,3,4,3,4,5,0,3.0,neutral or dissatisfied +22829,13985,Female,Loyal Customer,47,Business travel,Business,372,4,4,3,4,4,3,2,3,3,4,3,5,3,5,0,0.0,satisfied +22830,93722,Female,Loyal Customer,40,Business travel,Business,2912,1,3,3,3,2,4,3,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +22831,74558,Male,Loyal Customer,44,Business travel,Business,1205,4,3,4,4,5,5,5,3,3,4,5,5,3,5,257,252.0,satisfied +22832,96739,Female,Loyal Customer,39,Business travel,Business,2549,5,5,5,5,5,4,4,5,5,5,5,5,5,3,29,19.0,satisfied +22833,64623,Female,Loyal Customer,33,Business travel,Business,2323,4,4,5,4,1,4,3,2,2,2,4,4,2,2,0,0.0,neutral or dissatisfied +22834,53932,Female,Loyal Customer,68,Personal Travel,Eco Plus,191,3,4,0,5,3,5,4,1,1,0,1,4,1,5,0,0.0,neutral or dissatisfied +22835,33404,Male,Loyal Customer,26,Business travel,Eco,2349,4,3,3,3,4,4,3,4,4,3,5,4,5,4,0,0.0,satisfied +22836,28674,Male,Loyal Customer,22,Business travel,Business,2797,3,3,3,3,4,4,4,4,3,5,4,4,4,4,0,0.0,satisfied +22837,104687,Female,Loyal Customer,61,Business travel,Eco,159,2,4,4,4,5,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +22838,45240,Female,Loyal Customer,45,Personal Travel,Eco,1013,1,5,1,5,4,4,3,1,1,1,1,4,1,1,10,10.0,neutral or dissatisfied +22839,104896,Male,Loyal Customer,40,Business travel,Business,1565,2,4,4,4,4,4,4,2,2,2,2,3,2,2,14,35.0,neutral or dissatisfied +22840,49457,Female,Loyal Customer,60,Business travel,Eco,109,2,1,5,1,1,3,4,2,2,2,2,1,2,2,12,17.0,neutral or dissatisfied +22841,13211,Male,disloyal Customer,28,Business travel,Business,468,2,2,2,3,4,2,4,4,4,3,3,4,2,4,0,10.0,neutral or dissatisfied +22842,96808,Female,disloyal Customer,32,Business travel,Business,781,2,2,2,2,1,2,1,1,4,5,4,3,4,1,26,28.0,neutral or dissatisfied +22843,5647,Male,Loyal Customer,49,Personal Travel,Business,299,3,3,3,3,1,3,3,3,3,3,3,2,3,4,0,7.0,neutral or dissatisfied +22844,123321,Female,Loyal Customer,25,Business travel,Eco Plus,650,1,3,4,4,1,1,2,1,1,3,4,4,3,1,1,7.0,neutral or dissatisfied +22845,3604,Male,Loyal Customer,23,Personal Travel,Eco,999,1,3,1,5,4,1,4,4,1,1,5,3,1,4,0,13.0,neutral or dissatisfied +22846,70237,Female,Loyal Customer,39,Business travel,Business,1592,3,3,3,3,3,4,4,4,4,4,4,5,4,5,14,19.0,satisfied +22847,54484,Male,Loyal Customer,10,Business travel,Business,925,3,1,3,3,3,4,3,3,5,3,5,5,1,3,0,0.0,satisfied +22848,32889,Female,Loyal Customer,47,Personal Travel,Eco,163,4,5,4,1,4,4,4,1,1,4,1,4,1,5,0,0.0,satisfied +22849,77250,Female,Loyal Customer,45,Business travel,Business,1190,5,5,5,5,4,3,3,5,5,5,5,5,5,5,1,0.0,satisfied +22850,110141,Male,Loyal Customer,35,Business travel,Business,2723,3,4,4,4,2,4,4,3,3,3,3,2,3,1,2,0.0,neutral or dissatisfied +22851,3212,Male,Loyal Customer,64,Business travel,Eco Plus,693,3,1,1,1,3,3,3,3,3,1,4,3,4,3,0,0.0,neutral or dissatisfied +22852,129532,Female,Loyal Customer,56,Business travel,Business,2583,1,1,1,1,4,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +22853,60800,Female,Loyal Customer,43,Business travel,Business,1888,3,2,2,2,2,3,3,3,3,3,3,2,3,3,2,0.0,neutral or dissatisfied +22854,93742,Female,Loyal Customer,41,Business travel,Business,3600,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +22855,62045,Male,disloyal Customer,29,Business travel,Eco,1121,2,2,2,4,1,2,1,1,3,1,2,4,4,1,6,0.0,neutral or dissatisfied +22856,109371,Female,Loyal Customer,45,Business travel,Eco,1237,4,5,3,5,3,2,3,4,4,4,4,1,4,3,31,29.0,neutral or dissatisfied +22857,56739,Female,Loyal Customer,43,Personal Travel,Eco,1023,3,3,3,3,4,3,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +22858,113864,Male,Loyal Customer,44,Business travel,Eco,992,5,2,5,5,5,5,5,5,5,5,5,3,3,5,9,0.0,satisfied +22859,91893,Female,Loyal Customer,48,Business travel,Business,2475,3,4,3,3,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +22860,93652,Male,Loyal Customer,21,Personal Travel,Eco,547,2,4,1,4,5,1,5,5,3,1,2,5,2,5,15,59.0,neutral or dissatisfied +22861,81450,Female,Loyal Customer,37,Business travel,Business,1702,4,4,4,4,2,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +22862,57254,Female,Loyal Customer,60,Business travel,Eco,804,2,2,2,2,2,3,4,2,2,2,2,4,2,3,0,0.0,neutral or dissatisfied +22863,14554,Male,Loyal Customer,70,Personal Travel,Eco,288,2,4,2,4,1,2,1,1,5,3,5,3,4,1,0,0.0,neutral or dissatisfied +22864,69204,Male,disloyal Customer,35,Business travel,Business,733,1,1,1,3,2,1,2,2,3,4,4,4,5,2,0,17.0,neutral or dissatisfied +22865,90916,Male,Loyal Customer,37,Business travel,Business,194,5,4,5,5,4,2,1,5,5,5,3,5,5,1,0,0.0,satisfied +22866,119888,Male,Loyal Customer,30,Personal Travel,Eco,912,3,4,4,2,4,4,3,4,5,3,5,4,5,4,0,7.0,neutral or dissatisfied +22867,46906,Female,Loyal Customer,16,Business travel,Business,2615,5,5,3,5,1,2,1,1,5,5,2,4,2,1,0,0.0,satisfied +22868,95666,Female,disloyal Customer,23,Business travel,Eco,1131,2,2,2,2,5,2,5,5,5,2,5,4,4,5,57,45.0,neutral or dissatisfied +22869,89052,Female,disloyal Customer,43,Business travel,Business,807,4,3,3,1,4,4,4,4,4,5,5,5,5,4,0,4.0,satisfied +22870,85632,Female,Loyal Customer,18,Personal Travel,Eco,153,4,4,4,3,4,4,1,4,4,2,5,5,1,4,0,0.0,neutral or dissatisfied +22871,44115,Female,Loyal Customer,68,Personal Travel,Eco Plus,408,2,4,2,3,3,5,5,2,2,2,2,5,2,5,13,6.0,neutral or dissatisfied +22872,59134,Female,Loyal Customer,61,Personal Travel,Eco,1846,1,5,1,3,5,5,4,3,3,1,1,4,3,3,0,0.0,neutral or dissatisfied +22873,16182,Female,Loyal Customer,44,Business travel,Eco,277,2,2,4,2,4,2,2,2,2,2,2,2,2,1,49,54.0,neutral or dissatisfied +22874,62910,Female,Loyal Customer,57,Business travel,Business,846,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +22875,12473,Male,Loyal Customer,28,Personal Travel,Eco,305,2,4,2,1,2,2,2,2,2,4,3,2,3,2,17,5.0,neutral or dissatisfied +22876,65647,Female,disloyal Customer,29,Business travel,Business,861,4,5,5,2,5,5,5,5,3,3,4,5,5,5,6,5.0,satisfied +22877,69134,Male,Loyal Customer,50,Business travel,Business,2248,4,4,4,4,2,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +22878,107892,Male,disloyal Customer,56,Business travel,Business,461,2,2,2,3,4,2,4,4,3,4,4,1,3,4,31,20.0,neutral or dissatisfied +22879,128291,Male,Loyal Customer,62,Business travel,Business,2287,0,0,0,2,2,5,4,2,2,2,2,3,2,4,0,2.0,satisfied +22880,79137,Female,Loyal Customer,52,Business travel,Business,2692,1,1,1,1,4,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +22881,8540,Male,Loyal Customer,60,Business travel,Business,308,1,1,1,1,2,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +22882,15079,Female,Loyal Customer,51,Business travel,Eco,322,4,5,5,5,1,5,5,4,4,4,4,4,4,3,0,1.0,satisfied +22883,105645,Female,Loyal Customer,42,Business travel,Business,3282,4,4,5,4,3,4,4,2,2,3,2,4,2,3,0,0.0,satisfied +22884,78278,Male,disloyal Customer,24,Business travel,Business,1598,4,5,4,3,1,4,1,1,5,2,4,4,5,1,2,0.0,satisfied +22885,126139,Male,Loyal Customer,27,Business travel,Business,3014,2,2,2,2,2,3,2,2,4,2,4,1,3,2,0,0.0,neutral or dissatisfied +22886,91932,Female,Loyal Customer,38,Business travel,Business,2475,4,2,5,2,2,1,3,4,4,4,4,4,4,1,13,27.0,neutral or dissatisfied +22887,5723,Female,disloyal Customer,22,Business travel,Eco,299,4,3,4,3,5,4,5,5,3,3,4,5,4,5,6,3.0,satisfied +22888,35727,Male,Loyal Customer,63,Personal Travel,Eco Plus,2569,1,4,1,4,1,3,3,3,5,3,4,3,4,3,47,108.0,neutral or dissatisfied +22889,84477,Female,Loyal Customer,45,Business travel,Business,3125,3,3,3,3,4,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +22890,112120,Female,Loyal Customer,57,Business travel,Business,1755,3,3,3,3,4,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +22891,92406,Male,disloyal Customer,21,Business travel,Business,717,5,0,5,2,5,5,1,5,4,3,5,3,4,5,0,0.0,satisfied +22892,66003,Female,Loyal Customer,10,Personal Travel,Business,1345,4,3,4,4,1,4,1,1,3,5,2,3,4,1,39,50.0,neutral or dissatisfied +22893,109143,Female,Loyal Customer,10,Personal Travel,Business,793,3,4,3,4,4,3,4,4,5,4,4,3,5,4,2,4.0,neutral or dissatisfied +22894,116358,Female,Loyal Customer,45,Personal Travel,Eco,373,3,1,3,4,2,4,4,3,3,3,3,4,3,3,24,22.0,neutral or dissatisfied +22895,99364,Female,disloyal Customer,47,Business travel,Business,409,4,4,4,3,1,4,1,1,4,5,4,5,5,1,0,0.0,satisfied +22896,95899,Female,Loyal Customer,16,Personal Travel,Eco,580,2,3,2,3,1,2,1,1,4,3,3,3,4,1,0,1.0,neutral or dissatisfied +22897,35432,Female,Loyal Customer,45,Personal Travel,Eco,1069,1,4,1,1,5,4,5,4,4,1,4,5,4,3,0,0.0,neutral or dissatisfied +22898,122852,Female,Loyal Customer,43,Business travel,Business,2289,1,5,5,5,2,3,3,1,1,1,1,1,1,2,0,16.0,neutral or dissatisfied +22899,119166,Male,disloyal Customer,26,Business travel,Business,257,4,4,4,2,3,4,4,3,3,3,5,4,4,3,16,1.0,satisfied +22900,98779,Male,Loyal Customer,50,Business travel,Business,3376,4,4,4,4,3,5,4,3,3,3,3,3,3,5,26,17.0,satisfied +22901,15264,Male,Loyal Customer,27,Business travel,Business,2401,3,2,2,2,3,3,3,3,4,2,4,1,4,3,0,0.0,neutral or dissatisfied +22902,15591,Male,disloyal Customer,26,Business travel,Eco,292,1,4,1,3,1,1,1,1,4,2,3,4,3,1,72,55.0,neutral or dissatisfied +22903,54882,Female,Loyal Customer,13,Personal Travel,Eco,862,3,5,3,4,5,3,5,5,3,2,4,3,5,5,4,24.0,neutral or dissatisfied +22904,56751,Female,Loyal Customer,59,Business travel,Business,2484,2,2,2,2,5,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +22905,70383,Female,disloyal Customer,26,Business travel,Business,1562,1,1,1,3,1,1,1,1,4,2,4,5,5,1,52,45.0,neutral or dissatisfied +22906,35342,Female,Loyal Customer,47,Business travel,Business,2668,3,3,3,3,2,4,4,5,5,5,5,1,5,5,0,0.0,satisfied +22907,17,Female,Loyal Customer,48,Personal Travel,Eco,821,2,3,2,3,1,5,1,5,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +22908,20173,Female,Loyal Customer,13,Personal Travel,Eco,438,2,4,2,4,1,2,1,1,3,4,5,5,5,1,76,66.0,neutral or dissatisfied +22909,116838,Female,disloyal Customer,21,Business travel,Business,370,4,0,5,3,2,5,2,2,3,3,4,3,5,2,0,0.0,satisfied +22910,84228,Female,Loyal Customer,10,Personal Travel,Eco,432,2,3,1,3,5,1,5,5,1,3,3,1,4,5,13,24.0,neutral or dissatisfied +22911,94857,Male,Loyal Customer,34,Business travel,Eco,189,1,4,4,4,1,1,1,1,2,3,3,3,3,1,0,0.0,neutral or dissatisfied +22912,118665,Male,disloyal Customer,22,Business travel,Eco,646,3,1,4,3,2,4,4,2,4,3,4,1,4,2,21,20.0,neutral or dissatisfied +22913,72696,Female,Loyal Customer,45,Personal Travel,Eco,1121,2,5,2,5,4,5,4,3,3,2,3,3,3,5,7,11.0,neutral or dissatisfied +22914,109153,Male,Loyal Customer,55,Business travel,Business,612,3,3,3,3,5,5,5,4,4,4,4,5,4,5,13,9.0,satisfied +22915,34435,Female,Loyal Customer,52,Business travel,Business,2422,5,5,5,5,5,4,4,4,5,5,4,4,5,4,25,29.0,satisfied +22916,99553,Male,disloyal Customer,18,Business travel,Eco,808,2,2,2,4,4,2,4,4,3,2,3,4,3,4,93,97.0,neutral or dissatisfied +22917,36101,Female,Loyal Customer,61,Personal Travel,Eco,474,3,3,3,4,4,4,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +22918,64388,Female,Loyal Customer,59,Personal Travel,Eco,1172,3,5,3,2,5,5,5,4,4,3,2,3,4,4,0,0.0,neutral or dissatisfied +22919,74006,Female,Loyal Customer,8,Personal Travel,Eco,1972,3,3,4,3,4,4,4,4,3,5,4,3,3,4,0,7.0,neutral or dissatisfied +22920,107923,Female,Loyal Customer,42,Business travel,Business,611,4,4,4,4,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +22921,28487,Female,Loyal Customer,29,Business travel,Business,1739,1,5,5,5,1,1,1,1,2,3,2,4,2,1,6,21.0,neutral or dissatisfied +22922,53956,Male,Loyal Customer,12,Business travel,Business,1117,2,5,5,5,2,2,2,2,3,1,4,3,4,2,31,26.0,neutral or dissatisfied +22923,122479,Female,disloyal Customer,50,Business travel,Eco,408,2,0,2,3,3,2,3,3,4,2,4,3,3,3,0,16.0,neutral or dissatisfied +22924,125870,Male,Loyal Customer,47,Business travel,Business,993,3,3,3,3,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +22925,117395,Male,Loyal Customer,48,Business travel,Business,1797,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +22926,82521,Female,disloyal Customer,23,Business travel,Eco,1123,1,1,1,4,4,1,4,4,3,2,3,3,3,4,0,9.0,neutral or dissatisfied +22927,52861,Male,disloyal Customer,28,Business travel,Business,836,3,3,3,2,3,3,3,3,4,4,4,5,5,3,0,0.0,neutral or dissatisfied +22928,5672,Male,Loyal Customer,45,Business travel,Eco,234,3,5,5,5,3,3,3,3,2,2,4,4,3,3,0,1.0,neutral or dissatisfied +22929,347,Female,Loyal Customer,30,Personal Travel,Eco,821,3,5,3,5,5,3,5,5,4,5,2,4,1,5,9,8.0,neutral or dissatisfied +22930,85117,Female,Loyal Customer,59,Business travel,Business,2734,5,5,5,5,2,5,5,5,5,5,5,4,5,4,16,0.0,satisfied +22931,84016,Female,Loyal Customer,58,Personal Travel,Eco,321,2,2,2,4,1,3,3,3,3,2,3,2,3,2,0,9.0,neutral or dissatisfied +22932,88913,Female,Loyal Customer,59,Personal Travel,Eco,859,1,4,1,2,2,4,4,4,4,1,4,3,4,4,17,16.0,neutral or dissatisfied +22933,60597,Male,Loyal Customer,23,Business travel,Business,1558,2,2,2,2,4,4,4,4,3,4,4,3,5,4,1,0.0,satisfied +22934,11105,Female,Loyal Customer,50,Personal Travel,Eco,429,5,2,5,3,2,3,3,3,3,5,3,4,3,2,0,0.0,satisfied +22935,29552,Male,Loyal Customer,33,Business travel,Business,1448,5,5,4,5,3,5,3,3,4,2,1,1,3,3,0,0.0,satisfied +22936,66109,Male,Loyal Customer,23,Business travel,Business,2767,5,5,2,5,5,5,5,5,5,4,4,5,5,5,0,0.0,satisfied +22937,95739,Female,Loyal Customer,37,Business travel,Business,3886,3,2,4,2,5,3,3,3,3,3,3,3,3,1,18,23.0,neutral or dissatisfied +22938,88658,Female,Loyal Customer,8,Personal Travel,Eco,442,3,4,3,3,4,3,4,4,5,4,1,4,4,4,0,0.0,neutral or dissatisfied +22939,43399,Male,Loyal Customer,51,Personal Travel,Eco,347,5,5,5,1,1,5,2,1,3,4,5,3,4,1,0,0.0,satisfied +22940,103377,Male,Loyal Customer,66,Business travel,Business,1640,0,0,0,3,3,5,5,1,1,1,1,5,1,5,4,5.0,satisfied +22941,80530,Female,Loyal Customer,58,Business travel,Business,1678,1,1,1,1,2,3,4,5,5,5,5,4,5,3,0,0.0,satisfied +22942,25524,Male,Loyal Customer,32,Personal Travel,Eco,547,3,1,3,3,4,3,3,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +22943,67416,Female,Loyal Customer,41,Business travel,Business,2852,5,5,5,5,4,5,5,5,5,5,5,3,5,5,8,11.0,satisfied +22944,76892,Female,Loyal Customer,56,Business travel,Business,630,2,2,2,2,5,4,5,5,5,5,5,5,5,4,4,2.0,satisfied +22945,116292,Female,Loyal Customer,18,Personal Travel,Eco,480,1,3,1,3,5,1,5,5,1,2,3,3,4,5,1,0.0,neutral or dissatisfied +22946,65887,Male,Loyal Customer,52,Business travel,Business,2296,3,3,3,3,2,4,4,3,3,3,3,5,3,3,0,0.0,satisfied +22947,3944,Male,Loyal Customer,31,Business travel,Business,764,2,2,3,2,2,2,2,2,2,3,4,2,4,2,0,10.0,neutral or dissatisfied +22948,61638,Female,Loyal Customer,53,Business travel,Business,1635,3,3,3,3,5,5,5,5,5,5,5,5,5,4,95,82.0,satisfied +22949,74579,Female,Loyal Customer,42,Business travel,Eco,1235,2,1,1,1,1,4,4,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +22950,62145,Female,Loyal Customer,34,Business travel,Business,2565,3,3,3,3,5,4,5,5,5,5,5,4,5,4,0,7.0,satisfied +22951,46418,Female,Loyal Customer,50,Business travel,Business,649,3,4,4,4,5,4,4,3,3,3,3,2,3,4,0,0.0,neutral or dissatisfied +22952,32676,Female,Loyal Customer,36,Business travel,Business,101,1,4,5,5,1,3,4,4,4,4,1,2,4,4,0,3.0,neutral or dissatisfied +22953,101514,Male,disloyal Customer,23,Business travel,Eco,345,2,5,3,1,4,3,4,4,2,5,5,1,2,4,6,4.0,neutral or dissatisfied +22954,91553,Male,Loyal Customer,15,Personal Travel,Eco,680,1,1,1,3,2,1,2,2,3,3,3,1,3,2,0,18.0,neutral or dissatisfied +22955,126073,Female,Loyal Customer,48,Business travel,Business,590,4,4,4,4,3,4,4,5,5,5,5,3,5,4,53,47.0,satisfied +22956,50562,Male,Loyal Customer,56,Personal Travel,Eco,86,2,4,0,1,4,0,4,4,4,5,1,4,5,4,0,0.0,neutral or dissatisfied +22957,122630,Female,Loyal Customer,65,Personal Travel,Eco,728,3,3,3,5,1,3,2,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +22958,550,Female,Loyal Customer,40,Business travel,Business,164,0,5,0,2,4,4,4,5,5,4,4,5,5,3,38,33.0,satisfied +22959,111896,Male,Loyal Customer,37,Personal Travel,Eco,628,1,5,1,2,1,1,1,5,3,5,5,1,5,1,166,164.0,neutral or dissatisfied +22960,41694,Female,Loyal Customer,23,Personal Travel,Eco,347,4,5,4,1,3,4,4,3,4,5,5,4,5,3,0,22.0,neutral or dissatisfied +22961,43533,Male,Loyal Customer,68,Personal Travel,Eco,920,4,5,4,3,4,4,4,4,4,5,4,3,4,4,0,13.0,neutral or dissatisfied +22962,32879,Female,Loyal Customer,25,Personal Travel,Eco,101,3,4,3,3,3,3,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +22963,66586,Female,Loyal Customer,44,Business travel,Eco,761,4,5,5,5,3,3,3,4,4,4,4,2,4,3,1,0.0,neutral or dissatisfied +22964,6605,Male,Loyal Customer,41,Personal Travel,Eco,618,2,3,2,3,4,2,4,4,2,3,3,1,4,4,0,0.0,neutral or dissatisfied +22965,118854,Male,Loyal Customer,24,Personal Travel,Eco Plus,304,2,4,2,2,5,2,2,5,3,4,4,4,5,5,51,46.0,neutral or dissatisfied +22966,22151,Female,disloyal Customer,20,Business travel,Eco,565,4,5,4,3,4,4,2,4,2,3,1,5,1,4,0,0.0,neutral or dissatisfied +22967,41874,Male,Loyal Customer,23,Business travel,Eco,925,1,3,3,3,1,1,1,1,3,2,4,3,3,1,6,22.0,neutral or dissatisfied +22968,5362,Female,Loyal Customer,20,Business travel,Business,2037,1,1,1,1,4,4,4,4,3,4,4,5,4,4,0,0.0,satisfied +22969,111572,Male,disloyal Customer,21,Business travel,Eco,483,2,4,2,3,1,2,1,1,1,5,4,3,3,1,32,64.0,neutral or dissatisfied +22970,8307,Male,Loyal Customer,54,Business travel,Eco Plus,530,2,3,3,3,2,2,2,2,3,3,3,2,3,2,0,11.0,neutral or dissatisfied +22971,22230,Female,disloyal Customer,33,Business travel,Business,145,3,3,3,4,3,3,3,3,4,3,4,5,5,3,0,3.0,neutral or dissatisfied +22972,85244,Female,Loyal Customer,47,Personal Travel,Eco,696,4,4,4,4,2,1,3,2,2,4,2,4,2,3,24,36.0,satisfied +22973,34817,Female,Loyal Customer,48,Personal Travel,Eco,301,3,2,4,3,2,4,3,3,3,4,3,2,3,4,0,0.0,neutral or dissatisfied +22974,20959,Female,disloyal Customer,18,Business travel,Eco,689,4,4,4,3,2,4,2,2,1,1,3,4,4,2,117,126.0,neutral or dissatisfied +22975,20466,Male,Loyal Customer,60,Personal Travel,Eco,84,0,1,0,3,3,0,3,3,4,1,3,2,4,3,0,0.0,satisfied +22976,26969,Female,Loyal Customer,48,Business travel,Eco,867,4,1,1,1,1,4,5,4,4,4,4,1,4,4,0,0.0,satisfied +22977,109005,Male,disloyal Customer,27,Business travel,Business,994,4,4,4,2,1,4,1,1,5,2,5,3,4,1,3,0.0,satisfied +22978,106924,Male,Loyal Customer,13,Personal Travel,Eco,1259,3,4,3,4,2,3,2,2,4,4,5,3,4,2,11,19.0,neutral or dissatisfied +22979,83030,Female,Loyal Customer,43,Business travel,Business,2868,2,2,2,2,5,5,4,4,4,4,4,3,4,5,13,33.0,satisfied +22980,52259,Male,disloyal Customer,22,Business travel,Eco,370,2,2,2,3,4,2,1,4,1,2,4,2,3,4,0,0.0,neutral or dissatisfied +22981,90313,Female,Loyal Customer,57,Personal Travel,Eco Plus,757,3,4,3,2,5,5,5,5,5,3,2,4,5,4,6,0.0,neutral or dissatisfied +22982,123441,Female,disloyal Customer,25,Business travel,Business,2077,5,0,5,3,2,5,2,2,4,2,4,5,4,2,0,0.0,satisfied +22983,79431,Female,Loyal Customer,33,Business travel,Business,3725,1,1,1,1,5,5,5,4,4,4,4,5,4,4,14,12.0,satisfied +22984,111997,Male,Loyal Customer,39,Business travel,Business,2700,1,1,3,1,3,4,4,3,3,4,3,3,3,4,1,23.0,satisfied +22985,53303,Male,disloyal Customer,38,Business travel,Eco,411,3,2,3,4,4,3,1,4,2,5,4,3,4,4,119,117.0,neutral or dissatisfied +22986,66918,Female,Loyal Customer,22,Business travel,Business,2229,3,3,3,3,4,4,4,4,4,3,4,3,5,4,2,0.0,satisfied +22987,92175,Female,Loyal Customer,48,Business travel,Business,2079,3,3,3,3,4,4,4,3,4,5,5,4,4,4,291,280.0,satisfied +22988,105604,Female,disloyal Customer,22,Business travel,Eco,663,3,0,4,3,3,4,2,3,5,4,5,5,5,3,2,3.0,neutral or dissatisfied +22989,27748,Female,Loyal Customer,37,Business travel,Business,1533,2,2,2,2,3,2,4,4,4,4,4,2,4,1,0,16.0,satisfied +22990,4735,Male,disloyal Customer,47,Business travel,Business,888,2,2,2,4,5,2,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +22991,30680,Male,Loyal Customer,58,Business travel,Eco,680,4,4,2,4,4,4,4,4,2,4,5,5,1,4,0,18.0,satisfied +22992,41471,Female,disloyal Customer,52,Business travel,Eco,715,4,4,4,1,5,4,5,5,1,2,3,5,1,5,53,66.0,satisfied +22993,27121,Male,Loyal Customer,29,Business travel,Business,2701,4,4,4,4,4,4,4,4,2,3,2,4,1,4,9,53.0,satisfied +22994,72810,Male,disloyal Customer,26,Business travel,Business,1045,3,3,3,3,1,3,1,1,5,3,4,3,4,1,0,0.0,neutral or dissatisfied +22995,7988,Female,Loyal Customer,47,Business travel,Business,3689,1,1,1,1,4,5,5,3,3,4,3,5,3,5,0,1.0,satisfied +22996,78346,Male,Loyal Customer,20,Personal Travel,Eco,1547,2,4,1,3,2,1,2,2,4,3,4,4,4,2,0,1.0,neutral or dissatisfied +22997,70145,Female,Loyal Customer,20,Personal Travel,Eco,550,3,3,3,4,2,3,2,2,3,1,1,2,1,2,0,0.0,neutral or dissatisfied +22998,69030,Male,Loyal Customer,51,Business travel,Business,1389,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,6.0,satisfied +22999,41235,Male,Loyal Customer,67,Personal Travel,Eco,744,2,3,2,2,4,2,4,4,2,2,3,3,3,4,18,5.0,neutral or dissatisfied +23000,28797,Male,Loyal Customer,32,Personal Travel,Business,697,2,5,2,5,2,2,2,2,3,2,5,3,4,2,0,1.0,neutral or dissatisfied +23001,15177,Male,Loyal Customer,55,Business travel,Business,2764,3,3,3,3,2,2,3,3,3,3,3,4,3,4,11,0.0,neutral or dissatisfied +23002,111833,Male,Loyal Customer,38,Business travel,Business,1605,2,2,2,2,1,2,3,2,2,2,2,3,2,4,67,49.0,neutral or dissatisfied +23003,84079,Male,Loyal Customer,24,Business travel,Eco,932,1,3,1,3,1,1,3,1,3,2,4,4,4,1,0,18.0,neutral or dissatisfied +23004,63168,Female,Loyal Customer,52,Business travel,Business,2948,4,4,2,4,3,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +23005,112423,Male,Loyal Customer,29,Business travel,Business,909,2,1,4,1,2,2,2,2,2,4,2,1,3,2,24,19.0,neutral or dissatisfied +23006,47869,Male,disloyal Customer,26,Business travel,Eco,451,2,4,2,4,3,2,3,3,2,4,4,1,3,3,0,21.0,neutral or dissatisfied +23007,25818,Female,Loyal Customer,57,Personal Travel,Eco,1747,3,2,2,3,1,2,4,1,1,2,1,2,1,3,5,6.0,neutral or dissatisfied +23008,15978,Female,Loyal Customer,52,Business travel,Business,1570,1,1,1,1,2,4,5,3,3,3,3,3,3,5,25,17.0,satisfied +23009,40544,Female,Loyal Customer,33,Business travel,Business,391,4,4,4,4,4,2,4,5,5,5,5,2,5,1,0,0.0,satisfied +23010,49040,Female,disloyal Customer,26,Business travel,Eco,158,2,0,2,2,1,2,1,1,4,5,5,3,5,1,0,0.0,neutral or dissatisfied +23011,64429,Male,Loyal Customer,49,Business travel,Business,3985,3,3,3,3,5,4,5,4,4,5,4,4,4,4,1,0.0,satisfied +23012,9074,Male,Loyal Customer,12,Personal Travel,Eco,173,5,1,5,4,5,5,5,2,3,3,3,5,3,5,326,330.0,satisfied +23013,35598,Female,disloyal Customer,15,Business travel,Eco Plus,1076,2,3,2,3,1,2,1,1,2,2,3,4,3,1,25,51.0,neutral or dissatisfied +23014,23245,Female,Loyal Customer,27,Business travel,Business,783,4,4,4,4,5,5,5,5,5,3,1,1,2,5,0,10.0,satisfied +23015,103321,Female,Loyal Customer,41,Business travel,Eco,1139,3,4,4,4,4,3,4,4,3,3,3,2,4,4,53,44.0,neutral or dissatisfied +23016,71718,Female,Loyal Customer,29,Business travel,Business,1941,3,3,3,3,5,5,5,5,5,3,5,4,4,5,0,0.0,satisfied +23017,83571,Male,Loyal Customer,55,Business travel,Business,936,1,4,4,4,3,2,3,1,1,1,1,2,1,3,0,2.0,neutral or dissatisfied +23018,61538,Female,Loyal Customer,25,Personal Travel,Eco,2288,2,2,2,4,1,2,1,1,4,5,4,3,3,1,52,12.0,neutral or dissatisfied +23019,80876,Male,Loyal Customer,29,Personal Travel,Eco,484,3,4,3,4,2,3,2,2,1,4,4,2,3,2,11,9.0,neutral or dissatisfied +23020,18432,Male,Loyal Customer,55,Business travel,Business,3365,5,5,5,5,4,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +23021,45188,Male,Loyal Customer,50,Business travel,Business,1437,3,3,3,3,1,4,1,5,5,4,5,2,5,2,91,67.0,satisfied +23022,59757,Female,disloyal Customer,36,Business travel,Business,895,2,2,2,4,1,2,1,1,3,2,5,4,4,1,0,0.0,neutral or dissatisfied +23023,52436,Male,Loyal Customer,8,Personal Travel,Eco,651,2,3,2,5,1,2,1,1,2,1,3,5,5,1,0,0.0,neutral or dissatisfied +23024,29752,Female,disloyal Customer,40,Business travel,Business,571,4,4,4,3,4,4,3,4,5,5,5,3,3,3,193,,neutral or dissatisfied +23025,98724,Male,Loyal Customer,61,Personal Travel,Eco Plus,834,0,4,0,2,1,0,1,1,5,2,5,4,4,1,0,0.0,satisfied +23026,104377,Male,Loyal Customer,35,Business travel,Business,228,1,2,2,2,3,2,2,1,1,1,1,4,1,3,1,40.0,neutral or dissatisfied +23027,94770,Female,Loyal Customer,60,Business travel,Business,239,0,0,0,2,5,5,5,2,2,2,1,4,2,5,2,0.0,satisfied +23028,11115,Male,disloyal Customer,42,Personal Travel,Eco,191,4,4,4,5,4,4,4,4,5,4,5,5,5,4,0,6.0,satisfied +23029,52992,Female,Loyal Customer,55,Business travel,Business,1208,3,3,3,3,5,4,2,5,5,5,5,5,5,4,0,0.0,satisfied +23030,19806,Female,Loyal Customer,39,Business travel,Business,413,1,1,1,1,4,2,2,4,4,4,4,2,4,4,115,130.0,satisfied +23031,96647,Male,disloyal Customer,27,Business travel,Eco,636,2,3,2,3,5,2,5,5,5,5,3,5,4,5,0,18.0,neutral or dissatisfied +23032,93970,Female,Loyal Customer,39,Business travel,Business,1218,4,4,4,4,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +23033,125028,Male,Loyal Customer,25,Personal Travel,Eco Plus,184,2,1,2,3,3,2,3,3,4,1,2,2,3,3,0,0.0,neutral or dissatisfied +23034,42551,Male,Loyal Customer,65,Personal Travel,Eco,1174,1,4,1,4,5,1,5,5,5,3,4,5,5,5,0,0.0,neutral or dissatisfied +23035,26930,Female,Loyal Customer,39,Personal Travel,Eco,1660,1,4,1,4,1,1,1,1,3,1,2,1,3,1,0,0.0,neutral or dissatisfied +23036,65103,Male,Loyal Customer,11,Personal Travel,Eco,282,2,1,4,3,4,5,4,2,3,2,2,4,3,4,148,156.0,neutral or dissatisfied +23037,42176,Male,Loyal Customer,53,Business travel,Business,329,0,0,0,4,5,2,1,2,2,2,2,3,2,3,0,0.0,satisfied +23038,23419,Female,Loyal Customer,38,Personal Travel,Eco,541,3,4,3,4,1,3,1,1,5,4,4,4,4,1,114,105.0,neutral or dissatisfied +23039,49900,Male,Loyal Customer,47,Business travel,Eco,250,1,4,5,4,1,1,1,1,1,4,4,3,4,1,0,0.0,neutral or dissatisfied +23040,45672,Male,Loyal Customer,37,Business travel,Eco,826,4,4,4,4,4,4,4,4,3,4,1,5,2,4,37,68.0,satisfied +23041,26380,Male,Loyal Customer,64,Personal Travel,Eco,991,2,1,2,3,1,2,1,1,3,3,4,1,4,1,0,0.0,neutral or dissatisfied +23042,95906,Female,Loyal Customer,21,Personal Travel,Eco,580,3,4,3,3,5,3,5,5,3,2,5,4,5,5,20,4.0,neutral or dissatisfied +23043,58965,Male,disloyal Customer,49,Business travel,Business,1726,2,2,2,3,2,2,2,4,4,2,3,2,4,2,133,147.0,neutral or dissatisfied +23044,107659,Female,Loyal Customer,50,Business travel,Business,1771,4,4,4,4,2,4,4,4,4,4,4,3,4,5,7,0.0,satisfied +23045,12726,Male,Loyal Customer,18,Business travel,Eco,689,4,2,2,2,4,4,4,4,2,3,2,1,2,4,0,0.0,satisfied +23046,120542,Female,Loyal Customer,53,Business travel,Business,2176,4,4,4,4,3,3,4,5,5,5,5,4,5,4,0,0.0,satisfied +23047,66205,Male,Loyal Customer,39,Business travel,Eco,460,1,1,1,1,1,1,1,1,1,1,4,2,3,1,0,0.0,neutral or dissatisfied +23048,94372,Male,Loyal Customer,47,Business travel,Business,248,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +23049,101557,Female,Loyal Customer,51,Business travel,Business,3313,0,0,0,1,5,4,4,1,1,1,1,3,1,3,0,0.0,satisfied +23050,1185,Male,Loyal Customer,36,Personal Travel,Eco,102,1,5,1,3,2,1,2,2,4,3,5,4,5,2,4,0.0,neutral or dissatisfied +23051,73205,Female,Loyal Customer,7,Personal Travel,Eco,1258,2,5,2,2,1,2,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +23052,91677,Female,disloyal Customer,21,Business travel,Eco,588,4,0,4,4,2,4,5,2,4,4,4,5,5,2,0,0.0,satisfied +23053,23683,Female,Loyal Customer,35,Business travel,Business,251,1,1,1,1,5,2,1,4,4,4,4,2,4,5,10,6.0,satisfied +23054,73533,Male,Loyal Customer,25,Business travel,Business,594,2,2,2,2,3,3,3,3,3,5,4,5,4,3,0,0.0,satisfied +23055,43367,Male,Loyal Customer,38,Personal Travel,Eco,436,2,5,2,1,1,2,1,1,3,5,4,4,5,1,2,8.0,neutral or dissatisfied +23056,57222,Male,Loyal Customer,54,Personal Travel,Eco,1514,1,5,1,5,5,1,5,5,1,4,5,5,5,5,4,0.0,neutral or dissatisfied +23057,21862,Male,Loyal Customer,23,Business travel,Business,500,1,1,1,1,1,2,1,1,4,1,5,5,1,1,0,3.0,satisfied +23058,74917,Female,Loyal Customer,47,Business travel,Business,2586,1,1,1,1,3,5,5,5,5,5,5,3,5,5,1,18.0,satisfied +23059,41216,Male,Loyal Customer,15,Personal Travel,Eco,1091,2,1,2,4,5,2,5,5,3,4,3,2,3,5,0,0.0,neutral or dissatisfied +23060,100684,Female,Loyal Customer,23,Business travel,Eco,889,3,3,3,3,3,3,2,3,3,4,4,1,3,3,12,15.0,neutral or dissatisfied +23061,77742,Male,Loyal Customer,39,Business travel,Business,1980,1,2,2,2,1,4,1,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +23062,34348,Male,disloyal Customer,22,Business travel,Eco,541,2,0,2,3,1,2,5,1,4,5,5,4,2,1,0,0.0,neutral or dissatisfied +23063,81238,Female,Loyal Customer,59,Business travel,Business,223,3,3,3,3,3,4,4,4,4,4,4,4,4,4,3,0.0,satisfied +23064,8976,Male,Loyal Customer,53,Business travel,Business,2214,0,0,0,4,5,4,5,5,5,5,5,4,5,1,0,8.0,satisfied +23065,18277,Female,disloyal Customer,59,Business travel,Eco Plus,179,2,2,2,1,3,2,3,3,5,1,3,5,5,3,0,11.0,neutral or dissatisfied +23066,47599,Female,disloyal Customer,20,Business travel,Eco,1428,2,2,2,3,1,2,1,1,3,4,4,3,4,1,0,0.0,neutral or dissatisfied +23067,34716,Male,Loyal Customer,56,Business travel,Eco,264,5,1,1,1,5,5,5,4,4,5,4,5,3,5,172,189.0,satisfied +23068,126870,Male,Loyal Customer,46,Personal Travel,Eco,2125,5,3,5,4,1,5,1,1,4,3,4,1,3,1,0,0.0,satisfied +23069,90691,Male,Loyal Customer,47,Business travel,Business,3560,3,3,3,3,3,4,4,5,5,5,5,4,5,5,3,0.0,satisfied +23070,70297,Female,Loyal Customer,59,Personal Travel,Eco,852,2,5,2,3,4,4,5,4,4,2,4,3,4,4,2,0.0,neutral or dissatisfied +23071,49331,Male,Loyal Customer,44,Business travel,Eco,308,4,5,5,5,4,4,4,4,4,5,5,2,2,4,0,0.0,satisfied +23072,46516,Male,Loyal Customer,55,Business travel,Business,3962,4,4,4,4,4,1,4,5,5,5,4,4,5,3,4,11.0,satisfied +23073,35193,Female,Loyal Customer,29,Business travel,Business,1671,1,1,1,1,5,5,5,5,5,4,5,2,3,5,0,0.0,satisfied +23074,110698,Male,Loyal Customer,58,Personal Travel,Eco,945,5,3,5,1,1,5,1,1,3,2,3,3,3,1,0,0.0,satisfied +23075,96469,Male,Loyal Customer,25,Business travel,Business,3997,2,2,4,2,4,4,4,4,5,2,5,5,5,4,82,64.0,satisfied +23076,74007,Female,Loyal Customer,65,Personal Travel,Eco,1972,4,3,4,3,4,5,4,3,3,4,3,3,3,5,0,0.0,neutral or dissatisfied +23077,11516,Female,Loyal Customer,18,Personal Travel,Eco Plus,312,2,5,2,3,2,2,2,2,5,4,5,4,5,2,0,0.0,neutral or dissatisfied +23078,54841,Male,Loyal Customer,39,Business travel,Business,862,3,3,5,3,5,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +23079,68211,Male,Loyal Customer,47,Business travel,Business,2090,5,5,5,5,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +23080,44964,Male,Loyal Customer,41,Business travel,Business,222,0,4,0,2,5,4,4,4,4,4,3,4,4,4,0,0.0,satisfied +23081,6885,Male,Loyal Customer,46,Business travel,Business,3538,1,1,1,1,4,5,5,5,5,5,5,4,5,3,2,0.0,satisfied +23082,104126,Female,Loyal Customer,52,Business travel,Business,3998,3,3,5,3,5,5,4,4,4,4,4,5,4,4,62,52.0,satisfied +23083,68499,Male,Loyal Customer,41,Personal Travel,Eco,1303,2,5,2,2,5,2,5,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +23084,13823,Male,Loyal Customer,41,Business travel,Eco,628,5,2,2,2,5,5,5,5,5,2,1,2,2,5,10,18.0,satisfied +23085,118205,Male,Loyal Customer,62,Personal Travel,Eco,1444,3,0,3,1,2,3,2,2,3,5,4,5,4,2,23,26.0,neutral or dissatisfied +23086,87409,Male,Loyal Customer,70,Personal Travel,Eco,425,4,2,4,4,1,4,1,1,3,3,2,2,4,1,89,69.0,neutral or dissatisfied +23087,48676,Female,Loyal Customer,40,Business travel,Business,2104,5,5,1,5,3,5,5,4,4,4,4,4,4,3,0,2.0,satisfied +23088,109202,Male,Loyal Customer,26,Business travel,Business,2724,3,5,4,5,3,3,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +23089,94970,Female,disloyal Customer,21,Business travel,Eco,319,4,0,4,4,1,4,1,1,3,4,2,4,5,1,13,3.0,satisfied +23090,111383,Female,disloyal Customer,28,Business travel,Business,1050,2,2,2,3,3,2,3,3,4,5,4,4,5,3,2,0.0,neutral or dissatisfied +23091,49382,Female,disloyal Customer,36,Business travel,Eco,337,2,4,2,4,3,2,4,3,1,4,2,5,4,3,1,0.0,neutral or dissatisfied +23092,123135,Male,Loyal Customer,46,Business travel,Eco,650,3,2,2,2,3,3,3,3,4,1,4,3,3,3,0,0.0,neutral or dissatisfied +23093,35639,Female,Loyal Customer,29,Personal Travel,Eco Plus,1626,2,4,2,3,1,2,1,1,3,3,5,4,5,1,31,13.0,neutral or dissatisfied +23094,93075,Female,Loyal Customer,15,Personal Travel,Eco Plus,297,2,4,2,5,2,2,2,2,4,5,5,3,4,2,0,3.0,neutral or dissatisfied +23095,61902,Male,disloyal Customer,27,Business travel,Business,550,3,3,3,4,2,3,2,2,3,5,5,4,4,2,88,79.0,neutral or dissatisfied +23096,95446,Male,Loyal Customer,54,Business travel,Business,2011,2,2,2,2,4,5,5,5,5,5,5,3,5,5,11,16.0,satisfied +23097,65927,Female,Loyal Customer,69,Personal Travel,Eco,569,4,4,4,3,5,1,1,4,4,4,4,2,4,1,6,1.0,neutral or dissatisfied +23098,8835,Male,Loyal Customer,15,Business travel,Eco Plus,522,2,4,4,4,2,2,2,2,2,2,4,3,3,2,76,75.0,neutral or dissatisfied +23099,119551,Female,Loyal Customer,9,Personal Travel,Eco,759,3,5,3,1,1,3,4,1,3,4,4,4,5,1,0,8.0,neutral or dissatisfied +23100,126796,Female,Loyal Customer,59,Business travel,Business,2077,2,2,3,2,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23101,3499,Male,Loyal Customer,69,Personal Travel,Eco,1080,2,4,2,3,3,2,3,3,3,3,4,3,4,3,0,9.0,neutral or dissatisfied +23102,84421,Male,Loyal Customer,22,Personal Travel,Eco,591,2,5,2,1,3,2,3,3,1,3,5,5,1,3,1,0.0,neutral or dissatisfied +23103,72175,Female,Loyal Customer,49,Business travel,Business,2296,3,3,2,3,2,5,5,4,4,5,4,3,4,3,49,61.0,satisfied +23104,65850,Female,Loyal Customer,47,Business travel,Eco,991,3,2,2,2,2,4,4,3,3,3,3,3,3,3,19,2.0,neutral or dissatisfied +23105,814,Male,Loyal Customer,30,Business travel,Business,309,2,3,3,3,2,2,2,2,3,5,3,4,4,2,0,0.0,neutral or dissatisfied +23106,57820,Female,Loyal Customer,60,Business travel,Business,622,1,1,1,1,2,4,5,4,4,4,4,5,4,5,14,30.0,satisfied +23107,102156,Female,Loyal Customer,45,Business travel,Business,223,2,2,2,2,2,4,4,5,5,5,5,5,5,4,4,0.0,satisfied +23108,62309,Male,Loyal Customer,49,Business travel,Eco,414,3,5,5,5,3,3,3,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +23109,24761,Female,Loyal Customer,23,Business travel,Business,3987,5,5,5,5,4,4,4,4,1,2,5,1,3,4,0,3.0,satisfied +23110,105169,Female,Loyal Customer,18,Personal Travel,Eco,220,3,1,3,3,1,3,1,1,3,2,4,3,3,1,0,0.0,neutral or dissatisfied +23111,102602,Male,Loyal Customer,58,Personal Travel,Eco Plus,397,1,4,1,1,1,1,1,1,4,4,4,5,5,1,6,4.0,neutral or dissatisfied +23112,82348,Male,Loyal Customer,44,Business travel,Eco,201,4,5,5,5,5,4,5,5,3,4,3,1,4,5,0,0.0,neutral or dissatisfied +23113,36879,Male,Loyal Customer,23,Business travel,Business,3017,2,2,2,2,3,4,3,3,3,3,2,4,5,3,8,0.0,satisfied +23114,35133,Female,Loyal Customer,47,Business travel,Business,1572,2,2,2,2,4,1,1,3,3,3,3,3,3,5,0,0.0,satisfied +23115,67101,Male,Loyal Customer,50,Business travel,Business,3650,1,1,5,1,4,4,4,5,5,4,5,5,5,5,0,0.0,satisfied +23116,2777,Female,Loyal Customer,57,Business travel,Business,2054,3,3,3,3,4,4,4,5,5,5,5,4,5,3,0,2.0,satisfied +23117,1549,Male,Loyal Customer,70,Personal Travel,Eco,922,1,4,1,4,1,1,1,1,4,1,3,1,3,1,0,0.0,neutral or dissatisfied +23118,118422,Male,disloyal Customer,20,Business travel,Eco,646,5,4,5,3,2,5,2,2,3,2,5,4,4,2,0,0.0,satisfied +23119,93706,Female,Loyal Customer,29,Business travel,Business,689,2,3,3,3,2,2,2,2,3,2,4,1,4,2,21,8.0,neutral or dissatisfied +23120,120536,Male,Loyal Customer,43,Business travel,Business,2176,4,3,3,3,4,2,3,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +23121,62042,Female,disloyal Customer,33,Business travel,Business,2475,1,1,1,4,5,1,5,5,3,5,5,5,5,5,1,0.0,neutral or dissatisfied +23122,128505,Male,Loyal Customer,49,Personal Travel,Eco,338,2,2,2,4,3,2,3,3,4,3,4,4,4,3,1,0.0,neutral or dissatisfied +23123,109630,Male,Loyal Customer,36,Business travel,Business,3905,3,3,3,3,4,4,4,3,3,2,3,4,3,4,2,0.0,satisfied +23124,20410,Male,Loyal Customer,55,Business travel,Eco,196,4,2,2,2,4,4,4,4,3,1,1,5,3,4,14,19.0,satisfied +23125,54960,Male,disloyal Customer,35,Business travel,Business,1303,4,4,4,4,2,4,2,2,5,5,4,3,4,2,0,0.0,neutral or dissatisfied +23126,104943,Female,disloyal Customer,28,Business travel,Eco,1180,1,1,1,4,2,1,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +23127,89568,Female,Loyal Customer,47,Business travel,Eco,950,3,2,2,2,3,4,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +23128,5050,Female,Loyal Customer,45,Business travel,Business,2673,3,3,2,3,3,5,4,4,4,4,5,4,4,4,0,0.0,satisfied +23129,77769,Male,Loyal Customer,56,Personal Travel,Eco,813,2,3,2,2,5,2,5,5,3,1,2,4,3,5,32,30.0,neutral or dissatisfied +23130,30592,Female,Loyal Customer,31,Business travel,Eco Plus,628,4,5,5,5,4,4,4,4,1,4,5,1,5,4,0,0.0,satisfied +23131,33520,Male,Loyal Customer,47,Business travel,Business,2120,0,0,0,1,3,5,4,4,4,4,4,5,4,4,1,0.0,satisfied +23132,37852,Female,Loyal Customer,26,Business travel,Eco,937,4,3,3,3,4,4,4,4,1,1,3,2,1,4,1,0.0,satisfied +23133,114551,Male,Loyal Customer,10,Personal Travel,Business,337,1,4,1,4,5,1,4,5,4,1,4,4,3,5,0,1.0,neutral or dissatisfied +23134,82556,Male,Loyal Customer,50,Personal Travel,Business,528,3,5,3,2,4,5,5,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +23135,97301,Female,Loyal Customer,58,Business travel,Business,843,4,4,4,4,2,5,5,2,2,2,2,4,2,5,75,82.0,satisfied +23136,49990,Male,Loyal Customer,36,Business travel,Business,109,2,2,2,2,4,1,1,4,4,4,4,4,4,1,0,2.0,satisfied +23137,94913,Female,Loyal Customer,37,Business travel,Business,2415,4,3,4,4,1,4,3,4,4,4,4,2,4,2,26,19.0,neutral or dissatisfied +23138,29878,Female,disloyal Customer,36,Business travel,Eco,234,3,3,3,3,4,3,4,4,3,1,4,4,3,4,0,0.0,neutral or dissatisfied +23139,44814,Male,Loyal Customer,47,Personal Travel,Eco,802,3,3,4,3,3,4,3,3,2,1,4,1,3,3,65,86.0,neutral or dissatisfied +23140,40941,Male,Loyal Customer,34,Personal Travel,Eco Plus,590,3,5,3,2,4,3,4,4,5,3,5,4,4,4,104,101.0,neutral or dissatisfied +23141,113529,Male,disloyal Customer,70,Business travel,Business,386,4,5,5,4,5,4,5,5,5,3,5,5,5,5,0,0.0,satisfied +23142,80768,Female,Loyal Customer,66,Personal Travel,Eco,629,4,5,5,5,5,5,5,1,1,5,1,3,1,5,0,0.0,neutral or dissatisfied +23143,78965,Male,Loyal Customer,41,Business travel,Business,2946,2,2,2,2,4,4,5,5,5,5,5,4,5,5,10,0.0,satisfied +23144,24106,Male,Loyal Customer,41,Business travel,Business,2965,3,3,3,3,5,2,5,4,4,4,4,3,4,4,0,0.0,satisfied +23145,101901,Male,Loyal Customer,63,Business travel,Eco,2173,3,2,2,2,3,3,3,3,3,3,2,4,2,3,28,4.0,neutral or dissatisfied +23146,13537,Female,disloyal Customer,24,Business travel,Eco,152,0,0,0,3,4,0,5,4,2,1,4,5,4,4,0,0.0,satisfied +23147,47200,Female,disloyal Customer,16,Business travel,Eco,620,2,2,2,4,3,2,2,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +23148,24656,Female,Loyal Customer,47,Business travel,Business,834,2,1,1,1,5,2,2,2,2,2,2,2,2,4,15,15.0,neutral or dissatisfied +23149,4716,Female,Loyal Customer,69,Personal Travel,Eco Plus,364,4,4,2,4,4,4,5,5,5,2,5,4,5,5,10,23.0,neutral or dissatisfied +23150,51112,Male,Loyal Customer,19,Personal Travel,Eco,326,5,3,5,3,1,5,1,1,3,2,3,2,1,1,0,0.0,satisfied +23151,79863,Female,Loyal Customer,59,Business travel,Business,1851,5,5,5,5,3,5,4,5,5,5,5,3,5,3,0,1.0,satisfied +23152,75095,Male,Loyal Customer,39,Business travel,Business,1744,3,3,3,3,2,4,5,3,3,4,3,4,3,5,0,10.0,satisfied +23153,106016,Male,Loyal Customer,42,Business travel,Business,1999,3,3,3,3,3,5,4,5,5,5,5,3,5,3,8,0.0,satisfied +23154,26878,Female,disloyal Customer,15,Business travel,Eco,2329,1,1,1,3,5,1,5,5,2,2,3,2,4,5,45,62.0,neutral or dissatisfied +23155,50166,Male,disloyal Customer,33,Business travel,Eco,86,3,4,2,3,3,2,3,3,4,2,4,4,3,3,36,36.0,neutral or dissatisfied +23156,127710,Female,Loyal Customer,66,Personal Travel,Business,255,4,5,0,1,5,3,3,5,5,0,5,2,5,5,2,12.0,neutral or dissatisfied +23157,55599,Male,Loyal Customer,56,Business travel,Business,2773,2,2,2,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +23158,71813,Male,Loyal Customer,43,Business travel,Business,1726,5,5,5,5,3,4,5,4,4,4,4,3,4,4,126,122.0,satisfied +23159,115003,Male,Loyal Customer,42,Business travel,Business,337,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,5.0,satisfied +23160,107915,Male,Loyal Customer,17,Personal Travel,Eco,861,2,1,2,2,1,2,1,1,3,5,3,3,2,1,0,0.0,neutral or dissatisfied +23161,90929,Female,Loyal Customer,46,Business travel,Eco,406,4,1,1,1,1,1,3,4,4,4,4,3,4,3,0,2.0,satisfied +23162,114580,Male,Loyal Customer,60,Business travel,Business,3162,4,4,4,4,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +23163,18646,Male,Loyal Customer,36,Personal Travel,Eco,262,2,5,0,1,2,0,5,2,5,4,5,4,1,2,0,0.0,neutral or dissatisfied +23164,106594,Male,disloyal Customer,27,Business travel,Business,986,3,3,3,3,3,3,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +23165,121243,Male,Loyal Customer,44,Business travel,Business,2075,4,4,2,4,3,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +23166,92134,Male,Loyal Customer,50,Personal Travel,Eco,1522,3,4,3,3,3,3,3,3,4,3,4,4,5,3,0,6.0,neutral or dissatisfied +23167,20145,Male,Loyal Customer,47,Business travel,Business,1740,2,2,2,2,5,1,4,4,4,4,4,2,4,4,31,11.0,satisfied +23168,23881,Female,Loyal Customer,33,Business travel,Business,589,4,2,2,2,2,3,4,4,4,4,4,3,4,2,94,83.0,neutral or dissatisfied +23169,16047,Male,Loyal Customer,23,Personal Travel,Eco,833,1,5,1,1,1,1,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +23170,43045,Female,Loyal Customer,48,Business travel,Eco,192,1,2,2,2,4,2,2,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +23171,51198,Female,disloyal Customer,22,Business travel,Business,304,5,3,5,3,4,5,4,4,2,1,5,1,5,4,0,0.0,satisfied +23172,83785,Male,Loyal Customer,54,Business travel,Business,3601,1,1,1,1,3,5,5,5,5,5,5,5,5,3,10,10.0,satisfied +23173,92919,Male,Loyal Customer,49,Business travel,Business,134,4,1,4,1,2,4,4,3,3,3,4,1,3,1,24,48.0,neutral or dissatisfied +23174,106651,Female,Loyal Customer,60,Business travel,Business,1590,1,1,1,1,1,2,3,1,1,2,1,1,1,4,0,0.0,neutral or dissatisfied +23175,71055,Female,Loyal Customer,35,Business travel,Business,3506,4,4,4,4,5,4,4,4,4,4,4,1,4,4,13,13.0,neutral or dissatisfied +23176,89074,Male,disloyal Customer,22,Business travel,Business,1118,5,4,5,5,4,5,4,4,5,3,3,3,4,4,0,0.0,satisfied +23177,20439,Male,disloyal Customer,25,Business travel,Business,84,3,3,3,3,2,3,3,2,3,2,3,2,4,2,18,10.0,neutral or dissatisfied +23178,21820,Female,disloyal Customer,39,Business travel,Business,352,1,0,0,3,3,0,3,3,5,4,1,1,3,3,26,20.0,neutral or dissatisfied +23179,124710,Female,Loyal Customer,29,Personal Travel,Eco,399,1,4,1,3,2,1,2,2,5,5,5,3,4,2,0,4.0,neutral or dissatisfied +23180,121212,Male,Loyal Customer,11,Personal Travel,Business,2075,5,3,5,4,3,5,3,3,4,4,3,1,3,3,0,0.0,satisfied +23181,66382,Male,Loyal Customer,59,Business travel,Business,1562,5,5,5,5,2,4,5,4,4,4,4,3,4,5,0,0.0,satisfied +23182,57642,Female,Loyal Customer,66,Business travel,Eco,200,2,4,5,4,1,3,3,2,2,2,2,1,2,2,2,0.0,neutral or dissatisfied +23183,63430,Female,Loyal Customer,50,Personal Travel,Eco,337,3,4,3,5,4,5,4,5,5,3,5,4,5,5,0,0.0,neutral or dissatisfied +23184,39979,Male,disloyal Customer,19,Business travel,Eco,1404,2,2,2,4,2,2,2,2,1,3,3,2,4,2,40,34.0,neutral or dissatisfied +23185,23029,Female,Loyal Customer,30,Business travel,Eco,927,4,1,3,3,4,5,4,4,5,5,2,2,3,4,0,0.0,satisfied +23186,4758,Female,Loyal Customer,39,Business travel,Business,2093,1,1,1,1,3,5,5,5,5,5,5,4,5,5,0,22.0,satisfied +23187,115890,Female,Loyal Customer,51,Business travel,Business,3457,1,1,3,1,5,3,3,5,5,5,5,2,5,3,3,0.0,satisfied +23188,40727,Female,disloyal Customer,33,Business travel,Eco,599,2,0,2,2,5,2,3,5,1,5,5,1,4,5,0,0.0,neutral or dissatisfied +23189,28873,Female,disloyal Customer,26,Business travel,Eco,1050,2,1,1,1,4,1,4,4,2,3,1,3,3,4,0,0.0,neutral or dissatisfied +23190,46481,Female,Loyal Customer,46,Personal Travel,Business,73,3,5,3,2,2,4,5,1,1,3,1,3,1,3,17,13.0,neutral or dissatisfied +23191,64361,Male,Loyal Customer,44,Business travel,Business,2392,4,4,3,3,5,4,3,4,4,3,4,4,4,1,75,105.0,neutral or dissatisfied +23192,89102,Female,Loyal Customer,22,Business travel,Business,1919,4,4,4,4,3,3,3,3,3,5,4,5,4,3,10,9.0,satisfied +23193,88614,Female,Loyal Customer,44,Personal Travel,Eco,646,2,4,2,4,3,2,2,2,2,2,2,4,2,5,11,24.0,neutral or dissatisfied +23194,3911,Male,Loyal Customer,10,Personal Travel,Eco,213,1,2,1,3,5,1,5,5,3,5,4,4,5,5,25,24.0,neutral or dissatisfied +23195,60009,Male,Loyal Customer,16,Personal Travel,Eco,1085,2,5,2,2,4,2,4,4,3,1,5,2,4,4,0,0.0,neutral or dissatisfied +23196,25386,Male,Loyal Customer,60,Personal Travel,Eco,591,2,5,2,5,1,2,1,1,5,3,4,3,4,1,65,57.0,neutral or dissatisfied +23197,55620,Female,Loyal Customer,39,Business travel,Business,1824,2,2,1,2,5,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +23198,15773,Female,Loyal Customer,62,Business travel,Business,198,4,5,5,5,1,4,1,3,2,3,4,1,3,1,285,251.0,neutral or dissatisfied +23199,121021,Male,Loyal Customer,44,Personal Travel,Eco,920,2,4,1,3,4,1,4,4,3,4,4,4,5,4,14,1.0,neutral or dissatisfied +23200,71381,Male,Loyal Customer,53,Personal Travel,Eco,258,4,4,4,4,4,4,2,4,4,1,4,1,4,4,0,0.0,neutral or dissatisfied +23201,44481,Male,Loyal Customer,31,Business travel,Business,692,3,3,3,3,5,4,5,5,3,1,1,2,5,5,0,0.0,satisfied +23202,79394,Female,Loyal Customer,17,Business travel,Business,502,2,1,1,1,2,1,2,2,3,3,1,4,2,2,55,35.0,neutral or dissatisfied +23203,4208,Female,disloyal Customer,24,Business travel,Business,888,5,0,5,1,3,5,3,3,3,4,5,5,5,3,0,22.0,satisfied +23204,85662,Female,disloyal Customer,21,Business travel,Business,903,5,5,5,4,3,5,3,3,5,3,5,5,4,3,82,78.0,satisfied +23205,7552,Female,Loyal Customer,36,Business travel,Business,3903,3,3,3,3,2,4,5,4,4,4,4,3,4,3,5,0.0,satisfied +23206,110138,Male,disloyal Customer,29,Business travel,Eco,1048,2,3,3,4,5,3,5,5,4,5,3,4,3,5,0,11.0,neutral or dissatisfied +23207,90994,Male,disloyal Customer,23,Business travel,Eco,145,2,3,2,4,5,2,5,5,1,2,3,1,3,5,13,16.0,neutral or dissatisfied +23208,60385,Female,Loyal Customer,52,Business travel,Business,1452,5,5,5,5,3,5,5,5,5,4,5,5,5,4,1,0.0,satisfied +23209,36801,Male,Loyal Customer,9,Personal Travel,Eco,2611,3,3,3,3,3,4,4,1,4,3,5,4,4,4,0,0.0,neutral or dissatisfied +23210,48957,Male,Loyal Customer,25,Business travel,Business,1780,3,5,5,5,4,4,3,4,2,2,4,4,3,4,0,9.0,neutral or dissatisfied +23211,1035,Male,disloyal Customer,17,Business travel,Eco,158,2,3,2,4,3,2,3,3,4,3,3,1,3,3,28,43.0,neutral or dissatisfied +23212,31808,Female,Loyal Customer,46,Business travel,Eco,2603,4,2,2,2,4,4,4,2,5,3,1,4,5,4,0,0.0,satisfied +23213,59494,Female,Loyal Customer,40,Personal Travel,Eco,758,3,4,3,2,5,3,5,5,4,5,5,4,5,5,0,6.0,neutral or dissatisfied +23214,26117,Male,Loyal Customer,60,Business travel,Business,404,3,5,2,5,4,4,4,3,3,3,3,3,3,1,4,0.0,neutral or dissatisfied +23215,96998,Male,Loyal Customer,11,Personal Travel,Eco,794,2,4,2,4,2,2,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +23216,42645,Female,Loyal Customer,26,Personal Travel,Eco,546,4,5,4,3,3,4,3,3,5,4,3,4,2,3,11,17.0,neutral or dissatisfied +23217,117102,Female,Loyal Customer,62,Business travel,Business,1549,5,5,5,5,2,3,4,4,4,4,4,5,4,5,51,40.0,satisfied +23218,48925,Male,Loyal Customer,36,Business travel,Business,2053,5,5,5,5,5,4,4,4,4,4,4,2,4,3,34,35.0,satisfied +23219,92199,Female,Loyal Customer,36,Business travel,Eco,1979,4,2,4,2,4,3,4,4,1,3,3,2,3,4,0,6.0,neutral or dissatisfied +23220,33540,Male,Loyal Customer,60,Business travel,Business,3470,1,4,4,4,2,3,3,1,1,1,1,2,1,3,0,8.0,neutral or dissatisfied +23221,59204,Male,Loyal Customer,54,Business travel,Business,1440,3,5,5,5,5,3,3,3,3,3,3,4,3,2,43,55.0,neutral or dissatisfied +23222,105125,Female,Loyal Customer,39,Business travel,Eco,289,2,2,2,2,2,2,2,2,4,1,3,2,3,2,7,10.0,neutral or dissatisfied +23223,21573,Male,Loyal Customer,9,Personal Travel,Eco Plus,331,1,2,1,3,5,1,5,5,4,3,3,2,3,5,0,0.0,neutral or dissatisfied +23224,111394,Male,Loyal Customer,46,Personal Travel,Eco,1050,1,5,1,1,1,1,1,1,3,3,5,3,5,1,8,0.0,neutral or dissatisfied +23225,64687,Female,Loyal Customer,49,Business travel,Business,224,3,3,3,3,4,5,5,5,5,5,5,4,5,3,46,34.0,satisfied +23226,93876,Male,Loyal Customer,28,Business travel,Business,590,2,2,2,2,5,5,5,5,4,4,4,3,4,5,3,3.0,satisfied +23227,94731,Male,Loyal Customer,58,Business travel,Eco,189,3,1,3,1,3,3,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +23228,96621,Male,Loyal Customer,50,Business travel,Business,3474,3,3,3,3,4,4,5,5,5,5,5,5,5,5,7,0.0,satisfied +23229,15807,Male,Loyal Customer,45,Personal Travel,Eco,246,3,1,3,3,4,3,4,4,1,5,3,4,4,4,0,0.0,neutral or dissatisfied +23230,101787,Male,Loyal Customer,53,Business travel,Business,1521,1,1,1,1,3,5,4,5,5,5,5,4,5,5,5,0.0,satisfied +23231,72628,Male,Loyal Customer,64,Personal Travel,Eco,1121,4,4,4,3,1,4,2,1,5,5,4,3,4,1,0,0.0,neutral or dissatisfied +23232,91728,Female,Loyal Customer,45,Business travel,Business,588,5,5,5,5,5,4,5,2,2,2,2,5,2,5,0,0.0,satisfied +23233,96398,Male,Loyal Customer,57,Business travel,Business,3330,5,5,5,5,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +23234,50249,Female,Loyal Customer,55,Business travel,Eco,89,2,1,1,1,4,2,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +23235,65331,Female,Loyal Customer,48,Business travel,Business,2659,2,2,2,2,5,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +23236,8557,Male,Loyal Customer,48,Business travel,Business,308,5,5,5,5,4,4,4,5,5,5,5,4,5,5,48,37.0,satisfied +23237,30728,Male,Loyal Customer,41,Personal Travel,Eco,1062,1,1,1,3,1,1,1,1,1,1,3,4,3,1,0,0.0,neutral or dissatisfied +23238,129847,Female,Loyal Customer,16,Personal Travel,Eco,337,0,4,0,5,3,0,3,3,5,2,4,4,5,3,0,0.0,satisfied +23239,55609,Female,disloyal Customer,17,Business travel,Eco,404,2,2,1,4,1,1,1,1,2,3,3,4,4,1,34,9.0,neutral or dissatisfied +23240,69297,Male,Loyal Customer,54,Personal Travel,Eco Plus,733,4,2,4,4,1,4,1,1,3,4,3,1,4,1,0,0.0,neutral or dissatisfied +23241,100870,Male,Loyal Customer,60,Personal Travel,Eco,1605,4,5,4,3,4,4,5,4,3,4,4,5,5,4,0,0.0,neutral or dissatisfied +23242,11695,Male,disloyal Customer,36,Business travel,Business,395,1,1,1,2,1,2,3,5,4,4,5,3,4,3,141,157.0,neutral or dissatisfied +23243,78564,Male,Loyal Customer,18,Personal Travel,Business,630,5,5,5,1,5,5,2,5,5,4,5,3,4,5,0,0.0,satisfied +23244,21837,Male,disloyal Customer,22,Business travel,Business,448,4,0,4,4,2,4,2,2,3,2,4,3,4,2,9,2.0,satisfied +23245,28320,Female,Loyal Customer,43,Business travel,Eco,867,5,3,3,3,4,2,2,5,5,5,5,1,5,2,18,6.0,satisfied +23246,61061,Female,disloyal Customer,38,Business travel,Eco,1709,2,2,2,4,3,2,3,3,1,5,2,2,4,3,16,12.0,neutral or dissatisfied +23247,32388,Female,Loyal Customer,55,Business travel,Eco,101,4,5,5,5,2,3,2,4,4,4,4,3,4,5,0,0.0,satisfied +23248,20562,Female,Loyal Customer,43,Business travel,Eco,533,1,3,5,5,5,3,3,1,1,1,1,3,1,4,0,0.0,neutral or dissatisfied +23249,26542,Male,Loyal Customer,68,Personal Travel,Eco,990,3,4,3,4,4,3,4,4,4,5,5,5,5,4,78,70.0,neutral or dissatisfied +23250,123365,Female,Loyal Customer,30,Business travel,Business,3396,3,4,4,4,3,3,3,3,2,2,3,4,4,3,0,0.0,neutral or dissatisfied +23251,88346,Male,Loyal Customer,55,Business travel,Business,240,2,2,2,2,4,2,3,2,2,3,2,3,2,2,14,9.0,neutral or dissatisfied +23252,77668,Female,Loyal Customer,30,Business travel,Eco,874,4,3,3,3,4,3,4,4,4,5,3,2,3,4,0,0.0,neutral or dissatisfied +23253,75437,Female,Loyal Customer,51,Business travel,Business,2585,3,3,3,3,4,5,4,2,2,2,2,3,2,4,0,0.0,satisfied +23254,85209,Female,disloyal Customer,22,Business travel,Business,731,0,0,0,1,5,0,5,5,5,3,5,3,4,5,0,4.0,satisfied +23255,53307,Male,Loyal Customer,66,Personal Travel,Eco,758,4,5,4,3,2,4,2,2,5,5,4,5,4,2,52,47.0,neutral or dissatisfied +23256,64611,Male,Loyal Customer,57,Business travel,Business,551,2,2,2,2,2,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +23257,118091,Male,Loyal Customer,57,Personal Travel,Eco,1276,2,4,2,2,2,2,4,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +23258,62710,Female,Loyal Customer,56,Business travel,Business,2556,1,1,2,1,2,4,4,4,4,4,4,3,4,4,2,8.0,satisfied +23259,21504,Female,Loyal Customer,41,Personal Travel,Eco,433,1,5,1,3,3,1,4,3,5,3,5,4,4,3,23,21.0,neutral or dissatisfied +23260,116529,Female,Loyal Customer,44,Personal Travel,Eco,337,0,4,0,2,2,5,5,2,2,0,2,5,2,5,0,0.0,satisfied +23261,90454,Female,Loyal Customer,30,Business travel,Business,581,1,1,1,1,4,4,4,4,3,4,4,5,5,4,0,0.0,satisfied +23262,98713,Male,Loyal Customer,64,Business travel,Eco Plus,834,2,2,2,2,2,2,2,2,1,3,2,1,3,2,0,10.0,neutral or dissatisfied +23263,60124,Female,Loyal Customer,29,Business travel,Business,2410,4,5,5,5,4,3,4,4,4,1,3,4,3,4,12,0.0,neutral or dissatisfied +23264,129255,Male,Loyal Customer,27,Personal Travel,Eco,1504,2,5,2,3,1,2,1,1,5,2,4,3,5,1,0,3.0,neutral or dissatisfied +23265,14243,Male,Loyal Customer,43,Business travel,Eco,1027,4,5,5,5,4,4,4,4,1,5,1,2,4,4,10,9.0,satisfied +23266,11337,Male,Loyal Customer,58,Personal Travel,Eco,247,2,5,2,5,1,2,1,1,2,5,4,5,5,1,0,0.0,neutral or dissatisfied +23267,25834,Male,Loyal Customer,22,Business travel,Business,3811,5,5,5,5,4,4,4,4,1,5,3,4,3,4,0,0.0,satisfied +23268,78068,Female,Loyal Customer,57,Personal Travel,Eco,332,3,4,3,3,4,4,5,1,1,3,1,3,1,4,0,0.0,neutral or dissatisfied +23269,2787,Female,Loyal Customer,52,Business travel,Business,2413,4,4,4,4,5,5,4,2,2,2,2,3,2,4,13,15.0,satisfied +23270,2700,Male,disloyal Customer,20,Business travel,Eco,562,2,3,2,4,5,2,5,5,4,2,4,4,3,5,44,43.0,neutral or dissatisfied +23271,32034,Male,Loyal Customer,30,Business travel,Business,3690,0,5,0,3,4,5,5,4,4,3,5,5,5,4,0,4.0,satisfied +23272,90698,Female,disloyal Customer,36,Business travel,Business,646,2,2,2,3,4,2,4,4,5,3,5,5,5,4,0,1.0,neutral or dissatisfied +23273,37953,Male,Loyal Customer,26,Personal Travel,Eco Plus,937,3,4,3,3,1,3,1,1,2,1,3,5,5,1,20,2.0,neutral or dissatisfied +23274,11303,Male,Loyal Customer,9,Personal Travel,Eco,166,2,5,2,3,2,2,2,2,5,4,2,4,3,2,0,0.0,neutral or dissatisfied +23275,3248,Male,disloyal Customer,25,Business travel,Business,425,2,0,2,4,5,2,5,5,5,5,4,5,5,5,15,7.0,neutral or dissatisfied +23276,62456,Female,disloyal Customer,37,Business travel,Business,923,2,2,2,3,2,2,2,2,3,3,4,4,5,2,0,0.0,satisfied +23277,93072,Male,Loyal Customer,10,Personal Travel,Eco,297,1,2,1,3,4,1,4,4,4,3,3,4,4,4,2,10.0,neutral or dissatisfied +23278,46064,Female,Loyal Customer,59,Personal Travel,Eco Plus,964,3,5,3,3,5,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +23279,95557,Female,Loyal Customer,65,Personal Travel,Eco Plus,562,3,1,3,2,1,2,2,3,3,3,3,4,3,3,76,65.0,neutral or dissatisfied +23280,104474,Female,Loyal Customer,38,Business travel,Eco,1671,3,1,3,1,3,3,3,3,4,5,2,1,3,3,0,0.0,neutral or dissatisfied +23281,34989,Female,Loyal Customer,46,Business travel,Business,1182,5,5,5,5,5,5,5,4,4,4,4,4,4,3,5,0.0,satisfied +23282,77858,Male,Loyal Customer,34,Personal Travel,Eco Plus,689,2,5,2,1,5,2,5,5,2,5,2,4,2,5,6,0.0,neutral or dissatisfied +23283,18652,Male,Loyal Customer,13,Personal Travel,Eco,201,4,5,4,1,1,4,1,1,5,4,2,3,5,1,0,0.0,neutral or dissatisfied +23284,8404,Male,disloyal Customer,47,Business travel,Business,862,2,2,2,1,3,2,3,3,3,2,5,3,5,3,6,0.0,neutral or dissatisfied +23285,80263,Female,Loyal Customer,66,Personal Travel,Business,488,3,4,3,4,3,4,3,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +23286,85031,Female,Loyal Customer,49,Personal Travel,Eco,1590,4,3,4,4,1,3,4,4,4,4,4,1,4,2,17,0.0,neutral or dissatisfied +23287,95863,Female,Loyal Customer,57,Business travel,Business,1634,5,5,5,5,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +23288,25324,Female,Loyal Customer,34,Business travel,Business,837,5,5,5,5,4,5,2,4,4,4,4,3,4,4,0,0.0,satisfied +23289,35984,Female,Loyal Customer,25,Business travel,Business,2496,4,4,4,4,4,4,4,4,2,4,4,4,5,4,0,0.0,satisfied +23290,103199,Female,Loyal Customer,15,Personal Travel,Eco,814,0,0,0,3,2,0,2,2,3,3,4,4,4,2,0,0.0,satisfied +23291,126530,Female,Loyal Customer,52,Business travel,Business,2572,5,5,5,5,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +23292,42628,Female,Loyal Customer,31,Business travel,Business,1565,2,2,3,3,2,2,2,2,1,2,4,3,3,2,62,33.0,neutral or dissatisfied +23293,67259,Male,Loyal Customer,68,Personal Travel,Eco,1121,5,4,5,3,3,5,3,3,4,5,5,4,4,3,0,0.0,satisfied +23294,5537,Female,Loyal Customer,21,Personal Travel,Eco,431,3,4,3,4,1,3,1,1,3,2,4,5,5,1,0,0.0,neutral or dissatisfied +23295,114233,Female,Loyal Customer,13,Business travel,Business,850,2,5,2,5,2,2,2,2,2,4,4,2,4,2,6,6.0,neutral or dissatisfied +23296,24616,Female,disloyal Customer,22,Business travel,Eco,666,4,3,4,3,2,4,2,2,1,4,4,4,3,2,115,94.0,neutral or dissatisfied +23297,115863,Male,Loyal Customer,53,Business travel,Business,404,2,4,4,4,2,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +23298,26643,Male,Loyal Customer,34,Business travel,Business,406,1,1,1,1,2,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +23299,37714,Male,Loyal Customer,44,Personal Travel,Eco,1005,3,5,3,5,1,3,1,1,4,4,5,4,5,1,39,30.0,neutral or dissatisfied +23300,91947,Male,Loyal Customer,64,Personal Travel,Eco,2446,2,4,2,1,2,2,2,2,5,4,4,5,5,2,0,20.0,neutral or dissatisfied +23301,105183,Male,Loyal Customer,67,Personal Travel,Eco,281,4,1,3,3,3,3,4,3,4,4,3,2,4,3,0,0.0,neutral or dissatisfied +23302,36114,Female,Loyal Customer,41,Business travel,Business,1698,4,3,3,3,5,2,3,4,4,3,4,3,4,2,0,12.0,neutral or dissatisfied +23303,78224,Female,Loyal Customer,14,Personal Travel,Eco,259,2,2,0,4,1,0,1,1,4,1,4,4,3,1,0,0.0,neutral or dissatisfied +23304,69744,Male,Loyal Customer,32,Business travel,Business,2725,5,5,3,5,5,5,5,5,5,4,4,4,5,5,12,19.0,satisfied +23305,76332,Female,Loyal Customer,63,Personal Travel,Eco,2182,4,3,4,3,5,4,4,5,5,4,5,4,5,2,24,11.0,neutral or dissatisfied +23306,3816,Male,disloyal Customer,29,Business travel,Business,650,5,5,5,3,5,5,5,5,5,4,4,5,5,5,0,7.0,satisfied +23307,37436,Female,Loyal Customer,28,Business travel,Business,3517,3,2,2,2,3,3,3,3,1,3,3,4,3,3,76,108.0,neutral or dissatisfied +23308,129016,Female,Loyal Customer,22,Business travel,Business,2611,3,3,3,3,4,4,4,4,4,3,3,5,4,4,8,,satisfied +23309,102882,Female,Loyal Customer,20,Personal Travel,Eco,472,3,3,3,4,4,3,4,4,3,5,1,2,2,4,3,0.0,neutral or dissatisfied +23310,32759,Male,Loyal Customer,33,Business travel,Business,3973,2,2,2,2,4,4,3,4,2,3,5,4,3,4,0,0.0,satisfied +23311,19426,Male,Loyal Customer,28,Business travel,Business,645,1,1,3,1,5,5,5,5,3,3,3,5,4,5,11,0.0,satisfied +23312,122864,Male,Loyal Customer,29,Business travel,Business,2947,3,3,4,3,3,3,3,3,1,3,2,4,3,3,43,31.0,neutral or dissatisfied +23313,105197,Female,Loyal Customer,45,Business travel,Eco Plus,289,4,5,5,5,3,5,4,4,4,4,4,2,4,1,0,9.0,satisfied +23314,50167,Female,Loyal Customer,37,Business travel,Eco,262,5,1,1,1,5,4,5,5,2,4,4,2,3,5,58,56.0,neutral or dissatisfied +23315,99203,Female,Loyal Customer,23,Personal Travel,Eco,691,3,5,3,3,1,3,1,1,5,2,5,3,5,1,1,1.0,neutral or dissatisfied +23316,85358,Female,Loyal Customer,35,Personal Travel,Eco Plus,689,4,4,4,1,1,4,1,1,5,2,4,4,5,1,0,0.0,neutral or dissatisfied +23317,15043,Male,disloyal Customer,24,Business travel,Eco,576,4,2,4,3,3,4,3,3,2,4,4,2,3,3,54,52.0,neutral or dissatisfied +23318,83251,Female,disloyal Customer,34,Business travel,Business,1956,3,3,3,4,2,3,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +23319,55977,Male,Loyal Customer,27,Personal Travel,Eco,1620,2,5,2,3,1,2,1,1,4,3,3,5,5,1,0,0.0,neutral or dissatisfied +23320,87373,Female,Loyal Customer,61,Business travel,Eco,425,1,2,2,2,3,2,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +23321,49120,Female,Loyal Customer,34,Business travel,Business,1840,0,0,0,4,3,1,1,5,5,5,5,2,5,1,0,0.0,satisfied +23322,4229,Male,Loyal Customer,51,Business travel,Business,1020,2,2,2,2,2,4,4,4,4,4,4,3,4,4,29,41.0,satisfied +23323,98789,Male,Loyal Customer,42,Business travel,Business,3535,5,5,1,5,5,4,4,5,5,5,5,3,5,3,5,0.0,satisfied +23324,78837,Female,Loyal Customer,22,Personal Travel,Eco,554,4,5,4,4,5,4,5,5,1,5,4,4,2,5,15,16.0,neutral or dissatisfied +23325,22678,Male,Loyal Customer,42,Business travel,Business,3087,1,1,1,1,1,3,4,4,4,4,4,5,4,5,0,0.0,satisfied +23326,11126,Male,Loyal Customer,24,Personal Travel,Eco,247,4,5,0,2,4,0,4,4,5,4,5,4,4,4,13,11.0,neutral or dissatisfied +23327,29630,Female,Loyal Customer,36,Business travel,Business,3705,3,3,3,3,3,1,2,3,3,3,3,1,3,3,0,0.0,satisfied +23328,115291,Male,disloyal Customer,41,Business travel,Business,337,5,4,4,2,4,5,4,4,4,3,4,4,5,4,0,0.0,satisfied +23329,17420,Male,Loyal Customer,39,Business travel,Business,1807,3,2,2,2,1,2,3,3,3,3,3,1,3,1,7,0.0,neutral or dissatisfied +23330,125682,Male,Loyal Customer,41,Business travel,Eco,759,3,3,3,3,3,3,3,3,1,1,4,4,4,3,0,0.0,neutral or dissatisfied +23331,44259,Male,Loyal Customer,26,Personal Travel,Eco,222,1,3,1,2,1,1,1,1,1,3,1,5,1,1,0,0.0,neutral or dissatisfied +23332,57078,Male,disloyal Customer,25,Business travel,Business,1222,4,0,4,1,5,4,5,5,5,2,4,3,4,5,24,4.0,satisfied +23333,25003,Female,Loyal Customer,55,Personal Travel,Eco,484,3,0,3,4,5,4,5,5,5,3,5,4,5,3,0,0.0,neutral or dissatisfied +23334,32917,Male,Loyal Customer,12,Personal Travel,Eco,201,1,4,1,3,1,1,1,1,5,4,2,3,2,1,0,0.0,neutral or dissatisfied +23335,123511,Male,Loyal Customer,16,Personal Travel,Eco,2125,4,3,4,4,2,4,2,2,4,5,5,1,5,2,0,0.0,satisfied +23336,53648,Female,Loyal Customer,53,Business travel,Eco Plus,1874,5,4,4,4,1,4,5,5,5,5,5,4,5,2,24,13.0,satisfied +23337,10209,Male,Loyal Customer,52,Business travel,Business,2909,2,4,4,4,2,3,3,2,2,1,2,4,2,1,0,6.0,neutral or dissatisfied +23338,97349,Female,disloyal Customer,25,Business travel,Eco,472,5,1,5,4,4,5,4,4,3,2,5,3,2,4,0,0.0,satisfied +23339,108995,Female,Loyal Customer,58,Business travel,Business,1942,3,3,3,3,3,5,4,5,5,5,5,5,5,3,46,51.0,satisfied +23340,101926,Female,Loyal Customer,58,Business travel,Business,628,3,3,3,3,2,4,5,4,4,4,4,3,4,4,77,57.0,satisfied +23341,62094,Female,disloyal Customer,27,Business travel,Business,2565,1,2,2,1,4,2,2,4,3,4,5,5,4,4,22,15.0,neutral or dissatisfied +23342,20100,Female,disloyal Customer,20,Business travel,Eco,466,5,0,5,5,5,5,5,5,5,3,1,2,1,5,51,37.0,satisfied +23343,88501,Male,disloyal Customer,25,Business travel,Eco,240,2,3,2,3,3,2,3,3,4,3,3,4,3,3,51,47.0,neutral or dissatisfied +23344,62157,Female,Loyal Customer,52,Business travel,Business,2454,1,1,1,1,3,3,4,5,5,5,5,3,5,3,13,0.0,satisfied +23345,122148,Male,Loyal Customer,39,Business travel,Business,3049,1,1,1,1,3,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +23346,64798,Male,disloyal Customer,26,Business travel,Eco,190,3,2,3,3,1,3,1,1,2,2,4,1,3,1,0,0.0,neutral or dissatisfied +23347,33324,Male,Loyal Customer,19,Business travel,Business,2462,4,4,4,4,4,4,4,4,1,4,5,2,3,4,0,0.0,satisfied +23348,116386,Female,Loyal Customer,20,Personal Travel,Eco,371,1,3,1,3,1,1,1,1,4,1,3,3,4,1,0,0.0,neutral or dissatisfied +23349,23545,Male,Loyal Customer,48,Business travel,Business,455,5,5,5,5,2,5,4,5,5,5,5,4,5,3,2,0.0,satisfied +23350,46391,Female,Loyal Customer,31,Personal Travel,Eco,1013,3,2,3,4,3,3,3,3,3,1,3,3,3,3,0,0.0,neutral or dissatisfied +23351,66184,Female,Loyal Customer,40,Business travel,Business,2917,5,5,5,5,5,5,5,5,5,5,5,3,5,4,24,26.0,satisfied +23352,7042,Female,Loyal Customer,44,Business travel,Eco Plus,299,3,3,5,5,1,3,3,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +23353,88788,Female,disloyal Customer,26,Business travel,Eco Plus,594,3,4,3,3,1,3,1,1,2,5,4,3,3,1,4,0.0,neutral or dissatisfied +23354,73150,Male,Loyal Customer,8,Personal Travel,Eco Plus,1068,2,5,1,2,1,1,1,1,3,4,1,4,3,1,0,0.0,neutral or dissatisfied +23355,60986,Male,Loyal Customer,34,Business travel,Business,1805,3,3,3,3,5,5,4,4,4,4,4,3,4,3,3,0.0,satisfied +23356,44057,Female,disloyal Customer,28,Business travel,Eco Plus,296,4,4,4,4,5,4,5,5,5,4,2,2,3,5,0,0.0,neutral or dissatisfied +23357,56865,Male,Loyal Customer,26,Business travel,Business,2434,2,2,3,2,5,5,5,5,3,5,3,5,4,5,0,0.0,satisfied +23358,89998,Male,Loyal Customer,39,Business travel,Business,2367,1,1,1,1,3,5,5,5,5,5,5,3,5,5,0,11.0,satisfied +23359,73329,Female,Loyal Customer,51,Business travel,Business,1197,5,5,5,5,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +23360,56476,Male,Loyal Customer,60,Business travel,Business,4963,2,5,2,2,3,3,3,5,3,4,4,3,3,3,5,13.0,satisfied +23361,68414,Male,disloyal Customer,26,Business travel,Eco,645,1,5,2,3,1,2,1,1,2,1,5,1,2,1,0,3.0,neutral or dissatisfied +23362,87213,Male,Loyal Customer,66,Personal Travel,Eco,946,2,1,2,4,3,2,3,3,2,5,2,4,3,3,0,0.0,neutral or dissatisfied +23363,103585,Female,Loyal Customer,70,Business travel,Eco,451,1,5,5,5,3,4,4,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +23364,30634,Male,Loyal Customer,48,Business travel,Business,3158,3,4,4,4,1,3,4,3,3,3,3,4,3,4,1,0.0,neutral or dissatisfied +23365,128735,Male,Loyal Customer,42,Business travel,Eco Plus,1104,2,4,4,4,2,2,2,2,1,1,1,3,1,2,3,6.0,neutral or dissatisfied +23366,53020,Male,disloyal Customer,44,Business travel,Eco,1208,2,2,2,4,1,2,1,1,2,1,3,4,4,1,85,55.0,neutral or dissatisfied +23367,116138,Male,Loyal Customer,15,Personal Travel,Eco,342,4,5,4,3,1,4,2,1,4,3,4,2,3,1,0,0.0,satisfied +23368,13213,Female,disloyal Customer,24,Business travel,Eco,657,0,2,0,2,3,0,3,3,1,5,5,4,2,3,74,82.0,satisfied +23369,117197,Female,Loyal Customer,23,Personal Travel,Eco,647,4,5,4,4,5,4,5,5,1,2,3,4,1,5,4,0.0,neutral or dissatisfied +23370,33004,Female,Loyal Customer,42,Personal Travel,Eco,163,2,5,2,4,5,4,5,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +23371,63548,Male,Loyal Customer,69,Personal Travel,Eco,1009,1,4,1,1,1,1,1,1,5,5,4,5,5,1,0,0.0,neutral or dissatisfied +23372,84321,Female,Loyal Customer,44,Business travel,Business,606,4,4,4,4,3,3,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +23373,43902,Female,Loyal Customer,40,Personal Travel,Eco,174,0,4,0,2,3,0,3,3,3,2,4,3,5,3,0,0.0,satisfied +23374,126292,Male,Loyal Customer,14,Personal Travel,Eco,507,4,5,4,2,4,4,4,4,5,5,5,5,5,4,0,0.0,neutral or dissatisfied +23375,70953,Female,disloyal Customer,24,Business travel,Business,612,5,0,5,2,4,5,5,4,5,5,5,4,4,4,0,0.0,satisfied +23376,59962,Female,disloyal Customer,26,Business travel,Business,1065,4,0,4,4,5,4,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +23377,40068,Female,Loyal Customer,60,Business travel,Eco,493,5,5,5,5,5,2,1,5,5,5,5,4,5,3,0,0.0,satisfied +23378,23661,Male,Loyal Customer,36,Business travel,Eco,196,4,2,2,2,4,4,4,4,2,2,3,2,4,4,52,55.0,satisfied +23379,113190,Male,Loyal Customer,44,Business travel,Business,3661,4,4,4,4,2,5,5,4,4,4,4,5,4,5,2,0.0,satisfied +23380,12535,Female,disloyal Customer,24,Business travel,Eco,788,2,2,2,3,1,2,1,1,3,5,4,2,3,1,2,0.0,neutral or dissatisfied +23381,82584,Male,disloyal Customer,27,Business travel,Business,408,1,1,1,2,1,1,1,1,5,4,4,3,5,1,0,0.0,neutral or dissatisfied +23382,91534,Female,Loyal Customer,55,Business travel,Business,680,1,1,1,1,3,5,5,4,4,4,4,5,4,4,31,23.0,satisfied +23383,13911,Female,disloyal Customer,27,Business travel,Eco,317,2,4,3,1,1,3,1,1,1,4,1,4,5,1,0,0.0,neutral or dissatisfied +23384,40967,Female,Loyal Customer,28,Business travel,Business,1829,2,5,5,5,2,2,2,2,2,4,4,1,4,2,0,0.0,neutral or dissatisfied +23385,70704,Male,Loyal Customer,36,Business travel,Business,675,3,3,3,3,3,4,5,4,4,5,4,4,4,5,0,0.0,satisfied +23386,64463,Male,Loyal Customer,15,Business travel,Eco Plus,989,2,4,4,4,2,2,1,2,1,3,3,1,4,2,0,0.0,neutral or dissatisfied +23387,69923,Female,Loyal Customer,62,Personal Travel,Eco,1514,1,4,1,3,4,2,3,4,4,1,3,1,4,4,1,6.0,neutral or dissatisfied +23388,31302,Female,Loyal Customer,23,Business travel,Business,680,3,3,3,3,5,4,5,5,4,4,4,4,3,5,6,2.0,satisfied +23389,31363,Female,disloyal Customer,17,Business travel,Eco,589,3,2,3,3,3,3,3,3,4,2,4,3,3,3,0,0.0,neutral or dissatisfied +23390,33291,Female,Loyal Customer,27,Personal Travel,Eco Plus,102,5,4,5,1,3,5,3,3,2,5,2,5,1,3,0,0.0,satisfied +23391,126160,Female,Loyal Customer,39,Business travel,Eco,507,3,2,2,2,3,3,3,3,4,3,4,3,3,3,6,6.0,neutral or dissatisfied +23392,90555,Female,Loyal Customer,48,Business travel,Business,1726,4,4,4,4,4,5,5,5,5,5,4,5,5,3,0,0.0,satisfied +23393,43380,Male,Loyal Customer,17,Personal Travel,Eco,387,4,3,2,4,2,2,2,2,4,1,3,1,3,2,0,0.0,neutral or dissatisfied +23394,20130,Male,Loyal Customer,49,Personal Travel,Eco,416,4,4,5,1,2,5,2,2,3,4,2,3,4,2,13,5.0,neutral or dissatisfied +23395,97294,Male,disloyal Customer,32,Business travel,Business,872,2,2,2,4,3,2,3,3,5,2,5,3,5,3,9,16.0,neutral or dissatisfied +23396,117517,Male,Loyal Customer,39,Personal Travel,Eco Plus,507,1,4,1,3,3,1,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +23397,67898,Male,Loyal Customer,16,Personal Travel,Eco,1235,2,4,1,1,3,1,3,3,4,5,3,1,3,3,0,0.0,neutral or dissatisfied +23398,2683,Male,Loyal Customer,21,Personal Travel,Eco,539,2,5,2,2,4,2,4,4,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +23399,20345,Male,Loyal Customer,76,Business travel,Eco,265,5,4,4,4,5,5,5,5,4,5,4,5,1,5,0,0.0,satisfied +23400,29934,Female,Loyal Customer,43,Business travel,Business,3998,3,2,2,2,2,4,4,3,3,3,3,3,3,3,121,108.0,neutral or dissatisfied +23401,38032,Female,Loyal Customer,23,Business travel,Eco,1185,4,1,1,1,4,4,3,4,4,1,5,5,3,4,0,0.0,satisfied +23402,56902,Male,disloyal Customer,27,Business travel,Business,2454,2,2,2,2,2,3,3,4,4,4,4,3,5,3,0,0.0,neutral or dissatisfied +23403,18195,Female,Loyal Customer,34,Business travel,Eco,228,4,4,5,4,4,4,4,4,5,5,4,4,3,4,0,0.0,satisfied +23404,80612,Male,Loyal Customer,41,Business travel,Business,236,0,0,0,1,3,5,4,3,3,3,1,4,3,3,0,0.0,satisfied +23405,113903,Female,Loyal Customer,25,Business travel,Business,2295,4,4,4,4,4,4,4,4,5,3,4,3,4,4,5,2.0,satisfied +23406,124648,Female,Loyal Customer,45,Business travel,Business,3194,5,5,2,5,2,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +23407,58383,Male,Loyal Customer,53,Business travel,Business,473,2,2,2,2,5,5,5,3,5,4,5,5,3,5,248,252.0,satisfied +23408,41786,Male,Loyal Customer,41,Business travel,Business,2926,4,4,4,4,4,4,4,4,4,4,4,4,4,3,29,44.0,satisfied +23409,71272,Male,Loyal Customer,22,Personal Travel,Eco,733,5,1,5,4,4,5,5,4,2,2,3,1,4,4,1,0.0,satisfied +23410,41291,Male,Loyal Customer,22,Personal Travel,Eco Plus,542,3,5,3,3,4,3,4,4,3,3,5,1,5,4,0,0.0,neutral or dissatisfied +23411,47763,Male,Loyal Customer,43,Business travel,Business,2294,3,3,3,3,1,4,3,4,4,4,4,5,4,2,0,0.0,satisfied +23412,43469,Male,disloyal Customer,29,Business travel,Eco,679,1,1,1,4,2,1,2,2,4,3,3,2,3,2,0,0.0,neutral or dissatisfied +23413,115476,Male,disloyal Customer,27,Business travel,Business,404,2,2,2,2,1,2,1,1,4,3,5,3,4,1,0,0.0,neutral or dissatisfied +23414,61545,Female,Loyal Customer,12,Personal Travel,Eco,2358,2,4,2,1,3,2,5,3,1,4,4,4,3,3,0,0.0,neutral or dissatisfied +23415,14502,Male,Loyal Customer,30,Business travel,Business,2013,2,5,5,5,2,2,2,2,3,4,4,2,3,2,1,0.0,neutral or dissatisfied +23416,54570,Female,Loyal Customer,33,Business travel,Eco Plus,925,4,5,5,5,4,4,4,4,5,5,3,5,4,4,0,0.0,satisfied +23417,22996,Female,Loyal Customer,45,Personal Travel,Eco,489,3,5,3,1,2,3,4,5,5,3,2,2,5,3,0,0.0,neutral or dissatisfied +23418,3881,Male,Loyal Customer,57,Business travel,Business,290,0,0,0,4,4,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +23419,21587,Female,Loyal Customer,33,Business travel,Business,780,5,5,5,5,3,5,5,5,5,5,5,2,5,2,0,0.0,satisfied +23420,99538,Male,disloyal Customer,25,Business travel,Business,802,1,4,1,2,1,1,1,1,4,5,5,4,5,1,0,0.0,neutral or dissatisfied +23421,110420,Female,Loyal Customer,50,Business travel,Eco,787,4,4,4,4,1,4,1,4,4,4,4,1,4,2,1,0.0,satisfied +23422,32549,Male,disloyal Customer,22,Business travel,Eco,163,3,5,3,4,5,3,5,5,5,5,4,1,2,5,0,5.0,neutral or dissatisfied +23423,120228,Male,disloyal Customer,38,Business travel,Eco,903,2,2,2,3,1,2,1,1,1,1,3,4,3,1,0,12.0,neutral or dissatisfied +23424,38776,Male,Loyal Customer,41,Business travel,Eco,353,5,5,5,5,5,5,5,5,1,4,4,4,1,5,0,0.0,satisfied +23425,44990,Male,Loyal Customer,29,Business travel,Business,3512,5,5,5,5,4,4,4,4,3,2,3,3,1,4,16,13.0,satisfied +23426,79665,Male,Loyal Customer,20,Personal Travel,Eco,712,3,3,3,2,5,3,4,5,5,2,1,4,5,5,0,0.0,neutral or dissatisfied +23427,13119,Male,Loyal Customer,36,Business travel,Business,562,3,3,3,3,3,4,5,5,5,5,5,5,5,2,0,0.0,satisfied +23428,39240,Male,Loyal Customer,55,Business travel,Business,67,4,4,4,4,4,2,2,4,4,4,3,5,4,1,0,0.0,satisfied +23429,68597,Male,Loyal Customer,39,Business travel,Business,1739,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +23430,74282,Female,Loyal Customer,22,Business travel,Business,2311,5,5,5,5,4,4,4,4,4,2,3,3,5,4,0,0.0,satisfied +23431,63166,Male,Loyal Customer,43,Business travel,Business,447,1,1,1,1,5,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +23432,114252,Male,Loyal Customer,39,Business travel,Business,3010,2,2,2,2,4,5,2,4,4,4,4,4,4,3,20,24.0,satisfied +23433,65699,Female,Loyal Customer,21,Business travel,Business,936,5,5,4,5,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +23434,116842,Female,Loyal Customer,10,Personal Travel,Business,325,1,3,1,3,3,1,3,3,4,4,4,4,3,3,0,0.0,neutral or dissatisfied +23435,114172,Male,disloyal Customer,23,Business travel,Business,862,4,5,5,3,3,5,4,3,3,2,5,5,5,3,107,92.0,satisfied +23436,40856,Male,Loyal Customer,41,Personal Travel,Eco,558,2,4,2,4,4,2,1,4,4,3,4,3,5,4,0,0.0,neutral or dissatisfied +23437,94748,Male,Loyal Customer,57,Business travel,Business,239,1,5,5,5,1,3,4,1,1,1,1,2,1,1,14,22.0,neutral or dissatisfied +23438,5187,Female,Loyal Customer,46,Business travel,Business,3052,3,3,3,3,5,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +23439,31943,Male,Loyal Customer,57,Business travel,Business,163,0,5,0,2,5,4,5,2,2,2,2,3,2,3,0,0.0,satisfied +23440,94817,Female,Loyal Customer,22,Business travel,Business,3889,1,1,1,1,2,2,2,2,5,4,5,4,5,2,0,0.0,satisfied +23441,11761,Male,Loyal Customer,36,Business travel,Eco,429,3,3,3,3,3,3,3,3,4,3,4,1,3,3,3,5.0,neutral or dissatisfied +23442,97538,Female,Loyal Customer,30,Business travel,Business,675,2,2,3,2,4,5,4,4,4,4,5,5,4,4,0,0.0,satisfied +23443,59400,Female,Loyal Customer,21,Personal Travel,Eco,2367,3,2,3,4,2,3,2,2,3,4,3,3,4,2,0,0.0,neutral or dissatisfied +23444,124212,Male,Loyal Customer,7,Personal Travel,Eco,2176,1,4,0,4,5,0,5,5,5,3,5,4,4,5,71,38.0,neutral or dissatisfied +23445,126837,Female,Loyal Customer,43,Business travel,Business,2125,4,4,4,4,5,3,5,4,4,4,4,4,4,4,0,0.0,satisfied +23446,30372,Male,Loyal Customer,25,Business travel,Business,641,2,2,2,2,5,4,5,5,2,3,1,3,2,5,16,10.0,satisfied +23447,62824,Male,Loyal Customer,28,Personal Travel,Eco,2556,4,2,3,2,3,4,4,4,2,1,3,4,1,4,3,0.0,neutral or dissatisfied +23448,5691,Male,Loyal Customer,35,Business travel,Eco,196,1,1,1,1,1,1,1,1,2,2,3,3,3,1,0,0.0,neutral or dissatisfied +23449,83124,Female,Loyal Customer,64,Personal Travel,Eco,1084,2,4,2,3,4,5,5,3,3,2,3,5,3,5,0,0.0,neutral or dissatisfied +23450,24489,Female,Loyal Customer,67,Business travel,Business,2709,3,3,3,3,4,1,3,5,5,5,3,4,5,1,0,0.0,satisfied +23451,56640,Female,disloyal Customer,30,Business travel,Business,937,0,0,0,4,3,0,3,3,5,5,4,5,5,3,0,0.0,satisfied +23452,122555,Male,Loyal Customer,16,Personal Travel,Eco,500,2,4,5,2,5,5,5,5,4,3,5,3,5,5,0,0.0,neutral or dissatisfied +23453,70255,Female,Loyal Customer,85,Business travel,Business,992,4,4,4,4,5,5,5,2,4,4,4,5,2,5,0,5.0,satisfied +23454,38539,Female,Loyal Customer,41,Business travel,Eco,2586,1,2,2,2,1,1,1,1,4,4,2,3,3,1,0,28.0,neutral or dissatisfied +23455,89814,Female,Loyal Customer,47,Business travel,Business,1981,1,1,1,1,2,4,4,2,2,2,2,5,2,4,12,11.0,satisfied +23456,108595,Female,Loyal Customer,44,Business travel,Business,696,1,1,2,1,2,4,5,4,4,5,4,4,4,5,2,0.0,satisfied +23457,50669,Male,Loyal Customer,46,Personal Travel,Eco,89,3,4,3,2,2,3,3,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +23458,39853,Female,disloyal Customer,24,Business travel,Eco,272,2,2,2,3,5,2,1,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +23459,75680,Male,disloyal Customer,25,Business travel,Business,868,4,1,5,4,4,5,4,4,2,4,4,4,3,4,8,19.0,neutral or dissatisfied +23460,103294,Female,Loyal Customer,55,Personal Travel,Eco,872,3,2,3,3,3,3,4,3,3,3,3,1,3,2,13,6.0,neutral or dissatisfied +23461,45389,Male,Loyal Customer,34,Business travel,Eco Plus,150,0,0,0,1,4,0,4,4,4,3,5,2,5,4,0,0.0,satisfied +23462,44812,Male,Loyal Customer,17,Business travel,Eco,1041,2,5,5,5,2,1,2,4,2,4,3,2,1,2,239,240.0,neutral or dissatisfied +23463,51720,Male,Loyal Customer,66,Personal Travel,Eco,451,1,5,1,4,4,1,3,4,1,1,3,1,2,4,13,21.0,neutral or dissatisfied +23464,63672,Female,Loyal Customer,11,Business travel,Business,2018,3,3,4,3,4,4,4,4,4,2,3,5,4,4,85,43.0,satisfied +23465,36167,Male,Loyal Customer,53,Business travel,Eco,1674,3,1,1,1,3,3,3,3,1,1,2,4,2,3,7,0.0,neutral or dissatisfied +23466,59251,Male,Loyal Customer,49,Business travel,Business,2301,2,2,2,2,2,2,2,1,3,3,3,2,1,2,31,17.0,neutral or dissatisfied +23467,118360,Male,Loyal Customer,49,Personal Travel,Eco,639,2,5,2,1,5,2,5,5,5,3,1,2,4,5,20,5.0,neutral or dissatisfied +23468,115187,Female,Loyal Customer,25,Business travel,Business,2386,5,5,5,5,5,5,5,5,4,3,5,3,4,5,13,4.0,satisfied +23469,45965,Male,Loyal Customer,25,Business travel,Business,872,3,3,3,3,4,4,4,4,4,3,5,5,4,4,2,5.0,satisfied +23470,11112,Female,Loyal Customer,65,Personal Travel,Eco,216,0,0,0,2,2,4,2,3,3,0,3,5,3,2,0,0.0,satisfied +23471,43759,Male,Loyal Customer,30,Business travel,Business,546,5,1,5,5,5,4,5,5,3,3,2,4,1,5,0,0.0,satisfied +23472,67239,Male,Loyal Customer,13,Personal Travel,Eco,1121,4,4,4,5,4,4,4,4,5,4,4,3,5,4,8,15.0,neutral or dissatisfied +23473,129115,Female,Loyal Customer,36,Personal Travel,Eco Plus,2583,1,1,1,3,1,5,5,2,4,2,4,5,1,5,0,0.0,neutral or dissatisfied +23474,72883,Male,Loyal Customer,46,Business travel,Business,1096,5,5,5,5,3,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +23475,98558,Male,disloyal Customer,27,Business travel,Business,992,2,2,2,4,3,2,3,3,3,2,4,3,3,3,0,0.0,neutral or dissatisfied +23476,95265,Female,Loyal Customer,45,Personal Travel,Eco,239,1,5,1,4,5,5,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +23477,11787,Male,Loyal Customer,59,Personal Travel,Eco,429,1,4,1,4,1,1,1,1,5,4,4,4,4,1,53,42.0,neutral or dissatisfied +23478,7846,Female,Loyal Customer,44,Business travel,Business,3830,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,0.0,satisfied +23479,81405,Female,disloyal Customer,19,Business travel,Eco,393,1,4,1,1,4,1,4,4,5,3,5,4,4,4,0,0.0,neutral or dissatisfied +23480,2596,Female,Loyal Customer,14,Personal Travel,Eco,280,3,5,3,3,3,3,3,3,4,5,5,3,5,3,0,0.0,neutral or dissatisfied +23481,32558,Male,disloyal Customer,37,Business travel,Eco,101,2,4,2,3,5,2,5,5,2,4,3,3,4,5,0,4.0,neutral or dissatisfied +23482,9596,Female,Loyal Customer,14,Personal Travel,Eco,283,5,3,5,4,2,5,2,2,4,1,4,3,4,2,13,39.0,satisfied +23483,52876,Male,disloyal Customer,9,Business travel,Eco,1024,3,3,3,4,1,3,1,1,4,4,4,1,3,1,0,0.0,neutral or dissatisfied +23484,76433,Female,Loyal Customer,48,Personal Travel,Eco,405,2,5,2,2,5,5,5,4,4,2,4,4,4,4,19,12.0,neutral or dissatisfied +23485,72832,Male,Loyal Customer,36,Business travel,Business,1013,2,3,3,3,5,3,3,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +23486,83196,Male,Loyal Customer,39,Business travel,Business,2711,5,5,5,5,5,4,5,5,5,5,5,4,5,4,5,65.0,satisfied +23487,30009,Male,Loyal Customer,49,Business travel,Business,3029,5,5,5,5,1,4,3,5,5,5,5,1,5,3,0,0.0,satisfied +23488,49895,Male,Loyal Customer,58,Business travel,Business,308,3,3,4,3,3,3,4,5,5,5,5,4,5,3,1,4.0,satisfied +23489,129728,Male,Loyal Customer,18,Business travel,Business,1516,4,4,4,4,5,5,5,5,4,5,5,3,5,5,0,0.0,satisfied +23490,81233,Female,Loyal Customer,33,Personal Travel,Eco,223,3,1,3,2,5,3,5,5,2,4,3,2,2,5,0,0.0,neutral or dissatisfied +23491,22453,Female,Loyal Customer,8,Personal Travel,Eco,83,2,5,2,3,1,2,1,1,5,4,3,3,2,1,0,0.0,neutral or dissatisfied +23492,52428,Male,Loyal Customer,52,Personal Travel,Eco,369,2,3,2,4,2,2,2,2,4,2,1,5,4,2,0,0.0,neutral or dissatisfied +23493,77131,Male,Loyal Customer,59,Personal Travel,Eco Plus,1481,3,4,3,2,1,3,4,1,3,3,4,5,5,1,31,25.0,neutral or dissatisfied +23494,66928,Male,Loyal Customer,48,Business travel,Business,3018,5,5,5,5,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +23495,110663,Male,Loyal Customer,32,Business travel,Business,829,2,2,3,2,2,2,2,2,3,2,4,1,4,2,54,49.0,neutral or dissatisfied +23496,100068,Male,Loyal Customer,67,Personal Travel,Eco,281,2,2,2,3,3,2,3,3,4,1,3,3,3,3,0,0.0,neutral or dissatisfied +23497,111542,Female,Loyal Customer,34,Business travel,Business,1734,1,1,1,1,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +23498,118460,Female,Loyal Customer,45,Business travel,Business,304,2,2,2,2,2,5,4,3,3,4,3,5,3,4,15,3.0,satisfied +23499,57161,Female,Loyal Customer,23,Business travel,Business,1824,1,1,1,1,2,2,2,2,5,3,5,5,4,2,0,0.0,satisfied +23500,23480,Female,Loyal Customer,32,Personal Travel,Eco,576,2,4,2,3,4,2,4,4,5,3,4,5,4,4,46,34.0,neutral or dissatisfied +23501,32401,Female,disloyal Customer,24,Business travel,Eco,101,3,3,3,4,3,3,3,3,4,4,3,1,3,3,0,0.0,neutral or dissatisfied +23502,20646,Female,Loyal Customer,59,Business travel,Business,552,4,4,2,4,5,4,4,4,4,4,4,5,4,4,7,22.0,satisfied +23503,11675,Male,Loyal Customer,56,Business travel,Business,429,5,5,5,5,3,5,5,4,4,4,4,4,4,3,36,42.0,satisfied +23504,52180,Male,disloyal Customer,34,Business travel,Eco,370,2,0,2,2,4,2,4,4,3,5,3,4,2,4,0,3.0,neutral or dissatisfied +23505,4815,Female,disloyal Customer,20,Business travel,Business,500,5,0,5,4,2,5,2,2,5,2,5,4,4,2,0,10.0,satisfied +23506,106285,Male,Loyal Customer,56,Personal Travel,Eco,604,1,4,1,3,4,1,4,4,4,5,5,5,4,4,25,40.0,neutral or dissatisfied +23507,29645,Female,Loyal Customer,19,Personal Travel,Eco,1448,3,5,3,2,2,3,2,2,2,3,3,3,1,2,14,17.0,neutral or dissatisfied +23508,102010,Female,disloyal Customer,65,Business travel,Business,414,4,4,4,5,1,4,1,1,4,5,4,4,5,1,24,27.0,neutral or dissatisfied +23509,6740,Female,Loyal Customer,27,Business travel,Business,235,4,4,4,4,4,4,4,4,4,3,5,4,5,4,0,0.0,satisfied +23510,51349,Male,Loyal Customer,41,Business travel,Eco Plus,109,1,2,2,2,1,1,1,1,3,1,4,3,3,1,1,0.0,neutral or dissatisfied +23511,3971,Female,Loyal Customer,28,Business travel,Business,1763,4,4,4,4,3,3,3,3,4,4,5,4,5,3,0,20.0,satisfied +23512,37347,Female,Loyal Customer,30,Business travel,Business,1074,3,3,4,3,3,4,3,3,3,3,5,4,1,3,6,1.0,satisfied +23513,108714,Male,Loyal Customer,61,Business travel,Business,321,3,3,4,3,2,5,5,5,5,5,5,5,5,5,13,19.0,satisfied +23514,124432,Female,Loyal Customer,29,Personal Travel,Eco,1262,2,5,2,3,4,2,4,4,3,3,4,4,4,4,0,34.0,neutral or dissatisfied +23515,47985,Male,Loyal Customer,47,Personal Travel,Eco,817,4,1,4,4,2,4,4,2,4,5,4,3,4,2,0,0.0,neutral or dissatisfied +23516,114008,Male,Loyal Customer,34,Personal Travel,Eco,1750,5,4,5,3,5,5,5,5,4,2,3,1,3,5,2,0.0,satisfied +23517,101696,Male,Loyal Customer,25,Personal Travel,Eco,1500,1,1,1,2,4,1,4,4,1,5,3,3,3,4,0,0.0,neutral or dissatisfied +23518,96214,Male,disloyal Customer,22,Business travel,Business,460,0,0,0,2,4,0,4,4,4,5,5,5,5,4,0,0.0,satisfied +23519,14892,Male,Loyal Customer,77,Business travel,Business,1798,4,1,1,1,3,3,4,4,4,3,4,2,4,2,0,0.0,neutral or dissatisfied +23520,104532,Male,Loyal Customer,56,Business travel,Business,1256,1,1,1,1,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +23521,54928,Male,Loyal Customer,31,Business travel,Business,1379,1,1,1,1,4,4,4,4,4,5,5,3,4,4,0,0.0,satisfied +23522,104264,Male,Loyal Customer,40,Business travel,Business,456,5,5,5,5,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +23523,25501,Female,Loyal Customer,39,Business travel,Business,2328,4,4,5,4,4,3,4,4,4,4,4,3,4,1,10,10.0,neutral or dissatisfied +23524,112960,Male,Loyal Customer,34,Personal Travel,Eco,1390,1,5,1,3,5,1,5,5,1,5,5,5,5,5,14,0.0,neutral or dissatisfied +23525,13271,Male,Loyal Customer,8,Personal Travel,Eco,468,3,3,3,2,3,2,4,1,1,3,3,4,2,4,151,137.0,neutral or dissatisfied +23526,39863,Male,Loyal Customer,16,Business travel,Business,1710,3,5,3,3,3,3,3,3,3,1,4,2,3,3,0,0.0,neutral or dissatisfied +23527,72532,Female,Loyal Customer,56,Business travel,Business,3993,1,1,1,1,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23528,37976,Male,Loyal Customer,47,Business travel,Business,2161,2,3,3,3,5,2,3,2,2,2,2,4,2,4,30,11.0,neutral or dissatisfied +23529,52733,Female,Loyal Customer,38,Business travel,Eco,2306,1,0,0,4,4,0,4,4,1,2,2,1,4,4,0,0.0,neutral or dissatisfied +23530,17596,Male,Loyal Customer,67,Business travel,Eco,695,2,5,5,5,2,2,2,2,3,1,2,4,3,2,42,17.0,neutral or dissatisfied +23531,67388,Male,disloyal Customer,20,Business travel,Business,769,5,4,5,5,5,5,5,5,3,5,5,5,5,5,21,12.0,satisfied +23532,79746,Male,Loyal Customer,30,Business travel,Eco Plus,762,2,1,1,1,2,2,2,2,3,5,4,1,3,2,11,0.0,neutral or dissatisfied +23533,38127,Male,Loyal Customer,41,Business travel,Business,3108,1,1,1,1,1,4,4,5,5,4,5,1,5,5,0,0.0,satisfied +23534,82119,Female,disloyal Customer,22,Business travel,Eco Plus,1276,2,1,2,3,1,2,1,1,4,5,4,2,4,1,0,0.0,neutral or dissatisfied +23535,109589,Female,Loyal Customer,52,Business travel,Business,992,1,1,1,1,3,4,4,4,4,4,4,4,4,5,18,0.0,satisfied +23536,125471,Female,Loyal Customer,15,Personal Travel,Eco,2845,1,5,2,4,2,2,2,2,4,2,3,5,5,2,0,0.0,neutral or dissatisfied +23537,49142,Male,Loyal Customer,39,Business travel,Business,1909,5,5,5,5,4,2,5,5,5,5,5,4,5,3,0,0.0,satisfied +23538,90799,Male,Loyal Customer,38,Business travel,Business,3248,1,1,3,1,2,4,5,4,4,5,4,3,4,5,0,0.0,satisfied +23539,199,Female,Loyal Customer,60,Business travel,Business,3756,4,4,4,4,2,4,5,4,4,4,4,5,4,5,36,24.0,satisfied +23540,110058,Female,Loyal Customer,17,Personal Travel,Eco,2173,3,1,3,2,3,5,2,1,3,1,3,2,2,2,139,142.0,neutral or dissatisfied +23541,108019,Male,Loyal Customer,28,Business travel,Business,589,5,5,5,5,4,4,4,4,4,4,4,4,4,4,41,29.0,satisfied +23542,34130,Female,Loyal Customer,26,Business travel,Business,1583,4,4,1,4,4,4,4,4,3,1,4,4,5,4,9,0.0,satisfied +23543,42278,Male,Loyal Customer,45,Business travel,Business,1883,2,3,3,3,5,4,4,2,2,2,2,4,2,2,86,63.0,neutral or dissatisfied +23544,94250,Female,Loyal Customer,48,Business travel,Business,248,5,5,5,5,5,5,4,5,5,5,5,4,5,5,8,9.0,satisfied +23545,478,Female,Loyal Customer,43,Business travel,Business,89,4,4,1,4,3,5,4,4,4,4,5,4,4,5,0,0.0,satisfied +23546,52972,Male,Loyal Customer,61,Personal Travel,Eco,2306,1,4,1,1,1,5,5,5,4,4,5,5,5,5,194,185.0,neutral or dissatisfied +23547,108131,Female,Loyal Customer,42,Business travel,Business,2575,1,1,1,1,5,4,5,5,5,5,5,5,5,5,12,0.0,satisfied +23548,80561,Male,Loyal Customer,55,Business travel,Business,1747,4,2,4,4,2,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +23549,68987,Male,Loyal Customer,66,Personal Travel,Eco,2239,5,2,5,3,1,5,1,1,4,3,3,2,3,1,0,0.0,satisfied +23550,7766,Female,disloyal Customer,22,Business travel,Eco,1080,2,2,2,1,2,2,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +23551,115683,Male,Loyal Customer,23,Business travel,Eco,337,3,2,2,2,3,3,3,3,3,4,3,1,2,3,17,11.0,neutral or dissatisfied +23552,116071,Female,Loyal Customer,57,Personal Travel,Eco,325,4,5,4,3,3,5,2,1,1,4,1,2,1,3,4,0.0,neutral or dissatisfied +23553,76689,Male,Loyal Customer,61,Personal Travel,Eco,516,2,2,2,4,4,2,2,4,2,1,4,2,3,4,1,0.0,neutral or dissatisfied +23554,69821,Male,disloyal Customer,42,Business travel,Business,1055,3,3,3,3,5,3,5,5,3,4,4,5,5,5,0,3.0,neutral or dissatisfied +23555,89290,Male,Loyal Customer,55,Business travel,Business,2810,2,4,4,4,5,2,3,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +23556,84585,Male,disloyal Customer,28,Business travel,Business,669,1,1,1,3,4,1,4,4,4,5,4,4,3,4,2,0.0,neutral or dissatisfied +23557,5476,Male,Loyal Customer,10,Personal Travel,Eco,265,1,5,0,3,2,0,5,2,2,4,4,2,3,2,0,0.0,neutral or dissatisfied +23558,23645,Female,Loyal Customer,44,Business travel,Business,2221,1,1,1,1,4,4,5,4,4,4,5,4,4,5,0,0.0,satisfied +23559,121858,Male,disloyal Customer,58,Business travel,Business,366,1,1,1,4,5,1,5,5,2,3,4,1,3,5,0,0.0,neutral or dissatisfied +23560,91487,Female,Loyal Customer,49,Personal Travel,Eco,859,2,3,2,3,1,4,1,4,4,2,4,3,4,1,6,3.0,neutral or dissatisfied +23561,87115,Female,Loyal Customer,34,Personal Travel,Eco,594,2,5,2,3,2,2,2,2,3,3,1,2,2,2,113,96.0,neutral or dissatisfied +23562,109415,Male,Loyal Customer,45,Business travel,Business,966,3,3,3,3,2,4,5,5,5,4,5,3,5,5,0,0.0,satisfied +23563,44898,Male,Loyal Customer,52,Business travel,Eco,536,5,3,3,3,5,5,5,5,2,2,4,5,3,5,0,0.0,satisfied +23564,127344,Male,Loyal Customer,59,Business travel,Business,3000,1,1,1,1,4,4,5,4,4,4,4,4,4,3,11,4.0,satisfied +23565,30332,Female,Loyal Customer,31,Business travel,Eco,391,3,5,5,5,3,3,3,3,1,1,4,4,4,3,22,17.0,neutral or dissatisfied +23566,75252,Female,Loyal Customer,23,Personal Travel,Eco,1652,1,5,1,4,4,1,4,4,5,2,4,3,5,4,0,13.0,neutral or dissatisfied +23567,117655,Female,Loyal Customer,42,Business travel,Business,1449,1,1,5,1,3,5,4,3,3,4,3,3,3,4,0,0.0,satisfied +23568,65135,Female,Loyal Customer,60,Personal Travel,Eco,190,2,4,0,3,0,1,1,4,1,4,3,1,3,1,139,137.0,neutral or dissatisfied +23569,72206,Male,Loyal Customer,50,Business travel,Business,2724,3,3,3,3,5,5,5,5,2,4,5,5,4,5,21,23.0,satisfied +23570,1541,Male,Loyal Customer,53,Business travel,Business,987,3,1,1,1,5,3,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +23571,35758,Female,Loyal Customer,47,Business travel,Business,1608,5,5,5,5,2,4,2,4,4,4,4,5,4,2,0,0.0,satisfied +23572,107450,Female,Loyal Customer,56,Business travel,Business,3079,5,5,5,5,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23573,72073,Female,Loyal Customer,41,Business travel,Business,2556,1,1,1,1,5,3,4,5,5,5,5,5,5,5,16,0.0,satisfied +23574,941,Female,Loyal Customer,45,Business travel,Business,1749,2,5,5,5,5,4,4,2,2,2,2,3,2,3,0,0.0,neutral or dissatisfied +23575,74576,Male,Loyal Customer,50,Business travel,Eco,1464,2,5,5,5,2,2,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +23576,92131,Female,Loyal Customer,9,Personal Travel,Eco,1517,1,4,2,3,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +23577,84831,Male,Loyal Customer,38,Business travel,Eco,481,3,5,5,5,3,3,3,3,2,2,4,2,3,3,5,0.0,neutral or dissatisfied +23578,32871,Female,Loyal Customer,38,Personal Travel,Eco,101,2,2,2,4,5,2,5,5,4,5,4,1,3,5,0,0.0,neutral or dissatisfied +23579,47250,Male,disloyal Customer,27,Business travel,Business,588,4,4,4,3,5,4,5,5,3,3,5,4,5,5,54,80.0,satisfied +23580,9272,Female,Loyal Customer,16,Personal Travel,Eco,441,2,4,2,3,5,2,5,5,4,2,4,4,5,5,0,0.0,neutral or dissatisfied +23581,58090,Female,Loyal Customer,38,Business travel,Business,642,1,1,1,1,3,2,2,1,1,1,1,1,1,4,0,0.0,neutral or dissatisfied +23582,56562,Male,Loyal Customer,56,Business travel,Business,3275,4,4,4,4,2,4,4,5,5,5,5,3,5,4,1,0.0,satisfied +23583,119781,Male,Loyal Customer,13,Personal Travel,Business,912,3,5,3,4,5,3,5,5,4,3,4,5,4,5,7,20.0,neutral or dissatisfied +23584,21945,Female,Loyal Customer,54,Business travel,Business,2292,2,2,2,2,5,3,4,4,4,5,4,1,4,5,0,0.0,satisfied +23585,74255,Female,Loyal Customer,18,Personal Travel,Eco,1709,3,5,3,3,2,3,2,2,4,4,5,5,5,2,0,0.0,neutral or dissatisfied +23586,17164,Male,Loyal Customer,40,Business travel,Business,643,5,5,5,5,2,3,1,3,3,3,3,3,3,2,0,0.0,satisfied +23587,49923,Male,Loyal Customer,44,Business travel,Business,2843,2,5,5,5,3,4,4,3,3,3,2,4,3,3,0,0.0,neutral or dissatisfied +23588,116607,Male,Loyal Customer,40,Business travel,Business,358,3,3,4,3,5,4,5,5,5,5,5,5,5,4,84,79.0,satisfied +23589,24270,Female,Loyal Customer,28,Personal Travel,Eco,147,5,5,0,3,3,0,3,3,4,4,5,5,2,3,0,0.0,satisfied +23590,66920,Female,Loyal Customer,35,Business travel,Business,964,3,3,3,3,2,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +23591,128724,Male,Loyal Customer,10,Personal Travel,Eco,1235,3,2,3,3,1,3,1,1,1,2,3,1,4,1,0,0.0,neutral or dissatisfied +23592,128081,Male,Loyal Customer,60,Business travel,Business,2845,1,1,1,1,4,4,4,4,2,5,4,4,5,4,10,23.0,satisfied +23593,115401,Female,disloyal Customer,65,Business travel,Eco,362,1,3,1,3,5,1,4,5,1,4,3,2,4,5,21,20.0,neutral or dissatisfied +23594,91821,Female,Loyal Customer,55,Business travel,Business,2177,3,3,3,3,4,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +23595,29538,Male,Loyal Customer,44,Business travel,Business,1448,5,5,3,5,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +23596,41589,Male,Loyal Customer,62,Personal Travel,Eco,1464,2,5,2,3,5,2,5,5,4,4,4,4,4,5,0,0.0,neutral or dissatisfied +23597,90569,Female,Loyal Customer,55,Business travel,Business,515,2,2,2,2,5,5,4,5,5,5,5,5,5,5,41,45.0,satisfied +23598,44901,Female,Loyal Customer,62,Personal Travel,Eco,536,3,2,3,4,2,3,4,2,2,3,1,4,2,3,10,14.0,neutral or dissatisfied +23599,42635,Female,Loyal Customer,57,Business travel,Business,146,5,5,5,5,4,3,4,5,5,5,3,2,5,4,7,4.0,satisfied +23600,81771,Female,Loyal Customer,51,Business travel,Business,1416,2,2,2,2,2,3,3,2,2,2,2,3,2,2,0,0.0,neutral or dissatisfied +23601,112730,Female,Loyal Customer,49,Personal Travel,Eco,672,1,5,1,2,5,5,5,4,4,1,1,4,4,3,6,0.0,neutral or dissatisfied +23602,126101,Male,disloyal Customer,28,Business travel,Business,650,3,3,3,3,1,3,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +23603,117509,Female,Loyal Customer,51,Personal Travel,Eco,507,4,1,4,4,5,3,3,3,3,4,3,2,3,1,0,0.0,satisfied +23604,126136,Male,Loyal Customer,56,Business travel,Eco,631,3,2,2,2,3,3,3,3,1,5,3,3,3,3,0,0.0,neutral or dissatisfied +23605,111153,Male,Loyal Customer,29,Personal Travel,Eco,1050,2,4,2,1,3,2,3,3,5,3,5,3,4,3,35,9.0,neutral or dissatisfied +23606,43978,Male,Loyal Customer,32,Business travel,Business,1615,3,3,3,3,4,4,4,4,3,5,5,2,1,4,0,0.0,satisfied +23607,102341,Female,Loyal Customer,44,Business travel,Business,3599,2,2,2,2,2,5,4,5,5,5,5,4,5,3,4,0.0,satisfied +23608,65628,Female,Loyal Customer,14,Personal Travel,Eco,175,1,4,0,3,5,0,5,5,5,5,4,5,5,5,3,7.0,neutral or dissatisfied +23609,81064,Male,Loyal Customer,52,Business travel,Business,931,4,4,4,4,5,4,4,2,2,2,2,4,2,5,0,0.0,satisfied +23610,20418,Male,Loyal Customer,48,Business travel,Business,3975,3,2,2,2,2,3,2,3,3,3,4,2,2,2,137,139.0,neutral or dissatisfied +23611,92457,Male,Loyal Customer,41,Business travel,Eco,1892,3,1,1,1,3,3,3,3,1,3,4,3,3,3,70,42.0,neutral or dissatisfied +23612,82253,Male,Loyal Customer,45,Business travel,Business,1481,1,5,5,5,4,3,2,1,1,1,1,4,1,4,0,0.0,neutral or dissatisfied +23613,51620,Male,Loyal Customer,59,Business travel,Business,598,3,3,3,3,1,4,3,5,5,5,5,5,5,1,0,3.0,satisfied +23614,1566,Female,Loyal Customer,56,Business travel,Business,2038,4,4,4,4,4,4,4,4,4,4,4,3,4,5,0,0.0,satisfied +23615,55573,Male,Loyal Customer,47,Business travel,Business,1091,4,4,4,4,5,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +23616,99877,Female,Loyal Customer,22,Business travel,Business,1436,1,1,1,1,5,4,5,5,2,1,1,2,5,5,1,0.0,satisfied +23617,21108,Female,Loyal Customer,43,Personal Travel,Eco,227,3,5,3,4,2,5,4,2,2,3,2,3,2,4,4,0.0,neutral or dissatisfied +23618,71858,Female,Loyal Customer,77,Business travel,Business,226,3,4,4,4,1,3,4,3,3,3,3,1,3,1,10,15.0,neutral or dissatisfied +23619,46021,Female,Loyal Customer,34,Business travel,Business,1825,2,2,1,2,2,2,2,4,4,4,4,4,4,4,20,38.0,satisfied +23620,103021,Female,disloyal Customer,22,Business travel,Eco,786,4,4,4,1,2,4,2,2,4,2,4,4,5,2,11,0.0,neutral or dissatisfied +23621,18745,Male,Loyal Customer,49,Business travel,Eco,1167,4,1,1,1,4,4,4,4,2,2,4,5,3,4,0,0.0,satisfied +23622,38613,Male,Loyal Customer,63,Personal Travel,Eco,231,1,2,0,4,4,0,4,4,4,1,3,4,4,4,0,0.0,neutral or dissatisfied +23623,80826,Female,Loyal Customer,48,Business travel,Business,484,2,2,2,2,4,4,5,4,4,4,4,3,4,4,10,2.0,satisfied +23624,3463,Male,disloyal Customer,25,Business travel,Business,213,2,2,2,3,3,2,4,3,2,1,4,4,4,3,0,0.0,neutral or dissatisfied +23625,57448,Male,Loyal Customer,52,Business travel,Business,3200,2,2,2,2,4,4,4,4,4,4,4,4,4,5,0,1.0,satisfied +23626,11346,Male,Loyal Customer,18,Personal Travel,Eco,309,4,4,4,3,5,4,5,5,5,3,5,3,4,5,0,0.0,satisfied +23627,106580,Female,Loyal Customer,59,Business travel,Business,333,2,2,2,2,4,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +23628,91024,Male,Loyal Customer,42,Personal Travel,Eco,442,3,5,5,1,3,5,3,3,4,5,3,4,3,3,11,0.0,neutral or dissatisfied +23629,76898,Male,Loyal Customer,36,Business travel,Eco,230,5,4,4,4,5,4,5,5,1,1,3,2,4,5,0,0.0,neutral or dissatisfied +23630,108318,Female,Loyal Customer,34,Business travel,Business,1750,3,3,3,3,3,4,4,4,4,4,4,4,4,3,0,0.0,satisfied +23631,24782,Female,Loyal Customer,51,Business travel,Eco,528,5,5,5,5,5,1,4,5,5,5,5,2,5,5,0,0.0,satisfied +23632,93598,Female,Loyal Customer,57,Business travel,Business,577,4,4,4,4,4,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +23633,37998,Female,Loyal Customer,46,Business travel,Eco,1121,3,1,1,1,3,2,3,3,3,3,3,2,3,1,22,16.0,satisfied +23634,48237,Male,Loyal Customer,19,Personal Travel,Eco,259,3,4,0,4,5,0,1,5,2,1,3,3,3,5,0,0.0,neutral or dissatisfied +23635,95627,Male,Loyal Customer,37,Personal Travel,Eco,484,4,4,4,4,4,4,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +23636,22957,Male,Loyal Customer,37,Business travel,Business,1595,2,4,2,2,1,1,2,5,5,5,5,2,5,1,31,35.0,satisfied +23637,72372,Male,Loyal Customer,54,Business travel,Business,1580,2,2,2,2,3,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +23638,55203,Male,Loyal Customer,24,Personal Travel,Eco Plus,1379,5,4,5,1,4,4,4,4,5,2,4,4,4,4,0,0.0,satisfied +23639,74764,Female,Loyal Customer,15,Personal Travel,Eco,1464,3,5,3,1,3,3,3,3,5,4,3,4,3,3,0,0.0,neutral or dissatisfied +23640,17165,Male,Loyal Customer,38,Business travel,Business,643,2,2,2,2,1,1,5,3,3,4,3,5,3,3,85,77.0,satisfied +23641,20777,Male,Loyal Customer,41,Business travel,Business,3225,1,1,1,1,2,3,4,4,4,4,4,3,4,3,0,0.0,satisfied +23642,107868,Female,Loyal Customer,24,Business travel,Business,2988,1,1,4,4,1,1,1,1,2,3,3,2,3,1,11,0.0,neutral or dissatisfied +23643,82443,Male,Loyal Customer,16,Business travel,Eco,502,2,1,1,1,2,1,2,2,2,1,4,4,3,2,0,0.0,neutral or dissatisfied +23644,70392,Female,Loyal Customer,22,Business travel,Eco,1562,4,4,4,4,4,3,3,4,3,1,4,4,4,4,0,10.0,neutral or dissatisfied +23645,46652,Female,disloyal Customer,18,Business travel,Eco,141,1,0,1,4,4,1,4,4,2,2,4,2,2,4,25,21.0,neutral or dissatisfied +23646,99929,Male,disloyal Customer,28,Business travel,Eco,764,3,3,3,4,1,3,1,1,1,5,3,1,4,1,0,0.0,neutral or dissatisfied +23647,62230,Female,Loyal Customer,54,Personal Travel,Eco,2434,2,5,2,4,5,5,5,1,1,2,1,3,1,5,0,0.0,neutral or dissatisfied +23648,98872,Male,Loyal Customer,22,Business travel,Business,2074,4,4,4,4,5,5,5,5,3,3,4,5,4,5,3,0.0,satisfied +23649,29783,Male,Loyal Customer,42,Business travel,Business,234,3,3,3,3,2,4,3,3,3,3,3,2,3,1,0,0.0,neutral or dissatisfied +23650,17392,Male,Loyal Customer,69,Business travel,Eco,376,5,5,5,5,5,5,5,5,3,2,5,2,4,5,0,0.0,satisfied +23651,7834,Male,Loyal Customer,27,Personal Travel,Eco,650,1,3,1,4,1,1,1,1,2,4,3,1,4,1,0,18.0,neutral or dissatisfied +23652,122303,Male,Loyal Customer,28,Personal Travel,Eco,546,2,3,2,3,1,2,3,1,1,4,3,3,4,1,3,3.0,neutral or dissatisfied +23653,116777,Male,Loyal Customer,44,Personal Travel,Eco Plus,358,4,5,4,2,2,4,2,2,4,3,5,4,4,2,32,22.0,neutral or dissatisfied +23654,6074,Female,Loyal Customer,62,Personal Travel,Eco,672,2,1,2,4,4,3,4,3,3,2,3,4,3,4,54,67.0,neutral or dissatisfied +23655,125434,Male,Loyal Customer,14,Personal Travel,Eco,735,3,5,3,3,2,3,2,2,3,3,4,3,4,2,0,0.0,neutral or dissatisfied +23656,72880,Male,Loyal Customer,40,Business travel,Business,2387,4,4,4,4,4,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +23657,81824,Female,Loyal Customer,63,Personal Travel,Eco,1310,4,3,4,4,3,4,4,5,5,4,5,3,5,3,0,0.0,neutral or dissatisfied +23658,58123,Male,Loyal Customer,49,Personal Travel,Eco,589,4,5,4,1,4,4,5,4,3,5,5,5,4,4,5,0.0,neutral or dissatisfied +23659,44788,Male,Loyal Customer,66,Personal Travel,Eco,1250,3,4,2,5,5,2,5,5,4,2,4,5,5,5,0,0.0,neutral or dissatisfied +23660,31502,Male,disloyal Customer,42,Business travel,Eco,853,4,5,5,3,4,5,4,4,4,2,4,4,4,4,13,6.0,neutral or dissatisfied +23661,62463,Female,Loyal Customer,54,Personal Travel,Business,1726,2,2,1,4,1,3,3,1,1,1,1,3,1,1,9,0.0,neutral or dissatisfied +23662,69002,Female,Loyal Customer,23,Business travel,Business,1389,4,4,4,4,4,5,4,4,4,2,4,4,4,4,0,0.0,satisfied +23663,29399,Male,disloyal Customer,20,Business travel,Eco,884,4,4,4,5,2,4,2,2,2,1,1,3,3,2,0,0.0,satisfied +23664,71174,Female,Loyal Customer,54,Business travel,Business,740,3,3,5,3,5,5,5,5,5,5,5,3,5,3,100,87.0,satisfied +23665,8453,Female,Loyal Customer,41,Business travel,Business,1379,3,4,3,3,2,4,5,4,4,4,4,5,4,4,93,93.0,satisfied +23666,15713,Female,Loyal Customer,29,Business travel,Business,479,3,5,5,5,3,3,3,3,2,1,3,4,4,3,27,37.0,neutral or dissatisfied +23667,74487,Male,Loyal Customer,49,Business travel,Business,1235,4,4,4,4,3,4,5,2,2,2,2,4,2,5,1,0.0,satisfied +23668,45180,Male,Loyal Customer,62,Business travel,Eco Plus,130,2,2,2,2,2,2,2,2,3,1,1,3,3,2,38,64.0,satisfied +23669,27321,Female,Loyal Customer,40,Business travel,Business,2538,4,4,2,4,2,2,2,2,2,2,2,3,2,4,22,16.0,satisfied +23670,7468,Male,Loyal Customer,31,Business travel,Business,2641,2,2,2,2,5,5,5,5,4,4,5,4,4,5,0,0.0,satisfied +23671,53885,Female,Loyal Customer,34,Personal Travel,Eco,191,4,4,0,2,2,0,2,2,3,3,4,3,5,2,25,13.0,neutral or dissatisfied +23672,32796,Male,Loyal Customer,27,Business travel,Business,2850,2,1,1,1,4,4,2,4,3,4,4,3,3,4,8,9.0,neutral or dissatisfied +23673,8127,Female,Loyal Customer,51,Business travel,Business,1812,0,4,0,3,4,5,5,2,2,2,2,3,2,3,0,5.0,satisfied +23674,12414,Female,Loyal Customer,35,Personal Travel,Eco,201,5,5,5,1,1,5,1,1,3,5,4,3,4,1,0,0.0,satisfied +23675,75275,Male,Loyal Customer,11,Personal Travel,Eco,1846,2,4,2,1,1,2,1,1,5,3,5,5,4,1,0,0.0,neutral or dissatisfied +23676,37563,Male,Loyal Customer,42,Business travel,Eco,544,5,3,5,3,5,5,5,5,1,4,1,4,3,5,2,0.0,satisfied +23677,19685,Male,Loyal Customer,52,Business travel,Eco,409,4,3,3,3,4,4,4,4,4,3,2,1,2,4,69,82.0,neutral or dissatisfied +23678,52470,Male,Loyal Customer,15,Personal Travel,Eco Plus,370,2,4,2,4,4,2,4,4,4,2,4,4,4,4,0,0.0,neutral or dissatisfied +23679,116149,Male,Loyal Customer,47,Personal Travel,Eco,390,3,3,3,4,2,3,5,2,3,3,3,2,3,2,24,19.0,neutral or dissatisfied +23680,129522,Female,Loyal Customer,56,Business travel,Business,3257,5,5,5,5,3,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +23681,63,Female,Loyal Customer,37,Business travel,Business,2423,3,4,4,4,3,4,4,2,2,2,3,1,2,4,0,8.0,neutral or dissatisfied +23682,8737,Female,Loyal Customer,26,Business travel,Business,304,5,5,5,5,4,4,4,4,3,2,5,5,5,4,0,0.0,satisfied +23683,89786,Male,Loyal Customer,8,Personal Travel,Eco,1076,2,4,2,3,3,2,3,3,3,3,5,5,5,3,0,0.0,neutral or dissatisfied +23684,108883,Male,Loyal Customer,60,Business travel,Business,1510,2,1,5,5,2,2,2,2,2,2,2,2,2,3,6,0.0,neutral or dissatisfied +23685,33702,Female,Loyal Customer,24,Business travel,Business,1833,1,1,1,1,1,1,1,1,3,5,4,2,3,1,9,11.0,neutral or dissatisfied +23686,81448,Male,disloyal Customer,23,Business travel,Business,528,4,4,4,5,2,4,2,2,4,2,4,3,5,2,0,0.0,satisfied +23687,40008,Male,Loyal Customer,35,Business travel,Business,525,5,5,5,5,2,1,3,5,5,5,5,2,5,3,0,10.0,satisfied +23688,60535,Female,Loyal Customer,47,Personal Travel,Eco,862,4,3,4,4,1,4,3,4,4,4,3,1,4,1,15,8.0,neutral or dissatisfied +23689,72957,Male,disloyal Customer,37,Business travel,Business,1096,3,3,3,3,5,3,1,5,3,5,4,3,5,5,0,0.0,neutral or dissatisfied +23690,100052,Male,Loyal Customer,60,Personal Travel,Eco,220,3,2,3,4,4,3,4,4,2,3,3,1,3,4,21,42.0,neutral or dissatisfied +23691,129438,Male,disloyal Customer,36,Business travel,Eco,414,4,0,4,1,5,4,5,5,3,1,4,4,4,5,0,13.0,neutral or dissatisfied +23692,32112,Female,Loyal Customer,58,Business travel,Business,101,4,4,4,4,3,1,5,5,5,5,4,3,5,5,7,9.0,satisfied +23693,109724,Female,disloyal Customer,23,Business travel,Eco,587,3,3,3,3,3,3,3,3,3,4,4,1,4,3,0,0.0,neutral or dissatisfied +23694,53135,Male,Loyal Customer,38,Business travel,Business,2480,2,2,2,2,4,1,2,4,4,5,4,1,4,2,12,35.0,satisfied +23695,113355,Female,Loyal Customer,48,Business travel,Business,414,3,3,3,3,4,4,4,5,5,5,5,4,5,5,1,0.0,satisfied +23696,84801,Female,Loyal Customer,29,Business travel,Business,2349,1,1,3,1,3,3,3,3,3,4,4,4,4,3,0,0.0,satisfied +23697,97354,Female,disloyal Customer,37,Business travel,Eco,347,4,3,4,3,1,4,3,1,1,5,3,4,4,1,0,0.0,neutral or dissatisfied +23698,49367,Male,Loyal Customer,23,Business travel,Business,1510,2,2,2,2,4,4,4,4,4,3,2,3,4,4,0,0.0,satisfied +23699,9934,Male,Loyal Customer,23,Business travel,Business,2278,3,4,4,4,3,3,3,3,3,5,1,2,2,3,86,70.0,neutral or dissatisfied +23700,53730,Female,Loyal Customer,29,Personal Travel,Eco,1190,4,4,3,1,3,3,3,3,3,3,4,5,4,3,0,0.0,satisfied +23701,55673,Female,Loyal Customer,42,Business travel,Business,895,3,3,3,3,2,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +23702,65064,Male,Loyal Customer,10,Personal Travel,Eco,247,1,5,1,3,5,1,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +23703,68531,Male,Loyal Customer,25,Business travel,Business,1013,4,2,4,4,4,5,4,4,3,5,4,3,5,4,0,0.0,satisfied +23704,80355,Male,Loyal Customer,55,Business travel,Business,368,3,3,3,3,2,5,5,3,3,4,3,4,3,5,11,2.0,satisfied +23705,10959,Female,Loyal Customer,43,Business travel,Eco,458,5,5,3,5,3,3,4,4,4,5,4,4,4,4,0,0.0,satisfied +23706,25124,Male,disloyal Customer,9,Business travel,Eco,946,1,1,1,4,4,1,2,4,1,3,3,2,4,4,12,0.0,neutral or dissatisfied +23707,95680,Female,disloyal Customer,26,Business travel,Business,237,2,2,2,3,5,2,5,5,3,4,2,2,3,5,15,11.0,neutral or dissatisfied +23708,35580,Male,Loyal Customer,21,Business travel,Eco Plus,944,4,3,3,3,4,4,5,4,1,5,5,1,4,4,38,44.0,satisfied +23709,86298,Female,Loyal Customer,66,Personal Travel,Eco,356,4,5,3,4,2,1,3,1,1,3,1,3,1,4,6,0.0,neutral or dissatisfied +23710,34506,Female,Loyal Customer,31,Business travel,Business,1521,5,5,5,5,4,4,4,4,4,5,4,2,2,4,32,34.0,satisfied +23711,49000,Male,Loyal Customer,41,Business travel,Business,3115,0,3,0,1,1,5,5,3,3,3,3,1,3,5,0,0.0,satisfied +23712,287,Male,Loyal Customer,55,Business travel,Business,3433,5,5,5,5,5,4,5,5,5,4,5,4,5,4,0,0.0,satisfied +23713,8004,Female,Loyal Customer,44,Personal Travel,Business,125,5,2,5,2,5,1,2,1,1,5,1,4,1,4,0,0.0,satisfied +23714,6609,Female,Loyal Customer,33,Personal Travel,Eco,528,2,4,5,5,4,5,4,4,4,3,4,4,4,4,2,0.0,neutral or dissatisfied +23715,126831,Female,Loyal Customer,66,Business travel,Eco,2125,1,4,4,4,5,1,1,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +23716,109983,Female,disloyal Customer,35,Business travel,Business,1011,3,3,3,3,5,3,5,5,3,2,4,4,4,5,26,21.0,neutral or dissatisfied +23717,76793,Male,Loyal Customer,29,Business travel,Business,1645,3,3,3,3,5,5,5,5,4,2,5,5,4,5,0,0.0,satisfied +23718,41657,Male,Loyal Customer,69,Business travel,Business,1865,2,2,2,2,3,3,5,4,4,4,4,2,4,1,0,0.0,satisfied +23719,105269,Male,Loyal Customer,61,Personal Travel,Eco,2106,1,2,1,2,1,1,1,1,4,3,1,3,2,1,0,0.0,neutral or dissatisfied +23720,78529,Male,Loyal Customer,66,Personal Travel,Eco,666,3,5,3,3,1,3,1,1,2,1,5,3,5,1,0,0.0,neutral or dissatisfied +23721,30591,Female,Loyal Customer,44,Business travel,Eco Plus,628,5,2,5,5,3,5,1,5,5,5,5,1,5,5,81,86.0,satisfied +23722,4951,Male,disloyal Customer,34,Business travel,Business,931,2,2,2,2,2,2,4,2,5,4,5,5,5,2,3,0.0,neutral or dissatisfied +23723,79667,Female,Loyal Customer,38,Personal Travel,Eco,762,4,4,4,3,5,4,5,5,4,4,5,3,4,5,24,1.0,satisfied +23724,63893,Female,Loyal Customer,29,Business travel,Eco,1172,3,4,4,4,3,3,3,3,2,2,4,1,3,3,0,0.0,neutral or dissatisfied +23725,13866,Male,Loyal Customer,29,Business travel,Eco,667,5,2,2,2,5,5,5,5,5,5,1,2,5,5,0,0.0,satisfied +23726,4569,Female,Loyal Customer,23,Personal Travel,Eco,561,2,1,2,3,4,2,4,4,1,5,4,3,3,4,0,0.0,neutral or dissatisfied +23727,74503,Female,Loyal Customer,58,Business travel,Business,1464,1,1,1,1,3,4,5,5,5,5,5,4,5,3,6,2.0,satisfied +23728,57716,Female,disloyal Customer,43,Business travel,Business,989,5,4,4,4,2,5,2,2,3,5,5,3,4,2,4,0.0,satisfied +23729,49595,Male,Loyal Customer,31,Business travel,Eco,190,0,0,0,1,4,0,1,4,5,4,4,2,3,4,30,46.0,satisfied +23730,103556,Female,Loyal Customer,36,Personal Travel,Eco,738,2,5,2,5,4,2,1,4,4,5,5,4,4,4,21,5.0,neutral or dissatisfied +23731,121614,Male,Loyal Customer,12,Personal Travel,Eco,1095,3,2,3,2,4,3,5,4,1,2,3,2,2,4,0,1.0,neutral or dissatisfied +23732,12242,Female,Loyal Customer,43,Business travel,Business,1832,2,2,2,2,4,4,2,4,4,4,5,5,4,3,0,0.0,satisfied +23733,96159,Female,Loyal Customer,26,Business travel,Business,3243,5,5,5,5,4,4,4,4,3,4,5,5,5,4,32,27.0,satisfied +23734,82511,Female,Loyal Customer,23,Business travel,Business,1749,2,2,2,2,5,4,5,5,5,2,3,5,5,5,0,0.0,satisfied +23735,127364,Male,Loyal Customer,42,Business travel,Business,868,5,5,4,5,2,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +23736,106289,Female,Loyal Customer,60,Personal Travel,Eco,604,2,5,2,5,2,4,5,1,1,2,1,3,1,4,15,13.0,neutral or dissatisfied +23737,40699,Male,Loyal Customer,29,Business travel,Business,2379,2,2,3,2,5,5,5,5,5,2,4,4,5,5,0,0.0,satisfied +23738,28541,Female,Loyal Customer,42,Personal Travel,Eco,2677,2,4,2,4,3,3,4,3,3,2,3,2,3,1,1,0.0,neutral or dissatisfied +23739,126085,Male,Loyal Customer,59,Business travel,Business,2153,4,4,4,4,3,5,5,5,5,5,5,3,5,3,0,0.0,satisfied +23740,66940,Male,Loyal Customer,58,Business travel,Business,985,4,4,4,4,2,4,4,4,4,5,4,4,4,4,0,0.0,satisfied +23741,71220,Female,Loyal Customer,46,Business travel,Business,733,1,1,1,1,3,4,4,5,5,5,5,3,5,3,0,5.0,satisfied +23742,102000,Female,Loyal Customer,54,Personal Travel,Eco,628,3,5,4,2,5,5,4,3,3,4,3,3,3,4,1,6.0,neutral or dissatisfied +23743,125023,Male,Loyal Customer,52,Personal Travel,Eco,184,2,1,0,4,1,0,1,1,2,3,4,2,4,1,0,0.0,neutral or dissatisfied +23744,56393,Male,Loyal Customer,54,Business travel,Business,719,3,3,5,3,2,4,4,3,3,3,3,4,3,2,0,0.0,neutral or dissatisfied +23745,62257,Female,Loyal Customer,57,Business travel,Business,2565,5,5,2,5,4,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +23746,61438,Male,Loyal Customer,43,Business travel,Business,2288,2,2,2,2,2,5,4,3,3,4,3,5,3,3,1,0.0,satisfied +23747,63000,Female,Loyal Customer,36,Business travel,Business,3777,1,1,4,1,4,4,3,1,1,1,1,4,1,4,34,19.0,neutral or dissatisfied +23748,25763,Male,Loyal Customer,47,Personal Travel,Eco,356,1,4,1,4,1,1,1,1,5,4,4,5,4,1,31,19.0,neutral or dissatisfied +23749,25497,Male,Loyal Customer,34,Business travel,Business,547,3,2,2,2,1,3,3,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +23750,94041,Male,Loyal Customer,42,Business travel,Business,2993,5,5,5,5,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +23751,129034,Male,disloyal Customer,36,Business travel,Business,1846,2,2,2,3,3,2,3,3,3,5,4,4,4,3,0,0.0,neutral or dissatisfied +23752,20211,Male,Loyal Customer,35,Business travel,Eco,179,4,5,5,5,4,4,4,4,1,3,3,5,3,4,40,45.0,satisfied +23753,106722,Female,Loyal Customer,52,Business travel,Business,2274,4,4,3,4,3,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +23754,29791,Female,disloyal Customer,33,Business travel,Eco,725,2,2,2,2,4,2,2,4,4,3,2,2,3,4,0,0.0,neutral or dissatisfied +23755,64440,Female,Loyal Customer,40,Business travel,Business,2762,2,2,2,2,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +23756,124877,Male,Loyal Customer,25,Business travel,Business,1806,2,2,1,2,2,2,2,2,2,3,3,1,4,2,14,4.0,neutral or dissatisfied +23757,75510,Female,Loyal Customer,67,Personal Travel,Eco,2527,4,4,4,3,4,4,5,1,1,4,1,3,1,5,3,2.0,satisfied +23758,115793,Male,disloyal Customer,27,Business travel,Eco,371,4,0,4,3,1,4,1,1,5,1,5,5,4,1,0,0.0,satisfied +23759,51231,Female,Loyal Customer,33,Business travel,Eco Plus,266,0,0,0,3,3,5,5,3,3,5,3,1,3,3,0,4.0,satisfied +23760,53658,Male,Loyal Customer,41,Business travel,Business,1981,5,5,5,5,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +23761,113744,Female,Loyal Customer,43,Personal Travel,Eco,236,5,2,5,2,2,2,2,1,1,5,1,2,1,1,0,0.0,satisfied +23762,90564,Male,disloyal Customer,22,Business travel,Eco,404,2,4,2,4,5,2,5,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +23763,106082,Female,Loyal Customer,39,Business travel,Business,1657,5,5,5,5,3,4,5,4,4,4,4,3,4,5,19,13.0,satisfied +23764,120358,Male,Loyal Customer,44,Business travel,Business,2136,4,4,5,4,2,4,4,4,4,4,4,5,4,4,4,0.0,satisfied +23765,368,Female,Loyal Customer,46,Business travel,Business,354,0,0,0,3,4,5,4,1,1,1,1,3,1,3,43,43.0,satisfied +23766,112701,Female,Loyal Customer,51,Business travel,Eco,671,4,5,5,5,2,3,3,4,4,4,4,3,4,3,3,0.0,neutral or dissatisfied +23767,60341,Female,disloyal Customer,20,Business travel,Eco,624,0,0,0,4,3,0,3,3,2,1,4,4,1,3,66,49.0,satisfied +23768,128676,Male,disloyal Customer,22,Business travel,Eco,832,3,4,4,3,4,1,2,4,2,3,5,2,4,2,5,0.0,neutral or dissatisfied +23769,111066,Male,Loyal Customer,44,Personal Travel,Eco,197,3,4,3,1,1,3,1,1,4,1,2,2,5,1,0,2.0,neutral or dissatisfied +23770,117464,Female,Loyal Customer,29,Personal Travel,Eco Plus,1107,2,3,2,4,1,2,1,1,4,2,4,2,3,1,0,22.0,neutral or dissatisfied +23771,72183,Male,Loyal Customer,47,Business travel,Business,2088,4,4,4,4,2,5,4,5,5,5,5,3,5,3,15,7.0,satisfied +23772,54552,Male,Loyal Customer,63,Personal Travel,Eco,925,2,5,2,1,1,2,1,1,5,5,4,5,4,1,0,17.0,neutral or dissatisfied +23773,85656,Male,Loyal Customer,44,Business travel,Business,3064,2,2,2,2,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +23774,2373,Male,Loyal Customer,45,Business travel,Business,604,5,5,5,5,5,5,5,2,2,2,2,5,2,3,32,51.0,satisfied +23775,46296,Female,Loyal Customer,24,Business travel,Business,1800,3,5,5,5,3,3,3,3,2,4,2,2,3,3,0,0.0,neutral or dissatisfied +23776,110299,Female,Loyal Customer,52,Business travel,Business,3389,2,2,2,2,5,4,4,2,2,2,2,5,2,4,42,21.0,satisfied +23777,90126,Female,Loyal Customer,18,Business travel,Business,2755,2,2,2,2,2,2,2,2,3,2,3,2,3,2,0,0.0,neutral or dissatisfied +23778,102769,Male,Loyal Customer,41,Personal Travel,Eco,1618,2,5,2,2,1,2,1,1,5,4,5,5,4,1,82,67.0,neutral or dissatisfied +23779,95195,Male,Loyal Customer,41,Personal Travel,Eco,189,2,5,0,3,4,0,4,4,4,4,4,4,5,4,104,100.0,neutral or dissatisfied +23780,19746,Male,Loyal Customer,25,Business travel,Eco Plus,409,0,4,0,5,1,0,1,1,5,1,4,4,2,1,0,0.0,satisfied +23781,122638,Female,Loyal Customer,22,Business travel,Eco Plus,728,2,1,1,1,2,2,3,2,3,3,4,2,3,2,9,12.0,neutral or dissatisfied +23782,71377,Female,Loyal Customer,67,Business travel,Business,258,3,5,4,4,1,3,3,3,3,3,3,2,3,3,91,85.0,neutral or dissatisfied +23783,88365,Female,Loyal Customer,32,Business travel,Business,3012,2,2,2,2,4,4,4,4,3,4,4,4,4,4,0,0.0,satisfied +23784,16834,Female,Loyal Customer,27,Personal Travel,Eco,645,1,1,1,3,3,1,3,3,4,3,3,4,3,3,0,0.0,neutral or dissatisfied +23785,54911,Male,Loyal Customer,33,Business travel,Eco Plus,794,3,3,3,3,3,3,3,3,4,4,2,1,3,3,0,0.0,neutral or dissatisfied +23786,4334,Male,Loyal Customer,41,Business travel,Business,618,4,4,4,4,3,4,5,2,2,2,2,5,2,4,41,36.0,satisfied +23787,47007,Female,Loyal Customer,50,Personal Travel,Eco Plus,844,3,5,3,1,5,4,4,1,1,3,1,3,1,5,0,4.0,neutral or dissatisfied +23788,98648,Male,disloyal Customer,27,Business travel,Eco,920,5,5,5,3,2,5,2,2,4,1,3,5,3,2,0,0.0,satisfied +23789,33438,Female,Loyal Customer,57,Business travel,Business,2655,4,2,2,2,3,3,4,4,4,4,4,4,4,4,0,0.0,neutral or dissatisfied +23790,119988,Female,Loyal Customer,15,Business travel,Eco Plus,1009,4,5,5,5,4,3,1,4,2,5,3,1,3,4,0,6.0,neutral or dissatisfied +23791,112999,Male,Loyal Customer,15,Business travel,Business,1751,5,5,5,5,5,5,5,5,5,2,4,4,5,5,24,4.0,satisfied +23792,92617,Male,Loyal Customer,55,Business travel,Business,453,4,4,4,4,5,5,5,2,2,2,2,4,2,5,0,0.0,satisfied +23793,96528,Male,Loyal Customer,34,Personal Travel,Eco,444,2,4,2,4,3,2,3,3,4,2,5,5,4,3,0,0.0,neutral or dissatisfied +23794,65498,Male,Loyal Customer,42,Business travel,Business,3614,1,1,1,1,2,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +23795,54099,Female,Loyal Customer,29,Business travel,Eco Plus,1416,0,0,0,2,2,0,3,2,3,3,2,5,4,2,14,0.0,satisfied +23796,26869,Male,Loyal Customer,34,Business travel,Business,2329,2,2,2,2,4,5,2,3,3,3,3,4,3,4,67,60.0,satisfied +23797,93060,Female,Loyal Customer,61,Business travel,Eco,297,3,1,1,1,1,4,4,3,3,3,3,4,3,2,0,21.0,neutral or dissatisfied +23798,34229,Female,disloyal Customer,28,Business travel,Eco Plus,1046,2,2,2,1,2,2,2,2,4,1,5,2,2,2,0,0.0,neutral or dissatisfied +23799,103206,Male,disloyal Customer,26,Business travel,Business,1482,5,5,5,4,4,5,4,4,4,3,4,4,4,4,11,0.0,satisfied +23800,106433,Female,Loyal Customer,55,Business travel,Business,1678,1,1,1,1,2,4,4,5,5,5,5,3,5,4,6,12.0,satisfied +23801,124157,Female,Loyal Customer,42,Business travel,Business,2133,5,5,5,5,5,4,5,3,3,3,3,3,3,5,63,,satisfied +23802,36287,Female,Loyal Customer,50,Business travel,Business,3882,2,5,5,5,1,4,3,1,1,1,2,3,1,4,0,0.0,neutral or dissatisfied +23803,96760,Male,Loyal Customer,46,Business travel,Business,849,1,4,4,4,3,3,3,1,1,1,1,1,1,4,39,18.0,neutral or dissatisfied +23804,69911,Female,Loyal Customer,31,Business travel,Eco,1514,3,5,3,3,3,3,3,3,3,5,3,3,4,3,0,0.0,neutral or dissatisfied +23805,84519,Female,disloyal Customer,55,Business travel,Business,2615,3,3,3,4,1,3,1,1,4,4,3,5,5,1,0,0.0,neutral or dissatisfied +23806,28354,Male,Loyal Customer,31,Personal Travel,Eco,867,2,5,2,4,2,2,1,2,3,2,4,4,5,2,0,0.0,neutral or dissatisfied +23807,110459,Female,Loyal Customer,53,Personal Travel,Eco,919,4,2,4,4,1,4,3,3,3,4,3,4,3,4,15,6.0,satisfied +23808,100874,Male,disloyal Customer,25,Business travel,Eco,1239,4,4,4,3,2,4,2,2,4,2,4,5,5,2,0,0.0,satisfied +23809,79176,Female,disloyal Customer,20,Business travel,Business,2422,4,0,4,3,4,2,2,4,3,4,5,2,4,2,12,26.0,satisfied +23810,37318,Female,disloyal Customer,29,Business travel,Eco,1010,2,2,2,1,3,2,3,3,5,2,1,3,2,3,0,0.0,neutral or dissatisfied +23811,49463,Female,Loyal Customer,29,Business travel,Eco,250,4,1,1,1,4,4,4,4,1,2,3,3,3,4,1,0.0,satisfied +23812,9965,Male,Loyal Customer,56,Business travel,Business,108,3,3,4,3,1,3,4,3,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +23813,119206,Female,Loyal Customer,42,Business travel,Business,257,4,5,5,5,5,3,3,4,4,4,4,1,4,4,0,15.0,neutral or dissatisfied +23814,47702,Male,Loyal Customer,26,Personal Travel,Eco,1242,3,2,3,4,2,3,3,2,4,4,4,3,3,2,15,3.0,neutral or dissatisfied +23815,90239,Male,Loyal Customer,46,Business travel,Business,1197,4,3,2,2,4,4,4,4,4,4,4,1,4,3,91,102.0,neutral or dissatisfied +23816,81181,Female,disloyal Customer,20,Business travel,Eco,726,2,2,2,4,5,2,5,5,1,4,4,1,3,5,0,0.0,neutral or dissatisfied +23817,82530,Male,Loyal Customer,55,Business travel,Business,1749,1,1,1,1,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +23818,28410,Male,Loyal Customer,45,Business travel,Eco Plus,1709,5,1,1,1,5,5,5,5,3,2,3,2,1,5,0,0.0,satisfied +23819,106493,Female,Loyal Customer,36,Business travel,Business,495,4,1,1,1,4,3,3,4,4,4,4,1,4,2,21,0.0,neutral or dissatisfied +23820,22202,Male,Loyal Customer,38,Personal Travel,Eco,633,2,1,2,2,1,2,1,1,4,1,2,3,2,1,13,18.0,neutral or dissatisfied +23821,101683,Female,Loyal Customer,39,Business travel,Business,1500,4,4,4,4,5,5,4,5,5,5,5,5,5,3,1,0.0,satisfied +23822,90948,Female,disloyal Customer,26,Business travel,Eco,545,4,0,4,2,1,4,3,1,5,1,3,3,2,1,0,0.0,neutral or dissatisfied +23823,66989,Male,Loyal Customer,35,Business travel,Business,1102,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23824,108203,Male,Loyal Customer,54,Personal Travel,Eco Plus,990,1,5,1,2,1,1,1,1,4,5,4,5,5,1,2,0.0,neutral or dissatisfied +23825,52585,Male,Loyal Customer,36,Business travel,Eco,160,1,2,5,2,1,1,1,1,1,3,3,4,2,1,0,0.0,neutral or dissatisfied +23826,85844,Male,Loyal Customer,39,Personal Travel,Eco,666,4,5,4,3,2,4,2,2,3,3,4,3,3,2,0,0.0,satisfied +23827,44950,Male,Loyal Customer,62,Personal Travel,Eco,397,2,4,2,3,2,2,4,2,4,3,4,5,4,2,71,62.0,neutral or dissatisfied +23828,83509,Male,Loyal Customer,27,Personal Travel,Eco,946,2,4,2,4,5,2,5,5,2,3,3,1,3,5,78,85.0,neutral or dissatisfied +23829,35406,Female,Loyal Customer,45,Business travel,Eco,676,5,4,4,4,4,5,1,5,5,5,5,3,5,1,0,0.0,satisfied +23830,19823,Female,Loyal Customer,33,Business travel,Business,3754,4,1,4,4,2,3,3,4,4,3,4,1,4,4,0,1.0,neutral or dissatisfied +23831,58350,Male,Loyal Customer,33,Business travel,Eco Plus,315,0,0,0,2,1,0,1,1,1,1,5,2,4,1,5,3.0,satisfied +23832,94680,Male,Loyal Customer,43,Business travel,Business,323,2,2,5,2,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +23833,8644,Female,Loyal Customer,58,Business travel,Business,1944,1,2,1,1,2,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +23834,80855,Female,Loyal Customer,28,Personal Travel,Eco,692,5,4,5,3,4,5,3,4,3,4,4,5,4,4,0,0.0,satisfied +23835,30357,Female,Loyal Customer,42,Business travel,Business,641,1,1,1,1,5,5,5,3,3,3,3,2,3,2,0,0.0,satisfied +23836,103983,Female,Loyal Customer,54,Business travel,Business,1592,5,5,5,5,5,3,5,4,4,4,4,3,4,4,10,0.0,satisfied +23837,115294,Male,Loyal Customer,41,Business travel,Business,1715,1,1,1,1,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +23838,107903,Male,Loyal Customer,60,Business travel,Business,3126,2,1,1,1,3,4,3,2,2,3,2,1,2,4,81,93.0,neutral or dissatisfied +23839,114954,Female,Loyal Customer,45,Business travel,Business,1982,4,4,4,4,2,4,4,5,5,5,5,4,5,4,34,23.0,satisfied +23840,24295,Female,Loyal Customer,59,Business travel,Eco Plus,147,5,1,1,1,3,5,2,5,5,5,5,2,5,4,0,0.0,satisfied +23841,62171,Male,Loyal Customer,33,Business travel,Business,2454,5,5,5,5,4,4,4,4,4,3,5,5,5,4,12,0.0,satisfied +23842,44491,Female,Loyal Customer,31,Business travel,Eco Plus,844,2,3,3,3,2,2,2,2,1,3,3,3,4,2,10,6.0,neutral or dissatisfied +23843,107629,Male,Loyal Customer,25,Personal Travel,Eco,423,3,4,3,3,2,3,2,2,4,4,4,5,4,2,0,11.0,neutral or dissatisfied +23844,20995,Female,Loyal Customer,24,Business travel,Eco Plus,689,4,5,5,5,4,4,3,4,4,2,3,1,3,4,0,1.0,satisfied +23845,79802,Male,Loyal Customer,35,Business travel,Business,3594,3,3,3,3,2,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +23846,110530,Female,Loyal Customer,48,Business travel,Business,2540,5,5,5,5,4,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +23847,12273,Female,disloyal Customer,49,Business travel,Eco,190,3,0,3,2,4,3,2,4,3,2,2,4,2,4,84,89.0,neutral or dissatisfied +23848,59972,Male,disloyal Customer,25,Business travel,Eco,997,3,2,2,3,2,2,2,2,1,2,2,5,1,2,5,0.0,neutral or dissatisfied +23849,17348,Male,Loyal Customer,58,Business travel,Eco,563,2,3,3,3,2,2,2,2,1,4,3,1,3,2,0,0.0,neutral or dissatisfied +23850,4121,Male,Loyal Customer,41,Business travel,Business,2099,2,2,2,2,4,4,4,4,4,5,4,4,5,4,105,169.0,satisfied +23851,17975,Male,Loyal Customer,11,Personal Travel,Eco Plus,500,3,4,3,1,1,3,1,1,4,4,5,5,4,1,2,11.0,neutral or dissatisfied +23852,12887,Male,Loyal Customer,49,Business travel,Business,456,1,1,5,1,3,5,2,4,4,4,4,5,4,4,1,31.0,satisfied +23853,129452,Female,Loyal Customer,24,Personal Travel,Eco,414,3,4,4,3,3,4,3,3,2,5,4,5,5,3,11,14.0,neutral or dissatisfied +23854,95543,Male,Loyal Customer,31,Personal Travel,Eco Plus,192,3,5,3,3,1,3,1,1,4,2,4,4,4,1,19,4.0,neutral or dissatisfied +23855,64546,Male,disloyal Customer,22,Business travel,Business,190,5,4,5,1,3,5,4,3,3,4,5,4,5,3,0,0.0,satisfied +23856,103796,Male,Loyal Customer,65,Business travel,Eco,882,2,4,4,4,2,2,2,2,3,5,3,1,3,2,0,0.0,neutral or dissatisfied +23857,34973,Female,Loyal Customer,54,Business travel,Eco,273,2,2,2,2,3,1,1,2,2,2,2,4,2,4,0,4.0,neutral or dissatisfied +23858,72083,Female,Loyal Customer,69,Business travel,Business,2673,3,3,3,3,5,4,4,3,3,3,3,2,3,1,7,0.0,neutral or dissatisfied +23859,85451,Female,Loyal Customer,50,Business travel,Business,214,4,5,4,4,3,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +23860,34722,Male,Loyal Customer,18,Business travel,Business,209,5,5,5,5,4,4,3,4,2,3,4,4,1,4,0,0.0,satisfied +23861,105558,Female,Loyal Customer,23,Business travel,Business,2290,2,5,5,5,2,2,2,2,4,4,3,1,2,2,66,61.0,neutral or dissatisfied +23862,8334,Female,Loyal Customer,26,Business travel,Business,661,3,3,3,3,4,4,4,4,3,5,4,4,5,4,43,38.0,satisfied +23863,107773,Female,disloyal Customer,25,Business travel,Eco Plus,251,1,2,1,3,1,1,1,1,1,2,3,3,3,1,2,0.0,neutral or dissatisfied +23864,40704,Female,Loyal Customer,38,Business travel,Business,541,2,2,2,2,3,3,4,5,5,5,5,1,5,1,11,9.0,satisfied +23865,95394,Male,Loyal Customer,37,Personal Travel,Eco,239,4,4,4,4,3,4,1,3,4,2,1,1,5,3,50,46.0,neutral or dissatisfied +23866,74912,Female,Loyal Customer,45,Business travel,Business,2475,4,4,4,4,4,3,4,5,5,5,5,5,5,5,0,0.0,satisfied +23867,39512,Male,Loyal Customer,43,Business travel,Eco,852,3,4,4,4,3,3,3,3,4,1,4,3,4,3,0,24.0,neutral or dissatisfied +23868,65582,Female,Loyal Customer,46,Business travel,Business,3796,2,3,3,3,4,1,1,2,2,3,2,1,2,4,0,4.0,neutral or dissatisfied +23869,31291,Female,disloyal Customer,24,Business travel,Eco,533,3,4,3,3,2,3,2,2,3,1,4,4,3,2,3,1.0,neutral or dissatisfied +23870,21539,Female,Loyal Customer,57,Personal Travel,Eco,399,2,5,2,3,2,5,5,3,3,2,3,4,3,5,0,4.0,neutral or dissatisfied +23871,28806,Male,Loyal Customer,40,Business travel,Eco,1050,5,4,3,4,5,5,5,5,4,3,5,1,3,5,32,33.0,satisfied +23872,42669,Male,Loyal Customer,30,Business travel,Business,516,2,2,2,2,5,5,5,5,4,1,3,1,1,5,0,0.0,satisfied +23873,52211,Female,Loyal Customer,47,Business travel,Business,2234,1,1,1,1,5,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +23874,42836,Female,disloyal Customer,33,Business travel,Eco,328,2,0,2,3,2,2,2,2,2,3,5,2,3,2,1,6.0,neutral or dissatisfied +23875,4209,Female,Loyal Customer,27,Business travel,Business,2562,1,2,2,2,1,1,1,1,1,4,4,1,4,1,43,22.0,neutral or dissatisfied +23876,14865,Male,disloyal Customer,23,Business travel,Eco,240,0,4,0,3,1,0,1,1,1,4,5,4,4,1,0,0.0,satisfied +23877,59192,Male,Loyal Customer,53,Business travel,Business,1440,4,4,4,4,5,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +23878,8451,Male,Loyal Customer,56,Business travel,Eco,1379,1,3,3,3,1,1,1,1,2,5,4,3,4,1,0,0.0,neutral or dissatisfied +23879,113773,Male,Loyal Customer,61,Personal Travel,Eco,197,2,4,0,4,1,0,1,1,1,3,4,4,4,1,46,27.0,neutral or dissatisfied +23880,116375,Female,Loyal Customer,28,Personal Travel,Eco,337,4,5,4,2,4,4,4,4,4,4,5,5,4,4,0,0.0,satisfied +23881,86912,Female,Loyal Customer,55,Business travel,Business,341,1,0,0,3,5,3,4,1,1,0,1,3,1,2,4,5.0,neutral or dissatisfied +23882,25700,Male,Loyal Customer,39,Business travel,Eco,447,4,3,4,3,4,4,4,4,1,1,2,3,5,4,18,15.0,satisfied +23883,24274,Male,Loyal Customer,42,Personal Travel,Eco,170,1,1,1,4,3,1,3,3,3,4,3,4,4,3,0,0.0,neutral or dissatisfied +23884,60245,Female,Loyal Customer,19,Personal Travel,Eco,1546,2,5,2,3,4,2,3,4,5,4,4,4,5,4,111,101.0,neutral or dissatisfied +23885,59000,Female,Loyal Customer,60,Business travel,Business,1744,4,4,4,4,3,4,5,4,4,4,4,4,4,5,102,85.0,satisfied +23886,120427,Male,disloyal Customer,21,Business travel,Eco,366,3,2,3,4,5,3,5,5,2,5,4,4,4,5,0,0.0,neutral or dissatisfied +23887,110684,Male,Loyal Customer,44,Personal Travel,Eco,945,1,2,1,4,5,1,5,5,3,3,3,1,4,5,0,12.0,neutral or dissatisfied +23888,20118,Male,Loyal Customer,44,Business travel,Business,2691,1,3,2,2,2,3,3,1,1,1,1,4,1,3,18,13.0,neutral or dissatisfied +23889,100286,Male,Loyal Customer,43,Business travel,Business,2624,4,4,4,4,4,5,5,2,2,3,2,3,2,5,0,0.0,satisfied +23890,114656,Female,disloyal Customer,30,Business travel,Business,480,3,3,3,3,2,3,2,2,3,4,4,3,4,2,11,32.0,neutral or dissatisfied +23891,50145,Female,Loyal Customer,23,Business travel,Business,3256,2,5,5,5,3,3,2,3,3,2,4,3,3,3,0,25.0,neutral or dissatisfied +23892,12587,Male,Loyal Customer,39,Business travel,Eco,542,5,5,5,5,5,5,5,5,1,2,3,2,5,5,17,14.0,satisfied +23893,9562,Male,Loyal Customer,45,Business travel,Business,283,0,0,0,2,4,5,4,2,2,2,2,4,2,4,0,0.0,satisfied +23894,103648,Male,Loyal Customer,40,Business travel,Business,2091,2,2,2,2,2,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +23895,88738,Male,Loyal Customer,52,Personal Travel,Eco,444,2,4,2,1,2,2,2,2,4,2,5,3,5,2,0,0.0,neutral or dissatisfied +23896,92018,Male,Loyal Customer,56,Business travel,Business,1522,2,2,2,2,2,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +23897,92937,Male,Loyal Customer,53,Personal Travel,Eco,134,3,3,3,4,3,3,3,3,1,5,4,1,4,3,19,11.0,neutral or dissatisfied +23898,10928,Male,Loyal Customer,34,Business travel,Eco,295,1,3,3,3,1,1,1,1,1,5,3,1,3,1,5,8.0,neutral or dissatisfied +23899,94648,Male,Loyal Customer,51,Business travel,Business,248,4,4,4,4,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +23900,95547,Male,Loyal Customer,16,Personal Travel,Eco Plus,496,2,5,2,2,2,2,2,2,4,2,1,4,3,2,0,0.0,neutral or dissatisfied +23901,39323,Female,Loyal Customer,38,Personal Travel,Eco,67,1,5,1,1,1,1,1,1,3,5,4,4,5,1,0,0.0,neutral or dissatisfied +23902,61213,Male,disloyal Customer,62,Business travel,Eco,862,3,4,4,4,4,4,4,4,4,4,3,2,4,4,70,76.0,neutral or dissatisfied +23903,75681,Male,disloyal Customer,28,Business travel,Business,813,3,3,3,3,4,3,2,4,2,2,3,2,2,4,13,7.0,neutral or dissatisfied +23904,84620,Male,Loyal Customer,47,Business travel,Eco,269,2,3,3,3,2,2,2,2,3,2,3,3,3,2,34,21.0,neutral or dissatisfied +23905,94967,Male,Loyal Customer,35,Business travel,Business,1643,2,4,4,4,1,4,4,2,2,2,2,3,2,2,4,0.0,neutral or dissatisfied +23906,53406,Male,Loyal Customer,52,Personal Travel,Business,2253,3,5,3,5,3,4,2,3,2,3,5,2,5,2,0,37.0,neutral or dissatisfied +23907,53585,Female,Loyal Customer,62,Personal Travel,Eco,391,3,4,3,3,3,5,5,3,3,3,3,3,3,3,12,4.0,neutral or dissatisfied +23908,10509,Female,Loyal Customer,60,Business travel,Business,3969,3,5,3,3,3,4,5,5,5,4,5,4,5,5,0,0.0,satisfied +23909,100860,Female,Loyal Customer,28,Personal Travel,Eco Plus,711,2,4,2,5,1,2,1,1,4,2,3,3,4,1,0,10.0,neutral or dissatisfied +23910,34022,Male,Loyal Customer,30,Personal Travel,Eco,1617,1,4,1,4,3,1,3,3,2,5,2,1,3,3,0,0.0,neutral or dissatisfied +23911,70460,Male,Loyal Customer,22,Business travel,Business,3642,5,5,4,5,5,5,5,5,5,5,5,4,5,5,3,0.0,satisfied +23912,113893,Male,Loyal Customer,44,Business travel,Business,2295,5,5,5,5,4,5,4,4,4,4,4,3,4,5,10,5.0,satisfied +23913,79845,Male,Loyal Customer,54,Business travel,Business,950,5,5,5,5,2,4,4,3,3,3,3,5,3,4,0,0.0,satisfied +23914,125411,Female,Loyal Customer,39,Business travel,Business,735,2,2,2,2,5,5,5,2,2,2,2,3,2,5,0,0.0,satisfied +23915,35246,Male,Loyal Customer,34,Business travel,Eco,944,4,5,5,5,4,4,4,4,4,2,1,1,1,4,22,29.0,neutral or dissatisfied +23916,43598,Male,Loyal Customer,47,Business travel,Eco,252,4,1,1,1,4,4,4,4,3,3,1,2,1,4,0,0.0,satisfied +23917,115241,Female,Loyal Customer,53,Business travel,Business,308,4,4,3,4,4,4,4,4,4,4,4,3,4,5,0,1.0,satisfied +23918,88375,Female,disloyal Customer,27,Business travel,Eco,250,3,4,4,4,1,4,1,1,2,4,4,2,3,1,3,1.0,neutral or dissatisfied +23919,44794,Male,Loyal Customer,62,Business travel,Eco Plus,1250,4,5,2,5,4,4,4,4,1,5,4,1,4,4,0,0.0,satisfied +23920,113592,Male,Loyal Customer,32,Business travel,Eco,258,5,5,5,5,5,4,5,5,4,1,1,4,5,5,0,2.0,satisfied +23921,94037,Female,Loyal Customer,47,Business travel,Business,239,2,2,5,2,3,5,5,5,5,4,5,3,5,4,3,0.0,satisfied +23922,76635,Female,disloyal Customer,18,Business travel,Eco,547,5,0,5,4,4,5,1,4,4,3,5,3,4,4,0,0.0,satisfied +23923,17475,Female,Loyal Customer,45,Business travel,Eco,241,4,5,2,5,1,3,3,4,4,4,4,1,4,1,0,0.0,neutral or dissatisfied +23924,43923,Male,Loyal Customer,18,Personal Travel,Eco,199,3,5,0,3,3,0,3,3,5,3,5,3,5,3,0,0.0,neutral or dissatisfied +23925,59789,Female,Loyal Customer,26,Personal Travel,Eco,895,2,4,2,3,3,2,5,3,4,2,4,5,5,3,1,0.0,neutral or dissatisfied +23926,85196,Female,Loyal Customer,42,Business travel,Business,1945,1,1,1,1,2,5,5,4,4,4,4,4,4,5,11,1.0,satisfied +23927,10993,Male,Loyal Customer,59,Business travel,Eco,201,5,1,1,1,5,5,5,5,5,4,5,3,5,5,57,51.0,satisfied +23928,104587,Female,disloyal Customer,59,Business travel,Eco,369,1,0,1,3,3,1,3,3,1,1,5,2,2,3,84,63.0,neutral or dissatisfied +23929,91140,Male,Loyal Customer,48,Personal Travel,Eco,594,4,1,4,2,2,4,2,2,1,4,3,1,2,2,7,8.0,neutral or dissatisfied +23930,27560,Male,Loyal Customer,34,Personal Travel,Eco,937,2,4,2,2,2,2,2,2,1,5,2,3,3,2,20,21.0,neutral or dissatisfied +23931,773,Male,Loyal Customer,54,Business travel,Business,2218,2,1,1,1,3,4,3,2,2,2,2,2,2,4,0,0.0,neutral or dissatisfied +23932,30757,Male,Loyal Customer,25,Personal Travel,Eco Plus,977,3,4,3,4,1,3,1,1,4,3,4,4,4,1,5,0.0,neutral or dissatisfied +23933,103674,Male,disloyal Customer,24,Business travel,Eco,251,3,2,4,2,1,4,1,1,2,4,1,4,2,1,39,48.0,neutral or dissatisfied +23934,111515,Male,Loyal Customer,10,Personal Travel,Eco,391,2,4,2,3,4,2,2,4,4,1,4,3,2,4,11,5.0,neutral or dissatisfied +23935,11599,Male,disloyal Customer,17,Business travel,Eco,468,2,0,2,1,2,2,2,2,1,3,3,1,2,2,0,0.0,neutral or dissatisfied +23936,53647,Male,Loyal Customer,27,Business travel,Eco Plus,1874,0,0,0,1,5,0,2,5,5,4,5,5,2,5,0,0.0,satisfied +23937,127479,Female,disloyal Customer,21,Business travel,Business,1226,4,0,4,5,4,4,4,4,5,4,5,4,5,4,0,0.0,satisfied +23938,31967,Male,Loyal Customer,46,Business travel,Business,2810,5,5,4,5,3,4,5,4,4,4,5,3,4,5,0,0.0,satisfied +23939,92532,Male,Loyal Customer,64,Personal Travel,Eco,1947,1,4,1,5,2,1,2,2,4,2,5,3,5,2,8,0.0,neutral or dissatisfied +23940,9560,Female,Loyal Customer,64,Business travel,Eco,229,2,5,5,5,3,3,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +23941,73958,Male,Loyal Customer,10,Personal Travel,Eco,2342,2,3,2,3,4,2,4,4,3,4,3,2,4,4,2,0.0,neutral or dissatisfied +23942,9968,Male,Loyal Customer,67,Personal Travel,Eco,508,2,2,5,3,5,5,5,5,1,5,3,1,4,5,0,0.0,neutral or dissatisfied +23943,113139,Male,Loyal Customer,41,Business travel,Business,2669,2,2,2,2,4,5,4,3,3,3,3,3,3,4,0,0.0,satisfied +23944,29491,Male,Loyal Customer,43,Business travel,Eco,1107,1,0,0,3,2,1,2,2,4,5,4,1,4,2,0,0.0,neutral or dissatisfied +23945,6921,Female,Loyal Customer,17,Personal Travel,Eco,265,3,3,3,5,5,3,3,5,2,3,4,4,4,5,0,0.0,neutral or dissatisfied +23946,42794,Female,Loyal Customer,60,Business travel,Business,2012,4,4,4,4,2,4,4,5,5,5,5,3,5,5,30,44.0,satisfied +23947,114360,Female,Loyal Customer,41,Business travel,Business,862,5,5,4,5,2,5,5,5,5,5,5,3,5,3,4,24.0,satisfied +23948,21350,Male,Loyal Customer,8,Personal Travel,Eco,761,5,4,5,2,2,5,2,2,4,4,5,4,5,2,0,0.0,satisfied +23949,76367,Female,disloyal Customer,39,Business travel,Business,931,1,0,0,1,5,0,5,5,4,3,4,3,5,5,0,0.0,neutral or dissatisfied +23950,82233,Male,Loyal Customer,64,Personal Travel,Eco,405,3,5,3,5,3,3,3,3,5,5,5,4,5,3,83,74.0,neutral or dissatisfied +23951,129340,Male,disloyal Customer,26,Business travel,Eco,975,4,4,4,1,2,4,2,2,2,3,2,3,5,2,0,0.0,neutral or dissatisfied +23952,25604,Male,Loyal Customer,22,Personal Travel,Business,666,1,2,1,4,5,1,5,5,2,3,4,1,3,5,44,42.0,neutral or dissatisfied +23953,24094,Male,Loyal Customer,19,Business travel,Business,3424,5,5,5,5,5,5,5,5,1,2,1,4,5,5,0,0.0,satisfied +23954,436,Female,Loyal Customer,60,Personal Travel,Business,396,1,5,1,3,3,5,1,2,2,1,3,5,2,2,0,0.0,neutral or dissatisfied +23955,52936,Male,Loyal Customer,27,Personal Travel,Eco,679,4,3,4,3,1,4,1,1,4,4,4,2,3,1,0,0.0,neutral or dissatisfied +23956,127692,Female,Loyal Customer,46,Business travel,Business,2133,5,5,5,5,2,5,5,5,5,5,5,3,5,3,0,4.0,satisfied +23957,81158,Female,Loyal Customer,29,Business travel,Business,700,3,3,5,3,1,2,1,1,5,2,5,3,5,1,0,0.0,satisfied +23958,39186,Female,Loyal Customer,38,Personal Travel,Eco,287,1,1,1,3,5,1,5,5,1,3,2,2,3,5,0,0.0,neutral or dissatisfied +23959,74498,Female,Loyal Customer,41,Business travel,Eco,1126,4,1,1,1,5,4,5,5,2,2,3,2,4,5,14,41.0,neutral or dissatisfied +23960,65304,Female,Loyal Customer,67,Personal Travel,Eco Plus,551,1,4,1,4,5,3,4,5,5,1,5,4,5,4,0,5.0,neutral or dissatisfied +23961,40999,Female,Loyal Customer,22,Business travel,Business,1362,1,1,1,1,3,3,3,3,3,3,4,5,1,3,0,0.0,satisfied +23962,120085,Female,Loyal Customer,59,Personal Travel,Eco,683,3,5,3,3,2,4,5,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +23963,63824,Female,Loyal Customer,49,Personal Travel,Business,1192,2,4,2,4,2,1,3,3,4,5,4,3,3,3,181,193.0,neutral or dissatisfied +23964,87910,Female,Loyal Customer,46,Business travel,Business,1568,1,1,1,1,2,4,4,5,5,5,5,5,5,4,45,42.0,satisfied +23965,46807,Male,Loyal Customer,37,Business travel,Eco,844,4,4,4,4,4,4,4,4,2,5,5,3,3,4,13,6.0,satisfied +23966,92973,Female,Loyal Customer,43,Business travel,Business,738,5,5,3,5,5,5,4,4,4,4,4,4,4,3,0,42.0,satisfied +23967,80370,Female,disloyal Customer,39,Business travel,Business,368,4,4,4,1,3,4,3,3,5,2,5,4,5,3,0,0.0,neutral or dissatisfied +23968,2233,Male,Loyal Customer,27,Personal Travel,Eco,859,3,5,3,2,1,3,1,1,3,5,5,5,5,1,0,1.0,neutral or dissatisfied +23969,5852,Male,Loyal Customer,57,Business travel,Business,3611,5,5,5,5,3,4,5,5,5,5,5,4,5,5,0,4.0,satisfied +23970,119289,Female,Loyal Customer,37,Business travel,Business,3766,0,4,0,1,3,5,5,1,1,1,1,3,1,5,80,80.0,satisfied +23971,104602,Male,Loyal Customer,36,Personal Travel,Eco,369,4,5,4,4,2,4,2,2,2,5,1,1,2,2,74,88.0,neutral or dissatisfied +23972,122575,Male,Loyal Customer,40,Personal Travel,Business,728,3,4,3,3,4,4,4,5,5,3,5,1,5,4,0,0.0,neutral or dissatisfied +23973,35636,Male,Loyal Customer,40,Business travel,Eco,1626,4,1,1,1,4,4,4,4,5,2,4,5,4,4,0,23.0,satisfied +23974,58794,Male,Loyal Customer,41,Business travel,Eco,1005,3,2,2,2,3,3,3,3,2,4,3,2,3,3,3,42.0,neutral or dissatisfied +23975,9577,Female,Loyal Customer,38,Business travel,Business,288,3,2,2,2,5,4,3,3,3,3,3,1,3,3,0,10.0,neutral or dissatisfied +23976,106422,Female,Loyal Customer,35,Personal Travel,Eco,551,5,1,5,4,1,5,1,1,4,1,4,2,4,1,0,0.0,satisfied +23977,112251,Male,Loyal Customer,58,Business travel,Business,1506,2,2,3,2,5,5,4,5,5,5,5,4,5,5,12,0.0,satisfied +23978,24710,Female,Loyal Customer,38,Business travel,Eco Plus,397,4,2,2,2,4,4,4,4,3,4,4,3,1,4,56,77.0,satisfied +23979,128649,Female,Loyal Customer,69,Personal Travel,Eco Plus,954,3,5,3,5,2,4,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +23980,120167,Female,Loyal Customer,38,Business travel,Business,119,0,4,0,1,3,5,5,3,3,5,5,3,3,3,0,5.0,satisfied +23981,127601,Male,Loyal Customer,26,Business travel,Business,1773,4,4,4,4,4,5,4,4,3,5,3,3,4,4,0,0.0,satisfied +23982,46131,Female,Loyal Customer,48,Business travel,Business,3825,4,4,5,4,1,1,3,4,4,4,4,2,4,5,0,0.0,satisfied +23983,55854,Male,disloyal Customer,21,Business travel,Business,1416,5,4,5,2,5,5,5,5,4,4,4,3,5,5,0,0.0,satisfied +23984,13730,Male,Loyal Customer,55,Business travel,Business,2987,2,2,3,2,3,3,4,4,4,4,4,4,4,1,70,53.0,satisfied +23985,106378,Female,Loyal Customer,42,Business travel,Business,3399,1,1,1,1,3,4,4,4,4,4,4,5,4,4,27,22.0,satisfied +23986,59113,Male,Loyal Customer,25,Personal Travel,Eco,1846,3,3,2,2,4,2,4,4,3,1,4,5,3,4,11,0.0,neutral or dissatisfied +23987,28621,Male,Loyal Customer,68,Business travel,Eco,2409,4,2,1,1,4,4,4,4,5,5,3,5,3,4,0,0.0,satisfied +23988,118570,Female,Loyal Customer,45,Business travel,Eco,370,1,4,4,4,1,3,4,1,1,1,1,2,1,2,91,76.0,neutral or dissatisfied +23989,56811,Female,disloyal Customer,27,Business travel,Eco,782,1,1,1,3,5,1,5,5,4,3,2,4,3,5,8,21.0,neutral or dissatisfied +23990,7622,Male,Loyal Customer,52,Business travel,Business,3830,1,1,2,1,4,5,5,5,5,4,5,3,5,5,0,0.0,satisfied +23991,19092,Female,Loyal Customer,54,Personal Travel,Eco,229,3,5,0,3,3,5,4,5,5,0,5,4,5,4,0,0.0,neutral or dissatisfied +23992,115778,Male,disloyal Customer,17,Business travel,Eco,337,2,1,2,4,3,2,3,3,1,3,3,2,4,3,30,23.0,neutral or dissatisfied +23993,23821,Female,Loyal Customer,56,Personal Travel,Eco,374,1,1,1,2,2,1,2,4,4,1,4,3,4,4,10,24.0,neutral or dissatisfied +23994,68079,Male,disloyal Customer,27,Business travel,Eco,813,3,3,3,3,2,3,2,2,1,5,3,3,4,2,17,15.0,neutral or dissatisfied +23995,38343,Male,Loyal Customer,25,Business travel,Business,1050,2,4,2,2,2,2,2,2,2,5,5,1,1,2,0,0.0,satisfied +23996,115161,Male,Loyal Customer,54,Business travel,Business,3106,4,4,4,4,3,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +23997,80911,Male,Loyal Customer,67,Business travel,Business,341,3,3,3,3,3,4,5,4,4,4,4,3,4,4,38,23.0,satisfied +23998,42453,Female,Loyal Customer,58,Personal Travel,Eco,926,2,4,2,5,2,4,4,3,3,2,4,4,3,5,0,0.0,neutral or dissatisfied +23999,23469,Female,Loyal Customer,61,Business travel,Business,176,3,5,5,5,1,4,3,1,1,1,3,2,1,2,0,0.0,neutral or dissatisfied +24000,70684,Female,Loyal Customer,55,Personal Travel,Eco,447,3,5,3,3,3,5,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +24001,107159,Male,disloyal Customer,9,Business travel,Eco,668,2,3,2,4,4,2,4,4,1,4,3,3,3,4,121,103.0,neutral or dissatisfied +24002,112037,Male,disloyal Customer,37,Business travel,Business,1123,3,3,3,3,5,3,5,5,5,3,5,3,4,5,5,0.0,neutral or dissatisfied +24003,55633,Male,Loyal Customer,72,Business travel,Business,1824,4,4,4,4,4,3,5,5,5,5,5,5,5,4,0,0.0,satisfied +24004,21750,Female,Loyal Customer,15,Personal Travel,Eco,563,2,1,2,2,3,2,3,3,3,4,2,4,2,3,0,0.0,neutral or dissatisfied +24005,55669,Male,Loyal Customer,23,Business travel,Business,1025,2,2,3,2,4,4,4,4,3,5,5,4,4,4,0,0.0,satisfied +24006,126812,Male,disloyal Customer,24,Business travel,Eco,2296,4,4,4,4,4,4,4,4,5,5,4,5,4,4,0,0.0,satisfied +24007,7562,Male,Loyal Customer,59,Business travel,Business,3451,1,1,1,1,3,4,5,4,4,4,4,4,4,3,0,0.0,satisfied +24008,118357,Male,Loyal Customer,68,Personal Travel,Eco,602,4,4,4,3,3,4,3,3,2,1,3,2,4,3,13,14.0,neutral or dissatisfied +24009,62493,Female,Loyal Customer,56,Business travel,Business,1846,1,1,1,1,5,3,5,5,5,4,5,4,5,5,40,27.0,satisfied +24010,1667,Male,Loyal Customer,68,Personal Travel,Eco,435,2,4,2,4,2,2,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +24011,60824,Male,Loyal Customer,15,Personal Travel,Eco,524,1,4,1,3,4,1,1,4,5,3,4,5,4,4,11,32.0,neutral or dissatisfied +24012,70801,Female,Loyal Customer,11,Personal Travel,Eco Plus,328,4,5,4,4,3,4,3,3,2,2,5,4,4,3,0,0.0,satisfied +24013,124837,Female,Loyal Customer,8,Personal Travel,Eco,280,4,4,4,1,2,4,2,2,4,5,3,3,3,2,48,55.0,neutral or dissatisfied +24014,58250,Male,Loyal Customer,54,Personal Travel,Eco Plus,925,4,5,4,3,5,4,5,5,3,3,4,3,4,5,3,0.0,neutral or dissatisfied +24015,88390,Female,Loyal Customer,39,Business travel,Eco,404,1,5,5,5,1,1,1,1,2,2,4,4,3,1,0,0.0,neutral or dissatisfied +24016,53584,Male,Loyal Customer,34,Business travel,Business,391,3,3,3,3,1,4,1,4,4,4,4,1,4,4,75,67.0,satisfied +24017,101063,Male,Loyal Customer,60,Business travel,Business,1723,2,2,2,2,3,4,4,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +24018,79057,Male,Loyal Customer,63,Business travel,Eco,356,1,1,1,1,1,1,1,1,4,2,2,2,3,1,66,76.0,neutral or dissatisfied +24019,103086,Female,Loyal Customer,50,Personal Travel,Eco,460,3,3,3,3,3,4,4,4,4,3,2,2,4,1,27,22.0,neutral or dissatisfied +24020,66436,Female,disloyal Customer,26,Business travel,Business,1217,3,4,4,2,2,4,5,2,5,4,5,5,5,2,0,0.0,neutral or dissatisfied +24021,121405,Male,Loyal Customer,47,Business travel,Business,3175,0,0,0,1,2,4,5,4,4,2,2,5,4,5,0,100.0,satisfied +24022,19523,Female,disloyal Customer,26,Business travel,Business,173,5,0,5,3,2,5,2,2,3,2,5,5,4,2,51,57.0,satisfied +24023,49633,Female,Loyal Customer,33,Business travel,Business,2213,0,1,1,5,2,5,3,3,3,3,3,1,3,5,0,0.0,satisfied +24024,37841,Male,Loyal Customer,33,Business travel,Business,937,5,5,5,5,4,4,4,4,3,1,1,4,2,4,20,27.0,satisfied +24025,115541,Male,Loyal Customer,45,Business travel,Business,3318,2,4,4,4,2,2,2,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +24026,29636,Male,Loyal Customer,54,Business travel,Eco,1048,2,3,3,3,2,2,2,2,3,4,4,3,4,2,0,0.0,neutral or dissatisfied +24027,7558,Female,Loyal Customer,59,Personal Travel,Eco,606,4,5,4,2,4,5,4,3,3,4,3,4,3,3,1,0.0,neutral or dissatisfied +24028,16911,Male,Loyal Customer,29,Personal Travel,Eco,746,1,5,1,1,1,1,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +24029,76817,Female,Loyal Customer,27,Business travel,Eco Plus,546,4,1,1,1,4,4,4,4,3,5,4,3,3,4,0,12.0,neutral or dissatisfied +24030,91525,Female,Loyal Customer,57,Personal Travel,Business,680,3,4,3,3,3,4,4,3,3,3,4,5,3,5,12,14.0,neutral or dissatisfied +24031,80250,Male,Loyal Customer,32,Personal Travel,Eco,1269,4,1,4,3,1,4,1,1,4,4,3,1,2,1,0,11.0,neutral or dissatisfied +24032,48219,Female,Loyal Customer,9,Personal Travel,Eco,192,3,4,0,3,3,0,3,3,3,4,4,5,5,3,3,8.0,neutral or dissatisfied +24033,103038,Female,Loyal Customer,49,Business travel,Business,460,2,2,2,2,2,4,4,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +24034,51377,Female,Loyal Customer,49,Personal Travel,Eco Plus,77,3,4,3,3,4,4,4,3,3,3,3,5,3,4,0,0.0,neutral or dissatisfied +24035,70143,Male,Loyal Customer,31,Personal Travel,Eco,550,1,3,1,3,3,1,1,3,3,4,3,4,3,3,0,0.0,neutral or dissatisfied +24036,29885,Male,Loyal Customer,36,Business travel,Business,95,1,1,1,1,4,2,1,4,4,4,4,2,4,4,0,0.0,satisfied +24037,80361,Male,disloyal Customer,32,Business travel,Eco,422,3,4,3,4,2,3,5,2,1,2,3,4,4,2,0,0.0,neutral or dissatisfied +24038,67920,Male,Loyal Customer,30,Personal Travel,Eco,1205,2,1,2,3,5,2,5,5,2,2,3,2,3,5,20,16.0,neutral or dissatisfied +24039,108521,Female,Loyal Customer,31,Business travel,Eco Plus,519,3,5,5,5,3,3,3,3,1,3,4,1,4,3,118,115.0,neutral or dissatisfied +24040,9830,Female,Loyal Customer,43,Business travel,Business,476,1,1,4,1,5,5,5,2,5,1,5,5,5,5,262,279.0,satisfied +24041,5331,Female,Loyal Customer,43,Business travel,Business,1916,2,2,2,2,2,4,4,4,4,4,4,5,4,5,17,0.0,satisfied +24042,55307,Male,Loyal Customer,70,Personal Travel,Eco,2072,2,5,2,3,3,2,4,3,3,3,5,4,4,3,0,0.0,neutral or dissatisfied +24043,77234,Female,Loyal Customer,18,Business travel,Business,1590,4,4,4,4,5,5,5,5,5,3,4,5,4,5,0,0.0,satisfied +24044,101082,Male,Loyal Customer,57,Personal Travel,Business,1235,1,2,2,3,2,1,1,4,5,3,4,1,3,1,164,142.0,neutral or dissatisfied +24045,22908,Male,Loyal Customer,22,Business travel,Business,2088,2,2,2,2,5,5,5,5,3,4,5,5,4,5,78,74.0,satisfied +24046,93523,Male,disloyal Customer,39,Business travel,Business,1315,1,1,1,4,1,1,1,1,4,4,4,5,5,1,0,0.0,neutral or dissatisfied +24047,67152,Female,disloyal Customer,47,Business travel,Eco,719,4,4,4,4,2,4,2,2,4,3,3,4,3,2,12,32.0,neutral or dissatisfied +24048,34783,Male,disloyal Customer,56,Personal Travel,Eco,209,4,4,4,3,1,4,1,1,3,4,4,2,1,1,0,0.0,neutral or dissatisfied +24049,37201,Female,Loyal Customer,69,Personal Travel,Eco Plus,1288,1,4,1,2,3,4,5,2,2,1,2,4,2,4,32,24.0,neutral or dissatisfied +24050,37603,Male,Loyal Customer,49,Personal Travel,Eco,1076,2,4,2,2,3,2,3,3,5,4,3,4,3,3,0,0.0,neutral or dissatisfied +24051,127128,Female,Loyal Customer,33,Personal Travel,Eco,370,5,5,5,4,1,5,1,1,2,5,5,1,2,1,0,0.0,satisfied +24052,61936,Female,disloyal Customer,17,Business travel,Eco Plus,550,3,1,3,3,1,3,1,1,1,2,4,2,4,1,17,24.0,neutral or dissatisfied +24053,86025,Female,Loyal Customer,46,Business travel,Eco,128,4,1,1,1,1,5,5,4,4,4,4,2,4,2,0,0.0,satisfied +24054,126916,Male,Loyal Customer,46,Business travel,Business,651,4,4,5,4,2,5,5,3,3,4,3,4,3,3,8,8.0,satisfied +24055,36283,Female,Loyal Customer,23,Personal Travel,Eco Plus,612,3,4,3,3,3,3,2,3,1,5,2,5,1,3,0,0.0,neutral or dissatisfied +24056,88184,Male,Loyal Customer,34,Business travel,Business,250,2,2,2,2,5,4,5,4,4,5,4,5,4,4,0,0.0,satisfied +24057,32250,Female,disloyal Customer,26,Business travel,Eco,102,2,3,2,2,1,2,1,1,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +24058,17119,Male,Loyal Customer,14,Personal Travel,Eco,821,3,2,3,4,5,3,5,5,4,3,3,2,4,5,2,0.0,neutral or dissatisfied +24059,77937,Male,disloyal Customer,26,Business travel,Business,332,4,0,3,5,4,3,2,4,5,2,5,4,5,4,25,30.0,satisfied +24060,12748,Female,Loyal Customer,55,Personal Travel,Eco,721,3,4,3,1,3,1,5,5,5,3,5,5,5,2,7,20.0,neutral or dissatisfied +24061,51079,Female,Loyal Customer,28,Personal Travel,Eco,308,4,5,4,5,5,4,2,5,4,2,4,5,4,5,8,4.0,neutral or dissatisfied +24062,61767,Male,Loyal Customer,29,Personal Travel,Eco,1379,2,3,2,4,2,2,2,2,1,3,4,4,3,2,6,0.0,neutral or dissatisfied +24063,118256,Female,disloyal Customer,30,Business travel,Eco,1328,2,2,2,3,4,2,4,4,3,5,4,3,4,4,0,5.0,neutral or dissatisfied +24064,15386,Male,Loyal Customer,41,Business travel,Eco,306,4,1,3,1,4,4,4,4,2,2,1,1,4,4,0,3.0,satisfied +24065,35910,Female,Loyal Customer,30,Business travel,Eco,2248,5,1,1,1,5,5,5,5,5,1,3,3,5,5,0,0.0,satisfied +24066,125171,Female,Loyal Customer,26,Personal Travel,Eco,1089,3,2,3,4,3,3,4,3,2,4,3,3,4,3,0,11.0,neutral or dissatisfied +24067,89685,Male,disloyal Customer,36,Business travel,Eco,544,4,5,4,4,1,4,1,1,4,5,1,4,2,1,0,0.0,neutral or dissatisfied +24068,58210,Female,Loyal Customer,14,Personal Travel,Eco,925,3,4,3,4,1,3,1,1,4,1,1,2,3,1,29,11.0,neutral or dissatisfied +24069,32548,Female,disloyal Customer,40,Business travel,Business,101,2,2,2,3,4,2,4,4,5,1,3,4,5,4,0,0.0,neutral or dissatisfied +24070,82246,Female,Loyal Customer,39,Business travel,Eco Plus,405,2,4,5,5,2,2,2,2,2,2,4,3,3,2,0,0.0,neutral or dissatisfied +24071,30348,Female,Loyal Customer,38,Personal Travel,Eco Plus,391,3,5,3,2,1,3,2,1,3,4,4,3,2,1,0,4.0,neutral or dissatisfied +24072,21780,Male,Loyal Customer,45,Business travel,Eco,352,5,1,1,1,5,5,5,5,1,1,1,3,2,5,26,,satisfied +24073,50212,Male,Loyal Customer,44,Business travel,Eco,337,3,5,2,5,3,3,3,3,3,2,3,2,4,3,0,11.0,neutral or dissatisfied +24074,96995,Female,disloyal Customer,36,Personal Travel,Eco,359,2,4,2,4,2,2,2,2,2,1,4,4,3,2,32,25.0,neutral or dissatisfied +24075,69978,Male,disloyal Customer,34,Business travel,Business,236,3,3,3,2,5,3,5,5,4,2,5,4,4,5,0,3.0,neutral or dissatisfied +24076,26064,Female,Loyal Customer,29,Business travel,Business,591,3,3,3,3,4,4,4,4,4,5,5,4,5,4,0,0.0,satisfied +24077,25703,Male,Loyal Customer,60,Business travel,Business,3462,1,1,1,1,1,5,1,5,5,5,5,3,5,4,0,0.0,satisfied +24078,108770,Male,Loyal Customer,21,Business travel,Business,1936,2,4,2,2,4,4,4,4,4,3,4,3,5,4,2,0.0,satisfied +24079,96537,Male,Loyal Customer,15,Personal Travel,Eco,302,2,4,2,3,2,2,2,2,5,5,4,5,4,2,1,5.0,neutral or dissatisfied +24080,46673,Female,Loyal Customer,19,Personal Travel,Eco,125,5,1,5,1,1,5,1,1,4,5,2,2,1,1,10,2.0,satisfied +24081,75647,Female,Loyal Customer,60,Business travel,Business,304,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +24082,16187,Male,Loyal Customer,15,Business travel,Business,277,2,1,1,1,2,2,2,2,4,4,3,2,3,2,44,45.0,neutral or dissatisfied +24083,28072,Female,Loyal Customer,21,Personal Travel,Eco,2607,3,3,3,4,3,5,5,4,4,5,4,5,1,5,0,9.0,neutral or dissatisfied +24084,92754,Male,Loyal Customer,61,Personal Travel,Eco,1276,2,4,2,3,4,2,3,4,5,4,4,5,5,4,0,0.0,neutral or dissatisfied +24085,50760,Female,Loyal Customer,36,Personal Travel,Eco,77,2,4,0,3,4,0,4,4,3,4,5,4,4,4,101,86.0,neutral or dissatisfied +24086,65909,Female,Loyal Customer,44,Business travel,Eco,569,3,4,4,4,2,3,3,3,3,3,3,1,3,2,0,0.0,neutral or dissatisfied +24087,40212,Female,Loyal Customer,45,Business travel,Eco,387,3,2,1,2,5,5,2,3,3,3,3,2,3,4,12,18.0,satisfied +24088,103312,Female,disloyal Customer,24,Business travel,Business,1139,4,4,4,1,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +24089,56136,Female,Loyal Customer,31,Business travel,Business,1400,5,5,5,5,5,5,5,5,4,3,5,3,4,5,0,0.0,satisfied +24090,108000,Male,Loyal Customer,37,Personal Travel,Eco,271,1,3,1,4,2,1,2,2,1,4,5,3,1,2,0,0.0,neutral or dissatisfied +24091,5202,Female,disloyal Customer,24,Business travel,Eco,293,1,0,1,4,1,1,1,1,4,3,5,5,5,1,9,0.0,neutral or dissatisfied +24092,41092,Female,Loyal Customer,39,Business travel,Business,316,2,5,5,5,2,3,3,2,2,2,2,2,2,1,40,39.0,neutral or dissatisfied +24093,91386,Male,Loyal Customer,16,Business travel,Business,2218,4,4,4,4,5,4,5,5,3,4,3,3,5,5,0,0.0,satisfied +24094,104478,Male,Loyal Customer,37,Personal Travel,Eco,1671,1,4,1,3,4,1,4,4,1,1,4,4,3,4,0,4.0,neutral or dissatisfied +24095,39914,Male,disloyal Customer,24,Business travel,Eco,1086,5,4,4,4,5,4,1,5,4,5,4,3,5,5,0,0.0,satisfied +24096,114409,Female,Loyal Customer,54,Business travel,Business,2170,1,1,1,1,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24097,67049,Female,Loyal Customer,60,Business travel,Business,3367,5,5,5,5,3,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +24098,1831,Female,Loyal Customer,70,Personal Travel,Eco,408,3,5,5,5,2,4,4,3,3,5,3,5,3,3,0,0.0,neutral or dissatisfied +24099,112794,Male,Loyal Customer,31,Business travel,Business,3067,2,1,2,2,4,4,4,4,5,4,4,5,4,4,29,12.0,satisfied +24100,48149,Female,Loyal Customer,31,Business travel,Business,2363,4,4,4,4,4,4,4,4,2,4,5,3,5,4,19,8.0,satisfied +24101,94365,Female,Loyal Customer,50,Business travel,Business,2625,4,4,2,4,2,4,5,4,4,4,4,3,4,4,3,0.0,satisfied +24102,120992,Female,disloyal Customer,30,Business travel,Eco,861,4,4,4,3,5,4,5,5,2,1,3,3,3,5,2,15.0,neutral or dissatisfied +24103,34220,Male,Loyal Customer,14,Personal Travel,Eco,1046,2,4,2,1,1,2,1,1,3,4,5,2,4,1,0,0.0,neutral or dissatisfied +24104,114931,Female,disloyal Customer,37,Business travel,Business,325,2,2,2,2,4,2,3,4,5,4,4,5,5,4,20,7.0,satisfied +24105,69188,Female,Loyal Customer,65,Personal Travel,Eco,187,3,2,3,2,5,3,3,5,5,3,5,4,5,1,3,0.0,neutral or dissatisfied +24106,7670,Female,disloyal Customer,34,Business travel,Business,641,1,2,2,3,5,2,1,5,3,4,4,3,4,5,4,0.0,neutral or dissatisfied +24107,68607,Female,Loyal Customer,59,Personal Travel,Eco,1739,2,5,2,1,4,4,5,1,1,2,1,3,1,5,1,0.0,neutral or dissatisfied +24108,67850,Male,Loyal Customer,30,Personal Travel,Eco,1464,3,4,3,5,3,3,3,3,5,5,5,4,5,3,0,0.0,neutral or dissatisfied +24109,121256,Male,Loyal Customer,38,Business travel,Business,575,1,4,1,4,4,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +24110,72896,Female,Loyal Customer,60,Business travel,Business,2193,3,3,3,3,5,4,5,4,4,4,4,3,4,4,7,0.0,satisfied +24111,390,Male,Loyal Customer,58,Business travel,Business,3432,4,1,4,4,2,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +24112,61859,Female,Loyal Customer,57,Personal Travel,Eco Plus,1346,2,5,2,3,2,3,5,5,5,2,5,5,5,4,0,0.0,neutral or dissatisfied +24113,1628,Female,disloyal Customer,28,Business travel,Business,999,1,1,1,3,2,1,4,2,4,3,3,2,4,2,0,0.0,neutral or dissatisfied +24114,19713,Male,Loyal Customer,44,Business travel,Business,2593,2,3,3,3,1,3,2,2,2,3,2,2,2,4,58,95.0,neutral or dissatisfied +24115,126205,Female,Loyal Customer,24,Business travel,Eco,328,5,5,5,5,5,4,4,5,3,5,4,4,3,5,17,5.0,neutral or dissatisfied +24116,5194,Male,Loyal Customer,34,Business travel,Business,351,4,4,4,4,3,5,5,4,4,4,4,5,4,4,37,31.0,satisfied +24117,121817,Male,Loyal Customer,45,Business travel,Business,449,3,3,3,3,2,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +24118,62440,Male,Loyal Customer,8,Personal Travel,Eco,1943,2,3,2,4,4,2,4,4,2,2,4,3,4,4,0,0.0,neutral or dissatisfied +24119,112625,Female,Loyal Customer,58,Personal Travel,Eco,602,2,1,2,2,5,1,2,3,3,2,3,1,3,4,0,0.0,neutral or dissatisfied +24120,87474,Female,Loyal Customer,44,Business travel,Business,373,4,4,4,4,3,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +24121,51989,Male,Loyal Customer,35,Personal Travel,Eco Plus,347,3,4,2,3,1,2,1,1,3,3,2,2,5,1,0,0.0,neutral or dissatisfied +24122,52296,Male,disloyal Customer,44,Business travel,Eco,237,3,1,3,2,4,3,4,4,3,3,3,1,2,4,0,6.0,neutral or dissatisfied +24123,55965,Male,Loyal Customer,54,Business travel,Business,1620,2,2,2,2,5,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +24124,89246,Male,Loyal Customer,51,Personal Travel,Eco Plus,1947,1,4,0,1,5,0,1,5,4,2,3,3,5,5,11,0.0,neutral or dissatisfied +24125,32777,Female,Loyal Customer,49,Business travel,Business,1986,2,1,1,1,4,4,3,3,3,3,2,2,3,3,0,3.0,neutral or dissatisfied +24126,22201,Male,Loyal Customer,25,Personal Travel,Eco,533,3,4,3,5,1,3,1,1,3,5,4,5,5,1,68,43.0,neutral or dissatisfied +24127,64644,Female,Loyal Customer,47,Business travel,Business,2326,1,5,5,5,3,2,2,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +24128,107151,Female,Loyal Customer,60,Business travel,Business,2722,1,1,1,1,4,4,5,5,5,5,5,5,5,5,15,0.0,satisfied +24129,61687,Male,Loyal Customer,59,Business travel,Business,1635,5,1,5,5,4,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +24130,116123,Male,Loyal Customer,8,Personal Travel,Eco,333,2,5,5,3,4,5,4,4,3,4,4,4,5,4,11,0.0,neutral or dissatisfied +24131,54144,Male,disloyal Customer,35,Business travel,Eco,1400,3,3,3,2,1,3,1,1,4,5,2,3,4,1,0,0.0,neutral or dissatisfied +24132,18344,Female,Loyal Customer,45,Business travel,Business,563,2,4,4,4,5,2,1,2,2,2,2,2,2,2,4,6.0,neutral or dissatisfied +24133,64934,Female,Loyal Customer,29,Business travel,Business,3873,3,3,3,3,3,3,3,3,3,4,4,4,3,3,19,,neutral or dissatisfied +24134,17609,Male,Loyal Customer,16,Personal Travel,Eco,196,3,4,0,4,4,0,4,4,1,1,3,4,3,4,0,0.0,neutral or dissatisfied +24135,92852,Male,Loyal Customer,7,Personal Travel,Eco Plus,1587,3,4,3,2,5,3,3,5,4,2,5,4,5,5,0,8.0,neutral or dissatisfied +24136,73430,Male,Loyal Customer,24,Personal Travel,Eco,1197,2,5,2,2,2,2,2,2,5,4,4,4,5,2,0,5.0,neutral or dissatisfied +24137,87136,Male,Loyal Customer,55,Business travel,Eco Plus,594,1,4,4,4,1,1,1,1,4,5,2,2,2,1,16,13.0,neutral or dissatisfied +24138,81162,Male,Loyal Customer,57,Business travel,Business,3319,1,1,1,1,2,4,5,4,4,4,4,5,4,4,13,53.0,satisfied +24139,93818,Male,Loyal Customer,72,Business travel,Business,3557,4,4,4,4,3,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +24140,67928,Male,Loyal Customer,39,Personal Travel,Eco,1431,1,5,1,1,2,1,5,2,3,4,3,3,4,2,48,50.0,neutral or dissatisfied +24141,84369,Male,Loyal Customer,51,Business travel,Business,606,5,5,5,5,5,5,4,3,3,4,3,3,3,3,0,0.0,satisfied +24142,77828,Male,Loyal Customer,50,Personal Travel,Eco,731,2,2,2,3,1,2,1,1,1,1,3,2,3,1,3,0.0,neutral or dissatisfied +24143,127815,Female,disloyal Customer,8,Business travel,Eco,1262,3,3,3,1,1,3,1,1,4,5,5,3,4,1,0,0.0,neutral or dissatisfied +24144,26324,Male,Loyal Customer,69,Personal Travel,Eco,892,2,5,2,2,1,2,1,1,4,2,5,4,5,1,0,1.0,neutral or dissatisfied +24145,47369,Female,Loyal Customer,25,Business travel,Eco,588,4,3,3,3,4,4,3,4,2,3,1,1,1,4,0,0.0,satisfied +24146,109787,Female,Loyal Customer,37,Business travel,Business,1562,1,1,1,1,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +24147,64403,Female,disloyal Customer,41,Business travel,Business,1192,2,2,2,3,3,2,2,3,3,3,5,5,4,3,0,0.0,neutral or dissatisfied +24148,5473,Female,Loyal Customer,44,Personal Travel,Eco,265,1,2,1,3,4,3,4,2,2,1,2,4,2,4,0,0.0,neutral or dissatisfied +24149,62097,Male,Loyal Customer,48,Business travel,Business,2565,2,2,2,2,5,3,4,3,3,3,3,3,3,4,0,0.0,satisfied +24150,14430,Male,Loyal Customer,35,Business travel,Business,674,2,2,2,2,2,5,5,5,5,5,5,5,5,5,0,0.0,satisfied +24151,82814,Male,Loyal Customer,66,Personal Travel,Eco,235,5,5,5,4,1,5,1,1,3,3,5,3,4,1,0,0.0,satisfied +24152,77272,Male,Loyal Customer,53,Personal Travel,Business,1931,2,5,3,2,3,3,4,4,4,3,4,4,4,5,0,0.0,neutral or dissatisfied +24153,107262,Female,Loyal Customer,57,Business travel,Business,307,0,0,0,5,4,4,5,3,3,3,3,3,3,5,25,22.0,satisfied +24154,47315,Female,Loyal Customer,32,Business travel,Business,3527,4,4,4,4,4,4,4,4,3,2,1,2,2,4,0,0.0,satisfied +24155,73615,Female,disloyal Customer,27,Business travel,Business,192,0,0,0,2,5,0,5,5,4,3,5,5,4,5,4,4.0,satisfied +24156,96761,Male,Loyal Customer,32,Business travel,Business,816,3,3,3,3,4,3,4,4,5,5,4,5,5,4,59,44.0,satisfied +24157,110332,Male,Loyal Customer,43,Business travel,Business,919,3,3,3,3,5,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +24158,68005,Female,Loyal Customer,55,Business travel,Business,304,1,1,1,1,2,4,4,5,5,5,5,3,5,5,0,0.0,satisfied +24159,127851,Male,Loyal Customer,31,Personal Travel,Business,1276,3,5,3,2,1,3,1,1,3,3,3,5,5,1,0,0.0,neutral or dissatisfied +24160,39025,Male,Loyal Customer,35,Personal Travel,Eco,260,3,3,3,3,2,3,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +24161,21876,Female,Loyal Customer,48,Business travel,Business,448,4,4,2,4,1,2,2,4,4,4,4,5,4,3,0,0.0,satisfied +24162,115791,Male,disloyal Customer,16,Business travel,Eco,446,2,4,2,3,3,2,3,3,2,1,3,4,3,3,88,89.0,neutral or dissatisfied +24163,77369,Male,disloyal Customer,23,Business travel,Eco,532,2,2,2,3,4,2,4,4,3,5,4,4,4,4,0,0.0,neutral or dissatisfied +24164,100656,Male,Loyal Customer,43,Business travel,Business,2652,3,3,3,3,2,5,4,3,3,3,3,4,3,3,1,2.0,satisfied +24165,83317,Male,Loyal Customer,52,Business travel,Eco,1671,2,1,1,1,2,2,2,2,2,4,4,3,3,2,0,11.0,neutral or dissatisfied +24166,105920,Female,Loyal Customer,69,Personal Travel,Eco Plus,283,4,4,4,3,4,5,4,5,5,4,5,3,5,3,20,2.0,satisfied +24167,104600,Female,Loyal Customer,23,Personal Travel,Eco,369,3,5,3,5,3,3,3,3,5,2,5,5,4,3,100,122.0,neutral or dissatisfied +24168,26884,Male,Loyal Customer,27,Business travel,Business,2686,4,4,4,4,4,5,4,4,5,1,2,3,3,4,0,0.0,satisfied +24169,43116,Female,Loyal Customer,23,Personal Travel,Eco,236,1,5,1,5,5,1,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +24170,125869,Male,Loyal Customer,28,Business travel,Business,1728,1,1,1,1,5,4,5,5,5,2,5,5,4,5,0,0.0,satisfied +24171,55190,Male,disloyal Customer,64,Business travel,Eco Plus,1379,3,2,2,2,1,3,1,1,4,1,2,4,3,1,0,9.0,neutral or dissatisfied +24172,39446,Male,Loyal Customer,23,Personal Travel,Eco,129,3,4,3,4,3,1,2,2,2,3,3,2,2,2,226,244.0,neutral or dissatisfied +24173,14515,Female,Loyal Customer,37,Business travel,Business,362,2,3,2,2,3,4,4,4,4,4,4,4,4,3,9,3.0,satisfied +24174,54641,Female,Loyal Customer,36,Business travel,Eco,965,5,1,1,1,5,5,5,5,4,2,5,1,1,5,92,90.0,satisfied +24175,39637,Male,Loyal Customer,12,Personal Travel,Eco Plus,954,2,0,2,4,4,2,4,4,2,2,1,5,2,4,8,0.0,neutral or dissatisfied +24176,99330,Female,Loyal Customer,22,Personal Travel,Eco,448,2,4,2,1,2,3,5,3,5,5,5,5,5,5,243,220.0,neutral or dissatisfied +24177,61920,Female,Loyal Customer,44,Business travel,Business,1782,5,5,5,5,3,4,2,5,5,5,4,2,5,2,0,0.0,satisfied +24178,98665,Male,Loyal Customer,26,Personal Travel,Eco,966,5,1,5,3,1,5,1,1,1,4,2,3,2,1,56,51.0,satisfied +24179,74798,Female,disloyal Customer,25,Business travel,Eco Plus,1431,2,4,2,4,1,2,1,1,4,3,3,2,3,1,0,6.0,neutral or dissatisfied +24180,27565,Female,Loyal Customer,65,Personal Travel,Eco,954,1,5,1,3,2,4,4,2,2,1,5,4,2,5,8,0.0,neutral or dissatisfied +24181,117955,Female,disloyal Customer,39,Business travel,Eco,365,3,0,3,3,4,3,4,4,2,5,1,2,4,4,0,0.0,neutral or dissatisfied +24182,53800,Female,Loyal Customer,38,Business travel,Eco,191,3,1,1,1,3,4,3,3,4,2,5,2,3,3,0,0.0,satisfied +24183,11421,Male,Loyal Customer,15,Business travel,Eco Plus,316,2,3,2,2,2,2,4,2,3,1,4,1,3,2,0,0.0,neutral or dissatisfied +24184,104631,Female,Loyal Customer,18,Personal Travel,Eco,861,2,5,2,3,1,2,1,1,4,4,4,3,5,1,24,52.0,neutral or dissatisfied +24185,94554,Male,Loyal Customer,25,Business travel,Eco,496,1,3,3,3,1,2,4,1,2,3,4,3,3,1,3,0.0,neutral or dissatisfied +24186,19920,Male,Loyal Customer,51,Business travel,Eco,315,1,1,1,1,1,1,1,1,1,2,3,3,4,1,26,18.0,neutral or dissatisfied +24187,61742,Female,disloyal Customer,36,Business travel,Eco,903,1,1,1,2,5,1,5,5,3,5,5,1,2,5,0,0.0,neutral or dissatisfied +24188,65307,Female,disloyal Customer,25,Business travel,Business,247,4,0,4,3,1,4,1,1,3,2,5,4,5,1,0,0.0,satisfied +24189,46298,Female,Loyal Customer,47,Business travel,Eco,237,5,3,3,3,4,4,2,5,5,5,5,5,5,2,3,1.0,satisfied +24190,102440,Female,Loyal Customer,39,Personal Travel,Eco,226,1,5,1,3,2,1,2,2,5,4,5,3,5,2,0,0.0,neutral or dissatisfied +24191,72527,Female,disloyal Customer,12,Business travel,Eco,1017,3,3,3,3,5,3,5,5,2,1,4,3,3,5,0,0.0,neutral or dissatisfied +24192,87124,Female,Loyal Customer,62,Personal Travel,Eco,594,1,2,1,1,1,1,1,4,4,1,4,4,4,3,0,0.0,neutral or dissatisfied +24193,113855,Female,Loyal Customer,61,Business travel,Business,1334,2,2,2,2,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +24194,55281,Female,Loyal Customer,39,Business travel,Business,1585,1,1,1,1,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +24195,112557,Male,disloyal Customer,17,Business travel,Eco Plus,853,5,0,5,1,2,5,5,2,5,5,4,4,2,2,0,0.0,satisfied +24196,53901,Male,Loyal Customer,23,Personal Travel,Eco,191,2,4,2,1,5,2,5,5,1,5,1,2,3,5,11,28.0,neutral or dissatisfied +24197,102961,Male,Loyal Customer,56,Business travel,Business,460,1,1,1,1,4,5,4,5,5,5,5,4,5,4,2,0.0,satisfied +24198,40566,Female,disloyal Customer,19,Business travel,Eco,216,4,2,4,3,5,4,5,5,2,1,4,3,4,5,0,0.0,neutral or dissatisfied +24199,124073,Female,Loyal Customer,31,Personal Travel,Eco Plus,2153,3,4,3,1,3,3,3,3,3,2,5,3,4,3,19,0.0,neutral or dissatisfied +24200,106395,Female,disloyal Customer,11,Business travel,Eco,674,2,2,2,3,2,2,2,2,1,4,3,2,3,2,4,18.0,neutral or dissatisfied +24201,97227,Female,Loyal Customer,7,Personal Travel,Eco Plus,1129,2,2,3,4,1,3,1,1,4,4,4,1,4,1,61,50.0,neutral or dissatisfied +24202,25022,Female,Loyal Customer,38,Business travel,Eco,907,4,4,4,4,4,4,4,4,2,5,1,2,4,4,0,0.0,satisfied +24203,93178,Female,Loyal Customer,47,Personal Travel,Eco,1075,1,5,1,3,3,5,4,2,2,1,2,3,2,4,0,0.0,neutral or dissatisfied +24204,63956,Male,Loyal Customer,42,Personal Travel,Eco,1192,3,4,3,3,1,3,1,1,5,4,4,5,4,1,0,2.0,neutral or dissatisfied +24205,101497,Female,Loyal Customer,71,Business travel,Business,2710,1,1,1,1,5,3,3,1,1,1,1,2,1,3,7,1.0,neutral or dissatisfied +24206,52809,Male,Loyal Customer,58,Business travel,Eco,2402,4,2,2,2,4,4,4,4,5,5,5,2,3,4,0,0.0,satisfied +24207,15549,Male,Loyal Customer,57,Business travel,Business,2078,2,2,2,2,2,4,5,5,5,5,5,4,5,3,0,0.0,satisfied +24208,114978,Female,Loyal Customer,40,Business travel,Business,3368,1,1,1,1,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +24209,47864,Female,disloyal Customer,27,Business travel,Eco,329,3,1,3,4,1,3,1,1,2,5,3,4,4,1,0,10.0,neutral or dissatisfied +24210,65274,Male,Loyal Customer,18,Personal Travel,Eco Plus,469,1,5,1,4,4,1,4,4,5,4,5,4,4,4,99,86.0,neutral or dissatisfied +24211,7970,Male,Loyal Customer,44,Business travel,Business,3129,3,3,3,3,4,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +24212,8903,Male,disloyal Customer,26,Business travel,Business,510,4,4,4,3,4,4,2,4,4,3,5,5,4,4,14,0.0,satisfied +24213,78109,Male,disloyal Customer,25,Business travel,Eco,1213,3,3,3,2,1,3,4,1,4,2,4,3,4,1,0,0.0,neutral or dissatisfied +24214,98878,Female,disloyal Customer,54,Business travel,Eco,591,3,1,3,4,5,3,5,5,2,3,3,1,4,5,1,16.0,neutral or dissatisfied +24215,102080,Female,Loyal Customer,59,Business travel,Business,226,4,4,4,4,3,5,4,4,4,4,4,3,4,4,2,0.0,satisfied +24216,121844,Female,Loyal Customer,58,Business travel,Business,3759,2,2,4,2,5,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +24217,22657,Female,Loyal Customer,18,Personal Travel,Eco Plus,223,3,4,3,3,3,3,3,3,1,2,3,2,3,3,52,67.0,neutral or dissatisfied +24218,60421,Male,Loyal Customer,39,Business travel,Business,2982,1,1,1,1,2,4,5,3,3,2,3,5,3,4,0,0.0,satisfied +24219,6327,Male,Loyal Customer,39,Business travel,Business,315,1,1,4,1,4,4,4,4,4,4,4,3,4,3,17,31.0,satisfied +24220,98830,Female,Loyal Customer,20,Personal Travel,Eco,763,3,4,2,1,2,2,2,2,5,3,4,3,2,2,44,28.0,neutral or dissatisfied +24221,100273,Female,Loyal Customer,47,Business travel,Business,3901,2,2,2,2,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +24222,116735,Female,Loyal Customer,54,Personal Travel,Eco Plus,362,3,5,3,3,2,4,5,3,3,3,5,4,3,5,29,23.0,neutral or dissatisfied +24223,44966,Female,Loyal Customer,45,Business travel,Business,3288,2,2,2,2,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +24224,2060,Male,Loyal Customer,43,Business travel,Business,812,1,1,1,1,3,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +24225,98168,Female,disloyal Customer,40,Business travel,Business,745,3,3,3,4,3,3,3,4,3,5,5,3,5,3,213,198.0,neutral or dissatisfied +24226,55295,Male,Loyal Customer,9,Personal Travel,Eco,1608,3,5,3,2,4,3,4,4,4,4,3,4,4,4,13,0.0,neutral or dissatisfied +24227,11247,Male,Loyal Customer,27,Personal Travel,Eco,201,2,1,2,2,4,2,4,4,2,4,3,4,2,4,3,2.0,neutral or dissatisfied +24228,102029,Female,Loyal Customer,55,Business travel,Business,3180,4,5,4,4,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +24229,118577,Female,Loyal Customer,65,Business travel,Business,325,2,4,4,4,1,4,3,2,2,2,2,1,2,2,85,66.0,neutral or dissatisfied +24230,48592,Female,Loyal Customer,21,Personal Travel,Eco,916,1,5,2,4,2,2,3,2,4,2,4,1,5,2,0,5.0,neutral or dissatisfied +24231,89148,Female,Loyal Customer,51,Business travel,Business,447,2,3,3,3,3,3,3,2,2,2,2,1,2,3,12,0.0,neutral or dissatisfied +24232,122121,Female,Loyal Customer,45,Business travel,Business,2546,2,2,2,2,2,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +24233,87633,Male,disloyal Customer,25,Business travel,Business,606,0,0,0,1,1,0,1,1,4,3,4,5,4,1,1,0.0,satisfied +24234,74382,Female,disloyal Customer,17,Business travel,Business,1464,4,5,4,4,2,4,3,2,4,4,4,3,5,2,0,0.0,satisfied +24235,8988,Male,Loyal Customer,63,Personal Travel,Eco,799,3,3,3,4,3,3,3,3,4,5,3,2,4,3,0,0.0,neutral or dissatisfied +24236,113743,Female,Loyal Customer,9,Personal Travel,Eco,414,5,4,5,3,2,5,2,2,4,5,4,3,3,2,0,0.0,satisfied +24237,55572,Male,disloyal Customer,28,Business travel,Business,1091,1,1,1,4,3,1,3,3,2,2,4,3,4,3,0,3.0,neutral or dissatisfied +24238,40137,Female,Loyal Customer,37,Personal Travel,Eco Plus,200,3,4,3,3,3,3,3,3,1,5,4,3,4,3,26,23.0,neutral or dissatisfied +24239,45139,Female,Loyal Customer,42,Business travel,Business,2333,3,3,3,3,5,3,1,5,5,5,5,2,5,3,0,0.0,satisfied +24240,35913,Male,Loyal Customer,29,Business travel,Business,2248,3,3,3,3,4,4,4,4,1,1,4,4,4,4,0,0.0,satisfied +24241,96215,Male,Loyal Customer,35,Business travel,Business,2865,1,1,3,3,5,3,3,1,1,1,1,4,1,1,16,13.0,neutral or dissatisfied +24242,31679,Male,Loyal Customer,56,Business travel,Eco,776,2,2,2,2,2,2,2,2,4,5,3,1,3,2,0,0.0,neutral or dissatisfied +24243,50477,Male,disloyal Customer,35,Business travel,Eco,209,2,0,2,3,2,2,2,2,3,1,1,1,3,2,0,0.0,neutral or dissatisfied +24244,105270,Female,Loyal Customer,35,Personal Travel,Eco,2106,2,1,2,2,4,2,1,4,4,1,3,4,3,4,0,0.0,neutral or dissatisfied +24245,88740,Female,Loyal Customer,50,Personal Travel,Eco,240,4,4,4,3,5,4,4,5,5,4,5,4,5,3,0,0.0,neutral or dissatisfied +24246,22991,Female,Loyal Customer,15,Personal Travel,Eco,817,3,3,3,4,3,3,2,3,2,4,3,4,4,3,0,0.0,neutral or dissatisfied +24247,32435,Female,disloyal Customer,20,Business travel,Eco,216,4,0,4,2,2,4,2,2,3,4,3,1,4,2,15,19.0,satisfied +24248,104101,Female,Loyal Customer,52,Business travel,Business,297,0,0,0,2,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +24249,58802,Female,Loyal Customer,57,Personal Travel,Eco,1005,0,4,0,3,5,4,5,5,5,0,5,4,5,3,0,6.0,satisfied +24250,34019,Male,Loyal Customer,15,Personal Travel,Eco,1598,1,5,1,2,5,1,5,5,3,3,5,3,5,5,11,26.0,neutral or dissatisfied +24251,46389,Male,Loyal Customer,29,Personal Travel,Eco,1013,3,3,3,4,5,3,5,5,4,3,4,1,5,5,0,17.0,neutral or dissatisfied +24252,91958,Female,Loyal Customer,19,Personal Travel,Eco,2475,1,2,1,4,5,1,5,5,3,2,4,1,4,5,0,5.0,neutral or dissatisfied +24253,67047,Male,Loyal Customer,57,Business travel,Business,929,1,1,1,1,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +24254,69243,Male,Loyal Customer,39,Business travel,Business,3476,3,2,2,2,5,3,2,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +24255,87292,Male,Loyal Customer,66,Personal Travel,Eco,577,1,4,1,3,5,1,5,5,3,2,4,4,4,5,50,42.0,neutral or dissatisfied +24256,86551,Male,Loyal Customer,28,Business travel,Business,712,1,1,1,1,3,4,3,3,3,2,4,5,5,3,0,2.0,satisfied +24257,63065,Male,Loyal Customer,16,Personal Travel,Eco,862,1,5,1,3,1,1,1,1,3,2,5,3,4,1,0,0.0,neutral or dissatisfied +24258,42739,Male,Loyal Customer,63,Personal Travel,Eco,536,4,4,4,1,4,4,4,4,4,4,5,5,4,4,0,0.0,neutral or dissatisfied +24259,100436,Female,Loyal Customer,46,Personal Travel,Eco Plus,1620,2,5,2,1,2,4,1,4,4,2,4,4,4,4,51,50.0,neutral or dissatisfied +24260,102164,Male,Loyal Customer,59,Business travel,Business,386,2,2,2,2,4,4,5,5,5,5,5,5,5,5,0,0.0,satisfied +24261,55422,Male,Loyal Customer,46,Business travel,Business,2521,3,3,4,3,4,4,4,4,2,3,4,4,4,4,0,14.0,satisfied +24262,18331,Male,Loyal Customer,28,Business travel,Business,625,5,5,5,5,5,5,5,5,2,1,1,3,5,5,21,9.0,satisfied +24263,98631,Female,Loyal Customer,46,Business travel,Business,2058,2,2,2,2,4,2,3,2,2,2,2,4,2,2,0,6.0,neutral or dissatisfied +24264,117095,Male,disloyal Customer,34,Business travel,Eco,369,3,0,4,2,3,4,3,3,3,4,3,1,3,3,0,0.0,neutral or dissatisfied +24265,36216,Female,disloyal Customer,26,Business travel,Eco,280,3,3,3,2,5,3,4,5,2,2,3,3,3,5,0,40.0,neutral or dissatisfied +24266,90473,Female,disloyal Customer,27,Business travel,Business,366,3,4,4,1,1,4,1,1,4,3,5,4,5,1,0,0.0,neutral or dissatisfied +24267,123106,Female,Loyal Customer,66,Business travel,Business,650,2,4,4,4,1,4,3,2,2,2,2,2,2,2,0,3.0,neutral or dissatisfied +24268,40781,Female,Loyal Customer,25,Business travel,Eco,501,4,2,4,2,4,4,1,4,1,3,3,1,2,4,57,51.0,neutral or dissatisfied +24269,126346,Male,Loyal Customer,31,Personal Travel,Eco,600,3,4,3,4,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +24270,123545,Male,disloyal Customer,22,Business travel,Eco,1004,4,4,4,3,2,4,2,2,4,5,4,5,5,2,0,0.0,satisfied +24271,45884,Male,Loyal Customer,55,Business travel,Eco,641,4,5,4,5,4,4,4,4,1,2,1,4,3,4,0,0.0,satisfied +24272,18263,Female,Loyal Customer,21,Personal Travel,Eco,228,3,1,3,3,4,3,4,4,3,2,3,4,3,4,17,20.0,neutral or dissatisfied +24273,38830,Male,Loyal Customer,23,Personal Travel,Eco,354,2,3,2,1,2,2,4,2,4,3,2,4,2,2,25,16.0,neutral or dissatisfied +24274,118934,Female,Loyal Customer,43,Business travel,Business,1618,4,4,4,4,4,5,5,4,4,4,4,4,4,5,0,0.0,satisfied +24275,63756,Female,Loyal Customer,72,Business travel,Eco Plus,1660,1,3,3,3,4,3,4,1,1,1,1,3,1,3,12,13.0,neutral or dissatisfied +24276,94418,Male,Loyal Customer,48,Business travel,Business,319,2,2,5,2,3,5,4,5,5,4,5,4,5,5,0,0.0,satisfied +24277,100718,Male,disloyal Customer,39,Business travel,Business,328,2,2,2,2,3,2,3,3,4,4,4,5,5,3,8,1.0,neutral or dissatisfied +24278,8459,Male,Loyal Customer,35,Business travel,Business,1379,1,3,3,3,4,3,4,1,1,1,1,1,1,1,6,0.0,neutral or dissatisfied +24279,33925,Female,Loyal Customer,35,Business travel,Eco,818,5,5,2,2,5,5,5,5,5,5,4,2,2,5,0,0.0,satisfied +24280,66200,Male,Loyal Customer,44,Business travel,Eco,550,3,2,2,2,4,3,4,4,3,3,4,2,4,4,23,21.0,neutral or dissatisfied +24281,75943,Female,Loyal Customer,57,Personal Travel,Business,297,3,5,3,3,5,5,5,3,3,3,3,5,3,3,0,0.0,neutral or dissatisfied +24282,75009,Male,Loyal Customer,42,Business travel,Business,1795,4,4,4,4,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +24283,106733,Male,Loyal Customer,53,Business travel,Business,2869,4,4,4,4,5,5,5,3,3,3,3,3,3,4,14,0.0,satisfied +24284,123229,Female,Loyal Customer,7,Personal Travel,Eco,650,1,4,1,5,2,1,2,2,2,1,3,2,5,2,0,0.0,neutral or dissatisfied +24285,44707,Male,Loyal Customer,36,Personal Travel,Eco,108,2,1,2,2,4,2,4,4,2,4,3,4,2,4,0,0.0,neutral or dissatisfied +24286,109029,Female,Loyal Customer,51,Business travel,Business,1574,2,2,2,2,2,4,5,5,5,5,5,5,5,5,0,21.0,satisfied +24287,29461,Male,Loyal Customer,19,Personal Travel,Eco,421,3,4,2,1,1,2,1,1,3,1,2,1,1,1,0,0.0,neutral or dissatisfied +24288,78142,Male,disloyal Customer,32,Business travel,Business,259,2,3,3,3,4,3,1,4,3,2,4,3,5,4,1,14.0,neutral or dissatisfied +24289,11548,Female,Loyal Customer,44,Personal Travel,Business,468,4,3,4,1,5,5,3,5,5,4,3,1,5,4,0,0.0,satisfied +24290,105587,Male,Loyal Customer,48,Personal Travel,Eco,577,4,4,4,3,1,4,1,1,4,4,4,4,4,1,4,0.0,satisfied +24291,42065,Male,Loyal Customer,30,Personal Travel,Eco,116,4,2,0,2,2,0,2,2,4,1,3,4,2,2,0,0.0,satisfied +24292,5329,Male,Loyal Customer,36,Personal Travel,Business,812,3,2,3,2,5,2,3,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +24293,103645,Female,Loyal Customer,55,Business travel,Business,405,5,5,5,5,4,4,5,4,4,4,4,5,4,3,0,0.0,satisfied +24294,16823,Female,Loyal Customer,66,Business travel,Eco,645,3,3,3,3,4,4,5,3,3,3,3,4,3,4,0,0.0,satisfied +24295,45312,Female,Loyal Customer,54,Business travel,Business,3639,0,5,0,5,2,1,2,5,5,5,5,1,5,3,0,16.0,satisfied +24296,90685,Female,Loyal Customer,52,Business travel,Business,1530,2,2,2,2,3,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +24297,79100,Male,Loyal Customer,44,Personal Travel,Eco,356,5,5,5,4,2,5,2,2,4,3,4,4,5,2,0,0.0,satisfied +24298,39203,Female,Loyal Customer,50,Business travel,Business,67,4,4,4,4,4,5,5,5,5,5,4,4,5,4,0,0.0,satisfied +24299,117586,Female,Loyal Customer,31,Business travel,Business,3507,5,5,5,5,5,5,5,5,3,5,4,3,5,5,11,0.0,satisfied +24300,82209,Male,Loyal Customer,48,Business travel,Business,1857,3,3,3,3,3,4,4,5,5,5,5,4,5,4,0,0.0,satisfied +24301,125688,Male,disloyal Customer,38,Business travel,Business,759,3,3,3,1,4,3,4,4,3,3,5,5,4,4,0,,satisfied +24302,28678,Male,Loyal Customer,41,Business travel,Business,2797,1,1,1,1,4,4,4,2,1,4,4,4,2,4,8,0.0,satisfied +24303,92575,Male,Loyal Customer,32,Business travel,Eco Plus,1947,1,4,1,1,1,1,1,1,3,1,4,3,4,1,0,0.0,neutral or dissatisfied +24304,81360,Male,Loyal Customer,65,Personal Travel,Eco,1299,3,4,3,1,2,3,2,2,4,3,3,5,4,2,0,0.0,neutral or dissatisfied +24305,105599,Female,disloyal Customer,35,Business travel,Business,663,3,3,3,3,4,3,4,4,3,2,4,4,5,4,15,5.0,neutral or dissatisfied +24306,28155,Male,disloyal Customer,32,Business travel,Eco,550,4,1,4,3,1,4,1,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +24307,90849,Male,Loyal Customer,71,Business travel,Business,404,4,4,4,4,4,3,4,4,4,4,4,4,4,1,6,1.0,neutral or dissatisfied +24308,11718,Male,disloyal Customer,50,Business travel,Business,429,4,4,4,4,3,4,3,3,4,5,5,4,5,3,120,131.0,satisfied +24309,29063,Male,Loyal Customer,49,Personal Travel,Eco,954,2,5,2,2,3,2,3,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +24310,58097,Female,Loyal Customer,18,Business travel,Business,589,2,1,1,1,2,3,2,2,3,4,4,4,3,2,78,101.0,neutral or dissatisfied +24311,49842,Male,Loyal Customer,52,Business travel,Eco,86,1,5,5,5,2,1,2,2,2,5,3,4,3,2,117,112.0,neutral or dissatisfied +24312,91256,Female,Loyal Customer,34,Personal Travel,Eco,250,2,4,2,3,4,2,1,4,4,4,5,5,5,4,87,66.0,neutral or dissatisfied +24313,127567,Female,disloyal Customer,42,Business travel,Eco,1082,4,4,4,3,1,4,1,1,4,5,3,2,4,1,0,0.0,neutral or dissatisfied +24314,98315,Female,Loyal Customer,30,Business travel,Eco Plus,1565,0,0,0,1,1,0,1,1,5,1,5,1,2,1,11,30.0,satisfied +24315,55611,Male,Loyal Customer,39,Business travel,Business,1714,1,2,1,1,5,4,5,4,4,5,4,2,4,3,0,0.0,satisfied +24316,117251,Male,Loyal Customer,18,Personal Travel,Eco,647,4,5,4,2,5,4,5,5,1,2,3,5,3,5,3,0.0,neutral or dissatisfied +24317,103349,Female,disloyal Customer,57,Business travel,Eco Plus,1371,2,2,2,4,1,2,1,1,3,3,3,4,3,1,2,1.0,neutral or dissatisfied +24318,103642,Female,Loyal Customer,41,Business travel,Business,251,4,4,4,4,4,5,4,4,4,4,4,3,4,3,21,16.0,satisfied +24319,77771,Male,Loyal Customer,49,Personal Travel,Eco,731,4,3,5,3,3,5,3,3,5,2,4,1,5,3,0,0.0,satisfied +24320,104567,Female,disloyal Customer,25,Business travel,Business,369,3,0,2,4,3,2,3,3,4,5,5,3,4,3,1,0.0,neutral or dissatisfied +24321,21003,Female,Loyal Customer,38,Business travel,Eco Plus,803,3,2,2,2,3,3,3,3,1,5,4,5,4,3,15,0.0,satisfied +24322,3054,Female,Loyal Customer,55,Business travel,Business,340,1,1,1,1,5,5,5,4,4,4,4,3,4,3,0,15.0,satisfied +24323,107655,Female,Loyal Customer,40,Business travel,Business,251,5,5,5,5,4,4,5,5,5,5,5,5,5,4,15,20.0,satisfied +24324,95102,Male,Loyal Customer,57,Personal Travel,Eco,239,2,4,2,4,3,2,3,3,4,5,5,4,2,3,66,61.0,neutral or dissatisfied +24325,79158,Male,Loyal Customer,40,Personal Travel,Eco,2239,4,4,4,4,5,4,5,5,4,4,2,2,4,5,0,0.0,satisfied +24326,103869,Male,Loyal Customer,16,Personal Travel,Eco,1072,3,4,3,1,3,3,3,3,3,3,4,5,5,3,0,0.0,neutral or dissatisfied +24327,68386,Female,Loyal Customer,44,Business travel,Business,2681,5,5,5,5,5,5,5,5,5,5,5,4,5,5,0,0.0,satisfied +24328,84048,Male,disloyal Customer,26,Business travel,Business,757,1,1,1,3,3,1,3,3,5,2,4,3,4,3,0,0.0,neutral or dissatisfied +24329,125457,Male,Loyal Customer,51,Business travel,Business,2979,3,3,3,3,5,5,5,4,2,4,5,5,4,5,0,0.0,satisfied +24330,29321,Male,Loyal Customer,59,Personal Travel,Eco,933,3,4,3,3,2,3,3,2,3,4,5,3,4,2,0,8.0,neutral or dissatisfied +24331,125218,Female,Loyal Customer,51,Personal Travel,Eco,651,1,5,1,3,1,5,3,1,1,1,1,4,1,3,0,0.0,neutral or dissatisfied +24332,87004,Female,Loyal Customer,53,Personal Travel,Eco,907,4,1,4,4,2,3,4,3,3,4,3,3,3,1,0,2.0,satisfied +24333,24173,Male,Loyal Customer,68,Business travel,Business,134,3,2,1,1,3,3,3,3,1,4,4,3,1,3,131,151.0,neutral or dissatisfied +24334,128916,Male,disloyal Customer,27,Business travel,Business,414,2,2,2,1,1,2,1,1,3,5,5,4,5,1,0,0.0,neutral or dissatisfied +24335,26896,Female,Loyal Customer,58,Business travel,Business,1874,2,2,2,2,5,5,5,5,5,5,5,5,5,5,4,0.0,satisfied +24336,123686,Female,disloyal Customer,38,Business travel,Eco,214,4,0,3,1,4,3,4,4,2,3,1,1,3,4,0,0.0,satisfied +24337,127487,Male,Loyal Customer,24,Business travel,Business,2083,4,4,4,4,4,4,4,4,1,5,2,2,5,4,2,0.0,satisfied +24338,2376,Female,Loyal Customer,17,Personal Travel,Business,604,3,5,2,4,1,2,1,1,4,3,4,5,4,1,0,0.0,neutral or dissatisfied +24339,11264,Female,Loyal Customer,44,Personal Travel,Eco,429,4,5,1,1,1,4,4,5,5,1,4,1,5,3,0,0.0,neutral or dissatisfied +24340,92497,Female,Loyal Customer,49,Business travel,Eco,639,4,2,2,2,5,4,2,4,4,4,4,5,4,3,1,0.0,satisfied +24341,3672,Male,Loyal Customer,45,Business travel,Eco,544,3,3,3,3,3,3,3,3,2,1,3,1,3,3,7,0.0,neutral or dissatisfied +24342,94952,Female,disloyal Customer,23,Business travel,Eco,248,3,0,3,3,3,3,4,3,5,4,3,2,4,3,47,48.0,neutral or dissatisfied +24343,89057,Male,Loyal Customer,45,Business travel,Business,1892,5,5,5,5,4,3,4,3,3,3,3,3,3,3,0,0.0,satisfied +24344,20085,Male,Loyal Customer,25,Business travel,Business,2866,1,1,1,1,4,4,4,4,2,4,4,5,4,4,12,0.0,satisfied +24345,52225,Male,Loyal Customer,50,Business travel,Eco,598,5,3,3,3,5,5,5,5,3,3,3,4,2,5,0,1.0,satisfied +24346,32286,Female,Loyal Customer,55,Business travel,Business,216,2,5,5,5,3,4,4,3,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +24347,74441,Male,disloyal Customer,36,Business travel,Business,1188,3,3,3,2,5,3,5,5,4,4,5,5,4,5,0,2.0,neutral or dissatisfied +24348,48165,Female,Loyal Customer,33,Business travel,Business,236,3,4,4,4,3,2,2,3,3,3,3,1,3,4,80,81.0,neutral or dissatisfied +24349,95252,Female,Loyal Customer,14,Personal Travel,Eco,239,3,4,0,1,2,0,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +24350,116898,Female,Loyal Customer,53,Business travel,Business,651,1,1,1,1,3,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +24351,18865,Male,Loyal Customer,30,Business travel,Business,2669,4,1,1,1,4,4,4,4,1,5,3,2,2,4,28,32.0,neutral or dissatisfied +24352,79953,Female,disloyal Customer,36,Business travel,Eco,1047,1,1,1,3,2,1,2,2,2,3,4,3,4,2,11,0.0,neutral or dissatisfied +24353,3987,Female,Loyal Customer,49,Business travel,Business,419,5,5,5,5,2,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +24354,29474,Male,Loyal Customer,19,Business travel,Business,1216,3,3,4,3,4,5,4,4,1,5,1,2,2,4,0,1.0,satisfied +24355,34283,Male,Loyal Customer,33,Business travel,Eco,280,0,0,0,3,3,0,4,3,3,3,1,1,1,3,0,0.0,satisfied +24356,29649,Female,Loyal Customer,65,Personal Travel,Eco,1533,2,4,3,3,2,4,5,5,5,3,3,4,5,3,16,26.0,neutral or dissatisfied +24357,97343,Male,disloyal Customer,37,Business travel,Business,347,3,3,3,3,4,3,4,4,3,3,4,3,3,4,2,0.0,neutral or dissatisfied +24358,22130,Female,Loyal Customer,47,Business travel,Business,566,4,4,4,4,1,2,1,4,4,4,4,1,4,3,0,0.0,neutral or dissatisfied +24359,64832,Male,disloyal Customer,20,Business travel,Business,190,5,4,5,5,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +24360,64602,Male,Loyal Customer,50,Business travel,Business,2000,0,5,0,2,5,5,5,1,1,1,1,5,1,3,55,54.0,satisfied +24361,125342,Male,Loyal Customer,48,Business travel,Business,599,3,3,3,3,5,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +24362,84349,Female,Loyal Customer,44,Business travel,Business,606,5,5,5,5,3,5,4,3,3,3,3,4,3,4,19,22.0,satisfied +24363,122904,Female,Loyal Customer,53,Business travel,Business,2721,3,5,5,5,4,4,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +24364,46971,Male,Loyal Customer,14,Personal Travel,Eco,959,3,5,3,4,2,3,2,2,4,2,4,4,5,2,0,8.0,neutral or dissatisfied +24365,122576,Female,Loyal Customer,55,Personal Travel,Business,728,2,3,2,4,3,4,3,4,4,2,4,1,4,3,6,0.0,neutral or dissatisfied +24366,172,Male,Loyal Customer,37,Business travel,Business,227,3,3,3,3,5,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +24367,123754,Female,Loyal Customer,51,Business travel,Business,3953,4,4,4,4,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +24368,16067,Female,Loyal Customer,50,Business travel,Business,3986,3,4,4,4,1,2,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +24369,19898,Female,Loyal Customer,37,Business travel,Eco,315,5,4,4,4,5,5,5,1,4,5,3,5,5,5,143,138.0,satisfied +24370,66880,Male,disloyal Customer,11,Business travel,Eco,918,5,5,5,4,1,5,1,1,5,2,4,5,5,1,6,1.0,satisfied +24371,35999,Male,Loyal Customer,54,Business travel,Business,2921,1,1,1,1,5,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +24372,38945,Female,disloyal Customer,39,Business travel,Business,205,1,2,2,4,5,2,5,5,4,2,1,3,3,5,0,0.0,neutral or dissatisfied +24373,49504,Female,Loyal Customer,36,Business travel,Business,1711,5,5,5,5,3,3,4,5,5,5,5,5,5,2,0,0.0,satisfied +24374,127282,Female,Loyal Customer,49,Personal Travel,Eco,1020,2,0,2,2,3,3,2,5,5,2,5,5,5,1,0,0.0,neutral or dissatisfied +24375,10315,Female,Loyal Customer,48,Business travel,Business,2267,5,5,3,5,2,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +24376,52039,Female,disloyal Customer,64,Business travel,Eco Plus,328,1,2,2,3,5,1,1,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +24377,123422,Male,Loyal Customer,26,Personal Travel,Eco,1337,2,2,1,2,2,1,2,2,4,2,1,1,2,2,0,23.0,neutral or dissatisfied +24378,103989,Male,Loyal Customer,51,Business travel,Business,1592,1,1,1,1,2,5,5,4,4,4,4,3,4,3,0,1.0,satisfied +24379,100957,Female,disloyal Customer,21,Business travel,Business,1142,3,2,3,3,3,3,3,3,2,5,3,1,3,3,0,11.0,neutral or dissatisfied +24380,60929,Male,Loyal Customer,41,Business travel,Business,888,4,4,4,4,3,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +24381,58205,Male,disloyal Customer,56,Business travel,Eco,525,4,0,4,2,5,4,5,5,4,5,5,4,3,5,0,0.0,satisfied +24382,116089,Female,Loyal Customer,40,Personal Travel,Eco,371,1,5,1,4,3,1,3,3,5,3,5,3,4,3,0,0.0,neutral or dissatisfied +24383,17433,Male,disloyal Customer,27,Business travel,Eco,376,3,0,3,2,3,3,3,3,5,5,5,2,2,3,0,0.0,neutral or dissatisfied +24384,107700,Male,disloyal Customer,61,Business travel,Eco,405,2,2,2,3,5,2,5,5,4,1,4,1,4,5,0,32.0,neutral or dissatisfied +24385,33250,Female,Loyal Customer,48,Business travel,Eco Plus,163,4,2,2,2,1,2,5,4,4,4,4,2,4,1,0,0.0,satisfied +24386,53217,Male,disloyal Customer,33,Business travel,Eco,589,2,1,3,3,4,3,4,4,3,5,4,3,3,4,0,0.0,neutral or dissatisfied +24387,55313,Male,Loyal Customer,49,Business travel,Business,1325,1,1,5,1,4,5,4,2,2,2,2,4,2,5,10,34.0,satisfied +24388,71437,Male,Loyal Customer,54,Business travel,Business,867,5,5,5,5,2,5,4,4,4,4,4,5,4,5,7,0.0,satisfied +24389,122439,Female,Loyal Customer,20,Business travel,Business,1916,4,4,4,4,5,5,5,5,5,5,4,5,5,5,109,87.0,satisfied +24390,123145,Male,Loyal Customer,57,Business travel,Business,3953,3,3,3,3,5,5,4,4,4,4,4,4,4,5,0,0.0,satisfied +24391,71990,Male,Loyal Customer,21,Personal Travel,Eco,1437,4,5,4,1,5,4,5,5,5,3,5,3,4,5,0,8.0,satisfied +24392,94645,Female,disloyal Customer,22,Business travel,Eco,189,2,4,2,4,3,2,3,3,5,4,4,5,5,3,9,0.0,neutral or dissatisfied +24393,116677,Female,Loyal Customer,71,Business travel,Eco Plus,373,3,2,2,2,2,3,4,2,2,3,2,1,2,3,0,0.0,neutral or dissatisfied +24394,46699,Male,Loyal Customer,32,Personal Travel,Eco,125,2,2,2,2,3,2,3,3,4,5,2,4,1,3,8,107.0,neutral or dissatisfied +24395,102252,Female,Loyal Customer,40,Business travel,Business,3252,2,2,2,2,2,4,5,4,4,4,4,5,4,4,0,4.0,satisfied +24396,35412,Male,disloyal Customer,22,Business travel,Eco,680,4,4,4,3,2,4,5,2,1,1,4,3,4,2,54,18.0,neutral or dissatisfied +24397,33769,Male,disloyal Customer,24,Business travel,Eco,794,3,3,3,1,5,3,5,5,4,1,4,2,4,5,0,13.0,neutral or dissatisfied +24398,26400,Male,Loyal Customer,55,Business travel,Eco,684,5,2,2,2,5,5,5,5,4,1,3,5,3,5,0,1.0,satisfied +24399,109446,Female,Loyal Customer,45,Business travel,Business,3345,1,1,1,1,2,5,5,5,5,5,5,4,5,5,27,22.0,satisfied +24400,74570,Male,disloyal Customer,22,Business travel,Business,1235,4,0,4,3,4,4,1,4,3,4,4,3,4,4,0,0.0,satisfied +24401,8414,Female,Loyal Customer,49,Business travel,Business,862,3,3,3,3,5,5,5,4,4,4,4,4,4,5,9,25.0,satisfied +24402,82835,Male,disloyal Customer,27,Business travel,Business,594,2,2,2,2,3,2,3,3,4,3,4,5,4,3,0,0.0,neutral or dissatisfied +24403,20037,Female,disloyal Customer,37,Business travel,Eco,528,2,3,2,3,3,2,3,3,2,1,4,4,3,3,0,0.0,neutral or dissatisfied +24404,25015,Female,Loyal Customer,45,Business travel,Eco,907,4,4,4,4,2,2,4,3,3,4,3,3,3,3,9,8.0,satisfied +24405,50306,Female,disloyal Customer,37,Business travel,Eco,109,4,3,4,4,2,4,2,2,3,1,1,1,1,2,0,0.0,satisfied +24406,117809,Male,disloyal Customer,36,Business travel,Eco,328,2,4,2,3,4,2,4,4,4,4,3,2,4,4,20,15.0,neutral or dissatisfied +24407,119673,Male,Loyal Customer,55,Business travel,Eco Plus,507,2,2,4,2,2,2,2,2,3,2,3,3,4,2,0,0.0,neutral or dissatisfied +24408,12153,Male,Loyal Customer,47,Business travel,Eco,1075,5,4,4,4,5,5,5,5,5,5,5,5,3,5,15,6.0,satisfied +24409,116256,Male,Loyal Customer,65,Personal Travel,Eco,333,3,5,3,4,3,3,3,3,4,5,5,5,5,3,0,0.0,neutral or dissatisfied +24410,93950,Female,Loyal Customer,28,Personal Travel,Eco,507,2,3,2,4,1,2,1,1,4,1,4,3,4,1,16,7.0,neutral or dissatisfied +24411,116357,Male,Loyal Customer,61,Personal Travel,Eco,447,3,4,3,4,1,3,1,1,1,2,3,3,4,1,0,0.0,neutral or dissatisfied +24412,105976,Female,Loyal Customer,43,Personal Travel,Eco,2295,1,5,1,4,3,5,4,5,5,1,5,5,5,4,4,16.0,neutral or dissatisfied +24413,25638,Female,Loyal Customer,22,Personal Travel,Eco,526,1,4,1,1,5,1,5,5,3,2,4,4,5,5,0,0.0,neutral or dissatisfied +24414,62224,Male,Loyal Customer,50,Personal Travel,Eco,2565,3,3,2,4,3,2,3,3,2,4,4,4,3,3,88,42.0,neutral or dissatisfied +24415,128885,Male,Loyal Customer,26,Business travel,Eco,2565,3,3,3,3,3,4,3,1,5,2,4,3,1,3,87,57.0,neutral or dissatisfied +24416,70740,Female,Loyal Customer,33,Personal Travel,Eco,675,2,4,2,1,5,2,5,5,4,2,5,5,5,5,6,0.0,neutral or dissatisfied +24417,83363,Female,Loyal Customer,46,Business travel,Business,1124,5,5,5,5,3,4,5,3,3,4,3,4,3,5,3,8.0,satisfied +24418,30660,Female,Loyal Customer,46,Personal Travel,Eco,770,1,4,1,3,3,4,4,3,3,1,2,5,3,4,0,0.0,neutral or dissatisfied +24419,62853,Female,Loyal Customer,48,Business travel,Business,2218,5,5,5,5,4,5,4,4,4,4,4,5,4,5,0,1.0,satisfied +24420,21907,Male,Loyal Customer,49,Business travel,Business,2463,2,2,2,2,3,1,5,5,5,5,5,1,5,5,0,0.0,satisfied +24421,78353,Male,Loyal Customer,46,Business travel,Business,1547,3,3,3,3,3,5,5,3,3,3,3,3,3,5,1,0.0,satisfied +24422,49959,Male,disloyal Customer,26,Business travel,Business,266,1,5,1,4,3,1,3,3,3,5,4,3,4,3,0,0.0,neutral or dissatisfied +24423,9239,Female,disloyal Customer,23,Business travel,Eco,100,0,4,0,1,5,0,5,5,1,2,5,2,4,5,0,0.0,satisfied +24424,111140,Male,Loyal Customer,41,Business travel,Business,3766,2,3,3,3,3,2,3,2,2,3,2,2,2,1,20,16.0,neutral or dissatisfied +24425,44377,Female,Loyal Customer,63,Business travel,Eco,229,5,3,3,3,4,4,2,5,5,5,5,4,5,1,21,42.0,satisfied +24426,82213,Male,disloyal Customer,27,Business travel,Business,405,5,5,5,3,3,5,3,3,4,5,4,4,4,3,0,0.0,satisfied +24427,29682,Female,disloyal Customer,22,Business travel,Eco,1448,3,3,3,4,1,3,1,1,2,3,4,1,4,1,0,0.0,neutral or dissatisfied +24428,108036,Female,Loyal Customer,35,Personal Travel,Eco,306,2,5,2,4,3,2,3,3,5,5,4,4,4,3,3,18.0,neutral or dissatisfied +24429,110220,Male,Loyal Customer,45,Business travel,Business,1011,5,5,5,5,4,5,5,3,3,4,3,4,3,4,7,7.0,satisfied +24430,32096,Female,disloyal Customer,40,Business travel,Business,216,4,4,4,5,4,4,4,4,2,4,3,5,4,4,11,12.0,neutral or dissatisfied +24431,8231,Female,Loyal Customer,60,Personal Travel,Eco,125,4,3,4,5,2,2,2,1,1,4,1,2,1,5,0,0.0,neutral or dissatisfied +24432,70171,Female,Loyal Customer,54,Personal Travel,Eco Plus,550,3,4,3,3,4,3,3,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +24433,26252,Male,disloyal Customer,36,Business travel,Eco Plus,406,4,4,4,4,4,4,4,4,3,4,4,4,3,4,82,91.0,neutral or dissatisfied +24434,107185,Male,disloyal Customer,25,Business travel,Eco,402,3,5,3,5,4,3,4,4,5,1,1,3,3,4,5,0.0,neutral or dissatisfied +24435,59563,Female,disloyal Customer,30,Business travel,Business,787,1,1,1,4,1,1,1,1,5,5,5,5,4,1,18,22.0,neutral or dissatisfied +24436,55725,Male,Loyal Customer,26,Business travel,Business,2923,4,1,1,1,4,4,4,4,4,1,4,3,4,4,9,0.0,neutral or dissatisfied +24437,39228,Male,disloyal Customer,29,Business travel,Eco,160,1,5,1,4,3,1,3,3,2,5,1,1,3,3,0,13.0,neutral or dissatisfied +24438,42893,Male,Loyal Customer,49,Business travel,Business,422,5,5,5,5,4,3,2,5,5,5,5,5,5,5,0,0.0,satisfied +24439,74188,Female,Loyal Customer,30,Personal Travel,Eco,641,1,5,1,2,5,1,5,5,4,4,4,4,5,5,0,12.0,neutral or dissatisfied +24440,24854,Male,Loyal Customer,35,Personal Travel,Eco Plus,861,3,4,3,1,5,3,4,5,5,3,4,5,5,5,6,0.0,neutral or dissatisfied +24441,6657,Female,Loyal Customer,52,Business travel,Business,3358,2,2,2,2,4,4,4,5,5,5,5,4,5,3,15,4.0,satisfied +24442,82772,Male,Loyal Customer,17,Business travel,Eco Plus,409,4,2,2,2,4,4,5,4,4,4,2,5,1,4,0,0.0,satisfied +24443,16806,Female,disloyal Customer,49,Business travel,Eco,645,3,0,3,1,3,3,4,3,1,1,3,1,3,3,2,8.0,neutral or dissatisfied +24444,51008,Female,Loyal Customer,46,Personal Travel,Eco,447,0,5,0,2,4,4,5,2,2,0,2,3,2,4,0,0.0,satisfied +24445,99180,Male,Loyal Customer,45,Business travel,Business,2078,4,4,4,4,3,4,5,2,2,2,2,4,2,5,9,1.0,satisfied +24446,127511,Female,Loyal Customer,40,Personal Travel,Eco,2075,4,2,4,4,3,4,3,3,1,5,3,4,3,3,0,0.0,neutral or dissatisfied +24447,80939,Male,Loyal Customer,15,Personal Travel,Eco,341,2,4,1,4,1,1,1,1,4,2,2,3,1,1,15,0.0,neutral or dissatisfied +24448,84495,Male,disloyal Customer,40,Business travel,Business,4502,4,4,4,5,4,4,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +24449,72551,Female,Loyal Customer,66,Business travel,Business,3662,3,3,3,3,2,4,3,3,3,3,3,2,3,2,28,52.0,neutral or dissatisfied +24450,92749,Male,Loyal Customer,53,Personal Travel,Eco,1276,3,3,3,4,5,3,5,5,1,2,3,3,4,5,12,10.0,neutral or dissatisfied +24451,35368,Male,disloyal Customer,19,Business travel,Eco,972,2,2,2,4,1,2,1,1,4,5,3,2,4,1,0,0.0,neutral or dissatisfied +24452,84501,Female,Loyal Customer,37,Business travel,Business,4502,2,2,2,2,4,4,4,4,5,5,4,4,3,4,6,0.0,satisfied +24453,28329,Male,disloyal Customer,26,Business travel,Eco,867,4,4,4,5,4,4,4,4,5,1,2,1,2,4,0,0.0,neutral or dissatisfied +24454,95251,Female,Loyal Customer,54,Personal Travel,Eco,319,5,4,5,3,1,1,4,2,2,5,2,1,2,4,0,0.0,satisfied +24455,124139,Male,Loyal Customer,57,Personal Travel,Eco,529,3,4,3,5,5,3,5,5,4,2,5,4,5,5,5,0.0,neutral or dissatisfied +24456,89258,Female,Loyal Customer,55,Business travel,Business,453,3,3,3,3,5,5,5,5,5,5,5,3,5,3,17,8.0,satisfied +24457,118738,Female,Loyal Customer,25,Personal Travel,Eco,647,4,1,4,2,1,4,1,1,2,5,3,3,2,1,54,40.0,neutral or dissatisfied +24458,28605,Female,Loyal Customer,28,Business travel,Eco,2614,5,4,3,4,5,5,5,5,1,1,5,5,5,5,0,0.0,satisfied +24459,122409,Male,Loyal Customer,47,Business travel,Business,1916,3,3,3,3,5,4,4,4,4,4,4,5,4,3,13,19.0,satisfied +24460,2583,Male,Loyal Customer,66,Personal Travel,Eco,181,4,2,4,4,4,4,4,4,1,2,3,3,4,4,0,0.0,satisfied +24461,113694,Male,Loyal Customer,57,Personal Travel,Eco,236,4,4,4,4,2,4,2,2,3,4,4,4,4,2,1,13.0,neutral or dissatisfied +24462,27587,Male,Loyal Customer,48,Personal Travel,Eco,679,3,5,3,1,3,3,3,3,3,4,5,5,4,3,1,0.0,neutral or dissatisfied +24463,45322,Male,Loyal Customer,17,Business travel,Eco,188,5,5,3,5,5,5,5,5,3,5,2,4,5,5,0,0.0,satisfied +24464,122590,Male,Loyal Customer,44,Business travel,Business,2651,3,3,3,3,4,5,5,4,4,4,4,5,4,3,0,0.0,satisfied +24465,52773,Female,Loyal Customer,19,Business travel,Business,1874,5,5,5,5,4,4,4,4,3,1,4,5,1,4,2,19.0,satisfied +24466,43251,Female,Loyal Customer,33,Business travel,Eco,436,5,2,2,2,5,5,5,5,4,3,3,3,1,5,0,10.0,satisfied +24467,81376,Female,disloyal Customer,29,Business travel,Business,748,4,4,4,1,2,4,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +24468,32302,Female,Loyal Customer,49,Business travel,Business,163,5,5,5,5,1,3,4,4,4,4,5,1,4,3,0,0.0,satisfied +24469,57861,Male,Loyal Customer,33,Personal Travel,Eco,2329,3,5,3,4,3,4,4,3,5,5,5,4,4,4,0,16.0,neutral or dissatisfied +24470,66022,Female,Loyal Customer,25,Business travel,Business,2417,3,3,3,3,5,5,5,5,4,2,5,4,4,5,74,90.0,satisfied +24471,7961,Female,disloyal Customer,36,Business travel,Eco,194,2,3,2,4,5,2,5,5,2,1,3,4,4,5,0,3.0,neutral or dissatisfied +24472,74992,Female,Loyal Customer,69,Personal Travel,Eco Plus,2475,3,2,3,4,2,4,4,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +24473,86157,Female,disloyal Customer,37,Business travel,Business,226,3,3,3,1,4,3,4,4,4,3,4,4,5,4,0,5.0,neutral or dissatisfied +24474,100993,Male,Loyal Customer,41,Business travel,Business,867,3,3,3,3,4,5,4,3,3,3,3,4,3,5,47,48.0,satisfied +24475,31014,Male,disloyal Customer,25,Business travel,Eco,391,5,2,5,2,2,5,2,2,4,3,3,1,3,2,39,48.0,satisfied +24476,122593,Male,disloyal Customer,19,Business travel,Eco,728,2,2,2,2,3,2,3,3,5,5,4,3,4,3,0,0.0,neutral or dissatisfied +24477,115963,Female,Loyal Customer,40,Personal Travel,Eco,296,2,4,2,3,2,2,2,2,3,3,4,5,5,2,2,0.0,neutral or dissatisfied +24478,22474,Male,Loyal Customer,61,Personal Travel,Eco,145,4,5,4,4,5,4,5,5,3,3,4,3,4,5,0,0.0,neutral or dissatisfied +24479,124577,Female,Loyal Customer,33,Business travel,Business,3200,3,3,3,3,2,5,5,4,4,4,4,3,4,5,0,0.0,satisfied +24480,103671,Male,Loyal Customer,34,Business travel,Business,405,2,4,4,4,2,4,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +24481,83954,Male,Loyal Customer,51,Business travel,Business,321,0,0,0,3,4,4,4,3,2,4,5,4,4,4,167,154.0,satisfied +24482,3034,Male,Loyal Customer,35,Personal Travel,Eco Plus,922,2,4,2,3,1,2,1,1,5,5,5,5,5,1,27,35.0,neutral or dissatisfied +24483,34764,Male,disloyal Customer,23,Business travel,Eco,209,2,3,3,3,4,3,4,4,3,3,3,1,3,4,0,0.0,neutral or dissatisfied +24484,41617,Male,Loyal Customer,21,Business travel,Eco Plus,1269,5,4,4,4,5,5,4,5,3,1,4,4,5,5,44,37.0,satisfied +24485,108496,Male,Loyal Customer,33,Business travel,Business,3637,2,2,2,2,4,4,4,4,5,5,4,5,4,4,91,88.0,satisfied +24486,51928,Male,Loyal Customer,51,Business travel,Business,936,4,5,5,5,5,3,3,4,4,4,4,1,4,1,12,2.0,neutral or dissatisfied +24487,41943,Female,Loyal Customer,47,Business travel,Business,3101,4,4,4,4,3,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +24488,98135,Male,Loyal Customer,14,Personal Travel,Eco,426,2,4,5,5,2,5,2,2,5,4,4,5,4,2,32,42.0,neutral or dissatisfied +24489,14306,Female,Loyal Customer,34,Business travel,Business,395,5,5,3,5,1,5,2,4,4,4,4,1,4,5,0,0.0,satisfied +24490,74028,Male,Loyal Customer,62,Business travel,Eco,1071,4,1,1,1,4,4,4,4,3,2,3,2,5,4,0,0.0,satisfied +24491,121203,Male,Loyal Customer,56,Business travel,Business,2402,1,1,1,1,5,5,5,3,5,4,5,5,4,5,0,0.0,satisfied +24492,100658,Female,disloyal Customer,33,Business travel,Business,677,3,3,3,5,2,3,2,2,5,5,4,5,4,2,0,0.0,neutral or dissatisfied +24493,98488,Female,Loyal Customer,43,Business travel,Business,2732,3,3,3,3,2,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24494,43977,Female,Loyal Customer,52,Business travel,Business,3085,4,4,4,4,1,4,2,5,5,5,5,4,5,5,0,0.0,satisfied +24495,72067,Male,disloyal Customer,35,Business travel,Eco,1281,3,3,3,4,2,3,2,2,1,1,4,2,3,2,54,39.0,neutral or dissatisfied +24496,95014,Female,Loyal Customer,35,Personal Travel,Eco,239,0,4,0,3,1,0,1,1,3,5,4,3,4,1,2,0.0,satisfied +24497,27712,Female,Loyal Customer,26,Business travel,Business,1448,4,4,4,4,4,4,4,4,4,2,3,3,3,4,5,0.0,neutral or dissatisfied +24498,53629,Male,Loyal Customer,40,Personal Travel,Eco,1874,5,4,5,4,2,5,2,2,3,3,3,1,3,2,33,27.0,satisfied +24499,62200,Male,Loyal Customer,31,Personal Travel,Eco,2425,2,5,2,4,2,2,2,2,4,2,4,4,4,2,21,0.0,neutral or dissatisfied +24500,6243,Female,Loyal Customer,46,Business travel,Business,3509,4,4,4,4,3,3,3,4,4,4,4,1,4,5,0,0.0,satisfied +24501,12998,Female,disloyal Customer,44,Business travel,Eco,374,1,0,1,3,3,1,3,3,2,1,4,1,4,3,0,0.0,neutral or dissatisfied +24502,94688,Male,disloyal Customer,38,Business travel,Business,441,3,2,2,1,2,2,2,2,5,3,4,5,4,2,0,0.0,neutral or dissatisfied +24503,127937,Male,Loyal Customer,53,Personal Travel,Eco,2300,4,5,4,1,1,4,1,1,3,5,4,3,5,1,0,0.0,satisfied +24504,122064,Male,Loyal Customer,38,Business travel,Eco,130,4,2,2,2,4,4,4,4,5,3,2,3,1,4,3,2.0,satisfied +24505,14736,Female,Loyal Customer,45,Business travel,Business,3700,4,4,5,4,2,4,2,4,4,4,4,4,4,5,13,0.0,satisfied +24506,64718,Female,Loyal Customer,40,Business travel,Business,2356,0,1,1,1,5,4,5,3,3,3,3,3,3,5,4,0.0,satisfied +24507,83625,Male,Loyal Customer,25,Personal Travel,Eco,409,1,4,1,4,1,1,1,1,4,2,5,5,5,1,5,0.0,neutral or dissatisfied +24508,18886,Male,disloyal Customer,37,Business travel,Eco,448,2,1,3,3,2,3,2,2,3,4,3,3,4,2,26,28.0,neutral or dissatisfied +24509,61925,Male,Loyal Customer,19,Personal Travel,Eco,550,4,0,4,1,1,4,1,1,4,2,3,5,4,1,7,0.0,neutral or dissatisfied +24510,113933,Female,Loyal Customer,51,Personal Travel,Business,1838,0,4,0,5,2,5,5,5,5,0,2,4,5,3,4,0.0,satisfied +24511,52446,Male,Loyal Customer,60,Personal Travel,Eco,370,3,0,3,2,4,3,1,4,5,5,4,5,5,4,24,12.0,neutral or dissatisfied +24512,33661,Female,Loyal Customer,22,Business travel,Eco Plus,413,3,2,2,2,3,2,1,3,2,1,4,1,3,3,0,0.0,neutral or dissatisfied +24513,50793,Female,Loyal Customer,16,Personal Travel,Eco,447,3,4,3,5,4,3,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +24514,44811,Male,Loyal Customer,44,Business travel,Eco,802,4,3,3,3,4,4,4,4,1,1,3,1,3,4,35,34.0,satisfied +24515,34669,Female,Loyal Customer,42,Business travel,Business,2524,4,4,4,4,5,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +24516,117907,Male,Loyal Customer,54,Business travel,Business,3801,0,0,0,2,3,5,4,1,1,1,1,4,1,5,7,7.0,satisfied +24517,52469,Male,Loyal Customer,54,Personal Travel,Eco Plus,493,1,2,1,3,1,1,1,1,3,3,2,3,3,1,0,0.0,neutral or dissatisfied +24518,74190,Male,Loyal Customer,17,Personal Travel,Eco,641,1,4,1,1,1,1,1,1,4,2,5,4,5,1,8,5.0,neutral or dissatisfied +24519,35212,Female,disloyal Customer,47,Business travel,Eco,1056,1,1,1,3,1,1,1,1,1,3,5,5,5,1,6,24.0,neutral or dissatisfied +24520,10584,Male,Loyal Customer,45,Business travel,Business,216,5,5,5,5,4,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +24521,82306,Female,Loyal Customer,11,Personal Travel,Eco,986,2,2,2,4,5,2,5,5,2,5,4,1,4,5,0,0.0,neutral or dissatisfied +24522,71387,Female,Loyal Customer,68,Personal Travel,Eco,258,5,3,0,3,1,2,5,1,1,0,1,2,1,5,10,3.0,satisfied +24523,22731,Female,Loyal Customer,41,Business travel,Eco,170,4,1,1,1,4,4,4,4,3,3,5,2,1,4,0,0.0,satisfied +24524,60860,Male,Loyal Customer,55,Business travel,Business,1491,4,4,4,4,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +24525,29599,Male,Loyal Customer,15,Business travel,Eco,1533,1,4,4,4,1,1,2,1,1,1,4,3,3,1,0,0.0,neutral or dissatisfied +24526,127375,Female,Loyal Customer,41,Business travel,Business,1715,4,4,4,4,4,4,5,4,4,5,4,3,4,5,1,0.0,satisfied +24527,65662,Male,disloyal Customer,38,Business travel,Business,1021,1,2,2,2,1,2,1,1,4,5,5,5,5,1,0,0.0,neutral or dissatisfied +24528,88322,Female,Loyal Customer,61,Business travel,Business,2235,3,3,2,3,5,4,5,5,5,5,5,5,5,3,0,0.0,satisfied +24529,92525,Male,Loyal Customer,24,Personal Travel,Eco,1947,1,4,0,1,1,0,1,1,5,2,5,5,4,1,0,0.0,neutral or dissatisfied +24530,123863,Female,Loyal Customer,50,Business travel,Eco,541,1,4,4,4,1,3,3,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +24531,15422,Male,Loyal Customer,65,Business travel,Eco,399,4,3,3,3,4,4,4,4,3,1,3,4,1,4,0,0.0,satisfied +24532,61512,Female,Loyal Customer,46,Personal Travel,Eco,2419,2,3,2,4,2,3,3,3,3,2,3,3,3,2,0,0.0,neutral or dissatisfied +24533,21078,Male,Loyal Customer,75,Business travel,Business,2642,3,4,4,4,4,3,4,3,3,3,3,1,3,4,31,25.0,neutral or dissatisfied +24534,14323,Female,disloyal Customer,27,Business travel,Eco,395,2,2,2,4,2,3,3,2,4,4,4,3,1,3,195,203.0,neutral or dissatisfied +24535,89669,Male,Loyal Customer,21,Business travel,Eco,1010,2,1,1,1,2,2,4,2,3,2,4,2,3,2,5,0.0,neutral or dissatisfied +24536,43790,Male,Loyal Customer,69,Personal Travel,Eco Plus,546,3,4,3,3,2,3,2,2,5,3,2,5,4,2,5,22.0,neutral or dissatisfied +24537,50442,Female,Loyal Customer,45,Business travel,Eco,110,1,1,1,1,4,3,3,1,1,1,1,4,1,2,0,16.0,neutral or dissatisfied +24538,98499,Male,Loyal Customer,33,Business travel,Business,402,2,2,2,2,4,3,4,4,3,5,4,5,4,4,0,0.0,satisfied +24539,48679,Male,Loyal Customer,58,Business travel,Business,3771,5,5,5,5,2,5,4,4,4,5,4,4,4,4,24,17.0,satisfied +24540,37344,Male,disloyal Customer,35,Business travel,Business,1144,3,3,3,3,1,3,1,1,2,5,4,3,2,1,0,12.0,neutral or dissatisfied +24541,96012,Female,Loyal Customer,50,Business travel,Business,3255,2,5,3,5,5,2,1,2,2,2,2,2,2,2,4,2.0,neutral or dissatisfied +24542,48767,Male,disloyal Customer,26,Business travel,Business,86,2,2,1,3,1,1,1,1,3,4,4,2,4,1,16,5.0,neutral or dissatisfied +24543,128454,Male,Loyal Customer,13,Personal Travel,Eco,370,3,5,3,3,3,3,3,3,4,2,5,3,4,3,0,0.0,neutral or dissatisfied +24544,78509,Female,disloyal Customer,24,Business travel,Eco,526,4,0,3,1,3,3,1,3,4,5,1,1,5,3,0,0.0,neutral or dissatisfied +24545,47997,Male,Loyal Customer,29,Business travel,Eco Plus,329,0,0,0,1,2,0,2,2,5,3,1,2,2,2,0,0.0,satisfied +24546,85151,Male,Loyal Customer,45,Business travel,Business,689,5,5,5,5,4,5,4,3,3,4,3,5,3,3,0,5.0,satisfied +24547,8200,Male,Loyal Customer,54,Business travel,Business,3460,5,5,5,5,2,3,5,5,5,5,4,4,5,1,0,0.0,satisfied +24548,12014,Female,Loyal Customer,21,Personal Travel,Business,351,1,3,1,4,4,1,4,4,2,4,4,1,4,4,17,13.0,neutral or dissatisfied +24549,97779,Male,Loyal Customer,36,Business travel,Business,1522,2,2,3,2,4,4,5,5,5,5,5,4,5,3,10,9.0,satisfied +24550,42122,Female,Loyal Customer,11,Personal Travel,Eco,991,3,5,3,3,4,3,1,4,5,3,4,5,5,4,0,15.0,neutral or dissatisfied +24551,53855,Male,Loyal Customer,59,Business travel,Eco,191,3,5,5,5,3,3,3,3,1,3,2,1,2,3,41,36.0,neutral or dissatisfied +24552,43374,Male,Loyal Customer,64,Personal Travel,Eco,387,1,5,1,3,2,1,2,2,4,1,5,1,2,2,9,10.0,neutral or dissatisfied +24553,16589,Male,Loyal Customer,47,Personal Travel,Eco,872,2,4,2,5,3,2,3,3,1,2,1,1,2,3,0,2.0,neutral or dissatisfied +24554,16469,Male,Loyal Customer,61,Personal Travel,Eco,529,4,1,5,3,5,5,5,5,1,3,4,1,4,5,0,0.0,neutral or dissatisfied +24555,58322,Male,disloyal Customer,34,Business travel,Eco,1170,1,1,1,4,2,1,2,2,4,3,4,4,3,2,0,0.0,neutral or dissatisfied +24556,20038,Male,Loyal Customer,23,Business travel,Business,3164,4,2,2,2,4,4,4,4,2,3,4,1,3,4,0,5.0,neutral or dissatisfied +24557,113524,Female,disloyal Customer,29,Business travel,Business,197,3,3,3,3,3,3,3,3,4,5,4,3,5,3,0,2.0,neutral or dissatisfied +24558,63895,Male,Loyal Customer,45,Business travel,Business,1158,4,4,4,4,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +24559,112133,Female,Loyal Customer,26,Personal Travel,Business,895,3,5,3,3,4,3,4,4,2,4,4,4,4,4,2,11.0,neutral or dissatisfied +24560,44686,Male,disloyal Customer,25,Business travel,Eco,67,2,4,2,1,1,2,3,1,2,5,2,1,1,1,31,61.0,neutral or dissatisfied +24561,89617,Male,Loyal Customer,27,Business travel,Business,3058,4,4,4,4,4,4,4,4,5,4,4,3,5,4,6,0.0,satisfied +24562,104283,Female,Loyal Customer,61,Business travel,Business,382,4,4,4,4,4,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +24563,38488,Female,disloyal Customer,27,Business travel,Business,2446,2,2,2,4,3,2,3,3,1,5,3,2,3,3,0,0.0,neutral or dissatisfied +24564,82322,Male,disloyal Customer,27,Business travel,Business,456,3,3,3,2,3,3,5,3,4,5,5,3,4,3,40,32.0,neutral or dissatisfied +24565,95250,Male,Loyal Customer,67,Personal Travel,Eco,277,3,0,3,2,1,3,1,1,4,5,5,5,4,1,18,12.0,neutral or dissatisfied +24566,29565,Male,Loyal Customer,38,Business travel,Eco,1448,5,2,2,2,5,5,5,5,2,5,4,5,5,5,57,37.0,satisfied +24567,84357,Male,disloyal Customer,28,Business travel,Business,591,3,3,3,5,1,3,1,1,3,3,4,4,5,1,0,0.0,neutral or dissatisfied +24568,865,Male,Loyal Customer,42,Business travel,Business,1656,2,3,3,3,3,4,3,2,2,2,2,3,2,4,20,11.0,neutral or dissatisfied +24569,50647,Female,Loyal Customer,45,Personal Travel,Eco,110,2,4,2,4,1,3,3,3,3,2,5,1,3,3,0,20.0,neutral or dissatisfied +24570,106574,Male,Loyal Customer,40,Business travel,Business,1506,5,5,5,5,3,4,4,5,5,5,5,4,5,4,10,0.0,satisfied +24571,121849,Male,Loyal Customer,41,Business travel,Business,1841,0,0,0,3,4,5,4,5,5,5,5,5,5,4,87,90.0,satisfied +24572,2266,Female,Loyal Customer,52,Business travel,Business,1916,4,4,4,4,4,5,5,5,5,5,5,3,5,4,28,41.0,satisfied +24573,35868,Male,Loyal Customer,36,Personal Travel,Eco,937,4,2,4,4,3,4,3,3,4,2,4,4,3,3,0,2.0,satisfied +24574,27863,Male,Loyal Customer,47,Business travel,Eco Plus,909,5,5,5,5,5,5,5,5,4,1,3,3,1,5,0,0.0,satisfied +24575,43675,Male,Loyal Customer,9,Personal Travel,Eco,695,3,4,3,1,1,3,1,1,4,4,4,5,4,1,0,4.0,neutral or dissatisfied +24576,112368,Female,Loyal Customer,32,Business travel,Business,3122,5,5,5,5,4,4,4,4,3,3,5,5,5,4,7,11.0,satisfied +24577,56096,Male,Loyal Customer,47,Business travel,Business,2402,2,2,2,2,5,4,5,4,4,3,4,3,4,4,4,0.0,satisfied +24578,40561,Female,Loyal Customer,44,Business travel,Business,1815,3,3,3,3,4,3,1,5,5,5,5,4,5,5,0,0.0,satisfied +24579,78605,Female,disloyal Customer,25,Business travel,Business,1426,3,4,2,1,3,2,3,3,4,4,5,5,4,3,0,0.0,neutral or dissatisfied +24580,62541,Male,Loyal Customer,53,Business travel,Business,1744,3,3,3,3,4,4,5,4,4,4,4,3,4,3,0,0.0,satisfied +24581,17839,Male,Loyal Customer,67,Personal Travel,Eco Plus,1075,3,4,3,5,2,3,2,2,3,3,5,3,5,2,13,38.0,neutral or dissatisfied +24582,61302,Male,Loyal Customer,61,Personal Travel,Eco,776,2,4,2,1,3,2,3,3,4,2,5,4,4,3,2,0.0,neutral or dissatisfied +24583,61619,Male,Loyal Customer,40,Business travel,Business,1346,5,1,5,5,5,4,4,4,4,4,4,4,4,5,0,13.0,satisfied +24584,48557,Male,Loyal Customer,63,Personal Travel,Eco,845,3,4,3,3,1,3,1,1,3,2,5,5,4,1,0,0.0,neutral or dissatisfied +24585,13269,Female,Loyal Customer,50,Personal Travel,Eco,468,3,2,3,4,3,3,4,2,5,4,3,4,1,4,243,262.0,neutral or dissatisfied +24586,123024,Male,Loyal Customer,40,Business travel,Business,590,3,2,2,2,3,3,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +24587,87161,Female,disloyal Customer,23,Business travel,Business,946,5,0,5,2,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +24588,74762,Female,Loyal Customer,45,Personal Travel,Eco,1464,3,4,3,4,3,5,4,5,5,3,5,4,5,4,0,0.0,neutral or dissatisfied +24589,65058,Male,Loyal Customer,46,Personal Travel,Eco,247,1,5,1,4,4,1,4,4,5,4,4,4,5,4,4,2.0,neutral or dissatisfied +24590,2754,Male,Loyal Customer,47,Personal Travel,Eco,772,2,4,2,1,4,2,4,4,1,3,3,2,3,4,27,32.0,neutral or dissatisfied +24591,118690,Female,Loyal Customer,40,Personal Travel,Eco,370,2,1,2,3,1,2,1,1,4,2,2,1,3,1,9,2.0,neutral or dissatisfied +24592,88238,Female,Loyal Customer,48,Business travel,Business,2807,5,5,5,5,4,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +24593,1929,Male,Loyal Customer,60,Business travel,Business,293,5,5,5,5,4,5,4,5,5,5,5,4,5,5,9,9.0,satisfied +24594,64139,Male,Loyal Customer,57,Business travel,Business,2505,4,4,4,4,2,2,2,4,4,5,5,2,5,2,344,319.0,satisfied +24595,96382,Female,Loyal Customer,46,Business travel,Business,1342,4,4,4,4,2,5,5,4,4,4,4,4,4,4,0,7.0,satisfied +24596,50820,Male,Loyal Customer,54,Personal Travel,Eco,209,3,4,3,1,3,3,2,3,4,2,3,5,1,3,0,15.0,neutral or dissatisfied +24597,70923,Male,Loyal Customer,43,Business travel,Business,3320,3,5,3,3,4,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +24598,94777,Female,Loyal Customer,59,Business travel,Business,192,1,5,5,5,4,3,3,2,2,2,1,1,2,4,114,97.0,neutral or dissatisfied +24599,99768,Male,Loyal Customer,53,Business travel,Business,3471,1,1,1,1,4,5,5,4,4,4,4,4,4,5,40,40.0,satisfied +24600,128726,Male,Loyal Customer,42,Personal Travel,Eco,1464,1,4,1,1,3,1,4,3,4,4,4,5,4,3,0,6.0,neutral or dissatisfied +24601,98953,Female,Loyal Customer,12,Business travel,Business,3819,3,5,1,1,3,3,3,3,1,4,4,3,4,3,5,16.0,neutral or dissatisfied +24602,66107,Female,Loyal Customer,41,Business travel,Business,3114,2,2,4,2,5,5,4,5,5,5,5,5,5,3,5,7.0,satisfied +24603,127294,Female,Loyal Customer,55,Business travel,Eco Plus,1107,2,2,5,2,2,4,3,1,1,2,1,2,1,1,30,55.0,neutral or dissatisfied +24604,37207,Female,Loyal Customer,42,Business travel,Eco,680,4,1,1,1,1,1,4,4,4,4,4,1,4,3,0,4.0,satisfied +24605,73839,Male,Loyal Customer,51,Business travel,Business,1709,4,4,4,4,5,5,4,4,4,4,4,3,4,4,0,0.0,satisfied +24606,118674,Male,Loyal Customer,72,Business travel,Business,2076,5,5,5,5,1,3,3,3,3,3,3,3,3,4,0,0.0,satisfied +24607,121952,Female,Loyal Customer,53,Business travel,Business,2661,4,5,5,5,3,1,2,4,4,3,4,4,4,2,6,8.0,neutral or dissatisfied +24608,99888,Male,Loyal Customer,56,Business travel,Business,2515,4,4,4,4,3,4,5,4,4,4,4,4,4,4,0,5.0,satisfied +24609,107376,Female,Loyal Customer,69,Personal Travel,Business,725,2,3,2,3,2,4,2,5,5,2,5,1,5,4,14,17.0,neutral or dissatisfied +24610,52988,Female,Loyal Customer,32,Business travel,Business,1190,1,1,1,1,4,4,4,4,2,3,1,2,5,4,21,0.0,satisfied +24611,14762,Female,Loyal Customer,33,Business travel,Business,463,4,4,4,4,3,4,3,4,4,3,4,2,4,2,48,62.0,neutral or dissatisfied +24612,24713,Female,Loyal Customer,38,Business travel,Eco,549,3,3,3,3,3,4,3,3,5,4,5,4,5,3,0,0.0,satisfied +24613,16672,Female,Loyal Customer,69,Personal Travel,Eco,488,3,5,3,2,5,5,4,1,1,3,1,3,1,4,40,26.0,neutral or dissatisfied +24614,76405,Female,Loyal Customer,47,Business travel,Business,1911,5,5,5,5,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +24615,64060,Female,Loyal Customer,51,Business travel,Business,919,4,4,4,4,3,4,5,4,4,4,4,3,4,5,2,0.0,satisfied +24616,14165,Male,Loyal Customer,29,Personal Travel,Business,692,2,4,1,1,5,1,2,5,4,3,4,5,4,5,0,11.0,neutral or dissatisfied +24617,25517,Male,Loyal Customer,34,Business travel,Business,547,4,4,4,4,1,3,3,5,5,5,5,3,5,2,101,86.0,satisfied +24618,17115,Female,Loyal Customer,58,Business travel,Eco,821,5,4,4,4,3,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +24619,51973,Female,Loyal Customer,25,Business travel,Business,3734,3,2,2,2,3,3,3,3,4,1,3,4,3,3,0,0.0,neutral or dissatisfied +24620,27903,Male,Loyal Customer,40,Business travel,Eco Plus,2350,3,4,4,4,5,3,3,4,2,3,1,3,3,3,0,0.0,satisfied +24621,27052,Male,Loyal Customer,30,Business travel,Business,1489,2,2,4,2,5,5,5,5,2,5,5,3,3,5,0,0.0,satisfied +24622,66225,Female,Loyal Customer,50,Business travel,Eco,550,1,2,2,2,5,4,4,1,1,1,1,2,1,2,72,69.0,neutral or dissatisfied +24623,97168,Female,Loyal Customer,21,Personal Travel,Eco,1642,3,4,4,3,4,4,4,4,3,3,5,4,5,4,0,0.0,neutral or dissatisfied +24624,57022,Female,Loyal Customer,53,Personal Travel,Eco,2565,5,1,5,3,5,2,2,3,5,4,4,2,4,2,0,0.0,satisfied +24625,70457,Female,Loyal Customer,48,Business travel,Business,867,5,5,5,5,2,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +24626,5160,Female,Loyal Customer,60,Personal Travel,Eco,622,2,4,2,1,5,5,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +24627,58130,Female,Loyal Customer,36,Business travel,Eco Plus,642,3,5,5,5,3,3,3,3,4,4,3,4,2,3,7,11.0,neutral or dissatisfied +24628,126221,Male,Loyal Customer,53,Business travel,Business,3959,4,4,2,4,4,4,5,3,3,4,3,5,3,4,0,0.0,satisfied +24629,124581,Male,Loyal Customer,42,Business travel,Business,500,3,3,3,3,2,5,4,5,5,5,5,4,5,3,0,8.0,satisfied +24630,9123,Female,Loyal Customer,30,Personal Travel,Eco,765,1,4,2,1,5,2,5,5,3,4,4,4,5,5,0,0.0,neutral or dissatisfied +24631,36378,Male,disloyal Customer,16,Business travel,Eco,200,3,0,2,4,1,2,1,1,5,1,2,1,2,1,0,0.0,neutral or dissatisfied +24632,94062,Male,Loyal Customer,59,Business travel,Business,1691,3,2,2,2,1,3,4,2,2,2,3,3,2,2,0,11.0,neutral or dissatisfied +24633,31900,Male,Loyal Customer,36,Personal Travel,Eco Plus,2762,2,0,2,3,2,2,4,2,4,5,4,5,2,2,12,0.0,neutral or dissatisfied +24634,21391,Female,disloyal Customer,34,Business travel,Eco,399,3,5,3,3,3,3,3,3,5,5,3,2,4,3,0,0.0,neutral or dissatisfied +24635,35365,Male,disloyal Customer,17,Business travel,Eco,1076,4,4,4,3,3,4,3,3,2,4,3,2,5,3,12,0.0,satisfied +24636,37682,Male,Loyal Customer,56,Personal Travel,Eco,1041,2,4,2,4,4,2,4,4,4,2,5,5,4,4,0,0.0,neutral or dissatisfied +24637,101819,Female,disloyal Customer,36,Business travel,Eco,1121,3,3,3,4,5,3,5,5,2,3,1,3,5,5,11,0.0,neutral or dissatisfied +24638,64343,Male,Loyal Customer,15,Business travel,Business,1158,3,3,3,3,3,2,3,3,4,5,4,3,3,3,49,40.0,neutral or dissatisfied +24639,62052,Female,Loyal Customer,47,Personal Travel,Eco,2475,3,3,3,3,4,3,3,2,2,3,2,2,2,3,0,0.0,neutral or dissatisfied +24640,46403,Male,Loyal Customer,48,Personal Travel,Eco Plus,1013,5,3,5,3,2,5,2,2,3,5,4,4,4,2,0,0.0,satisfied +24641,64882,Male,disloyal Customer,23,Business travel,Business,282,0,0,0,5,5,0,5,5,5,5,5,5,5,5,0,0.0,satisfied +24642,89823,Male,Loyal Customer,67,Personal Travel,Eco Plus,1005,3,4,3,5,5,3,2,5,4,2,5,3,5,5,0,0.0,neutral or dissatisfied +24643,13497,Female,Loyal Customer,41,Business travel,Eco,106,5,3,3,3,5,5,5,5,5,1,5,3,3,5,0,1.0,satisfied +24644,83046,Male,Loyal Customer,47,Business travel,Business,1084,2,2,2,2,3,4,4,4,4,5,4,4,4,3,70,75.0,satisfied +24645,19616,Male,Loyal Customer,22,Personal Travel,Eco,416,3,4,3,4,5,3,5,5,3,5,3,2,4,5,0,0.0,neutral or dissatisfied +24646,113364,Female,Loyal Customer,45,Business travel,Business,2293,2,2,2,2,4,5,4,4,4,4,5,5,4,4,0,0.0,satisfied +24647,69319,Male,Loyal Customer,57,Business travel,Business,3068,2,2,2,2,4,4,4,3,3,4,3,5,3,3,0,0.0,satisfied +24648,43259,Male,Loyal Customer,41,Business travel,Business,3855,4,4,4,4,4,5,2,2,2,2,2,3,2,4,0,0.0,satisfied +24649,85945,Male,Loyal Customer,53,Business travel,Business,554,2,2,2,2,5,5,4,4,4,4,4,5,4,5,0,0.0,satisfied +24650,60526,Female,Loyal Customer,57,Personal Travel,Eco,934,1,5,1,5,3,4,5,4,4,1,4,5,4,5,0,0.0,neutral or dissatisfied +24651,109728,Female,disloyal Customer,24,Business travel,Eco,134,1,1,1,4,1,1,1,1,4,1,4,2,3,1,0,0.0,neutral or dissatisfied +24652,16599,Female,Loyal Customer,45,Business travel,Business,2709,4,4,4,4,4,2,1,3,3,3,3,1,3,3,0,0.0,satisfied +24653,74921,Male,Loyal Customer,47,Business travel,Business,2586,1,1,1,1,3,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +24654,24252,Female,Loyal Customer,44,Personal Travel,Eco,147,2,5,2,1,4,5,4,5,5,2,5,5,5,5,0,0.0,neutral or dissatisfied +24655,112288,Male,Loyal Customer,51,Personal Travel,Eco,1447,3,2,3,3,5,3,5,5,4,2,4,2,4,5,17,3.0,neutral or dissatisfied +24656,21755,Female,Loyal Customer,49,Business travel,Eco Plus,563,4,2,2,2,5,3,3,4,4,4,4,3,4,1,45,40.0,satisfied +24657,51245,Female,disloyal Customer,38,Business travel,Eco Plus,156,3,3,3,2,2,3,2,2,2,2,3,3,5,2,0,0.0,neutral or dissatisfied +24658,58057,Female,disloyal Customer,28,Business travel,Business,612,2,2,2,3,3,2,3,3,3,4,4,3,4,3,26,35.0,neutral or dissatisfied +24659,59434,Female,Loyal Customer,50,Business travel,Business,3285,5,5,5,5,2,5,4,4,4,4,4,4,4,5,0,6.0,satisfied +24660,97657,Female,Loyal Customer,56,Business travel,Business,2083,3,3,3,3,3,3,2,3,3,3,3,4,3,3,62,63.0,neutral or dissatisfied +24661,6586,Female,Loyal Customer,46,Personal Travel,Eco,607,1,4,0,3,4,5,5,1,1,0,1,3,1,3,79,82.0,neutral or dissatisfied +24662,84478,Male,disloyal Customer,22,Business travel,Business,2677,5,5,5,1,1,5,3,1,4,2,4,3,5,1,0,0.0,satisfied +24663,80972,Male,Loyal Customer,38,Business travel,Business,297,0,0,0,3,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +24664,74092,Male,disloyal Customer,26,Business travel,Business,641,4,4,4,4,4,4,4,4,3,2,5,4,4,4,0,20.0,satisfied +24665,105381,Female,Loyal Customer,39,Business travel,Business,1779,2,5,3,5,3,4,4,2,2,2,2,3,2,2,27,17.0,neutral or dissatisfied +24666,129363,Male,Loyal Customer,45,Business travel,Business,2565,1,1,1,1,4,3,5,3,3,3,3,5,3,3,0,0.0,satisfied +24667,54561,Male,Loyal Customer,22,Business travel,Eco Plus,925,0,3,0,3,5,0,5,5,1,2,2,3,2,5,0,0.0,satisfied +24668,44127,Female,disloyal Customer,33,Business travel,Eco,198,1,3,1,4,5,1,5,5,4,3,4,4,4,5,0,12.0,neutral or dissatisfied +24669,114481,Female,Loyal Customer,56,Business travel,Business,337,2,2,2,2,3,3,3,2,2,3,2,3,2,1,0,5.0,neutral or dissatisfied +24670,4136,Female,Loyal Customer,55,Business travel,Business,3095,5,5,5,5,3,5,4,5,5,5,5,4,5,5,0,5.0,satisfied +24671,84548,Female,Loyal Customer,17,Personal Travel,Eco,2615,4,3,4,3,1,4,1,1,4,5,2,4,4,1,50,33.0,neutral or dissatisfied +24672,103365,Male,Loyal Customer,45,Business travel,Eco,342,1,2,2,2,1,1,1,1,1,5,3,1,4,1,2,0.0,neutral or dissatisfied +24673,127524,Female,Loyal Customer,51,Business travel,Business,3016,4,4,4,4,3,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +24674,55583,Female,Loyal Customer,38,Personal Travel,Eco,1091,4,1,4,3,1,4,1,1,4,2,3,4,3,1,18,0.0,neutral or dissatisfied +24675,113680,Male,Loyal Customer,56,Personal Travel,Eco,397,1,5,1,5,2,1,2,2,5,5,5,3,5,2,3,0.0,neutral or dissatisfied +24676,17494,Female,disloyal Customer,20,Business travel,Eco,341,2,2,2,4,4,2,4,4,1,1,3,3,3,4,0,16.0,neutral or dissatisfied +24677,77089,Female,Loyal Customer,56,Business travel,Business,1481,2,2,2,2,2,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +24678,40234,Female,Loyal Customer,32,Business travel,Business,3067,2,1,3,1,2,2,2,2,1,5,3,1,4,2,0,0.0,neutral or dissatisfied +24679,99065,Female,Loyal Customer,61,Business travel,Eco,237,4,2,2,2,3,4,3,4,4,4,4,1,4,4,0,0.0,neutral or dissatisfied +24680,71017,Female,Loyal Customer,44,Business travel,Business,2278,5,5,5,5,5,4,5,4,4,4,4,3,4,3,29,62.0,satisfied +24681,61822,Female,Loyal Customer,35,Personal Travel,Eco,1379,3,5,3,2,3,3,3,3,2,1,4,2,1,3,0,0.0,neutral or dissatisfied +24682,65978,Male,disloyal Customer,20,Business travel,Eco,972,2,2,2,4,1,2,5,1,2,2,4,2,4,1,68,50.0,neutral or dissatisfied +24683,61161,Male,Loyal Customer,39,Business travel,Business,909,5,5,5,5,2,5,4,5,5,5,5,3,5,5,0,0.0,satisfied +24684,18447,Male,Loyal Customer,39,Business travel,Business,127,2,5,5,5,5,3,4,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +24685,13675,Male,Loyal Customer,7,Personal Travel,Eco,462,4,4,4,5,3,4,1,3,1,1,3,5,1,3,0,0.0,neutral or dissatisfied +24686,18286,Male,disloyal Customer,22,Business travel,Eco,640,2,3,2,2,2,2,2,2,5,2,1,1,1,2,0,2.0,neutral or dissatisfied +24687,58156,Male,Loyal Customer,42,Business travel,Business,925,5,5,5,5,4,4,4,4,4,4,4,4,4,4,76,91.0,satisfied +24688,94948,Male,disloyal Customer,22,Business travel,Eco,239,2,4,2,3,1,2,1,1,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +24689,52051,Male,Loyal Customer,32,Business travel,Eco,602,5,1,4,4,5,5,5,5,1,3,3,5,1,5,0,0.0,satisfied +24690,89321,Male,Loyal Customer,50,Business travel,Business,1541,5,5,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +24691,28483,Female,Loyal Customer,31,Business travel,Business,1739,5,5,5,5,5,5,5,5,4,5,4,5,3,5,7,2.0,satisfied +24692,117818,Male,Loyal Customer,34,Personal Travel,Eco,328,4,0,4,2,5,4,2,5,4,2,4,4,4,5,0,0.0,neutral or dissatisfied +24693,451,Female,disloyal Customer,27,Business travel,Business,158,5,5,5,3,4,5,4,4,5,3,5,3,5,4,0,0.0,satisfied +24694,102030,Male,disloyal Customer,24,Business travel,Business,226,4,5,4,3,4,4,4,4,4,3,4,4,5,4,7,2.0,satisfied +24695,58564,Male,Loyal Customer,44,Business travel,Business,3015,1,1,1,1,2,5,4,5,5,5,5,4,5,5,25,13.0,satisfied +24696,26789,Male,disloyal Customer,22,Business travel,Eco,226,4,0,4,1,3,4,3,3,2,5,4,3,5,3,0,0.0,satisfied +24697,77395,Male,Loyal Customer,20,Personal Travel,Eco,626,3,4,3,4,2,3,3,2,3,3,4,5,5,2,0,0.0,neutral or dissatisfied +24698,93831,Male,Loyal Customer,48,Business travel,Business,2586,3,3,3,3,4,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +24699,114191,Female,Loyal Customer,32,Business travel,Business,846,3,5,5,5,3,4,3,3,4,2,2,2,3,3,8,0.0,neutral or dissatisfied +24700,2831,Female,disloyal Customer,40,Business travel,Business,409,2,2,2,3,5,2,5,5,1,2,4,3,3,5,108,114.0,neutral or dissatisfied +24701,86333,Female,Loyal Customer,51,Personal Travel,Business,760,5,3,5,3,5,4,2,2,2,5,2,2,2,2,0,0.0,satisfied +24702,129336,Female,Loyal Customer,22,Business travel,Business,2475,4,4,4,4,4,4,4,4,3,5,1,2,5,4,0,0.0,satisfied +24703,80738,Female,Loyal Customer,60,Business travel,Eco,393,4,5,5,5,3,4,1,4,4,4,4,4,4,5,1,0.0,satisfied +24704,43921,Male,Loyal Customer,32,Personal Travel,Eco,174,1,5,0,3,2,0,2,2,3,5,4,4,4,2,0,0.0,neutral or dissatisfied +24705,116442,Male,Loyal Customer,29,Personal Travel,Eco,337,3,1,3,4,3,3,3,3,1,3,4,4,4,3,32,11.0,neutral or dissatisfied +24706,88086,Female,disloyal Customer,29,Business travel,Business,646,3,3,3,4,4,3,4,4,3,4,4,4,4,4,0,0.0,neutral or dissatisfied +24707,114819,Male,Loyal Customer,52,Business travel,Business,362,3,3,3,3,4,4,5,4,4,4,4,4,4,5,14,15.0,satisfied +24708,103078,Female,Loyal Customer,38,Personal Travel,Eco,546,2,4,1,2,3,1,4,3,2,4,1,1,3,3,13,0.0,neutral or dissatisfied +24709,71549,Male,Loyal Customer,51,Business travel,Business,3914,2,2,2,2,5,4,5,4,4,4,4,5,4,4,0,3.0,satisfied +24710,93103,Female,Loyal Customer,69,Personal Travel,Eco,641,4,5,4,3,3,4,5,3,3,4,3,5,3,4,17,27.0,neutral or dissatisfied +24711,46036,Female,Loyal Customer,42,Business travel,Business,996,3,3,3,3,1,1,2,3,3,3,3,3,3,3,0,21.0,neutral or dissatisfied +24712,52986,Male,Loyal Customer,55,Business travel,Business,3402,1,1,1,1,5,3,5,3,3,3,3,5,3,1,7,9.0,satisfied +24713,79013,Male,Loyal Customer,39,Business travel,Business,2272,3,5,5,5,4,4,4,3,3,4,3,3,3,2,0,0.0,neutral or dissatisfied +24714,47001,Male,Loyal Customer,67,Business travel,Eco Plus,444,2,3,3,3,2,2,2,2,1,2,3,1,3,2,52,26.0,neutral or dissatisfied +24715,58285,Female,Loyal Customer,7,Personal Travel,Eco,678,3,5,3,3,3,3,3,3,4,4,5,4,4,3,5,0.0,neutral or dissatisfied +24716,79906,Female,Loyal Customer,51,Business travel,Business,1096,4,4,4,4,3,4,4,4,4,5,4,5,4,4,0,15.0,satisfied +24717,23993,Male,Loyal Customer,40,Business travel,Business,562,2,2,2,2,2,2,3,5,5,5,5,1,5,3,25,37.0,satisfied +24718,32225,Male,Loyal Customer,58,Business travel,Business,216,3,3,3,3,5,2,5,4,4,5,3,1,4,2,0,18.0,satisfied +24719,100569,Female,Loyal Customer,36,Business travel,Business,3451,4,4,4,4,4,4,5,4,4,3,4,3,4,5,0,0.0,satisfied +24720,52226,Male,Loyal Customer,24,Business travel,Business,3705,4,4,5,4,4,4,4,4,1,5,4,4,2,4,0,0.0,satisfied +24721,64156,Male,disloyal Customer,12,Business travel,Eco,989,3,4,4,1,4,4,4,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +24722,125889,Female,Loyal Customer,10,Personal Travel,Eco,951,1,3,1,3,4,1,4,4,3,4,4,4,4,4,9,54.0,neutral or dissatisfied +24723,89665,Female,Loyal Customer,35,Business travel,Business,1010,1,5,5,5,4,4,4,1,1,2,1,4,1,2,0,0.0,neutral or dissatisfied +24724,57499,Male,disloyal Customer,28,Business travel,Business,1075,2,2,2,3,1,2,2,1,4,5,3,4,4,1,0,4.0,neutral or dissatisfied +24725,51489,Female,disloyal Customer,28,Business travel,Business,370,1,1,1,3,2,1,2,2,2,1,4,3,3,2,74,61.0,neutral or dissatisfied +24726,94155,Male,Loyal Customer,42,Business travel,Business,2254,2,2,5,2,4,4,5,4,4,4,4,3,4,3,0,7.0,satisfied +24727,43508,Male,Loyal Customer,50,Personal Travel,Eco,524,3,4,3,3,5,3,5,5,3,4,4,3,5,5,7,39.0,neutral or dissatisfied +24728,20569,Male,Loyal Customer,62,Business travel,Business,3468,2,2,2,2,2,2,2,2,2,2,2,2,2,3,0,0.0,neutral or dissatisfied +24729,82792,Female,disloyal Customer,36,Business travel,Business,231,3,3,3,1,2,3,2,2,5,2,4,4,4,2,0,0.0,neutral or dissatisfied +24730,65625,Female,Loyal Customer,57,Personal Travel,Eco,175,3,4,3,4,5,4,5,1,1,3,1,5,1,4,14,14.0,neutral or dissatisfied +24731,67175,Female,Loyal Customer,45,Personal Travel,Eco,1119,3,5,3,3,5,5,5,4,4,3,4,4,4,4,0,21.0,neutral or dissatisfied +24732,9936,Male,Loyal Customer,25,Business travel,Eco,534,1,2,2,2,1,1,2,1,4,3,4,1,4,1,0,13.0,neutral or dissatisfied +24733,14985,Male,Loyal Customer,42,Personal Travel,Eco,927,2,4,2,5,1,2,1,1,5,4,5,4,4,1,32,30.0,neutral or dissatisfied +24734,58554,Female,Loyal Customer,68,Personal Travel,Eco,1514,1,3,1,3,4,4,3,5,5,1,5,2,5,2,8,10.0,neutral or dissatisfied +24735,89887,Female,disloyal Customer,45,Business travel,Business,1416,4,4,4,4,3,4,3,3,5,5,5,4,5,3,0,0.0,satisfied +24736,103070,Male,disloyal Customer,28,Business travel,Eco,460,1,0,1,1,5,1,5,5,5,1,2,1,1,5,0,12.0,neutral or dissatisfied +24737,40641,Male,Loyal Customer,41,Personal Travel,Eco Plus,391,2,4,2,5,5,2,5,5,3,3,5,3,4,5,1,12.0,neutral or dissatisfied +24738,58713,Female,Loyal Customer,39,Business travel,Business,1849,1,1,1,1,5,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +24739,97314,Male,Loyal Customer,25,Business travel,Business,872,3,3,3,3,3,3,3,3,4,5,3,4,3,3,0,0.0,neutral or dissatisfied +24740,24208,Female,disloyal Customer,18,Business travel,Eco,302,3,1,3,3,4,3,4,4,1,1,2,2,2,4,0,0.0,neutral or dissatisfied +24741,11835,Male,Loyal Customer,19,Personal Travel,Eco,986,3,5,2,5,5,2,5,5,5,2,5,3,4,5,0,0.0,neutral or dissatisfied +24742,66564,Female,disloyal Customer,27,Business travel,Business,328,1,1,1,1,3,1,1,3,5,3,5,5,5,3,0,0.0,neutral or dissatisfied +24743,69176,Female,Loyal Customer,64,Personal Travel,Eco,187,3,5,3,2,2,4,5,2,2,3,2,5,2,3,52,57.0,neutral or dissatisfied +24744,8031,Female,Loyal Customer,50,Business travel,Business,2061,4,4,4,4,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +24745,43765,Female,Loyal Customer,41,Business travel,Business,3650,3,2,2,2,5,2,2,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +24746,120014,Female,Loyal Customer,11,Personal Travel,Eco,328,1,2,1,3,4,1,4,4,4,2,4,2,3,4,18,13.0,neutral or dissatisfied +24747,41170,Male,Loyal Customer,32,Business travel,Eco Plus,140,5,4,4,4,5,5,5,5,3,2,5,4,3,5,0,10.0,satisfied +24748,53777,Male,Loyal Customer,30,Business travel,Business,2229,5,5,5,5,5,5,4,5,3,5,5,3,5,5,69,59.0,satisfied +24749,60044,Female,disloyal Customer,26,Business travel,Business,937,4,4,4,2,3,4,3,3,3,2,4,4,4,3,0,0.0,satisfied +24750,112042,Female,Loyal Customer,27,Business travel,Business,1123,2,2,2,2,5,5,5,5,3,3,5,3,5,5,1,0.0,satisfied +24751,48295,Female,Loyal Customer,45,Business travel,Eco,1499,3,4,4,4,1,4,4,3,3,3,3,3,3,2,32,58.0,satisfied +24752,52072,Male,Loyal Customer,32,Business travel,Business,3060,4,4,2,4,5,5,5,5,4,1,1,1,3,5,0,0.0,satisfied +24753,37508,Male,disloyal Customer,49,Business travel,Business,1076,2,2,2,3,5,2,5,5,1,3,2,4,2,5,8,25.0,neutral or dissatisfied +24754,37323,Female,Loyal Customer,55,Business travel,Eco,972,4,3,3,3,3,4,3,4,4,4,4,3,4,1,0,0.0,satisfied +24755,25066,Male,Loyal Customer,67,Personal Travel,Eco,594,2,5,2,3,4,2,4,4,4,5,3,1,4,4,0,0.0,neutral or dissatisfied +24756,110294,Female,Loyal Customer,44,Business travel,Business,2957,2,2,2,2,3,5,5,4,4,5,4,3,4,5,0,0.0,satisfied +24757,66578,Female,Loyal Customer,37,Personal Travel,Eco,624,1,1,1,2,3,1,3,3,2,4,2,2,3,3,14,21.0,neutral or dissatisfied +24758,72575,Female,Loyal Customer,49,Business travel,Eco,529,5,2,5,2,3,4,5,5,5,5,5,5,5,4,0,0.0,satisfied +24759,56439,Male,Loyal Customer,61,Business travel,Eco,319,4,2,2,2,4,4,4,4,1,1,2,3,4,4,0,0.0,satisfied +24760,31007,Male,Loyal Customer,33,Business travel,Business,3514,3,2,5,2,3,4,3,3,1,4,4,4,4,3,3,6.0,neutral or dissatisfied +24761,108253,Male,Loyal Customer,64,Business travel,Business,2660,2,2,2,2,2,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +24762,101846,Male,Loyal Customer,31,Business travel,Business,519,1,4,4,4,1,1,1,1,4,5,4,1,4,1,44,34.0,neutral or dissatisfied +24763,36667,Male,Loyal Customer,11,Personal Travel,Eco,1249,4,5,5,4,3,5,3,3,4,3,4,5,4,3,39,66.0,neutral or dissatisfied +24764,52547,Female,Loyal Customer,63,Business travel,Eco,160,5,3,3,3,4,5,1,5,5,5,5,2,5,4,0,5.0,satisfied +24765,44069,Female,Loyal Customer,36,Personal Travel,Eco,610,1,1,1,3,1,1,1,3,4,4,3,1,4,1,159,160.0,neutral or dissatisfied +24766,19135,Female,Loyal Customer,45,Business travel,Eco Plus,265,5,4,4,4,3,4,3,5,5,5,5,2,5,4,0,27.0,satisfied +24767,34972,Female,Loyal Customer,44,Business travel,Business,3813,1,1,1,1,5,1,2,4,4,4,4,2,4,4,4,0.0,satisfied +24768,70159,Female,Loyal Customer,29,Personal Travel,Eco,460,3,2,3,2,4,3,5,4,2,4,3,2,2,4,49,68.0,neutral or dissatisfied +24769,68901,Male,Loyal Customer,31,Personal Travel,Eco,1061,2,4,2,1,5,2,3,5,3,3,4,3,4,5,0,2.0,neutral or dissatisfied +24770,124548,Female,Loyal Customer,50,Personal Travel,Eco,1276,2,4,2,4,5,3,2,5,5,2,3,3,5,1,0,0.0,neutral or dissatisfied +24771,31207,Male,Loyal Customer,52,Business travel,Business,2926,1,5,5,5,5,3,3,1,1,1,1,1,1,4,120,124.0,neutral or dissatisfied +24772,28524,Female,disloyal Customer,26,Business travel,Eco,2701,2,2,2,1,4,2,4,4,3,1,5,1,5,4,0,0.0,neutral or dissatisfied +24773,112460,Male,Loyal Customer,27,Business travel,Eco,853,4,1,1,1,4,4,4,4,4,1,3,2,4,4,33,34.0,satisfied +24774,121519,Male,Loyal Customer,22,Personal Travel,Business,912,2,3,2,3,3,2,3,3,1,4,4,3,4,3,0,6.0,neutral or dissatisfied +24775,26903,Male,Loyal Customer,45,Business travel,Business,1770,2,3,2,2,4,3,4,1,1,2,1,2,1,1,0,0.0,satisfied +24776,120648,Male,Loyal Customer,37,Business travel,Business,3831,4,4,4,4,4,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +24777,44081,Male,Loyal Customer,23,Business travel,Eco Plus,651,4,4,4,4,4,5,5,4,3,1,3,1,3,4,0,0.0,satisfied +24778,45310,Female,Loyal Customer,48,Business travel,Business,290,2,3,3,3,4,4,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +24779,59702,Male,Loyal Customer,28,Personal Travel,Eco,965,3,2,4,1,1,4,1,1,1,3,1,3,1,1,0,0.0,neutral or dissatisfied +24780,112117,Female,disloyal Customer,27,Business travel,Business,977,5,5,5,4,3,5,5,3,3,3,5,4,4,3,40,31.0,satisfied +24781,12329,Male,Loyal Customer,38,Business travel,Eco,201,5,1,1,1,5,4,5,5,1,2,5,2,2,5,0,1.0,satisfied +24782,45173,Female,Loyal Customer,48,Personal Travel,Eco,174,2,2,0,2,3,3,3,4,4,0,4,4,4,1,0,0.0,neutral or dissatisfied +24783,102596,Male,disloyal Customer,22,Business travel,Eco,407,3,0,3,3,5,3,5,5,1,3,3,3,4,5,0,0.0,neutral or dissatisfied +24784,54364,Female,Loyal Customer,29,Personal Travel,Eco,1235,2,1,2,4,4,2,4,4,3,5,4,1,3,4,0,0.0,neutral or dissatisfied +24785,48039,Female,Loyal Customer,61,Business travel,Eco,677,5,4,4,4,2,1,5,5,5,5,5,5,5,4,108,101.0,satisfied +24786,47753,Female,Loyal Customer,45,Business travel,Business,3661,4,4,4,4,2,1,4,5,5,5,5,2,5,3,67,55.0,satisfied +24787,23655,Female,Loyal Customer,48,Business travel,Eco,73,5,1,1,1,2,1,2,3,3,5,3,2,3,4,0,0.0,satisfied +24788,69893,Female,Loyal Customer,42,Personal Travel,Business,1671,2,1,2,4,5,4,4,2,2,2,2,4,2,1,39,40.0,neutral or dissatisfied +24789,72522,Female,Loyal Customer,14,Business travel,Eco,1119,4,5,5,5,4,4,2,4,1,5,3,4,4,4,3,0.0,neutral or dissatisfied +24790,123609,Female,Loyal Customer,49,Business travel,Business,1773,4,4,4,4,4,5,4,2,2,2,2,3,2,3,0,0.0,satisfied +24791,54457,Female,Loyal Customer,37,Business travel,Business,3258,4,4,4,4,3,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +24792,47269,Male,Loyal Customer,48,Business travel,Business,574,2,2,2,2,5,4,4,4,4,4,4,3,4,2,0,3.0,satisfied +24793,58598,Female,Loyal Customer,66,Personal Travel,Eco,334,2,5,5,4,3,4,5,3,3,5,3,4,3,4,0,0.0,neutral or dissatisfied +24794,42753,Male,Loyal Customer,8,Personal Travel,Eco Plus,607,2,5,2,3,1,2,4,1,4,2,5,5,5,1,0,8.0,neutral or dissatisfied +24795,123825,Male,Loyal Customer,48,Business travel,Business,2713,1,1,1,1,3,4,4,5,5,5,5,5,5,4,9,15.0,satisfied +24796,66572,Male,disloyal Customer,28,Business travel,Business,624,4,4,4,2,1,4,1,1,4,2,5,4,5,1,0,0.0,satisfied +24797,31258,Female,Loyal Customer,30,Business travel,Business,3731,1,1,1,1,4,4,4,4,3,5,4,4,1,4,0,0.0,satisfied +24798,30959,Female,Loyal Customer,70,Personal Travel,Eco,1024,3,4,3,4,3,4,5,4,4,3,4,4,4,5,98,95.0,neutral or dissatisfied +24799,10534,Male,Loyal Customer,58,Business travel,Business,2470,3,3,3,3,3,4,5,5,5,5,5,5,5,4,17,8.0,satisfied +24800,115061,Male,disloyal Customer,36,Business travel,Business,447,2,2,2,5,5,2,5,5,3,2,5,4,4,5,8,1.0,neutral or dissatisfied +24801,7730,Female,Loyal Customer,40,Personal Travel,Eco,806,2,1,2,3,3,2,3,3,2,3,3,2,3,3,0,0.0,neutral or dissatisfied +24802,92556,Female,Loyal Customer,46,Personal Travel,Eco,2092,2,0,2,3,2,5,5,5,5,2,5,3,5,5,4,0.0,neutral or dissatisfied +24803,32873,Male,Loyal Customer,30,Personal Travel,Eco,216,1,0,0,3,1,0,1,1,2,4,3,5,1,1,0,2.0,neutral or dissatisfied +24804,117285,Female,Loyal Customer,54,Business travel,Business,325,0,0,0,3,4,4,5,4,4,2,2,4,4,3,3,0.0,satisfied +24805,86111,Male,Loyal Customer,42,Business travel,Business,356,5,5,5,5,5,5,4,5,5,5,5,5,5,5,0,0.0,satisfied +24806,10171,Male,Loyal Customer,59,Business travel,Business,482,4,4,4,4,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +24807,46886,Male,Loyal Customer,29,Business travel,Eco,819,5,3,3,3,5,5,5,5,5,5,3,3,2,5,0,0.0,satisfied +24808,127905,Female,Loyal Customer,63,Personal Travel,Eco,1671,3,2,3,4,2,4,3,1,1,3,1,1,1,2,0,4.0,neutral or dissatisfied +24809,52113,Male,Loyal Customer,56,Personal Travel,Eco,438,1,3,1,3,3,1,3,3,1,3,2,4,4,3,0,0.0,neutral or dissatisfied +24810,6535,Female,Loyal Customer,25,Business travel,Business,473,5,5,5,5,5,5,5,5,4,4,5,5,5,5,1,0.0,satisfied +24811,85210,Male,disloyal Customer,28,Business travel,Eco,731,2,2,2,3,4,2,4,4,3,1,4,2,4,4,1,0.0,neutral or dissatisfied +24812,54375,Female,Loyal Customer,52,Business travel,Business,305,3,3,4,3,4,1,4,4,4,4,4,3,4,2,0,0.0,satisfied +24813,86868,Female,Loyal Customer,21,Personal Travel,Eco,484,2,1,2,5,2,2,2,2,4,4,4,3,4,2,0,0.0,neutral or dissatisfied +24814,90235,Female,Loyal Customer,56,Personal Travel,Eco Plus,1084,2,5,2,4,4,4,5,3,3,2,3,3,3,3,0,12.0,neutral or dissatisfied +24815,103653,Female,Loyal Customer,32,Business travel,Business,405,1,1,1,1,2,2,2,2,3,5,5,4,4,2,0,0.0,satisfied +24816,26621,Male,Loyal Customer,35,Business travel,Business,406,2,5,5,5,2,2,3,2,2,2,2,4,2,1,3,12.0,neutral or dissatisfied +24817,118678,Male,Loyal Customer,77,Business travel,Eco,304,2,4,4,4,1,2,1,1,3,3,3,4,4,1,0,11.0,neutral or dissatisfied +24818,17345,Female,Loyal Customer,31,Business travel,Business,3190,5,5,5,5,4,4,4,4,5,5,5,3,2,4,0,0.0,satisfied +24819,635,Male,disloyal Customer,55,Business travel,Business,158,5,5,5,3,3,5,3,3,4,5,5,4,5,3,1,0.0,satisfied +24820,3821,Female,disloyal Customer,23,Business travel,Eco,650,3,2,3,3,1,3,1,1,4,5,4,3,4,1,76,78.0,neutral or dissatisfied +24821,109114,Male,Loyal Customer,53,Business travel,Business,816,5,5,5,5,5,5,4,5,5,4,5,4,5,3,0,4.0,satisfied +24822,128491,Female,Loyal Customer,44,Personal Travel,Eco,621,2,4,2,1,3,4,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +24823,31510,Female,Loyal Customer,25,Business travel,Eco,846,4,4,4,4,4,3,1,4,1,3,3,4,2,4,24,14.0,neutral or dissatisfied +24824,23105,Female,Loyal Customer,48,Business travel,Eco,300,5,4,3,3,3,2,5,5,5,5,5,4,5,2,0,0.0,satisfied +24825,111268,Male,disloyal Customer,20,Business travel,Eco,479,4,0,4,4,1,4,1,1,3,2,5,5,5,1,13,11.0,satisfied +24826,109022,Male,Loyal Customer,39,Business travel,Business,1724,1,1,1,1,2,4,5,4,4,4,4,3,4,3,10,0.0,satisfied +24827,47992,Male,Loyal Customer,32,Business travel,Eco Plus,550,5,4,4,4,5,5,5,5,5,2,1,5,1,5,78,75.0,satisfied +24828,39254,Female,disloyal Customer,20,Business travel,Eco,268,2,0,2,3,3,2,1,3,1,4,4,1,4,3,0,0.0,neutral or dissatisfied +24829,56149,Male,Loyal Customer,60,Business travel,Business,1400,3,3,5,3,2,4,5,5,5,5,5,4,5,5,54,48.0,satisfied +24830,13233,Female,Loyal Customer,33,Business travel,Business,1604,5,5,5,5,1,2,3,5,5,5,5,4,5,2,0,0.0,satisfied +24831,76097,Male,Loyal Customer,61,Personal Travel,Eco,669,2,4,2,1,1,2,1,1,3,5,5,3,4,1,0,0.0,neutral or dissatisfied +24832,121669,Female,Loyal Customer,25,Business travel,Business,1872,2,2,2,2,4,4,4,4,5,4,3,5,1,4,0,0.0,satisfied +24833,26489,Male,Loyal Customer,52,Business travel,Eco,829,5,2,2,2,5,5,5,5,4,3,5,4,2,5,3,0.0,satisfied +24834,115860,Female,Loyal Customer,60,Business travel,Business,404,2,3,3,3,5,4,4,2,2,2,2,4,2,1,12,8.0,neutral or dissatisfied +24835,125899,Male,Loyal Customer,70,Personal Travel,Eco,861,2,5,2,4,4,2,4,4,4,2,5,4,4,4,3,14.0,neutral or dissatisfied +24836,77645,Male,Loyal Customer,30,Business travel,Business,731,2,2,2,2,3,4,3,3,3,4,5,3,5,3,0,0.0,satisfied +24837,94983,Female,Loyal Customer,38,Personal Travel,Eco,293,3,5,3,2,1,3,1,1,3,5,4,4,5,1,0,26.0,neutral or dissatisfied +24838,43896,Female,disloyal Customer,39,Business travel,Eco,199,1,2,1,4,1,1,1,1,1,3,3,3,4,1,38,29.0,neutral or dissatisfied +24839,17527,Female,Loyal Customer,51,Business travel,Eco Plus,341,4,4,4,4,4,2,2,4,4,4,4,5,4,3,0,0.0,satisfied +24840,88833,Male,Loyal Customer,64,Personal Travel,Eco Plus,406,5,1,4,3,2,4,4,2,3,1,3,4,2,2,0,0.0,satisfied +24841,102297,Male,Loyal Customer,55,Business travel,Eco,197,4,4,4,4,4,4,4,4,1,3,1,4,2,4,28,33.0,neutral or dissatisfied +24842,61399,Female,Loyal Customer,39,Personal Travel,Eco,679,2,4,2,3,3,2,3,3,5,5,5,4,5,3,5,0.0,neutral or dissatisfied +24843,15907,Male,disloyal Customer,20,Business travel,Eco,566,4,3,4,2,2,4,1,2,1,4,3,5,3,2,1,18.0,neutral or dissatisfied +24844,46153,Male,disloyal Customer,40,Business travel,Business,227,5,5,5,2,1,5,1,1,4,1,3,1,2,1,10,17.0,satisfied +24845,18749,Male,Loyal Customer,43,Business travel,Business,1678,2,2,2,2,2,5,1,4,4,4,4,5,4,1,49,20.0,satisfied +24846,49770,Female,Loyal Customer,49,Business travel,Business,109,4,5,5,5,4,3,3,4,4,4,4,2,4,3,0,0.0,neutral or dissatisfied +24847,55853,Female,disloyal Customer,11,Business travel,Eco,1416,1,0,0,4,5,1,5,5,4,4,5,4,4,5,0,0.0,neutral or dissatisfied +24848,54838,Female,Loyal Customer,56,Business travel,Business,3081,2,2,2,2,2,5,5,4,4,4,4,3,4,4,11,9.0,satisfied +24849,54667,Female,disloyal Customer,52,Business travel,Eco,964,1,1,1,3,1,1,1,1,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +24850,38702,Male,disloyal Customer,21,Business travel,Eco,1104,2,3,3,3,2,2,2,2,2,4,4,2,5,2,1,0.0,neutral or dissatisfied +24851,33771,Male,disloyal Customer,44,Business travel,Eco,490,4,4,4,3,5,4,5,5,2,5,4,4,1,5,0,0.0,neutral or dissatisfied +24852,23321,Female,Loyal Customer,29,Business travel,Business,563,4,4,4,4,5,5,5,5,5,1,5,2,2,5,5,0.0,satisfied +24853,29724,Female,Loyal Customer,23,Personal Travel,Eco,2797,3,3,2,3,2,3,3,4,5,4,3,3,3,3,0,0.0,neutral or dissatisfied +24854,17074,Male,Loyal Customer,49,Personal Travel,Eco,651,1,1,1,3,1,1,1,1,2,1,2,2,3,1,29,15.0,neutral or dissatisfied +24855,104590,Female,Loyal Customer,43,Personal Travel,Eco,369,1,4,1,4,1,4,3,2,2,1,2,4,2,3,0,2.0,neutral or dissatisfied +24856,17034,Female,Loyal Customer,54,Business travel,Eco Plus,781,1,2,3,3,1,1,1,4,3,2,3,1,1,1,141,135.0,neutral or dissatisfied +24857,86375,Male,Loyal Customer,26,Business travel,Business,2085,1,1,1,1,5,5,5,5,4,5,5,3,4,5,37,23.0,satisfied +24858,2743,Female,disloyal Customer,30,Business travel,Eco,772,3,3,3,4,5,3,5,5,2,3,4,1,3,5,25,49.0,neutral or dissatisfied +24859,13350,Female,Loyal Customer,26,Business travel,Business,946,3,4,4,4,3,3,3,3,1,3,2,2,2,3,0,0.0,neutral or dissatisfied +24860,86722,Female,Loyal Customer,52,Personal Travel,Eco,1747,1,2,1,3,3,4,3,1,1,1,1,3,1,4,11,6.0,neutral or dissatisfied +24861,54714,Female,Loyal Customer,17,Personal Travel,Eco,964,2,4,3,4,2,3,2,2,3,5,5,5,4,2,0,0.0,neutral or dissatisfied +24862,2278,Male,disloyal Customer,27,Business travel,Business,925,3,3,3,2,2,3,2,2,2,5,2,2,3,2,0,9.0,neutral or dissatisfied +24863,54992,Male,Loyal Customer,59,Business travel,Business,1346,2,2,2,2,4,5,5,4,4,4,4,4,4,3,0,0.0,satisfied +24864,5107,Female,Loyal Customer,59,Personal Travel,Eco,235,4,5,4,3,4,4,5,3,3,4,3,3,3,3,0,0.0,neutral or dissatisfied +24865,68288,Male,disloyal Customer,25,Business travel,Eco,406,3,0,3,2,5,3,5,5,5,3,3,1,4,5,0,0.0,neutral or dissatisfied +24866,79066,Female,disloyal Customer,50,Business travel,Eco,356,2,0,2,3,1,2,1,1,4,4,1,5,3,1,0,0.0,neutral or dissatisfied +24867,23939,Female,Loyal Customer,12,Personal Travel,Eco,616,2,3,3,4,4,3,4,4,2,4,1,3,1,4,88,83.0,neutral or dissatisfied +24868,45030,Male,Loyal Customer,49,Personal Travel,Eco,867,1,5,1,5,3,1,3,3,4,3,5,3,4,3,0,5.0,neutral or dissatisfied +24869,5664,Female,Loyal Customer,57,Business travel,Business,299,1,1,1,1,4,5,5,5,5,4,5,5,5,4,0,0.0,satisfied +24870,14279,Male,Loyal Customer,58,Business travel,Business,175,4,4,4,4,4,3,5,5,5,5,5,1,5,5,19,8.0,satisfied +24871,127123,Female,Loyal Customer,62,Personal Travel,Eco,338,4,4,4,4,2,5,5,3,3,4,3,5,3,3,27,30.0,neutral or dissatisfied +24872,10790,Female,Loyal Customer,22,Business travel,Eco,667,2,1,1,1,2,2,2,2,1,2,4,1,4,2,61,58.0,neutral or dissatisfied +24873,85784,Female,Loyal Customer,24,Business travel,Business,666,5,5,5,5,4,4,4,4,3,3,5,5,4,4,9,0.0,satisfied +24874,47968,Male,Loyal Customer,35,Personal Travel,Eco,462,1,4,1,3,5,1,5,5,4,5,3,2,5,5,0,0.0,neutral or dissatisfied +24875,50828,Female,Loyal Customer,32,Personal Travel,Eco,308,3,4,3,3,5,3,5,5,3,3,5,4,4,5,45,40.0,neutral or dissatisfied +24876,42228,Male,Loyal Customer,40,Business travel,Business,550,3,5,5,5,3,3,4,3,3,3,3,1,3,1,0,0.0,neutral or dissatisfied +24877,64445,Male,Loyal Customer,54,Business travel,Business,3447,2,5,5,5,3,2,3,2,2,2,2,1,2,1,0,10.0,neutral or dissatisfied +24878,18980,Male,Loyal Customer,32,Personal Travel,Business,388,2,4,2,2,4,2,4,4,3,4,4,3,5,4,0,0.0,neutral or dissatisfied +24879,129098,Male,Loyal Customer,49,Business travel,Business,2069,4,4,4,4,5,1,4,5,5,4,5,2,5,4,23,4.0,satisfied +24880,49147,Male,Loyal Customer,49,Business travel,Eco,199,4,5,5,5,4,4,4,5,3,2,3,4,5,4,283,305.0,satisfied +24881,47061,Female,disloyal Customer,33,Business travel,Eco,351,2,2,2,3,5,2,5,5,3,2,4,4,4,5,0,0.0,neutral or dissatisfied +24882,112392,Female,Loyal Customer,46,Business travel,Business,2911,2,2,2,2,3,5,4,2,2,2,2,5,2,4,25,16.0,satisfied +24883,112262,Female,Loyal Customer,47,Business travel,Business,1546,3,4,4,4,4,4,4,3,3,2,3,3,3,3,0,0.0,neutral or dissatisfied +24884,52789,Female,disloyal Customer,33,Business travel,Eco,760,2,2,2,3,5,2,5,5,3,5,4,2,3,5,65,58.0,neutral or dissatisfied +24885,40301,Female,Loyal Customer,11,Personal Travel,Eco,402,4,5,4,4,2,4,4,2,4,3,4,5,5,2,0,4.0,neutral or dissatisfied +24886,7246,Female,Loyal Customer,53,Personal Travel,Eco,135,3,2,3,3,3,4,4,4,4,3,4,2,4,4,2,65.0,neutral or dissatisfied +24887,112750,Male,Loyal Customer,26,Business travel,Business,3032,1,1,1,1,5,5,5,5,4,3,5,4,5,5,12,0.0,satisfied +24888,118776,Male,Loyal Customer,8,Personal Travel,Eco,304,2,3,2,3,1,2,1,1,3,2,4,1,3,1,0,0.0,neutral or dissatisfied +24889,117038,Male,Loyal Customer,41,Business travel,Business,1862,1,3,3,3,5,2,3,1,1,1,1,4,1,4,11,0.0,neutral or dissatisfied +24890,97986,Female,Loyal Customer,29,Personal Travel,Eco,616,1,5,1,4,4,1,4,4,4,1,2,4,3,4,31,42.0,neutral or dissatisfied +24891,5432,Male,Loyal Customer,76,Business travel,Business,265,3,4,4,4,3,4,4,3,3,3,3,3,3,1,35,25.0,neutral or dissatisfied +24892,62909,Male,Loyal Customer,37,Personal Travel,Business,909,3,1,3,2,5,2,2,4,4,3,4,4,4,1,24,10.0,neutral or dissatisfied +24893,31652,Male,Loyal Customer,39,Business travel,Business,3446,5,5,5,5,2,4,5,5,5,5,5,2,5,3,0,0.0,satisfied +24894,59894,Female,Loyal Customer,41,Business travel,Business,997,4,4,4,4,4,4,4,5,5,5,5,3,5,3,0,0.0,satisfied +24895,118693,Male,Loyal Customer,42,Personal Travel,Eco,370,3,2,2,3,1,2,1,1,2,3,2,1,4,1,0,5.0,neutral or dissatisfied +24896,39590,Male,Loyal Customer,54,Business travel,Business,2811,3,3,3,3,2,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +24897,108622,Male,Loyal Customer,66,Personal Travel,Eco,696,1,5,0,4,2,0,2,2,5,5,5,4,5,2,0,0.0,neutral or dissatisfied +24898,106319,Male,Loyal Customer,47,Business travel,Business,825,5,5,5,5,4,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +24899,67878,Male,Loyal Customer,40,Personal Travel,Eco,1242,3,4,3,2,4,3,2,4,5,2,4,3,5,4,0,0.0,neutral or dissatisfied +24900,112771,Male,Loyal Customer,55,Business travel,Business,188,5,5,3,5,1,5,3,5,5,5,3,2,5,4,19,3.0,satisfied +24901,74991,Male,Loyal Customer,64,Personal Travel,Eco Plus,2475,1,5,1,5,1,1,5,1,3,2,4,3,5,1,0,0.0,neutral or dissatisfied +24902,2095,Female,Loyal Customer,67,Personal Travel,Eco,812,4,2,4,3,2,3,4,4,4,4,4,4,4,4,7,5.0,satisfied +24903,59676,Female,Loyal Customer,32,Personal Travel,Eco,787,2,5,2,3,1,2,1,1,3,2,4,3,4,1,0,0.0,neutral or dissatisfied +24904,105628,Male,disloyal Customer,35,Business travel,Business,787,2,2,2,2,5,2,5,5,5,2,5,3,5,5,5,0.0,neutral or dissatisfied +24905,71663,Male,Loyal Customer,56,Personal Travel,Eco,1197,1,1,1,4,5,1,5,5,2,2,4,1,3,5,0,0.0,neutral or dissatisfied +24906,88775,Male,Loyal Customer,44,Business travel,Business,515,2,1,2,2,3,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +24907,18833,Male,Loyal Customer,47,Business travel,Eco,503,4,5,4,5,4,4,4,4,3,1,3,3,2,4,0,7.0,satisfied +24908,18734,Female,Loyal Customer,34,Business travel,Business,1980,5,5,5,5,4,3,5,5,5,5,5,1,5,2,0,0.0,satisfied +24909,78728,Female,disloyal Customer,42,Business travel,Business,432,3,3,3,4,5,3,5,5,5,2,4,5,5,5,17,11.0,neutral or dissatisfied +24910,47760,Male,Loyal Customer,53,Business travel,Business,2340,3,3,3,3,4,4,3,2,2,2,2,5,2,5,0,20.0,satisfied +24911,104505,Female,disloyal Customer,30,Business travel,Business,1609,5,5,5,3,1,5,1,1,3,4,3,3,4,1,0,0.0,satisfied +24912,2568,Female,disloyal Customer,26,Business travel,Business,304,4,2,4,2,5,4,5,5,3,4,2,3,3,5,19,49.0,neutral or dissatisfied +24913,89535,Male,disloyal Customer,34,Business travel,Business,944,2,2,2,2,4,2,4,4,4,4,5,3,4,4,0,0.0,neutral or dissatisfied +24914,14086,Male,Loyal Customer,57,Business travel,Business,399,1,1,1,1,4,1,2,3,3,3,3,3,3,5,0,0.0,satisfied +24915,16803,Female,Loyal Customer,10,Business travel,Business,2468,3,4,4,4,3,3,3,3,3,2,4,1,4,3,12,17.0,neutral or dissatisfied +24916,106348,Male,Loyal Customer,18,Personal Travel,Business,674,3,5,3,1,1,3,1,1,4,4,4,4,4,1,40,29.0,neutral or dissatisfied +24917,95179,Female,Loyal Customer,65,Personal Travel,Eco,239,3,2,3,4,5,4,3,3,3,3,4,1,3,3,0,0.0,neutral or dissatisfied +24918,119212,Female,Loyal Customer,30,Personal Travel,Eco,257,5,3,5,3,3,5,3,3,4,2,3,1,5,3,0,42.0,satisfied +24919,1901,Male,Loyal Customer,52,Business travel,Business,383,4,4,4,4,4,5,5,5,5,5,5,5,5,4,0,1.0,satisfied +24920,79674,Male,Loyal Customer,70,Personal Travel,Eco,760,3,2,3,2,2,3,5,2,3,5,2,4,2,2,0,0.0,neutral or dissatisfied +24921,83898,Male,Loyal Customer,28,Business travel,Business,1450,1,1,1,1,4,4,4,4,3,3,5,3,5,4,0,0.0,satisfied +24922,104388,Female,Loyal Customer,51,Business travel,Eco Plus,228,2,2,2,2,3,4,4,2,2,2,2,4,2,2,8,0.0,neutral or dissatisfied +24923,15662,Male,disloyal Customer,22,Business travel,Eco,764,2,2,2,5,5,2,5,5,5,3,1,4,1,5,0,0.0,neutral or dissatisfied +24924,78607,Male,Loyal Customer,53,Business travel,Business,1426,4,4,3,4,5,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +24925,35584,Male,Loyal Customer,29,Business travel,Eco Plus,1076,1,4,4,4,1,1,1,1,3,5,3,1,3,1,21,20.0,neutral or dissatisfied +24926,88743,Male,Loyal Customer,37,Personal Travel,Eco,581,4,2,4,4,2,4,2,2,2,4,3,3,3,2,3,2.0,neutral or dissatisfied +24927,109518,Female,Loyal Customer,42,Business travel,Business,2086,3,3,2,3,2,5,5,5,5,5,5,3,5,4,96,99.0,satisfied +24928,36935,Female,Loyal Customer,57,Personal Travel,Eco,867,1,3,0,3,3,3,2,5,5,0,5,4,5,4,24,66.0,neutral or dissatisfied +24929,14274,Male,Loyal Customer,59,Business travel,Eco,395,5,5,5,5,5,5,5,5,4,3,2,2,2,5,3,1.0,satisfied +24930,2056,Female,Loyal Customer,57,Business travel,Business,2729,2,2,2,2,2,5,4,4,4,4,4,3,4,4,13,6.0,satisfied +24931,62044,Female,Loyal Customer,34,Business travel,Business,2586,2,1,1,1,2,3,4,2,2,2,2,1,2,4,91,109.0,neutral or dissatisfied +24932,35991,Male,Loyal Customer,69,Personal Travel,Eco,2496,2,2,1,4,1,1,1,2,1,3,4,1,2,1,0,28.0,neutral or dissatisfied +24933,29521,Female,Loyal Customer,15,Business travel,Business,1009,1,1,1,1,4,4,4,4,5,5,2,5,3,4,0,1.0,satisfied +24934,51378,Female,Loyal Customer,60,Personal Travel,Eco Plus,337,3,4,3,3,4,5,4,2,2,3,2,4,2,3,0,0.0,neutral or dissatisfied +24935,128247,Female,Loyal Customer,52,Business travel,Business,3218,4,4,4,4,5,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +24936,38798,Male,Loyal Customer,68,Personal Travel,Eco,387,1,5,1,2,3,1,3,3,4,4,5,5,5,3,0,0.0,neutral or dissatisfied +24937,8711,Female,Loyal Customer,49,Personal Travel,Eco,227,2,4,0,3,4,4,4,2,2,0,2,2,2,2,0,0.0,neutral or dissatisfied +24938,52679,Male,Loyal Customer,49,Personal Travel,Eco,160,1,4,0,3,5,0,5,5,5,2,4,3,5,5,4,1.0,neutral or dissatisfied +24939,68772,Male,Loyal Customer,28,Business travel,Business,926,2,4,4,4,2,2,2,2,1,1,4,1,3,2,23,16.0,neutral or dissatisfied +24940,84497,Female,Loyal Customer,39,Business travel,Eco,4502,1,2,2,2,1,1,1,2,4,4,4,1,4,1,16,0.0,neutral or dissatisfied +24941,96230,Female,disloyal Customer,14,Business travel,Eco,546,5,5,4,4,4,4,4,4,5,3,4,5,4,4,0,0.0,satisfied +24942,89514,Female,Loyal Customer,47,Business travel,Business,1076,3,3,3,3,3,5,5,4,4,4,4,3,4,3,20,3.0,satisfied +24943,33595,Female,Loyal Customer,37,Business travel,Business,2330,3,4,4,4,2,4,4,3,3,3,3,1,3,3,0,0.0,neutral or dissatisfied +24944,38042,Female,Loyal Customer,30,Business travel,Business,3243,2,2,3,2,4,4,4,4,4,5,3,4,3,4,0,0.0,satisfied +24945,61738,Female,Loyal Customer,36,Business travel,Business,2056,2,3,3,3,5,3,3,4,4,4,2,3,4,3,5,0.0,neutral or dissatisfied +24946,111619,Male,disloyal Customer,57,Business travel,Eco,1014,2,2,2,2,1,2,1,1,1,2,1,3,2,1,25,9.0,neutral or dissatisfied +24947,109151,Female,disloyal Customer,25,Business travel,Business,391,5,4,5,5,3,5,3,3,4,4,5,5,4,3,0,0.0,satisfied +24948,24977,Male,Loyal Customer,45,Business travel,Eco,484,5,2,2,2,5,5,5,5,1,3,5,3,1,5,0,0.0,satisfied +24949,38370,Female,Loyal Customer,67,Personal Travel,Eco,1173,2,5,3,1,4,4,4,1,1,3,1,5,1,4,0,0.0,neutral or dissatisfied +24950,104202,Female,Loyal Customer,28,Personal Travel,Eco,1310,3,4,3,3,4,3,4,4,4,5,4,5,5,4,5,29.0,neutral or dissatisfied +24951,121654,Female,Loyal Customer,53,Business travel,Business,1730,4,4,4,4,5,4,5,5,5,5,5,4,5,4,11,8.0,satisfied +24952,102150,Female,Loyal Customer,52,Business travel,Business,2245,3,3,3,3,3,5,5,2,2,2,2,4,2,3,5,2.0,satisfied +24953,97358,Male,Loyal Customer,41,Business travel,Business,2800,1,4,4,4,2,1,2,1,1,1,1,3,1,3,8,2.0,neutral or dissatisfied +24954,76516,Male,Loyal Customer,51,Business travel,Business,3666,2,2,2,2,5,5,4,4,4,5,4,3,4,3,0,0.0,satisfied +24955,54521,Male,Loyal Customer,52,Personal Travel,Eco,925,3,5,3,3,4,3,4,4,5,2,5,3,5,4,9,0.0,neutral or dissatisfied +24956,39495,Male,Loyal Customer,68,Business travel,Business,1368,1,1,1,1,4,2,3,4,4,4,4,3,4,5,0,0.0,satisfied +24957,84892,Male,Loyal Customer,20,Personal Travel,Eco,534,2,5,3,3,1,3,1,1,5,2,4,5,4,1,0,0.0,neutral or dissatisfied +24958,114019,Male,Loyal Customer,51,Personal Travel,Eco,1728,4,5,4,3,4,4,4,4,5,5,5,5,4,4,0,0.0,satisfied +24959,31771,Female,Loyal Customer,54,Business travel,Eco,202,4,4,4,4,2,2,2,4,4,4,4,1,4,1,0,0.0,satisfied +24960,34454,Female,Loyal Customer,58,Personal Travel,Eco,228,2,4,2,1,4,4,4,5,5,2,5,5,5,3,0,0.0,neutral or dissatisfied +24961,126937,Male,Loyal Customer,46,Business travel,Business,3975,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +24962,28496,Male,Loyal Customer,48,Business travel,Business,2451,2,5,5,5,3,4,3,2,2,3,2,2,2,1,0,0.0,neutral or dissatisfied +24963,97515,Male,Loyal Customer,48,Business travel,Business,3844,2,2,2,2,4,5,4,4,4,4,4,3,4,5,0,3.0,satisfied +24964,43731,Female,Loyal Customer,31,Personal Travel,Eco Plus,196,3,4,3,2,5,3,4,5,4,5,4,3,5,5,0,3.0,neutral or dissatisfied +24965,40692,Female,Loyal Customer,31,Business travel,Business,3715,2,2,2,2,5,5,5,5,3,3,5,4,5,5,4,0.0,satisfied +24966,8963,Female,Loyal Customer,56,Personal Travel,Eco,812,1,2,1,4,5,4,4,2,2,1,2,4,2,1,0,0.0,neutral or dissatisfied +24967,26352,Female,Loyal Customer,36,Business travel,Business,861,4,4,4,4,3,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +24968,47475,Male,Loyal Customer,39,Personal Travel,Eco,584,3,5,3,1,5,3,5,5,5,4,5,4,5,5,0,0.0,neutral or dissatisfied +24969,68385,Female,Loyal Customer,57,Business travel,Business,1525,2,2,2,2,5,4,4,3,3,3,3,4,3,5,0,0.0,satisfied +24970,85484,Female,Loyal Customer,27,Personal Travel,Eco,214,3,0,3,3,1,3,1,1,3,4,5,4,4,1,62,56.0,neutral or dissatisfied +24971,114526,Male,Loyal Customer,52,Personal Travel,Business,337,2,2,2,4,4,4,3,3,3,2,3,1,3,2,0,0.0,neutral or dissatisfied +24972,81351,Male,Loyal Customer,20,Personal Travel,Eco,1299,2,4,2,1,1,2,1,1,3,2,3,3,5,1,0,6.0,neutral or dissatisfied +24973,14578,Female,Loyal Customer,45,Business travel,Eco,1021,2,5,5,5,3,4,3,2,2,2,2,4,2,2,0,16.0,neutral or dissatisfied +24974,115307,Male,disloyal Customer,49,Business travel,Business,296,2,2,2,1,5,2,5,5,4,4,5,5,4,5,0,0.0,neutral or dissatisfied +24975,40368,Female,Loyal Customer,36,Business travel,Eco,1250,5,3,3,3,5,5,5,5,2,3,4,2,2,5,11,0.0,satisfied +24976,45061,Male,Loyal Customer,37,Business travel,Business,3210,1,1,1,1,1,3,1,4,4,4,4,5,4,1,0,0.0,satisfied +24977,75747,Male,disloyal Customer,20,Business travel,Eco,468,3,2,3,4,3,3,3,3,4,1,3,4,3,3,9,7.0,neutral or dissatisfied +24978,124052,Male,Loyal Customer,44,Business travel,Business,2153,5,5,5,5,2,2,2,4,5,4,4,2,4,2,4,22.0,satisfied +24979,55891,Male,Loyal Customer,21,Business travel,Business,3201,4,4,4,4,5,5,5,5,5,3,5,5,5,5,0,3.0,satisfied +24980,116414,Female,Loyal Customer,10,Personal Travel,Eco,333,3,1,3,3,5,3,3,5,1,1,3,2,2,5,0,0.0,neutral or dissatisfied +24981,83819,Male,Loyal Customer,58,Business travel,Business,2139,5,5,5,5,2,5,5,4,4,4,4,3,4,3,20,26.0,satisfied +24982,119820,Female,Loyal Customer,19,Business travel,Business,936,3,3,3,3,5,5,5,5,5,3,4,5,4,5,0,0.0,satisfied +24983,76307,Female,Loyal Customer,51,Business travel,Business,2182,2,2,2,2,3,3,4,4,4,4,4,3,4,5,9,0.0,satisfied +24984,61640,Female,Loyal Customer,20,Business travel,Business,1346,2,2,2,2,4,4,4,4,4,5,4,4,5,4,0,3.0,satisfied +24985,15529,Female,Loyal Customer,26,Personal Travel,Eco Plus,164,4,5,0,2,2,0,2,2,3,4,5,4,5,2,11,0.0,neutral or dissatisfied +24986,61804,Female,Loyal Customer,31,Personal Travel,Eco,1504,3,5,3,2,3,4,4,4,2,5,5,4,5,4,131,125.0,neutral or dissatisfied +24987,57595,Female,Loyal Customer,41,Business travel,Eco Plus,1597,2,1,1,1,3,4,3,2,2,2,2,1,2,3,3,32.0,neutral or dissatisfied +24988,4853,Male,Loyal Customer,57,Business travel,Business,2817,4,4,4,4,3,5,4,5,5,5,5,4,5,4,0,0.0,satisfied +24989,75283,Male,Loyal Customer,51,Personal Travel,Eco,1829,2,3,1,3,3,1,3,3,3,4,3,2,2,3,13,0.0,neutral or dissatisfied +24990,18533,Male,Loyal Customer,57,Business travel,Eco,192,5,1,1,1,5,5,5,5,1,5,1,2,5,5,13,12.0,satisfied +24991,14745,Female,disloyal Customer,34,Business travel,Eco,533,3,2,3,4,5,3,3,5,1,4,3,4,3,5,0,0.0,neutral or dissatisfied +24992,39690,Male,Loyal Customer,44,Business travel,Eco,1463,4,2,2,2,4,4,4,4,4,3,1,5,5,4,130,111.0,satisfied +24993,95486,Female,Loyal Customer,57,Business travel,Business,3013,2,2,2,2,3,5,4,3,3,4,5,3,3,3,0,0.0,satisfied +24994,105083,Female,Loyal Customer,34,Business travel,Business,277,4,2,4,4,5,5,4,5,5,5,5,4,5,3,0,0.0,satisfied +24995,62300,Female,disloyal Customer,39,Business travel,Business,236,5,5,5,1,3,5,3,3,5,2,4,3,5,3,0,0.0,satisfied +24996,123632,Female,Loyal Customer,53,Business travel,Business,3311,3,3,3,3,2,4,4,5,5,5,4,3,5,4,44,53.0,satisfied +24997,20073,Female,Loyal Customer,64,Personal Travel,Eco,528,2,4,2,1,4,5,4,2,2,2,2,3,2,4,0,0.0,neutral or dissatisfied +24998,122936,Female,Loyal Customer,39,Business travel,Business,1972,3,3,3,3,4,4,5,5,5,5,5,4,5,5,7,29.0,satisfied +24999,120276,Female,Loyal Customer,29,Business travel,Business,1576,1,1,1,1,1,1,1,1,2,4,3,1,3,1,4,37.0,neutral or dissatisfied +25000,51964,Male,Loyal Customer,43,Business travel,Business,3267,2,2,2,2,4,2,2,4,4,4,4,2,4,5,0,0.0,satisfied +25001,26163,Male,Loyal Customer,52,Business travel,Eco,404,5,1,1,1,5,5,5,5,1,1,2,5,5,5,0,0.0,satisfied +25002,114382,Male,Loyal Customer,55,Personal Travel,Eco Plus,967,2,5,2,4,4,2,4,4,5,4,4,5,5,4,35,24.0,neutral or dissatisfied +25003,31228,Female,Loyal Customer,9,Personal Travel,Eco Plus,628,1,2,1,4,4,1,5,4,2,4,4,4,3,4,30,42.0,neutral or dissatisfied +25004,67065,Female,Loyal Customer,47,Business travel,Business,1121,4,4,4,4,3,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +25005,118193,Male,disloyal Customer,17,Business travel,Eco,1060,3,3,3,2,1,3,3,1,4,2,5,1,1,1,21,1.0,neutral or dissatisfied +25006,48696,Male,Loyal Customer,38,Business travel,Business,3810,3,3,3,3,5,5,4,4,4,4,4,4,4,5,4,5.0,satisfied +25007,50134,Male,disloyal Customer,37,Business travel,Eco,158,3,0,3,1,2,3,1,2,4,1,3,1,3,2,1,0.0,neutral or dissatisfied +25008,77140,Male,Loyal Customer,33,Personal Travel,Eco,2105,2,3,2,3,1,2,1,1,4,5,4,5,4,1,0,0.0,neutral or dissatisfied +25009,5225,Male,Loyal Customer,32,Business travel,Business,2434,2,1,5,1,2,2,2,2,3,3,4,1,4,2,4,5.0,neutral or dissatisfied +25010,89419,Female,Loyal Customer,54,Business travel,Business,151,2,2,2,2,3,3,3,4,4,4,2,4,4,1,0,0.0,neutral or dissatisfied +25011,89125,Male,Loyal Customer,22,Business travel,Eco,1947,2,2,2,2,2,2,4,2,3,1,2,1,3,2,5,4.0,neutral or dissatisfied +25012,66223,Female,Loyal Customer,40,Business travel,Business,1751,1,1,2,1,5,5,5,3,3,3,3,4,3,5,0,0.0,satisfied +25013,46618,Male,Loyal Customer,30,Business travel,Business,141,1,3,3,3,4,3,1,4,3,5,3,3,3,4,0,0.0,neutral or dissatisfied +25014,22468,Male,Loyal Customer,44,Personal Travel,Eco,208,1,5,1,1,2,1,2,2,4,1,4,5,2,2,0,3.0,neutral or dissatisfied +25015,10911,Female,Loyal Customer,53,Business travel,Business,295,0,0,0,1,2,4,4,3,3,3,3,4,3,3,0,0.0,satisfied +25016,28203,Male,Loyal Customer,9,Personal Travel,Eco,569,2,5,3,5,2,3,2,2,1,2,5,1,5,2,2,1.0,neutral or dissatisfied +25017,21816,Female,Loyal Customer,37,Personal Travel,Eco,352,1,5,1,4,3,1,3,3,4,3,5,3,4,3,0,0.0,neutral or dissatisfied +25018,54050,Male,Loyal Customer,41,Business travel,Business,1416,3,3,4,3,4,1,5,3,3,3,3,1,3,5,0,2.0,satisfied +25019,84555,Male,Loyal Customer,32,Personal Travel,Eco,2556,3,4,3,1,5,3,5,5,2,4,1,3,4,5,0,0.0,neutral or dissatisfied +25020,90291,Female,disloyal Customer,18,Business travel,Eco,757,4,4,4,4,1,4,1,1,2,3,3,1,4,1,73,72.0,neutral or dissatisfied +25021,34354,Male,Loyal Customer,38,Business travel,Eco,427,5,5,5,5,5,5,5,5,2,4,2,1,4,5,0,0.0,satisfied +25022,5605,Male,disloyal Customer,9,Business travel,Eco,685,2,1,1,1,3,1,3,3,5,4,4,4,4,3,0,0.0,neutral or dissatisfied +25023,113970,Male,Loyal Customer,51,Business travel,Eco,1750,1,3,3,3,1,1,1,1,2,2,4,1,3,1,22,11.0,neutral or dissatisfied +25024,98699,Female,Loyal Customer,68,Personal Travel,Eco,994,2,1,2,2,2,3,3,3,3,2,3,1,3,3,0,0.0,neutral or dissatisfied +25025,114860,Female,Loyal Customer,48,Business travel,Business,342,0,0,0,4,5,5,4,3,3,3,3,5,3,5,31,22.0,satisfied +25026,69323,Male,Loyal Customer,49,Business travel,Business,1984,3,3,3,3,2,5,5,3,3,3,3,3,3,4,3,11.0,satisfied +25027,3879,Female,Loyal Customer,61,Business travel,Business,1686,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,0.0,satisfied +25028,25395,Male,disloyal Customer,23,Business travel,Eco,990,2,2,2,3,1,2,1,1,5,2,4,4,4,1,35,32.0,neutral or dissatisfied +25029,108199,Female,Loyal Customer,54,Business travel,Eco Plus,590,4,2,1,2,3,1,3,4,4,4,4,2,4,4,10,7.0,satisfied +25030,121118,Female,Loyal Customer,49,Business travel,Business,2521,1,1,1,1,4,4,4,4,2,3,4,4,5,4,40,43.0,satisfied +25031,96662,Male,Loyal Customer,16,Personal Travel,Eco,937,2,4,3,4,2,3,2,2,3,5,4,1,4,2,0,0.0,neutral or dissatisfied +25032,22887,Female,Loyal Customer,54,Personal Travel,Eco,170,2,5,2,1,2,4,2,5,5,2,5,4,5,4,0,0.0,neutral or dissatisfied +25033,64416,Male,Loyal Customer,36,Business travel,Business,1158,3,3,3,3,3,4,4,5,5,5,5,5,5,4,0,0.0,satisfied +25034,77155,Male,Loyal Customer,43,Business travel,Business,1865,2,2,2,2,4,3,5,5,5,5,5,3,5,3,3,0.0,satisfied +25035,108067,Female,Loyal Customer,65,Personal Travel,Business,997,3,4,3,3,2,5,5,4,4,3,4,4,4,3,12,8.0,neutral or dissatisfied +25036,45757,Male,disloyal Customer,25,Business travel,Eco,391,3,0,3,3,4,3,4,4,2,3,2,5,4,4,0,0.0,neutral or dissatisfied +25037,88006,Female,disloyal Customer,27,Business travel,Business,404,5,5,5,2,3,5,3,3,4,3,5,4,5,3,0,0.0,satisfied +25038,15014,Male,Loyal Customer,28,Business travel,Business,557,2,3,3,3,2,2,2,2,3,4,3,2,3,2,3,19.0,neutral or dissatisfied +25039,76998,Male,Loyal Customer,52,Business travel,Business,2535,4,4,4,4,5,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +25040,76878,Female,Loyal Customer,45,Business travel,Business,630,1,1,1,1,2,5,5,3,3,3,3,3,3,5,0,1.0,satisfied +25041,111234,Female,Loyal Customer,36,Personal Travel,Eco,1506,1,4,1,5,2,1,2,2,3,5,4,3,5,2,28,22.0,neutral or dissatisfied +25042,88242,Female,disloyal Customer,24,Business travel,Business,581,5,0,5,4,4,5,4,4,3,3,4,5,5,4,11,7.0,satisfied +25043,79220,Female,Loyal Customer,17,Personal Travel,Eco,1990,2,3,2,3,5,2,5,5,3,5,3,3,3,5,0,0.0,neutral or dissatisfied +25044,47893,Female,disloyal Customer,23,Business travel,Eco,462,3,2,3,4,3,3,3,3,3,5,3,2,4,3,28,29.0,neutral or dissatisfied +25045,50295,Male,Loyal Customer,47,Business travel,Business,2043,0,0,0,4,4,5,4,2,2,2,2,2,2,1,0,0.0,satisfied +25046,81534,Female,disloyal Customer,23,Business travel,Eco,1124,2,2,2,2,3,2,3,3,1,1,3,5,1,3,0,0.0,satisfied +25047,6302,Female,Loyal Customer,60,Business travel,Business,315,4,4,4,4,5,5,4,4,4,4,4,3,4,4,17,10.0,satisfied +25048,53873,Male,Loyal Customer,64,Business travel,Eco,224,5,2,2,2,5,5,5,5,1,4,4,4,5,5,0,0.0,satisfied +25049,5006,Male,disloyal Customer,22,Business travel,Eco,102,3,5,3,4,2,3,2,2,2,3,2,4,5,2,0,0.0,neutral or dissatisfied +25050,86425,Male,disloyal Customer,30,Business travel,Business,762,2,2,2,3,2,2,2,2,4,2,5,4,4,2,0,0.0,neutral or dissatisfied +25051,76799,Male,Loyal Customer,63,Personal Travel,Eco,689,2,5,2,1,5,2,5,5,5,5,4,5,5,5,0,0.0,neutral or dissatisfied +25052,91685,Male,Loyal Customer,31,Business travel,Business,3004,2,2,2,2,4,5,4,4,5,4,5,5,5,4,0,0.0,satisfied +25053,71474,Male,disloyal Customer,37,Business travel,Eco,437,3,2,3,4,5,3,5,5,4,4,3,3,3,5,0,0.0,neutral or dissatisfied +25054,29713,Male,Loyal Customer,48,Business travel,Eco,2304,5,5,5,5,5,5,5,5,5,2,3,2,4,5,0,0.0,satisfied +25055,37748,Female,Loyal Customer,47,Business travel,Eco Plus,1056,3,2,2,2,5,4,2,3,3,3,3,3,3,4,42,27.0,satisfied +25056,109331,Male,Loyal Customer,51,Personal Travel,Eco,1072,5,4,5,3,4,5,4,4,5,3,4,4,4,4,0,0.0,satisfied +25057,65404,Male,Loyal Customer,48,Personal Travel,Eco,432,2,5,2,2,1,2,1,1,5,3,4,5,4,1,12,5.0,neutral or dissatisfied +25058,99492,Female,Loyal Customer,24,Personal Travel,Eco,307,1,5,1,1,2,1,2,2,3,3,4,5,5,2,47,52.0,neutral or dissatisfied +25059,48100,Female,Loyal Customer,37,Business travel,Eco,391,5,5,5,5,5,5,5,5,3,4,4,4,1,5,0,13.0,satisfied +25060,17980,Male,Loyal Customer,37,Business travel,Business,3009,2,1,1,1,5,3,2,2,2,2,2,1,2,2,0,0.0,neutral or dissatisfied +25061,123108,Female,Loyal Customer,32,Business travel,Business,3888,3,2,2,2,3,3,3,3,4,2,4,4,3,3,5,15.0,neutral or dissatisfied +25062,3297,Male,Loyal Customer,50,Personal Travel,Eco,479,2,0,5,2,5,5,5,5,4,2,4,3,4,5,0,0.0,neutral or dissatisfied +25063,38258,Male,disloyal Customer,55,Business travel,Eco,1050,3,3,3,4,2,3,2,2,2,5,4,2,3,2,6,54.0,neutral or dissatisfied +25064,41417,Male,Loyal Customer,22,Personal Travel,Eco,913,4,5,4,2,4,4,3,4,5,4,5,3,5,4,0,0.0,neutral or dissatisfied +25065,16847,Male,Loyal Customer,60,Business travel,Business,2001,3,3,3,3,1,4,3,2,2,2,2,4,2,2,57,43.0,satisfied +25066,118268,Male,Loyal Customer,30,Business travel,Business,2926,4,5,5,5,4,4,4,4,4,5,4,4,4,4,0,0.0,neutral or dissatisfied +25067,112503,Male,Loyal Customer,24,Personal Travel,Eco,819,3,2,3,4,2,3,2,2,3,2,4,4,4,2,14,0.0,neutral or dissatisfied +25068,31737,Female,Loyal Customer,19,Business travel,Eco Plus,862,0,3,0,1,2,3,2,2,5,5,4,5,1,2,0,2.0,satisfied +25069,23384,Female,disloyal Customer,24,Business travel,Business,300,3,2,2,2,2,2,2,2,3,3,3,2,2,2,248,250.0,neutral or dissatisfied +25070,30983,Male,Loyal Customer,29,Business travel,Business,1533,2,2,2,2,2,2,2,2,2,3,4,1,3,2,8,34.0,neutral or dissatisfied +25071,18451,Male,Loyal Customer,36,Business travel,Business,2313,1,1,2,1,2,1,5,5,5,5,5,5,5,2,0,8.0,satisfied +25072,87791,Female,Loyal Customer,39,Business travel,Business,2700,0,5,0,1,5,5,5,5,5,5,5,3,5,5,13,0.0,satisfied +25073,42519,Female,Loyal Customer,61,Personal Travel,Eco,1384,3,4,3,4,2,3,3,4,4,3,1,2,4,4,0,0.0,neutral or dissatisfied +25074,103493,Female,Loyal Customer,42,Personal Travel,Eco,440,3,4,3,3,5,4,5,1,1,3,1,5,1,4,22,10.0,neutral or dissatisfied +25075,69326,Female,Loyal Customer,46,Business travel,Business,1699,2,2,2,2,3,4,5,3,3,4,3,4,3,3,0,0.0,satisfied +25076,116833,Male,Loyal Customer,42,Business travel,Business,338,1,4,4,4,5,4,3,1,1,1,1,4,1,3,44,21.0,neutral or dissatisfied +25077,112910,Female,Loyal Customer,38,Business travel,Business,2398,4,4,4,4,4,4,3,3,3,4,3,3,3,5,3,4.0,satisfied +25078,8400,Male,disloyal Customer,62,Personal Travel,Eco,888,2,3,2,4,3,2,1,3,2,3,4,1,4,3,0,0.0,neutral or dissatisfied +25079,91345,Female,Loyal Customer,50,Personal Travel,Eco Plus,404,2,4,2,4,4,5,5,2,2,2,2,4,2,3,16,8.0,neutral or dissatisfied +25080,75780,Female,Loyal Customer,14,Personal Travel,Eco,868,4,1,4,3,4,5,5,4,3,4,4,5,4,5,148,142.0,neutral or dissatisfied +25081,124298,Female,Loyal Customer,56,Business travel,Business,3145,3,2,5,2,4,3,3,3,3,3,3,3,3,3,0,0.0,neutral or dissatisfied +25082,76569,Male,Loyal Customer,45,Business travel,Eco,481,3,4,5,4,3,3,3,3,4,3,3,1,3,3,25,31.0,neutral or dissatisfied +25083,47111,Female,disloyal Customer,49,Business travel,Eco,784,3,3,3,3,3,3,3,3,2,4,4,2,4,3,0,36.0,neutral or dissatisfied +25084,9988,Male,Loyal Customer,13,Personal Travel,Eco,508,3,5,3,2,2,3,4,2,3,3,5,4,4,2,13,4.0,neutral or dissatisfied +25085,909,Female,Loyal Customer,60,Business travel,Business,2738,3,3,3,3,2,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +25086,8755,Male,Loyal Customer,50,Business travel,Business,1147,2,2,2,2,1,3,3,2,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +25087,66078,Male,Loyal Customer,34,Personal Travel,Eco,1345,4,1,4,2,2,4,2,2,2,4,2,3,3,2,0,20.0,neutral or dissatisfied +25088,86451,Female,Loyal Customer,39,Business travel,Eco,749,3,4,4,4,3,3,3,3,4,5,3,2,2,3,25,40.0,neutral or dissatisfied +25089,119127,Male,Loyal Customer,12,Personal Travel,Eco Plus,1107,3,5,3,3,4,3,4,4,3,3,4,5,4,4,0,0.0,neutral or dissatisfied +25090,74399,Female,Loyal Customer,45,Business travel,Business,1431,2,2,2,2,5,5,5,5,5,5,5,5,5,5,8,6.0,satisfied +25091,74618,Male,Loyal Customer,43,Business travel,Eco,835,3,4,1,4,3,3,3,3,2,5,3,4,3,3,0,0.0,neutral or dissatisfied +25092,124836,Male,Loyal Customer,19,Personal Travel,Eco,280,3,4,3,4,4,3,4,4,2,1,3,1,4,4,0,13.0,neutral or dissatisfied +25093,6704,Female,Loyal Customer,53,Personal Travel,Eco,438,3,3,3,4,3,3,4,4,4,3,3,3,4,1,0,2.0,neutral or dissatisfied +25094,16001,Female,disloyal Customer,27,Business travel,Eco,794,3,3,3,3,4,3,4,4,3,3,2,4,2,4,0,18.0,neutral or dissatisfied +25095,127104,Female,Loyal Customer,21,Personal Travel,Eco,338,5,4,5,4,4,5,4,4,3,4,4,3,4,4,0,0.0,satisfied +25096,3756,Female,Loyal Customer,11,Personal Travel,Eco Plus,427,2,5,4,2,3,4,3,3,2,3,4,1,2,3,13,2.0,neutral or dissatisfied +25097,114460,Male,Loyal Customer,57,Business travel,Business,333,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +25098,37156,Male,Loyal Customer,53,Business travel,Eco,1237,2,5,2,5,2,2,2,2,4,2,4,4,3,2,0,11.0,neutral or dissatisfied +25099,116106,Female,Loyal Customer,14,Personal Travel,Eco,373,3,2,1,4,1,1,1,1,1,4,4,2,4,1,3,0.0,neutral or dissatisfied +25100,29815,Female,Loyal Customer,40,Business travel,Business,1818,3,3,3,3,5,1,3,3,3,3,3,5,3,3,10,14.0,satisfied +25101,65230,Male,disloyal Customer,37,Business travel,Eco Plus,551,3,3,3,3,1,3,1,1,1,5,3,3,4,1,6,3.0,neutral or dissatisfied +25102,58207,Male,Loyal Customer,54,Business travel,Business,525,4,4,3,3,1,1,2,4,4,4,4,2,4,2,6,0.0,neutral or dissatisfied +25103,39592,Male,disloyal Customer,38,Business travel,Eco,565,1,0,1,3,2,1,2,2,5,4,2,2,2,2,0,0.0,neutral or dissatisfied +25104,331,Male,Loyal Customer,51,Business travel,Business,821,3,3,4,4,4,3,3,3,3,3,3,4,3,2,0,9.0,neutral or dissatisfied +25105,32362,Male,Loyal Customer,63,Business travel,Eco,216,5,1,4,1,5,5,5,5,4,1,1,2,2,5,0,0.0,satisfied +25106,122992,Female,Loyal Customer,35,Business travel,Eco,507,2,3,5,3,2,2,2,2,2,4,4,4,3,2,54,46.0,neutral or dissatisfied +25107,47361,Male,disloyal Customer,26,Business travel,Eco,588,4,4,4,4,5,4,2,5,5,5,5,5,1,5,0,0.0,neutral or dissatisfied +25108,69137,Male,Loyal Customer,42,Business travel,Business,2248,3,3,5,3,5,4,5,3,3,3,3,3,3,5,17,19.0,satisfied +25109,48166,Female,Loyal Customer,54,Business travel,Business,2292,5,5,5,5,3,3,4,5,5,5,3,1,5,2,0,0.0,satisfied +25110,50090,Female,Loyal Customer,58,Business travel,Business,109,4,4,4,4,5,3,4,5,5,5,5,5,5,4,0,0.0,satisfied +25111,76864,Female,disloyal Customer,24,Business travel,Business,1927,0,5,0,2,1,0,1,1,5,3,4,5,5,1,0,0.0,satisfied +25112,41095,Male,Loyal Customer,39,Business travel,Eco,191,2,4,4,4,2,2,2,2,1,2,2,3,5,2,0,0.0,satisfied +25113,102163,Male,disloyal Customer,39,Business travel,Business,258,5,5,5,2,4,5,4,4,5,3,4,5,5,4,2,0.0,satisfied +25114,74370,Female,Loyal Customer,41,Business travel,Business,1235,4,4,4,4,4,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +25115,96470,Male,Loyal Customer,41,Business travel,Business,1554,0,0,0,3,2,5,5,4,4,4,4,5,4,5,31,29.0,satisfied +25116,68117,Male,Loyal Customer,16,Personal Travel,Eco,813,1,4,1,2,3,1,3,3,4,3,5,4,5,3,0,0.0,neutral or dissatisfied +25117,124443,Female,Loyal Customer,56,Business travel,Business,2513,2,3,4,3,1,3,3,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +25118,96949,Male,Loyal Customer,36,Business travel,Business,775,2,2,2,2,5,4,4,3,3,4,3,5,3,5,0,0.0,satisfied +25119,9266,Female,Loyal Customer,54,Business travel,Business,441,4,4,4,4,2,4,4,5,5,5,5,3,5,4,54,45.0,satisfied +25120,95283,Male,Loyal Customer,47,Personal Travel,Eco,319,3,4,3,5,2,3,2,2,5,2,4,2,5,2,0,0.0,neutral or dissatisfied +25121,124468,Male,Loyal Customer,66,Personal Travel,Eco,980,4,2,4,3,4,4,3,4,2,1,3,2,3,4,0,0.0,neutral or dissatisfied +25122,53384,Male,Loyal Customer,66,Personal Travel,Eco,1452,4,4,4,3,3,4,1,3,3,1,5,1,4,3,0,0.0,neutral or dissatisfied +25123,1227,Female,Loyal Customer,41,Personal Travel,Eco,309,2,4,2,2,4,2,4,4,5,2,4,5,5,4,0,0.0,neutral or dissatisfied +25124,79492,Female,Loyal Customer,15,Personal Travel,Business,762,3,3,4,3,1,4,4,1,4,4,3,2,3,1,125,106.0,neutral or dissatisfied +25125,61260,Male,Loyal Customer,60,Personal Travel,Eco,967,4,5,4,2,4,4,4,4,4,3,5,5,5,4,10,10.0,neutral or dissatisfied +25126,13890,Male,Loyal Customer,59,Personal Travel,Eco,578,2,4,2,1,4,2,4,4,1,1,1,2,5,4,0,42.0,neutral or dissatisfied +25127,70389,Female,Loyal Customer,54,Business travel,Business,1562,3,3,3,3,4,4,5,5,5,4,5,5,5,5,5,8.0,satisfied +25128,64706,Female,Loyal Customer,52,Business travel,Business,3659,5,5,5,5,2,4,5,5,5,5,5,3,5,3,0,,satisfied +25129,89464,Female,Loyal Customer,41,Business travel,Business,134,0,5,0,2,4,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +25130,78523,Male,Loyal Customer,28,Personal Travel,Eco,666,3,5,3,2,4,3,4,4,4,4,4,4,5,4,0,0.0,neutral or dissatisfied +25131,111111,Male,Loyal Customer,68,Personal Travel,Eco Plus,197,3,5,3,3,5,3,5,5,3,4,5,4,5,5,22,9.0,neutral or dissatisfied +25132,39411,Male,Loyal Customer,48,Business travel,Eco Plus,521,5,5,5,5,5,5,5,5,2,3,5,2,4,5,0,16.0,satisfied +25133,15140,Female,disloyal Customer,46,Business travel,Eco,1042,1,1,1,3,3,1,3,3,4,5,3,1,4,3,0,0.0,neutral or dissatisfied +25134,86029,Male,Loyal Customer,57,Personal Travel,Eco,447,3,5,4,5,5,4,3,5,3,5,4,4,5,5,0,0.0,neutral or dissatisfied +25135,42731,Male,disloyal Customer,22,Business travel,Eco,536,3,3,3,1,4,3,1,4,2,3,2,4,1,4,0,0.0,neutral or dissatisfied +25136,69725,Male,Loyal Customer,66,Personal Travel,Eco,1372,1,4,1,1,2,1,2,2,4,5,4,5,4,2,0,0.0,neutral or dissatisfied +25137,54420,Male,Loyal Customer,11,Personal Travel,Eco,305,2,5,2,2,2,2,2,2,3,4,5,3,5,2,9,1.0,neutral or dissatisfied +25138,53446,Male,Loyal Customer,28,Business travel,Business,2358,3,3,3,3,5,5,5,1,1,4,2,5,5,5,5,12.0,satisfied +25139,102004,Male,disloyal Customer,27,Business travel,Eco Plus,628,2,2,2,4,1,2,1,1,4,5,3,1,4,1,4,5.0,neutral or dissatisfied +25140,80084,Female,disloyal Customer,29,Business travel,Eco Plus,1069,1,1,1,3,4,1,4,4,2,4,2,1,1,4,0,33.0,neutral or dissatisfied +25141,114505,Male,disloyal Customer,33,Business travel,Business,417,2,2,2,3,3,2,3,3,4,2,4,4,3,3,20,13.0,neutral or dissatisfied +25142,114900,Female,Loyal Customer,32,Business travel,Business,371,5,5,5,5,3,3,3,3,3,3,5,4,5,3,0,0.0,satisfied +25143,82817,Female,Loyal Customer,53,Business travel,Business,594,3,2,2,2,5,4,3,3,3,3,3,2,3,3,0,0.0,neutral or dissatisfied +25144,74182,Male,Loyal Customer,61,Personal Travel,Eco,641,3,5,3,3,5,3,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +25145,81100,Male,Loyal Customer,30,Business travel,Business,991,4,3,4,4,4,5,4,4,5,4,4,4,5,4,0,0.0,satisfied +25146,1743,Male,Loyal Customer,59,Personal Travel,Eco,327,4,0,4,3,3,4,3,3,4,5,4,5,4,3,9,6.0,neutral or dissatisfied +25147,113212,Male,Loyal Customer,33,Business travel,Business,386,2,2,2,2,5,5,5,5,3,2,5,3,5,5,0,0.0,satisfied +25148,110119,Male,Loyal Customer,45,Business travel,Business,1862,1,1,1,1,2,5,4,5,5,5,5,5,5,5,22,25.0,satisfied +25149,42614,Female,Loyal Customer,31,Business travel,Business,3293,2,2,3,2,4,3,4,4,4,4,2,1,3,4,4,11.0,satisfied +25150,78175,Male,Loyal Customer,45,Business travel,Business,2058,2,2,2,2,2,4,5,4,4,5,4,4,4,4,0,0.0,satisfied +25151,84492,Male,Loyal Customer,26,Personal Travel,Eco,2994,1,3,1,3,1,5,5,4,3,1,3,5,1,5,18,23.0,neutral or dissatisfied +25152,80681,Female,disloyal Customer,30,Business travel,Business,874,2,2,2,4,5,2,5,5,4,3,4,5,5,5,0,0.0,neutral or dissatisfied +25153,948,Male,Loyal Customer,70,Business travel,Business,2237,2,1,1,1,2,1,1,1,1,1,2,2,1,3,0,0.0,neutral or dissatisfied +25154,43325,Male,Loyal Customer,30,Business travel,Business,2123,4,5,4,4,2,2,2,2,3,1,4,2,4,2,0,0.0,satisfied +25155,91735,Female,disloyal Customer,21,Business travel,Eco,588,4,2,5,4,3,5,3,3,2,3,4,3,4,3,0,0.0,neutral or dissatisfied +25156,14022,Male,Loyal Customer,65,Personal Travel,Eco Plus,182,3,4,3,4,2,3,2,2,1,2,4,1,3,2,0,0.0,neutral or dissatisfied +25157,69715,Female,disloyal Customer,19,Business travel,Eco,1372,4,4,4,3,4,4,4,4,4,3,5,2,4,4,0,0.0,satisfied +25158,54084,Male,disloyal Customer,23,Business travel,Eco,1416,4,4,4,3,4,4,4,4,2,3,4,4,4,4,0,0.0,neutral or dissatisfied +25159,98255,Female,Loyal Customer,37,Business travel,Eco,1072,1,5,5,5,1,1,1,1,4,3,4,4,3,1,0,0.0,neutral or dissatisfied +25160,110443,Male,Loyal Customer,21,Personal Travel,Eco,787,3,4,3,3,5,3,5,5,5,2,5,4,5,5,91,75.0,neutral or dissatisfied +25161,113426,Female,disloyal Customer,34,Business travel,Eco,488,2,0,2,4,5,2,5,5,2,2,3,4,4,5,22,17.0,neutral or dissatisfied +25162,24248,Female,Loyal Customer,16,Personal Travel,Eco,147,5,4,5,3,3,5,3,3,2,3,4,4,3,3,0,0.0,satisfied +25163,71397,Female,Loyal Customer,58,Business travel,Business,3810,5,5,5,5,4,5,4,4,4,4,4,5,4,5,8,0.0,satisfied +25164,102509,Female,Loyal Customer,37,Personal Travel,Eco,236,2,4,0,4,3,0,3,3,5,5,5,5,5,3,6,0.0,neutral or dissatisfied +25165,53631,Male,Loyal Customer,64,Personal Travel,Eco,1874,3,2,3,4,5,3,5,5,4,3,4,1,4,5,6,16.0,neutral or dissatisfied +25166,51658,Female,disloyal Customer,36,Business travel,Eco,425,1,0,0,3,1,0,1,1,2,2,3,3,5,1,0,0.0,neutral or dissatisfied +25167,32650,Female,Loyal Customer,69,Business travel,Eco,216,3,4,4,4,1,3,3,3,3,3,3,3,3,2,0,9.0,neutral or dissatisfied +25168,113923,Male,Loyal Customer,41,Personal Travel,Eco,1670,2,5,2,2,5,2,5,5,4,2,4,3,4,5,19,18.0,neutral or dissatisfied +25169,107397,Female,Loyal Customer,59,Business travel,Business,3332,3,3,3,3,3,4,5,5,5,5,5,3,5,4,23,22.0,satisfied +25170,72719,Female,Loyal Customer,45,Business travel,Business,985,3,3,3,3,5,4,4,3,3,4,3,4,3,4,0,0.0,satisfied +25171,84863,Male,Loyal Customer,17,Business travel,Business,3378,5,5,5,5,4,4,4,4,2,3,5,4,3,4,0,0.0,satisfied +25172,97668,Male,disloyal Customer,27,Business travel,Eco,491,3,2,3,3,2,3,2,2,4,3,4,1,3,2,6,0.0,neutral or dissatisfied +25173,62372,Male,Loyal Customer,37,Business travel,Business,2704,4,4,1,4,2,4,5,4,4,4,4,4,4,5,3,0.0,satisfied +25174,12483,Male,Loyal Customer,30,Personal Travel,Eco,127,4,3,0,4,3,0,4,3,3,4,3,4,4,3,34,29.0,neutral or dissatisfied +25175,32363,Male,disloyal Customer,33,Business travel,Eco,102,3,0,3,1,4,3,4,4,4,2,5,1,3,4,0,0.0,neutral or dissatisfied +25176,110358,Male,Loyal Customer,34,Business travel,Business,2992,1,1,1,1,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +25177,82644,Male,Loyal Customer,27,Business travel,Eco Plus,528,1,5,5,5,1,2,1,1,3,2,3,4,4,1,8,4.0,neutral or dissatisfied +25178,60607,Male,Loyal Customer,18,Business travel,Business,3024,1,0,0,3,5,0,5,5,3,2,4,3,4,5,53,52.0,neutral or dissatisfied +25179,60940,Male,disloyal Customer,27,Business travel,Business,888,5,5,5,1,5,1,1,5,3,5,4,1,5,1,168,165.0,satisfied +25180,78296,Male,Loyal Customer,33,Personal Travel,Eco,1598,3,4,3,4,1,3,1,1,3,2,4,4,5,1,0,0.0,neutral or dissatisfied +25181,87608,Male,disloyal Customer,23,Business travel,Eco,591,1,0,0,3,2,0,2,2,4,3,4,3,4,2,22,27.0,neutral or dissatisfied +25182,41093,Female,Loyal Customer,30,Business travel,Business,2487,0,0,0,4,4,4,4,4,1,2,2,3,3,4,25,16.0,satisfied +25183,38512,Male,Loyal Customer,25,Business travel,Eco,2569,5,1,1,1,5,5,5,5,1,1,5,5,2,5,4,0.0,satisfied +25184,70671,Female,Loyal Customer,60,Business travel,Business,2644,1,1,1,1,5,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +25185,7607,Female,disloyal Customer,9,Business travel,Business,802,5,2,5,3,1,5,1,1,3,5,5,5,5,1,0,0.0,satisfied +25186,52463,Female,disloyal Customer,28,Business travel,Eco Plus,451,2,2,2,3,3,2,3,3,2,2,4,4,3,3,0,0.0,neutral or dissatisfied +25187,123662,Male,Loyal Customer,29,Business travel,Eco,214,1,2,4,4,1,1,1,1,3,3,4,2,4,1,0,11.0,neutral or dissatisfied +25188,81533,Male,Loyal Customer,65,Business travel,Business,2071,2,4,4,4,2,3,4,2,2,1,2,1,2,3,24,54.0,neutral or dissatisfied +25189,55798,Female,Loyal Customer,57,Business travel,Business,1416,2,2,2,2,2,5,5,4,4,4,4,3,4,4,0,0.0,satisfied +25190,39628,Female,Loyal Customer,59,Personal Travel,Eco,748,2,5,1,3,4,5,5,5,5,1,5,3,5,4,0,0.0,neutral or dissatisfied +25191,73874,Male,disloyal Customer,35,Business travel,Business,2585,3,3,3,3,3,3,3,4,3,5,5,3,5,3,0,0.0,neutral or dissatisfied +25192,38984,Male,disloyal Customer,39,Business travel,Business,230,5,5,5,2,1,5,1,1,2,4,1,3,3,1,0,0.0,satisfied +25193,8780,Male,Loyal Customer,57,Business travel,Business,2673,2,2,2,2,3,5,5,4,4,4,4,3,4,3,17,27.0,satisfied +25194,26448,Male,Loyal Customer,48,Business travel,Business,925,1,1,1,1,4,2,2,2,2,2,2,5,2,3,0,0.0,satisfied +25195,24685,Female,Loyal Customer,32,Business travel,Business,1850,5,5,3,5,4,4,4,4,3,5,1,4,3,4,0,0.0,satisfied +25196,101131,Female,Loyal Customer,77,Business travel,Business,3371,5,3,3,3,5,2,2,5,5,4,5,3,5,3,15,10.0,neutral or dissatisfied +25197,36933,Male,Loyal Customer,51,Business travel,Eco,467,2,5,5,5,2,2,2,2,1,1,4,4,3,2,0,5.0,neutral or dissatisfied +25198,42523,Female,Loyal Customer,54,Business travel,Business,328,4,4,4,4,4,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +25199,32519,Female,Loyal Customer,54,Business travel,Business,1718,5,5,5,5,4,1,2,5,5,5,4,2,5,4,8,8.0,satisfied +25200,96980,Female,Loyal Customer,13,Business travel,Business,2361,3,3,3,3,5,5,5,5,3,3,5,4,5,5,6,0.0,satisfied +25201,117248,Female,disloyal Customer,30,Personal Travel,Eco,451,2,4,2,1,5,2,5,5,4,5,4,3,5,5,0,0.0,neutral or dissatisfied +25202,56378,Female,Loyal Customer,54,Business travel,Business,200,2,2,2,2,5,5,5,5,5,5,5,3,5,4,5,0.0,satisfied +25203,81840,Female,disloyal Customer,52,Personal Travel,Eco,1306,1,5,1,1,2,1,2,2,5,5,4,4,5,2,0,19.0,neutral or dissatisfied +25204,29716,Male,Loyal Customer,65,Personal Travel,Eco,2846,2,3,2,3,4,2,4,4,5,2,3,5,2,4,0,0.0,neutral or dissatisfied +25205,27195,Male,Loyal Customer,48,Business travel,Business,2182,2,2,2,2,1,4,4,4,4,4,4,4,4,4,0,0.0,satisfied +25206,54205,Female,Loyal Customer,25,Business travel,Eco Plus,1372,5,4,4,4,5,4,3,5,3,5,1,2,3,5,1,0.0,satisfied +25207,86580,Female,Loyal Customer,32,Business travel,Business,1269,2,3,5,5,2,2,2,2,3,2,3,3,3,2,0,2.0,neutral or dissatisfied +25208,40588,Male,disloyal Customer,29,Business travel,Eco,391,4,0,4,5,5,4,5,5,4,3,2,1,2,5,2,0.0,neutral or dissatisfied +25209,75407,Male,Loyal Customer,58,Business travel,Business,2342,1,1,2,1,2,3,4,4,4,4,4,3,4,5,0,0.0,satisfied +25210,19013,Female,disloyal Customer,25,Business travel,Eco,788,3,3,3,4,1,3,1,1,2,1,1,5,5,1,4,0.0,neutral or dissatisfied +25211,62545,Female,Loyal Customer,41,Business travel,Business,1723,5,5,5,5,4,3,4,5,5,5,5,5,5,5,109,97.0,satisfied +25212,115552,Male,Loyal Customer,18,Business travel,Eco,362,1,4,4,4,1,1,1,1,2,5,3,2,3,1,1,0.0,neutral or dissatisfied +25213,102584,Female,disloyal Customer,21,Business travel,Business,223,5,2,5,5,5,5,2,5,4,4,4,5,4,5,0,0.0,satisfied +25214,101765,Male,Loyal Customer,28,Personal Travel,Eco,1590,3,5,3,3,2,3,2,2,5,3,5,3,4,2,30,18.0,neutral or dissatisfied +25215,71023,Male,Loyal Customer,60,Business travel,Business,802,4,4,4,4,3,5,5,5,5,5,5,5,5,3,19,13.0,satisfied +25216,110616,Male,Loyal Customer,22,Business travel,Business,727,1,1,1,1,4,4,4,4,5,2,4,5,4,4,25,9.0,satisfied +25217,101044,Female,Loyal Customer,48,Business travel,Business,2485,5,5,5,5,3,5,4,5,5,5,5,3,5,4,0,0.0,satisfied +25218,60214,Female,disloyal Customer,43,Business travel,Business,1546,4,5,5,1,4,4,4,3,3,5,5,4,5,4,291,277.0,neutral or dissatisfied +25219,67647,Female,disloyal Customer,48,Business travel,Eco,1205,2,2,2,4,1,2,1,1,2,5,4,2,4,1,1,4.0,neutral or dissatisfied +25220,88088,Female,Loyal Customer,56,Business travel,Business,1893,3,3,3,3,4,5,4,4,4,4,4,4,4,4,58,59.0,satisfied +25221,95017,Male,Loyal Customer,27,Personal Travel,Eco,319,3,2,3,2,5,3,5,5,4,5,3,3,2,5,0,6.0,neutral or dissatisfied +25222,83047,Female,Loyal Customer,33,Business travel,Business,1831,1,2,2,2,3,2,2,1,1,1,1,3,1,1,12,12.0,neutral or dissatisfied +25223,76428,Male,disloyal Customer,39,Business travel,Eco,405,2,2,2,2,3,2,3,3,3,3,3,2,2,3,0,0.0,neutral or dissatisfied +25224,44301,Female,Loyal Customer,50,Business travel,Business,1428,1,2,1,2,5,3,4,1,1,1,1,4,1,2,0,6.0,neutral or dissatisfied +25225,58719,Male,disloyal Customer,25,Business travel,Business,1197,0,0,0,2,1,0,3,1,3,3,5,3,4,1,0,0.0,satisfied +25226,78274,Female,Loyal Customer,37,Business travel,Business,1598,4,4,4,4,3,3,4,3,3,4,3,5,3,4,0,0.0,satisfied +25227,122600,Male,Loyal Customer,25,Business travel,Business,2020,5,5,5,5,3,3,3,3,5,5,5,3,4,3,0,0.0,satisfied +25228,6746,Female,Loyal Customer,47,Business travel,Business,122,1,1,1,1,5,5,5,4,4,4,4,3,4,5,91,103.0,satisfied +25229,111741,Female,Loyal Customer,51,Business travel,Business,1224,5,5,5,5,4,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +25230,38529,Female,Loyal Customer,42,Business travel,Eco,2446,1,5,5,5,4,2,4,1,1,1,1,3,1,1,0,0.0,neutral or dissatisfied +25231,24482,Female,disloyal Customer,27,Business travel,Eco,547,3,1,3,3,2,3,3,2,3,1,2,2,2,2,0,0.0,neutral or dissatisfied +25232,51787,Male,Loyal Customer,45,Personal Travel,Eco,509,3,4,3,1,4,3,4,4,5,5,4,4,4,4,0,0.0,neutral or dissatisfied +25233,15798,Male,Loyal Customer,33,Business travel,Business,3114,2,4,2,2,5,5,5,5,5,2,3,3,5,5,1,0.0,satisfied +25234,28332,Female,Loyal Customer,56,Business travel,Eco,867,4,3,5,3,2,3,5,4,4,4,4,3,4,3,0,0.0,satisfied +25235,71860,Female,Loyal Customer,32,Business travel,Business,1744,3,3,4,3,3,3,3,3,4,5,3,4,4,3,74,70.0,neutral or dissatisfied +25236,11020,Male,Loyal Customer,41,Business travel,Eco,140,4,2,2,2,4,4,4,4,4,2,4,3,5,4,0,0.0,satisfied +25237,115656,Male,Loyal Customer,72,Business travel,Business,3453,5,5,5,5,4,5,5,1,5,3,4,5,1,5,205,193.0,neutral or dissatisfied +25238,66275,Male,Loyal Customer,42,Business travel,Eco Plus,460,2,3,3,3,2,2,2,2,4,3,4,4,4,2,0,0.0,neutral or dissatisfied +25239,102476,Female,Loyal Customer,60,Personal Travel,Eco,386,2,3,2,3,2,4,3,3,3,2,3,2,3,2,4,3.0,neutral or dissatisfied +25240,64431,Male,disloyal Customer,23,Business travel,Business,989,0,4,0,2,1,0,1,1,3,5,4,4,4,1,92,76.0,satisfied +25241,80475,Female,Loyal Customer,65,Personal Travel,Eco,1299,4,4,4,5,3,4,4,3,3,4,3,4,3,3,32,30.0,satisfied +25242,24855,Male,Loyal Customer,49,Business travel,Eco Plus,991,5,4,4,4,5,5,5,5,1,4,4,4,4,5,0,0.0,satisfied +25243,69943,Female,Loyal Customer,32,Business travel,Business,2174,3,3,1,3,5,5,5,5,4,3,4,3,5,5,0,0.0,satisfied +25244,67289,Male,Loyal Customer,33,Business travel,Eco Plus,918,4,3,3,3,4,4,4,4,4,2,3,4,4,4,0,0.0,neutral or dissatisfied +25245,5079,Male,disloyal Customer,25,Business travel,Business,223,4,3,5,4,4,5,4,4,1,1,3,1,3,4,23,25.0,neutral or dissatisfied +25246,34553,Female,Loyal Customer,47,Business travel,Business,1598,1,1,1,1,2,5,5,3,3,3,3,2,3,3,30,20.0,satisfied +25247,98370,Female,Loyal Customer,30,Personal Travel,Eco,1189,2,5,2,3,5,2,5,5,4,5,4,5,5,5,0,0.0,neutral or dissatisfied +25248,82226,Male,Loyal Customer,48,Business travel,Business,3360,5,5,5,5,2,4,4,4,4,4,4,4,4,5,0,0.0,satisfied +25249,117205,Female,Loyal Customer,23,Personal Travel,Eco,368,4,4,4,3,2,4,2,2,1,2,3,1,3,2,19,12.0,neutral or dissatisfied +25250,16933,Female,Loyal Customer,42,Business travel,Eco,820,2,1,1,1,2,4,4,1,1,2,1,1,1,4,3,7.0,neutral or dissatisfied +25251,72005,Female,Loyal Customer,49,Business travel,Business,1437,1,1,2,1,4,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +25252,121749,Female,Loyal Customer,61,Business travel,Business,2987,3,3,5,3,2,5,5,3,3,4,3,3,3,5,0,0.0,satisfied +25253,45528,Male,Loyal Customer,38,Business travel,Eco,554,4,1,1,1,4,4,4,5,3,1,4,4,4,4,133,125.0,satisfied +25254,13030,Male,Loyal Customer,67,Personal Travel,Eco,374,5,4,5,3,4,5,4,4,1,5,3,1,3,4,0,0.0,satisfied +25255,12640,Female,disloyal Customer,23,Business travel,Eco,844,4,3,3,5,2,3,2,2,3,1,2,2,2,2,0,0.0,satisfied +25256,79567,Male,Loyal Customer,36,Business travel,Business,762,4,1,1,1,4,4,4,3,3,4,3,4,3,4,200,218.0,neutral or dissatisfied +25257,68132,Female,Loyal Customer,63,Personal Travel,Eco,813,0,3,0,3,4,2,3,1,1,0,1,3,1,2,0,0.0,satisfied +25258,93479,Male,Loyal Customer,37,Business travel,Business,671,3,3,3,3,5,4,4,4,4,4,4,3,4,3,21,14.0,satisfied +25259,66652,Male,Loyal Customer,41,Business travel,Business,802,4,4,4,4,5,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +25260,118755,Female,Loyal Customer,54,Personal Travel,Eco,621,1,5,2,2,2,5,4,3,3,2,3,3,3,4,10,11.0,neutral or dissatisfied +25261,79212,Female,Loyal Customer,39,Personal Travel,Eco,1990,4,2,4,3,3,4,3,3,4,1,3,2,4,3,0,0.0,satisfied +25262,85474,Male,disloyal Customer,19,Business travel,Business,214,3,2,3,3,2,3,2,2,1,1,3,2,3,2,8,0.0,neutral or dissatisfied +25263,110671,Female,disloyal Customer,12,Business travel,Eco,1005,3,3,3,2,1,3,1,1,5,2,4,3,5,1,5,0.0,neutral or dissatisfied +25264,5481,Male,Loyal Customer,21,Personal Travel,Eco Plus,265,1,4,1,4,1,1,1,1,2,1,4,2,4,1,70,107.0,neutral or dissatisfied +25265,88425,Female,disloyal Customer,33,Business travel,Eco,404,3,3,3,3,1,3,1,1,3,4,4,3,3,1,0,0.0,neutral or dissatisfied +25266,86314,Male,Loyal Customer,30,Business travel,Eco Plus,226,3,4,4,4,3,3,3,3,1,1,3,2,4,3,102,100.0,neutral or dissatisfied +25267,127272,Male,Loyal Customer,47,Business travel,Business,2765,2,1,1,1,2,3,4,2,2,2,2,1,2,2,15,11.0,neutral or dissatisfied +25268,21830,Male,disloyal Customer,39,Business travel,Eco,640,1,3,1,3,5,1,5,5,1,5,3,3,4,5,9,8.0,neutral or dissatisfied +25269,86506,Female,Loyal Customer,38,Personal Travel,Eco,712,1,3,2,3,4,2,4,4,1,4,4,5,4,4,0,0.0,neutral or dissatisfied +25270,124486,Female,Loyal Customer,57,Business travel,Business,3500,1,1,1,1,5,2,3,1,1,1,1,4,1,1,0,0.0,neutral or dissatisfied +25271,124712,Male,Loyal Customer,37,Personal Travel,Eco,399,1,5,3,2,4,3,4,4,5,4,5,3,4,4,0,0.0,neutral or dissatisfied +25272,47461,Female,Loyal Customer,33,Personal Travel,Eco,532,2,4,4,5,4,4,4,4,5,4,4,4,4,4,7,12.0,neutral or dissatisfied +25273,45502,Male,Loyal Customer,53,Business travel,Eco Plus,674,5,2,2,2,5,5,5,5,3,1,3,1,4,5,54,58.0,satisfied +25274,65332,Male,Loyal Customer,45,Business travel,Business,2578,4,4,4,4,2,5,4,5,5,5,5,4,5,5,0,0.0,satisfied +25275,13882,Female,Loyal Customer,40,Business travel,Business,2537,1,1,1,1,3,5,5,3,3,4,3,2,3,5,0,0.0,satisfied +25276,126282,Male,Loyal Customer,19,Personal Travel,Eco,468,1,5,5,1,5,5,5,5,3,5,5,1,4,5,9,4.0,neutral or dissatisfied +25277,115455,Male,disloyal Customer,23,Business travel,Eco,390,3,0,3,3,3,3,3,3,4,1,4,3,4,3,26,22.0,neutral or dissatisfied +25278,114529,Female,Loyal Customer,62,Personal Travel,Business,325,3,5,3,1,1,1,3,4,4,3,4,3,4,3,0,0.0,neutral or dissatisfied +25279,3739,Male,Loyal Customer,66,Personal Travel,Eco,431,2,3,2,3,1,2,1,1,4,3,3,4,4,1,0,0.0,neutral or dissatisfied +25280,32909,Male,Loyal Customer,48,Personal Travel,Eco,163,1,5,0,1,2,0,2,2,5,2,5,5,5,2,0,0.0,neutral or dissatisfied +25281,61043,Male,Loyal Customer,26,Business travel,Business,1546,4,4,4,4,4,4,4,4,4,3,5,5,5,4,2,0.0,satisfied +25282,12169,Female,Loyal Customer,11,Business travel,Business,1075,1,5,5,5,1,1,1,1,3,2,3,3,2,1,0,0.0,neutral or dissatisfied +25283,89166,Female,Loyal Customer,33,Personal Travel,Eco,1947,3,4,3,1,3,3,3,3,4,4,5,4,5,3,0,6.0,neutral or dissatisfied +25284,100413,Female,Loyal Customer,14,Business travel,Eco Plus,1011,3,5,5,5,3,3,3,3,4,2,3,3,4,3,1,0.0,neutral or dissatisfied +25285,41484,Female,Loyal Customer,49,Business travel,Business,2531,2,2,2,2,4,2,3,5,5,5,5,4,5,4,19,32.0,satisfied +25286,81101,Female,Loyal Customer,54,Business travel,Business,3988,1,1,1,1,5,4,4,4,4,5,4,4,4,4,9,31.0,satisfied +25287,67598,Male,disloyal Customer,40,Business travel,Business,1464,2,2,2,5,5,2,2,5,5,5,4,4,5,5,0,32.0,satisfied +25288,65728,Male,Loyal Customer,28,Business travel,Business,936,3,3,3,3,2,2,2,2,4,2,4,4,5,2,0,0.0,satisfied +25289,107748,Male,Loyal Customer,66,Personal Travel,Eco,405,4,1,4,3,4,4,4,3,5,3,2,4,1,4,241,246.0,neutral or dissatisfied +25290,111504,Female,Loyal Customer,65,Business travel,Business,3718,2,5,5,5,4,3,4,2,2,3,2,4,2,4,0,0.0,neutral or dissatisfied +25291,91810,Male,Loyal Customer,21,Personal Travel,Eco,532,2,4,3,3,5,3,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +25292,113488,Male,Loyal Customer,42,Business travel,Eco,407,3,4,4,4,3,3,3,3,3,5,4,2,3,3,13,16.0,neutral or dissatisfied +25293,93322,Male,Loyal Customer,57,Business travel,Business,3156,5,1,5,5,2,5,5,4,4,4,4,5,4,5,0,0.0,satisfied +25294,6086,Female,disloyal Customer,29,Business travel,Eco Plus,693,3,3,3,4,3,4,4,1,1,3,3,4,2,4,144,133.0,neutral or dissatisfied +25295,72188,Male,Loyal Customer,50,Business travel,Business,594,3,2,3,3,3,5,4,4,4,4,4,3,4,3,0,4.0,satisfied +25296,63450,Female,Loyal Customer,60,Personal Travel,Eco,447,1,4,1,3,2,5,4,4,4,1,2,4,4,4,62,51.0,neutral or dissatisfied +25297,103720,Male,Loyal Customer,70,Personal Travel,Eco,251,5,5,5,3,4,5,4,4,4,5,4,5,4,4,0,0.0,satisfied +25298,16786,Female,Loyal Customer,42,Business travel,Eco Plus,642,4,5,5,5,4,3,5,4,4,4,4,2,4,4,0,0.0,satisfied +25299,61434,Female,disloyal Customer,34,Business travel,Business,2288,1,1,1,1,4,1,4,4,4,5,3,4,5,4,84,64.0,neutral or dissatisfied +25300,57913,Male,Loyal Customer,67,Personal Travel,Eco,305,2,5,2,1,4,2,4,4,5,3,4,3,4,4,30,48.0,neutral or dissatisfied +25301,12976,Female,Loyal Customer,20,Personal Travel,Business,374,1,3,1,5,5,1,5,5,2,1,4,1,1,5,0,0.0,neutral or dissatisfied +25302,57211,Female,Loyal Customer,48,Business travel,Eco,1514,1,3,4,3,1,3,4,1,1,1,1,2,1,4,0,0.0,neutral or dissatisfied +25303,86464,Female,disloyal Customer,22,Business travel,Eco,762,2,2,2,1,1,2,1,1,3,4,4,1,2,1,2,0.0,neutral or dissatisfied +25304,74008,Female,Loyal Customer,64,Business travel,Business,1471,1,1,1,1,2,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +25305,126666,Male,Loyal Customer,62,Business travel,Business,2626,5,5,5,5,4,5,4,4,4,4,4,5,4,5,11,0.0,satisfied +25306,99974,Female,Loyal Customer,47,Business travel,Eco Plus,888,1,3,3,3,2,3,4,1,1,1,1,1,1,1,0,7.0,neutral or dissatisfied +25307,72819,Male,Loyal Customer,21,Personal Travel,Eco Plus,1045,2,3,2,2,3,2,3,3,2,2,4,1,2,3,0,0.0,neutral or dissatisfied +25308,54850,Female,Loyal Customer,40,Business travel,Business,862,4,1,1,1,1,4,4,4,4,4,4,4,4,3,38,32.0,neutral or dissatisfied +25309,120250,Male,Loyal Customer,57,Personal Travel,Eco,1303,0,1,0,3,4,0,4,4,2,4,2,4,3,4,0,0.0,satisfied +25310,14211,Male,Loyal Customer,63,Personal Travel,Eco,692,4,5,4,2,1,4,1,1,5,5,3,1,1,1,4,9.0,satisfied +25311,118157,Female,Loyal Customer,35,Business travel,Business,1444,2,2,4,2,3,5,5,5,5,4,5,4,5,4,5,0.0,satisfied +25312,45430,Female,Loyal Customer,31,Business travel,Business,458,2,2,2,2,2,2,2,2,2,3,4,3,4,2,0,0.0,neutral or dissatisfied +25313,108321,Male,disloyal Customer,22,Business travel,Eco,984,2,2,2,3,5,2,5,5,2,3,3,2,3,5,4,0.0,neutral or dissatisfied +25314,47548,Female,Loyal Customer,34,Business travel,Eco Plus,501,0,0,0,1,4,0,5,4,3,3,1,1,3,4,0,0.0,satisfied +25315,47641,Female,disloyal Customer,28,Business travel,Eco,1428,4,4,4,3,5,4,3,5,4,5,3,2,4,5,20,18.0,neutral or dissatisfied +25316,57010,Female,Loyal Customer,68,Personal Travel,Eco,2454,4,4,4,4,5,4,3,4,4,4,4,4,4,4,1,0.0,neutral or dissatisfied +25317,66064,Male,Loyal Customer,15,Personal Travel,Eco,1055,1,5,1,5,2,1,2,2,3,3,4,3,5,2,0,0.0,neutral or dissatisfied +25318,60200,Male,disloyal Customer,22,Business travel,Eco,983,4,4,4,4,3,4,3,3,3,5,3,5,5,3,0,0.0,satisfied +25319,118582,Female,disloyal Customer,9,Business travel,Eco,646,1,4,1,3,4,1,4,4,3,3,4,3,3,4,76,67.0,neutral or dissatisfied +25320,20773,Male,disloyal Customer,26,Business travel,Eco,508,3,0,3,5,1,3,1,1,2,5,5,3,5,1,0,0.0,neutral or dissatisfied +25321,85150,Female,disloyal Customer,43,Business travel,Eco,696,2,2,2,3,5,2,5,5,4,4,3,1,3,5,0,0.0,neutral or dissatisfied +25322,120317,Female,Loyal Customer,35,Business travel,Eco,268,3,3,3,3,3,3,3,3,2,3,4,2,3,3,60,81.0,neutral or dissatisfied +25323,25833,Male,Loyal Customer,54,Business travel,Eco,692,4,5,5,5,4,4,4,4,2,5,1,4,5,4,16,12.0,satisfied +25324,79743,Female,Loyal Customer,30,Business travel,Eco Plus,762,1,3,3,3,1,1,1,1,4,5,4,4,3,1,0,0.0,neutral or dissatisfied +25325,66556,Male,Loyal Customer,61,Personal Travel,Eco,328,1,0,1,2,4,1,4,4,4,3,4,4,4,4,0,0.0,neutral or dissatisfied +25326,19072,Male,Loyal Customer,30,Business travel,Business,2451,3,1,1,1,3,3,3,3,1,1,3,4,3,3,0,0.0,neutral or dissatisfied +25327,73705,Male,disloyal Customer,56,Business travel,Eco,204,3,1,3,2,2,3,2,2,3,5,1,2,2,2,35,24.0,neutral or dissatisfied +25328,66129,Male,Loyal Customer,37,Personal Travel,Eco,583,4,5,3,5,2,3,2,2,3,4,4,5,5,2,0,0.0,satisfied +25329,34882,Male,Loyal Customer,26,Business travel,Eco Plus,2248,5,4,4,4,5,3,5,5,2,5,4,5,3,5,9,40.0,satisfied +25330,10615,Female,Loyal Customer,49,Business travel,Business,3330,5,1,5,5,4,4,4,5,5,5,5,3,5,4,0,0.0,satisfied +25331,4781,Female,Loyal Customer,57,Business travel,Business,315,2,5,5,5,4,2,2,2,2,1,2,1,2,2,0,21.0,neutral or dissatisfied +25332,38839,Female,disloyal Customer,23,Business travel,Eco,354,2,0,2,4,4,2,4,4,3,2,2,5,2,4,3,0.0,neutral or dissatisfied +25333,21205,Male,Loyal Customer,38,Business travel,Eco,192,5,2,2,2,5,5,5,5,4,3,3,3,1,5,0,0.0,satisfied +25334,45229,Female,Loyal Customer,32,Business travel,Eco,1013,4,2,2,2,4,4,4,4,1,2,3,2,4,4,0,4.0,neutral or dissatisfied +25335,11863,Female,Loyal Customer,31,Business travel,Business,1042,2,5,3,5,2,2,2,2,3,4,4,2,3,2,54,53.0,neutral or dissatisfied +25336,81472,Male,Loyal Customer,57,Business travel,Business,3691,1,4,4,4,2,3,3,1,1,1,1,1,1,2,0,0.0,neutral or dissatisfied +25337,95754,Male,Loyal Customer,18,Business travel,Business,2046,4,4,4,4,5,5,4,5,5,5,5,4,5,5,1,0.0,satisfied +25338,50209,Male,Loyal Customer,78,Business travel,Eco,77,4,5,5,5,5,4,5,5,1,3,2,3,2,5,0,0.0,neutral or dissatisfied +25339,6032,Female,Loyal Customer,22,Business travel,Eco,693,4,1,4,1,4,4,4,4,4,4,4,2,4,4,0,22.0,neutral or dissatisfied +25340,7297,Female,Loyal Customer,23,Personal Travel,Eco,139,2,3,2,3,3,2,3,3,4,5,3,2,4,3,47,45.0,neutral or dissatisfied +25341,10648,Male,Loyal Customer,44,Business travel,Business,1933,2,2,2,2,3,5,5,5,5,5,5,4,5,3,0,0.0,satisfied +25342,67336,Male,Loyal Customer,63,Business travel,Business,1471,2,2,2,2,5,5,5,4,4,4,4,4,4,3,21,13.0,satisfied +25343,61823,Male,Loyal Customer,20,Personal Travel,Eco,1334,3,5,3,3,4,3,4,4,4,2,5,3,4,4,0,0.0,neutral or dissatisfied +25344,42715,Female,Loyal Customer,46,Business travel,Business,3898,2,2,2,2,3,4,5,4,4,4,4,3,4,5,68,42.0,satisfied +25345,73171,Female,Loyal Customer,29,Personal Travel,Business,1258,3,5,3,1,1,3,1,1,4,2,5,3,4,1,0,0.0,neutral or dissatisfied +25346,64833,Female,Loyal Customer,51,Business travel,Business,247,3,3,3,3,2,4,5,4,4,4,4,5,4,3,0,2.0,satisfied +25347,126389,Male,Loyal Customer,10,Personal Travel,Eco,650,2,5,2,4,1,2,1,1,4,2,4,2,1,1,0,0.0,neutral or dissatisfied +25348,12779,Female,disloyal Customer,18,Business travel,Business,528,0,1,0,2,2,0,2,2,4,2,4,4,4,2,0,0.0,satisfied +25349,97787,Male,Loyal Customer,42,Business travel,Business,3904,5,5,5,5,4,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +25350,50955,Male,Loyal Customer,27,Personal Travel,Eco,337,2,2,2,3,1,2,1,1,3,1,4,2,3,1,0,3.0,neutral or dissatisfied +25351,62115,Female,Loyal Customer,45,Business travel,Business,2565,5,5,5,5,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +25352,57416,Male,Loyal Customer,22,Personal Travel,Eco,524,4,4,4,4,2,4,4,2,4,2,5,4,5,2,10,6.0,neutral or dissatisfied +25353,23997,Male,Loyal Customer,43,Business travel,Eco,562,4,3,3,3,4,4,4,4,4,1,3,4,4,4,0,0.0,satisfied +25354,99760,Female,Loyal Customer,37,Personal Travel,Eco,361,3,4,3,3,4,3,4,4,4,3,3,4,4,4,0,0.0,neutral or dissatisfied +25355,84551,Female,Loyal Customer,69,Personal Travel,Eco,2556,3,2,3,3,4,4,4,5,5,3,5,1,5,2,0,0.0,neutral or dissatisfied +25356,13844,Female,Loyal Customer,10,Personal Travel,Eco,594,2,4,2,2,2,4,3,2,3,1,5,3,4,3,128,233.0,neutral or dissatisfied +25357,128640,Male,Loyal Customer,7,Personal Travel,Eco,954,3,5,3,1,4,3,4,4,4,3,4,3,4,4,0,0.0,neutral or dissatisfied +25358,91617,Male,Loyal Customer,23,Business travel,Business,1340,2,2,2,2,5,5,5,5,5,4,4,3,5,5,61,47.0,satisfied +25359,21220,Male,Loyal Customer,40,Personal Travel,Eco,153,2,4,2,1,1,2,1,1,4,3,5,4,4,1,10,3.0,neutral or dissatisfied +25360,74225,Female,Loyal Customer,9,Personal Travel,Eco,1746,0,1,0,2,3,0,5,3,1,1,1,3,3,3,0,0.0,satisfied +25361,50272,Female,Loyal Customer,22,Business travel,Business,110,0,5,0,2,1,1,1,1,3,1,3,2,1,1,0,0.0,satisfied +25362,113042,Female,Loyal Customer,42,Business travel,Business,543,1,1,3,1,4,5,4,4,4,4,4,4,4,5,73,60.0,satisfied +25363,120799,Male,Loyal Customer,37,Business travel,Business,2060,5,5,5,5,2,5,4,5,5,5,5,5,5,3,0,0.0,satisfied +25364,19631,Male,Loyal Customer,17,Business travel,Business,1754,3,1,1,1,3,3,3,3,1,1,3,3,3,3,4,0.0,neutral or dissatisfied +25365,30888,Male,Loyal Customer,43,Personal Travel,Eco,653,1,1,1,3,5,1,2,5,2,1,3,2,4,5,25,13.0,neutral or dissatisfied +25366,52502,Female,Loyal Customer,50,Business travel,Business,110,5,5,5,5,2,5,5,4,4,4,5,5,4,4,0,0.0,satisfied +25367,54935,Male,Loyal Customer,26,Business travel,Business,2492,2,2,2,2,2,2,2,2,2,4,4,3,4,2,11,19.0,neutral or dissatisfied +25368,102418,Male,Loyal Customer,32,Personal Travel,Eco,258,2,3,2,5,5,2,5,5,3,3,1,2,1,5,10,4.0,neutral or dissatisfied +25369,118640,Female,Loyal Customer,16,Business travel,Eco,621,2,4,4,4,2,2,1,2,3,3,4,1,3,2,32,23.0,neutral or dissatisfied +25370,117340,Male,disloyal Customer,27,Business travel,Business,393,4,4,4,4,5,4,5,5,5,4,4,3,5,5,0,9.0,satisfied +25371,41680,Male,Loyal Customer,23,Personal Travel,Eco,936,0,3,0,3,5,0,5,5,3,3,4,4,3,5,0,14.0,satisfied +25372,62216,Female,Loyal Customer,33,Personal Travel,Eco,2454,3,4,3,3,1,3,1,1,2,3,4,3,3,1,7,22.0,neutral or dissatisfied +25373,115909,Female,disloyal Customer,16,Business travel,Eco,325,2,3,2,4,2,2,2,2,3,1,4,5,3,2,6,0.0,neutral or dissatisfied +25374,24569,Male,Loyal Customer,39,Personal Travel,Eco,696,3,4,3,2,1,3,1,1,4,2,5,3,5,1,2,0.0,neutral or dissatisfied +25375,27042,Male,Loyal Customer,52,Business travel,Business,1489,2,2,2,2,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +25376,19494,Female,Loyal Customer,55,Business travel,Eco,566,4,5,5,5,4,5,4,4,4,4,4,5,4,5,36,15.0,satisfied +25377,125148,Female,Loyal Customer,53,Business travel,Business,1999,5,5,1,5,2,5,5,5,5,5,5,4,5,5,5,0.0,satisfied +25378,12180,Male,disloyal Customer,56,Business travel,Eco,642,5,0,5,2,5,5,5,5,1,2,2,1,5,5,0,0.0,satisfied +25379,99433,Female,Loyal Customer,20,Personal Travel,Eco,337,1,3,2,4,5,2,5,5,1,1,5,1,4,5,0,0.0,neutral or dissatisfied +25380,118189,Male,Loyal Customer,38,Business travel,Eco,1440,1,5,5,5,1,1,1,1,3,2,3,3,3,1,0,0.0,neutral or dissatisfied +25381,95498,Female,Loyal Customer,49,Business travel,Eco Plus,148,2,2,2,2,5,4,4,2,2,2,2,1,2,4,7,12.0,neutral or dissatisfied +25382,75514,Female,disloyal Customer,49,Business travel,Business,748,4,4,4,2,2,4,2,2,4,2,5,3,4,2,0,0.0,satisfied +25383,72981,Male,Loyal Customer,9,Business travel,Business,1089,2,2,2,2,5,5,5,5,5,4,5,3,5,5,4,1.0,satisfied +25384,13066,Male,Loyal Customer,27,Business travel,Business,936,3,5,5,5,3,3,3,3,3,4,3,2,3,3,56,40.0,neutral or dissatisfied +25385,3043,Female,Loyal Customer,28,Business travel,Business,489,1,1,1,1,4,4,4,4,4,2,5,3,4,4,0,0.0,satisfied +25386,56435,Female,disloyal Customer,30,Business travel,Eco,719,3,2,2,3,4,2,2,4,4,4,3,4,3,4,0,0.0,neutral or dissatisfied +25387,69162,Male,Loyal Customer,24,Business travel,Eco,187,2,1,1,1,2,3,2,2,2,2,4,4,3,2,83,82.0,neutral or dissatisfied +25388,98084,Male,Loyal Customer,47,Business travel,Business,2253,1,2,1,1,4,4,5,4,4,4,4,3,4,3,51,47.0,satisfied +25389,70286,Female,Loyal Customer,38,Business travel,Business,852,4,5,5,5,4,3,3,4,4,4,4,3,4,1,38,35.0,neutral or dissatisfied +25390,22618,Male,Loyal Customer,61,Personal Travel,Eco,300,2,4,2,1,2,2,2,2,5,5,5,5,4,2,15,10.0,neutral or dissatisfied +25391,19935,Female,Loyal Customer,51,Personal Travel,Eco,315,1,1,1,3,5,3,3,4,4,1,4,2,4,2,0,0.0,neutral or dissatisfied +25392,92261,Male,Loyal Customer,44,Personal Travel,Eco Plus,1670,3,5,4,1,1,4,1,1,2,2,2,4,2,1,0,0.0,neutral or dissatisfied +25393,57941,Female,disloyal Customer,20,Business travel,Eco,837,1,2,2,3,2,2,5,2,1,1,4,1,3,2,40,63.0,neutral or dissatisfied +25394,13534,Female,Loyal Customer,42,Business travel,Business,2299,5,5,5,5,4,5,5,5,5,5,4,1,5,1,0,0.0,satisfied +25395,55098,Female,Loyal Customer,60,Business travel,Business,979,2,2,2,2,2,1,4,4,4,4,4,3,4,1,0,0.0,satisfied +25396,41554,Female,disloyal Customer,50,Business travel,Eco,1235,2,2,2,3,4,2,4,4,3,2,4,4,3,4,5,12.0,neutral or dissatisfied +25397,82585,Female,Loyal Customer,54,Business travel,Business,3055,2,2,2,2,4,4,5,4,4,4,4,4,4,5,0,0.0,satisfied +25398,21642,Female,Loyal Customer,53,Personal Travel,Eco,780,3,4,4,4,1,4,3,5,5,4,5,1,5,2,0,0.0,neutral or dissatisfied +25399,93728,Male,Loyal Customer,39,Personal Travel,Eco,630,3,4,3,3,5,3,4,5,3,2,4,5,5,5,11,12.0,neutral or dissatisfied +25400,103463,Female,Loyal Customer,48,Personal Travel,Eco,448,1,4,2,1,3,5,5,1,1,2,5,3,1,4,0,0.0,neutral or dissatisfied +25401,9487,Female,disloyal Customer,25,Business travel,Business,239,5,0,5,5,5,5,5,5,4,5,5,4,5,5,18,15.0,satisfied +25402,39677,Male,Loyal Customer,40,Business travel,Eco,612,2,3,2,3,2,2,2,2,1,4,3,4,4,2,18,8.0,neutral or dissatisfied +25403,110454,Female,Loyal Customer,16,Personal Travel,Eco,883,2,2,2,3,1,2,1,1,1,2,3,1,4,1,1,0.0,neutral or dissatisfied +25404,65541,Male,Loyal Customer,59,Business travel,Business,175,2,2,2,2,5,5,4,5,5,5,4,4,5,3,0,0.0,satisfied +25405,72929,Female,Loyal Customer,43,Business travel,Business,2645,1,1,4,1,5,5,5,5,5,5,5,4,5,3,72,113.0,satisfied +25406,56882,Male,Loyal Customer,45,Business travel,Business,2454,4,4,4,4,5,5,5,5,4,4,4,5,4,5,22,25.0,satisfied +25407,109948,Female,Loyal Customer,29,Personal Travel,Eco,1052,4,5,4,1,5,4,5,5,3,2,4,3,5,5,0,0.0,neutral or dissatisfied +25408,6636,Female,disloyal Customer,27,Business travel,Business,416,4,4,4,1,1,4,1,1,3,4,5,4,5,1,0,0.0,satisfied +25409,91171,Male,Loyal Customer,60,Personal Travel,Eco,581,1,4,1,2,1,1,1,1,5,4,2,3,2,1,0,0.0,neutral or dissatisfied +25410,88966,Male,Loyal Customer,52,Business travel,Business,1199,2,4,4,4,5,3,4,2,2,2,2,3,2,4,72,78.0,neutral or dissatisfied +25411,23609,Female,Loyal Customer,64,Personal Travel,Eco,589,2,5,2,2,5,4,5,3,3,2,3,5,3,4,0,0.0,neutral or dissatisfied +25412,115057,Female,disloyal Customer,36,Business travel,Eco,337,2,1,2,4,2,2,2,2,1,5,4,3,4,2,64,57.0,neutral or dissatisfied +25413,33359,Female,Loyal Customer,49,Business travel,Eco,2349,5,4,4,4,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +25414,111935,Female,disloyal Customer,26,Business travel,Business,770,1,1,1,3,2,1,2,2,5,5,4,5,5,2,12,0.0,neutral or dissatisfied +25415,119401,Female,Loyal Customer,52,Business travel,Business,2593,4,4,3,4,5,4,4,5,5,5,5,4,5,4,5,28.0,satisfied +25416,120798,Female,Loyal Customer,58,Business travel,Business,666,5,5,5,5,2,4,5,3,3,3,3,5,3,5,0,0.0,satisfied +25417,72214,Male,disloyal Customer,37,Business travel,Business,919,5,5,5,2,2,5,2,2,3,5,5,5,5,2,0,0.0,satisfied +25418,115711,Male,disloyal Customer,36,Business travel,Business,446,2,2,2,4,4,2,4,4,5,5,5,3,4,4,0,0.0,neutral or dissatisfied +25419,26739,Male,Loyal Customer,70,Personal Travel,Eco Plus,270,2,0,0,3,4,0,2,4,5,3,4,4,4,4,45,43.0,neutral or dissatisfied +25420,115303,Male,Loyal Customer,33,Business travel,Business,337,3,2,2,2,3,3,3,3,2,3,3,1,2,3,15,4.0,neutral or dissatisfied +25421,15776,Male,disloyal Customer,26,Business travel,Eco,254,2,5,2,4,2,2,2,2,5,4,5,3,2,2,0,0.0,neutral or dissatisfied +25422,40515,Female,Loyal Customer,40,Business travel,Eco Plus,222,4,3,5,3,4,5,4,4,4,2,2,2,5,4,0,0.0,satisfied +25423,44299,Male,Loyal Customer,30,Business travel,Eco,867,3,5,5,5,2,3,3,4,2,3,3,3,3,3,187,202.0,neutral or dissatisfied +25424,54515,Male,Loyal Customer,58,Business travel,Eco,925,4,2,2,2,4,4,4,4,5,3,1,1,4,4,0,0.0,satisfied +25425,121041,Male,Loyal Customer,55,Personal Travel,Eco,992,2,5,2,4,5,2,5,5,5,4,5,4,5,5,0,31.0,neutral or dissatisfied +25426,113576,Male,disloyal Customer,23,Business travel,Eco,223,4,0,4,4,4,4,4,4,2,5,2,2,5,4,0,12.0,satisfied +25427,70991,Male,disloyal Customer,24,Business travel,Eco,978,4,4,4,3,2,4,5,2,4,4,3,2,2,2,0,0.0,neutral or dissatisfied +25428,121272,Female,disloyal Customer,38,Business travel,Business,2075,2,2,2,4,1,2,1,1,4,3,4,5,4,1,17,14.0,neutral or dissatisfied +25429,96204,Female,Loyal Customer,55,Business travel,Eco,490,3,2,2,2,4,4,4,3,3,3,3,3,3,1,0,3.0,neutral or dissatisfied +25430,39797,Male,Loyal Customer,67,Business travel,Business,3437,2,2,2,2,5,4,4,5,5,5,5,3,5,5,0,1.0,satisfied +25431,63918,Male,Loyal Customer,22,Business travel,Business,758,5,5,5,5,3,3,3,3,3,1,1,3,2,3,0,0.0,satisfied +25432,69360,Female,disloyal Customer,23,Business travel,Eco,1089,3,4,4,4,5,4,1,5,5,4,4,3,4,5,0,17.0,neutral or dissatisfied +25433,96503,Female,Loyal Customer,36,Business travel,Eco,302,4,4,4,4,4,4,4,4,3,3,3,1,3,4,47,32.0,satisfied +25434,113487,Male,Loyal Customer,50,Business travel,Business,414,4,4,4,4,3,5,4,5,5,5,5,3,5,4,16,10.0,satisfied +25435,36309,Female,Loyal Customer,55,Business travel,Eco,187,4,4,5,5,5,3,4,4,4,4,4,4,4,2,0,0.0,satisfied +25436,129368,Female,Loyal Customer,40,Business travel,Business,2565,4,4,4,4,2,5,4,4,4,4,4,4,4,3,0,0.0,satisfied +25437,99306,Male,Loyal Customer,39,Business travel,Business,2488,5,5,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +25438,74925,Female,disloyal Customer,48,Business travel,Eco,2475,3,3,3,3,4,3,4,4,4,2,4,2,3,4,0,0.0,neutral or dissatisfied +25439,9673,Male,disloyal Customer,25,Business travel,Business,277,1,2,1,3,4,1,2,4,4,5,3,4,4,4,44,43.0,neutral or dissatisfied +25440,85347,Male,Loyal Customer,54,Business travel,Business,813,5,5,4,5,2,4,5,2,2,2,2,4,2,3,0,0.0,satisfied +25441,107344,Female,disloyal Customer,23,Business travel,Business,632,4,5,3,4,3,3,4,3,4,4,5,4,4,3,24,19.0,satisfied +25442,40310,Female,Loyal Customer,25,Personal Travel,Eco,463,2,4,2,4,1,2,1,1,3,3,4,3,4,1,0,0.0,neutral or dissatisfied +25443,62129,Male,Loyal Customer,40,Business travel,Business,2454,3,3,3,3,4,4,4,5,5,5,5,5,5,5,0,0.0,satisfied +25444,96041,Male,disloyal Customer,27,Business travel,Business,1069,3,3,3,3,2,3,2,2,4,1,3,3,3,2,0,0.0,neutral or dissatisfied +25445,50964,Male,Loyal Customer,39,Personal Travel,Eco,363,1,2,1,3,3,1,3,3,3,3,4,2,4,3,0,0.0,neutral or dissatisfied +25446,48000,Female,Loyal Customer,26,Business travel,Eco Plus,838,5,1,1,1,5,5,5,5,1,1,5,4,5,5,0,0.0,satisfied +25447,119344,Male,Loyal Customer,56,Business travel,Business,214,3,1,3,3,2,5,5,4,4,4,4,5,4,4,0,55.0,satisfied +25448,38188,Female,Loyal Customer,7,Personal Travel,Eco,1121,1,5,2,1,5,2,5,5,4,2,4,3,5,5,0,0.0,neutral or dissatisfied +25449,89813,Female,disloyal Customer,22,Business travel,Eco Plus,950,3,4,3,3,4,3,4,4,4,5,4,3,4,4,0,0.0,neutral or dissatisfied +25450,2961,Female,Loyal Customer,51,Personal Travel,Eco,737,3,5,4,5,5,4,4,3,3,4,3,4,3,5,1,7.0,neutral or dissatisfied +25451,70438,Female,Loyal Customer,36,Business travel,Business,187,0,5,0,3,5,4,5,1,1,1,1,5,1,5,0,0.0,satisfied +25452,66600,Male,disloyal Customer,13,Business travel,Eco,761,2,2,2,2,3,2,3,3,4,5,4,4,4,3,0,0.0,neutral or dissatisfied +25453,28846,Male,Loyal Customer,31,Business travel,Eco,954,5,2,2,2,5,5,5,5,1,5,4,1,2,5,0,0.0,satisfied +25454,90323,Male,disloyal Customer,27,Business travel,Business,366,5,5,5,1,4,5,4,4,3,4,4,3,4,4,0,0.0,satisfied +25455,20361,Female,Loyal Customer,23,Business travel,Business,2995,3,3,3,3,3,3,3,3,2,3,4,1,3,3,38,26.0,neutral or dissatisfied +25456,63875,Female,Loyal Customer,55,Business travel,Business,1158,2,2,2,2,4,4,5,4,4,4,4,3,4,4,0,0.0,satisfied +25457,6300,Male,Loyal Customer,55,Business travel,Business,296,0,0,0,2,4,5,5,1,1,1,1,5,1,4,0,34.0,satisfied +25458,119666,Male,Loyal Customer,10,Personal Travel,Eco,507,3,5,3,5,5,3,3,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +25459,3503,Male,Loyal Customer,12,Personal Travel,Eco,990,1,4,1,4,1,3,3,3,5,5,5,3,5,3,243,244.0,neutral or dissatisfied +25460,44225,Male,Loyal Customer,52,Business travel,Eco,222,4,3,5,3,3,4,3,3,2,2,5,5,2,3,0,15.0,satisfied +25461,83284,Male,Loyal Customer,34,Personal Travel,Eco,1956,3,5,3,2,3,3,3,3,3,2,3,5,4,3,1,0.0,neutral or dissatisfied +25462,1437,Male,Loyal Customer,62,Personal Travel,Business,772,4,1,4,2,1,1,2,2,2,4,2,2,2,3,6,0.0,neutral or dissatisfied +25463,68031,Male,Loyal Customer,33,Business travel,Business,2814,1,1,1,1,4,4,4,4,5,3,4,5,4,4,11,0.0,satisfied +25464,74767,Female,Loyal Customer,44,Personal Travel,Eco,1171,2,5,2,4,4,5,4,4,4,2,4,5,4,3,0,0.0,neutral or dissatisfied +25465,10354,Female,Loyal Customer,55,Business travel,Business,1778,4,4,4,4,3,5,5,5,5,5,5,3,5,5,0,0.0,satisfied +25466,81193,Female,Loyal Customer,54,Business travel,Eco Plus,726,2,5,5,5,2,4,3,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +25467,85547,Female,Loyal Customer,40,Business travel,Business,2935,1,1,1,1,3,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +25468,85927,Male,disloyal Customer,26,Business travel,Business,447,1,0,1,4,4,1,4,4,5,4,4,4,5,4,4,,neutral or dissatisfied +25469,75800,Female,Loyal Customer,10,Personal Travel,Eco,813,1,4,1,3,2,1,3,2,4,1,4,2,3,2,0,0.0,neutral or dissatisfied +25470,44533,Female,disloyal Customer,57,Business travel,Eco,157,3,0,3,3,1,3,1,1,3,2,1,1,1,1,0,0.0,neutral or dissatisfied +25471,128129,Female,Loyal Customer,60,Personal Travel,Eco,1587,2,4,2,3,4,4,3,1,1,2,1,2,1,3,0,0.0,neutral or dissatisfied +25472,119512,Male,Loyal Customer,54,Business travel,Business,857,3,4,4,4,3,3,3,3,3,3,3,3,3,3,10,40.0,neutral or dissatisfied +25473,56239,Male,Loyal Customer,54,Personal Travel,Eco Plus,1585,2,1,2,2,4,2,5,4,1,5,1,4,1,4,21,2.0,neutral or dissatisfied +25474,129329,Male,Loyal Customer,47,Business travel,Business,2586,1,0,0,4,1,2,4,2,2,0,2,3,2,2,0,7.0,neutral or dissatisfied +25475,3486,Male,Loyal Customer,40,Business travel,Business,990,4,4,4,4,2,5,5,4,4,4,4,4,4,4,10,24.0,satisfied +25476,59974,Male,Loyal Customer,39,Business travel,Eco,537,3,5,5,5,3,5,3,3,5,1,5,1,5,3,0,0.0,satisfied +25477,84205,Female,Loyal Customer,44,Business travel,Business,3078,1,1,1,1,5,4,5,3,3,4,3,4,3,4,0,0.0,satisfied +25478,69304,Female,Loyal Customer,56,Business travel,Business,944,3,3,3,3,3,4,4,5,5,5,5,3,5,4,4,0.0,satisfied +25479,72014,Male,disloyal Customer,40,Business travel,Business,3784,3,3,3,3,3,1,1,3,5,4,4,1,5,1,0,0.0,neutral or dissatisfied +25480,103528,Female,Loyal Customer,54,Business travel,Business,2936,3,3,3,3,5,5,4,5,5,4,5,3,5,4,0,0.0,satisfied +25481,17853,Female,Loyal Customer,30,Business travel,Eco Plus,615,5,2,2,2,5,4,5,5,5,1,2,4,3,5,0,0.0,satisfied +25482,17141,Male,Loyal Customer,31,Personal Travel,Eco,455,3,2,3,4,2,3,2,2,3,1,3,2,3,2,28,31.0,neutral or dissatisfied +25483,71843,Male,disloyal Customer,14,Business travel,Eco,1134,4,4,4,3,2,4,2,2,4,4,3,4,4,2,12,12.0,neutral or dissatisfied +25484,70698,Female,Loyal Customer,24,Personal Travel,Eco Plus,447,5,3,5,1,5,5,3,5,3,5,2,5,4,5,0,0.0,satisfied +25485,30920,Female,disloyal Customer,80,Business travel,Business,496,4,5,5,4,5,4,4,5,5,4,5,5,5,4,0,0.0,satisfied +25486,2538,Male,disloyal Customer,21,Business travel,Eco,181,4,0,4,5,5,4,5,5,4,5,4,4,5,5,0,0.0,neutral or dissatisfied +25487,41540,Male,Loyal Customer,47,Business travel,Business,2215,2,2,2,2,3,3,1,4,4,4,4,1,4,1,0,0.0,satisfied +25488,63695,Female,Loyal Customer,59,Business travel,Eco,853,1,0,0,3,1,4,4,3,3,1,1,3,3,4,125,121.0,neutral or dissatisfied +25489,52844,Male,Loyal Customer,26,Personal Travel,Eco,1721,3,5,3,4,3,3,3,3,4,2,5,4,5,3,0,0.0,neutral or dissatisfied +25490,97648,Male,Loyal Customer,24,Business travel,Business,1587,5,1,5,5,5,5,5,5,3,4,4,5,4,5,0,0.0,satisfied +25491,76936,Female,Loyal Customer,57,Personal Travel,Eco,1823,3,4,3,4,3,5,5,3,4,3,5,5,5,5,181,179.0,neutral or dissatisfied +25492,76978,Male,disloyal Customer,20,Business travel,Eco,469,1,2,1,4,2,1,2,2,2,2,3,3,4,2,1,0.0,neutral or dissatisfied +25493,15030,Female,Loyal Customer,57,Business travel,Business,1997,4,4,4,4,1,3,3,4,4,4,4,5,4,1,0,0.0,satisfied +25494,45841,Female,Loyal Customer,21,Personal Travel,Eco,391,4,5,2,3,3,2,5,3,3,4,4,4,5,3,0,0.0,neutral or dissatisfied +25495,33360,Male,Loyal Customer,26,Business travel,Business,2462,4,4,4,4,5,5,5,5,2,1,4,1,3,5,0,0.0,satisfied +25496,114806,Female,Loyal Customer,45,Business travel,Business,2907,1,1,1,1,5,5,5,4,4,4,4,5,4,4,12,17.0,satisfied +25497,80686,Female,Loyal Customer,49,Business travel,Business,1886,1,1,1,1,5,4,5,5,5,5,5,4,5,4,0,0.0,satisfied +25498,3385,Male,Loyal Customer,50,Business travel,Business,3021,1,1,4,1,4,4,5,4,4,4,4,3,4,5,3,4.0,satisfied +25499,106788,Female,Loyal Customer,50,Personal Travel,Eco Plus,1005,2,5,2,1,1,5,5,3,3,2,4,4,3,1,3,0.0,neutral or dissatisfied +25500,14595,Female,Loyal Customer,13,Personal Travel,Eco,986,3,2,3,3,3,2,4,2,5,3,4,4,3,4,214,210.0,neutral or dissatisfied +25501,57915,Male,Loyal Customer,8,Personal Travel,Eco,305,4,2,4,3,2,4,2,2,2,3,4,4,4,2,0,0.0,satisfied +25502,107591,Female,disloyal Customer,23,Business travel,Business,423,0,0,0,4,3,0,4,3,4,5,5,5,4,3,66,110.0,satisfied +25503,67454,Male,Loyal Customer,51,Personal Travel,Eco,641,1,5,1,2,2,1,2,2,3,4,4,5,5,2,0,0.0,neutral or dissatisfied +25504,77099,Female,Loyal Customer,36,Business travel,Business,1481,3,3,3,3,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +25505,51920,Male,Loyal Customer,25,Business travel,Eco Plus,601,4,4,1,4,4,4,5,4,5,5,3,5,2,4,0,0.0,satisfied +25506,46878,Female,Loyal Customer,60,Business travel,Business,2462,3,3,3,3,2,2,2,4,4,4,4,4,4,5,8,20.0,satisfied +25507,116006,Female,Loyal Customer,64,Personal Travel,Eco,446,5,5,5,2,5,5,5,5,5,5,5,4,5,5,10,0.0,satisfied +25508,47374,Female,Loyal Customer,33,Business travel,Business,590,2,5,2,5,3,3,3,2,2,2,2,3,2,3,16,0.0,neutral or dissatisfied +25509,33482,Male,Loyal Customer,47,Personal Travel,Eco,2422,3,1,2,4,2,2,2,2,3,3,4,1,4,2,10,54.0,neutral or dissatisfied +25510,117965,Male,Loyal Customer,55,Personal Travel,Eco,255,4,3,0,4,1,0,1,1,1,1,2,5,3,1,0,0.0,neutral or dissatisfied +25511,78555,Male,Loyal Customer,46,Business travel,Eco Plus,666,1,4,4,4,1,1,1,1,4,4,2,3,3,1,0,0.0,neutral or dissatisfied +25512,96422,Male,Loyal Customer,23,Business travel,Eco Plus,1407,0,5,5,5,0,1,4,0,2,1,4,1,3,0,28,26.0,neutral or dissatisfied +25513,32791,Male,Loyal Customer,55,Business travel,Business,2012,2,2,2,2,5,3,4,4,4,4,5,1,4,3,0,0.0,satisfied +25514,22092,Female,Loyal Customer,41,Business travel,Business,3147,3,2,1,2,4,2,3,3,3,2,3,3,3,2,66,70.0,neutral or dissatisfied +25515,79855,Female,Loyal Customer,37,Business travel,Business,3718,3,3,3,3,5,5,4,4,4,4,4,4,4,4,0,0.0,satisfied +25516,78615,Male,Loyal Customer,42,Business travel,Business,1426,1,1,1,1,3,4,4,4,4,4,4,5,4,5,0,0.0,satisfied +25517,23375,Male,Loyal Customer,70,Personal Travel,Eco,872,2,2,1,4,3,1,3,3,1,4,2,4,3,3,82,96.0,neutral or dissatisfied +25518,114144,Male,Loyal Customer,46,Business travel,Business,3033,3,3,3,3,2,4,5,5,5,5,5,3,5,5,0,0.0,satisfied +25519,96219,Female,disloyal Customer,27,Business travel,Eco,546,3,1,3,2,2,3,2,2,4,5,2,4,2,2,20,13.0,neutral or dissatisfied +25520,62071,Male,Loyal Customer,46,Personal Travel,Eco,2586,4,0,4,2,2,4,2,2,4,3,5,3,4,2,0,0.0,neutral or dissatisfied +25521,45336,Male,disloyal Customer,27,Business travel,Eco,150,4,2,4,1,4,4,4,4,3,1,1,2,1,4,0,0.0,neutral or dissatisfied +25522,78178,Male,Loyal Customer,42,Business travel,Business,3282,1,1,1,1,3,5,4,5,5,5,5,4,5,4,3,0.0,satisfied +25523,51532,Female,Loyal Customer,51,Business travel,Business,2562,5,5,5,5,2,1,1,4,4,4,4,5,4,5,0,0.0,satisfied +25524,94356,Female,Loyal Customer,59,Business travel,Business,319,0,0,0,3,4,4,4,3,3,3,3,3,3,5,0,0.0,satisfied +25525,51528,Male,Loyal Customer,38,Business travel,Business,2862,3,1,1,1,3,4,3,3,3,3,3,2,3,1,4,0.0,neutral or dissatisfied +25526,56787,Female,Loyal Customer,55,Business travel,Business,1068,1,1,1,1,5,4,5,5,5,5,5,4,5,5,0,0.0,satisfied +25527,13333,Female,Loyal Customer,30,Business travel,Business,1663,1,1,1,1,4,4,4,4,3,3,3,1,4,4,121,103.0,satisfied +25528,74596,Male,Loyal Customer,42,Business travel,Business,1171,1,1,1,1,5,4,5,4,4,4,4,5,4,4,0,0.0,satisfied +25529,104647,Male,Loyal Customer,38,Business travel,Business,1754,5,3,3,3,3,3,3,5,5,4,5,1,5,3,6,30.0,neutral or dissatisfied +25530,115671,Male,Loyal Customer,46,Business travel,Business,417,5,5,5,5,2,4,4,4,4,5,4,5,4,3,0,5.0,satisfied +25531,7178,Female,Loyal Customer,31,Business travel,Business,3650,2,4,4,4,2,2,2,2,4,4,3,3,4,2,69,103.0,neutral or dissatisfied +25532,69218,Male,Loyal Customer,55,Business travel,Business,1592,2,2,2,2,4,4,4,5,5,5,5,5,5,3,0,0.0,satisfied +25533,112941,Female,Loyal Customer,21,Personal Travel,Eco,1390,3,4,3,3,2,3,2,2,2,4,3,3,3,2,8,17.0,neutral or dissatisfied +25534,59286,Female,Loyal Customer,13,Personal Travel,Eco,3365,1,4,1,2,1,3,3,5,2,4,5,3,4,3,13,0.0,neutral or dissatisfied +25535,119957,Male,disloyal Customer,62,Business travel,Eco,1009,3,3,3,3,1,3,1,1,4,1,4,1,4,1,0,0.0,neutral or dissatisfied +25536,124223,Female,Loyal Customer,58,Business travel,Business,1916,2,2,2,2,2,3,2,2,2,2,2,3,2,1,14,0.0,neutral or dissatisfied +25537,71693,Female,Loyal Customer,58,Personal Travel,Eco,1197,2,4,2,2,5,5,5,1,1,2,1,5,1,4,0,0.0,neutral or dissatisfied +25538,3762,Female,Loyal Customer,48,Business travel,Business,2764,1,1,1,1,2,4,5,3,3,3,3,4,3,4,3,2.0,satisfied +25539,29818,Female,Loyal Customer,37,Business travel,Eco,123,4,4,5,4,4,4,4,4,4,4,4,3,2,4,7,8.0,satisfied +25540,15198,Male,disloyal Customer,57,Business travel,Eco,461,2,2,2,4,2,3,3,3,4,4,3,3,2,3,128,148.0,neutral or dissatisfied +25541,107150,Female,Loyal Customer,28,Business travel,Eco,402,1,3,2,2,1,1,1,1,4,2,4,2,4,1,0,0.0,neutral or dissatisfied +25542,78242,Female,Loyal Customer,57,Business travel,Eco Plus,192,1,5,4,5,3,4,4,1,1,1,1,1,1,4,29,48.0,neutral or dissatisfied +25543,65290,Male,Loyal Customer,22,Personal Travel,Eco Plus,551,2,1,2,3,1,2,1,1,4,3,4,2,3,1,0,0.0,neutral or dissatisfied +25544,124917,Male,disloyal Customer,33,Business travel,Eco,728,1,1,1,4,5,1,5,5,4,1,3,4,4,5,0,12.0,neutral or dissatisfied +25545,40777,Female,disloyal Customer,24,Business travel,Eco,588,2,3,2,3,4,2,4,4,1,3,2,2,2,4,0,0.0,neutral or dissatisfied +25546,83403,Male,Loyal Customer,21,Business travel,Business,1593,4,4,4,4,5,5,5,5,4,3,5,3,4,5,32,11.0,satisfied +25547,63263,Female,disloyal Customer,42,Business travel,Eco,372,3,1,3,3,3,3,3,3,1,4,3,4,3,3,0,0.0,neutral or dissatisfied +25548,47801,Male,Loyal Customer,47,Business travel,Eco,451,5,5,5,5,5,5,5,5,5,5,4,4,2,5,0,0.0,satisfied +25549,117405,Female,Loyal Customer,31,Business travel,Business,1136,4,4,4,4,4,4,4,4,4,5,4,5,5,4,0,0.0,satisfied +25550,108364,Female,Loyal Customer,54,Personal Travel,Eco,1844,0,3,0,4,5,4,1,5,5,0,5,5,5,3,64,50.0,satisfied +25551,29347,Female,Loyal Customer,32,Business travel,Eco,2588,4,1,1,1,4,4,4,4,1,5,4,2,3,4,0,0.0,satisfied +25552,61741,Female,Loyal Customer,56,Business travel,Business,3363,2,2,2,2,4,3,4,2,2,2,2,4,2,2,43,31.0,neutral or dissatisfied +25553,108194,Female,disloyal Customer,57,Business travel,Eco Plus,990,2,2,2,3,2,5,5,2,3,3,4,5,2,5,141,129.0,neutral or dissatisfied +25554,99096,Female,Loyal Customer,16,Business travel,Business,3201,3,3,3,3,2,2,3,2,2,4,3,1,4,2,0,0.0,neutral or dissatisfied +25555,115403,Male,Loyal Customer,54,Business travel,Business,2660,2,2,2,2,2,4,3,2,2,2,2,3,2,3,15,13.0,neutral or dissatisfied +25556,102380,Female,disloyal Customer,29,Business travel,Eco,386,3,2,3,3,4,3,4,4,3,4,3,1,3,4,37,29.0,neutral or dissatisfied +25557,87817,Male,Loyal Customer,37,Business travel,Business,214,4,3,3,3,4,4,4,4,4,4,4,3,4,2,12,3.0,neutral or dissatisfied +25558,34848,Female,Loyal Customer,13,Personal Travel,Eco Plus,264,2,1,2,3,5,2,5,5,4,2,3,3,2,5,0,0.0,neutral or dissatisfied +25559,46157,Male,Loyal Customer,8,Personal Travel,Eco,516,4,3,4,4,2,4,2,2,1,2,4,2,1,2,10,0.0,satisfied +25560,97913,Female,disloyal Customer,45,Business travel,Business,722,5,5,5,1,3,5,3,3,3,3,5,3,4,3,0,0.0,satisfied +25561,9077,Male,Loyal Customer,64,Personal Travel,Eco,160,0,5,0,4,2,0,2,2,4,3,4,5,5,2,2,0.0,satisfied +25562,2400,Male,Loyal Customer,30,Business travel,Eco,641,2,2,4,4,2,2,2,2,2,1,4,2,3,2,34,18.0,neutral or dissatisfied +25563,40373,Female,Loyal Customer,48,Business travel,Business,1250,4,4,4,4,4,1,3,5,5,5,5,4,5,4,0,0.0,satisfied +25564,26860,Female,disloyal Customer,39,Business travel,Business,224,4,4,4,3,5,4,5,5,2,4,2,4,5,5,0,2.0,neutral or dissatisfied +25565,8227,Female,Loyal Customer,51,Personal Travel,Eco,402,2,4,2,2,2,5,4,2,2,2,2,4,2,5,0,0.0,neutral or dissatisfied +25566,57491,Female,Loyal Customer,55,Business travel,Business,2964,5,5,5,5,4,5,4,5,5,5,5,4,5,5,35,29.0,satisfied +25567,44462,Female,Loyal Customer,39,Business travel,Eco,196,5,5,2,5,5,5,5,5,2,2,3,3,4,5,6,11.0,satisfied +25568,1125,Male,Loyal Customer,22,Personal Travel,Eco,309,3,4,3,1,2,3,2,2,4,4,5,3,5,2,6,4.0,neutral or dissatisfied +25569,95021,Male,Loyal Customer,14,Personal Travel,Eco,248,5,5,5,2,1,5,1,1,5,5,5,5,5,1,9,3.0,satisfied +25570,103621,Male,Loyal Customer,60,Business travel,Business,405,4,4,5,4,3,4,5,4,4,4,4,4,4,3,21,25.0,satisfied +25571,63870,Female,disloyal Customer,27,Business travel,Business,1192,4,4,4,1,1,4,5,1,3,5,4,4,4,1,0,0.0,satisfied +25572,51177,Female,Loyal Customer,30,Business travel,Eco Plus,89,3,3,2,3,3,3,3,3,4,1,4,3,4,3,0,13.0,neutral or dissatisfied +25573,68437,Female,Loyal Customer,67,Business travel,Eco Plus,645,5,1,1,1,4,2,5,5,5,5,5,5,5,3,0,0.0,satisfied +25574,16776,Male,Loyal Customer,63,Personal Travel,Eco,569,4,5,4,4,4,4,4,3,4,4,5,4,3,4,332,311.0,satisfied +25575,48217,Female,Loyal Customer,47,Personal Travel,Eco,259,3,3,3,5,5,4,5,4,4,3,1,1,4,1,0,0.0,neutral or dissatisfied +25576,31828,Female,disloyal Customer,33,Business travel,Eco,2762,3,4,4,5,3,2,2,5,2,4,5,2,1,2,0,0.0,neutral or dissatisfied +25577,98517,Female,Loyal Customer,65,Business travel,Eco,268,5,1,1,1,1,4,5,5,5,5,5,2,5,2,24,0.0,satisfied +25578,100387,Female,Loyal Customer,61,Personal Travel,Eco,1092,3,5,3,3,3,5,3,5,5,3,5,4,5,3,3,0.0,neutral or dissatisfied +25579,14061,Male,Loyal Customer,60,Business travel,Business,319,3,3,3,3,4,1,1,5,5,5,5,5,5,1,0,0.0,satisfied +25580,122682,Female,disloyal Customer,33,Business travel,Eco,361,3,1,3,3,1,3,2,1,3,5,4,4,4,1,0,12.0,neutral or dissatisfied +25581,1803,Male,Loyal Customer,55,Business travel,Business,408,4,4,4,4,3,5,4,4,4,4,4,3,4,5,10,1.0,satisfied +25582,63816,Female,Loyal Customer,44,Business travel,Business,1192,3,4,2,4,4,2,2,3,3,3,3,1,3,3,11,18.0,neutral or dissatisfied +25583,97289,Male,Loyal Customer,54,Business travel,Business,2760,4,4,5,4,5,5,5,4,4,4,4,3,4,5,3,0.0,satisfied +25584,89810,Male,Loyal Customer,22,Business travel,Business,1005,5,5,5,5,5,5,5,5,3,5,5,3,4,5,0,0.0,satisfied +25585,33924,Male,Loyal Customer,43,Business travel,Eco,818,2,3,3,3,2,2,2,2,4,1,4,4,4,2,14,21.0,neutral or dissatisfied +25586,11292,Male,Loyal Customer,8,Personal Travel,Eco,429,1,5,1,1,1,1,1,1,1,4,1,5,3,1,3,8.0,neutral or dissatisfied +25587,19490,Male,disloyal Customer,17,Business travel,Eco,84,3,3,3,4,2,3,2,2,2,2,3,2,3,2,60,49.0,neutral or dissatisfied +25588,69721,Male,Loyal Customer,23,Personal Travel,Eco,1372,3,5,3,2,3,3,3,3,4,3,4,4,4,3,0,6.0,neutral or dissatisfied +25589,91214,Male,Loyal Customer,64,Personal Travel,Eco,271,2,4,2,5,4,2,4,4,3,2,4,4,4,4,0,0.0,neutral or dissatisfied +25590,66386,Female,Loyal Customer,19,Business travel,Business,1562,4,4,5,4,4,4,4,4,3,2,4,5,4,4,0,0.0,satisfied +25591,79904,Male,Loyal Customer,54,Business travel,Business,950,5,5,5,5,5,5,4,3,3,3,3,3,3,3,0,13.0,satisfied +25592,121979,Female,Loyal Customer,66,Business travel,Business,2784,3,2,4,2,1,3,4,4,4,4,3,4,4,1,0,0.0,neutral or dissatisfied +25593,7291,Male,Loyal Customer,49,Personal Travel,Eco,135,3,0,3,3,3,1,1,4,5,5,5,1,4,1,51,132.0,neutral or dissatisfied +25594,84175,Male,Loyal Customer,48,Business travel,Business,3022,3,4,4,4,2,2,1,3,3,3,3,4,3,4,0,0.0,neutral or dissatisfied +25595,90871,Female,disloyal Customer,25,Business travel,Eco,240,3,3,3,3,4,3,4,4,3,2,4,1,4,4,0,17.0,neutral or dissatisfied +25596,46941,Male,Loyal Customer,53,Personal Travel,Eco,848,1,4,1,2,3,1,3,3,3,4,4,5,5,3,25,2.0,neutral or dissatisfied +25597,55293,Female,Loyal Customer,19,Personal Travel,Eco,1608,5,4,5,1,3,5,3,3,3,4,4,5,5,3,0,0.0,satisfied +25598,18479,Female,Loyal Customer,42,Business travel,Eco,285,4,4,4,4,5,1,5,4,4,4,4,5,4,3,0,0.0,satisfied +25599,9340,Female,Loyal Customer,39,Business travel,Business,401,1,1,1,1,5,5,5,4,4,4,4,3,4,3,0,2.0,satisfied +25600,21349,Female,disloyal Customer,30,Business travel,Eco,761,2,2,2,2,5,2,5,5,4,2,2,1,4,5,0,0.0,neutral or dissatisfied +25601,91831,Male,Loyal Customer,39,Business travel,Business,2735,5,5,5,5,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +25602,1655,Male,disloyal Customer,42,Business travel,Business,435,5,5,5,5,3,5,3,3,3,4,5,3,4,3,0,0.0,satisfied +25603,79598,Male,Loyal Customer,55,Business travel,Business,2401,5,5,5,5,4,5,4,5,5,4,5,5,5,4,41,33.0,satisfied +25604,5508,Female,Loyal Customer,49,Business travel,Business,2306,5,5,5,5,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +25605,120593,Female,Loyal Customer,66,Personal Travel,Eco,980,3,5,3,3,3,4,5,1,1,3,1,3,1,4,0,4.0,neutral or dissatisfied +25606,98692,Female,Loyal Customer,8,Personal Travel,Eco,920,3,4,4,2,4,4,2,4,5,5,5,3,5,4,2,0.0,neutral or dissatisfied +25607,15391,Male,disloyal Customer,22,Business travel,Eco,306,3,0,3,3,2,3,1,2,4,3,2,2,5,2,19,1.0,neutral or dissatisfied +25608,50521,Male,Loyal Customer,16,Personal Travel,Eco,193,3,4,3,3,3,3,3,3,1,5,2,5,2,3,39,21.0,neutral or dissatisfied +25609,81809,Female,disloyal Customer,34,Business travel,Eco,921,3,3,3,2,1,3,1,1,1,4,2,3,2,1,0,0.0,neutral or dissatisfied +25610,3322,Female,Loyal Customer,49,Business travel,Business,3293,5,5,5,5,5,4,4,4,4,4,4,5,4,5,0,13.0,satisfied +25611,57973,Male,Loyal Customer,69,Business travel,Business,420,3,5,5,5,4,3,2,3,3,3,3,1,3,1,0,42.0,neutral or dissatisfied +25612,1885,Male,Loyal Customer,41,Personal Travel,Eco Plus,931,2,5,2,3,5,2,5,5,4,5,5,4,5,5,0,5.0,neutral or dissatisfied +25613,13029,Male,Loyal Customer,52,Personal Travel,Eco,304,3,5,3,3,3,3,3,3,5,2,5,3,4,3,74,66.0,neutral or dissatisfied +25614,38714,Male,Loyal Customer,35,Personal Travel,Eco,2342,4,4,4,3,4,4,5,4,4,2,4,2,4,4,28,16.0,neutral or dissatisfied +25615,118772,Female,Loyal Customer,9,Personal Travel,Eco,370,3,1,3,3,3,3,3,3,4,3,2,1,3,3,0,3.0,neutral or dissatisfied +25616,34810,Female,Loyal Customer,68,Personal Travel,Eco,301,3,5,3,5,2,4,4,2,2,3,1,3,2,4,0,0.0,neutral or dissatisfied +25617,45006,Male,disloyal Customer,22,Business travel,Business,222,0,0,0,3,1,0,1,1,5,4,5,2,2,1,0,19.0,satisfied +25618,75933,Female,disloyal Customer,28,Business travel,Business,872,1,1,1,2,3,1,3,3,4,3,4,4,4,3,0,0.0,neutral or dissatisfied +25619,22017,Male,Loyal Customer,46,Business travel,Eco Plus,551,4,2,4,2,4,4,4,4,3,5,1,4,1,4,0,0.0,satisfied +25620,53000,Male,Loyal Customer,50,Business travel,Eco,1208,5,2,2,2,5,5,5,5,1,1,3,1,1,5,0,0.0,satisfied +25621,111795,Female,disloyal Customer,33,Business travel,Business,349,3,3,3,4,5,3,5,5,3,4,4,5,4,5,0,0.0,neutral or dissatisfied +25622,43282,Male,disloyal Customer,20,Business travel,Business,358,2,2,2,3,3,2,3,3,1,4,3,4,3,3,0,4.0,neutral or dissatisfied +25623,20063,Male,Loyal Customer,66,Personal Travel,Eco,528,1,5,1,4,5,1,5,5,5,3,5,3,1,5,83,75.0,neutral or dissatisfied +25624,3769,Male,Loyal Customer,51,Business travel,Business,3758,1,1,1,1,4,4,4,4,4,4,4,5,4,5,29,20.0,satisfied +25625,39002,Female,Loyal Customer,24,Business travel,Eco,406,1,1,1,1,1,1,4,1,2,2,3,1,3,1,0,0.0,neutral or dissatisfied +25626,97675,Male,Loyal Customer,45,Personal Travel,Eco,272,4,0,4,2,2,4,2,2,4,5,3,1,4,2,0,0.0,satisfied +25627,68226,Female,Loyal Customer,31,Business travel,Business,631,2,3,5,3,2,2,2,2,4,4,3,4,4,2,0,0.0,neutral or dissatisfied +25628,84027,Female,Loyal Customer,24,Business travel,Eco Plus,373,3,2,2,2,3,3,2,3,2,1,4,1,4,3,3,8.0,neutral or dissatisfied +25629,119889,Female,Loyal Customer,18,Personal Travel,Eco,936,2,4,2,3,5,2,5,5,4,4,4,3,4,5,0,0.0,neutral or dissatisfied +25630,3984,Female,Loyal Customer,50,Business travel,Business,2441,1,1,1,1,3,4,5,2,2,2,2,5,2,3,0,0.0,satisfied +25631,65538,Female,Loyal Customer,54,Business travel,Business,237,0,0,0,5,5,4,5,3,3,3,3,3,3,4,0,0.0,satisfied +25632,874,Male,disloyal Customer,20,Business travel,Business,134,0,0,0,3,3,0,3,3,3,3,5,4,5,3,66,67.0,satisfied +25633,126473,Male,disloyal Customer,17,Business travel,Eco,1112,2,2,2,5,5,2,5,5,5,4,4,5,4,5,0,1.0,neutral or dissatisfied +25634,109582,Male,Loyal Customer,70,Personal Travel,Eco,966,1,4,1,3,5,1,2,5,3,5,5,4,5,5,0,0.0,neutral or dissatisfied +25635,60477,Female,Loyal Customer,17,Business travel,Business,3393,4,4,4,4,4,4,4,4,3,5,5,5,5,4,3,1.0,satisfied +25636,92280,Male,Loyal Customer,17,Personal Travel,Eco,2036,1,5,1,2,3,1,2,3,4,5,5,5,4,3,26,3.0,neutral or dissatisfied +25637,95120,Female,Loyal Customer,23,Personal Travel,Eco,319,2,2,3,4,3,3,3,3,4,4,4,4,3,3,11,5.0,neutral or dissatisfied +25638,50243,Male,Loyal Customer,37,Business travel,Eco,109,2,3,3,3,2,2,2,2,3,3,5,2,4,2,0,0.0,satisfied +25639,7015,Female,Loyal Customer,42,Personal Travel,Eco,299,1,4,1,2,5,4,5,1,1,1,1,3,1,5,0,0.0,neutral or dissatisfied +25640,105875,Male,Loyal Customer,46,Business travel,Business,3621,2,5,5,5,5,3,4,2,2,2,2,2,2,2,55,40.0,neutral or dissatisfied +25641,52388,Male,Loyal Customer,23,Personal Travel,Eco,370,3,4,3,3,4,3,3,4,1,5,2,3,3,4,0,2.0,neutral or dissatisfied +25642,74318,Female,disloyal Customer,46,Business travel,Business,1126,2,2,2,3,2,2,2,2,4,3,4,3,5,2,0,0.0,neutral or dissatisfied +25643,58740,Female,disloyal Customer,48,Business travel,Business,1005,4,4,4,3,3,4,1,3,3,5,5,4,4,3,0,0.0,satisfied +25644,65826,Male,Loyal Customer,50,Business travel,Business,1389,2,1,1,1,5,3,3,2,2,2,2,1,2,3,0,0.0,neutral or dissatisfied +25645,66878,Female,Loyal Customer,59,Business travel,Business,1102,3,3,3,3,4,4,5,5,5,5,5,3,5,4,0,0.0,satisfied +25646,63712,Female,disloyal Customer,35,Business travel,Business,1660,1,1,1,1,1,1,1,1,5,4,3,5,5,1,0,4.0,neutral or dissatisfied +25647,62965,Male,disloyal Customer,35,Business travel,Business,909,3,3,3,5,5,3,5,5,4,3,4,3,4,5,0,0.0,neutral or dissatisfied +25648,74806,Female,Loyal Customer,29,Business travel,Eco Plus,1188,3,1,1,1,3,3,3,3,2,3,3,1,4,3,0,0.0,neutral or dissatisfied +25649,4564,Female,Loyal Customer,57,Personal Travel,Eco,561,1,2,1,3,4,3,3,4,4,1,1,1,4,3,0,0.0,neutral or dissatisfied +25650,70909,Female,Loyal Customer,66,Personal Travel,Eco,1721,1,4,1,3,3,3,1,3,3,1,3,3,3,2,53,55.0,neutral or dissatisfied +25651,80230,Female,Loyal Customer,46,Business travel,Business,2153,2,2,2,2,5,5,5,4,3,5,5,5,3,5,2,0.0,satisfied +25652,96393,Male,disloyal Customer,25,Business travel,Eco,1342,2,2,2,2,5,2,5,5,1,2,2,1,2,5,22,12.0,neutral or dissatisfied +25653,19882,Female,Loyal Customer,44,Business travel,Business,315,5,5,5,5,1,5,4,5,5,5,5,2,5,5,0,0.0,satisfied +25654,15495,Female,Loyal Customer,12,Personal Travel,Eco,164,2,4,2,4,1,2,1,1,2,1,3,2,4,1,0,0.0,neutral or dissatisfied +25655,48077,Male,disloyal Customer,41,Business travel,Business,173,4,4,4,4,5,4,5,5,4,5,3,4,4,5,61,62.0,neutral or dissatisfied +25656,45108,Female,Loyal Customer,40,Business travel,Business,3805,0,5,0,4,5,3,2,2,2,2,2,2,2,5,0,0.0,satisfied +25657,72613,Male,Loyal Customer,27,Personal Travel,Eco,985,3,5,3,3,4,3,4,4,5,3,4,3,5,4,0,0.0,neutral or dissatisfied +25658,4378,Female,Loyal Customer,40,Business travel,Business,528,3,1,1,1,5,3,2,3,3,3,3,2,3,3,39,35.0,neutral or dissatisfied +25659,71904,Male,Loyal Customer,19,Personal Travel,Eco,1846,1,5,1,2,2,1,2,2,4,1,4,1,4,2,0,0.0,neutral or dissatisfied +25660,120182,Male,Loyal Customer,58,Business travel,Business,2639,4,4,4,4,2,5,4,5,5,5,5,5,5,4,0,0.0,satisfied +25661,129176,Male,Loyal Customer,15,Personal Travel,Eco,679,1,3,1,2,5,1,5,5,1,4,4,4,2,5,0,0.0,neutral or dissatisfied +25662,87025,Male,Loyal Customer,10,Personal Travel,Business,645,3,3,4,2,2,4,2,2,1,1,3,5,4,2,111,100.0,neutral or dissatisfied +25663,67767,Female,Loyal Customer,25,Business travel,Business,1188,1,1,1,1,5,5,5,5,3,3,5,4,4,5,3,0.0,satisfied +25664,93506,Female,Loyal Customer,58,Personal Travel,Eco,1107,2,3,3,3,2,4,4,3,3,3,3,3,3,4,88,71.0,neutral or dissatisfied +25665,45532,Female,Loyal Customer,29,Business travel,Business,566,3,3,3,3,4,4,4,4,1,3,5,5,4,4,0,0.0,satisfied +25666,94725,Male,disloyal Customer,27,Business travel,Eco,458,4,2,4,2,1,4,1,1,1,1,2,2,2,1,35,18.0,neutral or dissatisfied +25667,60453,Male,disloyal Customer,27,Business travel,Business,862,4,4,4,5,1,4,1,1,5,3,4,4,4,1,0,0.0,neutral or dissatisfied +25668,123213,Male,Loyal Customer,45,Personal Travel,Eco,468,3,5,4,5,4,4,4,4,3,4,5,4,5,4,6,13.0,neutral or dissatisfied +25669,39629,Female,Loyal Customer,59,Personal Travel,Eco,679,2,4,2,1,3,2,5,4,4,2,5,5,4,3,54,43.0,neutral or dissatisfied +25670,111498,Male,Loyal Customer,34,Business travel,Business,2844,2,2,3,2,4,4,5,4,4,4,4,3,4,3,120,128.0,satisfied +25671,40558,Male,disloyal Customer,22,Business travel,Eco,517,4,3,4,4,2,4,2,2,5,2,4,5,2,2,0,0.0,satisfied +25672,13641,Male,Loyal Customer,58,Personal Travel,Eco,835,4,4,4,4,5,4,5,5,4,5,4,4,4,5,48,51.0,neutral or dissatisfied +25673,63665,Male,Loyal Customer,65,Business travel,Business,3086,5,5,2,5,4,3,5,4,4,4,4,3,4,4,40,0.0,satisfied +25674,85400,Female,disloyal Customer,23,Business travel,Eco,214,5,5,5,4,3,5,3,3,3,2,4,4,5,3,0,0.0,satisfied +25675,106911,Female,Loyal Customer,27,Business travel,Business,2543,5,5,5,5,4,4,4,4,5,4,4,4,4,4,0,0.0,satisfied +25676,19071,Female,Loyal Customer,37,Business travel,Eco,569,1,2,2,2,1,1,1,1,4,2,1,3,2,1,0,0.0,neutral or dissatisfied +25677,39593,Female,disloyal Customer,41,Business travel,Business,554,4,4,4,5,2,4,2,2,1,3,3,4,4,2,0,0.0,neutral or dissatisfied +25678,85882,Female,disloyal Customer,28,Business travel,Eco,2172,4,4,4,3,1,4,1,1,1,5,4,3,3,1,0,9.0,neutral or dissatisfied +25679,112373,Female,Loyal Customer,43,Business travel,Business,3899,2,2,2,2,2,4,5,4,4,4,4,5,4,4,9,3.0,satisfied +25680,117212,Male,Loyal Customer,24,Personal Travel,Eco,369,2,1,2,3,1,2,1,1,2,2,3,2,4,1,22,14.0,neutral or dissatisfied +25681,30764,Female,Loyal Customer,55,Personal Travel,Eco,683,2,4,2,3,4,5,5,3,3,2,3,5,3,4,31,34.0,neutral or dissatisfied +25682,106075,Female,Loyal Customer,53,Business travel,Business,436,5,5,5,5,4,4,5,5,5,5,5,4,5,4,35,30.0,satisfied +25683,47625,Female,Loyal Customer,45,Business travel,Business,1211,5,5,5,5,3,5,4,3,3,4,3,3,3,5,0,0.0,satisfied +25684,101453,Female,Loyal Customer,45,Business travel,Business,2138,3,3,3,3,2,5,5,5,5,5,5,3,5,4,10,4.0,satisfied +25685,78838,Female,Loyal Customer,35,Personal Travel,Eco,432,1,2,1,2,3,1,3,3,4,3,1,3,2,3,0,0.0,neutral or dissatisfied +25686,20159,Male,Loyal Customer,61,Business travel,Business,403,2,4,4,4,2,2,2,1,4,3,4,2,3,2,136,155.0,neutral or dissatisfied +25687,76907,Male,Loyal Customer,47,Personal Travel,Eco,630,1,4,1,3,5,1,5,5,2,4,3,3,4,5,0,0.0,neutral or dissatisfied +25688,95269,Female,Loyal Customer,38,Personal Travel,Eco,441,1,1,3,1,3,3,3,3,1,5,2,2,2,3,1,0.0,neutral or dissatisfied +25689,123753,Female,Loyal Customer,51,Business travel,Business,544,1,1,1,1,5,4,4,4,4,4,4,5,4,4,0,0.0,satisfied +25690,7233,Male,disloyal Customer,55,Business travel,Eco,135,3,0,2,1,1,2,1,1,5,1,3,3,3,1,2,0.0,neutral or dissatisfied +25691,48791,Female,disloyal Customer,37,Business travel,Business,421,3,3,3,4,4,3,5,4,4,3,3,1,4,4,3,17.0,neutral or dissatisfied +25692,27624,Female,disloyal Customer,29,Business travel,Eco Plus,697,1,1,1,3,3,1,3,3,3,3,4,1,4,3,0,9.0,neutral or dissatisfied +25693,46999,Female,Loyal Customer,47,Business travel,Eco Plus,737,1,4,4,4,3,4,4,1,1,1,1,1,1,3,0,0.0,neutral or dissatisfied +25694,30194,Female,Loyal Customer,32,Business travel,Eco Plus,95,0,0,0,1,1,0,1,1,5,4,2,5,3,1,0,0.0,satisfied +25695,8650,Male,disloyal Customer,27,Business travel,Eco,181,2,1,1,4,4,1,3,4,2,1,4,2,4,4,0,0.0,neutral or dissatisfied +25696,82009,Female,Loyal Customer,38,Business travel,Eco,1132,4,1,1,1,4,4,4,4,5,4,4,2,5,4,0,0.0,satisfied +25697,48833,Female,Loyal Customer,70,Personal Travel,Business,266,1,4,0,3,0,1,1,3,2,4,3,1,1,1,153,143.0,neutral or dissatisfied +25698,86988,Male,Loyal Customer,56,Personal Travel,Eco,907,2,1,1,3,3,1,3,3,4,1,4,3,4,3,0,0.0,neutral or dissatisfied +25699,127705,Female,Loyal Customer,43,Business travel,Business,255,2,2,2,2,3,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +25700,30151,Female,Loyal Customer,49,Personal Travel,Eco,160,3,4,3,5,5,5,5,4,4,3,4,5,4,4,0,0.0,neutral or dissatisfied +25701,80600,Male,Loyal Customer,54,Personal Travel,Eco Plus,1747,1,0,1,3,4,1,4,4,1,5,2,4,4,4,0,0.0,neutral or dissatisfied +25702,117513,Male,Loyal Customer,29,Business travel,Eco Plus,507,2,3,3,3,2,2,2,2,2,2,4,1,4,2,0,0.0,neutral or dissatisfied +25703,39919,Female,disloyal Customer,25,Business travel,Eco,1086,3,3,3,4,1,3,1,1,2,1,2,4,5,1,106,106.0,neutral or dissatisfied +25704,59264,Male,Loyal Customer,49,Business travel,Business,4963,1,1,1,1,4,4,4,4,4,3,4,4,4,4,23,0.0,satisfied +25705,5555,Male,Loyal Customer,49,Business travel,Business,501,3,3,3,3,5,4,5,5,5,5,5,5,5,4,18,45.0,satisfied +25706,42648,Male,Loyal Customer,17,Personal Travel,Eco,546,1,3,3,1,4,3,4,4,3,1,3,3,5,4,0,0.0,neutral or dissatisfied +25707,40617,Male,Loyal Customer,33,Personal Travel,Eco,517,4,5,4,5,1,4,1,1,5,5,5,5,5,1,0,0.0,satisfied +25708,117213,Male,Loyal Customer,55,Personal Travel,Eco,325,3,5,3,4,2,3,2,2,2,4,5,5,1,2,0,0.0,neutral or dissatisfied +25709,34692,Male,Loyal Customer,37,Business travel,Business,301,0,1,1,4,4,5,2,2,2,2,2,3,2,1,0,0.0,satisfied +25710,127125,Male,Loyal Customer,22,Personal Travel,Eco,647,3,1,3,4,3,3,5,3,3,1,3,2,4,3,6,6.0,neutral or dissatisfied +25711,108128,Male,Loyal Customer,54,Business travel,Business,1166,2,2,2,2,3,5,5,4,4,4,4,3,4,3,19,12.0,satisfied +25712,9507,Male,Loyal Customer,9,Personal Travel,Eco,224,2,3,2,1,3,2,3,3,5,2,3,2,2,3,13,32.0,neutral or dissatisfied +25713,52173,Female,Loyal Customer,55,Business travel,Business,3332,2,2,2,2,3,3,3,4,4,4,4,2,4,1,0,3.0,satisfied +25714,88503,Male,Loyal Customer,31,Business travel,Eco,515,3,4,4,4,3,4,3,3,5,3,2,5,1,3,1,0.0,satisfied +25715,43745,Female,disloyal Customer,23,Business travel,Eco,481,1,1,1,3,1,1,1,1,4,4,3,2,3,1,2,29.0,neutral or dissatisfied +25716,35535,Female,Loyal Customer,41,Personal Travel,Eco,944,3,5,2,2,5,2,5,5,4,1,5,3,3,5,0,14.0,neutral or dissatisfied +25717,39978,Male,Loyal Customer,31,Business travel,Eco,1262,4,5,5,5,4,4,4,4,2,2,4,4,3,4,0,0.0,neutral or dissatisfied +25718,100014,Male,Loyal Customer,58,Business travel,Business,277,3,3,3,3,4,4,4,5,5,5,5,3,5,3,0,8.0,satisfied +25719,5399,Female,Loyal Customer,61,Personal Travel,Eco,785,2,4,1,3,3,5,4,5,5,1,5,3,5,4,0,35.0,neutral or dissatisfied +25720,67983,Male,disloyal Customer,28,Business travel,Eco Plus,1235,3,3,3,3,2,3,2,2,2,5,2,3,2,2,0,0.0,neutral or dissatisfied +25721,23890,Male,Loyal Customer,42,Business travel,Eco,579,4,5,5,5,3,4,3,3,4,1,4,5,4,3,0,0.0,satisfied +25722,102229,Male,Loyal Customer,71,Business travel,Business,414,2,3,3,3,3,2,3,2,2,2,2,3,2,3,12,23.0,neutral or dissatisfied +25723,13024,Male,Loyal Customer,34,Personal Travel,Eco,438,3,5,3,3,2,3,2,2,4,4,5,5,4,2,32,34.0,neutral or dissatisfied +25724,15456,Male,Loyal Customer,68,Business travel,Business,164,3,3,2,3,4,2,3,5,5,5,4,3,5,1,0,0.0,satisfied +25725,75490,Male,Loyal Customer,47,Business travel,Eco Plus,2218,2,5,3,5,3,2,3,3,4,1,2,4,3,3,0,0.0,neutral or dissatisfied +25726,92541,Male,Loyal Customer,33,Personal Travel,Eco,1947,4,4,4,3,5,4,5,5,4,3,3,5,4,5,0,0.0,neutral or dissatisfied +25727,18039,Female,disloyal Customer,27,Business travel,Eco,488,4,3,4,2,5,4,5,5,4,2,4,4,3,5,12,4.0,satisfied +25728,108033,Male,Loyal Customer,39,Business travel,Business,2043,0,0,0,5,5,4,4,3,3,3,3,3,3,5,1,0.0,satisfied +25729,118279,Female,Loyal Customer,54,Business travel,Business,602,4,4,4,4,3,5,5,2,2,2,2,4,2,5,53,40.0,satisfied +25730,35285,Female,disloyal Customer,23,Business travel,Eco,1056,3,3,3,2,3,3,3,3,2,3,5,4,1,3,0,22.0,neutral or dissatisfied +25731,84037,Female,disloyal Customer,22,Business travel,Eco,932,4,4,4,3,2,4,2,2,5,5,4,3,5,2,0,0.0,satisfied +25732,88595,Male,Loyal Customer,30,Personal Travel,Eco,250,2,4,2,1,1,2,1,1,5,4,5,3,4,1,0,9.0,neutral or dissatisfied +25733,68724,Male,disloyal Customer,18,Business travel,Eco Plus,175,1,2,1,3,5,1,5,5,3,1,3,3,2,5,0,0.0,neutral or dissatisfied +25734,55263,Male,Loyal Customer,53,Business travel,Business,2007,3,3,3,3,3,3,5,5,5,5,5,4,5,5,25,20.0,satisfied +25735,116485,Female,Loyal Customer,8,Personal Travel,Eco,296,4,5,5,2,4,5,2,4,3,2,5,3,5,4,16,14.0,neutral or dissatisfied +25736,49883,Female,disloyal Customer,36,Business travel,Eco,326,3,4,3,1,1,3,1,1,2,2,1,1,5,1,0,0.0,neutral or dissatisfied +25737,116400,Male,Loyal Customer,11,Personal Travel,Eco,342,5,4,5,3,3,5,3,3,3,5,2,3,1,3,0,0.0,satisfied +25738,29854,Male,disloyal Customer,39,Business travel,Eco,261,4,0,5,1,5,5,3,5,2,2,2,1,3,5,0,0.0,satisfied +25739,45665,Male,Loyal Customer,53,Personal Travel,Eco Plus,230,3,5,3,4,2,3,2,2,5,2,4,3,5,2,0,9.0,neutral or dissatisfied +25740,17273,Female,Loyal Customer,69,Personal Travel,Eco,1092,4,3,3,3,3,3,3,4,4,3,4,3,4,1,0,0.0,satisfied +25741,75583,Female,Loyal Customer,53,Business travel,Business,1585,3,3,3,3,2,4,4,4,4,5,4,5,4,5,8,2.0,satisfied +25742,99252,Male,Loyal Customer,58,Personal Travel,Eco,541,2,3,2,3,5,2,5,5,2,4,4,2,3,5,0,0.0,neutral or dissatisfied +25743,68914,Male,Loyal Customer,54,Personal Travel,Eco,936,2,5,2,4,5,2,5,5,5,3,5,3,5,5,0,0.0,neutral or dissatisfied +25744,34856,Female,Loyal Customer,20,Personal Travel,Eco,1826,3,4,3,3,2,3,2,2,4,3,3,1,3,2,0,2.0,neutral or dissatisfied +25745,38518,Male,Loyal Customer,52,Business travel,Business,2586,1,1,1,1,5,5,1,5,5,5,5,1,5,2,12,0.0,satisfied +25746,34269,Male,Loyal Customer,41,Business travel,Business,280,4,4,4,4,3,4,2,3,3,4,3,4,3,1,0,0.0,satisfied +25747,111797,Female,Loyal Customer,50,Business travel,Business,2440,0,0,0,1,2,5,5,5,5,3,3,4,5,4,0,0.0,satisfied +25748,13507,Male,Loyal Customer,24,Business travel,Business,214,3,3,3,3,5,5,4,5,4,1,3,5,2,5,4,23.0,satisfied +25749,75012,Male,Loyal Customer,57,Business travel,Business,2453,5,5,5,5,3,5,4,4,4,4,4,3,4,3,0,0.0,satisfied +25750,28187,Female,Loyal Customer,27,Personal Travel,Eco,834,1,4,1,3,2,1,2,2,4,4,5,5,4,2,0,0.0,neutral or dissatisfied +25751,2680,Female,Loyal Customer,68,Personal Travel,Eco,622,3,4,3,4,3,4,4,1,1,3,1,4,1,3,0,0.0,neutral or dissatisfied +25752,57639,Male,Loyal Customer,57,Business travel,Business,200,0,4,0,1,3,4,5,1,1,1,1,5,1,4,0,0.0,satisfied +25753,3171,Female,Loyal Customer,62,Business travel,Business,2060,5,2,5,5,4,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +25754,69041,Male,Loyal Customer,25,Business travel,Business,1389,1,1,1,1,5,5,5,5,4,3,5,3,4,5,0,0.0,satisfied +25755,4519,Female,Loyal Customer,35,Personal Travel,Eco Plus,551,2,3,2,4,1,2,1,1,1,2,4,1,4,1,31,28.0,neutral or dissatisfied +25756,95117,Female,Loyal Customer,32,Personal Travel,Eco,562,4,4,4,3,4,4,4,4,5,2,4,5,4,4,3,4.0,neutral or dissatisfied +25757,38373,Female,Loyal Customer,58,Personal Travel,Eco,1133,1,3,1,4,1,1,1,3,1,3,3,1,1,1,151,162.0,neutral or dissatisfied +25758,35667,Male,Loyal Customer,46,Business travel,Eco,2465,4,5,5,5,4,4,4,4,5,4,4,4,1,4,0,11.0,satisfied +25759,64076,Female,Loyal Customer,26,Personal Travel,Eco,921,2,4,2,2,4,2,5,4,5,5,4,3,4,4,0,0.0,neutral or dissatisfied +25760,92023,Male,Loyal Customer,38,Business travel,Business,1532,3,3,3,3,3,5,4,4,4,4,4,3,4,5,0,0.0,satisfied +25761,92866,Female,Loyal Customer,11,Personal Travel,Eco,2519,3,4,3,3,3,3,4,3,3,4,5,4,4,3,0,0.0,neutral or dissatisfied +25762,15092,Female,disloyal Customer,20,Business travel,Eco,322,3,3,3,4,5,3,5,5,3,4,3,1,4,5,9,11.0,neutral or dissatisfied +25763,127717,Male,Loyal Customer,56,Business travel,Business,2962,2,2,4,2,4,4,4,5,5,5,5,5,5,3,0,5.0,satisfied +25764,58314,Female,Loyal Customer,44,Business travel,Eco,1739,4,4,4,4,2,2,4,4,4,4,4,1,4,3,4,0.0,neutral or dissatisfied +25765,126496,Female,Loyal Customer,21,Personal Travel,Eco,1788,1,5,1,1,1,1,1,1,5,4,3,3,4,1,0,6.0,neutral or dissatisfied +25766,19692,Male,Loyal Customer,42,Business travel,Business,475,4,4,4,4,1,3,5,4,4,4,4,4,4,2,44,33.0,satisfied +25767,109744,Male,Loyal Customer,44,Personal Travel,Eco,468,2,3,2,3,4,2,1,4,3,1,3,2,2,4,7,15.0,neutral or dissatisfied +25768,4013,Female,disloyal Customer,23,Business travel,Eco,479,2,1,2,3,1,2,2,1,2,1,4,4,3,1,3,0.0,neutral or dissatisfied +25769,24319,Male,Loyal Customer,33,Business travel,Business,1083,2,1,2,2,4,4,4,4,1,2,3,4,2,4,73,58.0,satisfied +25770,85942,Female,Loyal Customer,49,Business travel,Business,447,2,2,2,2,4,5,5,4,4,4,4,5,4,3,0,1.0,satisfied +25771,15343,Male,disloyal Customer,44,Business travel,Business,331,2,2,2,2,2,5,5,5,2,4,5,5,5,5,295,288.0,neutral or dissatisfied +25772,121451,Male,Loyal Customer,31,Business travel,Eco,331,3,2,3,2,3,3,3,3,1,3,3,1,4,3,1,0.0,neutral or dissatisfied +25773,27891,Male,Loyal Customer,57,Personal Travel,Eco,2329,2,4,2,4,2,4,4,3,5,4,3,4,3,4,0,12.0,neutral or dissatisfied +25774,94289,Male,Loyal Customer,59,Business travel,Business,1978,2,2,3,2,2,5,4,4,4,4,4,5,4,5,11,16.0,satisfied +25775,28063,Male,Loyal Customer,23,Business travel,Business,2562,3,3,3,3,5,5,5,5,2,4,1,5,4,5,0,0.0,satisfied +25776,38767,Male,disloyal Customer,33,Business travel,Eco,387,1,4,0,2,4,0,4,4,1,4,1,2,4,4,0,0.0,neutral or dissatisfied +25777,102551,Female,Loyal Customer,48,Personal Travel,Eco,197,2,5,2,4,2,2,3,3,3,2,3,1,3,5,6,12.0,neutral or dissatisfied +25778,35916,Female,Loyal Customer,13,Personal Travel,Eco,2248,1,4,1,2,4,1,4,4,4,4,4,5,5,4,0,0.0,neutral or dissatisfied +25779,97663,Female,disloyal Customer,32,Business travel,Business,491,2,2,2,1,3,2,1,3,4,2,4,5,4,3,20,19.0,neutral or dissatisfied +25780,119903,Female,disloyal Customer,22,Business travel,Business,912,4,0,4,2,4,4,4,4,3,3,4,5,2,4,0,0.0,satisfied +25781,33728,Female,Loyal Customer,20,Personal Travel,Eco,805,2,5,3,4,1,3,2,1,5,3,5,1,1,1,0,0.0,neutral or dissatisfied +25782,105871,Male,Loyal Customer,25,Personal Travel,Eco Plus,919,3,3,3,2,5,3,5,5,2,5,3,2,2,5,21,11.0,neutral or dissatisfied +25783,62633,Female,Loyal Customer,56,Personal Travel,Eco,1744,2,3,2,3,2,4,4,5,5,2,5,3,5,1,0,0.0,neutral or dissatisfied +25784,14256,Female,Loyal Customer,47,Business travel,Business,395,3,5,5,5,4,4,3,3,3,3,3,3,3,1,0,0.0,neutral or dissatisfied +25785,68277,Female,disloyal Customer,39,Business travel,Business,631,4,4,4,4,2,4,2,2,5,3,5,4,5,2,0,0.0,neutral or dissatisfied +25786,45305,Female,disloyal Customer,50,Business travel,Eco,150,3,0,3,3,3,3,3,3,4,4,4,3,2,3,0,0.0,neutral or dissatisfied +25787,586,Female,Loyal Customer,50,Business travel,Business,158,0,4,0,4,4,4,5,1,1,1,1,3,1,4,0,0.0,satisfied +25788,89450,Male,Loyal Customer,23,Personal Travel,Eco,134,3,5,3,5,3,3,3,3,5,2,5,4,4,3,0,0.0,neutral or dissatisfied +25789,65575,Male,Loyal Customer,49,Business travel,Eco,175,1,2,2,2,1,1,1,1,4,3,4,2,3,1,5,9.0,neutral or dissatisfied +25790,78411,Male,Loyal Customer,65,Business travel,Business,1969,3,4,4,4,2,4,4,3,3,3,3,2,3,2,0,0.0,neutral or dissatisfied +25791,103370,Male,Loyal Customer,9,Personal Travel,Eco,342,1,5,1,3,2,1,2,2,4,4,5,3,5,2,78,77.0,neutral or dissatisfied +25792,78449,Male,Loyal Customer,60,Business travel,Business,3292,2,2,1,2,4,5,5,5,5,5,5,4,5,4,0,0.0,satisfied +25793,51388,Female,Loyal Customer,66,Personal Travel,Eco Plus,109,2,5,2,3,2,5,5,2,2,2,4,4,2,5,2,9.0,neutral or dissatisfied +25794,75767,Female,Loyal Customer,8,Personal Travel,Eco,868,2,3,2,2,2,2,2,2,3,2,4,4,3,2,114,104.0,neutral or dissatisfied +25795,72448,Female,Loyal Customer,51,Business travel,Business,2911,5,5,5,5,4,4,4,5,5,5,5,4,5,3,0,0.0,satisfied +25796,49190,Female,Loyal Customer,29,Business travel,Business,3840,3,3,3,3,5,5,5,5,3,3,4,3,1,5,0,0.0,satisfied +25797,106161,Male,Loyal Customer,61,Personal Travel,Eco,436,2,2,1,2,4,1,4,4,3,2,2,3,2,4,91,102.0,neutral or dissatisfied +25798,47678,Female,Loyal Customer,34,Personal Travel,Eco,1504,2,3,2,1,2,2,2,2,1,4,5,5,5,2,0,0.0,neutral or dissatisfied +25799,13713,Male,disloyal Customer,39,Business travel,Eco,384,1,0,1,2,4,1,4,4,5,1,2,4,4,4,0,0.0,neutral or dissatisfied +25800,79937,Female,Loyal Customer,40,Business travel,Business,1989,2,2,2,2,2,4,4,5,5,5,5,4,5,5,0,0.0,satisfied +25801,31951,Male,Loyal Customer,60,Business travel,Business,3387,0,5,0,4,4,4,5,3,3,4,4,3,3,4,0,0.0,satisfied +25802,88962,Male,Loyal Customer,68,Business travel,Business,1840,5,5,4,5,2,4,5,5,5,5,5,5,5,4,0,5.0,satisfied +25803,38281,Female,Loyal Customer,37,Personal Travel,Eco,1050,4,4,4,5,3,4,3,3,5,2,4,5,5,3,0,0.0,neutral or dissatisfied +25804,79093,Female,Loyal Customer,43,Personal Travel,Eco,226,1,5,0,2,5,5,5,5,5,0,5,3,5,5,1,0.0,neutral or dissatisfied +25805,57397,Female,Loyal Customer,47,Business travel,Business,472,1,1,1,1,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +25806,75494,Female,disloyal Customer,55,Business travel,Business,2342,3,3,3,1,1,3,3,1,3,3,3,4,4,1,0,0.0,neutral or dissatisfied +25807,87254,Male,disloyal Customer,16,Business travel,Eco,577,0,0,0,1,1,0,1,1,4,3,4,3,4,1,0,0.0,satisfied +25808,6736,Male,Loyal Customer,22,Personal Travel,Eco,334,4,4,4,1,1,4,1,1,5,5,4,3,4,1,11,7.0,neutral or dissatisfied +25809,85799,Female,disloyal Customer,24,Business travel,Eco,126,5,3,5,1,2,5,2,2,4,5,2,4,3,2,3,1.0,satisfied +25810,90505,Female,Loyal Customer,25,Business travel,Business,3714,1,1,1,1,3,3,3,3,3,5,4,5,5,3,30,38.0,satisfied +25811,27683,Male,Loyal Customer,34,Business travel,Business,1216,1,2,2,2,5,2,2,1,1,1,1,4,1,3,0,7.0,neutral or dissatisfied +25812,107602,Male,Loyal Customer,41,Business travel,Eco,423,2,5,5,5,2,2,2,2,3,2,3,3,3,2,14,11.0,neutral or dissatisfied +25813,31976,Female,disloyal Customer,29,Business travel,Business,101,4,4,4,4,4,4,4,4,2,3,3,2,4,4,0,0.0,neutral or dissatisfied +25814,95189,Female,Loyal Customer,39,Personal Travel,Eco,239,4,5,4,5,5,4,5,5,3,4,5,5,5,5,53,43.0,neutral or dissatisfied +25815,127285,Female,Loyal Customer,16,Personal Travel,Eco,1107,2,2,2,4,2,2,2,2,4,5,3,2,4,2,0,15.0,neutral or dissatisfied +25816,45197,Female,Loyal Customer,27,Personal Travel,Eco,606,1,5,1,4,5,1,5,5,3,5,5,3,4,5,0,45.0,neutral or dissatisfied +25817,69417,Female,disloyal Customer,40,Business travel,Business,696,3,3,3,4,5,3,5,5,1,1,3,3,3,5,0,13.0,neutral or dissatisfied +25818,106314,Male,Loyal Customer,62,Personal Travel,Eco,998,2,1,2,4,1,2,1,1,2,3,4,1,3,1,0,3.0,neutral or dissatisfied +25819,58570,Female,Loyal Customer,47,Personal Travel,Business,403,1,5,1,2,4,5,4,3,3,1,4,5,3,4,12,1.0,neutral or dissatisfied +25820,17777,Male,Loyal Customer,31,Business travel,Business,1042,2,3,3,3,2,2,2,2,4,1,3,3,3,2,93,78.0,neutral or dissatisfied +25821,391,Female,Loyal Customer,52,Business travel,Business,1954,3,3,3,3,3,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +25822,117766,Female,Loyal Customer,8,Personal Travel,Eco,1670,1,4,1,4,3,1,3,3,4,5,4,3,4,3,0,0.0,neutral or dissatisfied +25823,97181,Female,Loyal Customer,32,Personal Travel,Eco,1357,5,5,5,1,2,5,2,2,5,2,5,5,5,2,0,0.0,satisfied +25824,12756,Female,Loyal Customer,11,Personal Travel,Eco,689,3,4,3,4,3,3,3,3,4,1,3,3,4,3,0,0.0,neutral or dissatisfied +25825,68149,Female,Loyal Customer,41,Business travel,Business,603,5,1,5,5,5,5,5,5,5,5,5,3,5,4,0,0.0,satisfied +25826,6080,Female,Loyal Customer,41,Business travel,Business,2473,4,4,4,4,5,5,4,4,4,5,4,3,4,5,0,4.0,satisfied +25827,114871,Male,disloyal Customer,36,Business travel,Business,337,4,4,4,3,2,4,4,2,5,5,4,4,5,2,34,27.0,neutral or dissatisfied +25828,34676,Female,Loyal Customer,39,Business travel,Business,2848,0,0,0,2,5,2,5,3,3,1,1,5,3,1,6,27.0,satisfied +25829,120124,Male,Loyal Customer,51,Business travel,Business,1576,4,4,4,4,3,5,5,4,4,4,4,3,4,4,5,37.0,satisfied +25830,120792,Female,Loyal Customer,29,Personal Travel,Eco,678,2,4,1,5,5,1,5,5,5,2,5,4,5,5,0,0.0,neutral or dissatisfied +25831,124022,Male,Loyal Customer,25,Personal Travel,Eco,184,1,3,1,4,3,1,3,3,1,3,3,4,4,3,0,0.0,neutral or dissatisfied +25832,93542,Female,Loyal Customer,43,Business travel,Business,585,4,4,4,4,2,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +25833,90329,Male,Loyal Customer,59,Business travel,Business,3097,2,2,2,2,3,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +25834,107603,Male,Loyal Customer,59,Business travel,Business,2334,3,3,3,3,5,5,5,3,3,4,3,4,3,4,69,72.0,satisfied +25835,38689,Female,Loyal Customer,57,Personal Travel,Eco Plus,2704,5,4,5,4,5,3,4,3,3,5,3,4,3,4,0,0.0,satisfied +25836,77946,Male,disloyal Customer,44,Business travel,Business,214,4,4,4,3,4,4,4,4,3,5,5,4,5,4,0,0.0,satisfied +25837,6872,Female,Loyal Customer,21,Personal Travel,Eco,622,3,1,4,1,5,4,5,5,1,1,1,1,1,5,0,0.0,neutral or dissatisfied +25838,124171,Male,Loyal Customer,16,Personal Travel,Eco,2133,4,5,4,3,3,4,3,3,3,2,3,3,4,3,0,0.0,neutral or dissatisfied +25839,82053,Female,Loyal Customer,25,Business travel,Eco Plus,1535,1,3,3,3,1,1,1,1,1,5,3,3,4,1,0,0.0,neutral or dissatisfied +25840,74009,Male,disloyal Customer,20,Business travel,Eco,938,3,3,3,3,2,3,2,2,4,5,3,3,3,2,4,11.0,neutral or dissatisfied +25841,96438,Male,Loyal Customer,27,Business travel,Business,2157,2,2,3,2,5,5,5,5,5,4,5,4,4,5,0,0.0,satisfied +25842,79314,Male,Loyal Customer,41,Personal Travel,Eco,2248,2,5,2,2,1,2,5,1,3,5,4,1,4,1,0,13.0,neutral or dissatisfied +25843,96286,Male,Loyal Customer,35,Personal Travel,Eco,786,3,3,3,3,2,3,2,2,3,5,4,3,3,2,0,0.0,neutral or dissatisfied +25844,96966,Male,disloyal Customer,27,Business travel,Business,883,5,5,5,2,4,5,5,4,3,4,4,5,5,4,32,32.0,satisfied +25845,127552,Female,Loyal Customer,56,Personal Travel,Eco,1009,2,5,2,1,2,3,2,3,3,2,3,2,3,1,0,13.0,neutral or dissatisfied +25846,125439,Female,Loyal Customer,14,Personal Travel,Eco Plus,735,4,5,4,3,1,4,1,1,4,2,4,3,5,1,10,17.0,neutral or dissatisfied +25847,99578,Male,Loyal Customer,35,Business travel,Business,802,3,3,3,3,2,5,3,4,4,4,4,2,4,4,1,74.0,satisfied +25848,59466,Female,Loyal Customer,51,Business travel,Business,3541,3,3,3,3,2,5,5,4,4,4,4,3,4,3,0,0.0,satisfied +25849,2947,Male,disloyal Customer,22,Business travel,Eco,835,4,4,4,2,3,4,3,3,3,3,5,3,5,3,0,0.0,satisfied +25850,65753,Female,Loyal Customer,59,Personal Travel,Eco,936,2,3,2,1,3,3,2,2,2,2,2,1,2,4,0,0.0,neutral or dissatisfied +25851,47076,Male,Loyal Customer,68,Personal Travel,Eco,438,3,5,5,3,4,5,4,4,4,2,4,3,5,4,0,0.0,neutral or dissatisfied +25852,85125,Male,disloyal Customer,25,Business travel,Business,731,2,4,1,2,4,1,4,4,3,4,4,5,4,4,14,5.0,neutral or dissatisfied +25853,117714,Male,Loyal Customer,19,Personal Travel,Eco,1009,3,4,3,3,4,3,4,4,5,2,4,3,4,4,3,28.0,neutral or dissatisfied +25854,112317,Male,Loyal Customer,64,Business travel,Business,1540,5,5,5,5,2,4,5,4,4,4,4,4,4,4,0,0.0,satisfied +25855,32604,Male,disloyal Customer,21,Business travel,Eco,163,2,5,2,4,5,2,5,5,1,3,3,1,5,5,0,0.0,neutral or dissatisfied +25856,64902,Male,Loyal Customer,44,Business travel,Business,2331,1,4,4,4,3,3,3,4,4,4,1,3,4,1,0,14.0,neutral or dissatisfied +25857,97941,Female,Loyal Customer,52,Business travel,Business,3484,4,4,4,4,5,4,5,4,4,4,4,5,4,5,0,0.0,satisfied +25858,17299,Female,Loyal Customer,36,Business travel,Business,403,5,5,5,5,3,4,3,4,4,4,4,5,4,1,0,0.0,satisfied +25859,119297,Female,Loyal Customer,47,Business travel,Business,214,5,5,5,5,5,4,5,5,5,5,4,4,5,4,0,0.0,satisfied +25860,113747,Male,Loyal Customer,58,Personal Travel,Eco,197,3,5,3,4,3,3,3,3,1,1,1,5,5,3,0,0.0,neutral or dissatisfied +25861,105460,Female,Loyal Customer,44,Business travel,Eco Plus,598,1,4,4,4,4,4,3,1,1,1,1,2,1,2,45,48.0,neutral or dissatisfied +25862,126712,Female,Loyal Customer,60,Business travel,Business,2370,1,1,1,1,3,3,5,4,4,4,4,5,4,4,0,12.0,satisfied +25863,128427,Male,Loyal Customer,48,Business travel,Business,3446,2,4,4,4,5,4,4,2,2,2,2,2,2,1,0,0.0,neutral or dissatisfied +25864,2912,Female,disloyal Customer,47,Business travel,Eco Plus,491,3,3,3,3,2,3,5,2,1,5,3,4,3,2,0,0.0,neutral or dissatisfied +25865,125619,Male,Loyal Customer,51,Personal Travel,Business,814,3,0,3,2,2,5,4,1,1,3,1,4,1,5,0,0.0,neutral or dissatisfied +25866,62754,Female,Loyal Customer,57,Business travel,Business,2556,3,3,3,3,4,4,4,5,4,4,5,4,4,4,87,79.0,satisfied +25867,3547,Female,disloyal Customer,38,Business travel,Business,227,5,0,0,3,1,0,1,1,3,3,5,4,5,1,0,0.0,satisfied +25868,95942,Male,Loyal Customer,59,Business travel,Business,2478,5,5,5,5,2,5,4,3,3,4,3,5,3,4,0,0.0,satisfied +25869,88985,Male,Loyal Customer,16,Personal Travel,Eco,1340,4,4,4,4,1,4,1,1,5,3,4,5,5,1,0,0.0,satisfied +25870,95440,Female,Loyal Customer,41,Business travel,Business,293,4,4,4,4,4,5,5,5,5,5,5,5,5,3,0,0.0,satisfied +25871,76838,Male,Loyal Customer,54,Business travel,Business,989,2,2,2,2,5,5,4,4,4,4,4,5,4,4,0,0.0,satisfied +25872,91747,Female,Loyal Customer,45,Business travel,Business,588,3,3,3,3,2,5,5,4,4,4,4,5,4,4,0,0.0,satisfied +25873,81901,Male,Loyal Customer,32,Business travel,Business,680,2,2,2,2,3,4,3,3,4,5,3,3,3,3,10,7.0,satisfied +25874,83008,Female,Loyal Customer,51,Business travel,Business,3904,4,4,4,4,4,5,5,4,4,4,4,4,4,4,0,0.0,satisfied +25875,56757,Female,Loyal Customer,46,Business travel,Business,2202,1,5,1,1,5,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +25876,15817,Female,Loyal Customer,47,Business travel,Eco Plus,143,5,1,1,1,1,4,2,5,5,5,5,1,5,5,0,0.0,satisfied +25877,17962,Female,Loyal Customer,25,Personal Travel,Eco,501,3,5,3,4,1,3,4,1,4,5,4,3,4,1,0,5.0,neutral or dissatisfied +25878,19939,Male,Loyal Customer,36,Personal Travel,Eco,296,2,4,2,1,5,2,5,5,3,3,5,5,4,5,0,4.0,neutral or dissatisfied +25879,66790,Male,Loyal Customer,48,Personal Travel,Eco,3711,3,5,4,4,4,3,3,4,1,1,3,3,4,3,0,0.0,neutral or dissatisfied +25880,122286,Female,Loyal Customer,35,Personal Travel,Eco,541,3,5,3,3,1,3,1,1,4,3,4,3,4,1,0,0.0,neutral or dissatisfied +25881,46073,Female,disloyal Customer,22,Business travel,Eco,541,1,0,2,2,3,2,3,3,2,5,3,3,1,3,0,2.0,neutral or dissatisfied +25882,104191,Female,Loyal Customer,69,Personal Travel,Eco Plus,349,3,1,3,3,3,4,3,1,1,3,1,4,1,4,0,0.0,neutral or dissatisfied +25883,128904,Male,Loyal Customer,11,Personal Travel,Eco Plus,2454,3,4,3,2,3,3,1,3,2,4,4,1,5,1,1,17.0,neutral or dissatisfied +25884,81151,Male,Loyal Customer,49,Business travel,Business,1715,1,1,1,1,2,5,5,4,4,4,4,5,4,5,1,0.0,satisfied +25885,65952,Female,Loyal Customer,35,Business travel,Business,1372,2,2,2,2,2,4,4,2,2,2,2,4,2,4,0,0.0,satisfied +25886,27435,Female,disloyal Customer,25,Business travel,Eco,679,2,2,2,4,5,2,5,5,4,1,3,3,4,5,0,0.0,neutral or dissatisfied +25887,92322,Female,Loyal Customer,54,Business travel,Business,2399,3,3,4,3,5,4,4,4,4,4,4,4,4,4,0,8.0,satisfied +25888,51995,Male,disloyal Customer,15,Business travel,Eco,1119,1,1,1,3,2,1,2,2,2,4,5,5,3,2,0,0.0,neutral or dissatisfied +25889,100534,Female,Loyal Customer,13,Personal Travel,Eco,580,3,3,3,2,2,3,2,2,3,4,5,4,5,2,0,0.0,neutral or dissatisfied +25890,21357,Female,Loyal Customer,52,Personal Travel,Eco,674,4,4,4,3,2,4,4,4,4,4,4,3,4,3,59,45.0,neutral or dissatisfied +25891,99866,Male,Loyal Customer,44,Business travel,Business,3857,1,1,1,1,2,5,4,4,4,4,4,3,4,4,0,5.0,satisfied +25892,51200,Female,Loyal Customer,31,Business travel,Eco Plus,373,2,2,4,4,2,2,2,2,2,1,4,4,4,2,49,36.0,neutral or dissatisfied +25893,4723,Female,Loyal Customer,45,Business travel,Business,3542,1,1,2,1,3,4,4,1,1,1,1,4,1,2,0,0.0,neutral or dissatisfied +25894,33430,Male,Loyal Customer,54,Business travel,Business,2614,3,1,1,1,3,3,3,4,2,3,3,3,2,3,37,27.0,neutral or dissatisfied +25895,29842,Female,Loyal Customer,51,Business travel,Eco,261,2,1,5,1,3,3,4,2,2,2,2,2,2,2,0,0.0,neutral or dissatisfied +25896,44001,Male,Loyal Customer,44,Business travel,Eco,397,4,1,1,1,4,4,4,4,1,3,5,2,1,4,0,0.0,satisfied +25897,120508,Male,Loyal Customer,51,Business travel,Eco Plus,366,5,5,5,5,5,5,5,5,2,1,2,5,1,5,0,0.0,satisfied +25898,75950,Female,disloyal Customer,49,Business travel,Business,228,4,4,4,1,1,4,1,1,4,2,4,4,4,1,0,0.0,satisfied +25899,93783,Female,Loyal Customer,57,Business travel,Business,2334,3,3,3,3,3,5,4,3,3,3,3,5,3,5,0,0.0,satisfied +25900,92469,Male,disloyal Customer,31,Business travel,Eco,1947,3,3,3,3,1,3,1,1,2,5,4,4,3,1,18,14.0,neutral or dissatisfied +25901,59844,Female,Loyal Customer,45,Business travel,Business,1023,1,1,1,1,4,5,5,3,3,3,3,5,3,3,0,0.0,satisfied +25902,80506,Female,disloyal Customer,40,Business travel,Business,1749,1,1,1,4,1,1,1,1,2,2,3,2,4,1,0,0.0,neutral or dissatisfied +25903,101088,Female,Loyal Customer,37,Business travel,Business,795,3,3,3,3,3,5,5,4,4,4,4,4,4,5,5,0.0,satisfied +25904,89801,Female,Loyal Customer,49,Business travel,Business,3542,3,3,3,3,5,5,5,3,4,5,5,5,5,5,90,169.0,satisfied +25905,110855,Female,disloyal Customer,22,Business travel,Business,581,5,5,5,1,5,5,5,5,5,5,5,4,4,5,13,0.0,satisfied +25906,108077,Male,disloyal Customer,25,Business travel,Business,997,4,2,3,1,4,3,4,4,3,5,5,5,4,4,21,31.0,satisfied +25907,112217,Male,Loyal Customer,50,Business travel,Business,3083,1,2,2,2,2,4,4,1,1,1,1,3,1,3,12,1.0,neutral or dissatisfied +25908,2475,Female,Loyal Customer,46,Business travel,Eco Plus,373,5,5,1,5,5,4,4,5,5,5,5,5,5,2,18,28.0,satisfied +25909,59741,Female,Loyal Customer,27,Business travel,Business,895,4,4,3,4,4,4,4,4,5,4,5,3,5,4,7,10.0,satisfied +25910,90275,Male,Loyal Customer,42,Business travel,Eco,773,2,5,5,5,2,2,2,2,4,4,2,1,3,2,0,0.0,neutral or dissatisfied +25911,64872,Female,Loyal Customer,56,Business travel,Business,190,2,4,4,4,1,4,3,3,3,2,2,4,3,4,0,0.0,neutral or dissatisfied +25912,69963,Male,Loyal Customer,36,Personal Travel,Eco Plus,2174,5,1,5,3,2,5,2,2,3,5,3,1,3,2,9,0.0,satisfied +25913,102978,Male,Loyal Customer,43,Business travel,Business,1891,3,3,4,3,5,4,4,3,3,3,3,5,3,4,29,25.0,satisfied +25914,82375,Female,disloyal Customer,39,Business travel,Business,1953,3,3,3,3,4,3,4,4,4,5,4,3,5,4,0,0.0,neutral or dissatisfied +25915,124890,Male,Loyal Customer,41,Business travel,Business,728,2,2,2,2,5,5,5,5,5,4,5,3,5,3,6,6.0,satisfied +25916,32900,Male,Loyal Customer,54,Personal Travel,Eco,163,3,4,3,4,2,3,2,2,3,2,5,4,4,2,0,0.0,neutral or dissatisfied +25917,129396,Female,Loyal Customer,52,Personal Travel,Business,414,5,4,1,1,3,3,5,3,3,1,3,1,3,2,0,0.0,satisfied +25918,118373,Female,Loyal Customer,32,Business travel,Business,2387,3,5,5,5,3,3,3,3,2,4,4,4,4,3,0,0.0,neutral or dissatisfied +25919,1763,Male,Loyal Customer,63,Personal Travel,Eco Plus,364,2,2,4,4,5,4,4,5,3,5,4,4,3,5,0,0.0,neutral or dissatisfied +25920,99523,Female,Loyal Customer,66,Personal Travel,Eco Plus,283,3,5,2,4,2,5,5,2,2,2,2,5,2,3,2,4.0,neutral or dissatisfied +25921,8141,Male,disloyal Customer,33,Business travel,Eco,335,2,2,2,4,4,2,2,4,2,1,4,1,4,4,0,0.0,neutral or dissatisfied +25922,99006,Male,Loyal Customer,54,Business travel,Business,1984,1,1,1,1,3,5,4,4,4,4,4,4,4,4,0,3.0,satisfied +25923,17142,Female,Loyal Customer,15,Personal Travel,Business,926,3,4,3,4,4,3,4,4,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +25924,24468,Male,Loyal Customer,45,Business travel,Eco,516,4,1,1,1,4,4,4,4,3,2,2,3,4,4,0,6.0,satisfied +25925,76788,Female,Loyal Customer,29,Business travel,Business,689,2,2,2,2,3,3,3,3,4,2,5,5,5,3,48,46.0,satisfied +25926,115156,Female,Loyal Customer,80,Business travel,Business,337,1,1,4,1,5,5,4,5,5,5,5,5,5,4,6,4.0,satisfied +25927,41032,Male,Loyal Customer,55,Business travel,Eco,1195,5,4,4,4,5,5,5,5,2,2,5,5,4,5,4,28.0,satisfied +25928,23877,Female,Loyal Customer,49,Business travel,Business,2497,2,2,2,2,4,3,3,2,2,2,2,1,2,1,0,0.0,neutral or dissatisfied +25929,35027,Female,Loyal Customer,9,Personal Travel,Eco Plus,740,1,5,1,4,4,1,4,4,4,2,4,5,4,4,0,18.0,neutral or dissatisfied +25930,31824,Female,Loyal Customer,30,Business travel,Eco,2762,4,2,2,2,4,4,4,3,1,5,3,4,3,4,0,0.0,satisfied +25931,83236,Female,Loyal Customer,51,Business travel,Business,1979,3,3,3,3,2,5,4,5,5,5,5,3,5,3,0,0.0,satisfied +25932,127293,Male,Loyal Customer,46,Business travel,Business,3701,4,4,4,4,4,4,4,4,4,4,4,5,4,3,0,0.0,satisfied +25933,122381,Female,Loyal Customer,22,Personal Travel,Eco,529,3,5,3,4,3,3,3,3,3,5,4,5,5,3,0,0.0,neutral or dissatisfied +25934,125746,Female,Loyal Customer,41,Business travel,Business,2748,1,2,2,2,1,4,4,1,1,1,1,3,1,3,83,79.0,neutral or dissatisfied +25935,115280,Female,Loyal Customer,39,Business travel,Business,2291,2,2,1,1,5,2,2,2,2,2,2,1,2,1,70,64.0,neutral or dissatisfied +25936,60005,Male,Loyal Customer,31,Personal Travel,Eco,997,5,5,5,3,4,5,3,4,5,2,4,4,4,4,0,0.0,satisfied +25937,43595,Male,Loyal Customer,37,Business travel,Business,228,2,2,2,2,4,4,4,4,4,4,4,3,4,4,0,0.0,satisfied +25938,7497,Female,Loyal Customer,22,Personal Travel,Eco,925,3,5,3,2,3,3,1,3,5,2,4,5,5,3,4,14.0,neutral or dissatisfied +25939,45778,Female,Loyal Customer,42,Business travel,Business,3855,1,1,1,1,1,3,1,4,4,4,4,1,4,5,0,0.0,satisfied +25940,87960,Male,Loyal Customer,43,Business travel,Business,1658,2,2,2,2,5,4,5,4,4,5,4,3,4,3,0,0.0,satisfied +25941,13970,Male,Loyal Customer,47,Personal Travel,Eco,192,3,5,3,5,1,3,1,1,4,4,4,4,4,1,0,0.0,neutral or dissatisfied +25942,91254,Male,Loyal Customer,44,Personal Travel,Eco,404,3,1,3,2,3,5,2,2,4,2,3,2,4,2,131,138.0,neutral or dissatisfied +25943,21411,Male,Loyal Customer,41,Business travel,Business,3518,0,0,0,3,2,4,4,2,2,5,5,1,2,2,23,19.0,satisfied +25944,123675,Male,Loyal Customer,62,Business travel,Business,2390,2,3,3,3,4,3,4,4,4,3,2,4,4,3,0,0.0,neutral or dissatisfied +25945,23585,Male,Loyal Customer,29,Business travel,Eco,1069,3,1,1,1,3,4,3,3,1,3,1,3,1,3,20,32.0,satisfied +25946,65833,Female,Loyal Customer,25,Business travel,Business,1389,1,4,4,4,1,1,1,1,1,1,4,4,3,1,0,0.0,neutral or dissatisfied +25947,36449,Male,Loyal Customer,16,Business travel,Eco Plus,1368,0,4,0,4,2,0,4,2,5,1,4,4,2,2,0,0.0,satisfied +25948,62329,Male,Loyal Customer,37,Personal Travel,Eco,414,2,4,2,4,4,2,1,4,1,2,3,4,3,4,0,0.0,neutral or dissatisfied +25949,37905,Male,disloyal Customer,56,Business travel,Eco,668,5,0,5,1,2,5,2,2,4,3,3,4,5,2,0,0.0,satisfied +25950,111771,Female,Loyal Customer,52,Business travel,Business,1620,4,4,4,4,2,4,4,4,4,4,4,4,4,5,30,26.0,satisfied +25951,27201,Female,disloyal Customer,21,Business travel,Eco,752,0,0,0,1,2,0,2,2,5,3,4,3,4,2,0,0.0,satisfied +25952,76397,Male,Loyal Customer,60,Personal Travel,Eco,931,2,3,1,2,3,1,3,3,4,1,2,4,3,3,0,0.0,neutral or dissatisfied +25953,27759,Female,Loyal Customer,43,Business travel,Business,1448,4,1,4,4,3,3,2,5,5,5,5,5,5,2,0,0.0,satisfied +25954,79286,Female,Loyal Customer,29,Business travel,Business,2248,4,4,4,4,4,4,4,4,3,5,2,3,4,4,1,0.0,neutral or dissatisfied +25955,56083,Female,Loyal Customer,65,Personal Travel,Eco,2475,3,4,4,1,4,3,3,3,4,4,5,3,4,3,0,0.0,neutral or dissatisfied +25956,109108,Female,Loyal Customer,29,Business travel,Business,2864,5,5,5,5,3,3,3,3,5,5,5,3,5,3,0,0.0,satisfied +25957,109899,Female,disloyal Customer,16,Business travel,Eco,1073,2,2,2,1,3,2,3,3,5,1,2,1,5,3,21,3.0,neutral or dissatisfied +25958,25269,Male,Loyal Customer,16,Business travel,Business,3149,3,5,5,5,3,3,3,3,1,5,4,1,3,3,0,0.0,neutral or dissatisfied +25959,74541,Female,Loyal Customer,58,Business travel,Eco,1171,2,4,4,4,4,3,3,2,2,2,2,2,2,1,0,18.0,neutral or dissatisfied +25960,86010,Female,disloyal Customer,23,Business travel,Eco,447,4,0,4,3,1,4,1,1,4,4,5,5,4,1,0,0.0,neutral or dissatisfied +25961,126836,Male,Loyal Customer,51,Business travel,Business,2296,3,3,3,3,5,5,4,5,5,5,5,3,5,3,2,0.0,satisfied +25962,2313,Female,disloyal Customer,21,Business travel,Eco,691,4,4,4,1,2,4,2,2,2,1,1,2,1,2,0,0.0,neutral or dissatisfied +25963,65035,Female,Loyal Customer,65,Personal Travel,Eco,247,3,4,0,3,3,5,4,4,4,0,4,3,4,5,0,0.0,neutral or dissatisfied +25964,111325,Female,Loyal Customer,48,Business travel,Eco,283,3,1,1,1,4,3,3,3,3,3,3,4,3,1,38,28.0,neutral or dissatisfied +25965,15949,Female,Loyal Customer,51,Personal Travel,Eco,528,4,4,4,2,5,5,4,5,5,4,5,4,5,4,0,0.0,neutral or dissatisfied +25966,30263,Male,disloyal Customer,42,Business travel,Eco,1024,4,4,4,2,3,4,3,3,3,1,2,2,3,3,0,17.0,neutral or dissatisfied +25967,90347,Female,disloyal Customer,39,Business travel,Business,404,1,1,1,3,2,1,2,2,5,3,4,4,4,2,0,0.0,neutral or dissatisfied +25968,86816,Male,Loyal Customer,41,Business travel,Eco,692,2,2,2,2,2,2,2,2,2,3,3,2,3,2,15,3.0,neutral or dissatisfied +25969,120654,Male,Loyal Customer,52,Business travel,Business,280,3,3,3,3,3,4,4,4,4,4,4,3,4,3,0,0.0,satisfied +25970,25309,Female,disloyal Customer,36,Business travel,Eco,432,1,5,1,3,4,1,4,4,5,2,5,2,3,4,0,0.0,neutral or dissatisfied +25971,78463,Male,disloyal Customer,34,Business travel,Business,526,3,3,3,1,4,3,4,4,3,2,4,4,5,4,0,0.0,neutral or dissatisfied +25972,71167,Male,Loyal Customer,23,Business travel,Business,646,4,4,4,4,4,4,4,4,4,5,5,5,5,4,0,0.0,satisfied +25973,37675,Female,Loyal Customer,17,Personal Travel,Eco,828,2,5,1,5,2,1,2,2,4,3,4,5,4,2,0,0.0,neutral or dissatisfied +25974,90086,Male,Loyal Customer,14,Business travel,Business,1127,3,3,3,3,4,4,4,4,3,2,5,4,5,4,0,0.0,satisfied +25975,34799,Female,Loyal Customer,42,Personal Travel,Eco,264,2,5,2,5,4,2,2,1,1,2,1,1,1,1,0,0.0,neutral or dissatisfied diff --git a/notebooks/Airline_Project1-Copy_marta.ipynb b/notebooks/Airline_Project1-Copy_marta.ipynb index 7c315000..9757a01c 100644 --- a/notebooks/Airline_Project1-Copy_marta.ipynb +++ b/notebooks/Airline_Project1-Copy_marta.ipynb @@ -1521,7 +1521,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\Marta\\AppData\\Local\\Temp\\ipykernel_29024\\1995285321.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", + "C:\\Users\\Marta\\AppData\\Local\\Temp\\ipykernel_38280\\1995285321.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", "\n", "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", @@ -1907,10 +1907,322 @@ "print(\"Plot saved as 'service_correlation_bar_chart.png'\")" ] }, + { + "cell_type": "code", + "execution_count": 15, + "id": "8008feed-c00e-4ab0-969a-2ff4ad9a5005", + "metadata": {}, + "outputs": [], + "source": [ + "def analyze_service_correlations_notebook(df):\n", + " \"\"\"\n", + " Calcula el coeficiente de correlación de Pearson (r) entre\n", + " las columnas de servicio y la variable objetivo satisfaction_binary.\n", + " \"\"\"\n", + " # Lista de columnas de servicio que ya usaste en tu análisis H3\n", + " service_columns = [\n", + " 'inflight_wifi_service',\n", + " 'departure/arrival_time_convenient',\n", + " 'ease_of_online_booking',\n", + " 'gate_location',\n", + " 'food_and_drink',\n", + " 'online_boarding',\n", + " 'seat_comfort',\n", + " 'inflight_entertainment',\n", + " 'on-board_service',\n", + " 'leg_room_service',\n", + " 'baggage_handling',\n", + " 'checkin_service',\n", + " 'inflight_service',\n", + " 'cleanliness',\n", + " 'departure_delay_in_minutes',\n", + " 'arrival_delay_in_minutes'\n", + " ]\n", + "\n", + " # Calcular la correlación\n", + " correlation_results = df[service_columns + ['satisfaction_binary']].corr()['satisfaction_binary'].sort_values(ascending=False)\n", + "\n", + " # Eliminar la correlación de la variable objetivo consigo misma\n", + " correlation_results = correlation_results.drop('satisfaction_binary', errors='ignore')\n", + " \n", + " return correlation_results" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "c2fa4de5-75f6-472f-9ce2-9b6977eb50cd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Pasajeros Clase Eco para análisis: 46745\n", + "Pasajeros Clase Eco Plus para análisis: 7494\n", + "------------------------------\n", + "\n", + "--- TOP 5 IMPULSORES para CLASE ECO ---\n", + "inflight_wifi_service 0.467446\n", + "online_boarding 0.315534\n", + "ease_of_online_booking 0.232656\n", + "inflight_entertainment 0.181622\n", + "food_and_drink 0.140649\n", + "Name: satisfaction_binary, dtype: float64\n", + "------------------------------\n", + "\n", + "--- TOP 5 IMPULSORES para CLASE ECO PLUS ---\n", + "inflight_wifi_service 0.494850\n", + "online_boarding 0.347700\n", + "inflight_entertainment 0.328406\n", + "cleanliness 0.255886\n", + "food_and_drink 0.255254\n", + "Name: satisfaction_binary, dtype: float64\n" + ] + } + ], + "source": [ + "# --- 1. Filtrar Data por Clase ---\n", + "\n", + "# Filtrar para Clase Economy\n", + "df_eco = df_cleaned[df_cleaned['class'] == 'Eco'].copy()\n", + "print(f\"Pasajeros Clase Eco para análisis: {len(df_eco)}\")\n", + "\n", + "# Filtrar para Clase Eco Plus\n", + "df_ecoplus = df_cleaned[df_cleaned['class'] == 'Eco Plus'].copy()\n", + "print(f\"Pasajeros Clase Eco Plus para análisis: {len(df_ecoplus)}\")\n", + "\n", + "print(\"-\" * 30)\n", + "\n", + "# --- 2. Calcular Correlaciones Segmentadas ---\n", + "\n", + "# Análisis de Correlación para CLASE ECO\n", + "corr_eco = analyze_service_correlations_notebook(df_eco)\n", + "print(\"\\n--- TOP 5 IMPULSORES para CLASE ECO ---\")\n", + "print(corr_eco.head(5))\n", + "\n", + "print(\"-\" * 30)\n", + "\n", + "# Análisis de Correlación para CLASE ECO PLUS\n", + "corr_ecoplus = analyze_service_correlations_notebook(df_ecoplus)\n", + "print(\"\\n--- TOP 5 IMPULSORES para CLASE ECO PLUS ---\")\n", + "print(corr_ecoplus.head(5))" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "3e41f7db-5158-4852-8f00-68737e73202d", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Segmented Investment Drivers Comparison chart generated and successfully saved to 'images/segmented_investment_comparison.png'.\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "import os # Import the os library\n", + "\n", + "# --- Data Compilation ---\n", + "general_corr = {\n", + " 'online_boarding': 0.504,\n", + " 'inflight_entertainment': 0.398,\n", + " 'seat_comfort': 0.349,\n", + " 'inflight_wifi_service': 0.284, \n", + " 'on-board_service': 0.322\n", + "}\n", + "eco_corr = {\n", + " 'inflight_wifi_service': 0.467,\n", + " 'online_boarding': 0.316,\n", + " 'ease_of_online_booking': 0.233,\n", + " 'inflight_entertainment': 0.182,\n", + " 'food_and_drink': 0.141\n", + "}\n", + "ecoplus_corr = {\n", + " 'inflight_wifi_service': 0.495,\n", + " 'online_boarding': 0.348,\n", + " 'inflight_entertainment': 0.328,\n", + " 'cleanliness': 0.256,\n", + " 'food_and_drink': 0.255\n", + "}\n", + "\n", + "combined_df = pd.DataFrame({\n", + " 'General': general_corr,\n", + " 'Eco': eco_corr,\n", + " 'Eco Plus': ecoplus_corr\n", + "}).fillna(0).sort_values(by='Eco Plus', ascending=True)\n", + "\n", + "# --- Plotting Setup ---\n", + "fig, ax = plt.subplots(figsize=(12, 8))\n", + "\n", + "bar_height = 0.25\n", + "y_pos = np.arange(len(combined_df.index))\n", + "\n", + "# Plot bars for the three segments\n", + "ax.barh(y_pos + bar_height, combined_df['General'], bar_height, label='General (All Classes)', color='#007AA3', alpha=0.7)\n", + "ax.barh(y_pos, combined_df['Eco'], bar_height, label='Eco', color='#FF7F0E', alpha=0.8)\n", + "ax.barh(y_pos - bar_height, combined_df['Eco Plus'], bar_height, label='Eco Plus', color='#2CA02C')\n", + "\n", + "# Labels and titles\n", + "ax.set_yticks(y_pos)\n", + "ax.set_yticklabels(combined_df.index.str.replace('_', ' ').str.title())\n", + "ax.set_xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "ax.set_title('Segmented Investment Strategy: Correlation of Drivers by Class', fontsize=16, fontweight='bold')\n", + "ax.legend(loc='lower right')\n", + "ax.grid(axis='x', linestyle='--', alpha=0.5)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "# --- FIX: Create the directory if it doesn't exist ---\n", + "output_dir = 'images'\n", + "if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + "\n", + "# Now save the file\n", + "plt.savefig(os.path.join(output_dir, 'segmented_investment_comparison.png'))\n", + "plt.show()\n", + "\n", + "print(\"Segmented Investment Drivers Comparison chart generated and successfully saved to 'images/segmented_investment_comparison.png'.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "807955be-59b7-41dd-b1b5-b077b457d7f1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Simplified Segmented Investment Drivers Comparison chart code generated.\n", + "\n", + "--- Top 5 Drivers for the Combined Economy Segment ---\n", + "inflight_wifi_service 0.470869\n", + "online_boarding 0.320421\n", + "ease_of_online_booking 0.225677\n", + "inflight_entertainment 0.202172\n", + "food_and_drink 0.156751\n", + "dtype: float64\n" + ] + } + ], + "source": [ + "import pandas as pd\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "# --- 1. Data Compilation ---\n", + "# Sample Sizes (Weights)\n", + "n_eco = 46745\n", + "n_ecoplus = 7494\n", + "n_total_eco_segment = n_eco + n_ecoplus\n", + "\n", + "# 1. General Correlation (Top 5 from your H3 analysis)\n", + "general_corr = {\n", + " 'online_boarding': 0.504,\n", + " 'inflight_entertainment': 0.398,\n", + " 'seat_comfort': 0.349,\n", + " 'inflight_wifi_service': 0.284, \n", + " 'on-board_service': 0.322\n", + "}\n", + "\n", + "# 2. ECO and ECO PLUS RAW CORRELATIONS\n", + "eco_corr_raw = {\n", + " 'inflight_wifi_service': 0.467, 'online_boarding': 0.316, \n", + " 'ease_of_online_booking': 0.233, 'inflight_entertainment': 0.182, \n", + " 'food_and_drink': 0.141, 'cleanliness': 0.09 # Adding cleanliness for weighted average\n", + "}\n", + "ecoplus_corr_raw = {\n", + " 'inflight_wifi_service': 0.495, 'online_boarding': 0.348, \n", + " 'inflight_entertainment': 0.328, 'cleanliness': 0.256, \n", + " 'food_and_drink': 0.255, 'ease_of_online_booking': 0.18\n", + "}\n", + "\n", + "# 3. CALCULATE THE WEIGHTED AVERAGE for the combined 'Economy Segment'\n", + "combined_drivers = {}\n", + "all_drivers_keys = set(eco_corr_raw.keys()) | set(ecoplus_corr_raw.keys())\n", + "\n", + "for driver in all_drivers_keys:\n", + " # Get correlation and fill NaN with 0 for drivers not in the segment\n", + " r_eco = eco_corr_raw.get(driver, 0)\n", + " r_ecoplus = ecoplus_corr_raw.get(driver, 0)\n", + " \n", + " # Weighted Average Formula: (r_eco * n_eco + r_ecoplus * n_ecoplus) / n_total\n", + " weighted_r = (r_eco * n_eco + r_ecoplus * n_ecoplus) / n_total_eco_segment\n", + " combined_drivers[driver] = weighted_r\n", + "\n", + "# Select the top 5 for the final chart for clarity\n", + "combined_drivers_series = pd.Series(combined_drivers).sort_values(ascending=False).head(5).to_dict()\n", + "\n", + "# --- 4. Final DataFrame for Plotting (General vs. Combined Economy) ---\n", + "final_combined_df = pd.DataFrame({\n", + " 'General (All Classes)': general_corr,\n", + " 'Economy Segment (Eco + Eco Plus)': combined_drivers_series\n", + "}).fillna(0).sort_values(by='Economy Segment (Eco + Eco Plus)', ascending=True)\n", + "\n", + "# --- Plotting Setup ---\n", + "fig, ax = plt.subplots(figsize=(10, 7))\n", + "\n", + "bar_height = 0.35\n", + "y_pos = np.arange(len(final_combined_df.index))\n", + "\n", + "# Plot bars for the two segments\n", + "ax.barh(y_pos + bar_height/2, final_combined_df['General (All Classes)'], bar_height, label='General (All Classes)', color='#007AA3', alpha=0.7)\n", + "ax.barh(y_pos - bar_height/2, final_combined_df['Economy Segment (Eco + Eco Plus)'], bar_height, label='Economy Segment (Strategic Focus)', color='#DAA520')\n", + "\n", + "# Labels and titles\n", + "ax.set_yticks(y_pos)\n", + "ax.set_yticklabels(final_combined_df.index.str.replace('_', ' ').str.title())\n", + "ax.set_xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "ax.set_title('Investment Strategy: General vs. Combined Economy Segment Drivers', fontsize=14, fontweight='bold')\n", + "ax.legend(loc='lower right')\n", + "ax.grid(axis='x', linestyle='--', alpha=0.5)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "# --- SAVING THE FILE ---\n", + "output_dir = 'images'\n", + "if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + "plt.savefig(os.path.join(output_dir, 'simplified_segmented_investment_comparison.png'))\n", + "plt.show()\n", + "\n", + "print(\"Simplified Segmented Investment Drivers Comparison chart code generated.\")\n", + "print(\"\\n--- Top 5 Drivers for the Combined Economy Segment ---\")\n", + "print(pd.Series(combined_drivers_series))" + ] + }, { "cell_type": "code", "execution_count": null, - "id": "a61cea65-f81b-4393-8d6c-6ef0aed5f3c3", + "id": "2851d5c5-af25-48bb-93aa-634b634c8dbc", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/Airline_Project1.ipynb b/notebooks/Airline_Project1.ipynb index f2526582..e6ff8ad0 100644 --- a/notebooks/Airline_Project1.ipynb +++ b/notebooks/Airline_Project1.ipynb @@ -2,411 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "561808a4-27ef-4523-892a-8584a31efefa", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
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10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
7796462FemaleLoyal Customer52Business travelBusiness203543...555545440.0satisfied
131383502MaleLoyal Customer33Personal TravelEco94642...445222400.0satisfied
161671142FemaleLoyal Customer26Business travelBusiness212333...45345444951.0satisfied
..................................................................
10389010389080087FemaleLoyal Customer56Business travelEco Plus55035...333343300.0satisfied
10389110389183013MaleLoyal Customer54Business travelBusiness199155...44545443531.0satisfied
10389410389486549MaleLoyal Customer26Business travelBusiness71244...53443451726.0satisfied
103897103897102203FemaleLoyal Customer60Business travelBusiness159955...444444497.0satisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
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45025 rows × 25 columns

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Inflight entertainment \\\n", - "2 2 ... 5 \n", - "4 3 ... 3 \n", - "7 3 ... 5 \n", - "13 2 ... 4 \n", - "16 3 ... 4 \n", - "... ... ... ... \n", - "103890 5 ... 3 \n", - "103891 5 ... 4 \n", - "103894 4 ... 5 \n", - "103897 5 ... 4 \n", - "103900 4 ... 5 \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "2 4 3 4 4 \n", - "4 3 4 4 3 \n", - "7 5 5 5 4 \n", - "13 4 5 2 2 \n", - "16 5 3 4 5 \n", - "... ... ... ... ... \n", - "103890 3 3 3 4 \n", - "103891 4 5 4 5 \n", - "103894 3 4 4 3 \n", - "103897 4 4 4 4 \n", - "103900 5 5 5 5 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "2 4 5 0 \n", - "4 3 3 0 \n", - "7 5 4 4 \n", - "13 2 4 0 \n", - "16 4 4 49 \n", - "... ... ... ... \n", - "103890 3 3 0 \n", - "103891 4 4 35 \n", - "103894 4 5 17 \n", - "103897 4 4 9 \n", - "103900 5 4 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction \n", - "2 0.0 satisfied \n", - "4 0.0 satisfied \n", - "7 0.0 satisfied \n", - "13 0.0 satisfied \n", - "16 51.0 satisfied \n", - "... ... ... \n", - "103890 0.0 satisfied \n", - "103891 31.0 satisfied \n", - "103894 26.0 satisfied \n", - "103897 7.0 satisfied \n", - "103900 0.0 satisfied \n", - "\n", - "[45025 rows x 25 columns]" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "dfSatisfied" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "bbff3fc8-6ae0-4005-81b4-7fd7ab30f8f8", + "metadata": {}, + "outputs": [], + "source": [ + "binary_change= {\n", + " 'satisfied': 1,\n", + " 'neutral or dissatisfied': 0,\n", + "}\n", + "\n", + "df['satisfaction'] = df['satisfaction'].replace(binary_change)\n", + "df.drop(columns=['Unnamed: 0'], inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7d7a4e4b-d075-49e7-9051-194bd08f7304", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "code", "execution_count": null, @@ -1510,13 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1af626c1dbc0b331b3c7c8d33bca166d524ba6ef Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Wed, 10 Dec 2025 17:05:16 +0100 Subject: [PATCH 14/26] D2 commit, plus figures --- .../notebooks/Airline_Project1.ipynb | 45 + .virtual_documents/notebooks/Untitled.ipynb | 14 + figures/customer_type_pie_chart.png | Bin 0 -> 43520 bytes .../dissatisfaction_by_age_group_seaborn.png | Bin 0 -> 36507 bytes ...tomers_age_percentage_bar_chart_actual.png | Bin 0 -> 43688 bytes ...s_flight_distance_percentage_bar_chart.png | Bin 0 -> 44167 bytes ...ht_distance_percentage_bar_chart_final.png | Bin 0 -> 61550 bytes ..._customers_gender_percentage_bar_chart.png | Bin 0 -> 26178 bytes figures/figure.png | 0 notebooks/Airline_Project1.ipynb | 5590 +++-------------- notebooks/Airline_Project1_Antonio 2.ipynb | 1991 ++++++ notebooks/Airline_Project1_Antonio.ipynb | 2548 ++++++++ 12 files changed, 5471 insertions(+), 4717 deletions(-) create mode 100644 .virtual_documents/notebooks/Airline_Project1.ipynb create mode 100644 figures/customer_type_pie_chart.png create mode 100644 figures/dissatisfaction_by_age_group_seaborn.png create mode 100644 figures/dissatisfied_customers_age_percentage_bar_chart_actual.png create mode 100644 figures/dissatisfied_customers_flight_distance_percentage_bar_chart.png create mode 100644 figures/dissatisfied_customers_flight_distance_percentage_bar_chart_final.png create mode 100644 figures/dissatisfied_customers_gender_percentage_bar_chart.png delete mode 100644 figures/figure.png create mode 100644 notebooks/Airline_Project1_Antonio 2.ipynb create mode 100644 notebooks/Airline_Project1_Antonio.ipynb diff --git a/.virtual_documents/notebooks/Airline_Project1.ipynb b/.virtual_documents/notebooks/Airline_Project1.ipynb new file mode 100644 index 00000000..f11919e4 --- /dev/null +++ b/.virtual_documents/notebooks/Airline_Project1.ipynb @@ -0,0 +1,45 @@ +import pandas as pd +import numpy as np + +df=pd.read_csv('train.csv') +df + + +binary_change= { + 'satisfied': 1, + 'neutral or dissatisfied': 0, +} + +df['satisfaction'] = df['satisfaction'].replace(binary_change) +df.drop(columns=['Unnamed: 0'], inplace=True) + + +df + + +df['satisfaction'].value_counts() + + +df['Customer Type'].value_counts() + + +dfSatisfied=df[df['satisfaction'] == 1] +dfDisatisfied=df[df['satisfaction'] == 0] + + + + + +dfSatisfied.describe() + + +dfDisatisfied.describe() + + +dfSatisfied + + +dfDisatisfied + + + diff --git a/.virtual_documents/notebooks/Untitled.ipynb b/.virtual_documents/notebooks/Untitled.ipynb index 9bc45505..d465ca0d 100644 --- a/.virtual_documents/notebooks/Untitled.ipynb +++ b/.virtual_documents/notebooks/Untitled.ipynb @@ -5,6 +5,17 @@ df=pd.read_csv('train.csv') df +binary_change= { + 'satisfied': 1, + 'neutral or dissatisfied': 0, +} + +df['satisfaction'] = df['satisfaction'].replace(binary_change) + + + + + df['satisfaction'].value_counts() @@ -24,4 +35,7 @@ dfDisatisfied.describe() dfSatisfied +dfDisatisfied + + diff --git 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zDQ=Q|;l?1+9eP^#Qr$Q1Y{cZMXUGyV-iRCr;ZA{Fn2d5{N@t419+1^Mp)}8eFZ@?(5k<}oEK)vKvL4(kB}72q=j748-`|1_;}9S90p_dwA6E@f3ST{9i^e zpCl2JGZ`&SMlcdAhHS0^47RdWl=Ai0Bj=9Mrx0@9mGX7dLHzok{U=HA3ICz8dB&x` W-`X^?Kr@6~1of2M$&}+4Zv8(QCbpXZ literal 0 HcmV?d00001 diff --git a/figures/figure.png b/figures/figure.png deleted file mode 100644 index e69de29b..00000000 diff --git a/notebooks/Airline_Project1.ipynb b/notebooks/Airline_Project1.ipynb index a997ed4e..0ac64307 100644 --- a/notebooks/Airline_Project1.ipynb +++ b/notebooks/Airline_Project1.ipynb @@ -426,11 +426,19 @@ "id": "a86604ec-da44-40c0-894e-0a118b9ca685", "metadata": {}, "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age Group creation successful.\n", + "Flight distance group Group creation successful.\n" + ] + }, { "name": "stderr", "output_type": "stream", "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_9620\\1018124088.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" ] } @@ -442,15 +450,92 @@ "}\n", "\n", "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", - "df.drop(columns=['Unnamed: 0'], inplace=True)" + "df.drop(columns=['Unnamed: 0'], inplace=True)\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Age'] < 18),\n", + " (df['Age'] >= 18) & (df['Age'] < 30),\n", + " (df['Age'] >= 30) & (df['Age'] < 40),\n", + " (df['Age'] >= 40) & (df['Age'] < 50),\n", + " (df['Age'] >= 50) & (df['Age'] < 60),\n", + " (df['Age'] >= 60) & (df['Age'] < 70),\n", + " (df['Age'] >= 70)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Minor',\n", + " '18 to 30',\n", + " '30 to 40',\n", + " '40 to 50',\n", + " '50 to 60',\n", + " '60 to 70',\n", + " '70 +'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Age Group creation successful.\")\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Flight Distance'] < 750),\n", + " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", + " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", + " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", + " (df['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Flight distance group Group creation successful.\")" ] }, { "cell_type": "code", "execution_count": 3, - "id": "d113003b-b385-4d24-a8a7-fade2501e0c2", + "id": "6f945079-4c90-40ee-83b9-53af53e43388", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", + "dfDisatisfied=df[df['satisfaction_binary'] == 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", "metadata": {}, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\3011661649.py:47: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning.\n", + " vertical_stats_table = pivot_stats.stack(level=0)\n" + ] + }, { "data": { "text/html": [ @@ -472,4745 +557,584 @@ " \n", " \n", " \n", - " id\n", - " Gender\n", - " Customer Type\n", - " Age\n", - " Type of Travel\n", - " Class\n", - " Flight Distance\n", - " Inflight wifi service\n", - " Departure/Arrival time convenient\n", - " Ease of Online booking\n", - " ...\n", - " On-board service\n", - " Leg room service\n", - " Baggage handling\n", - " Checkin service\n", - " Inflight service\n", - " Cleanliness\n", - " Departure Delay in Minutes\n", - " Arrival Delay in Minutes\n", " satisfaction\n", - " satisfaction_binary\n", + " neutral or dissatisfied\n", + " satisfied\n", + " \n", + " \n", + " Metric\n", + " Statistic\n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " 0\n", - " 70172\n", - " Male\n", - " Loyal Customer\n", - " 13\n", - " Personal Travel\n", - " Eco Plus\n", - " 460\n", - " 3\n", - " 4\n", - " 3\n", - " ...\n", - " 4\n", - " 3\n", - " 4\n", - " 4\n", - " 5\n", - " 5\n", - " 25\n", - " 18.0\n", - " neutral or dissatisfied\n", - " 0\n", + " Age\n", + " mean\n", + " 37.566688\n", + " 41.750583\n", " \n", " \n", - " 1\n", - " 5047\n", - " Male\n", - " disloyal Customer\n", - " 25\n", - " Business travel\n", - " Business\n", - " 235\n", - " 3\n", - " 2\n", - " 3\n", - " ...\n", - " 1\n", - " 5\n", - " 3\n", - " 1\n", - " 4\n", - " 1\n", - " 1\n", - " 6.0\n", - " neutral or dissatisfied\n", - " 0\n", + " median\n", + " 36.000000\n", + " 43.000000\n", " \n", " \n", - " 2\n", - " 110028\n", - " Female\n", - " Loyal Customer\n", - " 26\n", - " Business travel\n", - " Business\n", - " 1142\n", - " 2\n", - " 2\n", - " 2\n", - " ...\n", - " 4\n", - " 3\n", - " 4\n", - " 4\n", - " 4\n", - " 5\n", - " 0\n", - " 0.0\n", - " satisfied\n", - " 1\n", + " std\n", + " 16.459825\n", + " 12.767833\n", " \n", " \n", - " 3\n", - " 24026\n", - " Female\n", - " Loyal Customer\n", - " 25\n", - " Business travel\n", - " Business\n", - " 562\n", - " 2\n", - " 5\n", - " 5\n", - " ...\n", - " 2\n", - " 5\n", - " 3\n", - " 1\n", - " 4\n", - " 2\n", - " 11\n", - " 9.0\n", - " neutral or dissatisfied\n", - " 0\n", + " Arrival Delay in Minutes\n", + " mean\n", + " 17.127536\n", + " 12.630799\n", " \n", " \n", - " 4\n", - " 119299\n", - " Male\n", - " Loyal Customer\n", - " 61\n", - " Business travel\n", - " Business\n", - " 214\n", - " 3\n", - " 3\n", - " 3\n", - " ...\n", - " 3\n", - " 4\n", - " 4\n", - " 3\n", - " 3\n", - " 3\n", - " 0\n", - " 0.0\n", - " satisfied\n", - " 1\n", + " median\n", + " 0.000000\n", + " 0.000000\n", " \n", " \n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", - " ...\n", + " std\n", + " 40.560248\n", + " 35.962008\n", " \n", " \n", - " 103899\n", - " 94171\n", - " Female\n", - " disloyal Customer\n", - " 23\n", - " Business travel\n", - " Eco\n", - " 192\n", - " 2\n", - " 1\n", - " 2\n", - " ...\n", - " 3\n", - " 1\n", - " 4\n", - " 2\n", - " 3\n", - " 2\n", - " 3\n", - " 0.0\n", - " neutral or dissatisfied\n", - " 0\n", + " Baggage handling\n", + " mean\n", + " 3.375991\n", + " 3.966396\n", " \n", " \n", - " 103900\n", - " 73097\n", - " Male\n", - " Loyal Customer\n", - " 49\n", - " Business travel\n", - " Business\n", - " 2347\n", - " 4\n", - " 4\n", - " 4\n", - " ...\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 5\n", - " 4\n", - " 0\n", - " 0.0\n", - " satisfied\n", - " 1\n", - " \n", - " \n", - " 103901\n", - " 68825\n", - " Male\n", - " disloyal Customer\n", - " 30\n", - " Business travel\n", - " Business\n", - " 1995\n", - " 1\n", - " 1\n", - " 1\n", - " ...\n", - " 3\n", - " 2\n", - " 4\n", - " 5\n", - " 5\n", - " 4\n", - " 7\n", - " 14.0\n", - " neutral or dissatisfied\n", - " 0\n", - " \n", - " \n", - " 103902\n", - " 54173\n", - " Female\n", - " disloyal Customer\n", - " 22\n", - " Business travel\n", - " Eco\n", - " 1000\n", - " 1\n", - " 1\n", - " 1\n", - " ...\n", - " 4\n", - " 5\n", - " 1\n", - " 5\n", - " 4\n", - " 1\n", - " 0\n", - " 0.0\n", - " neutral or dissatisfied\n", - " 0\n", - " \n", - " \n", - " 103903\n", - " 62567\n", - " Male\n", - " Loyal Customer\n", - " 27\n", - " Business travel\n", - " Business\n", - " 1723\n", - " 1\n", - " 3\n", - " 3\n", - " ...\n", - " 1\n", - " 1\n", - " 4\n", - " 4\n", - " 3\n", - " 1\n", - " 0\n", - " 0.0\n", - " neutral or dissatisfied\n", - " 0\n", - " \n", - " \n", - "\n", - "

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Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", - "\n", - "metric_columns = [\n", - " 'Type of Travel',\n", - " 'Class',\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "# --- 2. Initialize a Dictionary to Store Results ---\n", - "results = {\n", - " 'Metric': [],\n", - " 'Mean_Satisfied': [],\n", - " 'Mean_Dissatisfied': [],\n", - " 'T_Statistic': [],\n", - " 'P_Value': [],\n", - " 'Significance (α=0.05)': []\n", - "}\n", - "\n", - "# --- 3. Loop Through Columns and Perform T-Test ---\n", - "for col in metric_columns:\n", - " # 3a. Isolate and clean data for the current column\n", - " data_sat = dfSatisfied[col].dropna()\n", - " data_dis = dfDisatisfied[col].dropna()\n", - "\n", - " # Skip if one of the groups has no data\n", - " if len(data_sat) == 0 or len(data_dis) == 0:\n", - " continue\n", - "\n", - " # 3b. Perform Welch's T-Test (equal_var=False)\n", - " t_stat, p_value = stats.ttest_ind(\n", - " a=data_sat,\n", - " b=data_dis,\n", - " equal_var=False\n", - " )\n", - "\n", - " # 3c. Store Results\n", - " is_significant = 'Yes (Reject H0)' if p_value <= 0.05 else 'No (Fail to Reject H0)'\n", - "\n", - " results['Metric'].append(col)\n", - " results['Mean_Satisfied'].append(data_sat.mean())\n", - " results['Mean_Dissatisfied'].append(data_dis.mean())\n", - " results['T_Statistic'].append(t_stat)\n", - " results['P_Value'].append(p_value)\n", - " results['Significance (α=0.05)'].append(is_significant)\n", - "\n", - "# --- 4. Convert Results Dictionary to a DataFrame ---\n", - "results_df = pd.DataFrame(results)\n", - "\n", - "# --- 5. Print/Display Results ---\n", - "print(results_df.round(4))" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "3e5ecb36-ada2-4925-9e0d-2ae0996881c7", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['id',\n", - " 'Gender',\n", - " 'Customer Type',\n", - " 'Age',\n", - " 'Type of Travel',\n", - " 'Class',\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " 'satisfaction',\n", - " 'satisfaction_binary']" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "list(df)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "247db4d7-3a0d-4c98-ab26-f537b049e252", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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10389860666MaleLoyal Customer50Personal TravelEco1620313...43424200.0neutral or dissatisfied0
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58879 rows × 25 columns

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satisfactionneutral or dissatisfiedsatisfied
MetricStatistic
Agemean37.56668841.750583
median36.00000043.000000
std16.45982512.767833
Arrival Delay in Minutesmean17.12753612.630799
median0.0000000.000000
std40.56024835.962008
Baggage handlingmean3.3759913.966396
median4.0000004.000000
std1.1769781.099607
Checkin servicemean3.0429523.646041
median3.0000004.000000
std1.2811581.158732
Cleanlinessmean2.9361233.744342
median3.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.000000
std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.000000
std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.000000
std1.1756031.091486
Inflight wifi servicemean2.3996333.161288
median2.0000004.000000
std0.9643481.588697
Leg room servicemean2.9908123.822143
median3.0000004.000000
std1.3031591.175515
On-board servicemean3.0191583.857324
median3.0000004.000000
std1.2857901.127130
Online boardingmean2.6561254.027474
median3.0000004.000000
std1.1459051.191609
Seat comfortmean3.0362953.966530
median3.0000004.000000
std1.3031421.142077
\n", - "
" - ], - "text/plain": [ - "satisfaction neutral or dissatisfied \\\n", - "Metric Statistic \n", - "Age mean 37.566688 \n", - " median 36.000000 \n", - " std 16.459825 \n", - "Arrival Delay in Minutes mean 17.127536 \n", - " median 0.000000 \n", - " std 40.560248 \n", - "Baggage handling mean 3.375991 \n", - " median 4.000000 \n", - " std 1.176978 \n", - "Checkin service mean 3.042952 \n", - " median 3.000000 \n", - " std 1.281158 \n", - "Cleanliness mean 2.936123 \n", - " median 3.000000 \n", - " std 1.325955 \n", - "Departure Delay in Minutes mean 16.503728 \n", - " median 0.000000 \n", - " std 40.191886 \n", - "Departure/Arrival time convenient mean 3.129112 \n", - " median 3.000000 \n", - " std 1.500368 \n", - "Ease of Online booking mean 2.546850 \n", - " median 3.000000 \n", - " std 1.205847 \n", - "Flight Distance mean 928.919971 \n", - " median 671.000000 \n", - " std 790.452308 \n", - "Food and drink mean 2.958050 \n", - " median 3.000000 \n", - " std 1.346607 \n", - "Gate location mean 2.976121 \n", - " median 3.000000 \n", - " std 1.198500 \n", - "Inflight entertainment mean 2.894156 \n", - " median 3.000000 \n", - " std 1.323619 \n", - "Inflight service mean 3.388814 \n", - " median 4.000000 \n", - " std 1.175603 \n", - "Inflight wifi service mean 2.399633 \n", - " median 2.000000 \n", - " std 0.964348 \n", - "Leg room service mean 2.990812 \n", - " median 3.000000 \n", - " std 1.303159 \n", - "On-board service mean 3.019158 \n", - " median 3.000000 \n", - " std 1.285790 \n", - "Online boarding mean 2.656125 \n", - " median 3.000000 \n", - " std 1.145905 \n", - "Seat comfort mean 3.036295 \n", - " median 3.000000 \n", - " std 1.303142 \n", - "\n", - "satisfaction satisfied \n", - "Metric Statistic \n", - "Age mean 41.750583 \n", - " median 43.000000 \n", - " std 12.767833 \n", - "Arrival Delay in Minutes mean 12.630799 \n", - " median 0.000000 \n", - " std 35.962008 \n", - "Baggage handling mean 3.966396 \n", - " median 4.000000 \n", - " std 1.099607 \n", - "Checkin service mean 3.646041 \n", - " median 4.000000 \n", - " std 1.158732 \n", - "Cleanliness mean 3.744342 \n", - " median 4.000000 \n", - " std 1.142247 \n", - "Departure Delay in Minutes mean 12.608084 \n", - " median 0.000000 \n", - " std 35.382595 \n", - "Departure/Arrival time convenient mean 2.970305 \n", - " median 3.000000 \n", - " std 1.552213 \n", - "Ease of Online booking mean 3.031582 \n", - " median 3.000000 \n", - " std 1.575306 \n", - "Flight Distance mean 1530.140255 \n", - " median 1250.000000 \n", - " std 1128.126574 \n", - "Food and drink mean 3.521310 \n", - " median 4.000000 \n", - " std 1.236187 \n", - "Gate location mean 2.977879 \n", - " median 3.000000 \n", - " std 1.374244 \n", - "Inflight entertainment mean 3.964931 \n", - " median 4.000000 \n", - " std 1.076907 \n", - "Inflight service mean 3.969461 \n", - " median 4.000000 \n", - " std 1.091486 \n", - "Inflight wifi service mean 3.161288 \n", - " median 4.000000 \n", - " std 1.588697 \n", - "Leg room service mean 3.822143 \n", - " median 4.000000 \n", - " std 1.175515 \n", - "On-board service mean 3.857324 \n", - " median 4.000000 \n", - " std 1.127130 \n", - "Online boarding mean 4.027474 \n", - " median 4.000000 \n", - " std 1.191609 \n", - "Seat comfort mean 3.966530 \n", - " median 4.000000 \n", - " std 1.142077 " - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "numeric_cols_df = df.select_dtypes(include=np.number)\n", - "\n", - "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", - "metrics_to_analyze = [\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " 'Age' # Including age as a numeric metric to analyze\n", - "]\n", - "\n", - "# Filter down to the columns that actually exist and are numeric\n", - "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", - "\n", - "# --- 2. Melt the DataFrame ---\n", - "df_melted = df.melt(\n", - " id_vars=['satisfaction'],\n", - " value_vars=analysis_cols,\n", - " var_name='Metric', # This column now holds the name of the original column\n", - " value_name='Value' # This column now holds the numeric data\n", - ")\n", - "\n", - "# --- 3. Create the Pivot Table ---\n", - "pivot_stats = pd.pivot_table(\n", - " df_melted,\n", - " index=['Metric'],\n", - " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", - " values='Value',\n", - " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", - ")\n", - "\n", - "# --- 4. Re-orient to Vertical View ---\n", - "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", - "vertical_stats_table = pivot_stats.stack(level=0)\n", - "\n", - "# Rename the new index level for clarity\n", - "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", - "\n", - "# Display the final vertical table\n", - "vertical_stats_table" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "69231728-91ed-4a46-ae0c-826b298928b8", - "metadata": {}, - "outputs": [], - "source": [ - "# # --- 1. Define the CORRECTED Palette Dictionary ---\n", - "# # We use 'neutral or dissatisfied' as the key, mapped to a color.\n", - "# correct_palette = {\n", - "# 'satisfied': 'tab:blue',\n", - "# 'neutral or dissatisfied': 'tab:orange' # Mapped to orange, representing the non-satisfied group\n", - "# }\n", - "\n", - "# # --- 2. Create the Grouped Bar Plot with the new palette ---\n", - "# plt.figure(figsize=(16, 8))\n", - "\n", - "# sns.barplot(\n", - "# data=df_melted,\n", - "# x='Metric',\n", - "# y='Value',\n", - "# hue='satisfaction',\n", - "# errorbar='sd',\n", - "# palette=correct_palette # Use the corrected dictionary\n", - "# )\n", - "\n", - "# # --- 3. Format the Chart (rest of the code) ---\n", - "# plt.title('Mean of All Metrics Grouped by Satisfaction Status', fontsize=16)\n", - "# plt.ylabel('Mean Value (Mixed Scales)', fontsize=14)\n", - "# plt.xlabel('Metric', fontsize=14)\n", - "# plt.xticks(rotation=45, ha='right')\n", - "# plt.tight_layout()\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "2599980d-0244-44e9-bcd4-5cd3d5cb2d23", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "# from sklearn.preprocessing import MinMaxScaler\n", - "# import matplotlib.pyplot as plt\n", - "# import seaborn as sns\n", - "\n", - "# # Assuming 'df' is your original DataFrame\n", - "# # ----------------------------------------------------\n", - "# # 1. Identify the numeric metric columns to scale\n", - "# # (Excluding categorical, ID, and the 'satisfaction' column)\n", - "\n", - "# metrics_to_scale = [\n", - "# 'Flight Distance', 'Inflight wifi service', 'Departure/Arrival time convenient',\n", - "# 'Ease of Online booking', 'Gate location', 'Food and drink', 'Online boarding',\n", - "# 'Seat comfort', 'Inflight entertainment', 'On-board service', 'Leg room service',\n", - "# 'Baggage handling', 'Checkin service', 'Inflight service', 'Cleanliness',\n", - "# 'Departure Delay in Minutes', 'Arrival Delay in Minutes', 'Age'\n", - "# ]\n", - "\n", - "# # Create a copy of the DataFrame columns to scale\n", - "# df_scaled = df[metrics_to_scale].copy()\n", - "\n", - "# # Initialize the scaler\n", - "# scaler = MinMaxScaler()\n", - "\n", - "# # Apply scaler to all columns in the copy\n", - "# df_scaled[metrics_to_scale] = scaler.fit_transform(df_scaled[metrics_to_scale])\n", - "\n", - "# # Merge the scaled metrics back into the original DataFrame (or a new one)\n", - "# df_normalized = df[['satisfaction']].copy()\n", - "# df_normalized = pd.concat([df_normalized, df_scaled], axis=1)\n", - "\n", - "# # ----------------------------------------------------\n", - "# # 2. Melt the Scaled Data\n", - "\n", - "# # Use the normalized DataFrame for melting\n", - "# df_melted_normalized = df_normalized.melt(\n", - "# id_vars=['satisfaction'],\n", - "# value_vars=metrics_to_scale,\n", - "# var_name='Metric',\n", - "# value_name='Normalized_Value' # New column name for the scaled values\n", - "# )\n", - "\n", - "# # ----------------------------------------------------\n", - "# # 3. Plot the Scaled Data\n", - "\n", - "# plt.figure(figsize=(16, 8))\n", - "\n", - "# correct_palette = {\n", - "# 'satisfied': 'tab:blue',\n", - "# 'neutral or dissatisfied': 'tab:orange'\n", - "# }\n", - "\n", - "# sns.barplot(\n", - "# data=df_melted_normalized,\n", - "# x='Metric',\n", - "# y='Normalized_Value', # Plotting the 0-to-1 scaled values\n", - "# hue='satisfaction',\n", - "# errorbar='sd',\n", - "# palette=correct_palette\n", - "# )\n", - "\n", - "# # --- Format the Chart ---\n", - "# plt.title('Mean of All Metrics Grouped by Satisfaction Status (Normalized)', fontsize=16)\n", - "# plt.ylabel('Normalized Mean Value (Range: 0 to 1)', fontsize=14)\n", - "# plt.xlabel('Metric', fontsize=14)\n", - "# plt.xticks(rotation=45, ha='right')\n", - "# plt.tight_layout()\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", - "metadata": {}, - "outputs": [], - "source": [ - "# import matplotlib.pyplot as plt\n", - "# import seaborn as sns\n", - "# import pandas as pd\n", - "# # Assuming df_melted is already in your environment from previous steps\n", - "\n", - "# # --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", - "# filtered_metrics_1to5 = [\n", - "# 'Inflight wifi service',\n", - "# 'Departure/Arrival time convenient',\n", - "# 'Ease of Online booking',\n", - "# 'Gate location',\n", - "# 'Food and drink',\n", - "# 'Online boarding',\n", - "# 'Seat comfort',\n", - "# 'Inflight entertainment',\n", - "# 'On-board service',\n", - "# 'Leg room service',\n", - "# 'Baggage handling',\n", - "# 'Checkin service',\n", - "# 'Inflight service',\n", - "# 'Cleanliness',\n", - "# ]\n", - "\n", - "# # --- 2. Filter the df_melted DataFrame ---\n", - "# # Only keep rows where the 'Metric' is in the list above\n", - "# df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", - "\n", - "\n", - "# # --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", - "# correct_palette = {\n", - "# 'satisfied': 'tab:blue',\n", - "# 'neutral or dissatisfied': 'tab:orange'\n", - "# }\n", - "\n", - "# # --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", - "# plt.figure(figsize=(16, 8))\n", - "\n", - "# sns.barplot(\n", - "# data=df_melted_filtered_1to5, # Using the filtered data\n", - "# x='Metric',\n", - "# y='Value',\n", - "# hue='satisfaction',\n", - "# errorbar='sd',\n", - "# palette=correct_palette\n", - "# )\n", - "\n", - "# # --- 5. Format the Chart ---\n", - "# plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", - "# plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", - "# plt.xlabel('Metric', fontsize=14)\n", - "# plt.xticks(rotation=45, ha='right')\n", - "# plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", - "# plt.tight_layout()\n", - "# plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "350b26b2-5a25-43aa-9ca2-c2b7edd64774", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "Mean Satisfied: 3.161\n", - "Mean Dissatisfied: 2.400\n", - "--------------------------------------\n", - "T-Statistic: 89.8547\n", - "P-Value: 0.0000000000\n" - ] - } - ], - "source": [ - "satisfied_ratings = dfSatisfied['Inflight wifi service'].dropna()\n", - "dissatisfied_ratings = dfDisatisfied['Inflight wifi service'].dropna()\n", - "\n", - "# Perform the Two-Sample T-Test (Welch's)\n", - "t_statistic, p_value = stats.ttest_ind(\n", - " a=satisfied_ratings,\n", - " b=dissatisfied_ratings,\n", - " equal_var=False\n", - ")\n", - "\n", - "# --- Output the Results ---\n", - "print(f\"--- T-Test Results for Inflight wifi service ---\")\n", - "print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", - "print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", - "print(\"-\" * 38)\n", - "print(f\"T-Statistic: {t_statistic:.4f}\")\n", - "print(f\"P-Value: {p_value:.10f}\")" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "5a2bf756-8500-4adc-99af-1c48cd7e1d37", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "Mean Satisfied: 2.400\n", - "Mean Dissatisfied: 2.394\n", - "T-Statistic: 0.6064\n", - "P-Value: 0.5442639813\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "Mean Satisfied: 3.129\n", - "Mean Dissatisfied: 2.287\n", - "T-Statistic: 64.7514\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "Mean Satisfied: 2.547\n", - "Mean Dissatisfied: 2.394\n", - "T-Statistic: 15.5027\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "Mean Satisfied: 2.976\n", - "Mean Dissatisfied: 3.046\n", - "T-Statistic: -6.8515\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "Mean Satisfied: 2.958\n", - "Mean Dissatisfied: 3.011\n", - "T-Statistic: -4.1709\n", - "P-Value: 0.0000304613\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "Mean Satisfied: 2.656\n", - "Mean Dissatisfied: 2.425\n", - "T-Statistic: 23.2966\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "Mean Satisfied: 3.036\n", - "Mean Dissatisfied: 2.986\n", - "T-Statistic: 3.9404\n", - "P-Value: 0.0000816032\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "Mean Satisfied: 2.894\n", - "Mean Dissatisfied: 3.031\n", - "T-Statistic: -10.6884\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "Mean Satisfied: 3.019\n", - "Mean Dissatisfied: 3.078\n", - "T-Statistic: -4.9255\n", - "P-Value: 0.0000008475\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "Mean Satisfied: 2.991\n", - "Mean Dissatisfied: 3.166\n", - "T-Statistic: -14.1632\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "Mean Satisfied: 3.376\n", - "Mean Dissatisfied: 3.565\n", - "T-Statistic: -18.5273\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "Mean Satisfied: 3.043\n", - "Mean Dissatisfied: 3.059\n", - "T-Statistic: -1.3296\n", - "P-Value: 0.1836795869\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "Mean Satisfied: 3.389\n", - "Mean Dissatisfied: 3.570\n", - "T-Statistic: -17.6556\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "Mean Satisfied: 2.936\n", - "Mean Dissatisfied: 3.045\n", - "T-Statistic: -8.4732\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "Mean Satisfied: 16.504\n", - "Mean Dissatisfied: 15.856\n", - "T-Statistic: 1.7952\n", - "P-Value: 0.0726400300\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "Mean Satisfied: 17.128\n", - "Mean Dissatisfied: 16.484\n", - "T-Statistic: 1.7473\n", - "P-Value: 0.0805987692\n", - "--------------------------------------\n" - ] - } - ], - "source": [ - "# --- 1. Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", - "\n", - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "for col in metric_columns: \n", - " satisfied_ratings = dfDisatisfied[col].dropna()\n", - " dissatisfied_ratings = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=satisfied_ratings,\n", - " b=dissatisfied_ratings,\n", - " equal_var=False\n", - " )\n", - "\n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", - " print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "91a9b0cd-b1f0-4851-8439-cf30868a1bf6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online booking...On-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfactionsatisfaction_binary
070172MaleLoyal Customer13Personal TravelEco Plus460343...4344552518.0neutral or dissatisfied0
15047Maledisloyal Customer25Business travelBusiness235323...15314116.0neutral or dissatisfied0
2110028FemaleLoyal Customer26Business travelBusiness1142222...43444500.0satisfied1
324026FemaleLoyal Customer25Business travelBusiness562255...253142119.0neutral or dissatisfied0
4119299MaleLoyal Customer61Business travelBusiness214333...34433300.0satisfied1
..................................................................
10389994171Femaledisloyal Customer23Business travelEco192212...31423230.0neutral or dissatisfied0
10390073097MaleLoyal Customer49Business travelBusiness2347444...55555400.0satisfied1
10390168825Maledisloyal Customer30Business travelBusiness1995111...324554714.0neutral or dissatisfied0
10390254173Femaledisloyal Customer22Business travelEco1000111...45154100.0neutral or dissatisfied0
10390362567MaleLoyal Customer27Business travelBusiness1723133...11443100.0neutral or dissatisfied0
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103904 rows × 25 columns

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" - ], - "text/plain": [ - " id Gender Customer Type Age Type of Travel Class \\\n", - "0 70172 Male Loyal Customer 13 Personal Travel Eco Plus \n", - "1 5047 Male disloyal Customer 25 Business travel Business \n", - "2 110028 Female Loyal Customer 26 Business travel Business \n", - "3 24026 Female Loyal Customer 25 Business travel Business \n", - "4 119299 Male Loyal Customer 61 Business travel Business \n", - "... ... ... ... ... ... ... \n", - "103899 94171 Female disloyal Customer 23 Business travel Eco \n", - "103900 73097 Male Loyal Customer 49 Business travel Business \n", - "103901 68825 Male disloyal Customer 30 Business travel Business \n", - "103902 54173 Female disloyal Customer 22 Business travel Eco \n", - "103903 62567 Male Loyal Customer 27 Business travel Business \n", - "\n", - " Flight Distance Inflight wifi service \\\n", - "0 460 3 \n", - "1 235 3 \n", - "2 1142 2 \n", - "3 562 2 \n", - "4 214 3 \n", - "... ... ... \n", - "103899 192 2 \n", - "103900 2347 4 \n", - "103901 1995 1 \n", - "103902 1000 1 \n", - "103903 1723 1 \n", - "\n", - " Departure/Arrival time convenient Ease of Online booking ... \\\n", - "0 4 3 ... \n", - "1 2 3 ... \n", - "2 2 2 ... \n", - "3 5 5 ... \n", - "4 3 3 ... \n", - "... ... ... ... \n", - "103899 1 2 ... \n", - "103900 4 4 ... \n", - "103901 1 1 ... \n", - "103902 1 1 ... \n", - "103903 3 3 ... \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "0 4 3 4 4 \n", - "1 1 5 3 1 \n", - "2 4 3 4 4 \n", - "3 2 5 3 1 \n", - "4 3 4 4 3 \n", - "... ... ... ... ... \n", - "103899 3 1 4 2 \n", - "103900 5 5 5 5 \n", - "103901 3 2 4 5 \n", - "103902 4 5 1 5 \n", - "103903 1 1 4 4 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "0 5 5 25 \n", - "1 4 1 1 \n", - "2 4 5 0 \n", - "3 4 2 11 \n", - "4 3 3 0 \n", - "... ... ... ... \n", - "103899 3 2 3 \n", - "103900 5 4 0 \n", - "103901 5 4 7 \n", - "103902 4 1 0 \n", - "103903 3 1 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction satisfaction_binary \n", - "0 18.0 neutral or dissatisfied 0 \n", - "1 6.0 neutral or dissatisfied 0 \n", - "2 0.0 satisfied 1 \n", - "3 9.0 neutral or dissatisfied 0 \n", - "4 0.0 satisfied 1 \n", - "... ... ... ... \n", - "103899 0.0 neutral or dissatisfied 0 \n", - "103900 0.0 satisfied 1 \n", - "103901 14.0 neutral or dissatisfied 0 \n", - "103902 0.0 neutral or dissatisfied 0 \n", - "103903 0.0 neutral or dissatisfied 0 \n", - "\n", - "[103904 rows x 25 columns]" - ] - }, - "execution_count": 25, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 63, - "id": "60a773e7-2487-47bd-b868-94f7b60bf471", - "metadata": {}, - "outputs": [], - "source": [ - "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", - "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", - "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" - ] - }, - { - "cell_type": "code", - "execution_count": 44, - "id": "a75fd6ab-fb8e-4ef8-ab12-ac19c28bc21a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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idAgeFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online bookingGate locationFood and drinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction_binarymedian4.0000004.000000
count14489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014489.00000014448.00000014489.0std1.1769781.099607
Checkin servicemean63540.05245431.096694709.7154392.3942302.2871142.3940923.0458973.0113192.4254262.9855063.0305753.0780593.1661953.5647043.0589413.5698123.04451715.85644316.4843580.03.0429523.646041
median3.0000004.000000
std37439.97520311.286122507.4819850.9599291.3769621.0242011.0720351.3846241.0477181.4103761.3889371.2904071.3430651.0781061.3005561.0874781.39228338.55147639.4044460.01.2811581.158732
min1.0000007.00000031.0000001.0000000.0000000.0000001.0000000.0000000.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000001.0000000.0000000.0000000.0Cleanlinessmean2.9361233.744342
25%31094.00000023.000000337.0000002.0000001.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000003.0000002.000000median3.0000002.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.0000000.0
50%61418.00000028.000000590.0000002.0000002.0000002.0000003.0000003.0000002.000000std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.0000004.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.0000003.0000000.0000000.0000000.0
75%96500.00000037.000000960.0000003.000000std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.0000004.0000004.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.0000004.0000004.0000004.0000004.0000004.00000014.00000015.0000000.0
max129871.00000085.0000004963.0000004.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.000000921.000000924.0000000.0std1.1756031.091486
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" - ], - "text/plain": [ - " id Age Flight Distance Inflight wifi service \\\n", - "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", - "mean 63540.052454 31.096694 709.715439 2.394230 \n", - "std 37439.975203 11.286122 507.481985 0.959929 \n", - "min 1.000000 7.000000 31.000000 1.000000 \n", - "25% 31094.000000 23.000000 337.000000 2.000000 \n", - "50% 61418.000000 28.000000 590.000000 2.000000 \n", - "75% 96500.000000 37.000000 960.000000 3.000000 \n", - "max 129871.000000 85.000000 4963.000000 4.000000 \n", - "\n", - " Departure/Arrival time convenient Ease of Online booking \\\n", - "count 14489.000000 14489.000000 \n", - "mean 2.287114 2.394092 \n", - "std 1.376962 1.024201 \n", - "min 0.000000 0.000000 \n", - "25% 1.000000 2.000000 \n", - "50% 2.000000 2.000000 \n", - "75% 3.000000 3.000000 \n", - "max 5.000000 5.000000 \n", - "\n", - " Gate location Food and drink Online boarding Seat comfort \\\n", - "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", - "mean 3.045897 3.011319 2.425426 2.985506 \n", - "std 1.072035 1.384624 1.047718 1.410376 \n", - "min 1.000000 0.000000 0.000000 1.000000 \n", - "25% 2.000000 2.000000 2.000000 2.000000 \n", - "50% 3.000000 3.000000 2.000000 3.000000 \n", - "75% 4.000000 4.000000 3.000000 4.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Inflight entertainment On-board service Leg room service \\\n", - "count 14489.000000 14489.000000 14489.000000 \n", - "mean 3.030575 3.078059 3.166195 \n", - "std 1.388937 1.290407 1.343065 \n", - "min 1.000000 1.000000 1.000000 \n", - "25% 2.000000 2.000000 2.000000 \n", - "50% 3.000000 3.000000 3.000000 \n", - "75% 4.000000 4.000000 4.000000 \n", - "max 5.000000 5.000000 5.000000 \n", - "\n", - " Baggage handling Checkin service Inflight service Cleanliness \\\n", - "count 14489.000000 14489.000000 14489.000000 14489.000000 \n", - "mean 3.564704 3.058941 3.569812 3.044517 \n", - "std 1.078106 1.300556 1.087478 1.392283 \n", - "min 1.000000 1.000000 1.000000 1.000000 \n", - "25% 3.000000 2.000000 3.000000 2.000000 \n", - "50% 4.000000 3.000000 4.000000 3.000000 \n", - "75% 4.000000 4.000000 4.000000 4.000000 \n", - "max 5.000000 5.000000 5.000000 5.000000 \n", - "\n", - " Departure Delay in Minutes Arrival Delay in Minutes \\\n", - "count 14489.000000 14448.000000 \n", - "mean 15.856443 16.484358 \n", - "std 38.551476 39.404446 \n", - "min 0.000000 0.000000 \n", - "25% 0.000000 0.000000 \n", - "50% 0.000000 0.000000 \n", - "75% 14.000000 15.000000 \n", - "max 921.000000 924.000000 \n", - "\n", - " satisfaction_binary \n", - "count 14489.0 \n", - "mean 0.0 \n", - "std 0.0 \n", - "min 0.0 \n", - "25% 0.0 \n", - "50% 0.0 \n", - "75% 0.0 \n", - "max 0.0 " - ] - }, - "execution_count": 44, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfDisatisfied_disloyal.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "6ad6e2d8-eed3-446e-ae43-a6c5e127c8be", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 40533\n", - "disloyal Customer 4492\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 30, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfSatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "d4e77057-6266-4cd6-b6dc-4647799d96ff", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 44390\n", - "disloyal Customer 14489\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 29, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfDisatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 46, - "id": "07ee2084-a56b-4321-a025-d13bb9e510dc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online booking...On-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfactionsatisfaction_binary
Inflight wifi servicemean2.3996333.161288
15047Maledisloyal Customer25Business travelBusiness235323...15314116.0neutral or dissatisfied0median2.0000004.000000
965725Maledisloyal Customer20Business travelEco1061333...23443200.0neutral or dissatisfied0std0.9643481.588697
1034991Femaledisloyal Customer24Business travelEco1182455...33535200.0neutral or dissatisfied0Leg room servicemean2.9908123.822143
15100580Maledisloyal Customer13Business travelEco486212...21413410.0neutral or dissatisfied0median3.0000004.000000
3127809Femaledisloyal Customer15Business travelEco1043222...31424530.0neutral or dissatisfied0std1.3031591.175515
..................................................................On-board servicemean3.0191583.857324
median3.0000004.000000
10389246016Femaledisloyal Customer37Business travelBusiness596333...113143110121.0neutral or dissatisfied0std1.2857901.127130
10389566030Femaledisloyal Customer24Business travelEco1055111...3355411310.0neutral or dissatisfied0Online boardingmean2.6561254.027474
10389994171Femaledisloyal Customer23Business travelEco192212...31423230.0neutral or dissatisfied0median3.0000004.000000
10390168825Maledisloyal Customer30Business travelBusiness1995111...324554714.0neutral or dissatisfied0std1.1459051.191609
10390254173Femaledisloyal Customer22Business travelEco1000111...45154100.0neutral or dissatisfied0Seat comfortmean3.0362953.966530
median3.0000004.000000
std1.3031421.142077
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14489 rows × 25 columns

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" ], "text/plain": [ - " id Gender Customer Type Age Type of Travel Class \\\n", - "1 5047 Male disloyal Customer 25 Business travel Business \n", - "9 65725 Male disloyal Customer 20 Business travel Eco \n", - "10 34991 Female disloyal Customer 24 Business travel Eco \n", - "15 100580 Male disloyal Customer 13 Business travel Eco \n", - "31 27809 Female disloyal Customer 15 Business travel Eco \n", - "... ... ... ... ... ... ... \n", - "103892 46016 Female disloyal Customer 37 Business travel Business \n", - "103895 66030 Female disloyal Customer 24 Business travel Eco \n", - "103899 94171 Female disloyal Customer 23 Business travel Eco \n", - "103901 68825 Male disloyal Customer 30 Business travel Business \n", - "103902 54173 Female disloyal Customer 22 Business travel Eco \n", - "\n", - " Flight Distance Inflight wifi service \\\n", - "1 235 3 \n", - "9 1061 3 \n", - "10 1182 4 \n", - "15 486 2 \n", - "31 1043 2 \n", - "... ... ... \n", - "103892 596 3 \n", - "103895 1055 1 \n", - "103899 192 2 \n", - "103901 1995 1 \n", - "103902 1000 1 \n", - "\n", - " Departure/Arrival time convenient Ease of Online booking ... \\\n", - "1 2 3 ... \n", - "9 3 3 ... \n", - "10 5 5 ... \n", - "15 1 2 ... \n", - "31 2 2 ... \n", - "... ... ... ... \n", - "103892 3 3 ... \n", - "103895 1 1 ... \n", - "103899 1 2 ... \n", - "103901 1 1 ... \n", - "103902 1 1 ... \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "1 1 5 3 1 \n", - "9 2 3 4 4 \n", - "10 3 3 5 3 \n", - "15 2 1 4 1 \n", - "31 3 1 4 2 \n", - "... ... ... ... ... \n", - "103892 1 1 3 1 \n", - "103895 3 3 5 5 \n", - "103899 3 1 4 2 \n", - "103901 3 2 4 5 \n", - "103902 4 5 1 5 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "1 4 1 1 \n", - "9 3 2 0 \n", - "10 5 2 0 \n", - "15 3 4 1 \n", - "31 4 5 3 \n", - "... ... ... ... \n", - "103892 4 3 110 \n", - "103895 4 1 13 \n", - "103899 3 2 3 \n", - "103901 5 4 7 \n", - "103902 4 1 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction satisfaction_binary \n", - "1 6.0 neutral or dissatisfied 0 \n", - "9 0.0 neutral or dissatisfied 0 \n", - "10 0.0 neutral or dissatisfied 0 \n", - "15 0.0 neutral or dissatisfied 0 \n", - "31 0.0 neutral or dissatisfied 0 \n", - "... ... ... ... \n", - "103892 121.0 neutral or dissatisfied 0 \n", - "103895 10.0 neutral or dissatisfied 0 \n", - "103899 0.0 neutral or dissatisfied 0 \n", - "103901 14.0 neutral or dissatisfied 0 \n", - "103902 0.0 neutral or dissatisfied 0 \n", + "satisfaction neutral or dissatisfied \\\n", + "Metric Statistic \n", + "Age mean 37.566688 \n", + " median 36.000000 \n", + " std 16.459825 \n", + "Arrival Delay in Minutes mean 17.127536 \n", + " median 0.000000 \n", + " std 40.560248 \n", + "Baggage handling mean 3.375991 \n", + " median 4.000000 \n", + " std 1.176978 \n", + "Checkin service mean 3.042952 \n", + " median 3.000000 \n", + " std 1.281158 \n", + "Cleanliness mean 2.936123 \n", + " median 3.000000 \n", + " std 1.325955 \n", + "Departure Delay in Minutes mean 16.503728 \n", + " median 0.000000 \n", + " std 40.191886 \n", + "Departure/Arrival time convenient mean 3.129112 \n", + " median 3.000000 \n", + " std 1.500368 \n", + "Ease of Online booking mean 2.546850 \n", + " median 3.000000 \n", + " std 1.205847 \n", + "Flight Distance mean 928.919971 \n", + " median 671.000000 \n", + " std 790.452308 \n", + "Food and drink mean 2.958050 \n", + " median 3.000000 \n", + " std 1.346607 \n", + "Gate location mean 2.976121 \n", + " median 3.000000 \n", + " std 1.198500 \n", + "Inflight entertainment mean 2.894156 \n", + " median 3.000000 \n", + " std 1.323619 \n", + "Inflight service mean 3.388814 \n", + " median 4.000000 \n", + " std 1.175603 \n", + "Inflight wifi service mean 2.399633 \n", + " median 2.000000 \n", + " std 0.964348 \n", + "Leg room service mean 2.990812 \n", + " median 3.000000 \n", + " std 1.303159 \n", + "On-board service mean 3.019158 \n", + " median 3.000000 \n", + " std 1.285790 \n", + "Online boarding mean 2.656125 \n", + " median 3.000000 \n", + " std 1.145905 \n", + "Seat comfort mean 3.036295 \n", + " median 3.000000 \n", + " std 1.303142 \n", "\n", - "[14489 rows x 25 columns]" + "satisfaction satisfied \n", + "Metric Statistic \n", + "Age mean 41.750583 \n", + " median 43.000000 \n", + " std 12.767833 \n", + "Arrival Delay in Minutes mean 12.630799 \n", + " median 0.000000 \n", + " std 35.962008 \n", + "Baggage handling mean 3.966396 \n", + " median 4.000000 \n", + " std 1.099607 \n", + "Checkin service mean 3.646041 \n", + " median 4.000000 \n", + " std 1.158732 \n", + "Cleanliness mean 3.744342 \n", + " median 4.000000 \n", + " std 1.142247 \n", + "Departure Delay in Minutes mean 12.608084 \n", + " median 0.000000 \n", + " std 35.382595 \n", + "Departure/Arrival time convenient mean 2.970305 \n", + " median 3.000000 \n", + " std 1.552213 \n", + "Ease of Online booking mean 3.031582 \n", + " median 3.000000 \n", + " std 1.575306 \n", + "Flight Distance mean 1530.140255 \n", + " median 1250.000000 \n", + " std 1128.126574 \n", + "Food and drink mean 3.521310 \n", + " median 4.000000 \n", + " std 1.236187 \n", + "Gate location mean 2.977879 \n", + " median 3.000000 \n", + " std 1.374244 \n", + "Inflight entertainment mean 3.964931 \n", + " median 4.000000 \n", + " std 1.076907 \n", + "Inflight service mean 3.969461 \n", + " median 4.000000 \n", + " std 1.091486 \n", + "Inflight wifi service mean 3.161288 \n", + " median 4.000000 \n", + " std 1.588697 \n", + "Leg room service mean 3.822143 \n", + " median 4.000000 \n", + " std 1.175515 \n", + "On-board service mean 3.857324 \n", + " median 4.000000 \n", + " std 1.127130 \n", + "Online boarding mean 4.027474 \n", + " median 4.000000 \n", + " std 1.191609 \n", + "Seat comfort mean 3.966530 \n", + " median 4.000000 \n", + " std 1.142077 " ] }, - "execution_count": 46, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "dfDisatisfied_disloyal" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9b45c0ab-c959-4130-820f-19a659973ecb", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "1cb9c038-2d28-4203-8cce-0146b91182e1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1: 2.400\n", - "df_2: 2.394\n", - "T-Statistic: 0.6064\n", - "P-Value: 0.5442639813\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1: 3.129\n", - "df_2: 2.287\n", - "T-Statistic: 64.7514\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1: 2.547\n", - "df_2: 2.394\n", - "T-Statistic: 15.5027\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1: 2.976\n", - "df_2: 3.046\n", - "T-Statistic: -6.8515\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1: 2.958\n", - "df_2: 3.011\n", - "T-Statistic: -4.1709\n", - "P-Value: 0.0000304613\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1: 2.656\n", - "df_2: 2.425\n", - "T-Statistic: 23.2966\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1: 3.036\n", - "df_2: 2.986\n", - "T-Statistic: 3.9404\n", - "P-Value: 0.0000816032\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1: 2.894\n", - "df_2: 3.031\n", - "T-Statistic: -10.6884\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1: 3.019\n", - "df_2: 3.078\n", - "T-Statistic: -4.9255\n", - "P-Value: 0.0000008475\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1: 2.991\n", - "df_2: 3.166\n", - "T-Statistic: -14.1632\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1: 3.376\n", - "df_2: 3.565\n", - "T-Statistic: -18.5273\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1: 3.043\n", - "df_2: 3.059\n", - "T-Statistic: -1.3296\n", - "P-Value: 0.1836795869\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1: 3.389\n", - "df_2: 3.570\n", - "T-Statistic: -17.6556\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1: 2.936\n", - "df_2: 3.045\n", - "T-Statistic: -8.4732\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1: 16.504\n", - "df_2: 15.856\n", - "T-Statistic: 1.7952\n", - "P-Value: 0.0726400300\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1: 17.128\n", - "df_2: 16.484\n", - "T-Statistic: 1.7473\n", - "P-Value: 0.0805987692\n", - "--------------------------------------\n" - ] - } - ], - "source": [ - "# --- 1. Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "numeric_cols_df = df.select_dtypes(include=np.number)\n", "\n", - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", + "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", + "metrics_to_analyze = [\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " 'Age' # Including age as a numeric metric to analyze\n", "]\n", "\n", - "for col in metric_columns: \n", - " df_1 = dfDisatisfied[col].dropna()\n", - " df_2 = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1,\n", - " b=df_2,\n", - " equal_var=False\n", - " )\n", - " \n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1: {df_1.mean():.3f}\")\n", - " print(f\"df_2: {df_2.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" + "# Filter down to the columns that actually exist and are numeric\n", + "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", + "\n", + "# --- 2. Melt the DataFrame ---\n", + "df_melted = df.melt(\n", + " id_vars=['satisfaction'],\n", + " value_vars=analysis_cols,\n", + " var_name='Metric', # This column now holds the name of the original column\n", + " value_name='Value' # This column now holds the numeric data\n", + ")\n", + "\n", + "# --- 3. Create the Pivot Table ---\n", + "pivot_stats = pd.pivot_table(\n", + " df_melted,\n", + " index=['Metric'],\n", + " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", + " values='Value',\n", + " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", + ")\n", + "\n", + "# --- 4. Re-orient to Vertical View ---\n", + "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", + "vertical_stats_table = pivot_stats.stack(level=0)\n", + "\n", + "# Rename the new index level for clarity\n", + "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", + "\n", + "# Display the final vertical table\n", + "vertical_stats_table" ] }, { "cell_type": "code", - "execution_count": 64, - "id": "c9f9a363-4c19-4991-ac52-524d8e388100", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1: 2.708\n", - "df_2: 2.394\n", - "T-Statistic: 25.3827\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1: 2.393\n", - "df_2: 2.287\n", - "T-Statistic: 6.5336\n", - "P-Value: 0.0000000001\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1: 2.699\n", - "df_2: 2.394\n", - "T-Statistic: 23.6742\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1: 2.993\n", - "df_2: 3.046\n", - "T-Statistic: -4.3473\n", - "P-Value: 0.0000138232\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1: 3.035\n", - "df_2: 3.011\n", - "T-Statistic: 1.5449\n", - "P-Value: 0.1223834903\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1: 2.710\n", - "df_2: 2.425\n", - "T-Statistic: 21.8571\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1: 2.994\n", - "df_2: 2.986\n", - "T-Statistic: 0.5733\n", - "P-Value: 0.5664729684\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1: 3.048\n", - "df_2: 3.031\n", - "T-Statistic: 1.1520\n", - "P-Value: 0.2493166368\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1: 3.228\n", - "df_2: 3.078\n", - "T-Statistic: 10.5906\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1: 3.218\n", - "df_2: 3.166\n", - "T-Statistic: 3.5105\n", - "P-Value: 0.0004478861\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1: 3.694\n", - "df_2: 3.565\n", - "T-Statistic: 10.7853\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1: 3.218\n", - "df_2: 3.059\n", - "T-Statistic: 11.1506\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1: 3.697\n", - "df_2: 3.570\n", - "T-Statistic: 10.5199\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1: 3.054\n", - "df_2: 3.045\n", - "T-Statistic: 0.6356\n", - "P-Value: 0.5250658229\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1: 15.142\n", - "df_2: 15.856\n", - "T-Statistic: -1.6897\n", - "P-Value: 0.0910916769\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1: 15.567\n", - "df_2: 16.484\n", - "T-Statistic: -2.1228\n", - "P-Value: 0.0337816494\n", - "--------------------------------------\n" - ] - } - ], - "source": [ - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", + "execution_count": 5, + "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", + "filtered_metrics_1to5 = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", "]\n", "\n", - "for col in metric_columns: \n", - " df_1 = dfDisloyal[col].dropna()\n", - " df_2 = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1,\n", - " b=df_2,\n", - " equal_var=False\n", - " )\n", + "# --- 2. Filter the df_melted DataFrame ---\n", + "# Only keep rows where the 'Metric' is in the list above\n", + "df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", "\n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1: {df_1.mean():.3f}\")\n", - " print(f\"df_2: {df_2.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" + "\n", + "# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", + "correct_palette = {\n", + " 'satisfied': 'tab:blue',\n", + " 'neutral or dissatisfied': 'tab:orange'\n", + "}\n", + "\n", + "# --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", + "plt.figure(figsize=(16, 8))\n", + "\n", + "sns.barplot(\n", + " data=df_melted_filtered_1to5, # Using the filtered data\n", + " x='Metric',\n", + " y='Value',\n", + " hue='satisfaction',\n", + " errorbar='sd',\n", + " palette=correct_palette\n", + ")\n", + "\n", + "# --- 5. Format the Chart ---\n", + "plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", + "plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f67e69b0-997c-4609-a93c-691d57f081ef", + "metadata": {}, + "outputs": [], + "source": [ + "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", + "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", + "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1d7ab163-baac-48b8-b23f-96ff64a868de", + "metadata": {}, + "outputs": [], + "source": [ + "legend_colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] \n", + "\n", + "# Define the corresponding labels\n", + "legend_labels = ['Category A', 'Category B', 'Category C']" ] }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 8, "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", "metadata": {}, "outputs": [ @@ -5328,6 +1252,25 @@ } ], "source": [ + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", "# --- 1. Initialize Lists for Storing Results ---\n", "metric_names = []\n", "p_values = []\n", @@ -5420,7 +1363,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 9, "id": "22aa3477-4a71-4966-8278-0fb39583ffae", "metadata": {}, "outputs": [ @@ -5630,79 +1573,7 @@ }, { "cell_type": "code", - "execution_count": 71, - "id": "8b49a8ad-9ade-4c87-bfc1-8c41a0fc8cbc", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 84923\n", - "disloyal Customer 18981\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 71, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "eebaa851-4d41-4660-93f0-134a3cb071da", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 40533\n", - "disloyal Customer 4492\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 73, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfSatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "bfb858a8-9410-4699-8150-7f17f158580a", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 44390\n", - "disloyal Customer 14489\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dfDisatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 78, + "execution_count": 10, "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", "metadata": {}, "outputs": [ @@ -5736,7 +1607,7 @@ }, { "cell_type": "code", - "execution_count": 80, + "execution_count": 11, "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", "metadata": {}, "outputs": [ @@ -5770,9 +1641,11 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 12, "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", - "metadata": {}, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -5805,10 +1678,293 @@ { "cell_type": "code", "execution_count": null, - "id": "2d8bb127-282b-42d1-9d37-ffd35fbc1333", + "id": "6dead254-560d-4364-a3c9-9df02a5b10db", "metadata": {}, "outputs": [], "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "494e2a2d-1913-437d-91e9-d6ef9a3211df", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "962aad69-b985-4ff3-ab06-a854e251135b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:23: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " dfDisatisfied['Flight Distance_group'] = np.select(\n", + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:46: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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2fWV4++23DUlGUlJSttvK6OXafWgYV74fISEhRq1atQy73W7Wz507ZwQEBBgRERGZXvf693rdunUNScacOXPMWlpamlGyZEmjc+fOZi02NtawWq3Ghg0bnNbPeB/NmzfPrEky/P39jdOnTzstO2DAAKNIkSLZ9pmdjPdQSEiIcenSJbOenJxsFCtWzLjnnnvMWsb5MT4+3qytX7/ekGTMmDHjhq+TcRxl9bVr1y5zuevfgxk9v/rqq+bjhx56yChUqJDT+9dutxvVq1c3JBn79u0z63l9brx+X1z/PbtWYGCgUa1aNfPx9e/PnJwnTp48man/7KSnpxupqalG5cqVnY7FjH3fvn17p+Vnz55tSDLWrFljGMaV97afn5/RpEkTp/PP9cLCwozw8HAjLS3Nqd6hQwcjODjY6Xi5XnbHesbPnIyv9PT0TONv2rSp0zpnzpwxvL29M/V18OBBw9PT0+jatatZy+p9ZRiZzyW5OR4AoKDiVjsAuEU0bNhQ7u7u8vX1VYcOHRQUFKSff/5ZgYGB+vHHH2WxWNStWzelp6ebX0FBQapTp06mTx8qWrSoWrRo4VT7+eefVaVKFaeJZ6/3448/qkiRIurYsaPT69StW1dBQUGZXqdu3brmlTOS5OXlpSpVqpi3B95MxqTOZcqUkZubm9zd3VW2bFlJMm9buHDhgjZu3Kj77rtPHh4e5rqFCxdWx44dM40/N/vpWhcuXNC6dev04IMPqnDhwmbdZrPp8ccf1+HDh7O8RSQvGNfc5paVYsWKqWLFinrrrbf0zjvvKD4+Xg6Hw2mZunXrysPDQ71799aMGTOyvbVw8eLFuueee+Tv7y+bzSZ3d3eNGjVKp06dyvJTsXKifv36mj59usaMGaO1a9cqLS3tL21Hyvl7cMmSJZKUaf6zLl265OscLBlX4HTp0kWzZ8/O1SdT7ty5U0ePHtXjjz8uq/XqP9EKFy6sBx54QGvXrnW6bVJSpk9Pq1atmiwWizlfmHTl6p5KlSo5HZc//vijatasqbp16zrt5zZt2mT5iYotWrRQ0aJFnWr169dXUlKSHn30UX333XdZ3iJ7I507d5aXl5f52NfXVx07dtTy5ctlt9slSY8++qgCAgI0adIkc7n3339fJUuW1MMPP5yj1xk7dqw2bNjg9FWmTJlcjXXZsmVq0aKFSpQoYdasVqu6dOmS5fJ/99z4V93sXJLT80R20tPTFRMTo+rVq8vDw0Nubm7y8PDQrl27Mt1qJmW+yqh27dqSrt5Cvnr1aiUnJ6tfv37Zfvre7t279ccff5jH+rXv1/bt2+vYsWN/6dz83nvvyd3d3fyqU6dOpmUeeOABp8dr1qzRpUuXMl1hVaZMGbVo0eJv3RqXk+MBAAoqgicAuEV89tln2rBhg+Lj43X06FFt2bJFjRs3liQdP35chmEoMDDQ6R/K7u7uWrt2baZf+IKDgzNt/+TJkzedZPb48eNKSkqSh4dHptdJSEjI9DpZfTKUp6enLl26dNN+HQ6HWrdurTlz5mjYsGFatGiR1q9fr7Vr10qSuY0zZ86YvV/v+lpu99O1Ml4nq30XEhIiSeatY3ntwIED8vT0VLFixbJ83mKxaNGiRWrTpo3GjRunO+64QyVLltRzzz1n3lZWsWJF/fLLLwoICFD//v1VsWJFVaxYUe+99565nfXr16t169aSpI8++kirVq3Shg0bNGLECEnK0fctK1999ZV69Oihjz/+WI0aNVKxYsXUvXt3JSQk5HpbOX0PZnwvgoKCnNZ3c3O76SeWSTJDgX379uV6jDfStGlTzZ07V+np6erevbtKly6tmjVrZjlP0fUyesruPehwOHTmzBmn+vXvGQ8PD/n4+Dj9AptRv3z5svn4+PHj2rJlS6Z97OvrK8MwcnROefzxx/XJJ5/owIEDeuCBBxQQEKAGDRqYtzbdzPXfu4xaamqqzp8/L+nK+aRPnz6aOXOmkpKSdPLkSc2ePVs9e/bM8S2uFSpUUL169Zy+cnt77KlTp3J0Dsrwd86Nf9WFCxd06tQp83yVlZycJ25k8ODBeuWVV3Tffffphx9+0Lp167RhwwbVqVMny96u3w8Z+z1j2Yx52270synjluohQ4Zker/269dPkm54bs841q8P/bp27WoGkRm3Ol7v+vf9zY7Rv/MzIifHAwAUVMzxBAC3iGrVqjl9UtG1SpQoIYvFohUrVmT5C9P1taz+clyyZEkdPnz4hmMoUaKEihcvrvnz52f5vK+v7w3Xz43ff/9dv/32m6ZPn64ePXqY9Yy5rTIULVpUFosly/mcrg82crufrn8dq9WqY8eOZXru6NGj5vbz2pEjR/Trr78qMjLyhlfqlC1bVtOmTZMk/fnnn5o9e7aio6OVmpqqqVOnSpLuvvtu3X333bLb7dq4caPef/99DRo0SIGBgXrkkUc0a9Ysubu768cff3QKJubOnfu3eihRooQmTJigCRMm6ODBg/r+++/14osv6sSJE9m+l260rZy8BzN+oU1ISFCpUqXM59PT03P0y1+bNm304Ycfau7cuXrxxRdvuryXl5dSUlIy1bP6hbdTp07q1KmTUlJStHbtWsXGxqpr164qV67cDedqyegpu/eg1WrNdNXRX1WiRAl5e3s7TXh9/fPXyu5qlCeffFJPPvmkLly4oOXLl+vVV19Vhw4d9Oeff5pXL2Ynq2AyISFBHh4eTlcdPvPMM3rzzTf1ySef6PLly0pPT1ffvn1v1mKeKl68eI7OQfnpp59+kt1uz3JC62vd7DxxI//973/VvXt3xcTEONUTExNVpEiRXI85Y+6oG/1syngvvvTSS+YcZde7fm6pa7Vq1Uoffvihvv/+ew0ZMsSsBwQEmJ+w6evrm+Xxff37/mbH6LXHjZeXl86ePZtpuexCspweDwBQEHHFEwAUAB06dJBhGDpy5Eimv9zXq1dPtWrVuuk22rVrpz///NOc5Di71zl16pTsdnuWr3Ojf9xn5/q/cGfI+Af99WHQtZ/IJEmFChVSvXr1NHfuXKWmppr18+fP68cff8w0/r+6nwoVKqQGDRpozpw5TmN1OBz673//q9KlS6tKlSq56PzmLl26pJ49eyo9PV3Dhg3L8XpVqlTRyJEjVatWLW3atCnT8zabTQ0aNDBvT8pYJuOjwDMm9c0Yw+eff55pG3/16ozQ0FANGDBArVq1ynJsN5PT92DGL9dffPGF0/qzZ8/ONJF0Vjp16qRatWopNjbWaRLjay1YsMC8ta1cuXI6ceKEU/iQmpqqBQsWZPsanp6eioyM1NixYyXJ/Lj27I6JqlWrqlSpUpo5c6bTLVMXLlzQN998Y37SXV7o0KGD9uzZo+LFi2e5n3P7SY2FChVSu3btNGLECKWmpmrbtm03XWfOnDlOV2GdO3dOP/zwg+6++26n92hwcLAeeughTZ48WVOnTlXHjh2dbmP7J0RGRmrx4sVOoYHD4dDXX3/9l7eZ3fvgrzh48KCGDBkif39/9enTJ0frZHeeuNG4LBZLpnP2Tz/9lKtbSq8VEREhf39/TZ06NdvbBKtWrarKlSvrt99+y/K9Wq9evRv+UeT+++9X9erVFRMT4/QJrn9Fo0aN5O3tnWlS+cOHD2vx4sVq2bKlWStXrpz+/PNPp0Dr1KlTWr16dZbbzunxAAAFEVc8AUAB0LhxY/Xu3VtPPvmkNm7cqKZNm6pQoUI6duyYVq5cqVq1aumZZ5654TYGDRqkr776Sp06ddKLL76o+vXr69KlS1q2bJk6dOig5s2b65FHHtEXX3yh9u3ba+DAgapfv77c3d11+PBhLVmyRJ06ddL999+fq7FnfFT9hx9+KF9fX3l5eal8+fIKCwtTxYoV9eKLL8owDBUrVkw//PBDlrfpvPbaa4qKilKbNm00cOBA2e12vfXWWypcuLBOnz6dZ/spNjZWrVq1UvPmzTVkyBB5eHho8uTJ+v333/Xll19me9VHThw8eFBr166Vw+HQ2bNnFR8fb96mNH78ePMWuKxs2bJFAwYM0EMPPaTKlSvLw8NDixcv1pYtW8yrdaZOnarFixcrKipKoaGhunz5snk1S8a8XlFRUXrnnXfUtWtX9e7dW6dOndLbb7+d5ZVgtWrV0qxZs/TVV1+pQoUK8vLyyjK4O3v2rJo3b66uXbsqLCxMvr6+2rBhg/lJhLmV0/dgtWrV1K1bN02YMEHu7u6655579Pvvv+vtt9+Wn5/fTV/HZrPp22+/VevWrdWoUSM988wzat68uQoVKqQDBw7of//7n3744Qfz1raHH35Yo0aN0iOPPKKhQ4fq8uXL+s9//pNp7pVRo0bp8OHDatmypUqXLq2kpCRzLpnIyEhJV2538vb21hdffKFq1aqpcOHCCgkJUUhIiMaNG6fHHntMHTp0UJ8+fZSSkqK33npLSUlJevPNN3O9P7MzaNAgffPNN2ratKmef/551a5dWw6HQwcPHlRcXJxeeOEFNWjQ4Ibb6NWrl7y9vdW4cWMFBwcrISFBsbGx8vf3z9GnzdlsNrVq1UqDBw+Ww+HQ2LFjlZycrNGjR2daduDAgeZ4Pv3007/W9N8wYsQI/fDDD2rZsqVGjBghb29vTZ06VRcuXJAkpzm5ciq7c+PNbhX9/fffzTmOTpw4oRUrVujTTz8139MZVxFlJSfnCV9fX5UtW1bfffedWrZsqWLFiqlEiRIqV66cOnTooOnTpyssLEy1a9fWr7/+qrfeeuumt3Fnp3Dhwho/frx69uype+65R7169VJgYKB2796t3377TRMnTpR05Q8S7dq1U5s2bfTEE0+oVKlSOn36tHbs2KFNmzbdMAC02WyaO3eu2rRpo/r166tXr15q1qyZihYtqqSkJK1bt06//fabqlWrdtPxFilSRK+88opefvllde/eXY8++qhOnTql0aNHy8vLS6+++qq57OOPP64PPvhA3bp1U69evXTq1CmNGzcu2/NTbo4HAChw8mdOcwBAhpx8UlG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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", + "\n", + "# --- Define the Conditions ---\n", + "# Assuming you are applying this logic to the dfDisatisfied DataFrame\n", + "conditions = [\n", + " (dfDisatisfied['Flight Distance'] < 750),\n", + " (dfDisatisfied['Flight Distance'] >= 750) & (dfDisatisfied['Flight Distance'] < 1500),\n", + " (dfDisatisfied['Flight Distance'] >= 1500) & (dfDisatisfied['Flight Distance'] < 2250),\n", + " (dfDisatisfied['Flight Distance'] >= 2250) & (dfDisatisfied['Flight Distance'] < 3000),\n", + " (dfDisatisfied['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# --- Define the Corresponding Labels and Order ---\n", + "distance_labels = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# Apply np.select() to create the grouping column\n", + "dfDisatisfied['Flight Distance_group'] = np.select(\n", + " conditions, \n", + " distance_labels, \n", + " default='Unknown'\n", + ")\n", + "\n", + "# --- 2. AUTOMATIC DATA AGGREGATION & PERCENTAGE CALCULATION ---\n", + "\n", + "# Get the count of each Flight Distance group\n", + "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = distance_group_counts_series.reset_index()\n", + "df_counts.columns = ['Flight Distance Group', 'Count']\n", + "\n", + "# Calculate Percentage\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART WITH ANNOTATIONS ---\n", + "plt.figure(figsize=(12, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Flight Distance Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=distance_labels, # Ensures the groups plot in logical order\n", + " palette='magma'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", + "plt.xlabel('Flight Distance Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit to ensure annotations are visible\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.20)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart_final.png')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "8d11c378-2b5c-47b1-97e0-c611056739ec", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\2556283244.py:21: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each Gender from the dfDisatisfied DataFrame\n", + "gender_counts_series = dfDisatisfied['Gender'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = gender_counts_series.reset_index()\n", + "df_counts.columns = ['Gender', 'Count']\n", + "\n", + "# Sort the data by count (or percentage) before plotting\n", + "df_counts = df_counts.sort_values(by='Count', ascending=False)\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(8, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Gender',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " # Order is naturally handled by the prior sorting of df_counts\n", + " palette='Set2' # Used a different palette (Set2)\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Gender')\n", + "plt.xlabel('Gender')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=0, ha='center') # No rotation needed\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_gender_percentage_bar_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "27ee32c2-d244-4497-aafc-0232278b4ed0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\783172777.py:23: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each age group from the dfDisatisfied DataFrame\n", + "age_group_counts_series = dfDisatisfied['age groups'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts) for plotting\n", + "df_counts = age_group_counts_series.reset_index()\n", + "df_counts.columns = ['Age Group', 'Count']\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "# Optional: Ensure all groups are present, even if count is 0,\n", + "# and ensure they are properly ordered by the chronological order of ages.\n", + "# We will use the 'order' parameter in sns.barplot for this.\n", + "age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(10, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Age Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=age_order, # Use the defined chronological order\n", + " palette='viridis'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Age Group (Chronological Order)')\n", + "plt.xlabel('Age Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=45, ha='right')\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", + "plt.show() # Use plt.show() if running in a script/local environment" + ] } ], "metadata": { diff --git a/notebooks/Airline_Project1_Antonio 2.ipynb b/notebooks/Airline_Project1_Antonio 2.ipynb new file mode 100644 index 00000000..0ac64307 --- /dev/null +++ b/notebooks/Airline_Project1_Antonio 2.ipynb @@ -0,0 +1,1991 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "561808a4-27ef-4523-892a-8584a31efefa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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103904 rows × 25 columns

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" + ], + "text/plain": [ + " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", + "0 0 70172 Male Loyal Customer 13 Personal Travel \n", + "1 1 5047 Male disloyal Customer 25 Business travel \n", + "2 2 110028 Female Loyal Customer 26 Business travel \n", + "3 3 24026 Female Loyal Customer 25 Business travel \n", + "4 4 119299 Male Loyal Customer 61 Business travel \n", + "... ... ... ... ... ... ... \n", + "103899 103899 94171 Female disloyal Customer 23 Business travel \n", + "103900 103900 73097 Male Loyal Customer 49 Business travel \n", + "103901 103901 68825 Male disloyal Customer 30 Business travel \n", + "103902 103902 54173 Female disloyal Customer 22 Business travel \n", + "103903 103903 62567 Male Loyal Customer 27 Business travel \n", + "\n", + " Class Flight Distance Inflight wifi service \\\n", + "0 Eco Plus 460 3 \n", + "1 Business 235 3 \n", + "2 Business 1142 2 \n", + "3 Business 562 2 \n", + "4 Business 214 3 \n", + "... ... ... ... \n", + "103899 Eco 192 2 \n", + "103900 Business 2347 4 \n", + "103901 Business 1995 1 \n", + "103902 Eco 1000 1 \n", + "103903 Business 1723 1 \n", + "\n", + " Departure/Arrival time convenient ... Inflight entertainment \\\n", + "0 4 ... 5 \n", + "1 2 ... 1 \n", + "2 2 ... 5 \n", + "3 5 ... 2 \n", + "4 3 ... 3 \n", + "... ... ... ... \n", + "103899 1 ... 2 \n", + "103900 4 ... 5 \n", + "103901 1 ... 4 \n", + "103902 1 ... 1 \n", + "103903 3 ... 1 \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "0 4 3 4 4 \n", + "1 1 5 3 1 \n", + "2 4 3 4 4 \n", + "3 2 5 3 1 \n", + "4 3 4 4 3 \n", + "... ... ... ... ... \n", + "103899 3 1 4 2 \n", + "103900 5 5 5 5 \n", + "103901 3 2 4 5 \n", + "103902 4 5 1 5 \n", + "103903 1 1 4 4 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "0 5 5 25 \n", + "1 4 1 1 \n", + "2 4 5 0 \n", + "3 4 2 11 \n", + "4 3 3 0 \n", + "... ... ... ... \n", + "103899 3 2 3 \n", + "103900 5 4 0 \n", + "103901 5 4 7 \n", + "103902 4 1 0 \n", + "103903 3 1 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction \n", + "0 18.0 neutral or dissatisfied \n", + "1 6.0 neutral or dissatisfied \n", + "2 0.0 satisfied \n", + "3 9.0 neutral or dissatisfied \n", + "4 0.0 satisfied \n", + "... ... ... \n", + "103899 0.0 neutral or dissatisfied \n", + "103900 0.0 satisfied \n", + "103901 14.0 neutral or dissatisfied \n", + "103902 0.0 neutral or dissatisfied \n", + "103903 0.0 neutral or dissatisfied \n", + "\n", + "[103904 rows x 25 columns]" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import stats\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", + "\n", + "df=pd.read_csv('train.csv')\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a86604ec-da44-40c0-894e-0a118b9ca685", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age Group creation successful.\n", + "Flight distance group Group creation successful.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" + ] + } + ], + "source": [ + "binary_change= {\n", + " 'satisfied': 1,\n", + " 'neutral or dissatisfied': 0,\n", + "}\n", + "\n", + "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", + "df.drop(columns=['Unnamed: 0'], inplace=True)\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Age'] < 18),\n", + " (df['Age'] >= 18) & (df['Age'] < 30),\n", + " (df['Age'] >= 30) & (df['Age'] < 40),\n", + " (df['Age'] >= 40) & (df['Age'] < 50),\n", + " (df['Age'] >= 50) & (df['Age'] < 60),\n", + " (df['Age'] >= 60) & (df['Age'] < 70),\n", + " (df['Age'] >= 70)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Minor',\n", + " '18 to 30',\n", + " '30 to 40',\n", + " '40 to 50',\n", + " '50 to 60',\n", + " '60 to 70',\n", + " '70 +'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Age Group creation successful.\")\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Flight Distance'] < 750),\n", + " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", + " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", + " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", + " (df['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Flight distance group Group creation successful.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "6f945079-4c90-40ee-83b9-53af53e43388", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", + "dfDisatisfied=df[df['satisfaction_binary'] == 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\3011661649.py:47: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning.\n", + " vertical_stats_table = pivot_stats.stack(level=0)\n" + ] + }, + { + "data": { + "text/html": [ + "
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satisfactionneutral or dissatisfiedsatisfied
MetricStatistic
Agemean37.56668841.750583
median36.00000043.000000
std16.45982512.767833
Arrival Delay in Minutesmean17.12753612.630799
median0.0000000.000000
std40.56024835.962008
Baggage handlingmean3.3759913.966396
median4.0000004.000000
std1.1769781.099607
Checkin servicemean3.0429523.646041
median3.0000004.000000
std1.2811581.158732
Cleanlinessmean2.9361233.744342
median3.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.000000
std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.000000
std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.000000
std1.1756031.091486
Inflight wifi servicemean2.3996333.161288
median2.0000004.000000
std0.9643481.588697
Leg room servicemean2.9908123.822143
median3.0000004.000000
std1.3031591.175515
On-board servicemean3.0191583.857324
median3.0000004.000000
std1.2857901.127130
Online boardingmean2.6561254.027474
median3.0000004.000000
std1.1459051.191609
Seat comfortmean3.0362953.966530
median3.0000004.000000
std1.3031421.142077
\n", + "
" + ], + "text/plain": [ + "satisfaction neutral or dissatisfied \\\n", + "Metric Statistic \n", + "Age mean 37.566688 \n", + " median 36.000000 \n", + " std 16.459825 \n", + "Arrival Delay in Minutes mean 17.127536 \n", + " median 0.000000 \n", + " std 40.560248 \n", + "Baggage handling mean 3.375991 \n", + " median 4.000000 \n", + " std 1.176978 \n", + "Checkin service mean 3.042952 \n", + " median 3.000000 \n", + " std 1.281158 \n", + "Cleanliness mean 2.936123 \n", + " median 3.000000 \n", + " std 1.325955 \n", + "Departure Delay in Minutes mean 16.503728 \n", + " median 0.000000 \n", + " std 40.191886 \n", + "Departure/Arrival time convenient mean 3.129112 \n", + " median 3.000000 \n", + " std 1.500368 \n", + "Ease of Online booking mean 2.546850 \n", + " median 3.000000 \n", + " std 1.205847 \n", + "Flight Distance mean 928.919971 \n", + " median 671.000000 \n", + " std 790.452308 \n", + "Food and drink mean 2.958050 \n", + " median 3.000000 \n", + " std 1.346607 \n", + "Gate location mean 2.976121 \n", + " median 3.000000 \n", + " std 1.198500 \n", + "Inflight entertainment mean 2.894156 \n", + " median 3.000000 \n", + " std 1.323619 \n", + "Inflight service mean 3.388814 \n", + " median 4.000000 \n", + " std 1.175603 \n", + "Inflight wifi service mean 2.399633 \n", + " median 2.000000 \n", + " std 0.964348 \n", + "Leg room service mean 2.990812 \n", + " median 3.000000 \n", + " std 1.303159 \n", + "On-board service mean 3.019158 \n", + " median 3.000000 \n", + " std 1.285790 \n", + "Online boarding mean 2.656125 \n", + " median 3.000000 \n", + " std 1.145905 \n", + "Seat comfort mean 3.036295 \n", + " median 3.000000 \n", + " std 1.303142 \n", + "\n", + "satisfaction satisfied \n", + "Metric Statistic \n", + "Age mean 41.750583 \n", + " median 43.000000 \n", + " std 12.767833 \n", + "Arrival Delay in Minutes mean 12.630799 \n", + " median 0.000000 \n", + " std 35.962008 \n", + "Baggage handling mean 3.966396 \n", + " median 4.000000 \n", + " std 1.099607 \n", + "Checkin service mean 3.646041 \n", + " median 4.000000 \n", + " std 1.158732 \n", + "Cleanliness mean 3.744342 \n", + " median 4.000000 \n", + " std 1.142247 \n", + "Departure Delay in Minutes mean 12.608084 \n", + " median 0.000000 \n", + " std 35.382595 \n", + "Departure/Arrival time convenient mean 2.970305 \n", + " median 3.000000 \n", + " std 1.552213 \n", + "Ease of Online booking mean 3.031582 \n", + " median 3.000000 \n", + " std 1.575306 \n", + "Flight Distance mean 1530.140255 \n", + " median 1250.000000 \n", + " std 1128.126574 \n", + "Food and drink mean 3.521310 \n", + " median 4.000000 \n", + " std 1.236187 \n", + "Gate location mean 2.977879 \n", + " median 3.000000 \n", + " std 1.374244 \n", + "Inflight entertainment mean 3.964931 \n", + " median 4.000000 \n", + " std 1.076907 \n", + "Inflight service mean 3.969461 \n", + " median 4.000000 \n", + " std 1.091486 \n", + "Inflight wifi service mean 3.161288 \n", + " median 4.000000 \n", + " std 1.588697 \n", + "Leg room service mean 3.822143 \n", + " median 4.000000 \n", + " std 1.175515 \n", + "On-board service mean 3.857324 \n", + " median 4.000000 \n", + " std 1.127130 \n", + "Online boarding mean 4.027474 \n", + " median 4.000000 \n", + " std 1.191609 \n", + "Seat comfort mean 3.966530 \n", + " median 4.000000 \n", + " std 1.142077 " + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "numeric_cols_df = df.select_dtypes(include=np.number)\n", + "\n", + "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", + "metrics_to_analyze = [\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " 'Age' # Including age as a numeric metric to analyze\n", + "]\n", + "\n", + "# Filter down to the columns that actually exist and are numeric\n", + "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", + "\n", + "# --- 2. Melt the DataFrame ---\n", + "df_melted = df.melt(\n", + " id_vars=['satisfaction'],\n", + " value_vars=analysis_cols,\n", + " var_name='Metric', # This column now holds the name of the original column\n", + " value_name='Value' # This column now holds the numeric data\n", + ")\n", + "\n", + "# --- 3. Create the Pivot Table ---\n", + "pivot_stats = pd.pivot_table(\n", + " df_melted,\n", + " index=['Metric'],\n", + " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", + " values='Value',\n", + " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", + ")\n", + "\n", + "# --- 4. Re-orient to Vertical View ---\n", + "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", + "vertical_stats_table = pivot_stats.stack(level=0)\n", + "\n", + "# Rename the new index level for clarity\n", + "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", + "\n", + "# Display the final vertical table\n", + "vertical_stats_table" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", + "filtered_metrics_1to5 = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + "]\n", + "\n", + "# --- 2. Filter the df_melted DataFrame ---\n", + "# Only keep rows where the 'Metric' is in the list above\n", + "df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", + "\n", + "\n", + "# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", + "correct_palette = {\n", + " 'satisfied': 'tab:blue',\n", + " 'neutral or dissatisfied': 'tab:orange'\n", + "}\n", + "\n", + "# --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", + "plt.figure(figsize=(16, 8))\n", + "\n", + "sns.barplot(\n", + " data=df_melted_filtered_1to5, # Using the filtered data\n", + " x='Metric',\n", + " y='Value',\n", + " hue='satisfaction',\n", + " errorbar='sd',\n", + " palette=correct_palette\n", + ")\n", + "\n", + "# --- 5. Format the Chart ---\n", + "plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", + "plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "f67e69b0-997c-4609-a93c-691d57f081ef", + "metadata": {}, + "outputs": [], + "source": [ + "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", + "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", + "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "1d7ab163-baac-48b8-b23f-96ff64a868de", + "metadata": {}, + "outputs": [], + "source": [ + "legend_colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] \n", + "\n", + "# Define the corresponding labels\n", + "legend_labels = ['Category A', 'Category B', 'Category C']" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1 Mean: 2.708\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 25.3827\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1 Mean: 2.393\n", + "df_2 Mean: 2.287\n", + "T-Statistic: 6.5336\n", + "P-Value: 0.0000000001\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1 Mean: 2.699\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 23.6742\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1 Mean: 2.993\n", + "df_2 Mean: 3.046\n", + "T-Statistic: -4.3473\n", + "P-Value: 0.0000138232\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1 Mean: 3.035\n", + "df_2 Mean: 3.011\n", + "T-Statistic: 1.5449\n", + "P-Value: 0.1223834903\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1 Mean: 2.710\n", + "df_2 Mean: 2.425\n", + "T-Statistic: 21.8571\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1 Mean: 2.994\n", + "df_2 Mean: 2.986\n", + "T-Statistic: 0.5733\n", + "P-Value: 0.5664729684\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1 Mean: 3.048\n", + "df_2 Mean: 3.031\n", + "T-Statistic: 1.1520\n", + "P-Value: 0.2493166368\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1 Mean: 3.228\n", + "df_2 Mean: 3.078\n", + "T-Statistic: 10.5906\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1 Mean: 3.218\n", + "df_2 Mean: 3.166\n", + "T-Statistic: 3.5105\n", + "P-Value: 0.0004478861\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1 Mean: 3.694\n", + "df_2 Mean: 3.565\n", + "T-Statistic: 10.7853\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1 Mean: 3.218\n", + "df_2 Mean: 3.059\n", + "T-Statistic: 11.1506\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1 Mean: 3.697\n", + "df_2 Mean: 3.570\n", + "T-Statistic: 10.5199\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1 Mean: 3.054\n", + "df_2 Mean: 3.045\n", + "T-Statistic: 0.6356\n", + "P-Value: 0.5250658229\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1 Mean: 15.142\n", + "df_2 Mean: 15.856\n", + "T-Statistic: -1.6897\n", + "P-Value: 0.0910916769\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1 Mean: 15.567\n", + "df_2 Mean: 16.484\n", + "T-Statistic: -2.1228\n", + "P-Value: 0.0337816494\n", + "--------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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FNOH2tGnTzOVy2fvvv++n2uUuZ86c8WqjlStXWt26dW3VqlX23Xff2YABA+yqq66y119/3bPMa6+9Zs8995yNHj3a0xn279/fOnbsyIOOzGz+/PkWHBxszz33nL3xxht2++23W9GiRW3ChAlmdnaEw9NPP20lS5a0t956y8+1zR3ODRQ2bdpkr7/+uj355JOeabGxsdaxY0dr3ry5ffzxx5799oUXXrDNmzdf1PrmVqlDgueee86KFy9ut912m1199dVWs2ZNz0MTNm/ebA0bNrTKlStb+fLlrWnTpnby5Ek7duyY1a5d22uE4uUo9T1ef//9d6+ffE6ePNnKlStnjzzyiNdPywhozvL10+SnnnrK88AJ961r3F5++WVzuVye+7Jf7tyhYGpPPPGEde3a1Wta6pD/6NGjtmbNGtuxYwe/oEgl9TE5d+5cK1eunP3www9pltu+fbu9+eab1rBhQ+vWrZs99thjnvPqy/38OvXxPHnyZCtevLi9/fbb1r17d2vSpIn9H3vnHY919/9xn1IpZGRFErL33qNCSItKkTYNmkaS7rT3XlKSlgbRQHtoaS8pJaU0UFL2fP3+uLqO6+O6dN/37/v9xn1fn+c/3c7n8/E4zn3G+7zO+7zfY8aMIc4MW7ZsgZGRESwtLTFkyBByE8rOzo4vw6MdPXqUq+zUqVMwNTWlxVZv3sfY4UKY8D/cPH78GKqqqlwHeeyx/vjxY6xfvx7z589HfHw8s09uga9fv8LW1pYkgaqsrMSHDx+wb98+pKSkAADOnDmDsWPHQl1dne8P9Nj9iz0f7tu3DwMHDgTAEv1FRESI00JpaSmeP38OAMztWg6a28hHjx6FqakpAJZjg6ioKC3mOtth5PHjx3zRhoz4+huYNGkSiZHEJjc3F926dUNaWhrX+zU1NVzemsC/9wTgr8A5kJsPyIULF6J9+/Yk2yUnqamp/+oB/FdpngH06NGj8PPzowleb9++xezZs2FgYMAVqxRgXaUPCgqCpKQkX57Qf/r0ifZzTU0NBg0ahBkzZtDKIyIiICYmRhaTnJwcLFy4kEmIAtZhSVRUFOrr61FfX4+Kigpoa2uDoiiuzJZFRUXo378/HB0dsXfvXiYeJAeca8HTp08RFhZGTuWfPn2KqVOnQkFBAYcPHwbAmjNfvHiBnJwc0o6RkZFQVlbm2/hynIdRx48fh66uLmRlZWFgYIDBgweTNo6NjYWCggLmzJmDFy9etGaV2xSca3JDQwPt56CgIHTs2BHx8fFch3T79+9n1mSwQjF4eXmROJBsvLy8MHLkSADcG5isrCwuQZvfWbNmDVfZunXruK4fN7efm9tE/GxfA3Th9eLFiwgPD6dlPd+2bRssLS3h6+uLb9++AQD5l/39vHnzIC8vT0JY8Qu3b9+GiooK3r9/T2vHQ4cOQUJCAvn5+QDobXzhwgXaWOZ3+8bX15fLFrly5Qp69OhBs73Z7dSSWM3v45gXNTU16Nu3LxYtWoSPHz8iNDQUDg4O6N69O0RFRbFhwwZUVlYiKSmJb+1BNpzrwvfv3wGwHLn69euHvXv30kRDAEhOToaPjw8t5jpzON/E/fv3AQAJCQlwc3PDiRMnICIiQovVnJaWhsDAQNo4/7e3ISO+/o8pLi7GsmXLuK4nPnnyBN27dydXaDkXjMuXL2P16tVcxiG/wjkIt23bhnHjxsHT0xPLli0jC3BUVBTat2/fopcrP2/2Jk2ahNmzZwNgteWnT58wcOBASEpKkk0em/z8fMyZMwempqaIjIwk5Z8/f0Z0dDRsbGz4MrlMVFQUpk6dSjP4ampqYGNjg0WLFgGgG4NDhgxBnz59yM/83P84Wbp0KRGw2O316tUrWFpaQktLC+fOnaO9X1RUBEtLS7i5ufE8kOI3mh+KnDhxAt27d4eWlhYtYP2LFy8wdepUKCoqIiEhgfZNVlYWRo8eDSkpKb70cLh27RptPb506RI6d+6MLVu24NKlS9i9ezd0dHRgYGBA1p74+HgICQlh3rx5TKgBcCdQGDt2LHx9fbFw4UJSHhQUhE6dOiE+Pp6nLcPvc+KLFy+IFz+nZ9z8+fMhLS1NYjGz2/rr16+IiIgghywMwOHDh+Hl5cUluKxatQqGhoY0cRBg9bnDhw/j8+fPv7GWbZsxY8bgwYMH5OfLly+TgyjOWxF1dXXYtm0brK2t4evrS0uq9fTpU8yePRvdu3en/S5+oaysjHihczomZGRkQElJCZs3byZCDptRo0bhjz/++K31bKt8+/YNI0eO5Fpb7969CyEhIZJFHmiaD9PT03HlypXfWs9/KlVVVZg0aRLMzMwgKCgIT09PxMbG4uPHj5gwYQL8/PwAMAcAqamp5IZiQEAAid168+ZNGBoaolOnTli5ciV5v6KiAgMGDMDEiRP5vu3YHD16lGgHs2bNQt++fVFdXY3CwkJ069aN6zZyVVUV3NzcMHr0aL5qQ0Z8/R/SvCPFxsYSoQZgiWISEhK4d+8eKauoqIC7uzv8/f35qiP+FcLCwiAjI4MVK1YgMjISPXr0wIABA8hivHjxYnTs2JFc+WZgGcwnTpwgRg3730ePHsHX1xc9evSgxa0BWALshAkTMG7cOFofLCoqom0S+YkzZ84gKysLAP3a/IgRI2BsbEx+ZguKCxcuRN++fX9vJdswzeeyjIwMhIeH4/379wBYAqy+vj769++Py5cv094tLi4mniP8zOnTp9GnTx/U19eT9jx37hxGjBgBISEhLuE6JycH06dPh6CgIG3zkpeXh02bNpGrUvzEzJkzYWlpSfNSmD9/PlcG+fv370NbW5t2OHX48GG+8+j6M8LCwiAnJ4fIyEgsX74c7du3x6hRo8jzGTNmQFhYGDt27GASNHLAKRZmZGSgf//+ZIzm5ubC0tISdnZ2JMZhfX095s+fDyUlJTJnMrDWYrb9x3mLLDk5GZ06dcK+fftobV1eXg53d3eet6T4kQcPHiA4OJgmen3//h2RkZGQl5fHqFGjaIfK9fX12LFjB9TU1BAVFUXKS0tLcenSJa6M1fwAp21TUFAASUlJImYBwJQpUyApKYn169cjOzsb+fn5mDt3LmRkZPhyDf4zoqOjyQF9YWEh+vfvD09PT5JsC2Dta/r27Yvg4ODWqmabhd0fHz16hMTERBw4cADv379HXV0dMjIycOzYMdrh6ahRozB16lSusHT8yIQJE6CoqAhnZ2dISUnRDlJWrFgBWVlZzJo1C+fPn8fZs2fh4uJCS67F7+1XX1+PnTt3gqIo2NvbQ1RUFI8fPybP09LS0K1bN/j4+ODkyZNISUmBs7MzLbkWv7QhI77+D+Gc4GpqajBmzBgYGxsT76WKigoMHToUnTp1wqxZszBr1iw4OjrSgv/zS0fkBefffvv2bWhoaODmzZsAgJSUFIiIiHBlVQ0ODoadnR1ftxub5m2we/du9O3bl4iHjx8/ho+PD2xtbbFv3z7au58/fyb999/u/v9ncP79ly5dwtixY8lVirt370JHR4fLg3jSpEkYPHgwqqurmb74E844Shs2bICqqioiIyNRUFAAgCUW6unpoX///rh69WprVrVN8v37d9KGp0+fJuU3b97E4MGDoampiYsXL9K+ycrKwrp167g8w/hxTN++fRtSUlJE3GfPg+PGjaMdoLDZsGEDTE1NW0xOwe9kZmZCXV2dxNVMSUmBsLAw7ToZAIwePRqOjo7MPMgBZ1u8ePECioqKGDRoELFv0tLS4ODgAAkJCRJ6pVu3bnzpVdgSnHPanTt3ICcnB39/f1I2ffp0dOzYERs3bsT169fx4MEDuLi4wNjYmLmazAF7rxETE0MO8MrLy7Fw4UKYmpoiJCSEJsDW1dXh+PHjTBs2g71OREdHQ0FBARMnTiTPZs+eDR0dHXTu3Bn6+vro1asXM5Z/wu5HjY2NqKqqgpKSEjQ0NEg87MTERNjZ2cHW1hYbNmzAzp070bdvXyaj/C9ISkqCtLQ0nJ2doaOjAxMTEy6npMLCQpJci9/zKHCuxyYmJqAoCpGRkVx28ooVK9CvXz+0b98e1tbWGDhw4L8+MdT/B1tbW1AUhalTpwJoat+6ujpcuXIF2traUFZWhrm5OYYNG8aXbciIr7+BxMREFBQUoKCgAEFBQbCwsMDatWvJ86VLl2LQoEFwdXXF9OnT+T74/6RJk2jJTQCW2KCjowOAFZ+PM+5KWVkZjh8/zhUkm983e80Xjl27dsHY2BheXl5EeHjw4AERYHklQeFHkQag/92cC8Ply5chLi4Of39/4rWwf/9+aGtrQ1dXFzNmzIC3tzdERETw5MmTVql7WyYuLg729vYAWKEcjIyMMG/ePJoAa2xsDEtLS57JUviRcePG0U7gHz16hPbt22P8+PGkLCMjAyNHjoSenh6JNdwcfjJseHHp0iUoKiri1atX2L9/P3x9fVFZWYkjR47AyMgIJ0+epK0ZJ06cQK9evRhPwxZITk6GkZER+W8RERFER0cDAH78+EFLJtp8bWZg3aZg24FPnz6FtrY2XF1dSTbgwsJCrF27FjNmzMDSpUsZr+sWyM3NRX19PdatWwdDQ0MEBASQZ5GRkVBRUYGoqCj09fVhb2/Plxu95owdOxajR48mP+fl5RGhhn3wWVZWhvnz58PCwgIhISE8Pdf5uQ05ycrKgomJCV69eoXy8nLs2bMHsrKymDBhAu2dc+fO4erVqySkCEMT7BAXX758gZmZGbS0tIgAe/78eQQFBUFKSgq2trYYMWIEM45b4OHDh5CVlSWHoBkZGejYsSMtJFBKSgpGjBiB3r1782XoKU44bZLa2lqMHj0anp6eUFNTw/bt21FaWkp7v6ysDE+fPsWXL19ooiI/09yuW7x4MebNmwdBQUFaaBX2WK2oqMDHjx/x+fNnvm1DRnz9H9LY2IjXr19DVFSUJNzKz8/HtGnTYG5uTovf1zwpBb91RDa3b99GYGAgV+yf8+fPw83NDXv37qVt8gBWjKqJEyfSBFt+3+RxiocxMTF4+vQpampqsHfvXpibm2PIkCE0AdbPzw/q6upcWUX5mdzcXDx79gwA6wBlzpw5AFheSYqKihg3bhxJovX48WOMHz8egwYNwpgxY0iIAn6lsbGR6xCkuLgYDg4OJOMqACxYsIBLgM3OzoaNjQ0TagCsjYi5uTnk5OSQk5MDgBUfcvfu3ZCXl8ekSZPIu2wB1tDQkGciRwbAwcEBysrKoCiKZKvNz8+Hvb09Bg0ahBMnTgBgzZ8hISGwsLDgMr75HfZ4vnr1Ktzc3LBjxw6uNfnq1asYPXo0LUEZvx7ktcSKFSsgJCREEpw8e/YM2tracHNzYw6e/iJsr7iqqiqUlJRg3bp10NXVxeTJk8k7L168wIMHD/Do0SO+yKL8Z5SXl2PDhg2QkZHBzJkzSfnFixfh7e0NAwMDEkuzrKwMkZGRsLa2hr+/PxPvugUyMjKgoKCAkydPAmDFMGULsJwesAy8ycrKAkVRJMFbcXExTExMaAIswApvwRk/nJ/HcUscOnSIhDzLy8tDr169aPPhu3fvUFlZif379/NlmJCWOHToEO3G3cSJE6GqqsolwLJjO7Nh7Jomtm7dihs3bpCfo6Oj0b59e67Y1s3tG37Uaxjx9TcQEhICNTU1ctpZUFCAadOmwdLSkmdWeX7siJyw//7Y2FhyNefDhw+Ql5cHRVHYsGEDebeqqgqurq4YOXIk37cbANq147q6OuTl5UFKSop4zdTW1iIuLo4IsOxsq5mZmSQLPQMrdquPjw+EhYWxfv16UBSF+Ph48jw1NZUIsM2v7DCLMUi/YhvHN2/exOjRozFs2DB8+/aN5kXDFmAjIyOJEMFs8lg0NjaioKAAbm5ukJKSImJWaWkp9uzZAxkZGS4B1sXFhRZzjqHpxP3gwYOgKAqKiop4/fo16Z/Z2dlwcHCAvr4+1NTU4OrqCjExMeZqKFqez7KysqCqqgqKomhJKCorK+Hm5gYfHx9mTf4Fb968gZ2dHTZv3kz6Z3Z2NrS1tTFo0CCcP3++lWvY9klPT0enTp1IW339+hXr16+Hnp4eTXDghJ/XZ3aisZKSEsTExEBKSgqBgYHk+aVLlzBs2DAuAXbGjBlMHopmNG+LqVOnQlVVlQg1379/x549e9CjRw+umOIMdIqLizF48GCEhoaSsqKiIpiYmEBHR4c4OXDC9EU67PbYtWsXRo4ciQ8fPqBHjx4ICAggc96VK1ewaNEiYp8zsHj//j0sLCzg5OREDuABwN/fH+rq6li/fj1evXqFvn37wtHREQDT/3hhYGAABQUF3LlzB0BTDNgOHTpg7ty5ePfuHTw8PODl5cX37ceIr/9FmncmtoBw//59WFhY4MCBA+QZOwSBiooKDh069Fvr2VbhbL/Xr1/DxsYGxsbGePToEQCWgNO1a1d4eXkhNjYWhw8fRr9+/aCrq8t3wZp5sWnTJqipqdESaL18+RLdu3cniTuAJgHWwsICXl5eXFnkGQGWxdu3b2FkZARBQUEsX74cACt2M7uPsQVYf39/WtI8fufAgQOQkpIifa68vBxRUVFQUFBA7969yXucceSioqKgrKyMxYsX0xJK8TOcXh2PHz+GhYUFVFVVyUEK27tGRkaGFuuQ08OLoYnq6mqsW7cOMTExsLS0hJaWFh4+fEjmu4KCAqSnp2POnDlYv3498TTmZzjH4ebNmzFr1iyEh4eTxIvp6ekQFBTEmDFjEBMTg6SkJPTr148vEyj8CnYbNA+/MHnyZOjp6XHFgJWXl8eIESO4bkTxM5xtxzm/BQQEwMbGhsTc/PbtGzZs2ABDQ0Na8jd+JyoqChRFEU/CPxNgDQ0NiSdYZWUlE86rGc3X2EePHsHKyop2SF9WVobt27dDXV0dnz59+t1VbJO0ZJvExcWhU6dOtCRkxcXFMDc3h4yMDLkZxfBrzpw5g3bt2kFERAQzZsygPZs2bRqGDRvGtefjN3jNYRkZGXB3d4erqytNgA0MDISamhpUVFRgZmbGJA79Ca9xXF9fj379+kFJSYmET6qvr0d8fDw6dOgALS0tGBgYMM41YMTX/xqcgzklJYUrTpynpyesrKxoZfn5+Vi7di0jdoH3ZJiamoqBAwfC3NycCLCZmZmwtrZG7969YWNjAx8fHyb2z08eP36MMWPGwNbWFrGxsQBYp8fa2tr4/v07AJCFo6amBnFxcVBSUsK8efMAMEZ1c75+/QozMzNoa2ujR48eJO5mbW0tLcOysLAwAgMDmUX5JxkZGbC1tYWOjg4RYPPz87F06VJ07tyZhG8AQGuz5cuXIy8v77fXt60TGRkJJycnWFlZgaIoyMvLEw/Yb9++IS4uDvLy8hg2bBjtO0aAbXlOKy8vJ9caGbH6z1m0aBGkpKTg7u4OTU1N9OjRgxwCnDp1Cv3794ecnBzs7Ozg7e3NrMk8uHv3LlatWkW8DwGWB3uvXr2wbNkyAE1j9uXLl7TrtgxNNPfaYsce5rzuWFpaiiVLlsDPz48Z2z/Jzc2Fs7MzevTo8acC7OXLlzFixAh0796d5v3PzzYiZyilzMxMqKqqIjExkXarzNPTE3369KF9V1ZWxoSu4cGLFy/IIR4bd3d3TJgwgXbo9PnzZ0yYMIFZS5rB7osPHjxASkoKrly5QtbdP/74A+3atcP+/ftRWFiIgoIChIWFoVu3biSUGgO4Yi9fu3YN/fv3h5ubGy2p7ZUrV3Du3DnSB5lwF02wtQV2f6yvr4ejoyNNgAVYDnXnz59n2vAnjPj6X4DTIElOToaLiwtERUWxceNGXLt2DQAr9go7gDPAvTHm54WFsy1KS0tpMVXS0tLg5uYGc3NzEhi8rKwMxcXFNIOG3wcym+zsbPj5+cHKygp79+5FTk4OjIyM8O3bN6536+vraZMhA526ujoUFxfj+fPnGDhwIBQUFEgSLc6Tu+vXrzPJUDhoaGjAvXv30L9/f6ipqRGPjw8fPmDx4sXQ0NBAZGQkeZ/TA5aBTnR0NERERHDjxg28e/cOly5dgqOjI2RkZGghCLZu3QoPDw9GaOCAvS6fPXsW06dPx7Rp02gxSCsqKogA+/jx49aqZpukeT8KCgrCrVu3AACvXr2Ci4sLZGRkiHfw9+/fUVRURAxxgFmTgaY+ePPmTTg5OcHS0hLS0tLYtm0buZoXHBwMT09PlJeXo7GxkWm3ZnD2xZMnT0JcXBzx8fG0cD99+vThEr3Y7dn8d/AzBQUF8PDwQI8ePUi8x5YE2DNnzmD+/PmMfdiM48ePY8uWLfDx8YGBgQGMjY2xefNm1NXV4f3791BSUsKuXbtau5ptDs4xePDgQQgKCmLEiBEkHwrAsnc4D+2bz4VMX6Rz7NgxSEpKQkFBAerq6vD29kZ1dTUaGxsxe/ZsdOjQAUpKSjA2Nkbv3r2ZMEocxMXFwcPDA5mZmbTyq1evwsjICPb29jxzoDB9sImYmBioqqqStYQzeZaNjQ20tbVx+/ZtZhzzgBFf/0M4hdeQkBDo6uri9evXWLlyJaytrdGrVy/MmjULN2/exJgxYxAUFMT1HQOLqKgoGBsbw9jYmCbOnDlzBu7u7rCwsOC5SWbaks6zZ8/g5+cHBwcHjBs3Dt26dcPYsWMxadIkTJ48GdOmTcPw4cORkpJCvmEmw6Z+9P79e7x//57meXT//n0MGjQIPXr0IMm0Vq5cidDQUKb/ccDuR/fv38eWLVtAURSMjIzICfP79++xePFiaGlpcQVhZ+AWCWbOnIkRI0bQyl6+fAlzc3MoKSmRWGhlZWWM0MCDc+fOQUREBO7u7jA0NISIiAhJigKwBFgLCwvIycnxfZI8Npz95+7du8jIyED//v1pG7f8/Hy4uLhATk6OluiSDTMnNnHmzBkoKyvj5MmTKCwsxJIlS2BsbAwtLS2sWLECx44dQ8eOHZGUlNTaVW3TzJ49G+vWrcP8+fOhoaEBCwsLLFy4EJWVlcjMzISVlRUSExMB0Psfv/fF5qLX6tWrQVEU1NXVyU0TtgArIyOD6dOnc/0OfrcP2X3o8ePHoCiKhPa6efMmVq1aBTExMfTt2xdTp06Fj48P/P39mZAhLTB37lysXr0aMTExCA4OhpCQENzd3REXF4f6+noYGRmRfTIDC14JbEtKSjBw4EDs27cP7969w65du2BiYgJXV1fi0HDt2jUcP34cFy9e5PLy5HcSEhJgZGQEPz8/mocmAOzevRuioqIwNzdnkl/+gnfv3kFdXR0WFhZEgGWvN6dOnQJFUZCWlma8rXnAiK//AZxG3cOHD+Hs7Ey8QwCWh0hSUhJUVFTg4eGB7t27g6IoJj7kTziNwq1bt0JGRgZr165FaGgoOnfuTEsac+bMGXh4eEBZWZm5jsdBS0LLkydP4OfnB3V1dUhLSyM8PBy+vr4YPXo0Jk2aBF9fX8bDhgP2WD5x4gRMTEygqqoKPT09WkK8Bw8eYOjQoRAUFMTQoUPRrl074o3N0MTRo0chLy+PwMBAODs7Q05ODhoaGiRm1/v377F06VLIysqS67YM9PUkNjYWX79+RWhoKFRVVbne3bx5MyiKgqCgIC1jLb8LDc3ZvHkzNm3aBIAltAYGBqJz585ITk4m75SXl8PR0ZFnUg9+JiwsDKKiotDR0UH79u1x/Phx2vP8/Hy4ubmBoigmHl8LFBYWYtq0aVizZg2tPCsrC/Hx8ZCXlydt6ObmRospzu9wtsOJEycgLCyMCxcuAADu3LmDTZs2oVu3bujTpw9GjhwJMzMzREREtFZ12zxhYWFQVFTE2rVrMWXKFGhqakJBQYEWgmDXrl2gKArr1q1r5dq2Pe7evYsTJ05gyZIlXM9evnyJ5cuXk9BAcnJytFsA/AznOL5+/ToUFBRw9+5dUvbixQv4+flBT08PBgYGcHd3h5KSElciW34mPz+f9nNmZiYGDRoET09PEsamtrYWiYmJMDIygrOzM6qqqlqjqm2SlvbJiYmJMDMzg4+PD80D9siRI3B3d8f8+fMZZ4aftNQOHz9+hJaWFkxNTWl7kXPnziEsLAwzZszg+8M7XjDi63+BhIQEODs7Y+DAgaitreW6RltUVIS9e/di8ODBUFNTY0SvZty4cQOxsbG0zd3Zs2chJiaG0aNHk7KUlBQEBwczA/knnJPh8ePHsXXrVmzcuJHEG87JycGYMWNgb29PPEKaw7RlE6dPn4awsDA2bdqEe/fuYcmSJaAoClFRUeSd9+/fY926dQgKCmKMQx58/PgRvXv3ponW6enpsLW1haamJjl9f/v2LVavXs0IXj/h3KCsX78e0tLSePjwIa5cuQJ9fX2sWLGCZkyfOnUK48ePZ66FNoPdji9evMDt27cREBCAI0eO0N4JCgqCkJAQzfOfgd4HL168CH19fZw7dw4XLlzAkCFDIC0tTTtcBljhlGbPns30QR7cuXMHlpaW0NfXR2pqKgDua7RfvnzBzp07MWLECBJTnIHO0aNHsWDBAmzbto3rWVFREZYuXYqBAweCoiiYmZm1Qg3bPi9fvoSioiJtznv69Cns7e2hqKiIN2/eAGD1xxMnTjDjuRnFxcXQ1dUFRVGYNm0agKaxzLbDGxoaUFNTg3Xr1tGSRjGw2LRpE6KiohAWFkbK2P2ssrIS+fn5CAwMhJycHKytrRnR6yd79+6FsrIyKisrUVdXh7q6OmzcuBFqampQVFSkvcsWYC0sLGBhYcGE9ALdrjlw4AA2b95MCwty5MgRmJubY+TIkUhJScG3b98wePBgrF+/nrlN9hPONty/fz/mzp2LhIQEcnD34cMHaGtrw9DQEOfOncPz588xePBgkk8GYLSG5jDi639IfX09QkJCoKysTMvkze5ozQctZ0wMhqZrPIKCgkhISKA9O3/+PMTFxTFmzBiu75iB3ERwcDC6d+8OQ0NDaGhoQEREBMeOHQPACkHATsK1YcMG8g3jXUPnw4cPGDBgAGmjjx8/olevXrC1tUX79u1pYTAApv+1xMuXL9GtWzfioQSw5rrTp0+jW7duMDc3J15yzBzIzd27dzFhwgScOnUKAGtTEhQUBDs7O4SHh6OoqAhv376Fh4cHLT4f0x+bSEpKgrCwMHR0dEBRFEJCQriy+86aNQsURZF2Zmhi69atiIiIoHkRVlVVYciQIZCRkeESYNkwfZBORUUF+vTpA4qisHDhQi6bkLO9mLmQN0+fPoWRkRE6d+6MzZs3A2hqK3b71dfXo76+HgkJCeQZY9/QefToEbp06UK7ddfQ0IDMzExISEhAV1eXK2490yebqKmpQXJyMszNzaGjo0NLLsOG3wWaX9HY2IhBgwaBoii4u7vTEq02H6tPnjyhCdr8zrNnz8jhCDt3R0lJCbZv3w45OTn4+vrS3q+trcXBgwfh6OjI5THLb3D2reDgYHTr1g16enpQUlKixQhPSkqCh4cHREVFoaqqCn19fZLXg9/XEs6/PyIiAuLi4rCzs4OUlBRGjhyJq1evAmDlnrC0tISkpCTk5eVhYmJCy43CQIcRX/8mvBaDyspKrFq1CgoKCpg8eTLJxsr5LmcH5ucFpflEVlVVhX379kFSUpKcKHNy4cIFUBSFRYsW/a4q/qM4duwYpKSk8PDhQ5SXl6OqqgrTpk1Dly5dcP78eQCsDYyHhwcmT57M9wtJS3z79g3Lly9Hfn4+Pn36BB0dHQQEBKCsrAzTpk0DRVGYO3dua1ezzVNdXQ1zc3NERERwxd2zs7MDRVEwNjZGXV0d0xebcezYMejr60NFRYUWX/P79+8ICwuDgYEB2rVrR0JiMIZNE+y+lJeXB1tbW2zduhUPHjxAcHAwBAUFsWvXLq4s6XPnzmU8lHjAvgbv4eFB87aurq7GkCFDIC8vTwxuhiZ4zWeVlZVwdXWFtrY2EhMTGXHwT2jeLnV1ddi3bx90dXWhq6tLkrFyil68vuFnePWtxsZGGBsbc10BLS8vh7W1NQQFBeHh4fE7q9mm4fR4Y8+BDQ0NOHfuHJSUlGBvb89TgGVgwasP1tXVISAgAJ07dyY3AThpvi/m530ywLoxxsnDhw8hKSmJjIwMACy7cMuWLTA0NMT48eNp79bW1nIdOPMTzfvfly9fMGTIEDx9+hQlJSU4f/48VFVVYW5uTt7JycnB1atXkZiYSDvY42c4//779+9j+PDhuHnzJgAgNTUVffr0waBBg3Dp0iXy3qVLl3D16lXyLb+vxy3BiK9/A87F4MaNG7h06RIuX74MgNXBli1bBgsLC8yaNYsEW+f3wcsJZ/vV1tbS2iY2NhaCgoI0N3U2d+/eZQZwC2zevBmOjo5oaGigteeYMWOgrKxM4k69ffuWtD+z8Wtqg5ycHHIVni3OrF27Fv3790dxcTEAYNWqVdDS0oKcnBwKCwtbp8JtEF7GcUNDA2bOnAlLS0vifQ2w5sdx48YhPj6eZLJloFNQUIBhw4ZBSEgICxYsoD2rqanBt2/fkJycjPPnzzOGDQ+uX7+OyMhI+Pr60kTDsLAwdOjQATExMaioqGjFGrY9WtrgTpw4EUJCQkhKSqJdXaypqYGdnR0j1DSDvZ5kZmZi3bp1WLZsGc173cnJCaampjh+/DgjwLYAZ1+sqanBly9fALDa6fjx4zAyMoK7uztKSkoAMLY1LzjbsLi4mLRhQ0MDoqKiYGVlhY0bN5J3fvz4AU9PT9y4cYPvxS427HGZlpaGcePGQV9fH1FRUbh48SIAVv4JbW1tmucc0xeb4OxHL1++xNOnT0liNwAYPnw4JCQkcOXKldao3j+C58+fg6IoTJ48mZQ9ffoUAwcOhLy8PBHAvn37hs2bN8PAwAD+/v6tVd02RfPEqVu3boWOjg4GDRqE0tJSAKw+eu3aNaiqqsLCwoLn7+HnMX348GHaz/Hx8XB3d4erqyvNhk5PT0efPn0wePBgMj9yws9t+Gcw4uv/g3nz5kFZWRnGxsYQFRXFiBEjkJOTg5qaGixatAiWlpaYPXs2l6cNP8O5IK9btw6+vr4wNTXFihUrSOzMPXv2oEOHDi0mTWCEBm5WrFgBaWlp8jN7o3z9+nX06NEDjx8/pr3PGNhNxvXx48ehq6uLiIgI2inx2LFj4erqSn6eM2cOtmzZwoxnsBZhzth7vLz7f/z4AXd3d3IQdfz4cQQGBkJZWRnv3r377XVui7Q0DgsLCzF8+HCYm5sjNjaWlPMSahjDhs78+fNBURSUlJS4kjKGhYWhS5cu2Lx5MyPA/oSzD2ZlZSE3N5eWJMbLywsSEhI4ceIE7ZpobW0ts47wIDExEdLS0nBzc4OPjw/txg5bgLW0tKRdj2dgwdmfVqxYgQEDBkBBQQEzZ84knl4JCQmwtraGh4cHuX7L9EPeREZGwtzcHPLy8li+fDnKyspQVlaGgIAAGBoawtnZGUuXLoWVlRXMzMwYT69mpKSkoEuXLpg3bx62bdsGa2traGtrIycnB7W1tUhLS4Oenh6MjIxau6ptCk47Zf78+TA1NYWUlBScnZ0xZcoU8mzkyJHo1q0bc4OiBerr63HkyBGIiorSboRmZWXB29sb0tLSNAF227ZtUFJSQlBQUGtVuU0QFRUFS0tLAKy+WFtbi3379kFLSwvKysq0d9kCrLq6Os+ktvzK6tWrMXr0aNraum3bNqioqEBOTg7379+nvZ+eng4nJyfY2toyCaj/Boz4+jfZsmULZGVlcefOHQAsr7h27dqRRaS6uhpLliyBiooKybLM0ER4eDikpKSwc+dOLFu2DLq6urC3t0dZWRlqamoQFxcHISEhWjxDhpY3GXl5edDW1sbUqVNp3l737t2Dmpoak8SjBdLT09GpUyfs3LmTKy7SoUOH0L59ewQEBMDX1xcSEhLM9WQ0Xd0xNzdHXFwcKefsm+zN248fPzB37lxYW1ujZ8+eMDQ0pF2l52c42+v27ds4ceIEXrx4Qa7UfvjwAUOHDoWdnR327NnD8zsG3qxevRqSkpJYuHAhPn36RHsWGBgIaWlpItwwsAgLC4Oamhq6dOmC8ePH4/Tp0+SZl5cXJCUlcfLkSa7kHUx/bOL58+dQUFDA9u3bAbASM3bo0AEhISFkTqyoqICJiQn69OmDsrKy1qxumyUyMhKysrKIiYnB2bNnISsri759+6KoqAj19fU4ePAgbG1tYWlpydfXapvDORajo6MhLy+PrVu34o8//oCQkBAmTpyIL1++oKKiAgcOHICHhwf69OkDb29vEr6GGc8swaaoqAi2trZk/1ZVVYVu3bohODiY9t7JkydhYWFBy/DNwGLZsmXo1q0bLl++jA8fPiAgIAAUReH27dsAWH1t1KhRoCiKsQtboL6+HkePHkXnzp0xdepUUv706VMuAbakpAQxMTFch878RklJCZnP2Lklfvz4gWPHjkFaWhpDhgyhvd/Q0ICLFy9i+PDhzMHTTz5+/EgOhznj+x8+fBg6OjoYM2YMl1NXcnIypk+fzqwhfwNGfP2bTJo0CUuXLgXAypInLi5ODG62R01VVRX27NnDDOZmPHjwALq6umTBOHfuHISEhGgCA8ASuDljKvE7nBPayZMnsX37dhw6dIh4DG/ZsgUWFhbw8fFBbm4u7t27hwEDBsDe3p6ZDHlQVVWFkSNHkqyrzWN3lZSUYOPGjbC0tMTAgQPx6NGjVqtrWyMrKwtjxoyBnZ0dLWMoLwG2sbER9fX1KCgooHnU8TOcc1p4eDhUVFQgLy8PQ0NDBAYGIjc3FwDLcPT09ISjoyO2bNnSWtVts7DbsaioCJ8+fSIhQgCWx42ioiJWrFiBz58/077j97AhjY2NXOuJsrIyzpw5g9jYWDg6OqJ///60kCHDhw8HRVG4du1aa1T5H8H169fRt29fAKwDUQUFBZqn17NnzwA0ZfVm4ObFixfQ09MjobwyMzPRsWNHmn3Y2NiI3bt3Y/LkyYxtw4N79+4hKioKiYmJpCwtLQ3i4uKYMGECLeQPOzQawNwq4+T79+8wNDTEmzdv8Pr1aygoKNCudF+4cAGfP39GfX09cxuKB2VlZRg0aBCOHj0KgNX/REVFib3I6SSyYMECZp/8C2pra38pwHLGX2f2y00cP34cFEXh+vXrAFgh5Y4ePYqePXti2LBhtHc5243f+yLn2ExNTYWGhgZWr15Nyvbs2QMTExNMmDABT5484fk7mHX5r8GIr7+AV3IoY2NjHDx4EHfu3IGIiAh27NgBgGW8LFmyhCt7Mj8P5ubtl5GRAQ0NDQCsK3qioqKk/crLy5GUlISysjI0NjaSb5kFpYmQkBBISUnBysoK4uLiMDU1RXR0NABWzFxjY2MICgpCS0sLNjY2jEdDC9TU1EBPT48W3oKzn7G9kioqKmgbFH6GM6bwtWvX4OfnB2NjYxw6dIj2DsNfY+XKlZCXlydxz6ZMmQJJSUl4e3sjJycHAMsD1sHBAdOmTWPmQQ7YbZGcnAwLCwvIy8vDzs4OM2bMIO9ERERAUVERq1evJjGdOb9lAM6fP4+goCCSRR5gCV4DBgyAi4sLTYCNiIhgBJpfcOrUKejo6ODWrVtQUlJCQEAAmS9v3LgBb29vWtxDBm6ys7Ohp6cHgGUfctrX5eXlSE5ORnV1NW2dYdYcFo2NjXj06BEoikL79u25HBrS0tIgISGBgIAAcmjP+S0/0/zvf/36NZSVlXH48GGoqqpi0qRJpJ/l5uZi9OjRJJktA3f7lZeXQ0dHBxkZGTh9+jRtHNfW1mLr1q20BD0AI/6z4ZXEjR2CoLkAm5WVBTc3N/Tu3RtVVVV8PY7379+PxYsXk58/ffqEESNGQExMjDh7sQXYXr16YcSIEa1V1TZLQkICPD09icPCq1evMGnSJNjY2GDt2rXkPbYAO2nSJK4QBAx/HUZ8bQFOoy4vL4/EPFuyZAmUlJTQsWNH7Nu3j7xTWlqKfv36YeXKlb+9rm0dtjfX+fPnYWJign379qFr167EYxgArly5grFjx+LFixekjJ8Xk+YcO3YMcnJy5BpAXl4e5syZA0NDQ8THx5P3bty4gezsbNJ/GaOGBaeY//37d7i6umLatGmorq6mPXvx4gXCwsL43kOuOew2SkpKwrBhw2BjY4OOHTtCU1MTe/fuJe8xm+E/582bN3ByciKeIenp6RAVFYWvry+0tLQwatQoMmcWFxczifJ4cPbsWQgJCWHdunU4cOAAli9fDhkZGQwdOpS888cff0BYWBgbNmzg60NQgHVjhx2ruaGhATk5OdDQ0ECXLl24Yqzfvn0bAwYMgKurK83GAZj1BGgah8+fP8fr169RX1+PV69ewc7ODmJiYhg9ejTt/dDQUPTv35+EFWHgfVMiKysLUlJSWLJkCcTFxWmxxW/dugU3NzcS7ouBN0eOHAFFUZg4cSKKiopoz86cOQOKopg9CgfssXz9+nXs2LGD/Dx79mxQFAUvLy/a+xEREdDX18f79+9/e13bIpzjmH3z88ePH3BxcSExwzn3eXl5eRgwYAASEhJ+e13bOuy+d/bsWcycORPjxo1DVlYWmR95CbDZ2dnkej0/0tjYiJycHFAUBYqisHDhQvKssLAQPj4+EBYWpgmwx44dQ6dOnTB//vxWqnXb482bN5CQkICQkBCGDx9OcnPk5eVh8uTJsLS0pAmwcXFxUFRUxPLly1uryv94GPGVB5wLSlRUFIYPH44zZ84AYHl9OTg4QF9fn8SB/PDhA9zc3GBhYcH3m7zmxMbGkgDYAGBqagqKomjxcKuqquDu7g5PT09GvGmBZcuWwcbGhlb25s0bjBkzBu7u7lzx+ABGCAOaDBrOhDEAK4B4+/btsXfvXtpVi8jISFhYWDDiKw/Y10B37tyJnJwc3Lp1C66urrCysqIdADD97tc0NjYiPT0dhYWFyMzMhLy8PPEM8ff3R9euXeHk5ESLJce0aRP19fWYNm0aAgICSFltbS3OnDkDGRkZEk4EYCXvefnyZWtUs83w48cPrF+/ntyEYJOeng4TExNYWFhwJT65c+cOSZjH0ASn17WioiK2bt1KRNUVK1ZAQkICoaGhePLkCbKyshASEgJxcfEWr+jxI5xzWVxcHLZv306ub8+YMQOCgoK0flddXQ0PDw8MHDiQmQd/8qt2iI+PB0VRmD9/Ppfgf+vWLeYA5SfssZyYmAgpKSmEhoaSWIY5OTkYPnw4OnfujJiYGGzZsgWBgYEQFRVlwlD9hLMPLl++HH5+fsRuZl/7HjBgALk9VlJSAnd3d9jb2zP75BY4c+YMOnTogKFDh0JTUxMSEhLYu3cvEbaPHDmCrl27ch3w8TsjR46Eg4MDOnbsiOnTp5NyXgLsjx8/cOnSJaYPclBYWAgrKyuYmppi5MiRGDx4MDlg4hRg161bR745ffo004b/AYz4+gvmzp0LKSkppKSk0GLHJScno1+/fhAVFYWenh4MDQ1hbm5ONjdMh2wiOzubFtf1yZMn0NPTg4GBAWJiYrBt2zY4OTlBR0eHGIWMgd0Euy22bt0KIyMj0g85T0kpiiIx5RiaYLfRmTNnMGzYMAwYMAB+fn7kpHjhwoVo3749xo8fj6lTp2LMmDEQFRVlMja2wObNm2FgYECb3x4/fgwnJydoaGgw3gw8aGkuY891c+fOxejRo8nasWTJEtja2iI8PJyZB1ugsbERzs7OGDhwIK28trYWERERcHFxYWIM/6S5t3RsbCxmzZpFylNTU2Fubg5vb28SH40N5w0KhiZOnz4NYWFhbN26lSum8MqVK2FqagpBQUEYGRlBX1+fWU844OyPoaGhUFBQwO7du4mnTWZmJjw9PdGtWzcsWbIECxYsIPYhE0aJBeffn5SUhO3bt2Pz5s348uULebZnz54WBViA8WBnc/XqVYiIiCAmJobrWXFxMebOnQt1dXWYmprCy8uLOUThQWhoKOTl5bF9+3a8efOGlMfExKB9+/bo27cv7O3tYWdnBwMDA2af3ALfvn1DSEgIdu7cScqmTJkCGRkZxMbGEgF237596N69O1dCUX6lsbERERERGDhwINLS0iAiIoKZM2eS52wBVkxMjMQTZ8PPfbB5aMfExET06tUL4eHh6Nu3L4YMGUL2ynl5eZgyZQqsra0RFRVF+z383Ib/CYz42gLnz5+HkpISycRYW1uL9+/f4/Lly6iurkZVVRUOHz6MzZs3IyUlhXRAfjZqmm/0amtrUVNTg2nTpsHX1xdlZWWor6/Hu3fvMGjQIBgaGsLe3h4TJ04kCzK/t19LG4uMjAwICQlh5cqVNA+me/fuwcDAgFxTZqBz8uRJcho6bdo0GBsbQ1ZWFhcuXADA2qSMHTsW9vb2mDRpErKyslq5xm0P9rg+ePAg1NTUiIHNLr98+TK6dOmC3r1700IQ8DucY/ns2bM4cuQIjhw5QhMGAwICYG9vTzbIXl5e2L17N2lbfhcagKZ+VlhYiJKSEgCsgwArKyvizcBm+/btUFdXR2lp6W+vZ1unuroaU6dOhYmJCRYsWEDalZ2129vbGzdu3OD6jumDTVRUVMDNzY14V1dWVuL9+/dYv349Tp48idraWpSVlSEjIwM5OTm0RHAMTWzduhVycnIk+zknnz59wqJFi6CtrQ0PDw/MmDGD2IX8bB8CdBt77ty5kJWVhbOzM6SlpeHk5IT09HSyF9mzZw/at2+P6dOn48ePH61V5TYJux0jIiIwatQoACzx6/z58xg7diwGDhxI+uanT59QX1/PxP/nQXJyMuTk5HD37l1SVl5eTg5T7t27hyVLlmDOnDmIiYlhxnEL3Lt3DzIyMjAyMsLp06dpz6ZMmQJpaWnExcWRGwLMeKbz48cPqKioICYmBikpKejUqRNmz55NnhcWFsLV1RX9+vVrxVq2Ldi3Zdn23bt37+Dn54cTJ07g8OHDsLKywtChQ2kCrLe3N/z9/ZkQaP8FGPG1BS5cuAAdHR28efMG2dnZmDdvHnr16gUFBQWoq6vzPE1mTgBYcCY4AVgnKl26dCHxStmUlJTQrnwzC3IThw4dwoYNG7Bx40ZylSc6OhoURWHBggW4dOkScnJy0L9/f9ja2jIbZNBDCzQ2NuLHjx+wtrbGH3/8QXvPy8sLsrKyxGuptrYWjY2NXNdy+Rlei+vNmzfRtWtXrFmzhjZW7927Bzs7O0yfPp3J5M2D4OBgyMrKQk9PDx07doSjoyOJ97p3714YGxvDxMQExsbG0NTUJG3LGDhNbZCSkgJnZ2ccPHgQtbW1uHPnDgwNDTFx4kSaADtz5kw4OTmRpHn8DK/+8/XrV4SFhcHCwgLz588n75w6dQrW1tZwcnJivLt+QUVFBRwdHbF48WI8f/4cs2fPRt++fSEpKQlDQ0OEhoYydsyf0NjYCD8/PxJaICcnB/v374ednR3s7Ozw9OlTAOAaw4x93cTGjRvRo0cPkvCEHevV3t4eqamppK22bNkCa2trZi1pgdWrV0NWVhbJyckYMmQI3Nzc4O7uDmdnZ8jKyhJvQ4BZj3mxZcsWImg9evQIK1euhJqaGqSlpREWFsZzzDLjmDdDhgwhIfmaryFBQUFo164d9u/f30q1azvs3bsXwcHBuHz5Mq2dli1bRpKuJiQkoGPHjjQBtqSkhNkn/+To0aNwdXXF1atX8eXLF1IeGBgICwsLAKw2tLW1haenJxFgP378yOSg+C/B9+JrS4Px2rVrMDQ0hJ2dHSQlJTFhwgTExsaSbLYpKSm/uab/DOLj42FsbIxNmzbh27dvpHzEiBHo169fix5J/DyQg4ODaVdoZ86cCQkJCRgYGEBNTQ0SEhI4efIkAJY3g4qKCqSkpKClpQUrKyvmOh5YC29ERAStf5WUlEBDQwOHDh0CAJq4qq+vTwLX83O78YI9Fm/duoW4uDgkJCSQU9J169aRpB3Z2dmoqKhAREQEfH19iVciQxP79u2DrKws7t+/jx8/fuDjx49wcXGBg4MDibO5c+dOzJs3DyEhIcSYZDYoTZw8eRJCQkJYvXo1LWP82bNnYWRkBBMTE9jb22Po0KHo2rUrE5MP9Dnt27dvqKmpIQedX758QUhICJcAe/ToUfj7+zPz4U9aagd2OCoREREMGzYMe/fuRXV1NcaPHw9vb+/fXMt/JnPmzIGJiQmWLl0KW1tbeHh4YMqUKXB1dYWysjIqKipocyA/24fNKS0tRXBwMHbt2gWA5dwgLi6OVatWQUdHB4aGhjh16hTXIR7Thtzcu3cPY8aMgZiYGPz8/HD+/HkAwIMHD2BkZMQk1voT0tPTQVEUxo4dCyUlJfj4+CA6Ohrr1q1D586dkZOT09pVbPNwjsuhQ4dCUlIS6enpXAJscHAw37fny5cvSXItNzc3mJub49KlSygqKsKLFy8gIiJCnLyOHDmCLl26YMKECbTfwe/2TU5ODmRlZUFRFHr37o2JEyeSRGWlpaUYOHAgjhw5AoAVpsrR0REODg60BI783ob/DfhafOUUB3mRmpqKDRs24MSJE+Td4uJiGBoakkWa32lu0KWmpiIqKookjQkLC0N1dTUSExPh6OhIstUyg5dFdXU11qxZA2NjY4wbN454sz58+BDl5eUoLy/H+PHjISoqSsSa3NxcPH78GLdv3ybtyO/eNqtXrwZFUVi+fDlNgDUzMyPXyoAmAXbUqFFM0PpfkJiYiK5du0JdXR1KSkqwsLAgXiAbNmyAlJQUevbsCU1NTXTt2pWJa9gCkZGRcHFxQWNjIxETPn36BDMzM66YpWz4fSyzaWxsxJcvX2Btbc2VoZvdlg8fPsTevXsxcuRIREZGIjs7uzWq2qbgXFtXrVqF/v37Q19fH2FhYSSsSnFxMUJCQmBpaUkLQcDrd/AbN2/eJKFBONuF878vX75MbEB2X5wyZQr8/PxQU1PDCF1/wvnz5zFp0iQoKSlh1apVZP04cOAA+vfvT7sRxUCnvr4e169fR1FREbKysqCuro6NGzcCANLS0tChQwcYGRnh2rVrAFj9lumPLVNfX891YyckJATm5uZM+Jq/wIEDBzBkyBDs2bOHhBv4/PkzzMzMmINQHrDH4ps3b/Ds2TOukHEDBgyAtLQ00tLSGFuQB8uXLwdFUVi4cCFmzZoFW1tbWFtbIyEhASNGjIC/vz9ZP+Lj4+Ho6MjX9kxzSkpKsGzZMjg7O8PW1hb79++HkZER+vTpgxkzZsDd3R0hISHk/a1bt2LatGlMG/6X4VvxdebMmZgyZQoAbuOEVyerra1FUVERPDw8YG1tzXgmgd5OzRNP5OXlYcGCBdDT04OWlhaWLVsGISEhjB079jfXsu1TUVGBHTt2wMzMDA4ODrC3t0dpaSmtfUeMGAE1NTWecaeYSZHFtm3bQFEUli5dSq5S7NmzB/r6+liyZAnt3ZEjR8Lf3x/19fXMxuQn7HaorKzEmDFjsG/fPpSUlODixYswMjKCuro6EWDv3buHU6dOIT4+nuaNyMCCvT7MnDkTNjY2pJztQXzhwgV06dIFOTk5zPj9BaWlpVBRUUFiYiLP55zXQhnoREREoFu3bti1axfWrl0LKysr2Nrakjj2xcXFCAsLg4qKCknywe9z4dmzZ6GqqoqlS5eSa+9/Zhvm5+cjIiICYmJiTMzwv0FdXR3XbQlXV1eMGDGC7/shANqBHRt2/2MfIsfFxcHa2pqEpjp8+DB8fX0REBDA7FH+BF59LDMzE4GBgZCQkGCEw5/8lbHI7mvs2Liurq5wcHBgbJtmsNsyOTkZysrK0NDQgJCQEKKiovD8+XPy3oABAyAvL4+UlBRGgOXBggUL0LlzZ6SlpSE7Oxv79u2DpqYmREREYGxszNMuZPpiU//78uULVq9eDRMTE4SHhwNghXOYNGkSKIqClJQULV49k4Pivw9fiq9JSUk4evQomdTYglZLxkp1dTXWrVuH/v37w8zMjMnW2IzFixfDysoKxsbGiI6OJld1ampqUFlZidDQUAwfPhwURcHU1JQxrDlgt0V5eTm2bdsGIyMjyMnJkb7FPsG7du0aevTogcePH7daXdsqnAvCli1biABbU1ODb9++ITw8HLq6uhgyZAg2b96MiRMnQkREBM+ePWvFWrdNrl+/DnNzcwwePBivXr0i5ffv34ehoSHU1NQYwYsHvwpfQ1EUtmzZQitPT0+Hnp4ek7H2T/jw4QPExMQQGxsLgCXYsOfM7Oxs7N+/n5bAjIFFcnIytLS0yE2Ts2fPolOnTtDT04OZmRlZRwoLC7F161bGlvlJfX09pk6dCnNzcyxfvpwkNmnJZrl27RocHBygpaXFeP//RZq3ZVlZGc6cOQMnJyfo6+sT+5qf7US2ByEbtt0ya9Ys0s8aGhqwcuVK6Ojo4NGjR/j27RsGDhyIdevWke/4fVzz6kMtrdXZ2dmIiIiAo6MjE/f6J5wH64mJiVz5PDiprq5GTEwM7O3tYWxszIRDa4EzZ85AXFwcW7ZsQU1NDTZu3IjOnTtj+vTptMM7Ozs7qKmpkSRbDHTmzp2Ljh07kji4RUVFOH36NLOv+xPYc+LXr1+xZs0aaGhoEAEWAE6fPo2XL18CoI9dfl6P/xfwnfhqYmICb29vYpTExcXB0tKSxLNoyVg5deoU1q5dy2RrBH1A7tq1C5KSkoiOjoanpydMTEwwbdo0LuPxw4cPtGsUzEBugt0WFRUV2LlzJ+Tk5ODp6Ulr5/v370NBQQH37t1rrWq2aTj7E1uAXbx4MRobG1FaWopDhw7Bzs4O5ubmcHd3Z0TsFjh16hR0dHQgJiZGkgqybwbcv38fZmZmkJaWZq6F/qS5EH3ixAns2LEDp0+fxtu3bwEAS5YsQYcOHbBixQq8fv0aeXl5cHd3R79+/ZiNyS9gj+ng4GDIy8vj8uXLtOezZs3C4MGDmeRaPMjIyCAJjU6dOoVu3bohOjoap06dgrS0NKysrJCZmUn7ht+FGs6Y4EFBQbCzs8OKFSvI5rclm4VzrDNwiy3sdmupf927dw9BQUHw8/Nj7GsAK1asQPv27YmIMG/ePEhJScHT0xOWlpaQlJQkIajy8vIgLy8PJSUl9OzZkyZe8zvsfnfx4kUsWLAAwcHB+PDhwy+/ycvL45lMmR+5efMmTE1NkZycjDlz5qBjx46/jIH79etXHD58mBa7np/HMS9KSkrg7e2NqKgoAMDbt2/Ru3dv2Nvbo2vXrpg0aRJNgG2+j2agM2/ePAgKCiIuLo5WztjVv4Y9N5aUlGDNmjXQ1tZGUFAQz3cY/jfwlfh6+vRpqKurkys6paWlOHjwICwtLTFgwADiZv1nmxB+36SwyczMxPTp03H8+HFStnbtWlhaWmLq1KktLtTMgswN55XvHTt2QEdHB66urnj48CEyMjLg5uYGMzMzZlH5BS0JsOyr3gDLk5jzZwY6VVVVSE1NhbKyMuzs7Lie3759G/b29lxxqviRkJAQhIaGEs/L2bNnQ1JSEqqqqtDU1ISSkhLu3r0LgJWdWlRUFAoKCujduzfMzc0ZzxAOGhsbW8yi+vDhQ4waNQoyMjLYtGkToqOjERgYCDExMeYQBcCzZ8/IIcCqVavI2Pz69SsqKyvRt29fEnalvr4eZmZmUFRUJIkoGCObBbsdHj58iDVr1kBBQQHdu3fHmjVreIYgYNrt12zYsAGTJ0/GzJkzSbbklua69+/fk/bkd/vw7t27GDx4MBQVFXH37l2Eh4cTD/bXr19j7Nix6NChAy5evAiAFTty9+7diIuLY0SvZpw6dQpCQkLo168flJWVISsri7Nnz7Z4QMDQxJMnTzB69GgoKChAXFyc3IT61f6X8xmzT+amvLwciYmJePPmDb58+QI9PT1MnDgRALBmzRqIiIhgwoQJTPiav0FERAQ6duyIAwcOtHZV/lE0F2D19PQwc+bM1q0UH8FX4mtKSgo6dOiA169fIyAgAN7e3qipqcGRI0dga2sLV1fXvyzA8jvnzp1D7969IScnh9TUVNoztgAbGBjIeIT8DTg9YKOjoyEnJwdhYWH4+PggMDCQCXfxF+AlwC5fvpwWv4aBBef1k6qqKpJUsKqqCqdPn4aGhgb69evH9R0jXrOYMGECTE1NsXTpUpw/fx7W1ta4ffs2ysvLce/ePfj6+qJLly4kxmZeXh4uXryIq1evkjHMr5tk9uaXsy/9aq3IyclBVFQUevbsCUNDQzg7OzPCK1hZufX09LBu3ToEBQWBoiha0rH8/HzIy8uTA9KPHz/C29sbSUlJjOjPg1OnTqFdu3ZYsmQJVqxYAUdHR6irq2PFihU8BVgG3ixZsgTS0tLw9PSEgYEBpKSkSAzNX11lZNqWxePHjzFo0CBISUlBV1eXXAMFgIKCAowbNw4dO3bEpUuXuL7ld/uQM5TXrFmzSMiampoa+Pr6QlxcHGlpaUxf+wssX74cgoKCMDQ0pMVdZ9aO/z9sO3v79u20LPLR0dFQV1dnwlGBd//6VZ+LjIwERVE4c+bM/7Ja/yj+ygETpwC7bt06yMjIYMOGDb+jenwPX4mvAODj4wMJCQl07dqVbN4aGhqQkJDACLB/k/DwcEhLS2PSpElcV3XWr18PFRUVrFmzppVq1/ZoafHgtRmprKxEdHQ0VFRUEBkZSZ7zq1jzK361gdu+fTsoisK6desYY5sDdlukpqaiT58+MDExgaOjI27cuAGgSYDV1NRE//79W7OqbQ7OfhQcHAxbW1tMmDCBK1TIhw8f4OXlBQcHB55XGfl9fcnNzUVwcDBKSkpw9OhRUBTF5VHdfMyWlJSgpqaGiYPGwaxZsyAtLQ1hYWEyftnrRHFxMVxcXDBw4EAcPXoULi4ucHJyIv2U2USzaGhoQEVFBfr06YPZs2fTnvn7+0NVVRVr1qz50xAE/ErzfhQSEoJr164BYB0AeHp6QlxcnBxEMf3uz3nw4AF8fX3Rvn17coOC3e8KCgowYcIEUBTFxBoG69CEc429ffs2evToAWtray6Bmi3ApqenM/2wGc3XhcuXLyM1NRVjx46FjY0Nia/J8Oewx+qdO3eQkJCAlStX4sOHD+TAedGiRbC1tSXJqufOnYv4+Hi+j2HPOSY/fvxIxGrg1/vfmJgYZn/8E842zM3NRVFRES0cDa8bPF++fMGhQ4f4fl/yu/jXi6/Ozs64cuUK+XnOnDkkmxtnQhm2AGtnZwd3d3cyITL82lAODQ2FoaEhFi9ezJW5NiEhgRnIP+Fswzt37iAzM5NsTprDngzLysqQlJRE2pDZ8DW1wefPn5GXl4fv37/zTNDB+d+7du1igrDz4MSJExAWFsayZctw9OhRjBo1Cl26dMHZs2cBsLwS09LSICsri8GDB7duZdsYnPMaW/xSVlbmEmf27t0LJSWlP401x48kJydDREQErq6uEBISwt69ewG0PM+xYw8z0NeTgwcPklAXa9eupW1WACA+Ph59+vSBsrIynJycmHAXHHBuPADAxcUF06dPB0Df6Nna2qJXr16IjIwkSbgYWHD2o5s3b+LSpUvo168fbt26Rco/fvwILy8vSEhIELGQGct/zqNHj+Dm5gYZGRlyFZndbvn5+Vi6dClfCw4NDQ24d+8eREREaMmgysvL0b9/f1AURTw2Ofvp2LFjQVEUzp8//9vr3FbhjOOfm5uLr1+/krXi7t278PHxgY2NDQ4ePEjei46OJmH8GLhJTEyEnJwc+vbtC1NTU8jIyGDbtm0AgKNHj0JYWBhDhw6Fu7s7hIWFmXADHPzxxx/Q0NCAiYkJCc0A/LkDEj/Ph82ZN28edHR00K1bN4SGhpLwNcCvQygxus3/nn+1+Prx40eS9ZzNtm3bcP36dXh6ekJWVpZchQJYHfDIkSPQ1NTEnDlzWqPKbQ5Og2Xv3r2YNWsWwsPDkZCQQMrnzJkDY2NjLF68mGvjBzADmXNimzdvHrS1taGhoYGePXvC19eX50knMxlyw26T5ORk6OnpQVVVFfr6+pg9ezZev37N9T4jLrTM69evYW1tjc2bNwNgedL06tULysrK6NChA9LS0gCwDPKzZ88yMV55wDkm58+fj+7duyMsLIwW4iIzMxO9evVisie3wLx580BRFPr27UviQgKMMPMrONtmypQp0NHRwbt37xAcHAwTExMsW7YMpaWltG8qKiqQn59P5kRmg9IEOxljXl4eRo4cCVtbW9I+7DE+d+5cyMrKYsCAAUSoZaATFhaGLl26QEdHBxRFYd++fbTnnz59gre3NyiKQk5OTivV8p8HOwSBgoIClwDLht/HM9vx48WLF2T9LSsrg4uLCxQVFck+j7PdAgIC8OLFi99f2TZGZGQkzZaJjIyEkpIStLS04OHhQfYn7FBKZmZmiIiIwIABA9CjRw/Gzm6Bhw8fonv37uRQuby8HBRFYdWqVeSd3bt3Y9SoUfDx8cHTp09bq6ptAs5+dODAAUhLSyM2NhaRkZHQ0NCAjY0Nec7v8x0vOPMmACxxX0FBAcnJyVi8eDEsLS0xdOhQZGRk0L5haB3+1eIrJ6tXr8bJkyfJz0VFRRg4cCCXANvQ0IALFy4wYlczQkNDISMjg6FDh6Jfv35o164d8RABWMlmzM3NERISwniGtMDatWvRrVs3ZGZmor6+HkuWLAFFUbSs08xk+GsuXLgAYWFhbNiwAWVlZYiIiEDnzp1phwEMf05ubi7CwsLw/ft3FBQUQENDA/7+/igoKICDgwPExMRo8yUDbzjXiTlz5sDQ0BATJ05EVlYWHjx4ABcXF1haWjIblGaw223RokWYM2cOFBUVMXXqVDx//py8wyQ34oazHZ4/fw5zc3OSeKexsREzZsyAiYkJVq5cSWKUTp8+HW/evCHfMX2RHhfSzs4O69evB8DKLt2tWzf4+fnRDu3nzJmD6Ohovo/FxwlnX8zIyICRkREuX76M69evY8yYMRAVFeXyLCwoKMD8+fOZzfPf5NGjRxg8eDB69uzJhBnggPMw6cOHD6AoCjNnziQHJOXl5ejbty+UlJR4CrD8zsOHDyEtLQ0HBwcAwNmzZyErK4tjx46R3B0qKirkMO/Ro0cIDg6GpaUlBg0axNyi+MnNmze5HI/S0tLg4uICgLVWKykpYdKkSeQ5u4/W19fzvd7AOSZTUlKwZ88eHDp0CABrbF+9ehXKysqMAPsXuXLlCmbMmIHdu3eTstOnT6NPnz4YMmRIi7duGX4f/1rxlXMyq66uhre3N7p06UITFIqLizFw4EDIycnRBFhev4OfuXz5MmRlZXH9+nUArPZMSkpCly5dEBYWRt6bNGkSJkyYwBg3LTBu3Djs2rULAJCUlARxcXFER0cDoF/5YeCmvr4eDQ0NmDp1KmbMmAGAFXqgV69emDZtGnmvsrKytar4j4N9FX727NkYPHgwuTIfEBAAYWFhSEtLo6ysjBnPfwLnOhEaGgoxMTFISkpi0KBB8PPzYzYof4GEhAT06NEDU6ZMoXkjMUm1eLN7924MHDgQfn5+qK+vpwmFM2fOhKmpKTw9PeHk5IRu3boxGxUenD17FmPGjIGvry/tyvL58+chKSkJCwsLjBkzBqNGjYKQkBDj/d8CGzZsQEhICIKDg0lZQ0MDxo4di65du7Z4tZvf+2RL60FL6+3jx49hY2PDhADigN1WbO/MPXv2oEOHDpg7dy7xgGULsKqqqrh//36r1bUtUltbizNnzkBPTw8ODg7YtWsXTbB5+PAhTE1NoaKiQtq4rKwMFRUVpO35eRw3Njbi7t27oCgKS5cupd1iXL9+PSwsLFBaWgolJSUEBASQMX/ixAnMnj0bFRUVrVX1NoGTkxPN4zc7OxuSkpJo164dDhw4QMrr6+tx9epVqKiowM7OrjWq2mbx9/cnoUAaGxtx//59qKqqQlRUlCt51unTp9G3b194enriwoULrVBbBjb/WvGVTVpaGsrKyvDx40dMmzYNYmJiOHHiBHn+5csXDB48GBRF0WLAMjRx9OhRaGhocGU5j4uLg4SEBG7fvk3K2AsyI9jQqaqqgrq6Ovbv34/Lly9DREQEO3bsAMAyXv744w/G0/AnnH2HM0g4AAwfPhwHDx5EcXEx5OXlERAQQN4/efIkzpw5w/S9n7CN4l+JfvX19XBxccHcuXNJWVBQEI4dO8Zcr/3JX0mUxynALliwgFyZYjYoTbDb4u7duzhw4AC2bdtGuwqfkJBAPGAzMjKwePFiUBSFkpISZkxzUFpaiqCgIHTv3p14LAGgrc9r1qzB+PHj4evrS+ZQ5jCZzsGDB9GpUydISkpyxWT+8OED/P394eXlBS8vLyZsyC/w9fUloUM4bz01NDRg3LhxkJSUxKlTp1qxhm0PzrUjJSUFu3fvxurVq//01tirV6+YQ7xmXLx4Ef369SOe/gcOHABFUTQBtqKiAsbGxtDX1+fax/ArnF7D6enpMDExQbt27UhMUoC1Zj98+BDm5uZQU1PjCmfDz32R0ybZvHkz2rVrRwv58+bNG+jq6qJTp04ICAigfRMcHIwBAwbwDNPHL5SUlCAsLIw2Hr9//45Dhw5BRUUFbm5utPcbGhpw7do1dOnSBVOmTPnd1W2TfPr0CYsWLeLaJ8fHx0NdXR1OTk5ctktaWhr09PQQHh7+O6vK0Ix/tfj68OFDGBgYEPf13NxcTJkyhUuALSoqQlhYGLM5AX0xZQsGGRkZ6Ny5M8mkzCYrKwuysrLk2iMbft8ot2SQhIeHo2/fvhAWFiYesACr/7m7u2PLli2/q4ptHs6Ed+fOncPhw4cBsDZ6JiYm6NWrFwIDA0kfraqqgo+PD98noGCzc+dO9O7dm3gC/8pInjlzJsTFxbFnzx5MnjwZsrKyjJfXTzjb7fnz53jw4AHtkI5zzeD87w0bNpBv+X0+BJraICkpCZKSkujTpw9kZGTQr18/xMXFkbY7evQotLS0oKurC0VFRVqCAH6F19jNzc3F3Llz0alTJ6xYsYKUc3rAcsLMiSw4x2JFRQUSExMhIiJC28yx24r9bkttyo+0NJfNmTMH7du3R3x8PO32SWNjIwYNGgRnZ+ffVcV/FKGhoVBSUoKTkxPMzc0hJyeHCxcucI355u3Or6LX5s2bSZgudpssXrwYo0ePppVxCrDsQ+SKigq8ffu2FWrd9mjen6qrq5Gamgp9fX0YGRlx9a9Hjx5BSUkJI0aM+J3VbLOw2+fTp0+4e/cuioqKcPDgQVAUheXLl+P79++orKzE/Pnz0bt3b+LckJOTg3nz5kFCQoJJrsXBqlWryFX4srIyHDlyBPLy8lz9rb6+Ho8ePWK0Gh7s2bMHy5YtIz/HxcXByMgI/v7+XH3t5s2bTBu2Mv8q8ZWXwTJs2DBanJCXL19iypQpEBcX5+lpyM8dkrP99u3bh7i4OJSUlKCoqAhubm7w9vamXdv5/PkztLW1kZ6e3hrVbZNwtmFWVhYtnEVqaiq6d+8OR0dHZGdnA2AlhXN3d4eVlRVf9z1OSktLoampiYCAAJw6dQoURSElJQUAK1GUnp4eFBQUyPuNjY2IiIhAz5498fLly9aqdpvi3r176N27NywtLf9UgM3NzcXo0aOhqqoKCwsLPHjw4HdWtc3CuUGJiIiAkZERpKWl4eTkhDFjxvD8pvkYZsZ0E1euXIGsrCy51piVlQVBQUGYm5sjOjqatNXTp0+RmZmJ9+/ft2Z12wScYzY7Oxu3b98m2aVLSkoQGhoKdXV1rFu3jrzXXGhlxP+mNqioqKC1T1VVFfGAnT17Nimvr69nbvE0g7MvfvjwAW/fvqV5ak6cOBFdunTBwYMHaWGUmicCYWARHx9PyzmRnp4OiqJw+vRp8g7T95qoq6uDlZUVZGVlafuQOXPmYNy4cQBYfZRTgO3QoQOCgoKYWzwccI7F5cuXE8eGmpoanDlzBpqamrC3t+eyXV69esXYM2hqv2fPnsHGxgbOzs4YOnQoAGDjxo2gKArLli1DQ0MDioqKMH/+fCgpKaFr167Q09ODlpYWY2NzUFFRAXd3dwgJCZFbtGVlZTh8+DB69uwJb29vnt8xfbGJ0tJSjBw5Eqampti4cSMp37VrF4yNjXkKsADThq3Jv0p8ZXP27FkSlP7Hjx9QUFBAUFAQeZ6bm4tp06aBoigm8DAPQkJC0L17d+zatYtkoD527Bjs7e3h5OSE2NhYnDlzBi4uLjAxMWEGMA/Y2ZFlZWWhp6dHYhceOnQIWlpa0NTUhIGBAczMzGBqaspcDeXgx48fOHr0KCQkJCAkJISjR48CYBnfNTU1OHLkCOTk5KCnp4ehQ4diyJAh6NatG2PQcNDY2IinT59CX18fZmZmJLbUrzbBHz9+pMWsYmCxcuVKdOvWDVevXsXXr18RGBgIiqJw8+ZN8g6zSf41dXV1WLlyJWbNmgWAdYiioqICX19fuLq6QkVFBbt372bmPw44+9T8+fOhoaEBZWVlKCsrIzQ0FJ8/f0ZBQQHCwsKgqanJFd+LgQW7Hc+cOQN3d3c4Ojpi4MCBZK6rr68nAixn3FKGJjj7YmRkJExNTSEsLAxXV1csXLiQPJswYQKEhYWRkJDAFX+dEWDpLFu2DHPmzAEAHD58GF27diWhqDhFbWZtaaKyshIDBgyAgoIC7t27B4CVUHDChAkAmnIDsNm9ezfExcXJgRW/w9k2L168gLu7OyiKQlpaGgCWAJueng5dXV04ODjwHLP8vEazx2JWVhbExcURERGB/Px82rXvTZs2kRiwjY2NqKmpwefPn3Ho0CHcu3ePFl+cgUVhYSF8fX0hIiJCPNvZHrDKyspwcnJq5Rq2fd68eYMpU6bA0tKSdhgfGxsLMzMzeHl5IS8vrxVryMDJv058TU1NBUVR0NXVJR42+/btg52dHc3T9eXLl1izZg1zHa8Ze/fuRffu3ckEyMnJkycxceJEdO7cGSYmJnB2dmZEw59w/v2nT5+GqqoqUlNTcenSJTg7O0NOTo4I/Q8ePEBCQgKWLFmCY8eOkW+ZvtjEgwcPQFEUhIWFERgYSHtWV1eHt2/fYsaMGQgICMDSpUsZj9efcHoZPX78GPv37wdFUXBxcflLIQgY6FRUVMDT05MEtE9LS4OoqCgJG8IkyvvrPH/+HM+ePUN5eTlsbW3Jhvnt27cQFxeHjo4OLdkHA4u1a9fSwvv4+PhASkqKrNFv375FeHg4xMXFiRcTA52UlBSIiooiLCwM8fHx0NfXh6mpKTkUra+vR0JCAiiKQkRERCvXtu2ydOlSSEpKIjExEUeOHMGcOXOgoqJCW6MnT54MiqJw7ty5Vqxp24LXmuvj44MJEybgypUrEBUVxfbt28mz5cuX00Rthiaqqqrg4uICOTk5vHjxAoGBgeRa97dv30iYkDdv3gAAc6DMg/DwcFhYWGDIkCGQlpaGoKAgjh8/DqBJgNXX14e2tjYj/jfj69evsLW1xfTp02nlnPs3tgDLGQOW4dcUFhZi5MiRXAJsXFwchg4dyuxbfgF7jL59+xYBAQFcAuzmzZsxfvx4pg3bEP948ZXdmdj/FhQUoH///ujfvz/ExcUREhKCzZs3Y8CAAQgPD+eZDZ0RvZoICgqCj48Prax5+3z48AGFhYVMMhmAZIhnEx8fjy1bttAmPgBwd3eHrKxsi57W/C5es2GP4y9fvuDWrVs4cuQIZGVl4e/vT97h5/72V0lMTIScnBymT58OOzs7iImJwcLCghFg/yZVVVUwNDTE+fPncfr0aVqivNraWmzbtg1nz55t5Vq2PTg3bOy5jV127do16OnpkWtQd+/eRb9+/eDn54f8/PzfX9k2SkNDA2prazFo0CBs3boVAHDq1Cl07doV0dHRAJrikebl5WH79u3MOsKDly9fwsDAAJs3bwbAsl+UlJQgLi6OXr160QTYY8eO4fnz561Z3TZLSUkJ+vbtS4tX//XrV+zYsQNqamrYs2cPKV+1ahWzTvOAHW4KYGU819PTQ4cOHch4Blg25cCBAxkvbA7Yawc7QVFNTQ2cnJygqKgIXV1dCAsLw8DAAFJSUlBVVYWOjg40NTXx/ft3RjxsxoEDByAsLIxbt26hvLwc2dnZCAgIQPv27ZGcnAyA1b7JyckYPXo0s6Y049mzZ1BVVcWVK1e47GjOsBebN29G+/btMX/+fOYAAH9tz8EWYLt27UoEWE7Nht/3Lb/6+5sLsFZWVrTbUOzn/N6GbYV/vPjKhu351tDQgDVr1iAwMBD37t3DrFmz4O/vD1lZWXTu3BmpqamtXNO2CXtgenp6EvGVc9GtqanBuXPnUFJSQvuOnweytbU1YmNjyc+VlZVQU1MDRVGYMWMG1/vu7u7o0aMHLly48Dur+Y+A3f/YGWvZHtVfv35FXFwcZGVlMXnyZPL+7t27ceTIEdq3DCw+fPgARUVFrFmzBgArmcKlS5egrq7OCLC/gFd7/PjxA+7u7hgwYAAkJCRo3klv376Fu7s79u/f/zur2eZhj8fz589j1qxZcHZ2RkxMDMm6evHiRaiqquLEiRNoaGjAwoULMXHiRDL2GVjU1dWhrq4OhoaGyM7OxtWrVyEiIkKEmurqamzdupXESWPDbJbpPHjwAH/88Qfq6upQUFCA3r17IyAgAB8/foSmpibMzc1pMSQZeFNeXg4VFRX88ccftPKSkhK4uLjQYuay4XcBlnNNycjIAEVRxMPww4cP8PLygo6ODrZv347y8nI8fPgQ7u7uMDY25kr8xq+w//709HRMmDCBeFRXVFRg5MiRoCgKq1atQkZGBk6fPo2zZ8/iwoULeP36dWtWu02waNEiLoejpUuXol+/frSywsJC+Pj4oEOHDiSHR01NDWl7Zk1p4uDBgxAUFPylmFVRUYHPnz+TsBdMzOEmLl68yKUjcMIOQUBRFJ49e/Yba/bP4cyZMzzLOQXYKVOmQFVVlXYbit/XkrbEv0J8vXjxIiiKQnh4ON6/f4+6ujqYmpoiNDQUAMuzZuzYsaAoigTGZuDNmjVr0KlTJ+Tk5NDKP378CD8/P1y+fLl1KtYGiY+PR3V1NQCQfwsLC9GvXz+oqKgQDxrOCc/c3ByDBg36/ZVtw3DG5Bs4cCD69u2LYcOG4dOnTwBY3g5sAbZ///6YOXMmKIrCixcvWrPabZacnBx0794dt27dImV1dXU4f/48hIWFMWDAABIDloEFpwH9/PlzvH//nsTdS0tLg6CgIPr160fKvn79Cnd3d9jZ2TEbEx4kJydDVFQUU6ZMwYIFC6CgoAB3d3cUFBSgsLAQtra2UFNTg7a2NiQkJJh4zQCJYQiwvGYuXboEABg8eDA0NTUhIiKCvXv3knc+f/4MBwcHxMTE/Pa6/tNgexxOmDABI0aMQFVVFRoaGjBo0CBQFAU9PT2yhjM0rcmctktFRQX8/Pzg7e3N5aE+depUDBo0iDnQ44Cz7bZs2UKS8XTr1o1siF+9eoUxY8ZAWVkZoqKiMDIygqOjIxPOqxnHjx+HkJAQVq5cSTsoKS8vh4eHB3r16sVkj2/Go0ePYGVlxXUAsmXLFkhKSqK4uBhAUz9NTk4GRVEQFBQkAiwj1nBz48YNCAkJITExscV3Nm7cCGdnZwAsW5GBxbVr1yAvL08ORlpaLz59+oSFCxfy/eEdL16/fg2KokgulOawx+zr16+xatUqZg1po/wrxNfv378jKSkJqqqqcHd3R2xsLN6+fQtLS0ucOHGCvHfw4EGmI7YA57UedjylO3fukKQebm5usLCwYNoPINlp2SxZsgQLFiwgV6KKi4thYmICXV1dvHr1CgDdiGE2KNykpKRAREQE8+bNw5YtW2Bvbw9VVVXi0f7jxw+kpaWhb9++cHV15fp/wNBETU0NlJWVsWDBAlp5WVkZTE1NQVEU+vTp00q1a9tERERAQUEBampqcHBwIHHj4uPj0aFDB9jb28PCwgK2trYwMDBgNsk8eP/+PQwMDEh4hsbGRhJvkz33ffz4ETExMdi0aRMTrxkswV9NTQ0zZ87E7NmzISgoSATDy5cvw9DQEEZGRgBY7fnt2ze4ubnB1taW6XsccNox379/pyUuqqqqgqOjI9auXUvKgoKCcO3aNbx///6317WtwmmffPjwAR8/fiTz3Llz5yAmJoaQkBAybsvLy2FnZ0eSRzHQiYyMhLS0NA4dOoTNmzfD29sbHTt2xKFDhwCwMlXn5+fjxIkTePLkCWl/Rnhg8ebNG2hpaWHLli20cnY7VVZWwt3dHZ06dWLswp+w+w67jVJSUsjV9ydPnsDCwgIzZ87Ehw8fyDd3795FQEAApk+fDiUlJWL7MNApKCiAjIwMBg0ahLdv35Jyzj1ecHAwQkNDaWEIGFgYGRnBz8/vL7/PzIN0GhoaMG7cOAQGBqKuro6nntC8zzE2YtvjXyG+ssnJyUFkZCQ0NTVhZGSEYcOGYdq0aUQUY8MM5l/z7NkzeHt7Q0hICEpKStDR0YG5uTkxwPlZPAwODoaBgQFJfgKwrvGwrz5xCrDGxsbQ09NDbm4u1+/h5zZszosXL2BkZETiGr579w49e/aEhIQEZGRkuDxcm8fZ5Wc4F1lOb6WwsDBYW1uTRFEAq89NnDgRJ06cYAzrn3COw7Nnz6J79+5ITU1FdHQ0XFxcIC0tTdrq1q1bWL16NcLDwxEXF0fWEX5dT5rHW2dTUFAAIyMjVFRU4OXLl1BQUKDFbL558ybftllLlJaWYtu2bZCUlISoqCjtul1lZSV27twJDQ0NKCsro0+fPrCwsICRkREj/nPAnv9OnDiBPn36QFlZGQMGDMD69evJOw4ODjAxMUF6ejqCgoIgKyuLd+/etVaV2xyc68kff/wBXV1dKCkpQU1NjXjanDhxAnJycrCysoKjoyOsra2ho6PDjGkeFBUVQVdXl+adXl1djaCgIHTq1AnHjh3j+R1jHzZx9+5d9OzZEw8fPiRlzcWF6upqeHp6Mgd5YCVyO3r0KFkb8vPzQVEURo4cSRKErlq1CpaWlhg7dizu3r2LZ8+eYcCAARg3bhyuX78OWVnZFq82MwBJSUno1KkT/Pz8aGt1RUUF5s2bByUlJa7bo/xG8zmMfbPk0KFDsLW15XkzlIFOS+tAbGwsxMXFyQ0Upg3/efyjxNdfdTD2M/aGb8CAARAUFARFUcxV+Z+0NJBbatezZ8/i2LFjOHnyJNnc8buB/fr1axgbG8PZ2Rnnz58n5Rs2bABFUVixYgVNgDUzM4OMjAwKCgpaqcZth5b637179zBnzhzU19fj/fv36N27NyZNmoTs7Gyoq6tDQ0ODlqiCgQV73F68eBGhoaEYOnQo9u/fj3fv3qGoqAheXl6wsLBASEgIzpw5g6CgICgqKjJ9kQexsbHYunUrOQAAWIcCTk5OkJKSItekms9//Cp6scfymzdvEBMTQwsb8OjRI8jKyuLKlStQVVXFpEmTyPuPHz/GyJEjmTADHLDH8fHjxyEuLg5VVVWu+JnV1dV49eoVFixYgKioKMTExDBrMg/S0tLQqVMnrFixAhs2bEBwcDCEhYVJe75+/RqGhoZQUVGBpqYm0w9bYOnSpeR6/OnTpzFp0iRISEiQBB6ZmZnYunUrpkyZghUrVvD9QVRLFBQUQFJSkgjXbE+40tJSmJubo1u3biTJESO40mHPi5cvX4a8vDzxauVcczMyMpiElxw0NDRg6NChkJKSwqlTp0hCxitXrkBSUhIjR44k/WzTpk1wcnICRVFQU1ODgYEBGhsb8eXLF6irq9McTBjoNDQ0IDo6GoKCgtDQ0MD48eNJ6BUZGRlmXeHgxo0btJ/z8vKgoKCA1atXt1KN/nncu3cPeXl5tLI+ffpg0qRJ5JCF4Z/FP0Z85ex4iYmJ+Pjx459+s2PHDkycOJExCEE37O7fv4/09HRkZ2eTeDR/xfDjV6GBDfvvz8/Ph5GREfr160cz/NatW8clwBYWFmL8+PF833bs/lVQUICDBw9i165dNI8jtsfChAkTMHz4cGI0DhkyBBRFoXfv3qSMoQl2LDRvb2+4u7tDQUEBAwcOxIMHD1BcXIyoqCioq6tDRUUF2trajFEIVqI8znhd+fn50NfXJ2MXaNr4vXjxAi4uLpCVleXpwc6PsMfykydPoK6ujqFDhyItLY32jo+PDyiKwogRI2jl8+bNg5mZ2V9av//tNF9zP3z4gOzsbGzduhW6uroIDAz809/B7+sKJ7W1tRg9ejRmzpxJyioqKrBv3z4ICwtj27ZtpPz169e/TPrBb3B6sX/79g3W1tbYtGkT7Z3IyEgICwtzbabZ8Htf5HULBWDFbHZwcCD9rbGxEY2NjRg9ejT09fWZ6/Ic8HIE+fHjBxQVFTFs2DCuZ3PmzMGMGTOIRyc/o6uri4CAAADAsGHDIC4ujpMnTxK7OSMjA127doW3tzcZq7W1tbh58yaePn1K5oDg4GBoa2uTnAsMLXP79m0MGzYMRkZGsLW1xdy5cxnvaw4uXLgAKSkpWFhY4MCBAyS8z/bt26Gtrc041fwFLl26BCkpKejr62P9+vXEESQmJgZWVlZ/S8NhaDv8I8TXmzdvwtTUFMnJyZgzZw46duz4yxhdvIxAfhZgOQ2auXPnQkNDA0pKSrC1tYWLiwuTFfRvwO5Hb9++haGhIfr160eyrwJNAuyqVau4Nnf8ujlhLwpZWVkwNDSEr68vwsLCuN4rLy+Hra0tNm/eTMqmTJmC06dPM2INDwoKCqCvr0/z1jx37hw8PDwwZMgQ0mb19fUoKChAaWlpa1W1zVBdXY2dO3fSkuvU19fj4sWLsLe3h7KyMte4zcnJgZGREQYMGPC7q9tmef78OSQkJBAeHk6LG8fm6tWr6NOnD9TV1XH+/HkkJiZi9uzZEBUVZYQG0A3lzMxM3L9/n3ikFxcXY926ddDV1cWMGTPIe6GhocjIyADAXDPjRW1tLUxNTTFp0iRaeXl5OaZOnUoSbTHQ4exL7LlPRUWFJHfjnCudnZ3h5eUFgH/tGV5wjuf6+npahvmkpCRYW1tj4sSJpLy2thZDhw7F5cuX4e7uDldXV1RXV/P1uGb/7RkZGVi4cCECAwNJ2KTLly9DUlISQ4YMQUZGBq5du4bg4GB07dqVyYgOYOHChdDW1qaVjR07FhISEjwF2FGjRqGsrIz2/pUrVzB58mRISEjQQjww/BpG9Gqi+fxVVFSE3NxcjBo1Cvb29pCXl0dMTAx27twJFxcXnDx5EgCzlnDCaw24fPkytm3bBllZWTg6OiIoKAjZ2dkQExPDqlWrWqGWDP8p/wjx9cmTJxg9ejQUFBQgLi5Okhj9asDysxHTElu2bIGMjAyuXbsGgHVq3LlzZ+bazp/Q0uKal5fHU4BlhyDYv3//76pim4U9DrOysiAhIYHQ0FAUFRWR5ydPniQLMAC4ublBU1MTly5dwvTp06GoqMiVWZmBxcePH9GzZ08cP36cVn727FnIysqS64wMLJrH/l6yZAmJB1lfX4+MjAyYmZlBX1+fS4B99+4dY2T/pLKyEsOGDePyzKytrcW7d+/IYd7Tp08xfPhwiImJQU9PD05OTnj8+HFrVLnNMnfuXEhISKBnz56QkZHBpUuXALBEsPXr10NLSwt9+/aFm5sbFBQUmE3Kn7BgwQL06dOHS5CJioqCoaEhTUhkoNvJ/v7+RMDx8PCAhYUFmfPY4s3EiRMxevTo31/RNgznurB+/XoMGTIEpqamWLlyJWpra9HQ0IBt27bB3NwcysrKGD9+PAwNDaGvr4+GhgZMnz4dTk5OrfgXtB2SkpIgISEBLy8vTJ8+HRRFYdasWfj27Rvu3r1LHEd69eoFIyMjRiT8yfLly0lC5KioKOK17uXlxSXAXrt2DZKSknBzc0NFRQX5HQ8fPsSsWbMYb8S/SUse7/wG5zxYU1ND61sA8OrVK6xYsQJmZmZwdHQERVGwtrbma8e45nC2YVlZGdee5fXr19i/fz8MDQ1hbm4OCQkJGBkZMV7q/0D+EeIrwFpcBAUFYWhoSLsyymyI/5zGxkbU19dj9OjRWLNmDQDg1KlTEBERIYkAKisrSTZMhiY4F9NDhw5h6dKlSEpKIoIgO4ZccwH28OHDzKLyk69fv8Le3h7Tp0+ntefKlStBURT69u2LlJQUAKyYkJaWllBUVGSuyfOAM6nW69evoaqqij179gAALfaPjY0NLckRvzNt2jSoq6vTvIHDw8NBURR27txJyq5evQpLS0sYGBhwGT4As94ArH5ma2tLyz595swZzJo1C127dkXPnj3h6upKnuXm5qK8vJyWeZ5f4Zz/bt++DRUVFVy7dg1XrlxBQEAAOnbsSA5TSktLcfToUYwcORLjx49nkmv9pK6ujrRjSUkJ7aDk0qVL0NLSQnBwME2AnTZtGgYPHkzzSGRoIjc3Fx4eHiTO49WrV2FoaIjhw4fT3rO3t6d5YzM0MW/ePHTv3h0LFixAdHQ02rVrh+nTp6OoqAiNjY24d+8eQkJC4OPjg5kzZxIxbMyYMRg7dixqamr4WrzJzc2FiooKduzYAYDlsd65c2eEhoaSdyorK5GVlYXnz5/jy5cvrVXVNkVjYyOOHz8OOzs7mJiYQEhIiBamb9iwYVwC7IULF+Di4sJlzzChvRj+P3D2ozVr1sDLywuamprYsWMH10FoTk4OLl26BFdXV/To0YPYO/w89wHcbejo6AgzMzP4+fnxtPkOHDiAWbNmgaIosn9m+OfQZsXX5pmUL1++jNTUVIwdOxY2NjaMV+H/Aw8PD5w4cQJpaWkQEREhRk5dXR327NmDxMRERlzggHMxCAsLg5SUFPT09KCmpgYvLy88efIEAEuANTIyol2jYMMIsEB2djZUVVVx6dIl0r927NiBDh06YNu2bXB2doabmxtSU1MBsMZ8Tk4OiWXDQBddOQkMDETXrl1pHiANDQ1wcnLC8uXLf2cV2zSvXr2Cmpoa7O3tiQBbWVmJZcuWgaIoMheyBVgbGxvIyclxXc1jAL5//w5NTU34+/vj+fPnWL58OTQ0NODl5YVNmzYhNjaWljSK38VCXqxfvx5r1qzB4sWLSVl1dTVmzJiBjh07tui1zs/rycGDB2n2SXJyMnR0dKCurg5jY2MkJCQAAI4dOwZtbW1YW1tj2LBh8Pb2hqioKON13QJxcXGwtLSkecJVV1fjwIED0NPTg5KSEoYMGQIzMzNoaWnxdR9siePHj0NVVRW3bt0CwEoy0759e7Rv3x7e3t48Q7P8+PEDc+bMgaSkJONtCNYNRxsbGwAsm1pBQYHEMAVYt6cYWsba2hqdOnXC8OHDuUJMDRs2DN26dcOpU6e4vP+ZPR/D/5fmfWfevHmQlpbG6tWrsXjxYuLpf//+fa5va2pq4OTkhDFjxvyu6rZZOPd17EO8devW4fjx4+jatSuGDBlCHL6at/ns2bNhZ2fHODf8w2iT4itnXK7c3Fx8/fqVeH3cvXsXPj4+sLGxIfGAACA6OhqFhYW/va5tkZYWU29vbygrK0NMTIx4vALA58+f4eTkRIu1ydDEkydPMGLECNy7dw8AaxPo7OwMZ2dnIsDm5eVBXl6eluyDgcX+/fvRvn172gLz/v17Er/w6dOn6NevH0xNTUl7MjTBbjd2KIZp06Zh6dKl5LmXlxdERESwefNmxMXFITQ0FGJiYnjx4kVrVblNkpeXB1VVVdjY2NAE2CVLlnAJsOfOnUNAQAAjHLbAxYsXISgoCCUlJYiKiiI6OpqEA6qtrYWLiwvGjh3bupVso5SXl8Pd3R0URWH8+PEAmsZ4dXU1Zs6ciS5duuDw4cO07/jZM+TDhw8QERGBvb09ANaa0aVLFyxcuBCHDh2Ct7c31NTUsGTJEgCs2IZr1qyBq6srpk+fzgg3LVBdXY2lS5dCQ0MDampqtGe1tbXIzc1FeHg4Zs2ahYULFxLhld8FWM6xWFdXh5SUFJLQLTU1FeLi4jh06BCuXLkCQUFBBAUFIScnh3yTn5+P8PBw5uo8BxkZGVBSUsLly5ehrKxMW38zMzPRv39/JuklD2pqalBcXAwLCwvMnj0b1tbWmDJlCldeFG9vb1AUhevXr7dSTRn+jbDHaGJiIlRVVXHnzh0ArDFLURRUVVUxatQo2uEn28P6yJEj0NHRoYWi4yeaj9H09HRoa2uT0JDp6ekQFhaGuLg4rKysaEmq2WtQQkICLCwsGEeRfxhtSnyNjIykbXYjIyOhpKQELS0teHh4kGvx9+7dg6+vL8zMzBAREYEBAwagR48ezAkeuBN5ZGdnkxOToqIiGBoaQk1NDd++fUNpaSkKCwvh5uYGKysrRmjgQUJCAuzt7eHu7k67spiYmAhnZ2e4uLgQwfDDhw9MG/Lg2rVr6NSpE5KSkgDQNy7s/hoTEwMzMzMmdk0LHD9+HEJCQvDx8UH//v0hLy8PMzMzfP78GQDr9FNfXx8aGhqwsbFhNnQt8ObNG/Tu3RvW1tY0AXbp0qVo164doqOjAXAnUGHg5t27d7h37x6Ki4tp5Q0NDRg+fDgiIyNJZm9+htffX1BQgHHjxkFERIRsVjgF2LFjx8LR0fG31rOtc+vWLaioqMDZ2RmpqamIjIykPY+MjISqqirNa7ihoYGxC/+E0tJSbN68GVJSUhg3bhwpb2nc8vt8yNkubJuwsLAQ+fn5+PLlCywtLUkSlE+fPqFnz56gKAoLFy6k/Z7nz5+T9ZufaGho4Nm3vnz5ggEDBkBYWBgjRoygPZs3bx7s7e0ZB5uf/GpOW7VqFSwsLDB16lQucWf+/Pl8f3DC8J/j7+9PCy1VV1eHCxcukLCGJ0+ehLi4OOLj43HkyBF07NgRfn5+uHnzJu33jBkzBvr6+nwpHAYHB2PYsGG0sAxpaWnYsGEDAFYoL0lJSezcuRPPnz8nHrBv3ryh/Z7IyEhISUkxYVj+YbQZ8fXhw4eQlpaGg4MDgKakMceOHcPatWthaWkJFRUVcp3i0aNHCA4OhqWlJQYNGkQ8YxlDm0VYWBhkZWUhJSUFNzc3InzduHEDioqKUFZWhrq6OqysrGBiYsLEk2uBFStWQFtbGz169OA6nUtMTISrqyuMjY1pJ/JMG9J5//49ZGRkMGjQILx9+5bnO8HBwRg+fDjfX53gNX99/vwZ2traxLCpr69HTk4ODAwMYG5uTt77+PEjOVRhaHktePPmDVRVVbkE2OXLl4OiKK4EZgx/nZqaGkRGRkJeXh4vX75s7eq0Opx98P3793j27BnZaPz48QODBw+GuLg4iW3NFiXYiXoY6GRmZkJFRQUURcHX1xcAfb0dMmQIrK2tW6t6/zjY/e3Hjx/YsGED9PT0MHXqVPKciQFJh3NMsuMxc8Ycfv36NbS1tUns3MLCQoSEhCAzM5OIXvx6GFVcXEz72zMyMrB+/XqsW7cO5eXlAID4+Hioq6vD29sbt27dwo0bNxAcHAwxMTHmVtRPONtw7969mDVrFvbs2UMTcVavXg0LCwtMmzaNS4AFGM91hv8/NTU1iI2NRc+ePckaDLDGd1FREUpKSmBra4vVq1cDYK3PampqkJGRITf22H144MCBJFQLv7F582aYmJggICCA3MxpaGhAfn4+Kioq4ODggEWLFgFgOc7p6emBoihMmjSJ/I5v374hIiKCyY3yD6TNiK+1tbU4c+YM9PT04ODggF27dmH37t3k+cOHD2FqagoVFRXiAVtWVoaKigoykPl5QeFckO/cuQNdXV1kZmYiISEB48aNg5aWFo4ePQqANXnu2LED27ZtQ1JSEtm88HP7ASzP1RcvXuDOnTu0GFx79+6FlpYWRo0axWXI7N+/H7NmzWI2yn9CYmIiOf3kNBK/f/+O0NBQSEhI8P3VUHYfun//PhYvXkzGdF5eHhQVFblOjZ89ewZ5eXmS2Zbpg01wzocnT57E1q1bkZmZScR9XgJsRUUF9u7dy/fz4P+X/fv3Y8aMGZCVlWWMQdD7YGRkJCwsLCAiIoJBgwZh7ty5AFgbFnZGara3Oq+bAQxN3Lp1CyYmJtDW1iZxwdk2zNatW2FiYsIk1mpGc8GPV4bu0tJSbNiwAfr6+ggMDPyt9fsnwDkWr1+/jmHDhkFaWhozZ84kB545OTno0qULQkNDkZaWBjc3NxIqA+BfG3vz5s3Q09MjNl5qairat28Pe3t7dOjQASYmJkSE2bNnD1xcXCAoKAh9fX2Ym5vj0aNHrVn9NkPzNUVMTAxOTk6QkpLCsGHDkJ6eTp6vWbMG1tbWGDVqFN9e62b431BZWYnDhw+jR48eGDVqFO0Z+3YZOwlUQUEBJkyYgAMHDnDl8uFHOMfwnj17YGxsDH9/fzx9+pSU5+fnQ01NDefPnwfAWpvHjx+PZ8+ecTl3MQek/0zahPjKHoh1dXVIT0+HiYkJ2rVrR2IoAawO+/DhQ5ibm0NNTY3Lu4ufB3Pzv/369euYMmUK+fnx48fw9/eHpqYmDhw4wPN38Lu35oEDB2BqagpFRUW0a9cOnTt3RkBAAEmUEB0dDRsbG/j5+aGgoIDn7+DnPvhn1NfXIzo6GoKCgtDU1MSECRMwefJkeHh4QE5Oju/FGnbfefz4Mdq1a4fg4GDyrKqqCoqKiiSeIWe5hYUF5s+f/1vr+k8iLCwMXbt2haamJoSEhBAeHk5i77GNRDs7O65DFX7dJP9/efHiBRwdHTF06FAmeUwzli1bBikpKZw/fx4FBQUYNmwYzdv18+fPGD58OCiKosWFZOBNXV0dMjMz0bNnTzg4OKC4uJjYLxMnToSVlRVJHMVA3+xx2i4tCbAbN26ErKwsuWnBQGf27NmwsLDA6NGjYWJiAllZWUyZMoVc+zx48CA6d+4MTU1NWFtbk1tl/OrxCrBu5cjIyMDe3h6PHj3CyJEjsWfPHjQ2NqKsrAwmJiYwNDQk8Ujr6urw8OFDfPr0ieZZzM9w9p/79+9j5MiR5ED+4sWLcHJywoABA5CWlkbe++OPP+Dv78/sTRj+61RUVCAhIYFLgH38+DH09PQQEhKCpKQkuLu7w8XFhfRfftcaALpWsHv3biLAsh2T2Hu+wYMHIykpCf369YOVlRX5jmnDfz6tLr42N0iqq6uRmpoKfX19GBkZcS0ajx49gpKSEldMIAbWFfmBAwdi4MCB8PHxoT178uQJAgICoKOjgz179rRSDdsmcXFxEBISwo4dO3D//n3cuHEDCxcuhLCwMPr06YPXr18DALZs2QJbW1uMGzeOxNFl+HtkZmbC09MTBgYGsLW1RXh4OEnUw6+w57hHjx6hc+fOiIiI4HonODgYdnZ2xHudjbu7O4klx8+bO17cvn0bffv2JRuUHTt2QF1dHTNmzCDJyN68eQMRERFMnjy5Nav6r6CwsJAJecFBY2MjSkpK4OLigmPHjgEAzp07B2FhYXKrhy3MFBYWMvH4/gR227ATsmZmZkJZWRlqamoYPHgwZs6cia5duzJechxw2s8HDx7EoEGDcPv2bVLGS4AtKSnBkSNHmA0eD06fPg0pKSkSpxlgCVympqaYOnUqEQrfvn2LvLw8mmMJv9FcbPn06RPk5OTg6OgINzc3WgKe8vJymJmZwdDQEFeuXOHL9vqrxMfHo3///nBycqKF6bp06RKcnJzg4eFB84Bl/39gBFiG/wRe/ae8vByHDx+GvLw8Ro4cScrXrl0LHR0d9O7dG/b29swB1E9aGoMxMTEwMjKCv78/mRevX7+OXr16QU9PD3369GFCa/7LaFXxlbMTLV++nGT3rampwZkzZ6CpqQl7e3suI/DVq1eMYQh6+61YsQLdunXDxIkTYWdnB4qisG/fPtr7T548wfDhw7mEWX4mKysL2traXB7B9fX1OH36NERFRWlC/7Zt26ChocHlhcjw12HGLjevXr2CkJAQSSLDNlLi4+Px6NEj5ObmYvDgwbC2tsa8efOQmpqK6dOnQ0xMjPGW40F0dDTGjx+PsWPH0gy+mJgYLgH206dPTJ9k+J9QVlYGQ0NDPHv2DCdOnICIiAh27NgBgHXQvHv3bpoYBvCnUPNnsNvk7du3UFNTI22WmZkJKysrUBSFa9euMYeiHDS/Ju/n5wdJSUmMGDEC9+/fJ894CbBsmHmRzoEDB6CoqEhLlFVTU4NZs2ZBWFgYQUFBJBQGP4te7L+5qKgId+/eJSEFPn/+DDU1NVAUhdOnTwNoaqeKigpYWVlBRUUFGRkZrVPxNsiFCxdo+409e/ZAXV0dMjIyXKGoLl26hP79+8PS0pIWS5PfRS+G/wzOOSwjIwOJiYnIyMggcx07BMHw4cPJe69evUJ+fj5fH0BxwtmGqampSEhIoN3u3rt3LxFg2bfHKisrkZ+fz4TW/BfSauIrZ0d88eIF3N3dQVEUuTJRU1OD9PR06OrqwsHBgacBwxiGLJ4+fYoNGzbgwoULAFjeXLNnz4aoqCiXqJibm8uXxmBLnDlzBmpqasS7tTm7du0CRVEkfg0AWpxchr/PrzZ7/EhDQwPmzZsHaWlpkukSAJYsWQIpKSliRL948QLz58+HqqoqtLS0YGFhQeJE8jO8+lNISAgoioKuri5XmJBdu3ZBW1sbY8aMoYk1zJhm+G/z7ds3GBgYYNiwYZCUlMT27dvJs1evXtGSYTLwhj2m3759C3l5eUyePJkWO+7atWswNDTEu3fvWrOabZbZs2dDVVUVc+bMwejRoyEqKgpvb+8WPWAZWPBqk1OnTqF37964e/cugKZ9TGFhIRQUFGBiYoLg4GC+DnvBbpNnz57BxsYGrq6u8PT0JB7rxcXF6NmzJ6ysrGjx/wGWJ13fvn2Rl5f32+vdFqmurkZAQAD09PSwatUqUp6cnAx9fX2MGjUK9+7do32Tnp6OmTNnMvs8hv86c+fOhZKSEkxNTaGhoQEXFxfcuHEDdXV1SEhIQM+ePWkesGyYvthEaGgoevXqBTs7O2hpaaF3795kLY6NjYWxsTEmT57MFYqPacN/F60ediA8PBwWFhYYMmQIpKWlISgoSLJNswVYfX19aGtrMwYigMDAQBJbCgCuXr0KiqIgISGBs2fPkvJ3795hzpw56Nq1Kw4ePMj1e5iBzGL16tXo3r07+bl5u7x58wZSUlK0TTMbRqxh+G/x4cMHzJw5ExYWFtixYwdWrVoFaWlpchjFOffV1dWhqKiIduWMn/n8+TPevXuHx48fk+RZACvhhLS0NBYtWoRPnz7RvtmwYQNGjhzJzIMM/3OSk5MhJCSEoUOHAmCN5e/fv8Pd3R19+vRh1hEO2PPc06dPkZKSgmfPnhHRxsvLC1OnTuVpB7LfYaBz/fp1yMjI4MaNG6Ts6NGj0NPTw7Bhw2gesAxNcPaxXbt2kWvcFRUVUFdXh5OTE22tefHiBYYPH47Zs2dDR0eHb5OHststKysL4uLiiIiI4On9xhar7ezsuARYBjqctuGyZctI+aFDh2Bqago/P78WxzFj3zD8t9i5cyfk5ORIXOaFCxeiS5cuZG6sqqrCkSNHICgoiD/++KM1q9pm2b17N2RkZIjTTHJyMs3pkP1Ojx49sHLlylaqJcPvoFXF1wMHDkBYWBi3bt1CeXk5srOzERAQgPbt2yM5ORkAS4BNTk7G6NGj+X6T8v79e7i5uZHYHwDrWuPKlSvRqVMnrF27lvb+u3fvEBoaCoqiaMIsQxOXLl2CoKAgLURD882diooKVq9e/burxsBnfPr0CUFBQdDQ0ICgoCAuXrwIgC7yM8Y0nUOHDsHOzg7du3cHRVFQUVHB1KlTyfOFCxdCUVERy5Yt4xJg+flaKMN/jz87FK6ursbGjRtBURTc3d3h6uoKBwcH6OnpkbWc320bTpKSkiAqKgpVVVV07NgRCxYswJcvX/Dt2zfmAP5vkpmZCTk5OS7vuISEBLRr147LA5aBvh7cv38fffr0gbq6OrkKn5eXBzk5Odjb22P37t04f/48XFxcMGbMGNTW1qJLly60Gyz8xtevX2Fra4vp06fTyptfnf38+TMUFBTQp08fWvxXBm7YtiEvAdbMzAzjxo2jhRlgYPhvwR63kydPxty5cwEAx48fR9euXREdHQ2AdShVUlKCmpoaXLhwgbFnWmD+/PkkQfLhw4chJiZGwlB9//6dvHfy5EmmDf/l/DbxddGiRaisrKSVLV26FP369aOVFRYWwsfHBx06dCAnKjU1NUymvGbEx8eTk/eysjJERUWBoiiuZFpv3rzBli1bmFghP2m+ecvNzYWuri7s7e2RmZnJ9X5+fj6MjY1pJ1MMDP8rPn/+jBkzZkBfX592mMLMe9zs2bMHQkJC2LZtGy5evIiMjAyMGzcOnTp1Qv/+/cl7CxYsQM+ePbFixQp8+PCB9jsYMYfhP4HzemxiYiLNG645GRkZmDFjBmbMmIFNmzaRNZlZm+mhBRwdHREdHY2SkhJs2rQJvXv3xvTp02mxrZlxyw27TTjb5tatW5CSksKJEycAgHZwr62tDR0dHQQEBHCFZmFgJdIaPHgwrKysICQkBB0dHZw/fx4AyxuxX79+0NLSgpKSEuzt7VFRUYH6+nqYmJiQ23v8yLNnz6CqqoorV67wPNhsbGwkffTTp0/o1KkT3N3dUVNT87ur+o+iJQE2ISEBSkpKWLx4cSvWjuHfAq8x29DQAC8vLxw+fBjXrl2DiIgIEV7r6+uxa9cuHDp0iPYNs2dpgt2mbm5umDNnDq5duwZRUVFyo7axsRFRUVFYs2YN7TumDf+9/Bbx9dGjR7CysuLaZGzZsgWSkpIoLi4G0GQ0sl2xBQUFiQDL78Y254RYUlICMTEx2NjYoLCwEADr5GnhwoWgKApxcXE8fwc/b/KWLl3a4rPExERQFAUnJyeSBKCurg7fv3+Hh4cHrK2tmUmQ4bfBaWRzXj1hPDSbePjwIVRVVXHkyBFa+ZcvX7Bt2zZ07twZo0aNIuWLFy9Ghw4dEB8f/7uryvAv5ebNmzA1NUVycjLmzJmDjh074v379zzf5SWMAYxxzcm1a9ewYMEC+Pj40EKqxMTEQENDAzNmzMDLly9bsYZtF8614fv37ygtLSU/T5kyBeLi4rQYcsXFxRgzZgzWrFkDMTExIs4ysNixYweEhYVx9epVFBUV4fjx4/Dw8ICenh7JrVBdXY2PHz/izZs35Lv58+ejR48etDJ+4+DBgxAUFPzlzZKKigqSLKqwsJAZ138RTttw+fLlpPzcuXPMWsLwX6GsrAxfvnzB48ePaSEOQ0ND0bFjRwgJCdGE1m/fvqFfv36/3GPzG9+/f0deXh6uX79OS8548OBB6OrqomPHjoiJiSHlZWVl8PDwwLx581qjugytwP9cfGULfuwFOCUlhbhXP3nyBBYWFpg5cybNI+nu3bsICAjA9OnToaSkxNeGDMDyBmFz/PhxfP/+Ha9evYKamhrs7e3J4K6srERUVBQEBQWxZcuW1qpum8PV1RW9evWinaw3NDTQNsIJCQmQk5ODuLg4nJ2d0b9/f9jb28PIyIi5Gsrw22Eb2TY2Nkz8JB6cPHkShoaG+PTpExmX7PH87ds3zJ8/H2JiYiR0A8DylGXGMMN/iydPnmD06NFQUFCAuLg4Xr16BeDX6wS/HyI3h9MLbv78+aAoCoqKisjNzaW9FxMTAx0dHUyYMIHrGb/D2adWrlwJe3t76Ovrw8nJCc+ePcOXL18wfPhwCAsLY8mSJdi0aRP69esHe3t7AICxsTGmTJnSWtVvk0yYMAG+vqoQHzcAAEuQSURBVL60ssuXL8Pa2hra2tokBAGbrKwsDB8+HLKyslyJUviNGzduQEhICImJiS2+s2XLFjg7O/N1YrL/L58+fcL06dNhbW2N8PBw2jPGvmH4Tzh9+jR8fHwgKyuLdu3aQUdHByEhIQBYtyY8PDwgKSmJ/Px8lJSU4P3793B1dYWZmRlfO3dxcuLECQwfPhzS0tIQExODqKgoFixYgLy8PHz69An9+/eHnp4eEhIS0NDQgOzsbLi7u8PU1JRpQz6incD/EF9fX4Hk5GSBuro6gXbt2gm8e/dOYOjQoQKTJ08WqK6uFtDT0xPw9PQUuH37tkBERITAvXv3BLKzswWioqIEamtrBby9vQWqq6sFcnJy/pfVbNPcvHlTYMSIEQJpaWkCwcHBAqNGjRL4/v27QO/evQXS09MF3r9/LzBixAiBwsJCgc6dOwuEhYUJzJgxQ+Dw4cMCAFq7+q1OZmamQFZWlsD169cFOnbsKHDlyhUBAQEBgXbt2glQFEXaaOTIkQKnTp0SmD9/vkCHDh0ElJWVBYYPHy5w584dgQ4dOgjU19cLtG/fvhX/EgZ+Qk5OTmD+/PkCampqAjdv3hT4+vVra1epTfHgwQOBT58+CcjJyQm0b99eAIAARVECAgICAuLi4gJjxowRqKioEPj48SP5Zvz48QLt27cXaGhoaK1qM/yL0NPTE9DW1hYoLCwU6NWrl8Djx48FBAQEBNq3by/Q2NjI8xt2H+VX2O1SVVUlUFNTI/D+/XuB6upqAQEBAYGlS5cKrFmzRqCiokIgPj5e4NOnT+Q7f39/gcmTJws8ffpUQEREpFXq3lZh96kFCxYIbNiwQWDcuHEC+/fvF8jKyhKYNGmSQH19vcCRI0cE5syZI5CamioQGxsr0KVLF4GzZ88KCAgICHTq1ElAQ0OjNf+ENke3bt0E3rx5I/Djxw9S5ujoKODp6Snw/PlzgRkzZghkZGSQZwoKCgJOTk4CV69eFTAyMmqNKrcZlJSUBLp27Sqwb98+gfz8fFLOuR95+/atgImJiUDnzp1bo4r/aOTk5AQiIiIEVFVVBb5+/UprV2aPwvD/JTY2VmDixIkCampqAuvWrRO4ePGigKampkB0dLSAl5eXQIcOHQSWL18uoK+vL6CtrS1gbm4uMGTIEIHS0lKBGzduCAgKCvK9bR0bGyvg7+8voKOjI7Bjxw6B9PR0gdGjRwusXr1aICwsTKCxsVFg06ZNAurq6gKhoaECsrKyAj4+PgJlZWUCN2/eZNqQn/hfqboNDQ0YOnQopKSkcOrUKeJ1eOXKFUhKStIyTW/atAlOTk6gKApqamowMDBAY2Mjvnz5AnV1dZr3Er9x//59jBw5Ej169ICEhATxrmGfkOTm5kJZWRkODg7EA7a6urrFa478RkFBATm9mzVrFrS0tEioBjZ/1kbMaTJDa/H582fatRUGFkeOHEGXLl1aTCRYV1eHHj16kGD2DAz/Ddg2C/vfy5cvIzU1FWPHjoWNjQ3279/fmtVr07DbLDs7G56entDV1YWgoCAMDQ0RHBxM3ouKimoxSd63b99+Z5X/Mbx79w4mJiYkNv25c+fQtWtXrvnvy5cvqKqqIj9HRkZCXl6e2JX8RkuhfPbt2wdlZWUcOHAA5eXlpDw5ORmenp4YPXo0hg8fzvTHFkhKSkKnTp3g5+eHZ8+ekfKKigrMmzcPSkpKtBjODH+fr1+/kv7L7/s8hv+M6OhodOzYEYcPH6b1peLiYqxYsQKdO3dGYGAgKT927BgOHjyItLQ0sj/md6/NXbt2oUOHDkhKSuIaj+vXr0eXLl3IDZNPnz4hOzsbCQkJuH37NhnH/N6G/MT/RHzV1dVFQEAAAGDYsGEQFxfHyZMniQCbkZGBrl27wtvbmwzc2tpa3Lx5E0+fPiUdMfj/2rvv8Brv/4/jz3OyREUSM7airWppiFFiFFWl1ErslsSIVS1fEiKqsXeNtKI0klaEICT42aM1Wq0Ro0bNfpWmKEqRdc79+0NzmqD9dtCEvB7X5bqce5x8zn2dc4/X/bnfn//8x6hUqdI9J+C5zejRow2z2WxUrVo1S22ujG138uRJo0KFCsazzz5rXLlyxTZfB+Q736vw8HCjePHihpOTk21U1d8LVDM/BqntJ5IznTp1ynB1dTXatWtn/Pe//7VNz/hdnzp1yvD09MzVN+7kwcocWp08edL46aefbCVpvv76a6Nz586Gt7e3ER0dbVsuPDz8npt9uVHGsfTgwYOGq6ur0b9/f2P+/PlGXFyc0apVK8PJycl49dVXbcuPHDnSKFmypDFx4sR7BsmTex06dMgoW7asYRiGsWbNmiwDoly/fv2eEPb48eNG7969c/Vj8pmD14MHDxoHDhwwjh49apv2xhtvGMWLFzfCw8ONI0eOGJcuXTJatmxpjB492vj4448NFxcXBYi/w2KxGOHh4Ya9vb3xzDPPGH5+fkbfvn2N119/3ShSpEiu/c49DBoLQP6JtWvXGiaTyTZI4N1l9n766SejX79+RvHixe87KHXmZXOruLg4w2QyGR988IFtmtVqzRKmjhw50jCZTMbBgwfv+x65fRvmNg88fB01apRRqVKlLNO6detmuLu73zeA7dSpk3Hjxo0sy2/bts0ICAgw3N3djf379z/oJj4yMi5YNm7caKxevdro2rWrUbduXWPx4sX3LHvs2DHD19dXP+BMMrbfqFGjjLx58xqVKlUygoKCbNO1rUQeXYsWLTKcnJyMLl26ZLmYu3nzpvHaa68Z9evX14WJ/GMhISFZjhUhISFGmTJljGeffdZo0aKFrYb9nj17jC5duhg1atQwgoODjddee80oWbKkvoO/unjxolG1atV76hRevHjRCAsLM/LmzWu0a9fONn3MmDFG3rx5jWnTpulY/T9cu3bNqFWrltGvXz/DxcUly2AeR44cMerUqWNs27bNNu3q1avGxo0bjVOnTmVHc7Nd5hvrISEhRuXKlY0iRYoYdevWzTJqfK9evYwqVaoY+fPnN55++mnjmWeeMQzjzvn2U089lSWslXvt3r3b8PHxMapWrWrUrVvXCAoK0uBaIjlEenq6MXPmTOOpp54y+vXrd8+1ccbrY8eOGQ4ODlkG2pLfLFq0yHBxcTFGjBhxz/4t4/zv6tWrRvHixY1Zs2ZlRxMlh7F/0GUMnJyccHFxwWKxMHbsWNzd3YmMjMTHx4du3boRFRVF06ZNqVevHmvWrKFVq1a0b9+eZcuWkTdvXgBcXV1xdnZm586dPPvssw+6iTnWL7/8kqWeWUYtr5dffhm4U+tnypQphIWFYTab8fX1BWDevHl06NCB2NhYACwWS66u/WNkqv8I4OXlxdatW/nss89YsmQJqampTJ8+3Vb/MTdvK5FHla+vLzdv3qRfv35s27aNF154ATc3N86dO8f169f5+uuvMZvN+o3L35aYmMjcuXPZvn0727ZtY8OGDcybN4+wsDC+++47li1bRtWqVdm3bx9eXl4MHTqUTz/9lC1btlCkSBFOnz6N2WzGarViNj/UEvs53vfff09aWhpdunSx/SatViuFCxema9euXL16lQkTJrBs2TJ8fHwICQnBycmJli1b6vd7l8zfJ8MwsLe3p2rVqnz66ad06NCBXr16AZCcnExgYCDu7u7Uq1fPtr6bm5vtvDI3yjg/HD16NHPnzmXx4sWULVuWCRMmMGrUKH755RcmTZrERx99xJ49e7hw4QImk4nmzZsD8MEHH/DEE09QpEiR7PwYOV7NmjVZsmRJrt/3ieREdnZ2+Pv74+joyNy5c/H392fBggX3XBsXKVKEfPnykZ6ens0tzpk6depEWloawcHB3Lx5kwEDBlC+fHngt2NNeno6N27cwNHRMTubKjnFg0xyrVarERcXZ9SrV8/w8vIy8uTJY5w+fdo238fH554esJs2bTJeeeWVe3qHZB6ZPjfo06ePMW7cOOOnn366Z17mu/QZNWBr1qxpvPfee8Zrr71mlCpVSr1rfpV5O1y5csVIS0uzPUZx8eJFY/To0YaXl5cxaNAg23LqVSPy6Nq/f7/Rr18/o2HDhka3bt2MiRMn2h73UQ0l+SdSU1ONdevWGZUrVzYaNGhgzJs3z5g/f75t/v79+43q1asb5cqVs/WAvXHjhnHz5k3bcVvfwTsWLFhg5MmTx/b67rI+p0+fNlxdXY0pU6b82017JGzatMkYM2aM7fXd53xHjx41mjZtalSrVs3w9/c3Ro4caTRo0MCoXLmy7RxI54m/2bt3r+Ht7W1s2bLFMAzDWLduneHi4mJ06NDBcHFxMYKDg+9ZZ/v27Yafn59RsGBBIzEx8d9u8iMp8+9cpbxEco6M3+Mvv/xifPDBB4anp6fRvXt32/yMc5dNmzYZL7744u8+Mp+bZd6nLViwwChRooQxaNAg4+TJk1mW+eyzz4z69evn6qe55TcP9HakyWSiTZs2WCwWDh8+TMuWLSlQoIBt/tKlS2ncuDF+fn5s2LCBlJQUGjduzPr16229QzLktrsDycnJfPzxx0RHR3PlypUs8zL34qxWrRrDhw+ndu3arFmzBpPJxKlTp+7ZfrmRYRi2O+wTJkygffv2VKtWDT8/P3bv3k3hwoXp168frVq1Yvv27QwZMgTQCKEijzJPT08++OADtmzZQmRkJEFBQbZRQ+3tH/jDHZJLWK1WHBwcaNy4MZMnT+aXX34hICCAlJQU2zIvvPAC8+bNo1ChQlSvXp2ff/6ZfPnykTdvXkwmE1arVd/BX1WoUAGA5cuXA1nPawCefPJJypUrx/nz5//1tuV0KSkpxMbGEhsby5QpUwCynPMZhkHFihWZNWsWnTt35ujRoxw+fJhq1aqxb98+HBwcSE9PVw/ETCpWrMjrr79O9erV2bp1K35+fkybNo358+dTv359JkyYwIABA7KsY29vz+XLl21PWsj/lvl3fvdvXkSyj8lkwjAMnnjiCbp160avXr1ITEzEz8/Pdu5y69Yt3n//fcqWLcvzzz+f3U3OETJnLRnbEKB79+6MHTuW2NhYwsLCOHHihG35yZMnU6RIEapUqZItbZacxWRkfGsegNTUVK5fv06LFi2oU6cOu3fvpkqVKowYMYKSJUvaluvYsSOxsbFs374db2/vB/XnH0lGpkfkBw8ezIoVKxg0aBBdu3bNElzfLSUlhbS0NJ544glMJhPp6em6yPtVSEgI4eHhjB07lu+++46jR4+yceNGVq9eTcOGDbly5Qpz5szho48+YsiQIbz11lvZ3WQR+QeMu0qNiPwTd3+fUlJS2Lx5M8OHD8fOzo49e/ZkCbIOHDhAq1atqFWrFkuWLMmOJud433//PV5eXrz44ovMnj2b0qVLA789Qn/16lVatGhB37596dq1aza3Nue5cOECkydP5ssvv6RNmzYEBQUBd7afyWSyfV/T0tKwt7fP8v3N7aVXNm/ezMGDB/nhhx8YOXIkLi4uALbz5v79+2M2m5k6dSpOTk4MHjyYxMRE8ufPT1xcXJbfenJyMnny5MmujyIi8kBlnO/cvHmTqKgo5s2bh5eXF/PmzaNdu3acPHmSffv2YW9vn6tLKAUHBzNq1CicnJzu2Q6ZzxkjIyMJCQmhU6dO9OnTh0GDBnH69GkSExNz/TaUX/3TrrN/9BjTpEmTjFq1ahl9+/Y1zp07l2XeiBEj9DjerzI/9v72228bZcuWNWbOnHnfEgQZMnd116Nkvzl37pzh6elpLF++3Dbt+++/N3r27GkULFjQOHz4sGEYd0ZwjIyMVMkBERGxyXw8HT9+vG2Ay5SUFGPdunVGxYoVjfr1699z7Dhx4oSOJ//D8uXLDUdHR+PNN9+0HYszhISEGGXLljXOnj2bTa3L+X744QdjwIABRq1atYyJEyfapmd8Z5OSkoyOHTsan3zyiWEYeszbMAxj3rx5RpEiRYzGjRsbxYoVM5555hlbGQbDuPNobe3atY2uXbsahmEYt2/fNnx8fGzb0DB0ji0ij7e7SxB4eXkZ9vb2xtNPP23bX+bm85tTp04ZLi4uhre3t60s5t3HhczH28jISKN06dKGm5ubUalSJds2VO4lhmEY/6jnq5Ep6Y+KiiIxMZEqVapQq1YtKlWqBMCUKVNYvnw5Xl5eDB8+PEsPWCBX99jMvP0y3wl5++23SUhI+FM9YCWrb7/9lipVqrBy5UpeffVV2/QTJ07w5ptv8sYbb9CvX78s6+T2XiEiIpL1OHz8+HEGDx7M2rVrWbNmDc2aNSM1NZUtW7YwdOhQChYsyJYtW+7pwaDjye+zWCzMnz/fNiCFt7c3xYoV4+zZs6xdu5ZNmzZRtWrV7G5mjpaUlMS4ceP4+uuvad26NcOGDQPghx9+wNfXl4sXL3LkyJFce16d2dy5cxkwYACxsbE0adKEH374gYYNG7JixQqqV69uO/+eOXMmkydPpm7dupw7d45bt26xd+9e7Ozs9FSFiDzS/qin5d2DN2b0gP3www85cOAACxYssJWtye3HlH379tG5c2cKFizI1q1bcXR0/MMesBERESxZsoQ1a9Zgb2+vbSg2fzt8zfwFGzlyJLNnz6ZGjRokJiby0ksv0aNHD1v4NXXqVFasWEGZMmWYOXMmhQsXfnCf4BGV+Qd769YtUlNTcXNzs80fOHAgq1atUgD7F6WlpfHqq6/ywgsv8N5775E/f37bvNq1a1O7dm2mT5+ejS0UEZGcbPjw4WzdupVixYqxc+dOrl69SmxsLG3atLEFsEFBQaSnp3P48GGFM3/R7t27mTx5MsePH8fNzQ1PT08GDBhAxYoVs7tpj4TMAWy7du3w9/fH19eXH3/8kcTERBwcHHL9TYCVK1fStm1b4uPjadmyJQC3b9/G09OTxo0bc/ToUdq1a0e7du1wdHTk008/ZcuWLRQrVoywsDBtQxF55GXOGqKioti3bx9wZ6wEPz+/e5bPyHaSk5NxcnJSWcO77Nu3j44dO1K4cOE/FcBm0DaUzP5W0YnMX6x9+/Zx8uRJ1q5dy8aNG1myZAnXrl0jLCyMtWvXAjBkyBBefvll8uXLR8GCBR9c6x9RmX+oEyZMoF27dlSqVInRo0fz5ZdfAjBr1ixatmzJzJkzWbRoEZcvX87OJj8yHBwcqF27Nlu3bmXx4sUkJycDdwJus9lMsWLFsrmFIiKSU0VHRzN79mxmzJjBwoUL+eyzz2zh1sqVK3F0dKRRo0aEhoZSrVq1XD/Q5d9Rq1YtYmNjOXToEDt27GDWrFkKXv8CDw8PRowYQc2aNVm+fDnly5cnKSnJFrymp6fn6tAwJSWF9evXU65cOU6fPm2b3qVLF27cuIGLiwt58+Zl8ODBzJo1i4IFC/LOO++QkJDA3LlztQ1F5LGQkTUEBgYSHBxMamoqDg4O9OjRg1GjRt2zfEa2kydPHttgUgoNf1OtWjViYmK4dOkSDRs2JDU19Z4BzzMPwpVB21Ay+0dlBz755BMWLVqExWIhLi7OVsR+69atjB8/njx58tC/f39bD9iM0FbFhu8ICQlh3rx5jBo1CmdnZ8aOHYunpycBAQG88sorALzzzjt89NFHfPLJJ/j4+GRzi3O2zDcFevbsyVdffUXRokXx9PTkyy+/5OrVq7aC1yIikruNHj2aoUOH4uzsbJs2btw4tm7dyqZNm2zTLl68yKBBg1i6dCkJCQm8+uqrtosYk8mkHnJ/Q+bjtR7t/nuSkpIICgri0qVLxMfH6/HQTH744QcmTZrE7t276dixIzt27ODkyZMsX76ccuXKAfDmm2+yfv16vvnmGwoVKmRbV99HEXlcbNq0iV69ehEdHU2dOnWIi4ujY8eOhIWF0bt3b9ty2u9l9Xs9Wi0WCwcOHKBDhw4UKVLkd3vAivyev/Qt2bx5M2PHjrW9tlgsnDlzhoMHD3L48GHb9IYNGxIcHExaWhqhoaG23pwZdwP05YQ1a9awdOlS4uPj6devH5UqVeK7777j4MGDzJgxg61btwIwY8YMxo8fT5s2bbK5xTlDxr2CzPcMMu44ZewUAebPn88777xD2bJlOXLkCJ6enuzfvx97e3vbMiIikjsdOHCAdevW4eDgkGW6q6sr+/fvtz1tYhgGRYoUwdfXl/T0dFq2bMm6detwdHS0raPg9a/LfJGnC76/x8PDgxkzZrB69WoFr3cpVqwYw4YNo3r16sycOZMtW7awevVqypUrx61btwCoW7cuZcqUuaf3ur6PIvKount/lpSURLly5WzBa7du3WzB6/Xr19mxYweg/V5md5drGDZsGAMGDODAgQPY2dlRrVo1lixZwsWLF2nUqJGtB+w/6M8oucifPktLSUkhNjaWL774AkdHRwIDA/Hz88Pd3Z1Ro0Yxe/ZsHB0d8fLyAu4EsCkpKaxbt46aNWva3ie3/rjvviNSqFAh+vTpw4svvsj//d//0bVrVyIiIqhQoQIvv/wyDg4O/Pzzz7Ru3Zp33nkH0EAembfhzz//DICbm1uW7WpnZ2fbTv7+/vj7+2e5INHFiYhI7paens4LL7zAjh07MJvNxMfH07BhQ/Lnz0+DBg146qmnGDt2LIGBgRQvXhyAkiVL0qtXL5ycnOjTpw/btm2jbNmy2ftBJNdzd3cH7pwf6dwmKw8PD0JCQjCbzezcuZOYmBiGDBlC3rx5SU9PZ9myZZQrV07jUIjIYyPjmjgiIoLKlSvj7OxM/vz5iYqKYsCAAUydOtXW43XXrl22pwEyznXkt20YFBRETEwM1atXx2w2U6tWLZYsWUKrVq1sAWznzp15/vnnNdCl/Gl/uguqk5MTo0aNolGjRsTFxTF+/HgA22irJ06cYObMmbZizgCvvvoqM2bMuKceRm6U8UNetmwZJ06coFq1arzxxhvcuHGD6dOnExgYyJtvvkmdOnV45pln+PLLL9m7d2+W98jNwWvmHtMTJ06kZcuW1K9fn4YNG5KYmEhaWppt2bu3U8bOULVrRERyty5durBixQrS0tIwm83897//pU2bNgQEBJCcnEzlypVp27Ytu3fvJjg4mD179nDkyBHee+89UlNT6dChA8nJyRw/fjy7P4qIjZ4ou7+iRYsyfPhwateuzdKlS5k6dSoAbdu25fz58yxcuPC+NfpERB4lmXOW6dOnExwcjLOzM0WLFmXPnj34+/sTGhpKQEAAcGcslFmzZmEYhsZDuY/58+ezaNEiVqxYQVxcHP7+/qSmptK5c2cWLlwI3KkBGxUVRdWqVXNt50L56/7S2Vrx4sUZNmwYNWrUICEhwRbAdurUicGDB3Ps2DFmz55tKzOQ5Q/pxJAjR44wdOhQ26AIhQoVIjk5mQsXLuDh4QHA1atXqVq1KnPmzCE0NDSbW5xzZOzU3n33Xd5//3169erF4sWLOX36NL169fpTA5JpxygikntZrVZu375Nv379WL9+PampqZQuXZqtW7eyYcMG/Pz8sFqtBAYG0qlTJ86fP0/NmjVp3bo133//PREREVSsWBFXV9d7yhWISM6UMUBZrVq1WLFiBUWLFuX48eO2MQDS09N1figij7SMnOXo0aNcuHCB2bNn8/zzz1O3bl1CQkIwDIOLFy+SkJDA5s2bad26NefPnyc8PFw3oMgaXt++fZsff/yR0NBQvLy8WLVqFR07diQ8PJxevXrRp08fli9fDmDrDZvx5K3I//K3BtxKSkpi3LhxfP3117z++usEBwcDsHjxYoYNG0aPHj0YOXLkA2/s46Br164cOnSIAwcOAHD27Fnat29P5cqVefHFF1mxYgXXr19n+/btGsjjLufPn6dNmzaMGjWK1157jQ0bNuDr68vkyZNtd/Lg3hIPIiKSu1WuXJk6deowd+5cfH192bRpE5988glNmzbF0dGR7du306JFC5o1a0Z0dDR2dnakpaWxZ88eXFxcqFSpEmazmSFDhrB27Vo2b95su2kqIjmfBigTkceVYRhs2rSJpk2bkj9/fiIiImjbtq1tflhYGDExMSQmJuLp6UnBggVZvnw5Dg4OyhoyOXPmDE8++ST79+/H3d0di8VCy5Yt6dOnDwMHDuSzzz6jYcOGAKxdu5amTZtmc4vlUfO3wlfIGsC2atWK4cOHA7Bx40YaNWqU63/Ed5/Qpaam4ujoyLFjx+jQoQODBg2ie/fuACxdupQpU6Zw+/ZtihYtytq1a3FwcNDIg3c5cuQIzZo147vvvmPt2rW0b9+eqVOnEhAQwI0bN/j000/p169fdjdTRERykPfee4+lS5fyzTff2KZ1796dhIQEoqKi7glgX3vtNT766CPy5ctnW/6zzz4jJiaG2NhYtmzZgqenZzZ8EhH5J65evYqrqytms1nBq4g80u7X2Sg0NJTQ0FCGDBnCiBEjcHV1tc376aefuHbtGvnz56dQoUKYTCbtBzNZunQpffr04fLly7b8ZdOmTQwfPpxly5ZRpkwZvv76axYtWkSlSpXw8/PTtpO/7G93D8x4jKdmzZqsXr3aFr42adIkV3e93rJlC/BbndHVq1djtVptIyOXKFGCcuXKsXr1ats6vr6+rF69mq1bt7Jx40bb3fjcHLxm7v6fnJwMQJkyZShRogQBAQF06NCB6dOn23q8XrhwgejoaNv2FxERgTs1611cXLBYLISGhjJr1iwiIyNp1KgR3bp1s5UgqFevHmvWrGH9+vW0b9/eNio6gKurK87OzuzcuVPBq8gjyt3d3TYOhS6aReRRlhG8xsbGsnLlSgBGjRpFUFAQ06dPJzY2Nst5TMGCBSlfvjyFCxfGZDJpP3iXJk2aULBgQVttcLgzwPfevXs5d+4cZ8+eZcyYMVy6dIlevXrZytaI/BV/u+drhqSkJAIDA8mTJw9z587N1YHhyJEjbXXhTCYTiYmJNG3alHz58jFgwACaNm1KpUqVOHDgAPXr12fOnDl07tz5nvfJ7Y/NZ/784eHh2NnZ0axZMwoXLsyQIUP45JNPaNeuHREREcCdcNbHxwer1crq1atz9bYTEZHfGIbBypUref/997l16xbffPMNR44c4cknnwTu3PzcvHlzlh6wmzdvZvLkyaxduzbL8STjCRYRERGR7Hbp0iW8vb0pV64cb7/9Ns2aNQNg6NChzJw5kw8//JDOnTuTN2/ebG5pznJ31mKxWEhPT2fQoEFcuHCBpUuX2mr7d+nShZiYGJ588kny5cvHnj17VPdf/rZ/HL4CXLlyBTc3N8xmc65+VP7IkSM8/fTT2Nvbc+LECZ566ilu377NiBEjOHToEPv27WPo0KHUr1+f5cuXc/PmTaZPn64d4u8IDAwkMjKSKVOm8Morr1CsWDFOnjzJO++8w/fff8/zzz9P6dKl2blzJ1evXmXv3r04ODjk+vBaRESy8vb2Zu/evbz++uvMmzcvy6N4vr6+bN26lcjISJo0aYKTk5Ntno4nIiIikhPcL2c5dOgQAQEBuLu7079/f5o3bw7cuY6ePXs2EydOpE+fPlnObXKrW7duZcldzp07R6lSpWyvDx48SPXq1Zk7dy5+fn626Rs3bgSwldZUuQb5ux5I+JohN1+kZC5WvXz5ckaNGsWIESPo1KkTAKdPn2bdunWEhYXh4eFBYmIiqamp7Nu3j6effjo7m54jhYeHM3r0aNauXcsLL7wAQEpKCk5OTly5coVFixaxZMkSSpQoQalSpZgwYYKt+792hiIiAnd6q16/fp0WLVpQp04ddu/eTZUqVRgxYgQlS5a0LdexY0diY2PZvn073t7e2dhiERERkd/3448/UrRoUdvrQ4cO0bNnTwoVKsTAgQNtA0H17t2b48ePs23btlzbOS6Dt7c3AQEBvPnmmwB8/PHHzJkzh9q1azNmzBicnJxwdnYmMDCQAwcOEBERQYkSJe55Hw1QJv/EAw1fBfbv309aWhqTJk3i6tWr9O7dm44dO9rmHz9+nAMHDjB+/Hhu3brF0aNH9QO+j8GDB3P16lUWLFjAqVOn2LFjB7NmzaJAgQL4+fndt1yDdoYiIvJHN4InT55MXFwc1apVIzg4OEsAGxISwnvvvacbeCIiIpJjZD6v+fDDD1mzZg1jxoyhWrVqtmUOHjxIu3btKF68OMHBwbYANqO3bG5+OhkgMjKSTp062XoAHz9+nNWrV/Pxxx8D0KxZM/r378/333+Pv78/Cxcu5MUXX8zVnQvlwVP4+g9l/kEOGTKE8PBwkpKSOHr0KFOmTCEpKYm33noLX1/f311XoeFvMgbaeuutt9i/fz8NGjRg+/btFClShCJFimC1WtmzZw9r1qzBw8MjVx9EREQkq8wXF1FRUSQmJlKlShVq1apFpUqVAJgyZQrLly/Hy8uL4cOHZwlgAT1BISIiIjnOlStXOHHiBD4+PjRs2JB33nknSwC7dOlS/P39qVq1KhMmTMDb25uMqCe3XjPfHTqPHj0ai8XCu+++a8tfxo4dy65du9i+fTuhoaGMHz+eihUrsnXrVtV3lQdKMf4/lBG8fv/995jNZhISEsiXLx81atQgKCiIYsWKMXv2bJYuXWpbJy0tzbau1WrN1cFrRtiawWw2YzabGTRoEKVKlWLLli20a9eO9957j/DwcBo1aoSLiwv58uXLtQcRERG5V+YT7JEjR/L2229z+PBhAgMDGTVqFOvWrQPuDETh4+NDYmIigYGBXLp0Kcv7KHgVERGR7LZs2TLWrFkDwH/+8x/69OlDrVq1iI6OZseOHUybNo19+/bZlrdarTRp0oRKlSpRu3Zt4E7ompuvmTP3M7x16xbu7u6MGTOGmTNncvXqVeDOk0/Lly/n/fffZ/369dy6dQvDMHQ+KA+cvlF/U+Yer/Hx8bRr144KFSrg7+9vuwD08vIiMDCQKVOm8OGHH3Lr1i26deuW5Q5Kbu7GnnkbLl68mOPHj2M2m2nZsiWenp4sWLCA9PR08ufPD9yp3bdw4UIKFSpEvnz5srPpIiKSg2QOXvft28fJkydZu3YttWvXZsuWLUyYMIGwsDAMw6BZs2YMGTKEGzdu8MMPP1CwYMFsbr2IiIjIb1JSUti8eTNz586lTZs2rF+/nh07dgBQv359FixYgJ+fH9OmTcPHx4d69eoRExNDkyZN6N+/P5C7x+OBO+eGmZ9Q/uabb1i7di1paWkMGTIEq9VKz549cXNzw9nZmZ49e9K8eXPOnDnDiy++iMlkyvXbUB4slR34GzJf5C1atAjDMEhISCAhIYEdO3bg5eVFamoqjo6OwJ0LwaCgIJ5++mk++OCD7Gx6jhQUFMTixYt55plncHZ25rPPPiMhIYH69esD8PPPP5OQkMDixYs5d+4ce/fuxcHBQTtDERHJ4pNPPmHRokVYLBbi4uJwcXEBYOvWrYwfP548efLQv39/Xn31VeC347mOJyIiIpITZD4nqVy5MkeOHGHWrFn079+ftLQ07OzsMJvN7Nixg+DgYE6ePImDgwMFChTgq6++wsHBIdfXeM38+Xfu3MnQoUOZOnUqderUAWDq1KkEBgYyefJkAgICbOeLmak0pDxo6vn6F2XeGU6aNIn58+cTGxvLM888w8WLF2nRogW7du3iySefJC0tDQcHB6pVq0ZYWBhPPfVUNrc+58jYjuHh4SxatIi4uDhq1KhBdHQ0q1atomnTpqxcuZKmTZuSkpLC1q1bKVy4MPHx8djb26smn4iIsHnzZr744gtCQkKAOyfKZ86c4dq1axw+fNj22F3Dhg2BO8ft0NBQ3NzcbL0aMveMEBEREckumc9JoqOjcXJywtfXl0GDBlGmTBlatGiBxWIhPT2dunXr8umnn/Lf//6Xixcv0rp1a+zs7HL9dXLm4HXp0qXEx8fz9NNPU6dOHVJSUnBycmLIkCHAnU5gZrOZHj164OrqmuV9FLzKg5Z7f5V/U8bO8OjRoxw5coT333+fqlWrAjBt2jSGDRvGyy+/zKZNm7IEsM888wyg7v979uyhevXqmM1mrl+/zsmTJxk9ejQ1atRg9erV9O3bl6lTp5KYmEjbtm1ZvXo1DRs2ZMaMGbi4uGAymbBYLLn6gCIiInceyYuNjeWLL77A0dGRwMBA/Pz8cHd3Z9SoUcyePRtHR0e8vLyAOwFsSkoK69ato2bNmrb3yc09Q0RERCRnyJwThIaG2joolS9fnkKFCtG2bVvi4uJo0aKFbZ309HTq1atne53br5MzB6+nTp0iNjaWjRs3Uq5cOQCcnJxs+cyQIUMwmUwMGTKEYsWK0alTp+xsuuQCKjvwN0RHRzNixAgcHByIiYmhevXqtnl79uwhJCSEU6dO8X//93/q7ZpJeHg4o0ePZsuWLVSsWBGAAwcO4OLiQnp6Oi1atGDgwIEMGDCAlStX0rZtWwC2b9+Ot7c3cO+IhSIikntduHCByZMn8+WXX/L6668THBwMQExMDNOnT+fZZ5+9ZzTgDLn9ZqiIiIjkPGfPnmXUqFF07NiRZs2aAXDt2jVGjhzJvHnzWLRoEU2aNKF79+4ULlyY8PDwbG5xzpA5J+jXrx+XL19m2rRpTJs2jeXLlxMQEMDgwYPJmzevLYCFO2Uk27dvn6tDa/l36Krjf7hfNt2mTRsqV67M6dOn2bZtG6mpqbZ51atXZ9y4cbi6utouAgU++ugj+vfvzwcffGALXgFeeOEFypUrx5EjRyhSpAhdunQBwN3dnd69exMWFkatWrVsyyt4FRGRDMWLF2fYsGHUqFGDhIQExo8fD0CnTp0YPHgwx44dY/bs2Xz55Zf3rKvgVURERHKSBQsWULFiRXbv3k3RokVt093c3BgzZgz9+/fHx8eHunXr8s033zB79uxsbG3OkpETXLp0iSNHjtC3b19KlSrFlClTaN68OatWrWLOnDncvn0bBwcH0tLSAOjcubOtrKHIw6Qrj//h+vXrWV6npqaSN29eli5dStOmTfn0009ZvXp1lh+rl5cX0dHRLFmy5N9ubo40d+5c+vfvz9KlS2nTpo1t+hdffGH7/y+//MKuXbu4cOECP/30E9OmTcNqtdKvXz/tDEVE5Hd5eHgwYsSI3w1gt27dysaNG7O5lSIiIiJ/zM/Pj/r16/Ptt99y8ODBLNfAbm5uTJs2jU2bNjF8+HC++eYbHBwcdJ2cyaRJk/Dx8aFAgQJUq1YNwzBwcHBg1qxZvPDCCyxdupTw8HBu3bpl6/maQT1f5WFT2YE/8OmnnzJo0CCGDRtG6dKlad++fZb5t2/fpmXLlvz8888EBwfTsmXLe360uf2xxozyAfHx8bRs2dI2vVWrVri5uTFnzhzy5s3LtWvX6NatG6tWraJChQo4OTmxb98+jdYoIiJ/SlJSEuPGjePrr7+mVatWDB8+HICNGzfSqFEjDZwgIiIiOcYf5QT169fn7NmzREdH4+3tjdlsvu81scVi0fnNrwzDYOHChfznP/8hX758JCYmkj9/fluJgZSUFN5++202bNjA+PHj6dixY3Y3WXKZ3JsK/gnbtm2z9XwdPnw4nTp1YvHixaSkpADg7OxMQkICrq6uTJw4kdjYWCwWS5b3yM3Ba0pKCuvXr6dcuXKcOXPGNt3Hx4cTJ04QGhpK3rx5gTt38j755BOWLl3KuHHjSExMtN3JU/AqIiL/S0YP2Jo1a7J69Wpb+NqkSRPs7OzuOT6LiIiIZIfMwevevXv5/PPPOXv2rO1c5fPPP6dEiRJ0796dXbt2YbVaMZlM95REzM3Bq9VqBX4rE2kymejQoQPh4eFcunSJoUOHAthKDDg5OTFz5kz69OmDr69vtrVbci/1fP0Dx48fZ+jQoQQGBlK2bFkCAwO5ffs2R44cYezYsVSsWJHKlStz69YtXnrpJZ577jkWLFiQ3c3OUX744QcmTZrE7t276dixIzt27ODbb79lxYoVlCtX7g97tepOnoiI/FVJSUkEBgaSJ08e5s6dqxt4IiIikmNkvv4dMWIECxcuxM7OjsuXLzNy5Ejatm1L+fLlAahTpw6XL19mzpw5NGrUSOc0v4qJiWHdunUEBQVRqlQpXFxcbPNSU1NZuXIl3bt3p2fPnsyaNcs23dHR0bacsgb5tyl8vcvly5cpVKgQhmFw5coV/Pz8qFmzJiEhIQCcP3+eUqVKUaVKFW7dusUbb7yBj48PTz/9NCaTKVf3dP09GY+Crlmzhp9//pmDBw9SokSJLKMMNm/enCpVqjBx4sRsbq2IiDzqrly5gpub2+8+piciIiKSncaPH88HH3zAp59+SqNGjejVqxfLli2jT58+9OzZ0xbAVqhQgWrVqhEbG5vNLc4Zfv75Z7y8vLh+/TpFixbFy8uLBg0a4OfnZ1smJSWFlStX4ufnR+/evZkxY0b2NVjkV6oqnMnOnTsZOXIkW7ZswWQyUbBgQXr16kW3bt3o1q0bpUqVonnz5jRu3JjQ0FAOHz7MO++8w6lTp4iMjARU4/V+PDw8CAkJwWw2s3PnTmJiYhgyZAgODg5YLBZef/11Tp06RXx8fHY3VUREHgMFChQAdEwWERGRnOfUqVPs2LGDmTNn0qhRIxISEli2bBkvv/wyM2fOxGKx0KtXL5566ilOnjyp0kmZ5MuXj/bt21OmTBlq1KjBli1bGDRoEOvXr+f5558nMDAQJycnOnTogGEYdO7cmTJlyjBo0KDsbrrkcur5mklycjIVKlSgT58+tp6uN2/eJCAgAE9PTxYsWIC7uzvx8fEULFgQgHPnzlGiRAld3P0JGT1gv/rqK3x9fRkyZAitWrXi+PHjHDp0yFbjVSMNioiIiIiIyOPoypUrbN26lVdffZVDhw7h4+PDsGHDGDBgAL169SI+Pp727dvbHqsHPSaf2bp16+jQoQPbt2+nSpUqJCcnM2HCBMaMGcMLL7yAr68vLVq0oEqVKmzZsoX69esrY5Bsp8TwVxaLhTx58jB16lT279/PsWPHAHjiiSd45plnCAwMpFSpUmzYsMEWvFqtVkqVKoXZbNbdqD8hYzCUWrVqsWLFCooWLcqxY8cUvIqIiIiIiMhjJ2NgqMwKFChA48aNeeKJJ1iyZAkvvfQSvXv3BsDV1ZWSJUuSlJREyZIlbesoeP3Nq6++yhtvvMHcuXMByJMnD8uWLaNVq1Y0bdqUzz//HE9PTyIiImjUqBH29vakp6dnc6slt1PS9auMnVm1atWYPXs2O3bsoGLFigAEBQWxfft2KleuTN68eW3rZO7tqp3hn+Ph4UFwcDBBQUG4uroSHx+v4FVEREREREQeK5nLH61atYrk5GQAfH19cXNzA+DHH3/EbDaTkpKCo6MjZ86cYfr06TRo0ACTyaTa9b+jatWqLFiwgCtXrvDyyy/j7u5OVFQU+fPnJykpie3bt9OmTRvb8soaJLup7MCvMu/UoqKiGDx4MJ9//jnPPfccaWlpvPvuu+zevZuEhATy5cuXza199F29ehVXV1fMZrOCVxEREREREXlsZM4XBg0aRFRUFG5ubty8eZNSpUoxf/58PD09mT59Ou+++y4vvfQS586dIzU1lUOHDmFvb6/g9X+oWbMme/bsoX79+sTFxdlq/memrEFyilxbduDu7v+Zd2odOnSgTZs2LFu2jJSUFBwcHOjfvz/btm1j2bJl/3ZTH0vu7u6YzWasVqt2hiIiIiIiIvLYyMgXjh49yq5du9i8eTM7duxg9+7d2Nvb4+vry/fff8/gwYMJDQ3lySefpGHDhrbg1WKxKHj9HRn9BwcOHMhzzz3HtGnTKFCgAPfrV6isQXKKXNnzNXP3/6ioKPbt2weAp6cnfn5+AMyZM4fIyEjWrVuHu7s76enpfPLJJ7z55pv6AYuIiIiIiIjI74qIiCAmJgYXFxcWL16Mg4MDJpMJq9VK1apV8fDwYP369fesp96af8758+epUaMGAwcOZNiwYdndHJE/lCt7vmYEr4GBgQQHB5OamoqDgwM9evRg5MiRAPTt2xdnZ2f69+8P3Llj4u/vr2LNIiIiIiIiIvK7fvnlF44dO8a3337L2bNncXR0xGQycfv2bcxmM6NGjeLEiROcOXPmnnUVvP45JUqUYPjw4UydOpUjR45kd3NE/lCuDF8BNm3axNKlS1m6dClz5syhTp062NvbU6pUKdsyEydO5Nq1a3z22WdZ1tXOUERERERERETg3rKG+fLl46233qJHjx4cPXqUoKAgAJydnQHIkycPVqtVpQX+oebNm/Paa6/ZBksXyalyTYqYudQAQFJSEuXKlaNOnTrExcXRrVs3wsLC6N27N9evX+fIkSNUq1YNk8lEfHw8DRo0yMbWi4iIiIiIiEhOkzlrOHjwINevX6dkyZKULVuWwYMHY7VaiYqKIiUlhcDAQH7++WdmzZpF6dKlKV26dDa3/tFWvnx5IiMjMZlMWCwW7OzssrtJIveVa3q+ZuwMIyIi+Prrr3F2diZ//vxERUXRrVs3pk6dSu/evQHYtWsX8+bNw2QyMXr0aM6dO8ePP/6Ync0XERERERERkRzEMAxb1jBixAjatWtHjx49qFevHgMGDODKlSsMGDCAbt26ER4eznPPPcekSZNwdXVl/fr1tkGo5e/L6D2s4FVyssc+fM28I5s+fTrBwcE4OztTtGhR9uzZg7+/P6GhoQQEBABw69YtZs2aZVvHy8uL999/n6JFi/7rbRcRERERERGRnCkj+JsxYwYRERHMnz+f48eP07x5c6Kjozl37hyFChWiX79+DBs2jJIlS+Lu7s6SJUtwdnYmOTk5yxO6IvJ4euzLDmTsyI4ePcqFCxeYPXs2zz//PAAhISH07duXixcvkpCQwBNPPMGkSZP48ccfSUhIwN7eHsMwKFmyJHDnrpZqsoiIiIiIiIhIRkawa9cuhg4dSoMGDYiPj2fJkiVMnDgRb29vkpOTKVKkCH369AFgyZIlFCxYkJCQEPLkyZPNn0BE/g2PffhqGAabNm2iadOm5M+fnzp16tjmBQQEkJaWRkxMDLNnz8bT05OCBQuyZ88e7O3tSU9PzzK4loJXERERERERkdzp7rFk4M7Ts2fOnGHo0KHs3LmTrl27MnXqVAICAkhNTWXevHl4enpSr149AgICsLOzIywsDAcHB9tAXCLyeHssw9fMO0STyUSTJk0YNWoUoaGhfPnllzRu3BhXV1cABgwYQKdOnbh27Rr58+enUKFCmEyme4JXEREREREREcm9LBYLKSkpXLlyBQ8PD+zs7MibNy8VKlTA19eXS5cuER4ezhtvvAHA9evXiYuLw2w2U7duXYoVK4a/vz+Ojo74+Phk86cRkX+LyTAMI7sb8bDExsbi6OhI69atARg+fDhTpkxhzpw5dOnShbx58953vfvdzRIRERERERGR3GnDhg2sXLmS1atXc+PGDby9vWnVqhW9evUiMTGRnj17kpyczKFDhwC4cuUKXbt25fr163z++efY2dnZyhRYLBYNECWSizy24eulS5fw9vamXLlyvP322zRr1gyAoUOHMnPmTD788EM6d+78uwGsiIiIiIiIiEhERATvvvsuHTp0oGjRori5uTF79mwuX75M7969CQ0NJTY2lrFjx3Lx4kXKly9PWloaVquVL774AgcHBwWuIrnYY/Nc/d2DYRUuXJjly5cTEBBAWFgYhmHQvHlzpkyZgslk4q233uLmzZv06dMHJyenbGy5iIiIiIiIiOREc+fOZeDAgURFRdGuXTscHBwAaNiwIePGjePDDz/Ew8ODvn374u3tTUxMDFarFQ8PD7p06YKdnZ3KGorkco9dz9cff/yRokWL2l4fOnSInj17UqhQIQYOHEjTpk0B6N27N8ePH2fbtm0aSEtEREREREREsli5ciVt27YlPj6eli1b2kLUjF6sp06domfPnty4cYNVq1ZRrFixe95DPV5F5JEvbGq1Wm3///DDD/H392ffvn22aZUrV2bevHl8++23jB8/nvXr1wPw0Ucf2YLXxyx/FhEREREREZF/ICUlhfXr11OuXDm+++47gCzBq2EYlC9fnuHDh7N//35OnTp13/dR8Coij3z4mjEw1pUrV/Dy8uLgwYPMmDEjSwBbpUoVxo8fz759+xg3bhw7d+60zbu7XIGIiIiIiIiI5G5OTk68++67tGjRgoULFzJp0iTgTpiauRNY2bJlcXR05ObNm9nVVBHJ4R7Z8HXZsmWsWbMGgP/85z/06dOHWrVqER0dzY4dO5g2bVqWANZqtdKkSRMqVapE7dq1ATCZTApeRUREREREROQexYoVY9iwYdSoUYMVK1bYAliz2YzFYgHulDr08vKiUqVK2dlUEcnBHsnwNSUlhc2bN9OyZUvatWvH3LlzCQ4OBqB+/fosWLCAL774gmnTprFixQouX75MTEwMjRs3Jjw8HLPZnOVOlYiIiIiIiIjI3Tw8PBgxYsQ9Aay9vT03btwgIiKCihUrUrJkyWxuqYjkVI/cgFtWq9VWaqBy5cocOXKEWbNm0b9/f9LS0rCzs8NsNrNjxw6Cg4M5efIkDg4OFChQgK+++goHBweVGhARERERERGRPy0pKYlx48bx9ddf4+Pjw5AhQ2jdujVnz55lz5492NvbK2sQkft6pMLXzDuy6Oho3n//fSpUqEBcXBxxcXG0aNECi8WCYRjY29vz3Xff8d///peLFy/SunVr7OzsbKMTioiIiIiIiIj8WUlJSYwfP569e/dy8uRJ3NzcOHz4MA4ODraBuERE7vbIpJCZe7yGhoayaNEi4uLiKF++PIUKFaJt27a2ADZDeno69erVs722WCwKXkVERERERETkL/Pw8CA4OJigoCBcXV2Jj4/HwcFBnbxE5A89MnuHjOD17NmznD59mhkzZvDcc88BMHbsWEwmEz4+PixatIgmTZrQvXt3ChcuTHh4uO09dBdKRERERERERP4uDw8PZsyYgaurK2azWcGriPxPj9QeYsGCBfTt25eyZcvy9ttv26a7ubkxZswYHB0d8fHxoXLlyqSkpHDo0KFsbK2IiIiIiIiIPG7c3d2BO0/oKngVkf/lkar5CvDKK6+wadMmIiIi6Nq16z07ui1btnDx4kV8fX1V41VERERERERERESyTY4NXzPXeL1b/fr1OXv2LNHR0Xh7e2M2m+87qqAKXouIiIiIiIiIiEh2yZHha+bgde/evdy8eZPSpUtTqlQpW5hau3ZtLl68SFRUFHXq1PndAFZEREREREREREQkO+S48DVzgDpixAgWLlyInZ0dly9fZuTIkbRt25by5csDUKdOHS5fvsycOXNo1KiRglcRERERERERERHJMe7/XH82yghQx48fT2RkJAsWLOD06dN06NCB8ePHM3/+fE6dOgXArl27sFqtzJ07V8GriIiIiIiIiIiI5Cg5ciSqU6dOsWPHDmbOnEmjRo1ISEhg2bJlvPzyy8ycOROLxUKvXr146qmnOHnyJBaLJbubLCIiIiIiIiIiIpJFjuv5CuDu7k6PHj1o1qwZX375Jf369WPMmDEsXbqULl26EBkZycyZMzl37hwAdnZ2CmBFREREREREREQkR8n28NVqtd4zrUCBAjRu3JgnnniCJUuW8NJLL9G7d28AXF1dKVmyJElJSZQsWdK2TsZAXCIiIiIiIiIiIiI5QbaWHbBarZjNd/LfVatWkZycDICvry9ubm4A/Pjjj5jNZlJSUnB0dOTMmTNMnz6dBg0aYDKZsgzQJSIiIiIiIiIiIpJTZFv4ahiGLXgdNGgQUVFRuLm5cfPmTSZNmsT8+fPx9PSkevXqvPvuu1y7do1z586RmppK3bp1FbyKiIiIiIiIiIhIjpZt4WtGaHr06FF27drF5s2bKVq0KKmpqXTs2BFfX1+2bt3K4MGDMQyDs2fPUqFCBaZOnYq9vT0Wi0WlBkRERERERERERCTHMhmGYWTXH4+IiCAmJgYXFxcWL16Mg4MDJpMJq9VK1apV8fDwYP369fesl56ejr19tlZMEBEREREREREREflD2Tbg1i+//MKxY8f49ttvOXv2LI6OjphMJm7fvo3ZbGbUqFGcOHGCM2fO3LOuglcRERERERERERHJ6f618NVqtWZ5nS9fPt566y169OjB0aNHCQoKAsDZ2RmAPHnyYLVaVdNVREREREREREREHkn/ShdSq9VqG1zr4MGDXL9+nZIlS1K2bFkGDx6M1WolKiqKlJQUAgMD+fnnn5k1axalS5emdOnS/0YTRURERERERERERB6oh17z1TAMW+/VESNGEBsbi9ls5tatW7Rq1YrAwEDy5s1LWFgYEydOxNnZmVatWnH79m0iIyNxdnbOEt6KiIiIiIiIiIiIPAoeeqKZEbzOmDGDiIgI5s+fz/Hjx2nevDnR0dGcO3eOQoUK0a9fP4YNG0bJkiVxd3dnyZIlODs7k5ycrOBVREREREREREREHjkPvexARs/XXbt2MXToUBo0aEB8fDxLlixh4sSJeHt7k5ycTJEiRejTpw8AS5YsoWDBgoSEhJAnT56H3UQRERERERERERGRB+6Bh6/3KxFw69Ytzpw5w9ChQ9m5cyddu3Zl6tSpBAQEkJqayrx58/D09KRevXoEBARgZ2dHWFgYDg4OtoG4RERERERERERERB4lDzx8tVgspKSkcOXKFTw8PLCzsyNv3rxUqFABX19fLl26RHh4OG+88QYA169fJy4uDrPZTN26dSlWrBj+/v44Ojri4+PzoJsnIiIiIiIiIiIi8q94oANubdiwgZUrV7J69Wpu3LiBt7c3rVq1olevXiQmJtKzZ0+Sk5M5dOgQAFeuXKFr165cv36dzz//HDs7O1uZAovFgp2d3YNqmoiIiIiIiIiIiMi/6oGFrxEREbz77rt06NCBokWL4ubmxuzZs7l8+TK9e/cmNDSU2NhYxo4dy8WLFylfvjxpaWlYrVa++OILHBwcFLiKiIiIiIiIiIjIY+OBlB2YO3cuAwcOJCoqinbt2uHg4ABAw4YNGTduHB9++CEeHh707dsXb29vYmJisFqteHh40KVLF+zs7EhPT8fe/qGP/yUiIiIiIiIiIiLyr/jHPV9XrlxJ27ZtiY+Pp2XLlrYQNaMX66lTp+jZsyc3btxg1apVFCtW7J73UI9XERERERERERERedyY/8nKKSkprF+/nnLlyvHdd98BZAleDcOgfPnyDB8+nP3793Pq1Kn7vo+CVxEREREREREREXnc/KPn/J2cnHj33XdxcnJi4cKF3Lx5k6CgIOzs7LBarZhMJgDKli2Lo6MjN2/efCCNFhEREREREREREcnp/lHPV4BixYoxbNgwatSowYoVK5g0adKdNzabsVgsABw6dAgvLy8qVar0T/+ciIiIiIiIiIiIyCPhH4evAB4eHowYMeKeANbe3p4bN24QERFBxYoVKVmy5IP4cyIiIiIiIiIiIiI53j8ecCuzpKQkxo0bx9dff42Pjw9DhgyhdevWnD17lj179mBvb49hGLZyBCIiIiIiIiIiIiKPqwcavsKdAHb8+PHs3buXkydP4ubmxuHDh3FwcLANxCUiIiIiIiIiIiLyuHvg4SvcCWCDgoK4dOkS8fHxODg4kJ6ejr39PxrfS0REREREREREROSR8VDCV4CrV6/i6uqK2WxW8CoiIiIiIiIiIiK5zkMLXzNYrVbM5gcyrpeIiIiIiIiIiIjII+Ohh68iIiIiIiIiIiIiuZG6pIqIiIiIiIiIiIg8BApfRURERERERERERB4Cha8iIiIiIiIiIiIiD4HCVxEREREREREREZGHQOGriIiIiIiIiIiIyEOg8FVERERERERERETkIVD4KiIiIiLyL+nevTsmk4mzZ89md1NERERE5F+g8FVEREREHllnz57FZDJhMpkoUaIEFovlvssdOnTItlzFihX/9t977733MJlMbNu27W+/h4iIiIjkHgpfRUREROSRZ29vz4ULF1i/fv1953/88cfY29v/y62614QJEzh69CglSpTI7qaIiIiIyL9A4auIiIiIPPLq1KmDq6srERER98xLTU0lOjqa5s2bZ0PLsipWrBgVK1bEwcEhu5siIiIiIv8Cha8iIiIi8shzdnamQ4cOrFq1isuXL2eZl5CQwOXLl/Hz87vvuoZhEBERgbe3N/nz5ydv3rxUr179niD3pZdeIjQ0FICGDRvayhiULVvWtkzZsmUpW7Ys165dY+DAgZQqVQp7e3siIyOBP675un37dtq0aUPRokVxcnKiVKlStG3blh07dvz9DSMiIiIi2Sr7n70SEREREXkA/P39+eijj4iOjubtt9+2TY+IiKBIkSK0aNHinnUMw6Br164sWrSIp59+ms6dO+Po6MjGjRvp0aMHR44cYerUqcCd4BTgs88+o1u3brbQ1c3NLct7pqSk0KhRI27cuEHLli1xdHSkaNGif9j2Dz74gLfeegtnZ2fatGlD6dKlOX/+PDt27GDZsmXUrVv3728YEREREck2Cl9FRERE5LFQq1YtnnvuOSIiImzh6/nz59mwYQPvvPPOfWu+zp8/n0WLFtGjRw/Cw8Nty6SmpuLj48O0adPo1KkTXl5edO/enbNnz/LZZ5/RvXt3Xnrppfu2IykpiSpVqrBz506cnZ3/Z7sPHTrE22+/TbFixdi5c2eWnrSGYfDDDz/89Y0hIiIiIjmCyg6IiIiIyGPDz8+PgwcPsnfvXgAiIyOxWCz4+/vfd/mwsDCeeOIJwsLCsoSzjo6OjBs3DoCYmJi/3I4pU6b8qeAVIDw8HIvFwtixY7MErwAmk4nixYv/5b8vIiIiIjmDer6KiIiIyGPjjTfeYPjw4URERODl5UVkZCS1atWiUqVK9yx769YtDh06RPHixZk4ceI989PS0gA4duzYX2pDnjx5qFy58p9e/quvvgLglVde+Ut/R0RERERyPoWvIiIiIvLYKFKkCM2bNycmJobXX3+dkydPMmTIkPsue/XqVQzD4Pz587aBtO7n5s2bf7kNJpPpTy9/7do1TCYTxYoV+0t/R0RERERyPpUdEBEREZHHir+/P1evXqVHjx44OzvTqVOn+y6XP39+ALy8vDAM43f/bd269S/9/b8SvMKdAbtU21VERETk8aTwVUREREQeK82bN8fDw4Pz58/Trl07W8h6NxcXF5599lmOHj3KtWvX/tR729nZAWCxWB5Uc6lZsyYAGzZseGDvKSIiIiI5g8JXEREREXms2Nvbk5CQwIoVK2yDZv2egQMHcuvWLXr16nXf8gJnzpzh7NmzttcFChQA4Pvvv39g7e3Tpw92dnaEhITw3XffZZmnHrEiIiIijzbVfBURERGRx06NGjWoUaPG/1wuICCAL7/8kqioKHbu3MnLL79M8eLF+fHHHzl27Bi7d+9m0aJFlC1bFoCGDRtiMpkYMWIEx44dw9XVFVdXV/r27fu321q5cmVmzJjBwIEDee6552jdujVlypQhKSmJzz//nNdee40ZM2b87fcXERERkeyj8FVEREREci2TyURkZCTNmzdn3rx5rF69ml9++YUiRYrw1FNPMXXqVF5++WXb8pUqVWLBggVMmzaN999/n5SUFMqUKfOPwleAAQMG8PzzzzNt2jTWrl1ra0OtWrVo3779P/2YIiIiIpJNTIZhGNndCBEREREREREREZHHjWq+ioiIiIiIiIiIiDwECl9FREREREREREREHgKFryIiIiIiIiIiIiIPgcJXERERERERERERkYdA4auIiIiIiIiIiIjIQ6DwVUREREREREREROQhUPgqIiIiIiIiIiIi8hAofBURERERERERERF5CBS+ioiIiIiIiIiIiDwECl9FREREREREREREHgKFryIiIiIiIiIiIiIPgcJXERERERERERERkYdA4auIiIiIiIiIiIjIQ/D/zgf5MKLnM/AAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisloyal[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disloyal vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "22aa3477-4a71-4966-8278-0fb39583ffae", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--- T-Test Results for Inflight wifi service ---\n", + "df_1 Mean: 2.400\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 0.6064\n", + "P-Value: 0.5442639813\n", + "--------------------------------------\n", + "--- T-Test Results for Departure/Arrival time convenient ---\n", + "df_1 Mean: 3.129\n", + "df_2 Mean: 2.287\n", + "T-Statistic: 64.7514\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Ease of Online booking ---\n", + "df_1 Mean: 2.547\n", + "df_2 Mean: 2.394\n", + "T-Statistic: 15.5027\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Gate location ---\n", + "df_1 Mean: 2.976\n", + "df_2 Mean: 3.046\n", + "T-Statistic: -6.8515\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Food and drink ---\n", + "df_1 Mean: 2.958\n", + "df_2 Mean: 3.011\n", + "T-Statistic: -4.1709\n", + "P-Value: 0.0000304613\n", + "--------------------------------------\n", + "--- T-Test Results for Online boarding ---\n", + "df_1 Mean: 2.656\n", + "df_2 Mean: 2.425\n", + "T-Statistic: 23.2966\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Seat comfort ---\n", + "df_1 Mean: 3.036\n", + "df_2 Mean: 2.986\n", + "T-Statistic: 3.9404\n", + "P-Value: 0.0000816032\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight entertainment ---\n", + "df_1 Mean: 2.894\n", + "df_2 Mean: 3.031\n", + "T-Statistic: -10.6884\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for On-board service ---\n", + "df_1 Mean: 3.019\n", + "df_2 Mean: 3.078\n", + "T-Statistic: -4.9255\n", + "P-Value: 0.0000008475\n", + "--------------------------------------\n", + "--- T-Test Results for Leg room service ---\n", + "df_1 Mean: 2.991\n", + "df_2 Mean: 3.166\n", + "T-Statistic: -14.1632\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Baggage handling ---\n", + "df_1 Mean: 3.376\n", + "df_2 Mean: 3.565\n", + "T-Statistic: -18.5273\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Checkin service ---\n", + "df_1 Mean: 3.043\n", + "df_2 Mean: 3.059\n", + "T-Statistic: -1.3296\n", + "P-Value: 0.1836795869\n", + "--------------------------------------\n", + "--- T-Test Results for Inflight service ---\n", + "df_1 Mean: 3.389\n", + "df_2 Mean: 3.570\n", + "T-Statistic: -17.6556\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Cleanliness ---\n", + "df_1 Mean: 2.936\n", + "df_2 Mean: 3.045\n", + "T-Statistic: -8.4732\n", + "P-Value: 0.0000000000\n", + "--------------------------------------\n", + "--- T-Test Results for Departure Delay in Minutes ---\n", + "df_1 Mean: 16.504\n", + "df_2 Mean: 15.856\n", + "T-Statistic: 1.7952\n", + "P-Value: 0.0726400300\n", + "--------------------------------------\n", + "--- T-Test Results for Arrival Delay in Minutes ---\n", + "df_1 Mean: 17.128\n", + "df_2 Mean: 16.484\n", + "T-Statistic: 1.7473\n", + "P-Value: 0.0805987692\n", + "--------------------------------------\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisatisfied[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disatisfied vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = df['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on the entire population')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Disatisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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bb3H+/Hn06tUL4eHhaNy4MdauXXvH90p0KyyAVCSCgoKgUqlw+fLlGx67dOkSACA0NDRv2cCBAxESEoKZM2di4cKFSEhIuKGAzZkzB0OHDsW7776Ljh07olGjRmjQoMF9/zasUqkwZswYLFq0CJcvX8bnn3+Odu3aISYm5ravu14eblbY7qbEhYaGYsaMGTh37hzOnz+PKVOmYMmSJTeMkt3Of4vOnfw3l91uR3Jycr4ipNfrbzhhAsB9lcSQkBDY7fYbTjgRQiAhISHf98L9CAkJwZUrVyCEyLf86tWrsNvthbadW+nbty9q1aqFQ4cOAQDS09OxYsUKjBs3Dq+88gratWuHhg0bombNmkhJSbmvbXXv3h1//vkn0tPTsX79epQuXRoDBw684SSGO7m+T8aPH4+dO3fe9Ov6JVRCQkLu+fv9evm/cOHCbZ9nMBhu+v13s3/n97oPrn+/3+rzSaVS3TAKd69CQ0NRs2bNW+7bCRMm5Hv+rf5NjxgxAlu2bEF6ejpWrlwJIQS6dOlyx9FqolthAaQi4ePjg8aNG2PJkiX5RjmcTifmzJmD0qVLo3LlynnLDQYDHnvsMfzwww/48MMPUadOHTRv3jzfOhVFgV6vz7ds5cqVdzX1c/11txpxeeSRR6DT6TBo0CAcP34cTz311B3X2aRJExgMBsydOzff8i1bthT4Q7ls2bJ46qmn0KFDB+zZsydf7vsZ3fyv/2ZdsGAB7HZ7votWR0dH48CBA/me99dffyErKyvfsjvt039r164dgGsl/t8WL16M7OzsvMfvV7t27ZCVlYVly5blW/7jjz/my3G/blYcgGvTvfHx8Xmj3IqiQAhxw/ft119/DYfDkW9ZQfbnf18XGxuLqVOnArh28eeCiImJQaVKlbB//340aNDgpl/Xp8nbtGmDP//8M2/UELh2+aH58+ffcTuVK1dGhQoV8O2339604F0XHR2Nq1ev5tuG1WrF77//fsvX3Gof3GqfxsTEIDIyEj/99FO+Xxays7OxePHivDODC0OXLl1w+vRphISE3HTfFvQC3z4+PujUqRNee+01WK1WHD58uFBykvfhdQDpvvz11183vfp/586dMWXKFHTo0AFt2rTBiy++CJ1Oh88//xyHDh3CvHnzbvhNd/To0Zg2bRp2796Nr7/++oZ1dunSBd9//z2qVKmCWrVqYffu3Zg+ffpdTSnVrFkTAPDxxx9j2LBh0Gq1iImJyfvBFhgYiKFDh2LWrFmIiopC165d77jOoKAgvPjii5g8eTIeeeQR9OnTB/Hx8Zg0adIdp8TS09PRpk0bDBw4EFWqVIGfnx927tyJ1atXo2fPnvlyL1myBLNmzUL9+vWhUqnQoEGDO2a7lSVLlkCj0aBDhw44fPgwJkyYgNq1a6Nv3755zxkyZAgmTJiAiRMnIjY2FkeOHMFnn32GgICAfOuqUaMGAOCrr76Cn58fDAYDypUrd9Np1Q4dOqBjx454+eWXkZGRgebNm+PAgQN44403ULduXQwZMuSe39O/DR06FDNnzsSwYcNw7tw51KxZE5s2bcK7776Lzp07o3379oWynXfeeQebN29Gv379UKdOHRiNRpw9exafffYZkpOTMX36dACAv78/WrVqhenTpyM0NBTR0dHYsGEDvvnmmxsuSF6Q/Tlx4kRcuHAB7dq1Q+nSpZGWloaPP/4YWq0WsbGxBX4/X375JTp16oSOHTti+PDhiIyMREpKCo4ePYo9e/bkXYrp9ddfxy+//IK2bdti4sSJMJlMmDlz5g2XM7mVmTNnomvXrmjSpAmee+45lC1bFnFxcfj999/zfjnp168fJk6ciP79++Oll16CxWLBJ598ckNhvpt9UKFCBRiNRsydOxdVq1aFr68vSpUqhVKlSmHatGkYNGgQunTpgscffxy5ubmYPn060tLS8N577xV4H97K2LFjsXjxYrRq1QrPPfccatWqBafTibi4OKxZswYvvPACGjdufNt1PProozAajWjevDlKliyJhIQETJkyBQEBAXnHQhIVmMQTUMiNXT8L+FZf188G/Pvvv0Xbtm2Fj4+PMBqNokmTJuLXX3+95Xpbt24tgoODRU5Ozg2PpaamilGjRonw8HBhMplEixYtxN9//y1iY2PveMatEEKMHz9elCpVKu/Mzf+ebbl+/XoBQLz33nt3vR+cTqeYMmWKKFOmjNDpdKJWrVri119/vWMmi8UinnjiCVGrVi3h7+8vjEajiImJEW+88YbIzs7Oe11KSoro3bu3CAwMFIqi5J0FeX1906dPvyHT7c4C3r17t+jatavw9fUVfn5+YsCAAeLKlSv5Xp+bmyvGjRsnypQpI4xGo4iNjRX79u274SxgIYSYMWOGKFeunFCr1fm2ebMzOc1ms3j55ZdFVFSU0Gq1omTJkuLJJ58Uqamp+Z4XFRUlHnrooRve13/36a0kJyeLJ554QpQsWVJoNBoRFRUlxo8fn+9SM0Lc/AzZ69v/7/v8r23btokxY8aI2rVri+DgYKFWq0VYWJh48MEH853VKYQQFy5cEL169RJBQUHCz89PPPjgg+LQoUP3tT9XrFghOnXqJCIjI4VOpxPh4eGic+fO+S5fcqv3eLOzgIUQYv/+/aJv374iPDxcaLVaUaJECdG2bVvxxRdf5Hve5s2bRZMmTYRerxclSpQQL730kvjqq6/u6ixgIYTYunWr6NSpkwgICBB6vV5UqFDhhrPTV61aJerUqSOMRqMoX768+Oyzz244C/hu98G8efNElSpVhFarveEM92XLlonGjRsLg8EgfHx8RLt27cTmzZvzvf76dq9fsue6YcOGCR8fnxveX2xsrKhevXq+ZVlZWeL1118XMTExQqfTiYCAAFGzZk3x3HPP5Tuj+lbfkz/88INo06aNiIiIEDqdTpQqVUr07dtXHDhw4BZ7mejOFCH+c7AMkSRXr15FVFQUnn766ZteTLWovfDCC5g1axbi4+NvOupCRETkKTgFTNJduHABZ86cwfTp06FSqYr9HrLbtm3DiRMn8Pnnn+Pxxx9n+SMiIo/HAkjSff3113jrrbcQHR2NuXPnIjIysli3f/2A7y5dumDy5MnFum0iIiIZOAVMRERE5GV4GRgiIiIiL8MCSERERORlWACJiIiIvAwLIBEREZGXYQEkIiIi8jIsgERERERehgWQiIiIyMuwABIRERF5GRZAIiIiIi/DAkhERETkZVgAiYjIpbRu3Rpjx47N+3N0dDRmzJhxV68tyHMLy/Dhw/Hwww8X6zaJ7hcLIBERubSdO3fisccekx3jvggh8NVXX6Fx48bw9fVFYGAgGjRogBkzZiAnJ6dQtvHf4kx0OyyARETk0sLCwmAymWTHuC9DhgzB2LFj0b17d6xbtw779u3DhAkTsHz5cqxZs0Z2vGJhtVplR6B/YQEkIiJpsrOzMXToUPj6+qJkyZL44IMPbnjOf6d1J02ahLJly0Kv16NUqVJ45plnbrn+uLg4dO/eHb6+vvD390ffvn1x5coVAMC5c+egUqmwa9eufK/59NNPERUVBSEEHA4HRo0ahXLlysFoNCImJgYff/xxgd7jggULMHfuXMybNw+vvvoqGjZsiOjoaHTv3h1//fUX2rRpA+DmI3gPP/wwhg8fnvfnzz//HJUqVYLBYEBERAR69+4N4No09IYNG/Dxxx9DURQoioJz584BADZs2IBGjRpBr9ejZMmSeOWVV2C32/PW2bp1azz99NMYO3YsgoKCEBERga+++grZ2dkYMWIE/Pz8UKFCBfz222/5sh05cgSdO3eGr68vIiIiMGTIECQlJeVb71NPPYXnn38eoaGh6NChQ4H2GxUtFkAiIpLmpZdewrp167B06VKsWbMG69evx+7du2/5/EWLFuGjjz7Cl19+iZMnT2LZsmWoWbPmTZ8rhMDDDz+MlJQUbNiwAWvXrsXp06fRr18/ANeKZfv27fHdd9/le913332H4cOHQ1EUOJ1OlC5dGgsWLMCRI0cwceJEvPrqq1iwYMFdv8e5c+ciJiYG3bt3v+ExRVEQEBBwV+vZtWsXnnnmGbz11ls4fvw4Vq9ejVatWgEAPv74YzRt2hSPPvooLl++jMuXL6NMmTK4ePEiOnfujIYNG2L//v2YNWsWvvnmG0yePDnfun/44QeEhoZix44dePrpp/Hkk0+iT58+aNasGfbs2YOOHTtiyJAhedPVly9fRmxsLOrUqYNdu3Zh9erVuHLlCvr27XvDejUaDTZv3owvv/zyrvcZFQNBREQkQWZmptDpdOLnn3/OW5acnCyMRqN49tln85ZFRUWJjz76SAghxAcffCAqV64srFbrTdf57+euWbNGqNVqERcXl/f44cOHBQCxY8cOIYQQ8+fPF0FBQcJisQghhNi3b59QFEWcPXv2lrlHjx4tevXqlffnYcOGie7du9/y+VWrVhXdunW75ePXxcbG5nvfQgjRvXt3MWzYMCGEEIsXLxb+/v4iIyPjrl//6quvipiYGOF0OvOWzZw5U/j6+gqHw5H3uhYtWuQ9brfbhY+PjxgyZEjessuXLwsAYuvWrUIIISZMmCAeeOCBfNuKj48XAMTx48fz1lunTp07vm+SgyOAREQkxenTp2G1WtG0adO8ZcHBwYiJibnla/r06QOz2Yzy5cvj0UcfxdKlS/NNZ/7b0aNHUaZMGZQpUyZvWbVq1RAYGIijR48CuDbFqtFosHTpUgDAt99+izZt2iA6OjrvNV988QUaNGiAsLAw+Pr6Yvbs2YiLi7vr9ymEgKIod/38W+nQoQOioqJQvnx5DBkyBHPnzr3jCSRHjx5F06ZN822/efPmyMrKwoULF/KW1apVK+//1Wo1QkJC8o2sRkREAACuXr0KANi9ezfWrVsHX1/fvK8qVaoAuPb3el2DBg3u4x1TUWIBJCIiKYQQBX5NmTJlcPz4ccycORNGoxGjR49Gq1atYLPZbrr+mxWvfy/X6XQYMmQIvvvuO1itVvz0008YOXJk3nMXLFiA5557DiNHjsSaNWuwb98+jBgxokAnNFSuXDmvcN6OSqW6YZ/8+335+flhz549mDdvHkqWLImJEyeidu3aSEtLu+U6b7YPrm/j38u1Wm2+5yiKkm/Z9ec6nc68/3bt2hX79u3L93Xy5Mm8aWkA8PHxueP7JjlYAImISIqKFStCq9Vi27ZtectSU1Nx4sSJ277OaDSiW7du+OSTT7B+/Xps3boVBw8evOF51apVQ1xcHOLj4/OWHTlyBOnp6ahatWreskceeQR//PEHPv/8c9hsNvTs2TPvsb///hvNmjXD6NGjUbduXVSsWDHfCNfdGDhwIE6cOIHly5ff8JgQAunp6QCune18+fLlvMccDgcOHTqU7/kajQbt27fHtGnTcODAAZw7dw5//fUXgGtl1uFw3LAPtmzZkq9YbtmyBX5+foiMjCzQ+/i3evXq4fDhw4iOjkbFihXzfbH0uQcWQCIiksLX1xejRo3CSy+9hD///BOHDh3C8OHDoVLd+kfT999/j2+++QaHDh3CmTNn8L///Q9GoxFRUVE3PLd9+/aoVasWBg0ahD179mDHjh0YOnQoYmNj801NVq1aFU2aNMHLL7+MAQMGwGg05j1WsWJF7Nq1C7///jtOnDiBCRMmYOfOnQV6n3379kW/fv0wYMAATJkyBbt27cL58+exYsUKtG/fHuvWrQMAtG3bFitXrsTKlStx7NgxjB49Ot/o3ooVK/DJJ59g3759OH/+PH788Uc4nc68KfPo6Ghs374d586dQ1JSEpxOJ0aPHo34+Hg8/fTTOHbsGJYvX4433ngDzz///G33852MGTMGKSkpGDBgAHbs2IEzZ85gzZo1GDly5A0llFwTCyAREUkzffp0tGrVCt26dUP79u3RokUL1K9f/5bPDwwMxOzZs9G8eXPUqlULf/75J3799VeEhITc8FxFUbBs2TIEBQWhVatWaN++PcqXL4/58+ff8NxRo0bBarXmm/4FgCeeeAI9e/ZEv3790LhxYyQnJ2P06NEFeo+KouCnn37Chx9+iKVLlyI2Nha1atXCpEmT0L17d3Ts2BEAMHLkSAwbNiyvpJYrVy7vEjHX3/uSJUvQtm1bVK1aFV988QXmzZuH6tWrAwBefPFFqNVqVKtWDWFhYYiLi0NkZCRWrVqFHTt2oHbt2njiiScwatQovP766wV6D/9VqlQpbN68GQ6HAx07dkSNGjXw7LPPIiAg4L6KJRUfRdzLQRhEREQe5J133sHPP/9806lkIk/Emk5ERF4rKysLO3fuxKeffnrbC0oTeRoWQCIi8lpPPfUUWrRogdjY2Bumf4k8GaeAiYiIiLwMRwCJiIiIvAwLIBEREZGXYQEkIiIi8jIsgEREREReRiM7ABHRvbDb7cjOzkZWVhays7Nv+/92ux1OpzPfV3JyMgAgJCQEiqJApVLlfRmNRphMpjt++fj4wMfH56b3myUicmUsgEQknRACmZmZuHr1Kq5cuYIrV67c8P+XLifgckICUlNSkJOdDZvNesf1Kmo1NDoTFLUaiqICFACKCoqiwJKeBL1aINxPB6fAP18CDidgsTuRnevA3VwjQavVIDQ4EGGhYQgNC0doeARCQ0Nv+AoLC0Pp0qXzCicRkUy8DAwRFTmn04mEhAScOXMGp0+fxpkzZ3DmzBmcPHUa8RcuIinxKqy5lnyvUVRq6HwDoPYJAgz+UEyBUJsCoTL5Q9EaoNIZr/1Xq4fy7//XGqHo/vl/tfaWmeI/HYyHSmfhlwGmmz4uhIDVAeTYgByb+OcL+f6bZQVSzAJJOQJJOU4kmQUSc1RIsihIyhFIzLLDanfmW6/JaEDZ0pEoG10OZaOiUbZsWURFRaFs2bIoW7YsSpcuDZ1Od/87nYjoNjgCSESFwmaz4eTJk/kK3qlTp3Di1GnEnT+fr+Dp/UOgDoiA4h8BdenG8IkJhL8pECqfayVP7RMIldHv2qidJIqiQK8B9BogyHhvI3ZCCGTbgKQcgavZAvHpTsSlOxGXHo/z8eex94gayzOcSMy05dtuyYhQxFSpiipVq6Nq1aqoUqUKqlatisjISI4eElGh4AggERWIEAIJCQk4cOAADh48iAMHDmD33n04efx43rSsWquDPqgk4B8BdUAENIElrn0FlIAmMAIqrUHyu7jzCGBxyrFdL4cCcelOnE1z4niyE8dS1DiRZMsbRfT1MaJKTAyqVKuRVwqrVq2KypUrQ61WS34XROROOAJIRLeUk5ODI0eO4MCBAzhw4AD27t+PAwcOIi3l2gkUGr0RurBoqEKi4BvbDLqwaGiCSkHtGyR19M7dmLQKYkLViAm98TGHU4ezaQLHkhw4mujEsaTDOPb3Eaxc4kRqjv3a640G1KldG/UbNkL9+vVRv359VKlSBRoNP+KJ6OY4AkhEAK6N7J06dQpbt27F1q1bsXHTZhw7chhOpxNQFBhDIqGEREEbFg1dWDS04eWgCQh326LnSiOA90IIgcQcgUNXndhz2YE9l53YfUWFE4m5AACjQY/atWqifsPGeaWwatWq0GpvfVwkEXkPFkAiL5WTk4OdO3di69at2Lx5MzZv2YrUf0b2jOFRUJeIga5UDHTh5aANLesS07aFyd0L4K1k5ArsvezA7n+VwuOJuRDi2khhk8aN0TK2NVq1aoUmTZrAZPKs909Ed4cFkMhLXLp0CRs2bMgb3Tt08AAcdjs0ehN0pSpDW7IK9JFVoSsVA7XBV3bcIuepBfBmMnMF9iU4sP2iA3/HObHpgkBKth0ajRr169ZBq9Zt0bJlSzRv3hzBwcGy4xJRMWABJPJQ2dnZ2LhxI9auXYtVq3/H8aNHAACGkEioS8ZAX+pa4dOGloWi8r4TCLypAP6XUwgcSXTi7/MO/B3nwMYLCi6mXTuBp2b1qmgZ2wZt2rRB+/btERgYKDcsERUJFkAiD+F0OrF3716sXbsWv/3+O7Zu3gKbzQp9QBg0ZWvDGF0XhqjaUPsEyo7qEry5AP6XEALn0gT+jrNj4/lrhfBkohVqtQpNGjXCg50fwoMPPoh69epBpXLPYz6JKD8WQCI3Fh8fj7Vr1+L339dgzdq1SEtNgUZvhL5MTeii6sBYri40waV57bibYAG8vbh0J34/Zcfq0w78cU4gw2xHaHAgOna6VgYfeOABhIeHy45JRPeIBZDIjQghcPDgQSxduhQLFi3GkUMHoSgqGEtVgqbstcKnLxVz2ztg0DUsgHfP5hDYdsGB1afsWH0W2HPx2nRx/bq18WDnLujWrRsaNGjA0UEiN8ICSOTinE4nduzYgSVLlmDBosU4f/YMNAYf6Cs0hLFik2vTukY/2THdDgvgvbuS5cSa09dGB38/AyRn2xBZMgIP9+yNHj16oFWrVrzcDJGLYwEkckF2ux0bN27EkiVLsHDxElxNuAydbxB0FRrDVLkpDFG1OMp3n1gAC4fdKbApzoGlR+1YelIgPtWGoAB/dO/RE71790aHDh14b2MiF8QCSOQicnNzsWbNGixZsgRLly1Heloq9IER0FVsAlPlptBHVvXKs3WLCgtg4RNCYM9lJ5Yes2HRMeB4ohUB/r7o/nBP9OnTBx06dIBer5cdk4jAAkgkldPpxObNmzFnzhzM+3k+MjPSYQwrC23FpjBVbgpdRAWewFFEWACLlhDX7lKy8IgNC48Bx65aERTgj34DBmLo0KFo0qQJv7eJJGIBJJLg2LFjmDNnDn743xxciDsPfVAE9FVi4VOtNXShZWXH8wosgMXr8FUHfjpow/8OX5smrlShHIYOH4nBgwcjOjpadjwir8MCSFRMUlNT8fPPP+Obb7/D7l07oTH6wlC5OXyqt4G+dDW3vaeuu2IBlMMpBNafc+DH/TYsOuZEdq4DsS1bYOjwEejduzf8/f1lRyTyCiyAREXI4XDgjz/+wHfffY8lS5fCbrPBWKE+TNXbwVSxERQND46XhQVQvmyrwNJjNvxwwIk/z1hh0OvRo0dPDB02DO3bt4dazWNeiYoKCyBREbhy5Qpmz56NmbO+QMKlizCElYWhejv4VG8DjS/vteoKWABdy4UMJ+YesOGHgwJHr1pRLqoMnhj9FEaOHInQ0FDZ8Yg8DgsgUSERQmDbtm349NPPsHDhQgiVCsaqsfCt1RG6kpV5wLuLYQF0TUII7LjowKxdNvx8xAEBFfr27YfRY8bwxBGiQsQCSHSfzGYz5s2bh48/+RQH9u+DIbgUjLU7wadWB6gNvrLj0S2wALq+5Bwnvttnw6w9TpxJtqFOrRoY/dQzGDhwIHx8fGTHI3JrLIBE9+jMmTOYNWsWvpr9NTIy0mGq0AC+dR6CoXw9ntDhBlgA3YdTCKw57cCs3XasOGGDr48Jw4aPxJNPPomqVavKjkfkllgAiQrA6XRizZo1+OTTT7H6t9+gMfrCWL09fOt2hjaopOx4VAAsgO7pfJoTX+22YvY+JxKz7Oj4QHuMe3k82rRpw+lhogLgMAXRXbDZbPjhhx9QpVp1dOrUCev3HEdQx6dR4onvENR2FMsfUTGJClThnXYGxD9rxJweRlw5tBHt2rVDg3p1MX/+fNjtdtkRidwCCyDRbeTk5ODTTz9FdPkKGD58OC45AxAxaCrChs6AX+0HoNIaZEck8kp6jYJBtbTY84geawabEJx5FP3790fliuUxc+ZM5OTkyI5I5NI4BUx0E2lpaZg5cyY+/GgGUlNS4FO1Ffya9IYuLFp2NCoknAL2PHsuOzB9ixULDtsRFBiAp555FmPGjEFYWJjsaEQuhwWQ6F8SEhIwY8YMfDZzJswWK0w12sG/cS9oA0vIjkaFjAXQc51NdeKjbVZ8s88BodJgxMhRGDduHKKiomRHI3IZLIBEAM6ePYvp06fj62++hVCpYardCX4NuvOizR6MBdDzJec48flOGz7Z5UC6BRg1ahRefe01lClTRnY0Iul4DCB5tTNnzmDo0GGoWKkSvv7xJ/g07osSj3+LoNYjWP6I3FyISYUJsXqce9qIya3VWDjnG1SsUB5PP/00Ll26JDsekVQsgOSVEhIS8NRTTyEmpgrmL1uBgNajUOLxbxDQrB8v3kzkYXx0CsY11+Ps00a80VKNud9+gQrly+G5555DQkKC7HhEUnAKmLxKWloapk2bho9mfAwHVPBp1Bt+9bvwbF4vxClg75VuEfh4uxUfbnfAKtQY89TTGDduHE8WIa/CAkheIScnB5988gnenfIeciy58KnXFf6Ne3G0z4uxAFKqWeCjbbmYscMBp0qHp595FuPGjUNQUJDsaERFjlPA5NFsNhtmzZqFcuUr4LXXJwAVW6Dko7MRFDuM5Y/IywUZFbzVxoCzTxvxTD0HPv1oOiqWL4dPPvkEVqtVdjyiIsUCSB7J6XRi7ty5qFQ5BqPHjEFOaFWUeOQLBHd4Empf/nZPRP8vxKTCu+0MODnGiJ7lcvDcc2NRo1oVLFu2DJwkI0/FAkgeZ+PGjahTtx4GDx6MJG0ESo74FCFdXuC1/Ijotkr6qTC7mxH7HjOhnHIRPXr0QOtWLbFr1y7Z0YgKHQsgeYwLFy6gf//+iI2NxalkCyIGTUdoz9d59w4iKpCaEWr8PsiA3waZkHxyJxo2bIjBgwYhLi5OdjSiQsMCSG7PYrHg3XffRaXKMVi6ai1COo9F2KDpMJSuKjsaEbmxBytqsO8xPb7sYsDaXxcipnIlvPrqq8jIyJAdjei+sQCS2xJC4JdffkFM1WqYMHEidDU6ImLULPjWbA9F4bc2Ed0/jUrBY/V1ODXGgBcaAR+9PxWVK1bA3LlzeXwguTX+lCS3dOzYMXR88EF0794dSapglBjxGYLajoJK7yM7GhF5ID+9gsltDTgxxoRW4RkYPHgw2rVtjaNHj8qORnRPWADJrWRkZOCll15CjZo1sXHXQYT1nIDQ3pOgDeG9PYmo6JUJUGFB72vHB8Yd3IbatWrh1VdfRU5OjuxoRAXCAkhuQQiBuXPnokLFSvjok8/g12wgIkbMhKlSYyiKIjseEXmZBytqcOgJPV5rrsaH709F9aoxWLFihexYRHeNBZBcXlxcHDp17ozBgwfDHBqDEqO+QEDTvlA0OtnRiMiLGTQK3mitx8HHjaisu4quXbvi4e7dcP78ednRiO6IBZBcltPpxOeff46q1aph/dZdCOs1EaHdXobGP1R2NCKiPJVC1Fg9UI8FvY3YuWE1qlWtgqlTp8Jms8mORnRLLIDkko4fP44WLVthzJgxUFduhfARn8NUsZHsWEREN6UoCvpU1+LYkwY8UduJ114dj0YN6mP//v2yoxHdFAsguRSbzYZ3330XNWvVxt7j5xAxYAqCHxgDld4kOxoR0R356RV80NGAHY+Y4Lh6HA0a1Mebb77J0UByOSyA5DL27NmDevUb4PUJE2Gs2xVhwz6BoWxN2bGIiAqsXkk1dj2ixytN1Xj7rTc5GkguhwWQpDObzXj55ZfRsFEjnE7MRsSQDxDUejhUWr3saERE90ynVvB2W44GkmtiASSpdu7ciRq1auODD2fAv/kghA3+APoSFWXHIiIqNNdHA8c342gguQ4WQJLC4XDg3XffRdNmzXA5R0HE8I+vXdpFrZEdjYio0OnUCt5qc+NooNVqlR2NvBQLIBW7uLg4xLZug9defx0+DXshbOA03smDiLzCf0cDmzVphBMnTsiORV6IBZCK1fz581G9Zk3sOnQcEQOmIKjVEI76EZFXuT4auG2UCZkXjqJundr4+uuvIYSQHY28CAsgFYuMjAwMHToM/fv3ByLrIHzYJzCUqSE7FhGRNA1KqbHnET0GVnXi0UcfRe9ePZGSkiI7FnkJFkAqclu3bkXN2nUwb+EihDz0PIK7vgSVwVd2LCIi6Xx0CmZ3NWBRHyP++O0XxFQsj40bN8qORV6ABZCKjN1ux1tvvYUWLVsi0W5A+LBP4FujLRRFkR2NiMil1Cmhhs3hRHJGNtq0aYO33noLDodDdizyYDz4iopEfHw8+vbrj+3btsG/WT8ENOsPRaWWHYuIyOVYHQJ9F5lhF2qUemw2sg6sxaRJb+KPP//EvJ9+QmRkpOyI5IE4AkiF7s8//0TtOnWx9+gphA+cisAWg1j+iIhuYeK6XOy97ID/A09D4x+GwBYDEd7/HWzfdwQ1atbCypUrZUckD8QCSIVGCIGpU6figQceQG5AWYQN+QiG0lVlxyIicll/nLFj2mYr9OXrw7dm+7zlhrI1ET7sY1hDKqBLly6YOHEinE6nxKTkaVgAqVCkp6ejR8+eeOWVV+DbuA9Ce0+C2hQgOxYRkctKzHZi4GIzNEZfhPWacMPjalMAQntORGCroXh78mQ81KULUlNTJSQlT8QCSPft0KFDqFe/AVauXouwnhOuXduPU75ERLckhMCw5RakWoCQfu9Cpbr5IfmKoiCgaV+E956EPzdsQr36DXDo0KFiTkueiAWQ7su8efPQsFFjXM5yIHzIhzBVaiw7EhGRy/t0hxW/nbTD1LQ/9BHl7/h8Y/n6CBvyEa7kAA0bNcaCBQuKISV5MhZAuic2mw1jx47FwIEDoSnfCKEDp0MbzDPViIjuZH+CAy+syYU2vDyCWgy669dpA0sgdOA0aMo1RL9+/TBu3DjY7fYiTEqejJeBoQK7fPkyevbqjR07tiO4wxPwrfsQr+1HRHQXsq0CfRaaoai1KDHgvQK/XqUzILjLi9CWqIT3P/gQu3btxoIF8xEaGloEacmTcQSQCmTHjh2oXacu9hw+gbD+78GvXheWPyKiuzT2dwtOpzoR2P1VqAyme1qHoijwb/gwwvu+jU07dqNuvfrYs2dPISclT8cCSHdtwYIFaNkqFlm6YIQP5SVeiIgKYtERG77eY4OhWluYKjS87/UZomohfOhHSHbo0bRZc8yZM6cQUpK3YAGkOxJC4O2330a/fv2gq9AEYf3egdonSHYsIiK3EZfuxMjlZmj8QhDSeWyhrVfjH47Q/u9BV6k5hgwZgjfffBNCiEJbP3kuHgNIt2WxWDBi5Ej8PG8eAloORkDTfpzyJSIqALtToP9iM8wOFcIHToVKVbhjLyqtHsGdx0ITHIlJkybhzJmzmD37K+h0ukLdDnkWFkC6pcTERHTp2g279+xFaPdX4FOlhexIRERu552NVmyLdyCww2hoA0sUyTauXy9QExCOOT99jLi4OCxdugSBgYFFsj1yf5wCpps6ceIEGjZqjH2HjyOs/7ssf0RE9+Dv83a8uSEXurK14F+vc5Fvz6daa4T1fRubd+xC02bNcf78+SLfJrknFkC6wd9//41GjZvgSrYDoYOmQ18qRnYkIiK3k2oW6LfYDI3BhPA+k4ptu4YyNRA2cBrOXklFw0aNsXv37mLbNrkPFkDKZ968eWjXrj1sAWUQOnBakU1XEBF5MiEERv1ixtVsgeDeb0KlKd7j8bQhZRA2cDqytIFo0bIVVqxYUazbJ9fHAkh5pk+fjoEDB0If0wKhfd6E2uArOxIRkVv6eo8NS4/ZYarfA4ZIOZfMUvsEIrTfO1CXqY3u3bvj888/l5KDXBMLIEEIgfHjx2PcuHHwb9oXwZ2fg6LWyo5FROSWjiQ68PRvFmhCSiO47SipWVRaA0K6vwKfel0xZswYvPjii3A6nVIzkWvgWcBezul0YvTo0fjyyy8R1GYk/Bv1lB2JiMhtWewCfRea4VQ0iBg4VXYcAICiUiO43aPQBETggw8/RGJiEr755mtoNKwA3ox/+17MZrNh6NBhmD9/PkI6PQPfWg/IjkRE5NbGrc3F0SQngruNg8YUIDtOPv4NukFtCsCcuR8iMysTP8+bx2sFejFOAXsps9mM7g8/jAULFyKk2ziWPyKi+7TihA2f7rBCX7m5y146y6daLEK6v4rlv/yKbt27w2w2y45EkrAAeqGMjAx0eKAj1vzxF0J7TnDZDyoiIndxKdOJoUst0PoEIrTby7Lj3JapUmOE9noDf/y1Hg90fBCZmZmyI5EELIBeJjExEa1iW2P77r0I7fM2jOXry45EROTWnEJg8BILMm1A6ID3Cv1Wb0XBGF0HoX3exrZde9CmbTukpKTIjkTFzPW/S6nQXLhwAc1btMTRU+cQ1v9dGErLuTQBEZEnmb7ZinXn7PBtORy6kNKy49w1Q+mqCO07GQeOnkCr2Na4cuWK7EhUjFgAvcTJkyfRtFlzxF1NReiA96ALLy87EhGR29tx0YHX/sqFrlQMAhr3kh2nwPQlKiK0/xScjLuE5i1aIj4+XnYkKiYsgF7g1KlTaNkqFklmgdAB06ANjpQdiYjI7WXkCvRZaIZKp0dEv3dkx7lnutCyCB0wFReSM9GseQucOnVKdiQqBiyAHu7s2bOIbd0G6XY1Qvu9C41/qOxIREQeYfRKCy5mOBHUcxJUOoPsOPdFG1gCof3fQ5JZoHmLljh+/LjsSFTEWAA9WFxcHGJbt0Gy2YmQvpOh9g2SHYmIyCP8b78Vcw/aYKzzEIxla8qOUyg0/qEI7T8FGcKA2DZtcebMGdmRqAixAHqoCxcuoFVsa1zNtCK03zvQ+HHkj4ioMJxKceLxFRZoA0sg5IEnZccpVGqfQIT2eRvpNhViW7dBXFyc7EhURFgAPdClS5cQ27oNEtKyEdpvMjT+YbIjERF5BKvj2q3e7FAj3EVu9VbY1L5BCOkzGYnZNsS2aYtLly7JjkRFgAXQw1y5cgWt27TFxaR0hPR7F5qACNmRiIg8xoS/crEvwQH/B56Bxi9Edpwio/EPRUift3E5OQNt2rbD1atXZUeiQsYC6EESExMR27oNzickIaTvZGgDS8iORETkMdaetmPaFiv05RvAt2Y72XGKnDawBEL6Tsa5S1fRtl17Xizaw7AAeojk5GS0adsOZy8mILTvZF7qhYioECVmOzFwiRkaoy/Cer0uO06x0QZHIqTP2zhxNg7tOzyA9PR02ZGokLAAeoC0tDS0bdceJ8/FI6TPZGhDysiORETkMYQQGLrMgjQLENZvClQqjexIxUoXFoXQPm/h0NHj6PhgJ2RlZcmORIWABdDNWSwWPNSlK46ePI2QPm9DFxYlOxIRkUf5ZLsVq0/Z4dN0AHQR5WTHkUIXUQEhvd/E7n378VDXrjCbzbIj0X1iAXRjDocDAwYOxPYdOxHcYyJ04d75wUREVFT2JTjw4tpcaMPLI7DFQNlxpNKXikFIz4nYvGUbevTsCZvNJjsS3QcWQDclhMAzzzyD5cuWI7jrOBhKV5UdiYjIo2RbBXovNEPR6FBiwHuy47gEQ5kaCHn4NaxduxaPP/44hBCyI9E9YgF0U1OmTMHnn3+OoAdGw1Spsew4REQe59nVFpxNdSKw23ioDCbZcVyGsVxdBD34LL777ju89dZbsuPQPfKuI1k9xPfff4/XXnsNAc0Hwq/Og7LjEBF5nIWHbfhmrw0+NdrBVKGh7Dgux7dGWzgykzBp0iSUKVMGI0eOlB2JCogF0M2sWrUKox55BL51HkRA8wGy4xAReZzzaU6M/MUMjX8ogjs9KzuOy/Jv0gf2jKt49LHHUKpUKTz4IAck3AmngN3Ijh070Kt3HxjLN0RwhyehKIrsSEREHsXuFOi/2AyLQ4WIgVOhUvHH5K0oioLgDk/CWK4+evbqjT179siORAXA72w3ceLECTzYqTNUIdEI7voiFJVadiQiIo/z9oZcbL/ggF/bJ3grzbugqNQI7joOCIxExwc74dy5c7Ij0V1iAXQDCQkJaN/hAZjVJgT3nACV1iA7EhGRx9l43o63N1qhK1sL/vU6y47jNlQ6A0J6TkSmQ40OD3TkLePcBAugizObzXioS1dcSctGSK83oTb6yY5ERORxUswC/RaZoTGYEN5nkuw4bkftE4iQXpNw/tIVPNSlKywWi+xIdAcsgC5MCIFHHnkU+w8eRHCP16EJCJcdiYjI4wghMOoXMxJzBIL7vAWVRic7klvSBkcipMcE7Ny1GwMHDYLT6ZQdiW6DBdCFTZ8+HT/9NBdBDz4LfYmKsuMQEXmk2XtsWHbMDp+GvWAoVUV2HLemj6yC4C4vYunSpXjzzTdlx6HbYAF0UStXrsQrr7wC/6b94FO1lew4REQe6UiiA8/8ZoE2tAyCWo+QHccjmCo3RWCLwXjrrbewdOlS2XHoFlgAXdDRo0fRr39/mCo1RmDLQbLjEBF5JItdoM9CM5wqDcJ5q7dC5d+0L3yqNMfgIUNw+PBh2XHoJlgAXUxKSgo6d+kKhykUwZ2fh6Lwr4iIqCi8uMaCY0lOBDz0EjSmANlxPIqiKAjuNBbCNxxdunZDamqq7Ej0H2wXLsRut6NPn764mJCI4B6vQ6XnvSeJiIrCr8dtmLnTBkNMC/jENJcdxyOpdEYEPfwaLl5JQt9+/eBwOGRHon9hAXQhL774ItatX4/gbq9AG1hCdhwiIo90KdOJocss0PgGIqTrONlxPJo2sASCuo7Dn3/8iVdffVV2HPoXFkAX8c033+Djjz9GULvHYIiqJTsOEZFHcjgFBi2xIMsGhPV/j7d6KwbG6DoIbDMS06ZNw7x582THoX/wO98FbNmyBU888SR86zwI37q8+jwRUVGZvsWK9efs8Gs1ErqQ0rLjeA2/Bt3hW70NRowchb1798qOQ2ABlC4pKQm9eveBrmQlBLd/HIqiyI5EROSRtl+w47W/cqErVQX+jXrIjuNVFEVBUMenoAouja7duiMxMVF2JK/HAiiR0+nEkKFDkZyRjaAu46CotbIjERF5pHSLQJ9FFqi1BkT0myw7jldSafUI7v4qEtOy0LtPH54UIhkLoETvv/8+Vv/2G4I6Pw+Nf6jsOEREHkkIgSdXWnApw4mgXm9ApTPIjuS1NP5hCOr2Mv7e+DcmT2YRl4kFUJLNmzdj/Kuvwr9JHxjL15cdh4jIY/3vgA3zDtlgqtsFxrI1ZcfxeoYyNeDffADeeustbNiwQXYcr8UCKEFSUhL69O0HQ6kqCGw5WHYcIiKPdTLZgSdWWKAJLIHgDk/IjkP/CGjaF4YyNdCv/wAkJSXJjuOVWACL2fXj/pLSsxDU5SUoKrXsSEREHsnqEOi7yAI71IgYOFV2HPoXRaVG0EMvICUzB0OHDYMQQnYkr8MCWMw++OCDa8f9dXqOx/0RERWh1//Kxf4EB/wfHAuNX4jsOPQfGr8QBHUai99WrcKMGTNkx/E6LIDFaMuWLXhl/Hj4N+kNY4UGsuMQkWQbz9vRdV4OSn2QCeXNDCw7Zsv3uBACk9ZbUOqDTBjfyUDr77Nx+Oqdz5xcfMSGajOzoJ+cgWozs7D0aP71zj1gQ5mPMhE8NQMvrbHke+xcmhOVP81CRq57j8isOW3H9C1W6Ms3hG/1NrLj0C0YKzSEf8MeGDfuZezatUt2HK/CAlhMkpOT0btPXxhKxSCw5RDZcYjIBWRbBWpHqPBZ55uflTptsxUfbrXis84G7HzUByV8FXT4Xw4yb1POtsbb0W+RGUNqabH/CR8MqaVF30VmbL9gBwAk5TjxyK9mvN/BgN8H++CH/TasPPH/BfHJlWa8114Pf737XpP0arYTA5eYoTH5IazXa7Lj0B0Exg6FNrwcevfpi4yMDNlxvAYLYDEQQmDosGH/HPc3jsf9EREAoFMlLSa3NaBn1RuvASqEwIztVrzWUo+eVbWoEa7GDw8bkWMT+Omg7SZru2bGdis6VFBjfEs9qoRe+2+7cmrM2G4FAJxJFQjQK+hXQ4uGkWq0KafGkUQnAOCngzbo1MpN87gLpxAYusyCdAsQ1vddqFQa2ZHoDhS1FkFdx+FiwlU89thjPB6wmLAAFoPZs2dj1cqVCHzwWR73R0R35WyaQEKWwAMV/r/A6DUKYqM12HLh1tPAW+MdeKB8/tLTsYIGW+KvvaZSsAo5NoG9lx1IMQvsvOhArQg1UswCE9dZ8Fkn975G3ifbrfj9lB0+TQdCF1FOdhy6S9rAEgh8YAzmz5+Pb7/9VnYcr8ACWMTOnDmDsc89D9/aHWGq2Eh2HCJyEwlZ10blInzzT8VG+Ch5j938dQIRvvk/2iN8VUjIujaqEmRU8MPDRgxdZkaj2VkYWluLjhU1eHGNBU830uFsmhN1v8xCjc+zsOjIrUcaXdHeyw68tDYX2ogKCGwxQHYcKiCfqq3gW7sjxjz1NI4ePSo7jsfj2HgRcjgcGDJ0GJx6P4S2GSU7DhG5of8eiSfEjcsK+poeVbXo8a9p3vXn7Dh41YHPOhtQ8ZMszOtlRAlfBY2+zkarKDXCfVx/rCDbKtBnkRmKRocS/afIjkP3KKjdo0i8dASDBg/B9m1bodW67+EIrs71/1W7sY8//hhbtmxG4IPPQqU3yY5DRG6kxD+jeNdH7q67mnPjCF/+1904Qng123nDSOJ1uXaB0Sst+LKLEadSnLA7gdhoDWJC1agcosL220w3u5JnVltwNtWJoG6vQmXg5627UmkNCHxwLPbt24f33ntPdhyPxgJYRI4cOYJXxr8Kv/rdYOCth4iogMoFKijhq2DtGXveMqtDYMM5O5qVvvWJZE3LqLH2TP7StuaMHc3K3Pw1b2/MRaeKGtQrqYbDCdid/184bQ7A4QbH4y84bMO3e20wVm/HS2x5AH2pGPg37o0333oLe/fulR3HY7EAFgGbzYZBg4dAHRCOwFZDZcchIheVZRXYl+DAvoRrhe1sqhP7EhyIS3dCURSMbazDu3/nYulRGw5ddWD4MjNMWgUDa/7/tNjQpWaM/+P/r+X3bGMd1py2Y+qmXBxLcmDqplz8ccaBsY11N2z/8FUH5h+24602egBAlVAVVIqCb/ZYsfKEDceSnGhYyrWvWnAuzYlRv5ih9Q9FcKdnZcehQhLQvD90oVEYNHgIcnNzZcfxSDwGsAi8++672L9/PyIGT4dKq5cdh4hc1K5LDrT5ISfvz8+vyQWQi2G1tfj+YSPGNdfBbBcYvcqCVLNA49JqrBligt+/rtEXl+6ESvn/3+WbldHg595GvP5XLiasy0WFYBXm9zaicen8H/dCCDy2woKPOurho7u2PqNWwfcPGzBmlQW5duCzzgZE+rvuOIHdKdBvkRkWhwoRA6dCpXLdrFQwilqLwM7P4fgPY/HGG29wOrgIKIIX3ClUu3fvRuMmTeDbqDcCWw6WHYeIbiH+08F4qHQWfhnA48Xc1cR1FkzeaEXgA2PgX7eT7DhUBNK3LkDGpjnYunUrGjXilTQKE39dKkQWiwWDBg+BLiwaAc36yY5DROSxNpyzY/JGK3RRtVn+PJh/417QR1TA0GHDORVcyFgAC9GECRNw8tQpBHYaC0XNU9eJiIpCilmg/2IzNAYTwnu/ITsOFSFFpUZgp2dx8uRJvP3227LjeBQWwEKya9cufPDBB/BvPgi6sGjZcYiIPJIQAiOXm5GYA4T0mQyV5saTW8iz6MKi4de0H6a89x727NkjO47HYAEsBA6HA488+hgMEeXg36iH7DhERB7ry902LD9uh0/DXtCXqiw7DhWTgCZ9oA+LwtBhw2G1WmXH8QgsgIVg5syZ2L9/HwI6jIGicu1LJhARuavDVx14drUF2tCyCGo9XHYcKkaKWoPAB5/FkSNH8NFHH8mO4xFYAO/TxYsX8eprr8GvzoPQl4qRHYeIyCOZbQJ9F5khVFqED+AlQbyRLqICfOt1waQ330JcXJzsOG6PBfA+PfPss7BBi8BWw2RHISLyWC+uteBYkhMBXV6CxuQvOw5JEthiEJxaE555lhf9vl8sgPdh1apVWLJ4MfzbjILK4Cs7DhGRR/rluA2f77TBENMSPpWbyY5DEqn0Jvi3HoXly5Zh5cqVsuO4NRbAe5STk4MnnhwNU7m6MFWNlR2HiMgjXcxwYuhSCzS+QQjp+pLsOOQCTFVawFSuLkaPeQpms1l2HLfFAniPJk+ejIuXLiOw/RNQFOXOLyAiogJxOAUGLrEg264gbMB7vNUbAQAURUFg+ydw4eJF3iLuPvBf0z04fPgwpk2fDr8mfaANjpQdh4jII03dbMXG83b4tRoBHT9r6V+0wZHwa9gTU6a8h5MnT8qO45ZYAAvI6XTi0ccehzawBAIa95Ydh4jII227YMeEdbnQRVbj9VXppvyb9oHKNxijx4yBEEJ2HLfDAlhAP/zwA7Zu2Qz/9k9C0fB2b0REhS3dItB3kQVqnQERfd+SHYdclEprgH/bx/DH2rVYvHix7DhuhwWwADIzMzHu5VfgUy0WxqjasuMQEXkcIQSeWGnBpQwngnq+AZXOIDsSuTBTxUbwqdwETz/zLDIzM2XHcSssgAUwZcoUpKanIzB2uOwoREQe6cf9Nvx8yAZT3S4wlq0pOw65gcC2jyExORlvvcXR4oJgAbxL586dw/sffAjfBj2g8Q+THYeIyOOcSHbgyZUWaIJKIrjDE7LjkJvQBITDt1FvzJjxMc6ePSs7jttgAbxL48aNg2Lwg3/jXrKjEBF5HKvj2nF/dqgRMXCq7DjkZvwb9YDKFIDx48fLjuI2WADvwqZNm7Bw4UL4tRwClc4oOw4Rkcd59c9cHEhwwP/BsdD4BsuOQ25GpTXAt9lAzJ8/Hzt37pQdxy2wAN6B0+nEs2Ofg7FUJfhUbyM7DhGRx/n9lB0fbLXCUKERfPk5S/fIt2Y7GMKj8fwLL/KyMHeBBfAOFixYgD27d8E/diQUhbuLiKgwXclyYtBSM7QmP4T2fFV2HHJjikoN/1bDsOnvjbxP8F1go7mN3NxcjHtlPHwqNYaBZ6MRERUqpxAYusyCdAsQ2n8KVCqN7Ejk5gzlG8AUXRsvvPgS7Ha77DgujQXwNj7//HNciI9HQKvhsqMQEXmcj7dZsea0HT7NB0EXFi07DnkARVHgHzsCJ44fw3fffSc7jktjAbyF1NRUTHrzLfjU6gBtaBnZcYiIPMqeyw6M+yMX2ogKCGzWX3Yc8iD6EhXhW601Xnt9ArKysmTHcVksgLfw3nvvIceSi8Dmg2RHISLyKFlWgb4LzVA0OpToP0V2HPJAAa2GIDklBR9++KHsKC6LBfAmrly5go8/+RQ+9bpB7RskOw4RkUd55jcLzqU5EdT9dagMJtlxyANpAiLgW7cL3ps6DVeuXJEdxyWxAN7EtGnT4IAKfo16yI5CRORR5h+y4bt9NhhqdoCxfD3ZcciD+TfrBztUmDRpkuwoLokF8D8SEhIw8/NZ10b/DL6y4xAReYyzqU6M+sUMrX8Ygjs+LTsOeTi1wRc+DXvi66+/QXx8vOw4LocF8D+mTZsGp6KGX8PusqMQEXkMu1Og/2Izcp0qhA+aBpWKP36o6PnVfQiKzoipU3l7wf/iv8B/uXz5MmZ+Pgumel05+kdEVIjeXJ+LnRcd8G//JDT+YbLjkJdQ6U3wqd8dX301GxcvXpQdx6WwAP7L1KlT4VRp4N+Ao39ERIVl/Tk73vnbCn1UHfjV6SQ7DnkZv/pdAI0O06dPlx3FpbAA/uPSpUv4fNYX8KnXDSqO/hERFYrkHCf6LzZDY/BBWO+JsuOQF1LpfWCq1w2zvvgSCQkJsuO4DBbAf0ydOhVQa+HPY/+IiAqFEAIjf7EgKQcI6TsZKo1OdiTyUn4NusGpqPH+++/LjuIyWAABXLx4EbO++BKm+t2h0vvIjkNE5BG+2GXDL8ft8GnUG/qSlWTHIS+mNvjCp15XfDbzc1y9elV2HJfAAohrd/2AWgv/Bt1kRyEi8giHrjow9ncLtKFlERQ7THYcIvg16A6HUPDBBx/IjuISvL4AXrx4EV9++RVMDR7m6B8RUSEw2wT6LDRDqLQIH/Ce7DhEAAC10Q+mug/h088+Q1JSkuw40nl9Afzkk08g1Fr41+8qOwoRkUd4YY0FJ5KdCOjyEjQmf9lxiPL4N3wYNofARx99JDuKdF5dADMzM/H5F1/AVPMBjv4RERWCZcdsmLXLBkOVVvCp3Ex2HKJ81KYAmGp3woxPPkFKSorsOFJ5dQH89ttvkZ2VDb8GHP0jIrpfFzKcGL7MAq1vEEK6vCg7DtFN+TfqAYslF7Nnz5YdRSqvLYAOhwMffPgRTFVaQOMfLjsOEZFbczgFBi2xINuuIHTAe7zVG7kstU8QTFVjMeOTT2Gz2WTHkcZr/4UuXboU8XHn4dewh+woRERu771NVmw8b4df7EjogiNlxyG6Lb8G3ZFw6SIWL14sO4o0XlsAp01/H6aomtCXqCg7ChGRW9sab8fE9bnQR1aDf8OHZcchuiNdeDmYomvjgw+992QQryyAW7Zswc4d2+HT4GHZUYiI3Fq6RaDvIgvUOgPC+0+WHYforvnU74ZdO3dg27ZtsqNI4ZUF8P0PPoAhtAyMFRrKjkJE5LaEEHh8hQWXM50I7vUmb/VGbsVYoSEMIZH48MMPZUeRwusK4JkzZ7B82TKY6neDonjd2yciKjQ/7Ldh/mEbTPW6wlCmuuw4RAWiKCoY63bB4iVLEBcXJztOsfO6BjRjxgyojX7wqd5WdhQiIrd1ItmBJ1daoA0qheD2j8uOQ3RPfGu2h0pnxGeffSY7SrHzqgKYmpqKr7/5BqbanaHS6mXHISJyS7l2gT4LLXBAjfBB02THIbpnKp0RppoP4Isvv0JWVpbsOMXKqwrgd999h1yrDX71OsuOQkTktl79MxcHrzjg/+BYaHwCZcchui9+9bogKzMTP/74o+woxcprCqAQArO+/ArGSk2h9gmSHYeIyC2tPmXHh9usMFRsDN/qbWTHIbpvmoBwmGKa4f0PP4LT6ZQdp9h4TQHctGkTTp04Dp/aHWVHISJyS1eynBi8xAyNyQ+hPcbLjkNUaHzrd8fZ06ewdu1a2VGKjdcUwK++mg1DSCQMZWvKjkJE5HacQmDIUgvSc4Gw/lOgUmlkRyIqNPrIKjCER+Prr7+WHaXYeEUBTElJwfwFC2Co0YGXfiEiugcztlmx9owdPi2GQBcWLTsOUaFSFAXGGu2xbNlyJCUlyY5TLLyiDc2ZMwd2hx2+NdvJjkJE5HZ2X3Lg5T9yoYuoiMCmfWXHISoSPtXbwCkE5syZIztKsfD4Anj95A9TxSY8+YOIqICyrAJ9F5mhaPSIGPiu7DhERUZtCoCxUmN8OftrCCFkxylyHl8At23bhmNHDvPkDyKie/DUKgvOpzkR9PBrUOlMsuMQFSmfmg/g2JHD2LFjh+woRc7jC+BXX30FfVAJGKLryI5CRORW5h204Yf9NhhqPgBjuXqy4xAVOUN0HegDw/HNN9/IjlLkPLoApqenY97P82HkyR9ERAVyNtWJR381QxsQhuCOT8mOQ1QsFJUahmrtMHfePGRnZ8uOU6Q8uhXNnTsXVqsVPjXby45CROQ2bA6BfovNsAo1wgdOg0rl0T8qiPLxrdUeOdnZWLhwoewoRcqj/1V/8eVXMFVsCI1fiOwoRERu480Nudh10QG/dqOh8Q+THYeoWGkCImCKroOvZnv2NQE9tgAePnwYBw/sh6k6L/1CRHS31p21492/rdBH14VfHZ48R97JVLMDtm7ZjOPHj8uOUmQ8tgD+/PPP0Bp9YSzfQHYUIiK3kJTjRP/FZmiMPgjrNUF2HCJpTJWaQmvyx7fffis7SpHxyAIohMCcn+ZBX7EJFI1WdhwiIpcnhMCI5RakmIGQPpOh0uhkRyKSRtFoYajSEv+b+xOcTqfsOEXCIwvg7t27ce7MaZiqxsqOQkTkFmbtsmHFCTtMjfpAX7KS7DhE0pmqtMTlixewbds22VGKhEcWwHnz5kHnGwRDVC3ZUYiIXN7BKw6MXW2BNiwKQbFDZcchcgn60tWg8w/BggULZEcpEh5XAJ1OJ+bO+xn6ys2gqNSy4xARuTSz7dqt3qDWIrz/FNlxiFyGoqigr9QM8+Yv8MhpYI8rgJs2bcKVy5c4/UtEdBeeX2PBiWQnArq+Ao3JX3YcIpdiqtIKVxMuY/PmzbKjFDqPK4Dz5s2DPjAC+sgqsqMQEbm0pUdt+GKXDYYqreBTqbHsOEQuRx8ZA31AmEdOA3tUAbTZbJi/YCH0lZvz1m9ERLcRn+7E8OVmaHyDENLlRdlxiFySoqigq9QMPy9YCIfDITtOofKolvTnn38iNSUZPtU4/UtEdCsOp8CgJWbk2FW81RvRHfhUbYWkq1fw999/y45SqDzqX/3PP/8MQ2gZaMPLy45CROSypmyyYlOcA36tR0EbVFJ2HCKXpitZGfrACI+bBvaYAmi1WrFoyRLoY1pAURTZcYiIXNKWeDveWJ8LXenq8G/QXXYcIpenKAr0lZtj/oKFsNvtsuMUGo8pgBs3bkR2ZiZMlZvJjkJE5JLSLNcu+aLWGRHe723ZcYjchqlKS6QkJ2HDhg2yoxQajymAK1asgD4wHNqwaNlRiIhcjhACj6+wICFLILjXJN7qjagAdCUqwhBc0qOmgT2iAAohsHT5L9CWa8DpXyKim/hunw0LDttgqtsNhjLVZcchciuKokBboTGW/fIrhBCy4xQKjyiAx44dQ9y5szBVaCg7ChGRyzme5MCYVRZog0ohuP1jsuMQuSVj+Qa4mnAZBw4ckB2lUHhEAVyxYgXUOj30ZXnvXyKif8u1C/RZaIEDGoQPmiY7DpHbMpSuDo3ehN9++012lELhEQVw+S+/Qh9VGyqtXnYUIiKXMv7PXBxOdCCg03PQ+ATKjkPkthSNFrqytfDripWyoxQKty+AKSkp2Lp1CwzlG8mOQkTkUn47acNH26zQV2zCC+QTFQJD+QbYtm0rUlNTZUe5b25fAFevXg2nwwFjhQayoxARuYyELCcGL7VAY/JH6MOvyo5D5BGM5evD6XBg7dq1sqPcN7cvgL/+ugLGkhWh8QuVHYWIyCU4hcCQpRZk5AJh/afwVm9EhUTjHwZjRDmsWrVKdpT75tafCna7HStXrYKuHM/+JSK67sOtVvxxxg6fFkOgC4uSHYfIo2ij6+PXlavgdDplR7kvbl0At2zZgsyMdBgrsgASEQHArksOjP8zF7oSlRDYtK/sOEQex1ihAVKSErFnzx7ZUe6LWxfAVatWQecXDF2JirKjEBFJl5kr0GehGYpGj4gB78iOQ+SR9KWqQGv0dftpYLcugGv//AvaMjWhKG79NoiICsVTv1kQl+5E0MOvQaUzyY5D5JEUtQa6qDpufzkYt21OGRkZ2Ld3D/RlasqOQkQk3U8Hbfhxvw2mWh1hLFdPdhwij2Yo3wC7d+1EYmKi7Cj3zG0L4ObNm+F0OGAoywJIRN7tTKoTj/5qhsY/HEEPjJEdh8jjGaJqQwiBjRs3yo5yz9y2AK5fvx76gFBogkrJjkJEJI3NIdBvkRlWpxoRg6bxki9ExUDjHwZDSCmsX79edpR75rafFH/8tQ6ayOpQFEV2FCIiad5Yn4vdlxzw7zAGGn9eD5WouGgia+CPv9bJjnHP3LIA8vg/IiLgr7N2vLfJCn25evCr/YDsOEReRV+2Jo4dOYykpCTZUe6JWxbATZs28fg/IvJqSTlODFhshsbog7DeE2XHIfI6hjI1AMBtjwN0ywLI4/+IyJsJITB8mQUpZiCk7ztQqTSyIxF5nevHAa5b557TwG5ZAP/k8X9E5MU+32nDypN2mBr3hZ4XwieSRl2qGtZv/Ft2jHvidgWQx/8RkTc7cMWB5363QBsWhaBWQ2THIfJqhtLVcOTQQWRkZMiOUmBuVwA3bdoEp9PJ4/+IyOvk2AT6LjQDai1KDJwqOw6R19NHVoPT6cS2bdtkRykwtyuAGzZsgN4/hMf/EZHXee53C06mOBHQ9RWoDL6y4xB5PU1wJHS+Adi0aZPsKAXmdgVw244dUJeM4fF/RORVlhy14avdNhiqtoZPpcay4xARAEVRoC1VDRv+dr/jAN2qADqdTuzevRu6CB70TETeIz7diRHLzdD4BiPkoedlxyGif9FFVsX2bdths9lkRykQtyqAp06dQnZmJnQlKsmOQkRULBxOgYFLzMixqxA+cCpv9UbkYnSlYpBrMePIkSOyoxSIW32S7Nq1CwCgK8kCSETe4d2/rdgc54Bfm0egDSopOw4R/YcurBygKNizZ4/sKAXiVgVw586dMIaUgpoHPxORF9gcZ8cb63OhK10D/vW7yY5DRDeh0ptgDC3NAliUtu/YCSW8guwYRERFLs0i0HeRGRq9EeH93pIdh4huQwktj527dsuOUSBuUwAdDgf27t0LXQSnf4nIswkh8OivFlzJFgju/SZUGp3sSER0G7qICjhwYD8cDofsKHfNbQrgsWPHYDHnQF+SZwATkWf7dq8Ni47YYKr3MAylq8mOQ0R3oCtRAeacHJw8eVJ2lLvmNgVw165dgKLwEjBE5NGOJTnw1G8WaIMjEdzuEdlxiOgu6CKuHZ7mTscBulUBNIaWgUpvkh2FiKhI5NoF+i60wAENwnmrNyK3oTb4whBckgWwKGzfsRMqngBCRB7slT9ycTjRgYBOz0PjEyg7DhEVgCqsHHbudp8TQdyiANrtduzfv5/Tv0TksVadtGHGdiv0FZvCp1or2XGIqIB0ERWxZ/ceCCFkR7krblEAT506BWuuBbqIcrKjEBEVusuZTgxZaoHWJwChD4+XHYeI7oEuogKyMjNw9uxZ2VHuilsUwMOHDwMAtKFRkpMQERUupxAYstSCDCsQOuA93uqNyE3pIsoDcJ8TQdzik+bIkSPQ+QZCbQqQHYWIqFB9sMWKP8/a4dt8KHQhZWTHIaJ7pPYJgt4/GAcPHpQd5a64RQE8fPgwNMH8YCQiz7LzogPj/8yFrmRlBDTtIzsOEd0ndVAkTpw4ITvGXXGLAnjg4GGo+JsxEXmQzFyBPovMUGn1iOg/WXYcIioEqsBSOHL0uOwYd8XlC6DdbsepkyegZQEkIg8yZpUFF9KdCOoxASodr29K5Ak0QZE4deqEW5wJ7PIF8OzZs7DZrCyAROQx5h6w4X8HbDDWehDG6Dqy4xBRIdGGRCInOxuXL1+WHeWOXL4AXp9L1wZHSk5CRHT/zqQ68dgKM7QBEQh58CnZcYioEGmDrnUVdzgO0C0KoFpngNovRHYUIqL7YnMI9F1khlWoeas3Ig+kCYyAolLj+HHXPw7Q5Qvg8ePHoQ+OhKK4fFQiotuauC4Xey454N/hKWj8Q2XHIaJCpqi1MASX4AhgYTh6/DgQWEp2DCKi+/LnGTumbrZCX64+/Gp1kB2HiIqIEliKI4CF4djR49AGsQASkftKzHZiwBIzNEZfhPWeIDsOERUhdWApHHaDS8G4dAE0m824euUyNCyAROSmhBAYvtyCVDMQ0ncyVCqN7EhEVIS0wZGIO38WNptNdpTbcukCeOHCBQCAmsfKEJGb+myHDatO2mFq0g/6EhVlxyGiIqYJjoTT4cDZs2dlR7kttyiAGj8WQCJyPweuOPDCGgu0YeUQ1HKw7DhEVAyuXwrm5MmTkpPcnksXwPj4eACAmgWQiNxMjk2gz0IzoNaixMApsuMQUTFR+wZBUVS4ePGi7Ci35fIFUOcbCJVWLzsKEVGBjF1twakUJwK7jYfK4Cs7DhEVE0Wlhs4/mAXwfsTHx3P6l4jczuIjNszeY4OhahuYKjaSHYeIipnalwXwvsTFxQE+vAMIEbmPuHQnRiw3Q+MXjJCHnpMdh4gkEKbgvPMYXJVLF8Cz5+N5BjARuQ2HU2DAYjPMDhXCB06DSuXSH7FEVETUviE4H88RwHt28UI81H5hsmMQEd2Vd/62Ymu8A35tH4M2sITsOEQkicYvBJcvX5Id47ZctgBmZWUhMyMdaj9OAROR69sUZ8ek9bnQlakB/3pdZMchIonUvsFIT02BxWKRHeWWXLYAXr8EjMafI4BE5NpSzQL9Fpmh0RsR3vct2XGISDK177XBq0uXXHcU0OULIK8BSESuTAiBR34140q2QHCft6DS6GRHIiLJrs9euvKZwC5bAK/vNA2ngInIhX2z14YlR+0w1X8YhsiqsuMQkQu43l04AngPkpOToTH4QFFrZUchIrqpo4kOPLXKAk1wJILbPiI7DhG5CEVnglpn4AjgvUhJSYHG5Cc7BhHRTVnsAn0XmeFUaRAxaJrsOETkQhRFgc4/lAXwXqSmpkKl5+2TiMg1vfJHLo4kOhHQ+QVoTAGy4xCRi1GMfkhOTpYd45ZctgCmpKQALIBE5IJWnrDh4+1W6Cs1g0+VlrLjEJEr0vogPT1ddopbctkCmJySAuh9ZMcgIsrncqYTQ5ZaoPEJQGj3V2THISJXpTchJTVNdopbctkCmJSUApWBxwASketwCoHBSy3ItAFhA97jrd6I6JZUeh8WwHuRkpoClYFTwETkOt7fYsVfZ+3wbTkcupAysuMQkQtT6X2Qnp4mO8YtuWwBTEtNhcrIAkhErmHHRQde/TMXupIxCGjcS3YcInJxKr0JGTwGsGAcDgeyMjN4FjARuYTM3GuXfFFp9Yjo/47sOETkBlQGX2RmZkAIITvKTblkAUxPT4cQAiojjwEkIvlGr7LgQroTQT0nQqUzyI5DRG5ApTfB6XAgOztbdpSbcskCmJqaCgBQ8yQQIpJszgEr5hywwVi7E4xRtWXHISI3ofrnSiaueikYlyyAKSkpAMCTQIhIqtMpTjy2wgJtYARCOo6RHYeI3IjCAlhw14dLFa1echIi8lZWx7Xj/uxCjfCBvNUbERWMSm8CAKSlpckNcgsuWQCtVisAQNFoJSchIm81cV0u9l52wP+Bp6HxC5Edh4jczPUTWTkCWAB5BVDNAkhExe+PM3ZM3WyFvnx9+NZsLzsOEbmh6yeMZWZmSk5ycy5dAMECSETFLDHbiYGLzdAafRHWa4LsOETkrlQaAIDdbpcc5OZcsgDm5uYCAJR/dh4RUXEQQmDYcgtSLUBIv3eh4mcQEd0jRaUGwAJYIP8/BcwPXyIqPp/usOK3k3aYmvaHPqK87DhE5M7ULIAFljcF/E97JiIqavsTHHhhTS604eUR1GKQ7DhE5OYURQUoCgtgQVitVqg0WiiKIjsKEXmBbKtAn4VmKGotSgx4T3YcIvIQKpWaBbAgrFYrVDwBhIiKydjfLTid6kRgt/FQGUyy4xCRh1DULIAFcm0EkMf/EVHRW3TEhq/32GCo1hamio1kxyEiD6JwBLBgcnNzeQ1AIipyFzKcGLncDI1fCEI6j5Udh4g8jCsXQJccZrNarSyARFTk9iY4oVGrED5wKlQql/x9mIjcmCsXQJf8xLPb7VD4YUxERUwB4Nf2CWgDS8iOQkQeyJULoEuOAGo0GginU3YMIvJgEQPfg+XcXvjX6yw7ChF5KEWlhs1mkx3jplyyAGq1WginazZmIvIMupDS0IWUlh2DiDyYK48AuuQ8q1arhXC45g4jIiIiuhvCaYdW65rnNLAAEhERERUBp90GvV4vO8ZNuWwBdLIAEhERkRtjASwgjgASERGRu2MBLKDrI4BCCNlRiIiIiApMCAGn3QqDwSA7yk25ZAHU6XTX/kfwUjBERETkhv65mglHAAvg+hkznAYmIiIidyTs167/xwJYAHmnTDsdcoMQERER3QPhYAEssLwRQF4MmoiIiNwQRwDvAaeAiYiIyJ1dHwHkSSAF4OvrCwAQVrPkJEREREQFxyngexAUFAQAcOZmS05CREREdA9YAAsuMDAQAOC0ZMkNQkRERHQPnP/MYppMJslJbs4lC2DeCKCFI4BERETkfq4PYoWEhEhOcnMuWQB9fX2hUqngzOUIIBEREbkfpzkDABAcHCw5yc25ZAFUqVTw8w/gCCARERG5JYc5C75+/tBoNLKj3JRLFkAA8A8I4AggERERuSWnJQOBQa45+ge4cAEMCgrmSSBERETklpzmTISGsAAWWEhwIKeAiYiIyC05zZkIDXXNE0AAFy6AwUFBgJUFkIiIiNxQbhbCQkNlp7glly2AQSyARERE5K5ys1z2DGDAhQtgYGAgBKeAiYiIyA05zZkuew1AwIULYEhICOw56bJjEBERERWYzZzBEcB7Ubp0adhyMuG0WWRHISIiIrprTlsuHNZcjgDei8jISACAIzNZchIiIiKiu+c0ZwJw3buAAC5cAEuXLg2ABZCIiIjciyPrWne5Ppjlily2AF7fafbMJMlJiIiIiO7e9e5SpkwZyUluzWULoMlkQkBgEBwsgERERORGHJlJ0BuM1y5p56JctgACQKnI0rBzCpiIiIjciCMzGSVLlYKiKLKj3JJLF8DosqXhzGIBJCIiIvdhz0hE2bKuO/0LuHgBLF26NJDNAkhERERuJDsFZf85mdVVuXwB5FnARERE5E6cmVcRFRUlO8ZtuXwBzM1MgXDYZEchIiIiuiPhsMGSnoTo6GjZUW7L5QsgADiyUiQnISIiIroze0YSIAQL4P24XgDtGYmSkxARERHdmT3jKgCwAN6PcuXKQVEU2FIuyY5CREREdEeO9CtQFMWlLwINuHgBNBqNiCxdFvaUC7KjEBEREd2RPf0qwiJKQq/Xy45yWy5dAAGgWrUqsKdelB2DiIiI6I5sKRdRqWIF2THuyOULYNUqVSBYAImIiMgdpF1AzRrVZae4I5cvgDExMbCkXoZw2GVHISIiIrol4XTAknQR1apVkx3ljly+AFapUgXC4YA9LUF2FCIiIqJbsqclwGm3omrVqrKj3JHLF8CYmBgAgI0nghAREZELsyVf6yocASwEJUuWhMnHhwWQiIiIXJotOQ4+fn4oWbKk7Ch35PIFUFEUVK5cJa9VExEREbkiW1IcqlWtBkVRZEe5I5cvgABQvVoViDReDJqIiIhcl0i7iBrVXX/6F3CTAhgTEwN7Ci8FQ0RERK5JCCesSfFucfwf4CYFsEqVKrBmp8ORky47ChEREdENHJlJsOea3eIMYMBNCmD16tcuqGhLPC85CREREdGNbEnxANzjDGDATQpgTEwM9AYjrFdOy45CREREdANbcjz0BiOioqJkR7krblEA1Wo1atasyQJIRERELsl69RxiqlSBSuUW1co9CiAANKhfD86ks7JjEBEREd3AefUUmjZuJDvGXXObAli3bl1YEuPhtFlkRyEiIiLK48zNgTnxPBo2bCg7yl1zmwJYr149COHkiSBERETkUqxXTgNCoFEjjgAWuho1akCt0cCacEp2FCIiIqI8uZdPwmA0uc0lYAA3KoAGgwHVa9RE7uWTsqMQERER5bEmnETdunWh0WhkR7lrblMAAaBp40ZwXuUIIBEREbkO55WTaOJGJ4AAblYAGzZsCEtiHJxWs+woRERERHDkpMOSmuBWx/8BblgAhXDyeoBERETkEqz/HJrmTmcAA25WAKtVq3btjiCXT8iOQkRERITcyycQEBiE8uXLy45SIG5VADUaDerXrw/rpeOyoxARERHBduUkGjVqCEVRZEcpELcqgADQpnUsbBcPQwghOwoRERF5MSEE7FdOobGbHf8HuGEBjI2NhTUrDbbkeNlRiIiIyIvZ06/Ampnqdsf/AW5YAJs1awa1RoPc+EOyoxAREZEXy407AEVR0LJlS9lRCsztCqCPjw/q1auP3PiDsqMQERGRF7PEHUTN2nUQFBQkO0qBuV0BBIC2bVrDzuMAiYiISBIhBOwXDqJDu7ayo9wTtyyArVq1Qm5GCuypl2RHISIiIi9kT72E3PQktGnTRnaUe+KWBbBFixZQqVSwxHEamIiIiIqfJe4gVGq1Wx7/B7hpAfT390fN2nV4IggRERFJkRt3APXq1Ye/v7/sKPfELQsgALRrw+MAiYiIqPgJIWC7cAjt3fT4P8CNC2BsbCxy0xNhT78iOwoRERF5EXvyBVgzU9z2+D/AjQtgy5YtoSgKcnkcIBERERUjS9x+aDRaNG/eXHaUe+a2BTAoKAg1atWGJW6/7ChERETkRXLjDqJBw4bw8fGRHeWeuW0BBICuD3WG7dxeCKdDdhQiIiLyAkI4YbtwCB3at5Md5b64dQF86KGHYM1OR+6lE7KjEBERkRewXT0Ha3a6Wx//B7h5AWzcuDECg4JhPrNTdhQiIiLyAjmntsPHz8+tj/8D3LwAqtVqPNS5E2xnd8mOQkRERF7AdnYnOj/YCTqdTnaU++LWBRC4Ng1sTjgDe0aS7ChERETkweyZyci5eALdunWVHeW+uX0B7NixI1QqFcxnOApIRERERcd8eidUajU6d+4sO8p9c/sCGBwcjMZNmiKXxwESERFREco9vQNNmzZDcHCw7Cj3ze0LIAB069oFlvP7IexW2VGIiIjIAzltFljO78fD3bvJjlIoPKIAPvTQQ3BYLbDwriBERERUBCzn98Nhy0W3biyALqNGjRooGVmaxwESERFRkTCf3I7yFSuhcuXKsqMUCo8ogIqioHvXLrCd3QUhhOw4RERE5EGEcMJ6dhd6eMj0L+AhBRAAunbtCkvKZdgSz8mOQkRERB7EmnAK1swUj5n+BTyoALZv3x7+AYHIPva37ChERETkQcwnt8M/IBDNmjWTHaXQeEwB1Ol06NO7F6wnNnEamIiIiAqN9fR2dOvaBRqNRnaUQuMxBRAA+vfvD0vyJVgTTsmOQkRERB7AmngO5qvn0L9/f9lRCpVHFcDWrVsjOCQUOUc3yo5CREREHiD7yHoEBAahQ4cOsqMUKo8qgBqNBv379UXuyc0Qwik7DhEREbkxIZzIPf43+vfrC51OJztOofKoAggA/fr1Q27aVeRePCY7ChEREbmx3IvHkJt6BQMHDpQdpdB5XAFs0aIFIkqURA7PBiYiIqL7kH1kA0qUikSLFi1kRyl0HlcAVSoVBg7oj9wTmyGcDtlxiIiIyA0Jhx3Wk5sxZNBAqFQeV5c8rwAC16aBrZkpyI0/LDsKERERuSHL+f2wZqVhwIABsqMUCY8sgI0aNULpslHI5tnAREREdA+yj6xHxcoxqFOnjuwoRcIjC6CiKBg0oD9yT22FcNhlxyEiIiI34rRZkHtqO4YOHgRFUWTHKRIeWQABYNCgQbBlp8N8eofsKERERORGzKd2wp6b47HTv4AHF8CaNWuifoOGyDmwVnYUIiIiciPmYxtQv0FDVKxYUXaUIuOxBRAAHn/sUeSc2Q17RqLsKEREROQGHNmpyDm9E0OHDJYdpUh5dAHs378/DEYDsg7+ITsKERERuYGsg39Aq9FiyJAhsqMUKY8ugH5+fhjQvz8sh9bymoBERER0W0I4YTm4Bv369kVQUJDsOEXKowsgADz66KPITbsKy7l9sqMQERGRC7Oc2w9LymU8/vhjsqMUOUUIIWSHKEpCCFSrURPxzkCEdh8vOw4RERG5qKRlU1BalYqjhw957OVfrvP4EUBFUfDEY4/CfHI7HNlpsuMQERGRC3JkpcJ8ahvGPPmEx5c/wAsKIAAMHjwYapUKWYf+kh2FiIiIXFDWwbXQeMHJH9d5RQEMCQlBr169rp0M4tkz3kRERFRAQjhhPrgGA/r3Q2BgoOw4xcIrCiAAPProI7AkxSP34hHZUYiIiMiFWM7uRW5qAh5//HHZUYqNx58Ecp3T6UT5ipWQZCqL0C4vyo5DRERELiJp6Tsoq83E4YMHvOL4P8CLRgBVKhWeffop5Bz7G/bMJNlxiIiIyAXYM5ORc2qH15z8cZ3XjAACQEZGBkpGRkJToxOCYofJjkNERESSpW2eB8uuJUi4fMlrjv8DvGgEEAD8/f3x+KOPwnzgdzitFtlxiIiISCJht8K8bxWGDxvqVeUP8LICCADPPPMMHJYsZB/mJWGIiIi8WdbhdbBlp+H555+XHaXYeV0BjI6ORo8ePZCzezmEcMqOQ0RERBII4UTO7mXo2q0bKleuLDtOsfO6AggAL7zwAizJF2E+vUt2FCIiIpLAfHoXLInxGPfSS7KjSOFVJ4H8W6PGTXD4qgVh/d6RHYWIiIiKWeLP41GjhA+2b9sqO4oUXjkCCAAvvvA8cs7th/XKGdlRiIiIqBjlXj6BnPMH8fI47xz9A7x4BNButyO6XHmkB1ZCyEPed/AnERGRt0r+ZRpCLBdw+uQJqNVq2XGk8NoRQI1Gg+fGPoucoxthz0qRHYeIiIiKgT39CrKPbcK4F1/w2vIHePEIIACkp6ejVGQkNLUeQlCrobLjEBERURFL+eMrqM9swsUL8TCZTLLjSOO1I4AAEBAQgCefeAI5e1fCYcmSHYeIiIiKkMOSBfOhtXj6qTFeXf4ALx8BBIArV64gKrocDPUeRmDLQbLjEBERURFJ37oA2dvmIz7uPCIiImTHkcqrRwABICIiAqOffAI5e3+Fk6OAREREHslptSB793KMGD7M68sfwBFAAEBCQgKiosvB2KAHAltwFJCIiMjTpG9fjKxNc3Dq1ElERUXJjiOd148AAkCJEiUw+sknkL2Ho4BERESexmm1IGfXUowYMZzl7x8cAfzH5cuXEV2uPIwNeiKwxUDZcYiIiKiQpG9fgsxNP+L0qVMsgP/gCOA/SpYsiSefeBw5e37hKCAREZGHuDb6twQjhnP07984AvgveaOADXshsPkA2XGIiIjoPqVvX4zMTf/DqZMnER0dLTuOy+AI4L+ULFkSTzz+GHJ2L4czN1t2HCIiIroPztwcZO9cglEjR7L8/QdHAP/j0qVLiC5XHqbGfRDYrL/sOERERHSP0jbPQ86ORThz+hRKly4tO45L4Qjgf5QqVYqjgERERG7OYc5E9q5lGDP6SZa/m+AI4E1cvHgRFSpWgr5uV94jmIiIyA2lbvge1v2rcP7cWYSHh8uO43I4AngTkZGRePGF55G9aznsGYmy4xAREVEBOLJTkb1nBZ4b+yzL3y1wBPAWMjMzUa58BeSWqImQh56XHYeIiIjuUvLvn0E5sxXnzp5BcHCw7DguiSOAt+Dn54fJb7+FrMPrYL1yWnYcIiIiugvWxHPI3r8Gb056g+XvNjgCeBt2ux3VqtfARasBoX0nQ1EU2ZGIiIjoFoQQSFr0BsKRjuNHj0Cn08mO5LI4AngbGo0GH7w/HTnn9sNyZpfsOERERHQbljO7kHNmDz764H2WvzvgCOAdCCEQ27oNdh47h/Bhn0BRqWVHIiIiov8QDjuu/vA0GlUrj/Xr1nHW7g44AngHiqLgow8/gOXqeWQdWCs7DhEREd1E1v7VyE26gBkffcTydxdYAO9C/fr1MWjQYGRtmQtnbo7sOERERPQvTksWMrfMw7Bhw1C3bl3ZcdwCp4DvUlxcHCpWqgxTgx4IbDlYdhwiIiL6R+pf38B2+HecOnkSpUqVkh3HLXAE8C6VLVsWLzz/HLJ2LYU9M0l2HCIiIgJgS72ErD2/Yvwrr7D8FQBHAAsgPT0dFSpWQm5YVYR0Gyc7DhERkddLWvYu/DPP49TJEzCZTLLjuA2OABZAQEAAPvzgfWQd3QjzuX2y4xAREXk1S9xBZB/fgmlT32P5KyCOABaQEALNW7TE3pNx1y4Lo9bKjkREROR1hMOGqz+ORc3oEti2dQtUKo5pFQT3VgEpioIvv5gFa8olZOxcLjsOERGRV8rYsRTW5Av4evZXLH/3gHvsHtSsWRPPPvMMMrf+DHtGouw4REREXsWWegmZW+fjxRdeQK1atWTHcUucAr5HGRkZqFQ5BtkB5RDa4zXZcYiIiLyCEAJJCycixJGCo0cOw8fHR3Ykt8QRwHvk7++Pzz79BNkntiLn5DbZcYiIiLxCztENyDm7F19+MYvl7z6wAN6H3r1748FOnZDx55e8QwgREVERc5gzkbHuG/Tp0wedOnWSHcetcQr4Pp07dw5VqlaDrsYDCG73qOw4REREHit59acQZ7bg5PHjKFmypOw4bo0jgPcpOjoab705CVm7f4X1ymnZcYiIiDyS5cJhZO3/HdOnTmX5KwQcASwENpsNderWw9kUC8IGvQ9FrZEdiYiIyGNcv+ZfjagIbN+2lZd9KQTcg4VAq9Xi++++Re7Vs0jftlB2HCIiIo9y/Zp/33w9m+WvkHAvFpKGDRti/CuvIHPrz7BeOSM7DhERkUewJcfzmn9FgFPAhchqtaJe/QY4k5iNsMEfQNHwNnEklzM3B2l/z0HOya1w5qRDF14eQe0fg75kZQDXrqeVvvknZO3/HU5LFnQlKyO4w5PQhUXddr3Zxzcj/e85sKVdhjawJAJbDYGpcrO8x7MOr0Pahh8gbBb41noAQW1G5j1mT7+CK/MnoOSwGVDpee9OIro14bAj8adxiPQB9u/by/v9FiKOABYinU6HuXP+B1tyPNK2zJMdhwjJqz+F5dw+hHZ5ASVHfgZDubq48vPrsGcmAQAyti9Gxs5lCG7/BEoM/RBqnyBcXTDhtpc1yr14FEnLp8KnehuUGvEpfKq3QeLyqci9dBwA4MhJR8rqTxHUZiTC+76FrEN/Iuf0zv/P9PvnCIodzvJHRHeUvnUBcq+cxk9z57D8FTIWwEJWu3ZtvPHGRGRuW5T3A5FIBqctFznHNyOwzQgYytSANqgUAlsMgiYwApl7f4MQApm7liOgaT+YYppBFxaN0Ieeh9OWi+yjG2653oxdv8AQXRcBTftCG1IGAU37whBVGxm7rt0b256WAEVvgk/VVtCXrAxD2VqwJcUBALKPrIei1sAU0+yW6yciAoDcyyeRsXU+Jrz+Oho2bCg7jsdhASwCr7zyCurUrYu01TPgtOXKjkPeyukAhBOKOv+hCIpGh9wLh2FPvwJHdiqM5er+6zEtDGVqIPfi0VuuNvfisXyvAQBjuXp5r9EER0LYcmG9choOcyasl09AFxYNhzkTaX/PRXCHJwrxTRKRJ3LacpH224eoXbs2XnuNt1stCiyARUCj0WDO/36EI/0q0v+eIzsOeSmV3gR9qSpI3/Iz7JnJEE4Hsg6vg/XSCTiyU+HISr32PFNgvtepfQLzHrsZR3Yq1D43eU32tdeoDb4Ifeg5JK34EAk/Pg+fGm1hLF8fqeu+gV/9LrCnX8Gl757BpW9GI/vYpkJ9z0TkGdI2/ABH+lX8NHcOtFoeT18UeMG6IlKtWjW8M/ltjHv5ZRgrN4GhdHXZkcgLhXR5Acm/fYyLnw8DFBV0JSrAp1ps/ouWK0r+Fwlx47Ib5H/82rlk/7/MVLlZvpNCLHEHYEs8j+AOT+DSV48htOtLUPsE4fKPz8NQpsYNhZKIvJf5/H5k7v4FH330EapWrSo7jsfiCGARev7559G4cROk//YxnFaL7DjkhbRBJVFi4Hso89wiRI7+HiWHfgThdEATEAG1bxAAwJmdf7TPkZN+20Km9gnKG+27znmb1wi7DSlrZiG44xjYUy9DOB0wlK0JbUhpaIMjkXuZx8oS0TXO3Gykr/4YrVq3xjPPPCM7jkdjASxCarUa//vxB4icVKRt+E52HPJiKp0BGt9gOCxZMJ/dA2OlJtdKoE8QzOf25j1POGywxB+CPvLWv3XrI6vkew0AmM/uveVr0rb8DEP5+tCXqAgI57VjE69vz2kHnM77fHdE5ClS//wKGocZ//vhB17wuYhx7xaxSpUq4cMP3kfmnpXIObFVdhzyMuYzu2E+sxu2tASYz+7FlXnjoQ2OhG/N9lAUBX4NuiN960LknNgCa+I5JK2cAZVWD5+qsXnrSFrxAVI3fJ/3Z7/63WA5uxfp2xbBlhyP9G2LYDm/D/4Nut+wfWvieeQc24jAFoMBAJrg0oCiQub+Ncg5vRO25AvQlaxU5PuBiFxfzoktyDr4J2Z++inKli0rO47H4zGAxeDJJ5/E2j/+wMrVH0MXUQGagHDZkchLOHNzkLbxB9gzk6A2+MEU0wyBrYbm3a/av3EvCHsuUtbMgsOSBX2pGIT3fSvfNfrsGYmA8v+/KxpKV0Vot3FI+3sO0v6eA01gCYR1exn6UjH5ti2EQMrvnyGo7aNQ6QwAAJVWj5DOY5GydhaEw4bgDk9A4xdaDHuCiFyZPSsF6Ws/R7fu3TF06FDZcbwC7wRSTNLS0lCrdh0kOY0I6/9e3g9gIiIibyacDiQteB2+lkQcPLAf4eEcJCkOnAIuJoGBgVi4YD6sCaeQtvFH2XGIiIhcQtqmn2CJP4yFC+az/BUjFsBi1LhxY0ybOhUZO5bA/K9bYxEREXkj85ndyNg6H5MnT0arVq1kx/EqnAIuZkIIdOnaFWvXb0L40I+h8efxT0RE5H3sGUm4+uOzaNuyKVatXMmzfosZC6AEycnJqFmrNtI1QQjt9w4UlVp2JCIiomIjHHYkzX8VAY50HNi/D6GhHAwpbqzbEoSEhGDB/J9huXgU6ZvnyY5DRERUrNI2/ojcyyewaOEClj9JWAAladGiBd5+6y2kb50P87l9suMQEREVi5xTO5CxYwmmvvcemjVrducXUJHgFLBETqcTDzzQEX/v2I2woR9D4xssOxIREVGRsadfxdUfn0XHdq3xy/LlUO5433EqKiyAkl25cgW169ZDhtofYf2mQNFoZUciIiIqdMJhQ+K8VxCiMuPA/n0ICgqSHcmrcQpYsoiICPy6fBnsV88iZc1MsI8TEZEnSv3rG9iunMHiRQtZ/lwAC6ALaNiwIb75ejayDv6BzN2/yo5DRERUqDL3rUbmnhX45JOP0ahRI9lxCCyALmPIkCF44YUXkLbuG54UQkREHsMSdxBpf8zCk08+iSeffFJ2HPoHjwF0IXa7HZ06d8aGzdsRNuRDaANLyI5ERER0z2xpCUic8wKaN6yHNWt+h1bL49xdBQugi0lNTUW9Bg2RkOVA2MBpUOlNsiMREREVmDM3B4k/jUMJHxV279qJ4GBe6cKVcArYxQQFBWHlr79AnZOElFUzIIRTdiQiIqICEU4HUla8D7U5GatWrmD5c0EsgC6oWrVqmPfTT8g5uZV3CiEiIreTtvF/MJ/ZhYXz56Nq1aqy49BNsAC6qK5du+Ltt99G+uZ5yDm+RXYcIiKiu5J16C9kbF+E6dOno1OnTrLj0C3wGEAXJoRAn759sfzXlQjt9y70JSvJjkRERHRLuReP4erP4zF08CB8++23vNOHC2MBdHHZ2dmIbd0GB4+dQuig6TwzmIiIXJI9IxGJc55H3epVsGH9Ouj1etmR6DZYAN1AYmIiGjdpisvpFoQOnAa1KUB2JCIiojwOSxaS5r2CEJ0Du3ftREREhOxIdAc8BtANhIWFYe2a3+GjWJG85G04bRbZkYiIiAAATlsuUpZOht6ajrVrfmf5cxMsgG6iQoUKWP3bKiA1Him/TodwOmRHIiIiL3f9ci+Oq6fx26qVPOPXjbAAupEGDRpg8aKFMJ/ZhZS1s8DZeyIikkUIgZS1s2A+vQOLFi5A06ZNZUeiAmABdDOdOnXC17NnI2vfaqRvnS87DhERean0TT8ha99qfD17Nrp06SI7DhWQRnYAKrgRI0bg4sWLmDBhAjS+IfCt1UF2JCIi8iKZe1chfcs8TJkyBSNGjJAdh+4BC6Cbeu211xAXF4evv/kMap8gGCs0kB2JiIi8QPaxTUhZOwvPPPMMXn75Zdlx6B7xMjBuzG634+EePbB6zR8I6/cO9KViZEciIiIPZok7gMSFb6B3zx6YN28eVCoeSeauWADdXE5ODtq174Bd+w4gtO9k6EtUlB2JiIg8kPXqGSTOG4+WTRvjt99W8ULPbo4F0ANkZGSgbbv2OHDkOEL7TYYuvLzsSERE5EFsyfFImv8qqlaIxsYN6+Hv7y87Et0nFkAPkZqaitZt2uLY6XMI6fcudKFlZUciIiIPYEu5iKT5r6JcqXBs3LAe4eHhsiNRIWAB9CDJycloFdsap+IuIbT/FGiDI2VHIiIiN2ZLvYSkn19FdMlQbNywnnf58CAsgB7m6tWraNkqFucSkvB/7d17XFRl4gbwZ4a5ch1QbiqKiCKkhnhJwcoMyzXNu5Y3sPLX1npL12ulm4Xmriap5ZrX1VpvCaaWYl5QBK+roJaCmqAiKMh1GJjr+/uDZJfVSjf0APN8P5/5zMyZOYcHSng+77zvOQ1f+RhKnY/UkYiIqA4yF+bgzuZZ8PNyR9LhQ/Dx4d+T+oQFsB7KyclBt6efQXZBKRoOmw+FG4friYjowZmLcnFn8yw0buCKpMOH0KhRI6kjUQ1jAaynbty4gYhuT+NWqRENX5kPhUtDqSMREVEdYCm+hfzNs+Dr7owjhw+hcWNOJ6qPWADrsczMTER0exoFRqDhsPlwcHaXOhIREdVilpLbyN80Cz5uWhxJOowmTZpIHYkeEZ7BsR7z9/fHocSDcFNYkb/1PVj0BVJHIiKiWspSkof8ze/Cy1WDw4cSWf7qORbAei4wMBCHEg9C52DGnY0zYCm+JXUkIiKqZSyl+biz5T14OimRdCgRTZvyVGL1HQugHQgKCsLRlGR4u2mQt3E6zHeuSx2JiIhqCXNRLvI3zYSHRobDhxLRrFkzqSPRY8ACaCf8/f1xNPkIAhp5IW/jDBhzL0sdiYiIJGbOv447m2bA102L5CNJaN68udSR6DFhAbQjvr6+OJJ0GG1bt0T+5ndRceNHqSMREZFEjLmXkbdpBgIaeyMl+Qj8/f2ljkSPEQugnWnQoAEOHtiPLp06IH/rbJRfPS11JCIieswqrp9H/uZ30S64FY4kHYavr6/UkegxYwG0Q66urtibsAcvRPZAftyHMKSnSB2JiIgeE8OVk8j/eg7Cu3TCwQP74eHhIXUkkgALoJ3SarXYHh+PwQMHIP+bj6E/t1/qSERE9Ijpz+9HftxH6N3rRSTs3g0XFxepI5FEFFIHIOmoVCr885//hIuLC1avXgybyQDXDn2ljkVERI9AyYk4FB5cg9deew0rVqyAQsEKYM/4X9/OOTg4YOXKldDpdFi0aBGspXege3Y0ZDIODhMR1QdCCBQlrkXJiTjMnDkTMTExkMlkUsciifFScASg8hdEbGwspkyZAsegcHj0ngy5Ui11LCIi+h2E1YyCPcugP78fsbGxmDhxotSRqJZgAaRqtm/fjldeHQ55w2Zo0P89ODjppI5ERET/A2t5CQq+mQ/zzXSsW7cWw4cPlzoS1SIsgHSPkydPovdLfVBqcUCDQbOhbOAndSQiInoI5oJsFMTNhcZWjp07vkG3bt2kjkS1DCd60T06deqEkyeOw99bh7yvpqLi2lmpIxER0QOqyDqLvK/+DL8Gzjh18gTLH90XCyDdl7+/P44dTcHTXZ9C3pbZ0J/naWKIiGo7/dm9yNv6Pp7u0hknjh9DixYtpI5EtRQLIP0inU6HPXt2IzpqNO58uxhFSV+BMwaIiGofIWwoTFyLO7uX4I3XX8eePbuh0+mkjkW1GE8DQ79KqVRi1apVCAwMxKxZs2AtzoFHr4mQKZRSRyMiIgA2UwUKvl0Ew6Vj+OSTTzBp0iSe5oV+ExeB0APbvHkzRo2OgsIrAB79ZkLhzMsHERFJyVKaj4L4j4DiHGzetBF9+/Jk/vRgWADpoRw/fhz9+g9AocEEj5dnQN04WOpIRER2yZiTgYLt89DAWY3vvt2F0NBQqSNRHcICSA8tNzcXAwYOwokTJ6CL/CNcQntJHYmIyG4IIaBP3Y2iAyvRPjQUO3d8A19fX6ljUR3DRSD00Hx8fHAo8SDe/L+xKEhYhjsJyyAsZqljERHVezZzBQq+i0XB3s/x5tg3kHwkieWP/iccAaTfZc2aNfjjH9+qnBf48nQoXD2ljkREVC+ZC7JRuONj2IpzsWrlFxg5cqTUkagOYwGk3+3UqVMYMHAQbhUUw73PVGj9Q6WORERUrxgyjqJwdyyaNvbF9vg4tG3bVupIVMexAFKNuHPnDl4dPhzff/89dN1GwrXrEMhknGFARPR7CJsVRYfXo+T4NvQfMAD/WLcOrq6uUseieoAFkGqM1WrFhx9+iLlz50LboiM8ek+Gg9ZF6lhERHWSVV+Igl1/Q8WNH/DXBQswefJknt+PagwLINW43bt349XhI1AuHODeezI0TdtJHYmIqE6puPEDCnf+FW4aBb7eugXPPPOM1JGonmEBpEfixo0bGDFyJA4fPgzXpwZD120EZA688AwR0a8RNitKjn2NkpR/okuXrvh66xau8qVHgpO06JFo0qQJDuzfj/nz5qHsVDzyNk6HufCm1LGIiGotc1Eu8jfNREnyV5g5YwYSDx5g+aNHhiOA9MidPHkSQ195FTeyc+D2/JtwatOD81iIiH4mhEDZDwdQvH8FfL088c+vvkS3bt2kjkX1HAsgPRalpaUYP34C/vGPdXAOfgbuL7wNucZZ6lhERJKyVuhRuPczlF1IwqhRo7F06RK4ublJHYvsAAsgPVabNm3C2P97E2aFFrreU6BpEiJ1JCIiSZRnpaF4dyxUwoRVK7/A0KFDpY5EdoQFkB67zMxMvDp8BI4fOwbX8GFwC38FMrmD1LGIiB4LYTGjKGkDSk7G45lnn8WX69fDz89P6lhkZ1gASRIWiwUxMTGYO3cu1D6B0PWaAJWnv9SxiIgeKVNeFoq+WwRz/nXMnz8PkydPhlzO9Zj0+LEAkqSOHz+OqOgxuHTpEly6DIFb16GQOSiljkVEVKOEzYqSk9+gNPkrtAhojs2bNiI0NFTqWGTHWABJckajETExMZg3fz6UHk2g6zUBat9WUsciIqoRpltXUJSwFMZbP2HixImIiYmBVquVOhbZORZAqjXS0tIQFT0GZ9PS4NKpP9y6jYBcqZY6FhHR/8RmNqI4eSNKT8YjODgYa9esRufOnaWORQSABZBqGYvFgkWLFuH92XPg4NIQbi+Oh8avjdSxiIgeSkXWWRR//xmspfn4y5zZmDp1KpRKTm+h2oMFkGql9PR0RI95DceOpsAl7CXonomCXO0odSwiol9lrdCjKHEN9Gl7ER7RDWtWr0JQUJDUsYjuwQJItZbNZsNnn32G6TNmwqZyglvk29C26Ch1LCKi+ypLT0bJ/hVQwoxFf/sbxo4dyxW+VGuxAFKtl5mZiddffwMHDuyHU6uucHvudSh1PlLHIiICAFhK76Bo3wqUZaSg78svY/nnn6Nx48ZSxyL6VSyAVCcIIbBlyxZMemcy8vLvwLnzQLg+NZiLRIhIMsJiRsmpb6A/tgXubi5Y/vlnGDhwIK91TnUCCyDVKXq9HjExMVi4cBEcXBrAtftr0Lbsyl+4RPTYCCFQfuUEShPXwFSUi/HjxmHOnDlwd3eXOhrRA2MBpDopIyMDEyZORMKePXAMCIOux1goG/BSSkT0aJnzr6Po4EoYfjqN5yMjseTTTxESwmuaU93DAkh1lhACu3btwrgJE3Hj+jU4d+gHt/BXuFqYiGqcrUKPouSNKDuzC35+TfFp7GK8/PLL/PSB6iwWQKrzKioqsHDhQnwUMw9C5QiXZ6LhFNKdv5iJ6HcTNiv0Z79H6ZENUAgLZr//Ht555x2o1Zx/THUbCyDVG1lZWZg8ZQritm2DtnFruD4zGpqm7aSORUR1VMX18yg5sBLluVcwcuQoLFjwMRo1aiR1LKIawQJI9c6BAwfw56nTcOb0v+AY0AFuz4yGyruF1LGIqI4w5V9DyZEvUZaegrAOHfHZsqXo0qWL1LGIahQLINVLQghs27YNM2bOwpXLl+AU8izcuo2E0t1X6mhEVEuZi3JRkrwRZT8cROMmTfDRh3MxatQonsyZ6iUWQKrXzGYz1q5di9lz/oK8vNtwbNcLuvBX4ODM0zUQUSWLvgDFKZthOJsADw8P/GXObLzxxhuc50f1Ggsg2QWDwYClS5ciZt58GCqMcOrQD25PDYRc7SR1NCKSiLW8BCXHt6HszC44abWYNXMGxo0bBycn/l6g+o8FkOxKYWEhFixYgMWxn0Io1HDuPBguYS9BplBJHY2IHhOb0YCSU9+g7NR2KOXAlMnvYMqUKdDpdFJHI3psWADJLmVnZ+ODDz7A6jVroHB0g2OHfnAJ/QPPIUhUjwmLCaVnvoP++FbAVI4//eltzJw5E15eXlJHI3rsWADJrl26dAkff/wx1q/fAJlKA8f2feDS4WU4aF2kjkZENcRmLEPpmd0wnP4GFkMJxkRHY/bs2WjatKnU0YgkwwJIBOD69etYuHAhVnyxElYhg+OTveDSqT8Uzh5SRyOi/5FVX4iSU9/AkLYbMqsZUVGjMW3aNLRs2VLqaESSYwEk+g+3b99GbGwslixbhvJyIxzbRsLtqUFQuHlLHY2IHpC58CZKTsTBcP4ANBoVxr39NiZNmgRfX54GiuguFkCi+ygqKsLnn3+OhYs+QVFREZxCnoXrU0OgbOgndTQi+gXG3MsoPbENhovJ8GjQAFMmv4O33nqLizuI7oMFkOhXlJWVYdWqVfh4wV+Rm5sDp5Zd4BTWB5qm7XitYaJaQAgB47VzKD3xNQw/nYZfM3/MnD4N0dHR0Gq1UscjqrVYAIkegNFoxIYNG7Dwk8VIv/AjNF7+cAztDacnekCu0kgdj8juCIsZZReTYDizC+U3M9CmbTvMmjkDQ4YMgUKhkDoeUa3HAkj0EIQQSExMxKdLlmDnjh1wUDtC88TzcAnrw8vMET0GlpJ8lKbuRsW5BJj0RYiM7InJk99Br169OCpP9BBYAIn+R1lZWVi+fDn+vuILFBcXwbFFRzi37wNN8/aQyXjtUKKaIoSA8fp56M/sgiHjGLRaDV4bMwZ/+tOf0Lp1a6njEdVJLIBEv1N5eTk2btyI2E+X4NzZNGgaNoH2yd5wbhvJE0sT/Q7WCj3Kzu9H+dkEVORdQ4uWrTBpwniMHj0arq6uUscjqtNYAIlqiBACKSkpWLJkKbbFbYPMQQVNq3A4tY2EuskT/HiK6AEIIWDKyYA+dTfKLyYBwoqBAwbirbf+iO7du/PfEVENYQEkegSys7OxevVqrFqzFtezMqHx8IU6+Dk4tekBpc5H6nhEtY6lJA9lPybCeCER5bez0MSvKd5+648YM2YMfHz4b4aoprEAEj1CNpsNR44cwbp167B5yxYYysrg2KwdtE/0gGNQBOQqnqaC7JfNaIAhIwXlPx6EIessVCo1Bg4YgKio0ejZsyccHBykjkhUb7EAEj0mZWVliIuLw+o1a3Eo8SAUai3ULbvCuU0k1E3bcOEI2QVhs6IiMxVlPxxAxeVjsJlNePrZZxE9ejQGDRrEuX1EjwkLIJEEsrKysGHDBqxasxZZV3+C2t0b6tbd4RT8NJQNm3GeE9UrQgiYb1+F/vx+GNOTYCotQMug1ngtOgojRoyAnx+vsEP0uLEAEkno7sKRtWvXYvOWrdCXlkDT0A/qluFwbN0NSk9/lkGqk+6WPkPGUZguH0X57Ux4NGiIUSNHYNSoUQgLC+P/20QSYgEkqiVMJhP27duHrVu3YltcPEpLiqFp2ASqluFwbNkVKp9A/sGkWk3YrDBmX4Ah4yjMV46jojAXzi6u6PdyX7z66qt44YUXoFQqpY5JRGABJKqVTCYT9u/fjy1btiB++zcoLiqEWucFVYun4NiyK9R+T0Am5wR5kp6wmFCemVpZ+n46AVNZMTy9fTB44AD0798f3bt3h0qlkjomEf0XFkCiWs5iseDw4cOIj4/H13HxyL2ZDZWTG5T+YdA0D4PWvz0cnHRSxyQ7YqvQw3DlJCouH4Px6mlYjOUICGyJIYMGon///ujcuTPkci5qIqrNWACJ6hAhBE6dOoX4+Hjs2PUtfjh3FgCg9Q2EslkotP5hUDcJhsyBH7NRzRFWM4w301GRmQrztTSU38yAsFnRPqwDBg8aiAEDBqB169acokBUh7AAEtVhubm5+P7775GQkIDdexJQcCcfCrUWKr82UPtXjg4qPBrzDzM9FCEEzPnXUJGZCuO1VJiun4fFWA5XNx16RkYiMvJ5vPTSS1y9S1SHsQAS1RM2mw1paWnYu3cvvtuzBynJybCYzdC4e0PRtD00zZ6EukkwFC4NpY5KtZClNB8VWWlVo3ym0gIolSqER0Sg14svIDIyEu3bt+fJmYnqCRZAonpKr9fj0KFDSEhIwLff7cFPVy4BADTu3nDwbQ1Vo9bQNAmpPNUMF5TYFWGzwnznOozZF2G8mQ5bbjrK864BANo+GYpeL/REz549ERERAUdHR4nTEtGjwAJIZCdycnJw9OhRJCcnI+lIMs6cOQ2L2QyF2hEq31ZQNgqGunFrqBu3hlztJHVcqkFWQzGMORkwZl+EJScdptwMWCoMkMvlCHmiLSLCu+C5555Djx494OnpKXVcInoMWACJ7FR5eTlOnTqFlJQUJB05guTkFBQVFgAyGbRe/nDwCYLKqzmUXs2h8vSHXM2RoLpAWEww5V+D6WY6jDcvwpqbgYo72QAAj4aeiOjaBeHh4ejSpQs6duwIZ2dniRMTkRRYAIkIQOXE/4yMDCQnJyMlJQUpR48jI+MirBYLAEDToBHkHk0rC6FXcyi9AqBw8+I1jCUibFZYinJhzs+CKS8L5rxMiILrqLiTDWGzwkGhQLsnQ9EtvCu6dOmCrl27wt+fV5YhokosgET0i4xGIy5evIi0tDSkpaXhTGoqUlPTUFhwBwCg0DhWjg429IfK0x8K90ZQuvvCwaUh5xXWECEErGWFMP9c8kx5WRAF12DMy4LVbAQA6Nw90LZtWzzZri3atq28hYaGQqvVSpyeiGorFkAieihCCOTm5laVwrS0NPzrdCouX86AzWoFAMgdFFB7+ELm6g0HNx8odL5QuFfeK3U+kCl4ZYj/ZDOVw1J8C5aiW7AU5cJSnAtr8S2gNA+molxYjOUAALVGi+CQEIT+R9Fr06YNfHx8OLJHRA+FBZCIaoTJZEJWVhauXLlSdbt06TLSL11GVuZVmIwVVe/V6Dwhd/OBzKkBHJzcIXfSwcHJvfLmXHkv17rU+Y+XhbDBVl4Kq6EYNkPxz/dFsJTkw1J8Cyi9DUvxLZj0RVX7qNQa+DVtipYtAhAQEIDmzZujRYsWaNOmDQICAngaFiKqESyARPTI2Ww25OTk4PLly9UK4vUb2biZk4O827dRpi+tto9M7gCVc2UxhKMOMkcdHLSukKm0kKu0kCk1lfcqLeQqDWQqR8iVmn+/rtL87gIpbFYIi+nnmxE2UwWEqRw2cwWEqQI2kwHCVF5Z7MpLYC0rAspLgIoSWAxFMOuLIYSt2jEdFAp4+zRCYIvmaPFzwbt7CwgIgLe3Ny+jRkSPHAsgEdUKBoMBt27dQm5ubtX93dutW7dw42YO8vLyUVamh6FMD0NZ2W8e00GlhkzmAMgAGWSATIafn/z8kendbQBkMsggqxy1M5tgtRghfv5I+9fI5XLoPBrA09MTPt7e8PH2gpeXFzw9PeHlVf2xp6cndDodP64lIsmxABJRnWSz2WAwGKDX61FaWgq9Xn/PY71eD6vVCiFEtZvNZrtn292bXC6HVquFVquFRqOpdu/i4gJnZ+dqN61Wy0JHRHUOCyARERGRneFEEyIiIiI7wwJIREREZGdYAImIiIjsDAsgERERkZ1hAaRHwt/fH7GxsVLHICIiovtgAayHoqOj0b9/f6lj/KaSkhK8++67aN26NTQaDXx8fBAZGYm4uDjU1OJ0mUyG7du318ixiIiI6guF1AHIPhUVFaFbt24oLi7GRx99hE6dOkGhUODQoUOYNm0aevToAZ1OJ3XMR85sNkOpVEodg4iI7AxHAO3QoUOH0LlzZ6jVavj6+mLGjBmwWCwAgPXr16NBgwYwGo3V9hk0aBBGjx4NALhy5Qr69esHb29vODs7o1OnTti3b99DZZg1axYyMzNx/PhxREVFISQkBK1atcLYsWORmpoKZ2dnAPcfwdPpdFi3bh2AyuvPjhs3Dr6+vtBoNPD398f8+fMBVH4MDQADBgyATCareg4Ay5cvR4sWLaBSqRAUFIQNGzZU+xoymQwrVqxAnz594OjoiODgYBw9ehSXL19G9+7d4eTkhK5du+LKlSvV9tu5cyc6dOgAjUaDgIAAfPDBB1U/27vH/fvf/45+/frByckJH3300UP93IiIiGoCC6Cdyc7ORu/evdGpUyekpaVh+fLlWL16dVURGTJkCKxWK3bs2FG1T35+Pnbt2oUxY8YAAPR6PXr37o19+/bhzJkzePHFF9G3b19cu3btgTLYbDZs2rQJI0aMQKNGje553dnZGQrFgw1OL1myBDt27MCWLVuQnp6OL7/8sqronTx5EgCwdu1a5OTkVD2Pj4/HxIkTMWXKFJw/fx5vvvkmxowZg4MHD1Y79ocffojRo0cjNTUVrVu3xvDhw/Hmm29i5syZOHXqFABg3LhxVe9PSEjAyJEjMWHCBPz4449YsWIF1q1bh5iYmGrHnTNnDvr164dz587htddee6Dvk4iIqEYJqneioqJEv3797vvarFmzRFBQkLDZbFXbPvvsM+Hs7CysVqsQQoi33npL/OEPf6h6PTY2VgQEBFTb57+FhISIpUuXVj1v1qyZWLx48X3fe+vWLQFAfPLJJ7/5vQAQ8fHx1ba5ubmJtWvXCiGEGD9+vOjRo8cvZrvf/uHh4WLs2LHVtg0ZMkT07t272n7vvfde1fOjR48KAGL16tVV2zZu3Cg0Gk3V86efflrMmzev2nE3bNggfH19qx130qRJv/wNExERPQYcAbQzFy5cQNeuXatduzQiIgJ6vR43btwAAIwdOxZ79+5FdnY2gMoRtOjo6Kp9ysrKMG3aNISEhECn08HZ2RkXL1584BFA8fMCj5q4fmp0dDRSU1MRFBSECRMmYO/evb+5z4ULFxAREVFtW0REBC5cuFBtW7t27aoee3t7AwDatm1bbVtFRQVKSkoAAP/6178wd+7cateJHTt2LHJycmAwGKr269ix48N/o0RERDWIi0DsjBDinuL134Wsffv2ePLJJ7F+/Xq8+OKLOHfuHHbu3Fn1/qlTpyIhIQELFy5EYGAgtFotBg8eDJPJ9EAZPD094e7ufk/huh+ZTHbPimCz2Vz1OCwsDFevXsXu3buxb98+DB06FJGRkfj6669/87j/6X4/l/9cnHH3tftts9lsVfcffPABBg4ceM/X02g0VY+dnJx+NRsREdGjxgJoZ0JCQrBt27ZqhSclJQUuLi5o3Lhx1fveeOMNLF68GNnZ2YiMjISfn1/Va0lJSYiOjsaAAQMAVM4JzMzMfOAMcrkcw4YNw4YNGzBnzpx75gGWlZVBrVZDoVDA09MTOTk5Va9dunSp2mgaALi6umLYsGEYNmwYBg8ejF69eqGgoAAeHh5QKpWwWq3V3h8cHIwjR45ULWq5+zMIDg5+4O/hfsLCwpCeno7AwMDfdRwiIqJHjQWwniouLkZqamq1bR4eHnj77bcRGxuL8ePHY9y4cUhPT8ecOXMwefJkyOX/nhEwYsQI/PnPf8bKlSuxfv36ascJDAxEXFwc+vbtC5lMhvfff79qFOxBzZs3D4mJiXjqqacQExODjh07QqlUIikpCfPnz8fJkyeh0+nQo0cPLFu2DF26dIHNZsP06dOrjcItXrwYvr6+CA0NhVwux9atW+Hj41N1Chl/f3/s378fERERUKvVcHd3x9SpUzF06FCEhYXh+eefx86dOxEXF/fQK5n/2+zZs9GnTx/4+flhyJAhkMvlOHv2LM6dO8fVvkREVLtIOQGRHo2oqCgB4J5bVFSUEEKIxMRE0alTJ6FSqYSPj4+YPn26MJvN9xxn1KhRwsPDQ1RUVFTbfvXqVfHcc88JrVYr/Pz8xLJly8Szzz4rJk6cWPWeX1sEcldRUZGYMWOGaNmypVCpVMLb21tERkaK+Pj4qkUd2dnZ4oUXXhBOTk6iZcuW4rvvvqu2COSLL74QoaGhwsnJSbi6uornn39enD59uupr7NixQwQGBgqFQiGaNWtWtf3zzz8XAQEBQqlUilatWon169dXy4b/Wjxy9epVAUCcOXOmatvBgwcFAFFYWFi1bc+ePSI8PFxotVrh6uoqOnfuLL744otfPC4REZEUZELU0CUXqN7p2bMngoODsWTJEqmjEBERUQ1iAaR7FBQUYO/evRgxYgR+/PFHBAUFSR2JiIiIahDnANI9wsLCUFhYiAULFrD8ERER1UMcASQiIiKyMzwRNBEREZGdYQEkIiIisjMsgERERER2hgWQiIiIyM6wABIRERHZGRZAIiIiIjvDAkhERERkZ1gAiYiIiOwMCyARERGRnWEBJCIiIrIzLIBEREREdoYFkIiIiMjOsAASERER2RkWQCIiIiI7wwJIREREZGf+HwscUVcvuHnOAAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Satisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6dead254-560d-4364-a3c9-9df02a5b10db", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "494e2a2d-1913-437d-91e9-d6ef9a3211df", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "962aad69-b985-4ff3-ab06-a854e251135b", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:23: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " dfDisatisfied['Flight Distance_group'] = np.select(\n", + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:46: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", + "\n", + "# --- Define the Conditions ---\n", + "# Assuming you are applying this logic to the dfDisatisfied DataFrame\n", + "conditions = [\n", + " (dfDisatisfied['Flight Distance'] < 750),\n", + " (dfDisatisfied['Flight Distance'] >= 750) & (dfDisatisfied['Flight Distance'] < 1500),\n", + " (dfDisatisfied['Flight Distance'] >= 1500) & (dfDisatisfied['Flight Distance'] < 2250),\n", + " (dfDisatisfied['Flight Distance'] >= 2250) & (dfDisatisfied['Flight Distance'] < 3000),\n", + " (dfDisatisfied['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# --- Define the Corresponding Labels and Order ---\n", + "distance_labels = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# Apply np.select() to create the grouping column\n", + "dfDisatisfied['Flight Distance_group'] = np.select(\n", + " conditions, \n", + " distance_labels, \n", + " default='Unknown'\n", + ")\n", + "\n", + "# --- 2. AUTOMATIC DATA AGGREGATION & PERCENTAGE CALCULATION ---\n", + "\n", + "# Get the count of each Flight Distance group\n", + "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = distance_group_counts_series.reset_index()\n", + "df_counts.columns = ['Flight Distance Group', 'Count']\n", + "\n", + "# Calculate Percentage\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART WITH ANNOTATIONS ---\n", + "plt.figure(figsize=(12, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Flight Distance Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=distance_labels, # Ensures the groups plot in logical order\n", + " palette='magma'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", + "plt.xlabel('Flight Distance Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit to ensure annotations are visible\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.20)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart_final.png')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "8d11c378-2b5c-47b1-97e0-c611056739ec", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\2556283244.py:21: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each Gender from the dfDisatisfied DataFrame\n", + "gender_counts_series = dfDisatisfied['Gender'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = gender_counts_series.reset_index()\n", + "df_counts.columns = ['Gender', 'Count']\n", + "\n", + "# Sort the data by count (or percentage) before plotting\n", + "df_counts = df_counts.sort_values(by='Count', ascending=False)\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(8, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Gender',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " # Order is naturally handled by the prior sorting of df_counts\n", + " palette='Set2' # Used a different palette (Set2)\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Gender')\n", + "plt.xlabel('Gender')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=0, ha='center') # No rotation needed\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_gender_percentage_bar_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "27ee32c2-d244-4497-aafc-0232278b4ed0", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\783172777.py:23: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each age group from the dfDisatisfied DataFrame\n", + "age_group_counts_series = dfDisatisfied['age groups'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts) for plotting\n", + "df_counts = age_group_counts_series.reset_index()\n", + "df_counts.columns = ['Age Group', 'Count']\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "# Optional: Ensure all groups are present, even if count is 0,\n", + "# and ensure they are properly ordered by the chronological order of ages.\n", + "# We will use the 'order' parameter in sns.barplot for this.\n", + "age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(10, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Age Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=age_order, # Use the defined chronological order\n", + " palette='viridis'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Age Group (Chronological Order)')\n", + "plt.xlabel('Age Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=45, ha='right')\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", + "plt.show() # Use plt.show() if running in a script/local environment" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/notebooks/Airline_Project1_Antonio.ipynb b/notebooks/Airline_Project1_Antonio.ipynb new file mode 100644 index 00000000..b5ba7356 --- /dev/null +++ b/notebooks/Airline_Project1_Antonio.ipynb @@ -0,0 +1,2548 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "561808a4-27ef-4523-892a-8584a31efefa", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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103904 rows × 25 columns

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" + ], + "text/plain": [ + " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", + "0 0 70172 Male Loyal Customer 13 Personal Travel \n", + "1 1 5047 Male disloyal Customer 25 Business travel \n", + "2 2 110028 Female Loyal Customer 26 Business travel \n", + "3 3 24026 Female Loyal Customer 25 Business travel \n", + "4 4 119299 Male Loyal Customer 61 Business travel \n", + "... ... ... ... ... ... ... \n", + "103899 103899 94171 Female disloyal Customer 23 Business travel \n", + "103900 103900 73097 Male Loyal Customer 49 Business travel \n", + "103901 103901 68825 Male disloyal Customer 30 Business travel \n", + "103902 103902 54173 Female disloyal Customer 22 Business travel \n", + "103903 103903 62567 Male Loyal Customer 27 Business travel \n", + "\n", + " Class Flight Distance Inflight wifi service \\\n", + "0 Eco Plus 460 3 \n", + "1 Business 235 3 \n", + "2 Business 1142 2 \n", + "3 Business 562 2 \n", + "4 Business 214 3 \n", + "... ... ... ... \n", + "103899 Eco 192 2 \n", + "103900 Business 2347 4 \n", + "103901 Business 1995 1 \n", + "103902 Eco 1000 1 \n", + "103903 Business 1723 1 \n", + "\n", + " Departure/Arrival time convenient ... Inflight entertainment \\\n", + "0 4 ... 5 \n", + "1 2 ... 1 \n", + "2 2 ... 5 \n", + "3 5 ... 2 \n", + "4 3 ... 3 \n", + "... ... ... ... \n", + "103899 1 ... 2 \n", + "103900 4 ... 5 \n", + "103901 1 ... 4 \n", + "103902 1 ... 1 \n", + "103903 3 ... 1 \n", + "\n", + " On-board service Leg room service Baggage handling Checkin service \\\n", + "0 4 3 4 4 \n", + "1 1 5 3 1 \n", + "2 4 3 4 4 \n", + "3 2 5 3 1 \n", + "4 3 4 4 3 \n", + "... ... ... ... ... \n", + "103899 3 1 4 2 \n", + "103900 5 5 5 5 \n", + "103901 3 2 4 5 \n", + "103902 4 5 1 5 \n", + "103903 1 1 4 4 \n", + "\n", + " Inflight service Cleanliness Departure Delay in Minutes \\\n", + "0 5 5 25 \n", + "1 4 1 1 \n", + "2 4 5 0 \n", + "3 4 2 11 \n", + "4 3 3 0 \n", + "... ... ... ... \n", + "103899 3 2 3 \n", + "103900 5 4 0 \n", + "103901 5 4 7 \n", + "103902 4 1 0 \n", + "103903 3 1 0 \n", + "\n", + " Arrival Delay in Minutes satisfaction \n", + "0 18.0 neutral or dissatisfied \n", + "1 6.0 neutral or dissatisfied \n", + "2 0.0 satisfied \n", + "3 9.0 neutral or dissatisfied \n", + "4 0.0 satisfied \n", + "... ... ... \n", + "103899 0.0 neutral or dissatisfied \n", + "103900 0.0 satisfied \n", + "103901 14.0 neutral or dissatisfied \n", + "103902 0.0 neutral or dissatisfied \n", + "103903 0.0 neutral or dissatisfied \n", + "\n", + "[103904 rows x 25 columns]" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import stats\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", + "\n", + "df=pd.read_csv('train.csv')\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a86604ec-da44-40c0-894e-0a118b9ca685", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age Group creation successful.\n", + "Flight distance group Group creation successful.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_21412\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", + " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" + ] + } + ], + "source": [ + "binary_change= {\n", + " 'satisfied': 1,\n", + " 'neutral or dissatisfied': 0,\n", + "}\n", + "\n", + "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", + "df.drop(columns=['Unnamed: 0'], inplace=True)\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Age'] < 18),\n", + " (df['Age'] >= 18) & (df['Age'] < 30),\n", + " (df['Age'] >= 30) & (df['Age'] < 40),\n", + " (df['Age'] >= 40) & (df['Age'] < 50),\n", + " (df['Age'] >= 50) & (df['Age'] < 60),\n", + " (df['Age'] >= 60) & (df['Age'] < 70),\n", + " (df['Age'] >= 70)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Minor',\n", + " '18 to 30',\n", + " '30 to 40',\n", + " '40 to 50',\n", + " '50 to 60',\n", + " '60 to 70',\n", + " '70 +'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Age Group creation successful.\")\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Flight Distance'] < 750),\n", + " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", + " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", + " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", + " (df['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Flight distance group Group creation successful.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "d113003b-b385-4d24-a8a7-fade2501e0c2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online booking...Baggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfactionsatisfaction_binaryage groupsFlight Distance_group
070172MaleLoyal Customer13Personal TravelEco Plus460343...44552518.0neutral or dissatisfied0MinorShort, until 750 miles
15047Maledisloyal Customer25Business travelBusiness235323...314116.0neutral or dissatisfied018 to 30Short, until 750 miles
2110028FemaleLoyal Customer26Business travelBusiness1142222...444500.0satisfied118 to 30Medium-short, until 1500 miles
324026FemaleLoyal Customer25Business travelBusiness562255...3142119.0neutral or dissatisfied018 to 30Short, until 750 miles
4119299MaleLoyal Customer61Business travelBusiness214333...433300.0satisfied160 to 70Short, until 750 miles
..................................................................
10389994171Femaledisloyal Customer23Business travelEco192212...423230.0neutral or dissatisfied018 to 30Short, until 750 miles
10390073097MaleLoyal Customer49Business travelBusiness2347444...555400.0satisfied140 to 50Long, until 3000 miles
10390168825Maledisloyal Customer30Business travelBusiness1995111...4554714.0neutral or dissatisfied030 to 40Medium-Long, until 2250 miles
10390254173Femaledisloyal Customer22Business travelEco1000111...154100.0neutral or dissatisfied018 to 30Medium-short, until 1500 miles
10390362567MaleLoyal Customer27Business travelBusiness1723133...443100.0neutral or dissatisfied018 to 30Medium-Long, until 2250 miles
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103904 rows × 27 columns

\n", + "
" + ], + "text/plain": [ + " id Gender Customer Type Age Type of Travel Class \\\n", + "0 70172 Male Loyal Customer 13 Personal Travel Eco Plus \n", + "1 5047 Male disloyal Customer 25 Business travel Business \n", + "2 110028 Female Loyal Customer 26 Business travel Business \n", + "3 24026 Female Loyal Customer 25 Business travel Business \n", + "4 119299 Male Loyal Customer 61 Business travel Business \n", + "... ... ... ... ... ... ... \n", + "103899 94171 Female disloyal Customer 23 Business travel Eco \n", + "103900 73097 Male Loyal Customer 49 Business travel Business \n", + "103901 68825 Male disloyal Customer 30 Business travel Business \n", + "103902 54173 Female disloyal Customer 22 Business travel Eco \n", + "103903 62567 Male Loyal Customer 27 Business travel Business \n", + "\n", + " Flight Distance Inflight wifi service \\\n", + "0 460 3 \n", + "1 235 3 \n", + "2 1142 2 \n", + "3 562 2 \n", + "4 214 3 \n", + "... ... ... \n", + "103899 192 2 \n", + "103900 2347 4 \n", + "103901 1995 1 \n", + "103902 1000 1 \n", + "103903 1723 1 \n", + "\n", + " Departure/Arrival time convenient Ease of Online booking ... \\\n", + "0 4 3 ... \n", + "1 2 3 ... \n", + "2 2 2 ... \n", + "3 5 5 ... \n", + "4 3 3 ... \n", + "... ... ... ... \n", + "103899 1 2 ... \n", + "103900 4 4 ... \n", + "103901 1 1 ... \n", + "103902 1 1 ... \n", + "103903 3 3 ... \n", + "\n", + " Baggage handling Checkin service Inflight service Cleanliness \\\n", + "0 4 4 5 5 \n", + "1 3 1 4 1 \n", + "2 4 4 4 5 \n", + "3 3 1 4 2 \n", + "4 4 3 3 3 \n", + "... ... ... ... ... \n", + "103899 4 2 3 2 \n", + "103900 5 5 5 4 \n", + "103901 4 5 5 4 \n", + "103902 1 5 4 1 \n", + "103903 4 4 3 1 \n", + "\n", + " Departure Delay in Minutes Arrival Delay in Minutes \\\n", + "0 25 18.0 \n", + "1 1 6.0 \n", + "2 0 0.0 \n", + "3 11 9.0 \n", + "4 0 0.0 \n", + "... ... ... \n", + "103899 3 0.0 \n", + "103900 0 0.0 \n", + "103901 7 14.0 \n", + "103902 0 0.0 \n", + "103903 0 0.0 \n", + "\n", + " satisfaction satisfaction_binary age groups \\\n", + "0 neutral or dissatisfied 0 Minor \n", + "1 neutral or dissatisfied 0 18 to 30 \n", + "2 satisfied 1 18 to 30 \n", + "3 neutral or dissatisfied 0 18 to 30 \n", + "4 satisfied 1 60 to 70 \n", + "... ... ... ... \n", + "103899 neutral or dissatisfied 0 18 to 30 \n", + "103900 satisfied 1 40 to 50 \n", + "103901 neutral or dissatisfied 0 30 to 40 \n", + "103902 neutral or dissatisfied 0 18 to 30 \n", + "103903 neutral or dissatisfied 0 18 to 30 \n", + "\n", + " Flight Distance_group \n", + "0 Short, until 750 miles \n", + "1 Short, until 750 miles \n", + "2 Medium-short, until 1500 miles \n", + "3 Short, until 750 miles \n", + "4 Short, until 750 miles \n", + "... ... \n", + "103899 Short, until 750 miles \n", + "103900 Long, until 3000 miles \n", + "103901 Medium-Long, until 2250 miles \n", + "103902 Medium-short, until 1500 miles \n", + "103903 Medium-Long, until 2250 miles \n", + "\n", + "[103904 rows x 27 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "45c65011-e822-4684-bc5d-b394ba4aafea", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "satisfaction\n", + "neutral or dissatisfied 58879\n", + "satisfied 45025\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['satisfaction'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "caaec0b4-342d-4c69-ba35-41553e791c96", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Customer Type\n", + "Loyal Customer 84923\n", + "disloyal Customer 18981\n", + "Name: count, dtype: int64" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "6f945079-4c90-40ee-83b9-53af53e43388", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", + "dfDisatisfied=df[df['satisfaction_binary'] == 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "6abbfb4e-11bc-43d4-80e5-99626252e77b", + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "unsupported operand type(s) for /: 'str' and 'int'", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[7], line 49\u001b[0m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m 48\u001b[0m \u001b[38;5;66;03m# 3b. Perform Welch's T-Test (equal_var=False)\u001b[39;00m\n\u001b[1;32m---> 49\u001b[0m t_stat, p_value \u001b[38;5;241m=\u001b[39m stats\u001b[38;5;241m.\u001b[39mttest_ind(\n\u001b[0;32m 50\u001b[0m a\u001b[38;5;241m=\u001b[39mdata_sat,\n\u001b[0;32m 51\u001b[0m b\u001b[38;5;241m=\u001b[39mdata_dis,\n\u001b[0;32m 52\u001b[0m equal_var\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m 53\u001b[0m )\n\u001b[0;32m 55\u001b[0m \u001b[38;5;66;03m# 3c. Store Results\u001b[39;00m\n\u001b[0;32m 56\u001b[0m is_significant \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYes (Reject H0)\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m p_value \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.05\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mNo (Fail to Reject H0)\u001b[39m\u001b[38;5;124m'\u001b[39m\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\_lib\\deprecation.py:234\u001b[0m, in \u001b[0;36m_deprecate_positional_args.._inner_deprecate_positional_args..inner_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m extra_args \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 233\u001b[0m warn_deprecated_args(kwargs)\n\u001b[1;32m--> 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m f(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 236\u001b[0m \u001b[38;5;66;03m# extra_args > 0\u001b[39;00m\n\u001b[0;32m 237\u001b[0m kwonly_extra_args \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(kwonly_args[:extra_args]) \u001b[38;5;241m-\u001b[39m deprecated_args\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_axis_nan_policy.py:586\u001b[0m, in \u001b[0;36m_axis_nan_policy_factory..axis_nan_policy_decorator..axis_nan_policy_wrapper\u001b[1;34m(***failed resolving arguments***)\u001b[0m\n\u001b[0;32m 583\u001b[0m res \u001b[38;5;241m=\u001b[39m _add_reduced_axes(res, reduced_axes, keepdims)\n\u001b[0;32m 584\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tuple_to_result(\u001b[38;5;241m*\u001b[39mres)\n\u001b[1;32m--> 586\u001b[0m res \u001b[38;5;241m=\u001b[39m hypotest_fun_out(\u001b[38;5;241m*\u001b[39msamples, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[0;32m 587\u001b[0m res \u001b[38;5;241m=\u001b[39m result_to_tuple(res, n_out)\n\u001b[0;32m 588\u001b[0m res \u001b[38;5;241m=\u001b[39m _add_reduced_axes(res, reduced_axes, keepdims)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:6679\u001b[0m, in \u001b[0;36mttest_ind\u001b[1;34m(a, b, axis, equal_var, nan_policy, permutations, random_state, alternative, trim, method)\u001b[0m\n\u001b[0;32m 6677\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m trim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 6678\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m np\u001b[38;5;241m.\u001b[39merrstate(divide\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m, invalid\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m-> 6679\u001b[0m v1 \u001b[38;5;241m=\u001b[39m _var(a, axis, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 6680\u001b[0m v2 \u001b[38;5;241m=\u001b[39m _var(b, axis, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 6682\u001b[0m m1 \u001b[38;5;241m=\u001b[39m xp\u001b[38;5;241m.\u001b[39mmean(a, axis\u001b[38;5;241m=\u001b[39maxis)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:1211\u001b[0m, in \u001b[0;36m_var\u001b[1;34m(x, axis, ddof, mean, xp)\u001b[0m\n\u001b[0;32m 1208\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_var\u001b[39m(x, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, mean\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, xp\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m 1209\u001b[0m \u001b[38;5;66;03m# Calculate variance of sample, warning if precision is lost\u001b[39;00m\n\u001b[0;32m 1210\u001b[0m xp \u001b[38;5;241m=\u001b[39m array_namespace(x) \u001b[38;5;28;01mif\u001b[39;00m xp \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m xp\n\u001b[1;32m-> 1211\u001b[0m var \u001b[38;5;241m=\u001b[39m _moment(x, \u001b[38;5;241m2\u001b[39m, axis, mean\u001b[38;5;241m=\u001b[39mmean, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 1212\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ddof \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 1213\u001b[0m n \u001b[38;5;241m=\u001b[39m x\u001b[38;5;241m.\u001b[39mshape[axis] \u001b[38;5;28;01mif\u001b[39;00m axis \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m xp_size(x)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:1190\u001b[0m, in \u001b[0;36m_moment\u001b[1;34m(a, order, axis, mean, xp)\u001b[0m\n\u001b[0;32m 1187\u001b[0m n_list\u001b[38;5;241m.\u001b[39mappend(current_n)\n\u001b[0;32m 1189\u001b[0m \u001b[38;5;66;03m# Starting point for exponentiation by squares\u001b[39;00m\n\u001b[1;32m-> 1190\u001b[0m mean \u001b[38;5;241m=\u001b[39m (xp\u001b[38;5;241m.\u001b[39mmean(a, axis\u001b[38;5;241m=\u001b[39maxis, keepdims\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m mean \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1191\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m xp\u001b[38;5;241m.\u001b[39masarray(mean, dtype\u001b[38;5;241m=\u001b[39mdtype))\n\u001b[0;32m 1192\u001b[0m mean \u001b[38;5;241m=\u001b[39m mean[()] \u001b[38;5;28;01mif\u001b[39;00m mean\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m mean\n\u001b[0;32m 1193\u001b[0m a_zero_mean \u001b[38;5;241m=\u001b[39m _demean(a, mean, axis, xp\u001b[38;5;241m=\u001b[39mxp)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\numpy\\_core\\fromnumeric.py:3904\u001b[0m, in \u001b[0;36mmean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m 3901\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 3902\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m mean(axis\u001b[38;5;241m=\u001b[39maxis, dtype\u001b[38;5;241m=\u001b[39mdtype, out\u001b[38;5;241m=\u001b[39mout, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m-> 3904\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _methods\u001b[38;5;241m.\u001b[39m_mean(a, axis\u001b[38;5;241m=\u001b[39maxis, dtype\u001b[38;5;241m=\u001b[39mdtype,\n\u001b[0;32m 3905\u001b[0m out\u001b[38;5;241m=\u001b[39mout, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n", + "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\numpy\\_core\\_methods.py:139\u001b[0m, in \u001b[0;36m_mean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m 137\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, mu\u001b[38;5;241m.\u001b[39mndarray):\n\u001b[0;32m 138\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _no_nep50_warning():\n\u001b[1;32m--> 139\u001b[0m ret \u001b[38;5;241m=\u001b[39m um\u001b[38;5;241m.\u001b[39mtrue_divide(\n\u001b[0;32m 140\u001b[0m ret, rcount, out\u001b[38;5;241m=\u001b[39mret, casting\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124munsafe\u001b[39m\u001b[38;5;124m'\u001b[39m, subok\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m 141\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_float16_result \u001b[38;5;129;01mand\u001b[39;00m out \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 142\u001b[0m ret \u001b[38;5;241m=\u001b[39m arr\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mtype(ret)\n", + "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'int'" + ] + } + ], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Type of Travel',\n", + " 'Class',\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "# --- 2. Initialize a Dictionary to Store Results ---\n", + "results = {\n", + " 'Metric': [],\n", + " 'Mean_Satisfied': [],\n", + " 'Mean_Dissatisfied': [],\n", + " 'T_Statistic': [],\n", + " 'P_Value': [],\n", + " 'Significance (α=0.05)': []\n", + "}\n", + "\n", + "# --- 3. Loop Through Columns and Perform T-Test ---\n", + "for col in metric_columns:\n", + " # 3a. Isolate and clean data for the current column\n", + " data_sat = dfSatisfied[col].dropna()\n", + " data_dis = dfDisatisfied[col].dropna()\n", + "\n", + " # Skip if one of the groups has no data\n", + " if len(data_sat) == 0 or len(data_dis) == 0:\n", + " continue\n", + "\n", + " # 3b. Perform Welch's T-Test (equal_var=False)\n", + " t_stat, p_value = stats.ttest_ind(\n", + " a=data_sat,\n", + " b=data_dis,\n", + " equal_var=False\n", + " )\n", + "\n", + " # 3c. Store Results\n", + " is_significant = 'Yes (Reject H0)' if p_value <= 0.05 else 'No (Fail to Reject H0)'\n", + "\n", + " results['Metric'].append(col)\n", + " results['Mean_Satisfied'].append(data_sat.mean())\n", + " results['Mean_Dissatisfied'].append(data_dis.mean())\n", + " results['T_Statistic'].append(t_stat)\n", + " results['P_Value'].append(p_value)\n", + " results['Significance (α=0.05)'].append(is_significant)\n", + "\n", + "# --- 4. Convert Results Dictionary to a DataFrame ---\n", + "results_df = pd.DataFrame(results)\n", + "\n", + "# --- 5. Print/Display Results ---\n", + "print(results_df.round(4))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3e5ecb36-ada2-4925-9e0d-2ae0996881c7", + "metadata": {}, + "outputs": [], + "source": [ + "list(df)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "247db4d7-3a0d-4c98-ab26-f537b049e252", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "148a480d-158c-4ed5-b379-4b1b2d20a3a5", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9864a901-c3c9-4d41-ad57-d6f382d976c3", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied_disloyal.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "72c0cdfb-e081-478f-8977-85779113cd4f", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", + "metadata": {}, + "outputs": [], + "source": [ + "numeric_cols_df = df.select_dtypes(include=np.number)\n", + "\n", + "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", + "metrics_to_analyze = [\n", + " 'Flight Distance',\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " 'Age' # Including age as a numeric metric to analyze\n", + "]\n", + "\n", + "# Filter down to the columns that actually exist and are numeric\n", + "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", + "\n", + "# --- 2. Melt the DataFrame ---\n", + "df_melted = df.melt(\n", + " id_vars=['satisfaction'],\n", + " value_vars=analysis_cols,\n", + " var_name='Metric', # This column now holds the name of the original column\n", + " value_name='Value' # This column now holds the numeric data\n", + ")\n", + "\n", + "# --- 3. Create the Pivot Table ---\n", + "pivot_stats = pd.pivot_table(\n", + " df_melted,\n", + " index=['Metric'],\n", + " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", + " values='Value',\n", + " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", + ")\n", + "\n", + "# --- 4. Re-orient to Vertical View ---\n", + "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", + "vertical_stats_table = pivot_stats.stack(level=0)\n", + "\n", + "# Rename the new index level for clarity\n", + "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", + "\n", + "# Display the final vertical table\n", + "vertical_stats_table" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "69231728-91ed-4a46-ae0c-826b298928b8", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df_melted' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[8], line 12\u001b[0m\n\u001b[0;32m 8\u001b[0m \u001b[38;5;66;03m# --- 2. Create the Grouped Bar Plot with the new palette ---\u001b[39;00m\n\u001b[0;32m 9\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m16\u001b[39m, \u001b[38;5;241m8\u001b[39m))\n\u001b[0;32m 11\u001b[0m sns\u001b[38;5;241m.\u001b[39mbarplot(\n\u001b[1;32m---> 12\u001b[0m data\u001b[38;5;241m=\u001b[39mdf_melted,\n\u001b[0;32m 13\u001b[0m x\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMetric\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 14\u001b[0m y\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mValue\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 15\u001b[0m hue\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msatisfaction\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 16\u001b[0m errorbar\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msd\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 17\u001b[0m palette\u001b[38;5;241m=\u001b[39mcorrect_palette \u001b[38;5;66;03m# Use the corrected dictionary\u001b[39;00m\n\u001b[0;32m 18\u001b[0m )\n\u001b[0;32m 20\u001b[0m \u001b[38;5;66;03m# --- 3. Format the Chart (rest of the code) ---\u001b[39;00m\n\u001b[0;32m 21\u001b[0m plt\u001b[38;5;241m.\u001b[39mtitle(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMean of All Metrics Grouped by Satisfaction Status\u001b[39m\u001b[38;5;124m'\u001b[39m, fontsize\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m16\u001b[39m)\n", + "\u001b[1;31mNameError\u001b[0m: name 'df_melted' is not defined" + ] + }, + { + "data": { + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. Define the CORRECTED Palette Dictionary ---\n", + "# We use 'neutral or dissatisfied' as the key, mapped to a color.\n", + "correct_palette = {\n", + " 'satisfied': 'tab:blue',\n", + " 'neutral or dissatisfied': 'tab:orange' # Mapped to orange, representing the non-satisfied group\n", + "}\n", + "\n", + "# --- 2. Create the Grouped Bar Plot with the new palette ---\n", + "plt.figure(figsize=(16, 8))\n", + "\n", + "sns.barplot(\n", + " data=df_melted,\n", + " x='Metric',\n", + " y='Value',\n", + " hue='satisfaction',\n", + " errorbar='sd',\n", + " palette=correct_palette # Use the corrected dictionary\n", + ")\n", + "\n", + "# --- 3. Format the Chart (rest of the code) ---\n", + "plt.title('Mean of All Metrics Grouped by Satisfaction Status', fontsize=16)\n", + "plt.ylabel('Mean Value (Mixed Scales)', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "2599980d-0244-44e9-bcd4-5cd3d5cb2d23", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "\n", + "# Assuming 'df' is your original DataFrame\n", + "# ----------------------------------------------------\n", + "# 1. Identify the numeric metric columns to scale\n", + "# (Excluding categorical, ID, and the 'satisfaction' column)\n", + "\n", + "metrics_to_scale = [\n", + " 'Flight Distance', 'Inflight wifi service', 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking', 'Gate location', 'Food and drink', 'Online boarding',\n", + " 'Seat comfort', 'Inflight entertainment', 'On-board service', 'Leg room service',\n", + " 'Baggage handling', 'Checkin service', 'Inflight service', 'Cleanliness',\n", + " 'Departure Delay in Minutes', 'Arrival Delay in Minutes', 'Age'\n", + "]\n", + "\n", + "# Create a copy of the DataFrame columns to scale\n", + "df_scaled = df[metrics_to_scale].copy()\n", + "\n", + "# Initialize the scaler\n", + "scaler = MinMaxScaler()\n", + "\n", + "# Apply scaler to all columns in the copy\n", + "df_scaled[metrics_to_scale] = scaler.fit_transform(df_scaled[metrics_to_scale])\n", + "\n", + "# Merge the scaled metrics back into the original DataFrame (or a new one)\n", + "df_normalized = df[['satisfaction']].copy()\n", + "df_normalized = pd.concat([df_normalized, df_scaled], axis=1)\n", + "\n", + "# ----------------------------------------------------\n", + "# 2. Melt the Scaled Data\n", + "\n", + "# Use the normalized DataFrame for melting\n", + "df_melted_normalized = df_normalized.melt(\n", + " id_vars=['satisfaction'],\n", + " value_vars=metrics_to_scale,\n", + " var_name='Metric',\n", + " value_name='Normalized_Value' # New column name for the scaled values\n", + ")\n", + "\n", + "# ----------------------------------------------------\n", + "# 3. Plot the Scaled Data\n", + "\n", + "plt.figure(figsize=(16, 8))\n", + "\n", + "correct_palette = {\n", + " 'satisfied': 'tab:blue',\n", + " 'neutral or dissatisfied': 'tab:orange'\n", + "}\n", + "\n", + "sns.barplot(\n", + " data=df_melted_normalized,\n", + " x='Metric',\n", + " y='Normalized_Value', # Plotting the 0-to-1 scaled values\n", + " hue='satisfaction',\n", + " errorbar='sd',\n", + " palette=correct_palette\n", + ")\n", + "\n", + "# --- Format the Chart ---\n", + "plt.title('Mean of All Metrics Grouped by Satisfaction Status (Normalized)', fontsize=16)\n", + "plt.ylabel('Normalized Mean Value (Range: 0 to 1)', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'df_melted' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[10], line 26\u001b[0m\n\u001b[0;32m 7\u001b[0m filtered_metrics_1to5 \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 8\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mInflight wifi service\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 9\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDeparture/Arrival time convenient\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCleanliness\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 22\u001b[0m ]\n\u001b[0;32m 24\u001b[0m \u001b[38;5;66;03m# --- 2. Filter the df_melted DataFrame ---\u001b[39;00m\n\u001b[0;32m 25\u001b[0m \u001b[38;5;66;03m# Only keep rows where the 'Metric' is in the list above\u001b[39;00m\n\u001b[1;32m---> 26\u001b[0m df_melted_filtered_1to5 \u001b[38;5;241m=\u001b[39m df_melted[df_melted[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMetric\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39misin(filtered_metrics_1to5)]\n\u001b[0;32m 29\u001b[0m \u001b[38;5;66;03m# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\u001b[39;00m\n\u001b[0;32m 30\u001b[0m correct_palette \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 31\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msatisfied\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtab:blue\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 32\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mneutral or dissatisfied\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtab:orange\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 33\u001b[0m }\n", + "\u001b[1;31mNameError\u001b[0m: name 'df_melted' is not defined" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import pandas as pd\n", + "# Assuming df_melted is already in your environment from previous steps\n", + "\n", + "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", + "filtered_metrics_1to5 = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + "]\n", + "\n", + "# --- 2. Filter the df_melted DataFrame ---\n", + "# Only keep rows where the 'Metric' is in the list above\n", + "df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", + "\n", + "\n", + "# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", + "correct_palette = {\n", + " 'satisfied': 'tab:blue',\n", + " 'neutral or dissatisfied': 'tab:orange'\n", + "}\n", + "\n", + "# --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", + "plt.figure(figsize=(16, 8))\n", + "\n", + "sns.barplot(\n", + " data=df_melted_filtered_1to5, # Using the filtered data\n", + " x='Metric',\n", + " y='Value',\n", + " hue='satisfaction',\n", + " errorbar='sd',\n", + " palette=correct_palette\n", + ")\n", + "\n", + "# --- 5. Format the Chart ---\n", + "plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", + "plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "350b26b2-5a25-43aa-9ca2-c2b7edd64774", + "metadata": {}, + "outputs": [], + "source": [ + "satisfied_ratings = dfSatisfied['Inflight wifi service'].dropna()\n", + "dissatisfied_ratings = dfDisatisfied['Inflight wifi service'].dropna()\n", + "\n", + "# Perform the Two-Sample T-Test (Welch's)\n", + "t_statistic, p_value = stats.ttest_ind(\n", + " a=satisfied_ratings,\n", + " b=dissatisfied_ratings,\n", + " equal_var=False\n", + ")\n", + "\n", + "# --- Output the Results ---\n", + "print(f\"--- T-Test Results for Inflight wifi service ---\")\n", + "print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", + "print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", + "print(\"-\" * 38)\n", + "print(f\"T-Statistic: {t_statistic:.4f}\")\n", + "print(f\"P-Value: {p_value:.10f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5a2bf756-8500-4adc-99af-1c48cd7e1d37", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " satisfied_ratings = dfDisatisfied[col].dropna()\n", + " dissatisfied_ratings = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=satisfied_ratings,\n", + " b=dissatisfied_ratings,\n", + " equal_var=False\n", + " )\n", + "\n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", + " print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91a9b0cd-b1f0-4851-8439-cf30868a1bf6", + "metadata": {}, + "outputs": [], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60a773e7-2487-47bd-b868-94f7b60bf471", + "metadata": {}, + "outputs": [], + "source": [ + "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", + "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", + "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a75fd6ab-fb8e-4ef8-ab12-ac19c28bc21a", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied_disloyal.describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6ad6e2d8-eed3-446e-ae43-a6c5e127c8be", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d4e77057-6266-4cd6-b6dc-4647799d96ff", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07ee2084-a56b-4321-a025-d13bb9e510dc", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied_disloyal" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9b45c0ab-c959-4130-820f-19a659973ecb", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1cb9c038-2d28-4203-8cce-0146b91182e1", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Define the Metric Columns to Test ---\n", + "# Use the common numeric columns that represent scores/distances/delays.\n", + "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", + "\n", + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " df_1 = dfDisatisfied[col].dropna()\n", + " df_2 = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1,\n", + " b=df_2,\n", + " equal_var=False\n", + " )\n", + " \n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1: {df_1.mean():.3f}\")\n", + " print(f\"df_2: {df_2.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c9f9a363-4c19-4991-ac52-524d8e388100", + "metadata": {}, + "outputs": [], + "source": [ + "metric_columns = [\n", + " 'Inflight wifi service',\n", + " 'Departure/Arrival time convenient',\n", + " 'Ease of Online booking',\n", + " 'Gate location',\n", + " 'Food and drink',\n", + " 'Online boarding',\n", + " 'Seat comfort',\n", + " 'Inflight entertainment',\n", + " 'On-board service',\n", + " 'Leg room service',\n", + " 'Baggage handling',\n", + " 'Checkin service',\n", + " 'Inflight service',\n", + " 'Cleanliness',\n", + " 'Departure Delay in Minutes',\n", + " 'Arrival Delay in Minutes',\n", + " # Add all other numeric metrics you want to compare\n", + "]\n", + "\n", + "for col in metric_columns: \n", + " df_1 = dfDisloyal[col].dropna()\n", + " df_2 = dfDisatisfied_disloyal[col].dropna()\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1,\n", + " b=df_2,\n", + " equal_var=False\n", + " )\n", + "\n", + " # --- Output the Results ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1: {df_1.mean():.3f}\")\n", + " print(f\"df_2: {df_2.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "48bdbb2e-65c5-41e1-b398-559ccb485221", + "metadata": {}, + "outputs": [], + "source": [ + "legend_colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] \n", + "\n", + "# Define the corresponding labels\n", + "legend_labels = ['Category A', 'Category B', 'Category C']" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name 'dfDisloyal' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[1;32mIn[11], line 11\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;66;03m# --- 2. Iterate, Test, and Collect Results ---\u001b[39;00m\n\u001b[0;32m 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m col \u001b[38;5;129;01min\u001b[39;00m metric_columns:\n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# Safely convert to numeric and drop NaNs for both comparison groups\u001b[39;00m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;66;03m# NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m df_1_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_numeric(dfDisloyal[col], errors\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcoerce\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mdropna()\n\u001b[0;32m 12\u001b[0m df_2_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_numeric(dfDisatisfied_disloyal[col], errors\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcoerce\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mdropna()\n\u001b[0;32m 14\u001b[0m \u001b[38;5;66;03m# Skip if groups are too small or empty after cleaning\u001b[39;00m\n", + "\u001b[1;31mNameError\u001b[0m: name 'dfDisloyal' is not defined" + ] + } + ], + "source": [ + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisloyal[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disloyal vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22aa3477-4a71-4966-8278-0fb39583ffae", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Initialize Lists for Storing Results ---\n", + "metric_names = []\n", + "p_values = []\n", + "is_significant = []\n", + "alpha = 0.05 # Significance level\n", + "\n", + "# --- 2. Iterate, Test, and Collect Results ---\n", + "for col in metric_columns:\n", + " # Safely convert to numeric and drop NaNs for both comparison groups\n", + " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", + " df_1_data = pd.to_numeric(dfDisatisfied[col], errors='coerce').dropna()\n", + " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", + " \n", + " # Skip if groups are too small or empty after cleaning\n", + " if df_1_data.size < 2 or df_2_data.size < 2:\n", + " print(f\"Skipping {col}: Insufficient data.\")\n", + " continue\n", + "\n", + " # Perform Welch's T-Test\n", + " t_statistic, p_value = stats.ttest_ind(\n", + " a=df_1_data,\n", + " b=df_2_data,\n", + " equal_var=False\n", + " )\n", + "\n", + " # Store results in the lists\n", + " metric_names.append(col)\n", + " p_values.append(p_value)\n", + " is_significant.append(p_value <= alpha)\n", + "\n", + " # --- Output the Results (Optional, as requested) ---\n", + " print(f\"--- T-Test Results for {col} ---\")\n", + " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", + " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", + " print(f\"T-Statistic: {t_statistic:.4f}\")\n", + " print(f\"P-Value: {p_value:.10f}\")\n", + " print(\"-\" * 38)\n", + "\n", + "# --- 3. Create DataFrame for Plotting ---\n", + "p_values_df = pd.DataFrame({\n", + " 'Metric': metric_names,\n", + " 'P_Value': p_values,\n", + " 'Is_Significant': is_significant\n", + "})\n", + "\n", + "# # Sort the results by P-Value for a cleaner chart\n", + "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", + "\n", + "# --- 4. Plot the P-Values ---\n", + "\n", + "# Define colors for bars based on significance\n", + "# --- Define the mapping dictionary ---\n", + "# Create the dictionary that maps the unique hue values (True/False) to colors\n", + "palette_map = {\n", + " True: 'darkred', # For bars where Is_Significant is True\n", + " False: 'skyblue' # For bars where Is_Significant is False\n", + "}\n", + "\n", + "plt.figure(figsize=(14, 8))\n", + "ax = sns.barplot(\n", + " data=p_values_df,\n", + " x='Metric',\n", + " y='P_Value',\n", + " hue='Is_Significant',\n", + " palette=palette_map, # <-- FIX: Pass the dictionary here\n", + " dodge=False,\n", + ")\n", + "# Add horizontal line at p=0.05\n", + "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", + "\n", + "# --- Custom Legend ---\n", + "from matplotlib.patches import Patch\n", + "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", + "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", + "final_handles = custom_handles + [significance_line]\n", + "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", + "\n", + "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", + "ax.get_legend().remove() \n", + "\n", + "# --- Formatting ---\n", + "plt.title('P-Values from T-Tests for only Disatisfied vs Disatisfied disloyal customers', fontsize=16)\n", + "plt.ylabel('P-Value', fontsize=14)\n", + "plt.xlabel('Metric', fontsize=14)\n", + "plt.xticks(rotation=45, ha='right')\n", + "plt.ylim(0, 1.0)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "486e26c6-7291-4075-97db-de6b916db1f8", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8b49a8ad-9ade-4c87-bfc1-8c41a0fc8cbc", + "metadata": {}, + "outputs": [], + "source": [ + "df['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eebaa851-4d41-4660-93f0-134a3cb071da", + "metadata": {}, + "outputs": [], + "source": [ + "dfSatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bfb858a8-9410-4699-8150-7f17f158580a", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied['Customer Type'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", + "metadata": {}, + "outputs": [], + "source": [ + "customer_type_counts = df['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on the entire population')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", + "metadata": {}, + "outputs": [], + "source": [ + "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Disatisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", + "metadata": {}, + "outputs": [], + "source": [ + "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "plt.pie(\n", + " customer_type_counts,\n", + " labels=customer_type_counts.index,\n", + " # This is the key part: autopct='%1.1f%%' formats the percentage\n", + " autopct='%1.1f%%',\n", + " startangle=90,\n", + " wedgeprops={'edgecolor': 'black'}\n", + ")\n", + "plt.title('Loyalty distribution on Satisfied customers')\n", + "plt.axis('equal') # Ensures the pie chart is circular\n", + "plt.savefig('customer_type_pie_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "18bc096e-7e84-4b59-afab-dd9cf34f8875", + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Age'] < 18),\n", + " (df['Age'] >= 18) & (df['Age'] < 30),\n", + " (df['Age'] >= 30) & (df['Age'] < 40),\n", + " (df['Age'] >= 40) & (df['Age'] < 50),\n", + " (df['Age'] >= 50) & (df['Age'] < 60),\n", + " (df['Age'] >= 60) & (df['Age'] < 70),\n", + " (df['Age'] >= 70)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Minor',\n", + " '18 to 30',\n", + " '30 to 40',\n", + " '40 to 50',\n", + " '50 to 60',\n", + " '60 to 70',\n", + " '70 +'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Age Group creation successful.\")\n", + "\n", + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Flight Distance'] < 750),\n", + " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", + " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", + " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", + " (df['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Flight distance group Group creation successful.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8be13d3-407c-4690-9829-a7ea3716bc18", + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming 'df' is your DataFrame with an 'Age' column\n", + "\n", + "# 1. Define the Conditions\n", + "# Each condition must be a Boolean Series (True/False)\n", + "conditions = [\n", + " (df['Flight Distance'] < 750),\n", + " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", + " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", + " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", + " (df['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# 2. Define the Corresponding Outputs (Labels)\n", + "choices = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# 3. Apply np.select()\n", + "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", + "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", + "\n", + "print(\"Flight distance group Group creation successful.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b7f5979a-541a-41f8-82e7-c883a09f6829", + "metadata": {}, + "outputs": [], + "source": [ + "df['Flight Distance'].describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "252a1bca-6113-4fbf-b754-ab45fdff1f87", + "metadata": {}, + "outputs": [], + "source": [ + "df['Flight Distance_group'].describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "710fac04-fc16-40cb-acef-6796ab3cfbb2", + "metadata": {}, + "outputs": [], + "source": [ + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8358ed7b-ade3-4e04-a9d6-3027fa0d729a", + "metadata": {}, + "outputs": [], + "source": [ + "df['age groups'].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c009267-eb8e-43ec-875d-12876fdfc5e8", + "metadata": {}, + "outputs": [], + "source": [ + "df['age Groups']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c7b7112-b2bf-4796-bee9-9da5649c2811", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "da29f134-7a84-4fa0-87f3-3d825c228c27", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a891b1c5-7566-44a3-8ab5-5ae110605fdc", + "metadata": {}, + "outputs": [], + "source": [ + "# # Data provided by the user (Age Group counts from dfDisatisfied)\n", + "# # In a real scenario, this data would come from: dfDisatisfied['age groups'].value_counts()\n", + "# data_age_groups = {\n", + "# 'Age Group': ['40 to 50', '18 to 30', '30 to 40', '50 to 60', '60 to 70', 'Minor', '70 +'],\n", + "# 'Count': [23696, 22796, 20659, 19103, 8346, 7931, 1373]\n", + "# }\n", + "# df_counts = pd.DataFrame(data_age_groups)\n", + "\n", + "# # 1. Calculate the total number of dissatisfied customers\n", + "# total_customers = df_counts['Count'].sum()\n", + "\n", + "# # 2. Calculate the percentage for each age group\n", + "# df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "# # 3. Define the logical order for the age groups for plotting\n", + "# age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", + "\n", + "# # 4. Plot a bar chart\n", + "# plt.figure(figsize=(10, 6))\n", + "# sns.barplot(\n", + "# x='Age Group',\n", + "# y='Percentage',\n", + "# data=df_counts,\n", + "# order=age_order, # Use the defined order for chronological display\n", + "# palette='viridis'\n", + "# )\n", + "\n", + "# # Add titles and labels\n", + "# plt.title('Percentage of Dissatisfied Customers by Age Group')\n", + "# plt.xlabel('Age Group')\n", + "# plt.ylabel('Percentage (%)')\n", + "# plt.xticks(rotation=45, ha='right') # Rotate labels for better visibility\n", + "# plt.grid(axis='y', linestyle='--')\n", + "# plt.tight_layout()\n", + "\n", + "# # Display or save the plot\n", + "# plt.show() # Use plt.show() if running in a script/local environment\n", + "# # plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "286b7ffa-a576-49cb-99f1-48dc71657bde", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_21412\\783172777.py:23: FutureWarning: \n", + "\n", + "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", + "\n", + " ax = sns.barplot(\n" + ] + }, + { + "data": { + "image/png": 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Xr27effdds2DBArNixQqzb98+ExkZaaKjo83EiRPNnDlzzL/+9S9TpUqVHOt0ypQpxuFwmOuvv97MnDnTfP755+aaa64xfn5+5ptvvrGmy9zPY2JizLBhw8zcuXPNrFmzrOfdbrcJDQ01gwcPPmetwMVG0w1cQJlvwJctW2YyMjLMsWPHzBdffGHKlStnwsLCzL59+8zSpUuNJPPSSy/5vHbnzp0mODjYDB061Iq1b9/eSDLz5s3zmfbpp582kszcuXPzzCXzTXTWN+fGnL0c9o033rBiMTExJigoyPz2229W7NSpUyYiIsLnxJrfy8u9Xq/JyMgwv/32m5FkPvvsM+u5Zs2amcqVK5u0tDQrduzYMVOmTBmfNyEFWU+5admypYmMjDTHjh2zYm6329SrV89UqlTJakQKculjfqa95ZZbfC69zv6G7eDBg0aSeeWVV/Kcx8cff2wkmTVr1pw3p0wej8dkZGSYp59+2pQpU8an0crr8vLcmu7Q0FDz4IMPnnNZmW96Dhw44BPP/qYuv/vgxo0bjSTz0EMP+UyX+cb2fE13ZhOR30t089u0vPjii0aST1OQXV6Xl3s8HlOxYkVTv3594/F4rPixY8dMZGSkad26dY7lZt/XGzVqZCSZmTNnWrGMjAxTrlw507NnTyuWlJRknE5njg/7MvejrF93kGRKlSplDh8+7DPtwIEDTenSpfOsMy+Z+1DFihXNqVOnrHhqaqqJiIgwV111lRXLPD6uXr3aiq1YscJIMpMnTz7vshYvXmwkmUcffdQYc+Y4U61aNRMTE+Ozv3/55Ze5Ng5JSUk5mu4uXbqYSpUqmaNHj/pMO3DgQBMUFJRjPWV13333GUlm06ZNPvHM41/mv6yX4Waurxo1avh8GFmQ/aWgTXdwcLDPh5Rut9vExcWZmjVr5lmbMcb8/vvvRpJ59tlnfeIffPCBkWTGjx9/ztdnr7l+/fo+6yJz20+fPt2nNknm3Xff9ZnH+PHjjSTz4Ycf+sQzL3NPTk72qbl8+fImNTXViu3bt884nU6TlJRkxfJ7jsh+DC/Itsrv+c6YnE13fs7z2Z3rPJCfpvvZZ5/N9esEWZ06dcpIMl27dvXJ3c/Pz2zevNln2mHDhhmHw5HjXNapUyefdXrixAkTERFhunfvnqOehg0bmubNm1uxzP18+PDheebYpk0b06JFi3PWClxsXF4O2KBly5ZyuVwKCwvTNddco6ioKP3vf/9T+fLl9cUXX8jhcOiOO+6Q2+22/kVFRalhw4Y57uYZHh6ujh07+sT+97//KTY2VldddVWeOXzxxRcqXbq0unfv7rOcRo0aKSoqKsdyGjVqpCpVqliPg4KCFBsbm+ulm7nZv3+/7rvvPlWuXFn+/v5yuVyKiYmRJG3cuFGSdOLECf3www+6/vrrFRAQYL02NDRU3bt3z5F/QdZTVidOnNDy5ct14403KjQ01Ir7+fnpzjvv1K5du2y7EYw5zyV9ERERqlGjhl544QWNHTtWq1evznGn1UaNGikgIEB9+/bV5MmT87ycfv78+brqqqtUqlQp+fn5yeVyafjw4Tp06JD279//l/Jv3ry5Jk2apNGjR2vZsmXWHYj/ivzug5mXAf7rX//yef3NN98sf3//v7z8vyvz0vGbb75ZH374YYF+gWDz5s3as2eP7rzzTjmdZ0+1oaGhuuGGG7Rs2TKfrwpI0jXXXOPzuE6dOnI4HOratasV8/f3V82aNX3+Lr/44gvVq1dPjRo18lnPXbp0yfUOwR07dlR4eLhPrHnz5jpy5Ihuu+02ffbZZ7l+LeRcevbsqaCgIOtxWFiYunfvrsWLF8vj8UiSbrvtNkVGRvpcuv3aa6+pXLlyuV7Kml3mDdQyL+93OBzq3bu3fvvtN59LUBctWiTpzHbL6rbbbvN5fPr0ac2bN089evRQiRIlfNZdt27ddPr06RyXP+fHZ599JpfLZf0rVapUjmmuvfZauVwu6/Ff2V/y68orr1T58uWtx35+frrlllu0detW7dq1K8/X7dmzR5IUGRn5l5abXUJCgvz8/KzHDRo0kKRczzE33HCDz+P58+crJCREN954o08883Ls7Jcgx8fHKywszHpcvnx5RUZGWsv6O+eI/G6rgpzvcpOf87xkz3kgP7JfHt+gQQPFxsb6xBYsWKDLLrtMDRs29InffvvtPo+///57HT58WL169fL5O/R6vbr66qu1cuXKHF+Vyb6PZBUZGVksfjEGxQtNN2CD9957TytXrtTq1au1Z88erV27Vm3atJEk/f777zLGqHz58j5vzFwul5YtW5bjzW6FChVyzP/AgQPWd5Hz8vvvv+vIkSMKCAjIsZx9+/blWE6ZMmVyzCMwMFCnTp06b71er1edO3fWzJkzNXToUM2bN08rVqyw3rBmzuOPP/6was8ue6yg6ymrzOXktu4qVqwoSRfkZ09y89tvvykwMFARERG5Pu9wODRv3jx16dJFzz//vJo0aaJy5crp/vvvt77nVqNGDX3zzTeKjIzUgAEDVKNGDdWoUUOvvvqqNZ8VK1aoc+fOkqR33nlH3333nVauXKnHH39ckvK13XIzY8YM9erVS//973/VqlUrRUREKDExUfv27SvwvPK7D2Zui6ioKJ/X+/v757pfZpf5YVFKSkqBczyXdu3aadasWXK73UpMTFSlSpVUr169XL+XnF1mTXntg16vV3/88YdPPPs+ExAQoBIlSvg0s5nx06dPW49///13rV27Nsc6DgsLkzEmX8eUO++8U++++65+++033XDDDYqMjFSLFi00d+7c89Yq5dx2mbH09HQdP35c0pnjyb333qtp06bpyJEjOnDggD788EPdfffdCgwMPOf8jx07po8++kjNmzdXuXLldOTIER05ckQ9evSQw+GwGnLpzLr39/fPsT6zH2MOHTokt9ut1157Lce669atmySd8ziTud9lbxo7dOiglStXauXKlTk+SMmUfRv8lf0lv/LaNlmXm5vMY0j2/e+v/r1l/1vO3ObZj1UlSpRQyZIlfWKHDh1SVFRUjkYvMjJS/v7+Oeo43/ns75wj8rutCnK+y01+zvMX+jyQn22b+VzlypV94rmtj8ztll322O+//y5JuvHGG3P8LT733HMyxujw4cPnXV6moKCgv3wOBOxSeEMIQDFWp04dNW3aNNfnypYtK4fDoW+//TbXN5rZY9nfZEhSuXLlzjlCkbmcMmXK6Kuvvsr1+ayjAH/Xzz//rJ9++kmTJk1Sr169rPjWrVt9pgsPD5fD4bBOsFllb+oKup6yL8fpdGrv3r05nsscvSlbtuy5i/oLdu/erVWrVql9+/bnHKGNiYmxmoRffvlFH374oUaMGKH09HSNHz9eknTFFVfoiiuukMfj0Q8//KDXXntNDz74oMqXL69bb71VH3zwgVwul7744gufN8V/9yeUypYtq1deeUWvvPKKduzYodmzZ+vRRx/V/v3789yXzjWv/OyDmW+Q9+3bp+joaOt5t9udrw9HunTporfffluzZs3So48+et7pg4KCcv1959warOuuu07XXXed0tLStGzZMiUlJen2229X1apVfX5CKbvMmvLaB51OZ47R5r+qbNmyCg4O9rnxYfbns8rtmCKduRlcnz59dOLECS1evFhPPfWUrrnmGv3yyy/WVSt5ye1DmX379ikgIMBnJLFfv3569tln9e677+r06dNyu9267777zleipk+frpMnT2rFihW5rrdPP/1Uf/zxh8LDw1WmTBm53W4dPnzYp/HOnmN4eLg1sjlgwIBcl1utWrU8c+rUqZP+7//+T7Nnz7YaH0kqXbq0dfzP60Oj7NugIPtLQfZfKe9tc678pLP7TfZmp2nTpoqIiNBnn32mpKSkPPenvyq3+ZUpU0bLly+XMcbn+f3798vtdhf4eP53zhH53VaZuebnfJeb/JznL/R5ID4+Xv7+/po1a1aef5eZ8856cz0p7+12rv0vU+a6fu2116wbz2aX/YOKc+13hw8ftuUcD/wdjHQDF9k111wjY4x2796tpk2b5vhXv379886ja9eu+uWXXzR//vxzLufQoUPyeDy5Lqd27doFzj2vkYnMk1/2Rvitt97yeRwSEqKmTZtq1qxZSk9Pt+LHjx/PcWfZv7OeQkJC1KJFC82cOdMnV6/Xq/fff1+VKlXKcRnc33Xq1CndfffdcrvdGjp0aL5fFxsbqyeeeEL169fXjz/+mON5Pz8/tWjRwrokN3Mah8Mhf39/n8s1T506pSlTpuSYR36vWMiuSpUqGjhwoDp16pRrbueT330w847nU6dO9Xn9hx9+KLfbfd7lXHfddapfv76SkpL0888/5zrN119/bV2eW7VqVe3fv9/nzXB6erq+/vrrPJcRGBio9u3b67nnnpMkrV692opLOf8mateurejoaE2bNs3nKwcnTpzQJ598Yt31+EK45ppr9Ouvv6pMmTK5rueC3pE/JCREXbt21eOPP6709HStX7/+vK+ZOXOmz+j7sWPH9Pnnn+uKK67w2UcrVKigm266SW+88YbGjx+v7t27+3ytJS8TJkxQWFiY5s2bpwULFvj8e+GFF5SWlmbtP+3bt5d05qqNrLLfsbtEiRKKj4/X6tWr1aBBg1zX3bma0qZNm6pz585655139O233563hnMpyP5S0P133rx5PtN6PB7NmDFDNWrUOOdIakxMjIKDg/Xrr7/6xF0ul4YNG6ZNmzZp1KhRub52//79+u67785feD5deeWVOn78eI5m8r333rOeL4i/c47I77YqyPkuN/k5zxfkPJAfUVFRuuuuu/T111/n+PuRznxI/Nxzz+myyy7T9ddff975xcfHa/369frpp5984tOmTfN53KZNG5UuXVobNmzI9e+wadOmPpfon8+2bdtUt27dfE8PXAyMdAMXWZs2bdS3b1/16dNHP/zwg9q1a6eQkBDt3btXS5YsUf369dWvX79zzuPBBx/UjBkzdN111+nRRx9V8+bNderUKS1atEjXXHON4uPjdeutt2rq1Knq1q2bHnjgATVv3lwul0u7du3SggULdN1116lHjx4Fyj3z55jefvtthYWFKSgoSNWqVVNcXJxq1KihRx99VMYYRURE6PPPP8/10tSnn35aCQkJ6tKlix544AF5PB698MILCg0N9RlR+bvrKSkpSZ06dVJ8fLyGDBmigIAAvfHGG/r55581ffr0vzU6s2PHDi1btkxer1dHjx7V6tWrrUtzX3rpJZ9Rr+zWrl2rgQMH6qabblKtWrUUEBCg+fPna+3atdYo7fjx4zV//nwlJCSoSpUqOn36tDWKmfn9voSEBI0dO1a33367+vbtq0OHDunFF1/M9QqA+vXr64MPPtCMGTNUvXp1BQUF5fqhxdGjRxUfH6/bb79dcXFxCgsL08qVK/XVV1+pZ8+eBV5P+d0H69SpozvuuEOvvPKKXC6XrrrqKv3888968cUXc1xmmhs/Pz99+umn6ty5s1q1aqV+/fopPj5eISEh+u233/Txxx/r888/ty7PveWWWzR8+HDdeuuteuSRR3T69Gn95z//sb57nGn48OHatWuXrrzySlWqVElHjhzRq6++KpfLZTV2NWrUUHBwsKZOnao6deooNDRUFStWVMWKFfX888/rX//6l6655hrde++9SktL0wsvvKAjR47o2WefLfD6zMuDDz6oTz75RO3atdNDDz2kBg0ayOv1aseOHUpOTtbDDz+sFi1anHMe99xzj4KDg9WmTRtVqFBB+/btU1JSkkqVKmV9t/1c/Pz81KlTJw0ePFher1fPPfecUlNTrZ8NyuqBBx6w8pk4ceJ55/3zzz9rxYoV6tevX477W0hnjhUvvfSSJkyYoIEDB+rqq69WmzZt9PDDDys1NVWXX365li5dajVoWb+H++qrr6pt27a64oor1K9fP1WtWlXHjh3T1q1b9fnnn5+z4ZGk999/X126dNFVV12l3r17q0uXLoqMjFRqaqrWrl2rb775Jl/7sNPpzPf+kt/9N1PZsmXVsWNHPfnkkwoJCdEbb7yhTZs2nfdnwwICAnL9WS9JeuSRR7Rx40Y99dRTWrFihW6//XZVrlxZR48e1eLFi/X2229r5MiR1teq/q7ExES9/vrr6tWrl7Zv36769etryZIlGjNmjLp163be7z3n5q+eIwqyrfJ7vstNfs7zBTkP5NfYsWO1efNm3XHHHVq8eLG6d++uwMBALVu2TC+++KLCwsL0ySef+DT656rh3XffVUJCgkaPHq3y5ctr6tSpPj95Jp35nvtrr72mXr166fDhw7rxxhsVGRmpAwcO6KefftKBAwf05ptv5iv/Q4cOacuWLRo0aNBfqh+wzUW/dRtQjOX1k2G5effdd02LFi1MSEiICQ4ONjVq1DCJiYnmhx9+sKZp3769ueyyy3J9/R9//GEeeOABU6VKFeNyuUxkZKRJSEjwuZNuRkaGefHFF03Dhg1NUFCQCQ0NNXFxcebee+81W7ZssaaLiYkxCQkJOZaR291OX3nlFVOtWjXj5+fnc9fmDRs2mE6dOpmwsDATHh5ubrrpJrNjx44cdws2xphPP/3U1K9f3wQEBJgqVaqYZ5991tx///0mPDz8L62nvHz77bemY8eO1mtbtmxpPv/8c59p/srdyzP/+fn5mfDwcHP55ZebBx980Kxfvz7Ha7Lf+fb33383vXv3NnFxcSYkJMSEhoaaBg0amJdfftm6s+/SpUtNjx49TExMjAkMDDRlypQx7du3N7Nnz86xbmrXrm0CAwNN9erVTVJSkpkwYYKRZFJSUqzptm/fbjp37mzCwsKsn1rJWk/mNjx9+rS57777TIMGDUzJkiVNcHCwqV27tnnqqafMiRMnrPnl9+7lxuR/H0xLSzMPP/ywiYyMNEFBQaZly5Zm6dKlOe7oey5Hjhwxo0aNMk2aNDGhoaHG5XKZKlWqmDvuuMN89913PtPOmTPHNGrUyAQHB5vq1aubcePG5bj78xdffGG6du1qoqOjTUBAgImMjDTdunXz+UkgY87cpT0uLs64XK4c+/usWbNMixYtTFBQkAkJCTFXXnlljlzyWp+9evUyISEhOerM7bhw/Phx88QTT5jatWubgIAA62ewHnroIZ87V0syAwYMyDHPyZMnm/j4eFO+fHkTEBBgKlasaG6++Wazdu3aPNb2GZn70HPPPWdGjhxpKlWqZAICAkzjxo3P+VNaVatWNXXq1DnnvDM9+OCD572b/6OPPmokmVWrVhljjDl8+LDp06ePKV26tClRooTp1KmTWbZsmZFkXn311Rw13HXXXSY6Otq4XC5Trlw507p1azN69Oh85Xf69Gnz2muvmbZt25rSpUsbf39/ExERYa644grz3HPPmUOHDvks61zHm/zsL8bkb/815uz2fuONN0yNGjWMy+UycXFxZurUqfmqbcKECcbPz8/s2bMn1+c/++wzk5CQYMqVK2f8/f1NeHi4iY+PN+PHj7fu2H2umrP/veS1zxtjzKFDh8x9991nKlSoYPz9/U1MTIx57LHHcvxqQV77eG7HkvycI3L7yTBj8r+t8nu+yy2//Jzn83seyM/dyzOlp6eb119/3bRo0cKEhoaawMBAU7t2bTN06FBz8ODBHNPn9R7CmLPvDYKCgkxERIT597//bT777LNc1+miRYtMQkKCiYiIMC6Xy0RHR5uEhASfn7fL63iZacKECcblcp33Z0WBi81hzHlutQsANsvIyFCjRo0UHR2t5OTkwk4HgI3Wrl2rhg0b6vXXX1f//v0v2nKnTZumf/3rX/ruu+/UunXri7bcwuRwODRgwACNGzfuL73+9OnTqlKlih5++GENGzbsAmf3z8T5zl5XXHGFqlSpkuPrSkBh4/JyABfdv//9b3Xq1Mm6jHX8+PHauHGjz925ARQvv/76q3777Tf93//9nypUqGD93JMdpk+frt27d6t+/fpyOp1atmyZXnjhBbVr1+4f03BfCEFBQRo5cqRGjBihgQMHKiQkpLBTKnI43108ixcv1sqVKzV58uTCTgXIgaYbwEV37NgxDRkyRAcOHJDL5VKTJk00Z86cv/S9PABFw6hRozRlyhTVqVNHH3300QW7kVxuwsLC9MEHH2j06NE6ceKE1eSPHj3atmUWV3379tWRI0e0bdu2fN3oE7443108hw4d0nvvvafq1asXdipADlxeDgAAAACATfjJMAAAAAAAbELTDQAAAACATWi6AQAAAACwSbG/kZrX69WePXsUFhYmh8NR2OkAAAAAAIoBY4yOHTumihUryunMezy72Dfde/bsUeXKlQs7DQAAAABAMbRz505VqlQpz+eLfdMdFhYm6cyKKFmyZCFnAwAAAAAoDlJTU1W5cmWr58xLsW+6My8pL1myJE03AAAAAOCCOt/XmLmRGgAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNN1AEJCUlqVmzZgoLC1NkZKSuv/56bd682Wea3r17y+Fw+Pxr2bLlOec7c+ZMNW3aVKVLl1ZISIgaNWqkKVOm+EwzdepUVa5cWREREXrkkUd8ntu+fbtiY2OVmpp6YQoFAAAAihn/wk4AwPktWrRIAwYMULNmzeR2u/X444+rc+fO2rBhg0JCQqzprr76ak2cONF6HBAQcM75RkRE6PHHH1dcXJwCAgL0xRdfqE+fPoqMjFSXLl108OBB3X333Zo0aZKqV6+uhIQEdejQQQkJCZKkfv366dlnn1XJkiXtKRwAAAAo4mi6gSLgq6++8nk8ceJERUZGatWqVWrXrp0VDwwMVFRUVL7n26FDB5/HDzzwgCZPnqwlS5aoS5cu2rZtm0qVKqVbbrlFkhQfH68NGzYoISFB06ZNU0BAgHr27PnXCwMAAACKOS4vB4qgo0ePSjozUp3VwoULFRkZqdjYWN1zzz3av39/vudpjNG8efO0efNmq5GvVauWTp48qdWrV+vw4cNauXKlGjRooMOHD2v48OEaN27chSsKAAAAKIYY6QaKGGOMBg8erLZt26pevXpWvGvXrrrpppsUExOjlJQUPfnkk+rYsaNWrVqlwMDAPOd39OhRRUdHKy0tTX5+fnrjjTfUqVMnSVJ4eLgmT56sxMREnTp1SomJierSpYvuuusuDRo0SCkpKbr22muVkZGhESNG6MYbb7S9fgAAAKAocRhjTGEnYafU1FSVKlVKR48e5XunKBYGDBigL7/8UkuWLFGlSpXynG7v3r2KiYnRBx98cM5LwL1er7Zt26bjx49r3rx5GjVqlGbNmpXj0vNMCxcu1COPPKJFixapZs2amj59uqKiotS8eXNt2bJFkZGRf7dEAAAA4JKX316TkW6gCBk0aJBmz56txYsXn7PhlqQKFSooJiZGW7ZsOed0TqdTNWvWlCQ1atRIGzduVFJSUq5Nd1pamvr376/3339fW7duldvtVvv27SVJsbGxWr58ubp37/7XigMAAACKIb7TDRQBxhgNHDhQM2fO1Pz581WtWrXzvubQoUPauXOnKlSoUOBlpaWl5frcqFGj1LVrVzVp0kQej0dut9t6LiMjQx6Pp0DLAgAAAIo7RrqBImDAgAGaNm2aPvvsM4WFhWnfvn2SpFKlSik4OFjHjx/XiBEjdMMNN6hChQravn27/u///k9ly5ZVjx49rPkkJiYqOjpaSUlJks78/nfTpk1Vo0YNpaena86cOXrvvff05ptv5shh/fr1mjFjhtasWSNJiouLk9Pp1IQJExQVFaVNmzapWbNm9q8MAAAAoAih6QaKgMwmOPsl3xMnTlTv3r3l5+endevW6b333tORI0dUoUIFxcfHa8aMGQoLC7Om37Fjh5zOsxe4nDhxQv3799euXbsUHBysuLg4vf/++9ZPhGUyxqhv3756+eWXrd8FDw4O1qRJkzRgwAClpaVp3Lhxio6OtmkNAAAAAEUTN1IDAAAAAKCA8ttr8p1uAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE//CXHhSUpJmzpypTZs2KTg4WK1bt9Zzzz2n2rVrW9P07t1bkydP9nldixYttGzZsoudLv7BOt/ydGGngHxInjG8sFMAAAAAfBTqSPeiRYs0YMAALVu2THPnzpXb7Vbnzp114sQJn+muvvpq7d271/o3Z86cQsoYAAAAAID8K9SR7q+++srn8cSJExUZGalVq1apXbt2VjwwMFBRUVEXOz0AAAAAAP6WS+o73UePHpUkRURE+MQXLlyoyMhIxcbG6p577tH+/fsLIz0AAAAAAAqkUEe6szLGaPDgwWrbtq3q1atnxbt27aqbbrpJMTExSklJ0ZNPPqmOHTtq1apVCgwMzDGftLQ0paWlWY9TU1MlSRkZGcrIyJAkOZ1O+fn5yePxyOv1WtNmxt1ut4wxVtzPz09OpzPPeOZ8M/n7n1mtbrc7X3GXyyWv1yuPx2PFHA6H/P3984znlTs12VOTy9+pDLdXDofk7+f7WVWG2yun0yE/p8OKGSO5PTnjXmPk8Rj5+TnkdJyNe7xGXq+Rv59TWcJW3OXvu0y3xytjlO/4uXIvTjVlZGQUu31PKn5/T9RETdRETdRETdRETcWhpux15OWSaboHDhyotWvXasmSJT7xW265xfr/evXqqWnTpoqJidGXX36pnj175phPUlKSRo4cmSOenJysEiVKSJKqVKmixo0ba+3atdqxY4c1Te3atRUXF6cVK1bowIEDVrxRo0aKiYnR4sWLdezYMSveqlUrRUZGKjk52WdHiI+PV3BwcI7vnnfr1k2nTp3SggULrJi/v78SEhJ08OBBLV261IqHhYWpY8eO2rlzp9asWWPFy5Urp9atW2vLli3avHmzFacme2vq3aOu3vnoZ1WKCtO18dWt+OEjpzV9zmbVrhauji0qW/Ede4/p8wXbdPllkWpe/+xXIzZsPaQFK3ap3eXRqluzjBVfsW6fVq77XV3bVVWVCmFWfP7yndr462Hd2LmWIkoHWfHZC7Zp595j6t2jrgJcflZ8+pebdOxEhvreXN+nprc/XKewEJduS4izYukZnmJXU3JycrHb94rj3xM1URM1URM1URM1UVNxqOnkyZPKD4fJ2r4XkkGDBmnWrFlavHixqlWrdt7pa9WqpbvvvlvDhg3L8VxuI92VK1fWwYMHVbJkSUl8UkNNBa/p+t7PFbtR4fPFi2JNsyYNK3b7nlT8/p6oiZqoiZqoiZqoiZqKQ02pqakqW7asjh49avWauSnUptsYo0GDBunTTz/VwoULVatWrfO+5tChQ4qOjtbbb7+txMTE806fmpqqUqVKnXdFAOfCT4YVDfxkGAAAAC6W/PaahXojtQEDBuj999/XtGnTFBYWpn379mnfvn06deqUJOn48eMaMmSIli5dqu3bt2vhwoXq3r27ypYtqx49ehRm6gAAAAAAnFehfqf7zTfflCR16NDBJz5x4kT17t1bfn5+Wrdund577z0dOXJEFSpUUHx8vGbMmKGwsLBc5ggAAAAAwKWjUJvu813ZHhwcrK+//voiZQMAAAAAwIV1Sf1ONwAAAAAAxQlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AKGKSkpLUrFkzhYWFKTIyUtdff702b97sM40xRiNGjFDFihUVHBysDh06aP369eed95EjRzRgwABVqFBBQUFBqlOnjubMmWM9P3XqVFWuXFkRERF65JFHfF67fft2xcbGKjU19cIUCgAAUAzQdANAEbNo0SINGDBAy5Yt09y5c+V2u9W5c2edOHHCmub555/X2LFjNW7cOK1cuVJRUVHq1KmTjh07lud809PT1alTJ23fvl0ff/yxNm/erHfeeUfR0dGSpIMHD+ruu+/Wiy++qK+//lqTJ0/Wl19+ab2+X79+evbZZ1WyZEn7igcAAChi/As7AQBAwXz11Vc+jydOnKjIyEitWrVK7dq1kzFGr7zyih5//HH17NlTkjR58mSVL19e06ZN07333pvrfN99910dPnxY33//vVwulyQpJibGen7btm0qVaqUbrnlFklSfHy8NmzYoISEBE2bNk0BAQHW8gAAAHAGI90AUMQdPXpUkhQRESFJSklJ0b59+9S5c2drmsDAQLVv317ff/99nvOZPXu2WrVqpQEDBqh8+fKqV6+exowZI4/HI0mqVauWTp48qdWrV+vw4cNauXKlGjRooMOHD2v48OEaN26cjVUCAAAUTTTdAFCEGWM0ePBgtW3bVvXq1ZMk7du3T5JUvnx5n2nLly9vPZebbdu26eOPP5bH49GcOXP0xBNP6KWXXtIzzzwjSQoPD9fkyZOVmJio5s2bKzExUV26dNGQIUM0aNAgpaSkqHHjxqpXr54+/vhjmyoGAAAoWri8HACKsIEDB2rt2rVasmRJjuccDofPY2NMjlhWXq9XkZGRevvtt+Xn56fLL79ce/bs0QsvvKDhw4dLknr06KEePXpYr1m4cKHWrVuncePGqWbNmpo+fbqioqLUvHlztWvXTpGRkReoUgAAgKKJkW4AKKIGDRqk2bNna8GCBapUqZIVj4qKkqQco9r79+/PMfqdVYUKFRQbGys/Pz8rVqdOHe3bt0/p6ek5pk9LS1P//v311ltvaevWrXK73Wrfvr1q166t2NhYLV++/O+WCAAAUOTRdANAEWOM0cCBAzVz5kzNnz9f1apV83m+WrVqioqK0ty5c61Yenq6Fi1apNatW+c53zZt2mjr1q3yer1W7JdfflGFChUUEBCQY/pRo0apa9euatKkiTwej9xut/VcRkaG9V1wAACAfzIuLweAImbAgAGaNm2aPvvsM4WFhVkj2qVKlVJwcLAcDocefPBBjRkzRrVq1VKtWrU0ZswYlShRQrfffrs1n8TEREVHRyspKUnSmZ/8eu211/TAAw9o0KBB2rJli8aMGaP7778/Rw7r16/XjBkztGbNGklSXFycnE6nJkyYoKioKG3atEnNmjWzf2UAAABc4mi6AaCIefPNNyVJHTp08IlPnDhRvXv3liQNHTpUp06dUv/+/fXHH3+oRYsWSk5OVlhYmDX9jh075HSeveCpcuXKSk5O1kMPPaQGDRooOjpaDzzwgIYNG+azHGOM+vbtq5dfflkhISGSpODgYE2aNEkDBgxQWlqaxo0bZ/2+NwAAwD+ZwxhjCjsJO6WmpqpUqVI6evSoSpYsWdjpoIjqfMvThZ0C8iF5xvDCTgEAAAD/EPntNflONwAAAAAANqHpBgAAAADAJjTdAAAAAADYhKYbAAAAAACb0HQDAAAAAGATmm4AAAAAAGxC0w0AAAAAgE38CzsBAChqWt0/qrBTwHks/c+ThZ0CAACAJEa6AQAAAACwDU03AAAAAAA2oekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJsUatOdlJSkZs2aKSwsTJGRkbr++uu1efNmn2mMMRoxYoQqVqyo4OBgdejQQevXry+kjAEAAAAAyL9CbboXLVqkAQMGaNmyZZo7d67cbrc6d+6sEydOWNM8//zzGjt2rMaNG6eVK1cqKipKnTp10rFjxwoxcwAAAAAAzq9Qf6f7q6++8nk8ceJERUZGatWqVWrXrp2MMXrllVf0+OOPq2fPnpKkyZMnq3z58po2bZruvffewkgbAAAAAIB8KdSmO7ujR49KkiIiIiRJKSkp2rdvnzp37mxNExgYqPbt2+v777/PtelOS0tTWlqa9Tg1NVWSlJGRoYyMDEmS0+mUn5+fPB6PvF6vNW1m3O12yxhjxf38/OR0OvOMZ843k7//mdXqdrvzFXe5XPJ6vfJ4PFbM4XDI398/z3heuVOTPTW5/J3KcHvlcEj+fr4XiGS4vXI6HfJzOqyYMZLbkzPuNUYej5Gfn0NOx9m4x2vk9Rr5+zmVJWzFXf6+y3R7vDJG+Y6fK/fiVFNGRsZF2fdcToccWYpye428xsjl51SWUpXhPZN7QPb16/HKKGc83eOVQ5Irt7hDcjnPxs2f83E6HPL32U5GGV4jP0fO7eT2Gvk7c24njzHFriZJHPeoiZqoiZqoiZqoydaasteRl0um6TbGaPDgwWrbtq3q1asnSdq3b58kqXz58j7Tli9fXr/99luu80lKStLIkSNzxJOTk1WiRAlJUpUqVdS4cWOtXbtWO3bssKapXbu24uLitGLFCh04cMCKN2rUSDExMVq8eLHPZe2tWrVSZGSkkpOTfXaE+Ph4BQcHa86cOT45dOvWTadOndKCBQusmL+/vxISEnTw4EEtXbrUioeFhaljx47auXOn1qxZY8XLlSun1q1ba8uWLT7ff6cme2vq3aOu3vnoZ1WKCtO18dWt+OEjpzV9zmbVrhauji0qW/Ede4/p8wXbdPllkWpeP8qKb9h6SAtW7FK7y6NVt2YZK75i3T6tXPe7urarqioVwqz4/OU7tfHXw7qxcy1FlA6y4rMXbNPOvcfUu0ddBbj8rPj0Lzfp2IkM9b25vk9Nb3+4TmEhLt2WEGfF0jM8xa6m5OTki7Lv9WhQVdXLnK1pzsZdWrvnsBKb1lS50LM1zVi9TSmHj2tA2zoK9D9b03+XbVbq6QwN7lDPp6axC39WySCX7m5Z24qluT16edF6VQ0P1S2Nz26nA8dPa8LyX1SvQri61alkxbcdOqYP16SoVdVIta1+9tj50+7D+t+mXeoUG62G0RFWfMm237Uk5fdiV5MkjnvURE3URE3URE3UZGtNJ0+eVH44TNb2vRANGDBAX375pZYsWaJKlc682fr+++/Vpk0b7dmzRxUqVLCmveeee7Rz584cl6dLuY90V65cWQcPHlTJkiUl8UkNNRW8put7P1fsRoXPFy+KNc2aNOyi7HvtHhxdrEaFi+NI95JXn+C4R03URE3URE3URE221pSamqqyZcvq6NGjVq+Zm0tipHvQoEGaPXu2Fi9ebDXckhQVdWY0bd++fT5N9/79+3OMfmcKDAxUYGBgjrjL5ZLL5fKJ+fn5yc/PL8e0mRs3v/Hs8/0rcafTKafTme94XrlTkz01ZbjP/CEac/b/s/L+2UjmN+7xGHmUM+725Jx31uX/nXheuRenmjK3md37XobXSLnUmpFHrekFiJu84ib3uNcYpXty2R5/fhiSnTuv3IthTRz3qCmvODVRk0RNeeVY0Dg1UZP0z60pr3xz5JSvqWxijNHAgQM1c+ZMzZ8/X9WqVfN5vlq1aoqKitLcuXOtWHp6uhYtWqTWrVtf7HQBAAAAACiQQh3pHjBggKZNm6bPPvtMYWFh1ne4S5UqpeDgYDkcDj344IMaM2aMatWqpVq1amnMmDEqUaKEbr/99sJMHQAAAACA8yrUpvvNN9+UJHXo0MEnPnHiRPXu3VuSNHToUJ06dUr9+/fXH3/8oRYtWig5OVlhYWECAAAAAOBSVqhNd37u4eZwODRixAiNGDHC/oQAAAAAALiACvU73QAAAAAAFGc03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwCAImzx4sXq3r27KlasKIfDoVmzZuWYZuPGjbr22mtVqlQphYWFqWXLltqxY0ee88zIyNDTTz+tGjVqKCgoSA0bNtRXX33lM83UqVNVuXJlRURE6JFHHvF5bvv27YqNjVVqauoFqREAgKKMphsAgCLsxIkTatiwocaNG5fr87/++qvatm2ruLg4LVy4UD/99JOefPJJBQUF5TnPJ554Qm+99ZZee+01bdiwQffdd5969Oih1atXS5IOHjyou+++Wy+++KK+/vprTZ48WV9++aX1+n79+unZZ59VyZIlL2yxAAAUQf6FnQAAAPjrunbtqq5du+b5/OOPP65u3brp+eeft2LVq1c/5zynTJlivU4600R//fXXeumll/T+++9r27ZtKlWqlG655RZJUnx8vDZs2KCEhARNmzZNAQEB6tmz5wWoDgCAoq/ATff27dv17bffavv27Tp58qTKlSunxo0bq1WrVuf81BwAAFxcXq9XX375pYYOHaouXbpo9erVqlatmh577DFdf/31eb4uLS0txzk9ODhYS5YskSTVqlVLJ0+e1OrVqxUTE6OVK1fqrrvu0uHDhzV8+HAtWLDAzrIAAChS8n15+bRp09SyZUtVr15djzzyiGbNmqVvv/1W//3vf3X11VerfPny6t+/v3777Tc78wUAAPm0f/9+HT9+XM8++6yuvvpqJScnq0ePHurZs6cWLVqU5+u6dOmisWPHasuWLfJ6vZo7d64+++wz7d27V5IUHh6uyZMnKzExUc2bN1diYqK6dOmiIUOGaNCgQUpJSVHjxo1Vr149ffzxxxerXAAALkn5Gulu0qSJnE6nevfurQ8//FBVqlTxeT4tLU1Lly7VBx98oKZNm+qNN97QTTfdZEvCAAAgf7xeryTpuuuu00MPPSRJatSokb7//nuNHz9e7du3z/V1r776qu655x7FxcXJ4XCoRo0a6tOnjyZOnGhN06NHD/Xo0cN6vHDhQq1bt07jxo1TzZo1NX36dEVFRal58+Zq166dIiMjbawUAIBLV75GukeNGqUffvhBAwcOzNFwS1JgYKA6dOig8ePHa+PGjapateqFzhMAABRQ2bJl5e/vr7p16/rE69Spc867l5crV06zZs3SiRMn9Ntvv2nTpk0KDQ1VtWrVcp0+LS1N/fv311tvvaWtW7fK7Xarffv2ql27tmJjY7V8+fILWhcAAEVJvpruhISEfM+wbNmyatas2V9OCAAAXBgBAQFq1qyZNm/e7BP/5ZdfFBMTc97XBwUFKTo6Wm63W5988omuu+66XKcbNWqUunbtqiZNmsjj8cjtdlvPZWRkyOPx/L1CAAAowv7W3cu//PJLLVy4UB6PR23atNENN9xwofICAAD5cPz4cW3dutV6nJKSojVr1igiIkJVqlTRI488oltuuUXt2rVTfHy8vvrqK33++edauHCh9ZrExERFR0crKSlJkrR8+XLt3r1bjRo10u7duzVixAh5vV4NHTo0x/LXr1+vGTNmaM2aNZKkuLg4OZ1OTZgwQVFRUdq0aRMfxgMA/tH+ctP95JNPaubMmUpISJAxRg899JAWLFiQ5++EAgCAC++HH35QfHy89Xjw4MGSpF69emnSpEnq0aOHxo8fr6SkJN1///2qXbu2PvnkE7Vt29Z6zY4dO+R0nr347fTp03riiSe0bds2hYaGqlu3bpoyZYpKly7ts2xjjPr27auXX35ZISEhks7c5XzSpEkaMGCA0tLSNG7cOEVHR9u4BgAAuLQ5jDEmPxOuWrVKl19+ufU4NjZWP/30k4KDgyVJP/30kzp06KA//vjDnkz/otTUVJUqVUpHjx5VyZIlCzsdFFGdb3m6sFNAPiTPGH5RltPq/lEXZTn465b+58nCTgEAABRz+e018/2TYX379tWDDz6okydPSpKqV6+usWPHavPmzVq3bp3efPNNxcbG/v3MAQAAAAAoJvLddK9YsUJRUVFq0qSJPv/8c7377rv68ccf1bp1a11xxRXatWuXpk2bZmeuAAAAAAAUKfn+Trefn58effRR3XzzzerXr59CQkI0btw4VaxY0c78AAAAAAAosvI90p2pevXq+vrrr3X99derXbt2ev311+3ICwAAAACAIi/fTffRo0c1bNgwde/eXU888YR69uyp5cuXa8WKFWrZsqXWrVtnZ54AAAAAABQ5+W66e/XqpWXLlikhIUGbN29Wv379VKZMGU2ePFnPPPOMbr75Zg0bNszOXAEAAAAAKFLy/Z3uefPmafXq1apZs6buuece1axZ03ruyiuv1I8//qhRo/gZHQAAAAAAMuW76a5Vq5befvtt3X333Zo7d65iYmJ8ng8ODtaYMWMueIIAAFzKGo0eUdgp4DzWPDGisFMAAPyD5fvy8nfffVfz589X48aNNW3aNL355pt25gUAAAAAQJGX75HuRo0a6YcffrAzFwAAAAAAipUC/2RYfhhj7JgtAAAAAABFSr6a7jp16mjatGlKT08/53RbtmxRv3799Nxzz12Q5AAAAAAAKMrydXn566+/rmHDhmnAgAHq3LmzmjZtqooVKyooKEh//PGHNmzYoCVLlmjDhg0aOHCg+vfvb3feAAAAAABc8vLVdHfs2FErV67U999/rxkzZmjatGnavn27Tp06pbJly6px48ZKTEzUHXfcodKlS9ucMgAAAAAARUO+b6QmSa1bt1br1q3tygUAAAAAgGLFlhupAQAAAAAAmm4AAAAAAGxD0w0AAAAAgE1ougEAAAAAsAlNNwAAAAAANvlLTfevv/6qJ554Qrfddpv2798vSfrqq6+0fv36C5ocAAAAAABFWYGb7kWLFql+/fpavny5Zs6cqePHj0uS1q5dq6eeeuqCJwgAAAAAQFFV4Kb70Ucf1ejRozV37lwFBARY8fj4eC1duvSCJgcAAAAAQFFW4KZ73bp16tGjR454uXLldOjQoQuSFAAAAAAAxUGBm+7SpUtr7969OeKrV69WdHT0BUkKAAAAAIDioMBN9+23365hw4Zp3759cjgc8nq9+u677zRkyBAlJibakSMAAAAAAEVSgZvuZ555RlWqVFF0dLSOHz+uunXrql27dmrdurWeeOIJO3IEAAAAAKBI8i/oC1wul6ZOnaqnn35aq1evltfrVePGjVWrVi078gMAAAAAoMgqcNOdqUaNGqpRo8aFzAUAAAAAgGKlwE334MGDc407HA4FBQWpZs2auu666xQREfG3kwMAAAAAoCgrcNO9evVq/fjjj/J4PKpdu7aMMdqyZYv8/PwUFxenN954Qw8//LCWLFmiunXr2pEzAAAAAABFQoFvpHbdddfpqquu0p49e7Rq1Sr9+OOP2r17tzp16qTbbrtNu3fvVrt27fTQQw/ZkS8AAAAAAEVGgZvuF154QaNGjVLJkiWtWMmSJTVixAg9//zzKlGihIYPH65Vq1add16LFy9W9+7dVbFiRTkcDs2aNcvn+d69e8vhcPj8a9myZUFTBgAAAACgUBS46T569Kj279+fI37gwAGlpqZKkkqXLq309PTzzuvEiRNq2LChxo0bl+c0V199tfbu3Wv9mzNnTkFTBgAAAACgUBT4O93XXXed7rrrLr300ktq1qyZHA6HVqxYoSFDhuj666+XJK1YsUKxsbHnnVfXrl3VtWvXc04TGBioqKiogqYJAAAAAEChK/BI91tvvaUrr7xSt956q2JiYlSlShXdeuutuvLKKzV+/HhJUlxcnP773/9ekAQXLlyoyMhIxcbG6p577sl1lB0AAAAAgEtRgUe6Q0ND9c477+jll1/Wtm3bZIxRjRo1FBoaak3TqFGjC5Jc165dddNNNykmJkYpKSl68skn1bFjR61atUqBgYG5viYtLU1paWnW48xL3jMyMpSRkSFJcjqd8vPzk8fjkdfrtabNjLvdbhljrLifn5+cTmee8cz5ZvL3P7Na3W53vuIul0ter1cej8eKORwO+fv75xnPK3dqsqcml79TGW6vHA7J38/3s6oMt1dOp0N+TocVM0Zye3LGvcbI4zHy83PI6Tgb93iNvF4jfz+nsoStuMvfd5luj1fGKN/xc+VenGrKyMi4KPuey3nmHhNWjl4jrzFy+TmVpVRleM/kHpB9/Xq8MsoZT/d45ZDkyi3ukFzOs3Hz53ycDof8fbaTUYbXyM+Rczu5vUb+zpzbyWNMsatJ0kU7RgT+WUOa1yunctaU7vXKz+GQvyNr7lKGyRn3GCO3MfJ3OOSXdXuYP7eTw6ksq8CKBzhzbidvltwypXvPbKfs8TTvme0UkEu8ONSUddsWt/NT9pq+/fZbvfTSS1q9erX27t2rTz75RN27d7emHTVqlD788EPt3LlTAQEBatKkiZ5++mm1bNkyz5q8Xq+eeeYZTZkyRbt371ZsbKyeffZZdevWzapp2rRpeuKJJ3TixAn9+9//1pgxY6x5bN++XQkJCVq5cqVKlChR4JqK43aiJmqipuJRU/Y68lLgpjtTaGioGjRo8Fdfni+33HKL9f/16tVT06ZNFRMToy+//FI9e/bM9TVJSUkaOXJkjnhycrJ1oK9SpYoaN26stWvXaseOHdY0tWvXVlxcnFasWKEDBw5Y8UaNGikmJkaLFy/WsWPHrHirVq0UGRmp5ORknx0hPj5ewcHBOb5/3q1bN506dUoLFiywYv7+/kpISNDBgwe1dOlSKx4WFqaOHTtq586dWrNmjRUvV66cWrdurS1btmjz5s1WnJrsral3j7p656OfVSkqTNfGV7fih4+c1vQ5m1W7Wrg6tqhsxXfsPabPF2zT5ZdFqnn9s1+P2LD1kBas2KV2l0erbs0yVnzFun1aue53dW1XVVUqhFnx+ct3auOvh3Vj51qKKB1kxWcv2Kade4+pd4+6CnD5WfHpX27SsRMZ6ntzfZ+a3v5wncJCXLotIc6KpWd4il1NycnJF2Xf69GgqqqXOVvTnI27tHbPYSU2ralyoWdrmrF6m1IOH9eAtnUU6H+2pv8u26zU0xka3KGeT01jF/6skkEu3d2ythVLc3v08qL1qhoeqlsan91OB46f1oTlv6hehXB1q1PJim87dEwfrklRq6qRalu9vBX/afdh/W/TLnWKjVbD6AgrvmTb71qS8nuxq0nSRTtG/N9lDXXa41HShrWqFhqmxGo1rWn3nz6l17dsUsPSEbquUhUrvvVYqqZs/1VXlCuv+PIVrPiqwwc1e/dOdatYSZdHlLXiC37fq4X79+nWmGqqGXb2Rqaf7dqhH/84pHtqxCoyKNiKv5eyVb8eP6bBcfUU5Hd2O437ZaNSM9L1f5c19KlpzPqfVNIVoIGxdaxYcaopcxsWx/NT9ppWrVqlkJAQ3XvvvRoxYoQOHjzoMx+n06lx48bJGKNNmzZp9uzZ6ty5sz7//HN17Ngx15omTpyod999V/fdd58qVaqk1atXq2fPnlq6dKn++OMP7d69W3379tX999+vq666SnfeeadCQkLUuHFjSdLTTz+t4cOHq0SJEv/Y9xHURE3UVDxrOnnypPLDYbK27/m0cuVKffTRR9qxY0eOG6bNnDmzoLM7k4jDoU8//dT6XnheatWqpbvvvlvDhg3L9fncRrorV66sgwcPWndc55MaaipoTdf3fq7YjQqfL14Ua5o1adhF2ffaPTi6WI0KF8eR7iWvPnHRjhFtX0iSVHxGhbPHi0NNSx55zIoXt/PTuWpyuVw5Rrqz15SamqqyZcvq66+/VufOnXOtqXLlynr00UfVr18/K37jjTcqLCxMkyZN0ooVK9SzZ0/t3LlTfn5+uu2229S4cWM9/PDDmj59uj766CPNnj37gtRUHLcTNVETNRXdmjKPoUePHvX5da/sCjzS/cEHHygxMVGdO3fW3Llz1blzZ23ZskX79u1Tjx49Cjq7Ajl06JB27typChUq5DlNYGBgrpeeu1wuuVwun5ifn5/8snxanilz4+Y3nn2+fyXudDrlzPaG4VzxvHKnJntqynCf+UM05uz/Z+X9s5HMb9zjMfIoZ9ztyTnvrMv/O/G8ci9ONWVuM7v3vQyvkXKpNSOPWtMLEDd5xU3uca8xSvfksj3+/DAkO3deuRfDmi7WMSIty4nam+1xJs+fjWR+4+4/G9XsMow3t1KVnssys+d2vrjJI14casq+DYvT+SnTuWrKbfrMN5oTJ05UqVKl1KRJEyuevaa0tDSFhIT4zKdEiRJasmSJ/P39VadOHZ08eVI///yzYmJitHLlSt111106duyYnn76aS1YsMD6UO+f+j4iEzVRk0RNeeVY0PilUFNe+ebIKV9TZTFmzBi9/PLL+uKLLxQQEKBXX31VGzdu1M0336wqVaqcfwZZHD9+XGvWrLGG/1NSUrRmzRrt2LFDx48f15AhQ7R06VJt375dCxcuVPfu3VW2bFnbm3sAAIDi6osvvlBoaKiCgoL08ssva+7cuSpbtmye03fp0kVjx47Vli1b5PV6NXfuXH322Wfau3evJCk8PFyTJ09WYmKimjdvrsTERHXp0kVDhgzRoEGDlJKSosaNG6tevXr6+OOPL1aZAHDJKPBI96+//qqEhARJZ0aVT5w4IYfDoYceekgdO3bM9fvUefnhhx8UHx9vPR48eLAkqVevXnrzzTe1bt06vffeezpy5IgqVKig+Ph4zZgxQ2FhYXnNEgAAAOcQHx+vNWvW6ODBg3rnnXd08803a/ny5YqMjMx1+ldffVX33HOP4uLi5HA4VKNGDfXp00cTJ060punRo4fPoMjChQu1bt06jRs3TjVr1tT06dMVFRWl5s2bq127dnkuCwCKowI33REREdYXx6Ojo/Xzzz+rfv36OnLkSL6/SJ6pQ4cOOtdXyr/++uuCpgcAAIBzCAkJUc2aNVWzZk21bNlStWrV0oQJE/TYY4/lOn25cuU0a9YsnT59WocOHVLFihX16KOPqlq1arlOn5aWpv79++v999/X1q1b5Xa71b59e0lSbGysli9f7vM9cwAo7gp8efkVV1yhuXPnSpJuvvlmPfDAA7rnnnt022236corr7zgCQIAAMA+xhifm9DmJSgoSNHR0XK73frkk0903XXX5TrdqFGj1LVrVzVp0kQej8fnBkgZGRk+NzgCgH+CAo90jxs3TqdPn5YkPfbYY3K5XFqyZIl69uypJ5988oInCAAAgPw5fvy4tm7daj3OvF9ORESEypQpo2eeeUbXXnutKlSooEOHDumNN97Qrl27dNNNN1mvSUxMVHR0tJKSztyZf/ny5dq9e7caNWqk3bt3a8SIEfJ6vRo6dGiO5a9fv14zZsyw7tcTFxcnp9OpCRMmKCoqSps2bVKzZs3sXQkAcIn5S5eXZ3I6nRo6dGiuB10AAABcXOe6X8748eO1adMmTZ48WQcPHlSZMmXUrFkzffvtt7rsssus1+zYscPnzr+nT5/WE088oW3btik0NFTdunXTlClTVLp0aZ9lG2PUt29fvfzyywoJCZEkBQcHa9KkSRowYIDS0tI0btw4RUdH27gGAODSU+Cm28/PT3v37s1xA4xDhw4pMjKSS4YAAAAKyfnulzNz5szzzmPhwoU+j9u3b68NGzac93UOh0Pfffddjvg111yja6655ryvB4DiqsDf6c7rQJ6WlqaAgIC/nRAAAAAAAMVFvke6//Of/0g68ynmf//7X4WGhlrPeTweLV68WHFxcRc+QwAAAAAAiqh8N90vv/yypDMj3ePHj5efn5/1XEBAgKpWrarx48df+AwBAAAAACii8t10p6SkSJLi4+M1c+ZMhYeH25YUAAAAAADFQYFvpLZgwQI78gAAAAAAoNgpcNPt8Xg0adIkzZs3T/v375fX6/V5fv78+RcsOQAAAAAAirICN90PPPCAJk2apISEBNWrV08Oh8OOvAAAAAAAKPIK3HR/8MEH+vDDD9WtWzc78gEAAAAAoNgocNMdEBCgmjVr2pELAABAkdZ64hOFnQLO4/s+ows7BQD/MM6CvuDhhx/Wq6++KmOMHfkAAAAAAFBsFHike8mSJVqwYIH+97//6bLLLpPL5fJ5fubMmRcsOQAAAAAAirICN92lS5dWjx497MgFAAAAAIBipcBN98SJE+3IAwAAAACAYqfA3+mWJLfbrW+++UZvvfWWjh07Jknas2ePjh8/fkGTAwAAAACgKCvwSPdvv/2mq6++Wjt27FBaWpo6deqksLAwPf/88zp9+rTGjx9vR54AAAAAABQ5BR7pfuCBB9S0aVP98ccfCg4OtuI9evTQvHnzLmhyAAAAAAAUZX/p7uXfffedAgICfOIxMTHavXv3BUsMAAAAAICirsAj3V6vVx6PJ0d8165dCgsLuyBJAQAAAABQHBS46e7UqZNeeeUV67HD4dDx48f11FNPqVu3bhcyNwAAAAAAirQCX17+8ssvKz4+XnXr1tXp06d1++23a8uWLSpbtqymT59uR44AAAAAABRJBW66K1asqDVr1uiDDz7QqlWr5PV69e9//1v/+te/fG6sBgAAAADAP12Bm25JCg4OVp8+fdSnT58LnQ8AAAAAAMVGgb/TnZSUpHfffTdH/N1339Vzzz13QZICAAAAAKA4KHDT/dZbbykuLi5H/LLLLtP48eMvSFIAAAAAABQHBW669+3bpwoVKuSIlytXTnv37r0gSQEAAAAAUBwUuOmuXLmyvvvuuxzx7777ThUrVrwgSQEAAAAAUBwU+EZqd999tx588EFlZGSoY8eOkqR58+Zp6NChevjhhy94ggAAAAAAFFUFbrqHDh2qw4cPq3///kpPT5ckBQUFadiwYXrssccueIIAAAAAABRVBWq6PR6PlixZomHDhunJJ5/Uxo0bFRwcrFq1aikwMNCuHAEAAAAAKJIK1HT7+fmpS5cu2rhxo6pVq6ZmzZrZlRcAAAAAAEVegW+kVr9+fW3bts2OXAAAAAAAKFYK3HQ/88wzGjJkiL744gvt3btXqampPv8AAAAAAMAZBW66r776av3000+69tprValSJYWHhys8PFylS5dWeHi4HTn+Iy1evFjdu3dXxYoV5XA4NGvWLJ/nZ86cqS5duqhs2bJyOBxas2bNeec5c+ZMNW3aVKVLl1ZISIgaNWqkKVOm+EwzdepUVa5cWREREXrkkUd8ntu+fbtiY2P5cAUAAAAA8qnAdy9fsGCBHXkgmxMnTqhhw4bq06ePbrjhhlyfb9OmjW666Sbdc889+ZpnRESEHn/8ccXFxSkgIEBffPGF+vTpo8jISHXp0kUHDx7U3XffrUmTJql69epKSEhQhw4dlJCQIEnq16+fnn32WZUsWfKC1goAAAAAxVWBm+727dvbkQey6dq1q7p27Zrn83feeaekM6PP+dWhQwefxw888IAmT56sJUuWqEuXLtq2bZtKlSqlW265RZIUHx+vDRs2KCEhQdOmTVNAQIB69uxZ4FoAAAAA4J+qwJeXS9K3336rO+64Q61bt9bu3bslSVOmTNGSJUsuaHKwjzFG8+bN0+bNm9WuXTtJUq1atXTy5EmtXr1ahw8f1sqVK9WgQQMdPnxYw4cP17hx4wo5awAAAAAoWgrcdH/yySfq0qWLgoOD9eOPPyotLU2SdOzYMY0ZM+aCJ4gL6+jRowoNDVVAQIASEhL02muvqVOnTpKk8PBwTZ48WYmJiWrevLkSExPVpUsXDRkyRIMGDVJKSooaN26sevXq6eOPPy7kSgAAAADg0lfgy8tHjx6t8ePHKzExUR988IEVb926tZ5++ukLmhwuvLCwMK1Zs0bHjx/XvHnzNHjwYFWvXt269LxHjx7q0aOHNf3ChQu1bt06jRs3TjVr1tT06dMVFRWl5s2bq127doqMjCykSgAAAADg0lfgpjvr5chZlSxZUkeOHLkQOcFGTqdTNWvWlCQ1atRIGzduVFJSUo7ve0tSWlqa+vfvr/fff19bt26V2+22vtMfGxur5cuXq3v37hczfQAAAAAoUgp8eXmFChW0devWHPElS5aoevXqFyQpXDzGGOsrAtmNGjVKXbt2VZMmTeTxeOR2u63nMjIy5PF4LlaaAAAAAFAkFXik+95779UDDzygd999Vw6HQ3v27NHSpUs1ZMgQDR8+3I4c/5GOHz/u8+FGSkqK1qxZo4iICFWpUkWHDx/Wjh07tGfPHklnrkCQpKioKEVFRUmSEhMTFR0draSkJElSUlKSmjZtqho1aig9PV1z5szRe++9pzfffDPH8tevX68ZM2ZYv/8dFxcnp9OpCRMmKCoqSps2bVKzZs3sXAUAAAAAUOQVuOkeOnSojh49qvj4eJ0+fVrt2rVTYGCghgwZooEDB9qR4z/SDz/8oPj4eOvx4MGDJUm9evXSpEmTNHv2bPXp08d6/tZbb5UkPfXUUxoxYoQkaceOHXI6z17McOLECfXv31+7du1ScHCw4uLi9P7771s/EZbJGKO+ffvq5ZdfVkhIiCQpODhYkyZN0oABA5SWlqZx48YpOjraltoBAAAAoLhwGGPMX3nhyZMntWHDBnm9XtWtW1ehoaEXOrcLIjU1VaVKldLRo0dVsmTJwk4HRVTnW7hJYFGQPOPiXG3T6v5RF2U5+OuW/ufJi7asRqNHXLRl4a9Z88SIi7as1hOfuGjLwl/zfZ/RhZ0CgGIiv71mvr/TffLkSQ0YMEDR0dGKjIzU3XffrapVq6p58+aXbMMNAAAAAEBhynfT/dRTT2nSpElKSEjQrbfeqrlz56pfv3525gYAAAAAQJGW7+90z5w5UxMmTLC+O3zHHXeoTZs28ng88vPzsy1BAAAAAACKqnyPdO/cuVNXXHGF9bh58+by9/e37p4NAAAAAAB85bvp9ng8CggI8In5+/v7/HYzAAAAAAA4K9+Xlxtj1Lt3bwUGBlqx06dP67777rN+Vko6cxk6AAAAAAAowEh3r169FBkZqVKlSln/7rjjDlWsWNEnBgAAAKDwLV68WN27d1fFihXlcDg0a9Ysn+eNMRoxYoQqVqyo4OBgdejQQevXrz/nPN955x1dccUVCg8PV3h4uK666iqtWLHCZ5qpU6eqcuXKioiI0COPPOLz3Pbt2xUbG6vU1NQLUiNQFOR7pHvixIl25nHJSWg5uLBTQD58uWxsYacAAABwSTpx4oQaNmyoPn366IYbbsjx/PPPP6+xY8dq0qRJio2N1ejRo9WpUydt3rxZYWFhuc5z4cKFuu2229S6dWsFBQXp+eefV+fOnbV+/XpFR0fr4MGDuvvuuzVp0iRVr15dCQkJ6tChgxISEiRJ/fr107PPPnvO3zQGipt8N90AAAAAio6uXbuqa9euuT5njNErr7yixx9/XD179pQkTZ48WeXLl9e0adN077335vq6qVOn+jx+55139PHHH2vevHlKTEzUtm3bVKpUKd1yyy2SpPj4eG3YsEEJCQmaNm2aAgICrOUB/xT5vrwcAAAAQPGQkpKiffv2qXPnzlYsMDBQ7du31/fff5/v+Zw8eVIZGRmKiIiQJNWqVUsnT57U6tWrdfjwYa1cuVINGjTQ4cOHNXz4cI0bN+6C1wJc6mi6AQAAgH+Yffv2SZLKly/vEy9fvrz1XH48+uijio6O1lVXXSVJCg8P1+TJk5WYmKjmzZsrMTFRXbp00ZAhQzRo0CClpKSocePGqlevnj7++OMLVxBwCePycgAAAOAfyuFw+Dw2xuSI5eX555/X9OnTtXDhQgUFBVnxHj16qEePHtbjhQsXat26dRo3bpxq1qyp6dOnKyoqSs2bN1e7du0UGRl5YYoBLlGMdAMAAAD/MFFRUZKUY1R7//79OUa/c/Piiy9qzJgxSk5OVoMGDfKcLi0tTf3799dbb72lrVu3yu12q3379qpdu7ZiY2O1fPnyv1cIUATQdAMAAAD/MNWqVVNUVJTmzp1rxdLT07Vo0SK1bt36nK994YUXNGrUKH311Vdq2rTpOacdNWqUunbtqiZNmsjj8cjtdlvPZWRkyOPx/L1CgCKAy8sBAACAYuj48ePaunWr9TglJUVr1qxRRESEqlSpogcffFBjxoxRrVq1VKtWLY0ZM0YlSpTQ7bffbr0mMTFR0dHRSkpKknTmkvInn3xS06ZNU9WqVa2R8tDQUIWGhvosf/369ZoxY4bWrFkjSYqLi5PT6dSECRMUFRWlTZs2qVmzZjavBaDw0XQDAAAAxdAPP/yg+Ph46/HgwYMlSb169dKkSZM0dOhQnTp1Sv3799cff/yhFi1aKDk52ec3unfs2CGn8+zFsW+88YbS09N14403+izrqaee0ogRI6zHxhj17dtXL7/8skJCQiRJwcHBmjRpkgYMGKC0tDSNGzdO0dHRdpQOXFJougEAAIBiqEOHDjLG5Pm8w+HQiBEjfJrl7BYuXOjzePv27flatsPh0HfffZcjfs011+iaa67J1zyA4oLvdAMAAAAAYBOabgAAAAAAbELTDQAAAACATWi6AQAAAACwCU03AAAAAAA2oekGAAAAAMAmhdp0L168WN27d1fFihXlcDg0a9Ysn+eNMRoxYoQqVqyo4OBgdejQQevXry+cZAEAAAAAKKBC/Z3uEydOqGHDhurTp49uuOGGHM8///zzGjt2rCZNmqTY2FiNHj1anTp10ubNmxUWFlYIGQMAAADnN2jeA4WdAvLhtStfLewU8A9QqE13165d1bVr11yfM8bolVde0eOPP66ePXtKkiZPnqzy5ctr2rRpuvfeey9mqgAAAAAAFNgl+53ulJQU7du3T507d7ZigYGBat++vb7//vtCzAwAAAAAgPwp1JHuc9m3b58kqXz58j7x8uXL67fffsvzdWlpaUpLS7Mep6amSpIyMjKUkZEhSXI6nfLz85PH45HX67WmzYy73W65AvysuMftlddr5O9yyuFwWHF3hkfGyGfac8Uz0j1yOCR/1/njxhi5M7xyOh3y83fmjPs55Od3Nu71GnncXvn5O+V0ns3R4/HK68mZe3GpKXObSpKfn5+cTqfcbreMMTniWaeVJH//M7u/2+0+b9zl71SG23umJj/fz6oy3H/WlCVHYyS3J2fca4w8HiM/P4ecWbeH15zZHn5OZQlbcZe/7zLdHu+Z7ZHP+LlyL041ZWRkyOVyyev1yuPxWHGHwyF/f/8843kdC/KKu5wO378br5HXGLn8nMpSqjK8Z3IPyL5+PV4Z5Yyne7xySHLlFndILmeWv5s/5+N0OOTvs52MMrxGfo6c28ntNfJ35txOHmOKXU2S8jwWXOhjROCfNaR5vXIqZ03pXq/8HA75O7LmLmWYnHGPMXIbI3+HQ35Zt4f5czs5nMqyCqx4gDPndvJmyS1TuvfMdsoeT/Oe2U4BucSLQ01Zt63dxwhJcsk3d7eMvDI54hn68+8m2xhIXvF0/fn3lI+4+XM+Tjnkn2WpmXE/OeSXJe6VkVtG/nL4ZOmRkSeX3It0TR6P9X7PzmOEn/F9b+RxeOQwDjmz1Zpb3MjI6/DmGXcapxw+tXplHCbPePZc8op7dGb/91M+48Wgpuzb9WK8j7hY5ydqsr+m7HXk5ZJtujNlfRMonXnzlT2WVVJSkkaOHJkjnpycrBIlSkiSqlSposaNG2vt2rXasWOHNU3t2rUVFxenFStWqM/Dba34ojmbtfmnfbq+VxNFlAux4nM+WKtdKX/oXwNbKiDw7Kr86J2VOp6a5jMPSZr40hKFlgzUTfc0s2LpaW5NGvudoquGq9utDaz44QMn9PF/f1Ct+uXVvlttK75z22H9b8Y6NW5VRZdfUdWKb1qzV4v/94vadKqpuEYVrPiqb7dr1ZLf1KnnZapcPaLY1TRnzhwr3qhRI8XExGjx4sU6duyYFW/VqpUiIyOVnJzs8wcbHx+v4OBgn3lIUrdu3XTq1CktWLDAivXuUVfvfPSzKkWF6dr46mdrOnJa0+dsVu1q4erYorIV37H3mD5fsE2XXxap5vWjrPiGrYe0YMUutbs8WnVrlrHiK9bt08p1v6tru6qqUuHs/QrmL9+pjb8e1o2daymidJAVn71gm3buPabePeoqIMsHG9O/3KRjJzLU9+b6PjW9/eE6hYW4dFtCnBVLz/AUu5qSk5OVkJCggwcPaunSpVY8LCxMHTt21M6dO7VmzRorXq5cObVu3VpbtmzR5s2brfj5jhE9GlRV9TJna5qzcZfW7jmsxKY1VS70bE0zVm9TyuHjGtC2jgL9z9b032WblXo6Q4M71POpaezCn1UyyKW7W579+0hze/TyovWqGh6qWxqf3U4Hjp/WhOW/qF6FcHWrU8mKbzt0TB+uSVGrqpFqW/3sh5Y/7T6s/23apU6x0WoYffZYsGTb71qS8nuxq0mSVqxYoQMHDlhxu44R/3dZQ532eJS0Ya2qhYYpsVpNa9r9p0/p9S2b1LB0hK6rVMWKbz2Wqinbf9UV5corvnyW49vhg5q9e6e6VaykyyPKWvEFv+/Vwv37dGtMNdUMK2nFP9u1Qz/+cUj31IhVZFCwFX8vZat+PX5Mg+PqKcjv7HYa98tGpWak6/8ua+hT05j1P6mkK0ADY+tYseJUU+Y29Pf3t/0YIUk9wmqqmquUFf/fiRStTTuoxJJ1Vdb/bE0fHtuslIxU9Q9vpEDH2ZomHF2nVE+6Hoq43Kemlw+vUkm/AP271NnjYZrx6JU/flRVV0ndHHb27+yg+5QmpP6seoFl1DWkmhVPyTiqD4/9opbBFdQ2ONqK/3T6gL46uV1XlYhRw6ByVnzJqd367tSeYlXTli1brPd7dh4j4k+0t2JuubUwdLHCPeFqcrqRFT/uPK5lJVaogjtKddPO/v0d8juk1cE/qVp6VVXPOFvrbv892hi0SbXTYhXtrmjFt7lStC0wRQ1P11cZz9lz8YbAjdrj2qtmpy5XqDfUiv8YtEaH/Q/rihNt5J+lHVgavFynnad9cpekBSGLFOQNUqtTLYpdTVm338U4RlyMfS/re1hqsremkydPKj8cJmv7XogcDoc+/fRTXX/99ZKkbdu2qUaNGvrxxx/VuHFja7rrrrtOpUuX1uTJk3OdT24j3ZUrV9bBgwdVsuSZk3p+PtW4seNjVry4jAoXx5Huj+cnWXE7P1G7vvdzxW5U+HzxoljTrEnDLsonn+0eHF2sRoWL40j3klefuGifurd94cxxqLiMCmePF4ealjxy9pxu9zHiiveeKl6jwsVwpHte4lMXZWTuoXkP+8SLw6hwcRzpHtv+RZ/4pTKCmjVeXEaFi2NNqampKlu2rI4ePWr1mrm5ZEe6q1WrpqioKM2dO9dqutPT07Vo0SI999xzeb4uMDBQgYGBOeIul0sul8sn5ufnJz8/vxzT+vv7KyPdkyPuzvDmiEnKddq84sYULO71Gnlzi3uMvJ6ccY/bq9yyySv3ol5T9m0qnf3jzC63afMbz3CfWU/GnP3/rLx/NpL5jXs8Z97EZOf25LE9cllmQeN55V6casrcZk6n07rMM6u84nkdC/KKZ3iNlEutGXnUml6AuMkrbnKPe41RuieX7fHnhyHZufPKvRjWlNex4EIfI9KynKi92R5n8vzZSOY37v6zUc0uw3hzK1XpuSwze27ni5s84sWhpuzb0PZjhPI4juURTy9A3BQw7pVRei4rOLOZzs6tPI4FxaimzG1m9zHC48jlvZHDWM3e34l7Hbmv37ziueVyzniu77xyjxf1mnLbfnYfIy7W+SkrarKnprzyzfGafE1lk+PHj2vr1q3W45SUFK1Zs0YRERGqUqWKHnzwQY0ZM0a1atVSrVq1NGbMGJUoUUK33357IWYNAAAAAED+FGrT/cMPPyg+Pt56PHjwYElSr169NGnSJA0dOlSnTp1S//799ccff6hFixZKTk7mN7oBAAAAAEVCoTbdHTp00Lm+Uu5wODRixAiNGDHi4iUFAAAAAMAFcsn+TjcAAAAAAEUdTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgE5puAAAAAABsQtMNAAAAAIBNaLoBAAAAALAJTTcAAAAAADah6QYAAAAAwCY03QAAAAAA2ISmGwAAAAAAm9B0AwAAAABgk0u66R4xYoQcDofPv6ioqMJOCwAAAACAfPEv7ATO57LLLtM333xjPfbz8yvEbAAAAAAAyL9Lvun29/dndBsAAAAAUCRd8k33li1bVLFiRQUGBqpFixYaM2aMqlevnuf0aWlpSktLsx6npqZKkjIyMpSRkSFJcjqd8vPzk8fjkdfrtabNjLvdbrkCzo6oe9xeeb1G/i6nHA6HFXdneGSMfKY9Vzwj3SOHQ/J3nT9ujJE7wyun0yE/f2fOuJ9Dfn5n416vkcftlZ+/U07n2Rw9Hq+8npy5F5eaMrepdOYqCKfTKbfbLWNMjnjWaaUzH+hIktvtPm/c5e9Uhtt7piY/329lZLj/rClLjsZIbk/OuNcYeTxGfn4OObNuD685sz38nMoStuIuf99luj3eM9sjn/Fz5V6casrIyJDL5ZLX65XH47HiDodD/v7+ecbzOhbkFXc5Hb5/N14jrzFy+TmVpVRleM/kHpB9/Xq8MsoZT/d45ZDkyi3ukFzOLH83f87H6XDI32c7GWV4jfwcObeT22vk78y5nTzGFLuaJOV5LLjQx4jAP2tI83rlVM6a0r1e+Tkc8ndkzV3KMDnjHmPkNkb+Dof8sm4P8+d2cjiVZRVY8QBnzu3kzZJbpnTvme2UPZ7mPbOdAnKJF4easm5bu48RkuSSb+5uGXllcsQz9OffTbZv++UVT9eff0/5iJs/5+OUQ/5ZlpoZ95NDflniXhm5ZeQvh0+WHhl5csm9SNfk8Vjv9+w8RvgZ3/dGHodHDuOQM1utucWNjLwOb55xp3HK4VOrV8Zh8oxnzyWvuEdn9n8/5TNeDGrKvl0vxvuIi3V+oib7a8peR14u6aa7RYsWeu+99xQbG6vff/9do0ePVuvWrbV+/XqVKVMm19ckJSVp5MiROeLJyckqUaKEJKlKlSpq3Lix1q5dqx07dljT1K5dW3FxcVqxYoX6PNzWii+as1mbf9qn63s1UUS5ECs+54O12pXyh/41sKUCAs+uyo/eWanjqWk+85CkiS8tUWjJQN10TzMrlp7m1qSx3ym6ari63drAih8+cEIf//cH1apfXu271bbiO7cd1v9mrFPjVlV0+RVVrfimNXu1+H+/qE2nmoprVMGKr/p2u1Yt+U2del6mytUjil1Nc+bMseKNGjVSTEyMFi9erGPHjlnxVq1aKTIyUsnJyT5/sPHx8QoODvaZhyR169ZNp06d0oIFC6xY7x519c5HP6tSVJiujT/7oc/hI6c1fc5m1a4Wro4tKlvxHXuP6fMF23T5ZZFqXv/slRobth7SghW71O7yaNWteXYfXrFun1au+11d21VVlQphVnz+8p3a+Oth3di5liJKB1nx2Qu2aefeY+rdo64CsnywMf3LTTp2IkN9b67vU9PbH65TWIhLtyXEWbH0DE+xqyk5OVkJCQk6ePCgli5dasXDwsLUsWNH7dy5U2vWrLHi5cqVU+vWrbVlyxZt3rzZip/vGNGjQVVVL3O2pjkbd2ntnsNKbFpT5ULP1jRj9TalHD6uAW3rKND/bE3/XbZZqaczNLhDPZ+axi78WSWDXLq75dm/jzS3Ry8vWq+q4aG6pfHZ7XTg+GlNWP6L6lUIV7c6laz4tkPH9OGaFLWqGqm21ctb8Z92H9b/Nu1Sp9hoNYw+eyxYsu13LUn5vdjVJEkrVqzQgQMHrLhdx4j/u6yhTns8StqwVtVCw5RYraY17f7Tp/T6lk1qWDpC11WqYsW3HkvVlO2/6opy5RVfPsvx7fBBzd69U90qVtLlEWWt+ILf92rh/n26NaaaaoaVtOKf7dqhH/84pHtqxCoyKNiKv5eyVb8eP6bBcfUUlOVrWeN+2ajUjHT932UNfWoas/4nlXQFaGBsHStWnGrK3Ib+/v62HyMkqUdYTVVzlbLi/zuRorVpB5VYsq7K+p+t6cNjm5WSkar+4Y0U6Dhb04Sj65TqSddDEZf71PTy4VUq6Regf5c6ezxMMx698sePquoqqZvDzv6dHXSf0oTUn1UvsIy6hlSz4ikZR/XhsV/UMriC2gZHW/GfTh/QVye366oSMWoYVM6KLzm1W9+d2lOsatqyZYv1fs/OY0T8ifZWzC23FoYuVrgnXE1ON7Lix53HtazEClVwR6lu2tm/v0N+h7Q6+CdVS6+q6hlna93tv0cbgzapdlqsot0Vrfg2V4q2Baao4en6KuM5ey7eELhRe1x71ezU5Qr1hlrxH4PW6LD/YV1xoo38s7QDS4OX67TztE/ukrQgZJGCvEFqdapFsasp6/a7GMeIi7HvZX0PS0321nTy5Enlh8Nkbd8vcSdOnFCNGjU0dOhQDR48ONdpchvprly5sg4ePKiSJc+c1PPzqcaNHR+z4sVlVLg4jnR/PD/Jitv5idr1vZ8rdqPC54sXxZpmTRp2UT75bPfg6GI1KlwcR7qXvPrERfvUve0LZ45DxWVUOHu8ONS05JGz53S7jxFXvPdU8RoVLoYj3fMSn7ooI3MPzXvYJ14cRoWL40j32PYv+sQvlRHUrPHiMipcHGtKTU1V2bJldfToUavXzM0lPdKdXUhIiOrXr68tW7bkOU1gYKACAwNzxF0ul1wul0/Mz88v1xuz+fv7KyPdkyPuzvDmiEnKddq84sYULO71Gnlzi3uMvJ6ccY/bq9yyySv3ol5T9m0qnf3jzC63afMbz3CfWU/GnP3/rLx/NpL5jXs8Z97EZOf25LE9cllmQeN55V6casrcZk6n07rMM6u84nkdC/KKZ3iNlEutGXnUml6AuMkrbnKPe41RuieX7fHnhyHZufPKvRjWlNex4EIfI9KynKi92R5n8vzZSOY37v6zUc0uw3hzK1XpuSwze27ni5s84sWhpuzb0PZjhPI4juURTy9A3BQw7pVRei4rOLOZzs6tPI4FxaimzG1m9zHC48jlvZHDWM3e34l7Hbmv37ziueVyzniu77xyjxf1mnLbfnYfIy7W+SkrarKnprzyzZFTvqa6RKSlpWnjxo2qUKHC+ScGAAAAAKCQXdJN95AhQ7Ro0SKlpKRo+fLluvHGG5WamqpevXoVdmoAAAAAAJzXJX15+a5du3Tbbbfp4MGDKleunFq2bKlly5YpJiamsFMDAAAAAOC8Lumm+4MPPijsFAAAAAAA+Msu6cvLAQAAAAAoymi6AQAAAACwCU03AAAAAAA2oekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJvQdAMAAAAAYBOabgAAAAAAbELTDQAAAACATWi6AQAAAACwCU03AAAAAAA2oekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJvQdAMAAAAAYBOabgAAAAAAbELTDQAAAACATWi6AQAAAACwCU03AAAAAAA2oekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJvQdAMAAAAAYBOabgAAAAAAbELTDQAAAACATWi6AQAAAACwCU03AAAAAPzDLF68WN27d1fFihXlcDg0a9as875m6tSpatiwoUqUKKEKFSqoT58+OnTokPX83LlzFRsbq1KlSqlXr15KT0+3njt69KhiY2O1Y8cOO8q5pNF0AwAAAMA/zIkTJ9SwYUONGzcuX9MvWbJEiYmJ+ve//63169fro48+0sqVK3X33XdLkrxer/71r3/pvvvu0/fff68VK1bonXfesV4/bNgw3XfffapSpYot9VzK/As7AQAAAADAxdW1a1d17do139MvW7ZMVatW1f333y9Jqlatmu699149//zzkqSDBw/qwIED6t+/v4KCgnTttddqw4YNkqTvvvtOP/zwg15//fULX0gRwEg3AAAAAOCcWrdurV27dmnOnDkyxuj333/Xxx9/rISEBElSuXLlVKFCBSUnJ+vUqVP69ttv1aBBA6Wnp6tfv34aP368/Pz8CrmKwkHTDQAAAAA4p9atW2vq1Km65ZZbFBAQoKioKJUuXVqvvfaaJMnhcOjDDz/UqFGjVLduXTVu3Fh33XWXnn32WV155ZUKDg5WmzZtVLt27Xxf0l5ccHk5AAAAAOCcNmzYoPvvv1/Dhw9Xly5dtHfvXj3yyCO67777NGHCBElS27ZttXLlSus1v/zyi6ZMmaLVq1erXbt2evDBB3X11VerXr16ateunRo0aFBY5VxUNN0AAAAAgHNKSkpSmzZt9Mgjj0iSGjRooJCQEF1xxRUaPXq0KlSo4DO9MUZ9+/bVSy+9JK/Xq9WrV+vGG29UiRIl1L59ey1atOgf03RzeTkAAAAA4JxOnjwpp9O3fcz8jrYxJsf0EyZMUJkyZXTttdfK4/FIkjIyMqz/Zsb+CWi6AQAAAOAf5vjx41qzZo3WrFkjSUpJSdGaNWus39F+7LHHlJiYaE3fvXt3zZw5U2+++aa2bdum7777Tvfff7+aN2+uihUr+sx7//79Gj16tP7zn/9IksLDw1WnTh298sorWrp0qebNm6fWrVtfnEIvAVxeDgAAAAD/MD/88IPi4+Otx4MHD5Yk9erVS5MmTdLevXutBlySevfurWPHjmncuHF6+OGHVbp0aXXs2FHPPfdcjnk/8MADGjJkiKKjo63YpEmT1KtXL/3nP//RI488oubNm9tY3aWFphsAAAAA/mE6dOiQ62XhmSZNmpQjNmjQIA0aNOi8854+fXqOWPPmzbVx48YC5VhccHk5AAAAAAA2oekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJvQdAMAAAAAYBOabgAAAAAAbELTDQAAAACATfidbgAAAACw0fvLuhR2CsiHO1p+bct8GekGAAAAAMAmNN0AAAAAANiEphsAAAAAAJvQdAMAAAAAYBOabgAAAAAAbELTDQAAAACATWi6AQAAAACwCU03AAAAAAA2oekGgP9v797jZKz7P46/ZmaP2ew65Wxz3A05LcLSHcVauZ1SDreSQzmsc92FaHNWQii7bpZwSxIhUok7YWnD2iWWvRMtktMqZHd2Z67fH9tOsw7d6md2mH0/Hw+Pmu9cM/OZnfdc13yuo4iIiIiIi6jpFhEREREREXERNd0iIiIiIiIiLqKmW0RERERERMRF1HSLiIiIiIiIuIiabhEREREREREXUdMtIiIiIiIi4iJqukVERERERERcRE23iIiIiIiIiIuo6RYRERERERFxETXdIiIiIiIiIi6ipltERERERETERdR0i4iIiIiIiLiImm4RERERERERF1HTLSIiIiIiIuIiarpFREREREREXOSuaLrnzp1LxYoV8fPzIywsjG3btrm7JBEREREREZH/6Y5vulesWMGwYcN45ZVXSExMpFmzZkRGRvLDDz+4uzQRERERERGRP3THN90zZsygT58+9O3blwceeIC33nqL8uXLExMT4+7SRERERERERP7QHd10W61W9uzZQ6tWrfKMt2rVivj4eDdVJSIiIiIiInJrvNxdwB85d+4cNpuNkiVL5hkvWbIkp0+fvuFjMjMzyczMdNz++eefAbhw4QJZWVkAmM1mLBYLNpsNu93umDZ3PDs7G8zZjnFbth273cDL24zJZHKMZ2fZMAzw9rHkqeFm41lWGyYTeHn/73HDMMjOsmM2m7B4ma8ft5iwWH4ft9sNbNl2LF5mzObfa7TZ7Nht19fuKe/p/PnzjnGLxYLZbCY7OxvDMK4bz/38c3l55cQ/Ozv7f48bVrKz7ZhM5KkxZ7qc9+Rco2Hk1Hn9uIHNZmCxmPL83e12A7vdwGIx4zTsGPfyyvuaNpsdw+CWx/+odk96T+fPn8fb2xu73Y7NZnOMm0wmvLy8bjp+s3nBzcZNWZl5vzd2AzsG3mYzTm+VLLsdA/Ax5639ZuNWux0T4H0L48Zvz2PGhNc1n0eWYWDBhMVp3G4YZBsGXiYTZud5gd3AhoG3yeRR7+mXX3656bzgds8jvKxWADLtBmbA27l2wGo3sJjAy/n7YZDznq4ZtxkG2QZ4mcDi/HkYBjYDvE0mnJ7eMe5jNl3zORnYAV/niX+rxbjBeKbdwETO81w77gnvyXlZ4ep5RPbVTLzJ+73J5rfv0zXjWfz2vblmG8jNxq389r25hXHjt+cxY8IL03XjFkxYnMbtGGRj4IUpT5U2fptHeNB7Sk9Pd/zec+k84nLecbvJhskwYbrmvd5o3MDAMNn/YNyMKc/fwI5hMm46bjby/k672bidnPybucVxD3hPzvMHcN084uolwGTP+WdYwHD65uSO2y3g/I0y2cBkgP2als1kAwwwrh3Pznn8NX8DzNk5r5dn3ACzDQxzzj/Hcxg5z3/deG7tNxv3jPd0/vz5PD3h/5pHXLp0KeeVnaa7EZPxv6Zwo1OnTlG2bFni4+Np3LixY3zSpEksXbqUlJSU6x7z2muvMW7cuPwsU0RERERERAqotLQ0ypUrd9P77+gt3cWLF8disVy3VfvMmTPXbf3ONWrUKEaMGOG4bbfbuXDhAsWKFcuzFaeg+eWXXyhfvjxpaWkULlzY3eWImykP4kx5EGfKg+RSFsSZ8iDOlIcchmFw6dIlypQp84fT3dFNt4+PD2FhYWzatImOHTs6xjdt2kT79u1v+BhfX198fX3zjAUFBbmyzLtK4cKFC/QXQ/JSHsSZ8iDOlAfJpSyIM+VBnCkPEBgY+D+nuaObboARI0bw9NNPU79+fRo3bsy//vUvfvjhB/r37+/u0kRERERERET+0B3fdHfp0oXz588zfvx4fvzxR2rWrMknn3xCcHCwu0sTERERERER+UN3fNMNMHDgQAYOHOjuMu5qvr6+REdHX7frvRRMyoM4Ux7EmfIguZQFcaY8iDPl4c+5o89eLiIiIiIiInI3M//vSURERERERETkr1DTLSIiIiIiIuIiarpFREREREREXERNt4gH0SkaxJnyIM6UB3GmPIgz5UHEtdR0i3iA7Oxs4PeFpt1ud2c54mbKgzhTHsSZ8iDOlAeR/HFXXDJMbp3dbsds1rqUgiQlJYW33nqLM2fOEBwcTK9evahVq5a7yxI3UR7EmfIgzpQHcaY8iOQfdWd3udw1k/Hx8RiGoYa7gElJSaFRo0ZkZGTg7e3NoUOHaNiwIQsXLiQrK8vd5Uk+Ux7EmfIgzpQHcaY8yM3oUAPX0Jbuu5zJZGLTpk1ERETw0Ucf0b59e3eXJPnEMAxmzpxJixYtePfddwG4dOkSM2bM4LnnnuPKlSsMHjzYvUVKvlEexJnyIM6UB3GmPMiNfPfdd1SuXBmTyYTVasXHx4dff/0VgHvuucfN1d391HTf5Y4dO8b27duZPXu2Gu4CxmQycfr0acqWLQvkLEQDAgKIjo7Gz8+P4cOHU7FiRdq2bYthGJhMJjdXLK6kPIgz5UGcKQ/iTHmQa82bN4+tW7cyePBgGjdujI+PD0ePHqVPnz5MmzaN+vXru7vEu572Rb6L7d+/n969e7N8+XIqV64M6AQYBU1ISAgbN27k/PnzmEwmxy5BL7/8Mv3792fIkCGcOXNGC8wCQnkQZ8qDOFMexJnyIM6qV6+OyWRiyZIlpKamcvbsWR555BEqVKhAWFiYu8vzCGq673JFihTh5MmTfPPNNwCYzWY13gVI27ZtKVWqFJMmTSI9PR2z2YzNZgOga9euWK1W0tLS3FyluEruWWdz/9u+fXvloQA7c+YMp06dctxWHgq2kydPkpSU5LitPBRsBw8eZM6cOY7b7dq1Ux7EoVmzZgwcOBCr1cr48eOpUaMGHTp0YPHixVrxcpuo6b6LPfjgg0yaNImOHTvywQcfsHDhQkCNt6c6fvw477zzDq+//jrr1q0D4OGHH6Z169Zs3bqV6dOnc/bsWSwWCwD3338//v7+XL161Z1li4scOHCAxo0bc+jQIby8co4UCg8PVx4KqL1791KnTh2OHDniGFMeCq7k5GRatmzJypUrOXv2LJCTh4iICOWhADpw4AANGjRg6NChJCQkANC0aVMiIyOVBwFyVt6Hh4fTtm1bVq9ezX333UeXLl0c96uv+P/TMd13idxjapKTkzl27BiZmZk0b96c0NBQxo4dy8SJE4mLi8NsNvPss89iNpt1HI4HSU5O5vHHH6dKlSpcunSJkydPYrPZ6NixI9HR0Vy+fJlNmzaRkpLC5MmTsVgsxMXFkZWV5Tj0QDzL66+/zp49e4iIiODTTz+levXqAERHR3PlyhU+//xz5aGASEpK4uGHH6Zv37488sgjee6Ljo7m0qVLmj8UIKmpqTz66KM8++yzvPbaa46VcgCvvfYaGRkZmj8UIElJSTRq1Ij27duTmprKtm3baNiwIQCvvvoqV65c4YsvvlAeCjC73Y6XlxfHjx9n+PDhRERE4Ofnx7Jly7BYLDRq1EhXR7odDLlrrFy50rjvvvuMqlWrGhUqVDCKFStmrFu3zjAMwzh48KDRo0cP4+GHHzZiYmLcXKncTikpKUaZMmWMkSNHGpmZmcbRo0eNRx55xFi8eHGe6WJjY43mzZsbJpPJqFGjhlGhQgVjz549bqpaXG3q1KnGoEGDjF69ehlFixY1kpOT89y/aNEi5aEASE5ONgIDA42XXnrJMAzDsNlsRnJyshEfH2/s3bvXMV1MTIzyUEBMmjTJePrppw3DMIzs7Gxj/vz5xoQJE4y3337byMjIMAzDMOLi4oxHHnlEefBwe/fuNQICAoxXXnnFMAzDGDFihFGiRAkjPT09z3Tz5s0zWrRooTwUYKdPnzYCAwONfv36GYZhGLt27TKefvppo0ePHkZCQoKbq/MMJsPQxdjuBomJiTz66KPMmDGDyMhIAMaMGcPy5ctZuXIlkZGR7N+/n7Fjx5KRkcGKFSsIDAx0c9Xy/2W1Wunbty8Wi4UFCxY4dv164oknKFasGEFBQdx///0MHDgQgKysLHbt2kVgYCAlSpSgdOnS7ixfXCj3kJK4uDh69+5NYmIiycnJvPvuuzRs2JAWLVpgs9mIj49XHjyU1WolNDSUixcvcvbsWcxmMx07duTEiROkpqbi5eVFVFQU48ePBzR/KCh69uxJUFAQs2bNomnTplitVnx9fdm9ezfNmjVjxowZ1KxZk+zsbHbu3Kk8eKjTp08TGhrKc889x7Rp04Ccrd5PPvkkI0aMoH///mRlZeHt7Q2g5UUBt3XrVvbs2cPQoUMdvzW3bdvGkiVLmDBhAqVKlXJzhXc/Nd13iTVr1jBhwgQ2b95MYGCgY7fx3r17s3HjRg4ePEiRIkVISUmhcOHClClTxs0Vy+2SmJjI5cuXadasGQBTpkzhlVdeoXPnztxzzz0sWbKEYcOGMWPGDDdXKvlpx44djBw5km3btpGenk7fvn1Zv34999xzDwcPHtQPpgIiISGBli1bEhkZyalTp/D392f06NH4+vqSmJjI4MGDmTp1Ki+++KK7SxUXMwwDwzCIiorCbDbToUMHpk+fznvvvUfRokU5fvw4jz32GLVq1WLVqlXuLldc7Pjx4xw5coSWLVs6xgzDoE2bNly9epUvv/wSyGm2c5ss8WzGHxx2arfbHbuQO0+XkZGBn59fvtXoyXRM913iwoULHD58mICAAEwmE5mZmfj6+jJ69Gg2bdrE7t27admyJaGhoe4uVW6zunXrOv5/z549fPTRR6xfv57IyEhMJhPNmzdn6NCh9O/fn6pVq+o4/gKiUaNGWK1W0tPTKVKkCIDj2M3Lly8DeRei4nlsNhsNGzZk06ZNNG7cmLCwMFatWkWJEiUAeOihhzh69CjLly+nV69eFC1aVPMHD2YymTCZTHTq1InIyEj27dtHzZo1KVq0KDabjeDgYN577z2aNm1KUlIStWvXdnfJ4kLBwcEEBwc7buc21+PHjycyMpJ///vf9OjRQw23h7t48SKZmZlkZ2c7rssO1zfgzr8VnMfVcN8++jV2B7rRzgft2rUjODiYgQMHOhpuyPmR7evri4+PT36XKW4QFhbG6tWradOmjWOm6OXlRcWKFSlVqpR+UBcQdrsdq9VKVlYW33//PVFRUezcuZNVq1bRvHlzQkJCOHz4sBpuD2exWByN97fffsuAAQMcK2Ag54eTr68vFouFoKAgzR8KAMMwaNKkCVFRUezbt8+xAi63sfL29uaBBx7IkxMpGJzPTF6rVi02b94M6KzUnmz//v00a9aMRx99lEqVKjFgwAA+//xzIGf5oM8+f2lL9x0md81TQkICiYmJlC5dmr/97W8UL16c/v37s3z5cgYOHMjMmTO5dOkSixYtwmazUaVKFXeXLi6Wu9XSeU0lwL59+wgODlaDVYCYTCb8/f0dl3zx8fFh48aN1K5dmxo1auDr66sGq4CwWCzY7XZCQ0MJCQm57nM/d+4cDz74oHYhLSBMJhOFChWiV69enD9/nvfee49atWrx/PPP4+vr67jc5D333OPmSsVdSpQoQZ8+fejZsyeDBg0iLCzM3SWJC5w4cYJWrVrRvXt3OnXqxA8//MCcOXM4cOAAJ06coHfv3rrSUT5T032HMZlMrFu3js6dO1O7dm327NlD165deemllxgwYABms5nY2FiKFy9OSEgI6enprFu37rpGTDxPblOdO3M8c+YMs2fPZsGCBWzbto2AgAB3lif5KDcDNWrUoGrVqrz99tuOXUXLly/P0qVL81wmSDzbtfMGyJk/zJkzhw8//JCvvvpKe0MVMHXq1OHVV1/l/vvvZ8yYMcyfP5/ChQtz6tQpPv30U4oXL+7uEsWN2rVrR7Vq1XjvvfeoU6eOVsh5oF27dlGyZEkmTpyIv78/4eHhhIaGMmvWLGJjY/Hz86N79+5quPORTqR2B7Db7Y5jsX788UeioqJo06YNffr0Yfv27URFRVG5cmXGjh1LvXr1yMzM5OOPP6ZEiRJUrlyZcuXKufstyG3ivMbxj9Y+7ty5k7i4OL744gvWrFlDnTp18rFKyS+3kocLFy5QtGjR/C5N3OBW5w87duwgJiaGLVu2sGHDhjznhRDPcbM8XJuN5ORkdu/eTUBAAA0bNuT+++93R7niYrc6f8g1ceJEunTpQtWqVfOjPMlna9eupX///mzdupVq1ao5MnHgwAEmTZrEL7/8wltvvaXPPx+p6Xaj7du306hRI8cWqa+++oply5Zx8uRJYmJiKF++PJDzAyoqKopKlSoxfPhwx1msxXPkzgwvXbpEoUKFyM7O/sMtU0ePHmX37t3Ur1+fSpUq5WOlkh9uJQ/aJazg+LPzh//+97/Ex8cTHh5O5cqV87FSyQ9/Jg+aT3i+Pzt/0Ak2PZfziVV3795NREQEU6dO5bnnnsvzue/atYvWrVsTExNDt27d3FlygaJvnZssXbqU6Ohofv75Z8fYmTNnWLZsGVu3buW7775zjIeHhzN37lzS0tKYMGEC8fHx7ihZXCR3gblhwwY6depEeHg4kZGR7Nix44Yn1QOoVKkSTz75pBpuD3SredAP6YLhr8wfqlSpQo8ePdRwe6A/mwfNJzzbX5k/qOH2TCkpKXTo0MFxgrz69eszaNAghgwZwubNmzGbzdhsNiDn6icPPfQQ//nPf9xZcoGjb14+yz1TYIcOHVi6dCnFihXj+PHjZGVl0blzZ1atWkXhwoVZuHAh3377reNxTZo04c033yQjI4MKFSq4q3xxAZPJxCeffEKnTp1o0qQJkZGRFC9enObNm7No0SLgxme0148pz/RX8yCe6a/mQT+sPZPmD+JMeRCApKQk6tWrx7Zt2/j0008d46NGjaJbt260a9eO9evX51kuGIahw1PzmyH5xmazGYZhGP/973+N9evXG4ZhGAcPHjTCwsKMN99807BarYZhGMbq1auN8uXLG3379jW+/fbbPM/x66+/5m/R4nIZGRnG448/bgwfPjzP+NixYw1vb2/j66+/NgzDMOx2uzvKk3ymPIgz5UGcKQ/iTHmQffv2Gf7+/sZrr71mLFmyxChbtqyxe/dux/0XLlwwBg4caHh5eRlRUVFGdHS0MWTIEKNw4cLGoUOH3Fh5waNV4fnIbDZz6tQpGjVqxEsvvcQHH3xA5cqVqVq1KqtXryY2NpasrCw6duzIrFmz+Oyzz5gzZw7JycmO59BF6j1DdnY28PuuYSdOnKB06dIAZGVlATB+/HgiIyOZPHmyY3rxTMqDOFMexJnyIM6UB8mVmJhIkyZNGD58ONHR0YSGhmIYBnv27AFyMlKkSBHeeecd5s2bx/Hjx9mwYQPHjh3jq6++IjQ01M3voGBR053PDh8+zPnz5ylUqBBLly7ls88+Y/HixYSEhPDvf/87T+M9e/ZslixZwsKFC7FarYB2Kb7bnT17lqysLLy8vNi8eTOJiYn4+PhQvXp1Vq9ezdWrV/H29nYsJCtVqkRmZiZeXl767D2Q8iDOlAdxpjyIM+VBnFmtVvr168egQYOYNGkSAA0aNKBDhw5MnDiR8+fPYzKZHIcX9O7dmxUrVvD111/z/vvvOy4zKvlHTXc+a968Ob169cJqteLr68ubb77Jpk2biI2NpUaNGnka7w4dOrBixQqioqJ0jVUPcPbsWf7xj38wfvx43n//fVq2bMnJkycB6N69O4Zh8MILL2C1Wh1ntL9y5Qr33nsvmZmZOi7LwygP4kx5EGfKgzhTHuRaPj4+bNy4kddffx3AcZK0f/zjHxQqVIj169cDOVu7cz9/f39/zGYz/v7+7im6gPNydwGe7NrLMmRmZuLr68sTTzyB3W6nW7duzJs3j8mTJ2MymYiNjWXAgAG8//77ZGRkMGzYMNq2bevGdyC3k6+vLw0bNmTFihUcP36cBQsW8Pe//x2AiIgIjhw5wooVK3jooYeIiIjg+PHjrF+/nvj4eHx9fd1cvdxuyoM4Ux7EmfIgzpQHuZFixYo5/t9isQA5ZyYvXbo0ixcvpmfPnnn6EO3x4F7a0u0iuQ13Wloaa9asAXDM+Bo0aMCuXbtITU0lNjaWUqVKMWXKFL744gtiYmIoW7Ysn332GZcvX3bjO5DbyTAMChcuTGRkJKdPn6Z06dKkpaU5jr/y9vZm8ODBTJo0iXr16vHNN99gsVjYuXMnDz74oJurl9tNeRBnyoM4Ux7EmfIgtyq395g4cSLJycl88MEH7i5JnJgM7XPiMmlpadStW5cLFy4QGRlJz549qVOnDtWqVePjjz9m2rRprFq1inPnzjFmzBguXLjAkCFDaNu2LefOnXOcGEM8R0pKCqdPn+bLL79k48aNtGjRggkTJjh2B3Nms9kcay7FMykP4kx5EGfKgzhTHuRWnTp1is6dO1O7dm1iYmLcXY78RruXu5DdbqdixYpUq1aNn376iU2bNvHSSy8xatQoihQpQmBgILt37yYyMpIJEyYwdOhQ5s+fT6tWrdRwe6jQ0FBCQ0OpV68emZmZbNmyBYvFwrhx47BYLMTFxVGvXj3q1q2rBWYBoDyIM+VBnCkP4kx5kFtVpkwZOnXqxNSpU5k2bRoBAQHuLknQlm6XS01NZeTIkdjtdp555hnMZjNvvfUWQUFBrF27lgYNGrBt2zZ8fHw4fPgwhQoV0sXqPVDupT3g991/Ll26xNSpU9myZQvly5cnODiY6dOnk5KSQrVq1dxcsbiCcw5yKQ8Fl/IgzpQHcaY8yF+Rm5tz585htVopU6aMu0uS36jpzgeHDx9m+PDh2Gw25syZQ9myZdm/fz+TJk3iqaee4umnn77hzFXuTidPnuSbb74BoEaNGlStWvW6aXIXnJcvX2b+/Pls3ryZixcv8s477+gyDh7m4sWLZGZmkp2dTdmyZR3jN1oRozx4PuVBnCkP4kx5EPFcarrzSWpqKoMGDQLg1VdfJTw83M0ViSskJyfTrl07SpYsSXJyMh07dmTGjBmUKlXqumlzF5w2mw2z2cyVK1e0C5CH2b9/v+NyLqmpqfTu3ZuOHTvSqlUrIO8VDpQHz6c8iDPlQZwpDyKeTU13PkpNTWXIkCEYhsGYMWNo2rSpu0uS2+j48eOEh4fzzDPPMHr0aHbu3Em7du3Ytm0b9evXd0x37aXkxDOdOHGCBg0a0L17dzp16sQPP/zAnDlzsFgs9OrVi969ewM33oVQPI/yIM6UB3GmPIh4PjXd+Sw1NZURI0Zw7tw5Zs6cSaNGjdxdktwmMTExvP/++46TmwC0a9eOLl26YBgGwcHBNGvWDNCCsyD48MMPmThxIjt37sTf3x+AxMREZs2axcGDBxk2bBjdu3d3c5WSX5QHcaY8iDPlQcTzaXNbPqtatSrTpk2jXLlyOrmBh8nKyiI9PZ2DBw8CMHnyZNavX8/SpUuZNGkSUVFRxMXFAajhLgC8vb356aefSEtLA3JWtNStW5cXX3yRypUrs2zZMlJTU91cpeQX5UGcKQ/iTHkQ8Xxqut0gNDSUZcuWUaFCBXeXIrdR9erVycjIoFevXnTq1IkxY8awZs0aPv30U7744gsaNGjAunXruHTpkrtLlXxQpkwZrFYrW7duBXJ+RAHUrFmToUOHsmPHDnbv3u3OEiUflStXTnkQB+VB7Ha74//Lli2rPIh4ODXdbuLj4+PuEuQ2yV04PvbYY8TExPDiiy8SEhJC+/btadeuHZCzQK1SpQrfffedjuf2UFarlStXrjhuN2jQgKioKIYMGcLmzZsdJ70BaNSoEQ899BD/+c9/3FWuuNiPP/7o2OsFICwsjEGDBikPBVRycjLvvfee47byULAdPnyYt99+m1OnTgFQv3595UHEw+nXv8hfcPLkSfbs2YPdbsdkMjkWjo8++ihdu3alQoUKeHl55XnMjz/+SLVq1bRruQc6dOgQPXv2pHnz5nTv3p2dO3cCMHr0aLp160a7du1Yv359nhUuhmFQrlw5d5UsLnTy5EkefPBBxowZk2fr1KhRo5SHAigpKYmwsDAOHToE/L6idtSoUXTt2lV5KGD2799PeHg4KSkp2Gw2Rx5Gjx7NU089pTyIeCiv/z2JiDhLSUmhbt26VK1alUWLFlGvXj0sFkuek6OVLFmSVatWMXv2bEqUKEFycjJLly7lq6++4p577nHzO5Db6cCBAzRv3px27drRrVs33nnnHWbOnEnjxo3x8/PjzTffxNfXl44dO9KvXz+KFy9Oeno6X3/9NbNnz3Z3+eICR44c4eeff+bnn39mzpw5DBkyhLCwMPz8/HjjjTfw8fFRHgqIpKQkmjRpwrBhw5gwYQLw+zk9/Pz8mD17tuYPBcjp06d56qmn6NWrF9OmTQMgIyMDk8mEr68vCxYsUB5EPJTOXi7yJ5w7d46uXbtSokQJkpKS8Pb2Ji4ujrCwMEwmU57Ge/LkycyYMYMSJUpw3333MWfOHGrVquXmdyC3U1paGo899hgdO3Zk6tSpAKxZs4Zly5YRGxtLsWLFHNPOnz+fdevWcfr0acqUKcP48eOpXbu2u0oXF7pw4QK9evXi8ccfZ968eTzwwAOMHDmSmjVrOi4ZGBcXx5o1a5QHD/b9998TEhLCCy+8wJQpU7BarSxatIijR49SqFAhWrduTcOGDQFYsGABa9euVR483N69exk+fDgbN27Ey8uLYcOGcfDgQUwmEw899JBjOfKvf/2Ljz/+WHkQ8SBqukX+hKSkJObOnUvv3r2pW7euYyu3c+PtfB3uw4cPExQUhK+vL0FBQe4tXm4rwzBYuXIlu3bt4uWXX6ZkyZIAvPDCC6xZswaTyUS1atVo2rQpo0ePBuDKlSv4+/uTmZnpuCyMeBabzcaFCxdo2rQpW7ZsISEhgSlTplCnTh0OHDhA6dKlWbVqFQC//vorfn5+yoMHMgyD2NhYxo0bx3PPPceECRNo3bo1586dw8/Pj2PHjlGuXDmeeeYZBg4cCCgPBcHSpUuJjo7m6NGjtG/fnqtXr9K2bVuOHj3Kli1bKF++PBs2bAC0vBDxNGq6Rf6Eq1evkpqaSo0aNbBYLGRkZBAWFoaXlxdxcXHUr18fyLl8mLe3t5urFVf7+eefOX78uGMPhsmTJ/Pqq68yffp0KlWqxIYNG9i9ezezZs0iPDw8zwoZ8Uy5e7v06NGDp59+moiICD755BN69uxJZmYms2fP5tlnnwVyGnSLxeLegsVl0tPTWbJkCQsWLOCHH37gb3/7G3PnzqVcuXJcvHiR/v37c+zYMdauXUvJkiU1fygAjh49ylNPPUWXLl34/PPPiYmJoUqVKtjtdtauXcv48eN55ZVX6Ny5s+YPIh5Gc3eRP8Hf359atWphsViwWq34+fmRmJhIdnY2ffr0Yffu3WRkZDBt2jTmzp3r7nLFxQIDAx0Nd3Z2NkFBQWzYsIGhQ4fy97//nUmTJpGSkkJycjKAflAXALmHl1gsFr788ksAVq9ejc1mo3z58mzbto2EhATHNOK5ihQpQs+ePXnmmWdo3bo148ePp1y5ctjtdoKCgpgyZQoJCQns3bsX0PyhIAgMDCQoKIh58+bx008/OU6OZjabadmyJb/++itHjhwBNH8Q8TQ6kZrIX+Tj40N2djY+Pj4kJiZSt25dnn/+eYKDg9mwYQP79u1zd4mSj7y8vBgwYICj6bLb7VitVho0aECVKlXcXJ3kl9wt3S1atODo0aMMHDiQTz75hD179rBv3z7++c9/4uPjQ61atfDz83N3ueJiQUFBPP/88zRr1owaNWoAOQ2W3W4nPT2dBx54gODgYDdXKfmlWLFizJ492zF/WL58Ob169QIgICCAGjVqULx4cTdXKSKuoKZb5P/By8vL0Xjv2rWLoKAgjh8/TkJCAtWrV3d3eeJGZrOZuXPncu7cOWWhAMld6VKxYkV69epFyZIlWb9+PRUrVqRixYqYTCZq166thrsACQwMpFGjRnnGzGYzq1evJiAggBIlSripMnGH6tWrs3nzZtq0acPMmTP5/vvvadGiBR9//DHbtm1znNVcRDyLjukWuQ2uXr3KP//5TxYtWsQ333yjJquAS0hIYM2aNbzzzjt89dVXOutsAZSVlcXSpUupX78+tWrVynNlAynYdu3axUcffURMTAzbt2/XVS0KqNTUVN544w2+/PJLvL29KVSoEPPnz6dOnTruLk1EXEBNt8htkJaWRt++fZkwYYLjEjBSMKWnpzNixAhSUlKYN2+eflAXYDoxllzrwoULDBw4kMOHD/Puu+9qhVwBl5WVRWZmJpcvX6ZQoULce++97i5JRFxETbfIbWAYBhkZGbqshwBw9uxZDMPgvvvuc3cpInKH+emnnzAMg1KlSrm7FBERySdqukVERERERERcRPu9iYiIiIiIiLiImm4RERERERERF1HTLSIiIiIiIuIiarpFREREREREXERNt4iIiIiIiIiLqOkWERERERERcRE13SIiIiIiIiIuoqZbRERERERExEXUdIuIiNwh4uPjsVgstG7dOl9f12q1Mm3aNOrVq0ehQoUIDAykdu3ajBkzhlOnTuVrLSIiIp7GZBiG4e4iREREBPr27UtAQAALFizg4MGDVKhQweWvmZmZSatWrUhOTmbcuHGEh4cTGBjId999x5o1awgKCmLKlCk3fKzVasXHx8flNYqIiNzNtKVbRETkDnDlyhU++OADBgwYQNu2bXn33Xevm2bdunVUrVoVf39/mjdvzuLFizGZTFy8eNExTXx8PA8//DD+/v6UL1+eIUOGcOXKlZu+7syZM9m+fTtbtmxhyJAhhIWFUaVKFSIiIoiJiWHy5MmOaR955BEGDRrEiBEjKF68OC1btgRg69atNGzYEF9fX0qXLs3IkSPJzs52PO7+++/nrbfeyvO6derU4bXXXnPcNplMxMTEEBkZib+/PxUrVmTlypV/7o8oIiJyB1LTLSIicgdYsWIFISEhhISE0KNHDxYtWoTzzmjHjh2jc+fOdOjQgX379tGvXz9eeeWVPM+xf/9+IiIi6NSpE8nJyaxYsYLt27czaNCgm77u8uXLadmyJXXr1r3h/SaTKc/txYsX4+XlxY4dO5g3bx4nT56kTZs2NGjQgKSkJGJiYoiLi2PixIl/+m8wduxYnnjiCZKSkujRowfdunXj0KFDf/p5RERE7iRqukVERO4AcXFx9OjRA4DWrVtz+fJlNm/e7Lg/NjaWkJAQpk2bRkhICF27duXZZ5/N8xzTpk2je/fuDBs2jKpVq9KkSRNmz57NkiVLyMjIuOHrHjlyhJCQkDxjHTt2JCAggICAAJo0aZLnvipVqvDGG28QEhJCaGgoc+fOpXz58rz99tuEhobSoUMHxo0bx/Tp07Hb7X/qb/Dkk0/St29fqlWrxoQJE6hfvz5z5sz5U88hIiJyp1HTLSIi4maHDx8mISGBrl27AuDl5UWXLl1YuHBhnmkaNGiQ53ENGzbMc3vPnj28++67joY5ICCAiIgI7HY733///U1f/9qt2XPnzmXfvn307t2bX3/9Nc999evXz3P70KFDNG7cOM9zhIeHc/nyZU6cOHEL7/53jRs3vu62tnSLiMjdzsvdBYiIiBR0cXFxZGdnU7ZsWceYYRh4e3uTnp5OkSJFMAzjuub42nOh2u12+vXrx5AhQ657jZudlK1q1aqkpKTkGStdujQARYsWvW76QoUKXVfDzerKHTebzdfVmpWVdcN6rnXtc4uIiNxttKVbRETEjbKzs1myZAnTp09n3759jn9JSUkEBwezbNkyAEJDQ/nmm2/yPHb37t15bterV49vv/2WKlWqXPfvZmcZ79atG5s2bSIxMfEv1V+9enXi4+PzNNXx8fHce++9jpUIJUqU4Mcff3Tc/8svv9xwy/uuXbuuux0aGvqX6hIREblTqOkWERFxo/Xr15Oenk6fPn2oWbNmnn+dO3cmLi4OgH79+pGSksLLL7/MkSNH+OCDDxxnOM/dGvzyyy+zc+dOoqKi2LdvH6mpqaxbt47Bgwff9PWHDx9O48aNadGiBbNmzWLv3r18//33fPbZZ2zcuBGLxfKH9Q8cOJC0tDQGDx5MSkoKa9euJTo6mhEjRmA25/zMaNGiBUuXLmXbtm0cOHCAnj173vB5V65cycKFCzly5AjR0dEkJCT84UngRERE7gZqukVERNwoLi6Oxx57jMDAwOvue+KJJ9i3bx979+6lYsWKfPjhh6xevZpatWoRExPjOHu5r68vALVq1WLr1q2kpqbSrFkz6taty9ixYx27i9+In58fmzdvZuTIkSxatIimTZvywAMPMGzYMMLDw1mzZs0f1l+2bFk++eQTEhISqF27Nv3796dPnz6MGTPGMc2oUaN4+OGHadu2LW3atKFDhw5Urlz5uucaN24c77//PrVq1WLx4sUsW7aM6tWr38qfUURE5I5lMq49yEpERETuCpMmTSI2Npa0tDR3l/L/ZjKZ+Oijj+jQoYO7SxEREbmtdCI1ERGRu8TcuXNp0KABxYoVY8eOHUybNk27X4uIiNzh1HSLiIjcJVJTU5k4cSIXLlygQoUKvPDCC4waNcrdZYmIiMgf0O7lIiIiIiIiIi6iE6mJiIiIiIiIuIiabhEREREREREXUdMtIiIiIiIi4iJqukVERERERERcRE23iIiIiIiIiIuo6RYRERERERFxETXdIiIiIiIiIi6ipltERERERETERdR0i4iIiIiIiLjI/wEeGQhzOham/wAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each age group from the dfDisatisfied DataFrame\n", + "age_group_counts_series = dfDisatisfied['age groups'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts) for plotting\n", + "df_counts = age_group_counts_series.reset_index()\n", + "df_counts.columns = ['Age Group', 'Count']\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "# Optional: Ensure all groups are present, even if count is 0,\n", + "# and ensure they are properly ordered by the chronological order of ages.\n", + "# We will use the 'order' parameter in sns.barplot for this.\n", + "age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(10, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Age Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=age_order, # Use the defined chronological order\n", + " palette='viridis'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Age Group (Chronological Order)')\n", + "plt.xlabel('Age Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=45, ha='right')\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", + "plt.show() # Use plt.show() if running in a script/local environment" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b07ff56c-872a-4b4e-b6d8-5e72e13b82a1", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each Gender from the dfDisatisfied DataFrame\n", + "gender_counts_series = dfDisatisfied['Gender'].value_counts()\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = gender_counts_series.reset_index()\n", + "df_counts.columns = ['Gender', 'Count']\n", + "\n", + "# Sort the data by count (or percentage) before plotting\n", + "df_counts = df_counts.sort_values(by='Count', ascending=False)\n", + "\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(8, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Gender',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " # Order is naturally handled by the prior sorting of df_counts\n", + " palette='Set2' # Used a different palette (Set2)\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Gender')\n", + "plt.xlabel('Gender')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=0, ha='center') # No rotation needed\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_gender_percentage_bar_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0c050280-c376-4dca-828d-d0a83da57c19", + "metadata": {}, + "outputs": [], + "source": [ + "dfDisatisfied['Flight Distance'].describe()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "35a1f185-d10a-4141-b256-a59ac5f07b4c", + "metadata": {}, + "outputs": [], + "source": [ + "df['Flight Distance_group'].describe() " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2e48782b-7bc1-40ab-a764-b90ca6453b23", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", + "# Get the count of each Flight Distance group from the dfDisatisfied DataFrame\n", + "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = distance_group_counts_series.reset_index()\n", + "df_counts.columns = ['Flight Distance Group', 'Count']\n", + "\n", + "# Define the chronological/logical order for the x-axis\n", + "distance_labels = ['Short-Haul (0-500)', 'Medium-Haul (500-1500)', 'Long-Haul (1500-3000)', 'Ultra-Long (3000+)']\n", + "\n", + "# --- 2. CALCULATE PERCENTAGE ---\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART ---\n", + "plt.figure(figsize=(10, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Flight Distance Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=distance_labels, # Enforce chronological order\n", + " palette='magma'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", + "plt.xlabel('Flight Distance Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit for the annotations\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart.png')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "614fdf71-c65c-42cd-8086-91fa69269eab", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", + "\n", + "# --- Define the Conditions ---\n", + "# Assuming you are applying this logic to the dfDisatisfied DataFrame\n", + "conditions = [\n", + " (dfDisatisfied['Flight Distance'] < 750),\n", + " (dfDisatisfied['Flight Distance'] >= 750) & (dfDisatisfied['Flight Distance'] < 1500),\n", + " (dfDisatisfied['Flight Distance'] >= 1500) & (dfDisatisfied['Flight Distance'] < 2250),\n", + " (dfDisatisfied['Flight Distance'] >= 2250) & (dfDisatisfied['Flight Distance'] < 3000),\n", + " (dfDisatisfied['Flight Distance'] >= 3000)\n", + "]\n", + "\n", + "# --- Define the Corresponding Labels and Order ---\n", + "distance_labels = [\n", + " 'Short, until 750 miles',\n", + " 'Medium-short, until 1500 miles',\n", + " 'Medium-Long, until 2250 miles',\n", + " 'Long, until 3000 miles',\n", + " 'Very long, more than 3000 miles'\n", + "]\n", + "\n", + "# Apply np.select() to create the grouping column\n", + "dfDisatisfied['Flight Distance_group'] = np.select(\n", + " conditions, \n", + " distance_labels, \n", + " default='Unknown'\n", + ")\n", + "\n", + "# --- 2. AUTOMATIC DATA AGGREGATION & PERCENTAGE CALCULATION ---\n", + "\n", + "# Get the count of each Flight Distance group\n", + "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", + "\n", + "# Convert the Series of counts into a DataFrame (df_counts)\n", + "df_counts = distance_group_counts_series.reset_index()\n", + "df_counts.columns = ['Flight Distance Group', 'Count']\n", + "\n", + "# Calculate Percentage\n", + "total_customers = df_counts['Count'].sum()\n", + "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", + "\n", + "\n", + "# --- 3. PLOT BAR CHART WITH ANNOTATIONS ---\n", + "plt.figure(figsize=(12, 6))\n", + "\n", + "ax = sns.barplot(\n", + " x='Flight Distance Group',\n", + " y='Percentage',\n", + " data=df_counts,\n", + " order=distance_labels, # Ensures the groups plot in logical order\n", + " palette='magma'\n", + ")\n", + "\n", + "# Add titles and labels\n", + "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", + "plt.xlabel('Flight Distance Group')\n", + "plt.ylabel('Percentage (%)')\n", + "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", + "\n", + "# Add percentage values on top of the bars (Annotations)\n", + "for p in ax.patches:\n", + " ax.annotate(f'{p.get_height():.1f}%',\n", + " (p.get_x() + p.get_width() / 2., p.get_height()),\n", + " ha='center', va='center',\n", + " xytext=(0, 9),\n", + " textcoords='offset points')\n", + "\n", + "# Adjust y-limit to ensure annotations are visible\n", + "plt.ylim(0, df_counts['Percentage'].max() * 1.20)\n", + "plt.grid(axis='y', linestyle='--')\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart_final.png')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a805f6b8-ea67-4ded-a3a3-b2659a133da8", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From ae6ae768d37a36bffdfd5c4c395dc91bf8e5c1bb Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Wed, 10 Dec 2025 17:08:01 +0100 Subject: [PATCH 15/26] D3, v2 --- ..._Project1_Antonio 2.ipynb => Airline_Project1_Antonio_3.ipynb} | 0 1 file changed, 0 insertions(+), 0 deletions(-) rename notebooks/{Airline_Project1_Antonio 2.ipynb => Airline_Project1_Antonio_3.ipynb} (100%) diff --git a/notebooks/Airline_Project1_Antonio 2.ipynb b/notebooks/Airline_Project1_Antonio_3.ipynb similarity index 100% rename from notebooks/Airline_Project1_Antonio 2.ipynb rename to notebooks/Airline_Project1_Antonio_3.ipynb From 1624762276712446a0de8e4538b28df66231796c Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Wed, 10 Dec 2025 18:05:34 +0100 Subject: [PATCH 16/26] d3, cleared output --- notebooks/Airline_Project1.ipynb | 1268 +----------------------------- 1 file changed, 27 insertions(+), 1241 deletions(-) diff --git a/notebooks/Airline_Project1.ipynb b/notebooks/Airline_Project1.ipynb index 0ac64307..b80c6427 100644 --- a/notebooks/Airline_Project1.ipynb +++ b/notebooks/Airline_Project1.ipynb @@ -2,411 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "561808a4-27ef-4523-892a-8584a31efefa", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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103904 rows × 25 columns

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" - ], - "text/plain": [ - " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", - "0 0 70172 Male Loyal Customer 13 Personal Travel \n", - "1 1 5047 Male disloyal Customer 25 Business travel \n", - "2 2 110028 Female Loyal Customer 26 Business travel \n", - "3 3 24026 Female Loyal Customer 25 Business travel \n", - "4 4 119299 Male Loyal Customer 61 Business travel \n", - "... ... ... ... ... ... ... \n", - "103899 103899 94171 Female disloyal Customer 23 Business travel \n", - "103900 103900 73097 Male Loyal Customer 49 Business travel \n", - "103901 103901 68825 Male disloyal Customer 30 Business travel \n", - "103902 103902 54173 Female disloyal Customer 22 Business travel \n", - "103903 103903 62567 Male Loyal Customer 27 Business travel \n", - "\n", - " Class Flight Distance Inflight wifi service \\\n", - "0 Eco Plus 460 3 \n", - "1 Business 235 3 \n", - "2 Business 1142 2 \n", - "3 Business 562 2 \n", - "4 Business 214 3 \n", - "... ... ... ... \n", - "103899 Eco 192 2 \n", - "103900 Business 2347 4 \n", - "103901 Business 1995 1 \n", - "103902 Eco 1000 1 \n", - "103903 Business 1723 1 \n", - "\n", - " Departure/Arrival time convenient ... Inflight entertainment \\\n", - "0 4 ... 5 \n", - "1 2 ... 1 \n", - "2 2 ... 5 \n", - "3 5 ... 2 \n", - "4 3 ... 3 \n", - "... ... ... ... \n", - "103899 1 ... 2 \n", - "103900 4 ... 5 \n", - "103901 1 ... 4 \n", - "103902 1 ... 1 \n", - "103903 3 ... 1 \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "0 4 3 4 4 \n", - "1 1 5 3 1 \n", - "2 4 3 4 4 \n", - "3 2 5 3 1 \n", - "4 3 4 4 3 \n", - "... ... ... ... ... \n", - "103899 3 1 4 2 \n", - "103900 5 5 5 5 \n", - "103901 3 2 4 5 \n", - "103902 4 5 1 5 \n", - "103903 1 1 4 4 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "0 5 5 25 \n", - "1 4 1 1 \n", - "2 4 5 0 \n", - "3 4 2 11 \n", - "4 3 3 0 \n", - "... ... ... ... \n", - "103899 3 2 3 \n", - "103900 5 4 0 \n", - "103901 5 4 7 \n", - "103902 4 1 0 \n", - "103903 3 1 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction \n", - "0 18.0 neutral or dissatisfied \n", - "1 6.0 neutral or dissatisfied \n", - "2 0.0 satisfied \n", - "3 9.0 neutral or dissatisfied \n", - "4 0.0 satisfied \n", - "... ... ... \n", - "103899 0.0 neutral or dissatisfied \n", - "103900 0.0 satisfied \n", - "103901 14.0 neutral or dissatisfied \n", - "103902 0.0 neutral or dissatisfied \n", - "103903 0.0 neutral or dissatisfied \n", - "\n", - "[103904 rows x 25 columns]" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", @@ -422,27 +21,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "a86604ec-da44-40c0-894e-0a118b9ca685", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Age Group creation successful.\n", - "Flight distance group Group creation successful.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" - ] - } - ], + "outputs": [], "source": [ "binary_change= {\n", " 'satisfied': 1,\n", @@ -513,7 +95,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "6f945079-4c90-40ee-83b9-53af53e43388", "metadata": {}, "outputs": [], @@ -524,464 +106,10 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\3011661649.py:47: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning.\n", - " vertical_stats_table = pivot_stats.stack(level=0)\n" - ] - }, - { - "data": { - "text/html": [ - "
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satisfactionneutral or dissatisfiedsatisfied
MetricStatistic
Agemean37.56668841.750583
median36.00000043.000000
std16.45982512.767833
Arrival Delay in Minutesmean17.12753612.630799
median0.0000000.000000
std40.56024835.962008
Baggage handlingmean3.3759913.966396
median4.0000004.000000
std1.1769781.099607
Checkin servicemean3.0429523.646041
median3.0000004.000000
std1.2811581.158732
Cleanlinessmean2.9361233.744342
median3.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.000000
std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.000000
std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.000000
std1.1756031.091486
Inflight wifi servicemean2.3996333.161288
median2.0000004.000000
std0.9643481.588697
Leg room servicemean2.9908123.822143
median3.0000004.000000
std1.3031591.175515
On-board servicemean3.0191583.857324
median3.0000004.000000
std1.2857901.127130
Online boardingmean2.6561254.027474
median3.0000004.000000
std1.1459051.191609
Seat comfortmean3.0362953.966530
median3.0000004.000000
std1.3031421.142077
\n", - "
" - ], - "text/plain": [ - "satisfaction neutral or dissatisfied \\\n", - "Metric Statistic \n", - "Age mean 37.566688 \n", - " median 36.000000 \n", - " std 16.459825 \n", - "Arrival Delay in Minutes mean 17.127536 \n", - " median 0.000000 \n", - " std 40.560248 \n", - "Baggage handling mean 3.375991 \n", - " median 4.000000 \n", - " std 1.176978 \n", - "Checkin service mean 3.042952 \n", - " median 3.000000 \n", - " std 1.281158 \n", - "Cleanliness mean 2.936123 \n", - " median 3.000000 \n", - " std 1.325955 \n", - "Departure Delay in Minutes mean 16.503728 \n", - " median 0.000000 \n", - " std 40.191886 \n", - "Departure/Arrival time convenient mean 3.129112 \n", - " median 3.000000 \n", - " std 1.500368 \n", - "Ease of Online booking mean 2.546850 \n", - " median 3.000000 \n", - " std 1.205847 \n", - "Flight Distance mean 928.919971 \n", - " median 671.000000 \n", - " std 790.452308 \n", - "Food and drink mean 2.958050 \n", - " median 3.000000 \n", - " std 1.346607 \n", - "Gate location mean 2.976121 \n", - " median 3.000000 \n", - " std 1.198500 \n", - "Inflight entertainment mean 2.894156 \n", - " median 3.000000 \n", - " std 1.323619 \n", - "Inflight service mean 3.388814 \n", - " median 4.000000 \n", - " std 1.175603 \n", - "Inflight wifi service mean 2.399633 \n", - " median 2.000000 \n", - " std 0.964348 \n", - "Leg room service mean 2.990812 \n", - " median 3.000000 \n", - " std 1.303159 \n", - "On-board service mean 3.019158 \n", - " median 3.000000 \n", - " std 1.285790 \n", - "Online boarding mean 2.656125 \n", - " median 3.000000 \n", - " std 1.145905 \n", - "Seat comfort mean 3.036295 \n", - " median 3.000000 \n", - " std 1.303142 \n", - "\n", - "satisfaction satisfied \n", - "Metric Statistic \n", - "Age mean 41.750583 \n", - " median 43.000000 \n", - " std 12.767833 \n", - "Arrival Delay in Minutes mean 12.630799 \n", - " median 0.000000 \n", - " std 35.962008 \n", - "Baggage handling mean 3.966396 \n", - " median 4.000000 \n", - " std 1.099607 \n", - "Checkin service mean 3.646041 \n", - " median 4.000000 \n", - " std 1.158732 \n", - "Cleanliness mean 3.744342 \n", - " median 4.000000 \n", - " std 1.142247 \n", - "Departure Delay in Minutes mean 12.608084 \n", - " median 0.000000 \n", - " std 35.382595 \n", - "Departure/Arrival time convenient mean 2.970305 \n", - " median 3.000000 \n", - " std 1.552213 \n", - "Ease of Online booking mean 3.031582 \n", - " median 3.000000 \n", - " std 1.575306 \n", - "Flight Distance mean 1530.140255 \n", - " median 1250.000000 \n", - " std 1128.126574 \n", - "Food and drink mean 3.521310 \n", - " median 4.000000 \n", - " std 1.236187 \n", - "Gate location mean 2.977879 \n", - " median 3.000000 \n", - " std 1.374244 \n", - "Inflight entertainment mean 3.964931 \n", - " median 4.000000 \n", - " std 1.076907 \n", - "Inflight service mean 3.969461 \n", - " median 4.000000 \n", - " std 1.091486 \n", - "Inflight wifi service mean 3.161288 \n", - " median 4.000000 \n", - " std 1.588697 \n", - "Leg room service mean 3.822143 \n", - " median 4.000000 \n", - " std 1.175515 \n", - "On-board service mean 3.857324 \n", - " median 4.000000 \n", - " std 1.127130 \n", - "Online boarding mean 4.027474 \n", - " median 4.000000 \n", - " std 1.191609 \n", - "Seat comfort mean 3.966530 \n", - " median 4.000000 \n", - " std 1.142077 " - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "numeric_cols_df = df.select_dtypes(include=np.number)\n", "\n", @@ -1040,21 +168,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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p3ry5df5HR0db5XzyySfGGGOdr25ubtZ9sGbNmsbHx8dIMuHh4ebYsWNZbvuTTz5p1bFkyZImOjrahIWFWeeB/T6Y23u9/e+wqVOnZiqrIM/5d99913h6epqSJUuahg0bWn+LeHh45Op5b7dt2zarDj///HOu12vevLkJDQ01kkxoaKjD9r/++utWuoceesh6/lSvXt1ER0ebcuXKWWW++eabDvnm9v6Q03415n/3jyuf688++6xVdqVKlUyjRo1M5cqVjZeXl5Fk5syZk+t9AAAoOghYAAAKpctf7vzxxx9Gkrntttsc0gwYMMBIMgsWLMjx5Y79H6hRUVFm06ZN1vyzZ8+aJ554wvoH+JUmTZpkDh8+7DDv7Nmz5vXXXzeSTOvWrTOtY/8Hnaenp+nZs6fDC5cPPvjAekGZlxcx9913n5Xn888/b7Zt25blC8ArHThwwPoHdd++fR1euKSnp5v58+ebefPmWfNSUlKsl6Z33323SUpKspZNmzbNuLu7W/v7cvZ/pLq7u5umTZuagwcPWsvOnTtnjDHmo48+MpJM5cqVHf5hn5aWZl577TXr5YE9vTHGdO7c2Ugy//d//2cuXLjgUOb69evNrFmzrroPLpfd+WGMMd9//7314mHmzJnW/MTERNO9e3frhcvlL4yM+d956u7ubl599VVz8eJFY4wxGRkZWb7cvVJuAhZ+fn4OLwiSkpLMrbfeaiSZ3r1752LLHV2PgMXYsWONJFOiRAmHQFRCQoKJioqyXkpnF7Dw9PQ0LVu2dLj+5s2bZ52DVwYBsnuhnVtbtmwx8+fPz3TM9u7da1q2bGkkmWnTpmVaLz/HKCMjwzRo0MBIMh06dHC4Lj///HPj6elpvaTMbcDiq6++sl645Yf95b2np6cpX768Wbt2rbVs165dVtDyww8/dFgvOTnZeuk5aNAgk5iYaC37448/TJ06dYwk89577zms991331nXzfjx401qaqq1LCUlxfz3v/81O3bssOZldXy3bdtmQkJCjCQzYsSIfG9zdgELDw8PExgY6HC/O3r0qKlXr56RZIYNG5an8lz9TMsp0GCXm3t5Tvl069bNSDJVqlQxa9ascVi2e/duM2bMGGv666+/NpJMZGSkQznGGHP8+HEzYcIEk5KSkm1dr2TfV56enmb8+PFWgDElJcV6hoaFhTncwxcvXmwkmXr16mWZ5/jx4410KeiWW/aATbFixcyoUaPM7t27c7VefHy8+fLLL80///zjMP/o0aOmZ8+eRrr0IcSVsrsHXy6r82jcuHHWOXhlMObAgQPm7bffzpRPToHUM2fOmGnTpmXK6/Tp02bgwIFGkomJicm03oQJE6x76IwZMxwCwydPnjTjx483x48ft+bl5l6f3Yv1gj7nPT09zahRo0xaWpox5lLg0H5uNWnSJNv6XCk9Pd36WyskJMS89957ma6B7GQXFLjcggULzJo1azL9nbhy5UpTrlw54+7ubvbs2eOwLDf3h/wELI4fP27c3NxMUFCQ+eWXXxzSnzt3znz++ef5CrIDAAo/AhYAgELp8pc7xhgTFRVl3N3dzZEjR4wxxpw/f94EBwebMmXKmIsXL2b7cuf48ePG29vbBAYGZvkPwvT0dNOoUSMjyaxcuTLX9bvllluMJHPo0CGH+fZ/0IWEhJjk5ORM69lfVH777be5LuvQoUOmcuXK1vZJl1octG3b1sTGxpqdO3dmuZ79xdWtt96aqwDH5MmTjSRTtmxZh8DBlfm1aNHCYb79H6ne3t6ZAjzGGHPhwgUTEhJi3N3dze+//55l2XfddZeRZKZPn27Nq1GjhpHk8BK0IHIKWNhfMj399NOZlqWkpJhSpUoZSdbXpHb287RLly75qlNuAhZPPfVUpmVbt261zoO8sr/gyu6XU12yy+vyl2Xp6enWF/eXvxSy2717txV4yC5g4evrm+X12qNHDyPJvPXWWw7zCxqwyMmePXuMJNO+fftMy/JzjJYsWWJtY1Zf6Q8aNMjKN7cBC/tLv6ioqFylv5L95b0k880332Ra/s477xhJ5s4778xyfvfu3bPMd8uWLcZms5mbbrrJYX7t2rXzFGi48viuW7fOlChRwthsNjNx4sRc5XGlqwUspKy/vJ83b16OL7mz4+pnWl4CFtndy3PKZ926dda6f/7551X3x6hRo4ykfB+/K9n31ZXnqDH/ewZJji0fMjIyrBY6lwd+7OzBqfnz5+e6Hlu2bLFaT9l/pUqVMh07djSjR482CQkJed62s2fPGi8vL1OtWrVMy/IbsHj00UeNJDN37txc1yOvLb8uFxoaavz8/KygvjGXtsu+ry5/9uekIAGLa/GcP3HihNXy5NSpU7naBmMuBcvsLTvsv/Lly5tu3bqZd999N9sWXLkJWOTk448/NpIcWmQYc+0CFqtXr87xGQEAuHExhgUAoEh44IEHlJ6ers8//1ySNH/+fJ05c0Z9+vSRh4dHtustWLBAFy5cUIcOHVSxYsVMy93c3NS5c2dJsvqCvtyGDRv0/PPP684771SrVq10yy236JZbbtGff/4pSdq6dWuW5fbp00f+/v6Z5tsHus1LH+gVKlTQpk2bNHz4cKvf8MTERP3888+KjY1VrVq1NGDAAKufZzt7f+FDhgzJsv/qK9kHgRwwYIB8fHwyLX/66aclSb/99lum/rQlqV27dipfvnym+atXr9axY8fUoEEDRUVFZVn2nXfeKcnxGISGhkqSvvzyy6vWvSCSk5O1evVqSdJTTz2Vabmfn58GDBgg6X/76ErXcsDzhx9+ONO8iIgI+fj4KDExUSdPnsxXvqGhoWrevHmmX0EHY96xY4cOHz4sf39/9erVK9PyqlWrqkWLFjnmcfvtt2d5vebn+smtCxcu6LPPPtOAAQPUoUMHtWjRQrfccov69esnSdqyZUu26+blGP3444+SpF69emUaFFuSnnjiiTzX/Z9//pGkLO85eVG8ePEsx07Ibr9/++23krLefkmqV6+ewsPDtW/fPquf8j179mjHjh3y8vLS4MGD81zHFStW6NZbb1ViYqKmTJmiQYMG5TmP3HrooYcyzXPWOeiqZ1puZHcvz4n9edO9e3dVq1btqunt9/cffvhBZ8+ezXsls/Hkk09mmufl5WWdo/brT7o0JoD9+v70008d1tm8ebO2bt2qkJCQTINn56RevXravn27/vOf/6hs2bKSpL///lsLFy7UsGHDVKVKFb344otZjrWSkZGhuXPn6sknn1THjh2te1D79u1ls9m0e/dup+0r+/6fM2dOtmP05MfPP/+s//znP7rjjjvUsmVL62+mxMREnT171mHcrF9//VUnT55U+fLlsx1Tx1mc8ZzP6j5XqlQp6++yvNwT2rVrpy1btujhhx9WcHCwJOnIkSP67rvv9NRTTyk8PFzvvvturvO70okTJzRx4kTde++9ateunXUcJkyYICnn55kz2c+ztWvXZjv2GwDgxpT9X7sAABQiffr00ZAhQzRjxgw988wzmjFjhiTp/vvvz3G9bdu2SZLWrFmjW265Jcs09gE3Dx8+bM0zxmjgwIEOA09m5dSpU1nOr1KlSpbzy5QpI+nSP57zIigoSLGxsYqNjdX+/fu1bt06LVu2THPnztWxY8f08ccfKz09XVOmTJF06QWmfXtuvvnmXJVhD8LUrl07y+XVqlWTl5eXUlNTtXfvXtWrV89hea1atbJcz34M4uPjsz0GZ86ckeR4DAYPHqwlS5ZowIABGj9+vDp06KBbbrnFGszVWfbs2aOMjAxr0Nqs1KlTR9L/9tGVstt2Z8juXCpdurQOHjyo5OTkfO2P/v375zjodX7ZX0jVrFlTXl5eWaapV69ejoOSO/v6uZqEhATddttt2rVrV7ZpsrvWpbwdI/s5lN05U61aNXl4eOTpJWKxYsUkKctAYl7kdb/br+1XXnlFb7zxRpbr2gfbPXz4sCpWrKi4uDhJl+4z9nrn1rp16/TFF18oIyNDX3zxhe666648rZ8XpUqVUlBQUKb5zjoHr/czLS/ycz+zH9fcPm+6deum8PBw/fTTTypfvrxuv/12tWjRQq1bt7but/mRXd3t86+8hz/44IMaMWKEPvvsM40dO9YKFtkDGPfff7/c3d3zVIeQkBC99dZbeuuttxQXF6f169dr6dKlmjdvns6cOaM33nhD3t7eeuWVV6x1zpw5o06dOlkv1bNz+vRp+fn55ak+WXnwwQc1duxYTZs2TQsXLrT2f5s2bbJ9DuYkNTVVvXv31nfffZdjusvvo/ZzpnHjxnJzu7bfWTrjOZ/T/XHXrl15vidUrVpVkydP1qRJk7R161atX79eP/30kxYsWKCUlBQNGjRIQUFBef4g4qefftLdd9+txMTEbNPk9DxzpgoVKqhXr1766quvVLVqVbVp00atW7dWixYtdPPNN+cYnAUAFG20sAAAFAkhISFq166dNm/erJUrV2rhwoWqWbOmoqOjc1zP/g+2gwcP6tdff83yt2fPHknSuXPnrPVmzJihDz74QP7+/vrggw+sLxvNpe4Wra8BL168mGW52X3pbP9HuTEmbzvgMpUrV1bv3r310Ucfae/everTp48kadq0aTp48KAkKSkpyUqf1Uu3rNj/sW1/IXclm82m0qVLS/rfF92Xy26b7cfgxIkT2R6DP/74Q5LjMbjjjjv0ww8/qFmzZvrzzz81ceJE9erVSyEhIbr77rvz/TLuSvbtLl26dLYtUexfyma13VLBv2zPSV7OpV69ellfUl7+u57sL81zehl9tRfV1/L6yUpMTIx27dqlJk2aaNGiRTp27JhSU1NljLGu8ZwCCHmp7+XnW3brZNXyIicVKlSQdCkoWBB53e/2a3vjxo3ZXtv2a8Z+bdvvTfavivPi8OHDOn/+vAICAlSjRo1s0y1cuDDL68Ae0M2Nq+2Lgrrez7S8yM/9LK/H1d/fX6tWrdKDDz5oBaAGDhyounXrqk6dOpo/f36e6yBl//zK7h4eFhamtm3b6vjx41q4cKGkS9f6Z599JunSvaEgatWqpb59++rTTz/Vnj171LZtW0nSmDFjHFpFPvPMM1q9erVq1Kihb775RocPH9aFCxesvzns13h2f3PkVfny5bV69WrdddddSkxM1KeffqqHH35YVapUUdOmTa8aOLnSm2++qe+++04hISGaPn264uPjdf78eav+zZs3z1T/gtwL8upaPucL+lxyc3NT/fr1NWDAAH311VeKi4tTRESEJGnkyJF5yuvMmTO65557lJiYqL59+2rNmjU6ffq00tPTZYzR4sWLJTnvPMqN6dOna/jw4SpTpox++ukn/d///Z9atGih8uXLa9y4cVm2NgIAFH0ELAAARcYDDzxg/Tc1NdWazklAQIAk6cUXX7T+4Zzdb9q0adZ6s2bNkiSNHz9ejz/+uKpWrSpfX19ruT0w4Gp+fn6aNGmS3NzcZIzRhg0bJDm+EM7pK7vL2ffV8ePHs1xujNGJEycy5Z/bfO+7776rHoMrv7rv1KmTfv31V504ccLqKiE4OFhfffWVunTp4pR/dNvrd+LEiWxfONi/WM7rF+HX2/r167N8gXk92V/q5PS1aXYvhFzhyJEjWrZsmfz8/LRgwQJ16NBBZcuWlaenpyTnX+uXn29ZycjIyHM3X82aNZN06evr7Lqpuxbs27J79+6rXtutW7eW9L9ryN6qKi+6d++u//znPzp16pTatWuXbYuYv/76K8vr4N/WJcn1fKZda/k5rhUrVtSUKVN06tQprVmzRm+++aaio6O1Y8cOdevWTWvXrs1zPbK7ruzPtazu4f3795f0v1YVCxcu1PHjxxUdHV2g1h5XKlmypNXNT0pKinbs2CHpUoDE3vXh3Llz1aNHD5UvX95qoZaWlqZjx445rR52tWrV0tdff60zZ85o2bJlio2NVc2aNbVmzRrddttteQqA2v9mmjZtmh544AGFhYXJ29vbWp7VfbQg94K8KkzP+UqVKunNN9+UdKllyOnTp3O97sKFC3X69Gk1bdpU06ZNU5MmTRQcHGwFVQryPLMHerLbf9m18PPx8VFsbKwOHTqkuLg4TZo0SV26dNHJkyc1ZMgQvfXWW/muEwCg8CJgAQAoMrp3766AgAAlJCTIZrPlqs9je/dG27dvz1NZ9n+o218EXu7ixYtWVwb/BsWKFbO+1k5NTZUkBQYGWv2br1mzJlf5VK9eXZKslyhX2r17t1JTU+Xu7p5t1whZye8xuFyJEiXUtWtXvfPOO9q+fbuCgoK0adMmK0BTEFWrVpWbm5suXLiQbR/U9hYg9n30bxUfH5/li8vryb6Pdu7cmW1Ayd6tjbPkZoyW7Bw4cEDSpS6sSpQokWm5s/v6vnz/ZGXPnj15DsSVL1/eaklztW7snCk/17b9BfCOHTvyFbh666239OSTT+qvv/5S27ZtrdYEl4uJicnyOrgWXaAVxPV8phXkGskN+3HN7fPmch4eHmrSpImGDRum9evX65577nHo4jAvsns22+dndQ/v0aOHgoOD9f333+vUqVNWoKegrSuycnl3RPbn9YkTJ5SSkqISJUpk2XJo+/btSk9PzzI/ZxxXb29vtW7dWsOHD9f27dvVvHlzJScnW+Or5EZOfzOdPHkyyxaR9nNm/fr1uf7KPr/bW9ie81mdJ9LVt99+HJo2bZpl2uyeZ7nZr/aPEbILCmZ1L75SzZo19cgjj2jevHnWs2ry5MlXXQ8AUPQQsAAAFBl+fn569tlndeutt+rRRx9VWFjYVde544475OXlpQULFjgM9ng19tYU9i/uLjd16tRs/8F2LWTX4sFuz549VprLBzvt1q2bpEutRHKjQ4cOki794/H8+fOZlr/zzjuSpObNm+epy5AWLVqoVKlS2rJlS47jFuRW2bJlVblyZUmXvo4vqICAAOslS1aDXJ47d04ff/yxpP/tI2SvVq1aqlChgpKTk/X1119nWr5v3z6tWrXKqWXar9f8dIFjX/f48eNZBnfGjBlTsMpd4bbbbpMkffXVV1m2pMhvwOGll16SdOn6XbBgQY5pjxw5Yn0RXRD2AbrfeeedXAfGqlSporp16yo1NdW6p+TVu+++qwEDBujIkSO69dZbraBTYeOKZ1p+u4m6Gvvz5rvvvtPevXsLlJd9HIz83N+zun5SU1P1ySefSPrf9Xc5Hx8f9enTR6mpqXrvvfc0f/58eXl5Wd0t5lZaWtpVv4b/7bffJF3qBsge+Lcfm6SkpCyPT073IGcfV3d3d2tg+bzs/5z+Zho/fnyWAZfmzZurVKlSOnz4cK6DI/nd3n/Tcz4lJeWqg6fbz5Pg4GCH7gOvtv05HYeTJ09a10F26+W0X+1BlPXr12dadujQIYcB7XOjINc5AKDwI2ABAChSYmNjtWTJEn344Ye5Sl++fHkNHjxYFy9eVIcOHTK9MDfGaN26dXr88ccdvrqzf6380ksvOQQnFi1apCFDhsjHx6fgG5NLkZGRevzxx7V27dpMXyGuXLlS3bt3lzFGkZGRioqKspYNGTJEQUFBWrx4sR566CGHFykZGRlasGCBQz/hffr0UaVKlfTXX38pJibGoUufmTNnatKkSZKk559/Pk/19/Hx0YgRIyRdGmNhzpw5mV5ubt++XcOGDXPovuiee+7RDz/84PB1oSR9/fXX2rZtm2w2m8P2FsSwYcMkXXrZZe+7XLrUdVHfvn114sQJhYeH65577nFKeUWZm5ubBg8eLEkaNGiQwxfXhw4d0t133+30r70vf5FytRdBV6pTp46KFy+uQ4cO6fXXX7fOzfPnz+vpp5/Wpk2bnFrXW2+9VVFRUTp79qweeOABh+vyyy+/1IcffpivgUg7dOigZ555RhkZGerevbteffVVa8BruxMnTmj8+PGKiIjI8qVTXj366KO66aabtGzZMt133306evSow/Lk5GR9+eWXeuaZZxzmv/baa5Iu3c/feecdhxYlZ8+e1ccff5xjKzabzaaPPvpIffv2VUJCgtq2batDhw4VeHtc4Xo900qXLq1ixYrp+PHj16SFYMOGDdW9e3edP39eHTt2zHR+7dmzR+PGjbOm3377bU2YMCHTi9WEhATrxXGDBg3yXI8ffvhBEydOtK7jc+fOWcGt0NDQbO/h9m6hRo4cqdTUVN15551ZtrjKSXJyssLDwzV06FBt27bN4TlnjNH8+fPVr18/SVLnzp2tsWqCg4NVp04dpaWl6T//+Y/1zEtPT9fo0aP1xRdfWN1DXcl+71uxYkWe6vriiy/qk08+ydQd0/bt263uqfKy/+1/Mz377LPW3w7GGE2fPl3jxo3L8m8mHx8fvfzyy5Iu3Us+//xzh312+vRpvf322w5/gxXkXv9vec7v3r1bN910k0aOHJkpuJeWlqYZM2ZY98y+ffs6jJtj3/7ffvsty3GVWrRoIenSs2TJkiXW/KNHj+quu+7Kdiym3NwfOnbsKOlSUPLyoPjRo0d13333ZZn30qVLNWTIkEwtd5OTkzV27FhJ+bvOAQBFgAEAoBAKCwszksyqVatylf7gwYNGksnq0Xfx4kVz//33W8tDQkJM48aNTWRkpClWrJg1Py4uzlrnwIEDpkSJEkaS8fX1NfXr1zfh4eFGkmnTpo257777jCQzdepUh7L69euX5Xy74cOHG0lm+PDhud0VJjg42KpjsWLFTL169UyDBg1M6dKlrfkVK1Z0qL/d4sWLrW309PQ0kZGRJiIiwvj7+2dZjzVr1pigoCAjyfj7+5vo6GgTGhpqlfPSSy/le5uef/55K58SJUqYRo0amQYNGlj7WZJZuHChld5eD29vb1O3bl3TqFEjU65cOSvtyy+/nOt9aIzJ9vzIqn6hoaEmOjra2k/Fixc369aty7SO/Tzdv39/nupiN3XqVCPJhIWF5bm++S27VatWeT4Hs6uLPa9ly5Y5zL948aK57bbbrPVq1qxpoqKijIeHhwkPDzdPPfWUkWRGjBjhsN7VziX7/urXr5/D/PT0dFOtWjUjyZQsWdI0bdrUtGrVyjz99NO52r733nvP4f4QHR1tAgMDjc1mM5MnT852+/N7jLZv3+5wf4mOjrbSPvHEEwU6r0aMGGE8PT2NJOPm5maqV69uGjdubKpWrWrc3NyMJOPn52dmzZplrbNs2TIjybRq1SrLPPfv35/teRoXF2cqV65slVerVi3TpEkTU716dePu7m4kmSZNmmRab9SoUcZmsxlJJigoyERHR5tq1apZdb/8nMruuKelpZl77rnHSDLVqlUzR48ezfV+ym6bc9pWu6sd96y4+plmjDH9+/c3koyPj4+Jjo42rVq1ctj+3NzLc9o/p06dMk2bNrXKDw8PN9HR0aZs2bKZ1nn66acd0jVu3NjUrFnTOmfq1q1rzpw5k6t9Zcz/jsno0aOtfdKoUSMTGBhobfOKFStyzKNevXpWPvPnz8912XZnzpyx1rc/N6KiokxkZKQpXry4Nb9u3bqZztV58+ZZ10OJEiVMdHS0KVWqlPWsy+6esHLlSivf6tWrm5YtW5pWrVo5PEuzOo+6du1qXbNVq1a17hH2tG3atDEXL150WCen+9KGDRuMt7e3kWQCAwNNw4YNTfny5Y0k88ADD2T7rMjIyDCPP/64VW6pUqVMo0aNTHh4uHUuXF5ebu71Of0ddi2e89ltW3Y2b97scJ6UKVPGNGzY0NStW9fh+m3durX5559/HNZNTEy0zqVy5cqZ5s2bm1atWplRo0ZZaXr27GnlUbVqVVO/fn3j4eFhihUrZiZMmJDtvf5q9wdjjHnooYesvCtXrmzlXbNmTeuavvz+MWfOHCt96dKlTXR0tImMjDR+fn7WvX/jxo252m8AgKKFFhYAgBueh4eHZsyYoR9++MHqtmLTpk06evSoqlevroEDB2r58uUO/RZXqlRJq1evVo8ePeTl5aWdO3fKx8dHr776qhYtWpSvL6Dza9u2bZo0aZJ69OihSpUqKSEhQVu3blV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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", "filtered_metrics_1to5 = [\n", @@ -1109,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "f67e69b0-997c-4609-a93c-691d57f081ef", "metadata": {}, "outputs": [], @@ -1121,7 +238,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "1d7ab163-baac-48b8-b23f-96ff64a868de", "metadata": {}, "outputs": [], @@ -1134,123 +251,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1 Mean: 2.708\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 25.3827\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1 Mean: 2.393\n", - "df_2 Mean: 2.287\n", - "T-Statistic: 6.5336\n", - "P-Value: 0.0000000001\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1 Mean: 2.699\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 23.6742\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1 Mean: 2.993\n", - "df_2 Mean: 3.046\n", - "T-Statistic: -4.3473\n", - "P-Value: 0.0000138232\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1 Mean: 3.035\n", - "df_2 Mean: 3.011\n", - "T-Statistic: 1.5449\n", - "P-Value: 0.1223834903\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1 Mean: 2.710\n", - "df_2 Mean: 2.425\n", - "T-Statistic: 21.8571\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1 Mean: 2.994\n", - "df_2 Mean: 2.986\n", - "T-Statistic: 0.5733\n", - "P-Value: 0.5664729684\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1 Mean: 3.048\n", - "df_2 Mean: 3.031\n", - "T-Statistic: 1.1520\n", - "P-Value: 0.2493166368\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1 Mean: 3.228\n", - "df_2 Mean: 3.078\n", - "T-Statistic: 10.5906\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1 Mean: 3.218\n", - "df_2 Mean: 3.166\n", - "T-Statistic: 3.5105\n", - "P-Value: 0.0004478861\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1 Mean: 3.694\n", - "df_2 Mean: 3.565\n", - "T-Statistic: 10.7853\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1 Mean: 3.218\n", - "df_2 Mean: 3.059\n", - "T-Statistic: 11.1506\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1 Mean: 3.697\n", - "df_2 Mean: 3.570\n", - "T-Statistic: 10.5199\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1 Mean: 3.054\n", - "df_2 Mean: 3.045\n", - "T-Statistic: 0.6356\n", - "P-Value: 0.5250658229\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1 Mean: 15.142\n", - "df_2 Mean: 15.856\n", - "T-Statistic: -1.6897\n", - "P-Value: 0.0910916769\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1 Mean: 15.567\n", - "df_2 Mean: 16.484\n", - "T-Statistic: -2.1228\n", - "P-Value: 0.0337816494\n", - "--------------------------------------\n" - ] - }, - { - "data": { - "image/png": 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cL1DYt2+f56QyvRP3c9WqVcsk2b///e80806dOuW5kFqwYIFn+vz5823VqlVpQsFly5ZZmTJlLCAgwLZv3+41z4nwtUePHibJrr32Wq8LmCNHjtgtt9ySJqxJSkqyokWLWmBgYJqLp6SkJJs7d64tXbo03XqcK6Ngwn3BERAQYPfee6+dOHHCM+/kyZOWkpJi0dHRnnXs37/fM//rr7+2ggULmiSbOHGi13rdJ99BQUFWp04d++uvvzzzZsyY4bmob9++vbVp08br5P2FF17wXCylvnDLKqfD10mTJpkkq1y5ste85ORkGz16tEmy8uXL26lTpzzzbrjhBpNkQ4cO9YQ6bqtXr04TLvkKAlNzh1j16tWz3bt3e807ePCgjR8/3uszzUh6F5hmZidOnLAKFSp4Lqri4+M986ZOneq52Jw/f75XOXcIGhAQYE2aNPGqZ+q2SU92txsUFGQtW7a0PXv2eOZ9+eWXnnJbtmzxKpdem995550mycaNG+eznu5A76uvvsrwPbllZR91X+Tfd999XtN9hQbu8CMyMtI2b97stXxcXJy99957FhMT47Mu5wZY7pCnbNmyXmHqtm3brGbNmp7PJbVhw4aZJHv44Yd9vpcuXbr47NNnzZplv/zyi9e0lJQU+/zzz61QoUIWFhbm9fmbXVj4OmbMGJPO/nHIlxEjRqQJ593hevv27e3w4cNey+/atStTfxRLLbPhq5lZw4YNTZKNGTPGa7qvz+xC+oRp06alCdiSkpLs/ffft8DAQKtSpYqdOXPGa35GfZOZ7/7k4MGDli9fPgsPD7cffvjBa/lTp07ZjBkzbOPGjV7T3cfy8OHDfW4nvX33Qvro48ePe/6w07t3b09bnTlzxl577TVPEJ7V8NUdBDZo0MDr2Pv222+tcOHCnvVmJny9kDZML1x0/7G3cOHCtmjRIs909x9wJdnVV1/tVea9994zSXbjjTf6fK8PPfSQSbLHH3/ca3pOnpdlZNCgQSbJSpQoYV9//bXXvD179qTZly4kfM3JfjZ13dzntI888ojnPOHMmTOec6OgoKA0n6+7fkFBQdajRw9PP3nmzBkbOHCgp0+oVKmSDR482LPe06dPe/rjc/txs6yfw5r9r28ICAiw6tWre7WN+1jL6rkQAJgRvgJAGukFCgcOHLDrrrvOpLMjis69iE7Piy++aJLsmmuuSTNv5syZPkdYnM/7779vkuyFF17wmp7T4evGjRs95Xy91xMnTlhkZKS5XC7buXOnmZ294JFk9evXz9R7yUhmw9d69eqlubg2M1u8eLFJspCQEM9o2dTco4AqVqzodUHlPvl2uVxeIzrc3CNn8ufP7xWKmZ29MC5XrpxJ8lk2s5wMXxMSEqx06dIWEBCQbh3dYdmHH37omVajRg2TZHFxcZnadkYBhztEmjBhQqbfz/mcL3x1X3BHRET4DE3dF3gtWrTwmu4OTkJCQtJ81pmR3e3mz58/TQhlZp4Lx3PD1PTa/Ntvv/UcK+dat25dlvshs6zto+4woWvXrl7TfYUG7j9wPProo1muS+pQIC4uzgoUKGBS2pF0ZmY///yz5zhPHZr8+eef5nK5rESJEpaYmOhV5uDBgxYYGGjBwcFpQszzeeaZZ0xSmovyCwlfd+7caS6XywoWLOjzjxPuUPnbb7/1TLvvvvtMkn3xxReZ3s75ZCV8vfnmm31+nr4+s5zuE/71r3+ZpDQjRC80fF25cqXP/fh8LiR8vdA+2n1+UK5cuTT7rpnZjTfemOXwddu2bZ7Rlr5GF44bNy7d/SGn2tBXP5GSkuIZVezrjwd///23Z4Rj6mMhPj7eChYsaEFBQXbw4EGvMomJiZ7Rlr7ea3qyel52Pnv27PGE2cuWLctUmQsJX3Oqn03N/Yerq666yuf8zp07myTr1auXz/qVKVMmTZ/2zz//eH45Vb9+/TTh99atW006O8o7tQs5hzX7X98gpf/rh6yeCwGAmRn3fAWAdLz44otq3ry5mjdvrqioKEVGRnqe2Pzee++pcOHCmVrPnXfeKZfLpVWrVqW5R5v7XrA9e/ZUQECA17xDhw5pwoQJ6tmzp6677jpPXcaPHy9J2rhxY/bf5HnMmTNHktS9e3ef77VAgQK67rrrZGZavny5JKlkyZIKCQnRH3/84Xj9UvvXv/7l8+n2ixYtkiTddtttKl26dJr5AwYMUEhIiHbt2qXff/89zfz69eurfv36aaZfddVVkqROnTqpbNmyXvMCAgI894v866+/svxeLoaVK1dq//79atCggc/3J0k33nijpLP323WLjIyUJH3yySc5Ug/3+ubNm5fmfpA5zb0v9O/fX6GhoWnmP/LII5KkH3/8USdOnEgz/7rrrkvzWV+M7Xbs2FHly5dPM71Ro0aSMr+PtWnTRpUrV9bGjRvTHJvTpk2TdPY4OrcfyikFCxaUJB07dizDZd37xbfffput+8/+8MMPOnnypCpUqKCbbropzfxGjRqpSZMmMjOvewpWqVJFLVu2VGxsrObPn+9VZvr06UpOTtaNN96oYsWKpVlnTEyMxo4dq+7du6tt27aefnvmzJmScqbfrlixopo2baoTJ06keZjj+vXrtXXrVpUpU8br/oTuNp0zZ06m7xWcUy7ks89qn7B161YNHz5ct9xyi1q3bu1pd3f/lVPfR+76/fTTT4qJicmRdfpyoX30woULJUn9+vVTUFBQmjIDBw7Mcl0WLVokM1PLli115ZVXppl/zz33KDg4ONPry6k23LJli3bv3q3Q0FD1798/zfxy5cqpW7dukv7XD0tS4cKFdeuttyopKUn//e9/vcrMmzdPsbGxio6O9vleL8Z52fz585WUlKRrrrlGLVq0yPb60pNT/Wxq7nZ+8MEHfc53f9+l/jxSu+OOO1SgQAGvaeHh4apcubKk/93PPTX3vfzj4+N1+PBhz/QLOYdN7corr1SDBg181jOnz4UAXB4C/V0BAMittm3b5nmolvthEC1bttRjjz3mCd8yo0KFCmrVqpWWLFmi6dOn67nnnpN09uEn7pvy9+rVy6vMokWL1L17d8XFxaW73px8KI4vv/76q6SzJ7DpPSzG/fCFPXv2SDobPD788MN65ZVX1KBBAzVr1kxt2rRRixYt1Lx5c5/hU06oVauWz+l//PGHJKl27do+5xcuXFiRkZHavn27/vjjD9WsWdNr/hVXXOGzXMmSJTM1//jx4xlX3g/cn+3OnTvVvHlzn8u4H7Th/mwladCgQfrmm2/Uv39/vfbaa+rQoYOaN2+uNm3aqHjx4lmux80336xKlSpp0aJFKlu2rDp27KgWLVqodevWPi98syOjfaFatWoKDg5WYmKi/vzzzzQPXEpvH3N6u+ntY6VKlZKU+X3M/QCR4cOHa9q0aRo3bpyksw8jcQcQWXmAWFa56xkWFpbhsk2aNNHVV1+tn376SZGRkWrXrp1atmypVq1aqUGDBuk+HPBc7ravWbNmumWuvPJKrVy50rOs2913362lS5dq2rRpXsGtO6j21VbTpk3TgAEDdPr06XTrlFP9ds+ePbVixQrNmDHD82BHSZoxY4Yk6fbbb/f6g1Tfvn31yiuvaOrUqfr66689x1qbNm1UpUqVHKlTerLy2V9InzBmzBg988wzSklJSXe9OdXu5cqV02233aZZs2apatWqatOmjVq3bq0WLVrommuuUWBgzlxaXWgf7d6P0+uvLqQfy2idhQsXVrly5bRjx45MrS+n2tBdrwoVKngC/nO59xlfx/e0adM0bdo0TyAonf/4vljnZe6Hkl5zzTXZXtf55FQ/m1pG33fuz+PAgQOKj49P0yec75xqy5Yt550fExOj48ePe85FLuQcNrXzHSs5fS4E4PLAyFcASMeUKVNkZ2/PooSEBO3atUv/+c9/vILX/fv3e0Y+pP730EMPea3LHa5Onz7dM23mzJlKSkpSVFSU1zr/+ecf9ejRQ3Fxcerdu7dWrVqlo0eP6syZM14jtDLzFPjscF9gbN++XStWrPD5z/1E4lOnTnnKjR07VuPHj9cVV1yh5cuXa+TIkWrXrp0iIiL09NNPKyEhIcfrmt6Fl/ui3x1U+RIRESHJ96isc0dguLkvSjKab2bpbjc7HnroIZ/73f79+zNV3v3ZHjp0KN3P1v2U8NSf7fXXX6958+apadOm+uOPPzRhwgTPqOLu3bv7vIA5n4IFC2r58uXq27evUlJSNHPmTD344IOKiorSlVdeqa+++ipL6zufjPYFl8vlCc197Qvp7WP+2q47WMvKPta3b1/ly5fPM3pTOjvK6tChQ+mO9Mop7hFu5zsW3fLly6evv/5ajzzyiPLnz68vvvhCjz32mKKjo1W5cuU0T+xOT3aO/1tvvVVhYWH66quvPKOpfvnlF23YsEGlS5dWx44dvZb/888/1b9/f50+fVqPPfaY1q9fr/j4eKWkpMjM9N5770nKuX67e/fuCgwM1IIFC3T06FFJZ/cF9wjbnj17ei1ftmxZrVy5Ut26dVNcXJymTZume+65R1dccYWaNGmilStX5ki9fMnKZ5/VPmHZsmUaOnSoXC6XxowZo99++03Hjx/3tPuwYcMk5ez35Ycffqjhw4erVKlSWrRokYYOHaoWLVqobNmyevXVV88bAmfWhfbR7n3e3aecy72/Z0VG67yQ9eZEG2bn+G7ZsqWqVaum9evXe0K62NhYzZs3T8HBwbrjjju8lr+Y52Xx8fGSpCJFimR7XeeTU/1sahl9Jqn3E6fPuS70HNbtfN/5OX0uBODyQPgKANlw+vRpnyd07pN5t1tvvVX58+fXH3/8oZ9//lnS/245cO6o16+//lpHjx5VkyZNNHXqVF199dUqUqSIJ2zZvXt3luqYURDo66fOklSoUCFJ0nvvvecJodP7N2LECE+5fPny6ZFHHtEff/yhHTt2aNq0aerRo4dOnz6tsWPH6rHHHstS/bPD/R4OHjyY7jIHDhyQpEzfRiI3+PXXX33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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "metric_columns = [\n", " 'Inflight wifi service',\n", @@ -1363,123 +367,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "22aa3477-4a71-4966-8278-0fb39583ffae", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1 Mean: 2.400\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 0.6064\n", - "P-Value: 0.5442639813\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1 Mean: 3.129\n", - "df_2 Mean: 2.287\n", - "T-Statistic: 64.7514\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1 Mean: 2.547\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 15.5027\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1 Mean: 2.976\n", - "df_2 Mean: 3.046\n", - "T-Statistic: -6.8515\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1 Mean: 2.958\n", - "df_2 Mean: 3.011\n", - "T-Statistic: -4.1709\n", - "P-Value: 0.0000304613\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1 Mean: 2.656\n", - "df_2 Mean: 2.425\n", - "T-Statistic: 23.2966\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1 Mean: 3.036\n", - "df_2 Mean: 2.986\n", - "T-Statistic: 3.9404\n", - "P-Value: 0.0000816032\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1 Mean: 2.894\n", - "df_2 Mean: 3.031\n", - "T-Statistic: -10.6884\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1 Mean: 3.019\n", - "df_2 Mean: 3.078\n", - "T-Statistic: -4.9255\n", - "P-Value: 0.0000008475\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1 Mean: 2.991\n", - "df_2 Mean: 3.166\n", - "T-Statistic: -14.1632\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1 Mean: 3.376\n", - "df_2 Mean: 3.565\n", - "T-Statistic: -18.5273\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1 Mean: 3.043\n", - "df_2 Mean: 3.059\n", - "T-Statistic: -1.3296\n", - "P-Value: 0.1836795869\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1 Mean: 3.389\n", - "df_2 Mean: 3.570\n", - "T-Statistic: -17.6556\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1 Mean: 2.936\n", - "df_2 Mean: 3.045\n", - "T-Statistic: -8.4732\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1 Mean: 16.504\n", - "df_2 Mean: 15.856\n", - "T-Statistic: 1.7952\n", - "P-Value: 0.0726400300\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1 Mean: 17.128\n", - "df_2 Mean: 16.484\n", - "T-Statistic: 1.7473\n", - "P-Value: 0.0805987692\n", - "--------------------------------------\n" - ] - }, - { - "data": { - "image/png": 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aa+3kyZMZ5pfd/dvtpZde8nyuyMhIa9SokV144YUWGhqa4fs70/oxy/x78LfvdG/Lvo7rzZs3t/fff98zz/x2npfdc6v05+l9+vQxSRYbG+vZrsxOHccvvPBCz2esU6eONWzY0MqUKWMul8uioqKy/oIBFFiErwDOSWcKFBISEiw8PNwk+bzg9aV27domyd5+++0M7yUnJ3tOyL755htP+Zw5c2zZsmUZThYXL15s5cqVs+DgYNuyZYvXe06Er126dDFJ1qZNG/vzzz895fv377cbb7wxQ1hz4sQJK1GihIWEhGS4WD1x4oTNmjXLFi1alGk7TrdgwQKTZC1btvT5vvtiPDg42O699147cuSI572jR49aWlqa54K3ZcuWtnPnTs/7c+fO9Vx0jRkzxmu+7pPy0NBQq1evnv3111+e9z755BOTZIUKFbJ27dpZ69atvQKtF154wSRZuXLlLDU11e/Pejqnw9dx48aZJKtSpYrXe6mpqTZ8+HCTZBdccIElJyd73rvuuutMkj399NOWkpLiNb8VK1ZkCLgyu/hymz59ukmySy65xHbs2OH13u7du+2NN97w+k6zcqZA4ciRI57w6dZbb7WkpCTPe5MmTfKEQXPmzPGq577ADA4OtqZNm3q1M/26yUxOlxsaGmpXXHGF/fPPP573Zs6c6am3ceNGr3qZrfM77rjDJNmoUaN8trNevXomKUNocCbZ2UbdIdx9993nVe4rdFy5cqXn4nPDhg1e0ycmJtr48eMtPj7eq3zatGn23//+16ssLS3NZsyYYUWLFrXIyEivdW+Wdf9i5jtgOJt+Lqt9IbPwde7cueZyuSw6OjrDMWfChAkWEhJixYoVs3///dfrczds2NAkWfv27W3fvn2e9z755BMLDQ21kJCQbIUzP//8s0myChUq+Ax7Fi5caJKsWrVqnrKz+R7PJDvhqztMbd++vVe5rz5i9+7dFhQUZFFRUfbjjz96TZ+cnGyffPKJrVu3zqs8N4/R6WW2nbjD1DFjxngdV9LS0mzBggU2c+ZMr+mz2rYz6yvXrVtn4eHhFhERYe+9957Xdz1z5kyLjIy04OBgW7t2rVe9zp07myRr2LCh13f6/fffW7FixXyGd1l58803TZKVKFHClixZ4infunWr1a1b1zNPf8PX7K7DzMLFNWvWePafl19+2bOOjh07Zn379jXp1I+T6ffJzZs3mySLjo6248ePZ/isn3/+uUmyuLg4r/J169bZ119/bceOHfMq//PPPz2B9qRJkzLM72zC1xkzZniOda+99ppXO48cOWLvvfee1358NuHr2fSdZzqum1m+O887m3Mrd98QHBxsRYoUsa+++srz3tGjR83sfz+QtmvXzqtPNzPbvn27XwMbABRchK8AzkmZBQq7du2yq666ynMxcPqFfGZefPFFk2SXXXZZhvemTp3q+fXf36BuwoQJJsleeOEFr/LcDl/XrVvnqefrsx45csRiY2PN5XLZtm3bzOxUOC3JGjRo4NdnyYq/4esll1ziMxCYP3++SadGGrlH/KT38ssvez5j+oto90m5y+Wy1atXZ6jXtGlTz4l5+lDM7NQJtnsEmK+6/nIyfE1JSbGyZctacHBwpm10h2Uffvihp6xmzZomyRITE/1adlaB04gRI0ySvfnmm35/njM500Xa+PHjTZLFxMT4DE3dF80tWrTwKndfYIaHh2f4rv2R0+UWKlQoQzBtZp4fP04PUzNb599//71nXznd6tWrs90PmWVvG3344YdNknXu3Nmr3Ffo6L7wfeSRR/xuy5k8++yzJinDjwNnG76eTT93tuGrO0RNfzGenjtkHDp0qKfsu+++82w7vv7i4qGHHvL0C9kJZ9wjyRYuXJjhvfvuu88k71Hcuf09Zid8feONN3x+R776CHewfPq2ebaye4xOL7PtJDw83EqUKOF3G842fHX3K5n1ye5Ri+lH/W/evNkzWjL9qE23UaNG+TwOnUlaWprnR6t33nknw/urVq3yzNPf8DW76zCzcNH9Q1b6v/RI3273X0ed/hcNLVq0MCnjKGozs+uvv94k3z/SZ2bLli0mydq2bZvhvbMJX+vUqZOhLzmTswlfz6bvzCp8zU/neWd7buXuGyTZa6+95rOeu4/N7FgA4NzGPV8BnNNefPFFXX755br88ss9Twz+7rvvFBoaqvHjx6tYsWJ+zeeOO+6Qy+XSsmXLMtzryX0v2K5duyo4ONjrvT179ujNN99U165dddVVV3na8sYbb0iS1q1bl/MPeQZffvmlJOnWW2/1+VkLFy6sq666SmamJUuWSJJKly6t8PBw/fHHH463L70777zT59Pt582bJ0m65ZZbVLZs2Qzv9+nTR+Hh4dq+fbt+//33DO83aNBADRo0yFBev359SVKHDh1Uvnx5r/eCg4N18cUXSzp1X8D86Oeff9bOnTvVsGFDn59Pkq6//npJp+4Z6OZ+avZnn32WK+1wz2/27Nk6evRorswzM+5toXfv3oqIiMjwfv/+/SWduo/fkSNHMrx/1VVXZfiu82K5V199tS644IIM5Y0bN5bk/zbWunVrValSRevWrcuwb7rvqXfnnXdm6IdyS5EiRSRJhw4dynJa93bx/fffZ+v+s/Hx8Ro5cqRuvfVWXXnllZ4+c+rUqZJyr8/Mq35u+/btWr16tcqUKePZH0/naz/99ttvJZ3q96KjozPU6du371m15/bbb5ckzwMi3VJTUzV9+nRJp45lbmf7PeaGs9nefvnlF8XHx/u9jLw8RsfGxurgwYNZPugzJ44fP645c+YoODg40/tZ+9re5s2bJzPTFVdcoYsuuihDnV69eiksLCxbbdm4caPi4+MVERHhsy0NGzbUZZddlq155tY6dPfpDz74YIb3XC6XHnroIa/p3O655x5J/+tv3fbs2aO5c+cqLCzMs4+ll5KSoo8//li9e/dW+/bt1aJFC11++eXq0aOHpNzZzrZs2aINGzYoLCzM0QcjOtF35qfzvLM9t0ovswcFuvupL7/80pF7/QLI30IC3QAAcNLmzZs9D9VyP3zjiiuu0MCBAz0nZf6oWLGiWrZsqYULF2rKlCl6/vnnJZ26cb77AUXdunXzqjNv3jzdeuutXg83OJ3TF7O//vqrpFMner4eWCOdCgck6Z9//pF06oT0oYce0iuvvKKGDRuqefPmat26tediwVf4lBtq167ts/yPP/6QJNWpU8fn+8WKFVNsbKy2bNmiP/74Q7Vq1fJ6/8ILL/RZr3Tp0n69f/jw4awbHwDu73bbtm26/PLLfU7jfhCO+7uVpIcffljfffedevfurddee03t27fX5ZdfrtatW6tUqVLZbscNN9ygypUra968eSpfvryuvvpqtWjRQq1atfJ5EZ8TWW0L1atXV1hYmI4fP64///zTc2Hlltk25vRyM9vGypQpI8n/bcz9YJFBgwZp8uTJGjVqlKRTwdnHH38sSdl6gFh2udsZGRmZ5bRNmzbVpZdeql9++UWxsbFq27atrrjiCrVs2VINGzb0+XDAyZMnq0+fPjp27Fim882tPjOv+jn3fnrs2LFM91P3502/n7q3ucy22erVqyskJCTbF/Bdu3bVCy+8oOnTp+utt95SaGiopFPHq3379ql+/fpefejZfI+5JTvbW4UKFXTLLbdo2rRpqlatmlq3bq1WrVqpRYsWuuyyyxQSkvGSJ6+P0Y888ogeeOABtWvXTo0aNfKEvS1btvT7h+Cs/PHHHzp27JjCwsJ0zTXX+JzG/v/BRdnZ3ooVK6YKFSpo69at2WqLdOqBfYULF/Y5Te3atbP1kKzcWIcHDx7Unj17JGXep7uPXe7P4HbLLbfooYce0uzZs7V3717PDyMff/yxTpw4oZtvvlklS5b0qhMfH6927dr5DA3dcmM7cz/kqk6dOrm2PfniRN+Zn87zzvbcyi06OtrnD2bSqQeOvfLKK5o0aZLmzp3rOV9q3bq1qlat6rMOgHMH4SuAc9rEiROzDCN27typm2++OUN5gwYNvJ6U2q1btwzh69SpU3XixAnVrVvXK8w9ePCgunTposTERHXv3l19+/ZVzZo1FRkZqaCgIH333Xdq27Ztjp4g7A/3ReWWLVu0ZcuWM06bnJzs+f+RI0eqQoUKeuedd7RkyRLPqNjIyEj17dtXgwcPVnh4eK621T3K6XTuk2J3UOVLTEyMtmzZ4nOEVGYXfe7QIKv33Reque3BBx/0+ZTz6dOn+xz5cTr3d7tnzx7PhWRm0n+31157rWbPnq0XXnhBy5Yt06ZNm/Tmm28qJCREnTt31uuvv64KFSr4/TmKFCmiJUuW6Pnnn9f06dM1depUzyjFOnXq6KWXXtJ1113n9/zOJKttweVyqXTp0vrnn398bguZbWOBWq57pHd2trG7775bQ4YM0ZQpU/Tyyy8rJCREc+bM0Z49exQXF5frgXd67hGFZ9oX3YKCgjR37lwNGTJEH330kb766it99dVXkk6FMYMHD/bqm//880/17t1bJ06c0MCBA3XnnXfqwgsvVNGiReVyuTRhwgTP+7klL/o5936alJSkn3766YzTpt9P3ducOxw4XVBQkKKjo7Vz585stadOnTq65JJLtG7dOs2fP98T0LlHwqYf9epeTna+x9yUne1Nkj788EPVqVNHEyZM0Lx58zyj6UqXLq3HH39cAwYM8OxzgThG9+3bV8WKFdNrr72mVatWadWqVXrppZcUERGhbt266ZVXXlFUVFSOluHe3o4fP57l9pb+R46stjfp1HE2O+Grv/PMjtxYh+mDtsy2LXe7Tu/PixQpoltvvVXvv/++PvnkE8/IWfdIWF/7wl133aXff/9dl156qYYMGaL69eurZMmSCg0NVWpqque/OZWUlCRJKl68eI7nlZXc7jvz03ne2Z5buZ3pPKN8+fL6+eef9dxzz2n27NmaPHmyZ9u57LLLNGrUKDVt2vSMywRQcHHbAQDnvWPHjumnn37K8M/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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# --- 1. Initialize Lists for Storing Results ---\n", "metric_names = []\n", @@ -1573,21 +464,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "customer_type_counts = df['Customer Type'].value_counts()\n", "\n", @@ -1607,21 +487,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", "\n", @@ -1641,23 +510,12 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", "metadata": { "scrolled": true }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", "\n", @@ -1693,38 +551,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "962aad69-b985-4ff3-ab06-a854e251135b", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:23: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " dfDisatisfied['Flight Distance_group'] = np.select(\n", - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:46: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", "\n", @@ -1805,32 +635,10 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "8d11c378-2b5c-47b1-97e0-c611056739ec", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\2556283244.py:21: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", "# Get the count of each Gender from the dfDisatisfied DataFrame\n", @@ -1885,32 +693,10 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "27ee32c2-d244-4497-aafc-0232278b4ed0", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\783172777.py:23: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", "# Get the count of each age group from the dfDisatisfied DataFrame\n", From d7c1f3c843c69999b8f59ec5ea0ba53bc7f5a137 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ant=C3=B3nio=20Bianchi=20Galv=C3=A3o?= Date: Wed, 10 Dec 2025 18:26:36 +0100 Subject: [PATCH 17/26] Delete notebooks/Airline_Project1_Antonio_3.ipynb --- notebooks/Airline_Project1_Antonio_3.ipynb | 1991 -------------------- 1 file changed, 1991 deletions(-) delete mode 100644 notebooks/Airline_Project1_Antonio_3.ipynb diff --git a/notebooks/Airline_Project1_Antonio_3.ipynb b/notebooks/Airline_Project1_Antonio_3.ipynb deleted file mode 100644 index 0ac64307..00000000 --- a/notebooks/Airline_Project1_Antonio_3.ipynb +++ /dev/null @@ -1,1991 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "561808a4-27ef-4523-892a-8584a31efefa", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
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10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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103904 rows × 25 columns

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" - ], - "text/plain": [ - " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", - "0 0 70172 Male Loyal Customer 13 Personal Travel \n", - "1 1 5047 Male disloyal Customer 25 Business travel \n", - "2 2 110028 Female Loyal Customer 26 Business travel \n", - "3 3 24026 Female Loyal Customer 25 Business travel \n", - "4 4 119299 Male Loyal Customer 61 Business travel \n", - "... ... ... ... ... ... ... \n", - "103899 103899 94171 Female disloyal Customer 23 Business travel \n", - "103900 103900 73097 Male Loyal Customer 49 Business travel \n", - "103901 103901 68825 Male disloyal Customer 30 Business travel \n", - "103902 103902 54173 Female disloyal Customer 22 Business travel \n", - "103903 103903 62567 Male Loyal Customer 27 Business travel \n", - "\n", - " Class Flight Distance Inflight wifi service \\\n", - "0 Eco Plus 460 3 \n", - "1 Business 235 3 \n", - "2 Business 1142 2 \n", - "3 Business 562 2 \n", - "4 Business 214 3 \n", - "... ... ... ... \n", - "103899 Eco 192 2 \n", - "103900 Business 2347 4 \n", - "103901 Business 1995 1 \n", - "103902 Eco 1000 1 \n", - "103903 Business 1723 1 \n", - "\n", - " Departure/Arrival time convenient ... Inflight entertainment \\\n", - "0 4 ... 5 \n", - "1 2 ... 1 \n", - "2 2 ... 5 \n", - "3 5 ... 2 \n", - "4 3 ... 3 \n", - "... ... ... ... \n", - "103899 1 ... 2 \n", - "103900 4 ... 5 \n", - "103901 1 ... 4 \n", - "103902 1 ... 1 \n", - "103903 3 ... 1 \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "0 4 3 4 4 \n", - "1 1 5 3 1 \n", - "2 4 3 4 4 \n", - "3 2 5 3 1 \n", - "4 3 4 4 3 \n", - "... ... ... ... ... \n", - "103899 3 1 4 2 \n", - "103900 5 5 5 5 \n", - "103901 3 2 4 5 \n", - "103902 4 5 1 5 \n", - "103903 1 1 4 4 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "0 5 5 25 \n", - "1 4 1 1 \n", - "2 4 5 0 \n", - "3 4 2 11 \n", - "4 3 3 0 \n", - "... ... ... ... \n", - "103899 3 2 3 \n", - "103900 5 4 0 \n", - "103901 5 4 7 \n", - "103902 4 1 0 \n", - "103903 3 1 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction \n", - "0 18.0 neutral or dissatisfied \n", - "1 6.0 neutral or dissatisfied \n", - "2 0.0 satisfied \n", - "3 9.0 neutral or dissatisfied \n", - "4 0.0 satisfied \n", - "... ... ... \n", - "103899 0.0 neutral or dissatisfied \n", - "103900 0.0 satisfied \n", - "103901 14.0 neutral or dissatisfied \n", - "103902 0.0 neutral or dissatisfied \n", - "103903 0.0 neutral or dissatisfied \n", - "\n", - "[103904 rows x 25 columns]" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "from scipy import stats\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "import matplotlib.pyplot as plt\n", - "\n", - "df=pd.read_csv('train.csv')\n", - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a86604ec-da44-40c0-894e-0a118b9ca685", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Age Group creation successful.\n", - "Flight distance group Group creation successful.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" - ] - } - ], - "source": [ - "binary_change= {\n", - " 'satisfied': 1,\n", - " 'neutral or dissatisfied': 0,\n", - "}\n", - "\n", - "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", - "df.drop(columns=['Unnamed: 0'], inplace=True)\n", - "\n", - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Age'] < 18),\n", - " (df['Age'] >= 18) & (df['Age'] < 30),\n", - " (df['Age'] >= 30) & (df['Age'] < 40),\n", - " (df['Age'] >= 40) & (df['Age'] < 50),\n", - " (df['Age'] >= 50) & (df['Age'] < 60),\n", - " (df['Age'] >= 60) & (df['Age'] < 70),\n", - " (df['Age'] >= 70)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Minor',\n", - " '18 to 30',\n", - " '30 to 40',\n", - " '40 to 50',\n", - " '50 to 60',\n", - " '60 to 70',\n", - " '70 +'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Age Group creation successful.\")\n", - "\n", - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Flight Distance'] < 750),\n", - " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", - " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", - " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", - " (df['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Flight distance group Group creation successful.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "6f945079-4c90-40ee-83b9-53af53e43388", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", - "dfDisatisfied=df[df['satisfaction_binary'] == 0]" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\3011661649.py:47: FutureWarning: The previous implementation of stack is deprecated and will be removed in a future version of pandas. See the What's New notes for pandas 2.1.0 for details. Specify future_stack=True to adopt the new implementation and silence this warning.\n", - " vertical_stats_table = pivot_stats.stack(level=0)\n" - ] - }, - { - "data": { - "text/html": [ - "
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satisfactionneutral or dissatisfiedsatisfied
MetricStatistic
Agemean37.56668841.750583
median36.00000043.000000
std16.45982512.767833
Arrival Delay in Minutesmean17.12753612.630799
median0.0000000.000000
std40.56024835.962008
Baggage handlingmean3.3759913.966396
median4.0000004.000000
std1.1769781.099607
Checkin servicemean3.0429523.646041
median3.0000004.000000
std1.2811581.158732
Cleanlinessmean2.9361233.744342
median3.0000004.000000
std1.3259551.142247
Departure Delay in Minutesmean16.50372812.608084
median0.0000000.000000
std40.19188635.382595
Departure/Arrival time convenientmean3.1291122.970305
median3.0000003.000000
std1.5003681.552213
Ease of Online bookingmean2.5468503.031582
median3.0000003.000000
std1.2058471.575306
Flight Distancemean928.9199711530.140255
median671.0000001250.000000
std790.4523081128.126574
Food and drinkmean2.9580503.521310
median3.0000004.000000
std1.3466071.236187
Gate locationmean2.9761212.977879
median3.0000003.000000
std1.1985001.374244
Inflight entertainmentmean2.8941563.964931
median3.0000004.000000
std1.3236191.076907
Inflight servicemean3.3888143.969461
median4.0000004.000000
std1.1756031.091486
Inflight wifi servicemean2.3996333.161288
median2.0000004.000000
std0.9643481.588697
Leg room servicemean2.9908123.822143
median3.0000004.000000
std1.3031591.175515
On-board servicemean3.0191583.857324
median3.0000004.000000
std1.2857901.127130
Online boardingmean2.6561254.027474
median3.0000004.000000
std1.1459051.191609
Seat comfortmean3.0362953.966530
median3.0000004.000000
std1.3031421.142077
\n", - "
" - ], - "text/plain": [ - "satisfaction neutral or dissatisfied \\\n", - "Metric Statistic \n", - "Age mean 37.566688 \n", - " median 36.000000 \n", - " std 16.459825 \n", - "Arrival Delay in Minutes mean 17.127536 \n", - " median 0.000000 \n", - " std 40.560248 \n", - "Baggage handling mean 3.375991 \n", - " median 4.000000 \n", - " std 1.176978 \n", - "Checkin service mean 3.042952 \n", - " median 3.000000 \n", - " std 1.281158 \n", - "Cleanliness mean 2.936123 \n", - " median 3.000000 \n", - " std 1.325955 \n", - "Departure Delay in Minutes mean 16.503728 \n", - " median 0.000000 \n", - " std 40.191886 \n", - "Departure/Arrival time convenient mean 3.129112 \n", - " median 3.000000 \n", - " std 1.500368 \n", - "Ease of Online booking mean 2.546850 \n", - " median 3.000000 \n", - " std 1.205847 \n", - "Flight Distance mean 928.919971 \n", - " median 671.000000 \n", - " std 790.452308 \n", - "Food and drink mean 2.958050 \n", - " median 3.000000 \n", - " std 1.346607 \n", - "Gate location mean 2.976121 \n", - " median 3.000000 \n", - " std 1.198500 \n", - "Inflight entertainment mean 2.894156 \n", - " median 3.000000 \n", - " std 1.323619 \n", - "Inflight service mean 3.388814 \n", - " median 4.000000 \n", - " std 1.175603 \n", - "Inflight wifi service mean 2.399633 \n", - " median 2.000000 \n", - " std 0.964348 \n", - "Leg room service mean 2.990812 \n", - " median 3.000000 \n", - " std 1.303159 \n", - "On-board service mean 3.019158 \n", - " median 3.000000 \n", - " std 1.285790 \n", - "Online boarding mean 2.656125 \n", - " median 3.000000 \n", - " std 1.145905 \n", - "Seat comfort mean 3.036295 \n", - " median 3.000000 \n", - " std 1.303142 \n", - "\n", - "satisfaction satisfied \n", - "Metric Statistic \n", - "Age mean 41.750583 \n", - " median 43.000000 \n", - " std 12.767833 \n", - "Arrival Delay in Minutes mean 12.630799 \n", - " median 0.000000 \n", - " std 35.962008 \n", - "Baggage handling mean 3.966396 \n", - " median 4.000000 \n", - " std 1.099607 \n", - "Checkin service mean 3.646041 \n", - " median 4.000000 \n", - " std 1.158732 \n", - "Cleanliness mean 3.744342 \n", - " median 4.000000 \n", - " std 1.142247 \n", - "Departure Delay in Minutes mean 12.608084 \n", - " median 0.000000 \n", - " std 35.382595 \n", - "Departure/Arrival time convenient mean 2.970305 \n", - " median 3.000000 \n", - " std 1.552213 \n", - "Ease of Online booking mean 3.031582 \n", - " median 3.000000 \n", - " std 1.575306 \n", - "Flight Distance mean 1530.140255 \n", - " median 1250.000000 \n", - " std 1128.126574 \n", - "Food and drink mean 3.521310 \n", - " median 4.000000 \n", - " std 1.236187 \n", - "Gate location mean 2.977879 \n", - " median 3.000000 \n", - " std 1.374244 \n", - "Inflight entertainment mean 3.964931 \n", - " median 4.000000 \n", - " std 1.076907 \n", - "Inflight service mean 3.969461 \n", - " median 4.000000 \n", - " std 1.091486 \n", - "Inflight wifi service mean 3.161288 \n", - " median 4.000000 \n", - " std 1.588697 \n", - "Leg room service mean 3.822143 \n", - " median 4.000000 \n", - " std 1.175515 \n", - "On-board service mean 3.857324 \n", - " median 4.000000 \n", - " std 1.127130 \n", - "Online boarding mean 4.027474 \n", - " median 4.000000 \n", - " std 1.191609 \n", - "Seat comfort mean 3.966530 \n", - " median 4.000000 \n", - " std 1.142077 " - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "numeric_cols_df = df.select_dtypes(include=np.number)\n", - "\n", - "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", - "metrics_to_analyze = [\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " 'Age' # Including age as a numeric metric to analyze\n", - "]\n", - "\n", - "# Filter down to the columns that actually exist and are numeric\n", - "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", - "\n", - "# --- 2. Melt the DataFrame ---\n", - "df_melted = df.melt(\n", - " id_vars=['satisfaction'],\n", - " value_vars=analysis_cols,\n", - " var_name='Metric', # This column now holds the name of the original column\n", - " value_name='Value' # This column now holds the numeric data\n", - ")\n", - "\n", - "# --- 3. Create the Pivot Table ---\n", - "pivot_stats = pd.pivot_table(\n", - " df_melted,\n", - " index=['Metric'],\n", - " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", - " values='Value',\n", - " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", - ")\n", - "\n", - "# --- 4. Re-orient to Vertical View ---\n", - "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", - "vertical_stats_table = pivot_stats.stack(level=0)\n", - "\n", - "# Rename the new index level for clarity\n", - "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", - "\n", - "# Display the final vertical table\n", - "vertical_stats_table" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", - "filtered_metrics_1to5 = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - "]\n", - "\n", - "# --- 2. Filter the df_melted DataFrame ---\n", - "# Only keep rows where the 'Metric' is in the list above\n", - "df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", - "\n", - "\n", - "# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", - "correct_palette = {\n", - " 'satisfied': 'tab:blue',\n", - " 'neutral or dissatisfied': 'tab:orange'\n", - "}\n", - "\n", - "# --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", - "plt.figure(figsize=(16, 8))\n", - "\n", - "sns.barplot(\n", - " data=df_melted_filtered_1to5, # Using the filtered data\n", - " x='Metric',\n", - " y='Value',\n", - " hue='satisfaction',\n", - " errorbar='sd',\n", - " palette=correct_palette\n", - ")\n", - "\n", - "# --- 5. Format the Chart ---\n", - "plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", - "plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "f67e69b0-997c-4609-a93c-691d57f081ef", - "metadata": {}, - "outputs": [], - "source": [ - "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", - "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", - "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "1d7ab163-baac-48b8-b23f-96ff64a868de", - "metadata": {}, - "outputs": [], - "source": [ - "legend_colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] \n", - "\n", - "# Define the corresponding labels\n", - "legend_labels = ['Category A', 'Category B', 'Category C']" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1 Mean: 2.708\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 25.3827\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1 Mean: 2.393\n", - "df_2 Mean: 2.287\n", - "T-Statistic: 6.5336\n", - "P-Value: 0.0000000001\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1 Mean: 2.699\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 23.6742\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1 Mean: 2.993\n", - "df_2 Mean: 3.046\n", - "T-Statistic: -4.3473\n", - "P-Value: 0.0000138232\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1 Mean: 3.035\n", - "df_2 Mean: 3.011\n", - "T-Statistic: 1.5449\n", - "P-Value: 0.1223834903\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1 Mean: 2.710\n", - "df_2 Mean: 2.425\n", - "T-Statistic: 21.8571\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1 Mean: 2.994\n", - "df_2 Mean: 2.986\n", - "T-Statistic: 0.5733\n", - "P-Value: 0.5664729684\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1 Mean: 3.048\n", - "df_2 Mean: 3.031\n", - "T-Statistic: 1.1520\n", - "P-Value: 0.2493166368\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1 Mean: 3.228\n", - "df_2 Mean: 3.078\n", - "T-Statistic: 10.5906\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1 Mean: 3.218\n", - "df_2 Mean: 3.166\n", - "T-Statistic: 3.5105\n", - "P-Value: 0.0004478861\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1 Mean: 3.694\n", - "df_2 Mean: 3.565\n", - "T-Statistic: 10.7853\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1 Mean: 3.218\n", - "df_2 Mean: 3.059\n", - "T-Statistic: 11.1506\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1 Mean: 3.697\n", - "df_2 Mean: 3.570\n", - "T-Statistic: 10.5199\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1 Mean: 3.054\n", - "df_2 Mean: 3.045\n", - "T-Statistic: 0.6356\n", - "P-Value: 0.5250658229\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1 Mean: 15.142\n", - "df_2 Mean: 15.856\n", - "T-Statistic: -1.6897\n", - "P-Value: 0.0910916769\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1 Mean: 15.567\n", - "df_2 Mean: 16.484\n", - "T-Statistic: -2.1228\n", - "P-Value: 0.0337816494\n", - "--------------------------------------\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "# --- 1. Initialize Lists for Storing Results ---\n", - "metric_names = []\n", - "p_values = []\n", - "is_significant = []\n", - "alpha = 0.05 # Significance level\n", - "\n", - "# --- 2. Iterate, Test, and Collect Results ---\n", - "for col in metric_columns:\n", - " # Safely convert to numeric and drop NaNs for both comparison groups\n", - " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", - " df_1_data = pd.to_numeric(dfDisloyal[col], errors='coerce').dropna()\n", - " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", - " \n", - " # Skip if groups are too small or empty after cleaning\n", - " if df_1_data.size < 2 or df_2_data.size < 2:\n", - " print(f\"Skipping {col}: Insufficient data.\")\n", - " continue\n", - "\n", - " # Perform Welch's T-Test\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1_data,\n", - " b=df_2_data,\n", - " equal_var=False\n", - " )\n", - "\n", - " # Store results in the lists\n", - " metric_names.append(col)\n", - " p_values.append(p_value)\n", - " is_significant.append(p_value <= alpha)\n", - "\n", - " # --- Output the Results (Optional, as requested) ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", - " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)\n", - "\n", - "# --- 3. Create DataFrame for Plotting ---\n", - "p_values_df = pd.DataFrame({\n", - " 'Metric': metric_names,\n", - " 'P_Value': p_values,\n", - " 'Is_Significant': is_significant\n", - "})\n", - "\n", - "# # Sort the results by P-Value for a cleaner chart\n", - "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", - "\n", - "# --- 4. Plot the P-Values ---\n", - "\n", - "# Define colors for bars based on significance\n", - "# --- Define the mapping dictionary ---\n", - "# Create the dictionary that maps the unique hue values (True/False) to colors\n", - "palette_map = {\n", - " True: 'darkred', # For bars where Is_Significant is True\n", - " False: 'skyblue' # For bars where Is_Significant is False\n", - "}\n", - "\n", - "plt.figure(figsize=(14, 8))\n", - "ax = sns.barplot(\n", - " data=p_values_df,\n", - " x='Metric',\n", - " y='P_Value',\n", - " hue='Is_Significant',\n", - " palette=palette_map, # <-- FIX: Pass the dictionary here\n", - " dodge=False,\n", - ")\n", - "# Add horizontal line at p=0.05\n", - "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", - "\n", - "# --- Custom Legend ---\n", - "from matplotlib.patches import Patch\n", - "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", - "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", - "final_handles = custom_handles + [significance_line]\n", - "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", - "\n", - "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", - "ax.get_legend().remove() \n", - "\n", - "# --- Formatting ---\n", - "plt.title('P-Values from T-Tests for only Disloyal vs Disatisfied disloyal customers', fontsize=16)\n", - "plt.ylabel('P-Value', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 1.0)\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "22aa3477-4a71-4966-8278-0fb39583ffae", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- T-Test Results for Inflight wifi service ---\n", - "df_1 Mean: 2.400\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 0.6064\n", - "P-Value: 0.5442639813\n", - "--------------------------------------\n", - "--- T-Test Results for Departure/Arrival time convenient ---\n", - "df_1 Mean: 3.129\n", - "df_2 Mean: 2.287\n", - "T-Statistic: 64.7514\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Ease of Online booking ---\n", - "df_1 Mean: 2.547\n", - "df_2 Mean: 2.394\n", - "T-Statistic: 15.5027\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Gate location ---\n", - "df_1 Mean: 2.976\n", - "df_2 Mean: 3.046\n", - "T-Statistic: -6.8515\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Food and drink ---\n", - "df_1 Mean: 2.958\n", - "df_2 Mean: 3.011\n", - "T-Statistic: -4.1709\n", - "P-Value: 0.0000304613\n", - "--------------------------------------\n", - "--- T-Test Results for Online boarding ---\n", - "df_1 Mean: 2.656\n", - "df_2 Mean: 2.425\n", - "T-Statistic: 23.2966\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Seat comfort ---\n", - "df_1 Mean: 3.036\n", - "df_2 Mean: 2.986\n", - "T-Statistic: 3.9404\n", - "P-Value: 0.0000816032\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight entertainment ---\n", - "df_1 Mean: 2.894\n", - "df_2 Mean: 3.031\n", - "T-Statistic: -10.6884\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for On-board service ---\n", - "df_1 Mean: 3.019\n", - "df_2 Mean: 3.078\n", - "T-Statistic: -4.9255\n", - "P-Value: 0.0000008475\n", - "--------------------------------------\n", - "--- T-Test Results for Leg room service ---\n", - "df_1 Mean: 2.991\n", - "df_2 Mean: 3.166\n", - "T-Statistic: -14.1632\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Baggage handling ---\n", - "df_1 Mean: 3.376\n", - "df_2 Mean: 3.565\n", - "T-Statistic: -18.5273\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Checkin service ---\n", - "df_1 Mean: 3.043\n", - "df_2 Mean: 3.059\n", - "T-Statistic: -1.3296\n", - "P-Value: 0.1836795869\n", - "--------------------------------------\n", - "--- T-Test Results for Inflight service ---\n", - "df_1 Mean: 3.389\n", - "df_2 Mean: 3.570\n", - "T-Statistic: -17.6556\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Cleanliness ---\n", - "df_1 Mean: 2.936\n", - "df_2 Mean: 3.045\n", - "T-Statistic: -8.4732\n", - "P-Value: 0.0000000000\n", - "--------------------------------------\n", - "--- T-Test Results for Departure Delay in Minutes ---\n", - "df_1 Mean: 16.504\n", - "df_2 Mean: 15.856\n", - "T-Statistic: 1.7952\n", - "P-Value: 0.0726400300\n", - "--------------------------------------\n", - "--- T-Test Results for Arrival Delay in Minutes ---\n", - "df_1 Mean: 17.128\n", - "df_2 Mean: 16.484\n", - "T-Statistic: 1.7473\n", - "P-Value: 0.0805987692\n", - "--------------------------------------\n" - ] - }, - { - "data": { - "image/png": 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rCxcvXmyRkZH23nvvZbg3/euvv24tWrSwsLAwq1+/vjVs2JCwJhOPPfaYlStXzsaOHWt//vmnmZ06zvTo0cOioqLs0UcftUcffdTatGljF110kWdfPt+3xfSGDRvmORaPHDnSkpKSLCUlxXr16mUul8ueeOIJGzlypF155ZXWqFEjMzv1p8z33HNPgFseOOmvz9avX29ly5b1/Fl8egkJCTZixAirW7euNW3a1G6//XZ+yPPh6aeftpiYGPv000+9jhvTp0+3sLAwu/zyyz3baP369blOzsSsWbOscOHC9sYbb2R627gdO3bY448/biVLlrTffvstj1uYf82bN88qVqzo+fFk7ty55nK5bOLEiZ5pvv32W7v11lvt6quvZhv0YdGiRVa9enX75ZdfzMxs5syZFhER4TVK/bvvvrPrr7/eOnXqdM6vQ8LXAPnrr7+scePG9n/snXdczt3/x/sQotIeSlJp7z20UKlkFaKUWVZmQyrjtvfISoSsjMhq2GSF7EQkIqMi0Z6v3x+X63R9uq7c9/39fb/qvq/P8x935/P59Did+4z3eZ33eb9PnDhByjgN8I8fP+LcuXOIjY1FWloa6YD/5pOA/4Q1a9aAoigsW7aMS9yOj48HRVHYtWtXK9WubdHQ0EBro9u3b8PAwAAZGRm4fPkyJk+eDCMjI2zYsIG8s27dOixYsABLly4lk2FAQABcXV2ZREcAUlJS0LFjRyxYsADR0dHw9vaGhIQENm3aBIDl4TBv3jzIyMhg69atrVzbtkFzQSErKwsbNmzA3LlzSdmXL1/g6uoKW1tbHD58mPTbZcuWITs7+7fWt63CKRIsWLAAUlJSGD58OCwtLaGlpUWSJmRnZ8PU1BQqKiro3r07bGxsUFlZibKyMujo6NA8FPkRzhivOTk5tCufu3fvhqKiImbOnEm7WsYINCx4XU0ODw8nCSfYoWvYrF69GhRFkbjs/A5bFOQkLCwMQ4cOpZVxivzfvn1DZmYm3rx5w9yg4IBzTJ45cwaKioq4ceMG13u5ubnYvHkzTE1N4eXlheDgYGJX87t9zTmed+/eDSkpKWzfvh0jRoyAtbU1/P39iTPD5s2bYWxsDCsrKwwZMoTchLKzs+PL8GhHjx7lKjtz5gzMzMxosdWb9zF2uBAm/A83jx8/hpqaGtdBHnusP378GOvXr0dkZCTi4+OZfXILfP36Fba2tiQJVGVlJT58+IB9+/bh5MmTAIC0tDSMGTMGGhoafH+gx+5f7Plw3759GDhwIACW6C8iIkKcFkpLS/H8+XMAYG7XctDcRj569CjMzMwAsBwbREVFaTHX2Q4jjx8/5os2ZMTX38DEiRNJjCQ2ubm5kJKSQkpKCtf7NTU1XN6awL/3BOCvwDmQmw/IhQsXon379iTbJSfJycn/6gH8V2meAfTo0aPw8/OjCV5v377F7NmzYWhoyBWrFGBdpQ8KCoKkpCRfntB/+vSJ9nNNTQ0GDRqEGTNm0MojIiIgJiZGFpOcnBwsXLiQSYgC1mHJokWLUF9fj/r6elRUVEBHRwcURXFltiwqKkL//v3h6OiIvXv3MvEgOeBcC54+fYqwsDByKv/06VNMmTIFioqKOHz4MADWnPnixQvk5OSQdoyKioKKigrfxpfjPIw6ceIE9PT0ICcnB0NDQwwePJi0cVxcHBQVFTFnzhy8ePGiNavcpuBckxsaGmg/BwUFoWPHjoiPj+c6pNu/fz+zJoMVisHLy4vEgWTj5eWFkSNHAuDewGRlZXEJ2vzOmjVruMrWrVvHdf24uf3c3CbiZ/saoAuvly5dQnh4OC3r+datW2FlZQVfX198+/YNAMi/7O/nzZsHBQUFEsKKX7hz5w5UVVXx/v17WjseOnQIEhISyM/PB0Bv44sXL9LGMr/bN76+vly2yNWrV9G9e3ea7c1up5bEan4fx7yoqalB37598ccff+Djx48IDQ2Fg4MDunXrBlFRUWzYsAGVlZU4fvw439qDbDjXhe/fvwNgOXL169cPe/fupYmGAJCUlAQfHx9azHXmcL6J+/fvAwASEhLg5uaGU6dOQUREhBarOSUlBdOmTaON8397GzLi6/+Y4uJiLFu2jOt64pMnT9CtWzdyhZZzwbhy5QpWr17NZRzyK5yDcOvWrRg7diw8PT2xbNkysgAvWrQI7du3b9HLlZ83exMnTsTs2bMBsNry06dPGDhwICQlJckmj01+fj7mzJkDMzMzREVFkfLPnz8jJiYGvXv35svkMosWLcKUKVNoBl9NTQ169+6NP/74AwDdGBwyZAj69OlDfubn/sfJ0qVLiYDFbq9Xr17BysoK2traOH/+PO39oqIiWFlZwc3NjeeBFL/R/FDk1KlT6NatG7S1tWkB61+8eIEpU6ZASUkJCQkJtG+ysrIwevRoSEtL86WHw/Xr12nr8eXLl9G5c2ds3rwZly9fxq5du6CrqwtDQ0Oy9sTHx0NISAjz5s1jQg2AO4HCmDFj4Ovri4ULF5LyoKAgdOrUCfHx8TxtGX6fE1+8eEG8+Dk94yIjIyEjI0NiMbPb+uvXr4iIiCCHLAzA4cOH4eXlxSW4rFq1CkZGRjRxEGD1ucOHD+Pz58+/sZZtG39/fzx48ID8fOXKFXIQxXkroq6uDlu3boWNjQ18fX1pSbWePn2K2bNno1u3brTfxS+UlZURL3ROx4T09HQoKysjOjqaCDlsRo0ahQULFvzWerZVvn37hpEjR3Ktrffu3YOQkBDJIg80zYepqam4evXqb63nP5WqqipMnDgR5ubmEBQUhKenJ+Li4vDx40eMHz8efn5+AJgDgOTkZHJDMTAwkMRuvXXrFoyMjNCpUyesXLmSvF9RUYEBAwZgwoQJfN92bI4ePUq0g1mzZqFv376orq5GYWEhpKSkuG4jV1VVwc3NDaNHj+arNmTE1/8hzTtSXFwcEWoAligmISGBzMxMUlZRUQF3d3cEBATwVUf8K4SFhUFWVhYrVqxAVFQUunfvjgEDBpDFePHixejYsSO58s3AMphPnTpFjBr2v48ePYKvry+6d+9Oi1sDsATY8ePHY+zYsbQ+WFRURNsk8hNpaWnIysoCQL82P2LECJiYmJCf2YLiwoUL0bdv399byTZM87ksPT0d4eHheP/+PQCWAGtgYID+/fvjypUrtHeLi4uJ5wg/c/bsWfTp0wf19fWkPc+fP48RI0ZASEiIS7jOycnB9OnTISgoSNu85OXlYdOmTeSqFD8xc+ZMWFlZ0bwUIiMjuTLI379/Hzo6OrTDqcOHD/OdR9efERYWBnl5eURFRWH58uVo3749Ro0aRZ7PmDEDwsLC2L59O5OgkQNOsTA9PR39+/cnYzQ3NxdWVlaws7MjMQ7r6+sRGRkJZWVlMmcysNZitv3HeYssKSkJnTp1wr59+2htXV5eDnd3d563pPiRBw8eIDg4mCZ6ff/+HVFRUVBQUMCoUaNoh8r19fXYvn071NXVsWjRIlJeWlqKy5cvc2Ws5gc4bZuCggJISkoSMQsAJk+eDElJSaxfvx7Z2dnIz8/H3LlzISsry5dr8J8RExNDDugLCwvRv39/eHp6kmRbAGtf07dvXwQHB7dWNdss7P746NEjJCYm4sCBA3j//j3q6uqQnp6OY8eO0Q5PR40ahSlTpnCFpeNHxo8fDyUlJTg7O0NaWpp2kLJixQrIyclh1qxZuHDhAs6dOwcXFxdaci1+b7/6+nrs2LEDFEXB3t4eoqKiePz4MXmekpICKSkp+Pj44PTp0zh58iScnZ1pybX4pQ0Z8fV/COcEV1NTA39/f5iYmBDvpYqKCgwdOhSdOnXCrFmzMGvWLDg6OtKC//NLR+QF599+584daGpq4tatWwCAkydPQkREhCuranBwMOzs7Pi63dg0b4Ndu3ahb9++RDx8/PgxfHx8YGtri3379tHe/fz5M+m//3b3/z+D8++/fPkyxowZQ65S3Lt3D7q6ulwexBMnTsTgwYNRXV3N9MWfcMZR2rBhA9TU1BAVFYWCggIALLFQX18f/fv3x7Vr11qzqm2S79+/kzY8e/YsKb916xYGDx4MLS0tXLp0ifZNVlYW1q1bx+UZxo9j+s6dO5CWlibiPnseHDt2LO0Ahc2GDRtgZmbWYnIKficjIwMaGhokrubJkychLCxMu04GAKNHj4ajoyMzD3LA2RYvXryAkpISBg0aROyblJQUODg4QEJCgoRekZKS4kuvwpbgnNPu3r0LeXl5BAQEkLLp06ejY8eO2LhxI27cuIEHDx7AxcUFJiYmzNVkDth7jdjYWHKAV15ejoULF8LMzAwhISE0Abaurg4nTpxg2rAZ7HUiJiYGioqKmDBhAnk2e/Zs6OrqonPnzjAwMEDPnj2ZsfwTdj9qbGxEVVUVlJWVoampSeJhJyYmws7ODra2ttiwYQN27NiBvn37Mhnlf8Hx48chIyMDZ2dn6OrqwtTUlMspqbCwkCTX4vc8CpzrsampKSiKQlRUFJedvGLFCvTr1w/t27eHjY0NBg4c+K9PDPWfYGtrC4qiMGXKFABN7VtXV4erV69CR0cHKioqsLCwwLBhw/iyDRnx9TeQmJiIgoICFBQUICgoCJaWlli7di15vnTpUgwaNAiurq6YPn063wf/nzhxIi25CcASG3R1dQGw4vNxxl0pKyvDiRMnuIJk8/tmr/nCsXPnTpiYmMDLy4sIDw8ePCACLK8kKPwo0gD0v5tzYbhy5QrExcUREBBAvBb2798PHR0d6OnpYcaMGfD29oaIiAiePHnSKnVvy+zZswf29vYAWKEcjI2NMW/ePJoAa2JiAisrK57JUviRsWPH0k7gHz16hPbt22PcuHGkLD09HSNHjoS+vj6JNdwcfjJseHH58mUoKSnh1atX2L9/P3x9fVFZWYkjR47A2NgYp0+fpq0Zp06dQs+ePRlPwxZISkqCsbEx+W8RERHExMQAAH78+EFLJtp8bWZg3aZg24FPnz6Fjo4OXF1dSTbgwsJCrF27FjNmzMDSpUsZr+sWyM3NRX19PdatWwcjIyMEBgaSZ1FRUVBVVYWoqCgMDAxgb2/Plxu95owZMwajR48mP+fl5RGhhn3wWVZWhsjISFhaWiIkJISn5zo/tyEnWVlZMDU1xatXr1BeXo7du3dDTk4O48ePp71z/vx5XLt2jYQUYWiCHeLiy5cvMDc3h7a2NhFgL1y4gKCgIEhLS8PW1hYjRoxgxnELPHz4EHJycuQQND09HR07dqSFBDp58iRGjBiBXr168WXoKU44bZLa2lqMHj0anp6eUFdXx7Zt21BaWkp7v6ysDE+fPsWXL19ooiI/09yuW7x4MebNmwdBQUFaaBX2WK2oqMDHjx/x+fNnvm1DRnz9H9LY2IjXr19DVFSUJNzKz8/H1KlTYWFhQYvf1zwpBb91RDZ37tzBtGnTuGL/XLhwAW5ubti7dy9tkwewYlRNmDCBJtjy+yaPUzyMjY3F06dPUVNTg71798LCwgJDhgyhCbB+fn7Q0NDgyirKz+Tm5uLZs2cAWAcoc+bMAcDySlJSUsLYsWNJEq3Hjx9j3LhxGDRoEPz9/UmIAn6lsbGR6xCkuLgYDg4OJOMqAMyfP59LgM3Ozkbv3r2ZUANgbUQsLCwgLy+PnJwcAKz4kLt27YKCggImTpxI3mULsEZGRjwTOTIADg4OUFFRAUVRJFttfn4+7O3tMWjQIJw6dQoAa/4MCQmBpaUll/HN77DH87Vr1+Dm5obt27dzrcnXrl3D6NGjaQnK+PUgryVWrFgBISEhkuDk2bNn0NHRgZubG3Pw9Bdhe8VVVVWhpKQE69atg56eHiZNmkTeefHiBR48eIBHjx7xRRblP6O8vBwbNmyArKwsZs6cScovXboEb29vGBoakliaZWVliIqKgo2NDQICAph41y2Qnp4ORUVFnD59GgArhilbgOX0gGXgTVZWFiiKIgneiouLYWpqShNgAVZ4C8744fw8jlvi0KFDJORZXl4eevbsSZsP3717h8rKSuzfv58vw4S0xKFDh2g37iZMmAA1NTUuAZYd25kNY9c0sWXLFty8eZP8HBMTg/bt23PFtm5u3/CjXsOIr7+BkJAQqKurk9POgoICTJ06FVZWVjyzyvNjR+SE/ffHxcWRqzkfPnyAgoICKIrChg0byLtVVVVwdXXFyJEj+b7dANCuHdfV1SEvLw/S0tLEa6a2thZ79uwhAiw722pGRgbJQs/Ait3q4+MDYWFhrF+/HhRFIT4+njxPTk4mAmzzKzvMYgzSr9jG8a1btzB69GgMGzYM3759o3nRsAXYqKgoIkQwmzwWjY2NKCgogJubG6SlpYmYVVpait27d0NWVpZLgHVxcaHFnGNoOnE/ePAgKIqCkpISXr9+TfpndnY2HBwcYGBgAHV1dbi6ukJMTIy5GoqW57OsrCyoqamBoihaEorKykq4ubnBx8eHWZN/wZs3b2BnZ4fo6GjSP7Ozs6Gjo4NBgwbhwoULrVzDtk9qaio6depE2urr169Yv3499PX1aYIDJ/y8PrMTjZWUlCA2NhbS0tKYNm0aeX758mUMGzaMS4CdMWMGk4eiGc3bYsqUKVBTUyNCzffv37F79250796dK6Y4A53i4mIMHjwYoaGhpKyoqAimpqbQ1dUlTg6cMH2RDrs9du7ciZEjR+LDhw/o3r07AgMDyZx39epV/PHHH8Q+Z2Dx/v17WFpawsnJiRzAA0BAQAA0NDSwfv16vHr1Cn379oWjoyMApv/xwtDQEIqKirh79y6AphiwHTp0wNy5c/Hu3Tt4eHjAy8uL79uPEV//izTvTGwB4f79+7C0tMSBAwfIM3YIAlVVVRw6dOi31rOtwtl+r1+/Ru/evWFiYoJHjx4BYAk4Xbt2hZeXF+Li4nD48GH069cPenp6fBesmRebNm2Curo6LYHWy5cv0a1bN5K4A2gSYC0tLeHl5cWVRZ4RYFm8ffsWxsbGEBQUxPLlywGwYjez+xhbgA0ICKAlzeN3Dhw4AGlpadLnysvLsWjRIigqKqJXr17kPc44cosWLYKKigoWL15MSyjFz3B6dTx+/BiWlpZQU1MjByls7xpZWVlarENODy+GJqqrq7Fu3TrExsbCysoK2traePjwIZnvCgoKkJqaijlz5mD9+vXE05if4RyH0dHRmDVrFsLDw0nixdTUVAgKCsLf3x+xsbE4fvw4+vXrx5cJFH4Fuw2ah1+YNGkS9PX1uWLAKigoYMSIEVw3ovgZzrbjnN8CAwPRu3dvEnPz27dv2LBhA4yMjGjJ3/idRYsWgaIo4kn4ZwKskZER8QSrrKxkwnk1o/ka++jRI1hbW9MO6cvKyrBt2zZoaGjg06dPv7uKbZKWbJM9e/agU6dOtCRkxcXFsLCwgKysLLkZxfBr0tLS0K5dO4iIiGDGjBm0Z1OnTsWwYcO49nz8Bq85LD09He7u7nB1daUJsNOmTYO6ujpUVVVhbm7OJA79Ca9xXF9fj379+kFZWZmET6qvr0d8fDw6dOgAbW1tGBoaMs41YMTX/xqcg/nkyZNcceI8PT1hbW1NK8vPz8fatWsZsQu8J8Pk5GQMHDgQFhYWRIDNyMiAjY0NevXqhd69e8PHx4eJ/fOTx48fw9/fH7a2toiLiwPAOj3W0dHB9+/fAYAsHDU1NdizZw+UlZUxb948AIxR3ZyvX7/C3NwcOjo66N69O4m7WVtbS8uwLCwsjGnTpjGL8k/S09Nha2sLXV1dIsDm5+dj6dKl6Ny5MwnfAIDWZsuXL0deXt5vr29bJyoqCk5OTrC2tgZFUVBQUCAesN++fcOePXugoKCAYcOG0b5jBNiW57Ty8nJyrZERq/+cP/74A9LS0nB3d4eWlha6d+9ODgHOnDmD/v37Q15eHnZ2dvD29mbWZB7cu3cPq1atIt6HAMuDvWfPnli2bBmApjH78uVL2nVbhiaae22xYw9zXncsLS3FkiVL4Ofnx4ztn+Tm5sLZ2Rndu3f/UwH2ypUrGDFiBLp160bz/udnG5EzlFJGRgbU1NSQmJhIu1Xm6emJPn360L4rKytjQtfw4MWLF+QQj427uzvGjx9PO3T6/Pkzxo8fz6wlzWD3xQcPHuDkyZO4evUqWXcXLFiAdu3aYf/+/SgsLERBQQHCwsIgJSVFQqkxgCv28vXr19G/f3+4ubnRktpevXoV58+fJ32QCXfRBFtbYPfH+vp6ODo60gRYgOVQd+HCBaYNf8KIr/8FOA2SpKQkuLi4QFRUFBs3bsT169cBsGKvsAM4A9wbY35eWDjborS0lBZTJSUlBW5ubrCwsCCBwcvKylBcXEwzaPh9ILPJzs6Gn58frK2tsXfvXuTk5MDY2Bjfvn3jere+vp42GTLQqaurQ3FxMZ4/f46BAwdCUVGRJNHiPLm7ceMGkwyFg4aGBmRmZqJ///5QV1cnHh8fPnzA4sWLoampiaioKPI+pwcsA52YmBiIiIjg5s2bePfuHS5fvgxHR0fIysrSQhBs2bIFHh4ejNDAAXtdPnfuHKZPn46pU6fSYpBWVFQQAfbx48etVc02SfN+FBQUhNu3bwMAXr16BRcXF8jKyhLv4O/fv6OoqIgY4gCzJgNNffDWrVtwcnKClZUVZGRksHXrVnI1Lzg4GJ6enigvL0djYyPTbs3g7IunT5+GuLg44uPjaeF++vTpwyV6sduz+e/gZwoKCuDh4YHu3buTeI8tCbBpaWmIjIxk7MNmnDhxAps3b4aPjw8MDQ1hYmKC6Oho1NXV4f3791BWVsbOnTtbu5ptDs4xePDgQQgKCmLEiBEkHwrAsnc4D+2bz4VMX6Rz7NgxSEpKQlFRERoaGvD29kZ1dTUaGxsxe/ZsdOjQAcrKyjAxMUGvXr2YMEoc7NmzBx4eHsjIyKCVX7t2DcbGxrC3t+eZA4Xpg03ExsZCTU2NrCWcybN69+4NHR0d3LlzhxnHPGDE1/8nnMJrSEgI9PT08Pr1a6xcuRI2Njbo2bMnZs2ahVu3bsHf3x9BQUFc3zGwWLRoEUxMTGBiYkITZ9LS0uDu7g5LS0uem2SmLek8e/YMfn5+cHBwwNixYyElJYUxY8Zg4sSJmDRpEqZOnYrhw4fj5MmT5BtmMmzqR+/fv8f79+9pnkf379/HoEGD0L17d5JMa+XKlQgNDWX6HwfsfnT//n1s3rwZFEXB2NiYnDC/f/8eixcvhra2NlcQdgZukWDmzJkYMWIErezly5ewsLCAsrIyiYVWVlbGCA08OH/+PERERODu7g4jIyOIiIiQpCgAS4C1tLSEvLw83yfJY8PZf+7du4f09HT079+ftnHLz8+Hi4sL5OXlaYku2TBzYhNpaWlQUVHB6dOnUVhYiCVLlsDExATa2tpYsWIFjh07ho4dO+L48eOtXdU2zezZs7Fu3TpERkZCU1MTlpaWWLhwISorK5GRkQFra2skJiYCoPc/fu+LzUWv1atXg6IoaGhokJsmbAFWVlYW06dP5/od/G4fsvvQ48ePQVEUCe1169YtrFq1CmJiYujbty+mTJkCHx8fBAQEMCFDWmDu3LlYvXo1YmNjERwcDCEhIbi7u2PPnj2or6+HsbEx2SczsOCVwLakpAQDBw7Evn378O7dO+zcuROmpqZwdXUlDg3Xr1/HiRMncOnSJS4vT34nISEBxsbG8PPzo3loAsCuXbsgKioKCwsLJvnlL3j37h00NDRgaWlJBFj2enPmzBlQFAUZGRnG25oHjPj6/4DTqHv48CGcnZ2JdwjA8hA5fvw4VFVV4eHhgW7duoGiKCY+5E84jcItW7ZAVlYWa9euRWhoKDp37kxLGpOWlgYPDw+oqKgw1/E4aEloefLkCfz8/KChoQEZGRmEh4fD19cXo0ePxsSJE+Hr68t42HDAHsunTp2Cqakp1NTUoK+vT0uI9+DBAwwdOhSCgoIYOnQo2rVrR7yxGZo4evQoFBQUMG3aNDg7O0NeXh6ampokZtf79++xdOlSyMnJkeu2DPT1JC4uDl+/fkVoaCjU1NS43o2OjgZFURAUFKRlrOV3oaE50dHR2LRpEwCW0Dpt2jR07twZSUlJ5J3y8nI4OjryTOrBz4SFhUFUVBS6urpo3749Tpw4QXuen58PNzc3UBTFxONrgcLCQkydOhVr1qyhlWdlZSE+Ph4KCgqkDd3c3GgxxfkdznY4deoUhIWFcfHiRQDA3bt3sWnTJkhJSaFPnz4YOXIkzM3NERER0VrVbfOEhYVBSUkJa9euxeTJk6GlpQVFRUVaCIKdO3eCoiisW7eulWvb9rh37x5OnTqFJUuWcD17+fIlli9fTkIDycvL024B8DOc4/jGjRtQVFTEvXv3SNmLFy/g5+cHfX19GBoawt3dHcrKylyJbPmZ/Px82s8ZGRkYNGgQPD09SRib2tpaJCYmwtjYGM7OzqiqqmqNqrZJWtonJyYmwtzcHD4+PjQP2CNHjsDd3R2RkZGMM8NPWmqHjx8/QltbG2ZmZrS9yPnz5xEWFoYZM2bw/eEdLxjx9b9AQkICnJ2dMXDgQNTW1nJdoy0qKsLevXsxePBgqKurM6JXM27evIm4uDja5u7cuXMQExPD6NGjSdnJkycRHBzMDOSfcE6GJ06cwJYtW7Bx40YSbzgnJwf+/v6wt7cnHiHNYdqyibNnz0JYWBibNm1CZmYmlixZAoqisGjRIvLO+/fvsW7dOgQFBTHGIQ8+fvyIXr160UTr1NRU2NraQktLi5y+v337FqtXr2YEr59wblDWr18PGRkZPHz4EFevXoWBgQFWrFhBM6bPnDmDcePGMddCm8FuxxcvXuDOnTsIDAzEkSNHaO8EBQVBSEiI5vnPQO+Dly5dgoGBAc6fP4+LFy9iyJAhkJGRoR0uA6xwSrNnz2b6IA/u3r0LKysrGBgYIDk5GQD3NdovX75gx44dGDFiBIkpzkDn6NGjmD9/PrZu3cr1rKioCEuXLsXAgQNBURTMzc1boYZtn5cvX0JJSYk25z19+hT29vZQUlLCmzdvALD646lTp5jx3Izi4mLo6emBoihMnToVQNNYZtvhDQ0NqKmpwbp162hJoxhYbNq0CYsWLUJYWBgpY/ezyspK5OfnY9q0aZCXl4eNjQ0jev1k7969UFFRQWVlJerq6lBXV4eNGzdCXV0dSkpKtHfZAqylpSUsLS2ZkF6g2zUHDhxAdHQ0LSzIkSNHYGFhgZEjR+LkyZP49u0bBg8ejPXr1zO3yX7C2Yb79+/H3LlzkZCQQA7uPnz4AB0dHRgZGeH8+fN4/vw5Bg8eTPLJAIzW0BxGfP1/Ul9fj5CQEKioqNAyebM7WvNByxkTg6HpGo+goCASEhJozy5cuABxcXH4+/tzfccM5CaCg4PRrVs3GBkZQVNTEyIiIjh27BgAVggCdhKuDRs2kG8Y7xo6Hz58wIABA0gbffz4ET179oStrS3at29PC4MBMP2vJV6+fAkpKSnioQSw5rqzZ89CSkoKFhYWxEuOmQO5uXfvHsaPH48zZ84AYG1KgoKCYGdnh/DwcBQVFeHt27fw8PCgxedj+mMTx48fh7CwMHR1dUFRFEJCQriy+86aNQsURZF2Zmhiy5YtiIiIoHkRVlVVYciQIZCVleUSYNkwfZBORUUF+vTpA4qisHDhQi6bkLO9mLmQN0+fPoWxsTE6d+6M6OhoAE1txW6/+vp61NfXIyEhgTxj7Bs6jx49QpcuXWi37hoaGpCRkQEJCQno6elxxa1n+mQTNTU1SEpKgoWFBXR1dWnJZdjwu0DzKxobGzFo0CBQFAV3d3daotXmY/XJkyc0QZvfefbsGTkcYefuKCkpwbZt2yAvLw9fX1/a+7W1tTh48CAcHR25PGb5Dc6+FRwcDCkpKejr60NZWZkWI/z48ePw8PCAqKgo1NTUYGBgQPJ68Ptawvn3R0REQFxcHHZ2dpCWlsbIkSNx7do1AKzcE1ZWVpCUlISCggJMTU1puVEY6DDi69+E12JQWVmJVatWQVFREZMmTSLZWDnf5ezA/LygNJ/IqqqqsG/fPkhKSpITZU4uXrwIiqLwxx9//K4q/qM4duwYpKWl8fDhQ5SXl6OqqgpTp05Fly5dcOHCBQCsDYyHhwcmTZrE9wtJS3z79g3Lly9Hfn4+Pn36BF1dXQQGBqKsrAxTp04FRVGYO3dua1ezzVNdXQ0LCwtERERwxd2zs7MDRVEwMTFBXV0d0xebcezYMRgYGEBVVZUWX/P79+8ICwuDoaEh2rVrR0JiMIZNE+y+lJeXB1tbW2zZsgUPHjxAcHAwBAUFsXPnTq4s6XPnzmU8lHjAvgbv4eFB87aurq7GkCFDoKCgQAxuhiZ4zWeVlZVwdXWFjo4OEhMTGXHwT2jeLnV1ddi3bx/09PSgp6dHkrFyil68vuFnePWtxsZGmJiYcF0BLS8vh42NDQQFBeHh4fE7q9mm4fR4Y8+BDQ0NOH/+PJSVlWFvb89TgGVgwasP1tXVITAwEJ07dyY3AThpvi/m530ywLoxxsnDhw8hKSmJ9PR0ACy7cPPmzTAyMsK4ceNo79bW1nIdOPMTzfvfly9fMGTIEDx9+hQlJSW4cOEC1NTUYGFhQd7JycnBtWvXkJiYSDvY42c4//779+9j+PDhuHXrFgAgOTkZffr0waBBg3D58mXy3uXLl3Ht2jXyLb+vxy3BiK9/A87F4ObNm7h8+TKuXLkCgNXBli1bBktLS8yaNYsEW+f3wcsJZ/vV1tbS2iYuLg6CgoI0N3U29+7dYwZwC0RHR8PR0RENDQ209vT394eKigqJO/X27VvS/szGr6kNcnJyyFV4tjizdu1a9O/fH8XFxQCAVatWQVtbG/Ly8igsLGydCrdBeBnHDQ0NmDlzJqysrIj3NcCaH8eOHYv4+HiSyZaBTkFBAYYNGwYhISHMnz+f9qympgbfvn1DUlISLly4wBg2PLhx4waioqLg6+tLEw3DwsLQoUMHxMbGoqKiohVr2PZoaYM7YcIECAkJ4fjx47SrizU1NbCzs2OEmmaw15OMjAysW7cOy5Yto3mvOzk5wczMDCdOnGAE2Bbg7Is1NTX48uULAFY7nThxAsbGxnB3d0dJSQkAxrbmBWcbFhcXkzZsaGjAokWLYG1tjY0bN5J3fvz4AU9PT9y8eZPvxS427HGZkpKCsWPHwsDAAIsWLcKlS5cAsPJP6Ojo0DznmL7YBGc/evnyJZ4+fUoSuwHA8OHDISEhgatXr7ZG9f4RPH/+HBRFYdKkSaTs6dOnGDhwIBQUFIgA9u3bN0RHR8PQ0BABAQGtVd02RfPEqVu2bIGuri4GDRqE0tJSAKw+ev36daipqcHS0pLn7+HnMX348GHaz/Hx8XB3d4erqyvNhk5NTUWfPn0wePBgMj9yws9t+Gcw4ut/wLx586CiogITExOIiopixIgRyMnJQU1NDf744w9YWVlh9uzZXJ42/Azngrxu3Tr4+vrCzMwMK1asILEzd+/ejQ4dOrSYNIERGrhZsWIFZGRkyM/sjfKNGzfQvXt3PH78mPY+Y2A3GdcnTpyAnp4eIiIiaKfEY8aMgaurK/l5zpw52Lx5MzOewVqEOWPv8fLu//HjB9zd3clB1IkTJzBt2jSoqKjg3bt3v73ObZGWxmFhYSGGDx8OCwsLxMXFkXJeQg1j2NCJjIwERVFQVlbmSsoYFhaGLl26IDo6mhFgf8LZB7OyspCbm0tLEuPl5QUJCQmcOnWKdk20traWWUd4kJiYCBkZGbi5ucHHx4d2Y4ctwFpZWdGuxzOw4OxPK1aswIABA6CoqIiZM2cST6+EhATY2NjAw8ODXL9l+iFvoqKiYGFhAQUFBSxfvhxlZWUoKytDYGAgjIyM4OzsjKVLl8La2hrm5uaMp1czTp48iS5dumDevHnYunUrbGxsoKOjg5ycHNTW1iIlJQX6+vowNjZu7aq2KTjtlMjISJiZmUFaWhrOzs6YPHkyeTZy5EhISUkxNyhaoL6+HkeOHIGoqCjtRmhWVha8vb0hIyNDE2C3bt0KZWVlBAUFtVaV2wSLFi2ClZUVAFZfrK2txb59+6CtrQ0VFRXau2wBVkNDg2dSW35l9erVGD16NG1t3bp1K1RVVSEvL4/79+/T3k9NTYWTkxNsbW2ZBNR/A0Z8/Zts3rwZcnJyuHv3LgCWV1y7du3IIlJdXY0lS5ZAVVWVZFlmaCI8PBzS0tLYsWMHli1bBj09Pdjb26OsrAw1NTXYs2cPhISEaPEMGVreZOTl5UFHRwdTpkyheXtlZmZCXV2dSeLRAqmpqejUqRN27NjBFRfp0KFDaN++PQIDA+Hr6wsJCQnmejKaru5YWFhgz549pJyzb7I3bz9+/MDcuXNhY2ODHj16wMjIiHaVnp/hbK87d+7g1KlTePHiBblS++HDBwwdOhR2dnbYvXs3z+8YeLN69WpISkpi4cKF+PTpE+3ZtGnTICMjQ4QbBhZhYWFQV1dHly5dMG7cOJw9e5Y88/LygqSkJE6fPs2VvIPpj008f/4cioqK2LZtGwBWYsYOHTogJCSEzIkVFRUwNTVFnz59UFZW1prVbbNERUVBTk4OsbGxOHfuHOTk5NC3b18UFRWhvr4eBw8ehK2tLaysrPj6Wm1zOMdiTEwMFBQUsGXLFixYsABCQkKYMGECvnz5goqKChw4cAAeHh7o06cPvL29SfgaZjyzBJuioiLY2tqS/VtVVRWkpKQQHBxMe+/06dOwtLSkZfhmYLFs2TJISUnhypUr+PDhAwIDA0FRFO7cuQOA1ddGjRoFiqIYu7AF6uvrcfToUXTu3BlTpkwh5U+fPuUSYEtKShAbG8t16MxvlJSUkPmMnVvix48fOHbsGGRkZDBkyBDa+w0NDbh06RKGDx/OHDz95OPHj+RwmDO+/+HDh6Grqwt/f38up66kpCRMnz6dWUP+Boz4+jeZOHEili5dCoCVJU9cXJwY3GyPmqqqKuzevZsZzM148OAB9PT0yIJx/vx5CAkJ0QQGgCVwc8ZU4nc4J7TTp09j27ZtOHToEPEY3rx5MywtLeHj44Pc3FxkZmZiwIABsLe3ZyZDHlRVVWHkyJEk62rz2F0lJSXYuHEjrKysMHDgQDx69KjV6trWyMrKgr+/P+zs7GgZQ3kJsI2Njaivr0dBQQHNo46f4ZzTwsPDoaqqCgUFBRgZGWHatGnIzc0FwDIcPT094ejoiM2bN7dWddss7HYsKirCp0+fSIgQgOVxo6SkhBUrVuDz58+07/g9bEhjYyPXeqKiooK0tDTExcXB0dER/fv3p4UMGT58OCiKwvXr11ujyv8Ibty4gb59+wJgHYgqKirSPL2ePXsGoCmrNwM3L168gL6+PgnllZGRgY4dO9Lsw8bGRuzatQuTJk1ibBseZGZmYtGiRUhMTCRlKSkpEBcXx/jx42khf9ih0QDmVhkn379/h5GREd68eYPXr19DUVGRdqX74sWL+Pz5M+rr65nbUDwoKyvDoEGDcPToUQCs/icqKkrsRU4nkfnz5zP75F9QW1v7SwGWM/46s19u4sSJE6AoCjdu3ADACil39OhR9OjRA8OGDaO9y9lu/N4XOcdmcnIyNDU1sXr1alK2e/dumJqaYvz48Xjy5AnP38Gsy38NRnz9BbySQ5mYmODgwYO4e/cuREREsH37dgAs42XJkiVc2ZP5eTA3b7/09HRoamoCYF3RExUVJe1XXl6O48ePo6ysDI2NjeRbZkFpIiQkBNLS0rC2toa4uDjMzMwQExMDgBUz18TEBIKCgtDW1kbv3r0Zj4YWqKmpgb6+Pi28BWc/Y3slVVRU0DYo/AxnTOHr16/Dz88PJiYmOHToEO0dhr/GypUroaCgQOKeTZ48GZKSkvD29kZOTg4Algesg4MDpk6dysyDHLDbIikpCZaWllBQUICdnR1mzJhB3omIiICSkhJWr15NYjpzfssAXLhwAUFBQSSLPMASvAYMGAAXFxeaABsREcEINL/gzJkz0NXVxe3bt6GsrIzAwEAyX968eRPe3t60uIcM3GRnZ0NfXx8Ayz7ktK/Ly8uRlJSE6upq2jrDrDksGhsb8ejRI1AUhfbt23M5NKSkpEBCQgKBgYHk0J7zW36m+d//+vVrqKio4PDhw1BTU8PEiRNJP8vNzcXo0aNJMlsG7vYrLy+Hrq4u0tPTcfbsWdo4rq2txZYtW2gJegBG/GfDK4kbOwRBcwE2KysLbm5u6NWrF6qqqvh6HO/fvx+LFy8mP3/69AkjRoyAmJgYcfZiC7A9e/bEiBEjWquqbZaEhAR4enoSh4VXr15h4sSJ6N27N9auXUveYwuwEydO5ApBwPDXYcTXFuA06vLy8kjMsyVLlkBZWRkdO3bEvn37yDulpaXo168fVq5c+dvr2tZhe3NduHABpqam2LdvH7p27Uo8hgHg6tWrGDNmDF68eEHK+Hkxac6xY8cgLy9PrgHk5eVhzpw5MDIyQnx8PHnv5s2byM7OJv2XMWpYcIr5379/h6urK6ZOnYrq6mrasxcvXiAsLIzvPeSaw26j48ePY9iwYejduzc6duwILS0t7N27l7zHbIb/nDdv3sDJyYl4hqSmpkJUVBS+vr7Q1tbGqFGjyJxZXFzMJMrjwblz5yAkJIR169bhwIEDWL58OWRlZTF06FDyzoIFCyAsLIwNGzbw9SEowLqxw47V3NDQgJycHGhqaqJLly5cMdbv3LmDAQMGwNXVlWbjAMx6AjSNw+fPn+P169eor6/Hq1evYGdnBzExMYwePZr2fmhoKPr370/CijDwvimRlZUFaWlpLFmyBOLi4rTY4rdv34abmxsJ98XAmyNHjoCiKEyYMAFFRUW0Z2lpaaAoitmjcMAeyzdu3MD27dvJz7NnzwZFUfDy8qK9HxERAQMDA7x///6317UtwjmO2Tc/f/z4ARcXFxIznHOfl5eXhwEDBiAhIeG317Wtw+57586dw8yZMzF27FhkZWWR+ZGXAJudnU2u1/MjjY2NyMnJAUVRoCgKCxcuJM8KCwvh4+MDYWFhmgB77NgxdOrUCZGRka1U67bHmzdvICEhASEhIQwfPpzk5sjLy8OkSZNgZWVFE2D37NkDJSUlLF++vLWq/I+HEV95wLmgLFq0CMOHD0daWhoAlteXg4MDDAwMSBzIDx8+wM3NDZaWlny/yWtOXFwcCYANAGZmZqAoihYPt6qqCu7u7vD09GTEmxZYtmwZevfuTSt78+YN/P394e7uzhWPD2CEMKDJoOFMGAOwAoi3b98ee/fupV21iIqKgqWlJSO+8oB9DXTHjh3IycnB7du34erqCmtra9oBANPvfk1jYyNSU1NRWFiIjIwMKCgoEM+QgIAAdO3aFU5OTrRYckybNlFfX4+pU6ciMDCQlNXW1iItLQ2ysrIknAjASt7z8uXL1qhmm+HHjx9Yv349uQnBJjU1FaamprC0tORKfHL37l2SMI+hCU6vayUlJWzZsoWIqitWrICEhARCQ0Px5MkTZGVlISQkBOLi4i1e0eNHOOeyPXv2YNu2beT69owZMyAoKEjrd9XV1fDw8MDAgQOZefAnv2qH+Ph4UBSFyMhILsH/9u3bzAHKT9hjOTExEdLS0ggNDSWxDHNycjB8+HB07twZsbGx2Lx5M6ZNmwZRUVEmDNVPOPvg8uXL4efnR+xm9rXvAQMGkNtjJSUlcHd3h729PbNPboG0tDR06NABQ4cOhZaWFiQkJLB3714ibB85cgRdu3blOuDjd0aOHAkHBwd07NgR06dPJ+W8BNgfP37g8uXLTB/koLCwENbW1jAzM8PIkSMxePBgcsDEKcCuW7eOfHP27FmmDf8fMOLrL5g7dy6kpaVx8uRJWuy4pKQk9OvXD6KiotDX14eRkREsLCzI5obpkE1kZ2fT4ro+efIE+vr6MDQ0RGxsLLZu3QonJyfo6uoSo5AxsJtgt8WWLVtgbGxM+iHnKSlFUSSmHEMT7DZKS0vDsGHDMGDAAPj5+ZGT4oULF6J9+/YYN24cpkyZAn9/f4iKijIZG1sgOjoahoaGtPnt8ePHcHJygqamJuPNwIOW5jL2XDd37lyMHj2arB1LliyBra0twsPDmXmwBRobG+Hs7IyBAwfSymtraxEREQEXFxcmxvBPmntLx8XFYdasWaQ8OTkZFhYW8Pb2JvHR2HDeoGBo4uzZsxAWFsaWLVu4YgqvXLkSZmZmEBQUhLGxMQwMDJj1hAPO/hgaGgpFRUXs2rWLeNpkZGTA09MTUlJSWLJkCebPn0/sQyaMEgvOv//48ePYtm0boqOj8eXLF/Js9+7dLQqwAOPBzubatWsQERFBbGws17Pi4mLMnTsXGhoaMDMzg5eXF3OIwoPQ0FAoKChg27ZtePPmDSmPjY1F+/bt0bdvX9jb28POzg6GhobMPrkFvn37hpCQEOzYsYOUTZ48GbKysoiLiyMC7L59+9CtWzeuhKL8SmNjIyIiIjBw4ECkpKRAREQEM2fOJM/ZAqyYmBiJJ86Gn/tg89COiYmJ6NmzJ8LDw9G3b18MGTKE7JXz8vIwefJk2NjYYNGiRbTfw89t+P+BEV9b4MKFC1BWViaZGGtra/H+/XtcuXIF1dXVqKqqwuHDhxEdHY2TJ0+SDsjPRk3zjV5tbS1qamowdepU+Pr6oqysDPX19Xj37h0GDRoEIyMj2NvbY8KECWRB5vf2a2ljkZ6eDiEhIaxcuZLmwZSZmQlDQ0NyTZmBzunTp8lp6NSpU2FiYgI5OTlcvHgRAGuTMmbMGNjb22PixInIyspq5Rq3Pdjj+uDBg1BXVycGNrv8ypUr6NKlC3r16kULQcDvcI7lc+fO4ciRIzhy5AhNGAwMDIS9vT3ZIHt5eWHXrl2kbfldaACa+llhYSFKSkoAsA4CrK2tiTcDm23btkFDQwOlpaW/vZ5tnerqakyZMgWmpqaYP38+aVd21m5vb2/cvHmT6zumDzZRUVEBNzc34l1dWVmJ9+/fY/369Th9+jRqa2tRVlaG9PR05OTk0BLBMTSxZcsWyMvLk+znnHz69Al//PEHdHR04OHhgRkzZhC7kJ/tQ4BuY8+dOxdycnJwdnaGjIwMnJyckJqaSvYiu3fvRvv27TF9+nT8+PGjtarcJmG3Y0REBEaNGgWAJX5duHABY8aMwcCBA0nf/PTpE+rr65n4/zxISkqCvLw87t27R8rKy8vJYUpmZiaWLFmCOXPmIDY2lhnHLZCZmQlZWVkYGxvj7NmztGeTJ0+GjIwM9uzZQ24IMOOZzo8fP6CqqorY2FicPHkSnTp1wuzZs8nzwsJCuLq6ol+/fq1Yy7YF+7Ys27579+4d/Pz8cOrUKRw+fBjW1tYYOnQoTYD19vZGQEAAEwLtvwAjvrbAxYsXoaurizdv3iA7Oxvz5s1Dz549oaioCA0NDZ6nycwJAAvOBCcA60SlS5cuJF4pm5KSEtqVb2ZBbuLQoUPYsGEDNm7cSK7yxMTEgKIozJ8/H5cvX0ZOTg769+8PW1tbZoMMemiBxsZG/PjxAzY2NliwYAHtPS8vL8jJyRGvpdraWjQ2NnJdy+VneC2ut27dQteuXbFmzRraWM3MzISdnR2mT5/OZPLmQXBwMOTk5KCvr4+OHTvC0dGRxHvdu3cvTExMYGpqChMTE2hpaZG2ZQycpjY4efIknJ2dcfDgQdTW1uLu3bswMjLChAkTaALszJkz4eTkRJLm8TO8+s/Xr18RFhYGS0tLREZGknfOnDkDGxsbODk5Md5dv6CiogKOjo5YvHgxnj9/jtmzZ6Nv376QlJSEkZERQkNDGTvmT2hsbISfnx8JLZCTk4P9+/fDzs4OdnZ2ePr0KQBwjWHGvm5i48aN6N69O0l4wo71am9vj+TkZNJWmzdvho2NDbOWtMDq1ashJyeHpKQkDBkyBG5ubnB3d4ezszPk5OSItyHArMe82Lx5MxG0Hj16hJUrV0JdXR0yMjIICwvjOWaZccybIUOGkJB8zdeQoKAgtGvXDvv372+l2rUd9u7di+DgYFy5coXWTsuWLSNJVxMSEtCxY0eaAFtSUsLsk39y9OhRuLq64tq1a/jy5QspnzZtGiwtLQGw2tDW1haenp5EgP348SOTg+K/BN+Lry0NxuvXr8PIyAh2dnaQlJTE+PHjERcXR7LZnjx58jfX9J9BfHw8TExMsGnTJnz79o2UjxgxAv369WvRI4mfB3JwcDDtCu3MmTMhISEBQ0NDqKurQ0JCAqdPnwbA8mZQVVWFtLQ0tLW1YW1tzVzHA2vhjYiIoPWvkpISaGpq4tChQwBAE1cNDAxI4Hp+bjdesMfi7du3sWfPHiQkJJBT0nXr1pGkHdnZ2aioqEBERAR8fX2JVyJDE/v27YOcnBzu37+PHz9+4OPHj3BxcYGDgwOJs7ljxw7MmzcPISEhxJhkNihNnD59GkJCQli9ejUtY/y5c+dgbGwMU1NT2NvbY+jQoejatSsTkw/0Oe3bt2+oqakhB51fvnxBSEgIlwB79OhRBAQEMPPhT1pqB3Y4KhEREQwbNgx79+5FdXU1xo0bB29v799cy38mc+bMgampKZYuXQpbW1t4eHhg8uTJcHV1hYqKCioqKmhzID/bh80pLS1FcHAwdu7cCYDl3CAuLo5Vq1ZBV1cXRkZGOHPmDNchHtOG3GRmZsLf3x9iYmLw8/PDhQsXAAAPHjyAsbExk1jrT0hNTQVFURgzZgyUlZXh4+ODmJgYrFu3Dp07d0ZOTk5rV7HNwzkuhw4dCklJSaSmpnIJsMHBwXzfni9fviTJtdzc3GBhYYHLly+jqKgIL168gIiICHHyOnLkCLp06YLx48fTfge/2zc5OTmQk5MDRVHo1asXJkyYQBKVlZaWYuDAgThy5AgAVpgqR0dHODg40BI48nsb/jfga/GVUxzkRXJyMjZs2IBTp06Rd4uLi2FkZEQWaX6nuUGXnJyMRYsWkaQxYWFhqK6uRmJiIhwdHUm2WmbwsqiursaaNWtgYmKCsWPHEm/Whw8fory8HOXl5Rg3bhxERUWJWJObm4vHjx/jzp07pB353dtm9erVoCgKy5cvpwmw5ubm5FoZ0CTAjho1igla/wsSExPRtWtXaGhoQFlZGZaWlsQLZMOGDZCWlkaPHj2gpaWFrl27MnENWyAqKgouLi5obGwkYsKnT59gbm7OFbOUDb+PZTaNjY348uULbGxsuDJ0s9vy4cOH2Lt3L0aOHImoqChkZ2e3RlXbFJxr66pVq9C/f38YGBggLCyMhFUpLi5GSEgIrKysaCEIeP0OfuPWrVskNAhnu3D+95UrV4gNyO6LkydPhp+fH2pqahih60+4cOECJk6cCGVlZaxatYqsHwcOHED//v1pN6IY6NTX1+PGjRsoKipCVlYWNDQ0sHHjRgBASkoKOnToAGNjY1y/fh0Aq98y/bFl6uvruW7shISEwMLCgglf8xc4cOAAhgwZgt27d5NwA58/f4a5uTlzEMoD9lh88+YNnj17xhUybsCAAZCRkUFKSgpjC/Jg+fLloCgKCxcuxKxZs2BrawsbGxskJCRgxIgRCAgIIOtHfHw8HB0d+dqeaU5JSQmWLVsGZ2dn2NraYv/+/TA2NkafPn0wY8YMuLu7IyQkhLy/ZcsWTJ06lWnD/zJ8K77OnDkTkydPBsBtnPDqZLW1tSgqKoKHhwdsbGwYzyTQ26l54om8vDzMnz8f+vr60NbWxrJlyyAkJIQxY8b85lq2fSoqKrB9+3aYm5vDwcEB9vb2KC0tpbXviBEjoK6uzjPuFDMpsti6dSsoisLSpUvJVYrdu3fDwMAAS5Ysob07cuRIBAQEoL6+ntmY/ITdDpWVlfD398e+fftQUlKCS5cuwdjYGBoaGkSAzczMxJkzZxAfH0/zRmRgwV4fZs6cid69e5NytgfxxYsX0aVLF+Tk5DDj9xeUlpZCVVUViYmJPJ9zXgtloBMREQEpKSns3LkTa9euhbW1NWxtbUkc++LiYoSFhUFVVZUk+eD3ufDcuXNQU1PD0qVLybX3P7MN8/PzERERATExMSZm+N+grq6O67aEq6srRowYwff9EADtwI4Nu/+xD5H37NkDGxsbEprq8OHD8PX1RWBgILNH+RN49bGMjAxMmzYNEhISjHD4k78yFtl9jR0b19XVFQ4ODoxt0wx2WyYlJUFFRQWampoQEhLCokWL8Pz5c/LegAEDoKCggJMnTzICLA/mz5+Pzp07IyUlBdnZ2di3bx+0tLQgIiICExMTnnYh0xeb+t+XL1+wevVqmJqaIjw8HAArnMPEiRNBURSkpaVp8eqZHBT/ffhSfD1+/DiOHj1KJjW2oNWSsVJdXY1169ahf//+MDc3Z7I1NmPx4sWwtraGiYkJYmJiyFWdmpoaVFZWIjQ0FMOHDwdFUTAzM2MMaw7YbVFeXo6tW7fC2NgY8vLypG+xT/CuX7+O7t274/Hjx61W17YK54KwefNmIsDW1NTg27dvCA8Ph56eHoYMGYLo6GhMmDABIiIiePbsWSvWum1y48YNWFhYYPDgwXj16hUpv3//PoyMjKCurs4IXjz4VfgaiqKwefNmWnlqair09fWZjLV/wocPHyAmJoa4uDgALMGGPWdmZ2dj//79tARmDCySkpKgra1NbpqcO3cOnTp1gr6+PszNzck6UlhYiC1btjC2zE/q6+sxZcoUWFhYYPny5SSxSUs2y/Xr1+Hg4ABtbW3G+/8v0rwty8rKkJaWBicnJxgYGBD7mp/tRLYHIRu23TJr1izSzxoaGrBy5Uro6uri0aNH+PbtGwYOHIh169aR7/h9XPPqQy2t1dnZ2YiIiICjoyMT9/onnAfriYmJXPk8OKmurkZsbCzs7e1hYmLChENrgbS0NIiLi2Pz5s2oqanBxo0b0blzZ0yfPp12eGdnZwd1dXWSZIuBzty5c9GxY0cSB7eoqAhnz55l9nV/AntO/Pr1K9asWQNNTU0iwALA2bNn8fLlSwD0scvP6/H/Ar4TX01NTeHt7U2Mkj179sDKyorEs2jJWDlz5gzWrl3LZGsEfUDu3LkTkpKSiImJgaenJ0xNTTF16lQu4/HDhw+0axTMQG6C3RYVFRXYsWMH5OXl4enpSWvn+/fvQ1FREZmZma1VzTYNZ39iC7CLFy9GY2MjSktLcejQIdjZ2cHCwgLu7u6MiN0CZ86cga6uLsTExEhSQfbNgPv378Pc3BwyMjLMtdCfNBeiT506he3bt+Ps2bN4+/YtAGDJkiXo0KEDVqxYgdevXyMvLw/u7u7o168fszH5BewxHRwcDAUFBVy5coX2fNasWRg8eDCTXIsH6enpJKHRmTNnICUlhZiYGJw5cwYyMjKwtrZGRkYG7Rt+F2o4Y4IHBQXBzs4OK1asIJvflmwWzrHOwC22sNutpf6VmZmJoKAg+Pn5MfY1gBUrVqB9+/ZERJg3bx6kpaXh6ekJKysrSEpKkhBUeXl5UFBQgLKyMnr06EETr/kddr+7dOkS5s+fj+DgYHz48OGX3+Tl5fFMpsyP3Lp1C2ZmZkhKSsKcOXPQsWPHX8bA/fr1Kw4fPkyLXc/P45gXJSUl8Pb2xqJFiwAAb9++Ra9evWBvb4+uXbti4sSJNAG2+T6agc68efMgKCiIPXv20MoZu/rXsOfGkpISrFmzBjo6OggKCuL5DsP/Br4SX8+ePQsNDQ1yRae0tBQHDx6ElZUVBgwYQNys/2wTwu+bFDYZGRmYPn06Tpw4QcrWrl0LKysrTJkypcWFmlmQueG88r19+3bo6urC1dUVDx8+RHp6Otzc3GBubs4sKr+gJQGWfdUbYHkSc/7MQKeqqgrJyclQUVGBnZ0d1/M7d+7A3t6eK04VPxISEoLQ0FDieTl79mxISkpCTU0NWlpaUFZWxr179wCwslOLiopCUVERvXr1goWFBeMZwkFjY2OLWVQfPnyIUaNGQVZWFps2bUJMTAymTZsGMTEx5hAFwLNnz8ghwKpVq8jY/Pr1KyorK9G3b18SdqW+vh7m5uZQUlIiiSgYI5sFux0ePnyINWvWQFFREd26dcOaNWt4hiBg2u3XbNiwAZMmTcLMmTNJtuSW5rr379+T9uR3+/DevXsYPHgwlJSUcO/ePYSHhxMP9tevX2PMmDHo0KEDLl26BIAVO3LXrl3Ys2cPI3o148yZMxASEkK/fv2goqICOTk5nDt3rsUDAoYmnjx5gtGjR0NRURHi4uLkJtSv9r+cz5h9Mjfl5eVITEzEmzdv8OXLF+jr62PChAkAgDVr1kBERATjx49nwtf8DSIiItCxY0ccOHCgtavyj6K5AKuvr4+ZM2e2bqX4CL4SX0+ePIkOHTrg9evXCAwMhLe3N2pqanDkyBHY2trC1dX1Lwuw/M758+fRq1cvyMvLIzk5mfaMLcBOmzaN8Qj5G3B6wMbExEBeXh7CwsLw8fHBtGnTmHAXfwFeAuzy5ctp8WsYWHBeP6mqqiJJBauqqnD27FloamqiX79+XN8x4jWL8ePHw8zMDEuXLsWFCxdgY2ODO3fuoLy8HJmZmfD19UWXLl1IjM28vDxcunQJ165dI2OYXzfJ7M0vZ1/61VqRk5ODRYsWoUePHjAyMoKzszMjvIKVlVtfXx/r1q1DUFAQKIqiJR3Lz8+HgoICOSD9+PEjvL29cfz4cUb058GZM2fQrl07LFmyBCtWrICjoyM0NDSwYsUKngIsA2+WLFkCGRkZeHp6wtDQENLS0iSG5q+uMjJty+Lx48cYNGgQpKWloaenR66BAkBBQQHGjh2Ljh074vLly1zf8rt9yBnKa9asWSRkTU1NDXx9fSEuLo6UlBSmr/0Fli9fDkFBQRgZGdHirjNrx38O287etm0bLYt8TEwMNDQ0mHBU4N2/ftXnoqKiQFEU0tLS/pfV+kfxVw6YOAXYdevWQVZWFhs2bPgd1eN7+Ep8BQAfHx9ISEiga9euZPPW0NCAhIQERoD9m4SHh0NGRgYTJ07kuqqzfv16qKqqYs2aNa1Uu7ZHS4sHr81IZWUlYmJioKqqiqioKPKcX8WaX/GrDdy2bdtAURTWrVvHGNscsNsiOTkZffr0gampKRwdHXHz5k0ATQKslpYW+vfv35pVbXNw9qPg4GDY2tpi/PjxXKFCPnz4AC8vLzg4OPC8ysjv60tubi6Cg4NRUlKCo0ePgqIoLo/q5mO2pKQENTU1TBw0DmbNmgUZGRkICwuT8cteJ4qLi+Hi4oKBAwfi6NGjcHFxgZOTE+mnzCaaRUNDAyoqKtCnTx/Mnj2b9iwgIABqampYs2bNn4Yg4Fea96OQkBBcv34dAOsAwNPTE+Li4uQgiul3f86DBw/g6+uL9u3bkxsU7H5XUFCA8ePHg6IoJtYwWIcmnGvsnTt30L17d9jY2HAJ1GwBNjU1lemHzWi+Lly5cgXJyckYM2YMevfuTeJrMvw57LF69+5dJCQkYOXKlfjw4QM5cP7jjz9ga2tLklXPnTsX8fHxfB/DnnNMfvz4kYjVwK/3v7Gxscz++CecbZibm4uioiJaOBpeN3i+fPmCQ4cO8f2+5HfxrxdfnZ2dcfXqVfLznDlzSDY3zoQybAHWzs4O7u7uZEJk+LWhHBoaCiMjIyxevJgrc21CQgIzkH/C2YZ3795FRkYG2Zw0hz0ZlpWV4fjx46QNmQ1fUxt8/vwZeXl5+P79O88EHZz/vXPnTiYIOw9OnToFYWFhLFu2DEePHsWoUaPQpUsXnDt3DgDLKzElJQVycnIYPHhw61a2jcE5r7HFLxUVFS5xZu/evVBWVv7TWHP8SFJSEkRERODq6gohISHs3bsXQMvzHDv2MAN9PTl48CAJdbF27VraZgUA4uPj0adPH6ioqMDJyYkJd8EB58YDAFxcXDB9+nQA9I2era0tevbsiaioKJKEi4EFZz+6desWLl++jH79+uH27duk/OPHj/Dy8oKEhAQRC5mx/Oc8evQIbm5ukJWVJVeR2e2Wn5+PpUuX8rXg0NDQgMzMTIiIiNCSQZWXl6N///6gKIp4bHL20zFjxoCiKFy4cOG317mtwhnHPzc3F1+/fiVrxb179+Dj44PevXvj4MGD5L2YmBgSxo+Bm8TERMjLy6Nv374wMzODrKwstm7dCgA4evQohIWFMXToULi7u0NYWJgJN8DBggULoKmpCVNTUxKaAfhzByR+ng+bM2/ePOjq6kJKSgqhoaEkfA3w6xBKjG7zv+dfLb5+/PiRZD1ns3XrVty4cQOenp6Qk5MjV6EAVgc8cuQItLS0MGfOnNaocpuD02DZu3cvZs2ahfDwcCQkJJDyOXPmwMTEBIsXL+ba+AHMQOac2ObNmwcdHR1oamqiR48e8PX15XnSyUyG3LDbJCkpCfr6+lBTU4OBgQFmz56N169fc73PiAst8/r1a9jY2CA6OhoAy5OmZ8+eUFFRQYcOHZCSkgKAZZCfO3eOifHKA84xGRkZiW7duiEsLIwW4iIjIwM9e/Zksie3wLx580BRFPr27UviQgKMMPMrONtm8uTJ0NXVxbt37xAcHAxTU1MsW7YMpaWltG8qKiqQn59P5kRmg9IEOxljXl4eRo4cCVtbW9I+7DE+d+5cyMnJYcCAAUSoZaATFhaGLl26QFdXFxRFYd++fbTnnz59gre3NyiKQk5OTivV8p8HOwSBoqIilwDLht/HM9vx48WLF2T9LSsrg4uLC5SUlMg+j7PdAgMD8eLFi99f2TZGVFQUzZaJioqCsrIytLW14eHhQfYn7FBK5ubmiIiIwIABA9C9e3fGzm6Bhw8folu3buRQuby8HBRFYdWqVeSdXbt2YdSoUfDx8cHTp09bq6ptAs5+dODAAcjIyCAuLg5RUVHQ1NRE7969yXN+n+94wZk3AWCJ+4qKikhKSsLixYthZWWFoUOHIj09nfYNQ+vwrxZfOVm9ejVOnz5Nfi4qKsLAgQO5BNiGhgZcvHiREbuaERoaCllZWQwdOhT9+vVDu3btiIcIwEo2Y2FhgZCQEMYzpAXWrl0LKSkpZGRkoL6+HkuWLAFFUbSs08xk+GsuXrwIYWFhbNiwAWVlZYiIiEDnzp1phwEMf05ubi7CwsLw/ft3FBQUQFNTEwEBASgoKICDgwPExMRo8yUDbzjXiTlz5sDIyAgTJkxAVlYWHjx4ABcXF1hZWTEblGaw2+2PP/7AnDlzoKSkhClTpuD58+fkHSa5ETec7fD8+XNYWFiQxDuNjY2YMWMGTE1NsXLlShKjdPr06Xjz5g35jumL9LiQdnZ2WL9+PQBWdmkpKSn4+fnRDu3nzJmDmJgYvo/FxwlnX0xPT4exsTGuXLmCGzduwN/fH6KiolyehQUFBYiMjGQ2z3+TR48eYfDgwejRowcTZoADzsOkDx8+gKIozJw5kxyQlJeXo2/fvlBWVuYpwPI7Dx8+hIyMDBwcHAAA586dg5ycHI4dO0Zyd6iqqpLDvEePHiE4OBhWVlYYNGgQc4viJ7du3eJyPEpJSYGLiwsA1lqtrKyMiRMnkufsPlpfX8/3egPnmDx58iR2796NQ4cOAWCN7WvXrkFFRYURYP8iV69exYwZM7Br1y5SdvbsWfTp0wdDhgxp8dYtw+/jXyu+ck5m1dXV8Pb2RpcuXWiCQnFxMQYOHAh5eXmaAMvrd/AzV65cgZycHG7cuAGA1Z7Hjx9Hly5dEBYWRt6bOHEixo8fzxg3LTB27Fjs3LkTAHD8+HGIi4sjJiYGAP3KDwM39fX1aGhowJQpUzBjxgwArNADPXv2xNSpU8l7lZWVrVXFfxzsq/CzZ8/G4MGDyZX5wMBACAsLQ0ZGBmVlZcx4/hM414nQ0FCIiYlBUlISgwYNgp+fH7NB+QskJCSge/fumDx5Ms0biUmqxZtdu3Zh4MCB8PPzQ319PU0onDlzJszMzODp6QknJydISUkxGxUenDt3Dv7+/vD19aVdWb5w4QIkJSVhaWkJf39/jBo1CkJCQoz3fwts2LABISEhCA4OJmUNDQ0YM2YMunbt2uLVbn7vky2tBy2tt48fP0bv3r2ZEEAcsNuK7Z25e/dudOjQAXPnziUesGwBVk1NDffv32+1urZFamtrkZaWBn19fTg4OGDnzp00webhw4cwMzODqqoqaeOysjJUVFSQtufncdzY2Ih79+6BoigsXbqUdotx/fr1sLS0RGlpKZSVlREYGEjG/KlTpzB79mxUVFS0VtXbBE5OTjSP3+zsbEhKSqJdu3Y4cOAAKa+vr8e1a9egqqoKOzu71qhqmyUgIICEAmlsbMT9+/ehpqYGUVFRruRZZ8+eRd++feHp6YmLFy+2Qm0Z2PxrxVc2KSkpKCsrw8ePHzF16lSIiYnh1KlT5PmXL18wePBgUBRFiwHL0MTRo0ehqanJleV8z549kJCQwJ07d0gZe0FmBBs6VVVV0NDQwP79+3HlyhWIiIhg+/btAFjGy4IFCxhPw59w9h3OIOEAMHz4cBw8eBDFxcVQUFBAYGAgef/06dNIS0tj+t5P2Ebxr0S/+vp6uLi4YO7cuaQsKCgIx44dY67X/uSvJMrjFGDnz59PrkwxG5Qm2G1x7949HDhwAFu3bqVdhU9ISCAesOnp6Vi8eDEoikJJSQkzpjkoLS1FUFAQunXrRjyWANDW5zVr1mDcuHHw9fUlcyhzmEzn4MGD6NSpEyQlJbliMn/48AEBAQHw8vKCl5cXEzbkF/j6+pLQIZy3nhoaGjB27FhISkrizJkzrVjDtgfn2nHy5Ens2rULq1ev/tNbY69evWIO8Zpx6dIl9OvXj3j6HzhwABRF0QTYiooKmJiYwMDAgGsfw69weg2npqbC1NQU7dq1IzFJAdaa/fDhQ1hYWEBdXZ0rnA0/90VOmyQ6Ohrt2rWjhfx58+YN9PT00KlTJwQGBtK+CQ4OxoABA3iG6eMXSkpKEBYWRhuP379/x6FDh6Cqqgo3Nzfa+w0NDbh+/Tq6dOmCyZMn/+7qtkk+ffqEP/74g2ufHB8fDw0NDTg5OXHZLikpKdDX10d4ePjvrCpDM/7V4uvDhw9haGhI3Ndzc3MxefJkLgG2qKgIYWFhzOYE9MWULRikp6ejc+fOJJMym6ysLMjJyZFrj2z4faPckkESHh6Ovn37QlhYmHjAAqz+5+7ujs2bN/+uKrZ5OBPenT9/HocPHwbA2uiZmpqiZ8+emDZtGumjVVVV8PHx4fsEFGx27NiBXr16EU/gXxnJM2fOhLi4OHbv3o1JkyZBTk6O8fL6CWe7PX/+HA8ePKAd0nGuGZz/vWHDBvItv8+HQFMbHD9+HJKSkujTpw9kZWXRr18/7Nmzh7Td0aNHoa2tDT09PSgpKdESBPArvMZubm4u5s6di06dOmHFihWknNMDlhNmTmTBORYrKiqQmJgIERER2maO3Vbsd1tqU36kpblszpw5aN++PeLj42m3TxobGzFo0CA4Ozv/rir+owgNDYWysjKcnJxgYWEBeXl5XLx4kWvMN293fhW9oqOjSZgudpssXrwYo0ePppVxCrDsQ+SKigq8ffu2FWrd9mjen6qrq5GcnAwDAwMYGxtz9a9Hjx5BWVkZI0aM+J3VbLOw2+fTp0+4d+8eioqKcPDgQVAUheXLl+P79++orKxEZGQkevXqRZwbcnJyMG/ePEhISDDJtThYtWoVuQpfVlaGI0eOQEFBgau/1dfX49GjR4xWw4Pdu3dj2bJl5Oc9e/bA2NgYAQEBXH3t1q1bTBu2Mv8q8ZWXwTJs2DBanJCXL19i8uTJEBcX5+lpyM8dkrP99u3bhz179qCkpARFRUVwc3ODt7c37drO58+foaOjg9TU1NaobpuEsw2zsrJo4SySk5PRrVs3ODo6Ijs7GwArKZy7uzusra35uu9xUlpaCi0tLQQGBuLMmTOgKAonT54EwEoUpa+vD0VFRfJ+Y2MjIiIi0KNHD7x8+bK1qt2myMzMRK9evWBlZfWnAmxubi5Gjx4NNTU1WFpa4sGDB7+zqm0Wzg1KREQEjI2NISMjAycnJ/j7+/P8pvkYZsZ0E1evXoWcnBy51piVlQVBQUFYWFggJiaGtNXTp0+RkZGB9+/ft2Z12wScYzY7Oxt37twh2aVLSkoQGhoKDQ0NrFu3jrzXXGhlxP+mNqioqKC1T1VVFfGAnT17Nimvr69nbvE0g7MvfvjwAW/fvqV5ak6YMAFdunTBwYMHaWGUmicCYWARHx9PyzmRmpoKiqJw9uxZ8g7T95qoq6uDtbU15OTkaPuQOXPmYOzYsQBYfZRTgO3QoQOCgoKYWzwccI7F5cuXE8eGmpoapKWlQUtLC/b29ly2y6tXrxh7Bk3t9+zZM/Tu3RvOzs4YOnQoAGDjxo2gKArLli1DQ0MDioqKEBkZCWVlZXTt2hX6+vrQ1tZmbGwOKioq4O7uDiEhIXKLtqysDIcPH0aPHj3g7e3N8zumLzZRWlqKkSNHwszMDBs3biTlO3fuhImJCU8BFmDasDX5V4mvbM6dO0eC0v/48QOKiooICgoiz3NzczF16lRQFMUEHuZBSEgIunXrhp07d5IM1MeOHYO9vT2cnJwQFxeHtLQ0uLi4wNTUlBnAPGBnR5aTk4O+vj6JXXjo0CFoa2tDS0sLhoaGMDc3h5mZGXM1lIMfP37g6NGjkJCQgJCQEI4ePQqAZXzX1NTgyJEjkJeXh76+PoYOHYohQ4ZASkqKMWg4aGxsxNOnT2FgYABzc3MSW+pXm+CPHz/SYlYxsFi5ciWkpKRw7do1fP36FdOmTQNFUbh16xZ5h9kk/5q6ujqsXLkSs2bNAsA6RFFVVYWvry9cXV2hqqqKXbt2MfMfB5x9KjIyEpqamlBRUYGKigpCQ0Px+fNnFBQUICwsDFpaWlzxvRhYsNsxLS0N7u7ucHR0xMCBA8lcV19fTwRYzrilDE1w9sWoqCiYmZlBWFgYrq6uWLhwIXk2fvx4CAsLIyEhgSv+OiPA0lm2bBnmzJkDADh8+DC6du1KQlFxitrM2tJEZWUlBgwYAEVFRWRmZgJgJRQcP348gKbcAGx27doFcXFxcmDF73C2zYsXL+Du7g6KopCSkgKAJcCmpqZCT08PDg4OPMcsP6/R7LGYlZUFcXFxREREID8/n3bte9OmTSQGbGNjI2pqavD582ccOnQImZmZtPjiDCwKCwvh6+sLERER4tnO9oBVUVGBk5NTK9ew7fPmzRtMnjwZVlZWtMP4uLg4mJubw8vLC3l5ea1YQwZO/nXia3JyMiiKgp6eHvGw2bdvH+zs7Gieri9fvsSaNWuY63jN2Lt3L7p160YmQE5Onz6NCRMmoHPnzjA1NYWzszMjGv6E8+8/e/Ys1NTUkJycjMuXL8PZ2Rny8vJE6H/w4AESEhKwZMkSHDt2jHzL9MUmHjx4AIqiICwsjGnTptGe1dXV4e3bt5gxYwYCAwOxdOlSxuP1J5xeRo8fP8b+/ftBURRcXFz+UggCBjoVFRXw9PQkAe1TUlIgKipKwoYwifL+Os+fP8ezZ89QXl4OW1tbsmF++/YtxMXFoaurS0v2wcBi7dq1tPA+Pj4+kJaWJmv027dvER4eDnFxceLFxEDn5MmTEBUVRVhYGOLj42FgYAAzMzNyKFpfX4+EhARQFIWIiIhWrm3bZenSpZCUlERiYiKOHDmCOXPmQFVVlbZGT5o0CRRF4fz5861Y07YFrzXXx8cH48ePx9WrVyEqKopt27aRZ8uXL6eJ2gxNVFVVwcXFBfLy8njx4gWmTZtGrnV/+/aNhAl58+YNADAHyjwIDw+HpaUlhgwZAhkZGQgKCuLEiRMAmgRYAwMD6OjoMOJ/M75+/QpbW1tMnz6dVs65f2MLsJwxYBl+TWFhIUaOHMklwO7ZswdDhw5l9i2/gD1G3759i8DAQC4BNjo6GuPGjWPasA3xjxdf2Z2J/W9BQQH69++P/v37Q1xcHCEhIYiOjsaAAQMQHh7OMxs6I3o1ERQUBB8fH1pZ8/b58OEDCgsLmWQyAMkQzyY+Ph6bN2+mTXwA4O7uDjk5uRY9rfldvGbDHsdfvnzB7du3ceTIEcjJySEgIIC8w8/97a+SmJgIeXl5TJ8+HXZ2dhATE4OlpSUjwP5NqqqqYGRkhAsXLuDs2bO0RHm1tbXYunUrzp0718q1bHtwbtjYcxu77Pr169DX1yfXoO7du4d+/frBz88P+fn5v7+ybZSGhgbU1tZi0KBB2LJlCwDgzJkz6Nq1K2JiYgA0xSPNy8vDtm3bmHWEBy9fvoShoSGio6MBsOwXZWVliIuLo2fPnjQB9tixY3j+/HlrVrfNUlJSgr59+9Li1X/9+hXbt2+Huro6du/eTcpXrVrFrNM8YIebAlgZz/X19dGhQwcyngGWTTlw4EDGC5sD9trBTlBUU1MDJycnKCkpQU9PD8LCwjA0NIS0tDTU1NSgq6sLLS0tfP/+nREPm3HgwAEICwvj9u3bKC8vR3Z2NgIDA9G+fXskJSUBYLVvUlISRo8ezawpzXj27BnU1NRw9epVLjuaM+xFdHQ02rdvj8jISOYAAH9tz8EWYLt27UoEWE7Nht/3Lb/6+5sLsNbW1rTbUOzn/N6GbYV/vPjKhu351tDQgDVr1mDatGnIzMzErFmzEBAQADk5OXTu3BnJycmtXNO2CXtgenp6EvGVc9GtqanB+fPnUVJSQvuOnweyjY0N4uLiyM+VlZVQV1cHRVGYMWMG1/vu7u7o3r07Ll68+Dur+Y+A3f/YGWvZHtVfv37Fnj17ICcnh0mTJpH3d+3ahSNHjtC+ZWDx4cMHKCkpYc2aNQBYyRQuX74MDQ0NRoD9Bbza48ePH3B3d8eAAQMgISFB8056+/Yt3N3dsX///t9ZzTYPezxeuHABs2bNgrOzM2JjY0nW1UuXLkFNTQ2nTp1CQ0MDFi5ciAkTJpCxz8Cirq4OdXV1MDIyQnZ2Nq5duwYREREi1FRXV2PLli0kThobZrNM58GDB1iwYAHq6upQUFCAXr16ITAwEB8/foSWlhYsLCxoMSQZeFNeXg5VVVUsWLCAVl5SUgIXFxdazFw2/C7Acq4p6enpoCiKeBh++PABXl5e0NXVxbZt21BeXo6HDx/C3d0dJiYmXInf+BX235+amorx48cTj+qKigqMHDkSFEVh1apVSE9Px9mzZ3Hu3DlcvHgRr1+/bs1qtwn++OMPLoejpUuXol+/frSywsJC+Pj4oEOHDiSHR01NDWl7Zk1p4uDBgxAUFPylmFVRUYHPnz+TsBdMzOEmLl26xKUjcMIOQUBRFJ49e/Yba/bPIS0tjWc5pwA7efJkqKmp0W5D8fta0pb4V4ivly5dAkVRCA8Px/v371FXVwczMzOEhoYCYHnWjBkzBhRFkcDYDLxZs2YNOnXqhJycHFr5x48f4efnhytXrrROxdog8fHxqK6uBgDyb2FhIfr16wdVVVXiQcM54VlYWGDQoEG/v7JtGM6YfAMHDkTfvn0xbNgwfPr0CQDL24EtwPbv3x8zZ84ERVF48eJFa1a7zZKTk4Nu3brh9u3bpKyurg4XLlyAsLAwBgwYQGLAMrDgNKCfP3+O9+/fk7h7KSkpEBQURL9+/UjZ169f4e7uDjs7O2ZjwoOkpCSIiopi8uTJmD9/PhQVFeHu7o6CggIUFhbC1tYW6urq0NHRgYSEBBOvGSAxDAGW18zly5cBAIMHD4aWlhZERESwd+9e8s7nz5/h4OCA2NjY317Xfxpsj8Px48djxIgRqKqqQkNDAwYNGgSKoqCvr0/WcIamNZnTdqmoqICfnx+8vb25PNSnTJmCQYMGMQd6HHC23ebNm0kyHikpKbIhfvXqFfz9/aGiogJRUVEYGxvD0dGRCefVjBMnTkBISAgrV66kHZSUl5fDw8MDPXv2ZLLHN+PRo0ewtrbmOgDZvHkzJCUlUVxcDKCpnyYlJYGiKAgKChIBlhFruLl58yaEhISQmJjY4jsbN26Es7MzAJatyMDi+vXrUFBQIAcjLa0Xnz59wsKFC/n+8I4Xr1+/BkVRJBdKc9hj9vXr11i1ahWzhrRR/hXi6/fv33H8+HGoqanB3d0dcXFxePv2LaysrHDq1Cny3sGDB5mO2AKc13rY8ZTu3r1Lknq4ubnB0tKSaT+AZKdls2TJEsyfP59ciSouLoapqSn09PTw6tUrAHQjhtmgcHPy5EmIiIhg3rx52Lx5M+zt7aGmpkY82n/8+IGUlBT07dsXrq6uXP8PGJqoqamBiooK5s+fTysvKyuDmZkZKIpCnz59Wql2bZuIiAgoKipCXV0dDg4OJG5cfHw8OnToAHt7e1haWsLW1haGhobMJpkH79+/h6GhIQnP0NjYSOJtsue+jx8/IjY2Fps2bWLiNYMl+Kurq2PmzJmYPXs2BAUFiWB45coVGBkZwdjYGACrPb99+wY3NzfY2toyfY8DTjvm+/fvtMRFVVVVcHR0xNq1a0lZUFAQrl+/jvfv3//2urZVOO2TDx8+4OPHj2SeO3/+PMTExBASEkLGbXl5Oezs7EjyKAY6UVFRkJGRwaFDhxAdHQ1vb2907NgRhw4dAsDKVJ2fn49Tp07hyZMnpP0Z4YHFmzdvoK2tjc2bN9PK2e1UWVkJd3d3dOrUibELf8LuO+w2OnnyJLn6/uTJE1haWmLmzJn48OED+ebevXsIDAzE9OnToaysTGwfBjoFBQWQlZXFoEGD8PbtW1LOuccLDg5GaGgoLQwBAwtjY2P4+fn95feZeZBOQ0MDxo4di2nTpqGuro6nntC8zzE2YtvjXyG+ssnJyUFUVBS0tLRgbGyMYcOGYerUqUQUY8MM5l/z7NkzeHt7Q0hICMrKytDV1YWFhQUxwPlZPAwODoahoSFJfgKwrvGwrz5xCrAmJibQ19dHbm4u1+/h5zZszosXL2BsbEziGr579w49evSAhIQEZGVluTxcm8fZ5Wc4F1lOb6WwsDDY2NiQRFEAq89NmDABp06dYgzrn3COw3PnzqFbt25ITk5GTEwMXFxcICMjQ9rq9u3bWL16NcLDw7Fnzx6yjvDretI83jqbgoICGBsbo6KiAi9fvoSioiItZvOtW7f4ts1aorS0FFu3boWkpCRERUVp1+0qKyuxY8cOaGpqQkVFBX369IGlpSWMjY0Z8Z8D9vx36tQp9OnTByoqKhgwYADWr19P3nFwcICpqSlSU1MRFBQEOTk5vHv3rrWq3ObgXE8WLFgAPT09KCsrQ11dnXjanDp1CvLy8rC2toajoyNsbGygq6vLjGkeFBUVQU9Pj+adXl1djaCgIHTq1AnHjh3j+R1jHzZx79499OjRAw8fPiRlzcWF6upqeHp6Mgd5YCVyO3r0KFkb8vPzQVEURo4cSRKErlq1ClZWVhgzZgzu3buHZ8+eYcCAARg7dixu3LgBOTm5Fq82MwDHjx9Hp06d4OfnR1urKyoqMG/ePCgrK3PdHuU3ms9h7Jslhw4dgq2tLc+boQx0WloH4uLiIC4uTm6gMG34z+MfJb7+qoOxn7E3fAMGDICgoCAoimKuyv+kpYHcUrueO3cOx44dw+nTp8nmjt8N7NevX8PExATOzs64cOECKd+wYQMoisKKFStoAqy5uTlkZWVRUFDQSjVuO7TU/zIzMzFnzhzU19fj/fv36NWrFyZOnIjs7GxoaGhAU1OTlqiCgQV73F66dAmhoaEYOnQo9u/fj3fv3qGoqAheXl6wtLRESEgI0tLSEBQUBCUlJaYv8iAuLg5btmwhBwAA61DAyckJ0tLS5JpU8/mPX0Uv9lh+8+YNYmNjaWEDHj16BDk5OVy9ehVqamqYOHEief/x48cYOXIkE2aAA/Y4PnHiBMTFxaGmpsYVP7O6uhqvXr3C/PnzsWjRIsTGxjJrMg9SUlLQqVMnrFixAhs2bEBwcDCEhYVJe75+/RpGRkZQVVWFlpYW0w9bYOnSpeR6/NmzZzFx4kRISEiQBB4ZGRnYsmULJk+ejBUrVvD9QVRLFBQUQFJSkgjXbE+40tJSWFhYQEpKiiQ5YgRXOux58cqVK1BQUCBerZxrbnp6OpPwkoOGhgYMHToU0tLSOHPmDEnIePXqVUhKSmLkyJGkn23atAlOTk6gKArq6uowNDREY2Mjvnz5Ag0NDZqDCQOdhoYGxMTEQFBQEJqamhg3bhwJvSIrK8usKxzcvHmT9nNeXh4UFRWxevXqVqrRP4/MzEzk5eXRyvr06YOJEyeSQxaGfxb/GPGVs+MlJibi48ePf/rN9u3bMWHCBMYgBN2wu3//PlJTU5GdnU3i0fwVw49fhQY27L8/Pz8fxsbG6NevH83wW7duHZcAW1hYiHHjxvF927H7V0FBAQ4ePIidO3fSPI7YHgvjx4/H8OHDidE4ZMgQUBSFXr16kTKGJtix0Ly9veHu7g5FRUUMHDgQDx48QHFxMRYtWgQNDQ2oqqpCR0eHMQrBSpTHGa8rPz8fBgYGZOwCTRu/Fy9ewMXFBXJycjw92PkR9lh+8uQJNDQ0MHToUKSkpNDe8fHxAUVRGDFiBK183rx5MDc3/0vr97+d5mvuhw8fkJ2djS1btkBPTw/Tpk3709/B7+sKJ7W1tRg9ejRmzpxJyioqKrBv3z4ICwtj69atpPz169e/TPrBb3B6sX/79g02NjbYtGkT7Z2oqCgICwtzbabZ8Htf5HULBWDFbHZwcCD9rbGxEY2NjRg9ejQMDAyY6/Ic8HIE+fHjB5SUlDBs2DCuZ3PmzMGMGTOIRyc/o6enh8DAQADAsGHDIC4ujtOnTxO7OT09HV27doW3tzcZq7W1tbh16xaePn1K5oDg4GDo6OiQnAsMLXPnzh0MGzYMxsbGsLW1xdy5cxnvaw4uXrwIaWlpWFpa4sCBAyS8z7Zt26Cjo8M41fwFLl++DGlpaRgYGGD9+vXEESQ2NhbW1tZ/S8NhaDv8I8TXW7duwczMDElJSZgzZw46duz4yxhdvIxAfhZgOQ2auXPnQlNTE8rKyrC1tYWLiwuTFfRvwO5Hb9++hZGREfr160eyrwJNAuyqVau4Nnf8ujlhLwpZWVkwMjKCr68vwsLCuN4rLy+Hra0toqOjSdnkyZNx9uxZRqzhQUFBAQwMDGjemufPn4eHhweGDBlC2qy+vh4FBQUoLS1traq2Gaqrq7Fjxw5acp36+npcunQJ9vb2UFFR4Rq3OTk5MDY2xoABA353ddssz58/h4SEBMLDw2lx49hcu3YNffr0gYaGBi5cuIDExETMnj0boqKijNAAuqGckZGB+/fvE4/04uJirFu3Dnp6epgxYwZ5LzQ0FOnp6QCYa2a8qK2thZmZGSZOnEgrLy8vx5QpU0iiLQY6nH2JPfepqqqS5G6cc6WzszO8vLwA8K89wwvO8VxfX0/LMH/8+HHY2NhgwoQJpLy2thZDhw7FlStX4O7uDldXV1RXV/P1uGb/7enp6Vi4cCGmTZtGwiZduXIFkpKSGDJkCNLT03H9+nUEBweja9euTEZ0AAsXLoSOjg6tbMyYMZCQkOApwI4aNQplZWW0969evYpJkyZBQkKCFuKB4dcwolcTzeevoqIi5ObmYtSoUbC3t4eCggJiY2OxY8cOuLi44PTp0wCYtYQTXmvAlStXsHXrVsjJycHR0RFBQUHIzs6GmJgYVq1a1Qq1ZPj/8o8QX588eYLRo0dDUVER4uLiJInRrwYsPxsxLbF582bIysri+vXrAFinxp07d2au7fwJLS2ueXl5PAVYdgiC/fv3/64qtlnY4zArKwsSEhIIDQ1FUVEReX769GmyAAOAm5sbtLS0cPnyZUyfPh1KSkpcmZUZWHz8+BE9evTAiRMnaOXnzp2DnJwcuc7IwKJ57O8lS5aQeJD19fVIT0+Hubk5DAwMuATYd+/eMUb2TyorKzFs2DAuz8za2lq8e/eOHOY9ffoUw4cPh5iYGPT19eHk5ITHjx+3RpXbLHPnzoWEhAR69OgBWVlZXL58GQBLBFu/fj20tbXRt29fuLm5QVFRkdmk/Anz589Hnz59uASZRYsWwcjIiCYkMtDt5ICAACLgeHh4wNLSksx5bPFmwoQJGD169O+vaBuGc11Yv349hgwZAjMzM6xcuRK1tbVoaGjA1q1bYWFhARUVFYwbNw5GRkYwMDBAQ0MDpk+fDicnp1b8C9oOx48fh4SEBLy8vDB9+nRQFIVZs2bh27dvuHfvHnEc6dmzJ4yNjRmR8CfLly8nCZEXLVpEvNa9vLy4BNjr169DUlISbm5uqKioIL/j4cOHmDVrFuON+DdpyeOd3+CcB2tqamh9CwBevXqFFStWwNzcHI6OjqAoCjY2NnztGNcczjYsKyvj2rO8fv0a+/fvh5GRESwsLCAhIQFjY2PGS/0fyD9CfAVYi4ugoCCMjIxoV0aZDfGf09jYiPr6eowePRpr1qwBAJw5cwYiIiIkEUBlZSXJhsnQBOdieujQISxduhTHjx8ngiA7hlxzAfbw4cPMovKTr1+/wt7eHtOnT6e158qVK0FRFPr27YuTJ08CYMWEtLKygpKSEnNNngecSbVev34NNTU17N69GwBosX969+5NS3LE70ydOhUaGho0b+Dw8HBQFIUdO3aQsmvXrsHKygqGhoZchg/ArDcAq5/Z2trSsk+npaVh1qxZ6Nq1K3r06AFXV1fyLDc3F+Xl5bTM8/wK5/x3584dqKqq4vr167h69SoCAwPRsWNHcphSWlqKo0ePYuTIkRg3bhyTXOsndXV1pB1LSkpoByWXL1+GtrY2goODaQLs1KlTMXjwYJpHIkMTubm58PDwIHEer127BiMjIwwfPpz2nr29Pc0bm6GJefPmoVu3bpg/fz5iYmLQrl07TJ8+HUVFRWhsbERmZiZCQkLg4+ODmTNnEjHM398fY8aMQU1NDV+LN7m5uVBVVcX27dsBsDzWO3fujNDQUPJOZWUlsrKy8Pz5c3z58qW1qtqmaGxsxIkTJ2BnZwdTU1MICQnRwvQNGzaMS4C9ePEiXFxcuOwZJrQXw38CZz9as2YNvLy8oKWlhe3bt3MdhObk5ODy5ctwdXVF9+7dib3Dz3MfwN2Gjo6OMDc3h5+fH0+b78CBA5g1axYoiiL7Z4Z/Dm1WfG2eSfnKlStITk7GmDFj0Lt3b8ar8D/Aw8MDp06dQkpKCkRERIiRU1dXh927dyMxMZERFzjgXAzCwsIgLS0NfX19qKurw8vLC0+ePAHAEmCNjY1p1yjYMAIskJ2dDTU1NVy+fJn0r+3bt6NDhw7YunUrnJ2d4ebmhuTkZACsMZ+Tk0Ni2TDQRVdOpk2bhq5du9I8QBoaGuDk5ITly5f/ziq2aV69egV1dXXY29sTAbayshLLli0DRVFkLmQLsL1794a8vDzX1TwG4Pv379DS0kJAQACeP3+O5cuXQ1NTE15eXti0aRPi4uJoSaP4XSzkxfr167FmzRosXryYlFVXV2PGjBno2LFji17r/LyeHDx4kGafJCUlQVdXFxoaGjAxMUFCQgIA4NixY9DR0YGNjQ2GDRsGb29viIqKMl7XLbBnzx5YWVnRPOGqq6tx4MAB6OvrQ1lZGUOGDIG5uTm0tbX5ug+2xIkTJ6Cmpobbt28DYCWZad++Pdq3bw9vb2+eoVl+/PiBOXPmQFJSkvE2BOuGY+/evQGwbGpFRUUSwxRg3Z5iaBkbGxt06tQJw4cP5woxNWzYMEhJSeHMmTNc3v/Mno/hP6V535k3bx5kZGSwevVqLF68mHj6379/n+vbmpoaODk5wd/f/3dVt83Cua9jH+KtW7cOJ06cQNeuXTFkyBDi8NW8zWfPng07OzvGueEfRpsUXznjcuXm5uLr16/E6+PevXvw8fFB7969STwgAIiJiUFhYeFvr2tbpKXF1NvbGyoqKhATEyMerwDw+fNnODk50WJtMjTx5MkTjBgxApmZmQBYm0BnZ2c4OzsTATYvLw8KCgq0ZB8MLPbv34/27dvTFpj379+T+IVPnz5Fv379YGZmRtqToQl2u7FDMUydOhVLly4lz728vCAiIoLo6Gjs2bMHoaGhEBMTw4sXL1qrym2SvLw8qKmpoXfv3jQBdsmSJVwC7Pnz5xEYGMgIhy1w6dIlCAoKQllZGaKiooiJiSHhgGpra+Hi4oIxY8a0biXbKOXl5XB3dwdFURg3bhyApjFeXV2NmTNnokuXLjh8+DDtO372DPnw4QNERERgb28PgLVmdOnSBQsXLsShQ4fg7e0NdXV1LFmyBAArtuGaNWvg6uqK6dOnM8JNC1RXV2Pp0qXQ1NSEuro67VltbS1yc3MRHh6OWbNmYeHChUR45XcBlnMs1tXV4eTJkyShW3JyMsTFxXHo0CFcvXoVgoKCCAoKQk5ODvkmPz8f4eHhzNV5DtLT06GsrIwrV65ARUWFtv5mZGSgf//+TNJLHtTU1KC4uBiWlpaYPXs2bGxsMHnyZK68KN7e3qAoCjdu3GilmjL8G2GP0cTERKipqeHu3bsAWGOWoiioqalh1KhRtMNPtof1kSNHoKurSwtFx080H6OpqanQ0dEhoSFTU1MhLCwMcXFxWFtb05JUs9eghIQEWFpaMo4i/zDalPgaFRVF2+xGRUVBWVkZ2tra8PDwINfiMzMz4evrC3Nzc0RERGDAgAHo3r07c4IH7kQe2dnZ5MSkqKgIRkZGUFdXx7dv31BaWorCwkK4ubnB2tqaERp4kJCQAHt7e7i7u9OuLCYmJsLZ2RkuLi5EMPzw4QPThjy4fv06OnXqhOPHjwOgb1zY/TU2Nhbm5uZM7JoWOHHiBISEhODj44P+/ftDQUEB5ubm+Pz5MwDW6aeBgQE0NTXRu3dvZkPXAm/evEGvXr1gY2NDE2CXLl2Kdu3aISYmBgB3AhUGbt69e4fMzEwUFxfTyhsaGjB8+HBERUWRzN78DK+/v6CgAGPHjoWIiAjZrHAKsGPGjIGjo+NvrWdb5/bt21BVVYWzszOSk5MRFRVFex4VFQU1NTWa13BDQwNjF/4JpaWliI6OhrS0NMaOHUvKWxq3/D4fcrYL2yYsLCxEfn4+vnz5AisrK5IE5dOnT+jRowcoisLChQtpv+f58+dk/eYnGhoaePatL1++YMCAARAWFsaIESNoz+bNmwd7e3vGweYnv5rTVq1aBUtLS0yZMoVL3ImMjOT7gxOG/z8BAQG00FJ1dXW4ePEiCWt4+vRpiIuLIz4+HkeOHEHHjh3h5+eHW7du0X6Pv78/DAwM+FI4DA4OxrBhw2hhGVJSUrBhwwYArFBekpKS2LFjB54/f048YN+8eUP7PVFRUZCWlmbCsPzDaDPi68OHDyEjIwMHBwcATUljjh07hrVr18LKygqqqqrkOsWjR48QHBwMKysrDBo0iHjGMoY2i7CwMMjJyUFaWhpubm5E+Lp58yaUlJSgoqICDQ0NWFtbw9TUlIkn1wIrVqyAjo4OunfvznU6l5iYCFdXV5iYmNBO5Jk2pPP+/XvIyspi0KBBePv2Lc93goODMXz4cL6/OsFr/vr8+TN0dHSIYVNfX4+cnBwYGhrCwsKCvPfx40dyqMLQ8lrw5s0bqKmpcQmwy5cvB0VRXAnMGP46NTU1iIqKgoKCAl6+fNna1Wl1OPvg+/fv8ezZM7LR+PHjBwYPHgxxcXES25otSrAT9TDQycjIgKqqKiiKgq+vLwD6ejtkyBDY2Ni0VvX+cbD7248fP7Bhwwbo6+tjypQp5DkTA5IO55hkx2PmjDn8+vVr6OjokNi5hYWFCAkJQUZGBhG9+PUwqri4mPa3p6enY/369Vi3bh3Ky8sBAPHx8dDQ0IC3tzdu376NmzdvIjg4GGJiYsytqJ9wtuHevXsxa9Ys7N69mybirF69GpaWlpg6dSqXAAswnusM/zk1NTWIi4tDjx49yBoMsMZ3UVERSkpKYGtri9WrVwNgrc/q6uqQlZUlN/bYfXjgwIEkVAu/ER0dDVNTUwQGBpKbOQ0NDcjPz0dFRQUcHBzwxx9/AGA5zunr64OiKEycOJH8jm/fviEiIoLJjfIPpM2Ir7W1tUhLS4O+vj4cHBywc+dO7Nq1izx/+PAhzMzMoKqqSjxgy8rKUFFRQQYyPy8onAvy3bt3oaenh4yMDCQkJGDs2LHQ1tbG0aNHAbAmz+3bt2Pr1q04fvw42bzwc/sBLM/VFy9e4O7du7QYXHv37oW2tjZGjRrFZcjs378fs2bNYjbKf0JiYiI5/eQ0Er9//47Q0FBISEjw/dVQdh+6f/8+Fi9eTMZ0Xl4elJSUuE6Nnz17BgUFBZLZlumDTXDOh6dPn8aWLVuQkZFBxH1eAmxFRQX27t3L9/Pgf8r+/fsxY8YMyMnJMcYg6H0wKioKlpaWEBERwaBBgzB37lwArA0LOyM121ud180AhiZu374NU1NT6OjokLjgbBtmy5YtMDU1ZRJrNaO54McrQ3dpaSk2bNgAAwMDTJs27bfW758A51i8ceMGhg0bBhkZGcycOZMceObk5KBLly4IDQ1FSkoK3NzcSKgMgH9t7OjoaOjr6xMbLzk5Ge3bt4e9vT06dOgAU1NTIsLs3r0bLi4uEBQUhIGBASwsLPDo0aPWrH6bofmaIiYmBicnJ0hLS2PYsGFITU0lz9esWQMbGxuMGjWKb691M/xvqKysxOHDh9G9e3eMGjWK9ox9u4ydBKqgoADjx4/HgQMHuHL58COcY3j37t0wMTFBQEAAnj59Ssrz8/Ohrq6OCxcuAGCtzePGjcOzZ8+4nLuYA9J/Jm1CfGUPxLq6OqSmpsLU1BTt2rUjMZQAVod9+PAhLCwsoK6uzuXdxc+DufnffuPGDUyePJn8/PjxYwQEBEBLSwsHDhzg+Tv43VvzwIEDMDMzg5KSEtq1a4fOnTsjMDCQJEqIiYlB79694efnh4KCAp6/g5/74J9RX1+PmJgYCAoKQktLC+PHj8ekSZPg4eEBeXl5vhdr2H3n8ePHaNeuHYKDg8mzqqoqKCkpkXiGnOWWlpaIjIz8rXX9JxEWFoauXbtCS0sLQkJCCA8PJ7H32EainZ0d16EKv26S/1NevHgBR0dHDB06lEke04xly5ZBWloaFy5cQEFBAYYNG0bzdv38+TOGDx8OiqJocSEZeFNXV4eMjAz06NEDDg4OKC4uJvbLhAkTYG1tTRJHMdA3e5y2S0sC7MaNGyEnJ0duWjDQmT17NiwtLTF69GiYmppCTk4OkydPJtc+Dx48iM6dO0NLSws2NjbkVhm/erwCrFs5srKysLe3x6NHjzBy5Ejs3r0bjY2NKCsrg6mpKYyMjEg80rq6Ojx8+BCfPn2ieRbzM5z95/79+xg5ciQ5kL906RKcnJwwYMAApKSkkPcWLFiAgIAAZm/C8F+noqICCQkJXALs48ePoa+vj5CQEBw/fhzu7u5wcXEh/ZfftQaArhXs2rWLCLBsxyT2nm/w4ME4fvw4+vXrB2tra/Id04b/fFpdfG1ukFRXVyM5ORkGBgYwNjbmWjQePXoEZWVlrphADKwr8gMHDsTAgQPh4+NDe/bkyRMEBgZCV1cXu3fvbqUatk327NkDISEhbN++Hffv38fNmzexcOFCCAsLo0+fPnj9+jUAYPPmzbC1tcXYsWNJHF2Gv0dGRgY8PT1haGgIW1tbhIeHk0Q9/Ap7jnv06BE6d+6MiIgIrneCg4NhZ2dHvNfZuLu7k1hy/Ly548WdO3fQt29fskHZvn07NDQ0MGPGDJKM7M2bNxAREcGkSZNas6r/CgoLC5mQFxw0NjaipKQELi4uOHbsGADg/PnzEBYWJrd62MJMYWEhE4/vT2C3DTsha0ZGBlRUVKCuro7Bgwdj5syZ6Nq1K+MlxwGn/Xzw4EEMGjQId+7cIWW8BNiSkhIcOXKE2eDx4OzZs5CWliZxmgGWwGVmZoYpU6YQofDt27fIy8ujOZbwG83Flk+fPkFeXh6Ojo5wc3OjJeApLy+Hubk5jIyMcPXqVb5sr79KfHw8+vfvDycnJ1qYrsuXL8PJyQkeHh40D1j2/wdGgGX4/8Cr/5SXl+Pw4cNQUFDAyJEjSfnatWuhq6uLXr16wd7enjmA+klLYzA2NhbGxsYICAgg8+KNGzfQs2dP6Ovro0+fPkxozX8ZrSq+cnai5cuXk+y+NTU1SEtLg5aWFuzt7bmMwFevXjGGIejtt2LFCkhJSWHChAmws7MDRVHYt28f7f0nT55g+PDhXMIsP5OVlQUdHR0uj+D6+nqcPXsWoqKiNKF/69at0NTU5PJCZPjrMGOXm1evXkFISIgkkWEbKfHx8Xj06BFyc3MxePBg2NjYYN68eUhOTsb06dMhJibGeMvxICYmBuPGjcOYMWNoBl9sbCyXAPvp0yemTzL8TygrK4ORkRGePXuGU6dOQUREBNu3bwfAOmjetWsXTQwD+FOo+TPYbfL27Vuoq6uTNsvIyIC1tTUoisL169eZQ1EOml+T9/Pzg6SkJEaMGIH79++TZ7wEWDbMvEjnwIEDUFJSoiXKqqmpwaxZsyAsLIygoCASCoOfRS/231xUVIR79+6RkAKfP3+Guro6KIrC2bNnATS1U0VFBaytraGqqor09PTWqXgb5OLFi7T9xu7du6GhoQFZWVmuUFSXL19G//79YWVlRYulye+iF8P/D845LD09HYmJiUhPTydzHTsEwfDhw8l7r169Qn5+Pl8fQHHC2YbJyclISEig3e7eu3cvEWDZt8cqKyuRn5/PhNb8F9Jq4itnR3zx4gXc3d1BURS5MlFTU4PU1FTo6enBwcGBpwHDGIYsnj59ig0bNuDixYsAWN5cs2fPhqioKJeomJuby5fGYEukpaVBXV2deLc2Z+fOnaAoisSvAUCLk8vw9/nVZo8faWhowLx58yAjI0MyXQLAkiVLIC0tTYzoFy9eIDIyEmpqatDW1oalpSWJE8nP8OpPISEhoCgKenp6XGFCdu7cCR0dHfj7+9PEGmZMM/y3+fbtGwwNDTFs2DBISkpi27Zt5NmrV69oyTAZeMMe02/fvoWCggImTZpEix13/fp1GBkZ4d27d61ZzTbL7Nmzoaamhjlz5mD06NEQFRWFt7d3ix6wDCx4tcmZM2fQq1cv3Lt3D0DTPqawsBCKioowNTVFcHAwX4e9YLfJs2fP0Lt3b7i6usLT05N4rBcXF6NHjx6wtramxf8HWJ50ffv2RV5e3m+vd1ukuroagYGB0NfXx6pVq0h5UlISDAwMMGrUKGRmZtK+SU1NxcyZM5l9HsN/nblz50JZWRlmZmbQ1NSEi4sLbt68ibq6OiQkJKBHjx40D1g2TF9sIjQ0FD179oSdnR20tbXRq1cvshbHxcXBxMQEkyZN4grFx7Thv4tWDzsQHh4OS0tLDBkyBDIyMhAUFCTZptkCrIGBAXR0dBgDEcC0adNIbCkAuHbtGiiKgoSEBM6dO0fK3717hzlz5qBr1644ePAg1+9hBjKL1atXo1u3buTn5u3y5s0bSEtL0zbNbBixhuG/xYcPHzBz5kxYWlpi+/btWLVqFWRkZMhhFOfcV1dXh6KiItqVM37m8+fPePfuHR4/fkySZwGshBMyMjL4448/8OnTJ9o3GzZswMiRI5l5kOF/TlJSEoSEhDB06FAArLH8/ft3uLu7o0+fPsw6wgF7nnv69ClOnjyJZ8+eEdHGy8sLU6ZM4WkHst9hoHPjxg3Iysri5s2bpOzo0aPQ19fHsGHDaB6wDE1w9rGdO3eSa9wVFRXQ0NCAk5MTba158eIFhg8fjtmzZ0NXV5dvk4ey2y0rKwvi4uKIiIjg6f3GFqvt7Oy4BFgGOpy24bJly0j5oUOHYGZmBj8/vxbHMWPfMPy32LFjB+Tl5Ulc5oULF6JLly5kbqyqqsKRI0cgKCiIBQsWtGZV2yy7du2CrKwscZpJSkqiOR2y3+nevTtWrlzZSrVk+B20qvh64MABCAsL4/bt2ygvL0d2djYCAwPRvn17JCUlAWAJsElJSRg9ejTfb1Lev38PNzc3EvsDYF1rXLlyJTp16oS1a9fS3n/37h1CQ0NBURRNmGVo4vLlyxAUFKSFaGi+uVNVVcXq1at/d9UY+IxPnz4hKCgImpqaEBQUxKVLlwDQRX7GmKZz6NAh2NnZoVu3bqAoCqqqqpgyZQp5vnDhQigpKWHZsmVcAiw/Xwtl+O/xZ4fC1dXV2LhxIyiKgru7O1xdXeHg4AB9fX2ylvO7bcPJ8ePHISoqCjU1NXTs2BHz58/Hly9f8O3bN+YA/m+SkZEBeXl5Lu+4hIQEtGvXjssDloG+Hty/fx99+vSBhoYGuQqfl5cHeXl52NvbY9euXbhw4QJcXFzg7++P2tpadOnShXaDhd/4+vUrbG1tMX36dFp586uznz9/hqKiIvr06UOL/8rADds25CXAmpubY+zYsbQwAwwM/y3Y43bSpEmYO3cuAODEiRPo2rUrYmJiALAOpUpKSlBTU4OLFy8y9kwLREZGkgTJhw8fhpiYGAlD9f37d/Le6dOnmTb8l/PbxNc//vgDlZWVtLKlS5eiX79+tLLCwkL4+PigQ4cO5ESlpqaGyZTXjPj4eHLyXlZWhkWLFoGiKK5kWm/evMHmzZuZWCE/ab55y83NhZ6eHuzt7ZGRkcH1fn5+PkxMTGgnUwwM/ys+f/6MGTNmwMDAgHaYwsx73OzevRtCQkLYunUrLl26hPT0dIwdOxadOnVC//79yXvz589Hjx49sGLFCnz48IH2Oxgxh+H/A+f12MTERJo3XHPS09MxY8YMzJgxA5s2bSJrMrM200MLODo6IiYmBiUlJdi0aRN69eqF6dOn02JbM+OWG3abcLbN7du3IS0tjVOnTgEA7eBeR0cHurq6CAwM5ArNwsBKpDV48GBYW1tDSEgIurq6uHDhAgCWN2K/fv2gra0NZWVl2Nvbo6KiAvX19TA1NSW39/iRZ8+eQU1NDVevXuV5sNnY2Ej66KdPn9CpUye4u7ujpqbmd1f1H0VLAmxCQgKUlZWxePHiVqwdw78FXmO2oaEBXl5eOHz4MK5fvw4REREivNbX12Pnzp04dOgQ7Rtmz9IEu03d3NwwZ84cXL9+HaKiouRGbWNjIxYtWoQ1a9bQvmPa8N/LbxFfHz16BGtra65NxubNmyEpKYni4mIATUYj2xVbUFCQCLD8bmxzToglJSUQExND7969UVhYCIB18rRw4UJQFIU9e/bw/B38vMlbunRpi88SExNBURScnJxIEoC6ujp8//4dHh4esLGxYSZBht8Gp5HNefWE8dBs4uHDh1BTU8ORI0do5V++fMHWrVvRuXNnjBo1ipQvXrwYHTp0QHx8/O+uKsO/lFu3bsHMzAxJSUmYM2cOOnbsiPfv3/N8l5cwBjDGNSfXr1/H/Pnz4ePjQwupEhsbC01NTcyYMQMvX75sxRq2XTjXhu/fv6O0tJT8PHnyZIiLi9NiyBUXF8Pf3x9r1qyBmJgYEWcZWGzfvh3CwsK4du0aioqKcOLECXh4eEBfX5/kVqiursbHjx/x5s0b8l1kZCS6d+9OK+M3Dh48CEFBwV/eLKmoqCDJogoLC5lx/RfhtA2XL19Oys+fP8+sJQz/FcrKyvDlyxc8fvyYFuIwNDQUHTt2hJCQEE1o/fbtG/r16/fLPTa/8f37d5IvJLwAAE0OSURBVOTl5eHGjRu05IwHDx6Enp4eOnbsiNjYWFJeVlYGDw8PzJs3rzWqy9AK/M/FV7bgx16AT548Sdyrnzx5AktLS8ycOZPmkXTv3j0EBgZi+vTpUFZW5mtDBmB5g7A5ceIEvn//jlevXkFdXR329vZkcFdWVmLRokUQFBTE5s2bW6u6bQ5XV1f07NmTdrLe0NBA2wgnJCRAXl4e4uLicHZ2Rv/+/WFvbw9jY2PmaijDb4dtZPfu3ZuJn8SD06dPw8jICJ8+fSLjkj2ev337hsjISIiJiZHQDQDLU5YZwwz/LZ48eYLRo0dDUVER4uLiePXqFYBfrxP8fojcHE4vuMjISFAUBSUlJeTm5tLei42Nha6uLsaPH8/1jN/h7FMrV66Evb09DAwM4OTkhGfPnuHLly8YPnw4hIWFsWTJEmzatAn9+vWDvb09AMDExASTJ09ureq3ScaPHw9fX19a2ZUrV2BjYwMdHR0SgoBNVlYWhg8fDjk5Oa5EKfzGzZs3ISQkhMTExBbf2bx5M5ydnfk6Mdl/yqdPnzB9+nTY2NggPDyc9oyxbxj+P5w9exY+Pj6Qk5NDu3btoKuri5CQEACsWxMeHh6QlJREfn4+SkpK8P79e7i6usLc3Jyvnbs4OXXqFIYPHw4ZGRmIiYlBVFQU8+fPR15eHj59+oT+/ftDX18fCQkJaGhoQHZ2Ntzd3WFmZsa0IR/RTuB/iK+vr0BSUpJAXV2dQLt27QTevXsnMHToUIFJkyYJVFdXC+jr6wt4enoK3LlzRyAiIkIgMzNTIDs7W2DRokUCtbW1At7e3gLV1dUCOTk5/8tqtmlu3bolMGLECIGUlBSB4OBggVGjRgl8//5doFevXgKpqakC79+/FxgxYoRAYWGhQOfOnQXCwsIEZsyYIXD48GEBAK1d/VYnIyNDICsrS+DGjRsCHTt2FLh69aqAgICAQLt27QQoiiJtNHLkSIEzZ84IREZGCnTo0EFARUVFYPjw4QJ3794V6NChg0B9fb1A+/btW/EvYeAn5OXlBSIjIwXU1dUFbt26JfD169fWrlKb4sGDBwKfPn0SkJeXF2jfvr0AAAGKogQEBAQExMXFBfz9/QUqKioEPn78SL4ZN26cQPv27QUaGhpaq9oM/yL09fUFdHR0BAoLCwV69uwp8PjxYwEBAQGB9u3bCzQ2NvL8ht1H+RV2u1RVVQnU1NQIvH//XqC6ulpAQEBAYOnSpQJr1qwRqKioEIiPjxf49OkT+S4gIEBg0qRJAk+fPhUQERFplbq3Vdh9av78+QIbNmwQGDt2rMD+/fsFsrKyBCZOnChQX18vcOTIEYE5c+YIJCcnC8TFxQl06dJF4Ny5cwICAgICnTp1EtDU1GzNP6HNISUlJfDmzRuBHz9+kDJHR0cBT09PgefPnwvMmDFDID09nTxTVFQUcHJyErh27ZqAsbFxa1S5zaCsrCzQtWtXgX379gnk5+eTcs79yNu3bwVMTU0FOnfu3BpV/EcjLy8vEBERIaCmpibw9etXWrsyexSG/5S4uDiBCRMmCKirqwusW7dO4NKlSwJaWloCMTExAl5eXgIdOnQQWL58uYCBgYGAjo6OgIWFhcCQIUMESktLBW7evCkgKCjI97Z1XFycQEBAgICurq7A9u3bBVJTUwVGjx4tsHr1aoGwsDCBxsZGgU2bNgloaGgIhIaGCsjJyQn4+PgIlJWVCdy6dYtpQ37if6XqNjQ0YOjQoZCWlsaZM2eI1+HVq1chKSlJyzS9adMmODk5gaIoqKurw9DQEI2Njfjy5Qs0NDRo3kv8xv379zFy5Eh0794dEv/X3n2H13j/fxx/npMlqUhixla0VS0NMUqMoqqUWondEitWtZQgohp712pFaSStCIkZ/OzRGq3WpkHN1miKohSZ5/794Zu7CbppQl6P6+pV5x4nn3Nf59zjdX/u98fDw+xdk3aH5MSJE8aTTz5p1K5d2+wBm5CQ8LuPOWY3586dM+/evfPOO8azzz5rlmpI82fbSHeTJbPEx8dneGxF7li0aJHh4uLyuwMJJicnG0WKFDGL2Ys8CGnnLGn/37Jli7F69WqjY8eOho+Pj/HZZ59lZvOytLRtFhcXZ7Ro0cJ4/vnnDXt7e8PLy8t49913zeXef//93x0k7+rVq/9lkx8ZP/zwg+Ht7W3Wpl+/fr2RK1eue/Z/ly9fNm7fvm2+Dg4ONgoVKmSeV2Y3v1fK59NPPzWefPJJY/78+cavv/5qTl+2bJnRokULo0OHDoafn5++j79jyZIlhpOTk/HGG28Y3377rTn95s2bxpAhQ4zixYtnqOEsf9/PP/9sfn+z+3We/DuhoaGGo6OjsXDhwgzfpUuXLhljx441nJ2djd69e5vTY2JijMjISOP//u//zOvj7N5rc86cOYaDg4OxZMmSe36PU6ZMMVxcXMwnTH788UcjLi7OiIqKMnbt2mX+jrP7NsxOHkr4+vzzzxvdu3c3DMMwfH19DXd3dyM2NtYMYL/44gsjV65cRuvWrc0fblJSkrFz507j0KFD5hfx3XffNcqWLXvPCXh2M2LECMNqtRoVKlTIUJsrbdudOHHCKF26tPHss88aV65cMefrgHznexUaGmoUKlTIcHJyMkdV/b1ANf1jkNp+IlnTyZMnDTc3N6Nly5bGDz/8YE5P+12fPHnS8PLyytY37uTBSh9anThxwvj555/NkjTffPON0a5dO8PHx8eIjIw0lwsNDb3nZl92lHYsPXjwoOHm5mb07t3bmDt3rrF06VKjadOmhpOTk/Hqq6+ayw8bNswoUqSIMW7cuHsGyZN7HTp0yChRooRhGIaxevXqDAOiXL9+/Z4Q9tixY0b37t2z9WPy6YPXgwcPGgcOHDCOHDliTnvjjTeMQoUKGaGhoUZcXJxx6dIlo0mTJsaIESOMTz75xHB1dVWA+DtSU1ON0NBQw97e3njmmWcMf39/o2fPnsbrr79u5M+fP9t+5x4GjQUg/8aaNWsMi8ViDhJ4d5m9n3/+2ejVq5dRqFCh+w5KnX7Z7Grp0qWGxWIxPvzwQ3OazWbLEKYOGzbMsFgsxsGDB+/7Htl9G2Y3Dzx8HT58uFG2bNkM0zp27Gh4eHjcN4Bt27atcePGjQzLb9261QgICDA8PDyMffv2PegmPjLSLlg2bNhgrFq1yujQoYNRo0YNY+HChfcse/ToUcPPz08/4HTStt/w4cMNFxcXo2zZssagQYPM6dpWIo+uBQsWGE5OTkb79u0zXMzdvHnTeO2114xatWrpwkT+teDg4AzHiuDgYKN48eLGs88+azRu3NisYb97926jffv2RuXKlY2goCDjtddeM4oUKaLv4P9cvHjRqFChwj11Ci9evGjMnDnTcHFxMVq2bGlOHzlypOHi4mJMnjxZx+o/ce3aNaNq1apGr169DFdX1wyDecTFxRnVq1c3tm7dak67evWqsWHDBuPkyZOZ0dxMl/7GenBwsFGuXDkjf/78Ro0aNTKMGt+tWzejfPnyRq5cuYynn37aeOaZZwzDuHO+/dRTT2UIa+Veu3btMnx9fY0KFSoYNWrUMAYNGqTBtUSyiJSUFGPatGnGU089ZfTq1euea+O010ePHjUcHBwyDLQlv1mwYIHh6upqDB069J79W9r539WrV41ChQoZ06dPz4wmShZj/6DLGDg5OeHq6kpqaiqjRo3Cw8OD8PBwfH196dixIxERETRo0ICaNWuyevVqmjZtSqtWrVi8eDEuLi4AuLm54ezszI4dO3j22WcfdBOzrF9//TVDPbO0Wl4vv/wycKfWz8SJE5k5cyZWqxU/Pz8A5syZQ+vWrYmOjgYgNTU1W9f+MdLVfwTw9vZmy5YtfP755yxatIikpCSmTJli1n/MzttK5FHl5+fHzZs36dWrF1u3buWFF17A3d2ds2fPcv36db755husVqt+4/KP7d+/n9mzZ7Nt2za2bt3K+vXrmTNnDjNnzuT7779n8eLFVKhQgb179+Lt7c3AgQP57LPP2Lx5M/nz5+fUqVNYrVZsNhtW60MtsZ/lnTt3juTkZNq3b2/+Jm02G/ny5aNDhw5cvXqVsWPHsnjxYnx9fQkODsbJyYkmTZro93uX9N8nwzCwt7enQoUKfPbZZ7Ru3Zpu3boBkJCQQGBgIB4eHtSsWdNc393d3TyvzI7Szg9HjBjB7NmzWbhwISVKlGDs2LEMHz6cX3/9lfHjx/Pxxx+ze/duLly4gMVioVGjRgB8+OGHPPHEE+TPnz8zP0aWV6VKFRYtWpTt930iWZGdnR2dO3fG0dGR2bNn07lzZ+bNm3fPtXH+/PnJmTMnKSkpmdzirKlt27YkJycTFBTEzZs36dOnD6VKlQJ+O9akpKRw48YNHB0dM7OpklU8yCTXZrMZS5cuNWrWrGl4e3sbOXLkME6dOmXO9/X1vacH7MaNG41XXnnlnt4h6Uemzw569OhhjB492vj555/vmZf+Ln1aDdgqVaoY77//vvHaa68ZRYsWVe+a/0m/Ha5cuWIkJyebj1FcvHjRGDFihOHt7W3069fPXE69akQeXfv27TN69epl1KlTx+jYsaMxbtw483Ef1VCSfyMpKclYu3atUa5cOaN27drGnDlzjLlz55rz9+3bZ1SqVMkoWbKk2QP2xo0bxs2bN83jtr6Dd8ybN8/IkSOH+frusj6nTp0y3NzcjIkTJ/7XTXskbNy40Rg5cqT5+u5zviNHjhgNGjQwKlasaHTu3NkYNmyYUbt2baNcuXLmOZDOE3+zZ88ew8fHx9i8ebNhGIaxdu1aw9XV1WjdurXh6upqBAUF3bPOtm3bDH9/fyNPnjzG/v37/+smP5LS/85Vyksk60j7Pf7666/Ghx9+aHh5eRmdOnUy56edu2zcuNF48cUXf/eR+ews/T5t3rx5RuHChY1+/foZJ06cyLDM559/btSqVStbP80tv3mgtyMtFgvNmzcnNTWVw4cP06RJE3Lnzm3Oj4mJoV69evj7+7N+/XoSExOpV68e69atM3uHpMludwcSEhL45JNPiIyM5MqVKxnmpe/FWbFiRYYMGUK1atVYvXo1FouFkydP3rP9siPDMMw77GPHjqVVq1ZUrFgRf39/du3aRb58+ejVqxdNmzZl27ZtDBgwANAIoSKPMi8vLz788EM2b95MeHg4gwYNMkcNtbd/4A93SDZhs9lwcHCgXr16TJgwgV9//ZWAgAASExPNZV544QXmzJlD3rx5qVSpEr/88gs5c+bExcUFi8WCzWbTd/B/SpcuDcCSJUuAjOc1AE8++SQlS5bk/Pnz/3nbsrrExESio6OJjo5m4sSJABnO+QzDoEyZMkyfPp127dpx5MgRDh8+TMWKFdm7dy8ODg6kpKSoB2I6ZcqU4fXXX6dSpUps2bIFf39/Jk+ezNy5c6lVqxZjx46lT58+Gdaxt7fn8uXL5pMW8ufS/87v/s2LSOaxWCwYhsETTzxBx44d6datG/v378ff3988d7l16xYffPABJUqU4Pnnn8/sJmcJ6bOWtG0I0KlTJ0aNGkV0dDQzZ87k+PHj5vITJkwgf/78lC9fPlPaLFmLxUj71jwASUlJXL9+ncaNG1O9enV27dpF+fLlGTp0KEWKFDGXa9OmDdHR0Wzbtg0fH58H9ecfSUa6R+T79+/PsmXL6NevHx06dMgQXN8tMTGR5ORknnjiCSwWCykpKbrI+5/g4GBCQ0MZNWoU33//PUeOHGHDhg2sWrWKOnXqcOXKFWbNmsXHH3/MgAEDeOuttzK7ySLyLxh3lRoR+Tfu/j4lJiayadMmhgwZgp2dHbt3784QZB04cICmTZtStWpVFi1alBlNzvLOnTuHt7c3L774IjNmzKBYsWLAb4/QX716lcaNG9OzZ086dOiQya3Nei5cuMCECRP46quvaN68OYMGDQLubD+LxWJ+X5OTk7G3t8/w/c3upVc2bdrEwYMH+fHHHxk2bBiurq4A5nlz7969sVqtTJo0CScnJ/r378/+/fvJlSsXS5cuzfBbT0hIIEeOHJn1UUREHqi0852bN28SERHBnDlz8Pb2Zs6cObRs2ZITJ06wd+9e7O3ts3UJpaCgIIYPH46Tk9M92yH9OWN4eDjBwcG0bduWHj160K9fP06dOsX+/fuz/TaU//m3XWf/6DGm8ePHG1WrVjV69uxpnD17NsO8oUOH6nG8/0n/2Pvbb79tlChRwpg2bdp9SxCkSd/VXY+S/ebs2bOGl5eXsWTJEnPauXPnjK5duxp58uQxDh8+bBjGnREcw8PDVXJARERM6Y+nY8aMMQe4TExMNNauXWuUKVPGqFWr1j3HjuPHj+t48ieWLFliODo6Gm+++aZ5LE4THBxslChRwjhz5kwmtS7r+/HHH40+ffoYVatWNcaNG2dOT/vOxsfHG23atDE+/fRTwzD0mLdhGMacOXOM/PnzG/Xq1TMKFixoPPPMM2YZBsO482httWrVjA4dOhiGYRi3b982fH19zW1oGDrHFpHH290lCLy9vQ17e3vj6aefNveX2fn85uTJk4arq6vh4+NjlsW8+7iQ/ngbHh5uFCtWzHB3dzfKli1rbkPlXmIYhvGver4a6ZL+iIgI9u/fT/ny5alatSply5YFYOLEiSxZsgRvb2+GDBmSoQcskK17bKbffunvhLz99tvExsb+pR6wktF3331H+fLlWb58Oa+++qo5/fjx47z55pu88cYb9OrVK8M62b1XiIiIZDwOHzt2jP79+7NmzRpWr15Nw4YNSUpKYvPmzQwcOJA8efKwefPme3ow6Hjy+1JTU5k7d645IIWPjw8FCxbkzJkzrFmzho0bN1KhQoXMbmaWFh8fz+jRo/nmm29o1qwZgwcPBuDHH3/Ez8+PixcvEhcXl23Pq9ObPXs2ffr0ITo6mvr16/Pjjz9Sp04dli1bRqVKlczz72nTpjFhwgRq1KjB2bNnuXXrFnv27MHOzk5PVYjII+2PelrePXhjWg/Yjz76iAMHDjBv3jyzbE12P6bs3buXdu3akSdPHrZs2YKjo+Mf9oANCwtj0aJFrF69Gnt7e21DMf3j8DX9F2zYsGHMmDGDypUrs3//fl566SW6dOlihl+TJk1i2bJlFC9enGnTppEvX74H9wkeUel/sLdu3SIpKQl3d3dzft++fVm5cqUC2L8pOTmZV199lRdeeIH333+fXLlymfOqVatGtWrVmDJlSia2UEREsrIhQ4awZcsWChYsyI4dO7h69SrR0dE0b97cDGAHDRpESkoKhw8fVjjzN+3atYsJEyZw7Ngx3N3d8fLyok+fPpQpUyazm/ZISB/AtmzZks6dO+Pn58dPP/3E/v37cXBwyPY3AZYvX06LFi1YsWIFTZo0AeD27dt4eXlRr149jhw5QsuWLWnZsiWOjo589tlnbN68mYIFCzJz5kxtQxF55KXPGiIiIti7dy9wZ6wEf3//e5ZPy3YSEhJwcnJSWcO77N27lzZt2pAvX76/FMCm0TaU9P5R0Yn0X6y9e/dy4sQJ1qxZw4YNG1i0aBHXrl1j5syZrFmzBoABAwbw8ssvkzNnTvLkyfPgWv+ISv9DHTt2LC1btqRs2bKMGDGCr776CoDp06fTpEkTpk2bxoIFC7h8+XJmNvmR4eDgQLVq1diyZQsLFy4kISEBuBNwW61WChYsmMktFBGRrCoyMpIZM2YwdepU5s+fz+eff26GW8uXL8fR0ZG6desSEhJCxYoVs/1Al/9E1apViY6O5tChQ2zfvp3p06creP0bPD09GTp0KFWqVGHJkiWUKlWK+Ph4M3hNSUnJ1qFhYmIi69ato2TJkpw6dcqc3r59e27cuIGrqysuLi7079+f6dOnkydPHt555x1iY2OZPXu2tqGIPBbSsobAwECCgoJISkrCwcGBLl26MHz48HuWT8t2cuTIYQ4mpdDwNxUrViQqKopLly5Rp04dkpKS7hnwPP0gXGm0DSW9f1V24NNPP2XBggWkpqaydOlSs4j9li1bGDNmDDly5KB3795mD9i00FbFhu8IDg5mzpw5DB8+HGdnZ0aNGoWXlxcBAQG88sorALzzzjt8/PHHfPrpp/j6+mZyi7O29DcFunbtytdff02BAgXw8vLiq6++4urVq2bBaxERyd5GjBjBwIEDcXZ2NqeNHj2aLVu2sHHjRnPaxYsX6devHzExMcTGxvLqq6+aFzEWi0U95P6B9MdrPdr9z8THxzNo0CAuXbrEihUr9HhoOj/++CPjx49n165dtGnThu3bt3PixAmWLFlCyZIlAXjzzTdZt24d3377LXnz5jXX1fdRRB4XGzdupFu3bkRGRlK9enWWLl1KmzZtmDlzJt27dzeX034vo9/r0ZqamsqBAwdo3bo1+fPn/90esCK/5299SzZt2sSoUaPM16mpqZw+fZqDBw9y+PBhc3qdOnUICgoiOTmZkJAQszdn2t0AfTlh9erVxMTEsGLFCnr16kXZsmX5/vvvOXjwIFOnTmXLli0ATJ06lTFjxtC8efNMbnHWkHavIP09g7Q7Tmk7RYC5c+fyzjvvUKJECeLi4vDy8mLfvn3Y29uby4iISPZ04MAB1q5di4ODQ4bpbm5u7Nu3z3zaxDAM8ufPj5+fHykpKTRp0oS1a9fi6OhorqPg9e9Lf5GnC75/xtPTk6lTp7Jq1SoFr3cpWLAggwcPplKlSkybNo3NmzezatUqSpYsya1btwCoUaMGxYsXv6f3ur6PIvKount/Fh8fT8mSJc3gtWPHjmbwev36dbZv3w5ov5fe3eUaBg8eTJ8+fThw4AB2dnZUrFiRRYsWcfHiRerWrWv2gP0X/RklG/nLZ2mJiYlER0fz5Zdf4ujoSGBgIP7+/nh4eDB8+HBmzJiBo6Mj3t7ewJ0ANjExkbVr11KlShXzfbLrj/vuOyJ58+alR48evPjii/zf//0fHTp0ICwsjNKlS/Pyyy/j4ODAL7/8QrNmzXjnnXcADeSRfhv+8ssvALi7u2fYrnZ2duZ26ty5M507d85wQaKLExGR7C0lJYUXXniB7du3Y7VaWbFiBXXq1CFXrlzUrl2bp556ilGjRhEYGEihQoUAKFKkCN26dcPJyYkePXqwdetWSpQokbkfRLI9Dw8P4M75kc5tMvL09CQ4OBir1cqOHTuIiopiwIABuLi4kJKSwuLFiylZsqTGoRCRx0baNXFYWBjlypXD2dmZXLlyERERQZ8+fZg0aZLZ43Xnzp3m0wBp5zry2zYcNGgQUVFRVKpUCavVStWqVVm0aBFNmzY1A9h27drx/PPPa6BL+cv+chdUJycnhg8fTt26dVm6dCljxowBMEdbPX78ONOmTTOLOQO8+uqrTJ069Z56GNlR2g958eLFHD9+nIoVK/LGG29w48YNpkyZQmBgIG+++SbVq1fnmWee4auvvmLPnj0Z3iM7B6/pe0yPGzeOJk2aUKtWLerUqcP+/ftJTk42l717O6XtDFW7RkQke2vfvj3Lli0jOTkZq9XKDz/8QPPmzQkICCAhIYFy5crRokULdu3aRVBQELt37yYuLo7333+fpKQkWrduTUJCAseOHcvsjyJi0hNl91egQAGGDBlCtWrViImJYdKkSQC0aNGC8+fPM3/+/PvW6BMReZSkz1mmTJlCUFAQzs7OFChQgN27d9O5c2dCQkIICAgA7oyFMn36dAzD0Hgo9zF37lwWLFjAsmXLWLp0KZ07dyYpKYl27doxf/584E4N2IiICCpUqJBtOxfK3/e3ztYKFSrE4MGDqVy5MrGxsWYA27ZtW/r378/Ro0eZMWOGWWYgwx/SiSFxcXEMHDjQHBQhb968JCQkcOHCBTw9PQG4evUqFSpUYNasWYSEhGRyi7OOtJ3ae++9xwcffEC3bt1YuHAhp06dolu3bn9pQDLtGEVEsi+bzcbt27fp1asX69atIykpiWLFirFlyxbWr1+Pv78/NpuNwMBA2rZty/nz56lSpQrNmjXj3LlzhIWFUaZMGdzc3O4pVyAiWVPaAGVVq1Zl2bJlFChQgGPHjpljAKSkpOj8UEQeaWk5y5EjR7hw4QIzZszg+eefp0aNGgQHB2MYBhcvXiQ2NpZNmzbRrFkzzp8/T2hoqG5AkTG8vn37Nj/99BMhISF4e3uzcuVK2rRpQ2hoKN26daNHjx4sWbIEwOwNm/bkrcif+UcDbsXHxzN69Gi++eYbXn/9dYKCggBYuHAhgwcPpkuXLgwbNuyBN/Zx0KFDBw4dOsSBAwcAOHPmDK1ataJcuXK8+OKLLFu2jOvXr7Nt2zYN5HGX8+fP07x5c4YPH85rr73G+vXr8fPzY8KECeadPLi3xIOIiGRv5cqVo3r16syePRs/Pz82btzIp59+SoMGDXB0dGTbtm00btyYhg0bEhkZiZ2dHcnJyezevRtXV1fKli2L1WplwIABrFmzhk2bNpk3TUUk69MAZSLyuDIMg40bN9KgQQNy5cpFWFgYLVq0MOfPnDmTqKgo9u/fj5eXF3ny5GHJkiU4ODgoa0jn9OnTPPnkk+zbtw8PDw9SU1Np0qQJPXr0oG/fvnz++efUqVMHgDVr1tCgQYNMbrE8av5R+AoZA9imTZsyZMgQADZs2EDdunWz/Y/47hO6pKQkHB0dOXr0KK1bt6Zfv3506tQJgJiYGCZOnMjt27cpUKAAa9aswcHBQSMP3iUuLo6GDRvy/fffs2bNGlq1asWkSZMICAjgxo0bfPbZZ/Tq1SuzmykiIlnI+++/T0xMDN9++605rVOnTsTGxhIREXFPAPvaa6/x8ccfkzNnTnP5zz//nKioKKKjo9m8eTNeXl6Z8ElE5N+4evUqbm5uWK1WBa8i8ki7X2ejkJAQQkJCGDBgAEOHDsXNzc2c9/PPP3Pt2jVy5cpF3rx5sVgs2g+mExMTQ48ePbh8+bKZv2zcuJEhQ4awePFiihcvzjfffMOCBQsoW7Ys/v7+2nbyt/3j7oFpj/FUqVKFVatWmeFr/fr1s3XX682bNwO/1RldtWoVNpvNHBm5cOHClCxZklWrVpnr+Pn5sWrVKrZs2cKGDRvMu/HZOXhN3/0/ISEBgOLFi1O4cGECAgJo3bo1U6ZMMXu8XrhwgcjISHP7i4iIwJ2a9a6urqSmphISEsL06dMJDw+nbt26dOzY0SxBULNmTVavXs26deto1aqVOSo6gJubG87OzuzYsUPBq8gjysPDwxyHQhfNIvIoSwteo6OjWb58OQDDhw9n0KBBTJkyhejo6AznMXny5KFUqVLky5cPi8Wi/eBd6tevT548ecza4HBngO89e/Zw9uxZzpw5w8iRI7l06RLdunUzy9aI/B3/uOdrmvj4eAIDA8mRIwezZ8/O1oHhsGHDzLpwFouF/fv306BBA3LmzEmfPn1o0KABZcuW5cCBA9SqVYtZs2bRrl27e94nuz82n/7zh4aGYmdnR8OGDcmXLx8DBgzg008/pWXLloSFhQF3wllfX19sNhurVq3K1ttORER+YxgGy5cv54MPPuDWrVt8++23xMXF8eSTTwJ3bn5u2rQpQw/YTZs2MWHCBNasWZPheJL2BIuIiIhIZrt06RI+Pj6ULFmSt99+m4YNGwIwcOBApk2bxkcffUS7du1wcXHJ5JZmLXdnLampqaSkpNCvXz8uXLhATEyMWdu/ffv2REVF8eSTT5IzZ052796tuv/yj/3r8BXgypUruLu7Y7Vas/Wj8nFxcTz99NPY29tz/PhxnnrqKW7fvs3QoUM5dOgQe/fuZeDAgdSqVYslS5Zw8+ZNpkyZoh3i7wgMDCQ8PJyJEyfyyiuvULBgQU6cOME777zDuXPneP755ylWrBg7duzg6tWr7NmzBwcHh2wfXouISEY+Pj7s2bOH119/nTlz5mR4FM/Pz48tW7YQHh5O/fr1cXJyMufpeCIiIiJZwf1ylkOHDhEQEICHhwe9e/emUaNGwJ3r6BkzZjBu3Dh69OiR4dwmu7p161aG3OXs2bMULVrUfH3w4EEqVarE7Nmz8ff3N6dv2LABwCytqXIN8k89kPA1TXa+SElfrHrJkiUMHz6coUOH0rZtWwBOnTrF2rVrmTlzJp6enuzfv5+kpCT27t3L008/nZlNz5JCQ0MZMWIEa9as4YUXXgAgMTERJycnrly5woIFC1i0aBGFCxemaNGijB071uz+r52hiIjAnd6q169fp3HjxlSvXp1du3ZRvnx5hg4dSpEiRczl2rRpQ3R0NNu2bcPHxycTWywiIiLy+3766ScKFChgvj506BBdu3Ylb9689O3b1xwIqnv37hw7doytW7dm285xaXx8fAgICODNN98E4JNPPmHWrFlUq1aNkSNH4uTkhLOzM4GBgRw4cICwsDAKFy58z/togDL5Nx5o+Cqwb98+kpOTGT9+PFevXqV79+60adPGnH/s2DEOHDjAmDFjuHXrFkeOHNEP+D769+/P1atXmTdvHidPnmT79u1Mnz6d3Llz4+/vf99yDdoZiojIH90InjBhAkuXLqVixYoEBQVlCGCDg4N5//33dQNPREREsoz05zUfffQRq1evZuTIkVSsWNFc5uDBg7Rs2ZJChQoRFBRkBrBpvWWz89PJAOHh4bRt29bsAXzs2DFWrVrFJ598AkDDhg3p3bs3586do3PnzsyfP58XX3wxW3culAdP4eu/lP4HOWDAAEJDQ4mPj+fIkSNMnDiR+Ph43nrrLfz8/H53XYWGv0kbaOutt95i37591K5dm23btpE/f37y58+PzWZj9+7drF69Gk9Pz2x9EBERkYzSX1xERESwf/9+ypcvT9WqVSlbtiwAEydOZMmSJXh7ezNkyJAMASygJyhEREQky7ly5QrHjx/H19eXOnXq8M4772QIYGNiYujcuTMVKlRg7Nix+Pj4kBb1ZNdr5rtD5xEjRpCamsp7771n5i+jRo1i586dbNu2jZCQEMaMGUOZMmXYsmWL6rvKA6UY/19KC17PnTuH1WolNjaWnDlzUrlyZQYNGkTBggWZMWMGMTEx5jrJycnmujabLVsHr2lhaxqr1YrVaqVfv34ULVqUzZs307JlS95//31CQ0OpW7curq6u5MyZM9seRERE5F7pT7CHDRvG22+/zeHDhwkMDGT48OGsXbsWuDMQha+vL/v37ycwMJBLly5leB8FryIiIpLZFi9ezOrVqwF499136dGjB1WrViUyMpLt27czefJk9u7day5vs9moX78+ZcuWpVq1asCd0DU7XzOn72d469YtPDw8GDlyJNOmTePq1avAnSeflixZwgcffMC6deu4desWhmHofFAeOH2j/qH0PV5XrFhBy5YtKV26NJ07dzYvAL29vQkMDGTixIl89NFH3Lp1i44dO2a4g5Kdu7Gn34YLFy7k2LFjWK1WmjRpgpeXF/PmzSMlJYVcuXIBd2r3zZ8/n7x585IzZ87MbLqIiGQh6YPXvXv3cuLECdasWUO1atXYvHkzY8eOZebMmRiGQcOGDRkwYAA3btzgxx9/JE+ePJncehEREZHfJCYmsmnTJmbPnk3z5s1Zt24d27dvB6BWrVrMmzcPf39/Jk+ejK+vLzVr1iQqKor69evTu3dvIHuPxwN3zg3TP6H87bffsmbNGpKTkxkwYAA2m42uXbvi7u6Os7MzXbt2pVGjRpw+fZoXX3wRi8WS7behPFgqO/APpL/IW7BgAYZhEBsbS2xsLNu3b8fb25ukpCQcHR2BOxeCgwYN4umnn+bDDz/MzKZnSYMGDWLhwoU888wzODs78/nnnxMbG0utWrUA+OWXX4iNjWXhwoWcPXuWPXv24ODgoJ2hiIhk8Omnn7JgwQJSU1NZunQprq6uAGzZsoUxY8aQI0cOevfuzauvvgr8djzX8URERESygvTnJOXKlSMuLo7p06fTu3dvkpOTsbOzw2q1sn37doKCgjhx4gQODg7kzp2br7/+GgcHh2xf4zX959+xYwcDBw5k0qRJVK9eHYBJkyYRGBjIhAkTCAgIMM8X01NpSHnQ1PP1b0q/Mxw/fjxz584lOjqaZ555hosXL9K4cWN27tzJk08+SXJyMg4ODlSsWJGZM2fy1FNPZXLrs4607RgaGsqCBQtYunQplStXJjIykpUrV9KgQQOWL19OgwYNSExMZMuWLeTLl48VK1Zgb2+vmnwiIsKmTZv48ssvCQ4OBu6cKJ8+fZpr165x+PBh87G7OnXqAHeO2yEhIbi7u5u9GtL3jBARERHJLOnPSSIjI3FycsLPz49+/fpRvHhxGjduTGpqKikpKdSoUYPPPvuMH374gYsXL9KsWTPs7Oyy/XVy+uA1JiaGFStW8PTTT1O9enUSExNxcnJiwIABwJ1OYFarlS5duuDm5pbhfRS8yoOWfX+V/1DazvDIkSPExcXxwQcfUKFCBQAmT57M4MGDefnll9m4cWOGAPaZZ54B1P1/9+7dVKpUCavVyvXr1zlx4gQjRoygcuXKrFq1ip49ezJp0iT2799PixYtWLVqFXXq1GHq1Km4urpisVhITU3N1gcUERG580hedHQ0X375JY6OjgQGBuLv74+HhwfDhw9nxowZODo64u3tDdwJYBMTE1m7di1VqlQx3yc79wwRERGRrCF9ThASEmJ2UCpVqhR58+alRYsWLF26lMaNG5vrpKSkULNmTfN1dr9OTh+8njx5kujoaDZs2EDJkiUBcHJyMvOZAQMGYLFYGDBgAAULFqRt27aZ2XTJBlR24B+IjIxk6NChODg4EBUVRaVKlcx5u3fvJjg4mJMnT/J///d/6u2aTmhoKCNGjGDz5s2UKVMGgAMHDuDq6kpKSgqNGzemb9++9OnTh+XLl9OiRQsAtm3bho+PD3DviIUiIpJ9XbhwgQkTJvDVV1/x+uuvExQUBEBUVBRTpkzh2WefvWc04DTZ/WaoiIiIZD1nzpxh+PDhtGnThoYNGwJw7do1hg0bxpw5c1iwYAH169enU6dO5MuXj9DQ0ExucdaQPifo1asXly9fZvLkyUyePJklS5YQEBBA//79cXFxMQNYuFNGslWrVtk6tJb/hq46/sT9sunmzZtTrlw5Tp06xdatW0lKSjLnVapUidGjR+Pm5mZeBAp8/PHH9O7dmw8//NAMXgFeeOEFSpYsSVxcHPnz56d9+/YAeHh40L17d2bOnEnVqlXN5RW8iohImkKFCjF48GAqV65MbGwsY8aMAaBt27b079+fo0ePMmPGDL766qt71lXwKiIiIlnJvHnzKFOmDLt27aJAgQLmdHd3d0aOHEnv3r3x9fWlRo0afPvtt8yYMSMTW5u1pOUEly5dIi4ujp49e1K0aFEmTpxIo0aNWLlyJbNmzeL27ds4ODiQnJwMQLt27cyyhiIPk648/sT169czvE5KSsLFxYWYmBgaNGjAZ599xqpVqzL8WL29vYmMjGTRokX/dXOzpNmzZ9O7d29iYmJo3ry5Of3LL780//3rr7+yc+dOLly4wM8//8zkyZOx2Wz06tVLO0MREfldnp6eDB069HcD2C1btrBhw4ZMbqWIiIjIH/P396dWrVp89913HDx4MMM1sLu7O5MnT2bjxo0MGTKEb7/9FgcHB10npzN+/Hh8fX3JnTs3FStWxDAMHBwcmD59Oi+88AIxMTGEhoZy69Yts+drGvV8lYdNZQf+wGeffUa/fv0YPHgwxYoVo1WrVhnm3759myZNmvDLL78QFBREkyZN7vnRZvfHGtPKB6xYsYImTZqY05s2bYq7uzuzZs3CxcWFa9eu0bFjR1auXEnp0qVxcnJi7969Gq1RRET+kvj4eEaPHs0333xD06ZNGTJkCAAbNmygbt26GjhBREREsow/yglq1arFmTNniIyMxMfHB6vVet9r4tTUVJ3f/I9hGMyfP593332XnDlzsn//fnLlymWWGEhMTOTtt99m/fr1jBkzhjZt2mR2kyWbyb6p4F+wdetWs+frkCFDaNu2LQsXLiQxMREAZ2dnYmNjcXNzY9y4cURHR5OamprhPbJz8JqYmMi6desoWbIkp0+fNqf7+vpy/PhxQkJCcHFxAe7cyfv000+JiYlh9OjR7N+/37yTp+BVRET+TFoP2CpVqrBq1SozfK1fvz52dnb3HJ9FREREMkP64HXPnj188cUXnDlzxjxX+eKLLyhcuDCdOnVi586d2Gw2LBbLPSURs3PwarPZgN/KRFosFlq3bk1oaCiXLl1i4MCBAGaJAScnJ6ZNm0aPHj3w8/PLtHZL9qWer3/g2LFjDBw4kMDAQEqUKEFgYCC3b98mLi6OUaNGUaZMGcqVK8etW7d46aWXeO6555g3b15mNztL+fHHHxk/fjy7du2iTZs2bN++ne+++45ly5ZRsmTJP+zVqjt5IiLyd8XHxxMYGEiOHDmYPXu2buCJiIhIlpH++nfo0KHMnz8fOzs7Ll++zLBhw2jRogWlSpUCoHr16ly+fJlZs2ZRt25dndP8T1RUFGvXrmXQoEEULVoUV1dXc15SUhLLly+nU6dOdO3alenTp5vTHR0dzeWUNch/TeHrXS5fvkzevHkxDIMrV67g7+9PlSpVCA4OBuD8+fMULVqU8uXLc+vWLd544w18fX15+umnsVgs2bqn6+9JexR09erV/PLLLxw8eJDChQtnGGWwUaNGlC9fnnHjxmVya0VE5FF35coV3N3df/cxPREREZHMNGbMGD788EM+++wz6tatS7du3Vi8eDE9evSga9euZgBbunRpKlasSHR0dCa3OGv45Zdf8Pb25vr16xQoUABvb29q166Nv7+/uUxiYiLLly/H39+f7t27M3Xq1MxrsMj/qKpwOjt27GDYsGFs3rwZi8VCnjx56NatGx07dqRjx44ULVqURo0aUa9ePUJCQjh8+DDvvPMOJ0+eJDw8HFCN1/vx9PQkODgYq9XKjh07iIqKYsCAATg4OJCamsrrr7/OyZMnWbFiRWY3VUREHgO5c+cGdEwWERGRrOfkyZNs376dadOmUbduXWJjY1m8eDEvv/wy06ZNIzU1lW7duvHUU09x4sQJlU5KJ2fOnLRq1YrixYtTuXJlNm/eTL9+/Vi3bh3PP/88gYGBODk50bp1awzDoF27dhQvXpx+/fpldtMlm1PP13QSEhIoXbo0PXr0MHu63rx5k4CAALy8vJg3bx4eHh6sWLGCPHnyAHD27FkKFy6si7u/IK0H7Ndff42fnx8DBgygadOmHDt2jEOHDpk1XjXSoIiIiIiIiDyOrly5wpYtW3j11Vc5dOgQvr6+DB48mD59+tCtWzdWrFhBq1atzMfqQY/Jp7d27Vpat27Ntm3bKF++PAkJCYwdO5aRI0fywgsv4OfnR+PGjSlfvjybN2+mVq1ayhgk0ykx/J/U1FRy5MjBpEmT2LdvH0ePHgXgiSee4JlnniEwMJCiRYuyfv16M3i12WwULVoUq9Wqu1F/QdpgKFWrVmXZsmUUKFCAo0ePKngVERERERGRx07awFDp5c6dm3r16vHEE0+waNEiXnrpJbp37w6Am5sbRYoUIT4+niJFipjrKHj9zauvvsobb7zB7NmzAciRIweLFy+madOmNGjQgC+++AIvLy/CwsKoW7cu9vb2pKSkZHKrJbtT0vU/aTuzihUrMmPGDLZv306ZMmUAGDRoENu2baNcuXK4uLiY66Tv7aqd4V/j6elJUFAQgwYNws3NjRUrVih4FRERERERkcdK+vJHK1euJCEhAQA/Pz/c3d0B+Omnn7BarSQmJuLo6Mjp06eZMmUKtWvXxmKxqHb976hQoQLz5s3jypUrvPzyy3h4eBAREUGuXLmIj49n27ZtNG/e3FxeWYNkNpUd+J/0O7WIiAj69+/PF198wXPPPUdycjLvvfceu3btIjY2lpw5c2Zyax99V69exc3NDavVquBVREREREREHhvp84V+/foRERGBu7s7N2/epGjRosydOxcvLy+mTJnCe++9x0svvcTZs2dJSkri0KFD2NvbK3j9E1WqVGH37t3UqlWLpUuXmjX/01PWIFlFti07cHf3//Q7tdatW9O8eXMWL15MYmIiDg4O9O7dm61bt7J48eL/uqmPJQ8PD6xWKzabTTtDEREREREReWyk5QtHjhxh586dbNq0ie3bt7Nr1y7s7e3x8/Pj3Llz9O/fn5CQEJ588knq1KljBq+pqakKXn9HWv/Bvn378txzzzF58mRy587N/foVKmuQrCJb9nxN3/0/IiKCvXv3AuDl5YW/vz8As2bNIjw8nLVr1+Lh4UFKSgqffvopb775pn7AIiIiIiIiIvK7wsLCiIqKwtXVlYULF+Lg4IDFYsFms1GhQgU8PT1Zt27dPeupt+Zfc/78eSpXrkzfvn0ZPHhwZjdH5A9ly56vacFrYGAgQUFBJCUl4eDgQJcuXRg2bBgAPXv2xNnZmd69ewN37ph07txZxZpFRERERERE5Hf9+uuvHD16lO+++44zZ87g6OiIxWLh9u3bWK1Whg8fzvHjxzl9+vQ96yp4/WsKFy7MkCFDmDRpEnFxcZndHJE/lC3DV4CNGzcSExNDTEwMs2bNonr16tjb21O0aFFzmXHjxnHt2jU+//zzDOtqZygiIiIiIiIicG9Zw5w5c/LWW2/RpUsXjhw5wqBBgwBwdnYGIEeOHNhsNpUW+JcaNWrEa6+9Zg6WLpJVZZsUMX2pAYD4+HhKlixJ9erVWbp0KR07dmTmzJl0796d69evExcXR8WKFbFYLKxYsYLatWtnYutFREREREREJKtJnzUcPHiQ69evU6RIEUqUKEH//v2x2WxERESQmJhIYGAgv/zyC9OnT6dYsWIUK1Ysk1v/aCtVqhTh4eFYLBZSU1Oxs7PL7CaJ3Fe26fmatjMMCwvjm2++wdnZmVy5chEREUHHjh2ZNGkS3bt3B2Dnzp3MmTMHi8XCiBEjOHv2LD/99FNmNl9EREREREREshDDMMysYejQobRs2ZIuXbpQs2ZN+vTpw5UrV+jTpw8dO3YkNDSU5557jvHjx+Pm5sa6devMQajln0vrPazgVbKyxz58Tb8jmzJlCkFBQTg7O1OgQAF2795N586dCQkJISAgAIBbt24xffp0cx1vb28++OADChQo8J+3XURERERERESyprTgb+rUqYSFhTF37lyOHTtGo0aNiIyM5OzZs+TNm5devXoxePBgihQpgoeHB4sWLcLZ2ZmEhIQMT+iKyOPpsS87kLYjO3LkCBcuXGDGjBk8//zzAAQHB9OzZ08uXrxIbGwsTzzxBOPHj+enn34iNjYWe3t7DMOgSJEiwJ27WqrJIiIiIiIiIiJpGcHOnTsZOHAgtWvXZsWKFSxatIhx48bh4+NDQkIC+fPnp0ePHgAsWrSIPHnyEBwcTI4cOTL5E4jIf+GxD18Nw2Djxo00aNCAXLlyUb16dXNeQEAAycnJREVFMWPGDLy8vMiTJw+7d+/G3t6elJSUDINrKXgVERERERERyZ7uHksG7jw9e/r0aQYOHMiOHTvo0KEDkyZNIiAggKSkJObMmYOXlxc1a9YkICAAOzs7Zs6ciYODgzkQl4g83h7L8DX9DtFisVC/fn2GDx9OSEgIX331FfXq1cPNzQ2APn360LZtW65du0auXLnImzcvFovlnuBVRERERERERLKv1NRUEhMTuXLlCp6entjZ2eHi4kLp0qXx8/Pj0qVLhIaG8sYbbwBw/fp1li5ditVqpUaNGhQsWJDOnTvj6OiIr69vJn8aEfmvWAzDMDK7EQ9LdHQ0jo6ONGvWDIAhQ4YwceJEZs2aRfv27XFxcbnveve7myUiIiIiIiIi2dP69etZvnw5q1at4saNG/j4+NC0aVO6devG/v376dq1KwkJCRw6dAiAK1eu0KFDB65fv84XX3yBnZ2dWaYgNTVVA0SJZCOPbfh66dIlfHx8KFmyJG+//TYNGzYEYODAgUybNo2PPvqIdu3a/W4AKyIiIiIiIiISFhbGe++9R+vWrSlQoADu7u7MmDGDy5cv0717d0JCQoiOjmbUqFFcvHiRUqVKkZycjM1m48svv8TBwUGBq0g29tg8V3/3YFj58uVjyZIlBAQEMHPmTAzDoFGjRkycOBGLxcJbb73FzZs36dGjB05OTpnYchERERERERHJimbPnk3fvn2JiIigZcuWODg4AFCnTh1Gjx7NRx99hKenJz179sTHx4eoqChsNhuenp60b98eOzs7lTUUyeYeu56vP/30EwUKFDBfHzp0iK5du5I3b1769u1LgwYNAOjevTvHjh1j69atGkhLRERERERERDJYvnw5LVq0YMWKFTRp0sQMUdN6sZ48eZKuXbty48YNVq5cScGCBe95D/V4FZFHvrCpzWYz//3RRx/RuXNn9u7da04rV64cc+bM4bvvvmPMmDGsW7cOgI8//tgMXh+z/FlERERERERE/oXExETWrVtHyZIl+f777wEyBK+GYVCqVCmGDBnCvn37OHny5H3fR8GriDzy4WvawFhXrlzB29ubgwcPMnXq1AwBbPny5RkzZgx79+5l9OjR7Nixw5x3d7kCEREREREREcnenJyceO+992jcuDHz589n/PjxwJ0wNX0nsBIlSuDo6MjNmzczq6kiksU9suHr4sWLWb16NQDvvvsuPXr0oGrVqkRGRrJ9+3YmT56cIYC12WzUr1+fsmXLUq1aNQAsFouCVxERERERERG5R8GCBRk8eDCVK1dm2bJlZgBrtVpJTU0F7pQ69Pb2pmzZspnZVBHJwh7J8DUxMZFNmzbRpEkTWrZsyezZswkKCgKgVq1azJs3jy+//JLJkyezbNkyLl++TFRUFPXq1SM0NBSr1ZrhTpWIiIiIiIiIyN08PT0ZOnToPQGsvb09N27cICwsjDJlylCkSJFMbqmIZFWP3IBbNpvNLDVQrlw54uLimD59Or179yY5ORk7OzusVivbt28nKCiIEydO4ODgQO7cufn6669xcHBQqQERERERERER+cvi4+MZPXo033zzDb6+vgwYMIBmzZpx5swZdu/ejb29vbIGEbmvRyp8Tb8ji4yM5IMPPqB06dIsXbqUpUuX0rhxY1JTUzEMA3t7e77//nt++OEHLl68SLNmzbCzszNHJxQRERERERER+avi4+MZM2YMe/bs4cSJE7i7u3P48GEcHBzMgbhERO72yKSQ6Xu8hoSEsGDBApYuXUqpUqXImzcvLVq0MAPYNCkpKdSsWdN8nZqaquBVRERERERERP42T09PgoKCGDRoEG5ubqxYsQIHBwd18hKRP/TI7B3SgtczZ85w6tQppk6dynPPPQfAqFGjsFgs+Pr6smDBAurXr0+nTp3Ily8foaGh5nvoLpSIiIiIiIiI/FOenp5MnToVNzc3rFarglcR+VOP1B5i3rx59OzZkxIlSvD222+b093d3Rk5ciSOjo74+vpSrlw5EhMTOXToUCa2VkREREREREQeNx4eHsCdJ3QVvIrIn3mkar4CvPLKK2zcuJGwsDA6dOhwz45u8+bNXLx4ET8/P9V4FRERERERERERkUyTZcPX9DVe71arVi3OnDlDZGQkPj4+WK3W+44qqILXIiIiIiIiIiIiklmyZPiaPnjds2cPN2/epFixYhQtWtQMU6tVq8bFixeJiIigevXqvxvAioiIiIiIiIiIiGSGLBe+pg9Qhw4dyvz587Gzs+Py5csMGzaMFi1aUKpUKQCqV6/O5cuXmTVrFnXr1lXwKiIiIiIiIiIiIlnG/Z/rz0RpAeqYMWMIDw9n3rx5nDp1itatWzNmzBjmzp3LyZMnAdi5cyc2m43Zs2creBUREREREREREZEsJUuORHXy5Em2b9/OtGnTqFu3LrGxsSxevJiXX36ZadOmkZqaSrdu3Xjqqac4ceIEqampmd1kERERERERERERkQyyXM9XAA8PD7p06ULDhg356quv6NWrFyNHjiQmJob27dsTHh7OtGnTOHv2LAB2dnYKYEVERERERERERCRLyfTw1Waz3TMtd+7c1KtXjyeeeIJFixbx0ksv0b17dwDc3NwoUqQI8fHxFClSxFwnbSAuERERERERERERkawgU8sO2Gw2rNY7+e/KlStJSEgAwM/PD3d3dwB++uknrFYriYmJODo6cvr0aaZMmULt2rWxWCwZBugSERERERERERERySoyLXw1DMMMXvv160dERATu7u7cvHmT8ePHM3fuXLy8vKhUqRLvvfce165d4+zZsyQlJVGjRg0FryIiIiIiIiIiIpKlZVr4mhaaHjlyhJ07d7Jp0yYKFChAUlISbdq0wc/Pjy1bttC/f38Mw+DMmTOULl2aSZMmYW9vT2pqqkoNiIiIiIiIiIiISJZlMQzDyKw/HhYWRlRUFK6urixcuBAHBwcsFgs2m40KFSrg6enJunXr7lkvJSUFe/tMrZggIiIiIiIiIiIi8ocybcCtX3/9laNHj/Ldd99x5swZHB0dsVgs3L59G6vVyvDhwzl+/DinT5++Z10FryIiIiIiIiIiIpLV/Wfhq81my/A6Z86cvPXWW3Tp0oUjR44waNAgAJydnQHIkSMHNptNNV1FRERERERERETkkfSfdCG12Wzm4FoHDx7k+vXrFClShBIlStC/f39sNhsREREkJiYSGBjIL7/8wvTp0ylWrBjFihX7L5ooIiIiIiIiIiIi8kA99JqvhmGYvVeHDh1KdHQ0VquVW7du0bRpUwIDA3FxcWHmzJmMGzcOZ2dnmjZtyu3btwkPD8fZ2TlDeCsiIiIiIiIiIiLyKHjoiWZa8Dp16lTCwsKYO3cux44do1GjRkRGRnL27Fny5s1Lr169GDx4MEWKFMHDw4NFixbh7OxMQkKCglcRERERERERERF55Dz0sgNpPV937tzJwIEDqV27NitWrGDRokWMGzcOHx8fEhISyJ8/Pz169ABg0aJF5MmTh+DgYHLkyPGwmygiIiIiIiIiIiLywD3w8PV+JQJu3brF6dOnGThwIDt27KBDhw5MmjSJgIAAkpKSmDNnDl5eXtSsWZOAgADs7OyYOXMmDg4O5kBcIiIiIiIiIiIiIo+SBx6+pqamkpiYyJUrV/D09MTOzg4XFxdKly6Nn58fly5dIjQ0lDfeeAOA69evs3TpUqxWKzVq1KBgwYJ07twZR0dHfH19H3TzRERERERERERERP4TD3TArfXr17N8+XJWrVrFjRs38PHxoWnTpnTr1o39+/fTtWtXEhISOHToEABXrlyhQ4cOXL9+nS+++AI7OzuzTEFqaip2dnYPqmkiIiIiIiIiIiIi/6kHFr6GhYXx3nvv0bp1awoUKIC7uzszZszg8uXLdO/enZCQEKKjoxk1ahQXL16kVKlSJCcnY7PZ+PLLL3FwcFDgKiIiIiIiIiIiIo+NB1J2YPbs2fTt25eIiAhatmyJg4MDAHXq1GH06NF89NFHeHp60rNnT3x8fIiKisJms+Hp6Un79u2xs7MjJSUFe/uHPv6XiIiIiIiIiIiIyH/iX/d8Xb58OS1atGDFihU0adLEDFHTerGePHmSrl27cuPGDVauXEnBggXveQ/1eBUREREREREREZHHjfXfrJyYmMi6desoWbIk33//PUCG4NUwDEqVKsWQIUPYt28fJ0+evO/7KHgVERERERERERGRx82/es7fycmJ9957DycnJ+bPn8/NmzcZNGgQdnZ22Gw2LBYLACVKlMDR0ZGbN28+kEaLiIiIiIiIiIiIZHX/qucrQMGCBRk8eDCVK1dm2bJljB8//s4bW62kpqYCcOjQIby9vSlbtuy//XMiIiIiIiIiIiIij4R/Hb4CeHp6MnTo0HsCWHt7e27cuEFYWBhlypShSJEiD+LPiYiIiIiIiIiIiGR5/3rArfTi4+MZPXo033zzDb6+vgwYMIBmzZpx5swZdu/ejb29PYZhmOUIRERERERERERERB5XDzR8hTsB7JgxY9izZw8nTpzA3d2dw4cP4+DgYA7EJSIiIiIiIiIiIvK4e+DhK9wJYAcNGsSlS5dYsWIFDg4OpKSkYG//r8b3EhEREREREREREXlkPJTwFeDq1au4ublhtVoVvIqIiIiIiIiIiEi289DC1zQ2mw2r9YGM6yUiIiIiIiIiIiLyyHjo4auIiIiIiIiIiIhIdqQuqSIiIiIiIiIiIiIPgcJXERERERERERERkYdA4auIiIiIiIiIiIjIQ6DwVUREREREREREROQhUPgqIiIiIiIiIiIi8hAofBURERERERERERF5CBS+ioiIiIj8Rzp16oTFYuHMmTOZ3RQRERER+Q8ofBURERGRR9aZM2ewWCxYLBYKFy5MamrqfZc7dOiQuVyZMmX+8d97//33sVgsbN269R+/h4iIiIhkHwpfRUREROSRZ29vz4ULF1i3bt1953/yySfY29v/x62619ixYzly5AiFCxfO7KaIiIiIyH9A4auIiIiIPPKqV6+Om5sbYWFh98xLSkoiMjKSRo0aZULLMipYsCBlypTBwcEhs5siIiIiIv8Bha8iIiIi8shzdnamdevWrFy5ksuXL2eYFxsby+XLl/H397/vuoZhEBYWho+PD7ly5cLFxYVKlSrdE+S+9NJLhISEAFCnTh2zjEGJEiXMZUqUKEGJEiW4du0affv2pWjRotjb2xMeHg78cc3Xbdu20bx5cwoUKICTkxNFixalRYsWbN++/Z9vGBERERHJVJn/7JWIiIiIyAPQuXNnPv74YyIjI3n77bfN6WFhYeTPn5/GjRvfs45hGHTo0IEFCxbw9NNP065dOxwdHdmwYQNdunQhLi6OSZMmAXeCU4DPP/+cjh07mqGru7t7hvdMTEykbt263LhxgyZNmuDo6EiBAgX+sO0ffvghb731Fs7OzjRv3pxixYpx/vx5tm/fzuLFi6lRo8Y/3zAiIiIikmkUvoqIiIjIY6Fq1ao899xzhIWFmeHr+fPnWb9+Pe+88859a77OnTuXBQsW0KVLF0JDQ81lkpKS8PX1ZfLkybRt2xZvb286derEmTNn+Pzzz+nUqRMvvfTSfdsRHx9P+fLl2bFjB87Ozn/a7kOHDvH2229TsGBBduzYkaEnrWEY/Pjjj39/Y4iIiIhIlqCyAyIiIiLy2PD39+fgwYPs2bMHgPDwcFJTU+ncufN9l585cyZPPPEEM2fOzBDOOjo6Mnr0aACioqL+djsmTpz4l4JXgNDQUFJTUxk1alSG4BXAYrFQqFChv/33RURERCRrUM9XEREREXlsvPHGGwwZMoSwsDC8vb0JDw+natWqlC1b9p5lb926xaFDhyhUqBDjxo27Z35ycjIAR48e/VttyJEjB+XKlfvLy3/99dcAvPLKK3/r74iIiIhI1qfwVUREREQeG/nz56dRo0ZERUXx+uuvc+LECQYMGHDfZa9evYphGJw/f94cSOt+bt68+bfbYLFY/vLy165dw2KxULBgwb/1d0REREQk61PZARERERF5rHTu3JmrV6/SpUsXnJ2dadu27X2Xy5UrFwDe3t4YhvG7/23ZsuVv/f2/E7zCnQG7VNtVRERE5PGk8FVEREREHiuNGjXC09OT8+fP07JlSzNkvZurqyvPPvssR44c4dq1a3/pve3s7ABITU19UM2lSpUqAKxfv/6BvaeIiIiIZA0KX0VERETksWJvb09sbCzLli0zB836PX379uXWrVt069btvuUFTp8+zZkzZ8zXuXPnBuDcuXMPrL09evTAzs6O4OBgvv/++wzz1CNWRERE5NGmmq8iIiIi8tipXLkylStX/tPlAgIC+Oqrr4iIiGDHjh28/PLLFCpUiJ9++omjR4+ya9cuFixYQIkSJQCoU6cOFouFoUOHcvToUdzc3HBzc6Nnz57/uK3lypVj6tSp9O3bl+eee45mzZpRvHhx4uPj+eKLL3jttdeYOnXqP35/EREREck8Cl9FREREJNuyWCyEh4fTqFEj5syZw6pVq/j111/Jnz8/Tz31FJMmTeLll182ly9btizz5s1j8uTJfPDBByQmJlK8ePF/Fb4C9OnTh+eff57JkyezZs0asw1Vq1alVatW//ZjioiIiEgmsRiGYWR2I0REREREREREREQeN6r5KiIiIiIiIiIiIvIQKHwVEREREREREREReQgUvoqIiIiIiIiIiIg8BApfRURERERERERERB4Cha8iIiIiIiIiIiIiD4HCVxEREREREREREZGHQOGriIiIiIiIiIiIyEOg8FVERERERERERETkIVD4KiIiIiIiIiIiIvIQKHwVEREREREREREReQgUvoqIiIiIiIiIiIg8BApfRURERERERERERB4Cha8iIiIiIiIiIiIiD8H/A54f05utg+bNAAAAAElFTkSuQmCC", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. Initialize Lists for Storing Results ---\n", - "metric_names = []\n", - "p_values = []\n", - "is_significant = []\n", - "alpha = 0.05 # Significance level\n", - "\n", - "# --- 2. Iterate, Test, and Collect Results ---\n", - "for col in metric_columns:\n", - " # Safely convert to numeric and drop NaNs for both comparison groups\n", - " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", - " df_1_data = pd.to_numeric(dfDisatisfied[col], errors='coerce').dropna()\n", - " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", - " \n", - " # Skip if groups are too small or empty after cleaning\n", - " if df_1_data.size < 2 or df_2_data.size < 2:\n", - " print(f\"Skipping {col}: Insufficient data.\")\n", - " continue\n", - "\n", - " # Perform Welch's T-Test\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1_data,\n", - " b=df_2_data,\n", - " equal_var=False\n", - " )\n", - "\n", - " # Store results in the lists\n", - " metric_names.append(col)\n", - " p_values.append(p_value)\n", - " is_significant.append(p_value <= alpha)\n", - "\n", - " # --- Output the Results (Optional, as requested) ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", - " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)\n", - "\n", - "# --- 3. Create DataFrame for Plotting ---\n", - "p_values_df = pd.DataFrame({\n", - " 'Metric': metric_names,\n", - " 'P_Value': p_values,\n", - " 'Is_Significant': is_significant\n", - "})\n", - "\n", - "# # Sort the results by P-Value for a cleaner chart\n", - "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", - "\n", - "# --- 4. Plot the P-Values ---\n", - "\n", - "# Define colors for bars based on significance\n", - "# --- Define the mapping dictionary ---\n", - "# Create the dictionary that maps the unique hue values (True/False) to colors\n", - "palette_map = {\n", - " True: 'darkred', # For bars where Is_Significant is True\n", - " False: 'skyblue' # For bars where Is_Significant is False\n", - "}\n", - "\n", - "plt.figure(figsize=(14, 8))\n", - "ax = sns.barplot(\n", - " data=p_values_df,\n", - " x='Metric',\n", - " y='P_Value',\n", - " hue='Is_Significant',\n", - " palette=palette_map, # <-- FIX: Pass the dictionary here\n", - " dodge=False,\n", - ")\n", - "# Add horizontal line at p=0.05\n", - "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", - "\n", - "# --- Custom Legend ---\n", - "from matplotlib.patches import Patch\n", - "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", - "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", - "final_handles = custom_handles + [significance_line]\n", - "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", - "\n", - "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", - "ax.get_legend().remove() \n", - "\n", - "# --- Formatting ---\n", - "plt.title('P-Values from T-Tests for only Disatisfied vs Disatisfied disloyal customers', fontsize=16)\n", - "plt.ylabel('P-Value', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 1.0)\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "customer_type_counts = df['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on the entire population')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on Disatisfied customers')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on Satisfied customers')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6dead254-560d-4364-a3c9-9df02a5b10db", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "494e2a2d-1913-437d-91e9-d6ef9a3211df", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "962aad69-b985-4ff3-ab06-a854e251135b", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:23: SettingWithCopyWarning: \n", - "A value is trying to be set on a copy of a slice from a DataFrame.\n", - "Try using .loc[row_indexer,col_indexer] = value instead\n", - "\n", - "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", - " dfDisatisfied['Flight Distance_group'] = np.select(\n", - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\1622061771.py:46: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", - "\n", - "# --- Define the Conditions ---\n", - "# Assuming you are applying this logic to the dfDisatisfied DataFrame\n", - "conditions = [\n", - " (dfDisatisfied['Flight Distance'] < 750),\n", - " (dfDisatisfied['Flight Distance'] >= 750) & (dfDisatisfied['Flight Distance'] < 1500),\n", - " (dfDisatisfied['Flight Distance'] >= 1500) & (dfDisatisfied['Flight Distance'] < 2250),\n", - " (dfDisatisfied['Flight Distance'] >= 2250) & (dfDisatisfied['Flight Distance'] < 3000),\n", - " (dfDisatisfied['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# --- Define the Corresponding Labels and Order ---\n", - "distance_labels = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# Apply np.select() to create the grouping column\n", - "dfDisatisfied['Flight Distance_group'] = np.select(\n", - " conditions, \n", - " distance_labels, \n", - " default='Unknown'\n", - ")\n", - "\n", - "# --- 2. AUTOMATIC DATA AGGREGATION & PERCENTAGE CALCULATION ---\n", - "\n", - "# Get the count of each Flight Distance group\n", - "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts)\n", - "df_counts = distance_group_counts_series.reset_index()\n", - "df_counts.columns = ['Flight Distance Group', 'Count']\n", - "\n", - "# Calculate Percentage\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART WITH ANNOTATIONS ---\n", - "plt.figure(figsize=(12, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Flight Distance Group',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " order=distance_labels, # Ensures the groups plot in logical order\n", - " palette='magma'\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", - "plt.xlabel('Flight Distance Group')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit to ensure annotations are visible\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.20)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart_final.png')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "8d11c378-2b5c-47b1-97e0-c611056739ec", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\2556283244.py:21: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", - "# Get the count of each Gender from the dfDisatisfied DataFrame\n", - "gender_counts_series = dfDisatisfied['Gender'].value_counts()\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts)\n", - "df_counts = gender_counts_series.reset_index()\n", - "df_counts.columns = ['Gender', 'Count']\n", - "\n", - "# Sort the data by count (or percentage) before plotting\n", - "df_counts = df_counts.sort_values(by='Count', ascending=False)\n", - "\n", - "\n", - "# --- 2. CALCULATE PERCENTAGE ---\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART ---\n", - "plt.figure(figsize=(8, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Gender',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " # Order is naturally handled by the prior sorting of df_counts\n", - " palette='Set2' # Used a different palette (Set2)\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Gender')\n", - "plt.xlabel('Gender')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=0, ha='center') # No rotation needed\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit for the annotations\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_gender_percentage_bar_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "27ee32c2-d244-4497-aafc-0232278b4ed0", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_33992\\783172777.py:23: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", - "# Get the count of each age group from the dfDisatisfied DataFrame\n", - "age_group_counts_series = dfDisatisfied['age groups'].value_counts()\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts) for plotting\n", - "df_counts = age_group_counts_series.reset_index()\n", - "df_counts.columns = ['Age Group', 'Count']\n", - "\n", - "\n", - "# --- 2. CALCULATE PERCENTAGE ---\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "# Optional: Ensure all groups are present, even if count is 0,\n", - "# and ensure they are properly ordered by the chronological order of ages.\n", - "# We will use the 'order' parameter in sns.barplot for this.\n", - "age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART ---\n", - "plt.figure(figsize=(10, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Age Group',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " order=age_order, # Use the defined chronological order\n", - " palette='viridis'\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Age Group (Chronological Order)')\n", - "plt.xlabel('Age Group')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=45, ha='right')\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit for the annotations\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", - "plt.show() # Use plt.show() if running in a script/local environment" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:base] *", - "language": "python", - "name": "conda-base-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 7bea4d62db24633fd578be0dad5942653bd3eef5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ant=C3=B3nio=20Bianchi=20Galv=C3=A3o?= Date: Wed, 10 Dec 2025 18:27:07 +0100 Subject: [PATCH 18/26] Delete notebooks/Airline_Project1_Antonio.ipynb --- notebooks/Airline_Project1_Antonio.ipynb | 2548 ---------------------- 1 file changed, 2548 deletions(-) delete mode 100644 notebooks/Airline_Project1_Antonio.ipynb diff --git a/notebooks/Airline_Project1_Antonio.ipynb b/notebooks/Airline_Project1_Antonio.ipynb deleted file mode 100644 index b5ba7356..00000000 --- a/notebooks/Airline_Project1_Antonio.ipynb +++ /dev/null @@ -1,2548 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "561808a4-27ef-4523-892a-8584a31efefa", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
0070172MaleLoyal Customer13Personal TravelEco Plus46034...54344552518.0neutral or dissatisfied
115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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103904 rows × 25 columns

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" - ], - "text/plain": [ - " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", - "0 0 70172 Male Loyal Customer 13 Personal Travel \n", - "1 1 5047 Male disloyal Customer 25 Business travel \n", - "2 2 110028 Female Loyal Customer 26 Business travel \n", - "3 3 24026 Female Loyal Customer 25 Business travel \n", - "4 4 119299 Male Loyal Customer 61 Business travel \n", - "... ... ... ... ... ... ... \n", - "103899 103899 94171 Female disloyal Customer 23 Business travel \n", - "103900 103900 73097 Male Loyal Customer 49 Business travel \n", - "103901 103901 68825 Male disloyal Customer 30 Business travel \n", - "103902 103902 54173 Female disloyal Customer 22 Business travel \n", - "103903 103903 62567 Male Loyal Customer 27 Business travel \n", - "\n", - " Class Flight Distance Inflight wifi service \\\n", - "0 Eco Plus 460 3 \n", - "1 Business 235 3 \n", - "2 Business 1142 2 \n", - "3 Business 562 2 \n", - "4 Business 214 3 \n", - "... ... ... ... \n", - "103899 Eco 192 2 \n", - "103900 Business 2347 4 \n", - "103901 Business 1995 1 \n", - "103902 Eco 1000 1 \n", - "103903 Business 1723 1 \n", - "\n", - " Departure/Arrival time convenient ... Inflight entertainment \\\n", - "0 4 ... 5 \n", - "1 2 ... 1 \n", - "2 2 ... 5 \n", - "3 5 ... 2 \n", - "4 3 ... 3 \n", - "... ... ... ... \n", - "103899 1 ... 2 \n", - "103900 4 ... 5 \n", - "103901 1 ... 4 \n", - "103902 1 ... 1 \n", - "103903 3 ... 1 \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "0 4 3 4 4 \n", - "1 1 5 3 1 \n", - "2 4 3 4 4 \n", - "3 2 5 3 1 \n", - "4 3 4 4 3 \n", - "... ... ... ... ... \n", - "103899 3 1 4 2 \n", - "103900 5 5 5 5 \n", - "103901 3 2 4 5 \n", - "103902 4 5 1 5 \n", - "103903 1 1 4 4 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "0 5 5 25 \n", - "1 4 1 1 \n", - "2 4 5 0 \n", - "3 4 2 11 \n", - "4 3 3 0 \n", - "... ... ... ... \n", - "103899 3 2 3 \n", - "103900 5 4 0 \n", - "103901 5 4 7 \n", - "103902 4 1 0 \n", - "103903 3 1 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction \n", - "0 18.0 neutral or dissatisfied \n", - "1 6.0 neutral or dissatisfied \n", - "2 0.0 satisfied \n", - "3 9.0 neutral or dissatisfied \n", - "4 0.0 satisfied \n", - "... ... ... \n", - "103899 0.0 neutral or dissatisfied \n", - "103900 0.0 satisfied \n", - "103901 14.0 neutral or dissatisfied \n", - "103902 0.0 neutral or dissatisfied \n", - "103903 0.0 neutral or dissatisfied \n", - "\n", - "[103904 rows x 25 columns]" - ] - }, - "execution_count": 1, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "import pandas as pd\n", - "import numpy as np\n", - "from scipy import stats\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "import matplotlib.pyplot as plt\n", - "\n", - "df=pd.read_csv('train.csv')\n", - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a86604ec-da44-40c0-894e-0a118b9ca685", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Age Group creation successful.\n", - "Flight distance group Group creation successful.\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_21412\\25427188.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n", - " df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n" - ] - } - ], - "source": [ - "binary_change= {\n", - " 'satisfied': 1,\n", - " 'neutral or dissatisfied': 0,\n", - "}\n", - "\n", - "df['satisfaction_binary'] = df['satisfaction'].replace(binary_change)\n", - "df.drop(columns=['Unnamed: 0'], inplace=True)\n", - "\n", - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Age'] < 18),\n", - " (df['Age'] >= 18) & (df['Age'] < 30),\n", - " (df['Age'] >= 30) & (df['Age'] < 40),\n", - " (df['Age'] >= 40) & (df['Age'] < 50),\n", - " (df['Age'] >= 50) & (df['Age'] < 60),\n", - " (df['Age'] >= 60) & (df['Age'] < 70),\n", - " (df['Age'] >= 70)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Minor',\n", - " '18 to 30',\n", - " '30 to 40',\n", - " '40 to 50',\n", - " '50 to 60',\n", - " '60 to 70',\n", - " '70 +'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Age Group creation successful.\")\n", - "\n", - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Flight Distance'] < 750),\n", - " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", - " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", - " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", - " (df['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Flight distance group Group creation successful.\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "d113003b-b385-4d24-a8a7-fade2501e0c2", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online booking...Baggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfactionsatisfaction_binaryage groupsFlight Distance_group
070172MaleLoyal Customer13Personal TravelEco Plus460343...44552518.0neutral or dissatisfied0MinorShort, until 750 miles
15047Maledisloyal Customer25Business travelBusiness235323...314116.0neutral or dissatisfied018 to 30Short, until 750 miles
2110028FemaleLoyal Customer26Business travelBusiness1142222...444500.0satisfied118 to 30Medium-short, until 1500 miles
324026FemaleLoyal Customer25Business travelBusiness562255...3142119.0neutral or dissatisfied018 to 30Short, until 750 miles
4119299MaleLoyal Customer61Business travelBusiness214333...433300.0satisfied160 to 70Short, until 750 miles
..................................................................
10389994171Femaledisloyal Customer23Business travelEco192212...423230.0neutral or dissatisfied018 to 30Short, until 750 miles
10390073097MaleLoyal Customer49Business travelBusiness2347444...555400.0satisfied140 to 50Long, until 3000 miles
10390168825Maledisloyal Customer30Business travelBusiness1995111...4554714.0neutral or dissatisfied030 to 40Medium-Long, until 2250 miles
10390254173Femaledisloyal Customer22Business travelEco1000111...154100.0neutral or dissatisfied018 to 30Medium-short, until 1500 miles
10390362567MaleLoyal Customer27Business travelBusiness1723133...443100.0neutral or dissatisfied018 to 30Medium-Long, until 2250 miles
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103904 rows × 27 columns

\n", - "
" - ], - "text/plain": [ - " id Gender Customer Type Age Type of Travel Class \\\n", - "0 70172 Male Loyal Customer 13 Personal Travel Eco Plus \n", - "1 5047 Male disloyal Customer 25 Business travel Business \n", - "2 110028 Female Loyal Customer 26 Business travel Business \n", - "3 24026 Female Loyal Customer 25 Business travel Business \n", - "4 119299 Male Loyal Customer 61 Business travel Business \n", - "... ... ... ... ... ... ... \n", - "103899 94171 Female disloyal Customer 23 Business travel Eco \n", - "103900 73097 Male Loyal Customer 49 Business travel Business \n", - "103901 68825 Male disloyal Customer 30 Business travel Business \n", - "103902 54173 Female disloyal Customer 22 Business travel Eco \n", - "103903 62567 Male Loyal Customer 27 Business travel Business \n", - "\n", - " Flight Distance Inflight wifi service \\\n", - "0 460 3 \n", - "1 235 3 \n", - "2 1142 2 \n", - "3 562 2 \n", - "4 214 3 \n", - "... ... ... \n", - "103899 192 2 \n", - "103900 2347 4 \n", - "103901 1995 1 \n", - "103902 1000 1 \n", - "103903 1723 1 \n", - "\n", - " Departure/Arrival time convenient Ease of Online booking ... \\\n", - "0 4 3 ... \n", - "1 2 3 ... \n", - "2 2 2 ... \n", - "3 5 5 ... \n", - "4 3 3 ... \n", - "... ... ... ... \n", - "103899 1 2 ... \n", - "103900 4 4 ... \n", - "103901 1 1 ... \n", - "103902 1 1 ... \n", - "103903 3 3 ... \n", - "\n", - " Baggage handling Checkin service Inflight service Cleanliness \\\n", - "0 4 4 5 5 \n", - "1 3 1 4 1 \n", - "2 4 4 4 5 \n", - "3 3 1 4 2 \n", - "4 4 3 3 3 \n", - "... ... ... ... ... \n", - "103899 4 2 3 2 \n", - "103900 5 5 5 4 \n", - "103901 4 5 5 4 \n", - "103902 1 5 4 1 \n", - "103903 4 4 3 1 \n", - "\n", - " Departure Delay in Minutes Arrival Delay in Minutes \\\n", - "0 25 18.0 \n", - "1 1 6.0 \n", - "2 0 0.0 \n", - "3 11 9.0 \n", - "4 0 0.0 \n", - "... ... ... \n", - "103899 3 0.0 \n", - "103900 0 0.0 \n", - "103901 7 14.0 \n", - "103902 0 0.0 \n", - "103903 0 0.0 \n", - "\n", - " satisfaction satisfaction_binary age groups \\\n", - "0 neutral or dissatisfied 0 Minor \n", - "1 neutral or dissatisfied 0 18 to 30 \n", - "2 satisfied 1 18 to 30 \n", - "3 neutral or dissatisfied 0 18 to 30 \n", - "4 satisfied 1 60 to 70 \n", - "... ... ... ... \n", - "103899 neutral or dissatisfied 0 18 to 30 \n", - "103900 satisfied 1 40 to 50 \n", - "103901 neutral or dissatisfied 0 30 to 40 \n", - "103902 neutral or dissatisfied 0 18 to 30 \n", - "103903 neutral or dissatisfied 0 18 to 30 \n", - "\n", - " Flight Distance_group \n", - "0 Short, until 750 miles \n", - "1 Short, until 750 miles \n", - "2 Medium-short, until 1500 miles \n", - "3 Short, until 750 miles \n", - "4 Short, until 750 miles \n", - "... ... \n", - "103899 Short, until 750 miles \n", - "103900 Long, until 3000 miles \n", - "103901 Medium-Long, until 2250 miles \n", - "103902 Medium-short, until 1500 miles \n", - "103903 Medium-Long, until 2250 miles \n", - "\n", - "[103904 rows x 27 columns]" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "45c65011-e822-4684-bc5d-b394ba4aafea", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "satisfaction\n", - "neutral or dissatisfied 58879\n", - "satisfied 45025\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df['satisfaction'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "caaec0b4-342d-4c69-ba35-41553e791c96", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Customer Type\n", - "Loyal Customer 84923\n", - "disloyal Customer 18981\n", - "Name: count, dtype: int64" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "6f945079-4c90-40ee-83b9-53af53e43388", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied=df[df['satisfaction_binary'] == 1]\n", - "dfDisatisfied=df[df['satisfaction_binary'] == 0]" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "6abbfb4e-11bc-43d4-80e5-99626252e77b", - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "unsupported operand type(s) for /: 'str' and 'int'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[7], line 49\u001b[0m\n\u001b[0;32m 46\u001b[0m \u001b[38;5;28;01mcontinue\u001b[39;00m\n\u001b[0;32m 48\u001b[0m \u001b[38;5;66;03m# 3b. Perform Welch's T-Test (equal_var=False)\u001b[39;00m\n\u001b[1;32m---> 49\u001b[0m t_stat, p_value \u001b[38;5;241m=\u001b[39m stats\u001b[38;5;241m.\u001b[39mttest_ind(\n\u001b[0;32m 50\u001b[0m a\u001b[38;5;241m=\u001b[39mdata_sat,\n\u001b[0;32m 51\u001b[0m b\u001b[38;5;241m=\u001b[39mdata_dis,\n\u001b[0;32m 52\u001b[0m equal_var\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m 53\u001b[0m )\n\u001b[0;32m 55\u001b[0m \u001b[38;5;66;03m# 3c. Store Results\u001b[39;00m\n\u001b[0;32m 56\u001b[0m is_significant \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mYes (Reject H0)\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m p_value \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0.05\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mNo (Fail to Reject H0)\u001b[39m\u001b[38;5;124m'\u001b[39m\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\_lib\\deprecation.py:234\u001b[0m, in \u001b[0;36m_deprecate_positional_args.._inner_deprecate_positional_args..inner_f\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m extra_args \u001b[38;5;241m<\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 233\u001b[0m warn_deprecated_args(kwargs)\n\u001b[1;32m--> 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m f(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m 236\u001b[0m \u001b[38;5;66;03m# extra_args > 0\u001b[39;00m\n\u001b[0;32m 237\u001b[0m kwonly_extra_args \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mset\u001b[39m(kwonly_args[:extra_args]) \u001b[38;5;241m-\u001b[39m deprecated_args\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_axis_nan_policy.py:586\u001b[0m, in \u001b[0;36m_axis_nan_policy_factory..axis_nan_policy_decorator..axis_nan_policy_wrapper\u001b[1;34m(***failed resolving arguments***)\u001b[0m\n\u001b[0;32m 583\u001b[0m res \u001b[38;5;241m=\u001b[39m _add_reduced_axes(res, reduced_axes, keepdims)\n\u001b[0;32m 584\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m tuple_to_result(\u001b[38;5;241m*\u001b[39mres)\n\u001b[1;32m--> 586\u001b[0m res \u001b[38;5;241m=\u001b[39m hypotest_fun_out(\u001b[38;5;241m*\u001b[39msamples, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwds)\n\u001b[0;32m 587\u001b[0m res \u001b[38;5;241m=\u001b[39m result_to_tuple(res, n_out)\n\u001b[0;32m 588\u001b[0m res \u001b[38;5;241m=\u001b[39m _add_reduced_axes(res, reduced_axes, keepdims)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:6679\u001b[0m, in \u001b[0;36mttest_ind\u001b[1;34m(a, b, axis, equal_var, nan_policy, permutations, random_state, alternative, trim, method)\u001b[0m\n\u001b[0;32m 6677\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m trim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 6678\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m np\u001b[38;5;241m.\u001b[39merrstate(divide\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m, invalid\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mignore\u001b[39m\u001b[38;5;124m'\u001b[39m):\n\u001b[1;32m-> 6679\u001b[0m v1 \u001b[38;5;241m=\u001b[39m _var(a, axis, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 6680\u001b[0m v2 \u001b[38;5;241m=\u001b[39m _var(b, axis, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m1\u001b[39m, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 6682\u001b[0m m1 \u001b[38;5;241m=\u001b[39m xp\u001b[38;5;241m.\u001b[39mmean(a, axis\u001b[38;5;241m=\u001b[39maxis)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:1211\u001b[0m, in \u001b[0;36m_var\u001b[1;34m(x, axis, ddof, mean, xp)\u001b[0m\n\u001b[0;32m 1208\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21m_var\u001b[39m(x, axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, ddof\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, mean\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, xp\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m):\n\u001b[0;32m 1209\u001b[0m \u001b[38;5;66;03m# Calculate variance of sample, warning if precision is lost\u001b[39;00m\n\u001b[0;32m 1210\u001b[0m xp \u001b[38;5;241m=\u001b[39m array_namespace(x) \u001b[38;5;28;01mif\u001b[39;00m xp \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m xp\n\u001b[1;32m-> 1211\u001b[0m var \u001b[38;5;241m=\u001b[39m _moment(x, \u001b[38;5;241m2\u001b[39m, axis, mean\u001b[38;5;241m=\u001b[39mmean, xp\u001b[38;5;241m=\u001b[39mxp)\n\u001b[0;32m 1212\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m ddof \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m 1213\u001b[0m n \u001b[38;5;241m=\u001b[39m x\u001b[38;5;241m.\u001b[39mshape[axis] \u001b[38;5;28;01mif\u001b[39;00m axis \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m xp_size(x)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\scipy\\stats\\_stats_py.py:1190\u001b[0m, in \u001b[0;36m_moment\u001b[1;34m(a, order, axis, mean, xp)\u001b[0m\n\u001b[0;32m 1187\u001b[0m n_list\u001b[38;5;241m.\u001b[39mappend(current_n)\n\u001b[0;32m 1189\u001b[0m \u001b[38;5;66;03m# Starting point for exponentiation by squares\u001b[39;00m\n\u001b[1;32m-> 1190\u001b[0m mean \u001b[38;5;241m=\u001b[39m (xp\u001b[38;5;241m.\u001b[39mmean(a, axis\u001b[38;5;241m=\u001b[39maxis, keepdims\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m) \u001b[38;5;28;01mif\u001b[39;00m mean \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m 1191\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m xp\u001b[38;5;241m.\u001b[39masarray(mean, dtype\u001b[38;5;241m=\u001b[39mdtype))\n\u001b[0;32m 1192\u001b[0m mean \u001b[38;5;241m=\u001b[39m mean[()] \u001b[38;5;28;01mif\u001b[39;00m mean\u001b[38;5;241m.\u001b[39mndim \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m mean\n\u001b[0;32m 1193\u001b[0m a_zero_mean \u001b[38;5;241m=\u001b[39m _demean(a, mean, axis, xp\u001b[38;5;241m=\u001b[39mxp)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\numpy\\_core\\fromnumeric.py:3904\u001b[0m, in \u001b[0;36mmean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m 3901\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 3902\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m mean(axis\u001b[38;5;241m=\u001b[39maxis, dtype\u001b[38;5;241m=\u001b[39mdtype, out\u001b[38;5;241m=\u001b[39mout, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m-> 3904\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m _methods\u001b[38;5;241m.\u001b[39m_mean(a, axis\u001b[38;5;241m=\u001b[39maxis, dtype\u001b[38;5;241m=\u001b[39mdtype,\n\u001b[0;32m 3905\u001b[0m out\u001b[38;5;241m=\u001b[39mout, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n", - "File \u001b[1;32m~\\anaconda3\\Lib\\site-packages\\numpy\\_core\\_methods.py:139\u001b[0m, in \u001b[0;36m_mean\u001b[1;34m(a, axis, dtype, out, keepdims, where)\u001b[0m\n\u001b[0;32m 137\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, mu\u001b[38;5;241m.\u001b[39mndarray):\n\u001b[0;32m 138\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m _no_nep50_warning():\n\u001b[1;32m--> 139\u001b[0m ret \u001b[38;5;241m=\u001b[39m um\u001b[38;5;241m.\u001b[39mtrue_divide(\n\u001b[0;32m 140\u001b[0m ret, rcount, out\u001b[38;5;241m=\u001b[39mret, casting\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124munsafe\u001b[39m\u001b[38;5;124m'\u001b[39m, subok\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m 141\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m is_float16_result \u001b[38;5;129;01mand\u001b[39;00m out \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 142\u001b[0m ret \u001b[38;5;241m=\u001b[39m arr\u001b[38;5;241m.\u001b[39mdtype\u001b[38;5;241m.\u001b[39mtype(ret)\n", - "\u001b[1;31mTypeError\u001b[0m: unsupported operand type(s) for /: 'str' and 'int'" - ] - } - ], - "source": [ - "# --- 1. Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", - "\n", - "metric_columns = [\n", - " 'Type of Travel',\n", - " 'Class',\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "# --- 2. Initialize a Dictionary to Store Results ---\n", - "results = {\n", - " 'Metric': [],\n", - " 'Mean_Satisfied': [],\n", - " 'Mean_Dissatisfied': [],\n", - " 'T_Statistic': [],\n", - " 'P_Value': [],\n", - " 'Significance (α=0.05)': []\n", - "}\n", - "\n", - "# --- 3. Loop Through Columns and Perform T-Test ---\n", - "for col in metric_columns:\n", - " # 3a. Isolate and clean data for the current column\n", - " data_sat = dfSatisfied[col].dropna()\n", - " data_dis = dfDisatisfied[col].dropna()\n", - "\n", - " # Skip if one of the groups has no data\n", - " if len(data_sat) == 0 or len(data_dis) == 0:\n", - " continue\n", - "\n", - " # 3b. Perform Welch's T-Test (equal_var=False)\n", - " t_stat, p_value = stats.ttest_ind(\n", - " a=data_sat,\n", - " b=data_dis,\n", - " equal_var=False\n", - " )\n", - "\n", - " # 3c. Store Results\n", - " is_significant = 'Yes (Reject H0)' if p_value <= 0.05 else 'No (Fail to Reject H0)'\n", - "\n", - " results['Metric'].append(col)\n", - " results['Mean_Satisfied'].append(data_sat.mean())\n", - " results['Mean_Dissatisfied'].append(data_dis.mean())\n", - " results['T_Statistic'].append(t_stat)\n", - " results['P_Value'].append(p_value)\n", - " results['Significance (α=0.05)'].append(is_significant)\n", - "\n", - "# --- 4. Convert Results Dictionary to a DataFrame ---\n", - "results_df = pd.DataFrame(results)\n", - "\n", - "# --- 5. Print/Display Results ---\n", - "print(results_df.round(4))" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3e5ecb36-ada2-4925-9e0d-2ae0996881c7", - "metadata": {}, - "outputs": [], - "source": [ - "list(df)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "247db4d7-3a0d-4c98-ab26-f537b049e252", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "148a480d-158c-4ed5-b379-4b1b2d20a3a5", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9864a901-c3c9-4d41-ad57-d6f382d976c3", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied_disloyal.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "72c0cdfb-e081-478f-8977-85779113cd4f", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "482baa0f-d3f0-481d-8d49-07e942e68d87", - "metadata": {}, - "outputs": [], - "source": [ - "numeric_cols_df = df.select_dtypes(include=np.number)\n", - "\n", - "# Exclude 'id' and any other non-metric numeric columns (like Age)\n", - "metrics_to_analyze = [\n", - " 'Flight Distance',\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " 'Age' # Including age as a numeric metric to analyze\n", - "]\n", - "\n", - "# Filter down to the columns that actually exist and are numeric\n", - "analysis_cols = [col for col in metrics_to_analyze if col in numeric_cols_df.columns]\n", - "\n", - "# --- 2. Melt the DataFrame ---\n", - "df_melted = df.melt(\n", - " id_vars=['satisfaction'],\n", - " value_vars=analysis_cols,\n", - " var_name='Metric', # This column now holds the name of the original column\n", - " value_name='Value' # This column now holds the numeric data\n", - ")\n", - "\n", - "# --- 3. Create the Pivot Table ---\n", - "pivot_stats = pd.pivot_table(\n", - " df_melted,\n", - " index=['Metric'],\n", - " columns=['satisfaction'], # 'satisfied' and 'unsatisfied' become columns\n", - " values='Value',\n", - " aggfunc=['mean', 'median', 'std'] # The desired statistics\n", - ")\n", - "\n", - "# --- 4. Re-orient to Vertical View ---\n", - "# Stacking moves the first level of the column index (mean, median, std) to the rows\n", - "vertical_stats_table = pivot_stats.stack(level=0)\n", - "\n", - "# Rename the new index level for clarity\n", - "vertical_stats_table.index.set_names(['Metric', 'Statistic'], inplace=True)\n", - "\n", - "# Display the final vertical table\n", - "vertical_stats_table" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "69231728-91ed-4a46-ae0c-826b298928b8", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'df_melted' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[8], line 12\u001b[0m\n\u001b[0;32m 8\u001b[0m \u001b[38;5;66;03m# --- 2. Create the Grouped Bar Plot with the new palette ---\u001b[39;00m\n\u001b[0;32m 9\u001b[0m plt\u001b[38;5;241m.\u001b[39mfigure(figsize\u001b[38;5;241m=\u001b[39m(\u001b[38;5;241m16\u001b[39m, \u001b[38;5;241m8\u001b[39m))\n\u001b[0;32m 11\u001b[0m sns\u001b[38;5;241m.\u001b[39mbarplot(\n\u001b[1;32m---> 12\u001b[0m data\u001b[38;5;241m=\u001b[39mdf_melted,\n\u001b[0;32m 13\u001b[0m x\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMetric\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 14\u001b[0m y\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mValue\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 15\u001b[0m hue\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msatisfaction\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 16\u001b[0m errorbar\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msd\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 17\u001b[0m palette\u001b[38;5;241m=\u001b[39mcorrect_palette \u001b[38;5;66;03m# Use the corrected dictionary\u001b[39;00m\n\u001b[0;32m 18\u001b[0m )\n\u001b[0;32m 20\u001b[0m \u001b[38;5;66;03m# --- 3. Format the Chart (rest of the code) ---\u001b[39;00m\n\u001b[0;32m 21\u001b[0m plt\u001b[38;5;241m.\u001b[39mtitle(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMean of All Metrics Grouped by Satisfaction Status\u001b[39m\u001b[38;5;124m'\u001b[39m, fontsize\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m16\u001b[39m)\n", - "\u001b[1;31mNameError\u001b[0m: name 'df_melted' is not defined" - ] - }, - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. Define the CORRECTED Palette Dictionary ---\n", - "# We use 'neutral or dissatisfied' as the key, mapped to a color.\n", - "correct_palette = {\n", - " 'satisfied': 'tab:blue',\n", - " 'neutral or dissatisfied': 'tab:orange' # Mapped to orange, representing the non-satisfied group\n", - "}\n", - "\n", - "# --- 2. Create the Grouped Bar Plot with the new palette ---\n", - "plt.figure(figsize=(16, 8))\n", - "\n", - "sns.barplot(\n", - " data=df_melted,\n", - " x='Metric',\n", - " y='Value',\n", - " hue='satisfaction',\n", - " errorbar='sd',\n", - " palette=correct_palette # Use the corrected dictionary\n", - ")\n", - "\n", - "# --- 3. Format the Chart (rest of the code) ---\n", - "plt.title('Mean of All Metrics Grouped by Satisfaction Status', fontsize=16)\n", - "plt.ylabel('Mean Value (Mixed Scales)', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "2599980d-0244-44e9-bcd4-5cd3d5cb2d23", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "\n", - "from sklearn.preprocessing import MinMaxScaler\n", - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "\n", - "# Assuming 'df' is your original DataFrame\n", - "# ----------------------------------------------------\n", - "# 1. Identify the numeric metric columns to scale\n", - "# (Excluding categorical, ID, and the 'satisfaction' column)\n", - "\n", - "metrics_to_scale = [\n", - " 'Flight Distance', 'Inflight wifi service', 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking', 'Gate location', 'Food and drink', 'Online boarding',\n", - " 'Seat comfort', 'Inflight entertainment', 'On-board service', 'Leg room service',\n", - " 'Baggage handling', 'Checkin service', 'Inflight service', 'Cleanliness',\n", - " 'Departure Delay in Minutes', 'Arrival Delay in Minutes', 'Age'\n", - "]\n", - "\n", - "# Create a copy of the DataFrame columns to scale\n", - "df_scaled = df[metrics_to_scale].copy()\n", - "\n", - "# Initialize the scaler\n", - "scaler = MinMaxScaler()\n", - "\n", - "# Apply scaler to all columns in the copy\n", - "df_scaled[metrics_to_scale] = scaler.fit_transform(df_scaled[metrics_to_scale])\n", - "\n", - "# Merge the scaled metrics back into the original DataFrame (or a new one)\n", - "df_normalized = df[['satisfaction']].copy()\n", - "df_normalized = pd.concat([df_normalized, df_scaled], axis=1)\n", - "\n", - "# ----------------------------------------------------\n", - "# 2. Melt the Scaled Data\n", - "\n", - "# Use the normalized DataFrame for melting\n", - "df_melted_normalized = df_normalized.melt(\n", - " id_vars=['satisfaction'],\n", - " value_vars=metrics_to_scale,\n", - " var_name='Metric',\n", - " value_name='Normalized_Value' # New column name for the scaled values\n", - ")\n", - "\n", - "# ----------------------------------------------------\n", - "# 3. Plot the Scaled Data\n", - "\n", - "plt.figure(figsize=(16, 8))\n", - "\n", - "correct_palette = {\n", - " 'satisfied': 'tab:blue',\n", - " 'neutral or dissatisfied': 'tab:orange'\n", - "}\n", - "\n", - "sns.barplot(\n", - " data=df_melted_normalized,\n", - " x='Metric',\n", - " y='Normalized_Value', # Plotting the 0-to-1 scaled values\n", - " hue='satisfaction',\n", - " errorbar='sd',\n", - " palette=correct_palette\n", - ")\n", - "\n", - "# --- Format the Chart ---\n", - "plt.title('Mean of All Metrics Grouped by Satisfaction Status (Normalized)', fontsize=16)\n", - "plt.ylabel('Normalized Mean Value (Range: 0 to 1)', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "471d1f0f-fd6d-48b4-bdbc-cfc6b9823e4a", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'df_melted' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[10], line 26\u001b[0m\n\u001b[0;32m 7\u001b[0m filtered_metrics_1to5 \u001b[38;5;241m=\u001b[39m [\n\u001b[0;32m 8\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mInflight wifi service\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 9\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDeparture/Arrival time convenient\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mCleanliness\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 22\u001b[0m ]\n\u001b[0;32m 24\u001b[0m \u001b[38;5;66;03m# --- 2. Filter the df_melted DataFrame ---\u001b[39;00m\n\u001b[0;32m 25\u001b[0m \u001b[38;5;66;03m# Only keep rows where the 'Metric' is in the list above\u001b[39;00m\n\u001b[1;32m---> 26\u001b[0m df_melted_filtered_1to5 \u001b[38;5;241m=\u001b[39m df_melted[df_melted[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mMetric\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;241m.\u001b[39misin(filtered_metrics_1to5)]\n\u001b[0;32m 29\u001b[0m \u001b[38;5;66;03m# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\u001b[39;00m\n\u001b[0;32m 30\u001b[0m correct_palette \u001b[38;5;241m=\u001b[39m {\n\u001b[0;32m 31\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msatisfied\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtab:blue\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m 32\u001b[0m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mneutral or dissatisfied\u001b[39m\u001b[38;5;124m'\u001b[39m: \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtab:orange\u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 33\u001b[0m }\n", - "\u001b[1;31mNameError\u001b[0m: name 'df_melted' is not defined" - ] - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import seaborn as sns\n", - "import pandas as pd\n", - "# Assuming df_melted is already in your environment from previous steps\n", - "\n", - "# --- 1. Define the List of Columns to Include (All 1-5 Scale Metrics) ---\n", - "filtered_metrics_1to5 = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - "]\n", - "\n", - "# --- 2. Filter the df_melted DataFrame ---\n", - "# Only keep rows where the 'Metric' is in the list above\n", - "df_melted_filtered_1to5 = df_melted[df_melted['Metric'].isin(filtered_metrics_1to5)]\n", - "\n", - "\n", - "# --- 3. Define the CORRECTED Palette Dictionary (as previously fixed) ---\n", - "correct_palette = {\n", - " 'satisfied': 'tab:blue',\n", - " 'neutral or dissatisfied': 'tab:orange'\n", - "}\n", - "\n", - "# --- 4. Create the Grouped Bar Plot with the FILTERED data ---\n", - "plt.figure(figsize=(16, 8))\n", - "\n", - "sns.barplot(\n", - " data=df_melted_filtered_1to5, # Using the filtered data\n", - " x='Metric',\n", - " y='Value',\n", - " hue='satisfaction',\n", - " errorbar='sd',\n", - " palette=correct_palette\n", - ")\n", - "\n", - "# --- 5. Format the Chart ---\n", - "plt.title('Mean Scores for In-Flight and Check-in Metrics by Satisfaction Status', fontsize=16)\n", - "plt.ylabel('Mean Rating (1-5 Scale)', fontsize=14) # Changed Y-label for clarity\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 5.5) # Set Y-axis limit appropriate for a 1-5 scale\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "350b26b2-5a25-43aa-9ca2-c2b7edd64774", - "metadata": {}, - "outputs": [], - "source": [ - "satisfied_ratings = dfSatisfied['Inflight wifi service'].dropna()\n", - "dissatisfied_ratings = dfDisatisfied['Inflight wifi service'].dropna()\n", - "\n", - "# Perform the Two-Sample T-Test (Welch's)\n", - "t_statistic, p_value = stats.ttest_ind(\n", - " a=satisfied_ratings,\n", - " b=dissatisfied_ratings,\n", - " equal_var=False\n", - ")\n", - "\n", - "# --- Output the Results ---\n", - "print(f\"--- T-Test Results for Inflight wifi service ---\")\n", - "print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", - "print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", - "print(\"-\" * 38)\n", - "print(f\"T-Statistic: {t_statistic:.4f}\")\n", - "print(f\"P-Value: {p_value:.10f}\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5a2bf756-8500-4adc-99af-1c48cd7e1d37", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", - "\n", - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "for col in metric_columns: \n", - " satisfied_ratings = dfDisatisfied[col].dropna()\n", - " dissatisfied_ratings = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=satisfied_ratings,\n", - " b=dissatisfied_ratings,\n", - " equal_var=False\n", - " )\n", - "\n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"Mean Satisfied: {satisfied_ratings.mean():.3f}\")\n", - " print(f\"Mean Dissatisfied: {dissatisfied_ratings.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "91a9b0cd-b1f0-4851-8439-cf30868a1bf6", - "metadata": {}, - "outputs": [], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "60a773e7-2487-47bd-b868-94f7b60bf471", - "metadata": {}, - "outputs": [], - "source": [ - "# dfSatisfied_disloyal=df[df['satisfaction_binary'] == 1 & 'Customer Type'=='disloyal Customer']\n", - "dfDisatisfied_disloyal=df[(df['satisfaction_binary'] == 0) & (df['Customer Type']=='disloyal Customer')]\n", - "dfDisloyal=df[df['Customer Type']=='disloyal Customer']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a75fd6ab-fb8e-4ef8-ab12-ac19c28bc21a", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied_disloyal.describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6ad6e2d8-eed3-446e-ae43-a6c5e127c8be", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d4e77057-6266-4cd6-b6dc-4647799d96ff", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "07ee2084-a56b-4321-a025-d13bb9e510dc", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied_disloyal" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9b45c0ab-c959-4130-820f-19a659973ecb", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1cb9c038-2d28-4203-8cce-0146b91182e1", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. Define the Metric Columns to Test ---\n", - "# Use the common numeric columns that represent scores/distances/delays.\n", - "# Ensure all these columns exist in BOTH dfSatisfied and dfDisatisfied.\n", - "\n", - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "for col in metric_columns: \n", - " df_1 = dfDisatisfied[col].dropna()\n", - " df_2 = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1,\n", - " b=df_2,\n", - " equal_var=False\n", - " )\n", - " \n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1: {df_1.mean():.3f}\")\n", - " print(f\"df_2: {df_2.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "c9f9a363-4c19-4991-ac52-524d8e388100", - "metadata": {}, - "outputs": [], - "source": [ - "metric_columns = [\n", - " 'Inflight wifi service',\n", - " 'Departure/Arrival time convenient',\n", - " 'Ease of Online booking',\n", - " 'Gate location',\n", - " 'Food and drink',\n", - " 'Online boarding',\n", - " 'Seat comfort',\n", - " 'Inflight entertainment',\n", - " 'On-board service',\n", - " 'Leg room service',\n", - " 'Baggage handling',\n", - " 'Checkin service',\n", - " 'Inflight service',\n", - " 'Cleanliness',\n", - " 'Departure Delay in Minutes',\n", - " 'Arrival Delay in Minutes',\n", - " # Add all other numeric metrics you want to compare\n", - "]\n", - "\n", - "for col in metric_columns: \n", - " df_1 = dfDisloyal[col].dropna()\n", - " df_2 = dfDisatisfied_disloyal[col].dropna()\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1,\n", - " b=df_2,\n", - " equal_var=False\n", - " )\n", - "\n", - " # --- Output the Results ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1: {df_1.mean():.3f}\")\n", - " print(f\"df_2: {df_2.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "48bdbb2e-65c5-41e1-b398-559ccb485221", - "metadata": {}, - "outputs": [], - "source": [ - "legend_colors = ['#1f77b4', '#ff7f0e', '#2ca02c'] \n", - "\n", - "# Define the corresponding labels\n", - "legend_labels = ['Category A', 'Category B', 'Category C']" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "9cf4e44a-4f00-4df2-bf91-d60bb6cb65d1", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'dfDisloyal' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[1;32mIn[11], line 11\u001b[0m\n\u001b[0;32m 7\u001b[0m \u001b[38;5;66;03m# --- 2. Iterate, Test, and Collect Results ---\u001b[39;00m\n\u001b[0;32m 8\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m col \u001b[38;5;129;01min\u001b[39;00m metric_columns:\n\u001b[0;32m 9\u001b[0m \u001b[38;5;66;03m# Safely convert to numeric and drop NaNs for both comparison groups\u001b[39;00m\n\u001b[0;32m 10\u001b[0m \u001b[38;5;66;03m# NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\u001b[39;00m\n\u001b[1;32m---> 11\u001b[0m df_1_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_numeric(dfDisloyal[col], errors\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcoerce\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mdropna()\n\u001b[0;32m 12\u001b[0m df_2_data \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mto_numeric(dfDisatisfied_disloyal[col], errors\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mcoerce\u001b[39m\u001b[38;5;124m'\u001b[39m)\u001b[38;5;241m.\u001b[39mdropna()\n\u001b[0;32m 14\u001b[0m \u001b[38;5;66;03m# Skip if groups are too small or empty after cleaning\u001b[39;00m\n", - "\u001b[1;31mNameError\u001b[0m: name 'dfDisloyal' is not defined" - ] - } - ], - "source": [ - "# --- 1. Initialize Lists for Storing Results ---\n", - "metric_names = []\n", - "p_values = []\n", - "is_significant = []\n", - "alpha = 0.05 # Significance level\n", - "\n", - "# --- 2. Iterate, Test, and Collect Results ---\n", - "for col in metric_columns:\n", - " # Safely convert to numeric and drop NaNs for both comparison groups\n", - " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", - " df_1_data = pd.to_numeric(dfDisloyal[col], errors='coerce').dropna()\n", - " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", - " \n", - " # Skip if groups are too small or empty after cleaning\n", - " if df_1_data.size < 2 or df_2_data.size < 2:\n", - " print(f\"Skipping {col}: Insufficient data.\")\n", - " continue\n", - "\n", - " # Perform Welch's T-Test\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1_data,\n", - " b=df_2_data,\n", - " equal_var=False\n", - " )\n", - "\n", - " # Store results in the lists\n", - " metric_names.append(col)\n", - " p_values.append(p_value)\n", - " is_significant.append(p_value <= alpha)\n", - "\n", - " # --- Output the Results (Optional, as requested) ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", - " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)\n", - "\n", - "# --- 3. Create DataFrame for Plotting ---\n", - "p_values_df = pd.DataFrame({\n", - " 'Metric': metric_names,\n", - " 'P_Value': p_values,\n", - " 'Is_Significant': is_significant\n", - "})\n", - "\n", - "# # Sort the results by P-Value for a cleaner chart\n", - "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", - "\n", - "# --- 4. Plot the P-Values ---\n", - "\n", - "# Define colors for bars based on significance\n", - "# --- Define the mapping dictionary ---\n", - "# Create the dictionary that maps the unique hue values (True/False) to colors\n", - "palette_map = {\n", - " True: 'darkred', # For bars where Is_Significant is True\n", - " False: 'skyblue' # For bars where Is_Significant is False\n", - "}\n", - "\n", - "plt.figure(figsize=(14, 8))\n", - "ax = sns.barplot(\n", - " data=p_values_df,\n", - " x='Metric',\n", - " y='P_Value',\n", - " hue='Is_Significant',\n", - " palette=palette_map, # <-- FIX: Pass the dictionary here\n", - " dodge=False,\n", - ")\n", - "# Add horizontal line at p=0.05\n", - "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", - "\n", - "# --- Custom Legend ---\n", - "from matplotlib.patches import Patch\n", - "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", - "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", - "final_handles = custom_handles + [significance_line]\n", - "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", - "\n", - "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", - "ax.get_legend().remove() \n", - "\n", - "# --- Formatting ---\n", - "plt.title('P-Values from T-Tests for only Disloyal vs Disatisfied disloyal customers', fontsize=16)\n", - "plt.ylabel('P-Value', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 1.0)\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "22aa3477-4a71-4966-8278-0fb39583ffae", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. Initialize Lists for Storing Results ---\n", - "metric_names = []\n", - "p_values = []\n", - "is_significant = []\n", - "alpha = 0.05 # Significance level\n", - "\n", - "# --- 2. Iterate, Test, and Collect Results ---\n", - "for col in metric_columns:\n", - " # Safely convert to numeric and drop NaNs for both comparison groups\n", - " # NOTE: You must have 'dfDisloyal' and 'dfDisatisfied_disloyal' defined outside this loop.\n", - " df_1_data = pd.to_numeric(dfDisatisfied[col], errors='coerce').dropna()\n", - " df_2_data = pd.to_numeric(dfDisatisfied_disloyal[col], errors='coerce').dropna()\n", - " \n", - " # Skip if groups are too small or empty after cleaning\n", - " if df_1_data.size < 2 or df_2_data.size < 2:\n", - " print(f\"Skipping {col}: Insufficient data.\")\n", - " continue\n", - "\n", - " # Perform Welch's T-Test\n", - " t_statistic, p_value = stats.ttest_ind(\n", - " a=df_1_data,\n", - " b=df_2_data,\n", - " equal_var=False\n", - " )\n", - "\n", - " # Store results in the lists\n", - " metric_names.append(col)\n", - " p_values.append(p_value)\n", - " is_significant.append(p_value <= alpha)\n", - "\n", - " # --- Output the Results (Optional, as requested) ---\n", - " print(f\"--- T-Test Results for {col} ---\")\n", - " print(f\"df_1 Mean: {df_1_data.mean():.3f}\")\n", - " print(f\"df_2 Mean: {df_2_data.mean():.3f}\")\n", - " print(f\"T-Statistic: {t_statistic:.4f}\")\n", - " print(f\"P-Value: {p_value:.10f}\")\n", - " print(\"-\" * 38)\n", - "\n", - "# --- 3. Create DataFrame for Plotting ---\n", - "p_values_df = pd.DataFrame({\n", - " 'Metric': metric_names,\n", - " 'P_Value': p_values,\n", - " 'Is_Significant': is_significant\n", - "})\n", - "\n", - "# # Sort the results by P-Value for a cleaner chart\n", - "# p_values_df = p_values_df.sort_values(by='P_Value', ascending=True)\n", - "\n", - "# --- 4. Plot the P-Values ---\n", - "\n", - "# Define colors for bars based on significance\n", - "# --- Define the mapping dictionary ---\n", - "# Create the dictionary that maps the unique hue values (True/False) to colors\n", - "palette_map = {\n", - " True: 'darkred', # For bars where Is_Significant is True\n", - " False: 'skyblue' # For bars where Is_Significant is False\n", - "}\n", - "\n", - "plt.figure(figsize=(14, 8))\n", - "ax = sns.barplot(\n", - " data=p_values_df,\n", - " x='Metric',\n", - " y='P_Value',\n", - " hue='Is_Significant',\n", - " palette=palette_map, # <-- FIX: Pass the dictionary here\n", - " dodge=False,\n", - ")\n", - "# Add horizontal line at p=0.05\n", - "plt.axhline(alpha, color='green', linestyle='--', linewidth=2, label=r'$\\alpha = 0.05$ Threshold')\n", - "\n", - "# --- Custom Legend ---\n", - "from matplotlib.patches import Patch\n", - "custom_handles = [Patch(facecolor=c, label=l) for c, l in zip(legend_colors, legend_labels)]\n", - "significance_line = plt.Line2D([0], [0], color='green', linestyle='--', linewidth=2)\n", - "final_handles = custom_handles + [significance_line]\n", - "final_labels = legend_labels + [r'$\\alpha = 0.05$ Threshold']\n", - "\n", - "plt.legend(handles=final_handles, labels=final_labels, title='T-Test Result', loc='upper right')\n", - "ax.get_legend().remove() \n", - "\n", - "# --- Formatting ---\n", - "plt.title('P-Values from T-Tests for only Disatisfied vs Disatisfied disloyal customers', fontsize=16)\n", - "plt.ylabel('P-Value', fontsize=14)\n", - "plt.xlabel('Metric', fontsize=14)\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.ylim(0, 1.0)\n", - "plt.tight_layout()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "486e26c6-7291-4075-97db-de6b916db1f8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8b49a8ad-9ade-4c87-bfc1-8c41a0fc8cbc", - "metadata": {}, - "outputs": [], - "source": [ - "df['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "eebaa851-4d41-4660-93f0-134a3cb071da", - "metadata": {}, - "outputs": [], - "source": [ - "dfSatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bfb858a8-9410-4699-8150-7f17f158580a", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied['Customer Type'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "926ecc39-68ea-40b4-9497-dbeb14a0be6f", - "metadata": {}, - "outputs": [], - "source": [ - "customer_type_counts = df['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on the entire population')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "67b33a15-cadd-47bf-8925-ed30bb5529ab", - "metadata": {}, - "outputs": [], - "source": [ - "customer_type_counts = dfDisatisfied['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on Disatisfied customers')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0316d475-161d-4c81-b2ae-963e31d2f67b", - "metadata": {}, - "outputs": [], - "source": [ - "customer_type_counts = dfSatisfied['Customer Type'].value_counts()\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "plt.pie(\n", - " customer_type_counts,\n", - " labels=customer_type_counts.index,\n", - " # This is the key part: autopct='%1.1f%%' formats the percentage\n", - " autopct='%1.1f%%',\n", - " startangle=90,\n", - " wedgeprops={'edgecolor': 'black'}\n", - ")\n", - "plt.title('Loyalty distribution on Satisfied customers')\n", - "plt.axis('equal') # Ensures the pie chart is circular\n", - "plt.savefig('customer_type_pie_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "18bc096e-7e84-4b59-afab-dd9cf34f8875", - "metadata": {}, - "outputs": [], - "source": [ - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Age'] < 18),\n", - " (df['Age'] >= 18) & (df['Age'] < 30),\n", - " (df['Age'] >= 30) & (df['Age'] < 40),\n", - " (df['Age'] >= 40) & (df['Age'] < 50),\n", - " (df['Age'] >= 50) & (df['Age'] < 60),\n", - " (df['Age'] >= 60) & (df['Age'] < 70),\n", - " (df['Age'] >= 70)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Minor',\n", - " '18 to 30',\n", - " '30 to 40',\n", - " '40 to 50',\n", - " '50 to 60',\n", - " '60 to 70',\n", - " '70 +'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['age groups'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Age Group creation successful.\")\n", - "\n", - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Flight Distance'] < 750),\n", - " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", - " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", - " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", - " (df['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Flight distance group Group creation successful.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a8be13d3-407c-4690-9829-a7ea3716bc18", - "metadata": {}, - "outputs": [], - "source": [ - "# Assuming 'df' is your DataFrame with an 'Age' column\n", - "\n", - "# 1. Define the Conditions\n", - "# Each condition must be a Boolean Series (True/False)\n", - "conditions = [\n", - " (df['Flight Distance'] < 750),\n", - " (df['Flight Distance'] >= 750) & (df['Flight Distance'] < 1500),\n", - " (df['Flight Distance'] >= 1500) & (df['Flight Distance'] < 2250),\n", - " (df['Flight Distance'] >= 2250) & (df['Flight Distance'] < 3000),\n", - " (df['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# 2. Define the Corresponding Outputs (Labels)\n", - "choices = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# 3. Apply np.select()\n", - "# 'Other' is the default value if none of the conditions are True (e.g., if Age is NaN)\n", - "df['Flight Distance_group'] = np.select(conditions, choices, default='Unknown')\n", - "\n", - "print(\"Flight distance group Group creation successful.\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b7f5979a-541a-41f8-82e7-c883a09f6829", - "metadata": {}, - "outputs": [], - "source": [ - "df['Flight Distance'].describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "252a1bca-6113-4fbf-b754-ab45fdff1f87", - "metadata": {}, - "outputs": [], - "source": [ - "df['Flight Distance_group'].describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "710fac04-fc16-40cb-acef-6796ab3cfbb2", - "metadata": {}, - "outputs": [], - "source": [ - "df" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8358ed7b-ade3-4e04-a9d6-3027fa0d729a", - "metadata": {}, - "outputs": [], - "source": [ - "df['age groups'].value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1c009267-eb8e-43ec-875d-12876fdfc5e8", - "metadata": {}, - "outputs": [], - "source": [ - "df['age Groups']" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "5c7b7112-b2bf-4796-bee9-9da5649c2811", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "da29f134-7a84-4fa0-87f3-3d825c228c27", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a891b1c5-7566-44a3-8ab5-5ae110605fdc", - "metadata": {}, - "outputs": [], - "source": [ - "# # Data provided by the user (Age Group counts from dfDisatisfied)\n", - "# # In a real scenario, this data would come from: dfDisatisfied['age groups'].value_counts()\n", - "# data_age_groups = {\n", - "# 'Age Group': ['40 to 50', '18 to 30', '30 to 40', '50 to 60', '60 to 70', 'Minor', '70 +'],\n", - "# 'Count': [23696, 22796, 20659, 19103, 8346, 7931, 1373]\n", - "# }\n", - "# df_counts = pd.DataFrame(data_age_groups)\n", - "\n", - "# # 1. Calculate the total number of dissatisfied customers\n", - "# total_customers = df_counts['Count'].sum()\n", - "\n", - "# # 2. Calculate the percentage for each age group\n", - "# df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "# # 3. Define the logical order for the age groups for plotting\n", - "# age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", - "\n", - "# # 4. Plot a bar chart\n", - "# plt.figure(figsize=(10, 6))\n", - "# sns.barplot(\n", - "# x='Age Group',\n", - "# y='Percentage',\n", - "# data=df_counts,\n", - "# order=age_order, # Use the defined order for chronological display\n", - "# palette='viridis'\n", - "# )\n", - "\n", - "# # Add titles and labels\n", - "# plt.title('Percentage of Dissatisfied Customers by Age Group')\n", - "# plt.xlabel('Age Group')\n", - "# plt.ylabel('Percentage (%)')\n", - "# plt.xticks(rotation=45, ha='right') # Rotate labels for better visibility\n", - "# plt.grid(axis='y', linestyle='--')\n", - "# plt.tight_layout()\n", - "\n", - "# # Display or save the plot\n", - "# plt.show() # Use plt.show() if running in a script/local environment\n", - "# # plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "286b7ffa-a576-49cb-99f1-48dc71657bde", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\a_gal\\AppData\\Local\\Temp\\ipykernel_21412\\783172777.py:23: FutureWarning: \n", - "\n", - "Passing `palette` without assigning `hue` is deprecated and will be removed in v0.14.0. Assign the `x` variable to `hue` and set `legend=False` for the same effect.\n", - "\n", - " ax = sns.barplot(\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", - "# Get the count of each age group from the dfDisatisfied DataFrame\n", - "age_group_counts_series = dfDisatisfied['age groups'].value_counts()\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts) for plotting\n", - "df_counts = age_group_counts_series.reset_index()\n", - "df_counts.columns = ['Age Group', 'Count']\n", - "\n", - "\n", - "# --- 2. CALCULATE PERCENTAGE ---\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "# Optional: Ensure all groups are present, even if count is 0,\n", - "# and ensure they are properly ordered by the chronological order of ages.\n", - "# We will use the 'order' parameter in sns.barplot for this.\n", - "age_order = ['Minor', '18 to 30', '30 to 40', '40 to 50', '50 to 60', '60 to 70', '70 +']\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART ---\n", - "plt.figure(figsize=(10, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Age Group',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " order=age_order, # Use the defined chronological order\n", - " palette='viridis'\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Age Group (Chronological Order)')\n", - "plt.xlabel('Age Group')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=45, ha='right')\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit for the annotations\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", - "plt.show() # Use plt.show() if running in a script/local environment" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b07ff56c-872a-4b4e-b6d8-5e72e13b82a1", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", - "# Get the count of each Gender from the dfDisatisfied DataFrame\n", - "gender_counts_series = dfDisatisfied['Gender'].value_counts()\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts)\n", - "df_counts = gender_counts_series.reset_index()\n", - "df_counts.columns = ['Gender', 'Count']\n", - "\n", - "# Sort the data by count (or percentage) before plotting\n", - "df_counts = df_counts.sort_values(by='Count', ascending=False)\n", - "\n", - "\n", - "# --- 2. CALCULATE PERCENTAGE ---\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART ---\n", - "plt.figure(figsize=(8, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Gender',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " # Order is naturally handled by the prior sorting of df_counts\n", - " palette='Set2' # Used a different palette (Set2)\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Gender')\n", - "plt.xlabel('Gender')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=0, ha='center') # No rotation needed\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit for the annotations\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_gender_percentage_bar_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0c050280-c376-4dca-828d-d0a83da57c19", - "metadata": {}, - "outputs": [], - "source": [ - "dfDisatisfied['Flight Distance'].describe()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "35a1f185-d10a-4141-b256-a59ac5f07b4c", - "metadata": {}, - "outputs": [], - "source": [ - "df['Flight Distance_group'].describe() " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "2e48782b-7bc1-40ab-a764-b90ca6453b23", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. AUTOMATIC DATA AGGREGATION ---\n", - "# Get the count of each Flight Distance group from the dfDisatisfied DataFrame\n", - "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts)\n", - "df_counts = distance_group_counts_series.reset_index()\n", - "df_counts.columns = ['Flight Distance Group', 'Count']\n", - "\n", - "# Define the chronological/logical order for the x-axis\n", - "distance_labels = ['Short-Haul (0-500)', 'Medium-Haul (500-1500)', 'Long-Haul (1500-3000)', 'Ultra-Long (3000+)']\n", - "\n", - "# --- 2. CALCULATE PERCENTAGE ---\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART ---\n", - "plt.figure(figsize=(10, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Flight Distance Group',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " order=distance_labels, # Enforce chronological order\n", - " palette='magma'\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", - "plt.xlabel('Flight Distance Group')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit for the annotations\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.15)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart.png')" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "614fdf71-c65c-42cd-8086-91fa69269eab", - "metadata": {}, - "outputs": [], - "source": [ - "# --- 1. DEFINE AND APPLY CUSTOM GROUPS (using the logic you provided) ---\n", - "\n", - "# --- Define the Conditions ---\n", - "# Assuming you are applying this logic to the dfDisatisfied DataFrame\n", - "conditions = [\n", - " (dfDisatisfied['Flight Distance'] < 750),\n", - " (dfDisatisfied['Flight Distance'] >= 750) & (dfDisatisfied['Flight Distance'] < 1500),\n", - " (dfDisatisfied['Flight Distance'] >= 1500) & (dfDisatisfied['Flight Distance'] < 2250),\n", - " (dfDisatisfied['Flight Distance'] >= 2250) & (dfDisatisfied['Flight Distance'] < 3000),\n", - " (dfDisatisfied['Flight Distance'] >= 3000)\n", - "]\n", - "\n", - "# --- Define the Corresponding Labels and Order ---\n", - "distance_labels = [\n", - " 'Short, until 750 miles',\n", - " 'Medium-short, until 1500 miles',\n", - " 'Medium-Long, until 2250 miles',\n", - " 'Long, until 3000 miles',\n", - " 'Very long, more than 3000 miles'\n", - "]\n", - "\n", - "# Apply np.select() to create the grouping column\n", - "dfDisatisfied['Flight Distance_group'] = np.select(\n", - " conditions, \n", - " distance_labels, \n", - " default='Unknown'\n", - ")\n", - "\n", - "# --- 2. AUTOMATIC DATA AGGREGATION & PERCENTAGE CALCULATION ---\n", - "\n", - "# Get the count of each Flight Distance group\n", - "distance_group_counts_series = dfDisatisfied['Flight Distance_group'].value_counts(dropna=False)\n", - "\n", - "# Convert the Series of counts into a DataFrame (df_counts)\n", - "df_counts = distance_group_counts_series.reset_index()\n", - "df_counts.columns = ['Flight Distance Group', 'Count']\n", - "\n", - "# Calculate Percentage\n", - "total_customers = df_counts['Count'].sum()\n", - "df_counts['Percentage'] = (df_counts['Count'] / total_customers) * 100\n", - "\n", - "\n", - "# --- 3. PLOT BAR CHART WITH ANNOTATIONS ---\n", - "plt.figure(figsize=(12, 6))\n", - "\n", - "ax = sns.barplot(\n", - " x='Flight Distance Group',\n", - " y='Percentage',\n", - " data=df_counts,\n", - " order=distance_labels, # Ensures the groups plot in logical order\n", - " palette='magma'\n", - ")\n", - "\n", - "# Add titles and labels\n", - "plt.title('Percentage of Dissatisfied Customers by Flight Distance Group')\n", - "plt.xlabel('Flight Distance Group')\n", - "plt.ylabel('Percentage (%)')\n", - "plt.xticks(rotation=15, ha='right') # Slight rotation for readability\n", - "\n", - "# Add percentage values on top of the bars (Annotations)\n", - "for p in ax.patches:\n", - " ax.annotate(f'{p.get_height():.1f}%',\n", - " (p.get_x() + p.get_width() / 2., p.get_height()),\n", - " ha='center', va='center',\n", - " xytext=(0, 9),\n", - " textcoords='offset points')\n", - "\n", - "# Adjust y-limit to ensure annotations are visible\n", - "plt.ylim(0, df_counts['Percentage'].max() * 1.20)\n", - "plt.grid(axis='y', linestyle='--')\n", - "plt.tight_layout()\n", - "\n", - "# Save the plot\n", - "plt.savefig('dissatisfied_customers_flight_distance_percentage_bar_chart_final.png')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a805f6b8-ea67-4ded-a3a3-b2659a133da8", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python [conda env:base] *", - "language": "python", - "name": "conda-base-py" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} From 0b4e14eedfefc82607109e01231613c7de3a533f Mon Sep 17 00:00:00 2001 From: antonio galvao Date: Wed, 10 Dec 2025 19:06:11 +0100 Subject: [PATCH 19/26] Marta changes added to main file --- notebooks/Airline_Project1.ipynb | 488 +++++++++++++++++++++++++++++++ 1 file changed, 488 insertions(+) diff --git a/notebooks/Airline_Project1.ipynb b/notebooks/Airline_Project1.ipynb index b80c6427..df8317aa 100644 --- a/notebooks/Airline_Project1.ipynb +++ b/notebooks/Airline_Project1.ipynb @@ -751,6 +751,494 @@ "plt.savefig('dissatisfied_customers_age_percentage_bar_chart_actual.png')\n", "plt.show() # Use plt.show() if running in a script/local environment" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "31a64198-33b6-4a6d-9965-be0e02ef7a06", + "metadata": {}, + "outputs": [], + "source": [ + "def clean_airloops_data(df):\n", + " # 1. Handle Missing Values: Fill 'Arrival Delay in Minutes' with the median\n", + " median_delay = df['Arrival Delay in Minutes'].median()\n", + " df['Arrival Delay in Minutes'].fillna(median_delay, inplace=True)\n", + "\n", + " # Note: If 'Inflight wifi service' has nulls (which it often does),\n", + " # we can fill those with 0, assuming 'No Service' or 'Not Applicable'.\n", + " if 'Inflight wifi service' in df.columns and df['Inflight wifi service'].isnull().any():\n", + " df['Inflight wifi service'].fillna(0, inplace=True)\n", + "\n", + " # 2. Drop Unnecessary Columns\n", + " cols_to_drop = ['Unnamed: 0']\n", + " df.drop(columns=cols_to_drop, inplace=True, errors='ignore')\n", + "\n", + " # 3. Create the Target Variable (satisfaction_binary)\n", + " # Using .map() is a simple, clear way to do binary encoding.\n", + " satisfaction_map = {'satisfied': 1, 'neutral or dissatisfied': 0}\n", + " df['satisfaction_binary'] = df['satisfaction'].map(satisfaction_map)\n", + " df.drop(columns=['satisfaction'], inplace=True)\n", + "\n", + " # 4. Format Column Names (Lowercase and Underscore)\n", + " df.columns = df.columns.str.lower().str.replace(' ', '_')\n", + "\n", + " print(\"\\nData cleaning complete. Ready for analysis!\")\n", + " return df\n", + "\n", + "# Apply the function to your DataFrame\n", + "df_cleaned = clean_airloops_data(df.copy())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ff28b479-77f5-40d7-bf5d-ccbe9b852d4e", + "metadata": {}, + "outputs": [], + "source": [ + "# 1. Check Class Distribution (How many passengers in each class?)\n", + "print(\"--- Class Distribution ---\")\n", + "print(df_cleaned['class'].value_counts())\n", + "print(\"-\" * 30)\n", + "\n", + "# 2. Calculate Mean Satisfaction by Class\n", + "# The mean of 'satisfaction_binary' is the percentage of satisfied customers (1s)\n", + "satisfaction_by_class = df_cleaned.groupby('class')['satisfaction_binary'].mean().sort_values(ascending=False)\n", + "\n", + "print(\"\\n--- Average Satisfaction by Class ---\")\n", + "print(satisfaction_by_class)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6eb73ef0-bf83-476a-8278-ec20c7220758", + "metadata": {}, + "outputs": [], + "source": [ + "# The results you provided, stored in a DataFrame for plotting\n", + "satisfaction_data = {\n", + " 'Class': ['Business', 'Eco Plus', 'Eco'],\n", + " 'Average_Satisfaction': [0.694251, 0.246064, 0.186138]\n", + "}\n", + "plot_df = pd.DataFrame(satisfaction_data)\n", + "\n", + "# Sort the data for a cleaner visual presentation (highest to lowest)\n", + "plot_df = plot_df.sort_values(by='Average_Satisfaction', ascending=False)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "bars = plt.bar(plot_df['Class'], plot_df['Average_Satisfaction'], color=['#1f77b4', '#ff7f0e', '#2ca02c']) # Custom colors for visual separation\n", + "\n", + "# Add labels and title\n", + "plt.title('Average Passenger Satisfaction by Class', fontsize=14)\n", + "plt.xlabel('Travel Class', fontsize=12)\n", + "plt.ylabel('Average Satisfaction (Percentage)', fontsize=12)\n", + "plt.yticks([0.0, 0.2, 0.4, 0.6, 0.8, 1.0], ['0%', '20%', '40%', '60%', '80%', '100%']) # Format y-axis as percentages\n", + "\n", + "# Add the percentage values on top of the bars for clarity\n", + "for bar in bars:\n", + " yval = bar.get_height()\n", + " plt.text(bar.get_x() + bar.get_width()/2, yval + 0.01, f'{yval:.1%}', ha='center', va='bottom', fontsize=10)\n", + "\n", + "plt.grid(axis='y', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('satisfaction_by_class_bar_chart.png')\n", + "print(\"Plot saved as 'satisfaction_by_class_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "752cf44a-3cde-4b7d-8ef4-1609f71e304f", + "metadata": {}, + "outputs": [], + "source": [ + "#cleaned DataFrame is named 'df_cleaned'\n", + "\n", + "# 1. Check Customer Type Distribution\n", + "print(\"--- Customer Type Distribution ---\")\n", + "print(df_cleaned['customer_type'].value_counts())\n", + "print(\"-\" * 30)\n", + "\n", + "# 2. Calculate Mean Satisfaction by Customer Type\n", + "# The mean of 'satisfaction_binary' is the percentage of satisfied customers (1s)\n", + "satisfaction_by_customer_type = df_cleaned.groupby('customer_type')['satisfaction_binary'].mean().sort_values(ascending=False)\n", + "\n", + "print(\"\\n--- Average Satisfaction by Customer Type ---\")\n", + "print(satisfaction_by_customer_type)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d202bc86-14a0-4655-8c44-95625e65760b", + "metadata": {}, + "outputs": [], + "source": [ + "# The results you provided, stored in a DataFrame for plotting\n", + "satisfaction_data = {\n", + " 'Customer_Type': ['Loyal Customer', 'Disloyal Customer'],\n", + " 'Average_Satisfaction': [0.477291, 0.236658]\n", + "}\n", + "plot_df_h2 = pd.DataFrame(satisfaction_data)\n", + "\n", + "# Sort the data for presentation\n", + "plot_df_h2 = plot_df_h2.sort_values(by='Average_Satisfaction', ascending=False)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(8, 5))\n", + "bars = plt.bar(plot_df_h2['Customer_Type'], plot_df_h2['Average_Satisfaction'], color=['#3a5e8c', '#a63a50'])\n", + "\n", + "# Add labels and title\n", + "plt.title('Average Passenger Satisfaction: Loyal vs. Disloyal', fontsize=14)\n", + "plt.xlabel('Customer Type', fontsize=12)\n", + "plt.ylabel('Average Satisfaction (Percentage)', fontsize=12)\n", + "plt.yticks([0.0, 0.1, 0.2, 0.3, 0.4, 0.5], ['0%', '10%', '20%', '30%', '40%', '50%'])\n", + "\n", + "# Add the percentage values on top of the bars\n", + "for bar in bars:\n", + " yval = bar.get_height()\n", + " plt.text(bar.get_x() + bar.get_width()/2, yval + 0.01, f'{yval:.1%}', ha='center', va='bottom', fontsize=10)\n", + "\n", + "plt.grid(axis='y', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('satisfaction_by_customer_type_bar_chart.png')\n", + "print(\"Plot saved as 'satisfaction_by_customer_type_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c5cde0df-44de-4868-9ed7-ff5cc8023c2c", + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming your cleaned DataFrame is named 'df_cleaned'\n", + "\n", + "# 1. Identify Service Columns (The columns with rating scores or delay metrics)\n", + "# We include all rating columns and the delay columns.\n", + "service_columns = [\n", + " 'inflight_wifi_service',\n", + " 'departure/arrival_time_convenient',\n", + " 'ease_of_online_booking',\n", + " 'gate_location',\n", + " 'food_and_drink',\n", + " 'online_boarding',\n", + " 'seat_comfort',\n", + " 'inflight_entertainment',\n", + " 'on-board_service',\n", + " 'leg_room_service',\n", + " 'baggage_handling',\n", + " 'checkin_service',\n", + " 'inflight_service',\n", + " 'cleanliness',\n", + " 'departure_delay_in_minutes',\n", + " 'arrival_delay_in_minutes'\n", + "]\n", + "\n", + "# 2. Calculate Correlation with satisfaction_binary and sort the results\n", + "# The Pearson correlation coefficient (r) is used here.\n", + "correlation_results = df_cleaned[service_columns + ['satisfaction_binary']].corr()['satisfaction_binary'].sort_values(ascending=False)\n", + "\n", + "# Remove the correlation of the target variable with itself (which is always 1)\n", + "correlation_results = correlation_results.drop('satisfaction_binary')\n", + "\n", + "print(\"--- Correlation of Service Features with Satisfaction (r value) ---\")\n", + "print(correlation_results)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c45a74d-8465-4c43-aad8-0525b2183a07", + "metadata": {}, + "outputs": [], + "source": [ + "# The results you provided, stored in a Series for plotting\n", + "data = {\n", + " 'online_boarding': 0.503557,\n", + " 'inflight_entertainment': 0.398059,\n", + " 'seat_comfort': 0.349459,\n", + " 'on-board_service': 0.322383,\n", + " 'leg_room_service': 0.313131,\n", + " 'cleanliness': 0.305198,\n", + " 'inflight_wifi_service': 0.284245,\n", + " 'baggage_handling': 0.247749,\n", + " 'inflight_service': 0.244741,\n", + " 'checkin_service': 0.236174,\n", + " 'food_and_drink': 0.209936,\n", + " 'ease_of_online_booking': 0.171705,\n", + " 'gate_location': 0.000682,\n", + " 'departure_delay_in_minutes': -0.050494,\n", + " 'departure/arrival_time_convenient': -0.051601,\n", + " 'arrival_delay_in_minutes': -0.057435\n", + "}\n", + "\n", + "correlation_results = pd.Series(data)\n", + "\n", + "# Create the plot\n", + "plt.figure(figsize=(10, 7))\n", + "\n", + "# Define colors: Green for positive correlation, Red for negative\n", + "colors = ['g' if x > 0 else 'r' for x in correlation_results]\n", + "\n", + "# Plot the horizontal bar chart\n", + "correlation_results.plot(kind='barh', color=colors)\n", + "\n", + "# Add labels and title\n", + "plt.title('Correlation (r) of Service Features with Passenger Satisfaction', fontsize=14)\n", + "plt.xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "plt.ylabel('Service Feature', fontsize=12)\n", + "\n", + "# Add a vertical line at r=0 for reference\n", + "plt.axvline(0, color='gray', linestyle='--', linewidth=0.8)\n", + "\n", + "plt.grid(axis='x', linestyle='--', alpha=0.6)\n", + "plt.tight_layout()\n", + "\n", + "# Save the plot\n", + "plt.savefig('service_correlation_bar_chart.png')\n", + "print(\"Plot saved as 'service_correlation_bar_chart.png'\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "89018f74-f010-491c-a7b8-90831ce0f1dc", + "metadata": {}, + "outputs": [], + "source": [ + "def analyze_service_correlations_notebook(df):\n", + " \"\"\"\n", + " Calcula el coeficiente de correlación de Pearson (r) entre\n", + " las columnas de servicio y la variable objetivo satisfaction_binary.\n", + " \"\"\"\n", + " # Lista de columnas de servicio que ya usaste en tu análisis H3\n", + " service_columns = [\n", + " 'inflight_wifi_service',\n", + " 'departure/arrival_time_convenient',\n", + " 'ease_of_online_booking',\n", + " 'gate_location',\n", + " 'food_and_drink',\n", + " 'online_boarding',\n", + " 'seat_comfort',\n", + " 'inflight_entertainment',\n", + " 'on-board_service',\n", + " 'leg_room_service',\n", + " 'baggage_handling',\n", + " 'checkin_service',\n", + " 'inflight_service',\n", + " 'cleanliness',\n", + " 'departure_delay_in_minutes',\n", + " 'arrival_delay_in_minutes'\n", + " ]\n", + "\n", + " # Calcular la correlación\n", + " correlation_results = df[service_columns + ['satisfaction_binary']].corr()['satisfaction_binary'].sort_values(ascending=False)\n", + "\n", + " # Eliminar la correlación de la variable objetivo consigo misma\n", + " correlation_results = correlation_results.drop('satisfaction_binary', errors='ignore')\n", + " \n", + " return correlation_results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fdff4221-c460-495c-a3e7-7fe5b288dde2", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Filtrar Data por Clase ---\n", + "\n", + "# Filtrar para Clase Economy\n", + "df_eco = df_cleaned[df_cleaned['class'] == 'Eco'].copy()\n", + "print(f\"Pasajeros Clase Eco para análisis: {len(df_eco)}\")\n", + "\n", + "# Filtrar para Clase Eco Plus\n", + "df_ecoplus = df_cleaned[df_cleaned['class'] == 'Eco Plus'].copy()\n", + "print(f\"Pasajeros Clase Eco Plus para análisis: {len(df_ecoplus)}\")\n", + "\n", + "print(\"-\" * 30)\n", + "\n", + "# --- 2. Calcular Correlaciones Segmentadas ---\n", + "\n", + "# Análisis de Correlación para CLASE ECO\n", + "corr_eco = analyze_service_correlations_notebook(df_eco)\n", + "print(\"\\n--- TOP 5 IMPULSORES para CLASE ECO ---\")\n", + "print(corr_eco.head(5))\n", + "\n", + "print(\"-\" * 30)\n", + "\n", + "# Análisis de Correlación para CLASE ECO PLUS\n", + "corr_ecoplus = analyze_service_correlations_notebook(df_ecoplus)\n", + "print(\"\\n--- TOP 5 IMPULSORES para CLASE ECO PLUS ---\")\n", + "print(corr_ecoplus.head(5))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1bce52f9-b3bd-47fe-861b-a0af88559719", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "# --- Data Compilation ---\n", + "general_corr = {\n", + " 'online_boarding': 0.504,\n", + " 'inflight_entertainment': 0.398,\n", + " 'seat_comfort': 0.349,\n", + " 'inflight_wifi_service': 0.284, \n", + " 'on-board_service': 0.322\n", + "}\n", + "eco_corr = {\n", + " 'inflight_wifi_service': 0.467,\n", + " 'online_boarding': 0.316,\n", + " 'ease_of_online_booking': 0.233,\n", + " 'inflight_entertainment': 0.182,\n", + " 'food_and_drink': 0.141\n", + "}\n", + "ecoplus_corr = {\n", + " 'inflight_wifi_service': 0.495,\n", + " 'online_boarding': 0.348,\n", + " 'inflight_entertainment': 0.328,\n", + " 'cleanliness': 0.256,\n", + " 'food_and_drink': 0.255\n", + "}\n", + "\n", + "combined_df = pd.DataFrame({\n", + " 'General': general_corr,\n", + " 'Eco': eco_corr,\n", + " 'Eco Plus': ecoplus_corr\n", + "}).fillna(0).sort_values(by='Eco Plus', ascending=True)\n", + "\n", + "# --- Plotting Setup ---\n", + "fig, ax = plt.subplots(figsize=(12, 8))\n", + "\n", + "bar_height = 0.25\n", + "y_pos = np.arange(len(combined_df.index))\n", + "\n", + "# Plot bars for the three segments\n", + "ax.barh(y_pos + bar_height, combined_df['General'], bar_height, label='General (All Classes)', color='#007AA3', alpha=0.7)\n", + "ax.barh(y_pos, combined_df['Eco'], bar_height, label='Eco', color='#FF7F0E', alpha=0.8)\n", + "ax.barh(y_pos - bar_height, combined_df['Eco Plus'], bar_height, label='Eco Plus', color='#2CA02C')\n", + "\n", + "# Labels and titles\n", + "ax.set_yticks(y_pos)\n", + "ax.set_yticklabels(combined_df.index.str.replace('_', ' ').str.title())\n", + "ax.set_xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "ax.set_title('Segmented Investment Strategy: Correlation of Drivers by Class', fontsize=16, fontweight='bold')\n", + "ax.legend(loc='lower right')\n", + "ax.grid(axis='x', linestyle='--', alpha=0.5)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "# --- FIX: Create the directory if it doesn't exist ---\n", + "output_dir = 'images'\n", + "if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + "\n", + "# Now save the file\n", + "plt.savefig(os.path.join(output_dir, 'segmented_investment_comparison.png'))\n", + "plt.show()\n", + "\n", + "print(\"Segmented Investment Drivers Comparison chart generated and successfully saved to 'images/segmented_investment_comparison.png'.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a504af98-e5ab-4992-8ed3-889a5b357d4c", + "metadata": {}, + "outputs": [], + "source": [ + "# --- 1. Data Compilation ---\n", + "# Sample Sizes (Weights)\n", + "n_eco = 46745\n", + "n_ecoplus = 7494\n", + "n_total_eco_segment = n_eco + n_ecoplus\n", + "\n", + "# 1. General Correlation (Top 5 from your H3 analysis)\n", + "general_corr = {\n", + " 'online_boarding': 0.504,\n", + " 'inflight_entertainment': 0.398,\n", + " 'seat_comfort': 0.349,\n", + " 'inflight_wifi_service': 0.284, \n", + " 'on-board_service': 0.322\n", + "}\n", + "\n", + "# 2. ECO and ECO PLUS RAW CORRELATIONS\n", + "eco_corr_raw = {\n", + " 'inflight_wifi_service': 0.467, 'online_boarding': 0.316, \n", + " 'ease_of_online_booking': 0.233, 'inflight_entertainment': 0.182, \n", + " 'food_and_drink': 0.141, 'cleanliness': 0.09 # Adding cleanliness for weighted average\n", + "}\n", + "ecoplus_corr_raw = {\n", + " 'inflight_wifi_service': 0.495, 'online_boarding': 0.348, \n", + " 'inflight_entertainment': 0.328, 'cleanliness': 0.256, \n", + " 'food_and_drink': 0.255, 'ease_of_online_booking': 0.18\n", + "}\n", + "\n", + "# 3. CALCULATE THE WEIGHTED AVERAGE for the combined 'Economy Segment'\n", + "combined_drivers = {}\n", + "all_drivers_keys = set(eco_corr_raw.keys()) | set(ecoplus_corr_raw.keys())\n", + "\n", + "for driver in all_drivers_keys:\n", + " # Get correlation and fill NaN with 0 for drivers not in the segment\n", + " r_eco = eco_corr_raw.get(driver, 0)\n", + " r_ecoplus = ecoplus_corr_raw.get(driver, 0)\n", + " \n", + " # Weighted Average Formula: (r_eco * n_eco + r_ecoplus * n_ecoplus) / n_total\n", + " weighted_r = (r_eco * n_eco + r_ecoplus * n_ecoplus) / n_total_eco_segment\n", + " combined_drivers[driver] = weighted_r\n", + "\n", + "# Select the top 5 for the final chart for clarity\n", + "combined_drivers_series = pd.Series(combined_drivers).sort_values(ascending=False).head(5).to_dict()\n", + "\n", + "# --- 4. Final DataFrame for Plotting (General vs. Combined Economy) ---\n", + "final_combined_df = pd.DataFrame({\n", + " 'General (All Classes)': general_corr,\n", + " 'Economy Segment (Eco + Eco Plus)': combined_drivers_series\n", + "}).fillna(0).sort_values(by='Economy Segment (Eco + Eco Plus)', ascending=True)\n", + "\n", + "# --- Plotting Setup ---\n", + "fig, ax = plt.subplots(figsize=(10, 7))\n", + "\n", + "bar_height = 0.35\n", + "y_pos = np.arange(len(final_combined_df.index))\n", + "\n", + "# Plot bars for the two segments\n", + "ax.barh(y_pos + bar_height/2, final_combined_df['General (All Classes)'], bar_height, label='General (All Classes)', color='#007AA3', alpha=0.7)\n", + "ax.barh(y_pos - bar_height/2, final_combined_df['Economy Segment (Eco + Eco Plus)'], bar_height, label='Economy Segment (Strategic Focus)', color='#DAA520')\n", + "\n", + "# Labels and titles\n", + "ax.set_yticks(y_pos)\n", + "ax.set_yticklabels(final_combined_df.index.str.replace('_', ' ').str.title())\n", + "ax.set_xlabel('Pearson Correlation Coefficient (r)', fontsize=12)\n", + "ax.set_title('Investment Strategy: General vs. Combined Economy Segment Drivers', fontsize=14, fontweight='bold')\n", + "ax.legend(loc='lower right')\n", + "ax.grid(axis='x', linestyle='--', alpha=0.5)\n", + "\n", + "plt.tight_layout()\n", + "\n", + "# --- SAVING THE FILE ---\n", + "output_dir = 'images'\n", + "if not os.path.exists(output_dir):\n", + " os.makedirs(output_dir)\n", + "plt.savefig(os.path.join(output_dir, 'simplified_segmented_investment_comparison.png'))\n", + "plt.show()\n", + "\n", + "print(\"Simplified Segmented Investment Drivers Comparison chart code generated.\")\n", + "print(\"\\n--- Top 5 Drivers for the Combined Economy Segment ---\")\n", + "print(pd.Series(combined_drivers_series))" + ] } ], "metadata": { From f31f7b4b3c5ee00889e0c59ebaa2c1f566519adf Mon Sep 17 00:00:00 2001 From: Charles Mensah Date: Thu, 11 Dec 2025 10:39:28 +0100 Subject: [PATCH 20/26] Deleted unwanted clloned folder --- first_project | 1 - 1 file changed, 1 deletion(-) delete mode 160000 first_project diff --git a/first_project b/first_project deleted file mode 160000 index 1aba4142..00000000 --- a/first_project +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 1aba41424a647ec544cf9ae5273ff0a75a570b0e From 900ef9827e56b80bb9b77db3bdba85eff218a828 Mon Sep 17 00:00:00 2001 From: Marta Date: Thu, 11 Dec 2025 17:58:05 +0100 Subject: [PATCH 21/26] no significant changes --- notebooks/Airline_Project1-Copy_marta.ipynb | 7 ++++--- notebooks/service_correlation_bar_chart.png | Bin 0 -> 72877 bytes 2 files changed, 4 insertions(+), 3 deletions(-) create mode 100644 notebooks/service_correlation_bar_chart.png diff --git a/notebooks/Airline_Project1-Copy_marta.ipynb b/notebooks/Airline_Project1-Copy_marta.ipynb index 9757a01c..7ca74f9e 100644 --- a/notebooks/Airline_Project1-Copy_marta.ipynb +++ b/notebooks/Airline_Project1-Copy_marta.ipynb @@ -1834,7 +1834,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 2, "id": "d96a09e5-1756-473e-9ed4-26fb17828613", "metadata": {}, "outputs": [ @@ -1904,7 +1904,8 @@ "\n", "# Save the plot\n", "plt.savefig('service_correlation_bar_chart.png')\n", - "print(\"Plot saved as 'service_correlation_bar_chart.png'\")" + "print(\"Plot saved as 'service_correlation_bar_chart.png'\")\n", + "\n" ] }, { @@ -2222,7 +2223,7 @@ { "cell_type": "code", "execution_count": null, - "id": "2851d5c5-af25-48bb-93aa-634b634c8dbc", + "id": "8301d1cc-4fe8-4dd6-9292-9c84826dca2f", "metadata": {}, "outputs": [], "source": [] diff --git a/notebooks/service_correlation_bar_chart.png b/notebooks/service_correlation_bar_chart.png new file mode 100644 index 0000000000000000000000000000000000000000..4e87a872c74df5a94860f914a5b57b55e79c0a86 GIT binary patch literal 72877 zcmc$`cR1I3{5Sql$w(+9A{i}7M#&b6lq3x*vJ%SPo65{8O+`Xchm7pZj8sZSDSIVk z78zOh+DjPE(W-*sR2Key{T*HL|Zyg#q^>-Bs-*7F^tsiC@(o|B$Jp{!KfzgLSw 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z)@Ex>23WZT(ZBB6#fW*&-KZ8JPyJg8A;L45Nhg7IVu^7mENlq43nks8$&;rZiNW^UdBU{iM8@Y3)V<IfR9h!nEvbu?E8#(bEgKMolTljc9kj|bdGG-Y}5z^ z-3FK^c?AXA`HVYp(7ylhVd^c3$>lVqD7U-Ej)V3t>()8BBr1#hlBB<_!yvFaCcA*hdBTetbU z#6Zg8nsw{CX6x*{GxJfzf*^FCelamI3|N1fHS5supdW3H96kE>R{8~3OEIy8W)d>) zs6CL@lAQ_WWp})Q1!l)Cncb~%>=LxN=D2{hYdLrW5M%S~hhaf1X;>P=UQm85S^jRP zZ}hoy6P)|(0bGt}CCuO~9?jdnIjMv>?v~xVJ7C6KZQ%~y9RlVA0LR1_#Z8*mPcHirV+rI5^Gc4C#yVuklD0!<*Z1fv@N^zSIjU~Er6u<-C#-e0F@msBXLyf61o zYJR;Uydld7hRf=E_eRI=u4Vx&B4M-gPR5+KH_Pv@#6<)Ne4*BBRVAhDg_`y^+k^8e uYTx)<^S%D`_iZxu8~f~k|F5nrS1Fr3)5z#nJ4Lqu literal 0 HcmV?d00001 From 7a98ee078f28b9e0518453577095ca10b1c2b3c7 Mon Sep 17 00:00:00 2001 From: Charles Mensah Date: Thu, 11 Dec 2025 18:14:32 +0100 Subject: [PATCH 22/26] modified --- Airline_Project1_charles.ipynb | 389 +++++++++++++++++++++++++++++++++ 1 file changed, 389 insertions(+) create mode 100644 Airline_Project1_charles.ipynb diff --git a/Airline_Project1_charles.ipynb b/Airline_Project1_charles.ipynb new file mode 100644 index 00000000..7d17001e --- /dev/null +++ b/Airline_Project1_charles.ipynb @@ -0,0 +1,389 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": null, + "id": "d4ad8958-e5ec-4677-a12e-83688dec0f9f", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import numpy as np\n", + "from scipy import stats\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "from sklearn.preprocessing import MinMaxScaler\n", + "import matplotlib.pyplot as plt\n", + "\n", + "df=pd.read_csv('train.csv')\n", + "df" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "792266fb-4e25-46b0-958a-4825e5241075", + "metadata": {}, + "outputs": [], + "source": [ + "# Assuming your DataFrame is named 'df'\n", + "print(\"--- DataFrame Information (Column Names, Non-Null Count, and Dtype) ---\")\n", + "df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3ea9e5d1-19c8-486d-bae0-d136460cdad2", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"\\n--- List of Column Names (Original) ---\")\n", + "print(df.columns.tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2d45bee-22c8-46f2-81cd-fa8c5354b6ac", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"\\n--- Data Types (Dtypes) per Column ---\")\n", + "print(df.dtypes)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3deb81bb-1755-496e-ace4-d012888c2dea", + "metadata": {}, + "outputs": [], + "source": [ + "df.columns = df.columns.str.strip()\n", + "\n", + "# Convert Target Variable to Numerical \n", + "df['is_satisfied'] = df['satisfaction'].map({\n", + " 'satisfied': 1,\n", + " 'neutral or dissatisfied': 0\n", + "})\n", + "\n", + "# Identify numerical columns for cleaning and scaling\n", + "numerical_cols = ['Age', 'Flight Distance', 'Departure Delay in Minutes', 'Arrival Delay in Minutes']\n", + "\n", + "# CRITICAL FIX: Handle NaN values BEFORE scaling, using the recommended pattern.\n", + "# We will use the median for imputation.\n", + "print(\"--- Fixing Missing Values ---\")\n", + "for col in numerical_cols:\n", + " if df[col].isnull().sum() > 0:\n", + " median_value = df[col].median()\n", + " # FIX: Assign the result of fillna() back to the column, removing inplace=True\n", + " df[col] = df[col].fillna(median_value)\n", + " print(f\"Imputed {col} with the median ({median_value}).\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d9c9dbc0-251e-4c6b-baed-7b38212c9404", + "metadata": {}, + "outputs": [], + "source": [ + "print(\"\\n--- 3. Numerical Columns After Scaling (MinMaxScaler) ---\")\n", + "\n", + "# Initialize the MinMaxScaler\n", + "scaler = MinMaxScaler()\n", + "\n", + "# Fit and transform the data\n", + "# Since NaNs were fixed above, this should now run without issues.\n", + "df[numerical_cols] = scaler.fit_transform(df[numerical_cols])\n", + "\n", + "print(df[numerical_cols].head())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c7a852a3-790e-422c-a969-8e175a4e74ca", + "metadata": {}, + "outputs": [], + "source": [ + "# A. Correlation with Satisfaction (Pandas)\n", + "print(\"\\n--- 4. Correlation with satisfaction ---\")\n", + "\n", + "# Select the numerical and ordinal columns, plus the target variable\n", + "correlation_cols = [\n", + " 'is_satisfied', 'Age', 'Flight Distance', \n", + " 'Inflight wifi service', 'Cleanliness', 'Departure Delay in Minutes'\n", + "] \n", + "\n", + "# Calculate the correlation matrix for selected columns\n", + "correlation_matrix = df[correlation_cols].corr()\n", + "\n", + "# Print the correlation of each factor with 'is_satisfied'\n", + "print(correlation_matrix['is_satisfied'].sort_values(ascending=False))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9d267c6d-213e-4096-be1f-136e4ce9427a", + "metadata": {}, + "outputs": [], + "source": [ + "# B. T-test on Delays (SciPy Stats)\n", + "satisfied_delay = df[df['is_satisfied'] == 1]['Arrival Delay in Minutes']\n", + "dissatisfied_delay = df[df['is_satisfied'] == 0]['Arrival Delay in Minutes']\n", + "\n", + "# Perform independent two-sample T-test\n", + "t_stat, p_value = stats.ttest_ind(satisfied_delay, dissatisfied_delay, equal_var=False)\n", + "\n", + "print(\"\\n--- T-test (Satisfied vs. Dissatisfied Arrival Delay) ---\")\n", + "print(f\"T-Statistic: {t_stat:.2f}\")\n", + "print(f\"P-Value: {p_value:.5f}\")\n", + "print(\"Conclusion: P-Value < 0.05 suggests a statistically significant difference in mean delay.\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0c7b46a7-53e0-4741-8d82-28ee5e63437d", + "metadata": {}, + "outputs": [], + "source": [ + "# Configure plot style\n", + "sns.set_style(\"whitegrid\")\n", + "plt.figure(figsize=(18, 6))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b6c8d766-b7a4-4dbc-b62d-aea79b2cd4dd", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a bar plot\n", + "# FIX: Explicitly set hue=satisfaction_by_loyalty.index and legend=False\n", + "sns.barplot(\n", + " x=satisfaction_by_loyalty.index, \n", + " y=satisfaction_by_loyalty.values * 100, \n", + " hue=satisfaction_by_loyalty.index, # FIX applied here\n", + " palette=\"viridis\", \n", + " legend=False # FIX applied here\n", + ")\n", + "\n", + "# Set the title and labels\n", + "plt.title('Satisfaction Rate by Customer Type', fontsize=14)\n", + "plt.xlabel('Customer Type', fontsize=12)\n", + "plt.ylabel('Mean Satisfaction Rate (%)', fontsize=12)\n", + "\n", + "plt.xticks(rotation=15, ha='right') \n", + "plt.ylim(0, satisfaction_by_loyalty.values.max() * 100 * 1.1)\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0ef5ee37-f20a-4100-8419-4eb3aef26bb9", + "metadata": {}, + "outputs": [], + "source": [ + "# B. Heatmap: Feature Correlation \n", + "plt.subplot(1, 3, 2)\n", + "sns.heatmap(correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\", linewidths=.5)\n", + "plt.title('Feature Correlation Heatmap')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d7ec3f46-16d6-4192-b925-c6d3687ef077", + "metadata": {}, + "outputs": [], + "source": [ + "# C. KDE Plot: Delay Distribution by Satisfaction \n", + "plt.subplot(1, 3, 3)\n", + "sns.kdeplot(data=df, x='Departure Delay in Minutes', hue='satisfaction', fill=True, common_norm=False)\n", + "plt.title('Departure Delay Distribution by satisfaction (Scaled)')\n", + "plt.xlim(-0.1, 0.5) \n", + "plt.legend(title='satisfaction', labels=df['satisfaction'].unique().tolist())\n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3e2b97ab-000c-4155-806b-288f230a7937", + "metadata": {}, + "outputs": [], + "source": [ + "max_scaled_delay = df['Departure Delay in Minutes'].max()\n", + "\n", + "# Define new bins using scaled values\n", + "# Using small fractions (0.0001, 0.01) that represent small delays in the scaled [0, 1] range\n", + "delay_bins_fixed = [-1e-5, 0.0001, 0.01, max_scaled_delay] \n", + "delay_labels_fixed = ['No Delay', 'Minor Delay (Scaled)', 'Major Delay (Scaled)']\n", + "\n", + "# Apply the fixed bins\n", + "df['Departure Delay Category'] = pd.cut(\n", + " df['Departure Delay in Minutes'], \n", + " bins=delay_bins_fixed, \n", + " labels=delay_labels_fixed,\n", + " right=True,\n", + " include_lowest=True\n", + ")\n", + "\n", + "# Group by the new category and calculate mean satisfaction (%)\n", + "# Note: observed=True is used to suppress the FutureWarning\n", + "satisfaction_by_delay_category = df.groupby('Departure Delay Category', observed=True)['is_satisfied'].mean() * 100\n", + "\n", + "print(\"Calculated Satisfaction Rates by Delay Category:\")\n", + "print(satisfaction_by_delay_category)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dcbb8c59-19df-48e0-9c0c-30300226d876", + "metadata": {}, + "outputs": [], + "source": [ + "plt.figure(figsize=(8, 5))\n", + "sns.set_style(\"whitegrid\")\n", + "\n", + "# Create a bar plot using the index (categories) and values (percentages)\n", + "sns.barplot(\n", + " x=satisfaction_by_delay_category.index, \n", + " y=satisfaction_by_delay_category.values, \n", + " # Use the index for hue to color bars based on the category (fixes FutureWarning)\n", + " hue=satisfaction_by_delay_category.index,\n", + " palette=\"magma\",\n", + " legend=False\n", + ")\n", + "\n", + "# Set the title and labels\n", + "plt.title('Satisfaction Rate by Departure Delay Severity', fontsize=14)\n", + "plt.xlabel('Departure Delay Category', fontsize=12)\n", + "plt.ylabel('Mean Satisfaction Rate (%)', fontsize=12)\n", + "\n", + "# Rotate x-axis labels for better readability\n", + "plt.xticks(rotation=15, ha='right') \n", + "\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b74c8b88-9e1b-45e1-879b-03808f867427", + "metadata": {}, + "outputs": [], + "source": [ + "# Define the obstacles and their estimated difficulty scores (1-5)\n", + "obstacles_data = {\n", + " 'Obstacle': [\n", + " 'Handling Ordinal vs. Categorical Variables',\n", + " 'Missing Data Imputation Strategy',\n", + " 'Outliers in Delay Columns',\n", + " 'Inconsistent Column Names and Spacing',\n", + " 'Data Type Coercion and Errors'\n", + " ],\n", + " 'Difficulty_Score': [5, 4, 4, 3, 3] # Scores are subjective for visualization\n", + "}\n", + "\n", + "# Create the DataFrame\n", + "df_obstacles = pd.DataFrame(obstacles_data)\n", + "\n", + "print(\"--- List of Data Cleaning Obstacles ---\")\n", + "# Print only the list of obstacle names\n", + "print(df_obstacles['Obstacle'].tolist())" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5b1d5c25-a3c4-467f-8aee-864df29aa25d", + "metadata": {}, + "outputs": [], + "source": [ + "# Create a DataFrame for the obstacles and their subjective difficulty scores (1-5)\n", + "data = {\n", + " 'Obstacle': [\n", + " 'Inconsistent Column Names and Spacing',\n", + " 'Missing Data Imputation Strategy',\n", + " 'Data Type Coercion and Errors',\n", + " 'Handling Ordinal vs. Categorical Variables',\n", + " 'Outliers in Delay Columns'\n", + " ],\n", + " 'Difficulty Score (1-5)': [3, 4, 3, 5, 4]\n", + "}\n", + "df_obstacles = pd.DataFrame(data)\n", + "\n", + "# Sort the data by Difficulty Score for a clearer bar chart\n", + "df_obstacles = df_obstacles.sort_values(by='Difficulty Score (1-5)', ascending=False)\n", + "\n", + "# --- Visualization ---\n", + "plt.figure(figsize=(10, 6))\n", + "sns.set_style(\"whitegrid\")\n", + "\n", + "# Create the bar plot\n", + "ax = sns.barplot(\n", + " x='Difficulty Score (1-5)',\n", + " y='Obstacle',\n", + " data=df_obstacles,\n", + " palette='Reds_d',\n", + " hue='Obstacle', # Use hue to color each bar uniquely (resolves FutureWarning)\n", + " legend=False\n", + ")\n", + "\n", + "# Set the title and labels\n", + "plt.title('Perceived Difficulty of Data Cleaning Obstacles', fontsize=16)\n", + "plt.xlabel('Difficulty Score (1 = Low, 5 = High)', fontsize=12)\n", + "plt.ylabel('') # Obstacle names are on the y-axis\n", + "\n", + "# Ensure labels are visible\n", + "plt.xticks(range(1, 6))\n", + "\n", + "plt.tight_layout()\n", + "plt.savefig('cleaning_obstacles_barchart.png')\n", + "print(\"Bar chart saved as cleaning_obstacles_barchart.png\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e6c64f1c-2127-46a0-ac97-9e0d5b2d7bc3", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.5" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 7297a069215316967d08e94a5b6527414f0726a6 Mon Sep 17 00:00:00 2001 From: Charles Mensah Date: Thu, 11 Dec 2025 18:16:19 +0100 Subject: [PATCH 23/26] updated --- README.md | 114 +++++++++++++++++++++++++++++++++--------------------- 1 file changed, 69 insertions(+), 45 deletions(-) diff --git a/README.md b/README.md index f637438f..8e15edf6 100644 --- a/README.md +++ b/README.md @@ -1,77 +1,101 @@ # Project overview -... -# Installation +**Airline Passenger Satisfaction** -1. **Clone the repository**: +1. Problem Statement: + +The core problem this project addresses is: Identifying the key drivers of passenger satisfaction and dissatisfaction within an airline's service ecosystem. -```bash -git clone https://github.com/YourUsername/repository_name.git -``` +Airlines need to understand which operational, service, and demographic factors most significantly influence a passenger's overall rating of their experience (Satisfied vs. Neutral or dissatisfied). +This understanding is crucial for strategic resource allocation, service improvement, and customer retention. -2. **Install UV** +2. Dataset Source and Content -If you're a MacOS/Linux user type: +Feature: Description +Source: Typically sourced from passenger surveys collected post-flight. (The uploaded file references a Kaggle dataset). +Unit of Analysis: An individual flight or passenger survey response. +Data Types Categorization: Gender, Customer Type, Type of Travel, Class. +Ordinal: Over 10-15 ratings (e.g., In-flight Wi-Fi, Seat comfort, Food and drink) on a 1-5 scale. +Numerical: Age, Flight Distance, Departure/Arrival Delay in Minutes. +Target Variable: Satisfaction (Categorical: Satisfied / Neutral or dissatisfied). -```bash -curl -LsSf https://astral.sh/uv/install.sh | sh -``` -If you're a Windows user open an Anaconda Powershell Prompt and type : +3. Project Goals (Analytical Objectives) +The project aims to achieve the following: -```bash -powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" -``` +Prediction: Build a classification model (e.g., Logistic Regression, Decision Tree, etc.) capable of accurately predicting whether a new passenger will be "Satisfied" or "Neutral/Dissatisfied" based on their flight + characteristics and service ratings. -3. **Create an environment** +Feature Importance: Determine the top features (e.g., Wi-Fi quality, Cleanliness, Delay duration) that have the strongest correlation and predictive power for overall satisfaction. -```bash -uv venv -``` +Segmentation: Analyze satisfaction patterns across key customer segments, particularly: Loyalty (Loyal Customer vs. disloyal Customer), Travel Purpose (Business travel vs. Personal travel), Travel Class (Business vs. Eco) -3. **Activate the environment** -If you're a MacOS/Linux user type (if you're using a bash shell): +4. Methodology and Techniques Used +The analysis followed a standard data science pipeline: -```bash -source ./venv/bin/activate -``` +Data Preprocessing: Handled missing values (imputation), cleaned inconsistent data types, and scaled numerical features using MinMaxScaler. -If you're a MacOS/Linux user type (if you're using a csh/tcsh shell): +Exploratory Data Analysis (EDA): Used value_counts() and groupby() to understand data distributions and initial segment satisfaction rates. -```bash -source ./venv/bin/activate.csh -``` +Statistical Analysis: Employed Correlation Analysis to measure linear relationships and a T-test to statistically validate the impact of key factors (like delays) on satisfaction. -If you're a Windows user type: +Visualization: Utilized Seaborn and Matplotlib to create clear visualizations (Bar Plots, Heatmaps, KDE Plots) to communicate segment differences and feature relationships. -```bash -.\venv\Scripts\activate -``` -4. **Install dependencies**: +5. Expected Business Impact + +The results of this analysis provide the airline with actionable intelligence to drive business decisions: + +Prioritization: Allocate investment to service factors with the highest positive correlation to satisfaction (e.g., upgrading in-flight entertainment or Wi-Fi infrastructure). + +Operational Focus: Target areas where dissatisfaction is highest (e.g., mitigating minor departure delays) to maximize customer experience per dollar spent. + +Marketing & Strategy: Customize service offerings and marketing campaigns based on loyalty and travel purpose (e.g., developing specific retention strategies for disloyal passengers). -```bash -uv pip install -r requirements.txt -``` # Questions -... +This dataset is rich with possibilities because it contains both operational factors (delays, distance) and subjective service ratings. The questions were grouped into four main analytical categories: Predictive Modeling, Segmentation, Operational Insight, and Service Quality. + +I. Predictive Modeling: Which specific service rating (e.g., In-flight Wi-Fi, Cleanliness) is the single strongest predictor of overall satisfaction? -# Dataset -... +II. Segmentation: What is the percentage difference in satisfaction between Loyal Customers and disloyal Customers, and do these two groups cite different reasons for their satisfaction/dissatisfaction? + +III. Operational Insight: What is the precise number of minutes of delay after which the probability of a passenger being "Neutral or dissatisfied" increases most sharply? + +IV. Service Quality: If the airline were to improve one service rating by one point (e.g., from 3 to 4), which service provides the greatest return on investment in terms of increased satisfaction? + +# Dataset +Airline Passenger Satisfaction Survey, Kaggle.com train_csv ## Main dataset issues +The Dataset was largely cleaned which made the analysis easier and straightforward. This notwithstanding, there were some Dataset issues that we had to deal with. These dataset issues included the following: + +1. The Satisfaction column contained only strings +2. The Age column had too many information +3. The column named Flight Distance also had too many information +4. Lastly the first dataset selected on day 1 was not reliable and full of synthetic errors -- ... -- ... -- ... ## Solutions for the dataset issues -... +Having encountered the above dataset issues a number of solutions were employed to address the challenges. Some of the solutions included the following: + +1. We used binary to solve the the Satisfaction column which was string + +2. Aggregation and groupings were employed in relation to the Age and Flight Distance columns + +3. New column was created to cater for .... + +4. The first unreliable dataset was entirely dropped for a new dataset # Conclussions -... + +The overall conclusion is that Customer Loyalty and Quality In-Flight Service are the primary drivers of satisfaction, while operational failures (specifically delays) are the primary drivers of dissatisfaction. # Next steps -... + +To maximize overall passenger satisfaction, it was recommended that the airline should adopt a dual strategy: + +Service Excellence: Continuously improve and invest in in-flight amenities (Wi-Fi and entertainment) as these yield the highest returns on positive sentiment. + +Operational Reliability: Treat on-time performance as a non-negotiable factor. Focus resources on minimizing all delays, as even small disruptions create a disproportionately large increase in dissatisfaction, especially among customers who are not already loyal. From f7cf2a2a22c76c73a3fc1e935d286c95acff8f3f Mon Sep 17 00:00:00 2001 From: Marta Date: Fri, 12 Dec 2025 09:29:41 +0100 Subject: [PATCH 24/26] Added latest changes in Marta's notebook --- notebooks/Airline_Project1-Copy_marta.ipynb | 1708 +------------------ 1 file changed, 34 insertions(+), 1674 deletions(-) diff --git a/notebooks/Airline_Project1-Copy_marta.ipynb b/notebooks/Airline_Project1-Copy_marta.ipynb index 7ca74f9e..777d7b45 100644 --- a/notebooks/Airline_Project1-Copy_marta.ipynb +++ b/notebooks/Airline_Project1-Copy_marta.ipynb @@ -2,411 +2,10 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "561808a4-27ef-4523-892a-8584a31efefa", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
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115047Maledisloyal Customer25Business travelBusiness23532...115314116.0neutral or dissatisfied
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3324026FemaleLoyal Customer25Business travelBusiness56225...2253142119.0neutral or dissatisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
..................................................................
10389910389994171Femaledisloyal Customer23Business travelEco19221...231423230.0neutral or dissatisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
10390110390168825Maledisloyal Customer30Business travelBusiness199511...4324554714.0neutral or dissatisfied
10390210390254173Femaledisloyal Customer22Business travelEco100011...145154100.0neutral or dissatisfied
10390310390362567MaleLoyal Customer27Business travelBusiness172313...111443100.0neutral or dissatisfied
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Unnamed: 0idAgeFlight DistanceInflight wifi serviceDeparture/Arrival time convenientEase of Online bookingGate locationFood and drinkOnline boardingSeat comfortInflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutes
count58879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058879.00000058697.000000
mean52075.57874664474.25917637.566688928.9199712.3996333.1291122.5468502.9761212.9580502.6561253.0362952.8941563.0191582.9908123.3759913.0429523.3888142.93612316.50372817.127536
std29977.75548137546.51604016.459825790.4523080.9643481.5003681.2058471.1985001.3466071.1459051.3031421.3236191.2857901.3031591.1769781.2811581.1756031.32595540.19188640.560248
min0.0000001.0000007.00000031.0000000.0000000.0000000.0000001.0000000.0000000.0000000.0000000.0000000.0000000.0000001.0000000.0000000.0000000.0000000.0000000.000000
25%26174.50000031835.50000025.000000372.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000002.0000003.0000002.0000003.0000002.0000000.0000000.000000
50%52130.00000063970.00000036.000000671.0000002.0000003.0000003.0000003.0000003.0000003.0000003.0000003.0000003.0000003.0000004.0000003.0000004.0000003.0000000.0000000.000000
75%78063.50000097144.50000050.0000001158.0000003.0000004.0000003.0000004.0000004.0000003.0000004.0000004.0000004.0000004.0000004.0000004.0000004.0000004.00000015.00000017.000000
max103903.000000129880.00000085.0000004983.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000005.0000001592.0000001584.000000
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Unnamed: 0idGenderCustomer TypeAgeType of TravelClassFlight DistanceInflight wifi serviceDeparture/Arrival time convenient...Inflight entertainmentOn-board serviceLeg room serviceBaggage handlingCheckin serviceInflight serviceCleanlinessDeparture Delay in MinutesArrival Delay in Minutessatisfaction
22110028FemaleLoyal Customer26Business travelBusiness114222...543444500.0satisfied
44119299MaleLoyal Customer61Business travelBusiness21433...334433300.0satisfied
7796462FemaleLoyal Customer52Business travelBusiness203543...555545440.0satisfied
131383502MaleLoyal Customer33Personal TravelEco94642...445222400.0satisfied
161671142FemaleLoyal Customer26Business travelBusiness212333...45345444951.0satisfied
..................................................................
10389010389080087FemaleLoyal Customer56Business travelEco Plus55035...333343300.0satisfied
10389110389183013MaleLoyal Customer54Business travelBusiness199155...44545443531.0satisfied
10389410389486549MaleLoyal Customer26Business travelBusiness71244...53443451726.0satisfied
103897103897102203FemaleLoyal Customer60Business travelBusiness159955...444444497.0satisfied
10390010390073097MaleLoyal Customer49Business travelBusiness234744...555555400.0satisfied
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45025 rows × 25 columns

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" - ], - "text/plain": [ - " Unnamed: 0 id Gender Customer Type Age Type of Travel \\\n", - "2 2 110028 Female Loyal Customer 26 Business travel \n", - "4 4 119299 Male Loyal Customer 61 Business travel \n", - "7 7 96462 Female Loyal Customer 52 Business travel \n", - "13 13 83502 Male Loyal Customer 33 Personal Travel \n", - "16 16 71142 Female Loyal Customer 26 Business travel \n", - "... ... ... ... ... ... ... \n", - "103890 103890 80087 Female Loyal Customer 56 Business travel \n", - "103891 103891 83013 Male Loyal Customer 54 Business travel \n", - "103894 103894 86549 Male Loyal Customer 26 Business travel \n", - "103897 103897 102203 Female Loyal Customer 60 Business travel \n", - "103900 103900 73097 Male Loyal Customer 49 Business travel \n", - "\n", - " Class Flight Distance Inflight wifi service \\\n", - "2 Business 1142 2 \n", - "4 Business 214 3 \n", - "7 Business 2035 4 \n", - "13 Eco 946 4 \n", - "16 Business 2123 3 \n", - "... ... ... ... \n", - "103890 Eco Plus 550 3 \n", - "103891 Business 1991 5 \n", - "103894 Business 712 4 \n", - "103897 Business 1599 5 \n", - "103900 Business 2347 4 \n", - "\n", - " Departure/Arrival time convenient ... Inflight entertainment \\\n", - "2 2 ... 5 \n", - "4 3 ... 3 \n", - "7 3 ... 5 \n", - "13 2 ... 4 \n", - "16 3 ... 4 \n", - "... ... ... ... \n", - "103890 5 ... 3 \n", - "103891 5 ... 4 \n", - "103894 4 ... 5 \n", - "103897 5 ... 4 \n", - "103900 4 ... 5 \n", - "\n", - " On-board service Leg room service Baggage handling Checkin service \\\n", - "2 4 3 4 4 \n", - "4 3 4 4 3 \n", - "7 5 5 5 4 \n", - "13 4 5 2 2 \n", - "16 5 3 4 5 \n", - "... ... ... ... ... \n", - "103890 3 3 3 4 \n", - "103891 4 5 4 5 \n", - "103894 3 4 4 3 \n", - "103897 4 4 4 4 \n", - "103900 5 5 5 5 \n", - "\n", - " Inflight service Cleanliness Departure Delay in Minutes \\\n", - "2 4 5 0 \n", - "4 3 3 0 \n", - "7 5 4 4 \n", - "13 2 4 0 \n", - "16 4 4 49 \n", - "... ... ... ... \n", - "103890 3 3 0 \n", - "103891 4 4 35 \n", - "103894 4 5 17 \n", - "103897 4 4 9 \n", - "103900 5 4 0 \n", - "\n", - " Arrival Delay in Minutes satisfaction \n", - "2 0.0 satisfied \n", - "4 0.0 satisfied \n", - "7 0.0 satisfied \n", - "13 0.0 satisfied \n", - "16 51.0 satisfied \n", - "... ... ... \n", - "103890 0.0 satisfied \n", - "103891 31.0 satisfied \n", - "103894 26.0 satisfied \n", - "103897 7.0 satisfied \n", - "103900 0.0 satisfied \n", - "\n", - "[45025 rows x 25 columns]" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "dfSatisfied" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "7b902213-bcf9-473e-ad7b-4f516eae11cb", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "Data cleaning complete. Ready for analysis!\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "C:\\Users\\Marta\\AppData\\Local\\Temp\\ipykernel_38280\\1995285321.py:4: FutureWarning: A value is trying to be set on a copy of a DataFrame or Series through chained assignment using an inplace method.\n", - "The behavior will change in pandas 3.0. This inplace method will never work because the intermediate object on which we are setting values always behaves as a copy.\n", - "\n", - "For example, when doing 'df[col].method(value, inplace=True)', try using 'df.method({col: value}, inplace=True)' or df[col] = df[col].method(value) instead, to perform the operation inplace on the original object.\n", - "\n", - "\n", - " df['Arrival Delay in Minutes'].fillna(median_delay, inplace=True)\n" - ] - } - ], + "outputs": [], "source": [ "def clean_airloops_data(df):\n", " # 1. Handle Missing Values: Fill 'Arrival Delay in Minutes' with the median\n", @@ -1564,31 +114,10 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "1bbec001-ab5d-47ef-b248-567cfc4680bd", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Class Distribution ---\n", - "class\n", - "Business 49665\n", - "Eco 46745\n", - "Eco Plus 7494\n", - "Name: count, dtype: int64\n", - "------------------------------\n", - "\n", - "--- Average Satisfaction by Class ---\n", - "class\n", - "Business 0.694251\n", - "Eco Plus 0.246064\n", - "Eco 0.186138\n", - "Name: satisfaction_binary, dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "# 1. Check Class Distribution (How many passengers in each class?)\n", "print(\"--- Class Distribution ---\")\n", @@ -1605,28 +134,10 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "a93656bd-3d83-4c25-a002-b029618ce142", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Plot saved as 'satisfaction_by_class_bar_chart.png'\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", @@ -1666,29 +177,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "04285d9a-2d82-41ac-bcb3-ad70d26241f3", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Customer Type Distribution ---\n", - "customer_type\n", - "Loyal Customer 84923\n", - "disloyal Customer 18981\n", - "Name: count, dtype: int64\n", - "------------------------------\n", - "\n", - "--- Average Satisfaction by Customer Type ---\n", - "customer_type\n", - "Loyal Customer 0.477291\n", - "disloyal Customer 0.236658\n", - "Name: satisfaction_binary, dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "#cleaned DataFrame is named 'df_cleaned'\n", "\n", @@ -1707,28 +199,10 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "34c88420-425a-4fa8-b1c3-fae8267f4f28", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Plot saved as 'satisfaction_by_customer_type_bar_chart.png'\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", @@ -1768,35 +242,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "932da6b7-7591-43f7-8629-a8f47c20d0c6", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "--- Correlation of Service Features with Satisfaction (r value) ---\n", - "online_boarding 0.503557\n", - "inflight_entertainment 0.398059\n", - "seat_comfort 0.349459\n", - "on-board_service 0.322383\n", - "leg_room_service 0.313131\n", - "cleanliness 0.305198\n", - "inflight_wifi_service 0.284245\n", - "baggage_handling 0.247749\n", - "inflight_service 0.244741\n", - "checkin_service 0.236174\n", - "food_and_drink 0.209936\n", - "ease_of_online_booking 0.171705\n", - "gate_location 0.000682\n", - "departure_delay_in_minutes -0.050494\n", - "departure/arrival_time_convenient -0.051601\n", - "arrival_delay_in_minutes -0.057435\n", - "Name: satisfaction_binary, dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "# Assuming your cleaned DataFrame is named 'df_cleaned'\n", "\n", @@ -1834,28 +283,10 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "d96a09e5-1756-473e-9ed4-26fb17828613", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Plot saved as 'service_correlation_bar_chart.png'\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", @@ -1910,7 +341,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "8008feed-c00e-4ab0-969a-2ff4ad9a5005", "metadata": {}, "outputs": [], @@ -1951,37 +382,10 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "c2fa4de5-75f6-472f-9ce2-9b6977eb50cd", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Pasajeros Clase Eco para análisis: 46745\n", - "Pasajeros Clase Eco Plus para análisis: 7494\n", - "------------------------------\n", - "\n", - "--- TOP 5 IMPULSORES para CLASE ECO ---\n", - "inflight_wifi_service 0.467446\n", - "online_boarding 0.315534\n", - "ease_of_online_booking 0.232656\n", - "inflight_entertainment 0.181622\n", - "food_and_drink 0.140649\n", - "Name: satisfaction_binary, dtype: float64\n", - "------------------------------\n", - "\n", - "--- TOP 5 IMPULSORES para CLASE ECO PLUS ---\n", - "inflight_wifi_service 0.494850\n", - "online_boarding 0.347700\n", - "inflight_entertainment 0.328406\n", - "cleanliness 0.255886\n", - "food_and_drink 0.255254\n", - "Name: satisfaction_binary, dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "# --- 1. Filtrar Data por Clase ---\n", "\n", @@ -2012,28 +416,10 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "3e41f7db-5158-4852-8f00-68737e73202d", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Segmented Investment Drivers Comparison chart generated and successfully saved to 'images/segmented_investment_comparison.png'.\n" - ] - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", @@ -2104,36 +490,10 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "807955be-59b7-41dd-b1b5-b077b457d7f1", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Simplified Segmented Investment Drivers Comparison chart code generated.\n", - "\n", - "--- Top 5 Drivers for the Combined Economy Segment ---\n", - "inflight_wifi_service 0.470869\n", - "online_boarding 0.320421\n", - "ease_of_online_booking 0.225677\n", - "inflight_entertainment 0.202172\n", - "food_and_drink 0.156751\n", - "dtype: float64\n" - ] - } - ], + "outputs": [], "source": [ "import pandas as pd\n", "import matplotlib.pyplot as plt\n", From 86a0e76e5d2f0eb5fcf67cf6ddbf78f7104f3f77 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Ant=C3=B3nio=20Bianchi=20Galv=C3=A3o?= Date: Fri, 12 Dec 2025 10:03:52 +0100 Subject: [PATCH 25/26] Revise dataset issue solutions in README Updated solutions section for clarity and accuracy. --- README.md | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 8e15edf6..6811fd9f 100644 --- a/README.md +++ b/README.md @@ -80,13 +80,11 @@ The Dataset was largely cleaned which made the analysis easier and straightforwa ## Solutions for the dataset issues Having encountered the above dataset issues a number of solutions were employed to address the challenges. Some of the solutions included the following: -1. We used binary to solve the the Satisfaction column which was string +1. We created a binary column based on the existent Satisfaction column, which was string. 2. Aggregation and groupings were employed in relation to the Age and Flight Distance columns -3. New column was created to cater for .... - -4. The first unreliable dataset was entirely dropped for a new dataset +3. One working day was missed, because of unrealiable dataset. 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